{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# TMLE Example Notebook" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This notebook demonstrates the issue of using uplift curves without knowing true treatment effect and how to solve it by using TMLE as a proxy of the true treatment effect." ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "ExecuteTime": { "end_time": "2019-11-11T22:36:37.694257Z", "start_time": "2019-11-11T22:36:37.346428Z" }, "pycharm": { "is_executing": false } }, "outputs": [], "source": [ "%reload_ext autoreload\n", "%autoreload 2\n", "%matplotlib inline" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "ExecuteTime": { "end_time": "2019-11-11T22:36:38.451348Z", "start_time": "2019-11-11T22:36:37.696398Z" }, "pycharm": { "is_executing": false } }, "outputs": [], "source": [ "import logging\n", "from matplotlib import pyplot as plt\n", "import numpy as np\n", "import pandas as pd\n", "from sklearn.model_selection import train_test_split, KFold\n", "import sys\n", "import warnings\n", "warnings.simplefilter(\"ignore\", UserWarning)\n", "\n", "from lightgbm import LGBMRegressor" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "ExecuteTime": { "end_time": "2019-11-11T22:36:38.477189Z", "start_time": "2019-11-11T22:36:38.453192Z" }, "pycharm": { "is_executing": false } }, "outputs": [], "source": [ "sys.path.append('../')" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "ExecuteTime": { "end_time": "2019-11-11T22:36:39.962314Z", "start_time": "2019-11-11T22:36:38.479150Z" }, "pycharm": { "is_executing": false } }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Using TensorFlow backend.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "0.4.1\n" ] } ], "source": [ "import causalml\n", "\n", "from causalml.dataset import synthetic_data\n", "from causalml.inference.meta import BaseXRegressor, TMLELearner\n", "from causalml.metrics.visualize import plot\n", "from causalml.propensity import calibrate\n", "\n", "print(causalml.__version__)" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "ExecuteTime": { "end_time": "2019-11-11T22:36:40.019168Z", "start_time": "2019-11-11T22:36:39.963865Z" } }, "outputs": [], "source": [ "logger = logging.getLogger('causalml')\n", "logger.setLevel(logging.DEBUG)\n", "plt.style.use('fivethirtyeight')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Generating Synthetic Data" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "ExecuteTime": { "end_time": "2019-11-11T22:36:40.359970Z", "start_time": "2019-11-11T22:36:40.021276Z" } }, "outputs": [], "source": [ "# Generate synthetic data using mode 1\n", "y, X, treatment, tau, b, e = synthetic_data(mode=1, n=1000000, p=10, sigma=5.)" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "ExecuteTime": { "end_time": "2019-11-11T22:36:40.550962Z", "start_time": "2019-11-11T22:36:40.362773Z" } }, "outputs": [], "source": [ "X_train, X_test, y_train, y_test, e_train, e_test, treatment_train, treatment_test, tau_train, tau_test, b_train, b_test = train_test_split(X, y, e, treatment, tau, b, test_size=0.5, random_state=42)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Calculating Individual Treatment Effect (ITE/CATE)" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "ExecuteTime": { "end_time": "2019-11-11T22:36:43.338139Z", "start_time": "2019-11-11T22:36:40.553261Z" } }, "outputs": [], "source": [ "# X Learner\n", "learner_x = BaseXRegressor(learner=LGBMRegressor())\n", "learner_x.fit(X=X_train, treatment=treatment_train, y=y_train)\n", "cate_x_test = learner_x.predict(X=X_test, p=e_test, treatment=treatment_test).flatten()" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "ExecuteTime": { "end_time": "2019-11-11T22:36:43.701075Z", "start_time": "2019-11-11T22:36:43.340126Z" } }, "outputs": [ { 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "alpha=0.2\n", "bins=30\n", "plt.figure(figsize=(12,8))\n", "plt.hist(cate_x_test, alpha=alpha, bins=bins, label='X Learner')\n", "plt.hist(tau_test, alpha=alpha, bins=bins, label='Actual')\n", "\n", "plt.title('Distribution of CATE Predictions by X-Learner and Actual')\n", "plt.xlabel('Individual Treatment Effect (ITE/CATE)')\n", "plt.ylabel('# of Samples')\n", "_=plt.legend()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Validating CATE without TMLE" ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "ExecuteTime": { "end_time": "2019-11-11T22:36:43.758232Z", "start_time": "2019-11-11T22:36:43.702586Z" } }, "outputs": [], "source": [ "df = pd.DataFrame({'y': y_test, 'w': treatment_test, 'tau': tau_test, 'X-Learner': cate_x_test, 'Actual': tau_test})" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Uplift Curve With Ground Truth" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "If true treatment effect is known as in simulations, the uplift curve of a model uses the cumulative sum of the treatment effect sorted by model's CATE estimate.\n", "\n", "In the figure below, the uplift curve of X-learner shows positive lift close to the optimal lift by the ground truth." ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "ExecuteTime": { "end_time": "2019-11-11T22:36:45.464112Z", "start_time": "2019-11-11T22:36:43.760390Z" } }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plot(df, outcome_col='y', treatment_col='w', treatment_effect_col='tau')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Uplift Curve Without Ground Truth" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "If true treatment effect is unknown as in practice, the uplift curve of a model uses the cumulative mean difference of outcome in the treatment and control group sorted by model's CATE estimate.\n", "\n", "In the figure below, the uplift curves of X-learner as well as the ground truth show no lift incorrectly." ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "ExecuteTime": { "end_time": "2019-11-11T22:36:47.550307Z", "start_time": "2019-11-11T22:36:45.466089Z" } }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plot(df.drop('tau', axis=1), outcome_col='y', treatment_col='w')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## TMLE " ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "ExecuteTime": { "end_time": "2019-11-11T22:36:47.607950Z", "start_time": "2019-11-11T22:36:47.552407Z" } }, "outputs": [], "source": [ "n_fold = 5\n", "n_segment = 5" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### TMLE Model Training" ] }, { "cell_type": "code", "execution_count": 14, "metadata": { "ExecuteTime": { "end_time": "2019-11-11T22:36:47.665100Z", "start_time": "2019-11-11T22:36:47.609673Z" } }, "outputs": [], "source": [ "kf = KFold(n_splits=n_fold)" ] }, { "cell_type": "code", "execution_count": 15, "metadata": { "ExecuteTime": { "end_time": "2019-11-11T22:37:06.035592Z", "start_time": "2019-11-11T22:36:47.667060Z" } }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "WARNING: Logging before flag parsing goes to stderr.\n", "I1111 14:36:47.735486 4599510464 tmle.py:124] Estimating ATE for group 1.\n", "I1111 14:36:47.737114 4599510464 tmle.py:129] Calibrating propensity scores.\n", "I1111 14:36:53.161776 4599510464 tmle.py:136] Training an outcome model for CV #1\n", "I1111 14:36:55.997822 4599510464 tmle.py:136] Training an outcome model for CV #2\n", "I1111 14:36:58.315356 4599510464 tmle.py:136] Training an outcome model for CV #3\n", "I1111 14:37:00.735098 4599510464 tmle.py:136] Training an outcome model for CV #4\n", "I1111 14:37:03.180316 4599510464 tmle.py:136] Training an outcome model for CV #5\n", "I1111 14:37:05.726341 4599510464 tmle.py:149] Training the TMLE learner.\n" ] }, { "data": { "text/plain": [ "(array([0.48793413]), array([0.44969964]), array([0.52616862]))" ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ "tmle = TMLELearner(learner=LGBMRegressor(num_leaves=64, learning_rate=.05, n_estimators=300), \n", " cv=kf, calibrate_propensity=True)\n", "\n", "ate_all, ate_all_lb, ate_all_ub = tmle.estimate_ate(X=X_test, p=e_test, treatment=treatment_test, y=y_test)\n", "\n", "ate_all, ate_all_lb, ate_all_ub" ] }, { "cell_type": "code", "execution_count": 16, "metadata": { "ExecuteTime": { "end_time": "2019-11-11T22:37:24.305226Z", "start_time": "2019-11-11T22:37:06.037844Z" } }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "I1111 14:37:06.182612 4599510464 tmle.py:124] Estimating ATE for group 1.\n", "I1111 14:37:06.183984 4599510464 tmle.py:129] Calibrating propensity scores.\n", "I1111 14:37:11.492189 4599510464 tmle.py:136] Training an outcome model for CV #1\n", "I1111 14:37:13.826500 4599510464 tmle.py:136] Training an outcome model for CV #2\n", "I1111 14:37:16.256622 4599510464 tmle.py:136] Training an outcome model for CV #3\n", "I1111 14:37:18.831965 4599510464 tmle.py:136] Training an outcome model for CV #4\n", "I1111 14:37:21.290154 4599510464 tmle.py:136] Training an outcome model for CV #5\n", "I1111 14:37:23.885609 4599510464 tmle.py:161] Training the TMLE learner for segment 0.\n", "I1111 14:37:23.973082 4599510464 tmle.py:161] Training the TMLE learner for segment 1.\n", "I1111 14:37:24.060353 4599510464 tmle.py:161] Training the TMLE learner for segment 2.\n", "I1111 14:37:24.140305 4599510464 tmle.py:161] Training the TMLE learner for segment 3.\n", "I1111 14:37:24.226202 4599510464 tmle.py:161] Training the TMLE learner for segment 4.\n" ] }, { "data": { "text/plain": [ "(array([[0.21359494, 0.37680156, 0.47705638, 0.54578996, 0.83998392]]),\n", " array([[0.1172803 , 0.30158022, 0.40692295, 0.45495861, 0.74524376]]),\n", " array([[0.30990959, 0.4520229 , 0.54718981, 0.63662131, 0.93472409]]))" ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" } ], "source": [ "tmle = TMLELearner(learner=LGBMRegressor(num_leaves=64, learning_rate=.05, n_estimators=300), \n", " cv=kf, calibrate_propensity=True)\n", "\n", "ate_actual, ate_actual_lb, ate_actual_ub = tmle.estimate_ate(X=X_test, p=e_test, treatment=treatment_test, y=y_test, segment=pd.qcut(tau_test, n_segment, labels=False))\n", "\n", "ate_actual, ate_actual_lb, ate_actual_ub" ] }, { "cell_type": "code", "execution_count": 17, "metadata": { "ExecuteTime": { "end_time": "2019-11-11T22:37:45.681370Z", "start_time": "2019-11-11T22:37:24.307861Z" } }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "I1111 14:37:24.454401 4599510464 tmle.py:124] Estimating ATE for group 1.\n", "I1111 14:37:24.456296 4599510464 tmle.py:129] Calibrating propensity scores.\n", "I1111 14:37:29.791435 4599510464 tmle.py:136] Training an outcome model for CV #1\n", "I1111 14:37:32.308604 4599510464 tmle.py:136] Training an outcome model for CV #2\n", "I1111 14:37:35.668303 4599510464 tmle.py:136] Training an outcome model for CV #3\n", "I1111 14:37:38.855995 4599510464 tmle.py:136] Training an outcome model for CV #4\n", "I1111 14:37:41.786494 4599510464 tmle.py:136] Training an outcome model for CV #5\n", "I1111 14:37:45.212327 4599510464 tmle.py:161] Training the TMLE learner for segment 0.\n", "I1111 14:37:45.310906 4599510464 tmle.py:161] Training the TMLE learner for segment 1.\n", "I1111 14:37:45.402297 4599510464 tmle.py:161] Training the TMLE learner for segment 2.\n", "I1111 14:37:45.473446 4599510464 tmle.py:161] Training the TMLE learner for segment 3.\n", "I1111 14:37:45.560100 4599510464 tmle.py:161] Training the TMLE learner for segment 4.\n" ] }, { "data": { "text/plain": [ "(array([[0.28326254, 0.41720096, 0.52000234, 0.5567797 , 0.67356684]]),\n", " array([[0.19190312, 0.33921252, 0.44215021, 0.46706366, 0.58111721]]),\n", " array([[0.37462195, 0.49518941, 0.59785446, 0.64649575, 0.76601646]]))" ] }, "execution_count": 17, "metadata": {}, "output_type": "execute_result" } ], "source": [ "tmle = TMLELearner(learner=LGBMRegressor(num_leaves=64, learning_rate=.05, n_estimators=300), \n", " cv=kf, calibrate_propensity=True)\n", "\n", "ate_xlearner, ate_xlearner_lb, ate_xlearner_ub = tmle.estimate_ate(X=X_test, p=e_test, treatment=treatment_test, y=y_test, segment=pd.qcut(cate_x_test, n_segment, labels=False))\n", "\n", "ate_xlearner, ate_xlearner_lb, ate_xlearner_ub" ] }, { "cell_type": "markdown", "metadata": { "ExecuteTime": { "end_time": "2019-11-08T18:57:24.230391Z", "start_time": "2019-11-08T18:57:24.147391Z" } }, "source": [ "### Uplift Curve with TMLE as Ground Truth" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "By using TMLE as a proxy of the ground truth, the uplift curves of X-learner and the ground truth become close to the original using the ground truth." ] }, { "cell_type": "code", "execution_count": 18, "metadata": { "ExecuteTime": { "end_time": "2019-11-11T22:37:45.972840Z", "start_time": "2019-11-11T22:37:45.683918Z" } }, "outputs": [ { "data": { "text/plain": [ "Text(0,0.5,'Lift in GB')" ] }, "execution_count": 18, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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yDOhMmJs/gyGufNpPlIYkPgFoxYoV3H///QBcd911BAUF8dVXX9G7d28+/PBDzp49y/fff1+4wLhBgwaFx4aEhGAwGIiLi7vscYcNG1b453r16jFlyhT69evH0qVL0emK/mYQQgjhZaqK7siBglo7v61Dl3buooe4q9XA2bEHzk49cV3RgO9P2pmzLZtNySnFHlMnVM+TrUJ5qHEIQYbiZ2pc2Qex7ZyIavM8l2KKwtx6IvqIZpf+2SqAJD4B5tChQ2zevJnly5cDoCgK9913HytXrqR3797s3LmTli1blstbVevXr2fOnDkcOHCArKwsXC4Xdrud5ORkatas6fXxhBBC/I9y6ijGxB8xJK5Fl3ziovu7I6JwdrgBZ6eeuBu2wKnCJ0fymfPZOf5ML2YBD9A80sDo+DDubhCEUVfyoynnuU3Y9rwCLs/2E0pIfSzxk9EFXf4/ssubJD7nKe2am4q0YsUKXC4XrVq1Ktym/v064okTJwr/fLkURdEc63T+7xvj2LFj9O3bl/79+/P8888THR3Njh07GDRoEHZ7yYvmhBBClI6ScqagGWjiWvTHDl50fzU4FOc1XQtmdppfBTo9VqfK+/vzmLc7myPZxb/R1T7WyFPxYdxcx4LuImtxVFXFefwj7H8l4Mv2E6UhiU8AcTqdvP/++0ycOJF//etfHrEhQ4bw3nvv0aZNG9asWUNqamqRsz4mkwlXEa8yVqtWjTNn/lea/OzZsx7//ccff2C325k5cyZ6fcGitm+++cZbH00IIcTflMw0DL/9VFBF+a/dF91fNVlwXt2lINlp3R6MBW9NZTvcvP1nNov+zCE5313s8T1qmXkqPozrapguafGx6nZiP7AI56ki2k9ccSemxoMrrP1EaUjiE0C+/fZbUlNTeeSRR4iOjvaI3XPPPSxfvpzExETmzJnDgw8+yEsvvUStWrXYs2cPoaGhdO3albp163L8+HG2b99OnTp1CA0NxWw207VrVxISEujYsSM6nY6pU6disVgKz9+wYUPcbjeLFy/m9ttvZ8uWLSxdurSi/wqEEKJyys3GsHVDQbKzZxuKWnyiAqDqDbjiO+Ls1APn1V3A/L9aOylWF0v35PLm3hwy7UU/BVCA3vWDGN06lKuqXfrr5aojG+vu6biLaj/ReBjGK2675HP5iiQ+AWTlypVcf/31mqQH4M4772TSpEls3ryZL7/8khdeeIH7778fh8NBo0aNmDFjBgB33HEHn3/+Ob179yYzM7PwdfZp06YxcuRIbrvtNmJjY5k8eTL79/+vhHmrVq14+eWXmTdvHtOnT6dDhw5MnTqVAQMGVNjnF0KISsVmxbB9Y8FjrJ2/oTgdJe6uKjpcza/C2aknzmu6QkiYR/x4jpMFu3NYeSCPfFfRCY9RB/c3DGZU61AaRRiL3Kc47rxTWHe+hJp3wfoifTDmVhMwxLS7rPP5ipKRkVG6RSEBLjMzk4iICF9fRpVitVo9ZpHKi9zbS5OUlETjxo19fRnib3I//E+53BOnA/2u3wveyPrjVxSb9aKHuBq1LEh22ndDjdQuYdif4WDurhw+OJiHs5jf6CEGhUebhjCsZSi1Qy7/MZS/tp8oDZnxEUIIIcqT24V+346CZGfLzyi52Rc9xFWnYcFjrI49UGOLfmt22zk7r+/M5stjVoqbwYgyKwxpHsrjzUOItpRu3Y3j9PfY983zy/YTpSGJjxBCCOFtqoru4J6CKsq/rUOXmXbRQ9xxtXF26omjYw/U2vWLOa3K+tM25uzMYf1pW7HnqhWsY3irMB5pEkyosXR11graT7yD4+hqTUwf1wNzs9EoxTQt9WeS+AghhBBeojt+qGBmZ/OP6M6dvuj+7qhqfxcW7IG7flMo5q0qt6ryxVErc3Zl80dK8WuBGoUbGNU6lPsaBmPWl749REH7idm4zv2iiRkbPIyxfj+/aD9RGpL4CCGEEGWgJJ8sTHb0J49cdH81NBxn++44OvXE3aQ1lFD53u5S+eBQHvN25XAgs/iig21ijIyJD+O2uhb0Fyk6eDElt594GkNctzKd39ck8RFCCCEuk5KegmHzuoI3sg7vu+j+qiUIZ9vrC2rttGwHhpJ//eY63Kw4kMeiP3M4kVt80cHrapgYEx/GDbXMXpmBKa79BMZILPGT/K79RGlI4iOEEEJcipxMDL+vL6i1s38HykUq5atGI642nXF06oGrTWcwmS86RIbNzbK9OSzdk0uarfhaPv+ua+Gp1mG0r+69NTbOlERsf74cUO0nSkMSHyGEEKI4+XkYtv1S8Bhr9+8oRVS+P5+q0+FqeU3B6+ftroOgkEsa5nSei8V/5vD2vlxyinknXa/AvVcGMbp1GM2jLq8GT4nXXGL7ifZ/t5+4tM8RCCTxEUIIIc7ndKLfvon6P3xCyF+7UBwX70foatoGR8ceONt3g/BLf737UJaTebuyef+vPOzFTPBY9PBw4xBGtAqlXph3f22X3H6iN6ZGj6Po/Lf9RGlI4iOEEEL8TZe0G8vyV9GdPkbQRfZ11W9SMLPT8QbU6OqXNc7OVDtzd+XwyZF83MU8MQs3KQxuFsKQFqFUD/J+8lFy+4knMF5xu9fH9AeS+IhLtmDBApYtW8auXbt8fSlCCOFdtnxMHyRg/OGjEtfuuGvVw/FPslOjzmUPs/GMjTk7s/n+ZPE1eKoH6RjWIpQBzUKIMJWuBs/FFLSfmIiad9wzoA/G3Op5DDHXlMu4/kASnwDzxBNP8P777wOg1+upWbMmvXr14qWXXiIyMrCqZwohhD/Q/7kV89uzi627464W93etnZ646zQsttZOcVRV5dsTVubuzCHxbPGPzeqF6nmydSj9GoUQZCi/GjmujN0F7SccWR7bFUtcwSLm0PrlNrY/kMQnAHXv3p033ngDp9PJ/v37GTFiBJmZmSxfvtzXlyaEEIEjLwfzf5dgXP9lkeHU1p0J6v0g7kYtLzvZAXC6VT4+nM+cXdnsSS++Bk+LKANPtQ7jrgZBGMpYg+diHKd/wL5vbqVpP1EakvicJ/fHmyt0vJAe35TqOLPZTFxcwWuFtWvX5q677mLVqlWF8YULF7Jq1SqOHDlCREQEN954I1OnTi2cEXrvvfcYO3Ysq1atYvz48Rw9epS2bduycOFC6tevX3ieefPmsWjRInJzc7nttts8YgBut5vZs2fzzjvvcO7cORo1asSECRO49dZbATh69Cht2rRh+fLlLF++nG3bttG4cWOWLFmCTqdj9OjR7N69m/j4eJYuXao5vxBClBf99o2Y//M6uvQUTcxdrQa2gc9yzBReqialVqfKqr/ymL87myPZxb8F1rG6iafiQ/nXFZZyr4Jc0H5iBY6j/9XE9HE3YG72VEC2nyiN8nl4KCrMkSNHWLt2LUbj/15t1Ol0zJw5k02bNvHmm2+ydetWxo4d63GczWbj9ddfZ+HChXz33XdkZmYyZsyYwvjHH3/MtGnTeO6551i/fj2NGzdm8eLFHudYsmQJCxYsYNKkSWzcuJFbb72Vhx9+mJ07d3rsN3PmTEaPHs33339PREQEgwcPZuzYsbzwwgusXbsWq9XKuHHjyuFvRwghLpCdgXnpNILmPK9JelRFwX7TPeRNf6ugyOBlyrK7mbszm/gPzzBmU0axSc+Ntc18eUs1vvl3NW6uE1T+SY/Lim33jCKTHmODhzG3GFtlkh6QGZ+A9MMPP1C7dm1cLhdWa0GhqenTpxfGhw0bVvjnevXqMWXKFPr168fSpUvR/V0a3el0Mnv27MJ/zYwcOZLhw4fjdrvR6XQsWbKEBx54gAEDBgDwzDPPsGHDBg4dOlR47oULFzJixAj69OkDwIQJE9i4cSMLFy5k2bJlhfsNHz6cXr16YbVaGTFiBPfffz8rVqyga9euAIWJkBBClBtVxfDbT5hWzkOXnaEJu2vWwTpwbEELict0Lt/F0j05vLkvlyx70QujdQrcWT+I0a1DiY+puCSjoP3EZNzZBy64IOPf7Se6V9i1+AtJfAJQly5dmDdvHvn5+bzzzjscOXKEoUOHFsbXr1/PnDlzOHDgAFlZWbhcLux2O8nJydSsWRMoeFx2/hRujRo1cDgcZGZmEhUVxf79+3n44Yc9xm3fvn1h4pOVlcXp06fp1KmTxz6dO3fmu+++89jWsmXLwj9Xr169yG25ubnk5eURHBxclr8aIYTQUDJSMb8zB8M2bcNNVafDccv92O985JIqK5/vWI6TBbtzePdAHvmuohMekw4eaBTMqNZhXBlesb9yXdmH/m4/cc4zYIzEEj8RfUTzCr0efyGJz3lKu+amogUHB3PllVcC8Oqrr3Lbbbfx6quv8txzz3Hs2DH69u1L//79ef7554mOjmbHjh0MGjQIu/1/bxMYLugT889Uq9tdfIn0S3XhtO35j+H+iZ0/vjfHFkKIQqqK4ZdvMK9ahJKXowm76jTENmgs7gZNL+u0+zIczNmZzYeH8ikm3yHUoDCgWQjDWoZSM7jiCwCW3H5iErqgGhV+Tf5CEp9KYNy4cfTp04dHH32UP/74A7vdzsyZM9HrC77Zvvnm8hO6pk2bsmXLFo9Zny1bthT+OTw8nJo1a5KYmEi3bv/r1Ltp0yaaNr28HyJCCOFtSsoZzP95DcOu3zUxVW/A3rs/jlsfAMOlt37Ycs7O6zuz+eqYtdh9os06hrYIYXDzUKLMFb+MtqD9xMfY/3qTqtB+ojQk8akErr/+epo1a8bs2bMZMGAAbrebxYsXc/vtt7NlyxaWLl162eccOnQoQ4cOpW3btlx33XV8+umnbN261aNW0MiRI5k5cyYNGzbkqquuYvXq1WzatImffvrJi59OCCEug9uNYd1nmNe8gWLN14RdVzYvmOW5osElnU5VVX46ZeP1ndlsOFN8DZ7awXpGtAqlf5NgQoy+eW+o5PYTd2BqNKTStZ8oDUl8Konhw4czfPhwRo0axcsvv8y8efOYPn06HTp0YOrUqYWLlC/V3XffzZEjR5g6dSr5+fnccsstDBs2zOO1+aFDh5KTk8PEiRM5e/YsjRs3ZsWKFcTHx3v74wkhxEUpZ05geWsW+v07NDHVaMJ+zyAc/7oXLuGXv8utsjZFz+C959ie6ih2vyYRBka1DqXPlcGY9OX7dlZJVEfO3+0n/vAMKDpMjYdivOIO31yYH1IyMjKKr81diWVmZhIREeHry6hSrFYrFoul3MeRe3tpkpKSSlWjRJQPuR9l4HZh/OYDTB+9VWRDUVezNlgHPosad8Ulne7zo/lM2ZpFUmbxRQevrmbkqdZh3FbPgq6cX0e/mKrcfqI0ZMZHCCFEwNKdOIQ54VX0h/dpYqolCFvfoTi73w66iz9+ynW4Gb85k5VJecXu07WmmTHxoXSraS73+juXoqq3nygNSXyEEEIEHqcD4xerMH22EsWlnZlxtu6AbcDTqDFxl3S6Hal2HlufXuwsz211LTwVH0a7WP8p9FfQfmIeqJ6P4nThzbHET6wS7SdKQxIfIYQQAUV3eD/mhFfQnzikiakhYdj6Dcd57b8uqb+Wqqos2ZPLpC2Z2C+oqKFXVO5rGMLo1qE0jbz0t7/Km7SfKBtJfIQQQgQGuw3TJ//B+PVqlCLqfjmv6Yrt4VGokTGXdLpz+S6GbUjn+5M2TaxxhIGJDbK57epLWxdUUVSXFdve13Cd3aCJGRs8jLF+P794BOfPJPERQgjh93QHdmJZPgvdmeOamDs8Clv/Ubjad7/k8/140srQDemczdcmUP2bBDOzQwSnjmQVcaTvuG1p2HZOkvYTZVSlEx9VVSUzrmRUtUq+pChE5WXNw/RhAsYfPkYp4vvb0eUmbA+OgNBLe5PT7lKZui2LBbu1lZzDTQrzu0RxZ4OgMl+2t0n7Ce+psolPSEgIGRkZREZGSvJTSaiqSkZGBmFhYb6+FCGEF+j/3IL5rdnoUs5oYu6oatgefRrXVZ0v+XwHM50MWp9WZF2eTtVNLOsWRd1Q//u16EzZ/Hf7Cc+CjEpIvYI3t6pw+4nS8L87XEEMBgNhYWFkZfnXVGZllpWVRXh4eLmOERYWpulDJoQIMLnZmP+7BOPPXxUZdnS/HVvfIRAcekmnU1WVVX/lMTYxk1yn56wdzAVCAAAgAElEQVSRToFn24TxbJswDDr/+kewqqo4T3yCPelNwPORnD76Gsytnqvy7SdKo0r/hjAYDFLorgKdPXuWOnXq+PoyhBB+TL/tV8zvzEGXkaKJuWNrYhv4LK4WbS/5fJl2N2M2ZvB/h7XtK64I0bOsaxRdalxeV/aKUNB+YjHOU9rkT9pPlE2VTnyEEEL4iawMzO8twJi4VhNSFQXHTfdgv3cQmC99/c3vZ+0MWp/GsRyXJnZHPQvzr40i0geNRC+moP3EDNzp2y6I6DA1kfYTZSWJjxBCCN9RVQybf8T87nyU7ExN2F2zLtbHxuFu1PKST+lyq8zdlcOMP7JwXbAeOkiv8HLHCPo3CfbL9Z3SfqL8SeIjhBDCJ5T0FMwr5mDY9qsmpup0OG7th/2Oh8F06Y+iTuW6ePznNH4popN6q2gjy7tF+VUxwvNJ+4mKIYmPEEKIiqWqGDZ8jfn9RSh5uZqwq24jbI+Nw13v8pq2fnk0nxG/ppNu0772PqR5CJOvicBi8L9ZHpD2ExVJEh8hhBAVRjl3GvPbr2H4c4smphqM2Hv3x/HvB+Ay3s7Md6q8+HsmCfu0SVSMWcei6yO5uY7/1eaBi7Wf6I652RhpP+FlkvgIIYQof243xh8/xbTmDRSbVRN2NWyBddBY1Nr1L+u0e9IdPPZTGnsytM1Fu9cys/T6KGoE++fbT6rL9nf7iZ81MWODhzDWf9Av1yEFOkl8hBBClCvlzHEsy2ehP7BTE1NNZuz3PIaj191wGa9nq6rK8n25vPB7JtYLXtoyKPBiu3BGtgpF56eJg9uWhm3XZNxZ+z0DOiPmZmMw1LjBNxdWBUjiI4QQony4nBi/+QDTx2+jOLSLjZ3Nr8Y24BnUuNqXddo0q4sRv2bw1THtzFGDMD3Lu0XTNtZ/Hw+5cw5h3VFU+4mIv9tPtPDNhVURkvgIIYTwOt3xQ5iXv4L+8H5NTLUEY7v/CZzdbgXd5dXR2XDaxpCf0ziVp20u2rdhELM7RxJm9L/aPP+Q9hO+J4mPEEII73E6MH3+LsbP30NxadfdONt0wvbIGNSY6pd1Wodb5eU/snh9Zw4XvrMVZlR4rXMk9zUMLsOFl6+C9hOfYk9ahrSf8C1JfIQQQniF7vA+zAmvoj9xSBNTQ8KxPTgCZ5eb4DLX3RzJdjJ4fRq/n9M2F21XzUhCt2gahPvvrzPV7cSetATnyS81MWk/UfH89ytFCCFEYLDbMH38H4xfr0ZRtY+gnO27YXt4FGpE9GWf+sNDeYzZmEGWw3OeRwFGtw7l+bbhGP2suej5pP2E/5HERwghRKnp9u/EsvxVdMknNDF3RBS2h0fjat/tss+b43AzNjGTVX/laWI1gnS80TWKbrUspbrmiuLOP12wiDnvmGdAH4y51XMYYtr75sKqOEl8hBBCXD5rHqYP3sT0w8dFhh3X/gtbv+EQGn7Zp96eUtBc9GCWtrnozXUsLLoukhiLfz8acmX8+Xf7Cc/+Y4qlOpb4KdJ+wock8RFCCHFZ9Lu3YH57FrqUZE3MHR2L7dFncLXpeNnndasqi3bnMGVbFo4LnpiZ9TD1mggGNw/x+6J+zjNrse2dW0T7iWZ/t5+I8tGVCZDERwghxKXKzcb8/mKMG74uMuy44Q5sfYdA0OW/nZSc5+KJDen8eMqmiTWNMLC8ezStov2zueg/VNWN4/BKHEfe18T01bthbj4GRX/pDVdF+ZDERwghxEXpt/2C+Z056DJSNTF39VrYBj6Lq/nVpTr39yesDNuQzjmrdmH0gKbBTO8QQbDBf2vzwEXaT9R/EGODh/x+pqqq8PlXUkJCAvHx8cTFxdGtWzc2btx4Scdt2rSJmJgYOnfuXM5XKIQQVVhWBubFUwia94Im6VEVHfab7yNv2lulSnpsLpXnNmfQ5/tUTdITaVJYcUM0c7pE+X3S47alYf1jrDbpUYyYW4zDdOXDkvT4EZ/O+Hz00UeMHz+e1157jU6dOpGQkECfPn1ITEykTp06xR6XkZHB0KFD6datG6dPn67AKxZCiCpCVTEk/oj5vfko2ZmasLtWPayDxuJu1LJUpz+Q4WDQ+nR2pWlr83SJM7GsaxRXhPr/Q4mC9hOTUG1nPQPSfsJv+TSNXrRoEf369eORRx6hadOmzJo1i7i4ON56660SjxsxYgQPPPAA7dvLq4BCCOFtSnoKlnkvYFk6VZP0qHo99jseJm/Km6VKelRVZcWBXLp/fk6T9OgVeP7qMD6/uVpAJD3OlN/I3/q0JulRQuoSdM08SXr8lM++sux2O9u3b2fkyJEe23v06MHmzZuLPS4hIYGzZ8/y7LPP8uqrr5b3ZQohRNWhqhh+/grzfxej5OVqwq56jbENGou7XuNSnT7D5uapjRl8fCRfE6sTqiehaxQd4/x/8W/J7SfaYW71vLSf8GM+S3xSU1NxuVzExsZ6bI+NjeXs2bNFHvPnn3/yyiuv8P3336PXX3oNh6SkpDJdq/AeuRf+Re6Hf/Hl/TCln6POVyuxHN6ribn1Bs50vZ3kTr3ADpTiOndk6Xhxv4nTNu2DhpuqOXmuUR5hWdkkZZXm6suP5p6oLiLSPyQk9xfNvrmh15MZfA8cPlVBV1d1NG5cumS7KD6fS7xwwZeqqkUuArPZbAwaNIipU6dSv379yxrDm39hovSSkpLkXvgRuR/+xWf3w+3GuPYTTB8sQ7FZNWFXo5ZYB40lvFY9Lr8UIbjcKrN3ZvPKrmzcF3QXDTYovNIxgocaB/vl4t8L74nqyMH25wxcuUW0n2g8hJA6vbm81qvCF3yW+MTExKDX6zWzOykpKZpZIIAzZ86wb98+hg8fzvDhwwFwu92oqkpMTAwffPABPXr0qJBrF0KIykA5fQzLW7PQH9iliakmC/Y+j+G48S4oZQPNEzlOHv85nY3Jdk2sdbSRt7pH0TjCv2vz/KPE9hMtx2Oo1sE3FyYum88SH5PJxFVXXcW6deu48847C7evW7eOO+7QNm2rVauW5lX35cuXs27dOt59913q1q1b7tcshBCVgsuJ8Zs1mD5+G8WhfavK2aIttgHPoFavVeohPjuSz5O/ppNhVzWxYS1DmNguArPe/2Z5ilJy+4nJ6EIb+OjKRGn49FHX8OHDGTJkCO3ataNjx4689dZbnDlzhgEDBgAwZMgQAN544w2MRiMtWniukK9WrRpms1mzXQghRNF0xw5iXv4K+iMHNDE1KATb/U/g7HYrlPLRU57TzfObM/nPAW1z0ViLjiXXR3HjFf7dXPR8zjM/Yts7R9pPVCI+TXzuvvtu0tLSmDVrFsnJyTRv3pw1a9YUzt6cOKHt9iuEEKIUnA5Mn72L8Yt3UVza5p/ONp2wPToGNbr0q1R2pTl47Kc09mc6NbGetc0suT6K6kH+3Vz0H6qqEpb5Jbbj32hi0n4isCkZGRnaeUghyoEspvUvcj/8S3neD93BvQWzPCePaGJqaDi2B0fi7HxjqWd5VFVl2d5cXtqSie2CnMqog5fahTO8ZSg6P1zAXJSC9hOv4zq7XhOT9hOBz+dvdQkhhCgndhumj97C+M0HKKq2D5ajww3YH34SNbz0j2tSrC6G/5LBt8e1b4Q1DNezvFs0V1Uzlfr8FU21p2PdORl31j7PgGLE3PwpDDXkJZpAJ4mPEEJUQrp9O7C89Sq65JOamDsiGlv/p3Bdc32Zxlh/ysqQn9M5k69Nqh5sHMwrHSMINfp3n63zuXMOF7y5VVT7idYvoY8sXXsO4V8k8RFCiMokPw/TB8swrf2kyLDjupux9RsOIWGlHsLhVpm+LYt5u3K4cK1EuFFhTpdI7rkyuNTn9wVnym/Y/pwJLs+q0kpIXSzxU9AF1fDRlQlvk8RHCCEqCf2u3zC//Rq61GRNzB1dHdvAZ3C1Llu9mcNZTh5bn8bWFO1r8O1jjbzZLZr6YYHzq6Wk9hNWSzOi202X9hOVTOB8dQohhChabjbmVYsw/qJ9AwnA3vNO7H0eh6CyzcKsPpjHM5syyHZ4zvMowNPxYYy7OgyjLnAW/apuF/akJThPfqGJGWrfRppyIzGS9FQ6kvgIIUQA02/ZgHnFHHSZaZqYO6421oHP4m52VZnGyLK7eSYxgzUHtc1FawXreKNrNNfXDKxXu1VnLrbd03GlFd1+wnDFHfDXXz65NlG+JPERQogApGSlY1o5H+Nv6zQxVdHhuLkP9rsGgLlsxQK3nbMzaH0ah7O1tX/+XdfCwmsjibYERm2ef7jzz2Dd+RJq7oXtJ4Iwt3xO2k9UcpL4CCFEIFFVDIlrMb87HyVH28rcVbs+tkHjcDdsXqZh3KrK/F05TNuWhfOCFcwWPUzvEMHApiEBV8/GlbkH687J2vYT5upY2kj7iapAEh8hhAgQSto5zO+8jmH7Jk1M1etx3PYQ9tsfBGPZ6uacznMx9Od01p+2aWItIg0kdI+mRVRgNBc9X0ntJ8ytX0JnjvbRlYmKJImPEEL4O1XFsP5LzP9dgpKfqwm76jXB9thY3HUblXmob47nM3xDBqk2bW2ewc1CmNI+giBDYM3yqKqK4/C7OI68p4lJ+4mqRxIfIYTwY8q505jfmoVhz4WLcEE1GrHfNQDHzfeBvmw/zq1OlZe2ZLJsrzaxijIrLLw2ilvrBZVpDF8ouf1Ev7/bTwROkUVRdpL4CCGEP3K7MP7wMaYPElDs2nYQrsatsA4ai1qzbpmH2p/hYOBPafyZrm0uen0NE290jaZWSGAtYIaLtZ8YjaFGT99cmPApSXyEEMLPKKeOYlk+C/1fuzUx1WzB3udxHD3vBF3ZZipUVeWdA3k8tzmTfJfnCma9AhPahjOqVSj6AKrN8w9pPyGKI4mPEEL4C5cT49erMX3yHxSHtjKys0VbbAOfRY2tWeah0m1unvw1nc+PameT6oXqSegWTfvqgdNc9HzO1N+x7Z4JrjyP7Upw3YI3t4LK/vcnApckPkII4QeCko8TtHIW+qMHNDE1OATb/cNwdv03eOH18V/P2Hh8fTon87S1ee69MojXOkcSYQrMdS+O459iT3qDC9tP6KLaYmn1PIox1DcXJvyGJD5CCOFLbhemT1fQ9LN3UdzaRMR5VRdsjzyFGh1b5qGcbpVXd2Qze0c27gtq84QYFGZ1iuCBRsEBV5sH/mk/sRTnyc81MUPt2zA1fgJFF3jrlIT3SeIjhBC+kp+LZclUDDsSNSE1NBzbQ6NwdurhlVmeYzlOHl+fTuJZuyZ2VYyR5d2iaRgRmL8SCtpPzMCVtvWCiA5T48cxXNE7IJM5UT4C86tcCCECnJJ8EsvcCehPHdHEHB1vwP7Qk6jhUV4Z6+PDeYzamEGWXdXERrYK5cW24Zj0gZkYlNx+YjyGah19c2HCb0niI4QQFUy/9w8sCyai5Hq2nHBHRGN7dAyuttd5ZZxch5vxmzNZmZSniVUP0rH0+ih61C5bLy9fKrn9xCR0oVf66MqEP5PERwghKpBh3WeYV85DcXmu58mtVR/GzkaNquaVcXak2nlsfTpJmdraPL2uMLPouihigwJ3zYvzzDps+14H94XtJ5pibj1R2k+IYkniI4QQFcHpxLRqIaa1n2hCjk49Sep2N428kPSoqsqSPblM2pKJ/YKuEyYdTL4mgqEtAq+56D9Kbj/RFXPzp6X9hCiRJD5CCFHecrKwLJpUZNsJ272DcdzWD/Wvv8o8zLl8F8M2pPP9SW1z0cYRBhK6RdEmJjBr8wCoLju2va8V037iAYwNHpb2E+KiJPERQohypJw6StDc59Eln/TYrpotWIdMwNXueq+M8+NJK0M3pHM2X9tctH+TYGZ2iCDEGLhJgbSfEN4iiY8QQpQT/c7NWBZP0XRUd1eLwzpqBu66Dcs8ht2lMnVbFgt252hi4SaF+V2iuLNB4DUXPZ8750jBm1vWotpPvIg+spVvLkwEJEl8hBDC21QV43cfYnp/CYrqOQPjatIa68gpXnlV/WCmk0Hr09ieqm1v0am6iWXdoqgbGtg/5otvP1EHS5sp0n5CXLbA/o4QQgh/47BjXjEX489faUPX34LtkafAWLZ1Nqqq8v5feTybmEmu07M2j06BZ9qEMbZNGIYAbC56Pmk/IcqDJD5CCOElSlY6lgUvoT+wy2O7quiw3/8Ejn/dW+YqzJl2N09vyuDDQ/ma2BUhepZ1jaJLjcB+q6nk9hO3/t1+Qn59idKRrxwhhPAC3bGDWOY9jy4l2WO7GhSCddhLuOLLXkH497N2HlufxtEcbU+vO+pZmH9tFJHmwF3ADP+0n5iJK23LBRFpPyG8QxIfIYQoI/22X7AsnYZis3psd8fVJn/0DNRa9cp0fpdbZe6uHGb8kYXrgq4TQXqFlztG0L9JYDYXPV9B+4mJqLlHPQPSfkJ4kSQ+QghRWqqK8Yv3MH+YoAk5W7TFOnwShIaXaYhTuS4e/zmNX85om4u2jDKwvHs0zSKNZRrDHxTffiIWS5vJ0n5CeI0kPkIIURp2G+a3ZmHc9IM21PNO7P1GgKFsP2K/PJrPiF/TSbdpm4sOaR7C5GsisBgCe5YHpP2EqFiS+AghxGVS0lOwzHsB/WHPYnqqToftoVE4e/Yu0/nznSov/p5Jwr5cTSzGrGPR9ZHcXCewa/PA3+0njryH4/C7mpi++vWYmz8j7SeE10niI4QQl0F3eB+WuS+gy0jx2K6GhGMdORlX86vLdP496Q4e+ymNPRna5qLdappZ2jWKmsGB21z0H6rLjm3f67iSf9LEpP2EKE+S+AghxCUybP4R85svozg819u4a9UrWMQcV7vU51ZVWL4vhwm/ZWK94KUtgwIvtA3nydah6AJ8ATP8035iCu6svZ4BxYip2SiMNW/0zYWJKkESHyGEuBi3G9Mn/8H06QpNyNmmE9ahL0Bw6YvppVldjN1r4qe0TE2sQZiehG7RtIsN3Oai5yu+/UQ4ltYvSfsJUe4k8RFCiJLY8rEsm4lhy8+akP2Wvtjvexx0pX/09Geag74/pHIiV/vjuG/DIGZ3jiQsgJuLns+ZugXb7hlFt5+In4wuuJaPrkxUJZL4CCFEMZSUM1jmTUB/7KDHdtVgxPboGJzX31Km8/96xsYDa1PJsnu+tRVqUHitSyR9GwaX6fz+xHHiM+wHlqJtP3E1llYTpP2EqDCS+AghRBF0SbuxzH8RXVa6x3Z3eBTWJ6fibly2RzKfH83nsfVp2C5Yz9OumpGEbtE0CK8cP55Vtwv7X2/gPPGZJmao9W9MTYZJ+wlRoeSrTQghLmDY8DXm/7yO4vSsK+Oq2xDr6BmoMXFlOv/b+3J5OjED9wXleR5rFsLMjhEYA7y56D+Kbz+h/N1+4s6ArzYtAo8kPkII8Q+3C9PqNzB9s0YTcra7Huvjz4Gl9I+fVFXl5e3ZvLI9WxMbVs/O9E61Kk0iUHz7CQvmls9J+wnhM5L4CCEEQF4OlqXTMOxI1ITsvftjv/NR0JV+kbHLrfL0pgz+c8BzYa9egbldIumknKo0SU9B+4kp4Mjw2K6YYzHHT0YfJu0nhO9I4iOEqPKU5JMEzX0e3SnP2QnVaMI2eDzOjj3KdP58p8pj69P48phnE9MgvcLbN0Rxc50gkpLKNITfKLb9RFgTzPET0ZljfHRlQhSQxEcIUaXp9/6BZcFElNwsj+3uyGpYR0/D3aBZmc6fYXPzwNpUNiV7Fj2MMiusvjGGDtUrR0uGEttPxF6HucUzKHqLD65MCE+S+AghqizDj59ifnc+isvz1SpXg2ZYR01DjapWpvOfzHVx73cp7L2g/cQVIXr+r1cMTStBV3W4SPuJevdjvLK/tJ8QfkMSHyFE1eN0Ylq1ENPaTzQhR+cbsQ18Fkxlm4nZn+Hgnu9SOZHrmVS1iDTwYa9q1AoJ/H5bAKo9A+vOyUW0nzBgajZa2k8IvyOJjxCiasnJwrJoEoY92zQh272DcdzWD8q4yHhzso2+P6SScUFhws5xJt7vGUOkuXLMfhS0n5iIak32DEj7CeHHJPERQlQZyqmjBYuYk096bFfNFqxDJuBqd32Zx/j6WD4Df0on3+WZ9Nxa10JCt2iCDJXjzS1pPyEClSQ+QogqQb9jM5YlU1Dycz22u6vFYR01A3fdhmUeY8WBXJ7amMEFOQ8DmgYzu1Mk+kpSmLD49hNXYWn1grSfEH5NEh8hROWmqhi//RDTf5egqJ6/qF1NWmMdOQU1PKqMQ6i8tjOHaduyNLHxV4Ux7qqwSlGjp+T2E7dgajJc2k8IvydfoUKIysthx7xiLsafv9KGuv4bW//RYDSVaQiXW2X85kze3Oc5k6RT4LVOkQxoFlKm8/sL1ZmL7c+XcaX+fkFEwdRoMIY6d1WK5E5UfpL4CCEqJSUrHcuCl9Af2OWxXVV02B94Akeve8u8iNnqVBmyIY1Pj3gWJjTrYXm3aG6rF1Sm8/uLgvYTk1Bzj3gG9BbMLcdjqNbJJ9clRGlI4iOEqHR0xw5imfs8ulTPt43UoBCsw17CFV/2PlGZdjcPrk3llzOehQkjTArv94yhS43KUZjQlbkX687JRbSfqIY5foq0nxABRxIfIUSlot+6Acsb01FsnrMw7rja5I+egVqrXpnHOJ1XUJjwz3TPwoS1gnV82KsaLaIqR2FCZ/JP2Pa+VkT7icaY4ydJ+wkRkCTxEUJUDqqK8Yv3MH+YoAk5W7TFOnwShIaXeZi/Mh3c9V0qx3M8CxM2iTDwf71iqBMa+D9WC9pPrMJxeKUmJu0nRKAL/O9QIYSw2zAvfxVj4lptqOed2PuNAEPZf9xtPWfnvu9TSbV5vh3WIdbEf2+MJtoS+NWYC9pPzMGVvE4Tk/YTojKQxEcIEdCU9BQs815Af3ifx3ZVr8f20JM4e/T2yjjfn7DyyLo08pyeRXr+VcfC292jCDYEfjKg2jOw7pqCO3OPZ0DaT4hKRBIfIUTA0h3eh2XuC+gyUjy2qyHhWEdOxtX8aq+M8/5feYz8JZ0Lch4eahzM3C6RGCpBYUJpPyGqCkl8hBAByZC4FnPCKygOz7eq3LXqFSxijqtd5jFUVWX+7hwmbtEWJnwmPowJbStHYcLi209cgSV+irSfEJWKJD5CiMDidmP6+G1Mn2kX3jrbdML6xIsQVPaigW5VZcJvmSzZ41mYUAFe6RjB4y0qR1sGx4nPsSctAbWo9hMTUIxhProyIcqHJD5CiMBhzcOybCaGrRs0IfstfbHf9zjoyr7A2O5SGfZLOh8eyvfYbtLBsq7R3Nkg8AsTSvsJUVXJV7UQIiAoKWewzJuA/thBj+2qwYhtwNM4r7vZK+NkO9w8/GMaP52yeWwPNyq82zOGrjUDvzBhye0nHsNQ5+5K8QhPiKJI4iOE8Hu6A7uwLHgJXVa6x3Z3eBTWJ6fibuydhbdn8130+T6VHameBfvignR8cFMM8TFl6+vlD9z5yQWLmItqP9FiHIbYzj65LiEqiiQ+Qgi/ZtjwNea3X0NxeVZJdtVtiHX0DNSYOK+McyjLyd3fpXAk27MwYcNwPf/Xqxr1wwL/x2XJ7Scmow9r6KMrE6LiBP53shCicnK7MK1+A9M3azQh5zVdsQ4eD5Zgrwy1PcVOn+9TOWf1XODbtpqRNTfFUK0SFCaU9hNCFJDERwjhf/JysCydhmFHoiZk790f+52Pgs47BQPXnbTy8I9p5FxQpOfG2mb+c0M0ocbALkwo7SeE8CSJjxDCryjJJwiaOwHdqaMe21WjCdvg8Tg79vDaWB8eyuOJDek4PCd66NswiIXXRWEM8MKEJbef6Ivxykek/YSociTxEUL4Df3eP7AsmIiS61kw0B1ZDevoabgbNPPaWIv+zGHCb5ma7U+2CmXSNeHoAvytppLbT4zCWPMm31yYED4miY8Qwi8Y1n6K+b35KC7PxcWuBs2wjpqGGlXNK+O4VZVJW7KYvztHE5veIYLhLQO/MKE79yjWHRNRrWc8A4awgvYTUa19c2FC+AFJfIQQvuV0Ylq1ENPaTzQhR+cbsQ18FkzeqZ3jcKuM+CWd1Qc9CxMadbDk+ijuvdI7i6V9yZm6Fdvu6dJ+QohiSOIjhPCdnCwsiyZh2LNNE7LdOxjHbf3AS4+cchxuHl2Xxg8nPQsThhoUVvaI5obagb/A13HiC+xJi6X9hBAlkMRHCOETyqmjBM15Dt3ZUx7bVbMF69AXcLW9zmtjpVhd3Pd9KttSPF/ljrUUFCa8qlpgFyZUVRf2pGU4T3yqiUn7CSE8yXeCEKLC6XdsxrJkCkq+ZwNQd7U4rKNm4K7rvUJ6R7Kd3PNdCgezPNcO1Q/T81GvalwZHtg/BqX9hBCXJ7C/44UQgUVVMX77Aab/LkW54HGMq0lr8kdOhfBIrw23K83Bvd+lkJzvOVabGCMf3BRD9aDALkwo7SeEuHyS+AghKobDjvmdORg3fK0Ndf03tkeeAoPRa8P9fNrGQ2tTyXJ4FibsXsvMyh7RhAV4YUJX5j5suyaj2j37lxW0n5iEPqyRj65MCP8miY8QotwpWelY5r+IPmm3x3ZV0WF/4Akcve712iJmgE8O5/P4z2nYLyhMeO+VQSy+LgqTPrAf/TiT12PbO1vaTwhRCpL4CCHKle7YX1jmTkCXmuyxXQ0OwTpsIq7WHbw63rI9OYzbnIl6wfYnWoQwvUNEQBcmLLn9xLWYWzwr7SeEuAifz/UmJCQQHx9PXFwc3bp1Y+PGjcXu+8svv9CrVy8aNGhAjRo1aN++PQsWLKjAqxVCXA791g0ETRuhSXrccbXJe3GxV5MeVVWZtjWLsUUkPZOvCWdGoCc9Lju2Pa8WmfQY692HudUESXqEuAQ+nfH56KOPGD9+PK+99hqdOnUiISGBPn36kJiYSJ06dTT7h4aGMmTIEFq0aEFQUBCbN2/mqaeeIigoiMcee8wHn0AIUSRVxfjFe5g/TNCEnC3aYh0+CULDvTac060yevCcKDQAACAASURBVGMG7yZ5Fu3TK7DwuigeaBTYhQlLbj/xJMaavXxzYUIEICUjI+PCfxxVmJ49e9KyZUvmz59fuK1t27b07t2biRMnXtI5HnroIcxmM8uXLy+vyxRekpSUROPGjX19GeJv5XY/7DbMy1/FmLhWG7rxLuwPDAeD9/7Nled0M+CndL49bvXYHmxQeOeGaG66IjBmQYq7HyW3n3gRfVR8BV1h1SM/syonnz3qstvtbN++nR49PDst9+jRg82bN1/SOXbs2MFvv/3GtddeWx6XKIS4TEp6CkEzntQkPapej/WRp7A/PMqrSU+a1cWd36Rqkp4Ys47Pb64WMElPcZypW8nf8pQm6VGCaxN0zVxJeoQoBZ896kpNTcXlchEbG+uxPTY2lrNnz5Z4bIsWLUhJScHpdDJu3DgGDhxY4v5JSUllvl7hHXIv/Is370fwqcM0+GAx+uwMj+3OoBAO3zOUnDrNwIvjnbEqjPzTzJF8z3+/1TS7WdAqn/CMHJIyijnYT51/P4JzNhCR/iEKnq+m2cxNSIsahHoyD5Dvp/ImP7P8gzdn3nz+VteFFUVVVb1oldGvvvqK3NxctmzZwsSJE6lXrx73339/sfvLVKV/kGlj/+LN+2FIXIt55WwUh91ju6tWfWyjp1MzrrZXxvnHnnQHQ75L4dQFhQlbRhn4sFc1agYHXmHCf+5HQfuJN3Gma5u2GmreTHDTEURL+4kKIT+zKieffffExMSg1+s1szspKSmaWaAL1a9fH4CWLVty9uxZXn755RITHyFEOXG7MX38NqbPtG8aOdt0wvrEixAU4tUhN56x8cDaVDLtnssTr6th4r2eMUSYfP6yaqmpzry/20/8dkFE2k8I4S0++wlhMpm46qqrWLduncf2devW0bFjx0s+j9vtxm63X3xHIYR3WfOwLJxYZNJjv6Uv1tHTvZ70fHE0n7u+S9EkPb3rW/jwpmoBnfTonWnkbx2jTXp0ZsytX8JY9x5JeoTwAp/Olw4fPpwhQ4bQrl07OnbsyFtvvcWZM2cYMGAAAEOGDAHgjTfeKPz/evXqFU49/vrrryxcuJBBgwb55gMIUUUpKWewzJ2A/vhBj+2qwYhtwNM4r7vZ62O+vS+XpxMzcF/wHurgZiG83DECvS5wkwJX5j6qJc9GdWd7bJf2E0J4n08Tn7vvvpu0tDRmzZpFcnIyzZs3Z82aNdStWxeAEydOeOzvcrmYNGkSx44dw2AwUL9+fSZOnHjRxc1CCO/RHdiFZf6L6C5YxOwOj8L65FTcjVt5dTxVVXllezYvb8/WxF5sG86Y+NCAnglxJv+Mbe9s9G7PmWtpPyFE+fBpHR9RtchCQf9Smvth+PlrzP95DcXl9NjuqtsI6+jpqDFx3rxEXG6VZxIzeHu/Z2FCnQJzu0TSv4l3H6VVpIL2E+/jOLxCE5P2E/5BfmZVTvJqgBDi4twuTKvfwPTNGk3IeU1XrI8/B+Ygrw6Z71R5bH0aXx7zrNFj0cPb3aO5pa53x6tIqtuObe9cXMk/amLGuvdhbPgoihK465WE8GeS+AghSpaXg2XJVAw7tYVF7b0fwX7nI6Dz7i/pDJubB9amsinZ8/FPpElh9Y0xdIwze3W8ilRc+wkVPeZmozDWkvYTQpQnSXyEEMVSkk8QNHcCulNHPbarRhO2weNxduxRzJGldzLXRZ/vUtiT4fk47YoQPf/XK4amkUavj1lRSmo/kRo1gHqS9AhR7iTxEUL8P3v3HdhU2bYB/DpZJ+melL33KCAIiMoGx6eoICCiIIiiqIiCLJWlsgoKKiiCDOUVRUTxFV+GyFAQHMheZc9Cm+6Rec73RxF8mra0NGmS9vr99fY+SZ4HIrwXybmfO1/aw3tg/HASpCzxpmIlLAqWkW9DqdXQ7WseS7Wj90YzLmQ5hXqjsNyDCasE+t/BhP9wJu+B5eA7gCNLqEsBVWCMnQrbxewCnklE7sTgQ0QudJvXQl4xD5IinozsrN0IlhFvQQ2Pcvuav1+1ot9PZqRYxX6LO2IMWNk1EmGy/97zYr+4Drbj8wFV/P3UhDWHsdkbkPTB4PgJotJRouCTnZ2N7OxsREW5/y9BIvIChwOGLz6EYbPruAT7Hd1gHfIaYHD//TXrz+dg8JYU5DjF0HN/dSM+7RgBk84/29VV1QnbicVwnP/W5Zqu0j0wNHgRksZ/v7oj8kc3DT67d+/Gt99+C71ej969e6NFixb4/fffMXbsWOzbtw8AULFiRYwbNw4DBw70+IaJyEMy02GcPxm6w3tcLlkffQb2Bx4HPHBezufHszByZyryZB48VT8As+8Ig85PDyYsfPzE09BV40nMRN5QaPD55Zdf8PDDD0NRFEiShEWLFmH58uV4+umnERwcjPvvvx92ux1//PEHRo4cibCwMPTs2bO09k5EbiJdOgvTe+OhuXpJqKuyEZbn3oDztrvcvqaqqpizPxNv70l3uTa2RTDGtQj222CgWK7Cun8SlMzT4gWNDLnJWOii23tnY0RUePCZO3cuatSogTVr1iAqKgojRozAM888gyZNmuC7776DyZR7jkZqaiq6d++OBQsWMPgQ+Rntvt0wfjQVUo54060SFQPLy9OgVK/j9jWdiopxu9Ow6Ki4pkYCZrcLw5CG/nswoTP9GKz7J0O1pQh1jp8g8g2F3i148OBBDBw4EDVr1kRQUBBeeeUVZGRkYPDgwddDDwCEhYXhiSeewKFDhzy+YSJyE1WFfv0qGN8b7xJ6nPWbIXvSQo+EHqtTxZBtyS6hR9YCyztH+HXocVzdDsue11xCjya4Loyt5zL0EPmAQj/xSUxMRKVKla7//M///nftHxUrVkRWVpZLnYh8kN2G6v9dBnn/TtdLHe6HddArgM79N92m2RQM2GzGrwniwYQhBgkru0bizor+eTChqqqwn/0S9lPLXa5po9tDbjyG4yeIfEShwUdVVWj+dSKrppDTWf31u3iicicjFaZ5byAo/qBQViUNbI8Ph717b4/cxJyQ7cSjm8w4mGwX6pUCNFjdPQpNIvyzu0lVbLAdnQdHwmaXaxw/QeR7btrVlZGRgcTERABAcnIyACAtLe167R/p6a43KBKRb5FSkmCcNRraS2eEuhoQCMvwSXA2a+ORdU+k2dFroxnnMsWDCeuH6rC6RySqB/nnkWKqLe3a+Ik8X/NLWhgajIC+8j3e2RgRFajQ6ezh4eEun+Soqprvpzv/1P8JR0R5cdKxd0mJl2GaOQqaRLFzS4mpgpyR06BWruGRdf9KtKHvJjPMVvHwvtuj9fiqWyQijP55GrOSde7a+InL4gVdEIzN3oQ2vHmxXo9/PnwP35OyqdB/Zo0dO7a09kFEHiRdOgvTrFHQpCQJdUejlrC8OAUICvHIuj9dsGDglmRkO8R/X91TVcbSzhEI0PnnV0AFjp8wVYGx+VRoAqp4aWdEdDOFBp9x48aV1j6IyEM0Z+NhjHsNmoxUoZ5avwV0r87wyEnMAPDliWy8+GsK8mQeDKgXgLntw6D304MJCx4/EQtjszevjZ8gIl/ln1+sE1GRaE4cgmnOGEjZ4icT9ju64XSn3qjngdCjqio+OJiJiX+63vc3KjYIb9wW4pfNEIWPn+gBQ4OXOH6CyA/cNPgcP34cOp0OtWvXBgDk5OTg/fffd3lclSpV8MQTT7h/h0R0S7SH/oJx3uuQrBahbu/0IKyDRgInT7l9TUVV8cYfaVhwKM9XQABmtA3FsMZBbl+zNOSOn5gJp3l3nisS9HWGQF/9Ub8Mc0TlUaHBZ+/evejSpQveffddIfjMmDHD5bEajQaxsbGIjY31zE6JqMi0e3bAOH8yJIfYOm67ty9sjz3vkXZ1m1PF8F9TsPpUjlA3aICFHcLxSK0At69ZGjh+gqhsKfTOws8++wzVq1fHoEGDXK4tW7YMx44dw7Fjx3DkyBFUqVIFn3/+ucc2SkRFo/ttM4wfvOkSeqyPDPZY6MmwK+j7k9kl9ATrJazuEeW3oceZfgyWP192CT2SIRLGVrMZeoj8UKGf+OzcuRMPPPBAvh/hhoWFoUKFCtd/7t27N/73v/+5f4dEVGS6rT9AXjYHkireUWzt/wLs9/bxyJpXc5zos8mMfWYxaMWYNPi6eyRiIw0eWdfTHFd/gfVwHKCIp0xrgutCjp0MjRzlpZ0RUUkUGnzOnTuH+vXrCzWtVotGjRohKEj8rr5GjRo4f/68+3dIREWiX78K8soFQk2VJFifGgVHpwc8subpdAd6bUzC6QzxYMI6IVp80yMKNYP9r38id/zEV7CfWuZyTRvVHnITjp8g8mc3HVmh5vmXY2hoKHbudJ3vI0kSFEVxqRORh6kq9N8th/zdMrGs1cL67AQ42nX1yLJ7k2zos8mMRIv45/62KD1WdY9ElB8eTJg7fuJ9OBJ+crmmr94H+jqDOX6CyM8VGnwqVaqEY8eOFemFjhw5gooVK7plU0RURKoKw5cfwbB+lVjW62F5YQqcLT1zD8rWSxY8sTkZmXkO6elaRcbyzhEI0vtfOCh8/MRL0Fe+1zsbIyK3KvRvp7vvvhtff/01MjIyCn2RtLQ0rF69Gh07dnTr5oioEIoT8tI5rqFHNsLyygyPhZ7Vp7LRZ5PZJfT0rWPCl90i/TL0KFnnkfPnSNfQowuCscU0hh6iMqTQv6FefPFFpKWloV+/frh48WK+j7lw4QIee+wxZGRkYPjw4R7ZJBHl4XBAXjgN+m0/CGU1IAg5Y+bA2aSVR5ZdcCgTQ7elwJ7nW+2Xmgbh47vD/fI0ZmfyHuT8NdJl5pZkqgJT67nFnrlFRL6t0K+66tWrh3nz5mHEiBFo2bIl7rzzzus3NmdmZuLw4cPYuXMnVFXF+++/73IjNBF5gM0K44Kp0P29QygrwWGwvBYHpYb7hyqqqorJf6Zj3sFMl2tv3x6CF5v655iGgsdPNIOx2USOnyAqg27actG/f3/Ur18fM2bMwLZt27B169br1/R6PTp16oSxY8eiVSvP/AuTiP7Fkg3jvDegO7xHKCvhUcgZM8cjE9btioqXfk3BlyfFM3r0GmDBXeHoU8f/zujh+Ami8qtIvaatWrXC119/DYvFgpMnTyIjIwPBwcGoXbs2TCaTp/dIRACQlQHTu+OhPXFQKCvRlZEzdg7U6EpuXzLTruCpLcn46aJVqAfpJHzeJQKdq/hfWzfHTxCVb8U6ZMNoNKJJkyae2gsRFSQ9Faa40dCeOyGUnZVrwjJmNtRw9x+ml2Rxou8mM/YkiQcTRhk1WN09Ei2i/O9gQsWSeG38RJ45ZRoZcpMx0EXf6Z2NEVGp8b/TxYjKGSn5KkyzRkNz+ZxQd9asj5zRs4DgMLeveTYj92DCk+niwYQ1g7VY0yMKtUP8768OZ/oxWPdPhmpLEeqSIRJy88nQBrv/3igi8j3+97cXUTkiXb0E08xXoUlKEOrO+s2Q88p0IMD9084PJNvx6MYkXMkRb/iNjdDj6+6RiAnwv4MJc8dPzAYU8Ss7TVAdyM2ncPwEUTnC4EPko6SLZ2CaNQqaVLNQdzS9HZYRUwHZ/ffX/XLZigGbzUi3i2f0dKwk4/MuEQgx+NcZPRw/QUR5MfgQ+SDNmeMwzX4NUkaaUHe0uhuW598E9O6/v2btmRw8sy0Ztjxn9PSuZcKCu8Mha/3rht/Cx088Cn2dIRw/QVQOMfgQ+RjN8QMwvTsOUk6WULe37wHr0DGA1v1/bBcdycSYXWlQ89SfaxyIaW1CofGzLqfc8RNvQUkTO+A4foKIGHyIfIj24J8wznsDks0i1O1dHoL1yZcBjXs/oVBVFe/sycDs/a5jaSa3CsHLzYL8rrVbyToPy/6JUHPEk5ihC4Kx2Zs8iZmonCtW8Pnss8+wfPlynDlzBikpKS7XJUmC2WzO55lEdDPav36BccFUSA6xfdx2f3/Y+j4LuDmAOFTgpR2pWBGfLe5DAj64MwyP1wt063qlwZn8NywH3wEc4gnTkqkyjM2nQhNQ1Us7IyJfUeTgM3XqVMydOxdNmjRBnz59EBbm/hZaovJKt3MT5EXTISniDTbW3k/D/uATbg892Q4FY44Y8EuyGHoCdBKWd45A96r+d8Ov/eKPsB3/sIDxE29C0od4aWdE5EuKHHxWrFiB+++/HytWrPDkfojKHd2W7yEvfw+SKt5hYx3wEuw9ert9vRSrgn6bzPg9WfzjHyFrsKp7JFpH+9fBhLnjJz6F4/wal2scP0FEeRU5+GRlZaFbt26e3AtRuaP/8UvIX30s1FRJA+uQ0XB0uN/t6yVZnHh4gxkHk8Wv06oFabGmRyTqhfpXQFAdObAengFnUt7xE7g2fqKP392jRESeVeTg065dOxw6dMiTeyEqP1QVhm+XwrD2M7Gs1cI67A042nZ2+5IJ2U48tD4Jx9IcQr1xuA7f9IhCJT87mLDQ8RONX4Ouwl3e2RgR+bQit4jExcVhw4YNWLFiBVQ1b9MrERWZqsLwxYeuoUdvgOXldzwSei5kOnD/j4kuoad9jAE/3hftd6HHmX4Mlj9HuIQeyRAB422zGXqIqEBF/sSnf//+sNlsGDFiBMaMGYPKlStDqxX/spQkCbt27XL7JonKDMUJeekc6Lf/KJRVowmWkdPgbNTS7UueyXCg5/oknMsU5261C3NidY9IBOj86xC/QsdPxE6GxhjtpZ0RkT8ocvCJiopCdHQ06tat68n9EJVdDjvkT6ZBv3uLUFYDg5EzaiaUOo3dvuSJNDt6rk/CpWyx0+neaka8US3Zr0JP4eMn7oDceAwknfvHeBBR2VLk4LNu3TpP7oOobLNZYfxwEnT7xE9ElZBwWF6bDaV6HbcveSTFjoc2JOFqnmGjPWsYsbhjBM6eSnb7mp6iKnbYjs4rZPzEYEiSf31dR0TewZObiTzNkg3j3NehO/K3UFYiKiBn7ByoFau5fcn9Zhse2WCG2SqGnr61c+du6TT+0+mk2tJgOfg2lNQD4gVJC0ODF6GvfJ93NkZEfqnA4HP+/HkAQLVq1YSfb+afxxMRgKwMmOaMhfbkYaGsxFRBzpg5UKMqun3JvxJt6LUxCWk2sQnhyXoBmNs+DFo/Cj2Fjp9o+ga0ES28szEi8lsFBp/Y2FhIkoSEhAQYDIbrP99McrL/fHxO5ElSWjKMca9Be/6kUHdWrQXLa7OhhkW6fc3frljRd5MZGXYx9AxtGIhZ7fxr2Gih4ydip0ATyH9kEVHxFRh8PvzwQ0iSBL1eL/xMRDcnma/CNGsUNAniJ6XOWg2RM3omEBTq9jW3XbKi/2Yzsh1i6HmxSRDeuj3Er/782i/+79r4CbETjeMniKikCgw+AwYMKPRnIsqfdOVCbuhJuiLUnQ2aI+eVaYDJ/cM/N12w4ImfzbCKOQGjmwfj9ZbBfhN6csdPLIHj/Dcu13QVu8PQcATHTxBRifDmZiI30lw4BeOs0dCkiV/5Opq1geWlqYDs/uGfP5zNweCtybCL9zHjjdtCMLp5sNvX85Tc8RMz4UxyPQtMX3sw9DX6+k2AIyLfxeBD5Caa00dhihsDKStdqDtad4Dl+TcBnfs/qVhzKhvPbE+BM89h6m/fHoIXm/pP6MkdPzEZSqZ4PxTHTxCRuzH4ELmB5th+mN4dB8mSLdTtd90D65DXAK37/6h9EZ+FF3ekQskTema3C8XQRkFuX89TnOnHYd0/GapN/JRMMkRAjp0MbUh9L+2MiMoiBh+iEtLu3w3jBxMh2cQRCrZuj8A24CVA4/7TkZcdy8LInalCTQLw/p1heLK+++8h8hTH1V9hPRzH8RNEVGoYfIhKQPvHNhg/eguSUxz+aXtgAGyPDgU8cE/Kx4czMW53mrgPCfjo7nD0rRPg9vU8ofDxE+0gNx7L8RNE5BFF/qfojh07kJSUVOB1s9mMHTt2uGVTRP5A9+sGGOdPcQk91kefga3PMx4JPXP3Z7iEHp0ELOkU4T+hR7HDduTdfEOPvnpvyM3eZOghIo8pcvB58MEHsWXLlgKvb9u2DQ8++KBbNkXk63Sbv4Nx0XRIqthKZX3yZdgfdP/RD6qqYsbf6Zj8l3jjtEEDfN4lAg/V9I+goNrTYdk7AY6ETeIFSQtDw5dhqPsMZ24RkUcV+asuVVULvW6z2aDxwL0MRL5Gv+4LyKs+EWqqpIF16Bg47rrX7eupqoopf6Vj7gHxBGOTVsIXXSPQuYr7W+Q9IXf8xCSoOZfEC7ogGJu+Dm1ES+9sjIjKlUKDT3p6OtLSbnysnpycnO/MrtTUVHzzzTeoVKmS+3dI5CtUFYZvPoXhvyvEslYHy/Nvwnl7Rw8sqWLc7jQsPJIl1IN0Er7sHom7KspuX9MTnMl7YTn4dj7jJyrBGDuV4yeIqNQUGnwWLFiAWbNmAQAkScL48eMxfvz4fB+rqirefPNN9++QyBcoCgxffAjDpjVCWdUbYBnxFpyxbd2/pKpi1G+pWHpMbJEP0UtY3SMSbSr4R+ixX/ofbMc4foKIfEOhwadTp04wGo1QVRVTp05Fr1690KxZM+ExkiQhICAALVu2ROvWrT26WSKvUJyQP42D/tf1Qlk1BiDnlelQGjZ3+5JORcWLO1Kx8oQYesJlCd/2iEKLKIPb13Q3VXXCfnIJ7OfyGz/R7dr4Cd//dRBR2VJg8NmxYwcaNGiAdu3aAQCsVit69uyJxo0bl9rmiLzOYYf88TvQ/7FVKKuBIcgZPQtK7YZuX9KuqBi2PQVrTucI9SijBt/dE4WmEb4/q4rjJ4jIVxV4N3LeLq6VK1fizJkzpbEnIt9gs8I47w2X0KOEhiNnwlyPhB6rU8VTW5JdQk9Fkwbr7vOP0KNYEmHZM9o19GhkyE3fgKFmP4YeIvKaAj/xCQwMRFbWjRsqz507J/xMVKblZMM0dzy0R/cJZSUyBjlj5kCtWNX9SzpUDPzZjE0XxVOMqwZq8f29Uagd4vvnjTrT42HdPymf8RPhkGOncPwEEXldgX+TNm3aFPPmzYPVakVISO7Nh7/99hscDkdBTwEA9O/f3707JCptmekwzRkL7akjQlmpWC039ERWcPuSWXYF/TcnY/tlMfTUDM4NPdWDfD/0cPwEEfkDKTU1Nd8Devbu3YvBgwdf/3pLkqSbnuUjSRKSk5MLfQyVX/Hx8ahXr563t1EoKdUMY9xoaC+cFurOqrVhGTMbamiE29dMtyno95MZv12xCfV6oTqsvScKlQM9c6Cfu96P3PETq2A/tdTlmjaqLeTG43gScxH4w5+P8obvSdlU4D8jW7Rogb/++gsXLlxAYmIiunXrhvHjx6NLly6luT+iUiOZr8A0cxQ0Vy4IdWedRsh5dSYQ5P6261Srgt4bk/BXkl2oNw7T4bt7o1DB5NunGKuKHbZjH8BxeaPLNV213jDUHcKTmInIpxT6+blGo0H16tVRvXp19O/fH126dGHLOpVJUsIFmGa+Ck3yVaHuaNgClpHTAJP752AlWZx4ZIMZB5LF0BMboce390Qi0ujbgUG1p8Ny4C0oqQfEC5IWhvovQl/lPu9sjIioEEW+cWDBggWe3AeR12jOn4IxbhQ0aSlC3dG8HSwvTgEM7j8o8Eq2Ew9tSMLRVPGeudbReqzuHoUw2bfHvyjZF2DZN5HjJ4jI7xQYfFauXAkAeOyxxyBJ0vWfb4Y3N5M/0Zw8AtOcMZCyMoS6vU1nWIdNAHTubx+/mOXEQ+uTcCJdDD13xBiwqnskgvW+HXqcKftgOfAWx08QkV8qMPgMHz4ckiShd+/eMBgMGD58+E1fTJIkBh/yG5qje2F6bzwki3hmjr3D/bAOHgVo3P9V09kMB3quT8LZTHF8Q6fKMv7TJQKBPh567JfWw3bsA9fxE6FNc8dPGEK9tDMioqIpMPjs25d7fonBYBB+JioLtPt2wfjBREh2sZPK1r03bI+/AGjcH0BOpuWGnovZYmjoUVXGZ50jYdT57qF+ueMnlsJ+brXLNY6fICJ/UmDwqV69eqE/55WUlISEhAT37IrIg7S/b4Xx47chOcWvmmw9n4St1xDAA6cKH02146H1SbiSowj1B6obsaRTBAxaHw49Tgush2bCmfSbyzV97aegr8GTmInIf7jtn7XLli1Dhw4d3PVyRB6h++V/MC6Y6hJ6rH2Hwdb7aY+EngPJdvzfj66hp3ctE5Z29u3Qo1gSYflrlGvo0ciQm74OQ83HGHqIyK/4/nGwRG6i37QG8or3hZoqSbA+ORKOrg95ZM09iTb02piEVJt4+OfjdQPwwZ1h0Gp8NzTkjp+YDNVmFuq54ycmQxvSwEs7IyK6dQw+VC7o/7sC8urFQk3VaGAdOg6OO3t4ZM1dV6zou8mMdLsYep5uGIi4dqHQ+PAnJY7EHbAempXP+InakGOncPwEEfktr7eQLF68GLGxsYiJiUHHjh2xc+fOAh/7/fff45FHHkGdOnVQtWpVdO3aFT/++GMp7pb8jqrCsGqha+jR6WF5YYrHQs8vl63ovdE19AxvEojZPhx6VFWF7ewqWA+85RJ6tJFtYbxtDkMPEfk1rwafNWvWYNy4cRg1ahS2b9+ONm3aoE+fPjh//ny+j9+xYwc6dOiAVatWYfv27ejevTueeOKJQsMSlWOKAsPn82BYJ55BpRpkWEZOg7P13R5ZdvNFC/psSkKWQww9o2KD8M7toT57T4yq2GE7+h7sJ5e4XNNV6wU5diJnbhGR3yv0q66//vqryC906dKlmz8oj/nz5+Pxxx/HoEGDAABxcXHYvHkzlixZgkmTJrk8fubMmcLP48aNw8aNG7Fu3Tq0b9++2OtTGeZ0QP40DvodG4SyagpEzqvTodSP9ciyP57LwVNbkmET72PG6y2D8VoL98/6cpeCx09oro2fuN87GyMicrNCg0+3bt2K/K9TVVWL9S9Zm82GvXv34qWXXhLqXbp0we7du4v8OpmZmQgLCyvyv5aUiQAAIABJREFU46kcsNtg/Pht6P7cLpTVoBDkjI6DUsszN+V+dzoHQ7clI88HPXirdQheahbskTXdIXf8xCSoORfFC7rAa+MnbvPOxoiIPKDQ4DN//nyPLWw2m+F0OhEdLd4vEB0djatXrxbwLNGiRYtw6dIl9OvXr9DHxcfH3/I+yb08/V5Iditqf/0RdKcOCXV7UChODHgFFocG8MAefryqxZTjBigQw/9rtW2415iA+HjfPOPq7IF1iDB/Co2SLdQd2igkRw2DwxwMmPnnp7Tw7yrfw/fEN9SrV89tr1Vo8Hn88cfdtlBB8n5KVNRPjtauXYuJEyfi008/venhiu78DaNbFx8f79n3IicLpnfHQ5sn9ChRFWEbMwfVYqp4ZNnPjmdh8vFU/PuDHgnAvDvDMLB+oEfWdIcLf3+G8NSv8hk/0QQhzSYilOMnSpXH/3xQsfE9KZu81s4eGRkJrVbr8ulOUlKSy6dAea1duxbPPfccPv74Y9x/P+89IACZaTDNHgPt6WNCWalUDTlj5kCNqOCRZRcdycRru9KEmkYCPro7HP3qBHhkzZJSVQX2k0sRnvK1yzWOnyCiss5rXV0GgwEtWrTAli1bhPqWLVvQtm3bAp/37bffYtiwYViwYAEeesgzh86Rf5FSzTBNe9kl9Dir10HOhPc9Fno+OJDhEnp0ErCkY4Tvhh6nBdYDb8N+zjX06Gs/BUOjUQw9RFSmefUAwxdeeAHDhg1Dq1at0LZtWyxZsgQJCQkYPHgwAGDYsGEAgIULFwIAvvnmGwwbNgxvvfUW2rdvjytXrgDIDVHh4eHe+UWQV0mJl2GaNQqaq2JXobNuE+S8OgMIdP9NxaqqIm5fBqb9nSHUDRpgWecI3F/dN1u+FWsSrPsmQck8KV7QGCA3fg26Cp5p7yci8iVeDT69evVCcnIy4uLicOXKFTRq1AirVq26fs/OhQsXhMcvWbIEDocD48ePx/jx46/X77zzTqxbt65U907eJ10+lxt6khOFuqPxbbC8/DZgdP+nLqqq4q096Xh3f6ZQN2qB/3SNRNcqRrev6Q7OjHhY93H8BBGRlJqaqt78YUQl584bBTXnTsAY9xo06SlC3dGiPSwvTAIMslvW+TdVVTHh9zR8dDhLqAfqJKzsFokOldy/pjs4EnfCemimy0nMdn1lhNw+AxqjZ74KpOLhjbS+h+9J2cRZXeR3NCcOwTRnLKRs8VMXe9susD47AdC5/z9rRVUx+rc0LDkmhp5gvYSvu0eiXYzvhR5VVWE/t/raScziv2+0kW1x2fgowhh6iKicYfAhv6I9vAfGuRMgWS1C3d7x/2B96lVAo3X7mk5FxUs7UvHFCfGsmzCDhDU9onBbtO/dDKwqdtiOfQDH5Y0u13TVHoGh7lCoJ055YWdERN7F4EN+Q7t3J4wfToJktwt12z19YOs/HPDADCy7ouL5X1Kw+lSOUI+UNfju3ig0i9C7fc2SUu0Z18ZP7BcvSBoY6r8AfZX/887GiIh8AIMP+QXd7p8hL3wHklM8bM/28CDYHn7KI6HH5lQxZGsyfjgnfroUY9Jg7b1RaBjme6FHyb4Iy76JHD9BRFQABh/yebpt6yAvnQ1JFe9TsT72POz3FT6u5FZZHCoGbTFjwwXxhuCqgVqsvScKdUJ974+OM2UfLAfeAhzivU+SsRKMzadAE1j4CedEROWB7/3tTfQv+g1fQ/5CnBmnShKsg16Fo/ODHlkzy65gwM/J2HpJDD01grT4/t4o1Aj2vT829ksbYDv2fr7jJ4zNJkLi+AkiIgAMPuSrVBX67z+HvGaJWNZoYH12Ahx3dPPIshl2BX03mfHbFZtQrxuiw9p7o1Al0P03T5fEP+Mn8juJWVexKwwNX+ZJzERE/8LgQ75HVWH46mMY/veVWNbpYXlhEpy33eWRZVOtCvpsSsIfieLN043CdPjunijEBPhY6HFaYD08C87EnS7X9LWfgr5GvyIN/CUiKk8YfMi3KArkz96Dfst/hbJqMMIy8m04m7T2yLLJFice2WjGPrMYeppF6PHdPZGINPpW6FGsSbDunwwl44R4QWOA3Hg0dBU6eGdjREQ+jsGHfIfTAXnRDOh/+0koqwGByHl1JpR6TT2y7NUcJx5en4TDqQ6h3ipKj296RCFM9tos33xx/AQR0a1j8CHfYLfBuGAqdHt+FcpqcChyXpsNpYZnjo2/lOXEQxuSEJ8mhp47Ygz4qlskQgy+FXoKGj+hCaoFOXYKx08QEd0Egw95nzUHxnlvQnfoT6GshEUhZ+wcqJVreGTZc5kO9FyfhDMZYidUh0oyVnaNQKDed0JP4eMn2kBuMg6Szv1DWYmIyhoGH/Ku7EyY3h0HbfxBoaxEV0LO2HehRlfyyLKn0nNDz4UsMfR0ryLjsy6RMOl856bg3PETH8JxeYPLtX/GT0iSb92DRETkqxh8yHvSU2GaPQbas8eFslK5BnJemw01Itojyx5LteOh9UlIyFGE+v3VjVjaKQKy1odCjz0DlgNvQ0ndJ17g+AkiolvC4ENeIaUkwTRrFDSXzgp1Z416yBkdB4SEeWTdg8l2PLwhCUkWMfT0qmXCwg7h0Gt8J/Qo2Rdh2T8RajbHTxARuQuDD5U6KfEyTDNHQZN4Sag76zVFzqszgIAgj6y7N8mGRzYmIcUq3iPzWB0T5t8VDq0PhR5nyv5r4ycyhLpkrAhj86kcP0FEdIsYfKhUSZfO5oae1CSh7mjSCpaX3wZkk0fW/f2qFY9uNCPdLoaep+oH4N32YdD40EF/9ksbr42fEDvNcsdPvAnJ4JlPw4iIygMGHyo1poRzCPjqfUgZaULdcdudsDw/ETDIHln31wQr+m0yI8shhp5hjQIxo22oz5xunDt+Yhns51a5XNPGdIHcaCTHTxARlRCDD5UKTfxB1P18NiRrjlC339EN1qHjAJ1n/lP8+aIFAzYnI8cphp6RzYIwqVWI74SeQsdPDIK+xmM+s1ciIn/G4EMepzm6F6Y54yDZLELd3vlBWAe+Amg8c17O+vM5GPhzMmzifcwY1yIYY1sE+0yQUKzma+Mn4sULGgPkRqOhi+H4CSIid2HwIY+S0lNg/HCyS+ix3dcPtn7PAR4KH2vP5ODprcnI8+0WJrcKwcjYYI+seSucGSdg3T8ZqlW854njJ4iIPIPBhzxHVSEvnQ1NRqpQtvYaAnvPJz0Wer4+mY3nfklBnm+3MKNtKJ5r7JmOsVvhSPwN1kMzXMZPSIE1czu3OH6CiMjtGHzIY3Q7NkC3Z4dQs/V8EvaHBnpszc+PZ2HEjlRhqIME4L32YXiqQaDH1i0OVVXhOP8NbCc+BcdPEBGVLgYf8gjJfAXyig+EWlblWlAfHuSxNRcfycToXWLHmEYC5t8Vjv51fSNIqIrj2viJ9S7XOH6CiMjzGHzI/RQF8uKZkHKyrpdUg4yzDw1Bda1n/pP78GAG3vgjXahpJWBRh3D0qu0joceeAcvBd6Ck7BUvcPwEEVGpYfAht9P/9C10h/cINVvfYbBGVvTIerP3ZeDtPWLo0WuApZ0i8EANzxyIWFxK9iVY9r/J8RNERF7mmT5iKrekS2dhWLVQqDka3wZ714fdvpaqqnh7T7pL6DFqgS+6RvpM6HGm7EfOny+7hB7JWBGmVu8y9BARlSJ+4kPu43TA+Ml0SHbb9ZIaEJh7QKGbz+pRVRVv/pGODw9lCvUAnYSVXSPRsbJnToEuLvvljbAdzW/8RGMYm03k+AkiolLG4ENuo//hC2hPHxVq1idehhrp3rZsRVUxdlcaFh3NEurBegmrukfijhjvhx5VVWA/tQz2sxw/QUTkSxh8yC00p4/BsHa5UHO0uhuO9t3duo5TUTFyZyo+j88W6qEGCWt6RKFVtPfDRO74iTg4E3e4XNPXGgh9zf4+c2o0EVF5w+BDJWezQv5kOiSn83pJCQmH5alRbj2k0KGoGP5LCladEud9RcgafHtPJJpHej/0cPwEEZFvY/ChEjN88ym0l84INevgUUCI++5fsTlVDN2WjO/PiqMvKpg0WHtPFBqF69221q1yZpyEdf+k/MdPNJsEbWhDL+2MiIj+weBDJaI5uhf6DV8LNftd98J5211uW8PiUDFoazI2nBdDT+UADb6/Nwp1Q70fehyJv8F6eCbgFPcoBdaEMXYKNKYYL+2MiIj+jcGHbl1ONoyLZkBSb4xdUCJjYB3wotuWyHYoGLA5GVsuifOsqgdp8f29UagZ7N3/hHPHT6yB7cRiuI6fuP3a+AnfGJVBREQMPlQC8sr50CQlCDXrM+OAAPcMAs2wK3jsJzN2JNiEeu3g3NBTNcjLoUdxwHZ8PhyX/udyTVf1YRjqPcPxE0REPobBh26Jdu9O6LetE2q2Hr3hbNTSLa+fZlPQZ6MZvyeKoadBqA5r741CxQDvBopCx0/UGw591Qe8szEiIioUgw8VX0Yq5CVxQkmpVB22Ps+65eWTLU702mjGXrNdqDcJ1+G7e6IQbfJu6MkdPzERavYF8YI2AHLT16GLbOWdjRER0U0x+FDxqCqMy9+DJi3lRkmjgeXZCYCh5AcHJuY48dCGJBxOEU86bhmlx5oeUQiXvTtlxZlyAJYDUwFHhlCXjBVhbD4FmsAaXtoZEREVBYMPFYtu12bo/tgm1Ow9n4RSu+St2peznXhofRKOp4mhp20FA1Z1j0Sowbuhx355E2xH53H8BBGRH2PwoSKTkhMhfzZXqDlr1oftwSdL/NrnMx3ouT4JpzOcQv3uigas7BaJIL33Qk/u+InlsJ/9yuWaNqYL5IYjIWm9f3giERHdHIMPFY2qQv50FqTsG0NBVb0+9ysuXcn+Mzqd7kDPDUk4nymGnq5VZKzoEgmTznvjHXLHT8yGM/FXl2v6Wk9CX/Nxjp8gIvIjDD5UJLqfv4fu4B9Czfbos1Cr1CzR68an2dFzfRIuZytC/b5qRizrHAFZ671QUfj4iVHQxXT0zsaIiOiWMfjQTUlXLkD+8iOh5mzYHPYevUv0uodT7Hh4QxKu5oih5+GaJizqGA69xnuhp6DxE9CHwRg7meMniIj8FIMPFU5xwvjJdEi2G6MYVKMJlqHjAM2t33ezN8mGXhvNSLaKoadfHRPm3xUOnRdDjyNpF6yHZnD8BBFRGcTgQ4XS//gltCcOCTXrgJegRle65df8M9GGXhuTkG4TRzwMrB+Aue3DoPHSPTMcP0FEVPYx+FCBNOdOwLBmqVBztLgDjrvvu+XX3JlgRd9NZmQ6xGDxTKNAzGwb6r3QU+j4iYdgqPssJA3HTxAR+TsGH8qf3Qb5k+mQnDfOrFGDQmAdPBq4xXDye6oGr+0yIztP6BnRNAhTWod4rTuq8PETz0Nf9UGv7IuIiNyPwYfyZfh2GbTnTwo1y1OjoIZF3tLrbTxvwSuHZNhUMfSMaRGM8S2CvRZ6Ch8/MQG6yNZe2RcREXkGgw+50Bw/AP2PXwo1+x3d4Lz91tq3/3cuBwO3JMOuiuFmYqsQvBobfMv7LCln6sHc8RP2dKEuGWNyb2IOqumdjRERkccw+JDIkg3joumQ1BvdVkp4FKxPvnxLL7cn0YYhW1NgF5u3MK1NKIY3CSrJTkvEfvkn2I7O5fgJIqJyhsGHBPJXC6G5ekmoWYeOAwKL/8nM+UwH+m82I8cpfr01545QPN3QO6End/zEZ7Cf/dLlmjamM+SGr3D8BBFRGcbgQ9dpD/wO/c9rhZqt68NwNi3+fS7pNgX9NplxJc/hhO/eEYYhDb3TEs7xE0RExOBDubIyIC+eJZSUmCqw9RtW7JdyKCoGb03G4VTxa6SBVexeCz254yemQMk4Ll7Q6K+Nn+jklX0REVHpYvAhAID8+TxoUm+MZ1AlTe4AUtlUrNdRVRVjdqVh80WrUO9Zw4gXqma7Za/F5cw4dW38RKJ4QR8GY+wkaEMbeWVfRERU+m595gCVGbrdW6D/7SehZn/gcSh1mxT7teYfysSSY1lCrVWUHh93CIc3plA4knbBsudVl9AjBdaEqfU8hh4ionKGn/iUc1KqGfLy94Sas3od2B4eVOzX+uFsDt78Q2wNrxqoxRddIxGgK92MnTt+4lvYTiwCx08QEdE/GHzKM1WFvCQOUtaNsKLq9LA+MwHQ6Yv1UnuTbHh2e4oQMUL0ElZ1j0RMQOmOeuD4CSIiKgiDTzmm27YOun27hJqt1xAo1esU63UuZDrw2E/iKAqtBCzvHIHG4cULUCWl2jOvjZ/4W7zA8RNERAQGn3JLSrwMeeV8oeas1xT2+/oW63Uy7Ar6/WRGQp629Tl3hKFzFWOJ91kcueMnJkHNPi9e4PgJIiK6hsGnPFKcMH4yHZIl53pJlY2wPDMeKMZXQA5FxZAtyTiUIratv9Q0CE81KN37Zzh+goiIioLBpxzSb1gN7fH9Qs3afzjUmCpFfg1VVTF+dxo25Wlbf6C6EVNah7hln0WVO35iHqDahbompBGMsZM4foKIiK5j8ClnNBdOw7B6sVBzNGsDR6fi3fvy8eEsLDoqtq23jNLjk47h0JTS6cccP0FERMXF4FOeOOyQP5kGyXHjkxE1MBjWp8cAxQgrP57LwYTf04Ra1UAtVpZi27rqtMB6ZA6cV39xucbxE0REVBAGn3LE8P3n0J6NF2rWgSOhhkcV+TX2JtkwdJvYth6sl/BVt0hULKW2dcWaDOv+yRw/QURExcbgU05oTh6G/r8rhJq9bWc42nUt8mtczHKi/2bXtvWlnSLQJKJ02tY5foKIiEqCwac8sFpyu7iUGy3nSmgErANHFvkl/mlbv5wttq3PaheKblVLp23dkbQb1kMzAGeOUJcCa8IYOxkaU8VS2QcREfkvBp9ywPD1ImgSxLNtrE+PAYJCi/R8h6Ji6NZkHEwWu6ZeaBKEpxsGuW2fBVFVFY4L38EWvwiAGLy0Ea0hNx3P8RNERFQkDD5lnPbQXzBs+kao2Ts9CGfzdkV+jQm/p2HDBbFt/f7qRkwthbZ1VXHAFv8RHBfXuVzTVe0JQ91hHD9BRERFxuBTlmVnQl48Uygp0ZVgfez5Ir/EwsOZ+OSI2LbeIlKPRR3CofXwuPXc8RPToKTsyXNFA0P956Cv2tOj6xMRUdnD4FOGyf/5AJrkq9d/ViUp93RmU0CRnr/hvAXj87StVwnQYmW3SATqPdu2ruRchmXfJKjZ58QLHD9BREQlwOBTRmn//AX6XzcINft9/aA0iC3S8/ebbRiyNRnKv/rWg3QSvuoeiUoeblvn+AkiIvIUBp8ySEpPgbxsjlBzVq0F2yODi/T8S1lO9PvJjKx/ta1rJGBJpwg09XDbOsdPEBGRJzH4lDWqCnnpbGgyUm+UtFpYn50AGOSbPj3TruCxfNrWZ7YNRY9qnmtbL3z8RCfIDV/l+AkiIioxBp8yRrdjA3R7dgg128NPQalR76bPdSoqhm5Lwf48bevPNQ7EM40817auOq3Xxk9sd7nG8RNERORODD5liGS+AnnFB0LNWacR7P/Xv0jPf/2PNKw/bxFq91Yz4p3bi3bez61QrMmwHpgCJf2YeIHjJ4iIyAMYfMoKRYG8eCaknBut56pBhuXZCYD25m/zoiOZ+Piw2LYeG6HH4o6ea1tXMk/Bsm8yVOtV8YI+DMbYidCGNvbIukREVH6VzijtQixevBixsbGIiYlBx44dsXPnzgIfm5CQgKFDh+L2229HREQEnn++6OfRlHX6n76F7rB43o2t7zCoFavd9Lkbz1swdrfYtl45QIMvu0UiyENt646k3cj5a5RL6JECa8DUei5DDxEReYRXg8+aNWswbtw4jBo1Ctu3b0ebNm3Qp08fnD9/Pt/HW61WREREYOTIkWjdmue4/EO6dBaGVQuFmqNJK9i7PnzT5x5Itru0rQfqJHzZLRKVA93ftq6qKuznv4N1/xSXmVvaiNYwtXqXM7eIiMhjvBp85s+fj8cffxyDBg1CgwYNEBcXh5iYGCxZsiTfx9eoUQOzZs3CgAEDEB4eXsq79VFOR+4AUrvtekkNCIT16bGApvC393K2E49tMiMzn7b12EgPdFCpTtiOz4ct/mPknbmlq9oTcuwUztwiIiKP8lrwsdls2Lt3L7p06SLUu3Tpgt27d3tpV/5H/8MX0J4+KtSsT7wMNbJCoc/Luta2fjHbKdSntwnFPR5oW1ftmYhI/BiOiz/kuaKBof5wyPWHc+YWERF5nNdubjabzXA6nYiOjhbq0dHRuHr1agHPujXx8fFufT1fYbp8Fg2+Wy7UUhvehtPRNYFCfs1OFRh7xIB9yeLb36+SHV30lwt76i3ROpIQkbgQRkeCUFckI1IiB8Oa06jQ/ZLnlNU/G/6K74fv4XviG+rVu/mRLEXl9a6uvOezqKrq9jNb3Pkb5jNsVpiWvANJufGJjRISDt0LE1EvpPDTjSf8noptyWIH1z1VZSzoWtntHVzO1EOwHJgLOMSbpyVjBQTGTkUwx094TXx8fNn8s+Gn+H74Hr4nZZPXgk9kZCS0Wq3LpztJSUkunwKRK8M3n0J76YxQsw4eBdwk9Hx6NBMLDomhp2mEHos7Rbg99DgSNsN6ZG4+4ycaXhs/wfu0iIiodHntHh+DwYAWLVpgy5YtQn3Lli1o27atl3blHzRH90K/4WuhZr/7Pjhvu6vQ5/10wYIxu8RPXioFaPBVt0gEu7FtXVUV2E4th/VwnEvo0VboCGPLWQw9RETkFV79quuFF17AsGHD0KpVK7Rt2xZLlixBQkICBg/OHaY5bNgwAMDChTdatffv3w8ASE9PhyRJ2L9/PwwGAxo2bFj6vwBvyMmGcdEMSOqNTiwlKgbWAS8W+rRDyXYM3poM57/a1gN0ElZ2jUQVN7atFzZ+Ij3kPlRsMoLjJ4iIyGu8Gnx69eqF5ORkxMXF4cqVK2jUqBFWrVqF6tWrAwAuXLjg8pwOHToIP69fvx7VqlXDgQMHSmXP3iavnA9NkniTsHXoOMBUcBt4QnbutPUM+43UIwH4tGM4WkS5r2290PETDV9FZkZVhh4iIvIqr9/cPHToUAwdOjTfa+vWrXOppaam5vPI8kG7dyf028TfE1uPR+Fs1LLA52TZFfTfbMaFLLFtfVqbUNxX3eS2vSmZp2HZNymf8ROhMMZOyj2JOYPdEURE5F1eDz5URBmpkJfECSWlUnXY+jxT4FMUVcWw7Sn4O0m8z+aZhoF4rrH7Dgp0JP0O66HpLicxS4E1YIydwpOYiYjIZzD4+ANVhXH5e9CkpdwoaTSwDJsAGOQCnzbpz3T8cE6ctt69iozpbUPd8pWTqqpwXFgLW/wnyHsSszaiNeSm43kSMxER+RQGHz+g27UZuj+2CTV7zyeh1Cr4hu6lR7PwwcFModYkXIclnSOgc0Pbuqo4YYv/KJ+TmHPHTxjqDuNJzERE5HMYfHyclJwI+bO5Qs1Zsz5sDz5Z4HM2X7Rg9C7xXqiKJve1rauOLFgPvgNn8p48VzQw1BsGfbWHSrwGERGRJzD4+DJVhfzpLEjZNz65UfV6WJ6dAOjyf+sOp9jx1BbXtvUvu0WialDJ324l5zIs+ydBzTonXtAGQG46HrrI20u8BhERkacw+Pgw3c/fQ3fwD6Fme/RZqFVq5vv4K9lO9N3k2ra+qIN72tZzx09MBeyu4yeMsVOh4fgJIiLycQw+Pkq6cgHylx8JNWfD5rD36J3v47Md+betv3V7CP6vRsnb1h0JP8N65D2OnyAiIr/G4OOLFCeMn0yHZLvRkaUaA2AZOg7QuN6jo6gqntuegj152taHNAjEC02CSrQVVVVhP/057Ge+cLmmrdARcqNXIWkL7iwjIiLyJQw+Pkj/45fQnjgk1KwDXoQaXSnfx0/5Mx3fnxXb1rtVkTGrXcna1nPHT7wL59VtLtf0NQdAX+sJnsRMRER+hcHHx2jOnYBhzVKh5mjRHo6778v38cuPZWFenrb1xuE6LOlUsrZ11ZYCy/4pUNKPihckPeRGr0JXsfMtvzYREZG3MPj4ErsN8sJpkJyO6yU1OBTWIaOBfD5Z2XrJgld/E9vWY661rYcYbr1tvUjjJ4iIiPwQg48PMXy7DNoLp4SaZdCrUEMjXB57JMWOgT+LbesmbW7berUStK0XPH6iem7nFsdPEBGRH2Pw8RGa4weg//FLoWZv3x3O2zu6PPZqjhN9fzIjPU/b+icdw9HyFtvWCx8/cRvkpq9z/AQREfk9Bh9fYMmGcdF0SOqNwKGER8H6xAiXh+Y4VDy+2YzzmWLb+tTWIXjwFtvWCx0/UeUBGOo9z/ETRERUJjD4+AD5q4XQXL0k1KxDxwGBwUJNUVU890sy/kwU29afqh+AF5veWtt67viJaXAm/5XnCsdPEBFR2cPg42XaA79D//NaoWbr+jCcTVu7PPatv9Kx9ozYtt65soy4O8Juqa1cyUmAZf/E/MdPNBkHXVSbYr8mERGRL2Pw8aasDMiLZwklJaYqbP2GuTz08+NZeO+A2LbeKEyHZZ0joL+FtnVn2mFY9k9xHT8hV4Cx+RRogmoV+zWJiIh8HYOPF8mfz4MmNen6z6qkgeXZ8YAs3quz7ZIFr+wU29YrmDT4slskQm+hbd2RsAXWo+8CCsdPEBFR+cLg4yW63Vug/+0noWZ/4HEodZsItWOpdjy5JRmOPG3rK7tGokZw8d6+3PETK2A/8x+Xaxw/QURE5QGDjxdIqWbIy98Tas7qdWB7eJBQS8zJnbaeblOF+scdwtEqunht6zcfPzEAknTrhx4SERH5Awaf0qaqkJfEQcpKv1HS6WF99nVAp79ey3GoGLA5GWfztK1PaR2Ch2oWr2298PETr0BXsUvxfx1ERER+iMGnlOm2rYNu3y6hZus1BEq12td/VlQVw39Jwe+JNuFxA+sHYEQx29aVzDO5nVuWfMZPNJsIbViT/J9IRERUBjH4lCIp8TKoD40OAAAcDElEQVTklfOFmrNeU9jv6yvU3tmTjm/PiCMjOlWWMaeYbesO8x+wHpwOOLPFfQRWhzF2CjSm/Ke9ExERlVUMPqVFccL4yXRIlhuBRpWNsDwzHvjXqcgr4rMwZ7/Ytt4wTIdlnYrXtm4/vxa2+IXg+AkiIqIbGHxKiX7DamiP7xdq1v7DocZUuf7z9stWjNwhtq1HGXPb1sPkot14nDt+4mM4Lv7X5RrHTxARUXnH4FMKNBdOwbB6sVBzNGsDR6cHr/98PNWOJ382C23rRi2wsmskahaxbb3w8RPPQlf1oVs64ZmIiKisYPDxNIcd8ifTITluHBaoBgbD+vQY4FoISbLkTltPy9u2fncEbq9QtLb1gsdPmK6Nn2hbsl8HERFRGcDg42GG7z+H9my8ULMOHAk1PAoAYLnWtn4mQ2xbn9QqBA/XKlrbOsdPEBERFQ2DjwdpTh6G/r8rhJq9bWc42nUFkHuS8os7UrD7qti2/mS9AIxsVrS29cLGT8jNJkIjR5TgV0BERFS2MPh4itWS28Wl3OiqUsIiYR048vrP0/7OwOpTYtt6h0oy3m1/87b1wsdPdIDcaBTHTxAREeXB4OMhhq8XQZNwXqhZh4wBgkIBACtPZCNuX4ZwvX6oDp8VYdq66rTBevRdOK9sdbmmr9kf+lpPcvwEERFRPhh8PEB76C8YNn0j1OydHoSzee4Nxr9ctmLEjhThepRRg1Xdb962Xvj4iZHQVexa8l8AERFRGcXg427ZmZAXzxRKSnRlWPs/DwCIT8ttW7f/61xBWQt80TXipm3rhY+feBPasKZu+SUQERGVVQw+bib/5wNokm8EE1WSYHl2HGAMgNmSO209NU/b+kd3haNNhcLvx3GY/4T14DTX8RMB1XM7tzh+goiI6KYYfNxI++cv0P+6QajZ7+sHpX4srE4VT/ycjNN52tbfuC0EvWoHFPq69gvfw3b8Y+QdP6EJvw3GphMg6Ys3uJSIiKi8YvBxEyk9BfKyOULNWbUWbI8Mzm1b/zUFv10R29b71w3AqNiCQ0vh4yf+79r4Cb6FRERERcX/13QHVYW8dDY0GTfmbKlaHazPTgAMMmb8nY6v87St31XRgHmFtK3njp+YDmfyn3mucPwEERHRrWLwcQPdjg3Q7dkh1GwPD4JSox6+OpmNmXvFtvV6oTp83iUSBm3+wSV3/MQkqFlnxQscP0FERFQiDD4lJCUlQF7xgVBz1mkE+//1x84EK176VWxbj5Q1WNUtEuEFtK0XPH4i+tr4idru/QUQERGVIww+JaEokBfPhJSTdb2kGmRYnp2Ak5nAgJ/NsP3rfmSDBvhP1wjUCsn/t73g8RMNIDebxPETREREJcTgUwL6n76F7sjfQs3W7zmYwyqjzw+JSLGKbesL7g5HuxjXtnVVVWE/8x/YT69wuaatcDfkRqM5foKIiMgNGHxukXTpLAyrFgo1R5NWyOzYEwM2JeNUnrb1CS2D8Wg+bescP0FERFR6GHxuhdORO4DUfqM9XQ0IhGXIGLz0W5pL2/pjdUx4rXmwy8vkjp+YCiX9iHhB0sPQ8GXoK3XzyPaJiIjKKwafW6D/4QtoT4uzsqxPvIyZF0xYdVLs4GofY8C8O8NdWs8LHj8RAmOziRw/QURE5AEMPsWkOX0MhrXLhZqjdQesjLkT039JFep1QrRY0SUCcp629YLHT1SDMXYKNAGVPbN5IiKico7BpzhsVsifTIfkvHH/jhISjl/vfwEv/CqGnnBZwqpuUYgwaoV6weMnWsLY9HWOnyAiIvIgBp9iMHzzKbSXzgi1c4+9gr67Fde29S6RqBN647dXVZywnVgIx4XvXV5XV/l+GOoP5/gJIiIiD+P/0xaR5uhe6Dd8LdQy29+LexMaINnqEOof3hWO9hVvtJ+rjixYD82A0/xHnleVro2feJjjJ4iIiEoBg09R5GTDuGgGJPXGuTzOyBj0qdQfJ8xi6BnXIhh969xoWy94/IQRcpPxHD9BRERUihh8ikBeOR+apAShNqPtC9hkFn/7+tYxYWyLG23rueMnpgJ28f4fSY6GHDsF2mCOnyAiIipNDD43od27E/pt64Taby17YlJ2HaF2R4wBH/yrbd1xZSusR+a4jp8Irg85dhI0cqRnN05EREQuGHwKk5EKeUmcUEqNqobuQY8ItdrBWvznWtt6oeMnou+C3Hg0JK3Ro9smIiKi/DH4FERVYVz+HjRpN6arKxoNHqj1LCxaw/VauCxhVfdIRBi118ZPvAfnlS0uL6ev8Rj0tQdy/AQREZEXMfgUQLdrM3R/bBNqs2s9gl2BN+7L0WuAFV0iUTdUD9WWCsv+KfmMn9DB0HAkx08QERH5AAaffEjJVyF/NleoHQytjYlVegq19+8Mx50V5WvjJyZBtVwRX4jjJ4iIiHwKg09eqgr50zhI2ZnXSzaNHo/Vfw6Ofx0w+FrzYPSvG8DxE0RERH6EwScP3c/fQ3dQPGhwXK1+OBpY5frPfWqbMKFlcCHjJ1rA2PQNjp8gIiLyMQw+/yIlXID85UdCbWtYI3xQ9Z7rP7erYMD77UNgi/+ogPET98FQ/wWOnyAiIvJB/H/nfyhOGBdNh2SzXC+la414usEwqNc6sWoFa/GfjkZIh6fAkd/4ibrPQFftEY6fICIi8lEMPtfof/wS2hOHhNordQfirCkaABBmkPBNBydMh16DM+uM+GStEXKTcdBFtSul3RIREdGtYPABoDl3AoY1S4XafyNvw/KKHQDktq1/c0cSYo5Ng+oyfiIKcuxUjp8gIiLyAww+dhvkhdMgOW8MG03UB2NYg6HAta+sVrc4iIbnPsxn/EQ9yLGTOX6CiIjIT5T74GP4dhm0F04JteH1h+CqIRSAiq/rb0Rr8yqX53H8BBERkf8p18FHc/wA9D9+KdQ+j7kL30a3gQw7vqrxOW637nB5HsdPEBER+afyG3ws2bldXOqNM3jOyxEYWXcgIjXp+KryAjRCvPgcjp8gIiLya+U2+MhfLYTm6iWh9kyDZ1EhIA1fxMxDZW2S+ASOnyAiIvJ75TL4aA/8Dv3Pa4Xah1V6wF5Zwn+jpyFYkyNckwKqwhg7leMniIiI/Fz5Cz5ZGZAXzxJKx00VcbBFJXwWOQ86Kb/xE69D0geX5i6JiIjIA8pd8JE/nwdN6o2vsRyShF+61MGUqK9cHsvxE0RERGVLufp/dN3uLdD/9tP1nxU9sPeeKngg8q88j5RgqDsUumq9OH6CiIioDCk3wUdKNUNe/t71n52BwOXuQagWmucmZq0RcuOx0EXfUco7JCIiIk8rH8FHVSEviYOUlQ4AsEVJSO1igN7kEB6WO35iCrTBdbyxSyIiIvKwchF8dNvWQbdvFwDAUlODtLv0gFb8CovjJ4iIiMq+8hF8vpgPFUBWrBZZLfUu1zl+goiIqHwoF8FHa89B+l16WOpoXa7pa/SDvvYgjp8gIiIqB8pF8Em5xwB7hTzBRtLB0HAE9JV6eGdTREREVOq8/jHH4sWLERsbi5iYGHTs2BE7d+4s9PG//vorOnbsiJiYGDRv3hxLliy56RouoUcXDGOL6Qw9RERE5YxXg8+aNWswbtw4jBo1Ctu3b0ebNm3Qp08fnD9/Pt/HnzlzBn379kWbNm2wfft2vPrqqxgzZgzWrl2b7+PzI5mqwNR6HrThzdz1yyAiIiI/4dXgM3/+fDz++OMYNGgQGjRogLi4OMTExBT4Kc7SpUtRsWJFxMXFoUGDBhg0aBD69++PDz/8sGgLhjWHqfVcztwiIiIqp7wWfGw2G/bu3YsuXboI9S5dumD37t35Puf33393eXzXrl3x999/w263F7qevcI9CGjxDmduERERlWNeu7nZbDbD6XQiOjpaqEdHR+Pq1av5Pufq1avo1KmTy+MdDgfMZjMqVqyY7/PO6u+H3nAvEk+edsve6dbFx8d7ewv0L3w/fAvfD9/D98Q31KtXz22v5fWurryzsFRVLXQ+Vn6Pz6/+b43vHlGCHZK7xMfHu/U/XioZvh++he+H7+F7UjZ57auuyMhIaLVal093kpKSXD4F+keFChXyfbxOp0NERITH9kpERERlg9eCj8FgQIsWLbBlyxahvmXLFrRt2zbf57Rp0wZbt251eXzLli3x/+3deVRUdRsH8C8vhQoFkwgDBriAC6vJKdzlxIiA1BE1Q4JTisoiZJobWC68uYCcpGRTIVQCMkwQU5MM5YAsaonlclDRJFEZE0ECF0B4/+gwrxMIzCSDcL+fc/iDO8+997k+Z5yH3+935774YstvZCYiIiJ6Upfe1RUQEICUlBQkJibi4sWLWLFiBcrLyzFnzhwAgK+vL3x9fWXxc+bMwc2bNxEUFISLFy8iMTERKSkpCAwM7KpLICIiom6kS9f4TJ8+HXfv3kV4eDikUinMzc2RmpoKExMTAEBZWZlc/MCBA5GamoqVK1ciISEBBgYGCAsLw9SpU7sifSIiIupm1Kqqqpq6OgkSBi4UfL6wHs8X1uP5w5r0TF3+yAoiIiIiVWHjQ0RERILBxoeIiIgEg40PERERCQYbHyIiIhIMNj5EREQkGGx8iIiISDDY+BAREZFgsPEhIiIiwWDjQ0RERILBxoeIiIgEg40PERERCQYbHyIiIhIMPp2diIiIBIMjPkRERCQYbHyIiIhIMNj4EBERkWCw8SEiIiLBYONDREREgtGtG5/4+HjY2NhALBbD3t4e+fn5bcYfP34c9vb2EIvFGDFiBBISElSUqTAoUo/9+/dj2rRpMDU1hZGRESQSCQ4dOqTCbHs+Rd8fzQoKCqCrq4sxY8Z0cobComg96urqsH79etjY2EBfXx9WVlbYunWrirIVBkVrsmfPHowfPx6GhoYYOnQofHx8IJVKVZRtz5WXl4dZs2bB3NwcIpEIycnJ7e5z/vx5TJkyBQYGBjA3N0dYWBiamjp2k3q3bXzS0tIQFBSEJUuWICcnB3Z2dpg5cyauX7/eavy1a9fw7rvvws7ODjk5Ofj444+xfPlyZGRkqDjznknReuTl5WHixIlITU1FTk4OHB0d4eXl1eEPZ2qbovVoVlVVBT8/P9jb26soU2FQph5z585FVlYWvvzyS5w6dQo7d+6EpaWlCrPu2RStSWFhIXx9feHh4YGCggIkJyejuLgY8+fPV3HmPU9tbS0sLCwQGhqKPn36tBtfXV2NadOmQV9fH0ePHkVoaCgiIyMRFRXVofN12+/xkUgksLS0xJYtW2TbbG1tMXXqVKxZs6ZF/Jo1a/D999/j9OnTsm0ffvghiouLceTIEZXk3JMpWo/WODg4YMyYMVi/fn1npSkYytbDy8sLVlZWaGpqwv79+1FQUKCKdHs8Retx9OhRzJ49G0VFRdDV1VVlqoKhaE0iIyOxbds2nDt3TrYtKSkJK1aswI0bN1SSsxC8+uqr2LRpEzw9PZ8a89VXX2Ht2rW4dOmSrFEKDw9HQkICLly4ADU1tTbP0S1HfOrq6nDmzBk4ODjIbXdwcMCJEyda3efkyZMt4iUSCYqKilBfX99puQqBMvVoTU1NDUQi0bNOT3CUrUd8fDxu376NZcuWdXaKgqJMPQ4ePIiRI0ciOjoaFhYWsLW1xfLly1FTU6OKlHs8ZWoyatQoSKVS/PDDD2hqakJFRQXS0tLg6OioipTpCSdPnsSYMWPkRockEglu3bqF0tLSdvfvlo1PRUUFHj9+DD09Pbntenp6uH37dqv73L59u9X4hoYGVFRUdFquQqBMPf4pLi4ON2/ehLu7e2ekKCjK1OP8+fMICwvD9u3boa6uroo0BUOZely7dg2FhYU4d+4cEhMTER4ejqysLCxYsEAVKfd4ytTEzs4O8fHx8PHxgZ6eHkxNTdHU1ITY2FhVpExPeNrnefNr7emWjU+zfw5nNTU1tTnE1Vp8a9tJOYrWo1lGRgZWr16N7du3w8TEpLPSE5yO1uPRo0eYO3cuPvvsMwwcOFBF2QmPIu+PxsZGqKmpIS4uDq+//jokEgnCw8Oxf//+Dv8xQe1TpCbFxcUICgrCsmXLkJ2djb1790IqlWLRokWqSJX+4d98nr/QKRl1Ml1dXairq7f4D+DOnTstusBm+vr6rca/8MIL6Nu3b6flKgTK1KNZRkYG/Pz8sHXrVkyZMqUz0xQMRetRXl6O4uJiBAQEICAgAMDfH7xNTU3Q1dXFnj17WkwJUMcp8/4Qi8UwNDSEjo6ObNvQoUMBAGVlZdDX1++8hAVAmZps3rwZtra2WLhwIQDAysoKmpqacHFxwapVq2BkZNTpedPfnvZ5DqDdzxygm474aGho4LXXXsOxY8fkth87dgyjRo1qdR87OztkZ2e3iB85ciRefPHFzkpVEJSpBwCkp6fD19cXMTExmDp1amenKRiK1qN///7Iz89Hbm6u7Mfb2xuDBw9Gbm4u7OzsVJV6j6TM+2P06NEoLy+XW9Nz5coVAICxsXHnJSsQytTkwYMHLaaBm3/v6G3U9GzY2dmhoKAADx8+lG07duwYDA0NMWDAgHb3Vw8KClrbifl1mpdffhkbN26EgYEBevfujfDwcOTn5yMqKgo6Ojrw9fXFgQMH8PbbbwMABg0ahC+++AJ//vknjI2NcejQIXz++edYt24dhg8f3sVX0/0pWo+9e/fCx8cHISEhmDx5Mmpra1FbW4v6+voO3c5IbVOkHurq6tDT05P7OX36NK5cuYLg4GBoaGh09eV0e4q+P8zMzJCcnIwzZ85g+PDhuHLlCpYtW4Zx48a1ebcLdZyiNXnw4AEiIyOhq6uLvn37yqa+xGIxPvrooy6+mu6tpqYGxcXFkEql+Prrr2FhYQFtbW3U1dVBR0cHISEh2Lx5Mzw8PAAApqam2LFjB86ePYshQ4agoKAAq1evxqJFi9r8Y7tZt5zqAoDp06fj7t27CA8Ph1Qqhbm5OVJTU2VrRMrKyuTiBw4ciNTUVKxcuRIJCQkwMDBAWFgYRxqeEUXrkZCQgIaGBgQHByM4OFi2fdy4cTh48KBKc++JFK0HdS5F6/HSSy9h3759WL58ORwcHCASieDq6trhr4ag9ilaE09PT9TU1CAuLg6ffvoptLW1MWHCBISEhHRF+j1KUVGRrMEEgI0bN2Ljxo3w8PBAbGwsysvL8fvvv8te19HRQXp6OpYuXYo333wTIpEIAQEBCAwM7ND5uu33+BAREREpqluu8SEiIiJSBhsfIiIiEgw2PkRERCQYbHyIiIhIMNj4EBERkWCw8SEiIiLBYONDRN2Wq6srXF1dn+kxS0tLIRKJkJyc/EyPS0TPBzY+RNSq5ORkiEQi2Y+uri4sLCwQGBiI8vLyrk7vX9u+fTubGyIB6rbf3ExEqhEUFIRBgwbh0aNHKCwsREpKCvLy8pCfn9+tHy8SFxcHfX39Fo+AMDExQXl5OZ/hR9RDsfEhojZJJBK88cYbAID3338fr7zyCqKjo3Ho0CHMmDGji7N79tTU1NC7d++uToOIOgmnuohIIRMnTgQAXLt2DQBw/fp1zJ8/H4MHD4ZYLMb48ePxzTffyO3TvG4mIiIC27Ztg42NDQwMDDBp0iT8/PPPcrH+/v6wtrZucd7mqbfS0tI284uMjISTk5Msn7FjxyIxMVEuxtraGpcvX0ZeXp5sKq/5nE9b43PhwgXMmjULJiYmMDQ0hKOjI44cOSIXk5ubC5FIhO+++w5RUVGwtraGWCyGo6Mjfv311zbzJiLV4IgPESmk+WGBffv2RUVFBZydnVFZWQkfHx8YGBggLS0N/v7+qKqqgr+/v9y+e/bswb179zB37lw0NjYiPj4ebm5uyM7OhpmZ2TPJLyYmBpMmTYKbmxvU1NRw4MABLFy4EI2NjZg9ezaAvx+CuHTpUmhra2PJkiUAAC0traces6SkBM7OztDQ0MCCBQugpaWFlJQUuLu7Y9euXXIPWASAqKgo1NfXw8fHBw0NDdiyZQs8PT1RVFTEKTSiLsbGh4jaVF1djYqKCjx8+BAnTpzApk2b0KdPHzg5OSEiIgI3btxARkYG7O3tAQDe3t5wcXHBunXr8N5770FHR0d2rJKSEpw6dQoDBgwAALi5uWH06NEIDQ1FfHz8M8n3l19+gaampux3Pz8/uLm5YcuWLbLG56233kJISAj09PTg7u7e7jH/+9//4v79+/jpp58wdOhQAMAHH3yAsWPHIjg4GK6urvjPf/4/gF5dXY38/HzZlNmQIUPg5eWFo0ePwsnJ6ZlcJxEph1NdRNSmGTNmwNTUFJaWlvD29oZYLMa3336L/v37IzMzEzY2NrKmBwA0NDTg7++P2tpaHD9+XO5YLi4usqYHAMzMzCCRSFpMGf0bzU1PfX09KisrUVFRgYkTJ+Lq1au4d++ewsd7/PgxsrKy4OzsLGt6AEBbWxve3t4oKyvD+fPn5fbx9PSUWyc0fvx4AP+fHiSirsMRHyJqU1hYGIYNG4ZevXrByMgIRkZGUFNTAwD88ccfLaZ5AGDYsGGy159kamraItbU1BSZmZm4d++e3OiQsg4ePIjw8HCcPXsWjx8/lnuturpa4XPcuXMHtbW1ck1Psyev88l1ScbGxnJxIpEIAFBZWanQuYno2WPjQ0RtsrW1ld3V1VFNTU2tbm9umNqKbS0GQIsmpjWFhYXw8vLC6NGjERERAQMDA2hoaODHH39ETEwMGhsbO5B9xz3tOtXV1RWKJyLVYeNDREozMTHBpUuXWmy/fPmy7PUnlZSUtIi9evUqdHR0ZCMxIpGo1Smpf44etWbfvn3o3bs30tPT5aaacnNzW8Q+rcH6p379+kFLS0uh6ySi5xfX+BCR0pycnPDbb78hJydHtq2+vh5bt26FpqambG1Ls8OHD8vdjl5SUoKsrCxMmjRJtm3w4MGorq6Wu/27pqYGu3fvbjcfdXV1qKmpyY3sVFVVISkpqUWspqYmqqqqOnRMiUSCzMxMucbtr7/+wo4dO2BkZARLS8t2j0NEzweO+BCR0hYvXoy0tDR4eHjA19cXYrEY6enpOHXqFDZs2NBiPY2pqSmmTJmCefPmobGxEXFxcejVqxdWrFghi3nnnXcQEhICLy8v+Pn5oaGhAUlJSejXrx/KysrazMfZ2RnR0dGYNm0a3N3dUVlZiV27dkFfXx9SqVQuduTIkdi5cydCQ0NhZmYGLS0tuLi4tHrcVatWITs7Gy4uLpg3b57sdvaysjLs3LlT7o4uInq+sfEhIqXp6uoiMzMTISEh2LFjB+7fvw8zMzPExsbCw8OjRfzMmTOhqamJ6OhoSKVSWFlZYcOGDXILh0UiEZKSkvDJJ59g7dq1MDQ0hL+/P7S1tREQENBmPhMmTEBsbCwiIiIQHByM/v37w8fHByKRCIGBgXKxQUFBuHXrFmJiYlBdXQ1jY+OnNj5DhgzB4cOHERISgujoaNTV1cHa2hq7d+/G5MmTlfiXI6KuolZVVcXVdkTUqUpLSzFixAisWbMGixcv7up0iEjAOD5LREREgsHGh4iIiASDjQ8REREJBtf4EBERkWBwxIeIiIgEg40PERERCQYbHyIiIhIMNj5EREQkGGx8iIiISDDY+BAREZFg/A+cbCAjwFtslwAAAABJRU5ErkJggg==\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "lift_actual = [0.] * (n_segment + 1)\n", "lift_actual[n_segment] = ate_all[0]\n", "\n", "lift_xlearner = [0.] * (n_segment + 1)\n", "lift_xlearner[n_segment] = ate_all[0]\n", "\n", "for i in range(1, n_segment):\n", " lift_actual[i] = ate_actual[0][n_segment - i] * .2 + lift_actual[i - 1]\n", " lift_xlearner[i] = ate_xlearner[0][n_segment - i] * .2 + lift_xlearner[i - 1] \n", "\n", "pd.DataFrame({'Population': np.linspace(0, 1, n_segment + 1),\n", " 'Actual': lift_actual,\n", " 'X-Learner': lift_xlearner,\n", " 'Random': np.linspace(0, 1, n_segment + 1)*lift_actual[-1]}).plot(x='Population', \n", " y=['X-Learner', 'Actual', 'Random'], \n", " figsize=(8, 8))\n", "plt.ylabel('Lift in GB')" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.6.0" }, "pycharm": { "stem_cell": { "cell_type": "raw", "metadata": { "collapsed": false }, "source": [] } }, "toc": { "base_numbering": 1, "nav_menu": {}, "number_sections": true, "sideBar": true, "skip_h1_title": true, "title_cell": "Table of Contents", "title_sidebar": "Contents", "toc_cell": false, "toc_position": {}, "toc_section_display": true, "toc_window_display": true } }, "nbformat": 4, "nbformat_minor": 2 }