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+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "B6pByon9zTBm"
+ },
+ "source": [
+ "# **Importing Needed Libraries**"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 169,
+ "metadata": {
+ "id": "kf3CXD-ezPYe"
+ },
+ "outputs": [],
+ "source": [
+ "import pandas as pd\n",
+ "import seaborn as sns\n",
+ "import numpy as np\n",
+ "from matplotlib import pyplot as plt\n",
+ "from sklearn.compose import ColumnTransformer\n",
+ "from sklearn.pipeline import Pipeline\n",
+ "from sklearn.experimental import enable_iterative_imputer\n",
+ "from sklearn.impute import SimpleImputer, IterativeImputer\n",
+ "from sklearn.preprocessing import StandardScaler, OneHotEncoder, LabelEncoder\n",
+ "from sklearn.model_selection import cross_val_score\n",
+ "from scipy import stats\n",
+ "from sklearn.cluster import AgglomerativeClustering\n",
+ "from scipy.cluster.hierarchy import linkage, dendrogram, fcluster\n",
+ "from sklearn.decomposition import PCA\n",
+ "from sklearn.model_selection import train_test_split\n",
+ "from sklearn.cluster import KMeans\n",
+ "from sklearn.linear_model import LogisticRegression\n",
+ "from sklearn.ensemble import RandomForestClassifier, GradientBoostingClassifier\n",
+ "from sklearn.svm import SVC\n",
+ "from sklearn.metrics import accuracy_score, precision_score, recall_score, f1_score, roc_auc_score\n",
+ "from keras.models import Model\n",
+ "from keras.layers import Input, Dense\n",
+ "import missingno as msno"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "-QCU9dRCyn8J"
+ },
+ "source": [
+ "# **Loading the Data**"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "YSSCOC5iycde"
+ },
+ "outputs": [],
+ "source": [
+ "patient_df = pd.read_csv ('patients_01.csv')"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "albGI76QziHE"
+ },
+ "source": [
+ "# **Exploring the data set**"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "qgr627fTzNmo",
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "outputId": "63c3eb70-93f8-46a5-9ba0-5f2359158d0d"
+ },
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ " age bmi alcohol_misuse health_gen health_ment \\\n",
+ "count 5124.000000 5124.000000 4098.000000 5064.000000 5041.000000 \n",
+ "mean 55.038642 28.123341 2.394339 2.468009 3.399127 \n",
+ "std 16.497927 6.919013 2.908278 1.089227 7.732750 \n",
+ "min 16.000000 0.000000 0.000000 0.000000 0.000000 \n",
+ "25% 43.000000 24.000000 1.000000 2.000000 0.000000 \n",
+ "50% 56.000000 27.000000 2.000000 2.000000 0.000000 \n",
+ "75% 66.000000 31.000000 3.000000 3.000000 2.000000 \n",
+ "max 104.000000 87.000000 27.000000 5.000000 30.000000 \n",
+ "\n",
+ " health_phys \n",
+ "count 4973.000000 \n",
+ "mean 4.007641 \n",
+ "std 9.619864 \n",
+ "min 0.000000 \n",
+ "25% 0.000000 \n",
+ "50% 0.000000 \n",
+ "75% 2.000000 \n",
+ "max 87.000000 \n"
+ ]
+ }
+ ],
+ "source": [
+ "print(patient_df.describe())"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "xksZJsKazz0G",
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "outputId": "22b720f1-2be2-4bbd-b425-a886a8f755f7"
+ },
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "<class 'pandas.core.frame.DataFrame'>\n",
+ "RangeIndex: 5124 entries, 0 to 5123\n",
+ "Data columns (total 18 columns):\n",
+ " # Column Non-Null Count Dtype \n",
+ "--- ------ -------------- ----- \n",
+ " 0 age 5124 non-null int64 \n",
+ " 1 gender 5124 non-null object \n",
+ " 2 bmi 5124 non-null int64 \n",
+ " 3 high_chol 4788 non-null object \n",
+ " 4 chol_check 4838 non-null object \n",
+ " 5 history_stroke 5124 non-null bool \n",
+ " 6 history_heart_disease 5072 non-null object \n",
+ " 7 history_smoking 3610 non-null object \n",
+ " 8 amount_activity 4191 non-null object \n",
+ " 9 alcohol_misuse 4098 non-null float64\n",
+ " 10 fruits 5019 non-null object \n",
+ " 11 vegetables 5012 non-null object \n",
+ " 12 health_gen 5064 non-null float64\n",
+ " 13 health_ment 5041 non-null float64\n",
+ " 14 health_phys 4973 non-null float64\n",
+ " 15 walking_diff 5124 non-null bool \n",
+ " 16 high_bp 5124 non-null object \n",
+ " 17 dissease 5124 non-null bool \n",
+ "dtypes: bool(3), float64(4), int64(2), object(9)\n",
+ "memory usage: 615.6+ KB\n",
+ "None\n"
+ ]
+ }
+ ],
+ "source": [
+ "print(patient_df.info())"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "0cXPZuRnz9A4",
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "outputId": "30946de5-c8bb-4cfb-cad2-3e62ae116c18"
+ },
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "5124\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Number of samples\n",
+ "num_rows = len(patient_df)\n",
+ "print(num_rows)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "tiFyXW0rz2oF",
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "outputId": "a46bc380-3eba-48b9-c851-807aa1c0ea05"
+ },
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "age 0\n",
+ "gender 0\n",
+ "bmi 0\n",
+ "high_chol 336\n",
+ "chol_check 286\n",
+ "history_stroke 0\n",
+ "history_heart_disease 52\n",
+ "history_smoking 1514\n",
+ "amount_activity 933\n",
+ "alcohol_misuse 1026\n",
+ "fruits 105\n",
+ "vegetables 112\n",
+ "health_gen 60\n",
+ "health_ment 83\n",
+ "health_phys 151\n",
+ "walking_diff 0\n",
+ "high_bp 0\n",
+ "dissease 0\n",
+ "dtype: int64\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Identify the number of missing values in each feature\n",
+ "missing_values = patient_df.isnull().sum()\n",
+ "print(missing_values)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "lWkDVD0L0oy0",
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "outputId": "a5504a0d-94dc-4134-be27-d5c859f59abf"
+ },
+ "outputs": [
+ {
+ "output_type": "execute_result",
+ "data": {
+ "text/plain": [
+ "age 0.00\n",
+ "gender 0.00\n",
+ "bmi 0.00\n",
+ "high_chol 6.56\n",
+ "chol_check 5.58\n",
+ "history_stroke 0.00\n",
+ "history_heart_disease 1.01\n",
+ "history_smoking 29.55\n",
+ "amount_activity 18.21\n",
+ "alcohol_misuse 20.02\n",
+ "fruits 2.05\n",
+ "vegetables 2.19\n",
+ "health_gen 1.17\n",
+ "health_ment 1.62\n",
+ "health_phys 2.95\n",
+ "walking_diff 0.00\n",
+ "high_bp 0.00\n",
+ "dissease 0.00\n",
+ "dtype: float64"
+ ]
+ },
+ "metadata": {},
+ "execution_count": 117
+ }
+ ],
+ "source": [
+ "# Calculating the percentage of missing values for each feature\n",
+ "round(100*(1-patient_df.count()/len(patient_df)),2)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "n7hYYtH80zMw",
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 444
+ },
+ "outputId": "53b1864e-32d5-4055-867f-89b0ac200cc3"
+ },
+ "outputs": [
+ {
+ "output_type": "execute_result",
+ "data": {
+ "text/plain": [
+ " age gender bmi high_chol chol_check history_stroke \\\n",
+ "4 61 male 32 normal checked False \n",
+ "6 55 male 37 high notchecked False \n",
+ "33 34 female 29 normal checked False \n",
+ "73 79 female 19 normal checked False \n",
+ "93 65 female 29 normal checked False \n",
+ "... ... ... ... ... ... ... \n",
+ "4958 83 female 26 NaN checked False \n",
+ "4990 69 female 35 normal checked False \n",
+ "4998 74 male 23 normal NaN False \n",
+ "5053 84 female 34 NaN NaN False \n",
+ "5113 48 female 22 high checked False \n",
+ "\n",
+ " history_heart_disease history_smoking amount_activity alcohol_misuse \\\n",
+ "4 False False NaN NaN \n",
+ "6 False NaN NaN NaN \n",
+ "33 False NaN NaN NaN \n",
+ "73 False NaN NaN NaN \n",
+ "93 False True NaN NaN \n",
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+ "\n",
+ " fruits vegetables health_gen health_ment health_phys walking_diff \\\n",
+ "4 True NaN 2.0 0.0 0.0 True \n",
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+ "33 True True 3.0 15.0 3.0 False \n",
+ "73 True True 5.0 5.0 20.0 True \n",
+ "93 NaN True 3.0 0.0 0.0 False \n",
+ "... ... ... ... ... ... ... \n",
+ "4958 False True 2.0 20.0 6.0 True \n",
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+ "4998 True True 1.0 0.0 0.0 False \n",
+ "5053 True True 3.0 0.0 0.0 False \n",
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+ "\n",
+ " high_bp dissease \n",
+ "4 normal False \n",
+ "6 normal False \n",
+ "33 normal False \n",
+ "73 high False \n",
+ "93 high False \n",
+ "... ... ... \n",
+ "4958 normal False \n",
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+ "\n",
+ "[222 rows x 18 columns]"
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+ " width: 32px;\n",
+ " }\n",
+ "\n",
+ " .colab-df-convert:hover {\n",
+ " background-color: #E2EBFA;\n",
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+ " background-color: #3B4455;\n",
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+ " background-color: #434B5C;\n",
+ " box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
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+ " </style>\n",
+ "\n",
+ " <script>\n",
+ " const buttonEl =\n",
+ " document.querySelector('#df-8b4d197c-7e62-4bcf-843f-78dced43efd5 button.colab-df-convert');\n",
+ " buttonEl.style.display =\n",
+ " google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+ "\n",
+ " async function convertToInteractive(key) {\n",
+ " const element = document.querySelector('#df-8b4d197c-7e62-4bcf-843f-78dced43efd5');\n",
+ " const dataTable =\n",
+ " await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+ " [key], {});\n",
+ " if (!dataTable) return;\n",
+ "\n",
+ " const docLinkHtml = 'Like what you see? Visit the ' +\n",
+ " '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+ " + ' to learn more about interactive tables.';\n",
+ " element.innerHTML = '';\n",
+ " dataTable['output_type'] = 'display_data';\n",
+ " await google.colab.output.renderOutput(dataTable, element);\n",
+ " const docLink = document.createElement('div');\n",
+ " docLink.innerHTML = docLinkHtml;\n",
+ " element.appendChild(docLink);\n",
+ " }\n",
+ " </script>\n",
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+ "\n",
+ "\n",
+ "<div id=\"df-2c3d3a50-e617-4c62-8a60-797b46119afc\">\n",
+ " <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-2c3d3a50-e617-4c62-8a60-797b46119afc')\"\n",
+ " title=\"Suggest charts\"\n",
+ " style=\"display:none;\">\n",
+ "\n",
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+ " --disabled-bg-color: #DDD;\n",
+ " }\n",
+ "\n",
+ " [theme=dark] .colab-df-quickchart {\n",
+ " --bg-color: #3B4455;\n",
+ " --fill-color: #D2E3FC;\n",
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+ " --disabled-bg-color: #3B4455;\n",
+ " --disabled-fill-color: #666;\n",
+ " }\n",
+ "\n",
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+ " border: none;\n",
+ " border-radius: 50%;\n",
+ " cursor: pointer;\n",
+ " display: none;\n",
+ " fill: var(--fill-color);\n",
+ " height: 32px;\n",
+ " padding: 0;\n",
+ " width: 32px;\n",
+ " }\n",
+ "\n",
+ " .colab-df-quickchart:hover {\n",
+ " background-color: var(--hover-bg-color);\n",
+ " box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+ " fill: var(--button-hover-fill-color);\n",
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+ "\n",
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+ " border: 2px solid var(--fill-color);\n",
+ " border-color: transparent;\n",
+ " border-bottom-color: var(--fill-color);\n",
+ " animation:\n",
+ " spin 1s steps(1) infinite;\n",
+ " }\n",
+ "\n",
+ " @keyframes spin {\n",
+ " 0% {\n",
+ " border-color: transparent;\n",
+ " border-bottom-color: var(--fill-color);\n",
+ " border-left-color: var(--fill-color);\n",
+ " }\n",
+ " 20% {\n",
+ " border-color: transparent;\n",
+ " border-left-color: var(--fill-color);\n",
+ " border-top-color: var(--fill-color);\n",
+ " }\n",
+ " 30% {\n",
+ " border-color: transparent;\n",
+ " border-left-color: var(--fill-color);\n",
+ " border-top-color: var(--fill-color);\n",
+ " border-right-color: var(--fill-color);\n",
+ " }\n",
+ " 40% {\n",
+ " border-color: transparent;\n",
+ " border-right-color: var(--fill-color);\n",
+ " border-top-color: var(--fill-color);\n",
+ " }\n",
+ " 60% {\n",
+ " border-color: transparent;\n",
+ " border-right-color: var(--fill-color);\n",
+ " }\n",
+ " 80% {\n",
+ " border-color: transparent;\n",
+ " border-right-color: var(--fill-color);\n",
+ " border-bottom-color: var(--fill-color);\n",
+ " }\n",
+ " 90% {\n",
+ " border-color: transparent;\n",
+ " border-bottom-color: var(--fill-color);\n",
+ " }\n",
+ " }\n",
+ "</style>\n",
+ "\n",
+ " <script>\n",
+ " async function quickchart(key) {\n",
+ " const quickchartButtonEl =\n",
+ " document.querySelector('#' + key + ' button');\n",
+ " quickchartButtonEl.disabled = true; // To prevent multiple clicks.\n",
+ " quickchartButtonEl.classList.add('colab-df-spinner');\n",
+ " try {\n",
+ " const charts = await google.colab.kernel.invokeFunction(\n",
+ " 'suggestCharts', [key], {});\n",
+ " } catch (error) {\n",
+ " console.error('Error during call to suggestCharts:', error);\n",
+ " }\n",
+ " quickchartButtonEl.classList.remove('colab-df-spinner');\n",
+ " quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
+ " }\n",
+ " (() => {\n",
+ " let quickchartButtonEl =\n",
+ " document.querySelector('#df-2c3d3a50-e617-4c62-8a60-797b46119afc button');\n",
+ " quickchartButtonEl.style.display =\n",
+ " google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+ " })();\n",
+ " </script>\n",
+ "</div>\n",
+ " </div>\n",
+ " </div>\n"
+ ]
+ },
+ "metadata": {},
+ "execution_count": 118
+ }
+ ],
+ "source": [
+ "# Extracting samples with 3 or more missing values\n",
+ "patient_df.loc[patient_df.isnull().sum(axis=1)>=3, :]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "apIJCXH108we",
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 697
+ },
+ "outputId": "8d8d1b5a-767f-4bc5-c475-0e4729d870e6"
+ },
+ "outputs": [
+ {
+ "output_type": "execute_result",
+ "data": {
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+ "427 65 female 25 NaN NaN False \n",
+ "920 73 female 32 normal notchecked False \n",
+ "1055 49 male 37 NaN checked False \n",
+ "1153 68 female 84 high NaN False \n",
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+ "4518 53 male 57 normal checked False \n",
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+ "\n",
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+ " <td>female</td>\n",
+ " <td>27</td>\n",
+ " <td>NaN</td>\n",
+ " <td>checked</td>\n",
+ " <td>False</td>\n",
+ " <td>False</td>\n",
+ " <td>False</td>\n",
+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " <td>True</td>\n",
+ " <td>2.0</td>\n",
+ " <td>3.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>False</td>\n",
+ " <td>normal</td>\n",
+ " <td>False</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>3320</th>\n",
+ " <td>51</td>\n",
+ " <td>female</td>\n",
+ " <td>26</td>\n",
+ " <td>NaN</td>\n",
+ " <td>checked</td>\n",
+ " <td>False</td>\n",
+ " <td>True</td>\n",
+ " <td>NaN</td>\n",
+ " <td>notactive</td>\n",
+ " <td>NaN</td>\n",
+ " <td>False</td>\n",
+ " <td>True</td>\n",
+ " <td>4.0</td>\n",
+ " <td>NaN</td>\n",
+ " <td>20.0</td>\n",
+ " <td>True</td>\n",
+ " <td>high</td>\n",
+ " <td>False</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>3450</th>\n",
+ " <td>58</td>\n",
+ " <td>female</td>\n",
+ " <td>22</td>\n",
+ " <td>NaN</td>\n",
+ " <td>checked</td>\n",
+ " <td>False</td>\n",
+ " <td>False</td>\n",
+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " <td>True</td>\n",
+ " <td>True</td>\n",
+ " <td>2.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>False</td>\n",
+ " <td>high</td>\n",
+ " <td>False</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>3682</th>\n",
+ " <td>46</td>\n",
+ " <td>female</td>\n",
+ " <td>27</td>\n",
+ " <td>high</td>\n",
+ " <td>checked</td>\n",
+ " <td>False</td>\n",
+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " <td>True</td>\n",
+ " <td>True</td>\n",
+ " <td>3.0</td>\n",
+ " <td>6.0</td>\n",
+ " <td>22.0</td>\n",
+ " <td>True</td>\n",
+ " <td>normal</td>\n",
+ " <td>False</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>4012</th>\n",
+ " <td>72</td>\n",
+ " <td>female</td>\n",
+ " <td>31</td>\n",
+ " <td>NaN</td>\n",
+ " <td>checked</td>\n",
+ " <td>False</td>\n",
+ " <td>False</td>\n",
+ " <td>NaN</td>\n",
+ " <td>notactive</td>\n",
+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " <td>True</td>\n",
+ " <td>1.0</td>\n",
+ " <td>30.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>False</td>\n",
+ " <td>normal</td>\n",
+ " <td>False</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>4174</th>\n",
+ " <td>60</td>\n",
+ " <td>male</td>\n",
+ " <td>26</td>\n",
+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " <td>False</td>\n",
+ " <td>False</td>\n",
+ " <td>False</td>\n",
+ " <td>NaN</td>\n",
+ " <td>3.0</td>\n",
+ " <td>False</td>\n",
+ " <td>NaN</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>False</td>\n",
+ " <td>normal</td>\n",
+ " <td>False</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>4518</th>\n",
+ " <td>53</td>\n",
+ " <td>male</td>\n",
+ " <td>57</td>\n",
+ " <td>normal</td>\n",
+ " <td>checked</td>\n",
+ " <td>False</td>\n",
+ " <td>False</td>\n",
+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " <td>True</td>\n",
+ " <td>NaN</td>\n",
+ " <td>2.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>12.0</td>\n",
+ " <td>False</td>\n",
+ " <td>high</td>\n",
+ " <td>False</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>4849</th>\n",
+ " <td>72</td>\n",
+ " <td>female</td>\n",
+ " <td>23</td>\n",
+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " <td>False</td>\n",
+ " <td>False</td>\n",
+ " <td>NaN</td>\n",
+ " <td>active</td>\n",
+ " <td>NaN</td>\n",
+ " <td>True</td>\n",
+ " <td>True</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>False</td>\n",
+ " <td>high</td>\n",
+ " <td>False</td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ "</table>\n",
+ "</div>\n",
+ " <div class=\"colab-df-buttons\">\n",
+ "\n",
+ " <div class=\"colab-df-container\">\n",
+ " <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-73d510df-ee79-42e0-aff3-25cea7d9d9d0')\"\n",
+ " title=\"Convert this dataframe to an interactive table.\"\n",
+ " style=\"display:none;\">\n",
+ "\n",
+ " <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
+ " <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
+ " </svg>\n",
+ " </button>\n",
+ "\n",
+ " <style>\n",
+ " .colab-df-container {\n",
+ " display:flex;\n",
+ " gap: 12px;\n",
+ " }\n",
+ "\n",
+ " .colab-df-convert {\n",
+ " background-color: #E8F0FE;\n",
+ " border: none;\n",
+ " border-radius: 50%;\n",
+ " cursor: pointer;\n",
+ " display: none;\n",
+ " fill: #1967D2;\n",
+ " height: 32px;\n",
+ " padding: 0 0 0 0;\n",
+ " width: 32px;\n",
+ " }\n",
+ "\n",
+ " .colab-df-convert:hover {\n",
+ " background-color: #E2EBFA;\n",
+ " box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+ " fill: #174EA6;\n",
+ " }\n",
+ "\n",
+ " .colab-df-buttons div {\n",
+ " margin-bottom: 4px;\n",
+ " }\n",
+ "\n",
+ " [theme=dark] .colab-df-convert {\n",
+ " background-color: #3B4455;\n",
+ " fill: #D2E3FC;\n",
+ " }\n",
+ "\n",
+ " [theme=dark] .colab-df-convert:hover {\n",
+ " background-color: #434B5C;\n",
+ " box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+ " filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+ " fill: #FFFFFF;\n",
+ " }\n",
+ " </style>\n",
+ "\n",
+ " <script>\n",
+ " const buttonEl =\n",
+ " document.querySelector('#df-73d510df-ee79-42e0-aff3-25cea7d9d9d0 button.colab-df-convert');\n",
+ " buttonEl.style.display =\n",
+ " google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+ "\n",
+ " async function convertToInteractive(key) {\n",
+ " const element = document.querySelector('#df-73d510df-ee79-42e0-aff3-25cea7d9d9d0');\n",
+ " const dataTable =\n",
+ " await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+ " [key], {});\n",
+ " if (!dataTable) return;\n",
+ "\n",
+ " const docLinkHtml = 'Like what you see? Visit the ' +\n",
+ " '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+ " + ' to learn more about interactive tables.';\n",
+ " element.innerHTML = '';\n",
+ " dataTable['output_type'] = 'display_data';\n",
+ " await google.colab.output.renderOutput(dataTable, element);\n",
+ " const docLink = document.createElement('div');\n",
+ " docLink.innerHTML = docLinkHtml;\n",
+ " element.appendChild(docLink);\n",
+ " }\n",
+ " </script>\n",
+ " </div>\n",
+ "\n",
+ "\n",
+ "<div id=\"df-1640c3dc-dbdf-4d01-b195-ff1fa06422c2\">\n",
+ " <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-1640c3dc-dbdf-4d01-b195-ff1fa06422c2')\"\n",
+ " title=\"Suggest charts\"\n",
+ " style=\"display:none;\">\n",
+ "\n",
+ "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+ " width=\"24px\">\n",
+ " <g>\n",
+ " <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
+ " </g>\n",
+ "</svg>\n",
+ " </button>\n",
+ "\n",
+ "<style>\n",
+ " .colab-df-quickchart {\n",
+ " --bg-color: #E8F0FE;\n",
+ " --fill-color: #1967D2;\n",
+ " --hover-bg-color: #E2EBFA;\n",
+ " --hover-fill-color: #174EA6;\n",
+ " --disabled-fill-color: #AAA;\n",
+ " --disabled-bg-color: #DDD;\n",
+ " }\n",
+ "\n",
+ " [theme=dark] .colab-df-quickchart {\n",
+ " --bg-color: #3B4455;\n",
+ " --fill-color: #D2E3FC;\n",
+ " --hover-bg-color: #434B5C;\n",
+ " --hover-fill-color: #FFFFFF;\n",
+ " --disabled-bg-color: #3B4455;\n",
+ " --disabled-fill-color: #666;\n",
+ " }\n",
+ "\n",
+ " .colab-df-quickchart {\n",
+ " background-color: var(--bg-color);\n",
+ " border: none;\n",
+ " border-radius: 50%;\n",
+ " cursor: pointer;\n",
+ " display: none;\n",
+ " fill: var(--fill-color);\n",
+ " height: 32px;\n",
+ " padding: 0;\n",
+ " width: 32px;\n",
+ " }\n",
+ "\n",
+ " .colab-df-quickchart:hover {\n",
+ " background-color: var(--hover-bg-color);\n",
+ " box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+ " fill: var(--button-hover-fill-color);\n",
+ " }\n",
+ "\n",
+ " .colab-df-quickchart-complete:disabled,\n",
+ " .colab-df-quickchart-complete:disabled:hover {\n",
+ " background-color: var(--disabled-bg-color);\n",
+ " fill: var(--disabled-fill-color);\n",
+ " box-shadow: none;\n",
+ " }\n",
+ "\n",
+ " .colab-df-spinner {\n",
+ " border: 2px solid var(--fill-color);\n",
+ " border-color: transparent;\n",
+ " border-bottom-color: var(--fill-color);\n",
+ " animation:\n",
+ " spin 1s steps(1) infinite;\n",
+ " }\n",
+ "\n",
+ " @keyframes spin {\n",
+ " 0% {\n",
+ " border-color: transparent;\n",
+ " border-bottom-color: var(--fill-color);\n",
+ " border-left-color: var(--fill-color);\n",
+ " }\n",
+ " 20% {\n",
+ " border-color: transparent;\n",
+ " border-left-color: var(--fill-color);\n",
+ " border-top-color: var(--fill-color);\n",
+ " }\n",
+ " 30% {\n",
+ " border-color: transparent;\n",
+ " border-left-color: var(--fill-color);\n",
+ " border-top-color: var(--fill-color);\n",
+ " border-right-color: var(--fill-color);\n",
+ " }\n",
+ " 40% {\n",
+ " border-color: transparent;\n",
+ " border-right-color: var(--fill-color);\n",
+ " border-top-color: var(--fill-color);\n",
+ " }\n",
+ " 60% {\n",
+ " border-color: transparent;\n",
+ " border-right-color: var(--fill-color);\n",
+ " }\n",
+ " 80% {\n",
+ " border-color: transparent;\n",
+ " border-right-color: var(--fill-color);\n",
+ " border-bottom-color: var(--fill-color);\n",
+ " }\n",
+ " 90% {\n",
+ " border-color: transparent;\n",
+ " border-bottom-color: var(--fill-color);\n",
+ " }\n",
+ " }\n",
+ "</style>\n",
+ "\n",
+ " <script>\n",
+ " async function quickchart(key) {\n",
+ " const quickchartButtonEl =\n",
+ " document.querySelector('#' + key + ' button');\n",
+ " quickchartButtonEl.disabled = true; // To prevent multiple clicks.\n",
+ " quickchartButtonEl.classList.add('colab-df-spinner');\n",
+ " try {\n",
+ " const charts = await google.colab.kernel.invokeFunction(\n",
+ " 'suggestCharts', [key], {});\n",
+ " } catch (error) {\n",
+ " console.error('Error during call to suggestCharts:', error);\n",
+ " }\n",
+ " quickchartButtonEl.classList.remove('colab-df-spinner');\n",
+ " quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
+ " }\n",
+ " (() => {\n",
+ " let quickchartButtonEl =\n",
+ " document.querySelector('#df-1640c3dc-dbdf-4d01-b195-ff1fa06422c2 button');\n",
+ " quickchartButtonEl.style.display =\n",
+ " google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+ " })();\n",
+ " </script>\n",
+ "</div>\n",
+ " </div>\n",
+ " </div>\n"
+ ]
+ },
+ "metadata": {},
+ "execution_count": 119
+ }
+ ],
+ "source": [
+ "# Extracting samples with 4 or more missing values\n",
+ "patient_df.loc[patient_df.isnull().sum(axis=1)>=4, :]"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "unb91sm61Se-"
+ },
+ "source": [
+ "# **PLots**"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "WN4sZ4RY1Igq",
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 564
+ },
+ "outputId": "c52d5a85-9236-4d58-9dbf-a14dc0d577a0"
+ },
+ "outputs": [
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ "<Figure size 1000x600 with 1 Axes>"
+ ],
+ "image/png": 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\n"
+ },
+ "metadata": {}
+ }
+ ],
+ "source": [
+ "# Plotting the distribution of age\n",
+ "plt.figure(figsize=(10, 6))\n",
+ "\n",
+ "# Plotting the histogram with specified bins and color\n",
+ "plt.hist(patient_df['age'], bins=20, color=\"seagreen\",alpha = 0.7, edgecolor=\"black\")\n",
+ "\n",
+ "plt.xlabel('Age')\n",
+ "plt.ylabel('Frequency')\n",
+ "plt.title('Distribution of Age')\n",
+ "plt.grid(axis='y', linestyle='--')\n",
+ "\n",
+ "plt.show()\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "sh4lBQlt1Xk0",
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 564
+ },
+ "outputId": "b3a00abe-3fac-4e60-8c45-6a226da6f01a"
+ },
+ "outputs": [
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ "<Figure size 1000x600 with 1 Axes>"
+ ],
+ "image/png": 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\n"
+ },
+ "metadata": {}
+ }
+ ],
+ "source": [
+ "# Plotting the distribution of BMI\n",
+ "plt.figure(figsize=(10, 6))\n",
+ "\n",
+ "# Plotting the histogram with specified bins and color\n",
+ "plt.hist(patient_df['bmi'], bins=20, color=\"darkorange\", alpha = 0.8,edgecolor=\"black\")\n",
+ "\n",
+ "plt.xlabel('BMI')\n",
+ "plt.ylabel('Frequency')\n",
+ "plt.title('Distribution of BMI')\n",
+ "plt.grid(axis='y', linestyle='--')\n",
+ "\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "oKkIHBE81any",
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 564
+ },
+ "outputId": "88cf41b5-2a63-445d-837e-eb700bf4a0c0"
+ },
+ "outputs": [
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ "<Figure size 1000x600 with 1 Axes>"
+ ],
+ "image/png": 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\n"
+ },
+ "metadata": {}
+ }
+ ],
+ "source": [
+ "# Plotting the distribution of drinking alcohol\n",
+ "plt.figure(figsize=(10, 6))\n",
+ "\n",
+ "# Plotting the histogram with specified bins and color\n",
+ "plt.hist(patient_df['alcohol_misuse'], bins=20, color=\"steelblue\",alpha = 0.9, edgecolor=\"black\")\n",
+ "\n",
+ "plt.xlabel('Amount of Drinking Alcohol')\n",
+ "plt.ylabel('Frequency')\n",
+ "plt.title('Distribution of Drinking Alcohol')\n",
+ "plt.grid(axis='y', linestyle='--')\n",
+ "\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "o52nuW3u1c-U",
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 564
+ },
+ "outputId": "f827b691-8f61-47ca-89f7-1fdaee215658"
+ },
+ "outputs": [
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ "<Figure size 1000x600 with 1 Axes>"
+ ],
+ "image/png": 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\n"
+ },
+ "metadata": {}
+ }
+ ],
+ "source": [
+ "# Plotting the distribution of having mental health issues\n",
+ "plt.figure(figsize=(10, 6))\n",
+ "\n",
+ "# Plotting the histogram with specified bins and color\n",
+ "plt.hist(patient_df['health_ment'], bins=20, color=\"brown\",alpha = 0.7, edgecolor=\"black\")\n",
+ "\n",
+ "plt.xlabel('Mental Health')\n",
+ "plt.ylabel('Frequency')\n",
+ "plt.title('Distribution of Mental Health Issues')\n",
+ "plt.grid(axis='y', linestyle='--')\n",
+ "\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "Z_tcS8J-1eoi",
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 564
+ },
+ "outputId": "15fb9b49-a6e3-4d2b-cbaa-8274c8686e06"
+ },
+ "outputs": [
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ "<Figure size 1000x600 with 1 Axes>"
+ ],
+ "image/png": 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\n"
+ },
+ "metadata": {}
+ }
+ ],
+ "source": [
+ "# Plotting the distribution of having general health\n",
+ "plt.figure(figsize=(10, 6))\n",
+ "\n",
+ "# Plotting the histogram with specified bins and color\n",
+ "plt.hist(patient_df['health_gen'], bins=10, color=\"red\", alpha=0.7, edgecolor=\"black\")\n",
+ "\n",
+ "plt.xlabel('General Health')\n",
+ "plt.ylabel('Frequency')\n",
+ "plt.title('Distribution of General Health')\n",
+ "plt.grid(axis='y', linestyle='--')\n",
+ "\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "fiZSQrxF1hdT",
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 564
+ },
+ "outputId": "75e2553b-cf83-4c19-ab61-e297475ed5ed"
+ },
+ "outputs": [
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ "<Figure size 1000x600 with 1 Axes>"
+ ],
+ "image/png": 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\n"
+ },
+ "metadata": {}
+ }
+ ],
+ "source": [
+ "# Plotting the distribution of having healthy body\n",
+ "plt.figure(figsize=(10, 6))\n",
+ "\n",
+ "# Plotting the histogram with specified bins, color, transparency, and edgecolor\n",
+ "plt.hist(patient_df['health_phys'], bins=15, color=\"purple\", alpha=0.7, edgecolor=\"black\")\n",
+ "\n",
+ "plt.xlabel('Physical Health')\n",
+ "plt.ylabel('Frequency')\n",
+ "plt.title('Distribution of Physical Health')\n",
+ "plt.grid(axis='y', linestyle='--')\n",
+ "\n",
+ "plt.show()\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "8rLxvwH81w0S"
+ },
+ "source": [
+ "# **Correlation**"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "WK1bl-kx1xUR"
+ },
+ "source": [
+ "* We want to see if there is any correlation between the features\n",
+ "Not all the feature are numeric so we can only use the numeric ones\n",
+ "* The code is generating a heatmap and the results will include numbers: these numbers shows the correlation coefficient between the corresponding pair of features\n",
+ "\n",
+ "* The colors are showing the the magnitude of the correlation coefficient. Darker colors represent stronger correlations, while lighter colors represent weaker correlations.\n",
+ "\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "3PMTjka81kdf",
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 544
+ },
+ "outputId": "e1aff59a-f20f-4660-ed2f-5f88f0922aba"
+ },
+ "outputs": [
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ "<Figure size 640x480 with 2 Axes>"
+ ],
+ "image/png": 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\n"
+ },
+ "metadata": {}
+ }
+ ],
+ "source": [
+ "correlation_matrix = patient_df.corr(numeric_only=True)\n",
+ "\n",
+ "sns.heatmap(correlation_matrix, annot=True, cmap='coolwarm', fmt=\".2f\", linewidths=0.5)\n",
+ "plt.title('Correlation Matrix')\n",
+ "\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "xK9b7VbV3ruI"
+ },
+ "source": [
+ "# **Train & Test Split**"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "go51N_hp3oWe"
+ },
+ "outputs": [],
+ "source": [
+ "X = patient_df.drop(['dissease'], axis=1)\n",
+ "y = patient_df['dissease']\n",
+ "\n",
+ "X_train, X_test, y_train, y_test = train_test_split(X,y,random_state=15)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "F7rIzOsxVMoq",
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+ "height": 444
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+ " age gender bmi high_chol chol_check history_stroke \\\n",
+ "1837 20 female 36 normal checked False \n",
+ "3369 76 female 24 NaN checked False \n",
+ "3896 70 male 23 high checked False \n",
+ "3733 55 female 26 normal checked False \n",
+ "4812 51 female 37 normal checked False \n",
+ "... ... ... ... ... ... ... \n",
+ "3271 62 female 27 high notchecked False \n",
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+ "2693 59 female 24 NaN checked False \n",
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+ "\n",
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+ " height: 32px;\n",
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+ " width: 32px;\n",
+ " }\n",
+ "\n",
+ " .colab-df-convert:hover {\n",
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+ "\n",
+ " const docLinkHtml = 'Like what you see? Visit the ' +\n",
+ " '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+ " + ' to learn more about interactive tables.';\n",
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+ " cursor: pointer;\n",
+ " display: none;\n",
+ " fill: var(--fill-color);\n",
+ " height: 32px;\n",
+ " padding: 0;\n",
+ " width: 32px;\n",
+ " }\n",
+ "\n",
+ " .colab-df-quickchart:hover {\n",
+ " background-color: var(--hover-bg-color);\n",
+ " box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+ " fill: var(--button-hover-fill-color);\n",
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+ "\n",
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+ " spin 1s steps(1) infinite;\n",
+ " }\n",
+ "\n",
+ " @keyframes spin {\n",
+ " 0% {\n",
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+ " border-bottom-color: var(--fill-color);\n",
+ " border-left-color: var(--fill-color);\n",
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+ " border-right-color: var(--fill-color);\n",
+ " border-bottom-color: var(--fill-color);\n",
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+ " quickchartButtonEl.disabled = true; // To prevent multiple clicks.\n",
+ " quickchartButtonEl.classList.add('colab-df-spinner');\n",
+ " try {\n",
+ " const charts = await google.colab.kernel.invokeFunction(\n",
+ " 'suggestCharts', [key], {});\n",
+ " } catch (error) {\n",
+ " console.error('Error during call to suggestCharts:', error);\n",
+ " }\n",
+ " quickchartButtonEl.classList.remove('colab-df-spinner');\n",
+ " quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
+ " }\n",
+ " (() => {\n",
+ " let quickchartButtonEl =\n",
+ " document.querySelector('#df-e8889059-095b-4588-ba69-869891203512 button');\n",
+ " quickchartButtonEl.style.display =\n",
+ " google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+ " })();\n",
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+ " </div>\n"
+ ]
+ },
+ "metadata": {},
+ "execution_count": 128
+ }
+ ],
+ "source": [
+ "X_train"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "ntBDPXy22s7q"
+ },
+ "source": [
+ "### **Dealing with Missing Values**"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "o0C2NsVaVMoq"
+ },
+ "outputs": [],
+ "source": [
+ "# Dealing with missing data in patient_df:\n",
+ "\n",
+ "# Identify numeric and non-numeric columns\n",
+ "numeric_columns_df = patient_df.select_dtypes(include='number').columns\n",
+ "non_numeric_columns_df = patient_df.columns.difference(numeric_columns_df)\n",
+ "\n",
+ "# Convert numeric columns to numeric type\n",
+ "patient_df[numeric_columns_df] = patient_df[numeric_columns_df].apply(pd.to_numeric, errors='coerce')\n",
+ "\n",
+ "# Handle non-numeric columns (drop them for simplicity)\n",
+ "patient_df = patient_df.drop(columns=non_numeric_columns_df)\n",
+ "\n",
+ "# Fill missing values for numeric columns\n",
+ "patient_df.loc[:, numeric_columns_df] = patient_df[numeric_columns_df].fillna(patient_df[numeric_columns_df].mean())\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "4KwRouM-ARSY",
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 983
+ },
+ "outputId": "10feb9a6-25d7-4c61-eb08-d794e792e8ff"
+ },
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stderr",
+ "text": [
+ "/usr/local/lib/python3.10/dist-packages/sklearn/preprocessing/_encoders.py:868: FutureWarning: `sparse` was renamed to `sparse_output` in version 1.2 and will be removed in 1.4. `sparse_output` is ignored unless you leave `sparse` to its default value.\n",
+ " warnings.warn(\n"
+ ]
+ },
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ "<Figure size 640x480 with 1 Axes>"
+ ],
+ "image/png": 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\n"
+ },
+ "metadata": {}
+ },
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ "<Figure size 640x480 with 1 Axes>"
+ ],
+ "image/png": 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\n"
+ },
+ "metadata": {}
+ }
+ ],
+ "source": [
+ "# Dealing with missing data in the X_train and X_test:\n",
+ "\n",
+ "# Imputation\n",
+ "numeric_columns = X_train.select_dtypes(include=['number']).columns\n",
+ "categorical_columns = X_train.columns.difference(numeric_columns)\n",
+ "\n",
+ "imputer_numeric = SimpleImputer(strategy='mean')\n",
+ "imputer_categorical = SimpleImputer(strategy='most_frequent')\n",
+ "\n",
+ "X_train_numeric = pd.DataFrame(imputer_numeric.fit_transform(X_train[numeric_columns]), columns=numeric_columns)\n",
+ "X_train_categorical = pd.DataFrame(imputer_categorical.fit_transform(X_train[categorical_columns]), columns=categorical_columns)\n",
+ "\n",
+ "X_test_numeric = pd.DataFrame(imputer_numeric.transform(X_test[numeric_columns]), columns=numeric_columns)\n",
+ "X_test_categorical = pd.DataFrame(imputer_categorical.transform(X_test[categorical_columns]), columns=categorical_columns)\n",
+ "\n",
+ "# Concatenating imputed data\n",
+ "X_train_imputed = pd.concat([X_train_numeric, X_train_categorical], axis=1)\n",
+ "X_test_imputed = pd.concat([X_test_numeric, X_test_categorical], axis=1)\n",
+ "\n",
+ "# One-Hot Encoding for categorical variables\n",
+ "encoder = OneHotEncoder(sparse=False)\n",
+ "X_train_encoded = pd.DataFrame(encoder.fit_transform(X_train_imputed[categorical_columns]), columns=encoder.get_feature_names_out())\n",
+ "X_test_encoded = pd.DataFrame(encoder.transform(X_test_imputed[categorical_columns]), columns=encoder.get_feature_names_out())\n",
+ "\n",
+ "X_train_prepared = pd.concat([X_train_imputed.drop(categorical_columns, axis=1), X_train_encoded], axis=1)\n",
+ "X_test_prepared = pd.concat([X_test_imputed.drop(categorical_columns, axis=1), X_test_encoded], axis=1)\n",
+ "\n",
+ "# Standardise data\n",
+ "scaler = StandardScaler()\n",
+ "X_train_scaled = scaler.fit_transform(X_train_prepared)\n",
+ "X_test_scaled = scaler.transform(X_test_prepared)\n",
+ "\n",
+ "\n",
+ "# PCA\n",
+ "pca = PCA(n_components=2)\n",
+ "X_train_pca = pca.fit_transform(X_train_scaled)\n",
+ "X_test_pca = pca.transform(X_test_scaled)\n",
+ "\n",
+ "# Visualising PCA results\n",
+ "plt.scatter(X_train_pca[:, 0], X_train_pca[:, 1], c=y_train, cmap='viridis')\n",
+ "plt.title('PCA Analysis - Training Data')\n",
+ "plt.xlabel('Principal Component 1')\n",
+ "plt.ylabel('Principal Component 2')\n",
+ "plt.show()\n",
+ "\n",
+ "plt.scatter(X_test_pca[:, 0], X_test_pca[:, 1], c=y_test, cmap='plasma')\n",
+ "plt.title('PCA Analysis - Testing Data')\n",
+ "plt.xlabel('Principal Component 1')\n",
+ "plt.ylabel('Principal Component 2')\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "p0ppezG4VMoq",
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 444
+ },
+ "outputId": "52d9a3c1-bffb-4c94-d9c6-cfee3245a7fb"
+ },
+ "outputs": [
+ {
+ "output_type": "execute_result",
+ "data": {
+ "text/plain": [
+ " age bmi alcohol_misuse health_gen health_ment health_phys \\\n",
+ "0 20.0 36.0 0.000000 3.0 0.0 0.0 \n",
+ "1 76.0 24.0 2.000000 4.0 3.0 0.0 \n",
+ "2 70.0 23.0 4.000000 5.0 22.0 23.0 \n",
+ "3 55.0 26.0 3.000000 2.0 0.0 0.0 \n",
+ "4 51.0 37.0 2.000000 1.0 3.0 6.0 \n",
+ "... ... ... ... ... ... ... \n",
+ "3838 62.0 27.0 2.000000 2.0 0.0 0.0 \n",
+ "3839 26.0 22.0 2.391473 2.0 2.0 0.0 \n",
+ "3840 72.0 30.0 4.000000 4.0 5.0 7.0 \n",
+ "3841 59.0 24.0 0.000000 1.0 0.0 0.0 \n",
+ "3842 53.0 31.0 1.000000 1.0 2.0 2.0 \n",
+ "\n",
+ " amount_activity_active amount_activity_notactive chol_check_checked \\\n",
+ "0 1.0 0.0 1.0 \n",
+ "1 0.0 1.0 1.0 \n",
+ "2 1.0 0.0 1.0 \n",
+ "3 1.0 0.0 1.0 \n",
+ "4 1.0 0.0 1.0 \n",
+ "... ... ... ... \n",
+ "3838 1.0 0.0 0.0 \n",
+ "3839 1.0 0.0 1.0 \n",
+ "3840 1.0 0.0 1.0 \n",
+ "3841 0.0 1.0 1.0 \n",
+ "3842 1.0 0.0 1.0 \n",
+ "\n",
+ " chol_check_notchecked ... history_heart_disease_False \\\n",
+ "0 0.0 ... 1.0 \n",
+ "1 0.0 ... 1.0 \n",
+ "2 0.0 ... 1.0 \n",
+ "3 0.0 ... 1.0 \n",
+ "4 0.0 ... 1.0 \n",
+ "... ... ... ... \n",
+ "3838 1.0 ... 1.0 \n",
+ "3839 0.0 ... 1.0 \n",
+ "3840 0.0 ... 1.0 \n",
+ "3841 0.0 ... 1.0 \n",
+ "3842 0.0 ... 1.0 \n",
+ "\n",
+ " history_heart_disease_True history_smoking_False history_smoking_True \\\n",
+ "0 0.0 0.0 1.0 \n",
+ "1 0.0 0.0 1.0 \n",
+ "2 0.0 1.0 0.0 \n",
+ "3 0.0 0.0 1.0 \n",
+ "4 0.0 1.0 0.0 \n",
+ "... ... ... ... \n",
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+ " height: 32px;\n",
+ " padding: 0;\n",
+ " width: 32px;\n",
+ " }\n",
+ "\n",
+ " .colab-df-quickchart:hover {\n",
+ " background-color: var(--hover-bg-color);\n",
+ " box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+ " fill: var(--button-hover-fill-color);\n",
+ " }\n",
+ "\n",
+ " .colab-df-quickchart-complete:disabled,\n",
+ " .colab-df-quickchart-complete:disabled:hover {\n",
+ " background-color: var(--disabled-bg-color);\n",
+ " fill: var(--disabled-fill-color);\n",
+ " box-shadow: none;\n",
+ " }\n",
+ "\n",
+ " .colab-df-spinner {\n",
+ " border: 2px solid var(--fill-color);\n",
+ " border-color: transparent;\n",
+ " border-bottom-color: var(--fill-color);\n",
+ " animation:\n",
+ " spin 1s steps(1) infinite;\n",
+ " }\n",
+ "\n",
+ " @keyframes spin {\n",
+ " 0% {\n",
+ " border-color: transparent;\n",
+ " border-bottom-color: var(--fill-color);\n",
+ " border-left-color: var(--fill-color);\n",
+ " }\n",
+ " 20% {\n",
+ " border-color: transparent;\n",
+ " border-left-color: var(--fill-color);\n",
+ " border-top-color: var(--fill-color);\n",
+ " }\n",
+ " 30% {\n",
+ " border-color: transparent;\n",
+ " border-left-color: var(--fill-color);\n",
+ " border-top-color: var(--fill-color);\n",
+ " border-right-color: var(--fill-color);\n",
+ " }\n",
+ " 40% {\n",
+ " border-color: transparent;\n",
+ " border-right-color: var(--fill-color);\n",
+ " border-top-color: var(--fill-color);\n",
+ " }\n",
+ " 60% {\n",
+ " border-color: transparent;\n",
+ " border-right-color: var(--fill-color);\n",
+ " }\n",
+ " 80% {\n",
+ " border-color: transparent;\n",
+ " border-right-color: var(--fill-color);\n",
+ " border-bottom-color: var(--fill-color);\n",
+ " }\n",
+ " 90% {\n",
+ " border-color: transparent;\n",
+ " border-bottom-color: var(--fill-color);\n",
+ " }\n",
+ " }\n",
+ "</style>\n",
+ "\n",
+ " <script>\n",
+ " async function quickchart(key) {\n",
+ " const quickchartButtonEl =\n",
+ " document.querySelector('#' + key + ' button');\n",
+ " quickchartButtonEl.disabled = true; // To prevent multiple clicks.\n",
+ " quickchartButtonEl.classList.add('colab-df-spinner');\n",
+ " try {\n",
+ " const charts = await google.colab.kernel.invokeFunction(\n",
+ " 'suggestCharts', [key], {});\n",
+ " } catch (error) {\n",
+ " console.error('Error during call to suggestCharts:', error);\n",
+ " }\n",
+ " quickchartButtonEl.classList.remove('colab-df-spinner');\n",
+ " quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
+ " }\n",
+ " (() => {\n",
+ " let quickchartButtonEl =\n",
+ " document.querySelector('#df-2cb4a76b-a116-4693-8c65-a3b0f5c2c6f8 button');\n",
+ " quickchartButtonEl.style.display =\n",
+ " google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+ " })();\n",
+ " </script>\n",
+ "</div>\n",
+ " </div>\n",
+ " </div>\n"
+ ]
+ },
+ "metadata": {},
+ "execution_count": 132
+ }
+ ],
+ "source": [
+ "X_train_encoded"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "vRWIhoQ-VMoq",
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "outputId": "e76c7c64-8b7f-4a41-b95a-157394492b98"
+ },
+ "outputs": [
+ {
+ "output_type": "execute_result",
+ "data": {
+ "text/plain": [
+ "Index(['amount_activity', 'chol_check', 'fruits', 'gender', 'high_bp',\n",
+ " 'high_chol', 'history_heart_disease', 'history_smoking',\n",
+ " 'history_stroke', 'vegetables', 'walking_diff'],\n",
+ " dtype='object')"
+ ]
+ },
+ "metadata": {},
+ "execution_count": 133
+ }
+ ],
+ "source": [
+ "categorical_columns"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "EoOfNHFw4JtL"
+ },
+ "source": [
+ "# **Outliers Removal**"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "gU_v1ZWa5Shu"
+ },
+ "source": [
+ "# Outlier Removal on patient_df"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "nYW9mpi74JRp",
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "outputId": "2d27bb9b-a198-45a7-eafd-4d614f3773b9"
+ },
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "\n",
+ "Z-Score Array:\n",
+ " age bmi alcohol_misuse health_gen health_ment health_phys\n",
+ "0 0.785712 1.174175 0.151637 1.355849 0.443223 0.422921\n",
+ "1 0.062962 2.728496 0.536172 0.491345 0.443223 0.422921\n",
+ "2 0.002342 0.271259 0.920707 1.355849 0.443223 0.422921\n",
+ "3 0.669158 1.318719 1.386502 0.491345 2.164643 0.210251\n",
+ "4 0.361375 0.560345 0.000000 0.432252 0.443223 0.422921\n",
+ "... ... ... ... ... ... ...\n",
+ "5119 1.517832 1.572149 0.232898 0.432252 0.469530 0.422921\n",
+ "5120 0.669158 0.451458 0.151637 0.432252 0.443223 0.422921\n",
+ "5121 0.244821 0.560345 0.000000 0.432252 0.443223 0.422921\n",
+ "5122 1.760311 0.017828 0.000000 0.491345 0.443223 0.422921\n",
+ "5123 2.063409 1.029632 0.536172 0.432252 0.182437 0.422921\n",
+ "\n",
+ "[5124 rows x 6 columns]\n",
+ "(5124, 6)\n",
+ "\n",
+ "Outliers:\n",
+ " (array([ 7, 78, 80, 97, 105, 125, 126, 126, 131, 142, 144,\n",
+ " 146, 147, 150, 164, 178, 180, 181, 183, 187, 203, 242,\n",
+ " 260, 260, 264, 267, 270, 277, 277, 294, 295, 299, 303,\n",
+ " 310, 314, 314, 315, 341, 355, 357, 365, 367, 372, 380,\n",
+ " 385, 392, 413, 413, 416, 423, 429, 431, 438, 439, 443,\n",
+ " 452, 452, 475, 477, 486, 490, 499, 500, 507, 514, 524,\n",
+ " 543, 543, 547, 557, 597, 598, 632, 638, 642, 646, 651,\n",
+ " 688, 694, 700, 701, 713, 717, 750, 757, 760, 763, 763,\n",
+ " 764, 765, 774, 775, 798, 805, 806, 816, 817, 824, 826,\n",
+ " 830, 830, 837, 848, 857, 860, 864, 866, 869, 894, 899,\n",
+ " 931, 943, 944, 951, 955, 959, 960, 965, 967, 993, 997,\n",
+ " 998, 1022, 1034, 1035, 1071, 1105, 1125, 1130, 1138, 1144, 1144,\n",
+ " 1153, 1160, 1166, 1167, 1171, 1191, 1191, 1194, 1194, 1195, 1195,\n",
+ " 1213, 1213, 1221, 1229, 1247, 1250, 1250, 1259, 1276, 1286, 1307,\n",
+ " 1308, 1315, 1322, 1330, 1334, 1334, 1339, 1348, 1373, 1373, 1375,\n",
+ " 1376, 1379, 1382, 1394, 1402, 1413, 1424, 1434, 1450, 1450, 1452,\n",
+ " 1452, 1461, 1462, 1464, 1491, 1498, 1506, 1513, 1546, 1555, 1563,\n",
+ " 1564, 1579, 1580, 1595, 1596, 1618, 1618, 1622, 1622, 1626, 1626,\n",
+ " 1627, 1635, 1653, 1675, 1680, 1705, 1706, 1711, 1724, 1724, 1727,\n",
+ " 1732, 1733, 1737, 1746, 1751, 1754, 1756, 1765, 1779, 1779, 1789,\n",
+ " 1789, 1802, 1802, 1804, 1820, 1821, 1825, 1857, 1857, 1857, 1861,\n",
+ " 1861, 1862, 1874, 1887, 1896, 1901, 1901, 1908, 1910, 1912, 1925,\n",
+ " 1926, 1931, 1937, 1937, 1945, 1945, 1949, 1951, 1959, 1971, 1979,\n",
+ " 1989, 1990, 1993, 1999, 2001, 2006, 2013, 2014, 2025, 2026, 2048,\n",
+ " 2052, 2052, 2068, 2075, 2080, 2080, 2089, 2089, 2097, 2102, 2102,\n",
+ " 2105, 2107, 2112, 2113, 2121, 2131, 2137, 2137, 2138, 2152, 2159,\n",
+ " 2164, 2167, 2170, 2172, 2183, 2193, 2199, 2202, 2207, 2208, 2228,\n",
+ " 2244, 2245, 2247, 2248, 2253, 2256, 2264, 2266, 2293, 2294, 2301,\n",
+ " 2314, 2323, 2327, 2327, 2338, 2344, 2344, 2345, 2399, 2401, 2424,\n",
+ " 2429, 2434, 2436, 2471, 2482, 2483, 2501, 2502, 2502, 2505, 2505,\n",
+ " 2509, 2510, 2510, 2511, 2511, 2515, 2535, 2544, 2545, 2545, 2559,\n",
+ " 2566, 2571, 2571, 2577, 2601, 2606, 2609, 2619, 2629, 2633, 2633,\n",
+ " 2633, 2641, 2653, 2675, 2680, 2683, 2686, 2695, 2695, 2697, 2700,\n",
+ " 2706, 2707, 2744, 2750, 2758, 2762, 2772, 2773, 2774, 2775, 2781,\n",
+ " 2786, 2789, 2796, 2798, 2813, 2818, 2825, 2827, 2846, 2855, 2863,\n",
+ " 2884, 2890, 2896, 2908, 2909, 2931, 2935, 2945, 2960, 2962, 2977,\n",
+ " 2987, 2993, 3017, 3036, 3036, 3036, 3041, 3043, 3043, 3048, 3060,\n",
+ " 3060, 3088, 3092, 3096, 3101, 3133, 3133, 3140, 3140, 3156, 3158,\n",
+ " 3169, 3175, 3182, 3190, 3197, 3201, 3213, 3224, 3225, 3244, 3248,\n",
+ " 3251, 3259, 3259, 3274, 3292, 3299, 3306, 3318, 3323, 3329, 3346,\n",
+ " 3353, 3365, 3365, 3368, 3385, 3386, 3419, 3420, 3436, 3468, 3470,\n",
+ " 3497, 3505, 3506, 3525, 3529, 3531, 3544, 3546, 3569, 3576, 3576,\n",
+ " 3577, 3608, 3620, 3624, 3628, 3636, 3637, 3637, 3638, 3638, 3644,\n",
+ " 3647, 3649, 3651, 3653, 3663, 3667, 3673, 3722, 3729, 3729, 3738,\n",
+ " 3738, 3748, 3757, 3759, 3763, 3767, 3792, 3799, 3800, 3801, 3809,\n",
+ " 3813, 3818, 3820, 3825, 3838, 3838, 3847, 3858, 3861, 3862, 3865,\n",
+ " 3883, 3884, 3905, 3908, 3918, 3920, 3920, 3951, 3959, 3973, 3983,\n",
+ " 3994, 3995, 4002, 4005, 4012, 4026, 4040, 4055, 4055, 4060, 4072,\n",
+ " 4072, 4114, 4117, 4138, 4148, 4149, 4165, 4180, 4196, 4208, 4244,\n",
+ " 4262, 4268, 4268, 4297, 4312, 4340, 4347, 4348, 4365, 4386, 4398,\n",
+ " 4398, 4405, 4408, 4415, 4468, 4472, 4473, 4476, 4508, 4514, 4518,\n",
+ " 4521, 4529, 4529, 4545, 4571, 4588, 4602, 4611, 4612, 4638, 4640,\n",
+ " 4661, 4674, 4675, 4675, 4688, 4697, 4707, 4709, 4709, 4713, 4734,\n",
+ " 4748, 4748, 4751, 4751, 4766, 4775, 4775, 4784, 4787, 4792, 4808,\n",
+ " 4813, 4814, 4814, 4820, 4841, 4845, 4860, 4865, 4867, 4868, 4870,\n",
+ " 4885, 4901, 4906, 4931, 4934, 4945, 4955, 4968, 4968, 4973, 4974,\n",
+ " 4975, 4977, 4988, 5001, 5005, 5007, 5007, 5009, 5009, 5030, 5038,\n",
+ " 5042, 5066, 5069, 5080, 5080, 5085, 5102, 5112]), array([1, 5, 5, 4, 2, 2, 4, 5, 4, 1, 2, 5, 2, 2, 4, 4, 5, 4, 5, 4, 1, 4,\n",
+ " 1, 4, 4, 5, 4, 4, 5, 2, 4, 1, 4, 2, 4, 5, 4, 4, 2, 1, 5, 4, 2, 5,\n",
+ " 4, 1, 1, 4, 2, 1, 4, 4, 4, 2, 1, 4, 5, 4, 2, 1, 4, 2, 1, 5, 5, 4,\n",
+ " 2, 5, 4, 2, 5, 4, 4, 4, 5, 4, 2, 4, 4, 1, 5, 2, 5, 1, 5, 1, 4, 5,\n",
+ " 5, 4, 4, 2, 2, 1, 4, 4, 2, 5, 4, 4, 5, 1, 2, 2, 4, 5, 5, 2, 4, 4,\n",
+ " 4, 4, 4, 1, 2, 4, 5, 1, 4, 4, 4, 2, 2, 4, 1, 2, 4, 4, 1, 4, 1, 4,\n",
+ " 1, 4, 1, 2, 5, 4, 5, 1, 4, 4, 5, 1, 5, 2, 4, 4, 4, 5, 2, 4, 5, 2,\n",
+ " 5, 5, 4, 5, 4, 5, 1, 5, 2, 4, 4, 2, 1, 1, 5, 4, 4, 2, 4, 4, 5, 4,\n",
+ " 5, 5, 5, 2, 5, 1, 5, 4, 1, 4, 4, 5, 4, 4, 5, 4, 4, 5, 4, 5, 4, 5,\n",
+ " 4, 1, 1, 4, 5, 1, 5, 5, 2, 4, 4, 5, 5, 2, 1, 2, 4, 1, 5, 1, 5, 4,\n",
+ " 5, 4, 5, 5, 4, 4, 1, 1, 4, 5, 4, 5, 5, 1, 1, 2, 1, 4, 1, 1, 2, 4,\n",
+ " 2, 4, 1, 5, 2, 4, 4, 1, 2, 4, 4, 5, 4, 4, 2, 1, 1, 5, 4, 2, 4, 4,\n",
+ " 2, 4, 4, 1, 4, 5, 4, 5, 4, 4, 5, 5, 5, 4, 1, 2, 1, 2, 4, 5, 5, 4,\n",
+ " 2, 4, 1, 5, 2, 4, 2, 2, 1, 4, 5, 5, 2, 1, 4, 5, 5, 1, 5, 4, 2, 2,\n",
+ " 4, 5, 4, 5, 2, 4, 5, 5, 4, 4, 4, 4, 4, 1, 4, 4, 4, 5, 4, 5, 4, 5,\n",
+ " 5, 4, 5, 1, 4, 4, 5, 5, 2, 4, 1, 4, 4, 5, 2, 4, 4, 4, 5, 4, 1, 4,\n",
+ " 5, 4, 5, 1, 1, 1, 5, 4, 5, 4, 5, 4, 5, 4, 5, 4, 4, 1, 4, 4, 1, 4,\n",
+ " 2, 1, 4, 4, 4, 2, 2, 5, 4, 2, 4, 4, 4, 5, 2, 2, 5, 4, 2, 4, 4, 5,\n",
+ " 4, 5, 4, 1, 4, 5, 5, 4, 5, 1, 4, 5, 1, 4, 4, 5, 4, 5, 4, 5, 4, 5,\n",
+ " 4, 2, 1, 2, 2, 4, 4, 4, 2, 4, 1, 5, 4, 5, 5, 4, 2, 4, 5, 5, 5, 5,\n",
+ " 2, 4, 5, 1, 4, 5, 4, 4, 4, 5, 4, 2, 5, 4, 4, 5, 5, 4, 5, 5, 1, 5,\n",
+ " 4, 4, 4, 4, 4, 2, 4, 5, 4, 5, 4, 1, 4, 4, 4, 2, 5, 4, 1, 4, 5, 2,\n",
+ " 4, 1, 4, 5, 1, 2, 1, 5, 4, 4, 5, 5, 4, 4, 4, 4, 5, 2, 5, 4, 4, 4,\n",
+ " 4, 4, 5, 2, 4, 4, 5, 2, 1, 5, 1, 2, 2, 4, 4, 4, 4, 5, 4, 5, 4, 1,\n",
+ " 4, 4, 2, 4, 4, 4, 4, 5, 4, 4, 2, 4, 4, 5, 4, 1, 4, 4, 5, 4, 4, 1,\n",
+ " 5, 5, 2, 1, 4, 4, 2, 4, 4, 5, 1, 4, 4, 5, 4, 5, 4, 5, 4, 5, 4, 1,\n",
+ " 4, 5, 4, 5, 5, 4, 5, 4, 5, 1, 2, 4, 5, 2, 4, 4, 4, 5, 4, 2, 4, 4,\n",
+ " 4, 4, 5, 4, 4, 2, 4, 1, 2, 4, 4, 5, 4, 4, 4, 2, 4, 5, 4, 5, 5, 2,\n",
+ " 5, 4, 4, 4, 5, 1, 4, 4, 5, 5, 2, 4, 2, 4, 4, 5, 2, 4, 5]))\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Performing outlier detection using Z-scores\n",
+ "p_num = patient_df[['age', 'bmi', 'alcohol_misuse', 'health_gen', 'health_ment', 'health_phys']]\n",
+ "z1 = np.abs(stats.zscore(p_num))\n",
+ "print('\\nZ-Score Array:\\n', z1)\n",
+ "\n",
+ "print(p_num.shape)\n",
+ "\n",
+ "threshold = 3\n",
+ "print('\\nOutliers:\\n', np.where(z1 > threshold))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "5BPwBT9IVMoq",
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 424
+ },
+ "outputId": "c7fc5765-8614-4992-b445-5ee2da21742d"
+ },
+ "outputs": [
+ {
+ "output_type": "execute_result",
+ "data": {
+ "text/plain": [
+ " age bmi alcohol_misuse health_gen health_ment health_phys\n",
+ "0 68 20 2.000000 1.0 0.0 0.0\n",
+ "1 54 47 1.000000 3.0 0.0 0.0\n",
+ "2 55 30 0.000000 1.0 0.0 0.0\n",
+ "3 44 19 6.000000 3.0 20.0 6.0\n",
+ "4 61 32 2.394339 2.0 0.0 0.0\n",
+ "... ... ... ... ... ... ...\n",
+ "5119 30 39 3.000000 2.0 7.0 0.0\n",
+ "5120 44 25 2.000000 2.0 0.0 0.0\n",
+ "5121 51 32 2.394339 2.0 0.0 0.0\n",
+ "5122 26 28 2.394339 3.0 0.0 0.0\n",
+ "5123 21 21 1.000000 2.0 2.0 0.0\n",
+ "\n",
+ "[5124 rows x 6 columns]"
+ ],
+ "text/html": [
+ "\n",
+ " <div id=\"df-03e4189e-e74e-4693-8705-ae3baf7f7402\" class=\"colab-df-container\">\n",
+ " <div>\n",
+ "<style scoped>\n",
+ " .dataframe tbody tr th:only-of-type {\n",
+ " vertical-align: middle;\n",
+ " }\n",
+ "\n",
+ " .dataframe tbody tr th {\n",
+ " vertical-align: top;\n",
+ " }\n",
+ "\n",
+ " .dataframe thead th {\n",
+ " text-align: right;\n",
+ " }\n",
+ "</style>\n",
+ "<table border=\"1\" class=\"dataframe\">\n",
+ " <thead>\n",
+ " <tr style=\"text-align: right;\">\n",
+ " <th></th>\n",
+ " <th>age</th>\n",
+ " <th>bmi</th>\n",
+ " <th>alcohol_misuse</th>\n",
+ " <th>health_gen</th>\n",
+ " <th>health_ment</th>\n",
+ " <th>health_phys</th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " <tr>\n",
+ " <th>0</th>\n",
+ " <td>68</td>\n",
+ " <td>20</td>\n",
+ " <td>2.000000</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>1</th>\n",
+ " <td>54</td>\n",
+ " <td>47</td>\n",
+ " <td>1.000000</td>\n",
+ " <td>3.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>2</th>\n",
+ " <td>55</td>\n",
+ " <td>30</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>3</th>\n",
+ " <td>44</td>\n",
+ " <td>19</td>\n",
+ " <td>6.000000</td>\n",
+ " <td>3.0</td>\n",
+ " <td>20.0</td>\n",
+ " <td>6.0</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>4</th>\n",
+ " <td>61</td>\n",
+ " <td>32</td>\n",
+ " <td>2.394339</td>\n",
+ " <td>2.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>...</th>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>5119</th>\n",
+ " <td>30</td>\n",
+ " <td>39</td>\n",
+ " <td>3.000000</td>\n",
+ " <td>2.0</td>\n",
+ " <td>7.0</td>\n",
+ " <td>0.0</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>5120</th>\n",
+ " <td>44</td>\n",
+ " <td>25</td>\n",
+ " <td>2.000000</td>\n",
+ " <td>2.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>5121</th>\n",
+ " <td>51</td>\n",
+ " <td>32</td>\n",
+ " <td>2.394339</td>\n",
+ " <td>2.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>5122</th>\n",
+ " <td>26</td>\n",
+ " <td>28</td>\n",
+ " <td>2.394339</td>\n",
+ " <td>3.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>5123</th>\n",
+ " <td>21</td>\n",
+ " <td>21</td>\n",
+ " <td>1.000000</td>\n",
+ " <td>2.0</td>\n",
+ " <td>2.0</td>\n",
+ " <td>0.0</td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ "</table>\n",
+ "<p>5124 rows × 6 columns</p>\n",
+ "</div>\n",
+ " <div class=\"colab-df-buttons\">\n",
+ "\n",
+ " <div class=\"colab-df-container\">\n",
+ " <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-03e4189e-e74e-4693-8705-ae3baf7f7402')\"\n",
+ " title=\"Convert this dataframe to an interactive table.\"\n",
+ " style=\"display:none;\">\n",
+ "\n",
+ " <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
+ " <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
+ " </svg>\n",
+ " </button>\n",
+ "\n",
+ " <style>\n",
+ " .colab-df-container {\n",
+ " display:flex;\n",
+ " gap: 12px;\n",
+ " }\n",
+ "\n",
+ " .colab-df-convert {\n",
+ " background-color: #E8F0FE;\n",
+ " border: none;\n",
+ " border-radius: 50%;\n",
+ " cursor: pointer;\n",
+ " display: none;\n",
+ " fill: #1967D2;\n",
+ " height: 32px;\n",
+ " padding: 0 0 0 0;\n",
+ " width: 32px;\n",
+ " }\n",
+ "\n",
+ " .colab-df-convert:hover {\n",
+ " background-color: #E2EBFA;\n",
+ " box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+ " fill: #174EA6;\n",
+ " }\n",
+ "\n",
+ " .colab-df-buttons div {\n",
+ " margin-bottom: 4px;\n",
+ " }\n",
+ "\n",
+ " [theme=dark] .colab-df-convert {\n",
+ " background-color: #3B4455;\n",
+ " fill: #D2E3FC;\n",
+ " }\n",
+ "\n",
+ " [theme=dark] .colab-df-convert:hover {\n",
+ " background-color: #434B5C;\n",
+ " box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+ " filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+ " fill: #FFFFFF;\n",
+ " }\n",
+ " </style>\n",
+ "\n",
+ " <script>\n",
+ " const buttonEl =\n",
+ " document.querySelector('#df-03e4189e-e74e-4693-8705-ae3baf7f7402 button.colab-df-convert');\n",
+ " buttonEl.style.display =\n",
+ " google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+ "\n",
+ " async function convertToInteractive(key) {\n",
+ " const element = document.querySelector('#df-03e4189e-e74e-4693-8705-ae3baf7f7402');\n",
+ " const dataTable =\n",
+ " await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+ " [key], {});\n",
+ " if (!dataTable) return;\n",
+ "\n",
+ " const docLinkHtml = 'Like what you see? Visit the ' +\n",
+ " '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+ " + ' to learn more about interactive tables.';\n",
+ " element.innerHTML = '';\n",
+ " dataTable['output_type'] = 'display_data';\n",
+ " await google.colab.output.renderOutput(dataTable, element);\n",
+ " const docLink = document.createElement('div');\n",
+ " docLink.innerHTML = docLinkHtml;\n",
+ " element.appendChild(docLink);\n",
+ " }\n",
+ " </script>\n",
+ " </div>\n",
+ "\n",
+ "\n",
+ "<div id=\"df-be512954-4d6d-48d8-830f-01f721c1d73a\">\n",
+ " <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-be512954-4d6d-48d8-830f-01f721c1d73a')\"\n",
+ " title=\"Suggest charts\"\n",
+ " style=\"display:none;\">\n",
+ "\n",
+ "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+ " width=\"24px\">\n",
+ " <g>\n",
+ " <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
+ " </g>\n",
+ "</svg>\n",
+ " </button>\n",
+ "\n",
+ "<style>\n",
+ " .colab-df-quickchart {\n",
+ " --bg-color: #E8F0FE;\n",
+ " --fill-color: #1967D2;\n",
+ " --hover-bg-color: #E2EBFA;\n",
+ " --hover-fill-color: #174EA6;\n",
+ " --disabled-fill-color: #AAA;\n",
+ " --disabled-bg-color: #DDD;\n",
+ " }\n",
+ "\n",
+ " [theme=dark] .colab-df-quickchart {\n",
+ " --bg-color: #3B4455;\n",
+ " --fill-color: #D2E3FC;\n",
+ " --hover-bg-color: #434B5C;\n",
+ " --hover-fill-color: #FFFFFF;\n",
+ " --disabled-bg-color: #3B4455;\n",
+ " --disabled-fill-color: #666;\n",
+ " }\n",
+ "\n",
+ " .colab-df-quickchart {\n",
+ " background-color: var(--bg-color);\n",
+ " border: none;\n",
+ " border-radius: 50%;\n",
+ " cursor: pointer;\n",
+ " display: none;\n",
+ " fill: var(--fill-color);\n",
+ " height: 32px;\n",
+ " padding: 0;\n",
+ " width: 32px;\n",
+ " }\n",
+ "\n",
+ " .colab-df-quickchart:hover {\n",
+ " background-color: var(--hover-bg-color);\n",
+ " box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+ " fill: var(--button-hover-fill-color);\n",
+ " }\n",
+ "\n",
+ " .colab-df-quickchart-complete:disabled,\n",
+ " .colab-df-quickchart-complete:disabled:hover {\n",
+ " background-color: var(--disabled-bg-color);\n",
+ " fill: var(--disabled-fill-color);\n",
+ " box-shadow: none;\n",
+ " }\n",
+ "\n",
+ " .colab-df-spinner {\n",
+ " border: 2px solid var(--fill-color);\n",
+ " border-color: transparent;\n",
+ " border-bottom-color: var(--fill-color);\n",
+ " animation:\n",
+ " spin 1s steps(1) infinite;\n",
+ " }\n",
+ "\n",
+ " @keyframes spin {\n",
+ " 0% {\n",
+ " border-color: transparent;\n",
+ " border-bottom-color: var(--fill-color);\n",
+ " border-left-color: var(--fill-color);\n",
+ " }\n",
+ " 20% {\n",
+ " border-color: transparent;\n",
+ " border-left-color: var(--fill-color);\n",
+ " border-top-color: var(--fill-color);\n",
+ " }\n",
+ " 30% {\n",
+ " border-color: transparent;\n",
+ " border-left-color: var(--fill-color);\n",
+ " border-top-color: var(--fill-color);\n",
+ " border-right-color: var(--fill-color);\n",
+ " }\n",
+ " 40% {\n",
+ " border-color: transparent;\n",
+ " border-right-color: var(--fill-color);\n",
+ " border-top-color: var(--fill-color);\n",
+ " }\n",
+ " 60% {\n",
+ " border-color: transparent;\n",
+ " border-right-color: var(--fill-color);\n",
+ " }\n",
+ " 80% {\n",
+ " border-color: transparent;\n",
+ " border-right-color: var(--fill-color);\n",
+ " border-bottom-color: var(--fill-color);\n",
+ " }\n",
+ " 90% {\n",
+ " border-color: transparent;\n",
+ " border-bottom-color: var(--fill-color);\n",
+ " }\n",
+ " }\n",
+ "</style>\n",
+ "\n",
+ " <script>\n",
+ " async function quickchart(key) {\n",
+ " const quickchartButtonEl =\n",
+ " document.querySelector('#' + key + ' button');\n",
+ " quickchartButtonEl.disabled = true; // To prevent multiple clicks.\n",
+ " quickchartButtonEl.classList.add('colab-df-spinner');\n",
+ " try {\n",
+ " const charts = await google.colab.kernel.invokeFunction(\n",
+ " 'suggestCharts', [key], {});\n",
+ " } catch (error) {\n",
+ " console.error('Error during call to suggestCharts:', error);\n",
+ " }\n",
+ " quickchartButtonEl.classList.remove('colab-df-spinner');\n",
+ " quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
+ " }\n",
+ " (() => {\n",
+ " let quickchartButtonEl =\n",
+ " document.querySelector('#df-be512954-4d6d-48d8-830f-01f721c1d73a button');\n",
+ " quickchartButtonEl.style.display =\n",
+ " google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+ " })();\n",
+ " </script>\n",
+ "</div>\n",
+ " </div>\n",
+ " </div>\n"
+ ]
+ },
+ "metadata": {},
+ "execution_count": 135
+ }
+ ],
+ "source": [
+ "p_num"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "64w3M8mj4atO",
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 721
+ },
+ "outputId": "89dceea6-4d55-4065-a38d-ebb529b484f6"
+ },
+ "outputs": [
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ "<Figure size 1000x700 with 1 Axes>"
+ ],
+ "image/png": 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+ },
+ "metadata": {}
+ }
+ ],
+ "source": [
+ "# Ploting the all the outliers\n",
+ "plt.figure(figsize=(10,7))\n",
+ "sns.boxplot(data=p_num)\n",
+ "plt.title('Outlier Visualization', fontsize=20)\n",
+ "plt.xticks(rotation=90)\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "x-3ktA5C3FMx",
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "outputId": "4c446c1b-4691-4f89-944a-77be1afbe9b6"
+ },
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "(5124,)\n",
+ "\n",
+ "After Removing Outliers:\n",
+ " (array([ 0, 0, 0, ..., 5123, 5123, 5123]), array([0, 1, 2, ..., 3, 4, 5]))\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Removing outliers\n",
+ "p_outliers = (z1 < threshold).all(axis=1)\n",
+ "print(p_outliers.shape)\n",
+ "print('\\nAfter Removing Outliers:\\n', np.where(z1 < threshold))\n",
+ "\n",
+ "p_outliers_removed = p_num[p_outliers]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "Bif4SFdAVMor",
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "outputId": "a8cdc9a1-41b9-433a-87bb-d167d440e4af"
+ },
+ "outputs": [
+ {
+ "output_type": "execute_result",
+ "data": {
+ "text/plain": [
+ "0 True\n",
+ "1 True\n",
+ "2 True\n",
+ "3 True\n",
+ "4 True\n",
+ " ... \n",
+ "5119 True\n",
+ "5120 True\n",
+ "5121 True\n",
+ "5122 True\n",
+ "5123 True\n",
+ "Length: 5124, dtype: bool"
+ ]
+ },
+ "metadata": {},
+ "execution_count": 138
+ }
+ ],
+ "source": [
+ "p_outliers"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "pQLJox8eVMor",
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 424
+ },
+ "outputId": "d42a3f03-f29d-4d08-83f8-76cbc92e5ba6"
+ },
+ "outputs": [
+ {
+ "output_type": "execute_result",
+ "data": {
+ "text/plain": [
+ " age bmi alcohol_misuse health_gen health_ment health_phys\n",
+ "0 68 20 2.000000 1.0 0.0 0.0\n",
+ "1 54 47 1.000000 3.0 0.0 0.0\n",
+ "2 55 30 0.000000 1.0 0.0 0.0\n",
+ "3 44 19 6.000000 3.0 20.0 6.0\n",
+ "4 61 32 2.394339 2.0 0.0 0.0\n",
+ "... ... ... ... ... ... ...\n",
+ "5119 30 39 3.000000 2.0 7.0 0.0\n",
+ "5120 44 25 2.000000 2.0 0.0 0.0\n",
+ "5121 51 32 2.394339 2.0 0.0 0.0\n",
+ "5122 26 28 2.394339 3.0 0.0 0.0\n",
+ "5123 21 21 1.000000 2.0 2.0 0.0\n",
+ "\n",
+ "[4567 rows x 6 columns]"
+ ],
+ "text/html": [
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+ " <td>0.0</td>\n",
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+ " <td>2.0</td>\n",
+ " <td>2.0</td>\n",
+ " <td>0.0</td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ "</table>\n",
+ "<p>4567 rows × 6 columns</p>\n",
+ "</div>\n",
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+ " display:flex;\n",
+ " gap: 12px;\n",
+ " }\n",
+ "\n",
+ " .colab-df-convert {\n",
+ " background-color: #E8F0FE;\n",
+ " border: none;\n",
+ " border-radius: 50%;\n",
+ " cursor: pointer;\n",
+ " display: none;\n",
+ " fill: #1967D2;\n",
+ " height: 32px;\n",
+ " padding: 0 0 0 0;\n",
+ " width: 32px;\n",
+ " }\n",
+ "\n",
+ " .colab-df-convert:hover {\n",
+ " background-color: #E2EBFA;\n",
+ " box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+ " fill: #174EA6;\n",
+ " }\n",
+ "\n",
+ " .colab-df-buttons div {\n",
+ " margin-bottom: 4px;\n",
+ " }\n",
+ "\n",
+ " [theme=dark] .colab-df-convert {\n",
+ " background-color: #3B4455;\n",
+ " fill: #D2E3FC;\n",
+ " }\n",
+ "\n",
+ " [theme=dark] .colab-df-convert:hover {\n",
+ " background-color: #434B5C;\n",
+ " box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+ " filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+ " fill: #FFFFFF;\n",
+ " }\n",
+ " </style>\n",
+ "\n",
+ " <script>\n",
+ " const buttonEl =\n",
+ " document.querySelector('#df-b7b9f65b-853c-4f72-a49d-cdd59e14b771 button.colab-df-convert');\n",
+ " buttonEl.style.display =\n",
+ " google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+ "\n",
+ " async function convertToInteractive(key) {\n",
+ " const element = document.querySelector('#df-b7b9f65b-853c-4f72-a49d-cdd59e14b771');\n",
+ " const dataTable =\n",
+ " await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+ " [key], {});\n",
+ " if (!dataTable) return;\n",
+ "\n",
+ " const docLinkHtml = 'Like what you see? Visit the ' +\n",
+ " '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+ " + ' to learn more about interactive tables.';\n",
+ " element.innerHTML = '';\n",
+ " dataTable['output_type'] = 'display_data';\n",
+ " await google.colab.output.renderOutput(dataTable, element);\n",
+ " const docLink = document.createElement('div');\n",
+ " docLink.innerHTML = docLinkHtml;\n",
+ " element.appendChild(docLink);\n",
+ " }\n",
+ " </script>\n",
+ " </div>\n",
+ "\n",
+ "\n",
+ "<div id=\"df-087f4741-42d8-4f60-9d22-0fb8b93f829c\">\n",
+ " <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-087f4741-42d8-4f60-9d22-0fb8b93f829c')\"\n",
+ " title=\"Suggest charts\"\n",
+ " style=\"display:none;\">\n",
+ "\n",
+ "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+ " width=\"24px\">\n",
+ " <g>\n",
+ " <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
+ " </g>\n",
+ "</svg>\n",
+ " </button>\n",
+ "\n",
+ "<style>\n",
+ " .colab-df-quickchart {\n",
+ " --bg-color: #E8F0FE;\n",
+ " --fill-color: #1967D2;\n",
+ " --hover-bg-color: #E2EBFA;\n",
+ " --hover-fill-color: #174EA6;\n",
+ " --disabled-fill-color: #AAA;\n",
+ " --disabled-bg-color: #DDD;\n",
+ " }\n",
+ "\n",
+ " [theme=dark] .colab-df-quickchart {\n",
+ " --bg-color: #3B4455;\n",
+ " --fill-color: #D2E3FC;\n",
+ " --hover-bg-color: #434B5C;\n",
+ " --hover-fill-color: #FFFFFF;\n",
+ " --disabled-bg-color: #3B4455;\n",
+ " --disabled-fill-color: #666;\n",
+ " }\n",
+ "\n",
+ " .colab-df-quickchart {\n",
+ " background-color: var(--bg-color);\n",
+ " border: none;\n",
+ " border-radius: 50%;\n",
+ " cursor: pointer;\n",
+ " display: none;\n",
+ " fill: var(--fill-color);\n",
+ " height: 32px;\n",
+ " padding: 0;\n",
+ " width: 32px;\n",
+ " }\n",
+ "\n",
+ " .colab-df-quickchart:hover {\n",
+ " background-color: var(--hover-bg-color);\n",
+ " box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+ " fill: var(--button-hover-fill-color);\n",
+ " }\n",
+ "\n",
+ " .colab-df-quickchart-complete:disabled,\n",
+ " .colab-df-quickchart-complete:disabled:hover {\n",
+ " background-color: var(--disabled-bg-color);\n",
+ " fill: var(--disabled-fill-color);\n",
+ " box-shadow: none;\n",
+ " }\n",
+ "\n",
+ " .colab-df-spinner {\n",
+ " border: 2px solid var(--fill-color);\n",
+ " border-color: transparent;\n",
+ " border-bottom-color: var(--fill-color);\n",
+ " animation:\n",
+ " spin 1s steps(1) infinite;\n",
+ " }\n",
+ "\n",
+ " @keyframes spin {\n",
+ " 0% {\n",
+ " border-color: transparent;\n",
+ " border-bottom-color: var(--fill-color);\n",
+ " border-left-color: var(--fill-color);\n",
+ " }\n",
+ " 20% {\n",
+ " border-color: transparent;\n",
+ " border-left-color: var(--fill-color);\n",
+ " border-top-color: var(--fill-color);\n",
+ " }\n",
+ " 30% {\n",
+ " border-color: transparent;\n",
+ " border-left-color: var(--fill-color);\n",
+ " border-top-color: var(--fill-color);\n",
+ " border-right-color: var(--fill-color);\n",
+ " }\n",
+ " 40% {\n",
+ " border-color: transparent;\n",
+ " border-right-color: var(--fill-color);\n",
+ " border-top-color: var(--fill-color);\n",
+ " }\n",
+ " 60% {\n",
+ " border-color: transparent;\n",
+ " border-right-color: var(--fill-color);\n",
+ " }\n",
+ " 80% {\n",
+ " border-color: transparent;\n",
+ " border-right-color: var(--fill-color);\n",
+ " border-bottom-color: var(--fill-color);\n",
+ " }\n",
+ " 90% {\n",
+ " border-color: transparent;\n",
+ " border-bottom-color: var(--fill-color);\n",
+ " }\n",
+ " }\n",
+ "</style>\n",
+ "\n",
+ " <script>\n",
+ " async function quickchart(key) {\n",
+ " const quickchartButtonEl =\n",
+ " document.querySelector('#' + key + ' button');\n",
+ " quickchartButtonEl.disabled = true; // To prevent multiple clicks.\n",
+ " quickchartButtonEl.classList.add('colab-df-spinner');\n",
+ " try {\n",
+ " const charts = await google.colab.kernel.invokeFunction(\n",
+ " 'suggestCharts', [key], {});\n",
+ " } catch (error) {\n",
+ " console.error('Error during call to suggestCharts:', error);\n",
+ " }\n",
+ " quickchartButtonEl.classList.remove('colab-df-spinner');\n",
+ " quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
+ " }\n",
+ " (() => {\n",
+ " let quickchartButtonEl =\n",
+ " document.querySelector('#df-087f4741-42d8-4f60-9d22-0fb8b93f829c button');\n",
+ " quickchartButtonEl.style.display =\n",
+ " google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+ " })();\n",
+ " </script>\n",
+ "</div>\n",
+ " </div>\n",
+ " </div>\n"
+ ]
+ },
+ "metadata": {},
+ "execution_count": 139
+ }
+ ],
+ "source": [
+ "p_outliers_removed"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "KjTVw-Kz53bT"
+ },
+ "source": [
+ "# Outlier Removal on X_train"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "4ZWHazYdVMow",
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 424
+ },
+ "outputId": "9fd40c30-3404-4d2a-d84e-a25979c2fe7a"
+ },
+ "outputs": [
+ {
+ "output_type": "execute_result",
+ "data": {
+ "text/plain": [
+ " age bmi alcohol_misuse health_gen health_ment health_phys\n",
+ "0 20.0 36.0 0.000000 3.0 0.0 0.0\n",
+ "1 76.0 24.0 2.000000 4.0 3.0 0.0\n",
+ "2 70.0 23.0 4.000000 5.0 22.0 23.0\n",
+ "3 55.0 26.0 3.000000 2.0 0.0 0.0\n",
+ "4 51.0 37.0 2.000000 1.0 3.0 6.0\n",
+ "... ... ... ... ... ... ...\n",
+ "3838 62.0 27.0 2.000000 2.0 0.0 0.0\n",
+ "3839 26.0 22.0 2.391473 2.0 2.0 0.0\n",
+ "3840 72.0 30.0 4.000000 4.0 5.0 7.0\n",
+ "3841 59.0 24.0 0.000000 1.0 0.0 0.0\n",
+ "3842 53.0 31.0 1.000000 1.0 2.0 2.0\n",
+ "\n",
+ "[3843 rows x 6 columns]"
+ ],
+ "text/html": [
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+ "<style scoped>\n",
+ " .dataframe tbody tr th:only-of-type {\n",
+ " vertical-align: middle;\n",
+ " }\n",
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+ " }\n",
+ "\n",
+ " .dataframe thead th {\n",
+ " text-align: right;\n",
+ " }\n",
+ "</style>\n",
+ "<table border=\"1\" class=\"dataframe\">\n",
+ " <thead>\n",
+ " <tr style=\"text-align: right;\">\n",
+ " <th></th>\n",
+ " <th>age</th>\n",
+ " <th>bmi</th>\n",
+ " <th>alcohol_misuse</th>\n",
+ " <th>health_gen</th>\n",
+ " <th>health_ment</th>\n",
+ " <th>health_phys</th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " <tr>\n",
+ " <th>0</th>\n",
+ " <td>20.0</td>\n",
+ " <td>36.0</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>3.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
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+ " <th>1</th>\n",
+ " <td>76.0</td>\n",
+ " <td>24.0</td>\n",
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+ " <td>4.0</td>\n",
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+ " <th>2</th>\n",
+ " <td>70.0</td>\n",
+ " <td>23.0</td>\n",
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+ " <td>5.0</td>\n",
+ " <td>22.0</td>\n",
+ " <td>23.0</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>3</th>\n",
+ " <td>55.0</td>\n",
+ " <td>26.0</td>\n",
+ " <td>3.000000</td>\n",
+ " <td>2.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
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+ " <th>4</th>\n",
+ " <td>51.0</td>\n",
+ " <td>37.0</td>\n",
+ " <td>2.000000</td>\n",
+ " <td>1.0</td>\n",
+ " <td>3.0</td>\n",
+ " <td>6.0</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>...</th>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>3838</th>\n",
+ " <td>62.0</td>\n",
+ " <td>27.0</td>\n",
+ " <td>2.000000</td>\n",
+ " <td>2.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
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+ " <tr>\n",
+ " <th>3839</th>\n",
+ " <td>26.0</td>\n",
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+ " <td>2.0</td>\n",
+ " <td>0.0</td>\n",
+ " </tr>\n",
+ " <tr>\n",
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+ " <td>72.0</td>\n",
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+ " <td>4.0</td>\n",
+ " <td>5.0</td>\n",
+ " <td>7.0</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>3841</th>\n",
+ " <td>59.0</td>\n",
+ " <td>24.0</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>3842</th>\n",
+ " <td>53.0</td>\n",
+ " <td>31.0</td>\n",
+ " <td>1.000000</td>\n",
+ " <td>1.0</td>\n",
+ " <td>2.0</td>\n",
+ " <td>2.0</td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ "</table>\n",
+ "<p>3843 rows × 6 columns</p>\n",
+ "</div>\n",
+ " <div class=\"colab-df-buttons\">\n",
+ "\n",
+ " <div class=\"colab-df-container\">\n",
+ " <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-ced35156-fd77-48d9-b19e-717c07b2cee1')\"\n",
+ " title=\"Convert this dataframe to an interactive table.\"\n",
+ " style=\"display:none;\">\n",
+ "\n",
+ " <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
+ " <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
+ " </svg>\n",
+ " </button>\n",
+ "\n",
+ " <style>\n",
+ " .colab-df-container {\n",
+ " display:flex;\n",
+ " gap: 12px;\n",
+ " }\n",
+ "\n",
+ " .colab-df-convert {\n",
+ " background-color: #E8F0FE;\n",
+ " border: none;\n",
+ " border-radius: 50%;\n",
+ " cursor: pointer;\n",
+ " display: none;\n",
+ " fill: #1967D2;\n",
+ " height: 32px;\n",
+ " padding: 0 0 0 0;\n",
+ " width: 32px;\n",
+ " }\n",
+ "\n",
+ " .colab-df-convert:hover {\n",
+ " background-color: #E2EBFA;\n",
+ " box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+ " fill: #174EA6;\n",
+ " }\n",
+ "\n",
+ " .colab-df-buttons div {\n",
+ " margin-bottom: 4px;\n",
+ " }\n",
+ "\n",
+ " [theme=dark] .colab-df-convert {\n",
+ " background-color: #3B4455;\n",
+ " fill: #D2E3FC;\n",
+ " }\n",
+ "\n",
+ " [theme=dark] .colab-df-convert:hover {\n",
+ " background-color: #434B5C;\n",
+ " box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+ " filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+ " fill: #FFFFFF;\n",
+ " }\n",
+ " </style>\n",
+ "\n",
+ " <script>\n",
+ " const buttonEl =\n",
+ " document.querySelector('#df-ced35156-fd77-48d9-b19e-717c07b2cee1 button.colab-df-convert');\n",
+ " buttonEl.style.display =\n",
+ " google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+ "\n",
+ " async function convertToInteractive(key) {\n",
+ " const element = document.querySelector('#df-ced35156-fd77-48d9-b19e-717c07b2cee1');\n",
+ " const dataTable =\n",
+ " await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+ " [key], {});\n",
+ " if (!dataTable) return;\n",
+ "\n",
+ " const docLinkHtml = 'Like what you see? Visit the ' +\n",
+ " '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+ " + ' to learn more about interactive tables.';\n",
+ " element.innerHTML = '';\n",
+ " dataTable['output_type'] = 'display_data';\n",
+ " await google.colab.output.renderOutput(dataTable, element);\n",
+ " const docLink = document.createElement('div');\n",
+ " docLink.innerHTML = docLinkHtml;\n",
+ " element.appendChild(docLink);\n",
+ " }\n",
+ " </script>\n",
+ " </div>\n",
+ "\n",
+ "\n",
+ "<div id=\"df-4e79922d-0055-4096-a45f-4fca599764f7\">\n",
+ " <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-4e79922d-0055-4096-a45f-4fca599764f7')\"\n",
+ " title=\"Suggest charts\"\n",
+ " style=\"display:none;\">\n",
+ "\n",
+ "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+ " width=\"24px\">\n",
+ " <g>\n",
+ " <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
+ " </g>\n",
+ "</svg>\n",
+ " </button>\n",
+ "\n",
+ "<style>\n",
+ " .colab-df-quickchart {\n",
+ " --bg-color: #E8F0FE;\n",
+ " --fill-color: #1967D2;\n",
+ " --hover-bg-color: #E2EBFA;\n",
+ " --hover-fill-color: #174EA6;\n",
+ " --disabled-fill-color: #AAA;\n",
+ " --disabled-bg-color: #DDD;\n",
+ " }\n",
+ "\n",
+ " [theme=dark] .colab-df-quickchart {\n",
+ " --bg-color: #3B4455;\n",
+ " --fill-color: #D2E3FC;\n",
+ " --hover-bg-color: #434B5C;\n",
+ " --hover-fill-color: #FFFFFF;\n",
+ " --disabled-bg-color: #3B4455;\n",
+ " --disabled-fill-color: #666;\n",
+ " }\n",
+ "\n",
+ " .colab-df-quickchart {\n",
+ " background-color: var(--bg-color);\n",
+ " border: none;\n",
+ " border-radius: 50%;\n",
+ " cursor: pointer;\n",
+ " display: none;\n",
+ " fill: var(--fill-color);\n",
+ " height: 32px;\n",
+ " padding: 0;\n",
+ " width: 32px;\n",
+ " }\n",
+ "\n",
+ " .colab-df-quickchart:hover {\n",
+ " background-color: var(--hover-bg-color);\n",
+ " box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+ " fill: var(--button-hover-fill-color);\n",
+ " }\n",
+ "\n",
+ " .colab-df-quickchart-complete:disabled,\n",
+ " .colab-df-quickchart-complete:disabled:hover {\n",
+ " background-color: var(--disabled-bg-color);\n",
+ " fill: var(--disabled-fill-color);\n",
+ " box-shadow: none;\n",
+ " }\n",
+ "\n",
+ " .colab-df-spinner {\n",
+ " border: 2px solid var(--fill-color);\n",
+ " border-color: transparent;\n",
+ " border-bottom-color: var(--fill-color);\n",
+ " animation:\n",
+ " spin 1s steps(1) infinite;\n",
+ " }\n",
+ "\n",
+ " @keyframes spin {\n",
+ " 0% {\n",
+ " border-color: transparent;\n",
+ " border-bottom-color: var(--fill-color);\n",
+ " border-left-color: var(--fill-color);\n",
+ " }\n",
+ " 20% {\n",
+ " border-color: transparent;\n",
+ " border-left-color: var(--fill-color);\n",
+ " border-top-color: var(--fill-color);\n",
+ " }\n",
+ " 30% {\n",
+ " border-color: transparent;\n",
+ " border-left-color: var(--fill-color);\n",
+ " border-top-color: var(--fill-color);\n",
+ " border-right-color: var(--fill-color);\n",
+ " }\n",
+ " 40% {\n",
+ " border-color: transparent;\n",
+ " border-right-color: var(--fill-color);\n",
+ " border-top-color: var(--fill-color);\n",
+ " }\n",
+ " 60% {\n",
+ " border-color: transparent;\n",
+ " border-right-color: var(--fill-color);\n",
+ " }\n",
+ " 80% {\n",
+ " border-color: transparent;\n",
+ " border-right-color: var(--fill-color);\n",
+ " border-bottom-color: var(--fill-color);\n",
+ " }\n",
+ " 90% {\n",
+ " border-color: transparent;\n",
+ " border-bottom-color: var(--fill-color);\n",
+ " }\n",
+ " }\n",
+ "</style>\n",
+ "\n",
+ " <script>\n",
+ " async function quickchart(key) {\n",
+ " const quickchartButtonEl =\n",
+ " document.querySelector('#' + key + ' button');\n",
+ " quickchartButtonEl.disabled = true; // To prevent multiple clicks.\n",
+ " quickchartButtonEl.classList.add('colab-df-spinner');\n",
+ " try {\n",
+ " const charts = await google.colab.kernel.invokeFunction(\n",
+ " 'suggestCharts', [key], {});\n",
+ " } catch (error) {\n",
+ " console.error('Error during call to suggestCharts:', error);\n",
+ " }\n",
+ " quickchartButtonEl.classList.remove('colab-df-spinner');\n",
+ " quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
+ " }\n",
+ " (() => {\n",
+ " let quickchartButtonEl =\n",
+ " document.querySelector('#df-4e79922d-0055-4096-a45f-4fca599764f7 button');\n",
+ " quickchartButtonEl.style.display =\n",
+ " google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+ " })();\n",
+ " </script>\n",
+ "</div>\n",
+ " </div>\n",
+ " </div>\n"
+ ]
+ },
+ "metadata": {},
+ "execution_count": 140
+ }
+ ],
+ "source": [
+ "# Splitting a training dataset\n",
+ "X_train_num = X_train_imputed[['age', 'bmi', 'alcohol_misuse', 'health_gen', 'health_ment', 'health_phys']]\n",
+ "X_train_cat = X_train_imputed[['gender', 'high_bp', 'high_chol', 'chol_check', 'history_smoking', 'history_stroke', 'history_heart_disease', 'amount_activity', 'fruits', 'vegetables', 'walking_diff']]\n",
+ "\n",
+ "X_train_num"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "MrpMONI2VMow",
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "outputId": "ba139d4d-56a1-444a-936b-6cdbcf3f3967"
+ },
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "\n",
+ "Z-Score Array:\n",
+ " age bmi alcohol_misuse health_gen health_ment health_phys\n",
+ "0 2.126519 1.124585 0.913683 0.470527 0.443662 0.429262\n",
+ "1 1.259147 0.590123 0.149566 1.387135 0.049203 0.429262\n",
+ "2 0.896397 0.733016 0.614552 2.303742 2.449039 1.972270\n",
+ "3 0.010478 0.304339 0.232493 0.446081 0.443662 0.429262\n",
+ "4 0.252311 1.267477 0.149566 1.362688 0.049203 0.197224\n",
+ "... ... ... ... ... ... ...\n",
+ "3838 0.412731 0.161446 0.149566 0.446081 0.443662 0.429262\n",
+ "3839 1.763769 0.875908 0.000000 0.446081 0.180689 0.429262\n",
+ "3840 1.017314 0.267231 0.614552 1.387135 0.213770 0.301639\n",
+ "3841 0.231356 0.590123 0.913683 1.362688 0.443662 0.429262\n",
+ "3842 0.131394 0.410123 0.531624 1.362688 0.180689 0.220434\n",
+ "\n",
+ "[3843 rows x 6 columns]\n",
+ "(3843, 6)\n",
+ "\n",
+ "Outliers:\n",
+ " (array([ 0, 0, 0, ..., 3842, 3842, 3842]), array([0, 1, 2, ..., 3, 4, 5]))\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Calculating the Z-scores for each element in the X_train_num\n",
+ "z1 = np.abs(stats.zscore(X_train_num))\n",
+ "print('\\nZ-Score Array:\\n', z1)\n",
+ "print(X_train_num.shape)\n",
+ "\n",
+ "threshold = 3\n",
+ "print('\\nOutliers:\\n', np.where(z1 < threshold))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "ba_tXbyfVMow",
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "outputId": "a1e0f0e0-1ad8-4d88-913c-85fc0a5f5d4b"
+ },
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "(3843,)\n"
+ ]
+ },
+ {
+ "output_type": "execute_result",
+ "data": {
+ "text/plain": [
+ "0 True\n",
+ "1 True\n",
+ "2 True\n",
+ "3 True\n",
+ "4 True\n",
+ " ... \n",
+ "3838 True\n",
+ "3839 True\n",
+ "3840 True\n",
+ "3841 True\n",
+ "3842 True\n",
+ "Length: 3843, dtype: bool"
+ ]
+ },
+ "metadata": {},
+ "execution_count": 142
+ }
+ ],
+ "source": [
+ "# Identifying outliers in X_train\n",
+ "X_train_outliers = (z1 < threshold).all(axis=1)\n",
+ "print(X_train_outliers.shape)\n",
+ "X_train_outliers"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "kMsQeePiVMow",
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "outputId": "8ee861cb-a13a-4617-cae1-c096993023d6"
+ },
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "\n",
+ "After Removing Outliers:\n",
+ " (array([ 0, 0, 0, ..., 3842, 3842, 3842]), array([0, 1, 2, ..., 3, 4, 5]))\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Remove the outliers in X_train\n",
+ "X_train_outliers_removed = X_train_num[X_train_outliers]\n",
+ "print('\\nAfter Removing Outliers:\\n', np.where(z1 < threshold))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "GRH6VXQMVMow",
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 424
+ },
+ "outputId": "782c7a01-b7df-4317-a538-c06352f7b0c3"
+ },
+ "outputs": [
+ {
+ "output_type": "execute_result",
+ "data": {
+ "text/plain": [
+ " age bmi alcohol_misuse health_gen health_ment health_phys\n",
+ "0 20.0 36.0 0.000000 3.0 0.0 0.0\n",
+ "1 76.0 24.0 2.000000 4.0 3.0 0.0\n",
+ "2 70.0 23.0 4.000000 5.0 22.0 23.0\n",
+ "3 55.0 26.0 3.000000 2.0 0.0 0.0\n",
+ "4 51.0 37.0 2.000000 1.0 3.0 6.0\n",
+ "... ... ... ... ... ... ...\n",
+ "3838 62.0 27.0 2.000000 2.0 0.0 0.0\n",
+ "3839 26.0 22.0 2.391473 2.0 2.0 0.0\n",
+ "3840 72.0 30.0 4.000000 4.0 5.0 7.0\n",
+ "3841 59.0 24.0 0.000000 1.0 0.0 0.0\n",
+ "3842 53.0 31.0 1.000000 1.0 2.0 2.0\n",
+ "\n",
+ "[3435 rows x 6 columns]"
+ ],
+ "text/html": [
+ "\n",
+ " <div id=\"df-31337703-1fa4-460a-8bb9-7d63ff37c27c\" class=\"colab-df-container\">\n",
+ " <div>\n",
+ "<style scoped>\n",
+ " .dataframe tbody tr th:only-of-type {\n",
+ " vertical-align: middle;\n",
+ " }\n",
+ "\n",
+ " .dataframe tbody tr th {\n",
+ " vertical-align: top;\n",
+ " }\n",
+ "\n",
+ " .dataframe thead th {\n",
+ " text-align: right;\n",
+ " }\n",
+ "</style>\n",
+ "<table border=\"1\" class=\"dataframe\">\n",
+ " <thead>\n",
+ " <tr style=\"text-align: right;\">\n",
+ " <th></th>\n",
+ " <th>age</th>\n",
+ " <th>bmi</th>\n",
+ " <th>alcohol_misuse</th>\n",
+ " <th>health_gen</th>\n",
+ " <th>health_ment</th>\n",
+ " <th>health_phys</th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
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+ " <td>3.0</td>\n",
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+ " <td>70.0</td>\n",
+ " <td>23.0</td>\n",
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+ " <td>5.0</td>\n",
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+ " <td>23.0</td>\n",
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+ " <th>3</th>\n",
+ " <td>55.0</td>\n",
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+ " <td>...</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>3838</th>\n",
+ " <td>62.0</td>\n",
+ " <td>27.0</td>\n",
+ " <td>2.000000</td>\n",
+ " <td>2.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>3839</th>\n",
+ " <td>26.0</td>\n",
+ " <td>22.0</td>\n",
+ " <td>2.391473</td>\n",
+ " <td>2.0</td>\n",
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+ " <td>0.0</td>\n",
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+ " <td>7.0</td>\n",
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+ " <tr>\n",
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+ " <td>59.0</td>\n",
+ " <td>24.0</td>\n",
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+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
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+ " <th>3842</th>\n",
+ " <td>53.0</td>\n",
+ " <td>31.0</td>\n",
+ " <td>1.000000</td>\n",
+ " <td>1.0</td>\n",
+ " <td>2.0</td>\n",
+ " <td>2.0</td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ "</table>\n",
+ "<p>3435 rows × 6 columns</p>\n",
+ "</div>\n",
+ " <div class=\"colab-df-buttons\">\n",
+ "\n",
+ " <div class=\"colab-df-container\">\n",
+ " <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-31337703-1fa4-460a-8bb9-7d63ff37c27c')\"\n",
+ " title=\"Convert this dataframe to an interactive table.\"\n",
+ " style=\"display:none;\">\n",
+ "\n",
+ " <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
+ " <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
+ " </svg>\n",
+ " </button>\n",
+ "\n",
+ " <style>\n",
+ " .colab-df-container {\n",
+ " display:flex;\n",
+ " gap: 12px;\n",
+ " }\n",
+ "\n",
+ " .colab-df-convert {\n",
+ " background-color: #E8F0FE;\n",
+ " border: none;\n",
+ " border-radius: 50%;\n",
+ " cursor: pointer;\n",
+ " display: none;\n",
+ " fill: #1967D2;\n",
+ " height: 32px;\n",
+ " padding: 0 0 0 0;\n",
+ " width: 32px;\n",
+ " }\n",
+ "\n",
+ " .colab-df-convert:hover {\n",
+ " background-color: #E2EBFA;\n",
+ " box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+ " fill: #174EA6;\n",
+ " }\n",
+ "\n",
+ " .colab-df-buttons div {\n",
+ " margin-bottom: 4px;\n",
+ " }\n",
+ "\n",
+ " [theme=dark] .colab-df-convert {\n",
+ " background-color: #3B4455;\n",
+ " fill: #D2E3FC;\n",
+ " }\n",
+ "\n",
+ " [theme=dark] .colab-df-convert:hover {\n",
+ " background-color: #434B5C;\n",
+ " box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+ " filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+ " fill: #FFFFFF;\n",
+ " }\n",
+ " </style>\n",
+ "\n",
+ " <script>\n",
+ " const buttonEl =\n",
+ " document.querySelector('#df-31337703-1fa4-460a-8bb9-7d63ff37c27c button.colab-df-convert');\n",
+ " buttonEl.style.display =\n",
+ " google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+ "\n",
+ " async function convertToInteractive(key) {\n",
+ " const element = document.querySelector('#df-31337703-1fa4-460a-8bb9-7d63ff37c27c');\n",
+ " const dataTable =\n",
+ " await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+ " [key], {});\n",
+ " if (!dataTable) return;\n",
+ "\n",
+ " const docLinkHtml = 'Like what you see? Visit the ' +\n",
+ " '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+ " + ' to learn more about interactive tables.';\n",
+ " element.innerHTML = '';\n",
+ " dataTable['output_type'] = 'display_data';\n",
+ " await google.colab.output.renderOutput(dataTable, element);\n",
+ " const docLink = document.createElement('div');\n",
+ " docLink.innerHTML = docLinkHtml;\n",
+ " element.appendChild(docLink);\n",
+ " }\n",
+ " </script>\n",
+ " </div>\n",
+ "\n",
+ "\n",
+ "<div id=\"df-1a4cb302-738e-4c23-943f-d812dac0a9f4\">\n",
+ " <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-1a4cb302-738e-4c23-943f-d812dac0a9f4')\"\n",
+ " title=\"Suggest charts\"\n",
+ " style=\"display:none;\">\n",
+ "\n",
+ "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+ " width=\"24px\">\n",
+ " <g>\n",
+ " <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
+ " </g>\n",
+ "</svg>\n",
+ " </button>\n",
+ "\n",
+ "<style>\n",
+ " .colab-df-quickchart {\n",
+ " --bg-color: #E8F0FE;\n",
+ " --fill-color: #1967D2;\n",
+ " --hover-bg-color: #E2EBFA;\n",
+ " --hover-fill-color: #174EA6;\n",
+ " --disabled-fill-color: #AAA;\n",
+ " --disabled-bg-color: #DDD;\n",
+ " }\n",
+ "\n",
+ " [theme=dark] .colab-df-quickchart {\n",
+ " --bg-color: #3B4455;\n",
+ " --fill-color: #D2E3FC;\n",
+ " --hover-bg-color: #434B5C;\n",
+ " --hover-fill-color: #FFFFFF;\n",
+ " --disabled-bg-color: #3B4455;\n",
+ " --disabled-fill-color: #666;\n",
+ " }\n",
+ "\n",
+ " .colab-df-quickchart {\n",
+ " background-color: var(--bg-color);\n",
+ " border: none;\n",
+ " border-radius: 50%;\n",
+ " cursor: pointer;\n",
+ " display: none;\n",
+ " fill: var(--fill-color);\n",
+ " height: 32px;\n",
+ " padding: 0;\n",
+ " width: 32px;\n",
+ " }\n",
+ "\n",
+ " .colab-df-quickchart:hover {\n",
+ " background-color: var(--hover-bg-color);\n",
+ " box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+ " fill: var(--button-hover-fill-color);\n",
+ " }\n",
+ "\n",
+ " .colab-df-quickchart-complete:disabled,\n",
+ " .colab-df-quickchart-complete:disabled:hover {\n",
+ " background-color: var(--disabled-bg-color);\n",
+ " fill: var(--disabled-fill-color);\n",
+ " box-shadow: none;\n",
+ " }\n",
+ "\n",
+ " .colab-df-spinner {\n",
+ " border: 2px solid var(--fill-color);\n",
+ " border-color: transparent;\n",
+ " border-bottom-color: var(--fill-color);\n",
+ " animation:\n",
+ " spin 1s steps(1) infinite;\n",
+ " }\n",
+ "\n",
+ " @keyframes spin {\n",
+ " 0% {\n",
+ " border-color: transparent;\n",
+ " border-bottom-color: var(--fill-color);\n",
+ " border-left-color: var(--fill-color);\n",
+ " }\n",
+ " 20% {\n",
+ " border-color: transparent;\n",
+ " border-left-color: var(--fill-color);\n",
+ " border-top-color: var(--fill-color);\n",
+ " }\n",
+ " 30% {\n",
+ " border-color: transparent;\n",
+ " border-left-color: var(--fill-color);\n",
+ " border-top-color: var(--fill-color);\n",
+ " border-right-color: var(--fill-color);\n",
+ " }\n",
+ " 40% {\n",
+ " border-color: transparent;\n",
+ " border-right-color: var(--fill-color);\n",
+ " border-top-color: var(--fill-color);\n",
+ " }\n",
+ " 60% {\n",
+ " border-color: transparent;\n",
+ " border-right-color: var(--fill-color);\n",
+ " }\n",
+ " 80% {\n",
+ " border-color: transparent;\n",
+ " border-right-color: var(--fill-color);\n",
+ " border-bottom-color: var(--fill-color);\n",
+ " }\n",
+ " 90% {\n",
+ " border-color: transparent;\n",
+ " border-bottom-color: var(--fill-color);\n",
+ " }\n",
+ " }\n",
+ "</style>\n",
+ "\n",
+ " <script>\n",
+ " async function quickchart(key) {\n",
+ " const quickchartButtonEl =\n",
+ " document.querySelector('#' + key + ' button');\n",
+ " quickchartButtonEl.disabled = true; // To prevent multiple clicks.\n",
+ " quickchartButtonEl.classList.add('colab-df-spinner');\n",
+ " try {\n",
+ " const charts = await google.colab.kernel.invokeFunction(\n",
+ " 'suggestCharts', [key], {});\n",
+ " } catch (error) {\n",
+ " console.error('Error during call to suggestCharts:', error);\n",
+ " }\n",
+ " quickchartButtonEl.classList.remove('colab-df-spinner');\n",
+ " quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
+ " }\n",
+ " (() => {\n",
+ " let quickchartButtonEl =\n",
+ " document.querySelector('#df-1a4cb302-738e-4c23-943f-d812dac0a9f4 button');\n",
+ " quickchartButtonEl.style.display =\n",
+ " google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+ " })();\n",
+ " </script>\n",
+ "</div>\n",
+ " </div>\n",
+ " </div>\n"
+ ]
+ },
+ "metadata": {},
+ "execution_count": 144
+ }
+ ],
+ "source": [
+ "X_train_outliers_removed"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "WnaFXCgL5GNr",
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 801
+ },
+ "outputId": "06b52e22-e260-4b3f-8d72-184524ad6c1a"
+ },
+ "outputs": [
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ "<Figure size 2000x1000 with 1 Axes>"
+ ],
+ "image/png": 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+ },
+ "metadata": {}
+ }
+ ],
+ "source": [
+ "# Ploting the train data outliers\n",
+ "plt.figure(figsize=(20,10))\n",
+ "sns.boxplot(data=X_train_num)\n",
+ "plt.title('Trian Data Outlier Visualization', fontsize=20)\n",
+ "plt.xticks(rotation=90)\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "v9Es0bRm5gNN",
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "outputId": "ed07c79b-a5b2-4b21-b46b-edc123334200"
+ },
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "\n",
+ "After Removing Outliers:\n",
+ " (array([ 0, 0, 0, ..., 3842, 3842, 3842]), array([0, 1, 2, ..., 3, 4, 5]))\n"
+ ]
+ }
+ ],
+ "source": [
+ "print('\\nAfter Removing Outliers:\\n', np.where(z1 < threshold))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "MAi4gmUw5i09",
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 801
+ },
+ "outputId": "128336eb-4df4-4462-81f2-606615dfe063"
+ },
+ "outputs": [
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ "<Figure size 2000x1000 with 1 Axes>"
+ ],
+ "image/png": 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\n"
+ },
+ "metadata": {}
+ }
+ ],
+ "source": [
+ "# Ploting the train data after removing the outliers\n",
+ "plt.figure(figsize=(20,10))\n",
+ "sns.boxplot(data=X_train_outliers_removed)\n",
+ "plt.title('Train Data After Outlier Removal', fontsize=20)\n",
+ "plt.xticks(rotation=90)\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "jTLRVJUT6Eab"
+ },
+ "source": [
+ "# Outlier Removal on X_test"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "hDTlRnOV5x5O",
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "outputId": "979bb7d2-7847-4549-c32d-fdc62e465801"
+ },
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "\n",
+ "Z-Score Array:\n",
+ " age bmi alcohol_misuse health_gen health_ment \\\n",
+ "0 0.038801 0.315286 0.941686 1.338436 0.187389 \n",
+ "1 0.283345 0.914740 0.549421 1.338436 0.449002 \n",
+ "2 1.550738 0.615013 0.549421 2.450707 0.441945 \n",
+ "3 0.144608 0.914740 1.411900 1.338436 0.441945 \n",
+ "4 1.122786 1.214467 0.157157 0.069860 0.441945 \n",
+ "... ... ... ... ... ... \n",
+ "1276 0.144608 0.883621 0.157157 1.503421 0.830836 \n",
+ "1277 0.344481 1.333211 0.627372 2.450707 0.441945 \n",
+ "1278 0.511424 0.315286 2.588693 0.556135 0.830836 \n",
+ "1279 1.444931 1.064603 0.627372 1.338436 0.194446 \n",
+ "1280 0.755969 0.015560 2.588693 1.503421 0.441945 \n",
+ "\n",
+ " health_phys amount_activity_active amount_activity_notactive \\\n",
+ "0 0.404971 0.493649 0.493649 \n",
+ "1 0.295795 0.493649 0.493649 \n",
+ "2 0.905139 0.493649 0.493649 \n",
+ "3 0.404971 0.493649 0.493649 \n",
+ "4 0.404971 0.493649 0.493649 \n",
+ "... ... ... ... \n",
+ "1276 0.404971 0.493649 0.493649 \n",
+ "1277 4.398766 0.493649 0.493649 \n",
+ "1278 0.077443 0.493649 0.493649 \n",
+ "1279 0.404971 0.493649 0.493649 \n",
+ "1280 0.043867 2.025731 2.025731 \n",
+ "\n",
+ " chol_check_checked chol_check_notchecked ... \\\n",
+ "0 0.1886 0.1886 ... \n",
+ "1 0.1886 0.1886 ... \n",
+ "2 0.1886 0.1886 ... \n",
+ "3 0.1886 0.1886 ... \n",
+ "4 0.1886 0.1886 ... \n",
+ "... ... ... ... \n",
+ "1276 0.1886 0.1886 ... \n",
+ "1277 0.1886 0.1886 ... \n",
+ "1278 0.1886 0.1886 ... \n",
+ "1279 0.1886 0.1886 ... \n",
+ "1280 0.1886 0.1886 ... \n",
+ "\n",
+ " history_heart_disease_False history_heart_disease_True \\\n",
+ "0 0.271595 0.271595 \n",
+ "1 0.271595 0.271595 \n",
+ "2 3.681958 3.681958 \n",
+ "3 0.271595 0.271595 \n",
+ "4 0.271595 0.271595 \n",
+ "... ... ... \n",
+ "1276 0.271595 0.271595 \n",
+ "1277 3.681958 3.681958 \n",
+ "1278 0.271595 0.271595 \n",
+ "1279 0.271595 0.271595 \n",
+ "1280 0.271595 0.271595 \n",
+ "\n",
+ " history_smoking_False history_smoking_True history_stroke_False \\\n",
+ "0 0.648211 0.648211 0.174846 \n",
+ "1 1.542708 1.542708 0.174846 \n",
+ "2 0.648211 0.648211 0.174846 \n",
+ "3 0.648211 0.648211 0.174846 \n",
+ "4 0.648211 0.648211 0.174846 \n",
+ "... ... ... ... \n",
+ "1276 0.648211 0.648211 0.174846 \n",
+ "1277 1.542708 1.542708 0.174846 \n",
+ "1278 1.542708 1.542708 0.174846 \n",
+ "1279 0.648211 0.648211 0.174846 \n",
+ "1280 0.648211 0.648211 0.174846 \n",
+ "\n",
+ " history_stroke_True vegetables_False vegetables_True \\\n",
+ "0 0.174846 2.324866 2.324866 \n",
+ "1 0.174846 0.430132 0.430132 \n",
+ "2 0.174846 0.430132 0.430132 \n",
+ "3 0.174846 0.430132 0.430132 \n",
+ "4 0.174846 0.430132 0.430132 \n",
+ "... ... ... ... \n",
+ "1276 0.174846 0.430132 0.430132 \n",
+ "1277 0.174846 2.324866 2.324866 \n",
+ "1278 0.174846 0.430132 0.430132 \n",
+ "1279 0.174846 0.430132 0.430132 \n",
+ "1280 0.174846 2.324866 2.324866 \n",
+ "\n",
+ " walking_diff_False walking_diff_True \n",
+ "0 0.412144 0.412144 \n",
+ "1 0.412144 0.412144 \n",
+ "2 2.426334 2.426334 \n",
+ "3 0.412144 0.412144 \n",
+ "4 0.412144 0.412144 \n",
+ "... ... ... \n",
+ "1276 0.412144 0.412144 \n",
+ "1277 2.426334 2.426334 \n",
+ "1278 0.412144 0.412144 \n",
+ "1279 0.412144 0.412144 \n",
+ "1280 0.412144 0.412144 \n",
+ "\n",
+ "[1281 rows x 28 columns]\n",
+ "(1281, 6)\n",
+ "\n",
+ "Outliers:\n",
+ " (array([ 0, 0, 0, ..., 1280, 1280, 1280]), array([ 0, 1, 2, ..., 25, 26, 27]))\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Calculating the Z-scores for each element in the X_test_num\n",
+ "X_test_num = X_test_imputed[['age', 'bmi', 'alcohol_misuse', 'health_gen', 'health_ment', 'health_phys']]\n",
+ "X_test_cat = X_test_imputed[['gender', 'high_bp', 'high_chol', 'chol_check', 'history_smoking', 'history_stroke', 'history_heart_disease', 'amount_activity', 'fruits', 'vegetables', 'walking_diff']]\n",
+ "\n",
+ "z2 = np.abs(stats.zscore(X_test_prepared))\n",
+ "print('\\nZ-Score Array:\\n', z2)\n",
+ "\n",
+ "print(X_test_num.shape)\n",
+ "threshold = 3\n",
+ "print('\\nOutliers:\\n', np.where(z2 < threshold))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "6W7xWHB96He_",
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 801
+ },
+ "outputId": "5d2cfad0-e74e-4ae5-a7a3-8d949d5ec09b"
+ },
+ "outputs": [
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ "<Figure size 2000x1000 with 1 Axes>"
+ ],
+ "image/png": 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jd+/e8fvf/z622WabonX69esXW221Vaf7yGQyMW3atMhms/HOO+/E7bffvs7y/uUvf4nGxsaIiPjmN78Zo0ePXmWdzTbbLK666qqIeP+6ScuPEuzMNddcE5WVlauMf+UrX4mtt946Ijo+wg4AoJQoRgAAUqi1tTXuvvvuiIj4whe+0OW6O++8cwwYMCAiIhoaGgrjK34w2NnFldNg4403Lvz81ltvdblua2trvPDCC/Hkk0/GE088EU888UThw93lc93pzTffjL///e9F97fppptGRMRTTz0VS5cuXeN9Ln+MKz7uD2rFbdb0FFHrm5tvvjki3i8GuyqjNt100xg6dGhEFL//VzZ27NjIZrPdku2YY44p/NzRRdhvu+22Qrkxbty4LvN3ZPnv7lNPPRV/+ctf1iJp93nnnXfixRdfLHqvr1hK/vWvf13nGdrb2+MrX/lK4TRbP/vZz+JTn/rUardbunRptLS0xNNPP13I/sorrxRK13WZfcXSpbOCOyJi1KhRhVP9dVXUDB06tNNT5GUymfjkJz8ZEe9ffB4AoJS5xggAQAo9+uij0d7eHhERX/7yl+PLX/7yB9puxaNEhgwZEv/xH/8R9913X0yfPj3mzp0bRx55ZOy7777xqU99ao2ueZCkFcuQjr4l3dzcHBdeeGHcfPPN0dzc3OW+Xn/99dh+++3XKs+8efNi+vTpMWfOnKLne2Xt7e3x5ptvrvF1RjbZZJNYuHBhvP3222ucbcVtOnqu0qK5uTn+/e9/R0TEmWeeGWeeeeYH2q6r16M7r7fymc98Jrbccst47bXXor6+vugaFRHFZcnRRx+9xvv/8pe/HOeff34sXrw4Ro0aFZ/5zGfikEMOib333jt23XXXNS5aPqzXX389Lrroorjxxhvjueee6/KIq+VHOq1LZ555ZqEwmzRpUpfP7dKlS+Oqq66KX/7yl/Hoo4/GkiVLOl13XWZ/4oknIuL96zJ94hOf6HLdPffcM55++ul47rnnYsmSJR1ey2mnnXbqch+bb755RKy+RAYA2NA5YgQAIIVee+21D7Xdu+++W7T861//OmprayPi/W+f//CHP4wDDjggNt1009hnn33iyiuvjLa2trXOuy4t/9CyvLw8Ntlkk6K5OXPmxC677BKXXXbZakuRiIj33ntvrbL8/Oc/j2HDhsW1117b5Yfwa3N/y4/+aW1tXePt58+fX/h5+bfh06i73v8r6s7TxZWXlxfKyr///e/xwAMPFObefvvtwmnURowYsdoPsjuy0047xa9//evYbLPNYtmyZfGHP/whTjjhhBg6dGhsueWWcfTRR6/zUyU9/PDDsdNOO8X5558fzz777GpPQ7e2v1ur88tf/jKmTp0aERGHHnponH/++Z2u+8Ybb0RtbW2cdNJJ8dBDD3VZikSs2+xvvPFGRLxfWJSXd/29xUGDBkVERD6fjzfffLPDdVZXaC8/tVoul1vTqAAAGxTFCABACq34odaMGTNi3rx5H+h23nnnFe1n8ODB8cADD8Ttt98eJ554YuHb5kuXLo377rsvTjjhhNhtt93i2Wef7emH+IG89tpr8corr0RExMc+9rGiuddffz2+8pWvxLvvvhsbb7xxTJ48ORoaGuK1116LxYsXRz6fj3w+H3fccUdhm7W5xsjf/va3+Na3vhXLli2LLbfcMv7nf/4nHn744ViwYEEsWbKkcH8///nP1+r+lh/Z0N7evsan+HnkkUcKP+++++5rfN/rixXf/+ecc84Hfv9fe+21ne6zu06jtdxXv/rVws8rHiFy4403FgqaFddZU0ceeWS88MILMWPGjPj85z8fW2yxRUS8/76fOXNm7LPPPjF+/PjCkWXdacmSJfGlL30pFixYEL169YpTTz017rnnnvjXv/4VbW1thff63//+98I2a3v9nq40NDTEN7/5zYiI2G233aK+vr7La6ucfPLJ8fDDD0dExOGHHx6zZ8+OF198Md59991ob28v5F9+bZJ1mX25njrKBwCA9zmVFgBACq34bf++ffvGbrvttlb7O+CAA+KAAw6IiPcvyn377bfHVVddFXfeeWf8/e9/j7Fjx8ajjz66VvexLtx2222Fn/fee++iuf/7v/+LhQsXRkTE7373uzjwwAM73Mfyb2yvreuuuy6WLVsW2Ww27rnnnk6PBFjb+9tnn33it7/9bUS8f8H4D3INheVmz55dtJ8VrfhBclcfpr/zzjsf+P7WlRXf/7169Vrr9/+6MGzYsNh1113jySefjN/85jfxk5/8JDbaaKNCSdKrV68PfAq8zlRVVcVxxx0Xxx13XEREPP3003HTTTfFpZdeGq+88kr84he/iE9+8pNx8sknF7bpjtf5zjvvLFyj4oorrohjjz22w/W663erKy+99FIcccQRsXjx4hgwYEDMnj17lSPHVtTa2hqzZs2KiIi6urqYOXNmp+t2dlRGd1p+aqsFCxbEsmXLujxqZPlRaJlMpluPcAIAKEWOGAEASKFPfOIThW8Y33///d267/79+8fYsWPjjjvuiDFjxkRExGOPPRbPPfdc0XpJf8M5n8/HJZdcUlg+4ogjiuaffPLJiHj/g8fOSpGIiKampi7v54M+zuX3t/vuu3d5eqTV3d/qHHXUUdG7d++IiLj22ms/8LVGGhsb48EHH4yIiD322KNwQfLlVvwwuasPhFd39FBPvC+23377qKqqiojuf/93p+VHhLzxxhvxxz/+Mf75z3/GXXfdFRERn/3sZ7v9dGY777xznHHGGfHggw9Gv379IiLiN7/5TdE63fE6L3+vR7x/0frOrO17fXXeeeedOOyww2L+/PnRq1evuPHGG2PIkCFdbvPcc8/F0qVLI6Lr7H/729+6/N3qrvf58lJvyZIl8dhjj3W57l/+8peIiNhhhx06vL4IAAAfnGIEACCFtthii8KRAr/61a8KF6LubsuPIolY9QLEFRUVERGxePHidXLfq3PBBRcUPigcNmxYHHTQQUXzy5Yti4iItra2Tr8Z/+677xad5qgjH/RxLr+/rr5p/69//avoqI0PY+DAgTF+/PiIeP8b5N/97ndXu817770Xxx9/fGH5e9/73irrrPiBclcfaP/617/u8r6WP18R6+69kc1m47Of/WxERPzpT3+Kp59+ep3cz9oaN25c4QiNX/7yl1FfX194L67NabRWZ5tttokdd9wxIlb9ve2O13n5ez2i8/d7e3t7/OxnP/tAeT+MfD4fRx99dKFMuPzyy1c5CqojHyR7RMSVV17Z5X66632+Yml7zTXXdLpeQ0NDPPXUU6tsAwDAh6MYAQBIqbPPPjsi3j81zBe+8IXCaaM6snjx4rj88suLLqT+2GOPdfkN5Xw+H7fffntEvP/t6O22265ofquttoqIiH/84x89cg7+5d5+++04/fTT48wzz4yI908ldvXVV6+y3g477BAR75cfK39rPuL961Qce+yxhWuUdGb543zttdfirbfe6nS95ff33HPPFV1se7l33303vvKVr3TLhZynTp1a+ID7yiuvjO9+97uFb8Gv7PXXX48xY8YUToX2pS99Kb74xS+ust5uu+1WOK3PZZdd1uGHvb/5zW/ihhtu6DLb8ucrIoquMdHdzjzzzMhms9He3h5f+MIXoqWlpdN1c7lc1NfXd7nOurD11lsXysU//OEPhaJg8803j8997nMfer+///3vu/x9f/nll+Nvf/tbRMQqR1B0x+u8/L0e8f4p5Dpy5plnFl3TprudffbZ8bvf/S4iIr7zne8UrjGyOh/96EcLR3v84he/6PDfrptvvjkuu+yyLvfTXe/zkSNHxvDhwyMi4mc/+1nRNY+WW7RoUaHYLCsrixNOOOFD3x8AAO9zjREAgJT67Gc/GyeffHL85Cc/iXvvvTd23nnn+Na3vhV777139O/fP9555514/vnn47777ovf/va38eabb8YxxxxT2P6xxx6Lr33tazFixIg49NBDY9iwYTFo0KBYunRpvPDCC3HttdcWruExZsyYog8CIyL22muvuPbaa+O1116LU089NcaNG1c4vVGvXr2ipqbmQz2upUuXxhNPPFG0vHDhwnjxxRfjgQceKLp2SFVVVdTX18cnP/nJVfbzpS99Kf7rv/4rFi9eHF/72tfisccei//8z/+MqqqqePLJJ+PSSy+Nhx9+OEaNGtXl6Zj22muviHj/G/Df+ta34tvf/nYMGDCgMP/Rj340IiKOPvrouPTSS6O9vT0OOeSQ+O53vxt77713VFRUxMMPPxzTp0+P5557brX390FUVlbG7Nmz46CDDopXXnklLrzwwrj55pvj61//eowYMSKqqqritddeizvvvDOuueaaWLBgQURE7Lvvvh2WSBER5eXlcfzxx8f5558fTzzxROy///4xadKk2HbbbWP+/Plxww03xHXXXRd77bVXh8XPys9XRMTEiRPjrLPOiq222qrwYfR2223X5XUUPqihQ4fGhRdeGBMnToynnnoqdttttzjuuONi//33j4EDB0ZbW1u8+OKL0dDQEP/3f/8X//rXv2LevHlRXV291ve9Jr761a/GbbfdFkuWLInnn38+It4/hdPanArp4osvjrq6ujjkkENi//33j5133jmqqqrizTffjKamprj00ksLBdy3vvWtom2743U+6KCDYsstt4zXXnstzj777HjxxRfjiCOOiAEDBsTzzz9f+IC/O97rHbnzzjvjv//7vyMiYtddd42vf/3rRf9mrGyjjTYqHEHTv3//+OxnPxu33HJL3HrrrTF69Og44YQToqamJl577bW48cYb47rrrovtt98+Fi5c2OnReNtuu21UV1dHS0tLXHjhhVFdXR0f+9jHIpvNRsT7R3Z1da2TFf3sZz+LPffcM5YsWRKf/exn49vf/nYceuih0a9fv3j00Ufjxz/+ceGaLqeffvp6eU0dAIDUyQMAsF6LiHxE5D/96U+vMtfe3p6fMmVKvry8vLBeZ7d+/fr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+ },
+ "metadata": {}
+ }
+ ],
+ "source": [
+ "plt.figure(figsize=(20,10))\n",
+ "sns.boxplot(data=X_test_num)\n",
+ "plt.title('Test Data Outlier Visualization', fontsize=20)\n",
+ "plt.xticks(rotation=90)\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "W6linSv26KW-",
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "outputId": "aaa8b8c3-9b9d-43f1-e910-b9d31041845d"
+ },
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "(1281,)\n",
+ "\n",
+ "After Removing Outliers:\n",
+ " (array([ 0, 1, 2, ..., 1278, 1279, 1280]),)\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Identifying outliers in X_test\n",
+ "X_test_outliers = (z2 < threshold).all(axis=1)\n",
+ "print(X_test_outliers.shape)\n",
+ "z2 = np.abs(stats.zscore(X_test_outliers))\n",
+ "print('\\nAfter Removing Outliers:\\n', np.where(z2 < threshold))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "-U5fawTBVMox",
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "outputId": "8b29916c-4457-46f2-edad-af1b5e2241f4"
+ },
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "\n",
+ "After Removing Outliers:\n",
+ " (array([ 0, 0, 0, ..., 3842, 3842, 3842]), array([0, 1, 2, ..., 3, 4, 5]))\n"
+ ]
+ }
+ ],
+ "source": [
+ "#\n",
+ "X_test_outliers_removed = X_test_prepared[X_test_outliers]\n",
+ "print('\\nAfter Removing Outliers:\\n', np.where(z1 < threshold))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "uuTKxfBNVMox",
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 444
+ },
+ "outputId": "3263769e-d42f-405b-c3fb-43e5aaa76b96"
+ },
+ "outputs": [
+ {
+ "output_type": "execute_result",
+ "data": {
+ "text/plain": [
+ " age bmi alcohol_misuse health_gen health_ment health_phys \\\n",
+ "0 54.0 26.0 0.000000 1.000000 2.0 0.000000 \n",
+ "1 50.0 22.0 1.000000 1.000000 7.0 1.000000 \n",
+ "3 57.0 22.0 6.000000 1.000000 0.0 0.000000 \n",
+ "4 73.0 20.0 2.000000 2.486665 0.0 0.000000 \n",
+ "5 72.0 29.0 0.000000 3.000000 0.0 0.000000 \n",
+ "... ... ... ... ... ... ... \n",
+ "1275 27.0 23.0 2.391473 1.000000 3.0 0.000000 \n",
+ "1276 57.0 34.0 2.000000 4.000000 10.0 0.000000 \n",
+ "1278 63.0 26.0 9.000000 3.000000 10.0 3.000000 \n",
+ "1279 31.0 21.0 4.000000 1.000000 5.0 0.000000 \n",
+ "1280 67.0 28.0 9.000000 4.000000 0.0 4.111141 \n",
+ "\n",
+ " amount_activity_active amount_activity_notactive chol_check_checked \\\n",
+ "0 1.0 0.0 1.0 \n",
+ "1 1.0 0.0 1.0 \n",
+ "3 1.0 0.0 1.0 \n",
+ "4 1.0 0.0 1.0 \n",
+ "5 1.0 0.0 1.0 \n",
+ "... ... ... ... \n",
+ "1275 1.0 0.0 1.0 \n",
+ "1276 1.0 0.0 1.0 \n",
+ "1278 1.0 0.0 1.0 \n",
+ "1279 1.0 0.0 1.0 \n",
+ "1280 0.0 1.0 1.0 \n",
+ "\n",
+ " chol_check_notchecked ... history_heart_disease_False \\\n",
+ "0 0.0 ... 1.0 \n",
+ "1 0.0 ... 1.0 \n",
+ "3 0.0 ... 1.0 \n",
+ "4 0.0 ... 1.0 \n",
+ "5 0.0 ... 1.0 \n",
+ "... ... ... ... \n",
+ "1275 0.0 ... 1.0 \n",
+ "1276 0.0 ... 1.0 \n",
+ "1278 0.0 ... 1.0 \n",
+ "1279 0.0 ... 1.0 \n",
+ "1280 0.0 ... 1.0 \n",
+ "\n",
+ " history_heart_disease_True history_smoking_False history_smoking_True \\\n",
+ "0 0.0 1.0 0.0 \n",
+ "1 0.0 0.0 1.0 \n",
+ "3 0.0 1.0 0.0 \n",
+ "4 0.0 1.0 0.0 \n",
+ "5 0.0 0.0 1.0 \n",
+ "... ... ... ... \n",
+ "1275 0.0 1.0 0.0 \n",
+ "1276 0.0 1.0 0.0 \n",
+ "1278 0.0 0.0 1.0 \n",
+ "1279 0.0 1.0 0.0 \n",
+ "1280 0.0 1.0 0.0 \n",
+ "\n",
+ " history_stroke_False history_stroke_True vegetables_False \\\n",
+ "0 1.0 0.0 1.0 \n",
+ "1 1.0 0.0 0.0 \n",
+ "3 1.0 0.0 0.0 \n",
+ "4 1.0 0.0 0.0 \n",
+ "5 1.0 0.0 0.0 \n",
+ "... ... ... ... \n",
+ "1275 1.0 0.0 0.0 \n",
+ "1276 1.0 0.0 0.0 \n",
+ "1278 1.0 0.0 0.0 \n",
+ "1279 1.0 0.0 0.0 \n",
+ "1280 1.0 0.0 1.0 \n",
+ "\n",
+ " vegetables_True walking_diff_False walking_diff_True \n",
+ "0 0.0 1.0 0.0 \n",
+ "1 1.0 1.0 0.0 \n",
+ "3 1.0 1.0 0.0 \n",
+ "4 1.0 1.0 0.0 \n",
+ "5 1.0 1.0 0.0 \n",
+ "... ... ... ... \n",
+ "1275 1.0 1.0 0.0 \n",
+ "1276 1.0 1.0 0.0 \n",
+ "1278 1.0 1.0 0.0 \n",
+ "1279 1.0 1.0 0.0 \n",
+ "1280 0.0 1.0 0.0 \n",
+ "\n",
+ "[1012 rows x 28 columns]"
+ ],
+ "text/html": [
+ "\n",
+ " <div id=\"df-bf3dfd43-817e-44a2-952e-0f8530bff718\" class=\"colab-df-container\">\n",
+ " <div>\n",
+ "<style scoped>\n",
+ " .dataframe tbody tr th:only-of-type {\n",
+ " vertical-align: middle;\n",
+ " }\n",
+ "\n",
+ " .dataframe tbody tr th {\n",
+ " vertical-align: top;\n",
+ " }\n",
+ "\n",
+ " .dataframe thead th {\n",
+ " text-align: right;\n",
+ " }\n",
+ "</style>\n",
+ "<table border=\"1\" class=\"dataframe\">\n",
+ " <thead>\n",
+ " <tr style=\"text-align: right;\">\n",
+ " <th></th>\n",
+ " <th>age</th>\n",
+ " <th>bmi</th>\n",
+ " <th>alcohol_misuse</th>\n",
+ " <th>health_gen</th>\n",
+ " <th>health_ment</th>\n",
+ " <th>health_phys</th>\n",
+ " <th>amount_activity_active</th>\n",
+ " <th>amount_activity_notactive</th>\n",
+ " <th>chol_check_checked</th>\n",
+ " <th>chol_check_notchecked</th>\n",
+ " <th>...</th>\n",
+ " <th>history_heart_disease_False</th>\n",
+ " <th>history_heart_disease_True</th>\n",
+ " <th>history_smoking_False</th>\n",
+ " <th>history_smoking_True</th>\n",
+ " <th>history_stroke_False</th>\n",
+ " <th>history_stroke_True</th>\n",
+ " <th>vegetables_False</th>\n",
+ " <th>vegetables_True</th>\n",
+ " <th>walking_diff_False</th>\n",
+ " <th>walking_diff_True</th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " <tr>\n",
+ " <th>0</th>\n",
+ " <td>54.0</td>\n",
+ " <td>26.0</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>1.000000</td>\n",
+ " <td>2.0</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>...</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>1</th>\n",
+ " <td>50.0</td>\n",
+ " <td>22.0</td>\n",
+ " <td>1.000000</td>\n",
+ " <td>1.000000</td>\n",
+ " <td>7.0</td>\n",
+ " <td>1.000000</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>...</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>3</th>\n",
+ " <td>57.0</td>\n",
+ " <td>22.0</td>\n",
+ " <td>6.000000</td>\n",
+ " <td>1.000000</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>...</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>4</th>\n",
+ " <td>73.0</td>\n",
+ " <td>20.0</td>\n",
+ " <td>2.000000</td>\n",
+ " <td>2.486665</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>...</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>5</th>\n",
+ " <td>72.0</td>\n",
+ " <td>29.0</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>3.000000</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>...</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>...</th>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>1275</th>\n",
+ " <td>27.0</td>\n",
+ " <td>23.0</td>\n",
+ " <td>2.391473</td>\n",
+ " <td>1.000000</td>\n",
+ " <td>3.0</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>...</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>1276</th>\n",
+ " <td>57.0</td>\n",
+ " <td>34.0</td>\n",
+ " <td>2.000000</td>\n",
+ " <td>4.000000</td>\n",
+ " <td>10.0</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>...</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>1278</th>\n",
+ " <td>63.0</td>\n",
+ " <td>26.0</td>\n",
+ " <td>9.000000</td>\n",
+ " <td>3.000000</td>\n",
+ " <td>10.0</td>\n",
+ " <td>3.000000</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>...</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>1279</th>\n",
+ " <td>31.0</td>\n",
+ " <td>21.0</td>\n",
+ " <td>4.000000</td>\n",
+ " <td>1.000000</td>\n",
+ " <td>5.0</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>...</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>1280</th>\n",
+ " <td>67.0</td>\n",
+ " <td>28.0</td>\n",
+ " <td>9.000000</td>\n",
+ " <td>4.000000</td>\n",
+ " <td>0.0</td>\n",
+ " <td>4.111141</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>...</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ "</table>\n",
+ "<p>1012 rows × 28 columns</p>\n",
+ "</div>\n",
+ " <div class=\"colab-df-buttons\">\n",
+ "\n",
+ " <div class=\"colab-df-container\">\n",
+ " <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-bf3dfd43-817e-44a2-952e-0f8530bff718')\"\n",
+ " title=\"Convert this dataframe to an interactive table.\"\n",
+ " style=\"display:none;\">\n",
+ "\n",
+ " <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
+ " <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
+ " </svg>\n",
+ " </button>\n",
+ "\n",
+ " <style>\n",
+ " .colab-df-container {\n",
+ " display:flex;\n",
+ " gap: 12px;\n",
+ " }\n",
+ "\n",
+ " .colab-df-convert {\n",
+ " background-color: #E8F0FE;\n",
+ " border: none;\n",
+ " border-radius: 50%;\n",
+ " cursor: pointer;\n",
+ " display: none;\n",
+ " fill: #1967D2;\n",
+ " height: 32px;\n",
+ " padding: 0 0 0 0;\n",
+ " width: 32px;\n",
+ " }\n",
+ "\n",
+ " .colab-df-convert:hover {\n",
+ " background-color: #E2EBFA;\n",
+ " box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+ " fill: #174EA6;\n",
+ " }\n",
+ "\n",
+ " .colab-df-buttons div {\n",
+ " margin-bottom: 4px;\n",
+ " }\n",
+ "\n",
+ " [theme=dark] .colab-df-convert {\n",
+ " background-color: #3B4455;\n",
+ " fill: #D2E3FC;\n",
+ " }\n",
+ "\n",
+ " [theme=dark] .colab-df-convert:hover {\n",
+ " background-color: #434B5C;\n",
+ " box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+ " filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+ " fill: #FFFFFF;\n",
+ " }\n",
+ " </style>\n",
+ "\n",
+ " <script>\n",
+ " const buttonEl =\n",
+ " document.querySelector('#df-bf3dfd43-817e-44a2-952e-0f8530bff718 button.colab-df-convert');\n",
+ " buttonEl.style.display =\n",
+ " google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+ "\n",
+ " async function convertToInteractive(key) {\n",
+ " const element = document.querySelector('#df-bf3dfd43-817e-44a2-952e-0f8530bff718');\n",
+ " const dataTable =\n",
+ " await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+ " [key], {});\n",
+ " if (!dataTable) return;\n",
+ "\n",
+ " const docLinkHtml = 'Like what you see? Visit the ' +\n",
+ " '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+ " + ' to learn more about interactive tables.';\n",
+ " element.innerHTML = '';\n",
+ " dataTable['output_type'] = 'display_data';\n",
+ " await google.colab.output.renderOutput(dataTable, element);\n",
+ " const docLink = document.createElement('div');\n",
+ " docLink.innerHTML = docLinkHtml;\n",
+ " element.appendChild(docLink);\n",
+ " }\n",
+ " </script>\n",
+ " </div>\n",
+ "\n",
+ "\n",
+ "<div id=\"df-666167f6-2e23-493a-9a37-0f3e4bfbe104\">\n",
+ " <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-666167f6-2e23-493a-9a37-0f3e4bfbe104')\"\n",
+ " title=\"Suggest charts\"\n",
+ " style=\"display:none;\">\n",
+ "\n",
+ "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+ " width=\"24px\">\n",
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+ " <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
+ " </g>\n",
+ "</svg>\n",
+ " </button>\n",
+ "\n",
+ "<style>\n",
+ " .colab-df-quickchart {\n",
+ " --bg-color: #E8F0FE;\n",
+ " --fill-color: #1967D2;\n",
+ " --hover-bg-color: #E2EBFA;\n",
+ " --hover-fill-color: #174EA6;\n",
+ " --disabled-fill-color: #AAA;\n",
+ " --disabled-bg-color: #DDD;\n",
+ " }\n",
+ "\n",
+ " [theme=dark] .colab-df-quickchart {\n",
+ " --bg-color: #3B4455;\n",
+ " --fill-color: #D2E3FC;\n",
+ " --hover-bg-color: #434B5C;\n",
+ " --hover-fill-color: #FFFFFF;\n",
+ " --disabled-bg-color: #3B4455;\n",
+ " --disabled-fill-color: #666;\n",
+ " }\n",
+ "\n",
+ " .colab-df-quickchart {\n",
+ " background-color: var(--bg-color);\n",
+ " border: none;\n",
+ " border-radius: 50%;\n",
+ " cursor: pointer;\n",
+ " display: none;\n",
+ " fill: var(--fill-color);\n",
+ " height: 32px;\n",
+ " padding: 0;\n",
+ " width: 32px;\n",
+ " }\n",
+ "\n",
+ " .colab-df-quickchart:hover {\n",
+ " background-color: var(--hover-bg-color);\n",
+ " box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+ " fill: var(--button-hover-fill-color);\n",
+ " }\n",
+ "\n",
+ " .colab-df-quickchart-complete:disabled,\n",
+ " .colab-df-quickchart-complete:disabled:hover {\n",
+ " background-color: var(--disabled-bg-color);\n",
+ " fill: var(--disabled-fill-color);\n",
+ " box-shadow: none;\n",
+ " }\n",
+ "\n",
+ " .colab-df-spinner {\n",
+ " border: 2px solid var(--fill-color);\n",
+ " border-color: transparent;\n",
+ " border-bottom-color: var(--fill-color);\n",
+ " animation:\n",
+ " spin 1s steps(1) infinite;\n",
+ " }\n",
+ "\n",
+ " @keyframes spin {\n",
+ " 0% {\n",
+ " border-color: transparent;\n",
+ " border-bottom-color: var(--fill-color);\n",
+ " border-left-color: var(--fill-color);\n",
+ " }\n",
+ " 20% {\n",
+ " border-color: transparent;\n",
+ " border-left-color: var(--fill-color);\n",
+ " border-top-color: var(--fill-color);\n",
+ " }\n",
+ " 30% {\n",
+ " border-color: transparent;\n",
+ " border-left-color: var(--fill-color);\n",
+ " border-top-color: var(--fill-color);\n",
+ " border-right-color: var(--fill-color);\n",
+ " }\n",
+ " 40% {\n",
+ " border-color: transparent;\n",
+ " border-right-color: var(--fill-color);\n",
+ " border-top-color: var(--fill-color);\n",
+ " }\n",
+ " 60% {\n",
+ " border-color: transparent;\n",
+ " border-right-color: var(--fill-color);\n",
+ " }\n",
+ " 80% {\n",
+ " border-color: transparent;\n",
+ " border-right-color: var(--fill-color);\n",
+ " border-bottom-color: var(--fill-color);\n",
+ " }\n",
+ " 90% {\n",
+ " border-color: transparent;\n",
+ " border-bottom-color: var(--fill-color);\n",
+ " }\n",
+ " }\n",
+ "</style>\n",
+ "\n",
+ " <script>\n",
+ " async function quickchart(key) {\n",
+ " const quickchartButtonEl =\n",
+ " document.querySelector('#' + key + ' button');\n",
+ " quickchartButtonEl.disabled = true; // To prevent multiple clicks.\n",
+ " quickchartButtonEl.classList.add('colab-df-spinner');\n",
+ " try {\n",
+ " const charts = await google.colab.kernel.invokeFunction(\n",
+ " 'suggestCharts', [key], {});\n",
+ " } catch (error) {\n",
+ " console.error('Error during call to suggestCharts:', error);\n",
+ " }\n",
+ " quickchartButtonEl.classList.remove('colab-df-spinner');\n",
+ " quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
+ " }\n",
+ " (() => {\n",
+ " let quickchartButtonEl =\n",
+ " document.querySelector('#df-666167f6-2e23-493a-9a37-0f3e4bfbe104 button');\n",
+ " quickchartButtonEl.style.display =\n",
+ " google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+ " })();\n",
+ " </script>\n",
+ "</div>\n",
+ " </div>\n",
+ " </div>\n"
+ ]
+ },
+ "metadata": {},
+ "execution_count": 152
+ }
+ ],
+ "source": [
+ "X_test_outliers_removed"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "plt.figure(figsize=(20,10))\n",
+ "sns.boxplot(data=X_test_outliers_removed)\n",
+ "plt.title('Test Data After Outlier Removal', fontsize=20)\n",
+ "plt.xticks(rotation=90)\n",
+ "plt.show()"
+ ],
+ "metadata": {
+ "id": "3zK8zsbrbsij",
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 874
+ },
+ "outputId": "93497b54-dadb-4110-8318-144b29348e33"
+ },
+ "execution_count": null,
+ "outputs": [
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ "<Figure size 2000x1000 with 1 Axes>"
+ ],
+ "image/png": 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\n"
+ },
+ "metadata": {}
+ }
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "WeyCMteg6vAD"
+ },
+ "source": [
+ "# **Clustering**"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "CTnfzpGF62F-"
+ },
+ "source": [
+ "# Hierarchical Clustering"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "A6PPTQcPC5vq",
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 857
+ },
+ "outputId": "5c81557b-d428-46aa-e64f-a90c86d7e411"
+ },
+ "outputs": [
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ "<Figure size 1500x1000 with 1 Axes>"
+ ],
+ "image/png": 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\n"
+ },
+ "metadata": {}
+ }
+ ],
+ "source": [
+ "plt.figure(figsize=(15, 10))\n",
+ "linkage_matrix = linkage(X_train_outliers_removed, method='ward')\n",
+ "dendrogram(linkage_matrix)\n",
+ "plt.title('Hierarchical Clustering Dendrogram')\n",
+ "plt.show()\n",
+ "k = 2\n",
+ "clusters = fcluster(linkage_matrix, k, criterion='maxclust')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "RAcw16HwVMox",
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "outputId": "92211771-71a1-4a11-fe8c-f7b4bd2358e0"
+ },
+ "outputs": [
+ {
+ "output_type": "execute_result",
+ "data": {
+ "text/plain": [
+ "array([[-2.1265186 , 1.12458477, -0.91368302, ..., -2.14523677,\n",
+ " 0.46242242, -0.46242242],\n",
+ " [ 1.25914707, -0.59012349, -0.14956562, ..., -2.14523677,\n",
+ " 0.46242242, -0.46242242],\n",
+ " [ 0.89639718, -0.73301584, 0.61455179, ..., -2.14523677,\n",
+ " -2.16252492, 2.16252492],\n",
+ " ...,\n",
+ " [ 1.01731381, 0.26723064, 0.61455179, ..., 0.46614901,\n",
+ " -2.16252492, 2.16252492],\n",
+ " [ 0.23135571, -0.59012349, -0.91368302, ..., 0.46614901,\n",
+ " 0.46242242, -0.46242242],\n",
+ " [-0.13139418, 0.41012299, -0.53162432, ..., -2.14523677,\n",
+ " 0.46242242, -0.46242242]])"
+ ]
+ },
+ "metadata": {},
+ "execution_count": 155
+ }
+ ],
+ "source": [
+ "X_train_scaled"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "JhxT-L8JDZnS"
+ },
+ "source": [
+ "# KMeans clustering"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "WBa8H0CPDYGf",
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "outputId": "9b0e077f-8013-4c6a-8ff8-56c68a5ea935"
+ },
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stderr",
+ "text": [
+ "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
+ " warnings.warn(\n"
+ ]
+ }
+ ],
+ "source": [
+ "num_clusters = 2\n",
+ "kmeans = KMeans(n_clusters=num_clusters, random_state=42)\n",
+ "kmeans.fit(X_train_prepared)\n",
+ "\n",
+ "# Assign cluster labels to the original data\n",
+ "X_train['cluster'] = kmeans.labels_\n",
+ "\n",
+ "# Combine the cluster labels with the original training set\n",
+ "patient_df_with_clusters = patient_df.loc[X_train.index].copy()\n",
+ "patient_df_with_clusters['cluster'] = X_train['cluster']"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "_n7QT2oS-el2",
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "outputId": "cf9c9ba2-4e8c-4f51-a108-f57ea69451c4"
+ },
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "\n",
+ "Cluster 0 Characteristics:\n",
+ " age bmi alcohol_misuse health_gen health_ment \\\n",
+ "count 1672.000000 1672.000000 1672.000000 1672.000000 1672.000000 \n",
+ "mean 39.925239 28.043062 2.427071 2.276658 3.896035 \n",
+ "std 9.586597 7.570016 2.630642 1.011418 7.892525 \n",
+ "min 16.000000 0.000000 0.000000 0.000000 0.000000 \n",
+ "25% 33.000000 23.000000 1.000000 2.000000 0.000000 \n",
+ "50% 41.000000 27.000000 2.000000 2.000000 0.000000 \n",
+ "75% 48.000000 31.000000 3.000000 3.000000 3.099782 \n",
+ "max 54.000000 87.000000 24.000000 5.000000 30.000000 \n",
+ "\n",
+ " health_phys cluster \n",
+ "count 1672.000000 1672.0 \n",
+ "mean 2.666501 0.0 \n",
+ "std 6.924956 0.0 \n",
+ "min 0.000000 0.0 \n",
+ "25% 0.000000 0.0 \n",
+ "50% 0.000000 0.0 \n",
+ "75% 2.000000 0.0 \n",
+ "max 60.000000 0.0 \n",
+ "\n",
+ "Cluster 1 Characteristics:\n",
+ " age bmi alcohol_misuse health_gen health_ment \\\n",
+ "count 2171.000000 2171.000000 2171.000000 2171.000000 2171.000000 \n",
+ "mean 66.916628 28.196684 2.365043 2.647921 2.973086 \n",
+ "std 9.829606 6.526621 2.608045 1.122564 7.355046 \n",
+ "min 50.000000 0.000000 0.000000 0.000000 0.000000 \n",
+ "25% 59.000000 24.000000 1.000000 2.000000 0.000000 \n",
+ "50% 65.000000 27.000000 2.000000 3.000000 0.000000 \n",
+ "75% 73.000000 31.000000 3.000000 3.000000 2.000000 \n",
+ "max 104.000000 84.000000 27.000000 5.000000 30.000000 \n",
+ "\n",
+ " health_phys cluster \n",
+ "count 2171.000000 2171.0 \n",
+ "mean 5.218108 1.0 \n",
+ "std 11.075999 0.0 \n",
+ "min 0.000000 1.0 \n",
+ "25% 0.000000 1.0 \n",
+ "50% 0.000000 1.0 \n",
+ "75% 4.007641 1.0 \n",
+ "max 87.000000 1.0 \n"
+ ]
+ }
+ ],
+ "source": [
+ "# Explore characteristics of each cluster\n",
+ "for cluster_label in range(num_clusters):\n",
+ " cluster_data = patient_df_with_clusters[patient_df_with_clusters['cluster'] == cluster_label]\n",
+ " print(f'\\nCluster {cluster_label} Characteristics:')\n",
+ " print(cluster_data.describe())"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "giJ6Z-6XVMox",
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "outputId": "95488115-e681-4dd2-d2d2-b904fbdfd6df"
+ },
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "\n",
+ "Mean Value of Features for Each Cluster:\n",
+ " age bmi alcohol_misuse health_gen health_ment \\\n",
+ "cluster \n",
+ "0 39.925239 28.043062 2.427071 2.276658 3.896035 \n",
+ "1 66.916628 28.196684 2.365043 2.647921 2.973086 \n",
+ "\n",
+ " health_phys \n",
+ "cluster \n",
+ "0 2.666501 \n",
+ "1 5.218108 \n"
+ ]
+ }
+ ],
+ "source": [
+ "# Calculate the mean of each feature for each cluster\n",
+ "# Exclude non-numeric columns from the calculation\n",
+ "cluster_means = patient_df_with_clusters.select_dtypes(include=['number']).groupby('cluster').mean()\n",
+ "print(\"\\nMean Value of Features for Each Cluster:\")\n",
+ "print(cluster_means)\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "uEXHwfrMVMox",
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 472
+ },
+ "outputId": "f43aa744-aab6-4496-a109-aa24d25b7faf"
+ },
+ "outputs": [
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ "<Figure size 640x480 with 1 Axes>"
+ ],
+ "image/png": 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Z7qqgoCBT0TExMTExMbnNuJqwk9sqGPnMmTM8+eSTFCpUCF9fX2rWrMm2bdtutlgmJiYmJiYmtyi3jUUnJiaGJk2a0LJlS5YuXUpERASHDx8mNDT0ZotmYmJiYmJicoty2yg6Y8aMoVSpUkyePNm+rVy5cjdRIhMTExMTE5NbndvGdbVw4ULq169P9+7dKVy4MHXq1OG7775zeUxaWhrx8fG5/kxMTExMTEz+O9w2is7Ro0eZOHEilSpVYvny5bz88sv079+fqVOnOj1m9OjRBAcH2//M1HITExMTE5P/FrdNrysvLy/q16/Pxo0b7dv69+/P1q1b2bRpk8Nj0tLSSEtLs7/OSk+Li4szs65MTExMTExuE+Lj4wkODr6q+/dtY9EpVqwY1apVy7WtatWqnDx50ukx3t7e9lRyM6XcxMTExMTkv8dto+g0adKEgwcP5tp26NAhypQpc5MkMjExMTExMbnVuW0UnUGDBrF582Y++ugjIiMjmTFjBpMmTaJfv343WzQTExMTExOTW5TbJkYHYPHixQwdOpTDhw9Trlw5Bg8eTJ8+fTw+/lp8fCa3PqnJaSz7cTVLJq3g4snLBBUKpF2vljzUtx1BhfJfNvy/SGpyGnvW7SMlMZUy1UtRpmr+esqYmJiYXA+u5f59Wyk614qp6Ny5JMUl8fr9I4ncdczYkPmpVhRBWLFQPl//PkXLFr55At7i6LrOL6PnMWvsApITUuzbqzepwqBJL5kKj4mJyU3lPxGMbGLiiomDp3L0nxOGgpNDddd1SfSFWD56/IubJdptwaQ3fmbKsJm5lByA/ZsPM7Dpu5w7duEmSWZiYmJybdw2lZFNTJwRH53Aqmnr0DXd4X7dprN/y2Eidx6jYh2zmvaVnDt6gd++WOxwn67ppCSkMKHf9/j4+3Bo2xGsPlaaPnwPnV5uS+HSETdYWhMTE5P8YVp0TG57juw6ji1DczlGCNi36dANkuj2YsVPf6Iozn8KNJvO1mW7+Gv+Fi6cuMTpg2eZ9elCnq02iD3r999ASU1MTEzyj2nRMbntUVT3+rqUoFryp9cf2X2cZT+uNgKbwwJo+UQz6txfAyHE1Yp6SxJ1Ntqjc5Jatk9Q13QyUtN5t9NoZpz8Bv8gv+spoomJiclVYyo6Jrc9letXwDfAh5TEVOeDBNRpVdOj+XRdZ+KgKcyfsBTVoqDZdFSLwrLJa6h9fw1GzR+Cb4BvAUl/8wktGsLV5CTouiQ5IYVV09bzUN9210EyExMTk2vHdF2Z3Pb4+vvQuV97p1YJRVW4t1N9ilco6tF8v322mPkTlgKG2ybn///5cx+fPvd1AUh969D6qeZO45vcIYRgz/p9BSyRiYmJScFhKjomdwTPjOpB00fuAbJdVFkurUp1yzFkyisezWPLsPHr2PlO9+uazro5m++oLKSSlYrR6eW2cBUeOQFGAJSJiYnJLYrpujK5I7BYLQyb9Ro7V+3h9x9Wcf7YRcKKhND6qfto3LkBFqtnH/XDO44RdznB5RgBbF26645y1/Qb/yyBoQH89vli0lLS7dt9/L1JS07DmWdLl5JazavfIClNTExM8o+p6JjcMQghqNv6buq2vvuq57Cl2zxaJyMt46rXKAg0TePc0Yvomk6x8oWxelmvaT5VVen9weP0ePNhdqz8h5TEVMrVKM354xcZ2fVTh8coisAv2I9WPZte09omJiYm1xNT0TExyUGZaiVRLSqazXm6uq5LKta9OfV4dF1n/oSlzB63iMunowAIDAugc7/2PPHOI9es8PgF+tK0S0P764p1ytHz3a5M/+A3e2A2GG5Bbz8vPlw89I4KzDYxMbnzMFtAmJhcwZhnJrB6xl8OA3QVVaF4xaL8uO+LG55mLqVkfN/vWPztijz7hCKo16YWHyx6C9WiFvja+zYdZOHXyzmwNRJvHy+admlIhxdaU6hYaIGv5Q5pO4lMmQUZB0HxQ3i3Ap/2COF1w2UxMTG5MZi9rjzEVHT+2yQnpJAcn0xQeBBe3s4tH/FRCQxs+i5nIs/nUnYUi4Kvvw+f/TmK8neXuREi52LP+v0Mbj7c5ZghU16hzdPNb5BENx6Z9BMy4UOMPAot8/86qKUQoVMRFrMnl4nJnYjZ68rExAUHt0bybqfRPBz6DI+XeolHCvVmwivfE3Mh1uH4oEKBjN/0EU++242wYiEA+Ab60PGFNnyz85ObouQALJm0wmXRQ6EIFk5cfgMlurHItLXIhA8wmplluRYzFVHtLDLmWaR0H2NlYmLy38K06Jjc0WxfsZt3O45G12Uu64xqUQgrFsqEzaPdul90XXfZIuFG0bf+mxzecdTlmMBQf+ZGTXG4Lz4qgfioBEKLBOMf7H8dJLy+6FFPQMYO7MqNA0TIRIRPqxsnlImJyQ3BtOiYmDjAlmFj9JPj0TQ9T7yNZtOJOhvDpDd+cjvPraDkAASG+buNC/Jz0Irh4LYjDH3gQ7oWfpbedw2ga8SzfPD455yJPHe9RC1wpEyBjG24UnLAgkxbe4MkMjExuV24NX7BTUyuA5sWbSfuUjxSd2y01DWdP2dtIj7add2cW4UWPZq4bNWgqAqtejbLtW33n3sZ2PRddqz8x/D4YCh56+dspt89b3HywJnrKXLB4ZFLSgI3N+3fxMTk1sNUdEzuWE7uP+22kadm0zh35Paoctzy8aYUr1DE4TkpqoJ/kC8P9Wtv36brOp/0+grNpuWxaOmaTkpCKhNe+f66y10giABQirsZpCMsZvFCExOT3JiKjskdi6+/D7oTa05OfAJ8boA0146PnzefrH6PcjWNYGjVothTyQuXDmfc2pG54o12rdnLhROXXFq0dq3+l3NHb31FTwiB8H8G530qBAgf8H34BkplYmJyO2AWDDS5Y2n8cAMmvjbF+QABJSoWo/RdJW6YTFdL5K5jrJ+zmaS4ZNo+04Je7z/GgS2H0TWdao2r0KB97TyxRGcOnUUInLZvyOL04XMUK1/kOkpfQPg9BelbIG1N5oasE1MBgQj+AqEE3iThTExMblVMRcfkjqVo2cK0fvI+Vk1f79iqIeHpEd1veOG//JCSlMronl+yaeE2VIuCEALNpmPxUun/VR/aP3u/02N9A33dKjkA/kG3R2VjISwQ8j9ImYNM/hlsRwEv8GmL8H8WYa16s0U0MTG5BTEVHZM7mkHfvkh6agbrZm/KVhQ0HUURvDD2ae5/opn7SW4iY56awJYlOwDs7RcAMtJsjHt+IiGFg2nUsZ7DYxs+WBert4WMNOeBvIWKh1LlnooFK/R1RAgL+D2G8HvsZotiYmJym2AqOiZ3NF4+Xgz7dTDH3j3BmpkbSIxJolj5IrR+ujmhhYNvtnguObHvFBvm/+10v1AEP4+a7VTRCQwNoOvAjswcOz/by3MFT7/XA1Ut+JYRJiYmJrcKpqJj8p+gXM0y9iDeW52M9Aw2zt/K1JGzXI6TuuTQtiNcOh1FRMlCDsf0+uAx0lLSmT9hKUIRKIph0VJVhWc/fIIOz5vF9UxMTO5sTEXHxOQW4vLZaIa0HsmpA2c9PiYlMdXpPlVV6ftFb7oN7sjqXzYQdymewqXDuf+JpgSHm9XBTUxM7nxMRcfE5BZBSsnwhz7m1EHPlRwvHysRpRxbc3JSuHQEj7358DVIZ2JiYnJ7Yio6Jia3CHvW7+fwjmMej1dUhbbPtMDX//aoA2RiYmJyMzAVHRMTJxzZfZwVU9cSdT6WsCIhtHmmORVrl7tu621duhMhhMs2D1koqkLRshH0et/MPjIxMTFxhanomJhcgWbT+PzFb1k+eQ2qRUHqEqEozP1yCa2fuo/Xf+hrr0hckGSk23CaHnUFHV9sw9PvPXpbx9kkxSezccFWe9xQo4718PLxutlimZiY3GGYio6JyRVMGTaTP6YY1XfttWt0DYBV09YTViSEPmOfuuZ1zkSeY9+mQ6iqwt3Nq1GlQUWPCvz5Bfny6v+eB0BqFyBtPZAOlqpgrX1LF0AEIxbp17EL+HnkLNJTM1BUBV3TCQjx55UJz+VpTGpiYmJyLZiKjskti5SStJR0LFYVi/XGfFSTE1KYN/53pwqHlJJ5/1vKE+88gn+w/1WtEX0+hrG9vmL7H7vt24QiuK/bvfgF+ZEcn+z0WCEE7Xvfj5SpyLj3IHU+oGP0gJJgqQzBnyGsla9KthvB7E8X8sPQ6fbXWQ1HE2OT+Pip8Xj5etHskYY3SzwTE5M7DLOpp8kthy3DxtwvlvB0xVfoFPAkHXweZ2j7D9i15t/rvvbutXtJS0l3OSYjNYOdq69OlqT4ZAbdN5xdq/fk2i51yfrfNhNRKgyhOLfIBBYKoNtrnZCxA3IoOWB3edmOIKOfQNpOX5V8W5Zs543WI3nA53E6+D7O0Ac+ZMfKf65qLkekJKbw08jZzgcI+P6taR7FKZmYmJh4gqnomNxS2DJsDO88hm9em8r54xcBoynljlV7eKP1SJZPWeNmhvxx8dRltizZzo6V/5CanEa6GyUni/TUjKta7/fvVnHu6IVc7Ryy0DWdE3tP8+InT1GmWsk8+6vcU5EvN3xIeOHjmY0t884BGsgkZPIP+ZZt6ohfebfTx/zz5z5s6TYy0mzsWPkPb7Z9n9mfLsz3fI7YvHgHaclpzgdIOBt5nsM7jhbIerciUk9Api5HpixEZhy82eKYmNzxmK4rk1uKxd+sYNvyXXlcR1nujc9f+Ib67WpTqFjoNa1z+Ww04/t+x+ZF2+3WA99AH1o/eZ9Hx5e/++qqLC/7cbXjBqOZKKrCztX/8v2/nxN7KY4dK/eQkZZBxTrlqFCrLAB63DcYHbs1J7NokDIXGTjc43id3X/uZdr7c4z5tWwFKuvfk4b8TO37a1CpbnmP5nNGfFSCR5llcZcTrmmdWxEpbcjELyBpKpCt7ElrLUTwxwhLhZsmm4nJnYxp0TG5pZj/v98x4k0cI3XJsh9WX9MaUeeiebnuG2xevD3XDTclIZXF3/xBaJFgVIvjr4aiSqrdA2UqX92NOOZ8jMv9uqZz+Uw0ACERwdz/eFPa9WppV3KMQdE4tubkQKYAnludFvxvmdNzBlAtCgu/Xu7xfM4oUibCI7dU0bIR17zWrYaMHwFJ35FTyQEg419k1GNX7W40MTFxjanomNwy2DJsnDl83uWNUAJH95y46jXWz93CM5X6E3sx3qFlRUqIuRCHb6Avippb4VJUSWCwxuufHTRuTBn7nMvp5BzCSxRypccB4O3n7XqAWgy3X10RghCep2rv33zIoTstC82ms2/zIY/nc0b9drUIKRzs9BooiqBqo0qUqlLimte6lZAZhyBlNo7LB2ggE5FJk260WCYm/wlMRcfklkFRFRTV9UdSUQRePtarmn/L7zt4v/s41zEiGNaLpg/X5qHesfj6G+4hHz+NTs9c5qs/DlGifCqQjkwYnes4zaax6Js/eL7mINpZe9DRvycfPzWeyF3Z1Y7b9m7ptlTO0d3HSUtxLqPwfQTnbisABfx6uF7kCqze7r3YVq9r93RbrBYGTOyDQORxqymqgsXLQr8vn73mdW41ZOp8DHejMzRImYeUthskkYnJfwdT0TG5ZVAUhUYd67l0oWg2ncYPNcj33FJKvhvys0duE82mU7LsAV4edZy5B/9lQeQe5h36l74fnCWieJY7SIf0LXZ3Q1YQ9fh+33Fy32mkbqTGr/11A6/cM5TNi7cTuesYv46Z73b91KQ01s3e7HS/sN4Fvj2d7FWxaYU5tL85MRfj8uyVGfuQiRPQEz5BpixGSiP4+t5ODVwqmYqiXNV1d0TTLg35YPFQSlYplmu7rulUqF0OTXPjlrsGzh45z1cDfqRHiRd4OPQZBjUfztpfN6Dr129NALRLHgxKA+m8tICJicnVYQYjm9xS9BjSmU2LttnLwuREtSgUK1+Exp3zf8M9/u9JTuzzLAZCtSgULW0DFBRFx8fPxU1QPweUZN74pWxdtgtkbrE1m44Q8EGPz7B6W0hOcN5p3L6+VeXQ9iO0ebq50zEiaBioRZBJP4A0FBopBdvXhfNp/zBiLo1BKILGnRvw0rhnKFLa20hJT9+IYVkQSGwQHwwhX/BQv3Ys+mY5Upd5lEFFEXj5WunwQmu3sntK+VplSE5IRagCqWWvd3BrJIPvG877C9+kQfs6BbYeGAHXb3f4CFuGDT3TTbdv40H+Xb+fjQu28ubPr6KqBV/xGgC1sAeDfED4XZ/1TUz+w5gWHZNbimr3VuHt6QOwWC0IRaCoit3CU6xCUcb8Meyq2i/EXor3eKxm0ylfpw5uA34BlFCklMyf8LtTa5GUkJaSTmJccq6MJqdI8PJ27Z4TQkEEvIQovAERNp2/N73CE3Wq8u4TRYm5ZBwrdcmmRdt4peFbpJ9/DtK3ZJ0hkOkikfHImBcoXiaGkfPfxMvHmquOjxACb38fPlzyNuHFw9zL7iGT3viJmAuxuZQcMKw6uq4z5un/kZF+dSn8jkhNTmNEl7FkpGXYlZys9QDW/LqBxd+sKLD1rkT4dsG1u1EF30cQwnz2NDEpaMxvlcktR4seTajTqiZ/TFnLkd3HsXpbubdTfRo+WPeqe0xFlAr3aJwQgoYd61Ki6kMQ9aWb0QpSKUlyXDIXT152P7mHNfA0m8Y9D9b1aKwQXiQmV+P9np+TnppXOdJtOhWqnseqRLoQSkcmTqJBuy+Ydvxrlk9ey571+xBCULtlDdr2akFgaIBnwntAfFQC62ZvyqVw5JJIl8Rdjmfzou0069qoQNZc88tfJMW6qDiNYO4Xi3mob7vr0kJDWCoifR+HlF8c7FVBBCECXizwdU1MTExFx+QWJTg8iO6vP1Rg85WsVIxqjatwYMthl1aVtr1a0P+r5xG2FR7oJToiYzuqtV6ByalaFMrfXYa776vm8TFrZm4gI815EGuTB2KwZYDFqZFIg7TlSGkjJCKYHkM602NI5/wJng/OHbvoMsMLQLWonNx/psDW3L/5MKpFcbqulJKzRy6QGJtUoEpdTkTQcKQSBsk/Zqb/Z2KtgwgejVCLOT/YxMTkqjEVHZP/DH0/78Wg5sNBSnQHqeX9v36eTi+1A0Amp+TZ7xCZiq+/DzWa3sW+TYdcKlGKIhyum5OSVUrw/qKh+bIqnD92EdWiYMtw7BrxD9JwP50GMh2u0XUipWTvxoPs23gQoSjUub8GFeuUyzXGN8DH7Ty6rns0zlOMQGv31/R6dKXPQggVETgA6f88pP8NpIGlklko0MTkOmMqOib/Gao0qMhna0fy9YDJ7N9y2L69eMWi9BnzJE27ZDeSTEkrhUe3WUtFAB57qwvvdhztcIhqUQgrFsqlU1Eup+r5bjeeHNY13w1MA8MCXCpQp464qcsDoBQC4Zuvda/kTOQ5RnUbx9F/ThiKhTQUlhpN72LYrMGEFTWqWZeqUpySlYtx5vA5593aJTTpcs81yZOTem3uZskk5zE4iiKoWKccfoHXdg08QSj+4NPyuq9jYmJiYAYjm/ynuOueSozf9BE/7PuCj5a+w1dbP2bKwfG5lJz9Ww7Ts+LXHN3ng+bUI6SCVyOExWgF0bBDXfp9+aw9gBqwFxwsUiaCz/4cRZf+HQByWWuy/t3p5bY8M/LRq+rS3vzRe12mR6+YFY5w+U1XwPfxa4pNibscz+D7hnN87ykgO6gYjGKEr98/0l4bSAjBMyN7OFVyhCJo83RzipQpuOrI9z5UnyJlIpym0Ou65NEhDxfYeiYmJrcOQv6H2gTHx8cTHBxMXFwcQUFBN1sck1uQuMvxPFPpVZLjUyhXLZlxcyPx8tWx5NA/pFQRShCi0K8IS9lcx58/fpElk1Zy/N+TePt50eThhjR95B6sXlZSk9P4rM83rP9tM7Z0Q4MKDAvgsbe60P21TtekaHz+4jcs/X51nswvIUAoCj/uqEWxiCnkzdtXwVIREfYLCbGSP2dtIupMNCFFgmnRozEhEcEerT/9g9+Y+t6vLvt4vfZDX9r3zrZkLPhqGd8MnoKm6aiqgq5LdE2n5WNNeH1yP7eZZ/nl5IEzvNFqJNHnY4yrILHH7Tw94lGeGtG9QNczMTEpOK7l/m0qOiYmOZj58Tx+eGeGXRcoUT6NxwdcoEXnWKxekvRUwaG9NanZfjxCLe7xvMkJKbzRaiSHdxw1lJHM+RVVwS/Ql3FrR151o1AwChZ+PXAySyatROoSRVXQbBrB4YG8/mM/GnWsh0xZgkz6GmyZbjvhB76Pgv+rzPlsNZOHzUTL0FAsCrqmoygKPd/pypPDu7lVwnrf1Z/Th8453S8UQe0W1Rm7ckSu7XGX41k1bT3njl7AP8SPlo81oUy1Uld9HdyRnJDCqmnrWD93MymJaVSsXZYHX2xDxdrl3B9sYmJy0zAVHQ8xFZ3/LpqmEXsxHotVJTg8KNf2/ZsOER+dSNGyhfn4qfEc23Myz/FWLx2/QI2keBWfgEDmRU3JM8aWYWPjgq3sWv0vui6p3qQKzbvfi5ePF/979QcWffOHw2BlRVUoWq4wUw6Ov+bU5stno9kw72+S41MoWbkYjTrVw+qVbRmRUhpFDmUqqMURwodFE5czvt/3Tud8/oN7efTNJxBqUadjuhV+1m3H8fJ3l+HbXZ/m/6RMTEz+81zL/dsMRja5o8lIz2D2p4uY/7+lxJyPBaBinXI89lYXbOk2vh86ncuns4OEncVwZKQrxEUZ+5LjU5BS5lJKTuw7xdAHPuTSqShUqwoSlkxawbev/cQ7Mwey7MfVTjOydE3nbOR5dq7+l7qtal7T+YYXD6Nzv/ZO9wshIIclypZhY+qIX13OOePjv+j02CR8Qu9HBI1EqHljZ4qVL0J8dKJT15WiKpSoZKZPm5iY3HjMYGSTOxZbho1hnT5myvCZdiUH4Mju43zQ4zM+fmp8LiUH8Khysa7pvFDrNS6cMPoXJcYm8fr9I4k6GwOAlqGh2YxU74SYRIY9NIa0lHSXcyqqwsG/nRX1u378s26/W0tMcqLKjnUBkLYGGd0DqcfmGfPgi21dxufoms4Dz7e6VnFNTExM8o2p6JjcsSz9fhXbV/6T5wbs6obsKacyA1tTk9NYPnkNcZfiHSpJuqaTkepaycnCYvWshsuFE5f4ZfQ8Jg6awuxxi4g+H5Mv2XOSFJvk0bitqwOJvihAOwvJP+fZ36pnU+5uXg1Fyet6EwKaP9qY+m1rXbWcJiYmJlfLbavofPzxxwghGDhw4M0WxeQ6cGT3cb4a8CPvPTKWz/p8w+4/93rUeTwnC75e5kGJuKtDs+mcO3qBtb9uZP1vm13KpuvSnmrudIymU799bddjdJ2vB03mqfL9mDJ8Jgu/XsZ3b/7ME6VfYvoHv+X7+gAeu5N+nxZOz3rVGDe4OKlReV1dVi8rH/3+No8M7Jir0F9gqD9PjXiUodP6X5fWCiYmJibuuC1jdLZu3cq3337L3XfffbNFMSlgdF03Ancn/mGk/mo6qqqy9IdV1G9XmxG/vY6PnwcF8IDTB886L0hXAAhF8OesDaQkuu9I7u3r7XScoirUvr8G5WqUdjnH1OG/Mm/870aHdE2iZxZC1nTJlOEzCQj1dxmf44jyd5ehUt3yHNl93K3bTtcEK2aFEX0hgY9WyjyKi7evNy9++jRPj3yUk/tOIxRB2RqlCzxN3MTExCQ/3HYWncTERHr27Ml3331HaGjozRbHpID5dcwCFk38AzCsJkjs8S7blu/itRYjWPztCnt8jCu8fL2uq6xSlyTFpVCyius0c6EI7mpYiY4vtQXyBjwriqBG47tcdutOikti9meLXDYG/XnUbGwZznteOWPgty9g9bI4DcTOidQF29YEsXvtXqdjfP19qNKgIpXrVTCVHBMTk5vObafo9OvXjwcffJDWrVvfbFFMCpj0tAxmf7rA5ZhD247w5cuTeLJcXz584gtSEp33pGrevTGqJf8fcZHZDqBERefp1GAUmytSNtyt0iV1SaW65Th96CxqZo2anNgyNH4eNZthD41xqqhsXbaLjFTnihBA3KV49m486HKMIyrXq8D4TR9Rv10tT9pBoVpgxc9/5nsdT9E0jeN7TxG58xgpSe6tZSYmJiauuK1cVzNnzmTHjh1s3brVo/FpaWmkpaXZX8fHx18v0UwKgENbI0mI8Sw4FmDtrxuIvRjH2BXDHcZ/dBvckVXT16HrMl8ByEIIXvjkKS6diuKT3l85HafZdNbO3OjRnLM+WYhQhFM5pJRs/2M3Mz6ax9MOKvQmJ3h2w0/xcNyVlL+7DB8ufpvo8zE8VuIFly4/zUauLLaCQkrJ/AlL+XXsfHsGm7efNw88dz/Pfvg4vgEF34dK6kmQ8hsy5TfQL4JSFOH3KPg+jLjG3l8mJia3BreNonPq1CkGDBjAihUr8PHxrKvx6NGjGTly5HWWzKSguHwmn9lDEnat/pftK3ZTtnopfPx9CAjx59ieE6z8eR3RF2Jp8vA9bPl9h8cKgKIqjJz/JnXur4lm0/hz1ka2Lt/lkaKkWnQsVklaiuPsKU/m+HnkLAqXDs/VKgGMRpiecPHUZTRNQ+EiMvkXSF2B0SW7JsL/SYRXA5fHhxUNJaxYqF3RcIRqUYkoWcgjefLD1wMnM3/C0lzb0pLTWPj1cvZvPsy4te/h7etZfNbFk5dYPmUtF09cIig8iFY9m+WpPC31aGTUE6Ady9oCejQyfgQk/wJhPyMUz1pgmJiY3LrcNpWR58+fT5cuXVDV7JuIpmkIIVAUhbS0tFz7wLFFp1SpUmZl5FuQI7uP81qLESTFJef72Kx+RQChRYKJuRCHalGQ0khtztrnKW2ebs4bk/shhCAjPYNZnyxk/oSlxF6Mc3mcUCRSFzTvHMPLo86w/c9AJrxVktRkz9LGsyeCL9Z/QPXGVeybpJT0vmsA545ccNnAE+Ce9iUZ/s0qrF7pQNZYFdDA/yWUwMEuj/955GymfTDHZXDylxs/pFqjyh6ekHsO7zhK3/pvOt0vFMFLnz7DIwMfdDmPlNKQ//05CEVkWvokmi1vDy095kVIWwdoDmZSwac9SsjnV39SJiYmBca1VEa+bWJ0WrVqxZ49e9i1a5f9r379+vTs2ZNdu3blUXIAvL29CQoKyvVncuuhaRrvdPjoqpQcyK3IxFyIs2/TNT3fSg7Aip/+ZMuSHYCRNt3zna7MPP0tLR9v6vI4qRvusz8XhLL9zyBaPhzL+z8fQ1Hy9yyhqgpzPluUa5sQgiFT+mHxUt0GDW9dfoqpY0PJVnLAfjNP+gaZutzl8Q/3f8Do9O0ovknA/U80pWrDSrk2S+0SMn07MmM/Uub/mv/+3UqX8VRSShZ984fbeRZN/IOfR81GSpn5/mv2z8DaWRv5qv+Pxny2U5C2FsdKDsb21KVI7WI+z8TExORW47ZRdAIDA6lRo0auP39/fwoVKkSNGjVutngmV0lyQgr9G79D1LmrL3pX0CiqwsKvl9lfb168nddajGDNL395dLxQJPO/D0e1wN33JtGgVf5iwzSbzt+/78izvdq9Vfhy44fUbFbV5fFSChZNLURqsqOvt4JM+tHl8YGhAXzx1/s0erBertgnH39vHnuzC0OmvGLfLrUz6DH9kJeaIaMfR0Z1Rl5ug0xxHVR+JWciz7tWSqXRGd4Vmk1j2gdznE+hS5b9uNr4rGXswmUKGwA6MvZVZPp2N+NMTExuZW6bGB2TOw8pJSO7fcqhrUdutii50DWdo5mNPed+uYSJg6Y4rPjrDKkLjvzri5Sga9C6WwxbVuQv1iMrpT4pPpnda/eSkWajQq0yVKgZSNMHM/jnT1wGDKcmqUTu8aVGwyuDu3XI2IWUGkI4d6mFFQ1l5LwhXDodxZFdx7F4WajepAq+/tnxcVI7j4zqDnoMuaxH2ilk3BugxyL8n/HofIMKBaCoeTPScuIX5Do4+ND2o26DpHVNZ8uSHTzQ08P3M2M3MvpxCHwL4f+sZ8eYmJjcUtzWis7atWtvtggm18CBvyPZseKfG7qmq8ynnPgF+HD2yHkmDp4CGNWN84NqkQhhpGIXKuI6LfxKFEVQqW55vntzGvMn/E56jrTyWk0SqdkoCSiMu1zwggi+iyhZyGngsUz4MlPJcez+kQljwLcTQglzu06LHk34c9Ymp/sVi0Lrnve5nCMtOc3lfjDe/7TkNPCqj2HQdudmM/bLhI/BWgfhVcftGiYmJrcWt7WiY3Ljibscz5JJK1k1fT1JcUmUrFKcTi+1o+kj9ziMk3LFvPG/XycpnXP3fdXYs36/S8uBoiq06NGE379biaK4tjI4Pl5yT6a7ymaDC6fzV7hQ1yWqVWX2pwvztHXYs9mfo/u8kdK1kuPto1O+mqMaQwpYa7u05niC1JMhdRHOY1wAdEhZCP693M53b6f6VKxTjqP/nMhzvRVVwdffJ1cgspQSMrYh0zYBOsKrDiWr1HCryEpdUqZ6KYRaFOnTHlKXuzmHLFRk8s+momNichty28TomNx8Th08Q5+ag5kyfCYn958m6mwMe9bt54MenzGy66f5rsr771/7r5Okztm9di9CEVi8LA7dUYqq4Bvow4MvtuHYv6fyreSAROrQ9SWjiKDFAn/86tyiIXLIkBVk3LhzA/ZuOOiwd5WuCZLiLRQqko6iOr6hK4qk/RNR+Ac6kl0vGBeMHgW4a1aqILXTHk2nWlTG/DGMWs2rGUeqij04uXDpcD5d/R5FykQAILVzyKguyOiekDQRkiYhY/oQZu3OvQ/e5TRYW1EUipYrTO2W1QEQQe+D1dP4Pg3S//ZwrImJya2EadEx8Qhd1xn+8FjioxJyPTFnKQKbF23nl9HzeGp43mJ3jkhLSePS6ajrIqs7tAwNoWanHquZXcO1DI2QiCA+WDyUsKIh+PgkIhRwnUSUfS2EAAS89vkpqjdIRtdh8x9B7Fwf4PxoXaIoAtWqUrl+BR5+5QH2rN+PalHtcTpXomuC5CSF8GIZXDpjNSSQwp7eXv2eJJ59+9wVR2Wll/dF+LR1f5HcoQQZJ+vSQSYRSojHUwYVCmTsyhEc2X2crct2YUu3UeWeitRrczeKYigvJ/YfYfEXAzm8W8PLuzz3to2ndfdo/IMA7Rwvj1jBwe3VibmYgJ4juFmxKFitFoZOH2CfSyiByODPjZo5yT8D7motKcj0nZCxB4QVvJoiLKU8Pj8TE5Obg6nomHjErtX/cvrgWaf7pZQs+N9SHh/aBYvV/ccqLTk9f0Ek7u6p+URqElRo8EAdSlQoipSSms2q0vjhBlisFmT8CO69fwXr5pZxM1O2YFJCUIhGheoppKYIlkwN58fRRfEkluaZkY/RY0hnANbN2YSuuXanpCRamLLxX1bPDeWPX8OIi7JQtEwaHZ6MpkXnWKxeMntdpSh41Uf4PYHwquf22niCUIKRXk0hfQPO41w08HFd9yYnUrsM2inKV/On/N2d81S7nvvlEiYOnoKieKNrAoRk118BTP+iMB//epTy1VIpXDyGCWsq8+v4QiybvIa05DRUi0Kzbo3o+U43ylYvZV9Lxr8HaStdyJ8TFWQKMroHOd9P6d0WETwaoThXZk1MTG4ut03BwILgWgoO/deZOuJXfhk9z6mVIYuXv+hN577tUC2uY0A0TaNbxHMkxjpr+ZD1sRT4+mukJCl41IjJAV2ev8i+7f4c3OkPSMrelYpfgM7Z416kpgTw2+XJuZpPyuTpyPiRpKcJXmhZhYunvNC0K9fOoUhcsd3qBV6+kBTnubyFS4cz/fhEACa88j1LJq10ca0l1eon8dmCI2TpAlnFEXVdzXTJ2UCEYvP/nPULNE7s3U94kdOUvqsEFe/pSEBoCZfySD3OsF6gI6zVEGrevl8yPTMjCY28WqgAny6IoDdBJoMSjhCOqxpL7Qwy/iNIW4Vd6VBLIwIGInw7ArDtj90Mbf+Bw+MVVRIcZmPq5v14+0pQSqAUXoMtw0ZCTBL+Qb54+WTHSUk9DhnVFbQzeBafY1+JvEqRAta6iLBpCGFGApiYXC+u5f5tWnRMPCLLzeOOiQMns/CrZXy8/F2Kli3sdJyqqnR8sQ2zPl2YJw7GYtUpVjadavWTaNohjvotE9i2OpBRz5clIz1/NxPVouMboPPlokiWzgijdtNEipc1Ykt0DTYuCybh0kEKlTRiNaTUkUk/AODlLRkz6wjvPFGeU5E+qBYJSDRNoAhwXKBYkJEOmqYghHQYZ+OIiycvk5GegdXLSttnWrDwa8dF/Zp1jKX30HOUKJcdH5Ol5GxdHUDpmq0pUiYUYa3J7s3F+fjJL+jR7zBPvBCNl48hS0bCZ2xbXYkStcdTrEL5XPNL22lk3FDI2JK9DZBqVUTIJwhrdjVk4VULQr/LTCW/jOEe0wEBXi2MNPOLDTMH+yJ9uyMC+iGU0Oy5tXPIqG6gx5I3RX0w6DEI/6eY9ckCp+nnuiaIuWTlz4UhtO0RA9JQni1WC6GF86b1y6SpoJ3GY0uOfZzjmCcytkH6evBu7sF8JiYmNxrTomPiEbv/3MvrLd/zaKxiUShatjA/7P3cpRsrKS6JAU3e5eSBM0hdMmDMSao1SKZo6Qx8/HLfVHQN5n0XwaRRnvV8ssuiSHoPPUf3vpcQwoi3yfngbbOBaimEEjEXoRZDt52Cy61yzaFpsG1NIH+vCsKWLqhQI4X4GJWfPy3mcE0hBFXuqcipg2dIik32KKVdsSgsTf0FRVGQeiIfde/Jn/OtubKr2j4WxWufnUbXQXGg70kJuk9frKEDOfbvSV5tOIQRkw9Ru0kiVybEaTY4sjcA/7K/UapKOeN42ynk5YcAZ1Y2AcGfovh2umJdm9FKQTsKwh+JgPgRxvhcyoEKaklEoV/tKed67FuQugDnlhUrMnw9D/i85PIaKqrkvk6xDP36NFjvRik0C03TyEiz4e3rlcsNpl9sajTwdIUIA7UEeDeEpNmAq/YfKvh0QAkZ53pOJ1w6HcX63zaTGJNEsQpFaNa1ET5+nvX0MjH5r/CfaAFhcnO5+75qlKtZ2mWZ/ix0m87ZyPNsXOC6y7x/sD+fr3+fJg/fQ5FSaTzQM4ayd6XlUXIAFBUefOYyfgH5cTWArguaPBBnd/Fc6V2wWEAQa9SEAUj4X545VBUatk7g1dFnGDTuNB2ejDJcJE6QUuIf5MuvZyYxZMorNHqwrls5rV6WbDdeyq+88cUBHn7+MlYv41r4+Gn0ff8sUjpRcrI8PulTkTKF2Z8upMH90dS7L6+SA0Z9n0p3J7Jp9ojsOeJH41zJAZAQ9zoybUOurUJYED73I/yfB5+HIGF05p4r30cNtNPIxPGZMid5kKJuQyYvcqsoSkmme1HnxPEOfPz0eDr6P0mngCfpXuQ5pgybSVJc5rnpl1zOBYBaFCX8N5TAIbi+JpnnpUe7n/PKo2wa41/5np5lX+ab16YyY/Rcxj7zPx4t9jyrPazCbWJi4h5T0fkPcv74RX54ewavt3qPtzt8yPwJS7NvAk4QQjBy/hAKFXdf/A2M9OCNC10rOgD7Nx9m86Jt1GqSmEcJuRIfX0mVOp73w1IU4ym/RHl3adAapC5Ct52EtPlu57VYYd9W58GniqpQpUFFvH29afN0c0bMfYNi5Ys4HFuyQipd+lzi4edOs3XBV4brLHk2FqvkpZFnmbl7L8N/OMbHvx7Fx09HOAn7EQogDeVBpm3nz1kbadcjCs1Fxr/UoXqdfzh37AJSi4L0VW7PHSQydjBSOimCmPo7yBScuzk1SJ6LlCmZ7i53xRRVFM5QoXbZXKn4DsSiat1k/t1xL680+4O1MzdgSzdOPu5yAr98PI9X732H+OgEEB5UqbbtR9oyK3YreeOTrpQR1XXMkyO+HjSZxRP/QOoSqUu0DEPhS0lIZfSTX7LFQRsQExOT/GPG6PzHWD5lDZ/1+QbITA0XsG35bn4aOYvRS98hISaJLYu3k5GWQYXaZWn15H34BRql94uVK8J3ez5j+eQ1fD1wsst1pC5zVfR1RFpKGh/1/ALNpqMq2bEmruj9YQ/iXtnL0X9OAOAf4k/VRpXYuXI3uq5nNtAUaDZBw7bxvPb5Sc8uDBngYX+mtLRgNq8IdDmmQ5/W9n+rqkrZmqU4d/SCfZtfoMaQ8Se5t108umacu2r5EXn5D9Cy+34FBOs0ecAoPujOySwUWL8kiKaPp5KemkGRUumoLr7higpFSqZz/PB5ipYAj9PaZIzRENOnTd5dtqMYPyuuaiqlgnYhM0Xd7WIIJYSuA5swtldeaxuAEBKrt6TVUw/T977DZKSn5LEA6ZrOqYNneKXBW5S5626Kl4qk/RNRlKmcu5ry5XMWYi5ZCSusUchvOiJoOMKvBzLxc1xllwlfz8oqZHHpdBSLJv7hNIZLCMGUYTNp2MG9NdDExMQ1pqLzH2LfpoOMe25i7h9XCRJJUmwS/Ru/g67p9owpTdOYNORn3p4xkHs71QfAL9CXLv07sODrZZw5fM7pvVEIKF/TdWr2ujmbSYo1LDT7tvm7VXLAwl2NO/Ptrt5kpGdgy9Dw8fNGCEHMiamsnPItZ4974x+o0fyhWCrUcFcXJcdl0GHGh7N47FUcunpy4h3+Nu16X2Dp96tQFGFvD6FaFHRNMvi7l+zF7bJIiM62mAkhGTX1GNXqG9uUnOtpZ7mWPPqFP4bT7OkqFC1bmJhLRyhZMc3p+UgJiQmK0UNKyd9PgUzbjHCg6BgWGg+CfIUfQglDejWG9C247CLu8yCtnyrNP+v3seyH1bmCklWLghAwbNZgDvyrEHXWRVE/CeeOXeTcMRAinLmTIuj20kWeH3aOw//48sMHxdi1IVuBrd10K8+P20vlej2NOCLbMcdy+nQF693uzzkH63/b7HK/1CWRO49x7ugFp9ZAExMTzzAVnf8Qcz5bjKIKNJuDiru6kVEE5EprTktOY2TXTxm/6UMq16tg397l1Q581f9HpJObslAE7Z+736U8R3efwGJVsWVonDjkw+6N/lS/JwmLw0+lCj4P2YNYrV5WrF5GSri0nSI4XKXri877LrlCs8HO9QEc/dcH1Um14ZwIn6YM+jac2i1rMH/87xzafhTVonBPh7p0HdQRi1Vl3vjfUVSFuq1rUqpKCSJKFkKxKOg2nTr3ZfWrcoRuD0C+UvFzpQhqGhza5cc/mwKJjw2i40ttWDrjADXvTXR5LsXLZKCGrEemB4NSDPQrCw06IWN3rpcyfSsyYWye7XlRwFoToRoZeSJgADL6CRwXShLg8wjCYijMgye9xD3t6zD/f0uJ3HEMq7eVJg834JGBD1KmWil+HjXbZaHFXPJmXuM53xRG02HxlPA8JQT+2eTNoGbD+WRJQ6q2mAEJH0HqYuzWKhFkVJn2fzFPzR93JMUmo6gKmu5aVuflF0xMTDzFVHT+Q2xdthPN5klKbTaG8Ucy69OFvPvLIAAunrxEYkwShcuEc+H4pVz3KEVV0HWdQZNeItxNPI+3r1cu69LYV0szbl4khUtkgDCCbnXduMEL612IoHdyy6bHGanQaau4WitIltvo53FFidzjS1y0SmCI5jDgV7NBmtaYANWw1tz/eFPuf7ypff/ZI+d5t9PHnDpwJtc1uadDHeq1rcWazADTlg/HYMswYn0cIYRE13EaeJznHAwPJJM/NmJJfnx7BmtmbiA1KYy/fg/hh/UHKFIyw6HipFokImmM+0WuxHbU/k+ZtgkZ8xyepWtLRMAr2TJ41YHQSci4IZltJXKkqPv2QAS9m0NeQbOujWjWtZHDmY3sKh2rt05Gmqfhh5IFP0SANALXc6JrAiR8/so6Jv0dgBIyFqkPhYxDRmVkaw2EyF8fsyyKVyxqj8lxhqIqFC4dflXzm5iYZGMGI/+H0PLdtynzOJvOhrlb0DSN796cxpPl+vHTyFlcPh1lPMlm3tCFgLqt7+aTlSNo16ul23nv7dwgl+J1+ZwXfdtW4cfRxTh9xJv4GJUzx4JQgt9DFPoFoWS7FaRMR0b3grQ1uFVy1PIQNhN8H8f4yAv703tslIVhT5fnwA5/bBkKnw0uBdKwkOTEZoPEeJUpn5R1uMSJfad5rtpAQ8kht0hbl+1i4qAp9teBIZrL2BkwFJxUD+Ou46IsjHyuLLs3BKKoCsunriU1yYg9KVUhjaKl8io5WVy53fNiE7bM8RIZPwzDkubu8yUgaBTiinozwrsZImIdIuRrRMAgIy4m4k+U4JEI4UQbvAKZvosHe8xn4dFdLD62h6mb91GjYSLuFWCBrok8Sk4Wui44cdCXgxt+ROrxCCUU4d0Q4VX3qpUcgKaP3IN/sJ/TGpiKqtC4cwOCw80yGCYm14qp6PyHqNKgotOGh+6wZWhMGzWHWZ8sQEqJruloNj2XRabX+4/z4ZKhWL2trJ+7hX2bHDemtMtTvwK1W9bIJVNSvMrsrwvTp/lddK9eg5Pn/2e0LhA+uQ9OXQ62vThzVek67Npci2PnpqFELEPxqmvcOCPWIoJG8POnJRjRqyw961Vjx5/ZCtTmP4J5q0cF9m/3yz53G/y1OJhXH6jE4kn7SU/LHWRty7DxRqv3sDl5Qpe6zHW/PXfCK48ilZOYSxa+eqc4zzapxoNlavJkg6rM+KIwiXF537vYywo961Vj8x/B9rVy9ngqWSEtzzGuEMITZUeA5S7DXZX4OWgncadQXDxjZfLHhfn0xe1MHfEr545dyLVfCCvCpzUi4AXwfQz0aKPysh7vVmaZuhQZ/Ri+Xpvt8UiFS2ZQrKy7bDvPOXdcgdQVBTaft683A795ASBPNpmiKgSE+PPCJ08V2HomJv9lzIKBN5Dzxy+SkpBC4dLh+Af73/D1183ZxPuPfnbd5vfy9SK0SLDhzsqkWIUi9PvyWafZIwkxiQzr9DF7Nx5EtaiGYpTpLntx3DM8MsBxryQ9ujekb8KZFUHX4dRhH15oWYVH3+jM8x/3zBVH0dbyqNvaLIWKZhAYYuPyOSuJcdkmmDkXf8j1pJ3f61qmSgqT1hxyuO/8SS8GPVSRmEuWHMUCJUKBYqXT+WxBJKERWdYUOLTbl/4dKjucC6B+i3g+nHHMI7mkhLRUgaIYVaFdIgqBdN+UNT1VMObV0vy1JMSoLC0FEsO92fOdrjwzsof9fZFSQsoMZOI3oGcpQlYjNitoSK6KynaZ9TjkxaYYndRzy/z1u8VZ8GM4V9s6JCcfTD/OPZ36GIpYAbJ12U4mD5vJ4e2GK1BRFZo8fA99xj5JsXJmELKJSRZmC4hbnM2LtzNl+EyO7DoOgMWq0uKxJjw3uqfbOJaCpFnXRnTu154FXy3LlbnirLR+fklPSefCidzF2M4fvciwTh8zasGbNOqYt6FkYGgAn69/n91r97Ju9iaSE1IoWbk47Z9tSXiJQs4X0y/jylWiKBAcblheZn2ygFJ3laBdrxbs33KYrUt3oqoKNjeBoFHnrUSdz+068Q3wISAkt5K69teNLue5khMHfZnzTQTdXrqUJ6V+zCuliI3KqeQACKQO5095MeGtEgz/wUitFwLOHHNdQXf3pgAS4xUCgpxfKykh6rxKeDEN7xwKTswlldAILdc4RKba4IGSAzBhaAk2LDWsTZot65wMWaZ/8BuhEUk81O9Ro5N44meQ9O0VM2RA6nxkxk4oNDuX+xKAlPk4UnIAmj4Yx4IfI/JsvxJFFeiac8UuMMRGrcbxoDquhH0tNGhfhwbt63Du2AWSYpOJKFUoj7tK13UO/B1JQlQCxcurlCy1AZm+HVAQ3k3A9xGE4kFtoJuA1BOMTELhj7CUvNnimPxHMS0615k/pq7lk95f5WkDoFoUQouE8L+/P6ZQsbxPqtcLKSV/zfub+RN+5+DWSCxWC4061iOseCizP1nooesi/wQWCmDCpo8oUbGYXY6cqez5RY952ajl4sx1pcGRvb680r4yQkDRcoUJLRLCvk2HjDTwzCJt+UFRFTr3a0/fL3rn2j6kzSh2rtqTzzOQPPTsZR575QKFihrncPyADy/eX8XlUUKRTNu6j/BiNnQd9mzy5+JZL2IvW1g5O5TjB3zzHNPt5Yv0GeY8myolSWD1lnmy3TQbxEVbSE0ShBXROHvci9+nhaFaJY++fIlCRfPWytF12LEukEO7fElLEfz6vyJXKG25r0FYERvTtkWi+rWCtKUuzlwB/5dRAgfkXi/urcz6R3k/B1JCnxaVOXU47zWxI6DnO12Z/sFvTof0ff8MnZ9PRRTegBAu5vIQKdMMRV34ObRS5WTNzA18P3Q6F09c4t72cbwz8YQRQK5kKcjCUCJCvyuwzvQFgdQuIBM+hdQl2LPULFWNRq0+7uP3TEyuxLTo3KIkxSfzZd/vAPLcVDWbTvSFWKYMm8lr3798w2QSQtDskYY0e6Rhnn217qvGN69N5fQhD1OM80FCVCK9Kven5n1VCQj15+/fd6JlaBSvWJTO/drT6eW29nRxd6Qmp5GR9gD+OK/kKxT4fZphEZISzh29yPljhrUpv5lnYCimhYqH8fjbj+TZV7JycXat+TefipNg0eRw7rk/gdDCCSgKHNzl/iYqdUHkHj/Ci8WjKFCjYRKSJBRFofvLl1gxK5TPXy+Vw3oCcyZG4Beg8Vj/iwhhlBfIyviKvmghNMLmMLtLtUBYYRtjXy3Fqt9CyXIBKarkz/mhfLEokqKls+NgIvf48n6fMpw/6Y1qkZkZba7cRoLoC1Yi96hUqb3MzZnrkDITrlB0wBtnrikh4LP5R+jbtjKXzniRu+O8oSwMm9GZpt174OMbx9T3/kCzCRRVomsC1SJ5+o3zPPTsZUTgR1el5Eg9FlJ+Q6ZtBJkGpBpZWxg1nqT1HkTAqwjvvN/HZZPXMO65rwEoXSmVd789jqJemYknQSZz+cCLrFwyiLORcfgH+3Hfo42p2rBSvtPeCwKpXcxs1HqZXAqo7QAy9kUI/hjhm/d7ZGJyvTAVnevI2pkbSE91HhCp23RWTV9H3y964Rtw7U+K10rDB+tx7uhFvh40Od/WDk/Zs25/rtdnj5znm8FT2bx4uxHInEPZkTIDbMcz86DLcGTXaaa9P4dNC7cCOh/OCKZ20/jMasjZGA0rfVk5J/fT8tUaLxWLQtOujXj5s14Ou2F36NOKRRMddxt3xT2tEmhwf4L9dVy0Z19Hi1dOy2DWvwzlrVW3GBJiVb59L2dLAsHPnxZHsz5KjfqRHNu9jcIlMmjWMY60FNfB6ZoGrbvHsOq3bBerrgnioi189lpJxs42YkvOn7LyRtcKpGbOl1PRckd6amb/CnfoUUiZnivbSfjcj0z5xekhQaGSn//ez6Kp4Sz4oRCXz1nx8tFp0TmWLn2iKF72U2RaWR7td5n2j/qzft5Zos+nEVYkg/s6xRFYqCgi4HOEr+NYMVfI9K3ImD6uW2JkbEPGPAMhnyN8HrBvTk1OY+Kg7OrjDz932V5y4Urmfx/GtyOLg5yPyKw++dsXS6jXthbDZ79mr2x+o5AJn+dVcow9xn/j3gPvtgjFeRsVE5OCxFR0riNnDp/DYlGdZuMAZKTZiDobQ8nKN1/RAShcJjzfSo4n3bmdklmZeeeqPTxarA/3dqpP535tqFx1BTLpJ5CxAOzaWIx3niiSmQpsPJkPf7o0z717zmiy6WOsb8uA1XNDmTisROYN9OpRVIWazary7q+DCIlwHgNRsXY5ug3uxJzPFnk8d4nyabz68Sl7jI6uQ1CojdxWh7x4++pUb+C8iJyiQKdeUcycUIyEWAtCGBaslo83IaRYZYY+sh4wlKDW3aJ5fvhZl7V6VBV78HNOdE2we0MgZ456UaJ8OvMmRZCaohi1Z/KBosp8ZIZ5A1dY/byagaUy2I7g2I2pI4TCQ70u81Cvy46njX0OgCB/ePDJzG3WBhAwGOFVB5GjCZuUEluGza31UWqXkDHPZ1pxXH03jJpBMm4oeDVHKEa236aF20iOT7GPatgmzmEhzT8XBjNxeA6lNkfc2c5Ve/j4qfGMmv+mS1kLEqNR60JcF+5MMwov+j12o8Qy+Y9jKjrXEf9gf3t7AFf4Bd0aSg5Ag/a1CQ4PJO5ygsP9QhEEhPiTFJecGWOj0KRLQ3av+dfpMa7Juj6CxJgkVv68jhU//ckTAy/wzJBYwLDQfNw31Ehnz1HvJCNd4ZvhJfhpbFGq1ElGKIb7JN5Dy4g7dE3nn3X77IqqZtPYuHAbq6avI+5SPMUrFOWB5+6nWuMK9Bnpw6PPR+HtfZa5kwoxdUxW4GreG3/pSql8vugw/oHZTToVBdp0j2H3hgBWzw11eJwQ8NALRfD1dx0PZPWS9B1bib9XFyekcDCtn7qPMtVK0qN47oyhlXPC6NT7MsGhKbnbUORAsxmZYLmRlKuaSmKcytY1gZQoH8XquaFXpeQ0eSDOoSKVFxV8OuVxxQihQOj3yOhnQYs0xuX4TCECQMblSy4AMrZC2nKEtxH3cmzPCX4du4A/Z2/Clm4jvEQYnV5uR5cBHfD198l7fMqsTCXHsyKKyGSjIapfNwAunbqcK0kgpxXPfpSEaZ8VRQjp0EWoazqbFm7jxP7TlKl6gwKB9Qu4b9RqQWonCyAXzsTEM0xF5zpyX/dGTBk+0+l+RRFUa1yFsKI3LhjZHVYvK69+1YcPHvvMKO6b4/dVURVUq8rope9Qskpx4qMSCA4Pwi/QlzUzN/DRE19c5arZP3lZ7qUZXxRh2YxQXnjvHBaLTsxF50/QvgE61e9Jomq9JDSbYPufgaycHUZSgnotbaMMeXTJ4e1H8fKxMrT9hxzadsR+A9q/+RBrflnN//6IpUzlUwSHCM4et/LT2GK4ssoMGHsKXwedyFULvDL6NOdOerN/mz9Z1h1VlWiaoFnHGHq9dsIjuVv2qM/9vbvZX29dtpOE6LztIJZOL0SV2qedzqNaYOmMKzMDBf0+PEPNRkns2+aHlBjXOh8oqqRQkQxeHnXGk9EgvBABfRzuFWpRCF8IaX8i01aCTEVYKoNvV2TUI1f/GUiehgx4hV1rT/DOgx/Za0cBXD4TzZThM/lr7hbGrX0vj+tZpq3BMyUnCwvSdsT+qQmOCMqVCXlgux/170/IZdW5cMqLk4ccKFk5UFSFDfP+vnGKjnDd7NZAR3g0zsSkYDALBl5HSlUpwf1PNM1TEAyMoGAp4en3Hr2uMkgpibkYR/T5GHTdsx/e5t3vZdT8NylZpXiu7Xc1rMTn696nSoOK+Af5UaxcEbv/v+VjTRg6fQChRfKb5upcIYi+6MXHfcvw7Xsl8sThZHFfp1h+2rKPJwZeoH6LRBrcn8BLI8/y05b9dHjadeq1p6gWlTFPTyByp1GPJusGpNl07m0fx7fDLTxRuxq9m1Rh7KulES6+VXWaxVOjYbLTysj+gZLP5kdSqlIKWdemUds4xs2L5O1vTmKxxHomtKVSrpeOlByAVXNCObDDD82BUUXX4O+Vgfy9Mm+Gg6+/cQ2q1E5GSihSynGKdzYSIYz9vgEanZ+9zP+WHb4ic0sBpVT2v8lUnpSiiNCfEJZy2bOl70aPfQ39YlP0i82Qce+CWgwleDRKyOeIgJdBKQRqaa6+jo4NW9J6PujxObYMLU8Qu9QlR3Yf56f3Zjs4XXdWjTwHIJTssgVNu9yDl0+2cr/gx4g8rqvUZPc/34oiSEvOX9HIa0GoEWCti+tbiwY54pFMTK43Znr5dSY9LYPPX/iGldPWoSgKQhFoGRp+Qb68/kNfp317rhUpJct+XM2sTxdy+uBZAIqUjaDrwI481K8dqrsW3ZlzHP3nBHGXEyhcOpySldzXEdFsGl8PmszCr/IfnOsMwzQPV96wyldP4X9LDyEUR0GaCrYMSY+7q+Uq9pd/JE27VOaveYcdCGYUwMvK0ska7+jGWq1BEi8MP0vVep71dRg3uCR/zCxE6UqpfLPqoNuWEdkoYKmEKLQQyMisYWJl35YEBjYdBkC5qil06nWZWk0Skbpg118BBIbYaPxAvL1QYGqyYPFP4Uz5uCgZ6TkvrqRIqXSmbDpgv+a6DvO+C+e7UcVdZlmN3/AGxSI+w993F6p6pdKtgvBFFMpMFU9ba7h+rFXBq2nuOJmkn5EJ7xvH2GNBjB5ZImg0wu8RZMpiZMLHoF/09MI55MD+5xjQapvLMX5Bvsw+/z1ePtkuPj1+JCTPxHWsSm5EoSUIa7aCOnPMfH4YOt3+uvdb53is/0U0m2FpS0lSeLRGddLd9PV6e8ZAWj7WxGM5rhWj91lvjO/ClbcXBXw6oYR8csPkMbkzuJb7t6no3CDOHjnPX3O3kByfQonKxbivWyO8fQvG4uCIrwdNZt6Xv+etiyOg5WNNeevnV1E86Rh5FaSlpDGo2XAidx0rwOytvAqEokqEgPLVUuj83GVadY3JpfBE7vHlq3eKs2+bf55jnc2ZvzGZriWLxOqlZz5hizzH1GqcyEe/HEEo4IF+CcAHL5Rh/eIQhn59nOad41x2Ls+DpSZ41YOU30Bmxk2pZfn+/UASY2MZ8PEpNC27qahmMyT+39tluXjGm/RUG4d3+5Ca7Fi7ev2Lk7R5NCbXttRkwRtdKxL5r6/DWJ0u/TvQ94veSD0RGfdGZiPWrOulgVoaETIeYa3m8tRkxj9G6rJTFAh4DRIL5kY6f9rzfPfODpcJBQCTD3xJycrZFlCZcRgZ1RHP/GYKeLdCCf0q+/i0DeiJE5kz/hjTPitCapLxwWnYOp7u/WKo3iAJRbUwfujdLP05zWHBw6x4uplnJuHl7VnphqtBs2koqpIrfkqmLkPGvQ0yESNCQgck+HRGBH9wTX3CTP6bmIqOh9zsFhA3in//2s+g+4a7HDPit9dp2iVv7Y6CIikuia8GTmbF1D8LcFbHSkdWMGbLLtEMmXCK1GSFj14qw9bVQZnWFvtIj+bzlCq1k+jxykUatYtHVSHqvIVFU8KZ+11EjrRtyQ9/HaB4mXSnAb9XkpoieOzu6oal5OC/+bDmuMJQwK6sxJyFrht/zze7C29fnZBwG7v+CkRRJYpixAgpCjz3zlm6vug4eyk5UWHqmGIsnRFmP//wEmH0GPIwnV9pn/tGaDsKaetApoO1Onjdm8tq4ww99g0jY8eppUTByMwqCHeNDz990Zhfxl12G2g9/fjXFC6duwqzTJqGTBhFbstTTjkzlTzvVojgcfaMK5k8Fxk/NHO/oUD/vSqQ+BgrRcuVoG6XKVgshpsrPiqBAU3e4eyRC7lierIUj/cXvkn9drVBxgOWXO6xayElKZX545eycOIyLp+OxsvHSoseTXj0jYcoU81wP0qZCqnLkLbjRiq5d1uEpXSBrG/y38NUdDzkv6LofNTzS9bN3ui0MJ6iKtRqUZ2xK1wrQwXBay1H8M+f+677OgaSweNOs25xMDvWBeY7Cyg/NGobx/DvjyPBHjshJUjd6D81pHsF0lJUqtVP4vOFkR7PK6URiP3TJ0UIK2zjl13Xfu0unLay5KdC3FUviYatEpwqTpoN/lwUQtMH4lAtkvMnvVi7IIT4aAtFSqdz/yMxhBRy74pJSbJy+tS9eIUPp3TVEh65ST1Fv9gc9IIvaOmYIA7t1nj1gYpORwghKF21BN/t+cxhcT6ZvhWZNBnSNxofDmstI25IxgDe4PsIik+z7PF6dGbvLmeZaIpRYDCgn31LQkwiMz+ez5JJK0iKS0ZRBI061eeJtx+icrUNRpmGrGtmrYcIeBHh3SL/lyOT5PhkvhnQj3KVD+Ljq3H8gFGzKineC9Wi8vHyYdRsVvWq5zcxcYSp6HjIf0XReaHWaxzbc9LlmNAiwcw69/11l2Xzku0M6/TxdV8HjPYIxcukceaY60yUa8XHT+OXXfvw8dMd1qDRNPh1QmGmji3K/Y/E8Ob/TrmcT9cybUsC5n8fzqSRxfH113lp5BnaPR7j8lh3/L0qkFHPlUXTBFM376dwCddBshnpRszRtesmAlF4K0Ip2O+ZfrEl6J5kal0jogjIS4DOG90q8O8Wf6eK89Bp/bn/iWYO9+VESg2Z+D9IngIyqxaSMCw6QSMRagQy6Qdkwie4zNhSwhERf+WxgGk2jcTYJHz8vfHyUZAxfSF9HbndZwqgIwKHIfzz3x1d6tGc3/UIRYqfxZb5UVIUo0DkF0NKsvq3QgSFB/HLqW+wWM2kXpOC41ru32bW1R2Ib4D7G70nYwqCRg/Wo2RlT5shXpvOLXXBmWM+KOrVzOPpMZKWD8fi6+9YyQEjDqfjM1E88GQUxcq6d6EoqlGAb9PyIKSEt74+yczde69Zybl01sqo58piyxAeW7esXgWh5ABI0GMLYqLceDfDno3lkAL6SZMXyFI2hk06TqW7jSByo8+UND5jAp4b3dMjJQcwMsOSvsqh5ABISFuDjH4UqccgMw7h1p2qX75iDjJlUwkODzJi/1JmQ/qf5P1cG+ckEz5A2nIr4FJmIFOXoce+jh7TDz3hS6R2Lsd+iRb1AuGFjeQGi9X4U1Sjzs/rn5/i7sbxxF6MY9NC1wHcJiY3ElPlvgNp3r0x+zcfdtryQFEVWvQomCyM04fPEXU2mtAiIZS+q4TDMf2/7sOQNqPc6BIS1SLz1TrAEUYK89XE3ng2XgioXDsZWwZYXcRTBoVqvPrRGY/ja6xekiYPxHs22EN+nxaGZhP2TKhdfwVwf9cYhxV2wbAsZTeLvFYsRnp3ASP8nkSmzHK21/gTwVdXJNAJQWEaXyyKZMe6QNYvCiYpUaVk+QzaP9ua4jUf9mgOmbEHUp01DtVAO4dMmgqKL+4/iwLcBPPKpJ/JDox3hIJMmY0IHGyM184ho58B7ThZGWykrUImTYSgEQi/xyFjK4r2j8O7hhCGJfPx/hfZsyWEyJ3HrltGqYlJfjEVnTuQtr1aMHPsfOIuxecKUARDyfEN8KHTy22vaY29Gw/yzeApHPg7O/6kYp1yvPjp09RuWSPX2Dr312Tk3CGM6DLWwUyGUhJcyEZCjEpOJaVIyXQat4/Dx1/n1GFvNq8Iwpbh/IldUSUly6dy8rAza5WkWoNk7m0Xh7ePzrF9vqyZH0JqssK97eLYtDxnDSDHNxspBfe0jrdnLLmiYIKIHZOeKrBYpcsA553rA9FzVJJe8GM4bbo7thJllVjyRMnRvXuipM3A+U1UBZ8HrynwVWYcgPRNgA7W2mCtixACYa0MwZ8i417HHsybtSYKImQ8yMzMrjzkLAGQPxQF6rdIoH6LrOrfKiLAc0VOJnzhZoQOKb8igschk2e4GKdmpts7z9iUUoJ2FNfnqYHtUOZ4DRn9HGinsvcZe4z/xo8AtSQybR1SqgjhOE5LtUDtpon4+Nrw8vFCapchZTYybS1IG3jVRfg9hrBUcCGXiUnBYyo6dyABIf58uvo93u7wIReOX0K1GndDLUMjODyQ9xcNJbxE9o+0rutsX/EPkTuOYfGycE+HOi4rqe5Zv58hrUfmUaKO7D7Om23f54PFQ2nQrnaufY07N6DUXcU5deDsFbMZN5+4KCvevhppKQpWb53+Y07TplsMUho3YYsVYqNUPnm1NNvWOvbP6prg9NGsG0Buq05QmI0RPxyjRkPDGiOloSi88N5ZxrxSmhYPx/HSyLP0aX4X6WnO08mtXpKwwjaXCoGzzCbPufJJ3BtI46OXS5OcqJCapHL6iBef/HaU4mXTcilUWTVWQHClQS9yjx9fDinJgLGn0fTsIGrNJpBIJrxZklc/Pu1UiZPS6HZ+ILI1TdqGQdIEB6NUEAGIgFcdHJ8OKQuRKb8a9X2UQgjfLuDb3d7gUWpRyNiBkLGFbDeUDmplZOBbCEtR8GmLsC43FIL0LcYQr/pgKW+kM1vuQgR/mllHJ0eGmFIMgt6F1OWQusDxSXqMBj7tPBop0zZC+nr3A/UopLWhUR7Ato+8mVrG50IEvOhyGiEEEi9cZ54pkNWNPW1dZvsM52Nl4rdgKetRN3SL1UbzLlbk5dYgU7HHG9n2IZN/gqCRCLPPlckNJN/ByLquO6y/ous6p0+fpnTpWzd98L8SjJyFZtPY8vsOdq7ag9QlNZtVpfHDDXI1JDy0/QjvP/oZ549dRLEooEt0XdLwwbq89XN/AkJyP5VLKelz92uc3H/aYY0cIQSFy4TzU+T/8nxO5k9YytcDf8xzAzaOy+7X89ZXJ2j+UGwea4WuGUrPa10qcmBHdouETMm4r1Msg8adZuOyYD4ZUMqoIaQLhJB8viiSynfnrUis69nTSB1OHvbh9+lhLP+lkNPO3p8tOET1BikO93mEtQFkbEXXhD2eSNOM2J7zZ6tTtGS60TNI8TZScgNfhfS/6dvoWyL/yT4B/yCNbi9d5MGnowgO08hIF2xYGk6Lp96AxDF8P8qL376NyBOfk1UwsE7TRLz9fPEKacmoJ0/wzwadl0adpvOzUaQkKayaE5qZvQbVGiTT/vEotqwMof79PhQqnBUQfEXqtLUh+PdCWCoatXEyb4xSTzKKyGXsIisg1v7eqSURYTNACUVGdQHbUVwW2hNB4PcEIuAVQCATxkLyDHL1WLLWhqCPEPoF0KNALYq01IP4tyF1Xn7fsStQwKc9SsgXHo3WL3cD2z/uB4oglCLbjMyrmBcg4x+yn0U1wAsRPAbh28H9mrGvGb2zXFxHEWx0ZdfjRhgxPU4zvTIJfBMSxuLKUhQXpTL+3YcZ9s0yjK7tjoKqBSJsJsKrjtvzMDHJ4oZkXcXHx/P888+zaNEigoKCePHFFxkxYoQ9dfTChQsUL14cTfO8EuiN5r+m6Ljj3NELvFjnddKS0x26uKo2qsRnf47KpbAc2n6Efg3ecjv3p2veo1bz6rm2paemM6TNKPZvOpynHUXNRons2RxAmcqpTFp70Om8mg12rAvk3SfLExhio1DRDJLiVV7/8gQ1c7RW2L42gGmfFWHftgDqNEvg41+POp0zpwUmS6xj+3x4o1tFkuLz+oaGTjxBi86xObZkFUTLRPgbTRod3WR8e5As3+KbV17gvo4HqN00AUWBC6es+AboV6RvZ1p2vJohQr5kXJ+fWPnznw7KBki8fXUy0hSEYuHRNx6i66B2JF1aybO15jhs75BFlfqFeOX9TZSulMqaeaFsWBZE7SaJ/PJlERLjVXu/M6HAc++co/vLl9D1nJWoM2W01ASlOKSvAdKNXWo5IxXatyN63LDMm6mjG59qpD37dUPGDXEubC4U8GoIIhTSlpL35quCCEKEz0eoRjC8TF2GjO3v4fxXYs2UXQPvBxAhYxDCfUC/tJ1GXr7fsyV8HkEJMTIUpZSQ/neO3l2VwPdhj7PYZMa+zMKKGg6vjVoSEb4EIbzQ44ZCynzcVnEOXwOX2+PMUqRpsGJ2VVr2bIu3Nt7BujnW926DEjreo3MxMYFru3977LoaNmwYu3fv5ueffyY2NpYPPviAHTt2MHfuXLy8jMC4/1Cm+h3B7HGLSE/Jq+SA0c9p74aDTHt/Dk+8/Yg9VfTC8UsezX3h+CVonnubl48XHy8fxk8jfmXJdytJjjesIqpVZd+2AEDSvHMsNhtOA2ZVC9RvmcDvJ3ejWgzFx2YTWCwyl7WmXotE6rVIJDZKRVEktgycumRyWuOzbuBl70rl5ffP8OmAvBbKkPAcloOgMZCxE2SyEXvg2xXQkHHDc6f2Cn+E/7Pg35eZQ39hxa82ls8oD0heGH6Wri9dJm8rssxj0/9Cxg6i44tDWD55jaMzIC0lUyHTNX4du4A1MzcwfuOHDJ1Wio96fmkEi2YqSFlNSRVF57k3t1ChegqqBR7oGU2TB+Lo1fguUhJVkMJ+q6reIJHuL1/KdY1yyWjbg6btyZ2xpR1Hxg1GaqcgZS7OU6Y1yPgbmZxBtrXHHXpmDI8zNJDxyKTvEUFG6wuZNC0f82eiRIB/P9BOGu41n/aGtcpT8hMUrWQ39xVCgHdDhPfVFfUU1moQ8pXhBiSV7AKFNlDLIMJ+sFcnFpaqSOa6ka0IQi0OwaMdxEeBrgtSU8vT/tXpEPcqOKjUnI3mmSvPxKSA8NiiU6ZMGaZOnUqLFi0AuHz5Mg8++CAhISEsXLiQ2NhY06JzA7h48hI7V/+LrulUbVSZstVLuT/ICZ1DnrYrG64IKRzMgIl9aNqlIbv/3MvrLd9ze8z7C9+iUcd6TvfHRyfwVrsPOLzjaK4u6X0/OE2HJ6NcZjRdiScxMbmtEJ5hy4An6lYjLipLQ5IUKmLj5237EAIUazmUCOc9vaTttBHwKbyNQEzhi6ZpdIt4jsRYIz24Ys1kvlruoI+WA0ShBfw4fAczx8x3nVADqBaFpl0a8u6vgzm+9xQL/reUv5ftxJZmQ1GiSU/RKVI6jfFLItn1VwCHdvuhqpKoCxbmfx+Rp2fV0InHadohzmX8jvP3wEPlQilW8MUAhR+i8E6EEOgX6mW3xPD08MB3EP7PXPXyUotCXmqM+wBoBfyeRAl696rXcri+ngipC5AZewEvhHdz8L4PIdQcY+IzixSmuZBTBZ8uiMBBhgKb+A2k/2WMVwoh/J4A/+cRwhc9+mlI3+xaMOGLUmR3wZykyX+CG2LRuXTpEmXKlLG/Dg8PZ+XKlbRr144OHTrw/ffXv/jcf5mk+GQ+f+Eb1s3enMtyVrNZVd6a1p/CpcLzNZ+U0iMlByD2Uhyjuo3jw9/fpm7rmoQVCyX6nPMaLwGh/tRtc7f9dcyFWBZN/INV09eRGJtMiUrFCAoL4MjOYyBz/7SeO+6d7zou7pScqw0OtlihUs0Utq21khXI8/wwI5j6wA4/dqzXkT6/ULXRXdRvVytPTJKwlARLSeP9krFIaSMpFruSA/DAE9EuLVjZKMiEcfQe+Qplqpfkp/dmce5odsPKiOJp1GiYRPV7kihSKp2NS0P4c+FGYi48S9nqpRgw8QUAJvT7lkpVfmDcwDLUbpbAs03u4twJb1RVZgZ+O9agKt2d4jLTzPX19dCCIkKBi+SnEaZbZDIyYxsyeZbD2jOOyYw78n0K/J6+puWFWgjp1RzS17oZqSPU3OUZpJ4IGTtAZoC1mt0Fl6/1lQDw6+kyYV0oQRAyLodbz9H11yB1HjJ9I6LQbJSwH4wWDzINRGDu4oXWepD+N87fd8NVmR9kxiHDCiTTwVoDvJp41DLExATyoeiULl2a/fv3U65cOfu2wMBA/vjjD9q2bUuXLl2ui4AmRlDx2x0+4sCWvLVx9m46yMCm7/LNzk8ICgv0aK7Ni7ezY+U/+Pr7kJKU6l4ACSjww1vTaLDzU54bWYVPXtiMs3o1vd5rZm8ieGL/aV5rMYKE6ES7iyw+OsHpg+OquaE89+65qyz655g8jU3zgaaBokiCC2Xw3DvnqdkokYGdKnFol2EBQcxHs+kULVeYkfOGUP7u7IeBwzsOM+/zr9i+8iS6plOzURIdegWhKCp6ZiB3yYqpHig5YLhq1kH0Ou5vXwW0RxjT+3fAKGJ36aw3a+Z5s2ZeGCXKp/La56foOeg8Zw9vIbSIkR2k6zoHtyxh/Ryj+eS6haFkvRFaroDlvO+ps8DsgiQ+RiMoqKAtwl4Q3RN7bRh3qOXBuxHC91G3DUY9RQQNRV7eQK5g6bwLg89DQGbhvsQvIOlnDLcTgEB6t0QEvY9Qr+ipJTPdeLaDIHzAu4XhZsqPjD5toNAs9q2ZwLyvj7L9z0CkLqjRMJEufS5Tp1kioIF+AZn4ZWZjTh9jvSvn8uuBTPoWHHYvB9DsVrIzkedY9PVytvy+A82mU7NZVR7q154q9Y0UdKnHIWMHZ7q6cjaBLQkhExDW6g7mNzHJjceuq/79+3Pu3Dlmz56dZ19CQgJt2rRh69atpuvqOvDXvC2M7Pqp0/2KInhm1GM88fYjLuc5fegsQx/4kPPHLqJaVXRNz3d38e/3jqFUWDd+n+bFpPeKk5Kk2jOmfPw0er11gS4vl0Qp9CtSSp6tOiBPw0F3PNT7Mv0+PIPUjSDYgiQru8nTsVHnLUQUN9LJdR2mjSvCr/8rnKeej6IqWL0sBEcEcvlMDBarQkZahlEeP1OJUFWjOWaZKimcivRF12DYd8e4t318Pq1YKunpPjxavRwpSVk//jlkUSSqVTJu/mFKlPdj1dK3CQgJ5syR80x/fw5XU1Cx5+Dz9Bx0oYCqJjtnx3p/6jRNKqCihfmJx1FBCUGE/4FQHD8wSD0ZUhch07cCILwagE8nezNOV+hpmyHmWZxlNonANxH+zyGlRMYNzsyYchREXAxRaC5CCTFkSt+NjBsE2mmM8808xqczIniURwHTWSz+dgVf9p2EmtnEFchsiivo9dY5Hu+fZUH0QhT+2+V5G4HfgzJfZd0TMt8P/74ogQPZtGgbo7p9iq5L+++DalHQbDovjXuGinVKE+7/CkWKX3Dw4KMYbslCCxCWq3ff2+XN2GdY/bQjhoXKp4NRxsDssn7LcEOyrmJiYjh79izVqzvWoBMSEtixYwfNmzd3uP9W4HZVdEZ0GcvmxdtdKgvFyhfhp8j/Od2fFJ/Mc9UGEnMhLl9Kx5WM++MBQnw/45fxRVg7PwRbhoLFqlOrcSL9PjpDiXJGxo0IX8HOP+N5s82oq1qnZZcY+r5/hqCwglOcNRuk28rh63PM7VhHMT0y8wF1w9IgPnyxbK5ifHnJ+lo5HqOqEl0q3Ncxmre/cd2XLEuef7f4c/6kF4EhGqUqpvNcs8pO51dUSYOW8Yz66Tijni/Lht+DHY7zlNCIDL5ffwBfPz1Pin7WL8i1KidSQkqSwtLphWjbI5rAkGt571WyU99dzZPpqlMKI0InI6yVHMuWvhMZ0wejC3iO+j4iCBH6nUep0tJ2Ehk/3GjwmYVSzMhM8+uWuc52ZPTjLmZREAGvIAJeQdoikZe7YsTWXPmdVsC7JUroRLdyAZzYd4o+NV9zmVDy6bxIajY03H8i/A+EpazLOWXGQWTiBEhbw5Wp//GpL/B4hR+wZdicWncbto5n1E+uvqsq+D2BkhlsfjVIKZGJn0LSd2R/XjIVMrU8IuwnhFr4quc3KThuSK+r0NBQp0oOGG6sW1nJuZ2JPh/rVjmJuxRPQkwiJ/afJuZi3kyPlT+vI+pczDUpOQDJ8Rd4pX1l1swNtVs1bBkKO/8K5PVHKnLhdGYgh3aevRsOoFquziSzZl4oZ497kZ4OX7xRglVzjBu1nuOe5Spt2hGqBXyDyrkfiGN3lxCGhalJh3jaPhbt8nhDSXKu5FSpk4RfgGDD0mCOHfBxeS7/bvGj97138UbXiowbVJr3epfjpVaVXCoWuib4e1UQMZdV6t2XHYBrsepUa5CU2SrDHdlj4qIsvP1YBdLTchcilBKSEhSjMek1ehuFAB8/nbvvTaRnver8b3h7CPnGcCflF6+GmQXx3ChLIgQRPA4Rsdq5kqNdMGoAycTMLTp2xUImImOeRWoX3IokLKVRwqYgItYhQn9CFJpjrJup5ADIlN9w3ctLRyb/mrn0txip/I6+05ktHDJc1+85eeAMK6etY+LgqS7vBqoqWfBDjjhAEeByXgPNKEZ4pRUrYzcB4hVqN411GaPd4uEYN99xDVKusfBjyuxMJSdzPsB+PbUTyJiXzWziOwAzmus2oEiZcBTV9VslkXQr/BzPVx/Eo0Wf5822o9i/JTubZ/1vm/Pd/SkXAmq1rM5370SSlqpcEdNh3FhjL1v439DMispqIRRVuaqbn6JIqtZLonKtFJZNL8SyGYUY278MnwwoxbH9hile1+Hfv/0Z9lQ5juzNR4NSlynJ2bgKYJY6dH72cp7tVm+d8tVSKHtXigOXm9EIslr9JF4dc4oHn46iVMUEbBkKI3pV5fQxxzeOyD0+DOlWkQtncpvQM9LdX1spBYmxKjUaJRJSKJ1HX7nAL7v28fmCSEpWTHOt7AhJRPEMrF46qkVSrUESj75yER8/ab8uUodJo4rxRJ3qLPm5YPpaKYoR+Fy+WjKLvj9H1OVaEDYH8MCFEPAaImQCInwlStgUXCsMmVjKIHw7uXRRyOSZuSv85kIHmWKM8RChFkV4N0JY786V/QSAdgG3ypl+ET19p9uCgKAiUxY53HP++EVeazmC56oNZMzTE9j+x26ki5RwTRPs/dsfUMBaH6G6T36Qce9gxBhdOa9ECJ0BY066/AwGhmju26h4HGDu4FApM2OJnP0yamDbY5SP8IBTB88wcdAUXmk0lIHN3mXGR3MdPnSa3HhMRec2oF3v+91aYlKT0nKN2bVmL4PvG8auNf8CkJKQcm1P3BLu7VSfkwfjnXbC1jXB36sDuXj+LlArUKdVTY8sSFlWH6EY8+q6IDVZ8NU7JZgypmim3IKVs8Po27YKD5apyYNl7mZIt4psXxvI0un5ucl6ZgZyZS1RVKPOTtYPuNVbp/fQc8zcvZeJKw/x7epDTN++j6r1My0AwoiJ0TXBgZ1+fPF6aWIuWvhycSS93jzHhZM6LzSvwK9fReRZa/xbJdGlUeE5vyiqJDTCxtxJESTGW0hNUvHyNt6PTk9HuT5YCh5+/hILIvfw+8l/GDfvCE07xGUrORKO7PVh7reFsaULfhlfxEEdoJyIzKwq9z85mg1q3mtcu8tnoklLUTl2pLELV6EKagWE/wsIn3YIS2btI+/GuFV2stogOEBm/IMeMxCSvsZ1rI8OaX+4XsdTlHDcK2gSonvgOrg5Ez1vdmTMxTgGNn2XvRsO5Es01WL4bo2K1G6WzYgE216n+4WAwiUyqN000emYs8e9sLn7uuYz6DoX2unM/l6ufhhVZJr7mj+/f7eS56oNYv7/lnLw70j2bjjIlOEzeabiK+xZv//qZTQpEExF5zagXpu7ufeh+nZFwBFXBhXrmo6m6XzS+yt0Xad8rbJX7UbK4vTBK/tUORJEcOp0D4QQVG1YiSoNKjpfV8DDrz7AA8+1olaL6pSump1ee2y/H4t/Cicp3sKVT1y2DMWubGma4NRh5w0O86AUwugd5ZzEONXNTRtsGUanbNUiGTnlGI/2vUhAUPZBJw55s39bppUmR02aLLm//6AER/714fEBF2nWMRaAHz8szoGd2Tfes8e9OLjT34WS4/zzoKiSJg/EgoA184xYqsVTC/H2E+XJSBe0fyKKyrWTURTnP/KzvirMxTOOc8qFgAo1Uhk98wgN28Rh9VZZOz/UhTItIXCIUTXaA7LOLOZCLD3L9WVAu8sc2OGLrnPFe6NkxslMyNOHSfg9g9tg5PRNyOS8xfL0pB+NysJpjoKCHSA9yF70AOHbmQJNr1fz9qyb9+USYi7EOaiw7WIaVXJP6xSjbYR3Y/cHpK1yO0RKKFbGeT+uZTMKuclIFEZX9avGk+sscKdQ7t14kM9f+hYpZa4HO6lL0pLTeOfBj4iPyl/9JpOCxVR0bgMURWHYrMF0HdgRb99sE7uiun7Kl7rk4snL7Fyxhgefr5mvHzaHcnioKHkH1SE+KoHlU9ZyzwO1CY4wAseyFLUsue9uXo37n2hKtcZVSIxN4sTe0/mWSSiSgGDPbgxSwrHIRvy1sgMXTjtzVQj+mF3BZXaRzQablhvn1PLhGOo1T8zTl2vhj+FG+rkTVFWyaGo4mgbdXrpIWOEMnhx8PlcAbsylq+u5q6gSH1+dngMvMOq5svaqybou2Pt3AGvmheDtKxkz6ygP9b6Mt2/25yK0aAhPDu+GUARxUVbefNR5fIwQUPe+REb8eIKfNkfSqmuMc0uYWgnFryuEZVUndo5qgT1bAqlcvwKf9P6KpNhk0pJVhnSvwFfvlODEQR9SkhQunbUSn/o4InyRw2rFwqsWBDjqYp4bmTjeSNHORE/8HhI+dntcDonBUiMf413gdS94NaNgfpp1hG/eTMxlP67OX6yeAIRC59e/8qjPFgC2I+6nFbh0TR3d58vcSYaL7EoFWqKA5S7wfcIzeRyhFgfhLkjfhrDWdDli7heLUZ2EFui6JDU5zUlFc5MbRb5/SVVV5dy5cxQunDsSPSoqisKFC9/S6eW3M1YvKy9++jRPDu/GgS2H0Ww6SXFJfPTEly6PE0Jyeue7dOoVRY/+5fh1fBBCEdkWoOyemC5RLYLo4wsY/v05ipdLJy5aZdVvoaydH0p6avaXPKhQAJsWbePNNqOwZWj2tYQQqBYVb18rGeka6Snp/LN2H/3vfecarorh0ql+j3Pzdxa6DknxKoMfiCQ5QQVRlYat43hi4CWiL6h4+Qhq3JOApt7H5NHRNGlnpVCxjDxPlFIacSQrZhnl+ms0SmTcoJIc3e+Ln79O0wdjad09hv07/PPEMeVE0wT7t/uhqnBX3RSmbNqPxUvaFSxNg7AID1wThlTktO5UujuZOs0SeP+Fcpw5mtt6ZfXW+HtVIG17xODrr/Py+2fpPfQ8pyK9Uf07Ua7hSFSLSlJsMvMn/M6FUz7sXB9ArcZ5lbncuCk+qR1Gj+6NCJmA9HsBkr9xOMxmg+MHfDm4058OfSpweMdR+2c1I01h8dRwFk81bn6qRaHD88Xp/7XzrBihBLq3x+hnjW7h1hrI9O2QONbdEVeeHMK/Zz6PcYwQAkK/QsaPctM2I9dROPwC+7+U7cbLQdyleI/lUVQFRRG8PWMg5Wo4DtZ2fKBn7uR924PsLUmM9QS6Ju2/G9++V5zzp7x4tN9FwosafqyMdBVrSA9EwOtuU/s1TWPL4h0s/XEVF45fIrRIMG2ebsF93e/Fy9sL6fcEJH2L4+usGOfh3crlGtv+2O3yIVLqku0rdtP99YdczmNy/ch393JFUTh//nweRefs2bNUqFCBlJRr6Op8nbld08udsW/zIQY0dq8oDJlwglZdY5HSyGaa9XU5ju0zFNIiZSPoOrAje/7az19ztzisq6NaJEMnnqDZg3H2Kr66ZmQgnYr0Zki3CsRcMlwcXj5W0lM9vUEXBJImHWJ555uTDp8Os1LCkxJU3n68PAd3Of9h9PG30q53Kxb8bxnFy6YxeuYRipbOQLMZ55plrRDCuCH/b2gJlk4Pt9fHQUgEEFrYhkASdcF1AK23r0bd+xJp3T2Ghq3isF7hUZMSXn+kAvu2+rtJZTfo+8Fp5n0fwbnjeV1z3r4aTw6+QIenonK52K5EhC9HWMqh2TS+eW0qC75aRtW6SXzy22EUBTfKjjuEkQ0V8h3E9Ye0Nei6QFGk3R11+ZyV0a804KmRg5jx4W9u4xvCioYw88y3kLoYmfSTobBgBe+WiIBnIX07MmEM7hQGETYN4XUPeswr+Yi3yVQw/PugBLq3HOUXPWUxxA12P9BSI/O8M89RiUD4v4z07YpIW4pM+xNkulFcz7c7j5cZRtRZ55XNhSIILRJMiUrFuLtZNTq80Dr/lddTlyNjX3UzyocLyUtZ+PUq/l66A82mUaNpVRp2qMvnL3xDUkIKelZ/NkVStmo6RcsEM/CHMYQWcR+bk56WwYiHx7Jt+a4c/d0Eui6pWKccY1YMIzDUCxn9PGRsIbfCqILwRoRONSyDLugU9BSpia5dl7VaVufTVe+5ldnEOTekjs748Uan2UGDBvH+++8TEJCdJaJpGuvWreP48ePs3OlZhPrN4E5TdDRN48myfbl8xnmqs9VL55dd+3K5RKSERP0jpFcbgsODEEKQEJPIk2X7kpyQV1F9+o3zPD7ggsNeUTYb7Pvbnze65aPRYQGjWiSz9/6LX4CeK1hWCIiPVpnxZRFWzAolMc4DA2YOC5fFqtO4fTz3tIrH6q1z+B8/9v7tx+tfnGL3xgDGv+m4UFmW6yglWXERX2NYYbIKslWtl8SHM47iH5j7hnxwly+vPVwRzSZcKjuqReHl9y+zbpEX/2zyzxUX5OWjM3b2ESrXTvag4F8AWCuDWhbhcz9RUbVY/9t2Avx30bTVPLx94sguxJd1PfOX5y/CpoO1LqStQCbPRGYcJynByqkT9bEpnanZ/B4UReGVRkM5+Heky7mCwvyZHVkEUuflkAuMgF4J/s/lSB92KpGR8q0WQb9Qx/NMHrUmIuA58HkgT3xQQSC188hLzXFnbhVhM0EtA9pRo1KxpaqRGh31DMiLZN/AFUDh5wmPM2Psvy7dV5+vf58aTe66etllBvJSC9AvO5FfgF9flKABDo+/ePIScz5bzB9T15IUl0xo0RA6vtCGLgM6EBjqSWo7TBw0hXkTfnf48KaoCg0frMuo+W8iZTqk/IZMng62E0YcmW9HhN8zHhUjfKvd+/b+g45QVIUn3n6EZ0b28EhuE8fcEEUnq/XDiRMnKFmyJGqOX0wvLy/Kli3LqFGjaNjw6rrt3gjuNEUHDH/7uOedFAUTksdevUjvt85fsUMBa22UQtkpsQf+Psyrjd7OM4XVW2fmrr0EBLt+In6pVWWO7XeewXK9KVIqjU69oujQMwr/IJ0Vs0OoXCuZGV8UZf2iEJdupPyR8+viek5F1ZG6yNMg0/FYSZMH4nh30ok8+/Zt82P8WyU5ti/v9RWKxAgvEXR+Pp0K1c7z2eBSuWTr+uJFnh92Lt9NTQFD4QmbjFBLIKUN0taDdhxEANKrHlxun88JLeD7KErwe25H/u/VH1j87R953AJePjp1miUQGCKp2zKIVg/vcb2eCAUZhWOrjgreLeyF9fQLtUB6YJX2aoESNsnpbilTIWUBMmUu6JdAKY7w656pFHlebVePeRnS1uI4cFYFtRwifEkuRUvKVOTFZjjrnB4fbaHfA/dy+Vyi3WKShRCCpo/cw7BZr12z8iYz/kFGP5N5Pa+49l5NEKHfenQtdF3P00fOHUnxyTxa9HnX1mUBUw9NoHiFovma+0r+XrqTdx78yOkaqkXl5yNfEVGyYEow/Fe5IQUDjx07xrFjx2jevDm7d++2vz527BgHDx5k+fLlt7SSc6fS/tn7eWncM1i8LAghsFhVFEUiFMkjfS7zzJArlRwAHWxHc21ZN2cTqiXvD1v5qqlulRxdg9pN3MfJXE8unPLihw+LMaR7BZITFdp0j2XmhCKcOepdgEoOZEZm4k7JUS06zTvF8cSgC9RtHo/xQ+/8mULXBH8tCebi6bxZTtXqJzNxxSG6vZxZgj9H7RGpC4QC/kE2jh+OoEXnWCzW3Ot06uUmldwV2ilkdG+kzEAIC8KnJcK/N8KvO0ItSc5UaM8emfTM6sLu6fhSW7RcT8mSR164xMzdexk19ThvfHnCjZKTuZ73fWRXSnY0JBqZMhcp0wxLkwcVp0RAH6f7pB6NjOqKjB8GGbuMNOaMbci4N5DRTyF1z2u/iKARoEQ4kF0F4YsIGZdHIZHxY5wqOQBBYTqf/+5F/Ta1cp2ql4+VRwY+yNDpAxBCIGW64YJK+gmZsthogZEPhPVuRPhi8HvGOAfhB5ZqiKAPEKGTPFb4cio5UqYhU+ajx72NHvcOMmWB8b5dwcGtR9y70CXsXus8Bd5T7nmgjr39Ts6EDdWioKoKQ6cNyKXkSJluVNpO24zUruG7aeIx+Q5GXrPm5kSPjx49mrlz53LgwAF8fX1p3LgxY8aMoUqVKjdFnluJroM60uaZ5qz5ZQMXT14myH8JLTruIaJ4uvODlGzzr5QaKVGryC5/no1wkX5sP56C70kFRlBtw9bxRP7ry+4NAWSkCxSVXMHP2QikbmRqTB5djJdGnuHBp6L4pH/pzBiQgnctuMM3UOOp1y4gBKyZF8zH/cq6HC+lYNeGANr2yBs/cfmclbnfZtbZucJCJHVBcqJKUDB4BzemdKVLHN3nQ5bLolgZF58Dt2iGBSdtNfi0y7VHCC+kT3tIXQZoXDxtpUgpxzeXqPMW/tkUgKYpVGsWQckQ9yuXrV6Kl8f1YuLgKSiqQo9+5+iVxzrpDh1kLKLQTGTChCu6iGc2iMzYjYzbCUk/ZGbhuPnMB7xp9LlygowbmuNBImuuTIUtYzcy4SNE8IceSS/UolBoLjLpe0iZlVmd2Rt8Oxt1g64INpYyw6j26xKd8ELr+XDJv5w7doHIHceweFm4+76q+Acb6f8yZaEREC3jsbu+hC8EDAK/Zzy29gi1BCJoKAQN9Wi8K2TGP8iYF0CPJuvWJVNmGxlyod8hrNmZb9JdfQj7OM9CVE/sO8Xib1ZweMdRvP28uPehBrR5ujn+QUbMX+8PHqdWi+rMm/A7+zYeQrUoNOpYjy79O1CuZhljLSkh+Qdk4ncgs77jCtK7PSLoXY+KMJpcHflWdDRNY8qUKaxatYqLFy+iX/GBWr16dYEJl5M///yTfv360aBBA2w2G2+//TZt27Zl3759+Pt7VpvjTiYoLJDO/Qw3gky2IOO3uxitgE+n7JcpMylZ7jC6ljfA7/gBH1KTBT5+rlKlYe9W940Nr8wOckW7x6Ko3TSRsf1Lo4jsxpiKmx8mXRP8s9EfXYfqDZJ5+f3TbFoWwpr5IfY06xuBZlOo3iDZHjPkziqWhbNijMtnhrk8Tuqwd3MUMnAc93fty7H92Astunv/3KMiU1chrlB0AIT/S8jUlYBk6OPl6Tn4PC0fjrO7yZITFca/WYK1C0JzxCvtoMEDH/HGj30JLRLicuVHBj5I2RqlWDxxFj0H77oK2RXAirDWJFF8xsl/+lOlxl+Z8l2hhNgicavkBI1C8XvM6W5pO5npanI2jw4p85CBryOUUI/OQKjhiKC3kIFDQCYblpwrKypnkbYeoy2EOzKQUlKsXBGKlSuSW8KkyZAwOseWzHORKYaShgL+T3ske0EhtYvI6N454qdyxIXpMcjoXhC+HKEalpNKdctjsarYMlxnAVdv4v5Befa4RUx64ycUi2K4+gTsWLWHae/P4ZNVIyhXw1A267a+m7qt73Z+DgkfQvJPV2zVIW05MnoPFJrj8WfCJH/k+zl8wIABDBgwAE3TqFGjBrVq1cr1d71YtmwZvXr1onr16tSqVYspU6Zw8uRJtm93dUP/j+LTCZQSODbVqyACSLZ1Yd743+l3z5vsWPIZaxcEO4wlSU1WWfJzIZxVDbDZ4PA/vhzc6Ymi46lVRRIQbOPT/7N33mFSFF0X/1X3xM2ZsOScswEDGFEBAQMioIIBFQXMARVzJphQUFBUUKIgKAIqEs0gGSRn2F02h5md1PX90bNh2Em7LKjfy3keH9ye7qrqnp6u07fuPeeBekgNn6Wn8kSgVZdCFMWXQFw7NJNJy3eRccTEu0+m8trwBiydmYg1UiMmobqqwSSR0W4CTWaKIolJcNPNKwQIuq1BRQfmimjR2f+yxuE9oUQRBdkZBhxZs7h65BRiEo2l/a1cGBdaYTYoJLpxpJ9ejc0RCdNASSH9sImJo+tyZK8Zj1tXOH56UCNWLYqvkJS9/odNPNTtWYryKy6HSCl1c0vbV8jiZXS8rDFjprfGWAUjaSk1hLk7mUezeODCR2jQ+JcguUqhvh8BIhIpyyf2a8jiFWg596Jl9tIjDiHbcYNrU/gnUdK7UBBKVGCSA+AJQ9QTQKnjNyqjObeeRHIqQha+recgnUHoNhxFBLbhKNQjXl7EJEZz+S3dAlrnqAaF9pe2pn6r4MnGfyzZwEeP6eSkNJ/JW8lZkF3Ik1e9jLM4NLGUrt1+SE4JPOA5iiz6NGQ7Z1E1VDqiM2vWLObMmUPPnmEKR50m5OXpa9AJCYHfdB0OBw5H2QM6Pz98/Yj/MoQSCQnTkbn3gHs3PtUxSgoZ+a/zaI83yTiYidHk5pV761GQG/jhOe31WjRtZ6dd1yI8Hj2CI6UeRcjJMPDSsPqET2LCw6/L4kojEv6gqJLjB80+S1KduhUw4tWj7N5s5bEbG+O0l3ly5WYavctw/qNKJotGt2tz6XJJAaoq2bkxgmWzEyjI8fcTETw0/jCrv41j9aL40sqpknGZLBrPT9uPyVI24cUlueneJ5dVi+L8Rm1UVdLynCIaNPdPKKyRmr48qEFyqpPu1+YSHe8h/bCJVYviKMpXUVSJ0TMda8pwxq98k6d7v0b6gRMsmFqTS6/LRQgZRtVVRUjgxNFEcnbupnGHBpjMvnlEwtQFklcQGXs7eZl2HujVhIatislON3L8oH+Cprk1ju05ztO9XsVgNBARY+XiG86nW18rRscY8Owv14EVDO3RiXv4jM3jhrxsA/s31GLuW+8Tn3AEa+SpiGZKyHsEaZ8DcR+CMCBzR+nLeqXO12d+idQH4UYErP38bw+nnF0WgmNVhaXM04ripYSy4ZDFSxBRw0u3DH9rKAe2HmLnur0IRKk5pxCC5LpJPPl5qPJ3mDN2oY/Oj0+PHo3s4zmsmvsrV97aPWg7ZWatgSJMGthmQvRDIcd0FpVHpXV0ateuzcqVK2nWrNnpGlNIaJpGnz59yM3NZe3atQH3e/7553nhhRcqbP//VHUVDFJKXeLe+SugIYydkKZujDjvGfZtOoDHrflU7QSDwejh0uvy6HlLFrXqO8nPUflxbgJLvkigILdqCr5BRu79t3KTxmuz9tL2/ELu6taCjKMm/8tAQlbIcanf3M5rM/eRWNOtuyULvTTd5RS8em99fvu+TD1VCMkFV+fxzBS9Ourn72JZ9GkSB3ZYMFs1uvfJpc8dmdSoUzF6lJ+j8tgNjTm406KfodRzH4SA5Nouxn+9h5RU/1GndSujGHNrI+594SjXDs1CSj26pRokbqfgoxdrk5tp0Ku2oh5HiboLj9vD74v/YtPKbdRIPUTPm+ZjMlUuoVRKXbzwls6tyDlhJDo+kusf7M3Ap67zqbwEmPTwp8x/e/HJLRBWcq9XIK52QydvzNlHSmpga4BQKNF4yskwMPrmxhzeF4nH5aHt+YWMmx9asTc0FLBcB2qit3S9ssuCBkTKz9WyTCG1HJDFSNcuKJoKnjTQDgUfk4iE5HUoJ4kiSdd2ZFa/sPoVMS8igizhVTe0jEtBOxp8J7U+SvIPPpucxU5++HwVi6f8SMahTOKSY7jq9svoeddlpflIgeBxe7jGfHPQJHtFVbh04IU8+fmo4OPPGQWOZYSUCqixtVJVef9LOCPl5SUYP348+/btY+LEiadFOyIcDB8+nCVLlrB27Vrq1Kno5VICfxGdunXr/s8QHX8IV2Twn0c4ZKdsElUUyeJDm9mwJoqnBjYOuxdrpIdpv/xNTLy7guCgpumT5v1XNePA31aiYt1cf/cJbh6ZEVC6PpjrOUCxTWHJlwksmZHAieMmYhP0JbB3vtlDbFLgfAJNg1ULY+neNy/g0svxQ0Zq1XMBVogdi7BchhDepE1POvLEFQRagvIHj0egCMm4h+ry49yyyKkQcNmgi3ni85GlzwB7UTEjzh3NoR2Vt/EoD1WV1GtWzKQfdwW9jhXHCumHjRzdZ8HpEPyxPIYVC3zzsiKiPczetM0n0nYKI0X3TAtNHIsKFPZvt6KoksatHZgTrkcJMxk5EKRjFbLwfb2qq7KInYhi7VGxTfu3yHAiOoCI/xhhvrjyfVcRWs594FhB4IiICuYrUeLfrbY+XU4XPS3BLSYURdDtpgt4+ssHg+6n5T3nXVoLljNkRdTY+I/Nq/92nArRqfSr+Nq1a1mxYgVLliyhdevWGI2+Yez58ysa5FUnRowYwbfffsvq1auDkhwAs9mM2VwJw8f/AWxZvSNgKPafhyQ20Y0QkJsZ4tYU0uflSFEligJ7t1q9UarwHhaX35BDXJLb76SqKDrBeGPuXpbPj6fv0EwMRn3iKsgxEB3v9hH40zyhlYMtERrX3ZXJdXdllm47uMtMVHzwpElFgUv65QWc/KXES3IA7JA3AlnYCBKmIdRaSNtsQpkTSkBqCoqioWmwfmUUcz9IYfOvvgJtUsLyL9bQc9gVtOvWCqkVMn7oMxzaEeKNOwx4PIL9O/Qqu4rO1v6tDjwe3WT15bsbsHdr4FwxW4HKslkJ9Lw1y+8SntQqUz3oIRTJkRJWfxPLuAfq4XToDUdEQ7+Rzbn1OTcGY9UiodI2B5n/DFXywxJWcG9Eal0QyknL/iKcPDv0yjRTGMae1QgRMRjp+DHIHh5ExCn4XvmB0WSkYdt6HNh2OGB1lpTQ6vzQqxvCei3SPjPIHipY+50lOacJlf6lxcXFcd11152OsQSFlJKRI0eyYMECVq5cWSpgeBaVQyUDeGcIkp63ZHPjvRmkNtIT+44dMPHVh8ks/jwBKU9+oMuyYI73dNwuhQN/m8k8bkRWgsOd3yM/aBTGYIDYBA83DMvk0G4z08fVYO13ep5NicjfbY+lUa+pAwkc2mUiNtHDsQMmCvJUkmu5SW3kwGT2f93dbqjfLLwoS7BnoL/PNNc+lOzbIWmxnlMRygYBEIrGvVe05OBOY8AKMNCTOZdMXU7b8/I5tmkUq76qR3Xlp6gGyboV0X6IjgKm88H5G+XfjI/sMTP+oXpBSU4Jpr5ci0at7bTqYkPT9Hyz0sJRJRkh3F4NmlN/EZAStq+LLCU5ALYCmPnatxzZdYJnZj9c6YlNerKQ+c97/wp3jOV+KNIORdOQ9sWQOFsvXy+Buau+rBVKGTrmxeAJ0acDpgvAegvYZ+BLeL3/HzFEtxepZlz/YG/G3/mB38+EEJitJq68LXh+DgDGzmDqDs41VPzevJpIkXee8njPwj8qTXSmTZt2OsYREvfffz9ffvklCxcuJDo6mrQ0XU8jNjYWq/WfU+T9r6Fd91b/smiOZORrR+g9JJvySgU16zkZ8epRmrSx8fZjdSh5exVClq2Zn5Rrs2BqstfEMtTkUbbkZbJoIRWDHXbBl+/UYNEnSTiKlVICoHkEPy+JZd2KaMbN30tUnJspL9fiz+W+FWyWCA/X353JoAfTMZrKCI/bDTvWRdL2/PAE5EIti50MRQE8+5DFKwB32MfXa1LE/u3B80c8bg1H4R5kzkf8/n1MoGBLFSFxu/0N1ANqS+Bnn60z363Bni3hPQOKbSpP9G/Mpdfn0OuWLGrUdZGXbeDYka5cOHCsnu9S8DYUzwujNRPBSrkVBbb+XjEPRErJ6nm/sf6HzXTpUclK1eIFVJ6EnfzFeEDLQOY/j4gvM1cVwgqRdyML3wrclOV6FOs1lez/1CGEgJgxuvGq7RNw79I/MDTVCYLl9ERDegzpzpY12/n+05U+kXDVoCAUhWfnPUJUXOBcn53r9jJvwiJ++2Y9bqebRm060/f2PVx2fQ6K4v3RqPURcRP8GrCeRfWgSrFTt9vNypUr2bt3L4MGDSI6Oppjx44RExPj44FVnZg0SZdov+SSS3y2T5s2jaFDh56WPv8/ouV5TWnauVFpMvI/jY4XF9J7iO7VVZ5wlPz/NYNzWLs4jnUr9TXZ8pVYiqqhecoOWvplcK0Zf9izOYI25xYFzLnxeGDPFiuz36vhJVm+D1PNI3AUK7w5qi65mQbysg0VCFixTeXLt1PYtcnKi5/tRzXoFUEOu8KiTxPDJjpVfo4Xvs2fK1P5c1ke970cuvzY5Qy9JKKoClfceAhw4yjWx1ZdwUKPW6F5hwDLQvaPK2zqe0cmKxaEn9jrcip8PyuR72fpmivn9uzIc189BkIDWYCIeQypZYNzFUFzKkydwPkH/oiHxy3YtcnKni3+o0yKqrDk4x8rTXSkey/VEznzgGMF0nMcodYq2xx5r15VVVRynQWl5xdxFyL60Wrou2oQQkDE9YiI65GaHu0TyumZb0qgKAqPfnwf5/XsxNcTl7B34wGMZiMXX38e/Ub1pH7LwOkTq+b+yquD3kYISp+1uzdpjB1Vj79+vpDHPmqPYm4Fxi5nl6xOMypNdA4ePMjVV1/NoUOHcDgcXHnllURHR/PGG2/gcDiYPHly6EaqgH/nkst/D0IInpv3KI9c8hwZhzLPyHWNinVz9aBsOl5cAOjh/KVfJpKVZqTvHZlBcyPcbug9NKuU6JSEDjpeXMjtTx5nVK/y6+PhPSwiYzwU5eu3/rfTE7n+7hMB91VV+PJtXVAtkGeV5hEc3GlF+KnoKj+2dStiWLUojsuuz2XnxgjefqwOh3dbyDh6nOTarqBERtP0PBSDQVbaQfznb9N46S4LUXFxDHv2uE9U6WQ4HUI3BQ0BzaPR8cJjgIdGrYvDzokKBaFIYuI8XNgzkIVBxbG37GzjnheO8uFzqWVO8mGiXotUXvr6HrC9gcydS6nPlaEDCLMu0BcIzvVgaAvuTZy8nJJ9wsir99YPeKjm0Ti2Jz3scZYi3DyasCDBvRPKER0hBCL6MWTErWBfhNROIJRksPbxXeb6h3G6CY5PX0LQ7caudLuxa9jH5GTk8fqt7+qCuuVu2ZJcn+WzD9Ohx7VcfXtghe2zqD5USTCwS5cu5OTk+CwZXXfddSxfvrxaB/e/Ao/HQ056LoW54XvgnApq1E/mw03juHfCEGo1TDmtfbW7oIA5W7YxbMxxulxSSJdLCrnl4XQ++20HF/XMpePFBUETQA0GaNjyZJNFwZbfIklt5KBJWxtKGDYV5eGwlXV4bL+ZD8akAnqUpQSa90V+2ax41q+KDqvdUOadQkgWTUvinsua8VCfphzcaUXTBNNeqxk0IlJcJJgxoQYv311fLyvX9H3/Wh3FJ6/VZOrLtfh1WYxfUUe3C959og5SQkGOkcXTEwimjp92yIitIDiTUlSFpp0aYbLoDXXqVkBKqlMnen7hb7uuaVTeYkRRJSazxnOf7A+Y01R69EkfXz8sk7cW7eai3rnEJ7tJqBVL4w4NQuQ1Ca5/4CLIGQi2L/Ax83RvCk5yAHCBpSci5jUKi5pQkGvh4E4LU1+qxYhrWpFxNHCZsFAEcSmVqxyRUoJSh+CVO5WF/2INodZERN2NEvM0IurufxXJ+S9g2Sc/4XF7Ai7nCkWw4N2TpRjO4nSh0hGdNWvW8Msvv2Ay+f6IGzRowNGjp1518b8EZ7GTueO+4euJS8jN0N9gW57flEFP3cD5vTuf1r4jYyK4/oFeXP9AL94Y8h4/Tl9d7X3EJbl4fda+ChEIRQFhlDz14cFS8cFg1UT2wooTr9ulcOyAmQfePMIj1zXB7Qpsn1DhWHfJ27e+/6JpSRzeY+bGezPo2K0QVYX9OywsmJrMD3PiqZ6lAp0IHT9oKqeQrGvo/P5DLEf3p5Pa0Dffo6RkuqhQ8N30RHJOGPl+TjwdLypizG0NObTLgmrQ25r7QQopqU6e/3Q/jVuXqdb+tTqa3MyyysipL9UmqZaLi3rm43brRLLkX4C6jZ3ccO8J5n5QkQDrRo+Szj3a8+T0kQh5AFwbUFUYPekgT97UGKeTk6I7/p/0D447jOYRfPt5Ikf2WLBEaHTvm8t1w05UuA7+IITvuAFadLTx1KRDrPjuWi6/Yzw5GXkMa/MQBTlFFfLSFFUhoVY8V96wGdyHqUgewiTP9nnMmXY3U5+MQFFblvYTmPR5W9ckV9wSRhJr6f65uupyVcrJA0FEgaljxb6c65FFH4NjNeABYxtExBCw9DpjSyxSKwTbl0j7bPBk6EKI1hsQkbdWrBb7F2Lnur1BbyGpSfZtOojH46mgR3UW1Y9KEx1N0/D4eXU8cuQI0dHhvfmeBTgdLkZf8wpb1uzwKV38+489jOnzOve/ewf9RpyZpL/HPx1B8y5NmPn6fLKP51ZLm5YID+8u3h0w90V4Rfk0LXjuidRg1aI4v5+ZLBoNmjt4a+Eepr5ciw1rwr3/Kna4YU00G9ZEI4REKOGTpspBYrZq2ApVGrayE5/k4pzLCriifw4x3vLy4weN/Lwklj1bIvh1WQzFNpWIaA+X9sthxYJ4zu+Rz6iezcg8rpMXT7mk3cw0I4/3b8xHK3aSWEMPTx0/YKI8qXM5FV66qwFtzi3iygE5JNZwkZVupH5zOy072REK3HDPCeZ/lOzTdt/7rya1WQ06dSuibr3fwH2Tj3pxqy42Ji7bxaz3Uli1MA63SyEqzk2Pm7KZ/1F50iSxRGj89n0ML3x6kF63Zlf5am79LZI25xVh8PK4/TssfDa2Jnn5Zi6/A+JTYhm34gXG9HmdtP0ZqEYVpC4EV6dZLV5a9BAGdx9OJUKSfWw/U5+cAeBDpkKJzNVvVYeLbzw/rD6klMic+8EVyqm9PASYLvHmGfkP4YnIOxHC4tuXbR4y/2n0YL/3uri26Po6zt+9FVenl+zo7u8DwXOwbOxaGhRNQtrnQcJMhCG4tMg/DYPJgFBABrm1VIPi48x+FqcPlSY6PXr04O233+ajjz4C9Le8wsJCnnvuuX/cFuK/hEXvL61AcqBsDXfSg9O4oE8XUuoln/axCCHoN/Iarr2vBytmruXNoe+HcPUNrXZ71zPHSQ6g8lsCRaF0KQZJBVLkcUNRvsp3MxJ8+xSSmnWd1Guql2U3aWvn9dn7SDtkxGyVFOQpTH42lb9WR1c6d0RKEfThFOJogl8XQfphfakgubaTV77Yj1DKiN6Bvy2M6tUEl0PxsbawFagsnp5Ez1sy+fm7ODKOGP32o3kEtnyVbz9LYsjjelVisV3xs69g6x9RbP2jLM/h3e92lf5/fLKbuk2KOfC3vjTd+94e3DehO+QM09VpA1TD12vq4PF3D/PIW4dx2BUsERogSKrloutVeUTHeTAYKbVhyM1SiYn3VKh6K7EZCQapwfiH6mErVEhJdVFUoJRe27YXl91IDVrX5dNd77Ju2Sa2rtkBQtDxsjZ0vLwteA4jM09eFq0cvp2eGFZekFCEroogJR0ua8NTXzxQwUojIFybwPVnpcYlokZB5DBk7kPg+AFd4FCjlMBYb4bI4T7HSPdhrz6PxJf8ecmGfTaYLwDL6X0Bk3kvgOcQFQmaBlomMu8xRGIwTZqT2vNkgJapyweop/95CnDu1R1ZOevngJ8rqsI5V3c8m4R8hlBpojN+/HiuuuoqWrVqRXFxMYMGDWL37t0kJSUxc2b4N9//Oha+vzQ4mRCCJR//xJAXBpyxMamqyhW3dMcaZeXNoROx5dtPyh3RJ/JWXYrYvi6q7AHvJwm3SVt7yLLtEigK5JwwkJDixu3lRgajvm3MrY3IyzJiNGs0b1+kT85SMOjB9Art16irJ/TGJ8NLn+/H6RCMua0RW36tjsRFSfOONnZtjEAIPZ/E4xZ+/LjCszzYty2CMbc24oXPDmIwamgeybTXa+By+pKc8hBCN+gMls+jaYIFU5LwuOHaoVm06BQiz0RIatVz0qy974SvqJBSP5mbHu3DtfdeCFlXg5YV8rxAJykRUfokJZH0uzOzlMSWH3d0rE5yHHaB2ap/YC9S+G5GPF2vKqBGXadfwuNxw4Y1UaU5MIV5ZY8xoQjO7dnppPGonNezE+edtF1WQ2Lvtj8iQpKcmMRoBj99A4qq0PHyNiGNJE+GLpQXzCepBLoZ2pGD7VjzQxIN2mzk/F7voERuQxYvAE82qDUR1hsQxoqu3dI+O2T7suhzxGkkOtKT4bVKCJRI5gHXeqRrF8IYXKhPurYgC8aD85eybaYLEdGPIYytqm/QftD9pq58/NQX5KTn+ffJ0jRufOTa0zqGsyhDpYlOnTp12LRpE7NmzWLz5s0UFhZy5513Mnjw4LN6NmHC4/aQtj8j6D6aprFnQ9nSgMftYd33mzi+L53o+CjO790ppFdLVXFhv3OZc3wKq+f+xsHth7FE5JN7eA6LpiVhMnt486u97N0SwZIvEzh+wERBnoH92y0+ybjFdiWkbkuJMahQYN92C+8/lUjbroUIAZt/jeLXZbGlyyc3j0qnWTs7226L5LbH0rjq5pwK7ZXvSzWAWUhemr6fWzq39JkMg8MfUdFzaW66P4PmHez8ND+O7HQjOzda2bkxotwyVwnpK98WftrTsW5lNAu+GM2l/f5m7Vcr+f0H/w7yJTh2wIwtXwmZ9OywK6xYEIclQuPqQVmMfP0wqxbGe6upTiJlUnDnM8d9rp0mI3l+0QfUqF8HITP1ZQstcGVaMAh8I3Unf0cAJovkpbvqc+K4kYM7LRTbVFZ/U8Sbc/cijdInD0dKlYI8eG90xaULoQgskWauvuNSfcK0z0M6N4BQEaaLdOXZctU6Qk1CGjuAazNVFQh8ZMIR7ri4OS5H4BCUNdrC9Q/2qlL7AEgH4ZDn44fiyU6zExW3kw4dX2fF17F8+XIdRn/Shtr1naAmI8yXIZUkKJyEtC/UxRHVBrpvlTPUddDAtbXq5xEO3NtDjMEL12YIQnSkcz0yewgVTGCdvyKzBkDCDITJt7Rfann6PWP/ThdNNDRHRAwE03mVjryYLCbe+OFZHr/iRbKP55TmtymqHsZ+YPI9tO/eulJtnkXVUWmvq/8yTsUrozohpaSnZSBuV/A3NKEIbnioN20vbsnb935ETlpu6Q/GZDHSd8Q1DHiiL7GJlTsXt8vN+u83kXEok5ikGM7r1QlLRGCrDKkVkrPjQu7q1ohzLsvnifcO+3yen6MyqGMrXE5ByQO5z+2Z3PfS0bAk9UvuwF+WxvDO43XIyzKWataYLRoDH0zn5pEZSA0mP1+T+15KC/tcNQ0+er42C6aeHLLWOy2xedDhm6TsAyExWyQzN2wjMkY/4POxNZj5bg0/+TySmHg3+TmhlyY+XBvF4k89fPuJLWAkpwRGk+C8Kwv4dWlkwCiCUPQIyrBnj5WdptCjLFt+i+S5oQ2xFehkKSrOzf0vH+Wy63NP6qgDIu5dfWkn5y7faqTTACkVvvowkSkv1vbZ3qCFncEPpXPhNXmoBpDSiLD25Y9VXXn+pi+QmiyX/CtIqGlg/NLO1Kq1okxQTv/U+08MIuFjhLFdWd+ONfo5BswcDa2EOPYBXy+w8lBU6H1XPYa+dD9RiQ2rtFSh5808FXQft1uXHihJ0C6f+6a/cKjevt3o77eecuelR4IQ8SBzCXq+IhKlxoZKn0O4kI61yJw7Qu4nYt9AWK/z+5nmPgJZ1+kkzi8UXWgwcVHp9yHde5DZt4KWTdn5e6No1sGImGer9N0V2xysnPUzv36zDpfDRZOODel195XUqH9mltD+P+GMmnoC7N69mxUrVpCRkaHrBJTDs88+W9nmzhj+LUQH4OWbJ7B2/u/hifYJ7+M2wDfVtHMjBo6+nouvDy2Bvuar33j3/ql6lZf3GW6NtjD0xZu5blTPgD9mLe8Z9q3/ll+/j2LgqIwKy0Y/zY/jzZH1ShN5I6I8fLz2b+IS3RWqrkoiPZpGhXZcTvjt+1h+XhJDo1bF9Loty8dPqme9tgx5PI3+w08g8VZwBdOf8cDaxbG8cm+Dkz6RDHowDVUV7NxkJSvN6LUQ0JmBP3FAIST3vXyUPrfrSziHdpsZ1r1F4M7DWMZ6Y+4e5k1K4eh+E8cPmoPmFCmKYPDoVkx/ZVvAfWrWdXDfK0fpcmlBhWUfjxs2/hzFmyPrccdTx+neJxdLhL+bSkFX/QVd+bey0Q6l0sdsX5/II/3q+Q3zR8RIul3fmoc/Hl2aPJtxOJPvpvzItl92ohpULrmxBlf0/hiFYMnNAohApKxAKHGlW6X9a2TeGPRzLZeEGwakhL9WRfHMLY0qEFWhSAxGyeQfdlKrgZNlc+pRzEiuG9Ub1aB/OSeOZJF5NJv4GrHUbOBf6kFqNuSJC73l7hW/L/0+lX5/B5VT0w5F6lSw9EKJGxdug5WG1AqRGRcAxUH2UhDJK/2WvOtE6R5C+boBiMQFCGNrpHQjT1ypJzwH+O5FzEuIiDOXRnAWFXFGic6UKVMYPnw4SUlJ1KxZ02diFELw119/VWoAZxL/JqKz+699jDz/KTSP59QVZb3Pp7vfvJX+j/YJuNtv365nTJ/XA34+fMLQgCF2qeUis27G49iPovp/qG7+NZJZ76awfnU0SEGb8wp58fP9REZrPg/cEi+qQNEejwe+fDuFGeNr0bxjES9+doDYRD1/57Xh9fl5SSyJNd1c0jebYc+mBX2Qe7xE51Uv0dENP6GEgMQkuHDaFTyaoGZdJzcOz+CSvjoBSDtk5JvPkvjm0yQcdgVF1ehxUw4PjS9z6H79/rqsXBjvh6CEl6szefnf/DA3gcZtbPy6NIafl8QHrPhSFMnzC57g2w9m8seyw3760MUENY+gfnM7r365j6Ra7grtPNC7CcU2hcfeOUSTtoEmlNCRDP8wQ8RtULwYtNAqzCV9FRWfzy0dJA6bw4f8K6pCYu143v3lFZJSE/0eLaUTeeJyPeG03ERlK1RYPi+eNYtjKS5SaNS6mF63ZtG0c2uIuBVBMRiagqE1yEIoXqQv51SyhLsgV2HI+S0pKlB9vg2TReO5jw/Q+RJdxVdqMPv9FHZu78Pgp29g6pMz2PBT2VJQy67NGPb6LbS9uGXFcyz+CZl7v/ev8pOxwOMRCBHayiR8+COqerRWJM5DGNtUV0d+oRW86VVmDkDCLdeixI2t8In0ZCJPXErAbPmTIOLeQViuQRb/UO7a+t1Tt2lIWlYtycNSFoOWCyIaoZye9IP/jzijRKd+/frcd999PPHEE5Xq6N+AfxPRAfh98XpevvltiouCvb1UDsNe70PvIUexiEWg5evJhxEDkZYBDG3xJMf3BlZjtUZZmH18CtZIi9/PncXZ/DnvXs6/fGNQcuGwC5wOhcgY/YE8+dma3P1cGqpBJzsHd5qo18wZtI0je03c6X3gR8e5mf7ndj4Yk8rxgyaO7EsgJ11/Y3tj7h7anhfYwkFKWDw9gUnPpuJxCeo1Kyb9sIliW0m4QycLbc4t5NWZ+1DL5YSUVIPt2mTl8f6NcdgVrhmcxYNjy/SiHMWC1++rxy9L43z6jY5zYy9ScLv8zz5CaAx8MIPbHk0vvQ6aBoumJfLZmzWxFVQ8oevvyWD+hynUa1WHxs0289fqaPKy/S+PqaqkTpNiJv24K2QFU3VCxLwK1n7I9I6EO+Hox73GsWMXMPvNhSyfsRpnsYvI2AiuufNybnq8L/EpsQGPlfZvkHmP+Gw7vMfM4/0bk51h8EZDRWny/OCH0rjtsXK/A0NLROzrYGiMzLjIu3wTHtwu+GFuPN/PSqB5RxsZR81IKfXy/ZvKZANK4HIKBnZsha3QRNvzCuh2bTbRcR7SDpv4flYixw5YefW7p+l0RbsKfWm2RWD7FNzbAAlKIlh6g+2zsMcbFkSsd9mnhOwqgIKIHYewnv7KWildyNyHvUnJJUnY3n9N5yHiJvslCLJwErLwHcKNJor4TxDmi9DyXwbbl1TI5zl5/+RfEGpSJc+m3Pg8R5EFE6F4EXrESQHzlYioEX6Tw8/CF2eU6MTExLBx40YaNWpUqY7+Dfi3ER2AA9sOM6ztw9XUmv5Vxqe4eX3WPhq0KCFQgl1bmjPyqsB5OCV4euaDXDLgQr+fvT38I76b8iN9b89g+Euh39alhGMHTbxyd32MJkl8sot6zRz0HJxFzXrBQ8vZGQYGdihL1mvVpZAd6/WHW2xKDC6Hh6JcG10uzeeVL/b7bcPj1icWS4TE49EJ2PNDG7HpF98qLINRY8a6HcQkuP1X+Xhg/kfJTH2pNn3uOMH95fyipISJo1P59vOSB6Ckw0UFvDxjP199mMK012pVbBDJ0CfTGDiqYkK6lHBwp5lRvZrhsOskSVEl512Rx51PH+eubi1RDArtL8hDEdKr2hyYMT75wQEu7RcoV6G64J0QI+9GRD0CWjbyRNfS89n8ayRrF8dhL1Ko09hBjwHZJKSUTCoqKCmI5KW6qSS6UrjD5sQSaQ5LZ0TLexLsCyi5/90uuP3ClmQeD+zAPnrSQS7pm1s6hqP7o1m97HIG3vtVpc9+VM+m7N5spXEbOxOX7g66r5Tw3uhULu6VR8eLC3G7vHliUs+tmT0xhcVftuXzPe+Xnrt07ULmjQZ3eR0dK0TeBZY+kHVlpcccFAlzEO6dSMcakC6EqR1Y+yPU06uiXh5SSnD+oevmeI7ppeER/cDUDREgFKxlD/WpsAoKEYtI+RkhTGj5L4FtJqGJzs9VLk+X7kPIrP4g8/GNyKmAAeEnOfosfHEq83elq6769+/P999/z7333lvZQ8/CD3IzcquxNf2hnpdl4MkBjZj2y99ezRLJL9/lAjXCGE++3+3ZaTks+Xg5UpN8/XEybrfgrqePY40K/vb0w6x49m6NQFElmga//QCNWtlJSc1DSvj9hxj2bbdiNEnO65FHg+YOPG448Hd5UibZvq6sYig3vaD0k3UrYpj6ci3ueuZ4aSJmSTWXvUjhyQGNGfxQGnu3RbB4eiLZ6RUjIFfelE18cuCHnKpCz1uy+OzNGqQdKjteSijKV7DbFP38PHp4/+aRJzAYYcCIDISQfDGhJo5ixbtsppfn+yM5oEe86jd30GfoCeZ9mILUBFKDX7+PZePaaAxGjUfeOsjFvfO4tmFbQi2PvX5ffVYtzGPok2k0aB5+hCU8CMAMIgKM7RHmywCJLJgAQEGuynNDG7DtjyhUg9d1XsLnb9Zk+EtHuXZolh5xjJ9WSnJALwePiK5EBaf7IOlHDPy2LJZim0JRgULGkWD2C5K5HySXEp3t68w8OaAu9ZttZmCYj7WS/LIFU5LYuVEvU4+IDh1JkBr0ujWr9CWkROywZOoeMCKDjKN/s3nVdjpc2gbpPojMHqhXAfnADkXv4XHlYsuzEhVjr7rpqw8ioPAtpJYFah1ExE1gvjQguTi+L51vJ3/PhhVbEULQ6fK29L63xykn2wohwHwewhw677AM4b+zi6gHEEK/R4SpC9I2PdjeoKaCcgrRnPzn/JAcKEkKl3mPQtL3Z3V1ThMqTXSaNGnCmDFj+O2332jbti1Go+/EMWrUqGob3P8CNizfWvV0iADQPIKcEwZWLIij5y16cubOjeFNHCn1/P+Y/1iyEa1c7sS3nyXxw5x4pqzaSUpqRUNKKeHYARNff5xcOqaS7d9NTyKppptX7q1PdrqxdBL85LVadLk0n1Zdipj1XnlSFvzHP/eDFNavjKb3kEyad7DhdCj8sjSWZbMSKMxTmfVeDf7+y/9aeFySi2HPHg+ZtBkZrdGyk42Hyi1bCQGRMRqPv3uYHgOymfxcbSKiNBJrlF2PASNOcO3QLL6emsQfy2PIz1ExWSSLpydw2fW5peJ5J1+7XrdlM3eSr5movUghIkrj/CvzcbtEyDJz7yj5/cdYNqyJZsLXe2jcpvqWSfWbthhkMThXI7NXgLFDaY7LS3fVL43ClVdZBpj4VB2SGvXigv5PIESYwnl+4LA7ePu+PJbP05c5y1StA+dISU2wZ0sERQUKZovGi3c1wOUoSUAPL3k344iROe+nsHh6Wd6QrkIdHIqKj0VHhbFJGDgqnfV/HdeJTuFEbxKyfxI1e+z32AvjuH10dREdm66AjAbuvUjHT2DqBvEflBKDEqya8wuv3fKOLvrpTSLfs2E/8yZ8w5g5j3BB3zNrWClM5yFLxh54Lz3qGDG4bJP5ClBSvDpR/pKRJSJiaJVJiHQfAWdg8UDQdBVo1zownTX5PB2oNNH56KOPiIqKYtWqVaxatcrnMyHEWaJTSbgcLlRVCVl9pSgCLahasS+EgN9/jCklOuFaGpxzTQc8Hg8blm8l4+AJYpKiOefqDjjtFf2HatV3MOvdFHZtisBklpzfI4+rB2YTm+ghL1tlVM+m2IsqrgVt+iWSx/uXVamUnwTXrYhm3Qr/Vg7RcW5shWqFSRNg33Yr7z7hX4jtwA7/OUcAgx9OxxqphTVJ3PviMWKTfCM/Jce1v6CIyT+WLVuUTJhSwpz3U5j5To3SHJFj+81sXBvFl2/X4M15eyt4OykK1KjrpOJkLbAVKqxaFMfVg7JJru3kxDH/KsnloXn0nKm3Hq3LQ+MP0bh15SI7vpN/IFZeYhewEYC/N1jZ9EtgSw6hwJfjCrnwpqqTHIA3h7zBmvkRpaQvmKq1yaIRHeehME/FYVfwuAW//RBLToY+hp63Zum6TgFymqTUpRRG9WxC+mFzBaKZcdTEX2ui6HhRYVDvNghMpoSApFpuUlJz9KTV4sUEqgRyOXVxyMI8lWbtbVzcOw+PG28pvm+bAXpD/y5L8mBK/i55Fnn7da5BFoxHxIwuPfLgjiO8OvidClVymkdD0+Clm8bzyY53qNUodBS52mDtD4WT0KvnAjwr495DWHr4bBLCCPEfIbNv05PSS8/fe10s/SDilqqPy7MvvP3ce84Y0ZHSAbZZSNuX4DkMIhKs1yIibkcYKido+V9ApYnO/v3+8yHOompo0rFhSJJjibLQuH0Dtv38d9jtSilwOsqecHUbO9j8a1RQwpNYO4E/l27k3fumkHWsTJAvIsZK1wpvZ5IDf0d4bQL0B+SOvyKYPTGF12bt4+clsX7NOHUIr1O4v7EEHl9BroEJC3fx/jN12LvFGnTf8lCNkgYN7Bz821fU0GjS6DEgO2S1iqbBiaPGoG/iJ08mJX+vWBDHzHf0h72nNKql/5udYeSZwY2YuubvCrlBxTZ/1g16u+tWRnPN4Gz63pHJx6/UCqtqT/MIdm+O4L4rW3DHU8cYMOJkAcDAJeElhE2fRP1X3J2MdSuj6dQtHykFuzdbKwg2Sg12rdtLTnou8TXiQjfoB3s3HWD1vC2Euo9q1nMw+KF0Lr0uF6NJ15pZ91M00XEedm2yoho0PG6Fcy4tqCCF4NOigMzjRtIOBSbOv/8QTaeLC4O2Ec731a7Lr6B1J1jeyKHdZvKz9ev6yj31ufCaPHoPyaJu02JsBSprvo3FZNG4dkhWRRkBpSaodfXEa6UGONcSOKwswTYTGTWyVHBx0ftLA98HEjRN8s2kZdw99rbQJ1tNEGoyxE/UfcHwUEYQdcIioh6rQHJKjzW2gqQlSNtMnVxKGxiaISIGgfmyU1tSEmEuw1aDUnc4kJoNmTNUtxbRt+jJ57aZSPt8SPjcR2vq/wNOqSBRSsn/kN7gacFFN5xPdEKU7oXjB4qq0G/ENby95iU+3fUud7w6CHNk6KRiRZE0bVcm9HbN4KyQUZ0L+nbh+evGkn3cV3XYlm9neQV3c1HhX6kJ7IUqTw9qhL1Iz0kJjKo8OCRLvkhkxMtHTzo+cD+qKjnnsgKGPJpWqjdSgthENxZr6PtXUWD7ukj8eNkGH63Uy4kDXQfNIzh2wMyfy2NO2g4r5scHbNPt0s+9752ZtLug0OuUHf7v8JNXa3v9w1QwXYhImAlKcJNEIcryScLBzSMyeG3Wfl6fvY+ZG7cz8rXDmK0VL6DDT6QwXKyc9TOKIdQjTDJu/h4uuyEHo0m/RgYDnHtFAUJASqqTEvuSYCSnDIF3iozxcNN9J0J+E+HMmap7MVLLJdi7aHlJAykFa7+L03PSOrVmWPcWfD62Fp+8WpuvPz55OVoF0zkoiV+gJC1GWK4OPSCKfUxF/1y6IegLmubR+GPpxjDarV4Ic3dE0ncQMQTUBqDWAUtvRMJcRNSw4MeqySjRo1CSl6GkrEFJ+BhhufzU82aMHSCk47oBzN1OrZ8wIQvf86qBn/zc8IAsRuaMQFbd8O9fiSoRnc8//5y2bdtitVqxWq20a9eO6dODJXOdRSCYzEaenfsIBqOKetJDWyiC5uc0ZvAzNwCQ2qQWA5+8jrlpU+k57Iogreo3b89byryJGrcppv8D3pDkSb9bRVVofUFzNq3QhehOhbtqmqAgV6UwL3BpddUh+Gt1NL/9EIPBpD9kVaOmLz35JRN6AvR1w05wwTX5PDj2MEazRAiJwahRbFNKNX2CYfNvkezcGFFparZzg5UDO6xBRQBVg8Zfq8uqwDSPHvmZ96H/ZM7kVCf9h+uJzCaz5OUZ+7nz6ePEJFTmwST58IXaSKkhooYjTJ3B1I5wHgfhPvPLkyKTWXLNLdm8OnMfBmPZBTdZTSTU8k/owkFBdmEI81kA3Y/McBJfKIniXXFjTimB3fJbZKnXmj943LDp58Bv3Xc9c4yEFHdY90no35iqRxYsvQhEruo2KSYiKvj3rnkErc852e/Mo1s+lO0VajAV9tM8oR8SUgu33eqFMNRDiXkSJfl7lOSfUOLG/qMVTUIYEZH3BdtD13VSqv5bCBdSOsA+i8DfuaYLJzpWBfj8v4lKz0QTJkxg+PDh9OzZkzlz5jBnzhyuvvpq7r33Xt56663TMcb/9+hwaRs+WPcmlw/uhsmqJ/zVbJDCsNdvYezy5yrYM1gjLTw4+W56DLkEwCcapKiAgAfePEbNui5KH5KW67lr/Js8MOlun4qIiJgIbnz4Wu6dMIRDfx+ttgjdqoXxVGuGtRdZaUbmTkrB7VQQQvL2oj288uU+rBGaT2RDUSWKAo+8dZgWHfXI1jWDs5m1cRv3v3KUPndkcv3dJyi2h56W3n8qlc2/Rob5xq8vdX0wpjYP9A5uOlgCt0uUTrDZJww8dkMjju03o6h63tNN92dw7dBMLumXzcerd9L63LKJy2SW9L/vBJ//vgNzRLhkR1BcpLJ1y2MI07n6JrV+mMdWDaoKbc610e3aslL3hJpxYTt4S1mMtH+LLJyMtM1CatnUaJAckuhYIjzEJwe+LpYIyVUDc1BUycKPkwJGrUrylL75zL9oYXyyi6sH5YRleYJIDo8weo4hokZ4lzQq3nxmq6TXnbWCRIMl9ZvbaXNeScWWdz/rIDB2KdvR2KnCsRVhBGOZ3EP7S1vR5dJCBj6QzoAR6TRp60umVINy1supPCJuhcgRlGgS6ZE673dqvRER/diZGYf7kJ8KvpNhQLo2n5HhnClUWkenYcOGvPDCC9x2m+/a62effcbzzz//r87h+Tfq6JwMKSWapqGGofKmaRrLv1jDgncWs2fjARRV4ZyrOnDjqLq07fwnyCxQ6yKs/XX/Iu/TVdM0ju9Lx+3yUKthCiaLib+Wb+GJK1+srrPw/luFkK8fJ/SKbeufn3dlHi9+dgCA/GyVZbMT+HN5NG63oFUXG71uzaJW/fCWRgJV20gJX09NYvJzqYxfsJsWnW0VogMnY/5HiXz4fCrhnv/5PfJo1t7O7s1Wfv8xBs0DBqNk2i87SEl143b7Wl0EmiRnvRdIt8c/Rk68iz73XQWA5vgDck4h4TIMeDyw7Y9IHruhCQA1GiQzY98HIY+T9m+85bmF6JODBqgUOG6if6OtAavPFEXSe0gW97+iV8pt+iWS+R8ms2FtNEhofV4h19+dSesuRTx8XRP2b7cyYGQ6d4xOK5Uq0MetV2SNf8i/p5XRpDFjQyZx8cfDuxAxb0D+0wTXbVHAfBWoKeA5ri8baeXaFxGIyGE41Tt55to32PjTVoQiSomfUARxSUbGLThMnYZebzg1FRF5F1gH+SzHyOKlyNwQRSTW/iixr+j7u3bhSLsbk/EYbjelxq1bfovk5bvrk5tpRAjBh5vG0bBNvfCuyf8IpCcN7F/r/yrxCGsfhKHhmevffQCZ6T9PqQyqLmIYFUwt+szjjAoGWiwWtm7dSpMmTXy27969m7Zt21JcXJ3lq9WL/wLR8QdbgZ1l01aw7NMV5KTnklw3iZ53XcEVt1yMyaJHgDRNQwhRpfXkbyZ/z7RnZlKQHTiJ8kzgshuyWfNNnN/S6ZOtGwBe/Gxfaa7F6cbQri1wFCuM+2oPtb1VUoGI0YGdZu67onlIk85QGDNlPxf18q9r5A9Swqdv1GTO+ylIqU/0eoWa7zgURXJhz1xuf7Y+qe0eQMhcZO4jBDZBrD5kHDFy67mtAD0Rf9L6N4PuL4uXI3OH+/8MmD2xBtNereh5BBKjWTL9jx3EJ7uZPyWJD59LLad3ROn/3/pIGgMfSOe3H2JYtTCO5FQnl12fS4PmxSgqLP8qjgVTktmzxf+y1bVDs7j/lSPh3YfmHijxE9Fyn4TihYT21fJV8Jbm61m/pikb10ikVGl9YXPOuboDq+f+xrcffs/RPWlEx0dxxa3d6HX3FcQmRepESSig1KqghyOlRGZdC+7dBI3AJsxDMbVDetKRmb29pNN37G43HN5jYeTVzRgxcTg977o8jAtyFmcSUmrIE5eFtGcRifNPu9VHZXFGBQObNGnCnDlzeOopXzfd2bNn07Rp08o2dxYhkJ2Ww8Pdn+PYnjQkEiTkpOex8489TH74U4xmI9EJUVw++GKuHd6DuOTAUvknIy8znxHnjSZtv3/xuuqG2epBiJKKIig/Aac2cvD4O4e5sn8OLw9rQFGB4rV1kHjcCqkNHVw1KIsVXyWwb7texVCQp1YLyQmlneJxw+U35jBjfE2GX9mM8Qv2BPSIEgIatnDQ5dIC/lhedTKtqJLjh0InnZ/c9+1PptHn9kxWfh1HVpqR6DgPCz9JIueEd01GSBRVMvSJNGrXOQzZayq9wFg5o8gyaBrkZOqPHKEILht0MX8u28iCd79j+687URSFc3t25PoHetGsc2N9Ei4YT6CSdgH0v/cEX01OJj/75AioQEqJ0aSxd5uFD59L1cfgJTlRsW7adi3CaJT8OC+e9hcWcuE1+Vx4jS+xlBLGPVAvqGZRr1szg8n2+ODgof40iJOIqHuRjmW6BpFfslNyzmWfSQnCMZdFExuybmU8CJg34RuS6iTy0qIneOfnV/x3Gqxc2HP0JKd3f1ARzp/B1A5p+9wvyQE9AtawRTFT/7qG2q3Okpx/I4RQIOoePULqFyoYO/7rSM6potJE54UXXmDAgAGsXr2aCy/UrQJ+/vlnli9fzpw5c6p9gP+rkFKyaeU2Xh30Njnpvm/aJeFpe2Ex9sJi8rMKmPHiXBZ9sIwJq16gbnP9oX5w+2E2r9qOlNC2W0ufMLKz2Mn95zxJ+sGTy4xPD8xWDwk13KQfNuFvRuh1SxYeDTp1K+TLDdtZ+XUcOzdZMRjgnMvy6dRdd+O+aXgmW3+P4NXhDXjnsbp0vqSA+KRTqxAINWlLCYk19CQal0OhUavioMe4XXBhz7wQREfSpK2dBi2KKSpQ+WtVdKnlA+ikoMQrrLJIrOHmhnsyAZ2kCUUy7bXaKIpEMUiennyQOo2rXu1UVXIpgO9nJ6AYBPFJKpn757PwnWyad7LToatky+9RrJz1Mz99uZbHPx3B5TfXBs+eoG0qqkb3voV8+1lchXwdt1Nh1ns1KMpXSzWMjCaNu8Yco+ct2ZjMZfvv3ea/ZFwIQd2mGod2BV5Krt3AETI3R0r4/cdonhsykfqtvmbUB8No2/UL3dPJs48yYlNS5u+H2Al9+W/gg+n8/mPZvZV9PIfHLnuBKVsnkFQ7VHXPyQgnAi+Q0q7/au2LCB6FUqhZ6w/gzkqOo3qgW0f8jixeCJ5sUGshIq7/f1cufUqw3qzn6tg+pkxDyXvfGZoi4t77Z8d3GlBponPDDTfw+++/89Zbb/H1118D0LJlS/744w86duxY3eP7n4SmaUwYNpll01ZU4hhJflYBz133JmOXP88bt73HhuVbQHgfoRLaX9KK0V88SGKteH6aufaMkRzQc06OHwgcoWjSriz3xRKhcfWgbK4e5H/fFp1tjP1qD/f3aMqymQncPNL/eVQ18nAyhNA1b0CiGmVAA9HS/RX9HILh+U/307VHmZWFrVBh5js1mPN+MiBQVbjgqvCXrQJBNehJ2OtXRtOuaxHXDM7y62geLqQEzdgX1ZTkfVCGB7cb0g6a+XFuPKkN7AwYlUF0rJu7nyooJQkup+D72fFMfi6Vsbe/T8eLhxEfIqglhMrNj13K+tVHObY3vULwZ+4HycQlu70aRpLRkw7StUd+hcTyBs39T/iFeQr5OVZ0ETr/KMxXMVuDX9OCXJU3R+oJ34f+PsrjV7zI2OXP0eaiJeBa742qWJDu7WD7gkBkQlWhZScbsYku8rL0KJ3m0bAV2Pl20vcMfelmv8cFhFIbMBPcgNWNMHgT62VBkP1Ar9o5/Uug/iClHZkzApxrKG8GKu1fIi03IGJfRgRSg/wfghACEfME0toHaZ8D7gOgxCAsPb2aQacm4vlvRKWJDkDnzp2ZMWNGdY/lLLz46q3FlSI5JdA8Gof/Psao858i87iuiOxd7QJg69q/ebj7s0xa/wbTnp5ZfQMOCYnbJUqF2fxh+7pIls+Lp6hApXYDJ1cPzCK1kf/JxWCA2g2cjHztKN/Pjaf/8BN+yUd15e6oBmjQwo7ZInE4BBlHjSTXrmh7UdovupibPyiqpGFLO+df6TthRERp3Pn0cUwWjS8m1KDfnSeIS6o6ISmP2AQPY78KU501BIQANX60XgprqIMseNs3t0dpCEoMuHUxshKymXHExM9Lo3nukwN0vLiQrHQDcUlun0iI0SS5ZlA2Neo6efa2Jiybvoub7/K/bFUGD8kNOjBt5xNsXLGNA1sOkZdVwNfvLaa4yI7mEeR6l+3adS2qsDRVAv/kVbDo81bkZwU3oN3424Vc3nctwSIdk5+rRUKKi6hYPaqpAZMe/pQP/nwDTF30/wCZ/zfhrIFZrJLydELzaKyYtbbSREcoEUjrDWCfHWD8AkQMlAjtqXW9pCzQd6Lq+jX/AGTe8+WsFjy+/xZ/hVRrIaLPKveXQBhbIoyBlrD+f6HSyciguwsvWLCAHTt2ANCqVSv69u2LIVQ5yj+M/0IyssfjYXD94T7KxJVB+coL/zvAZQMv5qcv11RxhFWFRFGDW1GoXuPPEr+iwQ+lceuj6QGTfoWA3EyVogKV1IZOPB5QBH6XEcKJ7kipLxkFKngrKtDtF2rUcdCpW1FQmf97L2vGoT0Wn/NVVYklQmPCwj3lnOV94XbBZ2/WYMgT6SGru/4ZGBE1Npa+9Unp1L2RtDww1ANDW90QMrOnlwAFEksMLtD39OCGFLvOZfzXR8H5KwFJhIhEpPxewYcpffd3zB//Jj/MiacgTwWpSw1cdkNO+NfVejO3tEvnxOHsgLsoqsKVt7Ti4dfmABUJkccNhXkqRrNGRJR+LY7sNTPznRR+nJfA1G1vUb9lmVijtM1F5j8ddFhFBQoD2rbG5fS90eNSYpmbNjXMkyuD1HKRWQPAc4iKztoCET8JYe7uHd/MIPkdOkTCLIQpnJL1U4d070PavoDin0A7GnxnEYVI+QUhAitbn8W/F6cyf1daR2fbtm00a9aMIUOGsGDBAhYsWMCQIUNo2rQpW7durWxzZ3ESju5OqzLJAULqighg7fzfqtx+1SHQQqSceDx6tVUJOfjirZosm+k/56CEZMTEe6jdQI/8qGpgIbZgJGfL75E8e1sDetZrR8+67bnnsmYs+SIBt8u3vchojZ6Ds+ncPTDJKenrpRn76XlLFmaLvoRlNGlc0T+bict2BSQ5oE/+KXVcuIoV/iG9tSBQwHKtT2hbCBPCfDHC2hs86cjswXDiAt1aIFgkJliOkxuuGZSFwSgQMU+BCGKWKe3gXF9hc0pdM/c8f4x527fxxbrtmK0aiTVdlSA5Q1BiXyQ7LfgyjObRyNj3G4GImLNYEBXrKSU5ALUbOnjs3cMMejCdzCNZvgdYenp1c/xfII8blnyRWIHkKKpC7cY1mPnaAt66ezIfj/6C/VsOhjxNAKHEIRLnQOQdIEr8yQSYL0EkziolOQBYbwBjZwJOHdYBYDwzKQyyeCkysxfYvgxNckBPonZuPO3jOot/Hyod0enatSvJycl89tlnxMfrSo45OTkMHTqUEydO8Msvv5yWgVYH/gsRnQPbDjOs7cP/9DBOA2RppCWYUrAPhKRmXSfTfvk7pB9VVeAsFox7qC6rFsbhz1KifrNiJv24y++yRrj5Px43FBWoRER5+Gt1NOdeHjzHweWEeZNSWDwjgWHPHueinnmlESaPG04cM2IwylPKs6k6zIikbxCGBhU+0QregqJJBPPMqiw8HgU1sh8414F2KMBeip5wmrQcIRRyT+SRfjCTqOgCasUOoOS73PRLJJnHjHTvlxua7KhNIG4iirERN9UeRk5absBdFVVyab9cHn/P//g0jaD37tHsadRtdaHPNln8AzJ3JPo9WUagPB44uNPCI/2aYPPnIydAURRdQFBKPG6NS2++kEen3V8JYUY3yHxdpydA5ENKO7LgHV1hV3qFApUkROSdEHF7hRL20wHpPuLVg/FQGWFSET8VcYasFs6ienFGy8s3btzIunXrSkkOQHx8PK+88grnnHPWYj4c7N9ykOP7M4hJiKJl12Y+4oCpTWsSHR9JQU4o9cqqIVxTwdPQM3Ua2ck4YsblKr+EFaQuVwrSDpk5stdMvaaVc9wOBYdd8OgNjdm10Z82ij6eg7ssLJuVUOoAD/q1K8pXiIwJbzJXDXrUSWowfXwNzrksuO6PaoDMNCMnjpp59Z4GxCa6qN3ASWSMm3UrYkrH1v7CAu565jjN2tuDkq5QbtmVgTRegFBrV9zu/NNLciAckhMuSVRVDYq/DtGmBp6jHPv7B6Y8vZlfFv1ZGtVs1KYDtz+xj3Mvz6P9BUUU5SvhRXQ8+yH7OmT8NK4aeilzxi6s4NJd2rtHcPmN/pe2QsoWeASpdX4BfImOsFwJCV8iCyeBczUgQcSy4deWvHJHIbaiQPbqeoSpfHBp5ZxfsESaeXiKfy2ikyGEAUTwyi0hrIiYJ5HRD4B7P2AAQyP92DMEaZ9JRa+mUFDA0Pw0jegs/s2oNPVu1qwZ6enpFbZnZGRUEBE8C1/s+H0393V5grvbP8pz/d7koW7PckuD+/hhepmviNFkpM/94ZjsVQ1SQq2GKadgVFdVliTp3jeXSct30vu2LGITXT6+R8HgclR+rM5iQW6WGtC7aNZ7KezaVLJEELj9bz4tM0T8ZWkMw69sxrtP1qkUcXC7Yf2qKHZvjiDtkDGoOajHLVi1KK7077wsIzvWR/qQHIAtv0bxcN8mrFgQS1a6/4lPavpE6ywWXjNQ/fuvMtF1rUTm3FfB8E8WzSCY2aXPvpWuhAt9jxw/aGLkRR/z6zfrfJZu92+XjLmtPisW6C9l4ZJT3dzQgcy9n+tGXUlsckwFHzrQIzUdLy6gYwC3ciGCn6uiSHD+iZb7EFr2ELS8Z5BOPYlbmDqhJEzR86FSfoPkX+ly7UO8830M4+Yf4bF3DtGpewFJteOIjA3svyU1ydJpK8g8mhVwn1CQ0o7U8pAnGcMJYUUYWyGMzfySHCklUstGek5UOPaU4QiSt+UXKpivRKg1qnccZ/GfQKWXrr777jsef/xxnn/+ec4//3wAfvvtN1588UVef/11LrrootJ9/23LQ2d66SrjcCZLP/6J/VsP4bA7+evHzWhuj9+J5sHJd9Pr7isBcDldjOr6NHs2VK+dhqIIajeJJ21/dlDzwuqHHrVRVMlFPXO56f4TNG1n55dlMbxwe3D5c9WgMXvzNqLjwntQ7t9h4cu3U1j7XRyaR2CJ8HDVzdkMfCBDr/IR+hLQze1bk58T+g1UKJKHJxzm58Wx/PZDLCAxGCWf/vo3CSmukKXmHjfkZRt4sHdTstINDH3yOH1vz0I1+C9T//iVWsx5PyWscy0jnZJet2Ux/MXjpQ7dACeOG/jo+VR+/zGGi3vlUruhg5gEN+0vKKRe01PQ0Yn7AGEpM5XVMi4NL0fiNOHFO+vz6/ex/hPdBUREqczadACzJRuI0p2kAy6FnXR47NukHe/Ma4PfYcfvu8u2K4LL+5sZ+cqfIaUEQqOsFBo8YO2PiHmpdAlISg8y7ykoXlC6j5QqQniwFbdnYBsPxbbARFMIwcj37+Lae0NJ//tCOn5FFn0ITm86gpKMiLgFIu9AiMB1/1JKKP4GWfRRmRihUhMROQQihlRL5EfLvAHcW0LvqHcOah09SVo92cn99EA61yNtM8G9U0+Yt/QE63UIJTr0wWfhF2fUAkIpt+BcEhUoaaL830IIPMFeXf8BnEmi883k75k4YioIgdS0kG/R1igLs49PwRqpr4s7i50MrHsP+VnVY8tgshjpcEkqfyw9gP/losr4U4UpA+unXVWVIOD5afvp3L2AW89tRU6GIahdwrW3n+D+l4+FjATs325mVO9muF3CZ9JTVElCiot3vt1NUi03GUeN3HpOq0qOvwR6u3UaFzN23l7iU9xeu4WyaIX0Vo7ZixSWzkxgzvspZKcbURTJHU8dp0ZdSc36RTRrZy9tNS9L5fNxNfn2s0RCXVtFlUREebAXqV6LBxBC0v7CAt6Ysx+PG14a1oDff4jxe11fn72XDhfZECL8CTor3cB30xNZ/U0cdpuVxp060Wf4VXS5qgPyRA/Qwkt8rW7kZqnc3L51yLyvF+ffyHmXbNAdwYNqxpSHASKGoMQ8AcDeTQfY+edejCYDHa9oS2LcUmT+C1Q9yhkYIuoRRNQ9AGgF70DRB377kVJhxYIY3hgR2JRVURWGvXELNz58bdj9S/t8ZN5o9KB/+ee4AOM5iIRPKlS6lUAf7/tUVLQWYL4cEffeKevZaAXjoOhjQkZ1lGSwDkBEDkEo4avGVxW6mvdrYPuUMgLrvTeVJETCdISh0Wkfx/9HnNEcnRUrKq/v8r+GP5dt5N37pnj/Cu8haC8s5ucFf3DFLd1YNecXZr+5MCjJiYyNoCjfFrh5AbUapfDI1PtAQqMOdXmo620IYQggZ1/+oRSKyIRPcpq0teN2Cg7s1G0bSgwSXx1en1kbt/P0hwcYPaAxbhdeUTf9OKFQ5m0lRVhLHrPer4HbKSpM7ppHkJ1hZNKzqYyZctBHETfU+COiPdRr6uDofjMF5SJAR/ZauP3CFlx2fS4XXpOHJdJDo5Z2vpuRyGdja2IwQnGR4jMWCVwyeCiRNfsyrO2zxMQeo1Y9O0UFKlt/j8TtCr6SnFjTxc0j0+kxIBtLhMTpEPw0P47Z79Xg2AEzG9fGkJtpICbBTVItl1+SU7OeI+BSSyDs2mTlyZsaYy89H0lW+gZ++2Y9Pe++glGv1EWERXQMaJq7WhPLTxw1hSQ5nS8poss5z3tFgCvz8uXxEchr3L4Bjds3KP1ban2gYILXEiEQaTR6+6xc1EcWfQyRt+vH2T4j0A9dCI1L+uXyyau1OHEsAPHwaNRvVcfvZ3779mQi857x9nny9ZLg+hOKPoWouyse69ruJTn4GbMEx49Q/A1Y+4U9Hn8QEQORRZ9QkUyV7gEJc1BM7U+pn0rDPs9LcqDs2nnHp2Ujc4ZB0vdnhQvPMCpNdLp37x56p/9xzHp9AYqqBExg9AsBmUey+Oy52cx4aZ5eOREEtgJ7iOpdQb8RPWnfvTUAh7cu5ODO4JUXQkCz9kXs/9uKszh4/0LIoP4/JaO47q4TXNQ7j1HXNOPgLj1aJaXAXqiw8us4rh6kl1zP/SCFFV/H4XIoJKS46XVbFrs2Wfj9hzh2b7aGnBylBhtWRwWMDGkewS9LY8k5YSA+2U3Dljb277ASmLTpZOu1mftp0cmG2wWrFsUx5cXapb5RxTaV72Yk8t2MRABe/Hwvn42thdspKly/2EQXdz+XRnLsWLC/xdiFPXnwqij2bTPr19LPCGo3dNCpWwGKKkk/ZOLBcUeISXCXJtSazJIr+udwce88HunXhP07rN5EaYhP9r82WSeACGMgOB2CMbc2xG7zJW2aW7+3v/voR5o1PcI1g4O34/K0Yu2iYyTWdNH6nKKQS37hIio2OHExWzWemrwPRZHknFA5sjeCNufZwswTkmCfj7T2QZjOrfixiICoR6DgNUqsFNIOG1kwJYUVC+KwFZrofp2ZUa9uw2wpQH/c+iMP/rrOBdcOwOElUoGhKND50iKWflGR6AhFkJSaQKcrK2GBYJ9PcGImkbYZEDmsQq6ftM2mLJLhd7RI2wzEqRIdNRXi3kHmPoDvNdXd7UXMC4gzTHKklMiiqQQmXx7wHAbHKrBcdkbH9r+OKj1uiouL2bx5MxkZGWgniX306dOnWgb2X0WxzcHmVdsrf6CEE0ezWfT+Uv3PEHo4oT6PrxVHy67NSpcRi7LD1dSAhycc4vX7GgTcR1Ul516Rx/Z1kaUy9P5gNGmcd2UBBqNk8ENpvDq8rE3VINm7TY/y1Gvq4JG3DvPwhMN43GAw6omz381I5Pcf4vj7rwj2bbNQv3lxwFLvw3tNPhEXf9A8giP7zMQnu2lzXhH7dwRI4hQSg0HyyFuHadFJL581GOGSvrm0PqeIUT2bkZddsa8GzYsZO28P4x+uxyEvqTNbNUa8epgr+ueWI2tuatdaxKyNuv/R7k1WCvNUFs9IxONWiIrx8Og7hzj/yoJSLZ3yS2MAe7damD8lmT+Xx+DxQNN2Nuo3k8SnuFENkJXm+72UEO/GndoA4askr10cS25m4O9YCMlXHyZx9aCsgORh92YrY24T5GTUJybRydi5+6jXzOFzXiXLf5VFrfpOGrexsW+71W9kp3vfHKyRGh+/XIuvPkrmifcOBhWFrAgPMmckpKzxWaqRxSv0ZatyLtBul2D2eyksnZnoXTrVWD7bzsqvGjLgwSgGP9kKg9GK1ArA9jmhozwukKGT6aSE2ERLhZcrRVVQjSqjZzzgU9kZsr2QJp+AlqZrGImTfkPunQQnchq494Y9lmAQlishaakuGOhYo/drOg8RMQhhbFEtfVQKWrZesRcUBqTzV8RZonNGUWmis3TpUm677TYyMzMrfPZvzMs503A7q65vsv6HTagGBY/71CsUso/lMOr8p2jQpi7DJwylYbMaKKoMqkwspWD/DgvnXp5PrQbFpB0yV5w8hESTcN1dmTRtZ+fzsbX8tiWEpN9dmUTH6ffDRb3yMFs9OOwlD1yByXxyFYdOKMo2lP3Pa/fVZ/yCPUTGeHzITsnk//f6yLAE9ixWfadjB8wgJJwUlTJZNAY9mM7VA7OJT/b9LlUDJNd2MWBkOh+9kFo2TEXS+pwiklPdpKS6+WjFTv7+K4Ije010ubSAuCSPXxKgKNC1R0Gp59XtT6bx8Su16HFzDo1b20v3KX99AH7+LoaX7m6AIsqW+zb9Eo3mEcyemMItD6ex+pu40uPiU2Jp1L4+ve/tQderiiB/UegL5cWW36KCWndIKTi8x0Jhnlr6XZdHdoaBJ7zLXgD5WSYe6N2Uqwdm0/OWLJJqucjNMvD9rHgSarjpe0flq4NufzKNZ25t6PdFunkHG9Neq8XcyckgvcualUqpkSBzoPh7sPbWtzjWIHOHV+hMNUgeePMobpfC97P1Em292k0wc7wNt6jNXa/fAs4/kaXLG4FgBENTL9EJrk0kBNz4xFPYXNv5/rOVOGwOFFXhwn7nMviZG3yW28KCsBB6eVqAP08kEUngiEbJPtbKjSfYKAz1EDGjgdHV1mbVEe5z+1+nBPr/HpV+hxo5ciT9+/fn+PHjaJrm89//OskBPXcmqU5ilY49cSizWkhOeRzYepgnerzEj3PhgqsL9GRgfxD6dodd5aFrm2IrUMuRHIlQJEJIVFXSuksRTw1qxOdjaxEZ49ZdsRWJ0eThol65vDZrL/O2b+XOp4+XNq8aICq27Nw8bsH5PQKbVhqMsO2PyNK/D+22cF+PZiz8JAlboe9tm5etsGZxqERDiTXSQ2INfekmP9vgQ3Iioj3cODyDGX9u5+aRGRVITvnzuGZQNkq56yg1wc4NEUwaUxtHsUAIaNnZxpU35RKf7J/k+IM1SjLitWM0a28PuLQjJezdZkVq5XOaynSJZr1bgw2ro3l5xn4u6ZeDahC0vqgFry8bw4XX1kLkV9LrR4THCkSA/b6bnoC9UPEh2MU2la8/TubuS1twfYs2vDSsPtYoSbdrg6gQi1hQ6vn96JzLChg9ucxiQTXo96pQ9CT0+R8ll37XG9ZGBbWe8A+DbraJd3ki/xX8abiUaFQNe/YYRpPv71jTJN9++APOYicYu+iihAFL8lWw9kMosXqVkOWa4PsaWhNX6wJGvX8XC7KnMfvYRyzM+5xn5z5SeZID3oq6YM9yVVdN9kN0hOUqgjNJVVd//ochPcfRCt5GyxqMln0rsnAS0lPx5b1SUBK9JqnB4EYYz4w9xlmUodJEJz09nYcffpgaNc7qEfiDEIJ+I64JmWPjD57K5PRUEh89No/mnWJQDP4e0FKPpphKhPKs5GWVm2m9lUQ16joQAnasL0ucfeajg3z+x3buePoYby3aw5gpB+l4cSFRsZrPBO9yQn6O/rBWVEnzjkW0Pte/KKLHrUcCfv7Ol7ycOGbiw+dr++jM2AoVHu7blHUrfXVmKkLgdgtuOac1917ejOMHTaXXIT7ZxcSlu7jzqePEJIQmJhHRGlGxvkTI5VT45rMknh3S8LSX7l/RP4dA56qokq8/TqJpexujPzjE8BcPs27ZBgA9r6JSybjQvmtRwGgO6PdO/eb2gBo1R/ZaglbUgb6MFIxcAhA5HJG0CCLuAMotl4gYiBzJJbcOZ9bGLTwx8SCDH0pj+IvH+GLddnKzfHWLVi2MJy9bxVOpwKsbnOuQWj64t4NnH4GTg3WByC6XVlTALsqzcXxfuu4eHfeO127hZAIjwNAEEf1EuVMcA2o9Kj6uFRAxiLgJpVuMJiMJNeOxRISwfQ8G08W4ZRM0zd/3rkdrRGTFRGQALL29k70/YqYAJkTEbVUfWzVAFi9DnrgciibridXO35GF7yBPXIZ0VF3ZXwgFETk0yB6KXgVmubLKfZxF1VBponPjjTeycuXK0zCU/z+4/sGedLq8baWPM5r8vcZXVv0zMD5+CVzOigJ5UgpSGxTjdp5UClq6g35M2iELHrcojSToybKFJNd20394Jk3b6QmZJxOFkvB9yWk0bGHnhU8PYC+qOAFKCcU2heeHNvDj5yNJSXVxSb+c0nL9bz9L5Oh+c9AlOSEktzySRp+hmXjcgv07rBTmGUrP8ZG3DlOjrhNFDU/MzuOGjhcVcP8rR7huWEZpNENqgk0/R7Pm27jQjVQR+kQaeJbWPILt6yJLc1CuHZpFl0u9yr2O5ZQnOm4XbFgTxZpvY9mzxepXAuHCnnkk1HD5RLDKQ0rBjfeeCHjdYkM6sAv/dgblYeqKiLwdoUSgxDyJUnMjSs1diBo7UWqsQ4keCY41mK0ql12fy+CHMuh7ZyaJNd0U5qo+y38Ou8LTgxphK1TRPGXiiSFFNlwbkVkDkO7QuW5SQkKKf7arGvXfuDA29RK3oV4lYgOodRHRjyESZiOUsvJZoSQgEudB1AN6ZKsUGkgb0jYDqVWPDAXAipm/MORcK/t36GTJ7dJFLzUNpDQgYscjTJ39HiuUCETC57rLOejnVZIhIWIQCR8jDP4jc2cC0r0HmfsgFSvhNMCBzLkX6UmregcRt4Kll/eP8ve1AiICET85YFn+WZw+VDpHZ+LEifTv3581a9bQtm1bjEbf8OWoUZUMjf8/hNFk5KVvnuTNoe+zctbP4R0kwBpRQHGRCUuEB2dxSZVL+RmkMvo1ARCgUurIvvDWzctXWjVtZwvrGCHAGikZNuYYtRo46XxJQcBkUCHg8B4zxw7qD1nVoAECj1tQu4GDR945gDWibFZaNC2JYKKrQkguuDqPwQ+lc3Sfma8+9BXjq1XfwTmXBfefKo8SAcCnJh8unRwbtixmwsN1AYGiSL77IpFLr8sNu83KQNMg42jwB2V5UuLxwM2jvJNgucTW72Yk8OkbNX2SyRu2svPAG0do2bnsezWaJC9P38cTAxpTmKeWlvyrqsTjEfS78wRX3pQTcCzRce6guWGqKkvzkfzCci1K3Hi/H/lU/EgH/l4IajVwVuh7z5YIbr+wBVcNyOaCa/IwWzRSGzmwRoZgO54DXrIYHEKA3abQ5/ZMYhPdZB4zsuqbOKITalK7cVkkXKg1ETFPQMwTQVrz7qtEI2UhuiN8eTjA9gXS+RckfIFQyqJd0nMCHD+AVgCGBmC+NOQku/PPPbx+23tITeH+Hk3p1K2ArlflY7JoHPg7gt9/qsekvy4j2NNCGOpB0hJwrkE6fkZfrukAlquDCg2eCegq3uD/5VECTqRtNiL6gSq1L4QKsePBcjWy6Avw7NYTti299CRptWZVh34Wp4BKE52ZM2fy/fffY7FYWLlypc/DRghxluh4YTQZeWTqcHb+sYe0AxlBq6RSUp00bGnHXqRSu4GTbX9GBdhT16BJrOkiN9PgXT4qE+RTVEmPAdn0vT2T+i2KcTkFP38Xy1cfJrN3a2CZ+KrC46oc6ep7Z3iJpi062fly/XZWf6tXXKkGSefuBXS+pICvP0qiZQcHhfkqr95bj8zjwR/cUgrycwwoCiTU0Cd6s1WjXtNiNA3qNw/sJF4eHg8c2m3G41JIbaRXDJXc+lfdnMOPcxPY/Kte3p528PS9sQmhk5RAUFVJl0sKyv0NDVt4c6GMHcDxAwumxjP52dQKxx7828JjNzRmwsK9NGtvw+0GgzcB+6MVf/PD7ERWfxtLsU2hUSs7vYdk0a5rcCf3Fp1sQaNtHo+g95AguRHF3yHdIxCGhoH3AYSxJbL46wrbz7sin+g4NwV5qg/JL8gxMG9yCvOnJNOpewGvzAhHhdwDxT+C2jjg8pWU4CgWPPLWYT2SJPVKxvtfPcLOHc19BFcrA+naBUVTAnyq6Utqti8gahhSupEFb4BtuneMXtE/EQexr/qoWp+MuRO+QVEEHk2Xj1i/Kob1q8qJswkbP325tlTFPRCE8ObxmC+p3ImeAqSWDbavkK4NgIowXwCWPgilLNcPx0+ErApzrIIqEh3Ql7CwXOXNVzqLfwMqTXSefvppXnjhBZ588skq/2j/V2CJMDPup+cY0+cN9m0+iBCC8kLUKalORr1xhC6XFJQ6e796bz0URQbMa5BSkHncSFlkR3j3l9z22HFuHnkCqYGigmqVdO+TS/e+ubx0VwN++z5Ywm7lo0Wbfo3C5RQ+tgNVgccNe7ZZaNSyGKOXI5gskstvyCGxhouf5sezeHoif66IZvnceOq1KGbG+Jper6rgKFFF1jTITtejF5f0zeHBcUdQFLAXBj9nKeHbzxOZ/V5KqSCb2aLRY0A2tz91nMhoDbcLet6SxeZfo0BIkmpV3V4hFDweWP1NHEKRfsqpJZoG19/tSxwMRv3mEpG3Unjiez551X+lnKYJ8AimvtqCka/uZ/8OyZIvEtj2RwTDxhznumEnGDAyw9uTBWHqVGYP4AcFuQrNO9i4elAWS79M9KlyK9Fh6nN7Ju0vCG5gK21fIGKeCboP1n5QMA5wUZ6AmMySB8cd4eVh9eEk7SdFlVgjNO557liF5gLD7q0s8k9yhACLteJnRhO0af8VWmFzlKihlejP27Z9LsH1aSTSPhMRNQyZ/xrYZ5Qbo/cYmYfMHQHxnyLM5/tt5fdv1wctiBAIflv8V0iic6Yhi1cgc0cBZb896VgGBW9BwscIY0kqQTg5amfUH+cszgAqzVScTicDBgw4S3LCREq9ZCZvGMu4n55n4Ojr6HnX5Zx/bWfad0tm4rJ9dO5eRnIAPXcgRPLmydA04X3TT9L1SMotCxmMeonyU5MOEhkT+EeuGiCxhlM3GgwTBTkGlnyRgBZmfmtJ+XfJvyVJojv+iuDJm5rw6Ru1SpeD7EUKTw5oxJMDGrN8Xjy/fR/DN9OSKCow8Mb99fj7r8igkYLSPj3Cm7wLS7/UIyHLZiXw1eRkQK90ClaW/vErtZg4ug4njpUt8TiKFRbPSOTR65tgL1IwGHVLCICuPfJ4c15wnZpwTVf87WcwwHMfH8ASoSGUsvwtRdUFDh8aX6b9UwoRg3QfQJjOYe2P1+MMYpKqeWDTGg9Yrmb9ykQ2/xKJw64y8ak63HJOa35ceAlu4wOIhC9QEj5FRD8FlC1HSKnnc3z6Rk1ubNWGG1u1Je2QiRuHp5PaoMx6oU7TCB4af4L7Xj4aIi/K49VICQ6hxCFi30Qn677rohf1zOPlL/bTuE3ZEpkQknMuzeedxbup28RROaNT9xb8PTpLqq6CovANNC1cC4ryfR4k5CTtOYrmPnYSySkPby5Z4VuBu3EF70NKidv57yICet7N/egkR5b7D5D5yOzbkVqu/rexM8ENaFUwdTmNoz2LfwKVjugMGTKE2bNn89RTT52O8fy/hBCC9pe0pv0lrUu3afkvgq1iomadxg7Wrwqc0yCEbiqpJxWXQUpBxhETG9ZE0bm7b2KiooDRLLmifzYLP072267HLchKL1lyCT+689ELtUmq5eKCqwOXimsevYpq3IN1UVR44v2DxMZr/Lk8mm8+S2L9ymikFHw1OZla9Rz0HpLN+IfrsPkXfQmvJPm5ZBIpyDWGNUYhJG27FtL+ogKOHzDx3RclZf+CuZOSuW7YCV/dnpNwcJeZuR+klB7je0665tCiT5Lof18GBbkG2p5fyJipB/0K30kJmccNZBwz0aKD7ZSUgVufa+OTtTtYNC2JP5bH4HELImM8PDj2sH+zTu04MrMH0nQBWVmXoqp7Q8oYFGV8zUPj7NwxWmXnxggSarhp1NKuk2jXSsh+B83YHhHzrJ6AafsYe5Hgy7dTWPJloo944+Zfo9j8axTPTj1Aqy5FCPMFREeuCUsG3+UU7Nmm4I7YRoPWdYlNCuxxI6w9Qa2lm0k6VlA+2bTLJQV0uaSAo/tNFOSqpKS6SEgp+/1VzvHv5AIBFZT6oOUjRKgSZY9uEeD1sQobSgzBIzqAiEQ4liKD6tho4NqA9KT5zRdp2rkRO3/fjRZgqV1RFZp3aVK5sZ9myKLPCVy0oYEsAPtXEHknIvJWpGNpkNY0REQIme+z+M+h0o9bj8fDm2++ybJly2jXrl2FZOQJEyYEOPIsSiClW//h+XloXTM4iwVT/JOREpitWoWKJNCF6w7vtlQgOqC/bTbvYMM/QSjL8/HdFprsuJwKL9zRgLbnF/LAm0eo28SJpnkVbzW9lZwTBh7v34Sj+/Q3/+eHNuS1mftZ/lU8f62OLl1OkFLw3ui6fPt5Evt3hBItCz22S/rl8MAbR9mwOpq3HqmLraBsYs3PNuCwKxiMWkBisvTLxNKkW3+QGnzzeSI3jchgxYJ4ho05xoljRn5ZEktRvkpqIwcXXpOH2aqX7yfXdpNQwx1UlVfT4K/VURTlq3S7Ni+gx1dCiocTx0ze3CtJSh1XaEdy5+/ER6Xj8QTKASvXvrfUOzbRw7mXB0jWdm1BZg3yCsxJPhiTyo9zEyqQdM3rbzbuwbrM3paPQSmJ0ASetDUN5k1KZu6kFF3ziOdRDSqX3HwBwycMJTYpBuncpJfMO/8EoYK5GyLiFpT4Sbrjd1Y/r3t22QSY2tD/NSqJxoSreeQLD2j7CUwuToJzLRA+0ZFSgpJC8IiOXrosCz8kLEE6LRf8EJ3rRvbk1V/fDnpoz2GXh26/kpCu7cjixaDlIdR6uo6QmhL6QND9s4JeG4ks/gkReSfCdA5EPeSNapUXYtQTqkTMCwjDv4vIncWpo9JEZ8uWLXTs2BGArVu3+nx2su/JWQSALALpv9KkfjMHgx5M48u3a1bwkxJCYjRLb2m0n2Y1+Gl+HNvXR1C3iYP2FxTQoqMdk0WfaDteVEBCDXdprkoZTv7eAn2PknZdi7jg6jzMVo39O6ws/yqeonyVLb9Fc1e35rS/sIhet2XRoHkxtgKVVQvjWDY7wYdk7FgXyYRH6tDr1mxWfxNfoRfdg+pUIDGa9KjYPZc3I/1wxUqPLpfmB9R+KcHR/SaCa2AKThw1UZCr0PfOdL79LEVfHhOgKBKPWyEy2sND4w9zce883C6CRpBAj6wd3Wfmg2fq8MOcPF747ACKUjYBlyQIL5qWyI9z9WsnFOhzezhiZx4uuuYg749ui8vp/9wVRdL63CJS6oSzPKGh2xQ4KCpQ+Omr+ICRSCkFhXkqzmI7hogQyrl4dZvqOKlVz+klOuBxe1gx62d2/rGHSWvbYHKPwyfKYZuFtM2CuLcRlquQnvSQ/ZTHqT2+KhMSqoQdg5TI/DFgnxNiTw08hwgvB0XxS3IALhlwAX8t38zSj39CUURpZEc1KGgeySNTh5NSL/iLWGUgZTEy9xG9OgwVEEg0KJwA0Y8jIu8Io5Fw7tWy5UIRNVwvx7dNp8SjDCSYLgJz4ETts/jvQkhZuaDtfxmnYvNenZDShUzvQKCkNynhx7nxzHovhSN7dc8ko6kkihMs0lJRByciys0N92Yy8IF0VBXsRbB8bgLvPVUHSkPcoZ/wsQluXpy+jxYd7aWCeIoKLodg3IP1WP1NbFjtlI5OSKb9uoNZ79YozZ0pO95fhOnUoRg0+t6eSYuONs65vIDI6MBER0oY90BdfloQePIGsEZ6+Hr3ViY8UofvZyVUNDoV+kLCa7P20eGiwpCTqcej57fMmVgDoUhq1HEyYeEezBaNYpvCnq1Wvvk0iXUroilJRG/RycYbc/ZisoT3U579fiqfvJJUYbtQdOXrsV/tpVWX8KQDSnB4t5m7ugf3F0pOdTLjzx1ht+l2gyLgjZH1WPl1GSFuc66N8V/vDnKkAZH8AzJ7KHhC6974QG2qa8BoXu0hQ13d/oEq5NUEgnUASuxLYe0q7d8i8x6uvr5RwXwlSvy7gfuUkhUz17Lg3e/Y/dc+4pM17hhjpuvVeUREAYY2iMhB5RJ8qw4t9xEoXkygKJSIHYewBvdP1LJvB+dvBCZ5KkQMQokZA4AsmooseNP/fmpNROJXCCVwZeNZ/DM4lfn7lIjOkSNHAKhTp05Vmzij+LcQHQAt90koXkiwNzCPB9KPGNn0cxRvPxpKZCs4Aep2bS5b/4gkO71METhcIiGE5J3Fu2nSpqI1gabpzT12Q2PqNnFw7e2ZZB438uxtjUKO9+5nj3HtHZksmZ7EvA+TyThS+Ryh8CDpd2cmN43IILFG+JK4fyyPZsytgc9DVSVXD87ipvtOMKRri4AaRSVkZMLCPSGJjuaBW89tWVo2r6iS867I5/lpB1j7XSwz305hj1cqICbeTe8hmdw8MgOz1UzZ22lwSAkLptZj+rhYbAVl63a1GzgY9FAae7ZEsHNDBEaTxm2PpYXl9p2VZmJQp5YVtienOolN0KOIBqPG9D//DmuMpWPV9N/Bree0IjtDD4c99eEBLromL0iekwBzd3CspnK+Qgoi6gFE1HCfrVrWreBaR2VVpQPCciNK3Kth7apl3QSuzVSPP5IKIhqROC9s0T7p2qoTRllA2XNDj6KJqAcg8r4qR/Kl+xAy80oCR8MEqPUQSd8H7UOvuAq2FCgQSYsRhiZITzryRHcCX08VIm5FiTmbg/pvwxklOpqm8fLLLzN+/HgKC/VckOjoaB555BGefvrpf3U11r+J6Ej3AWTWdSCL8f8ANQJuQPLkgIZsWKO/wZ9ir1Vqo+PFBbw+O3AlkcetC6RFROkPj10brfz+YywpqU7ysg38ND+Ogzv9LUdJrh2SyfCXjyGETurmTEzhuxmJVRpn+XbLH3/3c0e54Z7MSuVgSKmTuIf7NmHXpogKUR1FkZitGh+u+JvCPFW3vAA2/RLFwk+S2L25Yun7F+u3kVQrONGaPTGZT1719csRQrJwzxbMVonU4N0nGzPo5WkkJO5HVYqgcLwuZufnPrIXKfw4L56fvoonP0elTiMH19ySxbmXF+FyJbNhlYPCfEGteg72bLXywZhUFKXEO0vXZXp4wpGQ101iYfjl9TjwtwUpBW3OLeSOp4/T+hw9MiQ1WLcyik7dCiudiO3xwPRxNZn5ji62N3vLVuISq9tXTwBGRPJK3V+qHGTxMmTuyOrrynQeSsL0kLvpkd/26M+BaoChPcSORTE2CGt3Ke3IjEvQRQrLiIHbBUu+SGTRp0kc3mPBZDHT7cbz6f/ItTRsWz+Mdh1QvBRpmweu30PuL5K+C5o3oy/vvQz26fjm3XgJWfQziEjddkIWTkYWvk1Q4igiECnrEOIUKgbOotpxKvN3pVnJ008/zcSJE3n99dfZsGEDGzZs4NVXX+W9995jzJgxlW3ufxbC0ACR8CWoJ0cMVLD0BcoiL9v/jKI6Ihw6B618AO+Ca/IC+jcd3GXmzxXR3glO76N5Rzu3PJzGlTdlc+PwDD5asYvH3j2Iwej7cElJdWIrVFkwNYkDf5tRFdi+vsT9uOpQDbK0r0at7Nxwj56/UtkXTyHgpen76dRNT8ZVFIlq0K9fUi0XH/ywkxp13DRs4aBGHRcpdVxcel0O7323268IXlFB4NwMKeHrjxP9atxIKdi1yYqm6cs5KakFJNVOxhjZFaEYwbMXfyTnxDEjw69oxsTRqexYH8GRvRZ+Xx7Dc0Ma8VCfRuSk53B+j1yuuDEHl0vwwTN1QIpypE7w85I4XEHK0UEBQ2tE/GRufTQNKQWduhXwxry9PmXuQoHO3StPcsB7T3Uot5RW7YvtKqAi4t6uQHIAMPcA603eP6oh0qj56gZJ9xG0gvFo2UPQsoehFU1HK3gbmXER1UZyUMC9CQrfRsowSaL9O5A5lCcFLqfg2dsa8v7TqRzebUZq4LA5+OnLNdzX5Qn+XLohaJPSsRaZcSEy7zHdZyocBMhnLIEQAhHzDCL2bTC2Q5/WVDBdgIj/tJTkAEjPIUJOe9IGMnAV6Vn891Dpx85nn33G1KlT6dOnbN20Xbt2pKamct999/HKK69U6wD/P0MYW0LSt+DaBO6devWK+WKQGrJ4Yel+TuepP1yFkHS9Oo8Rrx5hz+YI5k5K0QXuwoDFWvHtZ/dmK++NTmXnhjLV0YEPpDH0iXSEoMKEdtn1udgLdT0WkCTXdvH5H3+XJdm6YOnMBI7uD0dVOHhkSmqC2BQX2WkmrhqYHVYSsD8oim7Q+MoX+zmw08wfP8bgcgqatLXT5dIyG4uTdYsARrxylJ0bIkojO6pBklQzcNKk5oEadVwBz+vR65uSXNvJgBEZ2G0RqAa9U2n7irJcq3LXQMKLdzXwLgeKMk8nr0bT339FMuT8FlzYO5pRr/3GvEkpfq0aivJVvnirBrePruj/I6Wu34SlN+Tex4XX2Bj15iHOvawQRVDBJbzyruElHeEjp7BhbRTdr82rensIUFJBywfcoMSDoQnIYqR0VrBJEEJAzEtg6oIs+lRXIT4VGBojbXOQti/BvRs9V6/cd+hcdWrt+4X3N+xYAkUtIOrekEdI56+cXNI+/6Mkn0rJEnjcGkIIXhrwFrOPfog1qmIEV7q2I3PuLtdeOMtxBq+haXAIIcDaE2HtWSrK6ne5S8QSminrvlRn8f8HlY7oZGdn06JFxaTDFi1akJ2dXS2D+l+CEAJh6oCIGICw9tWT4EQE5Se86ihmk1Lw67JYnujfhJbnFPHm3L1cPSg8S4aDuyw+k8rebRYe6deE3eWUiRVV0uf2rIB6JIqiqwfHJTmxRmmM+Xi/z3kZjNBzcDZPTzpI6AdR8AuiaYLsNH2yqlXfUSWSczIaNHdw0/0nGPxQBuddEdirqwQeT1kllKJKuvfJCVrlpRrgvCvziYgO/LZ94piRiU/VYfsGPQlUFk0Fx1L8rT4f229k18aIgKXxOgS/Ling0eua8NfqqIBJ17PeS2Hqy7WwF+mPi5LusjMM5DmfhMJ3St+6e92SQ3Jt1ymQEL/D5M+f9FC1okqWfpngI7IZDBt/juS5IQ3o17QN/Zq24bkhDdj4czQYUoFCoBi0o7ovU97DyMxrkO7DFYcgBMLaDyXpa0hapRMlf27i4cC1C5n/jJcwlZDfM1UTIpG2z5BhVSr5atNoGiz8ODngb1xKib3QzoqZ/v39ZOFHFdoMDlX3iFKCKbr7gwecvyDtC5COn3U5Dy+EtTfBc61UMF+BEJZK9nkW/2ZUmui0b9+eiRMnVtg+ceJE2rdvXy2DCob333+fBg0aYLFYOO+88/jjjz9Oe59nGkKJAFM3SspQa9X3b1hYWWgeweE9Zn6cq5dAj3rjCCmpoe0K1iyO8SElU16sjcslfBScm7W3kZDiDkrKFFX3u5q4ZBfN21dMnFVU6HpVAW3O828JEJ5ys8Rk8ZQ6ihfkGvBUIfp/quTSYIQOFxWiqJLYBLffiMjJUBQY9foRWp1ThP/vWx/UlrWHOLzlq9LKEX9jTW3k4p1vd5EYJIoE+j1xZG9w93cQzP0ghZvbt+KVe+ozcXQqTw1syG3ntuardzZQpkhb/ZASbAWKt6oPUhs6uOf542F9P/MmJ/NE/yb8+VMM9iIVe5HKHz/F8ET/hsx9ex96RKGEfJbIdR9D5tzhMzmeDMVQC5G0ABF1v1ffRoBIgMi7wNKP4I/VaPCEX3kWHkouRpjsUssKqxpNGDtS/nvNz1HJSi9vP1MRqqqya93eCtul9IBjGeEndHsroKIfD3N/bz/2xcgT3ZA5tyPzntD/PdENaf8OAGFsDebL8f8dKegJ6cP9fHYW/2VUmui8+eabfPLJJ7Rq1Yo777yTO++8k1atWvHpp58yduzY0zHGUsyePZuHH36Y5557jr/++ov27dtz1VVXkZGRcVr7/Scgou4v+b8K3kWnAgksmZGgTxRSFygMhZYdy6puMo8b2LAmusLEaIkIHYaWEvrdeYI6jQOTK7cbv27YV9yYTWItd1j2GE6HUhpaX/l1XNC8EH9vp9UmuCDh4l65vLt4Nympod+gpYSLe+fy1sI9PP1hxZymEiiqwpKps7wKuIHRtL2dsfP2eK0igg4To1mGJJHFNpXV38Tx7edJrF8Vg9slmf/BUe7v0Zi3H6vDni2nqn/kHxvWRDH0yTTGLdjDlFU7adTKQahH186NVqa8qCd1l0S1FEXS+pwiuvfN4bcfYvh7g7+3do9OAhw/lW6R0lUhr0UocYiokSgpa1Fq7kSp8RtK9KOImDFgaEpFMqCge2RVF7x5KACGlhD7Fpgvq94+rP280WX9WhuN4f0wjGZ/IVQXYZMcEQERg/UybzV8zR5p/w6Z9xBoJz0vtUxk3oPI4iV683FvgaUX+ndU7joqCYj4qToZOov/V6g00enevTu7du3iuuuuIzc3l9zcXK6//np27tzJxRdffDrGWIoJEyYwbNgwbr/9dlq1asXkyZOJiIjgk08+Oa39/hMQpg6IuA9ARHHVzdl0uKgIRDXMwFKQmaY/iBQVmrQNnugHYCiXslBy7Mk4vMcS1DMK9IiFJSL4ORgMkJDiSwosER5GvHaUuERXGBEd4WOquW+7hZwTql/yYi8SOB16/orLSZUiP4EgJcQluXlq8qEwxff0yEzJMttFvfK48+nj/tvWPKTtz0WEiKKoKtRu6CQ6LsSJeXNtKuuxBuBywJ6tEXw/K4H7r2rGl++EqWYbJoSAi3rlc91dmbQ9z44QKiJ2LCL+I1BKEod1obnyj7NvPk1CVcuuz0U9c/ns9x2Mm7+XpyYdYvyCvdSqH+h7UZG2r9GyBqGltUSmt0amt0TL7IsM4bsllGhEwixE1MOg1NbHJaIgYhDETQYCqExXFiJOF7iLn45IXIBi7YUS/77+zAiJCKSW73fJ06cLJQoRNxm9AlQlMkajeceioMTZ4/Zwbq9Ofj4xgxKKtCgQcQci5U+UmGcqpWUjpQdZELxkX+a/ipQehLCgxI1HJP2AiH4SETUKEfcBInk1wtw17D7P4r+DKtXP1a5d+4wnHTudTtavX8/o0aNLtymKwhVXXMGvv/7q9xiHw4HDUSb0lZ//38qkF5ZLwfwzpuKlvDR/F3PeOsHXH6ZTkB2anASGLPX4kRo4i0Nz3SN7y5SF45L8T5pZaUa2/RFJm/OKAi4r5GaqaJpuXxAIbhc+BpoAF/fOwxKhcUX/HP5YHmy9Xk9ybnNeESsWmAFJVpqJZwY34rq7M7n8hhwfqf8f5yUw7bWadOudR50mDjweGHD/iWrJiQLCFvDzB0WB3kOymDGhJkX5aoXPghm0lofUoG5jB9uygyUqSZJrOel0SQGLPkmmcjIE+n4lUZPP3qhFwxbFdL3qNPzWlKYQOQjd7iAJkbxK18rxHAARiTRdAtnXg5bJtj8jS8d0Ua9cxkw5iDyJiEfHBbqGHnD+WHGzewcy504oV65cHlLa9VwlEYuIugcRdQ9SytKkWOk5Xn0LfDJbT1oWEWA6h9Lvy3Q+qI0Dyg3osEH2zUhDC4gdhzA2C9iNMJ8HSd8hbV9A8TJufqCYF4b6jxopBoW6zWrRqbsH6dwAxhYIoUf5hBAQMRhZ+C6Bk5AlInIIQlQhqc75J2ghIvtaur6f17ldGOqBYWjl+zoDkNIO9m+Qxd/rVWDG5gjrwKDf1VkERtgRnd27dzNw4EC/ZCEvL49Bgwaxb19w1+ZTQWZmJh6Phxo1avhsr1GjBmlp/vMfXnvtNWJjY0v/q1u37mkb3+mCEBaEtR+WpMe57ZWxzDn+CVO2TqDj5VVTJRUCrh6kJ40LBX7/MYaIaA+9h2Ry38tHuOOpYzRrX+KJpePvvyI48LcZjxtq1nXRqkuR38iKyRI8pGOJ1Ph+dkJQWwWDEX6Y4/smV6u+E7cbLrwmj6btbChqxb5VVRId5+HSftmsWOCrtLx3u5Wxo+rx9qN1SkmO1ODyG3JwuxSWfJnIlBdrM+vdGhXarSqqgyyZzJJ2F1T0LfN4BJf2yw2rDUXViWIwlNwT9710jOen7T+lsSuKZO6k6rMI8IG2Ewqe05OGs/ohs24CNVX3MIq4GcVQExE1AgCDVwZAUSTDXzqK1KiQwFxVyS9Z8DLSXfask871aNl3IdM7IDPOR2Z0RSuYgNQKfSt/lJrs2tKItx6tw6heTXhyQCMWT08oTfKuEhxLwD6/9E8hBCJ+EigJhCSr7t3I7IF+k6/LQxjqosQ8iZKygotu+4l7xt2mF66p+rgVVe+nVn0jL3++BpE7EJk9AJlxAVrBWKT0RlgjhurLbBWmHf14Ef0EQq0orxAOZPGi8HY8eVnrXwjpPoQ8cbWesO5co4tV2mYhs3ojCyf908P7TyLsX9jYsWOpW7euX6GeEhJxunN0KovRo0eTl5dX+t/hw8F/0GcKUkr2bNjPXz9u5uge/8sTgWAwGmjQqi5v/vAs41Y8j9EcflBOUSS16ju5ZpBeHZWdbkDTJLM2buP+V47S89YsbrjnBO8t2c1rs/YRGeOmc/d8ss+evAAAwZdJREFURr1xhBPHTGiavrxzx9N6Mqgot5RWo66D5h3sQSdJi1WSXNtJ5nEDbj+BIU2DlQtj2bG+fGmnpCBXRVV0EvTarH2cc1l+6Wcly3lN2tl4+sMDzJlUkayUlFQvnZnI2sV6REgoYI3UuLh3bul+tgKVzOOGU87RqU5TFZPJlzwqqqRd10LaX1iRAAUaS0LNkmThkoGVDVBR9Xui5y1ZCAFtuxaGMf7AO2iaYNsfUQF1l6oV7h3eibrcC5Z1ICLqAc67okC/VhcUklTTHXaVVriQtln6v8XLkNmDwfkzpddF5kLRR/rYNP17klLyydMzGXlVND/MTmDnhkg2ro3i3SfqMKx7c44dCEdWwR8E0va57xZDA10JOPoxUIMJ+HlA2vTqvUrgxoev5bNd79H/kWs5r1cnLr7hfJ6aaubD5etJqV1uaU4WQdFUZM79+pKREoFImAGRd+jLeSUwNEPEvROer5UfSMdvYJ8X3s5q9b3MnA5I6Ubm3FEuOlXyW9PfDmXhW8jiYO7rZ+EPYc+Sq1atYsaMGQE/v+mmmxg0aFC1DMofkpKSUFWV9PR0n+3p6enUrOnfoM5sNmM2VzR0/CexZv7vTH1yBsf2lEWhWl/YnBHv3kmTjg0r1Vb77q256bG+fPnqfKQWenat26SY1+fsIzJGQ0rYsT6CR97SbTwUxfcNt/0FhUz/cweR0RpuF15iAwhofU4RL83Yx4RH6pJ5TH9AJ9UKL9n28hvyyE5X2fpbJO0vKCqdgKSEvGyVRdOSKP8mmpDiZsdfZUmu0XEeXvzsAEf3mdj4cxQet6BlZxtN29mZ/Fxtr6qv//4VRbLwk6TSCIfbBXUa+XoYOZ3ilCIaJc7t1YXdWyJQVelVahace3k+j793KOwxCgF/rYxGNUDv2zLpfVsWdZo4cDkFvyyJZdufEQx6MKP0nlj6pa5KbbJouByiNKnbn8ZOeUTHubmifw6NW9t9NG9OLzQ0jx135ttYaureTUIIiLqf3g915+tPXqyU5Uel4NqG1IqQeU+gT0YnRzM1PWJS+D4i5gl+nLGaWa8vAMqW+UqubVa6kWcGN2Tqmp1VuHckuHf6LJGBnixN5F1Iz3GwfUngZSwP2BcgY55DVIIN1m5ck7tev0Ufgf0bZN7kwONzrgLHcrD0QCiRiOjHkVEPgicNhAmUGqdkCC2LPsZXETkAlNpg7Fzlfs4IHCu95qyBoCALpyAsV5+pEf2/QNhE59ChQ6SkBE40TEpKOq0RE5PJROfOnVm+fDn9+vUDdDuK5cuXM2LEiNPWb3XixxmreeO29ypElHf8tpsHL3qGt39+mSYdKkd2rn+gF99NXU5OWm7IfQeMzCjNzxECzu+Rj9QqivuBvq3E9NKfDs3Kr+MozNVzRxq0sPHguGA/Tkr7BIhP8eB0OLj/miZcd2cW3frkYrZI4pM8TPh6L4d2mzl2wERkjEarzkW8cGcDvvkskT63Z5W2kdrISWojX92m3ZutQSdjTRM+lUGKCrZC3/wXh00lkNlqOChZFgt3zghkS+F2g71Q4Z7nj7JvuxWTWXLu5fnUa1p5c8ncLAPPT9vPOZcVlI7RbJFc0i+XS6/LLRuLBvMmJWE0abhdZSQHyshjzfoO0g76Rh8u6pnL4xMPYTTpFhVSVk2gsSpQFA3FtZSPHv+QO1+9q1RIsXaTNrzw9VMsGHeaPIu0TGTRFD1/IvBOYJ+NFvUgs99ciBDCbwKw5hEc3W/h6LH+1K0zn8p7agV5jGtZhC79L0Y3La1a1Zy0zSY40VCRtjkIS4/SLUKYwOu3Jd17ke69pflGQoT/ciqlBOfaIH2XQcSMqRSZ+ycgnWvRv89ABF0D9xakVoBQos/gyP7bCPtbj42NZe/eivoIJdizZ89p9496+OGHmTJlCp999hk7duxg+PDhFBUVcfvtt5/WfqsDzmInE0d+rP9x0nNH82i4nG4+fOTzigeGQExiNO/99ioGU3DOajBqnHNpwUnb/JOcUPC44aqbs3EUK9RvbuODH3ZTt3H45EAIqFnPzbvf7OHKm3Iwn5S0W6+pg/OvLKCtV0/n8htymPxcKo4Qc7zJXLaUFQgGU9nnqgprvvW9Z7f+Hul3Wa0EUgZfmhIifJIDYCtUKlR7edyQk2Fg/pQkzr28gEEPZHDjvSeqRHIABj+UzjmXFZRF5cqNtTwUFWIS3Hg8wg9h1P9OP2zCaC5bBmvewcZTkw9iNEkURb+fzhTJKYHBCCu//I7XbvV15D7nqg48+tlb2AuVal1OBPRk36IwKpxkIflpqzi47XDQKifVqLJvawFVMu80Xxo4IqLUJGSujogCTkEgz3OI4OP2+NXtke69aFkDdZHG3BG6flHGBcjCj0JWhJVrJUTfXhg6ICyXh9nmP4hw7TmqzRrkfwNhP5K7devGe++9F/Dzd99997SXlw8YMIBx48bx7LPP0qFDBzZu3MjSpUsrJCj/G/HLwj8pygv89qd5NDau2Er6wROVbrtGvWQ9QTAAhJD0vSOTmITqMUJUDdDmPBvDXzjKG3P2oapVS741hJGWoBr0Si+T2YOqBCcZ5/cInnSrqpILrtb3KSEsHS8u9PajN7x4RiJqkF+FEPDrspiQpfTh4smbGzH3g5TSirTcTJW5H6Rw/1XN+HpqCvaiU5+km7YrDuv7cbsg/XBw8UABdLxIz5FSVEn/+zKQVO9yXWWhadCycxFr5v3MH99MQSsYqyfBFi8nvlYTrPHtq62SrgzhfymerAdKj2nesYi7nzvKQ+MPc9OIdB8phT3bm1AFxQ9E5J2BP7PeQEglYOtNp7R0RMgycFFhH+k+hMwaAK6NvrvKAmThOGRhePmeQigBEpxP2s9yRVjt/dMQxnaEJDFqqi4vcBZhI+z3+dGjR9O1a1duvPFGHn/8cZo3bw7A33//zZtvvsmyZcv45ZdfTttASzBixIj/zFJVeWQcykRRFTRP8Bky41AmNepXvmql7/1Xk59VwPQX5gI6uRFeF+prBmcF1GQ5FfS9MzwLiVOB2wVph0wMfjgDgzE4obqifw5fTKhJQZ5acbIWEgT0vaOs6kIIeODNo/S8JZulMxNIO2QiNsHNwV1m6jd3lJqUlozDYISpL9eic/f8apvY0w6YmfZ6Laa9Xgvfsm5Jqy7+FaIri3DnMJdTUGwLrq6raYL1q2K4eVQ6xUUKXa/Kw/APmjyXkMCnPzzE3m0ZbFx7jM7n5Hqdo6aAUps9e0cQqWyjVv3QKuCnA7GJHuo0LubeF49yzqWFpYnaQoGhj6cx5cXaLJiaTOMOHUGtDZ5KpABEPQtaDlr27eDaBsII5isRkbciDI3BtQFdB6dixFXTFIQhCSXyrlM6P2HtiyzYQWDyJxHW63y3FL6vJysHImFFHyMjBiPU1ND9Rw7x5kr5/RQwQsSNIdv5V8DSCwpe914bf3OFQEQMOTVi+j+IsB9RHTt2ZN68edxxxx0sWLDA57PExETmzJlDp07+hKLOAiAmKQYtjDBATFLV1l2FENz23E30vOtyXh30Dns3buGGuzO59PocUhv+Mw/46oDBCMu/iqPfnZloGkE9piKjNV6fs5enBjYi54RBT0z2XnJFwKXXZ7N2cSyNW/tGOJq2s9O03dHSvzWPLiYYESVxOgTOYsGmX6L4emoym3+Nos25hWieUzCpLIfURg4KNqjeyjB9UMm1nTz78QGatT8VvaTKwxIhSUl1kHE0UI6EpFUXG1cNzOaKG7NP7xKVobXXC0qfPAPlMpVfjqvfvJjIaA+i3Bux1NJIiRvD/Vc1o33XAq67O5OEGi5sBQqpDcNZbrWg57BUHYoCL36+n5p19d/hydft3hePUVwczUX9akN+mCRHJELcu1C8BFn4IqXmmxKwz0ba5yIjbgbbdL+HSwm7NplZ+tXlPPBhfAXzCOnei7Qv1MuxlRSEtR/C0MD/WKw3gu1zPbm4AnFRQa0LljITaCmLofhbP/uWhwL2hRB1X5B9vLD0A8fvUDwf31wh/axE3IRKiQ/+kxBKBMS9j8wZhh7ZKblG3vMyXwkRt/xzA/yPQsjwF0MBsNvtLF26lD179iClpFmzZvTo0YOIiH+/22t+fj6xsbHk5eWd9nyik1GYW8RNte7C5fAflhSKoGGbekzeMLZa2PqP03+iU6cRxCYE95+CwJPIPw1Ng5/mx/H+07V5cOwRLuqZH1ZOkcMuWLUojvUroym2K2z+NRJbQYl6rmTRvi0V8oLKQ3pTUNxuwaCOrcjP8e306kFZPDj2SJWu2cnX+oe58Yx7oMyd2Wz1MPnHXaTUdf4jkZLl8+IY91C9ChExRZE8POEwV96UU2U3+MrAaZ2COaoleI4iRSSu/KW4cj4gIqrya4YeD3zxVg2+mFBWnTn9z+0k13b9a+57j2ZBjR0NBc+F3jn6CUTEHVC8GJn3cJX60zQ4tt/M/7F31vFSVP8bf5+Z7dtJdyMoKgqCgRgoioEoqIgoYnd+7e7ARhSwELAwUFFAbJQQEZHu5nbtvXdj5vz+OHt76waIP/d5vRTYnTlzZnd2zjOfeJ5xx3TjzvduZPD5RwMBheGiB6FsJjW9swxwXoRIvDtoQa80diMLbgikoireN8HaF5H8PELPrLbtHmT2sRFmaAHnCLSkh6I6HykllH+FLH0XfKsCka0TlQChtWdUYxxIkP7NyNK3oWwO4AFLZ4RrNDiGIURTOub+e9CY9bveROffjH+S6AC898jHvHXfzLpvCBAIHv3qLo4Y0qfJjmcUTQL3s2Fv5lKqupC4JANbQ6U8qmHbehvxiSbJGf56p3eqk4CSIo1P3khn+oTmmBIOPbqYJ97fXO/5LP0+gbsv6FjjtVsmbGPwOfkRicTyn+O547xOdV63O02m/LSalEx/vchIMELp98G9F3Vg2U8JIFWa8YanGkaimgIFuTqjD++J3y8q9YcALrx5D6Nv3rtfanH8Ppj3cQ9OvOID7M6q6NKLV97NtQ98GHbfUKR9x0Yb447pAUDrTuVM+Wltk865SWA9DHzLIm4mUqYg7Mdg5owA/0oaVMAcwHVDu2GN68PzPz0MgFn8LLgnhT52/PWVoozBIH0rwbsUaeSCuRvMAtDiEY4hAVdwK1KWIfceTvhaFB3irkJLuL5hJxYFpJRgbAKzGPTWCD098k4x/GNozPp9YPfa/T/DBXcP55JHzsfmUI/DQlN35KT0RO776JYmJTkAWsJlCNvRYbcRQj3tWhr5kCAlvP5gC8Yf14PHrmyH4RdhFZBDzUVKuOeiDow65CCmPdtC+S9JwfKfE9iw0hG2I+qdp5txz+gOfDI5nZJCdWn/8FlyDc8jgA9eycTwBZ9fddrvLg7+8/CUadxxXmdyA75f0RYmB1uALVZ48O0t9B1UDEiOPzs/bPHxvn4sSU4zeOS9TaRkVHzQEpvD5JzLs/drwXHuzjy+nFTThmHU/86JuF8oglg9EtS7X3Rii/sdvhVRbGQFay+kNMG/gsaQHICkVC/bVql0mTRLwP1W2O2le4qyJwgBYe2l6ktKJ0H5l+D9Ecq/RhbcgMw5E2lkgX8TWDoSvhvMQDjPqvf5RAtZPg+Zc5rq+Mo7D5l9NGb+1Uh/ZJmMGP59iBGd/QghBBfcNZwP9kzmf+9ez1XPjeXBT29n5o5JHH12v31wPB2ROhkcw0Jus+lvB844s1EePJ4ywSeT0/l4kgpP/7UonlvO7sTqpQ1LZ6Y18+Hz1Lw0pRTcO7oj29erNli/XxEMw1B/Try3Je9NaM6SBQlMur8lY/r1YNVSFyVFGrXrv7dvcHDn+R0pzFXhGL+PStJTnUi06hi6nXvnJjuXDuzOo1e0ozC3cSzRapPs2mxHCCWIGI5QNDbSEw1R6jPQzbQlqzjhnDyEgC4HlxKX2Pg2s4pjRyKGFiv8+Ws8s1+bW+P1jHa98Hrq3wZt+GHb+mp1R0Lsc8LYMPhBbw91KmaqwdYfRDKydEaTHDFntxVHfOAz9f6C0tMJA+kG7+LQb5d9jix5IfCviieJwBdubEbmDEHmng3+DYTtXLOfFKg/eh0ZFQGMHrJsFrLgGjCqy6WY4PkOmTsiRnb+H+If7Jf47yIu0cUJF+7bVvwKCKEhkp/FLDseCm+ndrj4u0+TSUozMI3whb6hYBgw/flmfPhqTTHJtX/EccvZXWje1kNacx/52RYee28TLdqHLwA1Teh+aCmDziygVz83UsKfv8Qz6/UMlv2YwNUnd6XfiUUcPVQZfW5dZ+fr6Wlk7azIu6lFrLRE5/YRnTjx3Lygasl/L45ndN+e9D+pkF793TRv42X3VhtnXVbVldW+m4duh7pZv8IVtOXa7xNsXOkgOb1xbftFeTq7tqiFePtGO227lte7PkdKKC7QQUJCihGSECmX8sjt4LoFRl2fxbcfp2KxNg0rEEIVec94KYOxt2cFnYOUkLXTyoqFcVise2vtb8OaPAbT/UYULvZV0C0w++2qtMTKRXEHTG1OHRhbCEt0vD8h868A7/eNOoxpwJY1DrauczHipoHqRRll0XWI7aSUyJLXqKiFqwsj0E0EoSNRdhBx4JmH9CxQ45SYSOshiOSXEHpwFfxoodSsH6z4V5D5FSOLn0GkvFh71xj+xYhFdP4j0Jyn47Pdxn0XtyNrlwUzEAmJSzT4aloqN5/ZhXtGd2DBrOQaEv7fzEzm9x/ig6Z5/H71RPj5m2mVsva1sWebnb8Xx7Nrs52f5yRFfJLWdTj1wjwOPqoEq01is0sOH1TM4zM3MeXn1Vxw4x56HO6m1K2xaqmLz6amVyM5VZCmwOfV0LTQ1gWGX7DwmyQ8ZRoZLX18OjkDrdamNz69A7vDDGIkKrHaJLe+sL3Ri2b1/edMS6t33c83M1K5fFA3zj2oF+f26sW4Y7rx1bTUoJ+1lEqMMOR4CCoW2rZdPAw4pYCtaxxN5l3ljJMs+yGBH2crz7HaYokAzVr7OPWCPFyJNZV6DcPgqavLWf27E9Okjht5KOTndWTlb/GccUkuF926h1793Kxa2jAV4P2DCMS5CUiOKeG1B1pjd9k589qAnYClS3QDWDqHGDgLjAiRmpDQwHK4Ei+UFXpYBpWEyLcSmXcR0gynRB0Fyr8GwnUzGuCZizTzG3ecGA4oRFWMHMyxPBT+iSLfaPFPFyP/03jlxql8+uIcEpL9nHphLlvXOVg0L4lK/RYhQQpatPMwYfZ6snbYuOG0LljtJlc9tIuTR9ZsKV72YzzP3tSGnN3RVTG74g1embuWFu2Cd7tE27ItpSJZuqZu2JMDOiRBtuTgASX0OrKU6c83qzy/Cmi6pF23ciZ8tgFnnMmkB1vQuqOHUy/MqxFt2LrOzptPNOe3uUmBAl1J3+OLGXvHHroc3PgWcCnh8uO7sX29HSnhthe2c8I5+XUUlmsX2koJr97bks+nZiCErLRsqPj70NE5XP/kzjqf9d0Xtqe0WOfs8TkcemwxCUlqMSnM0ykuO4vWvcdA3vlAKWVujceubMexZxQweHh+g6J+wc5hyXdxLP0ukUvv2o3dUXcbv0/w0VvjuODmBKTvb5AeZk/O5eU7Naw2yeljchl5bVa1WqIwsJ+KLJ8HUqk+67rE7yeiLtP/V2xd5+CVu1qxdUMrHv78DrofWUVwzJxzAm39wciWDtY+aGnB02bSvwOZM7gRM7MEjht6SRKJDyNcIxt8BLP4eXC/TiRRPpH2GcLao8HHiaHpsc+7rjRNi9jyXGEqZ9S3AnU/4r9MdP78fiW3Dn4w8oYBOOMN+gwsYfH8xMpoTVKaj0MGuNEtknV/uti5qf6GqS07eHjhi/XEJRg1WsUNvxJQk7JhKbQnrmnLd5+kBP6lxBJbtveQ3sLLkx9s5uvpqcx4MZO929Wc7U6TIaPyGHvH7sr6Eynhq2mpOOMMBp1VCFJFvSzWqtRQQY6FpFQ/SWnBr/OGturPfT+FZ29SbeaaJjnnymyGX55d6U1WUqQRl2DWGHv5L3HccW6Ip+sAHnlvU6X1h2mqaM7oI3pWRrk0XdKqgwchYPc2O5c9cQnDbzhNtQC7p0LZLJBF7NiUQqsO6im3KciBaQIyNLE1zUDaVQAow9FxR3dj5xZ7JVnNaOnlncWrI6ThqtIoUsL2DXZKSzSat/WSHOQ7zN6ts32Dg7ZdPKQ39xM6DfPvxK8LTmD5or4cNKA7A88+Equtpk6A9K1H5o0KeHhV/3x0EPGItA8QluB+fFL6kFkDQRbso9kLsPZFS3uvwSNI91Rk8VNEKuIWGT8g9BYNPk4MTY99TnR++OGHqAc87rjj6jWB/Yn/KtEpc5czssV4ykrqKXxWKwLSVGjRzsMl/9vN0acVVpKdPxfG0bZLOSkZ9SfKUkLOHgujD+9JRSeHpkv6nVjEXRO3Ygto5pgm7Nhox+cVtGzvxRkX/GZnmqpOxO4wSUwxGuQH1pBzeO3+lnw6OYOKhdVik5wwPJ/END8b/3LSd3ARw8dXGZs+PL4dv36dFDJtqOmSIwYX8dDbWyprlB64pAOL5oe+9m9//VBOHJWu0hj2YxDCgmkakHtqwK8o/O1CBv7XFEXT1ccoL9U4s3PvOtvd+8ZmjhoSTl9JEZWfvkji7aeas32DCh9pumTgqYVcft8uMlv7+HNhHK/d14pNq6pSWsPG5jP2HgfxrnWBoZJUMbD1cPD9CZ4v63UOBwJEytsI+1Fht5H+bciSiVD+OUpR2Q7OMxFxVyIsrcPuaxa/AO6JNKwbLAoHcksXtPTwn3s4SGM3MnsQoa9jAVqaMhjFBGs/pTL9L9Ti+f+GmI5OlPi3EZ3dm/fy88eLKMwtprSolITUeBJS4klpnsy0hz9iz+YspJS06JTJmHvPo3v/Lnz4zGx2rNtJcrMkBp03kH6nHcacyQt44arX99k805r7OPb0fL77JIXCPEsN1+twiE/yk9bMT3GBTl6WlTcXrqZl+4arOM98KYM3H29Z+W8hJDNX/B30yb0hqFi49uUC9teiON5/OZ24BMkV9+8itVlViD1rp5WVi10cdXIxzjiTSwZ2Z9fm8FG1zNZe3l28mg1/OXnrqTYsWeAMeY+32k1mLl9FfBKAoRRxk54FYUHmnR9x7qYp8Hlh8fwEjhpS1KSigl6PYFiHg2u9KunR181tL2yjZXsf0gweIfry3VRevKNNjfQeKLKTlOrn8vt38fQNbZX/WTXtIKEJhBA88fV19BnURS2ASGTB9eD5toZhRzDMfT+Fk87LP3DIjkhGZP6snMOjgJRekCUqkhP1Ph5k3jjwLal4JfBnQLk5JDRlQGruIZwLOvbj0VKiMFMNA7PwQSibTmiyU1td2UQkPkh+0RCWL1iJz+una99OdOjVNsT+MewL/CNEp7S0lG3btuH11lyYDj649s3owMG/heh4PT5euPJ15r7zfaOj5s5EB2XF5Q0cp2Kn0Hfqbn3cTJi9AYCifJ1PXs9gzvQ0ivIsEHEpqInL79/JWeNyGhVBuWZIFzb8VdXW/so36+jce/9aKTQEhr/KST4UoTJN9WmuWuak+2EOLjmqPXu3G4T7jNt2KWP4ldk8f0tbdIuG4Q/9xHzRLXsYfUv1TicNJdx2JbhDG/pWYO1yJ8/f1oZNfztJSvVz2HFF2BySnoe7OeWCxhd33jq8E38vjsM0BYcdV8z4e3fRsWdVlLK0REO3mDVqfooLdM7v0xOfN3h+S9MkdpdJealWg+RUQAhB846ZvL3uJYQQmMUTwP0aoX5QFR1ts15PZ9IDLZnw+QZ69m1kAW3NGaNqWYI9EIRPs4mEuxBxYwGQxl4wc0HLQOj199YLBym9UPo+svQ9FQUUDuXhJOwBS4ra89TA0h1cF0LR3WHHFimTEfZIqsqR5udHFj8BpdMC89AIR8I8ZYKX727N/A/Ta3gVHjSgG3e8ex0tOhz4ptL/H7BfiU52djaXXHIJc+bMCfp+rEan8Xhq7MvMn/Yj0jyQg20SIeDtRatJSvVTXqqTkOyvXKzLywSrlri4c1T4GpLq47Vo5+WNH9ZiscoGPQX7/TD/wxQm3KKetDr3LuWZWRtwxjX+c5QSSgoEcUmySYTzKkhMRQG2NKlRfBwqalSdBM18uSVvPZERcm3TNOUuvmBWCtm7bFgdVm54dTyv3DCVsuJydIuOYRhYLCbnXZPFmNv2BjmmDpZe4P8z4jndcV5Hlv9c16tNaJJ3F68mo2X0rVt+H3jKNZxxZuXnvWRBAveM7siRJxTx4FtKJbt6BMcwFMmofg6z30rjlbtbRR1lDIUJcwfS80gTSt8kktbM0ze2Yf4Hqei65MRz87j5uR2NOnYNiBRImQyeBeCeXHMuehvlEeb5BkUmqkUm4q5GxF8H/r+Qxc+A97eKAcE2EJFw635Jz8iyWSotZmwNHN6l3NPjrwfhUB5P3l+pG9URYD9F2Uk0UYhMGlngmQdmMdL3O3h+pjbhkRLuubADv/+YUIcIaxaN5PREXvvjaVKaJTfJnGIIjcas3/V+dr7xxhspKChg0aJFDBo0iE8++YS9e/fyyCOP8Oyzz9Z3uBhqYeeG3cx7J/qaqH0JTZO071HGpr9d6LqsrAXRdYkp4axx2Uy8tyWL5iVhmgJnnMGpF+Yx6rq9JKUZHHasm2sf38HLd7YifGRHrdR7ttv48fMkBp9T0KD5WizQ60j19HzWZdlc9dCuBo0TDNIEZ3zjSI6UyiHcZpcYftXebnNIRV60qm2qG1XWRsXrQsAJw7P4+LVU3EUWTKMm29F0icNl8uvcRLJ32dB0OPRYOyedu51jRkzg189Ws3drNonxv3H0iV+SmBqKhBgBBV4n4dpyC3N1Vi6KCz5nlKfXBTdkhdy/Ahv+cjLzpZb8MicO0xAkpvo5fUwuI67K4ojBxVz18A6OHlqoSilqfRfBith3b7WhWyR+X+MWxz3rZtCzVxGRWr9NAxKS1DaGIdgZIbUYHBURjwBREWlgO1xFMhynK+NHW29k3KXg+VGllywdwHoEht/Ab92GTX4NMhehNQfnGQi9GdK7FJl3ca1zkOD9FZk7ElKnIWyHNGC+9Tgz53BwnB1waPcq6wVRLQSXMglZ8iKUTlfnBSrlFncxxF3RpK7dQs9UUSRA5gwj2He7/Od4ln4ffFE1/SYF2UV88uJXXProBU02rxiaHvUmOgsWLOCzzz6jb9++aJpGu3btOOmkk0hMTOTxxx/ntNNO2xfzPCAhpWTlz2v4bfZSPGVeOh7SnuNHDcAZ33CNjh8//A1NE5gHQDTHNAXXProTv1/w6eR0/l4Sj65LjjihiG59Snn1nlaYpiA5w0/ztl7cRRqfTknj128SeX72BpLT/Qy7OJe/F8dV64gKBnXzkiY8dX07UjJ9HHasO8z2oeH3Q68jS5qU5ICKHATxMqwXhFAqyKA6uTStbuQq2vu4lJDews9TH27gntEdlR2FUONJU6DpkrISjW3r1LVoGnDO+OVQ/AsOHuH4oSciEh9GFnwIvkiRFglxY8J6IL37bHP8vuAfkNAke7dHrvH4/Yd47hvTAcMvKiMwRXkWpj+fyfsvZ3De1VmMvC6rXhG6+GRT2Yg0EkmpPiLq2xBI1gYOp2qADBRhkdX+DJU+FKBlgN5BuYbrrRGu88A+OKiRo9ASwKnut8u/W8nMJx5h2fwVSAktOmZy1nVDOeOqE9BxYxolUHg3NbRpKqFaumXRfYj0zyKeY2MhhABL8PoWIWyIhFuR8deCfyMglKFllDVCjZhV0Ffnf5SCpofW4jINk6/f/C5GdA5w1JvouN1uMjOVCm5KSgrZ2dl07dqV3r17s2xZZEO6/y8oyC7kvjOfYvVv69AtOkKA32/w2s1vced7N3DUsL4NGrekwB24U/6TREfV1pw+JoeeR5QiBBwyoIp4+H1wwWE9yWzj5Yr7dnHkicWVT9c7Ntp5+6lmTHm0BbdM2I404fwb9vLdJ0lU3Oi79Slj8Dn5JKX6ydppZe77qezYWPVUV1JoaVDBr2nCqiUuzr06q04qqLFoqgLk6mNEoxkUbhwhoGPPct7+bTULv05k4ddJ/PRFEoYEv1cAojISd+VDO+kzsBp59MxHZv9ERMl/AJwQd62S/vf9UeMdKeHNJ5oz+620MPtrJIbjuahi48evbleD5FQ7Www/zHixGaYUXHrnnijmrHDcGfm8/WRoNV2hSaWr41OfV11IktL8HDIwOn8sXYe/F6vIlmkIjh/ZCRw9EdZDkZaOkD8u7P4i7nJE3JiojlWBr6cu4NnxE9E0rVIksjB7N+VZj1O+/Q5ccdEU+JvgX430rTogOoyEcID1oP13QNsA8K+nNpnNz7KEJDkVKMyOXmcuhn8G9SY63bp1Y+3atbRv355DDjmESZMm0b59e1577TVatPhv6A6YpsldQx9j4/ItABj+qh9HubucB895mhd+eZRuR0Rbn1KFVp2b1yh4+ydgd5pc8r89nHVZTtDFfeHXSbjiTV6YvYG4hJreTC07eLh70jZeuL0VJYUa8Ukm7bp6SEozKC2B/72ylaOHFuH3VS36I6/N5pM30nnt/paAaBChqCAiQ0fn75OuqEjjVSww/0SHjdUmOe6MQo47o5ArH9T5eoaKqvm8Gj37ujl9TC4degSTFoiG5ACOoQhjG7IWyQF1vjs32dH0ujYbFTD8MHjcq4g0A5l7AcFSYAvnJFGcH+52pD7YGp5VYaHSPq0PvomTx5Yy750f6ygpi0AE7Jwrs3n/pWYEL54XjLtrT1QdZH4/bFzpZO1yF5qu0fHgdgw8/zE0a1WVubQcEqLeSahaKNd5UZ6fQs6uPJ6/cpLSfArcN1wJBs9+soF2XcvrX9hvbId/gOhI0w1lM5Gl74OxB7QUcA5Xrd1a6j4/vnBdgCx9h9qF0hktfTXS9sGQ2iJ5n88vhsah3s+8N9xwA7t37wbg/vvvZ86cObRt25YXX3yRxx57rMkneCDi93krWP/7pqCEpGLBm/nkpw0ae9Cogdid+zpMGx7SFJx6YW4NC4G1y51Me64Zbz3ZnJ+/SuKSu3bjSqirMaMFRP+ueHAXe3dUnUeHHuVc8+hOBgxRTz8Wq+oyqtj/7PE5jLxO1XCsX1H/1F/1upb9TTakGb6uZn8iJcPg/OuzePHLDUyct47rHt8ZguTUA0IiS0J3XV161250i0QE8Z8SmmDQyAF06tMdYT0IRPCVd9MqB7olMsFfuiAxpKs8qGtPSh0cwxFpnyLixnHja1fS//TDUQX0stLOQ7dI0pr5MA2dS+9vSVyivXLOoAjDDU9tZ8j5eWHnJAPCknl7LTx2RTsA+gzuxZNz78VirXa+ZTPCFHVLcI6oWa8SBb6esqCO1ccFN+5tGMkhQDj2M6RZiMwbqYT8jC1AOZi7wT0RmTNsv5hsCktbRPIEVDt5Vaj15JGFYUmOpglOG3/SPp9fDI1Do3V0SktLWbNmDW3btiU9PT3yDv8gmqrr6vkrJvH1mwvCtuoKTXDja1eQ1iKZw046uI4CaTjMe+cHnhr7coPn1xQ48oQi7puyhaI8jceubM/KxfFoulooXAkm7//5d9gbaYWnUkqmn9w9Fm4c1ol3l6wNSwY8ZYLh3XsRn2Qw889V+5U4SKkiEjl7rFhtJqmZB273YDRo2qiWA9XOHPp6X7PMyaNXtCdrp035i0mlbDxk7PFc98pl2Ozq+jfzrwPPfGqnCKY914z3JjSLmCYAOOPSbK55pG4NVsU5fzNrGKde/Wy11yXje9/M1tU7gmaEhSZo3bUFry59isVfLSN3Vz6p6ds58qjnsDsj3x4rjltWKvjpi2S6HlJKh2MWqaLhym28AdXgwtADaemIjB8RIchgMDw44hl++WRRJdmxWE0+WPk3cQn1jwpLCb9925Pli8/glHGD6XRI+3qP0RCYBbdB+ReEtJ2wHISW/tF+mYv0b1Vt8Z6fAIm09ePx8To/fryS2kulZtFo1jaDV5Y8QUJK/H6Z338Z+7XrqjqklDidTg477LDGDPOvQ5m7PGLrtzQlEy5/DYDEtATGPzmaUy6NzgfmpDHH8fu8P/n2vZ8aPdeGYvG3iVx9chfKSnRy9gQWKUPVMaQ396DpyoLg5y+SKSvVaNPZw8kj8yotCww/pGT6QcKnU9I57LjIT4p2p6R3/xJKCi0hvbCEpsZuKjG64gKdF25rzc9fJVXWhmiayfQ/VpGcHtoF/EBH0847ckSo+2FlvL1oNct+TGDrWjt2p+So4VeQ0XlszXnFjUV65tbZ/6ghhbz7THTO1J9PTUfXYewdu3G4JIahamPcRRoT72vF4gV5nHp11fbrlm5k66rQLd7SlGxfs4uNvz7MMcNvRmipATuDqSAj6/9UfNZOl+Tk8wLb1y4e9i4MT3JAFSB7l0AY5WIpfeD5IaBPE09K6naEJpEBgpia6W8Qyak4j8TELcx+7Rs+fXkOw646mWtfGofWFHoKISDNvDAkByq6/qTvbxUR3McQlnaIxLtqvPa/9/w06zCTz175Gk+pSvcKIeh/2uHcMHF8jOT8C9AgojNlyhQmTJjA+vXrAejSpQs33ngjl112WZNO7kBF2+6t61UwXJRbzLOXTURKyanjTohqn8ufvojv3/8lbNRoX6OiY6c2CnJ1bj6zM6uWxqFbZCBdAO881ZyrHtnJsItz0S3qIyrM05n1eianXZQTVZShTZdyTh5ZENTAcssaB59OTSdnl5XHZmxu9Pl5ywV3nNeRzaudNQpgex5RWm8rigNR7n9/Q9Og76Bi+g5S3loipWudbYTtcEh8AFn0ANWF2tp3L+fw44pYt8LJiecUcOSJRVhtkjV/uPjq3TR2balemyP45I0M5ryXylFDikhO95Oz28pv8xLxeTRsjpq1R7s27iUa7F47nx4H/wKpH4CWpOpEjAYIHWptEELNV5pFYOxE+jZFt28Ynyjp+R5ZeKcS+gvUIF39ALRomc7kR1pimgJPWcNJiZTg84nKe87siXNp1i6Tkbef2eAxI8K3mmi62fCt2L/FydVgsVoY/+RoLrznHP7+ZQ0+r5/Oh3Ygs82BncGIoQr1Jjr33Xcfzz33HNdddx1HHaWePH799Vduuukmtm3bxkMPPdTkkzzQMOTS43nnwQ/qvd8bd0zjhNHHVobxwyG1eQrXvHApL14zuSFTbDCccQY9+7qx2CQb/nKRu8dC7QLN/CwbhTnqHAx/1XsG8PKdrclo4aP/yaoWx+YwMfyCTX87o9KgOeeKbDJa+oOShpfvbsWqJXGkNfc1SVfV958ls3Glk9rnF62wXTTkRppq+H8vCdJB2EDWX11a+lYj7APqvC5c54O1L7LsPfAsBWMXul7CXa9tQWgCZ5yJQH2/Pfu6OefybF64ozUrF8Ux/PJsjjujALtTsn2Dnc/fTOfzN9Mrr0OhCdr2qOnHlJAa3RN3QrIPjEJk0aMIe38woiQntaHFK1PU4meh/EsiOWXXgN4q6MvSuwSZfyVVD1eKjGgaDL8ih+6HlXL/JR0ozLOwaqmLboeW1tscV0pY8m3NlMAHT3/G8BuH1iv1Xj9EuwQ1okWxieBKcHLEKYf+09OIoQGod41ORkYGL774IuefX9P7ZsaMGVx33XXk5OQ06QSbEk2pjPz5q9/w0rWT661589Bnd9Sr9Xzh50t4/opJ5O+NEPYOAyEkhx5TQkGOHjAtrLvq6hbJ2P/t5oxLcnAE6hJMAxZ+k8RL/2tFQU50NzqhSboeUsqLXypbiOICnRE9ewEmby5cS/M23qBt1cEiOLXJwYaVDm45qzNej8aDb27msEHFWILcJ6PtgLrl7E78vSSujuLpoccU88T79V/kqh+3Yv65ey18MyOV82/IaiKykwSWzuD/vSkGiwIWsPULKOk2oG5J76gKkPW2CNdIsB2DqMZQzfxrwPMtFQt3SEVoE/x+gabJytqwCkuMpd8n8MAl7St1fG5+48oakVOf18eoVldQlFsccpoJyX6m/7EKm12i6kI6BdqNG1DCaD1YdQ6ZuUT/mWmgd0SkfxlUFM/MPT/Q2h88wislFOXp3D6iE5mtvTz87pZ6RRkNA8rcGmP796C4oOaP6oWFj9Kzf93oXFNAmqXI7AEot/RQEIj0byMaiqrx8sC3Vl1z1t71Lu6O4cBFY9bvej8T+3w++vatu1Affvjh+P31eHL5l+OMq4fw0Gd30LVvp3rtl7+noF7bDzjjCN7f9QZHDTu8XvtVoHPvUqb+sobHZ26i88FlhNIKueOVrYy4MruS5IDSeTnq5EKe+3QDcYnR3bClKVj7RxwFORb8PvhtXuCCFIIZL2SGFEgOJpxXm4J37lXO87M3cMiAEl65pxUlhTq1LznDrxbAaJxIcvdYg/ob/bkwnry9ljrHj4Tq5+DzCt6bkMnovj15+6kW/LkwuGpw/VEYUCreDxBxiJTXwTWWBpEcUFER/zrwfIfMH48suF7VmQDSv0FJ8FdbvEMuzAIsVlmjAF7TVNTn8EHFnHNFNgg48tRDOfniQTV2tdqsjH1oZNhpjrltT4DkABhg7KDBWlZGUf1JDhoi6cGgJEcae8D3O+GKwYWAxFSDJz/cSEKywdLvq0exKvyxAL1z4O/q1i9N9XspK9G46/yOdUgOgM8TvXVHfSE0F7guIuSNAQ3sJ0ckOdIswCy4DZl1NDL/YmTehcisAZjFLyLlv7uxIIbGo95E56KLLmLixIl1Xn/99de58MILm2RS/xYcNawvL/32OB9lTeHRL++Map+0VvXXhBBC8OCndzDw7CPrtV+Ldh6e/mgjzdsqwbATAyJ9tdGrn5vjhhUGTS3pFmjezsuwi+sXqSsrVXo4n04O5LGlYMNKV/idasEMcl/v0KOcJ97fxNMfbWTvNhvlbq1SH8U0YdH8RF64rXXQSE9tZLTyBW2JNg3B6w+1DEq2IqFinbLaJBfcmMXRQwvQdMnc96P/3t3FGgU5ljBkrWrhqT2/xvVQVocG6d8hLb2h6P4mGC9wMp55yJJX1N/L5xFtSiKSLcZZ43K57PHzefDT29EtdcccdtUQrnz2YmwOJVqpWyQgsdpNxt+3i2Fjc2sNWtezK2qYW6kXMbQejEidhrAdEWK86KK5QkByusHtL22n76ASFTkT8eA4E1yjEakzVcQoYwHEXU2xuw+LFyQw6f6WjOnXk7V/1CXjukWn/UFtoj+XCJCmW3U2mVUt+yL+erCfWnHEmn9aD0EkPR5hzBJk3gWBouZq9zdZAu5XkIX/q9MxFcN/Cw0uRp47dy79+/cHYNGiRWzbto0xY8Zw8803V2733HPPNc0sD3AkpSdyxCmH0q5na7at3hnyR5WcmcThJzXM3V0Iwa1TrmbN4g3k7gyv61GB0TfvwRlvVi4Qhwx0M/2Pv5n7fioT72uFt1wxmyGj8vD7CUkONA2Gjs5l5kvRufTGJRqkZvqZMz2VbetV6FjXJR17lkWs0ynIsfDRaxl8PT2V4gIL8Ul+Th6Vx4grsklrXnUTy2ztI7O1D9OES4/uht8nKCm0UFqiA5LBw/Pp3d8dtgX+lPNzWbEweP3Gd5+koOuSG57eUe1JP3pUkKRbJmzn5y+TydkVOfX3+/fxzHixGX/9puaUlOZj2MW5nHt1Fg5X8DmEM/5sFPSOCC0JmTsczKa005BQ+g4y/kpkA+p+gkEISG3m47xbBiLCfOHn3HQ6Qy7uwU/vXEjuXgtpmX6OPq2AuMTaSoJJlJY42LgiDimhU6+yenYyRbpeLOA8G+E8C7RMhKVd+M31ZtQw6IyIQKOElolIfRNhqRV11psjEq4nMf46Jp9xEzvW7Q6qCabpGoNGDSApXUVlfV4fq35dR7nbQ9sererl2q1qlp6H8tlUEHVpOwoRf70qUE+eAL4LkKUfqmialq4+H/ugoPYXNVA6HfybCP75SCj/DFwXgC1WX/NfRb2JzsqVKyvbyTdu3AhAeno66enprFy5snK7pjRf+zdACMHVL1zKnac8ApKg7edXP39JTQGxeiI+OY43VjzLbSc8WKnKHAoJyT4Gn1NQZ8GzWOGU8/PIbOXlntEdkVKQ3sIXNgKiFpLqkaCKc6v7HWu6ZOjoXKxWyelj8ug7qJjbR3Rm7w4bp4/JrbN99UU5a4eVG8/oTH62tVJPpaTQwqeTM1jwcQrPfbaBVh1qytlv/NvJri1VeXiL1WTAKUrkq8ytlJkNP0EJz7HDCvlsqpv1f7qC+iHN/ygFzWJy0zM7kWbVGNESCSHA4ZIcc3oBFmv4xe+bGak8d2trtGrjFuZamf58M5Z+n8CTH2wMSXZAperuOK8DZ4/L5ahTihpPdCydkaUzwf93IwcKAlkCvrUISxdkQ1NiwSAik8n41E4MGXsslH9OsIXRWy5480kXX76TiKcsGVAF9adekMu4u3dHpasTGSZCb41P9qFobxFxSWVh/fGEloy0nwyeuUHnXGtrRVLjrwLHKWE9ooQQ3DPzJm467j7KistrkB1N12jVuTlXPTcWKSUfT/iC6Y/NojivygrjsBN7c8PEy2nZKbwsgDR2IXNHgJlPjUiXdxEybzSkTETYB4HtSIStflFrAFn2PuE/Fx1Z9iEiRnT+s2i0YOC/CU1ZjBwKy+av4KXrprBjbdVTcGa7DK54+iKOHRFaH6O+eG78ROZMWRDy/Qtv2sOY28K31d55fgeW/ZDIbS9u5fizCsJGP3L2WLjwsIPQNIlmMTENFZqpLvCmaZKOB5Xx9McbccWrG4/fD7s22/lmRgrj76vrUVTRmr5qSRxP3dCGrO22IF5HikB1P9TNhM831nh97vspPHuTMghs1sbDM7M2kNnKXzl2RWRFmsG9pdzFGq/e3YoFn6QEEatTlgDd+pRy9uXZ9B1UjMVqVhKOaMnEF++k0qqDl0OPCe6XVJBj4YLDemL4IRh5FJpkzG17Irp///RFEkcPLWxCj6/oJRTqPXLq+0gtE3KOb5oBLT3QojSklLIcWXBToAi66qIwDIN7R3dg2U8JdWq3NE3Sq5+bx2dubLSGU16WhemvjWfu28oMWGiC/qcfzuh7R9D18OA1f9K/DZkzHIjsqySSJyEc0X+ue7dm89Fzs5n3zg+4C0tJa5XKaeNPZPgNQ4lLimPKXdOZ+cQndfbTdI2ElDheXfokmW0zQo5v5l8fqMUKRmoFiGRE5s8IYVXRcO8ipGceyDKEpSs4z0RoKaHH33MQ1dO5QWHrj5b6TvhtGoE/v/+bWS98yZ8//I0QgkMH92b4jafRa2D3fXbM/xoas37HiM4+gJSSdUs3kr0jl+TMJHoe1XWfiG799fNqbj7uvmqFGVU352lLV5HewhdyMZYSNvzlYPIjLTnoCHdYUmT44f2XM3n7qRYkJPt54M0tWKySmS9lsmheIqYpKtMsI67KxhkX3BqjYi5SQtZOKz99kUyz1h7ef7kZ61dEV78zacFa2nevErD7/rNkHr+qHbpF8ubC1WS2Cn7O4TqxTAM+nZLG20+1oE1nD4mpfrascSpHcFSUqN+JRbRo76WkUKN7HzenXFAQVdu4lPDLV4ks+S6BAacU0e/Eqs4fM2Ad8eGrGUx9vEXQwujAKKRmqq6gcMerEM7bV/B6wO/VcCWE75CKDAci81cwdyNzhjbN5PT2YOmEcJ4J9hMQ1aI70rcykBLZCloywnEa2I8H/ypk2WwVadBS+OmDz3jk8vBppDte3srg4QVhttBApICsG70EyNlt4YZhB5OXJTH9NSMomq7x2Fd3cejg3kH3lf4tyPyrwNgY9H3QQW+JSJ8bOd0TAlLKGtH4vVuzGd3x6pB8V7co9eubXr8y+HhmHjJrAJEiUSL5JbAdgcy/XGnmVCYbDMCCSHpMfbdBYGYNUGKLIaGD41S05H1TSvHB05/xxh3T0Cxa5XeqWzQMv8k1L17KWdeeGmGEGKLBPic6w4cP56233iIxMZHhw4eH3XbWrFn1msD+xP4iOvsTv8/7k/JdlzLh1jYU5loriyw/Xb+yQbUltSFNFfWY/kImHbp7OHZYQY3wvdcj8HkEzngzKp2cCtx8VidWLY2rZrQY3Yp524vbOHFElYhbUb7O7ed25LK7d9P3+MgO07WjPELAX4tc+L2C3keVYrVVtdb/MieJ3+Ylcvn9u0hKNTD8VVGh6qQt0mJfXgpLv0vk4fEduPqRHZx5adUiuHKRi6/eS+O7oBGlmpi19q8Gq942BlLC6mUueh5eimlUfQYNMzLVwHURWuLdyuMoqx/R155EMTYmWHohUt8EkYgsegTK3kVFboyqPy29EalTEFqyOpey2dw59GX++CkhaBoTVFSn55Funp0VimhExmNXtuWnL1OCGqAKTZCSmcT0ba9VFlRLMw9KP0b6VwJWsB0L5V+Ddz4163YEaKmI1HcRlvqbCYfCtIc/4t2HPgxrNGx1WPk0/+2g+mDS+ycy79wIR7FA3HXgXQC+lYSK/IiUt5W+US2YxU+De2qI/QJ7p7yu0mNNjFW/reOGAXeH3kDAa8ue3m92Gv+fsc8tIJKSkipZflJSUv1nGMM+w+EnHcLqH85nxvLX+XpGKr99k0hyuoHfJ7DaZKNrNYQG8Ukml1dLO1Vf3G12GZZQGX6VmrE5JPFJylJh9lup/L04jmjJTXVYbTVvuIkpBq/OXR/VvlLCb3MTOOKEYjRNpRBSM/0cfFRdDQ9NhwGnFnL0aYWVC3qw1F64z7fic3K4oP+QIoSQTLy3Ff1PLiK9hY81y1zcfm4n0pqFjrxVHUdWkrD9jTnTUxh6oSKX1dN/1cneGw+1YMNKJyeem8/Rp+bjSoCaqa/A362HIRJUw4LQkgK1J6HSGvVF4Nrwr0RmDwZrX/B+F3jPqPmnfxWy4GZE6tTK13dssockOQCmKdi7LZzhrg2VQgn+PRXm6vz0ZXJIl3dpSvL2FLDoq2UMOOMIZPnXyIJbUJ1EQv1X/jloLSHxYfAsUFo/IgHhOB1cI8KmeBqC7O05yuQ0zNfjK/dRkl9CavMgx9aikVUwVETG92eYbTSk+7WgREe4LkaWfRzoTqs9UQ2sh4LtmCjmUX989vKcyuhNMOia5PPnruWGlwYgXKMRlrb7ZB4xhEdUROfNN98M+vcYDgx0P/YmjLzNDL1wHkMvzGtSL6hgiIY8lbk1nrmxDQu/ScT0q1BPUpqPdt3KWLEwgYaQHF03OfToulGbaJ3DhQC/X+P7T1M44Zx80poHV2CuOp5axBuadaw+tsWiSIKU8NW7abRs7+HVe1th+DWyd9vCpK1UfdIRxxfVIZT7w3aiKE9HmgK/L/Q1JU0YdFYBH0/KYMXCeN59pjnPfdWKjDaZ4PleqSpb2iKco8A5rEaBrEi4BeldqAqUmyyyA8jiaiQnGAzw/oyZc6YqYta7UOZWreehxZ4kSWlhtMKsR4Dvl5Bv79pijxi10y0a21bt4KhTHciCGwPzqfgvAHMvlLyKyJhbaTWxr5CcmRRRs0C3aMQlhUg9651UWtHYSuh6LwGUopajUJ+vAd6FSNONqEWehJ4JqTPU5+VfTRXBFmA/CZH0OELoddJyTYGVP68Ja9NjGIK/fhVQ+i6ydDqkTELYBzbpHGKIjHrfwjdv3lzpcVUd69evZ8uWLU0xpxjqCSF09NQXEa6LEGLfkpxgqH0fLHNrjOnXnZ+/TK4kOQCFuRZWLEykISQHJM3beYlPqvtoGe29S0rI2m5lznup9SJHjYVpws7NNgy/wDTgo9cyeO6WtpSX6oFjSJJSfWh6kIVAKC+xkddmYZpVxdsVn3n1v0eD3L0W5n+UwtfTU9n4d2TV2B+/SKZtl/Kw15SmQ5vOHkAgpSBnt5WHxmyHsumqNV26wdINHCfX6QISlnaItA9A7xD9STQl/KvBt4Ki3Z9TnF/X7qQ6BFSZdgYdK3xk0eGKTORMw2T+ez/w0zuXBRbQYF+uAeZuKP8q4niNxQmjjw27kOsWjWPPPQq7MzjhEkIg4m8kLMlxnkv0S5En6KvC0gGR9iki9UNEwr2IxIcQ6fMRiQ8g3ZMws45C7u2OmXUUZvGzSCN4DVV9EUyzqTZUx6UB+JAF1yCj1EWKoelQb6IzduxYFi5cWOf1RYsWMXbs2KaYUwwNgBA6WtK9kPIWaE0n8BXdsav+LiU8dV0bivKCrYyNYQ2qFmjKYy0Y3bcH5/Q8iJvO6MSCWclk77TwzjOZmEb4RV8I+GZmGru3hks/NBzhjv351AoDQFFpVVBtZpw0Mp8uvVUKTbeY6BaJECoteNfEraQ28yolYBH8v0goLxU8c2MbRvftydPXt2XCrW24+qRu3HB6Z3ZtCf15FGRbKHPrIdMt1cevgGkI1i13sHZ5Rcu0F8o+QuaNRpp104TC0hHhGhX5JPYh9myzBO32q4CmS5q39XLSyFAaVgJE+AB5u27lNG/rIVwnm5SwbfUOjhgcvgsSNGR5uIhV06Bt91acMm5w0EiIpmtY7VYuvGdE2DGEcygi8QFUak+gIjcBguA4G5F4r+quipS+1FJBhC6dEEIgbIcg4kar60noyNyzwD05oFQt1Z/uN5C5ZyGNxutD9TvtMDRL6GVU0yVHnlDRKSdVdLPs00YfN4b6od5E548//mDgwLqht/79+7N8+fKmmFMMjYBmH4DImA8J+1es8YU7WrLsxzgK8/Qq24cmhSRrl42PXssge5eNkgILa5bF8eS17Rh3bHemP9+cl+5ShojBCIeU8PlbqWxd5yA5XPqhEai9FpgBef0/fozni3fSQu5nmnD6mFxe+HIDT320gWFjcxkyKo+rH9nJzOV/c+ywQpxxslrhdv0gSeHBcR349qO6Bc/r/nRx85mdycsKvqqmNffx4xdJYVvW/X74/rOa9RmaJlnxa3UxRhP8a6Ds/eCDWLpFcyr7DJGiLYmpfp75eEOY7aRSIA4DTYPRt+wlEuGXpoiouwQmyODRjabGjRMv55ybTsNiq3mNtOrSgme+e5B2tUxUpTSQ5V9j5l2KmX0SZu4oQIOMbxEJ9yiV5vjrEOnz0JKfUFE+55lAuFC0Bs4L6tVNppzec6hLoEwwc9T7jcSZ15yCJkTQr1QIpcB9Wi39MOlb1ujjxlA/1Fu9TghBcXFdc7zCwkKMaAyGYtjnEEIg4k5H2joic68Bdu7T40kJicl+Zr+VgdVepbETZg+sdonPEyiwjAqBVqlq21cUjnrKNEDw/acplBZrXH7/LlIzjUriUV4qmPlSM2a+mAnA4HOiU5ZuLLJ3Wfl8ajqfTkkPRHGC1X9Izrw0hxbtlBDiIQPcHDLAXXMLqaT9G4o/fjuSZT/U1TACFX0pzLPw6eR0LrlzD7u32nAX6XTuXYYQcMzpBbzxcAsuvDGLjFbeOsKShgE+j1Zl9VENQdv8S2cg4i6p+4atH+jtwNhOsFqdvCwL2zfYcbgMOvcub/I2+jadPbTqWM7OzXYIEtkpyLby6FXteHzGpiDCjcqQk/jrFJGToa+vk86zUOi5kKl3zcA0JZqugZQqPVStdnvzGgcde5QH1X6qPKa1R0NOtd7QLTpXPHMx5985nCVfL8dT6qFtz9YcNKBbnUiPlB7VAu/9mcquMGObWtz1DpA6DU2vq7kjtGRIehxZeGtgv+rXu6Y66eIui3rO0r8FvL+G2cIA769I/xaEpX3U49ZG664tufeDW3h45HOYhhnoTpNomkpZ3Td1C81aV9f4qc89L4amQr11dIYNG4bT6WTGjBnogbuNYRiMHDkSt9vNnDlz9slEmwL/H9vLI0FKiSybjTfrdiw2M+pUR0NR5hac1aU34X/MkszWPrJ2RJtCClMgGng/Kc3PjOWr0HXYsdHO1zNS2LrWQZlbZ80yFz6vIhqaDp+u/wu7Y991MD16ZVuWLkiktEQRPk1XhMJqN2nfrZzTLsqlffdyPGVKvbnfScU1Cp7z9up891kKZSU67bt7OfjoDBIT1zV4Pk/f0IYFH6eE7ShKSvMx449VjDykJ8X5VjRdktnSy5mX5eD1H8RXb2bx0LubaN/Ng9+nyJfVBgW5Og9e0oFVS+t217w0Zx1dD6lt82BDa76yzrYA0rcCmXcRSC8VC13ObgsT723FL18nVRZsp2b6uODGvZx+cW6TXssVmkzBIDTJCefkc9sL26u9GmhV1zsjUqci9OaYvq2QexbgrjuI1hrS5qLpFvL25DPvnR/ZvWkvCanxzJnyLYXZVWKAJ4/K5eZnd4Q5Pw2RsQCht0T6d4DnO8CjImO2gTUc4vcnzKLHofQtgqfndLAegZYWWrhPehYh3RPBGyiP0FJVJCfuMmUAGiVk2ZfIwpsibieSJiCcp0U9bijk7Mzli0nz+HP+LATF9Dm6hFMvzCWtWd3osUh86B9P1f4bsc/by6vjySef5Nhjj6Vbt24cc4xq2fvpp58oKipiwYLQSr0x/DMQQvDFOw7evKsHJ4/M49gzCkhv4SO9+b5J3zjjJIkpBkX5OqHJieCIwYV8+U5oNVWFCoITaTUTFOZayd1jJbOVj5YdPFx2zx6+np7ChFvbVNtfcMUDO/YpyQHofFAZRbk6a5fHUebWadu1jHF37eKIwSUIoVJVmlZN0yewn5RKvye1mcGQkXk8cU073n2mOW27WZj0bcO7v/Zss4UlOQDFBRbeeKgFxfkqfWAagj3bbUx6oCWtuzjp0ieeKwd349BjS+h7XDGaRbL2Dxc/f5kYIJFV0HVJ1z6lQUgOoIWpsbAeDGmfIEsmQfkX5GVJbjitK3nZlhpdaXlZFl6+qzX52ZaI6t/1waAzCyjMsTDpwZaYpjoPaQoMQ3DcsAJueHJHxUmAbSDoLRD2E8B+bGVKRbO2Q2b+jCx9C0o/UoXYenOIvxphHwLGdszi90m2beDcy10Ix8lgP5EF7/1UYy7zP0jliOOLOea0QiR1v3uR+BBoKZgFN0P5l1XzwlDt58nPI2x96pyj9P6BdE8F748gDWUoGjcG7EPCdiTl7Mrjh/cXUpBVSGbbdI4bOYDE1JrGp9J0Q+kMQtcgGeD7Delbj7B2CbqFsPdD2PsFark8IJIaRtqisAOp13YRkN4qjbEPjULe1QxZcEWIrTQQieA4o0mOGUP0aJAy8q5du3j55Zf5888/cTqdHHzwwVx77bWkptbfmXt/4r8Y0SkrKeO8FuMpd1fl8w8/rojHZmzeZ8ecNSmdSQ+2CvGuylt/vGYld1/QMSAaGFoRGAGpmX7adS3HU66xbrkzSDGvwvRlf9cw/gQoyteQUlCYq7N7i53Djy+Oytm8cgaNaOE2/Kpr6bX7WvLItE10Obg88k4BmIZqTb3+tC5sXu3i/imb6H9ywzys7hzVkWU/hnfjTkr14y7Wgn62mq6pyGAQ/zb1viSztZe92+xIJM3beHlm1kYyWtaW5dchbhxawq0R5yyln1dvnMLnry7ANEwcLoPjzyqg26GlGH7B0h8SWDw/gTcXrqmVGmg8CnJ1Fnycwu6tduKT/Aw6q4B2XavXw2hgPQwtbbpa3MtmIctmqXoQvSXCORKcp9fpMJPuKcjip6hKzQRSO3oH3nxmCB9OWFSjw0nTJKeNyWHMbXtJTKmVyrEPVYrOvl+pm+rTABsifVYN8UBZOgtZdCc1U0OBOThHq6LgWheYaZpMuXM6Hz03Gykluq40Y3SrzrjHLmDEzcOqxvcuQeZdGOHTFaorKm50hO0aByVGORDwhtnKhsj8BRGGfEPgvEqnKzFD4UQ4TgLnKESQFByALJmELHmWKpFKUCQnTpmsWhtm7PxfR8wCIkr8F4nOvHd/4KmLX67xmsVqMv2PVSSlNmFNlW2A0kSRZeBZxjNXzGHezIqnpSpdC90ieXzmRg4Z4ObPhXHccV4n1YxQqy5CCMlRQwoYd88eWrX3VhbDFubqzHypGbNeT6cyUiMkrTp4mPLT2rBu3vUhLRXb+n3qz/AdMDX3qQ7Dj+pqkoJWnTz1isr4/fDTF8k8cXU7WrT38fqC1Vjt9ReB/HRKGhPvbR3yfSEkQpNR1FaFhm6RnHGZg5btPZw4fBWu+CAkRyQi0mcr3ZMIMPwGZ6VcTLnbQ5+ji7lv8hZcCWbAD0xJKOzaYmPxtwmcNa6+rcIV12P1hagBSP0YCm8FYwtVUYwAcbD2QaS8Wan5IsvnIQuuCTGQjtffjrM7JeH3m5VDCSF54K3NHDm4OEitTiQ3cx0cp6MlP62O79+BzDkx7D4i+SWEY0iN19554APefejDkPvc9PqVDL3sBHWMqInOPYi4iyJs13iYRY9A6bsEjzCJgEL3PSH3l1IiS54D9yTqkhaX+n5thwTf17cqQI5WgLAj7CcFBB0P7GDAgYz9TnQKCgpYvHgxWVlZmGbNH86YMWPqO9x+w3+R6Mx4/BPevv99DH/NG/rQ0bnc8NSOEHvVE5buiNR3KuX0AczsU1n7+y4mP9KC7esdWKySgacWMvqWPSQkV10zv36TyLM3t6E434JukaqNWcCIK7MYd7cqoA22sH84MYPJD7es/PdNz2znlAuatsh4w18Opj7enDMvyeXIE4sbHNlpTFTI74PT2x+MlIJDBrh54v0NYQpUg8NTLji7Wy+MoJGwSPVP0eP1H4to1/d+cL9I4Z4/+WtRPKYh6NrHTfMOHRDJLyAswU0ra6Mwp4gRmeNo07mcV+etw2KRdc7b8IO7SCcxasIeIDiWnpBwJ5R9olI4ZhlQkWarR2ubfhAYqwi+kGrgHIGW9IgaNWcE+FeGHX/l33dwx9B5mIYf0xT0HVTEo9MbE3m1Ipr9iRAWzOJnwf1GmONrYO2Lljat8hV3oZvzWozHWx46YpbaIoXpWyeiW3SkWYLMOopQWjcVEGmfI6z73uxSSq9SlvZ8Qx0LEPvJiOTnwrq7y/I5yIIbQryr0lAi8weECO08H0PTYb/W6MyePZsLL7yQkpISEhMTa4Q6hRAHNNH5LyKlWVLQbrivpqVhtZtceucu7M56LMQik0qlVktbhPOcgNptLfE5WUC3PmU8/dGmsMMdNaSI6ctW8dvcRHZutuOKNxh4aiHpLcLXEJ17VTZfT09lx0YHw6/IYsj5TUtypIROvcp5bPqWGqJ8DSEsjSmYtVjBYlMdan8ujKPUGEGc9ilCRF9jZXdIxty6hzcfbxnk3caRnIRkP6dfnMspF+TSrLUPM28sv32TyPO3d6cw11J5iH5DD+OWyWmkNItuXGeCE92icfb4bPQgJAdUlC0hpR4RGUsXRPw1YD9RmX7a+1W+Jf0bkCVTwfOV0jqJxrXd+DvMmyaUfYJMuAUQ4F8RaXL0OmIP72x8hS8nfcWK73/hvOu2VNZzNQw+kOUg4sG3nPAkzgyYaVZh8ZzlYUkOQN7ufFb/to5eR/dAaPFI10gonRbiWDpYD90vJAdQJCb5RfAtU6lFIxv0DIRzuLIiifDDlCVTCB05M0EWQNkX4Irk5RXDP416E51bbrmFSy+9lMceewyXK/oq+Bj+GRw9vB8vXjsZX5Ab1mdTMpj3QRrnXG1l9K0WMLahihnTVfeGbxUYgW4fvbNqC3aeE11xoN4OzDyiWTBsdsmxw+qnFmr4Yfx9ymyzx+F1ReiaAj6v0jTJz7Hw8xdJDBubi81RN3W0r6wYpFRKxj6P+rxdCQZO/ROEMPD54tiwAlb/7sDwC3r0LSWzlZfUTH9QFeOR12ZTUmjhw1czEBqIQCQnUpFyOKQ19/Hcp+vJaOWrFDME6HdyEc/3WM/NZ3YmP9sKEpZ8s5wbj76HV5c+SVxSZP8jm93KMSP6c+ywP5uolVyAlo5wBHeSFpbOiOTHkPIBZNnnUHQvodNamhKuk2FUkgHwqboOS5QLu/SR0TqNsQ9fBFyEmXMO+P+Kbt9gEIkgKu7RFWJ94RQ1a1447sLoflfuoqqic5FwK9K/FryLqCIJgQtDb4nYBw7iUkows5WukN6spsWIEGA7HGE7vJ5jeqMgpzrSuwgRIzoHPOpNdHbu3Mn1118fIzn/EsQnxzHm/vOYcud7dd4TQuAps9Dn1PvQ0noG3V9KD0ijXq2dAMI1Clm474SxdAv0P6munlNTQQj48NVM3nm6BQC9jixh+BU5IbffF2RHmjD7TaVPo+mSoRfmousG7mKNO0e2wDThsRmbSUgyKjtzKtSha89FCLjsnt2cPiaX+R+mkL3bis1hUpSn8/2n4esGNF2jebt4dm8urFFLdfNz20hv6atBRIRQHmGZrb3c9Mx27ru4IwCm32T35ixmvzaPUXecFdX5X3j3CJxxE8NuE/1nLiMK7EnPz8iCm9WTekgtVQ2wBFrgo4EIKPqmgQxXS+RHWA+q+ZKeAf5ItTihoIFrZOVDibAfh/T+HGZ7HezH13ilVZfmUR2pVeeq7YRwQMpUKP8aWTpT6SJpaQjn2eAcjtDiw4xUf8jyOciSiUqMEkAkIl2jEHFX1/ueFcP/X9Sb6AwZMoSlS5fSsWPHfTGfGPYBRt5+JharzrsPfUhptaevjLbp3Pz6FRx8bHCSAyjTwIYs4I7TVDeKZxFC/Lvq3SvSVP1OKCJ3j5V5H6Zy3jVZIQ0+90U0xzBgw19Otq6zc8UDO2nbtZxe/ZSh6at3t2LXVjtTf15DXIIRiNAoaLoiSDLEvJq39QbUeavQZ6CbNx5pgbuw1u0gEADodkQnHp59G9PuHMXnbyYgTWjZ0UPfQXUNVitgscCRJxTTrLWXvQG9JGlKPp4wm55HdaX3MT0ipg7aH9QG3y47kWo+ooMO1t4h35W+v5H5l1MVxQlBLiydIeF+yI9UdAuq7uVg8K9DmZaGggARp34z1V91no30hJPsCBWh0VX0pLrAnvNsKHkJZDHBz00i4i6u8cohgw6iWfsMsrblBO2403SNgwZ0o3XXmilRIawqne0cVmefpoTqYnuSGjcoWQTuyUjPb5D2boPrZ4SwIS29wL+K0ETTQNj6Nmj8GPYv6l2MPGXKFB566CEuueQSevfujdVaM9x5xhkHrkbAf7EYuTo8ZR6WfvMnRbnFtOjYjIOP64nW8AKAiJDSgyx5AaNwKrqlCZ2p9zGqd2kBbFxpp9NBnrA2CNVreAw/zP8ohdlvpbN9gx270+T4swo4c1w2LdtHboX2eQTzP0rhkIHFtGzvqxOh2bTKzqJ5SYy8Litk/YbfB1vXOuh4UHnlvqYJC2Yl066rhy4H19S48Xlh1ZI4fvoiiXUrXBTmWti7w8b5d47govtGoOtlyOLnyds6g4VfJ5LWzMdRQyJH1B4e346fv0yu/LfQlDZNi46Z3PT6lRw6ODT5ADCzjgczOmXv0hKN2W+m8+W7qeTssZGQ7Oek8/I5+7Js0pobiPSvEZbg5qFm/rXg+ZawXViJjyKcytdJ7u1N+NZlQO+ISJ+NzB6sUishF0wdkfI6wn5MjVel9CPzLgjUztTeVwetGcRdBO63lKM5ABZwDEUk3InQa9qOSN9KZN6lICvSxBIVoRKIpKcRztPrzOzP7//mf0MexjRlQPVXQdM17C4bL/zyKB16tQ3/OewDqC6yEwiditMQ8Tcj4i9v+DHKvkAW3hxyfEQ8IuPHWORoP2G/dl2FWxiFEAe0DcR/nej8U3Dnb8ZRNkQ9uP4L1c+jKQiVUkVSDAMevLQDSxYkIDQ4+KgSzr4sh979S5BSuZcnpYX/jVQIB2p6CBsFqciUpoefV0mhxrcfpXLmOJVy83oEY4/qTkmhzgtfbKBDj9C6PlJCWYnG+pWtOeT4Y8je9DFFeZDW3E9yevSF0A9c2p5fv67QKZG0aOelY88yFn6TgqZpPPPdA/QaGLqGJXyLcBWK8jSev72NsopYb6ekUD2AabokIcnguXkn0/bQq0Kcqxe59xDCt5pbwDUKLfE+Na+C26B8NmHTSsmvIvAjC64PO3e05oiMH4JGuKRZgiy8GzxfU+MzsB6JSH4GoTdHSgP8a1XhsaV92BZmaZZA+WfI8h8BH1gPQbhGIvTQaarVi9bz1r0zWDZf1QsJTTDgzCO49NELaNs9lF7WvoVZ/Dy4XyPs56+1QMv8ocHHkFKqiFHpVOq2lzsQKVMRtsMaPH4M9UNMRydKxIjOPwd/0WSE+yng30l2ItXgSAk/f5nIzs0O3nqiOVIKRl23l0vu3IPfR2WBcAVBaexnEE1NUHmp4OKjejD991XoFkWe3nqyOR9OzGTw8DxueyGyvMDKRS7efKIFKxep2gohJP1OLGLcPbtp2yV8SsnnFZzfpyfFBZbKfcf+bzfDL89h9OE9KS6w0nNANyb8+DDSLITyr5XonpYJjlMQWgLSvxmZcyqR6lRKCjXik8zK4y6YlcwbD7ekON+Cpgs69G7HxN+fquvNZBYi/dsg75wIn4QOjmFoyeoalr51yNzhgI+6JEwDvSci/SNk8SNQOhMITw5FxkKEXtcvrHKexi7w/hZQM+4TUll4XyJ/bwEF2UWktUghMa2WKrJvNbLsExW50jIQzrMQ1p6Bue+Gso+V/5SWgHAMBWvfiKnLcDALblDXSwQCLJqtDNtCHg2k51dk6Xvg+xuEHRxDEK7zw5LDGJoe+7W9PIYYGgJL4mWY1jZQ9DDIrH96OvVGpHuyEMrn67Mp6bTtWs4p5+cx/HIVSaneBRWN8GC08wkXaTL8sOYPFwXZVtb96aLH4aUIDQadVcD7LzejZ9/SiGTpz19d3Hle5xpu8FIKFi9I5M9f43n+8w2061YedAzTgDnTUytJDkhcCSanj8nFYpGcPCqPD1/NZOXPqyna8Rzxlqko0hB4ci56EBJuUZ1+SY8FnKZDL2pxiVVEyGqTnDginx6Hl3LD6V0oLdbZuHwLaxZvoEc/RRCkbx2y5PlAuiqaZz1Zw/xRWLtCymSlsyLzUbdSqeZu7YtIeQkhNGR9TGvDvau3BOfwKMfaN0hplkxKs+Qar0npRxbeC+Ufo7471c0nS99COs4GSycoqei0UucoS98Daz9Imdjw4mQRR13zz9qwEt4RPcpD2Y9C2I9q9Dgx/HOI6rb74osvcvnll+NwOHjxxRfDbnv99RHCtDH8Z6E5hyAdJ4OxCVn6EZRO+aen1GSQEtp1LeeOl7fS52h3pfZORa3PqiUuPp2SzpY1TlwJBsedWcCZl+Y0unU6FFnRLfDpFCVRr9zd1XaueBOr3eSkc/MjRqj+XhyPadZVrTYNgadM4+W7WvH0xxvVawHS5ferQuQlCxJ4/cHqRaoCn0coPRwB3fqUYnca3PzcduIt1dt4KyIfXmTx4yyas5ri0tM4esg47HJyyPnWPhfdAq06ehh+eTbTnm2OEIK1SxTRMb1/Qd5oVI1NtAFtiTSLwbsYrEcghEDY+0PmT1A+F+lfDdgRjuMR1Yqehe1IZOm7EcZ2KGsI53CwHVkj0iGlF3yrAZ/SAYpgV7C/IUueh/JZgX/VIh3ln4Te0bcImXUMxF+uusPqqRgsHCcjyz4Ks4WuooL/xvBxDE2OqFJXHTp0YOnSpaSlpdGhQ/BiPlA1Ops2hReIawi2bNnCww8/zIIFC9izZw8tW7Zk9OjR3H333dhs0YclY6mrAweqLqI30S80Bz4Mvzqb2l5apgF7d9i49pQulBSqJ3/dIvlqWyM0UoDNa+y06+rBNGqmxhTJSWPiva0QGry3dBVpzf34/bDk20RevqsV7/2+OuzYpglfvpPGy3eFto4AeHPhalKbJ7BoHqSkl5O9y8q8D1JZ/nN8HYIE8NRHG+h1pJvlv8TTpXcpCSlmWMJVkGNhTL/uHHNaIeffuJfWHaNt61bIy7Jwfp+DSMnw8dhHrejY9XeQDRGXFFRGECxdEcmvIiyRi3Cl9CGzTwwUC0ewbMBQYobJzwMW1T3knhxod0e95jgDkfi/Girk/xSUEvIAIHoPt7oQSmE49e3KVFdUx5YGMndEoK28dlRHABZE2kcIa49GzC2GAwn7PHW1efPmoH/fX1izZg2maTJp0iQ6d+7MypUrGT9+PG63m2eeeWa/zyeGxkMIG9J1FZS++k9PJSIMQ1kNuBKMuiSmWvooVO2NpkOzNl5OHJEfiLIIpBldkXMoSAk2u8HtIzox7JIcjhxcjK5L1i538ckb6fwyJwlNh/4nFVYanVos8MXbabiL9Mpi53BQDvRVaNetjL6DirFYJZtXO9i0ysmebVZadm5BoWc8j50zNap56xbodaQbiy2yb1dyup83F64hrZkiatIkbPdbbaRm+mnVsZxnZm0kJWONGqDaXMpLNTavttP9sLIa30Vhro4jzsRqk4HXA2kpAP9GZN5oZPJEKP8UPN+p2hnb4QjX6Bqu4UJYIeV1ZN6YAGEJ4+wN4PkWWfy00vwpm1lrG78qJPb/BanvN7kmTb3hXUzjSA4ofaMSZP54yPgu6noaIXRInYLMvxp8y1BEUQB+EAmI5OdjJCeGStSrGNnn89G9e3e++OILevT4Zy+ip59+mokTJ9YrghSL6Bx4MAsehvJIof1/BoahxO9W/BrHsze14cG3N9O+mwe/Hwgs2OWlGs64yK3z0oSNfzu5ZkjXytee/GAjvfuXNKpuJ2uXhfdfyuTHL5Ipyq2qR9B0SWqGj+e/2EBacx9CwDczUphwaxtAcN+UzfQ/qSjssS87thvbNzhISPbzv1e30ndQSaUXWQUpME3QLK3Ykf0E43qHf+iw2k2m//43FpvE7pRRp+0qvoeGwDSVPEDHgzxBx6iIcr1yTyuufngnfY4u4ZW7W5GcbjDu7l1hiKio9l9FREFFZUTC7Yi4y1Q3lOd7pbRs7lXkxSwEM1IRuBVVrxQKGiL+RkT8lRHG2beQZV8hC29ssvFE0nNBW9zDzkFK8C1XekPSo6JCjlPqWtLE8K9HY9bvej1PWq1Wyssby+CbBoWFhaSmxpxg/+3Qku+FjKVgHw5aS5qieLCpsOEvJ49e0Za3n2rO/17ZRvtuqsvIYgFPucZfv7l4+6nITtygohBJaTU7bz6cmNHo4uTMln6ufWwXM/5YxZjbdgMSh8vgjLE5vPT1ejJa+ti73cYrd7fi+dsUyQH467c4JS4Y4jHH54U9221ouuTR6Zs49GgleFe7pV3TAHMnrdOv4fhzW6Nbgt9SNE0yZFQefp9GXpa1XsSlMXVMmgZdDg5OckB9l/1OKgIkD45rzzVDurBgVgrHnxXJ3kGiUlHV0ybq77L4Kczy75F5FyALrgLPXBV18K+JguSAIjnhbs2mUh3+p9GknlUWpHdRvfcSQiBsh6Il3IKWeJfq9oqRnBhqod632WuuuYYnn3ySyZMnY6kdx99P2LBhAy+99FLEtJXH48HjqWqBLSoq2tdTi6EB0PRESHkCAFk6HVn0QIQ9koD6eWM1BFvXOsjPtvLkBxvrpEtc8Sa9+5dy8FHR+QEZBuzZZsOVYFDu1jBNwdLvEnnj4eaMv3dPo+YphFqwL7wpi3OuyMZqk+gWeOOR5nz3SQq5u61U7+rp3LuUy+7dHVLpGcBqg/OuzmLTKgfd+pQF36g6ZDG3PL+Xtcsy2LVxb523bQ5B1yOPYd2WEzj88PuA3RGHNE11bvu6nlTToHOvcrJ32ti1WS2S8cn+Rphp6lB4D8gKyxCj1p/RIEKU0GzcNRMtpPQowULpBUu3Gi3wwtIRaT0CfL8TfL4RvLXqHq2Rs91/2LlhNws/W4qn1EP7Xm3of/rhWKzRr4fSdEP5bKTnJ8BAWA8F54g6Io8xNA3qzVSWLFnCt99+y9y5c+nduzdxcTUN+mbNmhViz7r43//+x5NPPhl2m9WrV9O9e9WTw86dOznllFM499xzGT9+fNh9H3/8cR588MGo5xPDAQDncCj9EPyrCXrztPSG1A+g4Crwfr9Pp3LcGfn07l+CptWtZ6nv4qvr0O0wN5+sXUl5qWDeB6m8/3ImH01sxhGDiulzjLtJ5uxwVS0WI6/JZucmB4uyrCrlFMB5V6v2/kgL+ehb9rJljaOywDk8JFaxlHGPPcMjo6ZROyPuKRe8cMM6npw3EmtcH/BkEW7hlyZV695+aJzxeSrSUAo7NtjJaOFrYMTN2PcSCiIh8jYhIL3LkO4p4PkR1Q5/EMJ1MThOq+xSktIA90Sk+82AbQSAhrSfgki8F6GnIY09IN2EdConHvRk5XcV0a/Lj7Ad0eBz2l8oL/XwzKWv8sMHCxGaQNM0DL9BcmYSd753A4edEF7pGyoUqscFZAkUGZSe75VFR/IEhOOkfX0a/znUWzDwkksuCfv+m2++GfVY2dnZ5OaGM7qDjh07VnZW7dq1i0GDBtG/f3/eeuutiPYFwSI6bdq0idXoHOCQZjGy6FEo/5yqdmMHuEYhEm5VhczSUIWI3u/+yak2GH6/KnB+aFx7nvpwY5Pp6wTDljUO7hzVgbwsGyD5YstfWG1N//RsmjDmyJ7k7LYGTYkJTdC2eyte/30U5F8Udqz1KxysXe7i1Avzmsi9PDTKSwUjDz6I8tKqAw04pZD7p27ZtwduMHRwXYSWeFfILVR90I9I7w8gfQhrL3AMU63wRXdSU4MmYBzqHIlIfAghBGbh3VD2YfBj660h5R3l92XsJihhFQmQ+hFCT1ekqvQtkGGinyIBkflro8X99jXuO/NJFn35O2Yt7y+hCXSLzosLH6XLYaF9IKVZqLrwgnqOCUBHpH2qdJqaGNIsUsKNZZ8rGxC9I8I1CuyDK81fD2T8J5SRd+7cyfHHH8/hhx/OtGnT0Btw94sVI/+7IM28gIaIAOvBdbpMpDQDLsnvKeNEYQXrYWA7Hsws8MwHf3Qt3NF0ITU1DL+yZXDG7dufoGnC1nV2rhzcDU2DOTtWRN6pAVj+czx3nNcp4nYv/3YjXdpeTqiC2y/eSeXlu9qSmunlncWr0JtASToUTBM+fDWDqY/VNqaUTPpuLW27eBpw7Ggdx+ub2gHQlcdS+ucIvUXQLaSxU0UMjE1UBe39gANlkBr6mCL5BdBbI3PDKUVrYBsI3p/Dj5X4kFpIAdM0IP9S8P0aamtEyuQ6fl8HEtYu3ci1R/4v5PuarjHgjL7c//FtIbeR7jeRxU8Q+nPTwTkcLenRxk229nH925B5owMyBxXHrpA0GIJInoAQB7Z+8H4pRjZNkyeffJKBAwdyxBFH8L///Y+ysihy902AnTt3MmjQINq2bcszzzxDdnY2e/bsYc+e/ZOnjuGfgdBSEfaBCPuAoK20QmgI51C0tPfQmi1By1yIlvIyWtw5aAlXIdJmgPVIwl3mFb5S7uL9zHJQ6aB9TXJApag6dPcwbekqJn67tnqHdZMia2d0heR7175PuLRVm87ldOvbktw9Vp6/tQ1IMIzqbCPwdy34Qh8OFY91/gDH+uGzZN56svo4MrCd4PtPkzEb9FlFs5MOrktBi7YmI3AN6+0Rqe8h9BZIMx/pW480ciq3ktKLzBsLxtbAK36qoqLlhCdWGtL9NrKsQuU4FEzw/hphLIEs+7TqX4IA8QoNWfRQnZTngYQf3v8lZLE9gGmYLPxsCZ6y0NYoyo0+3DkaUP5twycZ7JhSIguuDhjLVj92haTBXHC/3qTHPNAQNYV79NFHeeCBBzjxxBNxOp288MILZGVlMXVqZO2MxmLevHls2LCBDRs20Lp1TQGzA/mHEcM/CyFsSmuj5DUonUala7OWCSIJZAl+v5P1qw5i8/qDOPWsZ9G0yO7i/1ZktPSTEcFzqTFITI1u7KTE3whHBg4Z4OGFuWnszb2TwuwiiuVWEp0fgPdHtZ/eARE3RhXCFt0NvuVRz7GkUGP173Fk77LyzcxU1v7hQonWqfczW3rJ2WPDNATLf0ng4tvrFlaHRkV7+T3K9ymomF1gO8cwtMQ7kNYuyMLQUYJKOIYjXGeDtS8YmzDzrwbPAio+R2kbgIi/SdXDVJKc+sIE30r124hYOB3pu5ZgVhNm9C6q5rAeYntjK/j+hGo6RAcSivPdRCoYM01JWUk5dqc9+AYyGsHLJr4H+ZaoiHdISKT7bYgbr3Sf/h8iaqLzzjvv8Oqrr3LFFVcAMH/+fE477TQmT54csVamsRg7dixjx47dp8eI4f8nhLAjEm5Axl+t6gmEVblFB/IRdqBXS+h1EphFuwNO2fso5PH/HIcdW0J8sp+SglC3FUl6Syc9+xZEGEktki06NKNFh2ZAF+BElarEQAirMojMPSd83UcQJCSblJdqvDehGbl7qupBMlqlcfo4G6eMmMfzt7bh17mJrFriYv1fTjr0KKsjFKkgFPGQhSD9YOuLcF2gtFzsxyHzRoGZT83rSYClEyLx7sC/o4skCucQhO0I5dGVNxJkec1xvb8h885XqduoU2fBDmQFPZWabt3BUOFrFeo4Guhtqv4ZluRUw37qJmsIWnZqjowQ4nMmOEhICSPkaD1EdbGF/Gx1sEYuaK4XvEuI+H3KfPBvgX/ALHZ/IGqis23bNoYOHVr57xNPPBEhBLt27aoTZYkhhgMNQlghgmS/SLgN6d8ciBxU3BgqFo2qeoponMz/ixY7Nrvk0jt38+IdbYK8q8weL7t7C7oloVonTzAI0FvWfVVoVKRwZNFTYTp+wuPYYYUMHFrIX7/FkbfXQnLzViyau4vy/AKS0wweeHMLe7bZWLk4jr3brXToUTtFH7g2HEMRSc8old7ac7W0g7TPkaXToGyWIjx6C1Wz4hyF0ALdqrZ+RCYmNrAeGjjvBwIkp/aiFdjf92eEscJBB/vxCMewQPoqOCQ6wjYw8DsJBRPhOq/qn9Gm6KJO5e1/nHTxcbx130xCpZ40XWPouBPQLaHJq3CNQpa+HeYoBsI1ulHzVCKKS8C7FBBIY2ejxqvfsT1KJVw4DyifsaiJjt/vx+GoKcRktVrx+f7/hvpj+G9BCBukvA6eH5RhoLEDtAyEc7hKDXi/Z8mnD3HYcSWVRKa6cacQ4C4WuOL/u+nU0y7KwzQFUx5pQZlbRwiJlIL4JIMrH9zF8Wfng/U48P5E6AXZgNJpmKUfgf0ERNzYyi4UaexCFk8A7/xGzVPXoc9Ad+B7K+SwAer1CuXn5m29NG8bLM3gAvtRirDYjg17Mxd6BiLhJki4Kcw2zZGOU6F8DsE/Dy1gepmooli+pWHOykQVGzc0oiOVW7ylF17zCCxySZ0Cfb9fqYHrmbfjtHkDNhC1j6WB7Wiwn1j1ku0oECmBluoQ0FqA9fAGzHv/IL1lKpc9MZrXb3unTh25pmtktk3n/LvCO8wLS0dIuBdZ/BA1oywVnW+jwX5Cg+co/dtUPY5/HVXRwij0m0QKWNo1/Ljl3yHdrwc0lQC9PcRdrEh9kAeB/Y2ou640TePUU0/Fbq/KPc6ePZvBgwfX0NKpj47O/kas6yqGxkBKycn6eThcfkZdn8UxpxeSlOrH5xWs+T2OTyZnsOLXOO54eRuDhxf809P9R1FeKlj8bSL5WVbSWvg48oQibPZoCWD1VUR5GInkl8HSEZl7Hsgimiq9GCr6VrcLTwctGZH6AcISLGLViDmYJcj8ceD7gyqSElgEbcciUl5BCDvS8z0y//ImOKILKKXqc1aRMpH0VKUFw+0n3snJwxcw6Kz8SiKvabBxpYMnr+tAj4GncPMblyCLn4PSmVR6XgkXuC5QFhW1WsVl2SfIwjtCzkokv4BwnNoE57dvMX/aj7z70Ifs2qDSbBabhcHnH81lT44mJTM6d3npWaTa7r2/ACZYewe0jIY2OBIizUJkzmlg5lI/cUqBiL8eEX9Nw47rnoIsfpKaBDtwDvZTAh1djS9v2S/t5ZH0cypQHx2d/Y0Y0YmhsRjVcji5e0I/oei6ZOjoHK59fNd+nFVTo2IBtFBVdGpB3Tz/iWiVQKVvejYyNRM9DCPgV64rCQBDPw1Xi9tCtnQ3FlL6laFn2SdgZIHeCuE6JxA1CqTrvL+rOpxI0NsFCpJrR3YE2I6BpGcQnq+Rnh+Vxo7tEHCei9CbAbBpxVau6HMrAOktvBw+qBirTbL+TxdrlzsBgcVm4f1dr5OYmqBUfv1r1PiW7gjNFfo8y2Yhi56gypEdFU1wnIKwdAZLJ7D1P+B1XaSUbF+7C0+phxYdmxGfHBd5pxDjAE2S5pHuycoQNuJvtOL3XdFefpIimQ1oL5f+TcicU8MeUyQ9jXCeWe+xa2Ofu5fDgU1gYohhf2Hope1474ntmGbwG5NhCIacHyo8X/Ek/U+gOmkJBwHWIxBJj4DeXDl1y3LIu5B9S3LiUJ9NsGNIwBOIeOwfaBq8eEcrlixIpDDPwht/3U6c3rzuzKRPERTvYgCE7UiVbqtn94oQFnAMQTiGhN7IeghoGYE24TAwtoOWrlJBFTpSWnNE3MXgGqPm5hpVqXFTG38vXFv595zdNr6ZUb1uRtL9MDetO3nI3jCDhL4XKOkHW3QpJ+EcDo7TwfOLUlb2/gie76FsBrJiAdZbKTIW5Zj/BIRQ4pdNMU5TQZZ9TsTfqNYCtBQVFdU7BAQDT2gwsVSea9XFJ+scEFn6bpMQncbgwFYIiiGGAwxn33QjC2bewO6tFkyj1k1KSE4ZlUeXg0PoS1l7IxwnIT3zwLseyAu+XVDo6mlXSjDWR9i2up2Bhkh8EOlbBWXTiUxWJCL+coSlfWDOByH9u9n3UZSmscBoKhgGxCcbZO+ykZyZRLN2GXW2kb7VKpVk7qXiVipLp4HWDFLeQDSp6WWADMXfiCy6O8KWpip+dpyOSH0b8IFIjnpR1fXgi17XQ0q55fkqc1t4Bpn1MsSPh7hrgi6WUpoqCmfmKeJs6alSWo7jkYV3B1rkK67JwJ/GbmTexZD2IcLaI6o5xwCYUfj/CRta+qdNd0z/KsKnyUzwhWtt3z84sOODMcSwH1CcX8KHz87muv53clmvm3jsguf566fVQbdNSGvHhJ8e5ZgzJJpeRRrik/xcfNsern8qjDu1sQ0RNwYt9V1IDF2rUBcB+4vUGYi4SyNsq4HjTHCcgYi/GZHxEzhPDxQnRiI5AXl/29GVr0jv7xHtGv4/Qtchb48VoQnOuu7UOp000shF5o0Bs0Ksr5own5mDzBujlL0bAXdRKfl7CzCMqoVEuM5FJPyPyG3phrJwEHaElhI1yZHGXg7p92ed19t3L+PpWRto06m2GF45suSlQI1GrbHKv0HmnIDMG4ksuAqZezYy53RVn+LfHLCYCHZNKhkBWfJyVHOOIQBLe8Iv6TroHZr4oCqVGRYHgK1HLKITw38aW/7ezq2DH6AotxgZ8K/ZsW4X3838hbNvGMpVz42ts0iktDiIez7+mLwtr7Np8WtY7ZJufUojF9tWU3cWemZ0iaDExxCOoZV1D9J5tpLeL/+SukW7JiLpCYTzrBpDmIX3VnZDVMiAVJxS1anpIFyI5JerakJ8K9WT9T4UGWxKmAbk7rGQ0SpQS6R3C0S/6h+N8pQJfpmTRL+hhzHy9iBh97IPQvgVgTL1LILSDyD+ynofe9n8Fbz36Mes+GEVAEnpCQy7agjn3nYKTu2rQIoiXLogAOkGswD0utGo4Ju/gyx+jBaZ0P/kdiz+NqEyajnm1j1YrTK0J1vpW8i4ixEBWQBZ9iWyMEi3mbEBmT9W+W6F1XYxVErQLAmqih5DXQjX+UhvKIsNUK3rwdOVDT6m4yTlpxYSOjhOadJjNgT/Gq+rpkCsGDmG6vD7/IzpfC25u/IxjeCL4a1Tr2bI2OODvqek1W8Ez9dEjpZoiPgbEPFXBfb1I7OPrRYRCLZLc0TGd3XaM6U0kWUfQMlrYO5C6c60g/gb0ZxDa25r5iOzjgZ8zH0/hbeeaEFRgc6pF+Zy+kW5tGjvRdMklsTzEPFXVy5UAGbeJQGp/wNfQFFK+OCVDKY+3oL+J/m54ZVzSO0wAgquAe/PFOXbKMwVJKcbJCRHJm6fTO1DcrvrGDRqQFBfPTPn9Ahqs4DWXD1lm8Vg6YxwjUTY+obdZe7b3/P0pa+gaVqNa1LTBF0OMXnqw5UBh/pobtsCkbmsSrMnDGT5XGTBtZX/Li7QuXNUR9avcBGf5OfDlX9H8ILTEPE3IeKvQEqfuuZCtpJryvRTlhCJrImM72tckzGEhpQGsuAa8HxH3etDgP3kQNFx0yVypFmKzBkSuI/V/i4FYEGkf6YKzRuJ/eJ1FUMM/9+w8LMlZG/PDUlyhBB8+MznIW1GhBCI5GcR8deBCPfD05WsvmtktX0tiITQ7tMAIvHO4BoU5h5wT60iOUhVgFp4E9Jdy5LFuxzw8dnUNJ69qS12l8HpF+XicJlMeqAlZ3XpxfDuvdiyrmuNBUUauVWtr41CPYot7UOpcHCu2lfdLCONU1KkKc8qKVi8wM6NJ/5KcZ6PTdvu4f7xZ3Jerx5cdmx3zu11EA9deQZb90yAhAdAr+U0raUiEh/mnLs+4IQLjwltHhyNIrO5R1kf+P+G8i+QeRdgFob2cyrMKWLC5a8pYeha16RpStb/CR9NzCA6kqOD7bioSA6ALH6lxr8Tkg0mfL6BOydu5ahTCqMwvNWQFaTd83N4vRzMgB1LpGvLBlpqpAPHEIAQOiL5JYi7JmDjUfFGsnrIaqI27xrH1FyI1HcUqQfUb1VJQiCciJSJTUJyGotY6iqG/yyWf/c3ulXH8AV/qpRSsnXVDorzSkhMSwi6jSoQvRbiLkd6voeiRwIy9tUl8gM1B8UTIO7iyh9+hWaJLH40oH1RMWgaOE5G+laDsVNpUVhaI/0bkCVToXwWVYtExaJnBMZ6AvS2CEeFWJuJu0hZHtz7xmaOPq0I0wBTgsUCe7dbefzqdky+93ce+3pM1Ryiqi/RwdIb/Mup68Stg95JLXiRuoQqoKUj0r9Clr4Pvr9UfYl9MBIdih8MuZtpwgevZFamWUy/SfaOXF6/7V2+/2Ahfq+/0sxTmvDrl9tZtmAmE356mI4Hnw/+leDfDloS2I6MrmPK0k1ZikTUK6n5/VA2DaydwXVBnS3nvv0DRgjSrc5TMPvtNC64aS/hXXcUQYxWF8V0vwtG3Zo0q00y6MwCBp1ZEM0ole3pUds9hIWu6syEI/KmMVRCCCsi4Xpk/JXg34Rq+e9QR9OoSY9p6QAZc1Wq0fMjSD/CejA4zzpg0o6x1FUM/1m8cPUk5kyejxEhk/FR1hSS0qO7XqQ0FeEpfgaMDdSto9HUU4792Gr7+MD7GxjZSP8GKH0PKEM9h5hqf9tAFR3AIPyTsAbW3mhpH6qxjSy+ev4MmrXxcsjAEmoHKAw/eD0a157ahae/PJLUpDkq1aK1BHNzhLMVkHAvQtiQ7teUkjSAcCpdlvgbQRYhc8+NjuzoHdEyvq7zspQeZO7Z4N9MbWLh90N+lpWrTuxKcS2PLU3XAIlp1L3FabpGl8M68vKixyPPKwik5ycl8ldvKHsLkf5tnafrZy59lfnTfsDwh490fPj3ShJTghGsgG6OSEIkP4OwHxdxNrL0PWRRaBIZPTRExo+q9qx8nkqhRILzfCibEeQNHbQkRNqsWNoqhkrEUlcxxNAAHHT4+rAkRwho2alZyGhO8H00hJkdIDlQM8phAH5kwfVIs7jaPlaE/Rilb1E6GUVyQBUBB4iO92eUq3GkcL9q560cX0tBt9g57Ni6JAdAt4DVbjLiyixyN88K5No9YG6J4mx1hPM0hOs8RPp8RPo3iLTZiIxf0RLvQWjxCL0lIv1LojOvDB4dEcKOSHkXrEcEXtEqi6o3/e3klrM71SE5oNI/wUhOxXtrl2xg88ptUcwrCGxHg/PcihnWY0eponRGXUFJR5w98lhCYneEuAZsx0Di05BwJ7JkEmbW0Zg5w5RyrVlUdyZmsRLvawrEXYXQM9Xf7ceqGpyQCNSUJdyPSHxIaQNVf892tFKgjpGcGJoIsdRVDP9JSDOPo0+cw6T0LhTlB9HEQaWuht9Uf0l26X6buqmcyndBlkHZpxBXs21blkwIs1994QvMZRpd++Tj94ElREbGYoHBwwsozK1ORqrPIficRPxNCC1F/V1oYKnbuiqNPYo82U4A77yg4yhoYDsy5NkIPQ2R9g7Stxa8v/HzBz8z69XdrP7dCSiy1u/EIlKb+cjPsrJofiLe8sjPcTvW7aZDr/Bmr0HnIwQkPgLW3krK39gaeCMxUGQbBSGthYFnH8lnr9SNaFVA0yWHHVuM3RniM0y4DYofUdHBiuiOmYUsfgrc70DadIReTeSufA4QzM+rHhBJiPirwTW26iVhh4TbkEX3Bduhcq7C96tKFyZPQuBXXWKWjvtMfTqG/y5iRCeG/yY832Oz+3jonc38b2Qnyt1apdqxpktMQ3DSefmcfmldNdxwMM2yatGcUNCQvj8RVBEd6d8WkNFvAmjNQCRjetdAydO0bG9EqOkAu0OS2SpUeKu2g2Gq8sYJUmdSAeldjix+BnyLo5y0CZaeEbcS1m5g7UZa5yNZ/btaSE8elcsV9+8iPsnENJWqsbtY442HWjLnvfBu2HGJzijnF2QuQoBrFDhHVtY0Se8yKIyQthFxyLzLkeZ25Q3lPB3huoQ+x/ei+5GdWbdsE2bt9JWQSAmjrs+q8fKOjTa+npHOzi0tcSY8y7GnruaIE0DXq+8vFeHJvx6RXuVKLo3dqEhbfeUDNHCNVVFI2xFB6z8q2phl8bOBwuOKXdPBdhwU3o2s9rq09EQkPRwjOQcgpJEDxiaVkrb0PCBMOuuLGNGJ4b8JU5kadutTxuQf1vDFO+n88FkSZaU6HXuUMWxsLv1OKkITIVSOQ8H9epQb1rpZyJL6HSckBMJ1EZi7A7YNfmz2Kv2cUAgX8QETkl5SNzih5P7DFexK75KA/k49O7bcE5Gu6NyOex3dnaPO6EucfS63PLejsti4gtDFJZjc+PQOTJNaFgZVSEiNp9cxjVfeFUKAHjiG43hkcQswswhZqCzdIDejonuFUDoTWTYLkfI2j3xxJ/cOe4LVi9ajW9RJmQZY7ZJbJmynd78qBenpz2fy9lMtAsTch6bn8u377encu5THpm8iKa368Q3w/4X0rVCFooDQUpD1Mn9EdfCkTUdYOlfaX5je5SB0hG0A2AZURkCFaxQ4h4PnJ1Vsr7dAeleCe0Ldcf1rkLkXQtoHTa4oHUPDII09yKJHwDOfyt+y1gzirw64kjedfcW+RqwYOYb/JKRnoRIuCwuByFhQM9wfbkyzFJk9IKrWY5H0XGXXldq3AJl1FPVzHa4zKtgGIlJeU+mK0mlEQzZCOXjXGDntS4S1SxRjSWTOyardvSGt6YmPIMy9SCNXdfE4zwxZq+EtK8Wzoy+ueH/Q+UsJhXk6Fxx6EIa/7gZXPTeW4TeeVv85RoD0rVKqyTVSWLUNNmtDAy0NkfE9YGHF99+x8P2HKC8TtO9Wzgnn5BOfVLX/tx8n89R17YKPpEt69nXz7Ccb6xxDJNxeqa4tjWyl5VSfa851MVri3UjfCmT+VYEi84rnZT9YuiBSXg/6m5FmXkDTKVQESQfbMWip0T4sxLCvII1sZO7wEPo4BNzOr6274z7EfjH1jCGG/1ew9VfmgUYoHyddPZ1GSXIA8C2JTl9FJIHj5JovaclI+xDwfEPDyI4F9DYBFVJT1QAFOa/apCYakoOWCZaOETYKwLesql6lISi6R7WTI5CYUPI80nkBCLs6J1msupZco7DonbAkhE67CAHJaQaHHlPMsh+T0TSBYZhomuDCe0Zw9g1DQ+7bGAhrT0j/Eln6HpTNDtSetAffWqoKzWvDVKTBswDhGMIhxw+m98GT1edZ63uUEma80AwhJFLW/fJMQ7ByUTxrlzvp1qf28aq2F3oGMm5cPaKQAhF/NdLYqSJ2snrRfMVfNyHzRkP6VwhRKy1Y9hXhr20DvD8gzTxETD/nH4V0TwxJcgBkyUvgPOdfk2qMEZ0Y/pMQQoOkp5F5Y1E/5uo/aB1EIiLx/voNKsuj2y5ufPC6hsTbkbmLlGx/jflUtA0ngyygqmam+p9+MLYoouCeoiwIgqA2qREiDvQuYPxFyEXIOSL6vLzRwC6mmoPU/GfZe9SoEzK2qYiVFl1Xzv9e8zP389Hk7c4nvVUqgy84mpRmyU0wz9AQejNEws2QcDMA0r9ZKciGhUWllgIO5iLxXmTuKFTBcNVnkrXTzvYN4fVldItk0bzEWkTHBFu/mvOMvxmJFdxvELEwOfFxhJaCWTQpcK2HsL8wdkLZF+A6t8Y70swick2QBCM7JhT4D0JKH5R9THhSKqDsE5XG+hcgRnRi+M9C2PpC2gfKPNDzLWohtYJjGCLhuvpFcwAskVM7AMJ+dPDX9ZaQ9rFq+fXMpXIhsRyMSLgBbIdB2ZfI8nng3wDm9sCetd2ft6nzCHRehYYLkT4bhFOl8fxrCdph5Z6I6d+ISHo8sgBYdUXWJoWs+3dzd1R7JmSewLm3DIvuKFKC91ekdwkgELYjwdavCeoRohAhRAJVBFhYe6jrs/iJgEq1gs8XhXeVkPi81SvQdbAeqqJN1TcTGiLhBmTcJeD5ThWeen8D72JU9EkHSy9IvAfNdojaqfxLIi2CsnwOwnUu0nSr61HYQEuLsJ/aV20Xwz8Gs6hatC4UNKSxs17CCv8kYkQnhv80hLUnIuVVpFmiCkO11Loh92jHsnREWo8IpBvUDX3jSgcb/nJhsZkcdmwpKS261llsKiCliSz9MOBVU+1pWeaBcKh5uUaA84xArUMoVESoIrWqlyFLJiAS70WkzUKWfQxFD1OXIEnwzEPm50LqtPAy8vYBqmC5yYqrwyHKGqCyaZiyGJFwK0IPvohKKZGeBVD0UIBAqQiWdL+sIl4pExGW+rehV0JvBXrbQO1SqO/EqCEkCarLTKS+qdr0jT1I72IyWz6LKyGZ0uLQUTbDp9G5tyq4Bwl6G0Ty8yG3F1qiqocCoK4QYpm7nNkvfMbs1+by6pxs4sKWSEgwCzCLHoTSj4FApFNrTvhrUguki9PDDf6vgt/n59fPl7Ll7+044hwMOLMvrTof4OkeLZ7whqsAErTk/TOfJkCM6MQQAwQiFY2XKxdJjyJzR7JjQzlPXdeKtcurvIY0XTJk7BFc+5IXm6Nu6koVEE+t8zrGDlUTkfY+wnqQiubIgggz0QKprkJC37AklH+F9K9GpH4QiASFIg8m+JaC9ycIo7grhAPir1VRiJDQA8ep+DNak8pQiFTo64fyT5G+RZD2UZ36D1k+X823Rtqt2mdmqLoTmTYb4V+papBEAtgHIbToxCSFEBB3JbIolL+ZDtZeYO0TfH+9OVLLgIJrsNklp12Uy8evZVRKItTYVhMkpsKA09LA2gXhPBOcZzSYwLsL3dwy6H42/bUNaUq2b3DQ5ZDSoAKUledibIPS1dT4HM29hCU5WBAJtzRojgcils1fweOjX6QgqxDdoiNNk9dve4fjzhvArVOvxuGy/9NTDAoh7Ej7yYGocmh3eeGILkp6ICBGdGKIoQkhLO3J8bzJzWc/RHF+zVoE0xB8/ebv5Gc9x0Of3lEjHSKNPVD6ZohRK7yynkekvkF0xcoCXOereony2WH2McC/EcpmQumsCGPryLLPwXqoSqXIMrB0RVh71dzMdQlCelRKED9qEavV6iwS1cJuG6iMNQuviuKcQiDuNnC/BIQrBDfA2I0seQWReG/lq7LsC2ThzREOYCj/spwTkDVqn2zIuPHK1NXciyydDuXfAl6w9kG4RqsiZFmq9GOc50D5F+BdWPcQwgFJz4VPkfmWVVppjL55Lyt+jWPdny6kCRVFxrou0a069310H/ZWkXWJosEbd0xj88rtZLTwcM6V2XToURaG5AAYqmi8Dqmp9m/hqlm4r3dAJD2qiPwBBin9aq4iLupatXW/b+Tu0x6r9C4z/FXX/08f/Yq3zMtDn92xT+bbFBDxV6sIZ6VfX413lf/ev0gGIEZ0YoihifHx84spzpfB1ZZNyW+zf+fvX9bQ6+hqGi7lXxA+rG+A90dM36rAAuEkdAeP2l7YByBsR2AW+AIquKGiHhJZOjNkAXPNOSxDZg2geuGqEnt7Uon5EYhexF8FrvORZV9B6btg1Gp1lkVqwddbgWscWLqqSFVDWtLL5xCe5FSbf9lHyIQ7lD+X9CCLHoj+OHU+Hy+4X0H6twRqvLxUzt/YgSz/vGpT4QJr3+AkB9R3WvIcJAfRmKlANRsHh8vk6Y828vlb6cx+M429O+zYHSbHnZXPudf3oN2R9awvCwF3USlz3/6BNp1Vu7or3kAPuWpUXL8uwn8fOjjPQ9j6q89Ubw/WQ5pEl0WaeVD6PrLss8DYHZWej+PUegvdSf82ZMlrUP456rt1Il3DEXFXIPTwQqLvPfIxpimRZt3fs2lKfp29lHW/b6Tr4Z3qNaf9BWHtBqlvIQtuAXMX6mEl0PjgHI5IfOCfnWA9ESM6McTQxPjmre8xw7hQ6xaNee/8UIPoSCOXyCkYCblnRTEDHSyd1MIKgShABAJh7FE1FOaOMBsJMHfWfdm/Fpl3AaTNQliqtF2ElozUEuuSnOoo+xDhOB2SnlRjyJodRlHBWBH9trJMqRjrzcGzIApyFwU8XwZ5sdbnLUvB+2O4iUH5l0j/jTU+wxpbyJq1U3an5Nyrsjn3quxKRWiFHcisHyDpMYTzjGjPIii2rd6Jz+Plzle3RSA5qBok1zgoDmb9UB0mGLsQjsENmpOUZaoo3/sTSCPglH0OyALV2m7mU/n5m3nIwsUqqpn8cnTO9ID0Ba5pWUrV9VimxB3Lv4bUDxCWNkH3LS/18NvspZhBSE4FdIvO9zN/OWCJDoCwHQ4ZC8D7K/jXKWVk+/FVLvX/IsRMPWOIoQlhmiYlBe6w2xh+k/yswhqvqSfEBkQzgkIEIiSrAcjdo0V0aEdLQbhGEv6WECbaJEuRJRNrbi1NVdwb/sDI0hkI60GItI8DOkAVT9774jlMgAjUTRm7qh3rQICmnL99K9Sf3j/UZ1iBslmh96zztXmRhbchPb82akZWm4WefUvp0KM8LMkxTQ1SZwSuoUi1JxpoDRNslb41yOwTVK1T+TeqSL7kWWT2caqOzSyg5u8o8HfP93Wuz5DHkBJZeHstklMBA8wCZNG9wXYFoKykPCzJqUBJQTRRyH8WQmgI+0BE3CUI16h/JcmBGNGJIYYmhaZpJGeGv4nrFp30VrW6fxyn07Cfo6B6S7KCH8rnIHPPwl/4Em/cXxR+kTKEeiJ2XRgQBmzI4m9A+WykrKbF4vkhiqJpsyrio3dCuMZC4hOQ9CJkLgHLwdTPHTwcNKUcXVFALJJpnBL1PoD7dWTuCGTBNci8kcicE1WxtPtd8H5fz8GEEn5rBDr0bkvvo2RECxFNMxH+9Sr95BhG+GvIQDjqL9YozRIlg2DmB16pXsjuC2+7gYTSd2ten6HgXxl4SAhT1+ZdqPzpgiAxNR5nQnidI2matOz07yQN/0bEiE4MMTQxhl52Ipoe+qdl+A1OufT4Gq8JPQ0Rf0MDjiZR9QO1j6du0lrZSxjeElb8Fhc0quP3Q0GOTn7x6QgtHpE6PbBQNSSa4qvRVi7LPoxuN5GA9PyKzBmCzDsXim6DwushZwjYDqVxHVk1DlRDtl7aj6bpSFRTwKSGASaAsRNZcDWy+OGGjef9TUknNBC6RafP4EMjq2eD0soBRPxlKPId7Degg/UwsA2o/2TKPwuQnGAEJIprRBZGJ2jpWxvdfPzBzXt1i86pl54Q9h6AEJx08aDojhNDoxEjOjHE0MQ456bTyWidhm6p+/MSAk66+Ljgufm4y1WRX4ME04I/cpumYMRV2dx3UQd++iK58sm8wuFuwwoXN53Zmd2bFQsSWjJa8lOQ+EgD5mBXbdcVMLaH3rQ69E7I/EvrWkeYWVD6NthPCrzQiNuVSEQkv4qwHVb1mvuNho+3zxCmU6nBQ9bTmLYWDhsahfqtSAJrb/VXS0dE6lugVQgbWqj87mwDlBdWOC2mEJDlC+q9T4MgwkdjqrYLnaK74O7hZLZNr0t2AoTxsidGk9YipYETjKG+iJl6xhDDPkDOrjxeuOp1Fn2xjIqfmDPewfAbTuOiB85FD9OfK6UP6V2m2r7NLHC/2uj5nNm5F+WlOhmtvBx6TDEWi0S3SPoOKqZTr3KSM5thTRqGcJ2P0JtjFk8IEIFIxT0V0ME5Ai2pKvJg5l2sChkjQUtXBcKhapREEiS/DvmXEF13VfV9EyD+ZoRrBKLawiTNkkD3WJS2HVhQpCNYNMGK+pwaeiuNVITeCIgkROavCNG4eiez4BZk2ZcIEXyeIv5mRPyVNV6T0q/Sl/5VgE0Vslq7NnwOeReBd1GD9pUS3MVOFi+ewLEjjg6qY1W5rZkfEOQMoywu4gOfa2iyk59VyOQ7prFgxs/4vep31KpLCy6671xOuPCYBp3HfxmNWb9jRCeGGPYhsrbnsOnPrVjtFnoO6IYzLkLuXkoom44seT1qi4NocHa3XtWUdCXXPb6D0y/Ow+8HS+UaqIFwIlLeAu9PyJJXiK6GJeANlv5JDadx0z0NiiMVI0eJuGvB/XL99hEJiMyFQRcj6V2CzLswmkHAea7SJCp6HHyLq97SmiHibwS9JTL/CtTCGMXnZT9BtZnLMkBQUNCd5OTV0Z1TvaBB3OVoCZF0giJDmqXIgmsCVhQVqrmBP52jEIkPNChKUx+YRU9C6Vs0pK5KmjD18RZ88EomGW3SeGr+/bTuElqh2Cx6FErfIRR5FfE3IeKj034qKXCzZ3MWdpeN1l1bIoRA+jcgy74As0BZzTjPROiZ9T6v/xJiRCdKxIhODAc6zKIngqsjNxiCgrxkRvVuU+l0ffKoXG55LlQbuaZC9yI1Qqt5NVj7IZIeqdMWbRr5kN0vxE7VjhcxmiGgUqm1Hrcrx5loyU8HfStqohN/I1o140Lp31qljGw9uFKbRRo7kaUzoHx+wPDSHyiO1VHn6AdsiKSHEM6zVVGsmc/HL/zMz+9P4bnPgtd7NBwaWLojUt9DaHGRN48CygdsMbKiVkZviXCOUJ5c+wHSvxWZczJhrwEtVbWUS4EQspLIz/8omWdvbItpCjRdI6N1Gm+ufQGrLXi7uZQ+ZOFdqi6oRmG1Ac6LEIl3Nyz9Jr2BcT8PjCuouP5F/C2I+PH1HvO/gsas3zEdnRhiOEAgfWuiJDkW1MJph/hrwf06SDfBCYMkqc11nHG1h89f/QYhJCOuzME0QAuaPTNVW62MIkXkvAARdzHC0iHo25qegmntD77fwgwSTcpGBuqW6vdMJhwnhX7T0pPIoosg7CfW+HdZWSbrl5WAhM6HlhOXpEiE0FshEm6FhFurZu1bpTRXpBuhd1A2DIG2aiFs/DJ7K5NunYkQLvbusJDZyh9d0W/NGaJITU/w/xV4KQlc5yPiLm8ykqPmLJC2I1WEzPsTUhpg7EJaujQ6NRbV8S3tIPEBZNH91PRiCpBl57kQfyfC8zlblr4KsojtG+x8NS2NZT/EU1EgYxome7dm8/OsxRw/amCIc7Uikp9G+sYp8UEzB/TmCOfZCEvHBp+DLHoooFQOtSNTsuRp5bXnOqfB48cQHDGiE0MMBwhk2QeEN9MTIFIQcReDlgmOIQgtHmntg8y/DEV+at38HaejxV/ANS8Kho4/gSVzfqFd1wcbMcvAuHFXqLqMCCuzSLgembeY4IRGR2muRCJVLoi/HMo+ILqaIR20ZmAPLUgntDika5Qqdg41N2vfypoSb7mXqXdN54tJ8/CUqRZlq8PKqZcOZvxTFwX1LRLWniENXAGmP/oxQhNIE3ZtttOsdbT1UDWOAknPozmHBIxpy0FL3ifEQxrZKn3lW05FNELiV0KTKa8gAsXI+xLCdT7oHZDuKeD9GTDB0kP9JhxnIoTAdIziqsGfYpqhU1OarrHoq99DEp3K41m7N5nVgTT2QNlHhCPssuQlcJ69z9OA/zXEiE4MMRwo8G8homOwLKxTGyDs/SD9C2Tpu8oOQZaDpRvCNRq/fiKfTfiST176iqytOQD8/GFnRl6TxYBTG6AKbOuHSLgHYe0S1ebC1heSX0AW3hGIElUr6rX0Bv/yyIPYByC0Fkj7UPDMJnxkR6iFPnVyxMVeJNyM9K8PLJgVBLPC7bstIvk5AAzD4P6znuL3+StqSPr7yn18MWkem1Zs5an594VMgwRDYU4R637fBEBGKy+HDAwvMhkaEnx/gHNIkxjTSukPdMsJ0FtXfoZSepWGjX9TYMvqZp1ZyLwxkDYbYWndqONXzsPIgrKP1fcjHAj7SWA/FiF0hL0/wt4/UOQv65AC0zAjCvZJKfF5GkIsG4FK76gwMHeBfw2EIcgx1B8xohNDDAcKtCQi1qyI4KkIYWmHSLwHEu+pfM3wGzw0/GkWfVnV+QWwbrmLB8d14LJ7d3HuVdn1mKBFEYAoSU7l3BxDwHZ0wOJggyp4dpyELJsVBdERgEDmnArGplrvVbifo2qKLK0RjlPBeQ5CS4o8L2GHlDfAMx9Z+r5a4LU0hPMscJyB0FwALPx0CUvn/hl0DNMwWfnzGr6fuZCTxoR2da8Nn6eqo2fAKYWN6CKXUDodGX9tgOg0cBTpB/dkZOnbYOaqF7UMiLsUXGOhfB7414fY2wRZjix9G5F4d4PnUDmX0g+RRfdR9aEIZNlHSu07ZWpl0a6KJtaNKFqsFtr2aMX2NTsJV4Ha5bCGp6AahEDxecQvO5q0cQz1Qiw+FkMMBwiE4zTC16zoUA/vorlvf89vX/xO7X4D01SLw+RHWrBjY+g22+CTjD5qUWM3LQ7hOg8t8S60hJuU47lnSRR7SvDMA2Nz7RHVH65LEBkL0Zr9ipb2ISLu0qhITuUoQkc4hqClTkXLmIeWNlNJ3QdIDsBXk78NK/4mNMGXb8yP+pgAKc2SSUpXmkNOlxlReTg8ysFXD7+vWpDSRBbchCyZUEVyAMxsZPGTyMI7kGVfEn65MKDs8zDvRzkXzy/IorvVeJiB/wLRI/9GZP5lNW0xQuDs608LTXKEEvWrLdq5z2HpROSaNE2ZnMbQpIgRnRhiOFBgHwSWgwgun6+6oYRrbNTDffbK1wgtdA2NpsFX0zJCvl8XfoQ9+qhFNONFj2BCehL8qxB6lcCi9G9Cln2lbBPM4qaYJHs2Z4U1aZWmZM/mrHqNqVt0zrj6FIQm2LbegaVh/LEawszPuxwz/0bMvUdi7j0CM/9apLcayfTMA883hIw0lH8O/hVhj6EO1ND0W7UhSl4j9LJkqLROKAf4ajj1ssEcO6I/QI3fgG7R0DSN/71zHckZ0RPiJoHt/9q77/io6uzx/6/3nWRSJoUkdDGAgAIK0hQFBVkRsKD83B9YUEFdXBQUF6XIigUbIlZ0QdSPoGJfK+oiIsUOSllRqoK4IL2kkWQyc75/3MmYIZPJpMAkk/N8PHjI3Hvn3pNLnHvmXc77bHvsWJk/nwPi+mIc9Y9lVHWCJjpK1RDGxGDS/w+cp/u2WPiTHqsxpNwL7v8i+YsRKb/Q3W8//R4wpuRIXo9h66bjwHGCnWDFXxLibA5wtLI/rKtLbEeq9hHkW+LAsx0p2oZ339XI3gHIoVvtZRN298CbPc3ulimHiMdOkoo2l1oPqV6j1HIHXac1qvhD87IJl3BKz7Ys/zyVA3ti8FZ62a2YMsd0SN5ryP7L7ERGDtrLIBQsQvYPtQf0ApL3OuX+O3jLS+QMOIKvuh4u8eaB+ztCJ1QxSMGikOfxeDzs/m0vw++/nH/M/jstT8nEWAZnfCxnXdqdp75+gN5DKrEERRUZ48CkTsf+f/rILzMOe8ZVNXT9qdJ0jI5SNYix0jDpcxH3z1CwDHAjpED+O3Do9j+/c5skcI0E14gyH8LOBCdF7rKnTxvLkJB6KlaDcf5tktsWyZ6G/eDz4B8z5DjON8C3+r4bGddQJP/dco4qv86OHJwA7u+DHFcAuS8gnt2YetODv1e8kDfXfugXP8xNKpJ4FSbpRoxxct7VvVn7RdkF/YwxFRqfUywuIY6pC+7kg38t4IWHXuHWh1chQsgFWEtz+MYTpZfaI+4NSNY9lK7obP9dsh+G2K52Be5qqMxsXFdW8QwFYRwjIMGP83q9vPPER/z78fns3b4fgPQmaVw65kL+OvYiYmIiv1K9iesOGW/axTgLFmH/28TZM62SRtXa1cFrOi0YqFQNJkWbkX1/9X24B3kYuW7ESv5H0Pc++reZLHxpCZ6ish9iE166mb5X9Trimlvtqe7ujWAS7Xo08f0xpoLjecIgOf9Ccp4gMKHxDdh09obCpWGcpfwBnibjHXtcUMlriyBZd0LQxUeNvdJ52mwK8z2MOm0iv2/YUaoLy4qxaJTZgJkrp+FKSQxynvB5Dv+AOfwvKPwiyN4jyw74ktuY9pj0l/5ckb0E76G7fVPyy2oqckD8BeBeD56yBhqHw4LYLpj0OVX6HRHxInvOBm+oAfIGk/xPjOuaI94rTBv+NJ+9sqzUr4Ix0GtwDya9OgbLqjmdGHY5gByw0kIuJaFsWhk5TJroqNrGe2C075tfWQ8rC9NgadBvglt/+p0bu47HU+Qp1YVlxVg0PL4+L/z0eMh1f44FyV+M5P4fuFcAArGdMa5rwXkGsrsn9ursVeGAxCuxUiYHXrdwObL/qpDvNKnTMAmDOLD7EFOvfoqVC/9rlzPCXj+pY6/23DHvFuofV5mFWIMTbxZ4sxC8GO8uMC7EaoI5/LY9+8h7ABxNMImX+2quBF9WxLv3whAzpYpVdZ0uF7iGYpJGlxlHRUjOTF/iGyweAzgxDb/yF14stuI/q5h0wYMhz33vu+PpcclpVY5RRYZWRlYqCok3Cwo+o9xuhfwPwfW3UptbnHw8U96fwH1DHuNwzmH/QqKeIg9NT2jEg5/8s9wkR8Rrj+nIe8Ne+sBKwyRcAvGDqq3qronvg4nvE7wuStLf7SJqVeIFT+kxJpL3BqELNFpI3quYhEGkNUzl4QWT2bZ+O2sWr0UEOpzdlpYdqjYuJRhjpYCV4muzybS3ASSNqOASAeF01YRYuDIcGW9hxbau2jlKcl0HBV/6uiKDJDspU0olOQDzn12II8Yqs/XSclh8OGuBJjp1lCY6StVU3gOEMx1VPLuDVBOxnda/E29sf5bPX/2S9cs3E+uM4fQLunDa+Z1CrqAOviJxB2/xFTrzJQSebYh7DeT+H6TPwzgaV/znKkPQuiiu0XbrSc6z2C07lVnp2wJHkNllRb8QukCj11fE8U+ZbY8js+1xFbx+hMT1gqKNVG78TRj1XnAGLOJaHYyJQ1zXwsEfglzfQO5MJP4cjJUWsOe3n/8XsovW6/Gy7eft1Rqrqj000VGqprLSKP/B7i131eOEpAQuvOE8LrwhxNpPQdgDJhf7XhUnBL6Hj2cHcvAWTMabFTpnRRljIOlmSBzmWzDzADiaIYfusMc3hMWDSbi09GYrlXIf6FUowhdpJvEKJHcOdqtNRbqmjD0Tz/MbZZcAMOA8E0xCVcMMIFIAh+4geLxe8PyOZD+BSQ1cxsSVWv74qHCOUdGp5ozMUkoFMFYKxPWl3C6I+IHVfm2RAsh7mbIfkB5wr0bcPwZ/vzcbyX0e757+eHd1xbtnAJL7gj0AsxKMlYJJvBTjut5XafkMwuuaMRA/sNRAZAATfxGhEwCrnCn3NZtxHIdJ+xfgpGIf9QK4Mf4xTcHaCwUKlyL7r0C8B6sYaQn5C+0p8KF+7w6/g3gDa/b0ubxnyJpRxjL85cqzqi9OVatooqNUDWaSbwUT4kHluuHoTEkt2hhGi4kFhctLbRXPXmTfpUj2I3ZFY8kGzxYkexqy76+Id3+VwzOuawnd7QTgtCsnp04NvjvhIl/tl2AJkwNMCibxzynTv6zZyicvLGLhy0vZ98eBSkZ+bJm4XpgGn2GSRtlTyWO7gKkXzhsxiVdg6j1pLyBbFvca5MBNpapvV5YUbaT8joYC8P4RsGXAdX8hrVG9oBWsLYdFav0Uzv/budUSo6p9NNFRqgYzMa0x6a9BzElH7EjCJN2OSQo+tbzqwn1wlT5ODk0Cz/+O2OerZOzZhhy6s9R7Kso4T8MkT/K9Kpmo+Iosum7CNPwGK2UipoxlK4xJwKS/DDHFq1M78D9kHU0x6a9gHA3Y8ctObj7jDkZ2HsdjI2YxbdjTXJk5kkeue4b8vHBqv9hEBCn4Dsl9Ccl7A/HsquBPXTnG0QiTdDNWxmtYGa9D4hBCt4ZZvpZE7LXDHE0JWa3Y/T24g68FVuFYTQLhjSkKnOGVVM/Fo0vupWkrO+l3xDhw+OrmNG7RgOmL7yG1vs60rat0erlStYS4f7ZXjzYuiDuzWqbzlnktyUd2n1luWX+T/hbGeeqf7yvahuw9j/JWGDcNFlfLQFZx/4TkvuKbpRMD8X0wCVdgYo4P/xwi4F4JhV8j4sU4O4PzLIyx2PfHAUZ2HkfWvuzSNXQsQ5e+HXnwk3+WWzlZ3D8iB8f6xr0UjwuyIOFSTMrdx7SOinh2IHsGYA/uPjKpsIA4TIP/YBxNEO8BZHf3cs4YA65rsZLHlXNcGLG5NyH7LgxxhIGYNpiMD4Pec6/Xy8rPfmTNkp9AhA692tOt/6k1qn6OqhydXq5UHWBi25dZ6r/ar2XikcQrIfcFgn/DdkBMe98yDiW4/0v5rUFiH1cNiY6JPRlT76GqncMYcHYFZ9dSo1HeeeKjoEkOgNcrfP/pGlYvXkvnv3Qo8/xS9Ktdr8df0bf4/njh8L8RbzYmrapT6MNnHE0h7Tnk4N99K2qX3JmASXsW42jiC7X8pUbs48quwF2h2GLbIHHn+gbBB/u9E1/NnuCJpWVZdOt3Kt36nRp0v6qbNM1VSgVlksaAs3hNoOKPCt8UcKsRJu2p0g8cE26Z/ciX4w/HgjmLQy7oaTksFr4cunqz5MwECdZ6Avbq7AsQ99qqBVryjJ69iPtnxLOzzGNMXHdMg2WY5Dvsbqq4vpjkSXbxSf9aa4BVH0x5356LMDEnVk/wYK8H5ezpexXj+2N3SZrkOzHxA6rtWqpuqHUtOgUFBXTv3p01a9awatUqOnXqFOmQlIpKxjghbTbkL7AXfvQXDBwECf9/0GUHiD2N0EX4AGLsFpRaIHtf6BXQvR4vB3cdKnO/iBvyPyb0/XAghz8IOjOsIsS90R4AXriM4lYjie2GSb4d4+xS6nhjpYBrOMY1vMxzGhOLJF4Ouc8TPFEzQDzEX1Sl2APjckHa874FbD8GycY4WtjdfLqyt6qEWpfojB8/nqZNm7JmTfUMflNKlc2YGEi4EJMQatxEieMd9ZH4SyD/PYI/GH3jUoIsQlkTpTVJY9/2smeJOWIsGjQLsfyDHCas6sPeqs3iEvfPyP4rfC1HJboO3SvtbrO05zFxlVux27hGIgVfQtF6Av9NHYBg6k3DVHO9Ibs78dSA8V+q4kTyIe9NJO81e4KAlQwJgzCJ11Rrsc+arlZ1XX3yySd8+umnTJ8efCVipVTkmZS7wFlcat8R+F/nGZiUqs+6OlYu/FtfrBD1WTxFXvpf95eyT2Bc9p/yOKpWbVmy7vGNATqy5cgLeJBDk+zlPCrBWEmY9HnguhFMcUViA86zMemv2nWNVI0j3lxk31VI9gPg+RV7Wv5eyH0R2TsQcW+MdIjHTK1p0dm1axcjRozgvffeIzExvAqXBQUFFBT8Of0zKyvraIWnlPIxViKkzYGCJcjhd8Cz016EMuGvENcLE/Y4nsgbdMv5fPbKUnZu3VN6rI6Bv1xxFu26tynz/cY4kITBvuKLZXVfeYNXbg6TFP0C7tWhjgDvDij8FirbqmO5MMljkKSbQbLAxB/VWX8VId4DUPg94IGYUzAxzSIdUo0gOY9B0VpKTw7wgOQgB0dD/QXlzhiMBrUi0RERhg8fzsiRI+nWrRtbt24N630PPfQQ9957b/kHKqWqlTEOiD8XE1+7i7QlpyXxxJf389So5/nqveX+VeATkuIZdPP5DLv3snIfFMZ1A5L/H/DuIWiy4xqBicmsfJBF28I7zrMNqFyiU8wYK7yCg8eASAGS9SAcfps/uwcNEtcHksZjCr9ACr4APBDbCZN4WZ3prhFvLuS9Rdk1iTzg2epLfs88hpFFRkTr6EycOJGHH3445DHr1q3j008/5c0332Tp0qU4HA62bt1Ky5Ytyx2MHKxF5/jjj9c6OkqpCtu7fR+/rN5KjDOG9j1OIsEVfouGeHYiWfdBwSL8Dx8rA+MaCYnXVOlbtRT+YI/PKYdJfQKTcEGlr1OTiHiRAyOg8CuC1wLyFagsWbMIC5P6SNjjzWozcf+I7PtrOUc5MEm3YpL+fkxiqqqq1NGJaKKzZ88e9u3bF/KYE044gSFDhvDhh4EFojweDw6Hg6FDhzJ37tywrqcFA5VSkSSe3b6ij/EQe3KZVZsrdE7xIHt6g3d3iKPiMQ2/rvZBw5EiBcuQA3+rxDstTMY7dk2qKCbun5F9g8o5ysIkj8O4rj8WIVVZrU10wrVt27aA8TU7duygf//+vP3223Tv3p1mzcLrk9VERylVm4iIPSaGWHvs05H7vdkgh5H8pZD9zzLPY39zv6ka4vFA0QZ7NllMy4jNnvMeuBUKFlD+emdHckD8xVj1Qvck1HYibmRPL/CGbkgwGR9iYk8KeUxNEfWVkTMzA/uvk5LsbyWtWrUKO8lRSqnaQsQNeS8huS/5F7CU2G6YpBswcecgBV8jOf8Ct29RVZNqF9krXIE9XqW4lpEDXH+3Z0xVKR6Bw2/a1/QvqOlA4gdgku/AOEIs/Hk0eHdS8SQH+z0Fi6s7mhrHmFhw/Q3JLiuhc4Dz9FqT5FRVrUh0lFKqqsSbC/kfIAVL7XozsR19A1SbHP1re3bC4Q8Q7y6MVR/iB5Y5O0jEjRy4KaDwH2DXxDlwg69O0QdQcsEKOQSF30BMG0gYAt79GCsDEi6onlaX3FlIzuNHbPRA/n+QwpWQ8Q7GEaKeUHWzGlF+YcqyFFVzMDVU4rVQtBUOv8Gf98oCvBBzIqbekf+e0atWdF1VF+26UqpuEvc65MC14N1P4ABVg0l9EJPw/x2d64ogOU9B7kzfFt+DBrEHISffYc9kKvmevFftujiVYoHrBqzksZWO+Uji+QPZcw5lr2HmgMSrsFLK7jqrblKwBDlwQyXe6QBnd6z0OdUdUo0lhauRw29CUXFl84EQ95dqGR92LEV915VSSlWWeHN9SU7xUg0lFtUE5NBEcLTEODtV/8XzXoTcZ0psKDFDKG8uYpIwyWMC4819hT+TsYryQt5rSNItdlXr6nD43XLi8cDht5DkCdV3zfI4e9nrsBV+S9lTqIPxYBKHHa2oaiTj7HR0frdrkVpVGVkppSos/0NfS05Z3RwWkvt/1X5ZkUJ7TEsouS8g3pwS7xHw/ELlkpzikxwC78HKv//I03n+B6XWdT/yoDzfoOljwxgLkzYLEv5Kqe/rjuICjiULU/oedYnXQtw5Rz9AVaNoi45SKqpJwTLKbZEoWFL9Fy5cEcbDPx8KvwTfitzGGAQnUBD6beWQgmWQMLB6uidMahgHOcJb6qIaGROPSX0ASb4NCpeDFNnjrmIykcJVSO6L9jgn8RUMdA2DuHPrRCVgFUgTHaVUdDtyocugjsIAVckL7zjvEcfF9wtjxfNyZE1E8l6B9BcxVjiJStlMwkVI3gshjnBAXD+MiavSdSrLWOn+RNG/zdkZ4+wckXhUzaNdV0qp6BbbkdAfdRbEnlL91405IczjWgW8tAu4GYJ3F1lAHIHdMmUoWoccGhdeDCGY2JMhrh/B76GFXWG3atPXlTqaNNFRSkU1kziE0GNMvJjEa6r/ujGtILYLZScllj2eJLZj4Pti22PqPQPEY8ftwN/47mgBGW9BbDitFXaXnBRtqeRPUCKmeo9C/MX8mYD5fiarESZ9Dia2bZWvodTRotPLlVJRTw5/gBwaj/2QLu4S8k31ThiMSbn/qIzdkKLNyL7LfN1YJbuiHIATk/EKJrZD8Pd6cyD/fcS91j427hz/6u8iguS9Dtl3lxOBwaTchUkcWj0/j2eHXXBP8u2aPc6eYa9GL+6fkfxPQfIwMSdA/EVRsySFOvp0erlSSoVgEi4GR3PfANXFvoGrJ9tTjeMvOGoDVE1Ma8h4x66lk/8J9lggC+L6YpJuwcS2Kfu9VhIkDg3aFmWMgdjW4c3NkiqM9Tnyuo6mUMGkSbw5yMF/QOFS7ATPIHgg6yFIfbBOLLKpIktbdJRS6hgQby54D4BVr1paMsSbhezuARSGPM6kv4Vxnlrl61WWd//f7Jllperd2CmcSZuDiTvzmMelapeqPL91jI5SSh0DxnJhYppVW3eNsVIgYRBlf4w7IObkiCY54l7rW8oiWFE/AQyS80yQfUpVH+26UkqpWsokT0TcP0HRz74txQ30FljpmHpPHrVri4i9/tbhd8CzGxwN7KU0Yrv5uwIlfwGh16Tygns54j2IseodtVhV3aaJjlJK1VLGSoKM1yDvLeTwG+DZDqYeJvFSe3zPEQt6ioi98re4wdGk0gUFRQqRg7dDwX8ouVK6HH4b4vpCvScwxukbhB3G+CfJA+pVKhalyqOJjlJK1WLGxIPraozr6jKPERHIfxfJeRY8vunmJhVJHIpJurHCxf4k+1EoWOB75Qn8b8EiJGsqJvUuTMwJ9sDjkD9AIlj1K3R9pSpCx+gopVSUk5yn7MVLPVtLbDwEubOQ/dcjEnpAc8C5vFmQN4+yq00LHH4D8R6A+IGAM8TZHJAwxG79Ueoo0URHKaWimLg3lVhB/cjkxAvuFZD3ZvgnLFxBeTO9wA2F3wEWJI32bbMfN1s3xPHk+GZc2bk9l3Vsz73DhNWL14Z/faUqSLuulFIqisnhNwk9IBgkbx7GdVWYZ3SHd93ceXDwdv5Mipx88VEcD41sDoDHY4/d+e6j//L1+6u5+q7BXHPPkDBjUCp82qKjlFLRrOgXQi8QKuD5LfzzxbQP7zh3YMvPnh1ept6Uicdr/EkOgKfInnr+8pS3WLFgdfhxKBUmTXSUUiqaWcmU+1FvEsI+nYnJBOdZlL2GV3ESE1g755N5aXg9psyhPZbD4p0nPwo7DqXCpYmOUkpFMRPXn+AF+4o5fIOGK3DO1AfBakjpR0jZj5S1y114vWVPNfd6vPz05foKxaFUODTRUUqpaBbfFxytCd4CYwGxGNfwCp3SOBpj6r8LrpFgZQDG/m/iUMpqsrEsytznP691dNYcU3WbJjpKKRXFjHFi0ueUGFvjwD8PxaqHSX8RE9Oi4ue10rGSb8Vq+A2m0Xr7v0ljKatAYJde2ZgQTxxHjEXXfpFbrkJFL511pZRSUc44GkLG2+D+ASlYBuLGxHaA+L7VUsOmeMkHY7kQZy/fIp6BA6D7X76feY83oiDfQoJ0YXk8Xv5660VVjkWpI2mLjlJK1QHGGIyzG1byWKyUCZiEC45KoT6TNKr4bwHbUzM83PfybzjjDVaJLipHjIUxhjH/uoGTe5xU7fEopS06Simlqo1xdoK0mcjBcXb1ZWKwB0N76XhOD+ZuvINPXvia7z5eicft4eQeJ3HRjf1o3q5ZZANXUcuISOjRYVEkKyuL1NRUDh06REpKSqTDUUqpqCVSCPmfIkWbMCYB4s/DxLSKdFiqlqrK81tbdJRSSlU7Y5yQcFE4a5crdVRpoqOUUkrVQFL0K5L3EuR/ClIAMe3tpTri+vkHgKvyaaKjlFJK1TBS8BVy4O/Ys9d8M9jcK5CD30H8pZD6ICbUfH3lp3dJKaWUqkHEm40cHIW9gGrJafq+Ctf578DhdyIQWe2kiY5SSilVkxx+D+QwZVeSNkjenGMXTy2niY5SSilVg4h7DWVVmPYdAUUbESk4ViHVaproKKWUUjWKRehEp5gOSA6HJjpKKaVUDWLienLkEhqBLIjtdlQqW0cjTXSUUkqpmiR+AFgNKPsR7cW4RhzLiGo1TXSUUkqpGsSYOEzai2DVw+6eKu6ictj7k8Zh4vtEKLraR+voKKWUUjWMiT0R6i+Ew+8iBZ+B5EPsyZiEyzGxuvhpRWiio5RSStVAxkoG1zUY1zWRDqVW064rpZRSSkUtTXSUUkopFbU00VFKKaVU1NJERymllFJRSxMdpZRSSkUtTXSUUkopFbU00VFKKaVU1NJERymllFJRSxMdpZRSSkUtTXSUUkopFbXq1BIQIgJAVlZWhCNRSimlVLiKn9vFz/GKqFOJTnZ2NgDHH398hCNRSimlVEVlZ2eTmppaofcYqUx6VEt5vV527NhBcnIyxhj/9qysLI4//nh+//13UlJSIhhhzaH3JDi9L6XpPSlN70lwel9K03sS3JH3RUTIzs6madOmWFbFRt3UqRYdy7Jo1qxZmftTUlL0F+0Iek+C0/tSmt6T0vSeBKf3pTS9J8GVvC8VbckppoORlVJKKRW1NNFRSimlVNTSRAeIi4vj7rvvJi4uLtKh1Bh6T4LT+1Ka3pPS9J4Ep/elNL0nwVXnfalTg5GVUkopVbdoi45SSimlopYmOkoppZSKWproKKWUUipqaaKjlFJKqailiU4ZCgoK6NSpE8YYVq9eHelwImbr1q1cf/31tGzZkoSEBFq1asXdd99NYWFhpEM75p555hlatGhBfHw83bt3Z/ny5ZEOKaIeeughTjvtNJKTk2nYsCGDBg1iw4YNkQ6rRpk6dSrGGG699dZIhxJR27dv56qrriIjI4OEhAQ6dOjA999/H+mwIsrj8TB58uSAz9b77ruvUms51VbLli1j4MCBNG3aFGMM7733XsB+EeGuu+6iSZMmJCQk0LdvXzZt2lTh62iiU4bx48fTtGnTSIcRcevXr8fr9fLss8/y008/8fjjjzNr1iwmTZoU6dCOqTfeeIOxY8dy9913s3LlSk499VT69+/P7t27Ix1axCxdupRRo0bx7bffsnDhQtxuN/369SM3NzfSodUIK1as4Nlnn6Vjx46RDiWiDhw4QM+ePYmNjeWTTz7h559/5tFHHyUtLS3SoUXUww8/zMyZM3n66adZt24dDz/8MNOmTWPGjBmRDu2Yyc3N5dRTT+WZZ54Jun/atGk89dRTzJo1i++++w6Xy0X//v3Jz8+v2IVElfLxxx9L27Zt5aeffhJAVq1aFemQapRp06ZJy5YtIx3GMXX66afLqFGj/K89Ho80bdpUHnrooQhGVbPs3r1bAFm6dGmkQ4m47OxsadOmjSxcuFB69+4tY8aMiXRIETNhwgQ566yzIh1GjXPhhRfKddddF7Dt0ksvlaFDh0YoosgC5N133/W/9nq90rhxY3nkkUf82w4ePChxcXHy2muvVejc2qJzhF27djFixAhefvllEhMTIx1OjXTo0CHS09MjHcYxU1hYyA8//EDfvn392yzLom/fvnzzzTcRjKxmOXToEECd+t0oy6hRo7jwwgsDfmfqqg8++IBu3boxePBgGjZsSOfOnXnuueciHVbE9ejRg0WLFrFx40YA1qxZw5dffsn5558f4chqhi1btrBz586A/4dSU1Pp3r17hT9369SinuUREYYPH87IkSPp1q0bW7dujXRINc7mzZuZMWMG06dPj3Qox8zevXvxeDw0atQoYHujRo1Yv359hKKqWbxeL7feeis9e/bklFNOiXQ4EfX666+zcuVKVqxYEelQaoRff/2VmTNnMnbsWCZNmsSKFSu45ZZbcDqdDBs2LNLhRczEiRPJysqibdu2OBwOPB4PDzzwAEOHDo10aDXCzp07AYJ+7hbvC1edaNGZOHEixpiQf9avX8+MGTPIzs7mjjvuiHTIR12496Sk7du3M2DAAAYPHsyIESMiFLmqiUaNGsXatWt5/fXXIx1KRP3++++MGTOGefPmER8fH+lwagSv10uXLl148MEH6dy5MzfccAMjRoxg1qxZkQ4tot58803mzZvHq6++ysqVK5k7dy7Tp09n7ty5kQ4t6tSJFp3bbruN4cOHhzzmhBNO4PPPP+ebb74ptbZGt27dGDp0aFT9AoZ7T4rt2LGDPn360KNHD2bPnn2Uo6tZ6tevj8PhYNeuXQHbd+3aRePGjSMUVc0xevRo5s+fz7Jly2jWrFmkw4moH374gd27d9OlSxf/No/Hw7Jly3j66acpKCjA4XBEMMJjr0mTJrRv3z5gW7t27fj3v/8doYhqhnHjxjFx4kQuv/xyADp06MBvv/3GQw89VKdbuooVf7bu2rWLJk2a+Lfv2rWLTp06VehcdSLRadCgAQ0aNCj3uKeeeor777/f/3rHjh3079+fN954g+7dux/NEI+5cO8J2C05ffr0oWvXrrz44otYVp1oCPRzOp107dqVRYsWMWjQIMD+lrpo0SJGjx4d2eAiSES4+eabeffdd1myZAktW7aMdEgRd+655/Ljjz8GbLv22mtp27YtEyZMqHNJDkDPnj1LlR3YuHEjzZs3j1BENUNeXl6pz1KHw4HX641QRDVLy5Ytady4MYsWLfInNllZWXz33XfceOONFTpXnUh0wpWZmRnwOikpCYBWrVrV2W+q27dv55xzzqF58+ZMnz6dPXv2+PfVpdaMsWPHMmzYMLp168bpp5/OE088QW5uLtdee22kQ4uYUaNG8eqrr/L++++TnJzs7zdPTU0lISEhwtFFRnJycqkxSi6Xi4yMjDo7dukf//gHPXr04MEHH2TIkCEsX76c2bNn17mW4SMNHDiQBx54gMzMTE4++WRWrVrFY489xnXXXRfp0I6ZnJwcNm/e7H+9ZcsWVq9eTXp6OpmZmdx6663cf//9tGnThpYtWzJ58mSaNm3q/8IZtuqZGBadtmzZUuenl7/44osCBP1T18yYMUMyMzPF6XTK6aefLt9++22kQ4qosn4vXnzxxUiHVqPU9enlIiIffvihnHLKKRIXFydt27aV2bNnRzqkiMvKypIxY8ZIZmamxMfHywknnCD//Oc/paCgINKhHTOLFy8O+hkybNgwEbGnmE+ePFkaNWokcXFxcu6558qGDRsqfB0jUofKMCqllFKqTqlbgy2UUkopVadooqOUUkqpqKWJjlJKKaWiliY6SimllIpamugopZRSKmppoqOUUkqpqKWJjlJKKaWiliY6SkWRFi1a8MQTT1Tb+YYPH17xKqTlWLJkCcYYDh48WK3nVUqpYDTRUaoGGj58uH8VeafTSevWrZkyZQpFRUUh37dixQpuuOGGaovjySefZM6cOdV2vopYtWoVgwcPplGjRsTHx9OmTRtGjBjBxo0bIxJPTRVucjt79mzOOeccUlJSNNFUdYomOkrVUAMGDOCPP/5g06ZN3Hbbbdxzzz088sgjQY8tLCwE7MVaExMTqy2G1NRU6tWrV23nC9f8+fM544wzKCgoYN68eaxbt45XXnmF1NRUJk+efMzjiQZ5eXkMGDCASZMmRToUpY6tal24QilVLYYNGyaXXHJJwLbzzjtPzjjjjID9999/vzRp0kRatGghIiLNmzeXxx9/3P8eQJ577jkZNGiQJCQkSOvWreX9998POO/atWvlwgsvlOTkZElKSpKzzjpLNm/eHDSO3r17y6hRo2TUqFGSkpIiGRkZcuedd4rX6/Uf89JLL0nXrl0lKSlJGjVqJFdccYXs2rXLv794fZsDBw4E/dlzc3Olfv36MmjQoKD7S75vyZIlctppp4nT6ZTGjRvLhAkTxO12B8Q7evRoGTNmjNSrV08aNmwos2fPlpycHBk+fLgkJSVJq1at5OOPPy4V3/z586VDhw4SFxcn3bt3lx9//DEgjrffflvat28vTqdTmjdvLtOnTw/Y37x5c3nggQfk2muvlaSkJDn++OPl2WefDThm27ZtMnjwYElNTZW0tDS5+OKLZcuWLf79xff/kUcekcaNG0t6errcdNNNUlhY6P/5qOAadOXdf6WijbboKFVLJCQk+FtuABYtWsSGDRtYuHAh8+fPL/N99957L0OGDOG///0vF1xwAUOHDmX//v2AvTp9r169iIuL4/PPP+eHH37guuuuC9lFNnfuXGJiYli+fDlPPvkkjz32GM8//7x/v9vt5r777mPNmjW89957bN26leHDh4f9cy5YsIC9e/cyfvz4oPuLW5i2b9/OBRdcwGmnncaaNWuYOXMmL7zwAvfff3+peOvXr8/y5cu5+eabufHGGxk8eDA9evRg5cqV9OvXj6uvvpq8vLyA940bN45HH32UFStW0KBBAwYOHIjb7Qbghx9+YMiQIVx++eX8+OOP3HPPPUyePLlUN9+jjz5Kt27dWLVqFTfddBM33ngjGzZs8N+n/v37k5yczBdffMFXX31FUlISAwYMCPh3Xrx4Mb/88guLFy9m7ty5zJkzx3+dd955h2bNmjFlyhT++OMP/vjjj7Dvs1J1RqQzLaVUaSVbUrxeryxcuFDi4uLk9ttv9+9v1KhRqZWOg7Xo3Hnnnf7XOTk5Asgnn3wiIiJ33HGHtGzZ0t9CECoOEbsFoV27dgEtOBMmTJB27dqV+bOsWLFCAMnOzhaR8lsUHn74YQFk//79ZZ5TRGTSpEly0kknBcTyzDPPSFJSkng8Hn+8Z511ln9/UVGRuFwuufrqq/3b/vjjDwHkm2++CYjv9ddf9x+zb98+SUhIkDfeeENERK688ko577zzAuIZN26ctG/f3v+6efPmctVVV/lfe71eadiwocycOVNERF5++eVS8RcUFEhCQoIsWLBAROz737x5cykqKvIfM3jwYLnssssCrlPy37w82qKj6hpt0VGqhpo/fz5JSUnEx8dz/vnnc9lll3HPPff493fo0AGn01nueTp27Oj/u8vlIiUlhd27dwOwevVqzj77bGJjY8OO64wzzsAY43995plnsmnTJjweD2C3dgwcOJDMzEySk5Pp3bs3ANu2bQvr/CIS1nHr1q3jzDPPDIilZ8+e5OTk8L///c+/reTP73A4yMjIoEOHDv5tjRo1AvDfk5I/V7H09HROOukk1q1b5792z549A47v2bNnwH048trGGBo3buy/zpo1a9i8eTPJyckkJSWRlJREeno6+fn5/PLLL/73nXzyyTgcDv/rJk2alIpVKVW2mEgHoJQKrk+fPsycOROn00nTpk2JiQn839XlcoV1niOTGGMMXq8XsLvDqlNubi79+/enf//+zJs3jwYNGrBt2zb69+8f0B0TyoknngjA+vXrA5KNygr285fcVpwoFd+T6hTq3ufk5NC1a1fmzZtX6n0NGjQI6xxKqfJpi45SNZTL5aJ169ZkZmaWSnKqS8eOHfniiy/8Y0/C8d133wW8/vbbb2nTpg0Oh4P169ezb98+pk6dytlnn03btm0r3PrQr18/6tevz7Rp04LuL54W3a5dO7755puAFqCvvvqK5ORkmjVrVqFrBvPtt9/6/37gwAE2btxIu3bt/Nf+6quvAo7/6quvOPHEEwNaX0Lp0qULmzZtomHDhrRu3TrgT2pqathxOp3OgFYkpVQgTXSUqsNGjx5NVlYWl19+Od9//z2bNm3i5Zdf9g+YDWbbtm2MHTuWDRs28NprrzFjxgzGjBkDQGZmJk6nkxkzZvDrr7/ywQcfcN9991UoJpfLxfPPP89HH33ExRdfzGeffcbWrVv5/vvvGT9+PCNHjgTgpptu4vfff+fmm29m/fr1vP/++9x9992MHTsWy6r6R9uUKVNYtGgRa9euZfjw4dSvX99fPPG2225j0aJF3HfffWzcuJG5c+fy9NNPc/vtt4d9/qFDh1K/fn0uueQSvvjiC7Zs2cKSJUu45ZZbArreytOiRQuWLVvG9u3b2bt3b5nH7dy5k9WrV7N582YAfvzxR1avXu0fmK5UtNJER6k6LCMjg88//5ycnBx69+5N165dee6550KO2bnmmms4fPgwp59+OqNGjWLMmDH+IoUNGjRgzpw5vPXWW7Rv356pU6cyffr0Csd1ySWX8PXXXxMbG8uVV15J27ZtueKKKzh06JB/VtVxxx3Hxx9/zPLlyzn11FMZOXIk119/PXfeeWflbsYRpk6dypgxY+jatSs7d+7kww8/9I+J6tKlC2+++Savv/46p5xyCnfddRdTpkyp0OyyxMREli1bRmZmJpdeeint2rXj+uuvJz8/n5SUlLDPM2XKFLZu3UqrVq0CuryONGvWLDp37syIESMA6NWrF507d+aDDz4I+1pK1UZGwh35p5Sq88455xw6depUrctM1DRLliyhT58+HDhwICLFEpVS1UtbdJRSSikVtTTRUUoppVTU0q4rpZRSSkUtbdFRSimlVNTSREcppZRSUUsTHaWUUkpFLU10lFJKKRW1NNFRSimlVNTSREcppZRSUUsTHaWUUkpFLU10lFJKKRW1NNFRSimlVNT6f5L0lCPZwsQsAAAAAElFTkSuQmCC\n"
+ },
+ "metadata": {}
+ }
+ ],
+ "source": [
+ "plt.scatter(X_train_pca[:, 0], X_train_pca[:, 1], c=kmeans.labels_, cmap='viridis')\n",
+ "plt.title('Clustering Analysis')\n",
+ "plt.xlabel('Principal Component 1')\n",
+ "plt.ylabel('Principal Component 2')\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "source": [
+ "# **Classifier: The Model**"
+ ],
+ "metadata": {
+ "id": "Nq-Q34MPfKUc"
+ }
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "# Prepare the classifiers\n",
+ "classifiers = {\n",
+ " \"Logistic Regression\": LogisticRegression(),\n",
+ " \"Random Forest\": RandomForestClassifier(random_state=42),\n",
+ " \"Gradient Boosting\": GradientBoostingClassifier(random_state=42),\n",
+ " \"Support Vector Machine\": SVC(probability=True, random_state=42)\n",
+ "}\n",
+ "\n",
+ "# Train and evaluate the classifiers\n",
+ "results = {}\n",
+ "for name, clf in classifiers.items():\n",
+ " # Train the classifier\n",
+ " clf.fit(X_train_scaled, y_train)\n",
+ "\n",
+ " # Predict on the test set\n",
+ " y_pred = clf.predict(X_test_scaled)\n",
+ " y_proba = clf.predict_proba(X_test_scaled)[:, 1]\n",
+ "\n",
+ " # Evaluate the classifier\n",
+ " accuracy = accuracy_score(y_test, y_pred)\n",
+ " precision = precision_score(y_test, y_pred)\n",
+ " recall = recall_score(y_test, y_pred)\n",
+ " f1 = f1_score(y_test, y_pred)\n",
+ " roc_auc = roc_auc_score(y_test, y_proba)\n",
+ " cv_scores = cross_val_score(clf, X_train_scaled, y_train, cv=5)\n",
+ "\n",
+ " # Store results\n",
+ " results[name] = {\n",
+ " \"Accuracy\": accuracy,\n",
+ " \"Precision\": precision,\n",
+ " \"Recall\": recall,\n",
+ " \"F1 Score\": f1,\n",
+ " \"ROC-AUC Score\": roc_auc,\n",
+ " \"Cross-validation scores\": cv_scores.tolist(), # Convert to list for printing\n",
+ "\n",
+ " }\n",
+ "\n",
+ " # Print the performance\n",
+ " print(f\"Results for {name}:\")\n",
+ " print(f\"Accuracy: {accuracy:.4f}\")\n",
+ " print(f\"Precision: {precision:.4f}\")\n",
+ " print(f\"Recall: {recall:.4f}\")\n",
+ " print(f\"F1 Score: {f1:.4f}\")\n",
+ " print(f\"ROC-AUC Score: {roc_auc:.4f}\\n\")\n",
+ " print(f\"Cross-validation scores: {cv_scores}\\n\")\n",
+ "\n",
+ "# Compare results\n",
+ "results_df = pd.DataFrame(results).transpose()\n",
+ "print(\"Comparison of Classifiers:\")\n",
+ "print(results_df)\n"
+ ],
+ "metadata": {
+ "id": "juXqa7yLkxbQ"
+ },
+ "execution_count": null,
+ "outputs": []
+ },
+ {
+ "cell_type": "markdown",
+ "source": [
+ "# **What is the most important feature?**"
+ ],
+ "metadata": {
+ "id": "7g7RHBOr4p16"
+ }
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "# Feature importance\n",
+ "# Train the classifier\n",
+ "clf =GradientBoostingClassifier(random_state=42)\n",
+ "clf.fit(X_train_prepared, y_train)\n",
+ "\n",
+ "feature_importance = clf.feature_importances_\n",
+ "important_features = X_train_prepared.columns[np.argsort(feature_importance)[::-1]]\n",
+ "\n",
+ "print(\"Most Important Feature:\", important_features[0])\n",
+ "\n",
+ "# 6.2 Exclude the best feature and retrain the classifier\n",
+ "X_train_subset = X_train_prepared.drop(important_features[0], axis=1)\n",
+ "X_test_subset = X_test_prepared.drop(important_features[0], axis=1)\n",
+ "\n",
+ "clf_subset = RandomForestClassifier(random_state=42)\n",
+ "clf_subset.fit(X_train_subset, y_train)\n",
+ "\n",
+ "y_pred_test_subset = clf_subset.predict(X_test_subset)\n",
+ "print(\"Test Accuracy (Excluding Best Feature):\", accuracy_score(y_test, y_pred_test_subset))\n"
+ ],
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "LN_0uHHPlvnA",
+ "outputId": "5c2da873-959c-4406-bf6f-a890dfea65f4"
+ },
+ "execution_count": null,
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "Most Important Feature: health_gen\n",
+ "Test Accuracy (Excluding Best Feature): 0.8329430132708822\n"
+ ]
+ }
+ ]
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "# Train the classifier\n",
+ "clf =RandomForestClassifier(random_state=42)\n",
+ "clf.fit(X_train_prepared, y_train)\n",
+ "\n",
+ "feature_importance = clf.feature_importances_\n",
+ "important_features = X_train_prepared.columns[np.argsort(feature_importance)[::-1]]\n",
+ "\n",
+ "print(\"Most Important Feature:\", important_features[0])\n",
+ "\n",
+ "# 6.2 Exclude the best feature and retrain the classifier\n",
+ "X_train_subset = X_train_prepared.drop(important_features[0], axis=1)\n",
+ "X_test_subset = X_test_prepared.drop(important_features[0], axis=1)\n",
+ "\n",
+ "clf_subset = RandomForestClassifier(random_state=42)\n",
+ "clf_subset.fit(X_train_subset, y_train)\n",
+ "\n",
+ "y_pred_test_subset = clf_subset.predict(X_test_subset)\n",
+ "print(\"Test Accuracy (Excluding Best Feature):\", accuracy_score(y_test, y_pred_test_subset))"
+ ],
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "IX_rAeHYlxbB",
+ "outputId": "8f442e9b-ff89-47db-9112-a06241957869"
+ },
+ "execution_count": null,
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "Most Important Feature: bmi\n",
+ "Test Accuracy (Excluding Best Feature): 0.8290398126463701\n"
+ ]
+ }
+ ]
+ }
+ ],
+ "metadata": {
+ "colab": {
+ "provenance": []
+ },
+ "kernelspec": {
+ "display_name": "Python 3 (ipykernel)",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.10.13"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
\ No newline at end of file