ISACWaveformDesign.m

%[text] # Symbolic Waveform Design for Integrated Sensing and Communications (ISAC)
%[text] Derive the joint radar-communications tradeoff for an OFDM ISAC waveform from first principles, then validate the design with waveform generation, spectral analysis, range-Doppler processing, and EVM measurement.
%[text] **Workflow:** First-principles physics $\\to$ symbolic ambiguity function $\\to$ Pareto frontier (sensing vs. comms) $\\to$ optimal pilot/data allocation $\\to$ waveform generation $\\to$ spectral verification $\\to$ range-Doppler map $\\to$ EVM
%[text] For a full system-level MIMO-OFDM ISAC simulation, see [Integrated Sensing and Communication II: Communication-Centric Approach Using MIMO-OFDM](https://www.mathworks.com/help/phased/ug/integrated-sensing-and-communication-2-communication-centric-approach-using-mimo-ofdm.html).
%[text] Requires: Symbolic Math Toolbox™, Communications Toolbox™, Signal Processing Toolbox™
%%
%[text] ## 1. OFDM Signal Model
%[text] An OFDM waveform partitions a wideband channel into $N$ narrowband subcarriers spaced by $\\Delta f$. In an ISAC system, some subcarriers carry known pilot symbols (used for radar sensing) and others carry random data symbols (used for communications). The split between the two is the fundamental design variable.
%[text] We define the signal model symbolically to derive the sensing and communications performance as closed-form expressions.
syms N positive integer           % total number of subcarriers
syms K positive integer           % number of pilot subcarriers
syms Delta_f positive             % subcarrier spacing [Hz]
syms T_sym positive               % useful OFDM symbol duration = 1/Delta_f [s]
syms T_cp positive                % cyclic prefix duration [s]
syms T positive                   % total symbol duration T_sym + T_cp [s]
syms M positive integer           % number of OFDM symbols in one frame
syms P_total positive             % total transmit power [W]
syms sigma2 positive              % noise variance (noise power) [W]
T_sym_def = 1 / Delta_f;
B = N * Delta_f;                  % total occupied bandwidth [Hz]
syms alpha positive               % alpha = K/N, pilot fraction (0,1)
P_pilot = P_total / N;           % power per pilot subcarrier
P_data  = P_total / N;           % power per data subcarrier (uniform for now)
%%
%[text] ## 2. Radar Performance: Cross-Ambiguity Function
%[text] The radar receiver correlates the received signal with the known pilot symbols to estimate target range (delay $\\tau$) and velocity (Doppler shift $\\nu$). The resolution is governed by the cross-ambiguity function, which we derive symbolically for uniformly-spaced OFDM pilots.
%[text] For $K$ pilot subcarriers with uniform spacing $N/K$ within a frame of $M$ OFDM symbols, the squared ambiguity function factors into a product of frequency-domain and time-domain terms:
%[text] $ |\\chi(\\tau, \\nu)|^2 = |A\_f(\\tau)|^2 \\cdot |A\_t(\\nu)|^2 $
%[text] where $A\_f$ captures range resolution (from pilot bandwidth) and $A\_t$ captures Doppler resolution (from frame duration).
syms tau nu real                  % delay [s] and Doppler shift [Hz]
A_f = (1/K) * symsum(exp(-1j*2*sym(pi)*sym('k')*(N/K)*Delta_f*tau), sym('k'), 0, K-1);
A_f = simplify(A_f);
disp('Frequency-domain ambiguity A_f(tau):') %[output:05335980]
disp(A_f) %[output:59af4e03]
A_f_closed = (1/K) * (1 - exp(-1j*2*sym(pi)*N*Delta_f*tau)) / ...
             (1 - exp(-1j*2*sym(pi)*(N/K)*Delta_f*tau));
A_f_closed = simplify(A_f_closed);
disp('Closed-form (geometric series):') %[output:8c32ddb5]
disp(A_f_closed) %[output:63719c4e]
%%
%[text] ### Dirichlet Kernel and Range Resolution
%[text] The magnitude-squared of the frequency-domain term is a Dirichlet kernel. Using $B = N \\Delta f$:
%[text] $ |A\_f(\\tau)|^2 = \\frac{\\sin^2(\\pi B \\tau)}{K^2 \\sin^2(\\pi B \\tau / K)} $
%[text] The mainlobe width (range resolution) depends on the total bandwidth $B$, but the sidelobe structure depends on $K$. More pilots means lower sidelobes and better target discrimination at the cost of data throughput.
syms B_sym positive
A_f_mag2 = sin(sym(pi)*B_sym*tau)^2 / (K^2 * sin(sym(pi)*B_sym*tau/K)^2);
disp('|A_f(tau)|^2 (Dirichlet kernel):') %[output:3a05fb2d]
disp(A_f_mag2) %[output:634dc154]
syms c_light positive             % speed of light
delta_R = c_light / (2 * B_sym);
disp('Range resolution (monostatic):') %[output:620acca3]
disp(delta_R) %[output:3db19f6e]
%%
%[text] ### Doppler Resolution
%[text] The time-domain ambiguity (Doppler resolution) comes from the coherent integration across $M$ OFDM symbols:
%[text] $ |A\_t(\\nu)|^2 = \\frac{\\sin^2(\\pi M T \\nu)}{M^2 \\sin^2(\\pi T \\nu)} $
%[text] Doppler resolution depends on the total frame duration $MT$ and is independent of pilot density - all $M$ symbols contribute to Doppler processing regardless of whether they carry pilots or data.
A_t_mag2 = sin(sym(pi)*M*T*nu)^2 / (M^2 * sin(sym(pi)*T*nu)^2);
syms f_c positive                 % carrier frequency [Hz]
delta_v = c_light / (2 * f_c * M * T);
disp('|A_t(nu)|^2:') %[output:44d7e3a8]
disp(A_t_mag2) %[output:632cad7d]
disp('Velocity resolution:') %[output:1c5edca0]
disp(delta_v) %[output:26b5d50e]
%%
%[text] ### Radar SNR
%[text] The radar signal-to-noise ratio at the matched filter output depends on the number of pilot subcarriers $K$ integrated across $M$ symbols. For a point target at range $R$ with radar cross section $\\sigma\_{\\mathrm{rcs}}$:
syms R_target positive            % target range [m]
syms sigma_rcs positive           % radar cross section [m^2]
syms G_ant positive               % antenna gain (linear)
syms lambda_c positive            % carrier wavelength [m]
P_r_sub = P_pilot * G_ant^2 * lambda_c^2 * sigma_rcs / ((4*sym(pi))^3 * R_target^4);
SNR_radar = K * M * P_r_sub / sigma2;
SNR_radar = simplify(SNR_radar);
disp('Radar SNR after coherent integration:') %[output:2c788d54]
disp(SNR_radar) %[output:0f1279b3]
SNR_radar_alpha = subs(SNR_radar, K, alpha*N);
SNR_radar_alpha = simplify(SNR_radar_alpha);
disp('In terms of pilot fraction alpha:') %[output:9de93885]
disp(SNR_radar_alpha) %[output:8a2023f5]
%%
%[text] ## 3. Communications Performance
%[text] The data subcarriers carry QAM-modulated information symbols. The achievable spectral efficiency on each data subcarrier (in the AWGN case) is given by the Shannon capacity formula. The total throughput depends on the number of data subcarriers $(1-\\alpha)N$.
%[text] Derive the per-frame throughput symbolically and express it in terms of the same pilot fraction $\\alpha$ used in the radar analysis.
SNR_data = P_data / sigma2;
C_sub = log2(1 + SNR_data);
N_data = (1 - alpha) * N;
R_bits_frame = N_data * M * C_sub;
R_bits_frame = simplify(R_bits_frame);
T_frame = M * T;
R_bits_rate = R_bits_frame / T_frame;
R_bits_rate = simplify(R_bits_rate);
disp('Throughput [bits/s]:') %[output:1e8f1ba5]
disp(R_bits_rate) %[output:15c9f6e2]
eta_spectral = R_bits_rate / B_sym;
eta_spectral = simplify(subs(eta_spectral, B_sym, N*Delta_f));
disp('Spectral efficiency [bits/s/Hz]:') %[output:0f0213a7]
disp(eta_spectral) %[output:40362cb4]
%%
%[text] ## 4. The ISAC Tradeoff: Pareto Frontier
%[text] Increasing the pilot fraction $\\alpha$ improves radar SNR (linearly) but decreases communications throughput (linearly). This is the fundamental ISAC tradeoff. Normalize both metrics to their maximum achievable values (at $\\alpha = 1$ for radar, $\\alpha = 0$ for comms) to plot them on a common scale.
rho_radar = alpha;
rho_comms = 1 - alpha;
disp('Normalized radar performance:  rho_radar = alpha') %[output:14f757be]
disp('Normalized comms performance:  rho_comms = 1 - alpha') %[output:4a429a79]
disp('Pareto constraint: rho_radar + rho_comms = 1') %[output:279dffa2]
%%
%[text] ### Cramér-Rao Bound for Range Estimation
%[text] The Cramér-Rao lower bound (CRB) on range estimation variance gives a more informative radar metric than raw SNR. For an OFDM radar with $K$ uniformly-spaced pilots, the CRB on delay estimation is:
%[text] $ \\mathrm{var}(\\hat{\\tau}) \\geq \\frac{3}{2\\pi^2 \\cdot \\mathrm{SNR}\_r \\cdot K \\cdot (K^2 - 1) \\cdot \\Delta f^2} $
%[text] Converting to range ($R = c\\tau/2$):
%[text] $ \\mathrm{CRB}\_R = \\frac{c^2}{4} \\cdot \\mathrm{var}(\\hat{\\tau}) $
%[text] This depends on $\\alpha$ through both $K = \\alpha N$ and $\\mathrm{SNR}\_r \\propto \\alpha$.
CRB_tau = 3 / (2 * sym(pi)^2 * SNR_radar * K * (K^2 - 1) * Delta_f^2);
CRB_R = c_light^2 / 4 * CRB_tau;
CRB_R = simplify(CRB_R);
disp('CRB on range estimation variance:') %[output:24bc8d33]
disp(CRB_R) %[output:2765c9d2]
CRB_R_alpha = subs(CRB_R, K, alpha*N);
CRB_R_alpha = simplify(CRB_R_alpha);
disp('In terms of alpha:') %[output:4f58d7e8]
disp(CRB_R_alpha) %[output:941a89a6]
RCRB = sqrt(CRB_R_alpha);
disp('Range RMSE lower bound (root CRB):') %[output:4c3622b4]
disp(RCRB) %[output:44b43fe9]
%%
%[text] ### Pareto Visualization
%[text] Evaluate the ISAC tradeoff at a concrete design point and generate the Pareto frontier, showing how pilot fraction $\\alpha$ trades radar range accuracy against communications throughput.
N_val       = 1024;               % subcarriers
Delta_f_val = 30e3;               % 30 kHz subcarrier spacing
T_cp_val    = 1/(Delta_f_val*14); % ~2.38 us CP (normal CP at 30 kHz)
T_val       = 1/Delta_f_val + T_cp_val;
M_val       = 14;                 % 14 symbols per slot (one 5G slot)
P_total_val = 1;                  % 1 W transmit power
sigma2_val  = 1e-10;              % noise power [W]
f_c_val     = 3.5e9;              % 3.5 GHz carrier
c_val       = 3e8;                % speed of light
lambda_val  = c_val / f_c_val;
G_ant_val   = 10^(15/10);         % 15 dBi antenna gain
R_target_val = 200;               % 200 m target range
sigma_rcs_val = 10;               % 10 m^2 RCS (vehicle)
cal_vars = [N, Delta_f, T_cp, T, M, P_total, sigma2, f_c, c_light, ...
            lambda_c, G_ant, R_target, sigma_rcs];
cal_vals = [N_val, Delta_f_val, T_cp_val, T_val, M_val, P_total_val, ...
            sigma2_val, f_c_val, c_val, lambda_val, G_ant_val, ...
            R_target_val, sigma_rcs_val];
CRB_R_fun = matlabFunction(subs(CRB_R_alpha, cal_vars, cal_vals), 'Vars', {alpha});
R_rate_fun = matlabFunction(subs(R_bits_rate, [cal_vars, B_sym], ...
    [cal_vals, N_val*Delta_f_val]), 'Vars', {alpha});
alpha_sweep = linspace(0.05, 0.95, 500);
CRB_sweep   = arrayfun(CRB_R_fun, alpha_sweep);
RCRB_sweep  = sqrt(CRB_sweep);
rate_sweep  = arrayfun(R_rate_fun, alpha_sweep);
%%
%[text] ### ISAC Tradeoff Curves
tiledlayout(2,1) %[output:92655115]
nexttile %[output:92655115]
yyaxis left %[output:92655115]
plot(alpha_sweep, RCRB_sweep, 'b-', 'LineWidth', 2) %[output:92655115]
ylabel('Range RMSE lower bound [m]') %[output:92655115]
set(gca, 'YScale', 'log') %[output:92655115]
yyaxis right %[output:92655115]
plot(alpha_sweep, rate_sweep/1e6, 'r-', 'LineWidth', 2) %[output:92655115]
ylabel('Throughput [Mbps]') %[output:92655115]
xlabel('Pilot fraction \alpha') %[output:92655115]
title('ISAC Tradeoff: Radar Accuracy vs. Communications Throughput') %[output:92655115]
legend('Range RMSE (CRB)', 'Data throughput', 'Location', 'north') %[output:92655115]
grid on %[output:92655115]
nexttile %[output:92655115]
plot(rate_sweep/1e6, RCRB_sweep, 'k-', 'LineWidth', 2) %[output:92655115]
hold on %[output:92655115]
alpha_pts = [0.1, 0.25, 0.5, 0.75, 0.9];
for i = 1:length(alpha_pts)
    crb_pt = sqrt(CRB_R_fun(alpha_pts(i)));
    rate_pt = R_rate_fun(alpha_pts(i))/1e6;
    plot(rate_pt, crb_pt, 'ko', 'MarkerSize', 8, 'MarkerFaceColor', 'k') %[output:92655115]
    text(rate_pt, crb_pt, sprintf('  \\alpha=%.2f', alpha_pts(i)), 'FontSize', 9)
end
hold off %[output:92655115]
xlabel('Throughput [Mbps]') %[output:92655115]
ylabel('Range RMSE lower bound [m]') %[output:92655115]
title('Pareto Frontier — Operating Point Selection') %[output:92655115]
set(gca, 'YScale', 'log') %[output:92655115]
grid on %[output:92655115]
%%
%[text] ### Design Point Summary
fprintf('Bandwidth:       %.1f MHz\n', N_val*Delta_f_val/1e6) %[output:52d2b21f]
fprintf('Frame duration:  %.2f ms\n', M_val*T_val*1e3) %[output:833509a9]
fprintf('Carrier freq:    %.1f GHz\n', f_c_val/1e9) %[output:8944c3cf]
fprintf('Target range:    %d m, RCS = %d m^2\n', R_target_val, sigma_rcs_val) %[output:24b7fa3e]
%%
%[text] ## 5. Pilot Sequence Design with Number-Theoretic Constraints
%[text] For the pilot subcarriers, we use Zadoff-Chu (ZC) sequences because of their ideal periodic autocorrelation, which is critical for unambiguous radar range estimation. ZC sequences have two number-theoretic requirements:
%[text] 1. The sequence length $L$ must be prime (for zero periodic cross-correlation between different root indices)
%[text] 2. The root index $u$ must be coprime with $L$ (automatically satisfied when $L$ is prime and $1 \\leq u \< L$) \
%[text] Given a desired number of pilot subcarriers $K = \\alpha N$, we must find the nearest valid (prime) sequence length. This is where `prevprime` and `nextprime` naturally enter the workflow.
alpha_sense = sym(3)/4;           % sensing-heavy: 75% pilots
alpha_comms = sym(1)/4;           % comms-heavy: 25% pilots
K_sense_raw = alpha_sense * N_val;
K_comms_raw = alpha_comms * N_val;
fprintf('Sensing-heavy (alpha=0.75): K_raw = %d\n', K_sense_raw) %[output:7e7b1609]
fprintf('  Next prime:     L = %s\n', char(nextprime(K_sense_raw))) %[output:9ef9c5ff]
fprintf('  Previous prime: L = %s\n', char(prevprime(K_sense_raw))) %[output:11682f80]
fprintf('Comms-heavy (alpha=0.25):   K_raw = %d\n', K_comms_raw) %[output:0a325973]
fprintf('  Next prime:     L = %s\n', char(nextprime(K_comms_raw))) %[output:49613928]
fprintf('  Previous prime: L = %s\n', char(prevprime(K_comms_raw))) %[output:4abbfa2a]
L_sense = double(prevprime(K_sense_raw));
L_comms = double(nextprime(K_comms_raw));
fprintf('Selected pilot lengths:\n') %[output:3afa8aa0]
fprintf('  Sensing-heavy: L = %d (prime)\n', L_sense) %[output:7de7002c]
fprintf('  Comms-heavy:   L = %d (prime)\n', L_comms) %[output:8d5625ab]
%%
%[text] ### Zadoff-Chu Root Index Selection
%[text] The root index $u$ determines the slope of the ZC sequence's frequency chirp, which directly affects the delay-Doppler coupling in the ambiguity function. Different roots $u$ and $u'$ produce zero cross-correlation when $L$ is prime, enabling multi-user ISAC or MIMO radar. Verify co-primality symbolically.
syms u positive integer
syms L_zc positive integer
syms n_idx integer
zc_seq = exp(-1j * sym(pi) * u * n_idx * (n_idx + 1) / L_zc);
disp('Zadoff-Chu sequence:') %[output:43ef14e7]
disp(zc_seq) %[output:3b008eb2]
u_candidate = sym(7);
L_check = sym(L_sense);
g = gcd(u_candidate, L_check);
fprintf('Root index u = %s, length L = %s\n', char(u_candidate), char(L_check)) %[output:521fd277]
fprintf('gcd(u, L) = %s\n', char(g)) %[output:228fe829]
if g == 1 %[output:group:21cd5fdf]
    fprintf('Coprime: valid ZC root\n') %[output:9612a67b]
end %[output:group:21cd5fdf]
fprintf('Number of valid roots for L = %d: %d (all of 1..%d)\n', ... %[output:group:882fceb1] %[output:1e6203dd]
    L_sense, L_sense-1, L_sense-1) %[output:group:882fceb1] %[output:1e6203dd]
%%
%[text] ### Autocorrelation Verification
%[text] The periodic autocorrelation of a ZC sequence is an ideal impulse. Verify this symbolically by computing the correlation sum, then confirm numerically with `zadoffChuSeq`.
syms m_shift integer
R_auto = symsum(exp(-1j*sym(pi)*u*n_idx*(n_idx+1)/L_zc) * ...
    exp(1j*sym(pi)*u*(n_idx+m_shift)*(n_idx+m_shift+1)/L_zc), n_idx, 0, L_zc-1);
R_auto_simplified = simplify(R_auto);
disp('Periodic autocorrelation R(m) (symbolic):') %[output:9bde0239]
disp(R_auto_simplified) %[output:1540606e]
u_val = 7;
zc_sense = zadoffChuSeq(u_val, L_sense);
R_numeric = abs(ifft(fft(zc_sense) .* conj(fft(zc_sense))));
R_numeric = R_numeric / max(R_numeric);
stem(0:L_sense-1, R_numeric, 'b', 'MarkerSize', 3) %[output:3dff80cd]
xlabel('Lag [samples]') %[output:3dff80cd]
ylabel('Normalized |R(m)|') %[output:3dff80cd]
title(sprintf('Periodic Autocorrelation — ZC(u=%d, L=%d)', u_val, L_sense)) %[output:3dff80cd]
ylim([-0.1 1.1]) %[output:3dff80cd]
grid on %[output:3dff80cd]
fprintf('Peak sidelobe level: %.2e (ideally 0)\n', max(R_numeric(2:end))) %[output:675c778e]
%%
%[text] ## 6. Convert Symbolic Design to Numerical Simulation
%[text] We now have two operating points on the Pareto frontier, each with a valid ZC pilot sequence length. The symbolic analysis produced:
%[text] - Function handles via `matlabFunction`: CRB and throughput vs. $\\alpha$
%[text] - Scalar parameters via `double`: $L$, $u$, $\\Delta f$, $T\_{\\mathrm{cp}}$, $M$ \
%[text] Generate the actual OFDM ISAC waveform at each operating point and compare the predicted vs. measured performance.
K1          = L_sense;            % use the prime-length pilot count
N_data1     = N_val - K1;
alpha1_actual = K1 / N_val;
K2          = L_comms;
N_data2     = N_val - K2;
alpha2_actual = K2 / N_val;
fprintf('Point 1 — Sensing-heavy:\n') %[output:4c95dc5a]
fprintf('  Pilots: K = %d (ZC length, prime)\n', K1) %[output:55f9166c]
fprintf('  Data:   %d subcarriers\n', N_data1) %[output:7814f289]
fprintf('  alpha:  %.4f\n', alpha1_actual) %[output:7adb7872]
fprintf('  Predicted range RMSE: %.3f m\n', sqrt(CRB_R_fun(alpha1_actual))) %[output:7a17f443]
fprintf('  Predicted throughput: %.1f Mbps\n', R_rate_fun(alpha1_actual)/1e6) %[output:42bacb35]
fprintf('Point 2 — Comms-heavy:\n') %[output:294c855f]
fprintf('  Pilots: K = %d (ZC length, prime)\n', K2) %[output:3966771b]
fprintf('  Data:   %d subcarriers\n', N_data2) %[output:55987d56]
fprintf('  alpha:  %.4f\n', alpha2_actual) %[output:852e1fb0]
fprintf('  Predicted range RMSE: %.3f m\n', sqrt(CRB_R_fun(alpha2_actual))) %[output:4af1d92f]
fprintf('  Predicted throughput: %.1f Mbps\n', R_rate_fun(alpha2_actual)/1e6) %[output:5e3de401]
%%
%[text] ### Waveform Generation
%[text] Generate one frame of the OFDM ISAC waveform at each operating point. Pilot subcarriers carry the Zadoff-Chu sequence with a per-symbol pseudo-random phase scramble to whiten the spectrum (avoiding periodic repetition artifacts). Data subcarriers carry QPSK symbols. The scrambling is transparent to both the radar processor (which divides out the known transmitted grid) and the communications equalizer (which estimates the channel from the known pilots).
rng(42)
mod_order = 4;  % QPSK
[grid1, pilot_idx1, data_idx1, zc1, data1] = ...
    buildISACGrid(N_val, K1, L_sense, u_val, M_val, mod_order);
[grid2, pilot_idx2, data_idx2, zc2, data2] = ...
    buildISACGrid(N_val, K2, L_comms, u_val, M_val, mod_order);
nfft = N_val;
cp_len = round(T_cp_val * N_val * Delta_f_val);
tx_waveform1 = ofdmmod(grid1, nfft, cp_len);
tx_waveform2 = ofdmmod(grid2, nfft, cp_len);
fprintf('OFDM symbols per frame: %d\n', M_val) %[output:6eaab5eb]
fprintf('FFT size: %d,  CP length: %d samples\n', nfft, cp_len) %[output:7e02a49e]
fprintf('Waveform 1 (sensing): %d samples\n', length(tx_waveform1)) %[output:5da4d248]
fprintf('Waveform 2 (comms):   %d samples\n', length(tx_waveform2)) %[output:4572c28c]
%%
%[text] ## 7. Spectral Verification
%[text] Verify that the generated waveform's power spectral density matches the symbolic bandwidth prediction $B = N \\Delta f$.
Fs = N_val * Delta_f_val;
B_predicted = N_val * Delta_f_val;
tiledlayout(2,1) %[output:572ed8f9]
nexttile %[output:572ed8f9]
[psd1, f1] = pwelch(tx_waveform1, hamming(nfft), nfft/2, nfft, Fs, 'centered');
plot(f1/1e6, pow2db(psd1), 'b-', 'LineWidth', 1.5) %[output:572ed8f9]
hold on %[output:572ed8f9]
xline(B_predicted/2e6, 'r--', 'B/2 (predicted)', 'LineWidth', 1.5) %[output:572ed8f9]
xline(-B_predicted/2e6, 'r--', '-B/2', 'LineWidth', 1.5) %[output:572ed8f9]
hold off %[output:572ed8f9]
xlabel('Frequency [MHz]') %[output:572ed8f9]
ylabel('PSD [dB/Hz]') %[output:572ed8f9]
title(sprintf('Sensing-Heavy (\\alpha=%.2f): %d pilots, %d data', ... %[output:572ed8f9]
    alpha1_actual, K1, N_data1)) %[output:572ed8f9]
grid on %[output:572ed8f9]
nexttile %[output:572ed8f9]
[psd2, f2] = pwelch(tx_waveform2, hamming(nfft), nfft/2, nfft, Fs, 'centered');
plot(f2/1e6, pow2db(psd2), 'b-', 'LineWidth', 1.5) %[output:572ed8f9]
hold on %[output:572ed8f9]
xline(B_predicted/2e6, 'r--', 'B/2 (predicted)', 'LineWidth', 1.5) %[output:572ed8f9]
xline(-B_predicted/2e6, 'r--', '-B/2', 'LineWidth', 1.5) %[output:572ed8f9]
hold off %[output:572ed8f9]
xlabel('Frequency [MHz]') %[output:572ed8f9]
ylabel('PSD [dB/Hz]') %[output:572ed8f9]
title(sprintf('Comms-Heavy (\\alpha=%.2f): %d pilots, %d data', ... %[output:572ed8f9]
    alpha2_actual, K2, N_data2)) %[output:572ed8f9]
grid on %[output:572ed8f9]
fprintf('Predicted bandwidth: %.2f MHz\n', B_predicted/1e6) %[output:7fa3468e]
%%
%[text] ## 8. Range-Doppler Processing
%[text] Simulate a single target at known range and velocity, then recover it from the OFDM radar processing chain:
%[text] 1. OFDM-demodulate the received signal
%[text] 2. Element-wise divide by the known pilot symbols (matched filter)
%[text] 3. IFFT across subcarriers (range axis)
%[text] 4. FFT across OFDM symbols (Doppler axis) \
%[text] Process both operating points to show how pilot density affects the range-Doppler map quality.
target_range = 150;               % [m]
target_velocity = 30;             % [m/s]
target_delay = 2 * target_range / c_val;
target_doppler = 2 * target_velocity * f_c_val / c_val;
fprintf('Range:     %d m  (delay = %.3f us)\n', target_range, target_delay*1e6) %[output:0831d31b]
fprintf('Velocity:  %d m/s (Doppler = %.1f Hz)\n', target_velocity, target_doppler) %[output:4b2b73a7]
snr_db = 20;
rx_grid1 = applyTargetChannel(grid1, N_val, M_val, ...
    target_delay, target_doppler, Delta_f_val, T_val, snr_db);
rx_grid2 = applyTargetChannel(grid2, N_val, M_val, ...
    target_delay, target_doppler, Delta_f_val, T_val, snr_db);
nfft_range = 512;
nfft_doppler = 256;
[rd1, range_ax1, vel_ax1] = ofdmRadarProcess(rx_grid1, grid1, ...
    pilot_idx1, N_val, M_val, Delta_f_val, T_val, c_val, f_c_val, ...
    nfft_range, nfft_doppler);
[rd2, range_ax2, vel_ax2] = ofdmRadarProcess(rx_grid2, grid2, ...
    pilot_idx2, N_val, M_val, Delta_f_val, T_val, c_val, f_c_val, ...
    nfft_range, nfft_doppler);
%%
%[text] ### Range-Doppler Maps
%[text] The red cross marks the true target location. The dashed rectangle shows the resolution cell predicted by the symbolic ambiguity function derivation.
delta_v_pred = c_val / (2 * f_c_val * M_val * T_val);
delta_R_pred1 = c_val / (2 * K1 * (N_val/K1) * Delta_f_val) * N_val;
delta_R_pred2 = c_val / (2 * K2 * (N_val/K2) * Delta_f_val) * N_val;
tiledlayout(1,2) %[output:204ef28f]
nexttile %[output:204ef28f]
imagesc(vel_ax1, range_ax1, pow2db(rd1 / max(rd1(:)))) %[output:204ef28f]
axis xy %[output:204ef28f]
colorbar %[output:204ef28f]
clim([-40 0]) %[output:204ef28f]
hold on %[output:204ef28f]
plot(target_velocity, target_range, 'r+', 'MarkerSize', 15, 'LineWidth', 2) %[output:204ef28f]
rectangle('Position', [target_velocity-delta_v_pred/2, target_range-delta_R_pred1/2, ... %[output:204ef28f]
    delta_v_pred, delta_R_pred1], 'EdgeColor', 'r', 'LineWidth', 1.5, 'LineStyle', '--') %[output:204ef28f]
hold off %[output:204ef28f]
xlabel('Velocity [m/s]') %[output:204ef28f]
ylabel('Range [m]') %[output:204ef28f]
title(sprintf('Sensing-Heavy (\\alpha=%.2f)', alpha1_actual)) %[output:204ef28f]
nexttile %[output:204ef28f]
imagesc(vel_ax2, range_ax2, pow2db(rd2 / max(rd2(:)))) %[output:204ef28f]
axis xy %[output:204ef28f]
colorbar %[output:204ef28f]
clim([-40 0]) %[output:204ef28f]
hold on %[output:204ef28f]
plot(target_velocity, target_range, 'r+', 'MarkerSize', 15, 'LineWidth', 2) %[output:204ef28f]
rectangle('Position', [target_velocity-delta_v_pred/2, target_range-delta_R_pred2/2, ... %[output:204ef28f]
    delta_v_pred, delta_R_pred2], 'EdgeColor', 'r', 'LineWidth', 1.5, 'LineStyle', '--') %[output:204ef28f]
hold off %[output:204ef28f]
xlabel('Velocity [m/s]') %[output:204ef28f]
ylabel('Range [m]') %[output:204ef28f]
title(sprintf('Comms-Heavy (\\alpha=%.2f)', alpha2_actual)) %[output:204ef28f]
%%
%[text] ## 9. EVM Measurement for Communications Quality
%[text] The Error Vector Magnitude (EVM) quantifies how accurately the data symbols are recovered. In a mobile channel, Doppler shift causes phase rotation across OFDM symbols/ So without compensation, the constellation "spins" and EVM is very high.
%[text] The same pilots used for radar sensing also provide per-symbol channel estimates for communications equalization. Estimate the channel on the pilot subcarriers, interpolate to the data subcarriers, and equalize. More pilots improves both radar accuracy and equalization quality.
eq_data1 = pilotEqualize(rx_grid1, grid1, pilot_idx1, data_idx1);
eq_data2 = pilotEqualize(rx_grid2, grid2, pilot_idx2, data_idx2);
ref_constellation = qammod(0:mod_order-1, mod_order, 'UnitAveragePower', true);
evm_meter = comm.EVM('ReferenceSignalSource', 'Estimated from reference constellation', ...
    'ReferenceConstellation', ref_constellation);
eq_data1_vec = eq_data1(:);
evm1 = evm_meter(eq_data1_vec);
release(evm_meter);
eq_data2_vec = eq_data2(:);
evm2 = evm_meter(eq_data2_vec);
fprintf('Sensing-heavy (alpha=%.2f): EVM = %.2f%%n', alpha1_actual, evm1) %[output:2aed64ec]
fprintf('Comms-heavy   (alpha=%.2f): EVM = %.2f%%n', alpha2_actual, evm2) %[output:99866cb9]
%%
%[text] ### Received Constellations
tiledlayout(1,2) %[output:612d2da7]
nexttile %[output:612d2da7]
plot(eq_data1_vec, '.', 'MarkerSize', 2) %[output:612d2da7]
hold on %[output:612d2da7]
plot(ref_constellation, 'r+', 'MarkerSize', 12, 'LineWidth', 2) %[output:612d2da7]
hold off %[output:612d2da7]
axis equal; grid on %[output:612d2da7]
title(sprintf('Sensing-Heavy — EVM = %.1f%%', evm1)) %[output:612d2da7]
xlabel('In-Phase'); ylabel('Quadrature') %[output:612d2da7]
nexttile %[output:612d2da7]
plot(eq_data2_vec, '.', 'MarkerSize', 2) %[output:612d2da7]
hold on %[output:612d2da7]
plot(ref_constellation, 'r+', 'MarkerSize', 12, 'LineWidth', 2) %[output:612d2da7]
hold off %[output:612d2da7]
axis equal; grid on %[output:612d2da7]
title(sprintf('Comms-Heavy — EVM = %.1f%%', evm2)) %[output:612d2da7]
xlabel('In-Phase'); ylabel('Quadrature') %[output:612d2da7]
%%
%[text] ## Local Functions
function [grid, pilot_idx, data_idx, zc_pilots, data_syms] = ...
        buildISACGrid(N, K_pilots, L_zc, u_root, M_sym, mod_order)
    pilot_idx = round(linspace(1, N, K_pilots));
    pilot_idx = unique(pilot_idx);
    K_pilots = length(pilot_idx);
    all_idx = 1:N;
    data_idx = setdiff(all_idx, pilot_idx);
    zc_full = zadoffChuSeq(u_root, L_zc);
    zc_pilots = zc_full(1:K_pilots);
    data_bits = randi([0 mod_order-1], length(data_idx)*M_sym, 1);
    data_syms_all = qammod(data_bits, mod_order, 'UnitAveragePower', true);
    data_syms = reshape(data_syms_all, length(data_idx), M_sym);
    grid = zeros(N, M_sym);
    scramble_phases = exp(1j*2*pi*rand(1, M_sym));
    grid(pilot_idx, :) = zc_pilots .* scramble_phases;
    grid(data_idx, :) = data_syms;
end
function eq_data = pilotEqualize(rx_grid, tx_grid, pilot_idx, data_idx)
    H_pilots = rx_grid(pilot_idx, :) ./ tx_grid(pilot_idx, :);
    H_all = interp1(pilot_idx(:), H_pilots, (1:size(rx_grid,1)).', 'linear', 'extrap');
    eq_grid = rx_grid ./ H_all;
    eq_data = eq_grid(data_idx, :);
end
function rx_grid = applyTargetChannel(tx_grid, N, M_sym, ...
        delay, doppler, Delta_f, T_total, snr_db)
    rx_grid = zeros(size(tx_grid));
    for m = 1:M_sym
        for k = 1:N
            phase_delay = exp(-1j*2*pi*(k-1)*Delta_f*delay);
            phase_doppler = exp(1j*2*pi*doppler*(m-1)*T_total);
            rx_grid(k, m) = tx_grid(k, m) * phase_delay * phase_doppler;
        end
    end
    noise_power = 10^(-snr_db/10) * mean(abs(rx_grid(:)).^2);
    noise = sqrt(noise_power/2) * (randn(size(rx_grid)) + 1j*randn(size(rx_grid)));
    rx_grid = rx_grid + noise;
end
function [rd_map, range_axis, vel_axis] = ofdmRadarProcess(...
        rx_grid, tx_grid, pilot_idx, N, M_sym, Delta_f, T_total, c, fc, nfft_r, nfft_d)
    rx_pilots = rx_grid(pilot_idx, :);
    tx_pilots = tx_grid(pilot_idx, :);
    H_est = rx_pilots ./ tx_pilots;
    rd_map = fft(ifft(H_est, nfft_r, 1), nfft_d, 2);
    rd_map = abs(rd_map).^2;
    K_p = length(pilot_idx);
    max_range = c / (2 * (N/K_p) * Delta_f);
    range_axis = linspace(0, max_range, nfft_r);
    max_doppler = 1 / (2 * T_total);
    doppler_axis = linspace(-max_doppler, max_doppler, nfft_d);
    vel_axis = doppler_axis * c / (2 * fc);
end
%[text] 

%[appendix]{"version":"1.0"}
%---
%[metadata:view]
%   data: {"layout":"inline"}
%---
%[output:05335980]
%   data: {"dataType":"text","outputData":{"text":"Frequency-domain ambiguity A_f(tau):\n","truncated":false}}
%---
%[output:59af4e03]
%   data: {"dataType":"symbolic","outputData":{"name":"","value":"\\left\\lbrace \\begin{array}{cl}\n1 & \\;\\textrm{if}\\;\\;\\frac{\\Delta_f \\,N\\,\\tau }{K}\\in \\mathbb{Z}\\\\\n\\frac{{\\mathrm{e}}^{-2\\,\\pi \\,\\Delta_f \\,N\\,\\tau \\,\\mathrm{i}} \\,{\\mathrm{e}}^{\\frac{2\\,\\pi \\,\\Delta_f \\,N\\,\\tau \\,\\mathrm{i}}{K}} \\,{\\left({\\mathrm{e}}^{2\\,\\pi \\,\\Delta_f \\,N\\,\\tau \\,\\mathrm{i}} -1\\right)}}{K\\,{\\left({\\mathrm{e}}^{\\frac{2\\,\\pi \\,\\Delta_f \\,N\\,\\tau \\,\\mathrm{i}}{K}} -1\\right)}} & \\;\\textrm{if}\\;\\;\\frac{\\Delta_f \\,N\\,\\tau }{K}\\not\\in \\mathbb{Z}\n\\end{array}\\right."}}
%---
%[output:8c32ddb5]
%   data: {"dataType":"text","outputData":{"text":"Closed-form (geometric series):\n","truncated":false}}
%---
%[output:63719c4e]
%   data: {"dataType":"symbolic","outputData":{"name":"","value":"\\frac{{\\mathrm{e}}^{-2\\,\\pi \\,\\Delta_f \\,N\\,\\tau \\,\\mathrm{i}} -1}{K\\,{\\left({\\mathrm{e}}^{-\\frac{2\\,\\pi \\,\\Delta_f \\,N\\,\\tau \\,\\mathrm{i}}{K}} -1\\right)}}"}}
%---
%[output:3a05fb2d]
%   data: {"dataType":"text","outputData":{"text":"|A_f(tau)|^2 (Dirichlet kernel):\n","truncated":false}}
%---
%[output:634dc154]
%   data: {"dataType":"symbolic","outputData":{"name":"","value":"\\frac{{\\sin \\left(\\pi \\,B_{\\textrm{sym}} \\,\\tau \\right)}^2 }{K^2 \\,{\\sin \\left(\\frac{\\pi \\,B_{\\textrm{sym}} \\,\\tau }{K}\\right)}^2 }"}}
%---
%[output:620acca3]
%   data: {"dataType":"text","outputData":{"text":"Range resolution (monostatic):\n","truncated":false}}
%---
%[output:3db19f6e]
%   data: {"dataType":"symbolic","outputData":{"name":"","value":"\\frac{c_{\\textrm{light}} }{2\\,B_{\\textrm{sym}} }"}}
%---
%[output:44d7e3a8]
%   data: {"dataType":"text","outputData":{"text":"|A_t(nu)|^2:\n","truncated":false}}
%---
%[output:632cad7d]
%   data: {"dataType":"symbolic","outputData":{"name":"","value":"\\frac{{\\sin \\left(\\pi \\,M\\,T\\,\\nu \\right)}^2 }{M^2 \\,{\\sin \\left(\\pi \\,T\\,\\nu \\right)}^2 }"}}
%---
%[output:1c5edca0]
%   data: {"dataType":"text","outputData":{"text":"Velocity resolution:\n","truncated":false}}
%---
%[output:26b5d50e]
%   data: {"dataType":"symbolic","outputData":{"name":"","value":"\\frac{c_{\\textrm{light}} }{2\\,M\\,T\\,f_c }"}}
%---
%[output:2c788d54]
%   data: {"dataType":"text","outputData":{"text":"Radar SNR after coherent integration:\n","truncated":false}}
%---
%[output:0f1279b3]
%   data: {"dataType":"symbolic","outputData":{"name":"","value":"\\frac{{G_{\\textrm{ant}} }^2 \\,K\\,M\\,P_{\\textrm{total}} \\,{\\lambda_c }^2 \\,\\sigma_{\\textrm{rcs}} }{64\\,N\\,{R_{\\textrm{target}} }^4 \\,\\sigma_2 \\,\\pi^3 }"}}
%---
%[output:9de93885]
%   data: {"dataType":"text","outputData":{"text":"In terms of pilot fraction alpha:\n","truncated":false}}
%---
%[output:8a2023f5]
%   data: {"dataType":"symbolic","outputData":{"name":"","value":"\\frac{{G_{\\textrm{ant}} }^2 \\,M\\,P_{\\textrm{total}} \\,\\alpha \\,{\\lambda_c }^2 \\,\\sigma_{\\textrm{rcs}} }{64\\,{R_{\\textrm{target}} }^4 \\,\\sigma_2 \\,\\pi^3 }"}}
%---
%[output:1e8f1ba5]
%   data: {"dataType":"text","outputData":{"text":"Throughput [bits\/s]:\n","truncated":false}}
%---
%[output:15c9f6e2]
%   data: {"dataType":"symbolic","outputData":{"name":"","value":"-\\frac{N\\,\\log \\left(\\frac{P_{\\textrm{total}} }{N\\,\\sigma_2 }+1\\right)\\,{\\left(\\alpha -1\\right)}}{T\\,\\log \\left(2\\right)}"}}
%---
%[output:0f0213a7]
%   data: {"dataType":"text","outputData":{"text":"Spectral efficiency [bits\/s\/Hz]:\n","truncated":false}}
%---
%[output:40362cb4]
%   data: {"dataType":"symbolic","outputData":{"name":"","value":"-\\frac{\\log \\left(\\frac{P_{\\textrm{total}} }{N\\,\\sigma_2 }+1\\right)\\,{\\left(\\alpha -1\\right)}}{\\Delta_f \\,T\\,\\log \\left(2\\right)}"}}
%---
%[output:14f757be]
%   data: {"dataType":"text","outputData":{"text":"Normalized radar performance:  rho_radar = alpha\n","truncated":false}}
%---
%[output:4a429a79]
%   data: {"dataType":"text","outputData":{"text":"Normalized comms performance:  rho_comms = 1 - alpha\n","truncated":false}}
%---
%[output:279dffa2]
%   data: {"dataType":"text","outputData":{"text":"Pareto constraint: rho_radar + rho_comms = 1\n","truncated":false}}
%---
%[output:24bc8d33]
%   data: {"dataType":"text","outputData":{"text":"CRB on range estimation variance:\n","truncated":false}}
%---
%[output:2765c9d2]
%   data: {"dataType":"symbolic","outputData":{"name":"","value":"\\frac{24\\,\\pi \\,N\\,{R_{\\textrm{target}} }^4 \\,{c_{\\textrm{light}} }^2 \\,\\sigma_2 }{{\\Delta_f }^2 \\,{G_{\\textrm{ant}} }^2 \\,K^2 \\,M\\,P_{\\textrm{total}} \\,{\\lambda_c }^2 \\,\\sigma_{\\textrm{rcs}} \\,{\\left(K^2 -1\\right)}}"}}
%---
%[output:4f58d7e8]
%   data: {"dataType":"text","outputData":{"text":"In terms of alpha:\n","truncated":false}}
%---
%[output:941a89a6]
%   data: {"dataType":"symbolic","outputData":{"name":"","value":"\\frac{24\\,\\pi \\,{R_{\\textrm{target}} }^4 \\,{c_{\\textrm{light}} }^2 \\,\\sigma_2 }{{\\Delta_f }^2 \\,{G_{\\textrm{ant}} }^2 \\,M\\,N\\,P_{\\textrm{total}} \\,\\alpha^2 \\,{\\lambda_c }^2 \\,\\sigma_{\\textrm{rcs}} \\,{\\left(N^2 \\,\\alpha^2 -1\\right)}}"}}
%---
%[output:4c3622b4]
%   data: {"dataType":"text","outputData":{"text":"Range RMSE lower bound (root CRB):\n","truncated":false}}
%---
%[output:44b43fe9]
%   data: {"dataType":"symbolic","outputData":{"name":"","value":"\\frac{2\\,\\sqrt{6}\\,{R_{\\textrm{target}} }^2 \\,c_{\\textrm{light}} \\,\\sqrt{\\sigma_2 }\\,\\sqrt{\\pi }\\,\\sqrt{\\frac{1}{N^2 \\,\\alpha^2 -1}}}{\\Delta_f \\,G_{\\textrm{ant}} \\,\\sqrt{M}\\,\\sqrt{N}\\,\\sqrt{P_{\\textrm{total}} }\\,\\alpha \\,\\lambda_c \\,\\sqrt{\\sigma_{\\textrm{rcs}} }}"}}
%---
%[output:92655115]
%   data: 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\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","height":337,"width":560}}
%---
%[output:52d2b21f]
%   data: {"dataType":"text","outputData":{"text":"Bandwidth:       30.7 MHz\n","truncated":false}}
%---
%[output:833509a9]
%   data: {"dataType":"text","outputData":{"text":"Frame duration:  0.50 ms\n","truncated":false}}
%---
%[output:8944c3cf]
%   data: {"dataType":"text","outputData":{"text":"Carrier freq:    3.5 GHz\n","truncated":false}}
%---
%[output:24b7fa3e]
%   data: {"dataType":"text","outputData":{"text":"Target range:    200 m, RCS = 10 m^2\n","truncated":false}}
%---
%[output:7e7b1609]
%   data: {"dataType":"text","outputData":{"text":"Sensing-heavy (alpha=0.75): K_raw = 768\n","truncated":false}}
%---
%[output:9ef9c5ff]
%   data: {"dataType":"text","outputData":{"text":"  Next prime:     L = 769\n","truncated":false}}
%---
%[output:11682f80]
%   data: {"dataType":"text","outputData":{"text":"  Previous prime: L = 761\n","truncated":false}}
%---
%[output:0a325973]
%   data: {"dataType":"text","outputData":{"text":"Comms-heavy (alpha=0.25):   K_raw = 256\n","truncated":false}}
%---
%[output:49613928]
%   data: {"dataType":"text","outputData":{"text":"  Next prime:     L = 257\n","truncated":false}}
%---
%[output:4abbfa2a]
%   data: {"dataType":"text","outputData":{"text":"  Previous prime: L = 251\n","truncated":false}}
%---
%[output:3afa8aa0]
%   data: {"dataType":"text","outputData":{"text":"Selected pilot lengths:\n","truncated":false}}
%---
%[output:7de7002c]
%   data: {"dataType":"text","outputData":{"text":"  Sensing-heavy: L = 761 (prime)\n","truncated":false}}
%---
%[output:8d5625ab]
%   data: {"dataType":"text","outputData":{"text":"  Comms-heavy:   L = 257 (prime)\n","truncated":false}}
%---
%[output:43ef14e7]
%   data: {"dataType":"text","outputData":{"text":"Zadoff-Chu sequence:\n","truncated":false}}
%---
%[output:3b008eb2]
%   data: {"dataType":"symbolic","outputData":{"name":"","value":"{\\mathrm{e}}^{-\\frac{\\pi \\,n_{\\textrm{idx}} \\,u\\,{\\left(n_{\\textrm{idx}} +1\\right)}\\,\\mathrm{i}}{L_{\\textrm{zc}} }}"}}
%---
%[output:521fd277]
%   data: {"dataType":"text","outputData":{"text":"Root index u = 7, length L = 761\n","truncated":false}}
%---
%[output:228fe829]
%   data: {"dataType":"text","outputData":{"text":"gcd(u, L) = 1\n","truncated":false}}
%---
%[output:9612a67b]
%   data: {"dataType":"text","outputData":{"text":"Coprime: valid ZC root\n","truncated":false}}
%---
%[output:1e6203dd]
%   data: {"dataType":"text","outputData":{"text":"Number of valid roots for L = 761: 760 (all of 1..760)\n","truncated":false}}
%---
%[output:9bde0239]
%   data: {"dataType":"text","outputData":{"text":"Periodic autocorrelation R(m) (symbolic):\n","truncated":false}}
%---
%[output:1540606e]
%   data: {"dataType":"symbolic","outputData":{"name":"","value":"\\left\\lbrace \\begin{array}{cl}\nL_{\\textrm{zc}} \\,{\\mathrm{e}}^{\\frac{\\pi \\,m_{\\textrm{shift}} \\,u\\,{\\left(m_{\\textrm{shift}} \\,\\mathrm{i}+\\mathrm{i}\\right)}}{L_{\\textrm{zc}} }}  & \\;\\textrm{if}\\;\\;\\frac{m_{\\textrm{shift}} \\,u}{L_{\\textrm{zc}} }\\in \\mathbb{Z}\\\\\n-\\frac{{\\mathrm{e}}^{\\frac{\\pi \\,{m_{\\textrm{shift}} }^2 \\,u\\,\\mathrm{i}}{L_{\\textrm{zc}} }} \\,{\\mathrm{e}}^{\\frac{\\pi \\,m_{\\textrm{shift}} \\,u\\,\\mathrm{i}}{L_{\\textrm{zc}} }} -{\\mathrm{e}}^{\\frac{\\pi \\,{m_{\\textrm{shift}} }^2 \\,u\\,\\mathrm{i}}{L_{\\textrm{zc}} }} \\,{\\mathrm{e}}^{\\frac{\\pi \\,m_{\\textrm{shift}} \\,u\\,\\mathrm{i}}{L_{\\textrm{zc}} }} \\,{\\mathrm{e}}^{2\\,\\pi \\,m_{\\textrm{shift}} \\,u\\,\\mathrm{i}} }{{\\mathrm{e}}^{\\frac{2\\,\\pi \\,m_{\\textrm{shift}} \\,u\\,\\mathrm{i}}{L_{\\textrm{zc}} }} -1} & \\;\\textrm{if}\\;\\;\\frac{m_{\\textrm{shift}} \\,u}{L_{\\textrm{zc}} }\\not\\in \\mathbb{Z}\n\\end{array}\\right."}}
%---
%[output:3dff80cd]
%   data: 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t+A4v1\/z+y8VjvHFZ7CJ145Tn7t5P7BrXfvbca8LduXAX7pmfB7o2QBmfJsx+2t7M5l8B9oWWUobXYEhdR9eOT9fclE34wMn18t5TizWz2hTG7m8c6lMnc72td0tL7f7T\/\/0T2m2fv7w8CZWX3luTxu5v9Iu5frNZbbTdljXUjqXaaPMy+3kfi2tZ5nXKZfWZxf7cn5uQ5k8S21gPNvFTrZZz9KHYt429si31EeJbVev0y512KItbUtbSmsLZXvrKtOO+tZ12cZSfW0q6+xbnvro9EG2VxnU1U6JoCd\/UJf5pdY\/OzrXt2\/Yo23wjT6tq64ydaQ7yW1aD9qXV9bThjLQuYwv5VnKc1zk9fXPDtDqjLVubkt96NNSG8osy\/S6+i3rWyfbJ992Suf88vhjM9uVWb7qVa8a9n61frZLHVoecrvsku60176wT6wH7etP3W7k9XN7uY4+taM962sHdKcNeR11raNfaLtb2Te\/+c1Abs+XBnchCY6NBOdgxqiN9bVTtsdWvmWH8sy73vWu5MfOMvWtD9tlqU3raUN9eerJm27uv+jEuPkNmyTu\/thrB7tf\/R+3Rf\/bd0r5d7x\/\/\/j9Yw+lMktp6yhXLxXM4EtPBjDfvP6+dOmo\/BVqemO9jXoGj4+66x7wwGwywWUal2t8yzeq5YN6zNWIuQAAEABJREFUNtlf27rxeEBQ5FKTS05GUIyGCGbGMtI327208sbvxCPtC2Pph66KXc+7NVb9+tp45Kovps2672\/fE1sd\/OZoXPhgSv\/uB\/+Ulg9+7aMxZ5udYo+vPBXz99w\/Hr70vJQ\/ky89F8C4y+jki3+V5sDkS0h56TbrnRbPn0l\/1X3XHqg9sA4PCFhm+pvlOsyri2oPDPOAERGjIJk8OjOs0ggJoypGfowAjVClZ7PnbrtbbLrF0LSMOQsXxbxtdw2jKoKZebs+NzbdfOvYfN\/D4tF\/\/UoahXnsp5fH\/J32Ttu05R+9IaSNyqSMGXrpuQCGH3beekG4bZqumWkP1P3XHqg9UHug9sCG5IG5T981djzl23HP\/\/6zuOOkP0p6wd4vTZuYg5mUqF6evP\/O+P3vHq5UhMAmiepl9QN3pcCmkjP2v+mM9TxCx0ZYDn32kmh946YRakx\/trskDDPWXJ1+G6n2Q+2H+hioj4H6GOjdY6D\/R9+NFTe0B1l9X\/+wE6fLRQKXnc\/41wAtb1ilWZDouQDmzgdXxReuuTu++uN70zwYc18yMzEH5rb7V8Zf\/O1348\/++3vCzP3J4L\/9txPipS\/dOf7ojw6MQw+NSWt3Mmyr2ziy3h9H1j6o3wf1MTCbj4G+d7867m4dOsi9f3V0lEHME7f9LM1jMRIDc1pcKorq78kVj8QT991WqYF\/817y5SbrDeRGzF2yNF1mymlLl6BM8DXRdzTUU996E2XTia44VevttHj+4E8K5LkveTkTc2AEMFc+tH187K8+F66PTgb\/9\/+eFS95yc7JhStXHhh77nnVpLR97LHHpjbPPvvsSWlvMrZ1pDZmk622YTbZW9v6pSk7\/mvf1r6dDZ8Hyz79zdixdUViyRtasbIajXni3qFRGJeCzHURQJjH4jKR+S05mBGoyDfPxXyXPB9m1Z03pnOMYMf8GPkpo3gR2JgYbLLvSChXr1htQrLnApgJbcU0rLTTTjuHZyNMFhdcEIN\/l1++c\/ziFweud\/sHHHBAajM\/n2OybJ2KdmaTrbZ\/Ntlb27r+7yX7vBu1b2vfOi56\/ThoPP8lsXCfZmLBPoek80L5sujgN6Y7jW47Zrfof8vidHfRNkedmaps++efjIev+vxgvroKFr\/uAyHQMbJiKS2\/RAC088euDcsyv1MrH0u9zvU60z0XwLiE5FJRvmxULuUr79yI6Uh\/79cPhNGY3NeKJ54MlOmsLZWBRqmlt9\/pyfjWt58kE0cfHdFuJ5le1EdKVC+lrpKp7zKv1LOhfPXvn2LmIL1ufzd7S5tLbaOkQaPUOV3mlXoyyrWx8onfWyQmu33tITVevZS6So77+Oy0tWyPhnZBgwYNGjRo0KBBgwYNGjRo0KAzs8letpb208jbQmPS02sa1DbWJLseG2X5bLC3\/DxgO8a6fepiuuqXtuY+LQUseYRkx\/d\/XVZCcNH47J3pduky32iLoMM6ltJphRl86bkAZqRLSK\/\/g+3iI4c\/I5TPhL8+9v\/648vX3j3Y9c33rQjkjFLLkwaNUuf0rvusiCuukBrAfJh2e0Crj4FUDOtLnjLQoHfYYYfwJE5LaShDqXO6zCv1dJSvmLt1vPL1bwy25v4sM+xBmc7aUhlolDqny7xST6Scvdm3E1l\/ffsfz\/p8yrdPzF\/M1MR41reC+qBR6pwu80o9nnK28munrWV7NLQLGjRo0KBBgwYNGjRo0KBBgwbN3m6+zeXq0KBBgwYNGjRo0KBBgwYNGjRo0GBr9q20MtCgQYMGDRo0aNCgQYMGDRo0aNCgQWM22Vt+HrAdtgU0aNCgQYMGDRo0aNCgQYMGDRo0aNz14PAnLsubDjwoz4PvXIoyQdjIzc1vWhSeQTNZ\/fdcADPShrVes1ec1749\/SL1SHVmY36zGdFqDVleBjFDuWNTPgDe\/OY3DwYFY1trZmo9bdvt4\/D\/dtSssJWH2DtbfOs44Nunb7c903satvLrFNg6JdvN3tq3U+La9FkwW46F2fR58OTvh0Zip2bPrd2quTXmz+xw\/FfTrdYPfvX09NC8pSd9K+77zNvS82bWXmv8ObMmgPnhbQ\/HHQ+tHP8WTtIaR+y\/Qxy055LB1nbcen4gZ5RanjRolDqnc97y5RFvfNPQJRWXk26+fsGktZ\/7s8zoG2U6a0tloFHqnC7zSj228s1iuy3nqJoY\/\/qT538GjN7\/ZqoNoj5yRqnlSYNGqXO6zCv1ZJTz7Q5bDdk82e1rD2xFqXO6zCt1t\/JOW8v6NKwHGjRo0KBBgwYNGjRo0KBBgwaNbr4ty2moCxo0aNCgQYMGDRo0aNCgQYMGDb4t0zSUgQYNGjRo0KBBgwYNGjRo0KBBgwaN2WHv8PdWaT8N2wIaNGjQoEGDBg0aNGjQoEGDBo2nbzlkq\/R08dTKR2L1fbfGip9\/JzZZsCg2222\/Se+65wIYc1zMdSnnvtBv6fvZjF5C+vK194R5MHkPPPDYE4EynbWlMtAodU6Xead9YkU0m0oi+vsjjnn7nLj0sqE5MmVdtaRBo9Q5XeaVujfKV8dDK4e+GfSefZ37dzW3DcJe5IxSy3tgko+P8bbPtw88NmTzeNdXH7YFpc7pMq\/UEysfbmvZHg3tggYNGjRo0KBBgwYNGjRo0KBBo5tvy3Ia6oIGDRo0aNCgQYMGDRo0aNCgQcNxMDzdeWz3Wnr1Wp+tvWf\/7DleH1k5dB5xPEwH5tEsfv0pcdepB8d9f\/POePqy\/xV+kkBavvLJsKPnAhhzXNwunW+dLpev3m\/bydjmCbXROQKzZPN5gdxYqeVJg0apc7rMo82HaTaVRtx5+yZxwnvmD07sVT5QMvAqjYFUDLNFnjLQKHVOl3mlnp7yubH1gqHDb\/r7H+\/+m8stg7AXOaPU8qRBo9Q5XeaVejLK+XbJ5kM2L6mOV+1mpFGms7ZUBhqlzukyr9QTKx9ua9keDe2CBg0aNGjQoEGDBg0aNGjQoEGjm2\/LchrqggYNGjRo0KBBgwYNGjRo0KBBY0l1HCwp9j8NZaBBgwYNGjRo0KBBgwYNGjRo0KBBY8mssHf2HK+LFszh1mnH3Usm\/O7xhUfCU35z2nKyjBk6g0xWi5PQziOrVscff\/KHwx5kJy1\/EpqfUBNTPQKTv2F0BjF5Tkwuz8ZLo0xnHRHpG0xvl288IzCe5Nz+7veHPcVYGvlppqWWJw0apc7pMq\/UP\/jBD+Ka634c7e\/+62Cf7WnsfzT7ynK2+u2kdoet7cJeGtYDDRo0aNCgQYMGDRo0aNCgQYNmbzff5nJ1aNCgQYMGDRo0aNCgf\/Hralh2zRvc+xprkl3f68PLZ8OIxhN5c6rtmQ321iMwgztsBGHyrkm8afLuGzYJS2n5I6wy7uyeC2AEKX96\/vXpbqNy9MXIjHzl497KSVhhOkZgspmCmINeOjQnRhDz8+uGX8dcUn2jQl6n1PKkQaPUOV3mlXp6yuduFCMwgpfjjz8+3nfM0cOe8CuN\/LTPUsuTBo1S53SZV2oTIT926glx8nHvHOyzLB9t\/eksZ+tf\/uVfrmVraS8NdoEGDRo0aNCgQYMGDRo0aNCgQbO3m29zuTo0aNCgQYMGDRo0aNCfOvPUcCyN9N4s37801MWSWTGiMY+pidlhbz0Ck3bWCC+ClLtOOyw9XyaNwnzlqci\/bi1f+Qirjit7agKYcZkwvPLDKwau17Ves9ewgpzO5cMKpyExXSMweVMu\/OqKeN2fDUX5r3nl3DjttFwa1beUta9bD5XOhvKNYwTGSeeaa66J2fB0ZE8YrZm6J81O1Lee\/usYcix5jxtdAQ0aNGjQqOfAPJE+L\/kCfAMaNGjQoEGDBs2nNAbS5QjSVPQ38fZnYg5MDlA8FI+P4Lkx7kqiczm9PvRcAGOkBQeddXX84NaBX8C0lJaP9dngia47nSMwbFxSjbD8zf95KlotqQFarQh3KEkpB41S53SZV+reKN84RmD4GrPh6cieMFpz4Ho\/EXuyfZif+uo4gvcyaNCgQYPGknoEZtgcwSXVZyv4BjRo0KBBgwa9pPIpjSWT0t7QCNRktzcTc2BM0t36VcfFPWe\/Pt1GzU+472\/fE36CQLn0+tJzAYwN+ps37xPvau4aLz\/3ujQPxlJavvKZYLpHYHJU7xZrl5TyNvf1RbiklMtzvnTWltKgUeqcLvNKPT3lG8cIDF\/W1B6YTA94ryK3SWPk9GyYU1KOMMwGe4dGx\/keI\/t\/ZkdkZmIExnNgfnvRCfH4zT9IP0lg\/gtW\/ODiePDij6b5MBvkjznmg+D4l+8e5RwY6Vw2E8u\/OmLvOGL\/HQe7Xrp4fiBnlFqeNGiUOqfLvFJ3ljebEZf9y9CcmHY74pAXLoxf\/ni+qol1ra9Cr5XvuNVmsd2Wc5mW6DX72INkXPXC3mox+K8MOaPU8qRBz2Z++tOfxvOe97zYY489BjEv49FHH522zVqXDexgD+hs1Pve9740\/0celOdtOOSQQ+Lee+9NVdXL+Xn5mc98JpV1viyvvk2wRb46uT7\/5HxL6VxmqW82gJaX0b\/22EOrI70uHFfIdWiMmN567c+qketH+lyb0fJZYG\/5ecBXGNH\/Xc4V01l\/my3mZdOmbWmEJf8cQZ4D07lUrt76GNWTIzDrs0FTte4uSxbErtssGGx+4bw5gZxRannSoFHqnC7zSt2t\/LD\/tEnccktEs6l04DbrP375nMF5MaOt33Plm82JBXM3GdiY6rXn7Ovcv5W9lZmD\/+xFzii1PGnQs53Xvva1cfPNNw+ydOnSdHfTdG7XumxYtGhRPPzww9X7o3qDVEYJBu66666QXyXjoosuioMPPnjQ\/lNOOSXOOussRbHFFlvExRdfPFhmO9\/5znemsvLl8ssvjx133DH23XffELzcdNNNg+to\/6STThoMitZla\/adfq6\/\/vp45JFHQtCz3Xbbhcf+s6Xst5t2XCGX0RgpvWDepmt9Vq2rvjKM1J4yTFX5rLC3+DzgC0yVP7SNibbPn3ndDW3ZkwGMO43cNu0Bdhlp+TO1AzzEbjJ\/zNGPeSFvT6nlSYMG3WhE+u2kVkvOAK1WpEtKygdyBl6lMZCK9ANqWVsqA41S53SZV+rJKPeDbStXD40qTXb72gNbUeqcLvNK3a2cvfIz6qNMZ22pDHQnLgH2Mp32ritt1CCPJhhdMILgZP9f\/+t\/HRyxccLXhsDC6If673jHO8KIhnz15UF78saDQOWFL3xh\/OY3v0mrCQye8YxnDAYwe+21Vwg4UmH1cthhh8XHP\/7xSo39\/zvf+U4cdNBBYfu0dcIJJwyuLKj55je\/GYKQwcwximc+85mx++67p9qWP\/rRjwYDoZTZ5cVxhVxEY8T0408Oe\/+rixHrPzHD9WeBveXnAV+iV\/050o85ZnunammirtumXTrKSMufrD43nayGJqsdQYrbpU3WLS8hSctXPll9jaedzh9zvOvBVYHcRqnlSYNGqXO6zCv1aDf4i94AABAASURBVOXVSHZ88R+Hflah3Y54xp6bDj70brT1e6L8oVVx76ND15HHs\/0zYn9lr34z7EWZztpSGehO2u2Idjui3Y5otyPa7Yh2O6Ldjmi3I9rtiHY7ot2OaLcj2u2Idjui3Y5otyPa7Yh2O6Ldjmi3I9rtiHY7ot2OaLcj2u2Idjui3Y5otyPa7Yh2O6Ldjmi3I9rtiHY7ot2OaLcj2u2Idjui3Y5otzutjfj6178+GIwIMtQQBAhIli1blkYiBA0CiVsME1YVttpqq5BnRMFJ2YnfqIfRD6MPz3\/+8+N3v\/tdOll\/7nOfSyM68gUbOeCpmhn8H8mGXOGlL31pCDKkLaVpsPUVr3jF4DYIotiujA2HH374YJnLP0ZElGXUVW\/3KtB47LHHUvbmm2+elt1e1mWrkSGTfPlxv\/32i2984xuR29xyyy3TiFAOxLq1Lc9xBRo0aNCgcffDj6\/1WVWW01AXNGjQoEGDBg0aNGjQoEGDBg0as8Le4vOA7WA7aNCgQYMGDRo0aNCgQYMGDRo0aNC4t9r\/ltOJIMXt0nO22Sn9qnW+fCQtX\/lk2NNzAUy+TTrfNp03Mqdzec6fruVMzoGxjeU1U+k\/edW8+NVNT0WzKTVwSemVr1wQRxyxY8pY2uW6aypY8zLT5a4h994cmDXOqRad\/mFvlT3431kuPVhYCWlUctb\/50siHqrm5JtHH4w43HPPPenk72SsPG+sSzZOyNtvv30aCREAKFPP0miGyzdO1jfccEO688dJXZBjhEOdkpFsyHX23HPPFBD97Gc\/C8FT7ieXC2IESPj0pz8dAilBFRsEWfLhoXpGVPJ6ncscuOSgI5fbdu1Jr8vW8hKS\/o444oj42te+ZrUEP\/FJSozw4rhCLqYxYnoWzCkZZv8ssLf8PGA7RvR\/l8\/i6aw\/E3NgcoBS3kbNPzmdy+WtDz0XwBhpOfTZS+KVn7ou\/C6SjbOUlq9c3nQz03Ngymugtl16rz03WeuS0jXXLIi9914QZ50xZ63r3tbLWB9lOmtLZaBR6pwu80o9pvLqGvLGOgfmqerKWS9j\/3VDwHLiiScOnvyNVBjtcCI22iK46baePIGCpXqW3\/ve91LAIcDZZ599BkdgtLWuyzudNmgLuf2+vr406VhexmUpl6lyWp9Gi3J6PEtBmVEigVZejx8EdXn0KeePZGsuz0vtZW072JfT3Zbea8hlNEZKmwOxrnJlGGl9ZZiu8llhb\/X5NV3+4HtMtD\/+zOtO19LkXLdL33HSHw3+8rQ7k6TlK58MW3omgBGk5B9xPPPS\/rjjgVWx74e+n26jtpT+wjV3DwY1k7Hx42ljsufArP71LQMPdfF0unY7XaMu7XFNFTmv1PKkQbuk9PNfPhmNhlREf39EqxVpbkx\/\/0BerjuQGpgTU+aVWh1p0Ch1Tpd5pR5LuWvIG+scGP6ZrRidcPmn1WqFE2273U4jMEZUbNO6Rg+c5E8\/\/fRU32UlJ2sn+be+9a2DIzBGYbpdQtJ2prQh51m6THTttddG5+hLq7LVZSpt42Uve1maMCsYMeJRXkJSLuDRXoaNbM0Bikm+gg51cdRRR8Vf\/dVfpQm+eZ287LS1vIRkXaNNRofUN4LDHn6VHgnvNeRyGiOmZ8GckmH2zwJ7fX6N6O+ZnkPU0f90zoERpLg92pwXt0v\/\/oG74rZjdku3TVtKP3zV5weDmuzDiS57JoAxsjLSjzjmuTDK1Zvoxq7PepM9B+ben\/4yoq8vovpwFWks3GxuRHWNPT2prgpqHrjk8rWuW5f2u8aJnLfZ4lVx440r49hjH8hZ0W4PNFk1N6wtFawLGqXO6TKv1JNSXl1DvncjnQPDf7MFJ+DTHECFwU7gRkmc2K+88so0B8all\/PPPz+cjKGOVdRRV7Bg1MKlG6MsgiB39aijvrxMXlcZ1mWDdrWvH+2wh4Z85fAU3Nw+W7WpbXVyfl7KU1ZiTo1Ro5zHxly\/bE+7p43gr047rF\/25TKUwIjtuZ9uS+9F5DIaI6VnxZySB1dl82NW2Ft9fmWD+R69mh5pDszKG78TN79pUQouysm1ZRBS5rvsIy04EaSol7c5L42suD06z3nptlSuXl5nfZZFALM+zWz46072HJjtfvj9tZ3W3x\/R1xdRBTVL\/+QVsed2WwxEIEcfHUvP+WhEuz24jmuoyBlZH3vsgymQaTZzSUTVXHpuTF\/fUJ76yDmllicNGqXO6TKv1GMpdw25ngPDUxsPbhN+73vfm0ZgvvzlL8frXve6WbPxgqO777473fI8FUabKHzppZeG0ZzR2vdeQ65HY8T0LJhTMsz+WWCvz68R\/T3Dc174Etm+bnNgBB\/3feZtsfSkb6VJtibX\/u4H\/5RW8bTcrQ5+czQufDClc\/6DX\/vo4G8bzd9z\/3j40vNS+Uy+1AHMGL0\/2XNg5n7otAh3bHjMrgij2exuSX9\/RF9fLDzj9IFrQptskoKahW\/\/71XehyPa7bReeY200Vj7dus7b98kDe4Y5Gm3I82PKdcptQalQaPUOV3mlXpM5dU15I11Dgz\/bIwYnTBaYeQhj5TMJj8YWbENU2GzURejMUZpRmvfew25Ho2R0uZArKtcGUZaXxmmq3xW2Ft9fg3zx7w5Odn1s3U6\/acvZIP4M+u8XPHz78Tcpc+OBXu\/NGXt+P6vx6KD35gu7az69bUxb9fnht8uMl\/l0X\/9Svo5gMd+ennM32nvVH\/LP3pDSBuVSRkz9FIHMDPk+NRtoxHRbEaYxCKQMbOzDGqWLUvV1nrp74+ogpoQ+HigyJqgZsErXxmLzz03ot1Oq2hWc6qljOqlvz9csUrBTH9\/lVH\/1x6oPVB7oPbABuWB1ff1x4ob2gm628Y9ef+d4VKQS0IuDeVgZM7CRTFv210HV1Hv978b+F1CgU0uWP3AXSmwyemZWNYBzEx4fV19NhoRzeZAUHPBBRHjCWra7VhSBTACmVgT1DSOPjSWx2lxywXt1GzuWvxjNKbjcn0urpe1B5IH3GHj2SgmnGZGm2RrMuoXv\/jFtP5YXsz90I\/LKCbQWn8s6020zmT143kv2pqoHZO4Xt1U7YFhHnjkigvj7tahifv+6uhhZRJP3PazEIDsfMa\/RmPNpSKXiJStDy5N5aBIYNQN5eqtTz953Z4LYO58cFV46q5lNrIXlpN9F5JZ98jbVmp50qCj0YgVB1VDfcuXR6wJalb88teBMLxSseLFVXmqXLz090dUQY06jSqQuaK9SdwSu8cVcWi04rRoRltRiHU6Axl9I9b8lVqWNGiUOqfLvFIrN4u\/vguJJ3qf\/FwTl37cBn3VVVdFeVty5xa4W+eXv\/xlZ\/aI6X\/+538esaxXCwRZ3\/3ud2fEPO8l5M5pjJieBXf1DLN\/Ftjr82tEf3fcBWTbMJ315x70ptixdUVi0etPzV0PLo2kzF2yNF0mcqnIHJhVd96Yyp9c8Ug8cd9tSXtRtukWW5Eh8EmiesnrV3LE\/4V\/eHiaY1NO5t2gJ\/G6ywhf+re7RnTKTBRM9l1IZq0jb0up5UmDRqlTevEOcVdFuvxUBTZ3ff3SWHnjjXF7dXJZffLJcf\/xJ0W3oKYR\/SFwWR6tFMg8FQNBzSFVtH7aJqdF+7R2+NMfaJQ6p8u8Uo+p\/KGN90m8\/DNbMUfDbc8mnNoGIyZ77LFHmpjrpwTcRn3mmWfGF77whfSbQUZWyhGczsBHWt13v\/vdcd9996XfBvJwN6M92hMoqJN\/moA2AqQc+mdHzqeNisi3Lu3Ju+qWP1\/gN4i69aNOtlc\/2rPUPm17\/ASC3z\/yALrjjjsu\/byAsunCew25PxojpWfFXT3VF9ds\/6ywt\/r8yvbyPXopfe9mO8TCfZqJh3d5cTZtcLnwOS+Np1Y+Eo\/fen26DOQykfkt7g4yQVeg4pKSeS7muwhyzIfJQY55MdLyBxuthPUFKAIWIzvaLUdhJnP0peouenIE5ppbHwrPgsm\/g5SXnhMzUyMzk30X0tIuM9XtkMyEyhuNWL3zzrH6gx+MhR\/5UET7ioGJwnkiTKsV0WzmLgaXZVDTrAKZ2GST2O2Fz4mlr31FpF+LrK43sWdwhUpIo5Lpv9QypEGj1NJm8W+0dyFV\/uXjnsUOWgeeU+K5KIKDZcuWpduojcx4OJw8D7t705veFG419lwTtx8bvfnsZz8bOfDJzR922GGhrqfjbrvttuE5KWeccUb6GQLtGc1R99nPfnbqR9+XXHLJ4IPvlOXggu6k89Zt9qgzUj8CG\/a6rGWkyfao34m7hdxFdc4554SgrrN8KtPeS8h90BgxPQvu6hlm\/yyw1+fXiP7u8tk+bPumubzbXUgCjcWvPyXuOvXg6H\/L4nR30TZHnZk2ydNyH77q84P5JvcqWPy6D0QOSCyl5Y+E4Gbnj107bARGcORhdhvsJSSjL573kp\/9Ui7lKx\/JYVOZP9l3IZkljmxzqeVJg0apc7rMK\/Ww8kYjotGIPFKTHt2b59W0WhGtVkSzaZVhzL391lj4\/e9EtFrpgXuDz6kxabi63rTwi1+IhXfePrjOiP2vqbFW+WZzJuvXqFMPa7U\/b066GyAVVi\/rXV7ZWzUz+K895IxSy5MGvaFhlEUg4M6ZkX5KIG\/zc5\/73Hj729+eRmgsc\/5Iy2c961nhN4cEBTvssMNgNc9HyYkXvOAFoW9p+R4GR3fCRnn5wXYetifwkjdSPwcffHAKSLTvByFtq\/q9hOMK2SYaI6XdhbKucmUYaX1lmK7yWWFv8XnAN5gu\/+gLY+2PP3PdcikwMVICdyHlMsFNHkUp88uARGAindfpthSkGHEpR2AEPrue8\/PQR7d1xpvXcyMw492Ayaj\/3ZseiD\/7Pz+Jj156czz+5O8no8neb6PRGDGo6Wu0oh3NWOuvvz+i3Y5otVJQU51pYpAqqEmjNe32WqvVGR0eaDYjms2IZjOi2YxoNiOazYhmM6LZjGg2I5rNiGYzotmMaDYjms2IZjOi2YxoNiOazYhmM6LZjGg2I5rNiGYzotmMaDYjms2IZjOi2YxoNiOazYhmM6LZjGg2I5rNiGYzotmMaDYjms2IZjOi2ewwdnjSZRlPtfXUW5dTRvspgbPPPjuMyOQRmOGtTSz1wx\/+MPLIiOBFEKMl2lLQYSQlBytGh+QbWclBjXQ3rrrqqnRJSPu\/+tWv0tOG1SvbHq0N9WtqD2yMHiiDFk\/efdpRZw0bgRlL4DMev\/VkAOMXp03kdenI8pf3\/i5ecvY18YNbB27lGs8Gjlb3vkcfj3\/8yX1xwZufG0sXL4x\/vuE\/RltlePmGlGo0UlCz7JblEVdcEbs3nord45Y4LVqJdnQ5ufX3R\/T3R7RaEa1WpHu03d6EOqiJrn+Vb\/m3Z+kw2t025pDAaIY5MC79uJzTbrfT6IrRDasJHiytYx7KjjvuGIcffniqI\/BRJgiyzAgIXJK58caBSYQ5v9ty3333jVe96lWDPz2gDlvY5Wd78z3EAAAQAElEQVQE2Piud71LdqLbzxekghFeXLayLX7XyXYaiZE+77zz0jZ86EMfihwYuQz1hje8YTCYGqHJOrv2wEbrgfs+dVR60m85CmNURqAzGU7puQBG8PKn518fO1XXCb997Atj0cI5sWN1TfTw520Xp158UyifjA3Pbdz625Wx1WabxsJqSPA5O24R9xSTyXKdjXHZbA5Mn7nilkb0L1serVgeh8YVsUkMBDVHxwUhsGlHVTE6\/vr7I\/r7I1qtiFYrUlBj3kcR1MydoTs4Oiytk6N4QMCQHz5nFAWHHXZYWsvJ3QPp5KmTf0ogr+PBbO985zvT3BV1PM5fnstDqYE1L\/Ksf8ghhwSdy0+rAmBt6U87a6qnuTXag\/ryS1uMorBFO51zYARU6lpPuXVzP7SfOGCLtvUrjw05T9vqW9f22H7tqVdTe2Bj94BLQ\/nyk0tT3VCuHl+tLz0XwDy84sm0Ta3X7JWW+eXIFy1NMpenxCgvZ3\/7lnjb528YrCX4MaJjZKecEPz0RZsN1qnFcA80GgN3bt9yS0SrNVDWH43oi2XRioGgZvfGU3HasqqCW7xbrYhmM7r+9fdHtFoRrVbMfdnLYvc99ogFe+8d6dJTdbJKl6e6rlhn1h6YmAdm888XTGyL67VqD8ycB4yseCie5bqsUD6WeutqQ1nPBTBGXiDweHTlajbG3Q+tild+6ro0KqMsZY7yYn13MpXVPnPl7amN+\/\/XoXHAbluHW7V32GqzcGeTea0PPPZEbDZn6JHQ5bobu240IpYvj+CnKv6IRmPII\/39Ea2+Rmxy9LI4tL08+t5yxUBFUc84gppuIzV1UDPk51qN3wPl6MlooyVGXMqRnvH3Vq8xuzxQWzsVHvCAPPNfystGnVq5euvbf88FMDbob968TxzT3CVed\/5P4rIb748DP\/pv8aYDdgz5ykfDyMtr\/mC7eH1Frmv05YpfPBDP3GHzlKVceusFc2OrBXPi2P97Y3zxmrvjZc\/ZJpXXLyN7YPnygctL4hPBTFmz3Y44+uiIdLXowkb0N5dFinzM+3jqqYEVq6DGs2pWHnBAueqQ7u+P0DDc9dRx+Sna7aG6s0Rdc8016dZft+fWXF374uqx++DOO++cJUd5bebG7gGXhlwi6nbpqDNPPfXXx2c9GcDYoFfvt20YKckc\/\/LdZY8JdV9drd+t8rN32HIw+46HVsbDq56MD7xij\/jkn+4dfcueGzsvWTBYXgpP4v3uTQ8Gbv6PFbFizdMWe2np6ZCebrtizZMsp9q27Xd6Mk446cn4+S+fjPdXy512qQKUNU7r748Qfwhk4ArRTb9+KlbstEuseOOb4tH3nxS3fOFL8cBDj6YnCq\/49r\/EipNO6frwvdRkf3+EBlEGNaIljbfbU7pPJurbp22\/NA6oArVzzz03jjzyyJraB4PHwFiPh+OPPz4dQ46l8bynJ3rMjqePyaw7m+ydTbau\/v3Q53L6LN2AXnougHE5x\/wUl4B6yc+exPuav\/5R4Pyrbo+b71uR8ARGSFtmpFGms7ZUBhqlzukyr9QjlleX2u59dHV4kqX6UBelzukyr9TjLd9s8ap407tWxJXXrYh2xXuOf2LYruvvjxB3PGOvTeIZe24aHzj593HLb1fE7Q8+kWz1ROGb93lR3HXcB8IThX997+\/il1f\/LG7+yiUjPlE4ddDfH9HXF6HxKqhZuNncmLfnnrH6zctixcmnxgOXXB62BeuzfdZnb\/attPZAo9Q5LW\/TLZ8ef3Hih+Ijn\/zb+Ph5FwwijZxXannSoFHqnC7zhulzPhP\/89SPxWn\/+\/xh\/Vkvoz7KdNaWykCj1Dld5pV6POUfqWx9\/4fOWsvWsj0a2gUNGjRo0KBBgwYNGjRo0KBBI+nK3m6+zeWpTrWvJzv9tve1wrFUHls0HGegQeOuNZ8Ht\/x25VqfVan8wVXp\/UHDuqBBgwYNGjRo0KBBgwYNGjRozCZ7y88DtsO2gAYNGjRo0KBBgwYNGjRo0KBBgwadSZ+XG+BLzwUw5rh4YB1fm2wLAY3ARt768ot7Hh1sYuetF8RWC+cMpkcTR+y\/Q3zjfzw\/3nHwLoNVPWERMiwz0ijTWVsqA41S53SZV+qRyj0d0tNtl249X\/WEupCwzEijTGdtqQw0Sp3TZV7WL9p3s\/joRzaNn935aPzLvz2WYgtlmTtv3yQ+efa8eMHuT4ujXrNHfO7TW0RuzzLzxC67VaMxBw8+UfiGOx+J1TfdHOFSVBWwdPuZBH14AN+iv7sotjn7jFj6J6+IPbfbIjxVeLv3vCOWnvPRWPrjqwf7Uz\/3V2p50qDh6lf2rbQy0Ch1Tue85++9R+z3gv3jlf\/pJYNII+eVWp40aJQ6p8u8Ur+ieVA8a5\/94rnPe8Gw\/qyX2e8F+w+zqVxfHWnQKHVOl3mlHk85Ww8+4AVr2Vq2R0O7oEGDBg0aNGjQoEGDBg0aNGjQ7O3m21yuDg0aNGjQoEGDBg0a9PY77pSO285ja13p\/HngCmw+FtdVXxnUBQ0aNGjQoEGDBg0aNGjQoDGb7C0\/D9gO2wIaNGjQoEGDBg0aNGjQoEGDBg0aNJ78\/Yb7bLNNbWgvYr5Lvnz0z3\/xwjSJd30CmUXz58ahz14Sv7znsbS53\/jxvSktP2WM8iJ4OWL\/HeMley2OPZ6+MN3a7fZuT0REqXO6zCv1lJVvNic93daTF\/UHfaHUOV3mlXqyyv\/gOfPS9BdvdpeYli0b7uT77pkXn\/jYZrF5Zfd\/OXCLOOuMOfGbO+ekJ+iyB2wBPXfP6jJis5nm1LjkdP+jjw\/MqamCGpefotkc3sGalKBm269+KRaecXosfPl\/joXVSM2zDnxu7HH8\/6jyPhwLv\/edtD\/1k9EfhtKbDfpWnjLQKHVOl3mlnvLyyp\/bbTknTFDXF6a1\/3lzkj\/LPkud7Ul5la0L5m6ylq2prGpnWN1eSFf2dvNtT9pb2Zp925P2de7PWWXv0OcB38KxCho0aNCgQYMGDRo0aNCgQYMGDRo0nr7lZms+CTe8xaa9ukkeWtc46cowAnPQWVfH59783DAys9Pi+RM2+Z2H7JLuONKmER3psTb25WvvCfNgcn13LKFMZ22pDDRKndNlXqk3xPK3HbcqLrggIk\/8feEBVfBhQ9dwZzUy02oNTP7Nc2YuvWzglnpVRvRPoxHRbKbLT2l0RrRUdXLXP16aLj\/FsmVWXwtBzcIvfSGi1Qp3P23jTa7j6lKU27pXXvb\/i7LPBx5bPawNZciZpZYnDRqlzukyr9STUf7Qyt9X9g\/ZPNntaw9sRalzuswrdffy4baW9WlYDzRo0KBBgwYNGjRo0KBBgwYNGt18W5bTUBc0aNCgQYMGDRo0aNCgQYMGDRqO3eHpJ6pjY+gyrzKoCxo0aNCgQYMGDRo0aNCgQYMGjdlh7+w5Xh9ZOfQ5yr\/TwUi3SY+UP1Gbei6AEVgYaTn14pvip8sPCqMw\/WccEn+421bj3kajOMgrGm351ntekNq0lM5loy2PqC4fHbTnksFqSzafF8gZpZYnDRqlzukyr9QbcnmjkQZQ4pvfWhX\/fPmtcfLJq9eKMfr7I1xmeuOfLAgxhTm6l319eODKX+ArlDoajVjwsv9UdVQFJ6KmKqh55MZfDV5+WqtDDaC\/P6Ldjmi1Bi8\/JQOqoGaXT50dC66+Wq2E\/pAS1Uupq2Q6Nsq8Uk9H+dYLNq1smKurxHT3rz+kzquXUlfJyrbO989wW8v6NKwHGjRo0KBBgwYNGjRo0KBBgwaNbr4ty2moCxo0aNCgQYMGDRo0aNCgQYMGjSWbz03+prGky2eXPGWgQYMGDRo0aNCgQYMGDRo0aNBYMivsnT3H66IFc7h1WhCgeNKu26Qfv\/kHYVneQi3NkNF+R0mdsdBzAcxO1QiLkZYPHb5X7Hva99IIjJEYIzJj2aCx1Rl\/rXoEZugbG+\/5xgQapc7pMq\/UA+WrY+E2q+KDH1ydRmba161IAyhV7KB4kP7+CHnHvH1OuJafA5qf\/vvqtb5FDq5UCf2hkun\/3qctjWg2q6BmeXoyn4nCt17388EhofuPPymi2Ux1h73090e027HorDNjxyOPjAULF4agxqWoOK0VUZWpX\/aV02VeqaejvNsogX4z7EGZztpSGWiUOqfLvFJPrHz2fKPt5tty+2nwA2jQoEGDBg0aNGjQoEGDBg0aNGbHiMbQ58vssHf2HK\/TOQLjtmi3R+963q2x2R5\/GJadt09P5u8h9VwA4w0HIy5GXozAGIk5tRqRMTJjhEb5dFOPwMwb5vIlXb7FlRVGL58bvsnmdfZ91twUP3jGTDVgEtffuDrMm2k0co2BZX9\/RKsV0XzhwjikwuhMX18M+4ap5uj9z4tFz9orotEYCGqWV41eccVAQFNdgjKnBtFsam44\/f2x8PvfCROFXX4SWZkonDSDqqBmLP2rkxsutTxp0Ch1Tpd5pVbOt0uqb7I0llT7yzIjjTKdtaUy0Ch1Tpd5pZ5Y+ez5RtvNt+X20+AH0KBBgwYNGjRo0KBBgwYNGjRoLKmOgyXF\/qehDDRo0KBBgwYNGjRo0KBBgwYNGjRoLJkV9s6e43XSR2DspFEQyAhULEepul7FPRvAuI3aXBXsduJ30oRbIzNGaNZriye4cj0CM\/QNiQt9wwONUud0mVfqgfLV4Zssjc7yzZ\/2eLztuFVpzkwVT4Rbs5tNNYfI82Y8CuZpW86LPDpTxQ9pdKZss9RakAaNQd1oRDQaaU6N27rTsFAVUf3y+z+KB449NjyAL5pNqwzDnJo0GtNqhUBmmy03i632fkbSUQU1qz93wbD6+kPOLLU8adAodU6XeaVWzre+ydLoLJeGMpQ6p8u8Uk9N+ez5RtvNt6V\/aPATaNCgQYMGDRo0aNCgQYMGDRo0HAfD0\/UcmPX3x+w5XqdzBMbxhnwpqbx8lLVLTMrVW196LoAxwpJHWm4986VpvopRGA+nW9+NXZ\/16xGYqR2BWVJ8Q7SfpEE3GgODJHmAxNLojLKSamAkWq0QP6TRmTe+dr7YIcUVua1cXxplOmtLZaCx6Fl7xoMCmA9+MM2lcQdUmlfTakW0WtHttu4yqHEbt5GaFGUdeujALd1f\/7sI0VbVQdlXlUwjSmVeqcdS3m2UwHoZ7aFMZ22pDDRKndNlXqknVj57vtF28225\/TT4ATRo0KBBgwYNGjRo0KBBgwYNGktmxYjG0OfLKPZ2fW8sKT4\/aNh20KBBgwYNGjRo0KBBL6l8SmNJ1Tdo0KBBgwYNGjRo0KBBgwYNGjRo0KAxUyMwLiV1Xj5a+IeHx9OOOisma2Sm5wIYIyxGWsY7ydaOmkrqEZgnhrnXNxjkzFLLkwaNUg+k1z0Coz7URdaNRkSzGWl05qZ7HwujM1X8EAe8ePhMe6Mz13x\/Tiir4oXYb++5KbCpBkNSzKA9aBulzukyz7dY+RllaV6Na14VHsAX1UhNNsicmm5BTYiyHsdDJAAAEABJREFUqqAl3dL99j+PZFQ1dJRGaxiHqlz7KPvL2lIZaJRautsogfyM+ijTWVsqA41S53SZV+qJlc+eb7TdfFtuPw1+AA0aNGjQoEGDBg0aNGjQoEGDhmN3eLoegVl\/f8ye43W0EZj7Lzox\/LDi7x97yOESRkeMkhgxKfOVS8tXrl5aYRwv2\/75J+OhS85JfYxjtRGr9lwAw1K\/W5R\/NdolJEjLVz4T\/NURe8cR++842PXSxfPTg6VyhnTWltKgUeqcLvNKvTGU54dW2VZMdPsbjTWjM+0o44doNrU6hICm3Y7IAY35M+UIzWj9s3eotUj7vlxnUDcayaCFH\/lQRPuK4UbpvNksmxnQVVCTRmuUo4q4zKlBGkKqghoP4BuoPPCqPwykBuzJ2jI\/dI9GWTeny7xSz0j51kN3mbEF7AANGjRo0KBBgwYNGjRo0KBBgwYNOqqXbr4ty2lUVdM\/jZSoXmhUMv3TSInqhUYl0z+NlKheaFQy\/dNIieqFRiXT\/9LKt8PSXT67eqp8Fthbfh7wHZKzqxcalUz\/NFKieqFRyfRPIyWqFxqVTP80UqJ6oVHJ9E8jJaoXGpVM\/9tsMS8tu72svPE78eD\/+\/Swovv+9j2x1cFvjsaFD6b83\/3gn9Lywa99NOZss1MYVZm\/5\/7x8KXnpfzxvKz4+XdiMn7EMffZcwGMIOVPz78+jMS4dJSRlq88Gz+dy12WLIhdt1kw2KUHBCFnlFqeNGiUOqfLvFJvFOVrHlplWzFZ299opPghTV0xOuNyk5ig2dTLEAKacoRm88qeaiAkxQvtdqSH6ZU2LazKh9buUj5vTlk8fP1GY8Co5csjGZZHatzi3c24qiUBDUJ5RbrrqbgNa+EZH04P4Kuqpv\/SVhkeYOaBhjQ6y6WhDKXO6TKv1FNR3mlr2R8N\/YIGDRo0aNCgQYMGDRo0aNCgQaObb8tyGuqCBg0aNGjQoEGDBg0aNGjQoEGDb8s0DWWgQYMGDRo0aNCgQYMGDRo0aNCgQWNW2Ft8HrAdbAcNGjRo0KBBgwYNGjRo0KBBgwYNGvxp2YkRld\/+3fLY6pA3DxYZVVn162tj3q7PDbc6b77vYfHov34l1H3sp5fH\/J32TnW3\/KM3hLT8lNHxoh2jNEZrSu771FEb9iWkh1cMXApovWavYS7J6Vw+rHAaEh5id9v9Kwd7yj9iljOks7aUBo1S53SZV+qNoTz\/GJptxVRsvx+bbDYHYodvffvJdHUnBzSdl5zYUA2ERKsV6apOESukoOa7352ryiDsRc4otTxp0Ch1Sq\/5Ucv0qOLKqBWPV0PSIq41QU3Xy08REdnIVqu7oe225mPl6qdixeMD7yUZa\/X\/xJNR5pU61y\/zSj0l5R22lv3R0C9o0KBBgwYNGjRo0KBBgwYNGjS6+bYsp6EuaNCgQYMGDRo0aNCgQYMGDRo0HAfD0l32fU+VV8dCT9nTxV8+v\/gWbAUNGjRo0KBBgwYNGjRo0KBBgwYNGjRG+jFHIyoLn3FAzH\/mi1UbZM7CRTFv210H00\/ef2f8\/ncPp7TAJonqxUjKSAGMOS7d5sAYvVl08BurtSfnv+dGYIy0wNN387NfLKXlY3I2fXyt+DHHL1979+BKd635IbScIZ21pTRolDqny7xSbxTla35ozrZiOra\/0YhoNgcCmi9+fVX64ckqdohWK9aaQ8OmMlZ42cvmxsEH7xKW1RWd+MdLnkg\/hKceJsX+RiNi2bIQ1JhT8+t7fzdwW3cV1JhTE82mrtamNLS6\/ORZNbs3D47VrdMjRV\/t9jBbNcBe0Ch1Tpd5pZ6Kcj9Aql3oCzRo0KBBgwYNGjRo0KBBgwYNGjRo0Mg\/6klDGWjQoEGDBg0aNGjQoEGDBg0aNGjQoMG3ZZqGMtCgQYMGDRo0aNCgQYMGDRo0aNCgMSvsrT6\/2Aq2gwYNGjRo0KBBgwYNGjRo0KBBgwZ9169\/GStuaCfu7f+V7GG4dLTiV9fE4td9YFj+bEv0XADDgZ6e+67mrvHyc69LD7KzlJavfCao58DMjygc7xorclap5UmDRqmlXUM2l4BGZ7k0lKHUOV3mlXqs5S\/ad7MUE6QrO+2IfGWn1YpYtkwrw7njjrlhJKbVivCU4L222zzdVOQ27r85Z36020P12YOcU2p50qBR6pxOeY1GxLJlkebUiLaykVVQE61WRLOp+losuOvO2PZ\/fyyi1Yqogpo9t9sikrGirwpzalL7a9YstSxp0Ch1Tpd5pZ5Q+dbzrZbQFlKieqFRyfRPIyWqFxqVTP80UqJ6oVHJ9E8jJaoXGpVM\/zRSonqhUcn077g1ryQlqhdlqGT6p5ES1QuNSqZ\/GilRvdCoZPqnkRLVC41Kpn8aKVG90Khk+qeREtULW4el6zkwaQ5b5Zr0zzdIieqFRiXTP42UqF5on1+VTP\/SSInqhUYl0z+NlKheaFQy\/dNIieqFRiXTP42UqF5oVDL900iJ6oXe6sd\/F3e3Dk1s8vl3VLnD\/x+77lux6udXRP9bFofLOp6ae9dph8WTjz0ST654JJ6477bBFcx72XSLgSfhP3Hbzwbz5y5Zmi4zDWZ0CKMzedJvvowkLb+j6oSTPRnA2Bq3Tef5L5bS8meKeg7MOuZ4VDulvOZaJYfPAaky1iqvriGbS1AVpf+1yufNSW2kwuplusobjTQAkp4OXMYKJ5+8Og44YOgSYmVS+jf40dcX8bEz5ogTBu+U9sOUaLdTtWHbIsf2gEapc7rMK3U0GhFVUGOkZticGgFOqxWrX\/ISTawNY6tyQY05NQs3qy6LmfhTRWDm1ES7PbiO\/pAzSi1PGjRKndNlXqm7lZfX6dWFeqBBgwYNGjRo0KBBgwYNGjRo0KBBw3E7q+ydt+mw48+2wLaABg0aNGjQoEGDBg0aNGjQoEGDBg2+LdM0lIEGDRo0aNCgQYMGDRo0aNCgQYMu58SldPV5pQy9kF7yn4+OHVtXJJa8ocWsYWxz1JlpMq5LOtv+xUXpqblLl18e83fdJ0zQFagINMxzMd8lz4dZdeeNqR3zYsyPkZ8yOl6sKyAS\/OgDeVKwfOUdq0wo2bMBTJetmdGseg7M0HwKO8I1VtAodU6XeaVW7hqyuQQ0OsuloQylzukyr9STWd5oRCxbFvG+9z8eX\/7y3bFixco0l8ZzaKCvToo4YVhQUw185Cs6af5JaXOptScNGqXO6TJvxU67RDSbKfpafdllceMvfx0PXF99W1oT1KxzTk1fX0SrFcOMrYKaQWOrDsu+quTk2\/\/40PGlL+gHNGjQoEGDBg0aNGjQoEGDBg0aNGg4bs0roaEMNGjQoEGDBg0aNGjQoEGDBg0aNGjQYOuwdJc5HT1VXh0LPWVPF3\/5\/OJbsBU0aNCgQYMGDRo0aNCgQYMGDRo06CcW7xIL92km5u59sOwx41bnh6\/6fBqdEYDkOSsuN5kPYzTFUnqkRnOAoq1cR7Czw\/FfTclcnhLr8dIzAcydD64KD7Bzy\/RIKFdvPbZ3wqvWc2BWDfNdus5a7bOcKZ21pTRolDqlq2vI5hLQWKu8arvMK3WuX+aVekrKK3u1i0Yj0nNo3nbcqsHLTl\/8x5UpBmg21VibzqBm82oE6hl7bho5TjCnplzL9iDnlVqeNGiUWppv766GeKPZTEGNOTWDxlZBjTk14wlq5u25Zwwa226nOTVln6XWvzRolDqnyzzzHuRDPmjQoEGDBg0aNGjQoEGDBg0aNGjQoJF8+\/DQr6krgzLQoEGDBg0aNGjQoEGDBg0aNGjQoMG3ZZqGMtCgQYMGDRo0aNCgQYMGDRo0aNCgMSvsLT4P2A62gwYNGjRo0KBBgwYNGjRo0KBBgwaNe9OxSnVHgOKx\/wIMNcoJuDu+\/+uyEsrVM5piKZ0KurxoY+tXHRf3nP36dAdTruIWbSM3ynPe+ix7JoAxOdcD7FwuGgnl6q3PBk903XoOzPxhrlva5Tp6WWG0cteQzSXI66iftaU0aJQ6p8u8Uk9FOXu1m9EfpBuNiD951bxhV3R+ddNT6epOqxXRbKq1Nm7l7uuLaLUG5tTkO58OPTTCnBpUsUJaMfeVEtWLNCqZ\/kstg2\/NfaAxWN5oRDSrb2Yf6XhOTRXURKsVsWyZ6muRbunu64totcJIjTk16Tk1ayIwc2rKlfSHnFdqedKg0WnrsLIux9pMlnfz7Uzao2\/wI2jQ4Nth6R7zJ9vAVswGe8vPA7aD7aBBgwYNGjRo0KBBgwYNGjRo0KBBY13PgVE+FbiN+rcXnRDm1phnY9QGK35wcTx48UeDdpu1euvTf88EMOuzEdOxbj0HZuOYA5OPpbWuY1cjJrnMcq3y4hq48r323CSazTT4kQKZPJ8mxwnNplprY6RG0GJODQQzApvnPHNOOQCS5jSwIbdQannd5mnIz6iPlG40IprNAWNNDu40dtmyVK3zpQxqzKkZnABUGW1OzcLvfWdwlcG+1uRIY00yzHvIWj56Nd3Ntz1tbw\/MgRmPfxwL46mvLqb1eCk+D\/SNae2\/+LzRN0bqnz9z2XQtjbCMdBu1ERwoV299bKoDmPXxXr1u7YFxeKDRiGg2B+IEgUxnnNBqRTSb3RsU2PT1RbRaYQBkMFYwB7ecW9N97QnkNhoRzeaAsSMFNc3m2g0zVATWasUwQ6ugppxTs\/aKdU7tgdoDtQfG54E6gBmfv+ratQcm1QONRkSzORAnLF8ew0ZrxA2tVkSz2b1LsQJarYhWKwbjhb33XpCeWfPhD8+d3Jih0YhoNgeMZZwozMP30GpFtFoRzebaxjJyhKBm7oc\/HAuuvnrtdSY1p26s9kDtgen2wCNXfTFdKnK5qGQyLh3lbakDmOyJUZb1XUhDd4lwlZnuoFHqnC7zSq3cLH53c9DoLJeGMpQ6p8u8Uk9FOXu1m9EfynTWlspAo9Q5XeaVWrmnCP\/pG58cnFfz2OMDTxLOsYI7oLo9Tdi64gXPrPnIR+ZGqxWDgY3RGqyZthJiCnWt09m\/NJSh1Dmd8hqNiEYjVpz0wYHAZk1Qs+KXv67yTolotSKaTasMR8eVAXM\/8pHY8cgjw8P30nNq8khNX99gff0gZ9CYqbTj1p09M9W\/bceY+6+OnXHV73LXzbSuPwvsLT8P+AZj3h\/T7N+RnsSb7Z2Kpbkt5sC4RdvlopLJuHSUbe6ZAMbdRX6w0ZJxnr77p3\/zk8i\/fSS\/LFdnOqnvQqrvQiqPN7P8kfNKLU8aNEqd02VeqUcqbzQiGo2BOOFtx60KTxPOl6HyXVCtVsRLXrJaE2shZkBfX0SrFSmwEdCYY\/OMPTdN6Xw5yl1RpU2l1rA0aJSakXct3iHuOu4DA8ZWQc3gU4VbrYhWK7reAcW4KqhRnib8MIyBzUNjxcmnRvT16arrHVBl\/zRS5eqFRiXTP42UqF5oVDL900iJ6oVGJdN\/fRfSqrQPkjOqF75BJdM\/jZSoXmhUMv3TSInqhUYl0399F9Lk+tXj3rcAABAASURBVHe0u5CS06fgxYPuFj7npVPQ8lCTPRPADJnUm6q+C6m+C6k8Mpd2uZNjpsobjaG7oFyGuuyy1fHzX94cP71hRbokVcULKSZoNksLh2t3ROXYQf3yScNiiJOPmx+Cm76+CPUmtP2NxkBAw8j2FbHi8dWx8sYb44Fjj43VJ58c0WwON0qqCmoWfv87sc3ZZ0QOatz9tPS1r4hkUGXU0h9fvd5PVrU9ugMNGjRo1HchzZ9af289xe13ee+W+5eGfQ0aNOj6LiSeGBmTc91G7bbpkWutf0kdwIzRh7P3LqSBDSxnqcuRBo1S53SZV+pJKd9sTribQ1uY9PbnzUl36mgb691+Za92MtpDmc7aUhlolDqny7xST0Y53+61x9CdUGKGaiAk8oiNS1GmsbRaEc1mRKOh17Wp4of0+5F\/\/6U50WoNxBCu8niOjTujaJekzjpjThogEdxoxfaARqlzOuU1GvGgAOaD1SWo0sBWK6LVimg2VR+Gu58ENdFqRbRa4Q6ohc\/cK9IlqCqg6XYHVOprTSs01iTTcTKeNN+Wd3ZYFxNtz7qYqvXZOpXtaxuTZf+ssLf4PLDtmKzt1xYmqz3+zG1N9dKlI3NczHm571NHhdum6RLl6k2GLXUAMxlerNuoPTCLPNBoRDQaEcuWDQyIiBsENDm4ka7iArFBNJsjb5jgRsDS1xehvkBGQJOv\/NDyqphiWHAzcotrShqNAcOWd8xq1gmazTUViwVjoBw6N3QEBoCxxSq1rD1Qe2ByPWDkxRyXcs5Lp1au3mT0POUBzGQYWbdRe6D2wPR4oNGIaDa7xw+CnDxqs2xZRLM5sk1iCfFCX1+EeEIgI6bIwY24Qp47pc49d3Goa50RW2w0uhuVDWo2115Vg2AASgMENNDx2mvWObUHag\/MAg\/0VABzx0MrY98PfT\/8lMDLz70uLrvx\/tjtxOr6919ekfKVzwKf1ibWHtjgPNBoRDQaEcuWDcQR4gYjNXnUZrzBjbiiry\/CnVLnnrskXvnKBekKUA5wxBoCHDFGX19E1zij0YhYtmzAoNIYxglYms3u+0HnyqGj3KnO0LWz7k3VubUHptADs7Zpl4hcKiovHQ3Tb1oUK28cetDlRDe0ZwKYnRbPDz8VMNLPCMhXrt5EN7Zer\/ZA7YHJ90CjEdFoRCxbNhBLiB\/KeKIMbsQMzea6bRBfiCH6+iLUF8jkOCPHGtLyxRt9fRHqW2+YIaURjNJYs9m9cysrh8ZzRzqADrqvWefWHqg90OEBl4i2OvjNsfAPD4\/yEtLiwz+Q8rZ922fiP\/r+Mtb3Rx17JoDp2P46WXug9sAG4IFGI6LRiFi2bCC4Kae1GL258caV8aUv3R0nn7w6xA7LlkU0m+vecLGGeKKvL8I6Ahkxh8tSOe6Qli\/2OO3CRrQby6L\/LR1zaiYQ1CzYe+9YfO654QF8wYh1mzq7S2vraw9M0ANGYB776eWx7Z9\/clgLW73imHjy\/jtj3na7pfw6gEluqF9qD9QemI0eaDQiDjxwZXzwg6vTQ\/vEFOXAyS23DDydWKCCZjOi2Vz3lnYGONYT0JQBzu6HNuLQC5fFabE8TmteEX0XPBXtC26J\/guuiLBCsxld\/6rGlwhgPvKRCI3miClHS3VQ09VtdebG5YH8S9W3\/c99Bi8VuWQkzROP3\/pTi8j1UmICLz01AuPhdY2Troy3ff6GtCk5bU7Mfqd\/PzzMLhXMwEv9JN76SbzlYefJm8h5pZYnDRqlzukyr9STUd7tabHazegPZTprS2WgUeqcLvNKPaHyx4eOL22teOLJaDQiGo2IAw56Mk44aeipxN\/69pNRPpn4vM8+GZ5MnOOOkZ5QzC5UMUhArGEdiD8OPboRux\/djE1ay2P3\/ivi0OZTcXTzlhDgnBataEczuv7190f09UVoaISgxjbldWlMW7ry7bT2t75Pmp0F9tZP4s1Hb\/elwGTnj10bLhXdderB6ScFLKV3OP6r8dC3zo2nL\/tfG1YAc\/6Vt8e7mrvG37x5n\/QE3lMvvik+9WfPCfNf3nTAjtH6xk3dvTUNuZ1P4r35vhWB3HWp5UmDRqlzuswr9cZQfstvV8TtDz5hUxO9vv3sTYaueWEv1iSHHQvylIFGqXO6zCv1ZJTz7S2\/XampxGS3rz2kxquXUlfJ5I8yr9TdyjttLevTsB5oNBoRjUbES1+1It70rhVpBOeKagDlb7+yIn5256NxSzV6g7\/9ymPx9uNWpfhi2bKI573oidhhp99rakT6+yMEOH3tRrTazWhVIzWHxhWxSTwVu8ctQZ9W5bajGV3\/+vsj+voi1gQ1CzebG2EIqIqUPFX4gUsuH1zNtiBn0JisNN9OZnvawmTZpy3k9maDveXnAduR7afRK+nyKcfZpulaLjr4jcPmwEibH7PLub+IBXuv\/1N6e2YExugKjnzR0uTbf7\/nsXh41RPxgl23Smn5ypEy6pdZ7QHzH3p6AzqMm232Mn+TTbzODqbC1kYjotGoRnBe\/Pt4z\/FPpADnggsivviPq+Lyf3ss7FMBzhf\/cWV87JOPp1hDvGEEByN5rj8a0Y5mtGJ5CmQ6g5q+WBZd\/\/r7I\/r60lOFl\/7JKyJsdBXUbPeed1R51SWpdjum4k83U9HuVLU5G+x17EzV9k92u0\/+ft3B+mT3N53t9UwA07nRV\/z7b2Or+fNiq4VzOotmJH3E\/jvEQXsuGex7x63nB3JGqeVJg0apc7rMK\/XGUb5ZbLfl0L7t\/e3fzG4ZhL3IGaWWJw0apc7pMq\/Uk1HOtztsNWTzZLevPbAVpc7pMq\/U3co7bS3r07AeaNCgQYMGDRo0aNCNRsQrXjYn\/vtbN0kBzvLlEd\/69u8TTlK4\/sbVVfrJEPyYbPyOd90fApxmUwsDlEHN0XFBjCeo2farX4odz\/loxJrLT8868Lmxxxv+OMIM5HY7brth4VqfNdl+vdOgQYMG35ZpGspAgwYNGjRo0KBBgwYNGjRo0KBBg8bssHf4e6u0n4ZtAQ0aNGjQoEGDBg0aNGjQoEGDxtO3HLJVGibP3vH+\/dOlHbc33\/2x18pOmICbb4FWR10FltLqK1dPfjeUqaNuJ\/KVd1tvvHmbjneFqarv9mh86d\/uSnNdvnDN3XHos5fEovnV0GvVqctHylElp\/3\/y9feE+bB5I4feOyJQJnO2lIZaJQ6p8u8UkdEarvMK\/WGsf7qeGjl0DeD3t++4T+QyF7YFyh1Tpd5pZ6Ocr594LEhm6e7f\/3BtqLUOV3mddo6vGzt99p0lm\/+tMfjmX+wKpYtizTZ+Ig\/\/4\/43N8\/HC5XCXBuuvexaF838LtTghyjPWgua0Q0m\/E3u5wa3YKakS5BDfuphCqoeeXL58bDWz4z2pscGn27nxZnvfw78ccv3zTFN2Kc\/\/O5p+LSy56MKtYJf3wDGnw7PD2z\/mQL2AYaNGaHvcPfW8Pt7y3\/PrJyaH4Z\/+LBr3005myzU7q8s+t5t8aqX18b9190oqLw+0VugW5c+GBK\/+4H\/5SW5Trz99w\/Hr70vJTf7cVlIk\/cLW+hpt1W\/bSjzgrl3dYbb17PBDAMb71mrxC4eJjdAbttHce\/fPcUzJjAq9zcGMuZoHMEZsnm8wLZllLLkwaNUud0mVfqjaN8bmy9YOjw6\/3tHwik7RuwFzRKndNlXqmno5xvl2w+ZPOS6njVb0YaZTprS2WgUeqcLvNKPbHy4baW7dHQLmjQoEGDBg0aNGjQoEGDBg0aNLr5dt9nzRWrpCDHKA4EM4IcIzi\/ffSJNCfnilsaccK3Xxrbf\/aDEa3lcWXrivizF\/86IaBBO5rR+deI\/mhGO5b1t+Kj3\/\/PcfX358ZbWrvHIa1DY8V7zoy\/+ZOr8wBO7LXd5nHICxfG3nsviCOO2DFOfd8W8TfnDP0Y5y9\/PD8e++3Qt3LbhljzR2NNMn3OTW96bupz5vpf+7N97e2fPcfrogVzsisHl9scdWbs+P6vp\/Tcp+8aAhIJIyOCmXm7PjdNsN1838Pi0X\/9Snpei9ui5++0t2qx5R+9IaSNyqSMMb64rfqhS84J\/YxxlXVWGzqDlNVmSBtd8bA6k3ZzsJLzcnqGTIt6BGZowq194BsHaJQ6p8u8Ug+U1yMwpU9KPeCftb\/Fyc+ojzKdtWU9AjN0vPIT+AU0aNCgQYMGDRrdfFuW01AXNBqNiEYj0mjOy167avCS1Ue+vkNg+VPLA5tc96249bqfR\/8Vt0S0WnH\/8SfFihe\/VFPDyEHN8mjFFXFoPBWbxC2xe9Bvu\/1D0ezvi2uuWRBf\/fvN4mNnDP0Y5x+\/fE7st\/fc2GSTSNCoBnvi6KMjjOqgry+i3Y746b+vTiPCsebPtmBNMpVNbnq6+1v7vTb69szuEZi87ywFE6vv+kVs\/sLqsmWVMWfhopi37a6VGvj33Jbf\/+7hlBDYJFG9rH7grhTYVHLM\/yt+\/p2w3phXGKViTwUwo9g6o8X1CMy8Yf73jQQ5s9TypEGj1APpufUIzOZDPl3bP2t\/C+S3jPoo01lbdhslkJ+xLsp01pbKQKPUOV3mlXpi5XOtltAWUqJ6oVHJ9E8jJaoXGpVM\/zRSonqhUcn0TyMlqhcalUz\/NFKieqFRyfTfzbdlOY1UuXqhUcn0TyMlqhcalUz\/RnMWPWuvaDQbMRDltGLFt\/8l4qmnwjDOipNOCUSzmeqXL2VQc0EcHU\/FUFDTitNiWVRRSQz\/u\/P2TQLtdkRfX8Qnz56XEMwIaprVaI5RHQHP7rtHGt1542vnDwY7Rncu+\/r8FOy025FGd8rtoZF7pTFyenaPwNg2jLx9a7+3J7v+NivvihU3tBOLHrszm7LW0gjKPWe\/Pha\/\/pRJuSsodyAo6n\/7ToNzbPI8mPs+dVRssJeQ8sb34rIegXli2G7xDQU5s9TypEGj1APpegSm9EmpB\/yz9rdC+Rn1Uaaztuw2SiA\/Y12U6awtlYFGqXO6zCv1xMpnzzfabr4tt58GP4AGDRo0aNCgQYMGHY1G3HXcBxJ5Eo7RGqM0UY3WRLOZqpUvjeiPZrRjebSiDGpuid2rHBetTgvlMYa\/\/v5Iwc41358TfX0RujS6c8zb56RLWAIeozlP23JeumtcwPPHL9803vbfNxkMeIzumLfTbke029FlBKcegRnc39U+oVHJ9E8jJaoXGpVM\/\/T9\/3JB3F1dXsSjn\/3zlN\/5Isi488QD0vNY3N6cy59c8Ug8cd9tOZnmymy6xcDdwE\/c9rPB\/LlLlqbLTIMZhXBZqtscGPNgyr6KVSYke2YE5s4HV4W5Lh5aNxLK1ZvQlq7nSvUIzNBoAVf6xgAapc7pMq\/UA+X1CEzpk1IP+Gftb2nyM+qjTGdt2W2UQH7GuijTWVsqA41S53SZV+qJldcjMPwGvgQNGjRo0DBaE8tbkUZrrrgi7n\/08Xjkxl\/F6pNPjgeOPXbEy0+N6I\/l4WbwVrjs9FRj9xDU\/OpNy+OK5mmn4+FfAAAQAElEQVRxwbJ2ClA8JPBPj3wyms2IZjNip12eirH89fdH9PdHCHa+9ndzo68votUaGOF5\/3s2C8EOjO7AnJ2DD94l3vz\/bREnHzeVIzzzJmGOTW8fr9v856Njx9YViUWvP3Wt3SV4uacaednxlG8PG3kReJgPI1AxOmOei\/kuHkxnPsyqO29MbZkXIy0\/ZczQS88EMJ3b\/\/o\/2C49wM58mIz5MebEdNadjnQ9AlOPwJTHmW85yHmllicNGqXO6TKv1JNR3m2UQLsZ\/aFMZ22pDDRKndNlXqknVl6PwPAb+BI0aNCgQYMGDfrepy2N1R\/8YDxYBTC3\/P3F8et7f5cuP7kX3GhNtzk1oo1G9MdeX\/hQNNutWNZ3aCzv2z0+\/IU94693OjUFNVcsb8eV162Im+59LG65JRKeowOTllutCHdgve7PVqdgp9mMMf\/190fcccfcuO6azeLvvzT2ER4jPkZ5XPIyuoNyhGdq5vD09vF6\/4KlsXCfZuLhXV681j5wp9HjN\/8gbjtmt8iXd\/JdSCbaPnzV56P\/LYvT6EseMVn8ug+k3zFS37wY6bUaLjIEQPm2a+tAWn5Rbb1kzwQwAhMBimDl1jNfmu4+KkdiZnL0hYf\/6oi944j9dyQTSxfPD6RE9VLqKpnKyrxS1+URO261WWy35VyuSPS6f9ibDF3zwl6sSab9nbWlMtAodU6XeaWejHK+Xbr1fE0lJrt97SE1Xr1kXcn0L42UqF5KXSWTv8q8TluHlXV5r81keTffzqQ9+ga\/ggYNvk3pRiNi2bJY+JEPRbSviDynRlATrVZEs6n6cPr7w23d25x9RkSrFYZN9txui9jthc+JxoWnJf5ki+\/Hn7xqnqbTINBHP7JpXPT5TdIVriuqbvzsA3LAIy8HO61WRKsVsWxZxEtesjp23nkoMBhuyNqpyrSA+TtGefr6IlqttUd4RprDY\/RH0GMOD\/r6ItrtCHdpPf7g8PdO8t8aE+jy80Aaa4rXPrZn+PjdZot52bTBpTuQXM4pcWeSCkZh8uUf9eTBaIufB7COpbT8bghS7jrtsBQAqZ9x67Z85d3WG29ezwQwpeGL5s+Nb73nBcNGYA7Ybet45aeuS4FNWXe69C5LFsSu2ywY7G7hvDmBnFFqedKgUeqcLvNKvVGUbzYnFszdxKYmen77K3uToWte2Is1yWHHgjxloFHqnC7zSj0Z5Xy7YN7Q23uy29ce2IpS53SZV+pu5Z22lvVpWA80aNCgQYMGDRo0aNCgQYMGDRrdfFuW01AXNGjQoEGDBg0aNGjQoEGDBg0afFumaSgzpyZFD8uXR4o41kwUXmdQU60oqEnRQqsVC1\/+n2Nh\/qmEavhj4RkfjoXf+05Va+BfX2g0IhqNiGYzYtmySMGObiGgueyy1XHVVbfHihUrI5sh6MkBjzqtVkSrFbFsWUSzGdFsRjQaA\/2M5bUMeNrtiL6+SHdomccjmBHU\/PHL58RznjknTFoGDfN5lP+Pt8+JT5w1P849d3F8+MNz4++\/OCeu+d6caLcjtG9bke2hMVNp+z\/3PV3LHKAYzSn7zOlcXpZNRA99wk1k7Sla584u82Hkfe+EF4WRminqdp3NeojdbfcP\/bbMii4\/WFY2UJc\/GXyQfVJqeX4MzQ8O0ugsl4YylDqny7wBrWQAaQykYpgt8pSBRqlzusxjr\/yMMpTprC2VgUapc7rMK\/VklPPtiseHHmA12e1rD2xFqXO6zCt11\/IOW8v6NKwHGjRo0KBBgwYNGjRo0KBBgwaNbr4ty2moCxo0aNCgQYMGDRo0aNCgQYMGDcfBsHSXz65h5TvtEive+KaBCKOKHlY8vjpW\/PLXkYOarpefdOTs3WpFtFphpCZFAM76VVATaLfVSu\/FYf112lMdC8objYhGI8KPef7pG59MQcvyKs464aQn468\/+2SKtyrz4ue\/fDL9uGcOeqT94GcOeMzhwbJlEc1m1d6LnxzzPB4G26xMux3R1xfxkY\/MrQKYJWmZAx\/Bjc0V9ICGfKjHDZm+voh2O6Ldjrjp10Pzimw79A0aNGjQoEGDBo3Vvx9qW3o6MIpjtOW2\/7lPrLxxIJi1lJavfDLs6JkARoDiMpHLRh5k95HDnzFsBMaIjJGZydjoibTR+WOOfiALua1Sy5MGjVLndJlX6o2i\/KFVce+jQ8PFPb\/9lb32S4a9KNNZWyoDjVLndJlX6sko59u7H35cU4nJbl97SI1XL6WukiENGqXO6TKv09ayjIb1QIMGDRo0aNCgQYMGDRo0aNCg0c23ZTkNdUGDBg0aNGjQoEGDBg0aNGjQoMG3ZZqGMtCgQYMGfdfiHSKWLUtBzV1fv3Rsc2qs7MzfakW0WpGDmnl77hmr31y15Uzebq91rKyPvY1GxGaLV6Vn7SxblsyNtx23KiGgEfB88eur0jyeHPC0r1sRUKaOOTxotSKWLRsIePx0RKNhg8aOTUe1iYG+vohWK6LVimi1It2VJbDBM\/baJMV7Ap9PfebJ5JPcU\/J\/9aV+oul7i8+B3MZ0LF1+Wvxf3h1+hdr8F0tp+ZPVf88EMJ0b9Ja+n4VgpkSAc2exIzvXmcr0WObAlP0v7XLdsy4f8oBryOYS5Bz+ytpSGjRKndNlXqmnopy92s3oD2U6a0tloFHqnC7zSj0Z5Xy7dOv5mkpMdvvaQ2q8eil1lQxp0Ch1Tpd5nbYOK+vyXprJ8m6+nUl79A1+BQ0afDssPVn+bDQilnWZUyMSaLUimk3dr4XLT4v+7qKIVisENXlOzYJjjonF554bS3\/0r+n4ySuyHVORbjQiXrTvZolmM6LanDCHB0Z7BDRXtKuraxUuZwl6zOe5\/mePpctdLnupg1YrotWK0EazGdFsRjQaEY1GtnxsyxfsM29St7\/bHJixWbL+tcyryfNfLKXXv9WhFnomgNmpelPlSbwm8nZDuXpD5k+fqufAzBnmbNd0kTNLLU8aNEqd0pvNqefAzBvy6Vr+qcrKvFIn\/41S3m2ehvUy2kOZztpSGWiUOqfLvFJPpLy8Tq8taAc0aNCgQYMGDRo0aNCgQYMGDRo0aHTzbVlOQ13QoEGDBg0aNGjQoEGDBg0aNGjwbZmmoQw0aNCgQYMGDRo06HS2bjYHhj4EMs74zvx0qxXRbKZqnS+CGtdmllQBzOLXvGpoTk113WXhGR+ObnNqchv6xnSmn7HnpmnCsYnHAhYIeCCYsbmw6eAG0FCmHlqtiFYrQhuYu+kmw+bU2TZMdPvs\/7zudC3dpu2OI8sx9jmhaj0TwIzF+utue3jGJvHWc2CG5lPYV66xgkapc7rMK7Vyc0rMJaDRWS4NZSh1Tpd5pZ6KcvZqN6M\/lOmsLZWBRqlzuswr9WSU8+2Kx4f22WS3rz2wFaXO6TKv1F3LO2wt69OwHmjQoEGDBg0aNGjQoEGDBg0aNLr5tiynoS5o0KBBgwYNGjRo0KBBgwYNGjQcB8PSnXNOpjptTs1BLx0MalbkOTXO4q1WrHNOTV9fRFXHSE26xmJSSRXUjGtOzRRsX\/l5wLfga9CgQYNuNCK23+nJMK9HsIITTnoyIJiBslzfOjRo0KBBgwYNGjM5B2ZdP\/jItvWlpwKYH9z6cDROujJdOiovF7lsJH30hUNPAVzfDR\/v+vUcmFXDXNbtumxZYdTyh+o5MHyUfVZqedKgUeqcLvNKrbzbPA35GfVRprO2VAYapc7pMq\/UEyk378F60BZo0KBBgwYNGjRo0KBBgwYNGjRo0KDRzbdlOQ11QYMGDRo0aNCgQYMGDRo0aNCgwbdlmoYy0KBBgwYNGjRo0KBBgwYNGvRd5tQ0mymoyXNqVt54Y9z9pS\/Fff\/z\/fHInx2l6tqYVNLXF1EENebURPPQiBHm1KT+iqkHXdPjLa8+v7Jxk9LeePsfR\/2ZmANj5GXVr6+NBy\/+6OBzZsyDgZ8YUJ79tz7LnglgHlm1Ok69+KZ4V3PXNHnXbdOtb9wU37z+vjCpV3omLyHVc2DmDzvOXJNGziy1PGnQKLW0OSXmEtDoLJeGMpQ6p8u8Uk9FOXu1m9EfynTWlspAo9Q5XeaVejLK+dbcB21hstvXHrSNUud0mVfqruUd83XK+jSsBxo0aNCgQYMGDRo0aNCgQYMGjW6+LctpqAsaNGjQoEGDBg0aNGjQoEGDBg3HwbB0dbm+J9ONRqw88MCYd9qpMffzVZCSr7msGalJ11hsUAcuPy38\/nci1gQ1eU5NGrWpgpqlP746Jnt7y88DbSObRaNX0jMxB8ZdRvlZMua+lMhXnv2zPsueCWAeXvFk2o4jX7Q0LVuv2SuuufWh+Iu\/+3l8+9gXxkz\/GnU9B2ZovoYd5JosaJQ6p8u8Uqfyeg7MWte5+SXDXyjTWVsqA41SS3ebpyE\/oz7KdNaWykCj1Dld5pV6IuXldXptQTugQYMGDRo0aNCgQYMGDRo0aNCgQaObb8tyGuqCBg0aNBbOm7PWsTCZ5Xw7me1pC2wHDRo0aNCgQYMGDRrD7K2Cmmg200hNuo27M6gRtDSbVhuGoCba7YiqfNhzag49NCZlTk31+ZU7ZDt6Nc2f2bYNbdkzAUw3x261YE78wzueH3+421bdiuu82gO1B2oP1B7Y2DzQaEQ0mwNBjVmzRmjMjEUVsASazbW94vJTux2hvApkBufU0NVITQp41l6rzpmgBx656otrXT7aYC8hdfPRVvPnxY7F0HK3OnVe7YHaA+vpgXr12gOz3QONRkSjMflBTV\/fbPfMjNhvjstvLzohtv2Li6K8fERvkJeQZsTL4+i0vgtp4BJfdplZ7ijTWVsqA41SS5vF724OGp3l0lCGUud0mVfqqShnr3Yz+kOZztpSGWiUOqfLvFJPRjnfrui4s0e7Gf2hTGdtqQw0Sp3TZV6pJ1TeYWvZHg3tggYNGjRo0KBBgwYNGjRo0KBBo5tvy3Ia6oIGDRo0aNCgQYMGDRo0aNCgQcNxMCw9BXflTGr71bEwKe01GhGNRqw46YOJ9Oje6hKUpwqvOOmUCCMxzSYXDaccqXHHk6fLufspj9T09cVTt94+uA5bkTNo9Ep6Ju5Csu1zlyyNhc95KTll9NQlpDseWpkm7Hp4nYm7V\/c\/NJiW504kdyRNmTfW0XB9F9KU3YWUvG4mfxJrXqSxJjnsyZTylIFGqXO6zCv1hMqLuw4mtH5x18B0rN\/tThn9ZvgDZTprS2WgUeqcLvNKPZFyd8pYD9oCDRo0aNCgQYMGDRo0aNCgQYMGDRo0uvm2LKehLmjQoEGDBg0aNGjQoEGDBg0aNPi2TNNQBho0aNCgQYMGDRo0aNCgQYMGDRo0ptzexTvEXcd9YGC0prr89Ot7fxe3XvfzCAFNRdfbujuCmoXPfmbscvDBsWDvvWPFyacm8iUo2wLbAho0aNCgQYMGDRo0aNCgQYMGjZm4C8kk3a1fdVzc97fvYcKU0TMBjAfUucuo2wPscp5y9abMG+tomsSbiAAAEABJREFUuL4Laf4w75hlj5xZannSoFFqabP43c1Bo7NcGspQ6pwu80o9FeXs1W5GfyjTWVsqA41S53SZV+rJKOdbd59oC5PdvvagbZQ6p8u8UnctLy4Vqwv1QIMGDRo0aNCgQYMGDRo0aNCgQYNGN9+W5TTUBQ0aNGjQoEGDBg0aNGjQoEGDhuNgWLpX70JibMVM2Lvdvs8cCGjMqWlfESseXx0xypyauXfcEVEFNn6pG+mup2qkxi91Lz3no5Fv6+Z7VJuW\/mmkRPVCo5Lpn0ZKVC80Kpn+aaRE9UKjkumfRkpUL9N5F5JLR26TNtflvk8dFSt+cPFa82CUq1eZtt7\/PRPArPeWTLSBMa5X34VU34VUHiruOkDOK7U8adAodU6XeaWejPJud8poN6M\/lOmsLZWBRqlzuswr9UTKyzsltAXtgAYNGjRo0KBBgwYNGjRo0KBBgwaNbr4ty2moCxo0aNCgQYMGDRo0aNCgQYMGDb4t0zSUgQYNGjRo0KBBgwYNGjRo0KBBgwaNnrG3uvwUAhpUIzVRXX5KQc0FF8Tqk0+OlQccwNzhVAGNO6AWnnF6RDWaI6hZuNncWPjMvSIFNKedlp4qXG4vjVjzR2NNMt2htj5p\/sxtTfXSyIs5Lua6jIRy9SbDlo0+gHFMfu2H98bh5\/04Tvr6r+KhFU9Mhl\/rNmoP1B6oPVB7YEPzgKBm2bJY\/cEPxt1f\/nKsXLFiYKSmCmpCwNJsdt\/iKrAJ5TCXJs+rqQKaFNi0293X6\/HcTvOMrEzHTwjkfjf6AKb\/Px6L79z0QHzl7fvFIc9YEl\/8t3uyb+pl7YHaA7UHag\/UHli3B9YENWm0pmOkJgUtzWb39UcKatrt7vXr3LU8sNEHMLtvu3n87\/\/2rNhszqZx2\/0rY9stNlvLSbMl45577onPf\/7zYdnrNrNxttjKl7PJ3tpWe2xqqH07NX7V6vh9a62ZYVRb1yeomaZNKp\/Tcv9FJ05Tr5PbTU8GMH5W4I8\/+cP0m0iWv7z3d\/GSs68Jv5U02ua7S6mzrp8jcBcTzv72LfHEk09F+9\/vj3\/44W\/i53c9mi5tfv7qu+MX9z4Whz9\/29G66Nlyb6oLL7xw1gQws8VWO7z2LS9MPrPJr7Z+Ntk7m2zdKHw7UlBj1MalpWaTG6YFl3oe\/OrpsfRDVyV+d+0\/hrzJ6Hz1A3fFbcfsttbkXRN7sUFP4hW8\/On514e7jfyEwKKFc9LD7A5\/3nbpt5KUj+RkAc5BZ10ddzywcrCKgOZj\/+\/m9HME2rv4J\/fGvY88Hvss3TL+aI\/FYXLuJ6+4Le7\/3ao460+ekUZiBleuRe2B2gO1B0bwQJ1de2C9PSCoaTYH7oASyJiU2Wyud7OjNbDi59+JJ1c8EnO33S02222\/2GTBopA32npjKff8l13Pu3WtB9jlSb0b9CTeh9f8JlLrNXsN81X+jaRcPqywSghUzr\/y9uh7y76x1fy5Vc7A\/w9vezgeXvlkCoKetcPmVdm8kLftos1SkNRfBTv\/cN1v4pe\/WRF\/8Xc3xrd++h8DK3a8epDdd296MPD962+Kq6++uue48847k9XXXHNNz9nW6a\/ZZCvbZ5O9ta1T996sfVv7djZ8HvT\/6Lux4oZ2YvV9\/em80Pki0Nh0860Hs5+47WeDeraInruEZOQFb\/v8DfHoytXJj3c\/tCpe+anrUsChLGV2vMj3g49bLhgKXnKVnbdeEFtVIzk5\/Yt7Hs0y9q1GYr5z\/P7x10fuXfGc+ON9nz5YRuy6zYI4aM\/F4UF2r\/nrHwX+vw98Oo488sie4\/jjj2dynHvuuT1nW6e\/ZpOtbO89e0c+\/mpbR\/aNfbk+1L6tfev46fXjoO\/dr467W4cm7vuro2PBPs2Yt10jnR82pJeeC2A4VyByTHOXeN35P4nLbrw\/Dvzov8WbDtgx5CufTgQwHmL3jf\/x\/Mj8w0ffHV\/60pdqah\/Ux0B9DNTHQH0M9NwxsOzT34wdW1cMst27LqguFw0PYMxV+f1jDw2eTuft+txBPVHh+S47f+zasJxoG+NZrycDGBvw6v22jfwEXsvjX7677Alxx0Mro7z09OwdthxXO4KYl+y1ODIv3m+vOPDAAzdq6u2v9399DNTHQH0M9OYx0Hj+S2JhNeqSmbvt8ODFbxTNWbgoVt93azx+6\/Xx1MpHQt64Tow9ULlnA5jJ8s0Ldt0qtlowJ1yG+vd7HouHVz0R8iar\/bqd2gO1B2oP1B6oPTCbPGCEZPHrT4m7Tj04QcubTdvA1p4LYEzG9aONbnnuRuOkK+MHtz7M9jFhbsz7\/8se8fJzr0vQ8sa0cl2p9kDtgdoDtQdqD2yAHlh08BsH7xSiZ+Mm9lwAI7gw3+X1f7DdsEtIJ76iEfI+9WfPWeft1H+421Zx\/fKDwjLvkFcXl6PonD\/a8jOf+Uzsscceicsvv3y06tNWzpZsFxvX1bG6Jp09+ujQxOV11Z+KMjaMZm9Z53nPe1789Kc\/nQpTRm2ztGMk37KNjbbpkEMOiXvvvXfUdqeqwljszX2zk73WyXnTudQvn2EsvlXvfe9733SaONjXWGxVmX3shHXkzQT6ZgO6+Tbve+UZx7BjebrtHc1W9pT2zpSd7MBY7OVHdvKt9xj7rdsrsOfVr371wOdqrxg1CXb0XABjBOaKXzwQ3W6jVrZ08fy02eWclpQxyS8OyEsuuSTdjvzZz342Pve5z8VMBgF58xyI7jK6+OKLA2yUl8vLpQ+yt7\/97WXWtGu2jWZvWefmm2+OY445Jt797ndPe2BQ2jGSbx0DZ555ZnziE58Itu6\/\/\/5x1llnTbtfdTgWe9XLsPP222\/PyWldjtXW3\/zmN7HPPvvE9ddfn\/z78Y9\/fFrt1NlYbfX+Ut9x4Hj5yle+MiOfEWOxd7vttosrr7wy+ZS9J5xwQnqf7bvvvjZh2hiLrYxxrHpvsdXngfec956y6WQs9rKLfexk7ymnnBLHHXfcjBwL3XzjXPayl70sbrvttm7Fszqv5wKYfLuzB9J5MB3vWkrT\/\/6bxywi10uJKXj53ve+F4sWLYrNN9889ttvv3jkkUfilltumYKextekD\/aHH344tt9++9h9992TjfI6W\/GtQZ4PKsuZgm2j2evD9Zvf\/GbkD9ODDjoottpqq2k3eSy2brnllumOg8MOO2zQvr322mtQT6cYi73ZHseDY9iky5w3ncux2nrTTTfF0qVLg5+n076yr7HY6qT1ox\/9KN7ylrekVR27559\/\/ozYPRZ7k5FrXpzQfPF53etetyZn+hbXX399jPZ5wJrO99RMHRNj8e1jjz2Wzg8+t9jus9l7Tb70TCIA88Rzx+bWW289k6ZMSd89F8Asmj83vvWeF4RLReatmAdjKe026r9u3xofOnyvUG9KPFI0Wr5pvOl8OyyKZ0zutNNOKbDKBvjQzzovnWDf+c535uSMLsdib2mg4PFZz3pWCGzK\/OnQY7XVScCQ8bXXXhszcSLIvhiLvT7EjCB+4AMfyKvNyHI0WwUFV111VXzta19Ll235l59nwtjRbM02ffrTn062unQgSMz5070cq73sckI79thjZ+T9pf+x2OqzSxDDr9aZiZE4\/WI0e33J9WXX55b6zhNGOyylZxKfoXy3xRZbzKQZU9Z3zwUweUvNVXH7dEba\/JjvHn\/AsPktuX693DA84CTgJNby2yA9vEm+cf\/kJz8Jw8VveMMbpv1y13hcYzj+rW99a2y77bbjWW3a6xp18Xwlw\/BwmW7SLyVO0lb5dv2LX\/winv\/856fLMi4zn3766T19HNh0wexdd92VRpWlexGBrHl7bHMcWErLp3sNx+2JJ54Y5513XgpmfVnYdddde83MDdKeng1gesHb3uj5TeOShqHBXrDrzjvvDB+g2RbfVLLuxeVY7TWn4NJLL02XaHwozMS2jNXWbJtj4qmnnoqZ+rY1mr1OWEaJzIVyKdRj0GmBYt6G6VqOZmunHTPp29Fs9a3bN\/P83ptJW\/ltNHvVgUsiRpZ9M5eeCUaz1WebSzD5kozlHXfcETN1CX80e\/kwf6ERcAlm5DkmLGumzgM9GcCUvx7tElLG7dUm8k6dO4Za9qbxJvJm8qY3RLj77rsPVZgh5SQkmHLC9IZmo7wZMmfUbtk2FnsFLxoz3Gk5E4zFVgHtO97xjsHZ\/IaNd9555zQfaQw2T2qVsdjrRJUnbzqOzYExWuAS46QaM0pjY7G1V3w7FlsF2AcffHAIuG269+Mmm2yS5qZJTydjsTfbw95XvOIVOTnty7HYKjj0eeu9xcBe963j1ghR\/lLgEt1MXQLnr42JngtgBCgnX\/yruHDZcyNfPsrL6095cfo9pOnYQSLqV73qVelpu+9973tDVO1Dazr6XlcfTkiuXx9++OEBWp51BAGgewW2sZGtoOWxj60wz8Hwq0sdrnljJm5FZBf72AlaXmmrY8BljaOOOioNF3\/5y1+Oc845Z0Ymb7KNjWwFLa+0l+4F2MU+doKWxzbHADp965iYifcdu9jHTtDySltpx4BRWserzwjzYXI95dOFPtnIVtDy9M+voJ1ofeGZyZEBdrGPnaDlsY+dcBx4T3lvzQbfstdx6hhgr2Oi1eOXwPl7Q6DnAhhO9eOLvfC03He+853p+ra5DgIatvUCvj0bqgSdbWIvctpS2rwCb7KQMQOwka2gswlsA9\/ysfKMUYP8wZbrT8eSfdkGOvfJTkiX9s6UnewAG0ezVz04BhwL1pGebvQ7mq2lbx0T0tNtp\/7GYmv2p22aSVvHY6+7UWbKp+zEWHzrve+9NVt8y6eOAfZ6jzk2bGuvwD5zCy17xabJsKPnAhgTdQ999pJofeOmydi+uo3aA7UHag\/UHqg9UHtgA\/TAdAYwY3KfS0hfuObu+OqP74089yUvp3MOzJiMrSvVHqg9UHug9kDtgdoDM+KBngtgjMCY65LnvZRL+cpnxFN1p7UHag\/UHqg9UHtgRjxQd9rNAz0XwHQzss6rPVB7oPZA7YHaA7UHag+UHujJAObsb9+y1uUjl5HqS0jlrqt17YHxe8BzYdzh5W6JEj9KqDV3hPnRN\/XkuStE\/kiop771OuvI8zRd\/eRbTDvrjCfNFjZZR9v61b90zdR6oG699kAveqDnAhhzYC7+yb3x7WNfGK\/\/g+0Gb6em33TAjtN2G3Uv7qzaptoDk+UBz4JxxwQ8H8atn4IMdyn4XSp3gaxvX57f4Ufk9OHOk\/Vtr1x\/Mu0s26117YHaA7PHAz0XwHDdVvPnxY5bz49n7rB5fOPH98oKv07tV6oFOCmjfqk9UHtgUjzglk9PZ73pppvSA\/q6jWx4hoiHdRlNgWBH3nHHHRc33HBDeCaKUZFskHJP\/PW7Rtb7t3\/7t\/DgNxgBMnKijrYy0nl9oy05\/zOf+Uwo85wg7RmF0Vdpp7yyvnbYp++yjFbWDX3kNmh12dGtbp1Xe6D2wMx7oOcCmK0Wzv2ReXYAABAASURBVEle+dK\/3RWHPutpcc0tD8YPbn04pO94aGUqq19qD9QemDwPCCb83EB+LH63lvODuYzWGL3x0C5Pgj7nnHNin332iYsuuiiMiuR1jbiol5\/8u3DhwnjooYfi1FNPDc\/3MDrzoQ99KC6++OL0rKUTTjgh\/IaMoEPw4JkV+vLTB5dcckl6wq06fjiz82nNggz2q6s9D8DTRrbF6JK22HPZZZelIC2X5aX6fstIG+qyxXoCs1ynXtYeqD3QWx7ouQBm0fy54VenjbYYhXnTHy0Nv0Z95qX98ZHDn1FfQuqt42ejsGZD3EijI3m0QZBxxBFHhKCj27YKKpzM3\/rWt6YnDqsvaMmPeu+2Tre8rbfeOgUiygQ7ghRL6TJ48rh7IzVGhlzKckkr11O3EyNH7FdXPZettJHr5bY8xr7bj+zZPgHLKaecEtrQr3VA53bqZe2B2gO95YGeC2C4x63S33rPC1KwcvzLdx\/8SYFX77et4praA7UH1tMDRiPMTcnkpwx3a9bvgflBu1zmpO6SU06PdVkGMNZxiSYHUQIqeb\/73e9CsESPBbZ11i+DIW10puWVaKPzEft33313+D20sl6taw\/UHugtD\/RkADOSi6677eHY+ObAjOSNOr\/2wPR4wI\/r7bTTToOdGbHoDBoGC8coXLLJl30EUQIqq26xxRYxnuCIbZ31jchoazz48cD8G0Euqf3whz8cz+p13doDtQdmwAM9FcCY69I46cp0C3V5y7SgRfroC382Ay6qu6w9sHF7II+4uMwieDFPxMTdyRqh0Ka2s5eNmLi8JF8wYdKvgCeXdy7V98N\/6prca57LeH5xWRCkTXNfLE0Wvu2228ia2gO1B3rYA6MGMNNl+yOrVsepF98U72ruGvf\/r0PjgN22Tr+H9M3r74t9P\/T9lK6fxDtde6Pup\/bAcA\/kSbzmkbjc84lPfCJN2nXyN3phsqvgYfhaI6fMozGqYykQetWrXhUu47ic43KWURV9KTe\/xfwcgUq+C6lsWf39998\/1D388MPjmGOOGXE+T7le1gK0E088MUxMdknrJS95SWorl9fL2gO1B3rTAz0TwDy84snkoSNftDQt3TZ9za0PxV\/83c\/TM2FM7E0F9UvtgdoDE\/aASaruAhIQdGvEJFiTZtVzt4\/gQD0neb+y63IP8vo53y\/xWlfdjDrWUUdZble5PGXasu4b3\/jGKMv1rQzZBu1JK+tsT54y5Pq5D+vp0zbpw7rSJfLYYf3Xvva10Qu\/2lzaV+tZ6YHa6Cn2wKZT3P56Nb\/VgjnxD+94fvzhblutVzv1yrUHag\/UHqg9UHug9sCG5YHeDmDWPNBuw3J5vTW1B2oP1B6YBg\/UXdQe2MA90NMBzAbu+3rzag\/UHqg9UHug9kDtgQl6oKcCGE\/aNWHXDzdaXt3\/UJrAKw13IrkjaYLbWq9We6D2wPR5oO6p9kDtgdoDU+qBnglgPLzOXUbuQBoJ5epNqUfqxmsP1B6oPVB7oPZA7YGe90DPBDA976nawNnlgdra2gO1B2oP1B7YoD1QBzAb9O6tN672QO2B2gO1B2oPbJgeqAOYqdmvdau1B2oP1B6oPVB7oPbAFHqgDmCm0Ll107UHag\/UHqg9UHug9sB4PDD2unUAM3Zf1TVrD9QeqD1Qe6D2QO2BHvFAHcD0yI6ozag9UHug9kDtgZn3QG3B7PFAHcDMnn1VW1p7oPZA7YHaA7UHag+s8UAdwKxxRL2oPVB7oPbAzHugtqD2QO2BsXqgDmDG6qm6Xu2B2gO1B2oP1B6oPdAzHqgDmJ7ZFbUhtQdm3gO1BbUHag\/UHpgtHqgDmNmyp2o7aw\/UHqg9UHug9kDtgUEP1AHMoCtqMfMeqC2oPVB7oPZA7YHaA2PzQB3AjM1Pda3aA7UHag\/UHqg9UHughzxQBzDFzqhl7YHaA7UHag\/UHqg9MDs8UAcws2M\/bRRW3nvvvXHIIYfEHnvsMYzPfOYzE9r+n\/70p\/G85z0vJrL+5Zdfnmyw1LkluyylxwsbrH\/kkUfGo48+Oq7V1X\/f+94X\/DOuFae58nj9vXz58rAOM\/mVfyyle4W839hWYn9kG22D4yyXO4Y795X6yOtMZNnZT+6PjaO1p+9udo22nrZzP3lpW9liXdupXWVlvjI4dh3zoOXZx9axrnTNBuGBGdmIOoCZEbfXna7LA6973evi5ptvTtDnnXfe4IluXet1lu27777xk5\/8JN75znd2Fo07fdhhhyV7LMe7sg\/uq666Kq12ww03xC233JL0WF9arVZce+21Y60+K+o5MX79618ftJVf7XPLwcweEI4dduH666+PAw88MFn1ile8Ii2djA8\/\/PA45phj0vGh3v777x8ve9nLBo9ZJ\/vLLrss8jppxQm85ONZH9mWXXbZJbxHJtDcmFYpt\/\/iiy+ORYsWpW1jiwDkDW94QxxxxBHBnn322SfOPPPMwQBd+ate9aq4+uqrh\/W13377pfTXvva1tKxfag9M1AN1ADNRz9XrTYsH3vKWt6R+vve976WlD0Xf3nzjgxOIAkGCb3mvfvWrA74N+oC0dLJUB7T1oB3tyUdZdumll8oaRD\/WsZSZ+5MH33Dld0PAInBxUlOet4WGdbMtuV3bQrPJdtx+++3pxOFkmNfRL3Jd+VDHditDtlmZ7dWXfGhfPrId2lN2ySWXBM2f0Ka2O9so29dOprOe9pWpf9ZZZ8UjjzwSTv7S0KelOp3rlnaqo+4nPvGJNMJGl+XWnwoEkk7GJ5xwQgi07J\/Pfe5zKag56qijBrv8+Mc\/ngJnJ3mZF154YSxevDjyiZsf7APbqA0+Bq3+WGAHTjnllNhuu+3Gssp618nbYfs1Jmh58MEH46CDDoott9wyvvSlLyVo2ya4cdyqW8JeQd6Xv\/zlyRtVLDuo9UbjgTqA2Wh29ezfUB\/wxx13XOy0007pG58P0ve+972D33Rt4W233RZnnHFGOoE84xnPkDWIk5zRHN8kffhqR3vadWJW5tusb7iDK40gnMwUaeezn\/1sCDKcWOV1kgOWo48+OnxLNRqjz8563dK+AbPJN23f4p0UnQCNyDiB4c4774xsjxPHu9\/97sERAeuefvrp6UShzEnFycM2slsgUdrthPPWt741jSY4ybKp9Onuu+8efMZ3tr3bPrAOtO3bub7Uyz5y8pf2bd6+kFY\/MxY71b377rvTfraNU30y5CP2H1iNwORgJQemBx98cDqBs6kT+\/muu+4KPnfi7izvTDtGBWSdyM91tZkDJ\/bk\/IkuHU+d\/Unb5tym94fjz\/7M23HTTTelwMyoi\/qOF\/sur2Ob\/+Vf\/iUcuzkvL41GCX5+85vf5Kx6WXtg3B6oA5hxu6xeYTo94Fuf\/nzL6zxhyFNWfggKEJxk5Zf40Bc45HLfEp2oBQDIQUYe8fEBW65fah\/SAoh84nICdpK2LOvRZb\/Pfe5zwzpGY2yL8vGS+3ZycCKBk4qTi5OMoMKJIfvGaMCVV16ZvqUrE6DkbXPyg5MhO9niZJNHCqSRfUazm\/22gw9zP+U+UA\/6Flw4sQlm5I2Fsdipnb322ssiLG1zNxtShfV84VeBMt+cc8453YKVEXt47LHHQoA5YoWOAgGrY6kT+blq5z7I+RNd2k+d\/UmXx3N+f+T9nftyPDkW7DNBreDWseS41O4WW2yRq661NAI3Vftsrc7qjA3SA3UAs0Hu1tm9Ub7p+kYH2qUCIw8+7HzoORkqc\/lB2jfB0bY4n0iWLl06rhNQt3bZ4YTZrawzr\/Nkk08A+YTQWX+0dO7bSbtb3XX5QplRj+23377bqmPK0z+fj7YPnMRcFhEgucxhtGdMHVSVxmrnSD6omkj\/Ag+XvRwrY4G97E4rr3mRNsJgm22HE\/OaojEt+Gusx4oGjbR0s1W+cuRjJx9L8taH0UZg+KAM\/su+HE\/sEMx6bwluHfNlnXVp+3pd5XVZ7YF1eaAOYNblnbpsRjzgW7tvgJn8TdCJ1wemyw+5zLL8djqSwZtvvnm69GQ43wdyt3pOUk443crKPHaY0zCWD18jSNrtPOFP9JJH174L45zU9ddtO9ZVVjSxTqn\/sewDJzEnM\/sq7791NlwUToadmhP0msTtGBkL5nA4EVs349KcEbpu22Gkz+iUk\/tIxxR\/OVZye6MtHcvdbJVvXf3oT7\/6l7e+GCnp1mfeb3lfGmkp\/WM\/lX13psuykfRE1hmprTp\/4\/NAHcBsfPt81m6xD2wf3D7AfZD7Vuobtm\/ao22UD14fwE6qPpCt79KJEQL4FunEnCfv5mW3dn0LdwnHZSSXdPTPDvaU9ZWpo31D7Pkk4WRo6F2e+j7EfUsXdLCNjfK70dm3PgRDJgg7Ybv841JHtp9NbGNjZ5kTM1xK459u\/XXmjXUf5BO3IC\/7urOtkdKTYedIbY8nn2\/tPwF1DiDK9fmM7\/jwoosuGiwyopF93i1wHs\/+Hmx0jRhpJJGPjSCBXlN9UhaOS0Exu8sG7SfBmSBdn96X3p+OkbLeSNr7zXEyUnmdX3tgNA\/UAcxoHqrLR\/PAtJU7YZiDYE6BD0+jGvny0liMcBJyu6tLT9a3jksb2nXy15ZLVobwla0L38xd8xecaE8Aof1yHQGKQEXgpI9c1hksOUE6EWjnpJNOil133TVXTUtzVrSjLxMrfWMWQEmDlqeyAOfTn\/50mBNjO0ofKfvKV76SbslW9va3vz1sf\/6mbf3RsB1j2Qf6MjeHP\/n6jjvuSLfgCmj0wQeWtlmQRWesu7525rYmY2kb+KskBwp8ZyKyCeC5nO8FNI4p\/nJpxTEr+GDPaPtbnakgH0PZzhxkTbQv+ykfa\/axbXRs2ObR2hRgO+brAGY0T9Xl6\/JAHcCsyzt12bR6wAeiCaf5ZNyt81wnj2Y4gajnQ9MlANDynEBcQigDCzqvW9ZVX1u5jA20vLIsp\/VhfXWgvnol6irTZ5mf7crrlNv0zW9+M6BtfVgvt6MtWp51pUHLy+T2lSGvo7zsq7NMO\/yvjrr6ZwdoeVCunvWR28\/95u21VA7fzst9kesqU08btOW6+lCmTlnX+trWpvLJonM79ZkpfaJf\/ecyWl62w8Twp556KoxkyCvbta9RtqfOSOR17auyjv1z4oknpiCxzM9a\/WxfXnbamet2Ljv9XZbbTu1o0zHBvrJcWn65fUZrXMoV4Cov69e69sB4PDD7A5jxbG1dt\/ZA7YHaA9PsASf5F73oReFSy1R1LSgwGuIWesHMVPUzGe265Ga0xkjUZLRXt7HxeqAOYDbefV9vee2B2gPT5AEjIJiq7gQt559\/fgiWpqqPyWrXiI5RmXr0ZbI8OvF2ZvuadQAz2\/dgbX\/tgdoDtQdqD9Qe2Ag9UAcwY9jpJiAa9qy5Ov2uSe2H2g\/1MVAfA+t\/DNQ+nC4fOoeN4VQ366rUAcwou8yOP\/7449NvwrjzoObI2hdH1j6o3wf1MVAfA7PnGHAOcy4S\/o7MAAAQAElEQVQb5XQ364rrAGaUXWanX3PNNXH22WenHyozm77k2GOPTS2MVF7WnW263raBH6er91tv+GGyj8de2q\/1tvXGMTbeY2I27Dc2Ooc5l6WT1Qb00tMBjAdJ+R2V\/NyC0ZaekTFV+yY\/88NzN0oOOOCA1OVI5WXd2abrbTswZts+Y++Gut821O3akPdZvW0z\/xmS3zfpRLWBvfR0AGOWutnqnjEwFsxu38D2T705G6wH6g2rPVB7oPZA7YH18UBPBzDrs2HjXddoz6tf\/erwyPXxrLvDDjuEB1VZjme92VDXNtXbNhv21HAbN9T9tqFul71XbxsvzD425P02G\/bGrAlgXB7qdglJ\/vo6WtDiUfC33XbbuJtyAL\/5zW8Oy3GvPIMrjKVr21Rv21g81Vt1NtT9tqFul6On3jZemH1syPttNuyNng9gBCgCF7+d0XkZyW\/N+EE+5epNxOFGXjwh00Ogtt5663E10d8f8cpXLog99tg99t57QfT3j2v1unLtgdoDtQdqD9QeqD0wQQ\/MUAAzNmsFFwIXgUq3p1h6+qRZ4wIbv8eh\/thaHqplno22t9hii6HMLsos7nzPfn9\/f6xcuTKOPjriD\/7gwbjxxl\/E61\/\/aHzwg6tTvrINhVWrVsWKFSs2uO2yf+ptWznr9mu9z2bfPqvfa9O\/z5yj8vnKzzZ0OaVtEFk9HcDk4EKgMpq33\/ve94b6o9WbaPm55547+PwTIzZ33313tNsRhx\/+YJx11sIUyFx5ZYT8DYV77rkn7rvvvvQjdBvKNuXtqLft7ll3rNb7bPbtM++3er9N8n6rzj38ui6co\/JzejwDZqLnvV5fr6cDmNJ5LhG5VNSJ26wnMvJStj0WXT7nxcTWHXfcMZrNiM98Zoe44ILd4vzzd4i99pob8jcUtt9++9h2223T\/J4NZZvydtTbtuOsO1brfTb79pn3W73fpn+\/OUe5OgHPgRnLOW421pkVAYwA5fTTT4\/Pfvaz4XJRidusp3LkJe\/U8jkvjUYjFixYUAUuUY1OLEhV7rhjbkrL31BYuHBhzJ8\/P23rhrJNeTvqbVsw6\/Zrvc96Yp+N+7ip99v07zfnKM\/gQf0cmHSKntkXAcR+++03s0Z09F7FMbF8+UDmBRdESA+k6tfaA7UHag\/UHqg9UHtgKj0wK0ZgjLAcfPDBcdZZZ02ZL\/bdd9+46qqrwnLKOqkbrj1Qe2D9PFCvXXug9kDtgTUemBUBzBpb42tf+1rM1ByYbEO9rD1Qe6D2QO2B2gO1B2beA7MigDEH5pJLLomLL754xubAzPyuqi3oAQ\/UJtQeqD1Qe6D2QI94YFYEMJtvvnk861nPCrPZe8RvtRn\/f\/bOLtSqaovj\/yCoxGP0EKc0YhiCQWlESIIXu5cUBAlB6MFuEFe4phQYaId6kLr0INgJCoJMLl6MqIdAkgiEzkMJwikfwixucAMl05IeAjUrCLr9ps3Tcp+zPV97n73m2n9x7LXWnHPNNcZvrL3XOPNrmYAJmIAJmIAJ9JBAEQEM68CsW7euq2NgeugDX9oETMAETMAETGCaBIoIYOhCYhp1ZQzM2FiYuVoHZppcXdwETMAETMAETKCLBIoIYJiFxHov1fVf8j7p5HeRkas2ARMwARMwgYYQaI4ZtQ5gaHl56aWXpkSbcpSfUmEXMgETMAETMAETKJpArQMYWlbuueee1F20c+fOcaAvXryY3k\/E1GrKUX5cISeYgAmYgAnUhoAVMYFOEah1AIORa9asSVOnGcRLoFIVVubdvHlzyqcc5S0mYAImYAImYALNJ1D7ACa7gAAlj3upbknPZbw1ARMwgasTcK4JmEBTCBQTwLQD\/vnnn8tjX9rRcboJmIAJmIAJNJNA7QOYEydOiPEtdB1Vp0wTtHD8xBNPNNMztqqRBGyUCZiACZhAZwjUOoBhkO7u3bu1bdu2NM5lxYoVaTG7kZERrVy5Uhx7GnVnbgTXYgImYAImYAIlEah1AHPp0qXEcuPGjWk7NDSkY8eOaceOHem9SMPDwyndH1Ml4HImYAImYAIm0AwCtQ5gJkK8YMECvfnmm1q2bNlE2U4zARMwARMwARPoAwJzGsB0gufAwIAGBwc7UZXrMAETMAETMAETKJRAcQFMoZyttgmYgAmYgAnMlIDPm4BA7QOYM2fOpAG7zEJi4O7o6OjYMWnMRGJG0gS2OckETMAETMAETKChBGodwPBqAGYZVReua90nn3IN9Y\/NMgETMIHeE7AGJlBDArUOYGrIyyqZgAmYgAmYgAnUgECtAxi6hugioqtoKsL6MDVgahVMwAQ6S8C1mYAJmMA4ArUOYOgaoouotduo3bHfizTOv04wARMwARMwgUYSqHUA00jiNqo8AtbYBEzABEygdgQcwNTOJVbIBEzABEzABExgMgIOYCYj1Pt8a2ACJmACJmACJtBCwAFMCxAfmoAJmIAJmIAJ1J\/A5AFMD22YyiwkZilRrodq+tImYAImYAImYAJzTKDWAUx1FtLGjRs1NDSk6gykffv2acWKFaLcHHPz5UzABEzABEzgqgSc2V0CtQ5gsum0sJw9e1YEMTmN7fLly0U6+RxbTMAETMAETMAE+oNAEQEMLSwLFy5M70Dau3dv8szOnTvTMenkp0R\/mIAJmIAJ\/EHAGxNoNoEiAhhcMDw8LLqM9uzZI1bl\/eCDD3To0CGRTr7FBEzABEzABEygfwgUE8DgElbazWNgjh8\/rmXLlpFsMQETqCEBq2QCJmAC3SRQVADTTRCu2wRMwARMwARMoBwCxQQwFy9e1COPPJK6j9iePHlSDz30kE6cONGWNoN7mWZNlxPnUEdrYdLIowxCec5rLefj0ghYXxMwARMwgSYTKCKAIcjYsmWLGLDLuJeBgQHdfPPNWr9+vXbv3i3yJ3IS42U2bdqkzz77LGWPjo6mbfXj0qVLunDhQhpPQ\/cUL4\/0oOAqIe+bgAmYgAmYQP0IFBHAEGSAjnVg2GbJ06pzfk5nSyvKsWPHtGTJEs2fP1+rV6\/W4cOHybpCzp07l44HBwfTtlMfrscETMAETMAETKB7BIoIYGgRofXlqaee0o8\/\/phofP\/993r44YdTqwz5KbHlY8GCBaoGJqwZ09pac\/ToUX3xxRdpSjZdSHmadktVPjQBEzABEzABE+g+gSlfoYgABmuYLr158+Y0DoYp1A8++KDoHiKd\/JnK1q1bx1b3pYvp7bff1sjIyLjqPv74Y5GPnDp1Sj\/\/\/HOSX3\/9NZXNx03b\/vLLL\/rpp5+Srbbtss9L4NBUvzXVLu4p21bO9wt\/Zamj33hG8axCzpw5k55RTfwoJoABfnUaNeNVCD5Ibyfnz59X7iKiDK04dCexP5HMmzdPixYt0ldffTUu+5VXXknBEwN+Dxw4oG+\/\/TYJLUEU\/uGHH9JxTm\/C9rvvvhP2wbAJ9lRtsG2X798qk7rv22fl+Yx7qji\/\/fHbju6TSV1t4xnFswp5+umneUQ1UooKYKbjAbqVeE8SwQjdRkeOHNG6devGVUGXEUIGM5u++eYbrVq1isMr5MUXX9Rbb72V5LHHHtOtt96a5KabbkrlGFSc05qypfsNu2655ZZka1Pswg7bdvn+hUUpYp+V5zPuLftt7v3GMyo\/r7Zv356eUU38aGwAg7MY9EuXEO9MovWFFhzSCVgQ9h999FER3DD+ZcOGDamVZaIF8miZWblyZRorExG6\/vrrx4R6rr322rHjal7J+zfccIOuu+66xtmFT2zbn\/cvPEqQPvFZ475v9tvcf9d4RuXn1f3336+m\/isigGFGEeuz0BxGa0p2Bumksc1p1S2tMB999FEa41IdK0PXE0JZupSIVOmSQnI6eRYTMAETMAETMIF6EigigAEdLSBsWfulXcBCvsUETGAWBHyqCZiACRRCoJgABp4vv\/yydu3apbVr1151BV7KWkzABEzABEzABJpLoKgABjcwjuXNN98UY1eYTk2apTEEbIgJmIAJmIAJTIlAcQEMVjHIluBl3759avIcd2y1mIAJmIAJmIAJjCdQ6wCGsS55kC6BCqOqmS2EsH\/69OnxFs0mxeeagAmYgAmYgAkUQaDWAQyziJghdPfddyvPJmKmUFVIp1wRtK2kCZiACZiACTSQQC9MqnUA0wsgvqYJmIAJmIAJmED9CdQ6gKELifVf6DJqJ+RTrv6oraEJmIAJmEB3CLjWfiRQ6wCGriG6iKpdRq375FOuH51nm03ABEzABEygXwnUOoDpV6fYbhMwgbIIWFsTMIG5J1BMAMO7iybqRnIX0tzfNL6iCZiACZiACfSaQBEBDGNc3n\/\/fR06dEgbN24U67\/QlcT+pk2b5C6kXt9Gvn5vCfjqJmACJtB\/BIoIYHDLwMCABgcHtWTJEh0+fJgkDQ0N6ciRIyLASQn+MAETMAETMAET6AsCRQQw8+bNS844ePCgVq1apU8++SS9C4ljFrhLmf7oGQFf2ARMwARMwATmmkARAcz8+fPFixxpbaEVhtV5N2zYoD179qSXO7oLaa5vG1\/PBEzABEzABHpLoIgABkQEKazKy3br1q1iDAyyZs0asi0mYAImYAImYAJ9RKCYAGZkZESehdRHd6ZNNQETMAET6C6BwmsvIoBhkO4LL7wwNvuIlpcsXsiu8DvQ6puACZiACZjADAgUEcBg16JFi7R8+XJ2LSZgAiZgAuUTsAUmMCsCRQQwjHtZvXp1GrQ7K2t9sgmYgAmYgAmYQCMIFBHAZNJMm24dB+OVeDMdb03ABKZFwIVNwASKJlBEAMMYmLwSbx77krceA1P0\/WflTcAETMAETGBGBIoIYFjIbunSpWkl3hlZ6ZNMoH4ErJEJmIAJmMAsCBQRwLCQ3bp16zwGZhaO9qkmYAImYAIm0CQCRQQwdCExjdpjYDp467kqEzABEzABEyiYQBEBDLOQGOuSx71Ut6STX7APrLoJmIAJmIAJmMA0CfQqgJmmmi5uAiZgAiZgAiZgAn8SKCKAoQuJFziy\/VN175mACZiACZhAvxGwvZlAEQEMXUQLFy4UY2Cy4t6agAmYgAmYgAn0L4EiAhhaXo4dO5ZmIXkhu\/69WW25CZhA7wlYAxOoC4EiAhhaYBisWx28m\/dJJ78uQK2HCZiACZiACZhA9wkUEcCA4eLFi2IcTLUFhmPSybeYgAn0AwHbaAImYAKXCRQRwBCkbNmyRYyDyS0vbDkmnfzL5vjTBEzABEzABEygHwgUEcBcunQp+WJoaCht80c+zvk53VsT6BYB12sCJmACJlAPAkUEMIxxobVl7dq1OnHiRCLHlmPSyU+JM\/zYu3evctfUyMjIDGvxaSZgAiZgAiZgAnNFoIgABhjDw8Patm2bNmzYkIINthyTTv5MhUCIN12Pjo5q37592r9\/v+rbJTVTK32eCZiACZiACTSLQDEBDNi3bt0qxr5k4Zj02cjRo0c1MDCgefPmafny5bpw4YJOnjw5vb6H8wAADjRJREFUmyp9rgmYgAmYgAmYQJcJTCuA6bIuPauebqj58+en658\/f17nzp1L+5N9nDol\/etfl0v97W\/SNdc0S2644frfW7sWi61tK8e3+OuOO5rnt6baxXfLtpXz\/cJfWerkt8WLpVOn1Ff\/ah3AsIDdAw888PtD9I62Qj7luu21jz\/+WHQzVeUf\/5A+\/LDbV3b9JmACJmAChRPouvqnTkn\/\/Oc3455TZ86c6fq1e3WBWgcwDM5lobrcZZS3n332mVauXJmYrVixQpRLBzP8OHv27Ni4lwULFmhwcHBcTa+88kpah4a1Z7J8+OG4Yk4wARMwARMwgZ4Q+PBDjXtOPf300z3RZS4uWusAZiIADLpdtWqVvvjiCx06dEizHcRLXYx7YSo2gRHjYRbTFtdy8RdffFFvvfXWFfLXv7YU8qEJmIAJ1JGAdeoLAn\/5y21XPKN4Zm3fvr2xthcVwOzcuTPNQmL69PHjx7Vs2bJZO4Y61q9fn1p0duzYoWeffVZ5PEy18kWLFqUytPxk+c9\/pL\/\/\/VfddtuvipAipAgpQoqQIqQIKUKKkCKkCClCipAipAgpQoqQIqQIKUKKkCKkCClCipAipAgpQoqQIqQIKUKKkCKkCClCipAipAgpQoqQIqQIKUKKkCKkCClCipAipAgpQopQssu2SRFShBQhRUgRUoQUIUVIEVKEFCFFSBFShBQhRUgRUoQUIUVIEVKEFCFFSBFShBQhRUgRUoQUIUVIEVKEFCFFSBFShBQhRUgRUoQUIUU012\/ci0iEFCFFSBFShBQhRUgRUoQUIUVIEVKEFCFFSBFShBQhRUgRUoQUIUVIEVKEFCFFSBFShBQhRUgRUoQUIUVIEVKEFCFFSBFShBQhRUgRUoQUIUVIEVKEFCFFSBFSRHN9FmHbIqQIKUKKkCKkCClCipAipAgpQoqQIqQIKUKKkCKkCClCipAipAgpQoqQIqQIKULimZSfT3l7\/\/33Vx9ljdovIoCh1eWee+7RBx980JFWl1YPMpuJ7qnpBkUR0r\/\/\/auOHDmt\/\/73ZzF5qUnyv\/\/ZthL9WUO\/deS70VS7uMdsmzpyj8ByLqVufotofbo1+7j2AUw3Wl066dLvvvtOb7zxhth2st461IVNtq0OnpieDk31W1Ptwru2DQrlSZP9VoI3ah3AMLvo2LFjiePBgwcnnIk0V7OQkhITfHADHzhwoLEBTCNss98mIFBekr9r5fkMje03KFi6QaDWAQyziz766KMrFq+jq6cq5FOuG3BcpwmYgAmYgAmYQD0J1DqAqROyidaBYU2YPMe+Xf7o6Oi4efmcV4LYttEifddUvzXVLn4LbJu\/a9wH3ZB8b9XpedopXRzATELytttuE6O4J1oHhvVg8hz7dvmUKVVs2yPj1lQowZdN9VtT7eKesm3+rnEfdEO4t3iG8Syb5HFXw+yrq+QA5up8hNMnWgOG+fWWK9fFMQ\/z8D3ge8D3QP3uAZ5hPMsmedwVl+0AZgouw\/F5Tr23K8eth2MmZuJ7wPdAE++BptjEM2wKj7riijiAKc5lVtgETMAETMAETMABjO8BEzABE6glAStlAiZwNQIOYK5GZ5K8vXv3jq1NMzIyMknp+majO4PHLl68OKZkO9tYm4e1d+644440wLV6ztjJNdjBJnREWMWZ1ZyzWqXbhi3YhG34Ap80xbZsBzZhG37MaU3yG75jkc6m2IYd2INdSFP8lu9DbMrCd4\/vIDaXfk9iQ8niAGaG3uMGfv\/999M023379mn\/\/v1jb7SeYZU9OY0v4JYtW6649tVs27NnjzZt2iRefMlJTPtjWyfhR4dZYbzskzWDtm3bpieffFKkl24bAePu3bv10ksvpfWReBs7PoF\/p22jzl4JNp0+fXrs8k2w7dy5c7rrrrvSd4f7cnh4ONnXBNv4HcEY7OJ7984776Tfw9JtY40x1hrDLmRoaEj8nvAOvdJtw1+liwOYGXrw6NGjGhgY0Lx587R8+XJduHBBJ3kJxwzr68Vp+a8kvpTV67ezjQCAlZGXLFmSXni5evVqHT58uHpqLfb50XnvvffGXva5atUqLViwIOlWum28aJRZHmvWrEn28IE\/2JZuGzYg3Jd8nxhAyTHSBNu++uorLVy4MH13sClL6bYRVH\/66ad67LHHkkk83F9\/\/fVkZ+m2JYP++MgBy8aNG1NKk2xLBhX44QBmFk6r\/hidP39e\/IU1i+rm\/FQeglu3bp3wuu1sIxAYHBwcO+fs2bPpL62xhI7tdK4ifmiWLl0qAhtqbYJt\/JjSlE1AmX9Qm2AbQTKtmc888wzmXCEl+42H\/JEjR5RfiYLv8GE2sGTbsg2vvvrqhF3qTbANG3mtyvbt28d+R0hrim3YUqI4gCnRa9Z5ygT4a54Hx\/PPPz\/lc0ooyF+5x48f165du\/Twww+n7rES9J5MR7qONm\/erJtvvnmyokXl55YzuiEQugBzt2ZRhkyg7KVLl\/Tll1\/q3nvvTd2adKm\/8MILjbknMZnAmj\/WaG3n2FIPAg5g2vhhKsnc0PxlRdnWlgnSSpZ2trW2NFX\/AqmbvfTL08VFlwsPkKxfE2zLttAa9ttvv421\/pVsGw8JWpQYk8WDgvFV7BOEYm\/JtqF\/VZrkN7rRFy1apNyV2STbss8Y88dvXW7FzelNuiezTSVtHcDM0FuMq6Cfnr8+uLkZD7N48eIZ1lav09rZxpeXQaP05RO40bKxbt26ein\/hzYEL+zmgZLsI6XbBvfHH39cufuB7jEWqeLeK9027q88YJLvFGNg+Guers7SbWuy3\/jjoDoejq70a665RgQypfuN3wyEP4Raf+uaYhv2dVjmrDoHMDNETRP++vXr06q0O3bs0LPPPpsGrc2wulqddjXbGPD79ttvp4HL\/EXCw6VWyv+uDA\/31157TXRH5KmPTMnlL\/zSbeNhQdfDo48+msYb4IuXX3453Xul2\/a769r+L922Vr9xf+bfjNJtw2ncj7RG8H3j95DxMASkTbCN4JM\/VgnIsDVLE2zLtpS6dQAzC88xAJb+bMYicDPPoqqenoodrd0spE1kGz9K+a\/k1taNnhpRuTi+wCfonwWd0Z1iJduG\/lX7qnaRV7pt2IDwwOeerAbIpdtW9Rv3J8fYipRuW\/YX37ee2wbQDgq2Mauq6q9cfel+y3aUunUAU6rnrLcJmIAJmIAJ9DEBBzB97HybbgIm0HECrtAETGCOCDiAmSPQvowJmIAJmIAJmEDnCDiA6RxL12QCvSdgDUzABEygTwg4gOkTR9tME4AAL9xD2O+0MFuDl4IyEyVPY+\/0NaZaHzbOVAfWncEGbMGmqV7T5UzABOaWgAOYueXd9KvZPhMQa7cwO6NUFMx84oWErO1Uqg3W2wT6gYADmH7wsm00gSkQYJ0c1suh9QGhFSOfllslcvpUWyeog3MQ9nN97a7FGj4PPfSQnnvuubTODe8M4tpZr2od7FNuorx8Hba0oqAvOiDURzpCHaQh7JNmMQETKINAswKYMphbSxOoHQEe8k899ZQ2bdqU3mdDC8Qnn3ySVvwl2ODdNrSssEIuC5ZNxQACBcpyDsJiYAQoV7sW9X799de69dZbkx5r165VXhitqhPlkHfffVcsmsZrB3gNAdckvSrPP\/+8WHSRNUqwgfrQg7IT6Vc91\/smYAL1JeAApr6+sWYmMGcEWKyLheNy1w+rjt54443p+gQfvOuGpf0px8sWU8Y0PjgvLwbGfrtrUSXXZZl29nm\/DkEMi4hVdSIPyXksUkjwxZLvpGch+CKwycvAY8Ndd9019u6oXA6dsn45zVsT6CcCJdrqAKZEr1lnE+gCAVok6EpBeNDTEsJlePcV2+kKY0l4Rw4vZqTO6qDadtfiGgQwBCvsTyYEOJOVIZ+XQqIDutBag01X049zLCZgAvUm4ACm3v6xdiYwJwRoqcjdRHS18JC\/\/fbb07WnGiSkwi0ftOhQH604vPyTwOVq12o5fdJDApFcqLqf09jypni6n9AjC3qRx5a0qn6kW+aagK9nAtMn4ABm+sx8hgk0nsDBgweVW2BotThz5owIahi\/sn\/\/\/inZT4tLdWAss3omalmpXmtKFVcK0T1EQISwn7uKchG6lpYuXaoDBw6kJMa+5IHBU9UvnegPEzCB2hFwAFM7l1ghE+guAQIGulOyEGTwoGcMSe5q+fHHH5XHipC3a9cukcfYlPvuu29KClbfUEwQdO+994qxLNTX7lpTqrhS6M477xTjYOjyok66hSrZaZdBvAzWxd4NGzZo27ZtolxVv6p+6SR\/mIAJ1J6AA5jau8gKmkDnCAwPD6fZPXSbZCGNK+TuFNKZqcNAWx705LEl\/fjx4\/r222\/TrB4GvpLXTsinDs5DqD+XZZ80pHotApz33ntPBDmUpVzWjzTyKEMeQlCETtRDWdIQzsnH7fRol875FhMwgfoTcABTfx9Zw8YTqLeBuduFFgyE1gxaNdppTUsN3TPt8uuezjgdWmqY9l13Xa2fCfQzAQcw\/ex9224CUyBAi0du5aClg1YVWi9aTyWNPMrk1o\/WMp08rraydLLe3NqELdjUybpdlwmYQOcIOIDpHMtia7LiJmACJmACJlAaAQcwpXnM+pqACZiACZiACagGAYy9YAImYAImYAImYALTI+AAZnq8XNoETMAETMAE6kGgz7VwANPnN4DNNwETMAETMIESCTiAKdFr1tkETMAEek\/AGphATwk4gOkpfl\/cBEzABEzABExgJgQcwMyEms8xARPoPQFrYAIm0NcEHMD0tfttvAmYgAmYgAmUScABTJl+s9a9J2ANTMAETMAEekjAAUwP4fvSJmACJmACJmACMyPwfwAAAP\/\/F0VZQQAAAAZJREFUAwCBpXmLuKO9rAAAAABJRU5ErkJggg==","height":337,"width":560}}
%---
%[output:675c778e]
%   data: {"dataType":"text","outputData":{"text":"Peak sidelobe level: 1.81e-13 (ideally 0)\n","truncated":false}}
%---
%[output:4c95dc5a]
%   data: {"dataType":"text","outputData":{"text":"Point 1 — Sensing-heavy:\n","truncated":false}}
%---
%[output:55f9166c]
%   data: {"dataType":"text","outputData":{"text":"  Pilots: K = 761 (ZC length, prime)\n","truncated":false}}
%---
%[output:7814f289]
%   data: {"dataType":"text","outputData":{"text":"  Data:   263 subcarriers\n","truncated":false}}
%---
%[output:7adb7872]
%   data: {"dataType":"text","outputData":{"text":"  alpha:  0.7432\n","truncated":false}}
%---
%[output:7a17f443]
%   data: {"dataType":"text","outputData":{"text":"  Predicted range RMSE: 0.060 m\n","truncated":false}}
%---
%[output:42bacb35]
%   data: {"dataType":"text","outputData":{"text":"  Predicted throughput: 171.0 Mbps\n","truncated":false}}
%---
%[output:294c855f]
%   data: {"dataType":"text","outputData":{"text":"Point 2 — Comms-heavy:\n","truncated":false}}
%---
%[output:3966771b]
%   data: {"dataType":"text","outputData":{"text":"  Pilots: K = 257 (ZC length, prime)\n","truncated":false}}
%---
%[output:55987d56]
%   data: {"dataType":"text","outputData":{"text":"  Data:   767 subcarriers\n","truncated":false}}
%---
%[output:852e1fb0]
%   data: {"dataType":"text","outputData":{"text":"  alpha:  0.2510\n","truncated":false}}
%---
%[output:4af1d92f]
%   data: {"dataType":"text","outputData":{"text":"  Predicted range RMSE: 0.525 m\n","truncated":false}}
%---
%[output:5e3de401]
%   data: {"dataType":"text","outputData":{"text":"  Predicted throughput: 498.7 Mbps\n","truncated":false}}
%---
%[output:6eaab5eb]
%   data: {"dataType":"text","outputData":{"text":"OFDM symbols per frame: 14\n","truncated":false}}
%---
%[output:7e02a49e]
%   data: {"dataType":"text","outputData":{"text":"FFT size: 1024,  CP length: 73 samples\n","truncated":false}}
%---
%[output:5da4d248]
%   data: {"dataType":"text","outputData":{"text":"Waveform 1 (sensing): 15358 samples\n","truncated":false}}
%---
%[output:4572c28c]
%   data: {"dataType":"text","outputData":{"text":"Waveform 2 (comms):   15358 samples\n","truncated":false}}
%---
%[output:572ed8f9]
%   data: 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","height":337,"width":560}}
%---
%[output:7fa3468e]
%   data: {"dataType":"text","outputData":{"text":"Predicted bandwidth: 30.72 MHz\n","truncated":false}}
%---
%[output:0831d31b]
%   data: {"dataType":"text","outputData":{"text":"Range:     150 m  (delay = 1.000 us)\n","truncated":false}}
%---
%[output:4b2b73a7]
%   data: {"dataType":"text","outputData":{"text":"Velocity:  30 m\/s (Doppler = 700.0 Hz)\n","truncated":false}}
%---
%[output:204ef28f]
%   data: 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","height":337,"width":560}}
%---
%[output:2aed64ec]
%   data: {"dataType":"text","outputData":{"text":"Sensing-heavy (alpha=0.74): EVM = 12.88%n","truncated":false}}
%---
%[output:99866cb9]
%   data: {"dataType":"text","outputData":{"text":"Comms-heavy   (alpha=0.25): EVM = 15.15%n","truncated":false}}
%---
%[output:612d2da7]
%   data: 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","height":337,"width":560}}
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