{ "cells": [ { "cell_type": "markdown", "id": "0e973fef", "metadata": {}, "source": [ "# Tutorial 1: Disease diagnosis and biomarker identification" ] }, { "cell_type": "markdown", "id": "da54dc6a-8c31-4764-9f14-439dc67fc5f9", "metadata": {}, "source": [ "CellFreeGMF leverages machine learning and differential expression analysis to achieve diagnostic classification and biomarker identification for pancreatic ductal adenocarcinoma." ] }, { "cell_type": "markdown", "id": "a133b6c0-d5d7-43a6-9975-80d5e95659d2", "metadata": {}, "source": [ "## Preparation" ] }, { "cell_type": "code", "execution_count": 1, "id": "04730b97", "metadata": {}, "outputs": [], "source": [ "import os\n", "import numpy as np\n", "import pandas as pd\n", "from sklearn.model_selection import train_test_split\n", "import shap\n", "import matplotlib.pyplot as plt" ] }, { "cell_type": "code", "execution_count": 2, "id": "8b4ba3a4-dcce-480e-b5d9-e9e7727707fc", "metadata": {}, "outputs": [], "source": [ "import CellFreeGMF" ] }, { "cell_type": "markdown", "id": "1b342af6-3d30-48b8-8afa-28e3f7cb5d87", "metadata": {}, "source": [ "## Hyperparameter Configuration" ] }, { "cell_type": "code", "execution_count": 3, "id": "cb221917-664b-4c6d-8547-fc40a62c882a", "metadata": {}, "outputs": [], "source": [ "current_path = os.path.abspath('')\n", "disease_name = 'PDAC'" ] }, { "cell_type": "markdown", "id": "6bc5958d-4b8e-484f-b348-909a170c0761", "metadata": {}, "source": [ "## Load Data" ] }, { "cell_type": "code", "execution_count": 4, "id": "26bf8842-f11f-410a-ab67-cfa2960bb897", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "R[write to console]: 'select()' returned 1:many mapping between keys and columns\n", "\n" ] } ], "source": [ "def read_sample_cfRNA(disease_name = 'PDAC'):\n", " data_path = current_path + '/data/' + disease_name\n", "\n", " data_exp = pd.read_csv(data_path + '/GSE133684_exp_TPM-all.txt', sep='\\t')\n", " data_exp = data_exp.set_index(data_exp.columns[0]).T\n", "\n", " label_all = pd.read_csv(data_path + '/GSE133684_series_matrix.csv', sep=',')\n", " \n", " label_all = label_all.set_index(label_all.columns[0])\n", " label_all['label'] = label_all[label_all.columns[0]].apply(lambda x: 1 if x == 'disease state: PDAC' else 0)\n", "\n", " # label_all = label_all.loc[data_exp.index]\n", " data_exp = data_exp.loc[label_all.index]\n", "\n", " data_all = {'data_exp': data_exp,\n", " 'label': label_all}\n", "\n", " return data_all\n", "\n", "# standardized matrix\n", "def log_cpm(matrix: pd.DataFrame) -> pd.DataFrame:\n", " # Rows represent samples, and columns represent cfRNAs.\n", " matrix = matrix.T\n", " lib_size = matrix.sum(axis=0)\n", " cpm = matrix.divide(lib_size, axis=1) * 1e6\n", " log_cpm = np.log2(cpm + 1)\n", " return log_cpm.T\n", "\n", "# read cfRNA data\n", "sample_cfRNA_exp = read_sample_cfRNA(disease_name)\n", "X_train, X_val, y_train, y_val = train_test_split(sample_cfRNA_exp['data_exp'], sample_cfRNA_exp['label']['label'], test_size=0.2, random_state=2025)\n", "\n", "# Differential expression analysis was performed using the limma package.\n", "DEG_res = CellFreeGMF.DEG_limma_fun(X_train, y_train, file_path = current_path + '/save_data/' + disease_name)\n", "\n", "X_train = log_cpm(X_train)\n", "X_val = log_cpm(X_val)" ] }, { "cell_type": "markdown", "id": "84671593-c412-427b-aa11-715df1ceb25f", "metadata": {}, "source": [ "## Diagnostic classification using machine learning was performed." ] }, { "cell_type": "code", "execution_count": 5, "id": "7887474c-7053-416d-b8df-948bb403c78a", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Logistic Regression:\n", "Training dataset Accuracy: 1.0000, Precision: 1.0000, Recall: 1.0000, F1-Score: 1.0000, AUC:1.0000\n", "Testing dataset Accuracy: 0.9383, Precision: 0.9387, Recall: 0.9383, F1-Score: 0.9368, AUC:0.9807\n", "****************************************************************************************************\n", "SVM:\n", "Training dataset Accuracy: 0.7250, Precision: 0.8023, Recall: 0.7250, F1-Score: 0.6289, AUC:0.9954\n", "Testing dataset Accuracy: 0.7284, Precision: 0.5306, Recall: 0.7284, F1-Score: 0.6139, AUC:0.9322\n", "****************************************************************************************************\n", "RandomForestClassifier:\n", "Training dataset Accuracy: 1.0000, Precision: 1.0000, Recall: 1.0000, F1-Score: 1.0000, AUC:1.0000\n", "Testing dataset Accuracy: 0.8642, Precision: 0.8720, Recall: 0.8642, F1-Score: 0.8515, AUC:0.9480\n", "****************************************************************************************************\n", "AdaBoostClassifier:\n", "Training dataset Accuracy: 1.0000, Precision: 1.0000, Recall: 1.0000, F1-Score: 1.0000, AUC:1.0000\n", "Testing dataset Accuracy: 0.9136, Precision: 0.9151, Recall: 0.9136, F1-Score: 0.9142, AUC:0.9769\n", "****************************************************************************************************\n", "DecisionTreeClassifier:\n", "Training dataset Accuracy: 1.0000, Precision: 1.0000, Recall: 1.0000, F1-Score: 1.0000, AUC:1.0000\n", "Testing dataset Accuracy: 0.7531, Precision: 0.7687, Recall: 0.7531, F1-Score: 0.7590, AUC:0.7165\n", "****************************************************************************************************\n", "KNeighborsClassifier:\n", "Training dataset Accuracy: 0.7875, Precision: 0.7898, Recall: 0.7875, F1-Score: 0.7602, AUC:0.8920\n", "Testing dataset Accuracy: 0.7407, Precision: 0.7073, Recall: 0.7407, F1-Score: 0.6992, AUC:0.6156\n", "****************************************************************************************************\n" ] } ], "source": [ "ML_lr, ML_lr_train, ML_lr_val, ML_lr_roc_ = CellFreeGMF.diagnosis_ML.ML_lr(X_train, y_train, X_val, y_val)\n", "ML_svm, ML_svm_train, ML_svm_val, ML_svm_roc_ = CellFreeGMF.diagnosis_ML.ML_svm(X_train, y_train, X_val, y_val)\n", "ML_rf, ML_rf_train, ML_rf_val, ML_rf_roc_ = CellFreeGMF.diagnosis_ML.ML_rf(X_train, y_train, X_val, y_val)\n", "ML_ada, ML_ada_train, ML_ada_val, ML_ada_roc_ = CellFreeGMF.diagnosis_ML.ML_ada(X_train, y_train, X_val, y_val)\n", "ML_dt, ML_dt_train, ML_dt_val, ML_dt_roc_ = CellFreeGMF.diagnosis_ML.ML_dt(X_train, y_train, X_val, y_val)\n", "ML_knn, ML_knn_train, ML_knn_val, ML_knn_roc_ = CellFreeGMF.diagnosis_ML.ML_knn(X_train, y_train, X_val, y_val)" ] }, { "cell_type": "markdown", "id": "150b7879-2082-4d3e-9290-22e87b7a0555", "metadata": {}, "source": [ "## Performance comparison of diagnostic classification algorithms to screen for the algorithm optimally suited to PDAC." ] }, { "cell_type": "code", "execution_count": 6, "id": "cb275464-3338-4878-bb1c-6293de044e8d", "metadata": {}, "outputs": [ { "data": { "image/png": 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E2rVrB5PJhKNHj2LUqFFOuZc/6lGZJk2aYOfOnVizZg2++uorfPXVV1iwYAFGjhyJRYsWSc8T8O161zcs1PXIkiVL0KRJE3sXb3mffPIJPv30U7zzzjsu/4g3adIEoaGhLrs0K44lJydD0zRkZGTY310DZWfUysvLQ3JycrXm72nhD1StWrVCYWFhpcW8upKTk7F3716n8T179thv97eVK1eiV69emDdvnsN4Xl6e0x6kJ1q1agUA+PPPP91m1rJlSwBAUFBQtXIdPHgwZs6cif/+979VFmpbhu5yjo2Nhclkkp5DZTIyMhx+FkJg37596NSpE4CyNxjp6elYtGgRRo4caV+uskPWngoODsbgwYMxePBgaJqGf//735g7dy6efvpptG7dOiC2ufqCh77rifPnz+OTTz7BoEGDMGzYMKd/Y8eOxdmzZ91+pcVgMKB3795YtWoVjh07Zh/ft28fvvrqK4dlBwwYAABOp7acNWsWAGDgwIHVWgfbH8G8vLxq3V9vt99+O7Zs2YI1a9Y43ZaXlweLxVLtxx4wYAC2bduGLVu22MfMZjPeffddpKSkoEOHDtV+bE8ZDAanvaMVK1ZU+hlxZS6//HK0aNECr732mtNrbnueJk2a4IYbbsDcuXORnZ3t9Bi2r8W506NHD/Tr1w/vv/8+Vq1a5XR7SUmJ/cQyCQkJ6NKlCxYtWuQwnz///BNr1661b/e+tHjxYofD8itXrkR2dra9L8S2l1o+dyGE09eoZJ06dcrhZ1VV7W8ObF+xDIRtrr7gHnU98dlnn+Hs2bP429/+5vL2q666Co0bN8aSJUswfPhwl8tMmzYNa9euxTXXXIMHHngAVqsVb775Ji699FLs3LnTvlznzp2RlpaGd999F3l5eejZsye2bduGRYsWYciQIfZGNlldunSBwWDAiy++iPz8fISEhODGG29EkyZNqvV4Ne2xxx7DZ599hkGDBmHUqFHo2rUrzGYz/vjjD6xcuRIHDhyo1p4nAEyaNAkfffQR+vfvj3HjxiEmJgaLFi1CVlYWPv744xo5mcmgQYPw7LPP4p577sHVV1+NP/74A0uWLLHv9cpSVRVvv/02Bg8ejC5duuCee+5BQkIC9uzZg7/++sv+hmfOnDm49tpr0bFjR9x3331o2bIljh8/ji1btuDIkSNO3+OuaPHixbj55pvx97//HYMHD8ZNN90Ek8mEjIwMLF26FNnZ2fbvUr/88svo378/evTogTFjxuD8+fN44403EBUV5Zfz4sfExODaa6/FPffcg+PHj+O1115D69atcd999wEoO3TfqlUrTJw4EUePHkVkZCQ+/vhjrz/3vffee3H69GnceOONaNasGQ4ePIg33ngDXbp0sR8lC4Rtrr5goa4nlixZgtDQUPTp08fl7aqqYuDAgViyZAlOnTqFRo0aOS3TtWtXfPXVV5g4cSKefvppJCUl4dlnn8Xu3bvth7ts3n//fbRs2RILFy7Ep59+ivj4eEyePNmrM6DFx8fjnXfewcyZMzFmzBhYrVZ89913taZQh4WFYePGjZgxYwZWrFiBxYsXIzIyEm3atMH06dPtDW3VERcXhx9//BFPPPEE3njjDRQVFaFTp074/PPPq30EQ9aUKVNgNpvx4YcfYtmyZbj88svxxRdfYNKkSdV+zL59++K7777D9OnT8eqrr0LTNLRq1cpeqICybv/t27dj+vTpWLhwIU6dOoUmTZrgsssuwzPPPFPlczRu3Bg//vgj3nrrLSxbtgxPPvkkSkpKkJycjL/97W94+OGH7cv27t0bX3/9NaZOnYpnnnkGQUFB6NmzJ1588UWfNUWWN2XKFPz++++YOXMmzp49i5tuuglvvfUWwsLCAJQd8v/8888xbtw4zJw5E6GhoRg6dCjGjh2Lzp07V/t5R4wYgXfffRdvvfUW8vLyEB8fj+HDh2PatGn2AhwI21x9oQh+kk9eGjJkCP766y+nz9OIqHo2bNiAXr16YcWKFRg2bJje0yGd8dgESal4WsKMjAx8+eWXuOGGG/SZEBFRHcdD3ySlZcuWGDVqFFq2bImDBw/i7bffRnBwsNuvHBERkXdYqElKv3798NFHHyEnJwchISHo0aMHZsyY4XRiBiIi8g1+Rk1ERBTA+Bk1ERFRAGOhJiIiCmC6fka9adMmvPzyy/jll1+QnZ2NTz/9FEOGDKn0Phs2bMCECRPw119/ISkpCU899RRGjRrl8XNqmoZjx44hIiKi1p+SkoiIaichBM6ePYumTZtWeXIYXQu12WxG586dMXr0aPz973+vcvmsrCwMHDgQ999/P5YsWYL169fj3nvvRUJCgseXSTx27JjTFZKIiIj0cPjw4SqvaBYwzWSKolS5R/3EE0/giy++wJ9//mkfu+OOO5CXl+d0CTZ38vPzER0djcOHD9svcUdERFSTCgoKkJSUhLy8vCrPSlirvp61ZcsWpyvk9O3bF4888ojHj2E73B0ZGel1odY0DQcOHEBKSgrPa+sB5iWPmclhXnKYlxx/5OXJR7C1qlDn5OQgLi7OYSwuLg4FBQU4f/68y8szFhcX26/2ApS9iwHKruNqtVoBlAWlqio0TXO4Co27cVVVoSgKrFYrioqKYLFYYDAYHMbLs72gFa8N627cdhWi8uO2ubgb93TuVa1TZevq7TppmuaQV11YJ3+/Tu62sdq8Tv58nSpuY3VhnVyN+2qdhBAoLi52yKu2r5M/XydXeXmzTp6qVYW6OmbOnInp06c7jWdmZiI8PBwAEBUVhYSEBBw/fhz5+fn2ZWJjYxEbG4ujR4/CbDbbx+Pj4xEdHY1Dhw7h9OnT2LdvH1RVRbNmzRAeHo7MzEyHF6ZFixYwGo1O58JOTU2FxWJBVlaWfUxVVbRp0wZmsxlHjhyxjwcHB6Nly5bIz89HTk6OfdxkMiEpKQmnT59Gbm6ufby663TgwAGUlJTYx325TufOnXPIqy6sk79fp2PHjjlkVhfWyZ+vU0lJiUNedWGd/Pk6NWnSBGaz2Z5XXVgnf75OzZs3t18TvPwedXXXyVO16jPq66+/HpdffrnDdY4XLFiARx55xO1Ku9qjtr3AtkPf1X0XVlpaioyMDLRu3Zp71B6sk8ViQXp6uj2vurBO/n6d3G1jtXmd/Pk6Wa1Wh22sLqyTq3Ff7lGnp6ejVatW3KP2cI86IyPDIa/qrpOtXyo/P7/Kj2Fr1R51jx498OWXXzqMrVu3Dj169HB7n5CQEISEhDiNGwwGh6CBi2FX5G7caDSiefPmCAoKcvicoeLjVmdcURSpcdm5y477Yp0MBoPLvGrzOvn7dXK3jdXmdfLn6yS7jdWGddI0DaWlpQ5jFX+uLiEEmjRpAqvV6lRkapqv1smfZPIKCgoCUPm25yldC3VhYSH27dtn/zkrKws7d+5ETEwMmjdvjsmTJ+Po0aNYvHgxAOD+++/Hm2++iccffxyjR4/Gt99+i+XLl+OLL77QZf6KotgPn1PVmJc8ZianruVVUlKCrKws3YsoVU90dDTi4+O9PmeHroV6+/bt6NWrl/3nCRMmAADS0tKwcOFCZGdn49ChQ/bbW7RogS+++ALjx4/H66+/jmbNmuH999/3+DvUvma1WpGZmel0GIRcY17ymJmcupSXEALZ2dkwGAxISkpyu3fu7XOUlJQgODiYJ4DygKd5CSFw7tw5nDhxAgCQkJDg1fPqWqhvuOGGSjvfFi5c6PI+v/76qx9nJYfvdOUwL3nMTE5dyctiseDcuXNo2rQpwsLC/PIctr+/oaGhLNQekMnL9i2kEydOoEmTJl69ceQX54iIApCtkSk4OFjnmVB12d5gefv5Ows1EVEA455u7eWr146F2guqqqJFixZ++eyoLmJe8piZHOYlz9W3Ysg9PfLi1uwlo7FWfcNNd8xLHjOTw7zkBOoeu6IoWLVqld7TcKJHXizUXtA0DRkZGXWmecXfmJc8ZiaHeckrKipye9uoUaOgKAruv/9+p9sefPBBKIri8WWGN2zYAEVRkJeX59Hy2dnZ6N+/v0fL1qTK8vIXFmoiInIrKSkJS5cuxfnz5+1jRUVF+PDDD9G8eXOfP5/tVJ7x8fE8LH8BC7WXLFa+cyeiuuvyyy9HUlISPvnkE/vYJ598gubNm+Oyyy6zj2mahpkzZ6JFixZo0KABOnfujJUrVwIADhw4YD9nRsOGDR32xG+44QaMHTsWjzzyCGJjY+3nxah46PvIkSO48847ERMTA5PJhG7dumHr1q0AgN9++w29evVCREQEIiMj0bVrV2zfvt2fsdQofpjjhZ+zTuO/mzJxd2gTdG8Vq/d0iIj8YvTo0ViwYAHuuusuAMD8+fNxzz33YMOGDfZlZs6cif/+97945513kJqaik2bNmHEiBFo3Lgxrr32Wnz88ce49dZbsXfvXkRGRjpc7XDRokV44IEH8MMPP7h8/sLCQvTs2ROJiYn47LPPEB8fjx07dtg/4rjrrrtw2WWX4e2334bBYMDOnTvtp/CsC1iovfDqN+nYcUjB8XV7sYKFukqqqiI1NZUduRKYmRzmJS80NLTKZUaMGIHJkyfj4MGDAIAffvgBS5cutRfq4uJizJgxA99884392gstW7bE5s2bMXfuXPTs2RMxMTEAgCZNmiA6Otrh8VNTU/HSSy+5ff4PP/wQJ0+exM8//2x/nNatW9tvP3ToEB577DG0a9fO/nj+4klevsZCXU1bMk9h+4EzMBmB7QfOYEvmKfRo1UjvaQU8i8XCEzhIYmZymJccIUSVncyNGzfGwIEDsXDhQgghMHDgQMTGXtw52bdvH86dO4c+ffo43K+kpMTh8Lg7Xbt2rfT2nTt34rLLLrMX6YomTJiAe++9Fx988AF69+6N2267Da1ataryeavDk7x8jW87q2nWur0IUoFr4zUEqWU/U+U0TeMFBiQxMzmapiFjXybzklD+MsCVGT16NBYuXIhFixZh9OjRDrcVFhYCAL744gvs3LnT/m/Xrl32z6krYzKZKr29/GFyV6ZNm4a//voLAwcOxLfffosOHTrg008/rfJ5q8PTvHyJhboatmSews8HzsB64TTlVgH8fGGvmoj083PWabyzKRPbD5zReyp1Tr9+/VBSUoLS0lKnCyF16NABISEhOHToEFq3bu3wLykpCcDFU6FWvMazJzp16oSdO3fi9OnTbpdp06YNxo8fj7Vr1+Lvf/87FixYIP08gYqFuhpmrdsLQ4UjHwaFe9VEepv9TTosVsHfRT8wGAzYvXs3du3a5XSBiYiICEycOBHjx4/HokWLkJmZiR07duCNN97AokWLAADJyclQFAWrV6/GyZMn7XvhnrjzzjsRHx+PIUOG4IcffsD+/fvx8ccfY8uWLTh//jzGjh2LDRs24ODBg/jhhx/w888/o3379j5dfz2xUEuquDdt0coqNveqPcMmH3nMzDNbMk9h+8EzsGgKth/k76KnZD5vjYyMRGRkpMvbnnvuOTz99NOYOXMm2rdvj379+uGLL75AixYtAACJiYmYPn06Jk2ahLi4OIwdO9bj5w0ODsbatWvRpEkTDBgwAB07dsQLL7wAg8EAg8GAU6dOYeTIkWjTpg1uv/129O/fH9OnT/f48WXocWYyRVR2nck6qKCgAFFRUcjPz3e7wVXmtnd+xI6DFwt1eQYFuDy5IVbcf7UPZkpEMsr/btaF38WioiJkZWWhRYsWunQak/cqew1lahHfqkuouDetQCA2VEBB2QD3qisnhEBhYWGl1yAnR8zMM7bfTU2U/U5qQvB30QNCCFitVm5fHtIrLxZqCRU/m1YVoFusBrXcGD+rdk/TNBw5coQduRKYmWdsv5vlfyf5u+gZ2yk7yTN65MVC7aGKe9PucK+aqGa5+93k7yLVFSzUHnLV6e0O38kT1ZzKfjf5u0h1AQu1Byrbmy4sdf4LwXfyrimKguDg4IC9/m0gYmaVc/W7Wf53kr+LVeO3CuTokRdfIQ/MWrcXrv5OWoWCzcdVWIXzjQrfyTtRVRUtW7bkHwYJzKxyFfemXf1Ocq/aPUVREBISwjeCHtIrL/72V+FciQW/HsqDqyY/BQLNTBe7vssTAvj1UB7Ol8ifhaeuEkIgLy+PHaYSmJl7rvamXf1Ocq/aPSEELBYLty8P6ZUXL8pRhbBgI7ZOuQlniyxOt2mahhNHstCkWQuXezwRoUY0CDY4jddXmqYhJycHERERTmc2IteYmXu2venyhVpVgEsbasg+pzqM2/aqV7Sqvd+r9pfS0lJuWxL0yIuF2gONwkPQKDzEadxqtaLkdDCSG4VxQyeqQba9aU+V36uur1e5Kyq1IjSIf6dqIx76JqJax13fSGXqc9/I1v2n0OXZtdiW5f6iFhS4WKi9oCgKTCYTGzE8xLzkMTNnlfWNAEBukeus6nPfyCtr96KoVMPLa/Y43eavo4FbtmyBwWDAwIEDHcY3bNgARVGQl5fndJ+UlBS89tprDmPfffcdBgwYgEaNGiEsLAwdOnTAo48+iqNHj/pl3lXR4+gpD317QVVV+yXcqGrMSx4zc1ZZ30hV6mPfSPmPCSoe/rd9/c8f5s2bh4ceegjz5s3DsWPH0LRpU+nHmDt3Lv79738jLS0NH3/8MVJSUnDo0CEsXrwYr776KmbNmuWHmbvnz7wqw0LtBU3TcPr0acTExPDrMx5gXvKYmWvu+kaYl7PyTXcVm+psXcxGo9GnR20KCwuxbNkybN++HTk5OVi4cCGmTJki9RhHjhzBuHHjMG7cOMyePds+npKSguuvv97lHrm/+SuvqnBL9oIQArm5ufxqg4eYlzxmJod5Oar4FTZXX1WzWOSPTFRl+fLlaNeuHdq2bYsRI0Zg/vz50q/JihUrUFJSgscff9zl7dHR0T6YqTx/5FUVFmoiojrK1elVa+IEMPPmzcOIESMAAP369UN+fj42btwo9RgZGRmIjIxEQkKCP6ZYq7BQExHVQXpdrGTv3r3Ytm0b7rzzTgCA0WjE8OHDMW/ePKnHEUKwifICFmovKIqCqKgobkweYl7ymJkc5nWRpxcr8XUX87x582CxWNC0aVMYjUYYjUa8/fbb+Pjjj5Gfn4/IyEgAQH5+vtN98/LyEBUVBQBo06YN8vPzkZ2d7dP5eUuPrm8Wai+oqoqEhAQ2rXiIecljZnKYV5mqLstr26v+af9pn170xWKx2Duyd+7caf/322+/oWnTpvjoo4+QmpoKVVXxyy+/ONx3//79yM/PR5s2bQAAw4YNQ3BwMF566SWXz6VHM5leF8lh17cXNE3D8ePHERcXV+//MHiCecljZnKYVxlXp1etyLZXvSSpG4KCgnxSfFavXo0zZ85gzJgx9j1jm1tvvRXz5s3D/fffj3vvvRePPvoojEYjOnbsiMOHD+OJJ57AVVddhauvLutIT0pKwuzZszF27FgUFBRg5MiRSElJwZEjR7B48WKEh4fj1Vdf9XrOMoQQKC0t9Vlenqq/W7IPCCGQn5/PDlMPMS95zEwO86p6b9rm4mfVuT577nnz5qF3795ORRooK9Tbt2/H77//jtdffx1paWl44okncMkll2DUqFHo1KkTPv/8c4cC+O9//xtr167F0aNHMXToULRr1w733nsvIiMjMXHiRJ/NW4bVWvMnzOEeNRFRHeLJ3rSNQQH+891+XN/ON53Vn3/+udvbrrzySoc3UNOmTcO0adOqfMzevXujd+/evphercU9aiKiOsLTvWkbqwB+OZSPn/bzEqCBjIXaC4qiIDY2lh2mHmJe8piZnPqeV/UvVpLunwnVQUZjzR+I5qFvL6iqitjYWL2nUWswL3nMTE59zquqi5W4U/5iJfXtPOiyFEVBUFBQjT8vC7UXNE3D0aNHkZiYWK87TD3FvOQxMzn1Oa/qXKzEdu7qhuGhLNIe0Kvrm4XaC0IImM3met1hKoN5yWNmcup7Xu4uVuKOEAJFRUUIDfX8PvWd1Wqt8b3q+vWWk6gWslg1vadARDpioSYKYD9nncY7mzKx/cL1hImo/mGh9oKqqoiPj693n4VVF/OSN+ubdOzMVfCqn692VFdwG5OnR3NUbcZmslpGURTdrolaGzEvOVsyT2HbgTwACo6Y87Al8xR6tGqk97QCGrcxF4QAzp0GSgqB4HAgLAa273ApiqLL141qK73y4ttOL2iahv3790PT+BmiJ5iXnFnr9iJYFbg2TkOwKvx+DeG6gNtYOefzgJ/eBv5zGfByS+D1TmX//c9lZePn8yCEQHFxcb1tvpOlV14s1F4QQqCkpIQbuYeYl+fKn2EqPEj4/RrCdQW3sQv2fQPM6gB8PRk4c8DxtjMHysZndQD2rffbm5otW7bAYDBg4MCBfnl8vejxJpCFmigAubqWcPlrCBO5te8bYMntQOl5AOLCv/IujJWeBz68Her+7/wyjXnz5uGhhx7Cpk2bcOzYMb88hydKSkp0e25fYaH2Ur1/504+5+58zdyrpiqdzwOWjSz7XBpV7flpgBAIXjUGKMrz6TQKCwuxbNkyPPDAAxg4cCAWLlzocPvnn3+OK664AqGhoYiNjcXQoUPttxUXF+OJJ55AUlISQkJC0Lp1a8ybNw8AsHDhQqcehFWrVjmcfGTatGno0qUL3n//fbRo0QKhoaEAgK+//hrXXnstoqOj0ahRIwwaNAiZmZkOj3XkyBHceeediImJgclkQrdu3bB161YcOHAAqqpi+/btDsu/9tprSE5O9vteNgu1FwrXfQPrhAkoXPeN3lOpFVRVRbNmzdiRW4Xye9OaALbnqtAuFG3uVVeu3m9jv30ElJ5D1UW6jAKtbM/6t6U+ncby5cvRrl07tG3bFiNGjMD8+fPtOzVffPEFhg4digEDBuDXX3/F+vXrceWVV9rvO3LkSHz00Uf4z3/+g927d2Pu3LkIDw+Xev59+/bh448/xieffIKdO3cCAMxmMyZMmIDt27dj/fr1UFUVQ4cOtRfZwsJC9OzZE0ePHsVnn32G3377DY8//jg0TUNKSgp69+6NBQsWIDg42P48CxYswKhRo/y+vbHdr5oK1qzFsQkTYNA0HJswAYoyG5F9b9Z7WgFNURTpX7j6xrY3bSOgILfo4u3l96rZAe6sXm9jQgBb50rfTQHK7tf9fkhf0cONefPmYcSIEQCAfv36IT8/Hxs3bsQNN9yA559/HnfccQemT59uX75z584AgPT0dCxfvhzr1q2zX9qyZcuW0s9fUlKCxYsXo3HjxvaxW2+91WGZ+fPno3Hjxti1axcuvfRSfPjhhzh58iR+/vlnxMTEAABat25tX/7ee+/F/fffj9mzZyMkJAQ7duzAH3/8gf/973/S85NVT992yjlYcBC7Tu26+G/lPBwZ/wisqorTN9wAq6riyPhHsGvlPIflDhYc1HvqAcVqtSI9PV2XC6/XFhU/mzYoAr2bajAootwY96rdqdfb2LnTwJksOH8mXRVRdr/zvjmpzt69e7Ft2zbceeedAMquNjV8+HD74eudO3fipptucnnfnTt3wmAwoGfPnl7NITk52aFIA0BGRgbuvPNOtGzZEpGRkUhJSQEAHDp0yP7cl112mb1IVzRkyBAYDAYsW7YMQggsXLgQvXr1sj+OP3GPugoHCw5i0KeD7D9336Nh/CoNEICiCGhGIxQhIDQBPP0KZg9RsbXdxfc/q4euRnJksh5TD0j82ox7FfembYyqwIX9HgDcq65Kvd3GSgq9u3/x2bLvWHtp3rx5sFgsaNq0qX1MCIGQkBC8+eabaNCggdv7VnYbUPbRRsW+oNLSUqflTCaT09jgwYORnJyM9957D02bNoWmabj00kvtzWZVPXdwcDDuvvtufPDBBxg+fDg+/PBDvP7665Xex1e4R10Fc6nZ/v/li3RRg8YoDG+GkuBIFIY3Q1GDxoAAxq/S0H2P5vL+RJVx1entDveqyUmwl4f8QyK8noLFYsHixYvx6quvYufOnfZ/v/32G5o2bYqPPvoInTp1wvr1613ev2PHjtA0DRs3bnR5e+PGjXH27FmYzRf/rto+g67MqVOnsHfvXjz11FO46aab0L59e5w54/imuFOnTti5cydOnz7t9nHuvfdefPvtt3jrrbdgsVjw97//vcrn9gXuUXuoYpH+qfs0QBWIbFqCgq43ApqCq7ZOQ+j5kxi/SsPsIXDYsyaqjLu9aXe4V01OwmKAhi0ufG/a88PfAgrQMAVKg4ZeT2H16tU4c+YMxowZg6ioKIfbbr31VsybNw8vv/wybrrpJrRq1Qp33HEHLBYLvvzySzzxxBNISUlBWloaRo8ejf/85z/o3LkzDh48iBMnTuD2229H9+7dERYWhilTpmDcuHHYunWrU0e5Kw0bNkSjRo3w7rvvIiEhAYcOHcKkSZMclrnzzjsxY8YMDBkyBDNnzkRCQgJ+/fVXNG3aFD169AAAtG/fHldeeSUmTZqE0aNHV7kX7iusJB4oX6RVAFZDWbs/NKDwUJC9wdJqCC0L1MWeNZUdtmrRokX97citxKx1e1328WgC2Jxzseu7PIV71U7q9TamKED3f1Xvvt3/5ZNGsnnz5qF3795ORRooK9Tbt29HTEwMVqxYgc8++wxdunTBjTfeiG3bttmXe/vttzFs2DD8+9//Rrt27XDffffZ96BjYmLw3//+F19++SU6duyIjz76CNOmTatyXqqqYunSpfjll19w6aWXYvz48Xj55ZcdlgkODsbatWvRpEkTDBgwAB07dsQLL7wAg8HxOt1jxoxBSUkJRo8eXY2EqkcR9eyLwAUFBYiKikJ+fj4iIyOrXH7XynkQT79iL9IAcDY8CT93mwT7oAYACq7Y/gIiCg8DF4egPDcRHYaN8cu61DZCCGiaBlVVa/Si64HuXIkFnaathcVVNYaAQcGF71Q7Z2ZUFfwxrS8aBBucbquP6tI2VlRUhKysLIfvAlfpfF7ZGcdKz8OTr2gJRQWMDYAJf/lkj7quE0Lgueeew8qVK/H7779XuXxlr6FMLeKh70oUrFkLPPOqQ5F2oAKRLUtQsD/Y6XdCRdneEJ55FQURSfzqFsqafDIyMpCamur0LrU+Cws2YuuUm3C2yOJ0m6ZpOHEkC02aud5LjAg1skiXU++3sQbRwPDFZWcmE/a9CDdUAApKhs5DcGh0jUyvNissLERWVhbmzJmD5557rkafm4XajYI1a3F0/Hj7Z9L2w90AzGHxLu9TcdxgLUKDotyyx5nN71kDgMXKjwNcaRQegkbhIU7jVqsVJaeDkdworH4WHpLXujdw1/KyM5SVnrswWP5ozYUjDUENgOEfQEu8uqZnWCuNHTsWH330EQYPHlyjh70BFmqXhBDImToV0DSctzWOeWBXh1FOY1dtnYaw8yeRM3UqIm7uU+sPx3nj56zT+O+mTNwd2gTdW8XqPR2iuqt1b2DCrrIzjm1958L3qy9omFJ2cpMudwIhkUBRkduHoYsWLlyIBQsWoKioqMbfNLNQu6AoCuKnT8fR8eNhMXr42ZAbFmMooKqInz69XhdpAJj9TToaWssu17iMhZrIvxpEA1fdX9Yodv5M2fekQyKABg0vNo7VrxalWqsetkZ6JrLvzUicPdtV/85FGlx+Pu1AARJ52BtbMk9h64EzWHdUxVZeWMJjqqoiNTW1fnYxVwPzckFRLnx1K7nsvxV2GDxuVCMA+uTFrbkSkX1vBu6/u9JlVGMV70jvv7veF2mg7GtERgVoYACM/FqRFIvFucmM3GNecurZF3+8pkdeLNRVMFzT2f2NKhDevLTSFCu9fz1hO5mHAHBtvAYBXq7RU5qmISsrq/6eFlMS85JXXFys9xRqFT3y4mfUVQiLNeKjLv+HyzKDcNcGAQjgfFi8y8axDrsWosG5HEABltyg4NdWpegV+2bNTzrAuDo1pu0UmCtaseOUiKgyLNQeyG9wEhsuBc4bL5yhzI0G53IQYT7sdGGO+qz8qTHLF2ueApPI9w4WHJS6voAQAiUlJWhoaoiUqBT/TYy8wkJdBVPQxauwbG2nYvYQ4N5vLt4uytdtBU5Fuvz96yPb3rT1wsc6Fu1iteZetWfYGCWnvuZV8Up/smrzlf4URcGnn36KIUOG+HRZd/evaSzUVUiOTMbqoasvvksdBJxN/QXYBkBTcHb/xZNUKA/cjQm3dLX/bAoy1doN3xcqXmjCKhR8c4yXa5RhMBjQpk0bvadRa9TnvLy9Up+vrvQ3atQoLFq0CAAQFBSE5s2bY+TIkZgyZQqMRv+UnOzsbDRs6NkpUGWWrUhRFF26vlmoPVCx2OYNTMH2bT8BEDCECVjPKQAUtB14K6Ibhekyx0BUcW9agUCjUOBU0YUr9oB71VURQsBsNsNkMtX77+F7gnkFhn79+mHBggUoLi7Gl19+iQcffBBBQUGYPHmyw3IlJSUIDg72+vni412fLdLbZSvS61zy9fMYkZei48Jw1/Sr0K+XBW1CfkS/XhbcNf0qRMexSNvY9qat5b7JoCpAt1gNqpvPqsmZpmk4cuQIu5g9xLwCQ0hICOLj45GcnIwHHngAvXv3xmeffYZRo0ZhyJAheP7559G0aVO0bdsWAHD48GHcfvvtiI6ORkxMDG655RYcOHDA4THnz5+PSy65BCEhIUhISMDYsWPttymKglWrVgEoK/5jx45FQkICQkNDkZycjJkzZ7pcFgD++OMP3HjjjWjQoAEaNWqEf/7znygsLLTfbpvzK6+8gqZNm6JJkyZ48MEHUVpa6vvg3GChrqbouDCkDOuNhJG3IWVYbxbpClx1ertj4Peqieq0Bg0aoKSkBACwfv167N27F+vWrcPq1atRWlqKvn37IiIiAt9//z1++OEHhIeHo1+/fvb7vP3223jwwQfxz3/+E3/88Qc+++wztG7d2uVz/ec//8Fnn32G5cuXY+/evViyZAlSUlJcLms2m9G3b180bNgQP//8M1asWIFvvvnG4U0AAHz33XfIzMzEt99+i3fffReLFi3y6DrYvsJD317i4TVnFT+brgo/qyaqm4QQWL9+PdasWYOHHnoIJ0+ehMlkwvvvv28/5P3f//4Xmqbh/ffft/89XbBgAaKjo7FhwwbcfPPN+L//+z88+uijePjhh+2PfcUVV7h8zkOHDiE1NRXXXnstFEVBcrL7PqEPP/wQRUVFWLx4MUymssbfN998E4MHD8aLL76IuLg4AEDDhg3x5ptvQlVVpKSkYODAgVi/fj3uu+8+n+RUFe5Re0FRFAQHB7NYVzBr3V6316AvLHV9g8K9ape4jclhXoFh9erVCA8PR2hoKPr374/hw4dj2rRpAICOHTs6fC7922+/Yd++fYiIiEB4eDjCw8MRExODoqIiZGZm4sSJEzh27Bhuuukmj5571KhR2LlzJ9q2bYtx48Zh7dq1bpfdvXs3OnfubC/SAHDNNddA0zTs3Xvx79Ell1xivxCHqqqIj4/HiRMnZCLxCveovaCqKlq2bKn3NALKuRILfj2U5/Jc/1ahYPNx139AhQB+PZSH8yVWXl+5HG5jcphXYOjVqxfefvttBAcHo2nTpg7d3uWLIlB2neeuXbtiyZIlTo/TuHFj6a/bXX755cjKysJXX32Fb775Brfffjt69+6NlStXVm9lUNa9DpS9EQwJCYGqqjXaB8FC7QUhBPLz8xEVFcV38BeEBRuxdcpNOFvkfL5lIQTOm8+igSnCZV4RoUYW6Qq4jckRQiAvLw/R0dHMS0cmk8ntZ8gVXX755Vi2bBmaNGmCyMhIl8ukpKRg/fr16NWrl0ePGRkZieHDh2P48OEYNmwY+vXrh9OnTyMmJsZhufbt22PhwoX2bwoAwA8//ABVVe2NbuUJIWC1Wmv8fN889O0FTdOQk5PDDtMKGoWHICXW5PSveUwDqEX5aB7TwOXtjcJDqn7weobbmJz8NWux6/kZyF/j/nAnBZa77roLsbGxuOWWW/D9998jKysLGzZswLhx43DkyBEAwLRp0/Dqq6/iP//5DzIyMrBjxw688cYbLh9v1qxZ+Oijj7Bnzx6kp6djxYoViI+PR3R0tMvnDg0NRVpaGv7880989913eOihh3D33XfbP5+uqCa7vW24R01EtY7LU2V+twXa9Neg9bwBRx6biGOFR4BePRwWqe8nIQpEYWFh2LRpE5544gn8/e9/x9mzZ5GYmIibbrrJvoedlpaGoqIizJ49GxMnTkRsbCyGDRvm8vEiIiLw0ksvISMjAwaDAVdccQW+/PJLl4fQw8LCsGbNGjz88MO44oorEBYWhltvvRWzZs3y6zrLUkQ9u8ZZQUEBoqKikJ+f7/Ywi6esVisyMjKQmppqbzQg95iXPGbmzNWpMrvv0fCvNY1gCQrDuWu6IuyHX2AsPYe5fU85nXe/tpwqs6ioCFlZWWjRooVHZ8PadWoXhq8eXu3nWzZoGTo06lDt+9cHQggUFRUhNDTUo49WKnsNZWoR96i9oCgKz4AkgXnJY2bOKu5J24r0tiunAYpAWLQF5y6/ERAK/rVmGgDHYu2rU2VS/aTHG2Z+Ru0FVVWRlJRUby8CIIt5yWNmleu+p+yKdlb1wt6KUHDuWBAgyt7YWNVQjF+lofsefsZP3tPr63/87feCpmnIzc1lo4+HmJc8ZuaerUhDlPtDpgiExFgApewTPRUABOpFsfb2Sn31/Up/nhBCoLS0tMa7vnno2wtCCOTm5lb7Siz1DfOSx8xcc1mkAUABQmKsKM4zABf+lqoAtAvFevYQANW/EmRAc7rSnwfKX4+6NnxuHwgsFovfrgLmDgs1EdUu323Bv9Y0wllTqL1Im8NcXxGp/LgG4F9rioCuW4BhdbNpSrbYlm+OosDFQk1EtUbBmrU4N2NxWeOYB3Z1GOU01n3GdBREJCGy782+nVyAE0KwKbGW4mfUXlAUhWeMksC85DGziwrWrMXR8eNhNVRyYhwBlBRcPOztitUQgqPjx6OgHp0UpWDNWmT0uNrlOvNrf3LY9V3LqKqKhIQEduR6iHnJY2ZlhBDImToV0DRbn5ibBRUUnTDau75dUQQATUPO1Kk13hSkB/sbnLw8pzcovIiJHHZ910KapiE7O5sduR5iXvKYWRlFURA/fTqgqpXVYEARCG1ysevbFaEAUFXET59e5wuUrUjbr5IjhEOxtjWT1Yc3LL6gV14s1F6wXTCBG7lnmJc8ZnZRZN+bkTh7NgzWYvcLKUBwpBWopP4arMVInD27zn9G7VCkyxXqisXaarXqOEv/UBQFq1atAgAcOHAAiqJg586dPnlsPfJiMxkR1RqRfW9G2NnDuHLGNFhVx65vV41jHXYthOlcDoCyrm+DVoSwKWn1s0jbXPj56PjxaDp7FoKvv96nzz1q1CgsWrQIAGA0GtGsWTPcdtttePbZZ9ldXk3coyai2qVXD8ztewoR5sMwFR5GROFhezGuyHQup+z2wsOIMB/G3L6nnC7UUddUWqRtLtx2bPwEmL9Z7/M59OvXD9nZ2di/fz9mz56NuXPnYurUqT5/nvqChdoLiqIgNja2zn/O5SvMSx4zc21rOxWzh6iAUranbCeA4tOOXd8aACjA7CGq0wU66hqPirTNhWVOPvEECtb6tgM+JCQE8fHxSEpKwpAhQ9C7d2+sW7cOQFnfxcyZM9GiRQs0aNAAnTt3xsqVKx3u/9dff2HQoEGIjIxEREQErrvuOmRmZgIAfv75Z/Tp0wexsbGIiopCz549sWPHDp/OvzI1fbITgIXaK6qqIjY2tt535HqKecljZs5sp7p0WayFguLTF7u+XRXpunqqTKkibVNuz9pfX1f7888/8eOPPyI4OBgAMHPmTCxevBjvvPMO/vrrL4wfPx4jRozAxo0bAQBHjx7F9ddfj5CQEHz77bf45ZdfMHr0aFgsFgDA2bNnkZaWhs2bN+Onn35CamoqBgwYgLNnz/pl/uUpioKgoKAaf+PMz6i9oGkajh49isTERP4h9QDzksfMnDmcKnMQgM7fwvjS8rIbFYGwBAvOZZcVa6NWBGXqWEzo0wtA3b0edbWKtE25z6zhoya71atXIzw8HBaLBcXFxVBVFW+++SaKi4sxY8YMfPPNN+jRo+wjiJYtW2Lz5s2YO3cuevbsiTlz5iAqKgpLly5FUFAQAKBNmzb2x77xxhsdnuvdd99FdHQ0Nm7ciEGD/Ht+WNu5vmu6WLNQe0EIAbPZzI5cDzEveczMNYdie0cHFDRsA2Xys7AEh6KwQVeE//oLjCVFSJ35VP1uHPOUj4t1r1698Pbbb8NsNmP27NkwGo249dZb8ddff+HcuXPo06ePw/IlJSW47LLLAAA7d+7EddddZy/SFR0/fhxPPfUUNmzYgBMnTsBqteLcuXM4dOiQV3P2lNVqdTs3f2GhJqJaL7LvzUgFcHjiRJSUpCLcfAxJr7xS54t0+RPB+ODBgAuPF3FzH6/2GE0mE1q3bg0AmD9/Pjp37ox58+bh0ksvBQB88cUXSExMdLhPSEjZGecaNGhQ6WOnpaXh1KlTeP3115GcnIyQkBD06NEDJSUl1Z5voNP9WNqcOXOQkpKC0NBQdO/eHdu2bXO7bGlpKZ599lm0atUKoaGh6Ny5M77++usanC0RBarIvjcj8eWXoYaGIvHll+t8kQYcTwQDbw/FKopfTgSjqiqmTJmCp556Ch06dEBISAgOHTqE1q1bO/xLSkoCAHTq1Anff/89SktLXT7eDz/8gHHjxmHAgAG45JJLEBISgtzcXJ/NNxDpWqiXLVuGCRMmYOrUqdixYwc6d+6Mvn374sSJEy6Xf+qppzB37ly88cYb2LVrF+6//34MHToUv/76aw3PvIyqqoiPj+dnhx5iXvKYmZyovjejw5NTEFUPirSN7UQwUJTqF+sL9/XXiWBuu+02GAwGzJ07FxMnTsT48eOxaNEiZGZmYseOHXjjjTfs370eO3YsCgoKcMcdd2D79u3IyMjABx98gL179wIAUlNT8cEHH2D37t3YunUr7rrrrir3wn2ppg97AzoX6lmzZuG+++7DPffcgw4dOuCdd95BWFgY5s+f73L5Dz74AFOmTMGAAQPQsmVLPPDAAxgwYABeffXVGp55GUVREB0dza/OeIh5yWNmchRFQcOGDetdXl4Vaz8XaaDsK01jx47FSy+9hMmTJ+Ppp5/GzJkz0b59e/Tr1w9ffPEFWrRoAQBo1KgRvv32WxQWFqJnz57o2rUr3nvvPXuBnDdvHs6cOYPLL78cd999N8aNG4cmTZr4Zd4VKYoCo9FY49uXInTqUikpKUFYWBhWrlyJIUOG2MfT0tKQl5eH//3vf073adSoEV566SWMGTPGPjZixAhs3rwZBw4c8Oh5CwoKEBUVhfz8fERGRnq1Dpqm4cCBA0hJSeEejweYlzxmJqcu5VVUVISsrCy0aNHC4zN6STeWXSjSTWfPQlTfvl7OuO6znevb0wtzVPYaytQi3ZrJcnNzYbVaERcX5zAeFxeHPXv2uLxP3759MWvWLFx//fVo1aoV1q9fj08++aTSc68WFxejuPjiuYELCgoAlHXu2e6nKApUVYWmaQ7dte7GVVWFoiiwWq0oKiqCxWKBwWBwGC/P9gej4oUV3I0bDAYIIRzGbXNxN+7p3Ktap8rW1dt10jTNIa+6sE7+fp3cbWO1eZ38+TpV3MZq8zrZlhFCOHX9K4ri8psAkX1vhpg9C8fGT8CFOzstU+5BAEVB4xdfRESfPk7r5erxZcdl+Oo5/T1e8TX1hKt6I/MYtarr+/XXX8d9992Hdu3aQVEUtGrVCvfcc4/bQ+VA2Zfrp0+f7jSemZmJ8PBwAEBUVBQSEhJw/Phx5Ofn25eJjY1FbGwsjh49CrPZbB+Pj49HdHQ0Dh06hNOnT2Pfvn1QVRXNmjVDeHg4MjMzHX7hWrRoAaPRiIyMDIc5pKamwmKxICsryz6mqiratGkDs9mMI0eO2MeDg4PRsmVL5OfnIyfn4ukSTSYTkpKScPr0aYeGiuqu04EDBxy6J325TufOnXPIqy6sk79fp2PHjjlkVhfWyZ+vU0lJiUNetXmdbLcLIVBUVGQfVxQFoaGh0DTN4bFVVUVISAhMN92Exi++iJNPPIELDwAn5fakjdde67AzYzQaERQUhNLSUoc3FEFBQTAajSgpKXGYe3BwMAwGA4qLix2KT0hICBRFcZg7AISGhkII4fCcVa2T1Wp1aC4zGAwIDg6GxWKxnwil/HjFuftqnWwnbSk/98rWCSh7HQ8ePGh/M1Z+2/NUrTr0bVNUVIRTp06hadOmmDRpElavXo2//vrL5bKu9qhtv4i2ww3VfbdcWlqKjIwMtG7dmnvUHqyTxWJBenq6Pa+6sE7+fp3cbWO1eZ38+TpZrVaHbaw2r1NRUREOHTpk/1ZMeZ7sBRasXVu2Z13xMHi5Ih15880oKiqyF1WZx/dkXEag7Tm7G3eVlzvFxcXIyspC8+bN7a+hbZvJz89HdHR0YB/6Dg4ORteuXbF+/Xp7odY0DevXr8fYsWMrvW9oaCgSExNRWlqKjz/+GLfffrvbZUNCQuzfzyvPYDDYf5Ft3H2m5W7caDSiefPmTmepqfi41RlXFEVqXHbusuO+WCeDweAyr9q8Tv5+ndxtY7V5nfz5OsluY4G8Trb/VxTFZVFwVyhs41F9+0KZPbvsM2ugrFgrjo1jQgj7560VH6+qx/d0XIavntNf45XlVRlX9Ubm/rp2W0yYMAHvvfceFi1ahN27d+OBBx6A2WzGPffcAwAYOXIkJk+ebF9+69at+OSTT7B//358//336NevHzRNw+OPP67L/BVFQXh4uE820PqAecljZnKYlyOHbnDAqbvb9kaFeXlGr7x0LdTDhw/HK6+8gmeeeQZdunTBzp078fXXX9sbzA4dOoTs7Gz78kVFRfYvzQ8dOhSJiYnYvHkzoqOjdZm/7TBbXbzwuj8wL3nMTA7zcmYr1oboaKevYNk+/+Ypaj2jV166N5ONHTvW7aHuDRs2OPzcs2dP7Nq1qwZm5bmKn5NR5ZiXPGYmh3k5i+x7s9vTgrJIy9Ejr9r9RUMiIvIID2/XXrrvURMRkf/kHT+H0uJyX0kKMSA6LkzHGZEsFmovqKqKFi1a1PozINUU5iWPmclhXo7yjp/Dkqk/OY3fNf0qe7F29a0Yck+PvLg1e8lo5HsdGcxLHjOTw7wuKr8n7W7c14fER40aZf/6Uvl/+/btw6ZNmzB48GA0bdoUiqJg1apVPn3umqDHRwgs1F7QNA0ZGRlsXvEQ85LHzOQwL3kVzxzmC/369UN2drbDvxYtWsBsNqNz586YM2eOz5+zpvgjr6rwrScREflUSEgI4uPjncb79++P/v376zCj2o2FmoiojqjYOHY62+xyOdu47fzU4VEaGsaZamSOJI+FmoioDnDXOObKNwucz0dRvsHMW6tXr7Zf9Ago25NesWKFTx67PmKh9oKqqkhNTWWHqYeYlzxmJqc+5+Wucaym7l9er1698Pbbb9t/Npnqzt66p9cG9yUWai9ZLBb7pc+oasxLHjOTw7z0ZzKZ0Lp1a72n4RdCiPp1ru/aTtM0ZGVlscPUQ8xLHjOTw7zI3ypei7omcI+aiKgOCApxfenMmrq/JwoLC7Fv3z77z1lZWdi5cydiYmLQvHlzvz9/bcVCTURUB0THheGu6Vc5dX27ahzrfU8HxCSYynV9h9XIaUW3b9+OXr162X+eMGECACAtLQ0LFy70+/PXVizUXqqPTSveYF7ymJmc+pyXp8U2JsGExs0jLhTqYJ+eFrOygnvDDTfU+qt16XFmMhZqLxgMBrRp00bvadQazEseM5PDvOQoiqJLF3NtpVdeLNReEELAbDbDZDLxEnIeYF7uHSw4CHOp88kphBAoLSpFUGiQy8xMQSYkRybXxBRrBW5jcoQQ0DQNqqoyLw/olRcLtRc0TcORI0eQmpoKg8H/jRi1HfNy7WDBQQz6dJDL2wwwoGdoT2ws2ggrXH/PdfXQ1SzWF3Abc+SuQaz8eElJCfeqJeiRFws1kc5c7UnX5P2p7nLVYMbrUdc+LNRERAHM2+YrFmX9+Kpxrv62R/qAoigIDg7mZzseYl7VY9a4x+ypurSN2Q7dl5SU+PV56nOXfHXI5HXu3DkAQFBQkFfPyT1qL6iqipYtW+o9jVqDecmzwoqtxT8BdaDw1IS6tI0ZjUaEhYXh5MmTCAoK8mtB1eNsW7VZVXkJIXDu3DmcOHEC0dHRXvdLsFB7QQiB/Px8REVF1Yl38P7GvOR13yMw6rc4LOx8HFvbMbOq1KVtTFEUJCQkICsrCwcPHvTb89i6mMkzMnlFR0e7vC63LBZqL2iahpycHERERLDD1APMS073PRoe+VzBmRs64JHPj+M1aNjajn9QK1PXtrHg4GCkpqb67fC31WrFwYMH0bx58zqRl7/J5BUUFOSzTFmoiQJQ9z0axq/SINQLv+gCGL9Kw+whYLGuZ1RV9dvXgaxWq/3xWairplde/I0nCjC2Ig0B2A7eKoC9WHffwytDEdUnLNReUBSFZ0CSwLyqVr5Iqygr0MGnTkHBhV9WFutKcRuTw7zk6JUXC7UXVFVFUlISGzE8xLwqV7FIA4BitSLy11+hWMtOWMFiXTluY3KYlxy98uKr4wVN05Cbm8uL1HuIebnnqkgDgFBVnGvZEqLcHwYWa/e4jclhXnL0youF2gtCCOTm5tb6y7bVFOblxndbXBZpABCKUlaoKxxqK1+s8d2WmpppwOM2Jod5ydErLxZqIh0VrFkLPPOqyyJdFVuxxjOvlj0OEdVJLNREOilYsxZHx4+HUo0ibaMCUARwdPx4FmuiOoqF2guKotSJMyDVFOZ1kRACOVOnApoGVHIYTRECoUePQqnsUJsQgKYhZ+rUen8Ik9uYHOYlR6+8WKi9oKoqEhIS2DHpIeZ1kaIoiJ8+HVDVSs/jrWgawnfvhlJZ84qiAKqK+OnT6/0fXG5jcpiXHL3y4qvjBU3TkJ2dzY5JDzEvR5F9b0bi7NmVFmqhqihs396h69uJoiBx9mxE9r3ZD7OsXbiNyWFecvTKi4XaC7YLANT3w42eYl7OHIu1cy5CUVCUmOjU9X3hVhbpCriNyWFecvTKi4WaSGeRfW9G4kvPX/jJ0z8AZcslvvQ8izRRHcdCTRQAIgcPReLkey/8VFWxvlCkJ9+LyMFD/TovItIfr57lBUVREBsbW+8beDzFvCoXmTYRAHB05vsABM41aAKLsQGQfRaFYYkwWs4j7PwJABeK9IXl6SJuY3KYlxy98lJEPftwoqCgAFFRUcjPz0dkZKTe0yFyUvD5p8iY+hp+unKq021XbZuO1GcfQeQg7kkT1WYytYiHvr2gaRoOHz7MjkkPMS/PRA4eipgnniz7QREIa1padlYTADFPPMkiXQluY3KYlxy98mKh9oIQAmazmR2THmJengvv0aPsfxTAGKbZL0xtHyeXuI3JYV5y9MqLhZqIiCiAsZmMKADkHT+H0mKr/efT2WaXy1UcDwoxIDouzK9zIyJ9sVB7QVVVxMfH8/R7HmJeruUdP4clU39yfaMGnD9hBC58JPbNgl1Oi9w1/SoW6wu4jclhXnL0youF2guKoiA6OlrvadQazMu18nvSzhSUFhi8uH/9wm1MDvOSo1defBvlBU3TsH//fnZMeoh5VYMiYGpeYu/6pspxG5PDvOTolRcLtReEECgpKWHHpIeYVzUogCFY2Lu+qXLcxuQwLzl65cVCTaSzoJDKD237+/5EFNj4GTWRzqLjwnDX9Kucur5dNY71vqcDYhJM9p/Z9U1U97FQe0FVVTRr1owdkx5iXu65LbYaYD4WZO/6jkkwoXHziJqbWC3DbUwO85KjV14s1F5QFAXh4eF6T6PWYF7VocB6jh9Qe4rbmBzmJUevvPg2ygtWqxXp6emwWvn1GE8wr2pQBSJaFgMqm308wW1MDvOSo1deLNRe4tca5DAvz5RvEFNU1+PkGrcxOcxLjh558dA3UQCyNZgVny/FkeMH0GxYCkIaBLFxjKgeYqEmClDRcWGwWq04UxSC2KRwGAzcmyaqjxRRz77pLnOx7qrYvvweHBwMRWHDT1WYlzxmJod5yWFecnyZl0wt4mfUXjIaeVBCBvOSx8zkMC85zEuOHnmxUHtB0zRkZGSwGcNDzEseM5PDvOQwLzl65cVCTUREFMBYqImIiAIYCzUREVEAY9e3F4QQ0DQNqqqyY9IDzEseM5PDvOQwLzm+zItd3zXIYrHoPYVahXnJY2ZymJcc5iVHj7xYqL2gaRqysrLYMekh5iWPmclhXnKYlxy98mKhJiIiCmAs1ERERAGMhdpLvOC6HOYlj5nJYV5ymJccPfJi1zcREVENY9d3DRFCoLCwEPXsvU61MS95zEwO85LDvOTolRcLtRc0TcORI0fYMekh5iWPmclhXnKYlxy98mKhJiIiCmAs1ERERAGMhdoLiqLwgusSmJc8ZiaHeclhXnL0yotd30RERDWMXd81RAiBvLw8dkx6iHnJY2ZymJcc5iVHr7xYqL2gaRpycnLYMekh5iWPmclhXnKYlxy98mKhJiIiCmAs1ERERAGMhdoLiqLAZDKxY9JDzEseM5PDvOQwLzl65cWubyIiohrGru8aomkacnNz2YjhIeYlj5nJYV5ymJccvfJiofaCEAK5ubn8aoOHmJc8ZiaHeclhXnL0youFmoiIKICxUBMREQUwFmovKIqCqKgodkx6iHnJY2ZymJcc5iVHr7zY9U1ERFTD2PVdQzRNQ3Z2NjsmPcS85DEzOcxLDvOSo1deLNReEEIgPz+fHZMeYl7ymJkc5iWHecnRKy8WaiIiogDGQk1ERBTAWKi9oCgKYmNj2THpIeYlj5nJYV5ymJccvfJi1zcREVENY9d3DdE0DYcPH2bHpIeYlzxmJod5yWFecvTKi4XaC0IImM1mdkx6iHnJY2ZymJcc5iVHr7xYqImIiAKY7oV6zpw5SElJQWhoKLp3745t27ZVuvxrr72Gtm3bokGDBkhKSsL48eNRVFRUQ7MlIiKqWboW6mXLlmHChAmYOnUqduzYgc6dO6Nv3744ceKEy+U//PBDTJo0CVOnTsXu3bsxb948LFu2DFOmTKnhmZdRVRXx8fFQVd3f79QKzEseM5PDvOQwLzl65aVr13f37t1xxRVX4M033wRQ9kF9UlISHnroIUyaNMlp+bFjx2L37t1Yv369fezRRx/F1q1bsXnzZo+ek13fRESkN5laZKyhOTkpKSnBL7/8gsmTJ9vHVFVF7969sWXLFpf3ufrqq/Hf//4X27Ztw5VXXon9+/fjyy+/xN133+32eYqLi1FcXGz/uaCgAABgtVphtVoBlH03TlVVaJrm0CTgblxVVSiKAovFggMHDiA5ORmqqtrHbY9bfnkATp2C7sYNBgOEEA7jtrm4G/d07lWtk7txX6yT1WpFVlaWPa+6sE7+fp3cbWO1eZ38+TppmuawjdWFdXI17qt1AoCsrCw0b97c/ly1fZ38+ToBwIEDBxzy8madPKVboc7NzYXVakVcXJzDeFxcHPbs2ePyPv/4xz+Qm5uLa6+9FkIIWCwW3H///ZUe+p45cyamT5/uNJ6ZmYnw8HAAQFRUFBISEnD8+HHk5+fbl4mNjUVsbCyOHj0Ks9lsH4+Pj0d0dDQOHjyInJwclJSUQFVVNGvWDOHh4cjMzHR4YVq0aAGj0YiMjAyHOaSmpsJisSArK8s+pqoq2rRpA7PZjCNHjtjHg4OD0bJlS+Tn5yMnJ8c+bjKZkJSUhNOnTyM3N9c+Xt11OnDgAEpKSuzjvl6n8nnVlXXy9+tUPrO6sk7+ep2Ki4sd8qoL6+TP16lJkyY4c+YMiouL7cWmtq+TP1+n5s2bo7i4GBkZGQ6Furrr5CndDn0fO3YMiYmJ+PHHH9GjRw/7+OOPP46NGzdi69atTvfZsGED7rjjDvzf//0funfvjn379uHhhx/Gfffdh6efftrl87jao7a9wLbDDdV9F1ZaWoqMjAy0bt0aBoOhXr2zrM46WSwWpKen2/OqC+vk79fJ3TZWm9fJn6+T1Wp12Mbqwjq5GvfVOgkhkJ6ejlatWtnzqu3r5M/XSQiBjIwMh7yqu075+fmIjo4O7EPfsbGxMBgMOH78uMP48ePHER8f7/I+Tz/9NO6++27ce++9AICOHTvCbDbjn//8J5588kmHdzg2ISEhCAkJcRo3GAwOQQNwef+qxlVVdXqsio9bnXFFUaTGqzN3mXFfrZOrvGr7Ovn7dXKVWW1fJ5lxf25jtWGd3I37Yp2sVqt9eW//HgbKOvlyvOJzVpaXq+WBytfJU7q1+gUHB6Nr164OjWGapmH9+vUOe9jlnTt3zilQWwB6HBiwHe529yKTI+Ylj5nJYV5ymJccvfLSbY8aACZMmIC0tDR069YNV155JV577TWYzWbcc889AICRI0ciMTERM2fOBAAMHjwYs2bNwmWXXWY/9P30009j8ODBbt+1+ZOiKPbPualqzEseM5PDvOQwLzl65aVroR4+fDhOnjyJZ555Bjk5OejSpQu+/vpre4PZoUOHHN65PPXUU1AUBU899RSOHj2Kxo0bY/DgwXj++ed1mb/VakVmZqbT5xXkGvOSx8zkMC85zEuOXnnpWqiBsu9Gjx071uVtGzZscPjZaDRi6tSpmDp1ag3MzDM8mb0c5iWPmclhXnKYlxw98uIHE0RERAGMhZqIiCiA6XoKUT348hSiQgiUlJQgODhYqtW+vmJe8piZHOYlh3nJ8WVeMrWIe9ReMhp1/5i/VmFe8piZHOYlh3nJ0SMvFmovaJqGjIwMNmN4iHnJY2ZymJcc5iVHr7xYqImIiAIYCzUREVEAY6EmIiIKYOz69oLtqii2K61Q5ZiXPGYmh3nJYV5yfJkXu75rkMVi0XsKtQrzksfM5DAvOcxLjh55sVB7QdM0ZGVlsWPSQ8xLHjOTw7zkMC85euXFQk1ERBTAWKiJiIgCGAu1l3jBdTnMSx4zk8O85DAvOXrkxa5vIiKiGsau7xoihEBhYSHq2XudamNe8piZHOYlh3nJ0SsvFmovaJqGI0eOsGPSQ8xLHjOTw7zkMC85euXFQk1ERBTAWKiJiIgCGC9E6gVFUXjBdQnMSx4zk8O8XDtYcBDmUrPTuNAE8kvzsef0Hiiqc2amIBOSI5NrYoq1gl7bF7u+iYjqsIMFBzHo00HVvv/qoatZrP2AXd81RAiBvLw8dkx6iHnJY2ZymJczV3vSNgoUJBgSoMD9HmJl969v9Nq+WKi9oGkacnJy2DHpIeYlj5nJYV5yVKhoH9QeKkuBR/Tavrx6dUpKSrB3715efYWIiMhPqlWoz507hzFjxiAsLAyXXHIJDh06BAB46KGH8MILL/h0gkRERPVZtQr15MmT8dtvv2HDhg0IDQ21j/fu3RvLli3z2eQCnaIoMJlM7DD1EPOSx8zkMC95p62n9Z5CraHX9lWtr2etWrUKy5Ytw1VXXeUw4UsuuQSZmZk+m1ygU1UVSUlJek+j1mBe8piZHOYlxwordpbu1HsatYZe21e19qhPnjyJJk2aOI2bzeZ69U5W0zTk5uayccVDzEseM5PDvOSoUNHC2ILNZB7Sa/uq1qvTrVs3fPHFF/afbcX5/fffR48ePXwzs1pACIHc3Fx+FcRDzEseM5PDvOQoUNDC2KLSr2fRRXptX9U69D1jxgz0798fu3btgsViweuvv45du3bhxx9/xMaNG309RyIi8rGo840Ram2AMDUSsYWJKDKcR36Dk3pPi1yo1h71tddei99++w0WiwUdO3bE2rVr0aRJE2zZsgVdu3b19RyJiMiHos43xp07n8LQvyagw/GrMfSvCbhz51OIOt9Y76mRC9J71KWlpfjXv/6Fp59+Gu+9954/5lRrKIqCqKioevW5vDeYlzxmJod5eSbIGlL2PwIoKTAAosI4uaTX9iW9Rx0UFISPP/7YH3OpdVRVRUJCAlSVjRieYF7ymJkc5iVJKCg6YQQE39h4Qq/tq1rPNmTIEKxatcrHU6l9NE1DdnY2O0w9xLzkMTM5zEuSIhDaxAIobL7zhF7bV7WayVJTU/Hss8/ihx9+QNeuXWEymRxuHzdunE8mF+iEEMjPz3f5VTVyxrzkMTM5zMuZKciEqPONHQ5rNzwfV/Y/ChAcaUVRbtnhb/v4BaWGYpiCHP++12d6bV/VKtTz5s1DdHQ0fvnlF/zyyy8OtymKUm8KNRFRoLM1jnnipn0jne8/tDHAKwLrqlqFOisry9fzICIiPygttup6f/Ke15+ICyHq7ckFFEVBbGwsO0w9xLzkMTM5zEuSAIpPX+z6psrptX1Vu1AvXrwYHTt2RIMGDdCgQQN06tQJH3zwgS/nFvBUVUVsbCw7TD3EvOQxMznMS5JQUHyaXd+e0mv7qtazzZo1Cw888AAGDBiA5cuXY/ny5ejXrx/uv/9+zJ4929dzDFiapuHw4cPsMPUQ85LHzOQwL2dBIQb3NyoCYU1LK+36rvT+9Yxe21e1PqN+44038Pbbb2PkyIuNB3/7299wySWXYNq0aRg/frzPJhjIhBAwm8319tC/LOYlj5nJYV7O1J2bcdW252FVg4EL5/Q2h8VjV4dRgAIYw7SyYQF02LUQpnM5F+4pYNBKoO58Euh7s06zDyx6bV/VKtTZ2dm4+uqrncavvvpqZGdnez0pIiLyXsGatTg6fjzCPNwDNJ3LQUThYYexo+PHA7NnI5LFWjfVOvTdunVrLF++3Gl82bJlSE1N9XpSRETkHVuRhrd7f0Lg6PjxKFiz1jcTI2nV2qOePn06hg8fjk2bNuGaa64BAPzwww9Yv369ywJeV6mqivj4eDaueIh5yWNmcphXGSEEcqZOBarak9aA8yeMQGWLCQFceLyIm/vU6456vbavaj3brbfeiq1btyI2NharVq3CqlWrEBsbi23btmHo0KG+nmPAUhQF0dHR9XrDlcG85DEzOcyrjKIoiJ8+HVBVwEUWBmuRbUmUFhhg++z64rjDgwGqivjp05mrTtuXIupZ10VBQQGioqKQn5+PyEjvTrejaRoOHDiAlJSUev8O3hPMSx4zk8O8HNkPf7vYsz7XoDEsQWE4d3kHhO3YBWPpOYSdd3E9alVFIj+jBuDb7UumFlXrmb788kusWbPGaXzNmjX46quvqvOQtZIQAiUlJeww9RDzksfM5DAvR5F9b0bi7NkX9qodMwk7fxLh5iMwGksRbj7iokgLQFFYpMspWLsO2W+9jYK162r0eatVqCdNmgSr1fm0ckIITJo0yetJERGRb0T2vRmJLz1/4SdP38CULZf40vMs0hcUrFmLo489Bq2oCEcfe6xGm+uqVagzMjLQoUMHp/F27dph3759Xk+KiIh8J3LwUCROvvfCT1UV6wtFevK9iBxcf3qOKuPUQV/DnfDVKtRRUVHYv3+/0/i+ffucLnlZl6mqimbNmvGzMA8xL3nMTA7zci8ybaJTsVY0DZG//grF/hl2uSKdNrHmJxmACj7/FEcfeQTQNChWa1leViugaTj6yCMo+PxTv8+hWlvzLbfcgkceeQSZmZn2sX379uHRRx/F3/72N59NLtApioLw8PB63wnpKeYlj5nJYV6Vi0ybiMSXZwJK2Z9+RQgEnzoFxbanqKhIfGUmi/QFBYtewdHHJgOi7I2MU15Cw9HHJqNg0St+nUe1CvVLL70Ek8mEdu3aoUWLFmjRogXatWuHRo0a4ZVX/DvhQGK1WpGenu7y83pyxrzkMTM5zKtqkYOHIvG11wBVhWY04vQNN0AzGsu6u197DZGDeLgbuFCkZ75/4aeyN36awVCWl8HgMH505vt+LdbVOuFJVFQUfvzxR6xbtw6//fYbGjRogM6dO+O6667z9fwCHk/+L4d5yWNmcphX1SL73gzMno3DEyeWFWl2dzso+PxTpyJtoxkrls2yjvqjM98HYlr55XN9qT3qLVu2YPXq1WVTUxTcfPPNaNKkCV555RXceuut+Oc//4ni4mKfT5KIiHwrsu/NSHz5ZaihoUh8+WUW6QsK1qzF0cefvPCTpx+hXNizfvxJvzSYSRXqZ599Fn/99Zf95z/++AP33Xcf+vTpg0mTJuHzzz/HzJkzfT5JIiLyvYg+vREzZjQi+vTWeyoBwbG7W7bPQfFbN7jUmckSEhLw+eefo1u3bgCAJ598Ehs3bsTmzZsBACtWrMDUqVOxa9cun07Sl3x5ZjLbyRWCg4PZvOIB5iWPmclhXnKY10UORdpNWRSKAmtYGAznzl1sKKtIUTz6KMFvZyY7c+YM4uLi7D9v3LgR/fv3t/98xRVX4PDhw67uWmcZnT6voMowL3nMTA7zksO8KlzEpLJ9VyGgFhVVuQw0DTlTp/rsDHlShTouLg5ZWVkAgJKSEuzYsQNXXXWV/fazZ88iKCjIJxOrDTRNQ0ZGBptXPMS85DEzOcxLDvMqU9VFTGyEwYDTvXpB2Lu+XT6Yzy9iIlWoBwwYgEmTJuH777/H5MmTERYW5tDp/fvvv6NVq1Y+mRjVTTwHMxEFIsfzonvBDx30UoX6ueeeg9FoRM+ePfHee+/hvffeQ3BwsP32+fPn4+ab2TlIrp1d9w1Oz5uPs+u+0XsqREROKruISdX8dxETqQ8nYmNjsWnTJuTn5yM8PByGCrv/K1asQHh4uE8nSHWD/YT2PXvi6GOPQVUUfh2EiAJOZN+bgZeeLzsjGTzt/vbvRUx4PWovCCGgaRpUVa33HZOVsXVTCiEgVBWKpkHhCRY8wm1MDvOSw7zcc3VmMoGyz6kVq7Vc+a7e+dH9fj1qushiseg9hYBW/oT2AKCFhpbdUIMntK/tuI3JYV5ymJdrri5iAkUp+xtmf1NTMxcxYaH2gqZpyMrKqvcdk+5UPKG9UFXk9egBYbuyUQ2d0L424zYmh3nJYV6Vq3gRE6e/YTV0ERMWavILV4eNnNXMCe2JiKqr/EVM7HvSF76CVVMXMWGhJp+r7IT2zsoVax4GJ6IA5PTVrRrusWGh9hIvUO+oqhPaqy4/D/PvCe1rO25jcpiXHOblGdtFTAxBxhq/iAm7vsln7OfK9ebzLlVlNzgRBSwhhE865Nn1XUOEECgsLOTZtlDxqjOuCUVBSaNGEJVt5H66+kxtxW1MDvOSw7zkCCFgNptrPC8Wai9omoYjR47U+45JT09oL1QVBZdddrFj0vWD+fyE9rUZtzE5zEsO85KjV14s1OQ1T09o7+GD+fyE9kREtRkLNflEIJ/QnoioNmOh9oKiKLzgejlVndBeAWA0F7r5wpb/Tmhfm3Ebk8O85DAvOXrlxa5v8rmCzz+9cEJ7QOqE9i/PRORg/588gIhIb+z6riFCCOTl5bHpqYLIwUOdz5GLsq7voqZNK3R9lztXLou0E25jcpiXHCEETuSeZl4e0mv7YqH2gqZpyMnJYcekC65OaC9UFYUdOpTr+q6ZE9rXZtzG5DAvOVszc/Hsih+wbf8pvadSK+i1fbFQk99UPKG9kxo6oT0RuTb7m3RYrAKz1u3VeypUCRZq8qtAOKE9ETnbknkK2w+eAQBsP3gGWzK5Vx2oWKi9oCgKTCYTOyarYOsGVxQFwadOQWF3t8e4jclhXp6btW4vDAqQW6TAoIB71R7Qa/tiofaCqqpISkriSe09ENn3ZjR75RU0zMpCs1deYZH2ELcxOczLM1syT+HnA2dQoinYnquiRFPw8wHuVVdFr+2LW7MXNE1Dbm4uG1c8FN6nNxp+/hnC+/TWeyq1BrcxOczLM7a9aRUCrSM1qBDcq/aAXtsXC7UXhBDIzc3lVxs8JITAqVOnmJcEbmNymFfVbHvT1rJzDKF1pICiAFYB7lVXQa/ti4WaiKgese1Nu8K96sBk1HsCRERUM2x70+6U36vu0apRDc4ssBwsOAhzqdlpXNM0nDl3BpbTFpefU5uCTEiOTPb5fFiovaAoCqKiothh6iHmJY+ZyWFelbPtTVsvHLkVAI6YFYcz89v2qle0ulqPKeruYMFBDPp0kMvbVKhoY2yD9D/SocH159Srh672ebHmoW8vqKqKhIQEdph6iHnJY2ZymJd75T+bttGEgj/PqNDExTc29f2zald70jYaNOyx7HFbpKu6f3Vxa/aCpmnIzs5mh6mHmJc8ZiaHebnn6rNpVRG4tKEGVXFsjuJn1a6pUNHO2A5qDZdOFmovCCGQn5/PDlMPMS95zEwO83LN1d40UHZtu2Ym4XSNu/q+V+2OAgVNjU2heHRVQN9hoSYiquNmrdsL2Y/tFe5VBwwWaiKiOuxciQW/HsqD7EEGIYBfD+XhfInVPxMjj7Hr2wuKoiA2NpYdph5iXvKYmRzm5Sws2IitU27C2SKL021CaDAX5OGJyGgoLq5yFxFqRINgQ01Ms1YQEMiyZEGgZj9aYaH2gqqqiI2N1XsatQbzksfM5DAv1xqFh6BReIjrGxtH1OxkajENGrIsWTX+vDz07QVN03D48GF2mHqIecljZnKYlxzm5bmo843RpLA5rtV6oUlhc0Sdb1xjz809ai8IIWA2m9lh6iHmJY+ZyWFecpiXZ6LON8adO58CVIHIliW4dH8woCn4qMv/Ib/BSb8/P/eoiYiIKhFkdf2xgbtxXwuIQj1nzhykpKQgNDQU3bt3x7Zt29wue8MNN0BRFKd/AwcOrMEZExER1QzdC/WyZcswYcIETJ06FTt27EDnzp3Rt29fnDhxwuXyn3zyCbKzs+3//vzzTxgMBtx22201PPOyxpX4+HiertBDzEseM5PDvOQwL0kacP6EEZWcQdQvdP+MetasWbjvvvtwzz33AADeeecdfPHFF5g/fz4mTZrktHxMTIzDz0uXLkVYWJguhVpRFERHR9f489ZWzEseM5PDvOQwL9eizjd2OKzd8Hzchf9TUFpgcDFeptRQ7Jf56FqoS0pK8Msvv2Dy5Mn2MVVV0bt3b2zZssWjx5g3bx7uuOMOmEwml7cXFxejuPhieAUFBQAAq9UKq7Xsi/yKokBVVWia5tBU4W5cVVUoigKLxYIDBw4gOTkZqqrax22PW355AE6dle7GDQYDhBAO47a5uBv3dO5VrZO7cV+sk9VqRVZWlj2vurBO/n6d3G1jtXmd/Pk6aZrmsI3VhXVyNe6rdQKArKwsNG/e3P5ctX2dvH2dtNMG3LnzSQAKoJZrslMFIARMSaUwHwkCoOCm/XeX3WabmgpoNxlgjbZ6tE6e0rVQ5+bmwmq1Ii7O8V1JXFwc9uzZU+X9t23bhj///BPz5s1zu8zMmTMxffp0p/HMzEyEh4cDAKKiopCQkIDjx48jPz/fvkxsbCxiY2Nx9OhRmM0Xr4gSHx+P6OhoHDx4EDk5OSgpKYGqqmjWrBnCw8ORmZnp8MK0aNECRqMRGRkZDnNITU2FxWJBVtbF7+Wpqoo2bdrAbDbjyJEj9vHg4GC0bNkS+fn5yMnJsY+bTCYkJSXh9OnTyM3NtY9Xd50OHDiAkpIS+7iv16l8XnVlnfz9OpXPrK6sk79ep+LiYoe86sI6+fN1atKkCc6cOYPi4mJ7Aa3t6+Tt61ScXwxDmID1nIKIlBKUPw9M4REjDCECka1KgHJXHCvYHwzVKBDevBTFp4uQYc3waJ08pQgd+/KPHTuGxMRE/Pjjj+jRo4d9/PHHH8fGjRuxdevWSu//r3/9C1u2bMHvv//udhlXe9S2FzgyMhJA9d+FlZaWIiMjA61bt4bBYKhz7yzLj/tinSwWC9LT0+151YV18vfr5G4bq83r5M/XyWq1OmxjdWGdXI37ap2EEEhPT0erVq3sedX2dfL2dco9XIiVL2yH0x41AKDs61kFWcEOhbr8HvWwx7shNim8ynXKz89HdHQ08vPz7bXIHV33qGNjY2EwGHD8+HGH8ePHjyM+Pr7S+5rNZixduhTPPvtspcuFhIQgJMS5hd5gMNg3TBvbBlRRZeOqqjo9VsXHrc64oihS49WZu8y4r9bJVV61fZ38/Tq5yqy2r5PMuD+3sdqwTu7GfbFOVqvVvry3fw8DZZ28HS/7/wtFWKt4XVCU3SYU59sAQIN9+6tq7jKnudW11S84OBhdu3bF+vXr7WOapmH9+vUOe9iurFixAsXFxRgxYoS/p+mW7XC3uxefHDEvecxMDvOSw7ycBYVUcm5zDTAfC6q067vS+1eTroe+gbKvZ6WlpWHu3Lm48sor8dprr2H58uXYs2cP4uLiMHLkSCQmJmLmzJkO97vuuuuQmJiIpUuXSj1fQUEBoqKiPDrcQERE9U/e8XMoLb54KP90thnfLNjltFzvezogJuFiI3NQiAHRcWEePYdMLdL961nDhw/HyZMn8cwzzyAnJwddunTB119/bW8wO3TokNO7vb1792Lz5s1Yu3atHlO2s1qtyMzMdPh8h9xjXvKYmRzmJYd5uea22KoCESklOHug7BSiMQkmNG7u/4ua6F6oAWDs2LEYO3asy9s2bNjgNNa2bduAOTctT2Yvh3nJY2ZymJcc5iXHxdVA/Y4fTBAREQUwFmoiIqJKuGsQ80fjmCu6N5PVNF82kwkhUFJSguDgYKlW+/qKecljZnKYlxzm5bm84+dQUmRBqaUUQcYgBIcaPW4cc6VWNZPVdkYjI5TBvOQxMznMSw7z8kx0XJj95CW2E6XUFB769oKmacjIyGAzhoeYlzxmJod5yWFecvTKi4WaiIgogLFQExERBTAWaiIiogDGrm8v6NVYUFsxL3nMTA7zksO85PgyL5laxD1qL1ksFr2nUKswL3nMTA7zksO85OiRFwu1FzRNQ1ZWFjsmPcS85DEzOcxLDvOSo1deLNREREQBjIWaiIgogLFQe4kXXJfDvOQxMznMSw7zkqNHXuz6JiIiqmHs+q4hQggUFhYGzLWxAx3zksfM5DAvOcxLjl55sVB7QdM0HDlyhB2THmJe8piZHOYlh3nJ0SsvFmoiIqIAxkJNREQUwFiovaAoCi+4LoF5yWNmcpiXHOYlR6+82PVNRERUw9j1XUOEEMjLy2PHpIeYlzxmJod5yWFecvTKi4XaC5qmIScnhx2THmJe8piZHOYlh3nJ0SsvFmoiIqIAxkJNREQUwFiovaAoCkwmEzsmPcS85DEzOcxLDvOSo1de7PomIiKqYez6riGapiE3N5eNGB5iXvKYmRzmJYd5ydErLxZqLwghkJuby682eIh5yWNmcpiXHOYlR6+8WKiJiIgCGAs1ERFRAGOh9oKiKIiKimLHpIeYlzxmJod5yWFecvTKi13fRERENYxd3zVE0zRkZ2ezY9JDzEseM5PDvOQwLzl65cVC7QUhBPLz89kx6SHmJY+ZyWFecpiXHL3yYqEmIiIKYCzUREREAYyF2guKoiA2NpYdkx5iXvKYmRzmJYd5ydErL3Z9ExER1TB2fdcQTdNw+PBhdkx6iHnJY2ZymJcc5iVHr7xYqL0ghIDZbGbHpIeYlzxmJod5yWFecvTKi4WaiIgogLFQExERBTAWai+oqor4+HioKmP0BPOSx8zkMC85zEuOXnkZa/TZ6hhFURAdHa33NGoN5iWPmclhXnKYlxy98uLbKC9omob9+/ezY9JDzEseM5PDvOQwLzl65cVC7QUhBEpKStgx6SHmJY+ZyWFecpiXHL3yYqEmIiIKYCzUREREAYyF2guqqqJZs2bsmPQQ85LHzOQwLznMS45eebHr2wuKoiA8PFzvadQazEseM5PDvOQwLzl65cW3UV6wWq1IT0+H1WrVeyq1AvOSx8zkMC85zEuOXnmxUHuJX2uQw7zkMTM5zEsO85KjR14s1ERERAGMhZqIiCiAKaKefdNd5mLdVbF9+T04OBiKovhohnUX85LHzOQwLznMS44v85KpRdyj9pLRyMZ5GcxLHjOTw7zkMC85euTFQu0FTdOQkZHBZgwPMS95zEwO85LDvOTolRcLNRERUQBjoSYiIgpgLNREREQBjF3fXhBCQNM0qKrKjkkPMC95zEwO85LDvOT4Mi92fdcgi8Wi9xRqFeYlj5nJYV5ymJccPfJiofaCpmnIyspix6SHmJc8ZiaHeclhXnL0youFmoiIKICxUBMREQUwFmov8YLrcpiXPGYmh3nJYV5y9MiLXd9EREQ1jF3fNUQIgcLCQtSz9zrVxrzkMTM5zEsO85KjV14s1F7QNA1Hjhxhx6SHmJc8ZiaHeclhXnL0youFmoiIKICxUBMREQUwFmovKIrCC65LYF7ymJkc5iWHecnRKy92fRMREdUwdn3XECEE8vLy2DHpIeYlj5nJYV5ymJccvfJiofaCpmnIyclhx6SHmJc8ZiaHeclhXnI0TcORo8fY9U11U97xc8g9XAhzfjFyDxci7/g5vadERCTl56zTeGdTJrYfOFOjz2us0Wejeinv+DksmfoToApEtizBT/tzAU3BXdOvQnRcmN7TIyLyyOxv0tHQKjBr3V4saxVbY8/LPWovKIoCk8nEjskqlBZby/5HAJZzKiAqjJNb3MbkMC85zMtzWzJPYfvBM8gtUrD94BlsyTxVY8/NQu0FVVWRlJTEk9p7Sig4dywIEPyj4CluY3KYlxzm5blZ6/YCULA9VwWgXPi5ZvDV8YKmacjNzWUjhqcUgZAYC6Cww9RT3MbkMC85zMszWzJP4ecDZyCEQOtIDUII/Hyg5vaqWai9IIRAbm4uv9pQQd7xczh56Kz93+lsc9kNChASYwUu7FCfzjY7LMcGM2fcxuQwLznMyzOz1u2FQQEUBWgdKaAogEFBje1Vs5mMfMreOOaBbxbschpjgxkRBRLb3jRQVpxtrAL2veoerRr5dQ7coyaf8rZBjA1mRBRIbHvTrtTUXjULtRcURUFUVBQ7Jj0lgJICg73rm6rGbUwO85LDvCpn25u2XvibJQAcMSv2P2Hl96r9iYXaC6qqIiEhgR2TnhIKik4Y2fUtgduYHOYlh3lVruLetCYU/HlGhVbub1hN7FXz1fGCpmnIzs5mx2Q5QSEG9zcqAqFNKu/6rvT+9RC3MTnMSw7zcq/i3jQAqIrApQ01qOX+htXEXjWbybwghEB+fj6aNGmi91QCRnRcGO6afpXDZ82ns81ljWMKEBxpRVFu2eHv3vd0QEyCyb5cUIiBjWQVcBuTw7zkMC/3bHvT5Qu1AqCZSWB3nuNRQdte9YpWV/tlLizU5HOeFtuYBBMaN4/w82yIiOSU7/T2hL87wHnom4iIqJxZ6/ZCtr9O8eNn1SzUXlAUBbGxseyY9JQAik+z61sGtzE5zEsO83J2rsSCXw/lwdU5YIQA9hUobm/79VAezpf4/iumPPTtBVVVERtbc1dQqa3sDWJCQfFpo/M4ucVtTA7zksO8nIUFG7F1yk04W2SRvm9EqBENgn3/d42F2guapuHo0aNITEzk1xsqYWswKz5fity844iNjkNIgyA2jnmA25gc5iWHebnWKDwEjcJDnMb1youF2gtCCJjNZp4n1wPRcWGwWq04U5SN2KRwGAzcm/YEtzE5zEsO85KjV166v4WaM2cOUlJSEBoaiu7du2Pbtm2VLp+Xl4cHH3wQCQkJCAkJQZs2bfDll1/W0GyJiIhqlq571MuWLcOECRPwzjvvoHv37njttdfQt29f7N271+X3+kpKStCnTx80adIEK1euRGJiIg4ePIjo6OianzwREVENUISOxzy6d++OK664Am+++SaAsuP/SUlJeOihhzBp0iSn5d955x28/PLL2LNnD4KCgqr1nAUFBYiKikJ+fj4iIyO9mr/tZAE8V65nmJc8ZiaHeclhXnJ8mZdMLdLt0HdJSQl++eUX9O7d++JkVBW9e/fGli1bXN7ns88+Q48ePfDggw8iLi4Ol156KWbMmAGrVZ8rLimKgujoaG7gHmJe8piZHOYlh3nJ0Ssv3Q595+bmwmq1Ii4uzmE8Li4Oe/bscXmf/fv349tvv8Vdd92FL7/8Evv27cO///1vlJaWYurUqS7vU1xcjOLiYvvPBQUFAACr1Wov8IqiQFVVaJrm0CTgblxVVSiKAovFggMHDiA5ORmqqtrHK75xsHUHVjyfrrtxg8EAIYTDuG0u7sY9nXtV6+Ru3BfrZLVakZWVZc+rLqyTv18nd9tYbV4nf75OmqY5bGN1YZ1cjftqnQAgKysLzZs3tz9XbV8nf75OAHDgwAGHvLxZJ0/Vqq5vTdPQpEkTvPvuuzAYDOjatSuOHj2Kl19+2W2hnjlzJqZPn+40npmZifDwcABAVFQUEhIScPz4ceTn59uXiY2NRWxsLI4ePQqz2Wwfj4+PR3R0NA4ePIicnByUlJRAVVU0a9YM4eHhyMzMdHhhWrRoAaPRiIyMDIc5pKamwmKxICsryz6mqiratGkDs9mMI0eO2MeDg4PRsmVL5OfnIycnxz5uMpmQlJSE06dPIzc31z5e3XU6cOAASkpK7OO+XqfyedWVdfL361Q+s7qyTv56nYqLix3yqgvr5M/XqUmTJjhz5gyKi4vtxaa2r5M/X6fmzZujuLgYGRkZDoW6uuvkKd0+oy4pKUFYWBhWrlyJIUOG2MfT0tKQl5eH//3vf0736dmzJ4KCgvDNN9/Yx7766isMGDAAxcXFCA4OdrqPqz1q2wts+1yguu/CSktLkZGRgdatW8NgMNSrd5bVWSeLxYL09HR7XnVhnfz9OrnbxmrzOvnzdbJarQ7bWF1YJ1fjvlonIQTS09PRqlUre161fZ38+ToJIZCRkeGQV3XXKT8/H9HR0R59Rq3bHnVwcDC6du2K9evX2wu1pmlYv349xo4d6/I+11xzDT788ENommYPJj09HQkJCS6LNACEhIQgJMT5i+sGg8Hpu7zl3yF5Oq6qqtNjufuOsMy4oihS49WZu8y4r9bJVV61fZ38/Tq5yqy2r5PMuD+3sdqwTu7GfbFOVqvVvry3fw8DZZ18OV7xOSvLy9XyQOXr5Cldv0c9YcIEvPfee1i0aBF2796NBx54AGazGffccw8AYOTIkZg8ebJ9+QceeACnT5/Gww8/jPT0dHzxxReYMWMGHnzwQV3mbzvc7e5FJkfMSx4zk8O85DAvOXrlpetn1MOHD8fJkyfxzDPPICcnB126dMHXX39tbzA7dOiQQyBJSUlYs2YNxo8fj06dOiExMREPP/wwnnjiCV3mryiK/XNuqhrzksfM5DAvOcxLjl556fo9aj348nvUVqsVmZmZTp9XkGvMSx4zk8O85DAvOb7Mq1Z8j7quqNg8QJVjXvKYmRzmJYd5ydEjLxZqIiKiAMZCTUREFMD4GbUXhBAoKSlBcHAwT8HnAeYlj5nJYV5ymJccX+bFz6hrkNFYq07upjvmJY+ZyWFecpiXHD3yYqH2gqZpyMjIYDOGh5iXPGYmh3nJYV5y9MqLhZqIiCiAsVATEREFMBZqIiKiAMauby/Yropiu9IKVY55yWNmcpiXHOYlx5d5seu7BlksFr2nUKswL3nMTA7zksO85OiRFwu1FzRNQ1ZWFjsmPcS85DEzOcxLDvOSo1deLNREREQBjIWaiIgogLFQe4kXXJfDvOQxMznMSw7zkqNHXuz6JiIiqmHs+q4hQggUFhainr3XqTbmJY+ZyWFecpiXHL3yYqH2gqZpOHLkCDsmPcS85DEzOcxLDvOSo1deLNREREQBjIWaiIgogLFQe0FRFF5wXQLzksfM5DAvOcxLjl55seubiIiohrHru4YIIZCXl8eOSQ8xL3nMTA7zksO85OiVFwu1FzRNQ05ODjsmPcS85DEzOcxLDvOSo1deLNREREQBjIWaiIgogLFQe0FRFJhMJnZMeoh5yWNmcpiXHOYlR6+82PVNRERUw9j1XUM0TUNubi4bMTzEvOQxMznMSw7zkqNXXizUXhBCIDc3l19t8BDzksfM5DAvOcxLjl55sVATEREFMBZqIiKiAMZC7QVFURAVFcWOSQ8xL3nMTA7zksO85OiVF7u+iYiIahi7vmuIpmnIzs5mx6SHmJc8ZiaHeclhXnL0youF2gtCCOTn57Nj0kPMSx4zk8O85DAvOXrlxUJNREQUwFioiYiIAhgLtRcURUFsbCw7Jj3EvOQxMznMSw7zkqNXXuz6JiIiqmHs+q4hmqbh8OHD7Jj0EPOSx8zkMC85zEuOXnmxUHtBCAGz2cyOSQ8xL3nMTA7zksO85OiVFws1ERFRAGOhJiIiCmAs1F5QVRXx8fFQVcboCeYlj5nJYV5ymJccvfIy1uiz1TGKoiA6OlrvadQazEseM5PDvOQwLzl65cW3UV7QNA379+9nx6SHmJc8ZiaHeclhXnL0youF2gtCCJSUlLBj0kPMSx4zk8O85DAvOXrlxUJNREQUwFioiYiIAhgLtRdUVUWzZs3YMekh5iWPmclhXnKYlxy98mLXtxcURUF4eLje06g1mJc8ZiaHeclhXnL0yotvo7xgtVqRnp4Oq9Wq91RqBeYlj5nJYV5ymJccvfJiofYSv9Ygh3nJY2ZymJcc5iVHj7xYqImIiAIYCzUREVEAU0Q9+6a7zMW6q2L78ntwcDAURfHRDOsu5iWPmclhXnKYlxxf5iVTi7hH7SWjkY3zMpiXPGYmh3nJYV5y9MiLhdoLmqYhIyODzRgeYl7ymJkc5iWHecnRKy++lSKfO1hwEOZSs9O4pmk4c+4MLKctLk8YYAoyITkyuSamSERUa7BQk08dLDiIQZ8OcnmbAQb0DO2JjX9shBWuv4e4euhqFmsionJ46Jt8ytWedE3en4iormGh9oKqqkhNTeV5cj1khRUbi9zvTZMzbmNymJcc5iVHr7z46njJYrHoPYVaQ4GCUCUUCvg1EBncxuQwLznMS44eebFQe0HTNGRlZbFj0kMqVHQP6Q6Vm53HuI3JYV5ymJccvfLiX0wiIqIAxkJNREQUwFiovcQmDDkWwc/DZHEbk8O85DAvOXrkxe9Re8FgMKBNmzZ6T6PWsMKKTcWb9J5GrcJtTA7zksO85OiVF99KeUEIgcLCQtSz65pUmwIFMWoMu74lcBuTw7zkMC85euXFQu0FTdNw5MgRdkx6SIWKLsFd2PUtgduYHOYlh3nJ0Ssv/sUkIiIKYCzUREREAYyF2guKovCC65LMGs/lLYPbmBzmJYd5ydErL3Z9e0FVVbRs2VLvaQQUU5DJ7W1WWLG1ZGu1718fcRuTw7zkMC85euXFQu0FIQTy8/MRFRXFd6QXJEcmY/XQ1S6vgiWEQLG5GCGmEJd58XrUzriNyWFecpiXHL3yYqH2gqZpyMnJQUREBAwGg97TCRjuiq3VakVGbgZSm6UyLw9xG5PDvOQwLzl65cXPqImIiAIYCzUREVEAY6H2gqIoMJlM/GzHQ8xLHjOTw7zkMC85euWliHp27riCggJERUUhPz8fkZGRek+HiIjqIZlaxD1qL2iahtzcXJ5+z0PMSx4zk8O85DAvOXrlxULtBSEEcnNzeUJ7DzEvecxMDvOSw7zk6JUXCzUREVEAY6EmIiIKYCzUXlAUhWf0kcC85DEzOcxLDvOSo1de7PomIiKqYez6riGapiE7O5sdkx5iXvKYmRzmJYd5ydErLxZqL9hO0F7PDkpUG/OSx8zkMC85zEuOXnmxUBMREQWwenf1LNs7oYKCAq8fy2q1orCwEAUFBbzyjAeYlzxmJod5yWFecnyZl60GebJ3Xu8K9dmzZwEASUlJOs+EiIjqu7NnzyIqKqrSZepd17emaTh27BgiIiK8brEvKChAUlISDh8+zA5yDzAvecxMDvOSw7zk+DIvIQTOnj2Lpk2bQlUr/xS63u1Rq6qKZs2a+fQxIyMjuZFLYF7ymJkc5iWHecnxVV5V7UnbsJmMiIgogLFQExERBTAWai+EhIRg6tSpCAkJ0XsqtQLzksfM5DAvOcxLjl551btmMiIiotqEe9REREQBjIWaiIgogLFQExERBTAWaiLS3bRp09ClSxe9p0EUkFioPTBq1CgMGTLE5W0pKSlQFAWKoiAsLAwdO3bE+++/X7MT1MnJkyfxwAMPoHnz5ggJCUF8fDz69u2LjRs3IjY2Fi+88ILL+z333HOIi4tDaWkpFi5cCEVR0L59e6flVqxYAUVRkJKS4uc10deoUaPs21BQUBBatGiBxx9/HEVFRfZlbLeX/3fttdfqOOuqbdmyBQaDAQMHDvTL45f/3TMYDGjatCnGjBmDM2fO+OX5XNmwYQMURUFeXl6NPaesittXXFwc+vTpg/nz50PTNPs6VPZvw4YNeq+Gz7n6u75y5UqEhobi1VdftedW8e/YqlWrHM5qacvvkksugdVqdVg2OjoaCxcu9HquLNQ+8OyzzyI7Oxt//vknRowYgfvuuw9fffWV3tPyu1tvvRW//vorFi1ahPT0dHz22We44YYbkJ+fjxEjRmDBggVO9xFCYOHChRg5ciSCgoIAACaTCSdOnMCWLVsclp03bx6aN29eI+uit379+iE7Oxv79+/H7NmzMXfuXEydOtVhmQULFiA7O9v+77PPPtNptp6ZN28eHnroIWzatAnHjh3zy3PYfvcOHTqEJUuWYNOmTRg3bpxfnqs2s21fBw4cwFdffYVevXrh4YcfxqBBg3D11Vc7bFe33367fXnbv6uvvlrvVfC7999/H3fddRfefvttPProowCA0NBQvPjiix69+du/fz8WL17sl7mxUPtAREQE4uPj0bJlSzzxxBOIiYnBunXr9J6WX+Xl5eH777/Hiy++iF69eiE5ORlXXnklJk+ejL/97W8YM2YM0tPTsXnzZof7bdy4Efv378eYMWPsY0ajEf/4xz8wf/58+9iRI0ewYcMG/OMf/6ixddKT7YhEUlIShgwZgt69ezttQ9HR0YiPj7f/i4mJ0Wm2VSssLMSyZcvwwAMPYODAgU57FS+88ALi4uIQERGBMWPGOBw9AICff/4Zffr0QWxsLKKiotCzZ0/s2LHD6Xlsv3uJiYno1asX0tLSnJb7+OOPcckllyAkJAQpKSl49dVXHW4/c+YMRo4ciYYNGyIsLAz9+/dHRkaG/faDBw9i8ODBaNiwIUwmEy655BJ8+eWXOHDgAHr16gUAaNiwIRRFwahRo7xIzX9s21diYiIuv/xyTJkyBf/73//w1VdfYfHixQ7bVYMGDezL2/4FBwfrvQp+9dJLL+Ghhx7C0qVLcc8999jHe/fujfj4eMycObPKx3jooYcwdepUFBcX+3x+LNQ+pGkaPv74Y5w5c6bOb9jh4eEIDw/HqlWrXG6YHTt2xBVXXOFQfIGyvcKrr74a7dq1cxgfPXo0li9fjnPnzgEAFi5ciH79+iEuLs5/KxGg/vzzT/z444+1ehtavnw52rVrh7Zt22LEiBGYP3++/XJ+y5cvx7Rp0zBjxgxs374dCQkJeOuttxzuf/bsWaSlpWHz5s346aefkJqaigEDBtivfufK0aNH8fnnn6N79+72sV9++QW333477rjjDvzxxx+YNm0ann76aYc3DqNGjcL27dvx2WefYcuWLRBCYMCAASgtLQUAPPjggyguLsamTZvwxx9/4MUXX0R4eDiSkpLw8ccfAwD27t2L7OxsvP76676K0O9uvPFGdO7cGZ988oneU9HVE088geeeew6rV6/G0KFDHW4zGAyYMWMG3njjDRw5cqTSx3nkkUdgsVjwxhtv+H6SgqqUlpYmbrnlFpe3JScni+DgYGEymYTRaBQARExMjMjIyKjZSepg5cqVomHDhiI0NFRcffXVYvLkyeK3336z3/7OO++I8PBwcfbsWSGEEAUFBSIsLEy8//779mUWLFggoqKihBBCdOnSRSxatEhomiZatWol/ve//4nZs2eL5OTkmlytGpeWliYMBoMwmUwiJCREABCqqoqVK1falwEgQkNDhclksv/79NNP9Zt0Fa6++mrx2muvCSGEKC0tFbGxseK7774TQgjRo0cP8e9//9th+e7du4vOnTu7fTyr1SoiIiLE559/bh8r/7sXGhoqAIju3buLM2fO2Jf5xz/+Ifr06ePwWI899pjo0KGDEEKI9PR0AUD88MMP9ttzc3NFgwYNxPLly4UQQnTs2FFMmzbN5by+++47AcDhOQNNZX+/hg8fLtq3b+/x8nVJWlqaCA4OFgDE+vXrXd5uy+Gqq64So0ePFkII8emnn4rypbP8NvDOO++ImJgYkZeXJ4QQIioqSixYsMDruXKP2gcee+wx7Ny5E99++y26d++O2bNno3Xr1npPy+9uvfVWHDt2DJ999hn69euHDRs24PLLL7fvrdx5552wWq1Yvnw5AGDZsmVQVRXDhw93+XijR4/GggULsHHjRpjNZgwYMKCmVkV3vXr1ws6dO7F161akpaXhnnvuwa233uqwzOzZs7Fz5077vz59+ug028rt3bsX27Ztw5133gmg7KON4cOHY968eQCA3bt3O+z1AkCPHj0cfj5+/Djuu+8+pKamIioqCpGRkSgsLMShQ4cclrP97v3+++9Yv349AGDgwIH2pp7du3fjmmuucbjPNddcg4yMDFitVuzevRtGo9FhPo0aNULbtm2xe/duAMC4cePwf//3f7jmmmswdepU/P77795GFDCEEF5f7rc269SpE1JSUjB16lQUFha6Xe7FF1/EokWL7NuEO2PGjEGjRo3w4osv+nSeLNQ+EBsbi9atW+O6667DihUrMG7cOOzatUvvadWI0NBQ9OnTB08//TR+/PFHjBo1yt4EFRkZiWHDhtmbyhYsWIDbb78d4eHhLh/rrrvuwk8//YRp06bh7rvvhtFYf67CajKZ0Lp1a3Tu3Bnz58/H1q1b7YXNJj4+Hq1bt7b/M5lMOs22cvPmzYPFYkHTpk1hNBphNBrx9ttv4+OPP0Z+fr5Hj5GWloadO3fi9ddfx48//oidO3eiUaNGKCkpcVjO9ruXmpqKG2+8Ea+99hp+/PFHfPfddz5bn3vvvRf79+/H3XffjT/++APdunXzz+FNHezevRstWrTQexq6SUxMxIYNG3D06FH069fP7Ucr119/Pfr27YvJkydX+nhGoxHPP/88Xn/9dZ82ULJQ+1hSUhKGDx9e5QtaV3Xo0AFms9n+85gxY7B582asXr0aP/74o0MTWUUxMTH429/+ho0bN2L06NE1Md2ApKoqpkyZgqeeegrnz5/XezpSLBYLFi9ejFdffdVh7/+3335D06ZN8dFHH6F9+/bYunWrw/1++uknh59/+OEHjBs3DgMGDLA3guXm5lb5/AaDAQDsubVv3x4//PCD02O3adMGBoMB7du3h8VicZjPqVOnsHfvXnTo0ME+lpSUhPvvvx+ffPIJHn30Ubz33nsAYO8jqPi1nNrg22+/xR9//OF05Ka+SU5OxsaNG5GTk1NpsX7hhRfw+eefO307paLbbrsNl1xyCaZPn+6zOdafXRYv5efnY+fOnQ5jjRo1crnsww8/jEsvvRTbt29Ht27damB2Ne/UqVO47bbbMHr0aHTq1AkRERHYvn07XnrpJdxyyy325a6//nq0bt0aI0eORLt27ar8msfChQvx1ltvuc22vrjtttvw2GOPYc6cOZg4caLe0/HY6tWrcebMGYwZMwZRUVEOt916662YN28eJk6ciFGjRqFbt2645pprsGTJEvz1119o2bKlfdnU1FR88MEH6NatGwoKCvDYY4+hQYMGTs939uxZ5OTkQAiBw4cP4/HHH0fjxo3t29mjjz6KK664As899xyGDx+OLVu24M0337Q3r6WmpuKWW27Bfffdh7lz5yIiIgKTJk1CYmKifTt+5JFH0L9/f7Rp0wZnzpzBd999Z//ef3JyMhRFwerVqzFgwAA0aNDA7REjPRUXFyMnJwdWqxXHjx/H119/jZkzZ2LQoEEYOXKk3tPTXVJSEjZs2IBevXqhb9+++Prrr52W6dixI+666y785z//qfLxXnjhBfTt29d3E/T6U+56IC0tTQBw+jdmzBiRnJwsZs+e7XSfvn37iv79+9f8ZGtIUVGRmDRpkrj88stFVFSUCAsLE23bthVPPfWUOHfunMOyM2bMEADESy+95PQ45ZvJXKkvzWSumndmzpwpGjduLAoLCwWAgG4esxk0aJAYMGCAy9u2bt0qAIjffvtNPP/88yI2NlaEh4eLtLQ08fjjjzs0k+3YsUN069ZNhIaGitTUVLFixQqn37Xk5GSH38fGjRuLAQMGiF9//dXheVeuXCk6dOgggoKCRPPmzcXLL7/scPvp06fF3XffLaKiokSDBg1E3759RXp6uv32sWPHilatWomQkBDRuHFjcffdd4vc3Fz77c8++6yIj48XiqKItLS0amfnL+X/fhmNRtG4cWPRu3dvMX/+fGG1Wl0uX1+aySqu55EjR0Rqaqq46qqrxNChQ51uz8rKsjeg2bhrKLz55psFAJ80k/Eyl0RERAGMn1ETEREFMBZqIiKiAMZCTUREFMBYqImIiAIYCzUREVEAY6EmIiIKYCzUREREAYyFmoiIKICxUBMREQUwFmoiIqIAxkJNREQUwFioiYiIAtj/A4gpH8utyIuMAAAAAElFTkSuQmCC", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Algorithm names\n", "algorithms = ['LR', 'SVM', 'RF', 'AdaBoost', 'DT', 'KNN']\n", "\n", "# Evaluation metric scores for each algorithm.\n", "metrics = {\n", " 'AUC': [ML_lr_val['auc_val'], ML_svm_val['auc_val'], ML_rf_val['auc_val'],ML_ada_val['auc_val'], ML_dt_val['auc_val'], ML_knn_val['auc_val']],\n", " 'Accuracy': [ML_lr_val['accuracy_val'], ML_svm_val['accuracy_val'], ML_rf_val['accuracy_val'],ML_ada_val['accuracy_val'], ML_dt_val['accuracy_val'], ML_knn_val['accuracy_val']],\n", " 'Precision':[ML_lr_val['precision_val'], ML_svm_val['precision_val'], ML_rf_val['precision_val'],ML_ada_val['precision_val'], ML_dt_val['precision_val'], ML_knn_val['precision_val']],\n", " 'Recall': [ML_lr_val['recall_val'], ML_svm_val['recall_val'], ML_rf_val['recall_val'],ML_ada_val['recall_val'], ML_dt_val['recall_val'], ML_knn_val['recall_val']],\n", " 'F1': [ML_lr_val['f1_val'], ML_svm_val['f1_val'], ML_rf_val['f1_val'],ML_ada_val['f1_val'], ML_dt_val['f1_val'], ML_knn_val['f1_val']]\n", "}\n", "\n", "# Assign a distinct marker shape to each evaluation metric.\n", "markers = {\n", " 'AUC': '^', # triangle\n", " 'Accuracy': 'o', # circle\n", " 'Precision': 's', # square\n", " 'Recall': 'D', # diamond\n", " 'F1': 'P' # pentagon\n", "}\n", "\n", "# plot\n", "plt.figure(figsize=(5, 6))\n", "\n", "# The x-axis denotes the algorithms.\n", "x = np.arange(len(algorithms))\n", "\n", "# Plot scatter points\n", "for metric, scores in metrics.items():\n", " plt.scatter(x, scores, label=metric, marker=markers[metric], s=100)\n", "\n", "# Set the legend, labels, and axes.\n", "plt.xticks(x, algorithms)\n", "plt.ylabel(\"Score\")\n", "plt.title(\"Algorithm Performance Comparison\")\n", "plt.legend(title=\"Metrics\")\n", "plt.grid(True, linestyle='--', alpha=0.5)\n", "\n", "plt.tight_layout()\n", "\n", "# Save as PDF\n", "plt.savefig(current_path + '/save_data/' + disease_name + \"/Fig2a.pdf\")\n", "\n", "plt.show()\n", "plt.close()" ] }, { "cell_type": "markdown", "id": "f12bb7b8-cb16-45ca-8468-e260e5eb6c06", "metadata": {}, "source": [ "## The optimal logistic regression model was selected and subsequently retrained on the full dataset; interpretability analysis was then performed to identify candidate target cfRNAs." ] }, { "cell_type": "code", "execution_count": 7, "id": "5a4d436b-4b63-41f5-ad9d-353052be98c6", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Logistic Regression:\n", "Training dataset Accuracy: 1.0000, Precision: 1.0000, Recall: 1.0000, F1-Score: 1.0000, AUC:1.0000\n", "****************************************************************************************************\n" ] } ], "source": [ "X = sample_cfRNA_exp['data_exp']\n", "ML_lr = CellFreeGMF.diagnosis_ML.ML_lr(sample_cfRNA_exp['data_exp'], sample_cfRNA_exp['label']['label'])" ] }, { "cell_type": "markdown", "id": "359f49e3-69f2-42fd-b063-32ef21b06d1f", "metadata": {}, "source": [ "## SHAP-based interpretability analysis" ] }, { "cell_type": "code", "execution_count": 8, "id": "8da9d84e-e5e8-4ae4-ad87-2921bd987201", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "explainer = shap.LinearExplainer(ML_lr, X, feature_names=X.columns)\n", "shap_values = explainer(X)\n", "\n", "shap.summary_plot(shap_values, X, feature_names=X.columns, show=False, max_display=10)\n" ] }, { "cell_type": "markdown", "id": "5f810d76-1499-4476-af66-b4125ecec819", "metadata": {}, "source": [ "## Save the differential expression analysis results and the SHAP results." ] }, { "cell_type": "markdown", "id": "acf212b3", "metadata": {}, "source": [ "save SHAP result" ] }, { "cell_type": "code", "execution_count": 9, "id": "f129b7ae", "metadata": {}, "outputs": [], "source": [ "# extract feature importance\n", "shap_importance = np.abs(shap_values.values).mean(axis=0)\n", "feature_names = X.columns\n", "\n", "importance_df = pd.DataFrame({\n", " 'Feature': X.columns,\n", " 'Mean_ABS_SHAP': shap_importance\n", "})\n", "\n", "importance_df = importance_df.sort_values(by='Mean_ABS_SHAP', ascending=False)\n", "importance_df.to_csv(current_path + '/save_data/' + disease_name + '/shap_feature_importance.csv', index=False)\n", "\n", "# the top 10% in terms of importance were selected\n", "sorted_idx = np.argsort(shap_importance)[::-1]\n", "\n", "feature_names[sorted_idx[:round(sorted_idx.size * 0.1)]].to_series().to_csv(current_path + '/save_data/' + disease_name + '/SHAP_ALL_gene.txt', header=False, index=False)\n", "pd.DataFrame({\n", " 'gene_id': feature_names[sorted_idx],\n", " 'feature_importance': shap_importance[sorted_idx]\n", "}).to_csv(current_path + '/save_data/' + disease_name + '/SHAP_results.csv', header=False, index=False)" ] }, { "cell_type": "markdown", "id": "4d0dfc87", "metadata": {}, "source": [ "save DEG result" ] }, { "cell_type": "code", "execution_count": 10, "id": "a7d4fddb-9b2b-4cd9-b245-39a0cc9c4628", "metadata": {}, "outputs": [], "source": [ "DEG_res.to_csv(current_path + '/save_data/' + disease_name + '/DEG_res.csv')" ] } ], "metadata": { "kernelspec": { "display_name": "CellFreeGMF", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.10.16" } }, "nbformat": 4, "nbformat_minor": 5 }