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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "pycharm": {
+     "name": "#%% md\n"
+    }
+   },
+   "source": [
+    "# Task 1: Introduction\n",
+    "\n",
+    "---\n",
+    "\n",
+    "For this project, we are going to work on evaluating price of houses given the following features:\n",
+    "\n",
+    "1. Year of sale of the house\n",
+    "2. The age of the house at the time of sale\n",
+    "3. Distance from city center\n",
+    "4. Number of stores in the locality\n",
+    "5. The latitude\n",
+    "6. The longitude\n",
+    "\n",
+    "![Regression](images/regression.png)\n",
+    "\n",
+    "Note: This notebook uses `python 3` and these packages: `tensorflow`, `pandas`, `matplotlib`, `scikit-learn`."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "pycharm": {
+     "name": "#%% md\n"
+    }
+   },
+   "source": [
+    "## 1.1: Importing Libraries & Helper Functions\n",
+    "\n",
+    "First of all, we will need to import some libraries and helper functions. This includes TensorFlow and some utility functions that I've written to save time."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Libraries imported.\n",
+      "<module 'tensorflow._api.v2.version' from 'C:\\\\Users\\\\Nadun\\\\anaconda3\\\\lib\\\\site-packages\\\\tensorflow\\\\_api\\\\v2\\\\version\\\\__init__.py'>\n"
+     ]
+    }
+   ],
+   "source": [
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "import tensorflow as tf\n",
+    "\n",
+    "from utils import *\n",
+    "from sklearn.model_selection import train_test_split\n",
+    "from tensorflow.keras.models import Sequential\n",
+    "from tensorflow.keras.layers import Dense, Dropout\n",
+    "from tensorflow.keras.callbacks import EarlyStopping, LambdaCallback\n",
+    "\n",
+    "%matplotlib inline\n",
+    "\n",
+    "# tf.logging.set_verbosity(tf.logging.ERROR)\n",
+    "tf.compat.v1.logging.set_verbosity(tf.compat.v1.logging.ERROR)\n",
+    "print('Libraries imported.')\n",
+    "print(tf.version)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "pycharm": {
+     "name": "#%% md\n"
+    }
+   },
+   "source": [
+    "# Task 2: Importing the Data"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "pycharm": {
+     "name": "#%% md\n"
+    }
+   },
+   "source": [
+    "## 2.1: Importing the Data\n",
+    "\n",
+    "The dataset is saved in a `data.csv` file. We will use `pandas` to take a look at some of the rows."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": "   serial  date  age  distance  stores  latitude  longitude  price\n0       0  2009   21         9       6        84        121  14264\n1       1  2007    4         2       3        86        121  12032\n2       2  2016   18         3       7        90        120  13560\n3       3  2002   13         2       2        80        128  12029\n4       4  2014   25         5       8        81        122  14157",
+      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>serial</th>\n      <th>date</th>\n      <th>age</th>\n      <th>distance</th>\n      <th>stores</th>\n      <th>latitude</th>\n      <th>longitude</th>\n      <th>price</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>0</td>\n      <td>2009</td>\n      <td>21</td>\n      <td>9</td>\n      <td>6</td>\n      <td>84</td>\n      <td>121</td>\n      <td>14264</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>1</td>\n      <td>2007</td>\n      <td>4</td>\n      <td>2</td>\n      <td>3</td>\n      <td>86</td>\n      <td>121</td>\n      <td>12032</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>2</td>\n      <td>2016</td>\n      <td>18</td>\n      <td>3</td>\n      <td>7</td>\n      <td>90</td>\n      <td>120</td>\n      <td>13560</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>3</td>\n      <td>2002</td>\n      <td>13</td>\n      <td>2</td>\n      <td>2</td>\n      <td>80</td>\n      <td>128</td>\n      <td>12029</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>4</td>\n      <td>2014</td>\n      <td>25</td>\n      <td>5</td>\n      <td>8</td>\n      <td>81</td>\n      <td>122</td>\n      <td>14157</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
+     },
+     "execution_count": 31,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df = pd.read_csv('data.csv',names= column_names)\n",
+    "df.head()\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "pycharm": {
+     "name": "#%% md\n"
+    }
+   },
+   "source": [
+    "## 2.2: Check Missing Data\n",
+    "\n",
+    "It's a good practice to check if the data has any missing values. In real world data, this is quite common and must be taken care of before any data pre-processing or model training."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": "serial       0\ndate         0\nage          0\ndistance     0\nstores       0\nlatitude     0\nlongitude    0\nprice        0\ndtype: int64"
+     },
+     "execution_count": 32,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.isna().sum()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "pycharm": {
+     "name": "#%% md\n"
+    }
+   },
+   "source": [
+    "# Task 3: Data Normalization"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "pycharm": {
+     "name": "#%% md\n"
+    }
+   },
+   "source": [
+    "## 3.1: Data Normalization\n",
+    "\n",
+    "We can make it easier for optimization algorithms to find minimas by normalizing the data before training a model."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": "       date       age  distance    stores  latitude  longitude     price\n0  0.015978  0.181384  1.257002  0.345224 -0.307212  -1.260799  0.350088\n1 -0.350485 -1.319118 -0.930610 -0.609312  0.325301  -1.260799 -1.836486\n2  1.298598 -0.083410 -0.618094  0.663402  1.590328  -1.576456 -0.339584\n3 -1.266643 -0.524735 -0.930610 -0.927491 -1.572238   0.948803 -1.839425\n4  0.932135  0.534444  0.006938  0.981581 -1.255981  -0.945141  0.245266",
+      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>date</th>\n      <th>age</th>\n      <th>distance</th>\n      <th>stores</th>\n      <th>latitude</th>\n      <th>longitude</th>\n      <th>price</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>0.015978</td>\n      <td>0.181384</td>\n      <td>1.257002</td>\n      <td>0.345224</td>\n      <td>-0.307212</td>\n      <td>-1.260799</td>\n      <td>0.350088</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>-0.350485</td>\n      <td>-1.319118</td>\n      <td>-0.930610</td>\n      <td>-0.609312</td>\n      <td>0.325301</td>\n      <td>-1.260799</td>\n      <td>-1.836486</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>1.298598</td>\n      <td>-0.083410</td>\n      <td>-0.618094</td>\n      <td>0.663402</td>\n      <td>1.590328</td>\n      <td>-1.576456</td>\n      <td>-0.339584</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>-1.266643</td>\n      <td>-0.524735</td>\n      <td>-0.930610</td>\n      <td>-0.927491</td>\n      <td>-1.572238</td>\n      <td>0.948803</td>\n      <td>-1.839425</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>0.932135</td>\n      <td>0.534444</td>\n      <td>0.006938</td>\n      <td>0.981581</td>\n      <td>-1.255981</td>\n      <td>-0.945141</td>\n      <td>0.245266</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
+     },
+     "execution_count": 33,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df=df.iloc[:,1:]\n",
+    "df_norm=(df - df.mean())/df.std()\n",
+    "df_norm.head()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "pycharm": {
+     "name": "#%% md\n"
+    }
+   },
+   "source": [
+    "## 3.2: Convert Label Value\n",
+    "\n",
+    "Because we are using normalized values for the labels, we will get the predictions back from a trained model in the same distribution. So, we need to convert the predicted values back to the original distribution if we want predicted prices."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "metadata": {
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "14263\n"
+     ]
+    }
+   ],
+   "source": [
+    "y_mean=df['price'].mean()\n",
+    "y_std=df['price'].std()\n",
+    "\n",
+    "def convert_label_value(pred):\n",
+    "    return int(pred*y_std +y_mean)\n",
+    "\n",
+    "print(convert_label_value(0.350088))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "pycharm": {
+     "name": "#%% md\n"
+    }
+   },
+   "source": [
+    "# Task 4: Create Training and Test Sets"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "pycharm": {
+     "name": "#%% md\n"
+    }
+   },
+   "source": [
+    "## 4.1: Select Features\n",
+    "\n",
+    "Make sure to remove the column __price__ from the list of features as it is the label and should not be used as a feature."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "metadata": {
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": "       date       age  distance    stores  latitude  longitude\n0  0.015978  0.181384  1.257002  0.345224 -0.307212  -1.260799\n1 -0.350485 -1.319118 -0.930610 -0.609312  0.325301  -1.260799\n2  1.298598 -0.083410 -0.618094  0.663402  1.590328  -1.576456\n3 -1.266643 -0.524735 -0.930610 -0.927491 -1.572238   0.948803\n4  0.932135  0.534444  0.006938  0.981581 -1.255981  -0.945141",
+      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>date</th>\n      <th>age</th>\n      <th>distance</th>\n      <th>stores</th>\n      <th>latitude</th>\n      <th>longitude</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>0.015978</td>\n      <td>0.181384</td>\n      <td>1.257002</td>\n      <td>0.345224</td>\n      <td>-0.307212</td>\n      <td>-1.260799</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>-0.350485</td>\n      <td>-1.319118</td>\n      <td>-0.930610</td>\n      <td>-0.609312</td>\n      <td>0.325301</td>\n      <td>-1.260799</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>1.298598</td>\n      <td>-0.083410</td>\n      <td>-0.618094</td>\n      <td>0.663402</td>\n      <td>1.590328</td>\n      <td>-1.576456</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>-1.266643</td>\n      <td>-0.524735</td>\n      <td>-0.930610</td>\n      <td>-0.927491</td>\n      <td>-1.572238</td>\n      <td>0.948803</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>0.932135</td>\n      <td>0.534444</td>\n      <td>0.006938</td>\n      <td>0.981581</td>\n      <td>-1.255981</td>\n      <td>-0.945141</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
+     },
+     "execution_count": 35,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "x=df_norm.iloc[:, :6]\n",
+    "x.head()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "pycharm": {
+     "name": "#%% md\n"
+    }
+   },
+   "source": [
+    "## 4.2: Select Labels"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "metadata": {
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": "0    0.350088\n1   -1.836486\n2   -0.339584\n3   -1.839425\n4    0.245266\nName: price, dtype: float64"
+     },
+     "execution_count": 36,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "y =df_norm.iloc[:,-1]\n",
+    "y.head()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "pycharm": {
+     "name": "#%% md\n"
+    }
+   },
+   "source": [
+    "## 4.3: Feature and Label Values\n",
+    "\n",
+    "We will need to extract just the numeric values for the features and labels as the TensorFlow model will expect just numeric values as input."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "(5000, 6)\n",
+      "(5000,)\n"
+     ]
+    }
+   ],
+   "source": [
+    "x_arr=x.values\n",
+    "y_arr=y.values\n",
+    "\n",
+    "print(x_arr.shape)#features\n",
+    "print(y_arr.shape)#labels\n"
+   ],
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   }
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 58,
+   "metadata": {
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "(3350, 6) (3350,)\n",
+      "(1650, 6) (1650,)\n"
+     ]
+    }
+   ],
+   "source": [
+    "x_train,x_test,y_train,y_test=train_test_split(x_arr,y_arr,test_size=0.33, random_state=1)\n",
+    "\n",
+    "print(x_train.shape,y_train.shape)\n",
+    "print(x_test.shape,y_test.shape)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "pycharm": {
+     "name": "#%% md\n"
+    }
+   },
+   "source": [
+    "## 4.4: Train and Test Split\n",
+    "\n",
+    "We will keep some part of the data aside as a __test__ set. The model will not use this set during training and it will be used only for checking the performance of the model in trained and un-trained states. This way, we can make sure that we are going in the right direction with our model training."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "metadata": {
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "pycharm": {
+     "name": "#%% md\n"
+    }
+   },
+   "source": [
+    "# Task 5: Create the Model"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "pycharm": {
+     "name": "#%% md\n"
+    }
+   },
+   "source": [
+    "## 5.1: Create the Model\n",
+    "\n",
+    "Let's write a function that returns an untrained model of a certain architecture."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "metadata": {
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Model: \"sequential_8\"\n",
+      "_________________________________________________________________\n",
+      " Layer (type)                Output Shape              Param #   \n",
+      "=================================================================\n",
+      " layer1 (Dense)              (None, 10)                70        \n",
+      "                                                                 \n",
+      " layer2 (Dense)              (None, 20)                220       \n",
+      "                                                                 \n",
+      " layer3 (Dense)              (None, 5)                 105       \n",
+      "                                                                 \n",
+      " dense_8 (Dense)             (None, 1)                 6         \n",
+      "                                                                 \n",
+      "=================================================================\n",
+      "Total params: 401\n",
+      "Trainable params: 401\n",
+      "Non-trainable params: 0\n",
+      "_________________________________________________________________\n"
+     ]
+    }
+   ],
+   "source": [
+    "def get_model():\n",
+    "    model=Sequential([\n",
+    "        Dense(10,input_shape=(6,),activation='relu',kernel_regularizer=tf.keras.regularizers.l2(0.1),name='layer1'),\n",
+    "        Dense(20,activation='relu',kernel_regularizer=tf.keras.regularizers.l2(0.1),name='layer2'),\n",
+    "        Dense(5,activation='relu',kernel_regularizer=tf.keras.regularizers.l2(0.1),name='layer3'),\n",
+    "        Dense(1)\n",
+    "    ])\n",
+    "    model.compile(\n",
+    "        loss='mse',\n",
+    "        optimizer='adam'\n",
+    "    )\n",
+    "    return model\n",
+    "get_model().summary()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "pycharm": {
+     "name": "#%% md\n"
+    }
+   },
+   "source": [
+    "# Task 6: Model Training"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "pycharm": {
+     "name": "#%% md\n"
+    }
+   },
+   "source": [
+    "## 6.1: Model Training\n",
+    "\n",
+    "We can use an `EarlyStopping` callback from Keras to stop the model training if the validation loss stops decreasing for a few epochs."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "metadata": {
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Epoch 1/100\n",
+      "149/149 [==============================] - 3s 11ms/step - loss: 2.5397 - val_loss: 1.5862\n",
+      "Epoch 2/100\n",
+      "149/149 [==============================] - 1s 9ms/step - loss: 1.2036 - val_loss: 0.7921\n",
+      "Epoch 3/100\n",
+      "149/149 [==============================] - 1s 9ms/step - loss: 0.6812 - val_loss: 0.5240\n",
+      "Epoch 4/100\n",
+      "149/149 [==============================] - 1s 9ms/step - loss: 0.4941 - val_loss: 0.4175\n",
+      "Epoch 5/100\n",
+      "149/149 [==============================] - 1s 9ms/step - loss: 0.4166 - val_loss: 0.3712\n",
+      "Epoch 6/100\n",
+      "149/149 [==============================] - 1s 9ms/step - loss: 0.3801 - val_loss: 0.3494\n",
+      "Epoch 7/100\n",
+      "149/149 [==============================] - 1s 9ms/step - loss: 0.3597 - val_loss: 0.3377\n",
+      "Epoch 8/100\n",
+      "149/149 [==============================] - 1s 9ms/step - loss: 0.3480 - val_loss: 0.3256\n",
+      "Epoch 9/100\n",
+      "149/149 [==============================] - 1s 9ms/step - loss: 0.3398 - val_loss: 0.3202\n",
+      "Epoch 10/100\n",
+      "149/149 [==============================] - 1s 9ms/step - loss: 0.3333 - val_loss: 0.3172\n",
+      "Epoch 11/100\n",
+      "149/149 [==============================] - 1s 9ms/step - loss: 0.3258 - val_loss: 0.3123\n",
+      "Epoch 12/100\n",
+      "149/149 [==============================] - 1s 9ms/step - loss: 0.3214 - val_loss: 0.3094\n",
+      "Epoch 13/100\n",
+      "149/149 [==============================] - 1s 9ms/step - loss: 0.3183 - val_loss: 0.3046\n",
+      "Epoch 14/100\n",
+      "149/149 [==============================] - 1s 9ms/step - loss: 0.3143 - val_loss: 0.3035\n",
+      "Epoch 15/100\n",
+      "149/149 [==============================] - 1s 9ms/step - loss: 0.3102 - val_loss: 0.3064\n",
+      "Epoch 16/100\n",
+      "149/149 [==============================] - 1s 9ms/step - loss: 0.3097 - val_loss: 0.2994\n",
+      "Epoch 17/100\n",
+      "149/149 [==============================] - 1s 9ms/step - loss: 0.3065 - val_loss: 0.2918\n",
+      "Epoch 18/100\n",
+      "149/149 [==============================] - 1s 9ms/step - loss: 0.3038 - val_loss: 0.2920\n",
+      "Epoch 19/100\n",
+      "149/149 [==============================] - 1s 9ms/step - loss: 0.3019 - val_loss: 0.2885\n",
+      "Epoch 20/100\n",
+      "149/149 [==============================] - 1s 9ms/step - loss: 0.2993 - val_loss: 0.2893\n",
+      "Epoch 21/100\n",
+      "149/149 [==============================] - 1s 9ms/step - loss: 0.2966 - val_loss: 0.2890\n",
+      "Epoch 22/100\n",
+      "149/149 [==============================] - 1s 9ms/step - loss: 0.2955 - val_loss: 0.2874\n",
+      "Epoch 23/100\n",
+      "149/149 [==============================] - 1s 9ms/step - loss: 0.2930 - val_loss: 0.2828\n",
+      "Epoch 24/100\n",
+      "149/149 [==============================] - 1s 9ms/step - loss: 0.2924 - val_loss: 0.2830\n",
+      "Epoch 25/100\n",
+      "149/149 [==============================] - 1s 9ms/step - loss: 0.2906 - val_loss: 0.2849\n",
+      "Epoch 26/100\n",
+      "149/149 [==============================] - 1s 9ms/step - loss: 0.2887 - val_loss: 0.2773\n",
+      "Epoch 27/100\n",
+      "149/149 [==============================] - 1s 9ms/step - loss: 0.2869 - val_loss: 0.2793\n",
+      "Epoch 28/100\n",
+      "149/149 [==============================] - 1s 9ms/step - loss: 0.2868 - val_loss: 0.2861\n",
+      "Epoch 29/100\n",
+      "149/149 [==============================] - 1s 9ms/step - loss: 0.2874 - val_loss: 0.2760\n",
+      "Epoch 30/100\n",
+      "149/149 [==============================] - 1s 9ms/step - loss: 0.2841 - val_loss: 0.2780\n",
+      "Epoch 31/100\n",
+      "149/149 [==============================] - 1s 9ms/step - loss: 0.2828 - val_loss: 0.2722\n",
+      "Epoch 32/100\n",
+      "149/149 [==============================] - 1s 9ms/step - loss: 0.2829 - val_loss: 0.2727\n",
+      "Epoch 33/100\n",
+      "149/149 [==============================] - 1s 9ms/step - loss: 0.2802 - val_loss: 0.2721\n",
+      "Epoch 34/100\n",
+      "149/149 [==============================] - 1s 9ms/step - loss: 0.2798 - val_loss: 0.2767\n",
+      "Epoch 35/100\n",
+      "149/149 [==============================] - 1s 9ms/step - loss: 0.2785 - val_loss: 0.2708\n",
+      "Epoch 36/100\n",
+      "149/149 [==============================] - 1s 9ms/step - loss: 0.2768 - val_loss: 0.2672\n",
+      "Epoch 37/100\n",
+      "149/149 [==============================] - 1s 9ms/step - loss: 0.2765 - val_loss: 0.2687\n",
+      "Epoch 38/100\n",
+      "149/149 [==============================] - 1s 9ms/step - loss: 0.2753 - val_loss: 0.2679\n",
+      "Epoch 39/100\n",
+      "149/149 [==============================] - 1s 9ms/step - loss: 0.2747 - val_loss: 0.2746\n",
+      "Epoch 40/100\n",
+      "149/149 [==============================] - 1s 9ms/step - loss: 0.2743 - val_loss: 0.2658\n",
+      "Epoch 41/100\n",
+      "149/149 [==============================] - 1s 9ms/step - loss: 0.2743 - val_loss: 0.2645\n",
+      "Epoch 42/100\n",
+      "149/149 [==============================] - 1s 9ms/step - loss: 0.2719 - val_loss: 0.2653\n",
+      "Epoch 43/100\n",
+      "149/149 [==============================] - 1s 9ms/step - loss: 0.2747 - val_loss: 0.2658\n",
+      "Epoch 44/100\n",
+      "149/149 [==============================] - 1s 9ms/step - loss: 0.2702 - val_loss: 0.2670\n",
+      "Epoch 45/100\n",
+      "149/149 [==============================] - 1s 9ms/step - loss: 0.2722 - val_loss: 0.2657\n",
+      "Epoch 46/100\n",
+      "149/149 [==============================] - 1s 9ms/step - loss: 0.2695 - val_loss: 0.2661\n"
+     ]
+    }
+   ],
+   "source": [
+    "es_cb=EarlyStopping(monitor='val_loss',patience=5)\n",
+    "\n",
+    "model=get_model()\n",
+    "preds_on_untrained=model.predict(x_test)\n",
+    "history=model.fit(\n",
+    "    x_train,y_train,\n",
+    "    validation_data=(x_test,y_test),\n",
+    "    epochs=100,\n",
+    "    callbacks=[es_cb]\n",
+    "\n",
+    ")\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "pycharm": {
+     "name": "#%% md\n"
+    }
+   },
+   "source": [
+    "## 6.2: Plot Training and Validation Loss\n",
+    "\n",
+    "Let's use the `plot_loss` helper function to take a look training and validation loss."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "metadata": {
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": "<Figure size 576x576 with 1 Axes>",
+      "image/png": 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\n"
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_loss(history)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "pycharm": {
+     "name": "#%% md\n"
+    }
+   },
+   "source": [
+    "# Task 7: Predictions"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "pycharm": {
+     "name": "#%% md\n"
+    }
+   },
+   "source": [
+    "## 7.1: Plot Raw Predictions\n",
+    "\n",
+    "Let's use the `compare_predictions` helper function to compare predictions from the model when it was untrained and when it was trained."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "metadata": {
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\Nadun\\anaconda3\\lib\\site-packages\\numpy\\core\\shape_base.py:65: VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray.\n",
+      "  ary = asanyarray(ary)\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": "<Figure size 576x576 with 1 Axes>",
+      "image/png": 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\n"
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "preds_on_trained =model.predict(x_test)\n",
+    "compare_predictions(preds_on_untrained,preds_on_trained,y_test)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "pycharm": {
+     "name": "#%% md\n"
+    }
+   },
+   "source": [
+    "## 7.2: Plot Price Predictions\n",
+    "\n",
+    "The plot for price predictions and raw predictions will look the same with just one difference: The x and y axis scale is changed."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "outputs": [
+    {
+     "data": {
+      "text/plain": "<Figure size 576x576 with 1 Axes>",
+      "image/png": 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\n"
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "price_untrained=[convert_label_value(y) for y in preds_on_untrained]\n",
+    "price_trained=[convert_label_value(y) for y in preds_on_trained]\n",
+    "price_test=[convert_label_value(y)for y in y_test]\n",
+    "\n",
+    "compare_predictions(price_test,price_trained,price_test)"
+   ],
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   }
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "outputs": [
+    {
+     "data": {
+      "text/plain": "   date  age  distance  stores  latitude  longitude  price\n0  2009   21         9       6        84        121  14264\n1  2007    4         2       3        86        121  12032\n2  2016   18         3       7        90        120  13560\n3  2002   13         2       2        80        128  12029\n4  2014   25         5       8        81        122  14157",
+      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>date</th>\n      <th>age</th>\n      <th>distance</th>\n      <th>stores</th>\n      <th>latitude</th>\n      <th>longitude</th>\n      <th>price</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>2009</td>\n      <td>21</td>\n      <td>9</td>\n      <td>6</td>\n      <td>84</td>\n      <td>121</td>\n      <td>14264</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>2007</td>\n      <td>4</td>\n      <td>2</td>\n      <td>3</td>\n      <td>86</td>\n      <td>121</td>\n      <td>12032</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>2016</td>\n      <td>18</td>\n      <td>3</td>\n      <td>7</td>\n      <td>90</td>\n      <td>120</td>\n      <td>13560</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>2002</td>\n      <td>13</td>\n      <td>2</td>\n      <td>2</td>\n      <td>80</td>\n      <td>128</td>\n      <td>12029</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>2014</td>\n      <td>25</td>\n      <td>5</td>\n      <td>8</td>\n      <td>81</td>\n      <td>122</td>\n      <td>14157</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
+     },
+     "execution_count": 46,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.head()"
+   ],
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   }
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "outputs": [
+    {
+     "data": {
+      "text/plain": "13229"
+     },
+     "execution_count": 57,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import numpy as np\n",
+    "x=np.array([[2015,10,6,4,84,160]])\n",
+    "x=(x-x.mean())/x.std()\n",
+    "pre=model.predict(x)\n",
+    "convert_label_value(pre)"
+   ],
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   }
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "outputs": [
+    {
+     "data": {
+      "text/plain": "array([[-1.6331055 , -0.52473452,  0.00693785,  0.34522379,  1.27407102,\n         0.00183081],\n       [ 0.56567221,  0.26964911, -0.61809404,  0.981581  ,  1.59032754,\n        -1.26079862],\n       [-0.16725369,  1.68188666,  0.00693785, -0.29113342,  1.59032754,\n         1.26446025],\n       ...,\n       [ 0.01597778, -0.08341028, -0.61809404,  0.34522379, -1.25598114,\n         0.63314553],\n       [-0.35048517, -1.67217753,  0.9444857 ,  1.2997596 , -0.93972462,\n        -1.57645598],\n       [ 1.11536664,  1.15229758,  1.25700164,  0.02704518, -1.25598114,\n         1.26446025]])"
+     },
+     "execution_count": 52,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "x_test"
+   ],
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   }
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "outputs": [],
+   "source": [],
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   }
+  }
+ ],
+ "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": "3.7.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
\ No newline at end of file
diff --git a/House price prediction/data.csv b/House price prediction/data.csv
new file mode 100644
index 0000000..2dba427
--- /dev/null
+++ b/House price prediction/data.csv	
@@ -0,0 +1,5000 @@
+0,2009,21,9,6,84,121,14264
+1,2007,4,2,3,86,121,12032
+2,2016,18,3,7,90,120,13560
+3,2002,13,2,2,80,128,12029
+4,2014,25,5,8,81,122,14157
+5,2008,11,9,3,88,126,14287
+6,2000,23,5,10,83,128,13721
+7,2004,15,8,9,88,124,14010
+8,2017,32,5,5,82,124,14689
+9,2017,14,3,0,90,126,12670
+10,2016,22,4,5,85,127,13157
+11,2017,12,6,4,81,125,13611
+12,2010,29,3,9,85,123,14463
+13,2004,7,6,7,81,124,13253
+14,2012,8,4,2,86,122,13552
+15,2011,24,8,0,80,127,14841
+16,2006,20,8,9,84,122,14254
+17,2007,32,2,4,82,124,13968
+18,2004,2,4,10,89,121,13628
+19,2004,5,8,10,81,128,13920
+20,2014,25,10,0,90,127,14527
+21,2006,1,10,9,81,130,13853
+22,2006,31,1,5,90,121,13249
+23,2006,29,9,1,86,123,15194
+24,2006,30,9,4,82,129,15056
+25,2000,15,7,6,87,126,14010
+26,2001,36,1,0,82,121,13359
+27,2014,8,2,2,85,124,11896
+28,2009,19,8,5,84,129,14555
+29,2005,9,8,9,81,125,13986
+30,2001,24,1,3,82,128,13494
+31,2003,2,9,7,84,122,14392
+32,2005,24,9,10,90,120,15287
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+460,2012,18,3,4,83,130,13663
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+462,2014,16,3,1,88,120,13640
+463,2001,4,1,10,86,124,12543
+464,2000,28,4,9,90,127,13962
+465,2010,35,2,2,81,124,14511
+466,2003,31,1,0,89,129,13275
+467,2004,8,4,9,86,128,13644
+468,2014,4,0,8,83,130,12578
+469,2012,31,10,2,88,124,16168
+470,2011,11,0,10,81,129,13130
+471,2007,11,8,0,81,123,14241
+472,2017,22,3,7,83,126,13039
+473,2015,9,10,3,87,128,14219
+474,2000,32,0,10,81,123,14071
+475,2010,20,3,4,80,126,13854
+476,2012,20,0,8,83,126,13470
+477,2014,0,4,2,83,122,12583
+478,2000,18,0,7,82,129,13385
+479,2006,24,9,5,83,124,14399
+480,2018,38,2,7,81,125,15206
+481,2007,24,7,8,90,120,15017
+482,2009,9,9,6,87,121,14837
+483,2004,33,1,8,87,120,14162
+484,2008,22,9,3,85,124,14695
+485,2017,33,4,9,87,126,14548
+486,2010,1,0,0,89,129,11735
+487,2010,32,2,6,82,127,14730
+488,2001,21,9,5,81,129,14329
+489,2017,29,9,1,80,120,14698
+490,2009,38,3,8,88,125,14317
+491,2013,30,9,3,87,126,14798
+492,2002,30,8,5,86,123,14982
+493,2009,6,1,5,85,123,12631
+494,2000,0,6,0,81,128,12605
+495,2006,32,8,7,84,122,15876
+496,2006,18,6,0,88,128,13444
+497,2008,6,0,1,88,123,11610
+498,2008,0,10,3,88,123,13918
+499,2018,2,5,1,85,130,12353
+500,2016,21,3,2,88,123,13740
+501,2017,31,3,1,89,124,14279
+502,2001,8,3,2,87,126,12058
+503,2014,27,6,3,90,128,14967
+504,2016,2,2,1,82,126,12819
+505,2001,27,6,7,83,123,13905
+506,2010,6,1,5,86,130,12050
+507,2017,31,1,6,86,120,13706
+508,2001,20,3,2,88,123,13480
+509,2009,22,0,2,86,130,13312
+510,2018,16,5,8,82,124,14418
+511,2002,27,4,5,85,128,13932
+512,2005,30,5,1,85,122,13769
+513,2008,21,3,10,82,122,13560
+514,2002,18,9,4,83,128,14118
+515,2011,6,4,0,86,120,12742
+516,2017,16,8,4,86,125,14500
+517,2011,20,6,3,83,124,13809
+518,2006,38,4,8,86,123,14740
+519,2006,34,0,0,87,120,12900
+520,2008,11,8,10,88,129,14814
+521,2013,2,8,9,88,129,13754
+522,2010,6,10,5,83,123,14399
+523,2011,3,4,5,83,123,12661
+524,2011,0,4,9,86,129,12594
+525,2016,38,2,6,90,129,14331
+526,2008,33,3,7,81,120,14510
+527,2003,1,2,8,89,127,12493
+528,2016,31,6,6,90,126,15167
+529,2004,0,5,8,85,129,13847
+530,2011,33,5,9,87,124,14463
+531,2008,33,1,9,83,121,13588
+532,2007,0,1,9,88,120,11793
+533,2001,30,10,6,81,120,15043
+534,2007,14,9,5,82,130,14755
+535,2016,14,5,4,89,123,13764
+536,2017,11,10,10,89,120,14746
+537,2010,6,10,10,83,127,14419
+538,2008,35,10,2,81,125,15195
+539,2001,6,10,3,82,123,13493
+540,2000,38,5,2,80,120,15580
+541,2000,32,1,1,86,128,13749
+542,2015,24,0,6,85,123,12492
+543,2012,22,8,9,83,128,14559
+544,2005,20,4,2,81,125,13683
+545,2013,3,9,8,85,120,13879
+546,2003,15,5,6,82,127,13959
+547,2010,14,0,4,84,123,11928
+548,2003,16,0,10,85,123,12798
+549,2010,2,3,7,80,128,12287
+550,2003,5,10,5,81,121,13936
+551,2013,19,0,8,83,127,13549
+552,2012,30,5,4,81,122,14186
+553,2001,33,1,1,87,126,13831
+554,2007,10,8,4,85,122,13408
+555,2017,33,6,1,82,123,14652
+556,2005,4,10,0,89,122,13714
+557,2004,6,3,6,86,121,13436
+558,2018,21,7,3,86,124,14005
+559,2006,15,4,7,90,129,13740
+560,2009,35,5,6,89,124,14989
+561,2012,20,8,6,89,124,14800
+562,2003,4,9,3,88,126,13779
+563,2013,14,5,4,87,121,12846
+564,2009,13,2,9,86,120,13533
+565,2002,9,7,10,85,126,13958
+566,2004,12,9,0,80,121,14216
+567,2015,20,6,1,87,129,14407
+568,2009,29,1,6,89,126,13811
+569,2017,6,7,9,83,124,13988
+570,2004,11,1,1,81,121,11920
+571,2018,14,5,10,83,127,13310
+572,2006,16,9,0,82,129,13708
+573,2007,36,5,9,85,121,15056
+574,2008,14,6,3,81,128,13999
+575,2004,13,9,9,88,122,13998
+576,2011,36,2,10,86,124,15030
+577,2009,5,10,2,86,120,14717
+578,2009,2,4,2,87,126,12389
+579,2015,17,2,10,87,128,13729
+580,2003,30,7,5,90,129,15581
+581,2015,28,2,5,83,128,14404
+582,2018,20,7,10,89,126,14323
+583,2009,32,1,4,89,120,14292
+584,2012,16,0,2,85,120,11796
+585,2013,33,9,6,84,121,15148
+586,2016,1,0,7,88,128,12483
+587,2003,20,7,4,80,120,14373
+588,2008,31,9,5,90,126,15848
+589,2004,20,9,7,88,125,15280
+590,2000,13,7,6,87,124,13654
+591,2013,8,0,8,82,126,12162
+592,2003,26,5,4,85,124,14380
+593,2002,27,4,6,80,130,14346
+594,2002,19,3,6,84,129,13893
+595,2016,1,5,8,90,121,13655
+596,2015,2,0,8,87,126,11902
+597,2011,20,2,6,90,120,12636
+598,2001,4,5,0,82,124,12595
+599,2010,24,5,5,86,129,14488
+600,2004,20,9,6,85,123,14070
+601,2013,37,0,4,85,120,13392
+602,2012,14,0,5,83,124,12996
+603,2002,29,7,1,82,122,14842
+604,2013,31,6,6,83,121,15468
+605,2014,19,0,6,90,127,13237
+606,2017,15,1,9,86,121,13090
+607,2006,0,8,7,85,125,14172
+608,2011,30,2,5,85,122,14008
+609,2014,2,0,6,87,129,11688
+610,2017,28,8,8,85,124,14677
+611,2006,23,7,1,87,128,14501
+612,2002,21,0,2,87,122,12294
+613,2003,18,9,0,83,126,13660
+614,2005,4,4,4,81,125,12607
+615,2014,36,3,10,81,130,15385
+616,2007,0,3,7,83,128,13255
+617,2011,5,5,5,81,128,13192
+618,2010,29,9,7,88,124,15277
+619,2004,31,3,9,81,126,13703
+620,2002,13,4,1,83,122,12876
+621,2002,5,5,1,90,125,12597
+622,2013,31,5,0,85,123,13844
+623,2010,7,5,3,89,129,13318
+624,2000,6,5,7,85,128,12656
+625,2017,5,2,10,87,121,12464
+626,2016,32,8,9,85,123,14903
+627,2012,27,3,3,84,130,13177
+628,2011,6,1,4,80,124,12193
+629,2001,24,2,1,87,128,12614
+630,2014,14,8,2,81,126,14143
+631,2017,10,3,3,81,129,12498
+632,2003,32,9,10,87,120,15476
+633,2015,14,10,8,80,129,14140
+634,2010,17,10,0,85,127,13876
+635,2009,30,7,2,83,120,14872
+636,2016,4,4,10,83,125,13350
+637,2018,18,2,8,84,129,13435
+638,2005,35,10,1,80,126,15131
+639,2008,20,6,3,83,127,13811
+640,2018,13,1,10,81,124,13548
+641,2017,8,5,8,89,121,13970
+642,2012,33,0,5,90,126,13774
+643,2004,28,4,7,86,127,13988
+644,2017,19,9,6,85,122,14198
+645,2000,32,7,4,85,125,15251
+646,2006,28,7,10,86,120,14994
+647,2018,17,8,4,84,123,13905
+648,2012,17,5,0,88,130,13347
+649,2002,31,0,6,83,126,13448
+650,2006,0,9,3,89,128,14478
+651,2006,5,8,0,87,122,13048
+652,2015,16,0,3,85,129,13045
+653,2004,19,6,4,88,128,13815
+654,2007,1,10,4,81,123,13821
+655,2001,34,5,7,90,128,15318
+656,2006,22,2,7,86,123,13156
+657,2016,28,9,8,85,125,15903
+658,2002,9,9,10,90,128,14300
+659,2014,26,10,7,89,130,15336
+660,2018,29,9,6,85,128,15401
+661,2008,9,2,5,87,130,13229
+662,2005,19,8,10,88,122,14010
+663,2017,38,10,2,87,124,15789
+664,2006,2,1,4,83,120,12435
+665,2003,12,7,6,82,121,13333
+666,2007,13,0,4,80,125,12993
+667,2002,1,3,1,83,125,13058
+668,2008,24,4,6,89,127,13441
+669,2017,33,5,1,80,129,15220
+670,2006,30,7,10,86,122,14527
+671,2004,14,8,8,85,128,14299
+672,2014,10,7,2,83,125,14017
+673,2010,22,0,3,89,127,13239
+674,2009,8,4,7,88,124,13430
+675,2012,37,2,4,90,121,14074
+676,2013,35,4,9,87,130,14848
+677,2003,7,5,5,89,127,13120
+678,2006,3,9,1,87,125,13658
+679,2003,27,3,10,86,121,14702
+680,2004,35,0,1,85,128,13944
+681,2012,0,2,10,80,122,12042
+682,2015,11,7,6,85,126,13647
+683,2013,21,8,8,88,128,14352
+684,2015,17,3,7,81,121,13589
+685,2003,23,8,1,90,121,14047
+686,2013,33,7,7,80,122,15759
+687,2014,13,0,2,86,123,12821
+688,2008,1,6,2,83,122,12992
+689,2006,8,6,3,87,124,12874
+690,2009,5,6,10,80,129,14147
+691,2013,1,8,5,83,128,14385
+692,2003,32,8,10,85,121,15759
+693,2005,35,9,3,84,128,15043
+694,2017,27,10,5,86,129,15931
+695,2001,12,10,10,85,126,14343
+696,2011,8,10,0,83,123,13462
+697,2007,5,7,1,87,124,13655
+698,2016,21,5,4,83,123,14357
+699,2010,16,10,3,84,129,14485
+700,2000,11,9,2,85,122,14159
+701,2007,18,8,2,82,121,13656
+702,2017,19,4,6,84,120,13747
+703,2017,28,9,7,82,130,15367
+704,2012,31,8,4,88,121,15816
+705,2014,8,0,10,89,121,11896
+706,2012,9,5,6,84,121,13855
+707,2018,21,4,1,82,124,13378
+708,2011,29,7,0,81,129,15123
+709,2011,32,7,0,86,126,15369
+710,2014,2,0,2,87,128,12239
+711,2011,27,2,1,86,123,13090
+712,2002,1,4,6,90,123,12783
+713,2017,4,9,10,89,128,13963
+714,2017,3,0,3,80,126,12155
+715,2003,24,0,0,80,123,13367
+716,2018,2,7,7,84,120,14150
+717,2018,21,8,4,90,129,15074
+718,2014,7,4,0,82,128,12687
+719,2007,30,6,8,84,122,15343
+720,2018,1,5,8,83,128,12787
+721,2007,20,4,6,90,122,13795
+722,2004,23,3,3,80,130,13475
+723,2016,18,7,5,84,125,14802
+724,2014,23,5,4,82,121,13573
+725,2017,12,5,10,90,120,13843
+726,2014,26,0,4,90,129,13211
+727,2018,38,8,9,82,123,15804
+728,2014,28,6,5,81,120,14168
+729,2003,6,10,4,83,120,13793
+730,2008,0,2,8,82,127,12086
+731,2007,0,0,6,84,122,11559
+732,2007,31,10,2,85,122,15613
+733,2003,15,10,5,86,121,14971
+734,2005,37,6,0,80,125,15651
+735,2016,37,7,3,87,129,15118
+736,2015,37,0,0,87,121,14226
+737,2005,23,9,4,85,125,15429
+738,2003,5,10,0,83,129,13740
+739,2008,34,10,1,82,124,15939
+740,2002,33,2,6,85,124,13889
+741,2000,34,7,7,86,120,15042
+742,2010,9,4,1,90,128,12951
+743,2012,6,5,9,89,122,13306
+744,2006,34,0,6,83,125,14090
+745,2003,32,2,9,84,125,14844
+746,2014,16,5,4,84,129,13228
+747,2000,20,0,10,85,125,13262
+748,2008,2,1,5,83,130,11921
+749,2013,25,3,1,83,126,13292
+750,2001,5,9,8,88,121,14522
+751,2002,29,1,5,88,123,12948
+752,2014,29,10,9,89,127,16142
+753,2012,15,5,0,80,123,13546
+754,2014,26,4,3,87,127,14203
+755,2016,29,5,1,90,123,14408
+756,2006,6,1,0,90,128,11663
+757,2013,16,0,7,81,120,12913
+758,2017,5,7,7,80,128,13363
+759,2000,19,2,10,87,121,13345
+760,2015,20,1,10,90,122,13798
+761,2001,26,4,7,89,124,14457
+762,2007,14,6,0,83,123,13826
+763,2016,35,4,3,80,122,14105
+764,2015,23,7,5,86,124,13962
+765,2008,14,5,5,88,129,13928
+766,2013,0,6,2,85,123,12762
+767,2015,19,0,0,86,120,12883
+768,2017,1,0,5,89,124,11992
+769,2006,11,3,7,83,130,13328
+770,2000,17,8,8,83,124,14897
+771,2002,4,10,3,81,120,13420
+772,2015,32,9,4,88,123,14880
+773,2004,33,3,4,81,122,13847
+774,2008,38,5,0,85,130,14467
+775,2013,35,7,6,81,122,15382
+776,2012,26,2,6,84,122,13888
+777,2011,10,1,0,90,127,12196
+778,2010,20,1,1,89,124,13455
+779,2007,27,3,6,89,122,13660
+780,2018,26,10,8,87,124,15614
+781,2009,22,5,5,81,130,13958
+782,2003,21,6,10,82,123,14546
+783,2011,21,7,0,87,130,13985
+784,2001,34,0,3,80,130,13550
+785,2009,13,4,9,82,120,13673
+786,2008,0,1,3,87,122,11882
+787,2014,10,5,2,84,120,13318
+788,2004,17,6,6,81,124,13875
+789,2006,37,0,10,84,124,13674
+790,2001,2,10,2,84,122,13343
+791,2009,7,0,0,82,126,12339
+792,2005,10,9,5,85,120,14284
+793,2013,22,0,0,81,130,12955
+794,2007,31,3,9,89,120,14355
+795,2015,38,1,6,80,123,14796
+796,2011,33,5,5,82,125,14118
+797,2009,32,5,4,81,129,14370
+798,2012,25,8,7,89,120,14639
+799,2017,13,4,4,89,128,13291
+800,2016,12,5,10,82,128,13843
+801,2005,9,5,2,81,127,13008
+802,2002,30,2,1,89,120,13394
+803,2016,37,4,4,88,121,15000
+804,2000,12,5,0,88,121,13128
+805,2018,29,9,7,82,123,14904
+806,2006,37,8,3,80,126,16240
+807,2003,27,5,9,88,130,14372
+808,2001,28,8,3,85,127,14238
+809,2006,10,3,3,80,122,12903
+810,2013,34,1,10,81,122,14499
+811,2004,22,6,5,88,127,14414
+812,2009,14,9,6,88,121,14417
+813,2015,7,9,8,87,123,14154
+814,2000,23,5,1,81,128,13639
+815,2003,34,4,0,80,127,14587
+816,2006,16,7,4,90,125,13494
+817,2015,3,6,4,80,126,13178
+818,2017,7,8,3,85,129,13468
+819,2014,4,3,10,90,122,13655
+820,2000,27,7,3,86,124,14815
+821,2014,5,2,10,87,129,13501
+822,2015,13,10,6,88,122,13996
+823,2011,15,9,0,90,128,14223
+824,2004,6,8,3,83,125,13088
+825,2009,4,6,1,88,127,13195
+826,2003,30,4,5,83,122,14748
+827,2002,12,10,9,84,125,14539
+828,2007,23,5,8,89,120,13515
+829,2015,36,6,8,87,129,15815
+830,2009,33,0,3,85,124,14000
+831,2009,6,2,5,82,129,12096
+832,2000,3,0,1,85,126,11743
+833,2004,20,0,1,85,128,12975
+834,2007,31,2,6,87,120,13864
+835,2018,30,6,9,84,120,15563
+836,2016,32,3,1,86,121,14702
+837,2016,6,4,5,82,130,12801
+838,2016,37,1,0,81,125,13416
+839,2013,25,3,4,90,129,13620
+840,2005,10,10,10,88,130,15076
+841,2014,13,0,6,89,123,12406
+842,2013,13,5,1,84,125,13540
+843,2010,19,4,4,81,121,13099
+844,2014,13,5,5,89,127,13277
+845,2009,17,3,10,85,123,14118
+846,2000,2,2,9,84,124,13011
+847,2009,2,3,8,82,124,13453
+848,2001,37,4,0,81,121,14564
+849,2007,5,0,6,80,126,12433
+850,2011,21,2,6,88,121,13951
+851,2000,1,3,9,89,129,12870
+852,2013,13,10,1,89,129,14536
+853,2005,32,1,3,87,123,13725
+854,2002,26,4,5,89,128,13755
+855,2017,34,0,3,81,129,13755
+856,2006,28,9,10,82,121,14908
+857,2006,18,2,1,81,121,13092
+858,2015,8,8,6,80,128,14619
+859,2009,10,10,10,87,127,14570
+860,2007,16,5,6,80,128,13772
+861,2002,3,4,2,83,129,12625
+862,2012,16,4,3,82,123,13420
+863,2014,31,10,1,89,123,16002
+864,2012,37,8,2,87,123,16112
+865,2005,16,0,8,80,129,13346
+866,2016,1,4,4,86,122,13231
+867,2017,22,5,9,90,124,13579
+868,2016,6,10,3,80,130,13975
+869,2016,37,4,7,89,129,15325
+870,2011,22,6,1,87,128,14628
+871,2016,22,7,8,82,129,14314
+872,2002,25,3,0,85,128,13335
+873,2009,5,8,1,80,127,13610
+874,2004,22,6,0,85,121,14494
+875,2000,5,3,4,81,128,12419
+876,2011,1,10,6,89,127,14759
+877,2015,31,10,10,83,126,15309
+878,2000,30,1,7,80,125,14220
+879,2004,1,8,6,82,128,14259
+880,2011,10,10,4,88,122,14509
+881,2012,5,0,3,81,129,11699
+882,2005,10,1,10,81,122,12089
+883,2009,4,1,4,89,120,12654
+884,2006,15,5,8,83,126,13191
+885,2004,10,8,10,84,127,14850
+886,2004,16,2,9,89,130,13090
+887,2004,8,0,3,90,122,12514
+888,2001,12,4,3,82,123,13433
+889,2014,2,9,9,85,123,14180
+890,2002,22,7,2,89,122,13688
+891,2007,23,9,6,90,121,15416
+892,2000,28,3,1,80,129,14072
+893,2015,1,6,6,89,122,13131
+894,2005,1,1,2,84,130,12496
+895,2010,38,5,8,87,127,15626
+896,2016,33,10,4,84,129,16334
+897,2013,18,2,4,89,121,12435
+898,2007,0,7,5,82,125,13595
+899,2001,23,5,2,90,120,13568
+900,2018,38,10,6,86,130,16779
+901,2007,12,8,5,81,126,14674
+902,2011,3,5,6,88,122,13569
+903,2009,18,2,6,90,127,13561
+904,2001,3,6,10,87,127,13323
+905,2012,30,0,4,83,125,13188
+906,2009,6,4,7,80,127,12965
+907,2006,5,4,0,90,124,12100
+908,2006,7,10,7,81,122,14746
+909,2007,21,2,3,82,129,13417
+910,2001,30,2,10,88,122,13467
+911,2009,1,5,3,81,130,12367
+912,2008,9,4,8,86,121,13484
+913,2014,2,8,7,90,121,13499
+914,2008,4,1,4,81,124,11749
+915,2012,38,9,4,87,129,16051
+916,2014,18,1,6,85,126,12597
+917,2003,27,8,8,90,123,15310
+918,2005,28,9,6,84,124,14603
+919,2003,30,8,9,86,128,14711
+920,2004,25,6,8,86,128,14881
+921,2005,21,0,3,90,125,12391
+922,2007,2,4,0,87,124,13149
+923,2006,3,2,7,81,121,12429
+924,2009,18,8,8,89,120,14625
+925,2015,11,9,2,81,127,13738
+926,2004,7,2,5,83,127,11970
+927,2003,19,3,0,83,123,12426
+928,2006,33,0,8,86,127,13375
+929,2003,32,1,8,85,130,14120
+930,2015,16,5,4,87,124,13346
+931,2001,16,8,0,81,120,14545
+932,2008,5,5,10,87,128,13961
+933,2001,18,0,5,89,122,12026
+934,2009,11,5,7,85,127,13752
+935,2005,4,8,4,85,120,13321
+936,2018,33,10,2,87,125,15859
+937,2018,14,9,7,86,123,14135
+938,2008,20,1,10,84,121,13728
+939,2000,5,5,7,81,124,13718
+940,2006,32,1,2,90,130,13356
+941,2013,35,0,1,84,122,13698
+942,2003,15,10,9,85,120,15286
+943,2008,2,9,4,89,126,13306
+944,2002,26,4,6,88,128,13548
+945,2016,20,8,1,86,128,14074
+946,2007,34,8,5,86,127,16113
+947,2000,22,2,4,87,128,13891
+948,2003,31,4,6,84,122,13874
+949,2001,12,2,9,86,129,13122
+950,2010,28,10,2,81,126,14644
+951,2005,24,5,3,83,125,13822
+952,2006,14,4,10,83,120,13254
+953,2015,24,3,6,81,128,14243
+954,2005,10,7,7,82,122,14326
+955,2001,23,2,4,90,124,13825
+956,2011,28,3,4,88,124,13533
+957,2001,30,1,8,90,125,14199
+958,2011,15,6,10,90,120,14537
+959,2005,25,6,5,85,122,14823
+960,2008,33,7,9,83,128,15379
+961,2008,6,5,4,89,125,12927
+962,2000,32,9,7,80,129,15830
+963,2014,30,6,1,86,122,14786
+964,2007,5,1,3,85,120,12601
+965,2015,10,8,3,80,122,14381
+966,2000,28,7,8,86,130,15298
+967,2016,8,3,6,87,122,12940
+968,2010,19,7,7,82,121,14517
+969,2010,37,0,5,83,128,14092
+970,2000,28,1,7,81,125,13191
+971,2016,25,7,4,90,123,14316
+972,2008,21,8,3,81,130,14179
+973,2017,7,7,0,82,120,12912
+974,2016,1,0,6,86,124,12400
+975,2004,15,0,3,82,123,12137
+976,2016,8,1,4,89,129,12481
+977,2002,21,7,8,90,124,14951
+978,2002,3,3,8,84,127,13216
+979,2015,9,10,8,90,121,14697
+980,2005,13,5,1,88,126,13652
+981,2015,37,4,7,86,122,14636
+982,2004,22,2,8,90,128,13244
+983,2008,34,2,5,81,128,13705
+984,2009,8,0,2,88,122,11849
+985,2008,1,2,6,89,129,12807
+986,2004,3,10,4,89,130,14055
+987,2012,11,2,5,83,121,13129
+988,2006,19,0,0,83,120,12949
+989,2010,34,7,5,82,127,15011
+990,2005,30,0,10,89,130,14015
+991,2017,11,3,0,80,122,13351
+992,2012,17,5,3,87,122,13699
+993,2016,38,3,3,90,129,14638
+994,2012,13,2,9,90,122,13201
+995,2012,38,3,10,84,128,15059
+996,2009,12,6,1,83,127,13568
+997,2005,20,1,6,86,124,13539
+998,2016,14,8,8,80,128,14082
+999,2001,15,5,9,82,130,13486
+1000,2001,11,9,2,83,121,13645
+1001,2013,36,7,6,80,130,15133
+1002,2010,22,0,8,82,123,13306
+1003,2003,35,5,9,86,121,15708
+1004,2008,5,2,2,89,123,11788
+1005,2011,37,5,7,90,122,14719
+1006,2009,2,2,5,80,124,12458
+1007,2017,22,3,2,83,125,13918
+1008,2012,1,0,10,85,127,12466
+1009,2004,18,7,1,86,128,14443
+1010,2015,16,4,5,82,122,13529
+1011,2003,38,9,6,89,122,15573
+1012,2005,7,4,3,88,120,12525
+1013,2003,32,8,8,89,124,15191
+1014,2005,14,5,6,89,130,13848
+1015,2013,23,6,6,84,122,14650
+1016,2008,31,4,4,82,129,13828
+1017,2018,29,10,9,83,127,15124
+1018,2016,1,6,9,80,122,13997
+1019,2003,6,7,4,85,130,12956
+1020,2012,21,0,4,86,126,13469
+1021,2016,7,3,0,81,123,12961
+1022,2017,21,1,6,90,124,12670
+1023,2001,4,9,10,81,127,13837
+1024,2003,27,4,8,83,120,14662
+1025,2009,16,6,7,80,126,13527
+1026,2016,3,9,2,87,125,13758
+1027,2016,3,0,0,84,129,12162
+1028,2004,38,1,1,81,123,14118
+1029,2014,1,9,0,80,124,14319
+1030,2001,10,7,6,85,121,13510
+1031,2000,17,7,7,85,125,13514
+1032,2015,13,8,6,87,122,14437
+1033,2002,17,10,2,84,121,14780
+1034,2007,32,3,6,82,124,14273
+1035,2005,19,6,6,85,124,13378
+1036,2015,22,2,1,85,128,12546
+1037,2008,29,2,10,89,127,13962
+1038,2005,31,1,7,88,129,14386
+1039,2013,29,8,4,88,124,14673
+1040,2013,6,10,0,87,129,14091
+1041,2005,32,3,4,90,123,13820
+1042,2013,12,2,8,84,125,12470
+1043,2015,15,10,4,84,128,14002
+1044,2012,29,5,5,83,121,14794
+1045,2010,0,3,4,88,122,12103
+1046,2001,37,8,10,84,126,15703
+1047,2017,18,0,3,89,125,12653
+1048,2004,0,3,0,89,120,12497
+1049,2017,35,8,4,84,123,15412
+1050,2009,32,8,0,87,130,15097
+1051,2008,5,5,8,89,129,13372
+1052,2012,36,0,9,84,127,14840
+1053,2009,10,9,3,80,130,13983
+1054,2009,38,8,7,84,120,16282
+1055,2014,11,5,10,85,123,13401
+1056,2001,29,2,10,81,120,14352
+1057,2006,5,8,10,90,126,13585
+1058,2010,30,9,9,81,121,15529
+1059,2003,3,3,5,84,128,13077
+1060,2004,21,3,4,81,130,13028
+1061,2012,7,4,3,84,120,13296
+1062,2014,9,2,3,86,124,12868
+1063,2015,26,10,10,80,123,15407
+1064,2014,17,2,0,82,129,13330
+1065,2005,3,10,8,86,125,14469
+1066,2018,11,2,9,89,124,13027
+1067,2000,38,3,3,88,126,14027
+1068,2010,37,6,6,85,127,15634
+1069,2011,14,4,3,87,123,13722
+1070,2010,3,1,5,85,125,11810
+1071,2001,35,2,0,83,126,14009
+1072,2011,35,3,6,86,126,14831
+1073,2017,29,0,0,82,126,13567
+1074,2004,1,9,6,86,124,13339
+1075,2009,37,10,7,85,128,16423
+1076,2008,23,8,5,88,121,14640
+1077,2003,27,0,8,80,122,13212
+1078,2011,22,6,1,90,120,13590
+1079,2002,24,1,0,82,129,12850
+1080,2006,14,5,0,85,120,13477
+1081,2005,11,6,2,83,120,13266
+1082,2011,6,0,6,83,128,12256
+1083,2018,12,8,8,83,120,14100
+1084,2010,24,1,8,90,125,12804
+1085,2003,20,0,8,80,127,12659
+1086,2013,22,0,10,89,124,12579
+1087,2004,36,7,7,80,129,16014
+1088,2017,5,6,10,81,125,14170
+1089,2008,32,5,7,85,121,14743
+1090,2017,36,3,1,87,124,14442
+1091,2017,18,10,4,84,127,14789
+1092,2001,33,4,3,85,125,14404
+1093,2003,15,0,5,80,124,11975
+1094,2000,25,4,0,81,130,13649
+1095,2001,3,5,5,87,124,13601
+1096,2001,31,0,2,90,130,13553
+1097,2006,11,10,7,90,123,14563
+1098,2005,16,8,6,86,126,13916
+1099,2004,1,4,4,84,120,12394
+1100,2001,36,8,7,89,126,15487
+1101,2010,34,9,0,87,127,16100
+1102,2010,32,7,7,84,126,14822
+1103,2011,9,10,1,89,123,14333
+1104,2011,9,1,3,86,126,12787
+1105,2018,2,4,3,84,120,12183
+1106,2008,17,4,5,84,125,14076
+1107,2016,6,3,5,89,120,13077
+1108,2004,2,3,3,84,124,12432
+1109,2012,34,8,2,86,123,15084
+1110,2005,25,9,10,87,130,15143
+1111,2016,30,6,0,90,129,14805
+1112,2007,6,3,5,88,125,13055
+1113,2018,31,10,7,81,130,15187
+1114,2009,12,2,4,89,123,13272
+1115,2005,20,4,2,80,120,13398
+1116,2007,30,2,2,81,122,13566
+1117,2012,22,3,3,80,130,12822
+1118,2003,30,2,8,90,124,14406
+1119,2013,4,3,3,90,129,12583
+1120,2004,20,1,1,84,127,13165
+1121,2011,18,5,5,82,126,13592
+1122,2000,28,10,5,81,128,14881
+1123,2010,5,10,6,86,125,13690
+1124,2010,38,4,1,85,125,14416
+1125,2006,34,0,8,80,123,14416
+1126,2004,6,2,8,86,130,12499
+1127,2013,21,4,1,85,125,13626
+1128,2018,24,2,4,84,124,14071
+1129,2000,2,10,10,85,130,14040
+1130,2007,31,7,9,89,128,15618
+1131,2000,25,8,8,83,126,15262
+1132,2017,10,10,5,85,128,14860
+1133,2008,2,10,6,84,129,14373
+1134,2012,11,8,1,90,122,14481
+1135,2018,35,0,8,82,127,14343
+1136,2013,16,2,8,82,123,13137
+1137,2018,30,0,1,80,123,13924
+1138,2011,2,10,0,86,129,13468
+1139,2015,0,8,1,81,127,13278
+1140,2016,18,6,8,89,120,13602
+1141,2015,23,7,5,80,123,14809
+1142,2018,22,5,4,87,128,13342
+1143,2003,23,7,9,84,126,14860
+1144,2005,5,6,4,88,125,12711
+1145,2002,30,3,3,86,121,14446
+1146,2010,10,9,10,84,120,14680
+1147,2000,24,9,7,80,122,15577
+1148,2018,1,4,3,88,125,13092
+1149,2010,20,8,7,84,122,15182
+1150,2008,13,8,5,86,124,13602
+1151,2000,10,1,10,89,121,12729
+1152,2006,5,8,8,81,125,14191
+1153,2002,24,3,1,85,129,12819
+1154,2014,11,10,8,82,124,15248
+1155,2003,1,6,0,82,123,12868
+1156,2008,11,7,10,80,123,14274
+1157,2007,31,6,9,87,130,14776
+1158,2000,30,2,6,83,120,14486
+1159,2002,8,9,0,87,129,14385
+1160,2014,8,10,1,87,120,13530
+1161,2011,3,10,6,83,123,13743
+1162,2015,18,3,9,83,120,12864
+1163,2011,27,9,0,87,121,15141
+1164,2004,37,9,10,89,122,16693
+1165,2018,5,3,9,85,129,12658
+1166,2010,11,10,3,81,120,14069
+1167,2012,17,6,10,85,123,13752
+1168,2002,5,7,6,80,123,14218
+1169,2001,21,9,3,83,126,14475
+1170,2002,16,4,4,89,124,13586
+1171,2010,5,0,2,80,120,11458
+1172,2002,10,10,10,88,123,14644
+1173,2008,31,5,4,81,130,15172
+1174,2007,36,5,10,85,128,15145
+1175,2012,20,4,5,87,124,14144
+1176,2009,16,5,6,84,120,13379
+1177,2007,34,9,8,88,127,15986
+1178,2013,19,2,10,86,128,12814
+1179,2012,35,4,2,87,130,15249
+1180,2000,7,3,6,84,123,13322
+1181,2000,6,1,10,88,128,13005
+1182,2013,17,8,0,81,120,14656
+1183,2001,1,2,6,90,120,12727
+1184,2001,34,7,0,86,125,15355
+1185,2010,6,4,3,80,121,13241
+1186,2004,0,4,1,81,128,12885
+1187,2010,28,8,2,84,125,15099
+1188,2017,18,2,7,86,123,13735
+1189,2005,4,6,0,90,128,13393
+1190,2016,21,2,10,80,123,13769
+1191,2018,1,7,4,82,127,13756
+1192,2013,10,9,9,86,129,14201
+1193,2005,32,8,5,80,125,15264
+1194,2013,37,0,6,85,128,14293
+1195,2013,33,4,10,87,128,15345
+1196,2018,30,7,8,85,122,14608
+1197,2016,20,6,6,86,126,14137
+1198,2008,31,7,10,84,124,15751
+1199,2009,16,4,0,83,129,13797
+1200,2014,19,2,4,87,130,12787
+1201,2007,0,10,7,87,124,14743
+1202,2005,11,10,5,87,124,14196
+1203,2002,21,1,9,87,122,13601
+1204,2004,1,5,3,82,123,12812
+1205,2003,16,1,0,83,127,12133
+1206,2000,32,9,8,80,124,15096
+1207,2018,27,8,2,85,128,15466
+1208,2001,30,0,7,89,126,13067
+1209,2009,22,5,9,85,122,14259
+1210,2008,23,7,5,80,128,14676
+1211,2001,33,4,4,85,125,14706
+1212,2003,19,0,6,84,123,13004
+1213,2010,24,7,6,89,126,15213
+1214,2000,38,4,6,84,130,15647
+1215,2000,8,1,0,85,124,11901
+1216,2001,23,4,10,82,121,14229
+1217,2007,37,3,0,90,129,14224
+1218,2017,23,8,0,87,122,14183
+1219,2013,15,6,3,89,120,13562
+1220,2017,24,2,1,81,129,12921
+1221,2011,0,5,9,81,128,13529
+1222,2010,11,1,8,83,128,12223
+1223,2012,13,5,6,82,127,13660
+1224,2016,11,6,4,83,130,13351
+1225,2004,22,8,8,86,129,14489
+1226,2006,27,8,1,88,130,14500
+1227,2003,26,1,8,89,121,13382
+1228,2007,29,2,10,86,122,14292
+1229,2011,26,2,6,89,130,13449
+1230,2018,10,6,5,80,130,14239
+1231,2005,10,7,2,80,127,13590
+1232,2013,38,5,6,90,125,15167
+1233,2008,27,10,2,86,127,15473
+1234,2004,37,1,10,80,128,14246
+1235,2006,10,6,10,90,125,14073
+1236,2007,27,0,5,87,127,13271
+1237,2015,9,9,3,85,129,13491
+1238,2003,22,8,6,89,128,14772
+1239,2018,5,2,5,87,128,12006
+1240,2004,21,5,3,82,120,13721
+1241,2011,34,10,3,82,124,16432
+1242,2018,7,4,6,80,124,12722
+1243,2018,4,0,2,88,122,11522
+1244,2017,23,4,2,90,128,13736
+1245,2008,18,1,0,84,120,12606
+1246,2011,21,5,2,81,127,14370
+1247,2011,8,2,6,83,128,13354
+1248,2002,20,3,0,80,129,13252
+1249,2014,31,0,0,84,128,13099
+1250,2011,33,1,3,90,129,13382
+1251,2017,29,1,7,80,124,13844
+1252,2007,1,2,2,80,126,12037
+1253,2013,20,4,3,88,125,13304
+1254,2007,16,6,4,82,128,14019
+1255,2012,37,4,0,84,127,14415
+1256,2010,2,9,2,80,126,13802
+1257,2002,34,9,9,88,129,15392
+1258,2010,3,4,5,84,130,12574
+1259,2008,9,0,4,80,121,12186
+1260,2018,17,10,10,90,126,14813
+1261,2015,29,7,9,84,124,14824
+1262,2016,25,0,8,81,122,13646
+1263,2015,21,8,10,89,124,14696
+1264,2001,0,10,6,84,129,13668
+1265,2009,5,1,2,84,123,12321
+1266,2003,28,3,6,82,120,13667
+1267,2007,35,10,6,84,125,15405
+1268,2012,18,3,10,88,123,13067
+1269,2008,18,3,7,81,124,12867
+1270,2013,13,0,7,84,122,12798
+1271,2018,28,7,6,80,122,14835
+1272,2014,32,1,4,80,123,13407
+1273,2003,12,0,1,83,123,11650
+1274,2013,20,7,5,89,127,14935
+1275,2008,1,4,2,85,125,12221
+1276,2012,24,10,6,86,129,15749
+1277,2005,37,10,8,80,128,16554
+1278,2014,0,9,8,80,127,14717
+1279,2004,2,7,1,88,129,12716
+1280,2009,30,0,10,89,126,14391
+1281,2011,32,7,5,86,126,15745
+1282,2008,8,6,10,80,122,14070
+1283,2008,18,1,9,80,128,13333
+1284,2006,14,8,8,80,120,14365
+1285,2018,38,9,4,88,126,16574
+1286,2000,26,0,3,87,122,13289
+1287,2003,10,5,4,80,129,13141
+1288,2007,20,9,10,83,130,14314
+1289,2002,17,4,3,83,122,13798
+1290,2006,33,2,2,84,124,13956
+1291,2001,23,4,4,86,120,14069
+1292,2005,22,9,8,86,128,14328
+1293,2017,12,0,5,83,128,12452
+1294,2001,6,1,3,87,129,12660
+1295,2001,25,10,2,82,120,15491
+1296,2004,18,7,5,81,123,14212
+1297,2012,30,0,4,88,130,13619
+1298,2018,32,3,3,85,127,13958
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+1303,2014,25,10,7,89,129,16017
+1304,2001,27,2,8,81,129,13272
+1305,2018,33,8,6,90,125,15260
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+1317,2012,35,5,6,80,122,14570
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+1319,2011,14,3,4,88,126,13334
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+1325,2007,20,6,7,82,129,14138
+1326,2018,37,10,5,85,122,15830
+1327,2006,29,2,10,90,123,14187
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+1329,2005,26,6,0,86,128,13925
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+1333,2008,38,8,5,89,123,15967
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+1337,2001,36,5,10,80,128,15342
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+1403,2011,34,3,3,90,127,13864
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+1418,2018,7,8,3,87,130,13489
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+1426,2004,38,5,0,89,127,15206
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+1433,2017,37,1,6,82,123,14723
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+1442,2011,28,9,3,86,124,15375
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+1502,2006,17,1,7,88,120,12535
+1503,2013,38,3,4,80,126,15110
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+1510,2010,12,9,3,87,123,14568
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+1512,2006,0,1,2,81,128,11826
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+1515,2008,12,10,3,86,120,13747
+1516,2006,0,4,8,84,120,12963
+1517,2013,30,3,6,81,126,14149
+1518,2009,34,6,8,90,130,15378
+1519,2009,16,10,0,87,125,14197
+1520,2011,18,1,8,81,129,12552
+1521,2011,22,0,5,80,127,12291
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+1530,2008,22,0,7,87,125,13282
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+1532,2002,34,1,4,83,126,13420
+1533,2005,14,1,8,88,130,12741
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+1541,2011,26,2,9,81,125,13909
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+1543,2007,37,6,10,87,127,16081
+1544,2018,9,0,7,83,128,12062
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+1557,2006,32,7,7,81,126,14786
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+1570,2003,29,8,2,86,130,14673
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+1586,2008,28,4,1,88,120,13805
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+1588,2003,35,0,5,90,123,13380
+1589,2005,37,0,3,82,129,13589
+1590,2005,25,7,6,88,125,14614
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+1601,2001,10,9,9,82,122,13704
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+1603,2009,30,1,9,83,120,14100
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+1605,2018,26,3,9,85,121,13391
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+1612,2008,32,4,5,82,121,14293
+1613,2014,19,8,7,90,126,15197
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+1615,2014,31,8,3,81,130,14531
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+1617,2006,12,4,5,82,122,13678
+1618,2010,33,5,2,90,128,14398
+1619,2011,28,5,0,81,121,13950
+1620,2009,26,1,10,89,121,14016
+1621,2004,21,1,0,83,128,13427
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+1623,2001,33,9,2,84,126,15294
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+1695,2017,20,8,2,83,120,14699
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+1699,2001,20,3,9,89,124,13840
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+1701,2017,11,9,5,83,126,14911
+1702,2009,26,9,2,84,126,14290
+1703,2010,5,3,8,88,129,13087
+1704,2012,6,8,3,87,120,13750
+1705,2014,26,3,10,84,124,14314
+1706,2012,12,6,2,82,122,13600
+1707,2016,23,8,3,88,130,14252
+1708,2008,18,0,9,84,125,12505
+1709,2012,10,3,7,85,121,12397
+1710,2010,30,5,8,87,130,15081
+1711,2015,5,5,8,84,121,13086
+1712,2017,16,9,8,87,126,15180
+1713,2006,11,4,6,80,126,13700
+1714,2011,6,9,7,82,126,14044
+1715,2016,26,2,2,87,125,13614
+1716,2010,36,0,3,90,126,14555
+1717,2009,36,0,3,89,124,14407
+1718,2004,3,5,3,86,120,12481
+1719,2009,24,9,0,86,123,14426
+1720,2015,17,10,1,84,124,14307
+1721,2005,32,8,7,80,122,14717
+1722,2005,29,7,10,88,128,14741
+1723,2018,33,8,3,88,128,15873
+1724,2018,21,3,10,90,122,13146
+1725,2016,23,0,6,82,121,12658
+1726,2005,21,1,2,81,121,13105
+1727,2003,27,4,3,81,129,13318
+1728,2007,38,9,1,86,124,16221
+1729,2015,23,0,8,90,120,13165
+1730,2018,10,10,0,88,129,14383
+1731,2005,8,1,4,85,124,12630
+1732,2004,5,5,3,84,123,12918
+1733,2013,34,8,2,89,124,15739
+1734,2004,14,3,0,87,130,12865
+1735,2000,25,2,2,90,126,12981
+1736,2003,23,4,3,84,128,13434
+1737,2013,17,8,2,85,124,13664
+1738,2009,28,4,4,85,120,13567
+1739,2003,30,9,1,88,122,14882
+1740,2005,14,3,3,81,122,12441
+1741,2003,38,9,7,87,122,16243
+1742,2001,25,1,4,88,130,13526
+1743,2011,37,3,10,85,129,15097
+1744,2004,12,4,4,90,122,12650
+1745,2000,3,6,5,88,128,13457
+1746,2000,11,2,2,81,122,12410
+1747,2000,12,9,0,86,130,14024
+1748,2018,23,5,0,90,130,13987
+1749,2005,0,0,2,86,124,12126
+1750,2005,19,8,7,83,123,14471
+1751,2017,16,0,3,81,128,13030
+1752,2017,30,0,6,85,122,13432
+1753,2009,27,8,6,81,124,14822
+1754,2010,4,10,4,89,127,14219
+1755,2018,28,3,5,88,121,14232
+1756,2015,0,6,4,87,126,13780
+1757,2011,2,2,6,89,122,12300
+1758,2004,17,0,3,81,124,12237
+1759,2017,0,4,4,89,129,12893
+1760,2014,20,2,4,83,122,13409
+1761,2010,27,3,8,90,120,14021
+1762,2001,23,4,7,83,125,14232
+1763,2010,4,2,2,86,130,12551
+1764,2013,26,1,1,81,124,13436
+1765,2003,17,9,7,88,123,14343
+1766,2002,31,9,8,89,127,15591
+1767,2015,17,8,7,83,126,14177
+1768,2013,31,5,8,80,122,15095
+1769,2006,23,6,0,80,121,14164
+1770,2003,0,0,0,86,126,11902
+1771,2016,25,0,8,86,125,13436
+1772,2013,1,0,7,86,122,12172
+1773,2005,19,1,1,85,122,12208
+1774,2013,10,3,3,82,126,12214
+1775,2014,31,9,9,84,130,15693
+1776,2007,13,0,9,86,124,12763
+1777,2009,21,4,10,89,129,14602
+1778,2000,24,5,8,86,127,14829
+1779,2004,5,10,8,88,126,14783
+1780,2005,29,7,0,88,120,14952
+1781,2007,9,4,9,80,129,13921
+1782,2016,20,1,0,83,128,12168
+1783,2007,23,1,4,85,124,13753
+1784,2013,11,6,10,88,128,13902
+1785,2013,5,9,7,80,121,14618
+1786,2017,24,7,2,87,123,14517
+1787,2012,26,1,3,81,127,12666
+1788,2010,21,3,6,90,127,13312
+1789,2011,35,7,6,81,127,15526
+1790,2013,28,2,2,90,120,12974
+1791,2015,35,3,0,87,121,14907
+1792,2001,35,6,0,84,125,14967
+1793,2018,31,5,10,86,120,14861
+1794,2006,11,3,3,81,122,12443
+1795,2014,15,10,6,85,121,15071
+1796,2016,21,4,5,88,123,13089
+1797,2015,12,9,1,85,127,13749
+1798,2005,34,2,0,84,122,14177
+1799,2011,34,10,1,90,124,15868
+1800,2010,36,8,1,85,129,15102
+1801,2018,1,1,9,85,120,12482
+1802,2011,17,0,1,80,123,12918
+1803,2009,32,0,2,89,121,13493
+1804,2007,6,5,0,90,123,12590
+1805,2011,35,9,4,84,121,15084
+1806,2018,6,9,6,89,127,13944
+1807,2000,20,0,0,86,127,12148
+1808,2017,37,2,9,89,125,14114
+1809,2013,34,7,2,88,123,14884
+1810,2006,18,0,3,90,129,11995
+1811,2014,32,8,5,82,123,15182
+1812,2006,5,9,6,87,122,13565
+1813,2011,13,3,8,87,124,13221
+1814,2014,1,2,10,86,130,12524
+1815,2002,30,8,3,87,124,14514
+1816,2004,18,6,8,87,124,13932
+1817,2002,3,1,7,82,129,11751
+1818,2007,32,3,8,82,124,14373
+1819,2012,27,7,3,90,128,14288
+1820,2001,9,1,4,82,121,12236
+1821,2008,9,9,5,88,120,14781
+1822,2017,0,1,2,83,125,11496
+1823,2016,9,0,5,84,128,12461
+1824,2005,24,7,0,84,121,13827
+1825,2004,3,7,10,85,126,14292
+1826,2015,6,8,2,82,128,13357
+1827,2015,23,5,9,81,126,14732
+1828,2001,28,5,10,84,125,14311
+1829,2008,13,5,6,89,121,13012
+1830,2009,2,0,4,90,126,11939
+1831,2003,6,10,4,80,120,14030
+1832,2001,22,9,3,85,130,14064
+1833,2001,11,3,5,90,120,12300
+1834,2012,30,5,8,89,127,14076
+1835,2003,33,0,0,82,121,13663
+1836,2018,34,2,10,82,123,14990
+1837,2003,16,8,4,83,128,13676
+1838,2017,1,6,5,82,124,12689
+1839,2011,18,5,2,89,128,13741
+1840,2013,28,8,4,82,121,14804
+1841,2011,25,9,1,85,126,14943
+1842,2015,5,1,1,88,123,12573
+1843,2003,38,0,0,83,130,14037
+1844,2006,20,6,2,80,124,13845
+1845,2015,1,0,2,88,127,11718
+1846,2015,16,7,7,81,121,13496
+1847,2007,22,1,5,85,130,13648
+1848,2008,26,3,5,86,124,13414
+1849,2012,14,5,3,81,121,13643
+1850,2010,19,4,5,80,122,13023
+1851,2013,29,0,9,89,121,13752
+1852,2009,11,10,3,86,130,14523
+1853,2013,9,10,0,86,128,14558
+1854,2018,13,10,8,81,123,14208
+1855,2001,10,1,7,83,120,12422
+1856,2004,21,5,0,81,122,13451
+1857,2014,36,3,2,82,127,14847
+1858,2001,0,5,5,87,126,13550
+1859,2014,13,3,5,90,120,13457
+1860,2002,38,3,10,88,130,14788
+1861,2014,25,3,10,80,127,14368
+1862,2011,10,5,0,80,128,12850
+1863,2012,25,7,3,88,126,14505
+1864,2018,1,6,8,84,123,13479
+1865,2016,1,2,10,82,124,12480
+1866,2008,25,0,1,88,130,12958
+1867,2006,21,9,3,90,128,14672
+1868,2008,4,8,1,80,120,13665
+1869,2012,29,1,3,83,123,13503
+1870,2015,10,8,8,84,124,14536
+1871,2013,18,4,3,80,124,13650
+1872,2012,6,8,2,90,120,14093
+1873,2013,19,3,8,85,120,13877
+1874,2001,21,3,1,86,122,13473
+1875,2017,30,1,9,87,120,14034
+1876,2009,38,2,7,89,120,14543
+1877,2009,28,2,3,90,128,14309
+1878,2001,26,10,7,89,130,14767
+1879,2010,1,10,7,88,122,14645
+1880,2014,1,2,1,84,129,11806
+1881,2015,6,2,2,85,130,12753
+1882,2005,34,10,2,90,127,15149
+1883,2015,18,9,4,81,120,14254
+1884,2009,19,10,1,84,122,14626
+1885,2002,35,10,3,80,125,15336
+1886,2015,7,10,4,88,122,14424
+1887,2007,37,1,0,85,125,14147
+1888,2018,34,2,3,85,127,14803
+1889,2007,2,7,5,86,122,14142
+1890,2003,9,2,5,86,129,13067
+1891,2009,30,4,6,83,128,13980
+1892,2007,28,7,5,81,129,15404
+1893,2002,28,9,2,83,130,14795
+1894,2006,36,6,8,81,127,14721
+1895,2005,13,0,7,83,125,12014
+1896,2009,31,0,4,84,124,13377
+1897,2005,2,5,9,84,129,13811
+1898,2012,21,2,9,90,120,13354
+1899,2014,19,10,5,84,124,14862
+1900,2013,28,2,1,81,130,13439
+1901,2011,20,6,2,87,121,14141
+1902,2010,19,4,6,84,130,13264
+1903,2011,30,6,10,81,127,15224
+1904,2002,17,5,4,80,126,13560
+1905,2016,35,5,8,89,121,15234
+1906,2008,18,9,4,86,130,14804
+1907,2003,4,5,0,85,130,13032
+1908,2006,20,2,4,86,121,13757
+1909,2012,1,9,10,80,127,14574
+1910,2003,29,9,5,86,125,14760
+1911,2011,3,4,4,89,127,12789
+1912,2016,13,3,3,82,129,12999
+1913,2004,1,9,7,88,122,13892
+1914,2005,4,2,10,89,124,12781
+1915,2005,7,1,6,80,122,12661
+1916,2011,14,5,9,85,126,13355
+1917,2012,37,3,1,86,124,14125
+1918,2016,16,8,7,83,120,14224
+1919,2014,28,6,7,83,120,14152
+1920,2007,16,6,7,84,130,14190
+1921,2008,17,10,5,82,128,14611
+1922,2009,35,3,9,82,129,14086
+1923,2001,6,9,1,84,127,14214
+1924,2016,37,8,10,85,130,15805
+1925,2002,3,8,7,90,121,14344
+1926,2014,28,2,5,81,128,13255
+1927,2016,35,9,5,84,124,16183
+1928,2007,10,0,5,90,128,12987
+1929,2008,32,1,5,86,122,14459
+1930,2015,5,8,5,82,124,13959
+1931,2010,33,10,10,82,121,15794
+1932,2003,9,0,4,87,123,11955
+1933,2007,15,2,7,82,125,13145
+1934,2003,22,5,7,88,122,14396
+1935,2009,37,7,8,85,129,15071
+1936,2006,36,3,0,88,124,13964
+1937,2011,32,4,6,86,122,14383
+1938,2017,10,5,9,86,122,13578
+1939,2016,28,9,2,82,124,15456
+1940,2012,32,2,4,85,120,14490
+1941,2011,10,2,0,84,125,12358
+1942,2002,23,6,0,88,120,13422
+1943,2011,11,3,10,80,125,12956
+1944,2012,23,9,0,81,123,15233
+1945,2015,36,1,5,84,121,13689
+1946,2006,28,0,5,82,128,13446
+1947,2016,10,9,1,86,123,13657
+1948,2004,19,7,0,80,122,14510
+1949,2001,31,6,9,85,120,15310
+1950,2006,5,10,6,81,122,13754
+1951,2008,38,10,6,86,128,16340
+1952,2007,3,8,10,84,120,14483
+1953,2003,19,1,3,86,124,12818
+1954,2003,32,5,6,82,129,15075
+1955,2003,15,6,1,88,126,13567
+1956,2017,36,10,6,80,123,16143
+1957,2004,13,8,7,87,120,14043
+1958,2001,19,0,1,88,123,12512
+1959,2006,8,1,7,89,129,12455
+1960,2001,4,1,2,85,122,12253
+1961,2006,22,1,0,82,129,12994
+1962,2008,3,5,1,84,130,13581
+1963,2012,22,6,5,90,126,14836
+1964,2013,27,7,1,80,123,14871
+1965,2009,15,3,0,82,127,13399
+1966,2013,13,3,7,82,120,13764
+1967,2008,6,8,3,81,122,14341
+1968,2005,20,9,3,85,124,15064
+1969,2012,24,5,2,86,130,14606
+1970,2008,33,8,0,85,122,15624
+1971,2002,37,0,7,84,122,14753
+1972,2001,31,9,4,89,120,15599
+1973,2003,35,6,3,89,130,14928
+1974,2005,32,0,8,89,126,13297
+1975,2010,25,3,8,82,123,13480
+1976,2001,35,10,6,85,120,16360
+1977,2004,37,8,5,85,125,16349
+1978,2002,35,1,3,86,127,13352
+1979,2005,5,1,7,90,127,12225
+1980,2006,34,6,6,90,121,14583
+1981,2017,20,2,2,86,127,13241
+1982,2005,38,0,9,89,125,15003
+1983,2017,21,9,9,87,130,15149
+1984,2017,3,8,0,83,120,14154
+1985,2000,4,6,8,87,122,13845
+1986,2011,1,8,8,85,126,14398
+1987,2009,17,8,7,82,127,14652
+1988,2008,11,5,0,88,127,13664
+1989,2012,27,8,3,85,130,14867
+1990,2000,14,0,4,88,130,12945
+1991,2006,20,8,7,90,123,14568
+1992,2005,31,4,3,85,129,14282
+1993,2001,2,10,2,88,121,14114
+1994,2003,19,1,8,85,129,13343
+1995,2003,19,1,10,83,130,13565
+1996,2001,22,6,10,83,129,13879
+1997,2016,11,1,4,85,128,12567
+1998,2011,12,7,1,88,124,14303
+1999,2003,9,10,3,85,120,14230
+2000,2015,2,0,2,87,127,11860
+2001,2018,31,2,10,86,120,14492
+2002,2002,19,9,4,88,123,14296
+2003,2009,29,5,7,80,127,14141
+2004,2012,17,4,10,84,124,13836
+2005,2006,37,10,5,81,121,15997
+2006,2005,31,5,8,86,125,15102
+2007,2000,25,3,3,84,121,14061
+2008,2005,32,4,8,89,124,14983
+2009,2012,13,5,3,83,123,12737
+2010,2006,28,9,3,85,125,14469
+2011,2006,12,2,2,87,124,12774
+2012,2007,20,2,5,80,125,13552
+2013,2002,10,6,10,90,127,14316
+2014,2007,4,10,2,82,120,14660
+2015,2012,13,9,5,82,124,14323
+2016,2014,8,6,10,82,123,13486
+2017,2010,1,8,8,83,120,13593
+2018,2003,16,3,4,90,124,12507
+2019,2010,19,10,10,84,130,15126
+2020,2002,2,10,1,82,122,13918
+2021,2003,24,8,0,89,121,13805
+2022,2016,38,8,5,87,121,15860
+2023,2001,23,4,0,89,124,13276
+2024,2016,36,2,6,84,120,14319
+2025,2012,3,6,7,83,122,13054
+2026,2011,33,9,5,87,120,15727
+2027,2016,3,10,8,87,123,15022
+2028,2006,10,7,4,85,126,14092
+2029,2007,34,5,0,88,126,14346
+2030,2017,37,4,3,87,122,14199
+2031,2015,22,8,8,86,125,14144
+2032,2007,38,3,2,89,120,14740
+2033,2014,32,7,9,85,122,15050
+2034,2007,11,7,2,84,129,13166
+2035,2009,32,8,6,87,120,15341
+2036,2000,17,7,8,84,129,13959
+2037,2017,0,8,5,88,129,13786
+2038,2012,20,4,5,86,128,13658
+2039,2014,1,7,8,82,123,14292
+2040,2017,13,2,5,90,122,12774
+2041,2003,25,0,2,80,126,13425
+2042,2005,22,9,6,89,130,14884
+2043,2014,6,5,1,90,121,13546
+2044,2003,6,4,4,80,122,13009
+2045,2006,36,7,3,81,130,15079
+2046,2013,35,4,2,84,130,14987
+2047,2005,38,5,2,84,128,14788
+2048,2017,9,8,9,87,123,14191
+2049,2017,2,0,9,87,125,12587
+2050,2008,12,1,10,83,120,12561
+2051,2010,35,3,10,84,124,14375
+2052,2013,24,7,0,83,121,14744
+2053,2007,37,5,8,83,125,15487
+2054,2011,15,0,7,82,125,12761
+2055,2011,5,6,8,90,122,14194
+2056,2018,4,6,4,81,121,12818
+2057,2013,24,7,9,80,120,14921
+2058,2016,9,0,9,81,122,12234
+2059,2005,34,0,1,84,125,13084
+2060,2013,8,1,4,87,124,12050
+2061,2007,7,9,1,89,126,13791
+2062,2000,32,1,5,88,128,13959
+2063,2008,1,3,2,90,126,12548
+2064,2014,6,3,3,80,129,13098
+2065,2007,24,4,0,82,122,13703
+2066,2015,32,2,5,83,122,13800
+2067,2018,1,9,4,83,124,14554
+2068,2007,30,1,8,87,127,13847
+2069,2010,2,0,1,85,129,12416
+2070,2017,16,7,9,85,121,14382
+2071,2007,17,10,3,82,125,14489
+2072,2002,14,1,5,83,123,12512
+2073,2004,5,2,6,85,127,12978
+2074,2007,29,10,0,82,125,14603
+2075,2001,34,8,3,85,127,15726
+2076,2000,32,5,2,90,126,14127
+2077,2008,20,10,4,83,127,15103
+2078,2000,33,8,8,90,129,16174
+2079,2003,2,1,4,84,129,11719
+2080,2004,19,1,4,80,128,12488
+2081,2002,3,8,10,90,126,13387
+2082,2017,4,4,0,85,121,13221
+2083,2007,4,1,6,88,124,12509
+2084,2003,33,6,8,83,127,15715
+2085,2000,31,0,3,89,120,12907
+2086,2016,1,9,0,82,120,13561
+2087,2018,5,0,4,88,123,12789
+2088,2002,36,8,6,82,124,16151
+2089,2000,38,7,9,89,126,15298
+2090,2005,8,8,3,88,122,14173
+2091,2010,33,2,0,86,120,13486
+2092,2006,12,3,7,83,126,13094
+2093,2007,26,6,0,88,126,13933
+2094,2013,4,4,1,88,126,12160
+2095,2001,3,4,7,90,128,13152
+2096,2013,16,8,4,88,120,14210
+2097,2016,24,3,5,85,130,14229
+2098,2013,24,10,3,84,130,14592
+2099,2005,18,8,9,80,123,14501
+2100,2000,0,2,6,89,125,12726
+2101,2015,31,3,8,85,124,13843
+2102,2011,27,0,7,83,122,13469
+2103,2010,20,5,4,89,120,14407
+2104,2018,10,2,4,80,128,12086
+2105,2000,13,0,0,88,128,11681
+2106,2004,8,0,5,82,124,12081
+2107,2016,9,0,3,82,130,12740
+2108,2004,22,4,6,83,130,13658
+2109,2003,28,2,0,89,128,14124
+2110,2018,37,7,10,83,121,16044
+2111,2007,1,6,4,83,123,13471
+2112,2003,21,6,9,82,125,14507
+2113,2014,29,8,4,82,124,14648
+2114,2002,2,4,3,86,129,12541
+2115,2002,3,1,9,85,130,11998
+2116,2012,27,5,2,81,126,13758
+2117,2006,37,6,3,81,126,14808
+2118,2002,36,7,9,85,125,15855
+2119,2004,15,9,5,80,124,14995
+2120,2018,25,0,7,86,122,13631
+2121,2012,34,6,2,85,125,15544
+2122,2010,0,4,6,81,120,13120
+2123,2016,4,5,0,85,122,13430
+2124,2009,11,9,10,90,120,13988
+2125,2012,31,8,1,83,129,15055
+2126,2006,0,9,1,81,127,13450
+2127,2003,27,2,2,80,127,13218
+2128,2018,31,6,7,85,124,14309
+2129,2009,9,10,10,90,129,14433
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+2131,2012,27,1,9,80,120,12993
+2132,2015,13,0,0,90,120,12099
+2133,2004,3,7,3,87,129,13590
+2134,2001,28,1,0,90,126,13023
+2135,2017,7,1,2,85,130,12969
+2136,2008,27,3,0,90,123,13250
+2137,2006,34,8,4,82,124,15265
+2138,2003,7,6,2,86,121,13007
+2139,2005,11,3,5,88,130,12618
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+2143,2013,8,7,4,88,124,13429
+2144,2013,33,0,7,86,130,13503
+2145,2008,11,8,1,90,125,13848
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+2151,2006,8,5,5,90,125,12910
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+2156,2013,34,10,3,89,130,15251
+2157,2000,17,4,8,80,125,13410
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+2159,2010,2,3,6,85,124,12743
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+2161,2016,3,9,1,82,130,14467
+2162,2018,29,5,2,83,128,14083
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+2168,2007,37,5,5,89,120,14583
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+2177,2010,19,1,6,82,120,13087
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+2191,2017,11,3,7,81,122,12446
+2192,2010,15,6,0,88,129,12938
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+2198,2018,0,9,9,80,127,14157
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+2200,2001,27,7,2,88,121,15016
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+2209,2018,28,10,5,89,127,15761
+2210,2000,1,8,0,90,121,13940
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+2214,2009,20,7,6,84,128,13938
+2215,2004,33,3,3,80,125,13557
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+2217,2017,29,3,10,90,127,13839
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+2219,2010,4,3,7,81,130,13107
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+2223,2006,36,1,10,88,127,14199
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+2227,2000,17,9,1,81,125,14382
+2228,2011,33,1,2,87,124,14171
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+2231,2010,9,1,10,82,130,12883
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+2238,2017,16,7,6,84,125,13493
+2239,2015,14,8,5,82,122,13903
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+2250,2009,27,7,1,89,126,14157
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+2260,2018,28,2,1,90,129,13125
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+2279,2014,33,7,2,84,123,14406
+2280,2002,35,0,3,83,130,14035
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+2291,2004,32,9,9,83,124,15181
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+2300,2018,4,3,5,84,123,13275
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+2315,2001,27,9,5,82,120,15436
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+2328,2002,0,5,5,84,122,12509
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+2330,2016,5,8,3,80,127,13493
+2331,2011,22,5,9,86,123,14280
+2332,2008,38,0,4,84,128,14256
+2333,2011,17,3,2,83,120,13701
+2334,2007,30,4,3,86,123,13681
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+2336,2017,30,6,10,84,123,14365
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+2339,2006,6,4,9,83,120,12648
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+2343,2010,23,1,6,82,123,13092
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+2346,2018,13,8,3,87,130,14473
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+2355,2014,25,0,4,89,130,12765
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+2359,2010,3,1,4,86,130,12549
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+2364,2018,33,9,3,84,122,15910
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+2367,2005,28,5,8,83,123,14467
+2368,2018,6,9,0,90,122,13243
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+2382,2018,7,2,2,85,125,13149
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+2398,2013,35,3,0,90,125,13800
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+2400,2015,15,1,9,82,124,13202
+2401,2014,25,1,2,85,123,12807
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+2410,2005,29,4,0,86,126,14091
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+2412,2006,30,0,9,82,121,13255
+2413,2016,31,8,9,80,121,16046
+2414,2012,38,9,7,80,129,15914
+2415,2016,16,3,9,89,129,13979
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+2417,2017,6,3,10,89,126,12484
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+2419,2004,25,1,5,80,121,13753
+2420,2006,28,9,8,81,125,14825
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+2422,2003,13,8,7,86,124,14307
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+2428,2000,27,0,10,84,123,13953
+2429,2000,32,3,3,84,124,13972
+2430,2017,4,1,5,88,122,12624
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+2432,2011,4,10,6,90,130,14220
+2433,2010,29,6,0,89,123,14912
+2434,2009,34,9,8,80,127,15956
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+2443,2012,32,9,1,88,125,15356
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+2455,2000,28,9,2,84,122,15375
+2456,2018,8,2,10,84,128,12586
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+2466,2002,36,3,8,80,128,15083
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+2477,2015,26,7,0,88,128,14072
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+2486,2007,27,2,4,90,123,13870
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+2492,2004,34,4,2,87,127,14979
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+2494,2003,17,10,7,89,126,15214
+2495,2018,8,9,4,86,128,14403
+2496,2004,2,0,1,89,130,11782
+2497,2002,16,2,8,82,129,13745
+2498,2001,27,9,2,80,127,15063
+2499,2018,9,9,0,85,121,13942
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+2501,2004,15,3,2,86,124,13099
+2502,2000,32,0,3,85,129,12892
+2503,2014,35,8,10,87,126,15350
+2504,2016,19,5,5,85,128,14455
+2505,2015,18,1,10,80,127,13790
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+2507,2018,17,5,2,89,120,14056
+2508,2007,27,8,9,82,121,15455
+2509,2007,0,6,9,85,124,14095
+2510,2013,28,10,1,84,124,14864
+2511,2011,38,3,3,88,128,14724
+2512,2009,25,7,8,87,125,14225
+2513,2014,25,3,1,90,130,13229
+2514,2018,24,10,1,90,128,15544
+2515,2016,25,2,9,84,129,14280
+2516,2002,2,10,7,83,130,14898
+2517,2003,30,4,4,86,121,14330
+2518,2012,25,6,3,89,125,13913
+2519,2006,17,10,9,82,129,14428
+2520,2004,26,3,7,82,121,13332
+2521,2011,18,9,5,80,129,14707
+2522,2011,16,4,10,83,129,13047
+2523,2010,34,2,9,86,130,13825
+2524,2003,33,8,9,82,130,15449
+2525,2009,36,1,5,84,122,14546
+2526,2007,9,10,7,90,121,14229
+2527,2013,36,6,2,90,122,15355
+2528,2004,20,0,3,84,129,12571
+2529,2012,8,2,10,85,122,12905
+2530,2014,5,0,7,86,122,12903
+2531,2013,18,2,3,81,129,12767
+2532,2004,28,10,2,88,130,15679
+2533,2005,11,9,10,87,123,14600
+2534,2006,38,10,1,80,129,16433
+2535,2001,3,8,0,82,127,13856
+2536,2013,3,5,2,80,122,12331
+2537,2011,6,9,0,82,121,13541
+2538,2014,12,2,1,90,123,12648
+2539,2005,23,10,5,84,125,14559
+2540,2001,16,5,1,89,126,13526
+2541,2014,18,1,10,84,121,13016
+2542,2008,1,4,5,83,120,12711
+2543,2001,25,7,8,85,130,15337
+2544,2004,18,6,9,87,126,13867
+2545,2012,4,3,4,88,130,12372
+2546,2004,14,10,0,87,120,14804
+2547,2015,21,10,5,85,120,15596
+2548,2010,0,6,2,88,123,12510
+2549,2004,5,4,6,84,128,12383
+2550,2017,8,4,2,89,123,13220
+2551,2013,2,4,10,83,122,13522
+2552,2012,28,10,10,83,122,15041
+2553,2001,0,3,6,82,123,12134
+2554,2006,22,10,7,81,127,15605
+2555,2018,33,8,0,87,130,14973
+2556,2012,12,0,7,89,123,12781
+2557,2003,16,4,2,83,122,12820
+2558,2000,26,3,3,86,130,13938
+2559,2009,11,8,2,89,121,13372
+2560,2001,14,7,5,82,127,13520
+2561,2003,29,9,5,89,129,14671
+2562,2001,2,5,9,88,123,13274
+2563,2011,27,8,0,84,125,15057
+2564,2002,37,8,9,88,128,16319
+2565,2008,12,6,10,86,123,14510
+2566,2016,25,5,10,90,123,13814
+2567,2004,35,8,5,90,121,14912
+2568,2009,18,7,10,83,125,14508
+2569,2017,17,9,4,85,120,13853
+2570,2012,18,2,10,86,128,13510
+2571,2009,23,2,9,88,123,13722
+2572,2018,18,4,2,88,123,14038
+2573,2004,0,1,10,81,120,13053
+2574,2011,35,10,10,89,126,16285
+2575,2007,27,0,2,88,129,13515
+2576,2007,15,0,7,83,129,13272
+2577,2016,7,0,3,87,124,12411
+2578,2008,21,6,6,82,130,13906
+2579,2009,32,7,6,81,121,15102
+2580,2005,29,5,3,88,120,14426
+2581,2018,6,2,0,89,130,11806
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+2584,2012,16,5,0,90,128,13925
+2585,2002,33,10,6,83,127,16096
+2586,2001,20,9,10,90,123,14658
+2587,2004,14,6,4,80,124,13497
+2588,2007,23,9,10,85,127,15624
+2589,2003,8,10,4,84,120,13988
+2590,2006,9,2,4,88,124,12384
+2591,2009,28,7,1,86,124,14707
+2592,2015,35,9,0,83,126,16060
+2593,2013,18,9,3,82,128,14622
+2594,2013,26,4,1,84,130,14226
+2595,2017,9,4,10,82,127,13390
+2596,2012,32,1,3,89,130,14061
+2597,2016,37,8,10,86,126,16544
+2598,2005,27,3,1,89,122,13526
+2599,2010,12,1,4,88,129,12346
+2600,2005,28,6,8,89,121,15327
+2601,2006,16,10,5,84,130,14823
+2602,2015,13,5,8,86,125,13532
+2603,2005,25,8,1,86,120,15045
+2604,2015,28,9,4,86,129,14969
+2605,2015,10,4,2,85,126,12648
+2606,2012,0,9,4,81,128,14518
+2607,2015,36,3,7,84,126,15232
+2608,2008,0,1,2,86,122,12331
+2609,2013,13,5,10,80,130,13620
+2610,2016,1,1,5,80,127,12286
+2611,2017,38,7,7,83,125,15122
+2612,2006,32,2,2,83,124,14120
+2613,2005,14,0,9,83,120,12509
+2614,2013,28,1,10,87,120,13408
+2615,2007,9,6,4,84,122,13568
+2616,2002,15,2,1,90,126,12740
+2617,2007,4,9,7,82,120,13557
+2618,2017,30,1,5,87,129,13380
+2619,2004,22,6,7,86,126,13742
+2620,2014,36,6,3,88,129,14935
+2621,2011,3,9,3,83,127,14404
+2622,2011,14,5,2,86,127,13898
+2623,2010,29,7,9,81,129,14812
+2624,2008,5,7,1,82,121,13493
+2625,2000,9,2,3,84,122,13155
+2626,2013,8,0,10,90,130,12828
+2627,2016,8,3,5,88,129,12556
+2628,2018,2,1,1,85,120,12229
+2629,2010,21,1,0,85,122,12551
+2630,2001,13,10,4,86,127,14978
+2631,2013,20,0,6,83,125,13369
+2632,2018,30,0,6,87,130,14122
+2633,2009,22,4,5,80,123,13579
+2634,2007,12,9,9,84,127,14482
+2635,2006,18,2,9,85,129,13430
+2636,2013,20,5,1,86,126,13409
+2637,2002,36,1,1,87,130,13867
+2638,2007,6,0,0,81,128,12430
+2639,2017,21,4,7,90,129,13615
+2640,2012,4,10,5,88,127,14652
+2641,2013,10,4,4,86,121,13598
+2642,2010,16,6,9,81,126,14393
+2643,2018,33,7,3,82,127,15496
+2644,2017,32,7,8,81,120,15740
+2645,2013,16,6,0,82,121,13432
+2646,2004,10,8,0,82,121,13551
+2647,2007,28,10,5,86,125,14924
+2648,2014,29,8,5,82,126,14710
+2649,2015,4,6,4,83,121,12813
+2650,2013,25,7,0,86,130,14246
+2651,2012,34,9,4,86,123,15401
+2652,2001,25,5,10,89,123,14112
+2653,2018,10,4,0,83,121,13408
+2654,2014,5,2,5,84,130,12612
+2655,2018,14,10,0,88,127,14540
+2656,2001,19,0,9,85,124,13532
+2657,2017,20,3,5,81,124,13680
+2658,2015,13,5,4,90,126,13357
+2659,2000,11,10,4,89,130,14039
+2660,2017,22,10,0,86,127,15209
+2661,2001,33,6,2,81,122,14485
+2662,2017,33,6,1,81,128,15305
+2663,2007,9,3,7,85,122,12844
+2664,2006,13,8,2,85,122,14182
+2665,2004,3,2,4,90,130,12868
+2666,2008,12,0,2,87,122,12369
+2667,2010,4,5,10,82,120,14000
+2668,2005,26,4,6,83,123,14014
+2669,2004,8,6,10,89,128,13499
+2670,2004,37,0,3,80,125,14056
+2671,2016,24,10,10,82,128,14936
+2672,2008,14,0,0,89,128,12149
+2673,2018,3,5,5,84,124,12537
+2674,2000,9,2,4,86,123,12213
+2675,2018,30,1,9,80,129,13424
+2676,2003,10,3,2,81,122,12465
+2677,2004,28,9,7,88,124,15424
+2678,2009,22,3,4,83,129,14000
+2679,2018,30,5,9,90,126,14659
+2680,2007,0,3,3,81,120,12748
+2681,2009,2,3,2,80,121,13001
+2682,2012,14,5,6,83,128,13968
+2683,2012,24,4,7,83,128,13361
+2684,2005,5,10,3,82,124,13489
+2685,2000,10,1,4,90,124,12954
+2686,2002,29,7,2,89,126,14320
+2687,2014,33,5,7,84,128,15142
+2688,2015,36,2,3,85,125,13819
+2689,2016,14,8,0,82,120,14151
+2690,2011,4,10,1,80,127,13525
+2691,2018,17,6,9,82,125,13476
+2692,2016,1,3,0,82,124,12185
+2693,2003,19,2,10,80,126,13857
+2694,2000,23,9,3,85,122,14455
+2695,2017,9,5,6,83,120,13239
+2696,2015,10,2,9,88,122,12957
+2697,2002,14,5,1,88,130,13326
+2698,2016,37,8,5,81,123,16000
+2699,2018,16,9,5,83,121,15113
+2700,2002,38,1,10,83,124,14321
+2701,2009,10,8,0,83,127,13866
+2702,2018,10,8,6,83,123,14441
+2703,2017,24,7,2,90,122,14778
+2704,2000,4,7,5,86,121,13772
+2705,2002,6,5,9,88,124,12884
+2706,2007,19,5,0,88,130,13556
+2707,2000,37,10,7,86,130,16520
+2708,2007,9,3,6,81,128,13312
+2709,2008,37,1,7,85,123,14491
+2710,2018,35,7,0,84,125,15769
+2711,2015,17,6,5,83,121,14126
+2712,2005,7,9,1,81,122,14096
+2713,2008,30,8,2,83,121,15340
+2714,2015,16,0,3,84,124,13012
+2715,2012,35,3,7,84,120,14843
+2716,2007,12,4,6,82,122,12725
+2717,2002,37,7,1,81,122,15887
+2718,2018,33,7,4,81,129,14796
+2719,2004,33,4,8,85,128,14938
+2720,2012,16,9,4,81,124,14283
+2721,2016,18,0,10,80,120,13177
+2722,2008,26,4,4,90,126,13980
+2723,2014,25,2,7,86,130,13682
+2724,2006,8,2,4,90,122,12474
+2725,2000,14,4,10,86,121,14001
+2726,2006,17,9,2,89,121,14102
+2727,2011,37,0,3,85,122,14225
+2728,2007,3,5,0,85,128,12386
+2729,2000,10,2,2,85,120,12632
+2730,2004,8,9,2,84,129,14480
+2731,2004,16,10,0,82,123,14136
+2732,2003,12,2,6,80,130,12706
+2733,2000,31,2,9,90,122,14509
+2734,2001,21,9,4,83,129,14289
+2735,2000,36,1,7,87,126,14639
+2736,2001,7,4,2,83,130,12360
+2737,2016,9,6,3,83,120,13799
+2738,2016,22,9,9,89,120,14781
+2739,2001,13,10,10,83,127,15263
+2740,2009,31,10,0,89,124,15176
+2741,2001,18,7,0,86,128,13370
+2742,2005,36,6,5,80,123,14539
+2743,2014,38,8,1,83,126,16161
+2744,2017,13,10,7,82,121,14651
+2745,2012,6,2,0,87,122,12351
+2746,2005,17,2,10,88,125,12785
+2747,2002,36,9,1,82,130,16152
+2748,2009,24,0,8,87,121,13569
+2749,2003,12,6,9,83,125,13423
+2750,2001,23,5,5,83,122,13820
+2751,2007,32,9,3,86,121,15777
+2752,2004,34,5,9,86,130,15550
+2753,2018,0,10,2,80,123,14256
+2754,2016,16,9,2,87,126,14875
+2755,2004,17,9,5,87,128,14271
+2756,2000,6,9,1,90,121,14332
+2757,2015,11,1,0,84,120,11682
+2758,2004,27,4,8,88,126,14725
+2759,2006,2,3,2,81,123,12372
+2760,2016,18,7,6,83,130,14119
+2761,2018,19,5,10,86,121,14681
+2762,2015,2,5,5,81,120,13092
+2763,2001,18,10,9,86,121,14936
+2764,2002,7,5,5,85,129,12728
+2765,2003,27,7,2,82,125,13884
+2766,2005,36,2,5,86,126,14636
+2767,2004,20,1,3,80,129,12626
+2768,2009,29,6,2,80,123,14710
+2769,2010,37,5,1,84,124,14395
+2770,2010,29,3,8,84,125,14545
+2771,2003,13,4,0,84,126,13111
+2772,2004,22,8,5,84,129,14455
+2773,2004,24,2,3,90,130,13889
+2774,2003,14,10,5,88,120,14676
+2775,2009,24,8,4,88,124,14550
+2776,2000,2,8,9,88,128,14440
+2777,2011,21,2,5,90,130,12827
+2778,2002,6,7,5,83,127,14234
+2779,2004,17,9,7,90,126,14248
+2780,2010,4,5,7,87,129,13547
+2781,2014,19,7,4,81,129,14174
+2782,2017,1,7,8,89,123,13712
+2783,2007,19,1,2,80,122,12621
+2784,2009,34,0,4,84,123,13243
+2785,2008,17,4,7,83,125,13415
+2786,2004,2,2,10,80,129,13089
+2787,2001,26,4,3,80,123,13199
+2788,2004,9,6,1,90,123,13691
+2789,2002,37,8,2,85,127,15192
+2790,2007,7,10,8,89,124,14852
+2791,2004,18,0,8,86,129,13223
+2792,2018,26,1,4,85,125,13511
+2793,2013,26,7,0,90,129,13951
+2794,2006,2,6,8,90,123,13596
+2795,2011,1,3,4,87,129,13043
+2796,2001,16,5,1,82,130,13639
+2797,2007,34,1,1,86,129,14335
+2798,2004,11,5,6,81,127,13531
+2799,2013,11,5,7,84,130,13154
+2800,2005,18,10,4,84,126,14597
+2801,2013,29,9,4,88,123,15641
+2802,2010,32,0,3,83,120,12882
+2803,2008,3,7,9,87,129,13910
+2804,2001,1,10,1,84,130,14577
+2805,2004,7,4,4,84,125,12578
+2806,2011,30,5,6,85,121,15178
+2807,2018,22,7,0,88,125,14058
+2808,2007,23,0,7,81,120,13660
+2809,2003,4,9,0,84,120,13575
+2810,2005,38,3,3,89,122,14539
+2811,2016,2,3,4,88,127,12327
+2812,2002,27,6,4,87,125,14547
+2813,2015,9,5,10,82,127,14219
+2814,2000,25,2,4,83,128,13688
+2815,2017,22,3,6,88,130,14045
+2816,2015,4,9,2,84,125,13637
+2817,2007,37,10,8,90,123,16964
+2818,2010,25,9,7,89,129,15148
+2819,2006,10,10,0,83,123,13635
+2820,2010,10,3,10,84,127,12691
+2821,2018,22,2,1,83,124,13032
+2822,2009,38,1,4,89,129,14870
+2823,2000,12,7,5,87,120,14169
+2824,2004,14,2,6,87,130,13086
+2825,2015,28,2,0,84,123,13249
+2826,2016,34,1,2,86,120,13624
+2827,2015,24,3,3,90,125,13239
+2828,2002,8,3,9,88,130,13196
+2829,2018,19,2,3,80,125,13702
+2830,2017,30,7,9,90,123,14810
+2831,2004,27,8,9,82,123,14569
+2832,2010,16,8,3,89,126,13932
+2833,2000,1,1,0,85,124,12594
+2834,2016,25,5,7,90,130,14963
+2835,2008,11,0,5,85,127,11866
+2836,2018,16,4,2,85,121,13026
+2837,2001,0,4,5,84,129,13090
+2838,2013,28,4,1,88,127,14121
+2839,2002,25,5,8,85,121,14112
+2840,2011,4,9,4,89,130,14022
+2841,2014,30,6,4,80,123,14912
+2842,2005,12,1,10,87,125,12468
+2843,2000,14,0,1,90,130,12427
+2844,2014,8,7,6,84,122,13377
+2845,2000,16,7,2,83,129,13981
+2846,2004,17,4,9,89,126,14160
+2847,2003,22,8,9,85,125,14129
+2848,2002,22,7,0,87,129,13743
+2849,2005,10,1,0,85,121,11856
+2850,2012,6,9,0,85,120,13429
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+2852,2007,27,2,0,83,126,13651
+2853,2007,14,7,1,83,121,13448
+2854,2007,38,6,1,86,123,15571
+2855,2005,38,9,0,82,124,15637
+2856,2003,35,0,3,81,124,13240
+2857,2001,12,8,10,83,120,14115
+2858,2007,5,7,10,85,122,13706
+2859,2000,18,3,9,83,125,13951
+2860,2012,16,7,5,80,124,13518
+2861,2011,4,5,5,84,121,12763
+2862,2016,3,5,5,89,123,13303
+2863,2000,1,4,3,81,123,12200
+2864,2007,8,1,3,86,128,12744
+2865,2014,25,1,9,85,128,13437
+2866,2011,36,5,2,80,128,14866
+2867,2015,20,9,6,86,120,14869
+2868,2002,33,3,8,88,127,13974
+2869,2005,38,2,2,86,120,14384
+2870,2009,4,10,4,83,126,14178
+2871,2002,20,9,7,87,130,14915
+2872,2004,15,4,1,80,130,12882
+2873,2001,13,0,9,88,130,12777
+2874,2007,23,7,7,82,123,14879
+2875,2007,20,3,6,85,120,13426
+2876,2001,4,0,9,86,123,12035
+2877,2008,8,3,0,83,122,12832
+2878,2001,7,3,10,86,121,12896
+2879,2001,21,5,6,86,129,14052
+2880,2010,26,7,8,90,124,15190
+2881,2015,38,2,8,83,123,15240
+2882,2017,18,0,3,86,126,12644
+2883,2004,3,2,5,80,121,13070
+2884,2008,1,0,6,83,124,11589
+2885,2005,27,0,5,86,128,12758
+2886,2004,20,9,1,80,129,14710
+2887,2017,35,6,1,82,121,14561
+2888,2000,21,1,8,85,130,13828
+2889,2009,11,4,4,89,120,13374
+2890,2011,12,8,1,86,126,13764
+2891,2009,32,1,3,88,124,13755
+2892,2008,0,0,3,81,128,12063
+2893,2011,27,4,4,82,129,14547
+2894,2005,18,10,4,89,124,14107
+2895,2006,19,5,9,81,129,13960
+2896,2018,31,5,5,89,129,14928
+2897,2011,22,6,3,80,126,13799
+2898,2016,27,3,9,89,124,14370
+2899,2011,33,8,8,85,123,15793
+2900,2018,29,0,5,80,127,14069
+2901,2008,26,4,1,90,127,13962
+2902,2008,6,2,10,84,126,13468
+2903,2018,14,9,9,80,121,14068
+2904,2018,36,2,4,89,128,14803
+2905,2011,3,5,10,87,121,13633
+2906,2002,20,7,6,89,130,14065
+2907,2000,36,5,1,86,128,14413
+2908,2007,26,5,7,82,130,14443
+2909,2003,23,3,6,80,125,13214
+2910,2018,36,5,7,90,120,14652
+2911,2002,38,6,7,85,127,15989
+2912,2006,6,4,4,82,128,13320
+2913,2000,6,8,5,85,127,13315
+2914,2002,34,10,8,87,124,16536
+2915,2015,4,2,0,87,124,12825
+2916,2005,8,9,8,89,123,14525
+2917,2006,12,2,3,80,122,12274
+2918,2009,5,2,0,85,122,12171
+2919,2017,17,4,1,84,120,13011
+2920,2001,29,1,8,90,127,14385
+2921,2009,25,1,8,90,128,13009
+2922,2006,15,0,6,90,121,12704
+2923,2015,23,6,7,88,122,14100
+2924,2006,30,1,6,84,130,13618
+2925,2001,36,3,5,86,123,15056
+2926,2016,38,3,6,81,128,14990
+2927,2003,38,0,1,89,129,13985
+2928,2013,8,5,9,82,120,13581
+2929,2003,2,0,8,88,126,12351
+2930,2016,12,5,7,89,129,13103
+2931,2007,26,4,8,82,122,13609
+2932,2004,24,8,8,83,127,15095
+2933,2005,31,3,0,84,128,13537
+2934,2005,16,4,10,83,129,14025
+2935,2003,12,0,2,80,128,12721
+2936,2016,11,4,3,80,126,13348
+2937,2011,17,7,1,88,127,14051
+2938,2002,33,6,9,82,130,15268
+2939,2011,35,0,5,90,127,13568
+2940,2000,21,8,8,84,128,15149
+2941,2004,22,10,10,84,125,14867
+2942,2010,22,2,5,87,120,13190
+2943,2011,31,5,4,80,123,15017
+2944,2011,0,10,4,87,120,13709
+2945,2008,33,8,0,81,121,15347
+2946,2006,20,9,0,84,120,14262
+2947,2010,28,2,9,90,126,13847
+2948,2013,4,7,4,90,127,13210
+2949,2012,20,5,3,82,125,13604
+2950,2014,17,0,8,86,122,12173
+2951,2015,7,6,2,80,125,13941
+2952,2007,19,7,4,88,123,14141
+2953,2006,2,1,10,81,127,13142
+2954,2000,2,4,0,87,120,12336
+2955,2015,9,7,6,85,127,14332
+2956,2000,28,9,0,83,130,15567
+2957,2005,30,7,10,89,126,14686
+2958,2017,31,8,8,81,128,15415
+2959,2004,20,9,0,89,121,15039
+2960,2014,2,0,0,88,129,12023
+2961,2007,24,9,7,88,120,14633
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+2963,2016,12,10,10,84,126,15295
+2964,2011,22,7,8,88,125,14045
+2965,2017,15,3,3,89,120,13459
+2966,2009,4,3,8,90,130,13323
+2967,2013,0,2,8,82,123,12341
+2968,2006,14,0,1,86,129,11927
+2969,2004,27,8,3,82,123,14143
+2970,2005,12,8,2,81,123,13490
+2971,2010,20,3,5,80,124,13892
+2972,2003,29,10,6,84,123,14882
+2973,2017,36,2,1,88,125,14626
+2974,2018,19,8,0,83,123,13808
+2975,2012,6,5,3,86,121,13238
+2976,2009,8,10,9,89,124,14189
+2977,2010,3,7,4,90,121,13137
+2978,2015,10,4,7,83,125,12631
+2979,2004,2,8,10,90,124,14245
+2980,2000,15,2,2,88,120,13366
+2981,2011,23,0,7,83,123,12573
+2982,2007,13,5,7,80,125,13790
+2983,2005,18,3,8,87,127,13201
+2984,2003,27,4,3,85,124,13562
+2985,2018,24,10,7,83,130,15190
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+2989,2001,27,1,0,85,128,13566
+2990,2008,26,9,8,80,129,15716
+2991,2018,0,9,7,83,129,14335
+2992,2000,13,4,2,82,128,12441
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+2994,2000,19,1,4,88,125,13373
+2995,2013,2,3,2,80,126,12292
+2996,2012,26,3,4,84,127,13895
+2997,2001,34,10,2,80,122,15177
+2998,2011,5,9,4,88,126,14273
+2999,2000,5,7,2,83,126,13661
+3000,2001,0,0,9,86,120,12308
+3001,2011,23,8,9,81,125,15472
+3002,2018,30,7,8,87,129,14531
+3003,2009,28,8,3,86,129,14924
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+3007,2000,6,9,8,81,120,14505
+3008,2003,19,0,3,87,123,13121
+3009,2015,32,1,3,86,127,13540
+3010,2018,37,2,6,84,125,14448
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+3016,2005,37,2,1,86,126,14401
+3017,2004,27,0,4,80,125,12656
+3018,2011,19,1,6,82,128,13011
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+3020,2002,38,8,7,87,120,15254
+3021,2000,12,7,5,88,122,14437
+3022,2006,36,7,8,82,123,15925
+3023,2002,1,3,1,81,129,12692
+3024,2004,23,5,8,83,121,13476
+3025,2012,4,0,3,87,123,12551
+3026,2009,22,7,9,88,123,14956
+3027,2005,34,6,2,89,125,14647
+3028,2014,34,2,6,84,123,13898
+3029,2018,24,4,9,86,122,14732
+3030,2018,38,1,8,86,126,14453
+3031,2007,0,3,0,86,129,12547
+3032,2008,16,6,0,90,124,14219
+3033,2001,8,2,9,90,122,12951
+3034,2016,37,10,10,84,123,16953
+3035,2014,32,1,9,89,125,14217
+3036,2005,2,5,4,86,128,13188
+3037,2010,5,9,6,82,127,13588
+3038,2003,18,1,3,85,121,12742
+3039,2003,19,7,6,88,121,14210
+3040,2010,26,6,5,90,126,14082
+3041,2008,25,4,10,80,126,13532
+3042,2009,8,6,4,85,122,13548
+3043,2009,27,10,6,83,120,15498
+3044,2012,35,6,4,88,128,15637
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+3047,2001,2,1,3,80,126,12127
+3048,2005,3,7,5,81,126,14027
+3049,2013,26,1,1,84,129,13479
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+3051,2003,2,2,4,80,122,12493
+3052,2015,0,6,3,90,123,12847
+3053,2009,31,2,2,85,122,13297
+3054,2004,15,8,7,81,120,14609
+3055,2016,28,1,3,88,124,13100
+3056,2010,1,9,5,87,126,14092
+3057,2000,36,3,2,90,129,14702
+3058,2002,23,7,0,84,122,13500
+3059,2013,9,0,8,82,128,13090
+3060,2002,31,6,2,83,130,15263
+3061,2003,33,10,6,80,121,15927
+3062,2008,26,9,2,89,123,14924
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+3064,2005,36,9,8,81,125,16358
+3065,2004,33,9,1,89,126,16040
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+3067,2008,18,6,5,90,124,14069
+3068,2008,0,4,3,86,130,12537
+3069,2008,9,4,10,83,120,13311
+3070,2008,22,8,10,84,122,15442
+3071,2015,32,10,9,80,126,16586
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+3074,2016,12,9,8,89,125,14995
+3075,2007,0,10,9,84,124,13694
+3076,2005,24,2,8,86,121,13696
+3077,2014,31,9,5,89,127,15879
+3078,2014,8,1,4,83,128,12814
+3079,2007,32,8,3,84,120,14536
+3080,2012,27,5,4,89,120,14746
+3081,2004,24,1,2,85,126,13210
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+3083,2003,17,7,0,86,123,13425
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+3085,2016,11,5,1,80,127,13462
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+3088,2013,19,10,9,81,124,14664
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+3095,2012,33,0,2,87,121,13581
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+3097,2002,37,2,1,90,121,14378
+3098,2014,20,7,5,82,127,14905
+3099,2010,28,1,0,83,129,12797
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+3102,2016,34,5,2,83,130,15371
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+3108,2010,15,6,10,84,125,14656
+3109,2009,13,1,1,83,129,12713
+3110,2003,25,5,4,90,123,13701
+3111,2008,12,5,7,84,121,13120
+3112,2003,7,0,4,90,130,12445
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+3115,2002,1,4,5,80,122,13181
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+3118,2015,36,1,2,88,123,14704
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+3123,2013,18,0,3,87,126,12754
+3124,2016,6,2,6,86,123,13050
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+3126,2006,32,10,10,83,122,16205
+3127,2010,26,0,6,83,120,13206
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+3129,2016,10,0,10,88,130,12401
+3130,2001,14,10,7,80,122,14989
+3131,2005,36,3,1,90,122,14638
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+3134,2002,31,5,7,80,124,15253
+3135,2000,31,3,0,84,123,14492
+3136,2005,0,1,10,90,126,13136
+3137,2006,37,2,1,82,123,14369
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+3140,2009,17,2,0,80,130,13427
+3141,2000,5,1,3,90,129,12389
+3142,2016,36,1,0,89,123,13858
+3143,2007,9,8,4,90,121,14399
+3144,2015,27,1,9,82,124,14300
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+3146,2005,17,6,5,89,127,13887
+3147,2005,13,5,2,84,127,13813
+3148,2012,35,8,6,80,127,15867
+3149,2000,28,3,3,80,124,13262
+3150,2015,10,1,10,82,126,13174
+3151,2011,6,2,6,86,123,12521
+3152,2000,10,4,7,90,120,12941
+3153,2014,25,8,7,89,130,14831
+3154,2012,36,6,4,85,129,15086
+3155,2010,15,1,8,84,130,12289
+3156,2009,29,5,8,82,128,14459
+3157,2007,21,7,5,87,123,14428
+3158,2010,6,2,6,80,126,12755
+3159,2006,4,10,5,80,120,14417
+3160,2007,14,7,9,84,129,14527
+3161,2012,19,5,6,88,123,13716
+3162,2007,37,9,7,89,127,16712
+3163,2011,17,5,4,89,126,13524
+3164,2006,6,3,2,82,122,12727
+3165,2015,14,3,8,84,123,12762
+3166,2009,8,3,0,82,130,12121
+3167,2010,8,10,7,86,123,13948
+3168,2000,19,4,7,88,130,14166
+3169,2007,25,5,5,87,122,14506
+3170,2013,24,3,2,90,126,14192
+3171,2009,32,2,4,89,124,13887
+3172,2010,19,7,4,89,121,14024
+3173,2007,15,0,0,88,130,11693
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+3175,2006,19,8,2,85,125,14247
+3176,2008,6,7,8,86,123,14029
+3177,2007,20,0,10,86,122,13159
+3178,2007,29,1,4,82,121,14142
+3179,2006,38,7,1,83,125,15649
+3180,2016,3,6,6,84,122,12777
+3181,2002,35,9,2,81,127,15335
+3182,2007,33,3,3,86,123,14599
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+3185,2011,3,2,2,85,129,12142
+3186,2017,24,2,6,87,126,13059
+3187,2010,35,7,7,85,123,14939
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+3191,2006,11,10,3,88,123,14101
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+3195,2003,37,7,4,86,128,15849
+3196,2017,32,6,7,82,127,14639
+3197,2018,15,4,8,85,121,13403
+3198,2005,37,2,4,86,125,15049
+3199,2008,10,9,2,90,122,13429
+3200,2011,34,4,6,88,125,14074
+3201,2010,8,0,10,81,129,12888
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+3203,2008,35,5,6,89,124,15488
+3204,2018,9,6,0,82,127,13567
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+3207,2000,33,2,9,84,124,13898
+3208,2018,8,5,6,87,127,13142
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+3210,2013,26,5,8,80,120,14583
+3211,2015,38,7,9,86,120,15829
+3212,2015,11,2,7,86,129,12421
+3213,2015,25,0,10,90,122,13156
+3214,2011,13,4,5,87,127,13295
+3215,2001,16,4,9,85,123,14184
+3216,2014,28,9,9,85,130,15593
+3217,2006,22,4,7,80,125,13297
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+3219,2000,15,9,0,82,120,14335
+3220,2003,20,4,5,84,127,12967
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+3223,2006,29,6,3,86,123,15153
+3224,2005,23,9,7,82,129,14830
+3225,2017,15,5,3,87,128,13532
+3226,2012,33,3,9,83,121,13890
+3227,2005,11,5,1,80,120,12738
+3228,2000,27,2,9,80,125,13542
+3229,2001,0,7,1,87,125,12634
+3230,2006,12,1,2,90,122,12953
+3231,2002,18,10,4,83,120,15048
+3232,2013,16,9,1,80,125,14517
+3233,2013,32,7,3,89,123,15653
+3234,2003,4,1,10,86,123,12044
+3235,2000,24,10,1,86,123,14398
+3236,2000,32,5,1,81,120,15007
+3237,2005,12,8,1,82,122,13691
+3238,2009,19,2,0,86,129,13055
+3239,2013,20,7,0,86,128,14676
+3240,2010,4,0,7,89,129,12910
+3241,2006,21,2,9,88,125,14098
+3242,2014,34,9,9,82,128,15921
+3243,2008,37,3,0,84,130,14079
+3244,2003,24,9,4,90,124,15503
+3245,2011,22,9,8,82,122,14934
+3246,2013,7,9,7,86,120,14072
+3247,2006,27,3,7,84,121,13927
+3248,2017,37,0,7,90,121,14097
+3249,2000,11,2,8,84,125,12868
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+3251,2007,5,1,7,81,122,12540
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+3253,2002,29,10,7,85,125,16203
+3254,2016,34,2,6,89,123,14563
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+3259,2010,32,7,5,81,126,14581
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+3261,2008,22,4,6,89,123,13921
+3262,2000,18,4,4,82,126,13404
+3263,2018,32,0,8,87,130,14382
+3264,2000,30,5,1,82,129,13768
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+3266,2015,34,9,2,83,121,15920
+3267,2003,4,6,7,85,122,14052
+3268,2004,32,0,7,89,121,13844
+3269,2018,12,6,1,82,120,13947
+3270,2009,34,9,3,90,121,15597
+3271,2004,13,0,9,90,122,12001
+3272,2014,8,9,9,90,130,15042
+3273,2004,1,7,10,89,121,13106
+3274,2016,28,0,10,85,122,13853
+3275,2002,10,0,4,88,130,11779
+3276,2015,17,2,5,81,127,12561
+3277,2018,36,7,1,88,124,15796
+3278,2018,24,0,4,88,129,12959
+3279,2016,14,9,0,90,127,14321
+3280,2001,22,10,3,88,130,14424
+3281,2002,25,6,10,90,122,15083
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+3283,2002,28,7,2,83,130,14237
+3284,2017,26,9,5,81,130,14614
+3285,2014,30,1,1,82,129,14148
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+3288,2012,21,10,5,87,122,15224
+3289,2012,10,5,9,87,120,13295
+3290,2001,23,8,8,89,120,14754
+3291,2000,16,4,2,81,124,13562
+3292,2008,24,2,3,85,120,13072
+3293,2004,15,0,1,82,129,11818
+3294,2009,32,9,1,89,123,15335
+3295,2012,36,0,1,82,126,13921
+3296,2016,29,4,9,89,129,14375
+3297,2006,12,1,10,88,127,12615
+3298,2008,12,10,3,87,125,14536
+3299,2004,23,6,0,87,127,14474
+3300,2007,36,6,4,88,121,15032
+3301,2006,23,4,6,90,124,14110
+3302,2016,36,8,0,85,126,15570
+3303,2017,5,5,10,83,126,13722
+3304,2018,29,2,8,89,120,13495
+3305,2016,28,8,9,83,127,15359
+3306,2000,33,10,0,80,125,15508
+3307,2005,17,2,6,86,128,12466
+3308,2008,2,1,10,90,129,12326
+3309,2005,9,5,4,86,120,13094
+3310,2002,7,7,7,90,128,13398
+3311,2002,19,3,2,89,128,12579
+3312,2012,7,10,8,86,128,14255
+3313,2017,3,1,1,88,126,12044
+3314,2018,15,2,10,86,128,12631
+3315,2003,3,7,5,90,129,13574
+3316,2009,38,10,6,81,120,16023
+3317,2007,17,5,7,82,125,13110
+3318,2005,36,7,8,90,127,15730
+3319,2009,3,6,2,90,123,13334
+3320,2016,35,5,2,90,120,14807
+3321,2002,5,7,0,81,129,13074
+3322,2010,21,6,1,83,120,13615
+3323,2010,35,10,10,82,125,16618
+3324,2010,17,4,4,82,120,13368
+3325,2000,17,7,8,81,122,14409
+3326,2009,13,2,9,88,124,13061
+3327,2009,25,7,5,83,126,14942
+3328,2018,3,10,8,90,125,14806
+3329,2014,24,6,3,84,124,14077
+3330,2001,19,6,10,89,126,13968
+3331,2002,32,8,10,88,122,15396
+3332,2017,37,3,6,90,122,15039
+3333,2018,1,6,10,81,129,13093
+3334,2001,19,3,7,85,128,13182
+3335,2011,3,8,4,87,120,13840
+3336,2000,33,2,2,88,127,14467
+3337,2014,5,4,9,88,120,13440
+3338,2010,36,9,7,87,123,15974
+3339,2015,31,6,3,81,121,14436
+3340,2010,17,6,5,80,127,13363
+3341,2004,22,8,9,83,129,15406
+3342,2001,19,3,5,83,123,13422
+3343,2011,37,0,10,87,126,13852
+3344,2012,2,6,4,85,123,13905
+3345,2015,5,5,5,87,120,13449
+3346,2001,35,8,8,81,120,15878
+3347,2004,4,4,6,80,122,12680
+3348,2010,18,5,5,81,122,13560
+3349,2015,38,8,4,85,128,15582
+3350,2010,15,10,0,86,127,14285
+3351,2013,36,3,9,84,126,15196
+3352,2018,36,3,5,87,122,14006
+3353,2008,25,5,1,89,128,13347
+3354,2009,3,4,7,84,126,12647
+3355,2005,5,0,6,84,123,11544
+3356,2013,33,10,7,90,129,16625
+3357,2013,9,2,2,86,121,12923
+3358,2008,19,2,5,85,128,12660
+3359,2005,0,7,5,89,124,13362
+3360,2002,22,2,3,81,128,13695
+3361,2015,11,9,9,88,127,15005
+3362,2002,25,5,10,89,122,13733
+3363,2005,13,1,5,86,124,12376
+3364,2003,5,1,9,90,129,12830
+3365,2010,11,1,0,89,124,11704
+3366,2018,0,6,9,86,122,13262
+3367,2009,14,9,0,87,127,13641
+3368,2009,33,5,1,88,124,15192
+3369,2010,34,5,9,86,121,14396
+3370,2002,0,9,0,89,123,13020
+3371,2015,1,4,1,83,128,12465
+3372,2002,8,6,1,85,127,13895
+3373,2003,30,1,6,82,124,13055
+3374,2018,28,6,1,84,123,14146
+3375,2007,16,10,0,81,129,14179
+3376,2006,8,3,0,86,126,13111
+3377,2014,17,9,3,81,123,14793
+3378,2015,21,3,6,82,124,13280
+3379,2004,6,0,8,81,126,11795
+3380,2002,4,1,7,86,126,12031
+3381,2011,5,6,10,88,125,14049
+3382,2009,38,5,5,83,125,15818
+3383,2012,13,4,7,85,127,13516
+3384,2000,22,4,6,90,127,13908
+3385,2006,0,6,8,83,125,13154
+3386,2014,35,8,8,89,129,16285
+3387,2001,7,7,6,88,121,13546
+3388,2004,26,10,4,82,130,14849
+3389,2010,11,10,0,80,122,14051
+3390,2001,35,5,1,90,127,15225
+3391,2011,31,1,2,83,124,13105
+3392,2003,8,0,9,88,128,12329
+3393,2017,28,4,2,90,128,14585
+3394,2001,33,4,8,84,130,14047
+3395,2004,31,6,4,85,122,15086
+3396,2009,36,10,5,80,125,16442
+3397,2001,18,0,8,80,130,12302
+3398,2013,12,4,5,82,121,12700
+3399,2008,27,6,7,81,122,14680
+3400,2006,15,2,6,87,123,12852
+3401,2007,36,1,9,86,127,13892
+3402,2010,4,1,10,89,129,12757
+3403,2012,13,3,6,83,128,13255
+3404,2004,37,2,9,86,124,14154
+3405,2006,17,9,5,82,123,14354
+3406,2014,25,1,4,90,129,13973
+3407,2011,27,0,7,83,130,13766
+3408,2004,20,5,4,80,128,13369
+3409,2017,33,5,1,90,122,15105
+3410,2013,14,2,0,84,120,12256
+3411,2015,37,2,0,88,124,14399
+3412,2003,36,10,4,82,120,16470
+3413,2015,23,3,3,80,126,14138
+3414,2016,0,6,0,82,120,13275
+3415,2009,29,6,0,86,127,13906
+3416,2001,11,0,5,85,126,12204
+3417,2013,16,1,10,82,126,12924
+3418,2009,23,7,7,89,124,14299
+3419,2018,21,3,8,87,127,13689
+3420,2009,33,1,10,84,129,13818
+3421,2010,19,2,1,85,123,12442
+3422,2010,11,6,7,85,130,13985
+3423,2008,0,3,8,80,122,13009
+3424,2016,17,7,1,81,130,14562
+3425,2004,38,7,7,89,125,15717
+3426,2012,21,6,7,82,128,14721
+3427,2014,13,1,2,86,121,13011
+3428,2006,16,4,2,82,129,13247
+3429,2018,18,7,5,81,128,14310
+3430,2016,10,1,5,82,125,12168
+3431,2008,2,10,6,84,126,14608
+3432,2004,9,8,0,81,123,13898
+3433,2008,14,3,5,85,125,13097
+3434,2009,7,3,3,80,120,13306
+3435,2013,16,10,6,85,122,15372
+3436,2010,0,5,7,89,124,12811
+3437,2010,22,6,10,85,130,14570
+3438,2001,2,9,2,87,129,13304
+3439,2007,21,10,4,85,130,14554
+3440,2013,16,9,2,90,129,14261
+3441,2004,27,9,6,82,122,15512
+3442,2018,27,5,10,81,128,14199
+3443,2011,23,1,0,89,122,12826
+3444,2012,3,9,4,82,123,14054
+3445,2015,30,3,5,87,130,14162
+3446,2014,5,7,9,88,126,13350
+3447,2004,5,10,1,88,124,14422
+3448,2005,25,10,6,85,130,15026
+3449,2007,7,1,4,82,129,12872
+3450,2004,17,10,5,86,127,15109
+3451,2005,13,4,10,81,127,13359
+3452,2004,2,9,3,88,124,14354
+3453,2006,11,8,6,80,122,14273
+3454,2003,3,1,2,83,124,12365
+3455,2012,5,10,3,84,125,14044
+3456,2000,35,7,5,88,129,14963
+3457,2003,7,9,1,82,126,14240
+3458,2003,22,2,7,90,126,13303
+3459,2013,19,0,6,86,120,12921
+3460,2008,32,9,3,84,124,14780
+3461,2010,8,0,9,82,128,12460
+3462,2013,32,8,7,83,124,15917
+3463,2008,23,3,1,81,129,13646
+3464,2004,2,3,6,80,125,12568
+3465,2001,32,8,7,83,120,14827
+3466,2000,8,3,3,90,120,12210
+3467,2000,33,6,3,87,127,15344
+3468,2009,16,3,0,88,121,13571
+3469,2016,33,9,4,89,120,15964
+3470,2005,20,8,5,84,128,13957
+3471,2002,26,0,1,84,123,12560
+3472,2005,8,2,9,81,126,13074
+3473,2018,14,3,2,84,124,12608
+3474,2017,12,2,1,89,124,13293
+3475,2009,38,2,2,84,128,15069
+3476,2002,28,5,4,85,124,14771
+3477,2002,0,1,6,81,130,11891
+3478,2004,27,9,9,86,123,15184
+3479,2007,6,6,1,86,120,12814
+3480,2010,10,6,7,82,128,13290
+3481,2017,37,8,5,88,120,15771
+3482,2002,18,6,6,89,124,14084
+3483,2015,34,3,0,83,123,13929
+3484,2006,16,9,1,87,122,14122
+3485,2008,2,3,1,80,128,12103
+3486,2011,13,3,0,80,129,12436
+3487,2015,11,9,2,84,126,14252
+3488,2005,22,10,1,80,127,14791
+3489,2006,4,4,2,82,124,12259
+3490,2013,36,5,0,90,130,14585
+3491,2000,25,0,0,81,124,12169
+3492,2003,0,8,7,82,122,13495
+3493,2001,4,0,10,89,130,12139
+3494,2016,2,3,10,90,122,12357
+3495,2015,25,1,0,81,130,12605
+3496,2010,24,10,6,82,125,15571
+3497,2011,1,7,0,85,124,13897
+3498,2017,12,6,5,88,126,13198
+3499,2013,30,9,0,82,123,15110
+3500,2010,7,2,6,90,121,12052
+3501,2003,12,10,7,88,130,14114
+3502,2003,9,6,8,84,121,14247
+3503,2014,6,7,0,83,123,13644
+3504,2008,33,1,3,90,126,13476
+3505,2001,1,7,0,80,128,13845
+3506,2015,34,7,9,83,127,15871
+3507,2000,34,5,7,87,125,15029
+3508,2006,8,1,9,85,126,12014
+3509,2013,23,3,1,86,123,12781
+3510,2015,18,1,5,85,123,13165
+3511,2005,20,7,6,80,120,13979
+3512,2004,2,1,0,83,123,12494
+3513,2012,5,8,2,88,126,13205
+3514,2002,32,10,1,80,121,15463
+3515,2012,3,8,8,88,128,14347
+3516,2000,30,10,8,82,123,15034
+3517,2014,32,4,3,82,130,14651
+3518,2016,24,6,2,89,126,14577
+3519,2002,5,1,10,82,126,13070
+3520,2013,9,1,8,88,123,12411
+3521,2018,15,6,1,84,120,13210
+3522,2015,4,10,6,84,129,14456
+3523,2000,17,1,4,83,123,13103
+3524,2001,35,3,7,80,130,14824
+3525,2017,30,0,8,86,124,14052
+3526,2007,21,8,8,85,127,14553
+3527,2017,6,5,4,89,128,13745
+3528,2011,20,3,2,90,121,12647
+3529,2015,21,7,6,80,122,13721
+3530,2006,15,2,1,85,125,12603
+3531,2002,37,8,4,89,122,15788
+3532,2017,17,0,0,90,129,12099
+3533,2008,13,5,7,81,128,13817
+3534,2008,25,10,9,90,128,15331
+3535,2004,23,0,5,86,123,13587
+3536,2008,37,8,9,88,126,16463
+3537,2006,20,1,7,83,125,13459
+3538,2013,32,1,1,88,120,13023
+3539,2017,29,9,9,80,130,15154
+3540,2009,36,7,0,88,122,15060
+3541,2010,32,7,0,80,127,15087
+3542,2014,2,3,8,81,129,12493
+3543,2002,31,5,3,87,130,14366
+3544,2010,13,4,2,80,121,12568
+3545,2000,21,1,3,87,128,12569
+3546,2001,3,10,5,83,130,13682
+3547,2000,27,2,0,87,121,12979
+3548,2013,33,5,4,80,129,15350
+3549,2018,6,5,4,90,121,13338
+3550,2014,8,7,2,88,123,13455
+3551,2005,26,10,0,82,122,14483
+3552,2009,4,6,6,87,122,13538
+3553,2018,26,1,3,90,129,13508
+3554,2010,28,8,10,83,129,14886
+3555,2010,14,0,7,80,122,13186
+3556,2011,10,8,7,85,125,13973
+3557,2013,33,1,7,81,128,13542
+3558,2007,34,8,10,86,127,15103
+3559,2014,29,2,1,90,129,13306
+3560,2013,6,6,7,86,130,13452
+3561,2015,18,0,10,80,125,12318
+3562,2006,24,10,0,82,127,15262
+3563,2014,34,7,6,80,120,15662
+3564,2005,34,7,10,90,125,15643
+3565,2016,20,1,2,81,127,12504
+3566,2011,29,10,2,87,126,15888
+3567,2009,7,5,0,84,122,13225
+3568,2007,32,7,1,80,127,14618
+3569,2007,16,2,6,82,126,13528
+3570,2000,21,2,3,81,129,13629
+3571,2005,8,7,3,87,122,13575
+3572,2016,2,8,10,87,125,14044
+3573,2005,24,7,6,88,121,14147
+3574,2010,31,8,2,82,128,15715
+3575,2018,7,1,9,80,129,13167
+3576,2011,15,8,3,89,130,13532
+3577,2005,12,4,9,84,123,13763
+3578,2003,26,6,9,82,120,14174
+3579,2017,26,10,8,87,127,15374
+3580,2007,37,0,7,80,124,14643
+3581,2001,3,6,7,90,120,13023
+3582,2006,28,8,5,87,124,14482
+3583,2003,4,6,0,87,125,13477
+3584,2008,34,3,0,86,122,14533
+3585,2018,1,2,4,83,126,11828
+3586,2006,9,9,3,83,128,14313
+3587,2004,5,2,7,87,125,12019
+3588,2012,10,3,2,80,127,13163
+3589,2000,21,7,9,88,122,14466
+3590,2009,9,8,7,87,129,14210
+3591,2014,8,5,7,83,126,13650
+3592,2001,13,10,8,85,126,14412
+3593,2013,11,0,3,82,125,12773
+3594,2005,19,4,3,88,128,13980
+3595,2006,36,3,3,85,124,14603
+3596,2003,36,0,2,82,121,13772
+3597,2003,0,2,5,80,130,12296
+3598,2015,16,3,8,83,130,13522
+3599,2004,16,9,4,86,123,14515
+3600,2013,17,6,1,85,129,13340
+3601,2014,16,2,0,83,129,12276
+3602,2001,29,0,8,86,124,14021
+3603,2017,35,5,5,81,120,14917
+3604,2009,2,0,8,81,122,12198
+3605,2004,14,3,5,85,120,12419
+3606,2008,3,2,1,85,127,11940
+3607,2016,10,9,5,87,130,14027
+3608,2004,5,6,10,87,122,13110
+3609,2005,18,6,6,82,121,14426
+3610,2018,19,5,5,80,125,13415
+3611,2001,4,2,8,81,127,12638
+3612,2003,14,6,1,88,120,14116
+3613,2001,20,0,7,84,128,12751
+3614,2007,21,10,2,87,123,15055
+3615,2000,6,4,8,84,120,12573
+3616,2001,5,0,7,89,129,12136
+3617,2004,28,9,8,81,128,15714
+3618,2017,19,7,7,80,122,14421
+3619,2008,34,3,7,83,122,14742
+3620,2015,1,9,5,80,126,14208
+3621,2004,37,0,7,88,120,14646
+3622,2017,24,1,8,86,126,14085
+3623,2007,5,0,10,90,125,12425
+3624,2018,5,3,4,84,129,12277
+3625,2007,23,1,4,84,121,12724
+3626,2007,15,4,3,82,124,13855
+3627,2000,37,10,10,84,121,16736
+3628,2015,34,5,0,86,125,14749
+3629,2005,25,3,1,83,122,13734
+3630,2003,33,2,1,85,129,14176
+3631,2007,3,2,6,84,129,13073
+3632,2015,26,1,10,84,129,13057
+3633,2007,21,4,10,88,130,13333
+3634,2007,7,0,8,88,123,12742
+3635,2005,14,4,4,84,122,13469
+3636,2010,15,1,3,80,121,12599
+3637,2018,36,5,4,80,130,14886
+3638,2018,7,5,4,81,125,13094
+3639,2009,31,2,4,90,125,13817
+3640,2012,6,0,8,80,121,12055
+3641,2016,19,2,1,90,123,13253
+3642,2018,13,5,10,88,127,13416
+3643,2007,19,8,0,86,127,14294
+3644,2004,23,10,4,82,126,15634
+3645,2006,3,0,5,83,126,12340
+3646,2005,0,9,10,84,125,13899
+3647,2006,21,0,3,87,125,12129
+3648,2001,27,3,7,80,126,13784
+3649,2011,29,2,5,89,126,13218
+3650,2015,22,3,0,80,127,13174
+3651,2007,23,8,4,90,126,14370
+3652,2005,16,0,9,80,124,12108
+3653,2004,14,3,9,83,130,12917
+3654,2015,23,9,5,86,125,14400
+3655,2011,8,8,7,83,127,13524
+3656,2011,26,1,3,81,130,13560
+3657,2011,7,9,10,86,130,14772
+3658,2010,24,1,7,89,122,13236
+3659,2018,29,7,7,80,125,15103
+3660,2003,24,7,3,86,121,14481
+3661,2001,35,8,5,80,123,15866
+3662,2011,13,3,8,86,127,13107
+3663,2015,21,3,7,89,126,12998
+3664,2016,26,5,0,86,122,14617
+3665,2015,32,4,2,88,122,13961
+3666,2001,33,3,10,83,122,14898
+3667,2013,6,3,4,80,125,12239
+3668,2010,22,4,8,84,125,13765
+3669,2005,34,6,9,85,124,15223
+3670,2007,35,0,4,82,124,13567
+3671,2006,37,3,5,81,121,15136
+3672,2014,35,2,4,82,130,13914
+3673,2008,5,5,8,82,123,12674
+3674,2010,21,6,4,90,126,14085
+3675,2017,23,9,0,87,120,14011
+3676,2014,20,0,4,90,123,12668
+3677,2002,11,4,4,83,126,13216
+3678,2017,35,4,8,81,126,15396
+3679,2013,4,1,8,89,121,13006
+3680,2008,34,5,3,90,129,14528
+3681,2013,10,6,1,88,127,13785
+3682,2010,19,5,7,82,122,14098
+3683,2011,18,9,7,82,127,14176
+3684,2015,37,7,10,82,127,16435
+3685,2016,21,9,3,84,128,14062
+3686,2003,1,4,7,90,120,12443
+3687,2000,27,2,4,87,122,13436
+3688,2012,10,9,8,89,129,14791
+3689,2011,35,10,1,83,123,16293
+3690,2014,17,9,8,80,121,14271
+3691,2009,4,1,10,83,128,12465
+3692,2006,3,6,7,83,121,14027
+3693,2002,33,10,1,82,128,15721
+3694,2007,35,3,3,86,127,14415
+3695,2001,1,3,4,86,124,12834
+3696,2010,32,7,0,83,125,14587
+3697,2003,8,3,4,83,120,12492
+3698,2007,11,6,3,85,130,13896
+3699,2017,32,9,8,85,129,15738
+3700,2005,35,6,9,86,128,15338
+3701,2000,5,6,2,90,120,12820
+3702,2010,35,5,9,84,120,14845
+3703,2012,20,1,5,86,124,12894
+3704,2015,9,10,5,88,129,14707
+3705,2011,29,7,5,80,130,14492
+3706,2007,38,3,10,87,128,15049
+3707,2016,3,4,9,86,123,12649
+3708,2017,33,3,3,87,121,14013
+3709,2013,35,3,9,85,120,14197
+3710,2013,19,10,8,84,126,15397
+3711,2012,19,10,10,81,125,15093
+3712,2017,15,1,1,81,126,12567
+3713,2006,28,10,3,81,126,14673
+3714,2017,18,8,10,81,122,14358
+3715,2009,35,5,0,85,129,15075
+3716,2013,11,10,4,87,129,14340
+3717,2000,38,8,9,84,127,15998
+3718,2018,29,8,0,81,121,14195
+3719,2011,20,7,0,83,128,13391
+3720,2002,4,5,5,90,126,13027
+3721,2009,4,2,3,82,126,12428
+3722,2008,36,10,0,84,130,15479
+3723,2018,0,2,6,87,129,12450
+3724,2015,24,9,6,81,122,15481
+3725,2015,12,3,1,87,128,12241
+3726,2005,17,9,0,88,130,14546
+3727,2018,8,5,1,80,125,12594
+3728,2003,25,10,10,84,127,15950
+3729,2014,36,8,2,88,130,15823
+3730,2005,0,7,2,81,128,13447
+3731,2011,17,8,3,89,121,13834
+3732,2011,30,5,5,80,124,13859
+3733,2007,30,6,7,82,122,14527
+3734,2011,23,0,9,86,124,13071
+3735,2013,10,1,0,85,125,12926
+3736,2015,30,0,1,86,126,13577
+3737,2006,28,8,4,81,129,14808
+3738,2000,7,4,8,82,122,13235
+3739,2009,37,6,3,85,129,15868
+3740,2018,22,3,1,84,120,13094
+3741,2016,29,5,6,87,126,14912
+3742,2003,32,2,7,85,130,14021
+3743,2017,6,8,6,85,126,14579
+3744,2005,27,4,2,88,126,13549
+3745,2016,2,0,7,85,120,12192
+3746,2007,6,2,4,90,128,12827
+3747,2008,26,6,2,89,124,14788
+3748,2013,22,5,8,84,129,14263
+3749,2005,31,2,10,90,125,13845
+3750,2009,36,5,0,80,124,14985
+3751,2008,4,1,4,90,127,12063
+3752,2006,9,1,8,80,122,12204
+3753,2004,24,2,6,80,130,13737
+3754,2015,9,10,7,84,127,14650
+3755,2007,33,6,2,84,121,14273
+3756,2000,21,9,3,81,130,14986
+3757,2010,23,6,5,90,124,14500
+3758,2013,20,6,4,87,124,13511
+3759,2006,6,1,7,84,129,11988
+3760,2002,8,8,1,84,125,14055
+3761,2009,24,8,1,80,120,14590
+3762,2013,25,1,3,81,126,12974
+3763,2018,37,6,6,80,128,15403
+3764,2015,4,10,5,90,123,13899
+3765,2003,22,1,7,83,127,12945
+3766,2013,13,9,3,88,125,14642
+3767,2007,7,2,4,87,130,12980
+3768,2004,23,6,10,89,120,14441
+3769,2011,36,5,8,89,124,15566
+3770,2000,25,2,10,83,125,13593
+3771,2012,35,4,10,85,121,14581
+3772,2005,24,6,5,88,129,13928
+3773,2002,22,4,8,83,123,13961
+3774,2001,30,3,5,90,125,13449
+3775,2015,10,4,5,84,124,12908
+3776,2004,30,3,3,84,121,13816
+3777,2005,18,7,8,80,124,13611
+3778,2000,26,1,9,88,121,13286
+3779,2009,16,2,3,86,123,12509
+3780,2004,22,8,1,90,130,14543
+3781,2008,36,3,4,83,121,14637
+3782,2008,36,10,0,82,120,16169
+3783,2011,7,10,2,90,126,13958
+3784,2008,15,2,0,82,127,12685
+3785,2003,36,2,0,85,125,14365
+3786,2015,26,3,1,83,122,13853
+3787,2015,9,3,0,88,129,12084
+3788,2006,22,5,7,87,121,13519
+3789,2012,25,8,1,80,122,15187
+3790,2016,17,4,3,84,126,12888
+3791,2000,16,1,5,87,120,13357
+3792,2017,1,4,9,90,126,13402
+3793,2005,5,7,7,85,121,13037
+3794,2002,15,6,1,80,126,13396
+3795,2009,22,3,1,80,124,12799
+3796,2010,23,4,5,83,121,14281
+3797,2012,34,7,3,81,129,14927
+3798,2002,14,5,6,88,127,13811
+3799,2003,14,0,8,84,121,12208
+3800,2018,2,5,8,87,125,13315
+3801,2012,24,8,3,87,129,15168
+3802,2011,15,8,3,83,126,14739
+3803,2014,3,8,1,90,123,13863
+3804,2001,13,8,1,85,127,13631
+3805,2003,26,1,9,86,129,12957
+3806,2017,23,2,10,80,122,13892
+3807,2002,19,0,7,82,121,13154
+3808,2013,27,5,9,86,130,15042
+3809,2016,12,3,0,83,125,12411
+3810,2001,22,5,4,80,130,14115
+3811,2018,25,7,6,80,121,14617
+3812,2016,33,3,6,87,129,14454
+3813,2008,34,6,3,86,128,15218
+3814,2012,9,4,8,84,130,13922
+3815,2015,32,6,4,81,124,14331
+3816,2012,33,0,1,84,121,12886
+3817,2001,37,8,4,80,125,15377
+3818,2010,38,9,7,81,126,16523
+3819,2016,18,4,8,90,122,14206
+3820,2002,5,10,5,81,127,14720
+3821,2016,6,1,0,83,130,12193
+3822,2010,17,6,0,87,120,13361
+3823,2009,31,2,4,81,124,13892
+3824,2008,11,0,3,80,126,11862
+3825,2017,3,8,9,90,125,13533
+3826,2010,27,9,0,81,125,15254
+3827,2018,6,6,6,89,121,13014
+3828,2004,8,7,2,83,124,13763
+3829,2014,33,2,6,90,124,14226
+3830,2000,23,8,6,80,128,14901
+3831,2007,27,5,8,86,129,14956
+3832,2013,9,4,6,83,122,13021
+3833,2012,22,3,8,90,121,13072
+3834,2013,29,7,1,89,128,14210
+3835,2009,29,5,2,90,127,14445
+3836,2008,14,10,2,90,124,14961
+3837,2015,35,6,6,84,121,15819
+3838,2014,21,8,5,81,127,14670
+3839,2004,35,10,6,90,129,15820
+3840,2015,7,5,6,86,126,13210
+3841,2016,27,9,7,84,127,15912
+3842,2009,3,10,8,89,124,14876
+3843,2015,30,1,5,80,129,13083
+3844,2011,36,0,2,86,127,14369
+3845,2018,35,0,8,88,124,14104
+3846,2008,8,0,7,80,128,12466
+3847,2003,6,1,9,88,120,13177
+3848,2013,28,2,10,87,130,13919
+3849,2000,11,4,8,80,128,13277
+3850,2012,34,0,5,82,123,13424
+3851,2006,26,7,9,86,124,15200
+3852,2003,13,2,6,89,124,13516
+3853,2004,38,7,7,81,125,15803
+3854,2011,13,0,10,80,125,12431
+3855,2009,38,4,2,86,129,14614
+3856,2004,26,5,0,85,126,13693
+3857,2005,30,6,9,87,125,14911
+3858,2010,14,5,8,85,125,13421
+3859,2016,17,9,2,80,129,14403
+3860,2002,28,1,3,84,123,13005
+3861,2012,24,9,7,83,120,14633
+3862,2009,16,5,9,84,124,13425
+3863,2016,4,1,0,87,123,11740
+3864,2017,12,4,3,88,123,12535
+3865,2009,33,10,4,82,120,15861
+3866,2009,34,1,5,82,129,14399
+3867,2015,37,1,7,80,123,14249
+3868,2012,18,2,0,88,126,12378
+3869,2004,26,10,8,83,124,15398
+3870,2003,11,5,10,84,121,13456
+3871,2007,7,3,2,82,127,12917
+3872,2014,34,9,0,82,126,15964
+3873,2012,28,3,8,84,128,14749
+3874,2017,35,6,8,89,121,14946
+3875,2011,17,6,3,81,121,14248
+3876,2002,23,0,1,86,121,12862
+3877,2018,13,6,6,84,125,13648
+3878,2013,2,10,8,84,124,14218
+3879,2015,9,10,8,90,129,14363
+3880,2016,32,8,2,84,129,15085
+3881,2010,11,2,5,84,125,13020
+3882,2008,38,1,3,86,125,13644
+3883,2014,9,2,6,84,121,12866
+3884,2015,31,9,10,83,130,16247
+3885,2002,23,0,3,86,126,13368
+3886,2017,31,10,10,80,128,16324
+3887,2013,30,10,4,89,124,15191
+3888,2008,4,4,7,84,126,13674
+3889,2011,26,10,2,81,130,15661
+3890,2006,38,4,2,84,127,15082
+3891,2002,2,4,2,90,122,12598
+3892,2001,15,10,1,89,130,14196
+3893,2018,24,6,6,85,122,14997
+3894,2010,26,7,7,86,128,14135
+3895,2012,1,8,0,85,121,13093
+3896,2016,2,7,4,85,124,14143
+3897,2018,30,3,5,86,123,13755
+3898,2013,0,9,2,84,124,14037
+3899,2006,25,3,8,80,128,14234
+3900,2007,16,4,3,81,124,13521
+3901,2000,36,6,9,89,127,15789
+3902,2003,13,0,5,85,130,11816
+3903,2013,35,4,3,90,124,14529
+3904,2012,37,4,5,86,125,14664
+3905,2000,4,9,8,88,122,13739
+3906,2006,3,7,3,88,128,13978
+3907,2008,20,1,0,89,128,12914
+3908,2011,35,6,2,89,123,15383
+3909,2016,18,0,2,81,121,12410
+3910,2004,12,9,4,81,120,14793
+3911,2016,15,5,9,81,127,13665
+3912,2008,31,8,2,86,128,15221
+3913,2013,23,3,6,87,124,13167
+3914,2011,0,8,7,81,121,13273
+3915,2012,32,10,6,81,127,15171
+3916,2007,18,6,5,87,123,13288
+3917,2006,2,5,4,88,129,13334
+3918,2005,23,4,2,89,129,13172
+3919,2006,24,4,4,86,123,14050
+3920,2017,2,10,8,86,123,13865
+3921,2013,28,1,3,87,122,13069
+3922,2018,20,9,4,84,123,14287
+3923,2012,13,7,7,80,126,13867
+3924,2013,10,5,3,80,125,12741
+3925,2007,10,8,10,82,120,13682
+3926,2011,24,5,10,80,129,14335
+3927,2002,7,4,6,89,123,13564
+3928,2012,28,3,9,89,125,14555
+3929,2011,0,5,3,83,122,12575
+3930,2003,30,10,10,82,124,15154
+3931,2002,31,1,8,82,123,14232
+3932,2006,34,1,5,83,120,14213
+3933,2001,18,0,2,88,129,12162
+3934,2011,36,3,4,83,123,14789
+3935,2012,10,2,1,89,124,12180
+3936,2005,26,0,6,85,128,12858
+3937,2010,37,4,1,89,127,14984
+3938,2000,35,10,2,81,125,16289
+3939,2017,35,5,9,84,121,15390
+3940,2003,27,4,5,88,130,14719
+3941,2011,38,10,9,85,124,16225
+3942,2003,6,9,4,86,122,14104
+3943,2001,30,10,3,87,121,15307
+3944,2010,12,5,2,84,124,13652
+3945,2014,19,4,6,84,126,13262
+3946,2004,3,1,10,89,123,12165
+3947,2014,24,5,0,85,121,13705
+3948,2010,24,2,3,80,122,13950
+3949,2018,10,9,10,83,126,14118
+3950,2002,5,1,3,87,126,11737
+3951,2001,22,7,10,84,120,15181
+3952,2010,32,5,1,86,121,14080
+3953,2003,0,8,0,85,130,12953
+3954,2007,11,3,7,89,125,12453
+3955,2007,24,0,0,85,122,12272
+3956,2017,22,9,10,86,127,14608
+3957,2017,12,0,0,84,123,11801
+3958,2005,33,3,6,82,125,14226
+3959,2006,27,0,6,86,130,13076
+3960,2004,8,6,7,81,120,14146
+3961,2002,17,8,6,88,130,14488
+3962,2007,18,8,5,90,121,14854
+3963,2008,16,10,10,84,130,15335
+3964,2004,26,4,4,89,128,14093
+3965,2011,12,0,2,80,126,11742
+3966,2006,20,1,8,87,122,13386
+3967,2008,14,0,0,87,122,11601
+3968,2010,11,9,7,82,122,14444
+3969,2009,28,8,7,90,124,14486
+3970,2008,29,6,2,80,122,14825
+3971,2008,25,0,1,89,130,12963
+3972,2011,7,3,7,83,121,13411
+3973,2018,26,9,7,86,121,15324
+3974,2008,14,5,4,87,123,13084
+3975,2005,23,3,1,86,126,13388
+3976,2002,9,10,3,80,128,14497
+3977,2003,10,4,7,80,126,13822
+3978,2000,31,10,8,85,125,15517
+3979,2016,0,1,4,87,125,11989
+3980,2001,22,4,10,88,130,13616
+3981,2005,2,4,5,82,120,12712
+3982,2014,18,4,5,87,127,13555
+3983,2018,15,7,7,81,121,14344
+3984,2012,0,6,6,87,128,13499
+3985,2003,16,8,1,86,122,13381
+3986,2010,31,4,8,89,124,15179
+3987,2001,24,5,0,81,128,14289
+3988,2002,23,9,7,86,127,14950
+3989,2004,32,9,2,87,126,15115
+3990,2003,6,10,0,89,125,14155
+3991,2004,9,2,7,80,127,13131
+3992,2012,30,2,1,80,124,13925
+3993,2011,31,7,2,87,122,14866
+3994,2007,29,6,5,83,127,14383
+3995,2001,31,9,9,86,126,15867
+3996,2002,2,9,10,88,125,14322
+3997,2013,38,1,0,88,126,13534
+3998,2000,14,10,9,90,121,14499
+3999,2013,29,9,5,84,129,15956
+4000,2007,2,2,10,89,130,12651
+4001,2012,9,2,0,84,124,12068
+4002,2011,27,8,1,85,122,14717
+4003,2006,16,3,3,81,120,13539
+4004,2011,13,8,0,83,122,13971
+4005,2016,31,6,4,88,126,15183
+4006,2010,38,2,7,90,123,14318
+4007,2015,18,9,4,80,128,14294
+4008,2004,31,4,9,82,130,14946
+4009,2011,20,0,2,89,130,12713
+4010,2001,24,3,6,85,130,14330
+4011,2009,27,10,8,87,127,15531
+4012,2016,37,10,2,81,125,16549
+4013,2010,5,4,7,90,126,13364
+4014,2003,20,2,3,85,127,13720
+4015,2016,22,0,0,80,128,12450
+4016,2004,20,7,6,88,123,14031
+4017,2004,20,5,1,87,122,13094
+4018,2018,31,0,7,90,126,13865
+4019,2003,8,7,1,81,120,13550
+4020,2018,15,2,0,88,122,12737
+4021,2006,29,3,6,85,129,14074
+4022,2010,16,3,6,84,130,12772
+4023,2014,11,0,2,85,122,11718
+4024,2011,8,3,2,86,129,13379
+4025,2013,11,10,4,90,120,14179
+4026,2007,32,0,3,88,128,14197
+4027,2003,27,9,1,80,126,15270
+4028,2015,9,0,8,83,121,13066
+4029,2018,34,10,1,85,121,16366
+4030,2016,33,9,4,90,123,15986
+4031,2000,30,0,7,90,124,14189
+4032,2006,22,9,4,81,129,14869
+4033,2007,24,1,10,81,130,13880
+4034,2012,29,8,0,81,122,14674
+4035,2012,8,9,3,87,125,14437
+4036,2007,7,7,4,80,123,13699
+4037,2015,14,3,1,87,122,12295
+4038,2002,2,3,0,90,124,12302
+4039,2014,19,10,1,87,129,15083
+4040,2008,15,6,2,90,130,13170
+4041,2011,32,1,3,85,130,13154
+4042,2015,2,8,1,81,121,13537
+4043,2007,10,3,0,81,122,13141
+4044,2007,5,5,1,80,120,12544
+4045,2016,8,10,6,84,121,14915
+4046,2000,7,10,5,82,125,14260
+4047,2009,37,0,3,80,130,14361
+4048,2012,1,8,7,87,121,14335
+4049,2010,0,1,10,83,123,12606
+4050,2004,19,6,7,90,123,13695
+4051,2017,20,1,4,82,127,12866
+4052,2012,4,5,6,87,121,13715
+4053,2000,2,1,8,87,129,11919
+4054,2014,37,5,5,88,120,14739
+4055,2004,37,1,1,83,120,14270
+4056,2015,37,5,0,83,130,14399
+4057,2010,34,1,6,81,125,13923
+4058,2004,15,0,2,87,129,12397
+4059,2006,20,10,5,89,124,15408
+4060,2008,16,1,1,82,128,12713
+4061,2008,18,0,3,87,129,12998
+4062,2012,20,8,5,85,130,15016
+4063,2004,8,7,7,89,122,13528
+4064,2018,36,8,8,81,125,15198
+4065,2011,17,7,3,89,122,14254
+4066,2012,35,3,10,84,125,14517
+4067,2002,17,9,0,80,126,14721
+4068,2016,26,0,6,85,125,13274
+4069,2003,38,9,2,88,130,16043
+4070,2001,3,1,8,86,122,13037
+4071,2003,31,6,4,82,130,14607
+4072,2016,29,9,1,82,126,14989
+4073,2000,22,0,0,87,123,12503
+4074,2012,13,5,3,88,120,13249
+4075,2010,23,1,7,88,129,13205
+4076,2011,29,0,0,83,121,12884
+4077,2001,11,8,10,83,129,13620
+4078,2000,19,8,10,90,121,15124
+4079,2006,5,3,5,89,125,12396
+4080,2007,22,8,1,85,129,14149
+4081,2006,5,1,3,84,124,12361
+4082,2002,34,6,0,88,127,14916
+4083,2017,21,7,8,80,127,13859
+4084,2014,0,5,1,86,126,13284
+4085,2015,20,7,5,81,126,14143
+4086,2003,20,4,9,83,122,14268
+4087,2011,24,0,2,90,121,12916
+4088,2014,35,10,8,90,122,15931
+4089,2010,11,0,1,86,130,11572
+4090,2010,26,2,8,81,129,13498
+4091,2011,2,8,0,85,127,13016
+4092,2004,28,1,10,89,128,13418
+4093,2017,25,6,3,89,126,13944
+4094,2000,17,5,5,81,128,14247
+4095,2003,16,10,6,90,127,15375
+4096,2011,19,3,5,82,124,13598
+4097,2002,4,10,6,90,126,14027
+4098,2016,15,7,9,88,125,14491
+4099,2000,25,2,1,82,126,13522
+4100,2013,23,3,0,82,122,12831
+4101,2001,32,8,6,89,122,14692
+4102,2005,20,5,1,83,130,14258
+4103,2002,19,3,10,81,128,13443
+4104,2012,34,7,10,82,120,16114
+4105,2003,9,3,5,83,127,12868
+4106,2006,38,1,6,90,125,14056
+4107,2001,23,3,0,83,129,13067
+4108,2017,13,6,2,81,129,14206
+4109,2001,5,1,1,88,120,11982
+4110,2013,7,5,2,81,129,12487
+4111,2013,7,10,10,82,126,15085
+4112,2008,21,5,7,87,126,14503
+4113,2016,26,6,0,87,124,13710
+4114,2004,15,4,7,86,126,13820
+4115,2000,26,6,8,81,128,14779
+4116,2015,37,9,10,87,128,16394
+4117,2006,28,7,9,84,121,15318
+4118,2016,7,2,9,89,128,13274
+4119,2016,31,0,4,86,122,13285
+4120,2001,2,4,8,87,128,13668
+4121,2014,28,6,7,86,124,15197
+4122,2007,33,7,3,86,126,14826
+4123,2003,38,9,5,84,120,15739
+4124,2002,36,2,4,83,124,13662
+4125,2017,32,4,10,89,128,14410
+4126,2005,15,7,3,86,128,14017
+4127,2016,30,10,0,90,126,14896
+4128,2006,19,0,10,81,122,13450
+4129,2014,32,1,1,85,124,13791
+4130,2005,36,0,10,81,122,14182
+4131,2018,27,8,9,85,130,15575
+4132,2016,1,6,1,81,130,13395
+4133,2011,15,5,2,81,126,14040
+4134,2002,25,4,4,84,130,14252
+4135,2016,34,4,7,90,121,15397
+4136,2012,0,1,7,80,122,12571
+4137,2016,14,7,4,87,123,13548
+4138,2007,34,2,6,84,128,14899
+4139,2008,2,4,8,88,126,12688
+4140,2011,5,4,1,83,121,12880
+4141,2005,5,3,10,84,120,13344
+4142,2012,27,8,6,87,120,15349
+4143,2012,34,5,1,81,122,15246
+4144,2016,27,6,5,85,124,14021
+4145,2013,16,0,3,80,126,13120
+4146,2016,27,2,1,85,126,14009
+4147,2007,13,5,9,90,124,13178
+4148,2012,5,3,8,86,121,12287
+4149,2017,10,6,2,84,130,13222
+4150,2000,33,7,7,90,122,15366
+4151,2012,3,3,0,90,128,13154
+4152,2014,2,10,9,90,123,14676
+4153,2014,28,10,2,82,121,15523
+4154,2002,35,6,7,80,120,14518
+4155,2005,21,7,6,89,129,14511
+4156,2015,5,4,7,81,128,13229
+4157,2007,11,0,1,82,128,12534
+4158,2001,31,1,8,84,120,13338
+4159,2002,29,10,3,85,129,14891
+4160,2015,32,0,9,89,124,14015
+4161,2000,10,10,4,83,120,13788
+4162,2001,17,2,4,80,125,13559
+4163,2009,0,9,4,89,121,13874
+4164,2016,36,3,10,82,130,14644
+4165,2003,19,9,7,86,130,14480
+4166,2013,26,4,8,86,127,13561
+4167,2008,23,0,1,87,124,12787
+4168,2017,21,0,3,85,129,13204
+4169,2004,19,4,6,89,123,13094
+4170,2003,28,9,9,82,121,14717
+4171,2012,12,1,0,86,126,13011
+4172,2008,0,8,9,87,122,13771
+4173,2015,36,5,7,87,127,14661
+4174,2007,27,5,1,86,123,13817
+4175,2012,9,1,3,86,128,12300
+4176,2004,3,6,10,82,121,13784
+4177,2005,32,7,6,83,130,14764
+4178,2018,14,6,7,86,120,14103
+4179,2000,6,6,5,90,120,13881
+4180,2010,8,0,6,80,123,12146
+4181,2003,19,1,7,90,127,13685
+4182,2005,7,7,10,86,129,13296
+4183,2018,21,3,7,81,129,13368
+4184,2018,7,10,7,82,124,15074
+4185,2014,2,7,0,90,125,12830
+4186,2016,23,8,9,82,121,14346
+4187,2018,9,8,10,81,130,14633
+4188,2002,36,2,1,85,122,14267
+4189,2013,8,10,6,81,123,14140
+4190,2016,27,9,7,88,123,15784
+4191,2004,4,4,8,82,130,13087
+4192,2011,11,3,3,85,130,13541
+4193,2018,18,6,10,80,126,14078
+4194,2003,5,1,7,87,127,12956
+4195,2006,16,2,2,90,125,12853
+4196,2013,37,10,7,86,129,16831
+4197,2016,10,6,6,81,122,13987
+4198,2011,26,5,6,83,122,13743
+4199,2013,0,8,4,82,120,13384
+4200,2016,23,9,9,81,123,15451
+4201,2014,38,3,6,90,126,14887
+4202,2008,21,10,5,87,120,14437
+4203,2007,12,6,1,85,130,13837
+4204,2006,17,4,6,88,130,14164
+4205,2002,5,0,4,83,128,11578
+4206,2002,35,4,10,85,124,14673
+4207,2002,37,0,6,88,122,14219
+4208,2018,13,8,8,86,124,14936
+4209,2010,22,4,10,82,128,14124
+4210,2009,5,9,0,84,125,14416
+4211,2011,18,6,8,80,121,14042
+4212,2009,27,9,4,86,129,15244
+4213,2006,7,4,5,89,129,12685
+4214,2000,21,1,4,89,123,13231
+4215,2016,18,1,10,88,129,13468
+4216,2003,24,6,4,80,121,13784
+4217,2016,25,9,3,89,126,15340
+4218,2001,38,0,5,85,120,13601
+4219,2005,22,6,5,81,123,14488
+4220,2009,1,9,5,81,127,13684
+4221,2015,10,7,5,88,124,13309
+4222,2015,21,6,1,80,121,13631
+4223,2017,8,1,8,83,120,13236
+4224,2014,23,6,5,81,130,13753
+4225,2007,2,1,8,89,126,11821
+4226,2013,15,0,1,86,130,11889
+4227,2000,9,7,4,83,125,13632
+4228,2007,32,10,6,88,122,15783
+4229,2010,17,9,1,87,122,14571
+4230,2007,7,5,5,83,125,13477
+4231,2009,5,6,6,89,122,13197
+4232,2005,26,5,9,81,121,14982
+4233,2011,15,4,6,84,120,14013
+4234,2002,10,4,3,81,128,12499
+4235,2005,20,8,4,80,122,13853
+4236,2008,18,0,3,81,128,12207
+4237,2012,31,7,4,86,129,15131
+4238,2003,17,1,4,90,129,13060
+4239,2002,28,7,10,88,121,15368
+4240,2003,12,7,1,84,123,13734
+4241,2009,9,8,0,88,121,14199
+4242,2018,4,1,0,83,129,12393
+4243,2014,30,2,6,86,129,13991
+4244,2014,8,2,6,86,126,13373
+4245,2010,31,6,9,84,120,15224
+4246,2002,29,1,10,84,125,13945
+4247,2000,32,7,5,89,126,14697
+4248,2006,31,10,9,87,126,15486
+4249,2014,7,0,8,84,120,12362
+4250,2012,38,6,7,85,129,15672
+4251,2011,37,9,1,83,128,16408
+4252,2008,14,7,5,85,126,14194
+4253,2018,29,5,1,82,129,14285
+4254,2005,26,5,7,88,124,13673
+4255,2010,34,2,7,89,128,14737
+4256,2004,3,7,9,86,125,13107
+4257,2005,25,9,9,84,126,15182
+4258,2014,5,8,6,83,121,13615
+4259,2006,2,8,5,90,123,13622
+4260,2006,25,0,9,86,129,13836
+4261,2017,15,3,3,80,120,12532
+4262,2017,5,4,6,87,130,12726
+4263,2014,28,0,0,81,123,13203
+4264,2001,16,9,3,84,123,14944
+4265,2018,5,6,0,88,121,12806
+4266,2002,31,6,8,84,125,15036
+4267,2010,2,8,2,83,125,13972
+4268,2015,8,5,9,82,129,14145
+4269,2009,29,0,10,84,126,14289
+4270,2010,20,2,1,85,128,13661
+4271,2006,11,4,10,90,123,13933
+4272,2001,1,4,0,86,125,12847
+4273,2018,2,6,6,84,122,12890
+4274,2017,16,10,4,84,122,15035
+4275,2002,5,8,4,81,129,13615
+4276,2007,34,0,2,85,122,14140
+4277,2015,37,4,0,88,127,15080
+4278,2005,34,1,10,90,124,14767
+4279,2007,32,4,2,83,127,13798
+4280,2003,11,2,4,81,129,13320
+4281,2015,18,4,1,84,128,13477
+4282,2013,27,4,10,83,121,14062
+4283,2003,24,3,1,89,122,12931
+4284,2009,28,10,6,87,121,15471
+4285,2004,32,7,4,83,129,14401
+4286,2012,11,3,6,87,123,12659
+4287,2018,28,8,8,89,122,15195
+4288,2006,6,1,3,86,121,12636
+4289,2010,5,6,5,81,127,13014
+4290,2011,0,9,4,85,121,13612
+4291,2014,26,10,4,83,129,14898
+4292,2001,2,6,1,86,126,12587
+4293,2017,4,6,5,83,126,13782
+4294,2000,9,6,8,87,120,13611
+4295,2004,19,3,3,81,123,13705
+4296,2012,35,6,3,90,121,15684
+4297,2008,8,5,5,86,129,13426
+4298,2009,32,3,9,89,127,14737
+4299,2004,22,8,7,80,129,14787
+4300,2002,32,8,10,83,121,15492
+4301,2008,4,2,0,90,129,12329
+4302,2000,14,10,10,88,122,15300
+4303,2011,25,8,0,86,128,14440
+4304,2012,19,9,9,82,120,15305
+4305,2008,19,10,6,87,130,14553
+4306,2001,27,10,6,90,121,15373
+4307,2009,37,7,8,89,129,15847
+4308,2013,15,2,2,87,121,12172
+4309,2015,28,4,0,82,120,13508
+4310,2002,14,3,3,86,123,13339
+4311,2012,20,7,1,88,123,13569
+4312,2003,23,0,9,86,124,13031
+4313,2000,36,3,9,90,130,15436
+4314,2009,21,7,10,84,127,15199
+4315,2007,16,8,8,80,127,14127
+4316,2014,9,10,5,81,130,14295
+4317,2012,34,6,6,89,121,14608
+4318,2003,35,2,9,86,127,15120
+4319,2004,22,10,6,81,122,14635
+4320,2014,33,6,2,81,125,14945
+4321,2011,10,2,1,83,127,13170
+4322,2014,12,1,4,85,126,12964
+4323,2004,15,10,9,89,130,14611
+4324,2003,19,9,6,83,122,15252
+4325,2011,20,9,3,85,125,14722
+4326,2002,30,1,3,87,128,13200
+4327,2009,15,4,7,88,127,13608
+4328,2004,33,6,8,80,128,15459
+4329,2001,6,6,1,86,120,12532
+4330,2009,30,2,3,90,130,13716
+4331,2007,1,3,0,88,128,12949
+4332,2004,0,2,9,81,126,13239
+4333,2017,18,8,6,80,123,14663
+4334,2003,1,5,2,89,121,12655
+4335,2005,35,8,8,83,130,15460
+4336,2017,16,0,8,85,125,12275
+4337,2003,26,8,4,83,129,14407
+4338,2016,7,1,9,84,127,12536
+4339,2005,4,0,8,89,123,12272
+4340,2014,34,0,3,80,126,14223
+4341,2004,27,8,6,84,124,15442
+4342,2005,7,5,10,81,122,13060
+4343,2001,11,10,2,84,130,14801
+4344,2011,7,1,10,87,126,12067
+4345,2012,26,1,7,87,121,13493
+4346,2010,0,5,0,80,124,12164
+4347,2014,3,0,1,81,126,12171
+4348,2010,21,8,1,84,130,14230
+4349,2015,27,0,9,87,121,14108
+4350,2015,22,7,8,85,130,15086
+4351,2004,21,6,7,86,120,13900
+4352,2018,1,5,2,90,124,13255
+4353,2007,29,1,2,85,121,14057
+4354,2013,30,9,2,87,129,15016
+4355,2013,26,6,0,85,127,13828
+4356,2015,30,9,7,89,123,15127
+4357,2005,29,7,5,88,127,15115
+4358,2004,13,8,5,80,125,14566
+4359,2017,20,5,7,83,127,14349
+4360,2012,27,0,2,88,129,12532
+4361,2018,31,9,7,84,123,16078
+4362,2003,14,0,2,89,121,12059
+4363,2000,4,8,9,85,122,13431
+4364,2015,26,2,5,89,122,13878
+4365,2006,37,9,1,90,129,15163
+4366,2006,13,0,8,85,125,11953
+4367,2015,2,8,0,87,127,13550
+4368,2009,21,0,4,86,130,12595
+4369,2002,19,7,0,81,124,13634
+4370,2013,36,0,6,86,124,13554
+4371,2017,5,2,0,84,127,12864
+4372,2002,21,1,5,82,129,12407
+4373,2014,10,7,4,85,124,13491
+4374,2009,8,0,0,90,123,11891
+4375,2016,20,2,5,86,123,13616
+4376,2010,12,5,7,86,128,14187
+4377,2002,9,9,10,88,129,14169
+4378,2009,14,7,10,86,130,14603
+4379,2013,14,3,8,87,120,13002
+4380,2018,22,1,0,81,121,13131
+4381,2007,1,5,3,86,124,13608
+4382,2004,29,2,0,82,122,13379
+4383,2013,4,8,4,81,126,13878
+4384,2018,3,0,0,81,121,11861
+4385,2013,33,2,3,90,128,13590
+4386,2007,18,7,6,88,120,13791
+4387,2005,0,2,5,80,126,12788
+4388,2002,37,2,9,88,124,14154
+4389,2001,12,1,4,87,122,11879
+4390,2001,12,3,2,87,122,12439
+4391,2002,33,10,8,88,127,15717
+4392,2008,12,1,0,81,125,11827
+4393,2006,28,5,10,88,123,15101
+4394,2000,5,7,9,84,121,13737
+4395,2001,36,5,7,86,121,14427
+4396,2014,32,10,4,89,123,16107
+4397,2015,29,6,8,84,124,15065
+4398,2014,2,6,4,80,120,13873
+4399,2000,33,9,8,84,123,15446
+4400,2015,11,7,10,90,123,14485
+4401,2015,20,2,4,87,127,13084
+4402,2017,12,4,9,80,125,13436
+4403,2010,8,9,7,86,128,13757
+4404,2009,20,4,3,87,127,13794
+4405,2000,8,8,3,89,123,13277
+4406,2008,0,3,3,84,123,12785
+4407,2009,30,9,2,83,127,15343
+4408,2015,24,10,10,83,124,15795
+4409,2010,18,2,0,86,130,12759
+4410,2012,17,8,3,86,123,14339
+4411,2015,21,3,3,83,128,12780
+4412,2017,31,3,6,80,120,13706
+4413,2014,32,1,1,88,125,13686
+4414,2014,1,7,3,84,130,13713
+4415,2004,12,3,4,85,123,12802
+4416,2000,38,6,7,84,120,15053
+4417,2004,38,7,9,87,121,15659
+4418,2016,8,1,4,86,121,12926
+4419,2002,12,6,2,88,124,13465
+4420,2009,22,4,0,85,120,13337
+4421,2008,13,10,1,83,123,14196
+4422,2011,18,6,7,82,128,14167
+4423,2017,33,5,0,87,125,15183
+4424,2000,24,0,10,81,122,12717
+4425,2011,10,7,2,82,120,13843
+4426,2002,11,10,3,89,125,14223
+4427,2017,38,7,7,86,130,15795
+4428,2014,25,5,5,89,125,14442
+4429,2008,20,9,5,89,120,14169
+4430,2018,33,1,8,84,121,14727
+4431,2011,38,10,5,86,121,15636
+4432,2002,18,9,10,85,122,14772
+4433,2016,8,3,1,81,122,12660
+4434,2003,38,6,3,89,124,15923
+4435,2009,22,5,2,84,126,13674
+4436,2001,38,4,10,80,127,14807
+4437,2011,19,5,4,84,125,14106
+4438,2008,16,8,9,81,130,14204
+4439,2009,5,1,2,83,129,12727
+4440,2018,4,0,0,90,122,12314
+4441,2007,29,2,10,86,120,13525
+4442,2017,31,8,6,82,121,14777
+4443,2003,30,6,6,90,122,14119
+4444,2013,37,9,6,82,127,15901
+4445,2000,37,4,2,83,124,15315
+4446,2007,1,2,7,81,123,12905
+4447,2001,33,7,2,84,130,15136
+4448,2011,24,5,10,82,125,14323
+4449,2011,27,7,9,83,122,14892
+4450,2003,12,4,6,88,125,13508
+4451,2008,26,0,9,81,128,13003
+4452,2016,0,3,4,90,127,12549
+4453,2007,7,4,3,82,129,12933
+4454,2016,19,8,4,88,127,15053
+4455,2005,24,0,7,86,128,13281
+4456,2003,32,9,6,88,125,15813
+4457,2016,38,7,7,87,128,16288
+4458,2011,28,5,3,83,129,13650
+4459,2005,37,4,1,82,125,14031
+4460,2007,4,0,6,84,129,12316
+4461,2005,18,0,6,90,124,12742
+4462,2013,11,9,2,86,124,13610
+4463,2014,3,9,7,82,126,14231
+4464,2004,2,2,5,81,129,12340
+4465,2009,9,1,0,90,125,12768
+4466,2012,32,1,6,84,125,13780
+4467,2001,33,5,1,86,127,13899
+4468,2007,0,8,9,82,120,14108
+4469,2008,10,1,0,85,130,12299
+4470,2003,13,10,7,85,129,14388
+4471,2007,28,6,10,83,121,15029
+4472,2014,25,8,9,88,128,14663
+4473,2018,31,5,0,83,127,14385
+4474,2011,4,7,9,80,127,14030
+4475,2016,16,0,9,83,127,12951
+4476,2002,5,1,1,83,126,11491
+4477,2004,29,0,6,83,130,13577
+4478,2014,6,3,4,85,120,12115
+4479,2016,36,10,9,83,130,16720
+4480,2013,14,0,1,82,125,12172
+4481,2008,35,0,4,83,120,14311
+4482,2016,3,8,5,87,121,13921
+4483,2002,30,3,1,88,120,14350
+4484,2011,24,4,5,81,121,13585
+4485,2003,0,1,7,87,126,12710
+4486,2006,21,8,3,90,130,14844
+4487,2011,28,10,3,89,123,15982
+4488,2014,35,10,7,90,120,16500
+4489,2003,11,7,10,84,120,14504
+4490,2016,3,8,7,88,130,13824
+4491,2006,19,4,8,89,127,13604
+4492,2006,3,1,9,87,127,12641
+4493,2001,29,4,1,84,122,13962
+4494,2017,7,8,2,87,127,14173
+4495,2005,6,2,2,86,130,12834
+4496,2013,10,9,5,87,125,14614
+4497,2007,17,8,2,83,129,14156
+4498,2000,17,2,0,85,125,13379
+4499,2014,1,4,4,83,127,12478
+4500,2007,8,0,9,84,121,12164
+4501,2002,0,9,5,87,128,13414
+4502,2008,24,1,2,84,121,13702
+4503,2006,5,9,8,90,121,13549
+4504,2000,14,0,1,80,130,11747
+4505,2016,24,10,6,81,124,15590
+4506,2005,21,7,2,85,124,14137
+4507,2008,36,4,0,86,126,14309
+4508,2014,18,3,8,89,122,13606
+4509,2003,32,8,8,82,129,15940
+4510,2006,30,1,8,82,125,13806
+4511,2006,7,10,6,85,123,14092
+4512,2002,18,5,5,88,128,13841
+4513,2010,0,3,8,81,128,12302
+4514,2011,26,7,6,80,130,15205
+4515,2007,19,4,9,90,125,13401
+4516,2014,17,4,3,86,125,13008
+4517,2010,36,1,10,89,127,14854
+4518,2002,23,5,5,82,130,14369
+4519,2017,14,9,10,87,123,14789
+4520,2006,2,5,5,84,124,13084
+4521,2005,37,1,6,84,120,13648
+4522,2011,2,1,1,80,127,12586
+4523,2000,30,10,2,82,125,15123
+4524,2016,7,9,0,83,123,13487
+4525,2010,22,4,8,89,130,13818
+4526,2004,18,5,0,88,125,13962
+4527,2001,34,2,9,89,129,14923
+4528,2005,37,10,8,86,128,16584
+4529,2015,25,4,1,85,124,13886
+4530,2015,28,10,1,87,126,15909
+4531,2002,32,2,8,87,122,14157
+4532,2013,15,6,3,82,130,14213
+4533,2017,3,9,1,89,126,14485
+4534,2000,20,4,0,83,126,12692
+4535,2007,37,5,5,81,122,14932
+4536,2010,27,8,8,87,130,14865
+4537,2004,35,3,8,82,130,14773
+4538,2001,33,10,10,80,123,15876
+4539,2018,22,10,1,88,123,14370
+4540,2004,8,0,0,81,124,12456
+4541,2002,37,8,0,81,125,15943
+4542,2002,6,2,6,82,120,12313
+4543,2015,17,0,8,83,123,13051
+4544,2017,17,6,2,86,123,13634
+4545,2015,23,4,5,86,121,14069
+4546,2006,21,5,3,80,129,14023
+4547,2006,21,9,10,88,129,14765
+4548,2012,37,4,3,83,123,15294
+4549,2005,25,6,9,84,121,14131
+4550,2005,7,2,9,82,127,12548
+4551,2016,10,5,10,89,126,14038
+4552,2006,31,7,1,80,120,14367
+4553,2017,17,5,6,85,126,13131
+4554,2010,18,7,1,80,129,14196
+4555,2008,16,10,6,87,129,14514
+4556,2005,24,10,1,88,123,14307
+4557,2010,29,6,9,90,125,14622
+4558,2009,17,10,9,87,122,14681
+4559,2016,36,6,0,83,128,14387
+4560,2006,29,10,4,83,130,16091
+4561,2018,34,8,3,82,122,15138
+4562,2000,31,2,2,81,121,14361
+4563,2002,2,9,7,84,129,14174
+4564,2004,17,7,8,89,127,14875
+4565,2014,22,4,6,85,130,13340
+4566,2013,27,8,2,87,121,15034
+4567,2004,2,7,1,83,123,13414
+4568,2010,3,7,8,85,129,14112
+4569,2000,22,7,7,83,125,13789
+4570,2016,14,10,10,80,129,14875
+4571,2003,36,3,3,83,122,14441
+4572,2000,29,9,3,86,121,14875
+4573,2015,0,6,10,85,122,14048
+4574,2014,15,8,8,90,121,14886
+4575,2002,3,0,0,85,129,11845
+4576,2013,2,3,0,89,127,12999
+4577,2000,28,6,8,88,126,14190
+4578,2006,23,2,3,82,125,13262
+4579,2008,25,8,1,88,121,14194
+4580,2018,23,2,10,80,125,13410
+4581,2017,28,7,1,82,123,14596
+4582,2013,25,10,6,89,129,15962
+4583,2003,10,6,10,84,127,13409
+4584,2006,4,10,3,80,129,13611
+4585,2012,11,9,10,86,127,14400
+4586,2008,17,6,7,86,120,13948
+4587,2001,0,2,5,84,126,12914
+4588,2014,0,8,0,87,129,13264
+4589,2016,1,10,4,89,123,13654
+4590,2011,28,2,2,80,123,14065
+4591,2008,30,4,1,88,129,13503
+4592,2011,22,2,9,81,126,13650
+4593,2011,22,7,4,87,123,14963
+4594,2007,22,8,4,80,125,14504
+4595,2005,7,8,10,80,129,14363
+4596,2017,24,7,5,81,127,14155
+4597,2007,17,10,8,82,130,14641
+4598,2005,8,10,0,87,123,14460
+4599,2010,36,8,8,82,125,16045
+4600,2015,12,5,10,88,121,13325
+4601,2014,2,4,3,88,121,13449
+4602,2009,31,4,3,86,127,14926
+4603,2017,33,5,10,82,124,14644
+4604,2006,28,8,0,83,120,14820
+4605,2002,15,3,5,88,130,12653
+4606,2010,20,2,8,89,129,13784
+4607,2008,6,6,7,85,126,13903
+4608,2001,23,8,5,88,126,14255
+4609,2018,15,2,9,83,120,13277
+4610,2010,4,4,1,84,121,13105
+4611,2015,21,1,4,86,128,13445
+4612,2008,2,8,10,90,124,14643
+4613,2015,36,1,0,90,130,13645
+4614,2006,37,10,2,82,129,15896
+4615,2004,31,6,5,85,123,15016
+4616,2018,8,2,2,89,121,12928
+4617,2002,36,4,8,80,122,15256
+4618,2012,2,0,4,87,122,12295
+4619,2008,9,3,8,81,123,12759
+4620,2010,30,7,5,81,128,14306
+4621,2008,4,0,7,86,129,12129
+4622,2002,26,0,7,88,122,13504
+4623,2013,34,3,5,90,128,14484
+4624,2010,37,2,9,88,124,15328
+4625,2009,10,3,7,80,128,13656
+4626,2016,9,4,6,84,128,13327
+4627,2007,9,9,3,81,127,13546
+4628,2016,5,10,1,83,124,13449
+4629,2004,0,4,8,86,128,12630
+4630,2003,11,4,3,82,125,12783
+4631,2011,20,4,5,81,122,13468
+4632,2002,5,8,4,89,125,13129
+4633,2006,1,9,5,81,130,14442
+4634,2000,15,7,9,90,130,14197
+4635,2001,25,5,7,90,127,14241
+4636,2012,5,7,7,80,127,13080
+4637,2001,31,2,1,87,120,13458
+4638,2004,14,5,4,86,120,13798
+4639,2003,32,0,5,89,130,13159
+4640,2002,4,1,7,85,128,12290
+4641,2009,36,10,10,84,130,16110
+4642,2016,32,1,2,87,128,13758
+4643,2010,29,0,6,85,122,12816
+4644,2007,13,3,9,89,122,12746
+4645,2010,30,9,4,83,121,15037
+4646,2001,25,1,2,84,130,13658
+4647,2016,14,10,3,83,126,14145
+4648,2011,31,0,10,82,124,14433
+4649,2003,38,3,0,86,121,14107
+4650,2011,4,1,10,83,122,11937
+4651,2013,6,6,1,82,123,13849
+4652,2010,3,6,7,84,120,13920
+4653,2013,37,8,7,84,128,15876
+4654,2017,37,10,4,89,121,16294
+4655,2000,28,2,5,82,130,13201
+4656,2013,12,10,7,89,120,14491
+4657,2013,10,5,5,89,121,12990
+4658,2015,7,5,2,88,123,13381
+4659,2018,30,3,2,88,123,13741
+4660,2004,36,7,10,86,121,16024
+4661,2003,24,4,8,89,127,14650
+4662,2012,15,5,6,80,121,13331
+4663,2003,24,0,8,84,127,13683
+4664,2007,31,0,0,84,127,13940
+4665,2018,0,1,4,88,121,12864
+4666,2016,8,0,3,82,127,12814
+4667,2010,5,2,5,80,128,12813
+4668,2013,7,0,0,83,123,12095
+4669,2013,36,0,5,84,121,13856
+4670,2007,11,4,10,82,127,13794
+4671,2005,11,4,3,89,124,13326
+4672,2014,25,9,1,90,125,15103
+4673,2015,19,8,0,85,127,14833
+4674,2011,20,9,3,86,129,15127
+4675,2016,16,3,9,82,130,13446
+4676,2001,9,1,0,84,127,11575
+4677,2010,23,4,5,85,127,13820
+4678,2008,18,1,0,83,120,12097
+4679,2015,34,4,8,86,130,14464
+4680,2018,9,3,10,83,130,12706
+4681,2010,8,3,9,80,123,12653
+4682,2008,19,10,8,88,128,15025
+4683,2007,33,10,2,88,130,15081
+4684,2005,2,8,2,89,122,13456
+4685,2000,1,5,10,80,121,13373
+4686,2016,26,5,9,81,126,14686
+4687,2004,30,6,6,89,124,14508
+4688,2006,7,3,10,81,121,12518
+4689,2010,7,0,6,83,126,11893
+4690,2002,19,7,1,90,121,13839
+4691,2013,28,3,3,84,120,13325
+4692,2004,16,1,2,85,128,12884
+4693,2008,13,7,9,89,122,14473
+4694,2007,6,3,4,86,124,13241
+4695,2009,11,0,4,83,125,12808
+4696,2015,34,8,3,80,122,15869
+4697,2018,31,9,7,82,120,14917
+4698,2017,3,0,8,85,125,12046
+4699,2010,38,3,2,83,123,14112
+4700,2017,12,4,3,83,126,13283
+4701,2015,5,9,9,81,121,14859
+4702,2001,29,6,5,88,128,14258
+4703,2013,14,8,10,86,123,14421
+4704,2001,3,3,4,82,127,12497
+4705,2011,28,9,8,89,120,14862
+4706,2014,32,5,0,87,128,14094
+4707,2001,25,9,10,83,122,15058
+4708,2008,29,7,10,83,130,14994
+4709,2017,0,7,8,87,126,13700
+4710,2010,28,5,9,80,127,14801
+4711,2017,25,6,3,81,123,13761
+4712,2002,1,1,0,88,130,12149
+4713,2017,14,7,9,84,128,13816
+4714,2010,4,4,4,83,127,12653
+4715,2013,34,3,1,88,123,14120
+4716,2002,0,5,8,86,125,13064
+4717,2014,3,0,4,89,123,12092
+4718,2006,28,5,8,84,125,14362
+4719,2012,7,2,1,82,120,12522
+4720,2011,36,1,9,82,122,14494
+4721,2010,24,4,8,85,124,14522
+4722,2008,14,7,2,84,130,13306
+4723,2012,4,7,1,81,121,12725
+4724,2003,28,6,5,86,130,15076
+4725,2015,16,4,5,89,124,13323
+4726,2010,1,2,2,82,123,12297
+4727,2018,3,7,5,89,122,13857
+4728,2009,7,7,6,85,128,13232
+4729,2000,33,8,1,87,123,15272
+4730,2005,21,7,3,81,122,14030
+4731,2001,21,2,3,81,126,12484
+4732,2006,15,1,2,85,130,13234
+4733,2011,15,4,1,81,126,13026
+4734,2016,37,3,2,82,123,14422
+4735,2007,6,1,4,88,126,12602
+4736,2001,3,8,5,90,128,13900
+4737,2012,10,7,8,90,120,14440
+4738,2016,19,3,2,81,129,13244
+4739,2014,9,10,0,81,122,14756
+4740,2009,15,6,5,87,120,13128
+4741,2008,36,6,3,80,120,15193
+4742,2000,12,5,2,84,121,12704
+4743,2005,8,8,10,88,126,14041
+4744,2007,5,6,0,82,122,13356
+4745,2016,38,7,8,80,122,16017
+4746,2007,12,4,2,80,127,13047
+4747,2008,16,0,4,84,121,12885
+4748,2009,0,3,9,83,127,13485
+4749,2002,16,10,9,87,120,14962
+4750,2017,4,0,4,87,123,11492
+4751,2002,21,9,2,90,120,13927
+4752,2018,27,0,4,80,125,13356
+4753,2002,4,10,6,85,126,13624
+4754,2009,12,1,1,82,123,12632
+4755,2009,37,2,10,80,128,14852
+4756,2011,9,3,0,82,124,13140
+4757,2003,16,3,7,80,130,13649
+4758,2008,25,2,6,84,121,13416
+4759,2006,28,5,1,83,130,13531
+4760,2003,9,0,1,84,124,11921
+4761,2015,32,5,8,90,127,14886
+4762,2001,37,10,1,87,126,15830
+4763,2008,6,2,10,86,125,12591
+4764,2008,15,5,5,89,123,13065
+4765,2000,38,2,1,86,126,14847
+4766,2010,28,9,5,87,126,15487
+4767,2002,9,3,6,86,124,12533
+4768,2006,38,5,1,84,125,14852
+4769,2001,33,2,1,86,122,14510
+4770,2000,24,0,7,80,123,12946
+4771,2004,22,6,0,90,129,14311
+4772,2005,5,0,0,84,125,12011
+4773,2006,24,2,8,89,122,12965
+4774,2006,27,0,5,89,123,13506
+4775,2015,31,8,10,83,128,14885
+4776,2009,4,8,10,84,121,13768
+4777,2009,10,3,0,83,122,12783
+4778,2004,7,9,3,82,129,13353
+4779,2005,22,10,3,87,126,14669
+4780,2011,36,4,7,81,130,14419
+4781,2015,15,6,7,84,125,13397
+4782,2012,1,9,1,87,124,13890
+4783,2011,22,3,10,90,120,14043
+4784,2005,27,4,7,84,127,14666
+4785,2014,31,9,8,88,130,15411
+4786,2008,5,4,6,90,121,12646
+4787,2012,34,3,5,85,125,14689
+4788,2008,11,2,4,82,129,12342
+4789,2008,15,1,6,85,130,12184
+4790,2001,18,4,9,84,121,13264
+4791,2005,19,5,5,84,129,13518
+4792,2012,6,10,1,80,129,14353
+4793,2015,32,8,5,80,124,15686
+4794,2017,37,5,5,81,129,15651
+4795,2008,25,8,7,82,124,14606
+4796,2005,33,6,5,84,123,15180
+4797,2002,13,9,6,85,129,14366
+4798,2007,36,4,6,90,122,15231
+4799,2004,16,7,10,89,123,13642
+4800,2015,0,6,8,87,123,13334
+4801,2015,20,9,2,85,126,14950
+4802,2008,21,4,3,85,120,13421
+4803,2003,17,8,5,87,120,14004
+4804,2015,6,6,10,84,122,14187
+4805,2004,30,0,8,80,127,13848
+4806,2006,31,9,2,81,130,15666
+4807,2008,35,7,8,88,128,15526
+4808,2012,10,9,9,83,128,14302
+4809,2008,33,2,0,80,125,13222
+4810,2014,28,2,0,84,130,13535
+4811,2015,15,0,5,88,124,11949
+4812,2002,18,9,2,87,122,14130
+4813,2005,19,0,7,82,125,12309
+4814,2000,28,0,0,88,126,13059
+4815,2015,10,8,9,82,127,14089
+4816,2012,17,3,3,86,121,13147
+4817,2004,2,6,1,89,121,13220
+4818,2001,2,2,2,87,122,11788
+4819,2003,21,1,9,87,127,13886
+4820,2015,31,2,1,88,122,13292
+4821,2002,33,6,5,89,124,14313
+4822,2004,13,8,7,81,128,13932
+4823,2009,35,10,0,89,129,15288
+4824,2002,28,6,10,84,124,14647
+4825,2016,11,0,0,86,129,12554
+4826,2012,10,9,9,86,130,14076
+4827,2014,6,1,0,83,120,12505
+4828,2004,24,0,7,80,128,13750
+4829,2001,11,10,1,90,123,14742
+4830,2003,36,5,10,80,125,14579
+4831,2017,27,9,0,85,124,14421
+4832,2004,38,8,9,80,130,16645
+4833,2003,35,9,7,82,125,15710
+4834,2017,35,7,2,88,123,15747
+4835,2017,35,3,2,82,128,14149
+4836,2008,38,5,4,90,129,15316
+4837,2014,35,2,0,83,124,13811
+4838,2007,31,0,8,81,130,13838
+4839,2013,12,4,9,90,129,12984
+4840,2007,36,0,4,84,129,14198
+4841,2001,16,1,3,80,124,12619
+4842,2003,1,1,6,81,127,12150
+4843,2006,36,2,0,85,122,13481
+4844,2011,21,6,6,82,123,14386
+4845,2015,37,4,10,89,125,14692
+4846,2002,18,6,0,87,128,13293
+4847,2007,12,7,8,84,128,14510
+4848,2009,35,6,7,86,129,14885
+4849,2007,15,3,4,87,124,12715
+4850,2011,7,6,6,85,125,13768
+4851,2018,30,0,10,87,129,14064
+4852,2014,24,4,2,87,121,13858
+4853,2009,33,4,9,80,126,15355
+4854,2015,13,2,7,81,124,12830
+4855,2016,12,2,10,88,128,13252
+4856,2015,27,10,4,88,127,15366
+4857,2010,22,2,7,89,125,13328
+4858,2001,34,10,3,84,121,15998
+4859,2003,17,5,9,86,125,13966
+4860,2016,34,2,2,80,126,14461
+4861,2016,26,9,4,85,128,14820
+4862,2011,25,3,10,80,130,14118
+4863,2018,23,6,8,80,129,14668
+4864,2013,19,10,7,81,128,15217
+4865,2006,10,7,4,90,121,14090
+4866,2017,5,0,1,87,123,12377
+4867,2016,11,9,7,80,122,13960
+4868,2000,12,1,6,85,128,12124
+4869,2017,22,3,5,87,127,13847
+4870,2004,25,3,5,84,121,13173
+4871,2009,16,3,2,88,125,13693
+4872,2008,19,6,2,88,122,14205
+4873,2014,15,10,4,88,120,14980
+4874,2015,0,8,7,82,123,14317
+4875,2001,30,2,9,84,121,14526
+4876,2012,2,8,1,85,124,12928
+4877,2017,11,7,5,84,126,13728
+4878,2013,17,0,2,85,125,12762
+4879,2000,37,6,3,88,125,15690
+4880,2005,19,8,4,88,125,14483
+4881,2010,23,10,2,83,124,14927
+4882,2001,35,9,7,81,126,16204
+4883,2016,32,7,8,84,122,15383
+4884,2008,7,6,0,84,129,12840
+4885,2012,17,6,7,86,120,13968
+4886,2017,30,7,6,83,128,15661
+4887,2010,30,4,7,88,128,14060
+4888,2018,18,7,8,84,127,14847
+4889,2006,32,0,3,85,120,13376
+4890,2015,29,2,9,89,122,13919
+4891,2002,28,10,10,90,121,15651
+4892,2011,24,10,8,80,124,15660
+4893,2006,29,7,3,85,125,15246
+4894,2006,1,2,0,88,127,11851
+4895,2011,29,5,2,80,128,14537
+4896,2002,17,9,4,87,129,14720
+4897,2009,30,0,4,87,123,13812
+4898,2007,11,7,4,88,129,13538
+4899,2017,16,7,8,82,124,14207
+4900,2001,5,1,7,80,120,12368
+4901,2013,13,3,8,87,120,12579
+4902,2012,37,10,3,88,122,16597
+4903,2016,30,0,10,89,129,13434
+4904,2016,20,8,1,90,120,14679
+4905,2012,10,9,7,82,129,14580
+4906,2009,38,2,1,90,124,14270
+4907,2014,29,10,2,83,121,15981
+4908,2000,4,0,0,80,130,12471
+4909,2016,24,5,3,82,125,13998
+4910,2014,33,6,4,85,127,15328
+4911,2018,26,6,3,81,120,14070
+4912,2018,29,8,0,83,120,14829
+4913,2001,27,1,1,85,121,13199
+4914,2000,14,9,3,82,120,13808
+4915,2001,1,9,5,89,121,13651
+4916,2017,37,3,2,84,126,14580
+4917,2016,20,7,1,84,121,14692
+4918,2008,13,9,0,85,124,14068
+4919,2006,19,0,8,86,123,12499
+4920,2014,11,10,1,88,126,14688
+4921,2011,17,3,10,82,125,13746
+4922,2014,24,1,3,87,121,12663
+4923,2017,14,3,8,80,128,13662
+4924,2006,30,8,6,81,128,15685
+4925,2011,24,6,4,87,124,13623
+4926,2007,36,3,6,81,125,14114
+4927,2001,34,5,0,88,125,15067
+4928,2015,23,8,9,87,124,15264
+4929,2009,25,1,4,88,129,13812
+4930,2016,29,9,1,84,126,15503
+4931,2012,32,1,5,84,130,14514
+4932,2009,9,3,6,87,122,12436
+4933,2016,30,4,10,83,128,14593
+4934,2004,2,6,2,82,130,13537
+4935,2001,37,9,6,89,129,15887
+4936,2012,38,1,2,80,122,14827
+4937,2004,12,0,9,84,120,12043
+4938,2003,23,3,10,85,129,13965
+4939,2013,13,7,6,85,122,13572
+4940,2015,20,7,3,90,125,14587
+4941,2011,4,8,8,85,127,14472
+4942,2005,23,5,8,86,129,14422
+4943,2007,4,5,4,84,122,12824
+4944,2007,35,4,0,87,126,14220
+4945,2011,3,7,10,81,127,14438
+4946,2014,15,4,5,90,124,13652
+4947,2013,23,3,10,88,125,13504
+4948,2007,34,4,5,89,128,15160
+4949,2006,35,7,10,89,125,15100
+4950,2009,12,1,2,81,123,12677
+4951,2005,9,7,0,87,122,13460
+4952,2018,32,1,3,89,122,14046
+4953,2002,29,4,7,87,126,13927
+4954,2008,11,7,7,85,127,13667
+4955,2012,36,2,9,82,124,14965
+4956,2010,22,6,5,89,127,14575
+4957,2011,34,2,7,81,128,14954
+4958,2004,13,9,8,90,120,14073
+4959,2002,34,4,4,84,126,14922
+4960,2016,1,7,1,83,122,12817
+4961,2008,4,1,0,88,124,12214
+4962,2018,27,6,1,80,129,14842
+4963,2011,2,8,4,83,122,14312
+4964,2015,33,4,5,89,124,13958
+4965,2010,0,4,7,80,126,13451
+4966,2007,2,9,0,84,126,13455
+4967,2006,15,3,0,80,122,13472
+4968,2000,8,6,2,87,123,12915
+4969,2017,28,4,2,87,124,14169
+4970,2004,24,9,9,82,124,14962
+4971,2014,29,9,5,86,126,15955
+4972,2007,21,1,5,87,121,13169
+4973,2000,37,6,0,89,120,15643
+4974,2013,15,8,9,85,124,13788
+4975,2005,15,1,7,89,130,12869
+4976,2005,36,6,7,80,122,15641
+4977,2000,6,3,9,83,127,13206
+4978,2003,23,0,3,83,121,12952
+4979,2015,17,7,6,85,130,14701
+4980,2001,33,5,6,90,120,14256
+4981,2008,28,3,5,83,128,14070
+4982,2014,30,0,4,82,128,13966
+4983,2009,8,0,0,88,130,12172
+4984,2017,3,3,5,80,124,13230
+4985,2003,10,7,6,89,129,13962
+4986,2009,0,10,2,82,125,13350
+4987,2005,12,5,9,80,122,13442
+4988,2007,10,4,2,87,124,13363
+4989,2014,27,5,1,89,126,13884
+4990,2014,22,9,1,85,126,14007
+4991,2009,10,6,4,84,121,13988
+4992,2011,12,9,4,89,124,14638
+4993,2018,17,10,5,81,129,15417
+4994,2010,26,1,4,90,121,13852
+4995,2007,17,6,3,90,125,13539
+4996,2016,7,10,0,85,129,14757
+4997,2017,6,10,5,90,125,14102
+4998,2010,37,3,5,81,128,14313
+4999,2018,9,1,9,90,127,12770
diff --git a/House price prediction/utils.py b/House price prediction/utils.py
new file mode 100644
index 0000000..87dd186
--- /dev/null
+++ b/House price prediction/utils.py	
@@ -0,0 +1,43 @@
+import matplotlib.pyplot as plt
+
+column_names = ['serial', 'date', 'age', 'distance', 'stores', 'latitude', 'longitude', 'price']
+
+def plot_loss(history):
+    h = history.history
+    x_lim = len(h['loss'])
+    plt.figure(figsize=(8, 8))
+    plt.plot(range(x_lim), h['val_loss'], label = 'Validation Loss')
+    plt.plot(range(x_lim), h['loss'], label = 'Training Loss')
+    plt.xlabel('Epochs')
+    plt.ylabel('Loss')
+    plt.legend()
+    plt.show()
+    return
+
+def plot_predictions(preds, y_test):
+    plt.figure(figsize=(8, 8))
+    plt.plot(preds, y_test, 'ro')
+    plt.xlabel('Preds')
+    plt.ylabel('Labels')
+    plt.xlim([-0.5, 0.5])
+    plt.ylim([-0.5, 0.5])
+    plt.plot([-0.5, 0.5], [-0.5, 0.5], 'b--')
+    plt.show()
+    return
+
+def compare_predictions(preds1, preds2, y_test):
+    plt.figure(figsize=(8, 8))
+    plt.plot(preds1, y_test, 'ro', label='Untrained Model')
+    plt.plot(preds2, y_test, 'go', label='Trained Model')
+    plt.xlabel('Preds')
+    plt.ylabel('Labels')
+    
+    y_min = min(min(y_test), min(preds1), min(preds2))
+    y_max = max(max(y_test), max(preds1), max(preds2))
+    
+    plt.xlim([y_min, y_max])
+    plt.ylim([y_min, y_max])
+    plt.plot([y_min, y_max], [y_min, y_max], 'b--')
+    plt.legend()
+    plt.show()
+    return
\ No newline at end of file