{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Demo - Uso de sklearn. Aproximación y generalización" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "# En esta celda se definen los modulos que se van a usar en el notebook \n", "# También se configuran otros aspectos comunes a toda la práctica\n", "\n", "import os\n", "import numpy as np\n", "import pandas as pd\n", "from scipy.fft import fft, fftshift, ifft, fftfreq\n", "from scipy.signal import spectrogram\n", "import matplotlib.pyplot as plt\n", "\n", "\n", "#estilo de las gráficas\n", "plt.style.use('ggplot')\n", "\n", "# FORMAS DE VER LAS GRAFICAS --------------------\n", "# ELEGIR UNA DE LAS OPCIONES Y DES-COMENTAR (sacar # de la linea)\n", "# ----------------\n", "# a) graficas en línea entre las celdas (no interactivo)\n", "# %matplotlib inline\n", "# ---------------- \n", "# b) graficas en línea entre las celdas con pan/zoom\n", "# %matplotlib notebook\n", "# ----------------\n", "# c) graficas en ventanas externas (abre una ventana por cada figura)\n", "# %matplotlib\n", "# ----------------\n", "# d) Si se usa \"jupyter lab\" en lugar de \"jupyter notebook\" usar %matplotlib widget en lugar de %matplotlib notebook \n", "# Si se usa vscode usar también %matplotlib widget en lugar de %matplotlib notebook\n", "# requiere instalar el modulo \"ipympl\". Ver https://stackoverflow.com/questions/51922480/javascript-error-ipython-is-not-defined-in-jupyterlab#56416229\n", "%matplotlib widget\n", "#---------------------------------------------------" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Uso de sklearn\n", "\n", "En este ejemplo suponemos que tenemos un conjunto de datos al cual ajustaremos una recta mediante regresión lineal.\n", "\n" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "from sklearn.linear_model import LinearRegression\n", "from sklearn.model_selection import train_test_split\n", "from sklearn.datasets import make_regression" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Generación de datos\n", "Para esta prueba los datos los vamos a generar en forma artificial a mano pero se podría usar **sklearn** que tiene algunos datasets de prueba y también generadores de datos en el [módulo \"datasets\"](https://scikit-learn.org/stable/datasets.html) \n", "Ver [sklearn.datasets.make_regression](https://scikit-learn.org/stable/modules/generated/sklearn.datasets.make_regression.html#sklearn.datasets.make_regression) \n", "\n", "\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Generación de datos de prueba con sklearn" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "cantidad_de_muestras = 100\n", "cantidad_de_features = 1 \n", "ruido = 10\n", "bias = 30\n", "\n", "X, y = make_regression(n_samples=cantidad_de_muestras, n_features=cantidad_de_features, \n", " bias=bias, noise=ruido, random_state=42)" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(0.5, 1.0, 'Datos generados')" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "2e637e57feba4f9c8674872f37e23944", "version_major": 2, "version_minor": 0 }, "image/png": 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", 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\n", " " ], "text/plain": [ "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.figure()\n", "plt.plot(X,y,'.')\n", "plt.xlabel('x')\n", "plt.ylabel('y')\n", "plt.title('Datos generados')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Generación de datos de prueba a mano\n", "\n", "Los datos corresponden a una recta pero tienen ruido agregado. \n" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "np.random.seed(42) # para que sea reproducible\n", "m = 100 # cantdad de datos \n", "# coeficientes de la recta\n", "corte_con_y = 4\n", "pendiente = 3\n", "\n", "\n", "def f(X, corte_con_y, pendiente):\n", " return corte_con_y + pendiente * X \n", "\n", "\n", "X = 2 * np.random.rand(m, 1) # X son muestras uniformes en [0,2]\n", "y = f(X,corte_con_y, pendiente) + np.random.randn(m, 1) # y = f(x) + ruido gausianno (0,1)" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(0.5, 1.0, 'Datos generados')" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "42669638b4f1459389d47861adbbb9b8", "version_major": 2, "version_minor": 0 }, "image/png": 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", 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\n", " " ], "text/plain": [ "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.figure()\n", "plt.plot(X,y,'.')\n", "plt.xlabel('x')\n", "plt.ylabel('y')\n", "plt.title('Datos generados')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Partición de los datos en entrenamiento y test\n", "Usaremos la función [sklearn.model_selection.train_test_split](https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.train_test_split.html#sklearn.model_selection.train_test_split)\n", "\n" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(10, 1) (90, 1) (10, 1) (90, 1)\n" ] } ], "source": [ "X_train, X_test, y_train, y_test = train_test_split(X, y, train_size = 10 , random_state=42)\n", "\n", "print(X_train.shape, X_test.shape, y_train.shape, y_test.shape)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "### Regresión\n", "Para el ajuste lineal usaremos [sklearn.linear_model.LinearRegression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LinearRegression.html#sklearn.linear_model.LinearRegression)" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Valores reales------------------\n", "Corte con el eje y: 4\n", "Pendiente de la recta: 3\n", "Predicciion---------------------\n", "Corte con el eje y: [2.69224545]\n", "Pendiente de la recta: [[4.17366396]]\n" ] } ], "source": [ "# Inicializamos un modelo de regresión lineal \n", "model = LinearRegression()\n", "\n", "# entrenamiento -> ajustamos el modelo con los datos de entrenamiento\n", "model.fit(X_train, y_train)\n", "\n", "# una vez ajustado vemos los parámetros obtenidos\n", "\n", "print('Valores reales------------------')\n", "print('Corte con el eje y:', corte_con_y)\n", "print('Pendiente de la recta:', pendiente)\n", "\n", "print('Predicciion---------------------')\n", "print('Corte con el eje y:', model.intercept_)\n", "print('Pendiente de la recta:', model.coef_)\n" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "3788eb88716944889b3d0b7a3ee178c6", "version_major": 2, "version_minor": 0 }, "image/png": 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\n", " " ], "text/plain": [ "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig, ax = plt.subplots(nrows=1, ncols=1)\n", "ax.plot(X_test, y_test , '.', label='Datos de test')\n", "ax.plot(X_train, y_train , 'o', label='Datos de entrenamiento') \n", "ax.plot(X, f(X, corte_con_y, pendiente) , '.g', label='Ideal y=f(X)')\n", "ax.plot(X, model.predict(X) , '.m', label='Ajuste por regresión lineal') \n", "#axs[0].set_ylim([-2, 2])\n", "fig.legend()\n", "\n", "y_pred_test = model.predict(X_test)\n", "for i, xx in enumerate(X_test):\n", " ax.plot(xx,)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Ejemplo sinusoidal de la presentación de la clase 2" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "El modelo real es sinusoidal y le ajustamos polinomios de distinto orden: \n", "* Orden 0: Una función constante\n", "* Orden 1: Una recta\n", "* Orden >=2: " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Datos\n", "\n", "y = sin(x) + ruido" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [], "source": [ "# Generate data\n", "N=1000\n", "np.random.seed(0)\n", "\n", "x = np.random.rand(N) * 2*np.pi\n", "y = np.sin(x) + np.random.normal(0, 0.1, N)\n", "\n", "# Reshape x to be a column vector\n", "x = x.reshape(-1, 1)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Ajuste lineal y polinomial" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "a97390a0a16844d2b42dc55482a1837f", "version_major": 2, "version_minor": 0 }, "image/png": 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Pc9CaJBNThBBCVJEEgKJuKm/8nSPdpeUFXGDa9+Eb5V/DaMT44xLYutZyraKbboX8PPvXLP5fffEhqnSL4/iptt3JZe5V+rnZa/2sbmAshBBCgEwCEXWVeTxeaaXG35VHpSZjvHLJOeXY8rN10LblZ9i1qeLzyrY4rlgEYyaagkA9mmZ5buXOPq6BiSlCCCEan1pvATx27BirVq0iNjaWtLQ0nn76afr371/bxRB1nDq633bcXvH4O93ji4MjFXcGtfzz8lv/XMFohDXLKiyXSk1G7d1mP8irZmBcnQk1QgghGo5aDwDz8vJo1aoVI0aM4B//+Edt3144SU0GEzYtYGZNW+kebzORozYNuhlt+B2oU0fAHHja6+qtoEva+L+lsHmN/v7iIK+ygbGZJLQWQghRWq0HgL169aJXr161fVvhRDUeTOh1cyqFeutpjFMet4yFIzEe5entuuAPYOdGFBqYJ4AUl7VK7AV/xUEeoP9cvX1Qqcl2g0DjuVMyblAIIYQVmQQiKqU2JiEoT2/7+xZ/hPF6Vkk3b3kTK2pL2RnBzqYU6vQxtPAo/cD403dRdgJx49a1qLIznaFyE2qEEEI0OHU+ACwoKKCgoMDyWNM0fHx8LD/XFPO1a/Ie9ZFKumJnfFoCWmi4/RPTUshNvAwe3mjl5K2zG7CUupf6bmGpAtWxsX41ZecvGDt2s79fKdQXH2H08cXQtjNaSFhJsK7HYECLiKnU61ulJqMS403nNbDAUd7vziX16VxSn84l9WlS5wPAFStWsGzZMsvj1q1b88477xAeXk6w4URRUVG1cp/6otDDwBXNAMpYstFgILJbD9zDInXPyfp5JWnv/50kZQTNQPATL+J/69iSayZfpfDyRYx5OaQs+sDhoK4IjeNBrUnzDCQ4P4PO6bG40YADwoX/V/5+ZUR9MociNJo88gTGnGwy9epSMxD8+Iv4d7UfUJp/J+5Nm+MeFmn5HWLnd9hQyPvduaQ+nUvq07kae31qSrmuCeW+++6rcBawvRbApKQkCgsLa6xsmqYRFRVFQkICLqwilymvtce4dS3GLz60rI5hKGcMoEpNpui5aTZBnducBWghYaZrVSLoo11nOHOcXWE3MK/d3aR4B1l2heamM/3MKgYmH6nUc61tLg1cNQ3DC/8od+k6q9+JpqFNeNjU6lpmSTy3t+c1mJbAxv5+dzapT+eS+nSuhlKf7u7u1WoMq/MtgB4eHnh4eOjuq41fnFKqXr9AqqKiSR7akFFoMS0tq2NobTro1pHdlCZA0Rt/Qpv9kqm7tzL127I9u9LdmNN1ss2uFK8mzOk6mWePflFng0CXB679bsJ4eDdKKbSgEJs1kJWnt/XvRCnUsgW21zEaUYnxDW4Zusb4fq9JUp/OJfXpXI29Pms9AMzNzSUhIcHyODExkbi4OPz9/QkLaxitCfVN6ZQuQIWTPMoGiEZ7kw/Km52bkYZ66+lKl7XIP5B53R+AImyTKhdPCJnX7i76JR/Vb1Vr3xVOH630fZ1hV9gNrg9cd28GQP2wpHptjg7mHhRCCFE31XoAePbsWV5//XXL40WLFgEwbNgwZs+eXdvFafTKBnOMuqfcJdgqmgWsUpNRZ4/XWGqW45t3kNKzO9gbu6tppHgHczyoNTekn7Pd78zgb/RYWLvSoUOL0JjX7m7Tg6oErnWJweBQ7kEhhBB1V60HgF27dmXp0qW1fVuhQy8/HGtX2qZWKd3aU85SZMaj+2s8J1+aZ6BTj6sqbeazaG07YVz3vUPP93hQa6tuX9sL2gtcNahDAaF26zi0EXdJ8CeEEPWcrAXcSBm3rjV1wdpbscLcSlW2tSciRrcFy5iTUzPBX98hVg+D8zMcOs3R46rEYEBr2wktJAxt/FSHTql64Kqg72DQ6sZbVa373vpxajLqxGHTMAKdx/aOE0II4Vp1fhKIcL5y88OVYm7lsmntGXUPlG75Ugo+erNmWv72brNqkeycHktobjopXk1sA9HisoTmpdM5PbbUE9Gsg9rqlLNMQGwYM54iKFkGzo5qBa57t5v+7zsYBtyMVpCP+nROJQvuJMWtvQpQG1aZAkJz3fYaBAd2ljwePxVDq3YY485YLZMny9AJIYTrSQBYjj2X9/DJzk9Iyk4i3Decce3G0Sui/i9jp84erzgIUgotsIlV8FdukuYa7PbVRo9FrV0JSuGGYvqZVabJFKWDOlMhAJh+ZnXJODqDAe25OWgFeZa1dNXijywpbBgwHH7dZHpcYUE0tOfm2KRQcRszHtX/JtM4yfBo1O4tJSuVFKtS4FrW3u2wbwdMng03jYEtdpaOq0mahjH2NPzjJevtSsH+HdaPv1uITa3KMnRCCFEnSABoxx83/pFvT39rtW3e0XkMjh5M84DmXMu/RoxvDDuv7EShmNFtBpM6TnJRaWuG8vCyzLVQqcnlr9BRg7QRd6GNuAt19gRocGObTjyXkMdnRzJIKUkRSZivB9MMsQxMKZ7oUdxaVzpg04aORnXtbQnWtJAw1NiHTGMYY0+X35KnlCmQ1CtjSJhlWTWtOCA0bv0ZflgCYB24orCaxaJ0Ald7lKpcV/td96PFtICQiCrNuta7P6VXYqkKWYZOCCFcTgJAHQcSD9gEf2bbr2yHK7bb/7TlT/xt19+Y2nUqET4R5BblsvHiRsJ9wmkR2IJbWtxSa62HpdO6lG5lsWwP1V+xo6zSwY46e9zp5XSoDBMetjwHLaRkPOCNITCgUwzHkrJJyyki2MeNLuG+uBnaoYb2sgrwbK5ZKlgr/ditYzdT4Pb5e3DsoG1hKpH6RB3dbwn+zAYmH+HZY4uZ12syKfkl20Pz0pl+ZrV1CpjyuqsdDf4MBgxDRpek7zEndK4DSn+5EEIIUfskANSxO2F3lc5Ly09j7oG5uvvmHphLp6BONA9ozqCYQUT7RRN3LY48Y55Tg0O9JM5a194YN6wqSVmiaTBoBOzaWG4wYTx6ELfi9WfVr1ucUr5KmfAwhjHj7e52M2h0i/Sz2V42wKu044dst2maw6lP7I6x1AwMum0YAwd35OiGLaRu/oXgvGt0vnYet87dIKV4rGJxyyXgeGufzsztsuXVWrWrM/OJ7bWkCiGEqB0SAOroH2V/abrqOJF+ghPpJ1h3cZ3V9rkH5jI4ejB3tL6Dw8mHSclJISU3BW83b4Y2HcrEDhOJ8Y+x27Jnppuj74sPbTOdK2Ua9zblCfj8PfsF/ulbjL5+qNhTcOjXaj57HZbJGQa4aTRax+4QGmEZr+eSMWJ6aW4AbcYzGPoN0TmhEteY+TSG4lnN3UcNQ/Xpat0VnZps03KpuvZG/bIatfZ7yzq8Vuswg9U4R+XhVfJ/fi4qNbnkWp7elaiIKigbhNpjMKA8vODEYbuvZSGEEDVLAkAdvSJ6cW/7e+12A9eE7Ve2m7qXy9iRsIN39r1DjCGEpqm5XHc30jbHm5l9n6D36MeAkq5dlXnN9gPY3gey0Qg7f6mwXM7oMtQmPGwzKaLs5Iw6EwSY09yULWvbTtW/Rhvra9jrii57jDbxEdSIu0ommZSZyFJ6nKNGSSuwKjPrVsvPrdkWwClPwKL3Kw4CW7RDvfW0pSzalMcxDB1d4RccIYQQzqOperoQXlJSEgUFBRUfWEWapnHJeIn/7vovu6/s5lCKTregKyno1aQzvXKbkH/+DCmeBbTM9aJZvhfBhe70zfInusDT1aWE2S/j1rM/ats6jF98aB201NFUIMata20DrEqW1RnXKFdaCiFFeaS6eVmtx6tSkzE+P90m+DS89ZmpXGX3OZF233Tw9ql8PsjilDHlpYqp6eBQ0zSio6O5cuVKo14b1FmkPp1L6tO5Gkp9enh4EB4eXuXzpQWwHP2a9qPZjc1QShGfFU9cRhzXC67zc9zPZORnEOUbxZcnviTXmFv7hdPgQMZxDgDozUtQMDItkAcTwznum81PQWlc9srHzQg9s/158koMPbNtx89VWscb4KT99WsNPj6m/4eOJnLEGK7+dgjCo+p0C49BZ6awK65RHi0kDO/oaLSyf8DKWalF69gNbfzUmpsI0rYzhjYdMDZtVbkZx2VnFpdJFaM3rrWufnkQQoj6QgJAB8X4xxDjHwPAqJajLNv/OvivrDu/jo0XN9IysCWZ+ZlE+ESQU5TDpoubiMuI40LWhdovsAYbQjLYEJxhs27uep8M1odk0Drbi0653ngXGsh1N5KDkRTPAu5JDmVmUpRjtxn/MFpQCMZDu+Grj613lpk16x4WiaFTt3rxjavaE0mcdI1Ks9P9bP492E1c7ej4PXsGjbB0QxvadKj+jGOj0ZRGJzAYvv7EZu1pY9NWaPm50l0shBBVJF3AdjizifhA4gH2Xt1Lem46x1OPMyB6ADF+MXxw8AOOpNpvPXMZBW5GmJoYzpBrgfgqN7K1ImJ98uiX6V/ScjhoBG7TnrKcVl63Z0Npcq8ryqtPR7qfzRNOSk8aUW8/U+Ug0PDO/JLJJsXdtcZ9O2HTj1V7go5yUougvD6dS+rTuaQ+nauh1Gd1u4AlALSjtl4g5uCwVWAr4hNP89v57SSf2c9evyzSvIw2rXe1zpyzuFTuYn+86BLYgTZRXfEweJCcm0yrwFZ0D+tOH6+2xFw32nR7NpQ3XF1RUX3qzSiuSNnAkS694Mg+h841PP0mWsdu5a8WU1OKxzhWpyVQXp/OJfXpXFKfztVQ6lPGANZzvSJ60SuiV/E4p5+LW2A6AIqDvtf5LDKB4z7ZeBkN+BoNXHc34m6EQwG5tRMcamX+B7LIY3fGb+zO+E33lEjfSAZHD6Z9cHvyCvPoGdETP08/BvoNxA23mi+zqFL3s964ReOa5SUzuDUNOnW3zZOoGVAZ6ahzp1yzWoysLCKEEJUmAWANqcysRZv8fcUJMnpm+/FBbFvdc6545LM+KJ1z3rnkYyTFs5CWuV5c8SxgZVhaScBWZtWx2nA1+yrLzy7X3RfgHkCYTxhDmg6hc0hngr2D6RvZ1zK+UrhW2cDRUGadY8ukDHNLoaaBMqI+fdeFpTYlLdcy0gHQ2naWcYFCCFEBCQBrQKVnLdpJHFye6AJPJidF6O574ZIpOEzyKKB7lh8nSs0Cvm4wkueOy7qWMwszyczMJPZErNX2fhH9cDO4EeARgI+7D74evqbu5Zxkuod1tyTDFrXPJigsbilUZ0+gPp3jwpKV8tO3lP76pE14GK1VO5kkIoQQdkgA6GS6q3GUSmmhS2/mZjWUDQ5vyQji8YSS4Omg73V+CUonxa2AlOgQvMObkXtiPz8HXaPIgHVwWEstiHsS99jd99P5n3hn3zuMazuO0S1H0zeyL0dTjrLhwgZGthhpNStb1A4tJAwSAyuRWNo8kLR2qO8Wmu4maWOEEEKXBIDOVk4eNntjlLSQMBh4s/XKHM1aw6VY3ePL5UAg2TPbzzST15ykOTUZ4/9MCYI/DU/gu/AUAgoNdMvxY3BGE/xvmcBPAYksOLag8uVxohVnV7Di7AqrbV+c+IJm/s1448Y38PXw5VLmJVafW016XjodgzvyUOeHnLbOsihD74uLVvxtoewqKLfcjTKvRV2bipdDNDZtZUlTI4QQQgJA59P9UDQNkqfUuqylqdRk2LXReqMjwV+PfnCoVMuZppkS/ZbN8VaWuVWkp2nNYy0kDG3ybNQXHzIzKaokB+DosRhG3o0WEsZgYFaPWbx/4H12xO8g1CeUNk3aWGYBZxdks+nyporLXAMuZV3i4bUP22w/kHSAb059Q7BXMJ2CO9EuqB3X8q6RkZ/BgKgB0q1cTZbXTZmUM1rxRBJzihlzDkK17vsaW4WkXEqh3nqaogkP4zZmfMWHy5J0QohGQNLA2FGdaeJF8+fqr7Nbpjuq9Bq+lR5ErxlAGW22Gd7+zLRWbHnLcWkahrfn2Xy4qdRk1NkToIHWplOlP/zis+J5/8D77Lm6hy4hXWgX3I78onxWnV3F2YyzlbpWbekX2Y/uod05mHSQO9rcQZBXECvOrOCG0BuYdsO0Ohsg1qU0BhWlnLHkBYw7Y73ihwtoEx7GoBMEmuvz8tLPMS76oNzxuxIgVqwuvT4bAqlP52oo9Sl5AGtIVV8gumuxllacs0zt3mKdXqOSvwZt9FjdLjVLPrZzp8pdjst8XG1Zf2E9nx75lNMpp/H38GdI0yF0Cu3EqrOr2JWwq9bKUVmtAloR4BFAblEurQJbEeAZQFJOEuPajWNSx0kuK1d9+QNWdkIUQ0dDXi7s3uKa1kA7X340TSPcw8CVh+/UXUfZfLwsS+eY+vL6rC+kPp2rodSn5AGsIUVGxb4LaZy+dI1gHze6hPviZnBgNkRFM3qNRoyfvw/HDpRsq8oLsM8QKNulVnrJrzYdME55XL8lsMwSbbVhVMtRTBk4xeYNN7XLVA4kHuDL418SlxFHgGcAPm6mWcDrLqwjOTe5VstZVlxmnOXn09dOW37eGr+Vv/36N8a3HY+nuyeXMy+bupajBzCxvXQtg/6EKLb8bPp5wsNoYRGoT96lNieHoJRlPK5VS15oOIWXL5Y7frdKE7yEEKKOkgBQx84Lmfx331VSsgst20J93ZnRJ5JBLQLKP9mRGb2lg78q0gryQG/8lV66jl9Wo9Z+b+oy1jnO1czJsPWsO7+OH879QLhvOC38WxDsHUyfyD4cTTnK33b9zaVdy2l5acw7Ns9q26bLm3hn7zt0DOqIv4c/7YPbE+UbxdGUowyKGcQNYTfQOrB14wgQy/sytPxztLfnwYSptmsGl33/dOkJxw46p0yaBuHRtiuWTH0C9xFjyl1HuSoTvIQQoq6SALCMnRcyeXvrZZvtKdmFvL31Ms8PbWoVBJYdD2QzML4y3budusOJw44dGx6NoWM3m5UbytJCwtAmPoIacVellwarC0a1HKWb5iXGP4ZRLUdZLaXn5+HHxcyL/HDuBw4mHSQ1L9UFJTY5mX4SgH1JJUuprbu4zvLzna3uJDk3mdTsVHw8ffBy8+L+jve7tFvZ6cr7MqQU6pfVaDf0sW3/K3u8s4I/gKGjUempNiuWGD9/n6zcLJsZzVZflvSejwta04UQwhlkDGApRUbFjO/PWrX8lRXm686n97TFzaBRtGa51aB2bcrjVhM81NkTqBOHSrq9KvLgH+DL/1R8XD0ce+SKMRfmruVTaafwcvOiXXA7ruVeY+OljWQUZNRKGSrLz92P3hG9ySvKo01gGy5fv6w7IaW+jGExjZn7yHbCEoBmQHt+DurtZ1wzHtARt92L2/jJlodl10vWHppVr96HtaW+vD7rC6lP52oo9SmTQJzot6vXeXn9xQqPe+OW5nQ98LNu15V5gHnZ4NAhN/SBI/sqPg5sBqfXdXXtDbfu/DqWnlpKE88m+Lr7cjj5MLe1vo0TqSdYenqpq4una0jMEJr5NcPDzYOz6Wfx9PKkuU9zPN08adukLaNajqqTXcsqNRnjt/Ng73abfYan30QlXqlai3kt0SY8jNb/JktLP1AvW9NrU117v9d3Up/O1VDqUyaBOFFaTpFDx6UeOYr67nPbHUph3PozFBnhp28rXwB7wd/w22DTT9bbZOxRtdjrWgZ4pu8zLDiygB1XduBl8CKnKIfcwlzcDG4cTzteyyUtsS1+W7n7X9zxIjeE3MAdbe7Ay82Ln+J+wtvNmw7BHRjXbpzLEmJrIWEY7p2Ocd8O3e7T0kMZlIeX4y2CxS1wKulq1d5vDlLfLSz5sqdpMH4qhlbtaux+QghRGyQALCXYx82h44LWfIXdmYs/LHFegcD0ITdoJGrzGhl7VEti/GN4aeBLuvvis+KJy4jDx92Hw8mHOZd+Dk83Ty5nmWYBn0w7Sfz1+FoucYkjqUc4knrEatvW+K3MOzqPzsGd8XTzxGg0EuQdhJvBjQGRtZMQ227S6OIvMOb1hjXAWPo4ywUMMHQ0WufuEBJhSTCtju53SvBXhMbxoNakeQYSnJ9B5/RY3PTe40rBdwsxQr0ciiGEEGbSBVxKhWMAlSI0L52Pd72t/+HgbKXGGNX3sUcNpcndEevOr2PRsUVk5GXQPrg9kb6RLDi2gGv511xdNLvubHUnhaqQ1NxU8ory6B7Wnc4hnQn2DqZvZF+nBYgVJY0ue1zp1UT0EpeXm3PTQbvCbmBeu7tJ8Q6ybAvNTWf6mVUMTD5i/0Sod0Mxaktjer/XBqlP56pOfVaUCL42E8XLGEAnM80CvmRq4NNK5f0rrqZnj35R8YeCIwwG6DkQ9u/Q3a3dNx2tz2CrF5CjH551kfwBsx532D64PevOryMlJ4XswmwuXb/k6uKVq3NwZwI8A7h6/SrBXsH4evrSwr8FD3Vx3VrL6sRhjP98uVrX2BV2A3O6Fk/yqMT7vXSLYcjY++jap6tjeUIbCXm/O5fUp3NVtT4rSgRf24niJQCsATuOXeaznRfLtAikMf3MaqcFf+YWvKKDu+HDN7HqUm6ArQryB6x88VnxrD+/nsPJh7mUdYn8onxaB7Ym/no8V7OvWtLK1EUdgzpyW6vbuKXlLUT6RrL36l4Ap7Yc6qluC2ARGo8NfIEUrybWwZ/lBvot/rotho7mCW0k5P3uXFKfzlWV+jSeO2U7PrnUZ7Xu3yM7Kw85i0wCqQE3dmlKvyNrObbnUMVjgipD09BmPIPWtmSdXbee/TFOKT+hs2j4YvxjmNJ1it39BxIPsPLsSq7nX8fDUDwL2NuT5t7Nib0Wy9YrW2uxtNZOpp/k5MGTzD0412Zfx+COoCC/KB9/D3+CvILw9/JnUodJdifhOMreuEKg/LWwix0Pam0VxNneQCPFO5jjQa25If0cUKbFsJSU7ALdPKFCiPrPJnG8ZUeplYLOHrf9m6MU6uwJtJAhtVPQSnJZALhmzRpWr15Neno6LVu2ZNq0abRrV3dm1nmMupsb1q90XkoKc3NwP9sXgnnFjvravStqXtnVUsp+g43PimfZ6WX8lvwb3cK64eXmxRfHvyA2I9aFpYaTafotlz/F/YS/uz+ze8wm0i+StefX4unmycCogZVKZ6P33lGpyQ59q0/zDHToHubjitCYd4M5UXfZFkPT48/2XaV/M3/pDhaigbAsAanHYEB5eMGJw6jEK/rnX8+swdJVj0sCwB07drBo0SJmzJhB+/bt+fHHH3nzzTeZO3cuTZo0cUWRbGghYQQ/8RJp77/plCBQm/GMbvBX+n6S0kVUVYx/DE/2etJq26PdH7V0LSfmJKKUYtOlTZZZwKfSTpGQk+CiEkNWYRbv7HvHatuqc6t4cceL9IvoR1xGHOE+4XQP746HwYOLWReJ8o3ioc7W4w7LvnfU2YpS9Wjw4GOENO0BuytOCB6cbzrmeFBrUvAq99jk7EKOJWXTLdLPZl9tDg4XQjiH8dBu/RhA02DAcNTbz5T7hVPzq7s9Ai4JAH/44QdGjhzJzTffDMCMGTPYv38/GzduZOzYsa4oki7/W8eS0awtRT984/hqHnoMBrS2nZxXMCEcVLZr+Zl+z1jtNy+lZ1RG9l7dS3JOMvlF+WQUZHDu2rnaLq7FnsQ9ACTlJnEs7ZjVvm9OfUO7Ju0YFD2I7MJsBscM5nT6aY4kH2Fcu3HcSzmth6XG33Y1KkKPZFc4679zuqkV1eEWQ518orU9OFwIUX1F8+fCzl/0d97zIHz/ZfkNRJpWpz/7az0ALCws5Ny5c1aBnsFgoFu3bpw6daq2i+MQQ7+hqMGjUDs32CZk1mMeUK6UjOkTdVrpruVHedRq34HEA3x54ksuXLuAn4cf6fnpJF5PpNBYyKVs185aPnPtDGeunQHguzPfWbZvjd/KG55BjGrpxtaAa6R4FNKk0I3xqaFMG/UaMZ1LZta7GTSm+15hzvXi96bOLODpZ1Zbxv6aWwIrUjafqKULyfxBoRRq8Ueorr0tXdbSMihE3WI8d8p+8AewcnH5Fyj+oleX39O1HgBmZGSYuqCCgqy2BwUFER9vm0C3oKDAaravpmn4+PhYfq4pmqaR9fNKisxdwJoGw+8o/5zb70Pr0hMtwpSgWSVeQYuQMX1Q8ruqyd9ZY1Ib9dk7sje9I3vr7ovPimfd+XWcu3YODzcPvAxe3NLyFj469BE/xv5YY2VyRGp+OksiSx4nehTxcdNEPj42i/H54+kX2Y9g72C8s/M5sPPv9PBsyZmI6Vz3aWs5JzQv3WbWf+f0WEJz0yucNdxx3S9wx6SS8Yj7ttu2EhiNkJSAOnYA46IPLH9jDKXWE6/P5P3uXFKfzlW2PlVqMioxHq30l7AKh5JUcI+Zz+JWzrCvuqDW08Ckpqby2GOP8cYbb9ChQwfL9sWLF3Ps2DH+/ve/Wx2/dOlSli1bZnncunVr3nnHetxQTShMvsqVh+/SX8ReR5NHniRwov1ZnEI0Fnsu72H7xe0YlZENZzdwIeMC+YX55BbmciHzgquLp0/BwMxomhiD8G7ejGvnfyWgyEDTfC+8lMbI9CB6ZvtVIm+ghu/I28n+5Sf9vyEGAxH/XEDinx6x3m8wEL1gNe5hkbbnCCGcqjD5Kpnff0PWisXFX8IMBD/xIv63jiXv1FES/9/Uql1Y04he+EOdfx/XegtgYGAgBoOB9PR0q+3p6ek2rYIA48aN484777Q8NkfsSUlJFBbaGbvjBOrkb44Ff5qG4YV/cL1NB65f0Z8FJEy/t6ioKBISEiSPlRPU5fpsZmjGpJam2bIPtHrAap95tvLmi5sxaAaGNh1KpF8k686v43LWZQ4lH3JFkUGDXYFXgCuQeRxCrHf/X9MEWuV6cF+7TsQkvMXuogJwa0Eh12jiNoB2hZ3KtBgqsjfYaQk1GDBMnk3y5Uu2f2OMRq7+dghDp27Ofoa1qi6/PusjqU/n0jQN/0O7SHvvDesdykjaB38no1lbU0tg115w9EBlL4424WGu/nbQukWxBri7u9evPIDu7u60adOGI0eO0L9/fwCMRiNHjhxhzJgxNsd7eHjg4eGhe60afSOER2NK7VD2Hprpm78qlbOvdXt5UzpIKSV15UT1rT6j/aJ5oucTPNHzCavt93W4DyhZa/m7U9/xy8VfCPMJo0d4D2IzYtmVsMsVRTbRIM6ngDmXvyzZVmjanly4mmv5bngGBPKdn0a3bD+8iwwc8r/OzelNuCUjqOScu+6HgCCUlzcqJ0f3VsrDs179TstT316fdZ3Up2McWa4t7f03bbYXoXE8sBXp+88ScoM3HQuNuNkcVY4Bw6BZa9R3C02/pzo+4csls4DvvPNOPvzwQ9q0aUO7du343//+R15eHsOHD3dFcXRpIWH4j3vQ1DRsRaHNfAYtoInk7BPCyWL8Y4jxj+HGmBtt9sVnxbPv6j5iM2JJyUkhryiPnMIcboy5kU8Of1L7q6VoJf8nexWxOjwNgCWkFi8lCV9EJuNTpNEi15M8jASfPEarPG80De5MDeEWgmwvW5BXa09BiPpML9BzZMa9OmObtNlqhZ8EIOEiocF3MD2syPEVwH7dDLu32J3wVde4JAC88cYbycjIYOnSpaSnp9OqVStefPFF3S5gVwoY+wBZK8tM8zYY0Np0qpO/TCEaMnNwqGdSx0mWlDaBnoHsSdjDlktbSM5JxsPNg6zCrNotbKngMMddcdLfFNTFUcABTC1/y8PTiM51p2u2LxluhdyXHM7QzEDWX9tC0p413NLyFqt8hzJbWIgSeoGe1rW3QzPujWWSM9td4cerCXO6Tra7Jrgu3QlfV+pknl9ZC9gO80oLl5d+jvGLD62Wmqqrzbl1maxl6VxSn5Vjbj1MzUtFU5ppFrC7N1+e+JL1F9ajqrvMozOYi1BqbknXkK4MjB5I6NU01P6dpHgU0ibXm9G3PEXTEfe7pJiOkNenc0l9WtNdd9dgQPv9n1GfvmtzvHbfdCgqQi3/vCSrR/G5VV0T3K5S1zaXy7xesLPJWsA1zDB0NHTpJcu0CVGP2Ws9HNVylCk4TNxHqjGV2KRY8grzuJR1iQCPAE6knai9rmWdz56jqUc5mnrU9KBFyfaXz/yZJ9yP8/xNr7Pu/DreP/A+CdcT6BLahT/2/iO9InpJi6FouBLj9VvaLGP0rfeppfOsjy21vyprgpdHGz8VtWKRVaNRXX3/SQDoAFmmTYiGK8Y/hqYBTe22sOw/vYmVXz/FdYORFnmeZLoV8WvgdfYHXLd/0eIxgDVGg/dPfsYXsctIz0+3bL6cfZl1F9fRwSMGv6Q0jAYYdq0JTXoPo22v2/D18KV1YGuH11oWok6KiNFtadPadoLJs1GLPyoOCCtW2TXBK6K1bo/21mf1otFIAkAhhChH7/bD6XnznJIPFYMBbeQsEnrdQFxGHNcLrrNt+0IS4w7hazTNAv4k6ioXvPNrNggEq+CvtFMF8ZjnlxwKyIGkJbB2iWV/E48mhHiH0C2sG+Pbj5fAUNQrWkgYWulAr1RLmzZ0NKprb4zfzoe92yq8lsMr/JQ9btgY2LzGepvBUBL01eHAz0wCQCGEqICh+EOl9Lf6GLAETKNajjJ1uSZdwXj0IJN/+pb1gel8EZFIsnsBBQZFLkZCCt1RmsaBwGzb4FBnDKBT6FzvWsE1rhVcIzYzllWxq4oP0xjZfCTtg9pzOesymQWZ9I/sz9BmQ8kuzJYAUdQpeu9JKw4Ef+D4Cj/mNcFNNzdguP0+jGFRYB5XWMe7e/VIACiEEA6o6Fu9FhJmiuHWvAzALRlB1jkAS7nikc8+/yzivHLZ73edTLdC7i2eBfxWs0usDEur8dbDshSK9RfXs/7iesu2jZc28s6+kpWXOgR1wNfdF4DsgmzCfMKY2X0mo1qOqt3CikbNeO4UnDkG7bpg6FiSNN0yy3fbOoev5YZi+plVplnA5gkilgvargmOplkCPbcx41H9b6oX3b16JAAUQghn0RucriO6wJM700J0970X24YXLpUEiCkehYQWmP5Ur2gHp/NLVhwK8QohNS/VOWV3wKn0U9aPr51iR8IOWvi3YFTLUbRt0pYY/xgOJR0iOT+Z/fH7CfQK5NHuj0qQKJyiaP5c2PlLyeNBI3Cb9pR1WphKGph8hGePflGSB7CYzZrgfYdguHeaVaBXX7p79UgAKIQQzqI3ON0RmgZDRsPWnwH7AeLjCXDQtwl7A7Lom+VPrwnPsT4okw+P/IczufGkF15zxrOotAtZF5h3dJ7d/TsTdloFid3Du7P10lbOpJ/hrrZ3SXAoHGI8d8oq+ANg5y8U9b4Rqhj8mQ1MPkK/5KMcD2pNmmcgwfkZdE6PtWr5Kxv81XcSAAohhJPoDU7n1gmwZlmZDyedZSYjoh26R89sP3pm+wGgvviQkcBI5Qu048o993CgcwSHkg+x+8pujBgZ1nQYQd5BfHjwQ5Jyk5zxNKvEXpD43dnviPCOYEL7CaTlpeHn4UdT/6bEXotlZIuREhwKwNS9q3Zs0N+55ttqBX8mGm4o61QvmmZ6m9bD8X2OkETQdkjiTeeS+nQuqU/ncnZ9mieEmMcFGbeutZ6xOG5KSVJaM3vbK+u2ezF06YHy9EbLz7XKA7jk5BLm/TaP1NxUfNx96BbWjXHtx7Hg6AI2X95czWddMwI8AugT2YeeYT25mHURpRQ5RTl0D+3OxA4TG8XElIb6fnc0V2V1uncdp6HNfAZCI0zLMYYXfyGrw+P7qpsIWgJAOxrqG85VpD6dS+rTuWqjPksHhSTGY/znyzbHGJ5+E8KjMf64BLb87Jwb21sPtcyH7/61H7Nhx2fkUcRlz3yyWjanf+c7WHh8IQnZCc4pSw0Y13YcHYI6kJybTFpuGpeyLtEnog/TbpjWYILDhvh+d2TNXrCz6kdNGT0Wt3un1fx9nERWAhFCiHqg9GBxBbqJbC2tDlvXOu/GSqG++NBqQfqiNcvhu4XFBdNg/FR6LP+JHqpUwHTegOG2B3ii9xMsObmElWdWYtAMpOelA5BTkEOhKuRsxlnnlbUKVpxdYbNt99Xd/Oe3/xDmFcasnrPwdvPmcNJh0KB7WHdGtRzVYILDusxeC59KTbZds/eLDzF6+6C17Wzd2ubgxCq7NA1t9FhUu67w4RvlH7vue9TIu+tka19NkABQCCFqWXmJbNWJw9X6wCtCsx3IrhTq7Am0kCEYSwd/YLqXXrdzqUXs7wsfyX2qs25XXXxWPOsurONc+jnaNmlLtH80h5JLZgHnFOZwLqPiJbRqQnJeMn/99a9W27459Q0v7niRkc1GYsRITmEOvSJ6EegRSF5RHre0vIVeEb1cUt6GpNwWPr2gTinUp++iyhyrPL2rNrHK7I77wMun4uCvuAzm13xjIAGgEEK4gN1Etnozie19ALbqAHElqVl2hd1gm8oiN53pZ1YxMOkKxnOnUKWDPzNz/jOdFsmKuupi/GOY2mWq1eVGtxpt1WUZnxXP+vPrOXvtLG2C2tA9rDsfHPyANefLrKRQizZcKplQsCthl+XnuQfn4uvmS6h3KH7ufgT7BBPtF20adxjWnYntG8e4w+ownjuFWvRByQalUIs/Mr3eAZVZzmz1Useqo/urP/bvhyVlp1vZV7oVvhGQMYB2NMQxF64k9elcUp/OVdfqs+ykETp1h2MHbY7THn0W9ckcwBT8zek6uXiHbTLbZ49+UZLPzOZCmv4i9l17246/MhgwvPVZud1kjtanJTDMOIuHwYP03HT8PPyI8Y/hP4f+49JZy+UZEjOE8e3Gk56XTpBXEBcyLhDhG1FjXct17fVZnnInbIweC+u+t064bOf5aI8+i/r03doZ+weW17zeOMS6SsYACiFEA1O6dVB5eKHefsb2IE2DkAjA1O07r93dJdvLHqcU89rdRb/koyV5zUobPxWt/00QGl5y3ZSrGLf+rNs1bNz6M1pMC9vxWpUU4x/DlK5TdPc92v1R1p1fx6Jji1AoeoT14FLWJXYn7OZC1oUq39MZtsVvY1u87VJjL+54kZf7v4yvuy9nr52lbZO2jWq8oc3YvtI0A6xdWepgBWgwbjKsXKzbJVzjwZ/BAOOmYGjdvs7O9K1JEgAKIUQdZJk0cuKwfqvPqHvQ8nNRwPGg1lbdvrYX00jxDuZ4UGvrPGcAt9+L5ueP8blKzH4s7lZTaGhT9GdvOsOolqN08wAeSDzAhgsb8DJ4EegdSEZuBsm5yey7uo8DyQdqpCyOemO39VizF3e8yJM9nyTIK4g2TdpwPOU4Wy9vJa8oj6Z+TWka2BQvNy9uadEAxh7am7ChaWij7kaVDgABUKbgb+DNNgme1eY11Rv7Z4/BgDZ+KmF9BpDq5gXBoc69fj0iAaAQQtRlumMCDRhG3m15mOYZ6NCldI/737eOj5GyUTLDGCiZ8Rla9W4pR/SK6GU3WIrPiuet3W+x5dIWAj0DeajLQ3i7e/Nb0m+svbCWlNyUGi2bnvcOvqe7fV/SPsvPcw/M5YaQG5jdczbNA5pzMfMicdfiyDPmMarlKKKj68bYNPPMXr08k/ZWwtGefxctKARl7v61uqCyXd0D4ORvENMSrlyofhBYPNPd3NJnCA3HOzoarR50qdckCQCFEKIOK3fGcGoyAMH5GQ5dy9HjdIVHQZJOPkClTHkLt64tGds15XG4b6rtsbUgxj+G90e8b3f/uvPr2HhxI8FewRxOPmyZBbzl0haOpNoZI1lLjqQe4Q+//MFm+9wDc+m0tRP9w/tzvfA6g2MG4+PuA0DfyL611sVcdnyfOZ2RNnk2Wtfepi8At02E/31bcpKmweU407F9boS92x2/Yfx5GD0O1tqm+rG45W7IvAa/2klkrmloz7+LoU0Hx+/bSMgkEDvq06Db+kDq07mkPp2rPtRn2dVFANSJwxj/+TJFaDw28AVSvJrYjgEEUIrQvHQ+3vW2/hhAZzMYiF6wmqQCY52tTz0HEg/w6W+fcjjpMEajET8P0yzgS5mXXD7usDxjWo6hdZPWbL20lYz8DPpG9mVUy1FODQ7LTchcE121DtJmPouh3xDL+0PFnraZzFR2iEJ9eL87QiaBCCFEI1A6kbRFhOnD3Q3F9DOrTLOAS8+wBMsH8/Qzq2sn+AMwGsk7fhhjobFeDa7vFdGL/4z8j+6+A4kHWHl2JUnXkwj3C6dLSBcy8jP44dwP7E3cW8sltVY2nc6FrAssP7scgH6R/ZjdYzY5hTnEXYvjfOZ5/Dz8GNduXKXGHKqzx+0Hea4KojQNrW0n04/F7w+tYzdU/5vq9BJudYW0ANrRUL4h1BVSn84l9elc9bU+jVvXWuVb088DmMb0M6vtp4CpgG5i6dKBZIu2cEFnNRBzq1AFy3zZHU9WjxxIPMDeq3vpG9mXSN9I1p9fz7lr52jTpA3b4rfxY9yPri6irhHNR3Bv+3sB8HH34WDSQbwMXrR0C6Ev0cQ072Fay3rNcv38kS5V9QlI9fX9XpasBVxDGsoLpK6Q+nQuqU/nqo/1aa9Lzvj8uxw3BpB24RJBa76yDdgqMnYyZKZDagq7LmbYTyxdmYBSJ3egbr64coLF+swcILYKbMWJlBOWWcBXc65yMeuiq4unT8G9iSE8HXoPy+J/ZmvgNfI1Rftcbx5MiqBntp9ry3fbvbiNn1ylU+vj+12PdAELIURjZCflhnthPt07xkD7GIye6cWTRxz8kDMYwM0NfvmBXaFdSxJLl5Li1YQ5XSeXn1i6rFLLykE5+eJKrQJRH1sC7Sk9a3lUy1E80fsJy74DiQf4/sz3ZBVk0SKwBa0DW9MsoBmXMi+x8uxK162WosG3Eal8ywJoUbJ5f5NslkSkEp7vRvNcT5SCZgVeFKC47JPHPUmhzEyKqvnyrVmGGn5bg3qd1DYJAIUQoj7SS7lRZimrsgmlSU20rBxiw2BAGzcFtfxzihTVSyytQ8WeRuvYzfTAXr44sAkWLecXdxfrdROXt6+ynHktR9hLadMrohd3tb2L+Kx4NlzYwNXCq6RcSyG7MJsbY25k6amlVkvY1Qid+UTm7UleRSR55QBwgBzLrt/8LvN288u0zfUmy62Qztm+jEkL5ppHEf0y/Z3XctjI1u2tCRIACiFEPVReepiyxxEShgao4sTRNte6bzpan8Gm8XhKcTyoTdUTS9uhvluIMTQcrW1nu/niAN31WMtbj1hvnyUlSSWDuKI1y8E81q2OdEebV0sp22U5qeMkS0Jsz9RUru1Ywzb/a2R4FJFhKCLdy1gSwBUvulErNCh0h5P+uQBc9slgfUiG6f4KOmR7cVtaMBlaEVuCruFTZGBIZhO6ZfvSN8uf6ALPMtezs2ScpjWqdXtrggSAQghRT5Vu4XNoxqOdVkOtz2BTXkEATateYulyqE/fRZmDtPFTUcs/ty3LQ7NMx544jPL0hpSr1t3FSqG++Aijtw+ERurs+9D0POxMQLHXwmcsHfyVupbR26fCJe9qutVQpSaTm3gZ5W69ckVP9+b09B+NCvFGfXsEaGbZtz4wnWXhyQQWujE6LZhcNyNxXrlsbJLB3ibZqLJfBWoySNRK/j/ll8cpvwSr+x0JzLWUoV22F32y/OmW7cuojBAS776b3dmn6LfpED2vF7ceml9D0vpXLTIJxI6GMki0rpD6dC6pT+dqTPVp3LrWptWwdIBk3LqW31av4S89ZlZ4rb8e/NjhFkCHTHgYzc/f/nqyVaEZMLxtmoBiryWx3Bx3YDp2/FS0Vu1sA8dyWicrw25gWnayzOixGEbejTq6v2r1pGkkTH2EuDAvfIOjuJR5CZWVidcXH3PY7zoLIq5yzUNZWuxM51T66dSICLcgmnmEkUAmEX7RhPuGU6AKGBA5gIkdJjqc87ChvN9lFnANaSgvkLpC6tO5pD6dq7HVp15S6dIKU5KYuSGZlAI7n/w1lVhaM4AyOu96ZsVBk02QVzw7mcR4jP982cEyVhA4ahrajKcrbDUsrcqBqaMsrb6loroyQa06ut/yxWBpaArrOngzqvlIhq7YwnehKWwJvMZhv2yy3VWdCQjLGtNyDD3CenA87ThJ2Um0DGzJQ50fshlj2VDe7zILWAghRKXoJpUuxT00nBkDvXl762XbnTWZWLqqwV9FK1Gs+x5jWJTtMeYJJ+WNSbQpY8lMZd3JLEpZdXVX1BpoPHfKthu7vOtXlqbBrJfgtz2w5Wfrcn63sGQ5t/FT0X7/Z9A0JoVEcH9+LsZ1K6HAk8cTonk8wTTebn1gOt+GJ5OlFZLtZrTMAj7rlcvRgFz94LCWxiCuOb/Gatb0zoSdfHPqGyJ9IxndYjQFxgJSclIoVIV0iuqEd5E3I1uMrFRC7IZEAkAhhBA2BrUI4PmhTfnvvqukZBdatod5wjSvSwxMPWbaoBlg6Cho3ga++tglq0Joz78L+7ej1q7Uv79SprKVVTzhxDKhxtEu1eLAUXl62z+meKxieSltyibyrtT1HaUUfPRm+c+rOBi02mTn0FsygrglI0h33xWPfNYHpfOrfyYnfXLJciukS7Yvae5F7A287rKWw6vZV/nixBdW2zZe2gjAvw/8m0CPQNo0aUObJm3IzM/kcuZl2oW0Y2a3mQ06OJQAUAghhK5BLQLo38yfY0nZpOUUEezjRpdwX9wMnVFDe2HcsArWrjS1LGkaDLwZft1kCmCcSdMgsikkXLJ7iN3gr5xrarfcXeYilciXGB6NlhhffhuoMlKwfhUnh00iLaeIoIIsOqedxXA907RfLyitzPUdVUtBeXSBF5OTIpicFGGz79Cs3/NL0Slyi3LxdvMmIy+DzZc24+vuS1xGHBmFGbVSRj0ZBRkcTD7IweSDlm3H0o+x6twqIrwj8HH3IdgrGF9PX8K8whgYM5BRLUc5bZ1lV5EAUAghhF1uBo1ukXZyt637vuRnpeDXTWjPzUEryCfYz4eUfbvhx2+qH4AoVX7wt3tz5e+hFGrtStS672H8VOsZwBUwp9sxd5/au/eusBuYl9mFlPUlq32E5now/cw2+0m0Nc1y/aLdWxx/Pq6maWjPv4tWkGeaUX1kX8m+QSPo3etuepdz+pKTS1hycgleBi+aBjSle1h3bml5C1ezrzL5p8mk5afV+FPQk5ibCMD5rPOWbaviVvHijhcZ03IMngZPMgsy6RTcie7h3fFx9+HctXP0j+pf51sPa3USyPLly9m/fz9xcXG4u7uzcOHCKl9LJoHUL1KfziX16VxSn5WnThzWnThhePpNDJ26W+qzaMvPJbOOG4ob+uL2x78ApvQxNulsMAV/lpVUSifTLj7O7koq9zyE1qWnKf3Np+/WROlNWrSFS7GO/16KE4Xj5oZaOs9mt3brOAwTH7E8Np47BWePQ9vOGNp0qHZxl5xcYloxJT+LKzlXiPCOIN+Yz7G0Y9W+dk25o9UdfDrq0xq7fr2aBFJYWMjAgQPp0KEDv/zyS23eWgghhDM5sBIJWOcqNObkwIdv1HJBa8CRvRQt/wItPNI6+Lv5Dtj4I0VoVV9J5fvFqO8XO1aOsQ/BSgePLeviOdPkkLRk+13RAN36Yrh1nGWspEpNRn0733bm84i7rE4ztOkATgj8zCZ1nMSkjpNstsdnxbP+/HrOZpwlzMs01vJY2jF2xO8gOTfZafevih/jfuSdPe/wXL/nXFoOe2o1ALzvvvsA2LRpU23eVgghhJM5uhKJ+VhCwnADiiY8XKnu1jrrp29RVsnygI0/Qu8bOX7uqtNXUtHlGwBly+AopUzBeNkAtayj+6HU77Uyv/faYF4pRc+BxAN8efxLrmZfpZl/M8ss4AJVwM4rO8ktyq3x8r1/8H0md55cJ8cL1vkxgAUFBVZdvZqm4ePjY/m5ppivXZP3aEykPp1L6tO5pD6rxu2mW1E39EElXkGLKMkpWF59ut82gSJNM806dWF3exEax4Nak+YZSHB+Bp3TY6uQ1kbn+P07SIvo6dDZlV1JxYqmwVf/qfr5ZhX9DoxGSEpACy3parT3e69rekf2pnek7chDTdOIiori9Z9fZ8nJJWhoeLl70TawLZkFmRxKPkRCdoJTyqBQnM88T9OApk65njO5JBH0pk2bWLhwoUNjAJcuXcqyZcssj1u3bs0777xTg6UTQghR0wqTr1IYf5Gi9DRS33mhcicbDHh170vewd1VuveusBuY1+5uq1a60Nx0pp9ZZX9yRiUcCWrDX3o+VuFxTl9JxRl0uvWjF6zGPSzSdWVygUsZl/jh5A8sP7Gc2NRYQr1D8fP2IyMvg71X9jp8HTfNjbin4mgW2Kzig2tZtVsAv/zyS77//vtyj/n3v/9N06ZVi37HjRvHnXfeaXls/kaZlJREYWGhvdOqzfwNISEhQQaFO4HUp3NJfTqX1KdzOVyf4U1Rbl62QUdFSZlbd6hk8FfSTWo1OaOUFK8mzOk62f7kjEronB5LaG46KV5N9LtYi1dS6ZweW637VKjfUNzunYY6uh/jog8qbu0zGErWaC7u3jVMnk1SgRGuXKnZstYiR16fbrhxT7N7uKfZPTb74rPi2Xd1H7EZsRxPOW6ZBZxZkMni44st6yxraLwz9B3crrtx5brz68/d3d21k0Duuusuhg8fXu4xkZFV/+bg4eGBh4eH7r7a+EOtlJIPBCeS+nQuqU/nkvp0LofqMzjUdkzZuCk2iYmtnD1R2ZIAVG9yhqM0DTelmH5mlSnQLF7eraQoFayk0r0fHN5j//qO1I/Z3m2oiY+gDRmFoUsv1C+rbfMlmoPtUutCq35DrZYKbKjviaq+36P9ormzzZ26+57s+ST7rppS4PSJ7EOMf0ydrb9qB4CBgYEEBlZjHIMQQohGrfRMYXPQUZSZbkoy7agBw+DXzeUecjyodc1Nzhj7EIZBIyxr6g5MPsKzxxYzr/sDpBSVfNSG5l0rt6tZu2MS6re9tq11moY281m0Nh1RR/fj0OQPpUx1GhJmmrwx8RHUiLtQZ0+ABlqbTqbjyqwLXdFSgcK+GP+YOjnhQ0+tTgJJTk4mKyuL5ORkjEYjcXFxAERFReHt7YQlb4QQQtRLZYMOw8i7Ma773rGJIgYDhvFTTcHNW0/bPczRSRdVmZxhaNfZFGSVCmZvDI9mYFCo1UoqHdduwK2cLmatIA9G3WNqqStNKbSAJqYfv/gQh2b+6qTl0ULC0EKGWB8nwV6jVKsB4JIlS9i8ueQb2rPPPgvAq6++SteuXWuzKEIIIeowm3QjZgYDDBhesuRc6TQkFSydFpzv2HJjjh5nVaZSgVbpYNYNLCupGLeuRW1dW+F1tJF32waABgNaRDTq6mXdoFib+SzkZteZ9Cyi7qvVAHD27NnMnj27Nm8phBCinirdNaw8vEytY+ZxaWMfsum61E1OrWmABspYM5MzSi3dZnWp1GRIjIeImJIEyl98aL9Fs0zApk153CqYC378RTLN4/F0ZupqbTuZ7lOmK10Ie+p8HkAhhBCNl7k1rWy4pjdOzW6S4uKgyBAeze8T8njngE4LX0WTM3QLZ1r/tuxSZ8ata0uCPU1DmzwbLTxKP/j73WMYYprbBGylg18tIgb/rt3IvHKlwkTMMn5POEoCQCGEEA2G3oQSwBIU3RgCz/sH8t99V0nJLkklFuYJ028IZEB+BDiygph51myZ4M+mpU8pU7D23BzdljtDj/52W+oswW+Z1kq7z1GISpAAUAghRINSUSvYoBYB9G/mbzU5o0u4L24GDbo8hXH47aaZuD8usV3z9vl3rbqibSTG27b0GY2mc5y4hJq09InqkgBQCCFEo+Nm0CyTM8oytOkAbTpgDAmzCdjKtvjZ0BuHWDy5w9Cxm7TciTpDAkAhhBBCR1W6WmWMnqgvJAAUQggh7KhKwCZj9ER9IAGgEEII4WTS0ifqOoOrCyCEEEIIIWqXBIBCCCGEEI2MBIBCCCGEEI2MBIBCCCGEEI2MBIBCCCGEEI2MBIBCCCGEEI2MBIBCCCGEEI2MBIBCCCGEEI2MBIBCCCGEEI2MBIBCCCGEEI2MBIBCCCGEEI2MBIBCCCGEEI2MBIBCCCGEEI2MBIBCCCGEEI2MBIBCCCGEEI2MBIBCCCGEEI2MBIBCCCGEEI2MBIBCCCGEEI2MBIBCCCGEEI2MBIBCCCGEEI2MBIBCCCGEEI2MBIBCCCGEEI2MBIBCCCGEEI2MBIBCCCGEEI2Me23eLDExke+++44jR46Qnp5OSEgIQ4cOZfz48bi712pRhBBCCCEarVqNuuLj41FKMXPmTKKiorh48SKffPIJubm5TJkypTaLIoQQQgjRaNVqANizZ0969uxpeRwZGUl8fDxr166VAFAIIYQQopa4fAxgdnY2/v7+ri6GEEIIIUSj4dKBdwkJCfz0009MnjzZ7jEFBQUUFBRYHmuaho+PT42PGdQ0DQAPDw+UUjV6r8ZA6tO5pD6dS+rTuaQ+nUvq07kaSn1WNw7SlBOe/Zdffsn3339f7jH//ve/adq0qeVxamoqr776Kl27duWxxx6ze97SpUtZtmyZ5fHgwYP54x//WN0iCyGEEEI0Wk4JADMyMsjMzCz3mMjISEu0mpqayuuvv0779u2ZNWsWBoP9nuiyLYBgito9PDyqW+xy5eTk8Nprr/Haa6/h4+NTo/dqDKQ+nUvq07mkPp1L6tO5pD6dS+rTxCn9qIGBgQQGBjp0rDn4a926dYXBH9ROsKdHKUVsbGy9bh6uS6Q+nUvq07mkPp1L6tO5pD6dS+rTpFbHAKampvLaa68RHh7OlClTyMjIsOwLCgqqzaIIIYQQQjRatRoAHj58mISEBBISEmzG/S1durQ2iyKEEEII0WjVagA4fPhwhg8fXpu3rDIPDw8mTpzoku7nhkjq07mkPp1L6tO5pD6dS+rTuaQ+TZwyCUQIIYQQQtQfLk8ELYQQQgghapcEgEIIIYQQjYwEgEIIIYQQjYwEgEIIIYQQjYxL1wKuy9asWcPq1atJT0+nZcuWTJs2jXbt2rm6WPXOsWPHWLVqFbGxsaSlpfH000/Tv39/Vxer3lqxYgW7d+/m8uXLeHp60qFDBx566CFiYmJcXbR6ae3ataxdu5akpCQAmjVrxsSJE+nVq5eLS1b/rVy5kq+++orbb7+dhx9+2NXFqZfKLoUKEBMTw9y5c11ToAYgNTWVxYsXc/DgQfLy8oiKimLWrFm0bdvW1UWrdRIA6tixYweLFi1ixowZtG/fnh9//JE333yTuXPn0qRJE1cXr17Jy8ujVatWjBgxgn/84x+uLk69d+zYMW699Vbatm1LUVERX3/9NW+88Qb/+te/8Pb2dnXx6p2QkBB+97vfER0djVKKzZs3M2fOHObMmUPz5s1dXbx668yZM6xbt46WLVu6uij1XvPmzXnllVcsjytaPUvYl5WVxSuvvELXrl158cUXCQwM5MqVK/j5+bm6aC4hAaCOH374gZEjR3LzzTcDMGPGDPbv38/GjRsZO3asawtXz/Tq1UtaU5zopZdesno8e/Zsfv/733Pu3Dm6dOniolLVX3379rV6/MADD7B27VpOnz4tAWAV5ebm8v777/Poo4+yfPlyVxen3jMYDLJSlpN8//33hIaGMmvWLMu2iIgIF5bItSQALKOwsJBz585ZBXoGg4Fu3bpx6tQp1xVMCB3Z2dkA+Pv7u7gk9Z/RaGTnzp3k5eXRoUMHVxen3vrss8/o1asX3bt3lwDQCRISEnj00Ufx8PCgQ4cO/O53vyMsLMzVxaqX9u7dS48ePfjXv/7FsWPHCAkJYfTo0dxyyy2uLppLSABYRkZGBkaj0eYbV1BQEPHx8a4plBA6jEYjCxcupGPHjrRo0cLVxam3Lly4wEsvvURBQQHe3t48/fTTNGvWzNXFqpe2b99ObGwsb731lquL0iC0b9+eWbNmERMTQ1paGsuWLeMvf/kL//znP/Hx8XF18eqdxMRE1q1bxx133MG4ceM4e/YsCxYswN3dvd6sUuZMEgAKUU/NmzePixcv8te//tXVRanXYmJiePfdd8nOzmbXrl18+OGHvP766xIEVlJycjILFy7k5ZdfxtPT09XFaRBKD59p2bKlJSDcuXMnI0aMcGHJ6iej0Ujbtm353e9+B0Dr1q25cOEC69atkwBQQGBgIAaDgfT0dKvt6enpMg5D1Bnz5s1j//79vP7664SGhrq6OPWau7s7UVFRALRp04azZ8/yv//9j5kzZ7q4ZPXLuXPnuHbtGs8995xlm9Fo5Pjx46xZs4avvvpKJjBUk5+fHzExMSQkJLi6KPVScHCwzRe7Zs2a8euvv7qoRK4lAWAZ7u7utGnThiNHjljSlRiNRo4cOcKYMWNcXDrR2CmlmD9/Prt37+a1115r1AOYa4rRaKSgoMDVxah3unXrZjPT/z//+Q8xMTHcc889Evw5QW5uLgkJCQwdOtTVRamXOnbsaDOUKz4+nvDwcBeVyLUkANRx55138uGHH9KmTRvatWvH//73P/Ly8hplE3F1mf9gmSUmJhIXF4e/v78MZK6CefPmsW3bNp599ll8fHwsLdW+vr7S7VYFX331FT179iQsLIzc3Fy2bdvGsWPHbGZbi4r5+PjYjEX18vIiICBAxqhW0aJFi+jbty9hYWGkpaWxdOlSDAYDQ4YMcXXR6qU77riDV155heXLl3PjjTdy5swZNmzY0Ghb+zWllHJ1IeqiNWvWsGrVKtLT02nVqhWPPPII7du3d3Wx6p2jR4/y+uuv22wfNmwYs2fPdkGJ6rf77rtPd/usWbPkC0oV/Oc//+HIkSOkpaXh6+tLy5Ytueeee+jevburi9YgvPbaa7Rq1UoSQVfR3LlzOX78OJmZmQQGBtKpUyfuv/9+y5AFUXn79u3jq6++IiEhgYiICO64445GOwtYAkAhhBBCiEZGBmUIIYQQQjQyEgAKIYQQQjQyEgAKIYQQQjQyEgAKIYQQQjQyEgAKIYQQQjQyEgAKIYQQQjQyEgAKIYQQQjQyEgAKIYQQQjQyEgAKIYQQQjQyEgAKIYQQQjQyEgAKIYQQQjQyEgAKIYQQQjQyEgAKIYQQQjQyEgAKIYQQQjQyEgAKIYQQQjQyEgAKIYQQQjQyEgAK4UKbNm1C0zRee+21al1n4cKFaJrGwoULnVIuV7BXF8OHD0fTNNcUyokefvhhNE0jLi6uWtdxZn04q0x1RatWrWjVqpWriyFEvSABoGhUNE1D0zQMBgNnz561e9zNN99sObY+B1VCCNf77bffePDBB2nXrh0+Pj40bdqUm2++mSVLlmA0Gl1dPNFISQAoGh13d3eUUsybN093/+nTp9m0aRPu7u61XDKhZ9GiRRw/ftzVxai2t956i+PHj9O0aVNXF0XUotWrV9O7d2+WLVtGr169+OMf/8htt93G4cOHuf/++3n00UddXUTRSEkAKBqdyMhI+vbty4IFCygsLLTZ/9lnnwFw11131XbRhI4WLVrQqVMnVxej2qKjo+nUqRMeHh6uLoqoRc8//zyFhYWsXbuWb7/9lrfffpvPPvuMo0ePEhERwWeffcaFCxdcXUzRCEkAKBqlGTNmkJCQwA8//GC1vaCggIULF3LjjTfSpUsXu+efPn2aKVOm0LRpUzw9PYmJiWHKlCmcPn1a9/irV68yffp0IiMj8fHxoWfPnnz++eflljE1NZUXXniBzp074+PjQ5MmTRg5ciRr166t1HPdt28fEyZMICIiAi8vL1q2bMmsWbO4cuWKw9coPT5v586d3HLLLTRp0oSAgABuvfVW9u7dq3vetWvXeOGFF+jYsSPe3t4EBwdz6623sn79eofvrTfmrXR5Dh48yB133EFQUBC+vr4MGzaMHTt2VLs8pe+xd+9exowZQ5MmTQgODmbChAlcvHgRgHPnznH//fcTHh6Oj48PN998M4cOHbK5nr3xdgsXLmTChAm0adMGHx8fAgMDGTx4MIsXL3a4jiqyfv16hg4dip+fHyEhIYwdO5YTJ06Ue86vv/7KxIkTiYqKwtPTk+bNm/Poo48SHx9fqXvn5eXx9ttv061bN3x9fQkMDGTo0KEsXbrU5ti4uDg0TePhhx/m1KlTTJo0iYiICAwGA5s2bQJAKcUHH3xA165d8fb2pmnTpjz++ONcu3at3HJ8/fXX3HzzzQQFBeHt7U3nzp154403yMvLszlW0zSGDx9OcnIyM2fOJDo6Gi8vL7p27cqCBQsq9fzPnTtHYGAgw4YNs9oeFRXFgAEDAEhKSqrUNYVwCiVEIwKopk2bqoyMDOXn56fuuOMOq/3Lli1TgFqwYIF66aWXLD+Xtnv3bhUYGKg0TVP33HOPeuGFF9S4ceOUpmkqMDBQ7d692+r4pKQk1aZNGwWoIUOGqOeff15NnTpVeXt7q7vvvlsB6tVXX7U6Jy4uTrVq1UoBaujQoeqpp55SM2bMUNHR0UrTNPXpp59aHb9gwQLdsq5evVp5enoqDw8P9cADD6jnn39ejRo1SgEqJiZGnTt3zqF627hxowLUmDFjlKenp7r99tvVCy+8oO69917l5uamvL291ZYtW6zOSUtLU126dFGA6tevn3ruuefU9OnTVUBAgNI0TX388ce69yhbF8OGDVNl/1SZj73jjjuUj4+PGjFihPrzn/+s7r33XmUwGJS3t7c6ceKEU8pz++23K29vb3XrrbeqP//5z2r06NEKUB06dFDHjx9XoaGhavDgwepPf/qTmjBhgtI0TYWHh6vMzEyr602dOlUBKjY21mq7t7e36tOnj5o6dap6/vnn1YwZM1TTpk0VoF5++WWb34VefZTn22+/tdSJ+R5DhgxRQUFB6qabbtIt07x585Sbm5vy9fVV999/v3rmmWfU2LFjlcFgUNHR0er8+fMO3TsvL89S3k6dOqmnn35azZo1S0VERChAvfDCC1bHx8bGWt4nQUFBqn///uqpp55Sjz76qNq3b59SSqknn3xSASo6Olo98cQT6k9/+pNq27at6tu3r4qOjlYtW7a0KccjjzyiANWsWTM1bdo09ac//UndeOONClDDhw9XBQUFVscDqkePHqpDhw7qhhtuUI8//riaMWOGCgoKUoBauHChw/Xfp08fBaitW7dabb969aqKjIxU0dHRKjs72+HrCeEsEgCKRsUcACql1PTp05Wbm5u6ePGiZf+tt96qAgMD1fXr13UDQKPRqDp16qQAtXjxYqtrf/PNNwpQHTt2VEVFRZbtM2bMUIB66qmnrI7fs2ePcnd3txv0aJqmvv76a6vtaWlpqkePHsrb21slJCRYtusFgJmZmSokJEQZDAab4Oztt99WgBo1alTFlaZKgiFAvf/++1b7Vq5cqQDVrl07q+c9c+ZMBaiZM2cqo9Fo2X7q1CkVGBioPD09rQKPqgSAekHvxx9/rAD1hz/8wWp7Vcuj97ueNm2aAlRwcLB64403rPb99a9/VYCaO3eu1XZ7AeCZM2dUWXl5eWrEiBHK3d1dXbp0qcL6sMf8GnB3d1d79uyx2vfUU09Znl/pMp08eVJ5eHiotm3b2tx7/fr1ymAwqLFjxzp0/7///e8KULfddptVkHX16lXVsmVLBajt27dbtpsDQL3gUCmltm/frgDVtm1blZKSYtmek5OjBg4cqACbAND83hg3bpxNoPXqq6/q/q7MZZg+fboqLCy0bD969Khyc3NTnTt3duj5K6XUli1bVGBgoPLy8lL33Xefev7559Xvf/97FRYWptq1a2fzhVGI2iIBoGhUSgeAu3btUoB6/fXXlVKmVjeDwWAJHPQCwG3btilADRo0SPf6Q4YMUYDavHmzUkqp/Px85evrqwICAlR6errN8eagoHTQc/DgQQWoiRMn6t7DHHB9+OGHlm16AeDixYsVoB544AGbaxQUFFhaGB1pzTEHQ2WDPDNzULJp0yallCmA8fX1Vf7+/lYf1GYvv/yyVd2XvkdlAsDBgwfbXDs/P1+5u7urPn36WLZVpzxDhgyxOX7z5s0KUK1atbIKEJQyvY4A9fDDD1tttxcA2vPdd98pQH3++edW2ysTAJpfA1OmTLHZl56erpo0aWJTJnNg+MMPP+hec+zYscrNzU1lZGRUeP927dopTdPU8ePHbfZ99tlnClCPPPKIZZs5AIyMjFS5ubk25/z+979XgJo/f77NPvPvq2wA2LNnT+Xu7q7S0tJsziksLFShoaGqX79+VtsB5evrq65du2ZzjrnVtGwLb3mOHj2qunbtagksARUQEKDefPNNlZOT4/B1hHAmmeYoGq0BAwbQrVs35s+fz8svv8xnn32G0WhkxowZds/Zv38/ACNGjNDdP2LECLZt28aBAwe46aabOHHiBNnZ2QwdOpQmTZrYHD98+HCbsYA7d+4ETOPV9PIDmscLVTQztryyuru7c9NNNxEXF8eBAwdo0aJFudcyGzp0KAaD7dDh4cOHs3nzZg4cOMCwYcM4efIk2dnZDB48mJCQEJvjR4wYwRtvvMGBAwccuq89ffv2tdnm4eFBZGQkaWlplm3VKY/ePWJiYgDo2bMnbm5uVvvMs3wvXbrk0HO4cOEC77zzDhs2bODChQvk5ORY7b98+bJD19Fjfg2UHX8G0KRJE3r27MnmzZuttptff5s3b2bPnj025yUmJlJUVMSpU6fo06eP3XtnZmZy5swZmjZtqjuJx/y61KvzHj164OXlVannM2TIEJvfRXZ2NocOHSIsLIy5c+fqltPLy0v3vdS+fXsCAwNttjdv3hyAtLQ0/P39da9Z2rp167j//vvp27cvixYtolOnTiQkJPDBBx/w0ksv8eOPP7J582bJOiBqnbziRKM2Y8YMnnzySX766ScWLFhAnz596NWrl93jzQPNo6Ojdfebt6enp1sdHxkZqXt8VFSUzbaUlBTA9MGxbt06u2XJysqyu68qZXVERc/DfM+auLeeoKAg3e3u7u4UFRVZHlenPHqBu/nDurx9BQUF9gte7Ny5c/Tv35+0tDSGDh3K6NGjadKkCW5ubsTFxfH555/rTlJwVHVef++++265167J159euUpfU+/5uLu7ExYWZrUtLS0NpRRJSUm8/vrr5Za3rPJeW4DV68ue1NRUJk2ahK+vLytWrMDX1xeANm3a8K9//YvY2FhWrlzJ4sWLefjhhytVPiGqS2YBi0Zt8uTJ+Pj48Nhjj3H58mVmzpxZ7vHmD/yEhATd/eaZtebjzP9fvXpV93i965jP+b//+z+UaZiG7r+KZiNWtqyOqOh5lH3ezrx3ddS18pj961//IiUlhXnz5rFp0ybee+89/va3v/Haa69x6623Vvv61Xn9Xbt2rdzXn14rnN51qlLn9lY6Ke/5FBYWkpycrHt8r169yn0uSqlyn0tV7dixg7S0NAYMGGAJ/kq7+eabAdNMfSFqmwSAolELCgpi4sSJXLp0CT8/Px544IFyjze3DppTUpS1ceNGAHr37g1Ap06d8PX15eDBg7ppKvSuM3DgQAC2bt3q6NOodFkLCwst1zeX1RHbtm3TXbnAfA/zPTt27Iivry+HDh3SbeEpW081ra6Vx+zMmTMATJgwwWZf2a7ZqjA/H71rXbt2jYMHD9psd9brLyAggLZt23L58mXd9EhVqfPyns+2bdtsWuX8/f3p2rUrR48eJTU1tTLFdwpz6629NC/m7Z6enrVWJiHMJAAUjd4bb7zBihUr+PnnnwkICCj32MGDB9OxY0e2bdvGsmXLrPYtW7aMrVu30qFDB4YMGQKYxqM9+OCDZGZm2ozn27t3L19++aXNPfr27cvQoUNZvnw58+fP1y3Hb7/9RmJiYrllHTt2LCEhIXz99dfs2rXLat/cuXOJjY3llltucXj8H5jyH3700UdW277//ns2b95Mu3btGDp0KGD6QDM/71deecXq+LNnz/Lee+/h4eHB5MmTHb53ddS18piZ160tG6T//PPPloTk1XHPPfcQHBzMV199ZZOr8bXXXtP9UvL444/j4eHB//t//49Tp07Z7M/Pz3c4OJw2bRpKKZ555hmr4Cw5OZm//e1vlmMcZe4mffPNN60CutzcXF544QXdc/70pz+Rn5/PtGnTdIP/tLQ0y9hCZxs0aBDu7u5s377dJn/nxYsX+eSTTwAYOXJkjdxfiPLIGEDR6LVo0cLhIEjTND7//HNGjRrFpEmTuOeee+jUqRMnT55k5cqVBAQEsGjRIquJEn//+9/ZsGEDc+fOZe/evQwZMoQrV66wZMkSbr/9dlatWmVzn6+++ooRI0Ywffp03nvvPQYMGEBQUBCXLl3i8OHDHDlyhJ07dxIREWG3rP7+/syfP597772XYcOGce+999KiRQv27dvH2rVriYqKsnwAOWrMmDH8+c9/5qeffqJHjx6cOXOG5cuX4+3tzfz5862e99tvv83WrVv54IMP2LNnDzfffDPJycksXbqUzMxMPvjgA1q3bl2p+1dHXSsPwKxZs1iwYAH33nsvEydOJCYmhiNHjrBmzRruu+8+lixZUq3r+/v78+mnnzJp0iSGDh3KpEmTiI6OZtu2bRw5coSbbrqJLVu2WJ3TqVMn5s+fz7Rp0+jatStjxoyhQ4cOFBQUcOHCBbZu3Up4eHiFiaQBnn76aX766Se+//57evTowe233052djbffvstiYmJPPvss5YvS44YPHgwTzzxBO+//z433HADEydOxMPDg++//57g4GDd8YbTpk1j3759fPTRR7Rt25Zbb72VFi1akJqaSmxsLFu2bOGRRx7h448/drgcjoqJieGVV17h1Vdf5bbbbuPOO++0TAJZvnw5WVlZjBs3jttvv93p9xaiQrU34VgI16NUGpiK2EsErZRSJ06cUA899JCKiopS7u7uKioqSj344IM2yYfNrly5oh555BEVFhamvL29VY8ePdSCBQvspj5RSqmMjAz15ptvqt69eys/Pz/l7e2tWrVqpW6//Xb1ySefqKysLMux9hJBK2VKXD127FgVFhamPDw8VPPmzdVjjz2mLl++7FA9KGWdomXHjh1q5MiRKiAgQPn7+6tRo0bZzWWWlpamnn32WdWuXTvl6empmjRpom655Rb1888/l3uP0spLA6NXb0op1bJlS92EwM4oj1Il6UqmTp2qe39ADRs2zGqbvTQw27dvVzfffLMKCgpS/v7+avDgwWrFihWVqo+KrF27Vg0ePFj5+PiooKAgdffdd6vjx4+Xm5rm8OHDaurUqapFixbK09NTBQcHq65du6qZM2eqDRs2OHzvnJwc9eabb6quXbsqb29vy3P86quvbI6tqF6VMuXifP/991WnTp2Up6enio6OVrNmzVLp6el2f+9KmZKi33HHHSo8PFx5eHioyMhI1a9fP/XSSy/ZpKnR+/2ZVTadj1Km1E1jxoxRYWFhys3NTQUEBKhBgwapjz76yCaNkBC1RVOqhka/CiEajE2bNnHzzTfz6quv6qamEUIIUb/IGEAhhBBCiEZGAkAhhBBCiEZGAkAhhBBCiEam1scArlixgt27d3P58mU8PT3p0KEDDz30kGVpJSGEEEIIUbNqPQB88803GTx4MG3btqWoqIivv/6aixcv8q9//Qtvb+/aLIoQQgghRKPk8lnAGRkZ/P73v+e1116jS5curiyKEEIIIUSj4PIxgNnZ2YApYakQQgghhKh5Ll0JxGg0snDhQjp27Gh3JYaCggIKCgqstnl4eODh4VEbRRRCCCGEaHBcGgDOmzePixcv8te//tXuMStWrLBac3Xw4MH88Y9/rI3iCSGEEEI0SC4bAzhv3jz27t3L66+/Xu56pmVbADVNw8fHh7S0NAoLC2usfJqmERYWRnJyMrJYSvVJfTqX1KdzSX06l9Snc0l9Opcz6jMpJ4njKccB6BzamXCfcGcW0SHu7u4EBwdX/XwnlsUhSinmz5/P7t27ee2118oN/sB+d29hYaFN17AzaZoGmAJQecNVn9Snc0l9OpfUp3NJfTqX1KdzVbc+vz7xNc9uexajMmLQDMwZMocHOj3g7GLWuFqfBDJv3jy2bt3KH//4R3x8fEhPTyc9PZ38/PzaLooQQgghhMPis+ItwR+AURl5bttzxGfFu7hklVfrLYBr164FsFlQftasWQwfPry2iyOEEEII4ZDYjFhL8GdWpIqIy4gjxr9+LWhR6wHg0qVLa/uWQgghhBDV1jqwNQbNYBUEumlutAps5bpCVZHL8wAKIYQQQtQHMf4xzBkyBzfNDTAFf+8Meafetf6Bi9PACCGEEELUJw90eoBhzYYRlxFHq8BW9TL4AwkAhRBCCCEqJcY/pt4GfmbSBSyEEEII0chIACiEEEII0chIACiEEEII0chIACiEEEII4aD4rHi2x2+vl8mfS5NJIEIIIYQQDmgoy8CBtAAKIYQQQlSoIS0DBxIACiGEEEJUqLxl4OojCQCFEEIIISpgXgautPq6DBxIACiEEEIIUaGGtAwcyCQQIYQQQgiHNJRl4EACQCGEEEIIhzWEZeBAuoCFEEIIIRodCQCFEEIIIRoZCQCFEEIIIRoZCQCFEEIIIRzQUJaBA5kEIoQQQghRoYa0DBxIC6AQQgghRLka2jJwIAGgEEIIIUS5GtoycCABoBBCCCFEuRraMnAgAaAQFVKpyagTh1Gpya4uihBCCBdoaMvAgUwCEaJcxq1rUV98CEqBpqFNno1h6GhXF0sIIUQta0jLwIEEgELYpVKTS4I/AKVQiz9Cde2NFhLm2sIJIYSodQ1lGTiQLmAh7EuMLwn+zIxGSLpS5UtKd7IQQoi6QFoARaOhUpNNQV1EjGMteBExoGnWQaDBAOHRVbpe2e5kxk/F0Kqd4+URQgjhMvFZ8cRmxNI6sHWDaAWUAFDUaZUO2uycb4w7A8s/1x3LV/oegNX9tMmzUYs/MrX8GQxoD81CCwkzBXOLPrDcR5vyeLljA/W6k/luIUaQsYVCCFHHNbQk0CABoKjDqjsBw+r80pRCffEhxqatUPu2wdqVJfvMLX6l7qe69jZ1+4ZHo4WEmYK5UsEfYLmelp9rCR6tAku97uTS5ank2EKVmkxu4mWUuxcEhzpcJ0IIISrHXhLoYc2G1euWQAkARZ1U3QkYNufbHKBQbz2tu92y3xzUBYWYHqenmloTr1zSv97bz6DM3bsDb4ZdG0uCyfFTbbuTSzOPLSz13Oy1fpoD2ySZmSyEEDWuvCTQEgAK4WzlTcCoIABUqcmovdvsB1uOKg4SS1+l3CuW7t7d+Yv1dVYsgjETYc0y/XKVGlsI9ls/ZWayEELULnMS6NJBYH1PAg0yC1jUUSrujO3GMkGS1fHFs2uNa5ZjfH466tv5NVzCSjIa7Qd/AAOGWwI4u0GeuUWwijOTZQayEEJUXkNMAg0uaAE8duwYq1atIjY2lrS0NJ5++mn69+9f28UQdZhKTUYt/9x2x7gpuq1cdsf6lWN9YDpLw5JpUuSOb6GBwwHXuS0lmKAid5aGJ5NHEfkG8C8ykONmpAgYlhHII4mRRBd4lrmaRgVtg8VPrJxjdv6CcfjtkHIVdfmC3SCvsoGx5XRJaC2EEFU2rNkw/jbobyRlJzGy5Uh6RfRydZGqrdYDwLy8PFq1asWIESP4xz/+Udu3F05S3dm55bIzYUILjdAthyPB3xWPfNYFpfOrfyabgzLIcDea4jYwxW4a7AvILr6R/jWOB+TycUwiTXM9mJAUyo3XA2k95F5ifKNQ332OQ0FgOXTHJJoZDCgPr0oFxpbrSrexEEJU2dcnvuaZrc+giv/Gzz04l3eHviuzgCurV69e9OpV/yPnxqymW5OUp7f+9k/nYMzNxjB0NMZzp+DMMZSHp93g76Dvdb4MT2RnYCYXvAvsBnaW7fb2lzn2sk8B7zVP4D0tAS35TW5KDySqpTt+RjfGpoTSM9vPgQtVUqsOaPm5pkkmZYvkZkClJtsN5tTZ41UeTymEEI1ZfFY8z2591hL8ASgUz259VmYB17SCggIKCgosjzVNw8fHx/JzTTFfuybvUR/Za03ihj7ltiY5Wp9l8+vZ3H/xRxQdPQD7tts9Zn1gOi+3Ok+8V6FjQV1VFF9XabA5OMOyeX5UEjem+zMyI4h+mf7OCwbPnUDl5enOJFZL56O+XYA24WG0Vu3QSrXKGreuRX3+vu31DAbTcfL6BuT97mxSn84l9elclanPuMw4jBhtthsxcj7zPE0Dmjq9fLWlzgeAK1asYNmyZZbHrVu35p133iE8PLxW7h8VFVUr96kvchMvm9KPlGY0ElKUh3e0/XFohclXyT20l7CmzXEPi7LZV3j5Isa8HFIWfVB+d67RWG7wN/yGI5zzyau5wK8iGuwIymJHcBYoaJnjyfvn2jglEPRPSSCvay/yj+y33akUatkC03dUzUDwEy/i3WcQVxZ9aHuswUDw4y/i37Wb3XuZfyfuTZvjHhZpd1tDI+9355L6dC6pT+dypD4H+g1EQ7NqAQQwYGBA+wFEB5Y//rouq/MB4Lhx47jzzjstj80Re1JSEoWFhTV2X03TiIqKIiEhQbfbrbFS7l66y6OlunmhXdGfiWrcuhajObDTNLQJD+M2ZrztvkoqQuN4UGvSPAMpah/Bc5nvcqUqrX7FYwAt7+/qBo+lupTP++Zzd9cTROd58OdLMdyXGmZV7uD8DDqnx+LmwPjBzK//69j9lZG099+EEXeBsv3mqs14hszuA8h08PdlmPK4aXuZbQ1pEom8351L6tO5pD6dqzL1eTXrqu72Fwe8iNt1N65cr/ra8NXl7u5ercawOh8Aenh44OHhobuvNt4ISqlG+YazO8kjONS0PNoXH5mCC820PBrBobr1pFKTrQO84paqwgvn0EbeZerurUz9dukFxw6wK+wG5rW7mxTvIJIK/8f5/LdAf+hgOU8S+mX4cUOWL78FXGdM8Szgb8vMAr7snc/lsoGlOWh0hAZXvAt4uu15nm99kVC3QQR7DcffrRMAobnpTD+zioHJRyr5BMp7bgo2rNIpiwYh4Ta/K/PvW3l6W/9OlML4+QdYTXBRCuMXH0KXXg1uEkljfb/XFKlP55L6dC5H6vPctXM2rX8APcJ61PvfRZ0PAEXNKxvsOTTJw9yypNPCVPq6dhMy796M2r258oWNbsYu/zbM8TGlDkor3Mn5/H86dq6CoHwDvbL96Jfpz4SUMJ2ULnBfqm1Qc8Ujn33+WawPTOeMbw75KE74V7KrWYNCNyNX2c7VvO24E4qP1oYIj7uZ03Uyzx79wrlBoJ7i5NZFt92LYfhtpqAv7oxpdrHdP2Y622USiRCiEfB199Xd7uPuU8slcb5aDwBzc3NJSEiwPE5MTCQuLg5/f3/CwuTDpLaVDfYYPxVKBwNlUoZYJoGUUna/Y0FF1RRt+IF5A18grWgnl/I/IQ+dZdmsCgfBeRo9s/2ZnBjBLRlBVbpvdIEnd6aFcGdaiGXbQb/r/NIknQO+19kcnFnpruNCUshUKWTm7wF8eL3NNH5I1hzqDq62n77F+NO3VT/fgdyDQghR32UXZutuzynMqeWSOF+tB4Bnz57l9ddftzxetGgRAMOGDWP27Nm1XZxGzXjulM2MXvSCttKtPeWsRGE8ur/SCZntCo2EFNuxF8eDWrNNvcL1/GPln68gtMDAglMdaiYti6bRc8xsehbXl7mFcEdAJosjk6swjjCHo3xI595u/C4ppObSyTiDwdTt39C6f4UQoqzWga0xYLCaCdwQloEDFwSAXbt2ZenSpbV9W1GG3XQr5pbAMpM8LK09ETG6+5WHl/OCPygJ/rr3g8N7LJvXB6ZzXZUf/PkbejAzPoKnLqQ6pyw6tBnPYOg3BGNmOmrtSqsWwieuRPNdaAp7AjLZ7Z/FdXflcECY617E/Ogk5kcl0TfDj+UnO9XYc6gK7dZxaCPukuBPCNEobL602WoMoIbWIJaBA1kLuFHS68a1PqA4CASb1h4tJAxt8mxTUGjaAr0Hoc6fcXp3L2AK/jSNKx75rA5OZaP/oXIPb+v5Bp28/2Xd1Wt+LppW8nN1GAxobU2BmTbybpvd0QWePJ4QzeenO3D8QG/+cbYlnkVulbuHBnsDr9O2zz7+PsCDKx4luTAZMKw6pa8WtfZ768epyRj3bMW4Z6vpdVVqvWF7PwshRH0QnxXPs9uetQkAhzVz3d9gZ5JJII2RnaXWrCiFNvNZtLadrFp7VGoyqrAQbr4Dzp6AuNOwd7vpXw1ZMqwZz15fiaogdgtxG02w20BCc9PonB5r2a7NeAYtsAmER6OO7jclrjYaS4LBygSumk5APOVx62sqKD1x4r7UMCakhnNn/wHEsZlsYlFcd+BeUOAGH6tdfNwTBl/zp2OOD+Na+NEj9D74nwta0lXxmsSA2rCqOCA0PVdTDsJSrcPmn8tsk3WIhRD1QWxGLMYyEx2NGInLiGsQLYASADZC9pZa01M6+KtolY6acND3Os9kryy3C9WTSNp4/QV/t46gYPqZ1SUTKYpb6ywB29DRqK69TWMa9QLCCoJBbebTGPoOsdpmKO+axdxQvHouizld5wJwPv8DkopWOl4RGmwPymJ7UBbz4/5Gp+vezPFt5ZJxgsbV38DJ3/R3lq6/0mNLS21TX3wo6xALIeq81oGtMWgGqyCwoYz/AwkAGyS7OfyKafm5js0zLRV0qdTkWg/+vglL5tk25+3uD3cbRKDbHQS7DwIgzNedaYZYBqYcNR1gZ7KCFhJmSV9iExCmp6Leelr/hgYDWhv9MXl61zQe3gNffWwJgAYmH+HZY18wr9vvwOsJoo33k1a0k9SClVxX5yuVV/CEfy53dz1B1+s+zD/dTjedDQB33Y8W0wJCIuw/r8qyF/w5SinU2RNoIUMqPlYIIVwkxj+GOUPm8Ny25yhSRbhpbg1m/B9IANjg6OXw07r2tiT51fJzTS2AFbZ2aVbBjvHHJTVf+FKueOSXG/wZNAM/3Pt/pGUHkZZTRLCPG13CfXEztEMN7WUJ6BxpZSodvIFu1jtTXVZi5qs6ut8q+DMV2sCg24YzoEskR9/+O2meAcUrgYST6BHI+qB0/t7skuOTRjQ46p/DgJ6/MTY5mBcuNbMOBA0GDENGl6wLPHosau1Kh8pf42RJUyFEPfBApwfoFNKJPQl76BfVj14RvVxdJKeRALAeqahlzzK5o3QOvy8+LB6SVmac1sCbYdfGcpP/GndvwW3MeNN9t/xcA8+ojN89htayHVpBHnf9+hDk6R+moTFnyByaBTSlWYDO/jIBXaUkxuvfs3jWryNsfg9gCiCfm4OhTQcMQLe7byvV9Wwgun1/Jh8/xOSkCJaGpfBKm3hyyHeszBqsDE9jZXgaN2T5cFtqMBNTw4gefq/1YSPvrhsBoKbZbUkVQoi65OsTX/PstmcxKiMGzcCcIXN4oNMDri6WU0gAWE84tDqH3uQOvQBPKdj5C/QcCAd32b/pdwsxAur4wWqVXZvwsG1SaE0DNNOkguKuWvPz+X+b/h+JefZni66+Z3XNfQuzk+bGPOvXIXZ+D1pBSURbdtygJYl20hXuD4/mgZAwlpxcwsrj33I16zIncy44dOsj/jkc8c/h3ebxtL98kpHvfcC0m56l6Yj7i48oveixk93zEHy/uOLj+t2E8cI5tL3boF0XDG061Ex5hBCiGsyzgM1jAI3KyHPbnmNYs2ENohtYAsB6QLdlT2/1DYe6dkspL/gz3/u7hVUvOMCt4zCMGY/yDzCtH2ssCfi0MgEQwDt73mHpafuzWx/p8kiNNsGb09xYWueqkvTYThBZduWMsi2VZR9P6jiJSR0nAXAg8QCv73qdPVf34BANTvvlcdrvKh+f+TP90r7gLy0epkdNrjJSVOjY62/3ZtNSgObTBo3AbdpT5bZwV9T6LYQQzqY3C7hIFcksYFGzSn/g2Vt9Q509gdpwCrXu+5J0GwNvhl83Wc1AdSWtVXvA1OIVOWIMV387BOFRJR/ipT7M/3PoP7x38D2712oZ0JI3Br9Ro+UF/da5ynBKEFlGr4herLx7Jf859B/e2F3JOtBgT+pB7kp9iuCeBjpe92Hm1agqL4tn9zbd+kJIGOqLj8pdI9rGzl8oCgqFNct0W7gdav0WQggnO5x02GZbQ5oFrClVE9l7a15SUhIFBQUVH1hFmqYRHR3NlStXqO0qqnB93vJoGjzwqOn/hEuwYXXNFnbAMNi9Rb9smobh7XmmgKiC+ozPiqff1/3s3qZlQEt23L/DmSWvceYu3aoEkeWJz4rnuzPf8dXJr7iQ4VjXsG3hILBA49GEKCamhNmfReyo4lY8KE4O/e286uWGNBgwvPUZAMbnp9u0phre+sypderK93tDJPXpXFKfzuVIfcZnxdP/6/5WSaABXu7/Mn/o8YfaKGaFPDw8CA8Pr/L50gJYx+h197J8EYyZCD9968AFlGn2aW0wd92Nn2paCzj2dEmgap6B7OCH9Cs7XrG7b3jT4Xx5+5fOKnWtqdZklHLE+MfwZK8neev2t/jfof/x733/Zv3F9ZUsHGR4Kt5tcYV3m1/h3qRQOuX40C/Tv/K5BQcMswR/YHrehnunY6xOAGg0Ytz6M1w4a7f1m8RA6RIWQtSIvVf32gR/AM38m7mgNDVDAsC6RncCgdFqPVyXmvgImsEAbTtbBu+bAx23jt1Q/W+qdKvXzHUzWXN+jd397970rlOK3hD1iujF52M+Jz4rnmWnl/Fb8m9su7yNjIIMxy+iwbcRKaafFQTlG7g/OZxHEiMcaxncvQU1fmpJuplzp+DMMRg4Anb9UoVnVewHO6mHNA316RzLjHbpEhZCOFtablqlttdHEgDWISo1GZV5TX/n5bhaLYs9hlbt0Dp2s7u/sq1eBxIP8GPcj3b3v9z/5QYx2LammVsFzf7fpv9X7mQauzRI9zLycdOrfNz0Kq2vexFc6Eb7XG8eTIqgp0czuFbmD6BSqH3boM8QjCsXm2aY16SyK4uUmhAlhBDOEOwdXKnt9ZEEgHWE1bg/VxgwDH7dXP4xOjNZq2vu/rl2941rO67OjLWob/49/N880/cZvjv1Hbuv7ubXK79yvciB9YfLiPXLIxbY3ySbJZGp+BnOMyjJgyevxFh1Faul81FL5zvxGVSC0Yg6dwJ11vTe0dp2lmBQCFEtzQOa625vFiBdwKIClUlboZs4uDYNGAahEeUfU8mVMBwRnxVf7ti1F/u/6LR7NUYx/jE80fsJy+MlJ5fwt11/Iy2/6l0Y1405rA/NYX1IBsG5GkOymtA03wsvpTEyPcglaxMDqE/mlPwMaFMel25hIUSVXcy8qLv9UualBrMaiASANaDSaSv0xv3VGg1txF2ot58p5xAN7fl3nZ6wd935dXb3Sdev85nzCh5IPMCXx79k48WNJOQkVO1iGqT5KFb7pFs2/V/TBG5PDWJKYgStc72qP7O4GtSiDzF6+0hroBBC2CEBoJNVlLRZl17i4FqiTZltWh/Y3r01A9rkWU4P/r4+8TUv7XhJd9/4tuOl67cG9YroZfkGeyDxAJ8c/oTVsU5IF6TB/0LS+V9oOigYkRqIUVNcMxTRIaQdDx7Or8UWQoX69F2UpqGNugdt5N0SCAohHNY3si8amtVMYA2NPpF9XFgq55IA0NnsJW0uHiSv9yGkhYSZEjiXHjzvFwDXM8u/V7M2cOlcmYsZHEvCW6pVT6Um6wegN92K4Y5JTv/gjM+K55mtz+hOsQd4of8LTr2fsK9XRC8+vuVj/pL1F9afX8/Gixs5lnqMS9cvVe2CWsn/v4SWzEQ+YDzMkq4Qku9GaKE7/gUGbskIZmJKaM22FCqFWrvStAbyhIdxGzO+5u4lhGgwYvxjeKn/S7y5+00UCgMG5gyd06B6piQAdLYI/ReHWjof9e0Cq+5gqyXcdm20PqGi4A9sgz+A8VPQ/PwrHFOojZ9qlcbFauUKTTPtr6EPy3lH5ukGfxoa7w59t0G9weqLGP8YpnSdwpSuU4DiZNOnvmPL5S2cSDtBal5q9W+iQapXEaleRQAcCDKtWXxvYghFmqJtrk/NBoTFa1tX9LqWZeeEEF+f+Jq/7/k7CoWGxov9X+SBTg+4ulhOJQFgTbDXnVuqO1jt3oIqlTS50t2/ds4xtG6P1rEbxqatUG89bf/01u2tz6vm8meOis+K55PfPrEtDxqr71ndYAbX1nfmCSTmSSQHEg/w3v732HR5E/nGfOfdSINvI1KLWw7TeLd5PA8mhlFgNLIlKIOeWX68fqmF04JCtfxzVP+b7L6+jVvXYlz0QbnjdyVAFKJhi8+K59ltz1rWAVYo3trzFve0vadBNVBIAGhHkVGx70Iapy9dI9jHjS7hvrgZtIpPrGhCh9GIcfnn1ilXqjL277aJ8NMymyWyzGlaDG06YJzyuH5LoJ10LjW1ckVpc/fP1W39e7TboxL81WG9InqxYMwCwDR5Z9GxRaTnpdPcvzkxATF4u3lzOu00P8T9UPmLa9Y/fxmZXDyVF9b4XGNN2G8MvGYaO+htNDAlMaLq6xgrZfqSo/M6L0y+WhL8FR9bdvyurEssRMMXmxFrCf7MilQRcRlxEgA2dDsvZPLffVdJyS60bAv1dWdGn0gGtQgo/2RHJnRUlG/PAYYuPVFhkSXdtgaDTZoWc6ue+mU1au33prGBOsfVln/s+AeLTyy22W7QDEy/YXqtl0dUzaiWoxjVcpTuvjErxvBb8m/Vv0mZoHBXUEkOw03BmUTkuzM6tQnZ7kbuTAlxPCDUSr78WFYsadcFt7YdKbx8UXf8rjlgrNIELyFEvePr7qu73cfdp5ZLUrMkACxj54VM3t56GYB8YxK56hLeWjNSssN5e+tlnh/a1CoILNsdpDeerkZm94ZHY+jYrcJuWy0kDG3iI6gRd9V492554rPieWadfqqZmTfMbFDfqhqzNePWsO78OjZe3EhQZj7fnPmWq16F1gFddWmQ6FXI4mjT8nXLw9KIzHcnKs+DFnlezLgaZXe2sTb6HrSQMIrmz7WadFXYZzD53XVm95VuLbczwctei6IQon7KLszW3Z5TmFPLJalZEgCWUmRU/HffVQCSCv/H+fx/g2nYOC09/x/h7rfz2b6r9G/mj5tBs9sdZGl5O3sCdeIQbPnZsQJ07+fYmr+ahjq6H23oaIe7bWuje7c8L29/2e4+af1rWMwthCo1mT+vOM1Bnyy+Ck/kglcehUpxwj+HDHdVEhQWd/dWmQZXvQq56lXIIXJYHZZOyxxPjEZFtmcRdyeF8vrlFqZjW7aj6OBu2+Xq9m3n2r7tttfuObDkC5Ne634NrI4jhHCt1oGtMWDASEk3sJvmRqvAVq4rVA2QALCUY0nZpGQXkm9MKhX8ARg5n/9vmhj6kZwdzrGkbG7wyEEt+qDk5DLdQerofuv9DtDumIRyJACsZ11P8VnxrDm/Rndf7/De0vrXQJlbw3su/oie561b5A76XueX4GtE3DGNg+c2sfTadusgsDpBoQbnfUsmqiyISWJhdBJ/O9+c4G9foG+WP9E4OKlk/w5UarJ+674Lh1MIIWrO5kubbfL/vTPknQb3WSUBYClpOab0FLnqElA2l56RXHUZT8JJyylCbVlle4Hi7iAFlQ7+ANSyBY4fXI+6nu5ceafdfU/2erIWSyJqm6U1fN921NJ5lu09s/3ome2HIXAoUyfN4ulLR9kXu5G0zKsEbdrI/PCr7G2S7ZyuYw2UBi+3Ll7aScGDiWE8GR/t0Oxi9ctqGHEXJMajde0Nz82Bs8egbRenJ0gXQriWeQZw2QBwWLNhLixVzZAAsJRgHzcAvLVmgAHrINCAt9YUgKDzx0yJZXUYt64FL++qFeD0Uf3td94PP3xjva2edD2tO7+OqzlXdfcFuAfYnUwgGg4tJAz6DEZ9O99u92nTZl1p2qwrKjUZ48rD3JkWwhWPfNYHpXPOO5d8jGwPzOScb371g8LimcZfRiQzMq0JvbN8aZHnQxO3zrgZogjOz6BzeixuxR8A6ucVqJ9XlDpfswz7MMosYCEaFL0ZwEaMDW4GMEgAaKVLuC+hvu6kZIfT0vP/2YwB9DSEEZqbTqfFb9m/iBNm+FoxGEytKCFh9bLracOFDXb3vX7j67VYEuFKjnaflj4uusCTyclRpokbI+4CIP7SYdan7edcVix5np4cS9jHvpyzVQsKNdgQco0NIdeKN5zDX+tFsPtNtCkcxeyz2xmYfMT2PJkFLESD1TqwNQbNYBUElh7/V1Ee0PqUJ1QCwFLcDBoz+kTy9tZLhLvdho9XG7KMv+Fv6Ia/oSMomH5mlaVloHo0qOg6pT4ktVpK1Oxs7gb9l1iEdwSTOk6q5dIIV3I02Xh5xzUNGcFURgCmP7TG56dzxb0bCyMS2RmQQYpHIRe9C6rcSpilDpBVcICLwJ42XXnZsyUPxdu2YBehcTyoNWmegYScTaBrUKhjeUKFEHVajH8Mc4bM4bltz1GkinDT3Czj/yrKA1rf8oRqStVEjpKal5SUREFBQY1ce8exy7y2YwFH1SeYWwC7ao/y6tls/RaBytIMaJNnoU4fs52NCKYXzoxn0Np2qjeBnp74rHgGfDPApjm9qV9Tdv9ut4tK1TBomkZ0dDRXrlyhnr6Fq02dOIzxn7azyw/6XudvzS+yJ/C6U8YQtsz2ZOS1JoxNCaVnth+7wm5gXru7SfEOshzjcJ7QRkJen84l9elcjtRnfFY8cRlxtApsZQr+zp1Cvf2MzTAWw1ufmSZ+Fn8htdqvaRjenldjn+MeHh6Eh4dX+XxpAdTRqoXG8e0fU9JCZ+SE8T+0vNYNHJ09aIc289mSwG7oaIzDb0etWwn7tpteOMWtfoZ+Q6r5LFxv79W9NsEfwNzhc2u/MKLh0UvLomn0zPHnu5OduOKRz8KIq+z3v06HbG+y3IysCE+rdFB43jef+b5JzI9Kom1uGH7BT+OpNbE6JiW7UDdPqBCiforxj7GM+TNuXas/sbN0ovizx23zhCqFOnsCLaRufp5LAKgjNiMWY5nu2SIN4rzzqr4mqbk5uExgZ2jTAR591jRuoJ5175bn6xNf88xW28TPDTGXknANe+MKuZ6F+m4h0QWevHC5udU5z1/OZ59/Fp9HJPFrYFblgkENzvokQ+4D+GqdifZ4kGD3QVaHlM4TKoSon+Kz4onNiKV1YGui8z1N3bp6DAaUhxecOIxKvKJ7iLqeWYMlrR6XBYBr1qxh9erVpKen07JlS6ZNm0a7du1cVRwrukkgFbTK9araBTUN7fl3y00Z4epEzc4UnxXPM1ufsVnz101z452hDS+XknAdvfGCxj1b7R4fXeDJnWkh3JkeyvJbb+XtjAvkFJ3jmtJJAl2ObHWcs/kv45bvTzOPPxDuMQaA5OxCjiVl0y3SdiWS+jQ4XIjG6usTX/Ps1mcxYsSAgXfaP8kkvW5iTYMBw1FvP2PqRtb0v/RpfnW3R8Dgipvu2LGDRYsWMXHiRN555x1atmzJm2++ybVr1yo+uRbE+Mcw56Y5uBVXj5uCt2JbVr31Tym0gjwnlrBu23t1r03wB/DBbR/wu06/c0GJREOmhYShdezmeFBV/IVs/Lg/0CPo97T3+Svdvb+hhfsfcSekUvcuIovzBe+yL/tOLuR+SFbRCUs+0dKMW9difH46xn++bPp/69pK3UcIUfPMjRfmxh8jRp49/X9c8ci3PfieB2HXRqusADY0Da1tpxoscfW4JAD84YcfGDlyJDfffDPNmjVjxowZeHp6snHjRlcUR9fvOv2OuP93nqW9/80O9Qj3J1d9oGV9ydnnLNvj9VtTQn1Da7kkojHS2na2+20cg8E0FKNNB9wMGtN9r4BSeGphRHjeTU/fb2nr+QY+VK43QpFDonE5J/Jm89qe+4nPii/Zl5pcMjMQStLHpCaX7D9x2PJYCOEaeo0XCsU+/yzbg1cu1g/6zDTT35q63Npf613AhYWFnDt3jrFjx1q2GQwGunXrxqlTp2yOLygosJrtq2kaPj4+lp9riqZpBO3cy8BPviz5JfccCAd32T+pW18Mt45HxZ1GLf/cMi7JMHk2htBqBJD1SHxWPF+e+FJ336Dmg9CyZWyUM5hf+zX5HqivtNBwmPI4xkUfgjKa/hBPmIrWqj1aRMkYW5WazMDv/sGzoV2tZvUGuw+iXWEnxsZ+Q6rxV/4beZU4H8cTUJ9MP0S/r/sxKHoQj7Z6gJFX3G0/KIxGSEpAHTuAcdEHlrQRhimP1+m0EY6S16dzSX06l736dGb9Gl4of9hXXVDrAWBGRgZGo5GgoCCr7UFBQcTHx9scv2LFCpYtW2Z53Lp1a955551qTX12RGHyVa68/3euuOcR651H61wvossJ/gLue4SgqbOLH42m8K6JFMZfxD2mOe5hkTVa1rrktdWv6Xb/Pj3oaZoFNoNAFxSqAYuKinJ1Eeqm+6ZSOGJMue/B3MTLJCnFwOQj9Es+asnr1+yWW2nx1ZzifJ8RTE6K4KDvdd6LiWd9cIbDgeDOKzvZGb8T/0KNP0RFMTElrGQYicFAWNOmJP7zZauWQeMXHxI5YkyD+Zshr0/nkvp0rjB3jcLLl9B8fFA5OdzarD8amvUycAr6ZPlX+tqhAX54R9ftnr86Pwt43Lhx3HlnyVqy5gg9KSmJwsLCGruvOvkb34Qm8nzr8xg1MCh4O7Yl9yeXac7VNAwv/IOcNh3IuVJmFlB4UygwQtntDdRHhz7i0/2f2mw3aAYeaPMAAAkJCf+/vTuPb6rM+gD+e9KkdAmldCcUutGWrdCyVEQQZBOlwIgswsiiKCi4zOsARcR3ZD6AQ1FhdHgRx2oFAVlVFERABAGFUihLoZWlLUvTlTaE0L33vn+kTZfcLE3TLM35fj5+hj735ub0TtKcPMt5qI6VGTDGEBAQQPfTED3vQV7cTlNGxgk8eisy1T32wTO1qgBEl7rjixvhyJVUYn1XJ+zwTgcHI+b1MkAl4bG2ay7WdsnFlAIvfHgnDKKZC1GUc1fdQ9kQxyH/8kWIuke15Le2Onp9mhfdT/NijEF68TRKPlnVqHfeiTEsGzcFqwt2gQev+dxv/vx/hqLsTIic2rXqELBYLLavOoAeHh4QiURQKBSN2hUKhVavIKAudCiRSASv1ZpvBLk70yR/AMAx4O2QWxh2vwM6VbdT/+Gu26kjJNzh35RylRwrz6wUPDav9zx0cld/E+J53uHvlTnR/WyBjt5aZWREMxeChYQDz84B9iQ1Pp8xdJr3T6wpuYfV2z7Fx114fOWTjmJxqXG9ggzY5V+MnwPKcCRYBpmbv2AdQ/gGtJn/T+n1aV50P82DLy5CySertaZmbPMuxOr8FPAMABjiFT3xXJGLKc8AflMCamx8NxCLJ4BisRihoaFIS0tDbGwsAIDjOKSlpWHs2LGWDkenbNF9TfJXR10LsByyGe+Ate/QZmr2mcPua7t1Hpvbe64FIyHEePVlZPLgH9UXhVUceJ6H09hJ4AD1XN66Au3PzAJzcQEvlcIJPP7nDvA/d3rggttDvBWShRtuFUYlgkq+DLEHxuBJSS/8UywyvboAIUSQwf16C+Rave/7/UOwNOh8w7Pwfsd0dPWfhHH5WSYGYtv7hVtlCDguLg4bNmxAaGgounXrhgMHDqCiogLDhw+3RjiCBDeE5oHgSlewUPveoq01XLp3SbA9yjuK6v4Rm8a8fMC8fdXz7hoMFYvGTgIf+zhQmAsuS72wS6jeV3SpO45e6Y0Lbg9x1FOBr30LUeRcoz8ZZMDP1VfwczSw7HZnvJJfO7eL5zU7CxBC9BNK9Izaj9e5ca/eaZ/eWBceBVQ27cjgsC58ELxr3E3fBrbBbiG2xioJ4ODBg6FUKrFz504oFAoEBwdj2bJlgkPA1iKTyvBZ3GeY/8M81IBT1wK8FQzZtL9R8idA17DEuOBxFo6EEPNhXj7q2YBNFmtoksAGr/voUndEl7rjLXlnDO+dhkxXI3oEGbC6aw62+BXgzRwZphb76CwZRYWkCaknlOixXv2ESy7V9sDVvYd4lVJznRowJHabABETnqsvYi5I7DYeA4uu1C4MM6DptA4bLgNntUUgY8eOtakhXyFz+81FdPtoZN69gOCKdpBN7kN/eAXIVXL8fOtnwWPPRjxr4WgIMbMCueAen2zeEkBxD/zORK2HHEvrjSMeCrwdfAv57aoN9gbeca3CorBb+CQwFyduZ0JkSq9GE5QwkrZKV21NvPR3wZJL/LlT4Gtq6qd0NJDuGYJ7Lp6orLog+FyVXD7uufRAumeIeqGYAWzSbPDfbm60PaWtvv9sfhWwtcmkMnSKtM3s3VYkpiUKln55JeoVGv4l9s9PJvitvq7Cv1ACCACjlJ4YdckTF9weYlbENSgknMFE8Fa7Srz544voWtUOI+97IubZeIO9GkJMSRgJsRtCX8o4DgDTfq9C93sUAEqc1bXJqiC8E1kVlI3OM4SFhIO9/3mj7SltlVV2ArEncpUcp+SnGlX2J/XkKjk+vfypVjsDo8UfpE1gXj5gMxeqh3KARt/qmZcP2KzXdO88AvXQ8KULMfjizzB0rHSC3lEkBnzrX4J/B+ZhQs8MTE5+HfL0kzoKSevYfN7AziOE2L26L2UN1X4pa/ReNULHSnWCJ0EHweOS2uK1defpxZgm6WvW9pRWQj2AeiSeT8S8H+eB4zmImAgJQxIwvft0a4dlUxLThL9ZzY+aT71/pM2oXy2s/a2+7hifmQHwAJ9xEfhNe0rEKKUnLl6IxhEPBRK65CDDrdxgj+AZDxViry7E650DsDinc4OA9Mwr0tU7YqMT0QlprrovZQ1LOGm+lNW+H7ldXwApJw1eq4ciC97lClQ69wSqmh5lkDr1hHd5CXooGqwEZkw91NtwSLluHqIdvccoAdRBrpJrkj8A4HgO8SfjMSxwGCU2taj3jzgS5uWjM4FS9wYOAQDU3CvQe51RSk+MuuKJV8Ju4oCXwqjSMZ90zsMJDyU23QhDpxoX/fOKdAxZ2+pEdEJMoe9LGQCjkj8AcAKPuTf2YXFk0/cTQ5DkLTgzX8y9saV+AUiDKRV87OPgb2aoR57tsDoIJYA6ZCmzGpWAAYAavgbZymxKAGst+m2RYDv1/hFHxRcXAXu/MurcT2+G4ULuQ/zXPx93nMtwwUN/j+CF9qV4JOYyXo98CUv1zOfT1ztCSFvAZV4DblwFuvWEKLJ+15y6hU/cycPNul7Q/fO4VXlZ6/0XXB2BhX9uqS8BwxjY0vo9fht+8bNHlADqIFgHkDkh2CPYekHZkNSCVBzPOa7VTr1/xKEJDb/qEV3qjg1ZoQCAb3yKEB9yq3YXAt0++fNz/HTrZ6wb9C/0Cx8uuNrXYO8IIXaq5ov1wB9H63/uNxhOry5tvPCpmVKkKoEvXzymXPsXBpV4aVrYmL9okr+2gBJAHTR1AH+cjxq+BiImwtsD36aerVrJecmC7XEhcXSPiOMSGn41BmN4zm80hl04g/cD7+I7nxK9vYE3yu9g/K9/xeRjvfDRWdf653t2DpzGTlJfUs+QNSH2iMu81ij5AwCc/x01WzcBxw+YlPzp02gpCWNgI8ab9frWRquA9Zjbby7ejn0bDAwcz2H12dXYnrHd2mHZhIziDMH2Z8Op7h9xXEIrhvHUFO0Vi01/5nkg/QI6VTnj46xQnLkQhRilm8EVw7v5KzjSvgS/t3+AXEklsCcJ3MG9Zv2dCLEFfHER+C8+Ej54bH+Lkr8BD9trfd9iPND/YXv1DyKR3S3wMAb1AOpxV3kXq5NXa2rc0UIQtY0XN2Ln9Z2Cx9wl7haOhhDbIjT8yvn6N56TN2oC+EPfNX4gz4M9+Qz4Q9+hU5Uzvs/ogbWyHHzSOU93byADXoy8qT7OA1MKvPDhniRw3r6Atz9YZbnu/VAFho6peDSxJGNfby0Z3jVGp0oJ1mQFY2nIbXDgIIIIa/q/i86TJ7XpaRSUAOpx/d51WgjShFwlx6rkVYLHRExEcyQJgfbwa9OkEAD4w99rF5ceMR5sxHhw+3cAv/2MxfLOeL7QF/O73cQFaal2Isijvo0Bu/yK8aunEuc/W6s5LFQIuubgXmBPUu3j1McBUPFoYlb6Ejxji5Vr1bVsJc8VemNY38m4PfQRBHsE13/Gt8HErw4NAeshdZYKtruKXS0cie3IUmYJ7voBAMsGLnPYxJgQQxoWh9VXXBoAcOKQ5nGdqpyxL70HXssJaDwk3DD50zwJUORcjUejMvBdp3CkeYaihgf4zf/RFILmGiZ/gLpQ9JYNeotH88VF4DMuUTFpYjTuxCFwS+eC+3C5+n8bvKYFi5Vv2QDu7Amt1xh/M71lyd/I8cDjTxo8LVdSiazkfQjiOjjM5xj1AOqhqlQJtpdVl1k4EtvhJnYTbH+h5wt4te+rFo6GEPulc6WujpXES+SdMbPQF0c8FSiUVCFXUokd/sXaF2ZAjutDvNHlG0jgjwhMxj8yVRh0MRksqBv4hslfHaEP2Nri0dyV89QzSJpF5240vfqpf0wR2N2G58F/thZ8g9cYd+IQ+M3/aVkwv/xg8JRvfIqwNOQWOAaIfnoSCUPXOsSmD5QA6hHuHU6lYJoorS4VbH865GkLR0KI/RNcqatnJXGnKmfMLPQDAFxweyicADZQhXxcwQbMCPXCJ1e9MG77Jj3BaBeP5iXtmr0PMSGCvXYcB+6XfUDTqQ9aD1a/xrjOwerXXivLlVQ2Kr/EgXeYuf40BKxHoEcgEoYmwIk5AVAnf2uGrGnzLwp9vrqqXeTW0ZNiQsxJa3iYCf+Zji6TYpzfMP0rhWtVoxivOq/DNu9C4ROenQNMml2/OpmJgCGjwV8+K/xBfuJnweE6QrgTh8D/9wPtA0wEHPrOuOFcjgNaOvRrpET/Aq3am3Vz/ds66gE0YEb3GRjWeRiyldmNJ4Y6oNSCVOzP2q/VvrDvQoe+L4SYW8PhYV6pAF+7qKOR0ROxKXIA1pz/U/9K4QaWhtzCsQ4KTC30wSilp7rx6Slg7tLGQ208J7ifscaPO8AD4MHAZtGQMFHTuWCDMbDRAivfAWDkBODoD1qP4QvzTKupaUjdlxyeR267avxXlq91igiOsaCREkAjyKQySnAALDu1TLDdy8VLsJ0QYjrN8HBxEfimH4RMBNHICQCAxfLOCOeH4x9BhSjhfjFwUeCg930c9LqPoDJnnEiLAg7sMqYTUYfaBSS1c7s0Kz69fU2+IrFjOuavspcXg4V11175DqiTv5hHgfO/N27/dT/QbzBw4bS6R7AlGAMmzYYoJFw935YxeNVUYL/8V/BnLmqdPqP7DIf4zKchYGKU1IJUXCq6JHhsgP8AC0dDiOMQXDE8c4FmNTH6DUa3shqEuSxDH5dv4IxAIy4K3HKtRLd+53DB7aFxgQSGCLfzPLj9O3Su+CRtS92KcC7zWqOV4XxxEfgH9wWLnrOw7uAVxUD/wQIX5LWTvzrnfwdmvgajurf1YC8vhtPYSY1W4bv0GQCFuEbw/F5evVr0fPaCegCJUVacXiHYHuIRghi/GAtHQ4hj0bVimC8uAs7/jh5g8C5X4F47H/Rx+wol1X9AXrkVZUjXfVEGVIqBCb0y8Pj99libFYxOVc66z7+bpftYw+Finge3ZQOqR4xt5m9JbF3Tgsx1dSYx6Ang9K86h2u5TQlApvDuUQZ99bH+4zNehUgWCF7SDiguUE+XaFpfM6y74EPP5p81LaY2gnoAiUFylVznG6WnV08LR0OIY2pYR1CjQA4AcAKPuTf2qdt4Hh3Fj6KX238Q5Px3Iy4M/Ob5AIOiL+MbHzMt6uA4VMvvmOdaxCZwmdeE5/fxvHp/Xl1z9Xje9OTPEMYg6jsQLDIKotAIiAYM0V9fs4G7yrv49sa3gpft6NKxdeK1MdQDSAzKUur+5j8lYooFIyGENMRl39D8e1BRGpZc2YLEbhNwz8UTAOArfhrBVRGQKD7EEY9rekfSeAbEh9xCobgSk+/5aHoDa8CQ7hmCEmcPdKxUoociC04NZw32Gwyk/tFkjiIDV14GLuNSm91Gqy1ruoMHd3CvcP1Iq2KC+/PqrK/ZxPV713VuatDfv7/Zo7VFlAASg766ol36BQCivKMwOmi0haMhhAC1H9J7G783BxWlYeCAHsjoMxIlGenw/O2H2oStPTb5d8aqrjkGk8C1XXOxtksu/lLUEU+WjsR3IdM1CSUAeJcrMPfGPgwqSlM3nP8deGoKcHB3o3qB91b8j/rfBrb5QoEcvLOL3n2LieU03aJNcIGGRdRucK3L42N0rj4XrK/ZhK6dvt6IfsMhFoAAlAASA1ILUrE/W7v0S1xwHDaN1lNUlhDSunSsuJT0jkafcBl4b2dwP3yMug/R+fkBmFDshVG90/BAzOufV8+A73xL8B12I1DkhQBM0xy6164DEnrNxJIrW+qTwJ926b6WjuLRuuaT0U4jptO3964xuMxrTcoB6Vmg0ep4/WVgfvsZ/LhpJn9h0LXT19DOQ026nj2iOYBEr+S8ZMH2AQG08pcQq6rbMaQhkQjw7QRAqKA0Q6fgGFxJ7YcPbgbhkfvu6Kt0NVhI+m71Z7hZvgrFVcdQyRVqnjOx23jUGLs6s3ZbuTo668U12YPYWLRXsRF77xq4P9yJQ+DfX2SJUI3HC2143UCD11Rzncs9p9XmaJsaUA8g0Ss2IFawnUq/EGJddQke//X/qRMsgQnvTedDoUAO7sPlmFrsg6nF6vOOeCjwYvebep+rhDuKEu4oUAUEiuchwHka7rl0RLpnCHorMo2Kl8+6DhYZpf5BR+8lgPpksUnPjq7eraZDli3tQWxpL5o16Nt7lzdiL2fN422Sjp5AxjRfdppLrpJj8eHFWu1vD3zbYYZ/AUoAjSZXyZGlzEKIR4hDvUBi/GIwJXwKdl2vH+KZEj6FSr8QYgOMmfDecD6UpmxHgw/TUSovTOnaE7tu/2DUc96t/gxF1YcR3G4RSpw9jI6V35MEztsXLKyH3v2O6/YgRsal+kUITZO8SbPBgruBd3YRTHy4zsEmzSmsObgXqFvsUFc8OLibweu0dtLIFxehvCAHvLgd0NFb63n5B/eFt+y7eBbY/qnhvZz1JeSAehs3voXFmBtdjwG9+wOXUwyfKxKBPTML/N6v6mNkwgtAjLX72m7B9uqaapOuZ68Yz1tgs71WUFhYiKqqqla7PmMMnTp1Qm5uLralb8OSk0vA8RxETISEIQmY3n16qz23LUotSEVKfgoG+A8wKflreD/t9CVnU+h+mpcj3U/uxCGtXkPR0DFILUjFa0dfQ/aDbKOv1aFSgnWZXeu3lTNGXd24P45qHxOJgEeG19eUYwwYOgY4cah5W4LVJZcCPV46exL1rXTV07No7h5IY6/fdA5lc7Cpc8H6P9aoniS3dK7wLh6zXgN/5jjw5+UW/y7qCzKwpWshCo1QzzlsOuzMGACmTjgbvD754iLwNzMABrDQ7i1KtF8+/DIOZB/Qan86+Gn8d/R/Tb6upUkkEvj6mr7rDiWAOtR9IJy7fg6x22PBNfj248SccPq50w7RE2iunk9H+oC1BLqf5uVo95MvLtLZazjr4Cz8csfAlnKNLgb0V7nj23ThYrvN0nQ1sTkwEUT/+ly4J7E2mdKXADW8Dnv572BhPfQnTiIRRO9/3uwERSgxFbw+Y8CCd4D/W9Wy+9SgJxV+MvVQcd0XAyYCGzMRbMR4cFs2AGna8+VMe071LjYNE2ShLyTMiDIuLfFx6sdYk7JGqz1+QDzeiHnD7M/XWlqaANIQsAFZyqxGyR8A1PA1yFZmt/kEcHvGdofv+SSkLdJXJmPz2M1ILUhFUtpP+OnmCTyE8BaQ9RcDzkkf4sWw6xiu7IDRCk/9O4roo281sd4Y6nv8tBeWcOB+2QfRyAk658kZHAKtvQ7/2VrwDXv5hB7HceDPnQIa9LDpvWxxEfhf9tXvk2vo+jwPbFhp8LqNCN4XHvyepPrV15Nmg730d/W5Xn5gleXgbmeaL/kDwOYtgmjAkEZtOqcxtOL8yykRUwQTwMnhk1vtOW0RJYAGhHiEQMREWj2AbX2lkFwl1yR/AMDxHOJPxmNY4LA2n/gS4uhi/GIQMyIGz3V7gBePTICy5pr+BzDgiLcSR7yVWM7fQdy9jpiX54/oUneLxMuWrgWrqgBXViacHB3+HpxPgGCyhsJc/XMSm2qYOOp4HL8zEfyuL8AmzYZo7CSdl+JOHGpcdkXo+uaw4B3gzK9Ayinh47XJoAZj5u8JZwwsVLiX2Ji6feYkk8qwdvRazUIQBoa1Q9c63GcblYExQCaVIWFIApyYEwB18rdmyJo2/0LR1/NJCHEMj3Ztj7Q5R7EidhPaiVyNexADfvQpwYReGegdnYqp4Rk44qFo1TiZpxf4glzdPWM8D2z7VOCBDLykXX3JHGM1LGujZws0fk+SemFJXVODcix6V942vH7TUj+m2LBSd/InpDWmQTz+pM2sqt6WsQ3xR+IBqJO/d2LfccjRLeoBNML07tMxLHAYspXZCPYIbvPJH+C4PZ+EkMacRAwv9Y3DS33jsOPPHXj75Nuo4CoMP5ABSmcOp50f4rTnTYSXueDrP8NNHx7Wg7+ZYVoZE54H/6/F4GYuBH9b95aXWurqLdbuxaxPzd7NuBI2CCU3M+H5yx70UGSqt9LrM1CTaOVKKpEiVaFEXI2O1WJ0qXLB3fKLyE7ZjqLAW3DmGCpFPCrBoVTMYfB9D7jyIs35A1TSVrmvzbZwOVhVJfjPErQOiZ6eaoWAtMlVciz+bbFmGzgePFYlr8LEsIkO8dnekEUTwL179+L8+fPIzs6GWCxGUlKSJZ++RWRSmUO9OOp6PuNPxqOGr3GYnk9CiG7TIqdhWuQ07PhzBz4/+x9cLc3Uv6NIHQZcdyvHI9GX8UxRRyy9G2jWhIW/dd30Xiue1x6GNeSZWWBePoJldRo67dNbvTdzshKADyr7TMLD8u/R7uFRuFRcReeQdrjrXIlUj1Lt+5is7qGCQKm7vT4ljc/ngWEl7VHkVIVyMYfpBb6YVxhg+PcwZ3mXfoPhFK2uG8uVl2ottrGV3r+U/BStPYB58DiXf87hPt8smgBWV1dj0KBBiIiIwNGjAiUAiM1ILUiFslKJxNGJcJe4O0zPJyHEsGmR0zDVdyS2fTAB8cG3wBs7SsmAb31L8K1PCZ4s7gB3ToS4e17NKyMj5OdvW/b45rp0Fhg7CfyV81rJX66kEoc9FTjl6Y4rvh3gKa5EZU0G8qt3oqTmuPqk2qmR51Fm2vM3vd8MOO71QPPjyuAcrO2Sg0eV7eFfJcFfC/2052MyBrY0AfytG8LD403V1uODkxP4nYnah0eMq/+3EfUpifVZNAGcOlXdBXzs2DFLPi1ppr8d+5tW4ef1w9dbLyBCiM1hXj6Y/tR7GLZjPY54FCPTpQJngl2QVnHbiAcDP3vfB6DuzfKtEuPZQi+040UYqfC02OIRk12/gpqtm4DjB3DB7SG2+hZAKa6Bf6UzkgIK6xO06gzcrv7Y8vExoEIMHKtNCnf4FeMRpTtmFfjVDxfzPPhTh9U1FvVei4HNW6ypvccXF4Hf9YVW6Zumu3JYemGHsXJUOVptDAz9/ftbIRrrojmApJHUgtRGyR8A7Lq+C7N7zqbdPwghjYiGjkHnXv0wu0FPz5qza/DxhWYkPQwodK7Gp50LAAD/7pyHKJUroh+64wlFh5b3DupQA4Z0zxCUOHugY6USPRRZ6rl5AnIlldjtXYSzUhXEPEPXynboeekrbO5RgEvuZfUJn4Gta62GAWc6PMSZDlkADzymkCI+JxDRv/1s+LE8D9a+g6YXz5gtCG2VXCXH6rOrtdrfiX3HIUe4bD4BrKqqalTwmTEGV1dXzb9bS921W/M5bNGmy5sE21PyU9DPv5/J13XU+9la6H6aF91P0zFvX8C7vhjt0tilmN1rNnZm7sT+P/ejpLwEOaXavS66LwhclpbhcvsybPEvQvsqhv4PpejzwB13XSvgVylBVJkUAx64mzyPUDM3z8VT0+ZdrsCw24n4o93vuOxeimpwcOecUMV4ZLpVaid2QsmeuV4+hhLJliSaDDjVUYUJnhl4utgTn94Ma3KcafXuMT9Zo/eG0+NPgu/dH3xBLpif/QzxZj/I1qpuAQDRftEO+d5v8U4gW7duxffff6/3nHXr1qFz586an48dO4akpCSjFoHs3LkTu3fX79sXEhKCNWu0CziSlrurvIsu67oIHkt+KRkDOw+0cESEkLZgys4p2J0uvP+q0QSSnuHF7THqvifuO1XjnqQaJaJqZLqV4yFfg6J21fCsdsLzBX5wgRMuu6kAAMXtvJHiFYR2zB8Puevg+ApInbpDWXMOZbjRshhbigf+mu+DaUU+uNuuAtntynFPUq21CvjR+x5IlT7EVv+iliWdPPBkcQdMKPZSDw3XuKDDnNdwP+k/mt69jq8tg/TJv5jrN7QqodehE3NC9t+yEegRaKWorKfFCaBSqcSDBw/0nuPv7w+xuL6zsTkJoK4ewMLCQlRXt97GzYwxBAQEIC8vzyG2hgKAiC8joKpSabUP6jQIe8fvFXiE8RzxfrYmup/mRffTvITuZ2pBKo7cOoJbylvYe7Nlf0+axdLDsgaezwVhcIIUYpTj8cJ8iDkGuUsl+qncMafAH53cOwGKe7ovwBjw+JPA8YPIlVTiXG35mDvOldjnVQy5S5Vpvy8PxHkMxKsj30O0uIvd9e4ZklqQinHfjdNqfyP6DSyNXWqFiFpOLBZbdys4Dw8PeHh4tPQyOkkkEkgkEsFjlvhDzfO8Q3wgbLq0STD5A4A5PeaY7R44yv20FLqf5kX307wa3s9o32hE+0YDAN6OfRvv/v4uDt462PpBWHhkL8olCM9lAKc83ZDmOwae4kGo5Iuh4tIgFfWGVBQJAFhyZQsGFaVphzv1RfCfrdW+MGNg85aAhaofzx0/iE5Vzogr8dKcsiwnUJMUXnZ7iAzXMjwM6oKzD9K1Sp9oXx/48cFZ/PjdOAwKGIRPnvgEMql3m3k/rDu3TrDdiTm1md+xuSw6B7CoqAgqlQpFRUXgOA7Z2dkAgICAALi4uFgyFNLEfy7oroPliKujCCGtRyaVIXFMIuQqOY7cOoKbypv47e5vuKYwsOWcLanr6eOB4DJn9Ow6CFP7vYjRQaPBFxdhdmEu/qjxwud/luFeqR+kTupt0LxRgblpOwSTPzAGePvr3Lu3bjEGd+KQzvqDdUlhXIkXIBJB9PLnyHWuxOu/vo7TeaeN+tVO553GwO0DMTV8KtYNF06c7IlcJceRO0cEj/m6md6DZu8smgDu2LEDx48f1/y8ZMkSAMA//vEP9OrVy5KhkAZSC1JRXFEseCwuOM4hV0cRQlqfTCrDrF6zND+nFqQiJT8FHM9hY+oGFFbcs60VtjwQUC7GOEVH9HjoBqWkBgMeSBFd6g7R2GVgQVEA6kugDAbwSHceVwtLUVJWA8/rqei+ax2cdBVf5nmwqgpg0uzGe/MCtYsxOtVvIdcw+WMMbOlaICdbcHWuDMCe8XuQWpCKNWfX4KT8pOEeQQA7r+/EqdxTSJ6ebNLtshUp+Sk6j43uOtqCkdgWiyaACxcuxMKFzdhv0QbJVXJkKbMQ4hHSZhKjr9O/FmyXMAk2jRZeFUwIIeYW4xejKTc1v898HDqQgM2XvwQYjyiVO77rWoHbfEnzLmpC4uhWAXjViCHlnNCxSoxu5a7wrhFjhK4ahQJ18Oo4iRii/N3BFxeB2/WR/h1Laq8jioxCDQDs/Up9fu1ijAdePuDTLwr3DlZVgBkowBzjF4Nvxn0DuUqOxLREfHrZcAHoHFUOlp5YisGywRjgP6DNfO4BwMweM9vU79NcNl8GxpZsz9iOJSeXgOM5iJgICUMS2sQG0vcr7gu2jw5y3G9GhBDrG/P0Eowe9KImoYn38kFqQSq2ZmxFvuIOIiWd0MU7AkpxDYrKi1B8PxeZ6Ueh4mtwr3YV8F8L/eDKN1gFHBiFszWSBquAKyF1ioSIuYHnq/DGrWI8L883PkgmXAePLy5S7xXsJ1MfK5AbTP4aXsdp7CTwsY8DhblgfjJIe0XhQW4u4CcTLNVSl4AaU4BZJpXh3UHvYm7vuTiXfw6fXf4M5wvP6zx/S8YWbMnYAkC9aCJ+YLze69saXcWf34x50wrR2A5KAI0kV8k1yR8AcDyH+JPxGBY4zO6/QUyLnIafbv2k1T41wjY27yaEOK6mCU3DXkIhnPSQ9jBok16xP24/wH/P5uJeef1QrI+4BnOjPPEIdgHGJICMAaMnQjRyglbyx504pL0Xbq9+2okbY8CCdyBydRXssav73RvWqDNnIea6Pe7Hh403uoD3xxc+xrn8c9gZt7PZz2cNcpUcq5JXabUnjE6ATCpz2AUgACWARstSZmkVkKzha5CtzLb7BHB00GhEeUfh8r3LmrYBfgOoB5AQYnd07kPbIEF6tGt7xAZKNXPzOro6oaevG5xEDOj5N3DDnwZ/OQXYv0Nwrh2rqtC5x63WHD2eB//1/4G9/7lg4iaKjjXf79gC8QPjMbPHTDz17VMoKi/Se+6p3FN4au9T+GmSdseBrUnJTxGc7xjUIcgK0dgWSgCN5CZ2E2w/kXMCg2WDLRyNeW28uBFp9+pXpL3Q8wWsfGylFSMihBDTGTMMWjc3T4goNAIIjQDn5aOdsIVG6H9yoaFejgMKc82auLXGXrsyqQwXZ17Ejj934Psb3+O4/LjOcy/du4THvnkMp547ZdYYzO2U3LbjsyaRtQOwF6XVpYLtn1z4BHKV3MLRmM/GixuxMnllo29Im9M32/XvRAgh5iAaOgai9z+HaNEq9f8OHWP4QXVz9BpdqPEcPRYZZdMFlqdFTsO2cdvwRvQbes/LfpCNXl/1wuFbhy0UWfPIVXJszdiq1c7A8GiXR60QkW2hBNBIIR4hgu08eJzLP2fhaMxD19yIuqFtQghxdM1N2Orm6EFU+/Hagjl61hY/MB4jAkfoPUdRqcCcQ3MwavcoC0VlvCxlluDw7yt9XnHIrd+aogTQSDKpDM93f97aYZiVrjeHCCIEewRbPiBCCGkDTOo5tFFbntpisCcQANJL0vHEridsavRo2cllWm0iiDC391wrRGN7KAFshjdj3gRrUlCKgdntThk/ZQlP4J3dc7bdL2whhBBrsoehXmPFD4zH2eln4e/qr/e8a4prGLh9ILZnbLdQZLpN+XEKbty/odVOn2/1KAFsBplUhsnhkxu1TQ6fbJcvJrlKjqSrSYLHgjxodRQhhJB6MqkM558/jx4dexg8d9GJRVadF5hakIrfc38XPNa0mocjowSwGeQqOfbc2NOobe+NvTbV5W0sXcO/ADDAf4CFoyGEEGIPjkw+gu4duxs8b86hOZj6o3VqyW66pHsHqye6PGHBSGwbJYDNoK8WoL25VHhJsH1c8Di9RVYJIYQ4tl8m/4KkMUnwcdE/vH0q9xR6ftXTop0kcpUcP2T9IHisR8ceVN+2AUoAmyHEIwQi1viWOTEnu1swIVfJsTJZu87fCz1fwGejP7NCRIQQQuzJ6KDRuDjzIkYGjtR73v3K+xadF/j6r68Ltkd4RuDI5CMWicFeUALYDDKpDAlDEuDEnACok781Q9bY3RxAXXMzIjwNFDglhBBCGtj81GYEuAUYPG/RiUVILUht1VhSC1JxOu+04LG3+r3Vqs9tjygBbKbp3afj9HOnsWvcLpx+7jSmd59u7ZCa7eido4LtBWUFFo6EEEKIvTv313OYGm54vl/c93HYeHFjq8Wx/vx6ncfstVpHa6IE0AQyqQyDZYPtrucPUA//Hrkj3A0+sqv+rnxCCCFEyLrh63B2+ll0cO6g97yVySvx+tHXzT4vUN9n26SwSXb5ed3aKAF0MIlpiYLtwzoPo8UfhBBCTCaTynB19lW4ObnpPW/vzb1mnxe4Onm1zmNvx75ttudpSygBdCBylRyfXRZe5PHB4x9YOBpCCCFt0fUXr2N8yHiD5y06sQhrz65t8fMtP7Uc3978VvDY892fp94/HSgBbAG5So5T8lN2UwcwS5kFDtpFMF+JeoXeIIQQQszm01Gf4seJPxo8b/2F9QhLDDP5c3TWwVn48uqXOo+/GfOmSdd1BJQAmmh7xnY88s0jmLp/Kh755hGb2PrGEDexcLd8XGichSMhhBDS1sX4xWB57HKD55Vz5Ri4fSCG7RyGHX/uMOracpUcz/7wLH6584vOc5bHLqfODT0oATSBXCXHkpNLNEWhOZ5D/Ml4m+8JXJsi3NVeVl1m4UgIIYQ4glf7vorlscvBwAyee+P+Dbz121uI/DJSZ8kYuUqO14++joHbB+os+QIAb0S/gVf7vmpy3I5AbO0A7JG+HUFs9dtGakEqjucc12pnYHZXyJoQQoj9eLXvq5gYNhH/Tv03vs742uD5qmoV4r6Pw7iQcXi1z6tIzkuGskKJ/Vn7cf3+dYOPf6HnC4gfGG+O0Ns0SgBNEOIRotVm64lUcl6yYHtcSJzNJq2EEELaBplUhjVD1+DNmDcxdMdQlHPlBh+zP2s/9mftb9bz9PPth5WPae90RbTRELAJ8kvztdp48ILttuKk/KRg+/w+8y0cCSGEEEclk8pwc+5NBLoHtsr1N43a1CrXbYsoATSBrt60lPwUC0dinNSCVMHdP0Z2GUm1/wghhFjcmRlnkDQmCf39zLdDxwdDP6ARrWagBNAEoR1CBdttdQj466vCcy78XP0sHAkhhBCiNjpoNPZN3Iez088i0jPS5OuMDRqLs9PP2uXWrNZEcwBN4CYRLqfiLnG3cCTGuV91X7i9UridEEIIsRSZVIajU44itSAV/0r+F07mCk9Zaspd7I5jU45Rr5+JKAE0QYhHCERM1GglsBNzstkeQGWFUrB9aoThzbsJIYQQS4jxi8GOuB2Qq+TIVmYj2CMY+aX5SMlPgaJcgdSCVFRylSitKsXEbhNpDnsLUQJoAplUhoQhCYg/GY8avgZOzAlrhqyxyW8hqQWpOJV7Squ9e8fuGB002goREUIIIbrJpDLN56lMKqO56q2EEkATTe8+HcMCh+Fc/jnw4DHAf4C1QxL02tHXBNtjfOkNRQghhDgqSgBb4Pjd41hyYgk4cBBBhIShCTY1CTW1IBXZD7IFj9H8P0IIIcRx0SpgE8lVciw+sRgcareDA4fFJxbb1HZwR24f0XmM5v8RQgghjosSQBOl5KeAB9+ojQePc/nnrBSRNl1lXrpKu9L8P0IIIcSBWXQIuKCgAHv27EFaWhoUCgW8vLwwdOhQTJo0CWKxfY1GZ9/Pbla7NZRWlwq27xm/x8KREEIIIcSWWDTrksvl4Hke8+bNQ0BAAO7cuYNNmzahvLwcs2bNsmQoLVbBVTSr3dLkKjlWn12t1b48drlNrlYmhBBCiOVYNAGMjo5GdHS05md/f3/I5XIcOnTI7hLAUV1HYX3qeq32Gr7G8sEIyFJmNapTWKevb18rREMIIYQQW2L1cdfS0lJIpVKdx6uqqlBVVaX5mTEGV1fXVh8yZowBACQSCXie1zoe2zkWb/R/AydyTjRqP5l3EvOr58PX1bdV4zOkl18v9O/UX6tYdU+/npBIJBaPx9D9JM1D99O86H6aF91P86L7aV5t5X62NA9ivBV/+7y8PMTHx2PmzJkYNWqU4Dk7d+7E7t27NT8/9thjePPNNy0VIiGEEEJIm2OWVcBbt27F1KlT9f6Xk5PT6DHFxcVYtWoVHn30UZ3JHwA888wzSEpK0vz38ssvN+oRbC1lZWWIj49HWVlZqz+XI6D7aV50P82L7qd50f00L7qf5kX3U80s46jjx4/H8OHD9Z7j7++v+XdxcTFWrFiByMhIzJs3T+/jJBKJVYYseZ5HVlaWXXcP2xK6n+ZF99O86H6aF91P86L7aV50P9XMkgB6eHjAw8PDqHPrkr+QkBAsWLAAIhGVIiSEEEIIsSSLLgIpLi7Ge++9B19fX8yaNQtKpVJzzNPT05KhEEIIIYQ4LIsmgJcuXUJeXh7y8vLwyiuvNDq2c+dOS4ZikEQiweTJk60y/NwW0f00L7qf5kX307zofpoX3U/zovupZtVVwIQQQgghxPJoAh4hhBBCiIOhBJAQQgghxMFQAkgIIYQQ4mAoASSEEEIIcTBW3wvYVh08eBA//PADFAoFgoKC8OKLL6Jbt27WDsvuXL16Ffv27UNWVhZKSkqwaNEixMbGWjssu/Xtt98iOTkZOTk5cHZ2RkREBJ5//nnIZDJrh2aXDh06hEOHDqGwsBAAEBgYiMmTJyMmJsbKkdm/7777Dtu2bcPTTz+NOXPmWDscu9R0K1QAkMlkWL9+vXUCagOKi4vx9ddf48KFC6ioqEBAQAAWLFiAsLAwa4dmcZQACvj999+xefNmvPzyywgPD8f+/fuxatUqrF+/Hh06dLB2eHaloqICwcHBGDFiBD744ANrh2P3rl69iieffBJhYWGoqanB9u3bsXLlSnz00UdwcXGxdnh2x8vLCzNmzECnTp3A8zyOHz+OhIQEJCQkoEuXLtYOz27duHEDhw8fRlBQkLVDsXtdunTBu+++q/mZNk8wnUqlwrvvvotevXph2bJl8PDwQG5uLtzd3a0dmlVQAijgxx9/xMiRI/HEE08AAF5++WWcP38ev/76K/7yl79YNzg7ExMTQ70pZvTOO+80+nnhwoV46aWXkJmZiZ49e1opKvs1YMCARj9Pnz4dhw4dwvXr1ykBNFF5eTk++eQTzJ8/H3v37rV2OHZPJBLRRglm8v3338Pb2xsLFizQtPn5+VkxIuuiBLCJ6upqZGZmNkr0RCIRoqKicO3aNesFRoiA0tJSAIBUKrVyJPaP4zj88ccfqKioQEREhLXDsVuff/45YmJi0KdPH0oAzSAvLw/z58+HRCJBREQEZsyYAR8fH2uHZZdSUlLQt29ffPTRR7h69Sq8vLwwZswYjBo1ytqhWQUlgE0olUpwHKf1jcvT0xNyudw6QREigOM4JCUlITIyEl27drV2OHbr9u3beOedd1BVVQUXFxcsWrQIgYGB1g7LLp06dQpZWVl4//33rR1KmxAeHo4FCxZAJpOhpKQEu3fvxv/+7//iww8/hKurq7XDszsFBQU4fPgwxo0bh2eeeQY3b97El19+CbFYjOHDh1s7PIujBJAQO5WYmIg7d+7gn//8p7VDsWsymQxr165FaWkpTp8+jQ0bNmDFihWUBDZTUVERkpKSsHz5cjg7O1s7nDah4fSZoKAgTUL4xx9/YMSIEVaMzD5xHIewsDDMmDEDABASEoLbt2/j8OHDlAASwMPDAyKRCAqFolG7QqGgeRjEZiQmJuL8+fNYsWIFvL29rR2OXROLxQgICAAAhIaG4ubNmzhw4ADmzZtn5cjsS2ZmJu7fv4/4+HhNG8dxSE9Px8GDB7Ft2zZawNBC7u7ukMlkyMvLs3Yodqljx45aX+wCAwNx5swZK0VkXZQANiEWixEaGoq0tDRNuRKO45CWloaxY8daOTri6HiexxdffIHk5GS89957Dj2BubVwHIeqqiprh2F3oqKitFb6b9y4ETKZDBMnTqTkzwzKy8uRl5eHoUOHWjsUuxQZGak1lUsul8PX19dKEVkXJYAC4uLisGHDBoSGhqJbt244cOAAKioqHLKLuKXq/mDVKSgoQHZ2NqRSKU1kNkFiYiJOnjyJJUuWwNXVVdNT7ebmRsNuJti2bRuio6Ph4+OD8vJynDx5ElevXtVabU0Mc3V11ZqL2q5dO7Rv357mqJpo8+bNGDBgAHx8fFBSUoKdO3dCJBJhyJAh1g7NLo0bNw7vvvsu9u7di8GDB+PGjRv45ZdfHLa3n/E8z1s7CFt08OBB7Nu3DwqFAsHBwXjhhRcQHh5u7bDszpUrV7BixQqt9mHDhmHhwoVWiMi+TZ06VbB9wYIF9AXFBBs3bkRaWhpKSkrg5uaGoKAgTJw4EX369LF2aG3Ce++9h+DgYCoEbaL169cjPT0dDx48gIeHB7p3747nnntOM2WBNN+5c+ewbds25OXlwc/PD+PGjXPYVcCUABJCCCGEOBialEEIIYQQ4mAoASSEEEIIcTCUABJCCCGEOBhKAAkhhBBCHAwlgIQQQgghDoYSQEIIIYQQB0MJICGEEEKIg6EEkBBCCCHEwVACSAghhBDiYCgBJIQQQghxMJQAEkIIIYQ4GEoACSGEEEIcDCWAhBBCCCEOhhJAQgghhBAHQwkgIYQQQoiDoQSQEEIIIcTBUAJICCGEEOJg/h9Ye0iN8cQI5QAAAABJRU5ErkJggg==", "text/html": [ "\n", "
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\n", " Figure\n", "
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\n", " " ], "text/plain": [ "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import numpy as np\n", "import matplotlib.pyplot as plt\n", "from sklearn.linear_model import LinearRegression\n", "\n", "from sklearn.model_selection import train_test_split\n", "from sklearn.metrics import r2_score, mean_squared_error\n", "from sklearn.pipeline import make_pipeline\n", "from sklearn.preprocessing import PolynomialFeatures\n", "\n", "\n", "polynomial_degree = 8\n", "\n", "linear_model = LinearRegression()\n", "polynomial_model = make_pipeline(PolynomialFeatures(degree=polynomial_degree), LinearRegression())\n", "\n", "\n", "muestras_de_entrenamiento = 10\n", "\n", "x_train, x_test, y_train, y_test = train_test_split(x, y, train_size=muestras_de_entrenamiento)\n", "\n", "# Fit\n", "linear_model.fit(x_train, y_train)\n", "polynomial_model.fit(x_train, y_train)\n", "\n", "\n", "\n", "# Create a figure and two subplots\n", "fig, axs = plt.subplots(2)\n", "\n", "# Plot on the first subplot\n", "axs[0].plot(x_test, y_test , '.', label='Fuera de muestra')\n", "axs[0].plot(x_train, y_train , 'o', label='Dentro de muestra') \n", "axs[0].plot(x, linear_model.predict(x) , '.g', label='Ajuste por modelo lineal') \n", "axs[0].set_ylim([-2, 2])\n", "\n", "axs[0].set_title('Modelo lineal')\n", "\n", "# Plot on the second subplot\n", "axs[1].plot(x_test, y_test , '.', label='Fuera de muestra')\n", "axs[1].plot(x_train, y_train , 'o', label='Dentro de muestra') \n", "axs[1].plot(x, polynomial_model.predict(x) , '.g', label='Ajuste por modelo lineal') \n", "axs[1].set_title(f'Modelo polinomial de orden {polynomial_degree}')\n", "axs[1].set_ylim([-2, 2])\n", "\n", "# Adjust layout\n", "plt.tight_layout()\n", "\n", "\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Curvas de Ein y Eout vs la cantidad de muestras de entrenamiento " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Datos\n", "Lo mismo de antes pero con más muestras" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [], "source": [ "# Generate data\n", "N=10000\n", "np.random.seed(0)\n", "#x = np.linspace(0, 2*np.pi, N)\n", "x = np.random.rand(N) * 2*np.pi\n", "y = np.sin(x) + np.random.normal(0, 0.1, N)\n", "\n", "# Reshape x to be a column vector\n", "x = x.reshape(-1, 1)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Curvas de error" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "a29cdf800c2e4cf9880f6028c87b4f4b", "version_major": 2, "version_minor": 0 }, "image/png": 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