From 0335fcc51dbbcb59b3a83781e4b4ed1daa840469 Mon Sep 17 00:00:00 2001 From: Lena Salfenmoser Date: Tue, 9 Jan 2024 15:27:37 +0100 Subject: [PATCH 01/14] ww implementation --- examples/example-5.2-oc-ww.ipynb | 642 ++++++++++++++++++ neurolib/control/optimal_control/oc.py | 326 +++++++-- .../control/optimal_control/oc_ww/__init__.py | 1 + .../control/optimal_control/oc_ww/oc_ww.py | 173 +++++ neurolib/models/wc/timeIntegration.py | 104 ++- neurolib/models/ww/model.py | 7 +- neurolib/models/ww/timeIntegration.py | 518 +++++++++++++- .../control/optimal_control/test_oc_utils.py | 88 ++- tests/control/optimal_control/test_oc_wc.py | 33 +- tests/control/optimal_control/test_oc_ww.py | 222 ++++++ 10 files changed, 2003 insertions(+), 111 deletions(-) create mode 100644 examples/example-5.2-oc-ww.ipynb create mode 100644 neurolib/control/optimal_control/oc_ww/__init__.py create mode 100644 neurolib/control/optimal_control/oc_ww/oc_ww.py create mode 100644 tests/control/optimal_control/test_oc_ww.py diff --git a/examples/example-5.2-oc-ww.ipynb b/examples/example-5.2-oc-ww.ipynb new file mode 100644 index 00000000..473ba925 --- /dev/null +++ b/examples/example-5.2-oc-ww.ipynb @@ -0,0 +1,642 @@ +{ + "cells": [ + { + "attachments": {}, + "cell_type": "markdown", + "metadata": { + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "### Optimal control of the Wilson-Cowan model\n", + "This notebook shows how to compute the optimal control (OC) signal for the Wilson-Cowan model for a simple example task." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "import os\n", + "\n", + "while os.getcwd().split(os.sep)[-1] != \"neurolib\":\n", + " os.chdir('..')\n", + "\n", + "# We import the model, stimuli, and the optimal control package\n", + "from neurolib.models.ww import WWModel\n", + "from neurolib.utils.stimulus import ZeroInput\n", + "from neurolib.control.optimal_control import oc_ww\n", + "from neurolib.utils.plot_oc import plot_oc_singlenode, plot_oc_network\n", + "\n", + "# This will reload all imports as soon as the code changes\n", + "%load_ext autoreload\n", + "%autoreload 2" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "We stimulate the system with a known control signal, define the resulting activity as target, and compute the optimal control for this target. We define weights such that precision is penalized only (w_p=1, w_2=0). Hence, the optimal control signal should converge to the input signal." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "# We import the model\n", + "model = WWModel()\n", + "\n", + "# Some parameters to define stimulation signals\n", + "dt = model.params[\"dt\"]\n", + "duration = 10.\n", + "amplitude = 1.\n", + "period = duration /4.\n", + "\n", + "# We define a \"zero-input\", and a sine-input\n", + "zero_input = ZeroInput().generate_input(duration=duration+dt, dt=dt)\n", + "input = np.copy(zero_input)\n", + "input[0,1:-1] = amplitude * np.sin(2.*np.pi*np.arange(0,duration-0.1, dt)/period) # other functions or random values can be used as well\n", + "\n", + "# We set the duration of the simulation and the initial values\n", + "model.params[\"duration\"] = duration\n", + "x_init = 0.\n", + "y_init = 0.0\n", + "model.params[\"r_exc\"] = np.array([[x_init]])\n", + "model.params[\"r_inh\"] = np.array([[y_init]])" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# We set the stimulus in x and y variables, and run the simulation\n", + "model.params[\"exc_current\"] = input\n", + "model.params[\"inh_current\"] = zero_input\n", + "model.run()\n", + "\n", + "# Define the result of the stimulation as target\n", + "target = np.concatenate((np.concatenate( (model.params[\"r_exc\"], model.params[\"r_inh\"], model.params[\"se_init\"], model.params[\"si_init\"]), axis=1)[:,:, np.newaxis],\n", + " np.stack( (model.r_exc, model.r_inh, model.se, model.si), axis=1)), axis=2)\n", + "target_input = np.concatenate( (input,zero_input), axis=0)[np.newaxis,:,:]\n", + "\n", + "# Remove stimuli and re-run the simulation\n", + "model.params[\"exc_current\"] = zero_input\n", + "model.params[\"inh_current\"] = zero_input\n", + "control = np.concatenate( (zero_input,zero_input), axis=0)[np.newaxis,:,:]\n", + "model.run()\n", + "\n", + "# combine initial value and simulation result to one array\n", + "state = np.concatenate((np.concatenate( (model.params[\"r_exc\"], model.params[\"r_inh\"]), axis=1)[:,:, np.newaxis],\n", + " np.stack( (model.r_exc, model.r_inh), axis=1)), axis=2)\n", + "\n", + "plot_oc_singlenode(duration, dt, state, target, control, target_input)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Compute control for a deterministic system\n", + "Cost in iteration 0: nan\n", + "Final cost : nan\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# We set the external stimulation to zero. This is the \"initial guess\" for the OC algorithm\n", + "model.params[\"exc_current\"] = zero_input\n", + "model.params[\"inh_current\"] = zero_input\n", + "\n", + "# We load the optimal control class\n", + "# print array (optional parameter) defines, for which iterations intermediate results will be printed\n", + "# Parameters will be taken from the input model\n", + "model_controlled = oc_ww.OcWw(model, target, print_array=np.arange(0,501,25))\n", + "model_controlled.weights[\"w_p\"] = 1. # default value 1\n", + "model_controlled.weights[\"w_2\"] = 0. # default value 0\n", + "\n", + "# We run 500 iterations of the optimal control gradient descent algorithm\n", + "model_controlled.optimize(0)\n", + "\n", + "state = model_controlled.get_xs()\n", + "control = model_controlled.control\n", + "\n", + "plot_oc_singlenode(duration, dt, state, target, control, target_input, model_controlled.cost_history)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Compute control for a deterministic system\n", + "Cost in iteration 0: 1.409261374589448e-07\n", + "Cost in iteration 25: 1.3051113114486073e-07\n", + "Cost in iteration 50: 1.2069164098268257e-07\n", + "Cost in iteration 75: 1.1215971283577606e-07\n", + "Cost in iteration 100: 1.0456327452784617e-07\n", + "Final cost : 1.0456327452784617e-07\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Do another 100 iterations if you want to.\n", + "# Repeated execution will continue with further 100 iterations.\n", + "model_controlled.optimize(100)\n", + "state = model_controlled.get_xs()\n", + "control = model_controlled.control\n", + "plot_oc_singlenode(duration, dt, state, target, control, target_input, model_controlled.cost_history)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "### Network case\n", + "\n", + "Let us know study a simple 2-node network of model oscillators. We first define the coupling matrix and the distance matrix. We can then initialize the model." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "cmat = np.array( [[0., 0.5], [1., 0.]] ) # diagonal elements are zero, connection strength is 1 (0.5) from node 0 to node 1 (from node 1 to node 0)\n", + "dmat = np.array( [[0., 0.], [0., 0.]] ) # no delay\n", + "\n", + "model = WWModel(Cmat=cmat, Dmat=dmat)\n", + "\n", + "# we define the control input matrix to enable or disable certain channels and nodes\n", + "control_mat = np.zeros( (model.params.N, len(model.state_vars)) )\n", + "control_mat[0,0] = 1. # only allow inputs in x-channel in node 0\n", + "\n", + "model.params.K_gl = 5.\n", + "\n", + "model.params[\"duration\"] = duration\n", + "zero_input = ZeroInput().generate_input(duration=duration+dt, dt=dt)\n", + "input = np.copy(zero_input)\n", + "input[0,1:-3] = np.sin(np.arange(0,duration-0.3, dt)) # other functions or random values can be used as well\n", + "model.params[\"r_exc\"] = np.vstack( [x_init, x_init] )\n", + "model.params[\"r_inh\"] = np.vstack( [y_init, y_init] )\n", + "\n", + "\n", + "# We set the stimulus in x and y variables, and run the simulation\n", + "input_nw = np.concatenate( (np.vstack( [control_mat[0,0] * input, control_mat[0,1] * input] )[np.newaxis,:,:],\n", + " np.vstack( [control_mat[1,0] * input, control_mat[1,1] * input] )[np.newaxis,:,:]), axis=0)\n", + "zero_input_nw = np.concatenate( (np.vstack( [zero_input, zero_input] )[np.newaxis,:,:],\n", + " np.vstack( [zero_input, zero_input] )[np.newaxis,:,:]), axis=0)\n", + "\n", + "model.params[\"exc_current\"] = input_nw[:,0,:]\n", + "model.params[\"inh_current\"] = input_nw[:,1,:]\n", + "\n", + "model.run()\n", + "\n", + "# Define the result of the stimulation as target\n", + "target = np.concatenate( (np.concatenate( (model.params[\"r_exc\"], model.params[\"r_inh\"]), axis=1)[:,:, np.newaxis], np.stack( (model.r_exc, model.r_inh), axis=1)), axis=2)\n", + "\n", + "# Remove stimuli and re-run the simulation\n", + "model.params[\"exc_current\"] = zero_input_nw[:,0,:]\n", + "model.params[\"inh_current\"] = zero_input_nw[:,0,:]\n", + "model.run()\n", + "\n", + "# combine initial value and simulation result to one array\n", + "state = np.concatenate( (np.concatenate( (model.params[\"r_exc\"], model.params[\"r_inh\"]), axis=1)[:,:, np.newaxis], np.stack( (model.r_exc, model.r_inh), axis=1)), axis=2)\n", + "\n", + "plot_oc_network(model.params.N, duration, dt, state, target, zero_input_nw, input_nw)" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Compute control for a deterministic system\n", + "Cost in iteration 0: 8.117061134315108e-06\n", + "Cost in iteration 25: 4.0329637221407195e-07\n", + "Cost in iteration 50: 2.133706589679289e-07\n", + "Cost in iteration 75: 1.0846418185856119e-07\n", + "Cost in iteration 100: 6.237553898673198e-08\n", + "Cost in iteration 125: 3.607365058691262e-08\n", + "Cost in iteration 150: 2.2496421814207724e-08\n", + "Cost in iteration 175: 1.5886138922670738e-08\n", + "Cost in iteration 200: 1.1727415781910453e-08\n", + "Cost in iteration 225: 9.005487959890062e-09\n", + "Cost in iteration 250: 7.191281120908631e-09\n", + "Cost in iteration 275: 5.835744371001404e-09\n", + "Cost in iteration 300: 4.915806895112334e-09\n", + "Cost in iteration 325: 4.206672224203755e-09\n", + "Cost in iteration 350: 3.6916483993194285e-09\n", + "Cost in iteration 375: 3.2948161905145206e-09\n", + "Cost in iteration 400: 2.9837006122863342e-09\n", + "Cost in iteration 425: 2.7310136209212046e-09\n", + "Cost in iteration 450: 2.5267282859627983e-09\n", + "Cost in iteration 475: 2.352356874896669e-09\n", + "Cost in iteration 500: 2.2057268519628175e-09\n", + "Final cost : 2.2057268519628175e-09\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# we define the precision matrix to specify, in which nodes and channels we measure deviations from the target\n", + "cost_mat = np.zeros( (model.params.N, len(model.output_vars)) )\n", + "cost_mat[1,0] = 1. # only measure in y-channel in node 1\n", + "\n", + "# We set the external stimulation to zero. This is the \"initial guess\" for the OC algorithm\n", + "model.params[\"exc_current\"] = zero_input_nw[:,0,:]\n", + "model.params[\"inh_current\"] = zero_input_nw[:,0,:]\n", + "\n", + "# We load the optimal control class\n", + "# print array (optional parameter) defines, for which iterations intermediate results will be printed\n", + "# Parameters will be taken from the input model\n", + "model_controlled = oc_ww.OcWw(model, target, print_array=np.arange(0,501,25), control_matrix=control_mat, cost_matrix=cost_mat)\n", + "\n", + "# We run 500 iterations of the optimal control gradient descent algorithm\n", + "model_controlled.optimize(500)\n", + "\n", + "state = model_controlled.get_xs()\n", + "control = model_controlled.control\n", + "\n", + "plot_oc_network(model.params.N, duration, dt, state, target, control, input_nw, model_controlled.cost_history, model_controlled.step_sizes_history)" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Compute control for a deterministic system\n", + "Cost in iteration 0: 2.2057268519628175e-09\n", + "Cost in iteration 25: 2.079569265893922e-09\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Cost in iteration 50: 1.969986550217457e-09\n", + "Cost in iteration 75: 1.874389888067335e-09\n", + "Cost in iteration 100: 1.7855706988225455e-09\n", + "Final cost : 1.7855706988225455e-09\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Do another 100 iterations if you want to.\n", + "# Repeated execution will continue with further 100 iterations.\n", + "model_controlled.optimize(100)\n", + "state = model_controlled.get_xs()\n", + "control = model_controlled.control\n", + "plot_oc_network(model.params.N, duration, dt, state, target, control, input_nw, model_controlled.cost_history, model_controlled.step_sizes_history)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Delayed network of neural populations\n", + "\n", + "We now consider a network topology with delayed signalling between the two nodes." + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "data": { + "image/png": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "cmat = np.array( [[0., 0.], [1., 0.]] ) # diagonal elements are zero, connection strength is 1 from node 0 to node 1\n", + "dmat = np.array( [[0., 0.], [18, 0.]] ) # distance from 0 to 1, delay is computed by dividing by the signal speed params.signalV\n", + "\n", + "model = WWModel(Cmat=cmat, Dmat=dmat)\n", + "\n", + "duration, dt = 2000., 0.1\n", + "model.params.duration = duration\n", + "model.params.dt = dt\n", + "model.params.K_gl = 10.\n", + "\n", + "model.run()\n", + "\n", + "e0 = model.r_exc[0,-1]\n", + "e1 = model.r_exc[1,-1]\n", + "i0 = model.r_inh[0,-1]\n", + "i1 = model.r_inh[1,-1]\n", + "\n", + "maxdelay = model.getMaxDelay()\n", + "\n", + "model.params[\"r_exc\"] = np.array([[e0] * (maxdelay + 1), [e1] * (maxdelay + 1) ])\n", + "model.params[\"r_inh\"] = np.array([[i0] * (maxdelay + 1), [i1] * (maxdelay + 1) ])\n", + "\n", + "duration = 6.\n", + "model.params.duration = duration\n", + "model.run()\n", + "\n", + "# we define the control input matrix to enable or disable certain channels and nodes\n", + "control_mat = np.zeros( (model.params.N, len(model.state_vars)) )\n", + "control_mat[0,0] = 1. # only allow inputs in E-channel in node 0\n", + "\n", + "zero_input = ZeroInput().generate_input(duration=duration+dt, dt=dt)\n", + "input = zero_input.copy()\n", + "input[0,10] = 1. \n", + "input[0,20] = 1.\n", + "input[0,30] = 1. # Three pulses as control input\n", + "\n", + "input_nw = np.concatenate( (np.vstack( [control_mat[0,0] * input, control_mat[0,1] * input] )[np.newaxis,:,:],\n", + " np.vstack( [control_mat[1,0] * input, control_mat[1,1] * input] )[np.newaxis,:,:]), axis=0)\n", + "zero_input_nw = np.concatenate( (np.vstack( [zero_input, zero_input] )[np.newaxis,:,:],\n", + " np.vstack( [zero_input, zero_input] )[np.newaxis,:,:]), axis=0)\n", + "\n", + "model.params[\"exc_current\"] = input_nw[:,0,:]\n", + "model.params[\"inh_current\"] = input_nw[:,1,:]\n", + "model.run()\n", + "\n", + "# Define the result of the stimulation as target\n", + "target = np.concatenate( (np.stack( (model.params[\"r_exc\"][:,-1], model.params[\"r_inh\"][:,-1]), axis=1)[:,:, np.newaxis], np.stack( (model.r_exc, model.r_inh), axis=1)), axis=2)\n", + "\n", + "# Remove stimuli and re-run the simulation\n", + "model.params[\"exc_current\"] = zero_input_nw[:,0,:]\n", + "model.params[\"inh_current\"] = zero_input_nw[:,0,:]\n", + "model.run()\n", + "\n", + "# combine initial value and simulation result to one array\n", + "state = np.concatenate( (np.stack( (model.params[\"r_exc\"][:,-1], model.params[\"r_inh\"][:,-1]), axis=1)[:,:, np.newaxis], np.stack( (model.r_exc, model.r_inh), axis=1)), axis=2)\n", + "plot_oc_network(model.params.N, duration, dt, state, target, zero_input_nw, input_nw)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Compute control for a deterministic system\n", + "Cost in iteration 0: 1.792835053390993e-07\n", + "Cost in iteration 25: 3.224858708247228e-10\n", + "Cost in iteration 50: 1.0235990384283723e-10\n", + "Cost in iteration 75: 8.627681277851615e-11\n", + "Cost in iteration 100: 8.09708890397755e-11\n", + "Cost in iteration 125: 6.901547805762654e-11\n", + "Cost in iteration 150: 6.563898918059379e-11\n", + "Cost in iteration 175: 6.358322097910284e-11\n", + "Cost in iteration 200: 5.819126634851626e-11\n", + "Cost in iteration 225: 5.598411882794661e-11\n", + "Cost in iteration 250: 5.458351655389417e-11\n", + "Cost in iteration 275: 5.101837452145287e-11\n", + "Cost in iteration 300: 4.9526343719852504e-11\n", + "Cost in iteration 325: 4.872279762423021e-11\n", + "Cost in iteration 350: 4.599347400927492e-11\n", + "Cost in iteration 375: 4.5049466495032303e-11\n", + "Cost in iteration 400: 4.32863678958512e-11\n", + "Cost in iteration 425: 4.241565430129624e-11\n", + "Cost in iteration 450: 4.121896579349796e-11\n", + "Cost in iteration 475: 4.036542019862459e-11\n", + "Cost in iteration 500: 3.990804399212831e-11\n", + "Final cost : 3.990804399212831e-11\n" + ] + }, + { + "data": { + "image/png": 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WwNraGlZWVvDx8cmzdoFaQEAAlixZghkzZqBp06ZaV4vy07JlSwDAhAkT4Ovrm2tg5efnh6pVq2LLli3o1asXnJycnnnMnj17wszMDH379sWYMWPw4MEDfP3113BycspzalpB/Oc//8G6devwwgsvYOLEiTlLYHt4eODEiRNFfp9+fn74/PPP8cILL+C1115DfHw8li1bhjp16hTouOq+rV+/Hj169MD48eNzlsCuUaMGEhMTc64W2tjYYPny5RgyZAhatGiBV199FY6Ojrh27Rp++uknPPfcc1i6dOlT+wsAw4cPx9q1a3HlyhV4enoW9lTm4uXlhWHDhmHlypW4d+8eOnfujCNHjmDt2rXw9/fPKfzr6OiIyZMnIygoCH369EHv3r0RGRmJ3bt3w8HBQeuY77//PkJDQ9GnT5+c5cxTUlJw8uRJbN26FdHR0bme87hp06Zhy5Yt6Nq1KyZOnIgHDx7gs88+Q9OmTTFixIhiv2ciIjJcHHdp47iL467ijruuXr2KdevWAUBOZv3cuXMBSIZZQerGEemNvpaBJKoI+vbtq1hYWCgpKSn5thk+fLhiamqqJCQkKIoiSySPGzdOcXNzU8zMzJTq1asrw4YNy3lcURTlxx9/VBo1aqSYmJhoLV395BLYatnZ2Yq7u7sCQJk7d26ux/NaAjszM1MZP3684ujoqKhUqjyXGn7nnXcUAMrGjRsLeEYUJTQ0VGnWrJliYWGheHp6KgsWLFC+/fbbXMtVe3h4KH5+frme37lzZ6Vz585a+06cOKF07txZsbCwUNzc3JQ5c+Yo33zzTYGWwH7a+/zmm2+UunXrKubm5kqDBg2U1atX5ywf/TgAytixY/M8fmRkpNKxY0fF3NxcqV69uhIUFKT897//VQAosbGxWm1//fVXxdfXV7G1tVUsLCyU2rVrK8OHD1fCw8ML1N/+/fsrlpaWyt27d5/6ntXv4fbt21r7V69eneucPXr0SJk1a5ZSs2ZNxdTUVHF3d1emTp2qPHz4UOu5WVlZyqxZsxRXV1fF0tJS6dKli3Lq1CnFw8NDawlsRZElv6dOnarUqVNHMTMzUxwcHJT27dsrCxcuVDIyMp7ad0VRlFOnTik9e/ZUKlWqpNjZ2SmDBw/OdS6JiKji4bgrN467OO4qzrjr119/VQDkuT3574KorFEpSilUHCSicmnSpEn45ptvEBsbi0qVKum7Owbj3XffxVdffYUHDx7kW6y0KJydnTF06FB89tlnOjsmERERlQ0cdxUNx11EFRNrdhFRkTx8+BDr169H//79OeB6irS0NK37d+7cwbp169ChQwedDrhOnz6NtLQ0fPDBBzo7JhEREZUNHHcVDMddRKTGzC4iKpT4+Hj88ssv2Lp1K0JCQhAREcFV8J7C29sbXbp0QcOGDREXF4dvvvkGMTExCAsLQ6dOnfTdPSIiIirDOO4qHI67iEiNBeqJqFDOnDmDwYMHw8nJCf/973854HqG3r17Y+vWrVi5ciVUKhVatGiBb775hgMuIiIieiaOuwqH4y4iUmNmFxERERERERERlRus2UVEREREREREROUGg11ERERERERERFRuVJiaXdnZ2YiJiYG1tTVUKpW+u0NERETlgKIouH//PqpVqwYjI15DVOO4i4iIiEpCQcdeFSbYFRMTA3d3d313g4iIiMqh69evo3r16vruRpnBcRcRERGVpGeNvSpMsMva2hqAnBAbGxs994aIiIjKg+TkZLi7u+eMM0hw3EVEREQloaBjrwoT7FKn0NvY2HDQRURERDrFqXraOO4iIiKikvSssReLSxARERERERERUbnBYBcREREREREREZUbDHYREREREREREVG5wWAXERERERERERGVGwx2ERERERERERFRuVFhVmMkIiIiIiIiIiIdUBTg9m3g7FnAyAi4fBn45x/g3Dlg+nSgSRO9do/BLiKi4oiLA+ztAVNTffeEiIiIiIhItxQFOHgQ2LsXCA8HLl0C4uOBBw+A7Oy8n+Pvz2AXEZHB+fJL4P594KWXgNdfB1QqYP16oG5dffeMiIiIiIio8BQFOHIE2LULOHMGqFoVOH1abicmPv25NWsCtWsDtWoB7u6At3epdPlpGOwiIiqsZcvkj765OXDxInDvnvxBDw4G3nhDgl9ERERERERlVXg48MMPwIEDwPnzwJ07EvDKj7k54OwsAa1GjYDmzYF27YB69crkLBcGu4iICismRn76+gL9+wPDhgG//gq8+SawcyewahXg6KjfPhIREREREQHArVsyEyUtDTh6FDh2TPblRR3U6t8faNkSaNwYqF8fsLQs3T4XE4NdRESFkZYmmVwA4OoK2NkBv/wCLF4MTJsGhIYCTZsC334L9O6tz54SEREREVFFdPIk8N138j3lwgUgNTV3G5VKAlvu7kCLFkDPnlJry96+1LtbEhjsIiIqDPUVEEtLwNZWbhsZAe+9B3TvDgweLHPbZ80CXnhBHiMiIiIiIiopiYlAWJjUFj54EHj0KHcbY2OgSxfgxRclY8vbG7CyKu2elhoGu4iICkM9hdHVNXdtLi8vmfv+8cfA6NGaQJeisI4XERERERHpxoMHwDffAN9/DyQlST3hJ+ttWVgAdepIgGvIEKBNG710VV8Y7CIiKgx1Zle1ank/bmEBfPaZ9r4PPwQyM4HZs+VxIiIiIiKiwjh0SBbE+uMPIC4u9+ONG0tgy8EBGD4c8PQs3f6VMQx2EREVxuOZXQVx6RKwYAGQnS3L+H73ncyJJyIiIiIieppz54A1a4D//ldqBz9OpQI8PICXXwYCAwE3N710saxisIuIqDBGjJArJmZmBWtfpw4QEiLTGk+fBnx8gOnTgalTARP+CSYiIiIion9lZMjK7vv2SaDr3Dntx21sgOeeA4YOBQYMkDpclCd+0yIiKgwbG6nNVRh9+wKnTgFvvw1s3SrBrh07gLVrgYYNS6afRERERERU9mVlabK3Tp2SGSFqpqZAt26y2vuIEUCjRnrrpqFhsIuIqDQ4OEgByf/9Dxg7Fjh6FOjcGbh6VVZ2JCIiIiKiimPfPmDuXODw4dyrJ3p6Ah99BLzyimYFeCoUBruIiArjk08kXXjYsILX7VJTqYDXXpMg1+jRwEsvMdBFRERERFRR3L8P/PADsH49EBam/Zinp2RvvfceYGWll+6VJwx2EREVxsKFwL17wIsvFj7YpebmBvz0k/a+ffuAiAj5cGMtLyIiIiKi8iElRRas+uor+R6RkaF5zMFBam9Nnw64uOiti+URv1ERERVUWpp8QAFAtWrFO5ZKpbn94AEwahRw/TqwbRuwejXn4xMRERERGbKDB4EPPwQOHNCuw1W/PjBkiMz4qFlTf/0r54z03QEiIoNx65b8tLDQ7dx5Kytgzhw55pEjQPPmwPz5QGam7l6DiIiIiIhK1qNHkqXl5AR06AD8/rsm0NW8OfDjj8DZsxIEY6CrRDHYRURUUOpgV7Vq2plZxaVSSQ2w06cBPz9JbZ46FWjbFjh+XHevQ0REREREupeVBWzZAnTtKhexb9+W/ZUrA2PGAPHxUrLkxRd1+z2C8sVgFxFRQamDXUWt1fUsbm7Ajh3A2rWAnR1w7BjQqhVw7lzJvB4RERERERWNokimVuvWQN26wMCBMnVRpQKaNpVC9ElJwIoVgKOjvntb4bBmFxFRQcXEyM/i1ut6GpUKGDoU6NEDGDdOVn5s0KDkXo+IiIiIiAouNRX48kspOp+QoNlftSowdqxkcpXk9wUqEAa7iIgKqqQzux7n6ipXg9LTNfvi4mQ1yOnTAWvrku8DERERERGJmzdliuKaNdpjdBsbWVF98mSgUiW9dY+0MdhFRFRQH3wADBpUuoEmc3PN7QkTgO+/BzZvlqWLe/UqvX4QEREREVVUv/wC+Ppqr6ro7g7Mng28/jpgwtBKWcOaXUREBWVnBzRrpr+VU0aPlte+fh3o3VuWLFYXvyQiIiIiIt25exe4eFHG3I8Hulq0kODX1avA8OEMdJVRDHYRERmK7t2BkyeBSZOkttf69VLPa/VqKZBJRERERETFc+oU0Lcv4OQkY+316yXQ5ecHREXJIlLPP89VFcs4BruIiArqgw+AoCBZVUVfrKyAzz8H/voL8PICEhOBkSOBJUv01yciKrJly5bB09MTFhYW8PHxwZEjR57afsuWLWjQoAEsLCzQtGlT7Nq1S+vxbdu2oWfPnqhatSpUKhWioqLyPZaiKOjVqxdUKhVCQkJy9t+5cwcvvPACqlWrBnNzc7i7u2PcuHFITk4uzlslIiIq2yIjgRdekJUUd+4EMjM1Qa7wcNnn5aXvXlIBMdhFRFQQDx8Cn34KTJsGZGXpuzdAmzbA0aPSp3r1gBEj9N0jIiqkzZs3IzAwEDNmzEBERAS8vLzg6+uL+Pj4PNsfOnQIgwYNwqhRoxAZGQl/f3/4+/vj1KlTOW1SUlLQoUMHLFiw4JmvHxwcDFUeV6WNjIzQr18/hIaG4sKFC1izZg1++eUXvPXWW0V/s0RERGXVpUvASy/J9MS9ezX727WTC8w7dwItW+qvf1QkKkWpGHNfkpOTYWtri6SkJNjY2Oi7O0RkaK5cAWrVkoLxaWkll7b84IGkTp86JQE2MzPA1DTvn9WqAfXry/PUtQIUBXjzTWDoUKBjx5LpIxHlKM74wsfHB61bt8bSpUsBANnZ2XB3d8f48eMxZcqUXO0DAgKQkpKCnTt35uxr27YtvL29sWLFCq220dHRqFmzJiIjI+Ht7Z3rWFFRUejTpw/Cw8Ph6uqK7du3w9/fP9++/ve//8Vnn32G69evF+i9cdxFREQGIS5OCs0/eqTZ5+MjK6B36KC/flG+CjrGYCU1IqKCuHVLfrq66ibQlZUlV5FOngROnJDt5Engn38KdxwLCyma37y5bLduAatWyfbGG8D8+UDVqsXvLxHpVEZGBo4dO4apU6fm7DMyMkL37t1x+PDhPJ9z+PBhBAYGau3z9fXVmoJYEKmpqXjttdewbNkyuLi4PLN9TEwMtm3bhs6dO+fbJj09HemPLcPOKY9ERFRmPXwoF7B/+AH4z380ga769YEvvwS6ddNv/0gnGOwiIiqImBj5Wa1a0Y+hKDLf/+uvgU2bgPv3827n6iq1AmxtgYwM+QB+8md6umSbPXgAHDkim5pKJa+1ahWwZYtcmRo5EjDizHWisiIhIQFZWVlwdnbW2u/s7Ixz587l+ZzY2Ng828fGxhbqtSdNmoT27dujX79+T203aNAg/Pjjj0hLS0Pfvn2xatWqfNsGBQVh1qxZheoHERFRqUpLA5YtA+bOBTw9gePHZb+rKzBvnqy6aGys1y6S7jDYRURUEOrMrqIEu5KSgA0bgJUrNR+qAGBpCTRpIoGtZs1ka9oUcHAo2HGzsyU7LDJSe7t9W/u1R48GPvwQmD5dsr3MzQv/HoioXAgNDcX+/fsRGRn5zLaLFy/GjBkzcOHCBUydOhWBgYH48ssv82yrflwtOTkZ7u7uOus3ERFRkSkK8P33QGCg5gL28eNApUqS2TV5siwCReUKg11ERAWh/mB0dS1Ye0UBDh2SLK7vv5crSYAEmvr3lwBUx47Fu3pkZCTF6evVAwICNK978yYQEQH89BOwcaNkf8XHA+PGAVOnAv36AQMGAD17yjRIIip1Dg4OMDY2RlxcnNb+uLi4fKcWuri4FKp9Xvbv34/Lly/Dzs5Oa3///v3RsWNH/Pbbb1qv5+LiggYNGsDe3h4dO3bExx9/DNc8/g6am5vDnIF0IiIqa06cAMaPB/74Q3v/0KGSzeXmpp9+UYnjnBYiooIoaGaXogDbtknGVocOwNq1Euhq3BgIDpag2YYNQJcuJZMmrVIB1asDL74IfPUVcO+eBNtq1ZLaXffvA+vXS8DL2VmucBW2ThgRFZuZmRlatmyJsLCwnH3Z2dkICwtDu3bt8nxOu3bttNoDwL59+/Jtn5cpU6bgxIkTiIqKytkAyeJavXp1vs/Lzs4GAK26XERERGXaRx9JTdvHA10dOgDHjskYnYGuco2ZXUREBbF4sQSGnjbF8Px5YMIE4Oef5X6lSpJxNXo00LZtya3g+DTGxpLFNWCATHs8fBjYuhX49lsgOVneV3CwBMcmTAC6dtVPP4kqoMDAQAwbNgytWrVCmzZtEBwcjJSUFIwYMQIAMHToULi5uSEoKAgAMHHiRHTu3BmLFi2Cn58fNm3ahPDwcKxcuTLnmImJibh27Rpi/s1GPX/+PABNlpZ6e1KNGjVQs2ZNAMCuXbsQFxeH1q1bo3Llyjh9+jTef/99PPfcc/D09CzJU0JERKQbcXEyJv/3Yg2qVgW++AJ47TWOdSsIBruIiAqiShXZ8vLggRS6/PxzKR5vZqaZ/29rW7r9fBojI+C556Q22Lffyj51Mfsff5StSRMJeg0eLME6IioxAQEBuH37NqZPn47Y2Fh4e3tjz549OUXor127BqPHFpZo3749Nm7ciI8++gjTpk1D3bp1ERISgiZNmuS0CQ0NzQmWAcCrr74KAJgxYwZmzpxZoH5ZWlri66+/xqRJk5Ceng53d3e8/PLLmDJlig7eNRERUQn54w9ZxOnSJSndkZQk+995B/jkE+CJKfxUvqkURVH03YnSkJycDFtbWyQlJcHGxkbf3SGi8kBRZLXD994DbtyQfb17y1WjOnX027dneTILrXJlWekxI0Pu29sDb74JTJoEODnpr59EZRzHF3njeSEiolKTmAi8/75czDU3l4AXALRsCSxfDrRurd/+kU4VdIzBml1ERM+Sni6FLYOCJHMLAM6eBXr0kGmKN24ANWsCoaHAzp1lP9AFAPXrA3v2SH0xDw/JTsvIAOrWlfoFiYnA/PnyvqZMARIS9N1jIiIiIiIN9SqLDRtqZi2kpwPW1sDSpcDffzPQVYEVKdi1bNkyeHp6wsLCAj4+Pjhy5MhT22/ZsgUNGjSAhYUFmjZtil27dmk9vm3bNvTs2RNVq1aFSqXKKZaaF0VR0KtXL6hUKoSEhBSl+0REhRMbKx+Ys2bJtL/Zs2UqYFiYrGY4cyZw+jTQt69h1QBQqYCXXgLOnAGmT5crYdeuAb/+CmzfLoOD1FRgwQIJen34oQTBiIiIiIj06fp1WXApIEBWHVcbNAi4cAEYO7ZkFoMig1HoYNfmzZsRGBiIGTNmICIiAl5eXvD19UX84//AHnPo0CEMGjQIo0aNQmRkJPz9/eHv749Tp07ltElJSUGHDh2wYMGCZ75+cHAwVIb0ZZKIDN+/hZ7h5AR07w7MmAFkZkpR9zNn5L6lpX77WByVKkkg78wZYM0aye7y95erYfPnA97ekvk1bx7g6SmBsbt39dtnIiIiIqqYoqOBRo2AHTs0+1xcZJbFxo1ymyq8Qtfs8vHxQevWrbF06VIAshS1u7s7xo8fn2fh0oCAAKSkpGDnzp05+9q2bQtvb2+sWLFCq210dDRq1qyJyMhIeHt75zpWVFQU+vTpg/DwcLi6umL79u3w9/cvUL9ZO4KIimzbNqB/f8DERIJclSsDK1ZIEffy7PBhoH17oE0b4JVXgA0bgOPH5TFbW6nnFRgoqeJEFRTHF3njeSEiohLz55/ACy8AKSlyf9gwWWE8v8WkqFwpkZpdGRkZOHbsGLp37645gJERunfvjsOHD+f5nMOHD2u1BwBfX9982+cnNTUVr732GpYtW5bnktlPSk9PR3JystZGRFRo6enAkiVyOzMTaNECiIgo/4EuAPjnHwnsHTkiq0s2bQqsXCkrNiYlyfTNOnWAr76Sc0NEREREpGtZWUBwsJTbePddoFMnCXS5ukq93DVrGOiiXAoV7EpISEBWVlbOkthqzs7OiI2NzfM5sbGxhWqfn0mTJqF9+/bo169fgdoHBQXB1tY2Z3N3dy/U6xER4eJFyWz67Te57+UFHDok0/wqgsGDpebBiBFyf/16yeZ69VVg3To5D/HxwFtvSQ2zn36SQqFERERERLpw5QrQpYuMQRs1klXPFQUYOVJKcPj56buHVEYZxGqMoaGh2L9/P4KDgwv8nKlTpyIpKSlnu379esl1kIjKn/XrNVlc5uayLyBAc7uicHWV1W2OHAHatZOraB99BHz5JXDqlGS9Va0qq1P26SM1zSIj9d1rIiIiIjJkigKsXi0XVP/8U/alpMiq4bt3A998A9jZ6bWLVLYVKtjl4OAAY2NjxMXFae2Pi4vLd2qhi4tLodrnZf/+/bh8+TLs7OxgYmICExMTAED//v3RpUuXPJ9jbm4OGxsbrY2I6JkePACGDweGDJHbnTsDbdvKY66ueu2aXrVuDRw8KHW73NyA0aMBMzNg3Djg0iWZ5mhuDuzfD7RsKbUTbtzQd6+JiIiIyNDcvg28/LJkbz14oNk/eLCsgP7CC/rrGxmMQgW7zMzM0LJlS4SFheXsy87ORlhYGNq1a5fnc9q1a6fVHgD27duXb/u8TJkyBSdOnEBUVFTOBgCLFy/G6tWrC/MWiIjyd/w40KoVsHYtYGQkNanCwoDt24GTJyVzqSJTqYDXXgPOn5dgltpPPwGxscCvv8rjigJ8951Mc5wxA0hN1V+fiYiIiMhwhIdLfdiQEM0+a2u54Lp+vSySRFQAJoV9QmBgIIYNG4ZWrVqhTZs2CA4ORkpKCkb8W9Nl6NChcHNzQ1BQEABg4sSJ6Ny5MxYtWgQ/Pz9s2rQJ4eHhWLlyZc4xExMTce3aNcTExAAAzp8/D0Cywh7fnlSjRg3UrFmz8O+aiOhxiiLT8t57TwrSu7nJB2rnzvJ4lSosevk4KyvN7UePgGnTpGDoli3A++9LjbOPPwYOHABmz5YU9M8+AwYOlIAZEREREVFeHByA+/c19zt0kFqxnp566xIZpkLX7AoICMDChQsxffp0eHt7IyoqCnv27MkpQn/t2jXcunUrp3379u2xceNGrFy5El5eXti6dStCQkLQpEmTnDahoaFo3rw5/P4tLvfqq6+iefPmWLFiRXHfHxHR0929C/TvL9Px0tMleysqShPooqczNZUg13PPAWlpEtwaNEimgm7eDHh4ANevS1H7Ll0ke46IiIiISO36dbn4/NtvQMeOMqY0NgY++UT2MdBFRaBSlIqxdFZycjJsbW2RlJTE+l1EJA4dksDMtWsStPnsM2DCBO3so7g4YM4cCdq8/77++lrWKQqwbZvU7vrnH9nn5SUr5vz+OzB/vgxcjIyAN9+Uc+rgoN8+E+kAxxd543khIqICWbMGeOcdoFs3YNcuGVPWrSuzLFq31nfvqAwq6BjDIFZjJCIdWrNGAjx//63vnuhPdjYQFAR06iSBrtq1gcOHgYkTc0+z++cfYNky2Sh/KpVkyJ05AyxcKPUUjh+X4Nb06cC5c7KaZXY2sGIFUK8esHQpkJmp754TERERUWlLTQVGjJAtLU1qwCoKMGqUrIbOQBcVE4NdRBXNl18CmzbJCoMvvQScOqXvHpWu6Gige3epM5WVJQXVIyJkBcG8qKdlV6tWal00aObmUvvs0iVg5UpJRQeAGjWkZtfmzZLxdfcuMH480KIF8Mcf+u0zEREREZWes2eBNm3kIryalRWwcSOwahVQubLeukblB4NdRBXN/v3A66/L7ZAQoFkzYOhQ4MoVvXarxGVnA8uXy+ouv/4KVKoEfPutrOrytCk2/y6cAVfX0ulneeHgAIwerbl/86b8uxs6FOjRA1i0CLC3l1UuO3eWpaTV55qIiIiIyqf16yVr6/Rpzb5mzeTi86BB+usXlTsMdhFVNJUry4omp0/LtDNFkfv16wMzZui7dyUjOloCLO+8A6SkSLbR8eOSNv2s1QGZ2aUbKSlyBS89XaY5fvIJMGmS1O9SqeRKXv36UjctI0PfvSUiIiIiXTt7Vi58pqRo9o0ZA/z1l5S4INIhBruIKqpGjYCtW4GjRyUQ9OhR+SsYrihSH6ppU8los7QEgoNlVZc6dQp2DHWwi5ldxVOvnmTU7dgh//YSE4GPPwb27pUga9u2wIMHUuC+WTNg3z5995iIiIiIdOnGDRmPA5ppiytWaPYR6RCDXUQVycGDQNeuwNSpmn2tWgE//ywBoDff1Ozfvh2YNQtITi71burE1asSxHv7bQmidOgAnDghReiNCvGnTz21jpldxadSAX36SFbdqlVyTq9elcUCNm+Wug1OTsD580DPnpJ5ePWqvntNREREREV16JAs+DRrFuDrK4XpOW2RSgGDXUQVycWLEtSKjMz9WOfOUlwckBXypkwBZs4EatYE5s+XgJEhyMqSIvxNmgBhYZpsrt9/L3g21+OY2aV7Jiay0s6lS8CnnwIffigF7IcNAy5ckNpexsbAtm1Aw4bA7NmySg8RERERGY5vvgG6dAG8veV7haJITVdOW6RSwGAXUUVS0GLrRkbA3LlAgwYy3WzqVKBWLeDzz8t20OGPP2RVxbFjNdlcx48XPpvrcb/+KkXU27fXbV9JApHvvy/TGdXOnZPCpW3byu8yLU2mOTZuDPz4owySiIiIiKjsevQImDABeOMNuX3/vlxUX7tWVuvmtEUqBQx2EVUkBS22bmQEDBgAnDolxevr1AFu3wbeew+oXVsybsqSq1eBgADJTjt+HLCzA5YskSy2unWLd2x7e8kSs7bWRU/pWcLDJfPr4EHg2DEJejk5yWqh/v5Ar14yzZGIiIiIyp47d4AXXpCxuJqHB3D4sBSnJyolDHYRVSQFzexSMzaWKWVnz0oasoeHBMzKSuAnNVVSohs0AL7/XoJ0b70l0zXHjZP+k2EZO1ayuwYPlhpff/0FJCRIwNHUVAraN20KfPCBXCUkIiIiorLh5EmpB7x/v2bfCy9Ifa7mzfXXL6qQGOwiqkgKmtn1JBMTYORIqae0ZQvQvbvmsS++AJYtAx4+1F0/n0VRJLjVsKEUu3z4EOjUST5Ily/X3aqS589L8GXZMt0cjwqmdm2ZyhgVBfTrB2RnS5ahs7Nkdj16JLW+GjQANmzg1EYiIiKismDMGCA6WnP/44+BnTtlpgRRKWOwi6giKW6xdTMz4JVXJOMGAO7eBaZPlyyq2rWBpUtLPuh14IBMVwwIAK5dk8Lm338vUxa9vHT7WmfOSLH7det0e1wqmGbNgJAQ4MgRWb3n44+BXbuAHTukhlxMjGQedugg0x+JiIiISD/+/FMWHwJkFkhoqCwyxJkWpCcMdhFVFIoim0pV+Myu/FSqBCxYALi7S+Bh/HgJei1ZovtC9n//DfTsKRlcBw5IYctZs2SK5YABmgCcLqmnferqfFHRtG4N7Nkjq/cAQJ8+wLRpMq3RxESWtG7TRrIPY2P121ciIiKiiiI7W1Y8X7EC6NpVavw2aSKzLfr21XfvqIJjsIuoolCpJK04I0OCU7pgbq6pkbV8uSboNWGCZN7s21f814iMlA/Ltm3leCYmkiJ94YJklVWqVPzXyE9xM+FItx4PaP7yi0xnzMyUK4aKAqxeLctYf/opkJ6uv34SERERlXcPHwKvvgp06QK8/baMyQICpN5qnTr67h0Rg11EFY6JiRRy16XHg14rVsjUwtu3i/dBd/q0TJls0ULm+hsZAcOHSx2tFSuA6tV11v18MbOr7Nq4Uf5dtGoFZGXJPiMjKVr/wQdyVXHHDtbzIiIiItK1xETJ5NqyRbNv/nzgf/8DrKz01y+ix5jouwNEVI6Ym0vW1YgRclWnZk3NY6NGSYbUu+8+vYD8mTPAJ5/Ih6V62uWrrwIzZgD165f4W9BS1IL+VPJUKsDPD+jdW+p4zZypqdtlZiY1I158EejRA1i0SFZwLCWKIrN4790DkpOBBw9kA6Q+a3q6bIcPAykpcmE0PV1+ZmTIbSsrWX/h0SPZwsLkcXUyW2amxPgyM6Vt06aafX/9JW2zs7U3RQEsLIC6daVddrbEjtPTNbOc1f0HJC5evbrmubduSf/yih8aGcn6AWoJCdL2SSqVZia1OlEvIUFT6u/J2cgqlfTXyEi2mBiJZ6qP8/gxVSpZ6MnUVJL9rlyRsbhKBbRvL/HRsrKQLBERkcG6elUCXVeuyH0rKwl69eql334RPUGlKBXjsndycjJsbW2RlJQEGxsbfXeHqPT9+CMQHCyFvqdMKd3XPndOvrkD8oH49tvAe+8BLi6aNhEREuTatk2z7+WXpS5Xkyal2181Ly/gxAlg925ZNpnKLkUBfvpJgl6zZwN//AEsXiwRF5VKgq2zZyPd3hX37kmQJyEBuHMHSErSbPfvS0CkenUJRCUlaQJNGRmaTR1wsrQE7Ozk8bQ0Ca5Q2XT3rvyudK2444tly5bhs88+Q2xsLLy8vLBkyRK0adMm3/ZbtmzBxx9/jOjoaNStWxcLFixA7969cx7ftm0bVqxYgWPHjiExMRGRkZHw9vbO81iKoqB3797Ys2cPtm/fDn9/fwDA8ePHMX/+fPz5559ISEiAp6cn3nrrLUycOLHA74vjLiKicigiAujWTQZIAODpCezdK2UkiEpJQccYzOwiqijOnJEVCz08Sv+169UDfvgBmDtXanAtXChF7IcPlw/MNWskoKT20kvARx/JFEZ9YmaX3imKZEfdugXcvCk/4+KA+HgJSlWtKo/Hxqqwb18fpKT4IW2kCunpvZFhNA+PkIksxRimqzKQvcoYj3Tcv9RUCZgVhKmpZHaZm8t244bE4YyNJWvJ2FizVakCeHvLc0xNZWyZnS3ZVuq6/OrbdnZSw9/YWPZFRUnm1uPt1JuVlcRw1a934YJki6mzodQZVMbGkgVWr54ma+r6dQn0qdsA2u0f/9OizgJ7XHa25ra6raJItlZKiiaDLCtLfqrv16mjuR8dLb9vdWZaVpb0X1Ek+NikiabtxYsS0MzKknNZkuX9imrz5s0IDAzEihUr4OPjg+DgYPj6+uL8+fNwcnLK1f7QoUMYNGgQgoKC0KdPH2zcuBH+/v6IiIhAk38vCqSkpKBDhw4YOHAgRqsXdchHcHAwVHks7nHs2DE4OTlh/fr1cHd3x6FDh/Dmm2/C2NgY48aN082bJyIiw3LlitTQffTvaKp7dxnf84IGlVHM7CKqKCZMkADTlClAUJB++qAoEtSaO1fmcD3OyEimK06dqr9MriclJsq39jp1JDpBxZKaKpnv+/dL4Co2VgJFiYlygTA5WWa42tpKFk58vLQrGcq/gSZVTpDI1FRmQLq4yHS4SpUkcys8XH5WqiTBIisroHJl2dzc5J+rhYX8E0lIkDGfra1s1tZyXCq/ijO+8PHxQevWrbF06VIAQHZ2Ntzd3TF+/HhMySMDNyAgACkpKdi5c2fOvrZt28Lb2xsrVqzQahsdHY2aNWvmm9kVFRWFPn36IDw8HK6urlqZXXkZO3Yszp49i/379xfovXHcRURUjiQmSvH5X36R+++/LzW6dF0HmKgAmNlFRNrKSpaSSqWd4gEAQ4cCH38sQaW7d/XTr7zY28tGObKzZbyjzqS5fVumBP7wgwSn7tyRWlUPHsi0vowMCRI9eqSpy/Q0V68+/XEjIwlMmZlJCbgmTSS4VKmSrGlgYyOZTlWq/Pvrq6LA4dZJVN/1FWqd/BGV8QBWSIEpMoEGDYGlSyW7kKiUZWRk4NixY5g6dWrOPiMjI3Tv3h2Hn7wY8K/Dhw8jMDBQa5+vry9CQkIK9dqpqal47bXXsGzZMrg8Pp38KZKSkmD/lL+H6enpSH9sFdTk5ORC9YmIiMqokydl1sXlyzLg+uYbuUBNVMYx2EVUUehzZUF1PaXZs4GjR2WfhQXwxhuyeXnJvuxsoGNHiVZMmSLFx3nFqMSlp8vUQHUcMjZWSpVt3CiZSnfvSi2rtDRN5nph3L+vuW1sLK9jZibZUpUrS/aTra0EqOrVA1q2lNs2NjIFzc1NAluWlrkLmD+bCkAzIGgp8PsAqQH322/y0NmzwPPPSx27efP0P22WKpSEhARkZWXB+fHK/gCcnZ1x7ty5PJ8TGxubZ/vY2NhCvfakSZPQvn179OvXr0DtDx06hM2bN+Onn37Kt01QUBBmzZpVqH4QEVEZ99ZbwKpVMiDz8ABCQ4FmzfTdK6ICYbCLqKJQZ3a5upbeayqKfCjOni1FhwCJWLzzDjB5snaBekBScy5elHSgvn2BRo2k3Wuvlf40wr//Br77ToohDR9euq+tIw8eaK+kFxUFrFsncc+EBJk6mJYmGVpFYWQkNbOqVJFjqQNWjo7yq61WDXB3B2rXloU5q1aV4FbhA1Y6oFIBXbrIduiQBL1cXCSit3evbM8/D6xYIRmGROVUaGgo9u/fj8jIyAK1P3XqFPr164cZM2agZ8+e+babOnWqVtZZcnIy3N3di91fIiLSA0WR1RX37pX79eoBf/4pgzwiA8FgF1FFoK4CDZROZld2tqz+OHu2RFgASXseO1aCV3kUXgYANG0qFagXLwa++kqK6o8cCXz4ITBxIjBmTMksp5aXiAjgyy8Bf/8yG+xKSwNOnQI2bwb++UcKnsfHSyZWSoqmSHlhsrHUNascHSWA5eAAODtLdlWNGkCtWkDdunLf3l4ytQxO+/aawdv06bJt3CjLLtarJxmFK1fqf8ovlWsODg4wNjZGXFyc1v64uLh8pxa6uLgUqn1e9u/fj8uXL8Puib+l/fv3R8eOHfGbOvMRwJkzZ/D888/jzTffxEcfffTU45qbm8OctQ2JiAxfaqpc7D1zRu63bAkcPMj6tWRwGOwiqggePJCUm/j43NlUuqQowK5dwLRpMg8OkFSeceOAwMCCXQ1ydQU+/VQCXCtXAsHBEqibMkWqhj8ls0Cn9Djt89Ej4PhxWbjy7Fng0iUJZMXFSQDK2lqS3xITC3YsQLKunJ0lQOboKKdZHbyqV0+SmVxdJZaol8wrfaldWzL4UlMlQKueclu9ugQ6v/5aUtKIdMzMzAwtW7ZEWFhYTmH47OxshIWF5bviYbt27RAWFoZ33303Z9++ffvQrl27Ar/ulClT8MYbb2jta9q0KRYvXoy+ffvm7Dt9+jS6deuGYcOG4ZNPPin4GyMiIsN1/boEt27flvsvvyyFWYkMEINdRBWBtbXMY8vMlOreJSEiQlZmUa/UZW0NjB8vQa6iBAtsbeV4EydK1s2ePUCPHprHt26VCE0eq4zpRAlN+8zOljjasWMS0LpwQVZyNjOTINONG8C1a1JHKz8pKZrbFhaSXWVjI0EsNzcpqVC/PtCwoSaIVamSTt9G+WJsDGzfLgO8wEBg2zb5RW3fLgGwgQMl8Gptre+eUjkTGBiIYcOGoVWrVmjTpg2Cg4ORkpKCESNGAACGDh0KNzc3BP27gu7EiRPRuXNnLFq0CH5+fti0aRPCw8OxcuXKnGMmJibi2rVriPk3YH/+/HkAkhX2+PakGjVqoGbNmgBk6mK3bt3g6+uLwMDAnJpgxsbGcOQUFiKi8ungQRlrp6XJ/cBAYNEi/faJqBgY7CKqSEoi0HXtGvDRR1IMCpCozYQJwNSpulnJ0MxMphE+PpXwwQNg9GhZ9q9bN/kw7tVLt8Xsi5DZ9eiRxMhu3pTSY9euSRdv3JCA1okTBVuRUM3YWEqcVakiWVnu7hK88vKSzc2tAmZilSR3d2DLFsmAHD9eAqrZ2cCmTcC+fTIFd9w4yVYk0oGAgADcvn0b06dPR2xsLLy9vbFnz56cIvTXrl2D0WN/19q3b4+NGzfio48+wrRp01C3bl2EhISgSZMmOW1CQ0NzgmUA8Oq/K2bNmDEDM2fOLFC/tm7ditu3b2P9+vVYv359zn4PDw9ER0cX4x0TEVGZ9N13MrbOyJD7ixcDj2URExkilaIoir47URqSk5Nha2uLpKQk2NjY6Ls7RIYvKQmYP18+DNVpSK+9BnzyCeDpWbKvfesW8N57wPffS2EqQFKZJk0ChgzRTRqTt7ekXu3aBeWFXkhKkvhXTIwEs27elESgc+ckqBUfLzG4wrCwkAQ2JycpV9a7t8yeq16d2Vhlwr17EvT6+2+JXgKS3eXtLdMb69fXZ++ojOD4Im88L0REBiArC/jgA00GV8eOspDUvxdKiMqigo4xGOwiqghWrQLWrwcCAoC33y7esR49kuLxs2bJkn4A0LkzsHAh0KpV8ftaGNeuAUuWyBSz5GTZV7UqsHYt4OdXoEOkpEjgKjZWAlnXrwOHDwO3dhxFQqYdEm1qIjnVpEgrFrq5ySlXB7DOnAEaN5aan+7uuk1EoxKUlQX873/AzJnA5cua/S1ayCIGPj566xrpH8cXeeN5ISIq4+7dk4Hqzz/L/Y8+kvE9B6hUxhV0jMFpjEQVwcmTwO+/A23bFu84R48Cb7yhKT7foAGwYAHQt69+5tLVqAF89pmspvfNN8AXXyAtOg7xlRsj9ax06dbVDFy9ZYaNG6XW5t27EhdLTZVM7fzD/a3lR7L23sqVZTG/atUkmPXtt5LsU6eOZGc1ayYJP3XrSh0tKgeMjYHXX5cB4ZQpEuB6+FDq1LVtK7/s+fOBl17inFIiIiIq+86fl/G7OnN97lxZHIqoHGGwi6giUBdbL+rKgikpElAKDpYaRlWryofiG2+UXMH7f2VkyBTB+HjA1BRwcJAsrCtXJOM6IQG4d88aDx68i4cPJyIbKqDL40cwe+ZrGBnJonyurnKKDhxQUMk8G/aV0+HobgnXaiq4ucl0wzp1tOvkz52r63dMZZapqfyjW7AAmD0b+Pxz+b9x8SLQv7+sFvrzz/KPlIiIiKgs2r1bpimqZ0WYmMjUA6JyhsEuoopAXWy9KCsL7tsHjBkj0SVA6nIFB8vSf0WUlSVBqlu3AHNzKb4eFycvMWeOBLbu3ZMaWOo6mQWjnVVja5MNl/sX4arE4BZcYWeaCqc61qjm444adS1Qu7Yk5Xh4PLlgpAqAMQAWzaI8mJhIsOvjj4EvvgDmzZOUwchI+cf05pvAyJGAi0ux/p8QERER6YyiyIW699/XTG0wNpZSDf7+eu0aUUlgsIuoIihKZtedO1IEfu1aue/uDqxYIVXU86Eo8rSMDJnuFxcHREfLTMPYWAlwJSXJFEI1IyNJFisoIyMJjjk7y0wyBweJKdSoAdSsKcGrOnXUBd6NgFs2wIqN0vf4eOAsgGhLKWTvPxFo1KjgL070OFNTWaExMBDYsEGCwBER8vO//5Upjf37S1Ykr5gSERGRvqSlycVr9erpgAyqN2wAXnlFf/0iKkEsUE9U3imKLOv38KEU165V69ntv/8emDBBgkMqFTBuHLLnfIJ7WdaIiwNu3AA2bpRi7rGxEuBKTpbPUUWRi0TqRRILys5OglbqWZJubhLAqlVLtmrV5HEHBzl+oT18CGzeLJk4kZGy77//ldX2nrRnDxAaCnTtCgwYUIQXowpJUSQTct48qZH3uNatJejVuzcLv5YzHF/kjeeFiKiMuH4dePllIDxcxvWKIj/XrQMGD9Z374gKjasxPoGDLqqw7t0DqlSR26mpgKUlAPmce/BAirbfvi1BqzPH0nB53UFci85GLJxxx8QFyaYOSMswRnb204q5583aWjKwMjOlC66u2hlYbm4SwHJyAiwsdPu286UowIEDsoLjsmWAra3s37pVlkt8800pQD5njqxc+eWXpdQxKlcOHgT+8x/g0CHt/S4usqrjmDF66RbpHscXeeN5ISIqAw4ckMyt+HjA3l6uIB87BqxeDQwbpu/eERUJV2MkqmAyMiTDSr0lJEgQ6/wRFeIsfsDtLHskdrDE3bsS/0pOziv7yhJAd83dzH+3x9jZSXAqOVmmKjo5SdDKw0MCWPXry4xHFxdJKCtzVCqgUyfZ1BRFsnEiI6XivLqAV1EL+hM995wEvE6dkmW8t22TtMXYWKmVkZEBjBgh/4mIiIiIdElRpITHhAly1dnLC9i+Xa48//Yb8MIL+u4hUYljZhdRGaAoQGKiBJASE6WefGys1Ly6fVtKA7m7y2N37gA//SSLwD18CKSny2dYYepePc7SUoGTRTIc717EOdSHsZGCKi7mcKlhjurVJQurXj2gWTPA2xswe/bihoYnO1umOC5dqp2Js2oVMGqU/vpF5UdsrBSFXbZMU7TOzg548UX5D//ee0DPnpziaIA4vsgbzwsRkZ6kpwPjxsk4FpBlxLdt4wU2Kjc4jfEJHHRRSVAUqVOVlCTZUhYWEhxKT5dA1ZIlEqxKTJTHk5KA+/clUOXkJFlQiYmyHT+umz6ZmAC1a8sicA4OwP79EsuxsJBMq8qVZUphrVpA6wb3Mf7PAFmCGAAGDpTpfeqpfRVRZKQEJM6dkwCYm5u+e0TlSUqKLPqweDFw6ZL2Y25uUux+5EgJhJFB4PgibzwvRER6EBMji+P89ZfMZnj1VWDTJqlRu3gxL6pRucBg1xM46KL8KIoEoNRZU7duyRYbK9PbnZ1lIbXkZNm3ZIkkZqSlSVDr8f9B6rpTDx8Wv19GRpLRZW4uQatWrWR2nb09cPas1MNydJSgmbOzZCW7ukobV9cCvMDvvwOvvSYfihYWUrh99Gj5YCSikpWVBezcCXzyCXD0qPZjZmbA668DEydKSiWVaRxf5I3nhYiolP31lxSiv3VLLppNniylFB49AsaOlS8xHOdTOcBg1xM46Co/FEWCSeqAk3pT309NBe7eBU6ckOBVYqLcT06WguwpKZLZ5OQk9+/ezZ1goSumppqMKisrwMZGkqbs7aUcVMOG0pcqVeQxBwfNfVNTHXUiKEhWFxwzRoJbWVlSl2r2bEn5atBAVl9s2lRHL0hEhXLihFxt3bBBBqRqtrZARMSzV1AlveL4Im88L0REpURRZGbGhAlSE7RxY1kMZ/hw+eITECDLqDOri8oJFqgvZZGREi+4eDH/Nk2aaOpex8UB58/nbqMOtjdqJNk6KpVMgzt9WvvxxzVsKLNfVCopSv7kdLjHn1OvnqyGB0iQJzw89/EURbZataTouKLI9Dt1W/Xj6tX5FEVe391d4ij370sfsrLksSd/2tnJecjIkMDUP/9IzamsLDlmZqZmMzKSLT1dE+DKXVS98GJiNOc0PyYmklVlawt4ekowysZGs7ihg4Mmq8rZWd6XnZ20t7OTtsbGxe9rsUVFAX/8IVd67tyRdOZffpHHhg+XOlVWVvrsIVHF1qyZrIq0aBHwzTdS2ys2Vv7w1q0L+PlJ7biICClq7+mp7x4TERFRWZCWBrzzDrBmjdx/+WVg6lTA11cCXT17At99x0AXVUgMdunI/v3A/PlPb/PDD6XTl4rKykoCeZUqAZaWEoC0tJStcmWZ9qcORNWsKcXWra3lMVNTmRJobS2blVU5yvKNiZGfjx4BrVsDV67ISVqxAhgyRL99IyINe3tZqTEwENi1S6Yb7NsH7NghGwDMmQM8/7xMcezVq4xE1ImIiKjUXbki9bkiIyWYFRQkWVwdOsjUljZt5AtouVxdiujZGOzSkfr1gc6dJUspPw0ayHcZQGpBPTl17vEJpXXqSFv1Kn2Pt31y4qmHhyZj7N494PLl/Pvg5ibZSIBM4csvE02lkrbVqsnt1FTgzBnNY+pAkPq2h4cURTcykgwsdU1EIyNNG/XWoIH87TU1leyurVs17YyM5LubOqPLxwd45RXJsHr0CJgxQ4JRzs6Ai4u8F3Uhdnd31hLP061b8vPjj+WXU7Mm8OOPnLZIVFYZGwN9+8p2/rxMTVi5Uv5oK4pkZv7yi/wBHD8eeOMN+YNIREREFcPu3cDgwTJVx9FRitB36yY/b96UL1w//cQVGKlCY80uovIsK0tS29R1gJ5/XlYYVEdHicgwpKXJlYHFi+UK7uOMjGQfi9nrBccXeeN5ISIqAdnZUnt35ky5ANamjYwP3N01bX78EWjRQnsfUTlS0DEGJ+8SlVfJyZIZog50jRsnheoZ6CIyPJaWMu04IkKKIr75pmb51+xsWa41IEAyvrZulau6REREVH7cvStj+xkzJND19ttyEWzcOCl/oNavHwNdRChisGvZsmXw9PSEhYUFfHx8cOTIkae237JlCxo0aAALCws0bdoUux7/zwhg27Zt6NmzJ6pWrQqVSoWoqKhcxxgzZgxq164NS0tLODo6ol+/fjh37lxRuk9U/l28CLRtKynOgNToWrJEqu4TkWFr1gz46itZveSrr4DmzSWo/f33QI8ewIABMsjt2RPYuVNW+yAiIiLDFREhF7Z27ZKLXR99BERHA889B4SGSrYXEWkpdLBr8+bNCAwMxIwZMxAREQEvLy/4+voiPj4+z/aHDh3CoEGDMGrUKERGRsLf3x/+/v44depUTpuUlBR06NABCxYsyPd1W7ZsidWrV+Ps2bPYu3cvFEVBz549kaWLpfmIypM9eySl+exZmcPv6CgF1YiofKlcWTK8IiJkGuM772hqcyiKFLfv21fqeU2d+vSCjkRERFT2KIosKtW+vRSHdnUFvLwkuLV7t9T5HDIE+PZbffeUqMwpdM0uHx8ftG7dGkuXLgUAZGdnw93dHePHj8eUKVNytQ8ICEBKSgp27tyZs69t27bw9vbGihUrtNpGR0ejZs2aiIyMhLe391P7ceLECXh5eeHSpUuoXYAv8qwdQeWeosgqLB99JLfbt5cVWFxc5H65WV6SiPKVmgps2QJ88UXu2l4A8PnnwKRJpd+vcozji7zxvBARFdP9+8CYMcD//if3a9QArl2T2yYmwNChcjGrTh399ZFID0qkZldGRgaOHTuG7t27aw5gZITu3bvj8OHDeT7n8OHDWu0BwNfXN9/2BZGSkoLVq1ejZs2acM9nPnJ6ejqSk5O1NqJyKzlZlh7+8EMJbI0eDezfr1mhjYEuooqhUiVg2DDJ9jpzBpgwQZawVQsMBDp2BFavBsLCgKNHcy/xS0RERPp18iTQurUEuoyNgYULgc8+k+Xsx4yRkiXffMNAF9FTFCrYlZCQgKysLDg7O2vtd3Z2RmxsbJ7PiY2NLVT7p/nyyy9RuXJlVK5cGbt378a+fftgZmaWZ9ugoCDY2trmbPkFxYgM3rlzgI8PsH07YGYGrFwpm7m5vntGRPrUsKFkeCUkSJZnz56ycuOffwIjR8r9Nm1koLxoERAXp+8eExER0Zo1Eug6fx6wtQV+/x147z2pyXnlikxr9PTUdy+JyjyDWo1x8ODBiIyMxO+//4569eph4MCBePjwYZ5tp06diqSkpJzt+vXrpdxbolIQEiJfVs+dA9zcgD/+kKwutUmTgE6dgJ9+0lsXiUjPzMyAl18G9u4Frl+X6c516sgqjoDUAJk8GahWDejeXQJj6en67TMREVFFk5oKDBoEjBih+Rw2NZXC9IDM1HBz01//iAxMoYJdDg4OMDY2RtwTV3/j4uLgop4u9QQXF5dCtX8aW1tb1K1bF506dcLWrVtx7tw5bN++Pc+25ubmsLGx0dqIyo2sLJmy+NJLMp+/Uyfg2DHJ8HrcsWPAgQPAgwf66ScRlS3VqgFTpgAXLsjfhkGDJBgGSPArLAx45RVZ3Yl/N4iIiErHsWOSrbVpk2bf88/L6oucrUFUJIUKdpmZmaFly5YICwvL2ZednY2wsDC0a9cuz+e0a9dOqz0A7Nu3L9/2BaUoChRFQTqvPlNFk5gI9OkDzJsn9999F/jlF+CJ6cIAgFu35Kera6l1j4gMgEoFdOgAbNwI3LkDrF2rHSw/dkxq/g0bBmzeLNlgzJAmIiLSLUWRKYqtWgG3b8u++vVlReVffpHpjERUJCaFfUJgYCCGDRuGVq1aoU2bNggODkZKSgpGjBgBABg6dCjc3NwQFBQEAJg4cSI6d+6MRYsWwc/PD5s2bUJ4eDhWrlyZc8zExERcu3YNMTExAIDz588DkKwwFxcX/PPPP9i8eTN69uwJR0dH3LhxA/Pnz4elpSV69+5d7JNAZDCOHgUCAmS+vqUl8PXXwODBebdVFE2wq1q10usjERmWypVlRaehQ2WVp7Vrge++Ay5dkp/ffSftpk2TQffbb8uCGMyYJiIiKrr794F33gHWr5f7lpZSa/ONN7i4FJEOFLpmV0BAABYuXIjp06fD29sbUVFR2LNnT04R+mvXruGW+gs2gPbt22Pjxo1YuXIlvLy8sHXrVoSEhKBJkyY5bUJDQ9G8eXP4+fkBAF599VU0b94cK1asAABYWFjgwIED6N27N+rUqYOAgABYW1vj0KFDcHJyKtYJIDIIigIsXixTi65ckTTnQ4fyD3QB8gGakiK3mdlFRAVRowbw8ccyzfHQIVnxqVIlzeNHj0px+6pVAX9/qQeYmam37hIRERmc69dlhkbLlhLoMjKSC04JCVJ7l4EuIp1QKUrFWHM8OTkZtra2SEpKYv0uMix37gDDhwM7d8r9l1+WpYbt7J7+vPPngQYNJPsiKamke0lE5VV6ugS1vvpKplSoC9sDMkBftgx47bUKm+nF8UXeeF6IiJ6QmgosWCClAR49kn3VqwP/+5+UFiCiAinoGMOgVmMkqnD+/BPw9pZAl5mZfKncuvXZgS4A+HdaMKcwElGxmJtrVnO8fRtYvhxo1kwey86WaY3OzrIkeps2UgD/zBn99tmALFu2DJ6enrCwsICPjw+OHDny1PZbtmxBgwYNYGFhgaZNm2LXrl1aj2/btg09e/ZE1apVoVKpEBUVle+xFEVBr169oFKpEBISovXYhAkT0LJlS5ibm8Pb27uI746IiKAowJYtQN26wOzZmkBX165AVBQDXUQlhMEuorIoO1uu+nTpAty4IR+Of/8t8/oLmtqcni7LE7u7l2hXiagCsbcH3noLOH4cuHwZmDNHCuk+fCiB+KNH5ap148ZAnTpym4Xt87V582YEBgZixowZiIiIgJeXF3x9fREfH59n+0OHDmHQoEEYNWoUIiMj4e/vD39/f5w6dSqnTUpKCjp06IAFCxY88/WDg4OhespnysiRIxEQEFD4N0ZEROLyZaB3b2DgQM2FaBMTIDhYVkCuWlWv3SMqzziNkaisiYsDhgyRVVgAqcu1fDlgbV204ykK5/4TUclRFLkyvXYtsG6drBj7pGbNJPD1wgul3r2SVpzxhY+PD1q3bo2lS5cCkBWu3d3dMX78eEyZMiVX+4CAAKSkpGCnelo7gLZt28Lb2zunzqladHQ0atasicjIyDwzs6KiotCnTx+Eh4fD1dUV27dvh7+/f652M2fOREhIyFMzxPLCcRcRVXipqYCHh9TiUqtVS7K8WrTQX7+IDBynMRIZot27AS8vCXRVqgR8+618eSxqoAtgoIuISpZKBTRvLlepb98Gfv9d6gxaWWnanDghQfzJkyX7Kz5e6hFWYBkZGTh27Bi6d++es8/IyAjdu3fH4cOH83zO4cOHtdoDgK+vb77t85OamorXXnsNy5Ytg4uLS+E7n4f09HQkJydrbUREFVpCgvYYfsgQuTjEQBdRqWCwi6gsSEmRuje9e0tmV5Mm8oVwxAgGq4jIcBgZAZ06AatXA3fvSmH7l16Sul8JCcCiRVLXq359wMlJ6pSsXVshF9FISEhAVlZWzmrWas7OzoiNjc3zObGxsYVqn59Jkyahffv26NevX+E6/RRBQUGwtbXN2dw5hZ6IKprbt+Viz6+/ytR+Ly9ZRb1yZVl18bvvincBm4gKhcEuIn37+2/JilBPQXn3XeDIEaBRo+Id9/XXgY4dgYMHi91FIqJCMzWVAP62bRL4+uEHqVlSqRJw757UJjx4UL4YVK0KdO4sga979/Tc8fItNDQU+/fvR3BwsE6PO3XqVCQlJeVs11mrjYgqCkUB1qyRVdDXrpVFXQYMkM+zNm0km2vwYD13kqjiYbCLSF8ePQJmzACeew64eFGWHv7lF2DxYsDSsvjHP3JEVnPMzCz+sYiIisPSUgb/mzfLFMZNm4Du3QFjY3k8Kwv44w8JfLm7A8eOyZeHcszBwQHGxsaIi4vT2h8XF5fv1EIXF5dCtc/L/v37cfnyZdjZ2cHExAQmJiYAgP79+6NLly6FexOPMTc3h42NjdZGRFTu3bgB+PnJbIzERMlkvndPZmZMnSpj8dq19d1LogqJwS4ifTh/XoJcs2fLl7zBg4GTJ4Hnn9fda6hXfKlWTXfHJCIqLisrICBAahMmJsrUjq5dNYGvBw+AVq1kFdoPPgD69AG++Ua7wG85YGZmhpYtWyIsLCxnX3Z2NsLCwtCuXbs8n9OuXTut9gCwb9++fNvnZcqUKThx4gSioqJyNgBYvHgxVq9eXfg3QkRUESmK1NZt3Fhq7pqYyOdYerqMvX/5BZg3T7KciUgvTPTdAaIimzJFMqL69JGpMk/UMSmTFEVWVpw8GUhLA+zsZPqirpd2v39f6oABgKurbo9NRKQrNjYS7B88WP5u/fSTZH3t3SvLtX/6qbT76Sdg9GiZ8j18ONC/f7kI5AcGBmLYsGFo1aoV2rRpg+DgYKSkpGDEiBEAgKFDh8LNzQ1BQUEAgIkTJ6Jz585YtGgR/Pz8sGnTJoSHh2PlypU5x0xMTMS1a9cQ8+8Fj/PnzwOQrLDHtyfVqFEDNWvWzLl/6dIlPHjwALGxsUhLS8sJijVq1AhmZmYlcj6IiAzG3r3AqFFy29ZWU3vyxRflAo2Dg/76RkQAmNlFhuTkSanpMn68BI02bZJaMCNHSkCnbVtg7lwgMrJsTn+5dg3o2RMYO1YCXT16AKdO6T7QBWiyuqytpSgmEVFZZ20NvPoqEBIiRX43b5aLGeqr4ooCREQAEyYAbm5S13DvXr12ubgCAgKwcOFCTJ8+Hd7e3oiKisKePXtyitBfu3YNt27dymnfvn17bNy4EStXroSXlxe2bt2KkJAQNGnSJKdNaGgomjdvDj8/PwDAq6++iubNm2OFui5kAb3xxhto3rw5vvrqK1y4cAHNmzdH8+bNc4JoREQVmq+vfPeoVEkCXRYWwLJl8hnGQBdRmaBSlLIYFdC95ORk2NraIikpiXUkDFVoKNCvH9C6tRR1P3YM2LED2LlTvgA97rnnZI58WaAoUqxy4kQgOVlq18yfD4wbJyuXlYTffpNpQfXqyZRJIiJDlZoqQa3vvgP27AEePtQ8ZmUlqz2+9BJQp478vW3WrFRXseX4Im88L0RUrly7Bnz4IfDf/wJmZsB77wFffSWPeXsDGzcCDRvqtYtEFUVBxxicxkiGQ3012dVVvsi0aiXbrFnAzZvArl0S/AoLk6kuao8eSWHkLl1kumODBqX3RejWLeDNNyUgB8gVoLVrJQhVklivi4jKi0qVNAGtjAwJ5q9bB/z4o0x9XL9eNiMjWeGxalWZ5vjaa3Lhw4RDHSIiKoZNm4C33pIMrgcPgLNnNReTJ0+WmSXm5vrtIxHlwmmMZDjUUznyCuC4uUk9l9BQ4M4dYOZMzWMHD0qwafJkmfZSqxbw9tuaL0olQT3NskkTeW0zM2DBAsk2K+lAFyBf+NzcgBo1Sv61iIhKi5mZTAdftw64exc4cACYNAmoWVP+7gHyGbBypVzgsLWVwNfVq3rtNhERGaDkZGDYMGDQIAl0ubvLuP78efk+sm8f8NlnDHQRlVEMdpHheDyz62ksLOTKvlr9+sAXX8gXJDMzIDpaisL7+wP29pJppUu3bwMDB8oHY2Ii0KKFTLn8z380q42VtNdfl6WQdf3eiIjKCmNjoEMH4PPPpZj9iRPARx9pL/Gemiq1HXv0AM6d019fiYjIsPz1l8wU+e47yRz28ACuXwcyMyXT+MQJoHt3ffeSiJ6CwS4yHEWdmufqKgWN9+6V4NOOHVIkvlYt+cBq3FjTdtcuKXi/aVPRlrkPDZVsrq1bZerMrFnyYflY8WAiItIxlQpo2hSYMwe4dElqq3zxBdCypXxJuXlTvqgQERE9y9atcjHln3+k2LylpWQIV6oErFoF/PCD9oV1IiqTWMiCDId6GuOzMruexspKVvfq00fuX7okQS+1rVuB1atlU6nki1LPnrK1ayeZYXl58ECm0qxaJfebNJGsqhYtit5XIiIqGnd3ucgxYQJw755cgbe01HeviIjIEHTtCjg5ybhfPQ3ex0em0Netq9++EVGBMbOLDIeiyBV6XRZdr1NHe0XEkSNldZVmzeT1wsOBefOk9kvVqlIj5kmHD8sqLKtWSYBs8mR5nj4DXT17Ah07AmfO6K8PRERlgZ0d0KmTvntBRERl2cGDMvYH5AIJIIEuY2OpBfznnwx0ERkYZnaR4YiMBLKySnYlxQ4dZAMkk+yXX4Cff5bN0RGoUkXTdtgwICoKOHlSPhzd3WVef5cuJde/gvrrLym+z1XIiIiIiIjy9vChzM5YsQL45hu5UPz55zK2r1NHVvv18dF3L4moCPhNmAxLaRV4B2S65JAhsmVnA/HxmsdOnpQPP/XqX4BMkQwJkSmNnToBNjal19fHPXigWWWyOFM+iYiIiIjKqytXgFdeASIi5GL6hx8CsbHy2JtvAosWAZUr67ePRFRknMZIVBBGRoCLi1zl+fJLoE0bCXRZWEjNL5VKVvr64gugb19ZjfFx6eml11d1bbPKlQFr69J7XSIiIiIiQxAaKiVHIiKk8LyxsQS6HB2BH38EvvqKgS4iA8dgFxmGX3+VbKkPP9RfH+7eBfz9ZSXHhw9lueFLl2TJ+9u3gS1bgDFjJPjVtavmebduSc2Ybt2ATz6RGl+PHpVcP9WrVjKri4iIiIhIIzMT+OADoF8/WcDE2hpITZX9ffrI7I0XX9R3L4lIBziNkQzDhQvAgQPaNbNK07FjwIABku5sZgZ8+ikwfrymuH3VqpIG/corcj8rS/PcAwckOPbrr7IBcqWoQwep7/XKK0Dt2rrrqzqzS5eF/ImIiIiIDN3ff8s4HgBMTaX0R+XKwOLFwKhRJVsbmIhKFTO7yDCoAzilna2kKMDy5UD79hLoqlkTOHQImDhRexXHJz1eW2zAAJniuGwZ0L8/YG8vdbX27AGmTAGOHNG0vXEDOHpUri4VFTO7iIiIiIhyq1MHaNhQbj96JBefjx8H3niDgS6icoaZXWQY1AGc0sxWevBApiVu3Cj3+/UDVq8ufHaZSgXUry/bO+9Ira+TJ4HffpOtc2dN2/XrgalTJaW6QweZutm5M9CqlVx9KghjY6B6daBGjcL1k4iIiIioPFFfuPbzk5Xd33xTyo+YmQFz5gDvvVe6C2ARUalhsIsMQ2lndp05I9MLz56VD8D58+XDUBdXfIyMAC8v2SZO1H4sPR2wtQWSkoDdu2UDpHBmu3bAd989O+A3cWLu4xIRERERVSTp6cBbbwFr1gAffwwkJsr+Zs2AdevkJxGVW5zGSIahNKfmrV8PtG4tga5q1ST7avLk0kltnjEDuHNHVoZZvBh46SWpB5aaKtMnHRw0bT//XLLAdu2SAptERERERCQXyrt0kUAXoAl0ffCBlBBhoIuo3GNmFxmG0ii6npkJTJoELF0q97t3BzZsAJycSu4182JsDDRvLtu778q0x7NngYsXJeVabdUq2T9/vgTimjUDOnaUzc8PsLIq3X4TEREREenb0aNSfkT9/QGQxaDWrJEyIURUITCzi8q+7GypV2VsXHKZXffvy4fi0qUSOJoxQwrIl3agKy9GRkDjxoC/v2afogD/+Q8wYoQU2lQUKa65dCkQEAD06KHJhiMiIiIiqgjWrweee0470DVunIyTGegiqlCY2UVln5ERcPUqkJX19BUQi+rGDaBPH/kQtLSUbK6XXtL96+iSSgUMHy4bIB/of/4JHDggP11dARcXffaQiIiIiKj0JCcDgYGyyiIAuLsDa9cCXbvqt19EpBcMdpHhKImVUiIjJdAVEyNZXDt2AG3a6P51SpqrKzBggGxERERERBXJoUNyEfj2bbk/ejSwaJGscE5EFRKnMVLFtXOn1LeKiQEaNQL+/tswA11ERERERBXRxYuAr69MUbx4EXBzk1IkK1cy0EVUwTHYRWXf999LUOrTT3V3zKVLpUZXSooUoj94EPD01N3xiYiIiIio5KxaBTRsCPz8s9SvHTYMOHVKgl9EVOEx2EVl39mzUofq8uXiHysrS1Y4HD9eCt+PGgXs2gXY2RX/2EREREREVLKSk6UMyejRMrY3MQFWr5bVFjmmJ6J/sWYXlX3qVQWrVSvecdLTgUGDgO3b5X5QEPDBB1LsnYiIiIiIyrbdu4HBg4G7d+V+tWrA4cNAjRr67RcRlTnM7KKyT710sKtr0Y/x8CHw8ssS6DI3BzZvBqZMYaCLiIiIiKisS0wEhg4FevfWBLp69ACuXGGgi4jyxGAXlX3qzK6iBrtSU4EXX5TpipaWUph+4EDd9Y+IiIiIiHRPUaR+b6NGwLp1mv0ffADs3QuYmemvb0RUpnEaI5V96syuokxjTEkB+vYFfv0VsLKSQFeXLjrtHhERERER6Vh0NDB2rFywBqQYfevWQOfOwMiReu0aEZV9DHZR2ZaVBcTGyu3CZnbdvy+pzn/+KUsP79olyxITEREREVHZlJkJBAcDM2bIDA1TU+DDD6UEibm5vntHRAaCwS4q25KSJMiVkAA4ORX8effuAb16AX/9BdjaAnv2AG3bllg3iYiIiIiomI4cAd58Ezh+XO5bWACNGwP/+Q8DXURUKKzZRWWbvT1w44Zc1TEpYGw2MVEKVv71F1ClChAWxkAXERGVScuWLYOnpycsLCzg4+ODI0eOPLX9li1b0KBBA1hYWKBp06bYpZ7e869t27ahZ8+eqFq1KlQqFaKiovI9lqIo6NWrF1QqFUJCQrQeu3btGvz8/FCpUiU4OTnh/fffR2ZmZlHfJhHR0yUnAxMmyJj9+HHAxgaws5NFpu7cAW7f1ncPicjAMNhFhsGogP9UExKA558HwsMBBwep1dWyZcn2jYiIqAg2b96MwMBAzJgxAxEREfDy8oKvry/i4+PzbH/o0CEMGjQIo0aNQmRkJPz9/eHv749Tp07ltElJSUGHDh2wYMGCZ75+cHAwVHmsSpyVlQU/Pz9kZGTg0KFDWLt2LdasWYPp06cX/c0SEeVFUYAtW6QA/ZIlcr9XL8DYWGZqNG4sJUm44iIRFZJKURRF350oDcnJybC1tUVSUhJsbGz03R0qCYmJUnz+5EnA2Rn45RegSRN994qIiMqx4owvfHx80Lp1ayxduhQAkJ2dDXd3d4wfPx5TpkzJ1T4gIAApKSnYuXNnzr62bdvC29sbK1as0GobHR2NmjVrIjIyEt7e3rmOFRUVhT59+iA8PByurq7Yvn07/P39AQC7d+9Gnz59EBMTA2dnZwDAihUr8MEHH+D27dswK8DqZxx3EdEznTkDjB8P7N8v92vXlimMs2fLIlM+PlJz195ev/0kojKloGMMZnZR2bZsGdCxI7By5dPbpaQAffpIoMvFBfjtNwa6iIiozMrIyMCxY8fQvXv3nH1GRkbo3r07Dh8+nOdzDh8+rNUeAHx9ffNtn5/U1FS89tprWLZsGVxcXPJ8naZNm+YEutSvk5ycjNOnT+d5zPT0dCQnJ2ttRER5Sk4G3nsP8PKSQJeFBTBzJjB/PvDxxzKu795dLlwz0EVERcRgF5VtJ09K6vLNm/m3SU8HXn4ZOHxYanTt2wc0aFB6fSQiIiqkhIQEZGVlaQWUAMDZ2Rmx6lWInxAbG1uo9vmZNGkS2rdvj379+hXqddSP5SUoKAi2trY5m7u7e6H6REQVgKIA69cD9esDn38uqy726ycZXjNmyFTGypVlXL9zp9wmIiqiIgW7SruYamJiIsaPH4/69evD0tISNWrUwIQJE5CUlFSU7pMhiYmRn9Wq5f14VhYwZAjw889ApUqS6syMLiIiojyFhoZi//79CA4O1ulxp06diqSkpJzt+vXrOj0+ERm448eBTp1k3B4bC9SpA3z3HdCtm2bF9UaNgL//BjZv5sqLRFRshQ526aOYakxMDGJiYrBw4UKcOnUKa9aswZ49ezBq1KjCdp8Mza1b8tPVNfdjigK8/bYUtTQ1BUJCuOoiEREZBAcHBxgbGyMuLk5rf1xcXJ5TCwHAxcWlUO3zsn//fly+fBl2dnYwMTGByb8rHffv3x9dunR56uuoH8uLubk5bGxstDYiIsTHA++8A7RoIbM1LCyk9IijIzB0KDBxolysVqtTp+ArsBMRPUWhg12ff/45Ro8ejREjRqBRo0ZYsWIFKlWqhG+//TbP9l988QVeeOEFvP/++2jYsCHmzJmDFi1a5BRjBYAhQ4Zg+vTpuepQqDVp0gQ//PAD+vbti9q1a6Nbt2745JNPsGPHjnyXwWbtiHJCHezKK7Nr2jTg669lpcaNG4EePUq3b0REREVkZmaGli1bIiwsLGdfdnY2wsLC0K5duzyf065dO632ALBv37582+dlypQpOHHiBKKionI2AFi8eDFWr16d8zonT57UupC5b98+2NjYoFGjRgV+LSKqwB4+BD79FKhbF1i+HMjOlpXSHz6UKYrqWoPPPcfpikRUIgoVNlcXU506dWrOvoIUUw0MDNTa5+vri5CQkML39jHqyvsm+UT+g4KCMGvWrGK9BulZVpakOQO5M7s++0yKWALAV18Br7xSun0jIiIqpsDAQAwbNgytWrVCmzZtEBwcjJSUFIwYMQIAMHToULi5uSEoKAgAMHHiRHTu3BmLFi2Cn58fNm3ahPDwcKx8bBGXxMREXLt2DTH/lgE4f/48AMnIenx7Uo0aNVCzZk0AQM+ePdGoUSMMGTIEn376KWJjY/HRRx9h7NixMOfUIiJ6GkUBtm4F/vMfIDpa9jVqJHW5EhLkfvv2wMCBQP/+QPXqeusqEZVvhcrs0mcx1Sf7MWfOHLz55pv5tmHtiHIgIUECXioV8Pi/oVWr5AMUABYsAN54Qz/9IyIiKoaAgAAsXLgQ06dPh7e3N6KiorBnz56ccdO1a9dwS53hDKB9+/bYuHEjVq5cCS8vL2zduhUhISFo8litytDQUDRv3hx+fn4AgFdffRXNmzfHihUrCtwvY2Nj7Ny5E8bGxmjXrh1ef/11DB06FLNnz9bROyeicunQIQlsDRwoga5q1YC1a2XBqTffBBYvBq5fBw4elOmLDHQRUQkyuAnRycnJ8PPzQ6NGjTBz5sx825mbm/Pqo6G7d08+BBVFM3f/hx+AMWPk9gcfaIJeREREBmjcuHEYN25cno/99ttvufYNGDAAAwYMyPd4w4cPx/DhwwvVB0VRcu3z8PDItaAQEVEuiiLTEidPBi5c0Ow3NpZi8+qA1ldf6ad/RFRhFSqzS1/FVNXu37+PF154AdbW1ti+fTtMTU0LfQwyIPXry9UfdVber78Cr70mc/5Hjwb+ndZBRERERESl7OuvZSXFF1/UBLosLICRI6Uml5ubfvtHRBVaoYJd+iqmCkhGV8+ePWFmZobQ0FBYWFgU6vlkwFQqWa7Y3x/IyJD5/cuXy34iIiIiIip5mZkyFn/wAJgzBxg/XlOHy8kJWLIEuH8f+OYboHVrjtWJSK8KPY1RH8VU1YGu1NRUrF+/Xmt1RUdHRxgbGxfvLFDZdvUq0KsXkJwMdO4MrF8vqdFERERERFSyLl+WANbatUDXrsC+fYB6tVZ3dyA4GHjpJQa3iKhMKXSwKyAgALdv38b06dMRGxsLb2/vXMVUjYw0CWPqYqofffQRpk2bhrp16+ZZTFUdLAOkmCoAzJgxAzNnzkRERAT+/vtvAECdOnW0+nPlyhV4enoW9m2QIZgxA9i7V6Yx3roFNGkChIRIejQREREREZWMzExgxw5gxQrg5581+zdskJ916gBz5wIDBgBGhZosRERUKlRKXlVJy6Hk5GTY2toiKSkJNjY2+u4OFUSfPsBPP8nt6tVl7j9XbSEiojKE44u88bwQGShFkSmKK1cCN2/mftzZGZg5Exg1CmD9ZCLSg4KOMQxuNUaqIDIzZVliALCykgwvBrqIiIiIiHRLUTRTEFUq4MABCXQZGwNZWbLfxkZWQp84UcbmRERlHHNOqexRFGDsWODePbm/eDHQqJFeu0REREREVK48eAB8+SXQrJmUDFEUmbp49ao8npUFWFsDH38MREcD06Yx0EVEBoOZXVT2qFOn1Xr10l9fiIiIiIjKk6tXgWXLgK+/1lxc/uAD4OxZIDxc7leuDEyYAAQGAlWr6q2rRERFxWAXlS2rVklhejWVSmoDEBERERFR0SgKcOiQrJy4bRuQnS37XV0BMzNg3Tq5X6kSMH48MHky4OCgt+4SERUXg11UdvzwAzBmjNx+4w0JfDk6svglEREREVFx3LsHdO8OPHwo9xs3Bu7fB65dk/uWllJG5P33AScnvXWTiEhXWLOLyoaffgJefVWuMo0aBQwfDri7Ax4e+u4ZEREREZFhSU0Ftm7V3K9SBRg5EujQQRZ9On1aAl02NsDUqVKT67PPGOgionKDmV2kf7/8AvTvLyswDhoEfPWVrP5y7ZqkXBMRERER0bPduQMsXQosWSK3jx4FGjaUGRM//iirLAJSh2vSJMnmsrPTa5eJiEoCg12kX3/8Abz4IpCeDrz0ErB2rQS61NTLIBMRERERUd6uXQM+/1yKzqemyj4PD1nVfO9eCXwBQLVqUo/rzTe5siIRlWsMdpH+/P034OcHpKUBvXsDmzaxPhcRERERUUHduSMrJm7cKLMkAKBBA8DFBTh4UPYDQK1asuLisGGAubn++ktEVEpYs4v0IzISeOEF4MEDoFs3qSlgZqZ5/J13gOeekytRRERERESUW+XKwP79Eujy9gZatQLOnQN++w149Aho2xbYsgW4cEGyuRjoIqIKgsEuKn2nTwM9esiqMM89B4SGygowjzt2TJZHTkvTSxeJiIiIiMqcM2eAd9/VZHEpCjBwIFC3LhAVBYSHSxmQl1+WzK7Dh4FXXtEuE0JEVAFwGiOVrgsXgOefl5Tr1q2BXbvyrhdw65b8rFatdPtHRERERFTWnDwJzJkjsyEUBahRA4iLA775RlOPq1IlWXHx3XeB2rX12l0iIn1jsItKz8WLEuiKiwOaNQP27JHljp+Una0Jdrm6lm4fiYiIiIjKijNngOnTgR9+0OxzcQHee09z390dePttYMwYwN6+9PtIRFQGMdhFpePIESlGn5Agyx/v25f/h/GdO5rUbBeX0usjEREREVFZkJYGvPUWsH69XAhWqSRzKyUFiI2VNj16AGPHyhjbhF/riKj0PXoExMRIFaJffwX++Qdwc5N1Mxo00G/f+FeRSt6uXcCAAbIMcsuWwE8/AU5O+bePiZGfTk5cnZGIiIiIKh5TU/n2mJ0NGBnJz5QUwM4OGDFCAmH16um7l0RUjsXHA3/9JSW3L14EoqNlAtadO8D9+4CFBZCUJDOrn/T88wx2UXm3Zg3wxhtAVhbg6yt1BipXfvpzOIWRiIiIiCqSe/eAxYuBXr2A7duBdes0Y+LsbKB5c8niGjRIMryIiIpIUSRwdeyYJpB19aokjTo4SFz9xg3g7t2nH+fhQ/lpairPS00FqlQB2rUD6tQp8bfxTAx2UclQFGDePOCjj+T+kCFSQLMgmVqPHknRTQ+Pku0jEREREZE+paUBCxYAn30m3xRnz9Y8VrUqMHgwMHw44O0tUxmJiJ5CUYArV4CICODUKQlk2dkB6ekSwDpzBrh+Pf/nX7qUe5+5OWBtLX+SXF3lq3rt2kD79lKK28FBElDLGga7SPeysoAJE4Avv5T7H3wABAUV/AO6b1/ZiIiIiIjKo4QEYNo0yeBSp0cA8o2xTx8JcPn5AWZmeusiEZUtiiIBq2PHJD/kwQO5Hx4OHDgg9x89KvjxVCoJZNnYSMCqWjWgQwegbVtZ96J69bzXkzMUDHaRbj18KFegtm2T/z1ffAGMH6/vXhERERER6Vd8PBASAnz9tXw7fVz16sC77wKvvw44O+ujd0SkZ2lpUr76+nX5E/HTT3JfXSMrI6Pgx1KppKaWjQ3g5QU895wEsBwdZX/z5pKpVZ4x2EW6c+cO8NJLElY2M5PVYwYM0HeviIiIiIj0459/ZLGmH34A/vhD6m+pGRkBXbsC8+fLIk6cpkhUbmVmAufOAb/8Apw9K1MNb96UJM/kZJlmmFeh97yoVLKWm5eXBLAcHIDERKB+fdlXEQJZBcFgF+nGb7/JlaibNyV8/OOPQJcuRTtW//5SkHPxYsDHR5e9JCIiIiIqOXfvAvv3A/v2yfbPP9qPt2wJ9Oghc48WLXr6CuVEZBDS0oDjx4GoKAlkXb4s/8Xj42VtttRU+Xr7eKw7PxYWEsBycgJu35aphTVrSiCrWTMJZDk7MzZeEAx2UfFkZgKzZgGffCKh6Pr1ZcXFJk2KfszwcODaNd31kYiIiIioJDx8CPz9tya4FR6eO3tLpQIaNgRCQ+VbKxEZjPR0KfQeFSXF3S9f1iyIev26FHSPjS3YsUxM5M9B5cqAvb0Ue/fwAOrVA5o2lVi4uzsDWbrCYBcVXXS01Oc6dEjujxolNbqsrIp+TEXRLLPs6lrsLhIRERER6URWlnzbPXoUOHJEfp44IRd/H9eggQS3IiKAq1dln7GxzDUiojIjI0MCWcePS1ArK0sCWGfOyMSl1FTZV1AmJhIIq1IFcHGRVQvbtAE6dZIglrNz2Vy1sLxisIuKZssWYPRoIClJpi2uXAkEBBT/uHfuaJaQcHEp/vGIiIjKsGXLluGzzz5DbGwsvLy8sGTJErRp0ybf9lu2bMHHH3+M6Oho1K1bFwsWLEDv3r1zHt+2bRtWrFiBY8eOITExEZGRkfD29tY6xpgxY/DLL78gJiYGlStXRvv27bFgwQI0aNAgp01YWBg+/vhjnDx5ElZWVhg2bBg++eQTmJhw6EgVxL17wPnzsp04IYGtY8eAlJTcbZ2dgW7dZHpikybA558DmzbJY/b2wLx5wBtvSMCLiEpFWpoEru7elUo7p09LpZ34ePnvXdhAlrExYGkpgazGjYHu3WVdCTc3wNoaaNQIMDUtsbdDRcARCxVOSoqsFLNqldxv2xbYuFF3KdnqrC4HBy61TERE5drmzZsRGBiIFStWwMfHB8HBwfD19cX58+fhlEcdn0OHDmHQoEEICgpCnz59sHHjRvj7+yMiIgJN/i0fkJKSgg4dOmDgwIEYPXp0nq/bsmVLDB48GDVq1EBiYiJmzpyJnj174sqVKzA2Nsbx48fRu3dvfPjhh/juu+9w8+ZNvPXWW8jKysLChQtL9JwQlRpFkW+8N29KpWh1YEu9xcfn/bzKlYFWrYDWrSVlo00bzbyjP/+UgvMpKZK+MWYMMGcOK0UT6VhqqvzXPX8e2LlTEigfL/aellaw+lhqRkaSZ9GmjQSwqlWTelmNGknB96ZNpZYWGRaVohS05r9hS05Ohq2tLZKSkmBjY6Pv7himw4eBkSNlGQmVCpg6FZg5U7ch7L17gRdekOp7x4/r7rhEREQloDjjCx8fH7Ru3RpLly4FAGRnZ8Pd3R3jx4/HlClTcrUPCAhASkoKdu7cmbOvbdu28Pb2xooVK7TaRkdHo2bNmnlmdj3pxIkT8PLywqVLl1C7dm1MmzYN+/btw9GjR3Pa7NixAwMHDkR8fDysra2f+d5KfNylKHJJ/mnfZlQqzXwRRdFPW0A7m+dZaQT6aquuK6XPPhS1rbrv2dky4+DuXQliJSVpfsbHAzExclE1Jka2mzdl3tLTVKsm9WgbNNAEuOrXz52hpe5DWpp8O65WDVi6VCpJE1GBZWZK6eY//pBA1pUrkp0VFyf/nR88kP9qDx8W7HgqlWReqQNY0dFyu04dmWnMQJZhKugYg5ld9Gz//ANMmSJTFwGppbV+vaRr6xrrdRERUQWQkZGBY8eOYerUqTn7jIyM0L17dxw+fDjP5xw+fBiBgYFa+3x9fRESElLkfqSkpGD16tWoWbMm3N3dAQDp6emweGLkb2lpiYcPH+LYsWPoksdqy+np6Uh/LHCQnJxc5D4VyKlTcmGMdM/CQoI3xsZPn+djYiLfEk1MZDt9WlIq8ms7cKAc18gI+OUXCTjlRaUChgyR4FV2tnzrvXEj//66uck34ORkCT7qypkz8m0YAN57T2rT5ufsWQmIWVpKf6tXZ4Vposc8fCh/Is6cAS5ckK+X6tUKExMldyIzU+4X9L+xlZUEsBISZGqhs7P816tdW2LO3t7yX5iz7ysu/uopf3fvyiqLS5ZI9T6VChgxApg/H3B0LLnX9fAAPD1L7vhERER6lpCQgKysLDg7O2vtd3Z2xrlz5/J8TmxsbJ7tYwu6DNRjvvzyS/znP/9BSkoK6tevj3379sHs3/IBvr6+CA4Oxv/+9z8MHDgQsbGxmD17NgDglvqi1BOCgoIwa9asQveDyqCCpkxkZgKRkQVvu3FjwdoqCvDddwVrC0iGVkHNnSvLnlWrBixbBvzvf/m3rVy54Md93L9BY6LyLjtbU8z94kUJYF27JrkLt29LRRojI1mp8M6dgh9XnThpYSGloR0cNKsW1q4NtGgh0w1tbBhTpqdjsItyy8gAli8HZs+WUDsgBTcXLiz5q6jDh8tGREREJWbw4MHo0aMHbt26hYULF2LgwIE4ePAgLCws0LNnT3z22Wd46623MGTIEJibm+Pjjz/GgQMHYJTPMlJTp07VyjpLTk7OyRQrEQ0bSgrA0zLIzMw0K0Srp7jlx9RUE9xQ13LSRVsTE6lcrHb3bv5tjY3l25vavXv5pzg82TYpKf/plM9qq54SmpUlt62tNffv3ZNxYVaWLCCUmSm3MzNls7SU/VlZ8rvIyJD96n3qdtnZ0ladrZWWJm2ys6WdOuNLvVlZaW6np8t5NDfPvVlYyDdhGxvAzk7e69OWOrOz0zzu7S1TDfNja6u5PWcO8OGHBWtLZMAePQIuXZLsq8uXpRbWjRsyjfDOHfmzamIi92NjC1fgHZD/fhYW8mfG3l6ysdzdZTrh889LUMvRkSsWkm4w2EUaigJs3w588IH8lQNkqYmFCwFfX4bOiYiIdMTBwQHGxsaIi4vT2h8XFweXfFYjdnFxKVT7p7G1tYWtrS3q1q2Ltm3bokqVKti+fTsGDRoEAAgMDMSkSZNw69YtVKlSBdHR0Zg6dSpq1aqV5/HMzc1hbm5e6H4UmYmJfCMqTKa5g0PB2xamoHhh2trbG1bb8szKShMMfZZKlWQjMjDp6RKUOnpUsq6uX5dkyPh4CV7duydxY1NTzZTCojA1lXi2jY38SXR2llnOvr4SwHJxkZgwVyuk0sRgF8lVxvXrgZUrpQYGIH+h5syRaYuc6ExERKRTZmZmaNmyJcLCwuDv7w9ACtSHhYVh3LhxeT6nXbt2CAsLw7vvvpuzb9++fWjXrl2x+qIoChRF0aq5BQAqlQrVqlUDAPzvf/+Du7s7WrRoUazXIiKiwnv0SJIyU1MlSHXjBrBnj2RYJSTI17mkJClfl5YmGVhZWcD9+0V7PZVKE8CytpaaWI6OklTbq5d8VXRxkRgw4+dUVjGKUVEpiiyP/PXXUnheXZ+hUiUpwvn++9pp96WlY0dJd1+7VmoqEBERlVOBgYEYNmwYWrVqhTZt2iA4OBgpKSkYMWIEAGDo0KFwc3NDUFAQAGDixIno3LkzFi1aBD8/P2zatAnh4eFYuXJlzjETExNx7do1xPxb/Pv8+fMAJCvMxcUF//zzDzZv3oyePXvC0dERN27cwPz582FpaYnevXvnHOezzz7DCy+8ACMjI2zbtg3z58/H999/D+MnV6EjIqICURQJVEVHS4ZVTIzkFNjYSLDq5k1g506ZEawOWqlnBhd27YXUVM1t9ZRAExOZQli5smRZVa0KODlJMfdu3TTJstbWTGSk8oHBrormzh0p+rlyJfB4AdxmzYA33wQGD5Z6BvqgKMCRI/JXvTSnQhAREelBQEAAbt++jenTpyM2Nhbe3t7Ys2dPThH6a9euadXIat++PTZu3IiPPvoI06ZNQ926dRESEoImTZrktAkNDc0JlgHAq6++CgCYMWMGZs6cCQsLCxw4cADBwcG4e/cunJ2d0alTJxw6dAhOTk45z9u9ezc++eQTpKenw8vLCz/++CN69epV0qeEiKjMys6WTKnbt4Hjx2V6YHy8ZFbduaPJrqpSRbKdkpIk8+r48aIFrPJiaipBKnt7KQRvZaUpWVe1qmRbVasG1K8PtGols7dtbVkDiyomlaLoco3esis5ORm2trZISkqCzeNFOnUlMVHySe3t8/9rYm8v4XRAwu1PK2hapYrkjQIS1n9aQVNbW03NgYcPtSdbZ2XJOq8HDwKHDgEHDkgeLCAh+xdfBF5/XYp0PlmTy9pak92VkSF/yfNTubKm+OmjR/IpkB8rK00hz6ws+RQA5Hw0bqx5Hwx4ERFRGVfi4wsDxfNCRPqmKJIldfu2fI2Jj5fbiYmyqTOc7t+XwNUff0hGVWqqfBVJT9esy2BiIrd19c1ZpZJj2ttLZlWVKtKX8+claOXoqAlcVa8uKxF6eEhQi2WUqaIr6BiDmV26EhICjBr19DahoUDfvnL7hx+AoUPzb/u//wH/Xo3Frl3AK6/k33bVKs1rh4UBffo8vR8tWkgWl4eHTLretCnvdkFBwJQpcvvkSbk8kJ+PPpIaX4As3dGwYf5tAwOBRYvkdkwMUKOG9uNVqzLQRURERERUDj16pAkkqa/TX74smVD372u2Bw9kc3aWYFBqqnx1+PtveZ46IJWRIcd69EizkGdKimy6kpGhuW1iItfrTUwk08rcXHIUKlWSa/916gA+PhKYsraWQJqLiyZo5ewsC4cSUclisEtXEhLkL15mZt6Pq1SyvPHp07IkxZkzTy/8/njIXh36f5L60sKOHZK5dfWqTAPM73gqlay0OG+e7Pvzz6f34ckMtdJoq1IBQ4bk/1wiIiIiIoKiSNBFvWVmypaaKsGi9HTZ1IEh9ebgIAGazEwJxFy6pN1O/bz0dKB2bQk0ZWRInanISLn9eIApM1N+urtLsCc9Xb4aXbkiU//UW2nMJ0pLy/8xlUq+hqiDVO7uQJMmkuFlairX9tVTAtXTAh0cpK5VzZpArVqSfWVhwewqIkPAaYy69OiR1MGKjJQtIgKIipL82acxNZVwv4uLXBZQlNyfDOrbCQlSvTArK//jWVtLofeuXYEuXYDmzXn5gIiIqARwul7eSvq8XL4MvPaadvnRJzk4AG5ucvvRI7nOmB97e/niC8gQS704dV7s7CQ7A5Ah2okT+be1sZEvyWonT8pwLi+VK0tgQe306fyvoVaqBNStq7l/5oymSsWTLCykfo/auXMSjMiLmZl2cv6FC/kHD0xNZfqV2qVL+WfSGBsDTZtq7v/zT/7DY5UK8PLS3L9y5elD6WbNNMPc6OinV/5o0kRzjfX6damzBOQdhGnQQM4HINlE6moeebWtVUvaKopMk7tzR7ud+raiyDVvMzP5d5CUJFU8FEW7jfpn5cry3rKz5feQ3+/NkKlUcj4yMiQQZWQk79nYWBOUqlVL/g1XqiTn4tQp+cpkZSXnqHJl+fpjayvtGjaUfeqAnqOjtGeAiqh8KOgYg8GukpadLZ/SERFSnfD6dakmqN7Un7KFZWYm0/88PTWTuD095ZO5efOnZ1YRERGRTjDYlbeSPi8nT0qQg4gKTj3Ro2pVCQyZmEgmV1ycdpDp8WBT/foSNDY1lWDmxYvyNUS9WVhIUMncXIKfnp6aINONGxJ0srLSlOy1sZGf9vaaPjAIRUSFwZpdZYWRkVymq10bGDAg9+MZGfIJow5+PX5Zw8hIk2+rvq2+nOjiwmU1iIiIqEKqUQNYt06uI+bH2VmTVZWRIdcd8+PoqMmqyswEwsPzb2tvD9SrJ7cVReoH5cfOTq5Dqv39d/5TuWxstDOlwsPzz+yqXFmylNQiIrRrCj3O0lI7UyoqSgIceTE3l2umaidOyJS4vJiYaJdzPXVK6is9SVEkcNK6tWbf2bOS1aR+/Elt22puX7igvfbSk1q31gyJL116+nXkli0laANIdll8vOaxJwMuLVpoSshGR8t0P3WbJ6uNeHtLMEelkuvaN25oAkvqNurhfPPmEuRRqSRj7MYNTaDJxEQ70NSggaYg+b17kl1mZibvQf3T3Fx+OjlJH9TXu9XnnV8XiKiiYmYXERERURFxfJE3nhciIiIqCQUdYzDWT0RERERERERE5QaDXUREREREREREVG4w2EVEREREREREROUGg11ERERERERERFRuMNhFRERERERERETlBoNdRERERERERERUbpjouwOlRVEUALJMJREREZEuqMcV6nEGCY67iIiIqCQUdOxVYYJd9+/fBwC4u7vruSdERERU3ty/fx+2trb67kaZwXEXERERlaRnjb1USgW5FJmdnY2YmBhYW1tDpVKVyGskJyfD3d0d169fh42NTYm8RnnHc1h8PIfFx3OoGzyPxcdzWHwlfQ4VRcH9+/dRrVo1GBmxOoQax12Ggeew+HgOdYPnsfh4DouP57D4SuMcFnTsVWEyu4yMjFC9evVSeS0bGxv+5ygmnsPi4zksPp5D3eB5LD6ew+IryXPIjK7cOO4yLDyHxcdzqBs8j8XHc1h8PIfFV9LnsCBjL16CJCIiIiIiIiKicoPBLiIiIiIiIiIiKjcY7NIhc3NzzJgxA+bm5vruisHiOSw+nsPi4znUDZ7H4uM5LD6ew/KLv9vi4zksPp5D3eB5LD6ew+LjOSy+snQOK0yBeiIiIiIiIiIiKv+Y2UVEREREREREROUGg11ERERERERERFRuMNhFRERERERERETlBoNdRERERERERERUbjDYpSPLli2Dp6cnLCws4OPjgyNHjui7Swbljz/+QN++fVGtWjWoVCqEhITou0sGJygoCK1bt4a1tTWcnJzg7++P8+fP67tbBmX58uVo1qwZbGxsYGNjg3bt2mH37t367pZBmz9/PlQqFd599119d8VgzJw5EyqVSmtr0KCBvrtlkG7evInXX38dVatWhaWlJZo2bYrw8HB9d4t0gOOu4uG4q/g47io+jrt0j+OuouHYSzfK2riLwS4d2Lx5MwIDAzFjxgxERETAy8sLvr6+iI+P13fXDEZKSgq8vLywbNkyfXfFYP3+++8YO3Ys/vrrL+zbtw+PHj1Cz549kZKSou+uGYzq1atj/vz5OHbsGMLDw9GtWzf069cPp0+f1nfXDNLRo0fx1VdfoVmzZvruisFp3Lgxbt26lbP9+eef+u6Swbl79y6ee+45mJqaYvfu3Thz5gwWLVqEKlWq6LtrVEwcdxUfx13Fx3FX8XHcpVscdxUPx17FUxbHXSpFURS9vXo54ePjg9atW2Pp0qUAgOzsbLi7u2P8+PGYMmWKnntneFQqFbZv3w5/f399d8Wg3b59G05OTvj999/RqVMnfXfHYNnb2+Ozzz7DqFGj9N0Vg/LgwQO0aNECX375JebOnQtvb28EBwfru1sGYebMmQgJCUFUVJS+u2LQpkyZgoMHD+LAgQP67grpGMddusVxl25w3KUbHHcVDcddxcOxV/GVxXEXM7uKKSMjA8eOHUP37t1z9hkZGaF79+44fPiwHntGFV1SUhIAGTRQ4WVlZWHTpk1ISUlBu3bt9N0dgzN27Fj4+flp/W2kgrt48SKqVauGWrVqYfDgwbh27Zq+u2RwQkND0apVKwwYMABOTk5o3rw5vv76a313i4qJ4y4qqzjuKh6Ou4qH467i49ireMriuIvBrmJKSEhAVlYWnJ2dtfY7OzsjNjZWT72iii47OxvvvvsunnvuOTRp0kTf3TEoJ0+eROXKlWFubo633noL27dvR6NGjfTdLYOyadMmREREICgoSN9dMUg+Pj5Ys2YN9uzZg+XLl+PKlSvo2LEj7t+/r++uGZR//vkHy5cvR926dbF37168/fbbmDBhAtauXavvrlExcNxFZRHHXUXHcVfxcdxVfBx7FV9ZHHeZ6O2ViajEjB07FqdOneJc8yKoX78+oqKikJSUhK1bt2LYsGH4/fffOfAqoOvXr2PixInYt28fLCws9N0dg9SrV6+c282aNYOPjw88PDzw/fffc1pHIWRnZ6NVq1aYN28eAKB58+Y4deoUVqxYgWHDhum5d0RUnnDcVXQcdxUPx126wbFX8ZXFcRczu4rJwcEBxsbGiIuL09ofFxcHFxcXPfWKKrJx48Zh586d+PXXX1G9enV9d8fgmJmZoU6dOmjZsiWCgoLg5eWFL774Qt/dMhjHjh1DfHw8WrRoARMTE5iYmOD333/Hf//7X5iYmCArK0vfXTQ4dnZ2qFevHi5duqTvrhgUV1fXXF+WGjZsyGkJBo7jLiprOO4qHo67iofjrpLBsVfhlcVxF4NdxWRmZoaWLVsiLCwsZ192djbCwsI435xKlaIoGDduHLZv3479+/ejZs2a+u5SuZCdnY309HR9d8NgPP/88zh58iSioqJytlatWmHw4MGIioqCsbGxvrtocB48eIDLly/D1dVV310xKM899xzOnz+vte/ChQvw8PDQU49IFzjuorKC466SwXFX4XDcVTI49iq8sjju4jRGHQgMDMSwYcPQqlUrtGnTBsHBwUhJScGIESP03TWD8eDBA63I+ZUrVxAVFQV7e3vUqFFDjz0zHGPHjsXGjRvx448/wtraOqd2ia2tLSwtLfXcO8MwdepU9OrVCzVq1MD9+/exceNG/Pbbb9i7d6++u2YwrK2tc9UrsbKyQtWqVVnHpIAmT56Mvn37wsPDAzExMZgxYwaMjY0xaNAgfXfNoEyaNAnt27fHvHnzMHDgQBw5cgQrV67EypUr9d01KiaOu4qP467i47ir+DjuKj6Ou3SDY6/iK5PjLoV0YsmSJUqNGjUUMzMzpU2bNspff/2l7y4ZlF9//VUBkGsbNmyYvrtmMPI6fwCU1atX67trBmPkyJGKh4eHYmZmpjg6OirPP/+88vPPP+u7Wwavc+fOysSJE/XdDYMREBCguLq6KmZmZoqbm5sSEBCgXLp0Sd/dMkg7duxQmjRpopibmysNGjRQVq5cqe8ukY5w3FU8HHcVH8ddxcdxV8nguKvwOPbSjbI27lIpiqKUZnCNiIiIiIiIiIiopLBmFxERERERERERlRsMdhERERERERERUbnBYBcREREREREREZUbDHYREREREREREVG5wWAXERERERERERGVGwx2ERERERERERFRucFgFxERERERERERlRsMdhERERERERERUbnBYBcREREREREREZUbDHYREREREREREVG5wWAXERERERERERGVGwx2EenBmjVroFKpEB0drZfXV6lUmDlzpk6P2aVLF3Tp0kWnxyxrCvoePT09MXz48BLvT3kUHR0NlUqFNWvW6LsrRERUTnDcZZg47ip5HHdRecZgF1ERnDx5Eq+88go8PDxgYWEBNzc39OjRA0uWLNFqN2/ePISEhOinkyXgzJkzmDlzpt4Gi1Q0X375ZYUfxISGhqJFixawsLBAjRo1MGPGDGRmZuq7W0REVAAcd0XruytUCBV93LV582a8/vrrqFu3LlQqVbkPylLZxWAXUSEdOnQIrVq1wvHjxzF69GgsXboUb7zxBoyMjPDFF19otc1v0DVkyBCkpaXBw8OjlHqtG2fOnMGsWbPyHHT9/PPP+Pnnn0u/U2XQ+fPn8fXXX+u7Gzkq+qBr9+7d8Pf3h52dHZYsWQJ/f3/MnTsX48eP13fXiIjoGTju4rjrWTjuKluWL1+OH3/8Ee7u7qhSpYq+u0MVmIm+O0BkaD755BPY2tri6NGjsLOz03osPj6+QMcwNjaGsbFxCfROf8zMzPTdhTLD3Nxc312gx0yePBnNmjXDzz//DBMT+dizsbHBvHnzMHHiRDRo0EDPPSQiovxw3JU3jrs0OO4qW9atWwc3NzcYGRmhSZMm+u4OVWDM7CIqpMuXL6Nx48a5BlwA4OTklHNbpVIhJSUFa9euhUqlgkqlyqknkFftCE9PT/Tp0we//fYbWrVqBUtLSzRt2hS//fYbAGDbtm1o2rQpLCws0LJlS0RGRmq9dn51DYYPHw5PT8+nvqerV6/inXfeQf369WFpaYmqVatiwIABWv1bs2YNBgwYAADo2rVrzntS9y+v14+Pj8eoUaPg7OwMCwsLeHl5Ye3atVpt1LUCFi5ciJUrV6J27dowNzdH69atcfTo0af2GwASExMxefJkNG3aFJUrV4aNjQ169eqF48ePa7X77bffoFKp8P333+OTTz5B9erVYWFhgeeffx6XLl3KdVx1XywtLdGmTRscOHDgmX1Re7J2hPr3ffDgQQQGBsLR0RFWVlZ46aWXcPv27VzP7dOnD37++Wd4e3vDwsICjRo1wrZt27TazZw5EyqV6v/s3XlYVNUbB/DvsA2bgMomiCBuuCUFirinKJpL5m6WiGslpqKVmIm2aGoa5q6lVmqapv7KTFPTFsVUzHLFfUkF3Fhkh7m/P24zMMwMzDDAZeD7eZ77MNw5d+adOxfm8HLOezSeu+i15ePjg/Pnz+PXX39VvWelGU7epUsXtGjRAhcuXMDzzz8PW1tbeHp6YuHChRpt9XnfASA5ORmjRo2Co6MjnJycEBYWhuTkZK3Pf+nSJQwaNAi1atWCtbU1AgMD8f3335cY94ULF3DhwgWMHz9elegCgDfeeAOCIGDHjh36nwQiIqpw7Hex31US9rsqT78LALy8vGBmxjQDSY8ju4gM5O3tjdjYWJw7d67Y/1Z8/fXXGDt2LNq0aYPx48cDABo0aFDsY1+9ehUvv/wyJkyYgFdeeQWffPIJ+vbti9WrV2PmzJl44403AADz58/HkCFDEB8fXyYfJidPnsSxY8cwbNgw1K1bFzdv3sSqVavQpUsXXLhwAba2tujUqRPefPNNfPbZZ5g5cyaaNm0KAKqvRWVmZqJLly64evUqIiIiUL9+fWzfvh2jRo1CcnIyJk+erNZ+y5YtSEtLw4QJEyCTybBw4UIMGDAA169fh6Wlpc7Yr1+/jt27d2Pw4MGoX78+EhMTsWbNGnTu3BkXLlyAh4eHWvuPP/4YZmZmmD59OlJSUrBw4UKMGDECf/75p6rNF198gQkTJqBdu3aYMmUKrl+/jn79+qFWrVrw8vIq7WnGpEmTULNmTURHR+PmzZuIiYlBREQEtm3bptbuypUrGDp0KF577TWEhYVhw4YNGDx4MPbt24fu3bsb9JwxMTGYNGkS7O3t8e677wIA3NzcShX/kydP0LNnTwwYMABDhgzBjh078M4776Bly5bo1asXAP3fd0EQ8OKLL+KPP/7Aa6+9hqZNm2LXrl0ICwvTeN7z58+jffv28PT0xIwZM2BnZ4dvv/0W/fv3x3fffYeXXnpJZ8zKP04CAwPV9nt4eKBu3boaf7wQEVHlwn4X+12lxX5Xxfe7iCoVgYgM8vPPPwvm5uaCubm5EBwcLLz99tvC/v37hZycHI22dnZ2QlhYmMb+DRs2CACEGzduqPZ5e3sLAIRjx46p9u3fv18AINjY2Ai3bt1S7V+zZo0AQDh8+LBqX+fOnYXOnTtrPFdYWJjg7e2ttg+AEB0drfo+IyND47jY2FgBgPDVV1+p9m3fvl3jeXU9f0xMjABA2LRpk2pfTk6OEBwcLNjb2wupqamCIAjCjRs3BABC7dq1hcePH6va/u9//xMACD/88IPGcxWWlZUl5Ofnq+27ceOGIJfLhffff1+17/DhwwIAoWnTpkJ2drZq/9KlSwUAwtmzZ1Uxurq6Cv7+/mrt1q5dKwDQeo6L8vb2Vnvfle93SEiIoFAoVPunTp0qmJubC8nJyWrHAhC+++471b6UlBShTp06wrPPPqvaFx0dLWj7Fa7t2mrevLlecRenc+fOGtdDdna24O7uLgwcOFC1T9/3fffu3QIAYeHChap2eXl5QseOHQUAwoYNG1T7u3XrJrRs2VLIyspS7VMoFEK7du2ERo0aFRv3okWLBADC7du3Ne5r3bq10LZtW/1PAhERVTj2u9jvKgn7XZWn31VUWZwLotLi+EIiA3Xv3h2xsbHo168f/v77byxcuBChoaHw9PTUe3ivLs2aNUNwcLDq+6CgIABA165dUa9ePY39169fN+r5lGxsbFS3c3Nz8ejRIzRs2BBOTk44ffp0qR5z7969cHd3x/Dhw1X7LC0t8eabb+Lp06f49ddf1doPHTpUrYhlx44dAZT8GuVyueq/rPn5+Xj06BHs7e3RpEkTrbGHh4er1bko+jynTp1CUlISXnvtNbV2ymHfxhg/frzaEPiOHTsiPz8ft27dUmvn4eGh9l8zBwcHjBw5En/99RcSEhKMisEY9vb2eOWVV1TfW1lZoU2bNmrvkb7v+969e2FhYYHXX39d1c7c3FyjaPzjx4/xyy+/YMiQIUhLS8PDhw/x8OFDPHr0CKGhobhy5Qru3r2rM+bMzEwA2ut5WFtbq+4nIqLKif0u/bDfpYn9rorvdxFVJkx2EZVC69atsXPnTjx58gQnTpxAVFQU0tLSMGjQIFy4cKHUj1u4YwVA9SFfdAi3cv+TJ09K/VyFZWZmYvbs2fDy8oJcLoezszNcXFyQnJyMlJSUUj3mrVu30KhRI43h/srh90U7GkVfu7IDVtJrVCgU+PTTT9GoUSO12P/55x+tsZf0PMq4GjVqpNbO0tISvr6+xcZSEn1fY8OGDTXqQjRu3BgAJF1+vG7duhpx1axZUy1+fd/3W7duoU6dOrC3t1dr16RJE7Xvr169CkEQ8N5778HFxUVti46OBlB8gWLlHxTZ2dka92VlZan9wUFERJUT+10lY79LE/tdFd/vIqpMWLOLyAhWVlZo3bo1WrdujcaNGyM8PBzbt29XfRgYStdKQbr2C4Kgui2TydS+V8rPzy/xeSdNmoQNGzZgypQpCA4OhqOjI2QyGYYNGwaFQqFn9MbR5zVqM2/ePLz33nsYPXo0PvjgA9SqVQtmZmaYMmWK1thL+zxloSyfW1uRVEC/97u0pDh3yvdw+vTpCA0N1dqmYcOGOo+vU6cOAOD+/fsaf7zcv38fbdq0KaNIiYiovLHfVXbY7zIM+10Fiut3EVUmTHYRlRFlAez79++r9un6YCwPNWvW1Dr0vOh/8rTZsWMHwsLCsHjxYtW+rKwsjRVaDHk93t7e+Oeff6BQKNT+23Tp0iXV/WVhx44deP755/HFF1+o7U9OToazs7PBj6eM68qVK+jatatqf25uLm7cuIFWrVoZF7AelP9VK3y+L1++DACqFZ6U/51MTk5WW6FK2/tdkdehvu+7t7c3Dh06hKdPn6r9lzE+Pl7t8ZT/1bW0tERISIjB8fj7+wMQp0kUTmzdu3cP//77r6qIMRERmRb2u9Sx31V67HcVMLbfRVSZcBojkYEOHz6s9T8qe/fuBaA+HNjOzk7nkr5lrUGDBrh06ZLaksp///03jh49WuKx5ubmGq9p2bJlGv+tsrOzAwC9XtMLL7yAhIQEtRVv8vLysGzZMtjb26Nz584lPoY+tMW+ffv2UtcTCAwMhIuLC1avXo2cnBzV/o0bN1bYe3nv3j3s2rVL9X1qaiq++uor+Pv7w93dHUDBClO//fabqp1yyfWiKvI61Pd9f+GFF5CXl4dVq1ap2uXn52PZsmVqj+fq6oouXbpgzZo1an/QKBVdQryo5s2bw8/PD2vXrlW7nletWgWZTIZBgwaV6nUSEVHFYL+L/a7yxn5XAWP7XUSVCUd2ERlo0qRJyMjIwEsvvQQ/Pz/k5OTg2LFj2LZtG3x8fBAeHq5qGxAQgIMHD2LJkiXw8PBA/fr1VUVOy9ro0aOxZMkShIaGYsyYMUhKSsLq1avRvHlzpKamFntsnz598PXXX8PR0RHNmjVDbGwsDh48iNq1a6u18/f3h7m5ORYsWICUlBTI5XJ07doVrq6uGo85fvx4rFmzBqNGjUJcXBx8fHywY8cOHD16FDExMahRo0aZvO4+ffrg/fffR3h4ONq1a4ezZ89i8+bNpa7zYGlpiQ8//BATJkxA165dMXToUNy4cQMbNmwwunaEvho3bowxY8bg5MmTcHNzw/r165GYmIgNGzao2vTo0QP16tXDmDFj8NZbb8Hc3Bzr16+Hi4sLbt++rfZ4AQEBWLVqFT788EM0bNgQrq6uqv+eKv9jWVY1KfR93/v27Yv27dtjxowZuHnzJpo1a4adO3dqrfexYsUKdOjQAS1btsS4cePg6+uLxMRExMbG4t9//8Xff/9dbEyLFi1Cv3790KNHDwwbNgznzp3D8uXLMXbsWJ1LuBMRUeXAfhf7XeWN/S51xva7fvvtN1VS8MGDB0hPT8eHH34IAOjUqRM6depUJq+dqEQVufQjUVXw008/CaNHjxb8/PwEe3t7wcrKSmjYsKEwadIkITExUa3tpUuXhE6dOgk2NjYCANWyyLqWwO7du7fG8wEQJk6cqLZPuWz0okWL1PZv2rRJ8PX1FaysrAR/f39h//79ei2B/eTJEyE8PFxwdnYW7O3thdDQUOHSpUsaSzkLgiCsW7dO8PX1FczNzdWWw9a2BHdiYqLqca2srISWLVuqLW1c3GvRFqc2WVlZwrRp04Q6deoINjY2Qvv27YXY2FiNeJRLYG/fvl3r8xeNa+XKlUL9+vUFuVwuBAYGCr/99pvOZcaL0rUE9smTJ9XaKWMqvKS48jrYv3+/8MwzzwhyuVzw8/PTiFsQBCEuLk4ICgoSrKyshHr16glLlizRem0lJCQIvXv3FmrUqKGxjLezs7PQtm3bEl9T586dhebNm2vs13Z96fO+C4IgPHr0SHj11VcFBwcHwdHRUXj11VeFv/76S+v7ce3aNWHkyJGCu7u7YGlpKXh6egp9+vQRduzYUWLsgiAIu3btEvz9/QW5XC7UrVtXmDVrltZl64mIqHJhv4v9rpKw31W5+l3R0dECAK1bSdcXUVmSCUIFVAckIiK9+Pj4oEWLFtizZ0+5P9eFCxfQvHlz7NmzB7179y735yMiIiKqTNjvIqq6WLOLiKiaOnz4MIKDg9nhIiIiIipn7HcRVSyO7CIiqkQq8j+MRERERNUZ+11EVRdHdhERERERERERUZXBkV1ERERERERERFRlcGQXERERERERERFVGRZSB1BRFAoF7t27hxo1akAmk0kdDhEREVUBgiAgLS0NHh4eMDPj/xCV2O8iIiKi8qBv36vaJLvu3bsHLy8vqcMgIiKiKujOnTuoW7eu1GFUGux3ERERUXkqqe9VbZJdNWrUACCeEAcHB4mjISIioqogNTUVXl5eqn4GidjvIiIiovKgb9+r2iS7lEPoHRwc2OkiIiKiMsWpeurY7yIiIqLyVFLfi8UliIiIiIiIiIioymCyi4iIiIiIiIiIqgwmu4iIiIiIiIiIqMqQJNn122+/oW/fvvDw8IBMJsPu3btLPObIkSN47rnnIJfL0bBhQ2zcuLHc4yQiIiIiIiIiItMiSbIrPT0drVq1wooVK/Rqf+PGDfTu3RvPP/88zpw5gylTpmDs2LHYv39/OUdKRERERERERESmRJLVGHv16oVevXrp3X716tWoX78+Fi9eDABo2rQp/vjjD3z66acIDQ0trzBJCvn5gLm51FEQ8VokIiIiIiIyUSZRsys2NhYhISFq+0JDQxEbG6vzmOzsbKSmpqptVMklJwP16gHh4VJHQtXdhx8CtWsDly5JHQkREREREREZyCSSXQkJCXBzc1Pb5+bmhtTUVGRmZmo9Zv78+XB0dFRtXl5eFREqGWPzZuDePYD12EpPEICDB4HYWCAvT+poTNd77wEpKcA770gdCRERERERERnIJJJdpREVFYWUlBTVdufOHalDopIoFFJHYPoyMoDu3YF27YCsLKmjMX12dlJHQERERERERAYyiWSXu7s7EhMT1fYlJibCwcEBNjY2Wo+Ry+VwcHBQ26iSk8kKbguCdHGYsvT0gtsPH0oXh6kLCxO/+vtLGgYREREREREZziSSXcHBwTh06JDavgMHDiA4OFiiiKhcWBRaL4GjvEqncLLr6lXp4jB1yhFdhc8nERERERERmQRJkl1Pnz7FmTNncObMGQDAjRs3cObMGdy+fRuAOAVx5MiRqvavvfYarl+/jrfffhuXLl3CypUr8e2332Lq1KlShE/lJSwMuHULuHOHq+CV1tOn2m+TYZjsIiIiIiIiMlkWJTcpe6dOncLzzz+v+j4yMhIAEBYWho0bN+L+/fuqxBcA1K9fHz/++COmTp2KpUuXom7duvj8888RGhpa4bFTObKxEVdjpNIrnJxhoqb0Fi0Sv6akSBsHERERERERGUySZFeXLl0gFFOTaaOW1fi6dOmCv/76qxyjokrh/n0gLU1MellbSx2N6WGyy3g5OQW3Fy6ULg4iIiIiIiIqFZOo2UXVxM6dgIcH0KQJcO6c1NGYpsJTF5nsKp3C55CrMRIREREREZkcJruo8jh4sOA2602VTrNmBbd5DktHmSS0tASsrKSNhYiIiIiIiAzGZBdVHpyCZ7xGjYApU8TbPIelozxvubnAqFGShkJERERERESGk6RmF5FWnIJXNt54AxgwAPDxkToS01T42mOdQCIiIiIiIpPDZBdVHoWTDJyCVzq3bgGPHwO+voCnp9TRmCYmXYmIiIiIiEwapzFS5cFpjMZbswZo2xZYtEjqSEyXtTUgl4u3eR0SERERERGZHCa7qPLgiBrjKc/h+vXA9u3SxmKqgoKAs2fF27wOiYiIiIiITA6TXVR5KBML/v7Ac89JGorJUp7DtDRgxQppYzFldnbi1/R0QBCkjYWIiIiIiIgMwmQXVR6HDgHnzgF//AH06CF1NKaJU0HLhr29+FWhALKzpY2FiEgPK1asgI+PD6ytrREUFIQTJ04U23779u3w8/ODtbU1WrZsib179+ps+9prr0EmkyEmJqaMoyYiIiIqH0x2UeXh5QU0b14wqoYMx6mgxlu+HGjaVLzt4gJkZkobDxFRCbZt24bIyEhER0fj9OnTaNWqFUJDQ5GUlKS1/bFjxzB8+HCMGTMGf/31F/r374/+/fvj3LlzGm137dqF48ePw8PDo7xfBhEREVGZYbKLKpfsbCAhAdDRQacScEVL4yUlAffuAW+8Id6uWVPqiIiIirVkyRKMGzcO4eHhaNasGVavXg1bW1usX79ea/ulS5eiZ8+eeOutt9C0aVN88MEHeO6557B8+XK1dnfv3sWkSZOwefNmWFpaVsRLISIiIioTTHZR5ZCTA7z1FlC/PlCnDjB+vNQRmSZOYzSe8rxxhCERmYCcnBzExcUhJCREtc/MzAwhISGIjY3VekxsbKxaewAIDQ1Va69QKPDqq6/irbfeQvPmzUuMIzs7G6mpqWobERERkVSY7KLKIS0N+OQT4P598XsmakrntdeA8HDxNs9h6SjPm7JuFxFRJfbw4UPk5+fDzc1Nbb+bmxsSEhK0HpOQkFBi+wULFsDCwgJvvvmmXnHMnz8fjo6Oqs3Ly8vAV0JERERUdpjsosqhaGKGU/BKZ/RoYNEi8XZ2NpCXJ208pkh57UVHA507A6dOSRsPEVEFi4uLw9KlS7Fx40bIZDK9jomKikJKSopqu3PnTjlHSURERKSbhdQBEAHQTHZxVFLpOToCP/4oTsPT848UKqTwtffbb2INOSKiSsrZ2Rnm5uZITExU25+YmAh3d3etx7i7uxfb/vfff0dSUhLq1aunuj8/Px/Tpk1DTEwMbt68qfGYcrkccrncyFdDREREVDY4sosqBya7ykZcHHD5MtCjhzgqydxc6ohMD69FIjIhVlZWCAgIwKFDh1T7FAoFDh06hODgYK3HBAcHq7UHgAMHDqjav/rqq/jnn39w5swZ1ebh4YG33noL+/fvL78XQ0RERFRGOLKLKgdOYzRefj4QGCjefvAAcHaWNh5T5eUF+PkBV6+K00B5LRJRJRcZGYmwsDAEBgaiTZs2iImJQXp6OsL/q+E4cuRIeHp6Yv78+QCAyZMno3Pnzli8eDF69+6NrVu34tSpU1i7di0AoHbt2qhdu7bac1haWsLd3R1NmjSp2BdHREREVApMdlHloEwo1KwJPHnC0TSlkZFRcHvvXrHo/6BBQJEixFSCL74Qvw4bBmzbxmuRiCq9oUOH4sGDB5g9ezYSEhLg7++Pffv2qYrQ3759G2ZmBYP527Vrhy1btmDWrFmYOXMmGjVqhN27d6NFixZSvQQiIiKiMsVkF1UOyoSClxfQrx9Qo4a08ZgiZcJQJgM++EAcmdSqFZNdpWVnJ35lsouITEBERAQiIiK03nfkyBGNfYMHD8bgwYP1fnxtdbqIiIiIKismu6hy6NkT+OcfwNJSnEJGhlMmZeztxa3wPjIck11EREREREQmickuqhwcHICWLaWOwrQpkzJ2dkzUGKNlS0AQgGefBaytxdtERERERERkMpjsosonI0OcklezpjjSi/SjnMbIZFfpCQJw/rz49eefga+/ljoiIiIiIiIiMpBZyU2IKsDPP4t1pn75BfD2FutMxcdLHZVp0TayiysJGiYrq2Akl3IqKBEREREREZkUJruocti3D5g9W0x6cVRS6fj4ALNmAWPG8ByWVuHzpTyHREREREREZFKY7KLKofAUPBZXL53GjcXRcW++yXNYWsrzZW0NHD8O9OkDTJsmbUxERERERERkENbsosqBU/DK1oQJQO/eXNnSUIWTrg8fAj/+KH4lIiIiIiIikyHZyK4VK1bAx8cH1tbWCAoKwokTJ4ptHxMTgyZNmsDGxgZeXl6YOnUqsrKyKihaKnfKZJe9PafglVZSkljn7NEjwN9fHJXUsKHUUZmWwklXjo4jIiIiIiIySZIku7Zt24bIyEhER0fj9OnTaNWqFUJDQ5GUlKS1/ZYtWzBjxgxER0fj4sWL+OKLL7Bt2zbMnDmzgiOncqNtZBeTDIZZtUocyfXuu1JHYrrMzMTpoA0a8DokIiIiIiIyUZIku5YsWYJx48YhPDwczZo1w+rVq2Fra4v169drbX/s2DG0b98eL7/8Mnx8fNCjRw8MHz68xNFgZEK0jajhNEbDFD6H168DX30lFv4n/QUGiqPjfvmFyS4iIiIiIiITVeHJrpycHMTFxSEkJKQgCDMzhISEIDY2Vusx7dq1Q1xcnCq5df36dezduxcvvPCCzufJzs5Gamqq2kaVWOFpjB07Aq++CjRpIm1MpqZwsuv334GwMCAmRtKQTBprxxEREREREZmkCi9Q//DhQ+Tn58PNzU1tv5ubGy5duqT1mJdffhkPHz5Ehw4dIAgC8vLy8NprrxU7jXH+/PmYO3dumcZO5WjrVuDxY6B5cyAkBHjjDakjMj2cClq2lCMMMzIAhUKc4khERERERESVnkn89XbkyBHMmzcPK1euxOnTp7Fz5078+OOP+OCDD3QeExUVhZSUFNV2586dCoyYDNa0KdC+PeDkJHUkpovF1Y331VfAM88A771XkDC0sgK4GAYREREREZHJqPCRXc7OzjA3N0diYqLa/sTERLi7u2s95r333sOrr76KsWPHAgBatmyJ9PR0jB8/Hu+++y7MtIy4kMvlkMvlZf8CqPwJApCdDeTnFyQcqGTaVrTkFDzD3L0LnD0r1u6ytQVycwGLCv81SUREREREREao8JFdVlZWCAgIwKFDh1T7FAoFDh06hODgYK3HZGRkaCS0zM3NAQCCIJRfsFQxBAH46COxvlRmJrBsGWBjA/yX3CQ9KRNbnMZYeoUThjIZE11EREREREQmSJK/5CIjIxEWFobAwEC0adMGMTExSE9PR3h4OABg5MiR8PT0xPz58wEAffv2xZIlS/Dss88iKCgIV69exXvvvYe+ffuqkl5kwjIzgVmzxNtjxnBUUmkNGwY89xzg5ydOvQOY7DJU4YQhERERERERmSRJkl1Dhw7FgwcPMHv2bCQkJMDf3x/79u1TFa2/ffu22kiuWbNmQSaTYdasWbh79y5cXFzQt29ffPTRR1KET2WtcELG1pajkkqrcFH/f/8Vv/IcGqZw3TMAmDoVuHYN+PhjoFkz6eIiIiIiIiIivUk2RyciIgIRERFa7zty5Ija9xYWFoiOjkZ0dHQFREYVTjmaxsYGMDdnsqssODsDmzeL51IQxCl5VLLC0xgB4OBB4Nw54M03mewiIiIiIiIyESxIQ9IrOpqG0xhL5+pVcWScmxtgbQ28/LLUEZmeotMYmXglIiIiIiIyORVeoJ5IQ9HRNEwwlE6zZoCnJ3DvntSRmC4nJ6BOHaBmTfF75TXJa5GIiIiIiMhkcGQXSa/oaBomGAyXkwPk5oq3ledv717g8WOgd++C5A0V76uv1L/nKEMiIiIiIiKTw2QXSa/oNMbatYEXXxS/kn4KJwaV53HCBLFQ/cmTQGCgNHGZOo4yJCIiIiIiMjlMdpH0OnQAfvsNkMvF793dgd27JQ3J5CiTMRYWgJWVeJuJGuPxHBIREREREZkcJrtIerVqAR07Sh2FaSs6Og7gdNDS6NYNyMoSV7L08Sk4hxkZkoZFRERERERE+mOyiyqvnBxxpJIZ11EokbZkF0clGe74cTGxJQji9/PmAR9/XDBajoiIiIiIiCo9ZhFIeseOAZ99BvzxR8G+2rXFaY3Xr0sXlylhsst4CkXBCC7lubOxEa9DmUy6uIiIiIiIiMggTHaR9PbsASZPBrZvL9hnaSl+ZaJGP25uQEQE8PLLBfuUU/C4kqB+MjMLbhdOGhIREREREZFJ4TRGkp6uelOJiUx26atxY2DZMvV9HNllmMJJQRsb8evRo8DKlUDTpsCsWdLERURERERERAbhyC6SnjIZoxyJBBQkajgqqfTGjAG+/hro21fqSExD4aSrsk7cv/8CW7YAhw5JFxcRkR5WrFgBHx8fWFtbIygoCCdOnCi2/fbt2+Hn5wdra2u0bNkSe/fuVd2Xm5uLd955By1btoSdnR08PDwwcuRI3Lt3r7xfBhEREVGZYLKLpKdMaLHeVOmlpgIJCeqrBnboALzyCtCsmXRxmZLi6p4x6UpEldi2bdsQGRmJ6OhonD59Gq1atUJoaCiSkpK0tj927BiGDx+OMWPG4K+//kL//v3Rv39/nDt3DgCQkZGB06dP47333sPp06exc+dOxMfHo1+/fhX5soiIiIhKjckukh6Lqxtv9WqgTh3g9deljsR05eWJtc9cXQv28TokIhOwZMkSjBs3DuHh4WjWrBlWr14NW1tbrF+/Xmv7pUuXomfPnnjrrbfQtGlTfPDBB3juueewfPlyAICjoyMOHDiAIUOGoEmTJmjbti2WL1+OuLg43L59uyJfGhEREVGpMNlF0ituGiOTDPrRdg5v3wa+/15c7ZJK9uyz4ui4s2cL9vE6JKJKLicnB3FxcQgJCVHtMzMzQ0hICGJjY7UeExsbq9YeAEJDQ3W2B4CUlBTIZDI4OTlpvT87OxupqalqGxEREZFUmOwi6WmbxhgUJNaaqltXmphMjbbRcT/9BLz4IrBwoTQxVQVc0ZKIKrmHDx8iPz8fbm5uavvd3NyQkJCg9ZiEhASD2mdlZeGdd97B8OHD4eDgoLXN/Pnz4ejoqNq8vLxK8WqIiIiIygZXYyTprVwJJCUBAQEF+6KipIvHFHEqaPngOSSiai43NxdDhgyBIAhYtWqVznZRUVGIjIxUfZ+amsqEFxEREUmGyS6SXmCg1BGYPhb5N96uXcCnnwIhIcDs2eI+5TnMzgby8wFzc+niIyLSwtnZGebm5khMTFTbn5iYCHd3d63HuLu769Vemei6desWfvnlF52jugBALpdDLpeX8lUQERERlS1OY6TKTRCkjsA0aKvZpbzNZJd+bt4Efv8diI8v2FerFvDwIZCZCZjx1yURVT5WVlYICAjAoUOHVPsUCgUOHTqE4OBgrccEBwertQeAAwcOqLVXJrquXLmCgwcPonbt2uXzAoiIiIjKAf96I+mtXg1s2KCelFm6FJDLgfBw6eIyJcVNY2S9Kf1oGx1nZgbUrg1YWwMymTRxERGVIDIyEuvWrcOXX36Jixcv4vXXX0d6ejrC//sMHTlyJKIKlQeYPHky9u3bh8WLF+PSpUuYM2cOTp06hYiICABiomvQoEE4deoUNm/ejPz8fCQkJCAhIQE5OTmSvEYiIiIiQ3AaI0krPx94/XXxdp8+BYkGc3MgJ4ejkvQVGgrUqQM0blywj9MYDaMtYUhEZAKGDh2KBw8eYPbs2UhISIC/vz/27dunKkJ/+/ZtmBUandquXTts2bIFs2bNwsyZM9GoUSPs3r0bLVq0AADcvXsX33//PQDA399f7bkOHz6MLl26VMjrIiIiIiotJrtIWhkZBbdZb6r0ChUFVuE0RsPoSnZFRQF37wJz5wL161d8XEREeoiIiFCNzCrqyJEjGvsGDx6MwYMHa23v4+MDgWUEiIiIyIQx2UXSUiYYZDLAxqZgP5NdxnNzE1e6LFzHi3TTlezavh24dg2YMIHJLiIiIiIiIhPAZBdJq3CCoXBNJCa7DPPwIWBrKyYMlefR3r5giiiVTFeyiyPkiIiIiIiITAoL1JO0tBUFBwoSDCyurh9fX/EcXr0qdSSmy9xcTBYWHQnHQv9EREREREQmhSO7SFq6RtNwZJf+BEH3efz9dyAlBejShdMZS7Jli/b9vBaJiIiIiIhMCpNdJC1dSZratcUEjbt7hYdkcrKzAYVCvF30PL70EvDoEXDuHNC8ecXHVhUw2UVERERERGRSJJvGuGLFCvj4+MDa2hpBQUE4ceJEse2Tk5MxceJE1KlTB3K5HI0bN8bevXsrKFoqN/7+wA8/AEuWqO+vXx84fBj45htJwjIphafXsd5U2eM5JCIiIiIiMimSjOzatm0bIiMjsXr1agQFBSEmJgahoaGIj4+Hq6urRvucnBx0794drq6u2LFjBzw9PXHr1i04OTlVfPBUtlxcgD59pI7CtCmTMHI5YFHkR5r1pvQ3dKh4nj77DGjQoGA/zyEREREREZFJkSTZtWTJEowbNw7h4eEAgNWrV+PHH3/E+vXrMWPGDI3269evx+PHj3Hs2DFYWloCAHx8fCoyZKLKS9dU0ML7OCqpZAcPAo8fA4sWqe+fNw/44APAwUGauIiIiIiIiMggFT6NMScnB3FxcQgJCSkIwswMISEhiI2N1XrM999/j+DgYEycOBFubm5o0aIF5s2bh/z8fJ3Pk52djdTUVLWNKqG//wa+/BLQNo3Vw0NcHe/u3YqPy5QoE1naCtBzCp7+dJ3HWrXEEYhyecXHRERERERERAar8GTXw4cPkZ+fDzc3N7X9bm5uSEhI0HrM9evXsWPHDuTn52Pv3r147733sHjxYnz44Yc6n2f+/PlwdHRUbV5eXmX6OqiMfP89MGoU8PnnmvdlZABZWUzUlMTREXj1VaB/f837OAVPP3l5YqF/QPsIOSIiIiIiIjIZJrEao0KhgKurK9auXQtzc3MEBATg7t27WLRoEaKjo7UeExUVhcjISNX3qampTHhVRsWNSrKzA1JSmKgpSePGwFdfab+P0xj1U/j8FE12xcYCmzYBzZoBEydWbFxERERERERksApPdjk7O8Pc3ByJiYlq+xMTE+Hu7q71mDp16sDS0hLm5uaqfU2bNkVCQgJycnJgZWWlcYxcLoec044qP2UiS9toGk7BM15YGNChA9Cxo9SRVG7Ka8zcXHO64uXLwMqVQM+eTHYRERERERGZgAqfxmhlZYWAgAAcOnRItU+hUODQoUMIDg7Wekz79u1x9epVKBQK1b7Lly+jTp06WhNdZEJYXN142dnidE9B0LyvVy8gIgJo1ari4zIlha9DmUz9Pl6HREREREREJqXCk10AEBkZiXXr1uHLL7/ExYsX8frrryM9PV21OuPIkSMRFRWlav/666/j8ePHmDx5Mi5fvowff/wR8+bNw0SOsjB9JU1jLNyGtFu7VizkP3y41JGYrqwscUQXk65EREREREQmT5KaXUOHDsWDBw8we/ZsJCQkwN/fH/v27VMVrb99+zbMzArycF5eXti/fz+mTp2KZ555Bp6enpg8eTLeeecdKcKnslTcNEYmGfSjPIe2tpr33b8vTsOrVQto2bJi4zIlLVuKCS9tK7yyyD8REREREZFJkaxAfUREBCIiIrTed+TIEY19wcHBOH78eDlHRRWuuGmMrVoBmZliooZ0K+4cbtsGTJ0KDBsGfPNNxcZligrVBVRh0pWIiIiIiMikmMRqjFSFffAB8O+/QNu2mvctWFDx8Zgi1j0rX1wogYiIiIiIyKQw2UXS6tRJ6ghMX3F1z5io0c+BA8BnnwHt2gGF6gUCYMKQiIiIiIjIxDDZRWTq9Kl7xnpTxbt6FdizB7C01LzP3V28385OXPGy6GqNREREREREVKlIshojkcq33wK7dmkfNbN0KeDmJtacIt04jdF4xZ1DCwugQQMx6cVEFxERERERUaXHkV0krVdfBXJygNu3NRMNublAUhLw6JE0sZmKtm3FJEzDhpr3cRqjfoqbCkpEREREREQmhckukk5enpjoAjgFzxhFa0wVxnOon+JGdgHiQgpJScDMmUCdOhUXFxERERERERmMyS6STuHRRpyCVz48PIB58wAnJ6kjqdxKSnatWQPcvQuEhzPZRUREREREVMkx2UXSUY42MjcHrKw072eySz+5udoLqwNArVrFj/wikfJa1DWNkSPkiIiIiIiITAYL1JN0CtdJ0lb4m/Wm9FO3rpjsOndO6khMV1aW+FXXyC5ei0RERERERCaDI7tIOiVNHeNoGv2kp4v1z2xstN9/5gyQlga0bg1YW1doaCZj2zZg0ybd93OUIRERERERkclgsouko0xi6Up21a4N+PsD3t4VFpLJUShKXkmwQwexzbVrgK9vxcVmanRNBQWY7CIiIiIiIjIhTHaRdBo3Br7+Wvdoo6ZNgb/+qtiYTE1mZsHt4kbIpadzhJwxOMqQiIiIiIjIZLBmF0nHzQ145RVg0CCpIzFdhUca2dpqb8NRSSWbOBEYMQK4ckX7/TyHRFTJrVixAj4+PrC2tkZQUBBOnDhRbPvt27fDz88P1tbWaNmyJfbu3at2vyAImD17NurUqQMbGxuEhITgiq7fkURERESVDEd2EZkyZfLF1hYw05G7ZnH1kv3vf8Ddu8C0adrv/+gjYNYsMUFLRFTJbNu2DZGRkVi9ejWCgoIQExOD0NBQxMfHw9XVVaP9sWPHMHz4cMyfPx99+vTBli1b0L9/f5w+fRotWrQAACxcuBCfffYZvvzyS9SvXx/vvfceQkNDceHCBVhXgvqPgkJAxsMMpD/Q/dlmbmkOa6eCWItra2ZhBpuaNqVqm/EoA4JC0NpWZiaDbW3bUrXNfJIJRZ5CZxx2LnalapuVnIX83PwyaWtb2xYyM3GRoezUbORl55VJW5uaNjCzEPs1OU9zkJuZWyZtrR2tYW5lbnDb3Ixc5KTn6GwrryGHhbWFwW3zsvKQnZats62VnRUsbS0Nbpufk4+slCydbS1tLGFlb2VwW0WeAplPMsukrYXcAnIHOYD/fp4fZZRJW0N+7vk7Qntb/o7g7whjf0fYudjB1rng/ZSKTBAE7T9NVUxqaiocHR2RkpICBwcHqcMhQBxFc+ECUL8+8Mwzmvfn5wNNmohJmvPngVq1Kj7Gyu7sWfHcubgASUna2wQHA8ePA7t2Af37V2h4JsPJCUhJAS5dEq85IiI9VYb+RVBQEFq3bo3ly5cDABQKBby8vDBp0iTMmDFDo/3QoUORnp6OPXv2qPa1bdsW/v7+WL16NQRBgIeHB6ZNm4bp06cDAFJSUuDm5oaNGzdi2LBhGo+ZnZ2N7OyCTnZqaiq8vLzK7bykJ6XD3k3H9H0iIiKS1NPEdNi5ls/ntL59L05jJOns3i0mXz75RPv95ubAnTtAQgJrJeliYwP07Qt07667DafglayklUGJiCqpnJwcxMXFISQkRLXPzMwMISEhiI2N1XpMbGysWnsACA0NVbW/ceMGEhIS1No4OjoiKChI52POnz8fjo6Oqs3Ly8vYl0ZERERUapzGSNJRJrB0rSKovO/xYyZqdGnYEPj+++LbMNlVvJwcIO+/YdK6rsU//xTPc9OmYp05IqJK4uHDh8jPz4dbkWnWbm5uuHTpktZjEhIStLZPSEhQ3a/cp6tNUVFRUYiMjFR9rxzZVV5snW3xNDGdU5RK0ZZTlDhFidMYDW/L3xGla8vfEaLq9jtCOY1Rakx2kXT0GU1jZycmuziyq/Refhlo0wYIDJQ6ksqp8LWl61r86y9g3jxxJCKTXUREGuRyOeRyeYU9n8xMBjtXO4OmSLAt25a2rSlyqKv/9GFD2tbwqFEube3di/nntxFtK8P1w7ZVv60pqgy/I8obk10kHX2TXYXbkjpBAGQlFP4bOrRiYjFVymvL0lLctOF1SESVlLOzM8zNzZGYmKi2PzExEe7u7lqPcXd3L7a98mtiYiLq1Kmj1sbf378MoyciIiIqH6zZRdJhsst4n38OyOXi6C0qHV6HRGTCrKysEBAQgEOHDqn2KRQKHDp0CMHBwVqPCQ4OVmsPAAcOHFC1r1+/Ptzd3dXapKam4s8//9T5mERERESVCUd2kXT0STIoaygxyaBderpYc6q4RVUfPQL+/ReoUQPw9a242ExFkyZAVhaQqbuuBJNdRFSZRUZGIiwsDIGBgWjTpg1iYmKQnp6O8PBwAMDIkSPh6emJ+fPnAwAmT56Mzp07Y/Hixejduze2bt2KU6dOYe3atQAAmUyGKVOm4MMPP0SjRo1Qv359vPfee/Dw8EB/rupLREREJoDJLpKOPsmuRo2AJ08AW+kL3FVK+pzDdeuAqCggPBxYv75i4jIlMpk4Oq64WjPKpCtrxxFRJTR06FA8ePAAs2fPRkJCAvz9/bFv3z5Vgfnbt2/DzKxgMH+7du2wZcsWzJo1CzNnzkSjRo2we/dutGjRQtXm7bffRnp6OsaPH4/k5GR06NAB+/btg7W1tcbzExEREVU2THaRdKZMAV58EWjbVnebdesqLByTpEx2FbeiJUclGY/nkIgquYiICERERGi978iRIxr7Bg8ejMGDB+t8PJlMhvfffx/vv/9+WYVIREREVGGY7CLp9OwpdQSmTznSSJ+poByVpN2xY8CqVYC/PzBtmvY2THYRERERERGZDBaoJzJlLK5uvMuXgU2bgIMHdbepVw84dQo4ebLi4iIiIiIiIqJSYbKLpHPgAHD4cPFJmM8+Axo3BubOrbi4TAmnMRpPn3MolwMBAWIxeyIiIiIiIqrUJEt2rVixAj4+PrC2tkZQUBBOnDih13Fbt26FTCbjakBVwaBBQNeuwN27utukpABXrhTfpjpr1gzo0gXw8dHdRpns4jRG7fSZCkpEREREREQmQ5Jk17Zt2xAZGYno6GicPn0arVq1QmhoKJKSkoo97ubNm5g+fTo6duxYQZFSuREEjkoqC7Nni6Pj+vXT3YbnsHj6TAUFgCVLgPfeAx4/Lv+YiIiIiIiIqNQkSXYtWbIE48aNQ3h4OJo1a4bVq1fD1tYW69ev13lMfn4+RowYgblz58LX17cCo6VykZMD5OeLt1lvqnzVrQu8/Tbw5ptSR1I56ZN0BYB584APPwQSEso/JiIiIiIiIiq1Ck925eTkIC4uDiEhIQVBmJkhJCQEsbGxOo97//334erqijFjxuj1PNnZ2UhNTVXbqBIpPKVOn5UEmewqvTp1gAULgOnTpY6kctJ3GiOngxIREREREZmECk92PXz4EPn5+XBzc1Pb7+bmhgQdIyb++OMPfPHFF1i3bp3ezzN//nw4OjqqNi8vL6PipjKmTF5ZWQEWFrrbMcFQvKZNARcX4MwZqSMxXfpOY+QoQyIiIiIiIpNQ6VdjTEtLw6uvvop169bB2dlZ7+OioqKQkpKi2u7cuVOOUZLB9J06xgRD8R48AB4+FJOGuggCcO0a8M8/QF5excVmKj7/HEhKAsaPL74dRxkSERERERGZhGKG1JQPZ2dnmJubIzExUW1/YmIi3N3dNdpfu3YNN2/eRN++fVX7FAoFAMDCwgLx8fFo0KCBxnFyuRxyubyMo6cyo+9ompo1gfr1xbpTpEnf89ikiVgj7d9/AU/P8o/LlFhbi1tJmHglIiIiIiIyCRWe7LKyskJAQAAOHTqE/v37AxCTV4cOHUJERIRGez8/P5w9e1Zt36xZs5CWloalS5dyeqKpqlsXWL68+BFJABAYCFy/XjExmZr8fCArS7xdXLJLJhPvT01losYYTHYRERERERGZhApPdgFAZGQkwsLCEBgYiDZt2iAmJgbp6ekIDw8HAIwcORKenp6YP38+rK2t0aJFC7XjnZycAEBjP5kQd3dg4kSpozBtGRkFt/WpN8Vkl3bvvQc8egRMmQI0bqy7HacxEhERERERmQRJkl1Dhw7FgwcPMHv2bCQkJMDf3x/79u1TFa2/ffs2zMwqfTkxImkpi/bLZCVPw+OoJN2++UasaTZiRPHJrrlzgWnTAB+fCguNiIiIiIiIDCdJsgsAIiIitE5bBIAjR44Ue+zGjRvLPiCqWP/+KyYYPDyARo10t8vKAjp0EBM7p08DtrYVF2NlV7hel0xWfFuOStLNkLpnREREREREVOlx+BRJY9cuoEsX4N13i29nZQXExQHx8UzUFGVuDnTsCAQHl9xWmchRjgajAvquDEpEREREREQmQbKRXVTN6TuaxswMsLEBMjPFRI2LS/nHZirq1wd++02/tpzGqJ0gFCQAS7oWT50CfvkF8PMD+vUr/9iIiIiIiIioVDiyi6RhyGgaTsEz3sCBwFtvAc2aSR1J5ZKVJSa8gJKTXb//DrzzDrB1a/nHRURERERERKXGkV0kDX1HdinbPHjAZJcxxo+XOoLKqfA1VdK1yKQrERERERGRSeDILpKGocmuwseQaNs2wNUVGDlS6khMl/KasrYWa6AVh3XPiIiIiIiITAJHdpE0SpPsYpJB3ZMn4oi3tLSS26alAY8eifXP3NzKPzZTUbcukJAg1oQrCZOuREREREREJoEju0gaysSVPjW7PD2BevVKHnlT3RiSMFy8WCxoP3du+cZkaszNxeSfj0/JbTmNkYiIiIiIyCRwZBdJY9QoIChI3Eqyc2e5h2OSDCnyz9FxxuM5JCIiIiIiMglMdpE0+vcXNyo9ZdKFdc9K7++/gXXrgKZNgYkTi2/Lc0hERERERGQSOI2RyFQZMo2RU/C0u3QJWLEC2LGj5La+vsChQ8DeveUfFxEREREREZUak10kjZMngdOn9SsMvmIF0KYNsHRp+cdlSriipfEMqR1nZwd07QoEBpZvTERERERERGQUJrtIGn37AgEBwJUrJbe9d09Mjl2/Xv5xmZJ69YBnnxVXFCwJk13aGZIwJCIiIiIiIpPAml0kDdabMt7774ubPngOtTM02bV2LZCWBowfD9SoUX5xERERERERUalxZBdVPEEAMjLE20x2VQwvL2DCBOCVV6SOpHIxJOkKAFOnAtOnAw8elF9MREQGePz4MUaMGAEHBwc4OTlhzJgxeFrCqrFZWVmYOHEiateuDXt7ewwcOBCJiYmq+//++28MHz4cXl5esLGxQdOmTbGUpQSIiIjIhHBkF1W8zEwx4QXoXysJKEhMkOF8fIDVq6WOovIxdGSXnZ2YqGXilYgqiREjRuD+/fs4cOAAcnNzER4ejvHjx2PLli06j5k6dSp+/PFHbN++HY6OjoiIiMCAAQNw9OhRAEBcXBxcXV2xadMmeHl54dixYxg/fjzMzc0RERFRUS+NiIiIqNSY7KKKVzhpZWtbcnuuJKhdx47A/fvAtm1i/TMynKHJLnt7cVQXr0UiqgQuXryIffv24eTJkwj8b/GMZcuW4YUXXsAnn3wCDw8PjWNSUlLwxRdfYMuWLejatSsAYMOGDWjatCmOHz+Otm3bYvTo0WrH+Pr6IjY2Fjt37mSyi4iIiEwCpzFSxVMmCmxsADM9LkFOY9Tuxg3g2jX92goC8OgRcPs2oFCUb1ymZOFCcZGECRP0a89RhkRUicTGxsLJyUmV6AKAkJAQmJmZ4c8//9R6TFxcHHJzcxESEqLa5+fnh3r16iE2Nlbnc6WkpKBWrVo678/OzkZqaqraRkRERCQVjuyiimfoaBoHB6BmTf2mPFYnhpzHvDzA2Vm8/egRUMwfLNVKzZripi8mXomoEklISICrq6vaPgsLC9SqVQsJCQk6j7GysoKTk5Pafjc3N53HHDt2DNu2bcOPP/6oM5b58+dj7ty5hr0AIiIionLCkV1U8ZydgQ8/BN56S7/2nTsDjx8Dhw6Vb1ymRplw0ScJaGkJWFmpH0eG45RaIqoAM2bMgEwmK3a7dOlShcRy7tw5vPjii4iOjkaPHj10touKikJKSopqu3PnToXER0RERKQNR3ZRxXN3B959V+ooTFturrgBhhVXz8lhoqawJUuAhw+B8HCgUaOS23MaIxFVgGnTpmHUqFHFtvH19YW7uzuSkpLU9ufl5eHx48dwd3fXepy7uztycnKQnJysNrorMTFR45gLFy6gW7duGD9+PGbNmlVsPHK5HHK5vNg2RERERBWFyS4iU1Q4YWVIsuvJEyZqClu/Hjh/HujWTb9k1+zZwKRJQLNm5R8bEVVbLi4ucHFxKbFdcHAwkpOTERcXh4D/Fir55ZdfoFAoEBQUpPWYgIAAWFpa4tChQxg4cCAAID4+Hrdv30ZwcLCq3fnz59G1a1eEhYXho48+KoNXRURERFRxmOyiivfwIfDvv+J0xrp1S26fmgoMGCAmaY4eBczNyz/Gyk6ZsCo8PbEknIKnydD6cVz1kogqkaZNm6Jnz54YN24cVq9ejdzcXERERGDYsGGqlRjv3r2Lbt264auvvkKbNm3g6OiIMWPGIDIyErVq1YKDgwMmTZqE4OBgtG3bFoA4dbFr164IDQ1FZGSkqpaXubm5Xkk4IiIiIqmxZhdVvN27gWefBV5/Xb/2lpZiva4//wQyMso1NJOhUACtWgEtWuh/DIurazI02UVEVMls3rwZfn5+6NatG1544QV06NABa9euVd2fm5uL+Ph4ZBT6/Pz000/Rp08fDBw4EJ06dYK7uzt27typun/Hjh148OABNm3ahDp16qi21q1bV+hrIyIiIiotjuyiiqersLogAGfPAikpgK1twWZjA8hk4v1PnwI1alR8zJVNvXrAmTOGHcNklyblucjNBa5fB5KTxesvJQWwsBCnN9rYFLT/+28x6dqoEfD885KETERUWK1atbBlyxad9/v4+EAQBLV91tbWWLFiBVasWKH1mDlz5mDOnDllGSYRERFRhWKyiyqecgqeMvmSmAhs2iTWT7pwofhjfXyAhg3FJERICNClC+DgUJ7RVh19+gBNmgDe3lJHIp1//wV++EHc/v67YKSgrumJtWoBo0YB48eL527vXmDmTGD0aCa7iIiIiIiIKikmu6jiKUfTJCYC/fsDP/4I5OWJ+6ytxVFLGRkFW1ZWwbE5OWJC7MIFYNkysX5XmzZi4iskBGjbVv8aVtXNW29JHUHFUyiA06cLElx//aW7ra0t4OgIODmJX+/eBe7cEVdsXLJETG4pE4Us8k9ERERERFRpSZbsWrFiBRYtWoSEhAS0atUKy5YtQ5s2bbS2XbduHb766iucO3cOgLiS0Lx583S2p0rs0iVg/37x9p49BfuDgsTRMkOHiomGwhQKcTTXjRvA9u2AmRlw8KC4XbkCxMaK2wcfiAmLrl2BgQOBF18EatasuNdWkfbuBaZMAdq3F1cIvHoVuHZN/Hr1qjjls2lTsaZX8+aAn5/6dLyqLC9PrPG2c6d4jd27V3CfTAYEBwN9+wLPPAP07i3uz8oC5HL1x8nPF6/V1avFhOzhwwX3xcWJ12P9+uX/eoiIiIiIiMggMqFoIYcKsG3bNowcORKrV69GUFAQYmJisH37dsTHx8PV1VWj/YgRI9C+fXu0a9cO1tbWWLBgAXbt2oXz58/D09NTr+dMTU2Fo6MjUlJS4MBpbxUvORmYMQNYs6Zgn50d8NprQHi4mJApzjPPiPW8fv4Z6N69YP+tW2JiQ5n8evCg4D4LC3G016BB4giy2rXL8hVVvLQ04PffxaTL/v3i+VDWMiuJmZmYmGncWDzXQUHiVNCqkgwUBHHU1tdfA998I44aVLK3B3r0APr1A154AVCuJJaXJyYIMzLEBROKc/s28Pnn4mjC5GRxn0wGTJ4MfPSRmGQlomqJ/QvteF6IiIioPOjbx5Ak2RUUFITWrVtj+fLlAACFQgEvLy9MmjQJM2bMKPH4/Px81KxZE8uXL8fIkSP1ek52uiQiCMC334pJAWUCwsNDHG2zeDEQGanf43TqBPzzj5jI6NVLexuFQkwAff+9OALs7NmC+8zNxRFfgwYBL71UkPCozDIzgWPHgF9+EbeTJ8XRRkXJ5YCvrzj6rUED8SsAnD8vbufOAY8fax5nZiaOcurVS9z8/cV9puTOHWDzZjHJVbjem7MzMHiwOLqvSxfNUVultXu3eP04OACpqeK+hg3FenMdO5bNcxCRSWH/QjueFyIiIioP+vYxKnwaY05ODuLi4hAVFaXaZ2ZmhpCQEMTGxur1GBkZGcjNzUWtWrV0tsnOzkZ2drbq+1TlH6ZUcW7eBCZOFKfcAWKB7zVrgIQEcRRO27b6P9Zvv5XcxswMaNVK3N57D4iPB3bsELczZ4ADB8TttdeAwECgZ08gNFQc5WRRCcrXZWaKK/399ps4euvYMbFGWWG+vmLS7vFjcZrewIFiMrG4JJUgiInGGTOAL78UpzSam4uJsKNHxW3WLMDdXTwnvXqJo+cq66ivhARxeuKWLcCRIwUj2+RyMbn16qvi+2ppWfbPrZxi6+kJbNsGjBsnThvt3Bl4801g3jyO8iIiIiIiIpJYhf+F//DhQ+Tn58PNzU1tv5ubGy5duqTXY7zzzjvw8PBASEiIzjbz58/H3LlzjYqVSikvD1i6VKwllZEhFoyPihI35QiboUPLP44mTYB33xW3q1eB774TR3zFxYmjpE6eFOt8OTqK0x1DQ8WtXr3yjw0Qp8MdPSpOTfz9dzGe3Fz1Nh4eYnKra1exQLqPj7g/OlpMdrm5lTwaSyYTE1nPPCN+HxAgrn55+zbw00/idvCgmETauFHczMyA1q3F89KtG9CuXdmNjjKUIIij+pRF5k+cUL+/c2cxwTVokGa9t+LEx4sjwnx9xXpx+rC3F7+mp4uJwXPnxNGJ69eL1/yePcCGDRzlRUREREREJKFKMJzFMB9//DG2bt2KI0eOwNraWme7qKgoRBaaIpeamgovL6+KCLF6O3UKGD++YNW7Tp3E0Vx+ftLG1bAh8M474nbvnlj7a98+caTX48diIuy778S2jRsDLVuKBd79/MSvTZqINcZKIysLuH5drA917Rpw+bI4auuffzTrbXl4iImSzp3FJFOjRmKyqijlaoCGxKRsqzy2Xj1gwgRxy84G/vhDHIX300/AxYviKLM//xRrUtnYiHF16yYmwMp7ymN2tji67YcfxATS7dvq9wcGitMJR4woWCHRUBcviq+tbVv9k12NGonXiXLUm6Mj8MUX4pTJcePE97dzZ2DSJHGUV2mvGSIiIiIiIiq1Ck92OTs7w9zcHImFC0gDSExMhLu7e7HHfvLJJ/j4449x8OBBPKMcpaKDXC6HXKqRKNVRfj7w/vvAhx+KtbNq1gQWLRKLzxdNily5Ik6j8/TUf7TQ6tXiSKbhw8XHNIaHBzBqlLjl54sjvfbtE4u+Hz8uJqMuX9Y8zttbTHw1agRYW4uvS7mZmxfcVijEwvnK5Nbdu7pjadhQTAh27Chuvr7ak1tFpaeLX0uT7FIeW5hcLiayunUTa6nduaNe+D8xUUwQ/vyz2L5mTXGlxyZNxM3PT/xav75hU0Jzc8VRd+fPizW3LlwQb8fHq49ys7ERk2x9+4orKHp46P8cupTmHDo5AQMGaO5XjvKaNk1Mfn32mbiC49dfi3XRiIiIiIiIqMJUeLLLysoKAQEBOHToEPr37w9ALFB/6NAhRERE6Dxu4cKF+Oijj7B//34EBgZWULSkl7t3xRE2v/4qfj98OBATA2hZWROAWA/q1i0xsRQUpN9zXL4sjsIqadU8Q5mbA23aiNvs2cCTJ+JoposXxe3SJfHrw4dizLduiYkxQ9WoIRaPV26BgUCHDkCdOqWLu2ZNMbGk6xxrU1yyqygvr4KEoCCISShl4uvXX8XzpJx+WZilpZjAUyYEBaFg9Frhr8qVEC9f1py6qeTpCfTpIya4unYVE15lqTTJruI4OoorNg4eDIwdK76+Tp2ATz4R63npk8QkIiIiIiIio0kyjTEyMhJhYWEIDAxEmzZtEBMTg/T0dIT/N2Jn5MiR8PT0xPz58wEACxYswOzZs7Flyxb4+PggISEBAGBvbw97ZQ0dksa+fWK9pIcPxXpGa9YAL79c/DGlSTIUrpVUnmrWFEfp9Oypvv/hw4LE1/XrYrJGoRC3/PyC2wqFmMzx9FRPbjk7l22yY/58cTNEac+hTAY0by5ukyeLyamzZ8XzER9f8PXyZbHIvjJRaEhczZqJW/PmBbe9vcs3QVSa61ChEAvTp6cDr7wiJvSKCg0VR3mNHy8uHjBlijhF9IsvxFUciYiIiIiIqFxJkuwaOnQoHjx4gNmzZyMhIQH+/v7Yt2+fqmj97du3YVZo6tuqVauQk5ODQYMGqT1OdHQ05syZU5Ghk1Jurrji4YIF4vf+/mISoHHjko9VJhkMSVQaMiqpPDg7iyOxOnSQ5vnLQt26wLBh4ogwY1haAs89J26FKRTi9Mf4eHFUU36+uF8mK0haKb+amYk1w5o3F0eRSTHqqTTJLplMHMUoCOJ0Sl0j8xwdga1bxetl2jRxRdB//hG/tmxpfOxERERERESkk2QF6iMiInROWzxy5Ija9zdv3iz/gEh/t2+LSZPYWPH7N94Q6zwVs2CASn6+OPoHMK64OhmuaVPgm2/K7/HNzMTRWKUtGF/RSpN0lcnE9mlpJSdeZTKxUH3r1uLUxsuXxWm7a9aIoyGJiIiIiIioXJTjcmpUJX3/vTiKKzZWnJK1fTuwYoV+iS4AyMgouF0ZpzGaigEDgIAA4MQJqSMxXaVZ0bJwe30Tr23biquT9ughJnpHjhRXwMzKMux5iYiIiIiISC9MdpF+cnOB6dOBF18Ui5MHBop/wBeZWloiZbJKJjOs4LjU0xgrm7NngdOngZwcw47LzwdSUwuKxVdnUVHAyZNibS1DlOZadHYG9u4F5swRr/21a4F27cT6b0RERERERFSmmOyikt27J66Gt3ix+P2UKcDRo4Cvr+GPVbhOkiF1mpTtmaQRlWYKXloaYGEh1pPiqCLAw0NM2tarZ9hxpR1laG4OREeLizrUri0mi597ThwtSURERERERGWGyS4q3pEjwLPPiqvJ1agBfPcd8OmngJVV6R7P3h546y2xzpchevYURyX99lvpnreqKc0UPFtbzePJcMbWj+vRQ0x0tW0LpKSIoyXfeUdc4ZOIiIiIiIiMxmQXaadQAB9/DHTrBiQliSvIxcWJtaKM4eYGLFxYsIqjvszMpFmxrzIShNKtJGhuXlBbjdNBgfXrxWvx6lXDjiuLKbVeXsCvv4qjJAExjq5dxVGUREREREREZBQmu0hTcjLw0ktiTSOFQiyoffw40KiR1JERAGRni+8LYNg0xsLtmewCVq0SR1TFxxt2XFSUuDBD587GPb+VlThKcvt2cdTk77+Loyh/+cW4xyUiIiIiIqrmmOwidWfOiKv8ff+9+Mf4mjXAxo3qU+CMkZYG3LwpFrk3xOPHwMCBQO/eZROHKSs8fa68VxKsykozOg4Ann9eXJjB0FpfugwaBJw6BTzzjDiKsnt3YN68goQmERERERERGYTJLhIJAvDFF0BwsLhCnI8PcOyYuFJdWU4f/P57oH59YMgQw4/duVNc0S43t+ziMUU5OYC3t1hg3dzcsGO5qmWB0tQ9Ky+NGwOxsUB4uJjkevddoG9f4NEjqSMjIiIiIiIyOUx2kTja6tVXgbFjxVX6evcW63MFBJT9cykTDIZOvyuckKjuiRoPD3F03N27hh/LZFeB0o7sunAB2LYNOHmybOOxtRXriK1fL9ZW27sXaNUKOHSobJ+HiIiIiIioimOyq7r7+28gMBDYvFkcJTR/vjj6qlat8nm+0iYYrKwACwv1xyDDdesGDB4MuLpKHYn0lNeRoYnXbduAYcPE6b3lITxcrJHXuLGY0AwJAaZOFRPRREREREREVCImu6orQRDrcQUFAZcvA3XriqvDzZghrnxYXkqb7JLJWG+qLMyfD3z7rfi+V2f5+WKhf6D0dc/KM+naqhVw+jTw+uvi9zExYlL677/L7zmJiIiIiIiqCCa7qqPUVGD4cOC118Q/+Hv3FgvTt29f/s9d2mRX4WOq+8iu334D2rQpSISQ4QpfQ5Ux2aV8npUrgR9/BNzcgPPnxfd90SIxWUdERERERERaMdlV3fz1l1iLa9s2cVrgokXitMXatSvm+Y0pCq6cblbdk13374v1oi5eLN3xCgWL/NvaAn/+CfzyCyCXG3ZsRY8wfOEF4OxZ4MUXxcUJ3n5bnI5661bFPD8REREREZGJYbKrulAogGXLgLZtgatXgXr1gN9/B6ZPL99pi0WVxciujIyyi8cUGXMOp00Ta7PNmVOmIZkcCwtxlNTzzxu+2qgUSVcXF2DXLuDzz8X3/ddfgWeeAb78UpySTERERERERCpMdlUHd+8CvXoBb74pjgzp108c4dW2bcXH0rUrMGFC6VZ6PHZMnL4VGlr2cZmS0hZWBwpGMVX30XHGkGo6rUwGjBkj1u0KDhanI48aJSbszp+v2FiIiIiIiIgqMSa7qrrt24GWLYGffwasrcXRXbt3l99qiyV59VVg9Wqge3fDj7W2rthRaJWVMVNBWeRfdPs28MknwDffGH6s1OewQQOxbtv8+YCNjTjKy98feOstvq9E1dDjx48xYsQIODg4wMnJCWPGjMHTEn4XZGVlYeLEiahduzbs7e0xcOBAJCYmam376NEj1K1bFzKZDMnJyeXwCoiIiIjKHjMHVVVysphYGjIEePJEXMntr7+AiAjDp21R5cIi/8a7eFFMDi1YYPixfn7A+vXA4sVlH5e+LCzElVMvXgT69wfy8sTknZ+fmODm1EaiamPEiBE4f/48Dhw4gD179uC3337D+PHjiz1m6tSp+OGHH7B9+3b8+uuvuHfvHgYMGKC17ZgxY/DMM8+UR+hERERE5YbJrqro8GGxns+mTeJIqPfeE6cA+vlJHRmQkAA8elS61eTWrQMGDwa++67s4zIlxkxjZLJLZMw5dHUFwsOBPn3KNqbS8PYWa3n9+CPg6ytOWR4yRJzqe/my1NERUTm7ePEi9u3bh88//xxBQUHo0KEDli1bhq1bt+LevXtaj0lJScEXX3yBJUuWoGvXrggICMCGDRtw7NgxHD9+XK3tqlWrkJycjOnTp1fEyyEiIiIqM0x2VSVZWWIB8q5dgTt3xOlOf/wBvP8+YGkpdXSi558HnJ3FuAz111/Ajh3iynTVmaUlULMm4Oho+LFc0VJkzFTQyuiFF4Bz54DoaLEu24ED4vTlqCjg8WOpoyOichIbGwsnJycEBgaq9oWEhMDMzAx//vmn1mPi4uKQm5uLkJAQ1T4/Pz/Uq1cPsbGxqn0XLlzA+++/j6+++gpmepQQyM7ORmpqqtpGREREJBUmu6qKY8fEou9Llojfjx8PnDkjFrKuTMpiCl51r0u0cKGYwJgxw/BjeQ5FxlyHeXnATz+J0wXz8so2LmPY2IirbJ47Jy5IkZMDfPwxUL8+MHs2k15EVVBCQgJcXV3V9llYWKBWrVpISEjQeYyVlRWcnJzU9ru5uamOyc7OxvDhw7Fo0SLUq1dPr1jmz58PR0dH1ebl5WX4CyIiIiIqI0x2mbqUFGDiRKBDB+DCBXGK1Q8/AGvWlG6KVnkri+Lq1X1UkjE8PYGePYH27aWORFrGJLsUCnEk1ZAhQFpa2cZVFho2FKc1/u9/4nTm1FTggw8AHx9xSjOTXkSV3owZMyCTyYrdLl26VG7PHxUVhaZNm+KVV14x6JiUlBTVdufOnXKLj4iIiKgkFlIHQEbYvVtMdCnrcoSHi0WqpVppUR/G1EriFDzjBQSIo5KqO2OuQysrcSppbq6YvK1Zs2xjKwsyGdCvn1hXbPduYO5c4J9/gA8/BJYuBSZPBqZOrdy/K4iqsWnTpmHUqFHFtvH19YW7uzuSkpLU9ufl5eHx48dwd3fXepy7uztycnKQnJysNrorMTFRdcwvv/yCs2fPYseOHQAA4b9FL5ydnfHuu+9i7ty5Go8rl8shl8v1fYlERERE5YrJLlN07x4waRKwc6f4fcOG4kiurl2ljaskeXni1CqA0xiNMW4ccP068NFHQNu2Ukdjmoyt2WVnJ654WtkTr2ZmwIAB4oqN//ufOM2xcNIrIgKYMEEsdE9ElYaLiwtcXFxKbBccHIzk5GTExcUhICAAgJioUigUCAoK0npMQEAALC0tcejQIQwcOBAAEB8fj9u3byP4v9IH3333HTIzM1XHnDx5EqNHj8bvv/+OBg0aGPvyiIiIiModpzGaEoVCTGo1ayYmuiwsxALU//xT+RNdgHpigNMYS+/PP4FffjEu6ffff+mrrddfF4u4jx1buuNN7Vo0MwNeeklc5GHnTnF6Y1oaMH++WNOrVy9xf26u1JESkQGaNm2Knj17Yty4cThx4gSOHj2KiIgIDBs2DB4eHgCAu3fvws/PDydOnAAAODo6YsyYMYiMjMThw4cRFxeH8PBwBAcHo+1//0Bp0KABWrRoodrq16+ver6iNcKIiIiIKiMmu0zF6dNAp07Aa6+Jdbpatwbi4oB588TC1KZAmZwxNxenghmK0xhFxoxKevRIPI8WFmLytLry9QVCQgA/v9Idb2rJLqWiSa+uXcXE5759wMCBQN26wDvvAFeuSB0pEelp8+bN8PPzQ7du3fDCCy+gQ4cOWLt2rer+3NxcxMfHIyMjQ7Xv008/RZ8+fTBw4EB06tQJ7u7u2KkcLU5ERERUBcgEoXoM8UhNTYWjoyNSUlLg4OAgdTj6S0wE3n0XWL9e/KPUzk5McE2cKCaNTMmDB+JrUSiAzz83/PicHCA7G7C1Nb3XXpbc3ICkJODvv8UROobIyChI1KSlVc5FDEzBc8+JCaO9e8VRUabs6lXgiy+ADRvE3zdKXbqII9969waKrNpGRAVMtn9RznheiIiIqDzo28eQbGTXihUr4OPjA2trawQFBamG1+uyfft2+Pn5wdraGi1btsTevXsrKFKJ5OSIxeYbNRL/EBUE4OWXgYsXgTffNM1kj4sLsHZt6RJdgDgarEYN03ztZcmYlQRtbMTi5YUfpzrauRNYvRq4dq10x1elUYYNG4rTGe/cEc9Lr17iNXLkCPDKK+LPbdeuwJIlwOXLUkdLRERERERUIkmSXdu2bUNkZCSio6Nx+vRptGrVCqGhoRorCikdO3YMw4cPx5gxY/DXX3+hf//+6N+/P86dO1fBkVcAQQB++AFo0QJ46y1x9E1gIHD0KLB5M+DlJXWEJCWFwriVBGUycWQcUL0L/X/6qVi366+/Snd8ZCSwbp04wquqsLQUpzju3QvcvAlER4vTPPPygMOHgWnTgCZNxAT81KnAoUMFC04QERERERFVIpJMYwwKCkLr1q2xfPlyAIBCoYCXlxcmTZqEGTNmaLQfOnQo0tPTsWfPHtW+tm3bwt/fH6tXr9brOct7OL0gABnX7iP9rO6RIubN/GBd11n8JjER6X8XqYtz5w7wxXrgnzMwgwI2ro7ABx8AISGabQsxa9wQNj7/LTH++DEyTl2ArjdV5usL24Zi0VokJyPjxDndbX18YNu4rvhNWhoyj/8Nha7Gdb1g1+y/Fd0yMpB59LRm2+xswKkm0LIl7JwsVbuzsoD8fJ0vr2AA04MHyJo5F/nHTwGLP9Fs2KIFbOs4iQOX7t5F9qXryMuXaX/QZs1g61lLbJuQgOzzV3S3bdIENl4uMDMDkJSEnLPxyNXVtlEj2Hi7iW0fPkTO3xd1t23QENY+7uJAtSdPkHP6nO62PvVh3cAT5lnpgJsrcmGBnGt3dSa85HKxLBcg1hxXy0k0bwY8fAB8uhR46SXInWzEtjduIO/mHWTn6siBt/KHVS17WFoCuHULeddv6W7bsiWsnB3Ftv/+i/wr15Glq23z5rB0qSmWcbt/H/mXruhu6+cHS3dnsW1iIhQX45GZo6Nto0aw9HQT2z54AMX5iwVtp08Hrl8DtmwFunUDIJ4vuVy8WxDEGZ+6qNpeugQhMQkZ2TpiaBMEc2tLWFtDrIN1/z7Ss3S0DQiEuZ212Pb6deDff3W39X8WZjXsxHJ9N28Ct2/rbtuqFcwcaoht79wBbtxARpaZ9p/7Fi0gc3IS86H37gFXryLjRiKEuNPAyZPAuXOAUPDDKrO1g21gMzEp5uyMzPpNoajlXDB6UKlJE8DZRfxZTkoCLl1CZraZ9t8njRoBrm5i20ePgPPnkZUjQ75Cy8+GbwOgTh2x7ZMnwNmzutv61Ac8PWFrC8jSUoEzZ5CdK9P+c+9VD6hXT2ybkQ7Exelu6+EJ1K8PGxvALDsTOHkSObky7T/LdeoAvg3Etnk5wPHjyMkBcrPzgZz/flDzcsUfWvsagJsbrBUZMFfkAufPIyfPDLkKLe+zgyNQzwvWlgqYmwnA2bPIzTdDTr6WtjUcAO96kFsqYGEOsW2eTHtbO3ugvk9B2/PnkZejQHa+ltG11jZAwwawshBgaSEAFy8iLytPe1u5NdCoYUHb+HjkZ+YgK09LW0sroEljWJoLsLIUgCtXkJ+epb2tuTnQtGlB22vXoEhLR2aeBeye84Nt9/aQWVlqHmckTtfTjueFiIiIyoO+fYwKT3bl5OTA1tYWO3bsQP/+/VX7w8LCkJycjP/9738ax9SrVw+RkZGYMmWKal90dDR2796Nv//+W+vzZGdnIzs7W/V9amoqvLy8yq3TlZ7O8kdERESV1dM7T2BXt2aZPy6TOtrxvBAREVF5qLQ1ux4+fIj8/Hy4ubmp7Xdzc0NCQoLWYxISEgxqDwDz58+Ho6OjavPi9D8iIqLqy4wLUBMRERFVFxZSB1BeoqKiEBkZqfpeObKrvNjaiiWQiqtXbW4OcYrS48dATAzSV34JZP03V6pjJ2BGlFifC2Kf3Mam4NjiHrdo24wMcRqWNoVLNhnaNjNTLBmlS+F66Ya01Xsaox5tbW0LZlBlZ4vlhsqirY1Nwd9JOTniLKOyaGttXVBv35C2GlMTiyh2GmMxbfPyxHOhi5WVWNrJ0Lb5+eJ7p4ulpdje0LYKhXitlUXbUk1j1KOt6uf+P3r9jtCjbaX8HfEoA4p/zgFn/gLOnAH++Qe4eQvIFS8UOxScqExYQ1H4/y0WVkBNJ6BmTcCpJuycbcTbNjbIktkg3+K/C8rCUvxqaSG+EYIAO7Ms8YLMzUVWpoD8nDzx+7z/LqaMdOBpOpCRDtvMx+LUxKdPkZ2eh7zUDLWpmYXZIgPKyYjZsEKero9MmTlsalrDrKYj4OSEHAdn5DrWFqcXOjmKC2vY1wBq2AP2NWBT2xZmjjWAGjWQI6+BXEsbcWqflZXGFFD+jhAZ+zvCzg6wtXXUfRARERERVSkVnuxydnaGubk5EgsvcQ8gMTER7u7uWo9xd3c3qD0AyOVyyJV/jVYAmUzsTBe7QN7Tp0DMUmDRIiAlBXYAEBQEfPSRqm6QLoYsvMe2Vb+tKTJkFoshbWvUKJ+2hkxLNqRtZbh+yq+tLVCvDdCnTcFOhQK4f1+sQ1Zos7t+HbhxA3jw4L/EFIAH94AHWh5X/xBK39bC4r9Em5P65ugI1K4Nu5o1gVq1xK3obXt7tSRVucXL3xGlamvIzz0RERERVQ0VnuyysrJCQEAADh06pKrZpVAocOjQIURERGg9Jjg4GIcOHVKr2XXgwAEEBwdXQMRlICUFWLlSXAHuwX9/ybVsKSa5+vTRLOZMRFRVmJkBnp7i1rGj5v2CIA5Le/xY+5aZKQ49KrophznJZP+N9Cq0WVgU3La2FpNRhTc7O/Xv/xtBxt/FRERERERVgyTTGCMjIxEWFobAwEC0adMGMTExSE9PR3h4OABg5MiR8PT0xPz58wEAkydPRufOnbF48WL07t0bW7duxalTp7B27VopwtdfUhIQEwOsWAGkpor7GjYE3n8fGDqU9UOIiGSygqRTvXpSR0NERERERFWAJMmuoUOH4sGDB5g9ezYSEhLg7++Pffv2qYrQ3759G2aFEkHt2rXDli1bMGvWLMycORONGjXC7t270aJFCynCL9mtW8AnnwCff15QWKRZM2DGDGDYsIIiJUREREREREREVKZkgqCr9HDVUiFLYF+8CCxYAGzeXFDtvE0bYOZMoG9fjuQiIiKqYiqkf2GCeF6IiIioPOjbx6iyqzFWuNmzgQ8/LFi2rFs3ICoK6NqVdWCIiIiIiIiIiCoIk11lJSBATHT17y8mudq0KfEQIiIiIiIiIiIqW0x2lZW+fcVpjH5+UkdCRERERERERFRtsYhUWTEzY6KLiIiIiIiIiEhiTHYREREREREREVGVwWQXERERERERERFVGUx2ERERERERERFRlcFkFxERERERERERVRlMdhERERERERERUZXBZBcREREREREREVUZFlIHUFEEQQAApKamShwJERERVRXKfoWyn0Ei9ruIiIioPOjb96o2ya60tDQAgJeXl8SREBERUVWTlpYGR0dHqcOoNNjvIiIiovJUUt9LJlSTf0UqFArcu3cPNWrUgEwmK5fnSE1NhZeXF+7cuQMHB4dyeY6qjufQeDyHxuM5LBs8j8bjOTReeZ9DQRCQlpYGDw8PmJmxOoQS+12mgefQeDyHZYPn0Xg8h8bjOTReRZxDffte1WZkl5mZGerWrVshz+Xg4MAfDiPxHBqP59B4PIdlg+fReDyHxivPc8gRXZrY7zItPIfG4zksGzyPxuM5NB7PofHK+xzq0/fivyCJiIiIiIiIiKjKYLKLiIiIiIiIiIiqDCa7ypBcLkd0dDTkcrnUoZgsnkPj8Rwaj+ewbPA8Go/n0Hg8h1UX31vj8Rwaj+ewbPA8Go/n0Hg8h8arTOew2hSoJyIiIiIiIiKiqo8ju4iIiIiIiIiIqMpgsouIiIiIiIiIiKoMJruIiIiIiIiIiKjKYLKLiIiIiIiIiIiqDCa7ysiKFSvg4+MDa2trBAUF4cSJE1KHZFJ+++039O3bFx4eHpDJZNi9e7fUIZmc+fPno3Xr1qhRowZcXV3Rv39/xMfHSx2WSVm1ahWeeeYZODg4wMHBAcHBwfjpp5+kDsukffzxx5DJZJgyZYrUoZiMOXPmQCaTqW1+fn5Sh2WS7t69i1deeQW1a9eGjY0NWrZsiVOnTkkdFpUB9ruMw36X8djvMh77XWWP/a7SYd+rbFS2fheTXWVg27ZtiIyMRHR0NE6fPo1WrVohNDQUSUlJUodmMtLT09GqVSusWLFC6lBM1q+//oqJEyfi+PHjOHDgAHJzc9GjRw+kp6dLHZrJqFu3Lj7++GPExcXh1KlT6Nq1K1588UWcP39e6tBM0smTJ7FmzRo888wzUodicpo3b4779++rtj/++EPqkEzOkydP0L59e1haWuKnn37ChQsXsHjxYtSsWVPq0MhI7HcZj/0u47HfZTz2u8oW+13GYd/LOJWx3yUTBEGQ7NmriKCgILRu3RrLly8HACgUCnh5eWHSpEmYMWOGxNGZHplMhl27dqF///5Sh2LSHjx4AFdXV/z666/o1KmT1OGYrFq1amHRokUYM2aM1KGYlKdPn+K5557DypUr8eGHH8Lf3x8xMTFSh2US5syZg927d+PMmTNSh2LSZsyYgaNHj+L333+XOhQqY+x3lS32u8oG+11lg/2u0mG/yzjsexmvMva7OLLLSDk5OYiLi0NISIhqn5mZGUJCQhAbGythZFTdpaSkABA7DWS4/Px8bN26Fenp6QgODpY6HJMzceJE9O7dW+13I+nvypUr8PDwgK+vL0aMGIHbt29LHZLJ+f777xEYGIjBgwfD1dUVzz77LNatWyd1WGQk9ruosmK/yzjsdxmH/S7jse9lnMrY72Kyy0gPHz5Efn4+3Nzc1Pa7ubkhISFBoqioulMoFJgyZQrat2+PFi1aSB2OSTl79izs7e0hl8vx2muvYdeuXWjWrJnUYZmUrVu34vTp05g/f77UoZikoKAgbNy4Efv27cOqVatw48YNdOzYEWlpaVKHZlKuX7+OVatWoVGjRti/fz9ef/11vPnmm/jyyy+lDo2MwH4XVUbsd5Ue+13GY7/LeOx7Ga8y9rssJHtmIio3EydOxLlz5zjXvBSaNGmCM2fOICUlBTt27EBYWBh+/fVXdrz0dOfOHUyePBkHDhyAtbW11OGYpF69eqluP/PMMwgKCoK3tze+/fZbTuswgEKhQGBgIObNmwcAePbZZ3Hu3DmsXr0aYWFhEkdHRFUJ+12lx36XcdjvKhvsexmvMva7OLLLSM7OzjA3N0diYqLa/sTERLi7u0sUFVVnERER2LNnDw4fPoy6detKHY7JsbKyQsOGDREQEID58+ejVatWWLp0qdRhmYy4uDgkJSXhueeeg4WFBSwsLPDrr7/is88+g4WFBfLz86UO0eQ4OTmhcePGuHr1qtShmJQ6depo/LHUtGlTTkswcex3UWXDfpdx2O8yDvtd5YN9L8NVxn4Xk11GsrKyQkBAAA4dOqTap1AocOjQIc43pwolCAIiIiKwa9cu/PLLL6hfv77UIVUJCoUC2dnZUodhMrp164azZ8/izJkzqi0wMBAjRozAmTNnYG5uLnWIJufp06e4du0a6tSpI3UoJqV9+/aIj49X23f58mV4e3tLFBGVBfa7qLJgv6t8sN9lGPa7ygf7XoarjP0uTmMsA5GRkQgLC0NgYCDatGmDmJgYpKenIzw8XOrQTMbTp0/VMuc3btzAmTNnUKtWLdSrV0/CyEzHxIkTsWXLFvzvf/9DjRo1VLVLHB0dYWNjI3F0piEqKgq9evVCvXr1kJaWhi1btuDIkSPYv3+/1KGZjBo1amjUK7Gzs0Pt2rVZx0RP06dPR9++feHt7Y179+4hOjoa5ubmGD58uNShmZSpU6eiXbt2mDdvHoYMGYITJ05g7dq1WLt2rdShkZHY7zIe+13GY7/LeOx3GY/9rrLBvpfxKmW/S6AysWzZMqFevXqClZWV0KZNG+H48eNSh2RSDh8+LADQ2MLCwqQOzWRoO38AhA0bNkgdmskYPXq04O3tLVhZWQkuLi5Ct27dhJ9//lnqsExe586dhcmTJ0sdhskYOnSoUKdOHcHKykrw9PQUhg4dKly9elXqsEzSDz/8ILRo0UKQy+WCn5+fsHbtWqlDojLCfpdx2O8yHvtdxmO/q3yw32U49r3KRmXrd8kEQRAqMrlGRERERERERERUXlizi4iIiIiIiIiIqgwmu4iIiIiIiIiIqMpgsouIiIiIiIiIiKoMJruIiIiIiIiIiKjKYLKLiIiIiIiIiIiqDCa7iIiIiIiIiIioymCyi4iIiIiIiIiIqgwmu4iIiIiIiIiIqMpgsouIiIiIiIiIiKoMJruIiIiIiIiIiKjKYLKLqJrx8fFBnz59pA6j1Lp06YIWLVpIHUalM2rUKPj4+JTpY3bp0gVdunQp08eszM9LRERUVHl8vpbWxo0bIZPJcOrUKalDKZUjR45AJpNhx44dUodSqdy8eRMymQwbN24ss8dUnusjR46U2WNW5ucl0obJLqJSuHbtGiZMmABfX19YW1vDwcEB7du3x9KlS5GZmVnmz5eRkYE5c+bo/cFx4cIFzJkzBzdv3izzWKqzvXv3Ys6cOZI9/7179zBnzhycOXNGshjKCq9RIqKq6+zZsxg0aBC8vb1hbW0NT09PdO/eHcuWLVNrN2/ePOzevVuaICuxlStXlmnigwzvS5eHLVu2ICYmRrLnL0u8RskUWEgdAJGp+fHHHzF48GDI5XKMHDkSLVq0QE5ODv744w+89dZbOH/+PNauXVumz5mRkYG5c+cCgF4jXi5cuIC5c+eiS5culea/kVXB3r17sWLFCskSXvfu3cPcuXPh4+MDf39/tfvWrVsHhUJRps/3888/l+njFVbcNVqez0tEROXr2LFjeP7551GvXj2MGzcO7u7uuHPnDo4fP46lS5di0qRJqrbz5s3DoEGD0L9/f+kCLkF5fL6WZOXKlXB2dsaoUaMq9HmrMkP70uVhy5YtOHfuHKZMmaK239vbG5mZmbC0tCyz5+rUqRMyMzNhZWVVZo9ZmK5rtLyfl8gQTHYRGeDGjRsYNmwYvL298csvv6BOnTqq+yZOnIirV6/ixx9/lDDC8pWeng47OzupwyAtyrKDpCRVR4UdJCIi0/XRRx/B0dERJ0+ehJOTk9p9SUlJ0gRlhPL4fJWCIAjIysqCjY2N1KFQETKZDNbW1mX6mGZmZmX+mJX5eYm04TRGIgMsXLgQT58+xRdffKGW6FJq2LAhJk+erPo+Ly8PH3zwARo0aAC5XA4fHx/MnDkT2dnZasedOnUKoaGhcHZ2ho2NDerXr4/Ro0cDEOfxu7i4AADmzp0LmUwGmUymc3TRxo0bMXjwYADA888/r2pfdNj2H3/8gTZt2sDa2hq+vr746quvNB5HJpPh119/xRtvvAFXV1fUrVtXdf/KlSvRvHlzyOVyeHh4YOLEiUhOTlZ7DB8fH63/ldRWk+nWrVvo168f7Ozs4OrqiqlTp2L//v065/1fuHABzz//PGxtbeHp6YmFCxdqtElKSsKYMWPg5uYGa2trtGrVCl9++aVaG121BYrWTxg1ahRWrFgBAKpzKpPJNJ6zKH3Ok7IOWVxcHNq1a6e6BlavXq0WZ+vWrQEA4eHhqucvHF/hEVLK+D/55BOsWLECvr6+sLW1RY8ePXDnzh0IgoAPPvgAdevWhY2NDV588UU8fvxYI67C75OPj4/aay+8Kc/frVu38MYbb6BJkyawsbFB7dq1MXjwYLXpiiVdo9quD33ey8Kvee3ataqfu9atW+PkyZMlvldERGS8a9euoXnz5hqJLgBwdXVV3ZbJZEhPT8eXX36p+hwo3Ge4e/cuRo8eDTc3N8jlcjRv3hzr169XezzlZ/i2bdswc+ZMuLu7w87ODv369cOdO3dKjDUtLQ1TpkyBj48P5HI5XF1d0b17d5w+fVrVpujna5cuXXR+Fhae1pWcnIwpU6bAy8sLcrkcDRs2xIIFC0ocJebj44Pz58/j119/VT1u0c/E7OxsREZGwsXFBXZ2dnjppZfw4MEDjcfp06cP9u/fj8DAQNjY2GDNmjUAgOvXr2Pw4MGoVasWbG1t0bZtW41/1ir7gUXLDejqNyn7GjY2NmjTpg1+//13nTU4FQoFPvroI9StWxfW1tbo1q0brl69qtFu+/btCAgIgI2NDZydnfHKK6/g7t27am10PUfh983QvrSSPudJ32uwS5cu+PHHH3Hr1i3V8xeOr+j1M2rUKNjb2+P27dvo06cP7O3t4enpqeqLnj17Fl27doWdnR28vb2xZcsWrXEp3yfl+6ltK3z+NmzYgK5du8LV1RVyuRzNmjXDqlWr1B67uGtU1/Whz3upfM13795F//79YW9vDxcXF0yfPh35+fnFvldE2nBkF5EBfvjhB/j6+qJdu3Z6tR87diy+/PJLDBo0CNOmTcOff/6J+fPn4+LFi9i1axcA8Y/4Hj16wMXFBTNmzICTkxNu3ryJnTt3AgBcXFywatUqvP7663jppZcwYMAAAMAzzzyj9Tk7deqEN998E5999hlmzpyJpk2bAoDqKwBcvXoVgwYNwpgxYxAWFob169dj1KhRCAgIQPPmzdUe74033oCLiwtmz56N9PR0AMCcOXMwd+5chISE4PXXX0d8fDxWrVqFkydP4ujRowb/FzQ9PR1du3bF/fv3MXnyZLi7u2PLli04fPiw1vZPnjxBz549MWDAAAwZMgQ7duzAO++8g5YtW6JXr14AgMzMTHTp0gVXr15FREQE6tevj+3bt2PUqFFITk5WS0rqY8KECbh37x4OHDiAr7/+Wq9jDDlPT548wQsvvIAhQ4Zg+PDh+Pbbb/H666/DysoKo0ePRtOmTfH+++9j9uzZGD9+PDp27AgAJV6LmzdvRk5ODiZNmoTHjx9j4cKFGDJkCLp27YojR47gnXfewdWrV7Fs2TJMnz5d4w+JwmJiYvD06VO1fZ9++inOnDmD2rVrAwBOnjyJY8eOYdiwYahbty5u3ryJVatWoUuXLrhw4QJsbW31ukYLM/S93LJlC9LS0jBhwgTIZDIsXLgQAwYMwPXr16vMf+iJiCorb29vxMbG4ty5c8UuKPP1119j7NixaNOmDcaPHw8AaNCgAQAgMTERbdu2hUwmQ0REBFxcXPDTTz9hzJgxSE1N1ZgG9tFHH0Emk+Gdd95BUlISYmJiEBISgjNnzhQ7kum1117Djh07EBERgWbNmuHRo0f4448/cPHiRTz33HNaj3n33XcxduxYtX2bNm3C/v37Vcm8jIwMdO7cGXfv3sWEuUI9MAAAZdpJREFUCRNQr149HDt2DFFRUbh//36xdZtiYmIwadIk2Nvb49133wUAuLm5qbWZNGkSatasiejoaNy8eRMxMTGIiIjAtm3b1NrFx8dj+PDhmDBhAsaNG4cmTZogMTER7dq1Q0ZGBt58803Url0bX375Jfr164cdO3bgpZde0hmbLqtWrUJERAQ6duyIqVOn4ubNm+jfvz9q1qyp9o9SpY8//hhmZmaYPn06UlJSsHDhQowYMQJ//vmnqs3GjRsRHh6O1q1bY/78+UhMTMTSpUtx9OhR/PXXX1qTqboY2pcGYPB5KukafPfdd5GSkoJ///0Xn376KQDA3t6+2Ljz8/PRq1cvdOrUCQsXLsTmzZsREREBOzs7vPvuuxgxYgQGDBiA1atXY+TIkQgODkb9+vW1PlanTp00+q+3bt3CrFmz1JLQq1atQvPmzdGvXz9YWFjghx9+wBtvvAGFQoGJEycC0O8aLcyQ9zI/Px+hoaEICgrCJ598goMHD2Lx4sVo0KABXn/99WLPF5EGgYj0kpKSIgAQXnzxRb3anzlzRgAgjB07Vm3/9OnTBQDCL7/8IgiCIOzatUsAIJw8eVLnYz148EAAIERHR+v13Nu3bxcACIcPH9a4z9vbWwAg/Pbbb6p9SUlJglwuF6ZNm6bat2HDBgGA0KFDByEvL0+trZWVldCjRw8hPz9ftX/58uUCAGH9+vVqzxUWFqYRQ+fOnYXOnTurvl+8eLEAQNi9e7dqX2ZmpuDn56fxOjp37iwAEL766ivVvuzsbMHd3V0YOHCgal9MTIwAQNi0aZNqX05OjhAcHCzY29sLqampgiAIwuHDh7Weqxs3bggAhA0bNqj2TZw4UdD316Yh50n5mhYvXqz2mvz9/QVXV1chJydHEARBOHnypEZMSmFhYYK3t7dG/C4uLkJycrJqf1RUlABAaNWqlZCbm6vaP3z4cMHKykrIyspSi6vw+1TUt99+KwAQ3n//fdW+jIwMjXaxsbEa71lx12jR59X3vVS+5tq1awuPHz9Wtf3f//4nABB++OEHna+FiIjKxs8//yyYm5sL5ubmQnBwsPD2228L+/fvV32WFWZnZ6e1nzBmzBihTp06wsOHD9X2Dxs2THB0dFR91ig/wz09PVWfBYJQ8Pm0dOnSYmN1dHQUJk6cWGybop+vRR09elSwtLQURo8erdr3wQcfCHZ2dsLly5fV2s6YMUMwNzcXbt++XexzNm/eXOvnr7JvFhISIigUCtX+qVOnCubm5mqf98r+3r59+9QeY8qUKQIA4ffff1ftS0tLE+rXry/4+Pio+izK57px44ba8UX7TdnZ2ULt2rWF1q1bq/UrNm7cKABQex3KY5s2bSpkZ2er9i9dulQAIJw9e1YQBPEz3tXVVWjRooWQmZmpardnzx4BgDB79mzVPl19laLvm6F9aX3PkyHXYO/evbVeS9r6nGFhYQIAYd68eap9T548EWxsbASZTCZs3bpVtf/SpUsar01X/1YpMzNTCAgIEDw8PIT79++r9mvrx4WGhgq+vr5q+3Rdo0Wf15D3UvmaC/crBUEQnn32WSEgIEDr6yAqDqcxEukpNTUVAFCjRg292u/duxcAEBkZqbZ/2rRpAKAaBq38b8aePXuQm5tbFqGWqFmzZqqRQYD4H68mTZrg+vXrGm3HjRsHc3Nz1fcHDx5ETk4OpkyZAjMzM7V2Dg4OpapZtm/fPnh6eqJfv36qfdbW1hg3bpzW9vb29njllVdU31tZWaFNmzZq8e/duxfu7u4YPny4ap+lpSXefPNNPH36FL/++qvBcRrC0PNkYWGBCRMmqL63srLChAkTkJSUhLi4uFLHMXjwYDg6Oqq+DwoKAgC88sorsLCwUNufk5OjMaRclwsXLmD06NF48cUXMWvWLNX+wv9Bz83NxaNHj9CwYUM4OTmpTQsxhKHv5dChQ1GzZk3V98prXdv1TUREZat79+6IjY1Fv3798Pfff2PhwoUIDQ2Fp6cnvv/++xKPFwQB3333Hfr27QtBEPDw4UPVFhoaipSUFI3Pk5EjR6r1zwYNGoQ6deqo+mK6ODk54c8//8S9e/dK9VoTEhIwaNAg+Pv7Y+XKlar927dvR8eOHVGzZk21+ENCQpCfn4/ffvutVM+nNH78eLVSCh07dkR+fj5u3bql1q5+/foIDQ1V27d37160adMGHTp0UO2zt7fH+PHjcfPmTVy4cMGgWE6dOoVHjx5h3Lhxav2KESNGqH0WFxYeHq5Wn7Po5/SpU6eQlJSEN954Q63+U+/eveHn51ch9XENPU+lvQZLUngUoZOTE5o0aQI7OzsMGTJEtb9JkyZwcnIyqJ/zxhtv4OzZs/juu+/g7u6u2l+4H5eSkoKHDx+ic+fOuH79OlJSUgyOvzTv5Wuvvab2fceOHdmHo1Kplsmu3377DX379oWHhwdkMlm5L3msq86NcigomQYHBwcAYn0Hfdy6dQtmZmZo2LCh2n53d3c4OTmpOiSdO3fGwIEDMXfuXDg7O+PFF1/Ehg0bNOp6laV69epp7KtZsyaePHmisb/ocGhl3E2aNFHbb2VlBV9fX42Olj5u3bqFBg0aaNTAKnrulOrWravRtmj8t27dQqNGjdQSTUDBVLnSxGkIQ8+Th4eHRvH/xo0bA4BGvQxDFH2vlYkvLy8vrfu1XQNFpaamYsCAAfD09MRXX32l9l5kZmZi9uzZqholzs7OcHFxQXJycqk6SYDh72XR16zsbOvz2oio7JVFv0sQBHzyySdo3Lgx5HI5PD098dFHH5V9sFQmWrdujZ07d+LJkyc4ceIEoqKikJaWhkGDBpWYTHnw4AGSk5Oxdu1auLi4qG3h4eEANAvdN2rUSO17mUyGhg0blvj5uXDhQpw7dw5eXl5o06YN5syZo/cf1Xl5eRgyZAjy8/Oxc+dOyOVy1X1XrlzBvn37NOIPCQnRGr+h9P2c0zal7datWxp9E6D0/SNl+6J9NgsLC50rgpcUv64+FAD4+fmVex9OGYMh56m012BxrK2tVbXGlBwdHbX2gx0dHfXu56xZswYbNmzAsmXL0LZtW7X7jh49ipCQENjZ2cHJyQkuLi6YOXMmAJSqH2foe6ntNev6G4WoJNWyZld6ejpatWqF0aNHq+Zsl6eTJ0+qFdU7d+4cunfvrirQTKbBwcEBHh4eOHfunEHHlVTEXCaTYceOHTh+/Dh++OEH7N+/H6NHj8bixYtx/PjxEufzl0bhkVqFCYKgsc+YVXt0vfb8/HydMejDkPhLUlyMVYGuc2XMORw1ahTu3buHEydOqJLASpMmTcKGDRswZcoUBAcHw9HRETKZDMOGDauwpdvL8vogIuOVRb9r8uTJ+Pnnn/HJJ5+gZcuWePz4scaiGlT5WFlZoXXr1mjdujUaN26M8PBwbN++HdHR0TqPUX5WvPLKKwgLC9PaprhaS4YYMmQIOnbsiF27duHnn3/GokWLsGDBAuzcuVNVA1SXt956C7GxsTh48KBGXSqFQoHu3bvj7bff1nqs8p9ZpaXv51x59eGMVdb9OG3HVYV+XHn04U6cOIHJkydj7Nixqlp5SteuXUO3bt3g5+eHJUuWwMvLC1ZWVti7dy8+/fTTCunHGfP3AVFR1TLZ1atXr2I/wLKzs/Huu+/im2++QXJyMlq0aIEFCxZoXelDH0Wz0x9//DEaNGiAzp07l+rxSDp9+vTB2rVrERsbi+Dg4GLbent7Q6FQ4MqVK2qFtxMTE5GcnAxvb2+19m3btkXbtm3x0UcfYcuWLRgxYgS2bt2KsWPH6rXqX2GGtjeEMu74+Hj4+vqq9ufk5ODGjRuq/1oC4n9iiq48CIj/5Sl8rLe3Ny5cuABBENRi17YyjyFx/vPPP1AoFGojgi5duqT2OpT/TSwap7b/GhpyXg05TwBw7949pKenq43uunz5MgCo/jNanu+rvj7++GPs3r0bO3fuhJ+fn8b9O3bsQFhYGBYvXqzal5WVpXF+DT2X+ryXRFQ5GdvvunjxIlatWoVz586pRgfoKsJMlVdgYCAA4P79+6p92j4LXFxcUKNGDeTn52t8Vupy5coVte8FQcDVq1f1SorVqVMHb7zxBt544w0kJSXhueeew0cffVTsNbt161bExMQgJiZGa3++QYMGePr0qd7xF1Xe/bj4+HiN/aXtHynbX716Fc8//7xqf15eHm7evFmqxGThPlTXrl3V7ouPj1f73K9Zs6bW0XhF4zT0nOp7npT0uQal7sc9ePBANe1WuapjYT/88AOys7Px/fffq42+07ZglL6vxZD3kqisVctpjCWJiIhAbGwstm7din/++QeDBw9Gz549NX6JlUZOTg42bdqE0aNHS/4Ljwz39ttvw87ODmPHjkViYqLG/deuXcPSpUsBAC+88AIAaKy4s2TJEgDiXHVAHLJd9D8x/v7+AKCaymhrawtAs8OhizJhom97Q4SEhMDKygqfffaZWtxffPEFUlJSVK8LEDt7x48fR05Ojmrfnj17NJYDDw0Nxd27d9VqeWRlZWHdunWljvOFF15AQkKC2spEeXl5WLZsGezt7VWdU29vb5ibm2vUzyhce0PJkPNqyHlSxqZcEhwQf1esWbMGLi4uCAgIMPj5y8PBgwcxa9YsvPvuu+jfv7/WNubm5hrX87JlyzT+w2rIa9H3vTRESkoKLl26VOqplURUdkrqdylXQt6zZw/q168PHx8fjB07liO7KqnDhw9rHWGirF1UeDqTnZ2dxueAubk5Bg4ciO+++07raPoHDx5o7Pvqq6/Uykzs2LED9+/fLzZhlZ+fr/EZ4OrqCg8Pj2JLSZw7dw5jx47FK6+8onNl5yFDhiA2Nhb79+/XuC85ORl5eXk6Hx/Qfl7KygsvvIATJ04gNjZWtS89PR1r166Fj48PmjVrBqBgZczC/aP8/HysXbtW7fECAwNRu3ZtrFu3Tu11bd68udRTzwIDA+Hq6orVq1ervRc//fQTLl68qNHXvHTpktp18ffff+Po0aNqj2loX1rf86SkzzVoZ2cnWb8jPz8fw4YNQ05ODr777ju1mmlKylFVhX9+U1JSsGHDBo22+l6jhryXhrh27RquXbtWqmOp+qiWI7uKc/v2bWzYsAG3b9+Gh4cHAGD69OnYt28fNmzYgHnz5hn1+Lt370ZycjJGjRpVBtFSRWvQoAG2bNmCoUOHomnTphg5ciRatGiBnJwcHDt2DNu3b1e9t61atUJYWBjWrl2L5ORkdO7cGSdOnMCXX36J/v37q/779eWXX2LlypV46aWX0KBBA6SlpWHdunVwcHBQJcxsbGzQrFkzbNu2DY0bN0atWrXQokULnUt6+/v7w9zcHAsWLEBKSgrkcjm6du2qtrRwabm4uCAqKgpz585Fz5490a9fP8THx2PlypVo3bq1WuH4sWPHYseOHejZsyeGDBmCa9euYdOmTaoOlNKECROwfPlyDB8+HJMnT0adOnWwefNmVSHL0iSGx48fjzVr1mDUqFGIi4uDj48PduzYgaNHjyImJkZVRNTR0RGDBw/GsmXLIJPJ0KBBA+zZs0drPQ1l0unNN99EaGgozM3NMWzYMKPPEyDW7FqwYAFu3ryJxo0bY9u2bThz5gzWrl0LS0tLAOL15+TkhNWrV6NGjRqws7NDUFBQhY1wGD58OFxcXNCoUSNs2rRJ7b7u3bvDzc0Nffr0wddffw1HR0c0a9ZMNcWjdu3aau0NuUb1fS8NsWvXLoSHh2PDhg38fUwkIX36XdevX8etW7ewfft2fPXVV8jPz8fUqVMxaNAg/PLLLxK/Aipq0qRJyMjIwEsvvQQ/Pz9VH2nbtm3w8fFR1d0CxM/VgwcPYsmSJfDw8ED9+vURFBSEjz/+GIcPH0ZQUBDGjRuHZs2a4fHjxzh9+jQOHjyokeisVasWOnTogPDwcCQmJiImJgYNGzbUudANINZgrVu3LgYNGoRWrVrB3t4eBw8exMmTJ9VGJxeljL9Tp04an4Xt2rWDr68v3nrrLXz//ffo06cPRo0ahYCAAKSnp+Ps2bPYsWMHbt68CWdnZ53PERAQgFWrVuHDDz9Ew4YN4erqqjEqprRmzJiBb775Br169cKbb76JWrVq4csvv8SNGzfw3XffqUZQN2/eHG3btkVUVBQeP36MWrVqYevWrRqJOisrK8yZMweTJk1C165dMWTIENy8eRMbN27UWo9VH5aWlliwYAHCw8PRuXNnDB8+HImJiVi6dCl8fHwwdepUVdvRo0djyZIlCA0NxZgxY5CUlITVq1ejefPmqsWlAMP70vqeJyV9rsGAgABs27YNkZGRaN26Nezt7dG3b1+Dz09prF69Gr/88gtee+01jZFabm5u6N69O3r06AErKyv07dsXEyZMwNOnT7Fu3Tq4urqqjchUvhZ9rlFD3ktDdOvWDYBxdW2pGqjYxR8rHwDCrl27VN8rl0G1s7NT2ywsLIQhQ4YIgiAIFy9eFAAUu73zzjtan69Hjx5Cnz59KuKlUTm6fPmyMG7cOMHHx0ewsrISatSoIbRv315YtmyZkJWVpWqXm5srzJ07V6hfv75gaWkpeHl5CVFRUWptTp8+LQwfPlyoV6+eIJfLBVdXV6FPnz7CqVOn1J7z2LFjQkBAgGBlZaXX0snr1q0TfH19BXNzc7UlgL29vYXevXtrtC+6dLNyyemTJ09qffzly5cLfn5+gqWlpeDm5ia8/vrrwpMnTzTaLV68WPD09BTkcrnQvn174dSpU1qXib5+/brQu3dvwcbGRnBxcRGmTZsmfPfddwIA4fjx42pxNm/eXON5tC0NnpiYKISHhwvOzs6ClZWV0LJlS7VlnZUePHggDBw4ULC1tRVq1qwpTJgwQTh37pzGMtB5eXnCpEmTBBcXF0Emkwn6/ArV5zwpX9OpU6eE4OBgwdraWvD29haWL1+u8Xj/+9//hGbNmgkWFhZq8RV9/cplrBctWqR2vHJJ6O3bt6vt1/Z+F32fivudp7y+njx5ojrn9vb2QmhoqHDp0iXB29tbY3l5XdeotutDn/dS12tWxl74Z0b5erVdD0RUfkrT7xo3bpwAQIiPj1cdFxcXJwAQLl26VNEvgUrw008/CaNHjxb8/PwEe3t7wcrKSmjYsKEwadIkITExUa3tpUuXhE6dOgk2NjYCALXPicTERGHixImCl5eXYGlpKbi7uwvdunUT1q5dq2qj/Ez75ptvhKioKMHV1VWwsbERevfuLdy6davYOLOzs4W33npLaNWqlVCjRg3Bzs5OaNWqlbBy5Uq1dkU/X729vXV+Fhb+TElLSxOioqKEhg0bClZWVoKzs7PQrl074ZNPPhFycnKKjS0hIUHo3bu3UKNGDQGA6jNRV99MeR6Un6PKOLX19wRBEK5duyYMGjRIcHJyEqytrYU2bdoIe/bs0douJCREkMvlgpubmzBz5kzhwIEDGs8lCILw2WefCd7e3oJcLhfatGkjHD16VAgICBB69uypEWfRPojy87voZ/K2bduEZ599VpDL5UKtWrWEESNGCP/++69GnJs2bRJ8fX0FKysrwd/fX9i/f7/WfqGhfWl9zpMh1+DTp0+Fl19+WXBychIAqOLT9vrDwsIEOzs7jZh09YOLvt9Fr4no6Gid123hPtf3338vPPPMM4K1tbXg4+MjLFiwQFi/fr0AQLhx44aqna5rVNu1KAj6vZe6XrMy9qKvt+j7S1SUTBCqd8VemUyGXbt2qabkbNu2DSNGjMD58+c1CuTZ29vD3d0dOTk5Ja7UUrt2bY1aXco6RTt37sSLL75Ypq+DqCqKiYnB1KlT8e+//8LT01PqcMpNly5d8PDhQ4MXPyAiMjWl6XdFR0dj3rx5yM3NVd2XmZkJW1tb/Pzzz+jevXtFvgSqRI4cOYLnn38e27dvx6BBg6QOhwpRKBRwcXHBgAEDjCpLUdnxGiSqvDiNsYhnn30W+fn5SEpKQseOHbW2sbKy0lqYuSQbNmyAq6trqecmE1VlmZmZaqsGZWVlYc2aNWjUqFGVTnQREVVn+vS72rdvj7y8PFy7dk01DV65gAeLGxNJLysrC3K5XG3K4ldffYXHjx+XeoEvIiJjVctk19OnT9VWebtx4wbOnDmDWrVqoXHjxhgxYgRGjhyJxYsX49lnn8WDBw9w6NAhPPPMM6VOVCkUCmzYsAFhYWGwsKiWp52oWAMGDEC9evXg7++PlJQUbNq0CZcuXcLmzZulDo2IiIxgbL8rJCQEzz33HEaPHo2YmBgoFApMnDgR3bt3R+PGjSV8ZUQEAMePH8fUqVMxePBg1K5dG6dPn8YXX3yBFi1aYPDgwVKHR0TVVLXMupw6dUptadzIyEgAQFhYGDZu3IgNGzbgww8/xLRp03D37l04Ozujbdu26NOnT6mf8+DBg7h9+zZGjx5tdPxEVVFoaCg+//xzbN68Gfn5+WjWrBm2bt2KoUOHSh0aEREZwdh+l5mZGX744QdMmjQJnTp1gp2dHXr16lVsEXEiqjg+Pj7w8vLCZ599pipmP3LkSHz88cdaV/0jIqoI1b5mFxERERERERERVR1mJTchIiIiIiIiIiIyDUx2ERERERERERFRlVFtanYpFArcu3cPNWrUUFsphIiIiKi0BEFAWloaPDw8YGbG/yEqsd9FRERE5UHfvle1SXbdu3cPXl5eUodBREREVdCdO3dQt25dqcOoNNjvIiIiovJUUt+r2iS7atSoAUA8IQ4ODhJHQ0RERFVBamoqvLy8VP0MErHfRUREROVB375XtUl2KYfQOzg4sNNFREREZYpT9dSx30VERETlqaS+F4tLEBERERERERFRlcFkFxERERERERERVRlMdhERERERERERUZXBZBcREREREREREVUZTHYREREREREREVGVUW1WYyxvF++n4vTtJ6hhbYka1hZwtLFEI1d71LC2lDo0IiIiIiIiIqJqgyO7ysjRqw/x7q5zePObvxC+4SQGrDyGVnN/RviGE7ialCZ1eERERERUCTxJz0Hvz37HF3/ckDqUcrPvXAJ6fPorLt5PlToUk/L3nWR0X/IrjsQnSR1KpZaWlYt+y//AisNXpQ5FcisOX0XfZX8gLStX6lAq1IO0bPRa+ju+PHZT6lDKzY//3EePT3/FlUTmEkqLya4yUremLbo3c0Nb31po7uEAdwdrKATgcPwDvLj8KOJuPZY6RCIiIiKS2MojV3H+Xio+2HNB6lDKzWub4nA58SkmbjktdSgmZdSGE7iS9BSjNpyUOpRK7ctjN/HPvylYtD9e6lAkt2h/PM7eTcFXsbekDqVCfXrwMi7eT0X09+elDqXcTNxyGpcTnyLy27+lDsVkcRpjGenZwh09W7ir7bv+4Cmidp7Fnzce463t/2Dv5I6wtjSXKEIiIiIiklpmbr7UIVSYjOzq81rLQmpWntQhmISsXIXUIVQ6OXnV65xk5VSf3y3pOfy9UFoc2VWOfF3ssXZkIFxqyHH9YTq2nrgtdUhEREREJCFBkDqCiiOTSR2BaRGq08VhBAE8T0VVt5+16nQFVLO3tkwx2VXOHG0s8VrnBgCAvecSJI6GiIiIiKTEP9JIl+p0bRiDOUFNsmr201adEsOy6pbJLENMdlWA0OZuAICTNx/j4dNsiaMhIiIiIqlUo7/RyEC8NvTD00S8BkgfTHZVgLo1bdHC0wGCABy+xNVViIiIiKqv6vNnGkckUHlgUlBTdftRq07XQDV7a8sUk10VJKh+bQDAxftcOpSIiIiouqpOf6QRlQfW7NJU3RIi1ekKqG6JzLLEZFcFaehqDwC4ksRkFxEREVF1VZ2SXfwjjahiVLeftWpVs6vapTLLDpNdFUSZ7LqW9FTiSIiIiIhIKhyVQmQk/ghVe7wESB9MdlWQhi5isuteShbSs/MkjoaIiIiIqHxVt9EmVDGY6NDE+nhVF9/a0mOyq4LUtLOCs70VAODaA47uIiIiIqqOqtHsG06/IaLyUY1+j1LpMdlVgRr8N7rr/+3df3yU1Z3//ffMJJmAGhCRBDAKra3WqgGhpLHbVddoylK+2t0+lq/1Ltxstbct9qvGXStdhXW7a2wrSrulpdZa2t2loLalW7VYiqK3NZUC5q5thVZFoS4JIpVAhPyYue4/wkzmmhlwCHNdZ+ac1/PxmIdkck3mnOvHeJ3PfD7nvEQpIwAAgJNcGqORkYAguDRfU6Fcu9ZcKgcna2/4CHaFaOLJIyRJXd29hlsCAAAABIshGoJArCsXWZT24sgOH8GuEJ1ywmAZ494egl0AACAcTz/9tGbPnq0JEyYoEolozZo1R93+Rz/6kS677DKdeuqpqqmpUVNTkx5//PFwGusAlwbqZCQgCA5dQgVz7VJz63PUdAvKF8GuEI05IS5JerOnz3BLAACAK3p6etTQ0KBly5YVtP3TTz+tyy67TI899pg2b96sSy65RLNnz9bzzz8fcEvd4FT5jekGwEouBToK5dq15tI5QLBr+CpMN8AlQ5ldBLsAAEA4Zs6cqZkzZxa8/dKlS30/33nnnfrJT36in/70p5o6dWqRW+cghwZpQBBcChgjP84BFIJgV4jGHA52vXmAYBcAACgPyWRS+/fv15gxY464TW9vr3p7h6Zp6O7uDqNpZcmpIRoZCQiAS1k9hXIt+8elc4D52IaPMsYQjTmRzC4AAFBe7r77bh04cEB/93d/d8Rt2traNGrUqPSjvr4+xBaWF5dWkmOIBgQn87PEtYCIO5+i7gUyi4lgV4hSZYxvMkE9AAAoAytXrtQdd9yhBx98UOPGjTvidgsXLtS+ffvSj507d4bYSpQqJqgHgpMZN+dSsxeHdvgoYwzRKScOTlB/qD+pt/sGNLKK3Q8AAErTqlWrdM011+ihhx5Sc3PzUbeNx+OKx+Mhtay8OZWRYLoBsJJL2ZFHk3B4PzjVdSKZw0ZmV4hOqIqpqmJwlzNvFwAAKFU/+MEPNH/+fP3gBz/QrFmzTDfHKi4N0hijIQgOXUJHlcwsY3TuYnPnLHDtyBYTwa4QRSIRVmQEAAChOnDggDo6OtTR0SFJ2r59uzo6OrRjxw5JgyWIc+fOTW+/cuVKzZ07V0uWLFFjY6M6OzvV2dmpffv2mWi+ddwZogHBcClgfDTJpOkWmMM5gEIQ7ArZGObtAgAAIdq0aZOmTp2qqVOnSpJaW1s1depULVq0SJK0a9eudOBLku677z4NDAxowYIFGj9+fPpxww03GGm/bVwqwXJt0myEwyNkLCkrs8tgO0xw6QxwLmmviJg0KmRj0pld/YZbAgAAXHDxxRcfNcCyYsUK388bNmwItkGOY5AGHB+H4sVHlfCVMRpsiAFufWmA4SKzK2QnVQ/GF3t6Bwy3BAAAAABQjryMMkYCIvZybz624iHYFbIRlYPBrrf7EoZbAgAAgNC5k5DAIA2BcOgSOqqEwxPUu3QOuHVki4tgV8hGVsUkSQf7yOwCAABwjUvzDTFIQxAyK9hcKmfLlnS47y513bE4ZlEZCXY9/fTTmj17tiZMmKBIJKI1a9YcdfsNGzYoEonkPDo7O8NpcBGlgl09ZHYBAAA4x6VBGhCMoYvI5espmRzqvGuBL7d6i+EyEuzq6elRQ0ODli1bdkyv27Ztm3bt2pV+jBs3LqAWBmdkFWWMAAAArnJpTEpGAoLgy+wy1wzjMmJdvn+7wKWMPla1HT4jqzHOnDlTM2fOPObXjRs3TqNHjy5+g0JEGSMAAABcQLALQUt6nmKOBgMys7lcCv44x83TuyjKas6uKVOmaPz48brsssv0y1/+8qjb9vb2qru72/coBSMOB7vI7AIAAHCPW3N2MUpD8Xm+jCZ3rqdsiSTlnC7gU3T4yiLYNX78eC1fvlw//OEP9cMf/lD19fW6+OKLtWXLliO+pq2tTaNGjUo/6uvrQ2zxkaUzu/oJdgEAALjGpUEpmV0IgsecXZLcDvq51F0+R4fPSBnjsTrrrLN01llnpX++8MIL9fLLL+vee+/Vf/zHf+R9zcKFC9Xa2pr+ubu7uyQCXqk5u3p6KWMEAABwTeYYzfM8RRjJAMfEvxqjuXaYlsgsYzTYDhNcypDF8JVFsCufGTNm6Jlnnjni7+PxuOLxeIgtKsxIyhgBAACclT1QtznWZXHXUCJcy2jKlNl31/aDS92lHHz4yqKMMZ+Ojg6NHz/edDOOGWWMAAAALnMoG8PmSB6M8Y7wb9ckHZ6zy6X+8jE6fEYyuw4cOKCXXnop/fP27dvV0dGhMWPG6PTTT9fChQv1+uuv6/vf/74kaenSpZo8ebLe//7369ChQ7r//vv1xBNP6Oc//7mJ5h8XJqgHAACAZP9Kcvb2DCa5PFdVpqQvS9Td/WCjzONJsGv4jAS7Nm3apEsuuST9c2purXnz5mnFihXatWuXduzYkf59X1+fbr75Zr3++usaOXKkzj//fP3iF7/w/Y1ykZqz6yDBLgAAAOe4NFBnkIYg+CaoTxpsiGGZqzEm7f4oyeFfpMC+uQ8zjydljMNnJNh18cUXHzX6vGLFCt/Pt9xyi2655ZaAWxWOEw5ndvX0DVh5YQIAAODI/BPUG2tGYHwZCQbbAYtlZjQ5XMjInF2Dkp4Us+zDJklmV1GU7Zxd5SpVxuh5Uu+Aw19FAAAAOCgzGGTj+NS1DBOEL/MUc/l8S1r+WXI02ava2ibh8oldRAS7QpYqY5SYtwsAAMA1/oG6fQMaf0YCKQkoPs/hjKZMTs/ZlZXZZRvXDmdQCHaFLBaNqKpicLe/3TdguDUAAAAIk+crwbJPZkYCoS4EwR/kMdcO0zKvNdd2g2/OLgt7n+BLg6Ig2GVAat4uJqkHAABwl41ZKZldYoyGIPjL9+y7hgpFhtsgG7ueZO7DoiDYZUCqlLGHYBcAAIBTbJ+g3peRwDANAfAFuwy2wzSnV2O0fFXbZGaGLB+jw0awy4DUJPWUMQIAALjFszwrxTfwZJCGACQz1viyMdBRKJfLOW3/0iDJx2hREOwyYCRljAAAICRPP/20Zs+erQkTJigSiWjNmjXv+JoNGzboggsuUDwe15lnnqkVK1YE3k4X2ZiNkbSxUygpCc/djKZMLpdz2l7C6fJ8bMVEsMuAkenMLoJdAAAgWD09PWpoaNCyZcsK2n779u2aNWuWLrnkEnV0dOjGG2/UNddco8cffzzglrrBN0G9hYM0MhIQNNuzIwuVtDzgczT+VW2NNSMw/nPcYEPKXIXpBriounIw2NU7kHyHLQEAAI7PzJkzNXPmzIK3X758uSZPnqwlS5ZIkt73vvfpmWee0b333quWlpagmukM2+fZSdjYKZQUX9aLw6eby/vB118L+55wOJBZTGR2GVAZG9ztfQS7AABAiWlvb1dzc7PvuZaWFrW3tx/xNb29veru7vY9kJ/tpUcek4cjYJnxVJcDAf5J2s21wwR/Zpd9nXd5PrZiIthlQNXhYFd/gmAXAAAoLZ2dnaqtrfU9V1tbq+7ubh08eDDva9ra2jRq1Kj0o76+PoymliVfGaO5ZgQmaXnGBcxLUuIlye0yxkw29j3pm7PLvv6FhWCXAVUVBLsAAIA9Fi5cqH379qUfO3fuNN2kkmV7eYrt/YN5BHkGuVwybHsGqe8cJ2QwbMzZZUBlbHC6TubsAgAApaaurk5dXV2+57q6ulRTU6MRI0bkfU08Hlc8Hg+jeWXPP1A32JCAJJMEIhCszMG/jddQoVwu57Q94OnysS0mMrsMqKSMEQAAlKimpiatX7/e99y6devU1NRkqEV28ZWnWDiISVqecQHzErbPTl4g2wM+R5M5jLax677FBwy2o9wR7DKAMkYAABCWAwcOqKOjQx0dHZKk7du3q6OjQzt27JA0WII4d+7c9PbXXXedXnnlFd1yyy3aunWrvvGNb+jBBx/UTTfdZKL51rF94mF/RoK5dsBenuXZkYVyee4yz/K++/tnYQdDQrDLgCpWYwQAACHZtGmTpk6dqqlTp0qSWltbNXXqVC1atEiStGvXrnTgS5ImT56sRx99VOvWrVNDQ4OWLFmi+++/Xy0tLUbab5uE5WV+Ccsz14KSdDlqc4xsv4YK5d8PBhtigO3nQIKAblEwZ5cBQ2WMnLkAACBYF1988VGDDitWrMj7mueffz7AVrnL9mwM2zMugmLjgD0otmdHFsq3sqtjO8L2Es6kr0zTvv6FhcwuA1JljExQDwAA4BbbB2msxjg8CfZVwWy/hgrlz6I02BADbA942r6QSVgIdhnABPUAAABusn1OK1bKGx4bB+xBsT07slAuB/1sPwf8/bOwgyEh2GVAZSwiiWAXAACAa/xzM9k3iGGQNjwJIoMFs30lvkK5nP1j/ZxdrMZYFAS7DIhXMEE9AACAi2wfoNqecREUGwfsQfEczmjK5Cvlcywk4puvzFwzAuPPALaxh+Eg2GUAZYwAAABuSlgeDPJnJFjYwYBkln9GIubaUQ7Iehnk8pxdtmd28aVBcRDsMiA1QX0fqzECAAA4xT+nlX33grbPSRaUzHOBWNfRuTxXVSaXM9xsL5dO+oJ5BhtS5gh2GZDK7OobSBhuCQAAAMJk+0Dd9v4FhdUYC+dfic/d/eZyZpftmU8Jy4N5YSHYZcBQGSMnLgAAgEtsH6Ql/RMJoUC+88JgO8qB7ddQoVye18n2DFLfnGQW9i8sBLsMSE1Qz5xdAAAAbrF9JbkEmV3Dksw6L8jmOLIEJV6S3A6Q2j43oO1zkoWFYJcBQ2WMBLsAAABcYvs8O57lGRdByT4XLDw1isZzOKMpk+3zVh2Nr1zawiE15eDFQbDLgMrY4LSTfWR2AQAAOMX2bAx//2zsYTBygl2G2lEOKGMc5Cvlc2xYaXvA01fGaK4ZZY9glwFVlDECAAA4yfbyFF//uNUtWPa+svHcKBb/xOzu7ifbS/mOJmF52qjLiw8UE8EuAyhjBAAAcJN/4mH7RjG29y8o2cEtgl1HZvvk5IXyl0QbbIgBtpf52d6/sBDsMmAos4sTFwAAwCUJy0uw/NkmKFQiu4yRnXdElMoO8i924dZ+SFoe6KNUtzgIdhlQdTizq5/MLgAAAKe4NEgjI6Fw2cEKdt2R2X4NFcrlgEjmcbcx0OfPXrSvf2Eh2GVA5eHMrl7m7AIAAHBK5txMNg5iCEQMT/awwMZzo1hsn/euUC4Hlv3ngMGGBIQ5u4qDYJcBqdUY+xNJKyPRAAAAyM/2bAx/xoW5dpQbVmMsnG9XObyjXA0s52ZB2td5//8n7OtfWAh2GRCPxSQNflAPuPTJBAAA4LiE5YMYVsobnuzV5VzL1DkWZHYN8s3ZZa4Zocu+Vmzsu6uBzGIj2GVAZUUk/e9+ShkBAACc4HmeLyvFxkGMy6VVxyN7V3kMEY6IQMAgz/LA+ZFkH/OkhSeB7eXuYSHYZUBqgnpJ6h/g5AUAAHBB9pjMxpXk/CvloVA5qzGy946IEq9Brma4ZffVwliXPwPYYDvKHcEuA2LRiCKHk7t6EwmzjQEAAE5YtmyZJk2apOrqajU2Nmrjxo1H3X7p0qU666yzNGLECNXX1+umm27SoUOHQmqtnVwYpPkyEmzsYEBcODeKJWl5dmShXJ0fL3d+O/s672rWXrER7DIgEomo8nB2V3+CkxcAAARr9erVam1t1eLFi7VlyxY1NDSopaVFu3fvzrv9ypUrdeutt2rx4sV68cUX9Z3vfEerV6/WF77whZBbbpecuWYsHMSQkTA82YFBG8+NYvFfR+7uJ1dLhnM/Rw01JEC++dgs7F9YCHYZEk8FuwYoyAcAAMG65557dO2112r+/Pk655xztHz5co0cOVIPPPBA3u2fffZZfehDH9InPvEJTZo0SZdffrmuuuqqd8wGw9HlzMtk4SDGn5FgsCFlJmceIvZdXtlBQJf3k6tzl+VeK/Z13tVAZrER7DKksmJw1/cxQT0AAAhQX1+fNm/erObm5vRz0WhUzc3Nam9vz/uaCy+8UJs3b04Ht1555RU99thj+uu//uu82/f29qq7u9v3QK7seZlsHMQkmFh5WFzI+isGVq0c4tsXDu2G3CxIQw0JkKuBzGKrMN0AV1XGBift6iOzCwAABGjPnj1KJBKqra31PV9bW6utW7fmfc0nPvEJ7dmzR3/xF38hz/M0MDCg66677ohljG1tbbrjjjuK3nbb5Mw1Y+EgJklm17BkB7fYdfnlLPLg8I7yz13mzo7Ind/Ovr5nBvQIfA8fmV2GVFWk5uwi2AUAAErLhg0bdOedd+ob3/iGtmzZoh/96Ed69NFH9cUvfjHv9gsXLtS+ffvSj507d4bc4vKQnZFg5SCN8pthcSHrrxhcCHQUKunoaow5K5da2PXMab1t7F9YjAS7nn76ac2ePVsTJkxQJBLRmjVr3vE1GzZs0AUXXKB4PK4zzzxTK1asCLydQUpNUE9mFwAACNLYsWMVi8XU1dXle76rq0t1dXV5X3P77bfrk5/8pK655hqdd955+tjHPqY777xTbW1tSiZz713i8bhqamp8D+RyYV4mf0aCwYaUGRfOjWJwITuyUL4sSoPtCFvO3IcW9t7jS4OiMBLs6unpUUNDg5YtW1bQ9tu3b9esWbN0ySWXqKOjQzfeeKOuueYaPf744wG3NDhVrMYIAABCUFVVpWnTpmn9+vXp55LJpNavX6+mpqa8r3n77bcVjfpvE2OxmCRKKo5H9nxDNg5RfRkJFvYvKKzGWJicuc0cPscSjs7rlDNvm4W5I5l9dOjQFp2RObtmzpypmTNnFrz98uXLNXnyZC1ZskSS9L73vU/PPPOM7r33XrW0tATVzEBRxggAAMLS2tqqefPmafr06ZoxY4aWLl2qnp4ezZ8/X5I0d+5cTZw4UW1tbZKk2bNn65577tHUqVPV2Niol156Sbfffrtmz56dDnrh2Lmwkpzn6AD8eJGxVJicDDiHh1KZ54hLwVEXSlldnY+t2Mpigvr29nbfCkKS1NLSohtvvPGIr+nt7VVvb2/651JbFShVxthLGSMAAAjYnDlz9MYbb2jRokXq7OzUlClTtHbt2vSk9Tt27PBlct12222KRCK67bbb9Prrr+vUU0/V7Nmz9W//9m+mumCF3FI1+wYxzNk1PC6cG8WQGzB2dz+5uhhEbhmjfViNsTjKItjV2dmZdwWh7u5uHTx4UCNGjMh5TamvCpRajZHMLgAAEIbrr79e119/fd7fbdiwwfdzRUWFFi9erMWLF4fQMnc4MbFyxq2tjf0LSk55Hvsur9wyRnclXJ2g3oGSX19Zs33dC421qzGW+qpAFYe/Pc2duwEAAAA2cm01RsnOgWgQyFgqTPbQyeXzK7PrLg0pc8sYDTUkQJQxFkdZZHbV1dXlXUGopqYmb1aXNLgqUDweD6N5w1JxOLNrwMarEwAAADlcmJcpN6AnHb7txVFkZ/0xRMjPhUBHoXyTmNv4YXIELnyOJigHL4qyyOxqamryrSAkSevWrTviCkLloCJ6ONhFGSMAAIATcrJSLKxPIfNmeHKDNuy3fFwIdBTK1Tm7XJjfLvNz077ehcdIsOvAgQPq6OhQR0eHJGn79u3q6OjQjh07JA2WIM6dOze9/XXXXadXXnlFt9xyi7Zu3apvfOMbevDBB3XTTTeZaH5RxKJkdgEAALgke/oKG1eSI0NpePJlxCFXzjVkYaCjUL5gl0MhERfmbfNn7fGlwXAZCXZt2rRJU6dO1dSpUyUNLoc9depULVq0SJK0a9eudOBLkiZPnqxHH31U69atU0NDg5YsWaL7779fLS0tJppfFBUx5uwCAABwiQvzMrnQxyDkluex3/LJWYnP4f3kn9fJXDvC5sK8gLkZsmbaUe6MzNl18cUXH/WkXLFiRd7XPP/88wG2KlypMkZWYwQAAHBDzmqMhtoRJL7IHR5WYyyMC1k9hXJ1NcbsjFgb+54T0DPUjnJXFnN22ShVxsgNAQAAgBuyB2kuZCTYOBANQvZuYr/ll5MB5/BYyrcvHNoNLszb5sLKvWEg2GVIZXRw1zNnFwAAgBucGKQ50Mcg5GT9sd/yIuNlSOa+cCkY4sK8gHweFAfBLkNisdRqjJy5AAAALsidl8lQQwJERsLwECQsTG7moJl2lILMTFGX9oML8wKS6VkcBLsMqUyXMTJnFwAAgAtcWEnOhayLIBAkLEzu3Gbu7qfMa82t1RiznrCw68zhVxwEuwyJHS5j7OcOAAAAwAk5K2yZaUagcgZlNnYyAC6cG8VABtyQzECfS/kTLqxcmluua18fw0Cwy5CKGBPUAwAAuCR3oG7ffaAL2WtBYL8VxoWV+AqVec7Y+FlyJLlZkIYaEiAXSt7DQLDLkIooc3YBAAC4JGeQZuEIxoWsiyC4EAgtBoIAQzL77tJuyM2CtK/3BHWLg2CXIelgl0s5pwAAAA7LWWHLUDuCxGp5w0N5XmFyryF3dxSrMQ6yMeDJaozFQbDLkIrY4K4fsPHqBAAAKDNPbtutq+77lXbufTuw98hdYSuwtzKGjIThYZXBwmRnvLl8evmDXQYbEjIXsiBd6GMYCHYZEkutxkgZIwAAgHHzv/trtb/ypm55+DeBvUf2l5w2DmBy+2ioIWWGObsKkz0FjI2lwIXK3BcunS7Z42cb+577eWCoIWWOYJchqTLGfsoYAQAASsYbB3oD+9sDCf99n42DtOwpOmzsYxD6HTg3iiEnmGqoHaVgwNEJ6rM/Y2wMDGcHdV06vsVEsMuQVBkjqzECAAC4IXugbuUgzYE+BiF7TMDgNj/OryGZ54xL+yH3HDDUkADlBvQMNaTMEewyhNUYAQAASk8kwL+dU4Jl4W1gdvaaS4Pw49HvwLlRDLnnl6GGlIDMbECXdoMLWU8u9DEMBLsMibEaIwAAgFNySvwsHKLmDtIMNaTM5JS4WnhuFEN2UNDlEyzzWnNp7jIXSn77KdctCoJdhlTGDk9Q79AHEwAAMGfZsmWaNGmSqqur1djYqI0bNx51+7feeksLFizQ+PHjFY/H9d73vlePPfZYSK21U/ZA3YlBmoV9DIILpVnFQHnXkMx94dJ15kIpKxmyxVFhugGuikUH44w5304AAAAU2erVq9Xa2qrly5ersbFRS5cuVUtLi7Zt26Zx48blbN/X16fLLrtM48aN08MPP6yJEyfqtdde0+jRo8NvvEVyBjAWjtQZpA1PdrYK+y2/3FJgd/dT5jjSpb2QmwVpHxdK3sNAsMsQMrsAAEBY7rnnHl177bWaP3++JGn58uV69NFH9cADD+jWW2/N2f6BBx7Q3r179eyzz6qyslKSNGnSpDCbbCUXSlNyyhgNtaPc5Mzjy47LK6eEzVA7SkFm0MeloF/u/Hb29b0/Z1Vb+/oYBsoYDUnN2ZX9gQ0AAFBMfX192rx5s5qbm9PPRaNRNTc3q729Pe9r/vu//1tNTU1asGCBamtrde655+rOO+9UIpHIu31vb6+6u7t9D+RyIespe5BmYx+DwH4rjAslbIXqd3Y1Rvvn7GLuw+Ig2GVIajVGMrsAAECQ9uzZo0QiodraWt/ztbW16uzszPuaV155RQ8//LASiYQee+wx3X777VqyZIn+9V//Ne/2bW1tGjVqVPpRX19f9H7YwIUBjAt9DAL7rTDZAWOXU7sy94VL50vu3If2dd6FSfjDQLDLkIrDc3ZlfzsBAABgWjKZ1Lhx43Tfffdp2rRpmjNnjv7pn/5Jy5cvz7v9woULtW/fvvRj586dIbe4PLhQmpI7SLOvj0HInXid/ZaPCyVshUgmPd88Ti7tBhfmsyKDsTiYs8uQ2OE5u7L/xwYAAFBMY8eOVSwWU1dXl+/5rq4u1dXV5X3N+PHjVVlZqVgsln7ufe97nzo7O9XX16eqqirf9vF4XPF4vPiNt4ybgzRDDSkzuUEcQw0pcazGOMjlslcXAsMulLyHgcwuQ1JljDmTUQIAABRRVVWVpk2bpvXr16efSyaTWr9+vZqamvK+5kMf+pBeeuklJTMGFX/4wx80fvz4nEAXCpe7iph994Eu9DEIOeV57Le8ckvYDDXEMJcXgnDhHMjpo6F2lDuCXYakyhiZswsAAASttbVV3/72t/W9731PL774oj7zmc+op6cnvTrj3LlztXDhwvT2n/nMZ7R3717dcMMN+sMf/qBHH31Ud955pxYsWGCqC1bIXo3RxtvAnAwlihgKQkZcYXKzI93cUS7vh5yAuoV9z52E374+hoEyRkMq0mWMnLgAACBYc+bM0RtvvKFFixaps7NTU6ZM0dq1a9OT1u/YsUPR6NB3oPX19Xr88cd100036fzzz9fEiRN1ww036POf/7ypLljBhdIUF0qMgpA91xn7LT+CAINy5/8z1BADssfPNnbdhZL3MBDsMiRdxsjXXQAAIATXX3+9rr/++ry/27BhQ85zTU1N+tWvfhVwq9ySnfVk4yiNKTqGh9UYC0N516B815nneYpEIgZaEy4XAsOsxlgclDEakl6NkRsCAAAAJ7iQ9eTCQDQIuSWu7Ld8XMiOLET2dSa5k/3jQtYTqzEWB8EuQ2JRyhgBAABKQWYpVJB3Zm4O0gw1pMzkzkNkqCEljvNrUL4xpCslnS6UcLo8J1sxEewypPLwnF1MUA8AAGBWTnlhwO+T+tLTxvFLapB2uIvODMCP10D2ueFsgd7RpTKahs4vg40xKBUcTZ0vkjuBv5xrxcKTIBXQs/n/FWEg2GVI6sTNl4IKAACA8IQ1h2rqfVJfetr4bX1/uo+DwwxXBuDHqz/73GCIkFcq0FFVMXh+2RjoKEQqcJ46XyQ7P0/ysf1zNJH00sGtVB8t62JoCHYZkroBILMLAADArLAyu9ID9ZidA/XMQZrrwYhjlX1u2DaAL5ZUUND1/TSQtR9c0p/zOWqyNcWXmQzj+nl+vNy7OkoEc3YBAACUhrC+fEwPUFOBoFDeNTyZGXLpgaipxpSZ1Dlo67lRLDn7ydEdNZC1HyR3AiLZ54Btw+nM/x/xeXB8CHYZUpEKdlHGCAAAYFTm/VgywJGT7dk7mZMqpweito1EA5LK5rA1669Ycq8hk60xJ3s/SO7si+xrxerPUUv7GBaCXYZUZHxAcxMAAABgTn/GvVj2Sl9BvI+tGQl5g12W9TEo2Zk67Lf80oEOx8tkB7L2g+TOvsiet802mf8PqnT8PD9edp4hZSBz5QxKGQEAAMzJzOzKXvI9iPeptHWumcxBWrqM0bJOBqTf8nOjWFLjpkrHy2T7s/aD5E6AdCBnEQy7Op76f1BFNKJohAnqjwfBLkMqMoJdTFIPAABgTuYE9UFOVm/7SnKp/sWiEcUYpB2T7HPDtgF8sWRndrm6n1zO7Oq3/FpJneMVsYgOf4w6E8gsNoJdhlTEMjO7mLcLAADAlMx7sSDvy/qzJ6i3bACTHqRFhwZptvUxKLYvXlAsuQFjk60xJzvgI7mzL3KuFcv6nc5ejEaVihi4EsgsNoJdhlREh3Z9kOnyAAAAOLrMe7Fgyxj9pUe2ZSRklphFDke7bOtjEDzPSwcvKpmg/qhsL2ErVPZ+kNzZF7mfoyZbU3wDGZld0fTnqMkWlS+CXYbEMr7xYs4uAAAAc/oz5uzqD3Cl7NTfjls6Cbl/kDb4nCsD8OOROaVJnFUsjyoVFIxbmtVTKFZjzDwH7Op46hyviEUz5uyyq49hIdhlUGreLsoYAQAAzMn84jHILyHTK+5ZOnl7epAWjQ6VMRpsT7nIPOeqHJ94/Z2kS9gsvYYKlW9eJ1f2Rc7nqGXdTmftZZaDG2xPOSPYZVBqRUbKGAEAAMzJzOZKJL3AvkW3fTXGodKqCBkJxyDz/LO1NKtYckrYHM0ZSAV8KqJR51bss70cPDOzi3Lw40Owy6DKw/N2sRojAACAOdlfPAa1IqP9q4ilBmmRoUGao8GIY5F5/tm6UmexsBrjoKHAuXslw7nngMnWFF/+cnCDDSpjBLsMisUoYwQAADAt+14sqHsz61cRSw3AM1cRM9ecspFapTMSGZrmxLZzo1gyF0GQ3D2/fNk/cuucSZcxVthZyupbjTG9qq1dfQwLwS6DUisyMkE9AACAOdmZXEFldtlefpMurXIw2+R4pM+LKGVL72QgKzvS1SBAvnmdXDln+i0vB+/PsxqjbX0Mi7Fg17JlyzRp0iRVV1ersbFRGzduPOK2K1asUCQS8T2qq6tDbG0wKpizCwAAwLjse7GBgFZkzF1FLJC3MSY9SIuyitixGEjkCxIabFAJs31F00L1+84ZtwIiA1krctoW5Btgzq6iMRLsWr16tVpbW7V48WJt2bJFDQ0Namlp0e7du4/4mpqaGu3atSv9eO2110JscTDSE9S7+ikNAABQAnLLGAPK7EqXYB0enNpWfpMY6t9Q+Y3BBpWJVBljRdS9lfWOVc415OgJ5g+IDD7nyq7IXAhDsq/fvqy9w8/Z1sewGAl23XPPPbr22ms1f/58nXPOOVq+fLlGjhypBx544IiviUQiqqurSz9qa2tDbHEwUhdogjm7AABAwI4lqz7TqlWrFIlEdOWVVwbbQINyyxgDmrPL8pXkUoO0WDRjgnoGae8oM3DhWpbOscouYXP1/BrICJBGHcr+8Twv/Xltazl4qn+xKOXgxyv0YFdfX582b96s5ubmoUZEo2publZ7e/sRX3fgwAGdccYZqq+v1xVXXKHf/e53R32f3t5edXd3+x6lJpXZFdS8EAAAANLwsuol6dVXX9U//MM/6MMf/nBILTUju2wxqCkm+pN2ryTnnzR7kG19DMJQ+WfG/EuuRnHeQfacXa6eX+lrLerWtZbIuC6sXegjORTQ5UuD4xN6sGvPnj1KJBI5mVm1tbXq7OzM+5qzzjpLDzzwgH7yk5/oP//zP5VMJnXhhRfqT3/60xHfp62tTaNGjUo/6uvri9qPYkhNUJ/g7AUAAAEaTlZ9IpHQ1VdfrTvuuEPvete7Qmxt+Pqz7sWCWI0xkfTSgzJbV5LLLC9KZyiZbFCZyFxhMMJ+O6rMQIDL0iufZpYMG2xPWDJLzIc+R+3qeX+eOfzcOLrFVxafEk1NTZo7d66mTJmiiy66SD/60Y906qmn6lvf+tYRX7Nw4ULt27cv/di5c2eILS5MRYw5uwAAQLCGm1X/L//yLxo3bpw+9alPveN7lENG/dFkZ3YFkXWfWRoZt3Qlucxsk8Pf6VrXxyAM+FZfG3zOhSydY5VZwmbr5OSF8q18GnVn/rJ8n6PWlYNnZu2R2XVcKsJ+w7FjxyoWi6mrq8v3fFdXl+rq6gr6G5WVlZo6dapeeumlI24Tj8cVj8ePq61BG1qN0bIrFAAAlIyjZdVv3bo172ueeeYZfec731FHR0dB79HW1qY77rjjeJtqTHaWfRBZ9/nKb2wbwCQyJg9PJN2ZR+h4pQMX0YhSU1Lbdm4UQ+Y+qbI00FGooTm7ok5NYp63jNGyrKdERoasSyWqQQg9s6uqqkrTpk3T+vXr088lk0mtX79eTU1NBf2NRCKhF154QePHjw+qmaGoOJx6yZxdAACgVOzfv1+f/OQn9e1vf1tjx44t6DXlkFF/NGFMUJ85D1i6/MayAUw6Qynq3gpxxyNz4YKoS5GLY5R5XdpawlaozJVPow5l/2R+Vqfmv7at3/0sWFE0oWd2SVJra6vmzZun6dOna8aMGVq6dKl6eno0f/58SdLcuXM1ceJEtbW1SRpMo//gBz+oM888U2+99Za+8pWv6LXXXtM111xjovlFU5kuY3T0KwkAABC4Y82qf/nll/Xqq69q9uzZ6eeSqSyCigpt27ZN7373u32vKYeM+qPJmaA+gNFTfzJ3oG7vIM2tAfjxSp0bFTFWsTyazOuyytJrqFC+xSAcWo0xc17AWMTO8s10H6ORdDm4C8c2CEaCXXPmzNEbb7yhRYsWqbOzU1OmTNHatWvT6fU7duxQNDqUdPbnP/9Z1157rTo7O3XyySdr2rRpevbZZ3XOOeeYaH7RVKYzuwh2AQCAYGRm1V955ZWShrLqr7/++pztzz77bL3wwgu+52677Tbt379fX/3qV0ty0Z/jlT1BfZCZXRUZy8nbNnzxryI2+JxtA9Eg+OfoGXzO1Yylo8kMSqdK2FzdTUNljBGnsijzXiuW9TvzS4OhQkYMh5FglyRdf/31eW+wJGnDhg2+n++9917de++9IbQqXJWUMQIAgBAcS1Z9dXW1zj33XN/rR48eLUk5z9siJ7MrwAnqM7OebAsE9fsCepTfFCpzZT0y4o6s31cK7E42Uz75Sl9d2BeZn6O2ZrQN+LL2Bp+zrY9hMRbswtCHNJldAAAgSMeaVe+a7LLFIKaYSL1HZdTeAcyAb66Zweds62MQ+pND2SrstyPLzGaKWhroKFT+4LnJFoUj/TmaMZ+VbYFhXxljqo+EC4aFYJdB6QnqBzh7AQBAsI4lqz7bihUrit+gEpL9xWMQWfcDeTISbBucZs6no8PlN5Z1MRD5zg12XK6BzPKuiNvnly94fvg5F0pf00G+aCSj33bpz5PZZVsfw+LuV3glIDWxYhCToAIAAKAw2WWLwZQx2p/11J8gQ2k4MkvSbM36K4ZUoKPSd34ZbJBB+cv5TLYoHL7yzdS0bZZdKwN5svb4PBgegl0GpcoY+yhjBAAAMCa7bDGYMsY8pSmWjV+Ye2p4+vOW55lsUWlKJQjYPO9doXwlww6t2DeQtD8QlJm1l17MxLI+hoUyRoOGyhg5eQEAAIKWSHrauH2vDvQOpJ87qbpCvVlTSnTsfEsjq4p3mxyR0hk7FbGhsqM/9/Rp3e+7ivY+Jp1QFUvvx8Fsk8HnX9zVbU0fg1AZi6jn8PlYmXFuvPZmD/stS3Xl4NipIhZNVclq38F+5/bTqSfFfcHzVEHfxu179eaBPpNNC1REUsIbWgQj5c0DFn2OxmPqHUhIGvwcTZ3ov/uf8vscPW/iKNWNqjbaBoJdBg2VMZLZBQAAELTVv96pL/z4hXfc7ru/fFXf/eWrgbShIhZJf+H5x90HdO33NwXyPiZVRKPpPq58bodWPrfDcIvKQ+a58YsXd+sXL+423KLSVBmNqPJwOtNrb75t5TVUqIpY9HBQRLrrZ1sNtyY8lbGoKg9fK1s791t5Dgz2cfDYfr/9NX2//TXDLTo2X//EVH30/AlG20CwyyDKGAEAAMLz2t4eSdK4k+KaePII/enPB/XG/t7072eeW6c3e/qKulL2of6kXtzVnf65uiKmpnefor8+r0679h0q2vuYtOutQ+rsHupLdWVM/1fj6drdfYj73KPY29On1958O/1zdUVM/6thgjp2vqX9h/oNtqy09A0k9bv/ybiGKmOaPulkffT88Xr9rYMGWxa+l3cfUPehoczU6sqoFlx8plZu3GFdOV+mg30Jbe3cn/45XhnTh84cq4+8v05d++34HP2ftw6qq3vo/0fxiqg+2XSG9vb0leXn6Mkjq0w3gWCXSZQxAgAAhKe3f3DAMOcD9br58rP0pbVb9c0NL6d/f+n7avXxaacV9T137n1bH/7yk+mfR1TFdGK8Qt+4elpR38ekZU++pK88vi3984jKqBrfdYpW/z9NBltV+h79zS4tWLkl/fOIqpjOHHeivv/3Mwy2qvTs3n9IM/5tffrn6sqYqitj+vonLjDYKjM++1+b9dgLnemfR1TG9LfTTtPfFvlzq9S8/MYBXbrkqfTPIyqjGjWiUss/ac/n6NJf/EFLf/HH9M8jqmK68N1jdeG7xxpsVXljgnqDKiljBAAACM3BvsG5UKorY4P/rYj5fp+aE6iY4ll/M4j3MC1e4e/TiKrYEbZEphFV/v2Wfa5gUOp6TXH5/Mr9zHJjX2T308Z+5/Sxwr4+ho1PVIOqDpcxFjNVHgAAAPkd7PcHu7KDDSMCGEBl/80g3sO07OCDjQPRIOQEcdhveblwDRWq2tFrzYVzIKePDgd1i4Vgl0GpMsY+yhgBAAAClwp2pQYVYQygXMhIyN5vNvYxCAS7ClMZi/pW37MxO7JQrgZEnAx2WdjHsLn7SVECKGMEAAAIz6FUsOtwRldOICqAgWPmilqSnQMYBmnD42rgYjgy95XLwVRXr7XsUukgPqtNczVrL0gEuwyqpIwRAAAgNKk5u9KZXVXhDBwzBy02BjSyB2k29jEIZMQVLvMccyXAk09Yn1mlJhqN+DL6bOw3we/iI9hlUCVljAAAAKHJmbMrpCyJzL/rxCDNwj4GwdXAxXCMsDxgXKjsgGh2xpPN+BzFsXLn6ihBlDECAACE5x3n7ApoEJ35d23M3iFDaXiYs6twtgc6CuUv54wqmjGXme1sD3iGsWCKawh2GUQZIwAAQHgOpcoYDw+Uwpojxf5BGuU3w0HZUuGqLQ8YFyozIOJaMMT2cyB3DklCNceLPWhQKrOrnzJGAACAwJlYjVHKmrPLwkEa5TfDUxmLKOZbZZD9diQjMudrcjgo6HKGm+1953O0+Ah2GZQOdlHGCAAAELhD/YP3XKmgQmZwIRqRb9XEYsqcWDnz37aIV1J+MxyRSCSnLA352R4wLlTc4VUpqy2/VnIyuxw7vkGw7ywpIxWUMQIAAITC87yhzK6q3MyuEZUxRSLBBLtGWD5AzQ4+uDRp9vEiiFMY27N6CmX7Z8nR2H4OZPcplRiD4WMPGlRFGSMAAEAoegeGvlzMV8ZYEeDAIrPsysZBWvag26VJs4+Xbw4mh8vz3okvyOPwfrJ9/r+jqbb8HMg8ngF97+Icgl0GUcYIAAAQjoOHJ6eXMsoYQ5oAuNryASoZCMNXGXV3wvFjUW15wLhQtgfOj8b2vpMRW3zsUYMoYwQAAAhHqoSxqiKanhS8KqQgje3lNzgOGRkcrpWlHQuuoUFulzHaHRgOqozeZQS7DKKMEQAAhGXZsmWaNGmSqqur1djYqI0bNx5x229/+9v68Ic/rJNPPlknn3yympubj7p9OUgFu6ozvj0Pa3Dh8gAVhSOz48j85Xvu7ifbJ2k/GpdLODE8bl0hJSaV8j1AGSMAAAjQ6tWr1draqsWLF2vLli1qaGhQS0uLdu/enXf7DRs26KqrrtKTTz6p9vZ21dfX6/LLL9frr78ecsuLJ1XGaGKQ5Cu/YZCGIyCz48gyrxuXA8aZ+yHq2PlCKSuOFcEug1JljH0DBLsAAEBw7rnnHl177bWaP3++zjnnHC1fvlwjR47UAw88kHf7//qv/9JnP/tZTZkyRWeffbbuv/9+JZNJrV+/Pu/2vb296u7u9j1KzaHUSowGBkmsuAccn2qyIyX5M1NdU13BOYBj4+7VUgLSZYwJyhgBAEAw+vr6tHnzZjU3N6efi0ajam5uVnt7e0F/4+2331Z/f7/GjBmT9/dtbW0aNWpU+lFfX1+UthdTuozxCIOkIJMkMsvTCHYBx445uwZlrhrrWGJXeq5Fyf4MWccObWAIdhlEGSMAAAjanj17lEgkVFtb63u+trZWnZ2dBf2Nz3/+85owYYIvYJZp4cKF2rdvX/qxc+fO4253sb1TGaMX0nePZCQAx64ylhHo4BqSFN5nVqnI7K/tGW6OHdrAVJhugMuGVmP05HkedfoAAKDk3HXXXVq1apU2bNig6urqvNvE43HF4/GQW3ZsDh2eNsL0QJlJyIHjY3tWD95ZRUgr6aK8cZYYVJlxkVLKCAAAgjB27FjFYjF1dXX5nu/q6lJdXd1RX3v33Xfrrrvu0s9//nOdf/75QTYzcIf6zM3ZlSka5ctN4HgQMAZQCD4pDKrKCHZRyggAAIJQVVWladOm+SaXT00239TUdMTXffnLX9YXv/hFrV27VtOnTw+jqYFKz9lFVghQ1qiGAVAIyhgNqsioPe8f8KQqg40BAADWam1t1bx58zR9+nTNmDFDS5cuVU9Pj+bPny9Jmjt3riZOnKi2tjZJ0pe+9CUtWrRIK1eu1KRJk9Jze5144ok68cQTjfXjeBx8h9UYKwLMuGJwjiMJ8ryzCddQLtdOHZf6y+dCcZDZZVDmSdyXILMLAAAEY86cObr77ru1aNEiTZkyRR0dHVq7dm160vodO3Zo165d6e2/+c1vqq+vTx//+Mc1fvz49OPuu+821YXj1n2wX5J0Ytz/Xe9XPn6+TopXaNnVFwT23h+/4DTV1sR11YzSW6WyWL5x9QU6KV6h7/7fHzDdlLLylY836KTqCn3xivebbkpJm3lunSaOHqGPTZ1ouinG/Z9L36OTR1aq9bKzTDclVFd/8AydelJcc5vOMN2UwHz1f0/RSfEKPcDnaFFEPM+NdRy6u7s1atQo7du3TzU1Naabk/bef/qZ+hJJtS/8K40fNcJ0cwAAwDEo1fsL00pxvyz80Qv6wcYdar3svfo/l77H97tk0gt8Lq0w3sM0F/oYBPZbYdhPQ1zdFy7024U+Hq9C7zHI7DIsvSLjgBMxRwAAACP+3NMnSTr5hNx5I8IYWLgweHGhj0FgvxWG/TTE1X3hQr9d6GNYCHYZllqRkTJGAACA4Ox9+3Cwa2Sl4ZYAAICgEewyLBXsYjVGAACA4KQyu8aMZEUgAABsR7DLsErKGAEAAAL357ePXMYIAADsQrDLMMoYAQAAguV5nv789uBqjGMIdgEAYD2CXYalMrsGCHYBAAAEovvQgBLJwSz60czZBQCA9Qh2GZbK7DrYnzDcEgAAADul5us6oSqmeEXMcGsAAEDQCHYZdvqYkZKku3++Tbu7DxluDQAAgH32Ml8XAABOIdhl2KLZ52jMCVX67evduvSep/TDzX/S/kP9ppsFAABgjfRKjAS7AABwAsEuw047eaRWXtuo808bpf2HBnTzQ/+fZvzben1zw8vyPFZoBAAAOF6pyelHjyTYBQCAC4wFu5YtW6ZJkyapurpajY2N2rhx41G3f+ihh3T22Werurpa5513nh577LGQWhq8s+tq9MPPXKjPXPxu1dVU62B/Ql9au1XPvLTHdNMAAADK3psHeiVJY5icHgAAJxgJdq1evVqtra1avHixtmzZooaGBrW0tGj37t15t3/22Wd11VVX6VOf+pSef/55XXnllbryyiv129/+NuSWB6cyFtXnP3K22hf+la6acbokadmTL+nVPT1KJsnwAgAAGK5X3+yRJJ1+ygmGWwIAAMIQ8QzUyjU2NuoDH/iAvv71r0uSksmk6uvr9bnPfU633nprzvZz5sxRT0+PHnnkkfRzH/zgBzVlyhQtX768oPfs7u7WqFGjtG/fPtXU1BSnIwHZ8ebbuvjuJ5WKcZ0Ur1D9mJEaWRXTiKqYRlbFVFURUzQiRSMRRSJSLBJRNBJRNCpFIpHDPw/+uxDZm0WU+7p8fyrfX8+7XdaTeVuV9++/czsKbsMw/1a+P1bIexZzHw73OBbajmLuw/ztKmwf2qbAw1bWHOhiwddfOXOgi/q76fWqriz+KnzldH8RplLbL3+3vF0bX92rr/7vKbpiykTTzQEAAMNU6D1GRYhtkiT19fVp8+bNWrhwYfq5aDSq5uZmtbe3531Ne3u7Wltbfc+1tLRozZo1R3yf3t5e9fb2pn/u7u4+voaH6PRTRuqO//V+Pbz5T3qxc7/29w7o97vKp/0AAJSaKxomBhLsQnl4+Y0DkqR3n3qi4ZYAAIAwhB7s2rNnjxKJhGpra33P19bWauvWrXlf09nZmXf7zs7OI75PW1ub7rjjjuNvsCGfbJqkTzZNUn8iqZffOKDOfYd0sC+ht/sSers/oYFEUklPSiY9JT1v8N+ed/jnw//Ok7SX/ZSnd95mcLtCtnnnF+ZLI8xOLizk/fNtV2hf3un9i/l+hfydfFvm3QcF7HPTx67w97OfCwtM2N9DOdHJvNe/hSpiDqSvIa+33u7Tm4dXY5w8ljJGAABcEHqwKywLFy70ZYN1d3ervr7eYIuGpzIW1dl1NTq7znwJAAAAQLl5+Y3B+brGj6rWCXFrb30BAECG0P+PP3bsWMViMXV1dfme7+rqUl1dXd7X1NXVHdP2khSPxxWPx4+/wQAAAChbL++mhBEAANeEvhpjVVWVpk2bpvXr16efSyaTWr9+vZqamvK+pqmpybe9JK1bt+6I2wMAAACS9P++tEeSdO7EUYZbAgAAwmIkl7u1tVXz5s3T9OnTNWPGDC1dulQ9PT2aP3++JGnu3LmaOHGi2traJEk33HCDLrroIi1ZskSzZs3SqlWrtGnTJt13330mmg8AAIAy0DeQ1IatuyVJl51T+w5bAwAAW4Se2SVJc+bM0d13361FixZpypQp6ujo0Nq1a9OT0O/YsUO7du1Kb3/hhRdq5cqVuu+++9TQ0KCHH35Ya9as0bnnnmui+QAAAGVn2bJlmjRpkqqrq9XY2KiNGzcedfuHHnpIZ599tqqrq3XeeefpscceC6mlxfPLl/dof++Axp4Y19T60aabAwAAQhLxXFgyTIMT1I8aNUr79u1TTQ2TvQMAgONXLvcXq1ev1ty5c7V8+XI1NjZq6dKleuihh7Rt2zaNGzcuZ/tnn31Wf/mXf6m2tjZ99KMf1cqVK/WlL31JW7ZsKejLxlLYLwOJpD76789oa+d+zWs6Q3dcwZekAACUu0LvMQh2AQAADFO53F80NjbqAx/4gL7+9a9LGpwvtb6+Xp/73Od066235mw/Z84c9fT06JFHHkk/98EPflBTpkzR8uXL3/H9TO6XgURSf+g6oLt/vk1PbN2t0SMr9cTNF2vMCVWhtgMAABRfofcYzqy/nIrpdXd3G24JAACwReq+opS/O+zr69PmzZu1cOHC9HPRaFTNzc1qb2/P+5r29na1trb6nmtpadGaNWvybt/b26ve3t70z/v27ZMU3H3Xq2/2aNGa36o/4WkgmVQi6ak/kVRfIqnd3b3qTwwej6qKqP75I2epInFI3d2HAmkLAAAIT6H3Xs4Eu/bv3y9Jqq+vN9wSAABgm/3792vUqNJc7W/Pnj1KJBLpuVFTamtrtXXr1ryv6ezszLt9Z2dn3u3b2tp0xx135DxfCvddH7vbdAsAAECxvdO9lzPBrgkTJmjnzp066aSTFIlEAnmP7u5u1dfXa+fOnSVdymAzjkFp4DiYxzEoDRwH84I+Bp7naf/+/ZowYULR/3Y5WbhwoS8TLJlMau/evTrllFO477Icx8E8jkFp4DiUBo6DeaVy7+VMsCsajeq0004L5b1qamq4sAzjGJQGjoN5HIPSwHEwL8hjUKoZXSljx45VLBZTV1eX7/muri7V1dXlfU1dXd0xbR+PxxWPx33PjR49eviNPgZcX6WB42Aex6A0cBxKA8fBPNP3XtFA3hkAAAAloaqqStOmTdP69evTzyWTSa1fv15NTU15X9PU1OTbXpLWrVt3xO0BAABKiTOZXQAAAK5qbW3VvHnzNH36dM2YMUNLly5VT0+P5s+fL0maO3euJk6cqLa2NknSDTfcoIsuukhLlizRrFmztGrVKm3atEn33XefyW4AAAAUhGBXEcXjcS1evDgnjR/h4RiUBo6DeRyD0sBxMI9jMGjOnDl64403tGjRInV2dmrKlClau3ZtehL6HTt2KBodSvi/8MILtXLlSt122236whe+oPe85z1as2aNzj33XFNdyMGxLQ0cB/M4BqWB41AaOA7mlcoxiHilvFY2AAAAAAAAcAyYswsAAAAAAADWINgFAAAAAAAAaxDsAgAAAAAAgDUIdgEAAAAAAMAaBLsAAAAAAABgDYJdRbJs2TJNmjRJ1dXVamxs1MaNG003yRpPP/20Zs+erQkTJigSiWjNmjW+33uep0WLFmn8+PEaMWKEmpub9cc//tG3zd69e3X11VerpqZGo0eP1qc+9SkdOHAgxF6Ut7a2Nn3gAx/QSSedpHHjxunKK6/Utm3bfNscOnRICxYs0CmnnKITTzxRf/u3f6uuri7fNjt27NCsWbM0cuRIjRs3Tv/4j/+ogYGBMLtS1r75zW/q/PPPV01NjWpqatTU1KSf/exn6d9zDMJ31113KRKJ6MYbb0w/x3EI3j//8z8rEon4HmeffXb69xwD+3HfFSzuvczj3qs0cO9Verj3MqMc770IdhXB6tWr1draqsWLF2vLli1qaGhQS0uLdu/ebbppVujp6VFDQ4OWLVuW9/df/vKX9bWvfU3Lly/Xc889pxNOOEEtLS06dOhQepurr75av/vd77Ru3To98sgjevrpp/XpT386rC6UvaeeekoLFizQr371K61bt079/f26/PLL1dPTk97mpptu0k9/+lM99NBDeuqpp/Q///M/+pu/+Zv07xOJhGbNmqW+vj49++yz+t73vqcVK1Zo0aJFJrpUlk477TTddddd2rx5szZt2qS/+qu/0hVXXKHf/e53kjgGYfv1r3+tb33rWzr//PN9z3McwvH+979fu3btSj+eeeaZ9O84Bnbjvit43HuZx71XaeDeq7Rw72VW2d17eThuM2bM8BYsWJD+OZFIeBMmTPDa2toMtspOkrwf//jH6Z+TyaRXV1fnfeUrX0k/99Zbb3nxeNz7wQ9+4Hme5/3+97/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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# We load the optimal control class\n", + "# print array (optional parameter) defines, for which iterations intermediate results will be printed\n", + "# Parameters will be taken from the input model\n", + "model_controlled = oc_ww.OcWw(model, target, print_array=np.arange(0,501,25), control_matrix=control_mat, cost_matrix=cost_mat)\n", + "\n", + "# We run 500 iterations of the optimal control gradient descent algorithm\n", + "model_controlled.optimize(500)\n", + "\n", + "state = model_controlled.get_xs()\n", + "control = model_controlled.control\n", + "plot_oc_network(model.params.N, duration, dt, state, target, control, input_nw, model_controlled.cost_history, model_controlled.step_sizes_history)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Compute control for a deterministic system\n", + "Cost in iteration 0: 3.990804399212831e-11\n", + "Cost in iteration 25: 3.8701660107380814e-11\n", + "Cost in iteration 50: 3.8275743610357815e-11\n", + "Cost in iteration 75: 3.731362663528545e-11\n", + "Cost in iteration 100: 3.694171527929222e-11\n", + "Final cost : 3.694171527929222e-11\n" + ] + }, + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# perofrm another 100 iterations to improve result\n", + "# repeat execution to add another 500 iterations\n", + "# converence to the input stimulus is relatively slow for the WC nodel\n", + "model_controlled.optimize(100)\n", + "state = model_controlled.get_xs()\n", + "control = model_controlled.control\n", + "plot_oc_network(model.params.N, duration, dt, state, target, control, input_nw, model_controlled.cost_history, model_controlled.step_sizes_history)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.12" + }, + "vscode": { + "interpreter": { + "hash": "31f2aee4e71d21fbe5cf8b01ff0e069b9275f58929596ceb00d14d90e3e16cd6" + } + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/neurolib/control/optimal_control/oc.py b/neurolib/control/optimal_control/oc.py index 82fcc145..e92bece7 100644 --- a/neurolib/control/optimal_control/oc.py +++ b/neurolib/control/optimal_control/oc.py @@ -62,7 +62,9 @@ def compute_gradient( for t in range(control_interval[0], control_interval[1]): grad[n, v, t] = df_du[n, v, t] for k in range(V): - grad[n, v, t] += control_matrix[n, v] * adjoint_state[n, k, t] * d_du[n, k, v, t] + grad[n, v, t] += ( + control_matrix[n, v] * adjoint_state[n, k, t] * d_du[n, k, v, t] + ) return grad @@ -125,15 +127,115 @@ def solve_adjoint( for k in range(state_dim[1]): if dxdoth[n, k, k] == 0: res = fx_fullstate[n, k, t + 1] - res += adjoint_input(hx_list, del_list, t, T, state_dim[1], adjoint_state, n, k) - res += adjoint_nw_input(N, n, k, dmat_ndt, t, T, state_dim[1], adjoint_state, hx_nw) + res += adjoint_input( + hx_list, del_list, t, T, state_dim[1], adjoint_state, n, k + ) + res += adjoint_nw_input( + N, n, k, dmat_ndt, t, T, state_dim[1], adjoint_state, hx_nw + ) adjoint_state[n, k, t] = -res elif dxdoth[n, k, k] == 1: der = fx_fullstate[n, k, t + 1] - der += adjoint_input(hx_list, del_list, t, T, state_dim[1], adjoint_state, n, k) - der += adjoint_nw_input(N, n, k, dmat_ndt, t, T - 1, state_dim[1], adjoint_state, hx_nw) + der += adjoint_input( + hx_list, del_list, t, T, state_dim[1], adjoint_state, n, k + ) + der += adjoint_nw_input( + N, n, k, dmat_ndt, t, T - 1, state_dim[1], adjoint_state, hx_nw + ) + + adjoint_state[n, k, t] = adjoint_state[n, k, t + 1] - dt * der + + else: + print("WARNING: Case dh_dxdot != 0 or 1 not implemented") + raise NotImplementedError + + return adjoint_state + + +@numba.njit +def solve_adjoint_ww( + hx_list, + del_list, + hx_nw, + fx, + state_dim, + dt, + N, + T, + dmat_ndt, + dxdoth, + state_vars, + output_vars, +): + """Backwards integration of the adjoint state. + + :param hx_list: list of Jacobians of systems dynamics wrt. 'state_vars' + :type hx_list: list of np.ndarray + :param del_list: list of respective time delay integer + :type del_list: list of int + :param hx_nw: Jacobians for each time step for the network coupling. + :type hx_nw: np.ndarray + :param fx: df/dx Derivative of cost function wrt. systems dynamics. + :type fx: np.ndarray + :param state_dim: Dimensions of state (N, V, T). + :type state_dim: tuple + :param dt: Time resolution of integration. + :type dt: float + :param N: Number of nodes in the network. + :type N: int + :param T: Length of simulation (time dimension). + :type T: int + :param dmat_ndt: N x N delay matrix (discrete number of delayed time-intervals). + :type dmat_ndt: np.ndarray + :param dxdoth: derivative of system dynamics wrt x dot + :type dxdoth: np.ndarray + :param state_vars: list of state variables of model + :type state_vars: list + :param output_vars: list of output variables of model + :type output_vars: list + + :return: Adjoint state. + :rtype: np.ndarray of shape `state_dim` + """ + # ToDo: generalize, not only precision cost + adjoint_state = np.zeros(state_dim) + fx_fullstate = np.zeros(state_dim) + + for sv_ind, sv in enumerate(state_vars): + for ov_ind, ov in enumerate(output_vars): + if sv == ov: + fx_fullstate[:, sv_ind, :] = fx[:, ov_ind, :] + + for t in range(T - 1, -1, -1): # backwards iteration including 0th index + for n in range(N): # iterate through nodes + adjoint_state[n, 2, t] = -fx_fullstate[n, 0, t] / hx_list[0][n, t, 2, 0] + adjoint_state[n, 3, t] = -fx_fullstate[n, 1, t] / hx_list[0][n, t, 3, 1] + + for k in range(state_dim[1]): + if dxdoth[n, k, k] == 0: + res = fx_fullstate[n, k, t + 1] + res += adjoint_input( + hx_list, del_list, t, T, state_dim[1], adjoint_state, n, k + ) + res += adjoint_nw_input( + N, n, k, dmat_ndt, t, T, state_dim[1], adjoint_state, hx_nw + ) + # if n == 0 and k == 0: + # print(t, n, k, res) + # print(adjoint_state[n,]) + + adjoint_state[n, k, t] = -res + + elif dxdoth[n, k, k] == 1: + der = fx_fullstate[n, k, t] + der += adjoint_input( + hx_list, del_list, t, T, state_dim[1], adjoint_state, n, k + ) + der += adjoint_nw_input( + N, n, k, dmat_ndt, t, T - 1, state_dim[1], adjoint_state, hx_nw + ) adjoint_state[n, k, t] = adjoint_state[n, k, t + 1] - dt * der @@ -173,6 +275,9 @@ def adjoint_input(hx_list, del_list, t, T_lim, state_dim1, adj, n, k): if t + 1 + int_delay < T_lim: for v in range(state_dim1): result += adj[n, v, t + 1 + int_delay] * hx[n, t + 1 + int_delay, v, k] + if int_delay == -1 and v == 2 and k == 0: + print("adjoint = ", adj[n, v, t + 1 + int_delay]) + print("hx = ", hx[n, t + 1 + int_delay, v, k]) return result @@ -206,7 +311,10 @@ def adjoint_nw_input(N, n, k, dmat_ndt, t, T_lim, state_dim1, adj, hxnw): for n2 in range(N): # iterate through connectivity of current node "n" if t + 1 + dmat_ndt[n2, n] < T_lim: for v in range(state_dim1): - result += adj[n2, v, t + 1 + dmat_ndt[n2, n]] * hxnw[n2, n, t + 1 + dmat_ndt[n2, n], v, k] + result += ( + adj[n2, v, t + 1 + dmat_ndt[n2, n]] + * hxnw[n2, n, t + 1 + dmat_ndt[n2, n], v, k] + ) return result @@ -288,7 +396,9 @@ def convert_interval(interval, array_length): else: interval_1_new = interval_1 - assert interval_0_new < interval_1_new, "Order of indices for interval is not valid." + assert ( + interval_0_new < interval_1_new + ), "Order of indices for interval is not valid." assert interval_1_new <= array_length, "Interval is not specified in valid range." return interval_0_new, interval_1_new @@ -359,7 +469,9 @@ def __init__( if type(weights) != type(dict()): if weights is not None: - print("Weights parameter must be dictionary, use default weights instead.") + print( + "Weights parameter must be dictionary, use default weights instead." + ) self.weights = getdefaultweights() else: defaultweights = getdefaultweights() @@ -367,14 +479,22 @@ def __init__( if k in weights.keys(): defaultweights[k] = weights[k] else: - print("Weight ", k, " not in provided weight dictionary. Use default value.") + print( + "Weight ", + k, + " not in provided weight dictionary. Use default value.", + ) self.weights = defaultweights self.N = self.model.params.N self.dt = self.model.params["dt"] # maybe redundant but for now code clarity - self.duration = self.model.params["duration"] # maybe redundant but for now code clarity - self.T = np.around(self.duration / self.dt, 0).astype(int) + 1 # Total number of time steps + self.duration = self.model.params[ + "duration" + ] # maybe redundant but for now code clarity + self.T = ( + np.around(self.duration / self.dt, 0).astype(int) + 1 + ) # Total number of time steps self.dim_vars = len(self.model.state_vars) self.dim_in = len(self.model.input_vars) @@ -388,7 +508,9 @@ def __init__( if self.N == 1: self.Dmat_ndt = np.zeros((self.N, self.N)).astype(int) else: - Dmat = computeDelayMatrix(self.model.params.lengthMat, self.model.params.signalV) + Dmat = computeDelayMatrix( + self.model.params.lengthMat, self.model.params.signalV + ) if self.model.name != "aln": Dmat[np.eye(len(Dmat)) == 1] = np.zeros(len(Dmat)) else: @@ -403,11 +525,15 @@ def __init__( self.cost_matrix = cost_matrix if isinstance(self.cost_matrix, type(None)): - self.cost_matrix = np.ones((self.N, self.dim_out)) # default: measure precision in all variables and nodes + self.cost_matrix = np.ones( + (self.N, self.dim_out) + ) # default: measure precision in all variables and nodes self.control_matrix = control_matrix if isinstance(self.control_matrix, type(None)): - self.control_matrix = np.ones((self.N, self.dim_in)) # default: all channels and all nodes active + self.control_matrix = np.ones( + (self.N, self.dim_in) + ) # default: all channels and all nodes active self.M = max(1, M) self.M_validation = M_validation @@ -430,7 +556,9 @@ def __init__( + 'If you want to study a deterministic system, please set model parameter "sigma_ou" to zero' ) if self.M > self.M_validation: - print('Parameter "M_validation" should be chosen larger than parameter "M".') + print( + 'Parameter "M_validation" should be chosen larger than parameter "M".' + ) else: # deterministic system if self.M > 1 or self.M_validation != 0 or validate_per_step: print( @@ -458,7 +586,9 @@ def __init__( self.print_array = print_array - self.zero_step_encountered = False # deterministic gradient descent cannot further improve + self.zero_step_encountered = ( + False # deterministic gradient descent cannot further improve + ) self.cost_interval = convert_interval(cost_interval, self.T) self.control_interval = convert_interval(control_interval, self.T) @@ -471,14 +601,20 @@ def __init__( for v, iv in enumerate(self.model.input_vars): control[:, v, :] = self.model.params[iv] - self.control = control.copy() + self.control = control.copy() self.check_params() self.control = update_control_with_limit( - self.N, self.dim_in, self.T, control, 0.0, np.zeros(control.shape), self.maximum_control_strength + self.N, + self.dim_in, + self.T, + control, + 0.0, + np.zeros(control.shape), + self.maximum_control_strength, ) - self.model_params = self.get_model_params() + self.model_params = self.get_model_params() def check_params(self): """Checks a subset of parameters and throws an error if a wrong dimension is found.""" @@ -514,17 +650,24 @@ def adjust_init(self): for init_var in self.model.init_vars: if "ou" in init_var: continue - if init_var[:-5] not in self.model.output_vars and init_var[:-6] not in self.model.output_vars: + if ( + init_var[:-5] not in self.model.output_vars + and init_var[:-6] not in self.model.output_vars + ): continue iv = self.model.params[init_var] - self.model.params[init_var] = adjustArrayShape(iv, np.ones((self.N, init_dur))) + self.model.params[init_var] = adjustArrayShape( + iv, np.ones((self.N, init_dur)) + ) def adjust_input(self): """Adjust the shape of the array provided as input to the model. Use adjustArrayShape function from model_utils.""" for input_var in self.model.input_vars: iv = self.model.params[input_var] - self.model.params[input_var] = adjustArrayShape(iv, np.ones((self.N, self.T))) + self.model.params[input_var] = adjustArrayShape( + iv, np.ones((self.N, self.T)) + ) def get_xs(self): """Extract the complete state of the dynamical system.""" @@ -609,7 +752,9 @@ def compute_total_cost(self): self.dt, self.cost_interval, ) - control_strenght_cost = cost_functions.control_strength_cost(self.control, self.weights, self.dt) + control_strenght_cost = cost_functions.control_strength_cost( + self.control, self.weights, self.dt + ) return accuracy_cost + control_strenght_cost @abc.abstractmethod @@ -624,7 +769,9 @@ def compute_gradient(self): :rtype: np.ndarray of shape N x V x T """ self.solve_adjoint() - df_du = cost_functions.derivative_control_strength_cost(self.control, self.weights) + df_du = cost_functions.derivative_control_strength_cost( + self.control, self.weights + ) d_du = self.Duh() return compute_gradient( @@ -670,7 +817,7 @@ def solve_adjoint(self): self.cost_matrix, self.cost_interval, ) - self.adjoint_state = solve_adjoint( + self.adjoint_state = solve_adjoint_ww( hx_list, del_list, hx_nw, @@ -714,14 +861,22 @@ def decrease_step(self, cost, cost0, step, control0, factor_down, cost_gradient) counter = 0 - while cost > cost0: # Decrease the step size until first step size is found where cost is improved. + while ( + cost > cost0 + ): # Decrease the step size until first step size is found where cost is improved. step *= factor_down # Decrease step size. counter += 1 # print(step, cost, cost0) # Inplace updating of models control bc. forward-sim relies on models parameters. self.control = update_control_with_limit( - self.N, self.dim_in, self.T, control0, step, cost_gradient, self.maximum_control_strength + self.N, + self.dim_in, + self.T, + control0, + step, + cost_gradient, + self.maximum_control_strength, ) self.update_input() @@ -733,11 +888,19 @@ def decrease_step(self, cost, cost0, step, control0, factor_down, cost_gradient) else: cost = self.compute_total_cost() - if counter == self.count_step: # Exit if the maximum search depth is reached without improvement of + if ( + counter == self.count_step + ): # Exit if the maximum search depth is reached without improvement of # cost. step = 0.0 # For later analysis only. self.control = update_control_with_limit( - self.N, self.dim_in, self.T, control0, 0.0, np.zeros(control0.shape), self.maximum_control_strength + self.N, + self.dim_in, + self.T, + control0, + 0.0, + np.zeros(control0.shape), + self.maximum_control_strength, ) self.update_input() @@ -776,23 +939,39 @@ def increase_step(self, cost, cost0, step, control0, factor_up, cost_gradient): cost_prev = cost0 counter = 0 - while cost < cost_prev: # Increase the step size as long as the cost is improving. + while ( + cost < cost_prev + ): # Increase the step size as long as the cost is improving. step *= factor_up counter += 1 # Inplace updating of models control bc. forward-sim relies on models parameters self.control = update_control_with_limit( - self.N, self.dim_in, self.T, control0, step, cost_gradient, self.maximum_control_strength + self.N, + self.dim_in, + self.T, + control0, + step, + cost_gradient, + self.maximum_control_strength, ) self.update_input() self.simulate_forward() - if np.isnan(self.get_xs()).any(): # Go back to last step (that was numerically stable and improved cost) + if np.isnan( + self.get_xs() + ).any(): # Go back to last step (that was numerically stable and improved cost) # and exit. logging.info("Increasing step encountered NAN.") step /= factor_up # Undo the last step update by inverse operation. self.control = update_control_with_limit( - self.N, self.dim_in, self.T, control0, step, cost_gradient, self.maximum_control_strength + self.N, + self.dim_in, + self.T, + control0, + step, + cost_gradient, + self.maximum_control_strength, ) self.update_input() break @@ -803,11 +982,19 @@ def increase_step(self, cost, cost0, step, control0, factor_up, cost_gradient): else: cost = self.compute_total_cost() - if cost > cost_prev: # If the cost increases: go back to last step (that resulted in best cost until + if ( + cost > cost_prev + ): # If the cost increases: go back to last step (that resulted in best cost until # then) and exit. step /= factor_up # Undo the last step update by inverse operation. self.control = update_control_with_limit( - self.N, self.dim_in, self.T, control0, step, cost_gradient, self.maximum_control_strength + self.N, + self.dim_in, + self.T, + control0, + step, + cost_gradient, + self.maximum_control_strength, ) self.update_input() break @@ -843,22 +1030,38 @@ def step_size(self, cost_gradient): self.compute_total_cost() ) # Current cost without updating the control according to the "cost_gradient". - step = self.step # Load step size of last optimization-iteration as initial guess. + step = ( + self.step + ) # Load step size of last optimization-iteration as initial guess. - control0 = self.control # Memorize unchanged control throughout step-size computation. + control0 = ( + self.control + ) # Memorize unchanged control throughout step-size computation. - while True: # Reduce the step size, if numerical instability occurs in the forward-simulation. + while ( + True + ): # Reduce the step size, if numerical instability occurs in the forward-simulation. # inplace updating of models control bc. forward-sim relies on models parameters self.control = update_control_with_limit( - self.N, self.dim_in, self.T, control0, step, cost_gradient, self.maximum_control_strength + self.N, + self.dim_in, + self.T, + control0, + step, + cost_gradient, + self.maximum_control_strength, ) self.update_input() # Input signal might be too high and produce diverging values in simulation. self.simulate_forward() - if np.isnan(self.get_xs()).any(): # Detect numerical instability due to too large control update. - step *= self.factor_down**2 # Double the step for faster search of stable region. + if np.isnan( + self.get_xs() + ).any(): # Detect numerical instability due to too large control update. + step *= ( + self.factor_down**2 + ) # Double the step for faster search of stable region. self.step = step print(f"Diverging model output, decrease step size to {step}.") else: @@ -874,14 +1077,18 @@ def step_size(self, cost_gradient): if ( cost > cost0 ): # If the cost choosing the first (stable) step size is no improvement, reduce step size by bisection. - step, counter = self.decrease_step(cost, cost0, step, control0, self.factor_down, cost_gradient) + step, counter = self.decrease_step( + cost, cost0, step, control0, self.factor_down, cost_gradient + ) elif ( cost < cost0 ): # If the cost is improved with the first (stable) step size, search for larger steps with even better # reduction of cost. - step, counter = self.increase_step(cost, cost0, step, control0, self.factor_up, cost_gradient) + step, counter = self.increase_step( + cost, cost0, step, control0, self.factor_up, cost_gradient + ) else: # Remark: might be included as part of adaptive search for further improvement. step = 0.0 # For later analysis only. @@ -909,9 +1116,17 @@ def optimize(self, n_max_iterations): self.control_interval = convert_interval(self.control_interval, self.T) self.control = update_control_with_limit( - self.N, self.dim_in, self.T, self.control, 0.0, np.zeros(self.control.shape), self.maximum_control_strength + self.N, + self.dim_in, + self.T, + self.control, + 0.0, + np.zeros(self.control.shape), + self.maximum_control_strength, ) # To avoid issues in repeated executions. - self.control = limit_control_to_interval(self.N, self.dim_in, self.T, self.control, self.control_interval) + self.control = limit_control_to_interval( + self.N, self.dim_in, self.T, self.control, self.control_interval + ) if self.M == 1: print("Compute control for a deterministic system") @@ -932,7 +1147,9 @@ def optimize_deterministic(self, n_max_iterations): cost = self.compute_total_cost() print(f"Cost in iteration 0: %s" % (cost)) - if len(self.cost_history) == 0: # add only if control model has not yet been optimized + if ( + len(self.cost_history) == 0 + ): # add only if control model has not yet been optimized self.cost_history.append(cost) for i in range(1, n_max_iterations + 1): @@ -970,7 +1187,9 @@ def optimize_noisy(self, n_max_iterations): if len(self.control_history) == 0: self.control_history.append(self.control) - if self.validate_per_step: # if cost is computed for M_validation realizations in every step + if ( + self.validate_per_step + ): # if cost is computed for M_validation realizations in every step for m in range(self.M): self.simulate_forward() grad_m[m, :] = self.compute_gradient() @@ -1005,12 +1224,16 @@ def optimize_noisy(self, n_max_iterations): print("Failed to improve further for noisy system.") if consecutive_zero_step > 2: - print("Failed to improve further for noisy system three times in a row, stop optimization.") + print( + "Failed to improve further for noisy system three times in a row, stop optimization." + ) break self.control_history.append(self.control) - if self.validate_per_step: # if cost is computed for M_validation realizations in every step + if ( + self.validate_per_step + ): # if cost is computed for M_validation realizations in every step for m in range(self.M): self.simulate_forward() grad_m[m, :] = self.compute_gradient() @@ -1036,7 +1259,10 @@ def optimize_noisy(self, n_max_iterations): self.control = oc self.update_input() self.cost_validation = self.compute_cost_noisy(self.M_validation) - print(f"Final cost validated with %s noise realizations : %s" % (self.M_validation, self.cost_validation)) + print( + f"Final cost validated with %s noise realizations : %s" + % (self.M_validation, self.cost_validation) + ) def compute_cost_noisy(self, M): """Computes the average cost from 'M_validation' noise realizations. diff --git a/neurolib/control/optimal_control/oc_ww/__init__.py b/neurolib/control/optimal_control/oc_ww/__init__.py new file mode 100644 index 00000000..22b96d13 --- /dev/null +++ b/neurolib/control/optimal_control/oc_ww/__init__.py @@ -0,0 +1 @@ +from .oc_ww import OcWw diff --git a/neurolib/control/optimal_control/oc_ww/oc_ww.py b/neurolib/control/optimal_control/oc_ww/oc_ww.py new file mode 100644 index 00000000..872d3fe8 --- /dev/null +++ b/neurolib/control/optimal_control/oc_ww/oc_ww.py @@ -0,0 +1,173 @@ +import numba + +from neurolib.control.optimal_control.oc import OC +from neurolib.models.ww.timeIntegration import ( + compute_hx, + compute_hx_min1, + compute_hx_nw, + Duh, + Dxdoth, +) + + +class OcWw(OC): + """Class for optimal control specific to neurolib's implementation of the two-population Wong-Wang model + ("WWmodel"). + + :param model: Instance of Wong-Wang model (can describe a single Wong-Wang node or a network of coupled + Wong-Wang nodes. + :type model: neurolib.models.ww.model.WWModel + """ + + def __init__( + self, + model, + target, + weights=None, + print_array=[], + cost_interval=(None, None), + cost_matrix=None, + control_matrix=None, + M=1, + M_validation=0, + validate_per_step=False, + ): + super().__init__( + model, + target, + weights=weights, + print_array=print_array, + cost_interval=cost_interval, + cost_matrix=cost_matrix, + control_matrix=control_matrix, + M=M, + M_validation=M_validation, + validate_per_step=validate_per_step, + ) + + assert self.model.name == "wongwang" + + def compute_dxdoth(self): + """Derivative of systems dynamics wrt. change of systems variables.""" + return Dxdoth(self.N, self.dim_vars) + + def get_model_params(self): + """Model params as an ordered tuple. + + :rtype: tuple + """ + return ( + self.model.params.a_exc, + self.model.params.b_exc, + self.model.params.d_exc, + self.model.params.tau_exc, + self.model.params.gamma_exc, + self.model.params.w_exc, + self.model.params.exc_current_baseline, + self.model.params.a_inh, + self.model.params.b_inh, + self.model.params.d_inh, + self.model.params.tau_inh, + self.model.params.w_inh, + self.model.params.inh_current_baseline, + self.model.params.J_NMDA, + self.model.params.J_I, + self.model.params.w_ee, + ) + + def Duh(self): + """Jacobian of systems dynamics wrt. external control input. + + :return: N x 4 x 4 x T Jacobians. + :rtype: np.ndarray + """ + + xs = self.get_xs() + xsd = self.get_xs_delay() + + return Duh( + self.model_params, + self.N, + self.dim_in, + self.dim_vars, + self.T, + self.control[:, self.state_vars_dict["r_exc"], :], + self.control[:, self.state_vars_dict["r_inh"], :], + xs[:, self.state_vars_dict["se"], :], + xs[:, self.state_vars_dict["si"], :], + self.model.params.K_gl, + self.model.params.Cmat, + self.Dmat_ndt, + xsd[:, self.state_vars_dict["se"], :], + self.state_vars_dict, + ) + + def compute_hx_list(self): + """List of Jacobians without and with time delays (e.g. in the ALN model) and list of respective time step delays as integers (0 for undelayed) + + :return: List of Jacobian matrices, list of time step delays + : rtype: List of np.ndarray, List of integers + """ + hx = self.compute_hx() + hx_min1 = self.compute_hx_min1() + return numba.typed.List([hx]), numba.typed.List([0]) + + def compute_hx(self): + """Jacobians of WwModel wrt. all variables. + + :return: N x T x 6 x 6 Jacobians. + :rtype: np.ndarray + """ + return compute_hx( + self.model_params, + self.model.params.K_gl, + self.model.Cmat, + self.Dmat_ndt, + self.N, + self.dim_vars, + self.T, + self.get_xs(), + self.get_xs_delay(), + self.control, + self.state_vars_dict, + ) + + def compute_hx_min1(self): + """Jacobians of WWModel dse/dre and dsi/dri. + Dependency is in same time step, so shift by -1 in time is required for OC computation. + + :return: N x T x 6 x 6 Jacobians. + :rtype: np.ndarray + """ + return compute_hx_min1( + self.model_params, + self.N, + self.dim_vars, + self.T, + self.get_xs(), + self.state_vars_dict, + ) + + def compute_hx_nw(self): + """Jacobians for each time step for the network coupling. + + :return: N x N x T x (4x4) array + :rtype: np.ndarray + """ + + xs = self.get_xs() + + return compute_hx_nw( + self.model_params, + self.model.params.K_gl, + self.model.Cmat, + self.Dmat_ndt, + self.N, + self.dim_vars, + self.T, + xs[:, self.state_vars_dict["se"], :], + xs[:, self.state_vars_dict["se"], :], + self.get_xs_delay()[:, self.state_vars_dict["se"], :], + self.control[:, self.state_vars_dict["r_exc"], :], + self.state_vars_dict, + ) diff --git a/neurolib/models/wc/timeIntegration.py b/neurolib/models/wc/timeIntegration.py index b5a8d3ec..f68d0381 100644 --- a/neurolib/models/wc/timeIntegration.py +++ b/neurolib/models/wc/timeIntegration.py @@ -209,7 +209,9 @@ def S_I(x): exc_input_d[no] = 0 for l in range(N): - exc_input_d[no] += K_gl * Cmat[no, l] * (excs[l, i - Dmat_ndt[no, l] - 1]) + exc_input_d[no] += ( + K_gl * Cmat[no, l] * (excs[l, i - Dmat_ndt[no, l] - 1]) + ) # Wilson-Cowan model exc_rhs = ( @@ -219,8 +221,10 @@ def S_I(x): -excs[no, i - 1] + (1 - excs[no, i - 1]) * S_E( - c_excexc * excs[no, i - 1] # input from within the excitatory population - - c_inhexc * inhs[no, i - 1] # input from the inhibitory population + c_excexc + * excs[no, i - 1] # input from within the excitatory population + - c_inhexc + * inhs[no, i - 1] # input from the inhibitory population + exc_input_d[no] # input from other nodes + exc_ext_baseline # baseline external input (static) + exc_ext[no, i - 1] # time-dependent external input @@ -235,8 +239,10 @@ def S_I(x): -inhs[no, i - 1] + (1 - inhs[no, i - 1]) * S_I( - c_excinh * excs[no, i - 1] # input from the excitatory population - - c_inhinh * inhs[no, i - 1] # input from within the inhibitory population + c_excinh + * excs[no, i - 1] # input from the excitatory population + - c_inhinh + * inhs[no, i - 1] # input from within the inhibitory population + inh_ext_baseline # baseline external input (static) + inh_ext[no, i - 1] # time-dependent external input ) @@ -261,10 +267,14 @@ def S_I(x): # Ornstein-Uhlenbeck process exc_ou[no] = ( - exc_ou[no] + (exc_ou_mean - exc_ou[no]) * dt / tau_ou + sigma_ou * sqrt_dt * noise_exc[no] + exc_ou[no] + + (exc_ou_mean - exc_ou[no]) * dt / tau_ou + + sigma_ou * sqrt_dt * noise_exc[no] ) # mV/ms inh_ou[no] = ( - inh_ou[no] + (inh_ou_mean - inh_ou[no]) * dt / tau_ou + sigma_ou * sqrt_dt * noise_inh[no] + inh_ou[no] + + (inh_ou_mean - inh_ou[no]) * dt / tau_ou + + sigma_ou * sqrt_dt * noise_inh[no] ) # mV/ms return t, excs, inhs, exc_ou, inh_ou @@ -313,20 +323,20 @@ def jacobian_wc( :param model_params: Tuple of parameters in the WC Model in order :type model_params: tuple of float - :param nw_e: N x T input of network into each node's 'exc' - :type nw_e: np.ndarray - :param e: Value of the E-variable at specific time. - :type e: float - :param i: Value of the I-variable at specific time. - :type i: float - :param ue: N x T combined input of 'background' and 'control' into 'exc'. - :type ue: np.ndarray - :param ui: N x T combined input of 'background' and 'control' into 'inh'. - :type ui: np.ndarray - :param V: Number of system variables. - :type V: int - :param sv: dictionary of state vars and respective indices - :type sv: dict + :param nw_e: N x T input of network into each node's 'exc' + :type nw_e: np.ndarray + :param e: Value of the E-variable at specific time. + :type e: float + :param i: Value of the I-variable at specific time. + :type i: float + :param ue: Value of control input to into 'exc' at specific time. + :type ue: float + :param ui: Value of control input to into 'ihn' at specific time. + :type ui: float + :param V: Number of system variables. + :type V: int + :param sv: dictionary of state vars and respective indices + :type sv: dict :return: 4 x 4 Jacobian matrix. :rtype: np.ndarray @@ -349,14 +359,26 @@ def jacobian_wc( jacobian = np.zeros((V, V)) input_exc = c_excexc * e - c_inhexc * i + nw_e + exc_ext_baseline + ue jacobian[sv["exc"], sv["exc"]] = ( - -(-1.0 - logistic(input_exc, a_exc, mu_exc) + (1.0 - e) * c_excexc * logistic_der(input_exc, a_exc, mu_exc)) + -( + -1.0 + - logistic(input_exc, a_exc, mu_exc) + + (1.0 - e) * c_excexc * logistic_der(input_exc, a_exc, mu_exc) + ) / tau_exc ) - jacobian[sv["exc"], sv["inh"]] = -((1.0 - e) * (-c_inhexc) * logistic_der(input_exc, a_exc, mu_exc)) / tau_exc + jacobian[sv["exc"], sv["inh"]] = ( + -((1.0 - e) * (-c_inhexc) * logistic_der(input_exc, a_exc, mu_exc)) / tau_exc + ) input_inh = c_excinh * e - c_inhinh * i + inh_ext_baseline + ui - jacobian[sv["inh"], sv["exc"]] = -((1.0 - i) * c_excinh * logistic_der(input_inh, a_inh, mu_inh)) / tau_inh + jacobian[sv["inh"], sv["exc"]] = ( + -((1.0 - i) * c_excinh * logistic_der(input_inh, a_inh, mu_inh)) / tau_inh + ) jacobian[sv["inh"], sv["inh"]] = ( - -(-1.0 - logistic(input_inh, a_inh, mu_inh) + (1.0 - i) * (-c_inhinh) * logistic_der(input_inh, a_inh, mu_inh)) + -( + -1.0 + - logistic(input_inh, a_inh, mu_inh) + + (1.0 - i) * (-c_inhinh) * logistic_der(input_inh, a_inh, mu_inh) + ) / tau_inh ) return jacobian @@ -450,7 +472,9 @@ def compute_nw_input(N, T, K_gl, cmat, dmat_ndt, exc_values): for t in range(1, T): for n in range(N): for l in range(N): - nw_input[n, t] += K_gl * cmat[n, l] * (exc_values[l, t - dmat_ndt[n, l] - 1]) + nw_input[n, t] += ( + K_gl * cmat[n, l] * (exc_values[l, t - dmat_ndt[n, l] - 1]) + ) return nw_input @@ -543,7 +567,7 @@ def Duh( K_gl, cmat, dmat_ndt, - exc_values, + exc_delay, sv, ): """Jacobian of systems dynamics wrt. external inputs (control signals). @@ -574,8 +598,8 @@ def Duh( :type cmat: np.ndarray :param dmat_ndt: delay index matrix :type dmat_ndt: np.ndarray - :param exc_values: N x T array containing values of 'exc' of all nodes through time. - :type exc_values: np.ndarray + :param exc_delay: N x T array containing values of 'exc' of all nodes through time incl. delay + :type exc_delay: np.ndarray :param sv: dictionary of state vars and respective indices :type sv: dict @@ -597,15 +621,27 @@ def Duh( inh_ext_baseline, ) = model_params - nw_e = compute_nw_input(N, T, K_gl, cmat, dmat_ndt, exc_values) + nw_e = compute_nw_input(N, T, K_gl, cmat, dmat_ndt, exc_delay) duh = np.zeros((N, V_vars, V_in, T)) for t in range(T): for n in range(N): - input_exc = c_excexc * e[n, t] - c_inhexc * i[n, t] + nw_e[n, t] + exc_ext_baseline + ue[n, t] - duh[n, sv["exc"], sv["exc"], t] = -(1.0 - e[n, t]) * logistic_der(input_exc, a_exc, mu_exc) / tau_exc - input_inh = c_excinh * e[n, t] - c_inhinh * i[n, t] + inh_ext_baseline + ui[n, t] - duh[n, sv["inh"], sv["inh"], t] = -(1.0 - i[n, t]) * logistic_der(input_inh, a_inh, mu_inh) / tau_inh + input_exc = ( + c_excexc * e[n, t] + - c_inhexc * i[n, t] + + nw_e[n, t] + + exc_ext_baseline + + ue[n, t] + ) + duh[n, sv["exc"], sv["exc"], t] = ( + -(1.0 - e[n, t]) * logistic_der(input_exc, a_exc, mu_exc) / tau_exc + ) + input_inh = ( + c_excinh * e[n, t] - c_inhinh * i[n, t] + inh_ext_baseline + ui[n, t] + ) + duh[n, sv["inh"], sv["inh"], t] = ( + -(1.0 - i[n, t]) * logistic_der(input_inh, a_inh, mu_inh) / tau_inh + ) return duh diff --git a/neurolib/models/ww/model.py b/neurolib/models/ww/model.py index 12d72ebc..2b4d3804 100644 --- a/neurolib/models/ww/model.py +++ b/neurolib/models/ww/model.py @@ -30,9 +30,10 @@ class WWModel(Model): state_vars = ["r_exc", "r_inh", "se", "si", "exc_ou", "inh_ou"] output_vars = ["r_exc", "r_inh", "se", "si"] default_output = "r_exc" + input_vars = ["exc_current", "inh_current"] + default_input = "exc_current" def __init__(self, params=None, Cmat=None, Dmat=None, seed=None): - self.Cmat = Cmat self.Dmat = Dmat self.seed = seed @@ -42,7 +43,9 @@ def __init__(self, params=None, Cmat=None, Dmat=None, seed=None): # load default parameters if none were given if params is None: - params = dp.loadDefaultParams(Cmat=self.Cmat, Dmat=self.Dmat, seed=self.seed) + params = dp.loadDefaultParams( + Cmat=self.Cmat, Dmat=self.Dmat, seed=self.seed + ) # Initialize base class Model super().__init__(integration=integration, params=params) diff --git a/neurolib/models/ww/timeIntegration.py b/neurolib/models/ww/timeIntegration.py index ae213ac1..f53c139a 100644 --- a/neurolib/models/ww/timeIntegration.py +++ b/neurolib/models/ww/timeIntegration.py @@ -257,7 +257,9 @@ def r(I, a, b, d): # input from other nodes for l in range(N): - ses_input_d[no] += K_gl * Cmat[no, l] * (ses[l, i - Dmat_ndt[no, l] - 1]) + ses_input_d[no] += ( + K_gl * Cmat[no, l] * (ses[l, i - Dmat_ndt[no, l] - 1]) + ) # Wong-Wang se = ses[no, i - 1] @@ -269,12 +271,18 @@ def r(I, a, b, d): - J_I * si + J_NMDA * ses_input_d[no] ) - I_inh = w_inh * (inh_current_baseline + inh_current[no, i - 1]) + J_NMDA * se - si + I_inh = ( + w_inh * (inh_current_baseline + inh_current[no, i - 1]) + + J_NMDA * se + - si + ) r_exc[no, i] = r(I_exc, a_exc, b_exc, d_exc) r_inh[no, i] = r(I_inh, a_inh, b_inh, d_inh) - se_rhs = -(se / tau_exc) + (1 - se) * gamma_exc * r_exc[no, i] + exc_ou[no] # exc_ou = ou noise + se_rhs = ( + -(se / tau_exc) + (1 - se) * gamma_exc * r_exc[no, i] + exc_ou[no] + ) # exc_ou = ou noise si_rhs = -(si / tau_inh) + r_inh[no, i] + inh_ou[no] # Euler integration @@ -283,10 +291,510 @@ def r(I, a, b, d): # Ornstein-Uhlenberg process exc_ou[no] = ( - exc_ou[no] + (exc_ou_mean - exc_ou[no]) * dt / tau_ou + sigma_ou * sqrt_dt * noise_se[no] + exc_ou[no] + + (exc_ou_mean - exc_ou[no]) * dt / tau_ou + + sigma_ou * sqrt_dt * noise_se[no] ) # mV/ms inh_ou[no] = ( - inh_ou[no] + (inh_ou_mean - inh_ou[no]) * dt / tau_ou + sigma_ou * sqrt_dt * noise_si[no] + inh_ou[no] + + (inh_ou_mean - inh_ou[no]) * dt / tau_ou + + sigma_ou * sqrt_dt * noise_si[no] ) # mV/ms return t, r_exc, r_inh, ses, sis, exc_ou, inh_ou + + +@numba.njit +def logistic(x, a, b, d): + """Logistic function evaluated at point 'x'. + + :type x: float + :param a: Parameter of logistic function. + :type a: float + :param b: Parameter of logistic function. + :type b: float + :param d: Parameter of logistic function. + :type d: float + + :rtype: float + """ + return (a * x - b) / (1.0 - np.exp(-d * (a * x - b))) + + +@numba.njit +def logistic_der(x, a, b, d): + """Derivative of logistic function, evaluated at point 'x'. + + :type x: float + :param a: Parameter of logistic function. + :type a: float + :param b: Parameter of logistic function. + :type b: float + :param d: Parameter of logistic function. + :type d: float + + :rtype: float + """ + exp = np.exp(-d * (a * x - b)) + return (a * (1.0 - exp) - (a * x - b) * d * a * exp) / (1.0 - exp) ** 2 + + +@numba.njit +def jacobian_ww( + model_params, + nw_se, + re, + se, + si, + ue, + ui, + V, + sv, +): + """Jacobian of the WW dynamical system. + + :param model_params: Tuple of parameters in the WC Model in order + :type model_params: tuple of float + :param nw_se: N x T input of network into each node's 'exc' + :type nw_se: np.ndarray + :param re: Value of the r_exc-variable at specific time. + :type re: float + :param se: Value of the se-variable at specific time. + :type se: float + :param si: Value of the si-variable at specific time. + :type si: float + :param ue: Value of control input to into 'exc' at specific time. + :type ue: float + :param ui: Value of control input to into 'ihn' at specific time. + :type ui: float + :param V: Number of system variables. + :type V: int + :param sv: dictionary of state vars and respective indices + :type sv: dict + + :return: 4 x 4 Jacobian matrix. + :rtype: np.ndarray + """ + ( + a_exc, + b_exc, + d_exc, + tau_exc, + gamma_exc, + w_exc, + exc_current_baseline, + a_inh, + b_inh, + d_inh, + tau_inh, + w_inh, + inh_current_baseline, + J_NMDA, + J_I, + w_ee, + ) = model_params + + jacobian = np.zeros((V, V)) + IE = ( + w_exc * (exc_current_baseline + ue) + + w_ee * J_NMDA * se + - J_I * si + + J_NMDA * nw_se + ) + jacobian[sv["r_exc"], sv["se"]] = ( + -logistic_der(IE, a_exc, b_exc, d_exc) * w_ee * J_NMDA + ) + jacobian[sv["r_exc"], sv["si"]] = logistic_der(IE, a_exc, b_exc, d_exc) * J_I + II = w_inh * (inh_current_baseline + ui) + J_NMDA * se - si + jacobian[sv["r_inh"], sv["se"]] = -logistic_der(II, a_inh, b_inh, d_inh) * J_NMDA + jacobian[sv["r_inh"], sv["si"]] = logistic_der(II, a_inh, b_inh, d_inh) + + jacobian[sv["se"], sv["r_exc"]] = -(1.0 - se) * gamma_exc + jacobian[sv["se"], sv["se"]] = 1.0 / tau_exc + gamma_exc * re + + jacobian[sv["si"], sv["r_inh"]] = -1.0 + jacobian[sv["si"], sv["si"]] = 1.0 / tau_inh + return jacobian + + +@numba.njit +def compute_hx( + wc_model_params, + K_gl, + cmat, + dmat_ndt, + N, + V, + T, + dyn_vars, + dyn_vars_delay, + control, + sv, +): + """Jacobians of WWModel wrt. the all variables for each time step. + + :param model_params: Tuple of parameters in the WC Model in order + :type model_params: tuple of float + :param K_gl: Model parameter of global coupling strength. + :type K_gl: float + :param cmat: Model parameter, connectivity matrix. + :type cmat: ndarray + :param dmat_ndt: N x N delay matrix in multiples of dt. + :type dmat_ndt: np.ndarray + :param N: Number of nodes in the network. + :type N: int + :param V: Number of system variables. + :type V: int + :param T: Length of simulation (time dimension). + :type T: int + :param dyn_vars: N x V x T array containing all values of 'exc' and 'inh'. + :type dyn_vars: np.ndarray + :param dyn_vars_delay: + :type dyn_vars_delay: np.ndarray + :param control: N x 2 x T control inputs to 'exc' and 'inh'. + :type control: np.ndarray + :param sv: dictionary of state vars and respective indices + :type sv: dict + + :return: N x T x 4 x 4 Jacobians. + :rtype: np.ndarray + """ + hx = np.zeros((N, T, V, V)) + nw_e = compute_nw_input(N, T, K_gl, cmat, dmat_ndt, dyn_vars_delay[:, sv["se"], :]) + + for n in range(N): + for t in range(T): + re = dyn_vars[n, sv["r_exc"], t] + se = dyn_vars[n, sv["se"], t] + si = dyn_vars[n, sv["si"], t] + ue = control[n, sv["r_exc"], t] + ui = control[n, sv["r_inh"], t] + hx[n, t, :, :] = jacobian_ww( + wc_model_params, + nw_e[n, t], + re, + se, + si, + ue, + ui, + V, + sv, + ) + return hx + + +@numba.njit +def jacobian_ww_min1( + model_params, + se, + V, + sv, +): + """Jacobian of the WW dynamical system. + + :param model_params: Tuple of parameters in the WC Model in order + :type model_params: tuple of float + :param se: Value of the se-variable at specific time. + :type se: float + :param V: Number of system variables. + :type V: int + :param sv: dictionary of state vars and respective indices + :type sv: dict + + :return: 4 x 4 Jacobian matrix. + :rtype: np.ndarray + """ + ( + a_exc, + b_exc, + d_exc, + tau_exc, + gamma_exc, + w_exc, + exc_current_baseline, + a_inh, + b_inh, + d_inh, + tau_inh, + w_inh, + inh_current_baseline, + J_NMDA, + J_I, + w_ee, + ) = model_params + + jacobian = np.zeros((V, V)) + + jacobian[sv["se"], sv["r_exc"]] = -(1.0 - se) * gamma_exc + jacobian[sv["si"], sv["r_inh"]] = -1.0 + return jacobian + + +@numba.njit +def compute_hx_min1( + wc_model_params, + N, + V, + T, + dyn_vars, + sv, +): + """Jacobians of WWModel wrt. the all variables for each time step. + + :param model_params: Tuple of parameters in the WC Model in order + :type model_params: tuple of float + :param N: Number of nodes in the network. + :type N: int + :param V: Number of system variables. + :type V: int + :param T: Length of simulation (time dimension). + :type T: int + :param dyn_vars: N x V x T array containing all values of 'exc' and 'inh'. + :type dyn_vars: np.ndarray + :param sv: dictionary of state vars and respective indices + :type sv: dict + + :return: N x T x 4 x 4 Jacobians. + :rtype: np.ndarray + """ + hx = np.zeros((N, T, V, V)) + + for n in range(N): + for t in range(T): + se = dyn_vars[n, sv["se"], t] + hx[n, t, :, :] = jacobian_ww_min1( + wc_model_params, + se, + V, + sv, + ) + return hx + + +@numba.njit +def compute_nw_input(N, T, K_gl, cmat, dmat_ndt, se): + """Compute input by other nodes of network into each node's 'exc' population at every timestep. + + :param N: Number of nodes in the network. + :type N: int + :param T: Length of simulation (time dimension). + :type T: int + :param K_gl: Model parameter of global coupling strength. + :type K_gl: float + :param cmat: Model parameter, connectivity matrix. + :type cmat: ndarray + :param dmat_ndt: N x N delay matrix in multiples of dt. + :type dmat_ndt: np.ndarray + :param se: N x T array containing values of 'exc' of all nodes through time. + :type se: np.ndarray + :return: N x T network inputs. + :rytpe: np.ndarray + """ + nw_input = np.zeros((N, T)) + + for t in range(1, T): + for n in range(N): + for l in range(N): + nw_input[n, t] += K_gl * cmat[n, l] * (se[l, t - dmat_ndt[n, l] - 1]) + return nw_input + + +@numba.njit +def compute_hx_nw( + model_params, + K_gl, + cmat, + dmat_ndt, + N, + V, + T, + se, + si, + se_delay, + ue, + sv, +): + """Jacobians for network connectivity in all time steps. + + :param model_params: Tuple of parameters in the WC Model in order + :type model_params: tuple of float + :param K_gl: Model parameter of global coupling strength. + :type K_gl: float + :param cmat: Model parameter, connectivity matrix. + :type cmat: ndarray + :param dmat_ndt: N x N delay matrix in multiples of dt. + :type dmat_ndt: np.ndarray + :param N: Number of nodes in the network. + :type N: int + :param V: Number of system variables. + :type V: int + :param T: Length of simulation (time dimension). + :type T: int + :param se: Array of the se-variable. + :type se: np.ndarray + :param si: Array of the se-variable. + :type si: np.ndarray + :param se_delay: Value of delayed se-variable. + :type se_delay: np.ndarray + :param ue: N x T array of the total input received by 'exc' population in every node at any time. + :type ue: np.ndarray + :param sv: dictionary of state vars and respective indices + :type sv: dict + + :return: Jacobians for network connectivity in all time steps. + :rtype: np.ndarray of shape N x N x T x 4 x 4 + """ + ( + a_exc, + b_exc, + d_exc, + tau_exc, + gamma_exc, + w_exc, + exc_current_baseline, + a_inh, + b_inh, + d_inh, + tau_inh, + w_inh, + inh_current_baseline, + J_NMDA, + J_I, + w_ee, + ) = model_params + hx_nw = np.zeros((N, N, T, V, V)) + + nw_e = compute_nw_input(N, T, K_gl, cmat, dmat_ndt, se_delay) + IE = ( + w_exc * (exc_current_baseline + ue) + + w_ee * J_NMDA * se + - J_I * si + + J_NMDA * nw_e + ) + + for n1 in range(N): + for n2 in range(N): + for t in range(T - 1): + hx_nw[n1, n2, t, sv["r_exc"], sv["se"]] = ( + logistic_der(IE[n1, t], a_exc, b_exc, d_exc) + * J_NMDA + * K_gl + * cmat[n1, n2] + ) + + return -hx_nw + + +@numba.njit +def Duh( + model_params, + N, + V_in, + V_vars, + T, + ue, + ui, + se, + si, + K_gl, + cmat, + dmat_ndt, + se_delay, + sv, +): + """Jacobian of systems dynamics wrt. external inputs (control signals). + + :param model_params: Tuple of parameters in the WC Model in order + :type model_params: tuple of float + :param N: Number of nodes in the network. + :type N: int + :param V_in: Number of input variables. + :type V_in: int + :param V_vars: Number of system variables. + :type V_vars: int + :param T: Length of simulation (time dimension). + :type T: int + :param nw_e: N x T input of network into each node's 'exc' + :type nw_e: np.ndarray + :param ue: N x T array of the total input received by 'exc' population in every node at any time. + :type ue: np.ndarray + :param ui: N x T array of the total input received by 'inh' population in every node at any time. + :type ui: np.ndarray + :param se: Value of the se-variable for each node and timepoint + :type se: np.ndarray + :param si: Value of the si-variable for each node and timepoint + :type si: np.ndarray + :param K_gl: global coupling strength + :type K_gl float + :param cmat: coupling matrix + :type cmat: np.ndarray + :param dmat_ndt: delay index matrix + :type dmat_ndt: np.ndarray + :param se_delay: N x T array containing values of 'exc' of all nodes through time. + :type se_delay: np.ndarray + :param sv: dictionary of state vars and respective indices + :type sv: dict + + :rtype: np.ndarray of shape N x V x V x T + """ + + ( + a_exc, + b_exc, + d_exc, + tau_exc, + gamma_exc, + w_exc, + exc_current_baseline, + a_inh, + b_inh, + d_inh, + tau_inh, + w_inh, + inh_current_baseline, + J_NMDA, + J_I, + w_ee, + ) = model_params + + nw_e = compute_nw_input(N, T, K_gl, cmat, dmat_ndt, se_delay) + + duh = np.zeros((N, V_vars, V_in, T)) + for t in range(T): + for n in range(N): + IE = ( + w_exc * (exc_current_baseline + ue[n, t]) + + w_ee * J_NMDA * se[n, t] + - J_I * si[n, t] + + J_NMDA * nw_e[n, t] + ) + duh[n, sv["r_exc"], sv["r_exc"], t] = ( + -logistic_der(IE, a_exc, b_exc, d_exc) * w_exc + ) + II = ( + w_inh * (inh_current_baseline + ui[n, t]) + J_NMDA * se[n, t] - si[n, t] + ) + duh[n, sv["r_inh"], sv["r_inh"], t] = ( + -logistic_der(II, a_inh, b_inh, d_inh) * w_inh + ) + return duh + + +@numba.njit +def Dxdoth(N, V): + """Derivative of system dynamics wrt x dot + + :param N: Number of nodes in the network. + :type N: int + :param V: Number of system variables. + :type V: int + + :return: N x V x V matrix. + :rtype: np.ndarray + """ + dxdoth = np.zeros((N, V, V)) + for n in range(N): + for v in range(2, V): + dxdoth[n, v, v] = 1 + + return dxdoth diff --git a/tests/control/optimal_control/test_oc_utils.py b/tests/control/optimal_control/test_oc_utils.py index f880908c..8e1b1d32 100644 --- a/tests/control/optimal_control/test_oc_utils.py +++ b/tests/control/optimal_control/test_oc_utils.py @@ -37,8 +37,12 @@ TEST_INPUT_1N_8 = ZERO_INPUT_1N_8.copy() INIT_INPUT_1N_8 = ZERO_INPUT_1N_8.copy() -TEST_INPUT_1N_8[:, : 1 + int(np.around(params.TEST_DURATION_6 / 0.1, 1))] = TEST_INPUT_1N_6 -INIT_INPUT_1N_8[:, : 1 + int(np.around(params.TEST_DURATION_6 / 0.1, 1))] = INIT_INPUT_1N_6 +TEST_INPUT_1N_8[ + :, : 1 + int(np.around(params.TEST_DURATION_6 / 0.1, 1)) +] = TEST_INPUT_1N_6 +INIT_INPUT_1N_8[ + :, : 1 + int(np.around(params.TEST_DURATION_6 / 0.1, 1)) +] = INIT_INPUT_1N_6 params.ZERO_INPUT_1N_8 = ZERO_INPUT_1N_8 params.TEST_INPUT_1N_8 = TEST_INPUT_1N_8 @@ -49,8 +53,12 @@ TEST_INPUT_1N_10 = ZERO_INPUT_1N_10.copy() INIT_INPUT_1N_10 = ZERO_INPUT_1N_10.copy() -TEST_INPUT_1N_10[:, : 1 + int(np.around(params.TEST_DURATION_6 / 0.1, 1))] = TEST_INPUT_1N_6 -INIT_INPUT_1N_10[:, : 1 + int(np.around(params.TEST_DURATION_6 / 0.1, 1))] = INIT_INPUT_1N_6 +TEST_INPUT_1N_10[ + :, : 1 + int(np.around(params.TEST_DURATION_6 / 0.1, 1)) +] = TEST_INPUT_1N_6 +INIT_INPUT_1N_10[ + :, : 1 + int(np.around(params.TEST_DURATION_6 / 0.1, 1)) +] = INIT_INPUT_1N_6 params.ZERO_INPUT_1N_10 = ZERO_INPUT_1N_10 params.TEST_INPUT_1N_10 = TEST_INPUT_1N_10 @@ -61,8 +69,12 @@ TEST_INPUT_1N_12 = ZERO_INPUT_1N_12.copy() INIT_INPUT_1N_12 = ZERO_INPUT_1N_12.copy() -TEST_INPUT_1N_12[:, : 1 + int(np.around(params.TEST_DURATION_6 / 0.1, 1))] = TEST_INPUT_1N_6 -INIT_INPUT_1N_12[:, : 1 + int(np.around(params.TEST_DURATION_6 / 0.1, 1))] = INIT_INPUT_1N_6 +TEST_INPUT_1N_12[ + :, : 1 + int(np.around(params.TEST_DURATION_6 / 0.1, 1)) +] = TEST_INPUT_1N_6 +INIT_INPUT_1N_12[ + :, : 1 + int(np.around(params.TEST_DURATION_6 / 0.1, 1)) +] = INIT_INPUT_1N_6 params.ZERO_INPUT_1N_12 = ZERO_INPUT_1N_12 params.TEST_INPUT_1N_12 = TEST_INPUT_1N_12 @@ -120,20 +132,50 @@ def gettarget_1n(model): return np.concatenate( ( - np.concatenate((model.params[model.init_vars[0]], model.params[model.init_vars[0]]), axis=1)[ - :, :, np.newaxis - ], + np.concatenate( + (model.params[model.init_vars[0]], model.params[model.init_vars[0]]), + axis=1, + )[:, :, np.newaxis], np.stack((model[model.state_vars[0]], model[model.state_vars[1]]), axis=1), ), axis=2, ) +def gettarget_1n_ww(model): + return np.concatenate( + ( + np.concatenate( + ( + model.params[model.init_vars[0]], + model.params[model.init_vars[0]], + model.params[model.init_vars[2]], + model.params[model.init_vars[3]], + ), + axis=1, + )[:, :, np.newaxis], + np.stack( + ( + model[model.state_vars[0]], + model[model.state_vars[1]], + model[model.state_vars[2]], + model[model.state_vars[3]], + ), + axis=1, + ), + ), + axis=2, + ) + + def gettarget_2n(model): return np.concatenate( ( np.stack( - (model.params[model.init_vars[0]][:, -1], model.params[model.init_vars[1]][:, -1]), + ( + model.params[model.init_vars[0]][:, -1], + model.params[model.init_vars[1]][:, -1], + ), axis=1, )[:, :, np.newaxis], np.stack((model[model.state_vars[0]], model[model.state_vars[1]]), axis=1), @@ -142,6 +184,32 @@ def gettarget_2n(model): ) +def gettarget_2n_ww(model): + return np.concatenate( + ( + np.stack( + ( + model.params[model.init_vars[0]][:, -1], + model.params[model.init_vars[1]][:, -1], + model.params[model.init_vars[2]][:, -1], + model.params[model.init_vars[3]][:, -1], + ), + axis=1, + )[:, :, np.newaxis], + np.stack( + ( + model[model.state_vars[0]], + model[model.state_vars[1]], + model[model.state_vars[2]], + model[model.state_vars[3]], + ), + axis=1, + ), + ), + axis=2, + ) + + def setinitzero_1n(model): for init_var in model.init_vars: if "ou" in init_var: diff --git a/tests/control/optimal_control/test_oc_wc.py b/tests/control/optimal_control/test_oc_wc.py index 4b7e21e5..51db3356 100644 --- a/tests/control/optimal_control/test_oc_wc.py +++ b/tests/control/optimal_control/test_oc_wc.py @@ -24,11 +24,15 @@ def test_1n(self): for input_channel in [0, 1]: for measure_channel in [0, 1]: - print("input_channel, measure_channel = ", input_channel, measure_channel) + print( + "input_channel, measure_channel = ", input_channel, measure_channel + ) cost_mat = np.zeros((model.params.N, len(model.output_vars))) control_mat = np.zeros((model.params.N, len(model.state_vars))) - control_mat[0, input_channel] = 1.0 # only allow inputs to input_channel + control_mat[ + 0, input_channel + ] = 1.0 # only allow inputs to input_channel cost_mat[0, measure_channel] = 1.0 # only measure other channel test_oc_utils.set_input(model, p.ZERO_INPUT_1N_6) @@ -56,7 +60,10 @@ def test_1n(self): for i in range(p.LOOPS): model_controlled.optimize(p.ITERATIONS) - c_diff = np.abs(model_controlled.control[0, input_channel, :] - p.TEST_INPUT_1N_6[0, :]) + c_diff = np.abs( + model_controlled.control[0, input_channel, :] + - p.TEST_INPUT_1N_6[0, :] + ) if np.amax(c_diff) < p.LIMIT_DIFF: control_coincide = True @@ -84,7 +91,6 @@ def test_2n(self): control_mat[0, 0] = 1.0 cost_mat[1, 0] = 1.0 - model.params.coupling = "additive" # test additive in undelayed network, diffusive in delayed network model.params["exc_ext"] = p.TEST_INPUT_2N_6 model.params["inh_ext"] = p.ZERO_INPUT_2N_6 model.run() @@ -101,7 +107,8 @@ def test_2n(self): model_controlled.maximum_control_strength = 2.0 model_controlled.control = np.concatenate( - [p.INIT_INPUT_2N_6[:, np.newaxis, :], p.ZERO_INPUT_2N_6[:, np.newaxis, :]], axis=1 + [p.INIT_INPUT_2N_6[:, np.newaxis, :], p.ZERO_INPUT_2N_6[:, np.newaxis, :]], + axis=1, ) model_controlled.update_input() @@ -137,8 +144,6 @@ def test_2n_delay(self): control_mat[0, 0] = 1.0 cost_mat[1, 0] = 1.0 - model.params.coupling = "diffusive" # test additive in undelayed network, diffusive in delayed network - model.params["exc_ext"] = p.TEST_INPUT_2N_8 model.params["inh_ext"] = p.ZERO_INPUT_2N_8 @@ -156,7 +161,8 @@ def test_2n_delay(self): model_controlled.maximum_control_strength = 2.0 model_controlled.control = np.concatenate( - [p.INIT_INPUT_2N_8[:, np.newaxis, :], p.ZERO_INPUT_2N_8[:, np.newaxis, :]], axis=1 + [p.INIT_INPUT_2N_8[:, np.newaxis, :], p.ZERO_INPUT_2N_8[:, np.newaxis, :]], + axis=1, ) model_controlled.update_input() @@ -166,9 +172,16 @@ def test_2n_delay(self): model_controlled.optimize(p.ITERATIONS) # last entries of adjoint_state[0,0,:] are zero - self.assertTrue(np.amax(np.abs(model_controlled.adjoint_state[0, 0, -model.getMaxDelay() :])) == 0.0) + self.assertTrue( + np.amax( + np.abs(model_controlled.adjoint_state[0, 0, -model.getMaxDelay() :]) + ) + == 0.0 + ) - c_diff_max = np.amax(np.abs(model_controlled.control[0, 0, :] - p.TEST_INPUT_2N_8[0, :])) + c_diff_max = np.amax( + np.abs(model_controlled.control[0, 0, :] - p.TEST_INPUT_2N_8[0, :]) + ) if c_diff_max < p.LIMIT_DIFF: control_coincide = True break diff --git a/tests/control/optimal_control/test_oc_ww.py b/tests/control/optimal_control/test_oc_ww.py new file mode 100644 index 00000000..cd2778b5 --- /dev/null +++ b/tests/control/optimal_control/test_oc_ww.py @@ -0,0 +1,222 @@ +import unittest +import numpy as np + +from neurolib.models.ww import WWModel +from neurolib.control.optimal_control import oc_ww + +import test_oc_utils as test_oc_utils + +p = test_oc_utils.params + + +class TestWW(unittest.TestCase): + """ + Test ww in neurolib/optimal_control/ + """ + + # tests if the control from OC computation coincides with a random input used for target forward-simulation + # single-node case + def test_1n(self): + print("Test OC in single-node system") + model = WWModel() + test_oc_utils.setinitzero_1n(model) + model.params["duration"] = p.TEST_DURATION_6 + + for input_channel in [0, 1]: + for measure_channel in range(4): + print( + "input_channel, measure_channel = ", input_channel, measure_channel + ) + + cost_mat = np.zeros((model.params.N, len(model.output_vars))) + control_mat = np.zeros((model.params.N, len(model.state_vars))) + control_mat[ + 0, input_channel + ] = 1.0 # only allow inputs to input_channel + cost_mat[0, measure_channel] = 1.0 # only measure other channel + + test_oc_utils.set_input(model, p.ZERO_INPUT_1N_6) + model.params[model.input_vars[input_channel]] = p.TEST_INPUT_1N_6 + model.run() + target = test_oc_utils.gettarget_1n_ww(model) + + test_oc_utils.set_input(model, p.ZERO_INPUT_1N_6) + + model_controlled = oc_ww.OcWw(model, target) + model_controlled.maximum_control_strength = 2.0 + + model_controlled.control = np.concatenate( + [ + control_mat[0, 0] * p.INIT_INPUT_1N_6[:, np.newaxis, :], + control_mat[0, 1] * p.INIT_INPUT_1N_6[:, np.newaxis, :], + ], + axis=1, + ) + + model_controlled.update_input() + + control_coincide = False + + for i in range(p.LOOPS): + model_controlled.optimize(p.ITERATIONS) + + c_diff = np.abs( + model_controlled.control[0, input_channel, :] + - p.TEST_INPUT_1N_6[0, :] + ) + + if np.amax(c_diff) < p.LIMIT_DIFF: + control_coincide = True + break + + if model_controlled.zero_step_encountered: + break + + self.assertTrue(control_coincide) + + def test_2n(self): + print("Test OC in 2-node network") + ### communication between E and I is validated in test_onenode_oc. Test only E-E communication + ### Because of symmetry, test only inputs to 0 node, precision measuement in 1 node + + dmat = np.array([[0.0, 0.0], [0.0, 0.0]]) # no delay + cmat = np.array([[0.0, 1.0], [1.0, 0.0]]) + + model = WWModel(Cmat=cmat, Dmat=dmat) + test_oc_utils.setinitzero_2n(model) + model.params.duration = p.TEST_DURATION_10 + + cost_mat = np.zeros((model.params.N, len(model.output_vars))) + control_mat = np.zeros((model.params.N, len(model.state_vars))) + control_mat[0, 0] = 1.0 + cost_mat[1, 0] = 1.0 + + model.params["exc_current"] = p.TEST_INPUT_2N_10 + model.params["inh_current"] = p.ZERO_INPUT_2N_10 + model.run() + + target = test_oc_utils.gettarget_2n_ww(model) + model.params["exc_current"] = p.ZERO_INPUT_2N_10 + + model_controlled = oc_ww.OcWw( + model, + target, + control_matrix=control_mat, + cost_matrix=cost_mat, + ) + model_controlled.maximum_control_strength = 2.0 + + model_controlled.control = np.concatenate( + [ + p.INIT_INPUT_2N_10[:, np.newaxis, :], + p.ZERO_INPUT_2N_10[:, np.newaxis, :], + ], + axis=1, + ) + model_controlled.update_input() + + control_coincide = False + + for i in range(p.LOOPS): + model_controlled.optimize(p.ITERATIONS) + c_diff = np.abs( + model_controlled.control[0, 0, :] - p.TEST_INPUT_2N_10[0, :] + ) + if np.amax(c_diff) < p.LIMIT_DIFF: + control_coincide = True + break + + if model_controlled.zero_step_encountered: + break + + self.assertTrue(control_coincide) + + # tests if the control from OC computation coincides with a random input used for target forward-simulation + # delayed network case + def test_2n_delay(self): + print("Test OC in delayed 2-node network") + + cmat = np.array([[0.0, 0.0], [1.0, 0.0]]) + dmat = np.array([[0.0, 0.0], [p.TEST_DELAY, 0.0]]) + + model = WWModel(Cmat=cmat, Dmat=dmat) + test_oc_utils.setinitzero_2n(model) + model.params.duration = p.TEST_DURATION_8 + model.params.signalV = 1.0 + + cost_mat = np.zeros((model.params.N, len(model.output_vars))) + control_mat = np.zeros((model.params.N, len(model.state_vars))) + control_mat[0, 0] = 1.0 + cost_mat[1, 0] = 1.0 + + model.params["exc_current"] = p.TEST_INPUT_2N_8 + model.params["inh_current"] = p.ZERO_INPUT_2N_8 + + model.run() + + target = test_oc_utils.gettarget_2n_ww(model) + model.params["exc_current"] = p.ZERO_INPUT_2N_8 + + model_controlled = oc_ww.OcWw( + model, + target, + control_matrix=control_mat, + cost_matrix=cost_mat, + ) + model_controlled.maximum_control_strength = 2.0 + + model_controlled.control = np.concatenate( + [p.INIT_INPUT_2N_8[:, np.newaxis, :], p.ZERO_INPUT_2N_8[:, np.newaxis, :]], + axis=1, + ) + model_controlled.update_input() + + control_coincide = False + + for i in range(p.LOOPS): + model_controlled.optimize(p.ITERATIONS) + + # last entries of adjoint_state[0,0,:] are zero + self.assertTrue( + np.amax( + np.abs(model_controlled.adjoint_state[0, 0, -model.getMaxDelay() :]) + ) + == 0.0 + ) + + c_diff_max = np.amax( + np.abs(model_controlled.control[0, 0, :] - p.TEST_INPUT_2N_8[0, :]) + ) + if c_diff_max < p.LIMIT_DIFF: + control_coincide = True + break + + if model_controlled.zero_step_encountered: + break + + self.assertTrue(control_coincide) + + # Arbitrary network and control setting, get_xs() returns correct array shape (despite initial values array longer than 1) + def test_get_xs(self): + print("Test state shape agrees with target shape") + + cmat = np.array([[0.0, 1.0], [1.0, 0.0]]) + dmat = np.array([[0.0, 0.0], [0.0, 0.0]]) # no delay + model = WWModel(Cmat=cmat, Dmat=dmat) + model.params.duration = p.TEST_DURATION_6 + test_oc_utils.set_input(model, p.TEST_INPUT_2N_6) + + target = np.ones((2, len(model.output_vars), p.TEST_INPUT_2N_6.shape[1])) + + model_controlled = oc_ww.OcWw( + model, + target, + ) + + model_controlled.optimize(1) + xs = model_controlled.get_xs() + self.assertTrue(xs.shape == target.shape) + + +if __name__ == "__main__": + unittest.main() From 6b0f1c98ee3ca308ab618ada2028bd52e3c1bc8f Mon Sep 17 00:00:00 2001 From: Lena Salfenmoser Date: Tue, 16 Jan 2024 19:20:08 +0100 Subject: [PATCH 02/14] fully tested implementation of ww oc --- examples/example-5.2-oc-ww.ipynb | 642 ------------------ neurolib/control/optimal_control/oc.py | 105 +-- .../control/optimal_control/oc_ww/oc_ww.py | 2 +- neurolib/models/ww/loadDefaultParams.py | 6 +- neurolib/models/ww/model.py | 2 +- neurolib/models/ww/timeIntegration.py | 14 +- tests/control/optimal_control/test_oc_ww.py | 7 + 7 files changed, 28 insertions(+), 750 deletions(-) delete mode 100644 examples/example-5.2-oc-ww.ipynb diff --git a/examples/example-5.2-oc-ww.ipynb b/examples/example-5.2-oc-ww.ipynb deleted file mode 100644 index 473ba925..00000000 --- a/examples/example-5.2-oc-ww.ipynb +++ /dev/null @@ -1,642 +0,0 @@ -{ - "cells": [ - { - "attachments": {}, - "cell_type": "markdown", - "metadata": { - "pycharm": { - "name": "#%% md\n" - } - }, - "source": [ - "### Optimal control of the Wilson-Cowan model\n", - "This notebook shows how to compute the optimal control (OC) signal for the Wilson-Cowan model for a simple example task." - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": { - "collapsed": false, - "pycharm": { - "name": "#%%\n" - } - }, - "outputs": [], - "source": [ - "import matplotlib.pyplot as plt\n", - "import numpy as np\n", - "import os\n", - "\n", - "while os.getcwd().split(os.sep)[-1] != \"neurolib\":\n", - " os.chdir('..')\n", - "\n", - "# We import the model, stimuli, and the optimal control package\n", - "from neurolib.models.ww import WWModel\n", - "from neurolib.utils.stimulus import ZeroInput\n", - "from neurolib.control.optimal_control import oc_ww\n", - "from neurolib.utils.plot_oc import plot_oc_singlenode, plot_oc_network\n", - "\n", - "# This will reload all imports as soon as the code changes\n", - "%load_ext autoreload\n", - "%autoreload 2" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "collapsed": false, - "pycharm": { - "name": "#%% md\n" - } - }, - "source": [ - "We stimulate the system with a known control signal, define the resulting activity as target, and compute the optimal control for this target. We define weights such that precision is penalized only (w_p=1, w_2=0). Hence, the optimal control signal should converge to the input signal." - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "# We import the model\n", - "model = WWModel()\n", - "\n", - "# Some parameters to define stimulation signals\n", - "dt = model.params[\"dt\"]\n", - "duration = 10.\n", - "amplitude = 1.\n", - "period = duration /4.\n", - "\n", - "# We define a \"zero-input\", and a sine-input\n", - "zero_input = ZeroInput().generate_input(duration=duration+dt, dt=dt)\n", - "input = np.copy(zero_input)\n", - "input[0,1:-1] = amplitude * np.sin(2.*np.pi*np.arange(0,duration-0.1, dt)/period) # other functions or random values can be used as well\n", - "\n", - "# We set the duration of the simulation and the initial values\n", - "model.params[\"duration\"] = duration\n", - "x_init = 0.\n", - "y_init = 0.0\n", - "model.params[\"r_exc\"] = np.array([[x_init]])\n", - "model.params[\"r_inh\"] = np.array([[y_init]])" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# We set the stimulus in x and y variables, and run the simulation\n", - "model.params[\"exc_current\"] = input\n", - "model.params[\"inh_current\"] = zero_input\n", - "model.run()\n", - "\n", - "# Define the result of the stimulation as target\n", - "target = np.concatenate((np.concatenate( (model.params[\"r_exc\"], model.params[\"r_inh\"], model.params[\"se_init\"], model.params[\"si_init\"]), axis=1)[:,:, np.newaxis],\n", - " np.stack( (model.r_exc, model.r_inh, model.se, model.si), axis=1)), axis=2)\n", - "target_input = np.concatenate( (input,zero_input), axis=0)[np.newaxis,:,:]\n", - "\n", - "# Remove stimuli and re-run the simulation\n", - "model.params[\"exc_current\"] = zero_input\n", - "model.params[\"inh_current\"] = zero_input\n", - "control = np.concatenate( (zero_input,zero_input), axis=0)[np.newaxis,:,:]\n", - "model.run()\n", - "\n", - "# combine initial value and simulation result to one array\n", - "state = np.concatenate((np.concatenate( (model.params[\"r_exc\"], model.params[\"r_inh\"]), axis=1)[:,:, np.newaxis],\n", - " np.stack( (model.r_exc, model.r_inh), axis=1)), axis=2)\n", - "\n", - "plot_oc_singlenode(duration, dt, state, target, control, target_input)" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": { - "collapsed": false, - "pycharm": { - "name": "#%%\n" - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Compute control for a deterministic system\n", - "Cost in iteration 0: nan\n", - "Final cost : nan\n" - ] - }, - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# We set the external stimulation to zero. This is the \"initial guess\" for the OC algorithm\n", - "model.params[\"exc_current\"] = zero_input\n", - "model.params[\"inh_current\"] = zero_input\n", - "\n", - "# We load the optimal control class\n", - "# print array (optional parameter) defines, for which iterations intermediate results will be printed\n", - "# Parameters will be taken from the input model\n", - "model_controlled = oc_ww.OcWw(model, target, print_array=np.arange(0,501,25))\n", - "model_controlled.weights[\"w_p\"] = 1. # default value 1\n", - "model_controlled.weights[\"w_2\"] = 0. # default value 0\n", - "\n", - "# We run 500 iterations of the optimal control gradient descent algorithm\n", - "model_controlled.optimize(0)\n", - "\n", - "state = model_controlled.get_xs()\n", - "control = model_controlled.control\n", - "\n", - "plot_oc_singlenode(duration, dt, state, target, control, target_input, model_controlled.cost_history)" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": { - "collapsed": false, - "pycharm": { - "name": "#%%\n" - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Compute control for a deterministic system\n", - "Cost in iteration 0: 1.409261374589448e-07\n", - "Cost in iteration 25: 1.3051113114486073e-07\n", - "Cost in iteration 50: 1.2069164098268257e-07\n", - "Cost in iteration 75: 1.1215971283577606e-07\n", - "Cost in iteration 100: 1.0456327452784617e-07\n", - "Final cost : 1.0456327452784617e-07\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Do another 100 iterations if you want to.\n", - "# Repeated execution will continue with further 100 iterations.\n", - "model_controlled.optimize(100)\n", - "state = model_controlled.get_xs()\n", - "control = model_controlled.control\n", - "plot_oc_singlenode(duration, dt, state, target, control, target_input, model_controlled.cost_history)" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "metadata": { - "collapsed": false, - "pycharm": { - "name": "#%% md\n" - } - }, - "source": [ - "### Network case\n", - "\n", - "Let us know study a simple 2-node network of model oscillators. We first define the coupling matrix and the distance matrix. We can then initialize the model." - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": { - "collapsed": false, - "pycharm": { - "name": "#%%\n" - } - }, - "outputs": [ - { - "data": { - "image/png": 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "cmat = np.array( [[0., 0.5], [1., 0.]] ) # diagonal elements are zero, connection strength is 1 (0.5) from node 0 to node 1 (from node 1 to node 0)\n", - "dmat = np.array( [[0., 0.], [0., 0.]] ) # no delay\n", - "\n", - "model = WWModel(Cmat=cmat, Dmat=dmat)\n", - "\n", - "# we define the control input matrix to enable or disable certain channels and nodes\n", - "control_mat = np.zeros( (model.params.N, len(model.state_vars)) )\n", - "control_mat[0,0] = 1. # only allow inputs in x-channel in node 0\n", - "\n", - "model.params.K_gl = 5.\n", - "\n", - "model.params[\"duration\"] = duration\n", - "zero_input = ZeroInput().generate_input(duration=duration+dt, dt=dt)\n", - "input = np.copy(zero_input)\n", - "input[0,1:-3] = np.sin(np.arange(0,duration-0.3, dt)) # other functions or random values can be used as well\n", - "model.params[\"r_exc\"] = np.vstack( [x_init, x_init] )\n", - "model.params[\"r_inh\"] = np.vstack( [y_init, y_init] )\n", - "\n", - "\n", - "# We set the stimulus in x and y variables, and run the simulation\n", - "input_nw = np.concatenate( (np.vstack( [control_mat[0,0] * input, control_mat[0,1] * input] )[np.newaxis,:,:],\n", - " np.vstack( [control_mat[1,0] * input, control_mat[1,1] * input] )[np.newaxis,:,:]), axis=0)\n", - "zero_input_nw = np.concatenate( (np.vstack( [zero_input, zero_input] )[np.newaxis,:,:],\n", - " np.vstack( [zero_input, zero_input] )[np.newaxis,:,:]), axis=0)\n", - "\n", - "model.params[\"exc_current\"] = input_nw[:,0,:]\n", - "model.params[\"inh_current\"] = input_nw[:,1,:]\n", - "\n", - "model.run()\n", - "\n", - "# Define the result of the stimulation as target\n", - "target = np.concatenate( (np.concatenate( (model.params[\"r_exc\"], model.params[\"r_inh\"]), axis=1)[:,:, np.newaxis], np.stack( (model.r_exc, model.r_inh), axis=1)), axis=2)\n", - "\n", - "# Remove stimuli and re-run the simulation\n", - "model.params[\"exc_current\"] = zero_input_nw[:,0,:]\n", - "model.params[\"inh_current\"] = zero_input_nw[:,0,:]\n", - "model.run()\n", - "\n", - "# combine initial value and simulation result to one array\n", - "state = np.concatenate( (np.concatenate( (model.params[\"r_exc\"], model.params[\"r_inh\"]), axis=1)[:,:, np.newaxis], np.stack( (model.r_exc, model.r_inh), axis=1)), axis=2)\n", - "\n", - "plot_oc_network(model.params.N, duration, dt, state, target, zero_input_nw, input_nw)" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": { - "pycharm": { - "name": "#%%\n" - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Compute control for a deterministic system\n", - "Cost in iteration 0: 8.117061134315108e-06\n", - "Cost in iteration 25: 4.0329637221407195e-07\n", - "Cost in iteration 50: 2.133706589679289e-07\n", - "Cost in iteration 75: 1.0846418185856119e-07\n", - "Cost in iteration 100: 6.237553898673198e-08\n", - "Cost in iteration 125: 3.607365058691262e-08\n", - "Cost in iteration 150: 2.2496421814207724e-08\n", - "Cost in iteration 175: 1.5886138922670738e-08\n", - "Cost in iteration 200: 1.1727415781910453e-08\n", - "Cost in iteration 225: 9.005487959890062e-09\n", - "Cost in iteration 250: 7.191281120908631e-09\n", - "Cost in iteration 275: 5.835744371001404e-09\n", - "Cost in iteration 300: 4.915806895112334e-09\n", - "Cost in iteration 325: 4.206672224203755e-09\n", - "Cost in iteration 350: 3.6916483993194285e-09\n", - "Cost in iteration 375: 3.2948161905145206e-09\n", - "Cost in iteration 400: 2.9837006122863342e-09\n", - "Cost in iteration 425: 2.7310136209212046e-09\n", - "Cost in iteration 450: 2.5267282859627983e-09\n", - "Cost in iteration 475: 2.352356874896669e-09\n", - "Cost in iteration 500: 2.2057268519628175e-09\n", - "Final cost : 2.2057268519628175e-09\n" - ] - }, - { - "data": { - "image/png": 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yQo0aNeDg4IDFixejbNmysLW1hY+PT7Y1DHT69euH+fPnY9q0aWjQoIHBWaOcNG7cGADw7rvvwtfXN8sEy8/PD46Ojli3bh26du0KFxeXpz5n586dYWFhgZdeegmjRo3Co0ePsHTpUri4uGS7NC03PvjgA6xYsQJdunTB2LFjM1phV61aFadOncr36/Tz88OcOXPQpUsXvPrqq4iMjMTChQtRs2bNXD2vbmy//vorXnzxRYwZMyajFXaVKlUQExOTcdbQzs4OixYtwqBBg9CoUSP0798fzs7OCAsLw7Zt2/DCCy9gwYIFTxwvAAwdOhQ///wzrl27Bg8Pj7y+lVl4eXlhyJAhWLJkCR48eIC2bdviyJEj+Pnnn+Hv759RANjZ2Rnvv/8+AgMD0b17d3Tr1g2hoaHYsWMHnJycDJ5zwoQJ2Lx5M7p3757R1jw+Ph6nT5/G+vXrcf369Sxfk9nkyZOxbt06tG/fHmPHjsWjR48wa9YsNGjQAMOGDXvm10xERMaH8y1DnG9xvvWs860bN25gxYoVAJCRUf/ZZ58BkAyz3NSNI1KVWm0giUqLl156SbGyslLi4+Nz3Gfo0KGKubm5Eh0drSiKtEoePXq0UqlSJcXCwkKpXLmyMmTIkIzHFUVRfv/9d6VevXqKmZmZQQvrx1th62i1WsXd3V0BoHz22WdZHs+uFXZaWpoyZswYxdnZWdFoNNm2HH777bcVAMqqVaty+Y4oyubNm5Xnn39esbKyUjw8PJSZM2cqP/74Y5a21VWrVlX8/PyyfH3btm2Vtm3bGmw7deqU0rZtW8XKykqpVKmS8umnnyrLli3LVSvsJ73OZcuWKZ6enoqlpaVSp04dZfny5RltpDMDoLzzzjvZPn9oaKjSunVrxdLSUqlcubISGBiozJs3TwGghIeHG+y7b98+xdfXV7G3t1esrKyUGjVqKEOHDlWOHTuWq/H26tVLsba2Vu7fv//E16x7DVFRUQbbly9fnuU9S01NVWbMmKFUq1ZNMTc3V9zd3ZVJkyYpSUlJBl+bnp6uzJgxQ6lQoYJibW2ttGvXTjlz5oxStWpVg1bYiiKtvydNmqTUrFlTsbCwUJycnJSWLVsqX3/9tZKSkvLEsSuKopw5c0bp3LmzYmNjozg4OCgDBw7M8l4SEVHpwflWVpxvcb71LPOtffv2KQCyvTz+e0FUHGkUpQiqDhJRiTV+/HgsW7YM4eHhsLGxUXs4RmPcuHH4/vvv8ejRoxyLluaHq6srBg8ejFmzZhXYcxIREZG6ON/KH863iEov1uwionxLSkrCr7/+il69enHi9QSJiYkG9+/du4cVK1agVatWBTrxOnv2LBITE/Hhhx8W2HMSERGRujjfyh3Ot4goM2Z2EVGeRUZGYs+ePVi/fj02bdqEkJAQdsF7Am9vb7Rr1w5169ZFREQEli1bhjt37iAoKAht2rRRe3hERERUDHG+lTecbxFRZixQT0R5du7cOQwcOBAuLi6YN28eJ15P0a1bN6xfvx5LliyBRqNBo0aNsGzZMk68iIiIKEecb+UN51tElBkzu4iIiIiIiIiIqMRgzS4iIiIiIiIiIioxGOwiIiIiIiIiIqISo9TU7NJqtbhz5w7Kli0LjUaj9nCIiIiohFEUBQ8fPkTFihVhYlI6zydyvkVERESFKbfzrVIT7Lpz5w7c3d3VHgYRERGVcDdv3kTlypXVHoYqON8iIiKiovC0+VapCXaVLVsWgLwhdnZ2Ko+GiIiISpq4uDi4u7tnzDlKI863iIiIqDDldr5VaoJdulR6Ozs7Tr6IiIio0JTm5XucbxEREVFReNp8q3QWlCAiIiIiIiIiohKJwS4iIiIiIiIiIioxGOwiIiIiIiIiIqISg8EuIiIiIiIiIiIqMRjsIiIiIiIiIiKiZ6coao8AQCnqxkhERER5kJgInDoFhITIJTwccHYG3NzkumJFoFYtwNsbOH0asLOT7ba2ao+ciIiIiIra5cvAN98Au3YBJ04AZcqoOhwGu4iIiEgkJgILFgArVgDnzgHp6U//mqpVgbt3gZQUue/uDvTvDwwcCDz/PPCUttBEREREZKTi4oAlSyTAtWePfvv69cDQoaoNC+AyRiIiIkpPB5Yvl0ytDz6QTK30dMDREfDwAExNDfcvUwZo3VqyuG7c0Ae6AODmTWDWLMn4atAAWLasKF8JERERERW2o0eBFi0ABwdgwgQJdGk0QNeuwMqVwGuvqT1CZnYRERGVWooCbNsGTJwInD0r29zdgalTgdu3gTlzgOvXZXvz5oCvr1w3awaULy+ZYLt2ydm7zZuBhw9lX11w7OxZICysyF8WERERERUwRQF+/VXmibr5ISDzvlGjJOjl4aHW6LJgZhcREVFplJYGDB8OvPSSBKXKlZOMrH//Bd54AzAxkdR0Ly9g+3bg0CFg+nSgSxcJdAGAtTXg7y8Tn6goYNMmCYSlp8vF0hKIiQEePJD9Q0LkuYiIiIjIOCgKMH++ZHENHqwPdNnbywnTR4+AhQuLVaALYLCLiIio9ElOlrpay5fL2bgJE6So6KhRgJWV7DN+PPC//0mAqmvXp9fesrQEevYE/vlHsry8veX7LFgA1K4NrFsHvPkm4Ocn+2U+I0hERERExYuiAEFBQNu2wLvvyklQQIJaK1bIyczAQP3csZhhsIuIiKg0iY8HevQAfvsNsLCQJYiffy61ujp0kMcBqcvVv79keOWFRiPZYsePy3PXqQNERgJ9+wKxsYCZmQTDGjaUJZBEREREVHykp8tSxerVgU6dgIMHZc7YoQNw+DBw7VqxqMn1NAx2ERERlRYPHkjdrT/+AGxspF5Xu3aSubVsmWRxHThQMN/LxATo1UtaT0+ZIhlk//4rRe1r1JCxdOsGfPWVnDkkIiIiInV9/72Utvj0U8nCt7AAxowBrlyRLK9mzdQeYa4x2EVERFQaREcD7dsDf/8tNRf27JHuiy+8IJMXW1vJuOrWrWC/r6WlTJiOHpWljbGxMmGqWhXQaoEPPwRefRVISCjY70tEREREubN7N1CpkpSc0DUcatZMTlrOmwdUrqzq8PKD3RiJCsK1a8CxY8DVq/rLtWtyQNm4sVyaNAHq15eDyi+/lAO7hAQgKQmoWxdo3Rpo00b2tbBQ+xURUUmi1UpA6cQJwMVFMruqVpWW0RcuABUrAlu3ytLCwtKwIXDkiGRyzZgB3LgBODlJhldYmL6DIxEREREVjcuXgVdeAU6f1m+rXRtYtQpo1Ei9cRUABruInkVYmHQn+/lnOZjMzvHj+tsWFsDzz0tgLLOrV2U5ESDPNXhwoQyXiEqpOXPkjJ21tQTca9eWpYsXLshZvOBgwN298Mdhbg589JEspezTR9Ljzc2Bl19mkJ+IiIioqKSnA0uWSDdFXeF5Z2fZ5u+v6tAKCoNdRPkRHS2dJxYulG5jANC0qRxAVq8uy3RWrpT9ADmIfPQIuH9fH+hq0AAYNEjSQ0NCgD//lOJ/bdrov09QEHD7tmRkmPHPlYjy4dgxYPJkuT13rmSYXrokZ/BsbSWjqygCXZk1aSInAoYMke8/YQJw5gzw3XfAjz9KAdR69Yp2TERERESlwaZNkmV/4oTcr1QJGDcOeP99FQdV8DSKUjqqwsbFxcHe3h6xsbGws7NTezhkrBQF+PZb6U6hW8vctq0sS2zeHIiJkbasK1fKY87Okr0weLAEtc6cAb75Rlq1pqXJPg0bAjNnAi++KNlhGo1cFEWWNIaGSgDto4/keRj0IqLcevhQUtAvX5Zi8evWyecLIFlVly9Llx21aLWyrPGjj+R2lSqSMevsDOzdK4E5I8K5Bt8DIiKiYuvaNcDPDzh/Xu47OEhd1TffNKpjzNzONVignii3FEUOyMaPlwNIb29g505g3z4JdG3eLJkIK1dKF7IPPpCDtoULAR8fOcBs0ECyFq5elei5jY0Eszp3Bt5+W2p46Q5E09KAfv2kps3Vq8Dw4dI17do1Fd8EIjIqY8ZIQMvdHVi6FEhM1D/m4aFuoAuQz8qJEyWL1dlZPjPNzICoKPm8051xJCIiIqL8URTJoq9ZUx/o8vKSLtmjRxtVoCsvGOwiyg1FkQOywEC5P2uWLMHx9dUHp06cACIigDp1gEOHJFvLyir753N3lwyvsDDgnXdk26JF8qFz8KDcNzeXLmXXr8v3K1tWuqh5eUlmWOlIyiSi/Fq1SmoAmphIED4sDKhWTQLzxU27dlK8/rnnJNCv0QD37slyxpAQtUdHREREZJxCQ6WT4tdfSxa9ubmsVDpxQk40lmAMdhE9jaJIltZXX8n9+fNlPbPJY38+kyZJEejQUMnkyg1HR2DBAmDPHlm+c/WqLIt8/33p0ghITZ333wdOngReeEGyygYPlmLTRETZuX5dUtIBYMoUWUY9cCAQGSmB9eIYLPfwkBMFXbvqx3f/PtCli2SnEREREVHupKXJyqBGjYA7d2RbixaSnPHuu+qOrYgw2EX0JIoCvPeeRMIBWZI4erTcTk4GvvhCX6De3FyWOOaUzfUkHTtKsejhw+V7zp4tmQ7h4fp9qlUD9u+XddW9ekmNLyKi7EycKIHxli2Bjz8Gpk0Dzp4FXFyAX37RZ6QWN3Z2knmWeRIWFSUBL12dRCIiIiLK2cWLQKtWUj4HkG7cK1fKScVy5dQdWxFisIvoSSZOlOWGALB4sdTVAiTr6pVXpIbXkCEF873s7IAffgC2bAHKlwcOH5YMsVOn9PuYmUmWRuYi04mJwF9/FcwYiMj4HT0KrFkjnxGLFkk3xlmz5LHvvy/+KetmZpJe/913+s85c/Os2bREREREpKfVypzP21uOJe3sgGHD5MThq6+qPboix5kjUU7++EO/dHHJEmDUKLmdlAS8/DKwfbtEyUeOLNjv27078M8/QK1aUmPnhReArVsN99EdAKanywdX+/bATz8V7DiIyPgoitT6A4BBg6QQ6ZAhMvl57TXA31/V4eXJW28Bv/8u2bIXLkj9rqgotUdFREREVPxcugRUry7ld5KSZBXQmTOS3WVrq/boVMFgF1F2YmNlSSEgyxZHjJDb6emyhHDnTumkuH27HIAVNE9PCXh16AA8egT06CH1wB6vs5OeLh9eaWkStf/ss+JZi4eIioauQ6ylpSx5njxZOu1UrAjMm6f26PLupZeAvXsl2/XIEel8O3kyP+eIiIiIdGbPliZpN27I/X79gF27pClaKcZgF1F2xo8Hbt0CatQAvvxSv336dAlw6QJd7doV3hjKlZMD15Ej9bXDAgIMD/IsLKT+zsSJcv/jjyUbIj298MZFRMVTero+q2v0aJngaLWSCbpsmfHWaGjRQjrR6pp4BAbqi+8TERERlVZxcbIK6P33Zc5naiqlIFavLr71WYsQg11Ej9u2DVi+XD4gfvpJn/a5Y4dkTgHA0qXSNbGwmZtLrbDZs+X+3LlSN0yr1e9jYiIHfwsWyJi//14y0TLvQ0Ql34oV0ujCwUGynzQayeY6d04KvBuzOnWA4GBpnQ3I0vJPP1V3TERERERqCQoCKlWSovOAnBS8dKnUdFrMjXwFuxYuXAgPDw9YWVnBx8cHR44ceeL+69atQ506dWBlZYUGDRpg+/btBo9Pnz4dderUga2tLcqVK4dOnTrh8OHDBvt4eHhAo9EYXL7MnHFDVBBiYvRLFsePly4WOhqNZEa8/XbRFvjTaCSja9kyub14sSyxfDx76513JIpvYiLBugkTim6MRKSuxETJ7ASASZNk2Z9OnTrqjKmgVawotScqVZL7U6cC8+erOyYiIiKiopSeDnz+udTkevRItr3+OnDlClCtmrpjK2byHOxas2YNAgICMG3aNISEhMDLywu+vr6IjIzMdv9Dhw5hwIABGD58OEJDQ+Hv7w9/f3+cOXMmY59atWphwYIFOH36NP766y94eHigc+fOiHqsEO0nn3yCu3fvZlzGjBmT1+ETPdm77wJ37wK1a+uzuHS6dAFOnJDaWWp4/XXg118lPfWnn6TYdGqq4T59+wI//yyZHa+8osYoiUgN8+fL0uvKlQE/P2micfGi2qMqePb2wPnz+o6S774rHSeJiIiISrrISKBrV2DKFClt4+QkjcyWLZNu1mRAoyh5q/Lq4+ODpk2bYsGCBQAArVYLd3d3jBkzBhN1dYMy6devH+Lj47E1Uze55s2bw9vbG4sXL872e8TFxcHe3h579uxBx44dAUhm17hx4zBu3LhcjTM5ORnJyckGz+nu7o7Y2FjY2dnl9uVSabJxowSITEwkHdTHR7bfv1+8at389hswYIAEuvz9gTVrpHZXZjExhpkdRFRyxcRIfcEHDySrc/Nm+Tzz88vaybWkiIyUTpMPH8r9b74Bcjk/KEy6+UtpnmvwPSAiIioE27fLMWBcnNSPXrgQGDxYjl1LmdzONfL0zqSkpOD48ePo1KmT/glMTNCpUycEBwdn+zXBwcEG+wOAr69vjvunpKRgyZIlsLe3h5eXl8FjX375JRwdHdGwYUPMmjULaWlpOY41MDAQ9vb2GRf3Ut6JgJ4iJUWWLQLSrlUX6Fq7Vg4ii9MBY69eciBraQls2iQfeo//LWQOdKmZjUZEhW/xYgl01a8vmV0bN0oG6FdfqT2ywuPiIjW8zM3l/vjxwCefsEsjERERlSxarZSr8fOTQFeFCsDRo8DQoaUy0JUXeXp3oqOjkZ6eDldXV4Ptrq6uCA8Pz/ZrwsPDc7X/1q1bUaZMGVhZWeGbb77B7t274eTklPH4u+++i9WrV2Pfvn0YNWoUvvjiC3zwwQc5jnXSpEmIjY3NuNy8eTMvL5VKm+XLpVWrm5vUgQGA8HBg1CjJ7Pr7b3XH9zg/P8nesLAANmyQJY7ZFaSPiADat5dOjkuXFv04iahwpabKmT1AOvG8957cfustoF499cZVFJ57Dti9W/+ap02T94ABLyIiIioJoqKABg2A776T+zY20pCopM/xCkixWdjZvn17nDhxAtHR0Vi6dCn69u2Lw4cPw8XFBQAQEBCQse/zzz8PCwsLjBo1CoGBgbC0tMzyfJaWltluJ8oiOVmK/AHSwczaWm4HBEi2RKNGxbPrV+fOknnWq5d86JUpIwe9mdvMuroCY8bI+N96C3B3N/6ubESkt349cOeOBOofPQJOnZJl19Onqz2yotG2rVzc3WUZ45w58rm9ZIlktxEREREZoz//lPpcCQlyv0EDYO9eqdNFuZKnzC4nJyeYmpoiIiLCYHtERATc3Nyy/Ro3N7dc7W9ra4uaNWuiefPmWLZsGczMzLBs2bIcx+Lj44O0tDRcv349Ly+BKKtly4CbN6XDl64T4x9/AP/7n6SGLllSfAv+9ewJ/PKLBLgWLQImTsya1TBjhqznTk8H+vQBTp5UZ6xEVLAURWpVAZLdOWOG3J4+HXB0VG1Yqhg7VgL7APDjj7K8OyVF3TERERER5ZWiyJyuXTt9oOvdd6U0DQNdeZKnYJeFhQUaN26MoKCgjG1arRZBQUFo0aJFtl/TokULg/0BYPfu3Tnun/l5MxeYf9yJEydgYmKSkflFlC9JSYZZXVZWQGKiZEEBcvDUuLF648uNV1+Vmj2A1OjRvR4djUaWMLZvL5kffn7StY2IjNs//0jNBktLCWZHRQF16ug/v0obLy99Zuu6dUCPHvpJIhEREVFxl5AgtbimT5egl6UlsGUL8O23rM+VD3lOVwkICMCQIUPQpEkTNGvWDHPnzkV8fDyGDRsGABg8eDAqVaqEwMBAAMDYsWPRtm1bzJ49G35+fli9ejWOHTuGJUuWAADi4+Px+eefo0ePHqhQoQKio6OxcOFC3L59G3369AEgRe4PHz6M9u3bo2zZsggODsb48ePx2muvoVxx6pJHxmfpUlkC5O4ODB8u2z7/HLh6VTK9iuPyxeyMHCmBrPfeAz7+WLI6Mh/w6mp7vfACcO6cBLwOHgTYKYvIeM2dK9cDB8qkqFw5oGFDfdH20mb4cKll8dprUsNw1y5Z7r1tG2Bvr/boiIiIiHJ29SrwyiuyCsfEBOjbF5g9G6hYUe2RGa08B7v69euHqKgoTJ06FeHh4fD29sbOnTszitCHhYXBJFPUsWXLlli1ahWmTJmCyZMnw9PTE5s2bUL9+vUBAKamprhw4QJ+/vlnREdHw9HREU2bNsXBgwfx3HPPAZD6W6tXr8b06dORnJyMatWqYfz48QZ1vIjyLDER+OILuf3RRxI5VxQgJka2zZ8PlC2r3vjyKiAAiI2VjmTvvCM1fF5+Wf+4g4O0rG3eHHB2ZhFnImMWFgb89pvcHjtWslI//FDdMRUHAwZIwKtPHyne//ffQJs2UsiemeBERERUHK1YISUp0tJkvrJmjSxjpGeiUZTSccQbFxcHe3t7xMbGwo7ZLARIrZuAAKBqVeDffyX7Sef0aaB+fcNi78ZAUaSD5NKlErzbswdo1cpwn8uXgSpVDF8vERmXDz+UZctt2gD79jG1/XF79sgyxsREuV+zJhAUJJ99haig5xoLFy7ErFmzEB4eDi8vL8yfPx/NmjXLcf9169bh448/xvXr1+Hp6YmZM2eiW7duGY9v2LABixcvxvHjxxETE4PQ0FB4e3tn+1yKoqBbt27YuXMnNm7cCH9//1yNmfMtIiKiXNJqgWHDpAYzIIkW584BlSurO65iLrdzDc6OqXSKjwe+/FJuT5mSNfDToIHxBboAGfN338lBXnIy8NJL8oGZWc2ahq/3ypWiHSMRPZv4eGmcAUiQ6/nngb/+UndMxU2nTtKxyN5eOtVeviyB/3//VXtkubZmzRoEBARg2rRpCAkJgZeXF3x9fREZGZnt/ocOHcKAAQMwfPhwhIaGwt/fH/7+/jhz5kzGPvHx8WjVqhVmzpz51O8/d+5caIzx/yAREZExuH8fqFdPH+hycgIOH2agqwAx2EWl0+LFQGQkUK0aMGSI1LsaOVIOiIydmZl0kmzRAnjwAOjSJfuC9KmpstzxueekyDURGYcVK+Rv291d2lKfPStL98hQ8+ZAaChw5owU7r95UwJeoaFqjyxX5syZgxEjRmDYsGGoV68eFi9eDBsbG/z444/Z7v/tt9+iS5cumDBhAurWrYtPP/0UjRo1woIFCzL2GTRoEKZOnYpOnTo98XufOHECs2fPzvF7ERER0TM4eFCCWhcvyv02bWSeUreuuuMqYRjsotInPR2YN09uf/SRFHOeM0eW/vXoUTJqWdnYSOcO3QFe165SzyszU1N5LDlZanuFh6szViLKPa1WOvIAUtNBqwV69gQaNVJ3XMVVtWqyVP3PP6V4f2ysfmljMZaSkoLjx48bBKVMTEzQqVMnBAcHZ/s1wcHBWYJYvr6+Oe6fk4SEBLz66qtYuHAh3Nzcnrp/cnIy4uLiDC5ERESUg/nzgbZtpfOiRgNMnQocOCD1V6lAMdhFpc/27VLcuXx56WIWFQXMmiWPTZtmnMsXs+PoCOzcCVSoIJkNvXtLNpeOiQnw668SELt9G+jVSwJfRFR87d8PXLgA2NoCISGybfp0NUdkHJydZcn6zp1Ay5Zqj+apoqOjkZ6entH8R8fV1RXhOZyYCA8Pz9P+ORk/fjxatmyJnj175mr/wMBA2NvbZ1zc3d3z9P2IqBRQFJljxsUB9+5lPQGr1aozLqKilJYmNVfffVf+JmxsZF43Y4baIyuxGOyi0ue77+R6+HCJoH/+uSxjbNRIOniVJFWrAtu2yYHxnj3Am28aZq7Z2QG//y51bQ4dkg9fIiq+fvpJrt3c5G/5lVeAHAqM02NeeQVo317tURRrmzdvxt69ezF37txcf82kSZMQGxubcbl582bhDZCIiofkZCn9sW+f1Bv6/HN9LUmd556T+aWFhZxgtbKS+05OWT+La9YErK0lY7l6dcDLC2jdWlYePN5p+Nw5WZmQlla4r5GoIF26BHTuLM2FAOCttyTZoE0bdcdVwpmpPQCiInXlipzZ12ika+H168CiRfLYl1+WzI5mDRtK+9oePYAffwRq1AAmT9Y/XquW1Pjy85OJSosWwNChqg2XiHIQFwesXy+3dY0lmNVVIjk5OcHU1BQREREG2yMiInJcWujm5pan/bOzd+9eXLlyBQ4ODgbbe/XqhdatW2P//v1ZvsbS0hKWlpa5/h5EZEQURb/iQauVVQBnzgBXr2bNxmreXOrf6sTGyv+t7CQmShORtDS5PHoEJCXJJSrKcN/atYH335dmI1ZWQN++UqvSxASoWBHw8JBgmaenFPvOZedYoiLz/fdSJzk9XRIQli8veQkWxRSDXVS6LF4s1126SNBn8GAgJQXo2BF48UV1x1aY/PykTtno0VKnrFo1YMAA/eNdu0oK7dSp8mHcrZucXSOi4mP9ejlAKF8eiImRCX+DBmqPigqBhYUFGjdujKCgIPj/d+Cm1WoRFBSE0aNHZ/s1LVq0QFBQEMaNG5exbffu3WjRokWuv+/EiRPxxhtvGGxr0KABvvnmG7z00kt5fh1EZGSuXwf+/hs4ckQu5cvLCgFAgkunTkmgC5AlWC4ukq1lZSWX116TYFVkpMyvzcyyz8C6cEHm3rlx8aJ+Tmpqqt+u1UoDplu39B2J3d1l2XqlSnL54APJLKtfX/5f1quXtQM7UWFJS5Pgq+5vyNxcgrzNmqk6rNKEwS4qPRITJbMJAN5+Gzh9WmpWAZLVVdK9845kg3zzjWRuubtLZzKdjz6SyUf//gx0ERVHuiWM778vSxerV1dzNFTIAgICMGTIEDRp0gTNmjXD3LlzER8fj2HDhgEABg8ejEqVKiEwMBAAMHbsWLRt2xazZ8+Gn58fVq9ejWPHjmFJpqVFMTExCAsLw507dwAAF//rAuXm5mZweVyVKlVQrVq1wn7JRKSG33+XerZ79ugDWTplywJ37kgm1blzshrAxkYCTA8eSHAst6yt5flsbSXgZGamv5iYSNaLLtMrLU2WSiYkSNaXrrFIevqTv4eu6y6gz0jLXL7DzEz+dzZpIie+Bw3K/fiJ8uLSJVmKq8u4rlIFCA6WbEQqMgx2Uemxdq1kQ1StKplMiYnAJ5/IP+omTdQeXdGYNUte78aN0sHt8GFJ/QZkorFyparDI6IcXLkibapNTCQjtVIltUdEhaxfv36IiorC1KlTER4eDm9vb+zcuTOjCH1YWBhMMi29b9myJVatWoUpU6Zg8uTJ8PT0xKZNm1C/fv2MfTZv3pwRLAOA/v37AwCmTZuG6VwSS1Q63L5t+D9kwQIJdAGSOVWzpmR0paRIUOtJ/28cHWUZYdWqcqlYUU6YurhIhpWzM+DgIAGuzFlZeZWeLoGvuDiZy9+7p7+OigLu3jW83L4t439cWhrw779yWbNGTgDXrSuXkBBZitmzpwT1SkrDKip6CxcCY8fqg7P9+wOrVvF3SgUaRckc7i654uLiYG9vj9jYWNjZ2ak9HFKDj4+kZAcGAhMnqj0a9SQkAO3aAUePSh2E4GCgXLms+924IWnhAwcW+RCJ6DHTpklwvmNH/UEJFTuca/A9ICqWLl6U+qwbNkjNrbt3AVdXqas1fTrw559y++pVw0woQE6yeHpKwfl69fSXGjWkjlZxpNVKRk1YmMxnb9yQk0anT0vGzeN1wR5nZiaBu+efBzp1kgYn7DRLubFkidSFBuT36KefeCxVCHI712Cwi0qHY8eApk0lbfrmTTnTVJqj63fvynrxW7fkn/j27bKOXOfmTVkm9eCBrC1v21atkRKRVivLLm7ckLPjCxcCQ4aoPSrKBucafA+Iio24OFnV8OOPcmJTx9RUDr4vXwb++Sdrofnq1WWO2LSpXBo2LL5BrfxKTgauXZMg4Pnzcpzw118SBHv8/dBxdZX3wstL5sg+PpLVVpqPJ0gvIUGyuX74Qe67u0sQ2cND1WGVVLmda3AZI5UOuo6LffrIGZ0ePYCPP5bC7aVRhQrAli1S12DPHmDMGHmPdP+wK1eWIvW//iqptydOyD95Iip6Bw5IoAsA4uNZ74GIiJ5szx6Z6+pqXZmYyMF3fDwQHQ388ot+3xo1JOO/fXu5Lg3L5C0tgTp15NKzp367okgAbONGYP9+yQSLiJDtERHS0X3nTv3+NjYS/GrfXgKEPj5AHjrgUgmQnCwNwHbvlrmaRiPHmFOnPtvSXSoQzOyiku/+fTk4TEqSDjOffy6ZTG+8ASxdqvbo1LV5s3QJURRg7lw5I6ETHy//uM+dk+yvnTv5oU2khiFD9AcmDRsCx4/zTHIxxbkG3wMiVaSmSjCmcmW5f++enNgsW1bqVMXF6fe1tAQ6dABeeklObFatqs6YjUV6uhTJv3ABCA0Fli+Xsig5qVwZaNlSAl/NmwONGkmnSip5Dh0CeveWFTOA1KpbtSr3nUYp37iM8TGcfJVic+cC48fLmZfly+WfjomJnLnRFWcvzWbPlu5uJiYS/Mqc7XbunKSwJyQAn34KTJmi3jiJSqOHDyWrUnd2/n//k2xLKpY41+B7QFSkYmOB778H5s+XzK2NG2Wu+9NPMs/VsbcHXn5ZTnB26iRL4il/tFrg1Clg1y6ZNx8/Ltk9OTE3l0ZYLVvqL8z+Mm7x8XJsmTlpokED4I8/Ss3PVlFkinr5MnDypJTEu3FDmrdGREisfckSoLAaOTPY9RhOvkoxb2/5K/zuO0lJXrsWGDBAIu8kn1ajRskHdpkycpaiQQP94z/9BAwbJsEw1u8iKlrLlwOvvy63q1WTDlJmrEBQXHGuwfeAqEjExQHz5gFz5sgKBkAyttLTJZMLkGyil14CXn1VupBbWqo33pIsJUUyvXbvlhpNkydLE6jDhyX4kZSU9Wtq1JBSIrpL7drM2DYWe/ZIzbvISLlvYgLMmCE/90wdko2Rouj7VJw+Lde6AFZkpDRAjYuTWHlMTPa/2pnt3194h40Mdj2Gk69S6vRp6aRiYSH/gFq0kL/kU6cMAzqlXWoq4OsL7Nsn6exHjkgqro5uGVXXrrIElIiKRps2wMGDcnvBAuCdd9QdDz0R5xp8D4gK1cOHEuSaPVsf5LKwkICLjo+PnMTs3VuWMZJ6Mv8PfxInJwl6tW4tl4YNeWKrODp0CHjhBf39atWA338v1seUCQnSd+HSJTn8DQvTZ19FR0svsocPpfzcgwdPTlLMjpWVfPxYWUnORLly0gfOzw8YPLjwysyyQD0RAKxYIdd+fpLmrShSsLMYfyipwtwcWL9eJkiXL0uq+969+rOA330nH+gffqjuOIlKkxs39JPk8uUlw5KIiEqvLVv0JSVMTGRJXUqKBLVee02CXF5e6o6R9A4ckOWkusL2+/frownly8vxyOHDEnXYtEkugEQNWrSQtJg2baSGLjPz1KHLC/rtN2nopTN2LDBzZpH9XBRFVk/euydZVTExUm0mNFSyrnSBq9hY2S8pST4ichu8evhQf9vaWr7O0lKyuBwcAEdHWZpYqZKU/PP2liobxX1FNINdVHKlpwMrV8rtrl2Bt9+W25Mnqzem4qx8eWDrVgl4HToEjBwpSxg1Gvkkmz5d7RESlS5r18p1s2bAtGly2o2IiEoPRZEjWVdXOQFy4IA+yKXVAtWrA++9JykUZcqoPVp6nEaj7/o4bpyk2Rw4IKskKlUCJk6UYOU//wCdO0sjqLQ0KYi/e7dcAIk6NG8uwa+2beU25wSFb/duYMIEybwLCpJtnp7ADz9IEDKPkpMlKHX7tj67KjJSDsFSUiRZ8+xZuTx6JL8uSUnyWHp6/l+GhYV8PDx6ZJiB5eQkHy2VK8uvlZeXLOyxts7/9ypuGOyikmvfPvkkKVdO1laXLy//YHx81B5Z8VW7NrBunQQHf/kFqFcvazZXejrwxRfSaaRlS3XGSVQarFkj18OGSccsIiIqPc6cAQIC5Mi3e3ep4ZiaKo81bQp88IFk4rNTtvGwsZE5dteu+m0WFpKZpygS3dAxN5d0mkeP5HLggFx0jzVtqg9+vfACg50FRFGA5H9CkTjpEzw6cBQxKI8YpCPGpA9s+nVH6iv9EX/bApc/laWBDx/KJT5efkyJiXKpUEHfCDUyUh4vCKamskzQ0VFiqeHh8qN3cJBDXRcXWTpYubL8WtSuDdjZld6ScKzZRSXX4MGyjPHNN4FFi9QejXH57jupDaTRABs2SPcencBAyY6rUgU4cUKCiURUsC5flrOHpqbS0trZWe0RUS5wrsH3gOiZxcdLNu/cuVnTOTp2BD7+WLJKSuvRa0n16JGUENm+Hdi2Dbh1S//YuHFA3boS7Nq/X07mZ2ZqCjRurF/22KqVRD+MkKJIJlNSklySkyUGmJys3x4RIXWodNlP8fFynZAggSYPD0l8TEqSLoG3bsnXJydLvDglRa7T0iRAlJ4uXxcXp0VqqgZA4f9taTTyYzMzk4yqGjXkR5aQIEmcjo4y9XN1leBVpUqSyOnhIdlZpR0L1D+Gk69SJj5ePh3i44G//jIsJki5M3o0sHChLGH8+299DYi4OKBRI/nv8corUuuLEy6ighUQAHzzjZyiu32bhWqNBOcafA+InsnOnVJ3KyzMcPsLLwCffgq0b6/OuKhoKYpk9u3YIcGvuXOlSBIA/O9/wBtvALVqyfLGW7dknpCZRiPz9jZt5NK6tWHjqTxKT9cHlaKiJFNJVx9Kd3n4UIJPNWtKkCkhQZIS796VIJNuOV7mQJOrqz6Adf++7FdcIxMajZQvdnKSQ6PYWHnrLS0l+GRrKxlWZcpIJlX79hKcsrOT15iQALi5SeCqXDlJzqP8Y7DrMZx8lTK//goMGiSfSmXKSNvlceMYCs+LtDRZOrV7N+DuLh0a3dzksWPHZAljaqpkgb31lrpjJSppnJykCunzzwMnT6o9GsolzjX4HhDlS0qKLFlftcpwe5MmwGefST0nnlgkQFZefPed4bYaNeSi0QCXL0N75Sruwg23UBnhcEMEXHHPqS7uudXDg3LV8ciuAp5rVgYPH2nw6JHUyI+M1AekdMGo9HTJkCoOHB3lkM7SUgJt9+5J+TozM8mQMjWVAJKZGdCpk8T2rKyAa9fkYmUltaisrWU1qY2NrB5t3x5wiz4D62kf4MGN+3iIsihv/gjlRvSG3XsjYetaBtbW8r2o+GCw6zGcfJUyvr7AH39IF8Zt2+QfwMWLrGuQV/fvSzeYixelGOa+ffqA4TffSPaJpaUEwp5/Xt2xEpUUhw/L3xsgy4hfflnd8VCuca7B94AoX0JDgRdflCN4QNI/Zs0CBgxgkKuUURTJkLp1S5brOTjIdPz+fUn8u3FDiwe3E/AwMhGPYtORmGKKJFhBCxM44h5iy1bGw0caKErB/95oNBL0SU/X39YFmszMJNjUubNkM1lbA//+K6/B2lofbNIFmmxsgJdektdnbS2vNy5Onx3l4CDX1tZyqFG+fAEdxmm1Umx+9mzJevvjD30tNAB4/XXgk09k3SAVWwx2PYaTr1Lk7l2pyqfVysLm69eBefMM28VS7l26JEX979+XQv8rVsh/OEUBevSQDo516ki2V3HvP0tkDDp3lozKMmVk5scDHaPBuQbfA6Jci4uTtV+zZgHz58u81dISmDRJOsCx257RS02VZX9Xr8rlxg35sdeuLXHN6GiZRkdEFEzXvawUaKDAVKOFmYkWFibpsFCSYJ32CF2wHXZ4iDJ4hOvwQLyJHeycLWDvbgeHGk5wqFcR5ao5oHx5STAsW1YCT+npEnQyuqlJeLg0eViyRI4NMzMzk1VAH3wAPPecKsOjvMntXCNfRUAWLlyIWbNmITw8HF5eXpg/fz6aNWuW4/7r1q3Dxx9/jOvXr8PT0xMzZ85Et0ydpaZPn47Vq1fj5s2bsLCwQOPGjfH555/DJ1PXvJiYGIwZMwZbtmyBiYkJevXqhW+//RZl2HmCHrdqlUwY6tQBLlwA7O0lNZzyx9NT6nL5+gIrV8o/gUmT5L/c8uVSE+DaNclG6dBB7dESGbfUVMmgBIC+fY1wNklERE918CDQp48Eu3Qd+AYMAGbOlNIRVCxptRKkunJFzgVfvSrl1R49kgbmunpWe/ZITaeCWALo5iY1nsqVA2JiJNhUtqwc3jg4yPI+JycpZq6rS29vD9hapcO2dmVoIsIBBUD6fxc3N6nh5ekpJ9UOHQcOzZcnj4Bcjv33zStXlhPep5tIAfzGjWFWvvyzv6iitGUL8OOPcv14JNHGRkqxjB3Lv7sSKs/BrjVr1iAgIACLFy+Gj48P5s6dC19fX1y8eBEu2RS+O3ToEAYMGIDAwEB0794dq1atgr+/P0JCQlC/fn0AQK1atbBgwQJUr14diYmJ+Oabb9C5c2dcvnwZzv91oBo4cCDu3r2L3bt3IzU1FcOGDcPIkSOx6vG17UQrVsi1Lmlx5Ei2431WHTrIWce33pJOjLVrS3F6Jydg3Tp5f7mMkejZzZsnhTIA4PPP1R0LEREVrLQ04L33ZE6lm6dWqQIsXSpZvaSK5GTg5k0pqH7xogSxYmOlAWJ4uFz27JHYZH6ZmAAWFhJfadFCptBOThJjsrAAKlSQlXNVqsjClEqVZN/8n/MyBW7dBI4elcHv3w8cOiQvZt06OYm9c6fsqtVKB9CUFInYHT8uBfJv3ZLLb7/pn7ZaNWlU5eUlc38vL6Bq1eJzci45WTIk79+X7pZvvy0RyMxq1QKGD5djRCPtWkm5k+dljD4+PmjatCkWLFgAANBqtXB3d8eYMWMwceLELPv369cP8fHx2Lp1a8a25s2bw9vbG4sXL872e+jS0vbs2YOOHTvi/PnzqFevHo4ePYomTZoAAHbu3Ilu3brh1q1bqFix4lPHzbT6UuL0afngNTOTCYWpqWQdMVpfMN59VyZoNjbS5bJhQ7VHRFSy1Kghs+xatWTGTUaFcw2+B0Q5unsX6NgROH9e7ms0UmLjiy9YBqKQKIosFTx3TmI3d+5Ih7zbt+Xy++/yeH6WDmo0ElOxsZF4SceOUhTdxUWStMuXl+9Vo4Zss7Ao8JeXd0lJUmd33z5pmzhwoGy/e1fqxAESlatXT7o/OjvL8dSdO8CJE5LSlh07O1n5Ubu2rKzRXVevXvgvPC1NSqls2iT1t86eBerXl/FmTq1zcAAGD5YGZo0bF5/gHOVLoSxjTElJwfHjxzFp0qSMbSYmJujUqROCg4Oz/Zrg4GAEBAQYbPP19cWmTZty/B5LliyBvb09vLy8Mp7DwcEhI9AFAJ06dYKJiQkOHz6Ml7Mp3pucnIzk5OSM+3Fxcbl+nWTEVq6U64oVJa+4d28GugrSnDlSbXLXLqkqefSonIrSOXxY9lmxopj8VycyIpnPPY0dq944iIioYG3dKssWk5LkfrVqki3Dk4bP5MEDOT9kbi6ZWWFhwM8/y3nuuDh5u/NandrcXGKPugBWhQpy0Wjkuk4dObQwyviklZUUZW/TxnB7fDzQqxcQHCyBrTNn5KIzbpyUNLl/H/j7b8kMu39f3uiLF+XNDg6WS2a6N61qVbl4eMh9Z2e56NZf6irRm5tnDUJptZJxlpAgWWl370rAbu9eOSa5fTtrtDIkRK7r1pXWjF26SAMIc/OCeBfJiOQp2BUdHY309HS4uroabHd1dcWFCxey/Zrw8PBs9w8PDzfYtnXrVvTv3x8JCQmoUKECdu/eDScnp4zneHyJpJmZGcqXL5/leXQCAwMxY8aMvLw8MnaKAqxZI7fffls+pFmUvmCZmcl73KKFnJns2VM6mFhbA4mJUrA+MlL+oX31ldqjJTIuoaEya7e2lrOPRERk/HbtAvz99Qfkb78NzJ3LA+9cSE+XWMbatbKy7to1iXXcvy/xmbzUxDI1lQBVixZSikrXbM/FRRKZ6tSR26WycXvNmhLMAiTYdfSo/hISoi9VUq6cFAT75Rf91+qigWXKyA/ExkbS5S5elB/SnTtyySExJgtLSzlhnpoqQa7c/pA1GqlH1rixdLHu3Fl+0FSq5atAfWFo3749Tpw4gejoaCxduhR9+/bF4cOHs60DlhuTJk0yyCiLi4uDOzN8SrajR6W7ho0NMHq0kZ5yMQL29lLk0cdH3vOhQ4HVq+UA/fvv5R/MrFlS56tLF7VHS2QcUlPl7wgA/PxYZ5CIyNilpkqd09mz5YRs2bLA5s1Au3Zqj6zYuHcP+OcfWYV2/ryc77lzRwq+lysn2Vq5WWJYvrzUunJ3l/3LlJFqAPXqSZymenWZplIuVKwoJ7N79pT7imIYcEpJkWOAy5flB3j3rlx0liwBRoyQr1u3DujXT7abmOgDvFqtPG5tnTVqmZwsl+w4OEhgzcFBWlhWqwa0bSvzpueek0AZUSZ5CnY5OTnB1NQUERERBtsjIiLg5uaW7de4ubnlan9bW1vUrFkTNWvWRPPmzeHp6Ylly5Zh0qRJcHNzQ+RjheXS0tIQExOT4/e1tLSEJX/hS5e1a+X6pZcY6CpsNWoAGzZIavDatZImPH26nLl8+23gu+8kM+XkScNljkSUvc8+A779Vm7rJoZERGSc/v5bil+fOyf3R46UoFcpO5GRmgqcOiUBrXPnJBh19apcgoP1jSizExsr12ZmEic0NwdcXSWo5ekpZZkaNpSMLBubonk9pZJGY5ju1rGjXABJsdO1pgwLk0hlo0b6r7OwkGtdwOzxINZXXwGjRkkAbe9eoFs3+UGXKSM/7MqV5QdetaqcQG/WrGheM5UYeQp2WVhYoHHjxggKCoK/vz8AKVAfFBSE0aNHZ/s1LVq0QFBQEMaNG5exbffu3WjRosUTv5dWq82oudWiRQs8ePAAx48fR+PGjQEAe/fuhVarhY+PT15eApVUWq0+2BUdLaeH6tZVd0wlXZs2ksn1+uvAjBky2+jfH/j6a2mpffq0BLx27ZKzOUSUvZQUYOFCubawkMkeEREZp1mzgA8/lAP8MmWkjul/x00lUXq6xDmuXJGp+LFjEvO4f1/+reWGpaUk67i5SVmnunVlFZqnp5wzLZVLC41BuXJAkyZyyY6/vxSQT0iQul6xsfqO04Bkkekq/b/4opREsbIqkqFT6ZDnZYwBAQEYMmQImjRpgmbNmmHu3LmIj4/HsGHDAACDBw9GpUqVEBgYCAAYO3Ys2rZti9mzZ8PPzw+rV6/GsWPHsGTJEgBAfHw8Pv/8c/To0QMVKlRAdHQ0Fi5ciNu3b6NPnz4AgLp166JLly4YMWIEFi9ejNTUVIwePRr9+/fPVSdGKgX++UdynU1MgKAgYNs2BruKwrBhElicNUuWM3p4AM2bS12vJk2k1fFXXwHZdGolov+sXy9LAQDJTOUpaiIi45OWJgf327bJfRsbOeHXsqWqwyoIDx/Kecx//pFMrStXZOWaLvsqc/wiO7rsrI4dZWlh9eoSJ6lVSwJaDGaVYCYmEvQtU0bf8TE7ZmZyISpAef6N6tevH6KiojB16lSEh4fD29sbO3fuzChCHxYWBpNMWRwtW7bEqlWrMGXKFEyePBmenp7YtGkT6tevDwAwNTXFhQsX8PPPPyM6OhqOjo5o2rQpDh48iOeeey7jeVauXInRo0ejY8eOMDExQa9evTBv3rxnff1UUugK02u1ckbg9dfVHU9pEhgo3VB+/13W9x8+LIHG+fOB4cPlvqKwxS9RTubP19/+7yQPEREZkagoOckXFib3a9SQjnHly6s7rjxITJTVl3//LXGJq1dlddrhw5KU8yQWFlI+ydZWpnuenlIry8dHLqwuQkRq0ChKXhuyGqe4uDjY29sjNjYWdnZ2ag+HClJ6uhQB0BVHHD4c+OEHdcdU2jx6BLRuDZw4IUUU/v5bTuHt2AF07cpAF1FOjh0DmjaV2xYWsgy7bFl1x0T5xrkG3wMqhUJDZQ4UHy/3X3lFCnMXwxIO6emyEGLPHmDfPmmYd/OmLDlMTX3611tbA46OMu2uXVvKM/n6SmyP2VlEVFRyO9dgriAZv7/+MuwC8s476o2ltCpTRt+h8cwZKbC9ZUvW2kPM8CIylDmrq2tXBrqIiIzJ1q1A7976wtuBgaqXblAUSTDbt0+yss6elWblVlbAjRtPr6NlaQm88ILUAvf0BJycpD54gwbFMn5HRJQjBrvI+OmWMAJSF6FhQ/XGUppVriwttdu0AXbuBMaP1x/IP3woQchWraQjERHJspfVq/X3e/VSbyxERJR7iiI1SSdNktvOztKJunfvIhvCw4dSReLyZcnQ2rtXkswePpQh5cTCQhrdJSfL1E2XodWmDdC4MTO0iKjkYLCLjFtamqSK6+TQFZSKSOPGwK+/ykH7ggVSeXTMGGDVKulGtG4d0KKFnB4kKu0cHYFvvwXeektabb/0ktojIiKip0lJAQYMADZskPujRgHz5kkUqYClpQHnzgEHDgBHj8rt3C47NDGRZGE3N8nQ8vcHOnQAqlRhQIuISgcGu8i47d8vNW6srSWwwswI9b38MvDll9J2e9w46dA4YoQUsN+xQ5Y4Hj3KaqVEJiby+QUAnTpJ33UiIiq+4uKAF1+U4vMajQS53nnnmUo0KAoQHi7dDoODJePqzh3J2vr3X6mzlRNbW8DLS7KznJ0lq6tFC6BdO8naYuUIIirNGOwi46ZbwjhoELB4Mf+rFxcTJkhe/dKlQP/+MoP7+WeZkZ0/D7z7LrBsmdqjJFLfb7/JNQP1RETF2507QNu2Mr8BgJo1gWHDcj33fPhQuhseOQL88YcEsu7cAWJjpZn4k5iayvmQSpWAOnUkkb5NG1l+WAgJZUREJQKDXWS8UlP1KeT9+jHQVZxoNMDChVIRdfduoHt3qZK6ahXQsSPw449A+/bAa6+pPVIidfTpI0VTTpyQo5iePdUeERER5eTcOZm3REbKfW9vWVv4WJZ6YiJw+rT0Tjp+XGpp3bol2VoPHjz929jaAs2bS5K8pydQrRpQrpwUiSciorxhsIuMV1AQEBMD2NtL4XMqXszNpUZXq1bSodHPT2Z/H38MzJgBvPmmtPqpVUvtkRIVrZMngfXr9W2t2rXjkQwRUXH1119Aly5AfDwAILFFB5z5cgv+3WKDu3clW+vkSTl3oWvKmBMXF+lseOuWXNetK1Oh1q1lKaIZj8yIiAoMP1LJeK1YIdexsZI11Lq1uuOhrOztgW3bAB8fOdXZrx+waZOcDT1/XrrRMdhFpc3ChXLt4CAB+yLs3kVERE93/75MU/Z+fwlnVtzBJWU/bqMy7msckRJsDrR98tebmemXHdaqBXTuLB/1LM1IRFR0GOwi45SSAmzcKLerVWNmV3FWpQqwZYsUl9i5U7ozrlwpS7dcXdUeHVHRun9fOpYCEujSaKRFFhERFZnkZFliePQoEBoqt8PCpELGgwfyUS08/7v8R9HfdHSUWvU1awI1agDXrgEtWwJNmwLlyxfdayEiouwx2EXGafduKYwAAOPHs15XcdekCfC//0kRiqVLpUPj5Mn6x1NSWGGVSofly+Wzq2JFqUzcqpX0hSciogKTmAicPSvBrKgoCW7duCFLDkNDJaj1NK64iwcoB3vLZFRwN4Wnlw28vE3QvLkUhmdAi4ioeGOwi4zT/PlybW4ODBmi7lgod3r2lBbdY8YAH30kGV+vvSYdNSdMAPbtk1OjRCVVerp+CaONjVxzCSMRUZ4kJUn/m8hIqX117RqweTMQESEJswkJ8nGbGyYmQJkyUjbR3V2qLrxmthrVvxgOWyQAr78OLFki2ehERGRUGOwi45OcDOzdK7e7dAHs7NQdD+Xe6NEyQ509WyaQFSpI4PLmTaBvX+DQIcDSUu1REhWOnTuBq1ellp2udf0rr6g7JiKiYiIpSQJWd+8Ct29Lyc9bt+T+vXtAXJzsk9tAFiAxqgoVgJdekoLwHh5AeDjQoAHQsKF0OjQwZw7w3nty284O+PRTBrqIiIwUg11kfNau1eefT5+u6lAoH776SgpjrFsH9OolXen69wdCQmSCuWCB2iMkKhy1akkX0uvXJfDVogVQubLaoyIiKhSpqZJ99eCBLCWMiAC2b5dgU1SU1MWKi5MmhykpgKI89SkzaDSSDF65shSBv3QJcHaWbXXrAt7eQP36krWVa5kDXYB0kXZxycMTEBFRccJgFxmfNWvk2s1NiiaQcTExAX75RU7V/vWXZHh98w0weLAs8WrbFujTR+1REhU8T09g0SKgXTu5zyWMRFTMKYo0vb51Sy63b0uCva2tBLGio4EdO2SfR49kCWFSkgS68hK80rGwkEwsNzc5L2ZrK/GmypWlH5GnpwSx6teXxwrMN98YBrr69ZO5ihkPlYiIjBU/wcm4JCcDBw/K7eXL1R0L5Z+VFfD779K26OJFYNYsYNw4YO5cYPhwWVtQs6baoyQqeOHhwJ9/ym0Gu4ioEKSlScZUbKxkTD16JIGpY8ekptX9+/JYbCzw8KE8bmUldavi4mTfixflefITsHpcuXISsHJ2lvpaVlayzdVVsrI8PCSQ9dxzEsQq8p5D334LBATo7/v7S9dcBrqIiIwaP8XJuPzxh8zEKlUCOndWezT0LMqX1y/lOn1aZr4vvAD8/bdkdgUHy4yYyNg9eiTB3BEjZLmuogDNmkmTBiIq0bRaOU/34IFMX3TBpYcPZfnew4f64E9SkgSg/v5bMqR0l8REeSwpSUr+ubrK9rg44MwZCUqlpUktq4IITj2JqamMtXFjwMFB/pWfPCnLBZ2d5VK5stTHqlZNlhU6OBTumJ7JvHny+azTuTOwejUDXUREJQA/ycm4zJ4t1336yHI4Mm4eHrL+oU0byXbp3l1myh07siAslRwrVgDLlsnvuK5GF7O6iPLl4kXgxx/lHElmuiCPokhicMWKcjsmRmLMWq3c12rlkp4u11Wryr7p6ZLxdPy4/nHdPrprXXZSaqoEqf79V/98uudWFLmYmcl1WlrRv0eZ2dtLIMrWVpYFmplJHxhLS2kKa2MDlC0r/447dpSa7GXLSg8NZ2d5bypXlgBbiTv/tGgRMHas3HZ2BurUATZuZKMcIqISgsEuMh4XLgAHDshtX191x0IFx9sb2LRJOmtu3Qq88YYsayzydQxEhUBRpOMoAAwapG+qwWAXUb6cOSN9Tp5k167cP9+xY7nfNyIi9/vq+ujkRKORi4mJZEp5eEiMxdxcXqO5udSvsrCQIJOVFWBtLdlSPj4SvLKykqwqOzsJapUrJ5lWTk5ycXSUr8mPEp88v2IF8PbbcnviRKnXZWEh0T8iIioRGOwi4/HRR3JtaVkKZmGlTIcOUgh2wADghx/ktPyHH8rRQng44O6u9giJ8icoCDh/XlIr7Owk9aNxYzliJaI8q1oV6NEDOHcu62O6cyTVq0s2kkYjGVinT0tQSRdgMjWV+yYm8u+menXZlpAAnDgh2U+mphL7MDPTB548PKSpqrm5ZGxduCBTEmtrfTDKykriJW5ukhVlaSnPkZ4uGVPm5gV7Lof9XPJh40Zg6FC5PWYM8MUXPMFGRFQCMdhFxiE5Gdi2TW537swljCVR//7SoTEgQM6yWlgA69dLf/JjxyRQQGRs5s2T66FD9Z9hzOoiyrcmTaS/CVG+7N4tnRa1Wrnv7c1AFxFRCcWIARmH1asl4AUAH3yg7lio8IwfD7z/vtx+/30piHLpEvD664VfdZeooF29KktzAWDgQGDvXrnNYBcRUdH7+2+gZ0/9GlMXF6kZSkREJRKDXWQcZs6Uazs76dhHJddXX0kWjFYrbanMzIDffpPW4ETGZOFCCdJ26QKcPSvrmLy9Zd0UUS4sXLgQHh4esLKygo+PD44cOfLE/detW4c6derAysoKDRo0wPbt2w0e37BhAzp37gxHR0doNBqcOHEiy3OMGjUKNWrUgLW1NZydndGzZ09cuHChIF8WUdE7cQLo2lVaWwKypnTnTn4eExGVYAx2UfF39qzUvAGAV19lunlJp9EAS5dKUZbUVH377wkTgL/+UndsRHlRowZQpQrw7ruyJBdgVhfl2po1axAQEIBp06YhJCQEXl5e8PX1RWRkZLb7Hzp0CAMGDMDw4cMRGhoKf39/+Pv748yZMxn7xMfHo1WrVpipO4GUjcaNG2P58uU4f/48du3aBUVR0LlzZ6Snpxf4ayQqElevykmHhw/lvqUlsHkz0LChuuMiIqJCpVGU0rE2KC4uDvb29oiNjYUda/8Yl3nz9K2hQ0I4OSktEhPlLOyBAzIxTU6Wir/Hj0vVXyJjkJYGPHgAVKggty9elArXVCIV5FzDx8cHTZs2xYIFCwAAWq0W7u7uGDNmDCZOnJhl/379+iE+Ph5bdUtnATRv3hze3t5YvHixwb7Xr19HtWrVEBoaCm9v7yeO49SpU/Dy8sLly5dRo0aNp46b8y0qViIjZUXA5cty38RETj68/LK64yIionzL7VyDmV1U/JUrJ9fVqskSICodrK2lCrG3twS6zM2lM+Mbb6g9MqLcMzOTul1paUCDBgx0Ua6kpKTg+PHj6NSpU8Y2ExMTdOrUCcHBwdl+TXBwsMH+AODr65vj/rkRHx+P5cuXo1q1anDPoStucnIy4uLiDC5ExcKjR4CfnwS6dAdDixcz0EVEVErkK9hVkDUkUlNT8eGHH6JBgwawtbVFxYoVMXjwYNy5c8fgOTw8PKDRaAwuX375ZX6GT8bmf/+T6yFDuISxtLG319fUSE2VANjUqWqPiujJ/vlHmmroiiCvWyfXXMJIuRQdHY309HS4uroabHd1dUV4eHi2XxMeHp6n/Z/ku+++Q5kyZVCmTBns2LEDu3fvhoWFRbb7BgYGwt7ePuOSU1CMqEilpAC9ekk3Zycn4OhR4PBhYMQItUdGRERFJM/BroKuIZGQkICQkBB8/PHHCAkJwYYNG3Dx4kX06NEjy3N98sknuHv3bsZlzJgxeR0+GRNFAU6elDbRANC/v7rjIXW4ugJ79gCVK8vSxrfflsL1RMXVZ58BAwZIYDY6GvjjD9net6+64yLKpYEDByI0NBQHDhxArVq10LdvXyQlJWW776RJkxAbG5txuXnzZhGPlugxWi0wbJh89lpbA9u2SVZts2Zqj4yIiIpQnoNdc+bMwYgRIzBs2DDUq1cPixcvho2NDX788cds9//222/RpUsXTJgwAXXr1sWnn36KRo0aZdSgsLe3x+7du9G3b1/Url0bzZs3x4IFC3D8+HGEhYUZPFfZsmXh5uaWcbG1tc1xnEyrLwGOHZMlbGlpcl27ttojIrVUrQoEBUmb8NBQWZawbZt0VyIqTi5dkt9NAHj9dakNk5YmtQbr1FF3bGQ0nJycYGpqioiICIPtERERcHNzy/Zr3Nzc8rT/k9jb28PT0xNt2rTB+vXrceHCBWzcuDHbfS0tLWFnZ2dwIVLV5MnAqlVyu0YNLh8nIiql8hTsKqoaErGxsdBoNHBwcDDY/uWXX8LR0RENGzbErFmzkJaWluNzMK2+BFi0SH/71VfVGwcVD7VqyVlaBwfg77+B7t0Bf3/g3j21R0ak99+JHHTrBnh66pdh8zOM8sDCwgKNGzdGUFBQxjatVougoCC0aNEi269p0aKFwf4AsHv37hz3zy1FUaAoCpKTk5/peYiKxKJFQOZuo7a2QA5LcImIqGQzy8vOT6ohceHChWy/Jq81JJKSkvDhhx9iwIABBmcH3333XTRq1Ajly5fHoUOHMGnSJNy9exdz5szJ9nkmTZqEgICAjPtxcXEMeBmT+/f1B4kA0K+femOh4sPLC9i+HejUCUhIAG7cAPr0kSCYWZ4+zogK3oMHgC7L+d13gZs3gT//lFqDXIZNeRQQEIAhQ4agSZMmaNasGebOnYv4+HgMGzYMADB48GBUqlQJgYGBAICxY8eibdu2mD17Nvz8/LB69WocO3YMS5YsyXjOmJgYhIWFZdRFvXjxIgBkZMxfvXoVa9asQefOneHs7Ixbt27hyy+/hLW1Nbp161bE7wBRHm3dCrzzjv6+p6dss7FRb0xERKSaYnV0mJqair59+0JRFCzKnNUDGASunn/+eVhYWGDUqFEIDAyEpaVllueytLTMdjsZiV9+AXT1QV54AahSRd3xUPHRogWweTPQtasUAN+3D3jvPeDbb9UeGZV2P/wg3b+eew7o3Bn4+mvZ3rq11JwjyoN+/fohKioKU6dORXh4OLy9vbFz586ME4hhYWEwMdEn6Lds2RKrVq3ClClTMHnyZHh6emLTpk2oX79+xj6bN2/OCJYBQP//grDTpk3D9OnTYWVlhYMHD2Lu3Lm4f/8+XF1d0aZNGxw6dAguLi5F9MqJ8uHYMamLqChy39kZ2LFDitMTEVGplKdgV2HWkNAFum7cuIG9e/c+teaDj48P0tLScP36ddRmLaeSRVGkNbQOl//Q4zp2BDZuBHr2BNLTgXnzpCbS0KFqj4xKq9RU+T0EgIAAyebS1YzhZxjl0+jRozF69OhsH9u/f3+WbX369EGfPn1yfL6hQ4di6BM+JytWrGjQMZvIKFy/LrU8ExPlvrW1ZHTVqKHqsIiISF15qtlVWDUkdIGuS5cuYc+ePXB0dHzqWE6cOAETExOeaSyJ9u8HdMtiTUxkmRrR4/z8pPi3RiP333gD+OcfdcdEpVdkJODhIU0UXn0VOH9eGiiYmQG9e6s9OiKikunBA6mRGBkJmJrKvHHNGnZeJCKivC9jLOgaEqmpqejduzdCQkKwdetWpKenZ9TzKl++PCwsLBAcHIzDhw+jffv2KFu2LIKDgzF+/Hi89tprKFeuXEG9F1RcZO7s+eKLkopOlB1/f6nt1r+/ZHi99RYQEqIPgBEVlUqVpD5XZCRgZaWvOdilC5CLEzhERJRHqalyMuH8efkMXrECuHULeOkltUdGRETFQJ6DXQVdQ+L27dvYvHkzAMDb29vge+3btw/t2rWDpaUlVq9ejenTpyM5ORnVqlXD+PHjDep4UQmyaBGwezcQEQEMGKD2aKi469cPiIsDRo6UTJpx44C5cxnwInW4uMhSbN0SRn6GEREVPEWRE1xBQUCZMsC2bdLEhoiI6D8aRdFVcizZ4uLiYG9vj9jY2KfWAyOVHT8ONGkCWFpKwMveXu0RkTFYvhx4/XW5PWaMBLxM8rRSmyh/1qyROnK6QshHjgA+PtIBLCJCDsSoVOBcg+8BFZGvvgI+/FBuf/45MHmyuuMhIqIik9u5Bo8EqfjQauVM3c8/y31/fwa6KPeGDQOWLpXb8+dLB7zSEcsnNV2+LNlbVasCUVGyTbeEsWdPBrqIiArahg36QBcA7N3L//dERJQFg11UfKxfD9Srp6/Zxc56lFdvvAEMHy63Dx0CunfnBJgK17ffyu9Yu3ZSXzA9HVi9Wh5jF0YiooJ19CgwcKD+fu3awNq1LF1ARERZMNhFxcd330kXxvh4oGJFKU5PlFc//AB06CC3t2+XrBsGvKgw3L+vD87rakju3w+EhwPlygGdO6s2NCKiEicsTIrPJyXJfRcX+T9fvry64yIiomKJwS4qHs6cAQ4c0J+ZGzRIWkgT5ceuXZIlCEg9paFDZZksUUH6/nsgIQF4/nl9gHXlSrnu0wewsFBvbEREJcnDh5KtHREh962tga1bgerV1R0XEREVWwx2UfHw3XdyrcvAGTJEvbGQ8TMzA/76C3Bzk/u//CK/U+np6o6LSo7EROCbb+T2e+9JoD4uToKrgATsiYjo2aWny9LF06flvkYjtRGbNlV3XEREVKwx2EXqi4sDVqzQ3/fxAerWVW88VDKUKwf8+ae+QPivv8pkOTVV3XFRybB8ORAZCVSpIktlAQl0JSRIDZkXXlB3fEREJcWHHwJbtki2bJcuUiuxZ0+1R0VERMWcmdoDIMKKFcCjR4ClJZCczKwuKjiensC2bbKkLCZGghHJyVJA3NJS7dGRMYuMlAOv998HzM1l2w8/yPUbb7BYMhFRQVi6FJg9W27/8gvQty8/X4mIKFeY2UXqUhT9EsbkZDl47N9f3TFRydKmDXDzJrBpkwS4Nm0C/P0lA4cov6ZPB65e1Xf/PHUKOHJEAl+DB6s6NCKiEmHvXuCtt+T2tGlAv34MdBERUa4x2EXqmz8fqFlTbvv7y/IzooJkYQH4+UmWl6UlsHMn0LUrEBur9sjImFWqBNjYyO1ly+S6Z0/pEEZERPl38SLw8sv6WptsMkNERHnEYBepS6MBWrUC7t+X+0OHqjocKuFsbfVNEP78E2jfXpajEeXW0aPAiROG25KS9HUH33ijyIdERFSi3LsnJ6Ti4uR+zZrA2LHqjomIiIwOg12kvm3bZGJToQLw4otqj4ZKskaN9IXDTUyA0FCgdWsgLEzdcZFxUBQ54GrYUF+fCwA2bJCAfZUqQKdO6o2PiMjYpaRIlv+1a3Lf0VGysR0dVR0WEREZHxaoJ/VMnw7ExwMnT8r9QYMAM/5KUiGysAB++00CXGfPyu/bv/9KAGz3bqBOHbVHSMXZwYNAcLAshfXz02/XBb5efx0wNVVnbERExk5RgJEjgb/+kvvW1sCOHUCNGuqOi4iIjBIjC6SOhw+Bb76RFHWT/xIM2YWRikK5cnKWuEUL4NYtmUzfuiUBsB07gCZN1B4hFVeBgXI9dKhkogLA5cvAvn2yJHvYMNWGRkRk9GbOBH7+WW6bmADr1wNNm6o7JiIiMlpcxkjq+PlnCXQ5OkrR0RdeAOrVU3tUVFpUriwBLwcHIDFRrqOjgXbtZDvR40JD5XfDxASYMEG//ccf5drXV5YxEhFR3m3YAEyaJLfNzYElS4Bu3dQdExERGTUGu6joabXAvHlyOy1Nrt95R73xUOn03HPA5s2yJK1tW6BDB1lW+9JL+jPLRDqffCLX/frpl9SkpQHLl8vtESPUGRcRkbE7cgR47TW5PXo0cPUqMHy4umMiIiKjx2WMVPR27gQuXZLlY7GxgIsL8Morao+KSqPWraUG0/PPS3vz118HVq6UZWp37gATJ8ryNCrdjh8HNm2SrK6pU/Xbt28HwsPlM6x7d9WGR0RktK5fB7p0kSzrrl2lxAXrtxIRUQFgZhcVvW+/lWtdZ50RIyS7hkgNDRtKUXELC+Cnn4D+/WX75Mlyhjk9XdXhUTEQHi41ul591bCJwfz5cj1kiPz+EBFR7j14IFnV9+9LgOvzzxnoIiKiAsNgFxWt8+eBP/6QbJlbtyRTYtQotUdFpM/sWr1allNoNMB330nWYXy82qMjNfn5AVeuAHPm6LedOAHs2SOBUi7DJiLKm5QUqcl17Zrc9/YGatdWdUhERFSyMNhFRcvODhg3DqhVS+736AG4u6s6JCIAEnh1cJDb//ufFCG3tJS6Xm3ayLJGKr2srQFnZ/39r7+W6759gapV1RkTEZExUhTJiA0Olvs1agC7dgE2NuqOi4iIShQGu6hoVaokhZ51gQNmRFBxodEAc+cCgwZJlte8ecDs2YCTExASAjRvDpw6pfYoqSgdPSqBz8eXst68KRmAAPDee0U/LiIiYzZ1qv4z1NkZ2L8fKF9e1SEREVHJw2AXFb1ffwUePpR09Y4d1R4NkZ6JCbBsmWQcJiVJG/QffpDf1Zs3gVatpMEClQ4ffih1uqZPN9z+7bcSAGvfHmjcWJWhEREZpaVLgc8+k9u2tsCBA0DlyuqOiYiISiQGu6hoJCVJxszBg8CCBbLtrbfY6Y6KH3NzYM0aoF07Ccq+/rpMztu3l/vdu0thckVRe6RUmPbtk4u5OfDGG/rtsbHAkiVye8IEdcZGRGSMduwA3nxTbpubS93DunXVHRMREZVYDHZR0fjlF8no6tMHOHdO6jIMGaL2qIiyZ2UltbqaN5cAV2ysZHQNHSoZPe++C4wcKQV2qeRRFGDaNLk9YoRhTa6lS+V3ol49oEsXdcZHRGRsjh6VOaBWC/TrJxldzZurPSoiIirBGOyiwqfVSu0jAHBzk+uBA/XFwImKo7Jl5Sz0H39INpeFBfDjj1KY3MREljd26gRERak9Uipof/whWaiWlsDkyfrtKSlS1w0A3n+fmalERLlx+TLQubN0Nu7cWU6Atmih9qiIiKiEy1ewa+HChfDw8ICVlRV8fHxw5MiRJ+6/bt061KlTB1ZWVmjQoAG2b9+e8Vhqaio+/PBDNGjQALa2tqhYsSIGDx6MO491PouJicHAgQNhZ2cHBwcHDB8+HI8ePcrP8Kmobd4M/PuvdGI8fVq2sTA9GQMHB1nOqHP9OvDKK8DWrfL7fPAg0LQpcPKkSgOkApeeLoEsAHj7bWmqobN2LXD7tgTtX31VnfERERmTqCigWTPgwQOgYkVg/Xo5eURERFTI8hzsWrNmDQICAjBt2jSEhITAy8sLvr6+iIyMzHb/Q4cOYcCAARg+fDhCQ0Ph7+8Pf39/nDlzBgCQkJCAkJAQfPzxxwgJCcGGDRtw8eJF9OjRw+B5Bg4ciLNnz2L37t3YunUr/vzzT4wcOTIfL5mK3KxZcl2jhmR5vfgi4OWl7piI8uryZaBNG6ndVa8e8M8/QM2awI0bwAsvSCCEjN+PPwJnzgDlygFTpui3K4pk9QGyjNXSUp3xEREZi9hYoGFD4P59uT9mjGRNExERFQGNouStyrKPjw+aNm2KBf8VGddqtXB3d8eYMWMwceLELPv369cP8fHx2Lp1a8a25s2bw9vbG4sXL872exw9ehTNmjXDjRs3UKVKFZw/fx716tXD0aNH0aRJEwDAzp070a1bN9y6dQsVK1Z86rjj4uJgb2+P2NhY2NnZ5eUl07M4dEgCAbqzeCkpUvQ5c7YMkTG4e1eCXZcvAx4e8ntsbw/07StFdgHgvfeAL78EzMxUHSo9g3/+kWDWq68C48bpt//xB+DrK93Dbt6UYBjRYzjX4HtA/0lIABo0AK5elfsBAfqSFkRERM8gt3ONPGV2paSk4Pjx4+jUqZP+CUxM0KlTJwQHB2f7NcHBwQb7A4Cvr2+O+wNAbGwsNBoNHP6r6RQcHAwHB4eMQBcAdOrUCSYmJjh8+HC2z5GcnIy4uDiDC6lAl9VVu7YEupo3B9q2VXdMRPlRoYIEuDw9ZTlj27ZytnrHDuCDD2Sf2bMlczGHTFcyAs2bS8Br9Gj9Nq0W+OgjuT1iBANdRERPkpIiS/x1ga4RIxjoIiKiIpenYFd0dDTS09Ph6upqsN3V1RXh4eHZfk14eHie9k9KSsKHH36IAQMGZETpwsPD4eLiYrCfmZkZypcvn+PzBAYGwt7ePuPi7u6eq9dIBczXF6heHbhyRe5PmsSizmS8KlcG9u8HatUCwsIkQ/H6dWDmTKlDUqaMPN6okQRMyDiZmBhm561dCxw7Jj/fSZPUGxcRUXGXng60bCmdtwFg0CDg++/VHRMREZVKxaobY2pqKvr27QtFUbBo0aJneq5JkyYhNjY243Lz5s0CGiXlyZtvAkOHSjp7/frS1Y7ImFWsKAGtOnVkOVu7drK0sVcv4MgR2X77tix5nDdPaj1R8TdqlNToevjQcHtysr4j44cfAo+deCEiov8oisz7jh+X+716AT//zJOcRESkijwFu5ycnGBqaoqIiAiD7REREXBzc8v2a9zc3HK1vy7QdePGDezevdtg7aWbm1uWAvhpaWmIiYnJ8ftaWlrCzs7O4EIqSEiQA34AmDhRMiaIjF2FChLwqlcPcHLSL2urWxc4fFgm+KmpwNixQO/e0oWKiq9jx4AlS4DPPwcuXjR8bPFi4No1+ZmPH6/O+IiIijtFkc/IH36Qud7UqcC6dQx0ERGRavIUebCwsEDjxo0RFBSUsU2r1SIoKAgtWrTI9mtatGhhsD8A7N6922B/XaDr0qVL2LNnDxwdHbM8x4MHD3Bcd6YIwN69e6HVauHj45OXl0BF5csvpavZ998D0dFAtWpAv35qj4qo4Li6Sg2vPXuAzJ9ZdnYywZ83DzA3BzZskGWNx46pN1bKmaJI4WQAeO01IFNtSMTGAp9+KrenT5fi9EREZEhRJHP/22/l/g8/ADNmMNBFRESqynPLsICAAAwZMgRNmjRBs2bNMHfuXMTHx2PYsGEAgMGDB6NSpUoIDAwEAIwdOxZt27bF7Nmz4efnh9WrV+PYsWNYsmQJAAl09e7dGyEhIdi6dSvS09Mz6nCVL18eFhYWqFu3Lrp06YIRI0Zg8eLFSE1NxejRo9G/f/9cdWKkInbnjhwYJicDzs6ybcIEdqijkufxJW3ffSfdp1q3lhbrzZtLkPfaNalh8vXXsp0HAMXHmjXAwYOAlRXwxReGj82cCdy7J0tTX39dnfERERVniiLL+f/8U+4vWgT8d0xARESkpjyvKevXrx++/vprTJ06Fd7e3jhx4gR27tyZUYQ+LCwMd+/ezdi/ZcuWWLVqFZYsWQIvLy+sX78emzZtQv369QEAt2/fxubNm3Hr1i14e3ujQoUKGZdDhw5lPM/KlStRp04ddOzYEd26dUOrVq0yAmZUzMyaJYEuT08gKkoyYDjxoZJu61bgnXekKcPOnbKtaVMgJAR45RX9ssbu3dmtsbi4f19+JoAUns/cyOT2bWDuXLn95ZcM1hMRPU5R5OSOLtDVpYvUPyQiIioGNIpSOqonx8XFwd7eHrGxsazfVZjCw2XJYlKSFPK+c0eyIz74QO2RERWuxESgTx9g2zZZvrhypdwH5IBg4ULg/fclEOziAvz0E9C1q6pDLvVGjgSWLpXMrRMnAEtL/WNvvAEsWwa88IJkfjEbj3KBcw2+B6WGVisZy4cPy/2XXgJ+/52flUREVOhyO9dgtXAqWLNnS6DLw0MCXc7OwFtvqT0qosJnbQ1s3Aj07y9ZXP37y3IOQCb/o0dL3a769SWzq1s34N13JUhGRS8yEvjf/+T2kiWGga5Tp4Dly+X2rFk8eCMiyiw1FWjYUB/oeuUVYPNmflYSEVGxwmAXFZzISKlZBAAxMXI9fTpQtqxqQyIqUubmwK+/yjIOrRZ4+23go48kswuQQNfRoxLkAoD586UgeqbmG1REXFyAM2fkM6t1a/321FRZdq3VSifNHJqvEBGVSikpUpvy1Cm5368f8Ntv6o6JiIgoGwx2UcGZMwdISAAqVADi4oBatYARI9QeFVHRMjWVjK5PPpH7X3wBZO5Ia2UlHau2b5d6dufOAT4+0qY9JUWdMZdWVatmzTz98kups1aunHTUJCIi8eiRLFe8eFHuv/MOsHq1umMiIiLKASvuUsHp3h346y/JXAHkoNHcXN0xEalBowE+/ljq1l2/DnTqlHWfrl0ls+idd4C1a4FPP5VlID//DHh5FfmQS41//5Xi8+3bZ33sxAl9kHLBAgnck9G5dw/45x/5cV68CNy4IdsqVQJu3pSyetWqqT1KIiMTHS2Brn/+AWxtgVWrgB491B4VERFRjhjsooLTqpUUev77bynq7O+v9oiI1DV8uOH9qChZJlexotx3cgLWrAF69ZIljydPSgfHKVOAiRMBC4uiH3NJptXKEtP9+6XToq4TIyBZdUOHAmlpwMsvAwMGqDRIehpFAS5dAoKD5U/k0iXg8mXgjz/kT0yrzf7rzp6V6xs3GOwiypMjR4C2baUma7lywI4dkpFMRERUjDHYRQXnzBkWdSbKSXKyBFFu3AC2bAG8vfWP9e0rBxJvvgls2gRMmybZXkuXsmZUQZo3TwJd1tZZMxI+/1yCjU5OwOLF/PwqBhRFEoX/+EOuL1wA7t6VlVS56SNtZSUlI52dJb7cpw9Qvbrhnx4RPcWvvwJDhkgU2cwM2LeP2cdERGQUGOyiZxcQIHWKTpyQyVCvXjxAJ3pcdLSspbp1S7IgH18C4uoKbNgg9U/GjpU0lBdekJpSgYHAE9rqUi6EhgIffii3v/7aMLUnJESCXYAUrHdxKfrxlXLR0cDvv0sssmxZOXdy+jTw4EHOX2NqCjRuDDz3HFCzpjTUdHUFmjcHatRgvJLomU2eLP9/APkD27OHgS4iIjIaLFBPz+bffyVb4uuvZRJkZqafGBGRXqVKsu6qUycgPl6W+X79tWGKikYjy+fOn5cldYoiwZd69SQQlpt0FsoqPl7e15QUoGdPw6L0SUmStZCeLhl2ffqoN85SIipKfq1feUWCUlZWkn31xhuSRLJoEXDwoAS6TEzkGLtSJaBNG2lkunatPEdaGnD4MPDjj3JM/t57wGuvSeCrpAS6Fi5cCA8PD1hZWcHHxwdHjhx54v7r1q1DnTp1YGVlhQYNGmD79u0Gj2/YsAGdO3eGo6MjNBoNTpw4YfB4TEwMxowZg9q1a8Pa2hpVqlTBu+++i9jY2IJ+aVScKYp8Vurmc46Osl64VSt1x0VERJQHDHbRs/noIzlILFtW7r/5JuDpqe6YiIorBwfpwjhqlBxMTJggR/jJyYb7OTrKkuCgIIkG3L4tGZNdukiAmfJm3DipVF6xIvDDD/pIiKIAw4ZJGpGzsxSlpwKVnCxx2jlzgEGDpKyji4v0Zdi4Ebh6Vf/rb2Iiv/qvvw6sWCGrShMSJB556xZw4IA0Mu3TR1ablnRr1qxBQEAApk2bhpCQEHh5ecHX1xeRkZHZ7n/o0CEMGDAAw4cPR2hoKPz9/eHv748zZ85k7BMfH49WrVph5syZ2T7HnTt3cOfOHXz99dc4c+YMfvrpJ+zcuRPDH68/SCVXYiJQv740TAHkZMvNm4C7u7rjIiIiyiONopSOVIG4uDjY29sjNjYWdlwOVDAOH5b1IhqNHDQ6OUlGSmk4CiF6FooiGZEBAbL0d9Ag4Jdfst83MRH44gvgq68kM8ncXFJYpkyRjlj0ZEePAs2ayefUnj1Ahw76x6ZNk+6LZmbArl2Gj1G+XL0K/O9/UmfrzBkgJib7/UxMJL5Yp44ki/j7y5JEY8/IKsi5ho+PD5o2bYoF/wVhtVot3N3dMWbMGEycODHL/v369UN8fDy2bt2asa158+bw9vbG4sWLDfa9fv06qlWrhtDQUHg/pYjZunXr8NprryE+Ph5mZk+vfsH5lhG7eRPo3VsK0gOS3bVxo/H/YRIRUYmS27kGa3ZR/igK8MEHclsX7Jo7l4EuotzQaKQuV506kg05ZUrO+1pbA59+Kkvtxo6VzLAvv5T1XjNnAv37S+SAste0qdRBu3zZMJj1668S6AKAJUsY6MoHrVbOb/z1lxwP79+fNUlRp0EDSU5s2hRo2BBwc+Px85OkpKTg+PHjmDRpUsY2ExMTdOrUCcHBwdl+TXBwMAICAgy2+fr6YtOmTc80Ft1EMqdAV3JyMpIz/eDj4uKe6fuRSvbskeXe0dGShfz++5K9T0REZKQY7KL82bED+PNPOVrRagFfX+DVV9UeFRVjyckyh37wAIiLM+xh8Ntv0t/g4UPptKZbupSQIJdff5V4TlqaJDht3w6kpsqvHiCxVl2O6s8/yzIpjUZWrG3dKslQ5uaAhYX+2spKVq1Vry73t2+XJlO2toCNjVzb2gJlysgq3Rde0NeIT06W4ti5SHJ4Ml9fWZZobq7fFhIi0YDHIwE1a8qL2bJFgl7XrwMDB0qQefZsoHXrZxxMCdavn+H9gwcB3bKsiRNlKSM9VVoasHOnZG4dOiR/z48eZd3PzAyoXBnw8ZGMrZ49JWZLuRcdHY309HS4uroabHd1dcWFCxey/Zrw8PBs9w8PD3+mcXz66acYOXJkjvsEBgZixowZ+f4epDKtVoJca9fK/YYN5Z9y5iYeRERERojBLsofXUaEokhkYPFinqYvhRRFGgyGhUnBaF9f2RYbC0yaJDGFe/ckwJWUZPi1vXrJgXJcnGSHPKnrWtWquR9T16653/e55/S3dQmKOWnTBqhQQQJg589LrXlzczmIt7WVgJiDA1CunMSiGjQA7O2Bu3clqcjRURIfnZwkaJbx55I50BUUBHTuLMGZ77/X18LLPMgePYAXX5QiSF9+Kcv02rQBXn5Z7teqlfs3oKRSFMl6GzxY6nRldvmyvFcpKfJLqOvCSFno6m2tWwf88w8QHp71b8TGRlazt2ghf+MDBwLe3vx3UBLExcXBz88P9erVw/Tp03Pcb9KkSQYZZXFxcXBnfSfjEB4uZ3KuXpX7rVrJGmRGp4mIqARgsIvy57vv5OgmJQX47DPAw0PtEVEhUxTpkrZnjyQV3bkj9XhSU/X7VKwoQa/M23Ly2295+/5mZhIXMjGRi6mpXAA5sNZddLEjrVbGkZYmt9PT9Ze0tKwH7U+rXvjnn1m3pabKJS5Oglo6u3bpb2cXRNNoJLPMxkaKbdevD5QvD8RsscJN5QtU+d91VNs/FtUXvAe3js8ZBscAORD56CMpbj99uizD27hRsr6GD5fHSvPB5uzZEm1dtEgikzY2sv3WLcDPTyKwTZtKnTQuAc3w6BGwezdw9qwsSfz776xBakCCuA0ayO/uW28ZxmupYDg5OcHU1BQREREG2yMiIuDm5pbt17i5ueVp/yd5+PAhunTpgrJly2Ljxo0wf8IP2dLSEpaWlnn+HqSylSslq1X3D7tbN+D33wsgZZmIiKh44H80yp8vvpBAV9Om0guejF5EhCQJ/f23LCm8dEm2NW8uNWvDwqRW+pPcuaO/rVsKWK6cZDW5usryQgcHyWyyt5frsmWzLh20tgYsLSUgZGkpywwLOlNEq5VfYd0lOVkO7JOS5HXqllEmJuqXU8bHyyUuTuIl9+9LFtuDB7IE8+FD2U9R5HZ6evZBNEWR501MlKRIvRf+uwC4C6CX3NRoFFhYaNC0qSRuOTrKeO/dc4W7+yJUm/oxau6YjzqHf0KF77+HZvly6fg4aZKko5Ummzbp6wm+954+0HX+vKQe3rwJVKkincZ0j5VSd+7IEuFt24BTp7LPrjQ1lb/hRo1kSeKAAfI3TIXLwsICjRs3RlBQEPz9/QFIgfqgoCCMHj06269p0aIFgoKCMG7cuIxtu3fvRovMa8ZzIS4uDr6+vrC0tMTmzZthZWWV35dBxVFysmQP//673DcxkfoA772n7riIiIgKGINdlDcXLwLnzklajqkpsHSpPr2GjEJqqqxcOH9eLitWyIFuTtlYe/YY3i9TRpbiVaokCX01a0rswM1NH9BydpZAVXFmYiJjLKxxKooEvmJj9ZcHD4DISEkwunNHgom2thIYu39fVpJERgLJyQq0Wk2m59IgOVkKgf/1V3bfrSKAwP8uCkxT0uEx/xqqLrwAZ88ImNarhRRTG7i7AzVqAJ6e8rNzcZGgY4lZchYSIuvoFAV4+21gzBjZHhwMdO8uqYi1a0vqXT6yXYzd/ftSa+uTT4DTp7MPXpuYyOrOdu2Atm2BunWZ/KaWgIAADBkyBE2aNEGzZs0wd+5cxMfHY9h/NeYGDx6MSpUqITAwEAAwduxYtG3bFrNnz4afnx9Wr16NY8eOYcmSJRnPGRMTg7CwMNz578zExYsXAUhWmJubG+Li4tC5c2ckJCTg119/RVxcXEbBeWdnZ5jy/71xu3AB6NhRf2bKxUWKVdarp+64iIiICgGDXZR7J09Kb3jdkc+ECYCXl7pjoid69Ehqmu/YAYSGyvLDhw+f/DXm5hLMqlJF5r/Nm0tAq2pVKTrN1Sq5o9HoM9UeLxuVi69GcpKCmFnLcGvGMlxJr4Lr/SaiTKuGePhQCoMfOyax5/h4yUJLS9N/bTrMcAWeuKL1BC5CLk8Yp7OzBC9dXPRZdR4eEhirXFkfxHRxkSy7Yun2beCllyTC2Lkz8O238uK2bZP1domJUjF969YS3zVWUYAbN/R/++fPy8/13Lms+5qayorXF16Qxp5du/L8RXHRr18/REVFYerUqQgPD4e3tzd27tyZUYQ+LCwMJpkikS1btsSqVaswZcoUTJ48GZ6enti0aRPq16+fsc/mzZszgmUA0L9/fwDAtGnTMH36dISEhODw4cMAgJo1axqM59q1a/BgyQLjlJYGfPMNMHWqfm2yv78Upec6ZCIiKqE0ivK0SjUlQ1xcHOzt7TNaaFMeabXS7e3QIbnfpImkmDDyUWwkJUliy7FjsjrhyJHsO6UBEq+sVUuyNtzcJIjRoQPw/PNcolTshITIWrPZs5+YgqUokil2/rw0eKxYQUHcwZOIXHcAQTdq4Dga4SHskAgbaJH/VJ2yZSV4p8sKc3CQwJguWJY5MJal1lhhiY6WbIVTpyRCe+iQDG7ZMlnOmZ4u9WjWrpXoYwm0aZP8moSESOZgTpmatWpJELNWLUmCa9KkBGX2FQOca/A9KHZOnpRItq6LZ+fOUoqicWN1x0VERJRPuZ1rMNhFufPzz8DQoXK7TBmZPFWvruqQSjNFAa5dk6yNbduA48dlhZY+u8eQg4Mc4DZtCnTpInNdNlsyUjExQM+ecrDSuvXT91cUaYs5cyawfTsA4CHK4G6j7rjWeRQuOrdCw6ZmiIuT5gLr10vdNl3NsWdhbq4PfpUrJwlVlSvrg2HOznLR3c53HCo6WqK1kZGyZLFMGeCdd6SNIAAMGSJLro04gyE1VZa5njsnsbwjR4BmzSS4eeKEJLY9TqOR99bbGxg0SP7unZ2LeuSlC+cafA+KjZQUYOJEYO5c+T9gawvMny9zOUa4iYjIiDHY9RhOvp7BgweSuhEbK/fXr5eiLlRk0tMlaWXXLmm4d/KkLF97nIuLrNTy9JTH/f0lBlBsl55R3r37rhywaDRSk+rTTyWFKjdOnZKg19q1+siomxswcqRcKlXK2FVR9F0m79yRbKErV2SlYHy8ZJH9+CMQFJRzkDWvrK0lGOPgIMGxChVkeE5OUpT/8evy5TPVXIuMlKJUZ88Cb74pkTszM2DaNOlOaQQHd/HxkixraioNEJYvB9askSWJ9+49vWOog4Nka7ZpA/ToIVlb/NsvWpxr8D0oFv78E3j1VX0U3NQUWLhQMl2JiIiMHINdj+Hk6xkMHSqZXYAUfV64UNXhlAZaLXDmjNSN3bcPOHAg+05pgBz4N2oEDB8upYmM4JienkVsLBAQIJEmQAJU8+YBL7+c+x/+nTvAkiXA999LtwJA1rb6+gKDB0vmWC5T/xRFhnT3ruHl5k2JnyUmShzq22+BP/7Ix+t9CktLSVhwKJsGh4dhcIy5DCdEwam8Aqc+HWBftyLs7ZFxsbOTS5kycrG1LbwaVYoiy4vNzCSpLC1NsrL++EOOQW/flh9FVJT8faekSAZmRETOS5AB+VG5ukpiX5s2krn1/POyxJTUxbkG3wNVRURIsH/TJv22WrUkBfyxGmxERETGisGux3DylU9HjkiqECDpQqdPs05XIbl5Uw6C16+XVWePZ26VKSO1tx0dpZh0376yLMnRUZ3xksr++EOCz1euyP2XXpKMr6pVc/8cKSnAxo0SwD54UL/dzk5+wV57DWjVqsCiQcnJciwWESExtogICYRFRAAffCCPR0UBX38tw8ppGWU5h3TEPgC0KJhxmZpKMMrBQV66tbUEph4+lMCSqalcm5hIAEtR5PhR968kLAy4fFmWGqalyUV3W1HkbzQl5enNIR7n7Czfo0YNydJq3hx47jn5EbOIfPHEuQbfA1WkpwOLFwPvv68vQG9qCkyZAnz8MT8wiIioRGGw6zGcfOWDokiq0G+/SWrChQty1EUFIjFRMrY2bZKuadnV3LG1lXlq+/aSvfXwoSzvIgIgv0Sffw589ZVEV54l8/LSJeCXX4AVK2TdnI6Tk6yJe/lloFOnTOsGC5eiSLZTdLQEwGJiZCnfvWPXMGJdZ9hGXMFDu8r4NuENrEt7GQ/ggDgTBySa2CI1TV+A39dXEt5iYyUgFRVVJMN/IjMzCaiVLStLjytWlJXitWvLOYVq1eR+Eb3VVIA41+B7UOT27ZNs3xMn9NuaNQNWreKcjYiISiQGux7DyVc+fP01MGGC3P75Z1neRM/kyhUpKr99u8xPdSdgMzM1lSZJvXsDXbsCmbrGE2Xv3Dk5g79smT4aeu+e3DbJY+dFrVbqvfzyi0Ri79/XP2ZrC7z4okRf27eXNKO8Pn9+KQrwzTeSApaeLhEs3b8vLy95/a+8ApiYIDVVAsOxsbLKU1e36uxZKVuWlCRxwvh42S8uTu736CGZVImJwD//SK17rdbwosv0atpU4oCAvNVhYRLAsrGRi5OTXFxcJLPLzk5qjDk4SLCLSibONfgeFJlLl6SG486dct/eXmo4Vq4sBTtZ04CIiEooBrsew8lXHv3vf1LcFABmz5azhpRnuho9GzdKgtzNm4aPV64s8YPYWDnQ9vcH2raVg2WifFMUycKKiZG/3w4d8vc8qamyvHHjRgl83bpl+LiTE9CuHdCihRSO8vIq+HW1kZHSmeHjjw0zzgBZYj1lCuDnxwM7KhY41+B7UOju3wdmzJBl61qtbBs1CvjsM30EnoiIqAQr1GDXwoULMWvWLISHh8PLywvz589Hs2bNctx/3bp1+Pjjj3H9+nV4enpi5syZ6NatW8bjGzZswOLFi3H8+HHExMQgNDQU3t7eBs/Rrl07HDhwwGDbqFGjsHjx4lyNmZOvPNi1S1KKFEW6vX37LQ8k8yA2Vk60rlkj14mJWfd5+22pIVu/vtTyYRk0KlDXr0vgKS5O7rdvL0Gh9u3z/7esKEBICLB7t6Ql/vWXFJF7XOXKEviqWRNwd5dL5cpyKVNGftl1LQcBSbPSrVGMiZGK7adOyZKckyel2n1m9vaSZdq3rxSv42cTFSOca/A9KDQJCRLg+vRTw6KedepIAfrq1dUbGxERUREqtGDXmjVrMHjwYCxevBg+Pj6YO3cu1q1bh4sXL8LFxSXL/ocOHUKbNm0QGBiI7t27Y9WqVZg5cyZCQkJQ/7/1WStWrMC1a9dQsWJFjBgxIsdgV61atfDJJ59kbLOxscn1RIqTr1w6f14OVFNSZE3OnTuy7oae6MYNYPNmuezfLxldjytXzrD0ka1tkQ+TSpOoKDn7v2SJZGgBQMuWEvTq0uXZg0QpKcCxY/ILf/y4BKeuXs3915uYyHq+lJQn76fRyMGco6MUzB85kgEuKrY41+B7UOBSU4Hly+WzO3PRwTJlpF7jyJEsQE9ERKVKoQW7fHx80LRpUyxYsAAAoNVq4e7ujjFjxmDixIlZ9u/Xrx/i4+OxdevWjG3NmzeHt7d3lqys69evo1q1ajkGu7y9vTF37txcjTM5ORnJyckZ9+Pi4uDu7s7J15Pcvi1V0CMj5f7WrbI8iLLQJbmsWwesXp11dVXVqrKtbl2gXz8Jcnl78xidVBAWBsyaBSxdKu0OAVmW6O9f8N8rLk6ysk6elOyymzdl6ePNm/L5klN7RRMTKWjl6CiXMmXkeRYtkhphjAyTkWCgh+9BgUlPl0nG1KlSn0vHxESWLX7yCZctEhFRqZTbuUaeyuSmpKTg+PHjmDRpUsY2ExMTdOrUCcHBwdl+TXBwMAIeq/fk6+uLTZs25eVbAwBWrlyJX3/9FW5ubnjppZfw8ccfwyaH4kaBgYGYMWNGnr9HqRUWJsWidIGu4cMZ6HpMcjKwd680q9u+XZYrZubmJl2/e/SQ1QTR0YCrqzpjJcpQpYosfZk8Wep3/fEH0L27/vFdu/StAJ+VnR3QqpVcHqcokqGQnCzZXMnJkgJpby9tCU1MJIL80Uf6gss7dxZOUI6IqLjSaoENG4Bp06T5CAA4O0u3i5o1gZkzC+bzmoiIqITLU7ArOjoa6enpcH3sCN7V1RUXLlzI9mvCw8Oz3T88PDxPA3311VdRtWpVVKxYEadOncKHH36IixcvYsOGDdnuP2nSJIMgmy6zi7Jx9arU8gkLk/vVqgHz5qk7pmIiKkoCW1u2yHF35jIZOq6uQM+ewKBBhsf4DHRRsVKhgnRYTU/XL3lJS5PA9u3bEuzu21eCSxUrFvz312ikLaKuNaJOaiqwdq0E5A4dkm0WFtJ1MdOJFSKiEk1RgN9/l+WKZ8/KNjs7OYs2bpx8LrLAJxERUa4ZTQP0kSNHZtxu0KABKlSogI4dO+LKlSuoUaNGlv0tLS1hyUnB0/37L9Cxo77LmqUlsH59qW0HqFue+MMPUu/18e6Jpqayz/PPS7NKf3/A01OVoRLlT+baLjExsnT57l3gwAG5jB4t3RVfeQXo3VvW5BYWRZGOiqGhct/cHOjTB5g+nX9YRFQ6pKdLJtcnnwBnzhg+9s470omWiIiI8ixPwS4nJyeYmpoiIiLCYHtERATc3Nyy/Ro3N7c87Z9bPj4+AIDLly9nG+yiXDh3TgJd4eGSHh8VBXz/vRz8liLR0cDKlVIa4/hxaQ6XmZeXZG699JLEAqtXZwkhKiFcXKSrQliYZFf99hvwzz+SYXXoEPDggXT+AqQe1+nTQMOGeQ+GK4oE1PbuBYKCgAUL5I9Io5EllXfuAG+9JXVonvF/AxGRUUhLk6Kfn3xiWJMLkInGp59K0U8iIiLKlzwFuywsLNC4cWMEBQXB/786KlqtFkFBQRg9enS2X9OiRQsEBQVh3LhxGdt2796NFi1a5HvQAHDixAkAQIUKFZ7peUqtw4clehMVJWlKu3dL1KdePbVHVuiSkuR4PihIyhUdPZp1HzMz4LnnJLHlvfekMSVRiVWliiyVef99WdK4caMEvtq00e9z4IAUpAOkKLKHh2R9Va0qS23699fXkTl9WgLn16/rL5nXAPfrJx0hAWDCBFm28/jyRiKikig5Gfj5Z+mkeOWK4WNVq0pB+sGDZSJCRERE+Zbn/6QBAQEYMmQImjRpgmbNmmHu3LmIj4/HsGHDAACDBw9GpUqVEBgYCAAYO3Ys2rZti9mzZ8PPzw+rV6/GsWPHsGTJkoznjImJQVhYGO7cuQMAuHjxIgDJCnNzc8OVK1ewatUqdOvWDY6Ojjh16hTGjx+PNm3a4Pnnn3/mN6HUWblS6vQkJ0vaUlCQdEBzcVF7ZIUiIUGftHLkiL4Gf2YajZQpatdO3ppWrWRFFVGpU6mSLGV8/ATGgwfyGREZKYHx6Gjg2DH94w0b6oNdJ04ACxcafr1GI/u8+KLUBdQpW7YwXgURUfHy8KGcBJg1Sz8RcXKSz83ISAn6DxjAyQcREVEByXOwq1+/foiKisLUqVMRHh4Ob29v7Ny5M6MIfVhYGExMTDL2b9myJVatWoUpU6Zg8uTJ8PT0xKZNm1C/fv2MfTZv3pwRLAOA/v37AwCmTZuG6dOnw8LCAnv27MkIrLm7u6NXr16YMmVKvl94qaTVymTqv0AkKlSQNPoHDyTYVUJERACrVgFr1gDnz8vqq8c5OEhiSefOUjLIw6PUlikjyp1Bg+Ty4AFw44b+cv26RJQ9PPT71qwpxeU9PCSw5eEBuLsDVlaqDJ2ISDWRkdKA49tvJeAFSHfFyZOBESPkvpWVYT1FIiIiemYaRVEUtQdRFOLi4mBvb4/Y2FjY2dmpPZyi9+iRHKhu2iT3mzaV9Xvm5sCffwLNm6s6vPxQFODkSXlJf/4p2y5fzlpUHpCkEhcXedm9e8uFdbeIiKgglfq5BvgeZLh8WTrg/vijdJ3N7IMPgJkz1RkXERGRkcvtXIMFAUqDCxekRs6pU1JhvXt3WdMHAEuXFvtAl6IA9+5Jvew1a6QcUFiYZGxlF6rVaIBateR2y5YS2OrcmeUviIiIqJAdOSKBrA0bDLdrNNLC+YMPiv28i4iIqCTg4X9JpigSzBo3DkhMBFxdgVdfBb75Rh6fOxcYMkTNEWZISZFY3JEjcn3pkqyO0mgk0PXgQc5fa2EhZYY6d5aX17AhywARERFREdFqga1bJZPr4EHDxywtgWHDgPHj9WfiiIiIqNAx2FVSRUdLLQjdssUXXwS6dgUCAuT+jBnA2LGFPoyEBKmhdfky8O+/wLVrks2flgbcuSONiM6fl/tPU6mS1NSvVg3w9pZi8l26AOXLF/arICIiInpMYiKwYgXw+eeScg5IGvmAAUCdOoCJCTByJCcqREREKmCwqyTavVsytu7elbSnwEDgrbeABg3k8fHjgY8/fuJTpKdLoCohAYiPl5JfsbESQ4uKkmtdU7aYGKmramEhWVgRERLUSknJfpnhk5iZAWXKSO3WqlWBNm2Al18GatQArK3z+X4QERERFZTsis4DgJ+fdFysVEm9sREREREABrsKTEQEEBwMXL1quD1zsKdyZekyrSgSOLpyRW7rLlqt/trNTRokpqdLbapLl+S27pKWpr92cgLKlQPSHjxC3Jb9OH9OizT8gFQbB6TWeR5pv5VB6mogxfIcyla5g7IXqiK5kwaPHhlmWmV+zsJoW2BqKgGrGjWkbFilStIQMixMMrUaN2bReCIiIiqmzp4FPvsMWLdOJkw6pqbAK69Ih0UGuoiIiIoFBrsKyL59krWurjIAuuvvJgAIyfy4BQAPICxvz2pjI0GoqCj9NjMzKUNhZSWPNWgAdOsmATp7e+CffwB3d8DDQ4JbFSrI/kRERERGQ1EkY37OHGDXLsPHHByA0aOBt9+WiQ4REREVGwx2FRA7O1l2Fx6e8z4uLjIvAmR54O3bho9rNPrrSpWknrypqZSEOH9e/5hGI2UgNBpAk54Gz/TzqPvoKMyQhsRylXDAohPMrC1gGhMJs7gYmFWpCNNy9rCwALy8pEOhpaVkdO3YIcEqGxt9UMvBQS716km2lUYj2WZRUVL43dpaP9acdOmSjzeRiIiIqDhISgKWLQNmzQJu3JBtGo2k01eoAEyaJNlcFhbqjpOIiIiyxWBXAenWTboHFpmrV4GpU4FVq+SsY9myklr/tq9M0Pq9AmzfLhOziQulZlc2ctuM0cREgm9EREREJVZkpDTx+fFHmU8BcjbwjTeAd9+VQJeNjbpjJCIioqdisMvYRERIUOv77yU1C5D1k19/DVSsKC0P+/cHQkMlBWvVKsDfX9UhExERERVroaHAe+8B+/cbFi51dpa5VKdOqg2NiIiI8s5E7QFQLkVEAB99JAWwFiyQQFfnzsCxYzIJq1ABWLxYKr2Hhkqa/b59DHQRERERZUdRgJ07gWbNgEaNZN6kC3Q1aSIZ8uHhDHQREREZIWZ2FXdXr0rW1vLl+nT6pk2BL78EOnTQ73fokH6pYqdOwE8/sSMQERER0eMSEoClS4ElS4Bz5/TbLS0lO37GDCnESkREREaLwa7iSFEkY2vOHGDtWqkODwA+PsDEiUDPnlkrxL/wgnQEqlFDakqYMGmPiIiIKMP168DYscC2bUB6umwrWxYYPhxo3Rrw82PraCIiohKCwa7iJD4e+N//gEWLgJAQ/fauXYEPPwTatNEHuf7+G5gyBfjhBwlwAcD8+UU/ZiIiIqLibM8eqcd16pR+m0Yj5SHefx+wt1dvbERERFQoGOxSm6IAJ05I159ffgHi4mS7pSXQt69Mzry89PufOyftrjdvlvszZsjXEREREZFQFOC774BPP5W6pzoWFkCfPsDs2WwzTUREVIIx2KWWsDApLL9ihWG9iJo1gTffBIYOBRwdZZtWK92Bli7VL2s0NZW0+2nT1Bg9ERERUfGTnCzzqzlzgDNn9NudnYGAAGDCBJlDERERUYnGYFdRunsX2LRJAlb79+u3W1oCPXoAI0YAHTtmrbfVsaPh/q+8Anz+OVCnThEMmoiIiKiYu3IFePtt4J9/9FnytrZArVrAZ58B3bqpOz4iIiIqUgx2FbarV4GNG4ENG4DgYH1LawBo1w547TWgVy/AwUG6Lf75p7S+Hj9etgFA27ZSw+vVVyUg1qiRCi+EiIiIqJjZv1+Kzmeux1WxomwbOVI/lyIiIqJShcGughYfDxw4AOzaJZeLFw0fb95cMrM6dgTu3JEzkdOmAadPA4cOSfo9ADRuLNlegAS+PvgAsLEp2tdCREREVBz99BPw8cfArVv6bVZWwODBsoTR1la1oREREZH6GOwqKLt2AZMnA6GhhtlbAGBuDpiZAV98AYwbJ9vWrZMC9I9zcwM6dJDaEjrsEkREREQEHDwIDBoE3Lih3+bkJF2rAwKyloIgIiKiUonBroISFydLDbOTmioXCwv9ttq1AW9voEYNoHp1wNMTaN1atms0RTJkIiIiIqNy544+0FWjBjBzppSDICIiIsqEwa6C0qmTtLd2cACqVZNUektLw4ubm37/55+XLDAiIiIiyp1evYBPPgH8/YEGDdQeDRERERVTDHYVlHLlgClT1B4FERERUcllZia1uoiIiIiegIUNiIiIiIiIiIioxGCwi4iIiIiIiIiISox8BbsWLlwIDw8PWFlZwcfHB0eOHHni/uvWrUOdOnVgZWWFBg0aYPv27QaPb9iwAZ07d4ajoyM0Gg1OnDiR5TmSkpLwzjvvwNHREWXKlEGvXr0QERGRn+ETEREREREREVEJledg15o1a/B/9u48Pqbr/+P4axKyCInaEiHW2ilqjaqlqBZVXRRVe0tbFEFttdZSlFLU1oUuWuVLi7ZaVdWF2rVVe+1LLEVCECT398f5JRFJSEhyJ5n38/GYR+7cOTP3M3OTyZnPnPM5ISEhDB8+nK1bt1KxYkUaN27M6dOnE22/bt062rRpQ5cuXdi2bRstWrSgRYsW7NixI7ZNREQEtWvXZvz48Uket0+fPixfvpxFixaxdu1aTpw4wdNPP53S8EVEREREREREJBNzWJZlpeQONWrUoFq1akyfPh2A6OhogoKC6NmzJwMHDkzQvlWrVkRERLBixYrYfTVr1qRSpUrMmjUrXttDhw5RtGhRtm3bRqVKlWL3h4WFkTdvXhYsWMCzzz4LwO7duylTpgzr16+nZs2ad4w7PDwcPz8/wsLC8PX1TclTFhEREbkj9TX0GoiIiEjaSm5fI0Uju65du8aWLVto2LBh3AO4udGwYUPWr1+f6H3Wr18frz1A48aNk2yfmC1btnD9+vV4j1O6dGkKFSqU5ONERkYSHh4e7yIiIiIiIiIiIplblpQ0Pnv2LFFRUfj7+8fb7+/vz+7duxO9T2hoaKLtQ0NDk33c0NBQPDw8yJkzZ7IfZ9y4cYwcOTLBfiW9REREJC3E9DFSOGg+U4l57upviYiISFpIbn8rRcmujGTQoEGEhITEXj9+/Dhly5YlKCjIxqhEREQks7t48SJ+fn52h2GLixcvAqi/JSIiImnqTv2tFCW78uTJg7u7e4JVEE+dOkVAQECi9wkICEhR+6Qe49q1a1y4cCHe6K7bPY6npyeenp6x17Nnz87Ro0fJkSMHDocj2cdOifDwcIKCgjh69KjqVNhI58F+OgfOQefBOeg8OIf0OA+WZXHx4kUCAwPT5PEzgsDAQPW3XITOg3PQebCfzoFz0HlwDs7U30pRssvDw4MqVaqwevVqWrRoAZgC9atXr6ZHjx6J3ic4OJjVq1fTu3fv2H2rVq0iODg42cetUqUKWbNmZfXq1TzzzDMA7NmzhyNHjiT7cdzc3ChYsGCyj3kvfH199QfmBHQe7Kdz4Bx0HpyDzoNzSOvz4KojumKov+V6dB6cg86D/XQOnIPOg3Nwhv5WiqcxhoSE0KFDB6pWrUr16tWZMmUKERERdOrUCYD27dtToEABxo0bB0CvXr2oW7cukyZNomnTpnzxxRds3ryZOXPmxD7muXPnOHLkCCdOnABMIgvMiK6AgAD8/Pzo0qULISEh5MqVC19fX3r27ElwcHCyVmIUERERERERERHXkOJkV6tWrThz5gzDhg0jNDSUSpUqsXLlytgi9EeOHMHNLW6Rx1q1arFgwQLeeOMNBg8eTIkSJfjqq68oX758bJtly5bFJssAWrduDcDw4cMZMWIEAO+88w5ubm4888wzREZG0rhxY9577727etIiIiIiIiIiIpI53VWB+h49eiQ5bfHnn39OsK9ly5a0bNkyycfr2LEjHTt2vO0xvby8mDFjBjNmzEhJqOnK09OT4cOHx6sVJulP58F+OgfOQefBOeg8OAedh8xD59I56Dw4B50H++kcOAedB+fgTOfBYbny+tgiIiIiIiIiIpKpuN25iYiIiIiIiIiISMagZJeIiIiIiIiIiGQaSnaJiIiIiIiIiEimoWSXiIiIiIiIiIhkGkp2pZIZM2ZQpEgRvLy8qFGjBhs3brQ7JJcybtw4qlWrRo4cOciXLx8tWrRgz549dofl8t566y0cDge9e/e2OxSXc/z4cV544QVy586Nt7c3FSpUYPPmzXaH5VKioqIYOnQoRYsWxdvbm+LFi/Pmm2+idWHS1i+//MITTzxBYGAgDoeDr776Kt7tlmUxbNgw8ufPj7e3Nw0bNmTfvn32BCsppv6WvdTfck7qb9lH/S37qb9lj4zQ31KyKxUsXLiQkJAQhg8fztatW6lYsSKNGzfm9OnTdofmMtauXUv37t35448/WLVqFdevX+fRRx8lIiLC7tBc1qZNm5g9ezYPPPCA3aG4nPPnz/PQQw+RNWtWvvvuO3bu3MmkSZO477777A7NpYwfP56ZM2cyffp0du3axfjx45kwYQLTpk2zO7RMLSIigooVKzJjxoxEb58wYQLvvvsus2bNYsOGDfj4+NC4cWOuXr2azpFKSqm/ZT/1t5yP+lv2UX/LOai/ZY8M0d+y5J5Vr17d6t69e+z1qKgoKzAw0Bo3bpyNUbm206dPW4C1du1au0NxSRcvXrRKlChhrVq1yqpbt67Vq1cvu0NyKQMGDLBq165tdxgur2nTplbnzp3j7Xv66aettm3b2hSR6wGspUuXxl6Pjo62AgICrIkTJ8buu3DhguXp6Wl9/vnnNkQoKaH+lvNRf8te6m/ZS/0t56D+lv2ctb+lkV336Nq1a2zZsoWGDRvG7nNzc6Nhw4asX7/exshcW1hYGAC5cuWyORLX1L17d5o2bRrv70LSz7Jly6hatSotW7YkX758VK5cmblz59odlsupVasWq1evZu/evQD8+eef/Pbbbzz++OM2R+a6Dh48SGhoaLz3Jj8/P2rUqKH/2U5O/S3npP6WvdTfspf6W85B/S3n4yz9rSzpdqRM6uzZs0RFReHv7x9vv7+/P7t377YpKtcWHR1N7969eeihhyhfvrzd4bicL774gq1bt7Jp0ya7Q3FZBw4cYObMmYSEhDB48GA2bdrEa6+9hoeHBx06dLA7PJcxcOBAwsPDKV26NO7u7kRFRTFmzBjatm1rd2guKzQ0FCDR/9kxt4lzUn/L+ai/ZS/1t+yn/pZzUH/L+ThLf0vJLsl0unfvzo4dO/jtt9/sDsXlHD16lF69erFq1Sq8vLzsDsdlRUdHU7VqVcaOHQtA5cqV2bFjB7NmzVLnKx19+eWXfPbZZyxYsIBy5cqxfft2evfuTWBgoM6DiGR46m/ZR/0t56D+lnNQf0uSommM9yhPnjy4u7tz6tSpePtPnTpFQECATVG5rh49erBixQrWrFlDwYIF7Q7H5WzZsoXTp0/z4IMPkiVLFrJkycLatWt59913yZIlC1FRUXaH6BLy589P2bJl4+0rU6YMR44csSki19S/f38GDhxI69atqVChAu3ataNPnz6MGzfO7tBcVsz/Zf3PznjU33Iu6m/ZS/0t56D+lnNQf8v5OEt/S8mue+Th4UGVKlVYvXp17L7o6GhWr15NcHCwjZG5Fsuy6NGjB0uXLuWnn36iaNGidofkkho0aMDff//N9u3bYy9Vq1albdu2bN++HXd3d7tDdAkPPfRQgqXg9+7dS+HChW2KyDVdvnwZN7f4/2bd3d2Jjo62KSIpWrQoAQEB8f5nh4eHs2HDBv3PdnLqbzkH9becg/pbzkH9Leeg/pbzcZb+lqYxpoKQkBA6dOhA1apVqV69OlOmTCEiIoJOnTrZHZrL6N69OwsWLODrr78mR44csXOB/fz88Pb2tjk615EjR44EdTt8fHzInTu36nmkoz59+lCrVi3Gjh3Lc889x8aNG5kzZw5z5syxOzSX8sQTTzBmzBgKFSpEuXLl2LZtG5MnT6Zz5852h5apXbp0if3798deP3jwINu3bydXrlwUKlSI3r17M3r0aEqUKEHRokUZOnQogYGBtGjRwr6gJVnU37Kf+lvOQf0t56D+lnNQf8seGaK/lW7rPmZy06ZNswoVKmR5eHhY1atXt/744w+7Q3IpQKKXjz76yO7QXJ6WwrbH8uXLrfLly1uenp5W6dKlrTlz5tgdkssJDw+3evXqZRUqVMjy8vKyihUrZg0ZMsSKjIy0O7RMbc2aNYn+P+jQoYNlWWY57KFDh1r+/v6Wp6en1aBBA2vPnj32Bi3Jpv6WvdTfcl7qb9lD/S37qb9lj4zQ33JYlmWlX2pNREREREREREQk7ahml4iIiIiIiIiIZBpKdomIiIiIiIiISKahZJeIiIiIiIiIiGQaSnaJiIiIiIiIiEimoWSXiIiIiIiIiIhkGkp2iYiIiIiIiIhIpqFkl4iIiIiIiIiIZBpKdomIiIiIiIiISKahZJeIiIiIiIiIiGQaSnaJiIiIiIiIiEimoWSXiIiIiIiIiIhkGkp2idhk3rx5OBwODh06ZMvxHQ4HI0aMSNXHrFevHvXq1UvVx3Q2yX2ORYoUoWPHjmkeT2Z06NAhHA4H8+bNszsUERHJ4NTfypjU30p76m9JZqdkl8hd+vvvv3n22WcpXLgwXl5eFChQgEaNGjFt2rR47caOHctXX31lT5BpYOfOnYwYMcK2TqPcnffee8/lOzPLli3jwQcfxMvLi0KFCjF8+HBu3Lhhd1giInIb6m8dsjsUSQFX728tXLiQF154gRIlSuBwODJ9Ulacm5JdIndh3bp1VK1alT///JOXXnqJ6dOn8+KLL+Lm5sbUqVPjtU2q89WuXTuuXLlC4cKF0ynq1LFz505GjhyZaOfrhx9+4Icffkj/oJzQnj17mDt3rt1hxHL1ztd3331HixYtyJkzJ9OmTaNFixaMHj2anj172h2aiIgkQf0t9bfuRP0t5zJz5ky+/vprgoKCuO++++wOR1xcFrsDEMmIxowZg5+fH5s2bSJnzpzxbjt9+nSyHsPd3R13d/c0iM4+Hh4edofgNDw9Pe0OQW7Sr18/HnjgAX744QeyZDH/+nx9fRk7diy9evWidOnSNkcoIiK3Un8rcepvxVF/y7l88sknFChQADc3N8qXL293OOLiNLJL5C78+++/lCtXLkHHCyBfvnyx2w6Hg4iICObPn4/D4cDhcMTWFUishkSRIkVo1qwZP//8M1WrVsXb25sKFSrw888/A7BkyRIqVKiAl5cXVapUYdu2bfGOnVR9g44dO1KkSJHbPqfDhw/z6quvUqpUKby9vcmdOzctW7aMF9+8efNo2bIlAPXr1499TjHxJXb806dP06VLF/z9/fHy8qJixYrMnz8/XpuYmgFvv/02c+bMoXjx4nh6elKtWjU2bdp027gBzp07R79+/ahQoQLZs2fH19eXxx9/nD///DNeu59//hmHw8GXX37JmDFjKFiwIF5eXjRo0ID9+/cneNyYWLy9valevTq//vrrHWOJcWsNiZjz/fvvvxMSEkLevHnx8fHhqaee4syZMwnu26xZM3744QcqVaqEl5cXZcuWZcmSJfHajRgxAofDkeDYt/5uFSlShH/++Ye1a9fGnrO7GVZer149ypcvz86dO6lfvz7ZsmWjQIECTJgwIUHb5Jx3gAsXLtCxY0f8/PzImTMnHTp04MKFC4kef/fu3Tz77LPkypULLy8vqlatyrJly+4Y986dO9m5cyddu3aNTXQBvPrqq1iWxeLFi5P/IoiISLpRf0v9rTtRf8t5+lsAQUFBuLkpxSDOQSO7RO5C4cKFWb9+PTt27LjttxaffPIJL774ItWrV6dr164AFC9e/LaPvX//fp5//nm6devGCy+8wNtvv80TTzzBrFmzGDx4MK+++ioA48aN47nnnmPPnj2p8k9l06ZNrFu3jtatW1OwYEEOHTrEzJkzqVevHjt37iRbtmzUqVOH1157jXfffZfBgwdTpkwZgNift7py5Qr16tVj//799OjRg6JFi7Jo0SI6duzIhQsX6NWrV7z2CxYs4OLFi3Tr1g2Hw8GECRN4+umnOXDgAFmzZk0y9gMHDvDVV1/RsmVLihYtyqlTp5g9ezZ169Zl586dBAYGxmv/1ltv4ebmRr9+/QgLC2PChAm0bduWDRs2xLb54IMP6NatG7Vq1aJ3794cOHCA5s2bkytXLoKCgu72ZaZnz57cd999DB8+nEOHDjFlyhR69OjBwoUL47Xbt28frVq14uWXX6ZDhw589NFHtGzZkpUrV9KoUaMUHXPKlCn07NmT7NmzM2TIEAD8/f3vKv7z58/z2GOP8fTTT/Pcc8+xePFiBgwYQIUKFXj88ceB5J93y7J48skn+e2333j55ZcpU6YMS5cupUOHDgmO+88///DQQw9RoEABBg4ciI+PD19++SUtWrTgf//7H0899VSSMcd8SKlatWq8/YGBgRQsWDDBhxgREXEO6m+pv3W31N9K//6WiNOxRCTFfvjhB8vd3d1yd3e3goODrddff936/vvvrWvXriVo6+PjY3Xo0CHB/o8++sgCrIMHD8buK1y4sAVY69ati933/fffW4Dl7e1tHT58OHb/7NmzLcBas2ZN7L66detadevWTXCsDh06WIULF463D7CGDx8ee/3y5csJ7rd+/XoLsD7++OPYfYsWLUpw3KSOP2XKFAuwPv3009h9165ds4KDg63s2bNb4eHhlmVZ1sGDBy3Ayp07t3Xu3LnYtl9//bUFWMuXL09wrJtdvXrVioqKirfv4MGDlqenpzVq1KjYfWvWrLEAq0yZMlZkZGTs/qlTp1qA9ffff8fGmC9fPqtSpUrx2s2ZM8cCEn2Nb1W4cOF45z3mfDds2NCKjo6O3d+nTx/L3d3dunDhQrz7Atb//ve/2H1hYWFW/vz5rcqVK8fuGz58uJXY23hiv1vlypVLVty3U7du3QS/D5GRkVZAQID1zDPPxO5L7nn/6quvLMCaMGFCbLsbN25YDz/8sAVYH330Uez+Bg0aWBUqVLCuXr0auy86OtqqVauWVaJEidvGPXHiRAuwjhw5kuC2atWqWTVr1kz+iyAiIulG/S31t+5E/S3n6W/dKjVeC5F7oTGGInehUaNGrF+/nubNm/Pnn38yYcIEGjduTIECBZI9zDcpZcuWJTg4OPZ6jRo1AHjkkUcoVKhQgv0HDhy4p+PF8Pb2jt2+fv06//33H/fffz85c+Zk69atd/WY3377LQEBAbRp0yZ2X9asWXnttde4dOkSa9eujde+VatW8YpZPvzww8Cdn6Onp2fst61RUVH8999/ZM+enVKlSiUae6dOneLVu7j1OJs3b+b06dO8/PLL8drFDP++F127do03FP7hhx8mKiqKw4cPx2sXGBgY79szX19f2rdvz7Zt2wgNDb2nGO5F9uzZeeGFF2Kve3h4UL169XjnKLnn/dtvvyVLliy88sorse3c3d0TFI0/d+4cP/30E8899xwXL17k7NmznD17lv/++4/GjRuzb98+jh8/nmTMV65cARKv6+Hl5RV7u4iIOBf1t5JH/a2E1N9K//6WiLNRskvkLlWrVo0lS5Zw/vx5Nm7cyKBBg7h48SLPPvssO3fuvOvHvbmDBcT+s791KHfM/vPnz9/1sW525coVhg0bRlBQEJ6enuTJk4e8efNy4cIFwsLC7uoxDx8+TIkSJRIM+48Zhn9rh+PW5x7TEbvTc4yOjuadd96hRIkS8WL/66+/Eo39TseJiatEiRLx2mXNmpVixYrdNpY7Se5zvP/++xPUhyhZsiSArcuQFyxYMEFc9913X7z4k3veDx8+TP78+cmePXu8dqVKlYp3ff/+/ViWxdChQ8mbN2+8y/Dhw4HbFyqO+WARGRmZ4LarV6/G++AhIiLORf2tO1N/KyH1t9K/vyXibFSzS+QeeXh4UK1aNapVq0bJkiXp1KkTixYtiv2nkFJJrRiU1H7LsmK3HQ5HvOsxoqKi7njcnj178tFHH9G7d2+Cg4Px8/PD4XDQunVroqOjkxn9vUnOc0zM2LFjGTp0KJ07d+bNN98kV65cuLm50bt370Rjv9vjpIbUPHZixVIheef7btnx2sWcw379+tG4ceNE29x///1J3j9//vwAnDx5MsGHmJMnT1K9evVUilRERNKK+lupR/2tlFF/K87t+lsizkbJLpFUFFMA++TJk7H7kvoHmRbuu+++RIeg3/qNXmIWL15Mhw4dmDRpUuy+q1evJlipJSXPp3Dhwvz1119ER0fH+9Zp9+7dsbenhsWLF1O/fn0++OCDePsvXLhAnjx5Uvx4MXHt27ePRx55JHb/9evXOXjwIBUrVry3gJMh5tu1m1/vvXv3AsSu9BTzLeWFCxfirVSV2PlOz9/D5J73woULs3r1ai5duhTv28Y9e/bEe7yYb3ezZs1Kw4YNUxxPpUqVADNd4ubE1okTJzh27FhsMWMREckY1N+KT/2tu6f+Vpx77W+JOBtNYxS5C2vWrEn0m5Vvv/0WiD8s2MfHJ8mlfVNb8eLF2b17d7yllf/8809+//33O97X3d09wXOaNm1agm+tfHx8AJL1nJo0aUJoaGi8lW9u3LjBtGnTyJ49O3Xr1r3jYyRHYrEvWrTorusKVK1albx58zJr1iyuXbsWu3/evHnpdi5PnDjB0qVLY6+Hh4fz8ccfU6lSJQICAoC4laZ++eWX2HYxS6/fKj1/D5N73ps0acKNGzeYOXNmbLuoqCimTZsW7/Hy5ctHvXr1mD17drwPNjFuXUr8VuXKlaN06dLMmTMn3u/zzJkzcTgcPPvss3f1PEVEJG2pv6X+VlpTfyvOvfa3RJyNRnaJ3IWePXty+fJlnnrqKUqXLs21a9dYt24dCxcupEiRInTq1Cm2bZUqVfjxxx+ZPHkygYGBFC1aNLbYaWrr3LkzkydPpnHjxnTp0oXTp08za9YsypUrR3h4+G3v26xZMz755BP8/PwoW7Ys69ev58cffyR37tzx2lWqVAl3d3fGjx9PWFgYnp6ePPLII+TLly/BY3bt2pXZs2fTsWNHtmzZQpEiRVi8eDG///47U6ZMIUeOHKnyvJs1a8aoUaPo1KkTtWrV4u+//+azzz6763oPWbNmZfTo0XTr1o1HHnmEVq1acfDgQT766KN7riGRXCVLlqRLly5s2rQJf39/PvzwQ06dOsVHH30U2+bRRx+lUKFCdOnShf79++Pu7s6HH35I3rx5OXLkSLzHq1KlCjNnzmT06NHcf//95MuXL/Zb1JhvLlOrNkVyz/sTTzzBQw89xMCBAzl06BBly5ZlyZIlidb9mDFjBrVr16ZChQq89NJLFCtWjFOnTrF+/XqOHTvGn3/+eduYJk6cSPPmzXn00Udp3bo1O3bsYPr06bz44otJLuUuIiL2Un9L/a20pv5WfPfa3/rll19ik4JnzpwhIiKC0aNHA1CnTh3q1KmTKs9dJFnSc+lHkcziu+++szp37myVLl3ayp49u+Xh4WHdf//9Vs+ePa1Tp07Fa7t7926rTp06lre3twXELo+c1FLYTZs2TXA8wOrevXu8fTHLR0+cODHe/k8//dQqVqyY5eHhYVWqVMn6/vvvk7UU9vnz561OnTpZefLksbJnz241btzY2r17d4IlnS3LsubOnWsVK1bMcnd3j7csdmJLcZ86dSr2cT08PKwKFSrEW+L4ds8lsTgTc/XqVatv375W/vz5LW9vb+uhhx6y1q9fnyCemKWwFy1alOjxb43rvffes4oWLWp5enpaVatWtX755Zcklxu/VVJLYW/atCleu5iYbl5aPOb34Pvvv7ceeOABy9PT0ypdunSCuC3LsrZs2WLVqFHD8vDwsAoVKmRNnjw50d+t0NBQq2nTplaOHDkSLOedJ08eq2bNmnd8TnXr1rXKlSuXYH9iv1/JOe+WZVn//fef1a5dO8vX19fy8/Oz2rVrZ23bti3R8/Hvv/9a7du3twICAqysWbNaBQoUsJo1a2YtXrz4jrFblmUtXbrUqlSpkuXp6WkVLFjQeuONNxJdvl5ERJyD+lvqb92J+lvO1d8aPny4BSR6udPvl0hqc1hWOlQIFBGRZCtSpAjly5dnxYoVaX6snTt3Uq5cOVasWEHTpk3T/HgiIiIizkD9LZHMTTW7RERc2Jo1awgODlbHS0RERCSNqL8lkv40sktExMmk5zeNIiIiIq5I/S2RzE0ju0REREREREREJNPQyC4REREREREREck0NLJLREREREREREQyjSx2B5BeoqOjOXHiBDly5MDhcNgdjoiIiGQylmVx8eJFAgMDcXNzze8T1d8SERGRtJTc/pbLJLtOnDhBUFCQ3WGIiIhIJnf06FEKFixodxi2UH9LRERE0sOd+lsuk+zKkSMHYF4QX19fm6MRERGRzCY8PJygoKDYPocrUn9LRERE0lJy+1suk+yKGUrv6+urzpeIiIikGVeevqf+loiIiKSHO/W3XLOghIiIiIiIiIiIZEpKdomIiIiIiIiISKahZJeIiIiIiIiIiGQaSnaJiIiIiIiIiEimoWSXiIiIiIiIiIhkGkp2iYiIpCXLgmvX7I5CRERERMRlZLE7ABERkUzp8GH49FP4+GPYuxdy54YiRaBwYXOpVAnatIGsWe2OVEREREQkU1GyS0REJLVcuQKff24SXGvXxr/tv//MZcuWuH0TJ8L06VC3bvrGKSIiIiKSiSnZJSIikhoOH4Ynn4Q//zTXHQ6oXx/atYPGjeHMGTh0yLQ7cAA++QR27IB69cwIr7ffhsBAO5+BiIiIiEimoGSXOKf9+83oh0OH4OBBczl6FIoWhRYtoHlz8Pe3O0oREeOXX+CZZ+DsWcibF/r0gbZtoVChuDb588MDD8Rdf+MNc5k924wGW74cRo+G114ziTIREREREbkrDsuyLLuDSA/h4eH4+fkRFhaGr6+v3eFIUvbsgeHDYeHC27dzOOChh0ziq0MHyJMnXcITEUlgzhzo3h1u3IDKleGrr+Inue5kyxZz/w0bzPVBg2DMGCW8MiD1NfQaiIiISNpKbl9DI7vEORw6BCNHmjo30dFmX82acP/9ZjRX0aJQoABs3gxLl5qfv/1mLpMmwZdfQu3atj4FEXEx169D797w3nvmeqtW8OGHkC1byh6nShVYtw4mT4b+/WHcOFO0fuTIVA9ZRERERMQVKNkl9rp2DQYONAWar183+5o3hzffjD/dJ8ajj8LgwWZK49dfw4wZsHu3qXkzcaL54KnRECKS1iwLOnc2qy06HGb64aBBd//+4+YG/fpBlixmCuSoUeDuDsOGpW7cIiIiIiIuwM3uAMSFnTkDDRvCO++YRFejRmYaz9dfJ57oullQEPToAZs2mcLOUVEQEgLPPQfh4ekTv4i4rrfeMokud3f43/9MEj41Eu29e5vEPZgp3WPH3vtjioiIiIi4GFuSXb/88gtPPPEEgYGBOBwOvvrqqzve5+eff+bBBx/E09OT+++/n3nz5qV5nJKGduyA6tXh11/B1xeWLYMffjD7UiJ7dvjsMzMyLGtWWLwYqlUztb9ERNLCkiUmuQXmveepp1L38fv1M1MZAYYMMas0ioiIiIhIstmS7IqIiKBixYrMmDEjWe0PHjxI06ZNqV+/Ptu3b6d37968+OKLfP/992kcqaSJ5cshONjU6SpeHP74A5544u4fz+EwxZ1/+QUKFoS9e+Gxx8zIMRGR1LRtG7RrZ7Z79oSXX06b4wwcaKZzg6njpf93IiIiIiLJZvtqjA6Hg6VLl9KiRYsk2wwYMIBvvvmGHTt2xO5r3bo1Fy5cYOXKlck6jlYHchLvvAN9+5p6N/Xrw6JFkDu3uc2yTA2vy5dNgWdPz5Q//unTUKsW/PuvKVj/44939zgiIrc6edKMPj12zNQP/OYbU2PrVteumanVlmUW3IiOBg8P8PJK+TFffRVmzoS8eWH7dggMvOenIWlHfQ29BiIiIpK2ktvXyBA1u9avX0/Dhg3j7WvcuDHr169P8j6RkZGEh4fHu4jNpk41dbUsC9q2NfW1+veHMmUgRw7zodHLC3LlgtWr4+63eTN07Wrq2KxfH7daY2Ly5YMVK8DPz6zU+PLL5ngiIvfiyhVo0cIkukqXhoULzXvWhQvx29WqZRLs2bKBj495b/PzA29vs7rs1atxba9du/NxJ0+GihXNSNUXXjBJNBERERERua0MkewKDQ3F398/3j5/f3/Cw8O5cuVKovcZN24cfn5+sZegoKD0CFWS8v77pvAywIgRUKcOvPIKfPSRWU3x0qX4SazLl+O2N2yAuXPh9dfNB8nChc1j/f574omv0qXhyy/N6mbz5sGkSWn3vETENbz+OmzcaJLxn31mkl01a0KpUvET6nnyJP0YN27EH93Vtq15T5s5E/77L/H7eHmZY/n4wJo1MGZM6jwfEREREZFMLEMku+7GoEGDCAsLi70cPXrU7pBc07lz0L49vPSSud6vHwwbZqYY1q9vijwvXw779sGJE2aUxLVr8OyzcY9Rvbq5zzPPmFESx46ZUWK1a0OhQibpdatHH4UpU8z266+b0V4iInfjp59MIXqAChVMgurll00i/uxZM306xrRp5np4uEniX75sRnOdOmVWmo1x+TJ8+60Zrfrqq5A/vxk5tmxZwtGopUqZhBjAyJGwdm2aPl0RERERkYwukWIjzicgIIBTp07F23fq1Cl8fX3x9vZO9D6enp54qlaTff77D4YPhzlz4Pp1s69AAZgwwRSUL1vWfIBMjmrVzAXMh8YffjC1vpYtM49dqVLi9+vRA/75B2bPhjZtTCH8cuXu+amJiAsJDzcjsGLEJJrKl4dOncxtN488Llw48cfJl89cYmTLBvv3wxdfwCefmML3X39tLjVqmBUYa9eOa9+unXnPnDcPnn/e1O/Kmze1nqWIiIiISKaSIUZ2BQcHs/rmGk7AqlWrCA4OtikiSVJUlBmBULIkzJgRl+iqUcMknhyOe3t8Ly9o3tx8ODx92qzA6ONjbouOhsaNTY2bq1fNsaZNg0ceMSMsOnQw04hERJKrXz8IDTXbPj5m5dfNm+Gvv0wNwlum2KdI/vzQpw9s3Qo7dphj+fiYEWO//pqw/fTpZpr2iRPQubPqEYqIiIiIJMGWZNelS5fYvn0727dvB+DgwYNs376dI0eOAGYKYvv27WPbv/zyyxw4cIDXX3+d3bt389577/Hll1/Sp08fO8KX22nf3kzJOXfO1MwCMzXnt99MkebU5OlppvfEWLHCjPrq2xeqVIEtWyBrVlNfJ2dOc33q1NSNQUQyn0uXTH2slStNvUAwSa59+0zCqUqVe0/c36pcObMIx/79ZuGOXr3ibjtyxMTk42PqEXp4mPe7hQtTNwbJkGbMmEGRIkXw8vKiRo0abNy48bbtFy1aROnSpfHy8qJChQp8++23SbZ9+eWXcTgcTIkpCyAiIiKSQdiS7Nq8eTOVK1emcuXKAISEhFC5cmWGDRsGwMmTJ2MTXwBFixblm2++YdWqVVSsWJFJkybx/vvv07hxYzvCl9t56SWTWMqd24y0qlPHTNPJkg4zZh9/3BTC9/eHnTtN8eg33zQFo2OK1A8dCgcOpH0sIpIxbd9ukllPPgkdO5p9vXqZJFf+/Gl//IAAM907WzZzPTLSxPLgg2ZEWYUKMGRIXFznz6d9TOK0Fi5cSEhICMOHD2fr1q1UrFiRxo0bc/rmOnI3WbduHW3atKFLly5s27aNFi1a0KJFC3bs2JGg7dKlS/njjz8IDAxM66chIiIikuocluUa8yDCw8Px8/MjLCwMX19fu8PJPPbuhV27zIcxMB/M6tUz9bGKFzfTcXLnTt+Yzp41Kz0uXmyuV68O8+ebkRk//QQNG5oRYKk9MkNEMi7LMtOe+/c3i2Rky2aKyJcsaeppxSSf0tuePeY969gx86XBmDHQs6dJyO3aZb5gmDPHntgkgfTua9SoUYNq1aox/f8XUIiOjiYoKIiePXsycODABO1btWpFREQEK25atKVmzZpUqlSJWbNmxe47fvw4NWrU4Pvvv6dp06b07t2b3jErKt+B+lsiIiKSlpLb18gQNbvESS1aBFWrmuLvf/9tPix262YSXX5+ZpXF9E50gRnJ9eWXcdMXN2409bpmzTI1v3780SS/RETAJMiffNKMlLp2zSTIL182U7Hnz7cv0QVmqvaff5oVam/cgAEDoFkzk/QCM80ysfpekuldu3aNLVu20LBhw9h9bm5uNGzYkPXr1yd6n/Xr18drD9C4ceN47aOjo2nXrh39+/enXDIWdYmMjCQ8PDzeRURERMRuSnZJyl27ZkYWPPccXLxoVkrMndtMvZk/H9zdTbKpTBn7YnQ4zIplf/8NTZuaFRlLlICRI83tISFwywqfIuKCtm83K7ouX25qYU2aZBa/APM+UbOmndEZuXKZ99T33zeJt59+MqNXW7Qwt3ftakbViks5e/YsUVFR+N+ySIK/vz+hMYsq3CI0NPSO7cePH0+WLFl47bXXkhXHuHHj8PPzi70EBQWl8JmIiIiIpD4luyRlLl40tbH+f8oEAwfC6tWwaRMMGmT2TZ0Kjz5qX4w3K1jQFHKuVMlcDwmB++83dW5uLgAtIq5pxgw4ftxMV9ywAcLD4dAhKFAAhg+3O7o4Dgd06WJWbqxQwSTrT5yAfPlg924YP97uCCUT2LJlC1OnTmXevHk4kjnVf9CgQYSFhcVejh49msZRioiIiNyZkl2SfGfOwCOPmFEFOXKYkRDjxpkVyl54wUxjfPVVUxvLWf3yCxw8aLYXLoTbrEIlIi5g+nR4/XWT6MqRA956y+x/5x3Int3e2BJTqpSZttiuHSxZAu++a/aPGWPqe4nLyJMnD+7u7py6ZZTyqVOnCAgISPQ+AQEBt23/66+/cvr0aQoVKkSWLFnIkiULhw8fpm/fvhQpUiTRx/T09MTX1zfeRURERMRuSnZJ8s2ebVYDy5MH1qwxdWPCwsxUmkuXoG5dcPblyS0r/gfYXr1MHRwRcR3ffmtWiwXw9DSjovz84LXXzHTAhg1NjSxn5ecHH39sRp8995wZbXvtGrz8snmPE5fg4eFBlSpVWL16dey+6OhoVq9eTXBwcKL3CQ4OjtceYNWqVbHt27Vrx19//cX27dtjL4GBgfTv35/vv/8+7Z6MiIiISCpTskuSb/Bg6N3bjCqoUsV8WGzf3qzIWLCgqSmTNavdUd5egwawbh0UKmSu798Pb79tb0wikj4syxR4b9oU+vaNnxhatswkwbJmNaO9MspqrQ4HNGlitn/+2Yz2EpcREhLC3LlzmT9/Prt27eKVV14hIiKCTp06AdC+fXsGxZQYAHr16sXKlSuZNGkSu3fvZsSIEWzevJkePXoAkDt3bsqXLx/vkjVrVgICAihVqpQtz1FERETkbijZJbd36BBERZltNzcztad0aXN9zBjzAdHDA/73P1M7JiMoW9asGJk3r7n+xhum5o2IZG6DB5uFNCD++9Xly3E1/Pr1M1MFM5Kbv2To3Nk8H3EJrVq14u2332bYsGFUqlSJ7du3s3Llytgi9EeOHOHkyZOx7WvVqsWCBQuYM2cOFStWZPHixXz11VeUL1/erqcgIiIikiYcluUacx7Cw8Px8/MjLCxM9SSSa98+qF0b6tc3U2Y8POJu+/ZbM43RsswKYV262Bfn3TpwwHyovXED7rvP1LuJSYCJSOYybpxJdgG8955ZzTDGG2+Y5H1QEOzaBT4+9sR4L2bONDUTAerVM1PNJd2pr6HXQERERNJWcvsaGtkliTt+HBo1gtOnTRLo6tW42/bvh+efN4mul1/OmIkugGLF4mqMXbwI16/bGo6IpJHp0+MSXRMnxk907d9v9oF5P8iIiS4wz6ljR7P9889xq+OKiIiIiLggJbskof/+g0cfhcOH4f77YeVKiMmYRkTA00+bwvTBwTB1qr2x3qtXXoFKlczortGj7Y5GRFLbvHnQs6fZHjbMTFO8Wf/+prj7o4/CU0+le3ip6sMPoXBhs/3WWxn//VlERERE5C4p2SXxXbpkijfv3GlW+lq1Cv6/9geWBV27wt9/m32LFsWf2pgRxdQhA5gzxzzvKVPij2QTkYzLywuyZIE+fWDEiPi3/fQTfPUVuLvD5MkZpyh9UhwOUz8xxvr19sUiIiIiImIjJbskTmSkGbW1YQPkygU//ABFisTdPn06LFhgPhh++aVJhmUG9eqZ+mNRUdC4sflQ3KmTWW1SRDK21q1h40aYNCl+Misqyvytg5mOXa6cPfGltipVzPsXmCmaeh8TERERERekZJfE2bgR1q41NWu+/dasWhjjt98gJMRsT5wIderYE2NaGT/ejPI6dswk8774AoYPtzsqEbkbR47AmTNx1ytXTjhq68MP4a+/IGfOhCO+MrqxYyFHDtiyBebPN9O0b1qRT0REREQks1OyS+I8/LBJdi1dCjVqxO0/eRJatjQfmFq1gt69bQsxzZQtGzcaolQp83P0aPNBUUQyjkuXzEjNatXMtOTEhIXBkCFme/hwyJMn/eJLDwEBMHSo2R40yNQjq18fzp+3Ny4RERERkXSiZJeYWlwxatY0qzDGuH7dJLhCQ800n/ffz/h1bZLyxhumts/OndCundn30ktmZTMRcX7R0fDCC6au4NWrZnRTYsaONSO/SpaEV19N3xjTy2uvmRVnT50yI7z27IHnntOqsyIiIiLiEpTscnUHDkDVqrB9e+K39+sHv/5qVmNcsgSyZ0/X8NJVkSJxo7uOHTNJvuvXTR2zf/+1NTQRSYYhQ+Drr8HT0/wMCkrY5t9/zSIUYOp4ZfRFNpLi6WmmZ4Opx5gtG/z4I/TqFf8LDhERERGRTEjJLld28SI0bw5bt5p6XLd+APr4Y3j33bjtkiXTP8b0NmQIZM0Ka9ZAly5mpFtkJOzaZXdkInI7n34Kb71ltj/4IP5U7Ju9/jpcu2ZGsDZtmn7x2eGZZ+Chh8x7WI0aZlTuzJkwa5bdkYmIiIiIpCklu1xVdDR06AD//AP585sPijdPT9yyBbp1M9vDhsGTT9oTZ3orXBg6dzbbY8fCokWmcH+zZvbGJSJJ++svM+UYTI2qtm0Tb7d2rRmh6uYGkydn3inZMRwO8zzBJPB79DDbvXub93gRERERkUxKyS5XNWmSKUTv4WE+/AUGxt12+jQ89ZSpedOsmeutSjh4sBnd9fPPsH+/qVUWIyrKtrBEJAn9+5v3q8ceMwtLJCY6Om5F2ZdegvLl0y8+O1WvDs8/b7b/+st8cXHtmvmyIzra3thERERERNKIkl2uaMMGk9ABmDbNTNWLcf26KWJ89KiZtvjpp2YUhCspVAhefNFsjxgRt/+336B0aVP8WkScx+efm7/Zjz9O+v3q00/NlO0cOWDUqPSNz27jxoGXlxnZ1rIlNG4MCxa43nu7iIiIiLgM9XRdzYUL0Lo13LhhkloxU39i9OtnPhBlzw5ffQV+fnZEab/Bg82ot7VrzfQfMMWe9++HZ5819c5ExDnkygVz50LevInfHhERl+AfMgTy5Uu/2JxBoULQp4/ZHjkSli2DBx6wNyYRERERkTSkZJeruXHDjE4qWhTmzIlfs2bevLiC9J98AmXK2BKiUyhYMC4ROHy4Kd7/0Udm/969pni9VjQTsc8//5hC9Mn5O5w0CY4fNyuu9uqV5qE5pYEDTZJv3z5TpD7GH3+ofpeIiIiIZDpKdrmaPHngm2/g11/jj9r67Tfo2tVsDx0KLVrYEp5TGTTIjO769VczuitPHvjyS8iSxRSu/+gjuyMUcU0REWY63osvxhVgT8qJE2ZUJpifXl5pH58z8vWFN9802yNHwrlzsGIFPPywGa16/ry98YmIiIiIpCIlu1xFeHjctpsbFCgQd/3QIVOQ/vp1s1T9zXWqXFmBAnGju2KKXgcHx2336gUHDtgTm4gre+012LXLrCTbrt3t277xBly+bP52W7ZMn/icVefOpjD/+fMm8VW7NgQFmf8Br75qd3QiIiIiIqlGyS5XcOWK+aDXpYsZEXGzixfhiSfg7FmoXBnmz1fR4pu9/rpZmXHNGvj9d7OvXz8zGuLSJfNB+8YNe2MUcSVffw0ffmimYC9YcPv6W9u2menZYEaA3Txt2xVlyRI3Em76dLPy7hdfgLu7+fnFF/bGJyIiIiKSSpTVcAWDB8POnfDtt/GTXVFRZkn6HTsgIMAULfbxsS9OZ1SoEHToYLZjRnS5u5tV33LkMCNLrlyxLz4RV3LmTNx06/79oV69pNtaFvTta362aRN/1VlX1qgRNGlikvT9+0P16qZoP5jRXSdO2BufiIiIiEgqULIrs/vlF5g61Wx/8EH8URCDBpmaLZ6eZuXFggVtCdHpDRxoElwrV8LmzWZfkSKwfbup3ZUjh53RibgGy4KXXzajkcqXh1Gjbt9+2TIzItPTE8aNS58YM4q33zbvacuWwU8/mameVaqY6Y2dO2vxDRERERHJ8JTsyswuXYJOncwHly5dzLf5MebOhYkTzfZHH0GNGvbEmBEUL25GwEHc6C6AYsXipkVZlqYziqSlbdtg6VIzFe/jj00SKynXrpnpxmBGdxUunD4xZhRlysArr5jtkBAzdf2TT8xr+v335ssPEREREZEMTMmuzGzAAFNAvVCh+CuWffNN3AedoUPNFB+5vcGDTWLr66/hr7/i33buHLRqBX362BObiCt48EEzUmvaNFNf8HamT4f9+8307IED0ye+jGb4cLMi759/mlqNZcqY/xPvvgtPPml3dCIiIiIi98RhWa4xXyE8PBw/Pz/CwsLw9fW1O5y0t3o1NGxotn/8ERo0MNubN0PdumZ1sg4dzKguVy/anFytWsGXX5qfNxdyXrUKHn3UbP/8s3l9RcQeZ85AiRIQFmYK2XfqZHdEzmvyZDPyLSAA9u7VlOxU4HJ9jUToNRAREZG0lNy+hkZ2ZVbXr5v6XK++GpfoOnAAmjY1ia5GjcxURiW6ki+miPOXX8Lu3XH7GzWKK5r94osqWC+Smr7+2ozSSq7hw02iq3LluMUlJHE9esD990NoaMK6ZhERJnkvIiIiIpIBKdmVWT32GPzzD4wfb67/9x88/rgp7lypEixeDFmz2hpihvPAA2Z6j2Ul/GA4YQIEBpoP5SNH2hOfSGZz9Ci88AJUrJhw+nBiduyA2bPN9jvvmFpUkjQPD1OsHmDSpLik4vHjUKGCqfN44IB98YmIiIiI3CV9Eshsbp6VmicPZM9uRnI1b26mqRQqZGp2aWrB3XnjDfPzs8/g33/j9vv5waxZZvvtt2HLlvSPTSQzsSzo3t0stFGpklmB8U7tQ0IgOhqeeUbTiZOreXMzDfvaNfP6gUncFy1qRql266bVGUVEREQkw1GyKzO5cgVq14YFC+I+nERGwtNPw7p1kDMnfPed+SAjd6dqVTNqLioK3nor/m1PPAGtW5vbunQxU0lF5O4sXgzLl5sRqHPn3nmU1rffmvp5Hh5mpKUkj8MBU6eaVS6XLzf/IxwOM0LOy8vUfJw/3+4oRURERERSRMmuzOTNN01S6/XXzWiuGzfg+efNUvLZspkRXWXL2h1lxjd0qPk5fz4cPhz/tqlTIXduOHtW039E7tb589Czp9kePPjO71s3j0rq0weKFUvb+DKb0qWhVy+z3bu3eT3vvz9uSnZICJw6ZVt4IiIiIiIpZVuya8aMGRQpUgQvLy9q1KjBxo0bk2w7b948HA5HvIuXl1c6RpsB/P03TJxotmfMAG9v6NwZliwxIx2+/hpq1bI3xsyiVi145BEzciumJlqMfPlgxQpTL61UKXviE8no+vc3yZUyZWDQoDu3nzrVTNP29zfJMUm5YcPM67d3r3k9wSS5Klc2yceYZJiIiIiISAZgS7Jr4cKFhISEMHz4cLZu3UrFihVp3Lgxp0+fTvI+vr6+nDx5MvZy+NYRNa4sKgpeesmM5Hr6aVODpWdP+OQTcHc3qwc2bGh3lJlLzOiuDz4wxZxvVrOmqeElIin322/m7wpgzhzw9Lx9+xMnYNQosz1+vOoR3i1f37jk/ahR5nXNkgXef9/8H1m40ExzFKeTki8PARYtWkTp0qXx8vKiQoUKfPvtt7G3Xb9+nQEDBlChQgV8fHwIDAykffv2nDhxIq2fhoiIiEiqsiXZNXnyZF566SU6depE2bJlmTVrFtmyZePDDz9M8j4Oh4OAgIDYi7+//22PERkZSXh4eLxLpjVrFmzYADlymG/kBw2C994zdVc+/tisICipq25dePhhM90nZkTdraKjYd48+OKLdA1NJEOrVg2GDzcjiWrXvnP7gQNNEfuaNaFdu7SPLzNr1w5q1DCv58CBZt+DD0Lfvub/yIMP2hufJJDSLw/XrVtHmzZt6NKlC9u2baNFixa0aNGCHTt2AHD58mW2bt3K0KFD2bp1K0uWLGHPnj00b948PZ+WiIiIyD1zWFb6LrN07do1smXLxuLFi2nRokXs/g4dOnDhwgW+/vrrBPeZN28eL774IgUKFCA6OpoHH3yQsWPHUq5cuSSPM2LECEbG1Bu5SVhYGL6Z6Zv/48fNVJ+LF2H6dDhyJK448+zZ0LWrvfFlZqtWmVXMvLzg0CEzBehmn35qPjzmzg179pifIpJ61q2Dhx4yif2NG80CEnJvNm0yCS/LMqPsHnrIjB52czOvs9xWeHg4fn5+6dbXqFGjBtWqVWP69OkAREdHExQURM+ePRkYk7C8SatWrYiIiGDFihWx+2rWrEmlSpWYFbOi8C02bdpE9erVOXz4MIUKFbpjTOn9GoiIiIhrSW5fI91Hdp09e5aoqKgEI7P8/f0JDQ1N9D6lSpXiww8/5Ouvv+bTTz8lOjqaWrVqcezYsSSPM2jQIMLCwmIvR48eTdXn4TSWLzeJrpo1Yd++uETX1KlKdKW1hg3Nh8KrV2HSpIS3t2oF5cvDf/8lr+6QiCv77z8zFTu5oqKgRw+z3aWLEl2ppVo1U+8R4OWXTW1Cd/f4ia6rV+2JTeK5du0aW7ZsoeFNZQrc3Nxo2LAh69evT/Q+69evj9ceoHHjxkm2B/MlocPhIGfOnIne7lIj6UVERCTDyBCrMQYHB9O+fXsqVapE3bp1WbJkCXnz5mX27NlJ3sfT0xNfX994l0zp5Zfhp5+gSJG4osLvvQevvWZrWC7B4Yir3fXee2YFxptlzQozZ5rtuXPhjz/SNz6RjMKyzMqx1arBX38l7z7vvw/btpn6eGPGpG18rmb8eMiTB3bsgLffjtt/+jS88AI0amTOmdjqbr48DA0NTVH7q1evMmDAANq0aZNkP2rcuHH4+fnFXoKCgu7i2YiIiIikrnRPduXJkwd3d3dO3bKM+alTpwgICEjWY2TNmpXKlSuzf//+tAgxY4mOhgULTF0oh8N8AHzlFbujch1Nmpg6NhERMGVKwttr14ZOncz2K6+kbOSKiKtYsgR++AF27oRs2e7c/tw5GDLEbI8aZVZBldSTOzdMnmy2R42Cf/8125GRsHSpmd748cf2xSfp4vr16zz33HNYlsXMmC9uEuEyI+lFREQkQ0n3ZJeHhwdVqlRh9erVsfuio6NZvXo1wcHByXqMqKgo/v77b/Lnz59WYTq/JUvMtMVOnUyCy80N5s8303kk/Tgc8MYbZnvaNPMh/Fbjx8N998H27WYEmIjEiYiA3r3N9oABcP/9d77P0KFm2mO5cvDqq2kanst64QV45BEzZfHVV81IrqAgGDbM3N6/P1y4YGuIru5uvjwMCAhIVvuYRNfhw4dZtWrVbUfHu8xIehEREclQbJnGGBISwty5c5k/fz67du3ilVdeISIigk7/PwKmffv2DLqpxtGoUaP44YcfOHDgAFu3buWFF17g8OHDvPjii3aEb78jR8wHkdKlzbfr7u7w2WdaicwuTz4JDzwA4eHwzjsJb8+bF956y2wPG2baiYgxejQcO2amYidSUDuBzZvjpgdPmwZZsqRpeC7L4TAr/Xp6mlF3MavK9uljFkU5cyYu0S+2uJsvD4ODg+O1B1i1alW89jGJrn379vHjjz+SW4uriIiISAZkS7KrVatWvP322wwbNoxKlSqxfft2Vq5cGVtH4siRI5w8eTK2/fnz53nppZcoU6YMTZo0ITw8nHXr1lG2bFk7wrdf9+5w5YqZwujlBV99Ba1b2x2V63JzgxEjzPaUKWbEya1efNEUff7uO9C33iLG7t1xizu8++6dpzBGRUG3bmaUUdu2UL9+2sfoykqUiEto9e4N58+DhwfMmGH2zZwJW7faFp6k/MvDXr16sXLlSiZNmsTu3bsZMWIEmzdvpsf/L/Zw/fp1nn32WTZv3sxnn31GVFQUoaGhhIaGcu3aNVueo4iIiMjdcFiWa1SZzTRLYc+fDx07mm0/P1i50qzEKPayLFO7a/t2s/Li2LF2RyTi3CwLHn0UfvwRmjUzK8veybRpZvENPz/YswduKbQtaSAyEipXhl274KWXYM4cs//55+Hzz82KtOvWmaS/2NLXmD59OhMnTiQ0NJRKlSrx7rvvUqNGDQDq1atHkSJFmDdvXmz7RYsW8cYbb3Do0CFKlCjBhAkTaNKkCQCHDh2iaNGiiR5nzZo11KtX747xZJr+loiIiDil5PY1lOzKSNavh4cfNqMbcuSATZugVCm7o5IYy5aZKY0+PnDwoJm+mJQjR6BAATMFVcQVXbgATZvCli2mMH2xYrdvf+KEmbp98aIZUfTyy+kSpgC//AJ165rtNWugXr248+HjYwrWFy9ua4jOIlP0Ne6RXgMRERFJS8nta+ir2Iziiy+gTh2T6MqSxdStUaLLuTzxBFSpYgpuv/120u0mTjTn7oMP0i82EWeTMyf8+its2HDnRBdASIhJdNWoAV27pnl4cpM6dcyoLjCLoly8CIGBsGIF7N2rRJeIiIiIOB0lu5xdVJSZFtemDdy4YfZNnw4lS9oblyTkcMTV7po+HU6fTrydh4dZ4WzIEFMDR8RVublBxYp3bvf997BwoWk/a5amzNnh7behcGE4dAj69TP76tQxo4xFRERERJyMPjE4s7AwaN48biW/4GAzfSTmG3ZxPk2bQrVqcPkyTJiQeJtXX4WyZeHsWRg5Mn3jE7HbsWMweLAZHZQcV66YRTnA1OuqVCnNQpPb8PWFjz4y23PmmHqRMSwLFiyA/fvtiU1ERERE5BZKdjmrPXvMdJ1vvzUrLn72mSkCvHq1RjU4M4cjLoH13nsQGpqwTdasZtVGMCPAdu5Mt/BEbDdwIIwbBx06JK/92LHw77+mxt2oUWkbm9xe/frQq5fZ7tIlbmTq66+b1TFjRnyJiIiIiNhMWRNn9MknpvbTnj3mA94vv5iVr0CJrozgscdMovLKFRg/PvE2jRqZYvZRUdC7txkZIZLZrV9vEvcOB7zxxp3b//VX3MjWqVM1Zc4ZjB1rptGfOGFG2gF07mwW2/j6a7O6poiIiIiIzZQ5cSaXLkHHjtC+vSlyXq8eDBtmpvCsX293dJJcDkfcCJSZM+Ho0cTbTZpk6netWgXLl6dffCJ2iI6OGxXUuTM8+ODt29+4YdrduAFPPQVPP532McqdZcsG8+ebL14+/RSWLIEyZaBHD3N7795x9SVFRERERGyiZJez+PNPqFo17kPEyJEmATJmDGzaZBIiknE0amSKN0dGJl2Xq3hx6NvXTFM9ciR94xNJb598Yt7LcuQw72t3MnkybNliVm2cMcMkkcU51KxppqMCdOsGJ0/C8OGQOzf88w/Mnm1vfCIiIiLi8pTsslt0tKnfVKNG3LTFn34yI7qmTDFJkKAg1ULJaByOuOlXH30Eu3Yl3m7QINi7N25UhEhmdPGi+V0HGDoU/P1v337vXpM8AZP0yp8/beOTlBs2zKykefasmWafIweMHm1uGzoUzp2zNz4RERERcWlKdtlp3z6oWxf69DEjgJo1g+3bzb4TJ0wRZzB1n7JlszVUuQvBwaYuV3R00vWJcuQwyUyRzGziRDP6p3jxuDpPSYmOhhdfhKtX4dFHzdRucT6enrBwIWTPDj//bEawvvQSlC9vCtfHJL5ERERERGygZJcdoqLgnXfggQfgt9/Mh4WZM2HZMsiTx7QZPBguXzYJk9at7Y1X7t7YsWZa6pIlsGHD7duuW2dWZxTJbF56ydQifPttkyS5nVmz4NdfwcfHTIfT9EXnVaoUzJ1rtseMMcXp334bKleG5s3tjU1EREREXJrDslxjGbjw8HD8/PwICwvD19fXvkB27TIf/H7/3Vxv0ADefx+KFIlrs3Wrqd9lWSZBUr26LaFKKunc2UxlrFfPTFFN7MP7n39CpUqQJYupeVOyZHpHKWK/w4fNyKBLl+Ddd6FnT7sjkuR45RWTpMyTB7Ztg8BAl1052Gn6GjbSayAiIiJpKbl9Ddfsjdrh4kXo39+M5vr9dzOaa/ZsU3j+5kQXwAcfmETX888r0ZUZjBhhRrP8/DP88EPibSpWhCZNzCpmAwakZ3Qiaefq1eS3jZm+eOkSPPSQWYVWMoZ33jGjuc6ehTZtzLmM4Rrfp4mIiIiIk1GyK61ZFnz+OZQubaZ33LgBTzwBO3ZA166Jj/KZNs2sXJacFcvE+RUqFPfBfeDA+B8EbzZxIri7w1dfmcSYSEZmWSaB++yzcPTondtPn26mwXl7m4S/i44MypC8vGDRIvD1NVPzhwyBiAhTx6tBg6Tf80RERERE0og+TaSlvXvhkUfMCK0TJ6BYMVixwtTmKlw46fu5ucELLyQc8SUZ16BB5oPg9u3w5ZeJtylbFrp1M9t9++oDomRsy5fDmjXmPe9Oo3t27Yob0ThxoqkFJRlL8eLw4Ydme8IEmD/ffMGzZg188YW9sYmIiIiIy1GyKy1ERcHkyWZq2s8/m2+9R40ytZiaNk36fps3m2/DJfPJk8dMYwWz+EBS07tGjDBJsa1bzeg+kYzo+vW43/c+fczoxqRcu2aS+1evQuPG8Oqr6ROjpL5nnoHXXzfbffrELa4yaBBcuWJfXCIiIiLicpTsSm1790KdOmZkztWr0KiRGbUwdKhJeiUlPNwkwkqUgJ070y9eST99+pjCzQcPwtSpibfJm9dMAQJ44w19QJSMac4c816YN69JdNzOm2+a5O5995mRQVp9MWMbNw6eftokMZcsAX9/OHIk6fc8EREREZE0oGRXaomKMkV6K1aEdesgRw7zge/775M3HXHCBDh92hSuv//+NA9XbODjA2+9ZbZHj4bQ0MTbvfaaKdD95pvg4ZF+8YmkhrAwM0IR4kYqJuWPP2DsWLM9a5ZJBkvG5uZmRqVWqwbnzsUlL8eOhTNn7I1NRERERFyGkl2pZfhwCAmJG821Ywe89FLyRikcO2amPQKMH68ER2bWtq1ZYfPSJTNyKzFeXqbIc8eOpmC9SEby1ltmVb7Spc17YFIiIqBdO1Ob7vnn4bnn0i9GSVvZspnalIUKmaR+9uxmReLRo+2OTERERERchJJdqaVHDzOCK2Y01+1q1Nxq6FAzXe3hh6FFi7SKUJyBmxtMmWK2P/wQtm27831UqF4yiuvXYfFisz1+PGTNmnTbXr1g/34oWNCsxCiZS0CAWZwgRw6T3AezyuaFC7aGJSIiIiKuQcmu1BIQYGrUJHc0V4y//jKrVoFZuUr1ajK/4GAzksWyzAf+pFaqsyzzu1GyJPz7b/rGKHI3smaFP/80idwnnki63YIFJvHhcJjf8fvuS78YJf1UqGBWn40ZofrEE7ef1ioiIiIikkqU7EpNtxvFkJSBA01S47nnzPQ2cQ1vvQXe3vDrr/C//yXexuGAzz83ia6YovUizi5bNujUKenE/b590K2b2X7jDXjkkfSLTdLfY4/Bxx+bUa1ffAHduyed4BcRERERSSVKdtkpMtJM8ciaFcaMsTsaSU9BQfD662a7f39T6y0xEyaYpMHChbBxY/rFJ5JSq1bdecptZCS0amWmtdWpA8OGpU9sYq/nnzcj+BwOsxDB889reraIiIiIpCklu+zk6WmSGP/+qxUYXVH//lCgABw6BJMmJd7mgQegQ4e49hoRIc5ozRp49FGoWRNu3Ei6Xf/+pk5d7txmKmOWLOkXo9jrhRfM9FYwI7yefFLvZyIiIiKSZpTscgZBQXZHIHbw8TEjt8CM7Dt4MPF2o0aZFRp/+QWWL0+/+ESSIzo6bpRi9epJJ7CWLoVp08z2/Pkm0SuupWNHePxxs71ihZnSGBVla0giIiIikjkp2WWHa9cgJAQOH7Y7ErFbmzZQv75ZjTOpWjZBQdC7t9keNOj2I2dE0tuXX8LmzZA9e9LTEg8dgs6dzXa/ftC0abqFJ05mwQKT6AeYOdOsQHzxoq0hiYiIiEjmo2SXHWbNgnfegXr19K22q3M4zAc+Dw/47jtYvDjxdgMGQK5csHMn/PRT+sYokpRr1+IWTxgwAPLlS9jmyhV4+mm4cMGM/FJ9QteWMye8+Wbc9RUr4OGH4ehR20ISERERkcxHya70FhZmpqWBWYkxZkl2cV2lSpnfBYBevczvyK1y5jRJ0t9+M7WRRJzB7Nlw4ADkzw99+iS83bKga1dTpytPHli0yCR2xbW9+ioUKWK2s2eHP/+EGjXMCEERERERkVSgZFd6mzgR/vvPJDi6dLE7GnEWgwZBiRJw8iS88UbibVq2hIceSt+4RJISHh6XuB8xIm5q2s2mTYNPPzVJ/S+/hEKF0jVEcVKenjB6tNl2OKB0afPeV6cOfP65vbGJiIiISKagZFd6OnkSJk822+PGaSUyiePlBe+9Z7ZnzIBNm27f/vhxOH8+7eMSScqZM2YV2ZIl4+px3WztWlObEEySv3799I1PnFubNlCxInh7w5QppnD9lSvw/PPmtnPn7I4ww5gxYwZFihTBy8uLGjVqsHHjxtu2X7RoEaVLl8bLy4sKFSrw7bffxrvdsiyGDRtG/vz58fb2pmHDhuzbty8tn4KIiIhIqnNYlmus/R0eHo6fnx9hYWH4+vraE8TLL5tpP8HB8Pvv5httkZu98AJ89hlUrgwbNyaeEH3vPejb1xS0f/vt9I9RJIZlQWiomcZ4s2PHoEoVOH3aJC8+/VTvd5LQ3r0QGGimMt64YWp5jRljalnmzw8ffgiPPWZ3lCmS3n2NhQsX0r59e2bNmkWNGjWYMmUKixYtYs+ePeRLpIbeunXrqFOnDuPGjaNZs2YsWLCA8ePHs3XrVsqXLw/A+PHjGTduHPPnz6do0aIMHTqUv//+m507d+Ll5XXHmNL6NbCiLS6fvUzEmYgk27hndccrZ1yst2vrlsUN7/u876rt5f8uY0Un3o12uDnIljvbXbW9cv4K0Teik4zDJ6/PXbW9euEqUdeTrhWbkrbZcmfD4Wbe1yPDI7kRmfTiOSlp632fN25ZzHfx1y5d4/qV66nS1svPC3cP9xS3vX75OtciriXZ1jOHJ1m8sqS47Y2rN4i8GJlkWw8fD7Jmy5ritlHXorgadjXJtlm9s+KR3SPFbaNvRHPl/JVUaZvFMwuevp7A//89/3c5Vdqm5O9e7xGJt9V7hN4jUus9wievD9nyxJ3X1JbcvoaSXell714oW9Z04n/5xRTkFbnVqVNmSs+FCzBpUtzImJt9+61Zzc7Dw/xeFS6c7mGKJOnqVahb1yRrK1aEdesgW7Y7308EzKjWdu1gzx5z/eWXYcIEyJHD3riSKb37GjVq1KBatWpMnz4dgOjoaIKCgujZsycDY2pB3qRVq1ZERESwYsWK2H01a9akUqVKzJo1C8uyCAwMpG/fvvTr1w+AsLAw/P39mTdvHq1bt07wmJGRkURGxnWyw8PDCQoKSrPXIOJ0BNn9E5k2LSIiIk7j0qkIfPKlzf/r5Pa3NI0xvQQEmLpMrVsr0SVJ8/c3U77ArHK3e3fCNo8/blbyvHYNhg9P1/BE2LcPhg41NbtuZVmmFuHGjXDffbBkiRJdcmfR0bBwIezYAdWqwdatZrEOMAtzFCtmVjC+mvS3i67o2rVrbNmyhYYNG8buc3Nzo2HDhqxfvz7R+6xfvz5ee4DGjRvHtj948CChoaHx2vj5+VGjRo0kH3PcuHH4+fnFXoKCgu71qYmIiIjcMxWNSi++vmaKhmsMpJN70aULLF4M338P7dubkTE3T2d0OGD8eLN62ccfmymNFSrYF6+4liFDzKqK//4LCxbEv23ECLMvSxbTplgxW0KUDGbIEHjrLWjSBL75xiRIp0yB5s3NyK59+8wo10mTYNgw6NQJsma1O2rbnT17lqioKPz9/ePt9/f3Z3diX5QAoaGhibYPDQ2NvT1mX1JtbjVo0CBCbhqFHDOyK61ky5ONS6ciNEXpLtpqipKmKGkaY8rb6j3i7trqPcJw1feImGmMdrMt2TVjxgwmTpxIaGgoFStWZNq0aVSvXj3J9osWLWLo0KEcOnSIEiVKMH78eJo0aZKOEd+lmORWTL0a1a2RO3E44IMPoHx5M6Vn/HjzYfBm1avDs8+apNigQXDTlBSRNLNxo0liORzm9+5mn3wStzrjrFnQoEH6xycZU5cupv7gt9/Czz+bkasAjzwCO3fC/PkwciQcPQrduplpjd26mUL2BQvaGbkAnp6eeHp6ptvxHG4OfPL5pGhqhNqq7d22zYh8CyZ/+nBK2uYITP508pS0zR6QPU3aOsPvj9pm/rYZkTO8R6QXW6YxLly4kJCQEIYPH87WrVupWLEijRs35vTp04m2X7duHW3atKFLly5s27aNFi1a0KJFC3bs2JHOkd+FlSuhVi349Ve7I5GMpEABmDbNbI8cCdu3J2wzdiy4u5uREL/8kq7hiQuyLIipAdS+ffzRhL/8YhIWAAMGxG2LJMf995vkFZjfn5tHQGfJYn6f9u6FqVMhb14zqvD116FQIbPK5/vvmzqHLiZPnjy4u7tz6tSpePtPnTpFQEBAovcJCAi4bfuYnyl5TBERERFnZEuB+tQuqJocab46kAWX/7tCxNFz8Xe2ewF2/gOvvIr7myO5eSGjiKRHweLmZlZkv5u2ly8nPVvS4YhfQiclba9cMaVVkuLjc3dtr141dftTo222bHGD5yIjzQJfqdHW29u8zmBKZV1PemRritp6eZl8VaJtLctM1/nuGyhTFq+1P+CezXx7fv26ac/rr8Pnn5sVzNq3j72rp2fczMfYtkm4ue2NG+a1SIqHR9zsoZS0jYq6fbmdrFlN+5S2jY42v2up0TZLFvNawP//PSc9Uj5Fbd3dSfbffUrapvt7xE+roU1ryOIBf/wBQUGm7Yn9JuFw/hxXnniO6DkfxP0B3ELvESlve9v3iNu0TcnfvVO8R5w4xdWKNeBKBLz/ITzxRLy2sX/Lly4RtWAhV7/4Cjb+EdfA4Q6lSkK5cmQtXxqPQgFQqBDRblm4Ehn3++gTlIts9wfi8EqbkUh2FKivXr060/7/y5Ho6GgKFSpEjx49kuxPXb58meXLl8fuq1WrFg888EC8AvX9+vWjb9++sc8pX758SRaov5XtCwKJiIhIppbcvka6T2OMKag66KYpMMkpqBpyy6p0jRs35quvvkryOImtDpSWLl+G7Hm9gQK33PKz+THz/y8iyeYA5pnNXUDCVeSBCebSH3MRSTMNgDNwA6h68/77gaNmczmQP73jkszBHzhkNl+8XbvsQJf/v9zEAnb//+V/tz/SpTWb8KlX7a6idDYhISF06NCBqlWrUr16daZMmUJERASdOnUCoH379hQoUIBx48YB0KtXL+rWrcukSZNo2rQpX3zxBZs3b2bOnDkAOBwOevfuzejRoylRogRFixZl6NChBAYG0qJFC7uepoiIiEiKpXuyKy0KqiZm3LhxjBw58t4DFhERkcwjE9XObNWqFWfOnGHYsGGEhoZSqVIlVq5cGdtnOnLkCG43jbSsVasWCxYs4I033mDw4MGUKFGCr776ivLly8e2ef3114mIiKBr165cuHCB2rVrs3LlSrxuHnYqIiIi4uQy7WqM6b46UDa4dCkDT1FKRltNYzTbtkxR6v4qXos/wb1AIKxfz/UcuRJOO9q0ydStadTI+aYoaRpjrAz5HnHkKIx/C0qVgp6vmRPU9nkcv/1Cttw+sGoVlCyp9whNY7z394j358LnX8Cbo6DWQ7Ftk3yP+OsvaNQAvLLB7t3g7X3bv3sfH8iWLd7QxAyvR48e9OjRI9Hbfv755wT7WrZsScuWLZN8PIfDwahRoxgVs+CEiIiISAaU7smutCiomph0Xx3IYTrRN3/ouhO1Vdtkt/3gLdi+CvbvhVc7wLJl8UcnLFsGTz4JgYGwb1/8bIWTSEnplpS0zZGChT9S0jZ78hf8SVFbp/9dS6xt3iD4cobJkEXdgOeeh9+Wmif+/fdQuaRzxau2GZKvL/B6JxjYJcm6b/HaAvz6P+AsPP4UFPZOtG1K/u5FREREJHNI99UYPTw8qFKlCqtXr47dFx0dzerVqwkODk70PsHBwfHaA6xatSrJ9iKZjq8vfPmlGWKxYgVMnhz/9saNoXBhOHEC3n3Xnhgl80ls+Fe3brB0qRk6s2wZVKmS/nFJ5pUlyx0TXfHE1O588sk0CUdEREREMqZ0T3aBKag6d+5c5s+fz65du3jllVcSFFS9uYB9r169WLlyJZMmTWL37t2MGDGCzZs3JzlsXyRTqlwZpkwx2wMHws0LOnh6wptvmu233oL//kv38CQTGj4cnnsO9u83ia8BA+DDD00y4osvzCqMImnh0iXznjZsWNJtDh400xjd3KBp0/SLTUREREScni3JrlatWvH2228zbNgwKlWqxPbt2xMUVD158mRs+5iCqnPmzKFixYosXrw4QUFVEZfQrRu0amWK4bRqFT+p9fzz8MADEBYG/7/ylshdO3kSJk2CRYvgzz9N0mHiRHPb3Lnw1FP2xieZ27p15ndu/Hg4fDjxNsuWmZ+1a0OePOkXm4iIiIg4PYdlJVWmOHMJDw/Hz8+PsLAwfFNSEEjE2YSHQ9WqpjZX06bmA1/MtJ/vvoMmTcwUs717zdRGkbvx6qswcybUqAGNGsHo0Wb/O+9A7962hiYuwLKgYUP46Sdo1w4+/jhhm1GjTDLszTfhpgVp7KS+hl4DERERSVvJ7WvYMrJLRO7BzfW7vvkmLgkB8NhjUK+eWVrtdtN/RG5n716YM8dslyoV9zs2ebISXZI+HA6TyAL49FMzuvBWw4bB2bPQtWv6xiYiIiIiTk/JLpGMqFIleO89sz18uJlqBuYD4oQJULCg6inJ3Rs8GKKioESJuBE1kyZBnz72xiWupWpVUzPOskydwsR4e6dsOVQRERERcQlKdolkVJ07xyUfOnSALVvMdrVqcOAAdOxoW2iSgf3xB/zvfyZxum+f2ff2204zTUxczJgxZoXGlSvNlMYYp0/bF5OIiIiIOD0lu0QysokT4fHH4coVaN4cTpww+7NmtTcuybhiitDHlHOcOBH69rUvHnFt998PL79stt94w/yMjDT7y5aNe88TEREREbmJkl0iGZm7O3z+edyHviefhMuXzW1RUTB/Pjz7bFziQuR2btwwteBiTJ0K/frZF48IwNChZvTqJ5+Y62vWwMWLcOECBATYGpqIiIiIOCclu0QyOj8/WL4ccueGzZuhUyeIjob//oMePcyUtMWL7Y5SnN2VK/DMMyZ56u5uanW99prdUYlAvnwwbx4UL26uf/21+dm8edxKtCIiIiIiN1EvUSQzKFYMliwx0xe//NKMxsmbN25UzuDBcP26vTGK8woPN6t4LlsGXl6wdCm0a2d3VCIJRUfHjfB68kl7YxERERERp6Vkl0hmUacOvP++2X7nHVPYOSTEjIrYvx9mz7Y3PnFOx47Bww/Dxo1mlMy8efDEE3ZHJZLQhQtmynZEhLn+yCO2hiMiIiIizkvJLpHMpH17mDLFbA8damp2jRhhro8caUbwiMTYuhVq1IC//jLX8+XTaBlxXj4+sGeP2a5ZM359ORERERGRmyjZJZLZ9OoFw4aZ7Z49IVs2KFUKzp6F8ePtjU2cx9dfmxFdJ07E1T2aMMFMYxRxRlmzwu+/Q926MGOG3dGIiIiIiBNTskskMxoxwiS6ALp0MYXHwUxv/O8/28ISJ2BZMGkSPPWUWbmzUCFTB6lSJWjb1u7oRG6vVi34+Wd48EG7IxERERERJ6Zkl0hm5HCY6Yzt2kFUFLz9NjRrBj/8YFZtFNd09Sq89JJZuMCyoE0bM7ILzO+IVrYTEREREZFMQJ9sRDIrNzf44AMzgufaNfj+ewgNtTsqscvhw2ba4gcfmGToO+9AZCTcuAFNmkCDBnZHKCIiIiIikiqU7BLJzLJmhYULoXVruH4dWrWCjz+GM2fsjkzS06pVUKUKbN5sRvatXAldu8bV65owwe4IRUREREREUo2SXSKZXdas8Omn0Lmzqc3UoQMUKGASIJK5RUfD2LHw2GOmVlvVqrBlCzz6qFm4YN062LABypWzO1IREREREZFUo2SXiCtwd4e5c+OK1l+/bpJeUVH2xiVp59QpeOIJGDLEJL1efBF+/RUKF45r43CYBJiIiIiIiEgmomSXiKtwc4OpU6FXL3P95Elo1MjUbJLM5dtv4YEHzE9PT5PonDsXvLxMna7x4+HiRbujFBERERERSRNKdom4kphVGps2NdfXrDFT3MLCbA1LUsnVqyaZ2bQpnD4N5cubOl0vvhjX5r33YOBAqFPHrMgoIiIiIiKSySjZJeKK/vc/CAgw26tXQ61acPCgvTHJvfnzT6heHd5911x/7TXYtMkkvGL89x+MGmW2u3c3yU8REREREZFMRskuEVfk6QkzZphthwN27oQaNeD33+2NS1IuMhKGDjW1t/7+G/Llg2++MVNWvbzitx05Ei5cMFMcO3WyJVwREREREZG0pmSXiKt66ikzlc3DA4oUgTNnoF49mDRJ09syij/+gAcfhNGjTe21p56Cv/6CJk0Stt21y0xhBHjnHbNogYiIiIiISCakZJeIq3I4YM4c2LMHduyAli1NwqRfP2je3Ex5E+d06RKEhJjppzt3mtFcixbBkiXg75/4ffr1M6tvPvkkPPJI+sYrIiIiIiKSjpTsEnFlpUpB4cLg4wMLF5qRP56esGIFVKqkaY3OxrJgwQJz3t55x1xv394kvJ59Nun7rVxpVmbMmhUmTky/eEUkzZw7d462bdvi6+tLzpw56dKlC5cuXbrtfa5evUr37t3JnTs32bNn55lnnuHUqVOxt//555+0adOGoKAgvL29KVOmDFOnTk3rpyIiIiKS6pTsEhHjjz+gZMm4n8eOQd26pqD59et2Ryd//mnOR9u2cOIEFCtmEljz50Pu3Le/b/ny5n6vvQYlSqRPvCKSptq2bcs///zDqlWrWLFiBb/88gtdu3a97X369OnD8uXLWbRoEWvXruXEiRM8/fTTsbdv2bKFfPny8emnn/LPP/8wZMgQBg0axPTp09P66YiIiIikKodluUZxnvDwcPz8/AgLC8PX19fucEScy6JF8NxzpnbXzp1mOuMrr8Bnn5nbH3gAPvwQqlSxNUyXdPq0KSw/axZER4O3NwwZAn37JixAfyfR0eCm7zhE0kp69TV27dpF2bJl2bRpE1WrVgVg5cqVNGnShGPHjhEYGJjgPmFhYeTNm5cFCxbw7P+PBN29ezdlypRh/fr11KxZM9Fjde/enV27dvHTTz8lKzb1t0RERCQtJbevoU89ImIKmhcsCIcOmQL1OXLAJ5+YZFfu3KboefXqMGAAXLlid7SuITwchg+H4sXN9NLoaJOQ3LPHJLuSk+iKjo5/XYkukUxh/fr15MyZMzbRBdCwYUPc3NzYsGFDovfZsmUL169fp2HDhrH7SpcuTaFChVi/fn2SxwoLCyNXrlxJ3h4ZGUl4eHi8i4iIiIjd9MlHREzNrphaTmPHwtGjpoD988+bVfzatDGJkwkTzCivH3+0N97M7OpVU4+rWDEzhfTSJTOi7qefTF21oKDkP1a/fmbhgYMH0y5eEUl3oaGh5MuXL96+LFmykCtXLkJDQ5O8j4eHBzlz5oy339/fP8n7rFu3joULF952euS4cePw8/OLvQSl5D1KREREJI0o2SUiRqtW8PDDZuRW//5x+/PmNUXRly2DAgVg/35o1AiaNTOJMEkdly/Du++amlohIWY1zJIlzRTTTZugfv2UPd4//5jHW7wY9u1Lm5hFJFUNHDgQh8Nx28vu3bvTJZYdO3bw5JNPMnz4cB599NEk2w0aNIiwsLDYy9GjR9MlPhEREZHbyWJ3ACLiJBwOkxypUsWMIHrlFVMQPcYTT0CdOjBsmJlW9803ZpW/bt1gxAiTFJOUu3ABZsyAKVPg7Fmzr2BB85p26ABZ7uJt2rKgZ0+IioKnnoLbfFAVEefRt29fOnbseNs2xYoVIyAggNOnT8fbf+PGDc6dO0dAQECi9wsICODatWtcuHAh3uiuU6dOJbjPzp07adCgAV27duWNN964bTyenp54enreto2IiIhIetPILhGJU6mSSV6BWbnvxo34t/v5wdSpZtTQk0+aZMp778H995si6ufOpXvIGdbBg/D661CoELzxhkl0FS0KM2eakVhdutxdogvMaLA1a0xdr8mTUzduEUkzefPmpXTp0re9eHh4EBwczIULF9iyZUvsfX/66Seio6OpUaNGoo9dpUoVsmbNyurVq2P37dmzhyNHjhAcHBy7759//qF+/fp06NCBMWPGpN2TFREREUlDSnaJSHxvvgnlypnV/pIqaF6yJHz1lUmoPPigKaY+YgQULmymQJ48mZ4RZxzR0fDdd2aUXPHipk7axYtQvrxZDGDvXnj55ZSvsniziAhz7gAGDjQrbIpIplKmTBkee+wxXnrpJTZu3Mjvv/9Ojx49aN26dexKjMePH6d06dJs3LgRAD8/P7p06UJISAhr1qxhy5YtdOrUieDg4NiVGHfs2EH9+vV59NFHCQkJITQ0lNDQUM6cOWPbcxURERG5G0p2iUh8uXPD339D+/Z3Xr2vXj1TT+rLL82osEuX4O23zQilV15RTa8Yx4+bxFbJkmblyxUrzFTDRo1g+XL480+zGMDdjuS62dixcOyYSXK9/vq9P56IOKXPPvuM0qVL06BBA5o0aULt2rWZM2dO7O3Xr19nz549XL58OXbfO++8Q7NmzXjmmWeoU6cOAQEBLFmyJPb2xYsXc+bMGT799FPy588fe6lWrVq6PjcRERGRe+WwLMuyO4j0EB4ejp+fH2FhYfj6+todjkjGce0aeHjcuZ1lmVFLY8bAunVx+x9+GLp2hWefvbcRSxnNpUuwZAl88gmsXm1eHzBTQTt1MsnAkiVT95jXrplRefv3m5F3Tz6Zuo8vIrelvoZeAxEREUlbye1raGSXiCRt4UIoVgz+fxrMbTkcZtTSb7/B2rXQvLkZGfbrr9CuHQQGQu/esGFDXOIns7lwwaxc2aoV+PubAvM//mieb+3aMHeuGeX1zjupn+gCk5Tcvh0+/NC8/iIiIiIiIi5II7tEJGnt25uRSZUrm4RXSqfZHT9uEi9z58LNy9EHBcEzz5jRXsHBd54u6awsCw4cMCPavv4afv45flH/EiVMoq9tW5M0FJFMTX0NvQYiIiKStpx2ZNe5c+do27Ytvr6+5MyZky5dunDp0qXb3qdevXo4HI54l5dffjmdIhZxYW+/DTlzwrZtMGNGyu9foAAMHWpWHvzmGzPiycfHJL6mTDGjnQoUgBdeMEmxw4dT+xmkvmPH4OOPzVTEIkXMSpQ9e5oRXDduQJkypjD8hg2wZ495/mmd6IqIgI8+MgXwRUREREREXFy6j+x6/PHHOXnyJLNnz+b69et06tSJatWqsWDBgiTvU69ePUqWLMmoUaNi92XLli1F3xjqm0aRuzRnDnTrBjlymILzBQrc2+NduQI//ACLF8OyZWYlx5sVKwZ160KVKmalxwceMAkyO5w9C1u2wObNcZdjx+K3yZLFjE5r3tzUyCpRIv3jfP11UwD/uefM1FMRsYX6GnoNREREJG0lt6+RrsmuXbt2UbZsWTZt2kTVqlUBWLlyJU2aNOHYsWOxy2Xfql69elSqVIkpU6Yk+1iRkZFERkbGXg8PDycoKEidL5GUio6Ghx6CP/6Ali3NyoupJTLSFLP/6SdTxH3jRoiKit/GzQ1KlYIKFUwiLOZStKhJvHl63tvxQ0PN5fhx2LcP9u41I7L27oUzZxLex80NqlaF+vXhkUfMa2NXMg7MSo5VqpjXbflyaNbMvlhEXJwSPXoNREREJG05ZbLrww8/pG/fvpw/fz52340bN/Dy8mLRokU89dRTid6vXr16/PPPP1iWRUBAAE888QRDhw4lW7ZsSR5rxIgRjBw5MsF+db5E7sLNCZXvvoPHHkub41y8CL/8YhJrW7eaS2jo7e/j4wO5ckHu3OZntmzg7m5GXGXJYrYjI+HyZTPd7/Jls1LiqVNw03tRkkqWNMmtqlXNa1C5shnl5gyiokyybcMGU/9s0SK7IxJxaUr06DUQERGRtJXcvkYKq03fm9DQUPLlyxc/gCxZyJUrF6G3+UD7/PPPU7hwYQIDA/nrr78YMGAAe/bsYcmSJUneZ9CgQYSEhMRejxnZJSJ3oWJF6NULJk82yai0SnblyAFNm5pLjJMnTc2w3btNMfiDB+N+RkaaBFZERPwC+Cnh4QEBAeZy//1mFFnJkuZniRKQPXvqPLe0MHu2SXTlyAFTp9odjYiIiIiIiFNIlWTXwIEDGT9+/G3b7Nq1664fv2vXrrHbFSpUIH/+/DRo0IB///2X4sWLJ3ofT09PPO9lw/HzaQAAq/RJREFUepOIxDdiBDzxBNSrl77HzZ/fXJo0ib8/OhrCwuDcOXP57z/z8+pVUyg+Ksr8vHHDTHXMls2MAov5mTevedz77gOHI32fU2o4cQIGDTLb48ZBEtPARUREREREXE2qJLv69u1Lx44db9umWLFiBAQEcPr06Xj7b9y4wblz5wgICEj28WrUqAHA/v37k0x2iUgqy5Ej/RNdt+PmZhJV990Hrvg+EBJiivtXrw5anVZERERERCRWqiS78ubNS968ee/YLjg4mAsXLrBlyxaqVKkCwE8//UR0dHRsAis5tm/fDkD+/PnvKl4RuUdHjpgpjRMnQtasdkfjmvr3h0OHYNYsU5dMREREREREAHBLz4OVKVOGxx57jJdeeomNGzfy+++/06NHD1q3bh27EuPx48cpXbo0GzduBODff//lzTffZMuWLRw6dIhly5bRvn176tSpwwMPPJCe4YsImGmBdeqYGlFvv213NK6rShVYvx4qVbI7EhEREREREaeSrskugM8++4zSpUvToEEDmjRpQu3atZkzZ07s7devX2fPnj1cvnwZAA8PD3788UceffRRSpcuTd++fXnmmWdYvnx5eocuImBWOHzzTbM9ciTcQz0+uQtHjsRtZ8RaYyIiIiIiImnMYVmWZXcQ6UFLYYukIssyKyZ+9x0EB8Ovv2oqXXr45hto0QKGDoVhw+yORkRuob6GXgMRERFJW8nta6T7yC4RyQQcDpg92xStX78epk2zO6LM7/x56NrVTCMNC7M7GhEREREREaelZJeI3J2goLiaXYMHw7//2htPZtenD5w4ASVLwujRdkcjIiIiIiLitJTsEpG799JL8MgjcOUKjB1rdzSZ1zffwPz5ZkTdRx+Bt7fdEYmIiIiIiDgtJbtE5O45HPD++9C/P8yYYXc0mVPM9EWAkBCoVcveeERERERERJxcFrsDEJEMrmhRmDDB7igyJ8syia6Y6Ysxq2CKiIiIiIhIkjSyS0RST1SUKVZ/6ZLdkWQe9eubhQA+/VTTF0VERERERJJByS4RST3t2sFrr5li6nLvHA549VU4fBiqVbM7GhERERERkQxByS4RST1du8bV8Vq61O5oMq7ISAgPj7t+3332xSIiIiIiIpLBKNklIqmnXj14/XWz/eKLcPy4reFkWAMGQOXKsHGj3ZGIiIiIiIhkOEp2iUjqGjUKHnwQzp2DNm3g+nW7I8pYvv0Wpk6FAwfgzBm7oxEREREREclwlOwSkdTl4QGff26Kqv/6KwwcaHdEGceJE9Cxo9l+7TVo2tTWcERERERERDIiJbtEJPWVLAnz55vtWbPg2DF748kIIiPhmWfMaK4HHoDx4+2OSEREREREJENSsktE0sZTT8HkyfDHH1CwoN3RODfLgh49zGt1332wZAl4edkdlYiIiIiISIaUxe4ARCQT69PH7ggyhk8/NStYurmZKaDFi9sdkYiIiIiISIalkV0ikj7WrYOePc0oJomvWTN47DEYOxYaN7Y7GhERERERkQxNyS4RSXtnz0KjRjB9uknoSHz33QcrVsDrr9sdiYhkEOfOnaNt27b4+vqSM2dOunTpwqVLl257n6tXr9K9e3dy585N9uzZeeaZZzh16lSibf/77z8KFiyIw+HgwoULafAMRERERNKOkl0ikvby5IFJk8z2G2+YaXuu7soV+PLLuJFu7u7gcNgbk4hkGG3btuWff/5h1apVrFixgl9++YWuXbve9j59+vRh+fLlLFq0iLVr13LixAmefvrpRNt26dKFBx54IC1CFxEREUlzSnaJSPp4+WXo189sd+4Ma9bYG4+dbtyANm2gVau410REJJl27drFypUref/996lRowa1a9dm2rRpfPHFF5w4cSLR+4SFhfHBBx8wefJkHnnkEapUqcJHH33EunXr+OOPP+K1nTlzJhcuXKCf3p9EREQkg1KyS0TSz/jx0LIlXL9uVmv85x+7I0p/lgWvvgpffw2entC8ud0RiUgGs379enLmzEnVqlVj9zVs2BA3Nzc2bNiQ6H22bNnC9evXadiwYey+0qVLU6hQIdavXx+7b+fOnYwaNYqPP/4YN7c7dxMjIyMJDw+PdxERERGxm5JdIpJ+3Nzg44/hoYcgLAyaNIHQULujSl8jRsDcuea1WLAA6ta1OyIRyWBCQ0PJly9fvH1ZsmQhV65chCbxnhoaGoqHhwc5c+aMt9/f3z/2PpGRkbRp04aJEydSqFChZMUybtw4/Pz8Yi9BQUEpf0IiIiIiqUzJLhFJX15eZlRTyZJQsybc8sErU5s5E0aNMtszZkAStXJExDUNHDgQh8Nx28vu3bvT7PiDBg2iTJkyvPDCCym6T1hYWOzl6NGjaRafiIiISHJlsTsAEXFBuXPDr7+awvXJmCaTKSxZAt27m+3hw00NMxGRm/Tt25eOHTvetk2xYsUICAjg9OnT8fbfuHGDc+fOERAQkOj9AgICuHbtGhcuXIg3uuvUqVOx9/npp5/4+++/Wbx4MQDW/y+gkSdPHoYMGcLIkSMTPK6npyeenp7JfYoiIiIi6ULJLhGxx81TcKKjTT2vV17JvCO9rlwxP7t1M8kuEZFb5M2bl7x5896xXXBwMBcuXGDLli1UqVIFMImq6OhoatSokeh9qlSpQtasWVm9ejXPPPMMAHv27OHIkSMEBwcD8L///Y8rMe9VwKZNm+jcuTO//vorxYsXv9enJyIiIpJulOwSEfv17w+TJ8PSpfDDD5kz4dW2Lfj7Q/364HDYHY2IZGBlypThscce46WXXmLWrFlcv36dHj160Lp1awIDAwE4fvw4DRo04OOPP6Z69er4+fnRpUsXQkJCyJUrF76+vvTs2ZPg4GBq1qwJkCChdfbs2djj3VrrS0RERMSZucj8IRFxau3bm6mNmzZBo0Zw/rzdEaWOzz6DEyfirjdsCO7u9sUjIpnGZ599RunSpWnQoAFNmjShdu3azJkzJ/b269evs2fPHi5fvhy775133qFZs2Y888wz1KlTh4CAAJYsWWJH+CIiIiJpymHFFGTI5MLDw/Hz8yMsLAxfX1+7wxGRW/31FzRoAGfPwoMPwjffQBK1ZzKESZOgXz8oWxb++ANy5LA7IhFJY+pr6DUQERGRtJXcvoZGdomIc3jgAVizBvLmha1boVo12LbN7qhSLjoahg41iS6A5s0he3Z7YxIREREREXEhSnaJiPMoXx5+/x1KlYJjx6BxY4iIsDuq5AsLgxYtYPRoc33MGBg3TjW6RERERERE0pEK1IuIcylRwkz7a90aunYFHx+7I0qeHTvg6adh3z7w9ISZM6FTJ7ujEhERERERcTlKdomI88mZE777Lv6IqD/+MCO+7rvPtrBuq3dvk+gqVAj+9z+oWtXuiERERERERFySpjGKiHO6OdF15oypfVW2LHz9tX0x3c68eWY02pYtSnSJiIiIiIjYSMkuEXF+p09DrlwQGmpqYj3/vFm10S6WBV9+Ca+/HrevYEH4/HPIk8e+uERERERERETJLhHJAMqVg+3bYcAAcHMzSaWyZeGzzyAqKn1j+fdfePxxaNUKJk6E335L3+OLiIiIiIjIbSnZJSIZg5cXvPWWqd1VrpyZ2vjCC/Dgg3D9etof/9Ah6NvXHPv778HDA4YP15RFERERERERJ5Puya4xY8ZQq1YtsmXLRs6cOZN1H8uyGDZsGPnz58fb25uGDRuyb9++tA1URJxTtWqmLtbo0aZYffXqkDVr3O2pnfg6cwaefRaKF4fJkyEyEho2hL//hhEjTBJOREREREREnEa6J7uuXbtGy5YteeWVV5J9nwkTJvDuu+8ya9YsNmzYgI+PD40bN+bq1atpGKmIOC1PTxgyBA4fhrFj4/b/+Sfkzm2SU/Pnm0RVSt24AXv3xl3PmRM2bIDoaGjUCL75Bn74AUqWvOenISIiIiIiIqkvS3ofcOTIkQDMmzcvWe0ty2LKlCm88cYbPPnkkwB8/PHH+Pv789VXX9G6deu0ClVEnF2OHOYSY/ZsuHgR/vc/c3E4IDgYqlSBoCDo0AHy5TNtT5yAo0fh3DlzOXYMfvkFfv3V3H7uHGTJYkaNzZ1rCtCXL5/+z1FERERERERSJN2TXSl18OBBQkNDadiwYew+Pz8/atSowfr165NMdkVGRhIZGRl7PTw8PM1jFRGbTZ8OnTrB8uWwYgVs2wbr1pkLwNNPxyW7Ro6EOXMSf5ycOeHAgbjRW489luahi4iIiIiISOpw+mRXaGgoAP7+/vH2+/v7x96WmHHjxsWOIhMRF+HmZmp6VasGo0aZ0Vrffw/798ORI1CgQFzbAgWgcGHIlctccuc29b/q14eKFcHd3b7nISIiIiIiInctVZJdAwcOZPz48bdts2vXLkqXLp0ah0uWQYMGERISEns9PDycoKCgdDu+iDiBggWhS5fEbxs2zFxEREREREQkU0mVZFffvn3p2LHjbdsUK1bsrh47ICAAgFOnTpE/f/7Y/adOnaJSpUpJ3s/T0xNPT8+7OqaIiIiIiIiIiGRMqZLsyps3L3nz5k2Nh0qgaNGiBAQEsHr16tjkVnh4OBs2bEjRio4iIiIiIiIiIpL5uaX3AY8cOcL27ds5cuQIUVFRbN++ne3bt3Pp0qXYNqVLl2bp0qUAOBwOevfuzejRo1m2bBl///037du3JzAwkBYtWqR3+CIiIiIiIiIi4sTSvUD9sGHDmD9/fuz1ypUrA7BmzRrq1asHwJ49ewgLC4tt8/rrrxMREUHXrl25cOECtWvXZuXKlXh5eaVr7CIiIiIiIiIi4twclmVZdgeRHsLDw/Hz8yMsLAxfX1+7wxEREZFMRn0NvQYiIiKStpLb10j3aYwiIiIiIiIiIiJpRckuERERERERERHJNNK9ZpddYmZrhoeH2xyJiIiIZEYxfQwXqRCRKPW3REREJC0lt7/lMsmuixcvAhAUFGRzJCIiIpKZXbx4ET8/P7vDsIX6WyIiIpIe7tTfcpkC9dHR0Zw4cYIcOXLgcDjS5Bjh4eEEBQVx9OhRFWW1kc6D/XQOnIPOg3PQeXAO6XEeLMvi4sWLBAYG4ubmmpUi1N9yHToPzkHnwX46B85B58E5OFN/y2VGdrm5uVGwYMF0OZavr6/+wJyAzoP9dA6cg86Dc9B5cA5pfR5cdURXDPW3XI/Og3PQebCfzoFz0HlwDs7Q33LNrx1FRERERERERCRTUrJLREREREREREQyDSW7UpGnpyfDhw/H09PT7lBcms6D/XQOnIPOg3PQeXAOOg+Zh86lc9B5cA46D/bTOXAOOg/OwZnOg8sUqBcRERERERERkcxPI7tERERERERERCTTULJLREREREREREQyDSW7REREREREREQk01CyS0REREREREREMg0lu1LJjBkzKFKkCF5eXtSoUYONGzfaHZJLGTduHNWqVSNHjhzky5ePFi1asGfPHrvDcnlvvfUWDoeD3r172x2Kyzl+/DgvvPACuXPnxtvbmwoVKrB582a7w3IpUVFRDB06lKJFi+Lt7U3x4sV588030bowaeuXX37hiSeeIDAwEIfDwVdffRXvdsuyGDZsGPnz58fb25uGDRuyb98+e4KVFFN/y17qbzkn9bfso/6W/dTfskdG6G8p2ZUKFi5cSEhICMOHD2fr1q1UrFiRxo0bc/r0abtDcxlr166le/fu/PHHH6xatYrr16/z6KOPEhERYXdoLmvTpk3Mnj2bBx54wO5QXM758+d56KGHyJo1K9999x07d+5k0qRJ3HfffXaH5lLGjx/PzJkzmT59Ort27WL8+PFMmDCBadOm2R1aphYREUHFihWZMWNGordPmDCBd999l1mzZrFhwwZ8fHxo3LgxV69eTedIJaXU37Kf+lvOR/0t+6i/5RzU37JHhuhvWXLPqlevbnXv3j32elRUlBUYGGiNGzfOxqhc2+nTpy3AWrt2rd2huKSLFy9aJUqUsFatWmXVrVvX6tWrl90huZQBAwZYtWvXtjsMl9e0aVOrc+fO8fY9/fTTVtu2bW2KyPUA1tKlS2OvR0dHWwEBAdbEiRNj9124cMHy9PS0Pv/8cxsilJRQf8v5qL9lL/W37KX+lnNQf8t+ztrf0siue3Tt2jW2bNlCw4YNY/e5ubnRsGFD1q9fb2Nkri0sLAyAXLly2RyJa+revTtNmzaN93ch6WfZsmVUrVqVli1bki9fPipXrszcuXPtDsvl1KpVi9WrV7N3714A/vzzT3777Tcef/xxmyNzXQcPHiQ0NDTee5Ofnx81atTQ/2wnp/6Wc1J/y17qb9lL/S3noP6W83GW/laWdDtSJnX27FmioqLw9/ePt9/f35/du3fbFJVri46Opnfv3jz00EOUL1/e7nBczhdffMHWrVvZtGmT3aG4rAMHDjBz5kxCQkIYPHgwmzZt4rXXXsPDw4MOHTrYHZ7LGDhwIOHh4ZQuXRp3d3eioqIYM2YMbdu2tTs0lxUaGgqQ6P/smNvEOam/5XzU37KX+lv2U3/LOai/5Xycpb+lZJdkOt27d2fHjh389ttvdofico4ePUqvXr1YtWoVXl5edofjsqKjo6latSpjx44FoHLlyuzYsYNZs2ap85WOvvzySz777DMWLFhAuXLl2L59O7179yYwMFDnQUQyPPW37KP+lnNQf8s5qL8lSdE0xnuUJ08e3N3dOXXqVLz9p06dIiAgwKaoXFePHj1YsWIFa9asoWDBgnaH43K2bNnC6dOnefDBB8mSJQtZsmRh7dq1vPvuu2TJkoWoqCi7Q3QJ+fPnp2zZsvH2lSlThiNHjtgUkWvq378/AwcOpHXr1lSoUIF27drRp08fxo0bZ3doLivm/7L+Z2c86m85F/W37KX+lnNQf8s5qL/lfJylv6Vk1z3y8PCgSpUqrF69OnZfdHQ0q1evJjg42MbIXItlWfTo0YOlS5fy008/UbRoUbtDckkNGjTg77//Zvv27bGXqlWr0rZtW7Zv3467u7vdIbqEhx56KMFS8Hv37qVw4cI2ReSaLl++jJtb/H+z7u7uREdH2xSRFC1alICAgHj/s8PDw9mwYYP+Zzs59becg/pbzkH9Leeg/pZzUH/L+ThLf0vTGFNBSEgIHTp0oGrVqlSvXp0pU6YQERFBp06d7A7NZXTv3p0FCxbw9ddfkyNHjti5wH5+fnh7e9scnevIkSNHgrodPj4+5M6dW/U80lGfPn2oVasWY8eO5bnnnmPjxo3MmTOHOXPm2B2aS3niiScYM2YMhQoVoly5cmzbto3JkyfTuXNnu0PL1C5dusT+/ftjrx88eJDt27eTK1cuChUqRO/evRk9ejQlSpSgaNGiDB06lMDAQFq0aGFf0JIs6m/ZT/0t56D+lnNQf8s5qL9ljwzR30q3dR8zuWnTplmFChWyPDw8rOrVq1t//PGH3SG5FCDRy0cffWR3aC5PS2HbY/ny5Vb58uUtT09Pq3Tp0tacOXPsDsnlhIeHW7169bIKFSpkeXl5WcWKFbOGDBliRUZG2h1aprZmzZpE/x906NDBsiyzHPbQoUMtf39/y9PT02rQoIG1Z88ee4OWZFN/y17qbzkv9bfsof6W/dTfskdG6G85LMuy0i+1JiIiIiIiIiIiknZUs0tERERERERERDINJbtERERERERERCTTULJLREREREREREQyDSW7REREREREREQk01CyS0REREREREREMg0lu0REREREREREJNNQsktERERERERERDINJbtERERERERERCTTULJLREREREREREQyDSW7REREREREREQk01CyS8QFFSlShGbNmtkdxl2rV68e5cuXtzsMp9OxY0eKFCmSqo9Zr1496tWrl6qP6czHFRERiZEW/1fv1rx583A4HGzevNnuUO7Kzz//jMPhYPHixXaH4lQOHTqEw+Fg3rx5qfaYMa/1zz//nGqP6czHFUmKkl0id+nff/+lW7duFCtWDC8vL3x9fXnooYeYOnUqV65cSfXjXb58mREjRiT7H8jOnTsZMWIEhw4dSvVYXNm3337LiBEjbDv+iRMnGDFiBNu3b7cthtSi31ERkczn77//5tlnn6Vw4cJ4eXlRoEABGjVqxLRp0+K1Gzt2LF999ZU9QTqx9957L1UTH5LyPnRaWLBgAVOmTLHt+KlJv6OSUWSxOwCRjOibb76hZcuWeHp60r59e8qXL8+1a9f47bff6N+/P//88w9z5sxJ1WNevnyZkSNHAiRrxMvOnTsZOXIk9erVc5pvJTODb7/9lhkzZtiW8Dpx4gQjR46kSJEiVKpUKd5tc+fOJTo6OlWP98MPP6Tq493sdr+jaXlcERFJG+vWraN+/foUKlSIl156iYCAAI4ePcoff/zB1KlT6dmzZ2zbsWPH8uyzz9KiRQv7Ar6DtPi/eifvvfceefLkoWPHjul63MwspX3otLBgwQJ27NhB79694+0vXLgwV65cIWvWrKl2rDp16nDlyhU8PDxS7TFvltTvaFofVySllOwSSaGDBw/SunVrChcuzE8//UT+/Pljb+vevTv79+/nm2++sTHCtBUREYGPj4/dYUgiUrOjFMOuDos6SiIiGc+YMWPw8/Nj06ZN5MyZM95tp0+ftieoe5AW/1ftYFkWV69exdvb2+5Q5BYOhwMvL69UfUw3N7dUf0xnPq5IUjSNUSSFJkyYwKVLl/jggw/iJbpi3H///fTq1Sv2+o0bN3jzzTcpXrw4np6eFClShMGDBxMZGRnvfps3b6Zx48bkyZMHb29vihYtSufOnQEznz9v3rwAjBw5EofDgcPhSHJ00bx582jZsiUA9evXj21/6/Dt3377jerVq+Pl5UWxYsX4+OOPEzyOw+Fg7dq1vPrqq+TLl4+CBQvG3v7ee+9Rrlw5PD09CQwMpHv37ly4cCHeYxQpUiTRbycTq8l0+PBhmjdvjo+PD/ny5aNPnz58//33Sc7/37lzJ/Xr1ydbtmwUKFCACRMmJGhz+vRpunTpgr+/P15eXlSsWJH58+fHa5NUjYFb6yh07NiRGTNmAMS+pg6HI8Exb5Wc1ymmDtmWLVuoVatW7O/ArFmz4sVZrVo1ADp16hR7/Jvju3mEVEz8b7/9NjNmzKBYsWJky5aNRx99lKNHj2JZFm+++SYFCxbE29ubJ598knPnziWI6+bzVKRIkXjP/eZLzOt3+PBhXn31VUqVKoW3tze5c+emZcuW8aYr3ul3NLHfj+Scy5uf85w5c2L/7qpVq8amTZvueK5EROTu/fvvv5QrVy5BogsgX758sdsOh4OIiAjmz58f+/5/c1/h+PHjdO7cGX9/fzw9PSlXrhwffvhhvMeL+d+9cOFCBg8eTEBAAD4+PjRv3pyjR4/eMdaLFy/Su3dvihQpgqenJ/ny5aNRo0Zs3bo1ts2t/1fr1auX5P/Am6d1Xbhwgd69exMUFISnpyf3338/48ePv+MosSJFivDPP/+wdu3a2Me99X9hZGQkISEh5M2bFx8fH5566inOnDmT4HGaNWvG999/T9WqVfH29mb27NkAHDhwgJYtW5IrVy6yZctGzZo1E3xJG9P/u7XMQFL9pZg+hre3N9WrV+fXX39NsvZmdHQ0Y8aMoWDBgnh5edGgQQP279+foN2iRYuoUqUK3t7e5MmThxdeeIHjx4/Ha5PUMW4+byntQ8dIzuuU3N/BevXq8c0333D48OHY498c362/Px07diR79uwcOXKEZs2akT17dgoUKBDbB/3777955JFH8PHxoXDhwixYsCDRuGLOU8z5TOxy8+v30Ucf8cgjj5AvXz48PT0pW7YsM2fOjPfYt/sdTer3IznnMuY5Hz9+nBYtWpA9e3by5s1Lv379iIqKuu25EkmKRnaJpNDy5cspVqwYtWrVSlb7F198kfnz5/Pss8/St29fNmzYwLhx49i1axdLly4FzIf4Rx99lLx58zJw4EBy5szJoUOHWLJkCQB58+Zl5syZvPLKKzz11FM8/fTTADzwwAOJHrNOnTq89tprvPvuuwwePJgyZcoAxP4E2L9/P88++yxdunShQ4cOfPjhh3Ts2JEqVapQrly5eI/36quvkjdvXoYNG0ZERAQAI0aMYOTIkTRs2JBXXnmFPXv2MHPmTDZt2sTvv/+e4m9DIyIieOSRRzh58iS9evUiICCABQsWsGbNmkTbnz9/nscee4ynn36a5557jsWLFzNgwAAqVKjA448/DsCVK1eoV68e+/fvp0ePHhQtWpRFixbRsWNHLly4EC8pmRzdunXjxIkTrFq1ik8++SRZ90nJ63T+/HmaNGnCc889R5s2bfjyyy955ZVX8PDwoHPnzpQpU4ZRo0YxbNgwunbtysMPPwxwx9/Fzz77jGvXrtGzZ0/OnTvHhAkTeO6553jkkUf4+eefGTBgAPv372fatGn069cvwQeKm02ZMoVLly7F2/fOO++wfft2cufODcCmTZtYt24drVu3pmDBghw6dIiZM2dSr149du7cSbZs2ZL1O3qzlJ7LBQsWcPHiRbp164bD4WDChAk8/fTTHDhwINN8Uy8i4mwKFy7M+vXr2bFjx20Xkvnkk0948cUXqV69Ol27dgWgePHiAJw6dYqaNWvicDjo0aMHefPm5bvvvqNLly6Eh4cnmAY2ZswYHA4HAwYM4PTp00yZMoWGDRuyffv2245kevnll1m8eDE9evSgbNmy/Pfff/z222/s2rWLBx98MNH7DBkyhBdffDHevk8//ZTvv/8+Npl3+fJl6taty/Hjx+nWrRuFChVi3bp1DBo0iJMnT962btOUKVPo2bMn2bNnZ8iQIQD4+/vHa9OzZ0/uu+8+hg8fzqFDh5gyZQo9evRg4cKF8drt2bOHNm3a0K1bN1566SVKlSrFqVOnqFWrFpcvX+a1114jd+7czJ8/n+bNm7N48WKeeuqpJGNLysyZM+nRowcPP/wwffr04dChQ7Ro0YL77rsv3hekMd566y3c3Nzo168fYWFhTJgwgbZt27Jhw4bYNvPmzaNTp05Uq1aNcePGcerUKaZOncrvv//Otm3bEk2mJiWlfWggxa/TnX4HhwwZQlhYGMeOHeOdd94BIHv27LeNOyoqiscff5w6deowYcIEPvvsM3r06IGPjw9Dhgyhbdu2PP3008yaNYv27dsTHBxM0aJFE32sOnXqJOi3Hj58mDfeeCNeEnrmzJmUK1eO5s2bkyVLFpb/X3v3HR9Fnf8P/LU1CQlJaEkIhFClN6mxFyR6WDgVy+GJqGABFfH0K3cetjuxHByCBdET9acIooeniCiCgiVURSmCiAgoJKEmEEjb/fz+SHYy5TO7s8ludjd5PR/ycHfmM7OfmdlkJ+99f96fDz/EnXfeCa/XiwkTJgCw9h5VC+Zaejwe5ObmYsiQIfjXv/6Fzz77DNOnT0enTp1wxx13+D1fRFKCiCwrKioSAMQVV1xhqf2mTZsEAHHrrbdqlv/lL38RAMTKlSuFEEIsXrxYABDr16833dfBgwcFAPHwww9beu1FixYJAOLzzz83rMvOzhYAxOrVq5VlhYWFIi4uTtx3333Ksnnz5gkA4qyzzhKVlZWatm63WwwfPlx4PB5l+XPPPScAiFdffVXzWmPGjDH04dxzzxXnnnuu8nz69OkCgHj//feVZadOnRLdunUzHMe5554rAIg33nhDWVZWViYyMjLEVVddpSybOXOmACDefPNNZVl5ebnIyckRSUlJori4WAghxOeffy49V7t37xYAxLx585RlEyZMEFZ/dQZznnzHNH36dM0x9evXT6SlpYny8nIhhBDr16839MlnzJgxIjs729D/Vq1aiWPHjinLp0yZIgCIvn37ioqKCmX59ddfL9xutygtLdX0S32d9N555x0BQDz22GPKspMnTxra5eXlGa6Zv/eo/nWtXkvfMbdo0UIcOXJEafu///1PABAffvih6bEQEVHdfPrpp8LhcAiHwyFycnLEAw88ID755BPlM0wtMTFRen9wyy23iNatW4tDhw5pll933XUiJSVF+YzxfXa3adNG+QwQouZz6dlnn/Xb15SUFDFhwgS/bfSfq3pff/21cLlc4uabb1aWPf744yIxMVH89NNPmrYPPvigcDgcYu/evX5fs2fPntLPXd892bBhw4TX61WW33vvvcLhcGg+5333ecuWLdPsY9KkSQKA+PLLL5Vlx48fFx06dBDt27dX7lV8r7V7927N9vr7pbKyMtGiRQsxaNAgzf3Ea6+9JgBojsO3bffu3UVZWZmy/NlnnxUAxObNm4UQVZ/taWlpolevXuLUqVNKuyVLlggAYurUqcoys3sU/XUL9h7a6nkK5j04YsQI6XtJdq85ZswYAUA88cQTyrKjR4+KhIQEYbPZxIIFC5Tl27dvNxyb2X2tz6lTp8SAAQNEZmamOHDggLJcdv+Wm5srOnbsqFlm9h7Vv24w19J3zOr7SSGE6N+/vxgwYID0OIgC4TBGoiAUFxcDAJo2bWqp/dKlSwEAkydP1iy/7777AEBJh/Z9q7FkyRJUVFSEoqsB9ejRQ8kMAqq++eratSt++eUXQ9tx48bB4XAozz/77DOUl5dj0qRJsNvtmnbJycm1qlm2bNkytGnTBpdffrmyLD4+HuPGjZO2T0pKwg033KA8d7vdGDx4sKb/S5cuRUZGBq6//nplmcvlwt13340TJ05g1apVQfczGMGeJ6fTidtuu0157na7cdttt6GwsBAbN26sdT9GjRqFlJQU5fmQIUMAADfccAOcTqdmeXl5uSG13My2bdtw880344orrsBDDz2kLFd/k15RUYHDhw+jc+fOSE1N1QwPCUaw1/Laa69Fs2bNlOe+97rs/U1ERKFx0UUXIS8vD5dffjm+//57PP3008jNzUWbNm3wwQcfBNxeCIH33nsPl112GYQQOHTokPIvNzcXRUVFhs+RG2+8UXNfdvXVV6N169bKPZiZ1NRUrF27Fvv376/Vsebn5+Pqq69Gv3798MILLyjLFy1ahLPPPhvNmjXT9H/YsGHweDxYvXp1rV7PZ/z48ZoSCmeffTY8Hg/27NmjadehQwfk5uZqli1duhSDBw/GWWedpSxLSkrC+PHj8euvv2Lbtm1B9WXDhg04fPgwxo0bp7mfGD16tOYzWG3s2LGaupz6z+cNGzagsLAQd955p6b+04gRI9CtW7d6qYsb7Hmq7XswEHUWYWpqKrp27YrExERcc801yvKuXbsiNTU1qPubO++8E5s3b8Z7772HjIwMZbn6/q2oqAiHDh3Cueeei19++QVFRUVB97821/L222/XPD/77LN570a11iiDXatXr8Zll12GzMxM2Gy2epn2+Pfff8cNN9yAFi1aICEhAb1798aGDRvC/roUWsnJyQCq6jxYsWfPHtjtdnTu3FmzPCMjA6mpqcqNybnnnourrroKjz76KFq2bIkrrrgC8+bNM9T1CqV27doZljVr1gxHjx41LNenRfv63bVrV81yt9uNjh07Gm64rNizZw86depkqIGlP3c+bdu2NbTV93/Pnj3o0qWLJtAE1AyVq00/gxHsecrMzDQU/z/ttNMAwFA3Ixj6a+0LfGVlZUmXy94DesXFxbjyyivRpk0bvPHGG5prcerUKUydOlWpVdKyZUu0atUKx44dq9XNEhD8tdQfs++m28qxERFR7Q0aNAj//e9/cfToUaxbtw5TpkzB8ePHcfXVVwcMphw8eBDHjh3D3Llz0apVK82/sWPHAjAWuu/SpYvmuc1mQ+fOnQN+bj799NPYsmULsrKyMHjwYDzyyCOW/6iurKzENddcA4/Hg//+97+Ii4tT1u3cuRPLli0z9H/YsGHS/gfL6uebbEjbnj17DPckQO3vi3zt9fdqTqfTdCbwQP03u3cCgG7duoX93s3Xh2DOU23fg/7Ex8crtcZ8UlJSpPe/KSkplu9vXnrpJcybNw+zZ8/G0KFDNeu+/vprDBs2DImJiUhNTUWrVq3w17/+FQBqdf8W7LWUHbPZ3yZEVjTKml0lJSXo27cvbr75ZmXcdjgdPXoUZ555Js4//3x8/PHHaNWqFXbu3Gn6jQdFr+TkZGRmZmLLli1BbReoiLnNZsO7776LNWvW4MMPP8Qnn3yCm2++GdOnT8eaNWsCjuuvDXWmlpoQwrCsLrP3mB27x+Mx7YMVwfQ/EH99bAjMzlVdzuFNN92E/fv3Y926dUoQ2Oeuu+7CvHnzMGnSJOTk5CAlJQU2mw3XXXddvU3hHsr3BxERBc/tdmPQoEEYNGgQTjvtNIwdOxaLFi3Cww8/bLqN7zPihhtuwJgxY6Rt/NVaCsY111yDs88+G4sXL8ann36KZ555Bk899RT++9//KrU/zdx///3Iy8vDZ599ZqhL5fV6cdFFF+GBBx6Qbuv7Equ2rH6+hevera5Cff8m264h3L+F495t3bp1uOeee3DrrbcqtfJ8du3ahQsvvBDdunXDjBkzkJWVBbfbjaVLl+Lf//53vdy/1eXvAiKZRhnsuuSSS/x+iJWVleFvf/sb3n77bRw7dgy9evXCU089JZ3tw4qnnnoKWVlZmDdvnrLMrIAgRb9LL70Uc+fORV5eHnJycvy2zc7Ohtfrxc6dOzWFtwsKCnDs2DFkZ2dr2g8dOhRDhw7FP//5T8yfPx+jR4/GggULcOutt1qa9U8t2PbB8PV7x44d6Nixo7K8vLwcu3fvVr69BKq+kdHPPAhUfduj3jY7Oxvbtm2DEELTd9kMPcH084cffoDX69VkBG3fvl1zHL7As76fsm8PgzmvwZwnANi/fz9KSko02V0//fQTACjfkIbzulr15JNP4v3338d///tfdOvWzbD+3XffxZgxYzB9+nRlWWlpqeH8BnsurVxLIiKKPgMHDgQAHDhwQFkm+wxo1aoVmjZtCo/HY/iMNLNz507NcyEEfv75Z0tBsdatW+POO+/EnXfeicLCQpx++un45z//6ffvhAULFmDmzJmYOXMmzj33XMP6Tp064cSJE5b7rxfu+7cdO3YYltf2vsjX/ueff8b555+vLK+srMSvv/5aq8Ck+t7pggsu0KzbsWOH5vO+WbNm0mw8fT+DPadWz5OPlfdgpO/fDh48qAy79c3qqPbhhx+irKwMH3zwgSb7TjZRlNVjCeZaEoVDoxzGGMjEiRORl5eHBQsW4IcffsCoUaNw8cUXG36RWfXBBx9g4MCBGDVqFNLS0tC/f3+8/PLLIe411ZcHHngAiYmJuPXWW1FQUGBYv2vXLjz77LMAgD/84Q8AYJh5Z8aMGQCqxqwDVdl/+m9k+vXrBwDKUMYmTZoAMN54mPEFTKy2D8awYcPgdrsxa9YsTb//85//oKioSDkuoOqmb82aNSgvL1eWLVmyxDAteG5uLn7//XdNTY/S0tI6/az84Q9/QH5+vmaGosrKSsyePRtJSUnKTWp2djYcDoehjoa6BodPMOc1mPPk65tvanCgKij20ksvoVWrVhgwYEDQrx8On332GR566CH87W9/w8iRI6VtHA6H4f08e/ZswzetwRyL1WsZjKKiImzfvr3WQyuJiEjr888/l2aY+GoXqYczJSYmGn7/OxwOXHXVVXjvvfekWfQHDx40LHvjjTc05SXeffddHDhwwG/AyuPxGH73p6WlITMz028JiS1btuDWW2/FDTfcYDqj8zXXXIO8vDx88sknhnXHjh1DZWWl6f4B+XkJlT/84Q9Yt24d8vLylGUlJSWYO3cu2rdvjx49egComRlTfV/k8Xgwd+5czf4GDhyIFi1a4OWXX9Yc11tvvVXroWcDBw5EWloa5syZo7kWH3/8MX788UfDPeb27ds174vvv/8eX3/9tWafwd5DWz1PPlbeg4mJiRG73/B4PLjuuutQXl6O9957T1MzzceXVaX++S0qKtIka/hYfY8Gcy2DsWvXLuzatatW21Lj0igzu/zZu3cv5s2bh7179yIzMxMA8Je//AXLli3DvHnz8MQTTwS9z19++QUvvvgiJk+ejL/+9a9Yv3497r77brjdbtMUbYpenTp1wvz583Httdeie/fuuPHGG9GrVy+Ul5fjm2++waJFi3DTTTcBAPr27YsxY8Zg7ty5OHbsGM4991ysW7cOr7/+OkaOHKl8C/b666/jhRdewB//+Ed06tQJx48fx8svv4zk5GQlYJaQkIAePXpg4cKFOO2009C8eXP06tXLdGrvfv36weFw4KmnnkJRURHi4uJwwQUXaKYYrq1WrVphypQpePTRR3HxxRfj8ssvx44dO/DCCy9g0KBBmsLxt956K959911cfPHFuOaaa7Br1y68+eabyo2Uz2233YbnnnsO119/Pe655x60bt0ab731llLQsjbfiI0fPx4vvfQSbrrpJmzcuBHt27fHu+++i6+//hozZ85UiommpKRg1KhRmD17Nmw2Gzp16oQlS5ZI62r4gk533303cnNz4XA4cN1119X5PAFVNbueeuop/PrrrzjttNOwcOFCbNq0CXPnzoXL5QJQ9f5LTU3FnDlz0LRpUyQmJmLIkCH1li16/fXXo1WrVujSpQvefPNNzbqLLroI6enpuPTSS/H//t//Q0pKCnr06KEM9WjRooWmfTDvUavXMhiLFy/G2LFjMW/ePOVnloiIau+uu+7CyZMn8cc//hHdunVT7o0WLlyI9u3bK3W3gKrP088++wwzZsxAZmYmOnTogCFDhuDJJ5/E559/jiFDhmDcuHHo0aMHjhw5gm+//RafffYZjhw5onnN5s2b46yzzsLYsWNRUFCAmTNnonPnzqYT3ABVtVfbtm2Lq6++Gn379kVSUhI+++wzrF+/XpOVrOfr/znnnGP4DDzjjDPQsWNH3H///fjggw9w6aWX4qabbsKAAQNQUlKCzZs3491338Wvv/6Kli1bmr7GgAED8OKLL+If//gHOnfujLS0NENWTG09+OCDePvtt3HJJZfg7rvvRvPmzfH6669j9+7deO+995TM6Z49e2Lo0KGYMmUKjhw5gubNm2PBggWGQJ3b7cYjjzyCu+66CxdccAGuueYa/Prrr3jttdekdVitcLlceOqppzB27Fice+65uP7661FQUIBnn30W7du3x7333qu0vfnmmzFjxgzk5ubilltuQWFhIebMmYOePXsqk0oBwd9DWz1PPlbegwMGDMDChQsxefJkDBo0CElJSbjsssuCPj+1MWfOHKxcuRK33367IVMrPT0dF110EYYPHw63243LLrsMt912G06cOIGXX34ZaWlpmoxM37FYeY8Gcy2DceGFFwKoWz1baiTqefbHqANALF68WHnumwo1MTFR88/pdIprrrlGCCHEjz/+KAD4/fd///d/yj5dLpfIycnRvO5dd90lhg4dWi/HSOHx008/iXHjxon27dsLt9stmjZtKs4880wxe/ZsUVpaqrSrqKgQjz76qOjQoYNwuVwiKytLTJkyRdPm22+/Fddff71o166diIuLE2lpaeLSSy8VGzZs0LzmN998IwYMGCDcbrelKZRffvll0bFjR+FwODRTAWdnZ4sRI0YY2uuncPZNPb1+/Xrp/p977jnRrVs34XK5RHp6urjjjjvE0aNHDe2mT58u2rRpI+Li4sSZZ54pNmzYIJ0u+pdffhEjRowQCQkJolWrVuK+++4T7733ngAg1qxZo+lnz549Da8jmyK8oKBAjB07VrRs2VK43W7Ru3dvzfTOPgcPHhRXXXWVaNKkiWjWrJm47bbbxJYtWwzTQVdWVoq77rpLtGrVSthsNmHl16iV8+Q7pg0bNoicnBwRHx8vsrOzxXPPPWfY3//+9z/Ro0cP4XQ6Nf3TH79vOutnnnlGs71vauhFixZplsuut/46+fu953t/HT16VDnnSUlJIjc3V2zfvl1kZ2cbppk3e4/K3h9WrqXZMfv6rv6Z8R2v7P1ARETB+/jjj8XNN98sunXrJpKSkoTb7RadO3cWd911lygoKNC03b59uzjnnHNEQkKCAKD5fCgoKBATJkwQWVlZwuVyiYyMDHHhhReKuXPnKm18n2Vvv/22mDJlikhLSxMJCQlixIgRYs+ePX77WVZWJu6//37Rt29f0bRpU5GYmCj69u0rXnjhBU07/edqdna26Weg+rPk+PHjYsqUKaJz587C7XaLli1bijPOOEP861//EuXl5X77lp+fL0aMGCGaNm0qACifhWb3ZL7z4Pv89PVTdp8nhBC7du0SV199tUhNTRXx8fFi8ODBYsmSJdJ2w4YNE3FxcSI9PV389a9/FcuXLze8lhBCzJo1S2RnZ4u4uDgxePBg8fXXX4sBAwaIiy++2NBP/b2H73Nb/1m8cOFC0b9/fxEXFyeaN28uRo8eLX777TdDP998803RsWNH4Xa7Rb9+/cQnn3wivR8M9h7aynkK5j144sQJ8ac//UmkpqYKAEr/ZMc/ZswYkZiYaOiT2f2v/nrr3xMPP/yw6ftWfa/1wQcfiD59+oj4+HjRvn178dRTT4lXX31VABC7d+9W2pm9R2XvRSGsXUuzY/b1XX+8+utLJGMTonFX67XZbFi8eLEyHGfhwoUYPXo0tm7daiiSl5SUhIyMDJSXlwecraVFixbKbBLZ2dm46KKL8MorryjrfdHw33//PbQHRNTAzJw5E/feey9+++03tGnTJtLdCZvzzjsPhw4dCnryAyIiosboiy++wPnnn49Fixbh6quvjnR3SMXr9aJVq1a48sorG3TpFr4HiaIbhzHq9O/fHx6PB4WFhTj77LOlbdxut7Qos5kzzzzTUOTwp59+YlE+Ip1Tp05pZg8qLS3FSy+9hC5dujToQBcRERFRLCotLUVcXJxmyOIbb7yBI0eO1HpyLyKiUGiUwa4TJ05oZnjbvXs3Nm3ahObNm+O0007D6NGjceONN2L69Ono378/Dh48iBUrVqBPnz61KqR377334owzzsATTzyBa665BuvWrcPcuXMNRR6JGrsrr7wS7dq1Q79+/VBUVIQ333wT27dvx1tvvRXprhERERGRzpo1a3Dvvfdi1KhRaNGiBb799lv85z//Qa9evTBq1KhId4+IGrFGGezasGGDZnrcyZMnAwDGjBmD1157DfPmzcM//vEP3Hffffj999/RsmVLDB06FJdeemmtXm/QoEFYvHgxpkyZgsceewwdOnTAzJkzMXr06JAcD1FDkZubi1deeQVvvfUWPB4PevTogQULFuDaa6+NdNeIiIiISKd9+/bIysrCrFmzlGL2N954I5588knprH9ERPWl0dfsIiIiIiIiIiKihsMeuAkREREREREREVFsYLCLiIiIiIiIiIgajEZTs8vr9WL//v1o2rSpZrYQIiIiolAQQuD48ePIzMyE3d44v0/k/RYRERGFk9X7rUYT7Nq/fz+ysrIi3Q0iIiJq4Pbt24e2bdtGuhsRwfstIiIiqg+B7rcaTbCradOmAKpOSHJycoR7Q0RERA1NcXExsrKylHuOxoj3W0RERBROVu+3Gk2wy5dKn5yczJsvIiIiCpvGPHyP91tERERUHwLdbzXOghJERERERERERNQgMdhFREREREREREQNBoNdRERERERERETUYDDYRUREREREREREDQaDXURERERERERE1GA0mtkYw23P4RJ89fMhNHE70MTtRKLbibbNEpDdokmjnpWJiIiIiIiIiKg+xUxml8fjwd///nd06NABCQkJ6NSpEx5//HEIISLdNQDA978V4W+Lt+Dehd/jtv+3ETf8Zy3O+9cXOPPJlXj1q93weKOjn0RERESNxTe7DiFn2gqc+eRKbNxz1LTdW2v34OKZq5FfVFqPvbNm456juGjGKny582BQ2837ejcuefZLHDpRJl3/2IfbcO1Leaj0eJVlQghMeOtbTJz/raZthceLa1/Kw+NLtmmWF52swKWzv8RLq3YBAPYfO4WLZ67G2+v2Km1+PFCMi2aswrItB5Rla345jItmrMKaXw4DAD7bVoCLZqzClt+L8MH3+zH836uw6+AJAMCba6quTUFxKeau3oURs75E0ckKzFj+E0Y+/zVOlXsAAI98sBXXz12jOR71cY2dtw4PvPu95fNHRESxLWaCXU899RRefPFFPPfcc/jxxx/x1FNP4emnn8bs2bMj3TUAQFrTOAzvkY6zu7TE6e1S0SUtCW6nHfuLSvHYkm24f9H3UROYIyIiImoMPttWiANFpfj92Cl8vr3QtN3fFm/B9vzjeGrZ9nrsnTU3vLIWOwtP4M//WRfUdo9+uA0/HijGrBU7petf/Xo31u4+gtWqINqRknJ8tPkAlvxwAMdOlivLV/90EGt3H8F/vtqt2cfLX/6CLb8XY9rHVeftiaU/Ynv+cUz572alzcT532Jn4Qnc/mZNAO26uWuws/AErpu7BgBw6xsbsLPwBG77fxtx99vf4aeCE3jg3R8AAA+9X3Ntnli6HVv3F2Pul7swa8VObNp3DO9++xsA4LVvfkXeL4eRVx1AU9uefxyf7ziIdzb8FtQ5JCKi2BUzwa5vvvkGV1xxBUaMGIH27dvj6quvxvDhw7FunfyDv6ysDMXFxZp/4TS0YwvMvXEg/t8tQ/DfO8/E8snn4oeHh+Pxkb3gsNvw3+9+x4L1+8LaByIiIoo9VrLXhRCYOnUqWrdujYSEBAwbNgw7d2qDGEeOHMHo0aORnJyM1NRU3HLLLThx4oSmzQ8//ICzzz4b8fHxyMrKwtNPP23oz6JFi9CtWzfEx8ejd+/eWLp0aXgOvB54VefQa+FLR1+WUDQ5VVG3PpUG2L7Soz5HNcvVp6vCIz93+n3Lzt+JskoLvTS2LdFtV1ZRk7FVXlnzuKJSm8klG02hXsYvn4mIGoeYCXadccYZWLFiBX766ScAwPfff4+vvvoKl1xyibT9tGnTkJKSovzLysqqz+4CAOJdDvx5aDbuz+0KAHh59S/8gCUiIiINK9nrTz/9NGbNmoU5c+Zg7dq1SExMRG5uLkpLa4bdjR49Glu3bsXy5cuxZMkSrF69GuPHj1fWFxcXY/jw4cjOzsbGjRvxzDPP4JFHHsHcuXOVNt988w2uv/563HLLLfjuu+8wcuRIjBw5Elu2bKmfkxFi6iCHh/dgUc9vmVvVOn/1cGXrhEkQj4iIGq6YCXY9+OCDuO6669CtWze4XC70798fkyZNwujRo6Xtp0yZgqKiIuXfvn2Ry6r689BsJLod+OVQiTS1moiIiBqvQNnrQgjMnDkTDz30EK644gr06dMHb7zxBvbv34/3338fAPDjjz9i2bJleOWVVzBkyBCcddZZmD17NhYsWID9+/cDAN566y2Ul5fj1VdfRc+ePXHdddfh7rvvxowZM5S+PPvss7j44otx//33o3v37nj88cdx+umn47nnnqv38xIKXk12XAQ7QpZYjHVZbucjoHofBNknIiKKTTET7HrnnXfw1ltvYf78+fj222/x+uuv41//+hdef/11afu4uDgkJydr/kVKYpwTl/drAwD46IcDAVoTERFRYxIoe3337t3Iz8/HsGHDlG1SUlIwZMgQ5OXlAQDy8vKQmpqKgQMHKm2GDRsGu92OtWvXKm3OOeccuN1upU1ubi527NiBo0ePKm3Ur+Nr43sdvfouGxEsdbCLkwUFpg4KWRn2GSvUh9KQjouIiMw5I90Bq+6//34luwsAevfujT179mDatGkYM2ZMhHsX2BmdWuDtdXuxZX903QQSERFRZD344IMoLi5Gt27d4HA44PF48M9//lPJXs/PzwcApKena7ZLT09X1uXn5yMtLU2z3ul0onnz5po2HTp0MOzDt65Zs2bIz8/3+zp606ZNw6OPPlqbw64XXlU5JwY5LNAEher/5S0PT/ST2iXbhfpQ+D4gImocYiaz6+TJk7Dbtd11OBzweo3TC0ejXm1SAFRNv1whmRKZiIiIGqdgs9ejSTSVjZBR1+nyMrMrIE+QBf1DzfowRm1L9bXVrwOgm+yhtr0jIqJYEjOZXZdddhn++c9/ol27dujZsye+++47zJgxAzfffHOku2ZJdvMmaBrnxPGySvxceALdW0duWCURERFFj0DZ6xkZGQCAgoICtG7dWtmuoKAA/fr1AwBkZGSgsLBQs9/KykocOXJE2T4jIwMFBQWaNr7ngdr41uvFxcUhLi6uNoddL7SzMUawI1HGbMIkb4SH+/krUK9J7NK1U/fVb5F7MNhFRNRYxExm1+zZs3H11VfjzjvvRPfu3fGXv/wFt912Gx5//PFId80Su92GHplVAa4tvxdFuDdEREQULQJlr3fo0AEZGRlYsWKFsr64uBhr165FTk4OACAnJwfHjh3Dxo0blTYrV66E1+vFkCFDlDarV69GRUWF0mb58uXo2rUrmjVrprRRv46vje91Yo2XszFKmdUv05wvC21Cz88wRj+t1NdWXqC+BocxEhE1DjET7GratClmzpyJPXv24NSpU9i1axf+8Y9/aIqsRjtfsGtH/vEI94SIiIiihS97/aOPPsKvv/6KxYsXY8aMGfjjH/8IoKpW0aRJk/CPf/wDH3zwATZv3owbb7wRmZmZGDlyJACge/fuuPjiizFu3DisW7cOX3/9NSZOnIjrrrsOmZmZAIA//elPcLvduOWWW7B161YsXLgQzz77LCZPnqz05Z577sGyZcswffp0bN++HY888gg2bNiAiRMn1vt5CQV1XMYsm6kxMotXWZm9MpzBIv+ZXTbTdpouyWp2qd8HtesaERHFmJgZxtgQtElNAAAUHi+LcE+IiIgoWsyePRt///vfceedd6KwsBCZmZm47bbbMHXqVKXNAw88gJKSEowfPx7Hjh3DWWedhWXLliE+Pl5p89Zbb2HixIm48MILYbfbcdVVV2HWrFnK+pSUFHz66aeYMGECBgwYgJYtW2Lq1KkYP3680uaMM87A/Pnz8dBDD+Gvf/0runTpgvfffx+9evWqn5MRYh7OxihlFrDyWMjs8ggRdX9ABL62DXOWSSIiMhdtn1UNWqumVTUtDjLYRURERNV82eszZ840bWOz2fDYY4/hscceM23TvHlzzJ8/3+9r9enTB19++aXfNqNGjcKoUaP8tokVgjW7pMwCPlZqdoUzVlTrAvWaYYyyAvWqx5wnioioUYiZYYwNQaukqmBX4fHSCPeEiIiIqOFTZ/wwo6eGaT0u09kYrWXI1fUM+y0ub1KgXgBQT84u24f2SPg+ICJqDBjsqkdpyczsIiIiIqovmkwlpnYprNTsstKmPskytnwC9UloMtZC1SMiIopmDHbVo1ZJVXU1iksrUVrhiXBviIiIiBo2r5fDGGXMAn9WanZ5wzgM0F9Ay1/WV8DZGE0z1oiIqKFisKseJSc44XZWnfJDJ5jdRURERBRO6sCGh0EOhZV6XOZ1vSI0G6OfPgTM7FI/5tuAiKhRYLCrHtlsNlXdLga7iIiIiMJJnZwkGOVQaM6LZrkqA8okg8tf0NBfyS0r/JbsUtfpUnXBhsDDFNXHxfcBEVHjwGBXPeOMjERERET1Q5PZxXGMCm1QS36OzOp3hTezy88wRlUoTN8Ddb9lBejVgTu+C4iIGgcGu+oZg11ERERE9cNKwfXGyDyQVfPYY1LnKpw1u6zyN4xRFoszn2WSiIgaKga76llaUw5jJCIiIqoPmkwlRrsUmkL0JoEgYZIVZ17vq+7n12/NLpNhjIA2ACfrn4dBTyKiRofBrnqWnOACAJworYxwT4iIiIgatvoafhdr1KdCmA5plLc3Gw4aitPrL9ilfa3gMrsEa3YRETU6DHbVsyYuBwDgVAWDXUREREThpAneMMah8JjU6TLL8tLUxDI5j+Ge7dLfkFSzfivrTQJ3RETUcDHYVc8S3FXBrpIyT4R7QkRERNSwcRY+ObPAkTDJhLNS8yoUmXM2P/MxmmXpCegzt/z3jRl+RESNA4Nd9SwxzgkAOFnOYBcRERFROKmzuRrTbIyB6pNZmo3RpA6WWQZXKArX+xvGKEyCckIIbeaWdDbGwJlpRETUsDDYVc+auDmMkYiIiKg+iEaa0RPoWM2ypMwf17Q3y5ALTWaXObO6W14hAs4WydptRESND4Nd9SzBxWGMRERERPXBLFOpoQtUP8tSnS6Tml0ek/MYippdNl1ql1mwUh288ngDzxbJ2RiJiBofBrvqmW8Y4ykOYyQiIiIKKysZPQ2xllegQzILHHk1hdzNM6mkrxmKYYz6faozytTLoe2PWbua/Wi3JiKiho/BrnrmK1B/ksMYiYiIiMLKa5LBpNYQa3kFOiZNPS6Tc6TO4DKbvVHzmrrzG4ogollGljZAJzTtZK+rzfyqc7eIiCgGMNhVz3w1u05yGCMRERFRWJllMGnb1FNn6lHgml3yTC0rwwbNsqj0r1mrWJcutctaPwNfZ9bsIiJqfBjsqmeJbs7GSERERFQfNJlBJlGthhj8CFSfzEo9Lq9JHSyzGl/681ubGl76YYxmwyorPdr+BJptkbMxEhE1Pgx21bMEZTZGT8BpoYmIiIio9oSFjJ4GGewKcEzaelzy7azM2KjdNrg+yOgL1JvNsujRBK9EwMwts/4TEVHDxWBXPfMNYwSqAl5EREREFB6Wak01wC8fPSYBKWW9V97WfDbGmvZek3Oqz+SqzeyX+swuzXGoBk1W6voQzGyMjHURETUODHbVs3inA74vrTiUkYiIiCh8zLKQtG3qqTP1SHPcAdbXpX6Xv2GMtcvs0j5Xz/Co3r2+4HygYvhmNceIiKjhYrCrntntNiS4qocyMthFREREFDZWZmNsiGUlzGZblC3zmtTs8pi2CRwoA2pXs0vPbJbFClVHvUKYZqcpywJkfhERUcPDYFcE+IYylpRXRrgnRERERA2XlVn4GmLwI1CNKu15MdtO3kaT8WWSeQVos7Ks0nfVrD/6QJymr5LXZc0uIqLGh8GuCGjCGRmJiIiIws5KrSZNIEc66C/26If5GdZbmFHRLCvO9HEIZmPUb2GWUVap65tmtkXJfj0B1hMRUcPDYFcE+DK7OIyRiIiIKHyEn2CMj6Yoey2ykaKROs4kCzqZBrhMsryEacaXto36lWqTQaXfRv1alaqULe1sjIEzt9SLAtX3IiKihoHBrghI4DBGIiIiorALNEuffnlDCYSY1bryMQtwWcna8pf9ZdbOX1+067XP1X2o9Kgzu7SBL23wy/9sjA2wRBsREUkw2BUBidXDGJnZRURERBQ+2lpO8iiHx2S4XizzBshoMwtwmWdwyfetr5Vlts7fMjV9oMqssLw+iBlotkUrs3ISEVHDwmBXBDCzi4iIiCj8zDKY1IRJUCeWBTpus4w30wwukzb62l9ek8ww2bY+ZgE2/etWeOSP9a8rDbJxNkYiokaHwa4IYM0uIiIiovALFHwBzAM8sSxQRpt2RsXA9bjM2gh9sEs9O6M0o8x/lpm/ml2aIJvmmgU7+2TDuMZEROQfg10RwNkYiYiIiMIvUO0qIHCgJBYFqlVmVsPKbPZDs9kb9QEos3Z++6IrNm+2rtLksb5WmOwKajLKGsYlJiKiABjsioA4Z9VpL69sIFP+EBEREUUhs8wgbRv/9a1ikTajTba+5rFZYEw7g6F83/q6Xv6GJJovM3997WyaXuljrxABZ1sM1C8iImp4GOyKAKfdBgCoaCjzWxMRERFFISs1uwIVN49FgWaY9Hrl663MxuivrpdZO3/LzAJsXqHNFDPL7PJ6A88CGSjjjIiIGh4GuyLA6ag67RWyr9qIiIiIKCTM6k6pxdJsjGZDMfUCZbSZ1TIzz+Cy0MarnxXRf4aVrK/611TXADMNuAld/wyvoAtoStYTEVHDw2BXBLgcVZldlV5mdhERERGFi5XC5LFUs8vqMMvgCrarHptmbcn7EOphjOrVQhfEqvTIH+uHMQYzVJKIiBqumAp2/f7777jhhhvQokULJCQkoHfv3tiwYUOkuxU0p52ZXUREREThpM/kMsvaCjSDYDSx2j1t0CrQerNC9CbtTQJH+mGHvqCYMAmUyfataSuE32L4Zq8baNgmU7uIiBoHZ6Q7YNXRo0dx5pln4vzzz8fHH3+MVq1aYefOnWjWrFmkuxY0l7M6s4s1u4iIiIjCQp/BY16zK3aKl1vNSgqU0WYesKppY1a43t9jTeCwep1+aKM+GKWdjVG3P1VT9YiISl0wz2yYpey4mNlFRNQ4xEyw66mnnkJWVhbmzZunLOvQoUMEe1R7rurMrspov6MiIiIiilH6TC7Tml0xNBuj1UBNoDpk2mNW7d9C4XqzgJjHK6SBMH19MP0pNuur16tdV6l5La9mG7PMM9lrRPklJiKiEImZYYwffPABBg4ciFGjRiEtLQ39+/fHyy+/bNq+rKwMxcXFmn/RwungbIxERERE4aSPeZgFivTZRNHMajAumNpZZsdvVrjeLHCkr7HlW6dfpj/HFX6GJ2oCbh554EvoAmiyMySEkD4mIqKGK2aCXb/88gtefPFFdOnSBZ988gnuuOMO3H333Xj99del7adNm4aUlBTlX1ZWVj332JxvNsZK1uwiIiIiBK5LKoTA1KlT0bp1ayQkJGDYsGHYuXOnZh9HjhzB6NGjkZycjNTUVNxyyy04ceKEps0PP/yAs88+G/Hx8cjKysLTTz9t6MuiRYvQrVs3xMfHo3fv3li6dGl4DjrM9IEhfQH1mnbqNtF1b6bvr9WsJG2GlP8aVp4gM7iEyb49XiGtq6UJYOnaANqyHup7Y/3+1AEuf+2kmV0xNFSViIhCI2aCXV6vF6effjqeeOIJ9O/fH+PHj8e4ceMwZ84cafspU6agqKhI+bdv37567rE5l52zMRIREVEVX11Sl8uFjz/+GNu2bcP06dM1dUmffvppzJo1C3PmzMHatWuRmJiI3NxclJaWKm1Gjx6NrVu3Yvny5ViyZAlWr16N8ePHK+uLi4sxfPhwZGdnY+PGjXjmmWfwyCOPYO7cuUqbb775Btdffz1uueUWfPfddxg5ciRGjhyJLVu21M/JCCFZ0ENezyl6AyGG7DTLszGqHweq2SV/PbOhgf5qeQnNvoRxn7o2gHbCJn3WmL8hk9p21mt2MbOLiKhxiJmaXa1bt0aPHj00y7p374733ntP2j4uLg5xcXH10bWg+TK7OBsjERERBapLKoTAzJkz8dBDD+GKK64AALzxxhtIT0/H+++/j+uuuw4//vgjli1bhvXr12PgwIEAgNmzZ+MPf/gD/vWvfyEzMxNvvfUWysvL8eqrr8LtdqNnz57YtGkTZsyYoQTFnn32WVx88cW4//77AQCPP/44li9fjueee870C8ZoJftO0SME7LDp2vnPgookQ90xqwXqTQJDsmVmbS0VsdcFsmT1z/RBKv0xaQvP1zz26mZjtNou0GyM0XWFiYgoXGIms+vMM8/Ejh07NMt++uknZGdnR6hHtedyMLOLiIiIqgSqS7p7927k5+dj2LBhyrKUlBQMGTIEeXl5AIC8vDykpqYqgS4AGDZsGOx2O9auXau0Oeecc+B2u5U2ubm52LFjB44ePaq0Ub+Or43vdfSiuUZqoIymmmX+10eSvj+yYvOBtpNtos+2kj3WFq4327d5hpXVml3qIYn6a2EWZDO2k6+T9TnarjEREYVHzAS77r33XqxZswZPPPEEfv75Z8yfPx9z587FhAkTIt21oDntzOwiIiKiKoHqkubn5wMA0tPTNdulp6cr6/Lz85GWlqZZ73Q60bx5c00b2T7Ur2HWxrdeL5prpMoCQ2bZXv62iSR9f612L7jZGOVZXmbF6s2GNHq8QhoU0wea9NlzZhM26WtxmbFUs0vTr4C7JCKiBiBmgl2DBg3C4sWL8fbbb6NXr154/PHHMXPmTIwePTrSXQuabzbGSs7GSERE1OgFW5c0mkRzjVTrmV3qYE9YuxQ0Q2ZXmGt2mW0nzDK+/GZiCZM22r5UmhyTENaCe/qJB+SZbP6HORIRUcMTMzW7AODSSy/FpZdeGulu1FnNMEZ+2BIRETV2geqSZmRkAAAKCgrQunVrpU1BQQH69euntCksLNTso7KyEkeOHFG2z8jIQEFBgaaN73mgNr71etFcIzVQFldNu+gd4lbrml1BzMYYbAaX2b69IvBsjLJsrbpmdlXN8FjzXDrjZoBgGBERNTwxk9nVkPiGMZZXRtnXh0RERFTvAtUl7dChAzIyMrBixQplfXFxMdauXYucnBwAQE5ODo4dO4aNGzcqbVauXAmv14shQ4YobVavXo2KigqlzfLly9G1a1dl5secnBzN6/ja+F4nlviCMnZVPXohufWK5ppd+v5azTwLNMNknTK4TANfxpkd9YEn2bJKk7Ie+kwxM/5qe0n7H2XXmIiIwoPBrghwMrOLiIiIqgWqS2qz2TBp0iT84x//wAcffIDNmzfjxhtvRGZmJkaOHAmgKhPs4osvxrhx47Bu3Tp8/fXXmDhxIq677jpkZmYCAP70pz/B7XbjlltuwdatW7Fw4UI8++yzmDx5stKXe+65B8uWLcP06dOxfft2PPLII9iwYQMmTpxY7+elrnxZQb5ZsIHghvRFg9pmdgWuYSU/ZvVyYZLlpZ2NUZsVps8G02dmBZqNUc1qsMujK3ovJPMtamZjjLJrTERE4RFTwxgbClf1TRdrdhEREZGvLumUKVPw2GOPoUOHDoa6pA888ABKSkowfvx4HDt2DGeddRaWLVuG+Ph4pc1bb72FiRMn4sILL4TdbsdVV12FWbNmKetTUlLw6aefYsKECRgwYABatmyJqVOnYvz48UqbM844A/Pnz8dDDz2Ev/71r+jSpQvef/999OrVq35ORgj5ghpOuw3l1csCDmOMsmhXbWdj1My2KDkmTSDLQuDLbKij+nWEpGaX/qVly8wmbKqauVG6SsP4urJ9Re9QVSIiCg8GuyLAF+zibIxEREQEBK5LarPZ8Nhjj+Gxxx4zbdO8eXPMnz/f7+v06dMHX375pd82o0aNwqhRo/x3OAb4gjIOmw02W1VgRp7ZpX4cXfdm+kCV1eLqZplbynqzrK0gM7609biMATL9+ZTNxmg2jDG42Ri1ryFrU9P/gLskIqIGgMMYI8Bp9w1jZGYXERERUTgoNbvsNjhsVfdegYrWW53tsL7ou2N1UIBZJpZsv6bF582GLvppr8kokwQXZcv83Q9bq9mlCwIGqNklG+ZIREQND4NdEVAzjJEftkRERETh4MsgstsAuy/YJQmeqAMl0Zb1E4rZGGXZYGY1rDyaYFXgjK9AszFKa3YZZmM0PyYroyC8un3GWl02IiIKDwa7IsBXoN5sqmUiIiIiqhtfUMNht6F6Imxp5pYmQBNl0S79kD+rmWdmmVg16+XHrC8wL1tuFjjyemtXs8tfDVsr9W31+2TNLiIiAhjsighX9R0XZ2MkIiIiCg9fsMZmsymZXbI4R1TX7NL1x2r3AtbsMqlxZSnjyyQ4qJ8VUVafy+s1HlOFn/thf+vUfdBmsknasGYXEVGjw2BXBPgyuziMkYiIiCg8fAEQh62mZlfg2Rjrp29WGWp2WZ6NUR7Aqtmv2RBFeWaXMMkEE7rH2kwvWc0uY9H6umZ26ScekA9VVT/m/TcRUWPAYFcEKMMYo+2OioiIiKiBUArU24DqWJeFek7RFQjRD0G02r/a1rAyy/gyy4zyV6PLI4QhOOcRxppd/r78tfLFsP51ZcGsQJluRETU8DDYFQG+YYxCRN+sP0REREQNge8Wy263wWH3zcYoCYQEmLkwkvSBG6tZSZoAVoBgl1mgyKwOlmmgTNJX/UvLlvn78tfKF8P6ml2yMxSoYD8RETU8DHZFgC+zC2CReiIiIqJw8AVx7KqaXfLi5TWPhYiuYIghM8ribWOg2QdNM7jMCtF75cEx9XJ9FpbHa/xSV7asrpldXq8wHYopW8bvmYmIGgcGuyLA5ag57SxST0RERBR6vqBV1WyM1TW7ZPWrDEMFw983q/SJTVaHMZoFqnyEWVDLNIMrcBt9fS1Zfa5w1OzyGmp2ydvI+kxERA0Xg10R4LTXZHZZ+RAnIiIiouDUzMZYVbcLCJz1Y9YmUgx9sxiJM8vcqllvErwyyeDymGV5qZbrZ06smo1R+7perzHYFYrZGLVF8yVtoimCSURE9YLBrghwqIJd5Qx2EREREYWcUrNLNRtjoMCP7HkkGQNxwW/nlQzNNAtweU2CRurHZllUhswuSWCrKgtL29e6z8YoAs62aJbJRkREDReDXRFgs9ngqq7bZaUWAREREREFxxfUcNhssPmp2WUsoh7unllnCMRZHcao206/mdkQRf3sitLHJlleFfqaXUJSc0wyG6N+O6vr1H0LNPukxyRAR0REDReDXRHiq9vFYBcRERFR6PmCHjYbUD0RtjRrSxaQiRb67lqv2aV9rj8ms6L05hlcgdtU6sYsVmVc6YNukppdfmZc9Leupg/m/VPaqHYTRZeXiIjCiMGuCPHV7bIypTIRERERBccX8HHYa4Yxyoa4RXPNLsPwQ4tpSYGOSTuMUd7OLIBkVu9LH0isKkZv7Jf+9PobNmplSKl+n/IC9RzGSETU2DDYFSHM7CIiIiIKH19gyG6zwW4LYjbGKBrnZgwgWdvOWNhet95k2J/ZcD/ZMEH9eTIMY/TK6qEZl9V1GKNXN4xRIHBAk4iIGj4GuyLEWV2zq4IF6omIiIhCzhfgsNttsNvNa3YZs4/C3TPrDMMRQ5bZJQ92BQpwqR8bhiPqC9RLhizKltW1QL2lYYwmBfmJiKjhYrArQpzVxSMq+YFLREREFHIeJbOr6h8Q+7MxyoZhyuhjRIa6ZJri86rXU2dImQXEvPJ9Vkgy5GQZZfpj0m9ndZ2PRxdAk11jbSZbwF0SEVEDwGBXhNTMxsjMLiIiIqJQU2p2qYYxygIhsiLq0ULfX6vF8w3HpA86CXlbS0Maq5fru2LM7JLXCtMHwOqa2SV0tcHkmV3+hzkSEVHDw2BXhDira3ZZqUVARERERMFRhjEGqNkVzbMx1rZmlyFbzeJsjJqhi6o4k0eS8aV/DX0dWo8Q0nOrX+avfq2V2rYeXc0uafaeSeCOiIgaLga7IsQ3G6OVKZWJiIiIKDg1NbuqZmQEAtdzkj2PJH1/rc/GqH/up2aXJpBl0kYSEAs0HFEIIc2a0y+r6zBGSzW7VLfb0ZS5R0RE4cNgV4RwNkYiIiKi8Kmp2WVTanbF/myMtSxQ76cumWyIon4fsppXgYYjVmVcIeCyug5j9O3XJ9BsjIx1ERE1Dgx2RQhnYyQiIiIKH19Qw6GZjdF/IMSsTaQYanbVejZG7fpgMrj025vPxiipzyWr2RXiYYz6drJBE4EK2BMRUcPDYFeEuDgbIxEREVHY+II1Nk2BemO7aB7GaJyN0dp2gTLCzGpcmQ1plGV8GWdj1BeoF9KsOePwR/Mvfv2tM2snn3FT3S9LuyQiohjHYFeEMLOLiIiIKHx8QQ+HrWpGRvUyNUMx9yiKhui7YrV4vmE7P8Evr0kgyKMZ+he4Zpchs8srJIFEY7Ar1Jldsi3U/edsjEREjQODXRHC2RiJiIiIwkc9G2N1rEsa7JIVUY8Wta7ZZSgWr1tvaeii/yGN+qQr/Re4prMxBtjO6jqzdrLrpw3cWdolERHFOAa7IsRdndlltfAmEREREVnnC8rY7TZlNkZZ1pYsIBMtAhWat7qd/pisZHCZZXx5zTK7JAE22TDMQNtZXWfWTjpUVb0+ijL3iIgofBjsihBndc0uK1MqExEREVFwamZjhFKzSxbHMgy1i6LvIQMVmjdjDG6ZD9UUoibIJavNZai75WurWy6bjVE2C6R+WShmY6wMkNmlfkneeRMRNQ4MdkWIk5ldRERERGHjC3qoZ2OUZXaZBXOigT7wZrWemGHYoiHrSh5E02R8mWRw+Spw6F9DX5qjqj4XAi7zV9LDarkPdTv5JATy4ZlERNRwMdgVIa7qml1WC28SERERkXXa2RirlskCHcbsqei5NwuUoWW6nSGAZ22/XslwQH1bWRYYAFRKZmM09MNrrOOl387qOrN2gSYhiKLLS0REYcRgV4Q4q++6rE6pTERERETW+eIbDpstwGyM+ufREw0xZmDVsmaXIegE6XpZBpT+Ja3PxijPINMvC/VsjDLql4ymCQiIiCh8GOyKECczu4iIiIjCpmY2xqrsrqplxnZmQ/qigT4QZ7VvgbLVZIXjq17PGOwyyxLTD420Phuj/+2srjNrJw1oaoJ4lnZJREQxjsGuCPGl00fTt4dEREREDYUS7LLbUP0do6XZGKNpGGOgDC3T7QxBsgAF6yVZXGYZXDWzMWpfQz9zotWaXSGfjVESH2PNLiKixofBrgjxTYHND1wiIiKi0PMl+9htNtVsjP5n6gOMGUuRZMzAslizK0C2mjFby1iHy/fQLHBmnI3RGBQzFP+XzsYY2mGMAsZzphnGaGmPREQU62Iy2PXkk0/CZrNh0qRJke5Krdn91I4gIiIiorrx3WM5bMHNxqgPFEWSoW8WS73qg2L64zabrVF9X2o+G6N8ub4OrVfIMsoCb2d1nVk7YzaZ9jlrdhERNQ4xF+xav349XnrpJfTp0yfSXakTh3LTFeGOEBERETVAvgCO3a7+klHSzqR+VTTQJzbVdjZGQ/DLJPNLHVuSZXtV7UveF0Mhe0l9Lo9kNkZ/h2T1WvgrQB+oOD8RETVMMRXsOnHiBEaPHo2XX34ZzZo1i3R36oTDGImIiIjCxxfjsNtscNh8yyQ1uyQBmWhR+9kYtc/Nhi3q18tqW5m39d8H/fBBs2WhZsha0wfXOJCRiKhRiKlg14QJEzBixAgMGzYsYNuysjIUFxdr/kUT3zeM0XRDRURERNRQ+DKI1DW7ZMEiWRH1aBEoSGVGNnxQ81yX3SQkWVyybC/1vgPdw8qyuGTZXqEWeCbKsL48ERFFCWekO2DVggUL8O2332L9+vWW2k+bNg2PPvpomHtVe/5mBSIiIiKiuvEFcBx2dc0uY7tAwZFIMmZoWd0uUMDHGITSZ10Fmo0xUO0rqzW7Qi1Qza5our5ERBQ+MZHZtW/fPtxzzz146623EB8fb2mbKVOmoKioSPm3b9++MPcyOA4WqCciIiIKG1+wxmYD7H6GMRqDOWHvmmW1no3R4rDFmvXyjCchycTyPQ30ha3V2RhDTb93Qz95601E1CjERGbXxo0bUVhYiNNPP11Z5vF4sHr1ajz33HMoKyuDw+HQbBMXF4e4uLj67qpl/mYFIiIiosbpySefxJQpU3DPPfdg5syZAIDS0lLcd999WLBgAcrKypCbm4sXXngB6enpynZ79+7FHXfcgc8//xxJSUkYM2YMpk2bBqez5lbviy++wOTJk7F161ZkZWXhoYcewk033aR5/eeffx7PPPMM8vPz0bdvX8yePRuDBw+uj0MPOd8tlsNmU2qlvvLlL3hv42+adgeKSjXP//b+Zjyx9Md66aM/bqcdKQkuzbK31+3F8m0FfrdrmRSHQyfKNMvuX/QDmrir7pU7tExEWaU2onfd3Dyc3s5YD/eC6avQIzNZs+zgiTJcMP0LdGqV5LcfK7YXGl5nwfp9GNy+ud/t6ur7fcdwwb++UJ73bJOiWf/f737Hpn3Hqp7YgD/2a4Nv9x7FnsMnAVTdo18zsC1Wbi9EYXHVeXQ6bLh2UDss3XwAR0vKAQBxLgeuGdgWi7/7HSdKK5EY58SVp7fBog2/obTCg+QEFy7vm4l3NuxDefV5aNk0DsN7pGPh+n3weAUyUxNwVpeWWLRhH4SoujZ92qbif5t+BwD0apOC1qnxWL616pqf0bkFPF5g7S+HAQDDe2Zg39GT+HF/VbmWkf3bYNO+Y/j1UAlsNmDUwCx8ufMgDhwrhcNuw7WDsvDp1gIcOlEGl8OOawZlYckP+1Fa4cWoAW3x/qbAx5IU58TFvTLwzoZ9qPQItGoahwu7p+GdDb+hdUo8zujUEos27kP7Fonol5WK97+rOpYemclo0ywBy7cWYFD75oh32fHlzkMAgAu7p+Hg8TL88FsRRvRpjZ0FJ/BT4XFc2b8NNuw5in1HTuLqAVn46mfjsRw7VY5rB7XDRz/sx8lyD0YNzMIH3+9HRaUXowa2xX+/rXp93/G4nHZc3jcTi6qvS/NEt3I8zZq4lWPJSI7HmZ1rjqV/VioWb/odXdObolOrJCzdfAD9slLRLNGNz7cX4szOLVHp9WLtL0cwrEc68otKseX3IlzaNxPbDxTj54MncNXpbbFu9xH8dvQkRg3MwuqfDqLweBmuHZiFL34qxPld07BsSz5OlFVi1MAsfPj9fpRV1lwbrxC46vS2eHfjb3DabbiiXxu8s2EfEtwOXNonE++s34fkBCdye2Zg4fp9aJHkxgXd0vDlzkNVx7JhH9o1b4IB2c3w3+9+x2lpTdElPQkf/XAAfbNS0TLJjRU/FiKnUwsIAPFOB46dKsemvcdwSe8M7D5Ugu0Hjte8zw6XYNSALOT9chhndGqBVTsO4tCJMuXaFJ2qwDWDsjTXZvm2fAzvkYH3N/0OIaqui+94Lu/XBos27EMTtwMj+mRixY8FuKBbmum1Wbf7sHIsnVsloVtGUyz54QB6t01BWtM4FJ2qQILLgS93HsI5p7XCibJKfLvnKHJ7ZWDvkZPo1CoJPx4oxq7qa7Ph1yMY0rEFvtp5CPnFpbhmYFus+LEQR0+W45qBWVi5vRAXdk/Hkh/241S5B9cMzML/Nv2OSq/A1QPa4pOt+cjtmaF5ny3flo+LemRors0XOw7i3NNaYeGGfcqxvLux6tqc3q4ZNv9ehG6tk7Hk+/1VvwNS4nG4pBxJcU6s/ukgzjmtFU6WVyK1iRsFxaXY/FsRLu3TGtvzj+PngydwZf822LjnKAZ3aIGvf645ltU/HcJ5XVtprs1n2wpwUY90/E/1M7NsSz4u7pWheZ99Wn0ci1S/Az7fUfWeXbh+H1omxeG8rq3w9a7DKCmrxNGScvz72n7om5Uaot/stWMTMTD/7vHjx7Fnzx7NsrFjx6Jbt274v//7P/Tq1SvgPoqLi5GSkoKioiIkJycHbB9us1fsxPTlP+H6wVmYdmVszyxJREREdb/XWL9+Pa655hokJyfj/PPPV4Jdd9xxBz766CO89tprSElJwcSJE2G32/H1118DqPoCsF+/fsjIyMAzzzyDAwcO4MYbb8S4cePwxBNPAAB2796NXr164fbbb8ett96KFStWYNKkSfjoo4+Qm5sLAFi4cCFuvPFGzJkzB0OGDMHMmTOxaNEi7NixA2lpafVyDkLpnx9tw8tf7sb4czqiRaIb0z7e7rd9x5aJ+OVQST31LjhOuw2VtfiCNNB2DrtN+sVrvMuO0gpjipvbaVcCN8G8Zm37T0REsem9O3IwIDs8X25YvdeIicyupk2bGgJaiYmJaNGihaVAVzRiZhcRERH5qGec/sc//qEsLyoqwn/+8x/Mnz8fF1xwAQBg3rx56N69O9asWYOhQ4fi008/xbZt2/DZZ58hPT0d/fr1w+OPP47/+7//wyOPPAK32405c+agQ4cOmD59OgCge/fu+Oqrr/Dvf/9bCXbNmDED48aNw9ixYwEAc+bMwUcffYRXX30VDz74YD2fkbqr8FTdYzntNow/pyPO7NwSpyo80ratkuLQplkCNv9eFBX3Zks3H8C8r39Vnt8wNBvXDMxCSXml3+2e+ng7Nuw5qjyfdX1/pCfHK8MY73n7O+xXZbK9f+eZKK30YPQrazVBrC/+cj62HSjCza9tUJY1a+LCsknnYNWOg3jgvR9M+zC0Ywv0b5eK2St/VpZd1jcTdpsN7337m+l2ofbyjQMx7o0N0nVJcU48PrIn7l34vbKsbbME3HxmBzy2ZJuyrHebFJzftRVmqY7l7C4t0aFlIt7I034R789t53bEhl+PYqPq2hARNWROe+QrZsVEsKshcvgplEpERESNi3rGaXWwa+PGjaioqNDMRN2tWze0a9cOeXl5GDp0KPLy8tC7d2/NsMbc3Fzccccd2Lp1K/r374+8vDzDbNa5ubmYNGkSAKC8vBwbN27ElClTlPV2ux3Dhg1DXl6eab/LyspQVlYzZC6aZr+urC6+5XTYYbPZ0Es3nE1GNpQvErbnH9c8d9pthuGEMi2S3JrnCW4HBmTXHFNinPbWPyXBhd4tUuB2aDO2Wia5Dd/IOx12pCfHo0+W//PodNjQOU07xNFpt6FrRtOA/Q+lwR3MMwriXXb0bZuqWdY03oWeunPcLNGNLunafqcnx6N9i8Sg+tK5VRJ2H4zOrEEionBwOmyR7kLsBru++OKLSHehTlignoiIiAD/M07n5+fD7XYjNTVVszw9PR35+flKG3Wgy7fet85fm+LiYpw6dQpHjx6Fx+ORttm+3Xz4XzTPfu3L0HLZI3/DHSx9n50Oa9+Q69u5dN+s69f7/hjR/1HisNvg0i3z9SnQt/VOux0uw+sYl4Wby1F1DL4MP01/JH10OWyS8yc5Dw7jMj2bDZqZLV2S49e3CbQPIqJYEg2ZXZHvQSPFYYxERERUmxmno0k0z36tDGOs5yBLKBiCLha/ITcGyYyBGtl69R8lLocNNpvN8IeKr0/6fSS4tJNEuRw2OO3G19X3Rb+d1XVW2zntdtM/tpyS/jglgS2nQ3Ie7HbD9dH3Q/9c9nqBtvH3vC7byp6Hqm2w7eJdwf9sWn3N+t4XEWlFQ2ZX7H36NxC+a+/hVzZERESNlnrGaafTCafTiVWrVmHWrFlwOp1IT09HeXk5jh07ptmuoKAAGRkZAICMjAwUFBQY1vvW+WuTnJyMhIQEtGzZEg6HQ9rGtw+ZuLg4JCcna/5Fi8rqWhFWA0XRxBB0sfgNeaAgmSEIZTcGsJySZVX79mWB6QI9bn1gR5LZZbcbssz021ldZ7WdLMBWs84YCHOaLZMGwHSBK3eAYJck8GYIKvnZh81WNTmAjz5IZNg2yOehahtsO5fdbjiXtd1XbYRyX0Skpf+dHwmR70Ej5avZ5WVmFxERUaN14YUXYvPmzdi0aZPyb+DAgRg9erTy2OVyYcWKFco2O3bswN69e5GTkwMAyMnJwebNm1FYWKi0Wb58OZKTk9GjRw+ljXofvja+fbjdbgwYMEDTxuv1YsWKFUqbWFPhrSlQH2uMQReLmV0BgmRWhjH6HttsNuV+FVAFxvSBHn1ml90YZKrvzC6HvSo7zWzopCyLSzY8sWoYoz6AaAzm6fsRL8l20+9b38bfPlx2u2Z7t9MO9WWI1cwuWcZbbfdVG8zsIgqfaMjsitmaXbGOwxiJiIjIyozTt9xyCyZPnozmzZsjOTkZd911F3JycjB06FAAwPDhw9GjRw/8+c9/xtNPP438/Hw89NBDmDBhAuLi4gAAt99+O5577jk88MADuPnmm7Fy5Uq88847+Oijj5TXnTx5MsaMGYOBAwdi8ODBmDlzJkpKSpTZGWONL7MrNocx+h9+aLpdgCCZMcDjC2DZDcuq9mdT7lXNMrv0WUbSoX+Selj+hrBZHd5m1s6p1BeTn7eqjK3AwxOrsr2M2XH68xoo00qWIaZv428f+nPq66tvUgH9tsE+D1XbYNs5HXa4PAKlsD5jV22GPtbHvohIi8GuRowF6omIiMiKf//737Db7bjqqqtQVlaG3NxcvPDCC8p6h8OBJUuW4I477kBOTg4SExMxZswYPPbYY0qbDh064KOPPsK9996LZ599Fm3btsUrr7yC3Nxcpc21116LgwcPYurUqcjPz0e/fv2wbNkyQ9H6WFFZXbOrcQ1jlAezzPajBIU0wxhV2VwOO8oqtUHDQEGbqmGMxv4bMsLCOTxOqS8mP2+mdcWktcYCD3cMNIzRZTcGAAMNY1QHYvQBNpfDBpfdhnKz14+ZYYw2VAab2cVhjEQxIRqGMTLYFSHM7CIiIiIZ/YzT8fHxeP755/H888+bbpOdnY2lS5f63e95552H7777zm+biRMnYuLEiZb7Gs1qhjFG/oY7WPo+Wy5Qbwhu+c/scigZUCaZXeoAS3VbQ+0t6TDGwDMdhnt4nPr/hvWS4YnSWSTtxsCdbIbGwAXqjfvxt43dBrgd2muivS6+LDQPACDeGd3DGOOcZtfJDmeQfwtxGCNRbIiGzK7Y+/RvIHyZXZLZkImIiIiojmqGMUb+hjtYxqLoFjO7DMEt88wu36yLvsey19YMnTMJIOlrT0mH/kmG8em3s7rOSjtfv/0NY6yq66VeJpmhUTok0zjcUd+PeEO2m2QYpyGTSz1sUfsa+qL4+ppjrurjMe1PgOehaisjy5jzcVZnqAXD6nujvvdFRFpmmbX1KfI9aKRYoJ6IiIgofGqGMcbe7W6gDC0zZgXoZc+1gSztkLmafmgDKrK+GLOYZFlTtoAZYVbXWWnn67e/YYyAsVaZvo8uSUaWSxKgMWZD6fYjG8apr9GlKUivDWbp64npZ5PUB8OiKbNLljHn45LUSQuEmV1EsSEaJoeJvU//BoLDGImIiIjCp8JbndkVBTfcwQqUoWVGH1AxDoeUD1HU1+ny18Zm0wVWdBlKVQEMY/8D1fqyuk7NNLMr4DBGY/0xWeF5p2RIpmxZoJpdsswuf7Mv6uuC6Wdz1Geh6Yc5RlPNLn8zLtZqNkbW7CKKCY4o+OxlsCtCfNfewwL1RERERCHXoDK7rM7GKKmVpVlvEtQyr9Nlkv3lMM8iqhqaZux/oJpVVtfp9yvjUoYx+s/s0gwNlATkrA7JDFRs3iUJ6qjb2G2A2+kvuKXth0uXLaUP1AVbwytUbWX0WWhqTkk2XSDM7CKKfuph8pEUe5/+DYQyGyMzu4iIiIhCrqIh1eyyGBAwBLckMwnW7NN6nS79vtUBCn12lSyLy2U3BjzqWgtKNjRS32+zwv6+vmgDfsb9uSSF7GXtAtW5qpqN0nwbfQF7p+586bPJ9MMW9QEll9MWVA2vYI7F6jp1382ug0uSTRcIa3YRRb9omRgmOnrRCCnDGJnZRURERBRylY1wNkZDFpKf2Ri1mUF2aRttwEUeBIvT1Z6SDgcMkNmkZ2V4md1PoMQZILNLNszRabfDbrdBfcqk2V6SYZrWhjGaZ4O57DbD+TUOU9RnoWnbG4Nl5kNN63MYo0tS0F/pp2R4ZyAcxkgU/aLlS6bY+/RvIJjZRURERBQ+vtkYrQaKokmgDC0zxmGM5rMxmmVtmQa+dMEWpY3dGIgxDmM0Fimv6/A4h82YdaXvt+kwR4cxGFazjf9sLytDMvXPZQEf4+yL5jW49LNCygvYa6+npoZXJAvU+5lxsWpSgCBrdnEYI1HUi5byAdHRi0bIwcwuIiIiorCpqK7ZFWzmSDQwBK0sBgTUARCbzVggWBsgkQev/AW1ZP0xBGIkWUxVmUuhrdnllOxT32+zP7h828mCeZpjk2SPyWpQBarZVTXksmY/Dt3wSH1wSn9sxoCifhijzVBfTVPDy8/Mj3qhn43RXwZe8MMY3U47QlUKiMEuovCIlolhYu/Tv4GomY0xwh0hIiIiaoAqY3g2RsOsilYzu+zy4FTNfkwK1JvNxmhW10tX3F4/HNBYYN+4LF4XENLUmLI8jNGkr3ZjAXp99pn+OGpmaDQPGvn2qV+m76+hZpd+2KEsM8tQLN88s0u6XlNTTddet39/59dwLEG0lfE/jNH4vgjEX622YFnpPxEFj5ldjRyHMRIRERGFTyzPxmgsLG91NkZ5cEpZZjKM0WmS8WVlxkanLktJn3WkLAsw9M9mss5sGKpDFzDSzmZozOxy6zKpfH3XL9PWNZMUrbcwJNM4jNEGfb00fSDRMHzSUKNLG8zyW9BeV+NLn20Xiswumw2Is/Cz5X8Yo3l2nhnZBAi1xcwuovBgza5Gzvd55OUwRiIiIqKQa0izMVrNZDHLyqpZbzbrorWglqw/Tl3gxuWwGYdPSmZj1Aca7DZ5MMasyLxDl72kDnbJCtBr1ktmY1SyvXQZUcai9YGHZBqHMeqDUfrglt04fNJQo0t/zv0Fx2zQZ+Kpr1kogl0uSaF+map6YmbDSc3Xme6vFgEyMwx2EYVHtGRUM9gVIb7MLtbsIiIiIgo932yMoRryVJ9kRdGtMMvKqtmPvPi8vgZXzf7kATF/xdCddjtsNmPwxVDU3a3tn7oOk3qd2bE7bMYZC/X91gaEZMXoJUMfJRlv+uGO+gCN/lhkmV3GoZ762mDmmVnSGl1+Zmd02bXBLf3QS30NL7/H4jYJVFmcSVFWw029j2AnkHBJhsnWltmxEVHdREtGdXT0ohHyfePFYYxEREREoVepFKiPjm+Yg2Esim61QL3/IJG2rpVJIMtkNkZZzStfe9nMjsai9eazEQLaYFecUz2M0TyzSzOMURLMMhvmWFOM3v/QR2WZn0CT7FjUzx12myH455LU4PI37NBY88tuyPwyDovUDZs0ZIbJ31P+jkVNX3TfjNNunJ2zpt/GjL+A+/MTPAtWvJOZXUThEC2fuwx2RYhSoJ6ZXUREREQhV+GN4WGM+ppXFgMCZllZPqZDFC0GtZQ2htkYja+r70ugoX/qYYyyYvOAtoi9fhhjnNMYvAs0jFGaxSUrdO9nCKHsWNTDGGuK5fspKC85h8ZhjAGGKfrpo75ulsvPLIiWhzH6KTyv5i84VZvAlez814Y+m46IQicUP6OhEB29aIRqCtRHuCNEREREDYzHK+D7PjEWhzHabMZMHSvMsrJk+3Hphr1J25jOxuhnGKOSVaULthiG/vkJdpnUENMHu/RF3/X91tT0kg5jNJ4D2Wvrhxwah2SaB4hcksCbfiiePvAiHaaoy0IzTAoQqIC9fpikyc+F4VhMZiy0GqiSFfTXrAvy51N/bLUVygwxItIKxc9oKMTep38D4fuw9nAYIxEREVFI+YrTA7GZ2QWYB6b8McvKUtbr6jjJXstsxkazwJJxGKOvXpZ2mb5ovT5jSKhGO+izmHwcqoCY3aY9RukwRdNhjMbhibJtarK9tIEmm82mrTFmGPoXOPinPf/6Gl52/8Ev3bBF/XBAQw0vQyaY9cwus6F+/oYnatuZF5TX1xKzQn9staWva0ZEocPMrkbOzgL1RERERGFR6VUHTmLzdtdpEpjyu02A2RhNM7tMCtebDWPUF0uXrQs0M6Q+qKK+JzZ7LeNQP//BLE0wTNIf/VBA2WsY2xmPRV/XSnbe9PvVn3PDMEf9sfqr4eWQ1QTTBdM0wyLNA0b6Y1GfVzV/hee17fzMxugn68tMqGZjZGYXUfhEy89WbH76NwAsUE9EREQUHpXqzK4omQK9LqxmsgSajdFhks3lsMsDXPrC7DXttcEcWYAsUGZavG54nLq0h1kWmV3VH7vdZh6kU4YxmmWjSepomdTW0u9H9n7SZz9J637p9qsdkqkLZumyoRx2m+6c64Nh+v3pZ3+UrDcrUK8/FpM/Wv3tw2o7fb+sqE02WLD9IqK6iZYvmZyR7kBj5bv+zOwiIiIiCq0KT839VbB/TEcjq/VPAmUg6Ycf1jw2q9NlzJbS98epy0pyyQJEsmwop5/MLpNC+tqAjXad26kuCm/X/L9qvf8C9tJsL5MC9XpxLu0yWVF9QzBLV2Mr0DBEw6QA/grU64c1GuqbmQeZ9MdiOpNiqArUe4MNdoWmQD3AAvVE4RItgWT+hEeIMoyRmV1EREREIVXpm4nRboPNFh033XVhNWDn1A1VM64PXIPLIcls0vdBX8Rd1s5plwfWZK8PaO+JtcEiVWaX6lo6dEX85QXozYZtymtxyY5N3x+X5FrE6Yb6Seul+Z090Tg7o6FAva6YvqHAvd369k6HHWY/FvqMDL+BKpNhpOrH+tpYmnW64ZVxJvvQbqM9NncdAlZm/bfSDyttgn1cV2bHE+h1zY4l0HYB24YomGjW11r1KcB6q9sES/aFRV37Vaf9hDDQK9t/tGR2RUcvGiEOYyQiIiIKj8rqzK5oqRtSV1YLaZsVdq9ZLw9kmc60aDK7oybLyBBoqdpGHUyR/aHnLwhpNiOk+u8nuy4byu00HoO2QL2xFpfsfMmK1psF+syORToTpu5cBixQrwlc6oNXxnOuD2b5fT0/wVN9YNVsNkx93TF1DTb1Y30gT7NOl+GmnvnRfH92mGXsBcu0/xb6YalNkI9r+lW731tm5zlgH0yOJeB2AdqGakY+s77Wpk+B1lvdJliygH9d+1WX/dT2s9FK/UUgejKqGeyKEBaoJyIiIgoP32yMDWW2NbvVzK4Aw+3MZl00C2pZmaXRkDUkLYwf3HUwey2HPrPLJMNHOoxREuiTHZ/ZMcv6Y6X/su0MBeoNwxiNwxT1wTG/BeoNNbv0BfGtXw+zIFnVbJjy4Io24KHtqz5wZSVg5i9AJht2apV6W/UMmqEKXtU22BXMME1NUNkuP4a69qe2bdXX3eqlkQVJzK5NbfpUmwBSKDK7ZL83IhrsqmUwKtBx+GsXCQ3jDiAG1WR2RbgjRERERA2MbzbGaLnhri+agvKyoFOQQS0rszTqh5XJAinB/mGl3p8NqgCXbrikWQCnZkZIs2GMxmBYzdBH+TEryywEIqTb6WdfNAQMtX01DnPUZXoZZqbUBjr1r2c2OQHgPxDhsJtfW01wRZ0dpHrs1PVVvU6fcWaabaTZxlifTHkc5M+7uv9Ok0CRWT8stQnysdIX1XEE+tFxmRy/LEAT7LEE3E7SVh2YMvud4Y/sd4VZQNRqn4JZL1sm+10abNaa7PdiXftVl/3Udpih7PdfvMu4LFq+aIqOXjRCvg8OZnYRERERhZYvs6uxFaDWZFIE+APNUvF5XUBFaeM30OL/j1UrzK6bJrPLbl4zynfs6v1oCtRLgmG+tmYF+muWBf4jVzZEU1+0Xh9o81uDSzLjpb+Ao36Yo75Gl/4PUX9DjtTHov8DX5sZ5ZA+1vdVs85uvs58fzZNAMhtMuzWCrPgkJV+hOqxtAaV6pwEqjkYqC6dWrB9q01bfU02ZbnF3wGy3xVuk/eI1T4Fs162zCW5RsEO0wvmetRlmdVtahvskv3+i3Ma9x8tXzQ1rjuAKMIC9URERETh4bu/kn0jHytq03P1Hxiy7fXZQbLHZkEwfSaSsq0+S0kScAj2D0N1oEb9t75DHzAKEMwyC4bJitHLZl70nRd1H3ztrB6Rb1v1fm3QBafsxmGKhswuQ3DMT2aY3Ti0VN1fp8OmyZizWTwapy4IYz4M0Pz9oV6nH36pzTYy2Z/dDvXZDxTgNWPTDcNUn3+zY9E8ttBXK4+lmZABfo41x6F6HGioarDHEnA7SVuzwLfVSyNrZ/Y+s9qnYNb7yH6fqFn9manZh/+MKKv9qs3xyc5ZrWt2WfwCgAXqGzn1zwyL1BMRERGFToVSoL5x3eoGymzRB1Skjy3M2KgPfNn9ZP/UhtkfSvpgl9msfL52ZpklsmL0vrbq7DErxeitMmZF6YM+2iCbv2GO+uCYrOaXv6Gltf1D16EvxG9SE007jNFuOtzRpQviWRkaqO+7JjAU5GG57PKfAZfJsYRjGKPsWgRTs0uzncnQ5ID9CeEwRpcu6BoKgSYkCMcwRtnvhroINCQ6nMMYZdehtsek/x0AmATAouSLpsZ1BxBF1B/WHMpIREREFDqVyjDG6Ljhri+BjtfKbIym9ZDs8j9i9X/UhCLAaJYJZtcXqDf5I9jXzmyYWk0xeuP50GRxhfD9ow9g6P+YNhak1wa//NXw0s/mGKhGV22DEPq/c83eN9ZnY9Qet3q4lbpdvNM8OFSXgIrdQmDXrPi3WV+tPFYP+5L1v5bxVMNsmXrBHkug7eSFyeW/Y+oiUE3AcBSoDxQ4DFagjKhwFqiXB1Rrd0yy96a0PmSUfNEUHb1ohNS/XDmUkYiIiCh0KpVhjI3rVjfQHzD6oW6yx6Yz3Zn8EWvIGgrjN/qamRn9ZHYpsy2aZB7VFKP3n4USyvePv8wuu83CMEVdYMZQo0sXpFQPs9IfRzDD/fwxC57GaWZj1PY13s86dVaKup1mCGqYjsVpEhyMMwsKmfTVUt0xP4HIutAOaTTu16wumdmxyJZp6o0FmOXPXtuonX6fAWZ7DUfNLrOgf23JzoT6uGR1r0JVs0sWeArVtanav2wYY3R80eSMdAcaK3UKoJeZXUREREQhU9FIM7sCDbGzFNQymbHRypBG/bpQMxSoVwewJJldmj6rM7uUYvT+s1BCGojQXRv98Dv9xADGAvTaP76dumClvwBKuH4OzCYwiPPTV0Nml12o1pllh5lfp1AdmT5Y6KOZSVKTQRM4+8vsscthfC+GmixAYzpk1ORY5G1VQUhJ38Px8282/FrWp5Bldtlt0seh5AoQ9AxVZle4a1fKrnlth3uHGoNdEeJgZhcRERFRWFQ20ppdgfgrMi97rB3GKD+XwczsV1fqLB67fjZGSc0uTQF7aTF6/39shjNLTX/e9MMS9YEkfV/1z/0VJw9XsMthN3nf6N5PmuFaunpVLq88mKTJAAtx/SQZ9aU2m7W0LjW74lzygF24AhGBgrehqNkl+/kIx3vN7H3mY5alJlsmWy+rA6adjMF6X4MRaGKP2tTskmd2hTfwFC31uWRi5g5g2rRpGDRoEJo2bYq0tDSMHDkSO3bsiHS3ak2dOuj1RrAjRERERA1MZfXNVSzPxhgOZn9ka4ubBw6Cme0z3PTZFpoC9E5jsEt9jLLZGDV/REtrJ9XPkMyq19cPU9TV6LJr++/SXSeHn0yUcA3ntZkU8zfWE5NnDrl0tcniVX+0a2qsmcyaGC5mPwOa4WJmwSKTx2aB4/r8+TGbUMDsWGTL4k0y7nxkBcxDSRYUMnt/yZZJM5+kGWqRe5/51CazSx7kDG/IJ5xfcNRVzAS7Vq1ahQkTJmDNmjVYvnw5KioqMHz4cJSUlES6a7XCAvVERERE4VEzG2P03oRHgvqPXbvJEBorQTC1+jzHhgL1ZrMxKgXqTTK7wjxk0Qp/hf3tumMz1OjSZbU57XZdYf3w1LXyRxOs09Rt0h6rvnaVafF6k+yq+vjD2vRnwGRIo5U6XWaBY1vIBmIGZnZOzY5FtsxKADycAtWHqlVNK8l7KpQ1rcwEGsZYm5pd0sBd2H9movdzNmaGMS5btkzz/LXXXkNaWho2btyIc845J0K9qj31e47DGImIiIhCR8ns4jBGDbOAjlkNISsZNfU5CYA60GG320yDdzXDGE0yuwJkh9QH/zW8tMdWNYzRPLPLWDet/v/41AZPtedSk3nj1mYGuVR/B2mHLsrrZtVLLSBN4DBwgMja0MXIZHOp6bMBfYIZxmhlaHM4yYJQZjN6+gQaxigL5NfH+0yTGSk5l+r3j4+s/5r3meT3dLTUz4qEmAl26RUVFQEAmjdvLl1fVlaGsrIy5XlxcXG99Msqm80Guw3wChaoJyIiIgolJbMriodXRIJZQMesuLm/OlA+oc4a8rc7/VA9TYBI0k4zbMtkWJx6f5FkrOGlq9Glu0b+Z8SMbJDXX4H8BF2WUKVHnp1nFmSqb5qfAZMMNdNC9CYBu0hdH7MJBdQ/G7JhcvFOeZAsambcM5lUw0eTuSapzxUNxyHrgywoLy9AH/4JD2JVTJ4Nr9eLSZMm4cwzz0SvXr2kbaZNm4aUlBTlX1ZWVj33MjDfBzEzu4iIiIhChwXq5UyzszR/0MuzBOorG8XfMDV9Zpe6T+q/C2WZXf4yoQK9bn3wFyAyZHLZ7ZraSIYaXRH+490QuFPX5XJpj8O8Rlz9Dl00YzYToFkAz8pQzEhxmPw8m2WsydZHQ4aantn7xkczg6RTNowxGq6NrEi+tTpe9THhQayK/JWthQkTJmDLli1YsGCBaZspU6agqKhI+bdv37567KE1vjRMBruIiIiIQqdmGCNv/NXMggZmsxKqh7/U13BFf7VyHLqaXeo+qWsf+fahr3PlU9/F6K3wV1ReVsNLO9ROezyRPhZ9tp9ZMMJQi0wyY2akqU+l5jgsFdaPssCQ6bHUPJYNnTP7OaqPulZWBDrP8W55ANLfsvomO5WyAGl8gGGY0RBUjSYxN4xx4sSJWLJkCVavXo22bduatouLi0NcXFw99ix4vhsODmMkIiIiCp2aYYy88VczC4IEGgYE1N8fhP6CHOpgncNuMx1C6duH5vqb1GGKFv5qeAH+hypFe1DX30yNtoqaaenNsqiihVmmY5zJEFnt0MXoukZmk0/ESYb56WcCjTaBAtlmwzB9Ip3VaUaWpSUfxhh9Q0ujRcwEu4QQuOuuu7B48WJ88cUX6NChQ6S7VGcOZnYRERERhVylp+oP6GgMakQjl0k2l1p9nUt/NcD0wa5A7TTDHNVZalH4B7ueoQ6Xn6FK0R7U1QYj/A2/VM+oGf5+BcssaKfNfJK3qc9ZF61wmARIZO8ls8zPaKH+2ZbO1qgORsqyOsPTrTqTBXzlmWnR/fMfSTFzZiZMmIA333wT8+fPR9OmTZGfn4/8/HycOnUq0l2rNbuS2RXhjhAREVHETJs2DYMGDULTpk2RlpaGkSNHYseOHZo2paWlmDBhAlq0aIGkpCRcddVVKCgo0LTZu3cvRowYgSZNmiAtLQ33338/KisrNW2++OILnH766YiLi0Pnzp3x2muvGfrz/PPPo3379oiPj8eQIUOwbt26kB9zuFVW31zV50yBsczKH0v1dS79BbFkMy76a6f+I1jdPNqybGT0fXT4yXqK9mwOs9k+9XHVaAykqGmGNJoM54vGAu4yNs3PgyrIKAsWqa5ZtAxdNCOdWVH1OJqviZ6sr7Lex9Ix1beYuQN48cUXUVRUhPPOOw+tW7dW/i1cuDDSXas1DmMkIiKiVatWYcKECVizZg2WL1+OiooKDB8+HCUlJUqbe++9Fx9++CEWLVqEVatWYf/+/bjyyiuV9R6PByNGjEB5eTm++eYbvP7663jttdcwdepUpc3u3bsxYsQInH/++di0aRMmTZqEW2+9FZ988onSZuHChZg8eTIefvhhfPvtt+jbty9yc3NRWFhYPycjRCqY2RUUK8GfUM+6aMZfX5wWg12Bjidahy2p6fuofubQBRwiXaMrELPC6HrRnqGmZhYgthqQjSZms5oq62PkOIDABdpj6T1m9f0TK++zSIiZqy2EkP676aabIt21WmOBeiIiIlq2bBluuukm9OzZE3379sVrr72GvXv3YuPGjQCAoqIi/Oc//8GMGTNwwQUXYMCAAZg3bx6++eYbrFmzBgDw6aefYtu2bXjzzTfRr18/XHLJJXj88cfx/PPPo7y8HAAwZ84cdOjQAdOnT0f37t0xceJEXH311fj3v/+t9GXGjBkYN24cxo4dix49emDOnDlo0qQJXn311fo/MXXgm40xFoarmenQKrFO22ekxPtdnxzvUh67TGr2NJEUQwaA5oluzfP0ZGOd3KzmTQzLOrasOiZlmGH1/zu0rDnW9i20x906JUF5rD6mVkna12waX1OdJSmu6rFbcyw1633BodQm2uMAgLSmxmNpmyo5llZJmue+12qnO279c8B4bVrozmdyvFMTwGridmiza+w1x+iTmqDdRyvdcbROTdA8z25R06+Ouveary5QG9026mPJ1K1Tnzf18aQkuDTtklXXye2wI0H1HktOqFnXTLWPlknaY2utOn9ZzWv6oX7v+Pqe4HIomS/qY87WXRf18aQ1rdl/88Sa41Ifi/pxU9XPUrLJY/XxqK+N7OfU7Nr4XrOl6r3fXvWzo/6Zy0zRXh8AaGlyLOp+qo9F1vdU1Xb69y0AtE5VX5ua/qh/xoGq3wGJ1ddefT3btzT+3lP/DpD9fKY2UR1LgrH/6mXqtj7NJMeRofqdpv85ALTHo/9Zk/3My34fpiXLf2Z8kiXXQnp86veZ7Hea9Pez8Zjat9D2Uf9zB8iPrbXkPSw7nkiImZpdDZHvM4vBLiIiIvIpKioCADRv3hwAsHHjRlRUVGDYsGFKm27duqFdu3bIy8vD0KFDkZeXh969eyM9PV1pk5ubizvuuANbt25F//79kZeXp9mHr82kSZMAAOXl5di4cSOmTJmirLfb7Rg2bBjy8vKkfS0rK0NZWZnyvLi4uG4HHyJllR4A8pnFYsVz15+OJ5b+iNvO7RjUdq/eNBDvffs77ruoq3T9E3/sjU37juKiHjXvFYfdhr8MPw3HSyvRtlnNHzM9M5Nx0xntDX/sXT2gLdbvPoIzO7cEANxxXmfsOXwSl/bJVNr8c2QvuBw23DA0W1n2ypiBeHrZDky8oDMA4P0JZ+K5lT/j/ou74tjJcrzy5W48dGkPAMAbNw/GwvX78LcR3TG8Zzo+/H4/7rqgC3q0Tsbn2wsxemg7AMA/RvbC5t+KcH7XNPztD93x+7FT6NM2BUBVUGDC+Z3gcthxertU3HRGe2Sq/hj/Q68MrB7QFoPbN1eW3XZuJ+w+fBIjemcoyx4b2RN2O3DDkJpjefnGgXjq4+2YcH7VsSy+8wzMXlF1LACw6PYcvPrVbvy9+ngA4D9jBuK/3/2Oe4edBgCYdX1/rPixQDlHT/yxN77fdwzDulddmymXdEN+cSm6ZTSFzWbDxPM7w263oWm8C73bpGBMTrbyR/TFvTIwakBbDMhuBgAYe2Z7/HigWLnOD+R2RdHJClw9sGqCr6ev7oPHPtyGsWd2QFrTODz58XbceX4nAMB7d5yBWSt24i+5Vf189/Yc/Oerqmuz+2AJ5q/bg4cvqzquOTcMwJIf9uPO8zuja0ZTfL69ENcNzoLbacd3e4/ioh5V59F3bU5v1wz3DjsNZZUepCXHIy0ZuOWsDmiR5EZOxxb405B2OC0tCSN6t8aXOw9hcPvmuLxfJrbuL8aF1eflL8O74sjJclx1ehv0ykyBw171Pstq1gT//OhHjD+3I5LjXfjXJztw14WdIQQM77O/jeiufZ/9oTtye2bgw+/3Y8L5ndC9dVOs3F6I0UPaISnOgQ2/HsUlvVrj4cvKsOvgCQxq3wz351btb0B2M0w8vzMcdhtOb5eKsWe2R3pyPM7u0hLXD26HHq2b4op+mfhm1yHkdGyBS/tkYkf+cQzvmY6zu7TCwRNlOPe0Vli14yCuHZSFzmlJeHxJ1bVp1TQOT1VfG7fTjpnLd2Ly8NNwstyDOV/swpQ/dMOBolK8/s2vePiyntieX4xFG37Dg5d0w/ndWmHJDwdwVueWyPvlMP6ck42UBBfW/XoEI3q3xtGScvxUeAJDOzbHAxd3xZETVcdy1wWdYQNQWulFSoILA7Ob4c9Ds9GhZSKG96x6n52e3QxXnt4Gm/Ydw9COLfD1rsO4pFcGzujUAkdPVuDq09uiZ2ay8jvAd20u6pGO5dsKMPGCzrDbbMr77HhpJV5a9Qv+NqI7fjt6Cv9vza+4oFs6Pt9eqPkdoH6fDerQHN/uOYbL+2biRFkltucfxxmdWuDBS7qhsLgMqU1cOFXhwentmuG2czsiye3EgOxmuDEnG+2aN8GugyfQo3Uy/ti/Ddb8chgDspth3e4juLB7Os7r2goHikpxed9MnJ7dDBUegfO7pWHl9gLcmNMerVPiMW3pdtx+Xic0cTsw49OfMLxnOj7dWlD9PqvAy6t/wbAe6Vi5vQAPX9YTPx6oujbndm2F1T8dxMTzO6NH62Ss3F6IG4Zmo2m8E+t/PYpemcnYUXAcZ3VuqfwOaN7EjRPllTi9XTPccV4nJLgcOHayAmnJccr7rLvyPjuM07NTsX73EZzfLQ0XdEvD70dP4ZwurbDqp4O4emBb9GidDLdzKy7slo7PfizArWd3QGoTN55ZtkM5jsnDT8Opcg9e/GIXLupR1U79O+D8rmn44qeD+Mvwrsjp1AIfb8nHGZ1aYO0vh3Hd4CxEA5sQjWMMXXFxMVJSUlBUVITk5ORIdwcAcMa0FdhfVIoPJp6JPm1TI90dIiIiqoNQ3Gt4vV5cfvnlOHbsGL766isAwPz58zF27FhNUAkABg8ejPPPPx9PPfUUxo8fjz179miGJJ48eRKJiYlYunQpLrnkEpx22mkYO3asJpi1dOlSjBgxAidPnsTRo0fRpk0bfPPNN8jJyVHaPPDAA1i1ahXWrl1r6O8jjzyCRx991LA80vdbD72/GW+u2YtJw7pgUnVggYiIiGKf1fut2P26qwHwjelmZhcREREBVRPybNmyBQsWLIh0VyyZMmUKioqKlH/79u2LdJcAAKfKq2p2yaZpJyIiooaPwxgjiAXqiYiIyGfixIlYsmQJVq9ejbZt2yrLMzIyUF5ejmPHjiE1NVVZXlBQgIyMDKWNftZE32yN6jb6GRwLCgqQnJyMhIQEOBwOOBwOaRvfPvTi4uIQF2esBxJppRVVwxgTTGpOERERUcPGzK4IcigF6iPcESIiIooYIQQmTpyIxYsXY+XKlejQoYNm/YABA+ByubBixQpl2Y4dO7B3715luGFOTg42b96smTVx+fLlSE5ORo8ePZQ26n342vj24Xa7MWDAAE0br9eLFStWaIY1xoJT1cGueCeDXURERI0RM7siiMMYiYiIaMKECZg/fz7+97//oWnTpsjPzwcApKSkICEhASkpKbjlllswefJkNG/eHMnJybjrrruQk5ODoUOHAgCGDx+OHj164M9//jOefvpp5Ofn46GHHsKECROUzKvbb78dzz33HB544AHcfPPNWLlyJd555x189NFHSl8mT56MMWPGYODAgRg8eDBmzpyJkpISjB07tv5PTB2cKq8OdjGzi4iIqFFisCuCqmNdHMZIRETUiL344osAgPPOO0+zfN68ebjpppsAAP/+979ht9tx1VVXoaysDLm5uXjhhReUtg6HA0uWLMEdd9yBnJwcJCYmYsyYMXjssceUNh06dMBHH32Ee++9F88++yzatm2LV155Bbm5uUqba6+9FgcPHsTUqVORn5+Pfv36YdmyZZpZHmOBL7OLNbuIiIgaJwa7IshuY2YXERFRY2dlYuz4+Hg8//zzeP75503bZGdnY+nSpX73c9555+G7777z22bixImYOHFiwD5Fs1IGu4iIiBo11uyKIF+Beg8zu4iIiIhCRsnscvNWl4iIqDHiHUAEKbMxMrOLiIiIKGSUml3M7CIiImqUGOyKIA5jJCIiIgo91uwiIiJq3BjsiiAls4vDGImIiIhCRqnZxdkYiYiIGiUGuyLIoWR2RbgjRERERA1EhceLCk/VF4nM7CIiImqcGOyKIHv12WeBeiIiIqLQ8GV1AazZRURE1Fgx2BVBLFBPREREFFq+el02GxDn5K0uERFRY8Q7gAhigXoiIiKi0Cotr6oPkeBywFZ9r0VERESNC4NdEeTL7OIwRiIiIqLQ8GV2cQgjERFR48VgVwT5CtRzGCMRERFRaCgzMTLYRURE1Ggx2BVBdmZ2EREREYVUTWYXb3OJiIgaK94FRBAzu4iIiIhCyxfsSnAzs4uIiKixYrArgpSaXQx2EREREYVEaTmHMRIRETV2DHZFUM0wxgh3hIiIiKiBYIF6IiIiYrArghzVs2FzGCMRERFRaJxigXoiIqJGj8GuCPJldpWUV0a4J0REREQNw6ly1uwiIiJq7BjsiqA+bVIAAG+u2YOiUxUR7g0RERFR7CtlZhcREVGjx2BXBP1pSDY6tkzEoRPluPvt71Dh8Ua6S0REREQxrbi0KmM+Mc4Z4Z4QERFRpDDYFUFupx3Tr+mLeJcdq346iL8s+p4zMxIRERHVwdGScgBA80R3hHtCREREkcJgV4T1b9cML94wAE67Df/btB9XvfgNfjxQHOluEREREcWkoycZ7CIiImrsGOyKAud3TcOs6/sjKc6JTfuOYcSsL3HHmxuRt+swZ2okIiIiCsKR6syuZk0Y7CIiImqsWMwgSvyhd2uc3q4ZHv1wKz7ekq/8S0+OwzldWqF9y0Rc3jcTbZslwGazRbq7RERERFHp6MmqSX+Y2UVERNR4MdgVRTJS4vHiDQOwI/84XvvmV3z4/X4UFJdh0cbfAADPfLIDrVPicUG3NAzIboZ+Wano0DKRwS8iIiKiakeUml2uCPeEiIiIIoXBrijUNaMppl3ZG49c3gNf7TyEH34rwrrdR7B292EcKCrFW2v34q21ewEAqU1c6J+VitPbNUO/dqno0ToZLZLiInwERERERPWv0uNF0amqzC4OYyQiImq8GOyKYnFOBy7sno4Lu6cDAE6Ve/DNrkP4ZtdhfLf3KLbsL8axkxX4fMdBfL7joLJdWtM49MhMRvfWyejRuur/HVomwmFnBhgRERE1XMeqA102G5CSwMwuIiKixorBrhiS4NYGv8orvfjxQDE27jmKb/cexdb9xdh9qASFx8tQuOMgvlAFwOJddnRomYT2LZogu0Uisls0QXaLJmjfIhEZyfGwMxBGREREMe5o9RDGlAQXnA7Ow0RERNRYMdgVw9xOO/pmpaJvVipuRgcAQElZJbbnH8e2A8X4sfrf9gPHcarCozyX7add8ybIbl4VCGvfsgnaNa8KhLVplgAXbxaJiIgoBviK03MIIxERUePGYFcDkxjnxIDsZhiQ3UxZ5vEK7Dlcgt2HSrDn8EnsOVyCPUdOYs/hk9h35CTKK734ufAEfi48Ydif3VZ1w5jaxIUWiXFo0ywB8S4H2rdogj/0bs3ZIYmIiChq+IrTN2vCIYxERESNGYNdjYDDbkPHVkno2CrJsK7S48WBolLsOXwSvx4uwd4jJ/GrLyh2pASlFV4cLinH4ZJy7DpYAvxas+20j7cjzmlHi0Q3mie50Twxrupx9b8WiW6kNvE9dyG1iRupHFZAREREYXL0pG8mRmZ2ERERNWYxF+x6/vnn8cwzzyA/Px99+/bF7NmzMXjw4Eh3K2Y5HXZkNW+CrOZNcFaXlpp1QggcPFGGoyUVOFJSjoMnynDg2CmcLPdg/a9H8M2uwyir9GJ/USn2F5Vafs3keCdSmriQ6HYiMa7qX5zTDpfDhhaJcchMTUCCy44mbifi3Q4kuKr/uWv+38TtQHz1creTwTMiIiICDp8oA8BhjERERI1dTAW7Fi5ciMmTJ2POnDkYMmQIZs6cidzcXOzYsQNpaWmR7l6DY7PZkNY0HmlN46XrT5ZX4vCJqqyvIyVlOHyiHEdKqv4drv7/0ZPlOHayKljmmwq8uLQSxaWVIeun025DgsuBeF8QzFn1ON5pR3x1MMztsMPpsMHlsMPlsMPtsCmBtHiXA067reqfoyro5rTXtHfaq/7vsNsMy5zVbV2O6m3tNjjsNtht1f/skD+2gcM/iYiIQmz3oZMAgOwWTSLcEyIiIoqkmAp2zZgxA+PGjcPYsWMBAHPmzMFHH32EV199FQ8++GCEe9f4NHE70aS5E1nNrd1QVnq8KDpVgaMnK1B0qgInyytRUuZBSVklyiq9qPB4sf/YKRwuKcepCg9OlVf/q1D9v/rxyfJKeEX1fr0Cx8sqcbwsdAG0+mCzVQW/HDab8thuA+z2moCYw26DzffYVv3YXvXYXr2dL7hms9ngsAM2VLWHzQYboATWqh7bgKr/lNesWlT9/+p2yrrqx+rlQFV7KOtUy5THvmO0qR7XrPMF+pRwn023T8M2tprHqo1shtfT7kf/evp9mr6eqt+Q9QH+WYlj2gLuJfB+LIVLA+zEyj5CcTzW9hGCfoQgiBwtx2tlP6F4H1lh5byG5uei7n0J9DqX9GqNVk3jLLwSxaJdB6vqj8pKNxAREVHjETPBrvLycmzcuBFTpkxRltntdgwbNgx5eXmG9mVlZSgrK1OeFxcbZyGk+uV02NEiKQ4tkur+R4YQAhUeoQmCnSyvxKlyD0orvCit8KC0siowVukVqPB4UV7pRYWn5nFpRc22lR4BT3U7X3tlmbfqcYXHC49XaNZXeqv2WenxosJb9X9fEC7wMQAeIeCBxQ2IiKjOerdJYbCrgRJCKMGuTgx2ERERNWoxE+w6dOgQPB4P0tPTNcvT09Oxfft2Q/tp06bh0Ucfra/uUT2z2WxwO21wO+1IQXTNuCSEUAJZXt9jb9VjrwC86sdCvtzjFRCqNlXPqx+LmnW+/Wpfo+q5EICo7k9VAM63D0BUPxaq/goIeL2qZZp1Va9ddXyoCc/5ltU8VLaFeln1chiWG/fp64u6HVTb69v69qN+LXW/ZPuUbQ9JX7X91/bZjPC/2jIRYEdWXiZQXwIdi5V9WOmLtXNS9/Nqra8heJ166IeVF7L2Hgj/+8jKfgL1w2pfAp+TwHtJZS2nBuvQiXIcL62EzcZhjERERI1dzAS7gjVlyhRMnjxZeV5cXIysrKwI9ogaC5tvWKK1QWZEREQUAr6srqxmTRDvckS4N0RERBRJMRPsatmyJRwOBwoKCjTLCwoKkJGRYWgfFxeHuDgOUyAiIiJqDHYW+oYwJka4J0RERBRp9kh3wCq3240BAwZgxYoVyjKv14sVK1YgJycngj0jIiIiokj7audBAEDvtqmR7QgRERFFXMxkdgHA5MmTMWbMGAwcOBCDBw/GzJkzUVJSoszOSERERESNT2mFB6t/OgQAGN4jPUBrIiIiauhiJrMLAK699lr861//wtSpU9GvXz9s2rQJy5YtMxStJyIiIqLae/7559G+fXvEx8djyJAhWLduXaS75Neqnw7iVIUHmSnx6JmZHOnuEBERUYTFVLALACZOnIg9e/agrKwMa9euxZAhQyLdJSIiIqIGY+HChZg8eTIefvhhfPvtt+jbty9yc3NRWFgY6a5JlVV68PSyqpm5L+2bCZuNE8QQERE1djEX7CIiIiKi8JkxYwbGjRuHsWPHokePHpgzZw6aNGmCV199NdJd0/B6Bbb8XoRbXtuAXQdL0DLJjQnndY50t4iIiCgKxFTNrroQQgAAiouLI9wTIiIiaoh89xi+e45YVF5ejo0bN2LKlCnKMrvdjmHDhiEvL8/QvqysDGVlZcrzoqIiAOG73/py50HMWrETx05W4MjJcpRVeAEA8S47HvtDd9gqT6G4+FRYXpuIiIgiz+r9VqMJdh0/fhwAkJWVFeGeEBERUUN2/PhxpKSkRLobtXLo0CF4PB5DPdT09HRs377d0H7atGl49NFHDcsjcb814pl6f0kiIiKKkED3W40m2JWZmYl9+/ahadOmYavlUFxcjKysLOzbtw/JySyOGim8DpHHaxAdeB2iA69DdKiP6yCEwPHjx5GZmRmW/UejKVOmYPLkycpzr9eLI0eOoEWLFrzfauB4HaIDr0N04HWIDrwO0SHc18Hq/VajCXbZ7Xa0bdu2Xl4rOTmZP1xRgNch8ngNogOvQ3TgdYgO4b4OsZrR5dOyZUs4HA4UFBRolhcUFCAjI8PQPi4uDnFxcZplqamp4eyigj9T0YHXITrwOkQHXofowOsQHcJ5Hazcb7FAPREREREBANxuNwYMGIAVK1Yoy7xeL1asWIGcnJwI9oyIiIjIukaT2UVEREREgU2ePBljxozBwIEDMXjwYMycORMlJSUYO3ZspLtGREREZAmDXSEUFxeHhx9+2JDOT/WL1yHyeA2iA69DdOB1iA68DtZde+21OHjwIKZOnYr8/Hz069cPy5YtMxStjxRey+jA6xAdeB2iA69DdOB1iA7Rch1sIpbnxyYiIiIiIiIiIlJhzS4iIiIiIiIiImowGOwiIiIiIiIiIqIGg8EuIiIiIiIiIiJqMBjsIiIiIiIiIiKiBoPBLiIiIiIiIiIiajAY7AqR559/Hu3bt0d8fDyGDBmCdevWRbpLDcrq1atx2WWXITMzEzabDe+//75mvRACU6dORevWrZGQkIBhw4Zh586dmjZHjhzB6NGjkZycjNTUVNxyyy04ceJEPR5FbJs2bRoGDRqEpk2bIi0tDSNHjsSOHTs0bUpLSzFhwgS0aNECSUlJuOqqq1BQUKBps3fvXowYMQJNmjRBWloa7r//flRWVtbnocS0F198EX369EFycjKSk5ORk5ODjz/+WFnPaxAZTz75JGw2GyZNmqQs47UIv0ceeQQ2m03zr1u3bsp6XoOGh/db4cX7rejAe67owHuu6MR7rsiIxXsuBrtCYOHChZg8eTIefvhhfPvtt+jbty9yc3NRWFgY6a41GCUlJejbty+ef/556fqnn34as2bNwpw5c7B27VokJiYiNzcXpaWlSpvRo0dj69atWL58OZYsWYLVq1dj/Pjx9XUIMW/VqlWYMGEC1qxZg+XLl6OiogLDhw9HSUmJ0ubee+/Fhx9+iEWLFmHVqlXYv38/rrzySmW9x+PBiBEjUF5ejm+++Qavv/46XnvtNUydOjUShxST2rZtiyeffBIbN27Ehg0bcMEFF+CKK67A1q1bAfAaRML69evx0ksvoU+fPprlvBb1o2fPnjhw4IDy76uvvlLW8Ro0LLzfCj/eb0UH3nNFB95zRR/ec0VWzN1zCaqzwYMHiwkTJijPPR6PyMzMFNOmTYtgrxouAGLx4sXKc6/XKzIyMsQzzzyjLDt27JiIi4sTb7/9thBCiG3btgkAYv369Uqbjz/+WNhsNvH777/XW98bksLCQgFArFq1SghRdc5dLpdYtGiR0ubHH38UAEReXp4QQoilS5cKu90u8vPzlTYvvviiSE5OFmVlZfV7AA1Is2bNxCuvvMJrEAHHjx8XXbp0EcuXLxfnnnuuuOeee4QQ/HmoLw8//LDo27evdB2vQcPD+636xfut6MF7rujBe67I4T1XZMXiPRczu+qovLwcGzduxLBhw5Rldrsdw4YNQ15eXgR71njs3r0b+fn5mmuQkpKCIUOGKNcgLy8PqampGDhwoNJm2LBhsNvtWLt2bb33uSEoKioCADRv3hwAsHHjRlRUVGiuQ7du3dCuXTvNdejduzfS09OVNrm5uSguLla+JSPrPB4PFixYgJKSEuTk5PAaRMCECRMwYsQIzTkH+PNQn3bu3InMzEx07NgRo0ePxt69ewHwGjQ0vN+KPN5vRQ7vuSKP91yRx3uuyIu1ey5nWPbaiBw6dAgej0dz0QAgPT0d27dvj1CvGpf8/HwAkF4D37r8/HykpaVp1judTjRv3lxpQ9Z5vV5MmjQJZ555Jnr16gWg6hy73W6kpqZq2uqvg+w6+daRNZs3b0ZOTg5KS0uRlJSExYsXo0ePHti0aROvQT1asGABvv32W6xfv96wjj8P9WPIkCF47bXX0LVrVxw4cACPPvoozj77bGzZsoXXoIHh/Vbk8X4rMnjPFVm854oOvOeKvFi852Kwi4iCNmHCBGzZskUzTpvqT9euXbFp0yYUFRXh3XffxZgxY7Bq1apId6tR2bdvH+655x4sX74c8fHxke5Oo3XJJZcoj/v06YMhQ4YgOzsb77zzDhISEiLYMyKi0OA9V2TxnivyeM8VHWLxnovDGOuoZcuWcDgchpkGCgoKkJGREaFeNS6+8+zvGmRkZBgK2FZWVuLIkSO8TkGaOHEilixZgs8//xxt27ZVlmdkZKC8vBzHjh3TtNdfB9l18q0ja9xuNzp37owBAwZg2rRp6Nu3L5599lleg3q0ceNGFBYW4vTTT4fT6YTT6cSqVaswa9YsOJ1OpKen81pEQGpqKk477TT8/PPP/HloYHi/FXm836p/vOeKPN5zRR7vuaJTLNxzMdhVR263GwMGDMCKFSuUZV6vFytWrEBOTk4Ee9Z4dOjQARkZGZprUFxcjLVr1yrXICcnB8eOHcPGjRuVNitXroTX68WQIUPqvc+xSAiBiRMnYvHixVi5ciU6dOigWT9gwAC4XC7NddixYwf27t2ruQ6bN2/W3AgvX74cycnJ6NGjR/0cSAPk9XpRVlbGa1CPLrzwQmzevBmbNm1S/g0cOBCjR49WHvNa1L8TJ05g165daN26NX8eGhjeb0Ue77fqD++5ohfvueof77miU0zcc4Wl7H0js2DBAhEXFydee+01sW3bNjF+/HiRmpqqmWmA6ub48ePiu+++E999950AIGbMmCG+++47sWfPHiGEEE8++aRITU0V//vf/8QPP/wgrrjiCtGhQwdx6tQpZR8XX3yx6N+/v1i7dq346quvRJcuXcT1118fqUOKOXfccYdISUkRX3zxhThw4IDy7+TJk0qb22+/XbRr106sXLlSbNiwQeTk5IicnBxlfWVlpejVq5cYPny42LRpk1i2bJlo1aqVmDJlSiQOKSY9+OCDYtWqVWL37t3ihx9+EA8++KCw2Wzi008/FULwGkSSemYgIXgt6sN9990nvvjiC7F7927x9ddfi2HDhomWLVuKwsJCIQSvQUPD+63w4/1WdOA9V3TgPVf04j1X/YvFey4Gu0Jk9uzZol27dsLtdovBgweLNWvWRLpLDcrnn38uABj+jRkzRghRNR323//+d5Geni7i4uLEhRdeKHbs2KHZx+HDh8X1118vkpKSRHJyshg7dqw4fvx4BI4mNsnOPwAxb948pc2pU6fEnXfeKZo1ayaaNGki/vjHP4oDBw5o9vPrr7+KSy65RCQkJIiWLVuK++67T1RUVNTz0cSum2++WWRnZwu32y1atWolLrzwQuWmSwheg0jS33jxWoTftddeK1q3bi3cbrdo06aNuPbaa8XPP/+srOc1aHh4vxVevN+KDrznig6854pevOeqf7F4z2UTQojw5IwRERERERERERHVL9bsIiIiIiIiIiKiBoPBLiIiIiIiIiIiajAY7CIiIiIiIiIiogaDwS4iIiIiIiIiImowGOwiIiIiIiIiIqIGg8EuIiIiIiIiIiJqMBjsIiIiIiIiIiKiBoPBLiIiIiIiIiIiajAY7CIiIiIiIiIiogaDwS4iIiIiIiIiImowGOwiIiIiIiIiIqIG4/8DpuBNI16SLuoAAAAASUVORK5CYII=", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# we define the precision matrix to specify, in which nodes and channels we measure deviations from the target\n", - "cost_mat = np.zeros( (model.params.N, len(model.output_vars)) )\n", - "cost_mat[1,0] = 1. # only measure in y-channel in node 1\n", - "\n", - "# We set the external stimulation to zero. This is the \"initial guess\" for the OC algorithm\n", - "model.params[\"exc_current\"] = zero_input_nw[:,0,:]\n", - "model.params[\"inh_current\"] = zero_input_nw[:,0,:]\n", - "\n", - "# We load the optimal control class\n", - "# print array (optional parameter) defines, for which iterations intermediate results will be printed\n", - "# Parameters will be taken from the input model\n", - "model_controlled = oc_ww.OcWw(model, target, print_array=np.arange(0,501,25), control_matrix=control_mat, cost_matrix=cost_mat)\n", - "\n", - "# We run 500 iterations of the optimal control gradient descent algorithm\n", - "model_controlled.optimize(500)\n", - "\n", - "state = model_controlled.get_xs()\n", - "control = model_controlled.control\n", - "\n", - "plot_oc_network(model.params.N, duration, dt, state, target, control, input_nw, model_controlled.cost_history, model_controlled.step_sizes_history)" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": { - "pycharm": { - "name": "#%%\n" - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Compute control for a deterministic system\n", - "Cost in iteration 0: 2.2057268519628175e-09\n", - "Cost in iteration 25: 2.079569265893922e-09\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Cost in iteration 50: 1.969986550217457e-09\n", - "Cost in iteration 75: 1.874389888067335e-09\n", - "Cost in iteration 100: 1.7855706988225455e-09\n", - "Final cost : 1.7855706988225455e-09\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Do another 100 iterations if you want to.\n", - "# Repeated execution will continue with further 100 iterations.\n", - "model_controlled.optimize(100)\n", - "state = model_controlled.get_xs()\n", - "control = model_controlled.control\n", - "plot_oc_network(model.params.N, duration, dt, state, target, control, input_nw, model_controlled.cost_history, model_controlled.step_sizes_history)" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Delayed network of neural populations\n", - "\n", - "We now consider a network topology with delayed signalling between the two nodes." - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": { - "collapsed": false, - "pycharm": { - "name": "#%%\n" - } - }, - "outputs": [ - { - "data": { - "image/png": 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "cmat = np.array( [[0., 0.], [1., 0.]] ) # diagonal elements are zero, connection strength is 1 from node 0 to node 1\n", - "dmat = np.array( [[0., 0.], [18, 0.]] ) # distance from 0 to 1, delay is computed by dividing by the signal speed params.signalV\n", - "\n", - "model = WWModel(Cmat=cmat, Dmat=dmat)\n", - "\n", - "duration, dt = 2000., 0.1\n", - "model.params.duration = duration\n", - "model.params.dt = dt\n", - "model.params.K_gl = 10.\n", - "\n", - "model.run()\n", - "\n", - "e0 = model.r_exc[0,-1]\n", - "e1 = model.r_exc[1,-1]\n", - "i0 = model.r_inh[0,-1]\n", - "i1 = model.r_inh[1,-1]\n", - "\n", - "maxdelay = model.getMaxDelay()\n", - "\n", - "model.params[\"r_exc\"] = np.array([[e0] * (maxdelay + 1), [e1] * (maxdelay + 1) ])\n", - "model.params[\"r_inh\"] = np.array([[i0] * (maxdelay + 1), [i1] * (maxdelay + 1) ])\n", - "\n", - "duration = 6.\n", - "model.params.duration = duration\n", - "model.run()\n", - "\n", - "# we define the control input matrix to enable or disable certain channels and nodes\n", - "control_mat = np.zeros( (model.params.N, len(model.state_vars)) )\n", - "control_mat[0,0] = 1. # only allow inputs in E-channel in node 0\n", - "\n", - "zero_input = ZeroInput().generate_input(duration=duration+dt, dt=dt)\n", - "input = zero_input.copy()\n", - "input[0,10] = 1. \n", - "input[0,20] = 1.\n", - "input[0,30] = 1. # Three pulses as control input\n", - "\n", - "input_nw = np.concatenate( (np.vstack( [control_mat[0,0] * input, control_mat[0,1] * input] )[np.newaxis,:,:],\n", - " np.vstack( [control_mat[1,0] * input, control_mat[1,1] * input] )[np.newaxis,:,:]), axis=0)\n", - "zero_input_nw = np.concatenate( (np.vstack( [zero_input, zero_input] )[np.newaxis,:,:],\n", - " np.vstack( [zero_input, zero_input] )[np.newaxis,:,:]), axis=0)\n", - "\n", - "model.params[\"exc_current\"] = input_nw[:,0,:]\n", - "model.params[\"inh_current\"] = input_nw[:,1,:]\n", - "model.run()\n", - "\n", - "# Define the result of the stimulation as target\n", - "target = np.concatenate( (np.stack( (model.params[\"r_exc\"][:,-1], model.params[\"r_inh\"][:,-1]), axis=1)[:,:, np.newaxis], np.stack( (model.r_exc, model.r_inh), axis=1)), axis=2)\n", - "\n", - "# Remove stimuli and re-run the simulation\n", - "model.params[\"exc_current\"] = zero_input_nw[:,0,:]\n", - "model.params[\"inh_current\"] = zero_input_nw[:,0,:]\n", - "model.run()\n", - "\n", - "# combine initial value and simulation result to one array\n", - "state = np.concatenate( (np.stack( (model.params[\"r_exc\"][:,-1], model.params[\"r_inh\"][:,-1]), axis=1)[:,:, np.newaxis], np.stack( (model.r_exc, model.r_inh), axis=1)), axis=2)\n", - "plot_oc_network(model.params.N, duration, dt, state, target, zero_input_nw, input_nw)" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Compute control for a deterministic system\n", - "Cost in iteration 0: 1.792835053390993e-07\n", - "Cost in iteration 25: 3.224858708247228e-10\n", - "Cost in iteration 50: 1.0235990384283723e-10\n", - "Cost in iteration 75: 8.627681277851615e-11\n", - "Cost in iteration 100: 8.09708890397755e-11\n", - "Cost in iteration 125: 6.901547805762654e-11\n", - "Cost in iteration 150: 6.563898918059379e-11\n", - "Cost in iteration 175: 6.358322097910284e-11\n", - "Cost in iteration 200: 5.819126634851626e-11\n", - "Cost in iteration 225: 5.598411882794661e-11\n", - "Cost in iteration 250: 5.458351655389417e-11\n", - "Cost in iteration 275: 5.101837452145287e-11\n", - "Cost in iteration 300: 4.9526343719852504e-11\n", - "Cost in iteration 325: 4.872279762423021e-11\n", - "Cost in iteration 350: 4.599347400927492e-11\n", - "Cost in iteration 375: 4.5049466495032303e-11\n", - "Cost in iteration 400: 4.32863678958512e-11\n", - "Cost in iteration 425: 4.241565430129624e-11\n", - "Cost in iteration 450: 4.121896579349796e-11\n", - "Cost in iteration 475: 4.036542019862459e-11\n", - "Cost in iteration 500: 3.990804399212831e-11\n", - "Final cost : 3.990804399212831e-11\n" - ] - }, - { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# We load the optimal control class\n", - "# print array (optional parameter) defines, for which iterations intermediate results will be printed\n", - "# Parameters will be taken from the input model\n", - "model_controlled = oc_ww.OcWw(model, target, print_array=np.arange(0,501,25), control_matrix=control_mat, cost_matrix=cost_mat)\n", - "\n", - "# We run 500 iterations of the optimal control gradient descent algorithm\n", - "model_controlled.optimize(500)\n", - "\n", - "state = model_controlled.get_xs()\n", - "control = model_controlled.control\n", - "plot_oc_network(model.params.N, duration, dt, state, target, control, input_nw, model_controlled.cost_history, model_controlled.step_sizes_history)" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Compute control for a deterministic system\n", - "Cost in iteration 0: 3.990804399212831e-11\n", - "Cost in iteration 25: 3.8701660107380814e-11\n", - "Cost in iteration 50: 3.8275743610357815e-11\n", - "Cost in iteration 75: 3.731362663528545e-11\n", - "Cost in iteration 100: 3.694171527929222e-11\n", - "Final cost : 3.694171527929222e-11\n" - ] - }, - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# perofrm another 100 iterations to improve result\n", - "# repeat execution to add another 500 iterations\n", - "# converence to the input stimulus is relatively slow for the WC nodel\n", - "model_controlled.optimize(100)\n", - "state = model_controlled.get_xs()\n", - "control = model_controlled.control\n", - "plot_oc_network(model.params.N, duration, dt, state, target, control, input_nw, model_controlled.cost_history, model_controlled.step_sizes_history)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.12" - }, - "vscode": { - "interpreter": { - "hash": "31f2aee4e71d21fbe5cf8b01ff0e069b9275f58929596ceb00d14d90e3e16cd6" - } - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/neurolib/control/optimal_control/oc.py b/neurolib/control/optimal_control/oc.py index e92bece7..5bbf1ec6 100644 --- a/neurolib/control/optimal_control/oc.py +++ b/neurolib/control/optimal_control/oc.py @@ -82,6 +82,7 @@ def solve_adjoint( dxdoth, state_vars, output_vars, + model_name, ): """Backwards integration of the adjoint state. @@ -122,9 +123,13 @@ def solve_adjoint( if sv == ov: fx_fullstate[:, sv_ind, :] = fx[:, ov_ind, :] + krange = range(state_dim[1]) + if model_name == "wongwang": + krange = range(state_dim[1] - 1, -1, -1) + for t in range(T - 2, -1, -1): # backwards iteration including 0th index for n in range(N): # iterate through nodes - for k in range(state_dim[1]): + for k in krange: if dxdoth[n, k, k] == 0: res = fx_fullstate[n, k, t + 1] res += adjoint_input( @@ -154,98 +159,6 @@ def solve_adjoint( return adjoint_state -@numba.njit -def solve_adjoint_ww( - hx_list, - del_list, - hx_nw, - fx, - state_dim, - dt, - N, - T, - dmat_ndt, - dxdoth, - state_vars, - output_vars, -): - """Backwards integration of the adjoint state. - - :param hx_list: list of Jacobians of systems dynamics wrt. 'state_vars' - :type hx_list: list of np.ndarray - :param del_list: list of respective time delay integer - :type del_list: list of int - :param hx_nw: Jacobians for each time step for the network coupling. - :type hx_nw: np.ndarray - :param fx: df/dx Derivative of cost function wrt. systems dynamics. - :type fx: np.ndarray - :param state_dim: Dimensions of state (N, V, T). - :type state_dim: tuple - :param dt: Time resolution of integration. - :type dt: float - :param N: Number of nodes in the network. - :type N: int - :param T: Length of simulation (time dimension). - :type T: int - :param dmat_ndt: N x N delay matrix (discrete number of delayed time-intervals). - :type dmat_ndt: np.ndarray - :param dxdoth: derivative of system dynamics wrt x dot - :type dxdoth: np.ndarray - :param state_vars: list of state variables of model - :type state_vars: list - :param output_vars: list of output variables of model - :type output_vars: list - - :return: Adjoint state. - :rtype: np.ndarray of shape `state_dim` - """ - # ToDo: generalize, not only precision cost - adjoint_state = np.zeros(state_dim) - fx_fullstate = np.zeros(state_dim) - - for sv_ind, sv in enumerate(state_vars): - for ov_ind, ov in enumerate(output_vars): - if sv == ov: - fx_fullstate[:, sv_ind, :] = fx[:, ov_ind, :] - - for t in range(T - 1, -1, -1): # backwards iteration including 0th index - for n in range(N): # iterate through nodes - adjoint_state[n, 2, t] = -fx_fullstate[n, 0, t] / hx_list[0][n, t, 2, 0] - adjoint_state[n, 3, t] = -fx_fullstate[n, 1, t] / hx_list[0][n, t, 3, 1] - - for k in range(state_dim[1]): - if dxdoth[n, k, k] == 0: - res = fx_fullstate[n, k, t + 1] - res += adjoint_input( - hx_list, del_list, t, T, state_dim[1], adjoint_state, n, k - ) - res += adjoint_nw_input( - N, n, k, dmat_ndt, t, T, state_dim[1], adjoint_state, hx_nw - ) - # if n == 0 and k == 0: - # print(t, n, k, res) - # print(adjoint_state[n,]) - - adjoint_state[n, k, t] = -res - - elif dxdoth[n, k, k] == 1: - der = fx_fullstate[n, k, t] - der += adjoint_input( - hx_list, del_list, t, T, state_dim[1], adjoint_state, n, k - ) - der += adjoint_nw_input( - N, n, k, dmat_ndt, t, T - 1, state_dim[1], adjoint_state, hx_nw - ) - - adjoint_state[n, k, t] = adjoint_state[n, k, t + 1] - dt * der - - else: - print("WARNING: Case dh_dxdot != 0 or 1 not implemented") - raise NotImplementedError - - return adjoint_state - - @numba.njit def adjoint_input(hx_list, del_list, t, T_lim, state_dim1, adj, n, k): """Compute input to adjoint state for backwards integration @@ -275,9 +188,6 @@ def adjoint_input(hx_list, del_list, t, T_lim, state_dim1, adj, n, k): if t + 1 + int_delay < T_lim: for v in range(state_dim1): result += adj[n, v, t + 1 + int_delay] * hx[n, t + 1 + int_delay, v, k] - if int_delay == -1 and v == 2 and k == 0: - print("adjoint = ", adj[n, v, t + 1 + int_delay]) - print("hx = ", hx[n, t + 1 + int_delay, v, k]) return result @@ -817,7 +727,7 @@ def solve_adjoint(self): self.cost_matrix, self.cost_interval, ) - self.adjoint_state = solve_adjoint_ww( + self.adjoint_state = solve_adjoint( hx_list, del_list, hx_nw, @@ -830,6 +740,7 @@ def solve_adjoint(self): dxdoth, numba.typed.List(self.model.state_vars), numba.typed.List(self.model.output_vars), + self.model.name, ) def decrease_step(self, cost, cost0, step, control0, factor_down, cost_gradient): diff --git a/neurolib/control/optimal_control/oc_ww/oc_ww.py b/neurolib/control/optimal_control/oc_ww/oc_ww.py index 872d3fe8..90931119 100644 --- a/neurolib/control/optimal_control/oc_ww/oc_ww.py +++ b/neurolib/control/optimal_control/oc_ww/oc_ww.py @@ -110,7 +110,7 @@ def compute_hx_list(self): """ hx = self.compute_hx() hx_min1 = self.compute_hx_min1() - return numba.typed.List([hx]), numba.typed.List([0]) + return numba.typed.List([hx, hx_min1]), numba.typed.List([0, -1]) def compute_hx(self): """Jacobians of WwModel wrt. all variables. diff --git a/neurolib/models/ww/loadDefaultParams.py b/neurolib/models/ww/loadDefaultParams.py index 974e3ab3..3f13dc51 100644 --- a/neurolib/models/ww/loadDefaultParams.py +++ b/neurolib/models/ww/loadDefaultParams.py @@ -82,8 +82,10 @@ def loadDefaultParams(Cmat=None, Dmat=None, seed=None): # ------------------------------------------------------------------------ - params.ses_init = 0.05 * np.random.uniform(0, 1, (params.N, 1)) - params.sis_init = 0.05 * np.random.uniform(0, 1, (params.N, 1)) + params.r_exc_init = 0.1 * np.random.uniform(0, 1, (params.N, 1)) + params.r_inh_init = 0.1 * np.random.uniform(0, 1, (params.N, 1)) + params.se_init = 0.05 * np.random.uniform(0, 1, (params.N, 1)) + params.si_init = 0.05 * np.random.uniform(0, 1, (params.N, 1)) # Ornstein-Uhlenbeck noise state variables params.exc_ou = np.zeros((params.N,)) diff --git a/neurolib/models/ww/model.py b/neurolib/models/ww/model.py index 2b4d3804..d7e13c38 100644 --- a/neurolib/models/ww/model.py +++ b/neurolib/models/ww/model.py @@ -26,7 +26,7 @@ class WWModel(Model): name = "wongwang" description = "Wong-Wang neural mass model" - init_vars = ["r_exc", "r_inh", "ses_init", "sis_init", "exc_ou", "inh_ou"] + init_vars = ["r_exc_init", "r_inh_init", "se_init", "si_init", "exc_ou", "inh_ou"] state_vars = ["r_exc", "r_inh", "se", "si", "exc_ou", "inh_ou"] output_vars = ["r_exc", "r_inh", "se", "si"] default_output = "r_exc" diff --git a/neurolib/models/ww/timeIntegration.py b/neurolib/models/ww/timeIntegration.py index f53c139a..125136ca 100644 --- a/neurolib/models/ww/timeIntegration.py +++ b/neurolib/models/ww/timeIntegration.py @@ -108,13 +108,13 @@ def timeIntegration(params): # ------------------------------------------------------------------------ # Set initial values # if initial values are just a Nx1 array - if np.shape(params["ses_init"])[1] == 1: - ses_init = np.dot(params["ses_init"], np.ones((1, startind))) - sis_init = np.dot(params["sis_init"], np.ones((1, startind))) + if np.shape(params["se_init"])[1] == 1: + ses_init = np.dot(params["se_init"], np.ones((1, startind))) + sis_init = np.dot(params["si_init"], np.ones((1, startind))) # if initial values are a Nxt array else: - ses_init = params["ses_init"][:, -startind:] - sis_init = params["sis_init"][:, -startind:] + ses_init = params["se_init"][:, -startind:] + sis_init = params["si_init"][:, -startind:] # xsd = np.zeros((N,N)) # delayed activity ses_input_d = np.zeros(N) # delayed input to x @@ -409,10 +409,10 @@ def jacobian_ww( jacobian[sv["r_inh"], sv["se"]] = -logistic_der(II, a_inh, b_inh, d_inh) * J_NMDA jacobian[sv["r_inh"], sv["si"]] = logistic_der(II, a_inh, b_inh, d_inh) - jacobian[sv["se"], sv["r_exc"]] = -(1.0 - se) * gamma_exc + # jacobian[sv["se"], sv["r_exc"]] = -(1.0 - se) * gamma_exc jacobian[sv["se"], sv["se"]] = 1.0 / tau_exc + gamma_exc * re - jacobian[sv["si"], sv["r_inh"]] = -1.0 + # jacobian[sv["si"], sv["r_inh"]] = -1.0 jacobian[sv["si"], sv["si"]] = 1.0 / tau_inh return jacobian diff --git a/tests/control/optimal_control/test_oc_ww.py b/tests/control/optimal_control/test_oc_ww.py index cd2778b5..ffe9b9d2 100644 --- a/tests/control/optimal_control/test_oc_ww.py +++ b/tests/control/optimal_control/test_oc_ww.py @@ -21,6 +21,9 @@ def test_1n(self): model = WWModel() test_oc_utils.setinitzero_1n(model) model.params["duration"] = p.TEST_DURATION_6 + # decrease time scale of sigmoidal function + # model.params["d_exc"] = 1.0 + # model.params["d_inh"] = 1.0 for input_channel in [0, 1]: for measure_channel in range(4): @@ -86,6 +89,10 @@ def test_2n(self): test_oc_utils.setinitzero_2n(model) model.params.duration = p.TEST_DURATION_10 + # decrease time scale of sigmoidal function + # model.params["d_exc"] = 1.0 + # model.params["d_inh"] = 1.0 + cost_mat = np.zeros((model.params.N, len(model.output_vars))) control_mat = np.zeros((model.params.N, len(model.state_vars))) control_mat[0, 0] = 1.0 From dd54e698bb99004383521d1d98c98ceba9be4a5c Mon Sep 17 00:00:00 2001 From: Lena Salfenmoser Date: Tue, 16 Jan 2024 19:49:12 +0100 Subject: [PATCH 03/14] formatting --- neurolib/control/optimal_control/oc.py | 164 +++++++------------------ 1 file changed, 43 insertions(+), 121 deletions(-) diff --git a/neurolib/control/optimal_control/oc.py b/neurolib/control/optimal_control/oc.py index 5bbf1ec6..b1c3dbab 100644 --- a/neurolib/control/optimal_control/oc.py +++ b/neurolib/control/optimal_control/oc.py @@ -62,9 +62,7 @@ def compute_gradient( for t in range(control_interval[0], control_interval[1]): grad[n, v, t] = df_du[n, v, t] for k in range(V): - grad[n, v, t] += ( - control_matrix[n, v] * adjoint_state[n, k, t] * d_du[n, k, v, t] - ) + grad[n, v, t] += control_matrix[n, v] * adjoint_state[n, k, t] * d_du[n, k, v, t] return grad @@ -132,23 +130,15 @@ def solve_adjoint( for k in krange: if dxdoth[n, k, k] == 0: res = fx_fullstate[n, k, t + 1] - res += adjoint_input( - hx_list, del_list, t, T, state_dim[1], adjoint_state, n, k - ) - res += adjoint_nw_input( - N, n, k, dmat_ndt, t, T, state_dim[1], adjoint_state, hx_nw - ) + res += adjoint_input(hx_list, del_list, t, T, state_dim[1], adjoint_state, n, k) + res += adjoint_nw_input(N, n, k, dmat_ndt, t, T, state_dim[1], adjoint_state, hx_nw) adjoint_state[n, k, t] = -res elif dxdoth[n, k, k] == 1: der = fx_fullstate[n, k, t + 1] - der += adjoint_input( - hx_list, del_list, t, T, state_dim[1], adjoint_state, n, k - ) - der += adjoint_nw_input( - N, n, k, dmat_ndt, t, T - 1, state_dim[1], adjoint_state, hx_nw - ) + der += adjoint_input(hx_list, del_list, t, T, state_dim[1], adjoint_state, n, k) + der += adjoint_nw_input(N, n, k, dmat_ndt, t, T - 1, state_dim[1], adjoint_state, hx_nw) adjoint_state[n, k, t] = adjoint_state[n, k, t + 1] - dt * der @@ -221,10 +211,7 @@ def adjoint_nw_input(N, n, k, dmat_ndt, t, T_lim, state_dim1, adj, hxnw): for n2 in range(N): # iterate through connectivity of current node "n" if t + 1 + dmat_ndt[n2, n] < T_lim: for v in range(state_dim1): - result += ( - adj[n2, v, t + 1 + dmat_ndt[n2, n]] - * hxnw[n2, n, t + 1 + dmat_ndt[n2, n], v, k] - ) + result += adj[n2, v, t + 1 + dmat_ndt[n2, n]] * hxnw[n2, n, t + 1 + dmat_ndt[n2, n], v, k] return result @@ -306,9 +293,7 @@ def convert_interval(interval, array_length): else: interval_1_new = interval_1 - assert ( - interval_0_new < interval_1_new - ), "Order of indices for interval is not valid." + assert interval_0_new < interval_1_new, "Order of indices for interval is not valid." assert interval_1_new <= array_length, "Interval is not specified in valid range." return interval_0_new, interval_1_new @@ -379,9 +364,7 @@ def __init__( if type(weights) != type(dict()): if weights is not None: - print( - "Weights parameter must be dictionary, use default weights instead." - ) + print("Weights parameter must be dictionary, use default weights instead.") self.weights = getdefaultweights() else: defaultweights = getdefaultweights() @@ -399,12 +382,8 @@ def __init__( self.N = self.model.params.N self.dt = self.model.params["dt"] # maybe redundant but for now code clarity - self.duration = self.model.params[ - "duration" - ] # maybe redundant but for now code clarity - self.T = ( - np.around(self.duration / self.dt, 0).astype(int) + 1 - ) # Total number of time steps + self.duration = self.model.params["duration"] # maybe redundant but for now code clarity + self.T = np.around(self.duration / self.dt, 0).astype(int) + 1 # Total number of time steps self.dim_vars = len(self.model.state_vars) self.dim_in = len(self.model.input_vars) @@ -418,9 +397,7 @@ def __init__( if self.N == 1: self.Dmat_ndt = np.zeros((self.N, self.N)).astype(int) else: - Dmat = computeDelayMatrix( - self.model.params.lengthMat, self.model.params.signalV - ) + Dmat = computeDelayMatrix(self.model.params.lengthMat, self.model.params.signalV) if self.model.name != "aln": Dmat[np.eye(len(Dmat)) == 1] = np.zeros(len(Dmat)) else: @@ -435,15 +412,11 @@ def __init__( self.cost_matrix = cost_matrix if isinstance(self.cost_matrix, type(None)): - self.cost_matrix = np.ones( - (self.N, self.dim_out) - ) # default: measure precision in all variables and nodes + self.cost_matrix = np.ones((self.N, self.dim_out)) # default: measure precision in all variables and nodes self.control_matrix = control_matrix if isinstance(self.control_matrix, type(None)): - self.control_matrix = np.ones( - (self.N, self.dim_in) - ) # default: all channels and all nodes active + self.control_matrix = np.ones((self.N, self.dim_in)) # default: all channels and all nodes active self.M = max(1, M) self.M_validation = M_validation @@ -466,9 +439,7 @@ def __init__( + 'If you want to study a deterministic system, please set model parameter "sigma_ou" to zero' ) if self.M > self.M_validation: - print( - 'Parameter "M_validation" should be chosen larger than parameter "M".' - ) + print('Parameter "M_validation" should be chosen larger than parameter "M".') else: # deterministic system if self.M > 1 or self.M_validation != 0 or validate_per_step: print( @@ -496,9 +467,7 @@ def __init__( self.print_array = print_array - self.zero_step_encountered = ( - False # deterministic gradient descent cannot further improve - ) + self.zero_step_encountered = False # deterministic gradient descent cannot further improve self.cost_interval = convert_interval(cost_interval, self.T) self.control_interval = convert_interval(control_interval, self.T) @@ -560,24 +529,17 @@ def adjust_init(self): for init_var in self.model.init_vars: if "ou" in init_var: continue - if ( - init_var[:-5] not in self.model.output_vars - and init_var[:-6] not in self.model.output_vars - ): + if init_var[:-5] not in self.model.output_vars and init_var[:-6] not in self.model.output_vars: continue iv = self.model.params[init_var] - self.model.params[init_var] = adjustArrayShape( - iv, np.ones((self.N, init_dur)) - ) + self.model.params[init_var] = adjustArrayShape(iv, np.ones((self.N, init_dur))) def adjust_input(self): """Adjust the shape of the array provided as input to the model. Use adjustArrayShape function from model_utils.""" for input_var in self.model.input_vars: iv = self.model.params[input_var] - self.model.params[input_var] = adjustArrayShape( - iv, np.ones((self.N, self.T)) - ) + self.model.params[input_var] = adjustArrayShape(iv, np.ones((self.N, self.T))) def get_xs(self): """Extract the complete state of the dynamical system.""" @@ -585,10 +547,11 @@ def get_xs(self): for ind_ov, ov in enumerate(self.model.output_vars): xs[:, ind_ov, 1:] = self.model[ov] - for iv in self.model.init_vars: - if str(ov) + "_init" == str(iv): - xs[:, ind_ov, 0] = self.model.params[iv][:, 0] - continue + if self.model.name != "wongwang": + for iv in self.model.init_vars: + if str(ov) + "_init" == str(iv): + xs[:, ind_ov, 0] = self.model.params[iv][:, 0] + continue return xs @@ -662,9 +625,7 @@ def compute_total_cost(self): self.dt, self.cost_interval, ) - control_strenght_cost = cost_functions.control_strength_cost( - self.control, self.weights, self.dt - ) + control_strenght_cost = cost_functions.control_strength_cost(self.control, self.weights, self.dt) return accuracy_cost + control_strenght_cost @abc.abstractmethod @@ -679,9 +640,7 @@ def compute_gradient(self): :rtype: np.ndarray of shape N x V x T """ self.solve_adjoint() - df_du = cost_functions.derivative_control_strength_cost( - self.control, self.weights - ) + df_du = cost_functions.derivative_control_strength_cost(self.control, self.weights) d_du = self.Duh() return compute_gradient( @@ -772,9 +731,7 @@ def decrease_step(self, cost, cost0, step, control0, factor_down, cost_gradient) counter = 0 - while ( - cost > cost0 - ): # Decrease the step size until first step size is found where cost is improved. + while cost > cost0: # Decrease the step size until first step size is found where cost is improved. step *= factor_down # Decrease step size. counter += 1 # print(step, cost, cost0) @@ -799,9 +756,7 @@ def decrease_step(self, cost, cost0, step, control0, factor_down, cost_gradient) else: cost = self.compute_total_cost() - if ( - counter == self.count_step - ): # Exit if the maximum search depth is reached without improvement of + if counter == self.count_step: # Exit if the maximum search depth is reached without improvement of # cost. step = 0.0 # For later analysis only. self.control = update_control_with_limit( @@ -850,9 +805,7 @@ def increase_step(self, cost, cost0, step, control0, factor_up, cost_gradient): cost_prev = cost0 counter = 0 - while ( - cost < cost_prev - ): # Increase the step size as long as the cost is improving. + while cost < cost_prev: # Increase the step size as long as the cost is improving. step *= factor_up counter += 1 @@ -869,9 +822,7 @@ def increase_step(self, cost, cost0, step, control0, factor_up, cost_gradient): self.update_input() self.simulate_forward() - if np.isnan( - self.get_xs() - ).any(): # Go back to last step (that was numerically stable and improved cost) + if np.isnan(self.get_xs()).any(): # Go back to last step (that was numerically stable and improved cost) # and exit. logging.info("Increasing step encountered NAN.") step /= factor_up # Undo the last step update by inverse operation. @@ -893,9 +844,7 @@ def increase_step(self, cost, cost0, step, control0, factor_up, cost_gradient): else: cost = self.compute_total_cost() - if ( - cost > cost_prev - ): # If the cost increases: go back to last step (that resulted in best cost until + if cost > cost_prev: # If the cost increases: go back to last step (that resulted in best cost until # then) and exit. step /= factor_up # Undo the last step update by inverse operation. self.control = update_control_with_limit( @@ -941,17 +890,11 @@ def step_size(self, cost_gradient): self.compute_total_cost() ) # Current cost without updating the control according to the "cost_gradient". - step = ( - self.step - ) # Load step size of last optimization-iteration as initial guess. + step = self.step # Load step size of last optimization-iteration as initial guess. - control0 = ( - self.control - ) # Memorize unchanged control throughout step-size computation. + control0 = self.control # Memorize unchanged control throughout step-size computation. - while ( - True - ): # Reduce the step size, if numerical instability occurs in the forward-simulation. + while True: # Reduce the step size, if numerical instability occurs in the forward-simulation. # inplace updating of models control bc. forward-sim relies on models parameters self.control = update_control_with_limit( self.N, @@ -967,12 +910,8 @@ def step_size(self, cost_gradient): # Input signal might be too high and produce diverging values in simulation. self.simulate_forward() - if np.isnan( - self.get_xs() - ).any(): # Detect numerical instability due to too large control update. - step *= ( - self.factor_down**2 - ) # Double the step for faster search of stable region. + if np.isnan(self.get_xs()).any(): # Detect numerical instability due to too large control update. + step *= self.factor_down**2 # Double the step for faster search of stable region. self.step = step print(f"Diverging model output, decrease step size to {step}.") else: @@ -988,18 +927,14 @@ def step_size(self, cost_gradient): if ( cost > cost0 ): # If the cost choosing the first (stable) step size is no improvement, reduce step size by bisection. - step, counter = self.decrease_step( - cost, cost0, step, control0, self.factor_down, cost_gradient - ) + step, counter = self.decrease_step(cost, cost0, step, control0, self.factor_down, cost_gradient) elif ( cost < cost0 ): # If the cost is improved with the first (stable) step size, search for larger steps with even better # reduction of cost. - step, counter = self.increase_step( - cost, cost0, step, control0, self.factor_up, cost_gradient - ) + step, counter = self.increase_step(cost, cost0, step, control0, self.factor_up, cost_gradient) else: # Remark: might be included as part of adaptive search for further improvement. step = 0.0 # For later analysis only. @@ -1035,9 +970,7 @@ def optimize(self, n_max_iterations): np.zeros(self.control.shape), self.maximum_control_strength, ) # To avoid issues in repeated executions. - self.control = limit_control_to_interval( - self.N, self.dim_in, self.T, self.control, self.control_interval - ) + self.control = limit_control_to_interval(self.N, self.dim_in, self.T, self.control, self.control_interval) if self.M == 1: print("Compute control for a deterministic system") @@ -1058,9 +991,7 @@ def optimize_deterministic(self, n_max_iterations): cost = self.compute_total_cost() print(f"Cost in iteration 0: %s" % (cost)) - if ( - len(self.cost_history) == 0 - ): # add only if control model has not yet been optimized + if len(self.cost_history) == 0: # add only if control model has not yet been optimized self.cost_history.append(cost) for i in range(1, n_max_iterations + 1): @@ -1098,9 +1029,7 @@ def optimize_noisy(self, n_max_iterations): if len(self.control_history) == 0: self.control_history.append(self.control) - if ( - self.validate_per_step - ): # if cost is computed for M_validation realizations in every step + if self.validate_per_step: # if cost is computed for M_validation realizations in every step for m in range(self.M): self.simulate_forward() grad_m[m, :] = self.compute_gradient() @@ -1135,16 +1064,12 @@ def optimize_noisy(self, n_max_iterations): print("Failed to improve further for noisy system.") if consecutive_zero_step > 2: - print( - "Failed to improve further for noisy system three times in a row, stop optimization." - ) + print("Failed to improve further for noisy system three times in a row, stop optimization.") break self.control_history.append(self.control) - if ( - self.validate_per_step - ): # if cost is computed for M_validation realizations in every step + if self.validate_per_step: # if cost is computed for M_validation realizations in every step for m in range(self.M): self.simulate_forward() grad_m[m, :] = self.compute_gradient() @@ -1170,10 +1095,7 @@ def optimize_noisy(self, n_max_iterations): self.control = oc self.update_input() self.cost_validation = self.compute_cost_noisy(self.M_validation) - print( - f"Final cost validated with %s noise realizations : %s" - % (self.M_validation, self.cost_validation) - ) + print(f"Final cost validated with %s noise realizations : %s" % (self.M_validation, self.cost_validation)) def compute_cost_noisy(self, M): """Computes the average cost from 'M_validation' noise realizations. From b13365dbe09cf185ec535121828cfd0dcc09e1cd Mon Sep 17 00:00:00 2001 From: Lena Salfenmoser Date: Tue, 16 Jan 2024 19:52:11 +0100 Subject: [PATCH 04/14] remove wrong line of code --- neurolib/control/optimal_control/oc.py | 9 ++++----- 1 file changed, 4 insertions(+), 5 deletions(-) diff --git a/neurolib/control/optimal_control/oc.py b/neurolib/control/optimal_control/oc.py index b1c3dbab..3b5d9c17 100644 --- a/neurolib/control/optimal_control/oc.py +++ b/neurolib/control/optimal_control/oc.py @@ -547,11 +547,10 @@ def get_xs(self): for ind_ov, ov in enumerate(self.model.output_vars): xs[:, ind_ov, 1:] = self.model[ov] - if self.model.name != "wongwang": - for iv in self.model.init_vars: - if str(ov) + "_init" == str(iv): - xs[:, ind_ov, 0] = self.model.params[iv][:, 0] - continue + for iv in self.model.init_vars: + if str(ov) + "_init" == str(iv): + xs[:, ind_ov, 0] = self.model.params[iv][:, 0] + continue return xs From 721183697b8f961bd344e5fda0185230d17b9445 Mon Sep 17 00:00:00 2001 From: Lena Salfenmoser Date: Tue, 16 Jan 2024 19:54:17 +0100 Subject: [PATCH 05/14] formatting --- neurolib/models/wc/timeIntegration.py | 73 +++++++-------------------- neurolib/models/ww/model.py | 4 +- neurolib/models/ww/timeIntegration.py | 57 +++++---------------- 3 files changed, 30 insertions(+), 104 deletions(-) diff --git a/neurolib/models/wc/timeIntegration.py b/neurolib/models/wc/timeIntegration.py index f68d0381..18d2675d 100644 --- a/neurolib/models/wc/timeIntegration.py +++ b/neurolib/models/wc/timeIntegration.py @@ -209,9 +209,7 @@ def S_I(x): exc_input_d[no] = 0 for l in range(N): - exc_input_d[no] += ( - K_gl * Cmat[no, l] * (excs[l, i - Dmat_ndt[no, l] - 1]) - ) + exc_input_d[no] += K_gl * Cmat[no, l] * (excs[l, i - Dmat_ndt[no, l] - 1]) # Wilson-Cowan model exc_rhs = ( @@ -221,10 +219,8 @@ def S_I(x): -excs[no, i - 1] + (1 - excs[no, i - 1]) * S_E( - c_excexc - * excs[no, i - 1] # input from within the excitatory population - - c_inhexc - * inhs[no, i - 1] # input from the inhibitory population + c_excexc * excs[no, i - 1] # input from within the excitatory population + - c_inhexc * inhs[no, i - 1] # input from the inhibitory population + exc_input_d[no] # input from other nodes + exc_ext_baseline # baseline external input (static) + exc_ext[no, i - 1] # time-dependent external input @@ -239,10 +235,8 @@ def S_I(x): -inhs[no, i - 1] + (1 - inhs[no, i - 1]) * S_I( - c_excinh - * excs[no, i - 1] # input from the excitatory population - - c_inhinh - * inhs[no, i - 1] # input from within the inhibitory population + c_excinh * excs[no, i - 1] # input from the excitatory population + - c_inhinh * inhs[no, i - 1] # input from within the inhibitory population + inh_ext_baseline # baseline external input (static) + inh_ext[no, i - 1] # time-dependent external input ) @@ -267,14 +261,10 @@ def S_I(x): # Ornstein-Uhlenbeck process exc_ou[no] = ( - exc_ou[no] - + (exc_ou_mean - exc_ou[no]) * dt / tau_ou - + sigma_ou * sqrt_dt * noise_exc[no] + exc_ou[no] + (exc_ou_mean - exc_ou[no]) * dt / tau_ou + sigma_ou * sqrt_dt * noise_exc[no] ) # mV/ms inh_ou[no] = ( - inh_ou[no] - + (inh_ou_mean - inh_ou[no]) * dt / tau_ou - + sigma_ou * sqrt_dt * noise_inh[no] + inh_ou[no] + (inh_ou_mean - inh_ou[no]) * dt / tau_ou + sigma_ou * sqrt_dt * noise_inh[no] ) # mV/ms return t, excs, inhs, exc_ou, inh_ou @@ -359,26 +349,14 @@ def jacobian_wc( jacobian = np.zeros((V, V)) input_exc = c_excexc * e - c_inhexc * i + nw_e + exc_ext_baseline + ue jacobian[sv["exc"], sv["exc"]] = ( - -( - -1.0 - - logistic(input_exc, a_exc, mu_exc) - + (1.0 - e) * c_excexc * logistic_der(input_exc, a_exc, mu_exc) - ) + -(-1.0 - logistic(input_exc, a_exc, mu_exc) + (1.0 - e) * c_excexc * logistic_der(input_exc, a_exc, mu_exc)) / tau_exc ) - jacobian[sv["exc"], sv["inh"]] = ( - -((1.0 - e) * (-c_inhexc) * logistic_der(input_exc, a_exc, mu_exc)) / tau_exc - ) + jacobian[sv["exc"], sv["inh"]] = -((1.0 - e) * (-c_inhexc) * logistic_der(input_exc, a_exc, mu_exc)) / tau_exc input_inh = c_excinh * e - c_inhinh * i + inh_ext_baseline + ui - jacobian[sv["inh"], sv["exc"]] = ( - -((1.0 - i) * c_excinh * logistic_der(input_inh, a_inh, mu_inh)) / tau_inh - ) + jacobian[sv["inh"], sv["exc"]] = -((1.0 - i) * c_excinh * logistic_der(input_inh, a_inh, mu_inh)) / tau_inh jacobian[sv["inh"], sv["inh"]] = ( - -( - -1.0 - - logistic(input_inh, a_inh, mu_inh) - + (1.0 - i) * (-c_inhinh) * logistic_der(input_inh, a_inh, mu_inh) - ) + -(-1.0 - logistic(input_inh, a_inh, mu_inh) + (1.0 - i) * (-c_inhinh) * logistic_der(input_inh, a_inh, mu_inh)) / tau_inh ) return jacobian @@ -472,9 +450,7 @@ def compute_nw_input(N, T, K_gl, cmat, dmat_ndt, exc_values): for t in range(1, T): for n in range(N): for l in range(N): - nw_input[n, t] += ( - K_gl * cmat[n, l] * (exc_values[l, t - dmat_ndt[n, l] - 1]) - ) + nw_input[n, t] += K_gl * cmat[n, l] * (exc_values[l, t - dmat_ndt[n, l] - 1]) return nw_input @@ -544,10 +520,7 @@ def compute_hx_nw( for n2 in range(N): for t in range(T - 1): hx_nw[n1, n2, t, sv["exc"], sv["exc"]] = ( - (1.0 - e[n1, t]) - * logistic_der(exc_input[n1, t], a_exc, mu_exc) - * K_gl - * cmat[n1, n2] + (1.0 - e[n1, t]) * logistic_der(exc_input[n1, t], a_exc, mu_exc) * K_gl * cmat[n1, n2] ) / tau_exc return -hx_nw @@ -626,22 +599,10 @@ def Duh( duh = np.zeros((N, V_vars, V_in, T)) for t in range(T): for n in range(N): - input_exc = ( - c_excexc * e[n, t] - - c_inhexc * i[n, t] - + nw_e[n, t] - + exc_ext_baseline - + ue[n, t] - ) - duh[n, sv["exc"], sv["exc"], t] = ( - -(1.0 - e[n, t]) * logistic_der(input_exc, a_exc, mu_exc) / tau_exc - ) - input_inh = ( - c_excinh * e[n, t] - c_inhinh * i[n, t] + inh_ext_baseline + ui[n, t] - ) - duh[n, sv["inh"], sv["inh"], t] = ( - -(1.0 - i[n, t]) * logistic_der(input_inh, a_inh, mu_inh) / tau_inh - ) + input_exc = c_excexc * e[n, t] - c_inhexc * i[n, t] + nw_e[n, t] + exc_ext_baseline + ue[n, t] + duh[n, sv["exc"], sv["exc"], t] = -(1.0 - e[n, t]) * logistic_der(input_exc, a_exc, mu_exc) / tau_exc + input_inh = c_excinh * e[n, t] - c_inhinh * i[n, t] + inh_ext_baseline + ui[n, t] + duh[n, sv["inh"], sv["inh"], t] = -(1.0 - i[n, t]) * logistic_der(input_inh, a_inh, mu_inh) / tau_inh return duh diff --git a/neurolib/models/ww/model.py b/neurolib/models/ww/model.py index d7e13c38..df6967b4 100644 --- a/neurolib/models/ww/model.py +++ b/neurolib/models/ww/model.py @@ -43,9 +43,7 @@ def __init__(self, params=None, Cmat=None, Dmat=None, seed=None): # load default parameters if none were given if params is None: - params = dp.loadDefaultParams( - Cmat=self.Cmat, Dmat=self.Dmat, seed=self.seed - ) + params = dp.loadDefaultParams(Cmat=self.Cmat, Dmat=self.Dmat, seed=self.seed) # Initialize base class Model super().__init__(integration=integration, params=params) diff --git a/neurolib/models/ww/timeIntegration.py b/neurolib/models/ww/timeIntegration.py index 125136ca..64fd9859 100644 --- a/neurolib/models/ww/timeIntegration.py +++ b/neurolib/models/ww/timeIntegration.py @@ -257,9 +257,7 @@ def r(I, a, b, d): # input from other nodes for l in range(N): - ses_input_d[no] += ( - K_gl * Cmat[no, l] * (ses[l, i - Dmat_ndt[no, l] - 1]) - ) + ses_input_d[no] += K_gl * Cmat[no, l] * (ses[l, i - Dmat_ndt[no, l] - 1]) # Wong-Wang se = ses[no, i - 1] @@ -271,18 +269,12 @@ def r(I, a, b, d): - J_I * si + J_NMDA * ses_input_d[no] ) - I_inh = ( - w_inh * (inh_current_baseline + inh_current[no, i - 1]) - + J_NMDA * se - - si - ) + I_inh = w_inh * (inh_current_baseline + inh_current[no, i - 1]) + J_NMDA * se - si r_exc[no, i] = r(I_exc, a_exc, b_exc, d_exc) r_inh[no, i] = r(I_inh, a_inh, b_inh, d_inh) - se_rhs = ( - -(se / tau_exc) + (1 - se) * gamma_exc * r_exc[no, i] + exc_ou[no] - ) # exc_ou = ou noise + se_rhs = -(se / tau_exc) + (1 - se) * gamma_exc * r_exc[no, i] + exc_ou[no] # exc_ou = ou noise si_rhs = -(si / tau_inh) + r_inh[no, i] + inh_ou[no] # Euler integration @@ -291,14 +283,10 @@ def r(I, a, b, d): # Ornstein-Uhlenberg process exc_ou[no] = ( - exc_ou[no] - + (exc_ou_mean - exc_ou[no]) * dt / tau_ou - + sigma_ou * sqrt_dt * noise_se[no] + exc_ou[no] + (exc_ou_mean - exc_ou[no]) * dt / tau_ou + sigma_ou * sqrt_dt * noise_se[no] ) # mV/ms inh_ou[no] = ( - inh_ou[no] - + (inh_ou_mean - inh_ou[no]) * dt / tau_ou - + sigma_ou * sqrt_dt * noise_si[no] + inh_ou[no] + (inh_ou_mean - inh_ou[no]) * dt / tau_ou + sigma_ou * sqrt_dt * noise_si[no] ) # mV/ms return t, r_exc, r_inh, ses, sis, exc_ou, inh_ou @@ -395,15 +383,8 @@ def jacobian_ww( ) = model_params jacobian = np.zeros((V, V)) - IE = ( - w_exc * (exc_current_baseline + ue) - + w_ee * J_NMDA * se - - J_I * si - + J_NMDA * nw_se - ) - jacobian[sv["r_exc"], sv["se"]] = ( - -logistic_der(IE, a_exc, b_exc, d_exc) * w_ee * J_NMDA - ) + IE = w_exc * (exc_current_baseline + ue) + w_ee * J_NMDA * se - J_I * si + J_NMDA * nw_se + jacobian[sv["r_exc"], sv["se"]] = -logistic_der(IE, a_exc, b_exc, d_exc) * w_ee * J_NMDA jacobian[sv["r_exc"], sv["si"]] = logistic_der(IE, a_exc, b_exc, d_exc) * J_I II = w_inh * (inh_current_baseline + ui) + J_NMDA * se - si jacobian[sv["r_inh"], sv["se"]] = -logistic_der(II, a_inh, b_inh, d_inh) * J_NMDA @@ -665,21 +646,13 @@ def compute_hx_nw( hx_nw = np.zeros((N, N, T, V, V)) nw_e = compute_nw_input(N, T, K_gl, cmat, dmat_ndt, se_delay) - IE = ( - w_exc * (exc_current_baseline + ue) - + w_ee * J_NMDA * se - - J_I * si - + J_NMDA * nw_e - ) + IE = w_exc * (exc_current_baseline + ue) + w_ee * J_NMDA * se - J_I * si + J_NMDA * nw_e for n1 in range(N): for n2 in range(N): for t in range(T - 1): hx_nw[n1, n2, t, sv["r_exc"], sv["se"]] = ( - logistic_der(IE[n1, t], a_exc, b_exc, d_exc) - * J_NMDA - * K_gl - * cmat[n1, n2] + logistic_der(IE[n1, t], a_exc, b_exc, d_exc) * J_NMDA * K_gl * cmat[n1, n2] ) return -hx_nw @@ -768,15 +741,9 @@ def Duh( - J_I * si[n, t] + J_NMDA * nw_e[n, t] ) - duh[n, sv["r_exc"], sv["r_exc"], t] = ( - -logistic_der(IE, a_exc, b_exc, d_exc) * w_exc - ) - II = ( - w_inh * (inh_current_baseline + ui[n, t]) + J_NMDA * se[n, t] - si[n, t] - ) - duh[n, sv["r_inh"], sv["r_inh"], t] = ( - -logistic_der(II, a_inh, b_inh, d_inh) * w_inh - ) + duh[n, sv["r_exc"], sv["r_exc"], t] = -logistic_der(IE, a_exc, b_exc, d_exc) * w_exc + II = w_inh * (inh_current_baseline + ui[n, t]) + J_NMDA * se[n, t] - si[n, t] + duh[n, sv["r_inh"], sv["r_inh"], t] = -logistic_der(II, a_inh, b_inh, d_inh) * w_inh return duh From 951d755853578fbe44ad8c04efb84afa13ecef5f Mon Sep 17 00:00:00 2001 From: Lena Salfenmoser Date: Tue, 16 Jan 2024 19:55:35 +0100 Subject: [PATCH 06/14] formatting --- .../control/optimal_control/test_oc_utils.py | 24 +++++-------------- 1 file changed, 6 insertions(+), 18 deletions(-) diff --git a/tests/control/optimal_control/test_oc_utils.py b/tests/control/optimal_control/test_oc_utils.py index 8e1b1d32..fc78d0e5 100644 --- a/tests/control/optimal_control/test_oc_utils.py +++ b/tests/control/optimal_control/test_oc_utils.py @@ -37,12 +37,8 @@ TEST_INPUT_1N_8 = ZERO_INPUT_1N_8.copy() INIT_INPUT_1N_8 = ZERO_INPUT_1N_8.copy() -TEST_INPUT_1N_8[ - :, : 1 + int(np.around(params.TEST_DURATION_6 / 0.1, 1)) -] = TEST_INPUT_1N_6 -INIT_INPUT_1N_8[ - :, : 1 + int(np.around(params.TEST_DURATION_6 / 0.1, 1)) -] = INIT_INPUT_1N_6 +TEST_INPUT_1N_8[:, : 1 + int(np.around(params.TEST_DURATION_6 / 0.1, 1))] = TEST_INPUT_1N_6 +INIT_INPUT_1N_8[:, : 1 + int(np.around(params.TEST_DURATION_6 / 0.1, 1))] = INIT_INPUT_1N_6 params.ZERO_INPUT_1N_8 = ZERO_INPUT_1N_8 params.TEST_INPUT_1N_8 = TEST_INPUT_1N_8 @@ -53,12 +49,8 @@ TEST_INPUT_1N_10 = ZERO_INPUT_1N_10.copy() INIT_INPUT_1N_10 = ZERO_INPUT_1N_10.copy() -TEST_INPUT_1N_10[ - :, : 1 + int(np.around(params.TEST_DURATION_6 / 0.1, 1)) -] = TEST_INPUT_1N_6 -INIT_INPUT_1N_10[ - :, : 1 + int(np.around(params.TEST_DURATION_6 / 0.1, 1)) -] = INIT_INPUT_1N_6 +TEST_INPUT_1N_10[:, : 1 + int(np.around(params.TEST_DURATION_6 / 0.1, 1))] = TEST_INPUT_1N_6 +INIT_INPUT_1N_10[:, : 1 + int(np.around(params.TEST_DURATION_6 / 0.1, 1))] = INIT_INPUT_1N_6 params.ZERO_INPUT_1N_10 = ZERO_INPUT_1N_10 params.TEST_INPUT_1N_10 = TEST_INPUT_1N_10 @@ -69,12 +61,8 @@ TEST_INPUT_1N_12 = ZERO_INPUT_1N_12.copy() INIT_INPUT_1N_12 = ZERO_INPUT_1N_12.copy() -TEST_INPUT_1N_12[ - :, : 1 + int(np.around(params.TEST_DURATION_6 / 0.1, 1)) -] = TEST_INPUT_1N_6 -INIT_INPUT_1N_12[ - :, : 1 + int(np.around(params.TEST_DURATION_6 / 0.1, 1)) -] = INIT_INPUT_1N_6 +TEST_INPUT_1N_12[:, : 1 + int(np.around(params.TEST_DURATION_6 / 0.1, 1))] = TEST_INPUT_1N_6 +INIT_INPUT_1N_12[:, : 1 + int(np.around(params.TEST_DURATION_6 / 0.1, 1))] = INIT_INPUT_1N_6 params.ZERO_INPUT_1N_12 = ZERO_INPUT_1N_12 params.TEST_INPUT_1N_12 = TEST_INPUT_1N_12 From 5693860b105fd43508f0247baa3b117c72a3cf07 Mon Sep 17 00:00:00 2001 From: Lena Salfenmoser Date: Tue, 16 Jan 2024 19:55:59 +0100 Subject: [PATCH 07/14] formatting --- tests/control/optimal_control/test_oc_wc.py | 24 ++++-------------- tests/control/optimal_control/test_oc_ww.py | 28 +++++---------------- 2 files changed, 11 insertions(+), 41 deletions(-) diff --git a/tests/control/optimal_control/test_oc_wc.py b/tests/control/optimal_control/test_oc_wc.py index 51db3356..ec4ab4c3 100644 --- a/tests/control/optimal_control/test_oc_wc.py +++ b/tests/control/optimal_control/test_oc_wc.py @@ -24,15 +24,11 @@ def test_1n(self): for input_channel in [0, 1]: for measure_channel in [0, 1]: - print( - "input_channel, measure_channel = ", input_channel, measure_channel - ) + print("input_channel, measure_channel = ", input_channel, measure_channel) cost_mat = np.zeros((model.params.N, len(model.output_vars))) control_mat = np.zeros((model.params.N, len(model.state_vars))) - control_mat[ - 0, input_channel - ] = 1.0 # only allow inputs to input_channel + control_mat[0, input_channel] = 1.0 # only allow inputs to input_channel cost_mat[0, measure_channel] = 1.0 # only measure other channel test_oc_utils.set_input(model, p.ZERO_INPUT_1N_6) @@ -60,10 +56,7 @@ def test_1n(self): for i in range(p.LOOPS): model_controlled.optimize(p.ITERATIONS) - c_diff = np.abs( - model_controlled.control[0, input_channel, :] - - p.TEST_INPUT_1N_6[0, :] - ) + c_diff = np.abs(model_controlled.control[0, input_channel, :] - p.TEST_INPUT_1N_6[0, :]) if np.amax(c_diff) < p.LIMIT_DIFF: control_coincide = True @@ -172,16 +165,9 @@ def test_2n_delay(self): model_controlled.optimize(p.ITERATIONS) # last entries of adjoint_state[0,0,:] are zero - self.assertTrue( - np.amax( - np.abs(model_controlled.adjoint_state[0, 0, -model.getMaxDelay() :]) - ) - == 0.0 - ) + self.assertTrue(np.amax(np.abs(model_controlled.adjoint_state[0, 0, -model.getMaxDelay() :])) == 0.0) - c_diff_max = np.amax( - np.abs(model_controlled.control[0, 0, :] - p.TEST_INPUT_2N_8[0, :]) - ) + c_diff_max = np.amax(np.abs(model_controlled.control[0, 0, :] - p.TEST_INPUT_2N_8[0, :])) if c_diff_max < p.LIMIT_DIFF: control_coincide = True break diff --git a/tests/control/optimal_control/test_oc_ww.py b/tests/control/optimal_control/test_oc_ww.py index ffe9b9d2..1005e508 100644 --- a/tests/control/optimal_control/test_oc_ww.py +++ b/tests/control/optimal_control/test_oc_ww.py @@ -27,15 +27,11 @@ def test_1n(self): for input_channel in [0, 1]: for measure_channel in range(4): - print( - "input_channel, measure_channel = ", input_channel, measure_channel - ) + print("input_channel, measure_channel = ", input_channel, measure_channel) cost_mat = np.zeros((model.params.N, len(model.output_vars))) control_mat = np.zeros((model.params.N, len(model.state_vars))) - control_mat[ - 0, input_channel - ] = 1.0 # only allow inputs to input_channel + control_mat[0, input_channel] = 1.0 # only allow inputs to input_channel cost_mat[0, measure_channel] = 1.0 # only measure other channel test_oc_utils.set_input(model, p.ZERO_INPUT_1N_6) @@ -63,10 +59,7 @@ def test_1n(self): for i in range(p.LOOPS): model_controlled.optimize(p.ITERATIONS) - c_diff = np.abs( - model_controlled.control[0, input_channel, :] - - p.TEST_INPUT_1N_6[0, :] - ) + c_diff = np.abs(model_controlled.control[0, input_channel, :] - p.TEST_INPUT_1N_6[0, :]) if np.amax(c_diff) < p.LIMIT_DIFF: control_coincide = True @@ -126,9 +119,7 @@ def test_2n(self): for i in range(p.LOOPS): model_controlled.optimize(p.ITERATIONS) - c_diff = np.abs( - model_controlled.control[0, 0, :] - p.TEST_INPUT_2N_10[0, :] - ) + c_diff = np.abs(model_controlled.control[0, 0, :] - p.TEST_INPUT_2N_10[0, :]) if np.amax(c_diff) < p.LIMIT_DIFF: control_coincide = True break @@ -184,16 +175,9 @@ def test_2n_delay(self): model_controlled.optimize(p.ITERATIONS) # last entries of adjoint_state[0,0,:] are zero - self.assertTrue( - np.amax( - np.abs(model_controlled.adjoint_state[0, 0, -model.getMaxDelay() :]) - ) - == 0.0 - ) + self.assertTrue(np.amax(np.abs(model_controlled.adjoint_state[0, 0, -model.getMaxDelay() :])) == 0.0) - c_diff_max = np.amax( - np.abs(model_controlled.control[0, 0, :] - p.TEST_INPUT_2N_8[0, :]) - ) + c_diff_max = np.amax(np.abs(model_controlled.control[0, 0, :] - p.TEST_INPUT_2N_8[0, :])) if c_diff_max < p.LIMIT_DIFF: control_coincide = True break From ef43a30007965b707d19d492cea54244100b538e Mon Sep 17 00:00:00 2001 From: Lena Salfenmoser Date: Wed, 17 Jan 2024 07:43:31 +0100 Subject: [PATCH 08/14] fixed problem in test_oc --- neurolib/control/optimal_control/oc.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/neurolib/control/optimal_control/oc.py b/neurolib/control/optimal_control/oc.py index 3b5d9c17..5c2d51be 100644 --- a/neurolib/control/optimal_control/oc.py +++ b/neurolib/control/optimal_control/oc.py @@ -80,7 +80,7 @@ def solve_adjoint( dxdoth, state_vars, output_vars, - model_name, + model_name=None, ): """Backwards integration of the adjoint state. From 3432d30f9d0301ab07106ed43f834e1e17760640 Mon Sep 17 00:00:00 2001 From: Lena Salfenmoser Date: Thu, 15 Feb 2024 08:45:02 +0100 Subject: [PATCH 09/14] relabelling of "delay" => "delayed" --- neurolib/models/ww/timeIntegration.py | 24 ++++++++++++------------ 1 file changed, 12 insertions(+), 12 deletions(-) diff --git a/neurolib/models/ww/timeIntegration.py b/neurolib/models/ww/timeIntegration.py index 64fd9859..bf4f395a 100644 --- a/neurolib/models/ww/timeIntegration.py +++ b/neurolib/models/ww/timeIntegration.py @@ -408,7 +408,7 @@ def compute_hx( V, T, dyn_vars, - dyn_vars_delay, + dyn_vars_delayed, control, sv, ): @@ -430,8 +430,8 @@ def compute_hx( :type T: int :param dyn_vars: N x V x T array containing all values of 'exc' and 'inh'. :type dyn_vars: np.ndarray - :param dyn_vars_delay: - :type dyn_vars_delay: np.ndarray + :param dyn_vars_delayed: N x V x T array containing all delayed values of 'exc' and 'inh'. + :type dyn_vars_delayed: np.ndarray :param control: N x 2 x T control inputs to 'exc' and 'inh'. :type control: np.ndarray :param sv: dictionary of state vars and respective indices @@ -441,7 +441,7 @@ def compute_hx( :rtype: np.ndarray """ hx = np.zeros((N, T, V, V)) - nw_e = compute_nw_input(N, T, K_gl, cmat, dmat_ndt, dyn_vars_delay[:, sv["se"], :]) + nw_e = compute_nw_input(N, T, K_gl, cmat, dmat_ndt, dyn_vars_delayed[:, sv["se"], :]) for n in range(N): for t in range(T): @@ -591,7 +591,7 @@ def compute_hx_nw( T, se, si, - se_delay, + se_delayed, ue, sv, ): @@ -615,8 +615,8 @@ def compute_hx_nw( :type se: np.ndarray :param si: Array of the se-variable. :type si: np.ndarray - :param se_delay: Value of delayed se-variable. - :type se_delay: np.ndarray + :param se_delayed: Value of delayed se-variable. + :type se_delayed: np.ndarray :param ue: N x T array of the total input received by 'exc' population in every node at any time. :type ue: np.ndarray :param sv: dictionary of state vars and respective indices @@ -645,7 +645,7 @@ def compute_hx_nw( ) = model_params hx_nw = np.zeros((N, N, T, V, V)) - nw_e = compute_nw_input(N, T, K_gl, cmat, dmat_ndt, se_delay) + nw_e = compute_nw_input(N, T, K_gl, cmat, dmat_ndt, se_delayed) IE = w_exc * (exc_current_baseline + ue) + w_ee * J_NMDA * se - J_I * si + J_NMDA * nw_e for n1 in range(N): @@ -672,7 +672,7 @@ def Duh( K_gl, cmat, dmat_ndt, - se_delay, + se_delayed, sv, ): """Jacobian of systems dynamics wrt. external inputs (control signals). @@ -703,8 +703,8 @@ def Duh( :type cmat: np.ndarray :param dmat_ndt: delay index matrix :type dmat_ndt: np.ndarray - :param se_delay: N x T array containing values of 'exc' of all nodes through time. - :type se_delay: np.ndarray + :param se_delayed: N x T array containing values of 'exc' of all nodes through time. + :type se_delayed: np.ndarray :param sv: dictionary of state vars and respective indices :type sv: dict @@ -730,7 +730,7 @@ def Duh( w_ee, ) = model_params - nw_e = compute_nw_input(N, T, K_gl, cmat, dmat_ndt, se_delay) + nw_e = compute_nw_input(N, T, K_gl, cmat, dmat_ndt, se_delayed) duh = np.zeros((N, V_vars, V_in, T)) for t in range(T): From e85171ea54e7ecc5986419bb0e5327bead85dcc2 Mon Sep 17 00:00:00 2001 From: Lena Salfenmoser Date: Thu, 15 Feb 2024 08:47:37 +0100 Subject: [PATCH 10/14] relabelling "delay" => "delayed" in WC time integration file --- neurolib/models/wc/timeIntegration.py | 38 ++++++++++++++------------- 1 file changed, 20 insertions(+), 18 deletions(-) diff --git a/neurolib/models/wc/timeIntegration.py b/neurolib/models/wc/timeIntegration.py index 18d2675d..be57bb32 100644 --- a/neurolib/models/wc/timeIntegration.py +++ b/neurolib/models/wc/timeIntegration.py @@ -372,7 +372,7 @@ def compute_hx( V, T, dyn_vars, - dyn_vars_delay, + dyn_vars_delayed, control, sv, ): @@ -394,8 +394,8 @@ def compute_hx( :type T: int :param dyn_vars: N x V x T array containing all values of 'exc' and 'inh'. :type dyn_vars: np.ndarray - :param dyn_vars_delay: - :type dyn_vars_delay: np.ndarray + :param dyn_vars_delayed: N x V x T array containing all values of delayed 'exc' and 'inh'. + :type dyn_vars_delayed: np.ndarray :param control: N x 2 x T control inputs to 'exc' and 'inh'. :type control: np.ndarray :param sv: dictionary of state vars and respective indices @@ -405,7 +405,7 @@ def compute_hx( :rtype: np.ndarray """ hx = np.zeros((N, T, V, V)) - nw_e = compute_nw_input(N, T, K_gl, cmat, dmat_ndt, dyn_vars_delay[:, sv["exc"], :]) + nw_e = compute_nw_input(N, T, K_gl, cmat, dmat_ndt, dyn_vars_delayed[:, sv["exc"], :]) for n in range(N): for t in range(T): @@ -465,7 +465,7 @@ def compute_hx_nw( T, e, i, - e_delay, + e_delayed, ue, sv, ): @@ -485,14 +485,16 @@ def compute_hx_nw( :type V: int :param T: Length of simulation (time dimension). :type T: int - :param e: Value of the E-variable at specific time. - :type e: float - :param i: Value of the I-variable at specific time. - :type i: float - :param ue: N x T array of the total input received by 'exc' population in every node at any time. - :type ue: np.ndarray - :param sv: dictionary of state vars and respective indices - :type sv: dict + :param e: Value of the E-variable at specific time. + :type e: float + :param i: Value of the I-variable at specific time. + :type i: float + :param e_delayed: Value of the delayed E-variable at specific time. + :type e_delayed: float + :param ue: N x T array of the total input received by 'exc' population in every node at any time. + :type ue: np.ndarray + :param sv: dictionary of state vars and respective indices + :type sv: dict :return: Jacobians for network connectivity in all time steps. :rtype: np.ndarray of shape N x N x T x 4 x 4 @@ -513,7 +515,7 @@ def compute_hx_nw( ) = model_params hx_nw = np.zeros((N, N, T, V, V)) - nw_e = compute_nw_input(N, T, K_gl, cmat, dmat_ndt, e_delay) + nw_e = compute_nw_input(N, T, K_gl, cmat, dmat_ndt, e_delayed) exc_input = c_excexc * e - c_inhexc * i + nw_e + exc_ext_baseline + ue for n1 in range(N): @@ -540,7 +542,7 @@ def Duh( K_gl, cmat, dmat_ndt, - exc_delay, + exc_delayed, sv, ): """Jacobian of systems dynamics wrt. external inputs (control signals). @@ -571,8 +573,8 @@ def Duh( :type cmat: np.ndarray :param dmat_ndt: delay index matrix :type dmat_ndt: np.ndarray - :param exc_delay: N x T array containing values of 'exc' of all nodes through time incl. delay - :type exc_delay: np.ndarray + :param exc_delayed: N x T array containing values of 'exc' of all nodes through time incl. delay + :type exc_delayed: np.ndarray :param sv: dictionary of state vars and respective indices :type sv: dict @@ -594,7 +596,7 @@ def Duh( inh_ext_baseline, ) = model_params - nw_e = compute_nw_input(N, T, K_gl, cmat, dmat_ndt, exc_delay) + nw_e = compute_nw_input(N, T, K_gl, cmat, dmat_ndt, exc_delayed) duh = np.zeros((N, V_vars, V_in, T)) for t in range(T): From 2736c750f76f57ff0a0bbcc84d8a8fa9e0af3863 Mon Sep 17 00:00:00 2001 From: Lena Salfenmoser Date: Thu, 15 Feb 2024 08:52:15 +0100 Subject: [PATCH 11/14] relabelling "del" => "delayed" in aln model for consistency --- neurolib/models/aln/timeIntegration.py | 108 ++++++++++++------------- 1 file changed, 54 insertions(+), 54 deletions(-) diff --git a/neurolib/models/aln/timeIntegration.py b/neurolib/models/aln/timeIntegration.py index fd953540..0b6a8283 100644 --- a/neurolib/models/aln/timeIntegration.py +++ b/neurolib/models/aln/timeIntegration.py @@ -732,8 +732,8 @@ def jacobian_aln( uri, nw_input, nw_input_sq, - re_del, - ri_del, + re_delayed, + ri_delayed, sv, ): """Jacobian of the ALN dynamical system. @@ -754,10 +754,10 @@ def jacobian_aln( :type nw_input: float :param nw_input_sq: sum of all network inputs into current node at current time with squared prefactors :type nw_input_sq: float - :param re_del: E rate delayed by de - :type re_del: float - :param ri_del: I rate delayed by di - :type ri_del: float + :param re_delayed: E rate delayed by de + :type re_delayed: float + :param ri_delayed: I rate delayed by di + :type ri_delayed: float :param sv: dictionary of state vars and respective indices :type sv: dict @@ -806,15 +806,15 @@ def jacobian_aln( jacobian = np.zeros((V, V)) - z1ee = z1ee_f * re_del + nw_input + c_gl * Ke_gl * ure - z2ee = z2ee_f * re_del + nw_input_sq + c_gl**2 * Ke_gl * ure - z1ei = z1ei_f * ri_del - z2ei = z2ei_f * ri_del + z1ee = z1ee_f * re_delayed + nw_input + c_gl * Ke_gl * ure + z2ee = z2ee_f * re_delayed + nw_input_sq + c_gl**2 * Ke_gl * ure + z1ei = z1ei_f * ri_delayed + z2ei = z2ei_f * ri_delayed - z1ie = z1ie_f * re_del + c_gl * Ke_gl * uri - z2ie = z2ie_f * re_del + c_gl**2 * Ke_gl * uri - z1ii = z1ii_f * ri_del - z2ii = z2ii_f * ri_del + z1ie = z1ie_f * re_delayed + c_gl * Ke_gl * uri + z2ie = z2ie_f * re_delayed + c_gl**2 * Ke_gl * uri + z1ii = z1ii_f * ri_delayed + z2ii = z2ii_f * ri_delayed sig_ee_den = (1 + z1ee) * taum + tau_se sig_ei_den = (1 + z1ei) * taum + tau_si @@ -1004,7 +1004,7 @@ def compute_hx( ui = control[n, sv["rates_inh"], t] ure = control[n, sv["mufe"], t] uri = control[n, sv["mufi"], t] - re_del, ri_del = dyn_vars[n, sv["rates_exc"], t - ndt_de], dyn_vars[n, sv["rates_inh"], t - ndt_di] + re_delayed, ri_delayed = dyn_vars[n, sv["rates_exc"], t - ndt_de], dyn_vars[n, sv["rates_inh"], t - ndt_di] hx[n, t, :, :] = jacobian_aln( model_params, precomp_factors, @@ -1016,8 +1016,8 @@ def compute_hx( uri, nw_input[n, t], nw_input_sq[n, t], - re_del, - ri_del, + re_delayed, + ri_delayed, sv, ) @@ -1056,8 +1056,8 @@ def jacobian_de( ure, uri, nw_input, - re_del, - ri_del, + re_delayed, + ri_delayed, sv, ): """Jacobian of the ALN dynamical system wrt relations with delay de @@ -1076,10 +1076,10 @@ def jacobian_de( :type ui: float :param nw_input: sum of all network inputs into current node at current time :type nw_input: float - :param re_del: E rate delayed by de - :type re_del: float - :param ri_del: I rate delayed by di - :type ri_del: float + :param re_delayed: E rate delayed by de + :type re_delayed: float + :param ri_delayed: I rate delayed by di + :type ri_delayed: float :param sv: dictionary of state vars and respective indices :type sv: dict @@ -1127,10 +1127,10 @@ def jacobian_de( jacobian = np.zeros((V, V)) - z1ee = z1ee_f * re_del + nw_input + c_gl * Ke_gl * ure # factors 1e-3 are in z1ee_f and in ne_input - z1ei = z1ei_f * ri_del - z1ie = z1ie_f * re_del + c_gl * Ke_gl * uri - z1ii = z1ii_f * ri_del + z1ee = z1ee_f * re_delayed + nw_input + c_gl * Ke_gl * ure # factors 1e-3 are in z1ee_f and in ne_input + z1ei = z1ei_f * ri_delayed + z1ie = z1ie_f * re_delayed + c_gl * Ke_gl * uri + z1ii = z1ii_f * ri_delayed sig_ee_den = (1 + z1ee) * taum + tau_se sig_ei_den = (1 + z1ei) * taum + tau_si @@ -1283,7 +1283,7 @@ def compute_hx_de( ui = control[n, sv["rates_inh"], t] ure = control[n, sv["mufe"], t] uri = control[n, sv["mufi"], t] - re_del, ri_del = dyn_vars[n, sv["rates_exc"], t - ndt_de], dyn_vars[n, sv["rates_inh"], t - ndt_di] + re_delayed, ri_delayed = dyn_vars[n, sv["rates_exc"], t - ndt_de], dyn_vars[n, sv["rates_inh"], t - ndt_di] hx[n, t, :, :] = jacobian_de( model_params, precomp_factors, @@ -1294,8 +1294,8 @@ def compute_hx_de( ure, uri, nw_input[n, t], - re_del, - ri_del, + re_delayed, + ri_delayed, sv, ) @@ -1313,8 +1313,8 @@ def jacobian_di( ure, uri, nw_input, - re_del, - ri_del, + re_delayed, + ri_delayed, sv, ): """Jacobian of the ALN dynamical system wrt relations with delay di @@ -1332,10 +1332,10 @@ def jacobian_di( :type ui: float :param nw_input: sum of all network inputs into current node at current time :type nw_input: float - :param re_del: E rate delayed by de - :type re_del: float - :param ri_del: I rate delayed by di - :type ri_del: float + :param re_delayed: E rate delayed by de + :type re_delayed: float + :param ri_delayed: I rate delayed by di + :type ri_delayed: float :param sv: dictionary of state vars and respective indices :type sv: dict @@ -1383,10 +1383,10 @@ def jacobian_di( jacobian = np.zeros((V, V)) - z1ee = z1ee_f * re_del + nw_input + c_gl * Ke_gl * ure - z1ei = z1ei_f * ri_del - z1ie = z1ie_f * re_del + c_gl * Ke_gl * uri - z1ii = z1ii_f * ri_del + z1ee = z1ee_f * re_delayed + nw_input + c_gl * Ke_gl * ure + z1ei = z1ei_f * ri_delayed + z1ie = z1ie_f * re_delayed + c_gl * Ke_gl * uri + z1ii = z1ii_f * ri_delayed sig_ee_den = (1 + z1ee) * taum + tau_se sig_ei_den = (1 + z1ei) * taum + tau_si @@ -1541,7 +1541,7 @@ def compute_hx_di( ui = control[n, sv["rates_inh"], t] ure = control[n, sv["mufe"], t] uri = control[n, sv["mufi"], t] - re_del, ri_del = dyn_vars[n, sv["rates_exc"], t - ndt_de], dyn_vars[n, sv["rates_inh"], t - ndt_di] + re_delayed, ri_delayed = dyn_vars[n, sv["rates_exc"], t - ndt_de], dyn_vars[n, sv["rates_inh"], t - ndt_di] hx[n, t, :, :] = jacobian_di( model_params, precomp_factors, @@ -1552,8 +1552,8 @@ def compute_hx_di( ure, uri, nw_input[n, t], - re_del, - ri_del, + re_delayed, + ri_delayed, sv, ) @@ -1617,7 +1617,7 @@ def compute_hx_nw( if cmat[n1, n2] == 0.0: continue for t in range(T): - re_del, ri_del = dyn_vars[n1, sv["rates_exc"], t - ndt_de], dyn_vars[n1, sv["rates_inh"], t - ndt_di] + re_delayed, ri_delayed = dyn_vars[n1, sv["rates_exc"], t - ndt_de], dyn_vars[n1, sv["rates_inh"], t - ndt_di] ue = control[n1, sv["rates_exc"], t] ure = control[n1, sv["mufe"], t] hx_nw[n1, n2, t, :, :] = jacobian_nw( @@ -1625,8 +1625,8 @@ def compute_hx_nw( precomp_factors, V, dyn_vars[n1, :, t], - re_del, - ri_del, + re_delayed, + ri_delayed, nw_input[n1, t], cmat[n1, n2], ue, @@ -1643,8 +1643,8 @@ def jacobian_nw( precomp_factors, V, fullstate, - re_del, - ri_del, + re_delayed, + ri_delayed, nw_input, cmat_entry, ue, @@ -1661,10 +1661,10 @@ def jacobian_nw( :type V: int :param fullstate: Value of all V=16 dynamical variables at given time :type fullstate: np.ndarray - :param re_del: E rate delayed by de - :type re_del: float - :param ri_del: I rate delayed by di - :type ri_del: float + :param re_delayed: E rate delayed by de + :type re_delayed: float + :param ri_delayed: I rate delayed by di + :type ri_delayed: float :param nw_input: sum of all network inputs into current node at current time :type nw_input: float :param cmat_entry: Entry of the connectivity matrix at n1, n2 @@ -1719,8 +1719,8 @@ def jacobian_nw( jac_nw = np.zeros((V, V)) - z1ee = z1ee_f * re_del + nw_input + c_gl * Ke_gl * ure - z1ei = z1ei_f * ri_del + z1ee = z1ee_f * re_delayed + nw_input + c_gl * Ke_gl * ure + z1ei = z1ei_f * ri_delayed sig_ee_den = (1 + z1ee) * taum + tau_se sig_ei_den = (1 + z1ei) * taum + tau_si From 3daca122b6599e42f9f6b8cb7fa61058017a21f7 Mon Sep 17 00:00:00 2001 From: Lena Salfenmoser Date: Thu, 15 Feb 2024 08:54:16 +0100 Subject: [PATCH 12/14] Relabelling "delay" => "delayed" in oc file --- neurolib/control/optimal_control/oc.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/neurolib/control/optimal_control/oc.py b/neurolib/control/optimal_control/oc.py index 5c2d51be..0af3d9b0 100644 --- a/neurolib/control/optimal_control/oc.py +++ b/neurolib/control/optimal_control/oc.py @@ -554,7 +554,7 @@ def get_xs(self): return xs - def get_xs_delay(self): + def get_xs_delayed(self): """Extract the complete state of the delayed dynamical system.""" maxdel = self.model.getMaxDelay() if maxdel == 0: From 397597eb2679b3891b76f388935478860292e81b Mon Sep 17 00:00:00 2001 From: Lena Salfenmoser Date: Thu, 15 Feb 2024 08:55:04 +0100 Subject: [PATCH 13/14] Relabelling "delay" => "delayed" in oc_ww --- neurolib/control/optimal_control/oc_ww/oc_ww.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/neurolib/control/optimal_control/oc_ww/oc_ww.py b/neurolib/control/optimal_control/oc_ww/oc_ww.py index 90931119..96e0daf4 100644 --- a/neurolib/control/optimal_control/oc_ww/oc_ww.py +++ b/neurolib/control/optimal_control/oc_ww/oc_ww.py @@ -83,7 +83,7 @@ def Duh(self): """ xs = self.get_xs() - xsd = self.get_xs_delay() + xsd = self.get_xs_delayed() return Duh( self.model_params, @@ -127,7 +127,7 @@ def compute_hx(self): self.dim_vars, self.T, self.get_xs(), - self.get_xs_delay(), + self.get_xs_delayed(), self.control, self.state_vars_dict, ) @@ -167,7 +167,7 @@ def compute_hx_nw(self): self.T, xs[:, self.state_vars_dict["se"], :], xs[:, self.state_vars_dict["se"], :], - self.get_xs_delay()[:, self.state_vars_dict["se"], :], + self.get_xs_delayed()[:, self.state_vars_dict["se"], :], self.control[:, self.state_vars_dict["r_exc"], :], self.state_vars_dict, ) From 71dd40043fd8efc57c42b2c41fe6fc1f2daf40f5 Mon Sep 17 00:00:00 2001 From: Lena Salfenmoser Date: Thu, 15 Feb 2024 08:55:36 +0100 Subject: [PATCH 14/14] relabelling "delay" => "delayed" in oc_wc --- neurolib/control/optimal_control/oc_wc/oc_wc.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/neurolib/control/optimal_control/oc_wc/oc_wc.py b/neurolib/control/optimal_control/oc_wc/oc_wc.py index 1329228a..bb9cb586 100644 --- a/neurolib/control/optimal_control/oc_wc/oc_wc.py +++ b/neurolib/control/optimal_control/oc_wc/oc_wc.py @@ -73,7 +73,7 @@ def Duh(self): """ xs = self.get_xs() - xsd = self.get_xs_delay() + xsd = self.get_xs_delayed() return Duh( self.model_params, @@ -116,7 +116,7 @@ def compute_hx(self): self.dim_vars, self.T, self.get_xs(), - self.get_xs_delay(), + self.get_xs_delayed(), self.control, self.state_vars_dict, ) @@ -140,7 +140,7 @@ def compute_hx_nw(self): self.T, xs[:, self.state_vars_dict["exc"], :], xs[:, self.state_vars_dict["inh"], :], - self.get_xs_delay()[:, self.state_vars_dict["exc"], :], + self.get_xs_delayed()[:, self.state_vars_dict["exc"], :], self.control[:, self.state_vars_dict["exc"], :], self.state_vars_dict, )