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cas-pml/SL/aufgaben/template/2_Code/3.2 Regression - Klassisch.ipynb
T
2026-05-21 14:16:30 +02:00

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{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"tags": []
},
"source": [
"# Feature Engineering\n",
"# Klassifikation\n",
"# Regression\n",
"## Einleitung\n",
"## Klassische Methoden "
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import sys\n",
"sys.path.append('./')"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"ExecuteTime": {
"end_time": "2020-04-08T10:06:24.890328Z",
"start_time": "2020-04-08T10:06:23.220148Z"
}
},
"outputs": [],
"source": [
"## prepare env and data\n",
"import pandas as pd\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"import seaborn as sns; sns.set()\n",
"%matplotlib inline\n",
"\n",
"datapath = '../3_data'\n",
"from os import chdir; chdir(datapath)\n",
"\n",
"from bfh_cas_pml import prep_data, prep_demo_data\n",
"X_train, X_test, y_train, y_test = prep_data('melb_data_prep.csv', 'Price', seed = 1234)\n",
"X_demo, y_demo = prep_demo_data('demo_data_regr.csv', 'y')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### LinearRegression (OLS)\n",
"#### Theorie"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"ExecuteTime": {
"end_time": "2020-04-08T10:06:26.121955Z",
"start_time": "2020-04-08T10:06:25.513807Z"
}
},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 600x600 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"## regression line on the base of demo data\n",
"plt.figure(figsize=(6,6))\n",
"ax = sns.regplot(x=X_demo, y=y_demo, ci=None)\n",
"ax.set(xlabel='X', ylabel='y');"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"ExecuteTime": {
"end_time": "2020-04-08T10:06:28.087182Z",
"start_time": "2020-04-08T10:06:28.060238Z"
},
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'copy_X': True, 'fit_intercept': True, 'n_jobs': None, 'positive': False}\n",
"model.intercept_ : -0.34791755729146434\n",
"model.coef_ : [0.41378104]\n",
"model.score : 0.6460242903212707\n"
]
}
],
"source": [
"## information about trained model\n",
"\n",
"## train\n",
"from sklearn.linear_model import LinearRegression\n",
"model = LinearRegression()\n",
"model.fit(X_demo, y_demo)\n",
"print(model.get_params())\n",
"\n",
"## model attributes\n",
"#print(model)\n",
"print('model.intercept_ :', model.intercept_)\n",
"print('model.coef_ :', model.coef_)\n",
"\n",
"## score\n",
"print('model.score :', model.score(X_demo, y_demo))"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"ExecuteTime": {
"end_time": "2020-04-08T10:06:28.593092Z",
"start_time": "2020-04-08T10:06:28.091186Z"
},
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"0.6460242903212707\n"
]
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 600x600 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"## qualitative and quantitative diagnostics\n",
"## make predictions\n",
"y_pred = model.predict(X_demo)\n",
"\n",
"## calc r2_score with skearn.metrics.r2_score\n",
"from sklearn.metrics import r2_score\n",
"print(r2_score(y_demo, y_pred))\n",
"\n",
"## visualize\n",
"plt.figure(figsize=(6,6))\n",
"ax = sns.scatterplot(x=y_pred, y=y_demo)\n",
"ax.set(xlabel='y_pred', ylabel='y')\n",
"ls = np.linspace(0.8, 2.6, 100)\n",
"plt.plot(ls, ls, color='black', linestyle='dashed');"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Exkurs: Lineare Regression mit Matrix-Operationen"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"see `extra_3.2.1.2_linear_regression_with_matrix_operations.ipynb`"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Praxis"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"ExecuteTime": {
"end_time": "2020-04-08T10:06:29.658010Z",
"start_time": "2020-04-08T10:06:29.644592Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'copy_X': True, 'fit_intercept': True, 'n_jobs': None, 'positive': False}\n"
]
}
],
"source": [
"## load classes and define model\n",
"from sklearn.linear_model import LinearRegression\n",
"model = LinearRegression()\n",
"model.fit(X_train, y_train)\n",
"print(model.get_params())"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"ExecuteTime": {
"end_time": "2020-04-08T10:06:29.658010Z",
"start_time": "2020-04-08T10:06:29.644592Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"-105513873.23404828\n",
"[ 2.45383606e+05 -1.41356398e+05 -4.03836664e+04 1.61336039e+05\n",
" 4.03911483e+04 8.33032709e+04 2.73783998e+05 -2.48422914e+03\n",
" -4.97722450e+03 -5.15021962e+05 1.92635869e+05 -1.19821800e+00\n",
" 9.42690151e+04 4.16608193e+04 5.41816991e+04 -1.85021045e+05\n",
" 8.79055470e+04 2.43998169e+05 2.65590236e+05 -2.31675039e+05\n",
" 1.75618897e+03 3.11569156e+04 4.70830468e+03]\n",
"Index(['Rooms', 'Type', 'Distance', 'Bathroom', 'Car', 'logLandsize',\n",
" 'logBuildingArea', 'YearBuilt', 'CouncilArea', 'Lattitude',\n",
" 'Longtitude', 'Propertycount', 'Method_S', 'Method_SP', 'Method_VB',\n",
" 'Regionname_Northern_Metropolitan',\n",
" 'Regionname_South_Eastern_Metropolitan',\n",
" 'Regionname_Southern_Metropolitan', 'Regionname_Victoria',\n",
" 'Regionname_Western_Metropolitan', 'month', 'year', 'day_of_week'],\n",
" dtype='object')\n"
]
}
],
"source": [
"## attributes\n",
"print(model.intercept_)\n",
"print(model.coef_)\n",
"print(X_train.columns) ## no model attribute"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"ExecuteTime": {
"end_time": "2020-04-08T10:06:29.658010Z",
"start_time": "2020-04-08T10:06:29.644592Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"0.5601419746121182\n"
]
}
],
"source": [
"## methode: Model score\n",
"print(model.score(X_test, y_test))"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"ExecuteTime": {
"end_time": "2020-04-08T10:06:29.658010Z",
"start_time": "2020-04-08T10:06:29.644592Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"0.5601419746121182\n"
]
}
],
"source": [
"## control with predict and explicit use of r2_score\n",
"from sklearn.metrics import r2_score\n",
"y_pred = model.predict(X_test)\n",
"print(r2_score(y_test, y_pred))"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"ExecuteTime": {
"end_time": "2020-04-08T10:06:30.136433Z",
"start_time": "2020-04-08T10:06:29.660156Z"
}
},
"outputs": [
{
"data": {
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BMy0tTR59dJKnl0MKCYUEIYQQj7Fnz27liUBpJyZ41q1b39NLIoWEQoIQQojH+PHH76VSpcqyatW3UqNGTU8vh7gBhQQhhJDLzpkzZ9TPsWMfljVrvpeKFSt6eknETSgkCCGEXFbWrv1KrrmmuZqdgU6VERERnl4SKQIUEoQQQi4bixZ9JsOHD5Wbbuoh7dp18PRySDFAIUEIIeSyMHfuLNX2+vbb75LZs+dLaGiop5dEigEKCUIIISVOZmamfPLJAnnwwXEydeo0CQoK8vSSSDHBzpaEEEJKdAx4YmKCxMWVV0mVUVHRnODpZ9AjQQghpETIy8uTRx4ZK716dZOsrCyJji5DEeGHeIWQWLFihdx8883SrFkzueWWW+Trr7/29JIIIYQUAQiHkSPvUcmV48dPZMtrP8bjQmLlypXy1FNPyZ133ilr1qyRXr16yYQJE2Tr1q2eXhohhBA3QKvroUOHyHfffS3z5y+UwYNv9/SSiL8KCcTO3n33XRk2bJgSErVq1ZIHHnhAOnToIH/88Ycnl0YIIcRN/vpri2zd+pd8/vlS6dnzFk8vh/hzsuWRI0fkxIkT0rt3b6vb582b57E1EUIIcY+kpCQxm4Olc+cusmXLDilbtpynl0RKg5AA6enpMnz4cNmzZ4/UqFFDeSW6du1apGMHB7vnbAkKCrT66W/w/Hwbfz4/fz630nB+J0+ekP79e8mQIXfIhAmPSfnyceJP+PvnF3TpvNzJhQ0wI77gwfyISZMmKfEwduxYadiwoXz77bcya9Ys+fDDD6V9+/ZuHRenxMxgQgi5POzfv19uuukmCQ4Olh9++EHq1Knj6SWR0uKRwNhYAG9E//791f83atRIeSaKIiRMJrOkpKS7rcpiYiIkJSVD8vJM4m/w/Hwbfz4/fz43fz6/HTu2y8CBfaVChYry448/SHR0rCQmpom/4a+fn+35mUwmCQwM9B0hUblyZfWzQYMGVrfXq1dPfv755yIdOze3aB80vihFPYY3w/Pzbfz5/Pz53Pzx/GbOnC41a9aSxYuXS7Vq1ZSI8Kfz8/fPzxZ3YhQeFRJNmjSRqKgo2b59u7Ru3dpy+4EDB1QFByGEEO8kNTVVoqOj5c0335Xc3BwpV66sp5dEPIRHs0bCw8NlxIgRMmPGDPnqq6/kn3/+kffff182bNgg9957ryeXRgghxA6rVi2XNm2ayaFDB9V1HB0rSenF47M2HnzwQTWL/u2335YzZ85I3bp15b333pO2bdt6emmEEEJsWLjwI5k48WHp33+gXHFFbU8vh3gBHhcSAN4HeiAIIcS7mTFjmrzwwtNyzz3DZcqUqYVOyiP+Cb8FhBBCnHL27Fl599031dyM119/iyKCeJdHghBCiHeCcsDs7GypVKmS/PrrH1K5chVPL4l4GZSUhBBCDMnJyZGxY0fLiBHDVKM/ighiBIUEIYSQAmRmZsrw4UNl5cplMmjQbewWTOzC0AYhhBArUlMvyrBht8uff26Wjz/+XG64oZunl0S8GAoJQgghVixduli2b98mixYtl3btOnh6OcTLoZAghBCiyMrKkrCwMBk27F654YabpEaNmp5eEvEBmCNBCCFEjh49Itde21bWrFmt8iEoIoirUEgQQkgpZ9++vdK7d3clIJo3b+Hp5RAfg0KCEEJKMVu3/il9+/ZQY8BXrfpWTfIkpDBQSBBCSCkFvSGefHKS1K1bX5Yv/0o1nSKksDDZkhBCSmmzqZCQEFmw4DM1DjwqKsrTSyI+Cj0ShBBSyliyZJHceGNnSUxMkMqVK1NEkCJBIUEIIaWI+fM/kDFjRknLlldJmTIxnl4O8QMoJAghpJTkQ7z77lR54olHZdSoB+Ttt6dLcDCj26To8FtECCGlgL1798hrr70kjz02WSZOfIKzM0ixQSFBCCF+TF5engQGBkrjxk1k3bpN0qBBvKeXRPwMhjYIIcRPyc7OlvvvHy5TprykfqeIICUBhQQhhPgh6enpcvfdt8vXX38lzZu38vRyiB/D0AYhhPgZKSnJcuedg2Xnzu2ycOGXct11XT29JOLHUEgQQoif8fbbb6r5GYsXr5Q2bdp6ejnEz2FogxBC/ASTyaR+Pv74U7J27Q8UEeSyQCFBCCF+wOHDh+SGGzrL7t27JDw8XOrXb+DpJZFSAoUEIYT4OLt27ZRevbpLdnaWxMbGeno5pJRBIUEIIT7MH39skv79b5Hq1WvIypXfSLVq1T29JFLKoJAghBAfJSsrS0aOvFs1m1q2bLVUqFDB00sipRBWbRBCiI/OzggLC5PPP18qV15ZRyIiIjy9JFJKoUeCEEJ8jC+++FTuvvsOycnJUd4IigjiSSgkCCHEh5g9e4aMG/eAVKpUWc3QIMTTMLRBCCE+Esp4441XZerU1+Whhx6Rp59+nhM8iVdAIUEIIT7ADz98q0QEBMS4cRM8vRxCLFBIEEKIl3si4Hm48cbusmrVN9KuXQdPL4kQKxhgI4QQLy7vHDHiblm9eoUSExQRxBuhkCCEEC8kNTVVTfD8/vtvVJknId4KQxuEEOJlJCYmyB13DFITPNEnomPHzp5eEiF2oZAghBAvY+LE8XLkyN+qW2WrVld7ejmEOIRCghBCvIyXXnpNLl68KPHxDT29FEKcwhwJQgjxAg4c2C+DBvWVCxcuqMFbFBHEV6CQIIQQD7N9+1bp06e7nD17RnJzczy9HEIKBYUEIYR4kN9+Wy/9+/dSg7dWrFgrlStX8fSSCPG9HIkzZ87ItddeW+D21157TQYMGOCRNRFCSElz7tw5VZ1x9dVt5KOPPpPo6GhPL4kQ3xQS+/btU3XSP/zwg1Xv+DJlynh0XYQQUpJUrFhR5s//RDp06CTh4eGeXg4hviskDhw4ILVr15ZKlSp5eimEEFLifPzxh3Lq1El5/PGnpGvXGz29HEJ8P0di//79UrduXU8vgxBCSpxp096WiRMflqSkRDVHgxBfJ9BbPBIJCQly5513SocOHeT222+XdevWeXpZhBBSbEA0TJ48WZ5//hmZMGGSvPrq/zgGnPgFHg9t5ObmyuHDh6VevXryxBNPqGSjNWvWyKhRo+TDDz+U9u3bu3Xc4GD3NFJQUKDVT3+D5+fb+PP5+fO5gY8+mi9TpkyRV16ZIg88MFb8DX///ErL+QW4oW0DzF7gW0tLS5OgoCCrZKMRI0aon3PnznV77C4hhHgLGRkZ8v3330ufPn08vRRC/MsjAaKiogrcVr9+fVm/fr1bxzOZzJKSku62KouJiZCUlAzJyzOJv8Hz8238+fz88dwgHh555CEZN268NGvWXIkIfzo/f//8SuP5mUwmCQwM9C0hcfDgQRkyZIi8//770rZtW8vtu3btUuEOd8nNLdoHjS9KUY/hzfD8fBt/Pj9/ObeLF1Nk6NDbZOvWP2XQoNulcWOTX52fPXh+vo07MQqPCwlUa9SpU0defPFFeeGFFyQ2Nla+/PJL2bZtmyxdutTTyyOEkEKDeRm33TZAjhw5LF9+uVLatm3n6SURUmJ4XEjAhTJr1iyZOnWqjB8/XlJSUqRx48Yq0bJBgwaeXh4hhBQ6R2vYsNvkxInjsnz5GhXSIMSf8biQABUqVFDtsAkhxNdBovfzz78ssbFxUq9efU8vh5ASxz/rWAgh5DKzZ89uefTRcaqkvU2bthQRpNRAIUEIIUVky5Y/pF+/nrJ1618qyZKQ0gSFBCGEFIF1636WgQP7Snx8I1m+/CsV0iCkNEEhQQghbrJv3165446B0q5de1m0aLmULVvO00sipHQmWxJCiC8SH99QXn/9LRk06DYJDQ319HII8Qj0SBBCSCGZO3eWrFmzWlVo3HnnMIoIUqqhkCCEkEL0iJg69XV58slJsm3bX55eDiFeAUMbhBDiooh47rmnZNas6TJ58jMyfvxETy+JEK+AQoIQQlzgjTdeVSLitdfelOHDR3l6OYR4DRQShBDiAsiFaNiwkfTtO8DTSyHEq2COBCGE2CEtLU2eeOJRSUi4IDVq1KSIIMQACglCCDEgOTlJBg/uJ1988ZkcOnTI08shxGthaIMQQmw4e/asDBnSX06c+FeWLl0lV1/dxtNLIsRroZAghBAdWVlZam7GxYsXZeXKb6RRo8aeXhIhXg2FBCGE6AgLC5NHHnlMWre+Rq68so6nl0OI18McCUIIEZGdO7fLzJnvqf9Hy2uKCEJcg0KCEFLq2bjxd+nX7xZZsWKJZGZmeno5hPgUFBKEkFLN//3f9zJkSD9p3ryFLF26WsLDwz29JEJ8CgoJQkipZcOGX2Xo0Nvk2muvk88+WyJlysR4ekmE+BwUEoSQUkurVlfLxIlPyPz5CyUiIsLTyyHEJ6GQIISUOubNmy179+6RyMhIVaEREhLi6SUR4rNQSBBCStUEzylTXpLJkx+TH374ztPLIcQvYB8JQkipwGQyyVNPTZJ58+bIc8+9LGPGjPP0kgjxCygkCCGlAgzf+uij+TJ16jQZOvQeTy+HEL+BQoIQUiro33+gdOzYmRM8CSlmmCNBCPFbUlMvyltvvSG5ubnSvn1HighCSgAKCUKIX5KQcEEGDuwjM2ZMk7//5hhwQkoKhjYIIX7H6dOnZPDgfnLu3FlZvvwriY9v6OklEeK3UEgQQvyK8+fPS69e3SU3N0dWrfpW6tdv4OklEeLXMLRBCPErypcvL4MH3yarV1NEEHI5oEeCEOIXbN36pwpldOvWUyZNetLTyyGk1ECPBCHE51m/fp0MGNBbZs2aobpXEkIuHxQShBCf5ttvv5bbb79VWrduI598skgCAgI8vSRCShUUEoQQn2XNmtVyzz13yI03dpeFC7+UqKgoTy+JkFIHhQQhxGdp3ryFjB49Rj74YIGEhYV5ejmElEooJAghPgVyID75ZIEkJiZIzZq15PnnX5bgYOaNE+IpKCQIIT4lIl588Vl59NFx8s03az29HEIIyz8JIb5CXl6eTJr0iPJGvPLK63L77Xd5ekmEEAoJQoiveCLGjBkpK1Ysk/femyVDhtzh6SURQi5BIUEI8XpQ0tmuXUfp3bu/3HJLb08vhxCig0KCEOK1pKQky9dfr1EeiHvuGe7p5RBCvD3Z8siRI9KqVStZtmyZp5dCCPEw586dk/79e8nTTz8hZ8+e9fRyCCHe7pHIycmRiRMnSnp6uqeXQgjxMCdOHJdBg/pKcnKyrFixVipVquTpJRFCiiIkunbtWqi2sz/++KMUlvfee0+io6ML/TxCiH/xzz/HpHfvHuqas3r1N1KnTj1PL4kQUlQhcc0111iEhMlkkjVr1kiZMmWkS5cuUrFiRUlKSpINGzZIQkKCDBkyRArL5s2bZdGiRbJixQq57rrrCv18Qoj/UL58BenYsbNMnvyMVKtW3dPLIYQUh5CYMmWK5f/ffPNNad68ucybN08iIiKsQhMPPPBAoUMTKSkpMmnSJHn66aelatWqUlwEB7uX/hEUFGj109/g+fk2/nx+f/65WapVqyQ1alwp778/R/wNf/7sAM/Pt9HOy52Zd4XOkVi8eLESFnoRAUJCQmTo0KEyYcIEeemll1w+3vPPP68SLHv3Lr6SrsDAAImNLdrwnpgY6/PzN3h+vo2/nd/3338v/fr1kz59+sjnn38u/oy/fXa28Px8m8DAwMuTbIkEKCNOnjxZqME5CGVs2bJFVq9eLcWJyWSWlJR0t1UZvigpKRmSl2cSf4Pn59v44/mtWrVCRo68V66/vqvMnz/fr87N3z87PTw//zg/pC8UVkwUWkgg8RLhDeRGdOzY0dJ17ocffpB33nmnUJ6FpUuXyoULFwrkRTz33HOydu1amTt3rrhLbm7RPmh8UYp6DG+mtJ+fOSBAMnLyJD0zVyLDgyUiJEgCzGbxFfzl81u06DN5+OEHpW/f/jJr1lzl6czMTPOLc/P3z84ePD/fxp3LYKGFxOTJk+XQoUMyfPhwCQ0NlbJly0piYqLqgw9h8dhjj7l8LAiSzMxMq9u6desm48aNUy5OQkqCvIAAmbl0h2w9cM5yW6v4ivLggOYS5ENiwh+oUaOm3HffSHnppSkqPEoI8T0KLSRiYmLkyy+/lF9++UWFJZAsGRsbK+3atZP27dsX6liVK1c2vL18+fJ27yOkKJgNRATYuv+czFy2Q8YOaO5TnglfBB7MVauWS69efVV1Bv4RQnwXt3IkUAqKcAT+ZWVlqZ2EOwkahFxuEM6wFRF6MYH7I92s+CHOQfz12Wcny5w578tnny2WG2/s7uklEUI8ISQOHz4s06ZNk99++01SU1NVJceSJUukTp06qnKjKOzfv79IzyfEEciJcHZ/ZHToZVtPaSI3N1cmTHhI5UW88cbbFBGE+AmF3nrt3btXBg4cKLt375ZevXopNyUICgqSV199VZYvX14S6ySkWEBiZVHuJ+6RnZ0tI0bcLUuWLJL335/LAVyElGYh8frrr0vTpk3l66+/lieffNIiJNBQCgLj448/Lol1ElIsoDoDiZVG4HbcT4qf4OBgNS9jwYJPZcCAQZ5eDiHEk0Ji27Ztcs8996gLg+38jZtvvlmOHj1anOsjpFhBIiWqM2zFhFa1wUTL4iUpKVF++229yqFCOKNbt56eXhIhpJgptB8XDadsSzY1MHMDJaGEeDMo8UR1hi/3kfAFzpw5I4MH95Pk5CTZuHGrhIeHe3pJhBBv8EigVwQSLU+fPm25DZ6JtLQ01ZWuQ4cOxb1GQoodiAZUZ1SIDlU/KSJKYoJnN0lMTJBFi5ZTRBDixxTaI4GGU5jw2aNHD2nYsKESEZi9ceTIEZUv8dZbb5XMSgkhPsGBA/tl0KC+yju5evW3csUVtT29JEKIN3kkMKFz5cqVcvfddyvhUKtWLTXxExUcy5Ytk5o1a5bMSgkhPgHCnw0bNpKvvvqOIoKQUkChPRIzZ86U7t27yyOPPFIyKyKE+CRbtvwh9es3UOIB4QxCSOmg0B6J2bNny/Hjx0tmNYQQn+T777+RAQN6yVtv/c/TSyGEeLuQqFevnsqHIIQQsHz5Ern77jvk+utvlMmTn/H0cggh3h7auP7661VC5a+//irx8fESGRlpdT+SL8eMGVOcaySEeCkffTRfJk16RAYOHCLvvjtT9ZchhJQuCv1XP336dPVzw4YN6p8tFBKElB6ys7Nk+PBR8vLLr3NwHyGllEILiX379pXMSgghPgGqtdCtEuO/R458wNPLIYR4mCJtIdAOe/v27Uy+JKQUjQF//PEJ0r//LbJ79y5PL4cQ4gW4FdD84osvVBnouXPnLLdVq1ZNHn30UTVvgxDif+Tk5MhDD90vK1Yslbffni5NmjT19JIIIb4oJD7//HN54YUX5IYbbpBu3bpJ+fLl5fz58/LNN98oIYFudjfeeGPJrJYQ4hEyMjJk5Mi75aeffpQPPlggvXv38/SSCCG+KiQWLFggd9xxhzz77LNWt/fr10/dNmPGDAoJQvyMvLw8JSY++WSRdO3Kv29CSBGEBIZ1wRthBDpeon02IcQ/uHDhgiQnJ0qdOvVkyZJVqiqLEEKKlGzZrFkz1UPCiK1bt6reEoQQ3+fUqZPSt28PGT16uKrUoIgghBSLR+KBBx6QCRMmqLHhffv2lcqVK0tiYqL8+OOP8uGHH8qTTz4pmzdvtjy+TZs2hX0JQoiHOXLksJrgiZDGRx99RhFBCLFLgBlbjUKA0eGWJ+suLtphtNu0HczevXvlcpOXZ5KEhDS3nhscHCixsVGSmJgmubkm8Td4fr7N5Ti/vXv3KBFRpkwZWbx4pdSocXkm+vKz8214fv5xfrCfQUGBJeuR+Pjjjwv7FEKID3H+/DmpWbOWfPzxF1KxYkVPL4cQ4uUUWkhcc801Ljeuueeee+TFF1+U2rVru7M2QshlZNeundKoUWPp3LmLrF37A8MZhBCXKLHm+Aht/PHHHyqXghDi3axZs1p69LheFiyYq36niCCEuAqn7BBSylm06DMZMWKY9Ohxiwwdeq+nl0MI8TEoJAgpxcydO0u1vb7ttjtl9uz5qjMtIYQUBgoJQkopCD9u375NHnjgIXnrrfckKCjI00sihJSWoV2EEN8WEAcO7Jf4+IbyzjszJDAwkDkRhBC3oUeCkFIEGkw98shY6d79Ojl79qzyQlBEEEKKAj0ShJQSsrKy5MEHR8ratavl3XdnSqVKlTy9JEJIaRQSuBiFhYWVzGoIISUCyrDvvfdO+f33DTJ//kLp2fMWTy+JEFJaQxsdO3aU5557Tnbs2OHwcXCXVqtWjVnghHgBFy6cl3/+OSaffbaEIoIQ4lmPxH333adGhX/55Zdy5ZVXyoABA9TwLttWukjg+r//+7/iXCshpJCcO3dOwsJCpVatK2T9+s0SHMxoJiHEwx6JBx98UL799lv59NNP5eqrr5bZs2fL9ddfL6NGjVK35+TkFPMSCSHucPz4v9KnT3d55JGH1O8UEYSQksDtqo2rrrpKXnrpJdmwYYO8++67kpGRIePHj5dOnTrJ66+/LidOnCjelRJCXObQoYPSu3d3ycnJlaefft7TyyGE+DFFKv88deqUzJ8/X6ZNmyabN29Ww7kQ6li3bp3cfPPNsnbt2uJbKSHEJXbu3K48EdHR0fLVV9/KlVfW8fSSCCF+TKF9nampqSqEsWLFCvnzzz8lPDxcevTooRIw4aUAjz/+uIwePVpeffVVJSgIIZePP/7YqMaAf/75UomLK+/p5RBC/Jxgd6o2srOzpUWLFmpEOIRCZGRkgcc1a9ZM9uzZU1zrJIQ4AVUZSKocPny0Gr7FiilCiFeGNu68805Zs2aNfPHFFzJw4EBDEQHuvfde+fnnn4tjjYQQJ6xatVzat79KfvjhW/U7RQQhxGs9EpMmTXLpcVFRUe6shxBSSBYu/EgmTnxY+vW7Vbp06erp5RBCShleMWvjwoUL8thjj0m7du2kVatWqpT077//9vSyCPF6ZsyYJhMmPCR3332fzJz5gYSEhHh6SYSQUoZXCIkxY8bIsWPHZM6cObJkyRKVwHnPPfeoklJCiP129atWLZPx4yfKlClTVRM4QvSYAwIkPdck51Oz1U/8Tkhx4/EONcnJyVK9enVV5dGgQQNL0yt0yzx48KA0b97c00skxKswmUxy+vRpqVChkqxY8bVERER4eknEC8kLCJCZS3fI1gPnLLe1iq8oDw5oLkFms0fXRvwLj29hypYtK1OnTrWIiISEBFmwYIFUqVJF6tWr5+nlES+jtO+w0Dn27rvvlp49b5TMzEyKCGKI2UBEgK37z8nMZTtK3d8N8XOPhJ5nnnlGzfBAxvn7779vtyLEFYKD3dNIQUGBVj/9DV8+v6w8s90dVlhQgM+fnzMgHEaMuFu+++5bmTNnvkRHu//34Y3482d3uc8vJTOvgIjQi4mMHJPEhAcV62vy8/NttPNyR2MGmM3e4+M6dOiQulhijge6Yn722WfSpEmTQh8Hp4Tpo8R/uJieLf9buEVdBG2BmHjsrtZSJjLU584pOTVL0jJyJCoiRMpGh9k9h4sXL0q/fv3k999/l6VLl0rPnj0v+3qJ77D/WIJMnPar3fvfHNdZ4q+Iu6xrIv6LV3kktFDGK6+8Itu3b5eFCxfKa6+9VujjmExmSUlJd1uVxcRESEpKhuTlmcTf8NXzUzssAxEBcHtCcqbkZuX4zPm54l3Rs3HjRtmxY4csW7ZKevS4sVjPL88skpaVJ+mZ+YImMjRIDJZQ4vjKZ+cL5xceGuz0/sTEtGJ9TX5+/nF+yMEqbOK2x4UEciKwy+revbtlOiFOAqLi7Nmzbh83N7doHzS+KEU9hjfja+cHI+fs/sjgAKvzy8kzS0YODGSuRIYHS0RIEFxw4u3x67EDmlvWidLo2NhYad26nfzxxw4pVy6mWD8/b0zI87XvpjeeX0RIoPoc7XnwcH9JrYGfn2/jzp+9x4M958+flwkTJigxoU8oQ3vtunXrenRtxHuAECjM/djxT1+6Q8a++bNMmr5e/Zy+bIcynJ4G4sZx/DpP/f/Ro0ekR4/r5fXXX1a/YwhXccKEPP8FQhRiEKJBjyYSvUFQE//B4x4JVGtce+218vLLL6t/qOKYPXu2pKSkqF4ShAB4ExzvsIIsUhq5B67u+D0BPCTO7v/n+N8yaFBflXB81133eEzQRLqZtEw8DzxK+K57o1eO+BdecZV46623pH379vLII4/IoEGDJCkpSSVcVqtWzdNLIz64w0ICoys7fm/1rhzct0P69u0h5ctXkNWrv1OTPD0laIhvg78LiMEK0aHqJ0UE8UuPBChTpow8//zz6h8heuBe1++oxtzaQrJyciUtw/4OC1UQjlDHig71Wu/K0kXzpG7d+vLZZ4ulXLlYrwkXEUKIEbxSEK/FUSJgRPQlZ5rBDguVB95sIDXvCsIsejHRsEaYut3U63+SnZ1d4oPvChMuIoQQrw5tEFKciYDox2AbAilgIL0kfj194nXyxthOcmOdszL7uSFyYM9uNXjrckzPLc0JeaW9QyohxQk9EqUIXCzRj+HssQSJCAuWcC+OmRYlERBNnYx2/N5mILX49RdffiRPPPGo3H77XVK/fn6r+MtFaUzI88aSV0J8GQqJUoKvXTxdSQR0lOeApk7ebiDRgXXatLfklVdekNGjH5QXXnjVaSMYNI86fvaiXEzLNjwn25wSV85ZEzSW99OL3iNP9vAghLgGhUQpwBcvnsWRCKgZyIgyYcq4XriY5VWCAs3Y5sx5XyZNelIeffRxp23dlRhcvN2uGPQ1segJWPJKSPFDIVEK8MWLZ3ElAnqjcc3Ly1MzZcqXLy+//rpJ4uLKF1kMoppl5pLtPiUWi4PCemCK6ukihBSEQqIU4IsXT3uVDYXJc/BGTwyqMcaOHSUXLiTIkiUrXRIRrojB9KxcnxOLRcUdkciSV0KKH/7VlAJ89eJZ1ERAb/PEpKeny/DhQ+XXX3+RWbPmF2pCrVMxmOF7YrEouCsSWfJKSPHjX1sUYoh28fTmcsiS6MznTZ0bU1KS5bbbBsjvv2+QTz9dLL169SleMRjhm2KxpOeV2FKaS14JKSn86+pC7MaMfaEcsjjOGc2ogtOzvc4T8/XXa2Tv3j2yePFKadOmbaGf72wnHRkWXKp22kUJ15XGkldCShIKiVIUM86/eJokMztXwkNx8fTePhLFcc6RXuDGRjgDg7eGDLlDrr/+RqlUqZJbx3EmBgNNJsv9e48kSJ9r60rDK2IFZ1c5NtKt13SnlPRyUVSRWJpKXgkpaQLMKGb3w3nxCQlpbj03ODhQYmOjJDExzadmzuOij7HZRu5eGBstZuyr52dk4EQCZN6qXQ7PGWdoz/iWdNXG4cOHZNCgfvLkk8/KrbcOLpZjBgQFSmauyW4fCQkIkGyzyOxlRatU8US1S2G+m+r7bvO56tfpjVUq/vC354nz8xZBW1o+v7w8kwQFFS7rgR4JP8HbEgtLCr2Be3Z4W5fO2RNu7F27dsrgwf0kNjZW2rfvWGzHDQoQqVGpzH8XM5vzwG+2IsJZEqLthRreqrkrdjo8BrD3nl6OC7+/h+uI95Zvk4JQSPgJvljiWdRM/ewck0vnfLnd2H/8sUnuuGOg1K59pXzxxTKpUKGCeKugtHeh7tWxjmw/dF79roVJ8H6HhgQK3vYPV++STXvOWD1nzIDmSshcrgs/cx38G28s3ybGUEj4Cd6UWHi5jCSMmjvnXJI7ZkQKX3nleWncuIksXLhIYmLKircKSkcXapNJpP/19aRe9XKy6tfD8uUPByz3t2pQUXp1yhcamdl5ludsO3ReNmw/eVkv/Mx18F9Ki5fVH/B960JKTX28rZHcdyxRWtSvKNsPun7OJekqRbfK8PBw+fDDhRIeHqGSLL1ZUDq6UOM9vbN7vHz67f4C7y+eYzLneyr0AiMuJtzu8ZAAmmMyS26eid4D4hKlwcvq63kjGhQSfkJpiBnbGslV6/6Wx+5qrf5fb+xwzqP6NZPM3DwJD7aO3ZeUq/TzzxfKW2+9IWvX/igVKxr37PA2QensQp2bZzYUaQC39722jtVt9kJN4aFB6nOavdw674KxblLavaz+kjdSOj8JP8XfY8ZIAtR7IOBW/9/CLWpnPOiG+hIaHCjZuSbZcei8PPL2L+p+/R9YSblKZ8+eIc88M1mGDr1X4uLixKsFJQREbr5XIDzM8Z9/hJMLta1wsBdqwueD8EgBzwZj3aSUe1n9JW+EQsLP8OeYcVZOrvTpnL8L1ouJ/ccSJb5WrAQGiDw96ze7f2DF7SpFPsQbb7wqU6e+LmPHjpdnnnmhUG2vL7egxDfhPd1FaPCNDRyHhkIdXx5shUNCSqbhhR+JmvoQiB7Guklp9rL6S94IhQTxiRgcSMvItXgg4FbXqgiQK4Hbx992leM/MIMdNtzuluZN5vzduqvnevDgAZk27S15+unnZdy4CXI5PpOUzDw5eyxBIsKCJdxBy3BbQYlHzbDZyTgKDSkvzqX/N9oRQoDgfdfev+b1KiiPUMPeTWVf8wSZu3KXJRHT2TtZmmPdpHR7Wf0lb4RCgrgVg/OE0MDrwDjZ293qd8h6gQDBkWcSiQoPlrZNKsum3WesYvcFqhKcxBtzc3MlMDBQGjSIlw0btqgyTw28L8jNMJsDxGQ2S2aW9fvj7vtW1Lio0U5GHxoa3qdJgbUCRzvCnLw8uf6qGjJnxc4C7987E66Ti2lZSvCgcZgjSmusm7iGP3tZ/SVvhH/BpNAxONUt0k2jVhQB4ixmikoCNKlCkmD1ilHywcpdBQzcA5eaKUFMFCZ2r607KTlNnnj0fqlZo6a88vIUKxEBY4+deLd2tQscFwJmeJ+m8r4b71txxEXt7WQ0Yda6YSU1GC3/Bc0u7QgDg4IMu6liXbOX/7curJ+xbkL8N2+EQoIUMgZnMmxL7YpRK+qu2lHMFM2QziVnqgTCjKxcVWaIXgdHTyZLUmr+EC885/1lO2TMrS3kzh6NVI6DK7F7bd2bd/0jW1ZNkYQTe2XQ/S+r2/UeGjymfq1YQ3FyRdWyMmPJDsvtmsekce04uZiRI8FofW3gEbD3meg9LudTsiQqwrEow/3IidA3lkJoAuENiAlHOxl7O0JX47WMdRNSPHjr3xKFBClUDC4tI8ep0IgMDiixbGP9DhmCoUxkqOSZzZJnFvni+wNWBrxNo8oyZWxnOX0+TRlLzXieTUyXJ9//TZ4Y1sbpexFRJkyte9OOI/LH8pfk4vljcs2AZyQtrIHMXbVLRvZtpoagpWXmyj29GktYSJB0aFZVktOyxWQyy96jCcpY6xMOtZDKN78fVbd/vHavbHMgrmw/E3dCMiHBQSopVf945DngON9tOurWTqYw8drLHev2xhwfQvw1b4RCghQqxhYehhQ8x0Ijssx/nRO1Lzti5ditw7BqSXiuZBvbMwh4bFhIvpG/pVMdWW3jBYCx7dG+tgolWCUSNqgo111VQ54f0c7puYaFBkl6dp5a9+KP3pG0xJPSftDLUq5KPXX8bm1ry4wl25U40ht3/evBWD8+rI3ERIWqsAu8AZXiIpR4aHRlnHq8XkToxdXo/s0lJTU/zwDeBM17UNhySryHtu8D0H4fO6iFBKCVZQnHay9XrNsb6+wJ8ee8EQoJUqgYXCh2ri4IDaOLubYDRoKfrZgwyjZ2ZBAgObT7ht3SWPYfS7By3WvG2qgrIxojxV8RKxXLRShhYeRhwVo37Dgli77bKy3jq8i8mVPlpVk3SXBU/hhwW2Nuz7hjXWEhDWTh13strwNBAfFwR7d4+fzb/YbvI95/iIhJ09cXeO8KW07prINlVnauWyVj3hiv9dY6e0L8GRZvE8MYHAyBHosBD8g3akbgdrj27V3MYbRgbGF0ne1enRkEhFC0+5BbACML1/2L8zbJlI83S9LFrAI7ff06YIyR6zHohgZKTNieB/pVLFz2s/z80Tj5ed0GWbvxX7mjbyfLY/B8vWiw/V0D57rohwNW56E1ckJSqCP09+vfO1eGlTn63dnji+u74gmD7UreBiGkeKFHghQqBhcUECBDbmygHmfrwsftoYEBku5kB2zbWtlo9+rMIKTemGP5vWx0WIH8CGfGFvfDK/LivI3y6oMdpXfnOhIZFiLpWTkqj+LJN7+QXxc9J2GR5SSiTIUC67Y9vr3XM/IeaGWqzjpL2t6PNaBM05l9jgwPsQoLIUTj7HXwWHcMv7fFawtbZ89cCkKKDoUEKVwMzmyWyuXC5bab6qvkwgzkP6C/Q1aOVCobru53dDFHLkFMVJglX6BMVIhUio0sEKN3ZhD0IZas7LwC3gBnk0G1+yEmzidlSlBggKRl5shL8zfJheO7ZfOKlyU6rqZc0/8ZCY0oU0AsREeGuPR6RgJDGzaGVk32Oktq99sC70uNymVUOSkqQWyrMI6cSJZ9xxJUg6h5K/NHfTvqYInb128/KQf/TXQ7h8Cb4rWFydtgLgUhxQOFBLGLvd0aTOOXPxw0vgA7uJhrCYmffrO3wHNH9W0mJrPJMmTLeWOV/4zwuaT0Avc6mgyqdWXUqFAuXOUqYF6HKS9Htn3zjpSrUl9a95kswaERlsdVLh+pKj1gtNUcD11+hb3XMxIYWkfJoydTHHp3tuzNb5xl621ApQp6UqCc1LYKY2S/pvL0+xuUyEAeCISEvQ6WWghHy1nxhxwCV/M2mEtBSPFBIUEMsbtbu7WFzLxUqWDvAmzvYu6o2gDdEVF98f2mozKiT1OHBgEGEEZWm7uBHgy22DOeLRvkG883PtliOVZenklVeBw5mSytGlaT9Fufl4gyFSUo+D8XOB73+85TViWc/xt3rWpApfIX7LzeheRMQ+/BweNJUjUuUsqXDZfOLatZtfzGc7Jy8mTZT4eszgnvR1RYkFxMz7ZbhfHBivyGWFinForRd7DEbRh+hpJVrbW4lvjqD3MvXK2z99aZBYT4IhQSpACOdmtnEtIt5Y76FtSaax3toSOCAlUHSX0DJgB3u91qgwPn5Nau9aVH+ytl1+ELUr9mrNx2U7wM7Fpfth88byl91O+iAdZQpXxUAdGhGU/s3O/sHi8JKVkWI60N1oKoGHxDAwkICJTnX31L/tzwnSxdvlLdh3Xr50gEBgQo464vw8zJzZO7b2kkAdJYsnPzVAtuhHw0UYDnS4BZ7urRSM4mZqjjHj6ZrJ4ff0WcdG5RXZ6d85t0uaqmxMWES0hIoFSMjZDqFaNVIqi+ssXi8QkQSU7NcikHRVuD/nMCWOcbn2y2NOoqjl79xZ1rUJTjuZK34a0zCwjxRSgkSAEc7dZS03PsNkSCkcfsBQkIUPF5uNb1O+089LB20oMCbvtftp6QdxdtszKi2P1fSMqQPUcTrHbReH10h+zbua5KKdCvG8YaBvrZOb8XMMpIsNy894wSBws/nCFff/Y/qd3yFnln0Xbp26W+9O9SV8qXi1AGXe+FgDB57cFOkngxU6UCbNl3RhrUjJWV6/5WAgdVI9pj8R6tXm/dJ0JfxokyVIgI2/ewb5e6UrtaWeUlwXtXrWKURIVqhjBAvU+O0ASDo8ZVLz/QUYVAbMWEUUhJM+paAzBUk6Rn5lhNFZ1RjLkGWSaRM4kZ6ruG782WfWfl2Klk5aly9XiO8jbgbcO4eUdw/gchrsO/FlIAR7s1XNjthSjw+5yVO2V0v2YqNo9/epBg6YjYMmHy6bf7DUMfc035wsTWowHDe+DfRGXMO7SopqovYEiRz4BQhFHPChyvd6c68tk3++TQxs9k/++LpX7bwdKgw+2SlZPfNhueB5ST6ltaa0YZTag04NVoVqeC7DuaID3a1bbc7ug90u7Xhx9sKzMAwi9oWmUbr4+KsE70NPqM8L7kmswFGnVp548QyNjBreTl+fnCx171jBbiQiMxnP/Cb6w/HzxnUNcG6v7iyDU4k5Am0xdvL9BE7K6ejeSjtXvk3psbF9nTobUydzhCnfM/CHEZCglSqN0YwhcOQxT7z6ldvi0wxOXKhNm/eDeoqMoQYVghGLTwgQaeg2RI3G4Z+40EyNhIVd44d8VOK+GCpEh7awR47vlj25SIePix5+TvvFYOyzbtCQN4G2BvcL8+sdJR0yjb8IMt2Ikf/CdR3nz4WsO5mSh3tZc/AmGDHhpIukQIxOi91taAqhtHvR/0IS4V0rEjSlBwowmjouQaoG3GDBsRoY5z4JwayIYwkhY6K6q3TRNG9kaoM9GSENehkCAFcJToCBfz1Q3zuzvaIzMrP5fgu41HVeIfjCpKPr/4br8lQdK2egA7zknv/WrJgzDqgAlDjfHUs5ZZVytgrb061pHth85bHu+o/BPDuiqVi5Cl7z8qm4dfJ/UbNpM8k8kqF8PWwDsTBnff0lgNCkO7aSRgutLHwt46UU4LYwevAUSVbWkmwgtGCYV435Dzge6iL83bKI/cfrXDNWRl5ckbYzvZzUHQh7hcFUZFyTVIy3LcfyQ9s76EBocVKYdC87bZJqBq4TeUIrP0k5DCQSFBCpX5jji1kcdBD/oxoJ8B4vAwhjBACGv8seeM7Dh0vsDFG16Oi2nZFhFg6/7XiI4INaxWMNoV2yvHzMvJkkO/vCeLa56UlMiWsu1AssiPBdtQ2xp4Z8LgbEK66qiJ9+jZ4e1UVYQr4Qd9GSrA85NTMy3tvlFhgZ9IQG1Wt4IkZ+TKqcQLUq5MqHRsXk2FaPTvIxps4XEj+zVXBlYrV9VP+tSIjAiWaO08DYynPsSV4ySnwN77U5hcA+RdOAKeGswsyQsIdLv/g3492gh1PdMnXqfyUGxh4ypC7EMh4cOU5MXNUea7s9JMGK0rq5dVIkIz5FqJptHFG9hO4rTd5Wplmo5c9frHG5VjBpmz5J8Nb8u/B7ZLWNSD0qdTHWmAsd+XDCweFxgo8vL9HdVPfZ8IVxtc4T3BRzCqX1OHczwSUjJVrwgYfv3tyDeICLee1ImwEMSJNiAMQJghl8AWbVjZV+sPO5xzgt8j0TnTwbAuvdFF/oor568H3xEIofTsXKffUXyXEdpyJHxU/46sXPlw9W63+z+4Mx+ksI2rKDpIaYNCwke5HF357GW+2/NY6EszNWGgeR5giPSlk64YIm2Xqx031Um1AoyW/jWwjhF9m8qdPeLlwrnzMmbk7bL/wEG5uu+z8v3+SPl+/6YCBlZLxESioxIiAflGylGDK+Ql6D0LyJs4m5ChEj/xjtmOCMdUzzPn02TvsQsyaWhrJbLKYKedZ5bU9GyVTIlhX7bzOlxpAe5KkidECnIosnNzJRyKyQWjGxwc6DC/BcLI6rb4iqoE+AOb3BWj76grA940gdq5RTWX+j/YM+au9pnQKGzjKkd/l7zYEn+F320fpDAXN9sLalQhEtUc7aw0j0VqVq6cvpCuhAKMDdpNQ0SgamL5L39b5zI0qChTH75WNuw4qZotaYJC7+LX9z1AF8d3Huki55Mz5b0vt8qLozs4XC/CCTCSmgFC+WfD2nHy246TMufNx+XQ30fkmltflLKV/vNcGIVRtDkcOAa8E8NubiznEjOkS6vq8sHKXQXKOUf2bSqPvrvOau0hIUESFQFhU1+JIH2zKeRovPbxZvV8rHXpT4cKVCnojaijeR22OMtlQEUIvDAo/Xzynmsk3EH+gt7o4nO1l98CwYQEUK3tOcpV4e2wFRFG31FHA960zwWfKV77u01H5dqW1cURKFHVxsvbE9mFmQ9SmMZVzv4uxw1s4XDthPgqHhcSSUlJ8tZbb8nPP/8sqampEh8fL48++qi0bp3vlibi9sVNvzvSN1c6l5yljFx4cKBdl6srHg88NzgoQO2o9WWb8ApARBhl389ZsUs6tahmZexhJCAU7uger+L+MNa2vRVeHNVBwkICnYZUVHgiQOT1sZ3VTxjtejXKyRPPvCJTPlwn0bHVnYZF9HM4UtKyVN+EQ8eTJDQ4UDWXQmIlcjqQXInXPHEuTT0e5/TN70ctBh2PKRMZoqpVXpy70dKzAeegTUA1rIS4VKWgiRtH8zpsn+ssl+PU+TR57aPNLucvaEY3LTtPJcMa5bfAewPPCnpo4NyUkc7OLSAijL6jzkaca5UlEBHIz0HjL0cgEdUVke3qfJDCNK5y9neJZNIKDo9GiG/icSExYcIEOXfunBIT5cuXl08++USGDx8uy5cvlzp1jDPBSzuuXNwiyvy3K3PUmMgoFFIYj0dYSHABY+hKhj8aNU0Z00lMZrMs+fGgPDS4lXKPQ2gYueXnrd4tjevEqeoMhPXtzYxQ6zxwTnonZ8jp43/Li09PlClvfyDVqlYxFBG2BhjeAL13JDYmTEJDgmXNhiMFxA1eE2EUGFEYWIgI5CcYNep6Zng7eer9DZbwya3X15fsHON8Ee2c0RQLokw/40PLHbDXktt2mJgtqErAeaE/hau9EvBZR4cGqTARGnzpRYTWpRP/rw8PuGqAnT0OlSXXtqwmEW1qquNiFoujHAeIvuJsfV2YIWDOz9lxaI4QX8WjQuLYsWOyYcMG+eyzz+Tqq/NL1Z555hn59ddfZfXq1fLwww97cnleiysXN/3uyNGMC6M4r9OdVXaeSnrLX4e50Lti5DJ0b1tbTdwMDQqUfl3qqK6XcTHlrJo9GQkQ7H61XTGWjB0/Oh/alopu/WuLPDZmqEhYrLy+8E955aHuDtdUKS5SXrm/g1QoFyGPT/9VGduJGKx1IkXWbTthN+cAnS5hRCGegL38hIVfizoevCRq6mlkqCo5xesY5YzgdnTW1Cdd2uYO6FuAX8zIkYrlItTzHHltDp1IUt4ahIHwObuaCIgVbth+skAeA5JA48qGqUTY7peMfWEMsLPHRUcG5xt+J/k5mohJvJhVrK2vC5Oc6fycHYs8cnlhUqyfCInY2FiZM2eONGvWzHIb5iDgX0pKiieX5tVoF7e9RxIKzLvArj4yJEjO6y6ojjwERrs0Zzurk+fSVKkjeMagW6WzCgcYMe358ABgp4schPRM64Q9W7TKD/25IC5ve27n/9ku499/XRo1aSb/e+8jKRcbq/pGODKwG3flD+TCY166v6OYTHg/gySrbLi8++V/7bptBQLWXt9kUuPUHb7Pl2aJPD3rN8tteC2jfhkAn+sna/cUaDMO0QLPh5Y7AM8COnTe0KaWCj2At8Z3Ue237XlttDCEqwm6jvIYkKsJIQpBqPdu2DPAEDp4z5DFej41W5VzFraKwlGOg6PJs3jPUBmC13XVcBQmOdOZ6MDANeIdcIS8HwmJmJgY6dKli9Vt3377rfJUPPnkk0U6NhL/3CHokrHSfnorYwY0l7NJmSqb3zZc0aJeBas2ys48BLgYx5QLN9w5GQ3nQsxf20nbVtzjdsT3HZU+6isc8Bg0cEJ76/Ix/63BiMDAgAKG1/bcsjNS5K/Vr0u79h2k/YDJ8vbifZZ1YfdsO4+jQFhE144bhlob822Pk+dSVc6BlmjorA+Cq10hW9avIPEoTTUIk2C95S99XhAbN7WtbXlPcJ4pqVmGAkR7jH6d+kRADAQzIiXTWU6OSWLCCxpJWwOsfQaLfzxgKV21fC6XjmU9aba5hMCFY9jfUyQkKFiiwoJV7sGFi8j7CZGIsGA1bXXT7v/yM5yF9sLsnbjuIon3B6+TP2MkRImC/KdZP9eu6Li1ucqx8YVri7v4yrUTHVRnLrY/wdje34KvnJ+7aOd1aaahb+VI6Pnrr79k8uTJ0q1bN7nuOjSGcQ8YnNjYqCKtJSYmQrwZjJJevMy4ORP+GB6+rZVld+TMQ4BOimdT8i/EyL6PCwuxeDyMLsAod9QMOsZha6JBu2Bjx9yrUx0lKBzlMljWjJyGznUclljidjSzQqMrfYigaoVIq5LPNs3ryn2fL5HtJyNl5+Eky/NxH3o2IBRwe7d4FUpBhj+SKOHuxy5db3QxCAznjLbcjkC1CkQEOne60oTKFq31t61YiI4MlUU/7LYbUhnas5HlOd3b1bYIK4gSzNhw1B7cdh34jmTmmqRGpTKGjz97qRTV3sTXrJxcia0aY/hcfB/QqhuDxuB9eB9GVncB1z4XeCmQTInPRPseIvzjiHNJGfLe4q0GRju/OkITE85Ce1ijs9cCriZK6s/Z6Fy8/dpSVLz9/I6fvehQGDv6W/CF8ysqgQ5Kwr1eSPzwww8yceJEueqqq+TNN98s0rFMJrOkpKS7rcrwRUlJyVBxX29F7RINXKgAt6em5Vh2Rw57INSvKGcSMpRhRolfmahMNb8Cz92GltFO5ktAvMKQwxmomjtdevzOv607WFaOi5TfdxkP0QJ4jJZAiLUYeQ1Q2YGkTNuJmsoLU2afHPvnqNzX62XJyM6TOvE50qiOdVMj/EQOhuY9eOeLvyxC6fNv91u93nVX1ZB3JnRRHgy77uoGFeXY6YvqmDCymCjqSAhBWGmvrU9WBNMnXi9nEtPV+4nbIXRcnZOh9zDAyENwOVqHbTdNgAqTxMT86hOjnBZHE1+7tq5p97kgKiRQokLC7H5n8bnAQzHjsetV4ib+9nKzciQxK8fhrvI9e7vKpdtl7MAWMrRnY+VBQDjDUWgvITlTvV5xop0z0M7FV64t7uIr54fvurP7jb7PvnJ+7qKdH8K6hRUTXiEkFi5cKK+88or06NFDXn/9dQkNdT0Zyh65Tlr6OgNflKIeoyRxlgGuXLDBoSqWjEFHGO+NyZz6CzlExIh+TeWjr/aokdp6AzmqfzOpX9N58mNgQIAyBCjbrFeznOWCbdvB0iiXQY8WKtF6N2hTPPVueaOdJco7F300XQ789rncevsIGffWzyrHBtib2aEd11Hzpg9W7pT6NWPVvBCt1bdtr4dBN/zXmVLtrOduVNUZC78p6KaHJ8T2fdbWh1BRgJjlpUt5C6BJnfLi6sVQ72HQCzLtXJx5hAByBux93yNCApXHwN57NXu5/Y6S+oQ2Z6FnbTy6K3976bkmx+EWJANfKu9EToTzvxU3/Ll+dm0pruRDbz0/DVcSgR2t39vPr6i4kyLicSGBio2XXnpJhg4dKk899ZTFCBDHuJoVr1paX4p95SeoodlSrkokPJuYUcC4AVygZy3bKQOur+fwNWC0KsVFyN8nkqV82XCHSZqqPNBB3kTVClFSLjpU9VpA7wYtGVAPdtswktociqzsPHn/nZeUiGhy7V0y6akX5aX5f1geb29mhyZOnE0xRYdLgPfINudA6w1h6+r/c98Z1QQLTazOXEhXt1UpHykfri74Pmvre2hQiwKdIXGxshdKwHuAHhZGHgbVRtpgIFVcTJjynhh5hJyNzcZ3CJ4Co5bcjsoqbRPanI2RL0xVg+13zfa9wtsDw+goAfO/1/X4ZdDjlKbkQ3fapBPHePQv6MiRI/Lqq6/KTTfdJKNHj5bz589b7gsPD5cyZezHqUo77vwx4KKKpLgrqsbI3iMXVAjB1rgBGHR4BJzNV4B4wMUfZYEINdgaCv3FHUOfOresJvuOJsq8Vbusulpil4yEy0nDWsuTM39ThrFNo8pqXofeiCLW/PiwNrLiUsfMYzu+k50/zJbuQybIi888psIBthjN7MDxkWtxVbzjKaZ4Xa0Sw/Z9QldIhFnsJUOeT8pQoROsF+du+3z9e4POnVHhwfL0fW1l+pdblZhC7gaSELVkWn1DMQgyVLBg0igSa+eu2mU5rj6MpV+XltSIKg9H1Qf2dqUZTj1g1mWVRpUejkJsha1q0Bt/Z8mU3mI4EI5BfB7eJG8qNyxsG3Bfp7Bt0omXCwlUaOTk5Mj333+v/unp37+/TJkyxWNr8+U/BlR0aO7ffIMQojpQIkFT/X96tjLKaN5jJCI0Vz524Y4u/LgY7jx0XvYdTShgKOxd3FteapONbpBYk76aYOjNjdR9qG64oXVNdXGzNQwYk92kTpwSB2npLWTXkGulbPXmKsHz3t6NlZiB4Y6NCVfHR95HbJlw5cWAeEDDqB83/yO3d49XYRlnQ6LsVWJUKBcuH63ZazcZEm2zYfghKJCzo8dRvgHee7SvxjO+/DF/voYjQwkhMbpPU5V8ic8aHUtvbFMzP6lR972AgKhULty4bBK9Q/JMEhgQKHNWGO9KC7urN+pFYi/kYtn5FsIZqRcHzpIpHxrQ3OOGQ+34bXI6tHkkObl5kpbhuV4GhWkD7i8Upk06cU6AGUFmPwNu4YQE+8lfzspGUfGBZBtfiIPZ7iDRQwKm0GgIkpawOGloG1WCB6+DbQgBu+LVly7KegNmL9autbjW4u54PJIhYbhQ9aFPitQ/HyLFNqzw2oMdVWwbRh2ll0YCpskV0bJ++ZsiVbtKbNUGVuuJDA+SyTN/M1wn1jOqXzO5kJgpERHB8vFaaxGgfyzEBHb9EDbgyZn5HSn1vDG2k0yanj9+3Ba8b5gRgqTPjEufy287T1mECkSNvfPTZlfAW6R9No4er7WkNho25cpFUnNp168V6/A1xtzaQmYs3W53V2+7BuQlGL0/mmelY/OqKjSlX1th//bU2pftUCEoo1CYfjR4wUFe/4lrlIyWpBHB60432PEb/S14Ipxg77PSf9cruNDEy9eunYWltJxfXp6p0CWuDA76IEZGwjI4yEBEAM1AjB3cyjJJEsZD70HABb5SbISVMfn7RJLcfUsjCQpsIheSMyQ6IsQynAslk3DBo2/BG2M7S2Jqlkp+7HdtXdWVUV8J4SjcoIFSOUz4bN2wkmHuQk5mqsx5fbJkJh6TFrd0LHBu9+kqGYxyJJD3ASO9eO1Bp9MxUb4KAYF8B4QEkFSpFxP2Oihq4gsNoexNs3RlsJaWeOhOQzHgyiwJvUsb74uj10CJZ2F29fY8GFoSLtpeW4yTm0ZT21WeT3Gtm6X2noTp2sfbnkdJGHBn80T0fwuOwgkl1YmROSSkqPAb4mdJUa4MQdKM5i9//auMZFJqlgSgbkA3I0Hvjfjs2/3y/Ih26nqvH86lxd3hgtd3f0TsPs/JBc42ZABDGxEaLDUrlZET51ILPD4rLUk2LXtBMi6elxkffCmrtlon22FNAap5kf0LNf7/vt7/nb+99wdongl4VHBUVF3oK1j0Db8KO8bbaYOwS27uwjQUK0zbZw39d8XZa8D1HhEd6LI7+HLlJeC1Ec5xhP699EQ+gLNOsbbvvZE4LMlkSG/JISG+C4WED2EKDJRzielyZ49GMuzSBEq4ZYOCAuT4uTQ1ayHNyUULMzK0XAiUKtoOyUKOgpFBRIOkT762DgfgMZp3Qw8GOzlDX7IIETFmYHNJTM2Qz7/ND7nogcDZsvp1yUpPkvaDX5aWV10tq7ZucvmCrb9QwyA6ApUWWnKjVh2C51evGCXvP95Vki9mSVhYsEqONMofceZtgFBxdk2OigyRkKAAlxuKubtj1L9frr6Gq1MzL2dCW2EMofN8AHxXzMW663f2+Ri993pxWNLih8mHpKhQSPgI2JHMXbFTurWrLYt+sHbNo8IByYNnE9OVgXtr/LUqhgf3e0iwdSIhBAGMJEIctr0RAKpvYSBtDSLEiqtGE4b38Mlkh4ma1SpEqZwI7Oxz8vJLUlPTc9XFEiEXvWFASXDTriMlODRCOrRpbthQCeC8nF2o0cXTEXis3eTGBvn5C8/P3SiP3nm1DLu5kXy81jpx0NklF0LF2Xuz71iCzFu5S4k6CD1n1Q56Q1kY97fewBXmNZyhX8Pw3k0luF/J5iIUxhA68w6gKZi+n0dx7PodCR17DcL0n83lSIZk8iEpChQSPoC2I4GBtXWbw+ihEgEVBPuPXWpp/Z21l0CLz6OyAY8Z3repKt3U50ZoO29UMsBAJtnkAKToGiBpzylXJtyw6gG/O2qKhFbImKhZr0Y5yc41Sdko7LwCVAdFgOe+M+E6ee6dJfL10vnSovtDUrZSnQJNoPSguRZeF4KqPo57qWT0QnKmyuPQXhu/O+r6iJbfEy8ljBaoAkBHz0ueGEwuhUdI6y+BShGM6MZYdEdUqRAp1StFqW6Qs5bukG22Ta665p8f3kdUtuD4aNfduWV1mb9ql6FrGw3HkKRaJjJMHdNV97fewDmrqHBWHuqyC76EDJOrhtCZd8A2OFYcu357QsdegzBb4ebqSPai4qq3iRBbKCR8AG1HYpQQpw9BqJkTduLzSB8Y3b+ZMlCRYUGSlWNSpZIw3ggdbD90/r95FY0qq3JCPVpLWEeli1oyIUQFqjlsmyJphj07N092H05QuRd6I3pPryYWkbJl0+/yxbRxckXtuvLQrY2lQoXycuQkGl+FqWPbipO+XepKcmq2qhTRJ3lqXgScEwSX1mbbqA338N5N5EJKpvLiGFWbANx+9y2NlbDC7AigjTZf+9tRxyWzDSqqJFVUxRw7lay8Qnf3aqwqO+ApwVCnR99dZ0nqRFWB9h5r74u+42e1CtGq/wY+O7TnhgF3dVS8xcDd2kLOJKSrkluIIxx/8I31JSQosIAxdiYSPN2PwBVD6I53oDh2/Xh/MAwKcxySL2ZLelaOamqG76o+iRdrQHWR/n1iMiTxdvgN9AG0HYlRQpw+vOBsjPXJ82ny9W/ot9BE5q/ebbeqAM2TrmlSRfV80Ayq5vqGoXSWTAhBgiTMFb8csnpMWEiQNL4yTj79Zl8Brwq8LejW+NyIdvLrzz/KyLH3SIuWreXaIc/KzJU4Tv6xsDs3mmx54N9E2XM4wdCLAG7p9F9pJ37C8Nq24UZYB82uerav7TQ8oY1B1943GGG895pXSP+eABiv0f2by9kL6ZbbX55vnecB747eqOjDDbYtx3E8tCXftOeMEpD4jthLIjU0hAEBkm0Wmb3EuLdBsGbIdJ4IZyLBF/oROAqD9Opo3D68uHb96JOBYVB5eSnyxMz1FnHYs0Ntq+8hZh2IrvyOyZDE26GQ8AG0HYdRUpZeXDjLvMf99WuVk92HLygjiqmR+rDEKl2pJLpPIkaPHS+Mg+b6DgsNcphMCAO//4o45eq/rVu8fLJ2bwEDiLr/v/aftYy91ns4Ll74V9Z98ojUa9JWPvl8qRw7myGDo8MsF1r00DJ6fXhX7JWbat4czUjDo7Fx12mD0d0V7Zam6tF/Dng8PAm3ds2fEmrUnhqPx3TQD1fvUq2ztbkijo4LHIWHIErGv/WzRUDajig3MoQRZcJUGASNp3YfOS+/bjtp6MGYsWSHqrwJgkG7hCsi4XK54I0oTG6IURgEnULHv/2L4edS3Lt+dPDUhIHtdxC3d29T00oYMBmSeDsUEj6AtiMxSojTGx9nmfcwYNjF2lZq6L0RmhHFBRW9DOC96J2UoQwidt3IoXD8GsHKY3DoeKLs+vuC4Q4WiQb9r6+nDH+B6pC4GtKyx8NStX57+fibQ9Lv2jpSVrXqDpDsnDyVsGeEKyLK2eAq7djOxpnbur/RylubfQFsvQfg7fFdZPvB86qdte3sD6t5JLqdp16UYNQ4OmTidTCXA6EmzehpYsUREeEhqimS1ngKn7OjMliEO6rGRliMlEsiwUMueHdKI23DIBAitu3DS2rXD89EYYUBkyGJN+NffU/9FG1Hgrg6jCCMmYZm9Gz/3xbcnmsyyweIqRuEJWDMYbCwM9OqH4KDg1SLZ3QNhCsf1QqornBEdGSIXNO4irRpXMX+DvbAOWnftKoKY6D5FF7/8J8r5fien1SFRvWGnSUwKFjdjoROJJJOeOcXeWLGetmw46ThOTozpEhyfPuRLmreh35wlVbm+fL9HVTuBjwbyE2AobV9HU2EaKO/bUd3IxRkBJ6HhE+8vzAcmJdhBD5f5Kboj4N1HvgnUYmoVxf8oZJAr25YucC5O/rsYaAQcsH7jrXifXUmvODhgNHScEUkaILX3hqUMS5mnIVccH9h/sZs119Su35NGKDrJjpH4udYJ9UhmvhBIy/8pIgg3gI9Ej4CLjAj+zZTJZ4wNuhHoPpIhAdJ16trqE6KzsZH45pqL4nQMhY8MEAdA/MoIsICJSw4UqZNuE7Ss3KV0cXUUG2Kp23FR5nIEDVRFKO3b70+39XvyFC9gLHb910j+zZ8Koc2LZb6bQcVeFzixUyrc9HO0TZZEkmcjqaLHvo3Sc3oaFa3giVZ01HiKEaIN7400wPnhgmeaHNtND1TG92tlWvaa72NTqAAyZy2a8Xj+nepJ9HhIdKxRTX1HM3TAA9EpbhIeeOhTlImPEQqlIuQ8wkmi/dCG0KG5xh99sh5GDc1PwyiCQhnwgv360MRaL2OcAd6hNhOIsVOXtsdX24XfHHmZVzuXT+rJIi/QCHhQ8AbAO+A3njD1Y0LZsMr41QY4vSFdNXSOiSoiZxNylDlbNpgrPG3XWX32DCqyCJH/wnMQLije0PJzTWrJlTYbWuvCY/B6AHNVSkicizsTb/M08XXDV8vDNUiJnnvf88qEdGo891St03/Ao/DwC3r98A4WRI7fvyO+Vj2DDmy4TftOmVJ1kTewsJv7A/ewuPwfsMQ3turiQoJGMXQ4YXRl2vaJoJq4kMz4lHhIdKhebUCyZ7b/z5vmDCqnccDA5qp/8cEydT0bLm/f3O1G9fEFcp79a+PdVWOi5Tk1EzLujUB4Ur45tqW1dXgN5SW4r3ClFdb8YOkWgwD04ytZoyRi2E2B6hyWDRBy0JYqgSMcnHnZdC4E1J4KCR8CFzQ7e2g+3Wpq8TAmg1HlBv7lQc6SpW4SBWT13aH9naheB7GXR8+kax2nEiUhOcDu/ybO1wpPTtcaRndrT3+2RFtZbFNYyx9qenIfk0dltkhUeLA74vk0KYv5eY7H5fAyu0NH4fkTltgFM8mZFgqJ/TnoSU5RoSFKG9NcGCgbNpzSt1fo1K0TNtzRlU6AIQxHHloME0U4qlK+Sh5cuZ6VTaq3adfIzqK4qe+XNMIvP94T/A4fbttVxJG8Zo5eWbZdficSoDFe4DupC+O7qBKUfHdQFkq8ihSM3OkQrkQiQwLlkCTydKfQy8g7HmvEFZBMux3m47KvtgImb54u92hYeqzDhQlHGyNcWhw0GWZZ+ErpZEIsaRk5snZYwkqFyecoQniR3jHXxlxiTKRobLwG+tZF5qnAO5y9Ci4t1djtQOEJwHjveFOR5gBoQR4HPQlnRoDrq+nSjNts/hhcIbc2EBOX0izuh1GLDPLgUv5wDll6NFcCYmVtrtYHBNhlnEPjRHT3bdIu8432Z0wioFgRhiJIn2SI4zy5Jn5Ew0RRsD7YDvO25UZFjC8cWXD5f4BLSx9Fmw9DskXM2VUv6ay52iCw10+QhQwpJhtYoSz9Zw8l6o+Iy0xNglTG9/7VR68tbk0rF1eiT98zlgXPmPkXKD5l1HjKVTo6KtLYNMgIv/Ye1qJiL7X1rM0/irs0LDL2U/CF0ojS3JOBiHeAIWED5GbZ7YSEYZtnOMrqgFTmMC5p1asuu3pWb9ZPQfXLr2xa9ukquorYc/Fj1BJYY0ecine+GSzmgtye7d4SUjJUgbu35Pn5enHx0n3gfdL5zaNJCaquTKGtuWSMNBoHvXag52UKLCNy8MoG4kio8oKrSMlQhvWa8w3fra5HtrrxESGqJ24UejmnS/+soQL8LxnP9ioGn49cGtzmb2soNHAa/+286TyEN3V03pKqfb6lctHGnYK1YBYtJ1oCqpXKqM8HEZCDK83uk9Tq9wFfSUISlf1I7U7NqsqXVpWtyqFLOzQsMvZT8LbSyM93aSLkMsBhYQPkZ6Z43TKJC5QmNOABkxIwENvBA19OeGd3ePlYnqO8gyozpYOSgFFrA2fK8l6iI1jLggM3LRHr5OQ4BzJzUqVSWPvlNPHD0tc3evk6y2JSiQg+VFvrGFY4SV55cFOMmfFTsO4POzQsJ6NCogifU6ErUBAyeSYgS1Ujwy8FzDWWsdLo3ARSmURJir4fvxnyDXRguO9u2ibtG1SWb0GfsfcBi1H5RGdYUZFCx53RdWyqsEWRq5jTfY6heJ58Kqgfbe2Bq1MF+uwHaamXydyJjJy8yQ8OEjNvUi7MUflp4SFBEooYlA6I1b+UqfO86nZVgKmsEPDLnc/CW8ujfSFJl2EFBUKCQ/jaiMduEcxl0LDWRdLNEhCQygYAexyYVRR/gnbAaOK10OoA8mGKgThwsTQAj0PHFRJIEETawRwtz817Ws5/H+vy7mzZ+WuR96Tjh3aqvujw4OVa15r76x5TeBxmLN8p6GBhPhBpUB8zVhLciF21fCCbNx1SnkyIEQgBFDuauuxmTq+i5w4m6p2411aVS9QaaG9Drw0Rj0fNENuT7QgtwSf5X6dV0E/TRQRlvv6NJWZS3ao49nLPwA4Ju7HjJFdh89b7te8BM6mjfbvUlc1oJpuz7XugjAo7EAvT+QteGuSpCebdBFyuaCQ8IHYqX5ol2a8XekDsPjHg/ktrS/FxTHjATtszeAlp2blT2cMCrDbbREYJTyixPPVBzupslN7HoE6l6pEggJN8vviZyQyJE8WfL5amjVrrC6gWGOq5MquIyfktpsaqFkX2MJ/uHq3ykWw5yVBOAOvoc+JePWBjpJ0MdNyrkqIGAgE7AIhUPC+4LmvPNDBoTfGXpdLrfGW1tjK0fwRbb6Hdj8EBT4L7fjOxo4D5Cto5aN6L4Gz7wGmvdp6dZy51vV5B/heYPLrPbc0Vu8pRJy+7NMofOALeQuXC19JBiWkKPBb7KWxUxh4ZCriootSOjxu79EES68CV/oAWAzhpTCIZTqoQV4FwgXIaUA4Qp8rAONRLjK0QA+BiLAgSUnNdFjuiN9hTC9mmKRhp6Hy3LgB0qp5Q5m1rKD4uKJKWVn20yEVt8e5orTUEdrraZ6AqIhgFU5BtQqqT1BJ4YpAuJjmuLW0PUONUlztPXQ0LA1gOJf+fr0XwZkQwFwP28fqc0BQ4ukIiMTCuta1vAPkV3Rrmx/2sRqEFl9RTWcNRdzGQBB4e97C5YSiipQGKCS8NHZ6tlO6pYfBqL7NLB6DTbtPyZCb6kt0eKg8M7ytJQavT8zTGxokaLZrWkUZr5ioRoZ9E/B6cPO/MKqDcudbiYwGFaXxleXlj92n5Y9LZZPq9viKclePRioPw2hHjef99vsmST20Ud472Vl63NxbKlWtaTdcASBKsF7gTCjBgO45csGuJ2BE36YOvSyFacxU4Nzi88eRazgLL8CroD9nvXiwPb5tXkfVClFqNPrynw5ZykfvH9BcVbNc27Ka8ow4KrNF/wZ3XOtaAzTbJE6A15q9/JI3wwfzFi4nFFWkNEAh4aWxU83YKFf8yp0y8a7WEhwYoBLz0AzK3uROJC7q4/bVK0apPAGEAxz1TUDi34KvClZu4HUQvoCR1wsJrAs9p1DRgdwNWw9D04pJcu/QOyUyrpYMn9RN9ZW4mJqlwjO2jZgggjQvARIBXWmYBMOES7A9T8B8BzMtXG3MhIs9PDK2rz34hgYSEx1qeZ4zrwJyTPDea+eqFw/617dbidOgomonXj4mTMYObKHeb83+BDoxVM6EhCPXOrwuRUkU9Na8hcvNf6IK81HQIRaiin0kiP9AIeGhxErNYNpDb2xw0UYvCCQw2m0MFCCq2+OWvWfk0IkkFU9H8iF6FjSoFat6SjgyeM521Ua5AlpFAypA0BsCjXbMYpbZH34hQ8c/Ile3bi9T3pknVSvHykvzNqrwiVE5pSaC8tdndtgwSY3j7tdcjp9LlbaNqzic+ImEU3veEs1jY6/lNtaAxkyxMWFKBOCaXyk2Qn7bdUq19karbXiGcO6YSeIINIuCd0k7V1RfaOJBf572RrSrdQWIjLm1hWoQZZtTM2ZAc7u7/6K41pkoWHzgs4gJD5IrqsZIYmKa6iBLiL9AIeGhxErE1QszYRKTOFs3quSwUqPvtXWlbvVylpi25ibHkKir4ys5FC+uTs/U0HbPH6/da+XlKGc+Lp9Pe1iuatdV/jf9A5nyyTZ5cVR76dqmlurI6Kg6AeEKCCGIksU/HlBJisgvQGggIzNX3Z+QnCG/7TwhDWrFKQPtCEwqtX2P0XsCYY9H312nfkfoA62lUS5r6yl545P8tuLooInzHd63qbRCPkflGPUYtO+ePGO9yitx9FmiOgbP1+7HzA8IM232iVaS26FZVYeNn04npBvm1My4lDRptPsvimudiYKEEFfglcBDiZXOBmzZjrnG0CZbN7st6MCoNZYycpM7Ei/OkvZsY/n2+lhcyKssNwwYI488PE4On0pXt2EQWIdm1Ry2f0aSJRIkMYPCbDLL0JsbSWRYiIrF2+7AUa5qW8VgBNzIWjKo1rnxyMlkNUFUy53A8dBHwmgYl3be+vdyho13ZNLQNipJ9Znh7eTjtcafpTYuHZ+DVpIJ843yVP1wrtSMHKfCSCV2Xpo+qs+lSM/Ok8hQ4xwEd/MVmChICHEFCgkPJVbqm0MN79NExdER+0b4wtaoYRf99/EkZQgdkWcyqx0uDB9yKlC22bN9bWVIscNGyabRvAi4+ivFRjpM2rP1kOhDIWhohTHgVa9sLvcM6SENr+ik+jpUiMtVzZkO/JOgPAiOwPjyj9bskTt7NFThg9aNKsus5TsK5HRouRl435zlNyBREWPI8d4GBwfK0ZPJEl87VurmllWhCawRXoEvvttvKCK083bU/AtMGdNJjSB3VMHSs0NtK8GHElfb7wRCKM6EEUJDEFAYnqaff+Ks7bKjfAV7vUyYKEgIcQUKicuAvViz1gehdcNKUiE6VIU/Dv5rPWFSZen3by4/bz0uja6Is+qIiB4BqPHH0KaQoED1D4OcIBZWrz9sZYRhFHE7wgVwxUO8IFyC+RMR4cEq0bJXxzrKSNvuqpEo+dFXe6zWrtkQiIh9v34sf29ZLje2ebZADkSrS6EE9Kxw/B7lqDHdGdm50rB2nCRdzHI68hyhB3teHcyYgLG2rTSpUiFK5TjoK1xwfhhUtnnvGSvxNrJvUzXRs2JshMOQAyawYvaIo4FdtqEhoyRGVyZyag254M0wEjaFbbvsrJcJqy8IIc6gkLgMuBpr1i7aqVm5kpGVpwwUvBT4ifHSIUEBcm/vpqoFdnyt2AKtkWEAsDtGeMPWCGuPg4iAwUPexNL/O6iqKLQEzr/2n7WaeYFwR1xMmOoWWa9WObmjR0OVq4CdcXREiJhNebLzx9nyz87v5I5RT0hMve6GiYIfrNglQ29pJC/f38EyVEpfsqr3eOw9kqDmUkBIOALr03t1VMVHaLBaG4B3Qy8ibL0ZmtHHerE+5EfAawDPCCoyDv6TpPIo8BroDOoIzcC6EhrCZ2TUKdRZ4qc+3KU15CpK2+V8L4RJziSmqXPH90D7PGwFCasvCCGOoJC4DDiKNcPDAAOYnp2rDBIaKyE3YP7qPcrIvTX+WmUU4TZv17SaGgilLvp2XO0o1cT9tkbUtvoiKiJEGSsYEc2o6jtF6t3t2w9eUIbrXGKG2p0jPwHG+NRfC+WfXT9Ii+4PyfiHH1aVCUZsO3hOBmbWtwwPA1oFA8ItEDdauSpuwznYM5QaEDhanwj9xE94KTDoy+j8bd8D29uwfvRsgJjRCzFXZk04+ow1oeSsJFMTRu880kUyc/Lk9Pn0AiESV5JjnVVTGHkhbGd7cA4EIcRVeJUoYbT48203xat2zEiWgwHURAQmdaLpz8Rpv8qWfWclLSNXzidnqFwBiAiELtDlEV4DjPPGxR/5Cfa6Nmr32wMGCEYDI7G13+2BdcZEhVkMb5XykRKhZkbUV7vXcQ+OkltHvSw1m9zgUstuPVj/V+sPy7BbGluMl5aLACOuufmNwO3HTl9Uhk97LxFCwVpfHN1B0nTDzey9B/Zuq1+jXAFvjqO1aEmHWj4Bfre9//4BzaRLq2pqhw+vkyY6jEDb6ZDAANUzBNUiEDcQSrY5HI7EjSPviL2OqqoU9dfD6jNwtfyTEEIAPRIliL3489vju4jJbJKwkGD5YMVOZTyQR2A0YAqtsjXvAxIn3SnV1INwhTYWHDt4eEP0zZI0g6V5B9AJU29YG9aIkMyj38prjz4hwSGhcm3n9pZcCUcYGT68Lzl5Jnl8WBvV/ht5H9r526tqQe4CvBXwPKjmW5eGWvXqVEeenrVBrR8hlMKuxdHsCkc9LZC/kpCapXpoRIYE2c8nCAq0Ksl8YEBzmbEkf1CZBsQKbnel/4O9Ch5n1RSOOqraemtY3kkIcQVeKTwwSwOdKtFcKD0rV/p2qafyDRC+QOMofTkgjHueyaQaP8GTUbl8pIrX46fjtsqRljJBq8TNBhVVzkVsSJCl26U917ZRpUJWerLMmTJBslPPyc19BkqFqldaBAg8K4Wp+tCA+x47bzzm2lbVLeEK2/wHnBdKYFG9gooFgLXde2mold71j8oXu9UcumZUenFSrUKUEiAxUaEF3k98FoeOJ0njOnGWCpuI8BD1uTz81s9WpaTwSjjLJ8B3Q+W5GFR5YJz4qD5NHVZMjBvcSvJy8wq8365UU7jaUZXlnYQQV6GQ8NAsjTMJ6bL90Hm1Cw+MDlGGeNayHQW6Pl53VXVV7rdynXE/CHttlW2FAX7Hrh1VITD8RsmYsM/9r6+n+h4gGVN/vIyL52TT0hckJzNV2t76khIR+m6NqAZBTwXM7EBViWaEy0SFqN36i3M3Gr4XmicArw8jqk+EtM3ZgOcEYSCVfHjpcad1Q630AqAlWlnfWF+2HzxvldQ5sl8zmfDOLwVaXq/bdkJ5RYbd3Eh14Fz0w4EC7ycaZUWHBklUaFCBsdyFqZrAd2PTnjPqnxFDezZSYsSoYiIqLFgqlItQ3RHdqaZwJSm0NJV32it9JYS4DoVECeFs54fqAPQ1aFQ7Tm36sItG4iPyIfRVDXuOJMj67SetdteutFXWt80OCQ6Sg/8kqtbZ1zSuojozwvNhG86AuMAo7/iasaonhUZ2Ror89sWT6v/bD3lVomOrWXau+moQNGZ6fWznAoKo5aXSU9uEQVtPhdYK3KiMUv9YvQteEyKO5lT8b9y1ciEpQ84lZUhgoChhpp9ump2TpyaPYm2dW1SXX7edMH4/A8VivIsygwIdOSEG9R4P/WehT5a0rZgI0k3JcqeawlnIBJ6ZwpSP+jLOSl8JIa5BIVFCONv5ITegdrWykpiSqVz2tmJB2+lrbZT16N3+nVpUc9g2e9jNjSUrK1saXBErv648YdVd0tZrAc4mZag16ZtfhYSXkdotb5ZqDTtJRJn8JEGsWZ9boRn295cVbCKFqg1clvXeBnsdPI3aWhs9FgZYH6aw2zTqwDnVmrtzy2pSvWK0nDyf320TbashtDD3YuHXey2eDOSM2JZD2oqEos6gKBMV5nDmSEnmJjhrMqUMaCkwoo5Cj4XtxUFIaYdCooRwuPNrUFF5IGC4YNCQcGlvBsWA6+sZHl9z++NYtuhd/Nj9QhQYdYnUz7nQjBo2vA2viFNtrSsGn5Htuw9KtfhOUrdNfyujh94SeI5mADH+25Vx2vBOoNeDUUkjQPkrqhzQIOrkuTS75Y9IGh3Vv5kq1cT5Ontt5DZg9PcbH2+29IbQZmjAQ2HryUDeBG5HUqf+dV3pGeGsamL2UuskS22NAEm39nIT8NyUzDw5eyxBhYvCg92bIMkmU85Djyx9JcR1KCQu884Phve+Pk3lsWnrpM5tVynTrRl4oyQ/zJ/QEhCN7i8b/V8/BXsufkfjw/VhAoiSahWi1XyLn3/6UTavek2q1GosVRt0tCQ42noHNAOISpDEFMdNpNDMCsmMGMhldBHHsc8lZcrL8zfJ2EEt1EwMe0IM5/vI27+o0BByGi6mZzt8bRjM1y+JCH1IBDkhWsmpHvyOM9ZyRlztGVHUqgkICSODXtxu+NLeZIqTTQkpPigkSjB5C7trVGfAeMHQwTuA3TXi9bgNxkzrcmg3xh9fURlK5B8gz8AoBwD3o0mUvWoLV8pFYcTv6tlIJTyuXbNKtq6dKpVqt5SnXpstLeKrqdBEmYgQ1evC1juA1zKbGzmdBRIZESwTp61T54kUDKPwhdbfAuEInBfsm211CZJGLY2TDuSHTe7r1cTha+N91ldXaOWTmObpaBT57d3iLffb9oxwZwaFMwOWkZkjUTYGjG744oeTTQkpPvjXUozY2zWi1wBmWmidH7WqC4iKtk2qqNucDYaaNKy1LPr+oGEOANAaWxm5+J11ZkSjKSRtXkzLllWrVsifX/1PqjXoKC17jJOV6/9V/zTPhr3wAeZ27D2WoEIXyImwBecbHpL/ddOXdcL+lYn8T6BgbDeA0Yc4QrIoBAZc+ZoQsxUyEBrmS6LKnqdjz9EEa2N/6f8RknGEdr+tSHA3POCOAbP1Yth6phxN/iTGcLIpIcUHg4DFhKNdI/ITMi6VHwIk8cE4HjmRrHpI4MLlsFvl/nMSFR7qsJvlFVXKyNuPdJGw0IKGyFlnRgzL0ronxlaNl/rXDJRWPcdLYJD1aHFHng3MAzl8PEnlN9i+luZt+HB1fnmnlt8BYfXS/E1qfLb2+nrRg9/PJmSoxyWnZtvt8giycnJVWAC5Dbbn9+CtzaVNo0oyfeJ1lu6SgZeEALxGzrwoEFBoDGYbQtDCAxi4hp+uGHJHXS0tBsyBF0PzXCFZE+8H8jwemvqzTF+2QwlZ4hqOOpGWltJXQooLeiSKCaPYt7ZzRK+I8mXDZUSfJqoqApd7VAvUr1VOklMzZVjPRpLgZEgVjK0jEi7lJxh5H+x1ZoSBH92/uTw89Sc58tdXcrFvHQmPjpP4jncYvgYSHG3BOcKAo7fBgOvqq3HaqHqwN067+6XunEYCxahxlXY+zrwq6Rm58uzs35Vn5u6bG6t1wEuC8eghYpbyUQVzAWAswkKCHE7c1DxJECH5qahFw52wiN5L4chzxTBH4WDSKSF+KiRmz54t69evl08++UR8CdvYNwwsWj+jlBIJkWcTM1QpJ3aSMOxIEoQBzsjKkaTUbCkXHebw+HD/O0IztEajqLVyUbzend3jleiAKMCF8/S5VPnzuzlydOtXsmT5FdIivqtdo6p5TzQDiHNEHgOSJ6cv3l7AA/HOF38V8B4YeTWwdqMST72w0IZe2eucidAFXktrWAUvxJ/7zkql2AiHAiA0MEA1mjISWbh9y94zxe7qLqwB07vhHVWnsNqg8JT2pFNC/E5IfPrpp/LOO+9I69b5u2dfQts1wrgi079t4yoSHByoRMO0L7cZ9gtY8NUeuad3Y8nMNqnrl70YP25Pzci2u3OGOx+GFhUex04lWyZn6h+LuRTN6laQ5NR8EYHy0xU/H5Czfy2Qo9vWSNMbRktyeEsZZfBcvD68DAgvoGHTvbc0kdTMHIkrE6YmdRoNgLItK9Ww9Szg2FUrRKk+D/rcB72wwHtatXykdG1dU1WU2FbB2AoQvD5KTNGd06kAMJulUrlw9fp6LwpKRTGlEy25Hbm63e2MWBgDpvdiOEucZbUBIaRUCokzZ87Ic889J5s2bZLatQu6vn0BGBBM80RnSrie8/LMyvvgqD9EvRrlZO6KXcoQa7Fvo2oGeBKeen+DqtrQH0O7H8mcmAwKE4MGVB9fGjuuGUYIB5RdwoSHoW/C9PVqyNZfa96U0wd/lxdee0+yy7ZSx9USIQfdUF81h8LjwsOD5c+9Z2T34QT1mDu6x0vTOhXkfHKmywOgjEIX2GWP7tdcMnNypHxMuMpFCAoKVD0kIHQ0caB5PdR48WvrSu9OdVRyJapE/thz2rAfRUZWnmrX7YpRx/vStE55JRwys/JUXkTl2EhYcMvcC093RtS8GGkG+SF6WG1ACLnceMVVZ/fu3RISEiKrVq2SGTNmyIkTJ8TXgLFBQh52jagiwC5Zvxu3zbSvXilKCQ3Md7DtVgkjjth8mahQ+X3nKTlxLk2FP2yHWGHnDOGB3XdoSJAy+ui9UKdmOTUOG7asclykHDmZLLExYTJn5S7pf11+gyv0hahcp7XUaNRFdiZdIX2a5wsPVEegBBNVFFpnx1fu76BEz2eXyiBhIr/88YD0aOdY9Ol3z6jmQAMptKOuW72shAQHqmZc49/OH3oFz8SgGxrIawv+UO228T7F39VadaNUXohLxtq29LXhlXGGyZeRYcGqpbUznIoBB56Iy12SieOVCQ9mtQEhxKvwCiHRtWtX9c/XwY4WIgKiATtrDVcHa2nVDPj3xthOqoET/h87ddshVtoxV9sk3mmufq0jI4zLyL7N5Hxihtzbu7FcuJAoLcsdkHvvGylmcxcVrth95IISDV9m58m0CdfJpOm/WhlniA69bYJIQW8FLYRiD21aKcpLIVAen/6rGugFbwnO49UHOqpyTzwOnoVdh8/LxLtaS0hQoPKcwOORk+egA6FNnwcNnHN6Vo5URF8LB0a1KGLAU50RMWsDnikMSStsDwtCCPFbIVESID/BHTQBoBcCrpKZli23d4+Xaxrl94ZwlmnvKJfgYnqOSs60l0CpP6attwO/wyC/uXCLMjYQEXHlwmXqgl9k/psPSWZqgmw8XkHatoq3lKFClHy36ahs3nu6wA4fHg8t2RPHxjwKAG+Io4oH5BmgPBHjuSEU4FVJ0oU8cFwkZGKoVrsmVVR8H+/71gNnZflPh1ROx8Ab6jt8z/XDxTQvBYQT2kfnfwXsJ1qi3bRjMWCSmPCC5ZggPdV5J82Yco4bdLkD3p/YmAh5eHBLSc3IlfTMHIkMD5GosKBLA718twS0KH97vgDPz7cpLecX4MYlxC+FBOZExMZGFekYMTHI9ncMulUieREX8zIRoRIVEapmP2CHjDyCMQNbqLJPGF7lqr+i4CAoo1wC7cPUBIRR+aaWve9o6qXm7ShfLlzemPe9fPi/sZKXmy0dhryqyjy1Y2kTRNHm+smZG6yECTa40ZGhkpKWLW0aVZYrq5cV06Vdb3BggGFip22XyqjwEDVd07aT5qHjSWqN81fl54non485F0GBgWpKqiPg6YDHBsZUJTuGBUtURIiUiXSecIiZFY6A0LmiaozhfWlOkh4Rlirqd9AR5ctFSvly4pe48rfny/D8fBt/P79AV2LCpUFIIL8gJSV/yqM7qgxflJSUDMnLs28ssvLMFrc4OlWiYgL5CVpoAzkFtjMcjKZtAttMfC0pURMQq0SUK3vs4FZq8BVCHjCWeN3goAC7Uy/By/d3lKNHj8i8KaMlMChYOt72mkSWrVxAyECEZGTm7/7thWFG9msqKalZsu3gefU7zgEeBdu8Da1vBMIWqCj5w8bLgeRPCA2MNbfnqQkLCZQ7ezSSA/8U9Mbo1wRRs3r9YRk7sIWEBOR/fhARzj4/oHlWHN2fmJhmfF9woMNcBdxv77lFwdXvpy/iz+cGeH6+TWk5P5PJVGgx4ZdCAuTmFu2DxhfF3jFsY+vYuQNNNMCwrlxnP5SB8lBUdWihCOQQQBSo/hJXxsmIPk2VKJFLAmL87Ver8sdZaGJkI0xG9WtqtdvXg8eibDM3sIxUrnuN1G87SHkibNGEDMJBr43pKIeOJyth0LN9bYswwNo+WLFL7u3V2CJwkMegz9uwBYIBFSdPv7/BysjiOQi7PH1fW7tzLjBi/cOvdsu+owmGzbRwnEFdG8jRkynSq2MdmbNip3rfwlTtiuPPTyMixLEYwP2OjuGosZQZry8lhyvn56v487kBnp9v4+/nZ3YjzcpvhURJYptoZ+tRcDpO+5bGsmDNngKhiKkPXyubdp+S9TtOSpMry6sSS7RwRkUGhIuRMMFwK6McC3Dh+G45fDBarrrqaml2w2i756P1dkC5Z2hwkKzfdrJAqELzpOgrTJCH4aj3BR730Vd7VBWGNnIcparHTl9UoQvb/AZ776FRtUqV8ggbmFWCJkQEXis71yTjBrYQVynK8K3i7ozobj8KQgjxNBQSxdDF0rbJkrOmQZg8aRSK+PSbfXJHj4aqD4TmsYCIuJhe8PG2XgcNLb/hwrG/5PEZL8nH6T2l9pSZKr9h894zBZ6vhVFgPNG5cvaKnQ6TQnHuWqgBXgV7vS/0Ezrv7NlQWtSrIOXLRcizc36TMwkZ6nFaNYoR+vfQyOsx5cFO8vzc361CJhADaVl5UkFcp6hioDg6I17OfhSEEOL3QmLKlCni7dg2/dG6Smq7c2dzIYyyYiEAUKGAHXyP9vlNrbTST2fCRDM1WuLla2/NkZULXpRKV14t5jq3qxJR5DcAvZjQkiK/+f2omlGRnZdfvmoEhEL/LnVV7weUkSJPAzG1nYfOSZM6cZYGVkhQtJ3QiSZP6GPxnE5EAFR1IIfC6DWN5nroQQjPqH8EEl99qU2yOyWoSPJFxUl+xQa9F4QQz+J1QsIXRxAjZwBzNe7p1URMq3cblmtqQGzYDqbSOl2iSgEGGaWfcOPDQGNOB6pQ0I9Bn6+gN6KoDMF66teMlZdef0+++uQ1qd6oi7To/pAEBgapdSC/AZ6Lnh1qq0RNVDeYTWZJvJilKjFQIuoo1ACRUiE2QoUR9IZfdafs31zWbT2ucjWMjHt4WJCkpGbLDW1qWZpaQUBg0BeEDGygbf4DOkvazV+AYLPjoUH1hi9R2H4USPJ9+1JZrwa9F4QQT0Ih4QZGsfV/Ticrw4iyT+wSjeZCwHiiu+PkGetVcqWWbImkxWoVomTeql3yx54zVgOxFn6919rl3aCivPJAR3lp3kbVlwG/b9p9Wjo0qyYNapWT2Z+UkzpX95VG1w6TgIDAAtUZmGT5zH1t1UArLVygjf3WkkaNQFhj3spdBbwHOL/Zy3ZIxxbVDEUE1nfwnyT1/51aVJdalWOUIIJnA6Wm6BWBstOki/n5D1UrREp0WLAEmE128xcG39BAXpi7seBrxVdU/RR8OUxmdL/mKfFEN01CCHEGhYSbaLH1zNw8VSozZ/lO+fCrvRYR8OLIdjL4hvpq9gWMQVR4sOq2GBIQIJOGtpFFlzpY2oYZMGMCBhmGG48xyqWA4+DZEe1UxcNt3eLlyZnr5diu/5MP3pwksVUbqH9GaCEShFY00WA19Orauna9ABiAZXfq5IFzcm/vJgW8MNqckEffXaeSK3FeaFAF0NUSt8HDAkGhiRCM69aMob38BdyL6hbDXbmP9WNyNhtDf7+numkSQogjKCSKAAxeeHCQTLfZJSJMgeqgRT8cLGhY+zRRA6icdbl0VvmRnllf5SpMnvGrbPlmphzb/o382gdlktF216uN64bxxuwL5F/o8xkQMnlnwnUFPCnwKiD/wRGpGTlWg8K0CZooY1UVFTkmycz6b/eNXAp4R5zNijDKX8BK7CdIBvh0mMzR+1EY7wUhhFwuKCSKiNEusXWjyvLRmr2GYiE5LduliZnOEixT0UJb8uSnxW/Iyf3r5akXp0q5mldJC1PBiaOaGIBh17wPECq2hrxR7TjJys5VuRaYsImukrFlwpQH5ELyf0mSRoSFBBl6WBCuARAWaJ6l1hJfUVWuWK2vkLMiPJkgWZwUpgS1MN4LQgi5XPDKU0SMd4kBdss1IQAcoQkIZ5UfgZInD42+V04d+E2uuuVR6TPgDiUQjJo35XelbCbrt59Qhh1hgaSLWVbHg+GCeEBVBTwTmLx5JiFdlv50SHkaUJViN4E0vqLqRImZGjg/fXdLeCPwPAiHg8eT/gtBXApjqLBPRLCEhQQrL0Vp7KPgaglqYbwXhBByuaCQKCIRBlUCehe+Lc4Egna/6u1gp9kTDPPBExelYcNGcutt90i7TtcrQ4+wCDphogGUbcvqswnpqmIC/SSG3txIVWggT0FVb+A/s8hT729QeQvaQDAcA8Jh/7EEVZUy5Mb83AvbCgtUbZxNSEM2oHy78WiB7pt4XlzZMNUR7saralgMpOZRQB+FGUu2e7yPgiebQrniYSlqAy1CCCkJKCSKQF5goBz853yBXaLmwjfCmUDQSkPhFXh9bGdVTqo33PWrhkgFOSL/nK4rA4aNl+mLt8v3+zdZno8R0/AEYCS4Bl7vmsZV5PkR7dQwqXmrrI+J+0f3b6aSRPH6WmIlWmQDeBVe/3izyv1Ai2yUo55LylDZCHj8+Ld+lvgr4pTwaFqvvBrtnZtnlvAwfL3MKtFUyS0M4LIxdjDe6M5Zv1asKk/Vi5+5q3bJqD5NL4uB9JWmUGFBAcrrlJCcyT4ShBCvgELCTWAA4fo/n5yhZj6YTP/t1NHjwJ4LGiO7h/dtqvo62IYfht3cSOUoNK1TXnLzTPLnvtMyun9TSUjJUiGDpIQzMurugZKaelF+/PVPeX3hdqdjybUuk0/P2qBu33+sYA4FjOf7y3aqSpAX525UiZi23hOICXg0IBCMjqGfJDpp+nrL7Xgf4La353JH1Qs8KEZDwpBjgfsjSnhsr6+VVWIoWW5WjkQGXxKsXrQ2Qkjpg0LCTbc3EhHTMnLUlM8X5220zILInyhpljYNK6vru+30T3StTEjKLFDhgB04QgtqouYjXeS3nafku41HpV3TqnLqQppkJJ2WMcMHi8mUJ2/N+kIkMNT+LI9ejaVOtbKqOyTWCnEAWjes5LQSBEYduQr2vCfOqkn0I9FdcbmbzcbTS7XfR/bN78hZkrCskhBC3IdCoghu72E9GyuvhDYLAk2mtN06wgQYajW0J5otZUlsTLhs3HVKhR0m33ONXWMMUtKy1XHgIYDnYt1vf8rGpc9JcGiEtLv1BVmx6aIcSfjb7rCuMxfSLf0aIF5u7nilqsTAUCtHwOvRvllVNecDAgLhFQwSm6PznjirJkHXzDfGdnLZ5Y4x4PYSU3G76TKUdLKskhBC3IfbrCK4vQ8dT7KaCYHdumYUIS4CA/ITGAHi2TD6uD0myrFRQh5DvocgV71uSHi0xFaNlw5DXpWImPywA+6314lSH5LA49o0rqzKM52B50GEIAyCcAjyHtAHolOLaqrnBNp0Vy4f6fAYSN608uLkmeR8arak55rU74VJTHXl/uKAZZWEEOI+FBJFcHujlFIrizTarasmTJdGbuMndvkAO37tObbgdtwP1v/6q2SlJ0l4dJy07vOEhEWWK3B8o+fbzvJAuAVdMtE109Hr4nkQE9qaO7esptbcsHacrF5/WHk5ft95yuEx1m8/qXIkxr75s7y3eLucvpAhz875Xf0+fdkO5d3xNiOulVUaYSmrJIQQYgiFRBHc3jC4py+ky/0DmimDY1vaqf2Ox2HkNnb5MLap6dkqkdDWIGsJhrj/9KFN8sj9t8uhP5bafX3bCZna8xGS0JOVk6c8E7jd6HUhFnD7sZPJFhECbwTCIc/M/l0em7ZOhWjglUBOyKh+TdXcEGevrV7z18MqBKNPXtR7JrzBiGtllbbrYFklIYQ4hz5bJzjbEWPyJiossGvH4C19tYZ+Cqi2y4dRjYkOlUXf7TdMuMRI75P7fpE/V78ubTreJDfe/qjs+Dt/6JUeHBejtKdNuE6SUrNUSSY8Dvrx3drjMPIb6Negf92YqDBZ9P1+VU3yz+mLqrEUzhtVI+grgcchZPEJBojtz8//wDEgHHBflfKRKjnU9rWNEjBtkxe9pTeCq02hCCGEWEMh4QTn3QQvNZA6miCt6leU+3o3lbmm/ORE7M5R84/997ZLYgJ5EigBvbtXY5m7YleBkses47/I7KlPSs2mN0rPoc/IyP4t1HRNoyZPWdl5kpqeLm999qd6HSRo2ooIGPsgXV8LbQ163p3QRdo2rSK5uXmqBwYEiX5UOY7Tt0tdVeaqVaLoy0uxFkfJo7YhGNvkRW8x4v7SdpsQQi4nFBJOcHXHPKpvM8nKzZMLSRnSuE6c3HNLY9UWOigwQHp1riN39mgo2Tl5KpESHgyUgGq343d0moQBn7b6jBoDftvwx+TWrvGSmp4lDa+MK9DkacveM7Lsp0Py2phOMv62q9TroKGTVoIKQRAcHCjZ2Xmq74BdMdSgohw+kazKRS8kZ8nKddalmHgexFGeySRPTF8v/a+vJ3ffnH9uiFDAi6KVi9rDNuRj5OXB+6iFMbRwEj0ChBDi/VBIuIArO2aT2SThIUGq42NcmXBZsGaPpQwUYQCUVW7ee0Z5I66sXlZVXOTmmlQvijJRIbJoySrp0aOHvPPqJMvkTOQ2nEvMkvIx4Wq6Zn7yZq4y3moexhVxKvlR7w3A6718f0dJSctSG+pyZcLk9Pk06du5boG+FhAJI/o0VZ6HJy9Vl2Ctg26oLyFBgZKTZ1LiBjkSECt4HEaXL//pkHoczgECBK9hT6jYJn/amwnhK50lCSGEWEMhUUi3d0SZMCUoLlzMUoIiMiRIzJcaK8Hw16wULeHhwWp2BIw6Qg5IOITB1Zo5QVBomE15svv/ZsnRHd9Li8a/yJX1GqskShjn1LQcqVm5jHz89d4Cja2eHd5OvR5aV2tor7fwm4KPh6fi2pbVVbMqJYbCglVew6PvrlN5EFoY4+C/idL16poyf/Uu+WPPf+u07XJpK16Mxo9roRXkTjjKe/C1zpKEEEL+g0KiENjummFAYdAX/3hA3Ybf0WshF3O3L+3uta6NWnKj1fFyc2Tb12/L6UMbpWWP8VK+aj3lGdC8GO2aVpFP1lqLAoDjoUcFQh76nAj96xV4fGB+l0iID3gU4BWBGEBoo1JspFo3BEyVuEg5m5huJSJsE0dtwTTR0AAp4LVBiCUrJ1deHNXeYd4DO0sSQojvwquzixjtmmG40Z9Buw1GHb0WtIZT+gZVMMT6cs28nCzZsvJVOXP4Dxn39LsyZ+rjUi46TLXHfuWBjtKhWVWV99C9XW1VdomumRAYGnjNJleWt1ojhm3Z6xIJg4yZHYf+TVZtuhEa0eZwnE/KkG83HZXKsRESaDJJkMFsC7ulo5e8DAhVaF6bCtGh6ieOhTkZ2u/2vAqudJYkhBDindAj4SJGu2Z7cydCggOVwdV7IGCI4WGw7OoDAiQ4JFSmzf5MTuVUlxfnbbLycnz544EC4QmELfQllshjmPbodcrQ4nnoAgnBgXXpS0q1Cgysq17NsnIuMVOFM3AfjvfCyPZW4QNM67RFXzo6vE8T9VrFVV3hDU2pCCGEuAev0C5itCs26iwJQ7v3SILc3g0TQc1WhhjDsx7sW1fOnfxbTqbFyOvTPiwwSVPzctgbYqWfr4GqDIyTfn7uRiUkMBcDx7MtKdUECKosHnl7XYE1R0UEW4kBeyWvOAfkUHRvU1OitZyJYshdcF5iWzA5kxBCiHfA0IaLGO2KbcsaAbwBH6/dI3FlwqSCrn02OHXyhHS7qat88+mr8tLo9ip8YSsY9OEQW/TzNXDcwyeTVTOoto0rK4HxwUrr0eTac5A3MbxPUzWxVAPCA94LNJ+CSNLPwrjcnR7xqqP7s7MkIYT4IvRIFGHXbJSACC8FRnFv//uCVK8QpfIKwIZN29QEz8DAIOl1zwvqcZgcCrTkSoiEMDWG3D54nr4aAh01h93cSIkBR+O90dcCHTC119OqSfTP0ZdbXq4mUVoC696jCeo96N2pjqqCQQJoZIj9vApCCCHeAT0SLmK0S0fuAbo66m+DlwKCAL0fUtJylLEPyz0lO1Y/J1Uqxsl3P/wk7Vo3U7cjZ0Ez6ghJIE8iy0lzJ0zfRGttLVcCeRSBAQFWYRQjMrJz1YCx50e0U30mMITL1nthOwvDNnlSM+q4Hx4MR1M9C5vAqpWU4j14ad4mVX5KCCHE+6FHohDY7tIjwkPk4D+JclePRjKsZ363x9iYMMnMypPk1GzLJM1vNxySKtXryLNT3pfyFSpJpcqBqkEVZmCgQgOdJfcfS3BaZgnBgqZXDWrF5idXXkq6zMjKVX0nHIHkSBhq7PjRrMq2pNTVcsvibBzFsk9CCPF9eJUuJNouvXyZMFm4do+UjQ5ThnzyzPWy/59ECZAA1e4ahn7njq3SvG6sVK3dRD78bIUcOJktF9Nz5OO1e+WRt39RPSPQEGrDjpOqigLPsVdmqUo1O9aRR975RVb/elhefqCjlLs0EwKvh5bYzkaEQzx8tf6wGsDlTrmlUQks1owpoWcSMwrtoWDZJyGE+D70SLgJdsub9pyR7YfOq2qJFvUrqNuxJ4eh/u7/Vsn4MSPkoUefluH975ZVvx6R5vXLy4WUTCUUerSrbVWeCdOLORZoQa2VWd7ZPV4uZuSo+7RSTXgh4K34YMUuGTu4lRIGyF9ITc9R472RcKn3NmDcNxpRnTiXpvpR4DjullvaehBcybVw53VcvZ8QQojn4ZXaTfS7ZQzdurdXU5m1fIcyqFXNO2XuO89JjUadZcidwyWuXJTMW7lL7u/fTGYt32kVttCXZ2IwF4SEli+AXAvkCxiBY6Cfw729msjG3adUt0qA6gwM1cJMDnSWPHQ8SXk99JM8r7+6hrRpVNmqVbcr5Za2HgJ7nTRdbW3Nsk9CCPF9KCTcJL8FdP6O/MC/SbJ+20mV51AmZYN8MPd/0m/QMHl5ylT590yqmCRDGd05K6xFhG1/CEz31KP9pq/q0DeaSs/IkSdmbrASI5jxgd/hnZizwrgcdM7ynTL05kaSazI5nGhqdM6uNORyNcfB1cmqhBBCvBcKCTfBbnlE36ZqR445GhARE++8WsaM/VDqXTNQcmr0lydm5Bt5lF6iQsNReaYa/63LXcDzUAJpL3yA+zFcC/fbNqvC78ibsNsu+8A5NXJ8eO+mIr3NLpd32noQjBpy6VHHvZTHYY/LVWZKCCGkZKCQcBMYuqZ1KkhcTLgSCXd2jpavNhyRKlcNlaq6ZEMYc4QX4sqGOzwe7KY29AszOeJiwiyhCnuDuDBtUy8eIEY0MJ7cEfkiID9x1GLsnRhvWw+CUUMud3IctARWV9dBCCHEe2DVhpugDBKG/Pk5G6RXvyFy24CesvGv/RJgULEwb9UuqVQuwuHxypcLl/XbT6ihX0/P+k2ysk1iMpulYe1Yh54FrdOlrYdA790wAmJF5SAUEs2DMH3idcpjYtuNskCOAyGEEL+GQsINtDLILXtOyJ9fvSEn9/8qT774loRHxxV4rJbfgImado1ug4pqE77sUsIkQEnpuq0n5XxSpsO16MWD5iFA2ONCcqbDctDKcZFuhw8sHoTggMvaSpsQQoj3wdCGGyCev3nXP7J55auSeHK/tO4zWXr26i+bbSos9PkNKPHE/5tM/yVYaiLirp6N5IUPfrdUVgBUXaDbZfumVR2uRS8etGZWKC9978ut8tDgVhIYkO+5sLxefEUZM7ClhAaYJddxioNLMMeBEEJKNxQSbgCDmZOVLjmZF6Xtrc9J+RpNDDtS2pZHav0hkMsAM1suOkw27T4tT72/wUpEaKJAy69ALwijTpTa4yAO7uvdVC6mZalR5ZgympSarV7v1Qc7yq1d60soPAjhwRIVFiwV4iIlMTGt2N4P5jgQQkjphUKikJw5c1qyJVAiypSXzne9JQEB+fMy0FkSJZdzV+6yeABsyyO1/hAab4/vorwOtiJCG8il5Veg4dXcVbusSyQbVJT7+jSVC0kZck3jKvLYtPxeEXg+hobhdRpdGSeRYcFSNiLE4iEIcm8sBiGEEGIIhUQhOHr0iAwa1FcaNW4ibfo9qQy7PnyBHAd0p0RjKZRfGiVe6jmbmK4GcN19S2M5m5Bu6Q+hdbAE+ImulEN7NlJzMvR9JDTxgI6V2uO16g14KTCaO0DMqjMmIYQQUhJQSLjIvn17lYiIjIyUV15+XarVukKVQWLOhBa+gKioV72cfPrtfvU7DLwjUDYKoDdQrWEPhCT+Pp6smk3ZC2/oQUdLrGv8Wz9L/BVxakJppXLhEsiQAyGEkGKGVRsusHXrn9K3bw8pX76CrFr1rdSsWUslGY65tYV0alHNqiGUPidCy5swAnkP1StGq+mhv+885bDComxUqFQoF2E4yAthECRy6kGiJkIb2lyORT8ckG2Hzrs97psQQgjxao+EyWSS6dOny+LFi+XixYvSpk0befbZZ6VmzZriLd6IevUayKeffinlysX+N057yXbp3q625XG2ORFapQawna+BUIWWT7H3aILh45AHgcdt3nta6lQrJ3ff0kiCAjFHI09yck2y49B5qzCIPQ+FFu5AZUVIkFd85IQQQvwEr7AqM2fOlM8++0ymTJkiVapUkf/9738yYsQIWb16tYSGOm6xfDm4/fa7ZNCg2yQ4OLjAOG20mtawbRkNA6+v1EDIAd4CGPqLadmWoVm2j8NxqlWIkvU7TqpR41oSpZaEiZAJJow6S9TUg2Oi2iSGEzUJIYQUIx63KtnZ2TJ//nyZOHGiXHfddeq2t99+Wzp37izfffed9OrVS7wBTUTYjtPWl30atYzWV2pAALx4qdcEWmHbexyYMqaT8nDUue0qqyRM5DxsO3heGteOU4maWltshD7Wbz9ZwEOhgWNwLDchhJDixuOWZd++fZKWlibt27e33BYTEyONGzeWzZs3e42QsDdOWwtfIP3AqJeEvZADWlQ7AmWbn3+Xn7Rp5HG4Or6StG5YSaIigiUkOEiFOQ78Y+2h0D8vISVTrqgUXYSzJoQQQrxQSJw+fVr9rFrVuoNjpUqVLPe5Q7CD8dWOQCtr/U8jIsP/EwFaWAKNn1JSs6Vzy+oyHz0fdA2kYMgfvLW5ZGTnSsv6FSUCngGz2WqSph51+4EzyuNwT6/GcuZCulQuH6mSMjWPQ1REiMSEBwkmj09bvF3lWUwa2lqVetq+tqraiA2XkMAAl87Pl+H5+S7+fG6A5+fblJbzCwjwQSGRkZGhftrmQoSFhUlycrJbxwwMDJDY2KgirSsmxv6QreD0bCsRAMN+NiFDlXBqszWQO6Hv+XDyfJq8MHej5RgdmlWV0f2ayewVO60bTcXnG/6MrDxZu+GIug0hD4RCtNAHHoNpomUiQ+X42YsW4fDGJ1ssfSxy88xqcFdkWJDERIepx7p6fv4Az8938edzAzw/38bfzy8wMND3hER4eLglV0L7f5CVlSUREe59YCaTWVJS0t1WZfiipKRkSF6e/WEUDwxoLu9fGqcNtPwI21wHjWkTrlMdKnHMPJNJYqLC5MPVu1W/B63RFMIdyGNAi+srqpZVVRpPztxgdXw1EOvW5pKblSOJWTkqaVMDr/35t/vVP403xnaSyJBA9djCnJ+vwvPzXfz53ADPz7cpLeeHKsrCigmPCwktpHH27FmpVauW5Xb8Hh8f7/Zxc4s4kQpfFHvHQNXGvJW7ZESfppJ4MUtS03OkXJkwhzMx9v+TKI2vjJMX522WZ4e3kw9W7lKP3bTnTIHHai2uky7WUeIAZaAY2Y3R3WoglgkDt/KbSzlLoMT9Rufh6Pz8AZ6f7+LP5wZ4fr6Nv5+f2Y2+hR4P9jRs2FCio6Nl06b/JmempKTInj17VD8JTwPRkJ5rkvOp2eonfs/MzVMC4FxihmTn5Mk3G48qzwE8C7ZNo+BBeODW5tKsXnk1EjwrO0+1zzYSHADJlajWAPBS4Hi9OtWRjKwcNRjLdqomhIXd8eTxFdX9hBBCSEnhcY8EciPuuusuefPNNyUuLk6qV6+u+kign0S3bt08urY8Xb8IDTXDol8zub17vNrtp2bkyB3dG6oqiwvJmSockZsbrzwVaIGN/Ah4L66sXlb1fZg0rLWk6MIRRmj9KJBgiYRLJFi+Oa6z4WMhLB4c0Fy167bNtcDtHOdNCCHEr4UEGDdunOTm5srTTz8tmZmZyhMxb948CQlxXCJZkqAawlZEgL1HEiQhJUv91OciwHMwsl9T+WTNHqtwBcISI/o2lQ07Tsr+YwkSFR4iiSlZDl8b+RB43h97TqsQh8WzYEcUoF332AHNVX8LlKZC4KgQCEUEIYSQEibAbPY/a4MYVkJCmttlo6j4OHYqRca++VOB+wff2EB5Fox6RcD4Y+JmRlau6tug9ZZArwk0kkIPiKjwYEnPypWV6/6byaFHlWveVB8xFdl1+Lwq64RnAWKhONDOLzExzS/jfDw/38Wfzw3w/Hyb0nJ+eXmmQpe4eoVHwhtJz8yvcrDFdp6GHngvcvJMsmDNngIiQft9dP9mEhQUoESF/nZ9w6nIsBB5YsZ6eeOhznLDVTXoWSCEEOK1UEi40HRKj+08DVvSM3IMPQ0AtyPZEj0ebGdr6Ntgo6oD1RqZWbkSbdB2mxBCCPEWKCTsEBUWZNh50miehp7wMMdVEtm5eSqHwV6/ifxj5H8snI1BCCHE2+F21w5BAaJyE2xLK1GZgVwII/DYsBBnfR1CJCw0uECZqEb+7fnts1m6SQghxNvhltcBWjVEalaunDqfrrwRh44nqfbX6AelD2GofhEDmsu+Iwl2Z2ioxlTHEqRh7Vi57aYGhjkSaI+NRE+WbhJCCPEFKCScAGMeFBig5mhoaPM0tPyGahWjVB+JD1bslLo1y8mIvs1kzvKddid3Pn1fWylfNlyuu6q6VY4EKj0qlA2XKuXCVaknml+xpJMQQog3QyHhAlr3SP2QLv0ALdXDITtX9Y/o3r62nDibqhpJQSQgsbJCuXBVLoQmVZjQGR4aLPNX7VZ9J7J1QqFW5TKSlZMryZm5UiYqTGYbNMMqzlJQQgghpKhQSLiAK90jIQaA5l2A0IDn4rG7WstHa/Zah0Ea5Le9zsxGVUaQREaHqi6aM5ZsV8LBXq8KvDbWAOFCzwQhhBBvgELCRZx1j9QqLLQyToQy4JVY9WvBxlMQC8ixGNm3qfodIQx9F02HvSr2n1NrwNwNQgghxNPQGhUCiAYY8ArRoQUGaGnhD4iIIyeSVT5E83oVHPaUMF16PoSBPoThtFfFJe8HIYQQ4mkoJIo5/HHsVLL0aF9bvvn9qIQ4aTMKQYCQhq0wcNargv0lCCGEeAsUEsUc/hjVp6lUKR8hd9/SWCKcGHzkUCDnwbaLphYaMYL9JQghhHgTFBIl4JmICAqUyOAAVRLa0o4gwO3nkzNVzkNwUIBV4ysM+UJoxFZMcDQ4IYQQb4M+8hIk0GSSBwc2lxlLdhToKTGiX1N5+v0N6veL6dlWVSEoL0W/CYwfx7+MzBz2kSCEEOKVUEiUMMFms4wZ2FzSMnMlIzNXhTvQZhsiIik1Wz0mIizYYVVIVHRo/sEoIgghhHgZFBKXAWQ0fLx2j2HbbEvOg9lsqQpBXwkFhQMhhBAvhzkSl7Giw3YAGHMeCCGE+Dr0SHhJQytCCCHEF6GQuIwwdEEIIcTfYGiDEEIIIW5DIUEIIYQQt6GQIIQQQojbUEgQQgghxG0oJAghhBDiNhQShBBCCHEbCglCCCGEuA2FBCGEEELchkKCEEIIIW5DIUEIIYQQt6GQIIQQQojbUEgQQgghxG0oJAghhBDiNhQShBBCCHGbALPZ/2ZZ45RMJvdPKygoUPLyTOKv8Px8G38+P38+N8Dz821Kw/mZzWYJCAgo1PP8UkgQQggh5PLA0AYhhBBC3IZCghBCCCFuQyFBCCGEELehkCCEEEKI21BIEEIIIcRtKCQIIYQQ4jYUEoQQQghxGwoJQgghhLgNhQQhhBBC3IZCghBCCCFuQyFBCCGEELehkCCEEEKI21BIXMJkMsm0adOkc+fO0rJlSxk5cqT8+++/4o/Mnj1bhg4dKv5EUlKSPPvss3LttdfKVVddJbfffrts2bJF/IULFy7IY489Ju3atZNWrVrJqFGj5O+//xZ/48iRI+r8li1bJv7EmTNnJD4+vsA/fzrPFStWyM033yzNmjWTW265Rb7++mvxBzZt2mT42eHfDTfcIL5Obm6uvPvuu3L99derv70777xTtm3bVriDYPonMZvfe+89c9u2bc0//fSTee/eveb77rvP3K1bN3NWVpbZn1i4cKG5YcOG5rvuusvsT9x7773mXr16mTdv3mw+fPiw+YUXXjA3b97c/Pfff5v9gSFDhpgHDRpk3r59u/nQoUPmhx56yNypUydzenq62V/Izs42DxgwwNygQQPz0qVLzf7Ezz//bG7WrJn5zJkz5rNnz1r+ZWRkmP2BFStWmBs3bqyuL8eOHTPPnDlTXWf++usvs68DG6D/zPDvu+++M8fHx5uXLFli9nWmTZtm7tixo/nXX381Hz161PzUU0+Zr776avVddRUKiUtflFatWpk//fRTy23JycnKEK1evdrsD5w+fdo8evRoc8uWLc09evTwKyGBLz+Mz5YtWyy3mUwm84033mh+5513zL5OUlKSecKECeb9+/dbboPYxTlDWPgLU6dONQ8bNswvhcScOXPMvXv3Nvsj+Fu7/vrrzVOmTLG6HZuxWbNmmf2NtLQ0db5PPPGE2R/o06eP+bXXXrP8fvHiRfU3+O2337p8DIY2RGTfvn2SlpYm7du3t9wWExMjjRs3ls2bN4s/sHv3bgkJCZFVq1ZJixYtxJ+IjY2VOXPmKJeqRkBAgPqXkpIivk7ZsmVl6tSp0qBBA/V7QkKCLFiwQKpUqSL16tUTfwB/Z4sWLZIpU6aIP7J//36pW7eu+CMIR504cUJ69+5tdfu8efNk9OjR4m/MmjVLMjIy5PHHHxd/oHz58vLTTz/J8ePHJS8vT/0dhoaGSsOGDV0+RnCJrtBHOH36tPpZtWpVq9srVapkuc/X6dq1q/rnj0D0denSxeq2b7/9Vo4dOyZPPvmk+BPPPPOMfPnll+oP/f3335fIyEjxdSD2Jk2aJE8//XSBv0F/4cCBA0rwIv4Mw3vFFVfIAw88oHJ6fB2cD0hPT5fhw4fLnj17pEaNGur8/O2ao4n4Rx99VMqVKyf+wFNPPSUPP/ywyvcICgqSwMBAee+996RWrVouH4MeCRGlLgEuznrCwsIkKyvLQ6si7vLXX3/J5MmTpVu3bnLdddeJP3H33XfL0qVLpVevXjJmzBjlafJ1nn/+eZXkZbuj9ReQzHb48GFJTk6Whx56SHnPkNCNhNnff/9dfJ3U1FT1Ezt0fC/nz58vHTt2lAcffNAvzk/PZ599JmXKlJEhQ4aIv3Do0CF1TjNmzFDeiAEDBsjEiRNl7969Lh+DHgkRCQ8PVz+zs7Mt/w8gIiIiIjy4MlJYfvjhB/VHgMqNN998U/wNLZTxyiuvyPbt22XhwoXy2muviS9n+qO6ZvXq1eKvBAcHq8x/7Pa060vTpk3l4MGDyv2vD6n6IgiZAngj+vfvr/6/UaNGyjPx4Ycf+vz52X5f+/XrZ2UnfJlTp04p7wq8LK1bt1a3IUQMcQGvxMyZM106Dj0SupDG2bNnrW7H75UrV/bQqkhhgVHFjg9lTIhjwqPkL+7UNWvWqJ2tBtyPEBW231lfA94VlLbCcwSvBP6B5557TkaMGCH+QlRUVAHjU79+fVUW6uto10gth0cD30/E3f0plw4tAfzJc7Z9+3bJycmxyi8DyKNDaNhVKCREVFJJdHS02jXo47ZQ1G3atPHo2ojrLseXXnpJxaDfeuutAmEqX+b8+fMyYcIEKzcx/vjx/fT1BD54jdauXat2eto/MG7cOOV18QfgeYCHTH99Abt27fKLZNkmTZoooQSjZJsXUpg4u7cDzxkSEwuThOjtIGFbSwa2/exq167t8nEY2riUG3HXXXepi1pcXJxUr15d/ve//6k3GXF24v3JXq+++qrcdNNNKkschlcDu0DE/3wZ7PSQlPfyyy+rf6jiQFMxiN177rlHfBl7Hj9csP3FGwixV6dOHXnxxRflhRdeUEmXSJhF0x94ZHwd/I3Be4QYOz6z5s2bKw/ahg0blMvcX4BwRxMqf6J58+Zy9dVXq/wWeAFh8yDmsWn5/PPPXT4OhcQlsAOC6xiZ45mZmcoTgfilFv8j3gsqNLBD//7779U/PYjZ+kNJIbwsKAF95JFH5OLFiyqe+emnn0q1atU8vTTiBIShEGrD5zd+/HglAFFajvwB23CAr4LESuSTvf322ypcA/GEGHvbtm3FXzh37pzfVGrov5uo/nrnnXdUgjoSgvGdhAAsTJuAADSTcPnRhBBCCCE6mCNBCCGEELehkCCEEEKI21BIEEIIIcRtKCQIIYQQ4jYUEoQQQghxGwoJQgghhLgNhQQhhBBC3IZCghBS4pRUuxq2wSGlndmzZ8vQoUML/Tx0sLz55pvVnI1bbrlFvv76a7fXQCFBCCkxMFEX7ctLYronJhOi+ywhpZVPP/1UdaUsLCtXrpSnnnpKzSZCO3OMf8c8n61bt7q1DgoJQkiJgemkH330kdXk0uLi3XfflYyMjGI/LiHezpkzZ+T+++9X86EKM1xL8+Lhb2fYsGFKSGCw2gMPPCAdOnSQP/74w631UEgQQgghPsTu3bvVHKhVq1YZzsT46aefZMCAAWooF4YZwmsB76A25PDEiRMFxqHDu4ehh+5AIUEIMeT1119XFyIMCbMNKWBioDNvwPHjx+WGG25Q/4+BQF27drUayYyJu7gIXnPNNWr6YEJCguV+k8mkBkDhOU2bNlU/MfQKw9mANoVx+vTpfjeRkRBn4O8BQ9Fq1qxZ4L5169ap4XCDBw+Wr776Sk31RP7DY489ZhESID09XYYPHy7t27eXQYMGyf/93/+Ju1BIEEIMGThwoGRlZck333xTIL6KJC1Me3REpUqVlKEHcJ1q/79582Y1/hzjp7FTevLJJ5VLFa5WTN4FH3zwgRpjPGbMGJk/f77cfvvtaseESYVg0aJFljVq/08IETVpFiLitttuU2GLTp06qfH1+DuGuE9NTVWPg3hHbgT+vjp27KgmuGJ8uDtwjDghxBCMgm7VqpUSDtixgL/++kuOHj3q0mj20NBQadSokfp/XNAwOhvAs3DllVeqbPOgoCB1GzwTyBxfunSpittCWMATceutt6r74bWAcClTpoz6vWXLlupnlSpVLP9PCBHZs2eP7NixQ5YsWVKguunvv/9WIREAb0T//v3V/+PvFM/DaHt4KAoLhQQhxC4w5M8884yKqVavXl2WL1+uRAAEhjsgHLJ9+3Z1EcPFTUvChIsWwmXDhg1KSLRt21YJjjvuuEO5ca+77joVCiGEOAZhwREjRlhEgp6KFSvK3r171f83aNDA6r569erJzz//LO7A0AYhxC5aCANeCYQ5EGtFEpe7pKSkqAsdQhdNmjSx+nfgwAFV5QFwIXz22WdVqAOZ6fBWwA27cePGYjw7QvyP+vXrqzyIK664wvLv9OnT8sYbb0haWpr6W4uKilKCXg/+/uA5dAd6JAghdsEFp0ePHkpAYAeDBK2+ffsW6XgBAQEqRwLiwBYt7yIwMFB5JvDvwoUL8ssvv6jY70MPPaS8FgibEEIKMnLkSJVsiZwk/I1BRKBnRI0aNZRHQhPqM2bMkMqVK6uEavSSwN/VggULxB0oJAghDkFC47Jly1Q/CNSa4+LjKloOhEZ0dLTKlTh8+LDqqKcBz8O4ceOkS5cuysWKRDHkSDz99NNSvnx55QVB9QiaWyFZLC4uTokNQog1EP6oeEIOEsR3uXLlVHhw4sSJlscgsRKiHY9DTwqEFVEFgpCiOwSY2WOWEOLCxQnuUlx4EO5wFRh9lIr26dPHUu65fv16GTVqlPTs2VPdnpeXpzLH4Wr95JNPVPIk8iNwGzwQyMfAxe6tt95SuRR4DMBFD6IEF8XWrVsrTwch5PJDIUEIcQqqNOCVgAgobFgBz0WJJrLF4T7FT5SZwfW6a9cu9TvithANEAQASZgo9UTDHbhmUa2BXdWjjz4qsbGx6jHIMEdPC/SWWLt2rVSrVq1Ezp0Q4hgKCUKIQ3CJQKwV9ejo+UAIIXqYI0EIsRuWQPLVzp075d9//7WaMIhwhLM9CEINtjkShBD/g0KCEGIIOk9+8cUXqlwTSY76drzo34/eEo5AEyktn4EQ4r8wtEEIKTT79++3DAFyVOpZp06dy7YmQohnoJAghBBCiNuwEJsQQgghbkMhQQghhBC3oZAghBBCiNtQSBBCCCHEbSgkCCGEEOI2FBKEEEIIcRsKCUIIIYS4DYUEIYQQQsRd/h8KyEai3TIXIAAAAABJRU5ErkJggg==",
"text/plain": [
"<Figure size 600x600 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.figure(figsize=(6,6))\n",
"ax = sns.scatterplot(x=y_test, y=y_pred)\n",
"ax.set(xlabel='y_test', ylabel='y_pred')\n",
"#ls = np.linspace(0, 8000000, 100)\n",
"ls = np.linspace(min(y_test), max(y_test), 100)\n",
"\n",
"plt.plot(ls, ls, color='black', linewidth=1, linestyle='dashed');"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Exkurs: Lineare Regression in der Datenanalyse"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"see `extra_3.2.1.4_linear_regression_in_data_analytics.ipynb`"
]
},
{
"cell_type": "markdown",
"metadata": {
"tags": []
},
"source": [
"### Regularisiert (Lasso & Ridge)\n",
"#### Theorie"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"kein Code"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Praxis"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Lasso"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"ExecuteTime": {
"end_time": "2020-04-08T10:06:30.858403Z",
"start_time": "2020-04-08T10:06:30.831507Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"-105470886.1768084\n",
"[ 2.45382007e+05 -1.41353663e+05 -4.03813210e+04 1.61339539e+05\n",
" 4.03901128e+04 8.33016390e+04 2.73752966e+05 -2.48435395e+03\n",
" -4.97724694e+03 -5.14822258e+05 1.92458888e+05 -1.19820804e+00\n",
" 9.42421791e+04 4.16277687e+04 5.41476009e+04 -1.85046554e+05\n",
" 8.78859504e+04 2.43991164e+05 2.65409309e+05 -2.31713779e+05\n",
" 1.75566829e+03 3.11522359e+04 4.70809165e+03]\n",
"0.5601427046293164\n"
]
}
],
"source": [
"from sklearn.linear_model import Lasso\n",
"model = Lasso()\n",
"model.fit(X_train, y_train)\n",
"print(model.intercept_)\n",
"print(model.coef_)\n",
"print(model.score(X_test, y_test))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Ridge"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"ExecuteTime": {
"end_time": "2020-04-08T10:06:30.889520Z",
"start_time": "2020-04-08T10:06:30.861514Z"
},
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"-104848432.75509366\n",
"[ 2.45313734e+05 -1.41286745e+05 -4.03551367e+04 1.61451266e+05\n",
" 4.03883258e+04 8.32645429e+04 2.73073082e+05 -2.48815619e+03\n",
" -4.97090955e+03 -5.01905886e+05 1.91808304e+05 -1.19046859e+00\n",
" 9.41302477e+04 4.15608389e+04 5.40286449e+04 -1.85615436e+05\n",
" 8.95306012e+04 2.44605950e+05 2.62482445e+05 -2.31923181e+05\n",
" 1.75409669e+03 3.11367809e+04 4.71584524e+03]\n",
"0.5601387631837789\n"
]
}
],
"source": [
"from sklearn.linear_model import Ridge\n",
"model = Ridge()\n",
"model.fit(X_train, y_train)\n",
"print(model.intercept_)\n",
"print(model.coef_)\n",
"print(model.score(X_test, y_test))"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" cols coefs\n",
"0 Rooms 253568.228957\n",
"3 Bathroom 168521.486901\n",
"4 Car 34293.196859\n",
"5 logLandsize 76942.997592\n",
"12 Method_S 18550.768445\n",
"17 Regionname_Southern_Metropolitan 286752.054486\n",
"22 day_of_week 781.020849\n",
"['Rooms', 'Bathroom', 'Car', 'logLandsize', 'Method_S', 'Regionname_Southern_Metropolitan', 'day_of_week']\n"
]
}
],
"source": [
"## use Lasso for feature selection\n",
"model = Lasso(alpha=10000)\n",
"model.fit(X_train, y_train)\n",
"results = pd.DataFrame({\n",
" 'cols' : X_train.columns,\n",
" 'coefs' : model.coef_})\n",
"print(results.loc[results['coefs'] > 0])\n",
"\n",
"## create a filter maks of the above\n",
"mask = results.loc[results['coefs'] > 0]['cols'].tolist()\n",
"print(mask)"
]
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"### Logistische Regression\n",
"(hier nur noch der Vollständigkeit halber, wurde unter Klassifikation behandelt)"
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