{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "QnEO4S54IUT2"
      },
      "source": [
        "# **Model Tuning Project - ReneWind**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "iubQwKtPIUp9"
      },
      "source": [
        "- Student: Alexey Tyurin\n",
        "- Group: Oct'22 C Sun - MLS Grp B\n",
        "- Batch: PGP-DSBA-UTA-OCT22-C\n",
        "- Date: 4/22/2023-5/4/2023"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9EaJ8AGwpM-2"
      },
      "source": [
        "# Problem Statement"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "yRCutHhbKS6X"
      },
      "source": [
        "## Description\n",
        "<center><p float=\"center\">\n",
        "  <img src=\"https://olympus.mygreatlearning.com/courses/79763/files/5778139/preview?verifier=mkUixA7fKm9LjCjmDdSmwkyKFOVDAKO7LuZRVxaL\">"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "x3-QehJxbp0t"
      },
      "source": [
        "## Business Context\n",
        "\n",
        "Renewable energy sources play an increasingly important role in the global energy mix, as the effort to reduce the environmental impact of energy production increases.\n",
        "\n",
        "Out of all the renewable energy alternatives, wind energy is one of the most developed technologies worldwide. The U.S Department of Energy has put together a guide to achieving operational efficiency using predictive maintenance practices.\n",
        "\n",
        "Predictive maintenance uses sensor information and analysis methods to measure and predict degradation and future component capability. The idea behind predictive maintenance is that failure patterns are predictable and if component failure can be predicted accurately and the component is replaced before it fails, the costs of operation and maintenance will be much lower.\n",
        "\n",
        "The sensors fitted across different machines involved in the process of energy generation collect data related to various environmental factors (temperature, humidity, wind speed, etc.) and additional features related to various parts of the wind turbine (gearbox, tower, blades, break, etc.). \n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ocF-Uj1LJNAO"
      },
      "source": [
        "## Objective\n",
        "“ReneWind” is a company working on improving the machinery/processes involved in the production of wind energy using machine learning and has collected data of generator failure of wind turbines using sensors. They have shared a ciphered version of the data, as the data collected through sensors is confidential (the type of data collected varies with companies). Data has 40 predictors, 20000 observations in the training set and 5000 in the test set.\n",
        "\n",
        "The objective is to build various classification models, tune them, and find the best one that will help identify failures so that the generators could be repaired before failing/breaking to reduce the overall maintenance cost. \n",
        "The nature of predictions made by the classification model will translate as follows:\n",
        "\n",
        "- True positives (TP) are failures correctly predicted by the model. These will result in repairing costs.\n",
        "- False negatives (FN) are real failures where there is no detection by the model. These will result in replacement costs.\n",
        "- False positives (FP) are detections where there is no failure. These will result in inspection costs.\n",
        "\n",
        "It is given that the cost of repairing a generator is much less than the cost of replacing it, and the cost of inspection is less than the cost of repair.\n",
        "\n",
        "“1” in the target variables should be considered as “failure” and “0” represents “No failure”.\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "q8C9L12SJNDe"
      },
      "source": [
        "## Data Description\n",
        "- The data provided is a transformed version of original data which was collected using sensors.\n",
        "- Train.csv - To be used for training and tuning of models. \n",
        "- Test.csv - To be used only for testing the performance of the final best model.\n",
        "- Both the datasets consist of 40 predictor variables and 1 target variable"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "roDkMOKCNUSJ"
      },
      "source": [
        "# Load essentials"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "v_-uuGqH-qTt"
      },
      "source": [
        "## Importing necessary libraries"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "id": "83D17_Wl4jal"
      },
      "outputs": [],
      "source": [
        "# Libraries to help with reading and manipulating data\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "import time\n",
        "\n",
        "# libaries to help with data visualization\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "\n",
        "# To be used for missing value imputation\n",
        "from sklearn.impute import SimpleImputer\n",
        "\n",
        "# To help with model building\n",
        "from sklearn.linear_model import LogisticRegression\n",
        "from sklearn.tree import DecisionTreeClassifier\n",
        "from sklearn.ensemble import (\n",
        "    AdaBoostClassifier,\n",
        "    GradientBoostingClassifier,\n",
        "    RandomForestClassifier,\n",
        "    BaggingClassifier,\n",
        ")\n",
        "from xgboost import XGBClassifier\n",
        "\n",
        "# To impute missing values\n",
        "from sklearn.impute import KNNImputer\n",
        "\n",
        "# To oversample and undersample data\n",
        "from imblearn.over_sampling import SMOTE\n",
        "from imblearn.under_sampling import RandomUnderSampler\n",
        "\n",
        "# To construct a pipeline of machine learning tasks\n",
        "from imblearn.pipeline import Pipeline\n",
        "\n",
        "# To tune model, get different metric scores and split data\n",
        "from sklearn.model_selection import GridSearchCV, RandomizedSearchCV\n",
        "from sklearn.model_selection import train_test_split, StratifiedKFold, cross_val_score\n",
        "from sklearn.metrics import (confusion_matrix,\n",
        "                             make_scorer,\n",
        "                             accuracy_score,\n",
        "                             precision_score,\n",
        "                             recall_score,\n",
        "                             f1_score)\n",
        "\n",
        "\n",
        "# To suppress the warnings\n",
        "import warnings\n",
        "\n",
        "warnings.filterwarnings(\"ignore\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xxhpZv9y-qTw"
      },
      "source": [
        "## Loading the dataset"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "id": "oJnKoHy14jam"
      },
      "outputs": [],
      "source": [
        "train = pd.read_csv('/content/Train.csv')\n",
        "test = pd.read_csv('/content/Test.csv')"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-4dGU7r8g41J"
      },
      "source": [
        "## User-defined functions"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "GS5dP02gg8jS"
      },
      "source": [
        "### Combined boxplot and histogram"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "id": "FMrPsPwkg4-x"
      },
      "outputs": [],
      "source": [
        "# functiom to create combined boxplot and histogram\n",
        "def histogram_boxplot(data, feature, figsize=(10, 5), fmt='{:.1f}', rotation=0,\n",
        "                      title=None, kde=True, bins=None, step=None, xlabel=None):\n",
        "    x = data[feature]\n",
        "    colors = sns.color_palette(\"Spectral\")\n",
        "    title = title if title else f'Distribution for `{feature}` column'\n",
        "\n",
        "    x_min, x_max = x.min(), x.max()\n",
        "\n",
        "    if (bins == None) & (step == None):\n",
        "        bins = int(3 * np.log(x.nunique())) + 2\n",
        "    elif bins == None:\n",
        "        x_min = step * round(x_min / step, 0)\n",
        "        x_max = step * round(x_max / step, 0) + step\n",
        "        bins = int((x_max - x_min) / step)\n",
        "\n",
        "    bw = (x_max - x_min) / bins\n",
        "\n",
        "    fig, ax = plt.subplots(nrows=2, ncols=1, sharex=True, figsize=figsize,\n",
        "                           gridspec_kw={\"height_ratios\": (0.3, 0.7)})\n",
        "\n",
        "    plt.suptitle(title, fontsize=16)\n",
        "    box = sns.boxplot(data=data, x=feature, ax=ax[0], showmeans=True, color=colors[1])\n",
        "    hist = sns.histplot(data=data, x=feature, kde=kde, ax=ax[1], color=colors[4], bins=bins)\n",
        "\n",
        "    ax[0].set_xlabel('')\n",
        "    ax[1].axvline(x.median(), color=\"grey\", linestyle=\"-\")\n",
        "    ax[1].axvline(x.mean(), color=\"darkgreen\", linestyle=\"--\")\n",
        "    ax[1].set_ylabel('Number of observations', fontsize=12)\n",
        "    if xlabel: ax[1].set_xlabel(xlabel, fontsize=12)\n",
        "\n",
        "    labels = [fmt.format(x) for x in np.arange(x_min, x_max, bw)]\n",
        "    ticks =  [x+bw/2 for x in np.arange(x_min, x_max, bw)]\n",
        "\n",
        "    ax[1].set_xticks(ticks)\n",
        "    ax[1].set_xticklabels(labels, rotation=rotation)\n",
        "\n",
        "    plt.show();"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Labeled barplots"
      ],
      "metadata": {
        "id": "1jzO0Q0wdofA"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# function to create labeled barplots\n",
        "def labeled_barplot(data, feature, perc=False, n=None, percfmt=\"{:.1f}%\", rnd=0,\n",
        "                    figsize=(10, 5), xlabel=None, xlo=0, title=None, sort=True, \n",
        "                    orient='h'):\n",
        "    \"\"\"\n",
        "    Barplot with percentage at the top\n",
        "\n",
        "    data: dataframe\n",
        "    perc: whether to display percentages instead of count (default is False)\n",
        "    n: displays the top n category levels (default is None, i.e., display all levels)\n",
        "    figsize: size of figure (default (10, 5))\n",
        "    xlabel: label for x axis\n",
        "    \"\"\"\n",
        "\n",
        "    fig, ax = plt.subplots(figsize=figsize)\n",
        "    plt.xticks(rotation=xlo, fontsize=14)\n",
        "    if orient == 'h':\n",
        "      sns.countplot(data=data, x=feature, palette=\"Paired\",\n",
        "                    order=data[feature].value_counts().index[:n] if sort else None)\n",
        "    else:\n",
        "      sns.countplot(data=data, y=feature, palette=\"Paired\",\n",
        "                    order=data[feature].value_counts().index[:n] if sort else None)\n",
        "\n",
        "    # draw lables\n",
        "    for p in ax.patches:\n",
        "      if orient == 'h':\n",
        "        if perc == True:\n",
        "          label = percfmt.format(100 * p.get_height() / data.shape[0])\n",
        "        else:\n",
        "          label = p.get_height()\n",
        "        ax.annotate(label, (p.get_x() + p.get_width() / 2, p.get_height()),\n",
        "                    ha=\"center\", va=\"center\", size=11, xytext=(0, 5),\n",
        "                    textcoords=\"offset points\")\n",
        "        ax.set_ylabel('Number of cases', fontsize=14)\n",
        "        if xlabel: ax.set_xlabel(xlabel, fontsize=14)\n",
        "      else:\n",
        "        if perc == True:\n",
        "          label = percfmt.format(100 * p.get_width() / data.shape[0])\n",
        "        else:\n",
        "          label = p.get_width()\n",
        "        ax.annotate(label, (p.get_width(), p.get_y() + p.get_height() / 2),\n",
        "                    ha=\"center\", va=\"center\", size=11, xytext=(20, 0),\n",
        "                    textcoords=\"offset points\")\n",
        "        ax.set_xlabel('Number of cases', fontsize=14)\n",
        "        if xlabel: ax.set_ylabel(xlabel, fontsize=14)\n",
        "\n",
        "    if title: plt.title(title, fontsize=16)\n",
        "    else: plt.title(f'Distribution for `{feature}` column', fontsize=16)\n",
        "\n",
        "    plt.show()"
      ],
      "metadata": {
        "id": "tCUzyGT5dopL"
      },
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "aB4G-J60jcI_"
      },
      "source": [
        "### Model Performance - compute different metrics and visualize results"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {
        "id": "_NXfVtUKjcU5"
      },
      "outputs": [],
      "source": [
        "# Let's define function to provide metric scores (accuracy, recall, precision, etc.) \n",
        "# on train and test set and a function to show confusion matrix \n",
        "# so that we do not have use the same code repetitively while evaluating models.\n",
        "# defining a function to compute different metrics to check performance of \n",
        "# a classification model built using sklearn\n",
        "\n",
        "def specificity_score(y_true, y_pred):\n",
        "  tn, fp, fn, tp = confusion_matrix(y_true, y_pred).flatten()\n",
        "  return (tn)/(tn+fp)\n",
        "\n",
        "def npv_score(y_true, y_pred):\n",
        "  tn, fp, fn, tp = confusion_matrix(y_true, y_pred).flatten()\n",
        "  return (tn)/(tn+fn)\n",
        "\n",
        "def model_performance(model, X_train, y_train, X_test, y_test, verbose=True, sets=['Train', 'Test']):\n",
        "  p_train = model.predict(X_train).astype(bool)\n",
        "  p_test = model.predict(X_test).astype(bool)\n",
        "  y_train = np.array(y_train).astype(bool)\n",
        "  y_test = np.array(y_test).astype(bool)\n",
        "\n",
        "  cm_train = confusion_matrix(y_train, p_train)\n",
        "  cm_test = confusion_matrix(y_test, p_test)\n",
        "  lab_train = np.asarray([[\"{0:,.0f}\".format(item) + \"\\n{0:.2%}\".format(item / cm_train.flatten().sum())] for item in cm_train.flatten()]).reshape(2, 2)\n",
        "  lab_test  = np.asarray([[\"{0:,.0f}\".format(item) + \"\\n{0:.2%}\".format(item / cm_test.flatten().sum())] for item in cm_test.flatten()]).reshape(2, 2)\n",
        "\n",
        "  df_perf = pd.DataFrame({'Accuracy':    [accuracy_score(y_train, p_train), accuracy_score(y_test, p_test)],\n",
        "                          'Precision':   [precision_score(y_train, p_train), precision_score(y_test, p_test)],\n",
        "                          'Recall':      [recall_score(y_train, p_train), recall_score(y_test, p_test)],\n",
        "                          'NPV':         [npv_score(y_train, p_train), npv_score(y_test, p_test)],\n",
        "                          'Specificity': [specificity_score(y_train, p_train), specificity_score(y_test, p_test)],\n",
        "                          'F1':          [f1_score(y_train, p_train), f1_score(y_test, p_test)]},\n",
        "                         index=sets)\n",
        "\n",
        "  if verbose:\n",
        "    fig, ax = plt.subplots(ncols = 2, nrows = 1, figsize=(9, 3))\n",
        "\n",
        "    sns.heatmap(cm_train, annot=lab_train, fmt=\"\", ax=ax[0], annot_kws = {\"size\": 10})\n",
        "    sns.heatmap(cm_test, annot=lab_test, fmt=\"\", ax=ax[1], annot_kws = {\"size\": 10})\n",
        "    ax[0].set_title(sets[0]+' dataset', fontsize=10)\n",
        "    ax[0].set_xlabel('Predicted label', fontsize=10)\n",
        "    ax[0].set_ylabel('True label', fontsize=10)\n",
        "    ax[1].set_title(sets[1]+' dataset', fontsize=10)\n",
        "    ax[1].set_xlabel('Predicted label', fontsize=10)\n",
        "    ax[1].set_ylabel('True label', fontsize=10)\n",
        "    plt.show();\n",
        "\n",
        "    print('\\033[1m' + 'Model performance:' + '\\033[0m')\n",
        "    display(df_perf.style.set_table_styles([dict(selector=\"th\", props=[('max-width', '75px')])]).format('{:.2%}'))\n",
        "  \n",
        "  return df_perf"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-hOzddAXbp0_"
      },
      "source": [
        "### Defining scorer to be used for cross-validation and hyperparameter tuning"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "dzLUm-eSi_cJ"
      },
      "source": [
        "- We want to reduce false negatives and will try to maximize \"Recall\".\n",
        "- To maximize Recall, we can use Recall as a **scorer** in cross-validation and hyperparameter tuning."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {
        "id": "91_wFqnbV_Ij"
      },
      "outputs": [],
      "source": [
        "# Type of scoring used to compare parameter combinations\n",
        "scorer = make_scorer(recall_score)\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "FD2P4EvZr4FP"
      },
      "source": [
        "### Defining 7 classifiers to be used for cross-validation and hyperparameter tuning"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {
        "id": "Zb0l0-8tJWyt"
      },
      "outputs": [],
      "source": [
        "models_grid = [('DecisionTreeClassifier', DecisionTreeClassifier(random_state=42),\n",
        "                {'max_depth': np.arange(2, 6),\n",
        "                 'min_samples_leaf': [1, 4, 7], \n",
        "                 'max_leaf_nodes' : [10, 15],\n",
        "                 'min_impurity_decrease': [0.0001, 0.001]}),\n",
        "               ('LogisticRegression', LogisticRegression(random_state=42),\n",
        "               {'C': np.arange(0.1, 1.1, 0.1)}),\n",
        "               ('RandomForestClassifier', RandomForestClassifier(random_state=42),\n",
        "               {'n_estimators': [200, 250, 300],\n",
        "                'min_samples_leaf': np.arange(1, 4),\n",
        "                'max_features': [np.arange(0.3, 0.6, 0.1), 'sqrt'],\n",
        "                'max_samples': np.arange(0.4, 0.7, 0.1)\n",
        "               }),\n",
        "               ('BaggingClassifier', BaggingClassifier(random_state=42),\n",
        "               {'max_samples': [0.8, 0.9, 1.0], \n",
        "                'max_features': [0.7, 0.8, 0.9],\n",
        "                'n_estimators' : [30, 50, 70],\n",
        "               }),\n",
        "               ('AdaBoostClassifier', AdaBoostClassifier(random_state=42),\n",
        "               {'n_estimators': [100, 150, 200],\n",
        "                'learning_rate': [0.2, 0.05],\n",
        "                'base_estimator': [DecisionTreeClassifier(max_depth=1, random_state=42), \n",
        "                                   DecisionTreeClassifier(max_depth=2, random_state=42), \n",
        "                                   DecisionTreeClassifier(max_depth=3, random_state=42)],\n",
        "               }),\n",
        "               ('GradientBoostingClassifier', GradientBoostingClassifier(random_state=42),\n",
        "               {'n_estimators': np.arange(100, 150, 25),\n",
        "                'learning_rate': [0.2, 0.05, 1],\n",
        "                'subsample': [0.5, 0.7],\n",
        "                'max_features': [0.5, 0.7]\n",
        "               }),\n",
        "               ('XGBClassifier', XGBClassifier(random_state=42),\n",
        "               {'n_estimators': [150, 200, 250],\n",
        "                'scale_pos_weight': [5, 10],\n",
        "                'learning_rate': [0.1, 0.2],\n",
        "                'gamma': [0, 3, 5],\n",
        "                'subsample': [0.8, 0.9]\n",
        "               }),\n",
        "               ]"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Defining a function to evaluate the performance of models using cross-validation and compute various performance metrics on different datasets"
      ],
      "metadata": {
        "id": "eK8VKts1Xvtb"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {
        "id": "kSP1Au3wIhNZ"
      },
      "outputs": [],
      "source": [
        "def cv_simple(models_grid, X_train, y_train, X_valid, y_valid, title):\n",
        "  # Empty DataFrame to store all model's CV scores\n",
        "  results = pd.DataFrame()\n",
        "\n",
        "  # Type of scoring used to compare parameter combinations\n",
        "  scorer = make_scorer(recall_score)\n",
        "\n",
        "  # Empty DataFrame to store temporarty parameters\n",
        "  res = pd.DataFrame(columns=['cv_recalls', 'duration_train', 'duration_valid'])\n",
        "\n",
        "  # loop through all models to get the mean cross validated score\n",
        "  print(\"\\n\" \"Cross-Validation performance on training dataset:\" \"\\n\")\n",
        "\n",
        "  for model in models_grid:\n",
        "      start_time = time.time()\n",
        "      kfold = StratifiedKFold(n_splits=10, shuffle=True, random_state=42)\n",
        "\n",
        "      cv_result = cross_val_score(estimator=model[1], X=X_train, y=y_train, \n",
        "                                  scoring=scorer, cv=kfold)\n",
        "\n",
        "      res.loc[model[0], 'cv_recalls'] = cv_result\n",
        "      res.loc[model[0], 'duration_train'] = time.time() - start_time\n",
        "\n",
        "      print(f'\\t{model[0]}: {cv_result.mean():.5f}')\n",
        "      print(f'\\t\\tIteration duration: {time.time() - start_time:.2f} seconds')\n",
        "\n",
        "  # loop through all models to get the validation score\n",
        "  print(\"\\n\" \"Validation Performance:\" \"\\n\")\n",
        "\n",
        "  for model in models_grid:\n",
        "      start_time = time.time()\n",
        "      model[1].fit(X_train, y_train)\n",
        "      score = recall_score(y_valid, model[1].predict(X_valid))\n",
        "      \n",
        "      res.loc[model[0], 'duration_valid'] = time.time() - start_time\n",
        "\n",
        "      print(f'\\t{model[0]}: {score:.5f}')\n",
        "      print(f'\\t\\tIteration duration: {time.time() - start_time:.2f} seconds')\n",
        "\n",
        "  # loop through all models to collect and show models' performace \n",
        "  for model in models_grid:\n",
        "      start_time = time.time()\n",
        "\n",
        "      print(f'\\n\\x1b[2;37;42m{model[0]}:{\" \" * (101-len(model[0]))}\\x1b[0m')\n",
        "      model_perf = model_performance(model[1],\n",
        "                                    X_train, y_train, \n",
        "                                    X_valid, y_valid, \n",
        "                                    verbose=True, sets=['Training', 'Validation'])\n",
        "\n",
        "      model_perf.loc['Training', 'duration'] = res.loc[model[0], 'duration_train']\n",
        "      model_perf.loc['Training', 'cv_recall'] = res.loc[model[0], 'cv_recalls'].mean()\n",
        "      model_perf.loc['Validation', 'duration'] = res.loc[model[0], 'duration_valid']\n",
        "      model_perf = model_perf.reset_index()\n",
        "      model_perf['model'] = model[0]\n",
        "      results = pd.concat([results, model_perf], ignore_index=True)\n",
        "\n",
        "  # Boxolot with Cross Validation Results for all models\n",
        "  cvs = pd.DataFrame([list(q) for q in res['cv_recalls'].values], \n",
        "                     index=res.index).T\n",
        "  fig, ax = plt.subplots(figsize=(10, 5))\n",
        "  ax.boxplot(cvs)\n",
        "  ax.set_title(f'Classificators Performace - {title} Data')\n",
        "  ax.set_xticklabels(list(cvs.columns), rotation=90)\n",
        "  plt.show()\n",
        "\n",
        "  return results\n",
        "  "
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Defining a function that uses RandomizedSearchCV to tune the hyperparameters of various models and evaluates models' performance by computing performance metrics on different datasets."
      ],
      "metadata": {
        "id": "L5ypdd3XY5aP"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "metadata": {
        "id": "5mDLYSmnIoxN"
      },
      "outputs": [],
      "source": [
        "def cv_tuned(models, X_train, y_train, X_valid, y_valid, title):\n",
        "  # Empty DataFrame to store all model's scores\n",
        "  results = pd.DataFrame()\n",
        "\n",
        "  # Type of scoring used to compare parameter combinations\n",
        "  scorer = make_scorer(recall_score)\n",
        "\n",
        "  for model in models:\n",
        "    start_time = time.time()\n",
        "    randomized_cv = RandomizedSearchCV(estimator=model[1], \n",
        "                                      param_distributions=model[2], \n",
        "                                      n_iter=10, n_jobs = -1, \n",
        "                                      scoring=scorer, cv=5, random_state=42)\n",
        "    \n",
        "    #Fitting parameters in RandomizedSearchCV\n",
        "    model_fit = randomized_cv.fit(X_train, y_train)\n",
        "    duration = time.time() - start_time\n",
        "\n",
        "    print(f'\\n\\x1b[2;37;42m{model[0]}:{\" \" * (101-len(model[0]))}\\x1b[0m')\n",
        "    print(f'\\tBest parameters are:')\n",
        "    for e in model_fit.best_params_:\n",
        "      print(f'\\t\\t{e}: {model_fit.best_params_[e]}')\n",
        "    print(f'\\tCV score={model_fit.best_score_:.5f}')\n",
        "    print(f'\\tIteration duration: {time.time() - start_time:.2f} seconds')\n",
        "    print('-' * 101)\n",
        "\n",
        "    model_perf = model_performance(model_fit, X_train, y_train, X_valid, y_valid, \n",
        "                                   verbose=True, sets=['Training', 'Validation'])\n",
        "\n",
        "    model_perf.loc['Training', 'best_params'] = [model_fit.best_params_]\n",
        "    model_perf.loc['Training', 'duration'] = duration\n",
        "\n",
        "    model_perf.loc['Validation', 'best_params'] = [model_fit.best_params_]\n",
        "    model_perf.loc['Validation', 'duration'] = duration\n",
        "\n",
        "    model_perf = model_perf.reset_index()\n",
        "    model_perf['model'] = model[0]\n",
        "    results = pd.concat([results, model_perf], ignore_index=True)\n",
        "\n",
        "  return results\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "UvpMDcaaMKtI"
      },
      "source": [
        "# Data Overview"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "tIiCRwqZ54_C"
      },
      "source": [
        "The initial steps to get an overview of any dataset is to: \n",
        "- observe the first few rows of the dataset, to check whether the dataset has been loaded properly or not\n",
        "- get information about the number of rows and columns in the dataset\n",
        "- find out the data types of the columns to ensure that data is stored in the preferred format and the value of each property is as expected.\n",
        "- check the statistical summary of the dataset to get an overview of the numerical columns of the data\n",
        "- [x] Observations\n",
        "- [x] Sanity checks"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "DugFAZkuOGrc"
      },
      "source": [
        "## View the first and last 5 rows of the dataset"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 235
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        "id": "01hJQ7EfMKtK",
        "outputId": "db521bd9-e0e1-4f72-bdaf-be6809e961a5"
      },
      "outputs": [
        {
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              "         V1        V2        V3        V4        V5        V6        V7  \\\n",
              "0 -4.464606 -4.679129  3.101546  0.506130 -0.221083 -2.032511 -2.910870   \n",
              "1  3.365912  3.653381  0.909671 -1.367528  0.332016  2.358938  0.732600   \n",
              "2 -3.831843 -5.824444  0.634031 -2.418815 -1.773827  1.016824 -2.098941   \n",
              "3  1.618098  1.888342  7.046143 -1.147285  0.083080 -1.529780  0.207309   \n",
              "4 -0.111440  3.872488 -3.758361 -2.982897  3.792714  0.544960  0.205433   \n",
              "\n",
              "         V8        V9       V10  ...       V32       V33        V34       V35  \\\n",
              "0  0.050714 -1.522351  3.761892  ...  3.059700 -1.690440   2.846296  2.235198   \n",
              "1 -4.332135  0.565695 -0.101080  ... -1.795474  3.032780  -2.467514  1.894599   \n",
              "2 -3.173204 -2.081860  5.392621  ... -0.257101  0.803550   4.086219  2.292138   \n",
              "3 -2.493629  0.344926  2.118578  ... -3.584425 -2.577474   1.363769  0.622714   \n",
              "4  4.848994 -1.854920 -6.220023  ...  8.265896  6.629213 -10.068689  1.222987   \n",
              "\n",
              "        V36       V37       V38       V39       V40  Target  \n",
              "0  6.667486  0.443809 -2.369169  2.950578 -3.480324       0  \n",
              "1 -2.297780 -1.731048  5.908837 -0.386345  0.616242       0  \n",
              "2  5.360850  0.351993  2.940021  3.839160 -4.309402       0  \n",
              "3  5.550100 -1.526796  0.138853  3.101430 -1.277378       0  \n",
              "4 -3.229763  1.686909 -2.163896 -3.644622  6.510338       0  \n",
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              "      <th>V1</th>\n",
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              "      <td>-2.369169</td>\n",
              "      <td>2.950578</td>\n",
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              "      <td>0.909671</td>\n",
              "      <td>-1.367528</td>\n",
              "      <td>0.332016</td>\n",
              "      <td>2.358938</td>\n",
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              "      <td>-4.332135</td>\n",
              "      <td>0.565695</td>\n",
              "      <td>-0.101080</td>\n",
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              "      <td>-1.795474</td>\n",
              "      <td>3.032780</td>\n",
              "      <td>-2.467514</td>\n",
              "      <td>1.894599</td>\n",
              "      <td>-2.297780</td>\n",
              "      <td>-1.731048</td>\n",
              "      <td>5.908837</td>\n",
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              "      <td>-5.824444</td>\n",
              "      <td>0.634031</td>\n",
              "      <td>-2.418815</td>\n",
              "      <td>-1.773827</td>\n",
              "      <td>1.016824</td>\n",
              "      <td>-2.098941</td>\n",
              "      <td>-3.173204</td>\n",
              "      <td>-2.081860</td>\n",
              "      <td>5.392621</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.257101</td>\n",
              "      <td>0.803550</td>\n",
              "      <td>4.086219</td>\n",
              "      <td>2.292138</td>\n",
              "      <td>5.360850</td>\n",
              "      <td>0.351993</td>\n",
              "      <td>2.940021</td>\n",
              "      <td>3.839160</td>\n",
              "      <td>-4.309402</td>\n",
              "      <td>0</td>\n",
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              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1.618098</td>\n",
              "      <td>1.888342</td>\n",
              "      <td>7.046143</td>\n",
              "      <td>-1.147285</td>\n",
              "      <td>0.083080</td>\n",
              "      <td>-1.529780</td>\n",
              "      <td>0.207309</td>\n",
              "      <td>-2.493629</td>\n",
              "      <td>0.344926</td>\n",
              "      <td>2.118578</td>\n",
              "      <td>...</td>\n",
              "      <td>-3.584425</td>\n",
              "      <td>-2.577474</td>\n",
              "      <td>1.363769</td>\n",
              "      <td>0.622714</td>\n",
              "      <td>5.550100</td>\n",
              "      <td>-1.526796</td>\n",
              "      <td>0.138853</td>\n",
              "      <td>3.101430</td>\n",
              "      <td>-1.277378</td>\n",
              "      <td>0</td>\n",
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              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>-0.111440</td>\n",
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              "      <td>-2.982897</td>\n",
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          "metadata": {},
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              "             V1         V2        V3        V4        V5        V6        V7  \\\n",
              "19995 -2.071318  -1.088279 -0.796174 -3.011720 -2.287540  2.807310  0.481428   \n",
              "19996  2.890264   2.483069  5.643919  0.937053 -1.380870  0.412051 -1.593386   \n",
              "19997 -3.896979  -3.942407 -0.351364 -2.417462  1.107546 -1.527623 -3.519882   \n",
              "19998 -3.187322 -10.051662  5.695955 -4.370053 -5.354758 -1.873044 -3.947210   \n",
              "19999 -2.686903   1.961187  6.137088  2.600133  2.657241 -4.290882 -2.344267   \n",
              "\n",
              "             V8        V9       V10  ...       V32       V33       V34  \\\n",
              "19995  0.105171 -0.586599 -2.899398  ... -8.273996  5.745013  0.589014   \n",
              "19996 -5.762498  2.150096  0.272302  ... -4.159092  1.181466 -0.742412   \n",
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              "19999  0.974004 -1.027462  0.497421  ...  6.620811 -1.988786 -1.348901   \n",
              "\n",
              "            V35       V36       V37       V38       V39       V40  Target  \n",
              "19995 -0.649988 -3.043174  2.216461  0.608723  0.178193  2.927755       1  \n",
              "19996  5.368979 -0.693028 -1.668971  3.659954  0.819863 -1.987265       0  \n",
              "19997  1.855555  5.029209  2.082588 -6.409304  1.477138 -0.874148       0  \n",
              "19998  8.529894  8.450626  0.203958 -7.129918  4.249394 -6.112267       0  \n",
              "19999  3.951801  5.449706 -0.455411 -2.202056  1.678229 -1.974413       0  \n",
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              "      <th>V1</th>\n",
              "      <th>V2</th>\n",
              "      <th>V3</th>\n",
              "      <th>V4</th>\n",
              "      <th>V5</th>\n",
              "      <th>V6</th>\n",
              "      <th>V7</th>\n",
              "      <th>V8</th>\n",
              "      <th>V9</th>\n",
              "      <th>V10</th>\n",
              "      <th>...</th>\n",
              "      <th>V32</th>\n",
              "      <th>V33</th>\n",
              "      <th>V34</th>\n",
              "      <th>V35</th>\n",
              "      <th>V36</th>\n",
              "      <th>V37</th>\n",
              "      <th>V38</th>\n",
              "      <th>V39</th>\n",
              "      <th>V40</th>\n",
              "      <th>Target</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>19995</th>\n",
              "      <td>-2.071318</td>\n",
              "      <td>-1.088279</td>\n",
              "      <td>-0.796174</td>\n",
              "      <td>-3.011720</td>\n",
              "      <td>-2.287540</td>\n",
              "      <td>2.807310</td>\n",
              "      <td>0.481428</td>\n",
              "      <td>0.105171</td>\n",
              "      <td>-0.586599</td>\n",
              "      <td>-2.899398</td>\n",
              "      <td>...</td>\n",
              "      <td>-8.273996</td>\n",
              "      <td>5.745013</td>\n",
              "      <td>0.589014</td>\n",
              "      <td>-0.649988</td>\n",
              "      <td>-3.043174</td>\n",
              "      <td>2.216461</td>\n",
              "      <td>0.608723</td>\n",
              "      <td>0.178193</td>\n",
              "      <td>2.927755</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19996</th>\n",
              "      <td>2.890264</td>\n",
              "      <td>2.483069</td>\n",
              "      <td>5.643919</td>\n",
              "      <td>0.937053</td>\n",
              "      <td>-1.380870</td>\n",
              "      <td>0.412051</td>\n",
              "      <td>-1.593386</td>\n",
              "      <td>-5.762498</td>\n",
              "      <td>2.150096</td>\n",
              "      <td>0.272302</td>\n",
              "      <td>...</td>\n",
              "      <td>-4.159092</td>\n",
              "      <td>1.181466</td>\n",
              "      <td>-0.742412</td>\n",
              "      <td>5.368979</td>\n",
              "      <td>-0.693028</td>\n",
              "      <td>-1.668971</td>\n",
              "      <td>3.659954</td>\n",
              "      <td>0.819863</td>\n",
              "      <td>-1.987265</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19997</th>\n",
              "      <td>-3.896979</td>\n",
              "      <td>-3.942407</td>\n",
              "      <td>-0.351364</td>\n",
              "      <td>-2.417462</td>\n",
              "      <td>1.107546</td>\n",
              "      <td>-1.527623</td>\n",
              "      <td>-3.519882</td>\n",
              "      <td>2.054792</td>\n",
              "      <td>-0.233996</td>\n",
              "      <td>-0.357687</td>\n",
              "      <td>...</td>\n",
              "      <td>7.112162</td>\n",
              "      <td>1.476080</td>\n",
              "      <td>-3.953710</td>\n",
              "      <td>1.855555</td>\n",
              "      <td>5.029209</td>\n",
              "      <td>2.082588</td>\n",
              "      <td>-6.409304</td>\n",
              "      <td>1.477138</td>\n",
              "      <td>-0.874148</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19998</th>\n",
              "      <td>-3.187322</td>\n",
              "      <td>-10.051662</td>\n",
              "      <td>5.695955</td>\n",
              "      <td>-4.370053</td>\n",
              "      <td>-5.354758</td>\n",
              "      <td>-1.873044</td>\n",
              "      <td>-3.947210</td>\n",
              "      <td>0.679420</td>\n",
              "      <td>-2.389254</td>\n",
              "      <td>5.456756</td>\n",
              "      <td>...</td>\n",
              "      <td>0.402812</td>\n",
              "      <td>3.163661</td>\n",
              "      <td>3.752095</td>\n",
              "      <td>8.529894</td>\n",
              "      <td>8.450626</td>\n",
              "      <td>0.203958</td>\n",
              "      <td>-7.129918</td>\n",
              "      <td>4.249394</td>\n",
              "      <td>-6.112267</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19999</th>\n",
              "      <td>-2.686903</td>\n",
              "      <td>1.961187</td>\n",
              "      <td>6.137088</td>\n",
              "      <td>2.600133</td>\n",
              "      <td>2.657241</td>\n",
              "      <td>-4.290882</td>\n",
              "      <td>-2.344267</td>\n",
              "      <td>0.974004</td>\n",
              "      <td>-1.027462</td>\n",
              "      <td>0.497421</td>\n",
              "      <td>...</td>\n",
              "      <td>6.620811</td>\n",
              "      <td>-1.988786</td>\n",
              "      <td>-1.348901</td>\n",
              "      <td>3.951801</td>\n",
              "      <td>5.449706</td>\n",
              "      <td>-0.455411</td>\n",
              "      <td>-2.202056</td>\n",
              "      <td>1.678229</td>\n",
              "      <td>-1.974413</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 41 columns</p>\n",
              "</div>\n",
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              "\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
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              "\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-127c7933-a1db-4af5-8321-8fbbefee5941 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-127c7933-a1db-4af5-8321-8fbbefee5941');\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",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ],
      "source": [
        "train.tail()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 12,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 235
        },
        "id": "kxwVUGqoOsqg",
        "outputId": "ad64e91a-d629-4531-bac5-c3c5f4224f02"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "         V1        V2        V3        V4        V5        V6        V7  \\\n",
              "0 -0.613489 -3.819640  2.202302  1.300420 -1.184929 -4.495964 -1.835817   \n",
              "1  0.389608 -0.512341  0.527053 -2.576776 -1.016766  2.235112 -0.441301   \n",
              "2 -0.874861 -0.640632  4.084202 -1.590454  0.525855 -1.957592 -0.695367   \n",
              "3  0.238384  1.458607  4.014528  2.534478  1.196987 -3.117330 -0.924035   \n",
              "4  5.828225  2.768260 -1.234530  2.809264 -1.641648 -1.406698  0.568643   \n",
              "\n",
              "         V8        V9       V10  ...       V32       V33       V34       V35  \\\n",
              "0  4.722989  1.206140 -0.341909  ...  2.291204 -5.411388  0.870073  0.574479   \n",
              "1 -4.405744 -0.332869  1.966794  ... -2.474936  2.493582  0.315165  2.059288   \n",
              "2  1.347309 -1.732348  0.466500  ... -1.318888 -2.997464  0.459664  0.619774   \n",
              "3  0.269493  1.322436  0.702345  ...  3.517918 -3.074085 -0.284220  0.954576   \n",
              "4  0.965043  1.918379 -2.774855  ...  1.773841 -1.501573 -2.226702  4.776830   \n",
              "\n",
              "        V36       V37        V38       V39       V40  Target  \n",
              "0  4.157191  1.428093 -10.511342  0.454664 -1.448363       0  \n",
              "1  0.683859 -0.485452   5.128350  1.720744 -1.488235       0  \n",
              "2  5.631504  1.323512  -1.752154  1.808302  1.675748       0  \n",
              "3  3.029331 -1.367198  -3.412140  0.906000 -2.450889       0  \n",
              "4 -6.559698 -0.805551  -0.276007 -3.858207 -0.537694       0  \n",
              "\n",
              "[5 rows x 41 columns]"
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              "      <th></th>\n",
              "      <th>V1</th>\n",
              "      <th>V2</th>\n",
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              "      <th>V5</th>\n",
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              "      <th>V8</th>\n",
              "      <th>V9</th>\n",
              "      <th>V10</th>\n",
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              "      <th>V32</th>\n",
              "      <th>V33</th>\n",
              "      <th>V34</th>\n",
              "      <th>V35</th>\n",
              "      <th>V36</th>\n",
              "      <th>V37</th>\n",
              "      <th>V38</th>\n",
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              "      <th>Target</th>\n",
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              "      <th>0</th>\n",
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              "      <td>-4.495964</td>\n",
              "      <td>-1.835817</td>\n",
              "      <td>4.722989</td>\n",
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              "      <td>2.291204</td>\n",
              "      <td>-5.411388</td>\n",
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              "      <td>0.574479</td>\n",
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              "      <td>-10.511342</td>\n",
              "      <td>0.454664</td>\n",
              "      <td>-1.448363</td>\n",
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              "      <th>1</th>\n",
              "      <td>0.389608</td>\n",
              "      <td>-0.512341</td>\n",
              "      <td>0.527053</td>\n",
              "      <td>-2.576776</td>\n",
              "      <td>-1.016766</td>\n",
              "      <td>2.235112</td>\n",
              "      <td>-0.441301</td>\n",
              "      <td>-4.405744</td>\n",
              "      <td>-0.332869</td>\n",
              "      <td>1.966794</td>\n",
              "      <td>...</td>\n",
              "      <td>-2.474936</td>\n",
              "      <td>2.493582</td>\n",
              "      <td>0.315165</td>\n",
              "      <td>2.059288</td>\n",
              "      <td>0.683859</td>\n",
              "      <td>-0.485452</td>\n",
              "      <td>5.128350</td>\n",
              "      <td>1.720744</td>\n",
              "      <td>-1.488235</td>\n",
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              "      <th>2</th>\n",
              "      <td>-0.874861</td>\n",
              "      <td>-0.640632</td>\n",
              "      <td>4.084202</td>\n",
              "      <td>-1.590454</td>\n",
              "      <td>0.525855</td>\n",
              "      <td>-1.957592</td>\n",
              "      <td>-0.695367</td>\n",
              "      <td>1.347309</td>\n",
              "      <td>-1.732348</td>\n",
              "      <td>0.466500</td>\n",
              "      <td>...</td>\n",
              "      <td>-1.318888</td>\n",
              "      <td>-2.997464</td>\n",
              "      <td>0.459664</td>\n",
              "      <td>0.619774</td>\n",
              "      <td>5.631504</td>\n",
              "      <td>1.323512</td>\n",
              "      <td>-1.752154</td>\n",
              "      <td>1.808302</td>\n",
              "      <td>1.675748</td>\n",
              "      <td>0</td>\n",
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              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0.238384</td>\n",
              "      <td>1.458607</td>\n",
              "      <td>4.014528</td>\n",
              "      <td>2.534478</td>\n",
              "      <td>1.196987</td>\n",
              "      <td>-3.117330</td>\n",
              "      <td>-0.924035</td>\n",
              "      <td>0.269493</td>\n",
              "      <td>1.322436</td>\n",
              "      <td>0.702345</td>\n",
              "      <td>...</td>\n",
              "      <td>3.517918</td>\n",
              "      <td>-3.074085</td>\n",
              "      <td>-0.284220</td>\n",
              "      <td>0.954576</td>\n",
              "      <td>3.029331</td>\n",
              "      <td>-1.367198</td>\n",
              "      <td>-3.412140</td>\n",
              "      <td>0.906000</td>\n",
              "      <td>-2.450889</td>\n",
              "      <td>0</td>\n",
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              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5.828225</td>\n",
              "      <td>2.768260</td>\n",
              "      <td>-1.234530</td>\n",
              "      <td>2.809264</td>\n",
              "      <td>-1.641648</td>\n",
              "      <td>-1.406698</td>\n",
              "      <td>0.568643</td>\n",
              "      <td>0.965043</td>\n",
              "      <td>1.918379</td>\n",
              "      <td>-2.774855</td>\n",
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              "      <td>1.773841</td>\n",
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              "      <td>-2.226702</td>\n",
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              "      <td>-0.805551</td>\n",
              "      <td>-0.276007</td>\n",
              "      <td>-3.858207</td>\n",
              "      <td>-0.537694</td>\n",
              "      <td>0</td>\n",
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              "    }\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",
              "    [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",
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              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
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              "          document.querySelector('#df-3a75ba9c-8b59-4530-acd3-55feb2839e8c 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-3a75ba9c-8b59-4530-acd3-55feb2839e8c');\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",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ],
      "source": [
        "test.head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 13,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 235
        },
        "id": "5ZcYZjcNOsyo",
        "outputId": "8779e307-17a8-4496-801e-b624057d71ec"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "            V1        V2        V3        V4        V5        V6        V7  \\\n",
              "4995 -5.120451  1.634804  1.251259  4.035944  3.291204 -2.932230 -1.328662   \n",
              "4996 -5.172498  1.171653  1.579105  1.219922  2.529627 -0.668648 -2.618321   \n",
              "4997 -1.114136 -0.403576 -1.764875 -5.879475  3.571558  3.710802 -2.482952   \n",
              "4998 -1.703241  0.614650  6.220503 -0.104132  0.955916 -3.278706 -1.633855   \n",
              "4999 -0.603701  0.959550 -0.720995  8.229574 -1.815610 -2.275547 -2.574524   \n",
              "\n",
              "            V8        V9       V10  ...       V32       V33        V34  \\\n",
              "4995  1.754066 -2.984586  1.248633  ...  9.979118  0.063438   0.217281   \n",
              "4996 -2.000545  0.633791 -0.578938  ...  4.423900  2.603811  -2.152170   \n",
              "4997 -0.307614 -0.921945 -2.999141  ...  3.791778  7.481506 -10.061396   \n",
              "4998 -0.103936  1.388152 -1.065622  ... -4.100352 -5.949325   0.550372   \n",
              "4999 -1.041479  4.129645 -2.731288  ...  2.369776 -1.062408   0.790772   \n",
              "\n",
              "           V35       V36       V37       V38       V39       V40  Target  \n",
              "4995  3.036388  2.109323 -0.557433  1.938718  0.512674 -2.694194       0  \n",
              "4996  0.917401  2.156586  0.466963  0.470120  2.196756 -2.376515       0  \n",
              "4997 -0.387166  1.848509  1.818248 -1.245633 -1.260876  7.474682       0  \n",
              "4998 -1.573640  6.823936  2.139307 -4.036164  3.436051  0.579249       0  \n",
              "4999  4.951955 -7.440825 -0.069506 -0.918083 -2.291154 -5.362891       0  \n",
              "\n",
              "[5 rows x 41 columns]"
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              "      <th></th>\n",
              "      <th>V1</th>\n",
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              "      <th>V32</th>\n",
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              "      <th>V34</th>\n",
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              "      <th>V39</th>\n",
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              "      <th>4995</th>\n",
              "      <td>-5.120451</td>\n",
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              "      <td>-1.328662</td>\n",
              "      <td>1.754066</td>\n",
              "      <td>-2.984586</td>\n",
              "      <td>1.248633</td>\n",
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              "      <td>9.979118</td>\n",
              "      <td>0.063438</td>\n",
              "      <td>0.217281</td>\n",
              "      <td>3.036388</td>\n",
              "      <td>2.109323</td>\n",
              "      <td>-0.557433</td>\n",
              "      <td>1.938718</td>\n",
              "      <td>0.512674</td>\n",
              "      <td>-2.694194</td>\n",
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              "    <tr>\n",
              "      <th>4996</th>\n",
              "      <td>-5.172498</td>\n",
              "      <td>1.171653</td>\n",
              "      <td>1.579105</td>\n",
              "      <td>1.219922</td>\n",
              "      <td>2.529627</td>\n",
              "      <td>-0.668648</td>\n",
              "      <td>-2.618321</td>\n",
              "      <td>-2.000545</td>\n",
              "      <td>0.633791</td>\n",
              "      <td>-0.578938</td>\n",
              "      <td>...</td>\n",
              "      <td>4.423900</td>\n",
              "      <td>2.603811</td>\n",
              "      <td>-2.152170</td>\n",
              "      <td>0.917401</td>\n",
              "      <td>2.156586</td>\n",
              "      <td>0.466963</td>\n",
              "      <td>0.470120</td>\n",
              "      <td>2.196756</td>\n",
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              "      <th>4997</th>\n",
              "      <td>-1.114136</td>\n",
              "      <td>-0.403576</td>\n",
              "      <td>-1.764875</td>\n",
              "      <td>-5.879475</td>\n",
              "      <td>3.571558</td>\n",
              "      <td>3.710802</td>\n",
              "      <td>-2.482952</td>\n",
              "      <td>-0.307614</td>\n",
              "      <td>-0.921945</td>\n",
              "      <td>-2.999141</td>\n",
              "      <td>...</td>\n",
              "      <td>3.791778</td>\n",
              "      <td>7.481506</td>\n",
              "      <td>-10.061396</td>\n",
              "      <td>-0.387166</td>\n",
              "      <td>1.848509</td>\n",
              "      <td>1.818248</td>\n",
              "      <td>-1.245633</td>\n",
              "      <td>-1.260876</td>\n",
              "      <td>7.474682</td>\n",
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              "      <th>4998</th>\n",
              "      <td>-1.703241</td>\n",
              "      <td>0.614650</td>\n",
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              "      <td>-0.104132</td>\n",
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              "      <td>-0.103936</td>\n",
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              "      <td>...</td>\n",
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              "      <td>-5.949325</td>\n",
              "      <td>0.550372</td>\n",
              "      <td>-1.573640</td>\n",
              "      <td>6.823936</td>\n",
              "      <td>2.139307</td>\n",
              "      <td>-4.036164</td>\n",
              "      <td>3.436051</td>\n",
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              "      <th>4999</th>\n",
              "      <td>-0.603701</td>\n",
              "      <td>0.959550</td>\n",
              "      <td>-0.720995</td>\n",
              "      <td>8.229574</td>\n",
              "      <td>-1.815610</td>\n",
              "      <td>-2.275547</td>\n",
              "      <td>-2.574524</td>\n",
              "      <td>-1.041479</td>\n",
              "      <td>4.129645</td>\n",
              "      <td>-2.731288</td>\n",
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              "      <td>-1.062408</td>\n",
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              "      <td>-7.440825</td>\n",
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              "      <td>-2.291154</td>\n",
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              "      <td>0</td>\n",
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              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 41 columns</p>\n",
              "</div>\n",
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              "              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 0 24 24\"\n",
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              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
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              "\n",
              "    .colab-df-convert {\n",
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              "      border: none;\n",
              "      border-radius: 50%;\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
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              "  </style>\n",
              "\n",
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              "          document.querySelector('#df-1c8d088a-46f4-44ff-bf68-933fb1bba66d 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-1c8d088a-46f4-44ff-bf68-933fb1bba66d');\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",
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              "  "
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ],
      "source": [
        "test.tail()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mOffGngcOlJl"
      },
      "source": [
        "## Understand the shape of the `Train` and `Test` datasets"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 14,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mhjr-HakOqf3",
        "outputId": "dc41e659-a006-4216-c7d4-7acc0a9cafde"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(20000, 41)"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ],
      "source": [
        "train.shape"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 15,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2fCeD4TAOqq2",
        "outputId": "baa7660c-2cac-4b8a-ae14-d82bf809a707"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(5000, 41)"
            ]
          },
          "metadata": {},
          "execution_count": 15
        }
      ],
      "source": [
        "test.shape"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "fYQIMY2sO4iE"
      },
      "source": [
        "- The `Train` dataset has 20000 rows and 41 columns of data\n",
        "- The `Test` dataset has 5000 rows and 41 columns of data\n"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Find out the data types of the columns"
      ],
      "metadata": {
        "id": "vN-3vjn2bZQI"
      }
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "AIN3Lth6PWML"
      },
      "source": [
        "df.info()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 16,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8d-F9ntvO3wk",
        "outputId": "07007e5a-4c8d-47e6-a336-5512a323efc9"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 20000 entries, 0 to 19999\n",
            "Data columns (total 41 columns):\n",
            " #   Column  Non-Null Count  Dtype  \n",
            "---  ------  --------------  -----  \n",
            " 0   V1      19982 non-null  float64\n",
            " 1   V2      19982 non-null  float64\n",
            " 2   V3      20000 non-null  float64\n",
            " 3   V4      20000 non-null  float64\n",
            " 4   V5      20000 non-null  float64\n",
            " 5   V6      20000 non-null  float64\n",
            " 6   V7      20000 non-null  float64\n",
            " 7   V8      20000 non-null  float64\n",
            " 8   V9      20000 non-null  float64\n",
            " 9   V10     20000 non-null  float64\n",
            " 10  V11     20000 non-null  float64\n",
            " 11  V12     20000 non-null  float64\n",
            " 12  V13     20000 non-null  float64\n",
            " 13  V14     20000 non-null  float64\n",
            " 14  V15     20000 non-null  float64\n",
            " 15  V16     20000 non-null  float64\n",
            " 16  V17     20000 non-null  float64\n",
            " 17  V18     20000 non-null  float64\n",
            " 18  V19     20000 non-null  float64\n",
            " 19  V20     20000 non-null  float64\n",
            " 20  V21     20000 non-null  float64\n",
            " 21  V22     20000 non-null  float64\n",
            " 22  V23     20000 non-null  float64\n",
            " 23  V24     20000 non-null  float64\n",
            " 24  V25     20000 non-null  float64\n",
            " 25  V26     20000 non-null  float64\n",
            " 26  V27     20000 non-null  float64\n",
            " 27  V28     20000 non-null  float64\n",
            " 28  V29     20000 non-null  float64\n",
            " 29  V30     20000 non-null  float64\n",
            " 30  V31     20000 non-null  float64\n",
            " 31  V32     20000 non-null  float64\n",
            " 32  V33     20000 non-null  float64\n",
            " 33  V34     20000 non-null  float64\n",
            " 34  V35     20000 non-null  float64\n",
            " 35  V36     20000 non-null  float64\n",
            " 36  V37     20000 non-null  float64\n",
            " 37  V38     20000 non-null  float64\n",
            " 38  V39     20000 non-null  float64\n",
            " 39  V40     20000 non-null  float64\n",
            " 40  Target  20000 non-null  int64  \n",
            "dtypes: float64(40), int64(1)\n",
            "memory usage: 6.3 MB\n"
          ]
        }
      ],
      "source": [
        "train.info()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 17,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "FeSvUVXRPfdg",
        "outputId": "bb82913e-89ed-469f-a245-8de6b76693ca"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 5000 entries, 0 to 4999\n",
            "Data columns (total 41 columns):\n",
            " #   Column  Non-Null Count  Dtype  \n",
            "---  ------  --------------  -----  \n",
            " 0   V1      4995 non-null   float64\n",
            " 1   V2      4994 non-null   float64\n",
            " 2   V3      5000 non-null   float64\n",
            " 3   V4      5000 non-null   float64\n",
            " 4   V5      5000 non-null   float64\n",
            " 5   V6      5000 non-null   float64\n",
            " 6   V7      5000 non-null   float64\n",
            " 7   V8      5000 non-null   float64\n",
            " 8   V9      5000 non-null   float64\n",
            " 9   V10     5000 non-null   float64\n",
            " 10  V11     5000 non-null   float64\n",
            " 11  V12     5000 non-null   float64\n",
            " 12  V13     5000 non-null   float64\n",
            " 13  V14     5000 non-null   float64\n",
            " 14  V15     5000 non-null   float64\n",
            " 15  V16     5000 non-null   float64\n",
            " 16  V17     5000 non-null   float64\n",
            " 17  V18     5000 non-null   float64\n",
            " 18  V19     5000 non-null   float64\n",
            " 19  V20     5000 non-null   float64\n",
            " 20  V21     5000 non-null   float64\n",
            " 21  V22     5000 non-null   float64\n",
            " 22  V23     5000 non-null   float64\n",
            " 23  V24     5000 non-null   float64\n",
            " 24  V25     5000 non-null   float64\n",
            " 25  V26     5000 non-null   float64\n",
            " 26  V27     5000 non-null   float64\n",
            " 27  V28     5000 non-null   float64\n",
            " 28  V29     5000 non-null   float64\n",
            " 29  V30     5000 non-null   float64\n",
            " 30  V31     5000 non-null   float64\n",
            " 31  V32     5000 non-null   float64\n",
            " 32  V33     5000 non-null   float64\n",
            " 33  V34     5000 non-null   float64\n",
            " 34  V35     5000 non-null   float64\n",
            " 35  V36     5000 non-null   float64\n",
            " 36  V37     5000 non-null   float64\n",
            " 37  V38     5000 non-null   float64\n",
            " 38  V39     5000 non-null   float64\n",
            " 39  V40     5000 non-null   float64\n",
            " 40  Target  5000 non-null   int64  \n",
            "dtypes: float64(40), int64(1)\n",
            "memory usage: 1.6 MB\n"
          ]
        }
      ],
      "source": [
        "test.info()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "via6ffMuPflh"
      },
      "source": [
        "**Observations:**\n",
        "- There are 41 numeric values (40 floats and 1 int) in both datasets\n",
        "- All of predictors are of type `float64`\n",
        "- Target variable is of type `int64`\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "pZGf9ag6RVqa"
      },
      "source": [
        "## Checking for missing values"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 18,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "HcLmJTmWRVyz",
        "outputId": "3fb3487b-2f0d-47a4-c63b-ca976c8263a7"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Number of Null values in the Train dataset:\n",
            "V1    18\n",
            "V2    18\n",
            "dtype: int64\n",
            "Number of Null values in the Test dataset:\n",
            "V1    5\n",
            "V2    6\n",
            "dtype: int64\n"
          ]
        }
      ],
      "source": [
        "nulls = train.isna().sum()\n",
        "print('Number of Null values in the Train dataset:')\n",
        "print(nulls[nulls>0])\n",
        "\n",
        "nulls = test.isna().sum()\n",
        "print('Number of Null values in the Test dataset:')\n",
        "print(nulls[nulls>0])"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Observations:**\n",
        "* There are some (less than 0.2%) null values in the datasets:\n",
        "  - 18 null values in V1 and V2 columns in the `Train` dataset\n",
        "  - 5 null values in V1 and 6 null values in V2 columns in the `Test` dataset"
      ],
      "metadata": {
        "id": "gc188q5ybu_y"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 19,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 643
        },
        "id": "9hpRDDTsSGvg",
        "outputId": "c4780e41-d0f1-4646-bee6-234267c59ae4"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       V1        V2        V3        V4        V5        V6        V7  \\\n",
              "89    NaN -3.961403  2.787804 -4.712526 -3.007329 -1.541245 -0.881148   \n",
              "5941  NaN  1.008391  1.227702  5.397082  0.064230 -2.706919 -2.028368   \n",
              "6317  NaN -5.205346  1.997652 -3.707913 -1.042200 -1.593126 -2.653309   \n",
              "6464  NaN  2.146202  5.004415  4.192063  1.427887 -6.438263 -0.931339   \n",
              "7073  NaN  2.534010  2.762821 -1.673718 -1.942214 -0.029961  0.911323   \n",
              "8431  NaN -1.398710 -2.008106 -1.750341  0.932279 -1.290327 -0.270476   \n",
              "8439  NaN -3.840585  0.197220  4.147789  1.151400 -0.993298 -4.732363   \n",
              "11156 NaN -0.666978  3.715829  4.934000  1.667596 -4.356097 -2.823137   \n",
              "11287 NaN -2.561519 -0.180836 -7.194814 -1.043832  1.384845  1.306093   \n",
              "11456 NaN  1.299595  4.382858  1.583219 -0.076564  0.658770 -1.638530   \n",
              "12221 NaN -2.326319 -0.051978  0.615063 -0.895755 -2.437003  0.349826   \n",
              "12447 NaN  0.752613 -0.271099  1.301204  2.038697 -1.485203 -0.411939   \n",
              "13086 NaN  2.056243  3.330642  2.741497  2.783166 -0.444191 -2.015376   \n",
              "13411 NaN  2.704511  4.587169  1.867930  2.050133 -0.925076 -1.669496   \n",
              "14202 NaN  7.038653  2.144536 -3.201788  4.112972  3.375972 -1.337179   \n",
              "15520 NaN  1.382556  3.236896 -3.818363 -1.917264  0.437686  1.347540   \n",
              "16576 NaN  3.933815 -0.761930  2.651889  1.753614 -0.554092  1.829107   \n",
              "18104 NaN  1.492173  2.659206  0.222784 -0.303648 -1.347322  0.044309   \n",
              "\n",
              "             V8        V9       V10  ...       V32       V33        V34  \\\n",
              "89     1.476656  0.574700 -1.100884  ... -8.326069 -5.140552   1.121314   \n",
              "5941   0.534046  3.006797 -2.362238  ...  1.869502 -3.115298  -0.550197   \n",
              "6317   0.852280 -1.310489  2.406924  ...  3.074149 -0.067649  -0.277521   \n",
              "6464   3.794120 -0.683032 -0.738941  ...  5.231472 -5.113312   1.745687   \n",
              "7073  -3.199743  2.948610 -0.413229  ... -4.887077 -2.611526  -1.500807   \n",
              "8431   4.458834 -2.776270 -1.211766  ...  4.560244 -0.420834  -2.037313   \n",
              "8439   0.558966 -0.926683  0.457914  ...  6.818725  3.451213   0.241818   \n",
              "11156  0.373175 -0.709951  2.177428  ...  6.663446 -2.897697   3.068461   \n",
              "11287  1.559192 -2.992173  1.274543  ... -2.531655  0.560392  -1.153884   \n",
              "11456 -4.814763 -0.914819  2.811808  ...  1.772287  5.755242   1.203739   \n",
              "12221  2.092611 -2.933523  2.291272  ...  0.134995 -5.183424   5.251667   \n",
              "12447  0.980629  0.810336 -0.065120  ...  4.410397 -2.208567  -1.358706   \n",
              "13086 -0.887154 -1.110920  0.025289  ...  5.112126  4.675408  -1.709632   \n",
              "13411 -1.653803 -0.243383 -0.317316  ...  2.527207  3.625279  -1.200200   \n",
              "14202 -4.546371  1.941427 -5.466593  ...  0.157778  9.768106 -10.258190   \n",
              "15520 -2.036067  1.155712  0.306502  ... -5.414599 -0.896510  -1.057864   \n",
              "16576 -0.105409 -3.737081  1.036776  ...  3.486408  1.028094   2.845747   \n",
              "18104 -0.159095  1.108116 -0.572670  ... -1.007343 -2.229579  -0.870845   \n",
              "\n",
              "            V35       V36       V37       V38       V39       V40  Target  \n",
              "89    -0.305907  5.315007  3.750044 -5.631174  2.372485  2.195956       0  \n",
              "5941   1.713781 -2.256960  0.410992 -3.434400 -1.299388 -1.768734       0  \n",
              "6317   3.196840  7.016205  1.302334 -4.580096  2.956254 -2.363150       0  \n",
              "6464   2.587189  3.990777  0.610716 -4.273457  1.864568 -3.599079       0  \n",
              "7073   2.036186 -0.828979 -1.369591  0.572366 -0.132183 -0.322007       0  \n",
              "8431   1.109793  1.520594  2.113872 -2.252571 -0.939249  2.542411       0  \n",
              "8439   3.215765  1.203210  1.274857 -1.921229  0.578890 -2.837521       0  \n",
              "11156  2.486862  4.808548  0.069305 -1.215784  3.013674 -5.972586       0  \n",
              "11287 -0.019205  4.065248  0.978880 -0.571288  0.630374  3.919467       0  \n",
              "11456  5.663939  0.413630 -2.643934  5.529745  2.104536 -4.945350       0  \n",
              "12221  0.716371  3.210930  1.641985  1.543559  1.805163 -2.039510       0  \n",
              "12447 -1.725697  1.679060 -0.208564 -2.335547  0.112248 -0.542931       0  \n",
              "13086  2.429762  0.996644 -1.190509  1.207054  0.511023 -0.884200       0  \n",
              "13411  2.328028  1.666937 -0.943228  0.946846  1.655145 -1.665439       0  \n",
              "14202  0.513864 -1.974958 -0.029436  3.127486  0.009482  4.538125       0  \n",
              "15520  1.417365  1.161990 -1.147123 -0.048258  0.604532  0.814557       0  \n",
              "16576  1.744060 -1.999615 -0.783041  8.698449  0.352489 -2.005397       0  \n",
              "18104  1.299595  0.667952 -0.503349 -1.485419 -0.153722  0.156501       0  \n",
              "\n",
              "[18 rows x 41 columns]"
            ],
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>V1</th>\n",
              "      <th>V2</th>\n",
              "      <th>V3</th>\n",
              "      <th>V4</th>\n",
              "      <th>V5</th>\n",
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              "      <th>V8</th>\n",
              "      <th>V9</th>\n",
              "      <th>V10</th>\n",
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              "      <th>V32</th>\n",
              "      <th>V33</th>\n",
              "      <th>V34</th>\n",
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              "      <th>V36</th>\n",
              "      <th>V37</th>\n",
              "      <th>V38</th>\n",
              "      <th>V39</th>\n",
              "      <th>V40</th>\n",
              "      <th>Target</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>89</th>\n",
              "      <td>NaN</td>\n",
              "      <td>-3.961403</td>\n",
              "      <td>2.787804</td>\n",
              "      <td>-4.712526</td>\n",
              "      <td>-3.007329</td>\n",
              "      <td>-1.541245</td>\n",
              "      <td>-0.881148</td>\n",
              "      <td>1.476656</td>\n",
              "      <td>0.574700</td>\n",
              "      <td>-1.100884</td>\n",
              "      <td>...</td>\n",
              "      <td>-8.326069</td>\n",
              "      <td>-5.140552</td>\n",
              "      <td>1.121314</td>\n",
              "      <td>-0.305907</td>\n",
              "      <td>5.315007</td>\n",
              "      <td>3.750044</td>\n",
              "      <td>-5.631174</td>\n",
              "      <td>2.372485</td>\n",
              "      <td>2.195956</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5941</th>\n",
              "      <td>NaN</td>\n",
              "      <td>1.008391</td>\n",
              "      <td>1.227702</td>\n",
              "      <td>5.397082</td>\n",
              "      <td>0.064230</td>\n",
              "      <td>-2.706919</td>\n",
              "      <td>-2.028368</td>\n",
              "      <td>0.534046</td>\n",
              "      <td>3.006797</td>\n",
              "      <td>-2.362238</td>\n",
              "      <td>...</td>\n",
              "      <td>1.869502</td>\n",
              "      <td>-3.115298</td>\n",
              "      <td>-0.550197</td>\n",
              "      <td>1.713781</td>\n",
              "      <td>-2.256960</td>\n",
              "      <td>0.410992</td>\n",
              "      <td>-3.434400</td>\n",
              "      <td>-1.299388</td>\n",
              "      <td>-1.768734</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6317</th>\n",
              "      <td>NaN</td>\n",
              "      <td>-5.205346</td>\n",
              "      <td>1.997652</td>\n",
              "      <td>-3.707913</td>\n",
              "      <td>-1.042200</td>\n",
              "      <td>-1.593126</td>\n",
              "      <td>-2.653309</td>\n",
              "      <td>0.852280</td>\n",
              "      <td>-1.310489</td>\n",
              "      <td>2.406924</td>\n",
              "      <td>...</td>\n",
              "      <td>3.074149</td>\n",
              "      <td>-0.067649</td>\n",
              "      <td>-0.277521</td>\n",
              "      <td>3.196840</td>\n",
              "      <td>7.016205</td>\n",
              "      <td>1.302334</td>\n",
              "      <td>-4.580096</td>\n",
              "      <td>2.956254</td>\n",
              "      <td>-2.363150</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6464</th>\n",
              "      <td>NaN</td>\n",
              "      <td>2.146202</td>\n",
              "      <td>5.004415</td>\n",
              "      <td>4.192063</td>\n",
              "      <td>1.427887</td>\n",
              "      <td>-6.438263</td>\n",
              "      <td>-0.931339</td>\n",
              "      <td>3.794120</td>\n",
              "      <td>-0.683032</td>\n",
              "      <td>-0.738941</td>\n",
              "      <td>...</td>\n",
              "      <td>5.231472</td>\n",
              "      <td>-5.113312</td>\n",
              "      <td>1.745687</td>\n",
              "      <td>2.587189</td>\n",
              "      <td>3.990777</td>\n",
              "      <td>0.610716</td>\n",
              "      <td>-4.273457</td>\n",
              "      <td>1.864568</td>\n",
              "      <td>-3.599079</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7073</th>\n",
              "      <td>NaN</td>\n",
              "      <td>2.534010</td>\n",
              "      <td>2.762821</td>\n",
              "      <td>-1.673718</td>\n",
              "      <td>-1.942214</td>\n",
              "      <td>-0.029961</td>\n",
              "      <td>0.911323</td>\n",
              "      <td>-3.199743</td>\n",
              "      <td>2.948610</td>\n",
              "      <td>-0.413229</td>\n",
              "      <td>...</td>\n",
              "      <td>-4.887077</td>\n",
              "      <td>-2.611526</td>\n",
              "      <td>-1.500807</td>\n",
              "      <td>2.036186</td>\n",
              "      <td>-0.828979</td>\n",
              "      <td>-1.369591</td>\n",
              "      <td>0.572366</td>\n",
              "      <td>-0.132183</td>\n",
              "      <td>-0.322007</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8431</th>\n",
              "      <td>NaN</td>\n",
              "      <td>-1.398710</td>\n",
              "      <td>-2.008106</td>\n",
              "      <td>-1.750341</td>\n",
              "      <td>0.932279</td>\n",
              "      <td>-1.290327</td>\n",
              "      <td>-0.270476</td>\n",
              "      <td>4.458834</td>\n",
              "      <td>-2.776270</td>\n",
              "      <td>-1.211766</td>\n",
              "      <td>...</td>\n",
              "      <td>4.560244</td>\n",
              "      <td>-0.420834</td>\n",
              "      <td>-2.037313</td>\n",
              "      <td>1.109793</td>\n",
              "      <td>1.520594</td>\n",
              "      <td>2.113872</td>\n",
              "      <td>-2.252571</td>\n",
              "      <td>-0.939249</td>\n",
              "      <td>2.542411</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8439</th>\n",
              "      <td>NaN</td>\n",
              "      <td>-3.840585</td>\n",
              "      <td>0.197220</td>\n",
              "      <td>4.147789</td>\n",
              "      <td>1.151400</td>\n",
              "      <td>-0.993298</td>\n",
              "      <td>-4.732363</td>\n",
              "      <td>0.558966</td>\n",
              "      <td>-0.926683</td>\n",
              "      <td>0.457914</td>\n",
              "      <td>...</td>\n",
              "      <td>6.818725</td>\n",
              "      <td>3.451213</td>\n",
              "      <td>0.241818</td>\n",
              "      <td>3.215765</td>\n",
              "      <td>1.203210</td>\n",
              "      <td>1.274857</td>\n",
              "      <td>-1.921229</td>\n",
              "      <td>0.578890</td>\n",
              "      <td>-2.837521</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11156</th>\n",
              "      <td>NaN</td>\n",
              "      <td>-0.666978</td>\n",
              "      <td>3.715829</td>\n",
              "      <td>4.934000</td>\n",
              "      <td>1.667596</td>\n",
              "      <td>-4.356097</td>\n",
              "      <td>-2.823137</td>\n",
              "      <td>0.373175</td>\n",
              "      <td>-0.709951</td>\n",
              "      <td>2.177428</td>\n",
              "      <td>...</td>\n",
              "      <td>6.663446</td>\n",
              "      <td>-2.897697</td>\n",
              "      <td>3.068461</td>\n",
              "      <td>2.486862</td>\n",
              "      <td>4.808548</td>\n",
              "      <td>0.069305</td>\n",
              "      <td>-1.215784</td>\n",
              "      <td>3.013674</td>\n",
              "      <td>-5.972586</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11287</th>\n",
              "      <td>NaN</td>\n",
              "      <td>-2.561519</td>\n",
              "      <td>-0.180836</td>\n",
              "      <td>-7.194814</td>\n",
              "      <td>-1.043832</td>\n",
              "      <td>1.384845</td>\n",
              "      <td>1.306093</td>\n",
              "      <td>1.559192</td>\n",
              "      <td>-2.992173</td>\n",
              "      <td>1.274543</td>\n",
              "      <td>...</td>\n",
              "      <td>-2.531655</td>\n",
              "      <td>0.560392</td>\n",
              "      <td>-1.153884</td>\n",
              "      <td>-0.019205</td>\n",
              "      <td>4.065248</td>\n",
              "      <td>0.978880</td>\n",
              "      <td>-0.571288</td>\n",
              "      <td>0.630374</td>\n",
              "      <td>3.919467</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11456</th>\n",
              "      <td>NaN</td>\n",
              "      <td>1.299595</td>\n",
              "      <td>4.382858</td>\n",
              "      <td>1.583219</td>\n",
              "      <td>-0.076564</td>\n",
              "      <td>0.658770</td>\n",
              "      <td>-1.638530</td>\n",
              "      <td>-4.814763</td>\n",
              "      <td>-0.914819</td>\n",
              "      <td>2.811808</td>\n",
              "      <td>...</td>\n",
              "      <td>1.772287</td>\n",
              "      <td>5.755242</td>\n",
              "      <td>1.203739</td>\n",
              "      <td>5.663939</td>\n",
              "      <td>0.413630</td>\n",
              "      <td>-2.643934</td>\n",
              "      <td>5.529745</td>\n",
              "      <td>2.104536</td>\n",
              "      <td>-4.945350</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12221</th>\n",
              "      <td>NaN</td>\n",
              "      <td>-2.326319</td>\n",
              "      <td>-0.051978</td>\n",
              "      <td>0.615063</td>\n",
              "      <td>-0.895755</td>\n",
              "      <td>-2.437003</td>\n",
              "      <td>0.349826</td>\n",
              "      <td>2.092611</td>\n",
              "      <td>-2.933523</td>\n",
              "      <td>2.291272</td>\n",
              "      <td>...</td>\n",
              "      <td>0.134995</td>\n",
              "      <td>-5.183424</td>\n",
              "      <td>5.251667</td>\n",
              "      <td>0.716371</td>\n",
              "      <td>3.210930</td>\n",
              "      <td>1.641985</td>\n",
              "      <td>1.543559</td>\n",
              "      <td>1.805163</td>\n",
              "      <td>-2.039510</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12447</th>\n",
              "      <td>NaN</td>\n",
              "      <td>0.752613</td>\n",
              "      <td>-0.271099</td>\n",
              "      <td>1.301204</td>\n",
              "      <td>2.038697</td>\n",
              "      <td>-1.485203</td>\n",
              "      <td>-0.411939</td>\n",
              "      <td>0.980629</td>\n",
              "      <td>0.810336</td>\n",
              "      <td>-0.065120</td>\n",
              "      <td>...</td>\n",
              "      <td>4.410397</td>\n",
              "      <td>-2.208567</td>\n",
              "      <td>-1.358706</td>\n",
              "      <td>-1.725697</td>\n",
              "      <td>1.679060</td>\n",
              "      <td>-0.208564</td>\n",
              "      <td>-2.335547</td>\n",
              "      <td>0.112248</td>\n",
              "      <td>-0.542931</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13086</th>\n",
              "      <td>NaN</td>\n",
              "      <td>2.056243</td>\n",
              "      <td>3.330642</td>\n",
              "      <td>2.741497</td>\n",
              "      <td>2.783166</td>\n",
              "      <td>-0.444191</td>\n",
              "      <td>-2.015376</td>\n",
              "      <td>-0.887154</td>\n",
              "      <td>-1.110920</td>\n",
              "      <td>0.025289</td>\n",
              "      <td>...</td>\n",
              "      <td>5.112126</td>\n",
              "      <td>4.675408</td>\n",
              "      <td>-1.709632</td>\n",
              "      <td>2.429762</td>\n",
              "      <td>0.996644</td>\n",
              "      <td>-1.190509</td>\n",
              "      <td>1.207054</td>\n",
              "      <td>0.511023</td>\n",
              "      <td>-0.884200</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13411</th>\n",
              "      <td>NaN</td>\n",
              "      <td>2.704511</td>\n",
              "      <td>4.587169</td>\n",
              "      <td>1.867930</td>\n",
              "      <td>2.050133</td>\n",
              "      <td>-0.925076</td>\n",
              "      <td>-1.669496</td>\n",
              "      <td>-1.653803</td>\n",
              "      <td>-0.243383</td>\n",
              "      <td>-0.317316</td>\n",
              "      <td>...</td>\n",
              "      <td>2.527207</td>\n",
              "      <td>3.625279</td>\n",
              "      <td>-1.200200</td>\n",
              "      <td>2.328028</td>\n",
              "      <td>1.666937</td>\n",
              "      <td>-0.943228</td>\n",
              "      <td>0.946846</td>\n",
              "      <td>1.655145</td>\n",
              "      <td>-1.665439</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14202</th>\n",
              "      <td>NaN</td>\n",
              "      <td>7.038653</td>\n",
              "      <td>2.144536</td>\n",
              "      <td>-3.201788</td>\n",
              "      <td>4.112972</td>\n",
              "      <td>3.375972</td>\n",
              "      <td>-1.337179</td>\n",
              "      <td>-4.546371</td>\n",
              "      <td>1.941427</td>\n",
              "      <td>-5.466593</td>\n",
              "      <td>...</td>\n",
              "      <td>0.157778</td>\n",
              "      <td>9.768106</td>\n",
              "      <td>-10.258190</td>\n",
              "      <td>0.513864</td>\n",
              "      <td>-1.974958</td>\n",
              "      <td>-0.029436</td>\n",
              "      <td>3.127486</td>\n",
              "      <td>0.009482</td>\n",
              "      <td>4.538125</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15520</th>\n",
              "      <td>NaN</td>\n",
              "      <td>1.382556</td>\n",
              "      <td>3.236896</td>\n",
              "      <td>-3.818363</td>\n",
              "      <td>-1.917264</td>\n",
              "      <td>0.437686</td>\n",
              "      <td>1.347540</td>\n",
              "      <td>-2.036067</td>\n",
              "      <td>1.155712</td>\n",
              "      <td>0.306502</td>\n",
              "      <td>...</td>\n",
              "      <td>-5.414599</td>\n",
              "      <td>-0.896510</td>\n",
              "      <td>-1.057864</td>\n",
              "      <td>1.417365</td>\n",
              "      <td>1.161990</td>\n",
              "      <td>-1.147123</td>\n",
              "      <td>-0.048258</td>\n",
              "      <td>0.604532</td>\n",
              "      <td>0.814557</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16576</th>\n",
              "      <td>NaN</td>\n",
              "      <td>3.933815</td>\n",
              "      <td>-0.761930</td>\n",
              "      <td>2.651889</td>\n",
              "      <td>1.753614</td>\n",
              "      <td>-0.554092</td>\n",
              "      <td>1.829107</td>\n",
              "      <td>-0.105409</td>\n",
              "      <td>-3.737081</td>\n",
              "      <td>1.036776</td>\n",
              "      <td>...</td>\n",
              "      <td>3.486408</td>\n",
              "      <td>1.028094</td>\n",
              "      <td>2.845747</td>\n",
              "      <td>1.744060</td>\n",
              "      <td>-1.999615</td>\n",
              "      <td>-0.783041</td>\n",
              "      <td>8.698449</td>\n",
              "      <td>0.352489</td>\n",
              "      <td>-2.005397</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18104</th>\n",
              "      <td>NaN</td>\n",
              "      <td>1.492173</td>\n",
              "      <td>2.659206</td>\n",
              "      <td>0.222784</td>\n",
              "      <td>-0.303648</td>\n",
              "      <td>-1.347322</td>\n",
              "      <td>0.044309</td>\n",
              "      <td>-0.159095</td>\n",
              "      <td>1.108116</td>\n",
              "      <td>-0.572670</td>\n",
              "      <td>...</td>\n",
              "      <td>-1.007343</td>\n",
              "      <td>-2.229579</td>\n",
              "      <td>-0.870845</td>\n",
              "      <td>1.299595</td>\n",
              "      <td>0.667952</td>\n",
              "      <td>-0.503349</td>\n",
              "      <td>-1.485419</td>\n",
              "      <td>-0.153722</td>\n",
              "      <td>0.156501</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>18 rows × 41 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-0cbee1e8-eabb-4581-a30c-48510c44fc23')\"\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 0 24 24\"\n",
              "       width=\"24px\">\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\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",
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              "\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",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
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              "    [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",
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              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-0cbee1e8-eabb-4581-a30c-48510c44fc23 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-0cbee1e8-eabb-4581-a30c-48510c44fc23');\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",
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              "          element.appendChild(docLink);\n",
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              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 19
        }
      ],
      "source": [
        "train[train.V1.isnull()]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 20,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 643
        },
        "id": "R_SKKgZeSZD4",
        "outputId": "79d80485-13e6-4196-d645-f33e5e3e801a"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "             V1  V2        V3        V4        V5        V6        V7  \\\n",
              "613   -2.048681 NaN -1.623885 -3.324224  0.152256  0.600157 -1.812802   \n",
              "2236  -3.760658 NaN  0.194954 -1.637958  1.261479 -1.573947 -3.685700   \n",
              "2508  -1.430888 NaN  0.659576 -2.876402  1.150137 -0.785760 -1.560174   \n",
              "4653   5.465769 NaN  4.540947 -2.916550  0.399752  2.798925  0.029477   \n",
              "6810  -2.631454 NaN  2.330188  1.090080  0.603973 -1.139383 -0.690121   \n",
              "7788  -4.203459 NaN  2.953868  0.584466  4.103940 -0.639211 -2.810799   \n",
              "8483  -4.484232 NaN  1.200644 -2.042064  2.779443 -0.801748 -5.403548   \n",
              "8894   3.263555 NaN  8.446574 -3.253218 -3.417978 -2.995838 -0.669271   \n",
              "8947  -3.793170 NaN  0.719610  2.306296  0.934728 -0.984321  0.504867   \n",
              "9362   2.662045 NaN  2.980068  4.430762 -0.237769  0.671919  0.380068   \n",
              "9425  -2.354134 NaN  2.053893  0.811660  2.540366 -0.924875 -0.208380   \n",
              "9848  -1.763501 NaN  2.845012 -2.753083 -0.811848 -0.101166 -1.382141   \n",
              "11637 -2.270541 NaN  1.710061  1.157522 -0.355177 -5.449480 -0.786321   \n",
              "12339 -1.663687 NaN -0.712286 -4.346935  1.391670 -0.093951 -2.163175   \n",
              "15913  0.768122 NaN  5.296110  0.043018 -1.173729 -2.248575  0.956395   \n",
              "18342 -0.928572 NaN  2.375506 -1.236914  3.228744 -2.100088 -2.189908   \n",
              "18343 -2.377369 NaN -0.009173 -1.471979  1.295482  0.724894 -1.122797   \n",
              "18907 -0.119181 NaN  3.657612 -1.231802  1.946873 -0.119089  0.652414   \n",
              "\n",
              "             V8        V9       V10  ...        V32       V33       V34  \\\n",
              "613    0.852194 -1.522600  0.211071  ...   3.264218  2.379064 -2.457084   \n",
              "2236   1.575651 -0.309823 -0.137656  ...   7.620821  1.695061 -3.956354   \n",
              "2508   2.898635 -2.346989 -0.217607  ...   6.279266  3.323914 -4.047760   \n",
              "4653  -7.334071  1.122874  1.695269  ...  -1.535753  4.596212 -4.103525   \n",
              "6810  -1.358935  0.355568 -1.189176  ...  -0.950215  0.209717  0.448728   \n",
              "7788  -0.112492 -1.362768 -0.800101  ...  12.522374  9.502488 -7.152953   \n",
              "8483  -1.225314  1.485831 -0.974382  ...   9.467401  4.281421 -7.588117   \n",
              "8894  -0.161283 -0.666870  3.133527  ...  -4.242730 -3.122680  2.522415   \n",
              "8947  -0.441008 -2.767177  1.734671  ...   1.527720 -0.496910  3.789736   \n",
              "9362  -7.646684  4.434754 -0.746393  ...  -5.493590 -1.104656  1.224987   \n",
              "9425  -0.562864 -0.140210 -2.146916  ...  -0.621103 -0.896509 -1.181480   \n",
              "9848  -1.105042 -0.054339  0.159742  ...  -2.158880  1.859682 -0.337278   \n",
              "11637  3.936176 -1.576138  0.800881  ...   2.651480 -8.429332  3.511387   \n",
              "12339 -0.380573  0.031191 -0.658845  ...   0.306588 -2.690990 -3.111879   \n",
              "15913 -0.089941 -0.241678 -1.061413  ...  -7.720265 -4.518617  3.182253   \n",
              "18342  0.588644  1.955973 -5.008491  ...   1.613181 -1.820569 -6.664808   \n",
              "18343 -3.190475  3.250575 -4.861648  ...  -5.093149  0.439355 -3.167241   \n",
              "18907 -1.490208 -0.033631 -2.556604  ...  -4.670353 -0.593916 -1.650592   \n",
              "\n",
              "            V35       V36       V37       V38       V39       V40  Target  \n",
              "613    1.719365  2.537010  1.701780 -1.434535  0.597365  0.739238       0  \n",
              "2236   2.707644  4.657387  1.619307 -5.537285  1.246650 -1.162793       0  \n",
              "2508   3.119220  3.336260  0.603524 -3.781725 -0.157478  1.503298       0  \n",
              "4653   4.295524  0.152672 -3.726700  6.562692  0.706452 -0.461696       0  \n",
              "6810   1.046063  0.536937  0.763187  1.728621  1.885821 -1.701774       0  \n",
              "7788   5.668769  1.249833 -2.158520 -0.954461 -0.002385 -1.546808       0  \n",
              "8483   3.266825  5.232311  1.278590 -5.370513  1.984130 -1.643391       0  \n",
              "8894   5.283805  7.291310 -0.867555 -4.315230  3.124488 -2.393239       0  \n",
              "8947   1.130689  0.618278 -0.111146  5.708912  1.542366 -2.481019       0  \n",
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              "        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>V1</th>\n",
              "      <th>V2</th>\n",
              "      <th>V3</th>\n",
              "      <th>V4</th>\n",
              "      <th>V5</th>\n",
              "      <th>V6</th>\n",
              "      <th>V7</th>\n",
              "      <th>V8</th>\n",
              "      <th>V9</th>\n",
              "      <th>V10</th>\n",
              "      <th>...</th>\n",
              "      <th>V32</th>\n",
              "      <th>V33</th>\n",
              "      <th>V34</th>\n",
              "      <th>V35</th>\n",
              "      <th>V36</th>\n",
              "      <th>V37</th>\n",
              "      <th>V38</th>\n",
              "      <th>V39</th>\n",
              "      <th>V40</th>\n",
              "      <th>Target</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>709</th>\n",
              "      <td>3.171300</td>\n",
              "      <td>NaN</td>\n",
              "      <td>-0.899604</td>\n",
              "      <td>-7.687193</td>\n",
              "      <td>-1.844379</td>\n",
              "      <td>2.229502</td>\n",
              "      <td>0.649609</td>\n",
              "      <td>0.680742</td>\n",
              "      <td>-0.079613</td>\n",
              "      <td>-3.926869</td>\n",
              "      <td>...</td>\n",
              "      <td>-8.569958</td>\n",
              "      <td>1.198974</td>\n",
              "      <td>-3.747194</td>\n",
              "      <td>-0.834087</td>\n",
              "      <td>0.364598</td>\n",
              "      <td>3.687177</td>\n",
              "      <td>-1.450631</td>\n",
              "      <td>-0.012682</td>\n",
              "      <td>6.569833</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1777</th>\n",
              "      <td>1.255877</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1.123121</td>\n",
              "      <td>0.347719</td>\n",
              "      <td>-0.199314</td>\n",
              "      <td>0.542522</td>\n",
              "      <td>-0.904536</td>\n",
              "      <td>-2.398356</td>\n",
              "      <td>0.228689</td>\n",
              "      <td>0.245489</td>\n",
              "      <td>...</td>\n",
              "      <td>0.851358</td>\n",
              "      <td>1.657839</td>\n",
              "      <td>-1.410919</td>\n",
              "      <td>3.587088</td>\n",
              "      <td>-1.116910</td>\n",
              "      <td>-0.865736</td>\n",
              "      <td>2.766820</td>\n",
              "      <td>-0.368560</td>\n",
              "      <td>-0.864084</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1869</th>\n",
              "      <td>-1.272832</td>\n",
              "      <td>NaN</td>\n",
              "      <td>4.426359</td>\n",
              "      <td>-3.013970</td>\n",
              "      <td>-1.294693</td>\n",
              "      <td>-0.883173</td>\n",
              "      <td>-1.731633</td>\n",
              "      <td>0.098774</td>\n",
              "      <td>-0.991360</td>\n",
              "      <td>2.495756</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.396983</td>\n",
              "      <td>1.190134</td>\n",
              "      <td>0.629071</td>\n",
              "      <td>2.411258</td>\n",
              "      <td>6.166668</td>\n",
              "      <td>-0.140616</td>\n",
              "      <td>-4.208798</td>\n",
              "      <td>2.623088</td>\n",
              "      <td>-1.368893</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2741</th>\n",
              "      <td>-2.938927</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2.913242</td>\n",
              "      <td>1.431121</td>\n",
              "      <td>4.003345</td>\n",
              "      <td>-4.743048</td>\n",
              "      <td>-2.450111</td>\n",
              "      <td>3.795883</td>\n",
              "      <td>-0.339877</td>\n",
              "      <td>-2.897700</td>\n",
              "      <td>...</td>\n",
              "      <td>12.077656</td>\n",
              "      <td>0.671770</td>\n",
              "      <td>-6.354040</td>\n",
              "      <td>3.887011</td>\n",
              "      <td>3.420416</td>\n",
              "      <td>0.506994</td>\n",
              "      <td>-5.913055</td>\n",
              "      <td>0.214129</td>\n",
              "      <td>-0.931294</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3266</th>\n",
              "      <td>5.896134</td>\n",
              "      <td>NaN</td>\n",
              "      <td>7.342806</td>\n",
              "      <td>-1.052112</td>\n",
              "      <td>-1.393952</td>\n",
              "      <td>-0.410402</td>\n",
              "      <td>0.392391</td>\n",
              "      <td>-6.141263</td>\n",
              "      <td>2.100145</td>\n",
              "      <td>1.897655</td>\n",
              "      <td>...</td>\n",
              "      <td>-5.652135</td>\n",
              "      <td>-1.973205</td>\n",
              "      <td>0.275744</td>\n",
              "      <td>3.894656</td>\n",
              "      <td>2.108591</td>\n",
              "      <td>-2.803778</td>\n",
              "      <td>3.971349</td>\n",
              "      <td>2.233942</td>\n",
              "      <td>-2.542753</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4186</th>\n",
              "      <td>5.034513</td>\n",
              "      <td>NaN</td>\n",
              "      <td>4.450708</td>\n",
              "      <td>-6.077425</td>\n",
              "      <td>0.445417</td>\n",
              "      <td>2.491588</td>\n",
              "      <td>1.958447</td>\n",
              "      <td>-5.311945</td>\n",
              "      <td>-1.397204</td>\n",
              "      <td>2.755499</td>\n",
              "      <td>...</td>\n",
              "      <td>-5.133693</td>\n",
              "      <td>1.139969</td>\n",
              "      <td>-1.421471</td>\n",
              "      <td>0.822456</td>\n",
              "      <td>4.099736</td>\n",
              "      <td>-2.152178</td>\n",
              "      <td>7.063377</td>\n",
              "      <td>2.377923</td>\n",
              "      <td>1.906096</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>6 rows × 41 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-ad1be7d1-1a56-4d47-babb-5b1a3c9843f1')\"\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 0 24 24\"\n",
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              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
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              "\n",
              "    .colab-df-convert {\n",
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              "      border-radius: 50%;\n",
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              "      height: 32px;\n",
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              "    }\n",
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              "    .colab-df-convert:hover {\n",
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              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
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              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
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              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-ad1be7d1-1a56-4d47-babb-5b1a3c9843f1 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-ad1be7d1-1a56-4d47-babb-5b1a3c9843f1');\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",
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              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 22
        }
      ],
      "source": [
        "test[test.V2.isnull()]"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "JahHJRQTR28T"
      },
      "source": [
        "* There are null values in the datasets:\n",
        "  - The `Train` dataset has 18 null values: `V1` and `V2` columns each contain some.\n",
        "  - No rows have nulls in both `V1` and `V2` in the `Train` dataset.\n",
        "  - The `Test` dataset has 5 null values in the `V1` column and 6 null values in the `V2` column.\n",
        "  - No rows have nulls in both `V1` and `V2` in the `Test` dataset.\n",
        "  - All rows with null values have a target variable of 0."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "a8hz1KbLTicI"
      },
      "source": [
        "## Сhecking the duplicate values"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 23,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "gFqIvF5pTikQ",
        "outputId": "762a835e-de62-47ea-de56-fbb80c582a0b"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0"
            ]
          },
          "metadata": {},
          "execution_count": 23
        }
      ],
      "source": [
        "train.duplicated().sum()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 24,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "g3TebYmaToYD",
        "outputId": "614703e8-f59b-4c05-e262-fe709cebaa2a"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0"
            ]
          },
          "metadata": {},
          "execution_count": 24
        }
      ],
      "source": [
        "test.duplicated().sum()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "AuYGE8KyTq7F"
      },
      "source": [
        "* There are no duplicate values in the datasets"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2N6_NIxlTwig"
      },
      "source": [
        "## Statistical summary of the dataset"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 25,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "AitZcFcZqJ6E",
        "outputId": "be7ced51-0240-40f3-f839-a3786294aa33"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "count    40.000000\n",
              "mean      3.045536\n",
              "std       0.861076\n",
              "min       1.651547\n",
              "25%       2.185043\n",
              "50%       3.167313\n",
              "75%       3.487960\n",
              "max       5.500400\n",
              "Name: std, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 25
        }
      ],
      "source": [
        "x = train.describe().T\n",
        "x['std'][:-1].describe()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 26,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "al2W3cojTwqA",
        "outputId": "4e330b62-7e47-4613-e9b5-26cc56aff93f"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "          count      mean       std        min       25%       50%       75%  \\\n",
              "V1      19982.0 -0.271996  3.441625 -11.876451 -2.737146 -0.747917  1.840112   \n",
              "V2      19982.0  0.440430  3.150784 -12.319951 -1.640674  0.471536  2.543967   \n",
              "V3      20000.0  2.484699  3.388963 -10.708139  0.206860  2.255786  4.566165   \n",
              "V4      20000.0 -0.083152  3.431595 -15.082052 -2.347660 -0.135241  2.130615   \n",
              "V5      20000.0 -0.053752  2.104801  -8.603361 -1.535607 -0.101952  1.340480   \n",
              "V6      20000.0 -0.995443  2.040970 -10.227147 -2.347238 -1.000515  0.380330   \n",
              "V7      20000.0 -0.879325  1.761626  -7.949681 -2.030926 -0.917179  0.223695   \n",
              "V8      20000.0 -0.548195  3.295756 -15.657561 -2.642665 -0.389085  1.722965   \n",
              "V9      20000.0 -0.016808  2.160568  -8.596313 -1.494973 -0.067597  1.409203   \n",
              "V10     20000.0 -0.012998  2.193201  -9.853957 -1.411212  0.100973  1.477045   \n",
              "V11     20000.0 -1.895393  3.124322 -14.832058 -3.922404 -1.921237  0.118906   \n",
              "V12     20000.0  1.604825  2.930454 -12.948007 -0.396514  1.507841  3.571454   \n",
              "V13     20000.0  1.580486  2.874658 -13.228247 -0.223545  1.637185  3.459886   \n",
              "V14     20000.0 -0.950632  1.789651  -7.738593 -2.170741 -0.957163  0.270677   \n",
              "V15     20000.0 -2.414993  3.354974 -16.416606 -4.415322 -2.382617 -0.359052   \n",
              "V16     20000.0 -2.925225  4.221717 -20.374158 -5.634240 -2.682705 -0.095046   \n",
              "V17     20000.0 -0.134261  3.345462 -14.091184 -2.215611 -0.014580  2.068751   \n",
              "V18     20000.0  1.189347  2.592276 -11.643994 -0.403917  0.883398  2.571770   \n",
              "V19     20000.0  1.181808  3.396925 -13.491784 -1.050168  1.279061  3.493299   \n",
              "V20     20000.0  0.023608  3.669477 -13.922659 -2.432953  0.033415  2.512372   \n",
              "V21     20000.0 -3.611252  3.567690 -17.956231 -5.930360 -3.532888 -1.265884   \n",
              "V22     20000.0  0.951835  1.651547 -10.122095 -0.118127  0.974687  2.025594   \n",
              "V23     20000.0 -0.366116  4.031860 -14.866128 -3.098756 -0.262093  2.451750   \n",
              "V24     20000.0  1.134389  3.912069 -16.387147 -1.468062  0.969048  3.545975   \n",
              "V25     20000.0 -0.002186  2.016740  -8.228266 -1.365178  0.025050  1.397112   \n",
              "V26     20000.0  1.873785  3.435137 -11.834271 -0.337863  1.950531  4.130037   \n",
              "V27     20000.0 -0.612413  4.368847 -14.904939 -3.652323 -0.884894  2.189177   \n",
              "V28     20000.0 -0.883218  1.917713  -9.269489 -2.171218 -0.891073  0.375884   \n",
              "V29     20000.0 -0.985625  2.684365 -12.579469 -2.787443 -1.176181  0.629773   \n",
              "V30     20000.0 -0.015534  3.005258 -14.796047 -1.867114  0.184346  2.036229   \n",
              "V31     20000.0  0.486842  3.461384 -13.722760 -1.817772  0.490304  2.730688   \n",
              "V32     20000.0  0.303799  5.500400 -19.876502 -3.420469  0.052073  3.761722   \n",
              "V33     20000.0  0.049825  3.575285 -16.898353 -2.242857 -0.066249  2.255134   \n",
              "V34     20000.0 -0.462702  3.183841 -17.985094 -2.136984 -0.255008  1.436935   \n",
              "V35     20000.0  2.229620  2.937102 -15.349803  0.336191  2.098633  4.064358   \n",
              "V36     20000.0  1.514809  3.800860 -14.833178 -0.943809  1.566526  3.983939   \n",
              "V37     20000.0  0.011316  1.788165  -5.478350 -1.255819 -0.128435  1.175533   \n",
              "V38     20000.0 -0.344025  3.948147 -17.375002 -2.987638 -0.316849  2.279399   \n",
              "V39     20000.0  0.890653  1.753054  -6.438880 -0.272250  0.919261  2.057540   \n",
              "V40     20000.0 -0.875630  3.012155 -11.023935 -2.940193 -0.920806  1.119897   \n",
              "Target  20000.0  0.055500  0.228959   0.000000  0.000000  0.000000  0.000000   \n",
              "\n",
              "              max  \n",
              "V1      15.493002  \n",
              "V2      13.089269  \n",
              "V3      17.090919  \n",
              "V4      13.236381  \n",
              "V5       8.133797  \n",
              "V6       6.975847  \n",
              "V7       8.006091  \n",
              "V8      11.679495  \n",
              "V9       8.137580  \n",
              "V10      8.108472  \n",
              "V11     11.826433  \n",
              "V12     15.080698  \n",
              "V13     15.419616  \n",
              "V14      5.670664  \n",
              "V15     12.246455  \n",
              "V16     13.583212  \n",
              "V17     16.756432  \n",
              "V18     13.179863  \n",
              "V19     13.237742  \n",
              "V20     16.052339  \n",
              "V21     13.840473  \n",
              "V22      7.409856  \n",
              "V23     14.458734  \n",
              "V24     17.163291  \n",
              "V25      8.223389  \n",
              "V26     16.836410  \n",
              "V27     17.560404  \n",
              "V28      6.527643  \n",
              "V29     10.722055  \n",
              "V30     12.505812  \n",
              "V31     17.255090  \n",
              "V32     23.633187  \n",
              "V33     16.692486  \n",
              "V34     14.358213  \n",
              "V35     15.291065  \n",
              "V36     19.329576  \n",
              "V37      7.467006  \n",
              "V38     15.289923  \n",
              "V39      7.759877  \n",
              "V40     10.654265  \n",
              "Target   1.000000  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-f58c764a-3796-46ad-b2ff-2c0c3f93f8ac\">\n",
              "    <div 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>count</th>\n",
              "      <th>mean</th>\n",
              "      <th>std</th>\n",
              "      <th>min</th>\n",
              "      <th>25%</th>\n",
              "      <th>50%</th>\n",
              "      <th>75%</th>\n",
              "      <th>max</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>V1</th>\n",
              "      <td>19982.0</td>\n",
              "      <td>-0.271996</td>\n",
              "      <td>3.441625</td>\n",
              "      <td>-11.876451</td>\n",
              "      <td>-2.737146</td>\n",
              "      <td>-0.747917</td>\n",
              "      <td>1.840112</td>\n",
              "      <td>15.493002</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V2</th>\n",
              "      <td>19982.0</td>\n",
              "      <td>0.440430</td>\n",
              "      <td>3.150784</td>\n",
              "      <td>-12.319951</td>\n",
              "      <td>-1.640674</td>\n",
              "      <td>0.471536</td>\n",
              "      <td>2.543967</td>\n",
              "      <td>13.089269</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V3</th>\n",
              "      <td>20000.0</td>\n",
              "      <td>2.484699</td>\n",
              "      <td>3.388963</td>\n",
              "      <td>-10.708139</td>\n",
              "      <td>0.206860</td>\n",
              "      <td>2.255786</td>\n",
              "      <td>4.566165</td>\n",
              "      <td>17.090919</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V4</th>\n",
              "      <td>20000.0</td>\n",
              "      <td>-0.083152</td>\n",
              "      <td>3.431595</td>\n",
              "      <td>-15.082052</td>\n",
              "      <td>-2.347660</td>\n",
              "      <td>-0.135241</td>\n",
              "      <td>2.130615</td>\n",
              "      <td>13.236381</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V5</th>\n",
              "      <td>20000.0</td>\n",
              "      <td>-0.053752</td>\n",
              "      <td>2.104801</td>\n",
              "      <td>-8.603361</td>\n",
              "      <td>-1.535607</td>\n",
              "      <td>-0.101952</td>\n",
              "      <td>1.340480</td>\n",
              "      <td>8.133797</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V6</th>\n",
              "      <td>20000.0</td>\n",
              "      <td>-0.995443</td>\n",
              "      <td>2.040970</td>\n",
              "      <td>-10.227147</td>\n",
              "      <td>-2.347238</td>\n",
              "      <td>-1.000515</td>\n",
              "      <td>0.380330</td>\n",
              "      <td>6.975847</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V7</th>\n",
              "      <td>20000.0</td>\n",
              "      <td>-0.879325</td>\n",
              "      <td>1.761626</td>\n",
              "      <td>-7.949681</td>\n",
              "      <td>-2.030926</td>\n",
              "      <td>-0.917179</td>\n",
              "      <td>0.223695</td>\n",
              "      <td>8.006091</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V8</th>\n",
              "      <td>20000.0</td>\n",
              "      <td>-0.548195</td>\n",
              "      <td>3.295756</td>\n",
              "      <td>-15.657561</td>\n",
              "      <td>-2.642665</td>\n",
              "      <td>-0.389085</td>\n",
              "      <td>1.722965</td>\n",
              "      <td>11.679495</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V9</th>\n",
              "      <td>20000.0</td>\n",
              "      <td>-0.016808</td>\n",
              "      <td>2.160568</td>\n",
              "      <td>-8.596313</td>\n",
              "      <td>-1.494973</td>\n",
              "      <td>-0.067597</td>\n",
              "      <td>1.409203</td>\n",
              "      <td>8.137580</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V10</th>\n",
              "      <td>20000.0</td>\n",
              "      <td>-0.012998</td>\n",
              "      <td>2.193201</td>\n",
              "      <td>-9.853957</td>\n",
              "      <td>-1.411212</td>\n",
              "      <td>0.100973</td>\n",
              "      <td>1.477045</td>\n",
              "      <td>8.108472</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V11</th>\n",
              "      <td>20000.0</td>\n",
              "      <td>-1.895393</td>\n",
              "      <td>3.124322</td>\n",
              "      <td>-14.832058</td>\n",
              "      <td>-3.922404</td>\n",
              "      <td>-1.921237</td>\n",
              "      <td>0.118906</td>\n",
              "      <td>11.826433</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V12</th>\n",
              "      <td>20000.0</td>\n",
              "      <td>1.604825</td>\n",
              "      <td>2.930454</td>\n",
              "      <td>-12.948007</td>\n",
              "      <td>-0.396514</td>\n",
              "      <td>1.507841</td>\n",
              "      <td>3.571454</td>\n",
              "      <td>15.080698</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V13</th>\n",
              "      <td>20000.0</td>\n",
              "      <td>1.580486</td>\n",
              "      <td>2.874658</td>\n",
              "      <td>-13.228247</td>\n",
              "      <td>-0.223545</td>\n",
              "      <td>1.637185</td>\n",
              "      <td>3.459886</td>\n",
              "      <td>15.419616</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V14</th>\n",
              "      <td>20000.0</td>\n",
              "      <td>-0.950632</td>\n",
              "      <td>1.789651</td>\n",
              "      <td>-7.738593</td>\n",
              "      <td>-2.170741</td>\n",
              "      <td>-0.957163</td>\n",
              "      <td>0.270677</td>\n",
              "      <td>5.670664</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V15</th>\n",
              "      <td>20000.0</td>\n",
              "      <td>-2.414993</td>\n",
              "      <td>3.354974</td>\n",
              "      <td>-16.416606</td>\n",
              "      <td>-4.415322</td>\n",
              "      <td>-2.382617</td>\n",
              "      <td>-0.359052</td>\n",
              "      <td>12.246455</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V16</th>\n",
              "      <td>20000.0</td>\n",
              "      <td>-2.925225</td>\n",
              "      <td>4.221717</td>\n",
              "      <td>-20.374158</td>\n",
              "      <td>-5.634240</td>\n",
              "      <td>-2.682705</td>\n",
              "      <td>-0.095046</td>\n",
              "      <td>13.583212</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V17</th>\n",
              "      <td>20000.0</td>\n",
              "      <td>-0.134261</td>\n",
              "      <td>3.345462</td>\n",
              "      <td>-14.091184</td>\n",
              "      <td>-2.215611</td>\n",
              "      <td>-0.014580</td>\n",
              "      <td>2.068751</td>\n",
              "      <td>16.756432</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V18</th>\n",
              "      <td>20000.0</td>\n",
              "      <td>1.189347</td>\n",
              "      <td>2.592276</td>\n",
              "      <td>-11.643994</td>\n",
              "      <td>-0.403917</td>\n",
              "      <td>0.883398</td>\n",
              "      <td>2.571770</td>\n",
              "      <td>13.179863</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V19</th>\n",
              "      <td>20000.0</td>\n",
              "      <td>1.181808</td>\n",
              "      <td>3.396925</td>\n",
              "      <td>-13.491784</td>\n",
              "      <td>-1.050168</td>\n",
              "      <td>1.279061</td>\n",
              "      <td>3.493299</td>\n",
              "      <td>13.237742</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V20</th>\n",
              "      <td>20000.0</td>\n",
              "      <td>0.023608</td>\n",
              "      <td>3.669477</td>\n",
              "      <td>-13.922659</td>\n",
              "      <td>-2.432953</td>\n",
              "      <td>0.033415</td>\n",
              "      <td>2.512372</td>\n",
              "      <td>16.052339</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V21</th>\n",
              "      <td>20000.0</td>\n",
              "      <td>-3.611252</td>\n",
              "      <td>3.567690</td>\n",
              "      <td>-17.956231</td>\n",
              "      <td>-5.930360</td>\n",
              "      <td>-3.532888</td>\n",
              "      <td>-1.265884</td>\n",
              "      <td>13.840473</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V22</th>\n",
              "      <td>20000.0</td>\n",
              "      <td>0.951835</td>\n",
              "      <td>1.651547</td>\n",
              "      <td>-10.122095</td>\n",
              "      <td>-0.118127</td>\n",
              "      <td>0.974687</td>\n",
              "      <td>2.025594</td>\n",
              "      <td>7.409856</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V23</th>\n",
              "      <td>20000.0</td>\n",
              "      <td>-0.366116</td>\n",
              "      <td>4.031860</td>\n",
              "      <td>-14.866128</td>\n",
              "      <td>-3.098756</td>\n",
              "      <td>-0.262093</td>\n",
              "      <td>2.451750</td>\n",
              "      <td>14.458734</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V24</th>\n",
              "      <td>20000.0</td>\n",
              "      <td>1.134389</td>\n",
              "      <td>3.912069</td>\n",
              "      <td>-16.387147</td>\n",
              "      <td>-1.468062</td>\n",
              "      <td>0.969048</td>\n",
              "      <td>3.545975</td>\n",
              "      <td>17.163291</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V25</th>\n",
              "      <td>20000.0</td>\n",
              "      <td>-0.002186</td>\n",
              "      <td>2.016740</td>\n",
              "      <td>-8.228266</td>\n",
              "      <td>-1.365178</td>\n",
              "      <td>0.025050</td>\n",
              "      <td>1.397112</td>\n",
              "      <td>8.223389</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V26</th>\n",
              "      <td>20000.0</td>\n",
              "      <td>1.873785</td>\n",
              "      <td>3.435137</td>\n",
              "      <td>-11.834271</td>\n",
              "      <td>-0.337863</td>\n",
              "      <td>1.950531</td>\n",
              "      <td>4.130037</td>\n",
              "      <td>16.836410</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V27</th>\n",
              "      <td>20000.0</td>\n",
              "      <td>-0.612413</td>\n",
              "      <td>4.368847</td>\n",
              "      <td>-14.904939</td>\n",
              "      <td>-3.652323</td>\n",
              "      <td>-0.884894</td>\n",
              "      <td>2.189177</td>\n",
              "      <td>17.560404</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V28</th>\n",
              "      <td>20000.0</td>\n",
              "      <td>-0.883218</td>\n",
              "      <td>1.917713</td>\n",
              "      <td>-9.269489</td>\n",
              "      <td>-2.171218</td>\n",
              "      <td>-0.891073</td>\n",
              "      <td>0.375884</td>\n",
              "      <td>6.527643</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V29</th>\n",
              "      <td>20000.0</td>\n",
              "      <td>-0.985625</td>\n",
              "      <td>2.684365</td>\n",
              "      <td>-12.579469</td>\n",
              "      <td>-2.787443</td>\n",
              "      <td>-1.176181</td>\n",
              "      <td>0.629773</td>\n",
              "      <td>10.722055</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V30</th>\n",
              "      <td>20000.0</td>\n",
              "      <td>-0.015534</td>\n",
              "      <td>3.005258</td>\n",
              "      <td>-14.796047</td>\n",
              "      <td>-1.867114</td>\n",
              "      <td>0.184346</td>\n",
              "      <td>2.036229</td>\n",
              "      <td>12.505812</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V31</th>\n",
              "      <td>20000.0</td>\n",
              "      <td>0.486842</td>\n",
              "      <td>3.461384</td>\n",
              "      <td>-13.722760</td>\n",
              "      <td>-1.817772</td>\n",
              "      <td>0.490304</td>\n",
              "      <td>2.730688</td>\n",
              "      <td>17.255090</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V32</th>\n",
              "      <td>20000.0</td>\n",
              "      <td>0.303799</td>\n",
              "      <td>5.500400</td>\n",
              "      <td>-19.876502</td>\n",
              "      <td>-3.420469</td>\n",
              "      <td>0.052073</td>\n",
              "      <td>3.761722</td>\n",
              "      <td>23.633187</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V33</th>\n",
              "      <td>20000.0</td>\n",
              "      <td>0.049825</td>\n",
              "      <td>3.575285</td>\n",
              "      <td>-16.898353</td>\n",
              "      <td>-2.242857</td>\n",
              "      <td>-0.066249</td>\n",
              "      <td>2.255134</td>\n",
              "      <td>16.692486</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V34</th>\n",
              "      <td>20000.0</td>\n",
              "      <td>-0.462702</td>\n",
              "      <td>3.183841</td>\n",
              "      <td>-17.985094</td>\n",
              "      <td>-2.136984</td>\n",
              "      <td>-0.255008</td>\n",
              "      <td>1.436935</td>\n",
              "      <td>14.358213</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V35</th>\n",
              "      <td>20000.0</td>\n",
              "      <td>2.229620</td>\n",
              "      <td>2.937102</td>\n",
              "      <td>-15.349803</td>\n",
              "      <td>0.336191</td>\n",
              "      <td>2.098633</td>\n",
              "      <td>4.064358</td>\n",
              "      <td>15.291065</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V36</th>\n",
              "      <td>20000.0</td>\n",
              "      <td>1.514809</td>\n",
              "      <td>3.800860</td>\n",
              "      <td>-14.833178</td>\n",
              "      <td>-0.943809</td>\n",
              "      <td>1.566526</td>\n",
              "      <td>3.983939</td>\n",
              "      <td>19.329576</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V37</th>\n",
              "      <td>20000.0</td>\n",
              "      <td>0.011316</td>\n",
              "      <td>1.788165</td>\n",
              "      <td>-5.478350</td>\n",
              "      <td>-1.255819</td>\n",
              "      <td>-0.128435</td>\n",
              "      <td>1.175533</td>\n",
              "      <td>7.467006</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V38</th>\n",
              "      <td>20000.0</td>\n",
              "      <td>-0.344025</td>\n",
              "      <td>3.948147</td>\n",
              "      <td>-17.375002</td>\n",
              "      <td>-2.987638</td>\n",
              "      <td>-0.316849</td>\n",
              "      <td>2.279399</td>\n",
              "      <td>15.289923</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V39</th>\n",
              "      <td>20000.0</td>\n",
              "      <td>0.890653</td>\n",
              "      <td>1.753054</td>\n",
              "      <td>-6.438880</td>\n",
              "      <td>-0.272250</td>\n",
              "      <td>0.919261</td>\n",
              "      <td>2.057540</td>\n",
              "      <td>7.759877</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V40</th>\n",
              "      <td>20000.0</td>\n",
              "      <td>-0.875630</td>\n",
              "      <td>3.012155</td>\n",
              "      <td>-11.023935</td>\n",
              "      <td>-2.940193</td>\n",
              "      <td>-0.920806</td>\n",
              "      <td>1.119897</td>\n",
              "      <td>10.654265</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Target</th>\n",
              "      <td>20000.0</td>\n",
              "      <td>0.055500</td>\n",
              "      <td>0.228959</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-f58c764a-3796-46ad-b2ff-2c0c3f93f8ac')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
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              "       width=\"24px\">\n",
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          },
          "metadata": {},
          "execution_count": 26
        }
      ],
      "source": [
        "train.describe().T"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 27,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "Si4hVbefT8N9",
        "outputId": "35028251-0991-45f7-8f8c-9e5e5b4e889e"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "         count      mean       std        min       25%       50%       75%  \\\n",
              "V1      4995.0 -0.277622  3.466280 -12.381696 -2.743691 -0.764767  1.831313   \n",
              "V2      4994.0  0.397928  3.139562 -10.716179 -1.649211  0.427369  2.444486   \n",
              "V3      5000.0  2.551787  3.326607  -9.237940  0.314931  2.260428  4.587000   \n",
              "V4      5000.0 -0.048943  3.413937 -14.682446 -2.292694 -0.145753  2.166468   \n",
              "V5      5000.0 -0.080120  2.110870  -7.711569 -1.615238 -0.131890  1.341197   \n",
              "V6      5000.0 -1.042138  2.005444  -8.924196 -2.368853 -1.048571  0.307555   \n",
              "V7      5000.0 -0.907922  1.769017  -8.124230 -2.054259 -0.939695  0.212228   \n",
              "V8      5000.0 -0.574592  3.331911 -12.252731 -2.642088 -0.357943  1.712896   \n",
              "V9      5000.0  0.030121  2.174139  -6.785495 -1.455712 -0.079891  1.449548   \n",
              "V10     5000.0  0.018524  2.145437  -8.170956 -1.353320  0.166292  1.511248   \n",
              "V11     5000.0 -2.008615  3.112220 -13.151753 -4.050432 -2.043122  0.044069   \n",
              "V12     5000.0  1.576413  2.907401  -8.164048 -0.449674  1.488253  3.562626   \n",
              "V13     5000.0  1.622456  2.882892 -11.548209 -0.126012  1.718649  3.464604   \n",
              "V14     5000.0 -0.921097  1.803470  -7.813929 -2.110952 -0.896011  0.272324   \n",
              "V15     5000.0 -2.452174  3.387041 -15.285768 -4.479072 -2.417131 -0.432943   \n",
              "V16     5000.0 -3.018503  4.264407 -20.985779 -5.648343 -2.773763 -0.178105   \n",
              "V17     5000.0 -0.103721  3.336513 -13.418281 -2.227683  0.047462  2.111907   \n",
              "V18     5000.0  1.195606  2.586403 -12.214016 -0.408850  0.881395  2.604014   \n",
              "V19     5000.0  1.210490  3.384662 -14.169635 -1.026394  1.295864  3.526278   \n",
              "V20     5000.0  0.138429  3.657171 -13.719620 -2.325454  0.193386  2.539550   \n",
              "V21     5000.0 -3.664398  3.577841 -16.340707 -5.944369 -3.662870 -1.329645   \n",
              "V22     5000.0  0.961960  1.640414  -6.740239 -0.047728  0.986020  2.029321   \n",
              "V23     5000.0 -0.422182  4.056714 -14.422274 -3.162690 -0.279222  2.425911   \n",
              "V24     5000.0  1.088841  3.968207 -12.315545 -1.623203  0.912815  3.537195   \n",
              "V25     5000.0  0.061235  2.010227  -6.770139 -1.298377  0.076703  1.428491   \n",
              "V26     5000.0  1.847261  3.400330 -11.414019 -0.242470  1.917032  4.156106   \n",
              "V27     5000.0 -0.552397  4.402947 -13.177038 -3.662591 -0.871982  2.247257   \n",
              "V28     5000.0 -0.867678  1.926181  -7.933388 -2.159811 -0.930695  0.420587   \n",
              "V29     5000.0 -1.095805  2.655454  -9.987800 -2.861373 -1.340547  0.521843   \n",
              "V30     5000.0 -0.118699  3.023292 -12.438434 -1.996743  0.112463  1.946450   \n",
              "V31     5000.0  0.468810  3.446324 -11.263271 -1.822421  0.485742  2.779008   \n",
              "V32     5000.0  0.232567  5.585628 -17.244168 -3.556267 -0.076694  3.751857   \n",
              "V33     5000.0 -0.080115  3.538624 -14.903781 -2.348121 -0.159713  2.099160   \n",
              "V34     5000.0 -0.392663  3.166101 -14.699725 -2.009604 -0.171745  1.465402   \n",
              "V35     5000.0  2.211205  2.948426 -12.260591  0.321818  2.111750  4.031639   \n",
              "V36     5000.0  1.594845  3.774970 -12.735567 -0.866066  1.702964  4.104409   \n",
              "V37     5000.0  0.022931  1.785320  -5.079070 -1.240526 -0.110415  1.237522   \n",
              "V38     5000.0 -0.405659  3.968936 -15.334533 -2.984480 -0.381162  2.287998   \n",
              "V39     5000.0  0.938800  1.716502  -5.451050 -0.208024  0.959152  2.130769   \n",
              "V40     5000.0 -0.932406  2.978193 -10.076234 -2.986587 -1.002764  1.079738   \n",
              "Target  5000.0  0.056400  0.230716   0.000000  0.000000  0.000000  0.000000   \n",
              "\n",
              "              max  \n",
              "V1      13.504352  \n",
              "V2      14.079073  \n",
              "V3      15.314503  \n",
              "V4      12.140157  \n",
              "V5       7.672835  \n",
              "V6       5.067685  \n",
              "V7       7.616182  \n",
              "V8      10.414722  \n",
              "V9       8.850720  \n",
              "V10      6.598728  \n",
              "V11      9.956400  \n",
              "V12     12.983644  \n",
              "V13     12.620041  \n",
              "V14      5.734112  \n",
              "V15     11.673420  \n",
              "V16     13.975843  \n",
              "V17     19.776592  \n",
              "V18     13.642235  \n",
              "V19     12.427997  \n",
              "V20     13.870565  \n",
              "V21     11.046925  \n",
              "V22      7.505291  \n",
              "V23     13.180887  \n",
              "V24     17.806035  \n",
              "V25      6.556937  \n",
              "V26     17.528193  \n",
              "V27     17.290161  \n",
              "V28      7.415659  \n",
              "V29     14.039466  \n",
              "V30     10.314976  \n",
              "V31     12.558928  \n",
              "V32     26.539391  \n",
              "V33     13.323517  \n",
              "V34     12.146302  \n",
              "V35     13.489237  \n",
              "V36     17.116122  \n",
              "V37      6.809938  \n",
              "V38     13.064950  \n",
              "V39      7.182237  \n",
              "V40      8.698460  \n",
              "Target   1.000000  "
            ],
            "text/html": [
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>count</th>\n",
              "      <th>mean</th>\n",
              "      <th>std</th>\n",
              "      <th>min</th>\n",
              "      <th>25%</th>\n",
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              "      <th>max</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>V1</th>\n",
              "      <td>4995.0</td>\n",
              "      <td>-0.277622</td>\n",
              "      <td>3.466280</td>\n",
              "      <td>-12.381696</td>\n",
              "      <td>-2.743691</td>\n",
              "      <td>-0.764767</td>\n",
              "      <td>1.831313</td>\n",
              "      <td>13.504352</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V2</th>\n",
              "      <td>4994.0</td>\n",
              "      <td>0.397928</td>\n",
              "      <td>3.139562</td>\n",
              "      <td>-10.716179</td>\n",
              "      <td>-1.649211</td>\n",
              "      <td>0.427369</td>\n",
              "      <td>2.444486</td>\n",
              "      <td>14.079073</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V3</th>\n",
              "      <td>5000.0</td>\n",
              "      <td>2.551787</td>\n",
              "      <td>3.326607</td>\n",
              "      <td>-9.237940</td>\n",
              "      <td>0.314931</td>\n",
              "      <td>2.260428</td>\n",
              "      <td>4.587000</td>\n",
              "      <td>15.314503</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V4</th>\n",
              "      <td>5000.0</td>\n",
              "      <td>-0.048943</td>\n",
              "      <td>3.413937</td>\n",
              "      <td>-14.682446</td>\n",
              "      <td>-2.292694</td>\n",
              "      <td>-0.145753</td>\n",
              "      <td>2.166468</td>\n",
              "      <td>12.140157</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V5</th>\n",
              "      <td>5000.0</td>\n",
              "      <td>-0.080120</td>\n",
              "      <td>2.110870</td>\n",
              "      <td>-7.711569</td>\n",
              "      <td>-1.615238</td>\n",
              "      <td>-0.131890</td>\n",
              "      <td>1.341197</td>\n",
              "      <td>7.672835</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V6</th>\n",
              "      <td>5000.0</td>\n",
              "      <td>-1.042138</td>\n",
              "      <td>2.005444</td>\n",
              "      <td>-8.924196</td>\n",
              "      <td>-2.368853</td>\n",
              "      <td>-1.048571</td>\n",
              "      <td>0.307555</td>\n",
              "      <td>5.067685</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V7</th>\n",
              "      <td>5000.0</td>\n",
              "      <td>-0.907922</td>\n",
              "      <td>1.769017</td>\n",
              "      <td>-8.124230</td>\n",
              "      <td>-2.054259</td>\n",
              "      <td>-0.939695</td>\n",
              "      <td>0.212228</td>\n",
              "      <td>7.616182</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V8</th>\n",
              "      <td>5000.0</td>\n",
              "      <td>-0.574592</td>\n",
              "      <td>3.331911</td>\n",
              "      <td>-12.252731</td>\n",
              "      <td>-2.642088</td>\n",
              "      <td>-0.357943</td>\n",
              "      <td>1.712896</td>\n",
              "      <td>10.414722</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V9</th>\n",
              "      <td>5000.0</td>\n",
              "      <td>0.030121</td>\n",
              "      <td>2.174139</td>\n",
              "      <td>-6.785495</td>\n",
              "      <td>-1.455712</td>\n",
              "      <td>-0.079891</td>\n",
              "      <td>1.449548</td>\n",
              "      <td>8.850720</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V10</th>\n",
              "      <td>5000.0</td>\n",
              "      <td>0.018524</td>\n",
              "      <td>2.145437</td>\n",
              "      <td>-8.170956</td>\n",
              "      <td>-1.353320</td>\n",
              "      <td>0.166292</td>\n",
              "      <td>1.511248</td>\n",
              "      <td>6.598728</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V11</th>\n",
              "      <td>5000.0</td>\n",
              "      <td>-2.008615</td>\n",
              "      <td>3.112220</td>\n",
              "      <td>-13.151753</td>\n",
              "      <td>-4.050432</td>\n",
              "      <td>-2.043122</td>\n",
              "      <td>0.044069</td>\n",
              "      <td>9.956400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V12</th>\n",
              "      <td>5000.0</td>\n",
              "      <td>1.576413</td>\n",
              "      <td>2.907401</td>\n",
              "      <td>-8.164048</td>\n",
              "      <td>-0.449674</td>\n",
              "      <td>1.488253</td>\n",
              "      <td>3.562626</td>\n",
              "      <td>12.983644</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V13</th>\n",
              "      <td>5000.0</td>\n",
              "      <td>1.622456</td>\n",
              "      <td>2.882892</td>\n",
              "      <td>-11.548209</td>\n",
              "      <td>-0.126012</td>\n",
              "      <td>1.718649</td>\n",
              "      <td>3.464604</td>\n",
              "      <td>12.620041</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V14</th>\n",
              "      <td>5000.0</td>\n",
              "      <td>-0.921097</td>\n",
              "      <td>1.803470</td>\n",
              "      <td>-7.813929</td>\n",
              "      <td>-2.110952</td>\n",
              "      <td>-0.896011</td>\n",
              "      <td>0.272324</td>\n",
              "      <td>5.734112</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V15</th>\n",
              "      <td>5000.0</td>\n",
              "      <td>-2.452174</td>\n",
              "      <td>3.387041</td>\n",
              "      <td>-15.285768</td>\n",
              "      <td>-4.479072</td>\n",
              "      <td>-2.417131</td>\n",
              "      <td>-0.432943</td>\n",
              "      <td>11.673420</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V16</th>\n",
              "      <td>5000.0</td>\n",
              "      <td>-3.018503</td>\n",
              "      <td>4.264407</td>\n",
              "      <td>-20.985779</td>\n",
              "      <td>-5.648343</td>\n",
              "      <td>-2.773763</td>\n",
              "      <td>-0.178105</td>\n",
              "      <td>13.975843</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V17</th>\n",
              "      <td>5000.0</td>\n",
              "      <td>-0.103721</td>\n",
              "      <td>3.336513</td>\n",
              "      <td>-13.418281</td>\n",
              "      <td>-2.227683</td>\n",
              "      <td>0.047462</td>\n",
              "      <td>2.111907</td>\n",
              "      <td>19.776592</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V18</th>\n",
              "      <td>5000.0</td>\n",
              "      <td>1.195606</td>\n",
              "      <td>2.586403</td>\n",
              "      <td>-12.214016</td>\n",
              "      <td>-0.408850</td>\n",
              "      <td>0.881395</td>\n",
              "      <td>2.604014</td>\n",
              "      <td>13.642235</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V19</th>\n",
              "      <td>5000.0</td>\n",
              "      <td>1.210490</td>\n",
              "      <td>3.384662</td>\n",
              "      <td>-14.169635</td>\n",
              "      <td>-1.026394</td>\n",
              "      <td>1.295864</td>\n",
              "      <td>3.526278</td>\n",
              "      <td>12.427997</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V20</th>\n",
              "      <td>5000.0</td>\n",
              "      <td>0.138429</td>\n",
              "      <td>3.657171</td>\n",
              "      <td>-13.719620</td>\n",
              "      <td>-2.325454</td>\n",
              "      <td>0.193386</td>\n",
              "      <td>2.539550</td>\n",
              "      <td>13.870565</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V21</th>\n",
              "      <td>5000.0</td>\n",
              "      <td>-3.664398</td>\n",
              "      <td>3.577841</td>\n",
              "      <td>-16.340707</td>\n",
              "      <td>-5.944369</td>\n",
              "      <td>-3.662870</td>\n",
              "      <td>-1.329645</td>\n",
              "      <td>11.046925</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V22</th>\n",
              "      <td>5000.0</td>\n",
              "      <td>0.961960</td>\n",
              "      <td>1.640414</td>\n",
              "      <td>-6.740239</td>\n",
              "      <td>-0.047728</td>\n",
              "      <td>0.986020</td>\n",
              "      <td>2.029321</td>\n",
              "      <td>7.505291</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V23</th>\n",
              "      <td>5000.0</td>\n",
              "      <td>-0.422182</td>\n",
              "      <td>4.056714</td>\n",
              "      <td>-14.422274</td>\n",
              "      <td>-3.162690</td>\n",
              "      <td>-0.279222</td>\n",
              "      <td>2.425911</td>\n",
              "      <td>13.180887</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V24</th>\n",
              "      <td>5000.0</td>\n",
              "      <td>1.088841</td>\n",
              "      <td>3.968207</td>\n",
              "      <td>-12.315545</td>\n",
              "      <td>-1.623203</td>\n",
              "      <td>0.912815</td>\n",
              "      <td>3.537195</td>\n",
              "      <td>17.806035</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V25</th>\n",
              "      <td>5000.0</td>\n",
              "      <td>0.061235</td>\n",
              "      <td>2.010227</td>\n",
              "      <td>-6.770139</td>\n",
              "      <td>-1.298377</td>\n",
              "      <td>0.076703</td>\n",
              "      <td>1.428491</td>\n",
              "      <td>6.556937</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V26</th>\n",
              "      <td>5000.0</td>\n",
              "      <td>1.847261</td>\n",
              "      <td>3.400330</td>\n",
              "      <td>-11.414019</td>\n",
              "      <td>-0.242470</td>\n",
              "      <td>1.917032</td>\n",
              "      <td>4.156106</td>\n",
              "      <td>17.528193</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V27</th>\n",
              "      <td>5000.0</td>\n",
              "      <td>-0.552397</td>\n",
              "      <td>4.402947</td>\n",
              "      <td>-13.177038</td>\n",
              "      <td>-3.662591</td>\n",
              "      <td>-0.871982</td>\n",
              "      <td>2.247257</td>\n",
              "      <td>17.290161</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V28</th>\n",
              "      <td>5000.0</td>\n",
              "      <td>-0.867678</td>\n",
              "      <td>1.926181</td>\n",
              "      <td>-7.933388</td>\n",
              "      <td>-2.159811</td>\n",
              "      <td>-0.930695</td>\n",
              "      <td>0.420587</td>\n",
              "      <td>7.415659</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V29</th>\n",
              "      <td>5000.0</td>\n",
              "      <td>-1.095805</td>\n",
              "      <td>2.655454</td>\n",
              "      <td>-9.987800</td>\n",
              "      <td>-2.861373</td>\n",
              "      <td>-1.340547</td>\n",
              "      <td>0.521843</td>\n",
              "      <td>14.039466</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V30</th>\n",
              "      <td>5000.0</td>\n",
              "      <td>-0.118699</td>\n",
              "      <td>3.023292</td>\n",
              "      <td>-12.438434</td>\n",
              "      <td>-1.996743</td>\n",
              "      <td>0.112463</td>\n",
              "      <td>1.946450</td>\n",
              "      <td>10.314976</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V31</th>\n",
              "      <td>5000.0</td>\n",
              "      <td>0.468810</td>\n",
              "      <td>3.446324</td>\n",
              "      <td>-11.263271</td>\n",
              "      <td>-1.822421</td>\n",
              "      <td>0.485742</td>\n",
              "      <td>2.779008</td>\n",
              "      <td>12.558928</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V32</th>\n",
              "      <td>5000.0</td>\n",
              "      <td>0.232567</td>\n",
              "      <td>5.585628</td>\n",
              "      <td>-17.244168</td>\n",
              "      <td>-3.556267</td>\n",
              "      <td>-0.076694</td>\n",
              "      <td>3.751857</td>\n",
              "      <td>26.539391</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V33</th>\n",
              "      <td>5000.0</td>\n",
              "      <td>-0.080115</td>\n",
              "      <td>3.538624</td>\n",
              "      <td>-14.903781</td>\n",
              "      <td>-2.348121</td>\n",
              "      <td>-0.159713</td>\n",
              "      <td>2.099160</td>\n",
              "      <td>13.323517</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V34</th>\n",
              "      <td>5000.0</td>\n",
              "      <td>-0.392663</td>\n",
              "      <td>3.166101</td>\n",
              "      <td>-14.699725</td>\n",
              "      <td>-2.009604</td>\n",
              "      <td>-0.171745</td>\n",
              "      <td>1.465402</td>\n",
              "      <td>12.146302</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V35</th>\n",
              "      <td>5000.0</td>\n",
              "      <td>2.211205</td>\n",
              "      <td>2.948426</td>\n",
              "      <td>-12.260591</td>\n",
              "      <td>0.321818</td>\n",
              "      <td>2.111750</td>\n",
              "      <td>4.031639</td>\n",
              "      <td>13.489237</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V36</th>\n",
              "      <td>5000.0</td>\n",
              "      <td>1.594845</td>\n",
              "      <td>3.774970</td>\n",
              "      <td>-12.735567</td>\n",
              "      <td>-0.866066</td>\n",
              "      <td>1.702964</td>\n",
              "      <td>4.104409</td>\n",
              "      <td>17.116122</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V37</th>\n",
              "      <td>5000.0</td>\n",
              "      <td>0.022931</td>\n",
              "      <td>1.785320</td>\n",
              "      <td>-5.079070</td>\n",
              "      <td>-1.240526</td>\n",
              "      <td>-0.110415</td>\n",
              "      <td>1.237522</td>\n",
              "      <td>6.809938</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V38</th>\n",
              "      <td>5000.0</td>\n",
              "      <td>-0.405659</td>\n",
              "      <td>3.968936</td>\n",
              "      <td>-15.334533</td>\n",
              "      <td>-2.984480</td>\n",
              "      <td>-0.381162</td>\n",
              "      <td>2.287998</td>\n",
              "      <td>13.064950</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V39</th>\n",
              "      <td>5000.0</td>\n",
              "      <td>0.938800</td>\n",
              "      <td>1.716502</td>\n",
              "      <td>-5.451050</td>\n",
              "      <td>-0.208024</td>\n",
              "      <td>0.959152</td>\n",
              "      <td>2.130769</td>\n",
              "      <td>7.182237</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V40</th>\n",
              "      <td>5000.0</td>\n",
              "      <td>-0.932406</td>\n",
              "      <td>2.978193</td>\n",
              "      <td>-10.076234</td>\n",
              "      <td>-2.986587</td>\n",
              "      <td>-1.002764</td>\n",
              "      <td>1.079738</td>\n",
              "      <td>8.698460</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Target</th>\n",
              "      <td>5000.0</td>\n",
              "      <td>0.056400</td>\n",
              "      <td>0.230716</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-f324c9ff-643e-4cdd-8414-debfeb19f1b5')\"\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 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\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",
              "    [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-f324c9ff-643e-4cdd-8414-debfeb19f1b5 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-f324c9ff-643e-4cdd-8414-debfeb19f1b5');\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",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 27
        }
      ],
      "source": [
        "test.describe().T"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ZAEzeV9wUJM8"
      },
      "source": [
        "* The target class distribution is imbalanced.\n",
        "  - In both datasets, about 5.6% of the rows have a target value of \"1\" while 94.4% have a target value of \"0\"\n",
        "  - In other words, the failure rate in the observations is 5.6%."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "__7ciGcIDPyk"
      },
      "source": [
        "## Exploratory Data Analysis (EDA)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "c2lm6IMGWGhX"
      },
      "source": [
        "- EDA is an important part of any project involving data.\n",
        "- It is important to investigate and understand the data better before building a model with it."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "T0Ov9D6aXCGD"
      },
      "source": [
        "## Univariate Analysis"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3tRPl0xNjFpY"
      },
      "source": [
        " # Histograms for all the variables overview"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 28,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "VQFHDcVEiDWn",
        "outputId": "45c74776-f98b-4c45-af73-fe0be2c8e8b7"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1400x1600 with 40 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "fig, axes = plt.subplots(nrows=8, ncols=5, figsize=(14, 16)) \n",
        "\n",
        "for i, var in enumerate(train.columns[:-1]):\n",
        "    ax = axes[i//5, i%5]\n",
        "    sns.kdeplot(data=train, x=var, hue='Target', common_norm=False, legend=False, ax=ax).set(xlabel='', ylabel='', xticks=[], yticks=[])\n",
        "    ax.set_title(var)\n",
        "\n",
        "fig.legend(axes[0, 0].lines, ['Failure (1)', 'No failure (0)'], bbox_to_anchor=(1.02, 0.88))\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "labeled_barplot(train, 'Target', perc=True, percfmt=\"{:.2f}%\", rnd=0,\n",
        "                    figsize=(10, 5), xlabel=None, xlo=0, title='Distribution for `Target` column in the `Train` dataset')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 495
        },
        "id": "k4H3J4PUcqhC",
        "outputId": "7672abc3-cb27-4be9-880d-942d38700897"
      },
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ZEIl0Ra4pCFe"
      },
      "source": [
        "* The majority of variables are closely distributed to the normal distribution.\n",
        "* For some variable, the distributions by the target variable are similar, while for others, they are different (shifted by mean or frequency).\n",
        "* About 5.55% of the rows have a target value of \"1\" in the `Train` dataset, while 94.45% have a target value of \"0\""
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "TWlGr1u1hKyk"
      },
      "source": [
        "### Plotting histograms and boxplots for all the variables\n",
        "### Plotting all the features at one go"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 30,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "W91y_f944jan",
        "outputId": "81be5254-6245-4f9d-cb72-f934e21a83ee"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x700 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x700 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x700 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x700 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x700 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x700 with 2 Axes>"
            ],
            "image/png": 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kSdKFF15YbXK4uuratavuu+8+SdKqVauqLasq1D6fL+Txa+P111+v8f6qa8wPGTJEDsf/riRbVYY2bNhwzGNKS0uPe55zqK+ndevWwUOrq/Y8H8k0zeD9w4cPr9PY4TZ06FDZbDatWrVKq1evPmb5vn37gueYW51VOlzEf/rTn0o6PAFf1SR8V199tTweT42PGTt2rAzD0Hfffafdu3cfs3z+/PmqrKyUYRg644wzwp656jz0f/7zn7WaA6A+fiYn+n9gzZo12rVrV63GAQA0bhR9AGgGTNPUxx9/rLPOOkubNm1SixYtjjvL+9E+++wzzZo165hZr03T1IcffihJatu2bbVlrVu3lqR6uY76kVasWKEnnnii2n1ffvmlpk2bJknBDzWqXHDBBZKkadOmVTunuaSkRLfccstxS07V61m/fn2dM/7f//2fJOnRRx+tVtZM09Tvf/97rVq1SomJibr55pvrPHY4tWnTRldeeaVM09QvfvGLanMbVL0/5eXlGjx4sAYPHmxh0v+pOkT/7bff1nvvvVftvpp06tRJ48aNk9fr1c0336yCgoLgsh07duj222+XdHhm+ZYtW4Y97yWXXKK+fftq7969uvLKK4+ZP6K8vFwff/xx8Pv6+JlU/T/w8MMPVztnfvv27Ro/fnydTnUBADRejpOvAgBoSl588UXNnz9f0uHJr3Jzc/XNN98oLy9PkjRs2DC9/PLLx5Tz41mzZo0mTZqk+Ph49evXTy1btlRZWZm++eYb7dixQwkJCXrkkUeqPWbs2LH6/PPPNW7cOI0YMUJJSUmSpHvuuUddunQJ22u94447dP/99+vVV19Vr169tHfvXi1cuFCBQEB33nnnMTOA/+QnP9Ezzzyj5cuXq0ePHhoyZIgCgYCWL18ul8ulG264ocZLtg0cOFAtW7bUypUr1a9fP/Xs2VNOp1NdunTRPffcc8KMv/jFL7R48WK99tprOuOMM3TuuecqPT1d33zzjTZu3KioqCjNnDnzmEutWWHatGn67rvvtGzZMnXs2FHDhw+Xw+HQggULdODAAbVv315vvPGG1TGDBg4cqO7duwc/gOnTp4/69et3wsf89a9/1bp16zR79mx16tRJAwcOVHl5uZYuXari4mL17t1bzz//fL3ktdlseu+99zRy5Eh9/PHHatOmjYYMGaKUlBTt2bNHq1evVmJiYvDUEyn8P5MHHnhA77zzjmbNmqXOnTvrzDPP1IEDB/T111/r7LPP1uDBgxvsUn0AgPrDHn0AiDCLFi3SK6+8oldeeUUffPCB1q9fr549e+pXv/qVvvrqK33++ecnnMX7aBdffLEmT56sM888U1u3btW7776r+fPnKyEhQb/+9a+1du3aY04BuPXWWzVlyhS1bdtWs2bN0ksvvaSXXnop7BOcXXbZZZo7d64yMzM1a9YsffXVV+rXr59mzJihZ5555pj1nU6n5s6dq9tuu01xcXH65JNPtGbNGl122WX65ptvlJWVVePzuFwuzZkzR5dccol2796t119/XS+99JI++uijk2Y0DEOvvvqqZs6cqSFDhmjFihV65513VFpaquuvv14rV67U6NGjT/WtCIuUlBQtXrxYU6ZMUfv27fXJJ5/oww8/VGpqqh544AGtWLHilK+UEG5H7sG/4YYbTrp+QkKCFi1apMcff1wtW7bUZ599psWLF+u0007TH/7wBy1ZsqRWV6MIVdu2bbV8+XL98Y9/VI8ePbRkyRK9++672rFjh84991z98Y9/rLZ+uH8m7du31+LFi3X55ZerqKhIH374ofbv368HH3xQs2bNOu7s9wCApsUwOUYLAAAAAICIwR59AAAAAAAiCEUfAAAAAIAIQtEHAAAAACCCUPQBAAAAAIggFH0AAAAAACIIRR8AAAAAgAhC0QcAAAAAIIJQ9AEAAAAAiCAUfQAAAAAAIghFHwAAAACACELRBwAAAAAgglD0AQAAAACIIBR9AAAAAAAiCEUfAAAAAIAIQtEHAAAAACCCUPQBAAAAAIggFH0AAAAAACIIRR8AAAAAgAhC0QcAAAAAIIJQ9AEAAAAAiCAUfQAAAAAAIghFHwAAAACACELRBwAAAAAgglD0AQAAAACIIBR9AAAAAAAiCEUfAAAAAIAIQtEHAAAAACCCUPQBAAAAAIggFH0AAAAAACIIRR8AAAAAgAhC0QcAAAAAIIJQ9AEAAAAAiCAUfQAAAAAAIghFHwAAAACACELRBwAAAAAgglD0AQAAAACIIBR9AAAAAAAiCEUfAAAAAIAIQtEHAAAAACCCUPQBAAAAAIggFH0AAAAAACIIRR8AAAAAgAhC0QcAAAAAIIJQ9AEAAAAAiCAUfQAAAAAAIghFHwAAAACACELRBwAAAAAgglD0AQAAAACIIBR9AAAAAAAiCEUfAAAAAIAIQtEHAAAAACCCUPQBAAAAAIggDqsDNEWBQEB79+5VXFycDMOwOg4AAAAAIMKZpqmioiK1bNlSNtuJ99lT9EOwd+9eZWVlWR0DAAAAANDM7Nq1S61btz7hOhT9EMTFxUk6/AbHx8dbnAYAAAAAEOkKCwuVlZUV7KMnQtEPQdXh+vHx8RR9AAAAAECDqc3p40zGBwAAAABABKHoAwAAAAAQQSj6AAAAAABEEIo+AAAAAAARhKIPAAAAAEAEoegDAAAAABBBKPoAAAAAAEQQij4AAAAAABGEog8AAAAAQARxWB0AAADUH9M05fV6rY5huSPfB5fLJcMwLE7UePB+AEDkoegDABDBvF6v7rzzTqtjoBGbOnWq3G631TEAAGHEofsAAAAAAEQQ9ugDANBM3DM4Si671Sms4fWbenJxuSTpnsEeuezN+1B1r196cnGZ1TEAAPWEog8AQDPhsqvZF1zp8HvA+2BaHQAAUI84dB8AAAAAgAhC0QcAAAAAIIJQ9AEAAAAAiCAUfQAAAAAAIghFHwAAAACACELRBwAAAAAgglD0AQAAAACIIBR9AAAAAAAiCEUfAAAAAIAIQtEHAAAAACCCUPQBAAAAAIggFH0AAAAAACIIRR8AAAAAgAhC0QcAAAAAIIJQ9AEAAAAAiCAUfQAAAAAAIghFHwAAAACACELRBwAAAAAgglD0AQAAAACIIBR9AAAAAAAiCEUfAAAAAIAIQtEHAAAAACCCUPQBAAAAAIggFH0AAAAAACIIRR8AAAAAgAjisDoAAJwK0zTl9XolSS6XS4ZhWJwIAAA0dWxfoKljjz6AJs3r9erOO+/UnXfeGfyDDAAAcCrYvkBTR9EHAAAAACCCUPQBAAAAAIggFH0AAAAAACIIRR8AAAAAgAhC0QcAAAAAIIJQ9AEAAAAAiCAUfQAAAAAAIghFHwAAAACACELRBwAAAAAgglD0AQAAAACIIBR9AAAAAAAiCEUfAAAAAIAIQtEHAAAAACCCUPQBAAAAAIggFH0AAAAAACIIRR8AAAAAgAhC0QcAAAAAIIJQ9AEAAAAAiCAUfQAAAAAAIghFHwAAAACACELRBwAAAAAgglD0AQAAAACIIBR9AAAAAAAiCEUfAAAAAIAI4rA6AOrXmjVr9Oabb+qnP/2pevXqZXUcy5zofaiP96imMWvzPEeuI0lvvvmmBg4cqC+++EKSdN1116lXr15as2aNXn311WPuO/KxVcuHDh2qL774Qj6fL/g8DodDXbp00TfffCO3260bbrghOMbLL7+s8vJyeTwe3XDDDcEcSUlJ2rJlixwOhxwOh/x+v3w+n0aPHq1LLrlEkvT+++9r9uzZGjVqlPbv368VK1bI6XSqV69eWrlypUaNGqV27drpzTffVPv27fXNN9/INM1q74HL5ZLf75ff7w/eZ7fbq31/PB999JEuv/zyk64HAABQW3feeWfwtt1ul2maCgQCyszMVHFxscrKyqptp3g8HvXo0UMrV65U+/bttWXLFklSZmamsrOzJUn9+/fXunXrVF5eHtzOcTqdstvtwXEcDkeN235dunTRypUr1bdvX23btu2Ybb+atg3rso1b9biatkGP9v777+vjjz8OvoYjtwsbQri24yOxM1H0I5jX69XMmTOVn5+vmTNnqmvXrnK5XFbHanAneh/q4z2qaUxJJ32eIx/3xhtvSJIKCgr08ccfB8vwG2+8oQ4dOuiNN95QcXFxtfuOfmzV8lmzZtWYc8WKFZKk8vJyvf7663rooYf0+uuvq7y8PHj/a6+9JpvNpoKCAuXl5UmSfD5ftQ8NPv74Y5133nnB26ZpVnvOysrK4HPNmjVLCQkJ1car6f07Wm1KviR98sknGjFihGJjY2u1PoDmJT8hX1vbbdXKQFcNsKdaHQdAE3TkNklVaT9aeXl5cNunquQfvX7V8iPHrKysVGVlZbWxatr2q3ps1X+P3vY7etuwLtu4R26PHr0NevQYxcXFwW2+qm3DWbNm6bzzzmuQbbFwbcdHamfi0P0INnv2bBUUFEg6XBhnz55tcSJrnOh9qI/3qKYxa/M8R69TdfvIPd4FBQV6/vnng8tquu/Ix9ZWYWGhnn/+eRUWFla7v6io6KRjmaap559/Xs8///wxe+drUtdsdfX888/X6/gAmibTNLWjzQ6VRZdpRmBzrX5fAYDVatr2q2mdk20b1nYb98jt0aO3QY8e43jbXA21LRau7fhI7Uzs0Y9QOTk5mj17dvB/UNM0NWfOHA0cOFDp6ekWp2s4J3ofJIX9Parp+ap+WZzoeY5+3Ils3ry5VvfV1amMEY7nD5fNmzdrzZo16tKli9VRgEahoqIiePvw7xjDujAW+sbMU3Hs4b1dm1Sk5eZBnWk03736R/69OfLfCIDDGlPZC2U768jH1HYb92Tbo7Nnzw6OsWHDhuPm2rx5szZs2KBu3brVOXdthavrRHJnoujXQkVFRbU/gkfv9WxsTNPUm2++edz7b7/9dhlG5G/onex9qOmX2Km8R8d7vkAgcMLnkVTj4xC6Z5991uoIQKNUGZDcVoewgGmaejWwWfrhcw6bpBm+LTrDmdIs/h7WpPKIP0333nuvdUEANIiTbeMebzv2SIFAQP/85z9122236YUXXjjhui+88IL+9Kc/yWYL/wHk4eo6kd6ZOHS/FqZMmaKEhITgV1ZWltWRTig7O1vr168/pmAGAgGtX7/+uOcTRZqTvQ8bNmwI63t0vOeryZHPU5fHAQDqbrl5UJtUFDyYISBpo1mo5eZBS3MBQEM52TZubbdHN2zYoIULF6q0tPSE65WWlmrt2rUh5z2RcHWdSO9M7NGvhfvvv19333138PvCwsJGXfYzMzPVvXt3fffdd9X+4dpsNnXt2lWZmZkWpms4J3sfTNPUxo0bw/YeHe/5anL089T2caidqKgoPf744/XyKTLQ1FRUVAT32Dqb4f8Spmlqhm+LbDpc8Ks09736R/5beOKJJ+R2N8djPYCa+Xw+/epXv7I6RlidbBu3ttux3bp10znnnKP333//hGU/Ojpap59++innrkm4uk6kdyaKfi243e4m9QfQMAz99Kc/1eTJk4+5/2c/+1mz2aA52ftgmmZY36PjPV9V2TzyF8jRz1PT4xC6CRMmKCoqyuoYQKPTXH7/H2m5eVAbzWNPuTtyr35zPFf/yH8LTW07B6hvbrdbl1xyid5//32ro4TNybZxj7cdeySbzaarr75adrtdN998s6ZOnXrcdX/xi1/U2w6XcHWdSO9MzfCz/eYhPT1do0aNCv4DNQxDI0eOVFpamsXJGtaJ3of6eI9qGnPUqFEnfZ6jH3cinTp1qvG+U/1lVNO4dXnsqTw+nDp16sREfAAk/W9v/vF+Oxo6vFefGfgBHO3888+3OkJQKNtYR24b1nYb92Tbo6NGjQqO0a1bt+PmaohtsXBtx0dyZ6LoR7BRo0YpISFBkpSQkKBRo0ZZnMgaJ3of6uM9qmnM2jzPkeskJiYGbx/5yzYxMVETJkwILqsa78j7quaSqIuqMeLj46vdHxcXd9KxDMPQhAkTNGHChFp92FDXbHU1YcKEeh0fQNNRKVM5ZrmOV+NNSTlmuSqPuwYAWOvo7bzjrXOybcPabuMeuT165HZdTWMcb5urobbFwrUdH6mdiaIfwVwul66++molJyfr6quvlsvlsjqSJU70PtTHe1TTmLV5nqPXueaaa5ScnKzRo0crNjZWsbGxuvrqqxUbG6trrrkmeF/V7arHXnPNNdWWX3TRRYqNjZXH4wl+xcbGqn///jIMQx6PJ7j+uHHj5PF4JEkej0fXXnttMEfHjh0lSQ6HQx6PR06nU4ZhVMs3evRo2Ww2XXTRRerfv78kyel0qn///sH7q8arev6a3ge73V7tvqO/P54RI0YoNja2Tj8vAJHLZdg0zTVAzzkH6C/2s9R7TW/1XtNbf7Gfpeech+9/1jVALoPNIQC1Y7fbg4ekZ2ZmKjY29pjtFI/HE9z2qdp+qlq/Sv/+/YPbXFWPdzqdx2yvVW2jHbltVzV2//79a9z2O3rbsC7buEdujx65jXfNNdccM0bVdqZhGHI4HDIMI7jd2RDCtR0fqZ3JMDlerc4KCwuVkJCggoKCY/aAAmhYFRUVuvPOOyVJU6dO5TxT4ChH/j/y4DlRctmb9jmHofL6TT22sExS834fqhz5fvC7EzgW2xdojOrSQ/kIGwAAAACACELRBwAAAAAgglD0AQAAAACIIBR9AAAAAAAiCEUfAAAAAIAIQtEHAAAAACCCUPQBAAAAAIggFH0AAAAAACIIRR8AAAAAgAhC0QcAAAAAIIJQ9AEAAAAAiCAUfQAAAAAAIghFHwAAAACACELRBwAAAAAgglD0AQAAAACIIBR9AAAAAAAiCEUfAAAAAIAIQtEHAAAAACCCUPQBAAAAAIggFH0AAAAAACIIRR8AAAAAgAhC0QcAAAAAIIJQ9AEAAAAAiCAUfQAAAAAAIojD6gAAcCpcLpemTp0avA0AAHCq2L5AU0fRB9CkGYYht9ttdQwAABBB2L5AU8eh+wAAAAAARBCKPgAAAAAAEYSiDwAAAABABKHoAwAAAAAQQSj6AAAAAABEEIo+AAAAAAARhKIPAAAAAEAEoegDAAAAABBBKPoAAAAAAEQQij4AAAAAABGEog8AAAAAQASh6AMAAAAAEEEo+gAAAAAARBCKPgAAAAAAEYSiDwAAAABABKHoAwAAAAAQQSj6AAAAAABEEIo+AAAAAAARhKIPAAAAAEAEoegDAAAAABBBKPoAAAAAAEQQij4AAAAAABGEog8AAAAAQASh6AMAAAAAEEEcVgcAAAANw+uXJNPqGJbw+s0abzdXh/8tAAAiFUUfAIBm4snFZVZHaBSeXFxudQQAAOoVh+4DAAAAABBB2KMPAEAEc7lcmjp1qtUxLGeaprxer6TD74lhGBYnajxcLpfVEQAAYUbRBwAgghmGIbfbbXWMRsHj8VgdAQCABsGh+wAAAAAARBCKPgAAAAAAEYSiDwAAAABABKHoAwAAAAAQQSj6AAAAAABEEIo+AAAAAAARhKIPAAAAAEAEoegDAAAAABBBKPoAAAAAAEQQij4AAAAAABGEog8AAAAAQARxWB2gKTJNU5JUWFhocRIAAAAAQHNQ1T+r+uiJUPRDUFRUJEnKysqyOAkAAAAAoDkpKipSQkLCCdcxzNp8HIBqAoGA9u7dq7i4OBmGYXWcJqOwsFBZWVnatWuX4uPjrY4Tskh4HbyGxoHX0DjwGhqPSHgdvIbGgdfQOPAaGo9IeB28hsN78ouKitSyZUvZbCc+C589+iGw2Wxq3bq11TGarPj4+Cb7P+eRIuF18BoaB15D48BraDwi4XXwGhoHXkPjwGtoPCLhdTT313CyPflVmIwPAAAAAIAIQtEHAAAAACCCUPTRYNxut373u9/J7XZbHeWURMLr4DU0DryGxoHX0HhEwuvgNTQOvIbGgdfQeETC6+A11A2T8QEAAAAAEEHYow8AAAAAQASh6AMAAAAAEEEo+gAAAAAARBCKPgAAAAAAEYSiDwAAAABABKHoAwAAAAAQQSj6AAAAAABEEIo+AAAAAAARhKIPAAAAAEAEoegDAAAAABBBKPoAAAAAAEQQij4AAAAAABGEog8AAAAAQASh6AMAAAAAEEEo+gAAAAAARBCKPgAAAAAAEYSiDwAAAABABKHoAwAAAAAQQSj6AAAAAABEEIo+AAAAAAARhKIPAAAAAEAEoegDAAAAABBBKPoAAAAAAEQQij4AAAAAABGEog8AAAAAQASh6AMAAAAAEEEo+gAAAAAARBCKPgAAAAAAEYSiDwAAAABABKHoAwAAAAAQQSj6AAAAAABEEIo+AAAAAAARhKIPAAAAAEAEoegDAAAAABBBKPoAAAAAAEQQij4AAAAAABGEog8AAAAAQASh6AMAAAAAEEEo+gAAAAAARBCKPgAAAAAAEYSiDwAAAABABHFYHaApCgQC2rt3r+Li4mQYhtVxAAAAAAARzjRNFRUVqWXLlrLZTrzPnqIfgr179yorK8vqGAAAAACAZmbXrl1q3br1Cdeh6IcgLi5O0uE3OD4+3uI0AADgZLxer5566ilJ0q9+9Su5XC6LEwEAUDeFhYXKysoK9tEToeiHoOpw/fj4eIo+AABNgNfrlcfjkXT47zdFHwDQVNXm9HEm4wMAAAAAIIKwRx8AAES8kooSPbbnMUnSHRV3sEcfABDRKPoAAKBZqDQrrY4AAECD4NB9AAAAAAAiCEUfAAAAAIAIQtEHAAAAACCCUPQBAAAAAIggFH0AAAAAACIIs+4DAICIZzNsautqG7wNAEAko+gDAICIF+WK0s/Tfx68DQBAJOMjbQAAAAAAIghFHwAAAACACMKh+wAAoMnyB/zK9+brYHmeDpYf1KGKQ6oIeOUP+OU3/fKZPjkMhwyvoSf2PiFJujj3EnVJ66wYZ4zF6QEAqB8UfQAA0KB27typ3NzckB/vl19FjmIVOApVYi+RaZgnXN9relVWWabSQKkkafmBFVpXvF6ugEuxvljF+WMU7Y+RTcZJnzs1NVVt2rQJOTsAAA2Bog8AABrMzp071a1bN5WWltbpcYZhqPe5vTX0imHqNbSXXG5XcFnRoSJtX7tN29Zt1/Z125Sfc0jecq+8FZWqLPfKExul9Hbp0uFJ97VlzRZ1P6O7vHav8lx5ylOeCvMKteSDxVr47hfa+d3O4+aIjo7Whg0bKPsAgEaNog8AABpMbm6uSktL9dhzj6vDaR1Our4pU2aMKX9cQHIesaBSspUaspXalORLVHK7furXrp80puZxSitKdeN7N0iSuqR0lmufU6bHVMBjyowyFZ8cr5HjR2nk+FGSV7KV2GQrMWSY/9vLv3XTVj146wPKzc2l6AMAGjWKPgAAaHAdTuugbr27HXd5wAzoYEWeDpQdkN/0S5JssinZk6wkV6I8do8M4+SH2lcpKimS3jt8u3OPzoqLiQsuM01TRZVFOuTNV6G3UKbLVMAVkJJtSnYlKsWTIrfdHdoLBQDAAhR9AADQaFSV7r2l++QNeCVJDsOhVE+qUtzJstvsYX9OwzAU74pXvCtevoBP+d585ZYflDfgVW7FQeVWHFScM04B94nnAgAAoLGg6AMAgEah3FeuvaX7VOwrlnS44GdEZSjJnSib0TBXBHbYqj5USFFxZbFyKw6qqLJIRZVFUrr00Ju/U6G9SKZp1umIAgAAGhJFHwAAWMo0TeWUH9D+sv2SJEOGUj2pSo9Kk90Izx58wzDU0tkyeLs268e54hTnilOFv0IHynOVV56nTn1P0y7t1vs7PlSv5J5qF9eWwg8AaHQo+gAAwDJev1c7S3ap1Hd4Fv54Z5xaRLcI+znxHqdHt2TcErxdF267W61jWqlwa4He/eA9/fgXP1aht1BfZi/Surx16p3aW61jWlH4AQCNRsMcBwcAAHAEU6byKg7p+4JNKvWVyiabsmJaq21s20Y78Z0RMPTO02+rc0kn9U7pJafNqUPefM3fu0Czd32iA2W5VkcEAEASRR8AADQwu9Muf1JAu0t2K6CAoh3R6pxwmpLcSU1ir7hddvVK6anL2l+qHkndZTfsyi3P1exdc7Rs/1fy+r1WRwQANHMcug8AABqMTz7d+9KvZcYensE+IypD6Z60ei/45d4yPb3vaUnSBd4LFOuMO8kjTs5td6tfWl91S+qqb3JXaWvhVn1fsEm7infrzPQz1CY2q0l8cAEAiDzs0QcAAA2iwFuobdHb1W1ANykgtYttp4yo9AYpw6akAn+BCvwFCvdF8qIcUTo7c5AuaH2+4pxxKvOX6Yt9C7Vw35eqDFSG+dkAADg5ij4AAKh32aXZmr1zjry2Sh3YfUCOHLviXae+V70xaRGdqYvbjlHP5NNlyNCO4p36eOccFXgLrY4GAGhmKPoAAKBe7SnZq3l7Ppc34FWUP0qTr/ydjMrIPKTdbrOrT2pvjcy6UFH2KBV4C/TxztnaVbzL6mgAgGaEog8AAOrNruLdmr93gQJmQK1jWqtdWRsV5UX+Hu60qDSNaTta6VFpqgxUav7eL7Q6d41MM9wnDgAAcKxGVfSfe+459erVS/Hx8YqPj9egQYP08ccfB5cPGzZMhmFU+5owYUK1MXbu3KkxY8YoOjpa6enpuueee+Tz+aqtM3/+fPXr109ut1udOnXSjBkzGuLlAQDQrOws2qUv9i5UwAyoTWyWzm15jmyNa9OjXkU5onRh6wvUNbGLJGlN3rf6+sAKyj4AoN41qln3W7durT/84Q867bTTZJqmXnnlFV166aVauXKlevToIUm6+eab9cgjjwQfEx0dHbzt9/s1ZswYZWZmavHixdq3b5+uu+46OZ1OPf7445Kkbdu2acyYMZowYYLeeOMNzZs3TzfddJNatGihkSNHNuwLBgAgQu0o2qGF+xbJlKm2cW01JHOwbEbzKflVbIZNZ6afoQRXgpblfKWN+RsVMP0akH4WM/IDAOpNoyr6F198cbXvH3vsMT333HNaunRpsOhHR0crMzOzxsd/8sknWr9+vT799FNlZGSoT58+evTRR3Xfffdp8uTJcrlcev7559W+fXs99dRTkqRu3brpyy+/1NNPP03RBwAgDPaU7AmW/PZx7TQ4c5DlJd+QlOZIC95uaJ0TT5PdsGnx/qXaVLBZATOggRkDLH9fAACRqdH+dfH7/XrzzTdVUlKiQYMGBe9/4403lJqaqtNPP13333+/SktLg8uWLFminj17KiMjI3jfyJEjVVhYqHXr1gXXueCCC6o918iRI7VkyZLjZqmoqFBhYWG1LwAAcKwDZblasHehTJlq10hKviR5XFGamDlREzMnyuOKsiRDx4SOGpI5WIYMbSncqkXZSxQwA5ZkAQBEtka1R1+Svv32Ww0aNEjl5eWKjY3Ve++9p+7du0uSrr76arVt21YtW7bUmjVrdN9992njxo169913JUnZ2dnVSr6k4PfZ2dknXKewsFBlZWWKijr2j/+UKVP08MMPh/21AgAQSQq8Bfp8z3z5Tb9aRrfQ4MyBjaLkNybt49vLZti1cN+X2l60XS6bU2eln8lh/ACAsGp0Rb9Lly5atWqVCgoK9M4772j8+PFasGCBunfvrltuuSW4Xs+ePdWiRQudf/752rJlizp27Fhvme6//37dfffdwe8LCwuVlZVVb88HAEBTU1JZqk93f6aKQIVS3Cka2vIc2Q271bEapbZxbSQN0Rf7Fur7gk2KdcaqR3J3q2MBACJIo/uY3eVyqVOnTurfv7+mTJmi3r17a+rUqTWuO2DAAEnS5s2bJUmZmZnav39/tXWqvq86r/9468THx9e4N1+S3G538EoAVV8AAOAwr9+reXs+U6mvVPHOOJ3XapicNqfVsaop95ZpWvY0TcuepnJvmdVx1Daujc5I6y9J+iZ3pbYXbbc2EAAgojS6on+0QCCgioqKGpetWrVKktSiRQtJ0qBBg/Ttt98qJycnuM7cuXMVHx8fPPx/0KBBmjdvXrVx5s6dW20eAAAAUDsBM6CF+75UgbdAUfYond/6PHkcHqtjHcOUdMB3QAd8B9RYLm7XLalr8NJ7i7KXaH9pzkkeAQBA7TSqon///ffriy++0Pbt2/Xtt9/q/vvv1/z583XNNddoy5YtevTRR7VixQpt375d77//vq677joNHTpUvXr1kiSNGDFC3bt317XXXqvVq1drzpw5+s1vfqOJEyfK7XZLkiZMmKCtW7fq3nvv1Xfffadnn31Wb7/9tiZNmmTlSwcAoEn65sBK7S3dJ7th1/BW5yrWGWt1pCalf1o/ZcVmKWAGNH/vAhV4mfAXAHDqGtU5+jk5Obruuuu0b98+JSQkqFevXpozZ44uvPBC7dq1S59++qmeeeYZlZSUKCsrS2PHjtVvfvOb4OPtdrs+/PBD3XrrrRo0aJBiYmI0fvx4PfLII8F12rdvr48++kiTJk3S1KlT1bp1a7344otcWg8AgDraXLBFG/K/kySdnTlIKZ4UixM1jA0bNoR1vFhFKyoqSmUq0+ytc9ShtJ3sCv/8BqmpqWrTpk3YxwUAND6Nqui/9NJLx12WlZWlBQsWnHSMtm3batasWSdcZ9iwYVq5cmWd8wEAgMNyynK0bP9XkqReyT3VNq6txYnqX+7+XMmQxo0bF/ax45Lj9ci7jyqlRYpeX/yG/nJ7zfMTnYro6Ght2LCBsg8AzUCjKvoAAKDxK6ks0fy9XyiggNrEZqlXSk+rIzWIosIiyZTumXKv+p3ZL+zjB2ym/KZfZ4w4U68vmyl7UfjOsNy6aasevPUB5ebmUvQBoBmg6AMAgFrzB/xasHehKvwVSnInaXDm4GZ3Dfg2HbLUrXe3ehn7YHme9pTuUSAxoLZZbRTnjKuX5wEARLZGNRkfAABo3FbkfqODFQflsrk0rOVQOW1NY5+BISnBnqAEe4Ia88cSKZ5kJbuTJEk7i3fJ6/danAgA0BQ1jb/OAADActuLtmtj/veSpLMzBzepGfY9rihNajEpeLsxaxndUmW+cpX5y7SjeIc6xneUzWDfDACg9virAQAATqrQW6gl2cskST2Suqt1bCuLE0Uum2FT29g2sht2lfnLlV2abXUkAEATQ9EHAAAn5Av4tGDvQvlMnzKi0tUntbfVkSKey+5SVkxrSVJuxUEVegstTgQAaEoo+gAA4IS+zlmufG++PHaPhrQY0iQPIy+vLNc/9v9D/9j/D5VXllsdp1biXfFKdadIknaV7OZ8fQBArTW9v9QAAKDB7Czaqc2FWyRJQ1qcrWhH4z6//XhM09Teyr3aW7lXpmlaHafWMqMzFWWPkt/0a1fJriaVHQBgHYo+AACoUamvVEv2/++8/BbRmRYnan5shk1tYrNkk00lvlLtL8uxOhIAoAmg6AMAgGOYpqnF2UvlDXiV7E5S79ReVkdqttx2t1rFHJ78MKc8R8WVxRYnAgA0dhR9AABwjI3532tf6T7ZDbuGZJ4tu2G3OlKzluROVJI7SZK0s3iXfAGfxYkAAI0ZRR8AAFSTX5Gvb3JXSpL6p/VVgjvB4kSQpFbRLeW2ueUzfZyvDwA4IYfVAQAAQN3t3LlTubm5YR/XlKmtUdvkt/sV64tR8dZifaNvwjb+hg0bwjZWc2MzbGob20abCjerqLJYB8pzlR6VZnUsAEAjRNEHAKCJ2blzp7p166bS0tKwj33xLy7RlXf/REWHinT7jyaqILcg7M8hScXFRfUy7olE26Ib/DnDzePwqGV0S+0p3aPssmzFOmMU7Wj6rwsAEF4UfQAAmpjc3FyVlpbqseceV4fTOoRtXNNhypfplyQlBhL0/Jt/D9vYVRbOW6hnp0xTeUXDXss+yhWle1veG7zdlCW7k1TsK1aBt0A7ineqc/xpstuYQwEA8D8UfQAAmqgOp3VQt97dwjKWaZraUrRVPl+p4pyxatepnQzDCMvYR9q2aVvYx2xuDMNQ6+hWKvOVyhuo1J7SPWoT28bqWACARoTJ+AAAgA5W5KnUVyqbbGoV3apeSj7Cx26zKysmS5KU7y3QoYpDFicCADQmFH0AAJo5r9+r7NJsSVJmdIZcdpfFicKvvLJc03Oma3rOdJVXNuxpA/UlxhmjjKh0SdKe0r3y+r0WJwIANBYUfQAAmjHTNLWndK8CCijaEa0Ud4rVkeqFaZra4d2hHd4dEXVZunRPuqId0QqYAe3kknsAgB9Q9AEAaMYKKgtVVFkkQ4Zax3DIflNjGIbaxGTJJptKfaXKKT9gdSQAQCNA0QcAoJkKmAHtK90nSUrzpMlj91icCKFw2V1qFdNSkrS/bL9KfeG/7CIAoGmh6AMA0EzllB1QZaBSTptT6VFpVsfBKUh0JSrBlSBJ2lm8S37Tb3EiAICVKPoAADRDFX6vDvxwmHfL6BayGWwSNGVVl9xz2pzyBrzaW7LP6kgAAAvxVx0AgGZoX+lemTIV64hVvDPe6jgIg8OX3GstSTrkPaR8b4HFiQAAVqHoAwDQzBR6i1RYWSRJahnTotlMwOc0nHIaTqtj1KtYZ6zSPIdPw9hTskfeQKXFiQAAVnBYHQAAADScgBnQ3tK9kqRUT2qzmYAvyhWlB1s9GLwdyTKi0lVcWawyf5l2F+9S+7j2VkcCADQw9ugDANCM5JYflDfglcNwKCMq3eo4qAc2w6Y2sVkyZKjYV6Lc8lyrIwEAGhhFHwCAZsIX8OlAeY4kKTM6U3bDbnEi1Be33a2W0YcvuZddtl+m07Q4EQCgIXHoPgAAzURO+QH5zYA8do+SXIlWx2lQFZUVeiP3DUnShZUj5HBG/iZQsjtJhZWFKqoski/ZL7uTD3YAoLlgjz4AAM2A1+/VwfKDkqQWUZnNZgK+KgEzoE3lm7SpfJMCZsDqOA3CMAy1jml1+MgNl3TprT+2OhIAoIFQ9AEAaAayy/b/cDm9GMU6Y62OgwbitDnV6odD+C/+xSUqs5VZnAgA0BDCdtxaaWmp3nzzTVVUVOiiiy5S27ZtwzU0AAA4BWW+MuV78yVJmdHN53J6OCzRnahdObtlj7Frt22vfAGfHLbIP3UBAJqzkH7L33jjjVq2bJnWrl0rSfJ6vRo4cGDw+4SEBH322Wfq27dv+JICAICQ7CvNliQluhIU7YjsS8uhZvZ8mw6U5CopPUmrclfrjPT+VkcCANSjkA7d//zzz3X55ZcHv585c6bWrl2rN954Q2vXrlVmZqYefvjhOo/73HPPqVevXoqPj1d8fLwGDRqkjz/+OLi8vLxcEydOVEpKimJjYzV27Fjt37+/2hg7d+7UmDFjFB0drfT0dN1zzz3y+XzV1pk/f7769esnt9utTp06acaMGXXOCgBAU1BUWaRiX7EMGcqMyrQ6DixiBAy99OCLkqQN+d8ppyzH4kQAgPoUUtHPzs5Wu3btgt//5z//0RlnnKGf/exn6t69u26++WYtW7aszuO2bt1af/jDH7RixQotX75c5513ni699FKtW7dOkjRp0iR98MEH+te//qUFCxZo79691T5w8Pv9GjNmjLxerxYvXqxXXnlFM2bM0EMPPRRcZ9u2bRozZoyGDx+uVatW6a677tJNN92kOXPmhPJWAADQaJmmqewf9uanuJPlsrssTgQrrflitRIrEyRJS7KXyhfwneQRAICmKqSiHxMTo/z8fEmSz+fT/PnzNXLkyODyuLg4FRQU1Hnciy++WBdddJFOO+00de7cWY899phiY2O1dOlSFRQU6KWXXtKf//xnnXfeeerfv7+mT5+uxYsXa+nSpZKkTz75ROvXr9frr7+uPn36aPTo0Xr00Uc1bdo0eb1eSdLzzz+v9u3b66mnnlK3bt1022236YorrtDTTz8dylsBAECjVVhZqDJ/uWyyKT0q3eo4aAQyKzIUZY9SYWWR1hz81uo4AIB6ElLR79evn1544QWtXLlSjz32mIqKinTxxRcHl2/ZskUZGRmnFMzv9+vNN99USUmJBg0apBUrVqiyslIXXHBBcJ2uXbuqTZs2WrJkiSRpyZIl6tmzZ7XnHjlypAoLC4NHBSxZsqTaGFXrVI1Rk4qKChUWFlb7AgCgMTNNU/t/ODw71ZPS7Cdfi3JFaXLryZrcerKiXM13ngK77BqQcZYkaf2hDcr94ZKLAIDIElLRf+yxx5STk6MzzjhDDz/8sMaOHauzzjoruPy9997T2WefHVKgb7/9VrGxsXK73ZowYYLee+89de/eXdnZ2XK5XEpMTKy2fkZGhrKzDx+WmJ2dfcwHDFXfn2ydwsJClZXVfMmZKVOmKCEhIfiVlZUV0msDAKChFHgLVO4vl82wKdWTZnUcNCJZsa3VLq6dTJlakr1EftNvdSQAQJiF9PH+GWecoe+++06LFy9WYmKizj333OCy/Px8/fKXv6x2X1106dJFq1atUkFBgd555x2NHz9eCxYsCGmscLn//vt19913B78vLCyk7AMAGq0j9+aneVLlsNktToTG5sz0/tpXuk/53gKtPbhOvVN7WR0JABBGIR/Hl5aWpksvvfSY+xMTE3XnnXeGHMjlcqlTp06SpP79++vrr7/W1KlTddVVV8nr9So/P7/aXv39+/crM/PwLMKZmZn66quvqo1XNSv/kescPVP//v37FR8fr6iomg/lc7vdcrvdIb8mAAAaUr63QBWBCtkNu1LdqVbHaRQqKiv09sG3JUkXVo6Qw9m8T2Xw2D0akH6mvtj3pb7NW6s2cVlKcidZHQsAECan9FeuqKhIO3bs0KFDh2Sa5jHLhw4deirDS5ICgYAqKirUv39/OZ1OzZs3T2PHjpUkbdy4UTt37tSgQYMkSYMGDQqeVpCefnjSoblz5yo+Pl7du3cPrjNr1qxqzzF37tzgGAAANGWH9+Yf/kA7zZMqO3vzJUkBM6D1ZeuDtyG1iW2jrNgs7SrepaX7v9KorBEyDMPqWACAMAip6B88eFC33Xab/v3vf8vvP/a8LtM0ZRhGjctO5P7779fo0aPVpk0bFRUVaebMmZo/f77mzJmjhIQE3Xjjjbr77ruVnJys+Ph43X777Ro0aJAGDhwoSRoxYoS6d++ua6+9Vk888YSys7P1m9/8RhMnTgzukZ8wYYL+9re/6d5779UNN9ygzz77TG+//bY++uijUN4KAAAalUPefHkDXtkNu1I8KVbHQSNmGIbOSjtD2aX7lFueq00Fm9U58TSrYwEAwiCkon/zzTfrgw8+0B133KFzzjlHSUnhOdQrJydH1113nfbt26eEhAT16tVLc+bM0YUXXihJevrpp2Wz2TR27FhVVFRo5MiRevbZZ4OPt9vt+vDDD3Xrrbdq0KBBiomJ0fjx4/XII48E12nfvr0++ugjTZo0SVOnTlXr1q314osvVrs8IAAATZFpmsoJnpufJrvB3nycWLQzWr1Temv5gRX6JnelsmJbK8rRfK9KAACRIqSi/8knn2jSpEl64oknwhrmpZdeOuFyj8ejadOmadq0acddp23btsccmn+0YcOGaeXKlSFlBACgscr/YW++w3Aolb35qKUuiZ21tXCb8irytPzACp3TYojVkQAApyiky+tFR0erXbt2YY4CAABCdXhv/gFJUqonVTYjpD/xaIZshk0DMwbIkKHtRTu0t2Sv1ZEAAKcopK2AcePG6b333gt3FgAAEKKCI2baT/EkWx0HTUyKJ1ldErtIkpblfC1fwGdxIgDAqQjp0P0rrrhCCxYs0KhRo3TLLbcoKytLdvux5wH269fvlAMCAIATM01TOeWHz81P9aRwbj5C0ie1l3YW71RxZbHW5q1Tn9TeVkcCAIQopKI/ZMj/zt2aO3fuMctDnXUfAADUXWFlkcr9FbLJphR3qtVxGiWP06MHWj4QvI1jOW1OnZl2hhbs+0LrDq1Xx/gOinPFWR0LABCCkIr+9OnTw50DAACE4MiZ9lM8KXLY2JtfE8Mw5LK5grdRs6zY1moRnal9pdlafuAbDW91rtWRAAAhCKnojx8/Ptw5AABACIori1XmL5MhQ2ke9ubj1BiGoTPTztAHOz7S7pLd2luyVy1jWlodCwBQR6c8JW9xcbE2bNigDRs2qLi4OByZAABALZgytb/8yL35IX1+3yx4fV69l/ee3st7T16f1+o4jVqCO0Fdkw5PzPd1znL5TU7FBICmJuSi//XXX2v48OFKSkrS6aefrtNPP11JSUk677zztHz58nBmBAAANTDdpkp9pezNrwV/wK/Vpau1unS1/AGK68n0Su4pj92jwsoifXdoo9VxAAB1FNJH/8uWLdOwYcPkcrl00003qVu3bpKkDRs26J///KeGDh2q+fPn66yzzgprWAAA8D+BOFOSlOROktPmtDgNIonL7lK/1D5avH+p1hz8Vu3j2yvaEWV1LABALYVU9B988EG1atVKX375pTIzM6stmzx5ss4++2w9+OCDNc7IDwAATl3bbm1lRh0u+mmeNIvTIBJ1iO+g7ws2Kbf8oFbmrtTZmYOtjgQAqKWQDt1ftmyZfvGLXxxT8iUpIyNDt9xyi5YuXXrK4QAAQM3G3PwjSVKiK0Fuu8viNIhEhmHozPQzJUlbC7cprzzP4kQAgNoKqejbbDb5fL7jLvf7/bLZTnmePwAAUIMKw6uzRg2QxN581K9UT4raxbWVJK3IXSnTNC1OBACojZDa+ODBgzVt2jTt2LHjmGU7d+7Us88+q7PPPvuUwwEAgGMddB2UzW6TUWYoivOmUc/6pvaRzbApuzRbe0v3WR0HAFALIZ2j//jjj2vo0KHq2rWrLrvsMnXu3FmStHHjRv33v/+Vw+HQlClTwhoUAABIpb4y5TsKJEm2QpvUyuJAiHixzlh1Teyi9Yc26JsD36hFdKZsBkduAkBjFlLR79u3r5YtW6YHH3xQ77//vkpLSyVJ0dHRGjVqlH7/+9+re/fuYQ0KAACk7w59J9Mw9f0336t7Wjer4zQZHqdH97S4J3gbdXN6cg9tLtiifG+BthZuU6eEjlZHAgCcQEhFX5K6d++u9957T4FAQAcOHJAkpaWlcW4+AAD1xOv36vuC7yVJH/79ffX4DR+q15ZhGIqxxwRvo27cdrd6ppyuFQe+0arc1Wob11ZOW8ibkQCAenbKrdxmsykjI0MZGRmUfAAA6tHGgu9VGfDJ7Xdr9YLVVsdBM9MlobNinbEq85dpw6ENVscBAJxArT6KfeSRR2QYhh588EHZbDY98sgjJ32MYRj67W9/e8oBAQCA5A/4tfHQRklSamUys5/Xkdfn1UeHPpIkjfCNlMPJ3ui6stvs6pPSW19mL9K6vPXqnHiaPHZOgwCAxqhWf+UmT54swzB03333yeVyafLkySd9DEUfAIDw2V60XWX+ckXZoxTvS7A6TpPjD/j1dcnXwdsITbu4tlp/aIPyKvK0Lm+9+qf1szoSAKAGtTrWPhAIyO/3y+VyBb8/2Zffzx9RAADCwTRNrf/hUOmuSV1kE+eYwxqGYahPai9J0sb871XmK7M4EQCgJpxUDwBAI7evdJ/yvQVyGA51TjjN6jho5lpGt1SaJ1V+06+1eeusjgMAqEFIRd9ut2vmzJnHXf7WW2/JbreHHAoAAPxP1d78Tgkd5bK7LE6D5s4wDPVO7S1J+r5gk0oqSyxOBAA4WkhF/2QTAPn9fi5dAwBAGORVHNK+0mwZMtQ1qavVcQBJUovoTGVEZShgBvRt3lqr4wAAjhLyofvHK/KFhYWaM2eOUlNTQw4FAAAOq7qMWZvYLMU5Yy1OA/xP1bn6mwu2qMhbZHEaAMCRal30H374YdntdtntdhmGoXHjxgW/P/IrKSlJr732mn7605/WZ24AACJeaWWpthfukCR1T+pmcRqguvSodLWMbiFTJnv1AaCRqfVFZM866yz98pe/lGmaevbZZ3XhhReqc+fO1dYxDEMxMTHq37+/Lr/88rCHBQCgOfkuf6MCCig9Kk2pURwpdyrcDrfuzLwzeBvh0Tu1t/bu3Kethdt0enIPxbvirY4EAFAdiv7o0aM1evRoSVJJSYkmTJigAQMG1FswAACas8pApTYVbJbE3vxwsNlsSnIkBW8jPFI9KWod00q7S/Zobd46Dc4cZHUkAIDqUPSPNH369HDnAAAAR9hcsEXegFdxzji1jmltdRxEiA0bNoR9TKfNKUVLWwq2yrbPJpfpDPtzpKamqk2bNmEfFwAiVUhFv8ru3bu1cuVKFRQUKBAIHLP8uuuuO5XhAQBolgJmQBsOfSdJ6p7UlSvZhEGlr1Kf5H8iSRrpGyWH85Q2gZqc3P25kiGNGzeuXsa/9+X7dPrZPfXcf57Tq4+8Evbxo6OjtWHDBso+ANRSSH/lysvLNX78eP373/9WIBCQYRjBS+4duTFC0QcAoO52Fe9Sia9EbptbHeI7WB0nIvgCPi0uXhy83dwUFRZJpnTPlHvV78x+YR8/4A7Ir4AuuPpCjRo2SkYgfB9Obd20VQ/e+oByc3Mp+gBQSyEV/QceeEDvvvuuHnvsMQ0aNEjDhg3TK6+8ohYtWuiZZ57R3r179eqrr4Y7KwAAEc80Ta374ZJ6nRNPk8PWvPY8o3616ZClbr3DP+eDaZraUrRVpb5SJXZMUsvoFmF/DgBA7YU0G80777yjn//857rvvvvUo0cPSVKrVq10wQUX6MMPP1RiYqKmTZsW1qAAADQHB8oP6GD5QdkMm7okdj75A4BGwDAMpXvSJEl55XnN8qgJAGhMQir6OTk5OuussyRJUVFRkg7PxF9l7Nixevfdd8MQDwCA5mV93uG9+R3i2ivKEWVxGqD24pxx8tg9Ciig3PKDVscBgGYtpKKfkZGhgwcP/wKPjo5WUlKSNm7cGFxeWFio8vLyOo87ZcoUnXnmmYqLi1N6erp+/OMfVxtXkoYNGybDMKp9TZgwodo6O3fu1JgxYxQdHa309HTdc8898vmqf7I8f/589evXT263W506ddKMGTPqnBcAgHAq9BZqV8luSVxSD02PYRhKj0qXJB2syJXf9FucCACar5CK/oABA/Tll18Gv7/44ov15JNP6o033tBrr72mp59+WgMHDqzzuAsWLNDEiRO1dOlSzZ07V5WVlRoxYkS1owUk6eabb9a+ffuCX0888URwmd/v15gxY+T1erV48WK98sormjFjhh566KHgOtu2bdOYMWM0fPhwrVq1SnfddZduuukmzZkzJ4R3AwCA8Kiaab9VTEsluBMsTgPUXYIzXm6bW34zoIPleVbHAYBmK6QZfu644w7961//UkVFhdxutx599FEtWbJE1157rSSpY8eO+stf/lLncWfPnl3t+xkzZig9PV0rVqzQ0KFDg/dHR0crMzOzxjE++eQTrV+/Xp9++qkyMjLUp08fPfroo7rvvvs0efJkuVwuPf/882rfvr2eeuopSVK3bt305Zdf6umnn9bIkSPrnBsAgFNV7i/XlsKtktibj6bLMAylRaVpd8lu5ZbnKtWTIpsR0n4lAMApCOk375AhQzR16lS53W5JUlZWljZs2KCVK1dqzZo12rBhg7p06XLK4QoKCiRJycnJ1e5/4403lJqaqtNPP13333+/SktLg8uWLFminj17KiMjI3jfyJEjVVhYqHXr1gXXueCCC6qNOXLkSC1ZsqTGHBUVFSosLKz2BQBAOH2fv0l+069kd7IyojJO/gDUidvh1i8zfqlfZvxSbofb6jgRLdGVIIfhkM/0Kd9bYHUcAGiWQtqjX1BQoISE6ocU2mw29e7dOyyhJCkQCOiuu+7S2WefrdNPPz14/9VXX622bduqZcuWWrNmje677z5t3LgxOPlfdnZ2tZIvKfh9dnb2CdcpLCxUWVlZcILBKlOmTNHDDz8cttcGAMCR/AG/NuZ/L0nqntRVhhG+a5DjMJvNpnRnevA26o/NsCnVk6rssmzllh9QkiuRf9MA0MBCKvrp6ekaNWqUrrrqKl1yySWKjY0Ndy5NnDhRa9eurTYXgCTdcsstwds9e/ZUixYtdP7552vLli3q2LFj2HNI0v3336+77747+H1hYaGysrLq5bkAAM3P1qJtKveXK9oRrbZxba2OA5yyFHeycspyVO6vUHFlseJccVZHAoBmJaSPtO+++26tW7dO48aNU3p6uq644gr961//UllZWVhC3Xbbbfrwww/1+eefq3Xr1idcd8CAAZKkzZs3S5IyMzO1f//+autUfV91Xv/x1omPjz9mb74kud1uxcfHV/sCACAcTNPUhkOHL6nXLbEr5zPXk0pfpT4v+FyfF3yuSl+l1XEint1mV7I7SZJ0oPyAxWkAoPkJaWtiypQp2rx5s5YtW6Zf/vKXWr58ua666iqlp6frZz/7mf7zn//I6/XWeVzTNHXbbbfpvffe02effab27duf9DGrVq2SJLVo0UKSNGjQIH377bfKyckJrjN37lzFx8ere/fuwXXmzZtXbZy5c+dq0KBBdc4MAMCp2FuyVwXeQjltDnVKqJ8j0yD5Aj4tKFqgBUUL5Av4Tv4AnLJUT6okqdhXojJfeHYGAQBq55R2G5x55pn605/+pO3bt2vRokW68cYbtXDhQo0dO/aYc+BrY+LEiXr99dc1c+ZMxcXFKTs7W9nZ2cEjBbZs2aJHH31UK1as0Pbt2/X+++/ruuuu09ChQ9WrVy9J0ogRI9S9e3dde+21Wr16tebMmaPf/OY3mjhxYnDywAkTJmjr1q2699579d133+nZZ5/V22+/rUmTJp3K2wEAQJ2t/2FvfqeETnLZXRanAcLHZXcp0XV4TqcD5bkWpwGA5iWkc/RrMmjQIKWmpiopKUl//vOfQ5qZ/rnnnpMkDRs2rNr906dP1/XXXy+Xy6VPP/1UzzzzjEpKSpSVlaWxY8fqN7/5TXBdu92uDz/8ULfeeqsGDRqkmJgYjR8/Xo888khwnfbt2+ujjz7SpEmTNHXqVLVu3Vovvvgil9YDADSovPI8ZZftlyFD3RK7Wh0HCLtUT5ryvQXK9+Yr05/Bh1kA0EBOuehv27ZNb731lt5++22tXr1aNptNw4cP11VXXVXnsUzTPOHyrKwsLViw4KTjtG3bVrNmzTrhOsOGDdPKlSvrlA8AgHCq2pvfNq6NYpwxFqcBwi/aEaVYR4yKfSXKrTioltEtrI4EAM1CSEV/165devvtt/XWW29pxYoVMgxD55xzjqZNm6axY8cqLS0t3DkBAIgoJZUl2l60Q5LUPambxWmA+pPqSVNxcYnyyvOUEZUuu2G3OhIARLyQin7btm1lGIYGDhyop59+WldeeWVwMjwAAHBy3+VvlClTGVEZSvGkWB0HqDdxzli5bW5VBCp0qOJQcJI+AED9CanoP/nkk/rJT37CteQBAAiB11+pTQWHLwvbPYlz8xHZDMNQqidFe0r3Krf8oFLcKTIMw+pYABDR6lz0S0tLNXPmTMXExGjChAn1kQkAgIi2uXCzKgOVinfFq1VMK6vjNAsuh0s3p98cvI2GleROUnbZfnkDXhVWFinBFW91JACIaHW+vF50dLS2bdvGJ7EAAIQgYAb03aHvJEndE7vx97SB2G12tXK1UitXK9ltnCPe0GyGTcnuZElSLpfaA4B6V+eiL0mjRo3SnDlzwp0FAICIt6Nop0p8pXLb3eoQ397qOECDSfmh6Jf4SlTmK7M4DQBEtpCK/m9/+1t9//33uvbaa/Xll19qz549ysvLO+YLAAD8j2mawUvqdU3swp7lBlTpq9SiokVaVLRIlb5Kq+M0Sy67SwmuBElSbvlBi9MAQGQLaTK+Hj16SJLWr1+vmTNnHnc9v98fWioAACJQTlmO8iryZDfs6pxwmtVxmhVfwKe5BXMlSQ8FfmdxmuYr1ZOqAm+B8r35ahHIlMMW0qYoAOAkQvrt+tBDD3FOIQAAdVS1N79jfAd5HB6L0wANL8YRrWh7lEr9ZTpYcVAZURlWRwKAiBRS0Z88eXKYYwAAENkKvAXaXbJHktSNS+qhGUv1pGpnyS4dLM9TmidNNiOkM0kBACcQlt+sBQUFHKYPAMAJbPhhpv3WMa0Vz6XF0IwluBLkNBzymT4VeAusjgMAESnkor98+XKNGjVK0dHRSklJ0YIFCyRJubm5uvTSSzV//vxwZQQAoEkr85VrS+FWSVL3pG4WpwGsZRiGUjwpkqQD5bkyTdPiRAAQeUIq+osXL9aQIUO0adMmjRs3ToFAILgsNTVVBQUF+vvf/x62kAAANGXf53+vgBlQijtF6VFpVscBLJfsTpYhQ+X+cpX4Sq2OAwARJ6Si/8ADD6hbt25av369Hn/88WOWDx8+XMuWLTvlcAAANHW+gE8bC76XJHVP7spktoAkh82hJHeSJCm3PNfiNAAQeUKajO/rr7/WlClT5Ha7VVxcfMzyVq1aKTs7+5TDAQDQ1G0t3KYKf4ViHDFqE9vG6jjNlsvh0vjU8cHbsF6qJ0V5FXkqrCxUhd8rt52fCwCES0h79J1OZ7XD9Y+2Z88excbGhhwKAIBIYJqmNvxwSb1uSV2ZXdxCdptd7T3t1d7TXnab3eo4kOSxexTrPLy9eJC9+gAQViFtcQwcOFDvvPNOjctKSko0ffp0nXvuuacUDACApm53yR4VVhbJaXOqU0JHq+MAjU6aO1WSlFdxSH6TKzgBQLiEVPQffvhhLV++XGPGjNHHH38sSVq9erVefPFF9e/fXwcOHNBvf/vbsAYFAKCpWf/D3vzOCafJaXNanKZ58/kr9VXxV/qq+Cv5/JVWx8EPYp2xctvcCiigQxWHrI4DABEjpKI/YMAAzZo1S5s3b9Z1110nSfrVr36lW265RX6/X7NmzVKvXr3CGhQAgKbkYPlB5ZTlyJChLoldrI7T7FX6fZqVP0uz8mep0u+zOg5+YBiGUn+41F5u+UEutQcAYRLSZHySdN5552njxo1atWqVNm3apEAgoI4dO6p///7MKAwAaPaq9ua3j2unGGe0xWmAxivJnaTssv3yBrwqrCxSgive6kgA0OSFXPSr9OnTR3369AlDFAAAGtbOnTuVmxv+ScC8RqW2R++QDMnYL32z75uwjr9hw4awjgdYyWbYlOxO1oHyA8otz6XoA0AYhFT0V61apQ0bNuhnP/tZ8L45c+boscceU0VFha6++mrdeeedYQsJAEC47dy5U926dVNpaWnYx77619do1M9Ha93itbru5+PCPn6V4uKiehsbaEgpnhQdKD+gEl+JynxlinJEWR0JAJq0kIr+vffeq+jo6GDR37Ztmy677DKlpKSoZcuWuvvuuxUVFaVbbrklrGEBAAiX3NxclZaW6rHnHleH0zqEbVzTMOVreXj28F6n9dI/P30zbGNXWThvoZ6dMk3lFeVhHxuwgsvmVIIrQQXeAuWWH1RWbGurIwFAkxZS0V+9erXuueee4Pevvvqq7Ha7Vq5cqdTUVF111VV6/vnnKfoAgEavw2kd1K13t7CNl1N2QNll2XLb3erc+bR6mbdm26ZtYR8TsFqaJ1UF3gLle/PVIpAph+2UzzAFgGYrpFn3CwoKlJKSEvx+1qxZuvDCC5WaevhaqBdeeKE2b94cnoQAADQRATOgg+WHz/lP86QyOS1QB9GOaEXbo2TK1MGKg1bHAYAmLaSi36JFi+BEQPv27dOKFSs0YsSI4PLi4mLZbCENDQBAk1XgLVCl6ZPDcCjRlWh1HBzBaXfq6pSrdXXK1XLanVbHwXGkeg7vNDpYnqeAGbA4DQA0XSEdE3XppZfqr3/9q8rLy7Vs2TK53W5ddtllweWrV69Whw7hO98RAIDGzjRNHfhhb36KJ0U2gw+8GxOH3aHOUZ2Dt9E4JbgS5CzLVmWgUvneAiW7k6yOBABNUkhbIb///e91+eWX67XXXlNOTo5mzJihjIwMSVJhYaHeeeedanv4AQCIdCW+EpX7y2XIUIo72eo4QJNkGIZS3IdPD80tz5VpmhYnAoCmKaSPtGNjY/XGG28cd9nu3bsVHR19SsEAAGhKDpQfkCQlu5OYRKwR8vkrtbJkpSRplH+UHE5+Ro1VsjtJ+8v2q9xfrhJfidVxAKBJOuXjCk3TVE5OjnJycmSapmw2mxISEuR0cv4bAKB5KPeXq6iyWNL/zjFG41Lp9+m/h/6r/x76ryr9Pqvj4AQcNoeSfjhkP7ecSfkAIBQhF/3169friiuuUHx8vFq0aKEWLVooPj5eV1xxhdauXRvOjAAANGpV5+bHO+PltrstTgM0famew4fvF1YWyrRz+D4A1FVIx60tXLhQo0ePViAQ0KWXXqrOnQ9PbrNx40a9//77+vjjjzV79mydc845YQ0LAEBjUxmoVH5FvqTDl9QDcOo8do/inLEqqixWII7Z9wGgrkIq+pMmTVJ6eroWLFigrKysast27dqloUOH6u6779bXX38dlpAAADRWB8sPypSpaHuUYpwxVscBIkaqO/Vw0Y8x5YmJsjoOADQpIR26v27dOv3yl788puRLUlZWlm699VatW7euzuNOmTJFZ555puLi4pSenq4f//jH2rhxY7V1ysvLNXHiRKWkpCg2NlZjx47V/v37q62zc+dOjRkzRtHR0UpPT9c999wjn6/6+Xjz589Xv3795Ha71alTJ82YMaPOeQEAzVvADOhgRZ4kKS0qzeI0QGSJdcbKbXNLNmno2KFWxwGAJiWkot+2bVtVVFQcd7nX663xQ4CTWbBggSZOnKilS5dq7ty5qqys1IgRI1RS8r8ZVydNmqQPPvhA//rXv7RgwQLt3btXl19+eXC53+/XmDFj5PV6tXjxYr3yyiuaMWOGHnrooeA627Zt05gxYzR8+HCtWrVKd911l2666SbNmTOnzpkBAM1XXsUh+U2/XDaX4p3xVscBIophGMFz9S+8doRMca4+ANRWSIfuP/TQQ5o0aZLGjBmjPn36VFu2cuVK/fWvf9UzzzxT53Fnz55d7fsZM2YoPT1dK1as0NChQ1VQUKCXXnpJM2fO1HnnnSdJmj59urp166alS5dq4MCB+uSTT7R+/Xp9+umnysjIUJ8+ffToo4/qvvvu0+TJk+VyufT888+rffv2euqppyRJ3bp105dffqmnn35aI0eODOUtAQA0M6ZpKveHSfhSPSkyDMPiREDkSXInaU/RXmW0yVBRWbHVcQCgyahV0b/jjjuOuS8jI0P9+/fX4MGD1alTJ0nSpk2btGTJEp1++ulaunSpfvazn51SuIKCAklScnKyJGnFihWqrKzUBRdcEFyna9euatOmjZYsWaKBAwdqyZIl6tmzpzIyMoLrjBw5Mng6Qd++fbVkyZJqY1Stc9ddd9WYo6KiotoRDIWFhaf0ugAATV9hZaG8Aa/shl3J7mSr4+AknHanrky+MngbTYPNsMlWYigQb+qgM8/qOADQZNSq6P/tb3877rJFixZp0aJF1e779ttvtXbtWk2dOjXkYIFAQHfddZfOPvtsnX766ZKk7OxsuVwuJSYmVls3IyND2dnZwXWOLPlVy6uWnWidwsJClZWVKSqq+oQvU6ZM0cMPPxzyawEARJ6qS+olu5NlM0K+Wi0aiMPuUI/oHsHbaDpsxTZ5oypU6ixVXnmekj18sAYAJ1OrLZNAIFDnL7/ff0rBJk6cqLVr1+rNN988pXHC4f7771dBQUHwa9euXVZHAgBYqMRXqlJfqQz97xxiAPXD8Bv6evZXkqQN+RtPsjYAQApxMr76dtttt+nDDz/U559/rtatWwfvz8zMlNfrVX5+frX19+/fr8zMzOA6R8/CX/X9ydaJj48/Zm++JLndbsXHx1f7AgA0XwfKDkiSEl2Jcto4DLwp8Pl9Wle6TutK18nn9538AWhU5rxyeB6nbYXbVFJZcpK1AQCnVPS3bdumZ599Vvfdd5/uu+8+Pfvss9q2bVvI45mmqdtuu03vvfeePvvsM7Vv377a8v79+8vpdGrevHnB+zZu3KidO3dq0KBBkqRBgwbp22+/VU5OTnCduXPnKj4+Xt27dw+uc+QYVetUjQEAwPGU+8tVWHl4rpa0qFSL06C2Kv2V+lfev/SvvH+p0l9pdRzU0dZvtyrGFy1TptYf2mB1HABo9EI+Se1Xv/qVpk6dqkAgUO1+m82mu+66S3/605/qPObEiRM1c+ZM/fe//1VcXFzwnPqEhARFRUUpISFBN954o+6++24lJycrPj5et99+uwYNGqSBAwdKkkaMGKHu3bvr2muv1RNPPKHs7Gz95je/0cSJE+V2uyVJEyZM0N/+9jfde++9uuGGG/TZZ5/p7bff1kcffRTq2wEAaCYOlB0+Nz/eGS+P3WNxGqD5SK1MUYmjVJsKNqtnyun8/wcAJxDSHv2nnnpKTz/9tC6//HItWbJE+fn5ys/P15IlS3TFFVfo6aef1tNPP13ncZ977jkVFBRo2LBhatGiRfDrrbfeCq7z9NNP60c/+pHGjh2roUOHKjMzU++++25wud1u14cffii73a5BgwZp3Lhxuu666/TII48E12nfvr0++ugjzZ07V71799ZTTz2lF198kUvrAQBOqDJQqXxvviQpzcPefKAhxfhjlOxOlt/067tDnKsPACcS0h79F154QZdcconefvvtavcPGDBAb775psrLy/X3v/9dkyZNqtO4pmmedB2Px6Np06Zp2rRpx12nbdu2mjVr1gnHGTZsmFauXFmnfACA5u1Aea5MmYpxRCvGGWN1HKBZMWTo9OQe+mLfQm3M/149krszRwYAHEdIe/S3b99+wr3fI0eO1Pbt20PNBABAo+MP+JVXfvg63mmeNIvTAM1TVmxrxTvj5A14tSl/s9VxAKDRCqnop6ena/Xq1cddvnr1aqWlsREEAIgcBysOKqCAPHa34pxxVscBmiWbYVOP5B6SpPWHNsgfOLXLOQNApAqp6F955ZV68cUX9Yc//EElJf+7xElJSYn++Mc/6sUXX9RVV10VtpAAAFgpYAaUW35Q0uG9+YZhWJwIaL7ax7dTtCNKZf4ybS0M/WpPABDJQjpH/9FHH9WqVav0wAMP6KGHHlLLli0lSXv37pXP59Pw4cOrTX4HAEBTdqjikHymT06bU4muRKvjIAROu0OXJl0avI2my27Y1S2pm1Yc+EbrDq1Xx4QOshmndMVoAIg4If2li46O1rx58/Tf//5XH3/8sXbs2CFJGjVqlC666CJdfPHF7O0AAEQE0zSVU35A0uGZ9vn71jQ57E71jekbvI2m7bSETlp7cJ2KKou0vWi7OsR3sDoSADQqp/SR9qWXXqpLL700XFkAAGh0DnkPqTJQKYfhULI72eo4ACQ5bU51T+6mlbmrtObgWrWLa8defQA4Ar8RAQA4DtM0lVOWI+nw3nyKRNPl8/v0fdn3+r7se/n8PqvjIAy6JHaW2+YO7tUHAPwPWywAABzHIW++vIFK2Q27UjwpVsfBKaj0V2rmwZmaeXCmKv2VVsdBGFTt1ZekNQfXKmAGLE4EAI0HRR8AgBpU35ufxt58oBFirz4A1IytFgAAapDvzZc34P1hbz7n5gONEXv1AaBmtSr6f/nLX/T999/XdxYAABqFw3vz/zfTvt2wW5wIwPF0Sewst/3wXv1t7NUHAEm1LPqTJk3S8uXLg9/b7XbNnDmz3kIBAGClAm+BKgIVnJsPNAFOm1M9kg7v1f+WvfoAIKmWRT8pKUn79+8Pfm+aZr0FAgDASqZpav8P5+anelLYmw80AZ2P2Ku/pXCr1XEAwHKO2qw0bNgwTZ48WatWrVJCQoIk6dVXX9XSpUuP+xjDMDR16tTwpAQAoIHkVRwK7s1P9aRaHQdALThtTp2e3EMrDnyjNQe/Vfu4dnLYarWZCwARqVa/AZ999lnddddd+uSTT5STkyPDMPTJJ5/ok08+Oe5jKPoAgKYmYAa0v+zwEWwZUenszY8gTrtDFyVeFLyNyNMlobM2HPpOpb5Sbcz/Xj2Su1sdCQAsU6tD99PT0zVz5kzt27dPfr9fpmnq9ddfVyAQOO6X3++v7+wAAIRVbnmufKZPTptTyW5m2o8kDrtTZ8WepbNiz5LD7rQ6DuqB3WZXn5RekqS1eevk9XstTgQA1gnp8nrTp0/X4MGDw50FAADL+AI+5ZQfnmk/MypDNoMr0AJNTfv49kpwJcgb8GrdofVWxwEAy4R07Nr48eODt9evX68dO3ZIktq2bavu3TlMCgDQ9OSUH1DADMhj9yjRlWh1HISZP+DXtvJtwduO0DaB0MjZDJv6pvbW/L1faMOh79QlsbOiHdFWxwKABhfy7or//ve/6tixo3r27Kkf/ehH+tGPfqSePXuqU6dOev/998OZEQCAeuX1e3Ww/KAkqUVUpgzDsDgRws3r8+qV3Ff0Su4r8vo4pDuStY5prTRPqvymX2sOfmt1HACwREhFf9asWRo7dqwk6fHHH9d7772n9957T48//rhM09Tll1+u2bNnhzUoAAD1ZX9ZjkyZinHEKNYZa3UcAKfAMAz1Te0rSdpcsEWF3kKLEwFAwwvpuLVHH31UvXr10sKFCxUTExO8/5JLLtFtt92mIUOG6OGHH9aoUaPCFhQAgPoQcJo65D0kSWoRzd58IBJkRKerVUxL7SnZq29yV2lYy6FWRwKABhXSHv01a9Zo/Pjx1Up+lZiYGF1//fVas2bNKYcDAKA+GYahQNLhq8QkuhI5lxeIIP1S+8qQoV3Fu5Rdmm11HABoUCEVfY/Ho7y8vOMuz8vLk8fjCTkUAAAN4ZzLz5HplmyyqUV0ptVxAIRRojtRnRNOkyQtP/CNAmbA4kQA0HBCKvrnnXeepk6dqiVLlhyzbNmyZfrLX/6iCy644JTDAQBQX/zy6yf/91NJUkZUupw2rq0ORJpeqT3lsrl0qOKQthRutToOADSYkM7Rf+KJJzRo0CANGTJEZ511lrp06SJJ2rhxo7766iulp6frj3/8Y1iDAgAQTjmuA4qPjZcqpdSkVKvjAKgHHrtHvVJ6avmBFVqVu1ptY9vKZedDPQCRL6Q9+u3bt9eaNWt0xx136NChQ3rrrbf01ltv6dChQ7rzzju1evVqtWvXLsxRAQAIj7yKQ8pzHp6Az37IxgR8zYDD5tCFCRfqwoQL5bCFtJ8DTVTnxNMU74xTub9ca/PWWh0HABpEyH/p0tPT9fTTT+vpp58OZx4AAOqVaZr6OudryZCWfbxMQ04/2+pIaABOh1Nnx50dvI3mw27Y1T+tnz7fu0Ab8r/TaQmdFOeKszoWANSrkPboAwDQVG0u3KKcsgMyTEP//MMbVscB0ABaxbRSi+hMBcyAVuSutDoOANQ7ij4AoNkorSzVigPfSJLSvWnKyz7+FWQQWfwBv/Z492iPd4/8Ab/VcdDADMNQ/7T+wcvt7SnZY3UkAKhXFH0AQLNgmqaW5XylykClUtwpSqlMtjoSGpDX59ULOS/ohZwX5PV5rY4DCyS5E9Utqask6auc5fIFfBYnAoD6Q9EHADQL24t2aHfJHtlk06DMgTLEBHxAc9MrpaeiHVEqrizWurz1VscBgHpD0QcARLxyX7m+PrBcktQz5XQluROtDQTAEk6bU2ek9ZckrT20ToXeIosTAUD9qHPRLy0tVf/+/fX888/XRx4AAMLu6wPLVeGvUKIrUT2Su1sdB4CF2sS2UYvoFgqYAX2d87VM07Q6EgCEXZ2LfnR0tLZt21Yv1xz+4osvdPHFF6tly5YyDEP/+c9/qi2//vrrZRhGta9Ro0ZVWycvL0/XXHON4uPjlZiYqBtvvFHFxcXV1lmzZo3OOecceTweZWVl6Yknngj7awEANA67indpe9EOGTI0OHOg7Ibd6kgALGQYhs5KP0M2w6a9pfu0s3iX1ZEAIOxCOnR/1KhRmjNnTrizqKSkRL1799a0adNO+Nz79u0Lfv3zn/+stvyaa67RunXrNHfuXH344Yf64osvdMsttwSXFxYWasSIEWrbtq1WrFihJ598UpMnT9Y//vGPsL8eAIC1ynxlWrJ/mSSpe1I3pXhSLE4EoDGId8Xr9KQekqTlB5bL66+0OBEAhJcjlAf99re/1ZVXXqlrr71Wv/jFL9S+fXtFRUUds15yct1mNB49erRGjx59wnXcbrcyMzNrXLZhwwbNnj1bX3/9tc444wxJ0l//+ldddNFF+tOf/qSWLVvqjTfekNfr1csvvyyXy6UePXpo1apV+vOf/1ztAwEAQNNmmqaW7l8WPGS/d0ovqyMBaER6JHfXtqJtKqos1srclRqQcZbVkQAgbEIq+j16HP4EdP369Zo5c+Zx1/P7w3+d2vnz5ys9PV1JSUk677zz9Pvf/14pKYf30CxZskSJiYnBki9JF1xwgWw2m5YtW6bLLrtMS5Ys0dChQ+VyuYLrjBw5Un/84x916NAhJSUlHfOcFRUVqqioCH5fWFgY9tcFAAivzYVbDs+yb9g0pMVg2W0cst+cOWwOnRt3bvA2mp4NGzaEfcwUe7KKoor1fcEmefdVKCYQE/bnSE1NVZs2bcI+LgCcSEh/6R566KF6OUf/ZEaNGqXLL79c7du315YtW/TAAw9o9OjRWrJkiex2u7Kzs5Wenl7tMQ6HQ8nJycrOzpYkZWdnq3379tXWycjICC6rqehPmTJFDz/8cD29KgBAuBV5i7Q8Z4UkqU9KbyW5j/3djubF6XBqeMLw4G00Hbn7cyVDGjduXL2Mf/3DN+i8n56npTlf6cFL7ldlRXgP44+OjtaGDRso+wAaVEhFf/LkyWGOUTs//elPg7d79uypXr16qWPHjpo/f77OP//8enve+++/X3fffXfw+8LCQmVlZdXb8wEAQhcwA1qUvVg+06eMqHR1S+pqdSQAp6CosEgypXum3Kt+Z/YL+/imYcrn8yuzXaamfzlD9oLwHf2zddNWPXjrA8rNzaXoA2hQYTl2raCgQLGxsbLbG/awyA4dOig1NVWbN2/W+eefr8zMTOXk5FRbx+fzKS8vL3hef2Zmpvbv319tnarvj3fuv9vtltvtrodXAAAIt3V563WgPFdOm0ODMwfJZoQ07ywiTCAQUE5lTvA2mp42HbLUrXe3ehm70Fuo7cU7FIg31aF1W0U7ouvleQCgoYS89bN8+XKNGjVK0dHRSklJ0YIFCyRJubm5uvTSSzV//vxwZTyu3bt36+DBg2rRooUkadCgQcrPz9eKFSuC63z22WcKBAIaMGBAcJ0vvvhClZX/Oyxr7ty56tKlS42H7QMAmo6D5XlafXCNJOnM9DMV64y1OBEaiwpfhZ7d/6ye3f+sKnwVJ38AmpV4V7wSXQmSpN0lexQw+TAIQNMWUtFfvHixhgwZok2bNmncuHHVPhlPTU1VQUGB/v73v9d53OLiYq1atUqrVq2SJG3btk2rVq3Szp07VVxcrHvuuUdLly7V9u3bNW/ePF166aXq1KmTRo4cKUnq1q2bRo0apZtvvllfffWVFi1apNtuu00//elP1bJlS0nS1VdfLZfLpRtvvFHr1q3TW2+9palTp1Y7NB8A0PT4Aj4tyl4kU6baxGapQ1z7kz8IAH7QMrql7IZd5f5y5ZQdsDoOAJySkIr+Aw88oG7dumn9+vV6/PHHj1k+fPhwLVu2rM7jLl++XH379lXfvn0lSXfffbf69u2rhx56SHa7XWvWrNEll1yizp0768Ybb1T//v21cOHCaofVv/HGG+ratavOP/98XXTRRRoyZIj+8Y9/BJcnJCTok08+0bZt29S/f3/96le/0kMPPcSl9QCgiVuZu0oF3kJF2T0akHGWJZPGAmi6HDaHWsW0kiTllOeo1FdqcSIACF1I5+h//fXXmjJlitxut4qLi49Z3qpVq+As93UxbNgwmaZ53OVz5sw56RjJycknvOSfJPXq1UsLFy6scz4AQOO0r2SfvsvfKEkalDlQHrvH4kQAmqJEV4IKXQnK9xZoZ/EudU44jXk+ADRJIf3mcjqdJ5zIZs+ePYqN5bxIAED9q/BXaPH+JZKkzgmnBffIAUAoWka3ktNwyBvwal/pPqvjAEBIQir6AwcO1DvvvFPjspKSEk2fPl3nnnvuKQUDAKA2vsr5WqW+MsU549QvLfyX3gLQvDhsdrWObS1JOliRpyJvkcWJAKDuQir6Dz/8sJYvX64xY8bo448/liStXr1aL774ovr3768DBw7ot7/9bViDAgBwtG2F27W9aIcMGTo7c7CctrBcNRZAMxfnjFOKO0WStKtkt3wBn8WJAKBuQtoiGjBggGbNmqVbb71V1113nSTpV7/6lSSpY8eOmjVrlnr16hW+lAAAHKWkslRf5XwtSeqZfLrSolItToTGzGFzaHDs4OBt4GRaRGequLJYFYEK7SnZozaxbZjkE0CTEfJfuvPOO08bN27UypUrtXnzZgUCAXXs2FH9+/fnlyAAoF6ZpqnF+5fIG/AqxZ2inimnWx0JjZzT4dSIxBHB28DJ2AybsmJba3PhFhVUFiqvIk8pnhSrYwFArZzyR9pHXg4PAICG8F3+RmWXZstu2HV2i8HMig2gXkQ7otUiKlP7yrK1t3SfYhwx8ji4qgeAxi/kol9RUaEXXnhBs2bN0vbt2yVJ7dq100UXXaSbbrpJHg+/BAEA4ZdfUaCVuaskSf3T+inBFW9tIDQJgUBAh3yHgreB2kr1pKrIV6ziymLtKNmp0+I78eEigEYvpN9Su3fvVp8+fXTHHXdo9erVSktLU1pamlavXq077rhDffr00e7du8OdFQDQzPlNvxZlL5bf9KtldAt1TjjN6khoIip8FZqaPVVTs6eqwldhdRw0IYZhKCumtRyGQxX+Cu3lknsAmoCQiv7EiRO1Y8cOvf3229qzZ48WLFigBQsWaM+ePXrrrbe0c+dOTZw4MdxZAQDN3NqD65RXkSeXzaVBmQOZEwZAg3DanMr64ZJ7eRV5KvAWWJwIAE4spKI/b948TZo0SVdcccUxy6688krdeeedmjdv3imHAwCgSl55nr7NWytJGpBxpqId0RYnAtCcxDnjlOZJk3T4knsVfo4MAdB4hVT04+LilJ6eftzlmZmZiouLCzkUAABHOnzI/hKZMtUmto3axra1OhKAZigzKkPRjmgFzIB2FO9UwGS+BwCNU0hF/+c//7lmzJih0tLSY5YVFxdr+vTpuvHGG085HAAAkvTtwbXK9+bLbXdrQPqZHLIPwBKGYahNbBvZDbvK/eWcrw+g0arVrPvvvvtute/79u2rjz76SF27dtX48ePVqVMnSdKmTZv06quvKjk5Wb169Qp/WgBAs3Ow/KDW5q2TJA1IP4tLWwGwlMvmVJuYLG0r3q68ijzFOKKV5E6yOhYAVFOron/FFVfIMAyZpilJ1W4/9thjx6y/e/du/exnP9NPfvKTMEYFADQ3/sD/DtlvF9dWbePaWB0JABTnilO6J1055TnaU7JXUY4oeex8CAmg8ahV0f/888/rOwcAAMdYfXCNCrwF8tg9OjP9DKvjoAmz2+w6M+bM4G3gVGVEpavUV6JiX4l2FO/UafGdZDNCOisWAMKuVkX/3HPPre8cAIAmaufOncrNzQ37uKW2Mm2L2i4ZUlpxitavXh/W8Tds2BDW8dC4uRwujUkaE7wNnCrDMJQVm6VNBZtV4a/Q7pI9yoppzRwiABqFWhV9AABqsnPnTnXr1q3GyVlPhdPt1KPv/V4tO7bSovcX6e/3PBfW8Y9UXFxUb2MDiGxOm1NtYttoa9FW5XvzFeOIUYon2epYABB60f/yyy/18ssva+vWrTp06FDwnP0qhmFo9erVpxwQANB45ebmqrS0VI8997g6nNYhbOP6E/wKxJuSXzq3/1AN+zT8R5YtnLdQz06ZpvKK8rCPjcbHNE2V+EuCt4FwiXXGKDMqQ9ll+7W3dK+iHVGKckRZHQtAMxdS0f/zn/+se+65Rx6PR126dFFyMp9cAkBz1uG0DurWu1tYxiqpLNGWoq2SpHYJbRWfFh+WcY+2bdO2ehkXjVN5Zbme3PekJOmSykvldDktToRIkuZJU4mvVEWVRcHz9ZkLAoCVQir6Tz75pM4++2x98MEHSkhICHcmAEAzFTAD2lWyW5KU5EpUvKt+Sj4AhJNhGMqKaa1NhZvlDXi1u2S32sRylRAA1glpatDS0lJdc801lHwAQFhll2bLG/DKYTjUMrql1XEAoNYcNofaxraRIUMFlYU6WHHQ6kgAmrGQiv7w4cP17bffhjsLAKAZK64sVu4PG8atY1px2CuAJifaEa0W0ZmSpH2l2Qq4mA8CgDVCKvp//etfNW/ePP3pT39SXl5euDMBAJoZv+kPHrKf7E7ikH0ATVaKO0UJrgSZMuVP8Ss2MdbqSACaoZCKflZWln7xi1/o17/+tdLS0hQTE6P4+PhqXxzWDwCorX2l2aoMVMppc6pFdAur4wBAyAzDUOuYVnLZXJJDuuWPE2SKPfsAGlZIk/E99NBDeuyxx9SqVSudccYZlHoAQMiKvEXKqzh8dFhWTGvZDQ7ZB9C02Q272sa20ab8zeozrE/wtCQAaCghFf3nn39eY8aM0X/+8x/ZbCEdFAAAgHyB/x2yn+pOUayTQ1xRP+w2u3pH9w7eBupblCNK9nyb/MkB5bgOaH/pfmVEZ1gdC0AzEVJL93q9GjNmDCUfAHBK9pbulc/0yWVzKfOHCayA+uByuHRZ8mW6LPkyuRwuq+OgmTBKDH353kLJkL7MXqQKf4XVkQA0EyE19R/96EdauHBhuLMAAJqRAm+B8r35kqSs2CzZDD48BhBZDBl65ZEZcgVcKvWVaXH2Upkm5+sDqH8hbVX97ne/0/r16/XLX/5SK1as0IEDB5SXl3fMFwAANfEFfNpdskeSlO5JU4wj2uJEiHSmacob8Mob8FK00KAqSivUuryVbIZNu0t26/uCTVZHAtAMhHSOfpcuXSRJq1at0t///vfjruf3+0NLBQCIWKZpanfJHvlNvzx2j9Kj0q2OhGagvLJcj+99XJI0uvIiOV1OixOhOYkKeNQvta+WH1ih5QdWKD0qTUnuJKtjAYhgIc+6bxhGuLMAAJqBfG++CisLZchQVkxrDtkH0Cx0TeyifaX7tKdkrxbu+1IXtRkthy2kTXEAOKmQfrtMnjw5zDEAAM2BN1CpPaV7JUkZUemKckRZnAgAGoZhGBqcMUgf7vhI/9/encdXUd/t/3/N2XKy73tIWGUTsIACYrUKZalVUVrUWywq1V/9glVp1VK1Lr0rtVbFWtx6K9a7WlvvqnUrihSQKqCiKAiGnYRsELKeJeecnDO/PwLRCGgSEibL9eQxj5wzM2fm+pBl5j3LZ2qDdXx4YAPjM8dZHUtEeiidRhERkRPCNE32efYRMSNE26NJd6dbHUlE5IRyO9xMzJ4IwPbaHZR4SixOJCI9VbvO6N99993fOI9hGNx+++1tWu4777zDfffdx4YNGygrK+Oll15ixowZzdNN0+SOO+7gT3/6EzU1NUycOJFHH32UQYMGNc9TVVXFddddx6uvvorNZmPmzJk89NBDxMV98WzmTz/9lHnz5vHBBx+Qnp7Oddddx80339ymrCIi0jYHA1V4Gj1Nl+zH5ekWMBHplbJjshiSNITPaz5nbcU6zov+PlH2KKtjiUgP0+GX7huGgWma7Sr0vV4vo0aN4qqrruKiiy46Yvrvfvc7/vCHP/DnP/+Zfv36cfvttzN16lS2bNmC2+0G4LLLLqOsrIzly5cTCoW48sorueaaa3juuecAqKurY8qUKUyePJnHHnuMTZs2cdVVV5GUlMQ111zTprwiItI6DY0NlPnKgKadXLfdbXEiERHrfCttFKW+UuqCdayveJ9vZ5+hg58i0qHaVehHIpGjjtu7dy9LlizhnXfe4V//+leblzt9+nSmT59+1GmmabJ48WJuu+02LrjgAgCeeeYZMjMzefnll7nkkkvYunUry5Yt44MPPmDs2LEAPPzww3zve9/j97//PTk5OTz77LMEg0GeeuopXC4Xw4cPZ+PGjTzwwAMq9EVEOkHEjFDkLcbEJN4ZR2pUqtWRREQs5bA5OCPrdP5V9CZ7PUX0qd9Lv4S+VscSkR6kw+7Rt9ls9OvXj9///vcMGjSI6667rqMWDcDu3bspLy9n8uTJzeMSExMZN24ca9euBWDt2rUkJSU1F/kAkydPxmazsX79+uZ5zjzzTFwuV/M8U6dOpbCwkOrq6qOuOxAIUFdX12IQEZHWKfdX0BBuwG7YyYvVJftiDZthY1j0MIZFD9OTHqRLSHWnMiL1ZADe3/8BvpDP4kQi0pN0ypbuzDPP5I033ujQZZaXlwOQmZnZYnxmZmbztPLycjIyWj6P2eFwkJKS0mKeoy3jy+v4qkWLFpGYmNg89OnT5/gbJCLSC9SH6qlsqASgT2weTpueXS7WiHJGMSt1FrNSZxHl1P3Q0jWMSDmZ1KgUgpEg71WswzRNqyOJSA/RKYX+hx9+iM3Wc46WL1y4kNra2uahuLjY6kgiIl1eY6SRYs8+AFKjUkhwJVicSESka7EZNiZmnY7dsFPmK2Nb7XarI4lID9Gue/SfeeaZo46vqanhnXfe4cUXX+THP/7xcQX7qqysLAAqKirIzs5uHl9RUcEpp5zSPM/+/ftbfK6xsZGqqqrmz2dlZVFRUdFinsPvD8/zVVFRUURF6ei/iEhrmabJPm8JjWYjUbYosmOyv/lDIiK9UGJUIt9KO4UPD2xgw4GPyI7J0oFRETlu7Sr0r7jiimNOS0tL4xe/+AW/+tWv2pvpqPr160dWVhYrVqxoLuzr6upYv3491157LQATJkygpqaGDRs2MGbMGAD+/e9/E4lEGDduXPM8t956K6FQCKez6RLS5cuXM3jwYJKTkzs0s4hIb1UVqKYuVIeBQX5cH90TLZbzB/3cue9OACYFJxPvjLc2kMiXDEkaTLFnHxX+Ct4rX8uUPt/V300ROS7tKvR37959xDjDMEhOTiY+vv0bTo/Hw44dO1qsZ+PGjaSkpJCfn88NN9zAf//3fzNo0KDmx+vl5OQwY8YMAIYOHcq0adO4+uqreeyxxwiFQsyfP59LLrmEnJwcAP7rv/6Lu+66i7lz53LLLbewefNmHnroIR588MF25xYRkS80hAOU+koByIrOJNoRbXEiEZGuzTAMJmZN4NW9r3OgoZLPqrcwIuVkq2OJSDfWrkK/oKCgo3MATff2n3322c3vFyxYAMCcOXN4+umnufnmm/F6vVxzzTXU1NRwxhlnsGzZMtzuL57H/OyzzzJ//nwmTZqEzWZj5syZ/OEPf2ienpiYyFtvvcW8efMYM2YMaWlp/OpXv9Kj9UREOkDEjFDsaXqUXpwjjjR3mtWRRES6hVhnLKdmjOW98rV8WrmJ3JgcUtwpVscSkW6qXYV+Z/nOd77ztb2NGobB3Xffzd13333MeVJSUnjuuee+dj0jR45kzZo17c4pIiJHV+Hfjz/sx27Y6ROnR+mJiLRF//h+FHv2Uewp5t3y9/he/nTsNrvVsUSkG2p1oT9y5Mg2LdgwDD755JM2BxIRke7JE/JwoOEAAHmxuXqUnohIGxmGwfiM0zjgP0BNsJZPDn7K6PRvWR1LRLqhVhf6KSkprTozU15eTmFhoc7iiIj0IqbNpMjT9OjRlKhkEl2JFicSEeme3A434zNPY1XpO3xWvYW8uFwyojOsjiUi3UyrC/1Vq1Z97fTy8nLuvfdeHn/8cex2O5dffvnxZhMRkW7AMAzCKRFM0yTKFkVOTI7VkUREurU+cX3on9CfXXW7eLd8Ld8v+J6ukhKRNjnu53ZUVFRw4403MmDAAJYsWcIll1zC559/zlNPPdUR+UREpIubduV0zGjz0KP08vVIKOmSbIaNQe5BDHIP0s+odAunpo8hxhGDJ+ThowMfWx1HRLqZdnfGd/gM/hNPPEEoFGL27Nncdttt9O/fvyPziYhIF+az+fnhglkA5MTkEO1wf8MnRKwR5YzisrTLml+LdHUuu4vTsybw9r4VbKvdTp+4PHJidcWUiLROmw9pl5eXc8MNN7Q4g19YWMhTTz2lIl9EpBcJhAPsc5fgcDowfAYpUclWRxIR6VGyY7IYnDQYgPfK1xEIByxOJCLdRasL/bKyMq6//nr69+/PI488wqWXXkphYSFPPvkk/fr168yMIiLSxZimybqK9YRsISqKKrBX2dQJq4hIJxiddgoJznj8YT/v7//Q6jgi0k20+tL9AQMGEAgEOOWUU/jlL39Jv379qK6uprq6+pifGT16dIeEFBGRrmVb7XaKPMUYJjxy4x+5Z/EiqyOJfC1/0M9vSn4DwKTgZOKd8RYnEmkdh83B6Vmn82bxW+yp30N+XB8K4vOtjiUiXVyrC/2GhgYAPv74Y2bNmvW185qm2dQLczh8fOlERKTLqWqo4sMDGwDIDGaye/NuixOJtE7IDFkdQaRd0qPTGJ4yjM1Vn7G+4n0yotOJdkRbHUtEurBWF/pLly7tzBwiItINhCIh3in7DxEzQl5sHgmeOKsjiYj0CiNTR1DiLaU6UM3aivWcnXOWbpkSkWNqdaE/Z86czswhIiJdnGmarK94n/pQPTGOGE7PGs9nFZ9ZHUtEpFewG3YmZk3gjaJllHhL2Fm3i4GJA6yOJSJdlB4kKyIirbKzbhe76/dgYPDt7IlE2fWIMhGREyk5KplTUkcC8OGBD/GEPBYnEpGuqtVn9EVEpPeqDtTw/v4PABiVNpKM6AyLE4mIdB9bt27tsGWZmMRER+PDz5s73qKvvwCDzrmEPy0tjfx8dfwn0h2p0BcRka8VDAdZXfoOYTNMdkw2JycPtzqSiEi3UFlRCQbMnj27Q5eb0SeDX//zNxALv1l6Dy/98cUOXf5hMTExbN26VcW+SDekQl9ERI7JNE3eLX+P+lA9sY4Yzsg+XZ0/SbdkGAYFroLm1yInQn1dPZhw06KbGX1qxz52OtIQIRwb4cL5F/GDi3+ALdCxd+Tu2r6LW6/9JZWVlSr0RbohFfoiInJMm6s+Y5+3BJth46ycM3Hb3VZHEmkXt9PNlRlXNr8WOZHy+/dh6KihHb7cYs8+qoPVGJk2BiUOwmHTrr2INFFnfCIiclSl3jI2HvwEgNMyTiXVnWpxIhER+bLc2ByibFE0mo0Ue/dhmqbVkUSki1ChLyIiR/CEPKwp+w8AAxMHMihxoMWJRETkq2yGjfy4PhgY1IfqqWyotDqSiHQRur5HRERaCEVCrCxZRTASJDUqhdPSx1odSeS4+YN+flf6OwAmBScT74y3OJFIx4h2RJMTk02Jr5QyfzkxjhhinbFWxxIRi+mMvoiINIuYEdaUvUtNsJZou5uzcs7EbrNbHUukQ/giPnwRn9UxRDpcSlQKia5EAPZ6ighGQhYnEhGrqdAXEZFmH1dupMRbgt2w852cs3RWSESkGzAMgz6xebjtbhrNRvbW7yViRqyOJSIWUqEvIiIA7KjdyZbqrQCcnjWetOg0ixOJiEhr2QwbfeMKsBt2/GE/Jd5Sdc4n0oup0BcRESp8FayveB+AkSkj6Bvf19pAIiLSZi67i/y4pmfeVwerORiosjiRiFhFhb6ISC9XHahmZelqIkQoiMtnZOoIqyOJiEg7xTvjyI7OAqDUV0p9yGNxIhGxggp9EZFezBPysGLfSkKREOnudE7PmoBhGFbHEhGR45DmTiPJlQTA3vq9+Bv91gYSkRNOhb6ISC/lb2zg7X3/xh/2k+RK5Ozcs3DY9NRV6ZkMwyDHmUOOM0cHs6THMwyDvNhcYh2xRIiwu34PwXDQ6lgicgJpj05EpBcKRUL8u2Ql9aF6Yh2xTMo9hyh7lNWxRDqN2+nmmsxrml+L9HSHO+fbWb+ThnCA3fV7GJDQXwd0RXoJndEXEellGiONrCxZTVWgiih7FJPzziHGGWN1LBER6WB2m52+8f1w2pwEIgH2ePTYPZHeQoW+iEgvEoo08u+SVVT4K3AYDiblnk2CK8HqWCIi0klcNif94vpiM2z4Gn3s9RSp2BfpBVToi4j0EqFIiJUlK6nwV+C0OZiUdzap7lSrY4mcEA1BPw+WPciDZQ/SEFTHZNK7uB1u+sb1xcCgPlSvYl+kF1ChLyLSCxy+J7/Cvx+nzcmk3HPIiM6wOpbICWMCteFaasO1mFaHEbFAnDOWvvFfFPtFnmIV+yI9mHrjEBHpIoqKiqisrOzw5YYJsze6GL/dj820kefJpXhrMcUUH/eyt27d2gEJRUTkRIh3xtE3voA99XupC9VR5CmmIC5fT6IQ6YFU6IuIdAFFRUUMHToUn8/XoctNzU7lZ3+6ibxBeXhrvfzuqt+ye/PuDl0HgMdT3+HLFBGRjhfvjKdvXAF7PE3F/l5PEflxfbAZutBXpCfpVoX+nXfeyV133dVi3ODBg/n8888BaGho4Gc/+xnPP/88gUCAqVOn8sgjj5CZmdk8f1FREddeey0rV64kLi6OOXPmsGjRIhyObvVfISI9TGVlJT6fj988eg/9B/XvkGWaTpPG9DDYgUZI9Cdwz+JFHbLsw9asWMMji5bQEGjo0OWKiEjniXfFUxCXz15PEXWhOnbX76FvfAF2w251NBHpIN2uuh0+fDhvv/128/svF+g33ngjr7/+Oi+88AKJiYnMnz+fiy66iHfffReAcDjMueeeS1ZWFu+99x5lZWX86Ec/wul0cs8995zwtoiIfFX/Qf0ZOmrocS+nPlTP3voiAKLsUfRL7Isrw3Xcy/2q3ds7/uoAERHpfAmuBPrF92VP/V68jV521e2iX3w/HLZuVx6IyFF0u2t0HA4HWVlZzUNaWhoAtbW1PPnkkzzwwAOcc845jBkzhqVLl/Lee++xbt06AN566y22bNnCX/7yF0455RSmT5/Or3/9a5YsWUIwGLSyWSIiHcI0TQ42HGR3/R4iRIh1xDIwfgAue8cX+SIi0r3FOePon9Afu2HHH25gR91OgmHtE4v0BN2u0N++fTs5OTn079+fyy67jKKipjNWGzZsIBQKMXny5OZ5hwwZQn5+PmvXrgVg7dq1jBgxosWl/FOnTqWuro7PPvvsmOsMBALU1dW1GEREupqIGWGft4QSXykASa5E+sX3xW7TpZgiBpDuSCfdkY66HRP5QowjmoEJA3DanAQjQXbU7cTX2LH9xYjIidetrs0ZN24cTz/9NIMHD6asrIy77rqLb3/722zevJny8nJcLhdJSUktPpOZmUl5eTkA5eXlLYr8w9MPTzuWRYsWHdE3gIhIVxIMB9nrKcIfbno+eFZ0FunuNPWkLHKI2xXNvKx5za9F5AtR9igGJgxgd/1uGsIBdtbtwhat7YdId9atCv3p06c3vx45ciTjxo2joKCAv//970RHd95Ge+HChSxYsKD5fV1dHX369Om09YmItEV9sJ4ibzFhM4zdsJMfl0+8M87qWCIi0o04bU4GJAygyFNEfchDOM3kvJ+cj4lpdTQRaYdud+n+lyUlJXHSSSexY8cOsrKyCAaD1NTUtJinoqKCrKwsALKysqioqDhi+uFpxxIVFUVCQkKLQUTEahEzQom3lN2ePYTNMNH2aAYlDFSRLyIi7WI37PSN60tqVCoAP7xxFiVRpTRGGi1OJiJt1a0LfY/Hw86dO8nOzmbMmDE4nU5WrFjRPL2wsJCioiImTJgAwIQJE9i0aRP79+9vnmf58uUkJCQwbNiwE55fRKS9/I1+ttft4GDgIACpUakMSOivTvdEjqEh6GdJ+RKWlC+hIei3Oo5Il2UYBrmxOdiqbIQbw9Q663iz+C3qg/VWRxORNuhWhf7Pf/5zVq9ezZ49e3jvvfe48MILsdvtXHrppSQmJjJ37lwWLFjAypUr2bBhA1deeSUTJkxg/PjxAEyZMoVhw4Zx+eWX88knn/Dmm29y2223MW/ePKKioixunYjINzNNkwP+A+yo20kgHMBhOOgb17dpp8zoVn/SRU4oEzjQeIADjQd0IbJIK9i9Nu6b+zvspp2qQDVvFC1jn6fE6lgi0krd6h79ffv2cemll3Lw4EHS09M544wzWLduHenp6QA8+OCD2Gw2Zs6cSSAQYOrUqTzyyCPNn7fb7bz22mtce+21TJgwgdjYWObMmcPdd99tVZNERFrN3+hnn7ekucO9eGc8fWLz9MxjERHpFFvWfcYAXz+qUqupbDjIytJVjEg5mZGpI3RwWaSL61Z7h88///zXTne73SxZsoQlS5Ycc56CggLeeOONjo4mItJpImaECv9+DjQcAMBm2MiJySbZlaxe9UVEpFM5TSdT+nyXDfs/orB2G5uqNrPfv5+JWacT64y1Op6IHIMOxYmIdGF1wTq21W5vLvITnQkMTjyJlKgUFfkiInJC2A07p2WeysSs03EYDir8+3l17+vsqd9jdTQROYZudUZfRKS3CIQDlPrKqA81dX7kMBzkxuaQ6Eq0OJmIiPRW/RP6keZO493yd6lsOMiasncp8ZZyavqpuOxOq+OJyJeo0BcR6UJMw6TMV05lQyUmJgYGae5UMqIzsBt2q+OJiEgvl+CKZ2qfKXx6cBObqz5jV91uyn0VjMs4jby4XKvjicghKvRFRLqACBGm/Ggqjdnh5sv0451xZMfk4LbrqSAix8sAEu2Jza9FpP1sho1T0kaRE5vNu+Vr8YQ8rCxdRd/4AsamjyXa4bY6okivp0JfRMRCpmmyp34PO2J2MfvWywGIskWRHZNFvDNe9+GLdBC3K5obs29sfi0ixy8jOoPvF5zLpwc/ZWv15+yp30upt4wx6aMZkNBf2zARC6nQFxGxgGmaFHmK+fTgJmqCNWCD6v3VpDlSOWnAIO0ciYhIt+C0ORiTPpq+8QWsrVhPdaCatRXr2FazjbEZY8iIzrA6okivpF73RUROINM0Kaov5vW9b/BO2RpqgjU4bU4yAuncNOXn2Lw2FfkiItLtpLpT+V7+NEanfQunzcHBQBVvFi9nTdl/8Ia8VscT6XV0Rl9E5ASImBH21O/ls6otTWfwaToLMiRpCEOTh/DZJ58R9AesDSnSgzWEGnii4gkAJoe+S5wzzuJEIj2PzbAxPGUY/RP6sfHgp+yo3cGe+r0UeYo5KfEkTk4ZRrRDt86InAgq9EVEOlEoEmJH7U62VG/F1+gDmh6VNyR5MMOShxKljvZETgjTNCkNlTa/FpHOE+2IZkLmOAYnDuLDAx9R4a/g85rP2V67ncFJJzE8eRhuddgn0qlU6IuIdAJ/o5/PawrZVrOdYCQIgNvuZkjSYE5KGqQCX0REerwUdwrfzZtEma+cTw5+QmXDQbZUb2VbzXYGJQ1kaNIQYp2xVscU6ZFU6IuIdKC6YB1bqreys24XETMCQLwznmHJQxmQ0B+7zW5xQhERkdbbunVrhywng3Ri7DHsdx2gwd7A1urP2Vr1OYmNiaSFUnBHOvYMf1paGvn5+R26TJHuRIW+iMhxMk2TMl8Zn9dso8Rb0jw+1Z3KycnDyIvLw2ao71MREek+KisqwYDZs2d3+LJHfHsk5/74XIaNH06ts5ZaZy2b/rOJFc8t5+OVH2NGjv/2mpiYGLZu3apiX3otFfoiIu0UDAfZWbeLbTXbqAvVN4/Pjc1hePIwMqIz1IO+iIh0S/V19WDCTYtuZvSpoztlHZEKk0h8BDPaZMQZIxhxxghoBJvHhs1rYETatw3dtX0Xt177SyorK1XoS6+lQl9EpI1qAjUU1mxjV91uGs1GAJw2JwMS+jM46SQSXAkWJxQREekY+f37MHTU0E5dRzAc5GCgiqpAFWFHmEhSBDPJINGVQGpUKjGOGB04F2kjFfoiIq0QNsPs85RQWLONCn9F8/hEVyKDk06if0I/nDanhQlF5JvE2GKsjiAiR+Gyu8iOySIzOoPaYC0HGw7iC/upCdZSE6zFbXeTGpVKUlQidkN93Yi0hgp9EZGvUROoZUfdDnbV7SYQbnrOvYFBn7g8BicNJlOX54t0C9GuaG7Oubn5tYh0PTbDRnJUMslRyfga/RxsOEhNsIaGcAMlvhJKfaUkuhJJiUom1hGr7a/I11ChLyI9SlFREZWVlce1jDAR6hx1VDtr8Nv9zeMdEQdJjYmkhJJxepyUlpdQSsnXLKn1OqpXYxERkZ4gxhFNTFwe2ZEsqgPVVAWqCUQC1ARrqAnW4LI5mw4KuJJx2V1WxxXpclToi0iPUVRUxNChQ/H5fO36/IBRAzjrB99h3LnjiXY3nfELN4bZuOpjVr+wik/XfEokHOnIyEfweOq/eSYREZFewmFzkB6dTpo7DV+jj+pgNTWBWoKREBX+/VT49xPniCM5KplEV4KeciNyiAp9EekxKisr8fl8/ObRe+g/qH+rPmM6TCIxESIxJnz5FvsQ2Lw2HF474wePZ/xt4zsn9CFrVqzhkUVLaAg0dOp6RHqrhlADS/cvBWBy6LvEOeMsTiQibWEYBrHOWGKdseTE5FAbrKUqUI230Yun0YOn0UOJ10aCK4GIO4LdqXv5pXdToS8iPU7/Qf2/tofgYDh46NK/WhrCXxTWBgZJrkSSo1KIPcE9/O7evvuErUukNzJNk73Bvc2vRaT7+vK9/MFwkKpANdXBakKREDXBGkiHh9f8kdKoMnJ85WREZ+hMv/Q6KvRFpFcIRULUHuq919f4xaX9BgZxzjiSXEkkuOLVm6+IiEg34rK7yIrJJDM6A1+jj5pgLQd9B4lLjqeaGpbvW0G0PZqC+Hz6xheQ5k5TJ37SK6jQF5EeKxAOUBusoy5U16K4B4h1xJLkSiLRlYDDpj+FIiIi3dmXL+2v3VHDr2/7Nb/7n9/hjfLhD/v5vKaQz2sKibZH0ycuj/y4PmTGZOpMv/RY2rsVkR7DxKTfiP6EE8MU1m5rfhzeYTH2aBKjkkhyJeqZ9yIiIj2UgcHWdVvICWQzatgoyrzl7Knfwz7vPvxhP9tqt7Otdjsum4u82Fz6xPUhJzZbB/6lR9FPs4h0a+FImHJ/BSWeEnbG7OKu/7ubCGZzkR/niCPBlUCiK0HFvYiISC9jN+zkxeWSF5d7aJ+hnCLPPoo9xQTCAXbV72ZX/W7shp2cmGz6xOWRE5tLtMNtdXSR46JCX0S6HW/IR4m3hBJvCWW+csJmuGmCDfxePzFGDHnpeSQ447HbdM+9iIiIgN1mJzc2l9zYXMZlnMoBfyXFnmKKPMV4G70Ue/dR7N0HQJo7jbzYXHLjckl2Jem+ful2VOiLSJcXMSNUNlRS4i2lxFNCdbCmxfQYRzS5sbkEyhv47vjv8swb/0tyXpIlWUWk63IauqpHRJrYDBuZMRlkxmQwJn001YFqij372OctoSpQRWVDJZUNlWw8+AkxjhjyYnPJi80lKyZLJxGkW1ChLyJdUiAcoNRbyj5vKaXeUoKRYPM0A4M0d2rTUfkvHWn/qOQjQsGQhalFpKuKdkVza+6tza9FpOfbunVrmz+TTSZpRgr1dg8ehweP3Yuv0dd8X79hGsSEY4gLxxIbjsUdicKgY8/2p6WlkZ+f36HLlN5Hhb6IdAnhSJgDDZWU+8op95VT2XAQky+ede2yuciJzSY3Npec2Gzcdt07JyIiIkeqrKgEA2bPnn3cy3JGORk2fjinnH0Kp3znW6Rmp+J1ePE6vADUHazls/c+47O1m9n87maqyquOe50xMTFs3bpVxb4cFxX6ImKJiBnhYMNByn0VlPvKOdBQ+cW99ockuRKb76VLj07TI3BERETkG9XX1YMJNy26mdGnju6w5ZqNJpRBxG1iuk3MKJOE1EQmnHc6E847vWmmEBgBA1vAwAga0Eibzvjv2r6LW6/9JZWVlSr05bio0BeRIxQVFVFZWdmhy2wkTIPdj9/WgM/uw2f3EzEiLeZxRBzEhmOIPXQ5nMvjhCqTEvZRwr5vXEd7LtETkd4hEArwbOWzAHw3NAWHU7tAIj1dfv8+DB01tNOWHzEj+Br9eEL1eEIefGE/OMF0moTjmq5KtBt2oh3RxDpiiDk06MSFnAjayolIC0VFRQwdOhSfz9euz9sddjLzM8kdlEveoD7kDsqlYGhfMgsyj5i3vrqereu3sGXdFrau30LZrrLjjQ+Ax1PfIcsRkZ4jYkbY3rC9+bWIyPGyGTbinLHEOWOBptsQPY1efI1evI0+/I1+wmaY+lA99aEv9k3cdjfR9miiHW7cdjduezQOdfAnHUyFvoi0UFlZic/n4zeP3kP/Qf1bTDMxwQbYwbSbh74eeu0A09E07phXqIXACDZdymYLGCSHkpg4fCITh0+Euceffc2KNTyyaAkNgYbjX5iIiIhIG9htdhJdCSS6EoCmg4oN4Qa8jT58jT58IS8hs5GGcAMN4Qaqv+hnGKfNSbTdTTghzNgppxIwAoQjYfXwL+3Wqwv9JUuWcN9991FeXs6oUaN4+OGHOe2006yOJdJpTNMkGAkSjIQIhYNNr8OhQ+OCBMNBylzl/H+/+wn5EwpwxruImGHCZoRwJEyE1p0Fs2Ejyh516Ch1FG5H05Frh61z/+Ts3r67U5cvIiIi0lo2w9Z8uf5hwXAQf9iPv7Gp2PeH/YQioeaBRPjpw9ezg13s3LGbWGcsCc4EElzxJLgSmgZnPDGOGAyjY3v7l56l1xb6f/vb31iwYAGPPfYY48aNY/HixUydOpXCwkIyMjKsjidyVBEzQigS+lKh3lSkh1oU6yFCh4r2w0X94dehSCsePeeCiRecgYmJr/Hol+/bDTtOmxOnzYHDcOKyO3HZXE2D3YXDcGjjIyIiIvIVLnvTvlKiK7F5XGMkTEPYT0O4gbL95ezas5MBwwcSMSJ4Qh48IQ+lX9kl++IgQnTzwYQvhqZx2ifr3Xptof/AAw9w9dVXc+WVVwLw2GOP8frrr/PUU0/xi1/8wuJ00hMUFRVxoPIAJiYRIkSMQ6+MCBFMIkbkiPdhI0yYCBEjTNg49JWm8REjckTnde1lmAZ2047dtGGj6avdtGMz7VRXVvPX/32O2VfPJjc/D7thPzTYml9rgyEiIiLSMRw2O3G2OOKccRyoPsAdM3/F//7lL5w0bCBBW5CAESRoaxoCtiBBI0iELw4CfC0T7NiwfWW/z2basGHDMA2+/A+TFu+bph9+csDhcV95T9O+JRgkJyWTm52D7dC+o+1L+5A2w6Z9yBOoVxb6wWCQDRs2sHDhwuZxNpuNyZMns3btWguTdayaQC2lvtKOWZjZmllaMVMHrtA8tE7TbJrXNJsKatM0af5nHuNrK6ZFvjINjhx3rGWGGkPUe+txRbuw2Tu+Z9WAP4Cv3oevzoe/3oe3vumrr96Ht9bbPM1X520xznto/sZQ4zeu46LzLyRpYOI3ziciIiIiHaOyohIMuHz27GPOY3fYSc5MJjkzmZTMFJIzU0jJSmkal5VCckbTNIfTAQaHThpFaMV1ncdtd3APH+39+JjTbYbtKAcAWh4U+OrBAbthB+PLBxyaGBjN45vHGEeZB444wNA8/vC8hz43KHEQ0Q738f43dAm9stCvrKwkHA6TmdmyF/DMzEw+//zzI+YPBAIEAoHm97W1tQDU1dV1btDjtKduD+/vf9/qGL1awP9Fp3CRsIkZNomEI198jZiY4QiRsEmkMUIkFG6aFooQbowQCUWINIYPTWsaZzZGjjgO4sBOPPHEO+MhjaahnT7buJnX/v4amz7ejM3oXh3A7Nq+C4DtW3YQ4461OE3bdNfs3TU3KLtVrMruD/rhUMdXn3zwCdGu6DYvQ//v1lB2ayi7NT7Z8AmY8IMrfsCAkwa27cN+CO0Osn93BfupwLCDYbdhc9qxOWzYHTZshwenDcNuayqMbQAG2AwMm4FhGE3jjMPvj/K6qaJumvfQuEgkjN/vJzklGcNhA0xMoyNPBHa+xD6JJEclWR3jmA7Xn4dPdH4dw2zNXD1MaWkpubm5vPfee0yYMKF5/M0338zq1atZv359i/nvvPNO7rrrrhMdU0RERERERKSF4uJi8vLyvnaeXnlGPy0tDbvdTkVFRYvxFRUVZGVlHTH/woULWbBgQfP7SCRCVVUVqampus+kDerq6ujTpw/FxcUkJCRYHafdekI71IauQW3oGtSGrqMntENt6BrUhq5Bbeg6ekI71IamM/n19fXk5OR847y9stB3uVyMGTOGFStWMGPGDKCpeF+xYgXz588/Yv6oqCiioqJajEtKSjoBSXumhISEbvvL+WU9oR1qQ9egNnQNakPX0RPaoTZ0DWpD16A2dB09oR29vQ2Jia3rQ6tXFvoACxYsYM6cOYwdO5bTTjuNxYsX4/V6m3vhFxEREREREemOem2hf/HFF3PgwAF+9atfUV5ezimnnMKyZcuO6KBPREREREREpDvptYU+wPz58496qb50jqioKO64444jboPobnpCO9SGrkFt6BrUhq6jJ7RDbega1IauQW3oOnpCO9SGtumVve6LiIiIiIiI9FQ2qwOIiIiIiIiISMdRoS8iIiIiIiLSg6jQFxEREREREelBVOiLiIiIiIiI9CAq9KXTvPjii0yZMoXU1FQMw2Djxo1HzNPQ0MC8efNITU0lLi6OmTNnUlFRceLDtlJFRQVXXHEFOTk5xMTEMG3aNLZv3251rDbxeDzMnz+fvLw8oqOjGTZsGI899pjVsdrMMIyjDvfdd5/V0dpk69atnH/++SQmJhIbG8upp55KUVGR1bFa7YorrjjiezBt2jSrY7XbT37yEwzDYPHixVZHaZM777yTIUOGEBsbS3JyMpMnT2b9+vVWx2q1UCjELbfcwogRI4iNjSUnJ4cf/ehHlJaWWh2tTVqz3evqlixZQt++fXG73YwbN47333/f6kht8s4773DeeeeRk5ODYRi8/PLLVkdqs0WLFnHqqacSHx9PRkYGM2bMoLCw0OpYbfLoo48ycuRIEhISSEhIYMKECfzrX/+yOtZx+e1vf4thGNxwww1WR2m1O++884ht9JAhQ6yO1WYlJSXMnj2b1NRUoqOjGTFiBB9++KHVsdqkb9++R91vnTdvXqetU4W+dBqv18sZZ5zBvffee8x5brzxRl599VVeeOEFVq9eTWlpKRdddNEJTNl6pmkyY8YMdu3axT//+U8+/vhjCgoKmDx5Ml6v1+p4rbZgwQKWLVvGX/7yF7Zu3coNN9zA/PnzeeWVV6yO1iZlZWUthqeeegrDMJg5c6bV0Vpt586dnHHGGQwZMoRVq1bx6aefcvvtt+N2u62O1ibTpk1r8b3461//anWkdnnppZdYt24dOTk5Vkdps5NOOok//vGPbNq0if/85z/07duXKVOmcODAAaujtYrP5+Ojjz7i9ttv56OPPuLFF1+ksLCQ888/3+pobdKa7V5X9re//Y0FCxZwxx138NFHHzFq1CimTp3K/v37rY7Wal6vl1GjRrFkyRKro7Tb6tWrmTdvHuvWrWP58uWEQiGmTJnSrfY18vLy+O1vf8uGDRv48MMPOeecc7jgggv47LPPrI7WLh988AGPP/44I0eOtDpKmw0fPrzFNvo///mP1ZHapLq6mokTJ+J0OvnXv/7Fli1buP/++0lOTrY6Wpt88MEHLb4Py5cvB+CHP/xh563UFOlku3fvNgHz448/bjG+pqbGdDqd5gsvvNA8buvWrSZgrl279gSn/GaFhYUmYG7evLl5XDgcNtPT080//elPFiZrm+HDh5t33313i3GjR482b731VosSdYwLLrjAPOecc6yO0SYXX3yxOXv2bKtjHJc5c+aYF1xwgdUxjtu+ffvM3Nxcc/PmzWZBQYH54IMPWh3puNTW1pqA+fbbb1sdpd3ef/99EzD37t1rdZQ2O9Z2r6s77bTTzHnz5jW/D4fDZk5Ojrlo0SILU7UfYL700ktWxzhu+/fvNwFz9erVVkc5LsnJyeb//M//WB2jzerr681BgwaZy5cvN8866yzz+uuvtzpSq91xxx3mqFGjrI5xXG655RbzjDPOsDpGh7v++uvNAQMGmJFIpNPWoTP6YpkNGzYQCoWYPHly87ghQ4aQn5/P2rVrLUx2dIFAAKDF2VabzUZUVFS3Ojp6+umn88orr1BSUoJpmqxcuZJt27YxZcoUq6O1W0VFBa+//jpz5861OkqrRSIRXn/9dU466SSmTp1KRkYG48aN65aXma5atYqMjAwGDx7Mtddey8GDB62O1CaRSITLL7+cm266ieHDh1sd57gFg0GeeOIJEhMTGTVqlNVx2q22thbDMEhKSrI6Sq8QDAbZsGFDi22yzWZj8uTJXXKb3JvU1tYCkJKSYnGS9gmHwzz//PN4vV4mTJhgdZw2mzdvHueee26L343uZPv27eTk5NC/f38uu+yybnV7IMArr7zC2LFj+eEPf0hGRgbf+ta3+NOf/mR1rOMSDAb5y1/+wlVXXYVhGJ22HhX6Ypny8nJcLtcRO3GZmZmUl5dbE+prHD4IsXDhQqqrqwkGg9x7773s27ePsrIyq+O12sMPP8ywYcPIy8vD5XIxbdo0lixZwplnnml1tHb785//THx8fJe97eNo9u/fj8fj4be//S3Tpk3jrbfe4sILL+Siiy5i9erVVsdrtWnTpvHMM8+wYsUK7r33XlavXs306dMJh8NWR2u1e++9F4fDwU9/+lOroxyX1157jbi4ONxuNw8++CDLly8nLS3N6ljt0tDQwC233MKll15KQkKC1XF6hcrKSsLhMJmZmS3Gd9Vtcm8RiUS44YYbmDhxIieffLLVcdpk06ZNxMXFERUVxU9+8hNeeuklhg0bZnWsNnn++ef56KOPWLRokdVR2mXcuHE8/fTTLFu2jEcffZTdu3fz7W9/m/r6equjtdquXbt49NFHGTRoEG+++SbXXnstP/3pT/nzn/9sdbR2e/nll6mpqeGKK67o1PWo0JcO8eyzzxIXF9c8rFmzxupIx+2rbVq3bh0vvvgi27ZtIyUlhZiYGFauXMn06dOx2brmr9LRvi8PP/ww69at45VXXmHDhg3cf//9zJs3j7ffftvquMf0TT9fTz31FJdddlmXvrf9q2043LHSBRdcwI033sgpp5zCL37xC77//e932c4Rj/Z9uOSSSzj//PMZMWIEM2bM4LXXXuODDz5g1apVVsc9qq+2YfXq1Tz00EM8/fTTnXpUvSMd6/fh7LPPZuPGjbz33ntMmzaNWbNmddl7q7/udzoUCjFr1ixM0+TRRx+1MOXX64nbPel65s2bx+bNm3n++eetjtJmgwcPZuPGjaxfv55rr72WOXPmsGXLFqtjtVpxcTHXX389zz77bJfev/g606dP54c//CEjR45k6tSpvPHGG9TU1PD3v//d6mitFolEGD16NPfccw/f+ta3uOaaa7j66qu77L5Sazz55JNMnz690/sEcnTq0qXXOP/88xk3blzz+9zc3G/8TFZWFsFgkJqamhZn9SsqKsjKyuqMmG1ytDZFR0ezceNGamtrCQaDpKenM27cOMaOHWth0mM7WhsmTZrESy+9xLnnngvAyJEj2bhxI7///e+77GVpX/fztWbNGgoLC/nb3/5mRbRW+2ob0tPTcTgcR5zdGDp0aJe9FaQ1v+f9+/cnLS2NHTt2MGnSpBMZr1W+2oYXXniB/fv3k5+f3zwuHA7zs5/9jMWLF7Nnzx4LUn69Y30fYmNjGThwIAMHDmT8+PEMGjSIJ598koULF1oV9ZiO1YbDRf7evXv597//3aXP5rdnu9eVpaWlYbfbj3jyTVfZJvdG8+fP57XXXuOdd94hLy/P6jht5nK5GDhwIABjxozhgw8+4KGHHuLxxx+3OFnrbNiwgf379zN69OjmceFwmHfeeYc//vGPBAIB7Ha7hQnbLikpiZNOOokdO3ZYHaXVsrOzj7qv9I9//MOiRMdn7969vP3227z44oudvi4V+tIh4uPjiY+Pb9NnxowZg9PpZMWKFc09pRcWFlJUVNQl7uH6ujYlJiYCTfc9ffjhh/z6178+kdFa7attqKurIxQKHXEFgt1uJxKJnOh4rfZ134snn3ySMWPGdPl7kY/WhlNPPfWIRyZt27aNgoKCExmt1Vrze75v3z4OHjxIdnb2CUrVNl9twzXXXMN5553XYp6pU6dy+eWXc+WVV57oeK3S2r+3kUikuW+RruZobThc5G/fvp2VK1eSmppqUbrWac92rytzuVyMGTOGFStWMGPGDKDpZ2jFihXMnz/f2nC9jGmaXHfddbz00kusWrWKfv36WR2pQ3Tlv0lHM2nSJDZt2tRi3JVXXsmQIUO45ZZbul2RD02PWN65cyeXX3651VFabeLEid1qX+mbLF26lIyMjOYTbp1Jhb50mqqqKoqKipqfg3z4lzQrK4usrCwSExOZO3cuCxYsICUlhYSEBK677jomTJjA+PHjrYx+TC+88ALp6enk5+ezadMmrr/+embMmNFtOrJLSEjgrLPO4qabbiI6OpqCggJWr17NM888wwMPPGB1vDarq6vjhRde4P7777c6SrvcdNNNXHzxxZx55pmcffbZLFu2jFdffbXLXvb+VR6Ph7vuuouZM2eSlZXFzp07ufnmmxk4cCBTp061Ol6rpKamHlFQOp1OsrKyGDx4sEWp2sbr9fKb3/yG888/n+zsbCorK1myZAklJSWd+9ieDhQKhfjBD37ARx99xGuvvUY4HG6+LzwlJQWXy2Vxwtb5pu1eV7dgwQLmzJnD2LFjOe2001i8eDFer7fLHvQ6Go/H0+Js5e7du9m4cSMpKSktrtzpyubNm8dzzz3HP//5T+Lj45t/FxITE4mOjrY4XessXLiQ6dOnk5+fT319Pc899xyrVq3izTfftDpaq8XHxx/RL0JsbCypqandpr+En//855x33nkUFBRQWlrKHXfcgd1u59JLL7U6WqvdeOONnH766dxzzz3MmjWL999/nyeeeIInnnjC6mhtFolEWLp0KXPmzMHhOAFleKf15y+93tKlS03giOGOO+5onsfv95v/7//9PzM5OdmMiYkxL7zwQrOsrMy60N/goYceMvPy8kyn02nm5+ebt912mxkIBKyO1SZlZWXmFVdcYebk5Jhut9scPHiwef/993fq4z06y+OPP25GR0ebNTU1VkdptyeffNIcOHCg6Xa7zVGjRpkvv/yy1ZFazefzmVOmTDHT09NNp9NpFhQUmFdffbVZXl5udbTj0t0er+f3+80LL7zQzMnJMV0ul5mdnW2ef/755vvvv291tFY7/Di6ow0rV660Ol6rtWa719U9/PDDZn5+vulyuczTTjvNXLdundWR2mTlypVH/R7MmTPH6mitdqzfhaVLl1odrdWuuuoqs6CgwHS5XGZ6ero5adIk86233rI61nHrbo/Xu/jii83s7GzT5XKZubm55sUXX2zu2LHD6lht9uqrr5onn3yyGRUVZQ4ZMsR84oknrI7ULm+++aYJmIWFhSdkfYZpmmbnH04QERERERERkROha3YVLiIiIiIiIiLtokJfREREREREpAdRoS8iIiIiIiLSg6jQFxEREREREelBVOiLiIiIiIiI9CAq9EVERERERER6EBX6IiIiIiIiIj2ICn0RERERERGRHkSFvoiIiHSY8847j2nTph112po1azAMg08//RSAp59+mpEjR+J2u8nIyGDevHknMqqIiEiP5bA6gIiIiPQcc+fOZebMmezbt4+8vLwW05YuXcrYsWMZOXIkDzzwAPfffz/33Xcf48aNw+v1smfPHmtCi4iI9DCGaZqm1SFERESkZ2hsbCQvL4/58+dz2223NY/3eDxkZ2dz3333cfHFF5Obm8urr77KpEmTLEwrIiLSM+nSfREREekwDoeDH/3oRzz99NN8+VzCCy+8QDgc5tJLL2X58uVEIhFKSkoYOnQoeXl5zJo1i+LiYguTi4iI9Bwq9EVERKRDXXXVVezcuZPVq1c3j1u6dCkzZ84kMTGRXbt2EYlEuOeee1i8eDH/93//R1VVFd/97ncJBoMWJhcREekZVOiLiIhIhxoyZAinn346Tz31FAA7duxgzZo1zJ07F4BIJEIoFOIPf/gDU6dOZfz48fz1r39l+/btrFy50sroIiIiPYIKfREREelwc+fO5R//+Af19fUsXbqUAQMGcNZZZwGQnZ0NwLBhw5rnT09PJy0tjaKiIkvyioiI9CQq9EVERKTDzZo1C5vNxnPPPcczzzzDVVddhWEYAEycOBGAwsLC5vmrqqqorKykoKDAkrwiIiI9iXrdFxERkU7x4x//mBdffJG6ujqKiorIyclpnjZjxgx27NjBE088QUJCAgsXLmTXrl1s3LgRp9NpYWoREZHuT2f0RUREpFPMnTuX6upqpk6d2qLIB3jmmWcYN24c5557LmeddRZOp5Nly5apyBcREekAOqMvIiIiIiIi0oPojL6IiIiIiIhID6JCX0RERERERKQHUaEvIiIiIiIi0oOo0BcRERERERHpQVToi4iIiIiIiPQgKvRFREREREREehAV+iIiIiIiIiI9iAp9ERERERERkR5Ehb6IiIiIiIhID6JCX0RERERERKQHUaEvIiIiIiIi0oOo0BcRERERERHpQf5/jLuDUZFZ82kAAAAASUVORK5CYII=\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x700 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x700 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x700 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x700 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x700 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x700 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x700 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x700 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x700 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x700 with 2 Axes>"
            ],
            "image/png": 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E35wAEIbmz5/vv03a8OHDG71cWlqabr31Vr366qvavn27Nm/erEGDBmn79u36zW9+01Rxj2vnzp31Pl97+nRERESda80dDockqbS0tN7lao+cBkvtadaHDh1SSUlJvfPs2LGjzryhUrv92jz1aS5ZpZqj6DExMdqyZYu++uorLV68WLt371ZCQoLGjBkT1G3Vjqh/vLNDas+SOfIuE8FSe9T6+++/b9T8tf9/Gvr5kE7+/+Xp/tkBADQdij4AhJni4mJNnTpVkvSjH/2ozuBwJ6tbt2564IEHJNXcZ/xItaWguro64PU3xhtvvFHv87X3mL/ooovqHIGtLTWbN28+ZpmKiooGT7sO9PW0a9fOf4r00fcXl2qOQtc+P3To0JNad7ANHjxYFotF2dnZWr9+/THTDxw44L9WPNRZpZpCXXud+ezZs/2D8I0fP14RERFB3dbo0aMVFRWl4uJirV69+pjpP/zwg7/o9u/fP6jbluS/FeL8+fO1f//+E85/3nnnKSYmRoWFhfrggw+OmX7kLQgb+//yeD87ubm5WrduXaPWAwAIPYo+AIQJ0zS1YMEC9e/fX1u3blVGRkaDo7wf7bPPPtP8+fOPGfXaNE19+OGHkqQOHTrUmdauXTtJapL7qB9p7dq1evrpp+s89+WXX/pHHK/9UKPWsGHDJEnPP/98nWuTy8vLNXny5AZH6K59PZs2bTrpjL/61a8kSY8//nidAm2app544gllZ2crISFBt95660mvO5jat2+vn/70pzJNU7/4xS/qHL2ufX+qqqp0wQUX6IILLghh0v+pPUX/7bff1nvvvVfnuWCKjY3VfffdJ6lmpPgjy/ahQ4d0yy23yOfzqX///ho4cGDQt3/uuefqqquuUmVlpa666irl5OTUmV5dXV2n0EdERGjKlCmSpPvuu6/O0XaPx6O7775bubm56tixo8aNG9eoDLU/O7///e9VVFTkf/7gwYO68cYbVVZWFujLAwCcZvVfhAYAaNZefvllffHFF5Ikl8ulgoICrVu3ToWFhZKkIUOGaPbs2ceU84Zs2LBBU6dOVVxcnPr27avMzExVVlZq3bp12r17t+Lj4/XYY4/VWWbs2LH6/PPPNWHCBA0fPlyJiYmSpF//+tfq2rVr0F7rXXfdpQcffFCvvfaaevXqpf3792vZsmXy+Xy6++67jxnJ+2c/+5n+/Oc/a82aNTr77LN10UUXyefzac2aNXI4HLr55pvrvWXbwIEDlZmZqW+++UZ9+/ZVz549Zbfb1bVrV/36178+bsZf/OIXWr58uV5//XWdd955uuSSS5Samqp169Zpy5YtioyM1Lx589SmTZugvS+Bev755/X9999r1apV6ty5s4YOHSqbzaYlS5bo4MGD6tixo+bOnRvqmH4DBw5Ujx49/B/AnHvuuerbt+9xl3n88cf10UcfHfP8lVde6T9zo2/fvnrhhRfqTH/kkUe0Zs0aLViwQN27d9fAgQNls9m0cuVKFRYWqkOHDv6j5E1hzpw5Gj16tFauXKkuXbroggsuUGZmpnJzc/Xtt9/q4MGDdcajmDFjhtasWaPFixere/fuGjp0qGJjY7VixQrl5OQoOTlZ//znP/2v+USmTJmil156SevWrVPXrl01aNAglZeXa/Xq1Wrfvr1+8pOf6P3332+iVw8ACCaKPgC0QF999ZW++uorSVJ0dLTi4+PVs2dPnXfeebrmmmt0/vnnn9T6rrjiChUXF2vZsmXaunWrVq5cqcjISGVlZek3v/mNpkyZ4j/iXev2229XaWmp3njjDc2fP98/8vWECROCWvSvvvpqXXXVVXrqqac0f/58ud1u9e3bV3feeWe9t7Oz2+1atGiRHn30Ub3//vv65JNPlJqaqquvvlqPP/74MeWulsPh0Mcff6yHH35YK1as0Pr16+Xz+XTJJZecsOgbhqHXXntNo0aN0t///netXbtW5eXlSk9P10033aTf/OY3QX1PTkVycrKWL1+u5557Tm+99ZY++eQT+Xw+dezYUbfeeqt+9atf+T+0aS4mTZrkP9pe34j4R9u+fbtWrVp1zPO1A1RKqvfUf4fDoQ8//FD/93//p1deeUXLly9XdXW1OnbsqNtuu0333Xdfo+5iEajExEQtWbJEs2fP1rx585Sdna3ly5crNTVV5557rn7yk5/Umd/pdGrhwoV66aWX9Nprr2nZsmVyuVzKysrSL3/5Sz3wwAMnNdZCQkKCvvrqKz300ENauHChFixYoLZt22ry5MmaNm2a7rzzziC/YgBAUzHMkxmqGAAAAAAANGtcow8AAAAAQBih6AMAAAAAEEYo+gAAAAAAhBGKPgAAAAAAYYSiDwAAAABAGKHoAwAAAAAQRij6AAAAAACEEYo+AAAAAABhhKIPAAAAAEAYoegDAAAAABBGKPoAAAAAAIQRij4AAAAAAGGEog8AAAAAQBih6AMAAAAAEEYo+gAAAAAAhBGKPgAAAAAAYYSiDwAAAABAGKHoAwAAAAAQRij6AAAAAACEEYo+AAAAAABhhKIPAAAAAEAYoegDAAAAABBGKPoAAAAAAIQRij4AAAAAAGGEog8AAAAAQBih6AMAAAAAEEYo+gAAAAAAhBGKPgAAAAAAYYSiDwAAAABAGKHoAwAAAAAQRij6AAAAAACEEYo+AAAAAABhhKIPAAAAAEAYoegDAAAAABBGKPoAAAAAAIQRij4AAAAAAGGEog8AAAAAQBih6AMAAAAAEEYo+gAAAAAAhBGKPgAAAAAAYYSiDwAAAABAGKHoAwAAAAAQRij6AAAAAACEEYo+AAAAAABhhKIPAAAAAEAYoegDAAAAABBGKPoAAAAAAIQRij4AAAAAAGGEog8AAAAAQBih6AMAAAAAEEYo+gAAAAAAhBGKPgAAAAAAYcQW6gAtkc/n0/79+xUbGyvDMEIdBwAAAAAQ5kzTVGlpqTIzM2WxHP+YPUU/APv371dWVlaoYwAAAAAAWpk9e/aoXbt2x52Hoh+A2NhYSTVvcFxcXIjTAAAAAADCXUlJibKysvx99Hgo+gGoPV0/Li6Oog8AAAAAOG0ac/k4g/EBAAAAABBGKPoAAAAAAIQRij4AAAAAAGGEog8AAAAAQBih6AMAAAAAEEYo+gAAAAAAhBGKPgAAAAAAYYSiDwAAAABAGKHoAwAAAAAQRmyhDgAAAP7HNE253e5Qx2jWjnyPHA6HDMMIcaLQ4j0AAByNog8AQDPidrt19913hzoGWpBnn31WTqcz1DEAAM0Ip+4DAAAAABBGOKIPAEAz9esLIuWwhjpF8+P2mnpmeZUk6dcXRMhhbX2nrbu90jPLK0MdAwDQTFH0AQBophxWtcoSezIcVqOVvkdmqAMAAJoxTt0HAAAAACCMUPQBAAAAAAgjFH0AAAAAAMIIRR8AAAAAgDBC0QcAAAAAIIxQ9AEAAAAACCMUfQAAAAAAwghFHwAAAACAMELRBwAAAAAgjFD0AQAAAAAIIxR9AAAAAADCCEUfAAAAAIAwQtEHAAAAACCMUPQBAAAAAAgjFH0AAAAAAMIIRR8AAAAAgDBC0QcAAAAAIIxQ9AEAAAAACCMUfQAAAAAAwghFHwAAAACAMELRBwAAAAAgjFD0AQAAAAAIIxR9AAAAAADCCEUfAAAAAIAwQtEHAAAAACCM2EIdAEB4Mk1TbrdbkuRwOGQYRogTAQCA1or9ErQ2HNEH0CTcbrfuvvtu3X333f4/rAAAAKHAfglaG4o+AAAAAABhhKIPAAAAAEAYoegDAAAAABBGKPoAAAAAAIQRij4AAAAAAGGEog8AAAAAQBih6AMAAAAAEEYo+gAAAAAAhBGKPgAAAAAAYYSiDwAAAABAGKHoAwAAAAAQRij6AAAAAACEEYo+AAAAAABhhKIPAAAAAEAYoegDAAAAABBGKPoAAAAAAIQRij4AAAAAAGGEog8AAAAAQBih6AMAAAAAEEYo+gAAAAAAhBGKPgAAAAAAYYSiDwAAAABAGKHoAwAAAAAQRij6AAAAAACEEVuoA6BpbdiwQW+++aauvfZa9erVK9Rxjpvn6Gm1jwcOHKilS5dKkm688cY6ywXy+o5c78qVK3XttddKkn89kvTaa69JkgYPHnzMPB07dtS6devkdDp16aWXaunSpXK5XKqurlanTp20Y8cO2Ww2OZ1O//KJiYnavn270tPTlZ+fr9TUVOXm5qpfv3669dZb/blmz56tqqoqSZJhGDJNU1arVZGRkUpLS9P27dv9r6Nz587+bVmtVtlsNt14441atWqV1q5dK0my2Wyqrq72r6vWkY/T09OVm5vbqPcuUB999JHGjBnTpNsAAABojIceekher1eS5PP55Ha7ZbPZ5PV61bdvX23ZskWVlZXyer2y2Wz+aR6Px7+O2n0sh8Mhi8Xi3w+r3R/94IMPtGDBAjmdTt18883atWuXFi5cqJEjR+qMM87Qa6+9purq6jrrq12+vv3b+p774IMP/Ou88sorj/uaN2zYUGf/9rPPPvPvczocDjkcDt14442S5M/m9XpVXV2tvn37aufOnY3a325M9hM9Ph2O3Kb0v33/o7tGS0bRD2Nut1vz5s1TUVGR5s2bp27dusnhcDTLPEdP69Spk//xggUL/KV07ty5/uUCeX1HLlO73rlz50qSiouLNXfuXJmmqbKyMkmqd57CwkJJUlVVVZ1skvxF3OPxyOPx+KfXLlNbqGv/u3btWo0dO1YxMTF64403/L9wJfnX6/V6VVZW5s/U0Lakml9SR85X+wfkyIxHP27qki9JixYt0vDhwxUTE9Pk2wIQXtb6Dun56i2aYuuqfpbkUMcBEAbKy8uPea52n6n2YMmRzx9ZyI+e3+12+5+r3U91u93+fcCqqiq9/vrrKi0tlVSzbxkTE3PMfl3t8kfuA9fu30o65rkjt7FgwQJdeumlDe5nud1uzZ0795j92yOnu91uvfHGG5J0TLba9+RE+9v17Zsfnf3o11ff623qvnJkztp9/NrXfGTXaOk4dT+MLVy4UMXFxZJqCurChQubbZ6jp7344ov+x0f+IjpyuUBe35HL1K63uLi4znpKSkr889c3z5GOLtAnO12SnnnmGS1cuLDOdgNV3x+N5sA0Tb344ouhjgGghTFNU7OrtynHLNfs6m2N+p0KAKFSuz/64osv1vl9VVvypZrfa0c+Pnr5I/eBa9dX3z7vkds40X7WkcvXzl+fkpKS4+6Pnmh/u76cx9vHb+j1NrWjMx353jSHzhQsHNEPU/n5+Vq4cGGdXwAff/yxBg4cqNTU1GaVR9Ix07Zt29bguhYuXKguXbqc9Os7OkNzcfjwYc2fPz/UMZrctm3btGHDBnXt2jXUUYBmzeVy+f9d8/vKCF2YEFtjHtIWs2anc4tZojXmIZ1vpIQ4VfNw5N+yI79nANRv3759p2U7p7pPd+Q+sGma/tJ55D7v0Ufka5fbvHmzunfvXuf5/Px8LViw4JQyHZmnof3t+vb1ax83tI9f3+Om7iuN6QMLFy4MWWcKJop+I7hcrjp/RINx5LUpmaapN998s8Hnf/nLX8owTt+O4/Hy/OMf/zjpLD6fTy+//HKD26nv9dVOa24lv7V54YUXQh0BaFE8PskZ6hAhYpqmXqneLoskn2pOQXylervOs3P6vlTzvVHr/vvvD10QAE3K5/Md81xD+7Mvv/yynnnmGVksFv98//jHP4K6/1vf/nZD+/r1ZQ9k/cHSUM6j+Xw+/eMf/9Bdd911WjtTsHHqfiPMnDlT8fHx/q+srKxQRzqu3Nxcbdq06ZgfLp/Pp02bNp2Wa7Ibm2fz5s31TjuR8vLyk3p9tRko+gDQMtQeza/9Te/T/47qAwCOVV5ero0bN/of5+bmavPmzUHdRn372w3t6wdr/cFyMjk3b9582jtTsHFEvxEefPBB3Xvvvf7HJSUlzbrsp6enq0ePHvr+++/rfCNbLBZ169ZN6enpzSZP165dZRjGMdNOJDo6WpWVlY1+fbUZNm/eTNkPoejoaD3xxBP+T5oBHMvlcvmP0Npb6Y/K0Ufza9Ue1f+TJSlEyZqPI783nn76aTmdrfXcD+DETNPU888/r61bt4Y6SpOKjo7WOeec43+cnp6u7t27B7Xs17e/3dC+frDWHywnk7N79+6nvTMFG0W/EZxOZ4v6A2oYhq699lpNnz79mOevu+66034KyvHyjB8/XqZpHjPteCwWi2699VY999xzx6yvodd3ZAaKfuhMnjxZkZGRoY4BtBgt+ZTBU3HktflHqj2qv84slBR12nM1J0d+b7S0/RQgFK655ho98cQToY5x0moPjhxZTI++bXKtyZMn1zmYUrtv/Nvf/jZo+7/17W83tK9vsVjqXKMf6PqDpaGcR7NYLBo/fnyL/xvcSo8VhL/U1FSNHDnS/w1qGIZGjBihNm3aNLs89U0788wzG/zhGjlypLp163bSr+/o7TQXiYmJGj16dKhjNLkzzzyTgfgAnFDt0fyGflMbkl7zbZMpPrQF0Hinax949OjROvPMMwNe/sh9YMMwNHLkyGP2eUeNGnXMNhraz0pNTdWoUaMCznOk4+1v17c/P3LkSI0aNarBffz6Hjd1X2lMHxg5cmTIOlMwUfTD2MiRIxUfHy9Jio+P18iRI5ttnqOn3Xbbbf7HR/4gHrlcIK/vyGVq15uQkFBnPXFxcf75a+epHZ/haCf60KAxHyr8+te/1siRI+tsN1CxsbGnvI6mYBiGbrvttlDHANACeGQq36xqsMabkgrkkmlQ9AE0L7X7o7fddludfcAj988Mw2hwf+3ofeDa9dW3z3vkNk60n3Xk8rXzN7T94+2Pnmh/u76cx9vHb+j1NrWjMx353jSHzhQsFP0w5nA4NH78eCUlJWn8+PFyOBzNNs/R02JiYvyPR40apZiYGMXExOj666/3LxfI6ztymVGjRvmXvf7665WUlKTrr79eEyZM8G+vdp7rr7/eP0+/fv1kGIYiIiL82ex2uwzDUOfOnWUYhux2e53lO3fuLKnm2iCLxeK/5qdfv35KSkqSw+HQhAkTFBER4c9a+0vYarUqJibGv45aR24rIiJCMTExuuGGG9SvXz//PDabrc66jl53baam9qMf/UgxMTFNvh0ALZ/DsOh5xwD9zd7w17PW/rKY7MIACEx0dLQiIiIUERHh33+02WwyDEP9+vVTTEyMrFar//mIiAjZ7fY666jdx3I4HP79sNr91Np9wNr9xRtuuEGjR4+WxWLRqFGjdMMNNygmJsaf4cjlj9wHrt2/rW+ft3Ybtes83n6Ww+Hwr7t2uSP3OWvXd+R+cO1rrn1PGrO/XV/O4+3j1/f4dPSVIzPV7uPX1zVaOsPkguWTVlJSovj4eBUXFwflKCwQjlwul+6++25J0rPPPsv1o0AjHfmz8/DFkXJYm9flRs2B22vqyWWVklrve3Tke8DvWODE2C9BODiZHsrH4QAAAAAAhBGKPgAAAAAAYYSiDwAAAABAGKHoAwAAAAAQRij6AAAAAACEEYo+AAAAAABhhKIPAAAAAEAYoegDAAAAABBGKPoAAAAAAIQRij4AAAAAAGGEog8AAAAAQBih6AMAAAAAEEYo+gAAAAAAhBGKPgAAAAAAYYSiDwAAAABAGKHoAwAAAAAQRij6AAAAAACEEYo+AAAAAABhhKIPAAAAAEAYoegDAAAAABBGKPoAAAAAAIQRij4AAAAAAGGEog8AAAAAQBih6AMAAAAAEEZsoQ4AIDw5HA49++yz/n8DAACECvslaG0o+gCahGEYcjqdoY4BAADAfglaHU7dBwAAAAAgjFD0AQAAAAAIIxR9AAAAAADCCEUfAAAAAIAwQtEHAAAAACCMUPQBAAAAAAgjFH0AAAAAAMIIRR8AAAAAgDBC0QcAAAAAIIxQ9AEAAAAACCMUfQAAAAAAwghFHwAAAACAMELRBwAAAAAgjFD0AQAAAAAIIxR9AAAAAADCCEUfAAAAAIAwQtEHAAAAACCMUPQBAAAAAAgjFH0AAAAAAMIIRR8AAAAAgDBC0QcAAAAAIIxQ9AEAAAAACCMUfQAAAAAAwghFHwAAAACAMGILdQAAAFA/t1eSzFDHaHbcXrPef7cmNd8bAADUj6IPAEAz9czyylBHaPaeWV4V6ggAADQ7nLoPAAAAAEAY4Yg+AADNiMPh0LPPPhvqGM2aaZpyu92Sat4vwzBCnCi0HA5HqCMAAJoZij4AAM2IYRhyOp2hjtHsRUREhDoCAADNFqfuAwAAAAAQRij6AAAAAACEEYo+AAAAAABhhKIPAAAAAEAYoegDAAAAABBGKPoAAAAAAIQRij4AAAAAAGGEog8AAAAAQBih6AMAAAAAEEYo+gAAAAAAhBGKPgAAAAAAYcQW6gAtkWmakqSSkpIQJwEAAAAAtAa1/bO2jx4PRT8ApaWlkqSsrKwQJwEAAAAAtCalpaWKj48/7jyG2ZiPA1CHz+fT/v37FRsbK8MwQh3ntCspKVFWVpb27NmjuLg4tsE22EaYbSMcXgPbYBstdRvh8BrYBttgG6FbP9sI722YpqnS0lJlZmbKYjn+Vfgc0Q+AxWJRu3btQh0j5OLi4prsB4JtsA22EfpthMNrYBtso6VuIxxeA9tgG2wjdOtnG+G7jRMdya/FYHwAAAAAAIQRij4AAAAAAGGEoo+T5nQ69dvf/lZOp5NtsA22EYbbCIfXwDbYRkvdRji8BrbBNthG6NbPNlrnNurDYHwAAAAAAIQRjugDAAAAABBGKPoAAAAAAIQRij4AAAAAAGGEog8AAAAAQBih6AMAAAAAEEYo+gAAAAAAhBGKPgAAAAAAYYSiDwAAAABAGKHoAwAAAAAQRij6AAAAAACEEYo+AAAAAABhhKIPAAAAAEAYoegDAAAAABBGKPoAAAAAAIQRij4AAAAAAGGEog8AAAAAQBih6AMAAAAAEEYo+gAAAAAAhBGKPgAAAAAAYYSiDwAAAABAGKHoAwAAAAAQRij6AAAAAACEEYo+AAAAAABhhKIPAAAAAEAYoegDAAAAABBGKPoAAAAAAIQRij4AAAAAAGGEog8AAAAAQBih6AMAAAAAEEYo+gAAAAAAhBGKPgAAAAAAYYSiDwAAAABAGKHoAwAAAAAQRij6AAAAAACEEYo+AAAAAABhhKIPAAAAAEAYoegDAAAAABBGKPoAAAAAAIQRij4AAAAAAGGEog8AAAAAQBih6AMAAAAAEEZsoQ7QEvl8Pu3fv1+xsbEyDCPUcQAAAAAAYc40TZWWliozM1MWy/GP2VP0A7B//35lZWWFOgYAAAAAoJXZs2eP2rVrd9x5KPoBiI2NlVTzBsfFxYU4DQAArYvb7dYf//hHSdJ9990nh8MR4kQAADS9kpISZWVl+fvo8VD0A1B7un5cXBxFHwCA08ztdisiIkJSzd9iij4AoDVpzOXjzWowvpkzZ+r8889XbGysUlNT9ZOf/ERbtmypM09VVZWmTJmi5ORkxcTEaOzYscrLy6szT05Oji6//HJFRUUpNTVVv/71r1VdXV1nni+++EJ9+/aV0+nUmWeeqVdeeaWpXx4AAAAAAE2uWRX9JUuWaMqUKVq5cqUWLVokj8ej4cOHq7y83D/P1KlT9Z///Ef//Oc/tWTJEu3fv19jxozxT/d6vbr88svldru1fPlyvfrqq3rllVc0bdo0/zw7d+7U5ZdfrqFDhyo7O1v33HOPbrnlFn388cen9fUCAICGlbvKFT0lWtFTolXuKj/xAgAAQJJkmKZphjpEQw4ePKjU1FQtWbJEgwcPVnFxsdq0aaN58+Zp3LhxkqTvv/9e3bt314oVKzRw4EAtWLBAP/7xj7V//36lpaVJkl588UU98MADOnjwoBwOhx544AF99NFH2rhxo39b1157rYqKirRw4cIT5iopKVF8fLyKi4s5dR8AgCZS7ipXzJ0xkqSyv5Yp2hktqebU/ZkzZ0qSHnzwQU7dBwC0CifTQ5vVEf2jFRcXS5KSkpIkSWvXrpXH49GwYcP883Tr1k3t27fXihUrJEkrVqxQz549/SVfkkaMGKGSkhJ99913/nmOXEftPLXrOJrL5VJJSUmdLwAAAAAAmqNmW/R9Pp/uueceXXjhhTrnnHMkSbm5uXI4HEpISKgzb1pamnJzc/3zHFnya6fXTjvePCUlJaqsrDwmy8yZMxUfH+//4tZ6AAAAAIDmqtkW/SlTpmjjxo168803Qx1FDz74oIqLi/1fe/bsCXUkAAAAAADq1Sxvr3fnnXfqww8/1NKlS9WuXTv/8+np6XK73SoqKqpzVD8vL0/p6en+eb7++us666sdlf/IeY4eqT8vL09xcXGKjIw8Jo/T6ZTT6QzKawMAAAAAoCk1qyP6pmnqzjvv1HvvvafPPvtMHTt2rDO9X79+stvtWrx4sf+5LVu2KCcnR4MGDZIkDRo0SN9++63y8/P98yxatEhxcXHq0aOHf54j11E7T+06AAAAAABoqZrVEf0pU6Zo3rx5+ve//63Y2Fj/NfXx8fGKjIxUfHy8Jk2apHvvvVdJSUmKi4vTL3/5Sw0aNEgDBw6UJA0fPlw9evTQDTfcoKefflq5ubl65JFHNGXKFP9R+dtuu01//etfdf/99+vmm2/WZ599prffflsfffRRyF47AACoy2JYdMlZl/j/DQAAGqdZFf2//e1vkqQhQ4bUeX7OnDm66aabJEmzZs2SxWLR2LFj5XK5NGLECL3wwgv+ea1Wqz788EPdfvvtGjRokKKjozVx4kQ99thj/nk6duyojz76SFOnTtWzzz6rdu3a6eWXX9aIESOa/DUCAIDGiXRE6otffxHqGAAAtDiGaZpmqEO0NCdz/0IAABBcbrdbM2fOlFQzYK7D4QhxIgAAmt7J9FDOgwMAAAAAIIw0q1P3AQAAapW7ynXGb86QJO363S5FO6ObbFs5OTkqKChosvWnpKSoffv2TbZ+AACORNEHAADNVkFZ05XvWjk5OerevbsqKiqabBtRUVHavHkzZR8AcFpQ9AEAQKtWUFCgiooKPfm3p9SpS6egr3/H1h16+PaHVFBQQNEHAJwWFH0AAABJnbp0Uvfe3UMdAwCAU0bRBwAArYrX9KrYVaxC12EVugq1N2Kv7p/9gKpTvNpVuluGYSjC6lSMLUZRtigZhhHqyAAAnBSKPgAACHten1d7y/dqW/EO5Vbmymf6/jfRJp1zYU+ZMlXiKZEkFUvKU74ssijaHq04e5wSnQmyGNywCADQ/FH0AQBA2CpyFWlr8TbtKNkpt8/tf95hcSjRmajkiCQVHSjSo488qjsfulPp7dLlM32q8FaqzFMmr+lVqadUpZ5S5Vflq01EGyU5Eyn8AIBmjaIPAACaJYth0XkdzvP/+2SUesq0vmC9dpbu8j8XZYtUp7hO6hTXUXH2OP8p+ev2rNOK/yzXXXffpeSIZP/8pmmqylulUk+ZDlUVyOPzaH/Ffh2szFebyFQlO5M4rR8A0CxR9AEAQLMU6YjU6kdWn9QyldVV+rZwo7YWbZVPNafnZ8VkqUv8mcqISj+pDwwMw1CkLVKRtkilRCSr0HVYByvz5TGrtb9iv4rdxcqKbieH1XFSGQEAaGoUfQAA0Kzl5OSooKDA/7i6utr/7+zsbNlsNpkyddhWpDxnvnxGTcGPro5WmruNIssilZebqzzl1rv+zZs3nzCDxbAoJSJZSc5EFboKlVuRp/Lqcm0t2aZ20W0V74g/xVcJAEDwUPQBAECzlZOTo+7du6uiosL/nN1u18MPPyxJuuiii5SYnqibn7xFPQb0kCTt3LhDbz3zljat/O6ktlVWVnrCeWoKf4pi7bHKKdujSm+ldpflKMmZpMyoDK7dBwA0CxR9AADQLFW4KjTwzwNVcUWFfjt4urp17SZJ8nl92rriB0nS//t8jpQsySLJJ1mKLeoS30WPPvFoo7ezbPEyvTDzeVW5qhq9jNPqVOe4TsqrzNfBqoMqdBWqyluljjFnyGqxnszLBAAg6Cj6AACgWTJl6kDpASlWOqPzGereu7skqdpT7S/6vkSfLBaLYmzRahvdTs6Uk79efufWnQHlsxgWZUSlK8Yeo5yy3aqortD20h3qGHuG7BZ7QOsEACAYOL8MAAC0KOWecv+/DRlqG5WpjrEd5QzRoHix9hh1iu0km2FTlbdK20t2yO11n3hBAACaCEUfAAC0CKZpKq8yTzvLdvmf6xzXSckRySG/zV2kLVKd4zrJbrHL7XNre8l2VXkbfykAAADBRNEHAADNnmmY2lm2S3mV+XWej7BGhCjRsZxWp86M6yynxSmPWa0dJTs5sg8ACAmKPgAAaPa8qV6VecpkyFC7qLahjtMgu8WuznGd5LQ6VW1Wa1fZbpmGGepYAIBWhqIPAACaP1tNiT4zrrMSnAmhTnNcNotNHWPO8F+z703xyWpjJH4AwOlD0QcAAM2OaZr6rnCT2ia3VdvktjJchrrEnalIW2SoozWKw+rQGbFnyCKLzAhTP39skkxxZB8AcHpQ9AEAQLNS7avWstyvtKX0B828+fcaFvEjRRVFyWZpWXcFjrJFqn1MlmRKg8cO1kF7QagjAQBaCYo+AABoNso95fp4zyfaXbpbhgxlVKXr1RmvyFBoR9UPVJwjTtbDNbtbB50F2le+P8SJAACtAUUfAAA0C3kV+fooZ4EKXYfltDr1o3bDlFSdGOpYp8xSbtGi1z+RJC3PXaHK6soQJwIAhDuKPgAACLkfirbq072L5fK6lOhM1Oj2IxVrjdFP3/ypNFZyVbtCHfGUvPn0P+T0OlXlrdJXuStkmlyvDwBoOhR9AAAQMj7Tp1V5X2tV/tfyyacOMe01Imu4YuwxMmVqx+EdUqJa/EB2HrdH7araympYdaDigDYd3hzqSACAMEbRBwAAIVFVXaVP9y7WD8VbJUnnJvfWxRkXyd7CBt1rrAjTqfPbnCdJ+qYgWwVVh0KcCAAQrsLzLykAAGjWCqsK9cX+pSqvLpfdYtOF6RcqK6ZdqGM1qc2bN6ubuikuIlYltlIt3rVYnSo6yirrKa87JSVF7du3D0JKAEA4oOgDAIDTanvxDq3K/1pe06tYe6yGZF6iBGd8qGM1mYK8AsmQJkyYIEmKiovSE+8/pZS2KZr19p/1j9/PO+VtREVFafPmzZR9AIAkij4AADhNvD6v1hxc6z9Vv210pi5Mv0BOqzPEyZpWaUmpZEq/nnm/+p7fV5Lkc/jklU+jfj5aV4y+QoYn8NsH7ti6Qw/f/pAKCgoo+gAASRR9AABwGpR7yrXkwDId+u916b2Te6ln0jkyjMALbkvTvlOWuvfu7n+8u3S3ij0lcrRzqnNsp1b1XgAAmhaD8QEAgCZ1oPyAPspZoENVh+SwOHRp2yHqldzzhMXWkKGM2AyptObf4SYjKkMWWVRRXaHD7sOhjgMACCPNqugvXbpUV1xxhTIzM2UYht5///060w3DqPfrmWee8c9zxhlnHDP9d7/7XZ31bNiwQRdffLEiIiKUlZWlp59++nS8PAAAWhXTNPXtoY1avO9zubwuJTmTNLrDKLWNbtuo5aOcUfpwwofSW5LTFn6n9zusDqVFpkqSDlTkqtpXHeJEAIBw0axO3S8vL1fv3r118803a8yYMcdMP3DgQJ3HCxYs0KRJkzR27Ng6zz/22GO69dZb/Y9jY2P9/y4pKdHw4cM1bNgwvfjii/r222918803KyEhQZMnTw7yKwIAIPzl5OSooKCgznNeebUvYr9KbWWSpARPvNLK2mjroR9Oat2bN4f3/eZTIlJ02H1YVV6Xcivz1K6RH4IAAHA8zarojxo1SqNGjWpwenp6ep3H//73vzV06FB16tSpzvOxsbHHzFtr7ty5crvdmj17thwOh84++2xlZ2frT3/6E0UfAICTlJOTo+7du6uiosL/XHrHDN37t3uV3jFDHrdHr814VUve+eKUtlNWVnqKSZsnwzDUNqqttpfuUKGrUInOREXbokIdCwDQwjWron8y8vLy9NFHH+nVV189Ztrvfvc7Pf7442rfvr3Gjx+vqVOnymareakrVqzQ4MGD5XA4/POPGDFCv//973X48GElJiYesz6XyyWXy+V/XFJS0gSvCACAlqegoEAVFRV68m9PqVOXTvI5ffKm+GouDqyWIg5H6LbbbtNtt9120ut2V7v1q/d/pYMH8lVSEb5/e6Pt0Up0JOiwu0gHKg4wMB8A4JS12KL/6quvKjY29phT/O+66y717dtXSUlJWr58uR588EEdOHBAf/rTnyRJubm56tixY51l0tLS/NPqK/ozZ87UjBkzmuiVAADQ8nXq0kltuqZqf8V+SVKULUodEtrLnmoPeJ2V7godfCdfaiOZMoMVtVlKj0pXkbtYFdUVKvOUKdYRe+KFAABoQIst+rNnz9b111+viIiIOs/fe++9/n/36tVLDodDv/jFLzRz5kw5nYEN5PPggw/WWW9JSYmysrICCw4AQJgxLIa8CV5/yU90JKhtdFtZjGY15m+zZrfYlRyRrIKqAuVW5inGHsNRfQBAwFpk0V+2bJm2bNmit95664TzDhgwQNXV1dq1a5e6du2q9PR05eXl1Zmn9nFD1/U7nc6APyQAACCcmTJ1+x/ukC+25oh7emS62kSkUFIDkBrRRoVVhar0VqrEU6J4R3yoIwEAWqgW+VH7//t//0/9+vVT7969Tzhvdna2LBaLUlNrbl8zaNAgLV26VB6Pxz/PokWL1LVr13pP2wcAAPXz+rzaE7FXAy8fJJlSh5j2So1sQ8kPkM1iU0pEsiQptzJPphnelysAAJpOsyr6ZWVlys7OVnZ2tiRp586dys7OVk5Ojn+ekpIS/fOf/9Qtt9xyzPIrVqzQn//8Z61fv147duzQ3LlzNXXqVE2YMMFf4sePHy+Hw6FJkybpu+++01tvvaVnn322zqn5AADg+Lw+r5YcWKpSW5ncLresBRaOQAdBm4g2shpWubwuFbmLQh0HANBCNauiv2bNGvXp00d9+vSRVHO9fZ8+fTRt2jT/PG+++aZM09R11113zPJOp1NvvvmmLrnkEp199tl68sknNXXqVP3973/3zxMfH69PPvlEO3fuVL9+/XTfffdp2rRp3FoPAIBGqvZV67P9X2hf+X4ZpqFZv/ijLFXNapeixbJarGoTkSJJyqvM56g+ACAgzeoa/SFDhpzwD9rkyZMbLOV9+/bVypUrT7idXr16admyZQFlBACgNfOZPi078KVyK3JlM2xqV9FW3634rsm2F2WLVkVpeZOtvzlKiUhRQdUhuX1uFboKlfzf0/kBAGgsPn4HAACNtvbgN9pbvk9Ww6rL2g1VtC+qybYV6YjSI70fkeZKTmvrGRTXYliUGtlGkpRfdZCj+gCAk0bRBwAAjbKl6Ad9X/S9JOnC9EFKjUwNcaLwleRMks2wyePzqMhdHOo4AIAWhqIPAABOaF/5Pq3OXyNJOjeltzrEdghxovBmMSz+U/YPclQfAHCSKPoAAOC4DrsOa+n+L2XKVOe4Tjon8ezTst0qT5Ve2vJ36XLJ7XWflm02J8nOJBkyVOWtUll16xqnAABwaij6AACgQR6fR0v2L1W1Wa20yDQNSOsvwzBOy7ZN06edZTulDMlU6zuibbPYlORMklRzVB8AgMai6AMAgAZ9nb9GpZ4yRduidEnmxbIa1lBHalVqb7VX5ilTZXVliNMAAFoKij4AAKjXzpJd2lGyQ4YMXZh+Yasa+b65cFgdinfES5IOVhWEOA0AoKWg6AMAgGOUecq0Kv9rSdI5SWcrLYoR9kOl9qh+kbuoVY5VAAA4eRR9AABQh8/06avc5fL4PEqJSFGv5J6hjtSqRdmiFG2LliQVuA6FOA0AoCWwhToAAABoWjk5OSooaPxp3/n2gzroLJDFtCjxULyyC7IbnHfz5s1BSIgTaRORovKychVWFSotMpWxEgAAx0XRBwAgjOXk5Kh79+6qqKho1PxZXbP02L+ekFVWvXD/81r+wVeNWq6srPRUYjbIbrHL4/I0ybpbklh7rJwWp1w+lw67ipQSkRzqSACAZoyiDwBAGCsoKFBFRYWe/NtT6tSl03HnNWXKm+qVaZOMCkO/vOuX+uVdvzzuMssWL9MLM59XlasqmLElSZGOKM3o85geuv1BOUe37oEADcNQckSS9lcc0CHXISU7k07bbQ4BAC0PRR8AgFagU5dO6t67+3HnKag6pP0V+2WRRV0zz5K9nf2E6925dWewIuIEEh2JOlCRK5fXpfLqcsXYY0IdCQDQTDEYHwAAkMfnUW5FriQpPSpddsuJSz5OL6vFqkRnoiTpkKswxGkAAM0ZRR8AAGhf+X755FOUNVLJzqRQx5EkuTwuvbr1FWm45PFynb4k//+bYnexPD7eEwBA/Sj6AAC0csXuEpV4SiRJbaPbNptrv32mV1tKtkjtJZ98oY7TLETaIhVli5IkFXJUHwDQAIo+AACtmNf0an/Ffkk1t3CLtEWGOBFOJNlZM+L+oapCmaYZ4jQAgOYoaIPxVVRU6M0335TL5dLo0aPVoUOHYK0aAAA0kfzKg/L4PLJb7EqLTAt1HDRCvCNOBypsqjarVfzfMzEAADhSQEV/0qRJWrVqlTZu3ChJcrvdGjhwoP9xfHy8PvvsM/Xp0yd4SQEAQFC5vG4VVBVIkjKjMmUxONGvJbAYFiU5E5VfdVCHqg6FOg4AoBkK6C/6559/rjFjxvgfz5s3Txs3btTcuXO1ceNGpaena8aMGUELCQAAgu9AxQGZMhVji1GcPTbUcXASkv47KF95dblMG6fvAwDqCqjo5+bm6owzzvA/fv/993XeeefpuuuuU48ePXTrrbdq1apVwcoIAACCrNRT5h+ALzMqo9kMwIfGcVgdirPHSZJ8MQxUCACoK6CiHx0draKiIklSdXW1vvjiC40YMcI/PTY2VsXFxUEJCAAAgss0Tf8AfMnOZEXYIkKcCIGoParvizJld9pDnAYA0JwEVPT79u2rl156Sd98842efPJJlZaW6oorrvBP3759u9LSGNAHAIDm6JCrUC6vS1bDqrTI1FDHaVCkI0pP9ZspvSw5rc5Qx2l2Yu0xslvsklU6f2T/UMcBADQjAQ3G9+STT2rEiBE677zzZJqmxo0bp/79//cH5r333tOFF14YtJAAACA4qn3VyqvMkySlRabJZgnaDXhwmhmGoSRnkvIq8zT0Z5eGOg4AoBkJ6K/7eeedp++//17Lly9XQkKCLrnkEv+0oqIi3XHHHXWeAwAAzUNeZZ68plcR1ggl//fUb7RcSc5E5VXkqet5XVVV4Qp1HABAMxHwx/ht2rTRVVdddczzCQkJuvvuu08pFAAACL7K6iodchVKahkD8Lk8Ls3bPle6VPJ4PaGO0yzZLXYZlYbMKFOHbYdDHQcA0Eyc0vl6paWl2r17tw4fPizTPPbWLoMHDz6V1QMAgCAxZerAfwfgi7PHKcYeE+JEJ+YzvdpYtFHqJPnEyPINsZQb8kaZKrIXq9pXzeUYAIDAiv6hQ4d055136t1335XX6z1mummaMgyj3mkAAOD0MyNNlVWXy5ChzKiMUMdBEBlVhg7uPag27doopyxHneI6hToSACDEAir6t956q/7zn//orrvu0sUXX6zExMRg5wIAAEFid9jlTag5It4mIkUOqyPEiRBMhgx98c/P9dOpP9MPRdso+gCAwIr+J598oqlTp+rpp58Odh4AABBkI24aKdkkm2FTm8g2oY6DJrDsX0v103t+poNVB1XkKlKCMyHUkQAAIWQJZKGoqCidccYZQY4CAACCzWN4dOVtNYPnZkSly2pYQ5wITaEov0ix3lhJ0tbibSFOAwAItYCK/oQJE/Tee+8FO4uWLl2qK664QpmZmTIMQ++//36d6TfddJMMw6jzNXLkyDrzFBYW6vrrr1dcXJwSEhI0adIklZWV1Zlnw4YNuvjiixUREaGsrCzOTAAAhK08x0FFREfIcEkJjoRQx0ETSvQkSJJ2lOxUta86tGEAACEV0Kn748aN05IlSzRy5EhNnjxZWVlZslqPPULQt2/fk1pveXm5evfurZtvvlljxoypd56RI0dqzpw5/sdOp7PO9Ouvv14HDhzQokWL5PF49POf/1yTJ0/WvHnzJEklJSUaPny4hg0bphdffFHffvutbr75ZiUkJGjy5MknlRcAgObsYGWBiu3FkiRLkVVGRvO+nR5OTYw3WtG2aJVXl2t3WY46c60+ALRaARX9iy66yP/vRYsWHTM90FH3R40apVGjRh13HqfTqfT09Hqnbd68WQsXLtTq1at13nnnSZL+8pe/aPTo0frDH/6gzMxMzZ07V263W7Nnz5bD4dDZZ5+t7Oxs/elPf6LoAwDChmmaWnNwjSRp6btLdVn/S0Oc6ORF2CM1/dwZmn7Pb+UYxgCCJ2LIUJf4M5V9aL22Fm2j6ANAKxZQ0T/yiPrp9sUXXyg1NVWJiYm69NJL9cQTTyg5OVmStGLFCiUkJPhLviQNGzZMFotFq1at0tVXX60VK1Zo8ODBcjj+t8MwYsQI/f73v9fhw4frvYOAy+WSy+XyPy4pKWnCVwgAwKnbUbpTBVWHZDEt+uest3XZP1pe0TcMo+YOAdU1/8aJdY7vrPWHNjAoHwC0cgEV/YkTJwY7R6OMHDlSY8aMUceOHbV9+3Y99NBDGjVqlFasWCGr1arc3FylpqbWWcZmsykpKUm5ubmSpNzcXHXs2LHOPGlpaf5p9RX9mTNnasaMGU30qgAACC6Pz6NvDmZLklLcySo+WBTSPDh9omyRyoppp5yyPdpavE3np5534oUAAGEnoKJ/pLKyMu3Zs0eSlJWVpZiYmFMO1ZBrr73W/++ePXuqV69e6ty5s7744gtddtllTbbdBx98UPfee6//cUlJibKysppsewAAnIqNhd+p0lupWHuMksuSQh0nYO5qt97Z9U9pcM2HF2icLvFnKqdsj3aU7FSflHNls5zy7h4AoIUJaNR9SVq9erWGDh2qxMREnXPOOTrnnHP8p9OvWbMmmBkb1KlTJ6WkpGjbtprbyKSnpys/P7/OPNXV1SosLPRf15+enq68vLw689Q+bujaf6fTqbi4uDpfAAA0R6XuUm06vFmS1K9NP1kC/1Mfcl5ftdYdWiedJflMX6jjtBgZURmKtkXL7XNrd1lOqOMAAEIgoL/+q1at0uDBg7Vu3TrdcsstmjVrlmbNmqVbbrlF69at0+DBg/X1118HO+sx9u7dq0OHDikjI0OSNGjQIBUVFWnt2rX+eT777DP5fD4NGDDAP8/SpUvl8fzvyMCiRYvUtWvXek/bBwCgJVl7cJ18pk8ZUelqF9021HEQAoZRMyifJG0t2hriNACAUAjoXK6HH35Ybdu21ZdffnnMUfDp06frwgsv1MMPP1zviPzHU1ZW5j86L0k7d+5Udna2kpKSlJSUpBkzZmjs2LFKT0/X9u3bdf/99+vMM8/UiBEjJEndu3fXyJEjdeutt+rFF1+Ux+PRnXfeqWuvvVaZmZmSpPHjx2vGjBmaNGmSHnjgAW3cuFHPPvusZs2aFchbAQBAs7GvfL/2lO+VIUPntenHAHat2Jn+QfkKdNhVpEQG5QOAViXgI/q/+MUv6j3VPS0tTZMnT9bKlStPer1r1qxRnz591KdPH0nSvffeqz59+mjatGmyWq3asGGDrrzySp111lmaNGmS+vXrp2XLlsnpdPrXMXfuXHXr1k2XXXaZRo8erYsuukh///vf/dPj4+P1ySefaOfOnerXr5/uu+8+TZs2jVvrAQBaNK/Pq9X5qyVJ3RK6Mtp6Kxf530H5JGlr8bYTzA0ACDcBHdG3WCyqrq5ucLrX65XFcvKfIQwZMkSmaTY4/eOPPz7hOpKSkjRv3rzjztOrVy8tW7bspPMBANBcfXd4k0o9ZYq0RqpXcq9Qx0Ez0CW+y38H5duhPim9ZbfYQx0JAHCaBHRE/4ILLtDzzz+v3bt3HzMtJydHL7zwgi688MJTDgcAAE6s1F2qjYXfSZLOS+0rh5VCBykjKl1x9lh5fB7tKNkZ6jgAgNMooCP6Tz31lAYPHqxu3brp6quv1llnnSVJ2rJli/7973/LZrNp5syZQQ0KAACOZZqmVh9cI6/pVXpUujrEdAh1JDQThmGoa0JXrT64Rt8XbdFZ8V0YtwEAWomAin6fPn20atUqPfzww/rggw9UUVEhSYqKitLIkSP1xBNPqEePHkENCgAAjrW3fK/2le+XRRb1Tz0/rIpchD1SD/V6WE/d/6QcwxyhjtMidY7vpOxD2Spxl+hARa4yozNCHQkAcBoEVPQlqUePHnrvvffk8/l08OBBSVKbNm0CujYfAACcvGpftVbn19xStkdSd8U74kKcKLgMw1CMPUaqUlh9gHE62S12dY7rrO+Ltuj7oi0UfQBoJU65lVssFqWlpSktLY2SDwDAabT+0AaVV5cr2halc5LOCXUcNFNdE2ousdxXvk+l7tIQpwEAnA6NOqL/2GOPyTAMPfzww7JYLHrsscdOuIxhGHr00UdPOSAAAOEuJydHBQUFJ7VMpaVSOyJ3SYaUXJqkb7M31Dvf5s2bg5AwNNzVbv0759/SBZLH5wl1nBYrzhGnzKhM7a/Yry1FP+i81H6hjgQAaGKNKvrTp0+XYRh64IEH5HA4NH369BMuQ9EHAODEcnJy1L17d/94N41hsVr027dnqOM5HbXyoxW68d7nT7hMWVnLO5Lr9VVr1cGVUg/JZ/pCHadF65Z4lvZX7Ne2ku3qndKLW+0BQJhrVNH3+XzHfQwAAAJTUFCgiooKPfm3p9SpS6dGLeON9cmX4JO80kXnXqSLP724wXmXLV6mF2Y+rypXVbAiowXKjMpUrD1WpZ5S7SjZ6T+dHwAQngIejA8AAARPpy6d1L139xPO5/a6taX4B0lSu7i2SmqTdNz5d27l/umovdXeWVpzcC232gOAViCg0fOsVqvmzZvX4PS33npLVqs14FAAAOBYpmlqb/k+mTIVbYtWoiMx1JHQgnSO6yy7xaYSd4n2lu8LdRwAQBMKqOibpnnc6V6vl0+JAQAIsiJ3kcqqy2TIULvotvytxUlxWO06K77mlP2NhRtPuD8HAGi5Ar4fXkM7FyUlJfr444+VkpIScCgAAFBXta9a+ysOSJLSIlPltDpDnAgtUffEbrIaVhVUHVJeZV6o4wAAmkiji/6MGTNktVpltVplGIYmTJjgf3zkV2Jiol5//XVde+21TZkbAIBW5UDFAXlNryKsTrWJaBPqOGihIm2R6hxXM+jjxsLvQpwGANBUGj0YX//+/XXHHXfINE298MIL+tGPfqSzzqo7YqthGIqOjla/fv00ZsyYoIcFAKA1KvWU6rC7SJLULrpdqzll32mL0K/PuV/PPPK07MO4HVywnJ3UQ1uLt+lARa4OVR1SckRyqCMBAIKs0UV/1KhRGjVqlCSpvLxct912mwYMGNBkwQAAQM394/eV75ckJTuTFWWLCnGi08disSjRmSiVSRYj4KsNcZQYe4w6xp6hHaU7tbHwO12SOTjUkQAAQRbQ7fXmzJkT7BwAAKAeeZV5cvvcslvsSo9KC3UchImzk87WjtKdyinbo2JXseKd8aGOBAAIooCKfq29e/fqm2++UXFxsXw+3zHTb7zxxlNZPQAArVpldaUOVhVIktpGZcpqtK5b13qqPVqwd77Uv2YwQgRPgjNeWdHttKd8rzYe3qQL0weFOhIAIIgCKvpVVVWaOHGi3n33Xfl8PhmG4b9Fy5HXDVL0AQAIjGma/nudxzviFeeIC3Gi06/a59GyvGVSL8lrekMdJ+yck3S29pTv1c6Sneqd3FMx9phQRwIABElAF7w99NBD+te//qUnn3xSX3zxhUzT1KuvvqpPPvlEo0aNUu/evbV+/fpgZwUAoNUocB1SpbdSVsOizKiMUMdBGEqJTFFGVLpMmVp/aEOo4wAAgiigov/OO+/o5z//uR544AGdffbZkqS2bdtq2LBh+vDDD5WQkKDnn38+qEEBAGgt3F63cityJUnpkRmyWxhxHk3j3JRzJUk7SnbqsOtwaMMAAIImoKKfn5+v/v37S5IiIyMl1YzEX2vs2LH617/+FYR4AAC0LqZpal/FPpkyFW2LVpIzMdSREMZSIpLVIaa9JOmbguzQhgEABE1ART8tLU2HDh2SJEVFRSkxMVFbtmzxTy8pKVFVVVVwEgIA0IoUuYtV6imTIUNto9vWGfsGaArnpvSWIUP7yvcrryIv1HEAAEEQUNEfMGCAvvzyS//jK664Qs8884zmzp2r119/XbNmzdLAgQODFhIAgNag2let/RX7JUmpkamKsDpDnAitQZwjTl3iz5QkrSvI9g+wDABouQIadf+uu+7SP//5T7lcLjmdTj3++ONasWKFbrjhBklS586d9dxzzwU1KAAA4e5ARa68plcRVqfaRKSEOg5amM2bNwe+sGHKiDJUUFWgJRuWKM5b9y4PKSkpat++/SkmBACcLgEV/YsuukgXXXSR/3FWVpY2b96sb7/9VlarVd26dZPNFtCqAQBolXxOnw67awZDaxvVVhYjoJPuworTFqG7e9yjZx/7s+zDGJCwIQV5BZIhTZgw4ZTWM/aecbrq9p9o1f6v9dAVD8rn9fmnRUVFafPmzZR9AGghAmrjxcXFio+Pr/OcxWJR7969gxIKAIDWxGq3yptYU6qSnUmKtkeHOFHzYLFYlBaZJhWJDz6Oo7SkVDKlX8+8X33P7xvwekzDVLXXq8zObfX6l2/IUl7znu/YukMP3/6QCgoKKPoA0EIEVPRTU1M1cuRIXXPNNbryyisVExMT7FwAALQao34+WrJLNsOm9Mj0UMdBC9W+U5a69+5+SusoqCrQ/ooDUrKhLp26yGbhDE0AaIkC+nj83nvv1XfffacJEyYoNTVV48aN0z//+U9VVlYGOx8AAGHNbbj1kylXS5IyotJltVhDnKj58FR79On+T6W+NQMVouklO5PltDrlNb3Kq2QEfgBoqQIq+jNnztS2bdu0atUq3XHHHVqzZo2uueYapaam6rrrrtP7778vt9sd7KwAAIQV0zR1wJkrR4RDRpWhBEdCqCM1K9U+jz47sFjqK3lNb6jjtAqGYahtVKYk6ZCrUBXVHMQBgJbolC54O//88/WHP/xBu3bt0ldffaVJkyZp2bJlGjt2rNLS0oKVEQCAsLSnbI/KbOXyuD2yHrbIMIxQRwIUY49RgqNmLKb95ftkitvtAUBLE7SRbQYNGqQpU6bo1ltvVUxMjEpKSoK1agAAwo7H59Hqg2slSfNf/khGNSUfzUdGVIYssqjCWykzmqIPAC3NKRf9nTt36ne/+5369u2rbt266YknntCAAQP097///aTXtXTpUl1xxRXKzMyUYRh6//33/dM8Ho8eeOAB9ezZU9HR0crMzNSNN96o/fv311nHGWecIcMw6nz97ne/qzPPhg0bdPHFFysiIkJZWVl6+umnA3rtAAAEav2hDaqorpDdZ9cHL/471HGAOuwWu9IiUyVJ3nifouO5EwQAtCQBDaW6Z88evf3223rrrbe0du1aGYahiy++WM8//7zGjh2rNm3aBBSmvLxcvXv31s0336wxY8bUmVZRUaF169bp0UcfVe/evXX48GHdfffduvLKK7VmzZo68z722GO69dZb/Y9jY2P9/y4pKdHw4cM1bNgwvfjii/r222918803KyEhQZMnTw4oNwAAJ6PQdVjfH94iScpwpcvj8oQ4EXCslIgUFboPyyWXxt3z01DHAQCchICKfocOHWQYhgYOHKhZs2bppz/9qTIyMk45zKhRozRq1Kh6p8XHx2vRokV1nvvrX/+q/v37Kycnp859XWNjY5WeXv/tiebOnSu3263Zs2fL4XDo7LPPVnZ2tv70pz9R9AEATc40TX2d97VMmeoQ014xZRwpRfNUOzDfjtKdGnrtpaqoqgh1JABAIwV06v4zzzzjH4DvrrvuCkrJD0RxcbEMw1BCQkKd53/3u98pOTlZffr00TPPPKPq6v/dkmfFihUaPHiwHA6H/7kRI0Zoy5YtOnz4cL3bcblcKikpqfMFAEAgthVv18GqAtkMm85r0y/UcYDjirHHyCgzZLFYtN+Zy90PAKCFOOmiX1FRoXnz5umjjz5qijyNVlVVpQceeEDXXXed4uLi/M/fddddevPNN/X555/rF7/4hZ566indf//9/um5ubnH3BGg9nFubm6925o5c6bi4+P9X1lZWU3wigAA4a6yukrrCr6RJJ2b0ltR9qgQJ2reHDan7uh2h/R+zTXjCA1rsUXFBcVyWV36rnBTqOMAABrhpIt+VFSUdu7cGdJbAHk8Hv3sZz+TaZr629/+VmfavffeqyFDhqhXr1667bbb9Mc//lF/+ctf5HK5At7egw8+qOLiYv/Xnj17TvUlAABaoXUF6+T2uZXoTFTXhLNCHafZs1qsahedJRVIFiNoNwrCSTJ8ht548nVJ0reFG1XsLg5xIgDAiQT0V3PkyJH6+OOPg52lUWpL/u7du7Vo0aI6R/PrM2DAAFVXV2vXrl2SpPT0dOXl5dWZp/ZxQ9f1O51OxcXF1fkCAOBk5FXkaUfJTknSgNT+FFe0KKvmr1RMdbR8pk8r81bJNLnlHgA0ZwHtZTz66KP64YcfdMMNN+jLL7/Uvn37VFhYeMxXsNWW/K1bt+rTTz9VcnLyCZfJzs6WxWJRamrNLWIGDRqkpUuXyuP53wjHixYtUteuXZWYmBj0zAAAeE2vVuV/LUk6K76L2kSmhDhRy+Cp9mhp7lKpp1Ttqz7xAmhSGa4M2Qyb8isPamvxtlDHAQAcR0Cj7p999tmSpE2bNmnevHkNzuf1ntyALWVlZdq27X9/OHbu3Kns7GwlJSUpIyND48aN07p16/Thhx/K6/X6r6lPSkqSw+HQihUrtGrVKg0dOlSxsbFasWKFpk6dqgkTJvhL/Pjx4zVjxgxNmjRJDzzwgDZu3Khnn31Ws2bNOtm3AQCARtl8+HsVu0sUYY3QuSm9Qx2nxaj2ebRw3wJpgBgErhlwmHadm9Jbaw6u1bqCb9Qupp2ibJGhjgUAqEdARX/atGlNco3+mjVrNHToUP/je++9V5I0ceJETZ8+XR988IEk6dxzz62z3Oeff64hQ4bI6XTqzTff1PTp0+VyudSxY0dNnTrVvx6p5jZ9n3zyiaZMmaJ+/fopJSVF06ZN49Z6AIAmUeYp04ZD30qS+rXpI6fVGeJEQOC6JpylnSW7dMh1SKvzV+uSzMGhjgQAqEdARX/69OlBjlFjyJAhx73m60TXg/Xt21crV6484XZ69eqlZcuWnXQ+AABOhmma+jp/jbymV2mRaeoY2zHUkYBTYjEsGpg+QPN3L1BO2R7tKdujrBjuRgQAzU1QRgIqLi4+6dP0AQAId3vK92pf+T5ZZNGA1PNDescaIFiSnInqkdhdkvR1/mq5vZ4TLAEAON0CLvpr1qzRyJEjFRUVpeTkZC1ZskSSVFBQoKuuukpffPFFsDICANDieHwerc5fI0nqkdRd8c74ECcCgqdXck/F2mNVUV2pbwq+CXUcAMBRAir6y5cv10UXXaStW7dqwoQJ8vl8/mkpKSkqLi7W//3f/wUtJAAALc2GQ9+qorpC0bZo9Uw6J9RxgKCyWWwakNZfkvRD8VblVx4McSIAwJECKvoPPfSQunfvrk2bNumpp546ZvrQoUO1atWqUw4HAEBLdNhVpM2Hv5ck9U89TzZLQEPiAM1aRlS6Osd1kiStzFslr4/LOAGguQhoz2P16tWaOXOmnE6nysrKjpnetm1b/63vAABoTWoG4PtapkxlRbdTu5h2oY7UYjlsTt1y1q16edZLsg+zhzpOq7d58+ZjnrPJKmuUVcXuYn363WK18aQEtO6UlBS1b9/+VCMCAP4roKJvt9vrnK5/tH379ikmJibgUAAAtFTbS3Yov/KgrIZV56eeF+o4LZrVYlWn2E7SgZrR3hEaBXkFkiFNmDCh3ukXXHmhbnvmdu3x7dWEK69Xwb6Ck95GVFSUNm/eTNkHgCAJqOgPHDhQ77zzju65555jppWXl2vOnDm65JJLTjUbAAAtisvr0rqDNQOT9U7upWh7dIgTAaeutKRUMqVfz7xffc/ve8x0U6a8VV45I52a9dGzshVYT2r9O7bu0MO3P6SCggKKPgAESUBFf8aMGbrkkkt0+eWX67rrrpMkrV+/Xjt27NAf/vAHHTx4UI8++mhQgwIA0NytO/iNXD6XEhzx6p7YLdRxWjyP16MV+Suk7uL672agfacsde/dvd5pVd4q/VC8VWakqbbd2yrOEXea0wEAjhTQeXADBgzQ/PnztW3bNt14442SpPvuu0+TJ0+W1+vV/Pnz1atXr6AGBQCgOcuvPKhtJdslSQPS+nOqeRBUez36z54PpAularM61HFwHBHWCLWJaCNJ2lexXz6z4Us8AQBNL+BhgC+99FJt2bJF2dnZ2rp1q3w+nzp37qx+/frJMIxgZgQAIKRycnJUUNDwdcemTG2P3ClZpQRPvPZu3qu92tuoddc3wBnQEqVFpqrIXSSPz6P8ynylR6WHOhIAtFqnfL+fc889V+eee24QogAA0Pzk5OSoe/fuqqioaHCeq+74icbePU6lh0t1x6jbVHb42DvSnEhZWempxARCzmJYlBmVod1lOTpYVaAEZ6IirM5QxwKAVimgop+dna3Nmzf7r8+XpI8//lhPPvmkXC6Xxo8fr7vvvjtoIQEACJWCggJVVFToyb89pU5dOh0z3bSbqk6ruX48wRevl/758kmtf9niZXph5vOqclUFJS8QSnH2OMXaY1XqKdWBiv3qGNsx1JEAoFUKqOjff//9ioqK8hf9nTt36uqrr1ZycrIyMzN17733KjIyUpMnTw5qWAAAQqVTl07HDERmmqa2lWxXtbdScfZYdTizw0lfvrZz685gxgRCyjAMZUZl6IfiMpV6ylTiLlWcIzbUsQCg1QlopKD169froosu8j9+7bXXZLVa9c0332jVqlUaN26cXnzxxaCFBACgOTpYVaBKb6UshkVto9syRg0gyWl1KjkiWZJ0oOKATNMMcSIAaH0CKvrFxcVKTk72P54/f75+9KMfKSUlRZL0ox/9SNu2bQtOQgAAmqEqr0t5lXmSpMyoDNkt9hAnApqPtIhUWQ2rXD6XDrkOhToOALQ6ARX9jIwM/yjBBw4c0Nq1azV8+HD/9LKyMlks3FYIABCeTNPU3vK9MmUqxh6jREdiqCOFJbvVoRvPnCh9LNmMUx4/GKeR1WJVemTNqPt5lXmq9nF7RAA4nQL6q3nVVVfpL3/5i6qqqrRq1So5nU5dffXV/unr169Xp07HDlgEAEA4OFhVoIrqCllkUbsoTtlvKjarTd3iu0l7aoojWpYkZ6IOuQ6pylulvMo8tY1uG+pIANBqBHTY/YknntCYMWP0+uuvKz8/X6+88orS0tIkSSUlJXrnnXfqHOEHACBcVFRXKLcyV5KUGZ0hh9UR4kRA81Q7MJ8kHXIVqqqaO0sAwOkS0BH9mJgYzZ07t8Fpe/fuVVRU1CkFAwCgufGaXuWU7ZEkxdvjOGW/iXm8Hq0tWCt1kbw+b6jjIAAx9hjF2eNU4inR/ooD6hTH7fYA4HQ45QvpTdNUfn6+8vPzZZqmLBaL4uPjZbczKBEAILzsLz8gt88tu8WuttHtOGW/iVV7PXp39zvSJVK1yTXeLVVGVIYMGSqrLlOppzTUcQCgVQi46G/atEnjxo1TXFycMjIylJGRobi4OI0bN04bN24MZkYAAELOF+nTYfdhSVJWdDvZuGYcaBSn1aFkZ5Ik6UBFLrfbA4DTIKBT95ctW6ZRo0bJ5/Ppqquu0llnnSVJ2rJliz744AMtWLBACxcu1MUXXxzUsAAAhEJSepK8ST5JUpuINoqxx4Q4EdCypEamqtB9WFXeKhW5i5To5LIXAGhKARX9qVOnKjU1VUuWLFFWVladaXv27NHgwYN17733avXq1UEJCQBAqPjk053P3iVZpEhrpNIj00IdCWhxbBabUiPaKLcyT7mVeYp3xMticCtmAGgqAf2G/e6773THHXccU/IlKSsrS7fffru+++67Uw4HAECo5TrzdOa5Z0peqX1Me67LBwKUEpEiu8Uuj8+jQ1WHQh0HAMJaQEW/Q4cOcrlcDU53u931fggAAEBLsrV4mw7bi+Tz+WQttMjJrfSAgFkMi9L+e0ZMflW+qn0MsAgATSWgoj9t2jQ999xzys7OPmbaN998o7/85S+aPn36KUYDACB0CioL9HV+zSVo7z77jixVnGYMnKpER4IirBHymj7lVx0MdRwACFuNukb/rrvuOua5tLQ09evXTxdccIHOPPNMSdLWrVu1YsUKnXPOOVq5cqWuu+664KYFAOA0qKyu0pIDy+QzfYqtjtGH//cfjR83PtSxWh271aHrOo3XP16aJ9tlAQ0rhGbGMAylR6ZrV9kuHao6pBRncqgjAUBYatRfzb/+9a8NTvvqq6/01Vdf1Xnu22+/1caNG/Xss8+eWjoAAE4zr8+rpQeWqqK6QnH2WGWWZXA7sBCxWW3qmdhT/9gpWbmdYdiItcco2hat8upy5VflhzoOAISlRp2H6PP5TvrL6/U2dXYAAILKNE19lbtc+ZUHZbfYNSTzEllFwQSCqeaofs21+oWuwzJtfJAGAMHGBYcAAPzXuoJvtLssRxZZNCRzsOKd8aGO1KpVe6v17eFvpY41Z1ogfETboxVrj5EkeeN8IU4DAOHnlC5427lzpxYsWKDdu3dLqhmNf9SoUerYsWNQwgEAcLp8f3iLNh3eLEkalD5Q6VHpIU4Ej9etf+yYJ10mVZuM0B5u0iLTVerZJjPKVNsu7UIdBwDCSsBH9O+77z516dJFd955p5555hk988wzuvPOO9WlSxf96le/CmidS5cu1RVXXKHMzEwZhqH333+/znTTNDVt2jRlZGQoMjJSw4YN09atW+vMU1hYqOuvv15xcXFKSEjQpEmTVFZWVmeeDRs26OKLL1ZERISysrL09NNPB5QXABAecsr2aPXBNZKkc1N6q1McH1gDTS3KFql4e5xkSGPvGhvqOAAQVgIq+n/84x81a9YsjRkzRitWrFBRUZGKioq0YsUKjRs3TrNmzdKsWbNOer3l5eXq3bu3nn/++XqnP/3003ruuef04osvatWqVYqOjtaIESNUVVXln+f666/Xd999p0WLFunDDz/U0qVLNXnyZP/0kpISDR8+XB06dNDatWv1zDPPaPr06fr73/9+8m8EAKDFO1hZoC8P1Awq2yX+TJ2TeHaIEwGtR1pUmmRK5w0/X5WWylDHAYCwEdCp+y+99JKuvPJKvf3223WeHzBggN58801VVVXp//7v/zR16tSTWu+oUaM0atSoeqeZpqk///nPeuSRR3TVVVdJkl577TWlpaXp/fff17XXXqvNmzdr4cKFWr16tc477zxJ0l/+8heNHj1af/jDH5SZmam5c+fK7XZr9uzZcjgcOvvss5Wdna0//elPdT4QAACEvxJ3qT7f/4W8pldtozPVP/V8GYYR6lhAqxFhjZBRYciMNpXvOBjqOAAQNgI6or9r1y6NGDGiwekjRozQrl27As1Ur507dyo3N1fDhg3zPxcfH68BAwZoxYoVkqQVK1YoISHBX/IladiwYbJYLFq1apV/nsGDB8vhcNTJu2XLFh0+fLjebbtcLpWUlNT5AgC0bFXVVfps3+dyeV1Kcibp4oyLZDEYoxY43azFFlV7qlVmK1deBbfbA4BgCGiPJjU1VevXr29w+vr169WmTZuAQ9UnNzdXkpSWllbn+bS0NP+03Nxcpaam1plus9mUlJRUZ5761nHkNo42c+ZMxcfH+7+ysrJO/QUBAEKm2letz/cvUamnVNG2aF3adojsFnuoYwGtkuE1tPTdJZKk7EPZMk1utwcApyqgov/Tn/5UL7/8sn73u9+pvLzc/3x5ebl+//vf6+WXX9Y111wTtJCh9uCDD6q4uNj/tWfPnlBHAgAEyGf69OWBr1RQVSCHxaHL2g1VpC0y1LGAVu3fL/xbhmkov/KgDlQcCHUcAGjxArpG//HHH1d2drYeeughTZs2TZmZmZKk/fv3q7q6WkOHDtVjjz0W1KDp6TW3OcrLy1NGRob/+by8PJ177rn+efLz657yVV1drcLCQv/y6enpysvLqzNP7ePaeY7mdDrldDqD8joAAMGXk5OjgoKCE85nylSuI0+FjsMyTEOZZRnavnH7cZfZvHlzsGLiJNmsdo3tME7vvvaObJed0h2B0cwdzitUkidRhxyFyi5Yr4yoDMbLAIBTENBfzaioKC1evFj//ve/tWDBAu3evVuSNHLkSI0ePVpXXHFF0H85d+zYUenp6Vq8eLG/2JeUlGjVqlW6/fbbJUmDBg1SUVGR1q5dq379+kmSPvvsM/l8Pg0YMMA/z8MPPyyPxyO7veY0zUWLFqlr165KTEwMamYAQNPLyclR9+7dVVFRccJ5R/58lMb/5npJ0l+mPqevF6xq9HbKykoDzojA2K129Uvpp3e3viOrxRrqOGhiKZ5kFTtLdMhVqD1le9U+lkslASBQp/Tx+FVXXeUfAT8YysrKtG3bNv/jnTt3Kjs7W0lJSWrfvr3uuecePfHEE+rSpYs6duyoRx99VJmZmfrJT34iSerevbtGjhypW2+9VS+++KI8Ho/uvPNOXXvttf6zDsaPH68ZM2Zo0qRJeuCBB7Rx40Y9++yzAd0OEAAQegUFBaqoqNCTf3tKnbp0anA+X6RP3hSfJMlSZNHU+6ZK9514/csWL9MLM59XlavqxDMDCJjNtKlbYldtLPxO2YfWq11MWwbIBIAANavz4NasWaOhQ4f6H997772SpIkTJ+qVV17R/fffr/Lyck2ePFlFRUW66KKLtHDhQkVERPiXmTt3ru68805ddtllslgsGjt2rJ577jn/9Pj4eH3yySeaMmWK+vXrp5SUFE2bNo1b6wFAC9epSyd179293mnlnnLtKN0pSUp2JiuzY+NPC965dWfQMuLkVHur9X3x91KW5PV5Qx0Hp8HZiT30Q9FWFbuLtbt0tzrGdQx1JABokZpV0R8yZMhxR1o1DEOPPfbYca//T0pK0rx58467nV69emnZsmUB5wQAtBxVXpd2le2WKVNx9jhlcu1vi+HxuvXatlelEVK1WR3qODgNHFaHeiR2V/ah9Vp/6Ft1iO3AUX0ACAC/OQEAYava59Wu0l3yml5FWSPVPiaLkg80c90SuyrCGqFST6m2l+wIdRwAaJEo+gCAsGSapnLKcuT2uWW32HVG7BkcGQRaALvFrrOTekiSvj20UV6TyzYA4GQ1ao/nueee0w8//NDUWQAACJr9FQdUVl0miyw6I6aDbJZmdbUagOM4K76LIq0RKq8u144SxskAgJPVqKI/depUrVmzxv/YarWe8Dp4AABC5VBVoQ65DkmSsmLaKdIWGeJEAE6GzWJTjyOO6vtMX4gTAUDL0qiin5iYqLy8PP/j4w2YBwBAKJV5yrWvYp8kKS0yTfGO+BAnAhCIs+K7KOK/R/W5Vh8ATk6jzmMcMmSIpk+fruzsbMXH1+wwvfbaa1q5cmWDyxiGoWeffTY4KQEAaASPz6OcshxJUrwjXqkRbUKcCECgbBabzk7qobUH1+nbQxvVOa4T42wAQCM1qui/8MILuueee/TJJ58oPz9fhmHok08+0SeffNLgMhR9AMDpZMpUTtkeVZvVirBGKCu6HSPst3A2q11XZF2p/7z5gWyXMcZCa3RWfBd9V7jJf1S/S/yZoY4EAC1Coz4WTU1N1bx583TgwAF5vV6Zpqk33nhDPp+vwS+vlxFSAQCnjy/ep/LqcllkUfuY9hz5CwN2q12DUgdJmyWrxRrqOAiB2qP6krSx8Duu1QeARgpoL2jOnDm64IILgp0FAICA9BrcW764mvFj2kW3VYTVGeJEAIKl9lr9Mk8ZI/ADQCMFdB7cxIkT/f/etGmTdu/eLUnq0KGDevToEZxkAAA0gtvw6Lanb5MkJTuTlOBMCG0gBI3X59WO0h1ShjiS24rVuVa/cKM6xXXkjB0AOIGAf0v++9//VufOndWzZ0/9+Mc/1o9//GP17NlTZ555pj744INgZgQAoF4+06e9EfsUkxgrwy1lRGWEOhKCyF3t0ss/vCRdXjPQIlovjuoDwMkJqOjPnz9fY8eOlSQ99dRTeu+99/Tee+/pqaeekmmaGjNmjBYuXBjUoAAAHO3bQxtVaa1UeUm5rAVWjvIBYcpmsensxJqzRr8t3MgZHgBwAgHtET3++OPq1auXNmzYoAceeEBXXnmlrrzySj3wwAPasGGDevbsqRkzZgQ7KwAAfvmVB/Vt4UZJ0ivTZsvwMsI+EM66JHBUHwAaK6Civ2HDBk2cOFHR0dHHTIuOjtZNN92kDRs2nHI4AADq4/Z69FXucpkyFe+J06oFq0IdCUATs3NUHwAaLaCiHxERocLCwganFxYWKiIiIuBQAAAcz+qDa1TmKVO0LVoZrvRQxwFwmnRJ6CKn1clRfQA4gYBG3b/00kv17LPPauTIkRo0aFCdaatWrdJzzz2n4cOHByUgAABH2l26WztKdsiQoQvTL9C+or2hjgQgCDZv3tyo+RLs8cpz5mvNgbUq3l4kQye+bCclJUXt27c/1YgA0GIEVPSffvppDRo0SBdddJH69++vrl27SpK2bNmir7/+Wqmpqfr9738f1KAAAFRUV2hl3teSpLOTeigtKlX7RNEHWrKCvALJkCZMmNCo+R2RTv1p8Z8Ulxyve56Yqi/fW3bCZaKiorR582bKPoBWI6Ci37FjR23YsEEzZ87UggUL9NZbb0mSOnTooLvvvlu/+c1vlJqaGtSgAIDWzTRNrcxbJbfPrSRnknon9wp1JDQxm8WukW1HaeG/Fsh6mTXUcdBESktKJVP69cz71ff8vo1axmv1ySefJj/xC90x5Y7jHtXfsXWHHr79IRUUFFD0AbQaARV9SUpNTdWsWbM0a9asYOYBAKBeO0p2al/5flkMiy5MH8St9FoBu82uwemDtfDbBbJZAt5lQQvRvlOWuvfu3qh5faZPm4u+l9fmVUa3DCU6E5s4HQC0LOwlAQCavQpPhVYfXCNJ6pXcUwnOhNAGAhBSFsOiNhFtJEl5lfkyTTPEiQCgeaHoAwCaNdM0tTJ/lTw+j5Kdyf7bayH8eX1e7S3fI6WIW6nhGMkRSbIaVrl9bhW5i0MdBwCaFYo+AKBZ21Gyw3/K/gWcst+quKtdeuH7F6SfSB6fJ9Rx0MxYDavaRKRIkvI5qg8AdbC3BABotmpO2V8rSeqd3EsJzvgQJwLQnCRHJMtqWOTyuVTMUX0A8KPoAwCaJdM0tSr/65pT9iOS1SOxcYN0AWg9rIZVKf89qp9XxVF9AKh10kW/oqJC/fr104svvtgUeQAAkCTllOVob/k+WWTRoLSBnLIPoF4pzhRZDItcXpdKPCWhjgMAzcJJ7zVFRUVp586dMoyG71cKAMCpcHld+jq/ZpT9c5LOViKj7ANogNViVYrzv0f1uVYfACQFeOr+yJEj9fHHHwc7CwAAkqS1B79RlbdKcY44nZN0dqjjAGjmUiKSZZFFVd4qlXhKQx0HAELOFshCjz76qH7605/qhhtu0C9+8Qt17NhRkZGRx8yXlJR0ygEBAC1fTk6OCgoKGjVvmbVcuyNzJEnJRYlaX7j+uPNv3rz5lPMBaNlsFpuSI5J1sOqg8ivzFGeP5exTAK1aQEX/7LNrjq5s2rRJ8+bNa3A+r9cbWCoAQNjIyclR9+7dVVFRccJ5HREOPfmfmUprn6ZP5y7Sa4+92ujtlJVxFC/c2Cx2XZpxmT77aLGsl1lDHQfNXJuIFB2qOqRKb5VKPaWKc8SFOhIAhExARX/atGl8SgoAaJSCggJVVFToyb89pU5dOh13Xm+8V744U6qWRl4yUqM+HXXC9S9bvEwvzHxeVa6qYEVGM2G32TUsc5g+W7dYNktAuyxoRWqO6ifpYFWB8irzFctRfQCtWEB/NadPnx7kGACAcNepSyd1793wLfIqqiu1rWSbJOmMhA6KS23c0bidW3cGJR+Alq9NRBsVVB1SpbdSZZ4yxTpiQx0JAEIiKPcqKi4uPm2n6Z9xxhkyDOOYrylTpkiShgwZcsy02267rc46cnJydPnllysqKkqpqan69a9/rerq6tOSHwBwLNM0tbd8ryQp3hHPKbeQJPl8PuVV5kkJks/0hToOWoDaa/UlKa+KEfgBtF4BF/01a9Zo5MiRioqKUnJyspYsWSKp5hTNq666Sl988UWwMtaxevVqHThwwP+1aNEiSdJPf/pT/zy33nprnXmefvpp/zSv16vLL79cbrdby5cv16uvvqpXXnlF06ZNa5K8AIATO1hVoCpvlayGVZlRGaGOg2bCVV2lZzf9WRoneXyeUMdBC9EmIkWGDFVUV6isujzUcQAgJAIq+suXL9dFF12krVu3asKECfL5/vcpe0pKioqLi/V///d/QQt5pDZt2ig9Pd3/9eGHH6pz58665JJL/PNERUXVmScu7n9Hhj755BNt2rRJb7zxhs4991yNGjVKjz/+uJ5//nm53e4myQwAaJjL66o5aispIypDdos9xIkAtGR2i11Jzpo7P+VX5skUR/UBtD4BFf2HHnpI3bt316ZNm/TUU08dM33o0KFatWrVKYc7EbfbrTfeeEM333xzncFW5s6dq5SUFJ1zzjl68MEH64z0vGLFCvXs2VNpaWn+50aMGKGSkhJ999139W7H5XKppKSkzhcA4NTVnLK/T6ZMxdiilehICHUkAGEgNbKNDBkqr66Q6aToA2h9AhqMb/Xq1Zo5c6acTqfKysqOmd62bVvl5uaecrgTef/991VUVKSbbrrJ/9z48ePVoUMHZWZmasOGDXrggQe0ZcsW/etf/5Ik5ebm1in5kvyPG8o8c+ZMzZgxo2leBAC0Yofdh1VeXS5DhtpGt2WEbABBUXNUP1GHXIXyxTG+A4DWJ6Cib7fb65yuf7R9+/YpJiYm4FCN9f/+3//TqFGjlJmZ6X9u8uTJ/n/37NlTGRkZuuyyy7R9+3Z17tw5oO08+OCDuvfee/2PS0pKlJWVFXhwAIA8Po8OVByQJKVHpslpdYY4EYBw0iYyVYWuwzIjTHUf0PAdPwAgHAV06v7AgQP1zjvv1DutvLxcc+bMqXPNfFPYvXu3Pv30U91yyy3HnW/AgAGSpG3bam7ZlJ6erry8vDrz1D5OT0+vdx1Op1NxcXF1vgAAp2Zf+X55TZ8irRFKiUgJdRwAYcZxxLX6Y+4ax7X6AFqVgIr+jBkztGbNGl1++eVasGCBJGn9+vV6+eWX1a9fPx08eFCPPvpoUIMebc6cOUpNTdXll19+3Pmys7MlSRkZNaM4Dxo0SN9++63y8/P98yxatEhxcXHq0aNHk+UFAPxPsbtYJZ6a8U7aRbfjlH0ATSI1so1kSl3P66pya8WJFwCAMBFQ0R8wYIDmz5+vbdu26cYbb5Qk3XfffZo8ebK8Xq/mz5+vXr16BTXokXw+n+bMmaOJEyfKZvvf1Qfbt2/X448/rrVr12rXrl364IMPdOONN2rw4MH+PMOHD1ePHj10ww03aP369fr444/1yCOPaMqUKXI6OW0UAJpatc+rfeX7JUmpEW0UaYsMcSI0VzaLXRenXSxtkKyGNdRx0ALZLXZZymo+SMx3HJRpclQfQOsQ0DX6knTppZdqy5Yt+uabb7Rt2zb5fD517txZ/fr1a/IjM59++qlycnJ0880313ne4XDo008/1Z///GeVl5crKytLY8eO1SOPPOKfx2q16sMPP9Ttt9+uQYMGKTo6WhMnTtRjjz3WpJkBADUOVBxQtVktp8Wp1MjUUMdBM2a32TWq3Wgt+3qZbJaAd1nQyllKLKqyV0oR0oGKXGVGZ4Q6EgA0uVP+q9mnTx/16dMnGFkabfjw4fV+IpuVlaUlS5accPkOHTpo/vz5TRENAHAcpZ5SHXYfliS1i24rixHQiWUA0GiGz9Bnby7WyJtGaf2hDcqISudyIQBhL+A9LJfLpb/+9a8aPXq0evTooR49emj06NH661//qqqqqmBmBACEAdMwtbd8nyQp2ZmsaHt0iBOhufP5fDrsOizFSD6TW6QhcB+99KEM01BBVYH2V+wPdRwAaHIBFf29e/fq3HPP1V133aX169erTZs2atOmjdavX6+77rpL5557rvbu3RvsrACAFswX75PH55HdYld6VFqo46AFcFVX6ZmNT0vX1tyOEQhUcUGxkjyJkqT1BRu4Vh9A2Auo6E+ZMkW7d+/W22+/rX379mnJkiVasmSJ9u3bp7feeks5OTmaMmVKsLMCAFqozr07yxdTs2PdLqotA6sBOO1SPMmyGTYdchVqTxkHpACEt4CK/uLFizV16lSNGzfumGk//elPdffdd2vx4sWnHA4A0PL55NOkJ2+VDCnRkaBYR2yoIwFohWymTd0Tu0mSsg+t53IQAGEtoKIfGxur1NSGR0pOT09XbCw7cgAAqcBxSO26tJO8UkYUo10DCJ0eid3lsDhU7C7WztJdoY4DAE0moKL/85//XK+88ooqKiqOmVZWVqY5c+Zo0qRJpxwOANCyHXYdVoG9QJJkPWzhFmkAQsphdeicpB6Saq7V95reECcCgKbRqD2uf/3rX3Ue9+nTRx999JG6deumiRMn6swzz5Qkbd26Va+99pqSkpLUq1ev4KcFALQYPtOnFbmrZBrS2k/XaEDXAaGOBADqmtBVmw9/r/Lqcm0r3q6uCWeFOhIABF2jiv64ceNkGIZ/hNIj//3kk08eM//evXt13XXX6Wc/+1kQowIAWpLNh7/XIdchWUyLXp3xigbOGxjqSAAgm8Wmnsk99XX+an176Ft1juvE2UYAwk6jfqt9/vnnTZ0DABBGDruKlH1ovSQp3ZWmovyi0AZCi2S12DSgzUCtWrJSlssCutoQqNeZ8Z216fBmlXnK9H3RFp2TdHaoIwFAUDWq6F9yySVNnQMAECa8pldf5S6Xz/SpbXSm4sviQh0JLZTD5tBV7a/SquUrZb/bHuo4CCNWw6reyT31Ve4KfVe4SV3iz5TT6gx1LAAIGj4eBwAE1YZD3+qw67CcFqcGpQ2UISPUkQDgGGfEnqEER7zcPrc2Fn4X6jgAEFQBX5D05Zdfavbs2dqxY4cOHz7sv2a/lmEYWr9+/SkHBAC0HAcrC/Rd4SZJ0oC0/oq0RYY4EVoy0zRV5imTInTMfgZwqiyGRX3b9NFn+77Q/2/vvuOjqPP/gb9me0k2vTcIJQRpUsSAIgo/iigW7lAERMXGBaV8DxEbKIeIlTvFdl9FUTmV74mneCKINJUiTSkh0gOkbtom2Wydz++PQCQQyCaZsCmv5z32SGZnPu/3gDOz7535fD4HSzKREtwZAdoAf6dFRKSIBhX6r776KmbNmgWDwYCUlBSEhoYqnRcREbUwHtmDn3J/hoBA+8B2SApM9HdK1MI53JV4/rcFwATAJbv8nQ61QrGmWESbopFrz8Vu66+4Nmagv1MiIlJEgwr9l156CQMHDsTXX3+NoKAgpXMiIqIWaGfBLpS5y2DSGNEvsq+/0yEiqpMkSegTfiW+yfoWx8uOo2tIF4QZwvydFhFRozWoj77dbsf48eNZ5BMREQAgqywLv5ceAgCkRaVxUCsiajFCDaFIDmwPANhZsJvdRIioVWhQoX/99ddj7969SudCREQtULm7HFvytgEAuoakItYc4+eMiIjqp1d4T6gkFfIq83C64rS/0yEiarQGFfqvv/461q1bh5dffhlFRUVK50RERC2ELGT8mPMTXLIL4YYwXBney98pERHVm1lrRmpwFwDALuseyEL2c0ZERI3ToEI/ISEBDz30EB5//HFERETAbDbDYrHUePGxfiKi1m+P9VcUOKzQqrS4NuYaqCTO2kpELVO30CugV+lR6irFodLD/k6HiKhRGjQY3zPPPIMFCxYgLi4Offv2ZVFPRNQGZVfkYH9x1VR6aVFXc1oqImrWMjIy6lwnRBuMXH0edubtQunRUmig9rn98PBwJCZythEiah4aVOi//fbbGDVqFL788kuoVLx7Q0TU1lS4K/Bj7k8AgM5BnTiVHjUJtUqD3mG9sWvLLqiG8PMGNYw1zwpIwIQJE+pcV6VW4W9fLkB85wT844vX8cmCj3yOYzKZkJGRwWKfiJqFBhX6LpcLo0aNYpFPRNQGeWQPNmRvgtPrRIg+BH0ievs7JWqldBod/tTuz9i1aBe06Vp/p0MtVJmtDBDArIWPoXe/us9Xsl6GFzKGTxyOUf/vRkgeqc5tjh46iienPAGr1cpCn4iahQYV+jfddBM2b96Mhx56SOl8iIioGRNCYGveNhQ5i6BX6zE4dhA0qgZdSoiILqvE5ASk9kz1ad3jZSdgc9tgSDCifWA7SFLdxT4RUXPSoFvyc+fOxYEDB/CXv/wFO3fuREFBAYqKii54ERFR65JRchDHyo5DgoRBMdeyXz41KSEEXF4XoAHnNqfLKsYUAwkSyj3lsLnL/J0OEVG9Neg2TEpKCgBgz549eOeddy66ntfrbVhWRETU7GRX5GBXwW4AQN+IPog2Rfk5I2rtHO5KzNszF7gHcMkuf6dDbYherUO4IRwFjgLk2HMQqA3grCJE1KI0eNR9PsJERNR22Fw2bM75EQICHSzJSAnu7O+UiIiaVKQxAsXOYrhkF6wOKyKNkf5OiYjIZw0q9OfNm6dwGkRE1FxVeirx/akf4JJdCDeEoX/kVfyyl4haPbWkRowpGicrTiGvMh/BumDo1Dp/p0VE5BM+g0RERBfl8rrxw+n1qPBUIFAbiMGxg6FW+T6vNBFRSxasC4ZZY4aAQLY9x9/pEBH5rEF39J977rk615EkCU8//XRDmiciombAK7zYmLMJRc5i6NV6DIm7HkaNwd9pERFdNpIkIc4Ui99th2Bz22Bz2WDRWfydFhFRnRR/dF+SJAghWOgTEbVgQghsyd2KXHsuNJIGQ+KuR6Au0N9pERFddgaNARGGcBQ4rDhtz0YAB+YjohagQYW+LMu1Ljtx4gSWLFmCTZs24dtvv210ckRE1PSysrJgtVqrfxcQyNXloUhXDAggtjIGJw6cwAmcaFD7GRkZSqVKROQXkcZIlLhK4ZbdyK/MR7Qp2t8pERFdUoMK/dqoVCq0b98eL7/8MsaPH49HHnkEy5cvV6p5IiJqAllZWUhNTYXdbq9eNm72XRh5340AgHcffwc/frlZkVjl5ZyLmupHJanRLbgb9u3aB9UNvINK/qOW1Ig1xeBEeRYKHFYE60NgUOv9nRYR0UUpVuifa9CgQZg9e7bi7c6bNw/PPvtsjWUpKSk4ePAgAMDhcOB//ud/8Omnn8LpdGL48OF48803ERX1x1zPWVlZmDJlCtavX4+AgABMmjQJCxcuhEbTJH8VRETNmtVqhd1ux4K3nkf7Tu0hB8mQLQIAoC5SIX1qOtKnpjcqxuZ1m/HmwiVwOB1KpExtiF6rx10dxuOJl+dA+5DW3+lQG2fRWhCoDUSZuwynK04jObA9ZyAhomarSarbHTt2QKVqmm/er7jiCnz//ffVv59boM+YMQPffPMNVqxYgaCgIEydOhW33347fvrpJwCA1+vFqFGjEB0djZ9//hk5OTm4++67odVq8fzzzzdJvkRELUFyp2SEdApBvqMAABBrikV4aJgibR87dEyRdoiI/EmSJMSaYvF76e+o8FSg2FWMUH2ov9MiIqpVgwr9ZcuW1bq8pKQEmzZtwhdffIH777+/UYldjEajQXT0hf2iSktL8d5772H58uW44YYbAABLly5Famoqtm7diquvvhpr1qzBgQMH8P333yMqKgq9evXC/PnzMXv2bMybNw86HedGJaK2yWvxnlPkxyDcoEyRT0TUmujVOkQZo5BbmYscey4CtYHQqvi0CRE1Pw0q9O+5556LvhceHo7HH38czzzzTENzuqRDhw4hNjYWBoMBaWlpWLhwIRITE7Fz50643W4MHTq0et0uXbogMTERW7ZswdVXX40tW7age/fuNR7lHz58OKZMmYL9+/fjyiuvrDWm0+mE0+ms/t1mszXJvhERXW4CAnfNGQ85qOpx/RhjNMIN4X7OiqhKpcuOJ3bOAe4HnF5n3RsQXQYRhnCUuErg8DqQbc9BUkCiv1MiIrpAgwr9Y8cufAxTkiSEhIQgMLDppl/q378/PvjgA6SkpCAnJwfPPvssrr32Wuzbtw+5ubnQ6XQIDg6usU1UVBRyc3MBALm5uTWK/LPvn33vYhYuXHjB2ABERC2dLGRk63Mw4p6RAM7eyWeRT0R0KZIkId4cj8O2wyh1lcLm4g0gImp+GlToJyUlKZ2HT0aOHFn9c48ePdC/f38kJSXh888/h9FobLK4c+bMwcyZM6t/t9lsSEhIaLJ4RERNzSu8+CnnZ5RoSyF7ZWhLNAgPZZFPROQLk8aICEM4ChxWnLZnQ0jC3ykREdXQoueqCQ4ORufOnXH48GFER0fD5XKhpKSkxjp5eXnVffqjo6ORl5d3wftn37sYvV4Pi8VS40VE1FK5ZTc2nN6IE+VZkATwxrR/QGVv0ZcDIqLLLsoYBZ1KB7fshhwk+zsdIqIafL6j36NHj3o1LEkSfv3113onVB/l5eU4cuQIJk6ciD59+kCr1WLdunUYM2YMACAzMxNZWVlIS0sDAKSlpWHBggXIz89HZGQkAGDt2rWwWCzo2rVrk+ZKRNQcVHoq8cPpDShyFkEtqRFfGYsda3cAys+ISkTUqqkkFeLMcThWdgxyoEBKvy7+TomIqJrPhX5oaKhPc4Xm5uYiMzOzSeYV/etf/4qbb74ZSUlJyM7Oxty5c6FWqzFu3DgEBQVh8uTJmDlzJkJDQ2GxWPDII48gLS0NV199NQBg2LBh6Nq1KyZOnIgXX3wRubm5eOqpp5Ceng69Xq94vkREzUmpqxTrTq1HhacCerUe18cOxsmMLH+nRUTUYgVqAxCqD0GRsxgPLHwQXvDOPhE1Dz4X+hs2bLjk+7m5uVi0aBHeeecdqNVqTJw4sbG5XeDUqVMYN24cCgsLERERgWuuuQZbt25FREQEAOC1116DSqXCmDFj4HQ6MXz4cLz55pvV26vVaqxatQpTpkxBWloazGYzJk2ahOeee07xXImImpM8ez42ZG+ES3YhUBuIIXHXI1AXiJNgoU9E1BgxphgUVRQjMiESea58f6dDRASggYPxnSsvLw8vvPAC3n33XbjdbkyYMAFPPvkkOnTooER+NXz66aeXfN9gMGDJkiVYsmTJRddJSkrCf//7X6VTIyJqtk6UncCPuT9DFjLCDeG4PvY6GDQGf6dFVCeVpEaKJQWZ+zKhatnDClErppbUUBep4I2UUawrRo49FzGmi4/9RER0OTT4qpmbm4sZM2YgOTkZS5YswR133IGDBw/i/fffb5Iin4iI6kcIgQPFGdiU8yNkISMhIAH/L34Ii3xqMfRaPSZ1ugdYA2jVWn+nQ3RRKqcK33+yFgCwJXcLXF63nzMiorau3oV+bm4upk+fjg4dOmDJkiW48847kZmZiffffx/JyclNkSMREdWTLGTsKNiJnQW7AABdglMwKOYaaFSNfpCLiIhq8dnLn0Ira1HhsWNnwU5/p0NEbZzPn/hycnLwwgsv4J///Cc8Hg/uvvtuPPnkk2jfvn1T5kdE1OZlZWXBarX6vL4MGacM2SjTlAEAopyRUJ2SsOfUngvWzcjIUCpNIqI2zWl3Is4Ri+OmEzhsO4L4gHgkBMT7Oy0iaqN8LvQ7dOgAp9OJXr164YknnkD79u1RXFyM4uLii27Tu3dvRZIkImqrsrKykJqaCrvd7tP6odGhmLZkBtp3aw+3y413Hnsb27/dVud25eVljU2VSHGVLjvm7n4GmAQ4vU5/p0NUJ7NsQmpIF2QUH8SWvK0IM4yCSWP0d1pE1Ab5XOg7HA4AwO7duzF27NhLriuEgCRJ8Hq9jcuOiKiNs1qtsNvtWPDW80judOnuUbJOwBvuBdQAvICh2IAZ/zMD+J+Lb7N53Wa8uXAJHE6HsokTKcQtuwF2z6cW5MqwXsi156HYWYyfc3/GkLgbmmTaaSKiS/G50F+6dGlT5kFERJeQ3CkZqT1TL/p+oaMI2fZsAIBBbUC7oCToInR1tnvs0DHFciQiIkCtUuPa6IH4Jutb5NhzkVFyEF1DLn7+JiJqCj4X+pMmTWrKPIiIqAGEEMi2Z6PQWQQACNIFIcEcD5XEqciIiPwlSB+EvhF9sC1/O3YX7EG0MQqhhlB/p0VEbQg/CRIRtVAe2YOjZceqi/woYxQSzQks8omImoFOQR2RYI6HDBmbc36CW/b4OyUiakP4aZCIqAWq9FTikO0wKjwVUEGFpIAkRBkj2Q+UiKiZkCQJadFXw6g2wua2YXv+dggh/J0WEbURLPSJiFqYUlcpDtuOwC27oVPp0NHSAUE6i7/TIiKi8+jVelwTMxASJBy1HcOh0sP+TomI2ggW+kRELYQQArn2PJwoz4KAQIAmAB0tHWDQGPydGlGTkCQV2ge0B3IACXxahVqmaFMUrgzvCQD4pWAHrI5CP2dERG0BC30iohZASAInyrOQ78gHAITrw9A+sB00Kp/HVCVqcQxaAx5IeRD4BtCp655Fgqi56hrStaq/vpCxMXsTHF5OaUpETYuFPhFRMxcRHwFPpBc2tw0SJMSb4xFrjmV/fCKiFkKSJAyITkOgNhB2jx0/5vwEWcj+TouIWjEW+kREzVi5ugLP/t9zgA7QSBp0sCQjVB/i77SIiKiedGodrou9FmpJjRx7Ln4t/M3fKRFRK8ZCn4ioGRJCIKP4IE4YshAQEgjJWTVVk0lj8ndqRJdNpcuOv/36N2A84PQ6/Z0OUaOF6ENwdVR/AMC+ov04ajvq54yIqLVioU9E1Mx4ZS+25G3DjoKdgAT8+OVmqPPV0Kq0/k6N6LKzeyoAo7+zIFJOsqU9rgjpCgDYkrcNefZ8P2dERK0RC30iombE7qnE2lPf44jtCCRIiHJG4t3Z73DEcSKiVuTK8F5IDEioHpzP5irzd0pE1MpwuGYiombC6ijExuyNsHsqoVPpcG3MNcjNzPF3WkRE5KOMjAyf1zXDBIPRAAcc+PboaiTb20EN9UXXDw8PR2JiohJpElEbwEKfiKgZOGo7hi15WyELGUE6CwbHXgeLzoJcsNAnImrurHlWQAImTJhQr+2CIoIx7/N5CIsNxxf7VuKVB16G2+WudV2TyYSMjAwW+0TkExb6RER+JAsZu617cKC46i5QvDkOA6MHQqdmf3wiopaizFYGCGDWwsfQu1/vem0rVAIe2YuuV1+B97d9AHWh6oLuWkcPHcWTU56A1WploU9EPmGhT0TkJy6vC5tzfkS2vequfbfQK9ArrCckif3xiYhaosTkBKT2TK33duXuchwrOw5hEggMDkS8OZ7XAiJqFBb6RESNlJWVBavVWq9tnJITWcZTcKlckISEOGcsRJaM3Vm7a6xXn/6eRK2NJKkQZ4rD6ROnOSAltWoB2gAkBiTiRPkJFLtKoJLUiDXFsNgnogZjoU9E1AhZWVlITU2F3W73eZue1/XClFf+ApPKBOtpK/6e/hpOZJy45Dbl5RyRmdoeg9aA9NSpeOIfc6C7S+fvdIiaVJDOggRzPE5WnEKhsxBqSY1oU5S/0yKiFoqFPhFRI1itVtjtdix463kkd0q+5LoCAnKggBwkAxIgOYBoROGF1xdddJvN6zbjzYVL4HA6lE6diIiamRB9CLxCRrY9G/mOfEgSEGVksU9E9cdCn4hIAcmdki/ZL1MWMk5XnEaxqwQAEKoPRWxIDFSxqku2e+zQMSXTJCKiZi7cEAZZyMitzEVeZT6EEBAQ/k6LiFoYFvpERE3MI3twvPwE7J6qx/tjTbEIN4T5OSui5q/SVYkX9y4C7qgavJKorYg0RkACkFOZi3xHAVRB7KtPRPXDQp+IqAk5PA4cKz8Ot+yGSlIhKSARgdpAf6dF1EIIlLhKgEDwjia1ORHGCEiShGx7DmSLwF1zxvM4ICKfXfqZUSIiajCby4bDtiNwy27oVDp0tHRgkU9ERD4LN4QjzhQLABhxz0hk63MhC9nPWRFRS8BCn4hIYUIIFDisOF5+AjJkmDVmdLR0gEFt8HdqRETUwoQZwqAuUkH2yijRlmBT9mZ4Za+/0yKiZo6FPhGRgoQQOG3PRo49B0DVCMrtA9tBo2JPKSIiahhVhQpvTPsHJCHhZMUpfH/6B45bQUSXxEKfiEghHtmDY2XHUOQsAgDEGKMRb4qDSuKploiIGmfH2h1IciRAq9IivzIfa06uhd1T6e+0iKiZalGfPhcuXIh+/fohMDAQkZGRuPXWW5GZmVljncGDB0OSpBqvhx9+uMY6WVlZGDVqFEwmEyIjIzFr1ix4PJ7LuStE1MoIjcBh2xGUeyqgggrtApKqB1IiIiJSgtlrxrD4oTCoDSh2lWB11ncocZb4Oy0iaoZaVKG/ceNGpKenY+vWrVi7di3cbjeGDRuGioqKGus98MADyMnJqX69+OKL1e95vV6MGjUKLpcLP//8Mz788EN88MEHeOaZZy737hBRK5F6dVd4Ir1wyS5oVVp0sCTDorP4Oy2iVkBCpCESKAYk8EszIgAINYRiRMIwBGoDUeGpwOqTa5Bjz/V3WkTUzLSoQn/16tW45557cMUVV6Bnz5744IMPkJWVhZ07d9ZYz2QyITo6uvplsfzxgXvNmjU4cOAAPv74Y/Tq1QsjR47E/PnzsWTJErhc7OtERPVTpCnGrP99DFADJo0JHS0dYNQY/Z0WUatg1Bkx/YoZwL8BnVrn73SImo1AXSBGJg5HpDECbtmNdad+wOHSI/5Oi4iakRZV6J+vtLQUABAaGlpj+SeffILw8HB069YNc+bMgd1ur35vy5Yt6N69O6KioqqXDR8+HDabDfv37681jtPphM1mq/EiorZNFjK25+9AjiEXGq0GUoWE5MD20Kq0/k6NiIjaAL1aj6FxQ9AusB0EBLbkbcVu6x4IIfydGhE1Ay220JdlGdOnT8fAgQPRrVu36uV33XUXPv74Y6xfvx5z5szBRx99hAkTJlS/n5ubW6PIB1D9e25u7Y89LVy4EEFBQdWvhISEJtgjImopHB4Hvj+1DpklVWOE/N/iFVAXqTjoHhERXVZqlRrXRA9A99Cqz8L7ivZjY85muGW3nzMjIn9rsfM9paenY9++ffjxxx9rLH/wwQerf+7evTtiYmIwZMgQHDlyBB06dGhQrDlz5mDmzJnVv9tsNhb7RG1UoaMIG7M3osJjh0bSIMYeja/e+g/GjRnn79SIWp1KVyUW738NGANOJUZ0EZIkoVd4TwTqArE1bxtOlp/EdyfLMTh2EAK0Af5Oj4j8pEUW+lOnTsWqVauwadMmxMfHX3Ld/v37AwAOHz6MDh06IDo6Gtu3b6+xTl5eHgAgOjq61jb0ej30er0CmRNRS3bUdhRb87bDK7ywaAMxOPY6HNnPPpFETUcg35EPhAACfByZKCMj45LvJ6kScNJwCsXOYnx1ZBUSHfEwySaf2g4PD0diYqISaRJRM9CiCn0hBB555BGsXLkSGzZsQPv27evcZs+ePQCAmJgYAEBaWhoWLFiA/Px8REZGAgDWrl0Li8WCrl27NlnuRNRyuWU3tuf/gqO2YwCAOHMsrokeyMHBiIjosrDmWQEJNbqjXkxYTBimvzkDSV3b4ZDmCJbN/xAbPl9f53YmkwkZGRks9olaiRZV6Kenp2P58uX4z3/+g8DAwOo+9UFBQTAajThy5AiWL1+OG2+8EWFhYfjtt98wY8YMDBo0CD169AAADBs2DF27dsXEiRPx4osvIjc3F0899RTS09N5156ILlDoKMLmnB9R5i6DBAk9wrqje2g3SBKn+iIiosujzFYGCGDWwsfQu1/vOtcXkoDXLkNj0uC++ZMxefb9UBerLjpN5dFDR/HklCdgtVpZ6BO1Ei2q0H/rrbcAAIMHD66xfOnSpbjnnnug0+nw/fffY/HixaioqEBCQgLGjBmDp556qnpdtVqNVatWYcqUKUhLS4PZbMakSZPw3HPPXc5dIaJmTgiBjJKD2G3dA1nIMGlMuCZ6IKJMkf5OjYiI2qjE5ASk9kz1aV0hBAocBcitzIMIENAG6ZAUkMin0YjaiBZV6Nc1XUhCQgI2btxYZztJSUn473//q1RaRNTKlDhLsTVvKwocVgBAgjkeadFXQ6/mUz9ERNQySJKESGMkjBojsspPotJbiUO2w0gMSEQgB+kjavVaVKFPRNSUvLIX+4r2Y1/RfsiQoZE06B1xJToHdeKj+kRE1CIFagPRydIRx8tPwOF14FjZMUQaIhFljOS1jagVY6FPRG2eEALZ9mzsKNgFm8sGAIg3x+GqyH4wa81+zo6oLZMQrAtGSWHJRfsWE1HddGodOlo6INuejSJnMfId+ajwVCAxIAFaldbf6RFRE1D5OwEiIn+yVlqx9tQ6/HB6A2wuGwxqAwbFXIPBsdexyCfyM6POiMe6zwY+A/sVEzWSSlIh3hyPBHM8VFChwlOBQ6WHUeYu83dqRNQEeEefiFq9rKwsWK3WGssckhMF+gLYNFUfcCQhIdQdgghXOApLC1GIQp/armtOYyIiouYkRB8Co8aErPKsM4/yH4cqWILOwC/TiFoTFvpE1KplZWUhNTUVdrsdAJDSNwWj7r8Jva6/EgAgyzJ+XPkjVr7+bxTm+Fbc16a8nHdEiIioZTCo9eho6YAcey4KnYWQAwWe+2I+KlWV/k6NiBTCQp+IWjWr1QqX24VX/70YEZ3CIc4OnC8AqVKCzqbFkKtuwJCPbmhQ+5vXbcabC5fA4XQolzQRAQAcbgeWZLwB3AK4vC5/p0PUqqgkFeLMsbBoA3Gs9DhiO8ThqDiOwEILrgjtCrWk9neKRNQILPSJqNUqddmQq8vD4k3/gCXUAgFAgoQQfQgiDOHQhzV+urxjh441PlEiqpUQMk7bTwMRgMClp9glooYJ1AVCk6vGz3t/xlUj+uPXwt9wouwEro66GhHGcH+nR0QNxEKfiFoVj+xBVvlJHCo9hPzKAkAHWEItgAeIDIhEuCEMGhVPfURERGdJsoQ3pr2Odb/eBqu5ECWuUqw++R26BKegV3hPjsxP1AJx1H0iahWKncXYnr8D/z66Ej/l/oz8ygJIkBDoCcCrD78CTY4a0aYoFvlEREQXEewJwuh2NyE5sD0A4GBJJr4+vgonyrIgBJ+qIWpJ+ImXiFost+zBibITOFR6GFbHH6PqmzVmdAzqgA6WDsjcexB71u+G9CTn4CYiIqqLQW3AwJgBaG9pj61521DhqcCmnM2IMkahX2QfhOhD/J0iEfmAhT4R+V1t099dSqWqEsXaEpRqbJAluWqhAAK9gQh1B8PsNcNT4kYmDnL6OyIiogaINcdgdLubsL/oAPYXH0BeZR6+OfEtOgV1RI+wHjBqDP5OkYgugYU+EfnV+dPfXYzBbETaTWkYPHYw2ndLrl6edyIPG1asx48rN6PUWnrR7Tn9HRERUf1oVBr0DO+BDkHJ2FWwGyfKs/B76SEctR1D15BUpIakQqdm/32i5oiFPhH5ldVqhd1ux4K3nkdyp+Qa7wkICB0gm2UIk/hjVJEzU+OpyiXEqWIx4Y4JmHDHhFrb5/R3RC2bSWOGvazC32kQtQmXegouAGa0UyciV5cPh9qB34r2Yn/hAYS7whDqDoGqjqG/wsPDkZiYqHTKRHQRLPSJqFlI7pSM1J6pAKpGzi92FqPIWQyn7KxeR6/SI1QfghB9CDRhvp2+OP0dUctl1JnwVM+n8MSUOdCPbvx0mERUO2ueFZCACRNq/9L8fH2H9cOfZvwZscmxyNPnI9P2O1Z/8C1++Nc6OCpq/2LdZDIhIyODxT7RZcJCn4iaBQEBm8uGImcxbG5b9XIJEoJ1QQjVh8KkMUGSOKgeERGRkspsZYAAZi18DL379fZpGwEBUSTgtcgIjgjGnbPG4c6Z46Aql6AqV0GS/7heHz10FE9OeQJWq5WFPtFlwkKfiPxGCAGHyoE/zRgLT4wXx8tPVL9nUhsRog9FsD4IakntxyyJiIjahsTkhOqn63wlCxklrlLkV+bDBRfkIAERJCNEH4JwfRgMHLSPyC9Y6BPRZVfqLMXx8hM4UXYCpSYbRj88GgCgltQI0QUjVB/KDwZEBIfbgX9mvguMAlxel7/TIaJaqCRVVbc6XTBK3TbkV+bD4XWgyFmEImcRAjRmyAYZKvWl+/ATkbJY6BNRk/PKXuRV5uN0xWlkV2TD5v5jBHxJSNj5ww7069kPqZ26QCXxgwARVRFCxrHyY0BM1WPCRNR8SVJVV7sgrQUVHjsKHVaUum0o91QAEcBrG/6OPF0+bC4bLDqLv9MlavVY6BOR4ryyF1ZHIfIr85FfmY+8ynx4hbf6fRVUiDFHo11gEgoPF2LiX8bjX99/yiKfiIiohZMkCQFaMwK0Zri8LhQ6C1FQYUVIZAisKMR/jn+NSGME2ge2R2JgAgxqPsFH1BRY6BNRo3iFF6XOUhQ5i6se03MUodBZBFnINdYzqo2IM8cizhyHaFN09by7JSjxQ9ZERETU1HRqHWJMMSg+VIxXF72CJxY/iQqNHfmVBcivLMD2/F8QY6r64j8+IB56NWfXIFIKC30i8plb9qDkzLR3RY4iFDmLUeIquaCoBwCD2oBIYyQijRGIMkUhRBfMEfOJiIjaIAkSdqzdgSRHIrp074JjZcdwvCwLRc4iZNtzkG3PgZQnIdIYgfiAeMSb4/h4P1EjsdAnolq5ZXfV3XlHEU4WnUSppxROyQXUUqurhApGrwEGuepl9BqhE1pIpRIqYcdxHMPxi8TJyMhoyt0gIiKiZuLca34MohAqBaNUY4NNUwan2om8M939dhbsgk7Wwew1wewxw+w1QVNH2RIeHs6p+4jOwUKfiKqnxrFWWlHoKITVUYhSV2nNwa/OdJ8vKSjBiQPHcfzAcZw4cALHDxyH9VRBo3MoLy+reyUiIiJqcax5VkACJkyYcNF1wuMjcOX1V6L3Db2R0q8LoAVcKheKtSWQZRknD2Zh/5b9OLB1PzJ3ZMJpd9bY3mQyISMjg8U+0Rks9InaGCEEKjwVsDoKzxT1VhQ6imoMlneWSWOC2qHG0jfex3XXX4eY8BhEyOGISA5H3+S+wE2Nz2fzus14c+ESOJyOxjdGRK2OVqWF2+n2dxpE1AhltjJAALMWPobe/XrXub7IExB6AWEQkA0CKq0KSV3bIalrO9w4eRQgAMkFSE4JklNCVkYW5jzwOKxWKwt9ojNY6BO1cFlZWbBarRd93wMvHOpK2FWVqFQ7UKmqhFd1YVF/9vF7o2yE0WuEUTZAK7TIyMjAV2/9B+PGjENq91TF8z926JjibRJR62DUmfDslc/hiSlzoL+Rg3QRtXSJyQlI7Vn/zxJu2Y1ydwXK3eUo95TDLbsh9IDQCwACcRHxWPjNIpzW5yCo9AgijBEI1AZybCBq01joE7VgWVlZSE1Nhd1uBwBo9VokpSYhuUcHJPdIRnL3DohuF33Bdh63Byczs3Dk1yM4+ttRHP3tCHKO5UCIi89TzUfriYiIyB+0Ki1C9MEI0QdDCAGX7EaFpxwVbjvsHjucshNxHeNQghL8nLcVQNWgwOGGcIQZQhFmCEWoPgxGDafyo7aDhT5RCySEgN1jx7Hi4xh81/W4ecJomMPMgBa1DpYHNyC5pOqXxqVG56DO6DyoMzDo0rH4aD0RERE1F5IkQa/WQa8ORag+FABwYO8BvPS3l/C3vy+AyqJCobMQDq8DpypO4VTFqeptzRoTwgxhCDWEIkwfhjBDKKf0o1aLhT5RM+aVvSj3VD2qVuYqQ4mrBCXOEpS4SuGW3YARuHPWuBrbaCQNjBojTBojTGoTjBojNKqGH+p8tJ6I/MXpduLDQx8AwwC3l/30iah2kixh9w+7EO2KRO/E3vDKXhQ6i1B4ZjyiQmcRbC4bKjx2VJTbkVV+snpbo9qIIH0QgnVBCNYHI1gXhCBdEHRqnR/3iKjxWOgT+ZFb9qDSY0elpxIVngqUucvP9EErQ7m7HHZP5UW3lSBB59Vhw7cbMPCagUiIT4BRbYBWpWWfNCJqFWThRaYtE0gEZMj+ToeImrnapuw1wQgT4uBFNBwqx5nxihxwqCvhUrlR6a1Epb0SufbcGttpZA0Msh46WQed0CE8IBwd4pJh1pqhltSXa5eIGoyFPlETcMtuVHoqYfdU4lTeSRSVF8MjeeCRPHBLHnhUVT/LUt0fXFVCBa2shU5ooZf1MMh66GU9dLIemRkH8db/LMGg769FkM5yGfaMiIiIqHnxZfq+2hjMRsR1jEVcp3jEd4pHXMd4xHWKQ2hUKDwqD8pVHgAVAIBcdx72Hd8PCRJMGhMCdYEI1AYgUBsIs9YMs8YMs9YEo9rIGy7ULLTpQn/JkiV46aWXkJubi549e+L111/HVVdd5e+0qJmqGvzFBYfXgUpPZXUhX+mtrPm7pxIe4am58SW6fzkqHCgpKEFRbiHys/JRcKoA+Ser/iw4mY+y4roHweNAeURERNRW1Xf6vktyAeKUgNAC0AoIjUC5owLWYisSOyZCqKumKa7wVCC3ls0lAWiEFlpZC63QQis00MpaaITmzEsNjdBABdUF24aHh3N6QFJMmy30P/vsM8ycORNvv/02+vfvj8WLF2P48OHIzMxEZGSkv9Ojy0QWMo5kHUV+cT68kgceyVt9591b/bP3zO8eiHp8QasSKsgOGRm/ZSAxKRGB5gDAK0HyAvACklcCvECgCECgOgAJcfFAXP3y50B5RERERFUaOn1fXTav2YynJjwBCCAoIhhRiZGITIhCVFIUIhIiEBYTjrCYMIREhUCtUcMtueFWXXpckQpbBUqtpSgtKIWtyAa7rQIepwf333c/IkIioFVpa7zUkgqSJEGC9Mef1T+rIEkABCDO/A+oukl15icIANnZ2SguLq76NuIMcc7/A1VdQyWhggoSJCHhzE+Qah3tuSZ+UdG8tNlC/9VXX8UDDzyAe++9FwDw9ttv45tvvsH777+Pxx9/3M/ZtU1CCMhChgwZspDhFd4zf8qQa/xc9fu5P9d879xtvXDLbrhkF1xe1zk/V/3pFWfmkzf5nqe9zI6S/GKUFJRUvfKrXsVnl53502l3Vm/zzy//iW5duyn8N8aB8oiIiIiamk9PDMiAyBGAGhBqABrxx58qAOozv6sBSIDZYobZYkZscmyNZk54snCiIKvpdsbcsM08bg/cTjeclU447U447I6qnyscVT/bnfC4PJh410SEBodCo9JAI2mgVWmgUWnP+10DrUoLjaSB6swXGKS8Nlnou1wu7Ny5E3PmzKleplKpMHToUGzZssWPmSmrxFmKbHt21S8C1d/uXfCTOH9p7ctrvH+2KBcybOU2VDoqq79BFNIf3yX+8bOoauGc36vWPfvNo1yvu+VKkr0yhEdALakhyVV32SUZVXffZQDemj8HwYIgnQVJcUl13oHnHXciIiKi1kGJJwbOfoZ2Czc8sqfqJTzIzcnD1yu+wqjRNyEoxAKvJEOWvJAhwyvJ53yWBmr7dC4gztxz/+MD9bm/y14Z5WVlMJpNUKvPGUzwj4/3f2x07usMjVYDjVYDY4Dxkvt30nsKJwtPXXKdmn8h+OOpAYEzTw6ceYZA/PEsgQQJQhZnBkL05fmCi69xsXd0Oj0GJV0Ds7aB34Y0M22y0LdarfB6vYiKiqqxPCoqCgcPHrxgfafTCafzj7uzpaWlAACbzda0iTbScdtxbM/f7u80GszrkeFxueFxe+HxeOB1eap/9rjc8Lo9cLu88Ho8Vd8yujyQPd7qn70eDzxOD+zldjjKK1FRZoej3AF7WQUqyyqrllc4UGGrwKy/zUKXbso/6uVyugAAhw4chsmg/Enj6KGjTdr+5YjB9lt3+5cjBttvve07PU6g6jSKwxlHEGKumjNb9spwOKq+QN29dTdU6gv7utZHS/47Yvv+b/9yxGD7rbt9APh1x6/47KVP8dlLnzZJ+2fNWuD7Z14BcWHhL6HqywZJAKo/fs85nYNfft4Og9EAnVEHvckAvVEHg8kAvVEPnVEPg0kPnUlftY5B22T72GAO4MDBA0hJSvF3Jhd1tv4U4vxvaC4kCV/WamWys7MRFxeHn3/+GWlpadXLH3vsMWzcuBHbtm2rsf68efPw7LPPXu40iYiIiIiIiGo4efIk4uPjL7lOm7yjHx4eDrVajby8vBrL8/LyEB0dfcH6c+bMwcyZM6t/l2UZRUVFCAsLa5N9Smw2GxISEnDy5ElYLE0zpRtjMAZj+C9Ga9gHxmCMlhqjNewDYzAGY/ivfcZo3TGEECgrK0NsbGyd67bJQl+n06FPnz5Yt24dbr31VgBVxfu6deswderUC9bX6/XQ62vOjxYcHHwZMm3eLBZLkx0QjMEYjOH/GK1hHxiDMVpqjNawD4zBGIzhv/YZo/XGCAoK8mm9NlnoA8DMmTMxadIk9O3bF1dddRUWL16MioqK6lH4iYiIiIiIiFqiNlvo33HHHSgoKMAzzzyD3Nxc9OrVC6tXr75ggD4iIiIiIiKilqTNFvoAMHXq1Fof1adL0+v1mDt37gXdGRiDMRijdcRoDfvAGIzRUmO0hn1gDMZgDP+1zxhtM0Zt2uSo+0REREREREStVeMmniUiIiIiIiKiZoWFPhEREREREVErwkKfiIiIiIiIqBVhoU9ERERERETUirDQp0tyu92YPXs2unfvDrPZjNjYWNx9993Izs6usV5RURHGjx8Pi8WC4OBgTJ48GeXl5T7H+eKLLzBs2DCEhYVBkiTs2bPngnWOHDmC2267DREREbBYLBg7dizy8vIUjZGbm4uJEyciOjoaZrMZvXv3xr///W/FYhw/fhySJNX6WrFihSL7AABbtmzBDTfcALPZDIvFgkGDBqGyslKRfQCAwYMHX5D/ww8/7FP79dkPABBCYOTIkZAkCV9++aWiMR566CF06NABRqMRERERuOWWW3Dw4EHFYhQVFeGRRx5BSkoKjEYjEhMT8eijj6K0tFTR/Xj33XcxePBgWCwWSJKEkpISn9v3NYbD4UB6ejrCwsIQEBCAMWPG1Ov4O19eXh7uuecexMbGwmQyYcSIETh06FCD26tNeXk5pk6divj4eBiNRnTt2hVvv/22ojEudjy/9NJLisbJyMjA6NGjERQUBLPZjH79+iErK0ux9u+5554L9mHEiBGKtX++hx9+GJIkYfHixYq2O2/ePHTp0gVmsxkhISEYOnQotm3bpkjbvl4PG6s+58eGWrJkCdq1aweDwYD+/ftj+/btirW9adMm3HzzzYiNja33edtXCxcuRL9+/RAYGIjIyEjceuutyMzMVDTGW2+9hR49esBiscBisSAtLQ3ffvutojHO9cILL0CSJEyfPl3RdufNm3fBsd2lSxdFY5w+fRoTJkxAWFgYjEYjunfvjh07dijWfrt27Wo9z6anpysWw+v14umnn0b79u1hNBrRoUMHzJ8/H0qPWV5WVobp06cjKSkJRqMRAwYMwC+//NLg9uo63oQQeOaZZxATEwOj0YihQ4fW+1pbVwwlzlmXiqHUubeu/VDi+lGf819TXQfPxUKfLslut2PXrl14+umnsWvXLnzxxRfIzMzE6NGja6w3fvx47N+/H2vXrsWqVauwadMmPPjggz7HqaiowDXXXINFixZd9P1hw4ZBkiT88MMP+Omnn+ByuXDzzTdDlmVFYgDA3XffjczMTHz11VfYu3cvbr/9dowdOxa7d+9WJEZCQgJycnJqvJ599lkEBARg5MiRiuzDli1bMGLECAwbNgzbt2/HL7/8gqlTp0Kl8u1w9yUGADzwwAM19uPFF1/0qf36xACAxYsXQ5Ikn9uuT4w+ffpg6dKlyMjIwHfffQchBIYNGwav16tIjOzsbGRnZ+Pll1/Gvn378MEHH2D16tWYPHmyovtht9sxYsQIPPHEEz63W98YM2bMwNdff40VK1Zg48aNyM7Oxu23396geEII3HrrrTh69Cj+85//YPfu3UhKSsLQoUNRUVHRoDZrM3PmTKxevRoff/wxMjIyMH36dEydOhVfffWVYjHOP57ff/99SJKEMWPGKBbjyJEjuOaaa9ClSxds2LABv/32G55++mkYDAbFYgDAiBEjauzLv/71L0XbP2vlypXYunUrYmNjFW+7c+fOeOONN7B37178+OOPaNeuHYYNG4aCgoJGt+3r9bCx6nN+bIjPPvsMM2fOxNy5c7Fr1y707NkTw4cPR35+viLtV1RUoGfPnliyZIki7dVm48aNSE9Px9atW7F27Vq43W4MGzZM0fNHfHw8XnjhBezcuRM7duzADTfcgFtuuQX79+9XLMZZv/zyC9555x306NFD8bYB4IorrqhxbP/444+KtV1cXIyBAwdCq9Xi22+/xYEDB/DKK68gJCREsRi//PJLjfzXrl0LAPjzn/+sWIxFixbhrbfewhtvvIGMjAwsWrQIL774Il5//XXFYgDA/fffj7Vr1+Kjjz7C3r17MWzYMAwdOhSnT59uUHt1HW8vvvgi/vGPf+Dtt9/Gtm3bYDabMXz4cDgcDsViKHHOulQMpc69de2HEtcPX89/TXkdrEEQ1dP27dsFAHHixAkhhBAHDhwQAMQvv/xSvc63334rJEkSp0+frlfbx44dEwDE7t27ayz/7rvvhEqlEqWlpdXLSkpKhCRJYu3atYrEEEIIs9ksli1bVmNZaGio+Oc//6lYjPP16tVL3HfffYq1379/f/HUU0/Vq736xrjuuuvEtGnTmjSGEELs3r1bxMXFiZycHAFArFy5UvEY5/r1118FAHH48OEmi/H5558LnU4n3G634jHWr18vAIji4uJ6tV1XjJKSEqHVasWKFSuql2VkZAgAYsuWLfWOk5mZKQCIffv2VS/zer0iIiKi3sfapVxxxRXiueeeq7Gsd+/e4sknn1QsxvluueUWccMNNyja5h133CEmTJigaJvnmzRpkrjllluaNIYQQpw6dUrExcWJffv2iaSkJPHaa681abzS0lIBQHz//fdN0v7510Ml1ee8Uh9XXXWVSE9Pr/7d6/WK2NhYsXDhQkXjCCEafN6ur/z8fAFAbNy4sUnjhISEiP/93/9VtM2ysjLRqVMnsXbtWsWureeaO3eu6Nmzp6Jtnmv27NnimmuuabL2azNt2jTRoUMHIcuyYm2OGjXqgs9it99+uxg/frxiMex2u1Cr1WLVqlU1lit1XTr/eJNlWURHR4uXXnqpellJSYnQ6/XiX//6lyIxzqXUOcuX80Zjz72+xGjs9eNiMS7ndZB39KneSktLIUkSgoODAVTdQQ4ODkbfvn2r1xk6dChUKpVij0w6nU5IkgS9Xl+9zGAwQKVSKfrN9IABA/DZZ5+hqKgIsizj008/hcPhwODBgxWLca6dO3diz5499brDeyn5+fnYtm0bIiMjMWDAAERFReG6665T9O/orE8++QTh4eHo1q0b5syZA7vdrmj7drsdd911F5YsWYLo6GhF265NRUUFli5divbt2yMhIaHJ4pSWlsJisUCj0TRZDKXt3LkTbrcbQ4cOrV7WpUsXJCYmYsuWLfVuz+l0AkCNO9IqlQp6vV7x4/mrr77C6dOnIYTA+vXr8fvvv2PYsGGKxThXXl4evvnmG8WOZwCQZRnffPMNOnfujOHDhyMyMhL9+/dvksehN2zYgMjISKSkpGDKlCkoLCxUtH1ZljFx4kTMmjULV1xxhaJt18blcuHdd99FUFAQevbs2SQxzr8eNnculws7d+6scSyrVCoMHTq0Qcdyc3G2O1RoaGiTtO/1evHpp5+ioqICaWlpiradnp6OUaNG1fg3UdqhQ4cQGxuL5ORkjB8/XtFuP1999RX69u2LP//5z4iMjMSVV16Jf/7zn4q1fz6Xy4WPP/4Y9913X4Oe9ruYAQMGYN26dfj9998BAL/++it+/PFHn5629JXH44HX673gaSyj0dgkn9OOHTuG3NzcGv9tBQUFoX///i36eAea/tzbVNePy30dZKFP9eJwODB79myMGzcOFosFQFW/9sjIyBrraTQahIaGIjc3V5G4V199NcxmM2bPng273Y6Kigr89a9/hdfrRU5OjiIxAODzzz+H2+1GWFgY9Ho9HnroIaxcuRIdO3ZULMa53nvvPaSmpmLAgAGKtHf06FEAVf2MHnjgAaxevRq9e/fGkCFDFO3/fNddd+Hjjz/G+vXrMWfOHHz00UeYMGGCYu0DVY+KDxgwALfccoui7Z7vzTffREBAAAICAvDtt99i7dq10Ol0TRLLarVi/vz59erW0hzk5uZCp9NdcEGNiopq0DF+9kuCOXPmoLi4GC6XC4sWLcKpU6cUPZ5ff/11dO3aFfHx8dDpdBgxYgSWLFmCQYMGKRbjXB9++CECAwMb3KWhNvn5+SgvL8cLL7yAESNGYM2aNbjttttw++23Y+PGjYrFGTFiBJYtW4Z169Zh0aJF2LhxI0aOHOlzNxZfLFq0CBqNBo8++qhibdZm1apVCAgIgMFgwGuvvYa1a9ciPDxc8Ti1XQ+bO6vVCq/Xi6ioqBrLG3osNweyLGP69OkYOHAgunXrpmjbe/fuRUBAAPR6PR5++GGsXLkSXbt2Vaz9Tz/9FLt27cLChQsVa/N8/fv3r+429tZbb+HYsWO49tprUVZWpkj7R48exVtvvYVOnTrhu+++w5QpU/Doo4/iww8/VKT983355ZcoKSnBPffco2i7jz/+OO6880506dIFWq0WV155JaZPn47x48crFiMwMBBpaWmYP38+srOz4fV68fHHH2PLli2KXvvOOntMt6bjHWjac29TXz8u13XwLBb6VMMnn3xSXfQEBARg8+bN1e+53W6MHTsWQgi89dZbTRLjYiIiIrBixQp8/fXXCAgIQFBQEEpKStC7d+9a+543JAYAPP300ygpKcH333+PHTt2YObMmRg7diz27t2rWIyzKisrsXz58ove/WtI+2fHK3jooYdw77334sorr8Rrr72GlJQUvP/++4rtw4MPPojhw4eje/fuGD9+PJYtW4aVK1fiyJEjisT46quv8MMPP/g8QElj/i3Gjx+P3bt3Y+PGjejcuTPGjh1ba9+1xv5722w2jBo1Cl27dsW8efMU3w9fXY4YdcXcunUrvvjiC/z+++8IDQ2FyWTC+vXrMXLkSJ/HkqgrxubNm/H6669j69at+Oqrr7Bz50688sorSE9Px/fff69YjHO9//77GD9+fKP6zp8f4+wAY7fccgtmzJiBXr164fHHH8dNN93U4IEFa9uPO++8E6NHj0b37t1x6623YtWqVfjll1+wYcMGRWJs3LgRf//73/HBBx8odhfuYv8e119/Pfbs2YOff/4ZI0aMwNixYxvU/7y5Xg+ppvT0dOzbtw+ffvqp4m2npKRgz5492LZtG6ZMmYJJkybhwIEDirR98uRJTJs2DZ988oni422ca+TIkfjzn/+MHj16YPjw4fjvf/+LkpISfP7554q0L8syevfujeeffx5XXnklHnzwQTzwwAOKD3x61nvvvYeRI0cq3rf5888/xyeffILly5dj165d+PDDD/Hyyy8r/oXFRx99BCEE4uLioNfr8Y9//APjxo1r8LWvrVHq3HsxSl0/arNz507Fr4N1arJOAdQi2Ww2cejQoeqX3W4XQgjhcrnErbfeKnr06CGsVmuNbd577z0RHBxcY5nb7RZqtVp88cUXPscQwrf+PQUFBdV9kKOiosSLL76oSIzDhw9f0G9YCCGGDBkiHnroIcX3Y9myZUKr1Yr8/Pxa329I+0ePHhUAxEcffVRj+dixY8Vdd92l+D6cVV5eLgCI1atXKxJj2rRpQpIkoVarq18AhEqlEtddd12T7YfT6RQmk0ksX75c0Rg2m02kpaWJIUOGiMrKyovGb+x++NJHvyEx1q1bV2u7iYmJ4tVXX71oLF9ilpSUVB8DV111lfjLX/5SZ3u+xtBqtRf0hZw8ebIYPny4YjHO2rRpkwAg9uzZ06C2LxajpKREaDQaMX/+/BrrPfbYY2LAgAGK78e5wsPDxdtvv61IjOeff/6ix3RSUlKT7kfHjh3F888/r1j7l7oeKrkPTdFH3+l0CrVafUG/0bvvvluMHj1asThnoYn76Kenp4v4+Hhx9OjRJotxriFDhogHH3xQkbZWrlwpAFxwTJw9TjwejyJxatO3b1/x+OOPK9JWYmKimDx5co1lb775poiNjVWk/XMdP35cqFQq8eWXXyrednx8vHjjjTdqLJs/f75ISUlRPJYQVZ+bsrOzhRBVn9FuvPHGRrd5/vF25MiRWs8hgwYNEo8++qgiMc7V1H30lTz3+npuauj1o7YYr732muLXwbq0nE6idFkEBgYiMDCwxrKz354dOnQI69evR1hYWI3309LSUFJSgp07d6JPnz4AgB9++AGyLKN///4+xaiPs4/Q/PDDD8jPz6911M2GxDjbx/z8b1XVanWtI/s3dj/ee+89jB49GhEREbW+35D227Vrh9jY2AumGfr9999r7WfW2H046+xUKjExMYrEePzxx3H//ffXWNa9e3e89tpruPnmmxWJURshBIQQ1X3IlYhhs9kwfPhw6PV6fPXVV5e8c6PUflxKQ2L06dMHWq0W69atqx5NPjMzE1lZWT71V71UzKCgIABVfUh37NiB+fPn1yu3i8Ww2Wxwu90+H88NiXGu9957D3369Gl0X77aYvTr16/WYzopKUmxGOc7deoUCgsLaz2mGxLjwQcfvODYHT58OCZOnIh7771XkRgXI8tyrcd0Q9qv63qoRIympNPp0KdPH6xbtw633norgKq/n3Xr1mHq1KmXLY/GEkLgkUcewcqVK7Fhwwa0b9/+ssRt6H9LtRkyZMgFTwvee++96NKlC2bPng21Wq1InPOVl5fjyJEjmDhxoiLtDRw4UNHz06UsXboUkZGRGDVqlOJt2+12Ra8XdTGbzTCbzSguLsZ3331Xr5mLfNW+fXtER0dj3bp16NWrF4Cqa+PZJ1RaEqXPvb5S8pifOHHiBWNxNPY6WBcW+nRJbrcbf/rTn7Br1y6sWrUKXq+3ul9PaGgodDodUlNTMWLEiOpHtdxuN6ZOnYo777zT50erioqKkJWVVT0n5tmLRnR0dPVAbEuXLkVqaioiIiKwZcsWTJs2DTNmzEBKSooiMbp06YKOHTvioYcewssvv4ywsDB8+eWX1VMGKrUfAHD48GFs2rQJ//3vf31q19f2JUnCrFmzMHfuXPTs2RO9evXChx9+iIMHD+L//u//FIlx5MgRLF++HDfeeCPCwsLw22+/YcaMGRg0aJDPUwPVFeP8v6+zEhMTff5AV1eMo0eP4rPPPsOwYcMQERGBU6dO4YUXXoDRaMSNN96oSAybzYZhw4bBbrfj448/hs1mg81mA1DVHcWXD3K+/DeVm5uL3NxcHD58GEBVv9LAwEAkJib6NDhVXTGCgoIwefJkzJw5E6GhobBYLHjkkUeQlpaGq6++2qe/q/OtWLECERERSExMxN69ezFt2jTceuutig2UZ7FYcN1112HWrFkwGo1ISkrCxo0bsWzZMrz66quKxDjLZrNhxYoVeOWVVxRt96xZs2bhjjvuwKBBg3D99ddj9erV+Prrrxv8WP35ysvL8eyzz2LMmDHVx/hjjz2Gjh07Yvjw4YrECAsLu+CDmVarRXR0tM/n8LpUVFRgwYIFGD16NGJiYmC1WrFkyRKcPn1akWm4fLkeKsHX60hDzZw5E5MmTULfvn1x1VVXYfHixaioqFDsg2Z5eXn1uQioGhBsz549CA0NRWJioiIx0tPTsXz5cvznP/9BYGBg9b9DUFAQjEajIjHmzJmDkSNHIjExEWVlZVi+fDk2bNiA7777TpH2AwMDLxhTwGw2IywsTNGxBv7617/i5ptvRlJSErKzszF37lyo1WqMGzdOkfbPjqfz/PPPY+zYsdi+fTveffddvPvuu4q0f5Ysy1i6dCkmTZrUJIPZ3nzzzViwYAESExNxxRVXYPfu3Xj11Vdx3333KRrn7FS+KSkpOHz4MGbNmoUuXbo0+Pir63ibPn06/va3v6FTp05o3749nn76acTGxlZ/0adEDCXOWZeKERMTo8i591IxwsLCFLl+1PV31dTXwQs0yXMC1GqcfQynttf69eur1yssLBTjxo0TAQEBwmKxiHvvvVeUlZX5HGfp0qW1xpg7d271OrNnzxZRUVFCq9WKTp06iVdeeaVeU6v4EuP3338Xt99+u4iMjBQmk0n06NHjgun2GhtDCCHmzJkjEhIShNfr9bnt+rS/cOFCER8fL0wmk0hLSxObN29WLEZWVpYYNGiQCA0NFXq9XnTs2FHMmjWrxtSHSu3HuVDPR0DrinH69GkxcuRIERkZKbRarYiPjxd33XWXOHjwoGIxzj5KX9vr2LFjisQQomr6pNrWWbp0qWIxKisrxV/+8hcREhIiTCaTuO2220ROTo5vf1G1+Pvf/y7i4+OFVqsViYmJ4qmnnhJOp7PB7dUmJydH3HPPPSI2NlYYDAaRkpJS7/OGL9555x1hNBpFSUmJou2e67333hMdO3YUBoNB9OzZU9FHV+12uxg2bJiIiIgQWq1WJCUliQceeEDk5uYqFqM2Sk8rVFlZKW677TYRGxsrdDqdiImJEaNHjxbbt29XpH1fr4eN1ZDzY329/vrrIjExUeh0OnHVVVeJrVu3Ktb2xc57kyZNUizGxf4dfD3n+eK+++4TSUlJQqfTiYiICDFkyBCxZs0axdqvTVNMr3fHHXeImJgYodPpRFxcnLjjjjvqPYVsXb7++mvRrVs3odfrRZcuXcS7776raPtCVE2zDEBkZmYq3rYQVd1opk2bJhITE4XBYBDJycniySefVPy69Nlnn4nk5GSh0+lEdHS0SE9Pb9S1o67jTZZl8fTTT4uoqCih1+vFkCFD6v13WFcMJc5Zl4qh1Ln3UjGUun7U9/zX1NPrSUIIASIiIiIiIiJqFTjEIxEREREREVErwkKfiIiIiIiIqBVhoU9ERERERETUirDQJyIiIiIiImpFWOgTERERERERtSIs9ImIiIiIiIhaERb6RERERERERK0IC30iIiIiIiKiVoSFPhERETXYzTffjBEjRtT63ubNmyFJEn777Tc8+uij6NOnD/R6PXr16lXr+kIIvPzyy+jcuTP0ej3i4uKwYMGCJsyeiIioddL4OwEiIiJquSZPnowxY8bg1KlTiI+Pr/He0qVL0bdvX/To0QMAcN9992Hbtm347bffam1r2rRpWLNmDV5++WV0794dRUVFKCoqavJ9ICIiam0kIYTwdxJERETUMnk8HsTHx2Pq1Kl46qmnqpeXl5cjJiYGL730Eh5++OHq5fPmzcOXX36JPXv21GgnIyMDPXr0wL59+5CSknK50iciImqV+Og+ERERNZhGo8Hdd9+NDz74AOfeO1ixYgW8Xi/GjRvnUztff/01kpOTsWrVKrRv3x7t2rXD/fffzzv6REREDcBCn4iIiBrlvvvuw5EjR7Bx48bqZUuXLsWYMWMQFBTkUxtHjx7FiRMnsGLFCixbtgwffPABdu7ciT/96U9NlTYREVGrxUKfiIiIGqVLly4YMGAA3n//fQDA4cOHsXnzZkyePNnnNmRZhtPpxLJly3Dttddi8ODBeO+997B+/XpkZmY2VepEREStEgt9IiIiarTJkyfj3//+N8rKyrB06VJ06NAB1113nc/bx8TEQKPRoHPnztXLUlNTAQBZWVmK50tERNSasdAnIiKiRhs7dixUKhWWL1+OZcuW4b777oMkST5vP3DgQHg8Hhw5cqR62e+//w4ASEpKUjxfIiKi1oyj7hMREZEi7r//fnzxxRew2WzIyspCbGxs9XuHDx9GeXk53n77baxfvx6fffYZAKBr167Q6XSQZRn9+vVDQEAAFi9eDFmWkZ6eDovFgjVr1vhrl4iIiFokFvpERESkiC1btmDAgAG48cYb8c0339R4b/DgwTUG6zvr2LFjaNeuHQAgOzsbjzzyCNasWQOz2YyRI0filVdeQWho6OVIn4iIqNVgoU9ERERERETUirCPPhEREREREVErwkKfiIiIiIiIqBVhoU9ERERERETUirDQJyIiIiIiImpFWOgTERERERERtSIs9ImIiIiIiIhaERb6RERERERERK0IC30iIiIiIiKiVoSFPhEREREREVErwkKfiIiIiIiIqBVhoU9ERERERETUirDQJyIiIiIiImpF/j9ay4zHAF21qwAAAABJRU5ErkJggg==\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x700 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x700 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x700 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x700 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x700 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x700 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x700 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x700 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x700 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x700 with 2 Axes>"
            ],
            "image/png": 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t/7c8HJr6Pq6/P0RT0+u/9k19nx+pnw8AiCQUfQCIQKZp6vvvv5ekJh9Ptr/bbrtN27Zt01//+lddffXVstvteuuttzRx4kQNGDAg5FH+6OjokJZrifrR2OaoP9OhLWnu6edWOxL/lvuqv9Fe/V3eTdMMlv7m3IQvLy9Pp512mn744QeNGTNGH3zwgaKiohqdt/5Ng+zs7CYfS1hfqsN5xkt7cqifnUN9H4f6fd5efj4AoC3hf04AiECzZ88OPibtzDPPbPZymZmZuvHGG/X666/rxx9/1Pr163XCCSfoxx9/bPR05yNhy5Ytjb5ef/q02+1ucK25y+WSJJWXlze6XP3IabjUn2ZdWFiosrKyRuf56aefGsxrlfrt1+dpTFvJKtWNosfFxWnjxo365ptvNHfuXG3btk1JSUm68MILD7psfn6+TjvtNK1fv16nn366PvzwQ7nd7ibnr7+j/sHODqk/S2bfp0yES/2o9YYNG5o1f/2/T1M/H1LL/y2P9M8OAODwoegDQIQpLS3VXXfdJUk644wzGtwcrqX69++v+++/X1Ldc8b3VV8KfD5fyOtvjr///e+Nvl7/jPkTTzyxwQhsfalZv379ActUVVU1edp1qPvTtWvX4CnS+z9fXKobha5/ffTo0S1ad7idfPLJstlsWrFihVauXHnA9D179gSvFbc6q1RXqOuvM3/11VeDN+G74oorDlraCwoKdNppp2nt2rU6/fTT9dFHHx3ybIQJEyYoJiZGpaWlWrp06QHTf/jhh2DRPf7440PdpSbVPwpx9uzZ2r179yHnHz58uOLi4lRUVKQPP/zwgOn7PoKwuf+WB/vZyc3N1Xfffdes9QAArEfRB4AIYZqmPvnkEx1//PHatGmTOnXq1ORd3vf3xRdfaPbs2Qfc9do0TX388ceSpO7duzeY1rVrV0k6LM9R39fy5cv19NNPN3jt66+/Dt5xvP5NjXpjxoyRJL344osNrk2urKzUTTfd1OQduuv3Z926dS3O+D//8z+SpMcee6xBgTZNU48//rhWrFihpKQk3XjjjS1edzh169ZNv/zlL2Wapn71q181GL2u//rU1NRo1KhRGjVqlIVJ/6v+FP133nlH77//foPXGlNUVKTTTz9da9as0ZgxY5pV8qW668TvueceSXV3it+3bBcWFuqGG25QIBDQ8ccfr5EjR7Zmlxp1zDHH6LzzzlN1dbXOO+88bd++vcF0n8/XoNC73W5NnjxZknTPPfc0GG33er264447lJubq549e+riiy9uVob6n53f//73KikpCb6en5+vq6++WhUVFaHuHgDgCGv8IjQAQJv2t7/9TfPmzZMkeTweFRQU6LvvvlNRUZEk6dRTT9Wrr756QDlvyqpVq3TXXXcpISFBQ4cOVefOnVVdXa3vvvtO27ZtU2Jioh599NEGy1x00UX68ssvNXHiRJ155plKTk6WJN17773q169f2Pb19ttv14MPPqiZM2dq8ODB2r17txYsWKBAIKA77rjjgDt5X3LJJfrf//1fLVu2TAMHDtSJJ56oQCCgZcuWyeVy6brrrmv0kW0jR45U586d9f3332vo0KE6+uij5XQ61a9fv+Bj2Zryq1/9SgsXLtQbb7yh4cOH65RTTlFGRoa+++47bdy4UdHR0Zo1a5bS09PD9nUJ1YsvvqgNGzZoyZIl6t27t0aPHi2Hw6H58+crPz9fPXv21Jtvvml1zKCRI0dqwIABwTdgjjnmGA0dOrTJ+W+44QatWrVKhmEoJSVFt9xyS6PznX/++Tr//PMbvPab3/xGy5Yt0yeffKKcnByNHDlSDodDixcvVlFRkbp37x4cJT8cZsyYoQkTJmjx4sXq27evRo0apc6dOys3N1erV69Wfn5+g/tRPPLII1q2bJnmzp2rnJwcjR49WvHx8Vq0aJG2b9+u1NRU/eMf/wierXIokydP1iuvvKLvvvtO/fr10wknnKDKykotXbpU3bp10/nnn68PPvjgMO09ACCcKPoA0A598803+uabbyRJsbGxSkxM1NFHH63hw4fr0ksv1XHHHdei9Z1zzjkqLS3VggULtGnTJi1evFjR0dHKzs7WAw88oMmTJwdHvOvdcsstKi8v19///nfNnj07eOfriRMnhrXoX3DBBTrvvPP05JNPavbs2aqtrdXQoUN16623Nvo4O6fTqc8//1wPP/ywPvjgA3322WfKyMjQBRdcoMcee0wvvfRSo9txuVz69NNP9dBDD2nRokVauXKlAoGATjnllEMWfcMwNHPmTI0fP15//etftXz5clVWViorK0vXXHONHnjggbB+TVojNTVVCxcu1PPPP6+3335bn332mQKBgHr27Kkbb7xR//M//xN806atuP7664Oj7Y3dEX9f9W92maapd955p8n5evTocUDRd7lc+vjjj/WXv/xFr732mhYuXCifz6eePXvq5ptv1j333NOsp1iEKjk5WfPnz9err76qWbNmacWKFVq4cKEyMjJ0zDHHHJA3KipKc+bM0SuvvKKZM2dqwYIF8ng8ys7O1m233ab777+/RfdaSEpK0jfffKMpU6Zozpw5+uSTT9SlSxfddNNNmjp1qm699dYw7zEA4HAxzJbcqhgAAAAAALRpXKMPAAAAAEAEoegDAAAAABBBKPoAAAAAAEQQij4AAAAAABGEog8AAAAAQASh6AMAAAAAEEEo+gAAAAAARBCKPgAAAAAAEYSiDwAAAABABKHoAwAAAAAQQSj6AAAAAABEEIo+AAAAAAARhKIPAAAAAEAEoegDAAAAABBBKPoAAAAAAEQQij4AAAAAABGEog8AAAAAQASh6AMAAAAAEEEo+gAAAAAARBCKPgAAAAAAEYSiDwAAAABABKHoAwAAAAAQQSj6AAAAAABEEIo+AAAAAAARhKIPAAAAAEAEoegDAAAAABBBKPoAAAAAAEQQij4AAAAAABGEog8AAAAAQASh6AMAAAAAEEEo+gAAAAAARBCKPgAAAAAAEYSiDwAAAABABKHoAwAAAAAQQSj6AAAAAABEEIo+AAAAAAARhKIPAAAAAEAEoegDAAAAABBBKPoAAAAAAEQQij4AAAAAABGEog8AAAAAQASh6AMAAAAAEEEo+gAAAAAARBCKPgAAAAAAEYSiDwAAAABABKHoAwAAAAAQQSj6AAAAAABEEIo+AAAAAAARhKIPAAAAAEAEoegDAAAAABBBKPoAAAAAAEQQij4AAAAAABHEYXWA9igQCGj37t2Kj4+XYRhWxwEAAAAARDjTNFVeXq7OnTvLZjv4mD1FPwS7d+9Wdna21TEAAAAAAB3Mjh071LVr14POQ9EPQXx8vKS6L3BCQoLFaQAAAAAAka6srEzZ2dnBPnowFP0Q1J+un5CQQNEHAAAAABwxzbl8nJvxAQAAAAAQQSj6AAAAAABEEIo+AAAAAAARhKIPAAAAAEAEoegDAAAAABBBKPoAAAAAAEQQij4AAAAAABGEog8AAAAAQASh6AMAAAAAEEEcVgcAAKAtM01TtbW1VsdoE/b9WrhcLhmGYXEi63T0/QcAtG0UfQAADqK2tlZ33HGH1THQxkyfPl1RUVFWxwAAoFGcug8AAAAAQARhRB8AgGa6d1S0XHarU1in1m/qmYU1kqR7R7nlsnesU9dr/dIzC6utjgEAwCFR9AEAaCaXXR2u3DbFZTc64NfCtDoAAADNwqn7AAAAAABEEIo+AAAAAAARhKIPAAAAAEAEoegDAAAAABBBKPoAAAAAAEQQij4AAAAAABGEog8AAAAAQASh6AMAAAAAEEEo+gAAAAAARBCKPgAAAAAAEYSiDwAAAABABKHoAwAAAAAQQSj6AAAAAABEEIo+AAAAAAARhKIPAAAAAEAEoegDAAAAABBBKPoAAAAAAEQQij4AAAAAABGEog8AAAAAQASh6AMAAAAAEEEo+gAAAAAARBCKPgAAAAAAEYSiDwAAAABABKHoAwAAAAAQQSj6AAAAAABEEIfVAQC0HaZpqra2VpLkcrlkGIbFiQAAQFvGsQPQNjGiDyCotrZWd9xxh+64447gL20AAICmcOwAtE0UfQAAAAAAIghFHwAAAACACELRBwAAAAAgglD0AQAAAACIIBR9AAAAAAAiCEUfAAAAAIAIQtEHAAAAACCCUPQBAAAAAIggFH0AAAAAACIIRR8AAAAAgAhC0QcAAAAAIIJQ9AEAAAAAiCAUfQAAAAAAIghFHwAAAACACELRBwAAAAAgglD0AQAAAACIIBR9AAAAAAAiCEUfAAAAAIAIQtEHAAAAACCCUPQBAAAAAIggFH0AAAAAACIIRR8AAAAAgAhC0QcAAAAAIIJQ9AEAAAAAiCAOqwPg8Fq1apXeeustXXbZZRo8eHCr1jNz5kxJ0tVXXy1Jeuutt9SzZ099//33GjdunM4999yDbr9+mfq/77u+wYMHB7fh8/nkcDh08skna/HixRo5cqQWL158wDr23Z/67TQ179atWzVnzhyNGzdOPXr0aLCODz/88IBpPXv21PLlyyVJw4YN04033hjMV1tbK6/Xq8TERJWUlMhut+tXv/qVtm7dqtmzZ0uSevfurR9//DGYz+l0ym63y+/3y+v1ymazKRAIBNf94Ycf6pNPPgnOM3ToUK1du1Y1NTXN/jeqX6fT6dTgwYOD+ffN4Pf7FQgElJSUpJKSkgPWkZSUFPz7mjVrNGzYsGZvHwAAdGx33HHHQadnZWVp7969stvt8vl8wdeHDRumjRs3yuPxyOv1Buft0qWLli9frqysLOXl5enYY4/Vli1bNHLkSH3xxRfyeDzq1auXfvrppwbrdDqdMk1TPp9PLpdLN9xwg5YsWaLly5erd+/eKi4u1siRI/XVV19JOvDY9rvvvlNUVJSuu+664OuNHWPu+1pjx9kffvhh8NhwwoQJjR4r1wvHMfu+x8P77lv9+vY/1t53WlM5mlpn/degtR2jrQhXZ2pLDNM0TatDtDdlZWVKTExUaWmpEhISrI7TpNraWk2dOlUlJSVKSkrSo48+KpfLFdJ6Hn74YZWWlkqSEhISZBhG8HNJMgxDzzzzjOLi4hrdfmJioiSptLRUiYmJMk1TZWVlkqTExEQ9/PDDeuyxxw5Yp2mawT/3Xce++7PvdhqbNyEhQeXl5cF1xcfHq6ysTElJSbrvvvv00EMPqf7HoP7fdX/Tpk3Tc8891+g0SYqJiVF1dbVC+XGaMmWKnnzyyRYvd7glJCTo8ccfD+l7BogkHo8nePD60EnRctkNixNZY3mgUH/yblTCuh5KKk3qkF+LWr+pJxZUS5KmT5+uqKgoixMB1isvL9e99957RLdZf7zXXHFxcaqoqGhyHY0d20pSfHy8bDabSktLGz3GrH+tsePsiooK3XvvvQ1yPvvssw2OleuF45h933XsKzExUY899pgkNTie33da/bb2z/Gb3/xGjz/+eKPrrP8atKZjtBXh6kxHQkt6KKfuR7A5c+YEf5hLS0s1Z86cVq9HqvsG2/8/QtM09fLLLx90+/v+vb7k13/+8ssvN7rOff/cfx31+7Pvdhqbt6ysrMG66rddWlqqZ555psF/wE0V+d/97ndNTpOkqqqqkEq+JP3+978PabnDraysLOTvGQCRxTRNverbrB2q1LZu22SKMQIAdT7//PMjvs2WHnPtX/L3X0djx7ZS3ZsYBzvG3Pe1/Y+ZXn755QNy7n+sXC8cx+z7H6/Xq19fY9P339b+ORo7Pq+fFo6O0VaEqzO1NZy6H6Hy8vI0Z86cBgX3008/1ciRI5WRkdHi9TTH5s2btX79euXk5Byw/eYs2xL1+9O3b98WbWf/dRQXFzdr3pacQt9Sfr//sK27tebMmaOhQ4cqPT3d6iiAZTweT/Dvdf/XdKxRbElaZhZqo1n3JmlFXIVKEkskxViayQr7/q7Z9/sC6Kjy8/P12WefWR3DcvsfZ69fv77RY9t9j5XrheOY/VDH3XPmzFEgEGhy2siRI4N/3zdHc47PQ+0YbUW4OlNbxKn7zeDxeBr8Qi8rK1N2dnabPXXfNE298MIL2rBhQ4MfapvNpv79++u2226TYRz6QLV+PevWrWv2tmNjY/X000/rxRdfPGD74Waz2RQdHd2q0XQAaIl7R7kV5+pYJ8OZpqlbvd9qk1mmgCSZUlxlnN5OHKEoR8f6WlTUBvTMwsP3xi+A9sswDOXk5Gjy5Mm67777VFlZ2eh80dHR+sMf/iCbzRaWY/b6daxfvz7k4+H+/fvLZrOFfOze0o7RVoSrMx1JnLofZk899ZQSExODH9nZ2VZHOqjc3FytW7fugB/UQCCgdevWKTc3t0XraYnKykotWLCg0e2HWyAQUGVlJSUfAA6j+tH84P/oRt2o/ndmkZWxAKBNMU1T69at04IFC5os+ZJUXV2tNWvWSArPMXv9OlpzPLxhw4ZWHbu3tGO0FeHqTG0Vp+43w4MPPqi77747+Hn9iH5blZWVpQEDBjT57lRWVlaL1tPSEf2TTjpJq1atYkQ/QvTr10+33HJLm3tHEzhSPB6P7rvvPkmSs4O9PW6apl7z/SibpAb/m5vSzMBmjTRTO9T/Dfv++z/99NPcjA8dmmmaeumll/TDDz9YHaVNqB/RP+mkk/TRRx8ddER/0KBBksJzzF6/jrYwot/cjtFWhKsztVUU/WaIiopqV7/MDcPQZZddpmnTph3w+uWXX97sg7J919PcH/qbbrpJdru90e2Hm2EYuvHGG/X8889T9A8Tm82miRMnyu12Wx0FaBM6UqmVGl6b34AhbVK5lpmFOs5IO/LBLLLvv397OzYADoeJEydq6tSpVsdoE2w2my6//HLZ7XbdcMMNmj59eqPz3XzzzbLZ6t41DMcx+77raOp4uP4RzE1Nu/LKK2WaZsjH7i3tGG1FuDpTW9XBxiY6joyMDI0bNy74DWoYhsaOHdvim6rVr6c5+vTpo379+jW6/eYs2xL1+9O/f/8WbWf/dSQnJzdr3sNZdO12+2Fbd2uNGzeOG/EBHVT9aH5T/7sakl7z/cgbrUAHlpGRoTPPPNPqGJbb/zg7Jyen0WPbfY+V64XjmP1Qx93jxo3ThAkTmpyWnp7eaI4+ffoc8hg71I7RVoSrM7VFFP0INm7cuOBzLhMTE5td2A+2nvp17fu5VPdDcfPNNx90+/V/T0pKanDziKSkJN18882NrnPfP5OSkhrdn323Uz/vvttLTExssK76bScmJuree+9t8B/Y/hnqPfDAA01Ok6SYmJiQ3/W7//77Q1rucGvN9wyA9s8rU3lmTZMP0jMl5Zk18vKoPaBDO+OMM474Nlt6zNXYs+v3P/5r7DgvPj7+oMeY+762/zHTzTfffEDO/Y+V64XjmH3/4/V6SUlJGjduXKPT99/W/jkaOz6vnxaOjtFWhKsztTUU/Qjmcrl0xRVXKCUlRVdccYVcLlfI67nyyisVFxenuLg4XXnllbryyiuVkpKiYcOGyWazafz48Qf8J7rv9vdd5oorrtDEiROD67viiiuC642Li5Pb7VZcXJzGjx+vlJSU4J9XXHFFg3XU78++26mfd9/tXXnllRo/fnww58SJE4PrqF/GZrNpwoQJDfar3rBhw5SVlRXM53K5ZBiGkpKSJNWNyF9zzTUaP358cJnevXs3+Fo4nU653W45nU5JCp6yNWzYMHXr1k0TJkyQYRhyOBwyDEPDhg1r8VkE9et0Op0N8u+boX6e+uz72/f1Sy65JOTvGQDtn8uw6UXXCP3Z+d+P5+3Ha8iqIRqyaoietx+vl1wj5DI4lAA6spYcK2RlZQWPd/Y1bNgwxcXFBY+T6uetP57JysqSzWbTsGHDgsdubrdbhmGod+/eB6zT6XQGP3e5XLr66quD6+rdu3dwHU0d2xqGIbfbrauuuir4emPHmPseo+7/dag/lq03YcKERt9wqM/Y2mP2fddRv63642yXy9XgeL7+WPvKK69ssK39c9Qvv/869z+ub+/Hi+HqTG0Nj9cLQUseawC0Jx6PR3fccYckafr06Vx/Cqjhz8VDJ0XLZW/f1+y1Rq3f1BMLqiV1zK/FvvvP/5FAHY4dgCOHx+sBAAAAANBBUfQBAAAAAIggFH0AAAAAACIIRR8AAAAAgAhC0QcAAAAAIIJQ9AEAAAAAiCAUfQAAAAAAIghFHwAAAACACELRBwAAAAAgglD0AQAAAACIIBR9AAAAAAAiCEUfAAAAAIAIQtEHAAAAACCCUPQBAAAAAIggFH0AAAAAACIIRR8AAAAAgAhC0QcAAAAAIIJQ9AEAAAAAiCAUfQAAAAAAIghFHwAAAACACELRBwAAAAAgglD0AQAAAACIIBR9AAAAAAAiCEUfAAAAAIAI4rA6AIC2w+Vyafr06cG/AwAAHAzHDkDbRNEHEGQYhqKioqyOAQAA2gmOHYC2iVP3AQAAAACIIBR9AAAAAAAiCEUfAAAAAIAIQtEHAAAAACCCUPQBAAAAAIggFH0AAAAAACIIRR8AAAAAgAhC0QcAAAAAIIJQ9AEAAAAAiCAUfQAAAAAAIghFHwAAAACACELRBwAAAAAgglD0AQAAAACIIBR9AAAAAAAiCEUfAAAAAIAIQtEHAAAAACCCUPQBAAAAAIggFH0AAAAAACIIRR8AAAAAgAhC0QcAAAAAIIJQ9AEAAAAAiCAUfQAAAAAAIghFHwAAAACACELRBwAAAAAggjisDgAAQHtR65ck0+oYlqn1m43+vaOo+/cHAKDto+gDANBMzyystjpCm/HMwhqrIwAAgCZw6j4AAAAAABGEEX0AAA7C5XJp+vTpVsdoE0zTVG1traS6r4thGBYnso7L5bI6AgAATaLoAwBwEIZhKCoqyuoYbYbb7bY6AgAAOARO3QcAAAAAIIJQ9AEAAAAAiCAUfQAAAAAAIghFHwAAAACACELRBwAAAAAgglD0AQAAAACIIBR9AAAAAAAiCEUfAAAAAIAIQtEHAAAAACCCUPQBAAAAAIggFH0AAAAAACKIw+oA7ZFpmpKksrIyi5MAAAAAADqC+v5Z30cPhqIfgvLycklSdna2xUkAAAAAAB1JeXm5EhMTDzqPYTbn7QA0EAgEtHv3bsXHx8swDKvjhEVZWZmys7O1Y8cOJSQkROw2rdpuR9mmVdtlXyNzu+xrZG6XfY3M7bKvkbld9jUyt8u+tt/tmqap8vJyde7cWTbbwa/CZ0Q/BDabTV27drU6xmGRkJBwRH8IrNqmVdvtKNu0arvsa2Rul32NzO2yr5G5XfY1MrfLvkbmdtnX9rndQ43k1+NmfAAAAAAARBCKPgAAAAAAEYSiD0lSVFSUfvvb3yoqKiqit2nVdjvKNq3aLvsamdtlXyNzu+xrZG6XfY3M7bKvkbld9jVyt7svbsYHAAAAAEAEYUQfAAAAAIAIQtEHAAAAACCCUPQBAAAAAIggFH0AAAAAACIIRR8AAAAAgAhC0QcAAAAAIIJQ9AEAAAAAiCAUfQAAAAAAIghFHwAAAACACELRBwAAAAAgglD0AQAAAACIIBR9AAAAAAAiCEUfAAAAAIAIQtEHAAAAACCCUPQBAAAAAIggFH0AAAAAACIIRR8AAAAAgAhC0QcAAAAAIIJQ9AEAAAAAiCAUfQAAAAAAIghFHwAAAACACELRBwAAAAAgglD0AQAAAACIIBR9AAAAAAAiCEUfAAAAAIAIQtEHAAAAACCCUPQBAAAAAIggFH0AAAAAACIIRR8AAAAAgAhC0QcAAAAAIIJQ9AEAAAAAiCAUfQAAAAAAIghFHwAAAACACELRBwAAAAAgglD0AQAAAACIIBR9AAAAAAAiCEUfAAAAAIAIQtEHAAAAACCCUPQBAAAAAIggFH0AAAAAACIIRR8AAAAAgAjisDpAexQIBLR7927Fx8fLMAyr4wAAAAAAIpxpmiovL1fnzp1lsx18zJ6iH4Ldu3crOzvb6hgAAAAAgA5mx44d6tq160HnoeiHID4+XlLdFzghIcHiNAAAHBm1tbX6wx/+IEm655575HK5LE4EAEDHUVZWpuzs7GAfPRiKfgjqT9dPSEig6AMAOoza2lq53W5Jdb8DKfoAABx5zbl8nJvxAQAAAAAQQSj6AADgoCo9lYqdHKvku5JVG6i1Og4AADgETt0HAACHVFVbZXUEAADQTIzoAwAAAAAQQSj6AAAAAABEEIo+AAAAAAARhKIPAAAAAEAEoegDAAAAABBBuOs+AAA4KJth0ylHnSLTNGVUGVbHAQAAh8CIPgAAOKhoV7Tm3TtPn9/5uZyG0+o4AADgECj6AAAAAABEEIo+AAAAAAARhGv0AQDAQVV6KtXjgR6SpJsSbpLL5mrR8uXeCu2q2KVCT6GqfTWq8deoxlet2oBXcc5YJbmSlBSVpCRXojJjMhVljzoMewEAQMdB0QcAAIdUUFFQ95eEQ89rmqYKawq1rWK7dlXuVmltaZPzltaWqbS2TNsqtkuSDNNQkjdJqd4URZkte0PhYNLS0tStW7ewrQ8AgLaMog8AAMLCH/BrW8V2bSjeqEJPYfB1Q4YyotOVFZOlmrIaTb5psvJ356u6olqZ3TLUpW9Xde2brd5DeqtLny4qdhWr0FGo7+Z+p4//8qF+Wv1Tq7PFxMRo/fr1lH0AQIdA0QcAAK3i8Xu0seQHbSz5QTX+Gkl1j+TrFpet7Liu6hTTKXg6/nfbvtOy/yzVE39+Ur369mqwHlOmzDxTgXhTtmibhp8xXMPHDJet3JCt1CZDoT3a76dNP+mhW6aooKCAog8A6BAo+gAAICQev0frizdoQ8lGeQNeSVK0PVr9ko5Sn8Q+ina4m1y2V99eyhmS0+T0Gn+N8qrzVVJbokCCqahkp7LjusnN9fsAABwSRR8AALTY6sI12lS5OVjwk1xJGpQyUN3ju8lmtP6hPm67W93ispVYm6CdlbtU7a/RptJN6hzTWSlRyTKM0Eb3AQDoCCj6AAB0cNu3b1dBQUGT06u91Qe8tqZ4rWwOm6L8UUqvTVNCRbyKi4pUrKKDbmv9+vUtypboSlSMI0Y7KnaqwlehXVW7VOOvUeeYTpR9AACaQNEHAKAD2759u3JyclRVVdX0THYp5spYpWT+dyR9z5Y9eu9P/9SyT5fKNM0Wb7eiorzZ8zptTvWM76H8mgLlVueq0FOogOlX19iulH0AABpB0QcAoAMrKChQVVVVozfHk6SAy1QgyS8zSgr4Atr6j7o74Gc7u+ru/7lb+p+WbW/B3AV66akXVeOpadFyhlF3536nzaEdlTtVXFsiv+lXt7jwXCoAAEAkoegDAIADbo5X469RbtVelXnLJEk22ZTmTtVW1RX9/kf3l8PZ8sOILZu2tCpnclSy7IZd2yq2q8xbri3lW9Ujvrvshr1V6wUAIJJQ9AEAQJAv4NPe6r0q9Pz3WvuUqBRlRmfI8LeN0+QTXAnqGd9DW8u3qdJXqa3l29Qzvgcj+wAA/IyiDwAAZMpUQU2B9lbnyW/6JUkJznhlxWTJ9Js695lzJZm6NuZauWwua8NKinPGqVdCT/1UtkWVvkrtqNypbrHZXLMPAIAo+gAAdHg5IwfIl+nX7qo9kuoebdc5ppPinHGSpGp/lfaU7K6bOcaqlAeKccSoe3x3bS3fqtLaUu0xHOrE3fgBABDnuAEA0EGVeyu03b1TD74+RXJJdsOuLjGd1TehT7Dkt3Xxzjh1je0qSSrwFKqgpunHBAIA0FEwog8AQAfjDfi0tmit1havU8ARkN/nl7PaoX7ZR8lha3+HBslRSfIFvNpTnas91bly2JxKjkqyOhYAAJZhRB8AgA7CNE1tKduiD7d+pNVFaxQwA4r1xeg35z8ke4m9XZb8emnuNKVFpUqSdlbuVLWv2uJEAABYp/3+RgcAAM2WX12gZfnLg6e2xzpiNTx9mPI35WnXpp0Wp2s9wzDUKaaTPIFalXvLta1iu/ok9JHDxmP3AAAdD0UfAIAIVumt1PcFK7SlfKskyWE4NChloHKS+8thc6hA+dYGDCPDMJQd21WbyjarNlCrHZU71COuu9WxAAA44ij6AAC0Mdu3b1dBQetuKhdQQAWuQhU4C2UapiQpyZuojNp0ectrtWrbKknS+vXrm7E2Q70yeklmqyIdEQ6bQ93juuvHsh9V7i1Xfk3kvJEBAEBzUfQBAGhDtm/frpycHFVVVYW0vGEYOuGcUbrknkuVkpUiSdq4bKPefPINbV27tcnlKirKm5wW7YrWe3e9L5/Xp4//+lFIuY6kGEe0Osd01q6qXcqt3it7FLckAgB0LBR9AADakIKCAlVVVemJPz+pXn17tWjZgMtUIMkvM+rnF3ySvcSmgZkD9NT03zW6zIK5C/TSUy+qxlPTyuRtS0pUsqp8VSquLZY/NaD4lASrIwEAcMRQ9AEAaIN69e2lnCE5zZrX4/cotypXpd4ySZJNNmVEpyvNnSZbxsFHs7ds2tLqrG2RYRjqEttZ1f5q1ahG10y7RmZ7uPYAAIAwoOgDANBO+QJ+5dXkqbCmMFhiU6KSlRmdKafNGbbtVNdW68oXr5BM6TLnZXLZXGFb9+FkM2x1N+cr3azjxh6vspoyqyMBAHBEUPQBAGhnTNNUoadQe6vz5Df9kqQ4R5w6xXRStMN9OLaon/J+qvtr58Ow+sMo2hEtW5lNgcSA9kTlqspXrRhHtNWxAAA4rLg7DQAA7YRpmiqtLdPG0h+0u2qP/KZfUfYo9YzroV4JPQ9TyW//bGWGtqzZIr8R0JK9S2SanMIPAIhsFH0AANqB2oBXWyu2aVvFNtUGauUwHOoS00VHJfRVvCve6nhtmiFDf33gLzJMQzsrd+mn8si8LwEAAPU4dR8AgDbMNE0VeYq0pypXAQVkyFC6O03p0emyG3ar47UbuzbtVHptmvKi8rU0b5k6xWQpxhFjdSwAAA4LRvQBAGijPP5a/VS+RbuqdiuggGIcMeqb2EdZMVmU/BCkeVOV6k6VN+DV8vzvrY4DAMBhQ9EHAKANCrgD2lS2SZW+Shky1Dmmk3rH95LbznX4oTJkaETG8ZKkreVblVedZ3EiAAAOD4o+AABtiClT5/36fPnTAgqYdaP4/RKPUpo7TYZhWJTKUKekzuqU1Mmi7YdPqjtFfRP7SJK+zVumgBmwOBEAAOFH0QcAoI2o9Xu1w71TF91xsWRIqVEp6hXfUy67tc+tj3ZF65P7P9FHd38sl83aLOFwTOoQuWwuFXuKtbl0s9VxAAAIO4o+AABtQLWvWnN2fKpyR4W8tV7Zi2zqEttFNoNf1eHmdrg1JHWwJOn7gpXy+D0WJwIAILw4egAAwGLVvmp9vvM/Kq0tlSPg0BNXPCZbJb+iD6ejkvoqyZWk2kCtVhSstDoOAABhxVEEAAAWqiv5c1VaW6YYR7R6VHfXT6t/sjpWAzXeGl3xpyt09ctXyWt6rY4TFjbDpuMyhkuSNpVuVpGn2OJEAACED0UfAACLVPtqfi75pYpxROuMrmcoymx718CbZkDrdq3Vut3rZJqm1XHCJismU93jusmUqe953B4AIIJQ9AEAsIDH79F/fj5dP9oerTO6jlGCK97qWB3OsWnHyJCh3VV7tLeKx+0BACJDmyr6Tz31lI477jjFx8crIyND559/vjZu3NhgnpqaGk2ePFmpqamKi4vTRRddpL179zaYZ/v27TrrrLMUExOjjIwM3XvvvfL5fA3mmTdvnoYOHaqoqCj16dNHr7322uHePQAAJEkBM6Cv9yxUyc8l/8zsMUpwJVgdq0OKd8WrT2JvSdKKwhURdcYCAKDjalNFf/78+Zo8ebIWL16szz//XF6vV2eeeaYqKyuD89x111366KOP9I9//EPz58/X7t27deGFFwan+/1+nXXWWaqtrdXChQv1+uuv67XXXtPUqVOD82zZskVnnXWWRo8erRUrVujOO+/UDTfcoE8//fSI7i8AoGNaVbhau6t2y27YdVqXUyn5Fjs65WjZDJvyqvO1p2qP1XEAAGg1h9UB9jVnzpwGn7/22mvKyMjQ8uXLdfLJJ6u0tFT/7//9P82aNUunnXaaJGnGjBnKycnR4sWLNXLkSH322Wdat26d/vOf/ygzM1PHHHOMHnvsMd1///2aNm2aXC6XXn75ZfXs2VN/+MMfJEk5OTn6+uuv9dxzz2ns2LFHfL8BAB3H9oodWl20RpI0MnOEUtwpFidCrDNG/RKP0vqSDVpRsFKdYjrJMAyrYwEAELI2NaK/v9LSUklSSkrdQdDy5cvl9Xo1ZsyY4Dz9+/dXt27dtGjRIknSokWLdPTRRyszMzM4z9ixY1VWVqa1a9cG59l3HfXz1K9jfx6PR2VlZQ0+AABoqVJPqRbmLpQk9U/qr14JPS1OhHoDUwbKYThU6CnSjsqdVscBAKBV2mzRDwQCuvPOO/WLX/xCgwYNkiTl5ubK5XIpKSmpwbyZmZnKzc0NzrNvya+fXj/tYPOUlZWpurr6gCxPPfWUEhMTgx/Z2dlh2UcAQMdR6/dq3u6v5A34lBmdoWHpx1odqUWSY5OVFJNkdYzDJtrhVv/kfpKklQUrFTADFicCACB0berU/X1NnjxZa9as0ddff211FD344IO6++67g5+XlZVR9gEALbIsf5nKvGWKccTopE4nyWa02ffaDxDtitGXv5knn9enj//6kdVxQrZ+/fqDTvfLL1usTSW1pZq3er6SfIkhbystLU3dunULeXkAAFqjTRb9W2+9VR9//LG++uorde3aNfh6VlaWamtrVVJS0mBUf+/evcrKygrO8+233zZYX/1d+fedZ/879e/du1cJCQmKjo4+IE9UVJSioqLCsm8AgI5nV+Vu/Vj2kyTppE4nKtrhtjhRx1Kwt0AypIkTJx5y3nNuPle/vOsSLduzXA9MuE9mILS78MfExGj9+vWUfQCAJdpU0TdNU7fddpvef/99zZs3Tz17Nrx2cdiwYXI6nZo7d64uuugiSdLGjRu1fft2nXDCCZKkE044QU888YTy8vKUkZEhSfr888+VkJCgAQMGBOeZPXt2g3V//vnnwXUAABAutX6vFu9dIknKSeqvjOh0ixN1POVl5ZIp3fvUfRp63NCDzmsapnwBvzr17KS/L3hTtuqWn3nx06af9NAtU1RQUEDRBwBYok0V/cmTJ2vWrFn617/+pfj4+OA19YmJiYqOjlZiYqKuv/563X333UpJSVFCQoJuu+02nXDCCRo5cqQk6cwzz9SAAQN01VVX6emnn1Zubq5+85vfaPLkycFR+Ztvvll/+tOfdN999+m6667TF198oXfeeUf//ve/Ldt3AEDbtX37dhUUFIS07O6oPapyVskZcEo7TX2387uDzn+o08utUOOt0eQZk2Wapsab4+Q0nFZHCkm3XtnKGZJzyPlyq3KVV5MvV2aU+iT05g78AIB2p00V/T//+c+SpFNPPbXB6zNmzNA111wjSXruuedks9l00UUXyePxaOzYsXrppZeC89rtdn388ce65ZZbdMIJJyg2NlaTJk3So48+GpynZ8+e+ve//6277rpL06dPV9euXfW3v/2NR+sBAA6wfft25eTkqKqqqsXL5ozI0YMzH5IkPXrNNK1f0vwSX1FR3uLtHS6mGdDyLcskSeM6j5UivPemudOUX1Ogan+1Kn2VinPGWR0JAIAWaVNF3zQPfR2c2+3Wiy++qBdffLHJebp3737Aqfn7O/XUU/X999+3OCMAoGMpKChQVVWVnvjzk+rVt1ezlzMNU74svyTJVmFo6hO/bdZyC+Yu0EtPvagaT01IedF6DptDKVEpKvQUKq86n6IPAGh32lTRBwCgrerVt1ezTvuut7tqjwpqCuS0OXVUdl/Zu9mbtdyWTVtCjYgwSnenqdBTqApfhap81YpxHHizXgAA2qr282wfAADaCY/fo4Kaumv6u8R0lt1oXslH2+Gyu5TkSpIk5dfkWxsGAIAWougDABBme6rqbiYb74xXgivB4jQIVbq77gkJpbWl8vg9FqcBAKD5KPoAAIRRhbdCZd4ySVKnmCyL06A1oh1uxTvjJTGqDwBoXyj6AACEiWma2l21R5KUGpUqt91tcaLwcTvdcjsjZ3+aK+PnUf1iT4m8Aa/FaQAAaB6KPgAAYVJcW6waf41shk2Z0RlWxwmbaFeMFj+6RF8//I1cNpfVcY6oWGesYuzRMmWqyFNkdRwAAJqFog8AQBj4Tb9yq/ZKkjLdGXLYeLBNpEhzp0mSCmuKFDADFqcBAODQKPoAAIRBfnWBfKZPLptLqe5Uq+MgjBJdiXIaDvlMn0prS62OAwDAITHcAABAK/kCvuDN2jrFZMlmRNb76B6vR/e8eY/MQECnmqfKaTitjnREGYahVHeqcqv3qqCmUEmuJBmGYXUsAACaFFlHIgAAWCC/Jl+mTEXbo5XgjLzH6QVMv77euEDfbPpGpmlaHccSKVEpMmSo2l+tKl+V1XEAADgoij4AAK3gC/hUWFN3k7bM6AxGeiOUw+ZQUlSSJKnAU2htGAAADiFsp+5XVVXprbfeksfj0YQJE9S9e/dwrRoAgDaroKZAAQXktv/3meuITGlRaSr2FKu0tlS1/lq57B3rCQQAgPYjpKJ//fXXa8mSJVqzZo0kqba2ViNHjgx+npiYqC+++ELHHnts+JICANDG+AP+4Oguo/mRL9rhVqwjVpW+ShV6itQpJsvqSAAANCqkU/e//PJLXXjhhcHPZ82apTVr1ujNN9/UmjVrlJWVpUceeSRsIQEAaIsKPAUKmAFF2aMi8tp8HCjt5ycqFHl41B4AoO0Kqejn5uaqR48ewc8/+OADDR8+XJdffrkGDBigG2+8UUuWLAlXRgAA2hy/6VdBTd1ofoab0fyOIsGZIJfNKb/pV7GnxOo4AAA0KqSiHxsbq5KSEkmSz+fTvHnzNHbs2OD0+Ph4lZbynFkAQOQqrCmS3/TLZXMpyZVodRwcIYZhKDWqblS/wFPQYZ9CAABo20Iq+kOHDtUrr7yi77//Xk888YTKy8t1zjnnBKf/+OOPyszMDFtIAADakoAZUEFNgSQpowNcmx/titGKp1Zq2aPL5bJxA7qUqBTZZJPH71Glr9LqOAAAHCCkm/E98cQTGjt2rIYPHy7TNHXxxRfr+OOPD05///339Ytf/CJsIQEAaEsKPUXymT65bE4lu5KsjoMjzG6zKzkqSYWeIhXUFCjOGWd1JAAAGgip6A8fPlwbNmzQwoULlZSUpFNOOSU4raSkRL/+9a8bvAYAQKQImAHlV+dLktK5Nr/DSnWnqdBTpDJvuTx+j6LsUVZHAgAgKKSiL0np6ek677zzDng9KSlJd9xxR6tCAQDQVhV5iuUzfXLanEqOSrI6zhHh8Xr00DsPyTQDGmmOlNNwWh3Jcm57lOKdcSr3VqiwplCdYztbHQkAgKCQi74klZeXa9u2bSouLm70ZjQnn3xya1YPAECbEjADyq+pH81Pl80I6VY37U7A9Os/az6XJI3oPELiJAZJUlpUmsq9FSqqLVZmTKbsht3qSAAASAqx6BcWFurWW2/VP//5T/n9/gOmm6YpwzAanQYAQHtV7CmRN+CVw3AoJSrZ6jiwWJwzTlG2KHkCHhV7ipXmTrM6EgAAkkIs+jfeeKM++ugj3X777TrppJOUnMzBDgAgspky/zuaH91xRvPRNMMwlOpO1e6q3SqoKVRqVCr3bAAAtAkhFf3PPvtMd911l55++ulw5wEAoE0yY0zVBmplN+xKjUqxOg7aiOSoJOVW56o2UKtyb7kSXAlWRwIAQCENR8TExKhHjx5hjgIAQNtk2Az5EwKSOta1+Tg0u2FXys9v/BR4Ci1OAwBAnZCOVCZOnKj3338/3FkAAGiTjh83QnLWlbpUN6P5aCgtKlWSVOGtUI2/xuI0AACEeOr+xRdfrPnz52vcuHG66aablJ2dLbv9wDvNDh06tNUBAQCwkilT591S9zjZNHcqd1bHAVx2lxKcCSrzlqmwhlF9AID1Qir6J554YvDvn3/++QHTues+ACBSlNvL1fWobClQ9zi1jsjtjNaiRxbJ5/XrPzMO/L2PujeByrxlKvaUyMYN+QAAFgup6M+YMSPcOQAAaHNM01S+q0CSZCs3ZE/rmKP5hmEo2hUjn+HjrvJNiHXEym2PUo3fI8VyDwcAgLVCKvqTJk0Kdw4AANqcXZW7VGP3qKayRnEVsVbHQRtmGIZSo9K0q2qXAvEBGTbeEAEAWCekor+viooK7dixQ5KUnZ2tuLi4VocCAMBqpmlqVdEaSdLc//uPzh97vrWBLFTrq9Vj7z8mMxDQMeYxchitPnyISPWP2vM7/BpyyjFWxwEAdGAhn1u2dOlSjR49WsnJyRo0aJAGDRqk5ORknXbaaVq2bFk4MwIAcMTtqcpVYU2hDNPQJ6/OtjqOpfwBnz767kN9vOJjBcyA1XHaLJthCz5qb+zVYy1OAwDoyEJ6S37JkiU69dRT5XK5dMMNNygnJ0eStH79ev3f//2fTj75ZM2bN0/HH398WMMCAHAkmKap1UWrJUnJ3iSVFZZZnAjtRWpUivKr8zVw1CDVVHmsjgMA6KBCKvoPPfSQunTpoq+//lpZWVkNpk2bNk2/+MUv9NBDDzV6R34AANq6vOo85VXny2bYlOZNtToO2hGX3SWj2pAZY6rIWWR1HABABxXSqftLlizRr371qwNKviRlZmbqpptu0uLFi1sdDgAAK9Rfm98nobecptPiNGhvbBV1h1cljlJ5/IzqAwCOvJCKvs1mk8/na3K63++XzcajZQAA7U9+db5yq3JlyNDAlAFWx0E7ZHikLWu2yDRM/VCyyeo4AIAOKKQ2PmrUKL344ovatm3bAdO2b9+ul156Sb/4xS9aHQ4AgCNtVWHdaH7vhF6Kc/IkGbScIUNzXvtEkrSxZKP8Ab/FiQAAHU1I1+g/+eSTOvnkk9W/f39dcMEFOuqooyRJGzdu1L/+9S85HA499dRTYQ0KAMDhVlhTqN1Vu2XI0KCUgVbHQTv27Zwluu3p21WtGm2t2KbeCb2sjgQA6EBCKvrHHnuslixZooceekgffvihqqqqJEkxMTEaN26cHn/8cQ0YwOmOAID2pX40v2d8D8W74i1O03a4ndH64qEv5ff59fXfF1gdp13we/1K8SYrLypf64s3qFd8TxmGYXUsAEAHEVLRl6QBAwbo/fffVyAQUH5+viQpPT2da/MBAO1SsadYOyt3SpIGpTKavy/DMJQSlyKf10dZbYFkb7IK3UUq9hRrb/VeZcUceBNjAAAOh1a3cpvNpszMTGVmZlLyAQDt1uqfR/O7x3dXoivR4jSIBA7Zg6fsry/eYHEaAEBH0qwR/UcffVSGYeihhx6SzWbTo48+eshlDMPQww8/3OqAAAAcbqWeUm2r2C5JOppr8w9Q66vVs/9+VmYgoH5mPzmMkE8I7HBykvvrh9JN2lm5S2W1ZUpwJVgdCQDQATTrN/W0adNkGIbuv/9+uVwuTZs27ZDLUPQBAO3F6qK60fzs2K5Kjkq2OE3b4w/49M7ityVJUzpPkTh7v9kSXAnqGttFOyt3aX3xBo3IPN7qSACADqBZ59oHAgH5/X65XK7g54f68Pt5lAwAoO0rqy3T1vK6x8UenTrI4jSIRDnJOZKkH8t+Uo2/xuI0AICOgIvqAQAd2qrC1TJlqmtsF6W6U62OgwiUGZ2hlKgU+U2/Nhb/YHUcAEAHEFLRt9vtmjVrVpPT3377bdnt9pBDAQBwJJTuM5o/OPVoi9MgUhmGoYEpdY8d3lCyUd6Az+JEAIBIF1LRN03zoNP9fj+P3wEAtHmrGc3HEdItLlvxzjjVBmq1uXSz1XEAABEu5FP3myryZWVl+vTTT5WWlhZyKAAADreGo/mDLU6DSGczbBqQXDeqv754vQJmwOJEAIBI1uyi/8gjj8hut8tut8swDE2cODH4+b4fycnJeuONN3TZZZcdztwAALTKf0fzuyrVnWJ1HHQAvRN6yW13q9JXpa3lW62OAwCIYM1+EO7xxx+vX//61zJNUy+99JLOOOMMHXXUUQ3mMQxDsbGxGjZsmC688MKwhwUAIBxKa0u5Nr8Fohxu/fu+2fJ7/Vr2zlKr47RbdptdOcn99X3BCq0pWqee8T251BEAcFg0u+iPHz9e48ePlyRVVlbq5ptv1ogRIw5bMAAADpdVhWsYzW8Bm82mLsld5PP6ZDN4YE9rHJXYV2uK1qi0tlS7Knepa1xXqyMBACJQSL+tZ8yYQckHALRLpZ7S4GnTQxjNxxHmsrvUN7GvJGlt8TqL0wAAIlWzR/Qbs3PnTn3//fcqLS1VIHDgTWWuvvrq1qweAICwW1G4SpKUHdtVKYzmN4vX59ULn70gMxBQd7O7HEarDh86vJzk/tpQslF51fnKq85TRnSG1ZEAABEmpN/UNTU1mjRpkv75z38qEAjIMIzgI/f2vdaMog8AaEsKawq1vWK7JGlI2hCL07QfvoBXMxe8Lkma0nmKxGXlrRLjiFGv+J7aXPaj1hatU0YXij4AILxCOnV/ypQpeu+99/TEE09o3rx5Mk1Tr7/+uj777DONHz9eQ4YM0cqVK8OdFQCAVllRUPe7qWd8DyVHJVkbBh3awJS6R+3trNylEk+JtWEAABEnpKL/7rvv6tprr9X999+vgQMHSpK6dOmiMWPG6OOPP1ZSUpJefPHFsAYFAKA19lbt1e6qPTJkaEjqYKvjoINLcCWoW1y2JGlt8XqL0wAAIk1IRT8vL0/HH3+8JCk6OlpS3Z3461100UV67733whAPAIDWM01T3/88mt83sY/iXfEWJwKkgSl1gyVbyrao0lt5iLkBAGi+kIp+ZmamCgsLJUkxMTFKTk7Wxo0bg9PLyspUU1MTnoQAALTS7srdyq/Jl92w6+iUQVbHASRJae5UZUZnypSpdcUbrI4DAIggIRX9ESNG6Ouvvw5+fs455+iZZ57Rm2++qTfeeEPPPfecRo4cGbaQAACEyjRNfV9YN5rfL+koxThjLE4E/Negn0f1N5dulsfvsTgNACBShFT0b7/9dvXq1UseT90vpMcee0xJSUm66qqrNGnSJCUmJur5558Pa1AAAEKxrWK7ij3FctocwRugAW1Fp5gspUQly2f6tLHkB6vjAAAiREiP1zvxxBN14oknBj/Pzs7W+vXrtXr1atntdvXv318OB8/YBQBYK2AGtPLna/NzknPktrstTtQ+RTncevfOf8rv82vt+2usjhNRDMPQgOQB+jr3G20o2agByTly2DiGAgC0Tki/SUpLS5WYmNjgNZvNpiFDWvdM4q+++krPPPOMli9frj179uj999/X+eefH5x+zTXX6PXXX2+wzNixYzVnzpzg50VFRbrtttv00UcfyWaz6aKLLtL06dMVFxcXnGfVqlWaPHmyli5dqvT0dN1222267777WpUdAHDkbN++XQUFBYecr9hRojJ3ueymXbXbPPpu23ct3tb69dwR3WazqU9mH/m8Pq031lkdJ+J0j++mFYUrVeGt0ObSH9U/uZ/VkQAA7VxIRT8jI0Pjxo3TpZdeqnPPPbdBiW6NyspKDRkyRNddd50uvPDCRucZN26cZsyYEfw8KiqqwfQrr7xSe/bs0eeffy6v16trr71WN910k2bNmiWp7kaBZ555psaMGaOXX35Zq1ev1nXXXaekpCTddNNNYdkPAMDhs337duXk5Kiqquqg8zmcDj3z2bNK7ZymN34/U3NmfNKq7VZUlLdqeaApNsOmgck5WpK3VGuL16lvUh/ZDbvVsQAA7VhIRf/uu+/WP/7xD02cOFFut1sTJkzQpZdeqrPPPjv4uL1QjB8/XuPHjz/oPFFRUcrKymp02vr16zVnzhwtXbpUw4cPlyS98MILmjBhgp599ll17txZb775pmpra/Xqq6/K5XJp4MCBWrFihf74xz9S9AGgHSgoKFBVVZWe+POT6tW3V5Pz+eMCCiQHJJ909cSrNenKSSFtb8HcBXrpqRdV4+m4T5Px+rz627y/KeAPKNPMkMPg1PLmaMnZIAEF5Iixq8pXpXmr5yvZl9SibaWlpalbt24tTAgAiFQh/aZ+6qmn9NRTT2np0qV6++239e677+q9995TbGyszj77bF166aWaMGGCXC5XuPNq3rx5ysjIUHJysk477TQ9/vjjSk1NlSQtWrRISUlJwZIvSWPGjJHNZtOSJUt0wQUXaNGiRTr55JMbZBs7dqx+//vfq7i4WMnJyQds0+PxBG88KNWdFQAAsFavvr2UMySn0Wl+06+NJT8oYAbUJaGLUjNSQt7Olk1bQl42UvgCXv1l7suSpCmdp0iGxYHauIK9BZIhTZw4sUXLjb9ugi6//wot271cD551v8yA2exlY2JitH79eso+AEBSiEW/3nHHHafjjjtOzz77rBYtWhQs/e+8844SEhJUXFwcrpyS6k7bv/DCC9WzZ0/9+OOPmjJlisaPH69FixbJbrcrNzdXGRkZDZZxOBxKSUlRbm6uJCk3N1c9e/ZsME9mZmZwWmNF/6mnntIjjzwS1n0BABw+hTWF8pk+uWwupUQd+P86cDiVl5VLpnTvU/dp6HFDm72caZjy+f3q3Kuz/r7gTdmqm/dwpJ82/aSHbpmigoICij4AQFIri/6+TjjhBKWlpSk5OVl//OMfD8uo92WXXRb8+9FHH63Bgwerd+/emjdvnk4//fSwb6/egw8+qLvvvjv4eVlZmbKzsw/b9gAAofMF/MqryZckZUZnyjAYfoY1uvXKbvKsk6bkVu1VXk2enJku9U3ow/cvACAkrS76W7Zs0dtvv6133nlHK1eulM1m0+jRo3XppZeGI99B9erVS2lpadq8ebNOP/10ZWVlKS8vr8E8Pp9PRUVFwev6s7KytHfv3gbz1H/e1LX/UVFRB9z0DwDQNuXX5CtgBuS2u5XkSjz0AkAbkuZOVUFNgWr8NSr3VijBFW91JABAOxRS0d+xY4feeecdvf3221q+fLkMw9BJJ52kF198URdddJHS09PDnbNRO3fuVGFhoTp16iSp7qyCkpISLV++XMOGDZMkffHFFwoEAhoxYkRwnoceekher1dOp1OS9Pnnn6tfv36NnrYPAGg/vAGvCmrqHrvHaD7aI4fNoRR3igpqCpRXk0fRBwCEJKSi3717dxmGoZEjR+q5557TL3/5y2DZbo2Kigpt3rw5+PmWLVu0YsUKpaSkKCUlRY888oguuugiZWVl6ccff9R9992nPn36aOzYsZKknJwcjRs3TjfeeKNefvlleb1e3XrrrbrsssvUuXNnSdIVV1yhRx55RNdff73uv/9+rVmzRtOnT9dzzz3X6vwAAGvlVefLlKkYe7QSnBQktE/p7jQV1hSqylelSm+lYp2xVkcCALQzIRX9Z555RpdccknYr1NftmyZRo8eHfy8/rr4SZMm6c9//rNWrVql119/XSUlJercubPOPPNMPfbYYw1Oq3/zzTd166236vTTT5fNZtNFF12k559/Pjg9MTFRn332mSZPnqxhw4YpLS1NU6dO5dF6ANDO1fprVeQpkiRlxWQxmo92y2lzKjkqWUWeIuXV5Kmns+ehFwIAYB8tLvpVVVWaNWuWYmNjdfPNN4c1zKmnnirTbPpRMp9++ukh15GSkqJZs2YddJ7BgwdrwYIFLc4HAGi79lbnyZSpOEes4pxxVseJKC5HlP7+6zfl9/v148ebD70AWi3dna4iT5HKvRWq8lUrxhFtdSQAQDvSvOe27CMmJkZbtmxhpAQA0GbU+GtUXFv3SNesmMZvrIrQ2W12DcoepIFdBspmtPjQASGIsruU5EqSJOVX5x18ZgAA9hPSb+tx48Y1a3QdAIAjYe/PRSjBmaAYR4zFaYDwyHDX3dy41FumGn+NxWkAAO1JSNfoP/zww/rlL3+pq666Sr/61a/Us2dPRUcfeEpZSkpKqwMCAHAwVb5qldaWSqq70z7Cz+vz6s2FbyrgDyjBjJfDaPXTedEMbodbCc4ElXnLlF9doOy4rlZHAgC0EyH9ph44cKAkad26dQe9Ht7v94eWCgCAZtpbnStJSnIlKdrhtjhNZPIFvPrfT+qeTjOl8xSJq/eOmIzodJV5y1RcW6xMf4ZcdpfVkQAA7UBIRX/q1Klcow8AsFylt1Ll3gpJUmZ0hsVpgPCLccQozhGnCl+F8mvy1SW2i9WRAADtQEhFf9q0aWGOAQBAy5gylVu9V5KUEpWiKHvUIZYA2qeM6HRVlFeoyFOsjOgMOW1OqyMBANq4sNw6t7S0lNP0AQBHlBllqtJXKUNG8KZlQCSKdcQqxhEjU6YKagqtjgMAaAdCLvrLli3TuHHjFBMTo9TUVM2fP1+SVFBQoPPOO0/z5s0LV0YAAA4QSAxIklKjUrhuGRHNMP77ZlZhTaF8AQZXAAAHF1LRX7hwoU488URt2rRJEydOVCAQCE5LS0tTaWmp/vKXv4QtJAAA+zr2tKEyoyRDhtKjGc1H5It3xsttdyuggAo9jOoDAA4upKI/ZcoU5eTkaN26dXryyScPmD569GgtWbKk1eEAANifKVMX3XGRJCnNncb1yugQ9h3VL6gpUMAMHGIJAEBHFlLRX7p0qa699lpFRUU1evf9Ll26KDc3t9XhAADYX5mjXN36d5cCUro7zeo4HYLLEaVXbvybXr72L3IYId3HF2GQ6EqUy+aS3/Sr0FNkdRwAQBsWUtF3Op0NTtff365duxQXFxdyKAAAGhMwA8pz5UuSbOU2OWyUziPBbrPruF7HaXjP4bIZYbmPL0JgGIbSfx7Vz6/OZ1QfANCkkH5bjxw5Uu+++26j0yorKzVjxgydcsoprQoGAMD+tpRtUa2tVuXF5bKVH3hGGRDpkqOS5DQc8pk+FXtKrI4DAGijQir6jzzyiJYtW6azzjpLn3zyiSRp5cqV+tvf/qZhw4YpPz9fDz/8cFiDAgA6Nr/p18rC1ZKkf7/ysQyTon+keP1evbXoLb2z5B35Te74biWbYQvegDK/Jl+maVqcCADQFoVU9EeMGKHZs2dr8+bNuvrqqyVJ99xzj2666Sb5/X7Nnj1bgwcPDmtQAEDHtrn0R1X6KuUI2PWfNz+3Ok6H4vN79bsPn9LT//49Rb8NSIlKkd2wqzZQq5LaUqvjAADaoJAvbjzttNO0ceNGrVixQps2bVIgEFDv3r01bNiwRm/QBwBAqHwBn1YXrpEkpXnTVFtTa3EiwDo2w6Y0d5r2Vu9Vfk2eTDGqDwBoqNV3MTrmmGN0zDHHhCEKAACN+6F0k6r91Yp1xCi5IsnqOIDl0qJSlV+drxq/R3Y3N0gEADQU0m+GFStW6P/+7/8avPbpp5/q5JNP1ogRIzR9+vSwhAMAwBvwak3RWknS0alHyxbary4gothtdqW6UyVJgQTuvg8AaCiko6X77rtPb7/9dvDzLVu26IILLtCWLVskSXfffbf++te/hichAKBD21C8UR6/R/HOePVO6GV1HKDNSHOnypAhM0rKGZFjdRwAQBsSUtFfuXKlTjzxxODnM2fOlN1u1/fff68lS5bo4osv1ssvvxy2kACAjsnj92ht8TpJ0pDUo3mGO7APp82plKgUSdK5N59ncRoAQFsS0hFTaWmpUlNTg5/Pnj1bZ5xxhtLS0iRJZ5xxhjZv3hyehACADmtd8Xp5A14luRLVI76H1XGANifdnSaZ0sBRg1Rlq7Y6DgCgjQjpZnydOnXS+vXrJUl79uzR8uXLde211wanV1RUyGZj1AUAELoaX402FG+UJA1JHcITXSzktLv0/KQXFPD5VTiv0Oo42IfL7pJRaciMM1XgKrA6DgCgjQip6J933nl64YUXVFNToyVLligqKkoXXHBBcPrKlSvVqxfXUQIAQremeK18pk8pUSnKjutqdZwOzWF36OT+J8vn9enj+R9ZHQf7sZfbVBvjVbmjQsWeEiVHJVkdCQBgsZCG3R9//HFdeOGFeuONN5SXl6fXXntNmZmZkqSysjK9++67OvPMM8MaFADQcVR5q/RDySZJ0jFpjOYDB2P4DC39dKkkae3PT6gAAHRsIY3ox8XF6c0332xy2s6dOxUTE9OqYACAjmt10Rr5Tb8yotPVOaaT1XE6PK/fq9krZivg9ytgBmQ37FZHwn4+/suHGjF+hLaWb9OQ1MGKd8VbHQkAYKFWX0hvmqby8vKUl5cn0zRls9mUmJgop9MZjnwAgA6m3FuhzaU/SpKO4dr8NsHn9+q3707VI+8/Ir/ptzoOGrFt/TbF+WJlygw+qQIA0HGFXPTXrVuniy++WAkJCerUqZM6deqkhIQEXXzxxVqzZk04MwIAOpDVhasVUECdYrKUGZNpdRyg3UirrXv60Y9lP6nKV2VxGgCAlUI6dX/BggUaP368AoGAzjvvPB111FGSpI0bN+rDDz/UJ598ojlz5uikk04Ka1gAQGQrrS3TT2VbJNWN5gNovthAjDKi05VXna91xes1PH2Y1ZEAABYJqejfddddysjI0Pz585Wdnd1g2o4dO3TyySfr7rvv1tKlS8MSEgDQMawsXCVTprrGdlVadJrVcYB2Z1DKIH2x60v9ULJJR6cMUpQ9yupIAAALhHTq/tq1a/XrX//6gJIvSdnZ2brlllu0di13fQUANF9RTZG2lW+TJA1JG2xxGqB96hzTSSlRKfKbfm0o3mh1HACARUIq+t27d5fH42lyem1tbaNvAgAA0JQVhSslST3iuyslKtniNED7ZBiGBqUMlCRtKNkob8BrcSIAgBVCKvpTp07V888/rxUrVhww7fvvv9cLL7ygadOmtTIaAKCjyKvO067K3TJkaEgqo/lAa3SLy1aCK0G1gVr9ULLJ6jgAAAs06xr922+//YDXMjMzNWzYMI0aNUp9+vSRJG3atEmLFi3SoEGDtHjxYl1++eXhTQsAiDimaer7grrR/N6JvZXgSrA4EfbntLv09BXPKODzq/KbSqvj4BAMw9Cg5IFauHeR1hWvV/+kfrLb7FbHAgAcQc0q+n/605+anPbNN9/om2++afDa6tWrtWbNGk2fPr116QAAEW9P1R7lVefJZtg0OOVoq+OgEQ67Q2cefaZ8Xp8+XviR1XHQDD0Temhl4UpV+qq0uexH9Us6yupIAIAjqFmn7gcCgRZ/+P3+w50dANDO7Tua3y/pKMU6YyxOBEQGm2HTwJQBkqS1RWvlNzkuA4COJKRr9AEACIftFTtU5CmSw3BoUPJAq+OgCT6/T5+t/kz/WfM5hbEd6ZPQR9H2aFX6qvRj6Y9WxwEAHEHNOnW/KVu2bNEnn3yibdvqHofUvXt3jR8/Xj179gxLOABA5AqYgeCd9gck58jtcFucCE3x+mt136x7JUlTOk+R3eB67/bAbrNrUMpALc1fptVFa9U7oTfX6gNABxFy0b/nnns0ffp0BQKBBq/bbDbdeeedevbZZ1sdDgAQubaUbVVZbZlcNpdykvtbHQeISH0T+2ht8VpVca0+AHQoIRX9P/zhD3ruued08cUX65577lFOTo4kaf369Xruuef03HPPqUuXLrrrrrvCGhYA0PZs375dBQUFLVomoIA2x/wk2aTk6iStWbmm2cuuX7++pRGBDqtuVH+Qvs1bqtWFa9SHUX0A6BBCKvqvvPKKzj33XL3zzjsNXh8xYoTeeust1dTU6C9/+QtFHwAi3Pbt25WTk6OqqqoWLTfmyjN09dRJKs4r1g1nXKfamtoWb7uiorzFywAdUZ+E3lpTVDeqv6l0s/on97M6EgDgMAup6G/dulV33HFHk9PHjh2rOXPmhBwKANA+FBQUqKqqSk/8+Un16turWcuYhilfp7obuqU6UvX6xzNbtM0FcxfopadeVI2npsV5gY7IbrPr6JSBWpK3VGuK1qpPYm85bK26TRMAoI0L6X/5jIwMrVy5ssnpK1euVHp6esihAADtS6++vZQzJKdZ8+ZV5ym3eq9cNpeO6t1XNqNlD4DZsmlLKBGBDq13Yt2ofuXPo/rcFwMAIltIj9f75S9/qb/97W/63e9+p8rKyuDrlZWV+v3vf6+//e1vuvTSS8MWEgAQGfwBv/Jr8iVJmdEZLS75AEJjN+qu1ZekNUVr5Qv4LE4EADicQhrRf+yxx7RixQpNmTJFU6dOVefOnSVJu3fvls/n0+jRo/Xoo4+GNSgAoP3Lr8mX3wwoyh6lJFeS1XHQTA67U49c/KgCfr8C3wYOvQDapN6JvX4e1a/UhpKNGpQy0OpIAIDDJKSiHxMTo7lz5+pf//qXPvnkE23btk2SNG7cOE2YMEHnnHOODMMIa1AAQPvmDXhVUFMoScqKzuT3RDvitDt13rDz5PP69PHSj6yOgxDZDbuGpA3WwtxFWlu0Tkcl9pXL7rI6FgDgMGjVnVjOO+88nXfeeeHKAgCIYHur8xRQQNH2aCU4E6yOA3RIPeN7aG3RWpXWlmld8XodkzbE6kgAgMOAiyMBAIddjb9GRZ4iSVKnmE6M5rczPr9PX234Sl9vXCC/6bc6DlrBZth0TGpduV9fvEHVvmqLEwEADgeKPgDgsMut2itJSnDGK84Za3EatJTXX6vbX79Nd755J0U/AmTHZSs1KkU+06c1RWutjgMAOAwo+gCAw6rSW6kyb5kkKSsmy+I0AAzD0DFpx0iSfijdpEpv5cEXAAC0O626Rh8AgIMxTVO7q/ZIklKiUuS2uy1OBESu9evXN3teU6Zi3DGqclTpix++VBdP5xZtKy0tTd26dWtpRADAEdKsov/8889r3LhxOuqoow53HgBABCmtLVW1v1o22ZQZnWF1HCAiFewtkAxp4sSJLVquzzF9NPXtaSqyFetXv7xJe37a0+xlY2JitH79eso+ALRRzSr6d911l9LS0oJF326364033tAVV1xxWMMBANqvgBlQbnXdtfnp0Wly2pwWJwIiU3lZuWRK9z51n4YeN7RFy/qq/bJF2/T0P5+Vo9DerGV+2vSTHrpligoKCij6ANBGNavoJycna+/evcHPTdM8bIEAAJGh0FOk2kCtHIZDae40q+MAEa9br2zlDMlp0TI1/hr9ULpJZoypbpndFMvNMgEgIjSr6J966qmaNm2aVqxYocTEREnSzJkztXjx4iaXMQxD06dPD09KAEC74gv4lPfzaH5mdKbsRvNGCgEcWW67WylRKSryFGl31R71SejN4y8BIAI0q+i/9NJLuvPOO/XZZ58pLy9PhmHos88+02effdbkMhR9AOi49lbvld8M/Fwikq2Og1Zy2J164NwHFfAHZF/BmzaRJjM6QyWeElX7q1VaW6qkqCSrIwEAWqlZj9fLyMjQrFmztGfPHvn9fpmmqb///e8KBAJNfvj9PGcXADqial+1Cj1FkqTOMZ0ZHYwATrtTl51wmS4ZcQlnZ0Qgp82p9Oi6y2tyq3MVMAMWJwIAtFaziv7+ZsyYoVGjRoU7CwCgnTNNU3t+fpxeojNBcVzvC7QL6e50OQyHagPe4Bt1AID2q1mn7u9v0qRJwb+vW7dO27ZtkyR1795dAwYMCE8yAEC7U+YtU4WvUoYMdYrpZHUchIk/4Nd3W7+T3+dXwAzIZoQ0ToA2zGbYlBmdqV1Vu5RXnadkV7IcNs7eAID2KuTf1P/617/Uu3dvHX300Tr77LN19tln6+ijj1afPn304YcfhjMjAKAdCJgB7anKlSSlu9PksrssToRwqfV5dOMrN+jmGb+Sz/RZHQeHSUpUsqLsUfKbfuXV5FkdBwDQCiEV/dmzZ+uiiy6SJD355JN6//339f777+vJJ5+UaZq68MILNWfOnLAGBQC0bQU1hcHH6aVHp1sdB0ALGYahTtFZkqTCmkLV+mstTgQACFVIp+4/9thjGjx4sBYsWKDY2P9ef3nuuefq1ltv1YknnqhHHnlE48aNC1tQAEDbZdpN5VXXjQB2isnihm1AOxXvjFecI1YVvkrlVueqW1w3qyMBAEIQ0oj+qlWrNGnSpAYlv15sbKyuueYarVq1qsXr/eqrr3TOOeeoc+e6uzR/8MEHDaabpqmpU6eqU6dOio6O1pgxY7Rp06YG8xQVFenKK69UQkKCkpKSdP3116uiouKA/CeddJLcbreys7P19NNPtzgrAOC//EkBBRRQjCNGSa4kq+MACJFhGMr6+f4aJbWlqvJVWZwIABCKkIq+2+1WUVHTd2QtKiqS2+1u8XorKys1ZMgQvfjii41Of/rpp/X888/r5Zdf1pIlSxQbG6uxY8eqpqYmOM+VV16ptWvX6vPPP9fHH3+sr776SjfddFNwellZmc4880x1795dy5cv1zPPPKNp06bpr3/9a4vzAgCkgScMlBljSpK68Dg9oN2LcUQH37DbU5Ur0zStDQQAaLGQTt0/7bTTNH36dI0bN04nnHBCg2lLlizR888/rzPPPLPF6x0/frzGjx/f6DTTNPW///u/+s1vfqPzzjtPkjRz5kxlZmbqgw8+0GWXXab169drzpw5Wrp0qYYPHy5JeuGFFzRhwgQ9++yz6ty5s958803V1tbq1Vdflcvl0sCBA7VixQr98Y9/bPCGAADg0AIyddXUuiexpEalKtoRbXEiAOGQFZ2p0tpSVfoqVe4tV4IrwepIAIAWCGlE/+mnn5bb7daJJ56oE044Qddcc42uueYanXDCCRo1apTcbrd+//vfhzXoli1blJubqzFjxgRfS0xM1IgRI7Ro0SJJ0qJFi5SUlBQs+ZI0ZswY2Ww2LVmyJDjPySefLJfrv3eDHjt2rDZu3Kji4uJGt+3xeFRWVtbgAwAgFToL1blXZ8lfVwwARAaX3aU0d6okRvUBoD0Kqej37NlTq1at0u23367i4mK9/fbbevvtt1VcXKw77rhDK1euVI8ePcIaNDe37pFNmZkNDyQzMzOD03Jzc5WRkdFgusPhUEpKSoN5GlvHvtvY31NPPaXExMTgR3Z2dut3CADauUpvpfJdBZIke4lNdp65HbEcNqfuHH+Xbj/zDtmMkJ/Mi3Ymw50hu2GXJ+BRkafxwRAAQNsU8m/rjIwMPffcc9qwYYOqq6tVXV2tDRs26I9//OMBZbu9e/DBB1VaWhr82LFjh9WRAMByy/KXyzRMbVy2UUYV1+VHMqfDqWtOvkZXn3i1HEZIV/2hHbLb7MqMrjum21u9V37Tb3EiAEBztZu35bOy6p7runfv3gav7927NzgtKytLeXl5Dab7fD4VFRU1mKexdey7jf1FRUUpISGhwQcAdGQ7K3Zqe8UOyZRmPvqaDFH0gUiUEpUil80ln+lTXnW+1XEAAM3Ubop+z549lZWVpblz5wZfKysr05IlS4I3BDzhhBNUUlKi5cuXB+f54osvFAgENGLEiOA8X331lbxeb3Cezz//XP369VNycvIR2hsAaL+8Aa++zVsqSUr1pmjHRs5yinT+gF9rdqzR2l1rFTADVsfBEWQzbOr88+P2CmoK5PF7LE4EAGiONlX0KyoqtGLFCq1YsUJS3Q34VqxYoe3bt8swDN155516/PHH9eGHH2r16tW6+uqr1blzZ51//vmSpJycHI0bN0433nijvv32W33zzTe69dZbddlll6lz586SpCuuuEIul0vXX3+91q5dq7ffflvTp0/X3XffbdFeA0D7srJglSp9VYp1xCqjNt3qODgCan0eTXzpSk36y9XymT6r4+AIi3fGK84RJ1Om9lQ1fj8jAEDb0qYutFu2bJlGjx4d/Ly+fE+aNEmvvfaa7rvvPlVWVuqmm25SSUmJTjzxRM2ZM0dutzu4zJtvvqlbb71Vp59+umw2my666CI9//zzwemJiYn67LPPNHnyZA0bNkxpaWmaOnUqj9YDgGYorCnUhpKNkqQRmcdrbwkH/UCkMwxDnWM66YeyTSrzlske1abGiQAAjWhTRf/UU0896ONbDMPQo48+qkcffbTJeVJSUjRr1qyDbmfw4MFasGBByDkBoCMKmAEt3vutTJnqEd9dXWI7a68o+kBH4Ha4lRqVokJPkfxJARk27ssBAG1Zi9+Sraqq0rBhw/Tyyy8fjjwAgDZqQ8lGFXmK5LK5NDx9mNVxABxhmdGZshs2ySWdcvGpVscBABxEi4t+TEyMtmzZIsPgnVwA6CgqvBVaWbBKkjQ07VhFO6ItTgTgSHPYHMqMzpQkXXznxfKLx+0BQFsV0kVW48aN06effhruLACANsg0TS3e+618pk8Z0enqk9jb6kgALJIalSp5pYTUROW7CqyOAwBoQkhF/+GHH9YPP/ygq666Sl9//bV27dqloqKiAz4AAO3fT2VbtKdqj2yGTSdkjuSMLqADMwxD9pK6w8ciZ5HKasssTgQAaExIN+MbOHCgJGndunUHvfGd388pXQDQnlX7qrUsf7kkaUjqYCW4EixOBCs4bE796vSbFfAHZNvEHdc7OluNTd999b2GnDxEy/O/1+gup1gdCQCwn5CK/tSpUxnRAYAO4Nu8paoN1ColKkUDknOsjgOLOB1O3TLmFvm8Pn28+SOr46AN+L+n3tSQk4ZoZ+VO7anco06xnayOBADYR0hFf9q0aWGOAQBoa7aVb9f2ih0yZOiErJGyGYzkAqiz+6fdSvEmq8hVrGX5y3VWzAT+jwCANiQs/yOXlpZymj4ARBCP36Nv85ZKkgalDFRKVLLFiWClQCCgzXs368e8HxUwA1bHQRuRXpsul82lktpSbSrdbHUcAMA+Qi76y5Yt07hx4xQTE6PU1FTNnz9fklRQUKDzzjtP8+bNC1dGAMARtjRvmWr8NUp0JejolEFWx4HFPL4aXfy/F+nSP10in+mzOg7aCIfsGpI6WJK0smCVPH6PxYkAAPVCKvoLFy7UiSeeqE2bNmnixIkKBP777n5aWppKS0v1l7/8JWwhAQBHzo6KHdpSvrXulP3ME2S32a2OBKCNOiqprxJdifIEPFpVuNrqOACAn4VU9KdMmaKcnBytW7dOTz755AHTR48erSVLlrQ6HADgyPL4PVq891tJ0oDkHKVHp1mcCEBbZjNsOi59mCRpY8kPKvYUW5wIACCFWPSXLl2qa6+9VlFRUY3efb9Lly7Kzc1tdTgAwJH1bd7S4Cn79afkAsDBdIrtpG5x3WTK1Ld5y2SaptWRAKDDC6noO53OBqfr72/Xrl2Ki4sLORQA4MjbXr5dW8u3yZChUVmjOGUfQLMNTx8qu2FXXnWetpZvszoOAHR4IRX9kSNH6t133210WmVlpWbMmKFTTjmlVcEAAEdOja9Gi/PqTtkfmDJAae5UixMBaE9inbEalDJQkrQ8/zt5A16LEwFAx+YIZaFHHnlEp5xyis466yxdfvnlkqSVK1fqp59+0rPPPqv8/Hw9/PDDYQ0KAGie7du3q6CgoEXL7IjaKY/Toyh/lPzbffpu+3fNWm79+vWhRAQQgQYmD9CPZT+pwluh1YVrNDT9WKsjAUCHFVLRHzFihGbPnq1bbrlFV199tSTpnnvukST17t1bs2fP1uDBXNsJAEfa9u3blZOTo6qqqmYvc9y443Xb9Nvl9/l1/yX3auvarS3ebkVFeYuXQfvhsDl19UmTZAYCsm0N+cm8iHB2m13HpQ/Tl7vna33xBvVO7K1EV4LVsQCgQwqp6EvSaaedpo0bN+r777/X5s2bFQgE1Lt3bw0bNqzRG/QBAA6/goICVVVV6Yk/P6lefXsdcn7TZsqX5ZckOSsdemr671q0vQVzF+ilp15UjacmpLxoH5wOp+6ecLd8Xp8+/utHVsdBG9Y1rqu6xHbWrsrdWpq3TKd3Gc1xIQBYIOSiX+/YY4/VscdyahYAtCW9+vZSzpCcg85jmqa2V2xXqbdMbrtbfXr0ls1o2Wjtlk1bWhMTQAQanj5ce6o+1p6qPdpRuVPd4rKtjgQAHU7I5995PB796U9/0oQJEzRgwAANGDBAEyZM0J/+9CfV1DCyAwBtXWltqUq9ZZKk7NiuLS756DgCgYB2Fe/S7uLdCphNP3UHkKQEV7wGJNe90bgsb7l8AZ/FiQCg4wnpqG7nzp065phjdPvtt2vlypVKT09Xenq6Vq5cqdtvv13HHHOMdu7cGe6sAIAw8Qa82lW1W5KUGZ2haEe0xYnQlnl8NTrr6Qk697lz5DMpbTi0QSmDFOOIUaWvUmuL1lkdBwA6nJCK/uTJk7Vt2za988472rVrl+bPn6/58+dr165devvtt7V9+3ZNnjw53FkBAGFgmqZ2Ve6W3/TLbXcrw51hdSQAEcZpc2h4+jBJ0pritSr3VlicCAA6lpCK/ty5c3XXXXfp4osvPmDaL3/5S91xxx2aO3duq8MBAMKvpLZUZd4yGTKUHduVG2UBOCy6xWUrKzpTATOg5XnLrY4DAB1KSEU/Pj5eGRlNjwBlZWUpPj4+5FAAgMPDG/Bq98+n7Gdwyj6Aw8gwDB2XcZwMGdpRuVO7KndbHQkAOoyQiv61116r1157rdHnNFdUVGjGjBm6/vrrWx0OABA+pmlqZ+Uu+U2/ou3RynCnWx0JQIRLikpU/+R+kqSlecvkD/gtTgQAHUOzHq/33nvvNfj82GOP1b///W/1799fkyZNUp8+fSRJmzZt0syZM5WSkqLBgweHPy0AIGQltSUq95Zzyj6AI2pwymBtLdumcm+51hSv1ZBUjhEB4HBrVtG/+OKLZRiGTNOUpAZ/f+KJJw6Yf+fOnbr88st1ySWXhDEqACBU+56ynxmdIbfDbXEiAB2Fy+7U8IxhWrDna60pWque8T2U4EqwOhYARLRmFf0vv/zycOcAABwm/z1lP6Boe7TSOWUfLWS3OXTJyEtlBgKy7Qrpqj90cN3jumlzTCftqdqjb/OW6vQup3FWEQAcRs0q+qeccsrhzgEAOEyKPMX/PWU/jlP20XIuh0tTzpsin9enj//6kdVx0EasX7++RfPHGjEyYgztqcrVvNXzlehr/qh+WlqaunXr1tKIANBhNavoAwDaJ4/foz1VeyRJWdGZcts5ZR9A6xTsLZAMaeLEiS1e9rzJ5+ui2y/WmrK1un/8vaquqG7WcjExMVq/fj1lHwCaKeSi//XXX+vVV1/VTz/9pOLi4uA1+/UMw9DKlStbHRAAEBrTNLWjcqcCCijWEas0d5rVkdBOmaap4spi+X1+mabJWSEdXHlZuWRK9z51n4YeN7RFy5oy5fP6lZSRpFfm/U32Evshl/lp00966JYpKigooOgDQDOFVPT/+Mc/6t5775Xb7Va/fv2UkpIS7lwAgFbKq8lXla9KNsPGXfbRKjXeap32xGhJ0pTOU+QyXBYnQlvQrVe2cobktHi5cm+FtpRvUSDeVK8u3RXjiDkM6QCgYwup6D/zzDP6xS9+oY8++kiJiYnhzgQAaKWA09Te6r2SpC4xneWyU8wAtA3xzjgluZJUUluinZW71DehD29EAkCYhXTr3KqqKl155ZWUfABog1xul/ypfklSoitRSa4kawMBwH46x3SS3bCrxl+j/Jp8q+MAQMQJqeiPHj1aq1evDncWAEAYXHrvZZJTchgOdYnpzEgZgDbHYXOoU0wnSdLe6jx5/B6LEwFAZAmp6L/wwguaO3eunn32WRUVFYU7EwAgROX2Cp0x8UxJUnZcVzlsPFwFQNuU7EpSnCNOpkztqtx1wI2dAQChC6noZ2dn61e/+pUeeOABpaenKzY2VgkJCQ0+OK0fAI4sj9+j3VF1j9KzlRuKd8ZbnAgAmmYYhrrEdpYhQxW+ShXXllgdCQAiRkhDPVOnTtUTTzyhLl26aPjw4ZR6ALCYaZpavHeJfDafdm3epe5uHkEFoO2LskcpMzpTudW52lO1RwnOeM5EAoAwCOl/0pdffllnnXWWPvjgA9lsIZ0UAAAIo5/Kt2h7xQ7JlF6+98/63fO/szoSIojd5tA5Q8+VGQjIls/vfYRXujtNJbUlqvHXaFflLnWP7251JABo90L6bV1bW6uzzjqLkg8AbUCFt0JL85ZKkjJq07Vt3VZrAyHiuBwuPfbLxzTtwkfkMBhtRXgZhqHs2K6SpFJvmUpqSy1OBADtX0hN/eyzz9aCBQvCnQUA0EIBM6BvchfKG/Ap3Z2uNG+q1ZEAoMWiHdHKcGdIknZV7pIv4LM4EQC0byEV/d/+9rdat26dfv3rX2v58uXKz89XUVHRAR8AgMNrVeFq5VXny2lz6hdZJ8gQj9JD+JmmqeraKlXXVnNndBw2GdHpctvd8pt+7arabXUcAGjXQjr/rl+/fpKkFStW6C9/+UuT8/n9/tBSAQAOKbcqV6uL1kiSRmYer3gXd9nH4VHjrdYJvz1BkjSl8xS5DJfFiRCJbIZNXWO7anPZZpXWlqqktlRJLm74DAChCPmu+4bBqBEAWKXGV6Ov9yyUJPVJ6K0e8T2sDQQAYRDjiFaGO115NfnaVblLcY5YqyMBQLsUUtGfNm1amGMAAJrLNE0t3LtI1f5qJboSdFzGcKsjAUDYZERnqMxbphq/Rzsrd8kUl4sAQEtx23wAaGfWl2zQrsrdshk2ndTpRJ45DSCi1J3Cny1JKvOWyYyh6ANAS4V0dPjoo48ech7DMPTwww+HsnoAQBPyqwv0ff4KSdJx6cOUHJVsbSAAOAxiHNHKis5UbvVe+ZMDSu+abnUkAGhXwn7qvmEYMk2Tog8AYVbjr9FXexYooIC6x3VT38S+VkcCgMMm3Z2ucm+FKn2VuvmZWziFHwBaIKRT9wOBwAEfPp9PP/74o+666y4NHz5ceXl54c4KAB1WwAzo6z0LVeWrUoIzQSdkjeSmqAAimmEYyo7tKgWkvkOPUr6zwOpIANBuhO0afZvNpp49e+rZZ59V3759ddttt4Vr1QDQ4a0uXKM9VXtkN+w6ufNJctqcVkdCB2Iz7Boz6AydPvB03mDCEeWyu2QvrjtczXcVqKCasg8AzXFYbsZ38skna/bs2Ydj1QDQ4eyu3K1VRaslSSMzj1dyVJK1gdDhRDmj9OyVz+r3lz4tp8GbTDiyjCpDiz5eJBnSgtxvVOuvtToSALR5h6XoL1u2TDYbN/QHgNaq8Fbo6z0LJUl9E/uoV0IvixMBwJFlyNDrj8yQM+BUhbdCi/YulmlyvT4AHExIN+ObOXNmo6+XlJToq6++0nvvvacbbrihVcEAoKPzBXyav/sref5/e3ceH0V9/w/8NXsfue+LhCRcwSq3gNoqggTKF0SpIl9FBCs/LShI64HWq1YRTzyo1xdRS61KK61iFQEBsYAiiIJGrgRCyLkhyV7JHjOf3x85JBBISHayyeb19LFmMzub13sCzMx7Z+YzigcxxhiMiB8e7JKIiILCbXejV10qjlgKUeg8hp+q9yMnekCwyyIi6rLa1ejfdNNNZ3wtLi4O9957Lx588MH21kRE1OMJIbC9bAdOeKpg1BpxWcqvoNVog10W9VC1XjdGPzQaAHBfyn0waAxBroh6IrNixrD4odhZ8Q12VexGnCkO8ea4YJdFRNQltavRLygoOG2aJEmIjo5GeHh4h4siIurpfqzKwxHHUUiQcGnyL2HVW4NdEhFR0PWP6ofy2nIcdRZia8lWTMr4NYxaY7DLIiLqctrV6GdkZAS6DiIialDsKsa3tj0AgBEJw5FoSQxuQUREXYQkSRiVOAonPFVw+Bz4b+k2jEm5jHeDICI6RbsafSIiarvCwkLYbG27JZRH8iLfUgAhCUT5IuHMd2A3drc5Ky8vr71lEhF1CwatHr9K+SU+LVyH465i7Kn8DkPiBge7LCKiLqXNjf4FF1xwTj9YkiR8991351wQEVEoKSwsRE5ODtxud6vzWiOtePC9h5GcmYyDuw9gyY2Pw+/ztyvX6XS0631ERN1BjDEaoxJH4r+l27DvxA+IMkQhM6J3sMsiIuoy2tzox8TEtOm0qNLSUuzfv5+nUBERAbDZbHC73Xjs5ceR1ffMt8YTEJDjZQgTAD+Qk5iDv36y6pzztm7cir8sWY46T10HqiYi6vqyIjJR7anGD1U/YnvZDkQYwhFrig12WUREXUKbG/3Nmzef9fXS0lIsXboUr776KrRaLWbOnNnR2oiIQkZW3yzkDMpp8TUhBIpcRajyVkMDDfrEZMOUYGpXTsHB0wdLJSIKVYPjBqHaW43jrmJsLt6CX6dPhFlnDnZZRERBp+noDygrK8Odd96J7OxsLF++HNdddx1++uknvPHGG4Goj4go5FXUVaDKWw0AyAhLh0nXviafSC0aSYtL+v8SF/e9mGfsUZeikTS4JOliRBoi4PbXYnPxF5AVOdhlEREFXbsb/dLSUtx5553IysrC8uXLMX369KYGPzs7O5A1EhGFrGpPNUprywAAqZYUhBt4i1Lqeox6I1666SU8P/MF6CV9sMshasagNeCylMtg0Bhgq7Phy9JtEEIEuywioqA650a/tLQUCxcubHYEf//+/XjjjTeQlXXm608D4eGHH4YkSc0eAwYMaHq9rq4O8+bNQ2xsLMLCwjBt2jSUlZU1+xmFhYWYNGkSLBYLEhIScNddd8Hvb99gV0REHeH0OXHMVQQAiDPG8tpSIqJ2ijCE49KUX0EjaVDoLMQ3FbvY7BNRj9bma/RLSkrwxBNP4PXXX4ff78eNN96I+++/H5mZmWrWd5rzzjsPGzZsaPpep/t5Ee688058/PHHWL16NSIjIzF//nxcffXV+O9//wsAkGUZkyZNQlJSErZt24aSkhLceOON0Ov1ePzxxzt1OYioZ6v11+KI4ygEBCL1EUi2JAe7JCKibi3JkoiLEkfjy9L/4qfq/bDqrBgY0/LYKEREoa7NjX52djY8Hg8GDx6M++67D5mZmaiqqkJVVdUZ3zN06NCAFHkynU6HpKSk06bX1NRgxYoVeOedd3D55ZcDAFauXImcnBzs2LEDo0aNwmeffYYff/wRGzZsQGJiIgYPHoxHH30U99xzDx5++GEYDIaA10tEdCqP7EWB4wgUKLDqrOgV1ovXPVOXVut1Y8yfxwAAFsUvgkHD7SV1TZkRvVHrr8Uu227ssu2GWWfmbfeIqEdqc6NfV1d/q6Zvv/0W11577VnnFUJAkiTIcuAHQzl48CBSUlJgMpkwevRoLFmyBOnp6di1axd8Ph/GjRvXNO+AAQOQnp6O7du3Y9SoUdi+fTvOP/98JCYmNs2Tm5uL2267DT/88AOGDBnSYqbH44HH42n63m63B3y5iKhn8Ct+FDgK4Bd+mLQm9A7LgEbq8LioRKqr8/GWjdQ95EQPgMvvwk/V+7GtdDtMOhOSLacfJCIiCmVtbvRXrlypZh1tMnLkSLz55pvo378/SkpK8Mgjj+CXv/wl9u3bh9LSUhgMBkRFRTV7T2JiIkpLSwHUjy9wcpPf+Hrja2eyZMkSPPLII4FdGCLqcWRFRoGjAF7FC71Gj8zw3tBqtMEui4ioW8jLy2vzvBpIiDCGw6534PNjnyOjNh0WxdLm98fFxSE9Pb09ZRIRdQltbvRnzZqlZh1tMnHixKbnF1xwAUaOHImMjAy8//77MJvVu2fq4sWLsWjRoqbv7XY7evXqpVoeEYUeIQkUOI+gVq6DVtIiKzwTeg1HLyciao2tzAZIwA033HBO79Ppdbjzld/j/EvOxz7fj1hy42Mo/KmwTe+1WCzIy8tjs09E3VabG/2uKCoqCv369cOhQ4dwxRVXwOv1orq6utlR/bKysqZr+pOSkvD11183+xmNo/K3dN1/I6PRCKPRGPgFIKIeQW/UQ45T4Pa7m5p8o5brFCKitnDYHYAA7lpyN4aOOLfxn4QkIHtkWCOt+PMHj0NXroXkP/uYKPkH83H/bffBZrOx0SeibqtbN/pOpxOHDx/GzJkzMWzYMOj1emzcuBHTpk0DAOzfvx+FhYUYPXo0AGD06NF47LHHUF5ejoSEBADA+vXrERERgYEDBwZtOYgodClQcMdLCyFMAhpokBneG2ademcgERGFqvSsXsgZdO6j6MuKjHxHPmpRBylVg+zwLBi0HFCSiEJbtxoB6g9/+AO2bNmCI0eOYNu2bbjqqqug1WoxY8YMREZG4uabb8aiRYuwadMm7Nq1C7Nnz8bo0aMxatQoAMD48eMxcOBAzJw5E9999x3WrVuHP/7xj5g3bx6P2BNRwClCQZHpOAb9ahCgAJnhvWHRtf0aUSIi6jitRovM8EwYNUb4FB/yHQXwyt5gl0VEpKpudUS/qKgIM2bMQGVlJeLj43HJJZdgx44diI+PBwA899xz0Gg0mDZtGjweD3Jzc/GXv/yl6f1arRZr167FbbfdhtGjR8NqtWLWrFn405/+FKxFIqIQJQsZW4u/hEPnhNfjhbnGBGucNdhlEbWLJGkwLHN4/V11fLwVJHU/Oo0OWRGZOGzPh1fxIt9RgKyILBg4VgoRhahu1ei/++67Z33dZDJh+fLlWL58+RnnycjIwH/+859Al0ZE1ERWZHxRshVFruOQhIQX5i/D4gfvC3ZZRO1m0puwYu4K+H1+rH3to2CXQ9Queo0eWeGZ9Uf0FS/y7fnIjsjiwKhEFJK61an7RERdnazI2FLyBYpcx6GVtEivS8P3X3wf7LKIiAiAQWtAVngmDBo9vIoXh+358Cm+YJdFRBRwbPSJiALEr/ixqXgLjruKoZW0GJN6GcLksGCXRUREJ6lv9uuP5LPZJ6JQxUafiCgAvLIXG49/jhJ3CXSSDmNTxyDZcubbdhJ1J7VeN8b8+TKMe2IsvAoHMaPuz6A1IPukZj/fXsBmn4hCCht9IqIOqvXX4rOiDSivrYBeo8fYtDFItCQGuyyigKpyVaHaXR3sMogC5uRm36N42OwTUUhho09E1AFOnxPrjq1HlacKJq0J49PGIcGcEOyyiIioDU4+jb+x2RcaEeyyiIg6jI0+EVE7VXuq8WnhZ3D4HLDqrMjtdQViTDHBLouIiM6BsWGAvsZm358gIyI2IthlERF1CBt9IqJ2qKi1Yd2x9aiVaxFpiMSEXuMRYeCOIRFRd2TUGuubfUkH6IHFb98Pn+QPdllERO3GRp+I6BwVu0qwoWgjvIoXcaZY5Pa6Aha9JdhlERFRBxi1RmRFZAF+ILVPKo6Yj8Ltdwe7LCKidmGjT0R0Do46CrHp+Gb4hR/JliSMSxsLo9YY7LKIiCgAjFojdOVaVBbb4NV48dmxDXD72OwTUffDRp+IqI0OVh/C1pIvoUBBRlg6xqRcBr1GH+yyiFQnSRoMTD0PA1MGQpKkYJdDpCpJlvDYzMegV/Rw+Bz4rGg9XD5XsMsiIjonbPSJiFohhMB3tu+xo/wrCAj0jeyDS5IvhlajDXZpRJ3CpDfhnfnv4O1b/wq9xA+3KPTZiirQuzYDYfowOHxOfFa0AU6fM9hlERG1mS7YBRARdbbCwkLYbLY2zSsgUGwsQbW+BgAQ542F/rgOe47vadP78/Ly2lsmEREFkUHoMT5tHNYXbahv9o9twPhe4xCmDwt2aURErWKjT0Q9SmFhIXJycuB2t37NpdFixPxlt2PQpYOhyAreeuRNbHrv83blOp2Odr2PiIiCx6q34oq0KxqafQc+O7YeV6SNQ7ghPNilERGdFRt9IupRbDYb3G43Hnv5cWT1zTrjfEIjIMfLEAYACqA/ocPcW+Zi7i1zzylv68at+MuS5ajz1HWwcqLgqfXW4urnrgYgMNsyGwaNIdglEXUaq96C8b3GYf2xDbD7HPisaAOuSBuHCDb7RNSFsdEnoh4pq28WcgbltPiaR/agwFEAvyJDK2mRGdUblrj23T6v4GBBR8ok6iIESqqL65/yTpLUA1l0FlzRq/7Ivt1rx/qi9Q3NfkSwSyMiahEH4yMiOonL58Ih+2F4FR8MGgP6RGTDomNnQ0TU01l0ZoxPG4dIQyTc/lp8dmwDarw1wS6LiKhFbPSJiBrUeO3IdxRAFjLMWjP6RGTDqDUGuywiIuoizDozrkgbhyhDFGrl+ma/2sNmn4i6Hjb6REQAbHU2HHUehYBAuD4c2RFZ0Gl4dRMRETVn1plwRa+xiDZGo06uw/qiDajyVAe7LCKiZtjoE1GPJoTAcddxFLtLAAAxxmj0DsuARuLqkYiIWmbSmnBF2ljEnNTsV9adCHZZRERNuCdLRD2WrMgocB5Bpad+5yzJnIRUSyokSQpyZURE1NUZtUaMSxuLWGMMPLIH64s2oMxdHuyyiIgAsNEnoh5KaAUOOQ7D6XNCgoSMsHQkmOPZ5BO1SEJWQhay4s98S0qinqi+2R+HRHMCfIoPG49/juOu4mCXRUTE2+sRUc/TZ0hf+BNl+GUZOkmH3uG9YdGZg10WUZdlNpjxwZ1r4Pf5sfa1j4JdDlGnyMvLa/O8MYiGy+SGU+fEpqJNSK1LRaR8brfei4uLQ3p6+rmWSUTUIjb6RNSjVOtqsPjt+wBt/TWWmeG9odfog10WERF1EbYyGyABN9xwwzm9T6vX4v8tvRWjJo1GoeEY3n70LXz+941tfr/FYkFeXh6bfSIKCDb6RNQjCCHwXeX3OG4qhh56SG4JfVKzOegeERE147A7AAHcteRuDB0x9JzeKyCgOBUgTIObHp6NOYvmQFOjgYSzXxaWfzAf9992H2w2Gxt9IgoINvpEFPJ8ig/bS3fgqLMQALD29Y8wdcJUaNLY5BO1Ra23Ftcv/19AANfpr4NBYwh2SUSqS8/qhZxBOef8PiEEyuvKUVZbDiVCIDIuHGnWNI4BQ0Sdinu5RBTSarw1+KRwHY46CyFBQkpdMt5/+r1Wj64Q0ckE8svzkV+RH+xCiLo8SZKQaE5EmjUVAFDlrUaB8whkIQe5MiLqSdjoE1HIOuooxH+Ofooabw3MWjPG9xqHaH9UsMsiIqIeIMYYg95hGZAgwelz4rA9H17ZG+yyiKiHYKNPRCFHFjJ2VezGFyVb4Rd+JJoTMCljIhLMCcEujYiIepAIQwSyI7Kgk3Sok+tw0H4ILp8r2GURUQ/Aa/SJKKTYvXZ8WfJfVHpOAAAGRudgSNxgDrpHRERBYdFZ0CeyD446jqBWrkO+owCp1hTEGGOCXRoRhTA2+kQUEoQQOGzPx87yb+AXfhg0BoxOHIn0cI5eTEREwWXQ6JEdkY1jriLUeGtQ5DqOWn8dki1J/CCaiFTBRp+Iur06uQ5fle1EYcOo+onmRFycNBpWvTXIlREREdXTSBqkW3uhXGtEWW05Kj2VqPW7kR7GD6SJKPDY6BNRtyWEQIHjCL6p2AWP7IEECYPjBmFgdA6PkBAFlITkqBQAItiFEHVrjSPym7VmHHMdg1uuxUH7IcDEf1tEFFhs9ImoW3L4nPi67GsUu0sAAFGGKFyUNAqxptggV0YUeswGMz655xP4fX6sfe2jYJdD1O1FGCLQV9sXR52FqJVrgXjgNwuvgeCHaUQUIGz0iahbkRUZedU/4fvKvZCFDI2kwQUx5+O8mIE8ik9ERN2GQWtAdkQWStwlqPScwJTbrkS+fAR9vH0RaYgIdnlE1M2x0SeioCssLITNZjvrPAICdp0dZYYK+DQ+AIDFb0GKJwk+hxd7ju5pU1ZeXl5HyyUiIgoIjaRBqjUV1cerUaOzA1HAx0f/g2HxQ9Avsh8kSQp2iUTUTbHRJ6KgKiwsRE5ODtxu9xnn6TesH667+3/RZ3AfAEBlSSVWP/c+tv37v+3OdTod7X4vUU9T56vDnFfnAELgKukq6CV9sEsiCimaWg3u/9/F+L9Nb8Clc+Hr8m9Q5DyOUYkjObAsEbULG30iCiqbzQa3243HXn4cWX2zmr2mGAWUCAWicZAiBdDYNUiUE3D77bfj9ttvP+e8rRu34i9LlqPOUxeI8ol6BCEU/Hj8BwDA1JSpAA8yEgVcVXkVMup6wZoZht22b1HsLsGHR9ZiSNxg9Ivqy8vTiOicsNEnoi4hq28WcgblQAgBl9+FstpyuPyuptdjjDFINCdAH9exI4kFBws6WioREZEqJEgYEN0fyZYkbC/7ChV1FdhZ8Q0KHAUYlTgK0caoYJdIRN0EG30i6hIEBKo8Vaios6FOrj/aLkFCtDEaCaZ4GLSGIFdIRETUOSKNkcjtdQUO1BzEt7ZvYaurxMdH/4OB0Tk4P/YX0Gt4+QwRnR0bfSIKKj/8+J+5k+FPkXHMVQSgvsGPMUYjng0+ERH1UJIkoX9UP6RZ0/B1+U4UuYrwQ9WPyLfnY2j8EGSGZ3KwPiI6Izb6RNTphBCoqKvAgeqDOGI9imt/Px0AoJN0iDPFIsYYA52GqyciIiKr3oIxqZeiyHkc31TsgsPnwH9Lt+NA9UEMTxiOOFNssEskoi6Ie9JE1Gk8sgdHHEdwoPoQqr3V9RMl4PD3h9EvtS8G9OnPwYaIiIhakBaWimRLEvKqf8Leyn2oqLPhk8JPkRGWjsFxgxBhiAh2iUTUhbDRJyJVCSFQVluGQzWHUeg8BlnIAACtpEXv8N4QpTJuvOYG/H3Du2zyibqwaGs0hBDBLoMopOXl5bVpviypN8oMFajR1eCosxBHHYWI9kUj3hcHvWjb7n1cXBzS09M7Ui4RdWFs9IlIFW6/G4dr8nHYfhgOn7NpepQhCn0is5EVkQmj1ojdxbuDWCURtYXZYMGmP26G3+fH2tc+CnY5RCHHVmYDJOCGG244p/f16t8L1yyajsGXDUaVoQqlcik+//tG/GfFx6ix1Zz1vRaLBXl5eWz2iUIUG30iChhFKChyHcehmsModhVDoP7on16jQ+/w3ugT2QexxhgOHkRERHQSh90BCOCuJXdj6Iih5/x+pVyBEqnAaDZi4pxfY+JNv4bGJUFj10BSTt/m5h/Mx/233QebzcZGnyhEsdEnog6ze+04VHMYh+35TbfGA4AEczz6RPRBeng69Bxcj4iI6KzSs3ohZ1BOu94rhIDT50RZbRncqIUSLiDCFUQZohBnioNZZwpwtUTUlXHPm4hOU1hYCJvNdtZ5/JBh19lRo6+BW1vbNF2raBHlj0K0LxJGpxE1FdXYi+oz/py2Xo9IRMFT56vDvJXzIITARDEBeon38CbqaiRJQrghHGH6MDj9TpTVlsPtd6PKW4UqbxXCdGGIM8UiXB8e7FKJqBOw0SeiZgoLC5GTkwO3233aawaTAUPGDMHoyRfhgl8Ogs5QvwpRZAXff/EdNq/ejO+27IHsl8851+l0dLh2IlKHEAp2FXwDAJiQkgvw6huiLkuSJITrwxGuD4fL54LNU4kabw2cfiecTif0Gj3kCAUxSTHBLpWIVMRGn4iasdlscLvdeOzlx5HVNwsCAsIkoFgEhFkAJw+M7wU0bg10bi1G9BmBEYtHAIvPLW/rxq34y5LlqPPUtT4zERERtZlVb4VVb4VX9sLmqcQJzwn4FB8QCTy7aRmOKoWItkcjLSwNeg3P1CEKJWz0ieg0BpMBvc/vjfC0cNR47ZCF8vNrGj2iDFGIMkTBFIDr/QoOFnT4ZxAREdGZGbQGpFiSkWRORI23BkWVRdCYNHBqXPiydBs0kgYplhRkhKcjzZoGg5ZNP1F3x0afiCCEgMPnQKm7FEdNx/CXr16BbFJwwlMFANBJOkQaIhFljIJFa+ao+URERN2QRtIg2hiN0opSLJizAG9+/CY8Vi8cPgeKXEUochVBgoR4czxSrMlItaQg2hjN7T5RN8RGn6gHEkKgxmtHRV0FytxlKHWXoVZuGFBPBxh0BsAPxFpjEGGIQJgujBt5IiKiEFJeWIZEbwKGnDcEVd5qHHUcRaHjGOw+O8pry1FeW449+A5GrRHxpngkmOMRb45DrDEWWo022OUTUSvY6BOFOEUocPicqPZU4YSnCrZaGyo9lfAp/mbzaSQN4k1xENUCt1zzWyxd/iRSB6UGqWoiIiJS26l3vumFVHileDi1Tjh1Lri0LnhkT9PRfgCQhASTYoJFNtc/FAt0ovWWIi4uDunp6aosBxGdjo0+URfXllvdAYCAgFfywaPxwKPxwKvxoq7huZDEafNLQoJZqd9IW2UrLLIZGocGeXl5OLb/GCQOq01EJzHpeQ9uolBhK7MBEnDDDTecdT6dXofev8hE3yF96x9D+yEyLhK12lrUamtR2fjzjttQsC8fR344giM/FKDghwI4q5zNfpbFYkFeXh6bfaJOwkafqAtr6VZ3BpMBSb2TkJKdipTsFKRkpyA5MwVJmUnQG1oePMfjrkPRwSIU/lSIgr35OPz9YRw/dByKrLQ4P8Db3RHRz8wGC3b86Sv4fX6sfe2jYJdDRB3ksDsAAdy15G4MHTG0ze8TtQIoBoRRQBgFFIMA9EBcahziUuMwIvfCn2f2A5JXguSVUHakFA/d+iBsNhsbfaJOwkafqAsSQqBOrsPRE0cxcvIo/OaW3yAiLhJCL87+r1ZB/YbVJ0HyS5B89c91fisGxAzAgIsGABedPZu3uyMiIuoZ0rN6IWdQTod+hixk1Ppr6x9yLdz+WngVL6ADhE5AWATiByfgLztewQHlIOzFTsQaYxBrikGMKQYmLc8WIlIDG32iIFKEAqfPiRqvHXZvTcNXO2q89vqNpAWY/ac5AOpPzW+klbQwao0waY0waowNz03Qa/QdHjSPt7sjIiKittJKWoTpwxCmD2uadmrzX+2qAfSAT+PHMecxHHMea5rXqrMgxhSLaGP9rXujjFEI14dBI2mCsThEIYONPpHKFKHA5XPB4XPC6XPC4XM0NfcOnwOKOPPp83pFj51f7MTQYUOQnJhS39hrjdBp+E+XiDqPx+fB7//2ewhFwWXiMugl3mObiM7s1ObfdTgPs6+cjc++XIfYjDhU1lXiRN0J2H0OuPxuuJzuZs2/RtLU39a34da+jc+teis/ACBqI3YLROfo1MHxBAR8kh8+yQefxtf01Sv54NV44ZN8ONu4dpKQYFQMMChGGBUDjMLY8L0B+/P249n/9zT+vuFdxGbEdMLSERGdThEyvty/FQBwacqlZ12nERG1pM5Vi8IfCmFVrLDCAisskCGjTlOHWm1d02DCdRoPFCio8lShylMFnDxkkAAMQg+9YoBB6GFo2F9qfK7Bzx8CcJR/6unY6BOdhRACXsULl88Fl9+NovIiLH99OSLiIxGbEovY5FhEJ0RDoz37p8tejxcVxypQcawcZcfKUXGsHCUFJSjJL0ZlcSWEOH1U/JNxYDwiIiLqrto6yj8ASJKEuNQ4pPXrhbS+aUjrm4bUfmlI6p0Eg9HQcCDFB1cL77WfsONEyQmcKK2EvcKO2TfMRmpcCiw6K6x6Cyw6C88IoB6jRzf6y5cvx1NPPYXS0lIMGjQIL774Ii688MLW30ghQVZk1Mq1qPXXoa7ha62/Fm65Fm6fCy6/Cy6fG37R/H7zubMnnP7DBAAZkPxSw9fG5xIkP6CTzehtzEDvPhlAn7bXyIHxiIiIqLtr7yj/JxPlAtDWD/DXNNCfDoBOQGgBaIGImAhExESg93m9AQAF/iMoKD3S7OeYtWZY9BZYdRZYdFZYdCaYdWaYdRaYtWaYdSYYNIYOj3lEFGw9ttF/7733sGjRIrzyyisYOXIkli1bhtzcXOzfvx8JCQnBLo8aCCEgIKAIpf4BBYoQUIQMRQgIoeB4STGqqk/UzycJKJAhSwpkSYYiKZDR8FVqnO6HX/JDls58bfyptIoWeqFHnb0O6z78FBOn/BppvdJg0Oih1+ihk3SqbBA4MB4RERGFikCM8n8mfkWGT/HCp/hQWHgM/3pvDaZccyUsURb4NT74JD+EJOoP8si1qETlGX+WJCTohK7hoYW26au26fufn2uhgQbxcfG8VIC6lB7b6D/77LO45ZZbMHv2bADAK6+8go8//hhvvPEG7r333iBXFzyNDbUs5PqHIkMWCmThb5imNEyTT5nn50d1TTVctW4ISWlqvgUUCABCqm/c60eQFyd9j6bpjdPqX29j4Zb2La/P60NNRQ1qbNWorqhGja0G1eXVqCypRGVxJSpLbDhRegI+j6/Z+y678FJEZUe2L5SIiIiIAkqn0UKnMcMMM6ryT+Afz6/GP5atbjZPeEwEYpNjEJMUW/81ORZR8VGIio9CZHwUohOiYY20Qkiifswl+M6Q1pyiKKirqEN0XTTMBjMM2voDQXqNHgaNATqNDjpJB61GC62khU6jq//aME0naSFJEiRoIEkSNJAavpeapjftKYufv5aUlqCquhpN92aSGu/RdIavTa///IrU8P/GrxDNp0mQIAkNNJAQExWD1JS0hmXQQiNpoZU0vByii+qRjb7X68WuXbuwePHipmkajQbjxo3D9u3bg1hZYJW5y3HIfggOpwN13jooTU20csbnbW6sW2MI0M9pgSIr8Pv9kH0yZJ8ffr8Ma5gVer2+fuWkAFAkQAEkgfp7y5/8vQxIcv0p9jqhhQVmJMckATEA+p89m6fSExEREXVt7b5UwA4IhwA0aLgcQEBoAGgBaBqeawChrZ+n8aHRaGAJt8ADDzxejxqLdGbtPNjVHvneI/jmyO7TXxCABhpIouFDiobnDc8anmtOev7zhweN/9V/wND8Ywer1YqY6JiGDzxO+ujh1LNoRfPbUKPp4w2cPk2cPOX0MbKyIjJh1BrP7RfTRfXIRt9ms0GWZSQmJjabnpiYiJ9++um0+T0eDzyen//R1tTUAADsdru6hXZQib0EP5T/0O73+30yfF4f/D4/fHU++Dw++LwNj7qfn/u9fvg8XnjrfPD76ufr/4v+iIyIhKIICFlAKD8/IBo+jRSof974mgCgNLx2yvdonP+Us+1/2LMPa99fizseWoBBQwd14LfVNl6PFwBw8MdDsJisquflH8zv1LxgZDKPeV09k3mAx+8BvA3PPR4okoJvd3zb6kCk7c0LtK74O2Ue84KZ2VPyPHUeuF1uVbOEJPDj9z9i1f+tgsVihslqgjncAnOYCWarBeZwM4xmI3RGHYwmIwwmA/RGPQwmAwwmY8NzPTQaLTRaDTQaDTRaCZJWU/+9pIFWp4UQAorccCmrrEAoChS/gNlqhk6nq292hajvZxv3m9HQzJ48rXG+k0hSw/8am2mpYRokSJr6hyz74ZN90BsM0Bv00Bm0qv5eAQDVDY9OZOllQbQxqnNDz0Fj/9naQN4AIIm2zBViiouLkZqaim3btmH06NFN0++++25s2bIFX331VbP5H374YTzyyCOdXSYRERERERFRM8eOHUNaWtpZ5+mRR/Tj4uKg1WpRVlbWbHpZWRmSkpJOm3/x4sVYtGhR0/eKouDEiROIjY0NmRE57XY7evXqhWPHjiEiIiJkM4OV21Myg5XLZQ3NXC5raOZyWUMzl8samrlc1tDM5bJ231whBBwOB1JSUlqdt0c2+gaDAcOGDcPGjRsxdepUAPXN+8aNGzF//vzT5jcajTAam1+rERUV1QmVdr6IiIhO/UcQrMxg5faUzGDlcllDM5fLGpq5XNbQzOWyhmYulzU0c7ms3TM3MrJtA4L3yEYfABYtWoRZs2Zh+PDhuPDCC7Fs2TK4XK6mUfiJiIiIiIiIuqMe2+hPnz4dFRUVePDBB1FaWorBgwfj008/PW2APiIiIiIiIqLupMc2+gAwf/78Fk/V74mMRiMeeuih0y5RCLXMYOX2lMxg5XJZQzOXyxqauVzW0MzlsoZmLpc1NHO5rKGbe7IeOeo+ERERERERUag69xvgEhEREREREVGXxUafiIiIiIiIKISw0SciIiIiIiIKIWz0iYiIiIiIiEIIG/0e6IMPPsD48eMRGxsLSZKwZ8+eZq+fOHECt99+O/r37w+z2Yz09HTccccdqKmpUS0TAF577TVcdtlliIiIgCRJqK6ubnfeueTW1dVh3rx5iI2NRVhYGKZNm4aysrIOZ5+srKwMN910E1JSUmCxWDBhwgQcPHgwoBmncjqdmD9/PtLS0mA2mzFw4EC88sorqmYCgCRJLT6eeuopVXPz8vIwZcoUREZGwmq1YsSIESgsLFQ186abbjptOSdMmKBq5sluvfVWSJKEZcuWqZ718MMPY8CAAbBarYiOjsa4cePw1VdfqZbn8/lwzz334Pzzz4fVakVKSgpuvPFGFBcXq5bZqC3rjUBbvnw5evfuDZPJhJEjR+Lrr79WNe+LL77A5MmTkZKSAkmS8K9//UvVPABYsmQJRowYgfDwcCQkJGDq1KnYv3+/6rkvv/wyLrjgAkRERCAiIgKjR4/GJ598onruyZ544glIkoSFCxeqmvPwww+ftk4aMGCAqpkAcPz4cdxwww2IjY2F2WzG+eefj2+++UbVzN69e7e4rZk3b55qmbIs44EHHkBmZibMZjOys7Px6KOPQu1xrR0OBxYuXIiMjAyYzWZcdNFF2LlzZ0AzWlsnCCHw4IMPIjk5GWazGePGjevwfkxrmWqti8+Wq9a2p7VlVWsbey7r+kDtU7SWqda+U1uWNdD7iq1lBmufuBEb/R7I5XLhkksuwdKlS1t8vbi4GMXFxXj66aexb98+vPnmm/j0009x8803q5YJAG63GxMmTMB9993X7pz25N5555346KOPsHr1amzZsgXFxcW4+uqrA1aDEAJTp05Ffn4+/v3vf+Pbb79FRkYGxo0bB5fLFbCcUy1atAiffvopVq1ahby8PCxcuBDz58/Hhx9+qFomAJSUlDR7vPHGG5AkCdOmTVMt8/Dhw7jkkkswYMAAbN68Gd9//z0eeOABmEwm1TIbTZgwodny/v3vf1c9EwDWrFmDHTt2ICUlpVPy+vXrh5deegl79+7Fl19+id69e2P8+PGoqKhQJc/tdmP37t144IEHsHv3bnzwwQfYv38/pkyZokreydqy3gik9957D4sWLcJDDz2E3bt3Y9CgQcjNzUV5eblqmS6XC4MGDcLy5ctVyzjVli1bMG/ePOzYsQPr16+Hz+fD+PHjVV0PAkBaWhqeeOIJ7Nq1C9988w0uv/xyXHnllfjhhx9UzW20c+dOvPrqq7jgggs6Je+8885rtk768ssvVc2rqqrCxRdfDL1ej08++QQ//vgjnnnmGURHR6uau3PnzmbLuX79egDANddco1rm0qVL8fLLL+Oll15CXl4eli5diieffBIvvviiapkA8Nvf/hbr16/HX//6V+zduxfjx4/HuHHjcPz48YBltLZOePLJJ/HCCy/glVdewVdffQWr1Yrc3FzU1dWplqnWuvhsuWpte1pbVrW2sW1d1wdyn6ItmWrsO7WWq8a+YmuZwdgnbkZQj1VQUCAAiG+//bbVed9//31hMBiEz+dTPXPTpk0CgKiqqupQVltyq6urhV6vF6tXr26alpeXJwCI7du3ByR7//79AoDYt29f0zRZlkV8fLx4/fXXA5LRkvPOO0/86U9/ajZt6NCh4v7771ctsyVXXnmluPzyy1XNmD59urjhhhtUzWjJrFmzxJVXXtnpuUVFRSI1NVXs27dPZGRkiOeee67Ta6ipqREAxIYNGzot8+uvvxYAxNGjRzsl71zWkR1x4YUXinnz5jV9L8uySElJEUuWLFE1txEAsWbNmk7JOll5ebkAILZs2dLp2dHR0eL//u//VM9xOByib9++Yv369eLSSy8VCxYsUDXvoYceEoMGDVI141T33HOPuOSSSzo1syULFiwQ2dnZQlEU1TImTZok5syZ02za1VdfLa6//nrVMt1ut9BqtWLt2rXNpqu5PT91naAoikhKShJPPfVU07Tq6mphNBrF3//+d1UyT6bmurgt679Ab3vakqnGNvZMuWruU7SU2Rn7Ti3lqr2v2JY/187YJz4Zj+hTm9TU1CAiIgI6nS7YpQTUrl274PP5MG7cuKZpAwYMQHp6OrZv3x6QDI/HAwDNPjHUaDQwGo2qHmm56KKL8OGHH+L48eMQQmDTpk04cOAAxo8fr1rmqcrKyvDxxx936GyQ1iiKgo8//hj9+vVDbm4uEhISMHLkyE45FRkANm/ejISEBPTv3x+33XYbKisrVc1TFAUzZ87EXXfdhfPOO0/VrDPxer147bXXEBkZiUGDBnVabk1NDSRJQlRUVKdlqs3r9WLXrl3N1kEajQbjxo0L2Dqoq2q8HCwmJqbTMmVZxrvvvguXy4XRo0ernjdv3jxMmjSp2Z+v2g4ePIiUlBRkZWXh+uuvV/0Spg8//BDDhw/HNddcg4SEBAwZMgSvv/66qpmn8nq9WLVqFebMmQNJklTLueiii7Bx40YcOHAAAPDdd9/hyy+/xMSJE1XL9Pv9kGX5tKOOZrNZ9bM1GhUUFKC0tLTZ3+PIyEiMHDky5NdTQOdvezpzGxusfYpg7DsFc18R6Jx94lOx0adW2Ww2PProo5g7d26wSwm40tJSGAyG01beiYmJKC0tDUhG4wcHixcvRlVVFbxeL5YuXYqioiKUlJQEJKMlL774IgYOHIi0tDQYDAZMmDABy5cvx69+9SvVMk/11ltvITw8PKCXQpyqvLwcTqcTTzzxBCZMmIDPPvsMV111Fa6++mps2bJFtVyg/tSzt99+Gxs3bsTSpUuxZcsWTJw4EbIsq5a5dOlS6HQ63HHHHaplnMnatWsRFhYGk8mE5557DuvXr0dcXFynZNfV1eGee+7BjBkzEBER0SmZncFms0GWZSQmJjabHsh1UFekKAoWLlyIiy++GL/4xS9Uz9u7dy/CwsJgNBpx6623Ys2aNRg4cKCqme+++y52796NJUuWqJpzspEjRzZdbvfyyy+joKAAv/zlL+FwOFTLzM/Px8svv4y+ffti3bp1uO2223DHHXfgrbfeUi3zVP/6179QXV2Nm266SdWce++9F9dddx0GDBgAvV6PIUOGYOHChbj++utVywwPD8fo0aPx6KOPori4GLIsY9WqVdi+fbuq+xAna1wX9bT1FNC5255gbGODsU8RjH2nYO4rNuqMfeJTsdEPcX/7298QFhbW9Ni6des5vd9ut2PSpEkYOHAgHn744U7JbK9g5bZWx44dO/DBBx/gwIEDiImJgcViwaZNmzBx4kRoNIH5J9jSsr/44ovYsWMHPvzwQ+zatQvPPPMM5s2bhw0bNgQk80y5J3vjjTdw/fXXB/Ra+VMzGwfzuvLKK3HnnXdi8ODBuPfee/E///M/AR18sKVlve666zBlyhScf/75mDp1KtauXYudO3di8+bNqmRu2bIFzz//PN58801Vj1qd6c91zJgx2LNnD7Zt24YJEybg2muvDdh15Gf7u+Tz+XDttddCCIGXX345IHltySX1zJs3D/v27cO7777bKXn9+/fHnj178NVXX+G2227DrFmz8OOPP6qWd+zYMSxYsAB/+9vfOmWskEYTJ07ENddcgwsuuAC5ubn4z3/+g+rqarz//vuqZSqKgqFDh+Lxxx/HkCFDMHfuXNxyyy2dMvhroxUrVmDixImqj1ny/vvv429/+xveeecd7N69G2+99Raefvpp1T/U+Otf/wohBFJTU2E0GvHCCy9gxowZAduHoJapue1piZrb2Jbs2rWrU/YpTqX2vlNLFEUBoP6+4tmosU/cmtA6D5tOM2XKFIwcObLp+9TU1Da/1+FwYMKECQgPD8eaNWug1+tVz+yI9uQmJSXB6/Wiurq62VH9srIyJCUlBawOs9mMPXv2oKamBl6vF/Hx8Rg5ciSGDx/eroy2ZI4dOxZr1qzBpEmTAAAXXHAB9uzZg6effjpgp5Ge7Xe+detW7N+/H++9915Ass6UGR8fD51Od9rRuZycnICe1tiWv19ZWVmIi4vDoUOHMHbs2IBnrl69GuXl5UhPT2+aJssyfv/732PZsmU4cuRIhzNbym1cVqvVij59+qBPnz4YNWoU+vbtixUrVmDx4sWqZTbuaB09ehSff/55wI+oBGt91SguLg5arfa0O310ZB3U1c2fPx9r167FF198gbS0tE7JNBgM6NOnDwBg2LBh2LlzJ55//nm8+uqrquTt2rUL5eXlGDp0aNM0WZbxxRdf4KWXXoLH44FWq1Ul+2RRUVHo168fDh06pFpGcnJyi+vff/7zn6plnuzo0aPYsGEDPvjgA9Wz7rrrrqaj+gBw/vnn4+jRo1iyZAlmzZqlWm52dja2bNkCl8sFu92O5ORkTJ8+HVlZWaplnqxxXVRWVobk5OSm6WVlZRg8eHCn1NDZ1N72tETNbWxLtm7d2in7FK0J9L5TS+Li4jplX/FM1Nonbg0b/RAXHh6O8PDwc36f3W5Hbm4ujEYjPvzww3P69Km9mR3Vntxhw4ZBr9dj48aNTSNg7t+/H4WFhe2+fvNsdURGRgKov4bym2++waOPPtqujNYy7XY7fD7faZ/2a7Xapk811cg92YoVKzBs2LCAX1/WUuaIESNOu03XgQMHkJGRoWruqYqKilBZWdlsRyiQmXPnzsXkyZObzZObm4uZM2di9uzZAclsKfdMFEVpGoNCjczGHa2DBw9i06ZNiI2NDUhWa7mdyWAwYNiwYdi4cSOmTp0KoP73unHjRsyfPz9odalBCIHbb78da9aswebNm5GZmRm0WgL5d7clY8eOxd69e5tNmz17NgYMGIB77rmnU5p8oP42q4cPH8bMmTNVy7j44otVX/+ezcqVK5GQkND0obaa3G636tvVs7FarbBaraiqqsK6devw5JNPdkpuZmYmkpKSsHHjxqbG3m63N50hE2o6Y9vTFmqvp2bOnHnagR819ilaE+h9p5YYDIZO2Vc8E7X2iVvDRr8HOnHiBAoLC5vuCdr4lz4pKQlJSUmw2+0YP3483G43Vq1aBbvdDrvdDqD+6Gl7dlBaywTqrwErLS1tOvKwd+9ehIeHIz09vd2DNbWWGxkZiZtvvhmLFi1CTEwMIiIicPvtt2P06NEYNWpUuzJbsnr1asTHxyM9PR179+7FggULMHXqVNUGxouIiMCll16Ku+66C2azGRkZGdiyZQvefvttPPvss6pknsxut2P16tV45plnVM8C6o+yTJ8+Hb/61a8wZswYfPrpp/joo49UPQ3M6XTikUcewbRp05CUlITDhw/j7rvvRp8+fZCbm6tKZmxs7Gk7HHq9HklJSejfv78qmUD97WMee+wxTJkyBcnJybDZbFi+fDmOHz+u2q2sfD4ffvOb32D37t1Yu3YtZFluuhY0JiYGBoNBlVygbeurQFq0aBFmzZqF4cOH48ILL8SyZcvgcrlU3dFyOp3NjvIWFBRgz549iImJaXZ0J5DmzZuHd955B//+978RHh7e9OcZGRkJs9msSiYALF68GBMnTkR6ejocDgfeeecdbN68GevWrVMtMzw8/LSxB6xWK2JjY1Udk+APf/gDJk+ejIyMDBQXF+Ohhx6CVqvFjBkzVMu88847cdFFF+Hxxx/Htddei6+//hqvvfYaXnvtNdUyGymKgpUrV2LWrFmdMljw5MmT8dhjjyE9PR3nnXcevv32Wzz77LOYM2eOqrnr1q2DEAL9+/fHoUOHcNddd2HAgAEBXUe0tk5YuHAh/vznP6Nv377IzMzEAw88gJSUlKYPKNXIVGtdfLbc5ORkVbY9Z8uMjY1VbRvb2u9YjX2Ks2XGxMSotu/U2rKqsa/Ylm1pZ+8TN9Np4/tTl7Fy5UoB4LTHQw89JIT4+fZ2LT0KCgpUyRSi/rZALc2zcuVK1ZZVCCFqa2vF7373OxEdHS0sFou46qqrRElJSbszW/L888+LtLQ0odfrRXp6uvjjH/8oPB5PQDNOVVJSIm666SaRkpIiTCaT6N+/v3jmmWdUvfVQo1dffVWYzWZRXV2telajFStWiD59+giTySQGDRok/vWvf6ma53a7xfjx40V8fLzQ6/UiIyND3HLLLaK0tFTV3FN1xu31amtrxVVXXSVSUlKEwWAQycnJYsqUKeLrr79WLbPxdkotPTZt2qRarhBtW28E2osvvijS09OFwWAQF154odixY4dqWUKceT0/a9Ys1TLP9OfZkXV8W8yZM0dkZGQIg8Eg4uPjxdixY8Vnn32mamZLOuP2etOnTxfJycnCYDCI1NRUMX36dHHo0CFVM4UQ4qOPPhK/+MUvhNFoFAMGDBCvvfaa6plCCLFu3ToBQOzfv79T8ux2u1iwYIFIT08XJpNJZGVlifvvv1/17fl7770nsrKyhMFgEElJSWLevHkB3762tk5QFEU88MADIjExURiNRjF27NgO/95by1RrXXy2XLW2PWfLVHMbe67r+kDsU5wtU819p7Ysa6D3FduSGYx94kaSEEKc/aMAIiIiIiIiIuouOFwnERERERERUQhho09EREREREQUQtjoExEREREREYUQNvpEREREREREIYSNPhEREREREVEIYaNPREREREREFELY6BMRERERERGFEDb6RERERERERCGEjT4RERG12+TJkzFhwoQWX9u6dSskScJ3332HGTNmoFevXjCbzcjJycHzzz9/2vwejwf3338/MjIyYDQa0bt3b7zxxhtqLwIREVHI0QW7ACIiIuq+br75ZkybNg1FRUVIS0tr9trKlSsxfPhw7Nq1CwkJCVi1ahV69eqFbdu2Ye7cudBqtZg/f37T/Ndeey3KysqwYsUK9OnTByUlJVAUpbMXiYiIqNuThBAi2EUQERFR9+T3+5GWlob58+fjj3/8Y9N0p9OJ5ORkPPXUU7j11ltPe9+8efOQl5eHzz//HADw6aef4rrrrkN+fj5iYmI6rX4iIqJQxFP3iYiIqN10Oh1uvPFGvPnmmzj52MHq1ashyzJmzJjR4vtqamqaNfQffvghhg8fjieffBKpqano168f/vCHP6C2tlb1ZSAiIgo1bPSJiIioQ+bMmYPDhw9jy5YtTdNWrlyJadOmITIy8rT5t23bhvfeew9z585tmpafn48vv/wS+/btw5o1a7Bs2TL84x//wO9+97tOWQYiIqJQwlP3iYiIqMMuvvhiZGdn4+2338ahQ4fQt29fbNq0CZdddlmz+fbt24cxY8ZgwYIFzU71Hz9+PLZu3YrS0tKmDwc++OAD/OY3v4HL5YLZbO7MxSEiIurWeESfiIiIOuzmm2/GP//5TzgcDqxcuRLZ2dm49NJLm83z448/YuzYsZg7d26zJh8AkpOTkZqa2uwMgJycHAghUFRU1CnLQEREFCrY6BMREVGHXXvttdBoNHjnnXfw9ttvY86cOZAkqen1H374AWPGjMGsWbPw2GOPnfb+iy++GMXFxXA6nU3TDhw4AI1Gc9po/kRERHR2PHWfiIiIAuK3v/0tPvjgA9jtdhQWFiIlJQVA/en6l19+OXJzc/HUU081za/VahEfHw+gfpT+nJwcjBo1Co888ghsNht++9vf4tJLL8Xrr78elOUhIiLqrnhEn4iIiALi5ptvRlVVFXJzc5uafAD4xz/+gYqKCqxatQrJyclNjxEjRjTNExYWhvXr16O6uhrDhw/H9ddfj8mTJ+OFF14IxqIQERF1azyiT0RERERERBRCeESfiIiIiIiIKISw0SciIiIiIiIKIWz0iYiIiIiIiEIIG30iIiIiIiKiEMJGn4iIiIiIiCiEsNEnIiIiIiIiCiFs9ImIiIiIiIhCCBt9IiIiIiIiohDCRp+IiIiIiIgohLDRJyIiIiIiIgohbPSJiIiIiIiIQggbfSIiIiIiIqIQ8v8BkyGnpT8L3gsAAAAASUVORK5CYII=\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x700 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x700 with 2 Axes>"
            ],
            "image/png": 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vkIcqSb7FMjt37lyr9mf6vawPNf0cV64vUdP2yrOMavo5P1u/HwAQzCj8ASAImaaptWvXSpJ69OhRq+fcfffd2rNnj1599VVNmDBBdrtd7777rsaPH6+uXbv6fRZAeHi4X8+rC9M0a9228kyIhqS2p6tb7Wx8L49XuXBf5Sy7aZq+NwFqs6hfdna2Bg8erB9//FFDhw7VJ598IqfTWW3byn2MGjWq2ts1jhs3Tg6HQ/n5+Vq5cqUfR9P4ne5353Q/x/7+nDeW3w8AaMj4nxQAglDldcmSNGzYsFo/LyUlRbfddpveeust7dy5U1u3blVGRoZ27txZ4+nR9W3Xrl3VPl65OntYWFiVa9UdDockqaCgoNrnVc6sBkrladlHjhyRy+Wqts1PP/1Upa1VKvdfmac6DSWrJP3P//yPoqKitG3bNi1ZskQLFy7Unj17FBcXp6uvvvqUzz18+LAGDx6srVu3asiQIfrPf/5zylv2Vd61oqazNkJCQnx3sqi8tWUgVc5q//DDD7VqX/n9qen3Q6r79/Js/+4AAM4eCn8ACDL5+fmaMmWKJOmyyy6rsthcXXXu3FkPP/ywJGndunVVtlUWCRUVFX73XxvvvPNOtY9X3uP+4osvVkhIiO/xyiJn69atJz2nuLi4xuud/T2eli1b+k6pru76b9M0fY8PGjSoTn0H2oABA2Sz2bRu3TqtX7/+pO2HDh3yXWtudVbp2Cnildepv/HGG75F/a6//vpTFvE5OTkaPHiwNm/erCFDhujTTz897dkKlT83K1asqHb7tm3bfG+mner0en9V3jZy7ty5Onjw4Gnbn3feeYqKilJubq7+85//nLT9+Fse1vZ7earfnczMzLN6a0AAQGBR+ANAkDBNU59//rkuuOACbd++XWlpaTWuIn+ir776SnPnzj1pVW3TNPXZZ59Jklq3bl1lW8uWLSVJmzdvDkD6mq1evVrPPfdclce+++4734rmlW9yVBo6dKgkacaMGVWubS4qKtLtt99e4wrglcezZcuWOmf8zW9+I0l66qmnqhTUpmnqD3/4g9atW6e4uDjddtttde47kFq1aqVf/vKXMk1Tv/71r6usjVD5+pSWlurCCy/UhRdeaGHS/6o8pf/999/33bP9VKf55+bmasiQIdq0aZOGDh1aq6JfOnYqvyQtXbpUzz//fJXLR7Kzs337POecc3Teeef5fTw16dWrl8aMGaOSkhKNGTPGdwZCpYqKiioFflhYmCZNmiRJeuCBB6rMxpeXl+vee+9VZmam2rZt6zu206n83fnTn/5UZR2Dw4cPa8KECSosLPT38AAAFgs5fRMAQEPz+uuva9GiRZKksrIy5eTkaM2aNb5TkAcOHKg33njjpGK9Jhs2bNCUKVMUExOjPn36qHnz5iopKdGaNWu0Z88excbG6sknn6zynLFjx+rrr7/W+PHjNWzYMMXHx0uSHnzwQXXq1Clgx3rPPfdo6tSpevvtt9WzZ08dPHhQ3377rbxer+69996TVgr/n//5H/3lL3/RqlWr1K1bN1188cXyer1atWqVHA6Hbr755mpvEde/f381b95ca9euVZ8+fdSjRw+FhoaqU6dOvtvA1eTXv/61li5dqn/+858677zzdOmllyo5OVlr1qzRtm3bFB4ertmzZ6tZs2YBe138NWPGDP3www9asWKF2rdvr0GDBikkJESLFy/W4cOH1bZtW82aNcvqmD79+/dX165dfW/I9OrVS3369Kmx/a233qoNGzbIMAwlJCTozjvvrLbdlVdeqSuvvNL39ahRo/TrX/9af//73/XQQw/p1VdfVc+ePVVQUKAVK1bI5XIpLi5O//znP+vtmvOZM2dq1KhRWr58uTp27KgLL7xQzZs3V2ZmpjZu3KjDhw9XeUPiiSee0KpVq7Rw4UJ16dJFgwYNUnR0tJYtW6a9e/cqMTFRH3zwge9sltOZNGmSXnvtNa1Zs0adOnVSRkaGioqKtHLlSrVq1UpXXnmlPvnkk3o5dgBA/aLwB4BGaMmSJVqyZIkkKTIyUrGxserRo4fOO+88XXPNNTr//PPr1N/ll1+u/Px8ffvtt9q+fbuWL1+u8PBwpaen63//9381adIk34x4pTvvvFMFBQV65513NHfuXN/K2uPHjw9o4X/VVVdpzJgxeuaZZzR37ly53W716dNHkydPrvb2eaGhoVqwYIF+97vf6ZNPPtH8+fOVnJysq666Sk899ZReeumlavfjcDj0xRdf6Le//a2WLVum9evXy+v16tJLLz1t4W8Yht5++22NHDlSr776qlavXq2ioiKlpqbqpptu0v/+7/8G9DU5E4mJiVq6dKlefPFFvffee5o/f768Xq/atm2r2267Tb/5zW98b+I0FLfccoseeOABSdLNN998yraVb36Zpqn333+/xnZt2rSpUvhL0iuvvKKRI0fqH//4h1atWqVPP/3Udzu64cOH6/777z/p9yCQ4uPjtXjxYr3xxhuaPXu21q1bp6VLlyo5OVm9evU6Ka/T6dS8efP02muv6e2339a3336rsrIypaen6+6779bDDz9cp7Ua4uLitGTJEj3yyCOaN2+ePv/8c7Vo0UK33367HnvsMU2ePDnARwwAOFsMsy5LIQMAAAAAgEaFa/wBAAAAAAhiFP4AAAAAAAQxCn8AAAAAAIIYhT8AAAAAAEGMwh8AAAAAgCBG4Q8AAAAAQBCj8AcAAAAAIIhR+AMAAAAAEMQo/AEAAAAACGIU/gAAAAAABDEKfwAAAAAAghiFPwAAAAAAQYzCHwAAAACAIEbhDwAAAABAEKPwBwAAAAAgiFH4AwAAAAAQxCj8AQAAAAAIYhT+AAAAAAAEMQp/AAAAAACCGIU/AAAAAABBjMIfAAAAAIAgRuEPAAAAAEAQo/AHAAAAACCIUfgDAAAAABDEKPwBAAAAAAhiFP4AAAAAAAQxCn8AAAAAAIIYhT8AAAAAAEGMwh8AAAAAgCBG4Q8AAAAAQBCj8AcAAAAAIIhR+AMAAAAAEMQo/AEAAAAACGIU/gAAAAAABDEKfwAAAAAAghiFPwAAAAAAQYzCHwAAAACAIEbhDwAAAABAEKPwBwAAAAAgiFH4AwAAAAAQxCj8AQAAAAAIYhT+AAAAAAAEMQp/AAAAAACCGIU/AAAAAABBjMIfAAAAAIAgRuEPAAAAAEAQo/AHAAAAACCIUfgDAAAAABDEKPwBAAAAAAhiFP4AAAAAAAQxCn8AAAAAAIIYhT8AAAAAAEEsxOoAjZHX69XBgwcVHR0twzCsjgMAAAAACHKmaaqgoEDNmzeXzVa3OXwKfz8cPHhQ6enpVscAAAAAADQx+/btU8uWLev0HAp/P0RHR0s69oLHxMRYnAYAAAAAEOxcLpfS09N99WhdUPj7ofL0/piYGAp/AAAAAMBZ48/l5izuBwAAAABAEKPwBwAAAAAgiFH4AwAAAAAQxCj8AQAAAAAIYhT+AAAAAAAEMQp/AAAAAACCGIU/AAAAAABBjMIfAAAAAIAgRuEPAAAAAEAQC7E6AAAAqD3TNOV2u62O0WAc/3o4HA4ZhmFxooaB1wIAcDwKfwAAGhG32617773X6hho4KZPny6n02l1DABAA8Gp/gAAAAAABDFm/AEAaKQevDBcDrvVKazl9ph6fmmpJOnBC8PksDfd09vdHun5pSVWxwAANEAU/gAANFIOu5p0oXsih91o4q+HaXUAAEADxan+AAAAAAAEMQp/AAAAAACCGIU/AAAAAABBjMIfAAAAAIAgRuEPAAAAAEAQo/AHAAAAACCIUfgDAAAAABDEKPwBAAAAAAhiFP4AAAAAAAQxCn8AAAAAAIIYhT8AAAAAAEGMwh8AAAAAgCBG4Q8AAAAAQBCj8AcAAAAAIIhR+AMAAAAAEMQo/AEAAAAACGIU/gAAAAAABDEKfwAAAAAAghiFPwAAAAAAQYzCHwAAAACAIEbhDwAAAABAEKPwBwAAAAAgiFH4AwAAAAAQxCj8AQAAAAAIYhT+AAAAAAAEsRCrAwBAJdM05Xa7JUkOh0OGYVicCAAABBPGGmiqmPEH0GC43W7de++9uvfee31/lAEAAAKFsQaaKgp/AAAAAACCGIU/AAAAAABBjMIfAAAAAIAgRuEPAAAAAEAQo/AHAAAAACCIUfgDAAAAABDEKPwBAAAAAAhiFP4AAAAAAAQxCn8AAAAAAIIYhT8AAAAAAEGMwh8AAAAAgCBG4Q8AAAAAQBCj8AcAAAAAIIhR+AMAAAAAEMQo/AEAAAAACGIU/gAAAAAABDEKfwAAAAAAghiFPwAAAAAAQYzCHwAAAACAIEbhDwAAAABAEKPwBwAAAAAgiFH4AwAAAAAQxCj8AQAAAAAIYhT+AAAAAAAEsRCrA6D+bNiwQe+++66uvfZa9ezZ0+o4fqvLcZyubW362rBhg95++21J0oQJE6q0q0v/kvzqx5/v23/+8x99/vnncjqdGjx4sJYvX67+/fvrm2++UUVFhSTJ4/GooqJCffr00ebNm1VaWqqwsDDdfPPN6tmzZ7X73bBhg9544w2VlpbKbrfL4/HI4XDI4XAoJSVFO3furJLDbrfL6/UqNjZWeXl5kqSQkBBfBkkyDEOmacpms8k0TfXp00fbtm1TWVmZysvLa3W8AAAAZ+ree++VzWaT1+ut9XNOHDtVjpMkqW/fvtq2bZvcbrfcbrev/eDBgzV//nxVVFTIZrPJbrf7xjyV46L27dvrwIEDvr4kyeFw6NZbb5V0bExZVlamiooKjRw5UpKqjP2++eabKtuvuOIKSdWPKyvHuhUVFVXGh9u2bZN0bNwq6YzriBP3feI4+d133/WNVyv3W5fxck3j7NPlaKqY8Q9Sbrdbs2fPVm5urmbPnu37z6exqctxnK5tbfpyu92aNWuWCgsLVVhYqFmzZvna1aX/WbNm6Z133qlzP/583woLC/X555/LNE2Vlpbq888/V25urj7//HMVFhaqtLRUpaWlKi8vl2maWr16te+PSmlpqS/nift1u9165513fG09Ho8vY2Fh4UlFf2Ub0zR9Rb+kKkW/JJmmKUnyer2+PIWFhScV/Y31ZxbA2ZcXm6c1567RWu8Rq6MAaGTqUvRLVcdOx4+TJPnGNMePYUpLSzV37lzfeMjr9VYZ81SOi3bu3FmlL+nYWOif//ynb3+VY7m5c+dWGfvNnTu3yvbKMWB148rjx7onjg8rx63vvPOOZs2adUZ1xIn7Pn6sOWvWLF//lVnrOl6uabx+uhxNeXxJ4R+k5s2bp/z8fElSfn6+5s2bZ3Ei/9TlOE7XtjZ9Hd/mxHZ17d/lctW5H3++b6+88orvj4b03z8gxz92Ki6XS6+88spJ+503b16VYzjbvvzyS8v2DaDxME1Te1rtUUlEid707qj1/30A4K/KsdPZGCcVFBRUu59T/V9nmqZeeeWVaseVJ451q+Nyuc64jjhx3yeONSs/P/44/Bkvny5jsNREgcCp/kEoOztb8+bNq1IAfvHFF+rfv7+Sk5MtTld7dTmO07WtTV/Z2dn6/PPPT8oxb948dezYsU79V+d0/VS2qcv3bevWrdqxY0ftXtBTOL4P0zQ1b968Or8DHmhffPGFzj//fDVr1szSHEBDU1ZW5vv82P8XhnVhGoA1Zq4KowolSdtVoFXmEZ1vJFmcyhrH/w06/ucEwH8tWbIkIP0EYvxVn3bs2BGQ8Z0/dUR14+7avl61HS9X97wTMwZLTRQohslb46dVVlZW5Q+oy+VSenq68vPzFRMTY2Gyk5mmqb/+9a/64Ycfqvxi22w2de7cWXfffbcMo+EPEutyHKdrO3nyZP3tb387ZV+S9OKLL2rr1q3V5omMjFRxcXGVQdXp+q9rP6Zpatu2bbX+vnm9Xj344IMqKio65T4BBK8HLwxTlKPpnrxnmqbucq/QdrNAMo6dxtjRiNHfQi9oFH/rAq3Q7dXzS0tP3xAA6qAudURN4/K6iIyMVElJSbVjYtM0axyvd+nSRffcc49v3YRgqIlO5HK5FBsb61cd2nRHC3Xw7LPPKjY21veRnp5udaQaZWZmasuWLSf9onm9Xm3ZskWZmZkWJaubuhzH6dpu2rTptH1lZmbW+J+IJBUVFZ00m3+6/uvaz9atW+v0fdu0aRNFP4AmbZV5RNtV4DvpwStpm+nSKpNr/QEgUOpSR9Q0Lq+LoqKiGsfEpxqvb9261ZcxWGqiQOJU/1qYOnWq7r//ft/XlTP+DVFqaqq6du1a47tbqampFqarvbocx+nadu/evVZ9denSxa8Z/5r6r2s/p5rxr+771r17d0VGRgZ18X/OOeforrvuapTvyAL1paysTA899JAkKbQJv31vmqberNgpm44V/JVskt6s2KnzQhOb3P8dx/88PPfcc3I6ndaFARogj8ej3/zmN5ZfztjY1KWOqGlcXhdnMuNfmTFYaqJAovCvBafT2Wj+eBqGoWuvvVaPP/74SY9fd911jWYQVJfjOF1bm81Wq76uu+46/f73vz9pRt5ms+m2227Tiy++WGXb6fo/0en6MU2zTt83m82mW2+9VdOnTz/lfv1R11vb1AfDMHTjjTcqLCzM0hxAQ9ZY/k+vD6vMI9pmnrzg1fGz/k3tWv/jfx4a09gFOJuuu+46zZo1y+oYlvB3fFeXOqKmcXltHT9eri5D5Xj5xOOw2Wy6/vrrfRmDpSYKpCY8VxC8kpOTNWLEiCo/+MOHD290i6TV5ThO17Y2fSUnJ/vui3q8ESNGqHPnznXqvzqn68ef71uXLl3UoUOHGrfXVocOHarsd8SIERo1atQZ93smhg0b1uh+ZgGcHZWz/TX9j2vo2Kw/yxgBONEFF1wQkH4CMf6qTx06dNCoUaPOeHznTx1R3Zj2+LHmqdR2vFzd807MGCw1UaBQ+AepESNGKDY2VpIUGxtb7S9IY1CX4zhd29r0dXwbSYqLi/O1q0v/cXFxVRbcqG0//nzf7rjjjpPOgDj+39OJjY3VHXfccdJ+R4wYYenilUOHDrVs3wAatnKZyjZLVVNZb0rKNktVXmMLAPBf5djpbIyTYmJiqt3PqcZ5hmHojjvuqHZceeJYt6Z9nmkdceK+jx9rxsXF+T4//jiO31dtx8unyxgsNVEgUPgHKYfDoeuvv14JCQm6/vrr5XA4rI7kl7ocx+na1qYvh8OhG264QVFRUYqKiqrSrq79jx8/vs79+PN9i4qK0siRI2UYhsLCwjRy5EglJCRo5MiRioqKUlhYmMLCwhQaGirDMNS3b1/f6fNhYWG+4z1xvw6HQ+PHj/e1tdvtvoxRUVFq3779SVnsdrsMw1BcXJzvsZCQqlcUVf4Hb7PZfHmioqIUGhp60usJANVxGDbNcPTTy6H99KL9Ap274Vydu+FcvWi/QC+HHnv8JUc/OQyGOQBOzWar2/8Tx4+djh8nSfKNaY4fw4SFhWnUqFG+8ZDNZqsy5qkcF7Vv3/6kyxsrx2KVY8rKsdyoUaOqjP1GjRpVZXvlGLC6ceXxY90Tx4eV49bx48frhhtuOKM64sR9nzjWrOy/MmtUVJRuuOGGWo+Xjx+vH/+80+VoyuNLbufnhzO5jQKAmpWVlenee++VJE2fPp3rU4FqHP978ttLwuWwN73rFI/n9ph6+tsSSbwex78W/B8KVI+xBhozbucHAAAAAACqReEPAAAAAEAQo/AHAAAAACCIUfgDAAAAABDEKPwBAAAAAAhiFP4AAAAAAAQxCn8AAAAAAIIYhT8AAAAAAEGMwh8AAAAAgCBG4Q8AAAAAQBCj8AcAAAAAIIhR+AMAAAAAEMQo/AEAAAAACGIU/gAAAAAABDEKfwAAAAAAghiFPwAAAAAAQYzCHwAAAACAIEbhDwAAAABAEKPwBwAAAAAgiFH4AwAAAAAQxCj8AQAAAAAIYhT+AAAAAAAEMQp/AAAAAACCGIU/AAAAAABBLMTqAABQyeFwaPr06b7PAQAAAomxBpoqCn8ADYZhGHI6nVbHAAAAQYqxBpoqTvUHAAAAACCIUfgDAAAAABDEKPwBAAAAAAhiFP4AAAAAAAQxCn8AAAAAAIIYhT8AAAAAAEGMwh8AAAAAgCBG4Q8AAAAAQBCj8AcAAAAAIIhR+AMAAAAAEMQo/AEAAAAACGIU/gAAAAAABDEKfwAAAAAAghiFPwAAAAAAQYzCHwAAAACAIEbhDwAAAABAEKPwBwAAAAAgiFH4AwAAAAAQxCj8AQAAAAAIYhT+AAAAAAAEMQp/AAAAAACCGIU/AAAAAABBjMIfAAAAAIAgRuEPAAAAAEAQC7E6AAAA8I/bI0mm1TEs5faY1X7eFB37eQAA4GQU/gAANFLPLy2xOkKD8vzSUqsjAADQIHGqPwAAAAAAQYwZfwAAGhGHw6Hp06dbHaPBME1Tbrdb0rHXxjAMixM1DA6Hw+oIAIAGhMIfAIBGxDAMOZ1Oq2M0KGFhYVZHAACgQeNUfwAAAAAAghiFPwAAAAAAQYzCHwAAAACAIEbhDwAAAABAEKPwBwAAAAAgiFH4AwAAAAAQxCj8AQAAAAAIYhT+AAAAAAAEMQp/AAAAAACCGIU/AAAAAABBjMIfAAAAAIAgFmJ1gMbINE1JksvlsjgJAAAAAKApqKw/K+vRuqDw90NBQYEkKT093eIkAAAAAICm5MiRI4qNja3TcwzTn7cLmjiv16uDBw8qOjpahmFYHadRc7lcSk9P1759+xQTE2N1nIDgmBoHjqlx4JgaB46pceCYGgeOqXEItmMKtuORgvOY8vPz1apVKx09elRxcXF1ei4z/n6w2Wxq2bKl1TGCSkxMTND8QlbimBoHjqlx4JgaB46pceCYGgeOqXEItmMKtuORgvOYbLa6L9XH4n4AAAAAAAQxCn8AAAAAAIIYhT8s5XQ69fvf/15Op9PqKAHDMTUOHFPjwDE1DhxT48AxNQ4cU+MQbMcUbMcjcUwnYnE/AAAAAACCGDP+AAAAAAAEMQp/AAAAAACCGIU/AAAAAABBjMIfAAAAAIAgRuEPAAAAAEAQo/AHAAAAACCIUfgDAAAAABDEKPwBAAAAAAhiFP4AAAAAAAQxCn8AAAAAAIIYhT8AAAAAAEGMwh8AAAAAgCBG4Q8AAAAAQBCj8AcAAAAAIIhR+AMAAAAAEMQo/AEAAAAACGIU/gAAAAAABDEKfwAAAAAAghiFPwAAAAAAQYzCHwAAAACAIEbhDwAAAABAEKPwBwAAAAAgiFH4AwAAAAAQxCj8AQAAAAAIYhT+AAAAAAAEMQp/AAAAAACCGIU/AAAAAABBjMIfAAAAAIAgRuEPAAAAAEAQo/AHAAAAACCIUfgDAAAAABDEKPwBAAAAAAhiFP4AAAAAAAQxCn8AAAAAAIIYhT8AAAAAAEGMwh8AAAAAgCBG4Q8AAAAAQBCj8AcAAAAAIIhR+AMAAAAAEMQo/AEAAAAACGIU/gAAAAAABLEQqwM0Rl6vVwcPHlR0dLQMw7A6DgAAAAAgyJmmqYKCAjVv3lw2W93m8Cn8/XDw4EGlp6dbHQMAAAAA0MTs27dPLVu2rNNzKPz9EB0dLenYCx4TE2NxGgAAmi63260XXnhBkvTAAw/I4XBYnAgAgPrhcrmUnp7uq0frgsLfD5Wn98fExFD4AwBgIbfbrbCwMEnH/i5T+AMAgp0/l5s32MX9/vjHP8owDN13332+x0pLSzVp0iQlJiYqKipKY8eOVVZWVpXn7d27V6NHj1ZERISSk5P14IMPqqKiokqbRYsWqU+fPnI6nerQoYPefPPNs3BEAAAAAACcfQ2y8F+5cqX+/ve/q2fPnlUenzJlij799FN98MEHWrx4sQ4ePKirr77at93j8Wj06NFyu91aunSp3nrrLb355pt67LHHfG127dql0aNHa9CgQVq3bp3uu+8+3Xrrrfriiy/O2vEBAIDAKCor0tMHntbTB55WUVmR1XEAAGiQGlzhX1hYqBtuuEGvvfaa4uPjfY/n5+frH//4h/785z9r8ODB6tu3r2bOnKmlS5dq+fLlkqT58+dry5Yteuedd9SrVy+NHDlSTz31lGbMmCG32y1JeuWVV9S2bVu98MIL6tKliyZPnqxx48Zp2rRplhwvAAA4M+VmucrNcqtjAADQYDW4wn/SpEkaPXq0hg4dWuXx1atXq7y8vMrjnTt3VqtWrbRs2TJJ0rJly9SjRw+lpKT42gwfPlwul0ubN2/2tTmx7+HDh/v6qE5ZWZlcLleVDwAAAAAAGoMGtbjfu+++qzVr1mjlypUnbcvMzJTD4VBcXFyVx1NSUpSZmelrc3zRX7m9ctup2rhcLpWUlCg8PPykfT/77LN64okn/D4uAAAAAACs0mBm/Pft26d7771Xs2bN8q3O21BMnTpV+fn5vo99+/ZZHQkAAAAAgFppMIX/6tWrlZ2drT59+igkJEQhISFavHixXnzxRYWEhCglJUVut1t5eXlVnpeVlaXU1FRJUmpq6kmr/Fd+fbo2MTEx1c72S5LT6fTduo9b+AEAAAAAGpMGU/gPGTJEGzdu1Lp163wf5513nm644Qbf56GhoVq4cKHvOdu2bdPevXuVkZEhScrIyNDGjRuVnZ3ta7NgwQLFxMSoa9euvjbH91HZprIPAAAAAACCSYO5xj86Olrdu3ev8lhkZKQSExN9j99yyy26//77lZCQoJiYGN19993KyMhQ//79JUnDhg1T165ddeONN+q5555TZmamHn30UU2aNElOp1OSdMcdd+hvf/ubHnroId1888366quv9P7772vOnDln94ABAMAZsxk2tXa09n0OAABO1mAK/9qYNm2abDabxo4dq7KyMg0fPlwvvfSSb7vdbtdnn32mO++8UxkZGYqMjNTEiRP15JNP+tq0bdtWc+bM0ZQpUzR9+nS1bNlSr7/+uoYPH27FIQEAgDMQ7gjXr5J/5fscAACczDBN07Q6RGPjcrkUGxur/Px8rvcHAMBCbrdbzz77rKRji/E6HA6LEwEAUD/OpA7lnDgAAAAAAIJYozrVHwAANG0F5YU6WHRQB4sOKaskSwVFLj138DlJUosf0pUak6JW0a3UOrq1Yh2clQcAgEThDwAAGjiP16Pt+Tu0Le9HucpdVbaZkoq9xZIkr+nVUXeejh7J0/ojGxTniFP7mHbqFH+O7IbdguQAADQMFP4AAKBB8ng92uHaqU25m1RcUSJJMmSoWXgzNY9MU/OINJWWlPraj2w5XGUhbu0p2KNDxZnKc+dpdc4a/eT6SRmpGUoMS7DqUAAAsBSFPwAAaFBM09Tugj1am7NWRRXHZvMjQiLUI6Gb2kS3kcP+3wX8jpYf9X0e5YhSenS8OsS2V5mnTHsK9mjdkQ066s7T53vnqXtCN/VI6C67jdl/AEDTQuEPAAAajJKKUn2f/b32Fu6TJIXbw9U9oZs6xnaoU8HutDt1Ttw5So9qpZXZK7WncK825m7SvsJ9Gtj8UkU7ouvrEAAAaHAo/AEAQIOwp2CvVmR/rzJPmQwZ6pHYXd3iuyrE5v9wJTwkTAOaX6I9BXu0Inul8tz5+mLfAg1pOVjxzrjAhQcAoAGj8AcAAJYq91ZoRdYK7SrYLUmKc8TpotQMJQTwmvzW0a3VLDxZC/d/pTx3nubvW6AhLQYpKTwpYPsAAKChslkdAAAANF0F7gLN2/uFdhXsliFD3RO6aVSrEbUu+m2GTc1Dm6t5aHPZjFMPayJCwjUsfaiSwhLl9rq1YP9CZRZnBeIwAABo0JjxBwAAljhQeEDfZS6V2+tWmD1MA9IuUUpEcp36CHeE6/aU232fn47T7tTQlkO06MBiZZZkaeGBrzSo+aVqHtncr2MAAKAxYMYfAACcVaZpasORjfrq4CK5vW41C0vS6NYj61z0+yvUFqrBLQapZWRLeU2vFh/8VkdKj5yVfQMAYAUKfwAAcNZ4vB59l7lU649skCSdE9tRl6UPVURIxFnNYbfZNaD5xUqLSFWFWaGvDixSgbvgrGYAAOBsofAHAABnRZmnTAsPfKXdP1/P3z+ln/qlXCC7Ufvb9J2o2F2saYemadqhaSp2F9fpuXbDrkubD1CCM16lnlItPPC1SipK/c4CAEBDReEPAADqXUF5oebtm6+skmzfqfYdYzuccb+maSrfk698T75M06zz8yuzRIZEqqC8QF8fWKRyb8UZ5wIAoCGh8AcAAPXqSOkRzdv7hVxulyJCIjQ8/TI1j0yzOpZPeEi4hrQcLKfNqSNlR/TtoW/lNb1WxwIAIGBY1R8AANSbQ8WZWnRgsSrMCsU74zW4xcB6u55/w4YNig6P9vv5zW1p2h2+RweKDmrOlrlqXpYmQ0YAE9YsKSlJrVq1Oiv7AgA0PRT+AACgXuwp2KvvMpfIa3qVGpGqgc0HKNQWGtB97N+/3/f50MuGqqLkzE7T7zWot+6bMUV5ofma+feZ+vivH51pxFqJiIjQ1q1bKf4BAPWCwh8AAATcj3k/akX2SklSq6hWujj1Qtlt/i/iV5Pc3Fzf53//8FVFOM/8bAJvvleeBK+umny1xl0/Trai+r0y8qftP+m3dz6inJwcCn8AQL2g8AcAoAnbu3evcnJyAtrn4dAcZTsPS5Liy+MUlRmh9ZnrA7qPStu3b/d9fk63cxQd6f+p/sfLLM5Sdmm2PAletWyVrlhHTED6BQDAChT+AAA0UXv37lWXLl1UXFy32+Cdytj7xmnMnVdKkv790if61/QPA9Z3dULCQtTspmaSFNCr8VPCk1Vuluto2VHtLdyrNtFtFB0aFcA9AABw9lD4AwDQROXk5Ki4uFhPv/yM2nVsd0Z9mTLljfPKG33slnq2PJvGXT5O4y4fF4ioNfp24bdKdh4r/MMc4QHr1zAMtYxoIY/XI1e5S7sLdqttdBtFUfwDABohCn8AAJq4dh3bqcu5Xfx+vmmaOlh8UEfKjl1v3zwiTUkJSYGKd0o//fiTyrPd9dK3YRhqFZWuPYV7VVBeoF0Fu9Uuuq0iQyPrZX8AANSX+l2tBgAABDXTNLW/6ICv6G8Z2UJJYWen6D8bbIZNraNaKSokSqZM7SrYraLyIqtjAQBQJxT+AADAL6Zpam/RPh11H5UkpUemK8GZcFYzuL1uzcicoRmZM1TqLqmXfdgMm9pEt1ZUSKS88mpXwW653K562RcAAPWBwh8AANSZ1/RqT+Fe5bvzZchQ66hWinfGnf0gpnS44rAOVxyWWY+7OVb8t1Hkz8X/7sI9yi7JlmnW514BAAgMCn8AAFAnx4r+PXKVu3xFf6wj1upY9c5m2NQ2uo3vrIbMkiztK9onr+m1OBkAAKdG4Q8AAGrNax471b2gvFCGDLWJbqOYJnSPe5thU8vIFmoR0VySlOfO107XTpVWlFqcDACAmlH4AwCAWqks+osqimSTTe2i2zbZe9snhiWqXXRb2Q27Sjyl+tG1XQeLDsrj9VgdDQCAk1D4AwCA0/KYnv8W/YZNbWO4rV1UaJQ6xnRQTOixMx5yyo5oW/6Pyi3L5dp/AECDQuEPAABOyWN6tPu4or9ddFtFhkRYHatBcNgdahPdWm2j28hpc6rCrND+ogPalv+jckpz5DE5AwAAYL0QqwMAAICGq3Kmv7ii2Ff0RzSkot+QYu2xlZ9aJjo0Wh1jI3Wk9IiyS7Pl9rp1sPiQskqylOBMUKIzUQ67w8KEAICmrEHN+L/88svq2bOnYmJiFBMTo4yMDH3++ee+7QMHDpRhGFU+7rjjjip97N27V6NHj1ZERISSk5P14IMPqqKiokqbRYsWqU+fPnI6nerQoYPefPPNs3F4AAA0Kg2+6JfksDk0JW2KpqRNUZgj3NIsNsOmZuHN1Dmus5pHNJfD5pDH9OpwaY5+yN+mPYV7VVReZGlGAEDT1KBm/Fu2bKk//vGP6tixo0zT1FtvvaUxY8Zo7dq16tatmyTptttu05NPPul7TkTEfwcgHo9Ho0ePVmpqqpYuXapDhw5pwoQJCg0N1TPPPCNJ2rVrl0aPHq077rhDs2bN0sKFC3XrrbcqLS1Nw4cPP7sHDABAA9UYiv6Gym7YlRSWqERnggrKC5RTmqPCiiLlu/OV785XhD1czcKbKSY0RoZh5XkKAICmokEV/pdffnmVr59++mm9/PLLWr58ua/wj4iIUGpqarXPnz9/vrZs2aIvv/xSKSkp6tWrl5566ik9/PDDevzxx+VwOPTKK6+obdu2euGFFyRJXbp00Xfffadp06ZR+AMAoKpFv92wqS1Fv18Mw1CMI0YxjhiVVJQqpzRHee48FXtKtKdwr6JDo9Q8ooXVMQEATUCDOtX/eB6PR++++66KioqUkZHhe3zWrFlKSkpS9+7dNXXqVBUXF/u2LVu2TD169FBKSorvseHDh8vlcmnz5s2+NkOHDq2yr+HDh2vZsmU1ZikrK5PL5aryAQBAMKpa9NvVNrpdgy76y73lejXrVb2a9apKy0utjlOj8JAwpUe1VJe4zkoOayZDhgrKC/Vj/o/yRHtlD7VbHREAEMQa1Iy/JG3cuFEZGRkqLS1VVFSUPv74Y3Xt2lWSdP3116t169Zq3ry5NmzYoIcffljbtm3TRx99JEnKzMysUvRL8n2dmZl5yjYul0slJSUKDz/5+sBnn31WTzzxRMCPFQCAhuTkor+tIkKsvW7+dEzT1MHyg77PG7oQW4hSI1IV74zXgaIDKqwokhln6qmP/iC3UW51PABAkGpwhX+nTp20bt065efn68MPP9TEiRO1ePFide3aVbfffruvXY8ePZSWlqYhQ4Zo586dat++fb1lmjp1qu6//37f1y6XS+np6fW2PwAAzjav6dXugj0nnN7fsIv+xsxpd6ptdFvlufO0z7VfLc9J127vbnV1d1WMI9rqeACAINPgTvV3OBzq0KGD+vbtq2effVbnnnuupk+fXm3bfv36SZJ27NghSUpNTVVWVlaVNpVfV64LUFObmJiYamf7JcnpdPruNFD5AQBAsDBlanfBHhVVFMkmiv6zxTAMxTvjFZJl16Fdh1Ruq9D8fQuUV5ZvdTQAQJBpcIX/ibxer8rKyqrdtm7dOklSWlqaJCkjI0MbN25Udna2r82CBQsUExPju1wgIyNDCxcurNLPggULqqwjAABAUxESGiJPkleFFYU/F/1tGvQ1/cHI8Bh6+oan5PQ4VeIp0fz9C5Rbmmt1LABAEGlQhf/UqVP1zTffaPfu3dq4caOmTp2qRYsW6YYbbtDOnTv11FNPafXq1dq9e7f+85//aMKECRowYIB69uwpSRo2bJi6du2qG2+8UevXr9cXX3yhRx99VJMmTZLT6ZQk3XHHHfrpp5/00EMP6YcfftBLL72k999/X1OmTLHy0AEAOOtMmZr0l8kyw00ZMtQmurUiQyOtjtUkuY641KaklRKdCSrzlGnB/oU6WnbU6lgAgCDRoAr/7OxsTZgwQZ06ddKQIUO0cuVKffHFF7rsssvkcDj05ZdfatiwYercubMeeOABjR07Vp9++qnv+Xa7XZ999pnsdrsyMjI0fvx4TZgwQU8++aSvTdu2bTVnzhwtWLBA5557rl544QW9/vrr3MoPANCkeE2v9jsPqO/Q8yRTahPdRlGhUVbHatJCFKKhLYeoWVgzub1ufXtoiSq8FVbHAgAEgQa1uN8//vGPGrelp6dr8eLFp+2jdevWmjt37inbDBw4UGvXrq1zPgAAgoHX9Gpp5jK5QgtU4a6QM9+h6MTGW/RH2ILn0gSH3aGBzQfosz1zlO/O1+rDa9Qv5QKrYwEAGrkGNeMPAADql2maWp61QrsKdkum9Lf7XpSttPEOBxx2hx5q/pAeav6Qwh3BsSBhWEiYLky9UJL0Y/527Svcb3EiAEBj13j/0gMAgDoxTVPfZ6/UTtdPMmSoZWkLrVm4xupYqEbzyDR1je8iSVqWuVzFFcUWJwIANGYU/gAANBEbczfpx/ztkqQLUzMU6+H2tA1Zr6RzleCMV5m3TEsyl8k0TasjAQAaKQp/AACagB/ztmv9kQ2SpAuSz1e7mLYWJwqMcm+5ZmbP1MzsmSotL7U6TkDZDbsuTrtYdsOuzOJM/ZC3zepIAIBGisIfAIAgt7dwn77PXilJ6pHQXZ3izrE4UeCYpqk97j3a494TlDPisY4YndesjyRp/ZENKvOUWZwIANAYUfgDABDEsoqz9e2h72TKVIeY9jo3safVkVBHHWI7KN4Rp3JvuTYc2WR1HABAI0ThDwBAkHK5XVp0cLG8plctI1uqX8oFMgzD6lioI5thU5+fZ/1/zPtRBe4CixMBABobCn8AAIKQ21OuRQcXy+11KyksUZekXSSbwZ/9xqp5ZJqaR6TJK6/W5qyzOg4AoJFhBAAAQJAxTVNLMpco3+1SuD1clza/VCG2EKtj4Qz1adZbhgztKdyrwyWHrY4DAGhEKPwBAAgy646s1/6iA7IZNg1scakiQsKtjoQAiHfGq11MO0nS6sNrgnIxQwBA/aDwBwAgiOwu2K1NuZslSRkp/ZUUlmhxovoXaoQq1Ai1OsZZ0Suxp+yGXYdLc7S3cJ/VcQAAjQTn/QEAECTyyvK0NHO5JKlrfBe1i2lrcaL657A79NsWv5UkhTuC/8yGiNAIdYvvqg25G7UuZ73So1qydgMA4LT4SwEAQBDweD369tASeUyP0iJS1Tupl9WRUE+6JnSRw+aQq9yl/YX7rY4DAGgEKPwBAAgCa3LWKs+dpzB7mC5KvZBZ4CAWagtVp7hzJEmbcjdzrT8A4LQYFQAA0MgdKDqgH/K2SZIuTOmv8Ca0mF+5t1yzcmZpVs4slZWXWR3nrOkc10l2w64jZbnKLM60Og4AoIGj8AcAoBErqSjxXdffOa6TWkS1sDjR2WWapraXbtf20u3yml6r45w1YSFh6hDbQZJ8izkCAFATCn8AABop0zS1NHO5Sj2linPEqU9Sb6sj4SzqFt9FhgxllmQppyTH6jgAgAYsYIV/cXGx3njjDb388svas2dPoLoFAAA12J6/XQeLD8pu2HVJ2kWy2+xWR8JZFBkaqbY/37mBWX8AwKn4dTu/W265RStWrNCmTZskSW63W/379/d9HRsbq6+++kq9ezPzAABAfSiuKNGanHWSpN5JvRTnjLM0D6zRPb6rfnL9pH1F+5VXlq84Z6zVkQAADZBfM/5ff/21rr76at/Xs2fP1qZNmzRr1ixt2rRJqampeuKJJwIWEgAAVLUqe5XKveVKdCb6VnhH0xPrjFV6VLokafNRZv0BANXzq/DPzMxUmzZtfF9/8sknOu+883Tdddepa9euuu2227RixYpAZQQAAMfZX3hAewr3ypCh/ikXcOu+Jq57fFdJ0i7XbhWVF1mcBgDQEPk1UoiMjFReXp4kqaKiQosWLdLw4cN926Ojo5Wfnx+QgAAA4L/KvRX6Pvt7SVKX+M5KCEuwOBGslhSepJTwZJkytS3vR6vjAAAaIL+u8e/Tp49ee+01DRo0SP/5z39UUFCgyy+/3Ld9586dSklJCVhIAABwzIYjG1RUUazIkEj1TOxpdRzLOewOPd7ycUlSuCPc2jAW6hLfRVkl2foxf7t6JHZXqC3U6kgAgAbEr8L/6aef1vDhw3XeeefJNE2NGzdOF1xwgW/7xx9/rIsuuihgIQEAgJRbmqutR3+QJPVLPl+hNr/+jCMItYxsoejQaBWUF2hn/k/qHN/J6kgAgAbErxHDeeedpx9++EFLly5VXFycLr30Ut+2vLw83XXXXVUeAwAAZ8Y0TX2fvUqmTLWOaqUWUS2sjoQGxDAMdYnvrO+zV2pr3g86J64jaz8AAHz8nipo1qyZxowZc9LjcXFxuvfee88oFAAAqGpv4T4dLj0su2HXec36Wh2nwSj3luv9I+9Lki4rH6aQ0KZ7FkT7mHZal7NeheWF2l+4X62iW1kdCQDQQJzRX8eCggLt2bNHR48elWmaJ20fMGDAmXQPAAAkebwerclZK0nqFt9VEaERFidqOEzT1JaSLZIkr+m1OI21QmwhOieuozblbtaWoz9Q+AMAfPwq/I8cOaLJkyfrX//6lzwez0nbTdOUYRjVbgMAAHXzQ942FZYXKtwerq4JXa2OgwasU1wnbcndqsOlh3W4JEfNwpOsjgQAaAD8Kvxvu+02ffrpp7rnnnt0ySWXKD4+PtC5AACApNKKUm3M3SRJ6p10Lgv64ZQiQsLVJqaNfnL9pK1Ht6pZ+CVWRwIANAB+jR7mz5+vKVOm6Lnnngt0HgAAcJwNRzaq3FuuBGe82sW0szoOGoEu8Z31k+sn7S3cp8LyQkWFRlkdCQBgMb+We42IiFCbNm0CHAUAABwvvyxfP+ZvlyT1bdZHhmFYnAiNQYIzXqkRqTJl6oe8bVbHAQA0AH4V/uPHj9fHH38c6Cx6+eWX1bNnT8XExCgmJkYZGRn6/PPPfdtLS0s1adIkJSYmKioqSmPHjlVWVlaVPvbu3avRo0crIiJCycnJevDBB1VRUVGlzaJFi9SnTx85nU516NBBb775ZsCPBQCAM7UmZ61MmWoZ2VKpEalWx0Ej0jW+syRpR/4OuT1ui9MAAKzm16n+48aN0+LFizVixAjdfvvtSk9Pl91uP6ldnz596tRvy5Yt9cc//lEdO3aUaZp66623NGbMGK1du1bdunXTlClTNGfOHH3wwQeKjY3V5MmTdfXVV2vJkiWSJI/Ho9GjRys1NVVLly7VoUOHNGHCBIWGhuqZZ56RJO3atUujR4/WHXfcoVmzZmnhwoW69dZblZaWpuHDh/vzcgAAEHA5JTnaX3RAhgz1adbb6jhoZJpHNFesI0b5bpd2uHaqa3wXqyMBACxkmNXdh+80bLb/nihQ3WmHgVzVPyEhQc8//7zGjRunZs2aafbs2Ro3bpwk6YcfflCXLl20bNky9e/fX59//rl+8Ytf6ODBg0pJSZEkvfLKK3r44Yd1+PBhORwOPfzww5ozZ442bdrk28e1116rvLw8zZs3r1aZXC6XYmNjlZ+fr5iYmDM+RgAATrRw/9c6WHxQ7WLa6qLUC+tlH2vWrFHfvn31/758V13ObZyF4Wfvf6birCJJ0lW/vlqhjlCLE9Xd1vVbdd3Qa/XOO++oS5fAfR+OhhzVwbBMhXpD1LG4gwzV/6UiSUlJatWK2wgCQH04kzrUrxn/mTNn+vO0OvF4PPrggw9UVFSkjIwMrV69WuXl5Ro6dKivTefOndWqVStf4b9s2TL16NHDV/RL0vDhw3XnnXdq8+bN6t27t5YtW1alj8o29913X41ZysrKVFZW5vva5XIF7kABAI3W3r17lZOTE/B+i20lOhhxUDIl2yGb1hxcE/B9SNLWrVvrpd+zyTAMOWwO3+eNUU5WjmQcu5QykEKdoZr29V8Ukxirux6dpO8/XxHQ/qsTERGhrVu3UvwDQAPjV+E/ceLEQOfw2bhxozIyMlRaWqqoqCh9/PHH6tq1q9atWyeHw6G4uLgq7VNSUpSZmSlJyszMrFL0V26v3HaqNi6XSyUlJQoPDz8p07PPPqsnnngiUIcIAAgCe/fuVZcuXVRcXBzwvn/z+kPqeUlPffPRN5rwSGCLweoUFhbU+z5QswJXgWRKDz77kPqcX7fLJE/HE+KRV6bu/tPdsj9wX73O+v+0/Sf99s5HlJOTQ+EPAA3MGd8MuLCwUPv27ZMkpaenKyrqzG4Z06lTJ61bt075+fn68MMPNXHiRC1evPhMY56RqVOn6v777/d97XK5lJ6ebmEiAIDVcnJyVFxcrKdffkbtOgbuNntehylPikcypcEZgzTky8EB6/tE3y78Vi89O0OlZaX1to/6VuGt0Me5xxYcHlYxXCGhZzy0sUyrdukBv+SiwluhrXk/yHSaat21tSJDIwPaPwCgcfD7r+PKlSv10EMP6bvvvpPX65V07Nr/Sy65RM8995zOO+88v/p1OBzq0KGDJKlv375auXKlpk+frmuuuUZut1t5eXlVZv2zsrKUmnpspePU1FR9//33VfqrXPX/+DYn3gkgKytLMTEx1c72S5LT6ZTT6fTreAAAwa1dx3YBLdZ+cu1SYUWh4p3xSu/eMmD9VmfX9l312v/Z4DW9Wl+8XpLk8Z752kLBJsQWonhnnHLLjupwaQ6FPwA0UX7dzm/FihUaMGCA1qxZo1tvvVXTpk3TtGnTdOutt2rNmjUaMGDASQW4v7xer8rKytS3b1+FhoZq4cKFvm3btm3T3r17lZGRIUnKyMjQxo0blZ2d7WuzYMECxcTEqGvXrr42x/dR2aayDwAArFJUXqTCikJJUkp4ssVpECySwpIkSa5yl8o8ZadpDQAIRn7N+P/2t79VixYt9N133/lm0is9/vjjuuiii/Tb3/5WCxYsqFO/U6dO1ciRI9WqVSsVFBRo9uzZWrRokb744gvFxsbqlltu0f3336+EhATFxMTo7rvvVkZGhvr37y9JGjZsmLp27aobb7xRzz33nDIzM/Xoo49q0qRJvhn7O+64Q3/729/00EMP6eabb9ZXX32l999/X3PmzPHnpQAAIGCySo69cZ3gjJfD7rA4DYJFmD1M0aFRKigv1OHSHLWMbGF1JADAWeb3jP+vf/3rk4p+6dhCebfffruWL19e536zs7M1YcIEderUSUOGDNHKlSv1xRdf6LLLLpMkTZs2Tb/4xS80duxYDRgwQKmpqfroo498z7fb7frss89kt9uVkZGh8ePHa8KECXryySd9bdq2bas5c+ZowYIFOvfcc/XCCy/o9ddf1/Dhw/14JQAACIzjZ/uTw5jtR2A1C2smSTpadlTl3nKL0wAAzja/ZvxtNpsqKipq3O7xeGSz1f09hX/84x+n3B4WFqYZM2ZoxowZNbZp3bq15s6de8p+Bg4cqLVr19Y5HwAA9SWr5Nj6MwnOBGb7EXCRIZGKCIlQcUWxDpfmqHlEmtWRAABnkV8z/hdeeKFmzJihPXv2nLRt7969eumll3TRRRedcTgAAJqCwvIiFVYUyZCh5J9nZoFAMgzDdyZJbmmuKrw1T+AAAIKPXzP+zzzzjAYMGKDOnTvrqquu0jnnnCPp2GJ7//73vxUSEqJnn302oEEBAAhWlbP98Vzbj3oUHRqlMHuYSj2lyik9otSIFKsjAQDOEr8K/969e2vFihX67W9/q//85z8qLi6WJEVERGjEiBH6wx/+4FtFHwAA1KywvFBFzPb7LdQWqgfTHpQkhYWGWZymYTMMQ8nhydpbuFdHyo6oWXiS7Ibd6lgAgLPAr8Jfkrp27aqPP/5YXq9Xhw8fliQ1a9bMr2v7AQBoikzTZCX/M2QYhiLtkb7PcWqxoTFy2pwq85bpSGmuksN5swkAmoIzrtJtNptSUlKUkpJC0Q8AQB0UVRT5ZvubhbOSP+qfYRhq9nOxn1OaI6/ptTgRAOBsqNWM/5NPPinDMPTb3/5WNputyu3xamIYhn73u9+dcUAAAILRsdn+ypX84+WwhVqcqHGq8FZoztE5kqRhFcMVEur3yYxNRrwjTlklWSr3liu37KiSwhKtjgQAqGe1+uv4+OOPyzAMPfzww3I4HHr88cdP+xwKfwAAalZYUaSiiuJj1/Yz2+83r+nVyqKVkiSP12Nxmsbh2Ar/zXSg+KCyS7KV4IyXzeCsTQAIZrX6X97r9crj8cjhcPi+Pt2Hx8MfXwAAqlN1tj9Bocz24yyLd8Yr1BaqCrNCR8pyrY4DAKhnvL0LAMBZVlhRqGLfbD+Lq+Hssxk2pfx8pkl2SbY8JhM2ABDM/Cr87Xa7Zs+eXeP29957T3Y7t4cBAOBEx6/kn8hsPywU74iXw+aQx/ToSOkRq+MAAOqRX4W/aZqn3O7xeLilDgAA1Sgs/+9sfzNm+2EhwzCUEp4iSTpcepg1EgAgiPl9qn9Nhb3L5dIXX3yhpKQkv0MBABCMjr+2n9l+NARxjliF2Z3ymF4dLj1sdRwAQD2pdeH/xBNPyG63y263yzAMjR8/3vf18R/x8fH65z//qWuvvbY+cwMA0OgUlBeq2FPCbD8ajONn/XNKj6jCW2FxIgBAfaj1zW4vuOAC3XXXXTJNUy+99JIuu+wynXPOOVXaGIahyMhI9e3bV1dffXXAwwIA0FhVme0PS2S2P0BCbCG6N/VeSZIzxGlxmsYpJjRG4fZwlXhKlF16WM0j0qyOBAAIsFoX/iNHjtTIkSMlSUVFRbrjjjvUr1+/egsGAEAwKSgvUEnlbH8Yl8MFis2wKT4k/tjnNm5W5A/DMJQanqJdhbt1pPSIkpyJctgdVscCAARQrQv/482cOTPQOQAACFpVVvJnth8NUFRolKJCIlVYUaTMkiy1ikq3OhIAIID8Kvwr7d+/X2vXrlV+fr68Xu9J2ydMmHAm3QMAEBSOn+1PDuPa/kCq8FZoft58SdLwihEKCT2joU2TZRiGUiPStMO1Q3nuPDWrSFJ4SLjVsQAAAeLXX8fS0lJNnDhR//rXv+T1emUYhu8Wf8ev9k/hDwBo6o6f7U8KS1SIjcI0kLymV0sLl0oSC9OdoYiQcMU5YpXnzteh4ky1i2lrdSQAQID4dTHcI488oo8++khPP/20Fi1aJNM09dZbb2n+/PkaOXKkzj33XK1fvz7QWQEAaHRcP8/222RTM2b70cClhqfKkKHCikIVlBdYHQcAECB+Ff4ffvihfvWrX+nhhx9Wt27dJEktWrTQ0KFD9dlnnykuLk4zZswIaFAAABqbE1fyZ7YfDZ3D7lBiWKIk6VBxpu+MTgBA4+ZX4Z+dna0LLrhAkhQefuz6r6KiIt/2sWPH6qOPPgpAPAAAGi9XuUulntKfZ/tZyR+NQ3JYM9kNm0o9pcpz51kdBwAQAH4V/ikpKTpy5IgkKSIiQvHx8dq2bZtvu8vlUmlpaWASAgDQCHFtPxqrEFuImoUlS5IyS7LkNU9ewBkA0Lj4NQrp16+fvvvuOz388MOSpMsvv1zPP/+80tLS5PV6NW3aNPXv3z+gQQEAaEyOn+1PYrYfjUxSWKKOlB1RubdcOaVHlBzO+hQA0Jj5NeN/zz33qF27diorK5MkPfXUU4qLi9ONN96oiRMnKjY2Vi+++GJAgwIA0Fgw24/GzmbYlBqeIknKLs3mjgkA0Mj5NRK5+OKLdfHFF/u+Tk9P19atW7Vx40bZ7XZ17txZISEMcgAATZNvtt9gtr++hdhCdFfKXZIkZ4jT4jTBJc4Rp8OlOSr1lCq7JFvNI5tbHQkA4Ce/qvP8/HzFxsZWecxms+ncc88NSCgAABqr41fyT3ImMdtfz2yGTcmhx65Ht9n8OpERNTAMQ2kRqdpVsFtHynKVGJYkp91hdSwAgB/8+guZnJysMWPGaPbs2SosLAx0JgAAGq38cpdKPWXM9iMoRIdGKyokSqZMZZZkWh0HAOAnvwr/+++/X5s3b9b48eOVnJyscePG6YMPPlBJSUmg8wEA0GicPNtvtzhR8KvwVujr/K/1df7XKq8otzpOUEqLSJUk5bvzVVxRbHEaAIA//Cr8n332We3YsUMrVqzQXXfdpVWrVumaa65RcnKyrrvuOn3yySdyu92BzgoAQIOW785X2c+z/c2Y7T8rvKZXiwsWa3HBYhagqyfhIeGKd8RJkg4VZ8o0TWsDAQDq7Iwuhjv//PP1f//3f9q9e7eWLFmiW265Rd9++63Gjh2rlJSUQGUEAKDBO34l/2ZhSbIz248gkhKeIkOGiiqKVFBeYHUcAEAdBWzFoYyMDCUlJSk+Pl5//vOf5XK5AtU1AAANXp47X2XeMtkNm5KczPYjuDjsDiWFJepwaY4OlWQqOjRahmFYHQsAUEtnvPztrl279Mc//lF9+vRR586d9Yc//EH9+vXTq6++Wue+nn32WZ1//vmKjo5WcnKyrrzySm3btq1Km4EDB8owjCofd9xxR5U2e/fu1ejRoxUREaHk5GQ9+OCDqqioevrfokWL1KdPHzmdTnXo0EFvvvlmnfMCACAdm+3P/nm2PymsGbP9CErJYcmyG3aVecp01H3U6jgAgDrwa8Z/3759ev/99/Xee+9p9erVMgxDl1xyiWbMmKGxY8eqWbNmfoVZvHixJk2apPPPP18VFRV65JFHNGzYMG3ZskWRkZG+drfddpuefPJJ39cRERG+zz0ej0aPHq3U1FQtXbpUhw4d0oQJExQaGqpnnnlG0rE3K0aPHq077rhDs2bN0sKFC3XrrbcqLS1Nw4cP9ys7AKDpyvfN9tuVFJZodRygXthtdiWHJ+tQ8SFlFmcpzhEnm8EtFAGgMfCr8G/durUMw1D//v01bdo0/fKXv1RaWtoZh5k3b16Vr998800lJydr9erVGjBggO/xiIgIpaamVtvH/PnztWXLFn355ZdKSUlRr1699NRTT+nhhx/W448/LofDoVdeeUVt27bVCy+8IEnq0qWLvvvuO02bNo3CHwBQJ6ZMZZVWzvYnym4w24/glehM0JHSHLm95TpcmqOU8GSrIwEAasGvt2mff/5534J+99xzT0CK/urk5+dLkhISEqo8PmvWLCUlJal79+6aOnWqiov/e2uZZcuWqUePHlUWFxw+fLhcLpc2b97sazN06NAqfQ4fPlzLli2rNkdZWZlcLleVDwAAJMkMN30r+XNtP4KdzbApNfzY5MvhksPcSQEAGok6z/gXFxdr9uzZioyMPOna+kDyer267777dNFFF6l79+6+x6+//nq1bt1azZs314YNG/Twww9r27Zt+uijjyRJmZmZJ91RoPLrzMzMU7ZxuVwqKSlReHh4lW3PPvusnnjiiYAfIwCgcTMMQ54YryQpyclK/lYIsYXotuTbJEmOEIfFaZqGWEeswktzVOIpUVZJtlpENrc6EgDgNOpc+EdERGjXrl31vpLrpEmTtGnTJn333XdVHr/99tt9n/fo0UNpaWkaMmSIdu7cqfbt29dLlqlTp+r+++/3fe1yuZSenl4v+wIANB59hvSVHMdmQZPCmO23gs2wqYWjhSTxxstZYhiG0iJS9VPBLh0pO6KksEQ57U6rYwEATsGvU/1HjBihL774ItBZfCZPnqzPPvtMX3/9tVq2bHnKtv369ZMk7dixQ5KUmpqqrKysKm0qv65cF6CmNjExMSfN9kuS0+lUTExMlQ8AQNNmytSVk66UJCU5ExVC0YkmJCo0StGh0ZKkrJKs07QGAFjNr8L/d7/7nX788UfdeOON+u6773TgwAHl5uae9FFXpmlq8uTJ+vjjj/XVV1+pbdu2p33OunXrJMm3zkBGRoY2btyo7OxsX5sFCxYoJiZGXbt29bVZuHBhlX4WLFigjIyMOmcGADRNBfZCte7aRvKK2X4LVXgrtKRgiZYULFF5RbnVcZqU1PBjl03mufNVUlFqcRoAwKn4tap/t27dJElbtmzR7Nmza2zn8Xjq1O+kSZM0e/Zs/fvf/1Z0dLTvmvzY2FiFh4dr586dmj17tkaNGqXExERt2LBBU6ZM0YABA9SzZ09J0rBhw9S1a1fdeOONeu6555SZmalHH31UkyZNktN57DS0O+64Q3/729/00EMP6eabb9ZXX32l999/X3PmzPHn5QAANDGmaeqwI0eSZCs0FJLk159TBIDX9GpB/gJJ0mPe31ucpmkJDwlXrCNW+e58Zv0BoIHza6Ty2GOP1cs1/i+//LIkaeDAgVUenzlzpm666SY5HA59+eWX+stf/qKioiKlp6dr7NixevTRR31t7Xa7PvvsM915553KyMhQZGSkJk6cqCeffNLXpm3btpozZ46mTJmi6dOnq2XLlnr99de5lR8AoFYOFB1Uqb1UpUWliiqItDoOYJmU8GTlu/PlKncpJJTLXQCgofKr8H/88ccDHOMY0zRPuT09PV2LFy8+bT+tW7fW3LlzT9lm4MCBWrt2bZ3yAQBgmqY2HNkoSfpy9gJdNeIqixMB1gmzhynOEac8d548sV6r4wAAauDXNf4nys/Pr/Np/QAANEYHiw/pSNkRGaahz9/43Oo4gOVSwpMlSWa4qQ69O1qcBgBQHb8L/1WrVmnEiBGKiIhQYmKibyY+JydHY8aM0aJFiwKVEQCABuH42f6E8ngV5LosTgRYz2l3KsEZL0kae+84i9MAAKrjV+G/dOlSXXzxxdq+fbvGjx8vr/e/p3YlJSUpPz9ff//73wMWEgCAhuBQcaZySnNkN+xKLE+0Og7QYCSHJUum1C2jm4rsRVbHAQCcwK/C/5FHHlGXLl20ZcsWPfPMMydtHzRokFasWHHG4QAAaCiOn+3vGNtBoSYr+QOVHHaHbIXHFn7Odhw+7bpNAICzy6/Cf+XKlfrVr34lp9NZ7er+LVq08N2KDwCAYJBZkqXDpYdlM2zqltDV6jj4WYgtRBOTJmpi0kQ5QhxWx2nSbC6b3KVuFdtLdLD4kNVxAADH8avwDw0NrXJ6/4kOHDigqKgov0MBANDQbDxutj8iJMLiNKhkM2xqG9ZWbcPaym7jdnJWMryGvpy1QJK0Lmc9s/4A0ID4Vfj3799fH374YbXbioqKNHPmTF166aVnFAwAgIYiqzhbWSXZx2b747tZHQdosOa89plspqHcslztK9pvdRwAwM/8KvyfeOIJrVq1SqNHj9bnnx+7ldH69ev1+uuvq2/fvjp8+LB+97vfBTQoAABW2Xx0sySpfUw7RYYy29+QeEyPvi/8Xt8Xfq8KT7nVcZq8gqMFSihPkCStZ9YfABoMvwr/fv36ae7cudqxY4cmTJggSXrggQd0++23y+PxaO7cuerZs2dAgwIAYIWjZXk6UHRQktQ1nmv7GxqP16O5eXM1N2+uyj0VVseBpCR3okJtocpz52tP4R6r4wAAJPm9JPHgwYO1bds2rVu3Ttu3b5fX61X79u3Vt2/fahf8AwCgMdqSu0WS1CqqlWIc0RanARo+u+zqGt9F649s0PqcjWoV1Uo2w6+5JgBAgJzxvYh69eqlXr16BSAKAAANS1F5kXYV7JYkdWclf6DWOsd11tajP8hV7tIu1261j21ndSQAaNL8evt13bp1+n//7/9VeeyLL77QgAED1K9fP02fPj0g4QAAsNKWo1tlylRqeIoSwxKtjgM0Gg57qO/Nsg25G+U1a74bFACg/vlV+D/00EN67733fF/v2rVLV111lXbt2iVJuv/++/Xqq68GJiEAABYo85Rpe/4OSVK3BFbyB+rqnLhOCrOHqbC8UDvzf7I6DgA0aX4V/uvXr9fFF1/s+/rtt9+W3W7X2rVrtWLFCo0bN06vvPJKwEICAHC2bcv7UR7To3hnvNIiUq2OAzQ6obYQdf/5TbMNuRvl8XosTgQATZdfhX9+fr4SE/97yuPcuXN12WWXKSkpSZJ02WWXaceOHYFJCADAWVbhrdAPedskSd3iu7JoLeCnjrEdFG4PV3FFsXa4dlodBwCaLL8K/7S0NG3dulWSdOjQIa1evVrDhg3zbS8sLJTNxuqtAIDGaadrp8o8ZYoKjVLr6FZWx8Ep2G12XZ94va5PvF6h9lCr4+AEIbYQ9Ug8Nuu/8cgmVXi55SIAWMGvVf3HjBmjv/71ryotLdWKFSvkdDp11VVX+bavX79e7dqxeisAoPHxml5tOfqDJKlrfGduQ9bA2Q27zgk/R5IUYj/jmxWhHnSI6aBNuVtUXFGs7fk71CW+s9WRAKDJ8Ws084c//EFXX321/vnPfyo7O1tvvvmmUlJSJEkul0sffvhhlTMAAABoLPYU7FVheaGcdqfax7S3Og7Q6NltdvVI6C5J2pS7mVl/ALCAX2+NR0VFadasWTVu279/vyIiIs4oGAAAZ5tpmtp8dIskqXNcJ4XYmEFu6DymR2uL1kqSRnhGKCSU71lD1CG2vTYf3aLC8kJty/tR3X6+1R8A4Ow44/MXTdNUdna2srOzZZqmbDabYmNjFRrKdXYAgMblUHGmjpYdld2wq1PcOVbHQS14vB79++i/9e+j/1a5h5nkhspm2Hyz/ptzt6jcW25xIgBoWvwu/Lds2aJx48YpJiZGaWlpSktLU0xMjMaNG6dNmzYFMiMAAGfF5tzNko6tRO60Oy1OAwSXdjFtFR0arTJvmX44us3qOADQpPh1Pty3336rkSNHyuv1asyYMTrnnGOzItu2bdN//vMfff7555o3b54uueSSgIYFAKC+HCk9osySLBky1DW+i9VxgKBjM2zqmdhDSzKXasvRreoUd44cdofVsQCgSfCr8J8yZYqSk5O1ePFipaenV9m2b98+DRgwQPfff79WrlwZkJAAANS3zbnHru1vE91akaGRFqcBglOb6NbalLtJ+W6Xtub9oHMTe1odCQCaBL9O9d+8ebPuuuuuk4p+SUpPT9edd96pzZs3n3E4AADOBpe7QHsL90kSi44B9ejYrP+xYn/r0R9U5imzOBEANA1+Ff6tW7dWWVnN/1G73e5q3xQAAKAh2nJ0i0yZahHZXPHOeKvjAEGtdVQrxTniVO4t15ajW62OAwBNgl+F/2OPPaYXX3xR69atO2nb2rVr9de//lWPP/74GUYDAKD+lVSUaKfrJ0lSt3hm+4H6ZhiG7xT/H45uU6mn1OJEABD8anWN/z333HPSYykpKerbt68uvPBCdejQQZK0fft2LVu2TN27d9fy5ct13XXXBTYtAAAB9kPeNnlNr5LCEpUcnmx1HNSR3WbXLxN+KUkKtXMr4cYiPaqlEpzxyi07qi25W9WnWW+rIwFAUKtV4f+3v/2txm1LlizRkiVLqjy2ceNGbdq0SdOnTz+zdAAA1KNyb7l+zNsuSeoW302GYVicCHVlN+zqFtFNkhRi92vNYligctb/64OL9UPeNnWJ76zwkHCrYwFA0KrVqf5er7fOHx6Pp76zAwBwRrbn7ZDb61ZMaIzSo1paHQdoUlpEtlBSWKI8pkcbczdZHQcAgppf1/gDANDYeUyPtuYdW1isa0IXZvsbKY/p0ebizdpcvFkVngqr46AODMNQr6Reko69CVfgLrA2EAAEsTM6J27Xrl36/PPPtWfPHknHVvsfOXKk2rZtG5BwAADUl92u3SquKFG4PVztovm71Vh5vB59kPuBJOkez70KU5jFiVAXaRGpSotI06HiQ1p/ZIMuTrvI6kgAEJT8nvF/4IEH1LFjR02ePFnPP/+8nn/+eU2ePFkdO3bUb37zG7/6fPbZZ3X++ecrOjpaycnJuvLKK7Vt27YqbUpLSzVp0iQlJiYqKipKY8eOVVZWVpU2e/fu1ejRoxUREaHk5GQ9+OCDqqioOguwaNEi9enTR06nUx06dNCbb77pV2YAQONjmqY2H90iSeoS30l2m93iREDT1TvpXEnSroLdOlp21OI0ABCc/Cr8X3jhBU2bNk1XX321li1bpry8POXl5WnZsmUaN26cpk2bpmnTptW538WLF2vSpElavny5FixYoPLycg0bNkxFRUW+NlOmTNGnn36qDz74QIsXL9bBgwd19dVX+7Z7PB6NHj1abrdbS5cu1VtvvaU333xTjz32mK/Nrl27NHr0aA0aNEjr1q3Tfffdp1tvvVVffPGFPy8HAKCR2V90QPlul0JtoeoY29HqOECTlhiWqNZRrSRJa3PWWRsGAIKUX6f6v/baa7riiiv0/vvvV3m8X79+evfdd1VaWqq///3vmjJlSp36nTdvXpWv33zzTSUnJ2v16tUaMGCA8vPz9Y9//EOzZ8/W4MGDJUkzZ85Uly5dtHz5cvXv31/z58/Xli1b9OWXXyolJUW9evXSU089pYcffliPP/64HA6HXnnlFbVt21YvvPCCJKlLly767rvvNG3aNA0fPtyflwQA0Ihszt0sSTontqMcdofFaQD0SjpXewv36UDRQWUVZyslgltrAkAg+TXjv3v37lMWyMOHD9fu3bv9zeSTn58vSUpISJAkrV69WuXl5Ro6dKivTefOndWqVSstW7ZMkrRs2TL16NFDKSkpVfK4XC5t3rzZ1+b4PirbVPZxorKyMrlcriofAIDGKbskW4dLc2QzbOoc39nqOAAkxThi1CG2vaRjs/6maVqcCACCi1+Ff3JystavX1/j9vXr16tZs2Z+h5KO3ULwvvvu00UXXaTu3btLkjIzM+VwOBQXF1elbUpKijIzM31tji/6K7dXbjtVG5fLpZKSkpOyPPvss4qNjfV9pKenn9GxAQCsszn32LX97aLbKoL7hgMNRs/EHrIbdh0uPaz9RQesjgMAQcWvwv+Xv/ylXn/9df3xj3+scv19UVGR/vSnP+n111/XNddcc0bBJk2apE2bNundd989o34CYerUqcrPz/d97Nu3z+pIAAA/5JXl+QqKbgldLU4D4HgRIRHqHNdJkrQuZ528ptfiRAAQPPy6xv+pp57SunXr9Mgjj+ixxx5T8+bNJUkHDx5URUWFBg0apCeffNLvUJMnT9Znn32mb775Ri1btvQ9npqaKrfbrby8vCqz/llZWUpNTfW1+f7776v0V7nq//FtTrwTQFZWlmJiYhQefvLsj9PplNPp9Pt4AAANw+ajWyVJraLSFeOIsTgNAsFus2tM/BhJUqj9jO5SjAagW0JXbc/foTx3vnYX7Fa7mHZWRwKAoODXjH9ERIQWLlyojz/+WDfffLO6dOmiLl266Oabb9Ynn3yiL7/8UhEREXXu1zRNTZ48WR9//LG++uortW1b9b7Kffv2VWhoqBYuXOh7bNu2bdq7d68yMjIkSRkZGdq4caOys7N9bRYsWKCYmBh17drV1+b4PirbVPYBAAg+ReVF2uXaJUnqGs9sf7CwG3b1juyt3pG9FWIPtToOzpDT7vSdjbMuZ4M8Xo/FiQAgOJzRW+NjxozRmDFjApVFkyZN0uzZs/Xvf/9b0dHRvmvyY2NjFR4ertjYWN1yyy26//77lZCQoJiYGN19993KyMhQ//79JUnDhg1T165ddeONN+q5555TZmamHn30UU2aNMk3a3/HHXfob3/7mx566CHdfPPN+uqrr/T+++9rzpw5ATsWAEDDsvXoDzJlKiU8Wc3Ck6yOA6AGneM66Yej21RUUaQf87erC4twAsAZ82vGv768/PLLys/P18CBA5WWlub7eO+993xtpk2bpl/84hcaO3asBgwYoNTUVH300Ue+7Xa7XZ999pnsdrsyMjI0fvx4TZgwocqlB23bttWcOXO0YMECnXvuuXrhhRf0+uuvcys/AAhSZZ4ybc/fIYlr+4ONx/Tox5If9WPJj6rwVFgdBwEQYgtRz8QekqSNuZtU7i23OBEANH4N6mK42ty6JSwsTDNmzNCMGTNqbNO6dWvNnTv3lP0MHDhQa9eurXNGAEDj82PedlWYFYpzxKl5RHOr4yCAPF6PZh+ZLUm603OXwhRmcSIEQofY9tpydKsKygu09egPvjcCAAD+aVAz/gAABFqFt0I/5G2TdGy23zAMixMBOB2bYVOvpHMlSVuOblFpRanFiQCgcaPwBwAEte35O1TqKVVkSKTaRLe2Og6AWmod1UoJzgSVeyu0MXeT1XEAoFGrVeH/4osv6scff6zvLAAABJTH69Hm3C2SpO4J3WQzeL8baCwMw1DvpF6Sjl2uU+AusDYQADRitRoBTZkyRatWrfJ9bbfbNXv27HoLBQBAIOxw7VSJp0QRIRFqz/3AgUaneWSa0iLS5JVX646stzoOADRatSr84+PjlZWV5fu6NovwAQBgJY/p0abczZKkbvFdZbfZLU4EwB99fp71312wRzmlR6wNAwCNVK1W9R84cKAef/xxrVu3TrGxsZKkt99+W8uXL6/xOYZhaPr06YFJCQBAHf3k2qXiimKF28PUIba91XEA+CkhLEHtYtrqJ9curTm8Rpe1HMoinQBQR7Uq/F966SXdd999mj9/vrKzs2UYhubPn6/58+fX+BwKfwDAqezdu1c5OTn10rcpU9sjdko2KaY4RhvWbQj4PrZu3RrwPlF3dptdo+JGSZJC7Q3qLsUIoF6J52p3wR5llWTrQNFBtYxqYXUkAGhUavUXMjk5uco1/TabTe+8846uv/76egsGAAhee/fuVZcuXVRcXFwv/V985SW6/U+/lutIvm4dfLPcpe562Y8kFRay4JiV7IZdF0RdIEkKsYdanAZS/b0pluCIV47jiJbuW6r2Je1kqH5m/ZOSktSqVat66RsArOLXW+MzZ87UhRdeGOgsAIAmIicnR8XFxXr65WfUrmNgF90zZaoi1SNJirPH663P3g5o/5W+XfitXnp2hkrLuL84IEk5WTmSIY0fP75e+o+IjtD/LXhBio/W/c8+oG8+XFw/+4mI0NatWyn+AQQVvwr/iRMn+j7fsmWL9uzZI0lq3bq1unbtGphkAICg165jO3U5t0tA+zxadlT7ivbLbtjVuW0n2Y36WdRv1/Zd9dIv6sZrerWr9Nj3wuP1KMS/oQ0CoMBVIJnSg88+pD7n96mXfXjklVde3frEbbrjzjtkmIGd9f9p+0/67Z2PKCcnh8IfQFDx+6/jv//9b91///3avXt3lcfbtm2rP//5z7riiivONBsAAHXiNb3KLDl2F5pmYc3qrehHw1HhrdBbOW9Jkm6tuE1Op9PiRGjVLj3gb+hV8ppe/Zj/o9wh5UrsmKSU8OR62Q8ABJta3c7vRHPnztXYsWMlSc8884w+/vhjffzxx3rmmWdkmqauvvpqzZs3L6BBAQA4ndyyXJV7yxVihCgpLNHqOAACzGbYlBqeKkk6XHJYFd4KixMBQOPg14z/U089pZ49e+rbb79VZGSk7/ErrrhCkydP1sUXX6wnnnhCI0aMCFhQAABOxWN6lFWSLUlKCU+WzfDrvW0ADVysI1bhpTkq8ZQoqyRLLSJZ4R8ATsevUdGGDRs0ceLEKkV/pcjISN10003asCHwt04CAKAmOaVH5DE9ctgcSnAmWB0HQD0xDENpEcdm/Y+U5arMU2ZxIgBo+Pwq/MPCwpSbm1vj9tzcXIWFhfkdCgCAuqjwVuhw6WFJUmp4igyjfm7zBaBhiAqNUnRotCQpszjT4jQA0PD5VfgPHjxY06dP17Jly07atmLFCr344osaOnToGYcDAKA2sksPy2t6FWYPU6wj1uo4AM6CtJ+v9c8vd6movMjiNADQsPl1jf9zzz2njIwMXXzxxbrgggvUqVMnSdK2bdv0/fffKzk5WX/6058CGhQAgOq4PW4dKT0i6VghwGw/0DSEhYQp3hmvo2VHdagkU+1D2vH7DwA18GvGv23bttqwYYPuueceHT16VO+9957ee+89HT16VPfee6/Wr1+vNm3aBDgqAAAnyyzJkilTkSGRigqNsjoOzjKbYdNlsZfpstjLFGLz+y7FaKRSw1NkyFBxRbFc5S6r4wBAg+X3X8jk5GRNmzZN06ZNC2QeAABqrai8SHnuPElSWgSz/U1RiC1EF0VfJEkKDQm1OA3OtlBbqJqFJSm79LAOFWcqJjSG/wcAoBrc6wgA0CiZpqmDxYckSfHOeEWERFicCIAVmoU3k92wy+11K7es5sWnAaApo/AHADRKR91HVeIpkc2w+Rb5QtPjNb064D6gA+4D8ng9VseBBeyGXSnhKZKkrJJseUx+DgDgRBT+AIBGx+P1KLM4S5KUEpbMtd1NWIW3Qq9lv6bXsl+Tu8JtdRxYJNGZIIfNoQqzQodLcqyOAwANDoU/AKDRySrNVoVZIafNqcSwRKvjALCYYRhKizh25s/h0sMq95ZbnAgAGhYKfwBAo1LqKVVO6bEZveYRabIZ/CkDIMWExijCHi5TprJKsq2OAwANSp1HS8XFxerbt69eeeWV+sgDAECNTNPUwaKDkqTo0GhFO6ItTgSgoTg2658mScoty1Wpp9TiRADQcNS58I+IiNCuXbu4VQoA4Kw76s5TYUWRDBlq/vMAHwAqRYZGKiY0RpKUWZxpcRoAaDj8Oj9yxIgR+uKLLwKdBQCAGlV4K3To59v3pYSnyGl3WpwIQEOUGnFshX9XeYEKy4ssTgMADYNfhf/vfvc7/fjjj7rxxhv13Xff6cCBA8rNzT3pAwCAQDlYfEge06Mwe5iahSVZHQdAAxVmD1OCM0GSdKj4kEzTtDgRAFjPr/sfdevWTZK0ZcsWzZ49u8Z2Hg/3UQUAnLkCd4Hy3HmSpJaRLbjcDD42w6ZLoy+VJG7rCJ+U8GTlleWpxFOifHe+4pxxVkcCAEv59RfyscceY9AFADgrvKZX+4sPSJKSnImKCImwOBEakhBbiAbFDpIkhYaEWpwGDUWoLVTNwpOUVZKtzJIsxThiuAMIgCbNr8L/8ccfD3AMAACql1mSpXJvuUJtoUr5+dpdADidpLAkHSnNldvrVm5ZrpK4RAhAExaQtz7z8/MDclr/N998o8svv1zNmzeXYRj65JNPqmy/6aabZBhGlY8RI0ZUaZObm6sbbrhBMTExiouL0y233KLCwsIqbTZs2KBLLrlEYWFhSk9P13PPPXfG2QEAgVdUUayc0hxJUouI5rIbdosToaHxml5ll2cruzxbXq/X6jhoQOyGXSnhx94szCrJlsfLJagAmi6/C/9Vq1ZpxIgRioiIUGJiohYvXixJysnJ0ZgxY7Ro0aI691lUVKRzzz1XM2bMqLHNiBEjdOjQId/H//t//6/K9htuuEGbN2/WggUL9Nlnn+mbb77R7bff7tvucrk0bNgwtW7dWqtXr9bzzz+vxx9/XK+++mqd8wIA6o/X9Gp/4X5JUpwjTjGOGIsToSGq8FbopayX9FLWSyqrKLM6DhqYBGe8nDanPKZH2aWHrY4DAJbx61T/pUuXavDgwWrRooXGjx+v119/3bctKSlJ+fn5+vvf/66BAwfWqd+RI0dq5MiRp2zjdDqVmppa7batW7dq3rx5Wrlypc477zxJ0l//+leNGjVK//d//6fmzZtr1qxZcrvdeuONN+RwONStWzetW7dOf/7zn6u8QQAAsFZmSZbKvGUKMULUPCLN6jgAGiHDMJQWkardhXuUU5qjRGeCHHaH1bEA4Kzza8b/kUceUZcuXbRlyxY988wzJ20fNGiQVqxYccbhqrNo0SIlJyerU6dOuvPOO3XkyBHftmXLlikuLs5X9EvS0KFDZbPZfHmWLVumAQMGyOH473/6w4cP17Zt23T06NFq91lWViaXy1XlAwBQf4rKi3yn+LeMbMFq7QD8Fh0araiQSJkydagk0+o4AGAJvwr/lStX6le/+pWcTme1q/u3aNFCmZmB/491xIgRevvtt7Vw4UL96U9/0uLFizVy5Ejf+gKZmZlKTk6u8pyQkBAlJCT48mRmZiolperiUJVf15T52WefVWxsrO8jPT090IcGAPiZ1/RqX9GxU/zjOcUfwBk6Nut/7KyhfHe+isqLLE4EAGefX1MooaGhp1xA58CBA4qKivI7VE2uvfZa3+c9evRQz5491b59ey1atEhDhgwJ+P4qTZ06Vffff7/va5fLRfEPAPUksyRLbq9bIUaI0iKaWx0HQBAIDwlXgjNeuWVHdbD4kDrEtOfW1ACaFL9m/Pv3768PP/yw2m1FRUWaOXOmLr300jMKVhvt2rVTUlKSduzYIUlKTU1VdnZ2lTYVFRXKzc31rQuQmpqqrKysKm0qv65p7QCn06mYmJgqHwCAwDv5FH9W8QcQGCnhKbLJphJPifLceVbHAYCzyq/C/4knntCqVas0evRoff7555Kk9evX6/XXX1ffvn11+PBh/e53vwto0Ors379fR44cUVrasdO3MjIylJeXp9WrV/vafPXVV/J6verXr5+vzTfffKPy8nJfmwULFqhTp06Kj4+v98wAgOp5Ta/2Fx2QxCn+AAIv1Baq5PBjl4QeKs6U1+T2jwCaDr8K/379+mnu3LnasWOHJkyYIEl64IEHdPvtt8vj8Wju3Lnq2bNnnfstLCzUunXrtG7dOknSrl27tG7dOu3du1eFhYV68MEHtXz5cu3evVsLFy7UmDFj1KFDBw0fPlyS1KVLF40YMUK33Xabvv/+ey1ZskSTJ0/Wtddeq+bNj50uev3118vhcOiWW27R5s2b9d5772n69OlVTuUHAJx9Wcet4s8p/qgtm2HThVEX6sKoC1kEEqeVFJaoUFuoKswKZZdwez8ATYfffyEHDx6sbdu2ae3atdqxY4e8Xq/at2+vvn37+n3N1KpVqzRo0CDf15XF+MSJE/Xyyy9rw4YNeuutt5SXl6fmzZtr2LBheuqpp+R0On3PmTVrliZPnqwhQ4bIZrNp7NixevHFF33bY2NjNX/+fE2aNEl9+/ZVUlKSHnvsMW7lBwAWKq4o1mFO8YcfQmwhGhY3TJIUGhJqcRo0dDbDprSINO0t3KvDpYeVEJYgh42fGwDB74zfGu/du7d69+4diCwaOHCgTNOscfsXX3xx2j4SEhI0e/bsU7bp2bOnvv322zrnAwAE3vGr+Mdxij+AehYbGqOIkAgVVxQrszhTraJYsBlA8PO78C8rK9Nrr72muXPnavfu3ZKkNm3aaNSoUbr11lsVFhYWqIwAgCCWXZKtMs+xU/yb/3zLLaC2vKZXRyuOHvv8FHccAioZhqHmEWna4dqpPHeekioSFRESYXUsAKhXfl3jv3//fvXq1Uv33HOP1q9fr2bNmqlZs2Zav3697rnnHvXq1Uv79+8PdFYAQJAxQ01llx67zrZFZHOu0UadVXgrND1zuqZnTldZRZnVcdBIRIREKN4RJ0k6WHzolGecAkAw8KvwnzRpkvbs2aP3339fBw4c0OLFi7V48WIdOHBA7733nvbu3atJkyYFOisAIIjYQ+2qSPBIkmIdsYp1xFqcCEBTkhqRKkOGiiuKle/OtzoOANQrvwr/hQsXasqUKRo3btxJ2375y1/q3nvv1cKFC884HAAgeF3x6zGSQ7IbdrVgFX8AZ9mx2/s1kyQdKuH2fgCCm1+Ff3R0tJKTk2vcnpqaqujoaL9DAQCCW4mtVJffcYUkqUVkC07xB2CJZmHNFGqEqNxbrpyf7ywCAMHIr8L/V7/6ld58800VFxeftK2wsFAzZ87ULbfccsbhAADBx2t6ddB5UCGhITKKDcVxij8Ai9gMm1IjUiVJ2SWHZdq51h9AcKrVFMtHH31U5evevXtrzpw56ty5syZOnKgOHTpIkrZv3663335bCQkJ6tmzZ+DTAgAavU25m1VqL1PB0QLFF8dJLa1OBKApi3PE6UhZroorimXGGVbHAYB6UavCf9y4cTIMw7fi6fGfP/300ye1379/v6677jr9z//8TwCjAgAau6Nledp4ZJMk6Z0/vK177rvX4kQAmjrDMNQiorm2u3bIjDDVtX83qyMBQMDVqvD/+uuv6zsHACDImaapFVkr5JVX0RVRWvbZMgp/nDGbYdP5kedLkuw2u8Vp0FiFh4Qr0ZmoI2VHNOGxCfKKU/4BBJdaFf6XXnppfecAAAS5Ha6dOlyaoxAjRGllqVbHQZAIsYVodPxoSZIjxGFxGjRmqeEpOlJ8RM3bt1BuWa7VcQAgoPxa3A8AgLoo9ZRqzeG1+v/t3Xl8VPW9//HXObNlT8ieQBJWBVRQQBDXKlzAWlzqrcvPBavVqxe8Wm7VUq2ivS6IdSmlLq1LvdZbr7dqrVoUUQQVRECQrZQlEMhKCFlmJpn1/P4IRCOIkEw4TPJ++pjHnDnbvL8OSeZzzvd8D8Dw7GG4LJfNiURE2nOYDhz1rV+Nd7l34Qv5bE4kIhI7Hb5/0scff8xzzz3H1q1b2bNnT9s1//sYhsHq1as7HVBEROLfyl1fEIwG6eXpxeCMY1nFKrsjSTdhWRa+iK9tWqQzDL/BP7dt5JiRx7J810rOKjzD7kgiIjHRoTP+jz76KGeddRavvPIKjY2NZGZmkpWV1e6RmZkZ66wiIhKHappr2NK4FYAxuSdjGupsJrETioaYXTmb2ZWzaQm12B1H4pyBwR/v/SNYUOYtY6e33O5IIiIx0aEz/rNnz+a0007jb3/7G+npuv+yiIgcWNSKsrR6GQCD0geSk5hjcyIRkYPbsbGMrFAmu911fFazjLykH+AydXmSiMS3Dp128fv9XHHFFSr6RUTkoDbs2UBDsAGPw8NJ2SfaHUdE5JDkBnNIcaXgD/v5olaXropI/OtQ4X/22WezZs2aWGcREZFuxBvysnp369+Kkdkj8Dg8NicSETk0JiZjckcDsLF+I7uad9mcSESkczpU+M+ZM4cFCxbwyCOPUFen252IiMj+Pq9ZQcSKkJuYS/+0fnbHERE5LIXJBfRP6w/AkuqlRKIRmxOJiHRchwr/oqIi/u3f/o2f//zn5OTkkJycTFpaWruHLgMQEem5dnh3stO3EwODMbknYxiG3ZFERA7bqJwRJDgSaAg2snbPOrvjiIh0WIcG97v77ru5//776d27N6NGjVKRLyIibULRMJ/XfA7A0F5DyPBk2BtIRKSDPA4PJ+eOZHHlJ6zdvY7ilCJ6eXrZHUtE5LB1qPB/6qmnOO+883jjjTcwTd2WSUREvrJm9xp8YT/JzmSGZZ1gdxzp5kzDZHjScAAcpsPmNNIdlaSUUJq8nZ2+nXxS+SnnFk/SvzURiTsdqtqDwSDnnXeein4REWmnPlDP+j0bADg5dxROs0PHl0UOmdN0clHmRVyUeRFup9vuONINGYbBKXmj8Tg87AnWs2q3RvkXkfjTocr9Bz/4AYsXL451FhERiWOWZfFZzTIsLPok96EopY/dkUREYiLRmcjYvFMAWL9nA5X+KpsTiYgcng4V/vfccw/r16/n3//931mxYgW7du2irq5uv4eIiPQcWxu3UtO8C4fhYHTuKLvjSA9hWRbBaJBgNIhlWXbHkW6sKKUPg9IHAvBp1RICkYDNiUREDl2H+mAee+yxAKxatYqnn376W9eLRHTbExGRniAQCbCi9gsAhmcNI9mVbHMi6SlC0RAPVDwAwLmh7+Nyu2xOJN3ZyJyRVPmraQo1sazmc84oON3uSCIih6TDo/rr1kwiIrLPyl1fEIgEyHCnM6TXYLvjiIh0CZfp5PT8U5m34z22NW2nMKmQAen97Y4lIvKdOlT4z5w5M8YxREQkXtU072Jz4xYAxuSNxjQ08KuIdF/ZidkMyzqB1bu/5LOaZfTyZJCZkGl3LBGRg9K3MxER6bCoFWVZ9TIABqT1Jzcx1+ZEIiJd74TM4+mdXEjEirCwYpGu9xeRo16Hzvjfd99937mOYRj88pe/7MjuRUQkTvyjfiN7gvW4TTcjck6yO46IyBFhGAan5Z/KO2Xz8Ia8fFz5CWf3/p56PInIUSvmXf0Nw8CyLBX+IiLdnC/kY3XtlwCMyDmJBEeCzYlERI4cj8PD9wrP5O9l71Lhr2T17i85KftEu2OJiBxQhw5LRqPR/R7hcJgtW7bw05/+lFGjRlFTUxPrrCIicpSwLIvPaj4nbIXJSchhYNoAuyOJiBxxvTy9OCVvDABr69ZR1rTD5kQiIgcWs/5IpmnSr18/HnnkEQYNGsTNN98cq12LiMhRpsy7g3JfOSYmp+SN1p1exDaGYTA0cShDE4eqm7XYon9aPwZntN7q+uOqT9jVXGtzIhGR/XXJX8gzzzyTd95557C3W7RoEZMnT6awsBDDMHjjjTfaLbcsi7vvvpuCggISExMZP348mzZtardOXV0dV1xxBWlpaWRkZHDdddfh9XrbrfPll19yxhlnkJCQQFFREQ8//PBhZxUR6amCkSCf1ywH4LjMoWR4MuwNJD2ay3RxSdYlXJJ1CR6Xx+440kONzBlBYVLrYH8flH9IQ7DB7kgiIu10SeG/fPlyTPPwd+3z+Rg+fDhz58494PKHH36Y3/zmNzz11FN89tlnJCcnM3HiRFpaWtrWueKKK1i3bh3z58/nrbfeYtGiRdxwww1tyxsbG5kwYQIlJSWsWLGC2bNnM3PmTJ555pnDb6iISA/0Re0qmiPNpLlSOSHzeLvjiIjYzjRMziw8gyxPFsFokAU7P8Qf9tsdS0SkTYcG93vxxRcPOL++vp5Fixbx2muv8ZOf/OSw93vuuedy7rnnHnCZZVk8/vjj3HXXXVxwwQVtOfLy8njjjTe47LLL2LBhA/PmzePzzz9n1KhRAMyZM4fvf//7PPLIIxQWFvKnP/2JYDDIc889h9vt5rjjjmPVqlU8+uij7Q4QiIjI/mqaa/hnQ2tPqzF5Y3CYDpsTiYgcHVymk3N6f495O96jKdTEB+ULmdBnPG6H2+5oIiIdK/yvueaab12WnZ3Nz3/+c+6+++6OZjqg0tJSqqqqGD9+fNu89PR0xowZw5IlS7jssstYsmQJGRkZbUU/wPjx4zFNk88++4yLLrqIJUuWcOaZZ+J2f/VLeOLEicyaNYs9e/bQq1ev/d47EAgQCHx1f9bGxsaYtk1EJB5ErAhLq5cBMCBtAPlJeTYnEmm99OTenTMBGBccT6or1d5A0qMlOBMY1/ts5u14jz2BPSys+Iize5+Ny+zQV24RkZjp0G+h0tLS/eYZhkGvXr1ITe2aP7hVVVUA5OW1/6KZl5fXtqyqqorc3Nx2y51OJ5mZme3W6dev33772LfsQIX/gw8+yL333hubhoiIxKm1u9fREGzA4/AwMucku+OIiByVUt2pjOt9Nu/tnE91cw0fli/k7N7fU/EvIrbq0DX+JSUl+z2Ki4u7rOi324wZM2hoaGh77NihW7WISM+yu2U3a+rWAjA6dxQehwZRExH5NpkJmYzrfQ4u00l1czUfli8kFA3bHUtEerC4ue9Nfn4+ANXV1e3mV1dXty3Lz8+npqam3fJwOExdXV27dQ60j6+/xzd5PB7S0tLaPUREeopINMInVUuwsChJKaZval+7I4mIHPVyEnNU/IvIUeOQ+xwNGzbssHZsGAarV68+7EDfpl+/fuTn57NgwQJOPPFEoPVa+88++4ybbroJgLFjx1JfX8+KFSsYOXIkAB988AHRaJQxY8a0rXPnnXcSCoVwuVwAzJ8/n2OPPfaA3fxFRHq6L+vW0BBsIMGRwOi8k+2OIyISN1qL/3EsKF+wt/j/cG+3f5fd0USkhznkwj8zMxPDML5zvaqqKjZu3HhI636T1+tl8+bNba9LS0tZtWoVmZmZFBcXc+utt/Jf//VfDBo0iH79+vHLX/6SwsJCLrzwQgCGDBnCpEmTuP7663nqqacIhUJMmzaNyy67jMLCQgD+3//7f9x7771cd9113HHHHaxdu5YnnniCxx577LDzioh0d7XNtayrWw/AmNzRJDgSbE4kItL1NmzYENP99TH7sD2xjOrmGv668U2Km4tx0nV3RcnOzqa4uLjL9i8i8eeQC/+FCxcedHlVVRWzZs3i6aefxuFwcNVVVx12mOXLl3P22We3vZ4+fToAU6ZM4YUXXuD222/H5/Nxww03UF9fz+mnn868efNISPjqi+if/vQnpk2bxrhx4zBNk4svvpjf/OY3bcvT09N57733mDp1KiNHjiQ7O5u7775bt/ITEfmGcDTMJ9WtXfz7pvalOLXI7kgiIl2qtroWDLjyyitjvu9+x/fjtj/cDr3g/fIFPHzdLBp21cf8fQCSkpLYsGGDin8RadPp4UWrq6t56KGHeOaZZwiFQlx55ZXceeedDBgw4LD39b3vfQ/Lsr51uWEY3Hfffdx3333fuk5mZiYvv/zyQd9n2LBhLF68+LDziYj0JF/UrqIx2EiiI4HRuaO+ewMRGxiGwaCEQQCYRtwMXSRHqabGJrDgtgdvZ8TJI2K+f6vFIhyJUHRsEXM+/C3OXQ6MyOH3kj2YrZu2cudNv6C2tlaFv4i06XDhv+8M/9cL/rvuuov+/fvHMp+IiNhgp3cn/6jfCMDYvFM0ir8ctVymiyuyrwDA49K/U4mN4v5FDBk+pEv2HYgEKW3aStAVwuhj0i+1ry6jEpEud9iHxquqqrj11lsZMGAAc+fO5bLLLmPjxo0899xzKvpFRLoBf8jPp1VLARicMZjeKb1tTiQi0n14HG4GpA3AY3oIRUNsadxKc7jZ7lgi0s0d8hn/yspKHnroIX7/+98TDoe5+uqrufPOO+nXr19X5hMRkW8oKyujtra2S/ZtYbEtoYyAM0BCxIOx02LlzpUxf59YD5wlIhJPXKaLAWn9KW3aRnOkmS1NW+mX0pdkV7Ld0USkmzrkwn/AgAEEAgFOPPFEfvGLX9CvXz/27NnDnj17vnWbESNif22UiEhPVlZWxpAhQ/D7/V2y/wv+/UIuvuVfafG1cPsPf0bVtqoueZ99vN6mLt2/dH/BSJAHyu8HYFxwPKmuVJsTiRwap+mkf2o/tnm34Qv72dpUSt+UElLd+jcsIrF3yIV/S0sLAF988QWXXHLJQde1LAvDMIhEIp1LJyIi7dTW1uL3+7n/yQfoPyi2l1dF3RaR3Nbf28ktSTz2h8djuv+vW7xgMb97cC4tgZYuew/pOUJWyO4IIh3iMB30S+3Hdu92mkJetnm3U5xSRLo73e5oItLNHHLh//zzz3dlDhEROQz9B/WP6cBToWiITQ2bwYIMdwbFg7r21n2lm0q7dP8iIvHCNExKUkrY4dtJQ7CB7d4ySlKKVfyLSEwdcuE/ZcqUrswhIiI2iVpRtnvLCFthPA4PvZML7Y4kItKjmIZJcXIROzCoD9az3VtGcUoxGSr+RSRGdMNbEZEersJfgT/sx2GY9E0pwWE47I4kItLjGIZBUXIferkzACjzllEfqLc1k4h0Hyr8RUR6sN0tu6kLtA7SWpxcjMeh+6CLiNjFMAz6JPehl7sXAGW+HexR8S8iMaDCX0Skh/KFfFT4KwHIT8zXSNIiIkeB1uK/d1vxv8O3g4Zgo82pRCTeqfAXEemBApEA27zbsbBId6eTk5BtdySRDjEMgxJ3CSXuEgzDsDuOSEzsK/4zvtbt3xvy2htKROLaIQ/uJyIi3UM4Gqa0aRsRK0KCI4Gi5D4qmCRuuUwXP879MQAJrgSb04jEzr5r/qNWlMZQI9uattM/rR9JziS7o4lIHNIZfxGRHiRiRSht2kYwGsRtuuiX2hfT0J8CEZGjkWEYFKcUkeJMJkqU0qZtNIdb7I4lInFI3/ZERHoIy7Io85bRHGnGYTjol9oPl+myO5aIiByEaZiUpJaQ5Ejce/C2lEAkYHcsEYkzKvxFRHoAy7LY6SunKeTFwKBfal+N4C/dQjAS5OGKh3m44mGag812xxHpEg7DQd/UfiQ4EghbYbY2lRKMhuyOJSJxRIW/iEg3Z1kWFf4K9gRbb9tXklKsa0SlW/FH/fijfrtjiHQpp+mgX2pf3KabUDREaWMp4WjY7lgiEidU+IuIdGP7iv7dgToAipL7kOZOszmViIh0hMt00X/vZVqBaIDSplIi0YjdsUQkDqjwFxHppr5Z9PdJ7kMvTy+bU4mISGe4HW76pfbDYThojrRQ6t1G1IraHUtEjnIq/EVEuqEDFf2ZKvpFRLqFBIeH/qn9MA0Tf9jPdu92Ff8iclAq/EVEupnWgfx2fq3o762iX0Skm0l0JtIvpS8GBk0hLzt8O7Esy+5YInKUUuEvItKNRK0o27zb2ROsB/ad6c+0N5SIiHSJZFcyfVNKMDBoCDZQ7i/HQsW/iOzPaXcAERGJjXA0zLambfgjzRgYlKQUayA/6fYMw6DQVdg2LdLTpLpTKUoposxbRl1gD2a6fg5EZH8q/EVEuoFgJEhp0zYC0UDr/Z5TSkh2JdsdS6TLuUwXN+TdAECCK8HmNCL2yHCnE03uzU5fOdE0i8k3nm93JBE5yqjwFxGJc96Ql+3eMiJWBJfpol9qXxIcKoBERHqSTE8mEStKpb+SH/30krZxXkREQNf4i4jEtd0tu9naVErEipDoSGRg2gAV/SIiPVROQjZmQ2tX/ypPNVsat9qcSESOFir8RUTikIXFTl855f4KoLWb54C0/rhMl83JRI6sYDTIY5WP8VjlY7QEm+2OI2I7s9Hk3RffBWBJ1VLKvDtsTiQiRwMV/iIicaZXXiaR3Ah1e7tx5ifmU5RchGnoV7r0QBY0RBpoiDRoLHMRwMDg5QdeIiOUjoXF4sqPqfBV2h1LRGymb4kiInHE6/Dyqzf+C8sDpmHSN6WE3MQcjWYuIiJtLMuiMFBAcUoRUSvKhxULqfBV2B1LRGykwl9EJA5ErSiralezPWEHaZlpEIRBaQN1uz4RETkgA4PT80+jT3KfvcX/R5T7yu2OJSI2UeEvInKU84X8vL/zA9bUrQUDFvzP+zirHXgcHrujiYjIUcxhOjiz8HSK9hb/CysWsdO70+5YImIDFf4iIkexsqYy3tr+NtXN1TgNJ71bCvnjzBcwUNd+ERH5bg7DwZmFZ7R1+/+oYjE7NOCfSI8TV4X/zJkzMQyj3WPw4MFty1taWpg6dSpZWVmkpKRw8cUXU11d3W4fZWVlnHfeeSQlJZGbm8ttt91GOBw+0k0RETmoUDTMkurP+KhyMcFokExPJueVnEtGON3uaCIiEmdMw+SMgtMpSSkmSmvxv6Vhi92xROQIctod4HAdd9xxvP/++22vnc6vmvDTn/6Ut99+m1dffZX09HSmTZvGD3/4Qz755BMAIpEI5513Hvn5+Xz66adUVlZy9dVX43K5eOCBB454W0REDmR3Sx0fV35CY6gRgON6DWV49jAchsPmZCJHIQNynDn7JkXkW5iGyekFp+GodrK1cSufVi+lJRLguMyhdkcTkSMg7gp/p9NJfn7+fvMbGhp49tlnefnllznnnHMAeP755xkyZAhLly7llFNO4b333mP9+vW8//775OXlceKJJ/KrX/2KO+64g5kzZ+J2u490c0RE2liWxfo9G1hVu5ooURIdiZxWcCoFSfv/zhORVm7TzdT8qQAkuBNtTiNydDMNk1PzTiHB4WH9ng2srP2ClkgLI7JP0t1hRLq5uOrqD7Bp0yYKCwvp378/V1xxBWVlZQCsWLGCUCjE+PHj29YdPHgwxcXFLFmyBIAlS5ZwwgknkJeX17bOxIkTaWxsZN26dd/6noFAgMbGxnYPEZFY8of9vF/+AStrvyBKlKKUIib3PU9Fv4iIxJRhGIzMGcGI7JMAWL9nA59WLyViRWxOJiJdKa4K/zFjxvDCCy8wb948nnzySUpLSznjjDNoamqiqqoKt9tNRkZGu23y8vKoqqoCoKqqql3Rv2/5vmXf5sEHHyQ9Pb3tUVRUFNuGiUiPtr2pjLe2vUOVvwqH4eCU3DGcVXCGRu0XEZEuc1zmUMbmnYKBwdbGrby/8wNaIi12xxKRLhJXXf3PPffctulhw4YxZswYSkpK+N///V8SE7uue9+MGTOYPn162+vGxkYV/yLSacFIkM9rlrO1qRSATE8vTi84jXS3BvATOVTBaJDfVc0FYHxwPCmuVJsTicSPgekDSHQmsrjyY2qaa/h72bucU/g90j36OyTS3cTVGf9vysjI4JhjjmHz5s3k5+cTDAapr69vt051dXXbmAD5+fn7jfK/7/WBxg3Yx+PxkJaW1u4hItIZlf4q/rb9bbY2lWJgcHzmcUwqnqiiX+RwWbArvItd4V1YdmcRiUO9kwuZVDSRFFcK3pCXv+94lwpfhd2xRCTG4rrw93q9bNmyhYKCAkaOHInL5WLBggVtyzdu3EhZWRljx44FYOzYsaxZs4aampq2debPn09aWhpDh2pEUxHpeuFomM9rlvP+zgX4w35SXSlMKPoXTso+UaP2i4iILTI86ZxbNJHcxBxC0RAflC9kTd1aLEuH00S6i7jq6v+zn/2MyZMnU1JSQkVFBffccw8Oh4PLL7+c9PR0rrvuOqZPn05mZiZpaWncfPPNjB07llNOOQWACRMmMHToUK666ioefvhhqqqquOuuu5g6dSoej66lFZGuVduym08qP227Td8x6YMYkXMSLtNlczIREenpEpwJjO89js9qPmdL4xZW1a5mV/MuTss/VWPOiHQDcVX479y5k8svv5zdu3eTk5PD6aefztKlS8nJab1/72OPPYZpmlx88cUEAgEmTpzI7373u7btHQ4Hb731FjfddBNjx44lOTmZKVOmcN9999nVJBHpAaJWlDW717aePcEi0ZHI2PxT6J1caHc0ERGRNg7Twan5p5CbmMOyms8p91Xw9vZ3OLPgDLITs+2OJyKdEFeF/5///OeDLk9ISGDu3LnMnTv3W9cpKSnhnXfeiXU0EZEDqmupY0n1UuoCewAoSS1hTO7JOnsiIiJHrYHpA8j09GJR5WKaQl7e3TGf4dnDGNprCKYR11cKi/RYcVX4i4jEi0g0wpd1a1hXtx4LC7fpZnTuyfRL62t3NBERke+UmZDJ94vPZUn1Usq8O/iidhXlvnJOzT+VVFeK3fFE5DCp8BcRibGa5l0sqV5KY7D1Wv7ilGJG544i0dl1tx0V6bEMSHek75sUkb02bNgQk/2kkEyhs4AqTzU1zbt4c+vfyA/kkRFOx+jCn7rs7GyKi4u7bP8iPY0KfxHpUcrKyqitre2SfUeIUuOuoc61BwxwRh0UBPJJ9SazoSo2X8Bi9UVOpLtwm25+WvBTABLcOrgmUltdCwZceeWVMd1vdp8cbnjo3xh88mAqEip5d/G7/PHeF6jZUfPdG3dAUlISGzZsUPEvEiMq/EWkxygrK2PIkCH4/f6Y7/u4U4/n2l9dR06f1sFGF/3lI15+6E/4G2P/XgBeb1OX7FdEROJbU2MTWHDbg7cz4uQRMd23hUW03iKaHuWEM4bxyHuPYjaamE1GTM/+b920lTtv+gW1tbUq/EViRIW/iPQYtbW1+P1+7n/yAfoP6h+TfVqmRSQ9ipWy917HYXDUmYwbPY5xr42LyXt83eIFi/ndg3NpCbTEfN8iItJ9FPcvYsjwIV2y70AkQLmvHG/YRzQjiivTQ+/kQlJ07b/IUUuFv4j0OP0H9e/0lyHLsqgL1FHVXI1ltRb9WZ4s8nvl4ch1xCLmAZVuKu2yfYvEo1A0xDPVzwAwPvQvKjxEjgCPw0O/1H7UB+up8FcSiAbY2lRKmiuV/KQCEnTnGpGjjgp/EZHD5A/7KfdV0BxpBiDBkUDvpEKSXck2JxPpeSzLoiJU0TYtIkeGYRj08vQi1ZVKdXM1uwN1NIaaaGxoIsuTSV5iHk5TpYbI0UI/jSIihygcDVPVXE1doA4A0zDJT8wjy5OFYWg8cRER6XmcppPeyb3JSsii0l9FU6iJ3YE69gTqyU7IIjshWwcARI4C+ikUEfkOrd3691DVXEXEigDQy51BflI+LtNlczoRERH7JTgS6JfaF2/IS4W/kpZICzUtu6ht2a0DACJHAf30iYgchLr1i4iIHLoUVwqD0gbSGGqkurmm3QGAzIRMsj1ZuB1uu2OK9Dgq/EVEDiAYCVLZXEVDsAFQt34REZFDZRgG6e500lxp7Q4A1LbUUttSS4Y7g5yEbBKdiXZHFekxVPiLiHxNJBqhuqWG3S27sWgdKKyXuxf5SXnq1i8iInIYvn4AoCnkZVfLLnxhH/XBeuqD9SQ7k8nyZJLuTtdBdZEupsJfRASIWlHqAnVUN9e0Xcef4kyhIClfZyREjnJJZpLdEUTkIAzDIM2dSpo7FX/Yz66WWhqCDfjCPnxhH05/JZmeTLISMnWQXaSLqPAXkR7NsiwaQ41U+qsIRoNA6/2JCxLzSXWl6gyEyFHO7XBze+HtACS6dZBO5GiX5EyiJKWYYDREXUsddYE6wlaYmpYaalpqSHelEfVE7Y4p0u2o8BeRHssb8lLVXI0/7AfAaTjJS8wl05Opgl9ERKQLuU0X+Ul55Cbm0BhsZHegDl/YR0OoEXLhoXdmsdtVR0ukhQRHgt1xReKeCn8R6XGibostjVvxhX0AGBjkJGSTk5iDw3DYnE5ERKTnMA2TDE8GGZ4MmsMt1AV2s7u5jsIBvamimr9seZ0+KX0YmD6AgqR8TMO0O7JIXFLhLyI9ht9s5rY/3E4kL4Iv7MPAINPTi9zEXF1TKBKnQtEQz9c8D8D40L+Q4kqxOZGIdFSiM4Hezt40bGng2Wef5d/uupEWRwtl3jLKvGUkOZMYkNafAWn9SXWn2h1XJK6o8BeRbm93y25W7/6S8qQKTjhjGFiQmZBJbkKO7iUsEucsy2J7cHvbtIjEP8MyWPDy+zz8n7PoO7Qvmxu3UtpYij/sZ03dWtbUrSUvMY+B6f0pSinSwXuRQ6DCX0S6rV3NtaytW8dO387WGRYseu0jzhl7Dn2O721vOBEREflOmQmZjE7IZGT2Sezw7WBzwxYq/VVUN1dT3VyNw1hGUUoR/VP7UpBcoEsBRL6FCn8R6VYsy6LcV866Peupad4FtF7D3ze1BEeVg6t/cSXj3h9nc0oRERE5HA7TQd/UvvRN7Ys35GXL3l4ATSEv25q2sa1pGx6Hh6KUIkpSislPytNBAJGvUeEvIt1CKBqitLGUf9RvpCHYCICJSd+0vhzfayjpnnRWVq60OaWIiIh0VoorheFZwxiWeQK1Lbsp3Vv4ByIBNjdsZnPDZtymm6KUPvRJ7kNBcr4uB5AeT4W/iMS1usAeNtVvYmtjKWErDIDLdDEofSBDMgaT5EqyOaGIiIh0BcMwyEnMJicxm1E5I6jyV1PmLWOHdyctkRa2NG5lS+NWTMMkNzGXPsm9KUgqIN2dptv2So+jwl9E4o4v5Gd703ZKm7ZRF6hrm5/mSuOYjEEMSOuvQftERER6ENMwKUwuoDC5gNG5J7OreRdl3h2U+ypoCjVR5a+iyl8FQIIjgdzEXPKTcslNzCPDna4DAdLtqfAXkbjQGGyiwlfBdm8ZNc01bfMNDIpTijgmYxB5iXn6wy3SA7kMdeEV6Y42bNjQqe0dmBTTh4ARoMnpxevw4nc00xL56haBAA7LQVIkieRIEkmRJBKiHgw6/30iOzub4uLiTu9HJBZU+IvIUak53EJtyy4qfVVU+CtoCnnbLc9NzKFval9KUopJcCbYlFJE7OZ2uLmz950AJLoTbU4jIrFQW10LBlx55ZUx37fT5aT/sP4ce/JgBp88hGNGDMKTlECTs4kmZxMAwZYgZf8oY9u6UkrXlrJtXSnlm8uJRqKH9V5JSUls2LBBxb8cFVT4i8ghKysro7a2Nqb7tLAIG2ECZoAWM0Cz2UKzo5mQGfrmiiRFkkiNpJAeTsPldeHb5WU96w/5vTp75kBERES6XlNjE1hw24O3M+LkEV36XtZuC6sJLI/V9nAnuBl44kAGnjjwqxWjYITACBoQMjDCYISM1vkH6B2wddNW7rzpF9TW1qrwl6OCCn8ROSRlZWUMGTIEv99/2NumZqaRXZhFZn4WWYVZZOZnklWYTU6fHAr6F5CYvP9Zumg0SsWWCjYu/wdrFn/J+qXrafG1xKIpeL1NMdmPiIiIdJ3i/kUMGT7kiL6nZVkEo0Gaw834I800h5tpjjQTNaNYntYDBGC1re8wTNwODx7Tg8fhIcHhwe1wYxnWt7+JiA1U+IvIIamtrcXv93P/kw/Qf1D/tvkWFjjBcnz1bDkBx1fzvvMyOQvYe+TcCBoYQXAGHfRL6Eu/0/sy6fRJMWnD4gWL+d2Dc2kJxOYAgojYLxQN8afaPwHwL6EJOF36aiMiHWcYBh5HaxGfQQbw1cEA/96DAIFIgEAkQDAaJGJF8Yf9+PnGiZE+MOeTuWxNLMVb4SPZlUyKK5lkZwrJrmSSnUkaiFiOKP11FJGDilpRfGE/XoePMy8+k5KRJSTnpBCMBglGgoStyCHtx2k4cZku3KYLl+nC5XDjNl14HB7cphvTMLu4JVC6qbTL30NEjizLstjUsglo/X0lIhJrXz8Y0GvvwQBo/Z2z7yBAIBqgZd8BgUiQKFHSs9NppoXtewcR/CaX6STJmUSSM5kkZxLJziSSXHuf985zOzR4qcSGCn+RHs6yLAKRAN6Ql6aQF2/YizfoxRv24Q158YV8rWf1E+EnD9xAFIv6YH27fRgYuPcW8i7T/VVxb7pwm26cpvOIFPYiIiIiR4ppmCQ6E0l0tr9k0bIsNqzdwIxpM3jh5efJLc7DF/LhDfnwhX34Qj6C0SChaJiGYCMNwcZvfQ+X6frqoEDbgYH2Bwpcpg4OyHfr0YX/3LlzmT17NlVVVQwfPpw5c+YwevRou2OJxFTEirRepxb24wv5aQ434wu3/vHxhrx4Q17CVvig+zANE2fEyfJPlnPiScPJzcnDbbr2FvtuHIZDt9ETERERobWHgBE12L5+G+Vry0mLpOHAJJ1U0kkFIEqUkBEiZIZbn40Q4bbpMCEzRNSIEoqGaAg20BBs+Nb3My0TV9SFy3Lislw4o63PLsuFa++0ScdPwOi2hN1Djy38X3nlFaZPn85TTz3FmDFjePzxx5k4cSIbN24kNzfX7ngiB7XvWrOWSAst4RZaIi00733eN+0P+/GH/bREDu169kRHIqnuFFKcKaS4vnqkulJIdCbyxRdfcNlPLuF/3v8zucU5XdxCERERkfgVi1sSJiQnkJmXSa/8TLIKMsnMbx0gObMgi8y8XmQWZJGUmkTUiBJwBAgQ+NZ9eeu91FXXUVdZR11VHXVVu6nfVY+v3oe3vglvgw9vvRdfvZdwqP0JId2WsHvosYX/o48+yvXXX8+Pf/xjAJ566inefvttnnvuOX7+85/bnE7sZFkWbf/tnY5a0bbXUcvCIvq1ZV+9jrZt8/XXrdPVu2pobGxoHQfWsGgdE7Z1xNe2V0brdNSIEiFK1IgQMaJE2fu8dzpsRL57wLyvMSwD596jwK6os23aHXXjjrr2OxIcIUwD9TRQ3zZPt8ITEREROTRH5JaE9WA1WK0DKjuttoGVLQft5mFCSkYKKRkpFB97CMV79KtHwN/CxjX/ZKV3FTuqduI0nDjN1nGbnKYTh2FiYGIaJqZhtJs2MTEME4O9vSBap9qmvz6/tefoV9Ntr9rWNWDv/Nb9731gqtfpIeqRhX8wGGTFihXMmDGjbZ5pmowfP54lS5bYmCy2tjaW7n+21/r65IFuM2IdaNUDb3OAFQ68z+/e/mCFdqO3iZaW5q+VyK0F8jfL5tbC+QDzYO8tVfYrs8Fo96ptXpfZ/651neJr8NFY10jj7kYaahtoqmt9bqxrpK6qjj1VrUd1m/bE7vZ1uhWeiIiIyKGx45aE3xSJRghFQ4SiIYJ7n0PREGErTCQaJmxFiOx9AGDufQAedwLDzhhGE02tBzOOQob11cGBA02bGHhcCfxg4PftjmqrHln419bWEolEyMvLazc/Ly+Pf/zjH/utHwgECAS+6jrT0NB6jU1j47cPxHE0WF62gvrgHrtjdCvRqEU0HCUajRKJRIhG9k6HI1jRKNGwRTQaJRqOEIlGW5dHInvnRcnMycTj8WBZgGV963M0HMUKt+4vEo4SDbVuH41EWqdDUSKhSOvR2L2SSSLZk0R+73zoDZwQ27avW7WWt/73LdZ8sRbTcMR250fI1k1bAdi0fjNJCck2p+mY7tAG6B7tUBuODtu2boNg6/Tqz1eT6I7xEdYjoDt8DtA92qE2HB3UBnu0nQAzwTIB02Lb1m3Mf2s+CUkJeBI9eJI8eBL2Picl4HI7MR0mDocDh9OB6XTgcDhwOh0YThOH04FhGq09ABx7ewC0Te99NsEwTEyHgWG2nsk3TKN1O9NsezbN1nU6wl/TzLrAOoqKimL6/+xI21d/WtbBT7YeiGF1ZKs4V1FRQe/evfn0008ZO3Zs2/zbb7+djz76iM8++6zd+jNnzuTee+890jFFRERERERE2tmyZQv9+/c/rG165Bn/7OxsHA4H1dXV7eZXV1eTn5+/3/ozZsxg+vTpba+j0Sh1dXVkZWXpmpJOamxspKioiB07dpCWlmZ3nJhQm+KD2hQf1Kb4oDbFB7UpPqhN8aG7tam7tQe6Z5saGhooLi4mMzPzsLftkYW/2+1m5MiRLFiwgAsvvBBoLeYXLFjAtGnT9lvf4/Hg8XjazcvIyDgCSXuOtLS0bvMDuY/aFB/UpvigNsUHtSk+qE3xQW2KD92tTd2tPdA922Sah397xh5Z+ANMnz6dKVOmMGrUKEaPHs3jjz+Oz+drG+VfREREREREpDvosYX/pZdeyq5du7j77rupqqrixBNPZN68efsN+CciIiIiIiISz3ps4Q8wbdq0A3btlyPH4/Fwzz337HcpRTxTm+KD2hQf1Kb4oDbFB7UpPqhN8aG7tam7tQfUpm/qkaP6i4iIiIiIiPQUhz8qgIiIiIiIiIjEDRX+IiIiIiIiIt2YCn8RERERERGRbkyFv4iIiIiIiEg3psJfbFVdXc0111xDYWEhSUlJTJo0iU2bNtkdq1O8Xi/Tpk2jT58+JCYmMnToUJ566im7Y3WKYRgHfMyePdvuaJ2yYcMGzj//fNLT00lOTubkk0+mrKzM7lgdds011+z3GU2aNMnuWDFz4403YhgGjz/+uN1ROmXmzJkMHjyY5ORkevXqxfjx4/nss8/sjtVhoVCIO+64gxNOOIHk5GQKCwu5+uqrqaiosDtah7322mtMmDCBrKwsDMNg1apVdkfqtLlz59K3b18SEhIYM2YMy5YtsztSpyxatIjJkydTWFiIYRi88cYbdkfqlAcffJCTTz6Z1NRUcnNzufDCC9m4caPdsTrlySefZNiwYaSlpZGWlsbYsWP5+9//bnesmHrooYcwDINbb73V7igdNnPmzP2+OwwePNjuWJ1WXl7OlVdeSVZWFomJiZxwwgksX77c7lgd1rdv3wN+F586deoh70OFv9jGsiwuvPBCtm7dyl//+le++OILSkpKGD9+PD6fz+54HTZ9+nTmzZvHSy+9xIYNG7j11luZNm0ab775pt3ROqyysrLd47nnnsMwDC6++GK7o3XYli1bOP300xk8eDALFy7kyy+/5Je//CUJCQl2R+uUSZMmtfus/ud//sfuSDHx+uuvs3TpUgoLC+2O0mnHHHMMv/3tb1mzZg0ff/wxffv2ZcKECezatcvuaB3i9/tZuXIlv/zlL1m5ciWvvfYaGzdu5Pzzz7c7Wof5fD5OP/10Zs2aZXeUmHjllVeYPn0699xzDytXrmT48OFMnDiRmpoau6N1mM/nY/jw4cydO9fuKDHx0UcfMXXqVJYuXcr8+fMJhUJMmDAhrr8P9enTh4ceeogVK1awfPlyzjnnHC644ALWrVtnd7SY+Pzzz3n66acZNmyY3VE67bjjjmv33eHjjz+2O1Kn7Nmzh9NOOw2Xy8Xf//531q9fz69//Wt69epld7QO+/zzz9t9RvPnzwfgRz/60aHvxBKxycaNGy3AWrt2bdu8SCRi5eTkWL///e9tTNY5xx13nHXfffe1mzdixAjrzjvvtClR7F1wwQXWOeecY3eMTrn00kutK6+80u4YMTVlyhTrggsusDtGzO3cudPq3bu3tXbtWqukpMR67LHH7I4UUw0NDRZgvf/++3ZHiZlly5ZZgLV9+3a7o3RKaWmpBVhffPGF3VE6ZfTo0dbUqVPbXkciEauwsNB68MEHbUwVO4D1+uuv2x0jpmpqaizA+uijj+yOElO9evWy/vCHP9gdo9OampqsQYMGWfPnz7fOOuss65ZbbrE7Uofdc8891vDhw+2OEVN33HGHdfrpp9sdo0vdcsst1oABA6xoNHrI2+iMv9gmEAgAtDvDapomHo8nro80nnrqqbz55puUl5djWRYffvgh//znP5kwYYLd0WKiurqat99+m+uuu87uKB0WjUZ5++23OeaYY5g4cSK5ubmMGTMm7ruKAixcuJDc3FyOPfZYbrrpJnbv3m13pE6JRqNcddVV3HbbbRx33HF2x4m5YDDIM888Q3p6OsOHD7c7Tsw0NDRgGAYZGRl2R+nxgsEgK1asYPz48W3zTNNk/PjxLFmyxMZkcjANDQ0AZGZm2pwkNiKRCH/+85/x+XyMHTvW7jidNnXqVM4777x2P1fxbNOmTRQWFtK/f3+uuOKKuL7sEeDNN99k1KhR/OhHPyI3N5eTTjqJ3//+93bHiplgMMhLL73Etddei2EYh7ydCn+xzeDBgykuLmbGjBns2bOHYDDIrFmz2LlzJ5WVlXbH67A5c+YwdOhQ+vTpg9vtZtKkScydO5czzzzT7mgx8cc//pHU1FR++MMf2h2lw2pqavB6vTz00ENMmjSJ9957j4suuogf/vCHfPTRR3bH67BJkybx4osvsmDBAmbNmsVHH33EueeeSyQSsTtah82aNQun08l//Md/2B0lpt566y1SUlJISEjgscceY/78+WRnZ9sdKyZaWlq44447uPzyy0lLS7M7To9XW1tLJBIhLy+v3fy8vDyqqqpsSiUHE41GufXWWznttNM4/vjj7Y7TKWvWrCElJQWPx8ONN97I66+/ztChQ+2O1Sl//vOfWblyJQ8++KDdUWJizJgxvPDCC8ybN48nn3yS0tJSzjjjDJqamuyO1mFbt27lySefZNCgQbz77rvcdNNN/Md//Ad//OMf7Y4WE2+88Qb19fVcc801h7dh13VAEGnvpZdespKTk9seixYtspYvX24NHz7cAiyHw2FNnDjROvfcc61JkybZHfeQHKhNs2fPto455hjrzTfftFavXm3NmTPHSklJsebPn2933ENyoDZ93bHHHmtNmzbNpnQd8802LVy40AKsyy+/vN16kydPti677DKbUh6e7/qcLMuytmzZElddyA/0OeXl5Vnl5eVt68RbV/9v+5y8Xq+1adMma8mSJda1115r9e3b16qurrY57aE52L+9YDBoTZ482TrppJOshoYGG1MeuoO1pzt09S8vL7cA69NPP203/7bbbrNGjx5tU6rYopt19b/xxhutkpISa8eOHXZH6bRAIGBt2rTJWr58ufXzn//cys7OttatW2d3rA4rKyuzcnNzrdWrV7fNi/eu/t+0Z88eKy0tLa4vyXC5XNbYsWPbzbv55putU045xaZEsTVhwgTrBz/4wWFv54zxAQiRb3X++eczZsyYtte9e/cmMTGRVatW0dDQQDAYJCcnhzFjxjBq1Cgbkx66A7Vp3LhxvP7665x33nkADBs2jFWrVvHII4/ERZewA7Vpn8WLF7Nx40ZeeeUVO6J12DfblJOTg9Pp3O+sw5AhQ+LmMpODfU779O/fn+zsbDZv3sy4ceOOZLwO+WabXn31VWpqaiguLm6bF4lE+M///E8ef/xxtm3bZkPKw/Ntn1NycjIDBw5k4MCBnHLKKQwaNIhnn32WGTNm2BX1kH1bm0KhEJdccgnbt2/ngw8+iJuz/YfysxTPsrOzcTgcVFdXt5tfXV1Nfn6+Tank20ybNo233nqLRYsW0adPH7vjdJrb7WbgwIEAjBw5ks8//5wnnniCp59+2uZkHbNixQpqamoYMWJE27xIJMKiRYv47W9/SyAQwOFw2Jiw8zIyMjjmmGPYvHmz3VE6rKCg4IDf8f7yl7/YlCh2tm/fzvvvv89rr7122Nuq8JcjJjU1ldTU1AMuS09PB1qvMVq+fDm/+tWvjmS0DvtmmxobGwmFQphm+6toHA4H0Wj0SMfrkIN9Ts8++ywjR46Mu2uRD9Smk08+eb9bJf3zn/+kpKTkSEbrsIN9Tvvs3LmT3bt3U1BQcIRSdc4323TDDTcwefLkdutMnDiRq666ih//+MdHOl6HHMrnBK1de/eNe3K0O1Cb9hX9mzZt4sMPPyQrK8umdIfvUD+jeOV2uxk5ciQLFizgwgsvBFr/vS1YsIBp06bZG07aWJbFzTffzOuvv87ChQvp16+f3ZG6RDz9rjuQcePGsWbNmnbzfvzjHzN48GDuuOOOuC/6ofW21Fu2bOGqq66yO0qHnXbaaXH9He9gnn/+eXJzc9tOMB4OFf5iq1dffZWcnByKi4tZs2YNt9xyCxdeeGHcDoSXlpbGWWedxW233UZiYiIlJSV89NFHvPjiizz66KN2x+uUxsZGXn31VX7961/bHSUmbrvtNi699FLOPPNMzj77bObNm8ff/vY3Fi5caHe0DvF6vdx7771cfPHF5Ofns2XLFm6//XYGDhzIxIkT7Y7XIVlZWfsVkC6Xi/z8fI499libUnWOz+fj/vvv5/zzz6egoIDa2lrmzp1LeXn54d2S5ygSCoX413/9V1auXMlbb71FJBJpu3Y8MzMTt9ttc8LDV1dXR1lZGRUVFQBtXyDz8/Pj8iz59OnTmTJlCqNGjWL06NE8/vjj+Hy+uDmAdiBer7fdGcnS0lJWrVpFZmZmu15C8WLq1Km8/PLL/PWvfyU1NbXtZyg9PZ3ExESb03XMjBkzOPfccykuLqapqYmXX36ZhQsX8u6779odrcNSU1P3G3chOTmZrKysuB2P4Wc/+xmTJ0+mpKSEiooK7rnnHhwOB5dffrnd0Trspz/9KaeeeioPPPAAl1xyCcuWLeOZZ57hmWeesTtap0SjUZ5//nmmTJmC09mBMj72Vx2IHLonnnjC6tOnj+Vyuazi4mLrrrvusgKBgN2xOqWystK65pprrMLCQishIcE69thjrV//+teHdbuNo9HTTz9tJSYmWvX19XZHiZlnn33WGjhwoJWQkGANHz7ceuONN+yO1GF+v9+aMGGClZOTY7lcLqukpMS6/vrrraqqKrujxVS8XeP/Tc3NzdZFF11kFRYWWm632yooKLDOP/98a9myZXZH67B918Ef6PHhhx/aHa9Dnn/++QO255577rE7WofNmTPHKi4uttxutzV69Ghr6dKldkfqlA8//PCAn9GUKVPsjtYh3/Yz9Pzzz9sdrcOuvfZaq6SkxHK73VZOTo41btw467333rM7VszF+zX+l156qVVQUGC53W6rd+/e1qWXXmpt3rzZ7lid9re//c06/vjjLY/HYw0ePNh65pln7I7Uae+++64FWBs3buzQ9oZlWVYnDjyIiIiIiIiIyFFMt/MTERERERER6cZU+IuIiIiIiIh0Yyr8RURERERERLoxFf4iIiIiIiIi3ZgKfxEREREREZFuTIW/iIiIiIiISDemwl9ERERERESkG1PhLyIiIiIiItKNqfAXERGRDps8eTKTJk064LLFixdjGAarV6/m8ssvp6ioiMTERIYMGcITTzyx3/p/+tOfGD58OElJSRQUFHDttdeye/furm6CiIhIt6fCX0RERDrsuuuuY/78+ezcuXO/Zc8//zyjRo1ixYoV5Obm8tJLL7Fu3TruvPNOZsyYwW9/+9u2dT/55BOuvvpqrrvuOtatW8err77KsmXLuP76649kc0RERLolw7Isy+4QIiIiEp/C4TB9+vRh2rRp3HXXXW3zvV4vBQUFzJ49mxtvvHG/7aZOncqGDRv44IMPAHjkkUd48skn2bJlS9s6c+bMYdasWQc8qCAiIiKHTmf8RUREpMOcTidXX301L7zwAl8/l/Dqq68SiUS4/PLLD7hdQ0MDmZmZba/Hjh3Ljh07eOedd7Asi+rqav7v//6P73//+13eBhERke5OZ/xFRESkU/7xj38wZMgQPvzwQ773ve8BcOaZZ1JSUsJ///d/77f+p59+yllnncXbb7/NhAkT2ua/+uqrXHvttbS0tBAOh5k8eTJ/+ctfcLlcR6opIiIi3ZLO+IuIiEinDB48mFNPPZXnnnsOgM2bN7N48WKuu+66/dZdu3YtF1xwAffcc0+7on/9+vXccsst3H333axYsYJ58+axbdu2A14mICIiIodHZ/xFRESk05577jluvvlmqqqqeOihh3jllVfYtGkThmG0rbN+/XrOPvtsfvKTn3D//fe32/6qq66ipaWFV199tW3exx9/zBlnnEFFRQUFBQVHrC0iIiLdjc74i4iISKddcsklmKbJyy+/zIsvvsi1117bruhft24dZ599NlOmTNmv6Afw+/2YZvuvJQ6HAwCdoxAREekcnfEXERGRmPjJT37Ca6+9RmNjI2VlZRQWFgKt3fvPOeccJk6cyOzZs9vWdzgc5OTkAPDCCy9w/fXX85vf/IaJEydSWVnJrbfeimmafPbZZ7a0R0REpLtQ4S8iIiIxsWTJEk499VS+//3v8/bbb7fNnzlzJvfee+9+65eUlLBt27a213PmzOGpp56itLSUjIwMzjnnHGbNmkXv3r2PRHwREZFuS4W/iIiIiIiISDema/xFREREREREujEV/iIiIiIiIiLdmAp/ERERERERkW5Mhb+IiIiIiIhIN6bCX0RERERERKQbU+EvIiIiIiIi0o2p8BcRERERERHpxlT4i4iIiIiIiHRjKvxFREREREREujEV/iIiIiIiIiLdmAp/ERERERERkW5Mhb+IiIiIiIhIN/b/AaUUauLC7yVJAAAAAElFTkSuQmCC\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x700 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x700 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x700 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x700 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x700 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x700 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x700 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x700 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x700 with 2 Axes>"
            ],
            "image/png": 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5LH9kZGRIyx0J0zRbPW/jlQ5dyaEuP+9KOuP/5f4aL5dvvHzeNM1g6Q/1UvrGqwDee++9Q85XVlYWnKejL9vvLg73vXO4f8eh/jvvLt8fANCV8JMTAMLQ3Llzg49JO/vss1u9XFpamq699lq99tpr2rJli3JzczVmzBht2bJFd999d0fFPaS8vLxmX298BFhERESTe81dLpcktXhpduOZ0/bSeJn13r17VVFR0ew8W7dubTKvVRq335inOV0lqyT9+Mc/VkxMjDZu3Kgvv/xSCxYsUH5+/mGfZ38o0dHRkqTi4uJDzjdnzhzV1dUpJydHp59+ekjbOhKNZ603bNjQqvkb//+09P0hHfn/y87+3gEAdByKPgCEmfLyct12222SpLPOOqvJ4HBHavDgwbrrrrskNdzvvL/GUuDz+UJef2u8+eabzb7e+Iz5cePGBZ+NLv3/UpObm3vQMjU1NS3erxzq+8nIyAheIn3g88WlpgO6TZw48YjW3d7Gjx8vm82mNWvWaO3atQdN3717d/BecauzSg2XfDfeZ/7yyy8HL6W/9NJLQ36efeMz2w83oOBf/vIXSQ1XALRmnIu2anwU4ty5c7Vr167Dzn/CCScoJiZGpaWlev/99w+avv8jCFv7//JQ3zuFhYVatWpVq9YDALAeRR8AwoRpmvroo4900kknadOmTerdu3eLo7wf6NNPP9XcuXMPGvXaNE395z//kSRlZ2c3mZaRkSFJHfIc9f2tXLlSTz75ZJPXFi9eHBxxvPGPGo3OPPNMSdLs2bOb3JtcXV2tn//85y2O0N34ftavX3/EGX/5y19Kkh555JEmBdo0Tf3mN7/RmjVrlJCQoGuvvfaI192esrKy9KMf/Uimaep///d/m4xt0Lh/6urqNHbsWI0dO9bCpP9f42Xz7777bqsupZ8zZ45Wrlx50Oumaeqf//xncJT3n//85y2u45tvvtGqVatks9l05ZVXtiF9640YMUIXXHCBamtrdcEFF6igoKDJdJ/P16TQR0REaObMmZKkX/ziF03Otnu9Xt1yyy0qLCxUTk6OLr744lZlaPze+e1vf6uysrLg63v27NEVV1yhqqqqUN8eAKCTOQ4/CwCgq3nppZe0cOFCSVJ9fb1KSkq0atUqlZaWSpImTJigl19++aBy3pJvvvlGt912m+Li4jRy5Ej16dNHtbW1WrVqlfLz8xUfH6+HH364yTLTpk3TZ599punTp+vss88ODlZ2xx13aNCgQe32Xm+++Wbdc889ev311zV8+HDt2rVLX3zxhQKBgG655ZaDRvL+8Y9/rP/7v//TihUrdMwxx2jcuHEKBAJasWKFXC6XfvaznzX7yLbRo0erT58+Wr16tUaOHKljjz1WTqdTgwYN0h133HHIjP/7v/+rJUuW6I033tAJJ5yg0047TampqVq1apU2btyoyMhIzZkzR7169Wq3/RKq2bNna8OGDVq+fLkGDBigiRMnyuFwaNGiRdqzZ49ycnL01ltvWR0zaPTo0Ro6dGjwDzAjRozQyJEjW5z/448/1mWXXaaMjAwNHz5cCQkJ2rt3rzZs2BAswzNnzjxk0W88m3/22WcrMzOzHd/Nob3yyis655xztGzZMh111FEaO3as+vTpo8LCQq1bt0579uxpMh7FQw89pBUrVmjBggUaMmSIJk6cqNjYWC1dulQFBQVKTk7W3/72t+DVKoczc+ZMvfjii1q1apUGDRqkMWPGqLq6Wl9//bWysrL0P//zP/rXv/7VQe8eANCeKPoA0A19+eWX+vLLLyU13HMcHx+vY489VieccIJ+8pOf6MQTTzyi9Z133nkqLy/XF198oU2bNmnZsmWKjIxUZmam7r77bs2cOTN4xrvR9ddfr8rKSr355puaO3ducOTr6dOnt2vRv/DCC3XBBRfoscce09y5c+XxeDRy5EjdeOONzT7Ozul06pNPPtH999+vf/3rX/r444+VmpqqCy+8UI888oief/75Zrfjcrk0f/583XfffVq6dKnWrl2rQCCg00477bBF3zAMvf7665oyZYr+/Oc/a+XKlaqurlZ6erquvPJK3X333e26T9oiOTlZS5Ys0bPPPqt33nlHH3/8sQKBgHJycnTttdfql7/8ZYePMH+krr76av3iF7+QJP3sZz875LzXXnut4uPjtWTJEq1atUp79+6V0+lURkaGZsyYoWuuuUbjxo1rcXmPxxP8Q8fhttXeEhMTtWjRIr388suaM2eO1qxZoyVLlig1NVUjRozQ//zP/zSZ3+12a968eXrxxRf1+uuv64svvlB9fb0yMzN100036a677jqisRYSEhL05Zdf6t5779W8efP00UcfqW/fvvr5z3+uBx54QDfeeGM7v2MAQEcxzCMZqhgAAAAAAHRp3KMPAAAAAEAYoegDAAAAABBGKPoAAAAAAIQRij4AAAAAAGGEog8AAAAAQBih6AMAAAAAEEYo+gAAAAAAhBGKPgAAAAAAYYSiDwAAAABAGKHoAwAAAAAQRij6AAAAAACEEYo+AAAAAABhhKIPAAAAAEAYoegDAAAAABBGKPoAAAAAAIQRij4AAAAAAGGEog8AAAAAQBih6AMAAAAAEEYo+gAAAAAAhBGKPgAAAAAAYYSiDwAAAABAGKHoAwAAAAAQRij6AAAAAACEEYo+AAAAAABhhKIPAAAAAEAYoegDAAAAABBGKPoAAAAAAIQRij4AAAAAAGGEog8AAAAAQBih6AMAAAAAEEYo+gAAAAAAhBGKPgAAAAAAYYSiDwAAAABAGKHoAwAAAAAQRij6AAAAAACEEYo+AAAAAABhhKIPAAAAAEAYoegDAAAAABBGKPoAAAAAAIQRij4AAAAAAGGEog8AAAAAQBih6AMAAAAAEEYo+gAAAAAAhBGKPgAAAAAAYYSiDwAAAABAGKHoAwAAAAAQRij6AAAAAACEEYo+AAAAAABhhKIPAAAAAEAYoegDAAAAABBGKPoAAAAAAIQRij4AAAAAAGHEYXWA7igQCGjXrl2KjY2VYRhWxwEAAAAAhDnTNFVZWak+ffrIZjv0OXuKfgh27dqlzMxMq2MAAAAAAHqY7du3KyMj45DzUPRDEBsbK6lhB8fFxVmcBgAAAAAQ7ioqKpSZmRnso4dC0Q9B4+X6cXFxFH0AAAAAQKdpze3jDMYHAAAAAEAYoegDAAAAABBGKPoAAAAAAIQRij4AAAAAAGGEog8AAAAAQBih6AMAAAAAEEYo+gAAAAAAhBGKPgAAAAAAYYSiDwAAAABAGHFYHQAA0LWZpimPx2N1jC5v//3kcrlkGIbFicIL+xQAgNaj6AMADsnj8eiWW26xOgZ6uGeeeUZut9vqGAAAdAtcug8AAAAAQBjhjD4AoNXuGBspl93qFF2Tx2/qqSV1kqQ7xkbIZecy87by+KWnltRaHQMAgG6Hog8AaDWXXRTYVnDZDfZTuzCtDgAAQLfEpfsAAAAAAIQRij4AAAAAAGGEog8AAAAAQBih6AMAAAAAEEYo+gAAAAAAhBGKPgAAAAAAYYSiDwAAAABAGKHoAwAAAAAQRij6AAAAAACEEYo+AAAAAABhhKIPAAAAAEAYoegDAAAAABBGKPoAAAAAAIQRij4AAAAAAGGEog8AAAAAQBih6AMAAAAAEEYo+gAAAAAAhBGKPgAAAAAAYYSiDwAAAABAGKHoAwAAAAAQRij6AAAAAACEEYo+AAAAAABhhKIPAAAAAEAYoegDAAAAABBGKPoAAAAAAIQRh9UB0DOZpimPxyNJcrlcMgzD4kQAAABoK47xgK6BM/qwhMfj0S233KJbbrkl+MsAAAAA3RvHeEDXQNEHAAAAACCMUPQBAAAAAAgjFH0AAAAAAMIIRR8AAAAAgDBC0QcAAAAAIIxQ9AEAAAAACCMUfQAAAAAAwghFHwAAAACAMELRBwAAAAAgjFD0AQAAAAAIIxR9AAAAAADCCEUfAAAAAIAwQtEHAAAAACCMUPQBAAAAAAgjFH0AAAAAAMIIRR8AAAAAgDBC0QcAAAAAIIxQ9AEAAAAACCMUfQAAAAAAwghFHwAAAACAMELRBwAAAAAgjFD0AQAAAAAIIxR9AAAAAADCCEUfAAAAAIAw4rA6ADrWN998o7fffls//elPNXz48DbP19xyr7/+uiTpiiuuOOyy77//vubNm6czzzyz1dsAAABA93PLLbe0eR0JCQkqKyuTJNntdkmS3+8/aD6n06mzzjpLn3/+uXw+nxwOh6644gpJCh6rDho0SCtXrpQkDRgwQPv27dNPf/pTSdLbb7+t0aNHa9myZU1e2//YuLnj3sZj6JycHK1evVqTJ0/W+eeff9Cx9f7zrVq1Sk6nUy6XS+PHj9fnn3/eZJ2NGrdXX18vn8+nKVOmqF+/fnrxxRfl9XqbvIcDl2vcduP79/l8khTcL/tnau3x/4HrDbU7NLdfDlzPiy++qJUrV2rUqFG69tprW73+UIXahboyin4Y83g8mjNnjsrKyjRnzhwNHjxYLpcr5PmaW+6tt95SVVWVJOmtt9465LJVVVX66KOPZJqmPvnkk7a9OQDoplYG9mq2b6NmOgZplC3Z6jgA0KU1lnyp+YLfyOv1au7cuU1ee/PNNyUpeKzaWPIlacuWLZIajl8lqby8PHicuv9rjcfGjfPuf9zbv3//4DF0aWmpJOmjjz7SuHHjmhxbNzefx+ORx+Npknn/Y+kDj7Mlae7cuYqJiZHX623yHvY/ft//uP6tt96SaZpN1tFc9tYc/x+43gP3T2u7Q0v7Zf/1lJaWBv9frVy5UtOmTVNSUtJh1x+qULtQV8el+2Fs3rx5Ki8vl9TwjThv3rw2zXeo5Vqz7AsvvCDTNCUp+F8A6ElM09TLvs0qMKv1sm8zPwsBoANVVFSooqLikPOUl5cHj2cbfybv/1rj8W1zx70vvPBCk9ca1/HUU081Wb65+VrK0ngsfeD2Gh1Y2g+1XHl5ebPv/8BMrTn+P3C9be0Oh8rw1FNPNVnuwK/bW6hdqKvjjH6YKi4u1rx585oU6/nz52v06NFKTU094vlaWv+B5s2b1+yyubm52rx5c7Prqq+vP+L3B6Dz7P892vCzwrAuTDe3wtyrjWbDQddGs0IrzL060UixOFXXtf8fQvhdAXQPL730ktUR2pVpmi0Wv5aObfft29dk+Zbma868efN01FFHHVHZbDx+b1yuNX9E3j/T4Y7/D+wLzW27td1h/87RXAa3291k/0kN+3Pp0qUaM2bMYd/XkQq1C3UHFP1WqK+vb3KAcbi/DFrNNE29/fbbLb5+0003yTCMVs/X0vRAIHDQtEAgoL/+9a+6+eabg8sGAoFD/tC/8847j+TtAbCQNyC5rQ7RTZmmqVd9W2STFFDDJXWv+rboBGdysz9r0fDvrRG/KwBYpblj3o7c1ksvvXTE2/T7/W36I0tLx/8t9YXWLHsk62ic77333mt22htvvKGTTjopOE5Dewi1C3UXXLrfCo8//rji4+ODH5mZmVZHOqTCwkKtX7/+oB8QgUBA69evV2Fh4RHN19L6W5Kbm9tk2W+//VbV1dWhvh0ACAuNZ/Mbf+IG9P/P6gMA0CjU4+bq6uqQ/yjR0vF/S32hNcseyToa13OoaV988cUhlz9SoXah7oIz+q1wzz336Pbbbw9+XVFR0aXLfnp6uoYOHaoNGzY0+Ydrs9k0ePBgpaenH9F8La2/pbI/ZMiQJssOGzZM0dHRLf7QeuKJJxQZGXnE7xNA56ivrw+eTXXy5+GQHHg2vxFn9Q9t/39vTz75pNxuricBurL9f18gdIc6bj7ccrW1tSGV/ZaO/1vqC61Z9kjW0bieQ23j1FNPbeW7aZ1Qu1B3QdFvBbfb3a0OLgzD0E9/+lM9+OCDB71+ySWXBA8mWzvfodZ/4DejzWbTpZde2mRZm82ma665Rs8880yz64uMjOxW+xfoySijodn/3vz97X9Wn3v1D7b/v7fu9rsY6IncbrdGjBihNWvWWB2lXdlsDX917IxL+G02m6699lo9++yzR7Q9u90eXC4ULR3/t9QXWrPskayjcb4LL7yw2cv3Z8yY0a6X7R8q1+HeT3fBuZkwlZqaqsmTJzcp9ZMmTVKvXr1Cmq+l9R9o8uTJzS47ZMgQDRw4MNS3AwDdVuPZ/JYOFww1nNVnBH4A4eCqq66yOkK7MgxDkydPbva4d+DAgc2WwcTExCbH1i3N15zJkydr8ODBzW7vUBknTZoUXK4129o/0+GO/w/sC81tu7XdoaX90rieSZMmKTExscmyiYmJOvnkkw/7nkIRahfqDij6YWzy5MmKj4+XJMXHx7f4A6O18x1qudYse9111zX5JgKAnsArU8VmnVqq8aakYrNO3hbnAACEIj4+XnFxcYecJyEhIXg823h8uv9rjce3zR33XnfddU1ea1zHHXfc0WT55uZrKUvjsfSB22sUExPT7PtsbrmW3n9CQkKTTK05/t9/vc3tn9Y4MFtLGe64444myx34dXsLtQt1dRT9MOZyuXTppZcqKSlJl156qVwuV5vma265yy67TDExMYqJidFll112yGVjYmI0ZcoU2Ww2nXXWWSG9JwDoblyGTbNdJ+uPzpY/nnedLJfBr2QAOFBCQkLwc7vd3uLl206nU+ecc45iYmIUERERPDadPn168Fh11KhRwfkHDBgQPPa97LLLlJSUpClTphz0WuOxcXPHvTExMcFj6FGjRslmszVZR+N/D5zPMAy5XC7FxMQEMzfO03gsvf/2nE6nDMPQOeecoyuuuEJOp/Og97D/co3b2v/9R0REBPfLgZlac/x/YF84cP+0xoHraClD436SpFGjRikpKalV6w9VqF2oqzNMrhU8YhUVFYqPj1d5eflh/0qI5tXX1+uWW26RJD3zzDPcdwl0Yft/v953aqRcdq7IaY7Hb+rRL2olsZ/ay/77lN8VQPfAMR7QcY6kh3L6AAAAAACAMELRBwAAAAAgjFD0AQAAAAAIIxR9AAAAAADCCEUfAAAAAIAwQtEHAAAAACCMUPQBAAAAAAgjFH0AAAAAAMIIRR8AAAAAgDBC0QcAAAAAIIxQ9AEAAAAACCMUfQAAAAAAwghFHwAAAACAMELRBwAAAAAgjFD0AQAAAAAIIxR9AAAAAADCCEUfAAAAAIAwQtEHAAAAACCMUPQBAAAAAAgjFH0AAAAAAMIIRR8AAAAAgDBC0QcAAAAAIIxQ9AEAAAAACCMUfQAAAAAAwojD6gDomVwul5555png5wAAAOj+OMYDugaKPixhGIbcbrfVMQAAANCOOMYDugYu3QcAAAAAIIxQ9AEAAAAACCMUfQAAAAAAwghFHwAAAACAMELRBwAAAAAgjFD0AQAAAAAIIxR9AAAAAADCCEUfAAAAAIAwQtEHAAAAACCMUPQBAAAAAAgjFH0AAAAAAMIIRR8AAAAAgDBC0QcAAAAAIIxQ9AEAAAAACCMUfQAAAAAAwghFHwAAAACAMELRBwAAAAAgjFD0AQAAAAAIIxR9AAAAAADCCEUfAAAAAIAwQtEHAAAAACCMUPQBAAAAAAgjFH0AAAAAAMIIRR8AAAAAgDDisDoAAKD78PglybQ6Rpfk8ZvNfo7QNfx7AwAAR4qiDwBotaeW1FodoVt4akmd1REAAEAPxqX7AAAAAACEEc7oAwAOyeVy6ZlnnrE6RpdnmqY8Ho+khn1mGIbFicKLy+WyOgIAAN0GRR8AcEiGYcjtdlsdo1uIiIiwOgIAAACX7gMAAAAAEE4o+gAAAAAAhBGKPgAAAAAAYYSiDwAAAABAGKHoAwAAAAAQRij6AAAAAACEEYo+AAAAAABhhKIPAAAAAEAYoegDAAAAABBGKPoAAAAAAIQRij4AAAAAAGHEYXWA7sg0TUlSRUWFxUkAAAAAAD1BY/9s7KOHQtEPQWVlpSQpMzPT4iQAAAAAgJ6ksrJS8fHxh5zHMFvz5wA0EQgEtGvXLsXGxsowDKvj4BAqKiqUmZmp7du3Ky4uzuo4lmAfsA8k9kEj9gP7QGIfNGI/sA8k9kEj9gP7QOr6+8A0TVVWVqpPnz6y2Q59Fz5n9ENgs9mUkZFhdQwcgbi4uC75zdqZ2AfsA4l90Ij9wD6Q2AeN2A/sA4l90Ij9wD6QuvY+ONyZ/EYMxgcAAAAAQBih6AMAAAAAEEYo+ghrbrdbv/71r+V2u62OYhn2AftAYh80Yj+wDyT2QSP2A/tAYh80Yj+wD6Tw2gcMxgcAAAAAQBjhjD4AAAAAAGGEog8AAAAAQBih6AMAAAAAEEYo+gAAAAAAhBGKPgAAAAAAYYSiDwAAAABAGKHoAwAAAAAQRij6AAAAAACEEYo+AAAAAABhhKIPAAAAAEAYoegDAAAAABBGKPoAAAAAAIQRij4AAAAAAGGEog8AAAAAQBih6AMAAAAAEEYo+gAAAAAAhBGKPgAAAAAAYYSiDwAAAABAGKHoAwAAAAAQRij6AAAAAACEEYo+AAAAAABhhKIPAAAAAEAYoegDAAAAABBGKPoAAAAAAIQRij4AAAAAAGGEog8AAAAAQBih6AMAAAAAEEYo+gAAAAAAhBGKPgAAAAAAYYSiDwAAAABAGKHoAwAAAAAQRij6AAAAAACEEYo+AAAAAABhhKIPAAAAAEAYoegDAAAAABBGKPoAAAAAAIQRij4AAAAAAGGEog8AAAAAQBih6AMAAAAAEEYo+gAAAAAAhBGKPgAAAAAAYcRhdYDuKBAIaNeuXYqNjZVhGFbHAQAAAACEOdM0VVlZqT59+shmO/Q5e4p+CHbt2qXMzEyrYwAAAAAAepjt27crIyPjkPNQ9EMQGxsrqWEHx8XFWZwGANAVeDwePf3005KkX/ziF3K5XBYnAgAA4aSiokKZmZnBPnooFP0QNF6uHxcXR9EHAEhqKPoRERGSGn4/UPQBAEBHaM3t4wzGBwAAAABAGKHoAwDQSarrqxU9M1rRM6NVXV9tdRwAABCmuHQfAIBOVOOpsToCAAAIc5zRBwAAAAAgjFD0AQAAAAAIIxR9AAAAAADCCEUfAAAAAIAwQtEHAAAAACCMMOo+AACdxGbYdNrRpwU/BwAA6AgUfQAAOkmkK1IL71hodQwAABDmOJ0AAAAAAEAYoegDAAAAABBGuHQfANAjmKapal+19tSWqKSuRDW+GtX66lTnb/gImAG5bC657C65bC5FOiKUEpGi1MhUJUUkym7Y25yhur5a/e7uJ0na9sQ2Rbuj27xOAACAA1H0AQBhy+P3aHvVDu2o3qE9tXtU66875Py1/lrV+muDXxdUbZck2Q27ekWkKCcuR/1is+Wwhf7rs6SqJORlAQAAWoOiDwAIK76AT9urdmhbZb521exSwAwEpxkylOROUq/IFMW54hRhj2j4cETIJkOegFeegEcev0dV3ioV1+5RcW2xPAGPCmuLVFhbpFV7VuuohIE6Ov5oRTujLHynAAAAzaPoAwDCQo23RhvLv9f3ZZvkCXiCr8e74pQdk63e0elKcicd0dn4Y9RwyX+5p1w7qnfq+7LvVe2r0bel3+m70vUaENdfI3sdL7fd3QHvCAAAIDQUfQBAt1ZaV6r1+3K1rTJfpkxJUrQjWjlx/dQvNlsJrgQZhhHy+g3DUII7QQnuBA1NHKIdVTu0oWyjimqLtblii7ZX79CJvUapj7tPe70lAACANqHoAwC6pXJPhdaWrFV+VUHwtdTIVA1JHKyM6L6yGe3/YBmbYVNWbJayYrNUXFusZUVfqdxTrsWFS5TmTG337QEAAISCog8A6FaqvdVau3edtlZsDZ7B7xebraGJQ5QckdxpOVIjUzU1e4rWl+bqm9J12l1b2GnbBgAAOBSKPgCgW/AFfPqudL2+3fddcIC9jOgMjUgZrkR3oiWZ7IZdxyYPU3Zslhbv+FLbtFWStH5fro5LHX7QLQM2w6YTsk8Ifg4AANARKPoAgC7NNE1tr96hFcUrVe2rliSlRabq+JQR6hXZy+J0DeJccTq970R9ra8kSWv3fqOqQJXGpI2W3WYPzhfpitTXv/raqpgAAKCHoOgDALqsSk+lvipeoV01uyRJUY4ondBrlLJiMts0wF5H2P8MvSFDeZXbVOmt0sS+pynCHmFhMgAA0NNw3SAAoMsJmAHl7tugD/I/1K6aXbIZNg1LOkbn9ztP2bFZXa7kH2hCn9PksrlUUleiT7YvUJ2/zupIAACgB6HoAwC6lPL6cs3f/olW7Fkpv+lXWmSazsuequNTRshp6x4XoqVHpWly1tmKtEeozFPWUPZ9daqpr1G/u/up3939VFNfY3VMAAAQprrHERMAIOwFzIDW78vV2r3fKGAG5LQ5NDJlpI6KH9jlz+A3J94Vr7Myz9In2z9pKPs7Fmhsr9HK35svScEnBgAAALQ3ij4AwHJV3ip9WbhExbV7JEl9o/vo5NSTFe2MsjhZ28S74pqU/U93LrQ6EgAA6AEo+gAAy5imqa2Vefq6+Gt5Az45DIdOSj1B/eP6d8uz+M1pUvZry6yOAwAAegCKPgDAEh6/R8uKliu/qkCS1Cuil05JH6NYV6zFydpfQ9k/U//e8kHwtYAZsDARAAAIZxR9AECn21tXqi92f6FKb5UMGTouebiOSRra5BF14SbeFa/xvU8Nfv1V8dc6PXNi2Fy5AAAAug6KPgCg05imqU3lm/T1npUKmAFFO6J0au9T1SsypdMyFBQUqKSkpN3X6/P5gp+vWbNGDsfBv2JrvbXBz/Mq8jTvO4/SPKntnuVwUlJSlJWV1enbBQAAnYOiDwDoFN6AT8uKlmlbZcOo8xnRfTU2fYzcdnenZSgoKNCQIUNUU9P+j7ZzOp267777JEnjxo2T1+s9eCa7pP+RouKiJMNQiXOvfvfY7/TpXxe0e55DiYqKUm5uLmUfAIAwZZimyfN9jlBFRYXi4+NVXl6uuLg4q+MAQJdX5a3Swl2fa1/9PhkydHzKCA1NHNLpl62vWrVKo0aN0qN/fEz9j+rfrusO+APatPR7SdJRY46WzX7o2xD8cQEF4gOSKdlLbLLVdc5tC1s3bdV919+rlStXauTIkZ2yTQAA0HZH0kM5ow8A6FBFNcVatPtz1fvrFWGP0Gl9TlVqZOdfrr6//kf115DjhrTrOn1eX7DoDzp2kBzOQ/+KNU1TO6p3ap9nn8xeUr+4fop0RLZrJgAA0DNR9AGgB+mo+9NbUurYp0J3oUxDivC7lVmdoR3lO7RDOzotw/5yc3Mt2W5zDMNQ3+g+8gQ8qvZVa1tVvgbGDZDT5rQ6GgAA6OYo+gDQQ3Tk/ekHMgxDP/7lTzT1mnMlScvnLtOL9/xZnjpPh2+7NaqqKi3Zbq2nVpfNvlSS9NbMOYp0RSo7JltbKraoPlCvbZX5GhDXP6yfPgAAADoeRR8AeoiSkhLV1NR0yP3p+zNlyp8UkBndMASMrdymU449ReP+M67DttlaXyz4Qs8/Plt19XUWJTC1tXhr8HNJctjs6hebrc0VW1Trr1VB1XZlx2Tx2D0AABAyij4A9DAdcX96o4AZUH5VgSq9DWfMM6IzlJSU2CHbCkXepjyrIzTLbXerX0y2tlbmqcJbocLaQvWO6m11LAAA0E1xbSAAoF34Aj5trdiqSm+lDBnqF5OtJHfXKfldXbQzWhnRGZKkPXUl2ltXanEiAADQXVH0AQBt5gv4tLUyTzX+WtkNu/rH5ijOxeNHj1SiO0FpPzyRYGfNzuCVEQAAAEeCog8AaBN/wK+8yjzV+evkMBwaENtf0c5oq2N1W6kRqUpwJUiS8qsKVOe3ajwBAADQXVH0AQAh85t+ba3MU62/ruFMflyOIhwRVsfq1gzDUEZ0X0U7ohQwA8qr3CZvwGt1LAAA0I1Q9AEAIfGbfuVVblPtfpfrR9gp+YdmqHdCH/VO6COp5VH1bYZN2THZctlc8ga8yqvcJn/A33kxAQBAt8ao+wCAIxYwA9pWma8aX43shk05sTmKdERaHavLi3RF6qO7PmrVvA6bQzmx/bSlYqvq/HXaVrVNObE5shn8jR4AABwaRwsAgCNimqZ2VO9Uta9aNjWU/ChKfodw293Kie0nm2FTta9G+VUFMk3T6lgAAKCL67JF/4knnpBhGLr11luDr9XV1WnmzJlKTk5WTEyMpk2bpqKioibLFRQUaOrUqYqKilJqaqruuOMO+Xy+JvMsXLhQI0eOlNvt1sCBA/Xqq692wjsCgPBQXFesMk+ZJCk7NktRjihrA4W5SEek+sX0kyFDld5K7ajeQdkHAACH1CWL/tdff60//elPGj58eJPXb7vtNn3wwQf629/+pkWLFmnXrl266KKLgtP9fr+mTp0qj8ejJUuW6LXXXtOrr76qBx54IDhPXl6epk6dqokTJ2rNmjW69dZbdc0112j+/Pmd9v4AoLvaV79PRbXFkqS+UX0V64y1OFH3Uuet06XPXapLn7tUdd7Wj6Yf44xWVkyWJGmfp0y7anZR9gEAQIu6XNGvqqrSZZddphdffFGJiYnB18vLy/WXv/xFv//973X66adr1KhReuWVV7RkyRItW7ZMkvTxxx9r/fr1evPNNzVixAhNmTJFjzzyiGbPni2PxyNJeuGFF5STk6Onn35aQ4YM0Y033qiLL75Ys2bNsuT9AkB3UeWt1o7qnZKkXhEpSo5IsjhR92OaAa3f+Z3W7/xOphk4omXjXXHKjM6QJO2tL9XOmp2UfQAA0KwuV/RnzpypqVOn6swzz2zy+sqVK+X1epu8PnjwYGVlZWnp0qWSpKVLl+rYY49VWlpacJ5JkyapoqJC3333XXCeA9c9adKk4DqaU19fr4qKiiYfANCTePwe5Vfly5SpeGec0iPTrY7UIyW6E5XxQ9kvrd+n7VzGDwAAmtGlRt1/++23tWrVKn399dcHTSssLJTL5VJCQkKT19PS0lRYWBicZ/+S3zi9cdqh5qmoqFBtba0iIw8eUOrxxx/XQw89FPL7AoDuLGAGlF9VIL/pV6Q9UpkxmTKMlh8Nh46V5E6UTYYKqrerzFMmU6ayovl/AgAA/r8uc0Z/+/btuuWWW/TWW28pIqJrPYf5nnvuUXl5efBj+/btVkcCgE6zu6ZQtf5a2Q27smOyeLxbF5DgTlB2TJYMGSr3lGtbVb78pt/qWAAAoIvoMkdrK1euVHFxsUaOHCmHwyGHw6FFixbp2WeflcPhUFpamjwej8rKyposV1RUpPT0hktI09PTDxqFv/Hrw80TFxfX7Nl8SXK73YqLi2vyAQA9QbmnXHvr90qSMqMz5LK7LE6ERvGu+GDZr/RWakvFVnn8HqtjAQCALqDLFP0zzjhD69at05o1a4IfJ5xwgi677LLg506nUwsWLAgus3HjRhUUFGjMmDGSpDFjxmjdunUqLi4OzvPJJ58oLi5OQ4cODc6z/zoa52lcBwCgQb2/Xturd0hqGHwvzsUfObuaOFecBsT1l8NwqM5fp80VW1TtrbY6FgAAsFiXuUc/NjZWw4YNa/JadHS0kpOTg69fffXVuv3225WUlKS4uDjddNNNGjNmjEaPHi1JOvvsszV06FBdfvnlevLJJ1VYWKhf/epXmjlzptxutyTpuuuu03PPPac777xTP/vZz/Tpp5/q3Xff1Ycffti5bxgAurCAGVBBVYECZkBRjigG32tHidGJh5/pCEQ5ojQwboC2VeWrzl+nrZV5yojuq0R3+24HAAB0H12m6LfGrFmzZLPZNG3aNNXX12vSpEl6/vnng9Ptdrv+85//6Prrr9eYMWMUHR2tGTNm6OGHHw7Ok5OTow8//FC33XabnnnmGWVkZOill17SpEmTrHhLANAlFdYWqdZfJ7thV1ZMFgO9tZNIV5Q++9XCdl+vy+7SgLj+2l61QxXeCm2v3qFqX7X6RPVhTAUAAHqgLl30Fy5c2OTriIgIzZ49W7Nnz25xmezsbM2dO/eQ650wYYJWr17dHhEBIOxUe6tVUlci6Yf78m1OixOhNRoHSyyqLVZxXbFK6/ep2lujrJhMRTqaH4MGAACEJ/7MDwAICpgB7ajeKUlKdCVwX343YxiG0qPS1D82Rw7DofpAvTZXbFFJXYlM07Q6HgAA6CQUfQBAUFFtkeoD9XIYDvWO6mN1nLBT563T1X++Wlf/+WrVees6bDsxzhgdHX+UYp2xMmVqV81u5VXmMSo/AAA9RJe+dB8A0HlqfDXa88Ml+xnRfeWw2S1OFH5MM6CVeSuCn3ckh82hfjHZ2lu/V7trClXlq9b35Zuk6A7dLAAA6AI4ow8AUMAMaHtVw6P0ErhkP2wYhqGUiBQdHX+UohxRCiigQFJAd71ytzwGZ/cBAAhXFH0AgIpqi4OX7PeJ6m11HLQzt92tAbH9G/7fBqRjxg7Tlqg8fV/2PffuAwAQhij6ANDD1fnrg6Ps943uI4eNu7rCUePZfUeRXRtXbFTACGh58df6744FqvJWWR0PAAC0I4o+APRgpmlqd80umTIV64xRnJNL9sOd4TP02PTfKL0+TXbDrsLaIn2w7UNtKtvM2X0AAMIERR8AerAKb6UqvVUyZKhPVB8ZhmF1JHQC0zSV7E3SudnnKDWyl3ymT8uKl+uL3YsZmR8AgDBA0QeAHipgBrS7ZrckKSUiRW672+JEPUOEM0IRzgirY0iS4lxxOjvjLI1MOV6GDOVXFejDgo9UUltidTQAANAG3IgJAD3UnroSeQIeOQ2HUiN7WR2nR4h0RWnZw8utjtGEYRg6JmmoUiNT9cXuxaryVmne9o81MuV4DUkczFUeAAB0Q5zRB4AeyOP3qLi2WJKUHtVbdsNucSJYrVdkis7NPkfZMVkyZWplySotLVomv+m3OhoAADhCFH0A6IF21xbKlKloR7QSXPFWx0EX4bK7dGrvcTqx1wkyZGhLxVYt2PGZ6v31VkcDAABHgKIPAD1MwGWq3FMuSeoT1ZtLsztRvbdeN756o2589UbVe7tmeTYMQ4MTB2li39PkMBwqqi3SvO0fq9JTaXU0AADQShR9AOhhAvEBSVKiK1GRjkiL0/QsAdOvxRu/0OKNXyjQxS+J7xvdV5OzzlaUI0oVngp9tH2+9taVWh0LAAC0AkUfAHqQYacMkxlhypChtMhUq+Ogi0t0J2pK1mQluZNU76/Xf3csUCllHwCALq/din5NTY1efvll/fGPf1R+fn57rRYA0E5MmfrR7T+RJCVHJMtld1mcCN1BlCNSZ2WcqZSIFHkCHn1C2QcAoMsLqehfffXVGjZsWPBrj8ej0aNH65prrtHMmTM1YsQIrV69ut1CAgDarsJRqZxhOVJASo3gcXpoPZfdqTP6TqTsAwDQTYRU9D/77DNddNFFwa/nzJmjb7/9Vm+99Za+/fZbpaen66GHHmq3kACAtgmYARW79kiSbJU2OWwOixOhu3HZXT+U/eRg2d9Xv8/qWAAAoBkhFf3CwkL169cv+PW//vUvnXDCCbrkkks0dOhQXXvttVq+fHl7ZQQAtNHm8i3y2Dyq2FsuWyWj7CM0DWX/9GDZ/3TnZ6r21lgdCwAAHCCkoh8dHa2ysjJJks/n08KFCzVp0qTg9NjYWJWXl7dLQABA2/gCPn2zd50k6d/P/0uGSdFH6BrLfrwrXjW+Wn22a6G8Aa/VsQAAwH5CKvojR47Uiy++qNWrV+vRRx9VZWWlzjvvvOD0LVu2KC0trd1CAgBCt6l8s2r9tXIGnPrsnc+sjtOjRbqitObxtVrz+FpFuqKsjhMyl92l0/tOUIQ9Qvvq9+nzXV8oYAasjgUAAH4QUtF/9NFHVVxcrBNOOEEPPfSQpk2bppNOOik4/b333tMpp5zSbiEBAKHxB/z6rnS9JCnFkyyf12dxIoSLGGeMJvadILth166a3fq6eIVM07Q6FgAAkBTSaEwnnHCCNmzYoCVLlighIUGnnXZacFpZWZluuOGGJq8BAKyxpWKLav21inJEKcEXb3UchJmUiGSd2vsULdz1ub4v36QYZ4yOSRpqdSwAAHq8kIdd7tWrly644IKDXk9ISNAtt9zSplAAgLYLmAF9+8PZ/GMSh6qmrNriRKj31uu+d++TJD3640fldrotTtR2mTGZOqHXKK3Ys1KrS9YoKSJJvaPSrY4FAECP1qbnK1VWVio/P1/79u1r9nK98ePHt2X1AIA22FqRp2pftSLsERoYP0Df6BurI/V4AdOv/377iSTpkR89bHGa9jMkcbD21ZdpS8UWfbF7sc7NOkdRzu47BgEAAN1dSEV/7969uvHGG/WPf/xDfr//oOmmacowjGanAQA6XsPZ/O8kSUMTh8hha9PfdYHDOin1BJXWlzYMzrf7C52Veabsht3qWAAA9EghHflde+21+uCDD3TzzTfr1FNPVWJiYnvnAgC0QX5lviq9lXLb3Do64Sir46AHcNgcOq33qZpbME976kq0as9qnZh6gtWxAADokUIq+h9//LFuu+02Pfnkk+2dBwDQRqZpat0PZ/OHJA6W0+a0OBF6ilhXrMamj9HCXYu0oWyjUiJSlBPXz+pYAAD0OCE9Xi8qKkr9+vVr5ygAgPZQULVd5Z5yuWwuDUo42uo46GEyYzI0LOkYSdKyouWq8FRYnAgAgJ4npKI/ffp0vffee+2dBQDQRqZp6rt9DSPtD0o4Wi67y+JE6ImOSx6utMg0+UyfFu9eooAZsDoSAAA9SkiX7l988cVatGiRJk+erJ///OfKzMyU3X7wgDsjR45sc0AAQOsV1xZrb91e2Q27BiUMsjoOeiibYdMp6WP0n/y52lu/V2v3fqPjU0ZYHQsAgB4jpKI/bty44OeffPLJQdMZdR8ArLF+X64kqX9cjiIdERanwYEinJFa+tDS4OfhLNoZrdFpJ+vz3V/o29Lv1Ceqt9Ki0qyOBQBAjxBS0X/llVfaOwcAoI3K68u1o3qnpIZH6qHrMQxDka6e83z57NgsDageoC0VW7S4cInOzT5Hbrvb6lgAAIS9kIr+jBkz2jsHAKCNGs/mZ0ZnKM4VZ3EaoMGJqaNUXFusSm+llhd9pVN7j5NhGFbHAgAgrIU0GN/+qqqqlJubq9zcXFVVVbVHJgDAEarx1WprZZ4kaWjSUIvToCUen0f3/+1+3f+3++XxeayO0ymcNqfG9T5FhgzlVxUor3Kb1ZEAAAh7IRf9r7/+WhMnTlRiYqKGDRumYcOGKTExUaeffrpWrFjRnhkBAIexsWyjAmZAvSJSlBrZy+o4aIE/4NMHq97XB6velz/gszpOp0mJSNbw5GMlSV8Xr1CNt8biRAAAhLeQLt1fvny5JkyYIJfLpWuuuUZDhjTcC5qbm6u//vWvGj9+vBYuXKiTTjqpXcMCAA7mDXj1fdkmSdLQRM7mo2salnSMdlTt0N76Ui0rXq6JfSZwCT8AAB0kpKJ/3333qW/fvlq8eLHS09ObTHvwwQd1yimn6L777mt2RH4AQPvaXL5FnoBHsc5YZcT0tToOuonc3NxO32aCkaDSqH3aWb1Ln677TIm+hE7P0CglJUVZWVmWbR8AgI4U8hn9Bx544KCSL0lpaWn6+c9/rkceeaTN4QAAhxYwA9pQtlGSNDRxsGxGm4deQZgrKSqRDGn69OmWbP+cq6fqp3deoi2+rbr33Lu1d/deS3JERUUpNzeXsg8ACEshFX2bzSafr+V7C/1+v2w2DjYBoKPtqNqpKm+VXDaX+sf1tzoOuoHKikrJlO54/E6NPHFkp2/flCl/vV+RMZH6v3nPyr7HJkOdewn/1k1bdd/196qkpISiDwAISyEV/bFjx2r27Nm69NJLlZ2d3WRaQUGBnn/+eZ1yyintEhAA0LLcsobLr49OOEoOW0g/0tFDZfXP1JDjhliy7Xp/vb4v3yQzwlTaoDQlRyRbkgMAgHAV0lHhY489pvHjx2vw4MG68MILdfTRR0uSNm7cqH//+99yOBx6/PHH2zUoAKCpvXV7VVy7R4YMDYo/2uo4QKu57W71jkrXrprd2l1TqFhnrFx2l9WxAAAIGyEV/eOPP17Lly/Xfffdp/fff181NQ2PyYmKitLkyZP1m9/8RkOHMvIzAHSk3H0bJEn9YrMV5YyyOA1aI8IZqU/v+yz4eU+W7E5WmadcNb4a7azZqX4x/RiFHwCAdhLydZ5Dhw7Ve++9p0AgoD179kiSevXqxb35ANAJanw1yq8skCQNSRxscRq0lmEYSopJsjpGl2AYhjKi+2pT+WZVeqtU5ilTojvR6lgAAISFNrdym82mtLQ0paWlUfIBoJNsLPteAQWUGtmL+5vRbUXYI5QWmSpJ2lWzW96A1+JEAACEh1ad0X/44YdlGIbuu+8+2Ww2Pfzww4ddxjAM3X///W0OCABoyhfwaVPZZknSkATO5ncnHp9Hv/vwd5KkX079pVwO7kvvFdFLZZ5y1fnrtKtmt7JjGAUfAIC2alXRf/DBB2UYhu666y65XC49+OCDh12Gog8AHSOvYpvqA/WKdkQrIybD6jg4Av6AT+8ue0eSdNuUWyVR9A3DUGZ0hjZVbFa5p1zlnnLFu+KtjgUAQLfWqqIfCAQO+TUAoHOYpqncsoZB+AYnDpLN4JYpdH+RjkilRvRScd0e7azepWhHjBw2u9WxAADotjhCBIBuZHdNoco95XIYDg2MG2B1HKDdpEamym1zy2f6tLtmt9VxAADo1kIq+na7XXPmzGlx+jvvvCO7nb/EA0B7y92XK0kaGD+A544jrNgMmzKi+0qS9nn2qdJTaXEiAAC6r5CKvmmah5zu9/t5Fi4AtLPy+nLt+uFM5+CEQRanAdpftDNaye6Gp0jsqNkpv+m3OBEAAN1TyJfut1TkKyoqNH/+fKWkpIQcCgBwsMZ78zOjMxTrirU4DdAx0qPS5LQ55Q14VVhTZHUcAAC6pVYX/Yceekh2u112u12GYWj69OnBr/f/SExM1BtvvKGf/vSnHZkbAHqUen+9tlbkSZKGJPJIPYQvu2FXRnTD0yT21u9Vtbfa4kQAAHQ/rRp1X5JOOukk3XDDDTJNU88//7zOOussHX300U3mMQxD0dHRGjVqlC666KJ2DwsAPdX3ZZvkN/1KcicpNTLV6jgIkdsRoQ/vnBv8HM2LdcYo0Z2offX7tL16h46OP4onTAAAcARaXfSnTJmiKVOmSJKqq6t13XXX6eSTT+6wYACABn7Tr41l30uShiQOYgyUbsxms6lvYl+rY3QLfSJ7q9JTKU/Ao6LaYvWOSrc6EgAA3Uari/7+XnnllfbOAQBoQX5lgWr9tYq0Ryo7NtvqOECnsNvs6hvdV/lV+dpTt0fxrnhFOSKtjgUAQLcQUtFvtGPHDq1evVrl5eUKBAIHTb/iiivasnoA6PFM01TuvoZB+AYlHC27waNLuzOvz6s/fPwHSdJNZ98kp8NpcaKuLd4Vp3hXvMo95dpRvUNHxQ3kihYAAFohpKJfV1enGTNm6B//+IcCgYAMwwg+cm//X8AUfQBom+LaPSqtL5XdsOuohIFWx0Eb+QJevf7Fa5Kk68+8Tk5R9A+nb1QfVXmrVOevU3HdHqUxRgUAAIcV0sg29957r/75z3/q0Ucf1cKFC2Wapl577TV9/PHHmjJlio477jitXbu2vbMCQI+z4YdH6uXE5SjCzuBt6HkcNof6RPWRJBXXFqvOX2dxIgAAur6Qiv7f//53XXXVVbrrrrt0zDHHSJL69u2rM888U//5z3+UkJCg2bNnt2tQAOhpKr1V2l61Q5I0JIFH6qHnSnDFK9YZK1OmdlTtCF5FCAAAmhdS0S8uLtZJJ50kSYqMbBgYp7r6/z/ndtq0afrnP//ZDvEAoOfasG+jTJnqE9VbCe54q+MAljEMQ32j+8pm2FTjr1VJ/V6rIwEA0KWFVPTT0tK0d2/DL9moqCglJiZq48aNwekVFRWqq+PSOgAIlcfv1ZaKzZKkwYmczQdcNqd6R/aWJBXWFKreX29xIgAAuq6Qiv7JJ5+sxYsXB78+77zz9NRTT+mtt97SG2+8oVmzZmn06NFHvN4//vGPGj58uOLi4hQXF6cxY8boo48+Ck6vq6vTzJkzlZycrJiYGE2bNk1FRUVN1lFQUKCpU6cqKipKqampuuOOO+Tz+ZrMs3DhQo0cOVJut1sDBw7Uq6++esRZAaAjbanYIm/Ap3hXnPpE9bY6DtAlJLkTFe2IbriEv3onl/ADANCCkIr+zTffrP79+6u+vuGv6Y888ogSEhJ0+eWXa8aMGYqPj9ezzz57xOvNyMjQE088oZUrV2rFihU6/fTTdcEFF+i7776TJN1222364IMP9Le//U2LFi3Srl27dNFFFwWX9/v9mjp1qjwej5YsWaLXXntNr776qh544IHgPHl5eZo6daomTpyoNWvW6NZbb9U111yj+fPnh7IrAKDdBcyANpQ1XCU1OGEwjxMDfmAYhjKi+8qQoWpftUrr91kdCQCALimkx+uNGzdO48aNC36dmZmp3NxcrVu3Tna7XYMHD5bDceSrPu+885p8/eijj+qPf/yjli1bpoyMDP3lL3/RnDlzdPrpp0uSXnnlFQ0ZMkTLli3T6NGj9fHHH2v9+vX673//q7S0NI0YMUKPPPKI7rrrLj344INyuVx64YUXlJOTo6efflqSNGTIEC1evFizZs3SpEmTQtkdANCudlTtVJW3Si6bS/3jcqyOg3bkdkTo77f+I/g5jpzb7lZ6VLp21+zW7trdinXFymXjMYUAAOwvpDP65eXlB6/IZtNxxx2nYcOGhVTyD+T3+/X222+rurpaY8aM0cqVK+X1enXmmWcG5xk8eLCysrK0dOlSSdLSpUt17LHHKi0tLTjPpEmTVFFREbwqYOnSpU3W0ThP4zqaU19fr4qKiiYfANBRcstyJUlHJxwlh63tP0/RddhsNg1MG6iBaQNls4X0KxiSUtzJirJHKmAGtJNL+AEAOEhIRxmpqam64IILNGfOHFVVVbVroHXr1ikmJkZut1vXXXed3nvvPQ0dOlSFhYVyuVxKSEhoMn9aWpoKCwslSYWFhU1KfuP0xmmHmqeiokK1tbXNZnr88ccVHx8f/MjMzGyPtwoAB9lbt1fFtXtkyNCghKOtjgN0SQ2X8GfIkKFKb6XKPGVWRwIAoEsJqejffvvt+u677zR9+nSlpqbq4osv1t/+9rcWi/KRGDRokNasWaPly5fr+uuv14wZM7R+/fo2r7ct7rnnHpWXlwc/tm/fbmkeAOFr/b6Gs/n9YrMV5YiyOA3am9fn1R//+0f98b9/lNfntTpOtxbhiFBqZKokaVfNLnkD7E8AABqFVPQff/xxbd68WcuXL9cNN9ygFStW6Cc/+YlSU1N1ySWX6F//+pc8Hk9IgVwulwYOHKhRo0bp8ccf13HHHadnnnlG6enp8ng8KisrazJ/UVGR0tPTJUnp6ekHjcLf+PXh5omLi1NkZGSzmdxud/BJAI0fANDeKr1Vyq8skCQNTRpqcRp0BF/Aqz8teEF/WvCCfBTTNkuN6KVIe6T8ZkDbq3ZwCT8AAD9o0w2CJ554on73u99p27Zt+vLLL3X11Vfriy++0LRp0w66PD5UgUBA9fX1GjVqlJxOpxYsWBCctnHjRhUUFGjMmDGSpDFjxmjdunUqLi4OzvPJJ58oLi5OQ4cODc6z/zoa52lcBwBYJbc0V6ZM9YnqrSR3otVxgC7PMAxlxjRcwl/lq1JpfanVkQAA6BLabZSnMWPGKCUlRYmJifr9738f0oB199xzj6ZMmaKsrCxVVlZqzpw5WrhwoebPn6/4+HhdffXVuv3225WUlKS4uDjddNNNGjNmjEaPHi1JOvvsszV06FBdfvnlevLJJ1VYWKhf/epXmjlzptxutyTpuuuu03PPPac777xTP/vZz/Tpp5/q3Xff1YcfftheuwIAjlidr06bK7ZIko7hbD7QahH2CPWOSteumt3aVbNbMc4Yue1uq2MBAGCpNhf9vLw8vfPOO3r33Xe1du1a2Ww2TZw4UT/5yU+OeF3FxcW64oortHv3bsXHx2v48OGaP3++zjrrLEnSrFmzZLPZNG3aNNXX12vSpEl6/vnng8vb7Xb95z//0fXXX68xY8YoOjpaM2bM0MMPPxycJycnRx9++KFuu+02PfPMM8rIyNBLL73Eo/UAWGpj2ffym34lu5OUFtk+V0QBPUWyO1kVngpV+aq1vXqHBsT2l2EYVscCAMAyIRX97du3691339U777yjlStXyjAMnXrqqZo9e7amTZumXr16hRTmL3/5yyGnR0REaPbs2Zo9e3aL82RnZ2vu3LmHXM+ECRO0evXqkDICQHvzBnzaULZRUsPZfAoKcGQaR+H/vmKTanw12lO3JzhQHwAAPVFIRT87O1uGYWj06NGaNWuWfvSjH6l3797tnQ0AeoTN5ZvlCXgU64xRZgyP7wRC4bK71Deqj7ZX71BhbZFinDE8uQIA0GOFVPSfeuop/fjHP+Z58gDQRgEzoNwfHqk3NHGIbEabxkgFerQEV4IqvJUq95SroGq7joofKLthtzoWAACd7oiLfk1NjebMmaPo6Ghdd911HZEJAHqM/Mp8VftqFGGPUP+4/lbHQQdzOdx684a3gp+jfRmGoYyovqrx1cgT8Ghn9S5lcZUMAKAHOuKiHxUVpby8PO4hBYA2Mk1T35aulyQNSjhaDlu7PQgFXZTdZtewzGFWxwhrdptdWdGZ2lK5VWWeMsXWxyiRx1UCAHqYkK4RnTx5subPn9/eWQCgR9lRvUNlnjI5bU4NThhkdRwgbEQ7o5X2w2B8O6t3qd5fb3EiAAA6V0hF//7779f333+vyy+/XIsXL9bOnTtVWlp60AcAoHmmaeqbvd9Kajib77K7LE6EzuD1efXq56/q1c9fldfntTpOWEuNSFWUI0oBBVRQtV0BM2B1JAAAOk1I14kec8wxkqT169drzpw5Lc7n9/tDSwUAYW5XzW6V1pfKbtg1JGGw1XHQSXwBr/7vo1mSpJ+M/rGcclqcKHwZhqGs6ExtqtikWn+tCmsK1Se6j9WxAADoFCEV/QceeIB79AEgRKZpat3edZKkoxOOUoQjwuJEQHhy2V3KiM5UflW+Sur3KsoZrQRXvNWxAADocCEV/QcffLCdYwBAz1FUW6w9dSWyGTYNTRxqdRwgrMW74tQrIkV76kq0o2qHIuP5wxoAIPy1ywOby8vLuUwfAFppXWnDvflHxQ1UlCPS4jRA+EuPTA/er59fVSDTMK2OBABAhwq56K9YsUKTJ09WVFSUkpOTtWjRIklSSUmJLrjgAi1cuLC9MgJA2NhTu0eFNYUyZOiYJM7mA53BMAxlx2TJbthV56+TP4GB+QAA4S2kS/eXLFmi008/XX379tX06dP10ksvBaelpKSovLxcf/rTnzRhwoT2ygkAbVZQUKCSkhJLM+RHFEgOKd4bp43rNnbqtnNzczt1e0BX4rQ5lRWTpbzKPJkxpsZffJrVkQAA6DAhFf17771XQ4YM0bJly1RZWdmk6EvSxIkT9dprr7VLQABoDwUFBRoyZIhqamosy9D/2P568O8Py+/z65pzrlFxQZElOaqqKi3ZLmC1WGeM0iLTVFRbpCt/fZVqfNb9PAAAoCOFVPS//vprPf7443K73aqqqjpoet++fVVYWNjmcADQXkpKSlRTU6NH//iY+h/V35IMvhS/TJly1Dn0zMvPdPr2v1jwhZ5/fLbq6us6fdto4HK49eK1LwU/R+dLjeil4r3FckQ5tN2xQzXeGkU5o6yOBQBAuwqp6DudTgUCLd/ftnPnTsXExIQcCgA6Sv+j+mvIcUM6fbvV3mptqdwqSTq679FyZ7k6PUPeprxO3yaastvsOrH/iVbH6NEMw5C91Kat2/OUNShLC3d9rkmZZ8lus1sdDQCAdhPSYHyjR4/W3//+92anVVdX65VXXtFpp3HvGwA0KqotliQluRPltnd+yQfw/xmmoWdumCW7adfe+r1aVvyVTJOR+AEA4SOkov/QQw9pxYoVmjp1qj766CNJ0tq1a/XSSy9p1KhR2rNnj+6///52DQoA3VWVt1pVvioZMpQakWp1HFjI6/fq7aVv6+2lb8vr91odp0fbs2OPMur6ypChrRVbtaGscwfHBACgI4VU9E8++WTNnTtXmzdv1hVXXCFJ+sUvfqGf//zn8vv9mjt3roYPH96uQQGgOzJNU0W1DYPuJboT5eJsfo/m83v1xPuP64n3H5ePom+5GH+0RvUaKUlauWeVdlfvtjgRAADtI6R79CXp9NNP18aNG7VmzRpt2rRJgUBAAwYM0KhRo2QYRntmBIBuq9pXrWpf9Q9n83tZHQfAAQYnDFJp/T5trdiqz3cv1jlZkxXrirU6FgAAbRJy0W80YsQIjRgxoh2iAEB4MU1ThT+czU9yJ3E2H+iCDMPQ6NSTVF5frr31e7Vw1yJNzpokp81pdTQAAEIW0qX7a9as0V//+tcmr82fP1/jx4/XySefrGee6fzHRgFAV1PlrVKNr6bhbH4kZ/OBrspus2tCn/GKtEeozFOuJYVLGZwPANCthVT077zzTr3zzjvBr/Py8nThhRcqL6/h0U233367/vznP7dPQgDohkzT1O7aQklSckQyZweBLi7KGaXxfcbLJpsKqrZrXem3VkcCACBkIRX9tWvXaty4ccGvX3/9ddntdq1evVrLly/XxRdfrBdeeKHdQgJAd1PuKVedv0422bg3H+gmUiN76aS0EyVJa/d+o4LKAosTAQAQmpCKfnl5uZKTk4Nfz507V2eddZZSUlIkSWeddZY2b97cPgkBoJvZ/978XpEpctjaPBwKgE5yVPxADU4YJElaXLhEpXWlFicCAODIhXT02bt3b+Xm5kqSdu/erZUrV+qqq64KTq+qqpLNFtLfEACg2yut3ydPwCO7YVdKRIrVcdCFOO0uPTvjD8HP0TWN6jVS5Z5y7a4p1MJdizQla4oiHRFWxwIAoNVCKvoXXHCB/vCHP6iurk7Lly+X2+3WhRdeGJy+du1a9e/fv91CAkB3ETADKvrhbH5aZKrsht3iROhKHHaHxg8eb3UMHIbNsOnU3uP0UcF8VXortWjX5zor4wzZbXw/AwC6h5BOu//mN7/RRRddpDfeeEPFxcV69dVXlZaWJkmqqKjQ3//+d5199tntGhQAuoO9dXvlM31y2pxKcidZHQdAiNx2tyb2nSCnzak9dXu0vPgrRuIHAHQbIZ3Rj4mJ0VtvvdXitB07digqKqpNwQCgu/EH/Cqu2yOp4Wy+zeAWJjTl9Xs1d81cSdI5I86R087TGLqyeFecxvcep093LtSWiq1KcCdoaOIQq2MBAHBYbR4hyjRN7dnTcGDbq1cv2Ww2xcfHtzkYAHQ3e+pK5Df9ctvcSnQlWh0HXZDP79Wv//6AJOnsY8+i6HcDfaL7aFSvkVqxZ6VW7VmteFec+kb3tToWAACHFPLppvXr1+viiy9WXFycevfurd69eysuLk4XX3yxvv2WZ88C6Fm8Aa9K6kokSelRaTIMw+JEANrL4IRBGhg3QKZMfbH7S5V7yq2OBADAIYV0Rv+LL77QlClTFAgEdMEFF+joo4+WJG3cuFHvv/++PvroI82bN0+nnnpqu4YFgK6quHaPAgoo0h6pOGec1XEAtCPDMHRS2omq8FaouHaPPtu5SFOyJsltd1sdDQCAZoVU9G+77TalpqZq0aJFyszMbDJt+/btGj9+vG6//XZ9/fXX7RISALoyj9+j0vqGZ22nR6VzNh8IQ3bDrvG9x+ujgnmq9Fbq892LdUbfiYzFAQDokkL67fTdd9/phhtuOKjkS1JmZqauv/56fffdd20OBwDdQVFtsUyZinFEK9YZY3UcAB0k0hGhiX1Pk8NwqLCmUKv2rLY6EgAAzQqp6GdnZ6u+vr7F6R6Pp9k/AgBAuKnz12mfZ5+khrP5AMJbojtRp6SPlSTllm3Q1oo8ixMBAHCwkIr+Aw88oGeffVZr1qw5aNrq1av1hz/8QQ8++GAbowFA11dYUyRJinPGKcrBY0WBniArNlPDko6RJC0rWq7SulKLEwEA0FSr7tG/+eabD3otLS1No0aN0tixYzVw4EBJ0qZNm7R06VINGzZMy5Yt0yWXXNK+aQGgC6nx1ajCWyGpYaR94HCcdpeevPSp4Ofovo5LHq599fu0s3qXFu76XOdkT1aEPcLqWAAASGpl0X/uuedanPbll1/qyy+/bPLaunXr9O233+qZZ55pWzoA6MIKawolSYmuRA7w0SoOu0NnH3u21THQDmyGTePST9HcHwbn+2LXYp2RcTqD8wEAuoRW/TYKBAJH/OH3+zs6OwBYptJbpSpftQwZSotMtToOAAu47C6d1md8w+B8tUVaXbLG6kgAAEgK8R59AOjJTNMMns1PcifJxSXYaCWf36eP132sj9d9LJ/fZ3UctINEd4LGpo+RJK3fl6vtVTssTgQAQCsv3W9JXl6ePvroI+Xn50tqGI1/ypQpysnJaZdwANAVVXgrVOuvlU02zubjiHj9Ht055w5J0tKHlsphb9OvYXQR2bFZGlw7SBvKNmpJ4VKdkz2FR20CACwV8hHGL37xCz3zzDMKBAJNXrfZbLr11lv1u9/9rs3hAKCraTib3zDSfkpEshw2ihoAaWSv41VSt1cldSX6fNcXmpx5tuw2u9WxAAA9VEiX7j/99NOaNWuWLrroIi1dulRlZWUqKyvT0qVLdfHFF2vWrFmaNWtWe2cFAMvt85SpPlAvu2FXr4heVscB0EXYDbvG9x4nl82l0vpSrdiz0upIAIAeLKSi/+KLL+r888/Xu+++q5NPPllxcXGKi4vTySefrLffflvnnXee/vSnP7V3VgCwVMAMqKi24Wx+r4henK0D0ES0M1rjeo+VJH1fvkl5FdusDQQA6LFCKvrbtm3TpEmTWpw+adIkbdu2LdRMANAlldaXyhvwymE4lBKRbHUcAF1Q3+i+GpZ0jCRpWdFylXvKLU4EAOiJQir6qampWrt2bYvT165dq169uKQVQPjwm34V1+6RJKVFpvKsbAAtOi55uNIi0+QzfVq06wt5AzxhAQDQuUI6Uv3Rj36kl156SU888YSqq6uDr1dXV+u3v/2tXnrpJf3kJz9pt5AAYLWSur3ymT65bC4luZOsjgOgC7MZNp3a+xRF2iNU7inXV8VfyTRNq2MBAHqQkIaLfuSRR7RmzRrde++9euCBB9SnTx9J0q5du+Tz+TRx4kQ9/PDD7RoUAKziC/i0p67xbH6aDMOwOBG6K4fdqYcufjj4OcJXpCNS43qP0393LNDWijylRqbqqPiBVscCAPQQIRX9qKgoLViwQP/+97/10UcfKT8/X5I0efJknXPOOTrvvPM4EAYQNvbU7VHADCjCHqEEV7zVcdCNOe1OXTDqAqtjoJOkR6XpuJThWlOyVl8Vf61kd5KSIrgiCADQ8dr0AOgLLrhAF1zAAQuA8OUNeFVSt1eSlM7ZfABHaFjiMdpTu0c7q3fp892LdU7WFLm4mgMA0MEYTQoADqGotlimTEU5ohTrjLU6Dro5n9+nzzd8rs83fC6fnwHaegLDMHRK+lhFO6JU6a3U8uLl3K8PAOhwFH0AaEG9v16l9aWSpN6R6ZzNR5t5/R7d/NpNuvm1m+T1e6yOg07itrt1au9xMmRoW2W+NldssToSACDMUfQBoAVFtUWSpFhnjKKd0RanAdCd9YrspREpx0mSvi5eoX31ZdYGAgCENYo+ADSj1lenMk+5JCk9Mt3iNADCwTGJQ9Unqrf8pl9f7P5C3gC3bwAAOkarBuN79tlnNXnyZB199NEdnQcAuoTGs/nxrnhFOiItTgOgI+Tm5nb6NmONGDkiHSr3VGhe7jz1re/T6RkapaSkKCsry7LtAwA6TquK/m233aaUlJRg0bfb7XrjjTd06aWXdmg4ALBCja9WFd4KSVJaZKrFaQC0t5KiEsmQpk+fbsn2B580RHe/eo/KnOV64t4ntOT9Ly3JERUVpdzcXMo+AIShVhX9xMREFRUVBb9mtFgA4azxbH6CK0ER9giL0wBob5UVlZIp3fH4nRp54khLMvirAgrEB3Tdb6/XjbffKMPXuYN9bt20Vfddf69KSkoo+gAQhlpV9CdMmKAHH3xQa9asUXx8vCTp9ddf17Jly1pcxjAMPfPMM+2TEgA6SY2vRpXeSkmczQfCXVb/TA05bogl2zZNU1sr81Ttq5Yjw6mBcQNkMxg6CQDQPlpV9J9//nndeuut+vjjj1VcXCzDMPTxxx/r448/bnEZij6A7qjwh7P5ia5Eue1ui9Mg3DjsTt19/j3Bz9FzGYahrJhMfV++SXX+Ou2u2a2+0X2tjgUACBOtKvqpqamaM2dO8GubzaY333yTe/QBhJVqb7WqvFWSpFTO5qMDOO1O/XTMT62OgS7CaXMqKzpTeVXbtLe+VDHOGMW74q2OBQAIAyFdI/bKK69o7Nix7Z0FACzVeG9+kjtRbrvL4jQAeoJYV6x6RfSSJG2v3iGP32NxIgBAOGjVGf0DzZgxI/j5+vXrlZ+fL0nKzs7W0KFD2ycZAHSiKm+VqnzVMmQoNYKz+egY/oBfq7atkiSN7DdSdpvd4kToCtIj01Ttq1aNr0b5VQUaENef+/UBAG0S8m+Rf//73xowYICOPfZYnXvuuTr33HN17LHHauDAgXr//ffbMyMAdCjTNFVUWyyp4Wy+i7P56CAeX72uffEaXfviNfL46q2Ogy7CMAxlRWfKbthV66/V7prdVkcCAHRzIRX9uXPnatq0aZKkxx57TO+9957ee+89PfbYYzJNUxdddJHmzZt3xOt9/PHHdeKJJyo2Nlapqan6n//5H23cuLHJPHV1dZo5c6aSk5MVExOjadOmNXn0nyQVFBRo6tSpioqKUmpqqu644w75fL4m8yxcuFAjR46U2+3WwIED9eqrrx5xXgDhocpXrerGs/ncmw/AAi67S1nRmZKkvfWl2le/z+JEAIDuLKSi/8gjj2j48OH65ptvdNddd+n888/X+eefr7vuukvffPONjj32WD300ENHvN5FixZp5syZWrZsmT755BN5vV6dffbZqq6uDs5z22236YMPPtDf/vY3LVq0SLt27dJFF10UnO73+zV16lR5PB4tWbJEr732ml599VU98MADwXny8vI0depUTZw4UWvWrNGtt96qa665RvPnzw9ldwDoxhrO5jf8sTDZnSSnjZHQAVgj1hUbvHVoR/VO1fnrLE4EAOiuQrpH/5tvvtFjjz2m6Ojog6ZFR0fryiuv1L333nvE6z3wKoBXX31VqampWrlypcaPH6/y8nL95S9/0Zw5c3T66adLahgYcMiQIVq2bJlGjx6tjz/+WOvXr9d///tfpaWlacSIEXrkkUd011136cEHH5TL5dILL7ygnJwcPf3005KkIUOGaPHixZo1a5YmTZoUwh4B0F1VeqtU46uRIUO9IntZHQdAD5cWmaoaX7WqfNXKryzQwPgBshuM5QAAODIhndGPiIhQaWlpi9NLS0sVERERcqhG5eXlkqSkpCRJ0sqVK+X1enXmmWcG5xk8eLCysrK0dOlSSdLSpUt17LHHKi0tLTjPpEmTVFFRoe+++y44z/7raJyncR0Hqq+vV0VFRZMPAN1fk7P5EcmczQdgOcMwlBWTJYfhUH2gXjuqd8o0TatjAQC6mZCK/umnn65nnnmm2WK8fPlyPfvsswcV6SMVCAR066236pRTTtGwYcMkSYWFhXK5XEpISGgyb1pamgoLC4Pz7F/yG6c3TjvUPBUVFaqtrT0oy+OPP674+PjgR2ZmZpveG4CuocJbqVp/rWyyKTWCs/kAugaHzaHsmCxJUrmnXHvqSixOBADobkK6dP/JJ5/UmDFjNG7cOJ100kkaNGiQJGnjxo366quvlJqaqt/+9rdtCjZz5kx9++23Wrx4cZvW0x7uuece3X777cGvKyoqKPtAN3fg2XyHLaQfhwDQIaKd0eob1Uc7a3apsLZQEfYIxblirY4FAOgmQjqyzcnJ0TfffKPHH39cH330kd555x1JUnZ2tm655RbdfffdSk0NfeTqG2+8Uf/5z3/0+eefKyMjI/h6enq6PB6PysrKmpzVLyoqUnp6enCer776qsn6Gkfl33+eA0fqLyoqUlxcnCIjIw/K43a75Xa7Q34/ALqeCm+F6vx1ssmmXhEpVsdBD+GwOXXrlNuCnwOHkuROUq2/VqX1+1RQXaCj7APltnM8AgA4vJAu3Zek1NRUzZo1Sxs2bFBtba1qa2u1YcMG/f73vw+55JumqRtvvFHvvfeePv30U+Xk5DSZPmrUKDmdTi1YsCD42saNG1VQUKAxY8ZIksaMGaN169apuLg4OM8nn3yiuLg4DR06NDjP/utonKdxHQDCm2maKvzhbH5KRApn89FpnA6nrhx/pa4cf6WcDoo+Ds0wDPWJ6qMoR5QCZkDbKvPlN/1WxwIAdAMhF/2OMHPmTL355puaM2eOYmNjVVhYqMLCwuB98/Hx8br66qt1++2367PPPtPKlSt11VVXacyYMRo9erQk6eyzz9bQoUN1+eWXa+3atZo/f75+9atfaebMmcGz8tddd522bt2qO++8Uxs2bNDzzz+vd999V7fddptl7x1A5yn3lKveXy+bwdl8AF2bzbApOyZLzh8G59tetZ3B+QAAh9Wliv4f//hHlZeXa8KECerdu3fwo/HWAEmaNWuWzj33XE2bNk3jx49Xenq6/vnPfwan2+12/ec//5HdbteYMWM0ffp0XXHFFXr44YeD8+Tk5OjDDz/UJ598ouOOO05PP/20XnrpJR6tB/QApkwV1TZc8dMrIkV2G4+tQufxB/z6dvu3+nb7t/IHODOL1nHanMqOzZYhQxXeSu2u2W11JABAF9elrldtzV+oIyIiNHv2bM2ePbvFebKzszV37txDrmfChAlavXr1EWcE0L2ZUabqA/WyG3alcDYfnczjq9f05y+TJC19aKkiXVEWJ0J3EeWIUmZ0hgqqt6ukfq9cdhc/wwAALepSZ/QBoCPZ7Db54wKSfjibb3A2H0D3keBOUHpkw+OBd9XsVoWnwuJEAICuiqIPoMcY9z/jJKdkN+xKjki2Og4AHLFeEb2U5E6UJOVXFajGV2txIgBAV3TERb+mpkajRo3SCy+80BF5AKBDBGTqghv+R5KUGtGLs/kAuiXDMNQ3qq9iHDEyZWpb5TZ5/B6rYwEAupgjLvpRUVHKy8uTYRgdkQcAOkSZo0y9MlIlvzibD6BbMwxD2bFZirBHyGf6tLUyT96A1+pYAIAuJKRL9ydPnqz58+e3dxYA6BD+gF97XCWSJFuFTTaDu5YAdG92w66c2H5y2VzyBDzKq8yTL+CzOhYAoIsI6Wj3/vvv1/fff6/LL79cixcv1s6dO1VaWnrQBwB0BZvKN8tn86m0sFS2Kq5GAhAenDancmJz5DAcqvPXa1vlNvlNHtsIAAjx8XrHHHOMJGn9+vWaM2dOi/P5/fyyAWAtX8Cnb0u/kyS9/8K/de3V11qcCD2Zw+bU/55xXfBzoK3cdpf6x+ZoS+VW1fhrlV+Zr36x/bhyCQB6uJCK/gMPPMA9+gC6hU3lm1Xrr5Uz4NCivy+k6MNSTodT1595vdUxEGYiHBHKie2nrRV5qvJVK7+qQNkxWZR9AOjBQir6Dz74YDvHAID2593vbH4vT4r8Xq4yAhCeohxR6hebrbzKbar0VlL2AaCHa5ef/uXl5VymD6DL+b7se9X56xTjjFGCL8HqOIACgYA2F23W5qLNCgQCVsdBmIlxxqhfbD8ZMn4o+/kKmPw7A4CeKOSiv2LFCk2ePFlRUVFKTk7WokWLJEklJSW64IILtHDhwvbKCABHzBvw6rvS9ZKk4UnHyhC3G8F69b46Xfx/03Tx/01Tva/O6jgIQ7HOGOUEy36VtlVS9gGgJwqp6C9ZskTjxo3Tpk2bNH369CZnJVJSUlReXq4//elP7RYSAI7Uhn0bVR+oV5wzVjlx/ayOAwCdJma/sl/lo+wDQE8UUtG/9957NWTIEK1fv16PPfbYQdMnTpyo5cuXtzkcAITC4/do/b5cSdLw5GO5RxVAjxPjjFH/2BzZZPuh7G+j7ANADxLS0e/XX3+tq666Sm63u9nR9/v27avCwsI2hwOAUKzflytPwKN4V5yyY7OtjgMAloh2Risntt8PZb9aeZR9AOgxQir6TqfzkIMI7dy5UzExMSGHAoBQ1fnqlLtvgyRpRPJxnM0H0KPtX/arKfsA0GOEdAQ8evRo/f3vf292WnV1tV555RWddtppbQoGAKH4dt938pk+JbmTlBmTaXUcALBctDNaOXE5shn/v+ybhml1LABABwqp6D/00ENasWKFpk6dqo8++kiStHbtWr300ksaNWqU9uzZo/vvv79dgwLA4VR7a7Sx7HtJ0oiU45q9tQgAeqJoR1TDPfs/lH1/L78ioiOsjgUA6CCOUBY6+eSTNXfuXF1//fW64oorJEm/+MUvJEkDBgzQ3LlzNXz48PZLCQCtsK50nQJmQKmRvdQnqrfVcYCDOGxOXXHqjODnQGeK+qHsb63MU8Ad0C9fvEN++a2OBQDoACEVfUk6/fTTtXHjRq1evVqbN29WIBDQgAEDNGrUKM6iAeh0lZ5KbS7fIkkakTyCn0PokpwOp24/53arY6AHayz7m8u26OhRg5Tv367j/CPksvOHJwAIJyEX/UbHH3+8jj/++PbIAgAhW7v3G5ky1Seqt9KiUq2OAwBdVpQjSo5iu8oiyqUEacHOT3VG34ly2V1WRwMAtJOQh6Our6/Xc889p3POOUdDhw7V0KFDdc455+i5555TXV1de2YEgEMqqy9TXuU2SQ335gNdVSAQ0M59O7Vz385DPr0G6GiG19Bvr3xcdtOukroS/Xfnp/L4PVbHAgC0k5CK/o4dOzRixAjdfPPNWrt2rXr16qVevXpp7dq1uvnmmzVixAjt2LGjvbMCQLPW7P1GkpQVk6nkiGSL0wAtq/fVaeqT52jqk+eo3scfxWGt/Nx8ZddmyWVzaW/dXv13B2UfAMJFSEV/5syZys/P17vvvqudO3dq0aJFWrRokXbu3Kl33nlHBQUFmjlzZntnBYCD7K3bq+1V2yVJxyVzNh8AjkRkIEJnZZ4pt82tvfV79d8dC1Tvr7c6FgCgjUIq+gsWLNBtt92miy+++KBpP/rRj3TLLbdowYIFbQ4HAIezpmStJKl/bI4S3PEWpwGA7ifJnaizMs+Q2+7W3vpS/XfHp5R9AOjmQir6sbGxSk1tebCr9PR0xcbGhhwKAFqjqKZIu2p2y5Ch4cnHWh0HALqtRHeizso4U267W6X1pVqw8zN5A16rYwEAQhRS0b/qqqv06quvqqam5qBpVVVVeuWVV3T11Ve3ORwAtMQ0Ta3Z23A2/6j4gYp18cdFAGiLRHeCzs744TL+ur1auHOR/AG/1bEAACFo1eP1/vnPfzb5+vjjj9eHH36owYMHa8aMGRo4cKAkadOmTXr99deVlJSk4cOHt39aAPjBrppdKq7dI7th17FJw6yOAwBhIcGdoDMyJuqTHf9VYW2RPt+9WKf1OVU2I+QHNQEALNCqon/xxRfLMAyZpilJTT5/9NFHD5p/x44duuSSS/TjH/+4HaMCQAPTNIP35g9KOFpRziiLEwFA+EiOSNbEPhO0YOdn2lG9Q0sKl+qU9LEyDMPqaACAVmpV0f/ss886OgcAtFpB1XaV1u+Tw3DomKShVscBWs1uc+jHo38S/BzoqtKi0jS+9zgt3PW58iq3yWlz6qTUEyn7ANBNtOoo47TTTuvoHADQKgEzoDUlayRJQxIHK8IeYW0g4Ai4HC7de8G9VscAWiUjJkOnpI/V4sIv9X35JrnsLh2fMsLqWACAVuCGKwDdyubyzarwVsptd2toImfzAaAj5cT108mpJ0qSvi39Tt+VfmdxIgBAa4R83eDixYv18ssva+vWrdq3b1/wnv1GhmFo7dq1bQ4IAI28Aa/W7l0nSRqedKxcdqfFiYAjY5qm9lXvkyQlRidyGTS6haMTjpYn4NXqkjVaVbJGTptLRyccZXUsAMAhhFT0f//73+uOO+5QRESEBg0apKSkpPbOBQAHWb8vV3X+OsU6Y3RUwkCr4wBHrM5bq9MfnShJWvrQUkW6GEgS3cOwpGPk8Xv03b71Wl78lZw2p3Li+lkdCwDQgpCK/lNPPaVTTjlFH3zwgeLj49s7EwAcpNZXq/WluZKkESkjZDfsFicCgJ7l+JQR8ga8+r58k74sXCKX3aW+0X2sjgUAaEZI9+jX1NTosssuo+QD6DTf7F0nn+lTsjtZ2TFZVscBgB7HMAydlHqi+sVmy5SpRbs+157aEqtjAQCaEVLRnzhxotatW9feWQCgWeWeCm0q3yxJGtXreO5rBgCLGIahselj1Ceqt/ymX5/u/Exl9eVWxwIAHCCkov+HP/xBCxYs0O9+9zuVlpa2dyYAaGJNyRqZMtU3uq/SotKsjgMAPZrdsGt8n/FKiUiWJ+DRgp2fqtpbbXUsAMB+Qir6mZmZ+t///V/dfffd6tWrl6KjoxUXF9fkg8v6AbSHopoiFVRtlyFDI3l+MwB0CU6bQ6f3nah4V5xqfDX6745PVeevszoWAOAHIQ3G98ADD+jRRx9V3759dcIJJ1DqAXSIgBnQij0rJUlHxQ9UgjvB2kAAgCC33a0z+p6ueds/VoW3Qp/uWKizMs+Q08ajTwHAaiEV/RdeeEFTp07Vv/71L9lsIV0UAACHtbUiT6X1++S0OXVc8nCr4wBtZrc5dN7I84OfA91dtDNaZ2acrvkFn2hv/V4t2vW5JvaZILuNJ6MAgJVCOsrweDyaOnUqJR9Ah/EGvFpTskaSNDzpWEU4IqwNBLQDl8OlR370iNUxgHYV74rX6X0n6JMdC7S7plBfFi3VuPSxshkcJwKAVUL6CXzuuefqiy++aO8sABD0bel3qvXXKdYZo0EJR1sdBwBwCCmRKTqtz3jZZFN+Zb5WFK+UaZpWxwKAHiukov/rX/9a69ev1w033KCVK1dqz549Ki0tPegDAEJR5a3S+n25kqSRvUZyCSjChmmaqvXUqNZTQwlC2OkT3Vun9B4jSdpY/r3W7v3G4kQA0HOFdOn+oEGDJElr1qzRn/70pxbn8/v9oaUC0KOtKlmjgBlQWmSaMqMzrI4DtJs6b63G/LqhCC19aKkiXVEWJwLaV7/Yfqr3e/RV8ddaV/qtHDaHhiUdY3UsAOhxQh513zCM9s4CACqqKVJ+Zb4k6YTUUfysAYBuZlDC0fIFvFpVskarS9bIbtg1JHGw1bEAoEcJqeg/+OCD7RwDABoep/dV8deSGh6nl+ROtDgRACAUxyQdI1/Ar29K12nFnpVyGA4dlTDQ6lgA0GMwHCqALmND2UaVecrltrl1fMoIq+MAANpgePKxGpo4RJK0rHi5tlZstTgRAPQcIZ3Rf/jhhw87j2EYuv/++0NZPYAeqMZXo29+GLjp+F4j5La7LU4EAGgLwzA0MuV4+QI+fV++SV8WLpVpmhoQP8DqaAAQ9tr90n3DMGSaJkUfwBFZuWe1vAGfkiOSNTCOg0AACAeGYeik1BMlSd+Xb9KSomUKmCaX8QNABwup6AcCgWZfy8/P1+zZs/X555/ro48+anM4AD1DYU2RtlVukySdnHoiA/ABQCfJzc3tlO04ZFeSK1Glrn1aVrxc+QXblORL6pRtH0pKSoqysrKsjgEA7S6kot8cm82mnJwc/e53v9Nll12mm266SXPmzGmv1QMIU/sPwHd0/FFKjki2OBHQcWyGXWcOOyv4OWCVkqISyZCmT5/eqdu95K5LNeVn52h3RJGeevR3+vj1+Z26/QNFRUUpNzeXsg8g7LRb0d/f+PHjddddd3XEqgGEmfX7clXuKZfb7taIlOOsjgN0KLfTrd9d9jurYwCqrKiUTOmOx+/UyBNHdtp2TZkKVAQUiDM1/b7LdcWNV8hWYZOhzr+Sa+umrbrv+ntVUlJC0QcQdjqk6K9YsUI2GwP6Azi0Ck+Fvtm7TpI0KuV4BuADgE6W1T9TQ44b0qnbNE1TxXV7VFRbpEC8qYTUOPWN6sttWwDQjkIq+q+//nqzr5eVlenzzz/XP//5T11zzTVtCgYgvJmmqWVFy+U3/eodla7+cf2tjgQA6ASGYSgtMlUOw6GdNTtVWr9PvoBfWTGZshmcKAKA9hBS0b/yyitbnJaSkqK7775bDzzwQKiZAPQAm8u3qKi2WHbDrpPTTuZMDnqEWk+Nxvx6jCRp6UNLFemKsjgRYJ3kiCQ5bHYVVG1XhbdCeZXblB2TJYetQy44BYAeJaSfpHl5eQe9ZhiGEhMTFRsb2+ZQAMJbja9GK0tWSZJGpBynWGeMxYkAAFaId8UrJ9aubVX5qvZVa3PFFuXE9uNWLgBoo5CKfnZ2dnvnANBDmKapr4q+ljfgVbI7WYMTBlkdCQBgoRhnjAbE9te2qnx5Ah5trtii7JhsxTijrY4GAN0WN0IB6FQFVdu1vXqHDBkak34y92MCABTpiNTAuAGKtEfKb/qVV5mn0vp9VscCgG6r1Wf0hw8ffkQrNgxDa9euPeJAAMJXra9Wy4u/kiQdkzRUie5EixMBALoKp82pAXH9tb16h8o95dpRvUP1/jqlR6YzjgsAHKFWF/2kpKRW/ZAtLCzUxo0b+YEMoAnTNLW0aJnq/fVKdCVoeNKxVkcCAHQxNsOmrOhMFdlcKq7boz11Jar11SqLQfoA4Ii0+ifmwoULDzm9sLBQv/3tb/WnP/1Jdrtdl19+eVuzAWhHBQUFKikpsWz7pY592h1RKMM0lFSWqLWlnXvFT25ubqduDwAQGsMwlB6VrghHpHZU7VCVr1qbKjarX0y2Ih2RVscDgG6hzX8aLSoq0hNPPKE///nP8nq9mj59uu677z4NGDCgPfLh/7V352FSlXf+99+n9u6u3vcGmkUWCQqICINojMpPII5IdNwmKorRJ3nAxJBxjYmay0QdJxG3uI1i8ouOTp6oMSgqogIaQASZQSXKJg30vlbXvp3nj6YLWlCRpU539efFVVTVqVN1PnVf3dX1Pfd97iNyBNTU1DB69GiCwaAl2y+rLufOl36NBw/P3P0nXnt6iSU5APz+Tsu2LWIz7Jwy6tTUbRH5cgWufDx57h6T9A3MGaDDvkREDsIhF/rdPfj7Fvi33norw4YNO+QwK1as4N5772XdunXU1dXx4osvMnv27NTjpmly22238cQTT9De3s7UqVN55JFHGDFiRGqd1tZWrr32Wv72t79hs9k4//zzuf/++/F6956+63//93+ZN28ea9eupbS0lGuvvZYbbrjhkHOL9HbNzc0Eg0F+/chvGDbi0H9HD4WJSaIsgekGI2xw+aWXM+fSOWnNALBy2Up+f9fDhCPhtG9bpJvb6eahKx6yOoZIn+FxeBiRN5yawE46Y53sDOwiGA9RlV2pw0RFRL7CNy706+vrufvuu3niiSeIxWJcdtll3HrrrQwdOvSwwwQCAcaNG8fcuXM577zz9nv83//933nggQf4wx/+wNChQ/nFL37B9OnT+eSTT/B4PAB8//vfp66ujqVLlxKLxbjyyiu55pprePbZZwHw+XycddZZTJs2jUcffZSNGzcyd+5cCgoKuOaaaw77PYj0ZsNGDGP0uNFp3WZDqJGGUAM2w8bI8hG4qlxp3X637Zu3W7JdERE5PHabnSHewTSEGmkMN9ISaSGcCFPtHYTT5rQ6nohIr3TQhX5dXV2qwI/H41x++eX8/Oc/PyIFfreZM2cyc+bMAz5mmiYLFy7k1ltv5dxzzwXgj3/8I+Xl5bz00ktcfPHFbNq0iddee421a9cyceJEAB588EG++93v8h//8R9UVVXxzDPPEI1Geeqpp3C5XIwZM4YNGzbwu9/9ToW+yBEWiAVoCDUAMCC7CpfdmiJfRET6tq7j9svJcmSx07+TQDzAlo4tDM4dTLYj2+p4IiK9zkEX+scccwyRSITx48dzyy23MHToUNra2mhr+/JznE6YMOGIhATYvn079fX1TJs2LbUsPz+fyZMns2rVKi6++GJWrVpFQUFBqsgHmDZtGjabjTVr1vC9732PVatW8e1vfxuXa2/BMX36dO655x7a2tooLNz/uK9IJEIkEknd9/l8R+x9iWSqeDLODn8NAAWuAgpcBdYGEukFQtEgp995OgBv3/o2WS4VKCLfRL4rD3f+cHZ07iCSjLDVt42q7CqKPUVWRxMR6VUOutAPh7uOa/3www+58MILv3Jd0zQxDINEInF46fZRX18PQHl5eY/l5eXlqcfq6+spKyvr8bjD4aCoqKjHOl8chdD9mvX19Qcs9O+66y7uuOOOI/NGRPoB0zSp8e8kbsZx29wMyKnSsZQie4RjmidC5HB47G6G5x/DTv8ufDEfu4O7CSWCVGVXYTNsVscTEekVDrrQX7Ro0dHM0avdfPPNLFiwIHXf5/MxaNAgCxOJ9G6N4Sb8cT8GBoO91dg1u7iIiBxBdsPOYG81TeEm6kMNtEbaCMXDDPZW6zAxERG+QaE/Z076Z8neV0VFBdB1Or/KysrU8oaGBsaPH59ap7Gxscfz4vE4ra2tqedXVFTQ0NDQY53u+93rfJHb7cbtdh+R9yGS6fwx/97j8nMG4HF4LE4kIiKZyDAMyrLKyHJkUePfSSgRYrNvC9XeanKd3q9/ARGRDNZnxjcNHTqUiooKli1bllrm8/lYs2YNU6ZMAWDKlCm0t7ezbt261DpvvfUWyWSSyZMnp9ZZsWIFsVgstc7SpUsZNWrUAYfti8jBiyVj1Ph3AlDoKqRI5zoWEZGjLNeZy4i84WTZPSTMBNs7t9MYasI0TaujiYhYplcV+n6/nw0bNrBhwwagawK+DRs2UFNTg2EYXHfdddx55528/PLLbNy4kcsvv5yqqipmz54NwOjRo5kxYwZXX30177//Pu+99x7z58/n4osvpqqqCoB//dd/xeVycdVVV/Hxxx/z/PPPc//99/cYmi8i31zSTPJ55w7iZhyPveu4fBERkXRw2V0ck3cMha6uHcz1oXpq/DUkzCM3X5SISF9y0EP30+GDDz7g9NNPT93vLr7nzJnD008/zQ033EAgEOCaa66hvb2dU045hddeew2PZ+/Q4GeeeYb58+dz5plnYrPZOP/883nggQdSj+fn5/PGG28wb948TjzxREpKSvjlL3+pU+uJHAbTNNkV2EUoEdpz3OQQTYgkIiJpZTNsDMwZQLYji9pgHR0xH+GOrQzOHYzHrkMwRaR/6VWF/ne+852vHGZlGAa/+tWv+NWvfvWl6xQVFfHss89+5XbGjh3LypUrDzmniPTUFG6iPdoBwGBvNW5NhCRyQIZh48ShE1O3ReTIMgyDYk8xHruHHf4aIskIWzq2MMg7kHxXvtXxRETSplcV+iLS9/iiPuq7J9/LrsKrCZBEvpTH6eHJa560OoZIxstx5jAifzg1/hoC8SA7/DWUeUopzyrX6V5FpF9Qd4KIHLJQPJyafK/YXUSxp9jiRCIiIl2cNifDcodR4u7629QYbmJ75+fEk3GLk4mIHH0q9EXkkEQTUT7v3E6SJDmOHKqyNfmeiIj0LoZhUJVTxaCcQRgY+ON+Nvu2EIqHrI4mInJUqdAXkW8snkyw3f85MTOO2+ZmsLdaQyFFDkIoGuT0O7/D6Xd+h1A0aHUckX6j0F3A8LxjcNlcxJIxtvi2ksxOWh1LROSoUaEvIt9I0kyyw7+DSCKCw3AwNHcIDpum+xA5WG2BNtoCbVbHEOl3shxZDM87hlynFxOTRHGSf735+5h8+UTQIiJ9lQp9ETlopmmy07+TQDyAzbAxNHcILs2wLyIifYTD5mCIdwhlnlIAZlwxk8+zagjFwxYnExE5slToi8hBMU2T2mAtHTEfBgZDvIPJcmRZHUtEROQbMQyDiuwK7M02QoEQQXuQV2uW0BxusTqaiMgRo0JfRL6WaZrUh+ppibQCMChnoE6jJyIifZotZOOOC27DlXQRjAd5fecbbOnYanUsEZEjQoW+iHytxnAjTeFmAAZkV1HgLrA2kIiIyBFQu7WWYcEhDMwZQNJMsqphNWsa3idhJqyOJiJyWFToi8hXago10RBqBKAyu5JiT7HFiURERI4cO3a+U3Ua44rHAvBZx2aW7lxGUKfgE5E+TIW+iHyp5nALdaF6AMqzyin1lFicSKRvMwwb3xowhm8NGINh6E+wSG9hGAZji4/n9KrTcNqcNIWbeHXHEppCTVZHExE5JDonlogcUHO4hdpgLQClnlLKs8osTiTS93mcHp6d/6zVMUTkSwz0DuS71TN4p3YFHdEO3tj5JieVTWRE/nAMw7A6nojIQVN3gojspzncnCrySzwlVGSVW5xIREQkPfJcecysnk61dxBJkqxpfJ/VDWtIJHXcvoj0HSr0RaSHpnAztcE6oKsnvzKrQr0YIiLSrzhtTr5deSonlIzHwGCLbyuv71pKIBa0OpqIyEFRoS8iKU2hJur2FPllnlIqsspV5IscQaFoiJn3zGTmPTMJRTXRl0hvZhgGxxWN4YwBp+OyuWgJt/BqzRIagg1WRxMR+Voq9EUE0zSpDzakJt4r85RRriJf5CgwqWuvpa69FjCtDiMiB6Eqp5LvVs+g0F1IOBFm6a5lbGr7B6ap32ER6b1U6Iv0c6ZpUhesozHcdQq9iqxyKrJV5IuIiHTLdeUyY9BZDMkdgonJB03rWFn3LrFkzOpoIiIHpEJfpB8zTZNdgd00R1oAqMquokyz64uIiOzHYXNwSsXJTCw9EQODHf4aXt3xGu2RdqujiYjsR4W+SD+VNJPU+Gtoi7YBMChnICWeYotTiYiI9F6GYTC68FimD/o/ZDuy8cV8vFrzGtt8262OJiLSgwp9kX4okUywvfNzOmI+DAwGe6spdBdaHUtERKRPKM0q5ezqmVRmV5AwE7xX/3fWNLyvU/CJSK+hQl+kn4klY2zt3EYgHsCGjSG5Q8h35VsdS0REpE/xODycMeB0xhYdD8BnHZt5fecb+GN+i5OJiKjQF+lXTIfJFt9WwokwDsPBMXnDyHV6rY4l0o8YDCsbxrCyYYAmvBTp62yGjXElY/eegi/Syis7lrDLv9vqaCLSzzmsDiAi6XHMuGOIlyUgmcBlczE0dyhuu8vqWCL9SpYrixd++qLVMUTkCBuQU8XZg2eyovZdWiItvF37DscVjWFc8VhshvrVRCT99Mkj0g902H3c/Mefgx2y7FkMzztGRb6IiMgR5HV6mT7o/zAqfyQAH7V+zLJdbxGKhy1OJiL9kQp9kQxmmiYft37CrqzduDwujJDBsLyhOGwazCMiInKk2W12JpWfxCkVJ2M37NSHGnhlx6s0hhqtjiYi/YwKfZEMlTSTrGl8n/XNHwLwxh9fx95sw27YLU4m0n+FoiHOu+97nHff9whFQ1bHEZGjZGjeUL5bPZM8Vx6hRIg3dr7Jx62fYJqm1dFEpJ9QoS+SgSKJCG/tfofNHVsAqIiU86df/18MTf4lYjGTbY3b2Na4DdAXfpFMVuDO57vVMxiSOxgTk/XNH/LW7rc1lF9E0kKFvkiG6Yh2sKTmdeqCddgNO9+pOo3iWJHVsURERPodp83JKRVTmVw2CbthpzZYxys7XqEuUGd1NBHJcCr0RTLI7sBultS8TmeskxxHNjMGncUg70CrY4mIiPRbhmEwsmAEM6tnkO/KJ5QI8+but/iweQNJM2l1PBHJUCr0RTJA96R7b+9eTiwZoyyrlJnVMynyqCdfRESkNyh0F/Dd6hmMyB8OdM3K/8bOpfhjfouTiUgm0tTbIn1cLBljVf1qdvhrABiedwyTyk/SpHsiIiIHYdOmTWndngsnA+0DqPXU0RRu5q/b/saAcCV5iby05uhWUlJCdXW1JdsWkaNHhb5IH9Ye6WB57Qp8MR82bEwsm8DI/JEYhibdExER+SrNDc1gwKWXXmrJ9ksGlPD//nYew08Ywc6s3bz13P/lv+55hkgwktYc2dnZbNq0ScW+SIZRoS/SR233fc7qhjXEzTjZjiy+XXkqpVmlVscSka9kUFlQlbotItbp9HWCCdffdQMTTppgSQYTk6QvSTLX5IyLz+CMfzkDe4sdWzQ9nw/bNm/j5z+6hebmZhX6IhlGhb5IHxNPxlnXtJ7POjYDUJFdwakVU/E4PBYnE5Gvk+XKYsmNS6yOISL7qB42iNHjRluawR/zszOwi5gjRqI8QaGnhIqscmyGptMSkUOjQl+kD2mLtLGy7j06oh0AHFc0hnHFY/VFQEREpA/zOr2MzB9BbbCOtkgbzeFmOqOdDMwZQI4zx+p4ItIHqdAX6QNM0+Szjs/4oGk9STNJlt3D1IqTqcyptDqaiIiIHAF2w86gnIHkO/PYFdhNJBlha+c2Cl2FVGZX4LDpa7uIHDx9Yoj0csF4kNUNa9gdqAVgQE4VJ5dP0VB9kT4oHAsz97G5ADz1/zyFx6nfYxHpKc+Vx0hHDvWhelojrbRF2/DFfFRmV1LoKtCEuyJyUFToi/RSpmmyvfNz1jZ+QDQZxWbYmFByAscWjNIfeZE+yjSTfLL749RtEZEDcdjsDMwZQKGrgN3B3YQTEXYFdtESbqEqu1LD+UXka6nQF+mFQvEQqxveZ1dgFwDF7mJOrphCgTvf4mQiIiKSLjnOHEbkjaAp3ExjqJFQIsTWzm3kOXOpyK7AY9eoIBE5MBX6Ir2IaZps7tjCh80bunrxsTG2+HjGFH1LE+6JiIj0Q4ZhUJZVSqG7gIZQI62RVnyxTnwdnRS6CinNKlHBLyL7UaEv0ku0RdpY0/A+TeFmAIrchZxcMYVCd6HFyURERMRqTpuTgTkDKPEUUx9swBfz0RZtoy3aRp4zj9KsUnIc2VbHFJFeQoW+iMWiiRgbWzeyqe0fmJg4DAfjS8YxqmCkevFFRESkB4/dw5DcwQTjQRpDTfhivtQl25FNkbuIfFcedsNudVQRsZAKfRGLJM0kW33b2ND8P4QTYQAGeQdxUulEcpzaIy8iIiJfLtuRzZDcwYQTYZpCzbRH2wnGgwTjQWoDNgrc+RS6Csl2ZGsSX5F+SIW+iAXqgw180LSOtkgbALnOXE4sncAg70CLk4nI0VaYo8NxROTI8dg9DPIOpCJZTlukjdZIG9FklNY9tx2GgzxXHnnOPLzOHI0WFOknVOiLpFFLuIUNzf9DbbAOAJfNxfHFxzGqYKSG2In0A1mubN6+9R2rY4hIBnLanJRllVHqKSUQD9IWaaUj6iNuxmmNtNIaacWGjRxnDl5HDjlOLyam1bFF5ChRoS+SBm2Rdv6n5X/Z6d8JgIHByPwRjC05XjPlioiIyBFjGAZeZw5eZw4DzCSBWICOmA/fnqK/M9ZJZ6wTQsAAuP4/b6DB1ciOzhqKPUXkOHI01F8kA6jQl36hpqaG5ubmtG83ZAvR7GzB5+gEAzAhP55PWbQEh9/OJ7s/SUuOTZs2pWU7IiIi0nvYDBu5rlxyXbmY2VWEEmECMT/+eIBAPEDSluT4U8fSTAsr6lYC4La5KfIUUewposhdRJGnCK+Kf5E+R4W+ZLyamhpGjx5NMBhM2zbHTBnD2Vf/M8dNPT61bM2SNbz44F+o3Vqbthxf5Pd3WrZtEYFwLMy8RfMAePjKh/E4NaJHRNLDMAyyHVlkO7IopRTTNNm0aRNPPPIEP711ATavQVuknUgyQl2wjro9hxkCOG0OClyFFLoLKHQXUOAupMBVgMvutPAdichXUaEvGa+5uZlgMMivH/kNw0YMO2rbMQ0TM9sk4U2Cq3shGEEDe6eNU46byimPTT1q2/8qK5et5Pd3PUw4ErZk+yLSxTSTrNv+Qeq2iIhVDMPAiBm8/dxb/Mf19zJhzAQSyQTt0XZawq20RFppDbfSHmknlozTFG6iKdzU4zW8Ti8FroI9OwC6dgR4nV5N+CfSC6jQl35j2IhhjB43+oi/biQRpSXSQlukjcSeL+4GBkXuIko9JbiKXV/zCkff9s3brY4gIiIivZzdZqfYU0yxpzi1LGkm6Yj6aI+00RZppy3STnu0jWA8hD/mxx/zsyuwa+9rGPZU8V+wzw4At91txVsS6bdU6Iscgq4/eh20RtoIxAOp5U6bk2J3MUXuQhw2/XqJiIhI32YzbKkh+0P3WR5JRPYU/m20p3YAtJMwE7REWmiJtPR4nTxXHqWeUkqzSij1lJLvytNx/yJHkSoRkYNkmib+eID2SDsd0Q6S7B1263V6KXEXk+vM1R8tERERyXhuu5uK7HIqsstTy5JmEn/Mn9oB0H0diAfwRbtm/t/q2wp0nWK4xFNMaVYppZ4SSrJKcaqTROSI0W+TyFcwTZNAPEBHtIP2aAcJM5F6zGVzdQ1HcxXgsls/PF9ERETkUByts/Pkk0s+ucSJE7KHCNpDBG0hQvYQ0WSU2mAdtXsm/TNMg+xEFjmJHLwJL56kG4P0dJ6UlJRQXV2dlm2JpIsKfZEvSCQTdMY68e05z+y+xb3dsJPvyqfQVUC2I1u99yIiItJnNTc0gwGXXnppWrdrs9sYNKqaESeMYPgJwxk5YRQlA0oIOIIEHEEaaaKjuYOP/v4RH727kY/e20hHc8dRy5Odnc2mTZtU7EtGUaEv/Z5pmkSSETqjXcX9vsfcA9gNG3nOfApc+XidXhX3InJYdEo9EektOn2dYML1d93AhJMmWJbDTJpQB0mPiekxMd0m+SX5TJ01lamz9pyxKAq2sIERsmFEOWK9/ds2b+PnP7qF5uZmFfqSUVToS78UT8YJxAP4YwE6Y51Ek9Eej7vtbvKcueQ688hRz72IHCFZrmxW/2qN1TFERHqoHjboqJyZ6FAlzSTBeBB/zE9nzE8oEQIXJF0m5CWwG3a8Tu+e72q52G12qyOL9Doq9KVf8BZ4SWYl2R2oJRAPEE70PJ+8gUGOM4c8Zy55zjwdcy8iIiJiEZthw+v04nV6qaCrg6b7sEr/nsMq26Nds/wD5Di6vsPluvJw21zqoBFBhb5koO4J9JrDLTSFmvg863MeWvV7ErZkj1O9eOxuchxevM4cvE4vdkN7g0VERER6G4fN0TUBsrsw9T2vM9aJL9pJJBkhEA8QiAeoC9XjsrlSRX+OIxubYbM6voglVOhLnxdNRGkJt9AcbqE53ExzuKVnj70dbNggBsXeInKcXryOHJ3nXkTSLhKL8LNnfgbAb7//W9xOt8WJRET6FsMwUr39ldmVRBKRVNEfiAeIJqM0R1pojrSkRmx6HV3rZ9k96u2XfkOVjvQZpmkSToRpi7TTvue8rC2RFjqivv3WNTAodBdS6ikhUB9g9pnn8tjzjzNg3AALkouIdEmaCd79dGXqtoiIHB633Y3b7qbEU0LCTOCP+fFFu86cFDfj+GN+/DE/hLrOnpTtyCLbkUO2I5tsR5bV8UWOGhX60ivFkjF8UR9tkfY9hX0bbdF2IonIAdf3Or2UeIop8ZRQ4imm0F2Y6rFfv3s9vpb9dwaIiIiISOboPg1yvit/TwdRBH+8q9APxAIkzASdeyb4S6mAeQuvpcnZzE7/LvJdeeQ4c3RIp/R5/brQf/jhh7n33nupr69n3LhxPPjgg0yaNMnqWP1GVzHftce1c8919/0vTpbXzcAg15lLgbuAQncBRe5Cij0lZDl0uioRERER6WIYBlkOD1kOD6WeEkzTJJQIEYwHCcSDBONBYskYOGHyzMk00kRj7fKu53YP+Xd6yXHkkOXwkO3IIsuehcfhwWlz4bK5cNmdOAyHDgeQXqnfFvrPP/88CxYs4NFHH2Xy5MksXLiQ6dOn8+mnn1JWVmZ1vD4vlowRjHd9mAZjXR+m+36wBuPBL+2d7+axeyhwF1Dg6irqC90F5LvydWy9iIiIiHwjhmHsGa6fTcmeZbFkjM8++4xnnn6Gi6+6BHeBm6gtimmYe4f8fx2za8dA6p95oNupFPv8v88yk69dp/v1bD1e29Z1f892bKYNGzZs3Y+ZXY/bTNue+6ln9EgFUFJSQnV19cE2p/QB/bZi+t3vfsfVV1/NlVdeCcCjjz7KK6+8wlNPPcVNN91kcbojq6amhubm5oNe39zzL0mSpLHnQs/rhJEkbsRJGAkSJLqujQTxPdemYR7UtuxJOy7ThSvpwp104TKduJJd9+3sHTLlowMfHd/4vQNs2rTpkJ4nIiIiIpnLaXPSWtPKq0+9wqtPvpJanl9aQHl1OWXVZRRVFFFQWpC65BbnkZ2bTZY3C4fTsadO7/oHfLFC75WSySTRUJRIKEI0HCESjBD/PM646Hi8WTk4DAd2mwOHYcdhc+AwHDhse2/b91lmN+xduw0MA/Zcd92yYRj77AQx9u4Aoft26nEbNuML62mUxGHrl4V+NBpl3bp13HzzzallNpuNadOmsWrVKguTHVkNwQY21P4Pr73xGobNwOFy4nQ5cDgdOFxOHHtuO1177jsdOFwOnC4nNvvhn4ok2Bmktb6VtoY22hpaaa3fe2lraKOltplgZ/AIvNOD4/d3pm1bIiIiItL7dfo6wYTr77qBCSdNOLgn+cH07+mG3/dC17WZum3uX/h/Wf36NcvN7tupy97XNr+Yw2YeYNne17LZbHhyPHhyeh762pHsoCNwaB1rR1xqpATsHdGw93bq1j7LDrzuPv+b+y3BMPc+Kzsrm0mDJ2XMJI39stBvbm4mkUhQXl7eY3l5eTn/+Mc/9ls/EokQiewdZt7R0fUL4PP17gne6nz17PDtYPQ/jT7o5yQTCSKhvTNBJ+MmyXiSZCKJGTdJJpNd9+NJEtEEZixJIpYgEU2SjCX23E6QjCXonlDahkExxRRXFEPFkX6XX+/jDR+x+L8Xs/HDj7D104lVtm3eBsDmT7aQ7cmxOI011AZqAzi6bZBMJAmHu+YX+XD1hwfcYRqJRyDKnnU24Hak//R6+jlQG4DaANQGoDaAvW0QCUcIBtLXAWUFE3O/4t80YOtnW3jl/1uMy+3Cne3G5XHjynLh8rhw77nt3mfZvo87XU5sNgObzYZhMzD2XNvsXYcI2Ox77tv2XttsNmz2XthjH4WcTdmMGjzK6iRfqrv+NM2vHz1tmAezVoapra1lwIAB/P3vf2fKlCmp5TfccAPLly9nzZo1Pda//fbbueOOO9IdU0RERERERKSHnTt3MnDgwK9cp1/26JeUlGC322loaOixvKGhgYqK/bucb775ZhYsWJC6n0wmaW1tpbi4WMeP9HI+n49Bgwaxc+dO8vLyrI5jCbWB2gDUBt3UDmoDUBt0UzuoDUBt0E3toDaA3t8GpmnS2dlJVVXV167bLwt9l8vFiSeeyLJly5g9ezbQVbwvW7aM+fPn77e+2+3G7e45vLKgoCANSeVIycvL65W/rOmkNlAbgNqgm9pBbQBqg25qB7UBqA26qR3UBtC72yA/P/+g1uuXhT7AggULmDNnDhMnTmTSpEksXLiQQCCQmoVfREREREREpC/qt4X+RRddRFNTE7/85S+pr69n/PjxvPbaa/tN0CciIiIiIiLSl/TbQh9g/vz5BxyqL5nD7XZz22237XfoRX+iNlAbgNqgm9pBbQBqg25qB7UBqA26qR3UBpBZbdAvZ90XERERERERyVT7n+RXRERERERERPosFfoiIiIiIiIiGUSFvoiIiIiIiEgGUaEvIiIiIiIikkFU6EvGuuKKKzAMo8dlxowZVsey1A9/+EMMw2DhwoVWR0mr22+/nWOPPZacnBwKCwuZNm0aa9assTpW2sRiMW688UaOP/54cnJyqKqq4vLLL6e2ttbqaGn3wgsvcNZZZ1FcXIxhGGzYsMHqSGn38MMPM2TIEDweD5MnT+b999+3OlJarVixgnPOOYeqqioMw+Cll16yOlJa3XXXXZx00knk5uZSVlbG7Nmz+fTTT62OlXaPPPIIY8eOJS8vj7y8PKZMmcKSJUusjmWpu+++G8MwuO6666yOkja33377ft8Vjz32WKtjWWL37t1ceumlFBcXk5WVxfHHH88HH3xgday0GTJkyH4/C4ZhMG/ePKujHTIV+pLRZsyYQV1dXeryX//1X1ZHssyLL77I6tWrqaqqsjpK2o0cOZKHHnqIjRs38u677zJkyBDOOussmpqarI6WFsFgkPXr1/OLX/yC9evX88ILL/Dpp58ya9Ysq6OlXSAQ4JRTTuGee+6xOoolnn/+eRYsWMBtt93G+vXrGTduHNOnT6exsdHqaGkTCAQYN24cDz/8sNVRLLF8+XLmzZvH6tWrWbp0KbFYjLPOOotAIGB1tLQaOHAgd999N+vWreODDz7gjDPO4Nxzz+Xjjz+2Opol1q5dy2OPPcbYsWOtjpJ2Y8aM6fFd8d1337U6Utq1tbUxdepUnE4nS5Ys4ZNPPuG3v/0thYWFVkdLm7Vr1/b4OVi6dCkAF1xwgcXJDp1OrycZ64orrqC9vb3f9dYcyO7du5k8eTKvv/46Z599Ntddd12/2mP/RT6fj/z8fN58803OPPNMq+NYYu3atUyaNIkdO3ZQXV1tdZy0+/zzzxk6dCgffvgh48ePtzpO2kyePJmTTjqJhx56CIBkMsmgQYO49tpruemmmyxOl36GYfDiiy8ye/Zsq6NYpqmpibKyMpYvX863v/1tq+NYqqioiHvvvZerrrrK6ihp5ff7mTBhAr///e+58847GT9+fL8Z+Xf77bfz0ksv9cvRXfu66aabeO+991i5cqXVUXqN6667jsWLF7N582YMw7A6ziFRj75ktHfeeYeysjJGjRrFj370I1paWqyOlHbJZJLLLruM66+/njFjxlgdx3LRaJTHH3+c/Px8xo0bZ3Ucy3R0dGAYBgUFBVZHkTSJRqOsW7eOadOmpZbZbDamTZvGqlWrLEwmVuro6AC6itz+KpFI8NxzzxEIBJgyZYrVcdJu3rx5nH322T0+G/qTzZs3U1VVxbBhw/j+979PTU2N1ZHS7uWXX2bixIlccMEFlJWVccIJJ/DEE09YHcsy0WiUP/3pT8ydO7fPFvkADqsDiBwtM2bM4LzzzmPo0KFs3bqVW265hZkzZ7Jq1SrsdrvV8dLmnnvuweFw8OMf/9jqKJZavHgxF198McFgkMrKSpYuXUpJSYnVsSwRDoe58cYbueSSS8jLy7M6jqRJc3MziUSC8vLyHsvLy8v5xz/+YVEqsVIymeS6665j6tSpHHfccVbHSbuNGzcyZcoUwuEwXq+XF198kW9961tWx0qr5557jvXr17N27Vqro1hi8uTJPP3004waNYq6ujruuOMOTj31VD766CNyc3Otjpc227Zt45FHHmHBggXccsstrF27lh//+Me4XC7mzJljdby0e+mll2hvb+eKK66wOsphUY++ZIRnnnkGr9ebuqxcuZKLL76YWbNmcfzxxzN79mwWL17M2rVreeedd6yOe9R8sR2WL1/O/fffz9NPP92n90h+Ewf6WQA4/fTT2bBhA3//+9+ZMWMGF154YcYel/xlbQBdE/NdeOGFmKbJI488YmHKo++r2kFEunpyP/roI5577jmro1hi1KhRbNiwgTVr1vCjH/2IOXPm8Mknn1gdK2127tzJT37yE5555hk8Ho/VcSwxc+ZMLrjgAsaOHcv06dN59dVXaW9v57//+7+tjpZWyWSSCRMm8Jvf/IYTTjiBa665hquvvppHH33U6miWePLJJ5k5c2afn9dKPfqSEWbNmsXkyZNT9wcMGLDfOsOGDaOkpIQtW7Zk7HHZX2yHP//5zzQ2NvY4BjuRSPCzn/2MhQsX8vnnn1uQ8uj6sp+FnJwchg8fzvDhw/mnf/onRowYwZNPPsnNN99sVdSj5svaoLvI37FjB2+99VbG9+YfzOdCf1JSUoLdbqehoaHH8oaGBioqKixKJVaZP38+ixcvZsWKFQwcONDqOJZwuVwMHz4cgBNPPJG1a9dy//3389hjj1mcLD3WrVtHY2MjEyZMSC1LJBKsWLGChx56iEgk0q9GQAIUFBQwcuRItmzZYnWUtKqsrNxvNMvo0aP5y1/+YlEi6+zYsYM333yTF154weooh02FvmSE3Nzcrx1itWvXLlpaWqisrExTqvT7Yjtcc801nHPOOT3WmT59OpdddhlXXnlluuOlxcH8LEDX3utIJJKGROl3oDboLvI3b97M22+/TXFxsUXp0udgfxb6C5fLxYknnsiyZctSk88lk0mWLVvG/PnzrQ0naWOaJtdeey0vvvgi77zzDkOHDrU6Uq+RyX8XDuTMM89k48aNPZZdeeWVHHvssdx44439rsiHrokJt27dymWXXWZ1lLSaOnXqfqfZ/Oyzzxg8eLBFiayzaNEiysrKOPvss62OcthU6EtG8vv93HHHHZx//vlUVFSwdetWbrjhBoYPH8706dOtjpc2xcXF+xV0TqeTiooKRo0aZVGq9AoEAvz6179m1qxZVFZW0tzczMMPP8zu3bv79ClTvolYLMa//Mu/sH79ehYvXkwikaC+vh7omoDL5XJZnDB9Wltbqampoba2FiD1xaaioqJf9GovWLCAOXPmMHHiRCZNmsTChQsJBAIZu+PvQPx+f4/euu3bt7NhwwaKior6xRko5s2bx7PPPstf//pXcnNzU58F+fn5ZGVlWZwufW6++WZmzpxJdXU1nZ2dPPvss7zzzju8/vrrVkdLm9zc3P3mZsjJyaG4uLjfzNnwb//2b5xzzjkMHjyY2tpabrvtNux2O5dcconV0dLqpz/9KSeffDK/+c1vuPDCC3n//fd5/PHHefzxx62OllbJZJJFixYxZ84cHI4MKJNNkQwUDAbNs846yywtLTWdTqc5ePBg8+qrrzbr6+utjma5wYMHm/fdd5/VMdImFAqZ3/ve98yqqirT5XKZlZWV5qxZs8z333/f6mhps337dhM44OXtt9+2Ol5aLVq06IDtcNttt1kdLW0efPBBs7q62nS5XOakSZPM1atXWx0prd5+++0D/gzMmTPH6mhp8WWfBYsWLbI6WlrNnTvXHDx4sOlyuczS0lLzzDPPNN944w2rY1nutNNOM3/yk59YHSNtLrroIrOystJ0uVzmgAEDzIsuusjcsmWL1bEs8be//c087rjjTLfbbR577LHm448/bnWktHv99ddNwPz000+tjnJEGKZpmmncryAiIiIiIiIiR5Fm3RcRERERERHJICr0RURERERERDKICn0RERERERGRDKJCX0RERERERCSDqNAXERERERERySAq9EVEREREREQyiAp9ERERERERkQyiQl9EREREREQkg6jQFxERkUN2zjnnMGPGjAM+tnLlSgzDYPny5cyYMYOqqircbjeDBg1i/vz5+Hy+1LpXXHEFhmHsdxkzZky63oqIiEjGUKEvIiIih+yqq65i6dKl7Nq1a7/HFi1axMSJExk7diznnnsuL7/8Mp999hlPP/00b775Jj/84Q9T695///3U1dWlLjt37qSoqIgLLrggnW9HREQkIximaZpWhxAREZG+KR6PM3DgQObPn8+tt96aWu73+6msrOTee+/tUdB3e+CBB7j33nvZuXPnAV/3pZde4rzzzmP79u0MHjz4qOUXERHJROrRFxERkUPmcDi4/PLLefrpp9m37+DPf/4ziUSCSy65ZL/n1NbW8sILL3Daaad96es++eSTTJs2TUW+iIjIIVChLyIiIodl7ty5bN26leXLl6eWLVq0iPPPP5/8/PzUsksuuYTs7GwGDBhAXl4e//mf/3nA16utrWXJkiX84Ac/OOrZRUREMpEKfRERETksxx57LCeffDJPPfUUAFu2bGHlypVcddVVPda77777WL9+PX/961/ZunUrCxYsOODr/eEPf6CgoIDZs2cf7egiIiIZScfoi4iIyGF76qmnuPbaa6mvr+fuu+/m+eefZ/PmzRiGccD13333XU499VRqa2uprKxMLTdNk5EjR/LP//zP3HfffemKLyIiklHUoy8iIiKH7cILL8Rms/Hss8/yxz/+kblz535pkQ+QTCYBiEQiPZYvX76cLVu27DcaQERERA6eevRFRETkiPjBD37ACy+8gM/no6amhqqqKgBeffVVGhoaOOmkk/B6vXz88cdcf/31FBUV8e677/Z4jcsuu4zNmzezevVqK96CiIhIRlCPvoiIiBwRV111FW1tbUyfPj1V5ANkZWXxxBNPcMoppzB69Gh++tOfMmvWLBYvXtzj+R0dHfzlL39Rb76IiMhhUo++iIiIiIiISAZRj76IiIiIiIhIBlGhLyIiIiIiIpJBVOiLiIiIiIiIZBAV+iIiIiIiIiIZRIW+iIiIiIiISAZRoS8iIiIiIiKSQVToi4iIiIiIiGQQFfoiIiIiIiIiGUSFvoiIiIiIiEgGUaEvIiIiIiIikkFU6IuIiIiIiIhkEBX6IiIiIiIiIhnk/wfd8bg0pEEw6AAAAABJRU5ErkJggg==\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x700 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x700 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x700 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "for feature in train.columns[:-1]:\n",
        "  histogram_boxplot(train, feature, figsize=(12, 7), step=1, fmt='{:.0f}')"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Let's look at the unique values of all the Target variable\n"
      ],
      "metadata": {
        "id": "LrD6bdIOfPOS"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "print(f'Unique values in `Target` in the `Train` dataset are :')\n",
        "display(pd.DataFrame(data=[train['Target'].value_counts(), train['Target'].value_counts(normalize=True)],\n",
        "                         index=['count', 'share']).T.style.format({'count': '{:,.0f}', 'share': '{:.2%}'}))\n",
        "print('*'*50)\n",
        "\n",
        "print(f'Unique values in `Target` in the `Test` dataset are :')\n",
        "display(pd.DataFrame(data=[test['Target'].value_counts(), test['Target'].value_counts(normalize=True)],\n",
        "                         index=['count', 'share']).T.style.format({'count': '{:,.0f}', 'share': '{:.2%}'}))\n",
        "print('*'*50)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 281
        },
        "id": "BaLmuJsLfPYL",
        "outputId": "49afd703-a650-49be-80a1-640280fbb2de"
      },
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Unique values in `Target` in the `Train` dataset are :\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7fe231682a10>"
            ],
            "text/html": [
              "<style type=\"text/css\">\n",
              "</style>\n",
              "<table id=\"T_97866\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th class=\"blank level0\" >&nbsp;</th>\n",
              "      <th id=\"T_97866_level0_col0\" class=\"col_heading level0 col0\" >count</th>\n",
              "      <th id=\"T_97866_level0_col1\" class=\"col_heading level0 col1\" >share</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th id=\"T_97866_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
              "      <td id=\"T_97866_row0_col0\" class=\"data row0 col0\" >18,890</td>\n",
              "      <td id=\"T_97866_row0_col1\" class=\"data row0 col1\" >94.45%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_97866_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
              "      <td id=\"T_97866_row1_col0\" class=\"data row1 col0\" >1,110</td>\n",
              "      <td id=\"T_97866_row1_col1\" class=\"data row1 col1\" >5.55%</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "**************************************************\n",
            "Unique values in `Target` in the `Test` dataset are :\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7fe22f6678b0>"
            ],
            "text/html": [
              "<style type=\"text/css\">\n",
              "</style>\n",
              "<table id=\"T_0763e\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th class=\"blank level0\" >&nbsp;</th>\n",
              "      <th id=\"T_0763e_level0_col0\" class=\"col_heading level0 col0\" >count</th>\n",
              "      <th id=\"T_0763e_level0_col1\" class=\"col_heading level0 col1\" >share</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th id=\"T_0763e_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
              "      <td id=\"T_0763e_row0_col0\" class=\"data row0 col0\" >4,718</td>\n",
              "      <td id=\"T_0763e_row0_col1\" class=\"data row0 col1\" >94.36%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_0763e_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
              "      <td id=\"T_0763e_row1_col0\" class=\"data row1 col0\" >282</td>\n",
              "      <td id=\"T_0763e_row1_col1\" class=\"data row1 col1\" >5.64%</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "**************************************************\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "DkKt_etBp2SM"
      },
      "source": [
        "**Observations:**\n",
        "* The majority of variables are closely distributed to the normal distribution.\n",
        "* There are many outliers for all the variables.\n",
        "* The average of means is close to zero (ranging from -3.6 to +2.5).\n",
        "* The standard deviation of the means lies between 1.65 and 5.5.\n",
        "* About 5.55% of the rows have a target value of \"1\", while 94.45% have a target value of \"0\". The failure rate in the observations is 5.6%.\n",
        "* The distribution of classes in the target variable is imbalanced.\n"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Bivariate Analysis"
      ],
      "metadata": {
        "id": "Rh4UIfrajkFc"
      }
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "soYzHjHGi5iS"
      },
      "source": [
        "### Correlation heatmap"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 32,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 907
        },
        "id": "CPumP-rci5q8",
        "outputId": "da9d1e93-be47-483e-ee76-518c12e85536"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1400x1000 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "plt.figure(figsize=(14, 10))\n",
        "sns.heatmap(train.corr(), annot=False, vmin=-1, vmax=1, fmt=\".2f\", cmap=\"Spectral\")\n",
        "plt.xlabel('')\n",
        "plt.ylabel('')\n",
        "plt.title('Correlation heatmap representing the correlation\\nbetween numeric variables of the dataset',\n",
        "          fontsize=16)\n",
        "plt.show();"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 33,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "77stzeCOrNMk",
        "outputId": "9fc85502-8ed2-4884-a0bb-ac10673598ce"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "V18   -0.293340\n",
              "V39   -0.227264\n",
              "V36   -0.216453\n",
              "V3    -0.213855\n",
              "V26   -0.180469\n",
              "Name: Target, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 33
        }
      ],
      "source": [
        "# The correlations between the dependent variable and predictors\n",
        "corr = train.corr()\n",
        "corr['Target'].sort_values().head()"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "corr['Target'][:-1].sort_values().tail()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "OpCntPFslCHC",
        "outputId": "9d17116b-dcd6-4b84-dbeb-5ce22ff52b01"
      },
      "execution_count": 34,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "V28    0.207359\n",
              "V16    0.230507\n",
              "V7     0.236907\n",
              "V15    0.249118\n",
              "V21    0.256411\n",
              "Name: Target, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 34
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "corr['Target'][:-1].describe()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "oGXnYu8akutA",
        "outputId": "3c81a325-52ce-4e4f-af56-0537d42091c0"
      },
      "execution_count": 35,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "count    40.000000\n",
              "mean      0.008393\n",
              "std       0.142960\n",
              "min      -0.293340\n",
              "25%      -0.101031\n",
              "50%       0.005693\n",
              "75%       0.108953\n",
              "max       0.256411\n",
              "Name: Target, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 35
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "* Either there are no correlations or weak positive/negative correlations between the dependent variable and the predictors."
      ],
      "metadata": {
        "id": "Ahjh_6ybkx-b"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 36,
      "metadata": {
        "id": "7oRbUMBFsuwP"
      },
      "outputs": [],
      "source": [
        "# The correlations between the independent variables\n",
        "pos, neg = [], []\n",
        "\n",
        "for i in range(len(corr)-1):\n",
        "  for j in range(i+1, len(corr)-1):\n",
        "    if corr.iloc[i, j] > 0.7:\n",
        "      pos.append([corr.index[i], corr.columns[j]])\n",
        "    if corr.iloc[i, j] < -0.7:\n",
        "      neg.append([corr.index[i], corr.columns[j]])\n",
        "      "
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 37,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 238
        },
        "id": "gZ0Xmj-lw_jn",
        "outputId": "eff8e228-ac13-49ff-c73c-3bf1069d066e"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Pairs of independent variables exhibiting strong positive correlations:\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "[['V2', 'V26'],\n",
              " ['V6', 'V11'],\n",
              " ['V7', 'V15'],\n",
              " ['V8', 'V16'],\n",
              " ['V8', 'V23'],\n",
              " ['V11', 'V29'],\n",
              " ['V16', 'V21'],\n",
              " ['V19', 'V34'],\n",
              " ['V24', 'V32'],\n",
              " ['V25', 'V27'],\n",
              " ['V36', 'V39']]"
            ]
          },
          "metadata": {}
        }
      ],
      "source": [
        "print('Pairs of independent variables exhibiting strong positive correlations:')\n",
        "display(pos)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 38,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 238
        },
        "id": "Q4fyaz0zxwub",
        "outputId": "f862aec2-ed32-4fce-c198-007b84aac8ca"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Pairs of independent variables exhibiting strong negative correlations:\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "[['V2', 'V14'],\n",
              " ['V3', 'V23'],\n",
              " ['V9', 'V16'],\n",
              " ['V14', 'V38'],\n",
              " ['V17', 'V27'],\n",
              " ['V21', 'V35'],\n",
              " ['V24', 'V27'],\n",
              " ['V25', 'V30'],\n",
              " ['V25', 'V32'],\n",
              " ['V25', 'V33'],\n",
              " ['V27', 'V32']]"
            ]
          },
          "metadata": {}
        }
      ],
      "source": [
        "print('Pairs of independent variables exhibiting strong negative correlations:')\n",
        "display(neg)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "twNXBPYZrz2R"
      },
      "source": [
        "* The correlations between the dependent variable and predictors are very weak, ranging from -0.29 to +0.25.\n",
        "* There are 11 pairs of independent variables that are strongly positively correlated with each other.\n",
        "* There are 11 pairs of independent variables that are strongly negatively correlated with each other.\n",
        "* The variables `V25` and `V27` have the highest number of mutual correlations with other predictors.\n",
        "  * They are also positively correlated with each other.\n",
        "  * `V25` is negatively correlated with `V30`, `V32`, and `V33`.\n",
        "  * `V27` is negatively correlated with `V17`, `V24`, and `V32`."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "knk0w9XH4jao"
      },
      "source": [
        "## Data Pre-processing"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9vo9Xr7z1XzS"
      },
      "source": [
        "* Preparing data for modeling\n",
        "* Missing value treatment\n",
        "* Feature engineering\n",
        "* Outlier detection and treatment\n",
        "* Any other preprocessing steps"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_NGpGEER5qs3"
      },
      "source": [
        "## Preparing data for modeling"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        ">In this project, two separate datasets have been provided: Train.csv and Test.csv. The Train.csv file can be split into training and validation sets to train, tune, and check how models perform. The Test.csv file should be used for testing the performance of the final model only. So, there is no need to split the Test.csv file."
      ],
      "metadata": {
        "id": "1q-v6O6el2OI"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 39,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_MnoDUBF5q04",
        "outputId": "a547c31a-1503-4c96-a927-d9301abf4adb"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "(15000, 40) (5000, 40) (5000, 40)\n"
          ]
        }
      ],
      "source": [
        "# Splitting training data into training and validation, as we already have tthe test set:\n",
        "X_temp, y_temp = train.drop(['Target'], axis=1), train['Target']\n",
        "X_test, y_test = test.drop('Target', axis=1), test['Target']\n",
        "\n",
        "#The next 3 lines were needed for a smoke-test purposes only during the project preparation\n",
        "#N = 1000\n",
        "#X_temp, y_temp = train[:N].drop(['Target'], axis=1), train['Target'][:N]\n",
        "#X_test, y_test = test[:N].drop('Target', axis=1), test['Target'][:N]\n",
        "\n",
        "X_train, X_valid, y_train, y_valid = train_test_split(\n",
        "    X_temp, y_temp, test_size=0.25, random_state=42, stratify=y_temp)\n",
        "\n",
        "print(X_train.shape, X_valid.shape, X_test.shape)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 40,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ehKbTff4H4pK",
        "outputId": "f789f1b1-d56d-4781-c5d5-51299a312f8c"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Number of rows in train data is 15000\n",
            "Number of rows in validation data is 5000\n",
            "Number of rows in test data is 5000\n"
          ]
        }
      ],
      "source": [
        "print(\"Number of rows in train data is\", X_train.shape[0])\n",
        "print(\"Number of rows in validation data is\", X_valid.shape[0])\n",
        "print(\"Number of rows in test data is\", X_test.shape[0])"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "0J99-7Kubp09"
      },
      "source": [
        "## Missing value imputation\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "BOGgSiGKIt2x"
      },
      "source": [
        " Let's drop the missing values\n",
        "> We reviewed three options to address missing values in this project.\n",
        "\n",
        "  * **Option 1**. Dropping rows with missing values. We can remove rows with missing values, as there are only a few.\n",
        "    * Pros:\n",
        "      - Easy to implement.\n",
        "      - Preserves the integrity of the data, as no artificial values are introduced.\n",
        "    * Cons:\n",
        "      - Sometimes it may result in loss of valuable information if the dataset is small or missing values are significant in number.\n",
        "      - May introduce bias if the missing values are not missing at random.\n",
        "\n",
        "  * **Option 2.** Median. We can replace missing values with the median value.\n",
        "    * Pros:\n",
        "      - Simple and fast to compute.\n",
        "      - Less sensitive to outliers compared to the mean value.\n",
        "    * Cons:\n",
        "      - May not accurately represent the missing data if the distribution is heavily skewed.\n",
        "      - Can distort the underlying distribution of the data.\n",
        "\n",
        "  * **Option 3.** KNN. We can replace missing values using the KNN algorithm.\n",
        "    * Pros:\n",
        "      - Can provide more accurate estimations of missing values, as it considers the similarity between instances in the dataset.\n",
        "      - Handles non-linear relationships between features.\n",
        "    * Cons:\n",
        "      - Computationally expensive, especially for large datasets.\n",
        "      - Sensitive to the presence of noise and outliers in the dataset.\n",
        "\n",
        ">**Option 3 has been selected for this project.**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 41,
      "metadata": {
        "id": "jy7GaTOSL4_Z"
      },
      "outputs": [],
      "source": [
        "# Option 1. Dropping rows with missing values. \n",
        "\n",
        "# Dropping missing values in the training dataset\n",
        "#X_train = X_train.dropna()\n",
        "#y_train = y_train[X_train.index]\n",
        "\n",
        "# Dropping missing values in the validation dataset\n",
        "#X_valid = X_valid.dropna()\n",
        "#y_valid = y_valid[X_valid.index]\n",
        "\n",
        "# Dropping missing values in the testing dataset\n",
        "#X_test = X_test.dropna()\n",
        "#y_test = y_test[X_test.index]\n",
        "\n",
        "#print(X_train.shape, X_valid.shape, X_test.shape)\n",
        "#print(y_train.shape, y_valid.shape, y_test.shape)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 42,
      "metadata": {
        "id": "JQV5Est6LF9_"
      },
      "outputs": [],
      "source": [
        "# Option 2. Replacing missing values with the median value.\n",
        "\n",
        "# Defining the KNN imputer\n",
        "#imp_median = SimpleImputer(missing_values=np.nan, strategy='median')\n",
        "\n",
        "# Fit the imputer on train data and transform the train data\n",
        "#X_train = pd.DataFrame(imp_median.fit_transform(X_train), columns=X_train.columns)\n",
        "\n",
        "# Transform the validation data using the imputer fit on train data\n",
        "#X_valid = pd.DataFrame(imp_median.transform(X_valid), columns=X_valid.columns)\n",
        "\n",
        "# Transform the test data using the imputer fit on train data\n",
        "#X_test = pd.DataFrame(imp_median.transform(X_test), columns=X_test.columns)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "RJhksgEL5Isv"
      },
      "source": [
        "* To address missing values in the dataset, we will use an adaptive imputation method: **KNN Imputer** can adapt to various data distributions and patterns, making it suitable for our datasets.\n",
        "  * `KNNImputer`: Each sample's missing values are imputed by looking at the n_neighbors nearest neighbors found in the training set. Default value for n_neighbors=5.\n",
        "  * KNN imputer replaces missing values using the average of k nearest non-missing feature values.\n",
        "  * Nearest points are found based on euclidean distance."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 43,
      "metadata": {
        "id": "qVBstow_r6Bp"
      },
      "outputs": [],
      "source": [
        "# Option 3. KNN. We can replace missing values using the KNN algorithm.\n",
        "# defining the KNN imputer\n",
        "imputer = KNNImputer(n_neighbors=5)\n",
        "\n",
        "# Fit the imputer on the training dataset\n",
        "imputer.fit(X_train)\n",
        "\n",
        "# Impute missing values in the training dataset\n",
        "X_train = pd.DataFrame(imputer.transform(X_train), columns=X_train.columns)\n",
        "\n",
        "# Impute missing values in the validation dataset using the same imputer\n",
        "X_valid = pd.DataFrame(imputer.transform(X_valid), columns=X_valid.columns)\n",
        "\n",
        "# Impute missing values in the test dataset using the same imputer\n",
        "X_test = pd.DataFrame(imputer.transform(X_test), columns=X_test.columns)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 44,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "wXcBng-yIQZg",
        "outputId": "6af8ab89-bac2-49e1-d7d1-737b040e9080"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Number of missing values in train data is 0\n",
            "Number of missing values in validation data is 0\n",
            "Number of missing values in test data is 0\n"
          ]
        }
      ],
      "source": [
        "# Checking that no column has missing values in train, validation or test sets\n",
        "\n",
        "print(\"Number of missing values in train data is\", X_train.isna().sum().sum())\n",
        "print(\"Number of missing values in validation data is\", X_valid.isna().sum().sum())\n",
        "print(\"Number of missing values in test data is\", X_test.isna().sum().sum())\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "O8k2N3WrIor1"
      },
      "source": [
        "* All missing values have been treated."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "FofrNVwP5qOx"
      },
      "source": [
        "## Feature engineering\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "CRNhdr_-MFkk"
      },
      "source": [
        "### Oversampling train data using SMOTE"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 45,
      "metadata": {
        "id": "Ho1SVpFuLA4s"
      },
      "outputs": [],
      "source": [
        "# Fit SMOTE on train data (Synthetic Minority Oversampling Technique)\n",
        "\n",
        "sm = SMOTE(sampling_strategy=1, k_neighbors=5, random_state=42)\n",
        "\n",
        "X_train_over, y_train_over = sm.fit_resample(X_train, y_train)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 46,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Zb9S8sy0MJd5",
        "outputId": "aed2ce33-3f99-4e8b-a2b1-6c94a986290e"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Before OverSampling, count of label '1': 833\n",
            "Before OverSampling, count of label '0': 14167 \n",
            "\n",
            "After OverSampling, count of label '1': 14167\n",
            "After OverSampling, count of label '0': 14167 \n",
            "\n",
            "After OverSampling, the shape of train_X: (28334, 40)\n",
            "After OverSampling, the shape of train_y: (28334,) \n",
            "\n"
          ]
        }
      ],
      "source": [
        "print(\"Before OverSampling, count of label '1': {}\".format(sum(y_train == 1)))\n",
        "print(\"Before OverSampling, count of label '0': {} \\n\".format(sum(y_train == 0)))\n",
        "\n",
        "print(\"After OverSampling, count of label '1': {}\".format(sum(y_train_over == 1)))\n",
        "print(\"After OverSampling, count of label '0': {} \\n\".format(sum(y_train_over == 0)))\n",
        "\n",
        "print(\"After OverSampling, the shape of train_X: {}\".format(X_train_over.shape))\n",
        "print(\"After OverSampling, the shape of train_y: {} \\n\".format(y_train_over.shape))"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "o-rigrbUMj4I"
      },
      "source": [
        "### Undersampling train data using Random Undersampler"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 47,
      "metadata": {
        "id": "XTD6CMYiLB7t"
      },
      "outputs": [],
      "source": [
        "# Fit Random Under Sampler on the train data\n",
        "\n",
        "rus = RandomUnderSampler(random_state=42, sampling_strategy=1)\n",
        "\n",
        "X_train_un, y_train_un = rus.fit_resample(X_train, y_train)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 48,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "EO5jva5VMpxc",
        "outputId": "8c2b57f6-4450-4746-ad96-0adcf8ba01b2"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Before Under Sampling, count of label '1': 833\n",
            "Before Under Sampling, count of label '0': 14167 \n",
            "\n",
            "After Under Sampling, count of label '1': 833\n",
            "After Under Sampling, count of label '0': 833 \n",
            "\n",
            "After Under Sampling, the shape of train_X: (1666, 40)\n",
            "After Under Sampling, the shape of train_y: (1666,) \n",
            "\n"
          ]
        }
      ],
      "source": [
        "print(\"Before Under Sampling, count of label '1': {}\".format(sum(y_train == 1)))\n",
        "print(\"Before Under Sampling, count of label '0': {} \\n\".format(sum(y_train == 0)))\n",
        "\n",
        "print(\"After Under Sampling, count of label '1': {}\".format(sum(y_train_un == 1)))\n",
        "print(\"After Under Sampling, count of label '0': {} \\n\".format(sum(y_train_un == 0)))\n",
        "\n",
        "print(\"After Under Sampling, the shape of train_X: {}\".format(X_train_un.shape))\n",
        "print(\"After Under Sampling, the shape of train_y: {} \\n\".format(y_train_un.shape))"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "LOlH6u8t5qeJ"
      },
      "source": [
        "## Outlier detection and treatment"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "gNgvlbLvOc5m"
      },
      "source": [
        "* There are quite a few observations at the extreme in each predictor, which can be considered as outliers.\n",
        "* We will not remove all such data points, as they represent real operational trends."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "x6s_j3ba5q-C"
      },
      "source": [
        "## Any other preprocessing steps"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "JKfRiTo3Ol2H"
      },
      "source": [
        "* No any other preprocessing steps are needed"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "RFN3BAE2pg0G"
      },
      "source": [
        "## Data leakage"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ne2Cqk7spg0G"
      },
      "source": [
        "* Data leakage is the situation where the model, while it is being created, is influenced by test data\n",
        "\n",
        "* Due to data leakage, model performance on test data is not trustworthy as the sanctity of test data is compromised\n",
        "* Data leakage can happen in multiple ways.\n",
        "  - Standardizing data before splitting into training and testing data. For e.g. using z-score\n",
        "  - Imputing missing values for the entire data before splitting into training and testing data\n",
        "  - Hyper parameter tuning to improve performance on test data\n",
        "* Best way to avoid data leakage is to keep a portion of the sample data away before doing any processing\n",
        "\n",
        "**Ensure no data leakage:**\n",
        "> * To prevent data leakage, we set aside a portion of the sample data before any processing is done - `Test` dataset.\n",
        "> * This ensures that the testing data remains untouched, and the model is not influenced by it during its creation.\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "OzOa9FGA6WtG"
      },
      "source": [
        "# Model Building"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "YZqmoqz7bp0-"
      },
      "source": [
        "## Model evaluation criterion"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "l2ORUgmUjDZC"
      },
      "source": [
        "The nature of predictions made by the classification model will translate as follows:\n",
        "\n",
        "- True positives (TP) are failures correctly predicted by the model.\n",
        "- False negatives (FN) are real failures in a generator where there is no detection by model. \n",
        "- False positives (FP) are failure detections in a generator where there is no failure.\n",
        "\n",
        "**Which metric to optimize?**\n",
        "\n",
        "* We need to choose the metric which will ensure that the maximum number of generator failures are predicted correctly by the model.\n",
        "* We would want **Recall** to be maximized as greater the Recall, the higher the chances of minimizing false negatives.\n",
        "* We want to minimize false negatives because if a model predicts that a machine will have no failure when there will be a failure, it will increase the maintenance cost."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "eqCDCbcw4jas"
      },
      "source": [
        "### Model Building with original data"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "dBtuhurlhKyp"
      },
      "source": [
        "Sample models building with original data:\n",
        "  * DecisionTreeClassifier\n",
        "  * LogisticRegression\n",
        "  * RandomForestClassifier,\n",
        "  * BaggingClassifier,\n",
        "  * AdaBoostClassifier,\n",
        "  * GradientBoostingClassifier,\n",
        "  * XGBClassifier."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 49,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "V-tpzI7g4jas",
        "outputId": "164f58a9-93e6-498b-daa6-73a4e6178d95"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "Cross-Validation performance on training dataset:\n",
            "\n",
            "\tDecisionTreeClassifier: 0.74062\n",
            "\t\tIteration duration: 18.28 seconds\n",
            "\tLogisticRegression: 0.48980\n",
            "\t\tIteration duration: 0.59 seconds\n",
            "\tRandomForestClassifier: 0.72750\n",
            "\t\tIteration duration: 139.68 seconds\n",
            "\tBaggingClassifier: 0.70816\n",
            "\t\tIteration duration: 108.72 seconds\n",
            "\tAdaBoostClassifier: 0.59664\n",
            "\t\tIteration duration: 48.78 seconds\n",
            "\tGradientBoostingClassifier: 0.69633\n",
            "\t\tIteration duration: 242.12 seconds\n",
            "\tXGBClassifier: 0.79587\n",
            "\t\tIteration duration: 106.63 seconds\n",
            "\n",
            "Validation Performance:\n",
            "\n",
            "\tDecisionTreeClassifier: 0.73285\n",
            "\t\tIteration duration: 2.14 seconds\n",
            "\tLogisticRegression: 0.45848\n",
            "\t\tIteration duration: 0.06 seconds\n",
            "\tRandomForestClassifier: 0.75812\n",
            "\t\tIteration duration: 15.56 seconds\n",
            "\tBaggingClassifier: 0.70758\n",
            "\t\tIteration duration: 12.70 seconds\n",
            "\tAdaBoostClassifier: 0.66426\n",
            "\t\tIteration duration: 5.23 seconds\n",
            "\tGradientBoostingClassifier: 0.72202\n",
            "\t\tIteration duration: 26.90 seconds\n",
            "\tXGBClassifier: 0.83755\n",
            "\t\tIteration duration: 11.58 seconds\n",
            "\n",
            "\u001b[2;37;42mDecisionTreeClassifier:                                                                               \u001b[0m\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 900x300 with 4 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[1mModel performance:\u001b[0m\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7fe22f51c340>"
            ],
            "text/html": [
              "<style type=\"text/css\">\n",
              "#T_9d456 th {\n",
              "  max-width: 75px;\n",
              "}\n",
              "</style>\n",
              "<table id=\"T_9d456\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th class=\"blank level0\" >&nbsp;</th>\n",
              "      <th id=\"T_9d456_level0_col0\" class=\"col_heading level0 col0\" >Accuracy</th>\n",
              "      <th id=\"T_9d456_level0_col1\" class=\"col_heading level0 col1\" >Precision</th>\n",
              "      <th id=\"T_9d456_level0_col2\" class=\"col_heading level0 col2\" >Recall</th>\n",
              "      <th id=\"T_9d456_level0_col3\" class=\"col_heading level0 col3\" >NPV</th>\n",
              "      <th id=\"T_9d456_level0_col4\" class=\"col_heading level0 col4\" >Specificity</th>\n",
              "      <th id=\"T_9d456_level0_col5\" class=\"col_heading level0 col5\" >F1</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th id=\"T_9d456_level0_row0\" class=\"row_heading level0 row0\" >Training</th>\n",
              "      <td id=\"T_9d456_row0_col0\" class=\"data row0 col0\" >100.00%</td>\n",
              "      <td id=\"T_9d456_row0_col1\" class=\"data row0 col1\" >100.00%</td>\n",
              "      <td id=\"T_9d456_row0_col2\" class=\"data row0 col2\" >100.00%</td>\n",
              "      <td id=\"T_9d456_row0_col3\" class=\"data row0 col3\" >100.00%</td>\n",
              "      <td id=\"T_9d456_row0_col4\" class=\"data row0 col4\" >100.00%</td>\n",
              "      <td id=\"T_9d456_row0_col5\" class=\"data row0 col5\" >100.00%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_9d456_level0_row1\" class=\"row_heading level0 row1\" >Validation</th>\n",
              "      <td id=\"T_9d456_row1_col0\" class=\"data row1 col0\" >96.92%</td>\n",
              "      <td id=\"T_9d456_row1_col1\" class=\"data row1 col1\" >71.73%</td>\n",
              "      <td id=\"T_9d456_row1_col2\" class=\"data row1 col2\" >73.29%</td>\n",
              "      <td id=\"T_9d456_row1_col3\" class=\"data row1 col3\" >98.43%</td>\n",
              "      <td id=\"T_9d456_row1_col4\" class=\"data row1 col4\" >98.31%</td>\n",
              "      <td id=\"T_9d456_row1_col5\" class=\"data row1 col5\" >72.50%</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "\u001b[2;37;42mLogisticRegression:                                                                                   \u001b[0m\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 900x300 with 4 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[1mModel performance:\u001b[0m\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7fe27b717130>"
            ],
            "text/html": [
              "<style type=\"text/css\">\n",
              "#T_98299 th {\n",
              "  max-width: 75px;\n",
              "}\n",
              "</style>\n",
              "<table id=\"T_98299\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th class=\"blank level0\" >&nbsp;</th>\n",
              "      <th id=\"T_98299_level0_col0\" class=\"col_heading level0 col0\" >Accuracy</th>\n",
              "      <th id=\"T_98299_level0_col1\" class=\"col_heading level0 col1\" >Precision</th>\n",
              "      <th id=\"T_98299_level0_col2\" class=\"col_heading level0 col2\" >Recall</th>\n",
              "      <th id=\"T_98299_level0_col3\" class=\"col_heading level0 col3\" >NPV</th>\n",
              "      <th id=\"T_98299_level0_col4\" class=\"col_heading level0 col4\" >Specificity</th>\n",
              "      <th id=\"T_98299_level0_col5\" class=\"col_heading level0 col5\" >F1</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th id=\"T_98299_level0_row0\" class=\"row_heading level0 row0\" >Training</th>\n",
              "      <td id=\"T_98299_row0_col0\" class=\"data row0 col0\" >96.65%</td>\n",
              "      <td id=\"T_98299_row0_col1\" class=\"data row0 col1\" >84.23%</td>\n",
              "      <td id=\"T_98299_row0_col2\" class=\"data row0 col2\" >48.74%</td>\n",
              "      <td id=\"T_98299_row0_col3\" class=\"data row0 col3\" >97.06%</td>\n",
              "      <td id=\"T_98299_row0_col4\" class=\"data row0 col4\" >99.46%</td>\n",
              "      <td id=\"T_98299_row0_col5\" class=\"data row0 col5\" >61.75%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_98299_level0_row1\" class=\"row_heading level0 row1\" >Validation</th>\n",
              "      <td id=\"T_98299_row1_col0\" class=\"data row1 col0\" >96.66%</td>\n",
              "      <td id=\"T_98299_row1_col1\" class=\"data row1 col1\" >88.19%</td>\n",
              "      <td id=\"T_98299_row1_col2\" class=\"data row1 col2\" >45.85%</td>\n",
              "      <td id=\"T_98299_row1_col3\" class=\"data row1 col3\" >96.91%</td>\n",
              "      <td id=\"T_98299_row1_col4\" class=\"data row1 col4\" >99.64%</td>\n",
              "      <td id=\"T_98299_row1_col5\" class=\"data row1 col5\" >60.33%</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "\u001b[2;37;42mRandomForestClassifier:                                                                               \u001b[0m\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 900x300 with 4 Axes>"
            ],
            "image/png": 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b8tWbGBkZsXHjRp4+fUrNmjXp3bs33333nVZMq1atGDZsGAMHDqRKlSocPnyYcePGacW0a9eOpk2b0qhRIwoWLJjhMKWWlpbs3LmT2NhYatSoQfv27WncuDELFy7U7YfxH1999RXjxo1j5MiRuLq6cv36dfr3768V89NPP/Hw4UOqVatGt27dGDx4MA4ODloxs2bNIjg4mCJFilC1alXgzd8jdnZ2bNiwgc8++4xy5cqxdOlSfvnlFypUqADA5MmTGTduHAEBAZQrV46mTZuydetWzffBRx99xMSJExk1ahSOjo4MHDjwnX4WQgColJx46FqIbJCWlka5cuXo0KEDkydPzu3mCCGEEEJ8MORxIPHBuH79Ort27aJhw4YkJSWxcOFCrl69SufOnXO7aUIIIYQQHxR5HEh8MIyMjAgMDKRGjRrUrVuXM2fO8Ndff2mesRdCCCGEEJkjjwMJIYQQQghhYKQnQAghhBBCCAMjRYAQQgghhBAGRooAIYQQQgghDIwUAUIIkc0OHDhAy5YtcXZ2RqVSsWnTplfG9uvXD5VKxdy5c7XWx8bG0qVLF2xsbLCzs8Pb25uEhAStmNOnT1O/fn3Mzc0pUqQI06dPT3f89evXU7ZsWczNzalUqRLbtm3LiksUQgjxgdHLIUKT71/J7SaIXGLhXD+3myByScrz2++0vy55w6RAiTcHvSQxMZHKlSvTq1cv2rZt+8q4jRs3cuTIEa1Jnl7o0qULd+/eJTg4mOTkZHr27Enfvn1Zu3YtAPHx8TRp0gR3d3eWLl3KmTNn6NWrF3Z2dvTt2xeAw4cP06lTJwICAmjRogVr166lTZs2nDhxgooVK+p0Te8TyfmGS3K+YcrJfA+65/wPhV6ODiRfCIZLvhAM1zt/KcRczHRsmm1RkpKStNaZmZlhZmb2xn1VKhUbN25MN1vr7du3qVWrFjt37sTT05OhQ4cydOhQACIiIihfvjzHjh2jevXqAOzYsYPmzZtz69YtnJ2dWbJkCWPGjCEqKgpTU1MARo0axaZNm7hw4QKgnjE1MTGRoKAgzXlr165NlSpVWLp0aaav/30jOd9wSc43TDmZ7wFMHEq/0/neV/I4kBBCAKSmZHoJCAjA1tZWawkICHjrU6elpdGtWzdGjBhBhQoV0m0PCQnBzs5OUwAAuLu7Y2RkRGhoqCamQYMGmgIAwMPDg8jISB4+fKiJcXd31zq2h4cHISEhb912IYT44OiQ70lNye3WZhu9fBxICCF0pShpmY4dPXo0vr6+Wusy0wvwKtOmTcPY2JjBgwdnuD0qKgoHBwetdcbGxtjb2xMVFaWJcXFx0YpxdHTUbMuXLx9RUVGadS/HvDiGEEIYAl3yvT6TIkAIIQDSMv+lkNlHfzIjLCyMefPmceLECVQqVZYcUwghxGvokO/1mTwOJIQQAEpa5pcs9PfffxMTE0PRokUxNjbG2NiY69ev880331C8eHEAnJyciImJ0dovJSWF2NhYnJycNDHR0dFaMS8+vynmxXYhhDAIuuR7Pe41kCJACCEA0lIzv2Shbt26cfr0acLDwzWLs7MzI0aMYOfOnQC4ubkRFxdHWFiYZr89e/aQlpZGrVq1NDEHDhwgOTlZExMcHEyZMmXIly+fJmb37t1a5w8ODsbNzS1Lr0kIId5ruuT7LM757xN5HEgIISBb7/YkJCRw6dIlzeerV68SHh6Ovb09RYsWJX/+/FrxJiYmODk5UaZMGQDKlStH06ZN6dOnD0uXLiU5OZmBAwfSsWNHzXCinTt3ZuLEiXh7e+Pn58fZs2eZN28ec+bM0Rx3yJAhNGzYkFmzZuHp6cmvv/7K8ePHWbZsWbZduxBCvHf0+O6+LqQnQAghQP2MaGYXHR0/fpyqVatStWpVAHx9falatSr+/v6ZPsaaNWsoW7YsjRs3pnnz5tSrV0/rj3dbW1t27drF1atXcXV15ZtvvsHf318zRwBAnTp1WLt2LcuWLaNy5cr8/vvvbNq06YOeI0AIIXSmS77X4/cHZJ4AoVdkzGjD9a7jRiddPpLpWLOStd/pXCJrSc43XJLzDVNO5nvQ35wvjwMJIQTo9d0eIYQQL5F8D0gRIIQQaqnJb44RQgjx4ZN8D0gRIIQQavKimBBCGAbJ94AUAUIIoSbdw0IIYRgk3wNSBAghhJrcGRJCCMMg+R6QIkAIIdTkzpAQQhgGyfeAFAFCCAGAoujvrJBCCCH+JfleTYoAIYQA6R4WQghDIfkekCJACCHUpHtYCCEMg+R7QIoAIYRQkztDQghhGCTfA1IECCGEmkweI4QQhkHyPSBFgBBCqEn3sBBCGAbJ94AUAUIIoSbdw0IIYRgk3wNSBAghhJrcGRJCCMMg+R6QIkAIIdTkS0EIIQyD5HtAigAhhABk8hghhDAUku/VpAgQQgiQO0NCCGEoJN8DUgQIIYSavCgmhBCGQfI9IEWAEEKoyZ0hIYQwDJLvASkChBBCLTUlt1sghBAiJ0i+B6QIEEIINekeFkIIwyD5HgCj3G6AEEK8F9LSMr/o6MCBA7Rs2RJnZ2dUKhWbNm3SbEtOTsbPz49KlSphZWWFs7Mz3bt3586dO1rHiI2NpUuXLtjY2GBnZ4e3tzcJCQlaMadPn6Z+/fqYm5tTpEgRpk+fnq4t69evp2zZspibm1OpUiW2bdum8/UIIcQHTZd8/w6PDk2dOhWVSsXQoUM16549e4aPjw/58+cnb968tGvXjujoaK39bty4gaenJ5aWljg4ODBixAhSUrR7L/bt20e1atUwMzOjVKlSBAYG6tw+KQKEEAKy9QshMTGRypUrs2jRonTbnjx5wokTJxg3bhwnTpxgw4YNREZG0qpVK624Ll26cO7cOYKDgwkKCuLAgQP07dtXsz0+Pp4mTZpQrFgxwsLCmDFjBhMmTGDZsmWamMOHD9OpUye8vb05efIkbdq0oU2bNpw9e1bnaxJCiA9WDhQBx44d44cffuCTTz7RWj9s2DC2bNnC+vXr2b9/P3fu3KFt27aa7ampqXh6evL8+XMOHz7MqlWrCAwMxN/fXxNz9epVPD09adSoEeHh4QwdOpTevXuzc+dOndqoUhRFeaure48l37+S200QucTCuX5uN0HkkpTnt99p/6dBszMda9HC963Po1Kp2LhxI23atHllzLFjx6hZsybXr1+naNGiREREUL58eY4dO0b16tUB2LFjB82bN+fWrVs4OzuzZMkSxowZQ1RUFKampgCMGjWKTZs2ceHCBQC++uorEhMTCQoK0pyrdu3aVKlShaVLl771NeU2yfmGS3K+YcrJfA+65/yEhASqVavG4sWLmTJlClWqVGHu3Lk8evSIggULsnbtWtq3bw/AhQsXKFeuHCEhIdSuXZvt27fTokUL7ty5g6OjIwBLly7Fz8+Pe/fuYWpqip+fH1u3btW6gdOxY0fi4uLYsWNHptspPQFCCAE63RVKSkoiPj5ea0lKSsqypjx69AiVSoWdnR0AISEh2NnZaQoAAHd3d4yMjAgNDdXENGjQQFMAAHh4eBAZGcnDhw81Me7u7lrn8vDwICQkJMvaLoQQ7z0dewJ0zfk+Pj54enqmy7dhYWEkJydrrS9btixFixbV5OGQkBAqVaqkKQBAnafj4+M5d+6cJiYrcrkUAUIIAeoXxTK5BAQEYGtrq7UEBARkSTOePXuGn58fnTp1wsbGBoCoqCgcHBy04oyNjbG3tycqKkoT8/KXBqD5/KaYF9uFEMIg6JDvdc35v/76KydOnMhw+4ue2hc3eF54OQ+/Sy6Pj4/n6dOnmf4xyOhAQggBOj33OXr0aHx9tbuHzczM3rkJycnJdOjQAUVRWLJkyTsfTwghRAZ0fM4/szn/5s2bDBkyhODgYMzNzd+piTlBigAhhACdhowzMzPLkj/6X/aiALh+/Tp79uzR9AIAODk5ERMToxWfkpJCbGwsTk5Ompj/jjDx4vObYl5sF0IIg6DjEKGZzflhYWHExMRQrVo1zbrU1FQOHDjAwoUL2blzJ8+fPycuLk6rN+DlPOzk5MTRo0e1jpvZXG5jY4OFhUWmr0seBxJCCMiR4eJe5UUBcPHiRf766y/y58+vtd3NzY24uDjCwsI06/bs2UNaWhq1atXSxBw4cIDk5GRNTHBwMGXKlCFfvnyamN27d2sdOzg4GDc3tyy/JiGEeG9l0+hAjRs35syZM4SHh2uW6tWr06VLF83/NzEx0crDkZGR3LhxQ5OH3dzcOHPmjNaNn+DgYGxsbChfvrwmJityufQECCEEQGpqth06ISGBS5cuaT5fvXqV8PBw7O3tKVSoEO3bt+fEiRMEBQWRmpqqee7T3t4eU1NTypUrR9OmTenTpw9Lly4lOTmZgQMH0rFjR5ydnQHo3LkzEydOxNvbGz8/P86ePcu8efOYM2eO5rxDhgyhYcOGzJo1C09PT3799VeOHz+uNYyoEELovWzK99bW1lSsWFFrnZWVFfnz59es9/b2xtfXF3t7e2xsbBg0aBBubm7Url0bgCZNmlC+fHm6devG9OnTiYqKYuzYsfj4+Gh6I/r168fChQsZOXIkvXr1Ys+ePaxbt46tW7fq1F4pAoQQArLlDv8Lx48fp1GjRprPL54t9fLyYsKECWzevBmAKlWqaO23d+9ePv30UwDWrFnDwIEDady4MUZGRrRr14758+drYm1tbdm1axc+Pj64urpSoEAB/P39teYSqFOnDmvXrmXs2LF8++23lC5dmk2bNqX70hJCCL2Wjfn+TebMmaPJ4UlJSXh4eLB48WLN9jx58hAUFET//v1xc3PDysoKLy8vJk2apIlxcXFh69atDBs2jHnz5lG4cGGWL1+Oh4eHTm2ReQKEXpExow3XO48bvWZcpmMtukx+p3OJrCU533BJzjdMOZnvQX9zvvQECCEE6PyimBBCiA+U5HtAigAhhFDLxe5hIYQQOUjyPSCjA+Wa4+Fn8Bk5nkatulCxbjN2Hzj8ytiJ0xdQsW4zfv5tY5Yc8/K1GwwcOYHaTdpRo3EbvvIezN0o9Vvot+9GU7FuswyXnXv+fvsLFtmqfz8vLv1zhIT4yxw+uIUa1avkdpM+PIqS+UWILLT853VUrNuMqXOXvjKmx8CRGebl/sP9AUhOSWH24p/4olt/ajRuQ6NWXRg9eSYx9x5oHedR/GP8Jkyj1udtcfNoz7iAOTx5kvnJhUTu+rpvd06EBRN7/wKx9y9w8MBmmno0evOOQpsu+V6Pc770BOSSp0+fUaZUCb7wbMLQb6e8Mu6v/Yc4fe4CDgXyvzJGl2PeuHWH7v2H07aFBz69u2JlacnlqzcwNTMFwMmhAPs2r9HaZ/2f21m59g/q166uwxWKnPLll62YOWM8A3xGcfTYSQYP6s22rWsoX7EB9/7zB4B4DbkzJHLBmYhI1v+5jY9Lubw2bt7347SGf4179Jh2PQbg0Uj9TPyzZ0mcj7zM1z06UaZUCeIfP2bqvB8Y6DeRdSv+fYHcb+J07t2P5ce535OSksLY7+cwYfp8pk/wy54LFFnq9u27jBkTwMVLV1GpVHTv9iUb/lhB9ZoenD//T24378Mh+R6QIiDX1HerQX23Gq+Nib53n4A5S/hh9ncMGOGfJcecv2wV9d1q8I2Pt2Zd0cLOmv+fJ08eCuS319pn94HDeDSuj6Vl5iegEDln2JA+LP9pLatWrwNggM8omjdrTM8eHZk+Y1Eut+4DIl8KIoc9efKUURNnMMFvCD+s+uW1sbY21lqft/+1H3MzM5p8pi4CrPNasXze91ox3/r2p1PvodyNiqGQkwOXr93g4JHj/Lp8HhXLfayOGdaf/sP9Ge7TG4eCb77ZJHJX0NZgrc/j/Kfxdd9u1KpZTYoAXUi+B+RxoPdWWloaoyfNpEfn9pQqUSzLjnng8DGKF/mIvsPG0MCzI536DH3to0jnLlzkwsUrtG2h27BTImeYmJhQrdon7H7pUS1FUdi95yC1a7vmYss+QEpa5hchssCUWYto4FYDtxpVdd53Q9Aumrk3xNLC/JUxCQlPUKlUWFtbAXDqbAQ21nk1BQBA7epVMTJScfr8Bd0vQOQqIyMjOnRohZWVJUdCw968g/iXLvlej3O+FAHvqZ/+t548eYzo+mXrLDtm7MM4njx9yk//W0e9WtVZNuc7Gjeow9Bvp3Ds5OkM99kQtJMSxYtQtVL5LGuHyDoFCthjbGxMTPR9rfUxMfdwciyYS636MCkpqZlehHhX2/7aR8Q/lxnar6fO+545H8nFK9do17LpK2OSkp4zZ8kKmrs3JK+Vugi4/+Ah9na2WnHGxnmwtbbmfuxDndshckfFimWJi/2HJwlXWbxwKu2/7E1ExMXcbtYHRZd8r885Xx4Heg+du3CR/63/k/UrFqBSqbLsuGlp6pdbGtV3o3vHLwAo+3FJws+cZ92mbdSo+olW/LOkJLYF7+PrHp2yrA1CvLf0+G6PeL/cjb7H1Lk/8OPc7zH7//exdLEhaCelSxanUvkyGW5PTknhm3HfoygK40YMfNfmivdMZORlXGs0wdbGmnbtPFnx01w+c28nhYAuJN8DUgS8l06cOkvswzg+b9ddsy41NY0ZC5fz87pN7Ppj1VsdN5+dDcZ58lCyeFGt9SWKF+HE6fPp4nftPcjTZ0m0atr4rc4nst/9+7GkpKTg4FhAa72DQ0Giou/lUqs+UGn6OwKEeL+cj7xI7MM4OvT69w/01NQ0wsLP8suGLZzYu5k8efJkuO+Tp8/Y/td+fHp3y3D7iwLgTnQMK+ZP1fQCABTIn4/YuEda8SkpqTx6/JgC9vmy4MpETkhOTuby5WsAnDh5huquVRg0sDcDfOTl7kyTfA9IEfBeatm0MbX/84zo18PG0rLpZ7Rp3uStj2tiYkKFch9z9cYtrfXXbt7G2ckhXfyGoJ00qlcL+3x2b31Okb2Sk5M5ceI0nzWqx+bNOwFQqVR81qgei5eszOXWfWDkRTGRQ2q7VmHjz0u01o39bjYuxYrg3fXLVxYAALv2/M3z5GRaenyWbtuLAuDGzTusWDAVO1sbre2VK5Yj/nEC5y5cpELZ0gCEhoWTlqbwSfmyWXBlIjcYGRm9VY+SQZN8D0gRkGuePHnKjVt3NJ9v34nmwj+XsbWxppCTQ7rkbWychwL2+XApVvitjwnQs3M7hvtPpXqVitSsVpmDR46z/1AoKxdM0zrWjVt3CAs/y5KZk7LickU2mjPvR1b+NIewE6c5duwkgwf1wcrKgsBVv+V20z4s8qUgcoiVlSWlSxTXWmdhYY6djXW69f+1IWgnn9V3S/cdkZySgu+Y7zj/zyUWTZ9IWloa9x/EAuqRhUxMTChZvCj1aldnwrR5+I8YRHJKCt/PWUIz94YyMtAH4rspo9ixYy83bt7G2jovnTq2oWFDN5p7ds7tpn1YJN8DUgTkmrMXLtJr0L9dd9MXLAOgdTN3vhv7TaaO0WPgSD5yctTEZ+aY7g3r4j9iIMt/XkfAnKUUL1qYOd+NpVrlilrH3hC0C0eHAtSpWe3tL1LkiPXrN1OwgD0T/Ifj5FSQU6fO4dmiKzEx99+8s/iXHk8IIz48Y6bM4nZUNIELp2vWXb1+ixOnz7Fsznfp4mPuPWDvwSMAtO/ho7VtxYJp1Kymfudr2viRfDd7Md6DR2NkpML907p8O7R/Nl6JyEoFCxZg5Yp5FCrkwKNHjzlzJoLmnp35a7dM5qkTyfcAqBRF/34Syfev5HYTcsTnbb3w8e5KG8/Pc7sp7w0L5/q53QSRS1Ke336n/Z/M7pPpWEvfH9/pXCJr6WPO7+EzghrVKuPj3TW3m/Jek5xvmHIy34P+5vxc7Qm4f/8+K1asICQkhKioKACcnJyoU6cOPXr0oGBBGeLwVS5duU7evJa0aiYv7QqRJeRFsWwnOT9zHickcvP2XRbPkMcxhcgWku+BXOwJOHbsGB4eHlhaWuLu7o6joyMA0dHR7N69mydPnrBz506qV6/+2uMkJSWRlJSktc7o8W3MzMyyre3i/SV3hQzXO98ZmtEr07GWI1a807kMkeR8kR0k5xumnMz3oL85P9d6AgYNGsSXX37J0qVL042FrygK/fr1Y9CgQYSEhLz2OAEBAUycOFFr3dgRg/EfOSTL2yyE0F/6PCHM+0ByvhDifSH5Xi3XegIsLCw4efIkZctmPCzZhQsXqFq1Kk+fPn3tceSukHiZ3BUyXO96Zyjxu+5vDvp/VmNWv9O5DJHkfJEdJOcbppzM96C/OT/XegKcnJw4evToK78Qjh49qukufh0zM7N0yT/5uYyKIoTQkcwgma0k5wsh3huS7wEwyq0TDx8+nL59+zJkyBA2b95MaGgooaGhbN68mSFDhtCvXz9GjhyZW83LNomJT5g6dymft/XCtVFrunzty5mIyAxjJ05fQMW6zfj5t42ZPv7yn9dRsW4zps5dqrW+x8CRVKzbTGuZOH2BZvuj+Mf4jBxPDfcvaN/Dh4h/LmntP2XWIgJ/+UOHKxWZ1b+fF5f+OUJC/GUOH9xCjepVXhvfrl0Lzp7ZT0L8ZU6e+ItmTdNPGjRh/HBuXj/B40eX2Ln9V0qVctFsMzU1JXDlfGLvX+D8ub9p/Jn2nbRvfPsxd87kLLm2D0qakvlF6Exyfs7m/KSk50yZtYi6zTpQw/0Lhn47hfuxDzXbJefnjuzI92XLlmLjhpU8uBfBo4cXCTm8lSJFnDXbZ04fT0zUWa5ePkanTl+kO/6mjYFZcWkfFl3yvR7n/FwrAnx8fFi1ahWhoaG0a9cONzc33NzcaNeuHaGhoQQGBjJgwIDcal628Z86j5BjJwnwH87Gn5dQp2Y1+gz5luh72ney/tp/iNPnLuBQIPMTuJyJiGT9n9v4+KU/+F7WvlVT9m1eo1m+8fn3xZhlq34l8clT1q9YQI2qnzB+6nzNtlNnIzh9LpJuHdrodrHijb78shUzZ4xn8pTZ1KjVlFOnz7Nt6xoKvmLiHrfa1Vnz8yJWrvyF6jU92Lx5J3/8/hMVKpTRxIwYPoCBPr0YMHAUdeq1JPHJE7YFrdHcPe3TuwvVqlWiXoNWLF/+P35evVCzb/HiRfD27sI4/2npzq330tIyvwidSc7P2Zw/bf4P7DsUyuwp3xK4cDr37j9g6LdTNNsl5+e87Mj3JUoUY//eTURGXqLx5+2p6urOd9/P5dkz9SNzLTw/p2PHNjRr3plR305h2dIZ5M+fDwAbG2smT/Jj0OBvs//i3ze65Hs9zvm5VgQAfPXVVxw5coQnT55w+/Ztbt++zZMnTzhy5AgdOnTIzaZli2dJSfy1/yC+Pt5Ur1KJooWd8fHuStHCzvy2casmLvrefQLmLGHa+JEYG796+viXPXnylFETZzDBbwg21nkzjDE3M6NAfnvNktfKSrPtyrUbNGvckOJFC9O+dTOuXr8BqGehnDRjIf4jBr52KnvxdoYN6cPyn9ayavU6IiIuMsBnFE+ePKVnj44Zxg8a5M3OnfuYNXspFy5cYvyEGZw8eZYB/XtqYgYP6s33AfPYsmUXZ85E0KPnEJydHWnd2gOAsmVLExS0i/Pn/2HxklU4OBSgQAF7ABYtCGD0t9/x+HFC9l/8+0buCmU7yfk5k/MfJySyIWgXIwf1oZZrFSqULc3kMb6EnznPqbMRgOT83JAd+X7yJD+279jDqNHfER5+jitXrhMUFMy9ew8AdS/B/gMhhJ04zW+//Ul8fAIuxYsCMDVgLD/8sJqbN+9k/8W/b6QnAMjlIuAFExMTChUqRKFChTAxMcnt5mSb1JRUUlPTMDPVvkYzM1NOnD4HQFpaGqMnzaRH5/aUKlEs08eeMmsRDdxq4Faj6itjtgbvpV7zr2jTtR9zlqzk6bNnmm0flyrB0ROnSElJ5XBoGB+XVN9ZWrFmPTWqVqJiuY91uVSRCSYmJlSr9gm79/w706OiKOzec5DatV0z3Kd2LVeteIBdwfs08S4uRSlUyJHdew5qtsfHP+bo0ZPUrqWOOX36PHXr1MTc3JwmTRpy504U9+/H0qnTFzxLSuLPP3dk9aV+GJS0zC/inUjOz96cfz7yIikpKdSu/u+2EsWKUMjRgVNnLwCS83NaduR7lUpF82aNuXjxCtuC1nDn1ikOH9xCq1YemvjTp8/jWu0T7OxsqVa1EhYW5ly6fI26dWpQtWpFFiz8KRuu9gOgS77X45z/XhQBhsLKypLKFcuxNPAXYu49IDU1lS0793Dq7AXu348F4Kf/rSdPHiO6ftk608fd9tc+Iv65zNB+PV8Z4/n5p0z1H8mKBVPp3a0DQTt3M2riDM323t06kCdPHpp16MXuA4eZNHoo12/eZvP23fTr2ZmJ0xfQ9MuefDPuex4nJL79D0FoFChgj7GxMTHR2o8FxMTcw8kx40mTnJwKEh1zT2tddPR9TbyTo8P/r/tPTMx9nJzU21YG/sqp0+c5c2ovo0cNplPnfuTLZ8cE/+EMGTqOSRNHcuH8QbYFrcHZ2SlLrvWDkI13hQ4cOEDLli1xdnZGpVKxadMmre2KouDv70+hQoWwsLDA3d2dixcvasXExsbSpUsXbGxssLOzw9vbm4QE7R6b06dPU79+fczNzSlSpAjTp09P15b169dTtmxZzM3NqVSpEtu2bdP5ekTm5FbOv//gISYmxul6CPLb23E/Vn1eyfk5KzvyvYNDAayt8zJyhA87d+2jmWdnNv25g9/XLadB/doA7Arez9pfNnDk8FZ++mkOPb2Hkpj4hIULA/DxGUW/r7tz7uwBDuzbRPnyBlT4SU8AIEVAjgsYNxwUhc/adKVao1asWf8nzdwbojIy4tyFi/xv/Z98N+abdONov8rd6HtMnfsDU8ePxMzM9JVxX7ZuTt1arnxc0oUWHp/x/bjh7D5wmBu31N2A1nmtmD7Bj+ANqwhcNIOSLsWYOH0B3/h4E7RrL7fu3GXLLz9ibmbG0pVrs+RnIXJHSkoKg4eMoXQZN9zqeHLo8DFmTPdn4aIVVKlSgVatPKhW/XNCj55g7hzDmbFUSUvL9KKrxMREKleuzKJFizLcPn36dObPn8/SpUsJDQ3FysoKDw8Pnr3UW9elSxfOnTtHcHAwQUFBHDhwgL59+2q2x8fH06RJE4oVK0ZYWBgzZsxgwoQJLFu2TBNz+PBhOnXqhLe3NydPnqRNmza0adOGs2fP6nxNInNyK+e/ieT8D5+RkfpPuM1bdjJv/o+cOnWO6TMWsXXbX/Tt200TN2nybMqWr0fVau78+ecORvkNZM/ugySnpPDt6CE0/LQNP61Yy8oV83LrUnKcLvn+bXL+hyLXhgg1VEULOxO4aAZPnj4jMfEJBQvY8824AAo7O3Hi1FliH8bxebt/x69NTU1jxsLl/LxuE7v+WJXueOcjLxL7MI4OvQZq7RMWfpZfNmzhxN7NGT7XWam8epi+m7fvUrSwc7rtG7fuwjqvFZ/Vd2PI6Mk0blAHE2NjmnxWn0XLf86KH4XBu38/lpSUFBwcC2itd3AoSNR/7uS/EBV1D0cH7btGjo4FNPFR0TH/v64gUVEx/8Y4FCD81LkMj/lpwzpUKP8xfb8ezvSp49ixYw9Pnjxl/e9btJ491Xsp2ZfomzVrRrNmzTLcpigKc+fOZezYsbRurb4bvHr1ahwdHdm0aRMdO3YkIiKCHTt2cOzYMc2MugsWLKB58+bMnDkTZ2dn1qxZw/Pnz1mxYgWmpqZUqFCB8PBwZs+erSkW5s2bR9OmTRkxYgQAkydPJjg4mIULF7J06dIM2yfeTW7k/AL585GcnEL84wSt3oAHsXEUsLfPsJ2S87NXduT7+/djSU5OJiJCu9fwwoWL1K1TM8NjlilTks6d2lG9ZhN69ujI3wdDuX8/lvW/b+Gn5XPIm9eKBEPo+cnGfP8hkSIgl1hamGNpYc6j+MccPhqG74BefP5pPWr/5/nOr4eNpWXTz2jTvEmGx6ntWoWNPy/RWjf2u9m4FCuCd9cvX/li14WLlwEokD/9F0LswziWrlzL6iUzAfUzq8kpKYD6LnJqqvzjyQrJycmcOHGazxrVY/PmnYD6Gc/PGtVj8ZKVGe5zJDSMzz6rx/wFyzXr3Bs34MiRMACuXr3B3bvRfNaoHqf+/49+a+u81KxZlaXL0k92YmZmxvz539HdayBpaWkY5THCRKV+ftnExIQ8eQyos1CH5z4zmrAqo/HrM+Pq1atERUXh7u6uWWdra0utWrUICQmhY8eOhISEYGdnpykAANzd3TEyMiI0NJQvvviCkJAQGjRogKnpv3eHPTw8mDZtGg8fPiRfvnyEhITg6+urdX4PD490jyeJrJeTOb98mdIYGxsTejyczxvVA+Dq9VvcjY6hcsX08zRIzs9+2ZHvk5OTOX78FB9/XFJrv9KlS3D9xq0Mj7lk0TRGjJxIYuIT8uTJg4mJ+s/AF+/mGMzL4Hr8nL8upAjIYYdCw1AUheJFC3Pj1h1mLfoJl6KFaePZBBNjY+xsbbTijY3zUMA+Hy7FCmvWeQ8eReMGdejcvhVWVpaULlFcax8LC3PsbKw162/cusO24H3Ud6uBna0N/1y6yrT5P1C9SkXKZDS03Lwf8OrYFseC6jsWVT8pz5Yde6hTsxq//7mdqp+Uz9ofigGbM+9HVv40h7ATpzl27CSDB/XBysqCwFW/AbByxTzu3LnLmLFTAViw4Cf27P6dYUO/Ztv2v/iqQ2tcXT+h34B/x1efv2A5344ezMVLV7h27SYTJ4zgzp1o/vxzZ7rzjx0zlB3b9xAeri4YDoccZ1rAWAJX/8aA/j04fPh4DvwU3hM6PPcZEBDAxIkTtdaNHz+eCRMm6HzaqKgogHQTZTk6Omq2RUVF4eDgoLXd2NgYe3t7rRgXF5d0x3ixLV++fERFRb32PCLr5UbOt85rRdsWTZi+4EdsbayxsrLk+zlLqFyxHJUrlkvXRsn5OSM78v3M2Uv4Zc0S/v77CPv2H8ajyae08Pycxu7t053fu1dn7t2PJWhrMACHDx/Df5wvtWpWo2nTRpw7H8mjR/E58JN4D+jxc/66kCIghz1OSGTu0pVE37uPrY01nzesx+CvvTAxzvyv4ubtuzzU4R+qiYkJR46f5Od1m3j67BlODgX5/NN6fJ3BsGSHQsO4cfsuAf4jNOs6tWvJuQsX6dxnKJXKl6F/ry6ZPrd4vfXrN1OwgD0T/Ifj5FSQU6fO4dmiKzEx6pfHihZxJu2l5xFDjhyna/eBTJo4kimT/bh46Srt2ntz7ty/kw/NmLkYKytLli6ejp2dDYcOHcOzZdd0d64rVChD+3Ytca3xuWbdH38E0bCBG/v2bOCffy7TtftADIWiw5fC6NGj091Rf5teAKH/ciPnA/gN/hojIyOGjplCcnIydWq6Mm64T7o4yfk5Jzvy/Z9/7mCAzyj8Rg5i7pxJRP5zhS+/6sOhw8e0zu3gUIDRowZTv+G/L6AfOx7OnLk/sPnP1cTcu0+vXkOz9wfwHtEl3+szlaIoeveTSL5/JbebIHKJhXP9NwcJvZTy/PY77f94cItMx1rPD3rr86hUKjZu3EibNm0AuHLlCiVLluTkyZNUqVJFE9ewYUOqVKnCvHnzWLFiBd988w0PH/4742tKSgrm5uasX7+eL774gu7duxMfH6/1aM/evXv57LPPiI2NJV++fBQtWhRfX1+GDh2qiRk/fjybNm3i1KlTb31NuU1yvuGSnG+YcjLfw7vl/PeZAT3wK4QQr5FLs0e6uLjg5OTE7t27Nevi4+MJDQ3Fzc0NADc3N+Li4ggLC9PE7Nmzh7S0NGrVqqWJOXDgAMnJyZqY4OBgypQpQ758+TQxL5/nRcyL8wghhEGQGYMBKQKEEEItG8eMTkhIIDw8nPDwcED9MnB4eDg3btxApVIxdOhQpkyZwubNmzlz5gzdu3fH2dlZ01tQrlw5mjZtSp8+fTh69CiHDh1i4MCBdOzYEWdn9ehenTt3xtTUFG9vb86dO8dvv/3GvHnztB5bGjJkCDt27GDWrFlcuHCBCRMmcPz4cQYONJzHvoQQQuYJUJN3AoQQArI10R8/fpxGjRppPr/4w9zLy4vAwEBGjhxJYmIiffv2JS4ujnr16rFjxw7Mzc01+6xZs4aBAwfSuHFjjIyMaNeuHfPnz9dst7W1ZdeuXfj4+ODq6kqBAgXw9/fXmkugTp06rF27lrFjx/Ltt99SunRpNm3aRMWKFbPt2oUQ4r2jx3/Y60LeCRB6RZ4PNVzv+oxo/NcemY61+SH9SEsi90jON1yS8w1TTuZ70N+cLz0BQggBcmdICCEMheR7QIoAIYQAQJEZJIUQwiBIvleTIkAIIUDuDAkhhKGQfA9IESCEEGpyY0gIIQyD5HtAigAhhABkBkkhhDAUku/VZJ4AIYQAGTNaCCEMRTbOE7BkyRI++eQTbGxssLGxwc3Nje3bt2u2P3v2DB8fH/Lnz0/evHlp164d0dHRWse4ceMGnp6eWFpa4uDgwIgRI0hJSdGK2bdvH9WqVcPMzIxSpUoRGBio849BigAhhAB193BmFyGEEB8uXfK9jjm/cOHCTJ06lbCwMI4fP85nn31G69atOXfuHADDhg1jy5YtrF+/nv3793Pnzh3atm2r2T81NRVPT0+eP3/O4cOHWbVqFYGBgfj7+2tirl69iqenJ40aNSI8PJyhQ4fSu3dvdu7UbShTmSdA6BUZM9pwveu40Q+//DTTsfnW73unc4msJTnfcEnON0w5me/h3XO+vb09M2bMoH379hQsWJC1a9fSvn17AC5cuEC5cuUICQmhdu3abN++nRYtWnDnzh0cHR0BWLp0KX5+fty7dw9TU1P8/PzYunUrZ8+e1ZyjY8eOxMXFsWPHjky3S3oChBACpCdACCEMhY49AUlJScTHx2stSUlJbzxNamoqv/76K4mJibi5uREWFkZycjLu7u6amLJly1K0aFFCQkIACAkJoVKlSpoCAMDDw4P4+HhNb0JISIjWMV7EvDhGZmXqxeDNmzdn+oCtWrXSqQFCCPE+kBfF1CTfCyH0na75PiAggIkTJ2qtGz9+PBMmTMgw/syZM7i5ufHs2TPy5s3Lxo0bKV++POHh4ZiammJnZ6cV7+joSFRUFABRUVFaBcCL7S+2vS4mPj6ep0+fYmFhkanrylQR0KZNm0wdTKVSkZqamqlYIYR4nygpb44xBJLvhRD6Ttd8P3r0aHx9fbXWmZmZvTK+TJkyhIeH8+jRI37//Xe8vLzYv3//2zQ1W2WqCEhLk/5vIYSekzQHSL4XQhgAHdOcmZnZa//o/y9TU1NKlSoFgKurK8eOHWPevHl89dVXPH/+nLi4OK3egOjoaJycnABwcnLi6NGjWsd7MXrQyzH/HVEoOjoaGxubTPcCwDu+E/Ds2bN32V0IId4bSlrmF0Mk+V4IoS90yfdZkfPT0tJISkrC1dUVExMTdu/erdkWGRnJjRs3cHNzA8DNzY0zZ84QExOjiQkODsbGxoby5ctrYl4+xouYF8fILJ2LgNTUVCZPnsxHH31E3rx5uXJFPSrDuHHj+Omnn3Q9nBBCvB/kxeB0JN8LIfRSNg4ROnr0aA4cOMC1a9c4c+YMo0ePZt++fXTp0gVbW1u8vb3x9fVl7969hIWF0bNnT9zc3KhduzYATZo0oXz58nTr1o1Tp06xc+dOxo4di4+Pj6Y3ol+/fly5coWRI0dy4cIFFi9ezLp16xg2bJhObdW5CPjuu+8IDAxk+vTpmJqaatZXrFiR5cuX63o4IYR4L0hPQHqS74UQ+ig7ewJiYmLo3r07ZcqUoXHjxhw7doydO3fy+eefAzBnzhxatGhBu3btaNCgAU5OTmzYsEGzf548eQgKCiJPnjy4ubnRtWtXunfvzqRJkzQxLi4ubN26leDgYCpXrsysWbNYvnw5Hh4eOrVV53kCSpUqxQ8//EDjxo2xtrbm1KlTlChRggsXLuDm5sbDhw91akB2kDGjDZeMGW243nXc6JjGDTMd67D7/XvBKzt8CPkeJOcbMsn5hikn8z3ob87P1IvBL7t9+7bmZYeXpaWlkZycnCWNEkKInGZId/gzS/K9EEIfSb5X0/lxoPLly/P333+nW//7779TtWrVLGmUEELkOEWV+cVASL4XQuglXfK9Hud8nXsC/P398fLy4vbt26SlpbFhwwYiIyNZvXo1QUFB2dFGIYTIdnJnKD3J90IIfST5Xk3nnoDWrVuzZcsW/vrrL6ysrPD39yciIoItW7ZoXnoQQogPTVqKKtOLoZB8L4TQR7rke33O+Tr3BADUr1+f4ODgrG6LEELkGkWPu3zfheR7IYS+kXyv9taThR0/fpyff/6Zn3/+mbCwsKxskxBC5LjsGi4uNTWVcePG4eLigoWFBSVLlmTy5Mm8PDCboij4+/tTqFAhLCwscHd35+LFi1rHiY2NpUuXLtjY2GBnZ4e3tzcJCQlaMadPn6Z+/fqYm5tTpEgRpk+f/tY/j5dJvhdC6JOcnizsfaVzT8CtW7fo1KkThw4d0kx5HBcXR506dfj1118pXLhwVrdRCCGynZKWPXeGpk2bxpIlS1i1ahUVKlTg+PHj9OzZE1tbWwYPHgzA9OnTmT9/PqtWrcLFxYVx48bh4eHB+fPnMTc3B6BLly7cvXuX4OBgkpOT6dmzJ3379mXt2rUAxMfH06RJE9zd3Vm6dClnzpyhV69e2NnZ0bdv37dqu+R7IYQ+yq58/6HRuSegd+/eJCcnExERQWxsLLGxsURERJCWlkbv3r2zo41CCJHtFCXziy4OHz5M69at8fT0pHjx4rRv354mTZpw9OjR/z+vwty5cxk7diytW7fmk08+YfXq1dy5c4dNmzYBEBERwY4dO1i+fDm1atWiXr16LFiwgF9//ZU7d+4AsGbNGp4/f86KFSuoUKECHTt2ZPDgwcyePfutfyaS74UQ+kiXfK9rzv+Q6FwE7N+/nyVLllCmTBnNujJlyrBgwQIOHDiQpY0TQoicoqSpMr0kJSURHx+vtSQlJWV43Dp16rB7927++ecfAE6dOsXBgwdp1qwZAFevXiUqKgp3d3fNPra2ttSqVYuQkBAAQkJCsLOzo3r16poYd3d3jIyMCA0N1cQ0aNBAa2ZfDw8PIiMj33pSL8n3Qgh9pEu+1+deA52LgCJFimQ4SUxqairOzs5Z0ighhMhpunwhBAQEYGtrq7UEBARkeNxRo0bRsWNHypYti4mJCVWrVmXo0KF06dIFgKioKAAcHR219nN0dNRsi4qKwsHBQWu7sbEx9vb2WjEZHePlc+hK8r0QQh9JEaCmcxEwY8YMBg0axPHjxzXrjh8/zpAhQ5g5c2aWNk4IIXKKLl3Do0eP5tGjR1rL6NGjMzzuunXrWLNmDWvXruXEiROsWrWKmTNnsmrVqhy+Qt1JvhdC6CN5HEgtUy8G58uXD5Xq30ooMTGRWrVqYWys3j0lJQVjY2N69epFmzZtsqWhQgiRnXS522NmZoaZmVmmYkeMGKHpDQCoVKkS169fJyAgAC8vL5ycnACIjo6mUKFCmv2io6OpUqUKAE5OTsTExGgdNyUlhdjYWM3+Tk5OREdHa8W8+PwiJjMk3wsh9J0+393XRaaKgLlz52ZzM4QQInelpWbPl8KTJ08wMtLudM2TJw9paepx51xcXHBycmL37t2aP/rj4+MJDQ2lf//+ALi5uREXF0dYWBiurq4A7Nmzh7S0NGrVqqWJGTNmDMnJyZiYmAAQHBxMmTJlyJcvX6bbK/leCKHvsivff2gyVQR4eXlldzuEECJXpWXT5DEtW7bku+++o2jRolSoUIGTJ08ye/ZsevXqBYBKpWLo0KFMmTKF0qVLa4YIdXZ21txpL1euHE2bNqVPnz4sXbqU5ORkBg4cSMeOHTXP5nfu3JmJEyfi7e2Nn58fZ8+eZd68ecyZM0en9kq+F0Lou+zK9x+at5ox+IVnz57x/PlzrXU2Njbv1CAhhMgN2TWD5IIFCxg3bhwDBgwgJiYGZ2dnvv76a/z9/TUxI0eOJDExkb59+xIXF0e9evXYsWOHZo4AUA8BOnDgQBo3boyRkRHt2rVj/vz5mu22trbs2rULHx8fXF1dKVCgAP7+/m89R8B/Sb4XQugLmTFYTaUour3ykJiYiJ+fH+vWrePBgwfptqempmZZ495W8v0rud0EkUssnOvndhNELkl5fvud9r/wcfNMx5b9Z9s7netD8SHke5Ccb8gk5xumnMz3oL85X+fRgUaOHMmePXtYsmQJZmZmLF++nIkTJ+Ls7Mzq1auzo41CCJHtZKSI9CTfCyH0kYwOpKbz40Bbtmxh9erVfPrpp/Ts2ZP69etTqlQpihUrxpo1azRjXwshxIdERotIT/K9EEIfSb5X07knIDY2lhIlSgDq50FjY2MBqFevnswgKYT4YKUpqkwvhkLyvRBCH+mS7/U55+tcBJQoUYKrV68CULZsWdatWweo7xjZ2dllaeOEECKnKIoq04uhkHwvhNBHuuR7fc75OhcBPXv25NSpUwCMGjWKRYsWYW5uzrBhwxgxYkSWN1AIIXKCPB+anuR7IYQ+kncC1HQeHei/rl+/TlhYGKVKleKTTz7Jqna9ExkpwnDJSBGG611Hiwgv1irTsVWub36nc32o3sd8D5LzDZnkfMOUk/ke9Dfnv9M8AQDFihWjWLFiWdEWIYTINWnyotgbSb4XQugDyfdqmSoCXp6Q5k0GDx781o0RQojcos8vf+lC8r0QQt9JvlfL1ONALi4umTuYSsWVK7nfLWts+lFuN0HkkgKWMoOpoYqKi3in/Y999EWmY2vc3vhO53qffWj5HsDMvEhuN0HkEisT8zcHCb0T+/jiO+2vS74H/c35meoJeDE6hBBC6Cu5M6Qm+V4Ioe8k36u98zsBQgihD/R4AAghhBAvkXyvJkWAEEIgd4aEEMJQSL5XkyJACCFAryeEEUII8S/J92pSBAghBJCW2w0QQgiRIyTfq0kRIIQQgILcGRJCCEMg+V7N6G12+vvvv+natStubm7cvq2ete3nn3/m4MGDWdo4IYTIKSmKKtOLIZF8L4TQN7rke33O+ToXAX/88QceHh5YWFhw8uRJkpKSAHj06BHff/99ljdQCCFygoIq04uhkHwvhNBHuuR7fc75OhcBU6ZMYenSpfz444+YmJho1tetW5cTJ05kaeOEECKnpOmwGArJ90IIfaRLvtfnnK/zOwGRkZE0aNAg3XpbW1vi4uKyok1CCJHj9Pluz9uSfC+E0EeS79V07glwcnLi0qVL6dYfPHiQEiVKZEmjhBAip8ldofQk3wsh9JH0BKjpXAT06dOHIUOGEBoaikql4s6dO6xZs4bhw4fTv3//7GijEEJkO/lCSE/yvRBCH0kRoKbz40CjRo0iLS2Nxo0b8+TJExo0aICZmRnDhw9n0KBB2dFGIYTIdtI9nJ7keyGEPpJ8r6ZzT4BKpWLMmDHExsZy9uxZjhw5wr1795g8eXJ2tE8IIXJEmirzi65u375N165dyZ8/PxYWFlSqVInjx49rtiuKgr+/P4UKFcLCwgJ3d3cuXryodYzY2Fi6dOmCjY0NdnZ2eHt7k5CQoBVz+vRp6tevj7m5OUWKFGH69Olv9bN4QfK9EEIf6ZLvdcn5AQEB1KhRA2traxwcHGjTpg2RkZFaMc+ePcPHx4f8+fOTN29e2rVrR3R0tFbMjRs38PT0xNLSEgcHB0aMGEFKSopWzL59+6hWrRpmZmaUKlWKwMBAnX8ObzVPAICpqSnly5enZs2a5M2b920PI4QQ74U0VJledPHw4UPq1q2LiYkJ27dv5/z588yaNYt8+fJpYqZPn878+fNZunQpoaGhWFlZ4eHhwbNnzzQxXbp04dy5cwQHBxMUFMSBAwfo27evZnt8fDxNmjShWLFihIWFMWPGDCZMmMCyZcve+Wcj+V4IoU90yfe65Pz9+/fj4+PDkSNHCA4OJjk5mSZNmpCYmKiJGTZsGFu2bGH9+vXs37+fO3fu0LZtW8321NRUPD09ef78OYcPH2bVqlUEBgbi7++vibl69Sqenp40atSI8PBwhg4dSu/evdm5c6dOPweVoiiKLjs0atQIlerVP5A9e/bo1IDsYGz6UW43QeSSApY2ud0EkUui4iLeaf8NTp0zHds2am2mY0eNGsWhQ4f4+++/M9yuKArOzs588803DB8+HFCPw+/o6EhgYCAdO3YkIiKC8uXLc+zYMapXrw7Ajh07aN68Obdu3cLZ2ZklS5YwZswYoqKiMDU11Zx706ZNXLhwIdPtfdmHkO8BzMyL5HYTRC6xMjHP7SaIXBD7+OKbg15Dl3wPuuX8l927dw8HBwf2799PgwYNePToEQULFmTt2rW0b98egAsXLlCuXDlCQkKoXbs227dvp0WLFty5cwdHR0cAli5dip+fH/fu3cPU1BQ/Pz+2bt3K2bNnNefq2LEjcXFx7NixI9Pt07knoEqVKlSuXFmzlC9fnufPn3PixAkqVaqk6+GEEOK9kKZSZXpJSkoiPj5ea3kxkdZ/bd68merVq/Pll1/i4OBA1apV+fHHHzXbr169SlRUFO7u7pp1tra21KpVi5CQEABCQkKws7PTFAAA7u7uGBkZERoaqolp0KCBpgAA8PDwIDIykocPH77Vz0TyvRBCH+mS73XN+S979OgRAPb29gCEhYWRnJysle/Lli1L0aJFtfJ9pUqVNAUAqHN5fHw8586d08S8fIwXMS+OkVk6vxg8Z86cDNdPmDAh3fOpQgjxodClSzQgIICJEydqrRs/fjwTJkxIF3vlyhWWLFmCr68v3377LceOHWPw4MGYmpri5eVFVFQUgFbCf/H5xbaoqCgcHBy0thsbG2Nvb68V4+Liku4YL7a9/PhRZkm+F0LoI50egUG3nP9CWloaQ4cOpW7dulSsWBFA01NrZ2enFfvffJ/R98GLba+LiY+P5+nTp1hYWGTqunQuAl6la9eu1KxZk5kzZ2bVIYUQIsfoMgzc6NGj8fX11VpnZmaW8XHT0qhevTrff/89AFWrVuXs2bMsXboULy+vt21urpJ8L4T4kOk67KcuOf8FHx8fzp49y8GDB3U8W8556xeD/yskJARzc3k2TwjxYdJlpAgzMzNsbGy0lld9IRQqVIjy5ctrrStXrhw3btwA1BNyAelGh4iOjtZsc3JyIiYmRmt7SkoKsbGxWjEZHePlc2QVyfdCiA+ZrqMD6ZLzAQYOHEhQUBB79+6lcOHCmvVOTk48f/483Yzr/833b8rlr4qxsbHJdC8AvEVPwMtvMIP6pba7d+9y/Phxxo0bp+vhhBDivaDrqD+ZVbdu3XRDxP3zzz8UK1YMABcXF5ycnNi9ezdVqlQB1CP9hIaGaibkcnNzIy4ujrCwMFxdXQH1S7lpaWnUqlVLEzNmzBiSk5MxMTEBIDg4mDJlyrzVo0Ag+V4IoZ+yK98risKgQYPYuHEj+/btS/eIpqurKyYmJuzevZt27doBEBkZyY0bN3BzcwPUufy7774jJiZG8xhocHAwNjY2mhtKbm5ubNu2TevYwcHBmmNkls5FgK2trdZnIyMjypQpw6RJk2jSpImuhxNCiPeCrs+IZtawYcOoU6cO33//PR06dODo0aMsW7ZMM3SnSqVi6NChTJkyhdKlS+Pi4sK4ceNwdnamTZs2gLrnoGnTpvTp04elS5eSnJzMwIED6dixI87OzgB07tyZiRMn4u3tjZ+fH2fPnmXevHmvfK4/MyTfCyH0UXblex8fH9auXcuff/6JtbW15hl+W1tbLCwssLW1xdvbG19fX+zt7bGxsWHQoEG4ublRu3ZtAJo0aUL58uXp1q0b06dPJyoqirFjx+Lj46PpfejXrx8LFy5k5MiR9OrViz179rBu3Tq2bt2qU3t1GiI0NTWVQ4cOUalSpbe+s5QTZIhQwyVDhBqudx0idPVHXTMd2/32/3Q6dlBQEKNHj+bixYu4uLjg6+tLnz59NNsVRWH8+PEsW7aMuLg46tWrx+LFi/n44481MbGxsQwcOJAtW7ZgZGREu3btmD9/vta4/adPn8bHx4djx45RoEABBg0ahJ+fn05tfeFDyfcgQ4QaMhki1DC96xChuuR7yHzOf9WQyitXrqRHjx6AerKwb775hl9++YWkpCQ8PDxYvHix1mOb169fp3///uzbtw8rKyu8vLyYOnUqxsb/3rvft28fw4YN4/z58xQuXJhx48ZpzpFZOs8TYG5uTkRERLoujveJFAGGS4oAw/WuRUCgDl8KPXQsAj5UH0K+BykCDJkUAYbpXYsAXfI96G/O1/nF4IoVK3LlypXsaIsQQuSaVFXmF0Mh+V4IoY90yff6nPN1LgKmTJnC8OHDCQoK4u7du+kmTxBCiA9Rmg6LoZB8L4TQR7rke33O+Zl+MXjSpEl88803NG/eHIBWrVppPfukKAoqlYrU1NSsb6UQQmQzfU70upJ8L4TQZ5Lv1TJdBEycOJF+/fqxd+/e7GyPEELkCkWPu3x1JfleCKHPJN+rZboIePH+cMOGDbOtMUIIkVvkztC/JN8LIfSZ5Hs1neYJeNXQR0II8aGTLwVtku+FEPpK8r2aTkXAxx9//MYvhtjY2HdqkBBC5IbsmjzmQyX5XgihryTfq+lUBEycODHdDJJCCKEP0uTGtxbJ90IIfSX5Xk2nIqBjx444ODhkV1uEECLXSPewNsn3Qgh9JfleLdNFgDwfKoTQZ/Kl8C/J90IIfSb5Xk3n0YGEEEIf6fOskLqSfC+E0GeS79UyXQSkpUndJITQX5Lh/iX5XgihzyTDqen0ToAQQugrufcthBCGQfK9mhQBQggBpMnXghBCGATJ92pSBAghBNI9LIQQhkLyvZoUAUIIgXQPCyGEoZB8ryZFgBBCIHeGhBDCUEi+V5MiQAghkBkkhRDCUEi+V5MiQAghkBfFhBDCUEi+VzPK7QaIrFG/Xi02bQzkxrUwUp7fplUrj9xuknhHRkZGjBwzmKOngrl69yRHTu5k2Ij+WjHDR/nw99GtXLkdxoVrR1i3aQVVXT/RbC9S1JnZC6ZoHWPE6IGYmJjk9OW891J1WITISc7OTqxcOY87t08T9/AiYceDqVbt33/nSc9uZrj4Dvs6F1stdDX0m6/5a98fXL9zksgrR/j5l8WUKu2iFePV8ys2b/sf12+fJPbxRWxsrdMdxy6fLT8sn8X12ye5ejOM+Yu+x8rKMqcu44OgS77X55wvRYCesLKy5PTp8wwaMia3myKyyMChvfHq1ZFvR0yhQS1Ppoyfhc9gb7y/7qqJuXzpGt+OmMKndVrTumlXbt64zW8blpM/fz4ASpUugZGRihFDx9Owdkv8v51K955f8a3/0Fy6qvdXGkqmFyFyip2dLXv3biA5OYVWrbtTpepn+I2aTFzcI01M0WLVtJY+fb8hLS2NjZu252LLha7q1q3JTz+uweOzL2nbqgcmJib8sWkllpYWmhgLCwt2/3WA2bOWvPI4y5bPomy50rRt3YOOHfriVqcGc+ZPyYlL+GDoku/1OeerFD2cH97Y9KPcbkKuSnl+m7bte7F5887cbkqOK2Bpk9tNyDI//7qEe/ce4DtorGbd8tXzePb0GQO/9stwn7zWVly6eZz2rXpy8MCRDGMGDOqFl3dHalVpki3tzi1RcRHvtP/I4p0yHTv92i/vdC6RtczMi+R2E7LNlMmjcKtTg8aN22V6n/XrlmNtbUXTZpn/b/pDZWVinttNyDb5C9hz8Woonk07E3LomNa2uvVqsmX7GooXrkb8o8ea9R+XKcmR4zv4rMEXhJ88C0Bj9/r89sdyKpapT1RUTI5eQ3aJfXzxnfbXJd+D/uZ86QkQ4j117OhJ6jesTYmSxQEoX7EMtWpXY89ff2cYb2JiQjevDjx6FM/5sxdeeVxrG2viHj565XZDlabD8i6mTp2KSqVi6NChmnXPnj3Dx8eH/PnzkzdvXtq1a0d0dLTWfjdu3MDT0xNLS0scHBwYMWIEKSkpWjH79u2jWrVqmJmZUapUKQIDA9+xtSK3tWjxOSfCTrN2zRJu3jhJ6JHt9Or16j9gHBwK0KzZZ6wM/C0HWymyg41NXgDiYuMyvU+NmlWJe/hIUwAA7Nt7mLS0NFxrVM7qJn6wdMn3+jySkLwYLMR7asGcH7G2zsvBY1tJTU0lT548BEyey4b1QVpxn3t8ytKfZmJhaUF01D2+auNN7Cu+NIq7FMW7bxcmjpuRA1fwYcmJLt9jx47xww8/8Mknn2itHzZsGFu3bmX9+vXY2toycOBA2rZty6FDhwBITU3F09MTJycnDh8+zN27d+nevTsmJiZ8//33AFy9ehVPT0/69evHmjVr2L17N71796ZQoUJ4eMg7Qh8qF5ei9O3blXnzlzNt+kKqV6/M7FmTeP48mf/97/d08d26tufx40Q2yaNAHzSVSsX308ZyJOQ4ERGZv+vt4FiAe/cfaK1LTU3l4cNHODgUzOpmfrD0+REfXUgRIMR7qtUXzWj7ZQv69x5B5IWLVKxUjkkBo4mOimHdL39q4g79HUrj+m2xz5+Prl5fsixwDs0bf8X9+7Fax3Mq5MAvfyxjy587WbN6fU5fznsvu78SEhIS6NKlCz/++CNTpvz7fO6jR4/46aefWLt2LZ999hkAK1eupFy5chw5coTatWuza9cuzp8/z19//YWjoyNVqlRh8uTJ+Pn5MWHCBExNTVm6dCkuLi7MmjULgHLlynHw4EHmzJkjRcAHzMjIiLCw0/j7TwPg1KlzVChfhj69u2ZYBHh5fcWvv24kKSkpp5sqstCM2RMoV640zZvo/yNduUFKADV5HEiI95T/pOEsnLucPzds48L5i/z+22aWLV7FoGF9teKePHnKtas3OHH8FL6DxpKSkkqnbtrPDzs6FeSPLas4fjSc4UP8c/IyPhi6dA0nJSURHx+vtbzpjy4fHx88PT1xd3fXWh8WFkZycrLW+rJly1K0aFFCQkIACAkJoVKlSjg6OmpiPDw8iI+P59y5c5qY/x7bw8NDcwzxYbobFUPEBe07wRcuXKJIkfTvvtWtW5MyZUqxYqV+Pr9sKKbN9MejaSNaeXbjzp0onfaNib5PwQL5tdblyZOHfPlsiYm5l5XN/KDJ40BqUgQI8Z6ysLQgLU07/aSmpmJk9Pp/tkZGKszMTDWfnQo5sCFoNafDzzFkwLfo4VgAWULR4X8BAQHY2tpqLQEBAa889q+//sqJEycyjImKisLU1BQ7Ozut9Y6OjkRFRWliXi4AXmx/se11MfHx8Tx9+lTnn4d4P4SEHOfjj0tqrStdugQ3btxKF9ujR0fCwk5z5sy7vSQvcs+0mf54tvyc1i26ceN6+t/xmxw7ehK7fLZUrlJBs65BQzd1j9KxU1nZ1A+aLvle0eN+A3kcSE9YWVlSqtS/4wm7FC9K5coViI19yM2bd3KxZeJtBe/Yy5Bvvub2rbvqx4E+KU8/nx788r8NAFhaWjDkm6/ZuX0vMdH3sLe3o2efzjgVcmTLJvXIUC8KgFs37zBx3HTyF7DXHP9ezP1cua73lS53e0aPHo2vr6/WOjMzswxjb968yZAhQwgODsbcXH9HMhHZY/785ezft5GRIwfyx+9BVK9RBW/vzgzw0R4hzNo6L+3aeuLnNzmXWire1YzZE2j/ZUu6dOxPwuNEHBwKABAf/5hnz9Q9jQ4OBXBwLEiJksUAKF+hDAmPE7l16w5xDx/xT+Rl/tq1n7kLvuObof6YmBgzbZY/G37fqjcjA2UFfb67rwspAvREddfK7P7r3+dDZ82cAMCq1evw7j0sl1ol3sW3I6fgN2YIU2f5k7+APdFRMaxeuY7Z0xcD6l6BUh+XoEOnNtjnz8fD2DjCT56hTbOuRF64BEDDRnUoUbIYJUoWIzxiv9bxnezK5fg1vc9SdbjbY2Zm9so/+v8rLCyMmJgYqlWr9u+5UlM5cOAACxcuZOfOnTx//py4uDit3oDo6GicnJwAcHJy4ujRo1rHfTF60Msx/x1RKDo6GhsbGywsLBAfprCwU3To0IfJk0cx5tshXLt2k+EjJvDrr5u04jp0aIVKpeK3dX9mfCDx3vPu0wWAoB1rtNb79PPjlzXqmz89vTvh9+1gzbZtO39JF9O39zdMnzmejVtWoaQpbNm8k1EjpDh8mS75Xp/JPAFCr+jTPAFCN+86T8DXxb/MdOwP1zL/YvXjx4+5fv261rqePXtStmxZ/Pz8KFKkCAULFuSXX36hXTv1uxyRkZGULVuWkJAQateuzfbt22nRogV3797FwcEBgGXLljFixAhiYmIwMzPDz8+Pbdu2cebMGc15OnfuTGxsLDt27Mh0ez9E+jxPgHg9fZ4nQLzau84ToEu+B91y/odEegKEEILs6x62tramYsWKWuusrKzInz+/Zr23tze+vr7Y29tjY2PDoEGDcHNzo3bt2gA0adKE8uXL061bN6ZPn05UVBRjx47Fx8dH0yPRr18/Fi5cyMiRI+nVqxd79uxh3bp1bN26NZuuTAghPkzyOJCaFAFCCAG5+vLXnDlzMDIyol27diQlJeHh4cHixYs12/PkyUNQUBD9+/fHzc0NKysrvLy8mDRpkibGxcWFrVu3MmzYMObNm0fhwoVZvny5DA8qhBD/oc8v++rivX4c6ObNm4wfP54VK1a8MiYpKSnd0Hz58pdFpVJld/PEe0geBzJc7/o4UK/i7TMdu+Ja+vHZxbt725xfoGB5yfkGSh4HMkzv+jiQLvke9Dfnv9dDhMbGxrJq1arXxmQ0VJ+S9jiHWiiE0BcyXFzue9ucn5oan0MtFELoAxkiVC1XHwfavHnza7dfuXLljcfIaKi+fPnLvlO7hBCGR54RzX7ZlfMLFCz/Tu0SQhgWyfdquVoEtGnTBpVK9drJi97UxZvRUH3SLSyE0FXa+/tkpN6QnC+EeB9IvlfL1ceBChUqxIYNG0hLS8twOXHiRG42L0f17+fFpX+OkBB/mcMHt1CjepXXxrdr14KzZ/aTEH+Zkyf+olnTz7S2t2nTjO1b1xJ99ywpz29TuXKFdMeYOX08MVFnuXr5GJ06fZHu+Js2Br7rZYnXGD7Kh6i4CK3l76OvHsnlq85t0sVfiwrXipm3+Pt0MWt/X6bZbmpqwoIfpnHxxjEOHd9O/YZuWvsPGNSL76aPydLr/FAoOizi7UjOh3r1arHhjxVcvXKcpGc3adXy9S9u16lTg717N3Dn9mniHl7k9Km9DB7U+5Xxw4cPIOnZTWbOGK+1fvo0f+7eOcOlS6F07NhGa1vbtp5s+OPV72GIrDfEty+xjy/y/dRX59vuPTqwdedartw4zpUbx9mwOZBqrp+kixs9ZgjnLx7idswZNmwO1EwkBmBqasqSZTO4fvskR0/uouGndbT2HTSkN1NnjMu6C/tA6JLv9Tnn52pPgKurK2FhYbRu3TrD7W+6Y6QvvvyyFTNnjGeAzyiOHjvJ4EG92bZ1DeUrNuDevQfp4t1qV2fNz4sYMzaArdv+olPHL/jj95+oUasp585FAuoZhA8dPsr637ew7IeZ6Y7RwvNzOnZsQ7PmnSlV2oXly2axa9c+Hjx4iI2NNZMn+eHR9Ktsv3ZDd+H8Rb5s00vzOTUl5bXx8Y8eU7dGc83njP597Ak+wBCff79Ynic91/z/bj06ULlyeVo06cRn7vVZsnwGFUvXA6BosY/o4vUlHo10e2FKX6RKB3G2k5wPVpYWnD4TQeCqdaxf9+Mb4xMTn7BkySrOnIngyZMn1KlTg0ULp5L45Ak//bRWK9bVtTJ9enfh9OnzWus9m7vz1Vet8WzRhVKlXFj2w0yCg/dr8v2kiSNp1rxTll6neLWq1SrRo2dHzp55/WAGdevV4o/1QRwNPUlSUhJDhvXlj00rqVOzOXfvqicGHDysL337dWdAv5Fcv3aLb8cN5feNK3Gr0ZSkpOd49fyKKlUr4tH4S9ybNGTZitmUKaEeerhoscJ069GBxg3aZvs1v28k36vlak/AiBEjqFOnziu3lypVir179+Zgi3LHsCF9WP7TWlatXkdExEUG+IziyZOn9OzRMcP4QYO82blzH7NmL+XChUuMnzCDkyfPMqB/T03MmjV/MOW7ueze83eGxyhbthT7D4QQduI0v/32J/HxCbgULwrA1ICx/PDDam7evJP1Fyu0pKSmcC/mvmaJjY17bbyCohV/P4MiMen5c62YR4/+fWmy9Mcl2bl9L5EXLrFy+VoKFMxP/vz5AJg6azxTJswi4XFill7jhyJNh0W8Hcn5sHPXPiZMmMHmzZmbwO3UqXOsW/cnERH/cP36LX75ZSPBwfupW7emVpyVlSWrAufTf4AfD+MeaW0rW7YUBw4c4cSJ06xb9yfx8Y8p/v/5PuD7b1m27GfJ9znEysqSH36axdBBY4mLe/0L7V/3/oYVy9dy9kwEF/+5wmCfbzEyMqLBp//24PYb4MWsGYvZvnU3589F0r/vCJwKOeDZ4nMAPi5Tku3bdnPhwiWWL/sfBQvmJ38BewBmzZnIRP8ZPH6ckH0X/J7SJd/rmvMPHDhAy5YtcXZ2RqVSsWnTJq3tiqLg7+9PoUKFsLCwwN3dnYsXtUc7io2NpUuXLtjY2GBnZ4e3tzcJCdq/p9OnT1O/fn3Mzc0pUqQI06dP17GluVwE1K9fn6ZNm75yu5WVFQ0bNszBFuU8ExMTqlX7ROuPdUVR2L3nILVru2a4T+1arun+uN8VvO+V8Rk5ffo8rtU+wc7OlmpVK2FhYc6ly9eoW6cGVatWZMHCn97ugoROSpQoRnjEfkLDd7Fo2XQ+KlzotfFWVpYcP7ObsLN7CFy7kDJlS6WLqVOvJmcvHuTgsW1MmzWefPnsNNvOnb1AzdrVMDc349PG9Yi6G8ODBw9p+2ULkpKS2B70V1Zf4gcjDSXTi3g7kvPfXeXKFahd25W//z6itX7evCls376HPXsOptvn9OkIXF3V+b7q/+f7y5evUadODapUqcTCRfIoUE6ZPns8wTv2sX/fYZ33tbS0wNjEmIcP1UVeseJFcHJyYN/ef4/1OD6BsOOnqFGzKgBnz1ygtpsr5uZmfOZen7t3o3lwP5b2HVrxLCmJrVuCs+bCPjC65Htdc35iYiKVK1dm0aJFGW6fPn068+fPZ+nSpYSGhmJlZYWHhwfPnj3TxHTp0oVz584RHBxMUFAQBw4coG/fvprt8fHxNGnShGLFihEWFsaMGTOYMGECy5Yty+iUrySTheWyAgXsMTY2Jib6vtb6mJh7lC1TMsN9nJwKEh1zT2tddPR9nBwLZvq8u4L3s/aXDRw5vJWnz57R03soiYlPWLgwAG/vYfT7ujs+Pr14cD+WfgNGcv78P7pfnHitE8dPM2TAt1y6dBVHx4J84+fDn9v/R0O3liQmPEkXf+niNYYNHMv5c5HY2FjTf1BPtuxcS0O3lty9o+4a3vPXQbZuCebG9VsUdynKt+OGsvb3H/D8vBNpaWn88r8NlK9QhgOhQcQ+eEjfnsOws7Nl5LeDaNvCC78xQ2jTrhnXrt5k2MAxRN2NyekfS67R52HgxIfv8qWjFCyo/r6YPGUOK1f+qtn25ZetqFqlEnXqtshw3+C/1Pn+8KEgnj59hndvXxITn7Bg/vf07uPL1327MWBAT+4/iGXAgFFEREi+zw5t23lSuXIFGjd8u8dvxk8aQdTdGPbvPQSAo2MBAO7FaP/9cC/mPg7/v23Nz79ToWIZQo5t58GDh/TyGoJdPltGjxlCq+Zd+HbcMNq28+Ta1RsMGjBa85iRvsvOfN+sWTOaNWuW8XkVhblz5zJ27FjNY5GrV6/G0dGRTZs20bFjRyIiItixYwfHjh2jevXqACxYsIDmzZszc+ZMnJ2dWbNmDc+fP2fFihWYmppSoUIFwsPDmT17tlax8CZSBBiwSZNnM2nybM3ncWOHsWf3QZJTUvh29BCqVGuMZ3N3Vq6YR63aGf8HLd7enr/+7c2JOPcPJ8JOc/z0blp90Yxffv4jXXzYsXDCjoVrPh8LPcnfR4Po1vMrpn83H4A/N2zTbL9w/iLnz0Zy9FQwderV5OCBI6SkpDB6xGQY8e9x5y76juU//I+Kn5SjmWdjGtf7Ap8h3kyZNobe3Ydk/YW/p+QxH/E+a+zeDisrK2rVqsqUyaO5fPka69b9SeHChZg1cwLNPTunm0TtZVOmzGHKlDmaz2PGDGXPnoMkJyczatRgXKt/TvPm7qz4aQ5udTxz4pIMykcfOfH99LG0bdWDpJfe08qsIb59advOk5bNu+q0f0pKCiO/mai1buGSqSxbuppKlcvj2cKdBnVaMnhoH6bOGIdX14E6t+1DpGu+z2iSwoxGKnuTq1evEhUVhbu7u2adra0ttWrVIiQkhI4dOxISEoKdnZ2mAABwd3fHyMiI0NBQvvjiC0JCQmjQoAGmpqaaGA8PD6ZNm8bDhw/Jly9fptrzXk8WZgju348lJSVFU7W/4OBQkKjoexnuExV1D0cH7bv+jo4FXhmfGWXKlKRzp3b4T5hOwwZu/H0wlPv3Y1n/+xZcq31C3rxWb31skTnxjx5z5fI1XFyKZio+JSWFs6cjXht/4/otHtyPxaVExjF169ekTNlSrFi2hjr1arI7+ABPnjxl88Yd1KlXM8N99JWiKJlehMhp167d5Ny5C6xY8QvzFyxn3NhhAFSr+gmOjgUJPbKdxISrJCZcpWEDN3x8epGYcBUjo/Rf82U+LknnTm2ZMHEGDRu4cfD/8/3vv2+hmuT7bFG5akUcHAqw7+AmYh5GEPMwgnr1a9G3f3diHkZk+Ht6YeBgb4YO+5p2bXpy/v8H/wD1EwAABR20/34o6FAg3dMFL9SrX4syZUvx4w8/U69+LYJ37efJk6ds2rCNuvUNJ+frku8VRclwksKAgACdzxsVFQWAo6Oj1npHR0fNtqioKBwcHLS2GxsbY29vrxWT0TFePkdmSBGQy5KTkzlx4jSfNaqnWadSqfisUT2OHAnLcJ8joWF89lk9rXXujRu8Mj4zliyaxoiRE0lMfEKePHkwMVF3EpmYmACQJ0+etz62yBxLK0uKuRQhOpPFnJGREWXLf/za+ELOjuSzt8swxszMlIAZ4xgxbAJpaWnkyWOE8f//3o1NjMmTx7DSg7wTID4URkYqTM3UdwD37D1I1Wru1KjZVLMcP36KX37dSI2aTUlLS3/Pc+GiqYwcOemlfK/O85Lvs8+BfSHUrdmchnVaaZYTYadZ/9tmGtZpleHvCWDQ0D4MH+nDl229CT95Vmvb9Ws3iYqKoeFLLwpbW+fFtXpljh09me5YZmamzJg9Ad8h/uqcb5QHE+MXOd+EPEaG83vX9Z2A0aNH8+jRI61l9OjRuX0Z70weB3oPzJn3Iyt/mkPYidMcO3aSwYP6YGVlQeCq3wBYuWIed+7cZczYqQAsWPATe3b/zrChX7Nt+1981aE1rq6f0G/ASM0x8+Wzo2jRj3AupK4MP/5Y/X5BVFRMuj8IvXt15t79WIK2ql8QOnz4GP7jfKlVsxpNmzbi3PlIrRFmRNYYP3kEu3bs49bN2zg6OTBi9CDSUtPY9Lt6roAFS6dy9040309Sd+H7jhxA2LFwrl65ga2dDQMG9aJwEWfWrv4dUBcRw/0GELQ5mHsx9yhWvCjjJg3n6pUb7Nud/mXBYSP6szv4AGdPq4epO3bkJP6TR/Drmg306tOFY0fSf4noM3kcSOQEKytLSpYsrvlcvHgRPvmkPA8fxnHz5h0mT/bD2dkJb2/1nf5+X3tx8+ZtIiMvAeo7ucOGfs2ixSsBSEhI5Pz5SK1zJD55QuyDh+nWA/Tq1Yn79x6wdZt6EIDDIccZO3YYNWtWxcOjEecl32eLhIREIiK0R4B58uQpD2PjNOsX/zCdu3ejmTxhFqAe/nP0mCH07eXLjeu3cPj/O/6JiU9ITFS/N7Z08Sq+GTGAy5evaYYIjbobw9ag9C/8DvfzIXjXPs78/xCyoUfCmDjFjzX/+4M+X3clNFT/5+l4Qdd8/zaP/mTEyckJgOjoaAoV+ncgkOjoaKpUqaKJiYnRfh8vJSWF2NhYzf5OTk5ER2u/v/Hi84uYzJAi4D2wfv1mChawZ4L/cJycCnLq1Dk8W3Ql5v9f9ilaxFnrLkHIkeN07T6QSRNHMmWyHxcvXaVde2/NHAEALVs0YcVP/z7/+cuaJQBMmjxL6z0AB4cCjB41mPoN/x23+9jxcObM/YHNf64m5t59evUaml2XbtAKOTuxZPlM8tnb8eB+LEePnKC5e0cePHgIwEeFC2n93m3tbJg1fzIFHQrwKO4Rp8PP09KjM/9EXgYgLTWVchXK0KFTG2xsrYmOuse+PYeY9t18nj9P1jp32XKlafVFM9zr/ztJ3JY/d1KnXk3+3PY/Ll+6Sv/eIzAk8mKwyAmurp8QvGu95vOM/5/Ua/XP6+nTxxcnJ0eKFPlIs93ISMXkyaMoXrwIKSkpXLlynTFjAvhx+f90PreDQwH8/Abx6af//rs/fjycufOWsWnjKu7du493b993uDrxLgoXcdaaybaXdyfMzExZtWahVty07+czLWABAPPnLMPK0oI586dga2vDkZDjfNm2V7r3BsqVK02bL5rTsG4rzbo/N+2gbv1abNv5CxcvXqGvt+H87nMr37u4uODk5MTu3bs1f/THx8cTGhpK//79AXBzcyMuLo6wsDBcXdWjPu7Zs4e0tDRq1aqliRkzZgzJycmaHrzg4GDKlCmT6fcBAFSKHj7gamz60ZuDhF4qYGmT200QuSQq7vUT77xJ86LN3xz0/7bd2PbmIJFjzMyL5HYTRC6xMjHP7SaIXBD7+OKbg15Dl3wPuuX8hIQELl1S99xVrVqV2bNn06hRI+zt7SlatCjTpk1j6tSprFq1ChcXF8aNG8fp06c5f/485ubq/56bNWtGdHQ0S5cuJTk5mZ49e1K9enXWrlVPEPjo0SPKlClDkyZN8PPz4+zZs/Tq1Ys5c+bI6EBCCKGrVP27HyKEECID2Znvjx8/TqNGjTSffX3VPSxeXl4EBgYycuRIEhMT6du3L3FxcdSrV48dO3ZoCgCANWvWMHDgQBo3boyRkRHt2rVj/vz5mu22trbs2rULHx8fXF1dKVCgAP7+/joVACA9AULPSE+A4XrXnoAmRV49idV/7bqZudleRc6QngDDJT0BhuldewJ0yfegvzlfegKEEAJk1B8hhDAQku/VpAgQQgiQ8f+FEMJASL5XkyJACCGQO0NCCGEoJN+rSREghBDIEKFCCGEoJN+rSREghBCgNT63EEII/SX5Xs0otxsghBDvA0WHRRcBAQHUqFEDa2trHBwcaNOmDZGR2jO5Pnv2DB8fH/Lnz0/evHlp165dutkgb9y4gaenJ5aWljg4ODBixAhSUlK0Yvbt20e1atUwMzOjVKlSBAYG6thaIYTQf7rke30uF6QIEEII1M+IZnbRxf79+/Hx8eHIkSMEBweTnJxMkyZNSExM1MQMGzaMLVu2sH79evbv38+dO3do27atZntqaiqenp48f/6cw4cPs2rVKgIDA/H399fEXL16FU9PTxo1akR4eDhDhw6ld+/e7Ny5891/OEIIoUd0yff6/P6AzBMg9IrME2C43nWegNrOn2Y69sidfW99nnv37uHg4MD+/ftp0KABjx49omDBgqxdu5b27dsDcOHCBcqVK0dISAi1a9dm+/bttGjRgjt37uDo6AjA0qVL8fPz4969e5iamuLn58fWrVs5e/as5lwdO3YkLi6OHTv0c4zrF2SeAMMl8wQYpnedJ0CXfA/vlvPfZ9ITIIQQ6HZnKCkpifj4eK0lKSkpU+d59OgRAPb29gCEhYWRnJyMu7u7JqZs2bIULVqUkJAQAEJCQqhUqZKmAADw8PAgPj6ec+fOaWJePsaLmBfHEEIIoSY9AWpSBAghBOrRIjL7v4CAAGxtbbWWgICAN54jLS2NoUOHUrduXSpWrAhAVFQUpqam2NnZacU6OjoSFRWliXm5AHix/cW218XEx8fz9OnTt/qZCCGEPtIl3+vzSEIyOpAQQqDb5DGjR4/G19dXa52Zmdkb9/Px8eHs2bMcPHhQ5/YJIYTIGnr4JPxbkSJACCHQbfIYMzOzTP3R/7KBAwcSFBTEgQMHKFy4sGa9k5MTz58/Jy4uTqs3IDo6GicnJ03M0aNHtY73YvSgl2P+O6JQdHQ0NjY2WFhY6NRWIYTQZ/r8iI8u5HEgIYRAfWcos4uuxx04cCAbN25kz549uLi4aG13dXXFxMSE3bt3a9ZFRkZy48YN3NzcAHBzc+PMmTPExMRoYoKDg7GxsaF8+fKamJeP8SLmxTGEEEKo6ZLv9bnXQHoChBCC7Lsz5OPjw9q1a/nzzz+xtrbWPMNva2uLhYUFtra2eHt74+vri729PTY2NgwaNAg3Nzdq164NQJMmTShfvjzdunVj+vTpREVFMXbsWHx8fDQ9Ev369WPhwoWMHDmSXr16sWfPHtatW8fWrVuz5bqEEOJDJT0BalIECCEE2TeN/JIlSwD49NNPtdavXLmSHj16ADBnzhyMjIxo164dSUlJeHh4sHjxYk1snjx5CAoKon///ri5uWFlZYWXlxeTJk3SxLi4uLB161aGDRvGvHnzKFy4MMuXL8fDwyNbrksIIT5U+vyyry5kngChV2SeAMP1rvMEVHSsnenYs9FH3ulcImvJPAGGS+YJMEzvOk+ALvke9DfnS0+AEEIAqUpabjdBCCFEDpB8ryZFgBBCIN3DQghhKCTfq0kRIIQQQJr+PRkphBAiA5Lv1aQIEEII5M6QEEIYCsn3alIECCEEcmdICCEMheR7NSkChBACuTMkhBCGQvK9mhQBQggBKDJahBBCGATJ92pSBAghBDKDpBBCGArJ92pSBAghBKCH8yYKIYTIgOR7NSkChBACmTxGCCEMheR7NSkChBACGS1CCCEMheR7NSkChBACGS1CCCEMheR7NSkChBACeUZUCCEMheR7NSkChBACGS1CCCEMheR7NSkChBACuTMkhBCGQvK9mhQBQgiBvCgmhBCGQvK9mhQBQgiB3BkSQghDIfleTYoAIYRAnhEVQghDIfleTYoAIYRA7gwJIYShkHyvJkWAEEIgM0gKIYShkHyvJkWAEEIgL4oJIYShkHyvJkWAEEIg3cNCCGEoJN+rGeV2A4QQ4n2g6PC/t7Fo0SKKFy+Oubk5tWrV4ujRo1l8BUIIITJDl3z/tjn/QyBFgBBCoL4zlNlFV7/99hu+vr6MHz+eEydOULlyZTw8PIiJicmGKxFCCPE6uuR7fe41kCJACCHI3iJg9uzZ9OnTh549e1K+fHmWLl2KpaUlK1asyIYrEUII8TpSBKhJESCEEICiw5KUlER8fLzWkpSUlOFxnz9/TlhYGO7u7pp1RkZGuLu7ExISkq3XJIQQIj1d8r3+lgB6+mJwyvPbud2EXJOUlERAQACjR4/GzMwst5sjcpD87t+NLnljwoQJTJw4UWvd+PHjmTBhQrrY+/fvk5qaiqOjo9Z6R0dHLly48FZtFdqSnt3M7SbkCvk3b7jkd/9uDPnvxJepFH3u5zBA8fHx2Nra8ujRI2xsbHK7OSIHye8+5yQlJaW7829mZpbhl/GdO3f46KOPOHz4MG5ubpr1I0eOZP/+/YSGhmZ7e4V+kn/zhkt+9yIr6GVPgBBCZKdX/cGfkQIFCpAnTx6io6O11kdHR+Pk5JQdzRNCCCHeSN4JEEKIbGRqaoqrqyu7d+/WrEtLS2P37t1aPQNCCCFETpKeACGEyGa+vr54eXlRvXp1atasydy5c0lMTKRnz5653TQhhBAGSooAPWNmZsb48ePlRSEDJL/799dXX33FvXv38Pf3JyoqiipVqrBjx450LwsLoQv5N2+45HcvsoK8GCyEEEIIIYSBkXcChBBCCCGEMDBSBAghhBBCCGFgpAgQQgghhBDCwEgRIIQQQgghhIGRIkCPLFq0iOLFi2Nubk6tWrU4evRobjdJ5IADBw7QsmVLnJ2dUalUbNq0KbebJITIAZLzDY/ke5GVpAjQE7/99hu+vr6MHz+eEydOULlyZTw8PIiJicntpolslpiYSOXKlVm0aFFuN0UIkUMk5xsmyfciK8kQoXqiVq1a1KhRg4ULFwLqGUmLFCnCoEGDGDVqVC63TuQUlUrFxo0badOmTW43RQiRjSTnC8n34l1JT4AeeP78OWFhYbi7u2vWGRkZ4e7uTkhISC62TAghRFaTnC+EyApSBOiB+/fvk5qamm72UUdHR6KionKpVUIIIbKD5HwhRFaQIkAIIYQQQggDI0WAHihQoAB58uQhOjpaa310dDROTk651CohhBDZQXK+ECIrSBGgB0xNTXF1dWX37t2adWlpaezevRs3N7dcbJkQQoisJjlfCJEVjHO7ASJr+Pr64uXlRfXq1alZsyZz584lMTGRnj175nbTRDZLSEjg0qVLms9Xr14lPDwce3t7ihYtmostE0JkF8n5hknyvchKMkSoHlm4cCEzZswgKiqKKlWqMH/+fGrVqpXbzRLZbN++fTRq1Cjdei8vLwIDA3O+QUKIHCE53/BIvhdZSYoAIYQQQgghDIy8EyCEEEIIIYSBkSJACCGEEEIIAyNFgBBCCCGEEAZGigAhhBBCCCEMjBQBQgghhBBCGBgpAoQQQgghhDAwUgQIIYQQQghhYKQIEEIIIYQQwsBIESByVI8ePWjTpo3m86effsrQoUNzvB379u1DpVIRFxf3yhiVSsWmTZsyfcwJEyZQpUqVd2rXtWvXUKlUhIeHv9NxhBDifSA5//Uk54vcJEWAoEePHqhUKlQqFaamppQqVYpJkyaRkpKS7efesGEDkydPzlRsZpK4EEKI15OcL4QAMM7tBoj3Q9OmTVm5ciVJSUls27YNHx8fTExMGD16dLrY58+fY2pqmiXntbe3z5LjCCGEyDzJ+UII6QkQAJiZmeHk5ESxYsXo378/7u7ubN68Gfi3O/e7777D2dmZMmXKAHDz5k06dOiAnZ0d9vb2tG7dmmvXrmmOmZqaiq+vL3Z2duTPn5+RI0eiKIrWef/bNZyUlISfnx9FihTBzMyMUqVK8dNPP3Ht2jUaNWoEQL58+VCpVPTo0QOAtLQ0AgICcHFxwcLCgsqVK/P7779rnWfbtm18/PHHWFhY0KhRI612Zpafnx8ff/wxlpaWlChRgnHjxpGcnJwu7ocffqBIkSJYWlrSoUMHHj16pLV9+fLllCtXDnNzc8qWLcvixYt1bosQQrwLyflvJjlf6DspAkSGLCwseP78uebz7t27iYyMJDg4mKCgIJKTk/Hw8MDa2pq///6bQ4cOkTdvXpo2barZb9asWQQGBrJixQoOHjxIbGwsGzdufO15u3fvzi+//ML8+fOJiIjghx9+IG/evBQpUoQ//vgDgMjISO7evcu8efMACAgIYPXq1SxdupRz584xbNgwunbtyv79+wH1F1fbtm1p2bIl4eHh9O7dm1GjRun8M7G2tiYwMJDz588zb948fvzxR+bMmaMVc+nSJdatW8eWLVvYsWMHJ0+eZMCAAZrta9aswd/fn++++46IiAi+//57xo0bx6pVq3RujxBCZBXJ+elJzhd6TxEGz8vLS2ndurWiKIqSlpamBAcHK2ZmZsrw4cM12x0dHZWkpCTNPj///LNSpkwZJS0tTbMuKSlJsbCwUHbu3KkoiqIUKlRImT59umZ7cnKyUrhwYc25FEVRGjZsqAwZMkRRFEWJjIxUACU4ODjDdu7du1cBlIcPH2rWPXv2TLG0tFQOHz6sFevt7a106tRJURRFGT16tFK+fHmt7X5+fumO9V+AsnHjxldunzFjhuLq6qr5PH78eCVPnjzKrVu3NOu2b9+uGBkZKXfv3lUURVFKliyprF27Vus4kydPVtzc3BRFUZSrV68qgHLy5MlXnlcIId6F5PyMSc4XhkbeCRAABAUFkTdvXpKTk0lLS6Nz585MmDBBs71SpUpaz4SeOnWKS5cuYW1trXWcZ8+ecfnyZR49esTdu3epVauWZpuxsTHVq1dP1z38Qnh4OHny5KFhw4aZbvelS5d48uQJn3/+udb658+fU7VqVQAiIiK02gHg5uaW6XO88NtvvzF//nwuX75MQkICKSkp2NjYaMUULVqUjz76SOs8aWlpREZGYm1tzeXLl/H29qZPnz6amJSUFGxtbXVujxBCvC3J+W8mOV/oOykCBACNGjViyZIlmJqa4uzsjLGx9n8aVlZWWp8TEhJwdXVlzZo16Y5VsGDBt2qDhYWFzvskJCQAsHXrVq1EDOpnXrNKSEgIXbp0YeLEiXh4eGBra8uvv/7KrFmzdG7rjz/+mO4LKk+ePFnWViGEeBPJ+a8nOV8YAikCBKBO+KVKlcp0fLVq1fjtt99wcHBId2fkhUKFChEaGkqDBg0A9d2PsLAwqlWrlmF8pUqVSEtLY//+/bi7u6fb/uKuVGpqqmZd+fLlMTMz48aNG6+8m1SuXDnNC28vHDly5M0X+ZLDhw9TrFgxxowZo1l3/fr1dHE3btzgzp07ODs7a85jZGREmTJlcHR0xNnZmStXrtClSxedzi+EEFlJcv7rSc4XhkBeDBZvpUuXLhQoUIDWrVvz999/c/XqVfbt28fgwYO5desWAEOGDGHq1Kls2rSJCxcuMGDAgNeO91y8eHG8vLzo1asXmzZt0hxz3bp1ABQrVgyVSkVQUBD37t0jISEBa2trhg8fzrBhw1i1ahWXL1/mxIkTLFiwQPPiVb9+/bh48SIjRowgMjKStWvXEhgYqNP1li5dmhs3bvDrr79y+fJl5s+fn+ELb+bm5nh5eXHq1Cn+/vtvBg8eTIcOHXBycgJg4sSJBAQEMH/+fP755x/OnDnDypUrmT17tk7tEUKInCQ5X3K+0EO5/VKCyH0vvySmy/a7d+8q3bt3VwoUKKCYmZkpJUqUUPr06aM8evRIURT1S2FDhgxRbGxsFDs7O8XX11fp3r37K18SUxRFefr0qTJs2DClUKFCiqmpqVKqVCllxYoVmu2TJk1SnJycFJVKpXh5eSmKon6xbe7cuUqZMmUUExMTpWDBgoqHh4eyf/9+zX5btmxRSpUqpZiZmSn169dXVqxYofNLYiNGjFDy58+v5M2bV/nqq6+UOXPmKLa2tprt48ePVypXrqwsXrxYcXZ2VszNzZX27dsrsbGxWsdds2aNUqVKFcXU1FTJly+f0qBBA2XDhg2KoshLYkKI7Cc5P2OS84WhUSnKK97YEUIIIYQQQugleRxICCGEEEIIAyNFgBBCCCGEEAZGigAhhBBCCCEMjBQBQgghhBBCGBgpAoQQQgghhDAwUgQIIYQQQghhYKQIEEIIIYQQwsBIESCEEEIIIYSBkSJACCGEEEIIAyNFgBBCCCGEEAZGigAhhBBCCCEMzP8Bv+QzEQTzbE0AAAAASUVORK5CYII=\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[1mModel performance:\u001b[0m\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7fe22ebbf610>"
            ],
            "text/html": [
              "<style type=\"text/css\">\n",
              "#T_bc077 th {\n",
              "  max-width: 75px;\n",
              "}\n",
              "</style>\n",
              "<table id=\"T_bc077\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th class=\"blank level0\" >&nbsp;</th>\n",
              "      <th id=\"T_bc077_level0_col0\" class=\"col_heading level0 col0\" >Accuracy</th>\n",
              "      <th id=\"T_bc077_level0_col1\" class=\"col_heading level0 col1\" >Precision</th>\n",
              "      <th id=\"T_bc077_level0_col2\" class=\"col_heading level0 col2\" >Recall</th>\n",
              "      <th id=\"T_bc077_level0_col3\" class=\"col_heading level0 col3\" >NPV</th>\n",
              "      <th id=\"T_bc077_level0_col4\" class=\"col_heading level0 col4\" >Specificity</th>\n",
              "      <th id=\"T_bc077_level0_col5\" class=\"col_heading level0 col5\" >F1</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th id=\"T_bc077_level0_row0\" class=\"row_heading level0 row0\" >Training</th>\n",
              "      <td id=\"T_bc077_row0_col0\" class=\"data row0 col0\" >99.99%</td>\n",
              "      <td id=\"T_bc077_row0_col1\" class=\"data row0 col1\" >100.00%</td>\n",
              "      <td id=\"T_bc077_row0_col2\" class=\"data row0 col2\" >99.88%</td>\n",
              "      <td id=\"T_bc077_row0_col3\" class=\"data row0 col3\" >99.99%</td>\n",
              "      <td id=\"T_bc077_row0_col4\" class=\"data row0 col4\" >100.00%</td>\n",
              "      <td id=\"T_bc077_row0_col5\" class=\"data row0 col5\" >99.94%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_bc077_level0_row1\" class=\"row_heading level0 row1\" >Validation</th>\n",
              "      <td id=\"T_bc077_row1_col0\" class=\"data row1 col0\" >98.60%</td>\n",
              "      <td id=\"T_bc077_row1_col1\" class=\"data row1 col1\" >98.59%</td>\n",
              "      <td id=\"T_bc077_row1_col2\" class=\"data row1 col2\" >75.81%</td>\n",
              "      <td id=\"T_bc077_row1_col3\" class=\"data row1 col3\" >98.60%</td>\n",
              "      <td id=\"T_bc077_row1_col4\" class=\"data row1 col4\" >99.94%</td>\n",
              "      <td id=\"T_bc077_row1_col5\" class=\"data row1 col5\" >85.71%</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "\u001b[2;37;42mBaggingClassifier:                                                                                    \u001b[0m\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 900x300 with 4 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[1mModel performance:\u001b[0m\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7fe22eff34f0>"
            ],
            "text/html": [
              "<style type=\"text/css\">\n",
              "#T_e8a7a th {\n",
              "  max-width: 75px;\n",
              "}\n",
              "</style>\n",
              "<table id=\"T_e8a7a\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th class=\"blank level0\" >&nbsp;</th>\n",
              "      <th id=\"T_e8a7a_level0_col0\" class=\"col_heading level0 col0\" >Accuracy</th>\n",
              "      <th id=\"T_e8a7a_level0_col1\" class=\"col_heading level0 col1\" >Precision</th>\n",
              "      <th id=\"T_e8a7a_level0_col2\" class=\"col_heading level0 col2\" >Recall</th>\n",
              "      <th id=\"T_e8a7a_level0_col3\" class=\"col_heading level0 col3\" >NPV</th>\n",
              "      <th id=\"T_e8a7a_level0_col4\" class=\"col_heading level0 col4\" >Specificity</th>\n",
              "      <th id=\"T_e8a7a_level0_col5\" class=\"col_heading level0 col5\" >F1</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th id=\"T_e8a7a_level0_row0\" class=\"row_heading level0 row0\" >Training</th>\n",
              "      <td id=\"T_e8a7a_row0_col0\" class=\"data row0 col0\" >99.76%</td>\n",
              "      <td id=\"T_e8a7a_row0_col1\" class=\"data row0 col1\" >99.87%</td>\n",
              "      <td id=\"T_e8a7a_row0_col2\" class=\"data row0 col2\" >95.80%</td>\n",
              "      <td id=\"T_e8a7a_row0_col3\" class=\"data row0 col3\" >99.75%</td>\n",
              "      <td id=\"T_e8a7a_row0_col4\" class=\"data row0 col4\" >99.99%</td>\n",
              "      <td id=\"T_e8a7a_row0_col5\" class=\"data row0 col5\" >97.79%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e8a7a_level0_row1\" class=\"row_heading level0 row1\" >Validation</th>\n",
              "      <td id=\"T_e8a7a_row1_col0\" class=\"data row1 col0\" >98.20%</td>\n",
              "      <td id=\"T_e8a7a_row1_col1\" class=\"data row1 col1\" >95.61%</td>\n",
              "      <td id=\"T_e8a7a_row1_col2\" class=\"data row1 col2\" >70.76%</td>\n",
              "      <td id=\"T_e8a7a_row1_col3\" class=\"data row1 col3\" >98.31%</td>\n",
              "      <td id=\"T_e8a7a_row1_col4\" class=\"data row1 col4\" >99.81%</td>\n",
              "      <td id=\"T_e8a7a_row1_col5\" class=\"data row1 col5\" >81.33%</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "\u001b[2;37;42mAdaBoostClassifier:                                                                                   \u001b[0m\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 900x300 with 4 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[1mModel performance:\u001b[0m\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7fe22eea9570>"
            ],
            "text/html": [
              "<style type=\"text/css\">\n",
              "#T_d76eb th {\n",
              "  max-width: 75px;\n",
              "}\n",
              "</style>\n",
              "<table id=\"T_d76eb\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th class=\"blank level0\" >&nbsp;</th>\n",
              "      <th id=\"T_d76eb_level0_col0\" class=\"col_heading level0 col0\" >Accuracy</th>\n",
              "      <th id=\"T_d76eb_level0_col1\" class=\"col_heading level0 col1\" >Precision</th>\n",
              "      <th id=\"T_d76eb_level0_col2\" class=\"col_heading level0 col2\" >Recall</th>\n",
              "      <th id=\"T_d76eb_level0_col3\" class=\"col_heading level0 col3\" >NPV</th>\n",
              "      <th id=\"T_d76eb_level0_col4\" class=\"col_heading level0 col4\" >Specificity</th>\n",
              "      <th id=\"T_d76eb_level0_col5\" class=\"col_heading level0 col5\" >F1</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th id=\"T_d76eb_level0_row0\" class=\"row_heading level0 row0\" >Training</th>\n",
              "      <td id=\"T_d76eb_row0_col0\" class=\"data row0 col0\" >97.63%</td>\n",
              "      <td id=\"T_d76eb_row0_col1\" class=\"data row0 col1\" >89.31%</td>\n",
              "      <td id=\"T_d76eb_row0_col2\" class=\"data row0 col2\" >65.19%</td>\n",
              "      <td id=\"T_d76eb_row0_col3\" class=\"data row0 col3\" >97.98%</td>\n",
              "      <td id=\"T_d76eb_row0_col4\" class=\"data row0 col4\" >99.54%</td>\n",
              "      <td id=\"T_d76eb_row0_col5\" class=\"data row0 col5\" >75.36%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_d76eb_level0_row1\" class=\"row_heading level0 row1\" >Validation</th>\n",
              "      <td id=\"T_d76eb_row1_col0\" class=\"data row1 col0\" >97.76%</td>\n",
              "      <td id=\"T_d76eb_row1_col1\" class=\"data row1 col1\" >90.64%</td>\n",
              "      <td id=\"T_d76eb_row1_col2\" class=\"data row1 col2\" >66.43%</td>\n",
              "      <td id=\"T_d76eb_row1_col3\" class=\"data row1 col3\" >98.06%</td>\n",
              "      <td id=\"T_d76eb_row1_col4\" class=\"data row1 col4\" >99.60%</td>\n",
              "      <td id=\"T_d76eb_row1_col5\" class=\"data row1 col5\" >76.67%</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "\u001b[2;37;42mGradientBoostingClassifier:                                                                           \u001b[0m\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 900x300 with 4 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[1mModel performance:\u001b[0m\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7fe22e1ce710>"
            ],
            "text/html": [
              "<style type=\"text/css\">\n",
              "#T_1cd6b th {\n",
              "  max-width: 75px;\n",
              "}\n",
              "</style>\n",
              "<table id=\"T_1cd6b\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th class=\"blank level0\" >&nbsp;</th>\n",
              "      <th id=\"T_1cd6b_level0_col0\" class=\"col_heading level0 col0\" >Accuracy</th>\n",
              "      <th id=\"T_1cd6b_level0_col1\" class=\"col_heading level0 col1\" >Precision</th>\n",
              "      <th id=\"T_1cd6b_level0_col2\" class=\"col_heading level0 col2\" >Recall</th>\n",
              "      <th id=\"T_1cd6b_level0_col3\" class=\"col_heading level0 col3\" >NPV</th>\n",
              "      <th id=\"T_1cd6b_level0_col4\" class=\"col_heading level0 col4\" >Specificity</th>\n",
              "      <th id=\"T_1cd6b_level0_col5\" class=\"col_heading level0 col5\" >F1</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th id=\"T_1cd6b_level0_row0\" class=\"row_heading level0 row0\" >Training</th>\n",
              "      <td id=\"T_1cd6b_row0_col0\" class=\"data row0 col0\" >98.78%</td>\n",
              "      <td id=\"T_1cd6b_row0_col1\" class=\"data row0 col1\" >97.51%</td>\n",
              "      <td id=\"T_1cd6b_row0_col2\" class=\"data row0 col2\" >80.07%</td>\n",
              "      <td id=\"T_1cd6b_row0_col3\" class=\"data row0 col3\" >98.84%</td>\n",
              "      <td id=\"T_1cd6b_row0_col4\" class=\"data row0 col4\" >99.88%</td>\n",
              "      <td id=\"T_1cd6b_row0_col5\" class=\"data row0 col5\" >87.94%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_1cd6b_level0_row1\" class=\"row_heading level0 row1\" >Validation</th>\n",
              "      <td id=\"T_1cd6b_row1_col0\" class=\"data row1 col0\" >98.28%</td>\n",
              "      <td id=\"T_1cd6b_row1_col1\" class=\"data row1 col1\" >95.69%</td>\n",
              "      <td id=\"T_1cd6b_row1_col2\" class=\"data row1 col2\" >72.20%</td>\n",
              "      <td id=\"T_1cd6b_row1_col3\" class=\"data row1 col3\" >98.39%</td>\n",
              "      <td id=\"T_1cd6b_row1_col4\" class=\"data row1 col4\" >99.81%</td>\n",
              "      <td id=\"T_1cd6b_row1_col5\" class=\"data row1 col5\" >82.30%</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "\u001b[2;37;42mXGBClassifier:                                                                                        \u001b[0m\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 900x300 with 4 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[1mModel performance:\u001b[0m\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7fe22e8300a0>"
            ],
            "text/html": [
              "<style type=\"text/css\">\n",
              "#T_6cada th {\n",
              "  max-width: 75px;\n",
              "}\n",
              "</style>\n",
              "<table id=\"T_6cada\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th class=\"blank level0\" >&nbsp;</th>\n",
              "      <th id=\"T_6cada_level0_col0\" class=\"col_heading level0 col0\" >Accuracy</th>\n",
              "      <th id=\"T_6cada_level0_col1\" class=\"col_heading level0 col1\" >Precision</th>\n",
              "      <th id=\"T_6cada_level0_col2\" class=\"col_heading level0 col2\" >Recall</th>\n",
              "      <th id=\"T_6cada_level0_col3\" class=\"col_heading level0 col3\" >NPV</th>\n",
              "      <th id=\"T_6cada_level0_col4\" class=\"col_heading level0 col4\" >Specificity</th>\n",
              "      <th id=\"T_6cada_level0_col5\" class=\"col_heading level0 col5\" >F1</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th id=\"T_6cada_level0_row0\" class=\"row_heading level0 row0\" >Training</th>\n",
              "      <td id=\"T_6cada_row0_col0\" class=\"data row0 col0\" >100.00%</td>\n",
              "      <td id=\"T_6cada_row0_col1\" class=\"data row0 col1\" >100.00%</td>\n",
              "      <td id=\"T_6cada_row0_col2\" class=\"data row0 col2\" >100.00%</td>\n",
              "      <td id=\"T_6cada_row0_col3\" class=\"data row0 col3\" >100.00%</td>\n",
              "      <td id=\"T_6cada_row0_col4\" class=\"data row0 col4\" >100.00%</td>\n",
              "      <td id=\"T_6cada_row0_col5\" class=\"data row0 col5\" >100.00%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6cada_level0_row1\" class=\"row_heading level0 row1\" >Validation</th>\n",
              "      <td id=\"T_6cada_row1_col0\" class=\"data row1 col0\" >98.96%</td>\n",
              "      <td id=\"T_6cada_row1_col1\" class=\"data row1 col1\" >97.07%</td>\n",
              "      <td id=\"T_6cada_row1_col2\" class=\"data row1 col2\" >83.75%</td>\n",
              "      <td id=\"T_6cada_row1_col3\" class=\"data row1 col3\" >99.05%</td>\n",
              "      <td id=\"T_6cada_row1_col4\" class=\"data row1 col4\" >99.85%</td>\n",
              "      <td id=\"T_6cada_row1_col5\" class=\"data row1 col5\" >89.92%</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "res_orig = cv_simple(models_grid, X_train, y_train, X_valid, y_valid, title='Original')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 50,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 488
        },
        "id": "lsHY3UKGX0B4",
        "outputId": "7094b7b9-2a7d-4f14-ebab-898f815b7f0e"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "         index  Accuracy  Precision    Recall       NPV  Specificity  \\\n",
              "0     Training  1.000000   1.000000  1.000000  1.000000     1.000000   \n",
              "1   Validation  0.969200   0.717314  0.732852  0.984312     0.983062   \n",
              "2     Training  0.966467   0.842324  0.487395  0.970588     0.994635   \n",
              "3   Validation  0.966600   0.881944  0.458484  0.969110     0.996401   \n",
              "4     Training  0.999933   1.000000  0.998800  0.999929     1.000000   \n",
              "5   Validation  0.986000   0.985915  0.758123  0.986004     0.999365   \n",
              "6     Training  0.997600   0.998748  0.957983  0.997535     0.999929   \n",
              "7   Validation  0.982000   0.956098  0.707581  0.983107     0.998094   \n",
              "8     Training  0.976333   0.893092  0.651861  0.979850     0.995412   \n",
              "9   Validation  0.977600   0.906404  0.664260  0.980613     0.995977   \n",
              "10    Training  0.987800   0.975146  0.800720  0.988405     0.998800   \n",
              "11  Validation  0.982800   0.956938  0.722022  0.983928     0.998094   \n",
              "12    Training  1.000000   1.000000  1.000000  1.000000     1.000000   \n",
              "13  Validation  0.989600   0.970711  0.837545  0.990548     0.998518   \n",
              "\n",
              "          F1    duration  cv_recall                       model  \n",
              "0   1.000000   18.276706   0.740620      DecisionTreeClassifier  \n",
              "1   0.725000    2.138366        NaN      DecisionTreeClassifier  \n",
              "2   0.617490    0.587506   0.489802          LogisticRegression  \n",
              "3   0.603325    0.058208        NaN          LogisticRegression  \n",
              "4   0.999399  139.675461   0.727496      RandomForestClassifier  \n",
              "5   0.857143   15.562946        NaN      RandomForestClassifier  \n",
              "6   0.977941  108.716687   0.708161           BaggingClassifier  \n",
              "7   0.813278   12.694744        NaN           BaggingClassifier  \n",
              "8   0.753643   48.776676   0.596644          AdaBoostClassifier  \n",
              "9   0.766667    5.226020        NaN          AdaBoostClassifier  \n",
              "10  0.879367  242.121486   0.696328  GradientBoostingClassifier  \n",
              "11  0.823045   26.894625        NaN  GradientBoostingClassifier  \n",
              "12  1.000000  106.620129   0.795869               XGBClassifier  \n",
              "13  0.899225   11.581028        NaN               XGBClassifier  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-2baa0406-48d4-48e9-97ae-db98e35e53a8\">\n",
              "    <div 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>index</th>\n",
              "      <th>Accuracy</th>\n",
              "      <th>Precision</th>\n",
              "      <th>Recall</th>\n",
              "      <th>NPV</th>\n",
              "      <th>Specificity</th>\n",
              "      <th>F1</th>\n",
              "      <th>duration</th>\n",
              "      <th>cv_recall</th>\n",
              "      <th>model</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Training</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>18.276706</td>\n",
              "      <td>0.740620</td>\n",
              "      <td>DecisionTreeClassifier</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Validation</td>\n",
              "      <td>0.969200</td>\n",
              "      <td>0.717314</td>\n",
              "      <td>0.732852</td>\n",
              "      <td>0.984312</td>\n",
              "      <td>0.983062</td>\n",
              "      <td>0.725000</td>\n",
              "      <td>2.138366</td>\n",
              "      <td>NaN</td>\n",
              "      <td>DecisionTreeClassifier</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Training</td>\n",
              "      <td>0.966467</td>\n",
              "      <td>0.842324</td>\n",
              "      <td>0.487395</td>\n",
              "      <td>0.970588</td>\n",
              "      <td>0.994635</td>\n",
              "      <td>0.617490</td>\n",
              "      <td>0.587506</td>\n",
              "      <td>0.489802</td>\n",
              "      <td>LogisticRegression</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Validation</td>\n",
              "      <td>0.966600</td>\n",
              "      <td>0.881944</td>\n",
              "      <td>0.458484</td>\n",
              "      <td>0.969110</td>\n",
              "      <td>0.996401</td>\n",
              "      <td>0.603325</td>\n",
              "      <td>0.058208</td>\n",
              "      <td>NaN</td>\n",
              "      <td>LogisticRegression</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Training</td>\n",
              "      <td>0.999933</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.998800</td>\n",
              "      <td>0.999929</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.999399</td>\n",
              "      <td>139.675461</td>\n",
              "      <td>0.727496</td>\n",
              "      <td>RandomForestClassifier</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Validation</td>\n",
              "      <td>0.986000</td>\n",
              "      <td>0.985915</td>\n",
              "      <td>0.758123</td>\n",
              "      <td>0.986004</td>\n",
              "      <td>0.999365</td>\n",
              "      <td>0.857143</td>\n",
              "      <td>15.562946</td>\n",
              "      <td>NaN</td>\n",
              "      <td>RandomForestClassifier</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>Training</td>\n",
              "      <td>0.997600</td>\n",
              "      <td>0.998748</td>\n",
              "      <td>0.957983</td>\n",
              "      <td>0.997535</td>\n",
              "      <td>0.999929</td>\n",
              "      <td>0.977941</td>\n",
              "      <td>108.716687</td>\n",
              "      <td>0.708161</td>\n",
              "      <td>BaggingClassifier</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>Validation</td>\n",
              "      <td>0.982000</td>\n",
              "      <td>0.956098</td>\n",
              "      <td>0.707581</td>\n",
              "      <td>0.983107</td>\n",
              "      <td>0.998094</td>\n",
              "      <td>0.813278</td>\n",
              "      <td>12.694744</td>\n",
              "      <td>NaN</td>\n",
              "      <td>BaggingClassifier</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>Training</td>\n",
              "      <td>0.976333</td>\n",
              "      <td>0.893092</td>\n",
              "      <td>0.651861</td>\n",
              "      <td>0.979850</td>\n",
              "      <td>0.995412</td>\n",
              "      <td>0.753643</td>\n",
              "      <td>48.776676</td>\n",
              "      <td>0.596644</td>\n",
              "      <td>AdaBoostClassifier</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>Validation</td>\n",
              "      <td>0.977600</td>\n",
              "      <td>0.906404</td>\n",
              "      <td>0.664260</td>\n",
              "      <td>0.980613</td>\n",
              "      <td>0.995977</td>\n",
              "      <td>0.766667</td>\n",
              "      <td>5.226020</td>\n",
              "      <td>NaN</td>\n",
              "      <td>AdaBoostClassifier</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>Training</td>\n",
              "      <td>0.987800</td>\n",
              "      <td>0.975146</td>\n",
              "      <td>0.800720</td>\n",
              "      <td>0.988405</td>\n",
              "      <td>0.998800</td>\n",
              "      <td>0.879367</td>\n",
              "      <td>242.121486</td>\n",
              "      <td>0.696328</td>\n",
              "      <td>GradientBoostingClassifier</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>Validation</td>\n",
              "      <td>0.982800</td>\n",
              "      <td>0.956938</td>\n",
              "      <td>0.722022</td>\n",
              "      <td>0.983928</td>\n",
              "      <td>0.998094</td>\n",
              "      <td>0.823045</td>\n",
              "      <td>26.894625</td>\n",
              "      <td>NaN</td>\n",
              "      <td>GradientBoostingClassifier</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>Training</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>106.620129</td>\n",
              "      <td>0.795869</td>\n",
              "      <td>XGBClassifier</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>Validation</td>\n",
              "      <td>0.989600</td>\n",
              "      <td>0.970711</td>\n",
              "      <td>0.837545</td>\n",
              "      <td>0.990548</td>\n",
              "      <td>0.998518</td>\n",
              "      <td>0.899225</td>\n",
              "      <td>11.581028</td>\n",
              "      <td>NaN</td>\n",
              "      <td>XGBClassifier</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
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            ]
          },
          "metadata": {},
          "execution_count": 50
        }
      ],
      "source": [
        "res_orig"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "XH_7yK5MQmac"
      },
      "source": [
        "**Observations:**\n",
        "* **XGBClassifier** performs best on both the training and validation datasets, making it the most promising model for this dataset.\n",
        "\n",
        "* **RandomForestClassifier** and **DecisionTreeClassifier** also demonstrate good performance on both datasets, and they could be considered as alternative models.\n",
        "\n",
        "* **GradientBoostingClassifier** and **BaggingClassifier** exhibit moderate performance on the training dataset and reasonable performance on the validation dataset.\n",
        "\n",
        "* **LogisticRegression** and **AdaBoostClassifier** show below-average performance on both the training and validation datasets, indicating that they may not be suitable models for this specific problem.\n",
        "\n",
        "* The decision-tree-based algorithms (DecisionTreeClassifier, BaggingClassifier, RandomForestClassifier) seem to exhibit overfitting, as evidenced by the high recall on the training set, approaching or equal to 1, in contrast to the considerably lower recall observed on the validation dataset.\n",
        "\n",
        "* The initial models employing boosting algorithms show no significant overfitting, as evidenced by their consistent performance on both the training and validation datasets.\n",
        "\n",
        "* The **XGBClassifier** model demonstrates very good performance in terms of recall on the validation dataset compared to other models. This indicates that it is the most effective at identifying true positives, minimizing the number of false negatives.\n",
        "\n",
        "* Among the models in our training data, the median recall score of **XGBClassifier** is the highest.\n",
        "\n",
        "* In addition to delivering the highest recall score for the validation dataset, the **XGBClassifier** model has a relatively efficient learning duration. While some other models take longer to train, **XGBClassifier** achieves superior performance with a shorter training time, making it a more time-effective choice. This balance between performance and learning duration emphasizes the suitability of **XGBClassifier** for our problem.\n",
        "\n",
        "* Given these findings, **XGBClassifier** is the top-performing model for our dataset. However, **RandomForestClassifier** and **DecisionTreeClassifier** could also be viable options if properly optimized."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "oBKJaFU24jas"
      },
      "source": [
        "### Model Building with Oversampled data\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 51,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "RWeUIolSGL9h",
        "outputId": "cd196319-ec45-4045-89e5-d470dcd1dbac"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "Cross-Validation performance on training dataset:\n",
            "\n",
            "\tDecisionTreeClassifier: 0.97184\n",
            "\t\tIteration duration: 21.93 seconds\n",
            "\tLogisticRegression: 0.87393\n",
            "\t\tIteration duration: 1.37 seconds\n",
            "\tRandomForestClassifier: 0.98482\n",
            "\t\tIteration duration: 191.60 seconds\n",
            "\tBaggingClassifier: 0.97551\n",
            "\t\tIteration duration: 137.09 seconds\n",
            "\tAdaBoostClassifier: 0.89229\n",
            "\t\tIteration duration: 96.17 seconds\n",
            "\tGradientBoostingClassifier: 0.92398\n",
            "\t\tIteration duration: 468.36 seconds\n",
            "\tXGBClassifier: 0.99054\n",
            "\t\tIteration duration: 226.97 seconds\n",
            "\n",
            "Validation Performance:\n",
            "\n",
            "\tDecisionTreeClassifier: 0.76534\n",
            "\t\tIteration duration: 2.58 seconds\n",
            "\tLogisticRegression: 0.87726\n",
            "\t\tIteration duration: 0.19 seconds\n",
            "\tRandomForestClassifier: 0.85921\n",
            "\t\tIteration duration: 21.77 seconds\n",
            "\tBaggingClassifier: 0.83032\n",
            "\t\tIteration duration: 15.60 seconds\n",
            "\tAdaBoostClassifier: 0.88809\n",
            "\t\tIteration duration: 11.02 seconds\n",
            "\tGradientBoostingClassifier: 0.89531\n",
            "\t\tIteration duration: 52.77 seconds\n",
            "\tXGBClassifier: 0.89170\n",
            "\t\tIteration duration: 25.28 seconds\n",
            "\n",
            "\u001b[2;37;42mDecisionTreeClassifier:                                                                               \u001b[0m\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 900x300 with 4 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[1mModel performance:\u001b[0m\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7fe22efc7f40>"
            ],
            "text/html": [
              "<style type=\"text/css\">\n",
              "#T_12814 th {\n",
              "  max-width: 75px;\n",
              "}\n",
              "</style>\n",
              "<table id=\"T_12814\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th class=\"blank level0\" >&nbsp;</th>\n",
              "      <th id=\"T_12814_level0_col0\" class=\"col_heading level0 col0\" >Accuracy</th>\n",
              "      <th id=\"T_12814_level0_col1\" class=\"col_heading level0 col1\" >Precision</th>\n",
              "      <th id=\"T_12814_level0_col2\" class=\"col_heading level0 col2\" >Recall</th>\n",
              "      <th id=\"T_12814_level0_col3\" class=\"col_heading level0 col3\" >NPV</th>\n",
              "      <th id=\"T_12814_level0_col4\" class=\"col_heading level0 col4\" >Specificity</th>\n",
              "      <th id=\"T_12814_level0_col5\" class=\"col_heading level0 col5\" >F1</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th id=\"T_12814_level0_row0\" class=\"row_heading level0 row0\" >Training</th>\n",
              "      <td id=\"T_12814_row0_col0\" class=\"data row0 col0\" >100.00%</td>\n",
              "      <td id=\"T_12814_row0_col1\" class=\"data row0 col1\" >100.00%</td>\n",
              "      <td id=\"T_12814_row0_col2\" class=\"data row0 col2\" >100.00%</td>\n",
              "      <td id=\"T_12814_row0_col3\" class=\"data row0 col3\" >100.00%</td>\n",
              "      <td id=\"T_12814_row0_col4\" class=\"data row0 col4\" >100.00%</td>\n",
              "      <td id=\"T_12814_row0_col5\" class=\"data row0 col5\" >100.00%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_12814_level0_row1\" class=\"row_heading level0 row1\" >Validation</th>\n",
              "      <td id=\"T_12814_row1_col0\" class=\"data row1 col0\" >94.20%</td>\n",
              "      <td id=\"T_12814_row1_col1\" class=\"data row1 col1\" >48.51%</td>\n",
              "      <td id=\"T_12814_row1_col2\" class=\"data row1 col2\" >76.53%</td>\n",
              "      <td id=\"T_12814_row1_col3\" class=\"data row1 col3\" >98.58%</td>\n",
              "      <td id=\"T_12814_row1_col4\" class=\"data row1 col4\" >95.24%</td>\n",
              "      <td id=\"T_12814_row1_col5\" class=\"data row1 col5\" >59.38%</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "\u001b[2;37;42mLogisticRegression:                                                                                   \u001b[0m\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 900x300 with 4 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[1mModel performance:\u001b[0m\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7fe22ef69bd0>"
            ],
            "text/html": [
              "<style type=\"text/css\">\n",
              "#T_a0d0c th {\n",
              "  max-width: 75px;\n",
              "}\n",
              "</style>\n",
              "<table id=\"T_a0d0c\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th class=\"blank level0\" >&nbsp;</th>\n",
              "      <th id=\"T_a0d0c_level0_col0\" class=\"col_heading level0 col0\" >Accuracy</th>\n",
              "      <th id=\"T_a0d0c_level0_col1\" class=\"col_heading level0 col1\" >Precision</th>\n",
              "      <th id=\"T_a0d0c_level0_col2\" class=\"col_heading level0 col2\" >Recall</th>\n",
              "      <th id=\"T_a0d0c_level0_col3\" class=\"col_heading level0 col3\" >NPV</th>\n",
              "      <th id=\"T_a0d0c_level0_col4\" class=\"col_heading level0 col4\" >Specificity</th>\n",
              "      <th id=\"T_a0d0c_level0_col5\" class=\"col_heading level0 col5\" >F1</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th id=\"T_a0d0c_level0_row0\" class=\"row_heading level0 row0\" >Training</th>\n",
              "      <td id=\"T_a0d0c_row0_col0\" class=\"data row0 col0\" >87.45%</td>\n",
              "      <td id=\"T_a0d0c_row0_col1\" class=\"data row0 col1\" >87.46%</td>\n",
              "      <td id=\"T_a0d0c_row0_col2\" class=\"data row0 col2\" >87.43%</td>\n",
              "      <td id=\"T_a0d0c_row0_col3\" class=\"data row0 col3\" >87.43%</td>\n",
              "      <td id=\"T_a0d0c_row0_col4\" class=\"data row0 col4\" >87.46%</td>\n",
              "      <td id=\"T_a0d0c_row0_col5\" class=\"data row0 col5\" >87.44%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_a0d0c_level0_row1\" class=\"row_heading level0 row1\" >Validation</th>\n",
              "      <td id=\"T_a0d0c_row1_col0\" class=\"data row1 col0\" >87.88%</td>\n",
              "      <td id=\"T_a0d0c_row1_col1\" class=\"data row1 col1\" >29.82%</td>\n",
              "      <td id=\"T_a0d0c_row1_col2\" class=\"data row1 col2\" >87.73%</td>\n",
              "      <td id=\"T_a0d0c_row1_col3\" class=\"data row1 col3\" >99.19%</td>\n",
              "      <td id=\"T_a0d0c_row1_col4\" class=\"data row1 col4\" >87.89%</td>\n",
              "      <td id=\"T_a0d0c_row1_col5\" class=\"data row1 col5\" >44.51%</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "\u001b[2;37;42mRandomForestClassifier:                                                                               \u001b[0m\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 900x300 with 4 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[1mModel performance:\u001b[0m\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7fe22e90fd90>"
            ],
            "text/html": [
              "<style type=\"text/css\">\n",
              "#T_bcbe0 th {\n",
              "  max-width: 75px;\n",
              "}\n",
              "</style>\n",
              "<table id=\"T_bcbe0\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th class=\"blank level0\" >&nbsp;</th>\n",
              "      <th id=\"T_bcbe0_level0_col0\" class=\"col_heading level0 col0\" >Accuracy</th>\n",
              "      <th id=\"T_bcbe0_level0_col1\" class=\"col_heading level0 col1\" >Precision</th>\n",
              "      <th id=\"T_bcbe0_level0_col2\" class=\"col_heading level0 col2\" >Recall</th>\n",
              "      <th id=\"T_bcbe0_level0_col3\" class=\"col_heading level0 col3\" >NPV</th>\n",
              "      <th id=\"T_bcbe0_level0_col4\" class=\"col_heading level0 col4\" >Specificity</th>\n",
              "      <th id=\"T_bcbe0_level0_col5\" class=\"col_heading level0 col5\" >F1</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th id=\"T_bcbe0_level0_row0\" class=\"row_heading level0 row0\" >Training</th>\n",
              "      <td id=\"T_bcbe0_row0_col0\" class=\"data row0 col0\" >100.00%</td>\n",
              "      <td id=\"T_bcbe0_row0_col1\" class=\"data row0 col1\" >100.00%</td>\n",
              "      <td id=\"T_bcbe0_row0_col2\" class=\"data row0 col2\" >100.00%</td>\n",
              "      <td id=\"T_bcbe0_row0_col3\" class=\"data row0 col3\" >100.00%</td>\n",
              "      <td id=\"T_bcbe0_row0_col4\" class=\"data row0 col4\" >100.00%</td>\n",
              "      <td id=\"T_bcbe0_row0_col5\" class=\"data row0 col5\" >100.00%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_bcbe0_level0_row1\" class=\"row_heading level0 row1\" >Validation</th>\n",
              "      <td id=\"T_bcbe0_row1_col0\" class=\"data row1 col0\" >98.88%</td>\n",
              "      <td id=\"T_bcbe0_row1_col1\" class=\"data row1 col1\" >93.33%</td>\n",
              "      <td id=\"T_bcbe0_row1_col2\" class=\"data row1 col2\" >85.92%</td>\n",
              "      <td id=\"T_bcbe0_row1_col3\" class=\"data row1 col3\" >99.18%</td>\n",
              "      <td id=\"T_bcbe0_row1_col4\" class=\"data row1 col4\" >99.64%</td>\n",
              "      <td id=\"T_bcbe0_row1_col5\" class=\"data row1 col5\" >89.47%</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "\u001b[2;37;42mBaggingClassifier:                                                                                    \u001b[0m\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 900x300 with 4 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[1mModel performance:\u001b[0m\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7fe22e90fa90>"
            ],
            "text/html": [
              "<style type=\"text/css\">\n",
              "#T_5227f th {\n",
              "  max-width: 75px;\n",
              "}\n",
              "</style>\n",
              "<table id=\"T_5227f\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th class=\"blank level0\" >&nbsp;</th>\n",
              "      <th id=\"T_5227f_level0_col0\" class=\"col_heading level0 col0\" >Accuracy</th>\n",
              "      <th id=\"T_5227f_level0_col1\" class=\"col_heading level0 col1\" >Precision</th>\n",
              "      <th id=\"T_5227f_level0_col2\" class=\"col_heading level0 col2\" >Recall</th>\n",
              "      <th id=\"T_5227f_level0_col3\" class=\"col_heading level0 col3\" >NPV</th>\n",
              "      <th id=\"T_5227f_level0_col4\" class=\"col_heading level0 col4\" >Specificity</th>\n",
              "      <th id=\"T_5227f_level0_col5\" class=\"col_heading level0 col5\" >F1</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th id=\"T_5227f_level0_row0\" class=\"row_heading level0 row0\" >Training</th>\n",
              "      <td id=\"T_5227f_row0_col0\" class=\"data row0 col0\" >99.92%</td>\n",
              "      <td id=\"T_5227f_row0_col1\" class=\"data row0 col1\" >99.97%</td>\n",
              "      <td id=\"T_5227f_row0_col2\" class=\"data row0 col2\" >99.87%</td>\n",
              "      <td id=\"T_5227f_row0_col3\" class=\"data row0 col3\" >99.87%</td>\n",
              "      <td id=\"T_5227f_row0_col4\" class=\"data row0 col4\" >99.97%</td>\n",
              "      <td id=\"T_5227f_row0_col5\" class=\"data row0 col5\" >99.92%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_5227f_level0_row1\" class=\"row_heading level0 row1\" >Validation</th>\n",
              "      <td id=\"T_5227f_row1_col0\" class=\"data row1 col0\" >98.10%</td>\n",
              "      <td id=\"T_5227f_row1_col1\" class=\"data row1 col1\" >82.73%</td>\n",
              "      <td id=\"T_5227f_row1_col2\" class=\"data row1 col2\" >83.03%</td>\n",
              "      <td id=\"T_5227f_row1_col3\" class=\"data row1 col3\" >99.00%</td>\n",
              "      <td id=\"T_5227f_row1_col4\" class=\"data row1 col4\" >98.98%</td>\n",
              "      <td id=\"T_5227f_row1_col5\" class=\"data row1 col5\" >82.88%</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "\u001b[2;37;42mAdaBoostClassifier:                                                                                   \u001b[0m\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 900x300 with 4 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[1mModel performance:\u001b[0m\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7fe22e3a6bf0>"
            ],
            "text/html": [
              "<style type=\"text/css\">\n",
              "#T_158b7 th {\n",
              "  max-width: 75px;\n",
              "}\n",
              "</style>\n",
              "<table id=\"T_158b7\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th class=\"blank level0\" >&nbsp;</th>\n",
              "      <th id=\"T_158b7_level0_col0\" class=\"col_heading level0 col0\" >Accuracy</th>\n",
              "      <th id=\"T_158b7_level0_col1\" class=\"col_heading level0 col1\" >Precision</th>\n",
              "      <th id=\"T_158b7_level0_col2\" class=\"col_heading level0 col2\" >Recall</th>\n",
              "      <th id=\"T_158b7_level0_col3\" class=\"col_heading level0 col3\" >NPV</th>\n",
              "      <th id=\"T_158b7_level0_col4\" class=\"col_heading level0 col4\" >Specificity</th>\n",
              "      <th id=\"T_158b7_level0_col5\" class=\"col_heading level0 col5\" >F1</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th id=\"T_158b7_level0_row0\" class=\"row_heading level0 row0\" >Training</th>\n",
              "      <td id=\"T_158b7_row0_col0\" class=\"data row0 col0\" >90.62%</td>\n",
              "      <td id=\"T_158b7_row0_col1\" class=\"data row0 col1\" >91.53%</td>\n",
              "      <td id=\"T_158b7_row0_col2\" class=\"data row0 col2\" >89.53%</td>\n",
              "      <td id=\"T_158b7_row0_col3\" class=\"data row0 col3\" >89.76%</td>\n",
              "      <td id=\"T_158b7_row0_col4\" class=\"data row0 col4\" >91.71%</td>\n",
              "      <td id=\"T_158b7_row0_col5\" class=\"data row0 col5\" >90.52%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_158b7_level0_row1\" class=\"row_heading level0 row1\" >Validation</th>\n",
              "      <td id=\"T_158b7_row1_col0\" class=\"data row1 col0\" >91.00%</td>\n",
              "      <td id=\"T_158b7_row1_col1\" class=\"data row1 col1\" >36.99%</td>\n",
              "      <td id=\"T_158b7_row1_col2\" class=\"data row1 col2\" >88.81%</td>\n",
              "      <td id=\"T_158b7_row1_col3\" class=\"data row1 col3\" >99.28%</td>\n",
              "      <td id=\"T_158b7_row1_col4\" class=\"data row1 col4\" >91.13%</td>\n",
              "      <td id=\"T_158b7_row1_col5\" class=\"data row1 col5\" >52.23%</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "\u001b[2;37;42mGradientBoostingClassifier:                                                                           \u001b[0m\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 900x300 with 4 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[1mModel performance:\u001b[0m\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7fe22efc4b80>"
            ],
            "text/html": [
              "<style type=\"text/css\">\n",
              "#T_321fe th {\n",
              "  max-width: 75px;\n",
              "}\n",
              "</style>\n",
              "<table id=\"T_321fe\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th class=\"blank level0\" >&nbsp;</th>\n",
              "      <th id=\"T_321fe_level0_col0\" class=\"col_heading level0 col0\" >Accuracy</th>\n",
              "      <th id=\"T_321fe_level0_col1\" class=\"col_heading level0 col1\" >Precision</th>\n",
              "      <th id=\"T_321fe_level0_col2\" class=\"col_heading level0 col2\" >Recall</th>\n",
              "      <th id=\"T_321fe_level0_col3\" class=\"col_heading level0 col3\" >NPV</th>\n",
              "      <th id=\"T_321fe_level0_col4\" class=\"col_heading level0 col4\" >Specificity</th>\n",
              "      <th id=\"T_321fe_level0_col5\" class=\"col_heading level0 col5\" >F1</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th id=\"T_321fe_level0_row0\" class=\"row_heading level0 row0\" >Training</th>\n",
              "      <td id=\"T_321fe_row0_col0\" class=\"data row0 col0\" >94.92%</td>\n",
              "      <td id=\"T_321fe_row0_col1\" class=\"data row0 col1\" >96.98%</td>\n",
              "      <td id=\"T_321fe_row0_col2\" class=\"data row0 col2\" >92.73%</td>\n",
              "      <td id=\"T_321fe_row0_col3\" class=\"data row0 col3\" >93.03%</td>\n",
              "      <td id=\"T_321fe_row0_col4\" class=\"data row0 col4\" >97.11%</td>\n",
              "      <td id=\"T_321fe_row0_col5\" class=\"data row0 col5\" >94.81%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_321fe_level0_row1\" class=\"row_heading level0 row1\" >Validation</th>\n",
              "      <td id=\"T_321fe_row1_col0\" class=\"data row1 col0\" >96.10%</td>\n",
              "      <td id=\"T_321fe_row1_col1\" class=\"data row1 col1\" >59.90%</td>\n",
              "      <td id=\"T_321fe_row1_col2\" class=\"data row1 col2\" >89.53%</td>\n",
              "      <td id=\"T_321fe_row1_col3\" class=\"data row1 col3\" >99.37%</td>\n",
              "      <td id=\"T_321fe_row1_col4\" class=\"data row1 col4\" >96.49%</td>\n",
              "      <td id=\"T_321fe_row1_col5\" class=\"data row1 col5\" >71.78%</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "\u001b[2;37;42mXGBClassifier:                                                                                        \u001b[0m\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 900x300 with 4 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[1mModel performance:\u001b[0m\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7fe22e4e3f10>"
            ],
            "text/html": [
              "<style type=\"text/css\">\n",
              "#T_553dc th {\n",
              "  max-width: 75px;\n",
              "}\n",
              "</style>\n",
              "<table id=\"T_553dc\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th class=\"blank level0\" >&nbsp;</th>\n",
              "      <th id=\"T_553dc_level0_col0\" class=\"col_heading level0 col0\" >Accuracy</th>\n",
              "      <th id=\"T_553dc_level0_col1\" class=\"col_heading level0 col1\" >Precision</th>\n",
              "      <th id=\"T_553dc_level0_col2\" class=\"col_heading level0 col2\" >Recall</th>\n",
              "      <th id=\"T_553dc_level0_col3\" class=\"col_heading level0 col3\" >NPV</th>\n",
              "      <th id=\"T_553dc_level0_col4\" class=\"col_heading level0 col4\" >Specificity</th>\n",
              "      <th id=\"T_553dc_level0_col5\" class=\"col_heading level0 col5\" >F1</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th id=\"T_553dc_level0_row0\" class=\"row_heading level0 row0\" >Training</th>\n",
              "      <td id=\"T_553dc_row0_col0\" class=\"data row0 col0\" >99.99%</td>\n",
              "      <td id=\"T_553dc_row0_col1\" class=\"data row0 col1\" >99.99%</td>\n",
              "      <td id=\"T_553dc_row0_col2\" class=\"data row0 col2\" >99.99%</td>\n",
              "      <td id=\"T_553dc_row0_col3\" class=\"data row0 col3\" >99.99%</td>\n",
              "      <td id=\"T_553dc_row0_col4\" class=\"data row0 col4\" >99.99%</td>\n",
              "      <td id=\"T_553dc_row0_col5\" class=\"data row0 col5\" >99.99%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_553dc_level0_row1\" class=\"row_heading level0 row1\" >Validation</th>\n",
              "      <td id=\"T_553dc_row1_col0\" class=\"data row1 col0\" >98.62%</td>\n",
              "      <td id=\"T_553dc_row1_col1\" class=\"data row1 col1\" >86.36%</td>\n",
              "      <td id=\"T_553dc_row1_col2\" class=\"data row1 col2\" >89.17%</td>\n",
              "      <td id=\"T_553dc_row1_col3\" class=\"data row1 col3\" >99.36%</td>\n",
              "      <td id=\"T_553dc_row1_col4\" class=\"data row1 col4\" >99.17%</td>\n",
              "      <td id=\"T_553dc_row1_col5\" class=\"data row1 col5\" >87.74%</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "res_over = cv_simple(models_grid, X_train_over, y_train_over, X_valid, y_valid, title='Oversampled')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 52,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 488
        },
        "id": "3z8BGv-BXXoV",
        "outputId": "3fca5c01-58c3-49c2-d4bd-aa7cc8fd3930"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "         index  Accuracy  Precision    Recall       NPV  Specificity  \\\n",
              "0     Training  1.000000   1.000000  1.000000  1.000000     1.000000   \n",
              "1   Validation  0.942000   0.485126  0.765343  0.985755     0.952361   \n",
              "2     Training  0.874462   0.874594  0.874285  0.874330     0.874638   \n",
              "3   Validation  0.878800   0.298160  0.877256  0.991876     0.878891   \n",
              "4     Training  1.000000   1.000000  1.000000  1.000000     1.000000   \n",
              "5   Validation  0.988800   0.933333  0.859206  0.991781     0.996401   \n",
              "6     Training  0.999188   0.999717  0.998659  0.998660     0.999718   \n",
              "7   Validation  0.981000   0.827338  0.830325  0.990047     0.989837   \n",
              "8     Training  0.906226   0.915284  0.895320  0.897555     0.917131   \n",
              "9   Validation  0.910000   0.369925  0.888087  0.992849     0.911285   \n",
              "10    Training  0.949213   0.969807  0.927296  0.930349     0.971130   \n",
              "11  Validation  0.961000   0.599034  0.895307  0.993676     0.964853   \n",
              "12    Training  0.999929   0.999929  0.999929  0.999929     0.999929   \n",
              "13  Validation  0.986200   0.863636  0.891697  0.993636     0.991743   \n",
              "\n",
              "          F1    duration  cv_recall                       model  \n",
              "0   1.000000   21.925469   0.971836      DecisionTreeClassifier  \n",
              "1   0.593838    2.580847        NaN      DecisionTreeClassifier  \n",
              "2   0.874440    1.365862   0.873933          LogisticRegression  \n",
              "3   0.445055    0.186492        NaN          LogisticRegression  \n",
              "4   1.000000  191.593849   0.984824      RandomForestClassifier  \n",
              "5   0.894737   21.773816        NaN      RandomForestClassifier  \n",
              "6   0.999188  137.088547   0.975506           BaggingClassifier  \n",
              "7   0.828829   15.595947        NaN           BaggingClassifier  \n",
              "8   0.905192   96.166766   0.892286          AdaBoostClassifier  \n",
              "9   0.522293   11.014912        NaN          AdaBoostClassifier  \n",
              "10  0.948075  468.356503   0.923979  GradientBoostingClassifier  \n",
              "11  0.717800   52.771510        NaN  GradientBoostingClassifier  \n",
              "12  0.999929  226.971239   0.990542               XGBClassifier  \n",
              "13  0.877442   25.277743        NaN               XGBClassifier  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-1be01a9a-d2ec-4536-859a-86ec839f6ee2\">\n",
              "    <div 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>index</th>\n",
              "      <th>Accuracy</th>\n",
              "      <th>Precision</th>\n",
              "      <th>Recall</th>\n",
              "      <th>NPV</th>\n",
              "      <th>Specificity</th>\n",
              "      <th>F1</th>\n",
              "      <th>duration</th>\n",
              "      <th>cv_recall</th>\n",
              "      <th>model</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Training</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>21.925469</td>\n",
              "      <td>0.971836</td>\n",
              "      <td>DecisionTreeClassifier</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Validation</td>\n",
              "      <td>0.942000</td>\n",
              "      <td>0.485126</td>\n",
              "      <td>0.765343</td>\n",
              "      <td>0.985755</td>\n",
              "      <td>0.952361</td>\n",
              "      <td>0.593838</td>\n",
              "      <td>2.580847</td>\n",
              "      <td>NaN</td>\n",
              "      <td>DecisionTreeClassifier</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Training</td>\n",
              "      <td>0.874462</td>\n",
              "      <td>0.874594</td>\n",
              "      <td>0.874285</td>\n",
              "      <td>0.874330</td>\n",
              "      <td>0.874638</td>\n",
              "      <td>0.874440</td>\n",
              "      <td>1.365862</td>\n",
              "      <td>0.873933</td>\n",
              "      <td>LogisticRegression</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Validation</td>\n",
              "      <td>0.878800</td>\n",
              "      <td>0.298160</td>\n",
              "      <td>0.877256</td>\n",
              "      <td>0.991876</td>\n",
              "      <td>0.878891</td>\n",
              "      <td>0.445055</td>\n",
              "      <td>0.186492</td>\n",
              "      <td>NaN</td>\n",
              "      <td>LogisticRegression</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Training</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>191.593849</td>\n",
              "      <td>0.984824</td>\n",
              "      <td>RandomForestClassifier</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Validation</td>\n",
              "      <td>0.988800</td>\n",
              "      <td>0.933333</td>\n",
              "      <td>0.859206</td>\n",
              "      <td>0.991781</td>\n",
              "      <td>0.996401</td>\n",
              "      <td>0.894737</td>\n",
              "      <td>21.773816</td>\n",
              "      <td>NaN</td>\n",
              "      <td>RandomForestClassifier</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>Training</td>\n",
              "      <td>0.999188</td>\n",
              "      <td>0.999717</td>\n",
              "      <td>0.998659</td>\n",
              "      <td>0.998660</td>\n",
              "      <td>0.999718</td>\n",
              "      <td>0.999188</td>\n",
              "      <td>137.088547</td>\n",
              "      <td>0.975506</td>\n",
              "      <td>BaggingClassifier</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>Validation</td>\n",
              "      <td>0.981000</td>\n",
              "      <td>0.827338</td>\n",
              "      <td>0.830325</td>\n",
              "      <td>0.990047</td>\n",
              "      <td>0.989837</td>\n",
              "      <td>0.828829</td>\n",
              "      <td>15.595947</td>\n",
              "      <td>NaN</td>\n",
              "      <td>BaggingClassifier</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>Training</td>\n",
              "      <td>0.906226</td>\n",
              "      <td>0.915284</td>\n",
              "      <td>0.895320</td>\n",
              "      <td>0.897555</td>\n",
              "      <td>0.917131</td>\n",
              "      <td>0.905192</td>\n",
              "      <td>96.166766</td>\n",
              "      <td>0.892286</td>\n",
              "      <td>AdaBoostClassifier</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>Validation</td>\n",
              "      <td>0.910000</td>\n",
              "      <td>0.369925</td>\n",
              "      <td>0.888087</td>\n",
              "      <td>0.992849</td>\n",
              "      <td>0.911285</td>\n",
              "      <td>0.522293</td>\n",
              "      <td>11.014912</td>\n",
              "      <td>NaN</td>\n",
              "      <td>AdaBoostClassifier</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>Training</td>\n",
              "      <td>0.949213</td>\n",
              "      <td>0.969807</td>\n",
              "      <td>0.927296</td>\n",
              "      <td>0.930349</td>\n",
              "      <td>0.971130</td>\n",
              "      <td>0.948075</td>\n",
              "      <td>468.356503</td>\n",
              "      <td>0.923979</td>\n",
              "      <td>GradientBoostingClassifier</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>Validation</td>\n",
              "      <td>0.961000</td>\n",
              "      <td>0.599034</td>\n",
              "      <td>0.895307</td>\n",
              "      <td>0.993676</td>\n",
              "      <td>0.964853</td>\n",
              "      <td>0.717800</td>\n",
              "      <td>52.771510</td>\n",
              "      <td>NaN</td>\n",
              "      <td>GradientBoostingClassifier</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>Training</td>\n",
              "      <td>0.999929</td>\n",
              "      <td>0.999929</td>\n",
              "      <td>0.999929</td>\n",
              "      <td>0.999929</td>\n",
              "      <td>0.999929</td>\n",
              "      <td>0.999929</td>\n",
              "      <td>226.971239</td>\n",
              "      <td>0.990542</td>\n",
              "      <td>XGBClassifier</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>Validation</td>\n",
              "      <td>0.986200</td>\n",
              "      <td>0.863636</td>\n",
              "      <td>0.891697</td>\n",
              "      <td>0.993636</td>\n",
              "      <td>0.991743</td>\n",
              "      <td>0.877442</td>\n",
              "      <td>25.277743</td>\n",
              "      <td>NaN</td>\n",
              "      <td>XGBClassifier</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
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            ]
          },
          "metadata": {},
          "execution_count": 52
        }
      ],
      "source": [
        "res_over"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "B9CX6ELUa1dc"
      },
      "source": [
        "**Observations:**\n",
        "\n",
        "Using the **oversampled** data, we observe the following:\n",
        "\n",
        "* Both **XGBClassifier** and **GradientBoostingClassifier** demonstrate the highest performance on the training and validation datasets, indicating that they are the most promising models for our dataset.\n",
        "\n",
        "* In terms of validation performance, **AdaBoostClassifier** achieves relatively high scores, indicating that it generalizes well to unseen data.\n",
        "\n",
        "* While **DecisionTreeClassifier**, **RandomForestClassifier**, and **BaggingClassifier** show high scores on the training dataset, their performance on the validation dataset is comparatively lower, suggesting that they might be overfitting to the training data.\n",
        "\n",
        "* **LogisticRegression** has demonstrated a significant improvement in performance when applied to oversampled data compared to the original training dataset. Nevertheless, it still shows lower values for the performance metric when compared to other models.\n",
        "\n",
        "* Learning durations for the models vary significantly, with **LogisticRegression** being the fastest and **GradientBoostingClassifier** taking the longest time to train."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "6XZwUM-tXXxk"
      },
      "source": [
        "Based on these findings, **XGBClassifier** remains promising model for the oversampled dataset. However, **AdaBoostClassifier** and **GradientBoostingClassifier** also show good performance on the validation dataset, and they could be considered as alternative options with proper optimization.\n",
        "\n",
        "Upon analyzing the model performance on oversampled data, we observe some  overfitting concerning our Recall measure for DecisionTree, RandomForest and Bagging classifiers.\n",
        "  - This overfitting may result in poor generalization when applied to test data or in a production environment.\n",
        "  - To address this issue, it is crucial to improve the model's performance by reducing overfitting and achieving a better balance between recall and other evaluation metrics."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "1aimb6bn4jat"
      },
      "source": [
        "### Model Building with Undersampled data"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 53,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "jROP_DVF4jau",
        "outputId": "201cb6d7-bd52-41df-9f2f-a485f241f826"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "Cross-Validation performance on training dataset:\n",
            "\n",
            "\tDecisionTreeClassifier: 0.85851\n",
            "\t\tIteration duration: 0.84 seconds\n",
            "\tLogisticRegression: 0.85711\n",
            "\t\tIteration duration: 0.25 seconds\n",
            "\tRandomForestClassifier: 0.89924\n",
            "\t\tIteration duration: 9.02 seconds\n",
            "\tBaggingClassifier: 0.87279\n",
            "\t\tIteration duration: 4.60 seconds\n",
            "\tAdaBoostClassifier: 0.86681\n",
            "\t\tIteration duration: 5.53 seconds\n",
            "\tGradientBoostingClassifier: 0.89203\n",
            "\t\tIteration duration: 23.07 seconds\n",
            "\tXGBClassifier: 0.89924\n",
            "\t\tIteration duration: 10.64 seconds\n",
            "\n",
            "Validation Performance:\n",
            "\n",
            "\tDecisionTreeClassifier: 0.84838\n",
            "\t\tIteration duration: 0.10 seconds\n",
            "\tLogisticRegression: 0.88087\n",
            "\t\tIteration duration: 0.03 seconds\n",
            "\tRandomForestClassifier: 0.91336\n",
            "\t\tIteration duration: 1.00 seconds\n",
            "\tBaggingClassifier: 0.85560\n",
            "\t\tIteration duration: 0.54 seconds\n",
            "\tAdaBoostClassifier: 0.87726\n",
            "\t\tIteration duration: 0.64 seconds\n",
            "\tGradientBoostingClassifier: 0.90253\n",
            "\t\tIteration duration: 2.55 seconds\n",
            "\tXGBClassifier: 0.90253\n",
            "\t\tIteration duration: 2.47 seconds\n",
            "\n",
            "\u001b[2;37;42mDecisionTreeClassifier:                                                                               \u001b[0m\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 900x300 with 4 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[1mModel performance:\u001b[0m\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7fe23179dd50>"
            ],
            "text/html": [
              "<style type=\"text/css\">\n",
              "#T_d5a0a th {\n",
              "  max-width: 75px;\n",
              "}\n",
              "</style>\n",
              "<table id=\"T_d5a0a\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th class=\"blank level0\" >&nbsp;</th>\n",
              "      <th id=\"T_d5a0a_level0_col0\" class=\"col_heading level0 col0\" >Accuracy</th>\n",
              "      <th id=\"T_d5a0a_level0_col1\" class=\"col_heading level0 col1\" >Precision</th>\n",
              "      <th id=\"T_d5a0a_level0_col2\" class=\"col_heading level0 col2\" >Recall</th>\n",
              "      <th id=\"T_d5a0a_level0_col3\" class=\"col_heading level0 col3\" >NPV</th>\n",
              "      <th id=\"T_d5a0a_level0_col4\" class=\"col_heading level0 col4\" >Specificity</th>\n",
              "      <th id=\"T_d5a0a_level0_col5\" class=\"col_heading level0 col5\" >F1</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th id=\"T_d5a0a_level0_row0\" class=\"row_heading level0 row0\" >Training</th>\n",
              "      <td id=\"T_d5a0a_row0_col0\" class=\"data row0 col0\" >100.00%</td>\n",
              "      <td id=\"T_d5a0a_row0_col1\" class=\"data row0 col1\" >100.00%</td>\n",
              "      <td id=\"T_d5a0a_row0_col2\" class=\"data row0 col2\" >100.00%</td>\n",
              "      <td id=\"T_d5a0a_row0_col3\" class=\"data row0 col3\" >100.00%</td>\n",
              "      <td id=\"T_d5a0a_row0_col4\" class=\"data row0 col4\" >100.00%</td>\n",
              "      <td id=\"T_d5a0a_row0_col5\" class=\"data row0 col5\" >100.00%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_d5a0a_level0_row1\" class=\"row_heading level0 row1\" >Validation</th>\n",
              "      <td id=\"T_d5a0a_row1_col0\" class=\"data row1 col0\" >83.78%</td>\n",
              "      <td id=\"T_d5a0a_row1_col1\" class=\"data row1 col1\" >23.41%</td>\n",
              "      <td id=\"T_d5a0a_row1_col2\" class=\"data row1 col2\" >84.84%</td>\n",
              "      <td id=\"T_d5a0a_row1_col3\" class=\"data row1 col3\" >98.95%</td>\n",
              "      <td id=\"T_d5a0a_row1_col4\" class=\"data row1 col4\" >83.72%</td>\n",
              "      <td id=\"T_d5a0a_row1_col5\" class=\"data row1 col5\" >36.69%</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "\u001b[2;37;42mLogisticRegression:                                                                                   \u001b[0m\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 900x300 with 4 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[1mModel performance:\u001b[0m\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7fe27b73dea0>"
            ],
            "text/html": [
              "<style type=\"text/css\">\n",
              "#T_9491f th {\n",
              "  max-width: 75px;\n",
              "}\n",
              "</style>\n",
              "<table id=\"T_9491f\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th class=\"blank level0\" >&nbsp;</th>\n",
              "      <th id=\"T_9491f_level0_col0\" class=\"col_heading level0 col0\" >Accuracy</th>\n",
              "      <th id=\"T_9491f_level0_col1\" class=\"col_heading level0 col1\" >Precision</th>\n",
              "      <th id=\"T_9491f_level0_col2\" class=\"col_heading level0 col2\" >Recall</th>\n",
              "      <th id=\"T_9491f_level0_col3\" class=\"col_heading level0 col3\" >NPV</th>\n",
              "      <th id=\"T_9491f_level0_col4\" class=\"col_heading level0 col4\" >Specificity</th>\n",
              "      <th id=\"T_9491f_level0_col5\" class=\"col_heading level0 col5\" >F1</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th id=\"T_9491f_level0_row0\" class=\"row_heading level0 row0\" >Training</th>\n",
              "      <td id=\"T_9491f_row0_col0\" class=\"data row0 col0\" >86.37%</td>\n",
              "      <td id=\"T_9491f_row0_col1\" class=\"data row0 col1\" >86.59%</td>\n",
              "      <td id=\"T_9491f_row0_col2\" class=\"data row0 col2\" >86.07%</td>\n",
              "      <td id=\"T_9491f_row0_col3\" class=\"data row0 col3\" >86.16%</td>\n",
              "      <td id=\"T_9491f_row0_col4\" class=\"data row0 col4\" >86.67%</td>\n",
              "      <td id=\"T_9491f_row0_col5\" class=\"data row0 col5\" >86.33%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_9491f_level0_row1\" class=\"row_heading level0 row1\" >Validation</th>\n",
              "      <td id=\"T_9491f_row1_col0\" class=\"data row1 col0\" >86.44%</td>\n",
              "      <td id=\"T_9491f_row1_col1\" class=\"data row1 col1\" >27.45%</td>\n",
              "      <td id=\"T_9491f_row1_col2\" class=\"data row1 col2\" >88.09%</td>\n",
              "      <td id=\"T_9491f_row1_col3\" class=\"data row1 col3\" >99.20%</td>\n",
              "      <td id=\"T_9491f_row1_col4\" class=\"data row1 col4\" >86.34%</td>\n",
              "      <td id=\"T_9491f_row1_col5\" class=\"data row1 col5\" >41.85%</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "\u001b[2;37;42mRandomForestClassifier:                                                                               \u001b[0m\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 900x300 with 4 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[1mModel performance:\u001b[0m\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7fe22f2ed9f0>"
            ],
            "text/html": [
              "<style type=\"text/css\">\n",
              "#T_8af64 th {\n",
              "  max-width: 75px;\n",
              "}\n",
              "</style>\n",
              "<table id=\"T_8af64\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th class=\"blank level0\" >&nbsp;</th>\n",
              "      <th id=\"T_8af64_level0_col0\" class=\"col_heading level0 col0\" >Accuracy</th>\n",
              "      <th id=\"T_8af64_level0_col1\" class=\"col_heading level0 col1\" >Precision</th>\n",
              "      <th id=\"T_8af64_level0_col2\" class=\"col_heading level0 col2\" >Recall</th>\n",
              "      <th id=\"T_8af64_level0_col3\" class=\"col_heading level0 col3\" >NPV</th>\n",
              "      <th id=\"T_8af64_level0_col4\" class=\"col_heading level0 col4\" >Specificity</th>\n",
              "      <th id=\"T_8af64_level0_col5\" class=\"col_heading level0 col5\" >F1</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th id=\"T_8af64_level0_row0\" class=\"row_heading level0 row0\" >Training</th>\n",
              "      <td id=\"T_8af64_row0_col0\" class=\"data row0 col0\" >100.00%</td>\n",
              "      <td id=\"T_8af64_row0_col1\" class=\"data row0 col1\" >100.00%</td>\n",
              "      <td id=\"T_8af64_row0_col2\" class=\"data row0 col2\" >100.00%</td>\n",
              "      <td id=\"T_8af64_row0_col3\" class=\"data row0 col3\" >100.00%</td>\n",
              "      <td id=\"T_8af64_row0_col4\" class=\"data row0 col4\" >100.00%</td>\n",
              "      <td id=\"T_8af64_row0_col5\" class=\"data row0 col5\" >100.00%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_8af64_level0_row1\" class=\"row_heading level0 row1\" >Validation</th>\n",
              "      <td id=\"T_8af64_row1_col0\" class=\"data row1 col0\" >95.08%</td>\n",
              "      <td id=\"T_8af64_row1_col1\" class=\"data row1 col1\" >53.26%</td>\n",
              "      <td id=\"T_8af64_row1_col2\" class=\"data row1 col2\" >91.34%</td>\n",
              "      <td id=\"T_8af64_row1_col3\" class=\"data row1 col3\" >99.47%</td>\n",
              "      <td id=\"T_8af64_row1_col4\" class=\"data row1 col4\" >95.30%</td>\n",
              "      <td id=\"T_8af64_row1_col5\" class=\"data row1 col5\" >67.29%</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "\u001b[2;37;42mBaggingClassifier:                                                                                    \u001b[0m\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 900x300 with 4 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[1mModel performance:\u001b[0m\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7fe22ebbceb0>"
            ],
            "text/html": [
              "<style type=\"text/css\">\n",
              "#T_a4a4a th {\n",
              "  max-width: 75px;\n",
              "}\n",
              "</style>\n",
              "<table id=\"T_a4a4a\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th class=\"blank level0\" >&nbsp;</th>\n",
              "      <th id=\"T_a4a4a_level0_col0\" class=\"col_heading level0 col0\" >Accuracy</th>\n",
              "      <th id=\"T_a4a4a_level0_col1\" class=\"col_heading level0 col1\" >Precision</th>\n",
              "      <th id=\"T_a4a4a_level0_col2\" class=\"col_heading level0 col2\" >Recall</th>\n",
              "      <th id=\"T_a4a4a_level0_col3\" class=\"col_heading level0 col3\" >NPV</th>\n",
              "      <th id=\"T_a4a4a_level0_col4\" class=\"col_heading level0 col4\" >Specificity</th>\n",
              "      <th id=\"T_a4a4a_level0_col5\" class=\"col_heading level0 col5\" >F1</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th id=\"T_a4a4a_level0_row0\" class=\"row_heading level0 row0\" >Training</th>\n",
              "      <td id=\"T_a4a4a_row0_col0\" class=\"data row0 col0\" >98.86%</td>\n",
              "      <td id=\"T_a4a4a_row0_col1\" class=\"data row0 col1\" >100.00%</td>\n",
              "      <td id=\"T_a4a4a_row0_col2\" class=\"data row0 col2\" >97.72%</td>\n",
              "      <td id=\"T_a4a4a_row0_col3\" class=\"data row0 col3\" >97.77%</td>\n",
              "      <td id=\"T_a4a4a_row0_col4\" class=\"data row0 col4\" >100.00%</td>\n",
              "      <td id=\"T_a4a4a_row0_col5\" class=\"data row0 col5\" >98.85%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_a4a4a_level0_row1\" class=\"row_heading level0 row1\" >Validation</th>\n",
              "      <td id=\"T_a4a4a_row1_col0\" class=\"data row1 col0\" >92.88%</td>\n",
              "      <td id=\"T_a4a4a_row1_col1\" class=\"data row1 col1\" >42.86%</td>\n",
              "      <td id=\"T_a4a4a_row1_col2\" class=\"data row1 col2\" >85.56%</td>\n",
              "      <td id=\"T_a4a4a_row1_col3\" class=\"data row1 col3\" >99.10%</td>\n",
              "      <td id=\"T_a4a4a_row1_col4\" class=\"data row1 col4\" >93.31%</td>\n",
              "      <td id=\"T_a4a4a_row1_col5\" class=\"data row1 col5\" >57.11%</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "\u001b[2;37;42mAdaBoostClassifier:                                                                                   \u001b[0m\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 900x300 with 4 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[1mModel performance:\u001b[0m\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7fe22e50b340>"
            ],
            "text/html": [
              "<style type=\"text/css\">\n",
              "#T_21569 th {\n",
              "  max-width: 75px;\n",
              "}\n",
              "</style>\n",
              "<table id=\"T_21569\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th class=\"blank level0\" >&nbsp;</th>\n",
              "      <th id=\"T_21569_level0_col0\" class=\"col_heading level0 col0\" >Accuracy</th>\n",
              "      <th id=\"T_21569_level0_col1\" class=\"col_heading level0 col1\" >Precision</th>\n",
              "      <th id=\"T_21569_level0_col2\" class=\"col_heading level0 col2\" >Recall</th>\n",
              "      <th id=\"T_21569_level0_col3\" class=\"col_heading level0 col3\" >NPV</th>\n",
              "      <th id=\"T_21569_level0_col4\" class=\"col_heading level0 col4\" >Specificity</th>\n",
              "      <th id=\"T_21569_level0_col5\" class=\"col_heading level0 col5\" >F1</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th id=\"T_21569_level0_row0\" class=\"row_heading level0 row0\" >Training</th>\n",
              "      <td id=\"T_21569_row0_col0\" class=\"data row0 col0\" >92.02%</td>\n",
              "      <td id=\"T_21569_row0_col1\" class=\"data row0 col1\" >93.53%</td>\n",
              "      <td id=\"T_21569_row0_col2\" class=\"data row0 col2\" >90.28%</td>\n",
              "      <td id=\"T_21569_row0_col3\" class=\"data row0 col3\" >90.60%</td>\n",
              "      <td id=\"T_21569_row0_col4\" class=\"data row0 col4\" >93.76%</td>\n",
              "      <td id=\"T_21569_row0_col5\" class=\"data row0 col5\" >91.88%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_21569_level0_row1\" class=\"row_heading level0 row1\" >Validation</th>\n",
              "      <td id=\"T_21569_row1_col0\" class=\"data row1 col0\" >88.92%</td>\n",
              "      <td id=\"T_21569_row1_col1\" class=\"data row1 col1\" >31.85%</td>\n",
              "      <td id=\"T_21569_row1_col2\" class=\"data row1 col2\" >87.73%</td>\n",
              "      <td id=\"T_21569_row1_col3\" class=\"data row1 col3\" >99.20%</td>\n",
              "      <td id=\"T_21569_row1_col4\" class=\"data row1 col4\" >88.99%</td>\n",
              "      <td id=\"T_21569_row1_col5\" class=\"data row1 col5\" >46.73%</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "\u001b[2;37;42mGradientBoostingClassifier:                                                                           \u001b[0m\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 900x300 with 4 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[1mModel performance:\u001b[0m\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7fe22eb27880>"
            ],
            "text/html": [
              "<style type=\"text/css\">\n",
              "#T_a8809 th {\n",
              "  max-width: 75px;\n",
              "}\n",
              "</style>\n",
              "<table id=\"T_a8809\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th class=\"blank level0\" >&nbsp;</th>\n",
              "      <th id=\"T_a8809_level0_col0\" class=\"col_heading level0 col0\" >Accuracy</th>\n",
              "      <th id=\"T_a8809_level0_col1\" class=\"col_heading level0 col1\" >Precision</th>\n",
              "      <th id=\"T_a8809_level0_col2\" class=\"col_heading level0 col2\" >Recall</th>\n",
              "      <th id=\"T_a8809_level0_col3\" class=\"col_heading level0 col3\" >NPV</th>\n",
              "      <th id=\"T_a8809_level0_col4\" class=\"col_heading level0 col4\" >Specificity</th>\n",
              "      <th id=\"T_a8809_level0_col5\" class=\"col_heading level0 col5\" >F1</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th id=\"T_a8809_level0_row0\" class=\"row_heading level0 row0\" >Training</th>\n",
              "      <td id=\"T_a8809_row0_col0\" class=\"data row0 col0\" >97.12%</td>\n",
              "      <td id=\"T_a8809_row0_col1\" class=\"data row0 col1\" >99.37%</td>\n",
              "      <td id=\"T_a8809_row0_col2\" class=\"data row0 col2\" >94.84%</td>\n",
              "      <td id=\"T_a8809_row0_col3\" class=\"data row0 col3\" >95.06%</td>\n",
              "      <td id=\"T_a8809_row0_col4\" class=\"data row0 col4\" >99.40%</td>\n",
              "      <td id=\"T_a8809_row0_col5\" class=\"data row0 col5\" >97.05%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_a8809_level0_row1\" class=\"row_heading level0 row1\" >Validation</th>\n",
              "      <td id=\"T_a8809_row1_col0\" class=\"data row1 col0\" >92.72%</td>\n",
              "      <td id=\"T_a8809_row1_col1\" class=\"data row1 col1\" >42.59%</td>\n",
              "      <td id=\"T_a8809_row1_col2\" class=\"data row1 col2\" >90.25%</td>\n",
              "      <td id=\"T_a8809_row1_col3\" class=\"data row1 col3\" >99.39%</td>\n",
              "      <td id=\"T_a8809_row1_col4\" class=\"data row1 col4\" >92.86%</td>\n",
              "      <td id=\"T_a8809_row1_col5\" class=\"data row1 col5\" >57.87%</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "\u001b[2;37;42mXGBClassifier:                                                                                        \u001b[0m\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 900x300 with 4 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[1mModel performance:\u001b[0m\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7fe22e2b1810>"
            ],
            "text/html": [
              "<style type=\"text/css\">\n",
              "#T_98c93 th {\n",
              "  max-width: 75px;\n",
              "}\n",
              "</style>\n",
              "<table id=\"T_98c93\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th class=\"blank level0\" >&nbsp;</th>\n",
              "      <th id=\"T_98c93_level0_col0\" class=\"col_heading level0 col0\" >Accuracy</th>\n",
              "      <th id=\"T_98c93_level0_col1\" class=\"col_heading level0 col1\" >Precision</th>\n",
              "      <th id=\"T_98c93_level0_col2\" class=\"col_heading level0 col2\" >Recall</th>\n",
              "      <th id=\"T_98c93_level0_col3\" class=\"col_heading level0 col3\" >NPV</th>\n",
              "      <th id=\"T_98c93_level0_col4\" class=\"col_heading level0 col4\" >Specificity</th>\n",
              "      <th id=\"T_98c93_level0_col5\" class=\"col_heading level0 col5\" >F1</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th id=\"T_98c93_level0_row0\" class=\"row_heading level0 row0\" >Training</th>\n",
              "      <td id=\"T_98c93_row0_col0\" class=\"data row0 col0\" >100.00%</td>\n",
              "      <td id=\"T_98c93_row0_col1\" class=\"data row0 col1\" >100.00%</td>\n",
              "      <td id=\"T_98c93_row0_col2\" class=\"data row0 col2\" >100.00%</td>\n",
              "      <td id=\"T_98c93_row0_col3\" class=\"data row0 col3\" >100.00%</td>\n",
              "      <td id=\"T_98c93_row0_col4\" class=\"data row0 col4\" >100.00%</td>\n",
              "      <td id=\"T_98c93_row0_col5\" class=\"data row0 col5\" >100.00%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_98c93_level0_row1\" class=\"row_heading level0 row1\" >Validation</th>\n",
              "      <td id=\"T_98c93_row1_col0\" class=\"data row1 col0\" >94.84%</td>\n",
              "      <td id=\"T_98c93_row1_col1\" class=\"data row1 col1\" >51.98%</td>\n",
              "      <td id=\"T_98c93_row1_col2\" class=\"data row1 col2\" >90.25%</td>\n",
              "      <td id=\"T_98c93_row1_col3\" class=\"data row1 col3\" >99.40%</td>\n",
              "      <td id=\"T_98c93_row1_col4\" class=\"data row1 col4\" >95.11%</td>\n",
              "      <td id=\"T_98c93_row1_col5\" class=\"data row1 col5\" >65.96%</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "res_un = cv_simple(models_grid, X_train_un, y_train_un, X_valid, y_valid, title='Undersampled')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 54,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 488
        },
        "id": "V3WFB4YyX-sF",
        "outputId": "a4087cdf-a169-441e-d2fc-e7e68c5146eb"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "         index  Accuracy  Precision    Recall       NPV  Specificity  \\\n",
              "0     Training  1.000000   1.000000  1.000000  1.000000     1.000000   \n",
              "1   Validation  0.837800   0.234064  0.848375  0.989489     0.837180   \n",
              "2     Training  0.863745   0.865942  0.860744  0.861575     0.866747   \n",
              "3   Validation  0.864400   0.274466  0.880866  0.991973     0.863434   \n",
              "4     Training  1.000000   1.000000  1.000000  1.000000     1.000000   \n",
              "5   Validation  0.950800   0.532632  0.913357  0.994696     0.952996   \n",
              "6     Training  0.988595   1.000000  0.977191  0.977700     1.000000   \n",
              "7   Validation  0.928800   0.428571  0.855596  0.991005     0.933093   \n",
              "8     Training  0.920168   0.935323  0.902761  0.906032     0.937575   \n",
              "9   Validation  0.889200   0.318480  0.877256  0.991975     0.889900   \n",
              "10    Training  0.971188   0.993711  0.948379  0.950631     0.993998   \n",
              "11  Validation  0.927200   0.425894  0.902527  0.993882     0.928647   \n",
              "12    Training  1.000000   1.000000  1.000000  1.000000     1.000000   \n",
              "13  Validation  0.948400   0.519751  0.902527  0.994025     0.951090   \n",
              "\n",
              "          F1   duration  cv_recall                       model  \n",
              "0   1.000000   0.843659   0.858505      DecisionTreeClassifier  \n",
              "1   0.366901   0.094575        NaN      DecisionTreeClassifier  \n",
              "2   0.863335   0.252838   0.857114          LogisticRegression  \n",
              "3   0.418525   0.026560        NaN          LogisticRegression  \n",
              "4   1.000000   9.019661   0.899240      RandomForestClassifier  \n",
              "5   0.672872   0.994174        NaN      RandomForestClassifier  \n",
              "6   0.988464   4.604301   0.872791           BaggingClassifier  \n",
              "7   0.571084   0.541749        NaN           BaggingClassifier  \n",
              "8   0.918754   5.526041   0.866810          AdaBoostClassifier  \n",
              "9   0.467308   0.643924        NaN          AdaBoostClassifier  \n",
              "10  0.970516  23.070930   0.892025  GradientBoostingClassifier  \n",
              "11  0.578704   2.552907        NaN  GradientBoostingClassifier  \n",
              "12  1.000000  10.641260   0.899240               XGBClassifier  \n",
              "13  0.659631   2.471798        NaN               XGBClassifier  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-e604b58d-a588-4772-84a2-38966d5140d3\">\n",
              "    <div 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>index</th>\n",
              "      <th>Accuracy</th>\n",
              "      <th>Precision</th>\n",
              "      <th>Recall</th>\n",
              "      <th>NPV</th>\n",
              "      <th>Specificity</th>\n",
              "      <th>F1</th>\n",
              "      <th>duration</th>\n",
              "      <th>cv_recall</th>\n",
              "      <th>model</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Training</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.843659</td>\n",
              "      <td>0.858505</td>\n",
              "      <td>DecisionTreeClassifier</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Validation</td>\n",
              "      <td>0.837800</td>\n",
              "      <td>0.234064</td>\n",
              "      <td>0.848375</td>\n",
              "      <td>0.989489</td>\n",
              "      <td>0.837180</td>\n",
              "      <td>0.366901</td>\n",
              "      <td>0.094575</td>\n",
              "      <td>NaN</td>\n",
              "      <td>DecisionTreeClassifier</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Training</td>\n",
              "      <td>0.863745</td>\n",
              "      <td>0.865942</td>\n",
              "      <td>0.860744</td>\n",
              "      <td>0.861575</td>\n",
              "      <td>0.866747</td>\n",
              "      <td>0.863335</td>\n",
              "      <td>0.252838</td>\n",
              "      <td>0.857114</td>\n",
              "      <td>LogisticRegression</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Validation</td>\n",
              "      <td>0.864400</td>\n",
              "      <td>0.274466</td>\n",
              "      <td>0.880866</td>\n",
              "      <td>0.991973</td>\n",
              "      <td>0.863434</td>\n",
              "      <td>0.418525</td>\n",
              "      <td>0.026560</td>\n",
              "      <td>NaN</td>\n",
              "      <td>LogisticRegression</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Training</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>9.019661</td>\n",
              "      <td>0.899240</td>\n",
              "      <td>RandomForestClassifier</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Validation</td>\n",
              "      <td>0.950800</td>\n",
              "      <td>0.532632</td>\n",
              "      <td>0.913357</td>\n",
              "      <td>0.994696</td>\n",
              "      <td>0.952996</td>\n",
              "      <td>0.672872</td>\n",
              "      <td>0.994174</td>\n",
              "      <td>NaN</td>\n",
              "      <td>RandomForestClassifier</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>Training</td>\n",
              "      <td>0.988595</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.977191</td>\n",
              "      <td>0.977700</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.988464</td>\n",
              "      <td>4.604301</td>\n",
              "      <td>0.872791</td>\n",
              "      <td>BaggingClassifier</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>Validation</td>\n",
              "      <td>0.928800</td>\n",
              "      <td>0.428571</td>\n",
              "      <td>0.855596</td>\n",
              "      <td>0.991005</td>\n",
              "      <td>0.933093</td>\n",
              "      <td>0.571084</td>\n",
              "      <td>0.541749</td>\n",
              "      <td>NaN</td>\n",
              "      <td>BaggingClassifier</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>Training</td>\n",
              "      <td>0.920168</td>\n",
              "      <td>0.935323</td>\n",
              "      <td>0.902761</td>\n",
              "      <td>0.906032</td>\n",
              "      <td>0.937575</td>\n",
              "      <td>0.918754</td>\n",
              "      <td>5.526041</td>\n",
              "      <td>0.866810</td>\n",
              "      <td>AdaBoostClassifier</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>Validation</td>\n",
              "      <td>0.889200</td>\n",
              "      <td>0.318480</td>\n",
              "      <td>0.877256</td>\n",
              "      <td>0.991975</td>\n",
              "      <td>0.889900</td>\n",
              "      <td>0.467308</td>\n",
              "      <td>0.643924</td>\n",
              "      <td>NaN</td>\n",
              "      <td>AdaBoostClassifier</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>Training</td>\n",
              "      <td>0.971188</td>\n",
              "      <td>0.993711</td>\n",
              "      <td>0.948379</td>\n",
              "      <td>0.950631</td>\n",
              "      <td>0.993998</td>\n",
              "      <td>0.970516</td>\n",
              "      <td>23.070930</td>\n",
              "      <td>0.892025</td>\n",
              "      <td>GradientBoostingClassifier</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>Validation</td>\n",
              "      <td>0.927200</td>\n",
              "      <td>0.425894</td>\n",
              "      <td>0.902527</td>\n",
              "      <td>0.993882</td>\n",
              "      <td>0.928647</td>\n",
              "      <td>0.578704</td>\n",
              "      <td>2.552907</td>\n",
              "      <td>NaN</td>\n",
              "      <td>GradientBoostingClassifier</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>Training</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>10.641260</td>\n",
              "      <td>0.899240</td>\n",
              "      <td>XGBClassifier</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>Validation</td>\n",
              "      <td>0.948400</td>\n",
              "      <td>0.519751</td>\n",
              "      <td>0.902527</td>\n",
              "      <td>0.994025</td>\n",
              "      <td>0.951090</td>\n",
              "      <td>0.659631</td>\n",
              "      <td>2.471798</td>\n",
              "      <td>NaN</td>\n",
              "      <td>XGBClassifier</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
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              "  "
            ]
          },
          "metadata": {},
          "execution_count": 54
        }
      ],
      "source": [
        "res_un"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "XsR-0pSVbvRx"
      },
      "source": [
        "**Observations:**\n",
        "\n",
        "Using the **undersampled** data, we can make the following observations:\n",
        "\n",
        "* When comparing the performance of models trained on original, undersampled, and oversampled data, the Recall metric appears to be more consistent for models trained on undersampled data.\n",
        "\n",
        "* **RandomForestClassifier** displays the highest performance on the training and validation datasets, indicating its potential as the most promising model for our dataset\n",
        "\n",
        "* Both **XGBClassifier** and **GradientBoostingClassifier** achieve very good scores, suggesting good generalization to unseen data.\n",
        "\n",
        "* **LogisticRegression**, **BaggingClassifier**, and **AdaBoostClassifier** demonstrate moderate performance on both training and validation datasets.\n",
        "\n",
        "* Learning durations for the models are generally shorter compared to the oversampled data scenario, with **LogisticRegression** being the fastest and **GradientBoostingClassifier** taking the longest time to train.\n",
        "\n",
        "Based on these findings, **RandomForestClassifier**, **GradientBoostingClassifier**, and **XGBClassifier** emerge as the top-performing models for the underdamped dataset. However, it is important to fine-tune and optimize these models to achieve even better performance."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "CucTNEL8cD4w"
      },
      "source": [
        "### Consolidated resultas"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Resulting columns show in percentage\n",
        "col_perc = ['Accuracy', 'Precision', 'Recall', 'NPV', 'Specificity', 'F1']"
      ],
      "metadata": {
        "id": "uCpXpjDlpSER"
      },
      "execution_count": 55,
      "outputs": []
    },
    {
      "cell_type": "code",
      "execution_count": 56,
      "metadata": {
        "id": "LnoXk8klcKYj"
      },
      "outputs": [],
      "source": [
        "res_orig['model'] += ' (original)'\n",
        "res_over['model'] += ' (oversampled)'\n",
        "res_un['model'] += ' (undersampled)'"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 57,
      "metadata": {
        "id": "8oWcCAoUp-WU"
      },
      "outputs": [],
      "source": [
        "results = pd.concat([res_orig, res_over, res_un], axis=0)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 58,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 831
        },
        "id": "hM5wHSfMcCwn",
        "outputId": "b315d3a4-bc4d-4c36-d202-cf3fecba098a"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "------------------------------------------------------------------------------------------------------------------------\n",
            "   Performance metrics of models trained on original, oversampled, and undersampled subsets of the training dataset\n",
            "------------------------------------------------------------------------------------------------------------------------\n",
            "\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7fe22e6d18a0>"
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            "text/html": [
              "<style type=\"text/css\">\n",
              "</style>\n",
              "<table id=\"T_c0473\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th class=\"blank level0\" >&nbsp;</th>\n",
              "      <th id=\"T_c0473_level0_col0\" class=\"col_heading level0 col0\" >Accuracy</th>\n",
              "      <th id=\"T_c0473_level0_col1\" class=\"col_heading level0 col1\" >Precision</th>\n",
              "      <th id=\"T_c0473_level0_col2\" class=\"col_heading level0 col2\" >Recall</th>\n",
              "      <th id=\"T_c0473_level0_col3\" class=\"col_heading level0 col3\" >NPV</th>\n",
              "      <th id=\"T_c0473_level0_col4\" class=\"col_heading level0 col4\" >Specificity</th>\n",
              "      <th id=\"T_c0473_level0_col5\" class=\"col_heading level0 col5\" >F1</th>\n",
              "      <th id=\"T_c0473_level0_col6\" class=\"col_heading level0 col6\" >duration</th>\n",
              "      <th id=\"T_c0473_level0_col7\" class=\"col_heading level0 col7\" >cv_recall</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th class=\"index_name level0\" >model</th>\n",
              "      <th class=\"blank col0\" >&nbsp;</th>\n",
              "      <th class=\"blank col1\" >&nbsp;</th>\n",
              "      <th class=\"blank col2\" >&nbsp;</th>\n",
              "      <th class=\"blank col3\" >&nbsp;</th>\n",
              "      <th class=\"blank col4\" >&nbsp;</th>\n",
              "      <th class=\"blank col5\" >&nbsp;</th>\n",
              "      <th class=\"blank col6\" >&nbsp;</th>\n",
              "      <th class=\"blank col7\" >&nbsp;</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th id=\"T_c0473_level0_row0\" class=\"row_heading level0 row0\" >DecisionTreeClassifier (undersampled)</th>\n",
              "      <td id=\"T_c0473_row0_col0\" class=\"data row0 col0\" >100.00%</td>\n",
              "      <td id=\"T_c0473_row0_col1\" class=\"data row0 col1\" >100.00%</td>\n",
              "      <td id=\"T_c0473_row0_col2\" class=\"data row0 col2\" >100.00%</td>\n",
              "      <td id=\"T_c0473_row0_col3\" class=\"data row0 col3\" >100.00%</td>\n",
              "      <td id=\"T_c0473_row0_col4\" class=\"data row0 col4\" >100.00%</td>\n",
              "      <td id=\"T_c0473_row0_col5\" class=\"data row0 col5\" >100.00%</td>\n",
              "      <td id=\"T_c0473_row0_col6\" class=\"data row0 col6\" >0.84</td>\n",
              "      <td id=\"T_c0473_row0_col7\" class=\"data row0 col7\" >85.85%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c0473_level0_row1\" class=\"row_heading level0 row1\" >RandomForestClassifier (undersampled)</th>\n",
              "      <td id=\"T_c0473_row1_col0\" class=\"data row1 col0\" >100.00%</td>\n",
              "      <td id=\"T_c0473_row1_col1\" class=\"data row1 col1\" >100.00%</td>\n",
              "      <td id=\"T_c0473_row1_col2\" class=\"data row1 col2\" >100.00%</td>\n",
              "      <td id=\"T_c0473_row1_col3\" class=\"data row1 col3\" >100.00%</td>\n",
              "      <td id=\"T_c0473_row1_col4\" class=\"data row1 col4\" >100.00%</td>\n",
              "      <td id=\"T_c0473_row1_col5\" class=\"data row1 col5\" >100.00%</td>\n",
              "      <td id=\"T_c0473_row1_col6\" class=\"data row1 col6\" >9.02</td>\n",
              "      <td id=\"T_c0473_row1_col7\" class=\"data row1 col7\" >89.92%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c0473_level0_row2\" class=\"row_heading level0 row2\" >XGBClassifier (undersampled)</th>\n",
              "      <td id=\"T_c0473_row2_col0\" class=\"data row2 col0\" >100.00%</td>\n",
              "      <td id=\"T_c0473_row2_col1\" class=\"data row2 col1\" >100.00%</td>\n",
              "      <td id=\"T_c0473_row2_col2\" class=\"data row2 col2\" >100.00%</td>\n",
              "      <td id=\"T_c0473_row2_col3\" class=\"data row2 col3\" >100.00%</td>\n",
              "      <td id=\"T_c0473_row2_col4\" class=\"data row2 col4\" >100.00%</td>\n",
              "      <td id=\"T_c0473_row2_col5\" class=\"data row2 col5\" >100.00%</td>\n",
              "      <td id=\"T_c0473_row2_col6\" class=\"data row2 col6\" >10.64</td>\n",
              "      <td id=\"T_c0473_row2_col7\" class=\"data row2 col7\" >89.92%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c0473_level0_row3\" class=\"row_heading level0 row3\" >DecisionTreeClassifier (original)</th>\n",
              "      <td id=\"T_c0473_row3_col0\" class=\"data row3 col0\" >100.00%</td>\n",
              "      <td id=\"T_c0473_row3_col1\" class=\"data row3 col1\" >100.00%</td>\n",
              "      <td id=\"T_c0473_row3_col2\" class=\"data row3 col2\" >100.00%</td>\n",
              "      <td id=\"T_c0473_row3_col3\" class=\"data row3 col3\" >100.00%</td>\n",
              "      <td id=\"T_c0473_row3_col4\" class=\"data row3 col4\" >100.00%</td>\n",
              "      <td id=\"T_c0473_row3_col5\" class=\"data row3 col5\" >100.00%</td>\n",
              "      <td id=\"T_c0473_row3_col6\" class=\"data row3 col6\" >18.28</td>\n",
              "      <td id=\"T_c0473_row3_col7\" class=\"data row3 col7\" >74.06%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c0473_level0_row4\" class=\"row_heading level0 row4\" >DecisionTreeClassifier (oversampled)</th>\n",
              "      <td id=\"T_c0473_row4_col0\" class=\"data row4 col0\" >100.00%</td>\n",
              "      <td id=\"T_c0473_row4_col1\" class=\"data row4 col1\" >100.00%</td>\n",
              "      <td id=\"T_c0473_row4_col2\" class=\"data row4 col2\" >100.00%</td>\n",
              "      <td id=\"T_c0473_row4_col3\" class=\"data row4 col3\" >100.00%</td>\n",
              "      <td id=\"T_c0473_row4_col4\" class=\"data row4 col4\" >100.00%</td>\n",
              "      <td id=\"T_c0473_row4_col5\" class=\"data row4 col5\" >100.00%</td>\n",
              "      <td id=\"T_c0473_row4_col6\" class=\"data row4 col6\" >21.93</td>\n",
              "      <td id=\"T_c0473_row4_col7\" class=\"data row4 col7\" >97.18%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c0473_level0_row5\" class=\"row_heading level0 row5\" >XGBClassifier (original)</th>\n",
              "      <td id=\"T_c0473_row5_col0\" class=\"data row5 col0\" >100.00%</td>\n",
              "      <td id=\"T_c0473_row5_col1\" class=\"data row5 col1\" >100.00%</td>\n",
              "      <td id=\"T_c0473_row5_col2\" class=\"data row5 col2\" >100.00%</td>\n",
              "      <td id=\"T_c0473_row5_col3\" class=\"data row5 col3\" >100.00%</td>\n",
              "      <td id=\"T_c0473_row5_col4\" class=\"data row5 col4\" >100.00%</td>\n",
              "      <td id=\"T_c0473_row5_col5\" class=\"data row5 col5\" >100.00%</td>\n",
              "      <td id=\"T_c0473_row5_col6\" class=\"data row5 col6\" >106.62</td>\n",
              "      <td id=\"T_c0473_row5_col7\" class=\"data row5 col7\" >79.59%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c0473_level0_row6\" class=\"row_heading level0 row6\" >RandomForestClassifier (oversampled)</th>\n",
              "      <td id=\"T_c0473_row6_col0\" class=\"data row6 col0\" >100.00%</td>\n",
              "      <td id=\"T_c0473_row6_col1\" class=\"data row6 col1\" >100.00%</td>\n",
              "      <td id=\"T_c0473_row6_col2\" class=\"data row6 col2\" >100.00%</td>\n",
              "      <td id=\"T_c0473_row6_col3\" class=\"data row6 col3\" >100.00%</td>\n",
              "      <td id=\"T_c0473_row6_col4\" class=\"data row6 col4\" >100.00%</td>\n",
              "      <td id=\"T_c0473_row6_col5\" class=\"data row6 col5\" >100.00%</td>\n",
              "      <td id=\"T_c0473_row6_col6\" class=\"data row6 col6\" >191.59</td>\n",
              "      <td id=\"T_c0473_row6_col7\" class=\"data row6 col7\" >98.48%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c0473_level0_row7\" class=\"row_heading level0 row7\" >XGBClassifier (oversampled)</th>\n",
              "      <td id=\"T_c0473_row7_col0\" class=\"data row7 col0\" >99.99%</td>\n",
              "      <td id=\"T_c0473_row7_col1\" class=\"data row7 col1\" >99.99%</td>\n",
              "      <td id=\"T_c0473_row7_col2\" class=\"data row7 col2\" >99.99%</td>\n",
              "      <td id=\"T_c0473_row7_col3\" class=\"data row7 col3\" >99.99%</td>\n",
              "      <td id=\"T_c0473_row7_col4\" class=\"data row7 col4\" >99.99%</td>\n",
              "      <td id=\"T_c0473_row7_col5\" class=\"data row7 col5\" >99.99%</td>\n",
              "      <td id=\"T_c0473_row7_col6\" class=\"data row7 col6\" >226.97</td>\n",
              "      <td id=\"T_c0473_row7_col7\" class=\"data row7 col7\" >99.05%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c0473_level0_row8\" class=\"row_heading level0 row8\" >RandomForestClassifier (original)</th>\n",
              "      <td id=\"T_c0473_row8_col0\" class=\"data row8 col0\" >99.99%</td>\n",
              "      <td id=\"T_c0473_row8_col1\" class=\"data row8 col1\" >100.00%</td>\n",
              "      <td id=\"T_c0473_row8_col2\" class=\"data row8 col2\" >99.88%</td>\n",
              "      <td id=\"T_c0473_row8_col3\" class=\"data row8 col3\" >99.99%</td>\n",
              "      <td id=\"T_c0473_row8_col4\" class=\"data row8 col4\" >100.00%</td>\n",
              "      <td id=\"T_c0473_row8_col5\" class=\"data row8 col5\" >99.94%</td>\n",
              "      <td id=\"T_c0473_row8_col6\" class=\"data row8 col6\" >139.68</td>\n",
              "      <td id=\"T_c0473_row8_col7\" class=\"data row8 col7\" >72.75%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c0473_level0_row9\" class=\"row_heading level0 row9\" >BaggingClassifier (oversampled)</th>\n",
              "      <td id=\"T_c0473_row9_col0\" class=\"data row9 col0\" >99.92%</td>\n",
              "      <td id=\"T_c0473_row9_col1\" class=\"data row9 col1\" >99.97%</td>\n",
              "      <td id=\"T_c0473_row9_col2\" class=\"data row9 col2\" >99.87%</td>\n",
              "      <td id=\"T_c0473_row9_col3\" class=\"data row9 col3\" >99.87%</td>\n",
              "      <td id=\"T_c0473_row9_col4\" class=\"data row9 col4\" >99.97%</td>\n",
              "      <td id=\"T_c0473_row9_col5\" class=\"data row9 col5\" >99.92%</td>\n",
              "      <td id=\"T_c0473_row9_col6\" class=\"data row9 col6\" >137.09</td>\n",
              "      <td id=\"T_c0473_row9_col7\" class=\"data row9 col7\" >97.55%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c0473_level0_row10\" class=\"row_heading level0 row10\" >BaggingClassifier (undersampled)</th>\n",
              "      <td id=\"T_c0473_row10_col0\" class=\"data row10 col0\" >98.86%</td>\n",
              "      <td id=\"T_c0473_row10_col1\" class=\"data row10 col1\" >100.00%</td>\n",
              "      <td id=\"T_c0473_row10_col2\" class=\"data row10 col2\" >97.72%</td>\n",
              "      <td id=\"T_c0473_row10_col3\" class=\"data row10 col3\" >97.77%</td>\n",
              "      <td id=\"T_c0473_row10_col4\" class=\"data row10 col4\" >100.00%</td>\n",
              "      <td id=\"T_c0473_row10_col5\" class=\"data row10 col5\" >98.85%</td>\n",
              "      <td id=\"T_c0473_row10_col6\" class=\"data row10 col6\" >4.60</td>\n",
              "      <td id=\"T_c0473_row10_col7\" class=\"data row10 col7\" >87.28%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c0473_level0_row11\" class=\"row_heading level0 row11\" >BaggingClassifier (original)</th>\n",
              "      <td id=\"T_c0473_row11_col0\" class=\"data row11 col0\" >99.76%</td>\n",
              "      <td id=\"T_c0473_row11_col1\" class=\"data row11 col1\" >99.87%</td>\n",
              "      <td id=\"T_c0473_row11_col2\" class=\"data row11 col2\" >95.80%</td>\n",
              "      <td id=\"T_c0473_row11_col3\" class=\"data row11 col3\" >99.75%</td>\n",
              "      <td id=\"T_c0473_row11_col4\" class=\"data row11 col4\" >99.99%</td>\n",
              "      <td id=\"T_c0473_row11_col5\" class=\"data row11 col5\" >97.79%</td>\n",
              "      <td id=\"T_c0473_row11_col6\" class=\"data row11 col6\" >108.72</td>\n",
              "      <td id=\"T_c0473_row11_col7\" class=\"data row11 col7\" >70.82%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c0473_level0_row12\" class=\"row_heading level0 row12\" >GradientBoostingClassifier (undersampled)</th>\n",
              "      <td id=\"T_c0473_row12_col0\" class=\"data row12 col0\" >97.12%</td>\n",
              "      <td id=\"T_c0473_row12_col1\" class=\"data row12 col1\" >99.37%</td>\n",
              "      <td id=\"T_c0473_row12_col2\" class=\"data row12 col2\" >94.84%</td>\n",
              "      <td id=\"T_c0473_row12_col3\" class=\"data row12 col3\" >95.06%</td>\n",
              "      <td id=\"T_c0473_row12_col4\" class=\"data row12 col4\" >99.40%</td>\n",
              "      <td id=\"T_c0473_row12_col5\" class=\"data row12 col5\" >97.05%</td>\n",
              "      <td id=\"T_c0473_row12_col6\" class=\"data row12 col6\" >23.07</td>\n",
              "      <td id=\"T_c0473_row12_col7\" class=\"data row12 col7\" >89.20%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c0473_level0_row13\" class=\"row_heading level0 row13\" >GradientBoostingClassifier (oversampled)</th>\n",
              "      <td id=\"T_c0473_row13_col0\" class=\"data row13 col0\" >94.92%</td>\n",
              "      <td id=\"T_c0473_row13_col1\" class=\"data row13 col1\" >96.98%</td>\n",
              "      <td id=\"T_c0473_row13_col2\" class=\"data row13 col2\" >92.73%</td>\n",
              "      <td id=\"T_c0473_row13_col3\" class=\"data row13 col3\" >93.03%</td>\n",
              "      <td id=\"T_c0473_row13_col4\" class=\"data row13 col4\" >97.11%</td>\n",
              "      <td id=\"T_c0473_row13_col5\" class=\"data row13 col5\" >94.81%</td>\n",
              "      <td id=\"T_c0473_row13_col6\" class=\"data row13 col6\" >468.36</td>\n",
              "      <td id=\"T_c0473_row13_col7\" class=\"data row13 col7\" >92.40%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c0473_level0_row14\" class=\"row_heading level0 row14\" >AdaBoostClassifier (undersampled)</th>\n",
              "      <td id=\"T_c0473_row14_col0\" class=\"data row14 col0\" >92.02%</td>\n",
              "      <td id=\"T_c0473_row14_col1\" class=\"data row14 col1\" >93.53%</td>\n",
              "      <td id=\"T_c0473_row14_col2\" class=\"data row14 col2\" >90.28%</td>\n",
              "      <td id=\"T_c0473_row14_col3\" class=\"data row14 col3\" >90.60%</td>\n",
              "      <td id=\"T_c0473_row14_col4\" class=\"data row14 col4\" >93.76%</td>\n",
              "      <td id=\"T_c0473_row14_col5\" class=\"data row14 col5\" >91.88%</td>\n",
              "      <td id=\"T_c0473_row14_col6\" class=\"data row14 col6\" >5.53</td>\n",
              "      <td id=\"T_c0473_row14_col7\" class=\"data row14 col7\" >86.68%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c0473_level0_row15\" class=\"row_heading level0 row15\" >AdaBoostClassifier (oversampled)</th>\n",
              "      <td id=\"T_c0473_row15_col0\" class=\"data row15 col0\" >90.62%</td>\n",
              "      <td id=\"T_c0473_row15_col1\" class=\"data row15 col1\" >91.53%</td>\n",
              "      <td id=\"T_c0473_row15_col2\" class=\"data row15 col2\" >89.53%</td>\n",
              "      <td id=\"T_c0473_row15_col3\" class=\"data row15 col3\" >89.76%</td>\n",
              "      <td id=\"T_c0473_row15_col4\" class=\"data row15 col4\" >91.71%</td>\n",
              "      <td id=\"T_c0473_row15_col5\" class=\"data row15 col5\" >90.52%</td>\n",
              "      <td id=\"T_c0473_row15_col6\" class=\"data row15 col6\" >96.17</td>\n",
              "      <td id=\"T_c0473_row15_col7\" class=\"data row15 col7\" >89.23%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c0473_level0_row16\" class=\"row_heading level0 row16\" >LogisticRegression (oversampled)</th>\n",
              "      <td id=\"T_c0473_row16_col0\" class=\"data row16 col0\" >87.45%</td>\n",
              "      <td id=\"T_c0473_row16_col1\" class=\"data row16 col1\" >87.46%</td>\n",
              "      <td id=\"T_c0473_row16_col2\" class=\"data row16 col2\" >87.43%</td>\n",
              "      <td id=\"T_c0473_row16_col3\" class=\"data row16 col3\" >87.43%</td>\n",
              "      <td id=\"T_c0473_row16_col4\" class=\"data row16 col4\" >87.46%</td>\n",
              "      <td id=\"T_c0473_row16_col5\" class=\"data row16 col5\" >87.44%</td>\n",
              "      <td id=\"T_c0473_row16_col6\" class=\"data row16 col6\" >1.37</td>\n",
              "      <td id=\"T_c0473_row16_col7\" class=\"data row16 col7\" >87.39%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c0473_level0_row17\" class=\"row_heading level0 row17\" >LogisticRegression (undersampled)</th>\n",
              "      <td id=\"T_c0473_row17_col0\" class=\"data row17 col0\" >86.37%</td>\n",
              "      <td id=\"T_c0473_row17_col1\" class=\"data row17 col1\" >86.59%</td>\n",
              "      <td id=\"T_c0473_row17_col2\" class=\"data row17 col2\" >86.07%</td>\n",
              "      <td id=\"T_c0473_row17_col3\" class=\"data row17 col3\" >86.16%</td>\n",
              "      <td id=\"T_c0473_row17_col4\" class=\"data row17 col4\" >86.67%</td>\n",
              "      <td id=\"T_c0473_row17_col5\" class=\"data row17 col5\" >86.33%</td>\n",
              "      <td id=\"T_c0473_row17_col6\" class=\"data row17 col6\" >0.25</td>\n",
              "      <td id=\"T_c0473_row17_col7\" class=\"data row17 col7\" >85.71%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c0473_level0_row18\" class=\"row_heading level0 row18\" >GradientBoostingClassifier (original)</th>\n",
              "      <td id=\"T_c0473_row18_col0\" class=\"data row18 col0\" >98.78%</td>\n",
              "      <td id=\"T_c0473_row18_col1\" class=\"data row18 col1\" >97.51%</td>\n",
              "      <td id=\"T_c0473_row18_col2\" class=\"data row18 col2\" >80.07%</td>\n",
              "      <td id=\"T_c0473_row18_col3\" class=\"data row18 col3\" >98.84%</td>\n",
              "      <td id=\"T_c0473_row18_col4\" class=\"data row18 col4\" >99.88%</td>\n",
              "      <td id=\"T_c0473_row18_col5\" class=\"data row18 col5\" >87.94%</td>\n",
              "      <td id=\"T_c0473_row18_col6\" class=\"data row18 col6\" >242.12</td>\n",
              "      <td id=\"T_c0473_row18_col7\" class=\"data row18 col7\" >69.63%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c0473_level0_row19\" class=\"row_heading level0 row19\" >AdaBoostClassifier (original)</th>\n",
              "      <td id=\"T_c0473_row19_col0\" class=\"data row19 col0\" >97.63%</td>\n",
              "      <td id=\"T_c0473_row19_col1\" class=\"data row19 col1\" >89.31%</td>\n",
              "      <td id=\"T_c0473_row19_col2\" class=\"data row19 col2\" >65.19%</td>\n",
              "      <td id=\"T_c0473_row19_col3\" class=\"data row19 col3\" >97.98%</td>\n",
              "      <td id=\"T_c0473_row19_col4\" class=\"data row19 col4\" >99.54%</td>\n",
              "      <td id=\"T_c0473_row19_col5\" class=\"data row19 col5\" >75.36%</td>\n",
              "      <td id=\"T_c0473_row19_col6\" class=\"data row19 col6\" >48.78</td>\n",
              "      <td id=\"T_c0473_row19_col7\" class=\"data row19 col7\" >59.66%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c0473_level0_row20\" class=\"row_heading level0 row20\" >LogisticRegression (original)</th>\n",
              "      <td id=\"T_c0473_row20_col0\" class=\"data row20 col0\" >96.65%</td>\n",
              "      <td id=\"T_c0473_row20_col1\" class=\"data row20 col1\" >84.23%</td>\n",
              "      <td id=\"T_c0473_row20_col2\" class=\"data row20 col2\" >48.74%</td>\n",
              "      <td id=\"T_c0473_row20_col3\" class=\"data row20 col3\" >97.06%</td>\n",
              "      <td id=\"T_c0473_row20_col4\" class=\"data row20 col4\" >99.46%</td>\n",
              "      <td id=\"T_c0473_row20_col5\" class=\"data row20 col5\" >61.75%</td>\n",
              "      <td id=\"T_c0473_row20_col6\" class=\"data row20 col6\" >0.59</td>\n",
              "      <td id=\"T_c0473_row20_col7\" class=\"data row20 col7\" >48.98%</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n"
            ]
          },
          "metadata": {},
          "execution_count": 58
        }
      ],
      "source": [
        "print(f\"\\n{'-'*120}\\n   Performance metrics of models trained on original, oversampled, and undersampled subsets of the training dataset\\n{'-'*120}\\n\")\n",
        "results[results['index']=='Training'].set_index('model').drop('index', axis=1)\\\n",
        "  .sort_values(by=['Recall', 'duration'], ascending=[False, True]).style\\\n",
        "  .format('{:.2f}')\\\n",
        "  .format('{:.2%}', subset=col_perc+['cv_recall'])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 59,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 831
        },
        "id": "ZiIYEcaycUn6",
        "outputId": "54ce5699-dd8b-4b30-fa00-06314cbff58d"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "---------------------------------------------------------------------------------------------------------------------------\n",
            "Performance metrics of models trained on original, oversampled, and undersampled subsets of the validation dataset (Recall)\n",
            "---------------------------------------------------------------------------------------------------------------------------\n",
            "\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7fe22e83d360>"
            ],
            "text/html": [
              "<style type=\"text/css\">\n",
              "#T_78513 th {\n",
              "  min-width: 75px;\n",
              "  text-align: right;\n",
              "}\n",
              "#T_78513_row0_col2, #T_78513_row0_col3, #T_78513_row6_col6, #T_78513_row12_col0, #T_78513_row12_col5, #T_78513_row15_col1, #T_78513_row15_col4 {\n",
              "  background-color: lightgreen;\n",
              "}\n",
              "</style>\n",
              "<table id=\"T_78513\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th class=\"blank level0\" >&nbsp;</th>\n",
              "      <th id=\"T_78513_level0_col0\" class=\"col_heading level0 col0\" >Accuracy</th>\n",
              "      <th id=\"T_78513_level0_col1\" class=\"col_heading level0 col1\" >Precision</th>\n",
              "      <th id=\"T_78513_level0_col2\" class=\"col_heading level0 col2\" >Recall</th>\n",
              "      <th id=\"T_78513_level0_col3\" class=\"col_heading level0 col3\" >NPV</th>\n",
              "      <th id=\"T_78513_level0_col4\" class=\"col_heading level0 col4\" >Specificity</th>\n",
              "      <th id=\"T_78513_level0_col5\" class=\"col_heading level0 col5\" >F1</th>\n",
              "      <th id=\"T_78513_level0_col6\" class=\"col_heading level0 col6\" >duration</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th class=\"index_name level0\" >model</th>\n",
              "      <th class=\"blank col0\" >&nbsp;</th>\n",
              "      <th class=\"blank col1\" >&nbsp;</th>\n",
              "      <th class=\"blank col2\" >&nbsp;</th>\n",
              "      <th class=\"blank col3\" >&nbsp;</th>\n",
              "      <th class=\"blank col4\" >&nbsp;</th>\n",
              "      <th class=\"blank col5\" >&nbsp;</th>\n",
              "      <th class=\"blank col6\" >&nbsp;</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th id=\"T_78513_level0_row0\" class=\"row_heading level0 row0\" >RandomForestClassifier (undersampled)</th>\n",
              "      <td id=\"T_78513_row0_col0\" class=\"data row0 col0\" >95.08%</td>\n",
              "      <td id=\"T_78513_row0_col1\" class=\"data row0 col1\" >53.26%</td>\n",
              "      <td id=\"T_78513_row0_col2\" class=\"data row0 col2\" >91.34%</td>\n",
              "      <td id=\"T_78513_row0_col3\" class=\"data row0 col3\" >99.47%</td>\n",
              "      <td id=\"T_78513_row0_col4\" class=\"data row0 col4\" >95.30%</td>\n",
              "      <td id=\"T_78513_row0_col5\" class=\"data row0 col5\" >67.29%</td>\n",
              "      <td id=\"T_78513_row0_col6\" class=\"data row0 col6\" >0.99</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_78513_level0_row1\" class=\"row_heading level0 row1\" >XGBClassifier (undersampled)</th>\n",
              "      <td id=\"T_78513_row1_col0\" class=\"data row1 col0\" >94.84%</td>\n",
              "      <td id=\"T_78513_row1_col1\" class=\"data row1 col1\" >51.98%</td>\n",
              "      <td id=\"T_78513_row1_col2\" class=\"data row1 col2\" >90.25%</td>\n",
              "      <td id=\"T_78513_row1_col3\" class=\"data row1 col3\" >99.40%</td>\n",
              "      <td id=\"T_78513_row1_col4\" class=\"data row1 col4\" >95.11%</td>\n",
              "      <td id=\"T_78513_row1_col5\" class=\"data row1 col5\" >65.96%</td>\n",
              "      <td id=\"T_78513_row1_col6\" class=\"data row1 col6\" >2.47</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_78513_level0_row2\" class=\"row_heading level0 row2\" >GradientBoostingClassifier (undersampled)</th>\n",
              "      <td id=\"T_78513_row2_col0\" class=\"data row2 col0\" >92.72%</td>\n",
              "      <td id=\"T_78513_row2_col1\" class=\"data row2 col1\" >42.59%</td>\n",
              "      <td id=\"T_78513_row2_col2\" class=\"data row2 col2\" >90.25%</td>\n",
              "      <td id=\"T_78513_row2_col3\" class=\"data row2 col3\" >99.39%</td>\n",
              "      <td id=\"T_78513_row2_col4\" class=\"data row2 col4\" >92.86%</td>\n",
              "      <td id=\"T_78513_row2_col5\" class=\"data row2 col5\" >57.87%</td>\n",
              "      <td id=\"T_78513_row2_col6\" class=\"data row2 col6\" >2.55</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_78513_level0_row3\" class=\"row_heading level0 row3\" >GradientBoostingClassifier (oversampled)</th>\n",
              "      <td id=\"T_78513_row3_col0\" class=\"data row3 col0\" >96.10%</td>\n",
              "      <td id=\"T_78513_row3_col1\" class=\"data row3 col1\" >59.90%</td>\n",
              "      <td id=\"T_78513_row3_col2\" class=\"data row3 col2\" >89.53%</td>\n",
              "      <td id=\"T_78513_row3_col3\" class=\"data row3 col3\" >99.37%</td>\n",
              "      <td id=\"T_78513_row3_col4\" class=\"data row3 col4\" >96.49%</td>\n",
              "      <td id=\"T_78513_row3_col5\" class=\"data row3 col5\" >71.78%</td>\n",
              "      <td id=\"T_78513_row3_col6\" class=\"data row3 col6\" >52.77</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_78513_level0_row4\" class=\"row_heading level0 row4\" >XGBClassifier (oversampled)</th>\n",
              "      <td id=\"T_78513_row4_col0\" class=\"data row4 col0\" >98.62%</td>\n",
              "      <td id=\"T_78513_row4_col1\" class=\"data row4 col1\" >86.36%</td>\n",
              "      <td id=\"T_78513_row4_col2\" class=\"data row4 col2\" >89.17%</td>\n",
              "      <td id=\"T_78513_row4_col3\" class=\"data row4 col3\" >99.36%</td>\n",
              "      <td id=\"T_78513_row4_col4\" class=\"data row4 col4\" >99.17%</td>\n",
              "      <td id=\"T_78513_row4_col5\" class=\"data row4 col5\" >87.74%</td>\n",
              "      <td id=\"T_78513_row4_col6\" class=\"data row4 col6\" >25.28</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_78513_level0_row5\" class=\"row_heading level0 row5\" >AdaBoostClassifier (oversampled)</th>\n",
              "      <td id=\"T_78513_row5_col0\" class=\"data row5 col0\" >91.00%</td>\n",
              "      <td id=\"T_78513_row5_col1\" class=\"data row5 col1\" >36.99%</td>\n",
              "      <td id=\"T_78513_row5_col2\" class=\"data row5 col2\" >88.81%</td>\n",
              "      <td id=\"T_78513_row5_col3\" class=\"data row5 col3\" >99.28%</td>\n",
              "      <td id=\"T_78513_row5_col4\" class=\"data row5 col4\" >91.13%</td>\n",
              "      <td id=\"T_78513_row5_col5\" class=\"data row5 col5\" >52.23%</td>\n",
              "      <td id=\"T_78513_row5_col6\" class=\"data row5 col6\" >11.01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_78513_level0_row6\" class=\"row_heading level0 row6\" >LogisticRegression (undersampled)</th>\n",
              "      <td id=\"T_78513_row6_col0\" class=\"data row6 col0\" >86.44%</td>\n",
              "      <td id=\"T_78513_row6_col1\" class=\"data row6 col1\" >27.45%</td>\n",
              "      <td id=\"T_78513_row6_col2\" class=\"data row6 col2\" >88.09%</td>\n",
              "      <td id=\"T_78513_row6_col3\" class=\"data row6 col3\" >99.20%</td>\n",
              "      <td id=\"T_78513_row6_col4\" class=\"data row6 col4\" >86.34%</td>\n",
              "      <td id=\"T_78513_row6_col5\" class=\"data row6 col5\" >41.85%</td>\n",
              "      <td id=\"T_78513_row6_col6\" class=\"data row6 col6\" >0.03</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_78513_level0_row7\" class=\"row_heading level0 row7\" >LogisticRegression (oversampled)</th>\n",
              "      <td id=\"T_78513_row7_col0\" class=\"data row7 col0\" >87.88%</td>\n",
              "      <td id=\"T_78513_row7_col1\" class=\"data row7 col1\" >29.82%</td>\n",
              "      <td id=\"T_78513_row7_col2\" class=\"data row7 col2\" >87.73%</td>\n",
              "      <td id=\"T_78513_row7_col3\" class=\"data row7 col3\" >99.19%</td>\n",
              "      <td id=\"T_78513_row7_col4\" class=\"data row7 col4\" >87.89%</td>\n",
              "      <td id=\"T_78513_row7_col5\" class=\"data row7 col5\" >44.51%</td>\n",
              "      <td id=\"T_78513_row7_col6\" class=\"data row7 col6\" >0.19</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_78513_level0_row8\" class=\"row_heading level0 row8\" >AdaBoostClassifier (undersampled)</th>\n",
              "      <td id=\"T_78513_row8_col0\" class=\"data row8 col0\" >88.92%</td>\n",
              "      <td id=\"T_78513_row8_col1\" class=\"data row8 col1\" >31.85%</td>\n",
              "      <td id=\"T_78513_row8_col2\" class=\"data row8 col2\" >87.73%</td>\n",
              "      <td id=\"T_78513_row8_col3\" class=\"data row8 col3\" >99.20%</td>\n",
              "      <td id=\"T_78513_row8_col4\" class=\"data row8 col4\" >88.99%</td>\n",
              "      <td id=\"T_78513_row8_col5\" class=\"data row8 col5\" >46.73%</td>\n",
              "      <td id=\"T_78513_row8_col6\" class=\"data row8 col6\" >0.64</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_78513_level0_row9\" class=\"row_heading level0 row9\" >RandomForestClassifier (oversampled)</th>\n",
              "      <td id=\"T_78513_row9_col0\" class=\"data row9 col0\" >98.88%</td>\n",
              "      <td id=\"T_78513_row9_col1\" class=\"data row9 col1\" >93.33%</td>\n",
              "      <td id=\"T_78513_row9_col2\" class=\"data row9 col2\" >85.92%</td>\n",
              "      <td id=\"T_78513_row9_col3\" class=\"data row9 col3\" >99.18%</td>\n",
              "      <td id=\"T_78513_row9_col4\" class=\"data row9 col4\" >99.64%</td>\n",
              "      <td id=\"T_78513_row9_col5\" class=\"data row9 col5\" >89.47%</td>\n",
              "      <td id=\"T_78513_row9_col6\" class=\"data row9 col6\" >21.77</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_78513_level0_row10\" class=\"row_heading level0 row10\" >BaggingClassifier (undersampled)</th>\n",
              "      <td id=\"T_78513_row10_col0\" class=\"data row10 col0\" >92.88%</td>\n",
              "      <td id=\"T_78513_row10_col1\" class=\"data row10 col1\" >42.86%</td>\n",
              "      <td id=\"T_78513_row10_col2\" class=\"data row10 col2\" >85.56%</td>\n",
              "      <td id=\"T_78513_row10_col3\" class=\"data row10 col3\" >99.10%</td>\n",
              "      <td id=\"T_78513_row10_col4\" class=\"data row10 col4\" >93.31%</td>\n",
              "      <td id=\"T_78513_row10_col5\" class=\"data row10 col5\" >57.11%</td>\n",
              "      <td id=\"T_78513_row10_col6\" class=\"data row10 col6\" >0.54</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_78513_level0_row11\" class=\"row_heading level0 row11\" >DecisionTreeClassifier (undersampled)</th>\n",
              "      <td id=\"T_78513_row11_col0\" class=\"data row11 col0\" >83.78%</td>\n",
              "      <td id=\"T_78513_row11_col1\" class=\"data row11 col1\" >23.41%</td>\n",
              "      <td id=\"T_78513_row11_col2\" class=\"data row11 col2\" >84.84%</td>\n",
              "      <td id=\"T_78513_row11_col3\" class=\"data row11 col3\" >98.95%</td>\n",
              "      <td id=\"T_78513_row11_col4\" class=\"data row11 col4\" >83.72%</td>\n",
              "      <td id=\"T_78513_row11_col5\" class=\"data row11 col5\" >36.69%</td>\n",
              "      <td id=\"T_78513_row11_col6\" class=\"data row11 col6\" >0.09</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_78513_level0_row12\" class=\"row_heading level0 row12\" >XGBClassifier (original)</th>\n",
              "      <td id=\"T_78513_row12_col0\" class=\"data row12 col0\" >98.96%</td>\n",
              "      <td id=\"T_78513_row12_col1\" class=\"data row12 col1\" >97.07%</td>\n",
              "      <td id=\"T_78513_row12_col2\" class=\"data row12 col2\" >83.75%</td>\n",
              "      <td id=\"T_78513_row12_col3\" class=\"data row12 col3\" >99.05%</td>\n",
              "      <td id=\"T_78513_row12_col4\" class=\"data row12 col4\" >99.85%</td>\n",
              "      <td id=\"T_78513_row12_col5\" class=\"data row12 col5\" >89.92%</td>\n",
              "      <td id=\"T_78513_row12_col6\" class=\"data row12 col6\" >11.58</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_78513_level0_row13\" class=\"row_heading level0 row13\" >BaggingClassifier (oversampled)</th>\n",
              "      <td id=\"T_78513_row13_col0\" class=\"data row13 col0\" >98.10%</td>\n",
              "      <td id=\"T_78513_row13_col1\" class=\"data row13 col1\" >82.73%</td>\n",
              "      <td id=\"T_78513_row13_col2\" class=\"data row13 col2\" >83.03%</td>\n",
              "      <td id=\"T_78513_row13_col3\" class=\"data row13 col3\" >99.00%</td>\n",
              "      <td id=\"T_78513_row13_col4\" class=\"data row13 col4\" >98.98%</td>\n",
              "      <td id=\"T_78513_row13_col5\" class=\"data row13 col5\" >82.88%</td>\n",
              "      <td id=\"T_78513_row13_col6\" class=\"data row13 col6\" >15.60</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_78513_level0_row14\" class=\"row_heading level0 row14\" >DecisionTreeClassifier (oversampled)</th>\n",
              "      <td id=\"T_78513_row14_col0\" class=\"data row14 col0\" >94.20%</td>\n",
              "      <td id=\"T_78513_row14_col1\" class=\"data row14 col1\" >48.51%</td>\n",
              "      <td id=\"T_78513_row14_col2\" class=\"data row14 col2\" >76.53%</td>\n",
              "      <td id=\"T_78513_row14_col3\" class=\"data row14 col3\" >98.58%</td>\n",
              "      <td id=\"T_78513_row14_col4\" class=\"data row14 col4\" >95.24%</td>\n",
              "      <td id=\"T_78513_row14_col5\" class=\"data row14 col5\" >59.38%</td>\n",
              "      <td id=\"T_78513_row14_col6\" class=\"data row14 col6\" >2.58</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_78513_level0_row15\" class=\"row_heading level0 row15\" >RandomForestClassifier (original)</th>\n",
              "      <td id=\"T_78513_row15_col0\" class=\"data row15 col0\" >98.60%</td>\n",
              "      <td id=\"T_78513_row15_col1\" class=\"data row15 col1\" >98.59%</td>\n",
              "      <td id=\"T_78513_row15_col2\" class=\"data row15 col2\" >75.81%</td>\n",
              "      <td id=\"T_78513_row15_col3\" class=\"data row15 col3\" >98.60%</td>\n",
              "      <td id=\"T_78513_row15_col4\" class=\"data row15 col4\" >99.94%</td>\n",
              "      <td id=\"T_78513_row15_col5\" class=\"data row15 col5\" >85.71%</td>\n",
              "      <td id=\"T_78513_row15_col6\" class=\"data row15 col6\" >15.56</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_78513_level0_row16\" class=\"row_heading level0 row16\" >DecisionTreeClassifier (original)</th>\n",
              "      <td id=\"T_78513_row16_col0\" class=\"data row16 col0\" >96.92%</td>\n",
              "      <td id=\"T_78513_row16_col1\" class=\"data row16 col1\" >71.73%</td>\n",
              "      <td id=\"T_78513_row16_col2\" class=\"data row16 col2\" >73.29%</td>\n",
              "      <td id=\"T_78513_row16_col3\" class=\"data row16 col3\" >98.43%</td>\n",
              "      <td id=\"T_78513_row16_col4\" class=\"data row16 col4\" >98.31%</td>\n",
              "      <td id=\"T_78513_row16_col5\" class=\"data row16 col5\" >72.50%</td>\n",
              "      <td id=\"T_78513_row16_col6\" class=\"data row16 col6\" >2.14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_78513_level0_row17\" class=\"row_heading level0 row17\" >GradientBoostingClassifier (original)</th>\n",
              "      <td id=\"T_78513_row17_col0\" class=\"data row17 col0\" >98.28%</td>\n",
              "      <td id=\"T_78513_row17_col1\" class=\"data row17 col1\" >95.69%</td>\n",
              "      <td id=\"T_78513_row17_col2\" class=\"data row17 col2\" >72.20%</td>\n",
              "      <td id=\"T_78513_row17_col3\" class=\"data row17 col3\" >98.39%</td>\n",
              "      <td id=\"T_78513_row17_col4\" class=\"data row17 col4\" >99.81%</td>\n",
              "      <td id=\"T_78513_row17_col5\" class=\"data row17 col5\" >82.30%</td>\n",
              "      <td id=\"T_78513_row17_col6\" class=\"data row17 col6\" >26.89</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_78513_level0_row18\" class=\"row_heading level0 row18\" >BaggingClassifier (original)</th>\n",
              "      <td id=\"T_78513_row18_col0\" class=\"data row18 col0\" >98.20%</td>\n",
              "      <td id=\"T_78513_row18_col1\" class=\"data row18 col1\" >95.61%</td>\n",
              "      <td id=\"T_78513_row18_col2\" class=\"data row18 col2\" >70.76%</td>\n",
              "      <td id=\"T_78513_row18_col3\" class=\"data row18 col3\" >98.31%</td>\n",
              "      <td id=\"T_78513_row18_col4\" class=\"data row18 col4\" >99.81%</td>\n",
              "      <td id=\"T_78513_row18_col5\" class=\"data row18 col5\" >81.33%</td>\n",
              "      <td id=\"T_78513_row18_col6\" class=\"data row18 col6\" >12.69</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_78513_level0_row19\" class=\"row_heading level0 row19\" >AdaBoostClassifier (original)</th>\n",
              "      <td id=\"T_78513_row19_col0\" class=\"data row19 col0\" >97.76%</td>\n",
              "      <td id=\"T_78513_row19_col1\" class=\"data row19 col1\" >90.64%</td>\n",
              "      <td id=\"T_78513_row19_col2\" class=\"data row19 col2\" >66.43%</td>\n",
              "      <td id=\"T_78513_row19_col3\" class=\"data row19 col3\" >98.06%</td>\n",
              "      <td id=\"T_78513_row19_col4\" class=\"data row19 col4\" >99.60%</td>\n",
              "      <td id=\"T_78513_row19_col5\" class=\"data row19 col5\" >76.67%</td>\n",
              "      <td id=\"T_78513_row19_col6\" class=\"data row19 col6\" >5.23</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_78513_level0_row20\" class=\"row_heading level0 row20\" >LogisticRegression (original)</th>\n",
              "      <td id=\"T_78513_row20_col0\" class=\"data row20 col0\" >96.66%</td>\n",
              "      <td id=\"T_78513_row20_col1\" class=\"data row20 col1\" >88.19%</td>\n",
              "      <td id=\"T_78513_row20_col2\" class=\"data row20 col2\" >45.85%</td>\n",
              "      <td id=\"T_78513_row20_col3\" class=\"data row20 col3\" >96.91%</td>\n",
              "      <td id=\"T_78513_row20_col4\" class=\"data row20 col4\" >99.64%</td>\n",
              "      <td id=\"T_78513_row20_col5\" class=\"data row20 col5\" >60.33%</td>\n",
              "      <td id=\"T_78513_row20_col6\" class=\"data row20 col6\" >0.06</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n"
            ]
          },
          "metadata": {},
          "execution_count": 59
        }
      ],
      "source": [
        "print(f\"\\n{'-'*123}\\nPerformance metrics of models trained on original, oversampled, and undersampled subsets of the validation dataset (Recall)\\n{'-'*123}\\n\")\n",
        "\n",
        "results[results['index']=='Validation'].set_index('model').drop(['index', 'cv_recall'], axis=1)\\\n",
        "  .sort_values(by=['Recall', 'duration'], ascending=[False, True]).style\\\n",
        "  .set_table_styles([dict(selector=\"th\", props=[('min-width', '75px'), \n",
        "                                                ('text-align', 'right')])])\\\n",
        "  .highlight_max(color='lightgreen', axis=0, subset=col_perc)\\\n",
        "  .highlight_min(color='lightgreen', axis=0, subset=['duration'])\\\n",
        "  .format('{:.2f}')\\\n",
        "  .format('{:.2%}', subset=col_perc)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 60,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 831
        },
        "id": "0KDkyrzCp17P",
        "outputId": "8a3ed8dc-3491-4968-da45-1a07bcdcb98d"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "--------------------------------------------------------------------------------------------------------------------------\n",
            "   Performance metrics of models trained on original, oversampled, and undersampled subsets of the validation dataset (F1)\n",
            "--------------------------------------------------------------------------------------------------------------------------\n",
            "\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7fe22e6d3c10>"
            ],
            "text/html": [
              "<style type=\"text/css\">\n",
              "#T_c8788 th {\n",
              "  min-width: 75px;\n",
              "  text-align: right;\n",
              "}\n",
              "#T_c8788_row0_col0, #T_c8788_row0_col5, #T_c8788_row3_col1, #T_c8788_row3_col4, #T_c8788_row10_col2, #T_c8788_row10_col3, #T_c8788_row19_col6 {\n",
              "  background-color: lightgreen;\n",
              "}\n",
              "</style>\n",
              "<table id=\"T_c8788\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th class=\"blank level0\" >&nbsp;</th>\n",
              "      <th id=\"T_c8788_level0_col0\" class=\"col_heading level0 col0\" >Accuracy</th>\n",
              "      <th id=\"T_c8788_level0_col1\" class=\"col_heading level0 col1\" >Precision</th>\n",
              "      <th id=\"T_c8788_level0_col2\" class=\"col_heading level0 col2\" >Recall</th>\n",
              "      <th id=\"T_c8788_level0_col3\" class=\"col_heading level0 col3\" >NPV</th>\n",
              "      <th id=\"T_c8788_level0_col4\" class=\"col_heading level0 col4\" >Specificity</th>\n",
              "      <th id=\"T_c8788_level0_col5\" class=\"col_heading level0 col5\" >F1</th>\n",
              "      <th id=\"T_c8788_level0_col6\" class=\"col_heading level0 col6\" >duration</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th class=\"index_name level0\" >model</th>\n",
              "      <th class=\"blank col0\" >&nbsp;</th>\n",
              "      <th class=\"blank col1\" >&nbsp;</th>\n",
              "      <th class=\"blank col2\" >&nbsp;</th>\n",
              "      <th class=\"blank col3\" >&nbsp;</th>\n",
              "      <th class=\"blank col4\" >&nbsp;</th>\n",
              "      <th class=\"blank col5\" >&nbsp;</th>\n",
              "      <th class=\"blank col6\" >&nbsp;</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th id=\"T_c8788_level0_row0\" class=\"row_heading level0 row0\" >XGBClassifier (original)</th>\n",
              "      <td id=\"T_c8788_row0_col0\" class=\"data row0 col0\" >98.96%</td>\n",
              "      <td id=\"T_c8788_row0_col1\" class=\"data row0 col1\" >97.07%</td>\n",
              "      <td id=\"T_c8788_row0_col2\" class=\"data row0 col2\" >83.75%</td>\n",
              "      <td id=\"T_c8788_row0_col3\" class=\"data row0 col3\" >99.05%</td>\n",
              "      <td id=\"T_c8788_row0_col4\" class=\"data row0 col4\" >99.85%</td>\n",
              "      <td id=\"T_c8788_row0_col5\" class=\"data row0 col5\" >89.92%</td>\n",
              "      <td id=\"T_c8788_row0_col6\" class=\"data row0 col6\" >11.58</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c8788_level0_row1\" class=\"row_heading level0 row1\" >RandomForestClassifier (oversampled)</th>\n",
              "      <td id=\"T_c8788_row1_col0\" class=\"data row1 col0\" >98.88%</td>\n",
              "      <td id=\"T_c8788_row1_col1\" class=\"data row1 col1\" >93.33%</td>\n",
              "      <td id=\"T_c8788_row1_col2\" class=\"data row1 col2\" >85.92%</td>\n",
              "      <td id=\"T_c8788_row1_col3\" class=\"data row1 col3\" >99.18%</td>\n",
              "      <td id=\"T_c8788_row1_col4\" class=\"data row1 col4\" >99.64%</td>\n",
              "      <td id=\"T_c8788_row1_col5\" class=\"data row1 col5\" >89.47%</td>\n",
              "      <td id=\"T_c8788_row1_col6\" class=\"data row1 col6\" >21.77</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c8788_level0_row2\" class=\"row_heading level0 row2\" >XGBClassifier (oversampled)</th>\n",
              "      <td id=\"T_c8788_row2_col0\" class=\"data row2 col0\" >98.62%</td>\n",
              "      <td id=\"T_c8788_row2_col1\" class=\"data row2 col1\" >86.36%</td>\n",
              "      <td id=\"T_c8788_row2_col2\" class=\"data row2 col2\" >89.17%</td>\n",
              "      <td id=\"T_c8788_row2_col3\" class=\"data row2 col3\" >99.36%</td>\n",
              "      <td id=\"T_c8788_row2_col4\" class=\"data row2 col4\" >99.17%</td>\n",
              "      <td id=\"T_c8788_row2_col5\" class=\"data row2 col5\" >87.74%</td>\n",
              "      <td id=\"T_c8788_row2_col6\" class=\"data row2 col6\" >25.28</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c8788_level0_row3\" class=\"row_heading level0 row3\" >RandomForestClassifier (original)</th>\n",
              "      <td id=\"T_c8788_row3_col0\" class=\"data row3 col0\" >98.60%</td>\n",
              "      <td id=\"T_c8788_row3_col1\" class=\"data row3 col1\" >98.59%</td>\n",
              "      <td id=\"T_c8788_row3_col2\" class=\"data row3 col2\" >75.81%</td>\n",
              "      <td id=\"T_c8788_row3_col3\" class=\"data row3 col3\" >98.60%</td>\n",
              "      <td id=\"T_c8788_row3_col4\" class=\"data row3 col4\" >99.94%</td>\n",
              "      <td id=\"T_c8788_row3_col5\" class=\"data row3 col5\" >85.71%</td>\n",
              "      <td id=\"T_c8788_row3_col6\" class=\"data row3 col6\" >15.56</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c8788_level0_row4\" class=\"row_heading level0 row4\" >BaggingClassifier (oversampled)</th>\n",
              "      <td id=\"T_c8788_row4_col0\" class=\"data row4 col0\" >98.10%</td>\n",
              "      <td id=\"T_c8788_row4_col1\" class=\"data row4 col1\" >82.73%</td>\n",
              "      <td id=\"T_c8788_row4_col2\" class=\"data row4 col2\" >83.03%</td>\n",
              "      <td id=\"T_c8788_row4_col3\" class=\"data row4 col3\" >99.00%</td>\n",
              "      <td id=\"T_c8788_row4_col4\" class=\"data row4 col4\" >98.98%</td>\n",
              "      <td id=\"T_c8788_row4_col5\" class=\"data row4 col5\" >82.88%</td>\n",
              "      <td id=\"T_c8788_row4_col6\" class=\"data row4 col6\" >15.60</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c8788_level0_row5\" class=\"row_heading level0 row5\" >GradientBoostingClassifier (original)</th>\n",
              "      <td id=\"T_c8788_row5_col0\" class=\"data row5 col0\" >98.28%</td>\n",
              "      <td id=\"T_c8788_row5_col1\" class=\"data row5 col1\" >95.69%</td>\n",
              "      <td id=\"T_c8788_row5_col2\" class=\"data row5 col2\" >72.20%</td>\n",
              "      <td id=\"T_c8788_row5_col3\" class=\"data row5 col3\" >98.39%</td>\n",
              "      <td id=\"T_c8788_row5_col4\" class=\"data row5 col4\" >99.81%</td>\n",
              "      <td id=\"T_c8788_row5_col5\" class=\"data row5 col5\" >82.30%</td>\n",
              "      <td id=\"T_c8788_row5_col6\" class=\"data row5 col6\" >26.89</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c8788_level0_row6\" class=\"row_heading level0 row6\" >BaggingClassifier (original)</th>\n",
              "      <td id=\"T_c8788_row6_col0\" class=\"data row6 col0\" >98.20%</td>\n",
              "      <td id=\"T_c8788_row6_col1\" class=\"data row6 col1\" >95.61%</td>\n",
              "      <td id=\"T_c8788_row6_col2\" class=\"data row6 col2\" >70.76%</td>\n",
              "      <td id=\"T_c8788_row6_col3\" class=\"data row6 col3\" >98.31%</td>\n",
              "      <td id=\"T_c8788_row6_col4\" class=\"data row6 col4\" >99.81%</td>\n",
              "      <td id=\"T_c8788_row6_col5\" class=\"data row6 col5\" >81.33%</td>\n",
              "      <td id=\"T_c8788_row6_col6\" class=\"data row6 col6\" >12.69</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c8788_level0_row7\" class=\"row_heading level0 row7\" >AdaBoostClassifier (original)</th>\n",
              "      <td id=\"T_c8788_row7_col0\" class=\"data row7 col0\" >97.76%</td>\n",
              "      <td id=\"T_c8788_row7_col1\" class=\"data row7 col1\" >90.64%</td>\n",
              "      <td id=\"T_c8788_row7_col2\" class=\"data row7 col2\" >66.43%</td>\n",
              "      <td id=\"T_c8788_row7_col3\" class=\"data row7 col3\" >98.06%</td>\n",
              "      <td id=\"T_c8788_row7_col4\" class=\"data row7 col4\" >99.60%</td>\n",
              "      <td id=\"T_c8788_row7_col5\" class=\"data row7 col5\" >76.67%</td>\n",
              "      <td id=\"T_c8788_row7_col6\" class=\"data row7 col6\" >5.23</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c8788_level0_row8\" class=\"row_heading level0 row8\" >DecisionTreeClassifier (original)</th>\n",
              "      <td id=\"T_c8788_row8_col0\" class=\"data row8 col0\" >96.92%</td>\n",
              "      <td id=\"T_c8788_row8_col1\" class=\"data row8 col1\" >71.73%</td>\n",
              "      <td id=\"T_c8788_row8_col2\" class=\"data row8 col2\" >73.29%</td>\n",
              "      <td id=\"T_c8788_row8_col3\" class=\"data row8 col3\" >98.43%</td>\n",
              "      <td id=\"T_c8788_row8_col4\" class=\"data row8 col4\" >98.31%</td>\n",
              "      <td id=\"T_c8788_row8_col5\" class=\"data row8 col5\" >72.50%</td>\n",
              "      <td id=\"T_c8788_row8_col6\" class=\"data row8 col6\" >2.14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c8788_level0_row9\" class=\"row_heading level0 row9\" >GradientBoostingClassifier (oversampled)</th>\n",
              "      <td id=\"T_c8788_row9_col0\" class=\"data row9 col0\" >96.10%</td>\n",
              "      <td id=\"T_c8788_row9_col1\" class=\"data row9 col1\" >59.90%</td>\n",
              "      <td id=\"T_c8788_row9_col2\" class=\"data row9 col2\" >89.53%</td>\n",
              "      <td id=\"T_c8788_row9_col3\" class=\"data row9 col3\" >99.37%</td>\n",
              "      <td id=\"T_c8788_row9_col4\" class=\"data row9 col4\" >96.49%</td>\n",
              "      <td id=\"T_c8788_row9_col5\" class=\"data row9 col5\" >71.78%</td>\n",
              "      <td id=\"T_c8788_row9_col6\" class=\"data row9 col6\" >52.77</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c8788_level0_row10\" class=\"row_heading level0 row10\" >RandomForestClassifier (undersampled)</th>\n",
              "      <td id=\"T_c8788_row10_col0\" class=\"data row10 col0\" >95.08%</td>\n",
              "      <td id=\"T_c8788_row10_col1\" class=\"data row10 col1\" >53.26%</td>\n",
              "      <td id=\"T_c8788_row10_col2\" class=\"data row10 col2\" >91.34%</td>\n",
              "      <td id=\"T_c8788_row10_col3\" class=\"data row10 col3\" >99.47%</td>\n",
              "      <td id=\"T_c8788_row10_col4\" class=\"data row10 col4\" >95.30%</td>\n",
              "      <td id=\"T_c8788_row10_col5\" class=\"data row10 col5\" >67.29%</td>\n",
              "      <td id=\"T_c8788_row10_col6\" class=\"data row10 col6\" >0.99</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c8788_level0_row11\" class=\"row_heading level0 row11\" >XGBClassifier (undersampled)</th>\n",
              "      <td id=\"T_c8788_row11_col0\" class=\"data row11 col0\" >94.84%</td>\n",
              "      <td id=\"T_c8788_row11_col1\" class=\"data row11 col1\" >51.98%</td>\n",
              "      <td id=\"T_c8788_row11_col2\" class=\"data row11 col2\" >90.25%</td>\n",
              "      <td id=\"T_c8788_row11_col3\" class=\"data row11 col3\" >99.40%</td>\n",
              "      <td id=\"T_c8788_row11_col4\" class=\"data row11 col4\" >95.11%</td>\n",
              "      <td id=\"T_c8788_row11_col5\" class=\"data row11 col5\" >65.96%</td>\n",
              "      <td id=\"T_c8788_row11_col6\" class=\"data row11 col6\" >2.47</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c8788_level0_row12\" class=\"row_heading level0 row12\" >LogisticRegression (original)</th>\n",
              "      <td id=\"T_c8788_row12_col0\" class=\"data row12 col0\" >96.66%</td>\n",
              "      <td id=\"T_c8788_row12_col1\" class=\"data row12 col1\" >88.19%</td>\n",
              "      <td id=\"T_c8788_row12_col2\" class=\"data row12 col2\" >45.85%</td>\n",
              "      <td id=\"T_c8788_row12_col3\" class=\"data row12 col3\" >96.91%</td>\n",
              "      <td id=\"T_c8788_row12_col4\" class=\"data row12 col4\" >99.64%</td>\n",
              "      <td id=\"T_c8788_row12_col5\" class=\"data row12 col5\" >60.33%</td>\n",
              "      <td id=\"T_c8788_row12_col6\" class=\"data row12 col6\" >0.06</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c8788_level0_row13\" class=\"row_heading level0 row13\" >DecisionTreeClassifier (oversampled)</th>\n",
              "      <td id=\"T_c8788_row13_col0\" class=\"data row13 col0\" >94.20%</td>\n",
              "      <td id=\"T_c8788_row13_col1\" class=\"data row13 col1\" >48.51%</td>\n",
              "      <td id=\"T_c8788_row13_col2\" class=\"data row13 col2\" >76.53%</td>\n",
              "      <td id=\"T_c8788_row13_col3\" class=\"data row13 col3\" >98.58%</td>\n",
              "      <td id=\"T_c8788_row13_col4\" class=\"data row13 col4\" >95.24%</td>\n",
              "      <td id=\"T_c8788_row13_col5\" class=\"data row13 col5\" >59.38%</td>\n",
              "      <td id=\"T_c8788_row13_col6\" class=\"data row13 col6\" >2.58</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c8788_level0_row14\" class=\"row_heading level0 row14\" >GradientBoostingClassifier (undersampled)</th>\n",
              "      <td id=\"T_c8788_row14_col0\" class=\"data row14 col0\" >92.72%</td>\n",
              "      <td id=\"T_c8788_row14_col1\" class=\"data row14 col1\" >42.59%</td>\n",
              "      <td id=\"T_c8788_row14_col2\" class=\"data row14 col2\" >90.25%</td>\n",
              "      <td id=\"T_c8788_row14_col3\" class=\"data row14 col3\" >99.39%</td>\n",
              "      <td id=\"T_c8788_row14_col4\" class=\"data row14 col4\" >92.86%</td>\n",
              "      <td id=\"T_c8788_row14_col5\" class=\"data row14 col5\" >57.87%</td>\n",
              "      <td id=\"T_c8788_row14_col6\" class=\"data row14 col6\" >2.55</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c8788_level0_row15\" class=\"row_heading level0 row15\" >BaggingClassifier (undersampled)</th>\n",
              "      <td id=\"T_c8788_row15_col0\" class=\"data row15 col0\" >92.88%</td>\n",
              "      <td id=\"T_c8788_row15_col1\" class=\"data row15 col1\" >42.86%</td>\n",
              "      <td id=\"T_c8788_row15_col2\" class=\"data row15 col2\" >85.56%</td>\n",
              "      <td id=\"T_c8788_row15_col3\" class=\"data row15 col3\" >99.10%</td>\n",
              "      <td id=\"T_c8788_row15_col4\" class=\"data row15 col4\" >93.31%</td>\n",
              "      <td id=\"T_c8788_row15_col5\" class=\"data row15 col5\" >57.11%</td>\n",
              "      <td id=\"T_c8788_row15_col6\" class=\"data row15 col6\" >0.54</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c8788_level0_row16\" class=\"row_heading level0 row16\" >AdaBoostClassifier (oversampled)</th>\n",
              "      <td id=\"T_c8788_row16_col0\" class=\"data row16 col0\" >91.00%</td>\n",
              "      <td id=\"T_c8788_row16_col1\" class=\"data row16 col1\" >36.99%</td>\n",
              "      <td id=\"T_c8788_row16_col2\" class=\"data row16 col2\" >88.81%</td>\n",
              "      <td id=\"T_c8788_row16_col3\" class=\"data row16 col3\" >99.28%</td>\n",
              "      <td id=\"T_c8788_row16_col4\" class=\"data row16 col4\" >91.13%</td>\n",
              "      <td id=\"T_c8788_row16_col5\" class=\"data row16 col5\" >52.23%</td>\n",
              "      <td id=\"T_c8788_row16_col6\" class=\"data row16 col6\" >11.01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c8788_level0_row17\" class=\"row_heading level0 row17\" >AdaBoostClassifier (undersampled)</th>\n",
              "      <td id=\"T_c8788_row17_col0\" class=\"data row17 col0\" >88.92%</td>\n",
              "      <td id=\"T_c8788_row17_col1\" class=\"data row17 col1\" >31.85%</td>\n",
              "      <td id=\"T_c8788_row17_col2\" class=\"data row17 col2\" >87.73%</td>\n",
              "      <td id=\"T_c8788_row17_col3\" class=\"data row17 col3\" >99.20%</td>\n",
              "      <td id=\"T_c8788_row17_col4\" class=\"data row17 col4\" >88.99%</td>\n",
              "      <td id=\"T_c8788_row17_col5\" class=\"data row17 col5\" >46.73%</td>\n",
              "      <td id=\"T_c8788_row17_col6\" class=\"data row17 col6\" >0.64</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c8788_level0_row18\" class=\"row_heading level0 row18\" >LogisticRegression (oversampled)</th>\n",
              "      <td id=\"T_c8788_row18_col0\" class=\"data row18 col0\" >87.88%</td>\n",
              "      <td id=\"T_c8788_row18_col1\" class=\"data row18 col1\" >29.82%</td>\n",
              "      <td id=\"T_c8788_row18_col2\" class=\"data row18 col2\" >87.73%</td>\n",
              "      <td id=\"T_c8788_row18_col3\" class=\"data row18 col3\" >99.19%</td>\n",
              "      <td id=\"T_c8788_row18_col4\" class=\"data row18 col4\" >87.89%</td>\n",
              "      <td id=\"T_c8788_row18_col5\" class=\"data row18 col5\" >44.51%</td>\n",
              "      <td id=\"T_c8788_row18_col6\" class=\"data row18 col6\" >0.19</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c8788_level0_row19\" class=\"row_heading level0 row19\" >LogisticRegression (undersampled)</th>\n",
              "      <td id=\"T_c8788_row19_col0\" class=\"data row19 col0\" >86.44%</td>\n",
              "      <td id=\"T_c8788_row19_col1\" class=\"data row19 col1\" >27.45%</td>\n",
              "      <td id=\"T_c8788_row19_col2\" class=\"data row19 col2\" >88.09%</td>\n",
              "      <td id=\"T_c8788_row19_col3\" class=\"data row19 col3\" >99.20%</td>\n",
              "      <td id=\"T_c8788_row19_col4\" class=\"data row19 col4\" >86.34%</td>\n",
              "      <td id=\"T_c8788_row19_col5\" class=\"data row19 col5\" >41.85%</td>\n",
              "      <td id=\"T_c8788_row19_col6\" class=\"data row19 col6\" >0.03</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c8788_level0_row20\" class=\"row_heading level0 row20\" >DecisionTreeClassifier (undersampled)</th>\n",
              "      <td id=\"T_c8788_row20_col0\" class=\"data row20 col0\" >83.78%</td>\n",
              "      <td id=\"T_c8788_row20_col1\" class=\"data row20 col1\" >23.41%</td>\n",
              "      <td id=\"T_c8788_row20_col2\" class=\"data row20 col2\" >84.84%</td>\n",
              "      <td id=\"T_c8788_row20_col3\" class=\"data row20 col3\" >98.95%</td>\n",
              "      <td id=\"T_c8788_row20_col4\" class=\"data row20 col4\" >83.72%</td>\n",
              "      <td id=\"T_c8788_row20_col5\" class=\"data row20 col5\" >36.69%</td>\n",
              "      <td id=\"T_c8788_row20_col6\" class=\"data row20 col6\" >0.09</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n"
            ]
          },
          "metadata": {},
          "execution_count": 60
        }
      ],
      "source": [
        "print(f\"\\n{'-'*122}\\n   Performance metrics of models trained on original, oversampled, and undersampled subsets of the validation dataset (F1)\\n{'-'*122}\\n\")\n",
        "\n",
        "results[results['index']=='Validation'].set_index('model').drop(['index', 'cv_recall'], axis=1)\\\n",
        "  .sort_values(by=['F1', 'duration'], ascending=[False, True]).style\\\n",
        "  .set_table_styles([dict(selector=\"th\", props=[('min-width', '75px'), \n",
        "                                                ('text-align', 'right')])])\\\n",
        "  .highlight_max(color='lightgreen', axis=0, subset=col_perc)\\\n",
        "  .highlight_min(color='lightgreen', axis=0, subset=['duration'])\\\n",
        "  .format('{:.2f}')\\\n",
        "  .format('{:.2%}', subset=col_perc)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "nIzPVm3HctR0"
      },
      "source": [
        "**Observations:**\n",
        "\n",
        "1. **XGBClassifier** and **RandomForestClassifier** consistently perform well across different datasets, particularly when using undersampled and oversampled data. These two models achieve high recall scores, which is a key performance metric for our task, as **minimizing false negatives** is a priority.\n",
        "\n",
        "2. **GradientBoostingClassifier** also shows strong performance, especially when using undersampled and oversampled data. However, it takes considerably longer to train compared to **XGBClassifier** and **RandomForestClassifier**.\n",
        "\n",
        "3. **LogisticRegression** and **AdaBoostClassifier** achieve moderate recall scores when trained on undersampled and oversampled data, but their performance is lower when using the original dataset.\n",
        "\n",
        "4. The decision tree-based models, **DecisionTreeClassifier** and **BaggingClassifier**, demonstrate varied performance across the different datasets. They have lower recall scores when trained on the original data compared to the undersampled and oversampled datasets.\n",
        "\n",
        "In terms of duration, **LogisticRegression** is the fastest model to train, while **GradientBoostingClassifier** generally takes the longest.\n",
        "\n",
        "Overall, **XGBClassifier** and **RandomForestClassifier** are the top-performing models in terms of recall scores, particularly when trained on undersampled and oversampled data. These models could be the best choice as our main goal is to maximize recall. Additionally, fine-tuning and optimizing the models could lead to even better performance."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "yZGY1eL84jau"
      },
      "source": [
        "## Hyperparameter Tuning "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "czq7BZ5b4jau"
      },
      "source": [
        "**Hyperparameter tuning can take a long time to run, so to avoid that time complexity - you can use the following grids, wherever required.**\n",
        "\n",
        "- For Gradient Boosting:\n",
        "```\n",
        "  param_grid = {\n",
        "      'n_estimators': np.arange(100, 150, 25),\n",
        "      'learning_rate': [0.2, 0.05, 1],\n",
        "      'subsample': [0.5, 0.7], \n",
        "      'max_features': [0.5, 0.7]\n",
        "  }\n",
        "\n",
        "- For Adaboost:\n",
        "```\n",
        "  param_grid = {\n",
        "      'n_estimators': [100, 150, 200],\n",
        "      'learning_rate': [0.2, 0.05],\n",
        "      'base_estimator': [DecisionTreeClassifier(max_depth=1, random_state=42),\n",
        "                         DecisionTreeClassifier(max_depth=2, random_state=42)\n",
        "                         DecisionTreeClassifier(max_depth=3, random_state=42)]\n",
        "  }\n",
        "\n",
        "- For Bagging Classifier:\n",
        "```\n",
        "  param_grid = {\n",
        "      'max_samples': [0.8, 0.9, 1], \n",
        "      'max_features': [0.7, 0.8, 0.9],\n",
        "      'n_estimators' : [30, 50, 70],\n",
        "  }\n",
        "\n",
        "- For Random Forest:\n",
        "```\n",
        "  param_grid = {\n",
        "      'n_estimators': [200, 250, 300],\n",
        "      'min_samples_leaf': np.arange(1, 4),\n",
        "      'max_features': [np.arange(0.3, 0.6, 0.1), 'sqrt'],\n",
        "      'max_samples': np.arange(0.4, 0.7, 0.1)\n",
        "  }\n",
        "\n",
        "- For Decision Trees:\n",
        "```\n",
        "  param_grid = {\n",
        "      'max_depth': np.arange(2, 6), \n",
        "      'min_samples_leaf': [1, 4, 7],\n",
        "      'max_leaf_nodes' : [10, 15],\n",
        "      'min_impurity_decrease': [0.0001, 0.001]\n",
        "  }\n",
        "\n",
        "- For Logistic Regression:\n",
        "```\n",
        "  param_grid = {\n",
        "    'C': np.arange(0.1, 1.1, 0.1)\n",
        "  }\n",
        "\n",
        "- For XGBoost:\n",
        "```\n",
        "  param_grid = {\n",
        "    'n_estimators': [150, 200, 250],\n",
        "    'scale_pos_weight': [5, 10],\n",
        "    'learning_rate': [0.1, 0.2],\n",
        "    'gamma': [0, 3,5],\n",
        "    'subsample': [0.8, 0.9]\n",
        "  }\n",
        "```"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "wy_XMXSVuFEM"
      },
      "source": [
        ">We need to identify at least three top-performing models from all previously constructed models.\n",
        "\n",
        "- We have chosen the following classifiers based on their performance in terms of Recall and F1 scores, as observed during previous stages of model building with default hyperparameters:\n",
        "  - RandomForestClassifier\n",
        "  - GradientBoostingClassifier\n",
        "  - XGBClassifier\n",
        "\n",
        "- These classifiers have demonstrated a strong ability to accurately identify positive instances while also maintaining a balanced trade-off between precision and recall.\n",
        "\n",
        "- These classifiers will be fitted on each of the three datasets: original, oversampled, and undersampled."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 61,
      "metadata": {
        "id": "2l0B7th6rdzM"
      },
      "outputs": [],
      "source": [
        "clfs = ['RandomForestClassifier', 'GradientBoostingClassifier', 'XGBClassifier']\n",
        "\n",
        "models_tuned_grid = list(filter(lambda clf: clf[0] in clfs, models_grid))"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "GMReRXdH_YUd"
      },
      "source": [
        "### Tuning RF, GBM, and XGB models using the original dataset"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 62,
      "metadata": {
        "id": "EO4uhS5jTu0y",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "c4b40a1e-a248-4b1e-d9d3-a4564fbcd50d"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "\u001b[2;37;42mRandomForestClassifier:                                                                               \u001b[0m\n",
            "\tBest parameters are:\n",
            "\t\tn_estimators: 250\n",
            "\t\tmin_samples_leaf: 2\n",
            "\t\tmax_samples: 0.6\n",
            "\t\tmax_features: sqrt\n",
            "\tCV score=0.68666\n",
            "\tIteration duration: 351.70 seconds\n",
            "-----------------------------------------------------------------------------------------------------\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 900x300 with 4 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[1mModel performance:\u001b[0m\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7fe22e86ded0>"
            ],
            "text/html": [
              "<style type=\"text/css\">\n",
              "#T_cd5b3 th {\n",
              "  max-width: 75px;\n",
              "}\n",
              "</style>\n",
              "<table id=\"T_cd5b3\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th class=\"blank level0\" >&nbsp;</th>\n",
              "      <th id=\"T_cd5b3_level0_col0\" class=\"col_heading level0 col0\" >Accuracy</th>\n",
              "      <th id=\"T_cd5b3_level0_col1\" class=\"col_heading level0 col1\" >Precision</th>\n",
              "      <th id=\"T_cd5b3_level0_col2\" class=\"col_heading level0 col2\" >Recall</th>\n",
              "      <th id=\"T_cd5b3_level0_col3\" class=\"col_heading level0 col3\" >NPV</th>\n",
              "      <th id=\"T_cd5b3_level0_col4\" class=\"col_heading level0 col4\" >Specificity</th>\n",
              "      <th id=\"T_cd5b3_level0_col5\" class=\"col_heading level0 col5\" >F1</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th id=\"T_cd5b3_level0_row0\" class=\"row_heading level0 row0\" >Training</th>\n",
              "      <td id=\"T_cd5b3_row0_col0\" class=\"data row0 col0\" >99.11%</td>\n",
              "      <td id=\"T_cd5b3_row0_col1\" class=\"data row0 col1\" >99.72%</td>\n",
              "      <td id=\"T_cd5b3_row0_col2\" class=\"data row0 col2\" >84.27%</td>\n",
              "      <td id=\"T_cd5b3_row0_col3\" class=\"data row0 col3\" >99.08%</td>\n",
              "      <td id=\"T_cd5b3_row0_col4\" class=\"data row0 col4\" >99.99%</td>\n",
              "      <td id=\"T_cd5b3_row0_col5\" class=\"data row0 col5\" >91.35%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_cd5b3_level0_row1\" class=\"row_heading level0 row1\" >Validation</th>\n",
              "      <td id=\"T_cd5b3_row1_col0\" class=\"data row1 col0\" >98.44%</td>\n",
              "      <td id=\"T_cd5b3_row1_col1\" class=\"data row1 col1\" >98.54%</td>\n",
              "      <td id=\"T_cd5b3_row1_col2\" class=\"data row1 col2\" >72.92%</td>\n",
              "      <td id=\"T_cd5b3_row1_col3\" class=\"data row1 col3\" >98.44%</td>\n",
              "      <td id=\"T_cd5b3_row1_col4\" class=\"data row1 col4\" >99.94%</td>\n",
              "      <td id=\"T_cd5b3_row1_col5\" class=\"data row1 col5\" >83.82%</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "\u001b[2;37;42mGradientBoostingClassifier:                                                                           \u001b[0m\n",
            "\tBest parameters are:\n",
            "\t\tsubsample: 0.7\n",
            "\t\tn_estimators: 100\n",
            "\t\tmax_features: 0.7\n",
            "\t\tlearning_rate: 0.2\n",
            "\tCV score=0.73590\n",
            "\tIteration duration: 313.59 seconds\n",
            "-----------------------------------------------------------------------------------------------------\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 900x300 with 4 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[1mModel performance:\u001b[0m\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7fe22f39b610>"
            ],
            "text/html": [
              "<style type=\"text/css\">\n",
              "#T_82675 th {\n",
              "  max-width: 75px;\n",
              "}\n",
              "</style>\n",
              "<table id=\"T_82675\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th class=\"blank level0\" >&nbsp;</th>\n",
              "      <th id=\"T_82675_level0_col0\" class=\"col_heading level0 col0\" >Accuracy</th>\n",
              "      <th id=\"T_82675_level0_col1\" class=\"col_heading level0 col1\" >Precision</th>\n",
              "      <th id=\"T_82675_level0_col2\" class=\"col_heading level0 col2\" >Recall</th>\n",
              "      <th id=\"T_82675_level0_col3\" class=\"col_heading level0 col3\" >NPV</th>\n",
              "      <th id=\"T_82675_level0_col4\" class=\"col_heading level0 col4\" >Specificity</th>\n",
              "      <th id=\"T_82675_level0_col5\" class=\"col_heading level0 col5\" >F1</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th id=\"T_82675_level0_row0\" class=\"row_heading level0 row0\" >Training</th>\n",
              "      <td id=\"T_82675_row0_col0\" class=\"data row0 col0\" >99.24%</td>\n",
              "      <td id=\"T_82675_row0_col1\" class=\"data row0 col1\" >98.26%</td>\n",
              "      <td id=\"T_82675_row0_col2\" class=\"data row0 col2\" >87.88%</td>\n",
              "      <td id=\"T_82675_row0_col3\" class=\"data row0 col3\" >99.29%</td>\n",
              "      <td id=\"T_82675_row0_col4\" class=\"data row0 col4\" >99.91%</td>\n",
              "      <td id=\"T_82675_row0_col5\" class=\"data row0 col5\" >92.78%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_82675_level0_row1\" class=\"row_heading level0 row1\" >Validation</th>\n",
              "      <td id=\"T_82675_row1_col0\" class=\"data row1 col0\" >98.30%</td>\n",
              "      <td id=\"T_82675_row1_col1\" class=\"data row1 col1\" >90.34%</td>\n",
              "      <td id=\"T_82675_row1_col2\" class=\"data row1 col2\" >77.62%</td>\n",
              "      <td id=\"T_82675_row1_col3\" class=\"data row1 col3\" >98.70%</td>\n",
              "      <td id=\"T_82675_row1_col4\" class=\"data row1 col4\" >99.51%</td>\n",
              "      <td id=\"T_82675_row1_col5\" class=\"data row1 col5\" >83.50%</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "\u001b[2;37;42mXGBClassifier:                                                                                        \u001b[0m\n",
            "\tBest parameters are:\n",
            "\t\tsubsample: 0.8\n",
            "\t\tscale_pos_weight: 10\n",
            "\t\tn_estimators: 250\n",
            "\t\tlearning_rate: 0.1\n",
            "\t\tgamma: 3\n",
            "\tCV score=0.84514\n",
            "\tIteration duration: 866.33 seconds\n",
            "-----------------------------------------------------------------------------------------------------\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 900x300 with 4 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[1mModel performance:\u001b[0m\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7fe22ef6be80>"
            ],
            "text/html": [
              "<style type=\"text/css\">\n",
              "#T_75266 th {\n",
              "  max-width: 75px;\n",
              "}\n",
              "</style>\n",
              "<table id=\"T_75266\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th class=\"blank level0\" >&nbsp;</th>\n",
              "      <th id=\"T_75266_level0_col0\" class=\"col_heading level0 col0\" >Accuracy</th>\n",
              "      <th id=\"T_75266_level0_col1\" class=\"col_heading level0 col1\" >Precision</th>\n",
              "      <th id=\"T_75266_level0_col2\" class=\"col_heading level0 col2\" >Recall</th>\n",
              "      <th id=\"T_75266_level0_col3\" class=\"col_heading level0 col3\" >NPV</th>\n",
              "      <th id=\"T_75266_level0_col4\" class=\"col_heading level0 col4\" >Specificity</th>\n",
              "      <th id=\"T_75266_level0_col5\" class=\"col_heading level0 col5\" >F1</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th id=\"T_75266_level0_row0\" class=\"row_heading level0 row0\" >Training</th>\n",
              "      <td id=\"T_75266_row0_col0\" class=\"data row0 col0\" >99.96%</td>\n",
              "      <td id=\"T_75266_row0_col1\" class=\"data row0 col1\" >99.28%</td>\n",
              "      <td id=\"T_75266_row0_col2\" class=\"data row0 col2\" >100.00%</td>\n",
              "      <td id=\"T_75266_row0_col3\" class=\"data row0 col3\" >100.00%</td>\n",
              "      <td id=\"T_75266_row0_col4\" class=\"data row0 col4\" >99.96%</td>\n",
              "      <td id=\"T_75266_row0_col5\" class=\"data row0 col5\" >99.64%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_75266_level0_row1\" class=\"row_heading level0 row1\" >Validation</th>\n",
              "      <td id=\"T_75266_row1_col0\" class=\"data row1 col0\" >98.98%</td>\n",
              "      <td id=\"T_75266_row1_col1\" class=\"data row1 col1\" >92.80%</td>\n",
              "      <td id=\"T_75266_row1_col2\" class=\"data row1 col2\" >88.45%</td>\n",
              "      <td id=\"T_75266_row1_col3\" class=\"data row1 col3\" >99.32%</td>\n",
              "      <td id=\"T_75266_row1_col4\" class=\"data row1 col4\" >99.60%</td>\n",
              "      <td id=\"T_75266_row1_col5\" class=\"data row1 col5\" >90.57%</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n"
            ]
          },
          "metadata": {}
        }
      ],
      "source": [
        "res_tuned_orig = cv_tuned(models_tuned_grid, X_train, y_train, X_valid, y_valid, 'original')"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "chN8hbfThKyr"
      },
      "source": [
        "### Tuning RF, GBM, and XGB models using the oversampled dataset"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 63,
      "metadata": {
        "id": "tVZcJ0hv4jau",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "38a16742-d0c1-4faa-ad47-e682cf3cfeb1"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "\u001b[2;37;42mRandomForestClassifier:                                                                               \u001b[0m\n",
            "\tBest parameters are:\n",
            "\t\tn_estimators: 200\n",
            "\t\tmin_samples_leaf: 2\n",
            "\t\tmax_samples: 0.6\n",
            "\t\tmax_features: sqrt\n",
            "\tCV score=0.97508\n",
            "\tIteration duration: 518.66 seconds\n",
            "-----------------------------------------------------------------------------------------------------\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 900x300 with 4 Axes>"
            ],
            "image/png": 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evJmXL1/y5Zdf0q1bNyZOnKgV88033zBgwAB69+5N+fLlOXr0KKNGjdKKadmyJY0aNaJevXrkyZMn2WVKs2XLxu7du4mMjKRKlSq0atWKBg0aMHfuXN1+jP/47rvvGDVqFEOHDqVSpUrcunWLXr16acX89ttvPHnyhIoVK/L999/Tt29f7O3ttWKmTZtGQEAA+fPnp0KFCsCHryO2trZs2rSJ+vXrU7JkSRYuXMgff/xB6dKlARg/fjyjRo3C19eXkiVL0qhRI7Zv3665Hnz22WeMHTuW4cOH4+DgQO/evVP1WwgBoFIyYtK1EOkgMTGRkiVL0qZNG8aPH5/ZzRFCCCGEyDJkOpDIMm7dusWePXuoU6cOsbGxzJ07lxs3btC+ffvMbpoQQgghRJYi04FElmFkZISfnx9VqlShRo0anD9/nr/++kszx14IIYQQQqSMTAcSQgghhBDCwMhIgBBCCCGEEAZGOgFCCCGEEEIYGOkECCFEOjt06BBNmzbFyckJlUrFli1b3hnbs2dPVCoVM2fO1CqPjIykQ4cOWFtbY2tri6enp+ZNo2+cO3eOWrVqYWFhQf78+Zk8eXKS+tevX0+JEiWwsLCgbNmy7NixIy1OUQghRBYjnQAhhEhnMTExlCtXjnnz5r03bvPmzRw7dkxrffc3OnTowMWLFwkICMDf359Dhw7Ro0cPzf6oqCgaNmxIwYIFCQoKYsqUKYwZM4ZFixZpYo4ePUq7du3w9PTkzJkzNG/enObNm3PhwoW0O1khhBBZgl4+GBz36HpmN0FkEkunWpndBJFJ4l/fTdX3dckbprkLfTjoHVQqFZs3b07yoqa7d+9StWpVdu/ejbu7O/3796d///4AhISEUKpUKU6ePEnlypUB2LVrF02aNOHOnTs4OTmxYMECRo4cSXh4OGZmZgAMHz6cLVu2EBoaCqhflhQTE4O/v7/muNWqVaN8+fIsXLjwo88ps0nON1yS8w1TRuZ7SF3O/5TJSIAQQgAkJqR4i42NJSoqSmuLjY39+EMnJvL9998zZMgQzRtE3xYYGIitra2mAwDg6uqKkZERx48f18TUrl1b0wEAcHNzIywsjCdPnmhiXF1dtep2c3MjMDDwo9suhBBZjg75nsSEzG5tupFOgBBCACTEp3jz9fXFxsZGa/P19f3oQ//yyy+YmJjQt2/fZPeHh4djb2+vVWZiYoKdnR3h4eGaGAcHB62YN58/FPNmvxBCGAQd8j0J8Znd2nQjbwwWQghAURJTHDtixAgGDhyoVWZubv5Rxw0KCmLWrFmcPn0alUr1UXUIIYRIOV3yvT6TToAQQgAkpvyiYG5u/tF/9P/X4cOHefDgAQUKFNCUJSQkMGjQIGbOnMnNmzdxdHTkwYMHWt+Lj48nMjISR0dHABwdHYmIiNCKefP5QzFv9gshhEHQId/rM5kOJIQQAEpiyrc09P3333Pu3DmCg4M1m5OTE0OGDGH37t0AuLi48PTpU4KCgjTf27dvH4mJiVStWlUTc+jQIeLi4jQxAQEBFC9enJw5c2pi9u7dq3X8gIAAXFxc0vSchBDik6ZLvtfjUQMZCRBCCEjXh7+io6O5evWq5vONGzcIDg7Gzs6OAgUKkCtXLq14U1NTHB0dKV68OAAlS5akUaNGdO/enYULFxIXF0fv3r1p27atZjnR9u3bM3bsWDw9PRk2bBgXLlxg1qxZzJgxQ1Nvv379qFOnDtOmTcPd3Z01a9Zw6tQprWVEhRBC7+nxw766kJEAIYSAdL0rdOrUKSpUqECFChUAGDhwIBUqVMDHxyfFdaxatYoSJUrQoEEDmjRpQs2aNbX+eLexsWHPnj3cuHGDSpUqMWjQIHx8fLTeJVC9enVWr17NokWLKFeuHBs2bGDLli2UKVNG53MSQogsS0YCAHlPgNAzsma04UrtutGvr59IcaxZoS9TdSyRtiTnGy7J+YYpI/M96G/Ol+lAQgiBrBYhhBCGQvK9mnQChBACZLUIIYQwFJLvAekECCGEWkLch2OEEEJkfZLvAekECCGEmgwPCyGEYZB8D0gnQAgh1GR4WAghDIPke0A6AUIIoSZ3hoQQwjBIvgekEyCEEGpyZ0gIIQyD5HtAOgFCCAGAosgbJIUQwhBIvleTToAQQoAMDwshhKGQfA9IJ0AIIdRkeFgIIQyD5HtAOgFCCKEmd4aEEMIwSL4HpBMghBBq8vIYIYQwDJLvAekECCGEmgwPCyGEYZB8D0gnQAgh1GR4WAghDIPke0A6AUIIoSZ3hoQQwjBIvgekEyCEEGpyURBCCMMg+R6QToAQQgDy8hghhDAUku/VpBMghBAgd4aEEMJQSL4HpBMghBBq8qCYEEIYBsn3gHQChBBCTe4MCSGEYZB8D0gnQAgh1BLiM7sFQgghMoLkewCMMrsBQgjxSVASU74JIYTIunTJ96nI+ZMmTUKlUtG/f39N2atXr/Dy8iJXrlxYWVnRsmVLIiIitL53+/Zt3N3dyZYtG/b29gwZMoT4eO2Oy4EDB6hYsSLm5uYUKVIEPz8/ndsnnQAhhAD18HBKNx0dOnSIpk2b4uTkhEqlYsuWLZp9cXFxDBs2jLJly5I9e3acnJzo1KkT9+7d06ojMjKSDh06YG1tja2tLZ6enkRHR2vFnDt3jlq1amFhYUH+/PmZPHlykrasX7+eEiVKYGFhQdmyZdmxY4fO5yOEEFmaLvn+I6cOnTx5kl9//ZUvvvhCq3zAgAFs27aN9evXc/DgQe7du0eLFi00+xMSEnB3d+f169ccPXqU5cuX4+fnh4+Pjybmxo0buLu7U69ePYKDg+nfvz/dunVj9+7dOrVROgFCCAHpekGIiYmhXLlyzJs3L8m+Fy9ecPr0aUaNGsXp06fZtGkTYWFhfPPNN1pxHTp04OLFiwQEBODv78+hQ4fo0aOHZn9UVBQNGzakYMGCBAUFMWXKFMaMGcOiRYs0MUePHqVdu3Z4enpy5swZmjdvTvPmzblw4YLO5ySEEFlWOncCoqOj6dChA4sXLyZnzpya8mfPnvHbb78xffp06tevT6VKlVi2bBlHjx7l2LFjAOzZs4dLly7x+++/U758eRo3bsz48eOZN28er1+/BmDhwoU4Ozszbdo0SpYsSe/evWnVqhUzZszQqZ3SCRBCCEjXoeHGjRszYcIEvv322yT7bGxsCAgIoE2bNhQvXpxq1aoxd+5cgoKCuH37NgAhISHs2rWLJUuWULVqVWrWrMmcOXNYs2aNZsRg1apVvH79mqVLl1K6dGnatm1L3759mT59uuZYs2bNolGjRgwZMoSSJUsyfvx4KlasyNy5cz/yRxNCiCxIx+lAsbGxREVFaW2xsbHvrN7Lywt3d3dcXV21yoOCgoiLi9MqL1GiBAUKFCAwMBCAwMBAypYti4ODgybGzc2NqKgoLl68qIn5b91ubm6aOlJKOgFCCAE63RXS9YKgq2fPnqFSqbC1tQXUCd/W1pbKlStrYlxdXTEyMuL48eOamNq1a2NmZqaJcXNzIywsjCdPnmhi0uLCIYQQWZqOIwG+vr7Y2Nhobb6+vslWvWbNGk6fPp3s/vDwcMzMzDS5/Q0HBwfCw8M1MW93AN7sf7PvfTFRUVG8fPkyxT+DdAKEEAJ0uiukywVBV69evWLYsGG0a9cOa2trQJ3w7e3tteJMTEyws7NLkwvHm/1CCGEQdBwJGDFiBM+ePdPaRowYkaTaf/75h379+rFq1SosLCwy4cR0I0uECiEE6DTvc8SIEQwcOFCrzNzcPNVNiIuLo02bNiiKwoIFC1JdnxBCiGToOM/f3Nw8RTk+KCiIBw8eULFiRU1ZQkIChw4dYu7cuezevZvXr1/z9OlTrdGAiIgIHB0dAXB0dOTEiRNa9b5ZPejtmP+uKBQREYG1tTWWlpYpPi8ZCRBCCNDprpC5uTnW1tZaW2o7AW86ALdu3SIgIEAzCgDqhP/gwQOt+Pj4eCIjIz94UXiz730xb/YLIYRBSKclQhs0aMD58+cJDg7WbJUrV6ZDhw6a/25qasrevXs13wkLC+P27du4uLgA4OLiwvnz57Vy/ptrQqlSpTQxb9fxJuZNHSklnQAhhIB0Xy7ufd50AK5cucJff/1Frly5tPa7uLjw9OlTgoKCNGX79u0jMTGRqlWramIOHTpEXFycJiYgIIDixYtrVqdIqwuHEEJkaem0OlCOHDkoU6aM1pY9e3Zy5cpFmTJlsLGxwdPTk4EDB7J//36CgoLo0qULLi4uVKtWDYCGDRtSqlQpvv/+e86ePcvu3bvx9vbGy8tLc7OpZ8+eXL9+naFDhxIaGsr8+fNZt24dAwYM0OlnkOlAQggBkJCQblVHR0dz9epVzecbN24QHByMnZ0defPmpVWrVpw+fRp/f38SEhI0c/Tt7OwwMzOjZMmSNGrUiO7du7Nw4ULi4uLo3bs3bdu2xcnJCYD27dszduxYPD09GTZsGBcuXGDWrFlaS8b169ePOnXqMG3aNNzd3VmzZg2nTp3SWkZUCCH0Xjrm+w+ZMWMGRkZGtGzZktjYWNzc3Jg/f75mv7GxMf7+/vTq1QsXFxeyZ8+Oh4cH48aN08Q4Ozuzfft2BgwYwKxZs8iXLx9LlizBzc1Np7aoFEVR0uzMPhFxj65ndhNEJrF0qpXZTRCZJP713VR9/+Ufo1Mca9lurE51HzhwgHr16iUp9/DwYMyYMTg7Oyf7vf3791O3bl1A/bKw3r17s23bNs0FZPbs2VhZWWniz507h5eXFydPniR37tz06dOHYcOGadW5fv16vL29uXnzJkWLFmXy5Mk0adJEp/P51EjON1yS8w1TRuZ70D3nZxXSCRB6RS4IhivVF4VVo1Ica9lhfKqOJdKW5HzDJTnfMGVkvgf9zfkyHUgIIeCjXgImhBAiC5J8D0gnQAgh1NLhgV8hhBCfIMn3gKwOlGlOBZ/Ha+ho6n3TgTI1GrP30NF3xo6dPIcyNRqzcu3mVNc5csI0ytRorLX9MNBbK+ZS2FW69fsJF7dW1GjchjG/zOLFi5S/gU5kHCMjI8aOGcKVsECeP7tKWMgRRv7UP7OblTUpSso3IdLQkpXrKFOjMZNmLnxnTOfeQ5Pk7jI1GtNrsI8mRlEU5i5eQd1v2lOpXjO69RvBrX+0p038uvwPOvwwkMr1m+Pi1irdzkmk3rChvQk8up0nj8O4d+csGzf8RrFihTX7c+a0ZeaM8Vy8cIjnz65y/eoJZkwfh7V1jkxsdRahS77X45wvIwGZ5OXLVxQvUohv3RvS/6cJ74z76+ARzl0MxT53rnfG6FpnzWqVmfDTv8tImZqaav77g4eP6dZvBI0a1GbkwB+JfhHDL7MWMXLiNGZM9E6uOpGJhg7x4ocenejq2Z+Ll8KoVKkcvy2ezrNnUcydtzSzm5e1yJ0hkQnOh4Sx/s8dFCuS/MPhb8z6eZTW8q9Pnz2nZecfcav375z4pavWs2rDViZ6D+KzvI7MXbyCHwZ68+fvv2JubgZAXFw8bvVqUb5MSTb5706fkxJponataixYsJxTQcGYmJgwYdxwdm5fTdlydXnx4iVOTg44OTkwbNh4LoVcpmCBfMybNwknJ0e+a9sjs5v/aZN8D0gnINPUcqlCLZcq742JePgI3xkL+HX6RH4c4vPe2JTWCWBmakruXHbJ7jt49DgmJiZ4D/LCyEg9UOQzpDctOv3I7Tv3KJDP6YP1i4zjUq0yW7ftZsdO9drvt27doe13zahSpXzmNiwrkouCyGAvXrxk+NgpjBnWj1+X//HeWJv/3N3d+ddBLMzNaVhf3QlQFIWV67bQw6Mt9Wup3/vw86jB1Gnajr2Hj9LEtS4Avbt9D8CW7QFpfDYirbk37aj1uWu3/oTfO0+lil9w+O/jXLwYRpvv/v1j//r1W4zy+YUVfrMxNjYmIROXwfzkSb4HZDrQJysxMZER46bSuX0rihQqmKZ1nzxzjtrubfm6bTfGTZnD02dRmn2vX8dhamqi6QAAWPz/5RSnz15M03aI1As8dor69WpStGghAL74ohQ1qn/Jrt37M7llWVA6vD1SiPeZMG0etV2q4FKlgs7f3eS/h8audchmaQHAnXvhPHr8BJfK/9aVwyo7X5QqztkLoWnWZpF5bGzUbxGPfPL03THWOYiKipYOwIek0xuDsxoZCfhE/fb7eoyNjejYulma1lujWiVc69TgMycH/rl7n1m/+tFz0ChW/TodY2NjqlYqz5Q5i1m6agPft2nGi5evmLFAPa3k4ePING2LSL1fJs/F2tqKi+cPkpCQgLGxMaN8fuGPP97//IhISomXi6bIODv+OkDI5WusWTJL5++evxTGles3GTeiv6bsUeQTAHLZ5dSKzWWXk0ePn6SqrSLzqVQqpk8dy5EjJ7h4MSzZmFy5cjLyp/4s+W1VBrcu65F8ryadgE/QxdAr/L7+T9YvnYNKpUrTut8MCQMUK+xMscLONG7TlZNnzlGtcgWKFCrIRO9BTJ6zmFm/LsPIyIgOrZqRyy4nRkZp2xaReq1bN6Vd2xZ07OTFpUuXKVeuNNOnjuXe/QhWrlyf2c3LWvT4bo/4tNyPeMikmb+yeObPmrn6utjkv5uihT+nbKni6dA68SmaM/tnSpcuTp163ya7P0cOK7b9uYKQkMuMHTctg1uXBUm+B6QT8Ek6ffYCkU+e8lXLTpqyhIREpsxdwsp1W9izcXmaHSv/Z3nJaWvN7Tv3qfb/YWT3hvVwb1iPR5FPyGZhASoVK9ZuJp9T3jQ7rkgbv/iOYvKUuaxbtxWACxdCKVggH8OG9pZOgK4S9XcFCPFpuRR2hcgnT2nTtbemLCEhkaDgC/yxaRun92/F2Ng42e++ePmKnX8dxOv/c/vfyP3/EYDHkU/Ik/vfZ74eRz6heNHCiKxr1swJuDdxpV6DFty9ez/Jfiur7OzwX8Xz5zG0bN2N+Pj4TGhlFiP5HpBOwCepaaMGVPvPHNEfBnjTtFF9mjdpmKbHCn/wkKfPnpMnmQeF31xUNvnvxtzM9KPmrYr0lS2bJYn/SWYJCQlaz3SIFJIHxUQGqVapPJtXLtAq8544HeeC+fHs2PqdHQCAPfsO8zoujqZu9bXK8zk5kjtXTo4FBVPi/8tIRsfEcO5SGG2+dU/7kxAZYtbMCTRv1ogGX7Xm5s1/kuzPkcOKndtXExsbS/MWnYmNjc2EVmZBku8B6QRkmhcvXnL7zj3N57v3Igi9fA0b6xzkdbTH9v8PAL1hYmJMbrucOBfM99F1vnjxkvlLV/FV3RrkzmXHP3fvMX3+Ugrkc6JG1Yqa763esJXyZUuRzdKCwJNnmDbvN/r36oJ1Dqs0/AVEWvDfHsCI4X3555+7XLwURvnyZejfrwd+y9dkdtOyHrkoiAySPXs2ihb6XKvM0tICW+scScr/a5P/burXcklyjVCpVHzfpjmLlq+hYL7P+MzJgbmLV2KfOxcNalXXxN0Pf8CzqOfcj3hAQkIioZevAVAgnxPZslmmyfmJtDFn9s+0a9ucFi278vx5NA4OeQB49uw5r169IkcOK3bt+APLbBZ06twHa+scmncEPHz4mETJae8mvw0gnYBMcyH0Cl37DNN8njxnEQDNGrsy0XtQiuro3Hsonzk6aOI/VKeRsRGXr91g686/iIqOwT63HdW/rEjv7p0wM/t3Xur5kMvM++13Xrx8iXPB/PgM7cM3jRqk+pxF2uvX35uxY4YyZ/bP2Nvn4t69CBYv+Z3xE2ZkdtOyHj1+IYzIekZOmMbd8Aj85k7WlN24dYfT5y6yaMbEZL/TtUNrXr58xZjJs3keHU3FL0qzcNp4recO5i5ZyZ87/9J8btVFPSVp6Zxf+LLiF+l0NuJj9OrpAcC+vRu1yrt6DmDFynVUrFCWqv+/gXc5VPvloIWLVuXWrTsZ09CsSPI9ACpF0b9fIu7R9cxuQob4qoUHXp4dae7+VWY35ZNh6VTrw0FCL8W/vvvhoPd4Mb17imOzDVycqmOJtKWPOb+z1xCqVCyHl2fHDwcbMMn5hikj8z3ob87P1JGAR48esXTpUgIDAwkPDwfA0dGR6tWr07lzZ/LkyZOZzfukXb1+CyurbHzTWO7QC5Em5EGxdCc5P2WeR8fwz937zJ8yLrObIoR+knwPZOJIwMmTJ3FzcyNbtmy4urri4OAAQEREBHv37uXFixfs3r2bypUrv7ee2NjYJA/CGD2/i/n/X3AlDIvcFTJcqb4zNKVrimOzDVmaqmMZIsn5Ij1IzjdMGZnvQX9zfqaNBPTp04fWrVuzcOHCJGvhK4pCz5496dOnD4GBge+tx9fXl7Fjx2qVeQ/pi8/QfmneZiGE/pKXx6QvyflCiE+F5Hu1TBsJsLS05MyZM5QoUSLZ/aGhoVSoUIGXL1++tx65KyTeJneFDFdq7wzFTOz04aD/yz5yRaqOZYgk54v0IDnfMGVkvgf9zfmZNhLg6OjIiRMn3nlBOHHihGa4+H3Mzc2TJP+414/SpI1CCAMib5BMV5LzhRCfDMn3AGTaG4UGDx5Mjx496NevH1u3buX48eMcP36crVu30q9fP3r27MnQoUMzq3kZYsnKdZSp0ZhJMxdqym7fuUffEeOo5f4dVb9qwaBRP/Mo8sl764mJecGkmQv5qoUHleo1o8MPAzkfEqYVU6ZG42S3pas2APD69WuGj5tC1a9a4N62G4Enz2h9f+mqDfw8fX4anbl4W6+eHly9fIzoqGsc/XsbVSqXf298y5Zfc+H8QaKjrnHm9F80bqT90iCfUQO5cP4gz55c4WHERXbvXMOXb73ozczMDL9ls4l8FMqli4dpUF/7TtqggT2ZOWN8mp1flpGopHwTOjPUnJ+S/PzG2MlzKFOjMSvXbv5gvX9s3EbDlh5UrPcN7br35/ylf+t8FvWcn6fP5+u23ahUrxmuLTrx84wFPI+O0YrxGjqaKq7f0qqzFyGXr2rVP2HaPPz+0F6aUqServn+jTZtviH+9V02bvjtnTHz5k4i/vVd+vbppimTfP8OuuR7Pc75mTYS4OXlRe7cuZkxYwbz588nIUE9P8vY2JhKlSrh5+dHmzZtMqt56e58SBjr/9xBsSLOmrIXL1/RY8BIihcpxG+zJwEwd/FKeg8dw+pFM975FlifSbO4ev0mvj6Dsc+di22799G930/8uepXHPLkBuDA1lVa3zl87BQ+vjP5qm4NANb/uZNLYVdY9esMDh87ybAxv3DQ/w9UKhV37oWzcdsu1v42Kz1+CoPWuvU3TJ0ymh+9hnPi5Bn69unGju2rKFWmNg8fPk4S71KtMqtWzmOkty/bd/xFu7bfsnHDb1Sp2oiLF9V/BFy+cp1+/by5fuMWlpYW9OvbnZ07VlO8ZA0ePYqke7cOVKxYlpq1v6GRWz1WrpiLU75yAHz+eX48PTtQtVrjDP0dPgny8ph0Zag5PyX5GeCvg0c4dzEU+9y5Pljnzr8OMnnOInyG9OGLUsVZuW4LPwz0Ztsfi8mV05YHjx7z4FEkg3t3o9DnBbgf8YBxU+by8NFjZkz0BmDR8jXEvHjJ+qVzWLt5O6MnzWbd0tkAnL0QwrmLYYzo3zN9fhQDpWu+f6NgwXxMnuTD4cPH3hnTrFkjqlatyN2797XKJd+/g+R7IBNHAgC+++47jh07xosXL7h79y53797lxYsXHDt2TC8vBm+8ePGS4WOnMGZYP6238J45d5F74Q+Y6D2QYoWdKVbYmYneg7gYeoXjQWeTretVbCx/HfybgV6eVC5flgL5nPDy7EiBfE6s3bxdE5c7l53Wtv/wMb6s+AX5P8sLwPVb/1CvZjWKFCpIu5ZNiXz6jCdPnwEwfupcBvTqglX27On4qximAf26s+S31SxfsY6QkCv86DWcFy9e0qVz22Tj+/TxZPfuA0ybvpDQ0KuMHjOFM2cu8GOvLpqYNWu2sHffYW7cuM2lS5cZPGQsNjbWfFG2FAAlShTF338Ply5dZv6C5djb5yZ3bjsA5s3xZcRPE3n+PDr9T/5TI3eF0p2h5fyU5ueIh4/wnbGAX0YPxcTE+IP1rli7mVZNG/Ote0MKOxfEZ0gfLMzN2ey/B4CihT5n5s/e1K1ZjQL5nKhaqTx9e3hw4Mhx4v//QOT1m7dp3KAOnxfIR6tmjblx6zYAcfHxjJsyF58hvTE2/nBbRMrpmu8BjIyMWLl8LmPHTeX6jdvJxjg5OTJrxgQ6efQmLi5ea5/k+3eQkQAgkzsBb5iampI3b17y5s2LqalpZjcn3U2YNo/aLlVweWuKBkBcXBwqFZi99RuYm5liZKTi9LmLydaVEJ9AQkIi5mbav5u5udk7v/Mo8gmHjp6gxddumrLiRQpx+txFXsXGcuR4EHly2ZHT1gb/3fswNzPDtU6Njz1d8Q6mpqZUrPgFe/cd1pQpisLefX9TrVqlZL9TrWolrXiAPQEH3hlvampK924dePr0GWf//7+Hc+cuUaP6l1hYWNCwYR3u3Qvn0aNI2rX7llexsfz55640OsMsRklM+SZSxVByfkryc2JiIiPGTaVz+1YUKVTwg3XGxcVxKewK1aqU15QZGRlRrXJ5zl4Ieef3nkfHYJU9m6aTUaxIIU6cPkt8fAJHjwdRrLB6VHrpqvVUqVCWMiWL6Xq64j0+Jt8DjPIewIOHj1jmtybZ/SqViuXLZjNt+gIuXbqcZL/k+3fQJd/rcc7/JDoBhmTHXwcIuXyN/j27JNn3RekSWFpYMH3+Ul6+esWLl6+YOncJCQmJPHocmWx92bNno1yZkiz0+4MHDx+TkJDAtt37OHshlEePkv/O1p1/kS2bpdYf9t9+3ZDiRQrRrMMPLFq+hmnjRxD1PJq5S1YyYkAvZi9aTuM2XekxYCQRD+UhvLSQO7cdJiYmPIjQ/j0fPHiIo0PyL01ydMxDxIOHWmUREY+SxLs3ceVp5GVinl+nX9/uNGrcjseP1c+WLPNbw9lzlzh/dj8jhvelXfue5MxpyxifwfTrP4pxY4cSeulvdvivwsnJMQ3P+BOXjneFDh06RNOmTXFyckKlUrFlyxat/Yqi4OPjQ968ebG0tMTV1ZUrV65oxURGRtKhQwesra2xtbXF09OT6GjtO3jnzp2jVq1aWFhYkD9/fiZPnpykLevXr6dEiRJYWFhQtmxZduzYofP5iJRJSX7+7ff1GBsb0bF1sxTV+eRpFAkJieSyy6lVnssu5zufH3vy9Bm/+v1Bq2/+nfbR7fs2GBsb07hNV/YeOsq4Ef259c9dtu7cS88u7Rk7eQ6NWndh0KiftZ4lEB/nY/J9jepV6NK5HT/0HPLOeocO8SI+Pp45c5N/VkDy/TvISAAgnYAMdT/iIZNm/sqk0UMxNzdLst8upy3Txv/EgSPH+dK1BS5uLYmKjqFU8SJJ1tV+m++owaAo1G/ekYr1vmHV+j9p7FoH1TueIdjsv4evG9bTaoOpiQneg7zYvcGPtb/NpmK5MkyZs5gOrZsRevka+w4FsnH5fL4oXQLfGQuTrVd8OvYfOEKlKg2pVbsZu/cc4I/VC8mTRz3XOD4+nr79RlK0uAsu1d05cvQkUyb7MHfeUsqXL80337hRsfJXHD9xmpkzDOeNpUpiYoo3XcXExFCuXDnmzZuX7P7Jkycze/ZsFi5cyPHjx8mePTtubm68evVKE9OhQwcuXrxIQEAA/v7+HDp0iB49emj2R0VF0bBhQwoWLEhQUBBTpkxhzJgxLFq0SBNz9OhR2rVrh6enJ2fOnKF58+Y0b96cCxcu6HxOImXel58vhl7h9/V/MnHkoPfm+NSIjonhxyGjKexcgB89O2rKc1hlZ/KYYQRsWo7fvCkUdi7I2MlzGOTlif+e/dy5d59tfyzGwtychctWp0vbxLtZWWXHb9lsevYaormB818VK5SlT29PunYb8M56JN8nT5d8/zE5P6vItAeDDdGlsCtEPnlKm669NWUJCYkEBV/gj03bOL1/KzWqVmLX+mU8efoMY2NjrHNYUadpexo1yPvOegvkc8Jv3hRevHxFTMwL8uS2Y9AoX/Il06sPCr7Ajdt3mDJuxHvbeiLoLFdv3GLs8H5Mm/cbtVyqkM3Sgkb1a+Ox8d13JUTKPXoUSXx8PPYOubXK7e3zEB7xMNnvhIc/xMFe+66Rg0PuJPEvXrzk2rWbXLt2k+MnThNy8W+6dmnHL5PnJqmzbp3qlC5VjB4/DGbypFHs2rWPFy9esn7DNq1nDfRefPol+saNG9O4cfIP3ymKwsyZM/H29qZZM/Xd4BUrVuDg4MCWLVto27YtISEh7Nq1i5MnT2reqDtnzhyaNGnC1KlTcXJyYtWqVbx+/ZqlS5diZmZG6dKlCQ4OZvr06ZrOwqxZs2jUqBFDhqj/Pzx+/HgCAgKYO3cuCxdK5z49vC8/nz57gcgnT/mq5b9rlickJDJl7hJWrtvCno3Lk9SX09YaY2MjHv/nrv/jyCfk/s/oQEzMC34YOIrs2SyZ9fMoTE3efcnfvH0POayyU7+WC/1GjKdB7eqYmpjQsH4t5i1ZmcpfQeia7wsX/hxn5wJs2eynKXuzOMirF7coVaY2NWtWxd4+NzeundDEmJiYMGWyD337dKNIsWpJ6pV8/3/pmO+zEukEZKBqlcqzeeUCrTLvidNxLpgfz46ttR7CymlrA8DxoGAinzylXs2k/2f+r2yWFmSztOBZ1HOOnghi4I9JX4u9yX83pYoXpUTRQu+sJzb2NROmz+OX0UMxNjYmITGRN++Ui4+PJ1GPe8UZKS4ujtOnz1G/Xk22bt0NqOd31q9Xk/kLliX7nWPHg6hfvyaz5yzRlLk2qM2xY0HvPZaRkSrZ0Sdzc3Nmz55IJ4/eJCYmYmRshKlKPX/Z1NQUY2MDGizUYd5nci+sSm79+pS4ceMG4eHhuLq6aspsbGyoWrUqgYGBtG3blsDAQGxtbTUdAABXV1eMjIw4fvw43377LYGBgdSuXRszs3//nd3c3Pjll1948uQJOXPmJDAwkIEDB2od383NLcn0JJH2ksvPX9WtSbX/PBv2wwBvmjaqT/MmDZOtx9TUlFLFi3L8VDANalcH1M8VHA8Kpl3LbzRx0TEx/DDAG1MzU+b8MjrZ//+/EfnkKQuXrWbFgqma+uLi1Q+YxsfHk5AgOT+1dM33oaFXKVdBe/nncWOHksPKigGDfPjnn3v8vmpjkmfEdvivYtXqjfgtX5ekTsn3b9Hjef66kE5ABsqePRtFC32uVWZpaYGtdQ5N+ebteyhUMD85bW04ezGUSTMX0um7b3EumE/zHc++w2lQuzrtW6kT/pHjQSiKwucF8nH7zj2mzfsN5wL5aO6ufRGJjolhz/7DDO7d/b3tXOi3mlouVShZrAgAFcqWYtq832ju3pDVG7dR/v+rzIjUmzFrMct+m0HQ6XOcPHmGvn26kz27JX7L1wKwbOks7t27z0hv9ZKxc+b8xr69GxjQ/wd27PyL79o0o1KlL+j5o3p99WzZLPlpRD+2bdvD/fAIcueyo1evznz2mSMbNvonOb73yP7s2rmP4GD1Q4pHA0/xi683fivW8mOvzhw9eiqDfolPgA7zPn19fRk7dqxW2ejRoxkzZozOhw0PDwdI8qIsBwcHzb7w8HDs7e219puYmGBnZ6cV4+zsnKSON/ty5sxJeHj4e48j0t778rOpiQm2NtZa8SYmxuS2y/nenN/pu28ZOXEapUsUpUyp4vy+bgsvX8XS3P0rQJ3re/QfycvYWGb5DCEm5gUxMS8A9Q2m/67688usX/Fo20KzZGmFL0qxbdc+qn9ZkQ1/7qTCF5Lz04Iu+T42Nlaz7PMbT59GAWjKIyOfEPmfEaG4uHjCwx9y+fK1JMeXfP8WPZ7nrwvpBHxibt6+w8yFfjyLes5neR3o4dGWTt99qxXzz937PHkWpfn8PDqGmQuXEfHwETbWOfiqTk36/uCRZOh3518HURRo8lXddx7/yvWb7N53mA1+/85dblivJifPnMPjx8F8XiAfk8cMS5uTFaxfv5U8ue0Y4zMYR8c8nD17EfevO/LggfrhsQL5nbRGXgKPnaJjp96MGzuUCeOHceXqDVq28tRcFBISEilevDDfd1xE7tx2PH78hFNBZ6lbr0WSlSNKly5Oq5ZNqVTlK03Zxo3+1KntwoF9m7h8+RodO/XGUCg6XBRGjBiR5I76x4wCCP2X0vz8Pv/N+Y1d6/Dk6TPmLvmdR5GRlChamIXTxmumA10Ku8a5/788rMl3nlp17d7gx2d5/+0IHjkexO279/H1+XeaZ7uWTbkYeoX23ftTtlRxenXt8FHnLrTpmu/TkuR7bbrke32mUt7M89AjcY+uZ3YTRCaxdKr14SChl+Jf303V95/3/TrFsTlmJx1VSSmVSsXmzZtp3rw5ANevX6dw4cKcOXOG8uXLa+Lq1KlD+fLlmTVrFkuXLmXQoEE8efLvXb/4+HgsLCxYv3493377LZ06dSIqKkpras/+/fupX78+kZGR5MyZkwIFCjBw4ED69++viRk9ejRbtmzh7Nnk30WSFUjON1yS8w1TRuZ7SF3O/5QZ0AQwIYR4j8TElG9pyNnZGUdHR/bu3aspi4qK4vjx47i4uADg4uLC06dPCQr699mPffv2kZiYSNWqVTUxhw4dIi4uThMTEBBA8eLFyZkzpybm7eO8iXlzHCGEMAi65Hs9fg5SOgFCCAHpumZ0dHQ0wcHBBAcHA+qHgYODg7l9+zYqlYr+/fszYcIEtm7dyvnz5+nUqRNOTk6a0YKSJUvSqFEjunfvzokTJzhy5Ai9e/embdu2ODk5AdC+fXvMzMzw9PTk4sWLrF27llmzZmlNW+rXrx+7du1i2rRphIaGMmbMGE6dOkXv3oYzDUAIIeQ9AWryTIAQQkC6JvpTp05Rr149zec3f5h7eHjg5+fH0KFDiYmJoUePHjx9+pSaNWuya9cuLCwsNN9ZtWoVvXv3pkGDBhgZGdGyZUtmz56t2W9jY8OePXvw8vKiUqVK5M6dGx8fH613CVSvXp3Vq1fj7e3NTz/9RNGiRdmyZQtlypRJt3MXQohPjh7/Ya8LeSZA6BWZH2q4UjtHNOoHtxTHWv+6O1XHEmlLcr7hkpxvmDIy34P+5nwZCRBCCJA7Q0IIYSgk3wPSCRBCCAAUeYOkEEIYBMn3atIJEEIIkDtDQghhKCTfA9IJEEIINbkxJIQQhkHyPSCdACGEAOQNkkIIYSgk36vJewKEEAJkzWghhDAU6fiegAULFvDFF19gbW2NtbU1Li4u7Ny5U7P/1atXeHl5kStXLqysrGjZsiURERFaddy+fRt3d3eyZcuGvb09Q4YMIT4+XivmwIEDVKxYEXNzc4oUKYKfn5/OP4N0AoQQAtTDwyndhBBCZF265Hsdc36+fPmYNGkSQUFBnDp1ivr169OsWTMuXrwIwIABA9i2bRvr16/n4MGD3Lt3jxYtWmi+n5CQgLu7O69fv+bo0aMsX74cPz8/fHx8NDE3btzA3d2devXqERwcTP/+/enWrRu7d+u2lKm8J0DoFVkz2nCldt3oJ63rpjg25/oDqTqWSFuS8w2X5HzDlJH5HlKf8+3s7JgyZQqtWrUiT548rF69mlatWgEQGhpKyZIlCQwMpFq1auzcuZOvv/6ae/fu4eDgAMDChQsZNmwYDx8+xMzMjGHDhrF9+3YuXLigOUbbtm15+vQpu3btSnG7ZCRACCFARgKEEMJQ6DgSEBsbS1RUlNYWGxv7wcMkJCSwZs0aYmJicHFxISgoiLi4OFxdXTUxJUqUoECBAgQGBgIQGBhI2bJlNR0AADc3N6KiojSjCYGBgVp1vIl5U0dKpejB4K1bt6a4wm+++UanBgghxKdAHhRTk3wvhNB3uuZ7X19fxo4dq1U2evRoxowZk2z8+fPncXFx4dWrV1hZWbF582ZKlSpFcHAwZmZm2NraasU7ODgQHh4OQHh4uFYH4M3+N/veFxMVFcXLly+xtLRM0XmlqBPQvHnzFFWmUqlISEhIUawQQnxKlPgPxxgCyfdCCH2na74fMWIEAwcO1CozNzd/Z3zx4sUJDg7m2bNnbNiwAQ8PDw4ePPgxTU1XKeoEJCbK+LcQQs9JmgMk3wshDICOac7c3Py9f/T/l5mZGUWKFAGgUqVKnDx5klmzZvHdd9/x+vVrnj59qjUaEBERgaOjIwCOjo6cOHFCq743qwe9HfPfFYUiIiKwtrZO8SgApPKZgFevXqXm60II8clQElO+GSLJ90IIfaFLvk+LnJ+YmEhsbCyVKlXC1NSUvXv3avaFhYVx+/ZtXFxcAHBxceH8+fM8ePBAExMQEIC1tTWlSpXSxLxdx5uYN3WklM6dgISEBMaPH89nn32GlZUV16+rV2UYNWoUv/32m67VCSHEp0EeDE5C8r0QQi+l4xKhI0aM4NChQ9y8eZPz588zYsQIDhw4QIcOHbCxscHT05OBAweyf/9+goKC6NKlCy4uLlSrVg2Ahg0bUqpUKb7//nvOnj3L7t278fb2xsvLSzMa0bNnT65fv87QoUMJDQ1l/vz5rFu3jgEDBujUVp07ARMnTsTPz4/JkydjZmamKS9TpgxLlizRtTohhPgkyEhAUpLvhRD6KD1HAh48eECnTp0oXrw4DRo04OTJk+zevZuvvvoKgBkzZvD111/TsmVLateujaOjI5s2bdJ839jYGH9/f4yNjXFxcaFjx4506tSJcePGaWKcnZ3Zvn07AQEBlCtXjmnTprFkyRLc3Nx0aqvO7wkoUqQIv/76Kw0aNCBHjhycPXuWQoUKERoaiouLC0+ePNGpAelB1ow2XLJmtOFK7brRDxrUSXGs/d5P7wGv9JAV8j1IzjdkkvMNU0bme9DfnJ+iB4PfdvfuXc3DDm9LTEwkLi4uTRolhBAZzZDu8KeU5HshhD6SfK+m83SgUqVKcfjw4STlGzZsoEKFCmnSKCGEyHCKKuWbgZB8L4TQS7rkez3O+TqPBPj4+ODh4cHdu3dJTExk06ZNhIWFsWLFCvz9/dOjjUIIke7kzlBSku+FEPpI8r2aziMBzZo1Y9u2bfz1119kz54dHx8fQkJC2LZtm+ahByGEyGoS41Up3gyF5HshhD7SJd/rc87XeSQAoFatWgQEBKR1W4QQItMoejzkmxqS74UQ+kbyvdpHvyzs1KlTrFy5kpUrVxIUFJSWbRJCiAyXXsvFJSQkMGrUKJydnbG0tKRw4cKMHz+etxdmUxQFHx8f8ubNi6WlJa6urly5ckWrnsjISDp06IC1tTW2trZ4enoSHR2tFXPu3Dlq1aqFhYUF+fPnZ/LkyR/9e7xN8r0QQp9k9MvCPlU6jwTcuXOHdu3aceTIEc0rj58+fUr16tVZs2YN+fLlS+s2CiFEulMS0+fO0C+//MKCBQtYvnw5pUuX5tSpU3Tp0gUbGxv69u0LwOTJk5k9ezbLly/H2dmZUaNG4ebmxqVLl7CwsACgQ4cO3L9/n4CAAOLi4ujSpQs9evRg9erVAERFRdGwYUNcXV1ZuHAh58+fp2vXrtja2tKjR4+ParvkeyGEPkqvfJ/V6DwS0K1bN+Li4ggJCSEyMpLIyEhCQkJITEykW7du6dFGIYRId4qS8k0XR48epVmzZri7u/P555/TqlUrGjZsyIkTJ/5/XIWZM2fi7e1Ns2bN+OKLL1ixYgX37t1jy5YtAISEhLBr1y6WLFlC1apVqVmzJnPmzGHNmjXcu3cPgFWrVvH69WuWLl1K6dKladu2LX379mX69Okf/ZtIvhdC6CNd8r2uOT8r0bkTcPDgQRYsWEDx4sU1ZcWLF2fOnDkcOnQoTRsnhBAZRUlUpXiLjY0lKipKa4uNjU223urVq7N3714uX74MwNmzZ/n7779p3LgxADdu3CA8PBxXV1fNd2xsbKhatSqBgYEABAYGYmtrS+XKlTUxrq6uGBkZcfz4cU1M7dq1td7s6+bmRlhY2Ee/1EvyvRBCH+mS7/V51EDnTkD+/PmTfUlMQkICTk5OadIoIYTIaLpcEHx9fbGxsdHafH19k613+PDhtG3blhIlSmBqakqFChXo378/HTp0ACA8PBwABwcHre85ODho9oWHh2Nvb6+138TEBDs7O62Y5Op4+xi6knwvhNBH0glQ07kTMGXKFPr06cOpU6c0ZadOnaJfv35MnTo1TRsnhBAZRZeh4REjRvDs2TOtbcSIEcnWu27dOlatWsXq1as5ffo0y5cvZ+rUqSxfvjyDz1B3ku+FEPpIpgOppejB4Jw5c6JS/dsTiomJoWrVqpiYqL8eHx+PiYkJXbt2pXnz5unSUCGESE+63O0xNzfH3Nw8RbFDhgzRjAYAlC1bllu3buHr64uHhweOjo4AREREkDdvXs33IiIiKF++PACOjo48ePBAq974+HgiIyM133d0dCQiIkIr5s3nNzEpIfleCKHv9Pnuvi5S1AmYOXNmOjdDCCEyV2JC+lwUXrx4gZGR9qCrsbExiYnqdeecnZ1xdHRk7969mj/6o6KiOH78OL169QLAxcWFp0+fEhQURKVKlQDYt28fiYmJVK1aVRMzcuRI4uLiMDU1BSAgIIDixYuTM2fOFLdX8r0QQt+lV77PalLUCfDw8EjvdgghRKZKTKeXxzRt2pSJEydSoEABSpcuzZkzZ5g+fTpdu3YFQKVS0b9/fyZMmEDRokU1S4Q6OTlp7rSXLFmSRo0a0b17dxYuXEhcXBy9e/embdu2mrn57du3Z+zYsXh6ejJs2DAuXLjArFmzmDFjhk7tlXwvhNB36ZXvs5qPemPwG69eveL169daZdbW1qlqkBBCZIb0eoPknDlzGDVqFD/++CMPHjzAycmJH374AR8fH03M0KFDiYmJoUePHjx9+pSaNWuya9cuzTsCQL0EaO/evWnQoAFGRka0bNmS2bNna/bb2NiwZ88evLy8qFSpErlz58bHx+ej3xHwX5LvhRD6Qt4YrKZSFN0eeYiJiWHYsGGsW7eOx48fJ9mfkJCQZo37WHGPrmd2E0QmsXSqldlNEJkk/vXdVH0/tFiTFMeWuLwjVcfKKrJCvgfJ+YZMcr5hysh8D/qb83VeHWjo0KHs27ePBQsWYG5uzpIlSxg7dixOTk6sWLEiPdoohBDpTlaKSEryvRBCH8nqQGo6Twfatm0bK1asoG7dunTp0oVatWpRpEgRChYsyKpVqzRrXwshRFYiq0UkJfleCKGPJN+r6TwSEBkZSaFChQD1fNDIyEgAatasKW+QFEJkWYmKKsWboZB8L4TQR7rke33O+Tp3AgoVKsSNGzcAKFGiBOvWrQPUd4xsbW3TtHFCCJFRFEWV4s1QSL4XQugjXfK9Pud8nTsBXbp04ezZswAMHz6cefPmYWFhwYABAxgyZEiaN1AIITKCzA9NSvK9EEIfyTMBajqvDvRft27dIigoiCJFivDFF1+kVbtSRVaKMFyyUoThSu1qEcEFv0lxbPlbW1N1rKzqU8z3IDnfkEnON0wZme9Bf3N+qt4TAFCwYEEKFiyYFm0RQohMkygPin2Q5HshhD6QfK+Wok7A2y+k+ZC+fft+dGOEECKz6PPDX7qQfC+E0HeS79VSNB3I2dk5ZZWpVFy/nvnDsiZmn2V2E0QmeXnvcGY3QWQS09yFUvX9k599m+LYKnc3p+pYn7Kslu9Bcr4hs7XIntlNEJngUdTlVH1fl3wP+pvzUzQS8GZ1CCGE0FdyZ0hN8r0QQt9JvldL9TMBQgihD/R4AQghhBBvkXyvJp0AIYRA7gwJIYShkHyvJp0AIYQAvX4hjBBCiH9JvleTToAQQgCJmd0AIYQQGULyvZp0AoQQAlCQO0NCCGEIJN+rGX3Mlw4fPkzHjh1xcXHh7l31W9tWrlzJ33//naaNE0KIjBKvqFK8GRLJ90IIfaNLvtfnnK9zJ2Djxo24ublhaWnJmTNniI2NBeDZs2f8/PPPad5AIYTICAqqFG+GQvK9EEIf6ZLv9Tnn69wJmDBhAgsXLmTx4sWYmppqymvUqMHp06fTtHFCCJFREnXYDIXkeyGEPtIl3+tzztf5mYCwsDBq166dpNzGxoanT5+mRZuEECLD6fPdno8l+V4IoY8k36vpPBLg6OjI1atXk5T//fffFCpUKE0aJYQQGU3uCiUl+V4IoY9kJEBN505A9+7d6devH8ePH0elUnHv3j1WrVrF4MGD6dWrV3q0UQgh0p1cEJKSfC+E0EfSCVDTeTrQ8OHDSUxMpEGDBrx48YLatWtjbm7O4MGD6dOnT3q0UQgh0p0MDycl+V4IoY8k36vpPBKgUqkYOXIkkZGRXLhwgWPHjvHw4UPGjx+fHu0TQogMkahK+aaru3fv0rFjR3LlyoWlpSVly5bl1KlTmv2KouDj40PevHmxtLTE1dWVK1euaNURGRlJhw4dsLa2xtbWFk9PT6Kjo7Vizp07R61atbCwsCB//vxMnjz5o36LNyTfCyH0kS75Xpec7+vrS5UqVciRIwf29vY0b96csLAwrZhXr17h5eVFrly5sLKyomXLlkRERGjF3L59G3d3d7Jly4a9vT1DhgwhPj5eK+bAgQNUrFgRc3NzihQpgp+fn86/w0e9JwDAzMyMUqVK8eWXX2JlZfWx1QghxCchEVWKN108efKEGjVqYGpqys6dO7l06RLTpk0jZ86cmpjJkycze/ZsFi5cyPHjx8mePTtubm68evVKE9OhQwcuXrxIQEAA/v7+HDp0iB49emj2R0VF0bBhQwoWLEhQUBBTpkxhzJgxLFq0KNW/jeR7IYQ+0SXf65LzDx48iJeXF8eOHSMgIIC4uDgaNmxITEyMJmbAgAFs27aN9evXc/DgQe7du0eLFi00+xMSEnB3d+f169ccPXqU5cuX4+fnh4+Pjybmxo0buLu7U69ePYKDg+nfvz/dunVj9+7dOv0OKkVRFF2+UK9ePVSqd/8g+/bt06kB6cHE7LPMboLIJC/vHc7sJohMYpo7dQ+qbnJsn+LYFuGrUxw7fPhwjhw5wuHDyf9vU1EUnJycGDRoEIMHDwbU6/A7ODjg5+dH27ZtCQkJoVSpUpw8eZLKlSsDsGvXLpo0acKdO3dwcnJiwYIFjBw5kvDwcMzMzDTH3rJlC6GhoSlu79uyQr4HyfmGzNYie2Y3QWSCR1GXU/V9XfI96Jbz3/bw4UPs7e05ePAgtWvX5tmzZ+TJk4fVq1fTqlUrAEJDQylZsiSBgYFUq1aNnTt38vXXX3Pv3j0cHBwAWLhwIcOGDePhw4eYmZkxbNgwtm/fzoULFzTHatu2LU+fPmXXrl0pbp/OIwHly5enXLlymq1UqVK8fv2a06dPU7ZsWV2rE0KIT0KiSpXiLTY2lqioKK3tzYu0/mvr1q1UrlyZ1q1bY29vT4UKFVi8eLFm/40bNwgPD8fV1VVTZmNjQ9WqVQkMDAQgMDAQW1tbTQcAwNXVFSMjI44fP66JqV27tqYDAODm5kZYWBhPnjz5qN9E8r0QQh/pku91zflve/bsGQB2dnYABAUFERcXp5XvS5QoQYECBbTyfdmyZTUdAFDn8qioKC5evKiJebuONzFv6kgpnR8MnjFjRrLlY8aMSTI/VQghsgpdhkR9fX0ZO3asVtno0aMZM2ZMktjr16+zYMECBg4cyE8//cTJkyfp27cvZmZmeHh4EB4eDqCV8N98frMvPDwce3t7rf0mJibY2dlpxTg7Oyep482+t6cfpZTkeyGEPtJpCgy65fw3EhMT6d+/PzVq1KBMmTIAmpFaW1tbrdj/5vvkrgdv9r0vJioqipcvX2JpaZmi89K5E/AuHTt25Msvv2Tq1KlpVaUQQmQYXZaBGzFiBAMHDtQqMzc3T77exEQqV67Mzz//DECFChW4cOECCxcuxMPD42Obm6kk3wshsjJdl/3UJee/4eXlxYULF/j77791PFrG+egHg/8rMDAQCwuLtKpOCCEylC4rRZibm2Ntba21veuCkDdvXkqVKqVVVrJkSW7fvg2oX8gFJFkdIiIiQrPP0dGRBw8eaO2Pj48nMjJSKya5Ot4+RlqRfC+EyMp0XR1Il5wP0Lt3b/z9/dm/fz/58uXTlDs6OvL69eskb1z/b77/UC5/V4y1tXWKRwHgI0YC3n6CGdQPtd2/f59Tp04xatQoXasTQohPgq6r/qRUjRo1kiwRd/nyZQoWLAiAs7Mzjo6O7N27l/LlywPqlX6OHz+ueSGXi4sLT58+JSgoiEqVKgHqh3ITExOpWrWqJmbkyJHExcVhamoKQEBAAMWLF/+oqUAg+V4IoZ/SK98rikKfPn3YvHkzBw4cSDJFs1KlSpiamrJ3715atmwJQFhYGLdv38bFxQVQ5/KJEyfy4MEDzTTQgIAArK2tNTeUXFxc2LFjh1bdAQEBmjpSSudOgI2NjdZnIyMjihcvzrhx42jYsKGu1QkhxCdB1zmiKTVgwACqV6/Ozz//TJs2bThx4gSLFi3SLN2pUqno378/EyZMoGjRojg7OzNq1CicnJxo3rw5oB45aNSoEd27d2fhwoXExcXRu3dv2rZti5OTEwDt27dn7NixeHp6MmzYMC5cuMCsWbPeOa8/JSTfCyH0UXrley8vL1avXs2ff/5Jjhw5NHP4bWxssLS0xMbGBk9PTwYOHIidnR3W1tb06dMHFxcXqlWrBkDDhg0pVaoU33//PZMnTyY8PBxvb2+8vLw0ow89e/Zk7ty5DB06lK5du7Jv3z7WrVvH9u3bdWqvTkuEJiQkcOTIEcqWLfvRd5YygiwXZ7hkiVDDldolQld81jHFsZ3u/q5T3f7+/owYMYIrV67g7OzMwIED6d69u2a/oiiMHj2aRYsW8fTpU2rWrMn8+fMpVqyYJiYyMpLevXuzbds2jIyMaNmyJbNnz9Zat//cuXN4eXlx8uRJcufOTZ8+fRg2bJhObX0jq+R7kJxvyGSJUMOU2iVCdcn3kPKc/64llZctW0bnzp0B9cvCBg0axB9//EFsbCxubm7Mnz9fa9rmrVu36NWrFwcOHCB79ux4eHgwadIkTEz+vXd/4MABBgwYwKVLl8iXLx+jRo3SHCOldH5PgIWFBSEhIUmGOD4lckEwXNIJMFyp7QT46XBR6KxjJyCrygr5HiTnGzLpBBim1HYCdMn3oL85X+cHg8uUKcP169fToy1CCJFpElQp3wyF5HshhD7SJd/rc87XuRMwYcIEBg8ejL+/P/fv30/y8gQhhMiKEnXYDIXkeyGEPtIl3+tzzk/xg8Hjxo1j0KBBNGnSBIBvvvlGa+6ToiioVCoSEhLSvpVCCJHO9DnR60ryvRBCn0m+V0txJ2Ds2LH07NmT/fv3p2d7hBAiUyh6POSrK8n3Qgh9JvleLcWdgDfPD9epUyfdGiOEEJlF7gz9S/K9EEKfSb5X0+k9Ae9a+kgIIbI6uShok3wvhNBXku/VdOoEFCtW7IMXhsjIyFQ1SAghMkN6vTwmq5J8L4TQV5Lv1XTqBIwdOzbJGySFEEIfJMqNby2S74UQ+kryvZpOnYC2bdtib2+fXm0RQohMI8PD2iTfCyH0leR7tRR3AmR+qBBCn8lF4V+S74UQ+kzyvZrOqwMJIYQ+0ue3QupK8r0QQp9JvldLcScgMVH6TUII/SUZ7l+S74UQ+kwynJpOzwQIIYS+knvfQghhGCTfq0knQAghgES5LAghhEGQfK8mnQAhhECGh4UQwlBIvleTToAQQiDDw0IIYSgk36tJJ0AIIZA7Q0IIYSgk36tJJ0AIIZA3SAohhKGQfK8mnQAhhEAeFBNCCEMh+V7NKLMbIHTnM2og8a/vam0Xzh/U7J8/7xfCQo7w/NlV7t89x6aNSylevHAmtli87VTwebyGjqbeNx0oU6Mxew8dfWfs2MlzKFOjMSvXbk51nQEHjtC9/0/UaNyGMjUaE3r52jvrUxSFnoNGfbB9+iRBh02IjPJDj06cDgog8lEokY9C+fvQVhq51dPs3xuwPsn1YN7cSZnYYvGx+g38gYADG7l59zQh1wJZsXo+RYo4vzN+zcYlPIq6TGN3V01Z6TIlWLR0OmcvHeSfiHMcPbmTHr06ZUTzsxRd8r0+53zpBGRRFy6G8ln+8pqtTt3mmn2nT5+jW/eBlPmiLk3c26NSqdi5/Q+MjOSf+1Pw8uUrihcpxMhBP7437q+DRzh3MRT73LnSpM6Xr15R8YvSDOjV9YP1rVy7BUMbLU1ESfEmREa5e/c+I0f68mW1xlR1acL+A0fYtHEppUoV08QsXvK71vVg+IgJmdhi8bGq16zCb4t+x61BG1o164KpqQnrtywlWzbLJLE9vTon+2bvcuVL8/DhY3p1H0zNqu7MmLoA79GD8OzRMSNOIcvQJd/rc86X6UBZVHx8AhERD5Pdt+S3VZr/fuvWHXxGT+ZM0F98/nl+rl+/lVFNFO9Qy6UKtVyqvDcm4uEjfGcs4NfpE/lxiE+a1PlNowYA3L0f8d640MvXWL5mI2t/m03dbzp88Nj6Qn/TvMjK/LcHaH0e5fMLP/T4nqpfVuTSpcsAvHjx6p3XA5F1fNeim9bn3j2HEXbjOOXKlybw6ClNeZmyJfmxd1dc67Tg0lXtkdrVv2/U+nzr5j9U/rICXzf9it8W/Z5+jc9iJN+rya3hLKpoEWdu3wzicuhRViyfQ/78TsnGZctmSedO33H9+i3++edeBrdSfIzExERGjJtK5/atKFKoYIYe++WrVwwd+wsjB3mRO5ddhh47syXqsKXGpEmTUKlU9O/fX1P26tUrvLy8yJUrF1ZWVrRs2ZKICO3O2u3bt3F3dydbtmzY29szZMgQ4uPjtWIOHDhAxYoVMTc3p0iRIvj5+aWyteJTYmRkRJs235A9ezaOHQ/SlLdv9y3h984TfGYvEycMx9LSIhNbKdKKtU0OAJ48eaYps7S04NffpjFs0FgePHiUsnqsrbTqELrle31eSUhGArKgEyfO0LXbAC5fvkZeR3tGeQ/kwL7NlKtQn+joGAB6/uDBJN+RWFllJzTsKo2atCMuLi6TWy5S4rff12NsbETH1s0y/NiTZy+ifJlS1K/lkuHHzmwZMeR78uRJfv31V7744gut8gEDBrB9+3bWr1+PjY0NvXv3pkWLFhw5cgSAhIQE3N3dcXR05OjRo9y/f59OnTphamrKzz//DMCNGzdwd3enZ8+erFq1ir1799KtWzfy5s2Lm5tbup+bSD9lypTg70NbsbAwJzo6hlatuxEScgWAP9Zs4fbtO9y7H0HZsiXxnTiSYsUK07pN90xutUgNlUrFxEkjORYYROj//60BJvj+xMnjZ9i5Y2+K6qnyZQWat2hCu9Y90qupWZI+T/HRhXQCsqBdu/dr/vv58yEcP3GG61eP07pVU5b5rQFg9R+b+GvvIfI62jNwYE/+WL2Q2nWaExsbm1nNFilwMfQKv6//k/VL56BSZeys/P2Hj3E86Cwbls3N0ON+KtL7khAdHU2HDh1YvHgxEyb8O2f72bNn/Pbbb6xevZr69esDsGzZMkqWLMmxY8eoVq0ae/bs4dKlS/z11184ODhQvnx5xo8fz7BhwxgzZgxmZmYsXLgQZ2dnpk2bBkDJkiX5+++/mTFjhnQCsriwsGtUqtIQG+sctGzpztLfZlLftSUhIVe0pn9euBBK+P0HBOxZR6FCBWX6ZxY2edpoSpQsirtbO01Zo8b1qVWnGvVqNk9RHSVKFmXlmgVMmTSXA/uOpFNLsybpAqjJdCA98OxZFJevXKdIkc81ZVFRz7l69QaH/z5Om+96UKJ4EZo3b5R5jRQpcvrsBSKfPOWrlp0oV9udcrXduRf+gClzl9CwpUe6Hvt4UDD/3L2PS6NWmmMDDBg5kc69h6brsT8FugwNx8bGEhUVpbV9qIPt5eWFu7s7rq6uWuVBQUHExcVplZcoUYICBQoQGBgIQGBgIGXLlsXBwUET4+bmRlRUFBcvXtTE/LduNzc3TR0i64qLi+PatZucPnOekd6TOHfuEn16d0s29viJ0wAUKfx5BrZQpKVJU31o2Kgezb/uxP17/04LrFmnGp87F+DaP6cIj7xEeOQlAPx+n8Of21dq1VGseGE2bVvOimVrmT5lQYa2PyuQ6UBqMhKgB7Jnz0bhQgVZtWpjsvtVKhUqlQpzM/MMbpnQVdNGDahWpYJW2Q8DvGnaqD7NmzRM12N3+74NLb/R7ih++30vhvbtQd0aVdP12J8CRYd7Q76+vowdO1arbPTo0YwZMybZ+DVr1nD69GlOnjyZZF94eDhmZmbY2tpqlTs4OBAeHq6JebsD8Gb/m33vi4mKiuLly5dYWiZdYURkTUZGRpibmyW7r3y50gDcD3+QkU0SaWTSVB/cv/6KZu4duX3rjta+2dMX8fvy9Vplfx/fjveIn9m9898ZAsVLFGGz/wrWrt7Mz+NnZEi7sxpd8r0+k05AFjR50ij8twdw6/YdnPI6MtpnEAkJiaxZuwVn5wK0af0NAQEHefjoMfk+c2LoUC9evnzFzl0pm0Mo0teLFy+5feffh7Tv3osg9PI1bKxzkNfRHlsba614ExNjctvlxLlgvo+uE+BZ1HPuhz/gwaPHANy4rb7A5M6Vk9y57DTbf+V1yEM+J8ePP+EsQpe7PSNGjGDgwIFaZebmyXey//nnH/r160dAQAAWFvLAptDNxAnD2bVrP7f/uUuOHFa0a9ucOnVcaOLenkKFCtKu7bfs3LmXx5FPKFu2JNOmjOHQoUDOnw/J7KYLHU2ePpqWrZryfbteRD+Pwd4+N6Ae2X/1KpYHDx4l+zDwnX/uazoMJUoWZbP/Cvbv/ZsFc5dp6khISODx4ycZdzKfOH2+u68L6QRkQZ/ly8vvK+eRK1dOHj6M5MjRE9So1ZRHjyIxNTWlZo0v6dunGzlz2hAR8YjDfx+jVp1mPHz4OLObLoALoVfo2meY5vPkOYsAaNbYlYneg1JUR+feQ/nM0UETn5I69x8+hvfP0zUxQ0arXyjUq2sHvDxlDekEHe4MmZubv/OP/v8KCgriwYMHVKxY8d9jJSRw6NAh5s6dy+7du3n9+jVPnz7VGg2IiIjA0VHd+XJ0dOTEiRNa9b5ZPejtmP+uKBQREYG1tbWMAmRhefLkZtnSWeTNa8+zZ885fz6EJu7t+WvvYfLlc6JB/Zr07dON7Nkt+eef+2zesoOJP8/K7GaLj9C1m3pJ5q07V2mV9+45jDWr3//CyDe+ad6IPHly0aZtM9q0/Xdxidu37lCxbP20a2wWp0u+12cqJbm3TWRxJmafZXYTRCZ5ee9wZjchQ3zVwgMvz440d/8qs5vyyTDNXShV3//h89Ypjv315voPB/3f8+fPuXVL+wHNLl26UKJECYYNG0b+/PnJkycPf/zxBy1btgQgLCyMEiVKEBgYSLVq1di5cydff/019+/fx95ePbKzaNEihgwZwoMHDzA3N2fYsGHs2LGD8+fPa47Tvn17IiMj2bVrV4rbmxVJzjdcthbZM7sJIhM8irqcqu/rku9Bt5yflchIgBBZzNXrt7CyysY3jRtkdlP0SnoND+fIkYMyZcpolWXPnp1cuXJpyj09PRk4cCB2dnZYW1vTp08fXFxcqFatGgANGzakVKlSfP/990yePJnw8HC8vb3x8vLSjEj07NmTuXPnMnToULp27cq+fftYt24d27dvT6czE0KIrEmmA6lJJ0CILKZIoYJsXiGrPaS1zHxQbMaMGRgZGdGyZUtiY2Nxc3Nj/vz5mv3Gxsb4+/vTq1cvXFxcyJ49Ox4eHowbN04T4+zszPbt2xkwYACzZs0iX758LFmyRJYHFUKI/5AHg9U+6elA//zzD6NHj2bp0qXvjImNjU2yNF/OXCUyfI118WkwlOlAIqnUTgfq+nmrFMcuvbkhVccSyZOcL3Ql04EMU2qnA+mS70F/c/4n/Z6AyMhIli9f/t4YX19fbGxstDYl8XkGtVAIoS8UHf4j0ofkfCFERtAl3+tzzs/U6UBbt2597/7r169/sI7klurLmatEqtolhDA8Mkc0/UnOF0J8CiTfq2VqJ6B58+aoVCreNyPpQ0O8yS3VJ8PCQghdJX66MyP1huR8IcSnQPK9WqZOB8qbNy+bNm0iMTEx2e306dOZ2bwM1aunB1cvHyM66hpH/95Glcrl3xlbqlQx1q1dxNXLx4h/fZe+fZK+Pt7KKjvTpo7l2pXjPH92lcMH/6RypXJaMQMH/MC9O2e5d+csA/r/oLXvyyoVOH5sJ8bGxmlyfkLbkpXrKFOjMZNmLtSU3b5zj74jxlHL/TuqftWCQaN+5lHk+1/ukpCQwJxFK3Br1ZlK9ZrRqHUXFi5brfVHVsCBI3Tv/xM1GrehTI3GhF6+lqSeybMXUb1Raxp8+z3+u/dp7du97zBeQ0en8ow/fYoOm/g4kvPVdMn3ewPWE//6bpJt65YVWnFjRg/mn1unef7sKrt3rqFIEWfNPjMzM/yWzSbyUSiXLh6mQf1aWt8dNLAnM2eMT9NzFO/Xd0APHkVdZsKkn94b98OPHhwL2sU/Eec4e+kgE3xHvPNt0e+qc/zPI7hy6wRnLx2kVZumWvu+ad6IVWsXYmh0yff6nPMztRNQqVIlgoKC3rn/Q3eM9EXr1t8wdcpoxk+YTpWqjTh77hI7tq8iT55cycZns7TkxvXb/OT9M/fvRyQbs+jXqbi61qJzl76Ur+hKwF8H2b1rDU7/f/Nr2bIlGTN6CB06/kjH770YN3YIZcqoh9SNjY2ZN28SXl7DSUhISJ+TNmDnQ8JY/+cOir11kX7x8hU9BoxEhYrfZk9i5cJpxMXF03voGBIT3z1w+dvv61m7ZTs/DfyRrasXMfDHrixdtYFVG/6ddvHy1SsqflGaAb26JlvHgb+PsT3gAItmTGTQj56MnjSLJ0+fAfA8OobZi5bjPdArjc7+05VAYoo38XEk5+ue71u16c5n+ctrti/K1yM+Pp4NG/01MUMG/0hvr6782Hs41Ws2JebFC3b4r9KMmHTv1oGKFctSs/Y3LFnyOytXzNV89/PP8+Pp2YFRPr+k74kLjQoVy+LR5TsunA99b1zL1l8zasxgpkyaS/UqjenX+yeat2iC9+ikL5V8V51ujerRovXXtG7elbE+k5kxZyJ2djkByGFtxUifAQwdNDbtTi6L0CXf63POz9ROwJAhQ6hevfo79xcpUoT9+/dnYIsyx4B+3Vny22qWr1hHSMgVfvQazosXL+nSuW2y8aeCzjJsxATWrdtKbOzrJPstLCxo8W0TRoyYyOG/j3Pt2k3GjZ/O1Ws36flDJwCKFy/C+fMh7D9whH37/+b8+RCKFy8CwOBBvTh8+Bings6m30kbqBcvXjJ87BTGDOuHdQ4rTfmZcxe5F/6Aid4DKVbYmWKFnZnoPYiLoVc4/p5/h+ALIdSrVY061b/ks7wONKxXi+pfVuT8pTBNzDeNGtCrawdcqlRIto7rt/6hSoWylClZjCZf1SV79mzcuR8OwPT5v/Fdc3fyOtqn0S/w6UrUYRMfR3K+7vn+yZOnREQ81GyuDWrz4sVLNmzcponp26cbP/vOYtu2PZw/H0LnLv1wcnKgWTP18rAlShTF338Ply5dZv6C5djb5yZ3bjsA5s3xZcRPE3n+PDr9T16QPXs2Fi6ZyoC+o3j2/5st71KlakVOHDvNxvX+/HP7Lgf2HWHThu1UqPRFiussVrwwR/8+QfCZC2zasJ3nz6Mp+Hk+AMaMG8qy3/7g7p37aXuSWYAu+V6fc36mdgJq1apFo0aN3rk/e/bs1KlTJwNblPFMTU2pWPEL9u77d2lLRVHYu+9vqlWr9FF1mpgYY2JiwqtX2svovXr5ihrVqwBw4UIIRYs6kz+/EwUKfEbRooW4eDGUQoUK4uHxHT6jJ3/8SYl3mjBtHrVdqiT5gzwuLg6VCsxMTTVl5mamGBmpOH3u4jvrK1+mJMdPBXPz9h0AQq9c5/S5i9SqVjnFbSpepBAXQ6/wLOo5F0OvEBsbS4HPnDh99gKXwq7SofU3Op5l1pSIkuJNfBxDz/lpke+7dGnL2nV/8uLFSwCcnQuQN68De/f9rYmJinrOiRNnqFZVXee5c5eoUf1LLCwsaNiwDvfuhfPoUSTt2n3Lq9hY/vxTv98o/Sn5ZdpoAnYf4NCBox+MPXn8NOXKl9b80V/w8/y4NqzDX3sOprjOCxdCKVehDDa21pQrXxpLCwuuX79F1WqV+KJ8aRYtWJHkO4ZAl3yva84/dOgQTZs2xcnJCZVKxZYtW7T2K4qCj48PefPmxdLSEldXV65cuaIVExkZSYcOHbC2tsbW1hZPT0+io7U76ufOnaNWrVpYWFiQP39+Jk/W/e82eVlYJsud2w4TExMeRDzSKn/w4CElihf+qDqjo2MIDDzFyJ/6ERJ6hYiIh7Rt25xq1Spx9dpNAEJDr+I96hd27VwDwEjvSYSGqueSDh8xgYYN6+IzaiBxcfEMHOjD4b+Pp+o8Bez46wAhl6+xZsmsJPu+KF0CSwsLps9fSr+enVEUmLlgKQkJiTx6HPnOOrt934aYFy9o2r4HxkZGJCQm0reHB1+71U9xu2pUrcTXbvVp260fFubmTPQeRDZLC8ZPnceEkQNZu3k7qzdsxdbWhjFD+1KkUMGPOv9PnT4vAyc+DanN91Uql6dsmZL06DFYU+booB6li4h4qBUb8eARjv8fwVvmt4ayZUty/ux+Hj2OpF37nuTMacsYn8E0+Ko148YOpU3rb7h+/Rbdegzi3r3w1J6qSMa3Ld35olwpvqrbMkXxG9f7Y5crJ9t3r0alUmFqasqyJauZOe3fOfwfqnP/3r/ZsHYrAQc28urlK7x6DuNFzEumzBhDn17D6dKtPd1/6Mjjx08Y2HcUYaFX0+RcP3Xpme9jYmIoV64cXbt2pUWLFkn2T548mdmzZ7N8+XKcnZ0ZNWoUbm5uXLp0CQsLCwA6dOjA/fv3CQgIIC4uji5dutCjRw9Wr14NQFRUFA0bNsTV1ZWFCxdy/vx5unbtiq2tLT169EhxW6UToKc8uvRlyaJp/HPrNPHx8Zw5c541a7dQseK/w4iLFq9k0eKVms/ff9+a59HRHDsWxKULh6hW3Z18n+Vl1e/zKVLMhdevk049EilzP+Ihk2b+yuKZPyf7UJddTlumjf+J8VPnsmrDVoyMVDR2rUup4kXeu/LJrn2H8N+zn1/GDKWIc0FCr1znl1m/Yp/bjmZNvkpx+7w8O+Ll2VHzef7SVVSrXB4TExN+Xb6GzSvmc/DoCX6aMJV1S+fodvJZhD4P+Qr90KVLO86dv8TJU8E6fS8+Pp6+/UZqlS1ZPJ2585ZSvnxpvvnGjYqVv2LI4B+ZOWMcbb5L+R8RImWcPnNk4i8jadWsS7LTeJNTo+aX9B/Uk6EDxxJ06izOhQry8y8jGTT0R6ZNnp/iOif7zmGy7795e8jw3hw6cFR9k29IL2pX+5qGjeox/9fJNKiT9I9WfaRrvk/uJYXJrVQG0LhxYxo3bpxsPYqiMHPmTLy9vWnWrBkAK1aswMHBgS1bttC2bVtCQkLYtWsXJ0+epHJl9aj+nDlzaNKkCVOnTsXJyYlVq1bx+vVrli5dipmZGaVLlyY4OJjp06fr1An4pF8WZggePYokPj4ee4fcWuX29nkI/8+dHV1cv36L+q6tsLYtwueFquBS42tMTU25cf12svG5cuVk1MgB9Os/ii+/rMCVK9e5evUGBw4exdTUlGLFUvc2VkN3KewKkU+e0qZrb8rVdqdcbXdOnTnPqg1bKVfbnYSEBGpUrcSu9cs45P8Hh7evZZLPECIePiafU9531jtt3m9069iGJq51KVbYmW8aNaDTd9+yZOW6j27r9Vv/4L97H326d+LkmXNULl8Gu5y2uNWvzaWwq8TEvPjouj9liqKkeBPiY6Qm32fLZsl3bb5h2bI1WuXhEQ8AcHDIo1XuYJ+b8PAHydZVt051Spcqxrz5y6hbuzq7du3jxYuXrN+wjTq13/3Mhvh45cqXwd4+N/sObyY88hLhkZeoUasqPXp2IjzyEkZGSf8cG+7dn/Vr/uT3FesJuXSZHf4BTBw3nX4Df0ClUn1UnUWKFqL1d9/gO2EWNWp9SeCRkzx+/IQ/N++kXIUyWFkZxhuYdcn3iqIk+5JCX19fnY9748YNwsPDcXV11ZTZ2NhQtWpVAgMDAQgMDMTW1lbTAQBwdXXFyMiI48ePa2Jq166Nmdm/NxXd3NwICwvjyZP3ryr4NhkJyGRxcXGcPn2O+vVqsnXrbkC9Qkb9ejWZv2BZqut/8eIlL168xNbWhoZf1WH4iInJxk2bOpZZsxdz9+59Klcuh8lbc9NNTIxlqdBUqlapPJtXLtAq8544HeeC+fHs2Frr981pawPA8aBgIp88pV7Nau+s99WrWFRG2iMFRkZGH70GsqIojJs8m6F9upMtmyWJCYnExccD6ruJAAnvWa0oK5O5/iK9pSbft2rZFHNzM1at3qRVfuPGbe7fj6B+vZqcPat+fihHDiu+/LICCxclne9tbm7O7NkT6eTRm8TERIyMjTBVqfO9qakpxsZybzA9HD4YSM2q7lplcxZM4srl68yesSjZVeCyWVokKX+zYp9KpfqoOqfPGseoEb7ExLzA2NgY0/9f601M1X8OGhnIv7+u+T65lxQmNwrwIeHh6ql2Dg4OWuUODg6afeHh4djbay/GYWJigp2dnVaMs7Nzkjre7MuZM2eK2iOdgE/AjFmLWfbbDIJOn+PkyTP07dOd7Nkt8Vu+FoBlS2dx7959RnpPAtSJulSpYgCYmZnymZMj5cqVJjo6hmv/n/Pf8Ks6qFQqwi5fo0jhz5k0aRRhYdc0db7NtUEtihV1pkvXfgCcOnWWEsUL08itHvnyOZGQkEhYWNK15UXKZc+ejaKFPtcqs7S0wNY6h6Z88/Y9FCqYn5y2Npy9GMqkmQvp9N23OBfMp/mOZ9/hNKhdnfat1A/r1q1RlcXL15DXwZ4izgUJuXyVFWs38a17Q813nkU95374Ax48egzAjf8/RJw7V05y57LTatPGbbvIaWtD3f93PCp8UYr5S3/n7IUQDh87ReHPC2itaqRP9LNrIz41uub7N7p2acufW3cTmcy7Q2bPWcJPI/py5ep1bt78h7FjhnDvXgR//rk7Saz3yP7s2rmP4GB1h+Fo4Cl+8fXGb8VafuzVmaNHT6XDWYvo6BhCQ7Qf/nwR84LIyCea8nm/Tub+vQgmjJ0GwO5d++nl1YXz50L+Px2oAMO9+7Nn534SExNTVOfbvvdow6NHkezepV6B6/ix0wwd3odKVcrh+lUdQkOuEPXseXqc/idH13z/rqk/WZ10Aj4B69dvJU9uO8b4DMbRMQ9nz17E/euOPHigfnisQH4nrR69k5MDQSf3aD4PGtSLQYN6cfDgURp81RoAaxtrJo4fTr58eYmMfMqmzTsY5fOL5m7uGxYWFsyaNZH2HXpppjncvXuffv1HsWTxdGJjX9PVsz+vXr1K75/B4N28fYeZC/14FvWcz/I60MOjLZ2++1Yr5p+793nyLErz+acBvZizeAUTps4j8slT8uS2o3WzJvTq0l4Ts//wMbx/nq75PGS0+o+LXl07aD0H8CjyCYuWr+H3hf/Gli1VHI+2LfhxyGjsctrys3fS9an1hTwYLDKCrvkeoFixwtSsWZVGjZNfRnTK1PnqZSLnT8bW1pojR07i3rRjkjnMpUsXp1XLplSq8u/zQhs3+lOntgsH9m3i8uVrdOzUO43PWKRUvnx5tf7tp02ej6IojBjVn7x5HXj8/z/gJ46b/p5akpcnTy4GDO5Jk6/+/d/QmaBzzJ+7lD/WL+LRw0i8eg5Lk/PICjIr3zs6qt/VFBERQd68/071jYiIoHz58pqYBw+0p/LFx8cTGRmp+b6joyMREdrviXrz+U1MSqgUPZzgamL2WWY3QWSSl/cOfzhI6CXT3Kl7bqVJgSYpjt1xe0eqjiXSluR8w2VrYRhz2IW2R1GXU/V9XfI9fHzOV6lUbN68mebNmwPqKbdOTk4MHjyYQYPUN9WioqKwt7fHz89P82BwqVKlOHXqFJUqqZf53bNnD40aNeLOnTs4OTmxYMECRo4cSUREhGZK108//cSmTZsIDX3/S+jeZhiTv4QQ4gMSFCXFmxBCiKxLl3yva86Pjo4mODiY4OBgQP0wcHBwMLdv30alUtG/f38mTJjA1q1bOX/+PJ06dcLJyUnTUShZsiSNGjWie/funDhxgiNHjtC7d2/atm2Lk5MTAO3bt8fMzAxPT08uXrzI2rVrmTVrVpLnFj5EpgMJIQQyHUgIIQxFeub7U6dOUa9ePc3nN3+Ye3h44Ofnx9ChQ4mJiaFHjx48ffqUmjVrsmvXLs07AgBWrVpF7969adCgAUZGRrRs2ZLZs2dr9tvY2LBnzx68vLyoVKkSuXPnxsfHR6flQUGmAwk9I9OBDFdqpwO55ndLcexf/yR94FJkHsn5hkumAxmm1E4H0iXfg/7mfBkJEEIIkPX/hRDCQEi+V5NOgBBCIO8JEEIIQyH5Xk06AUIIgTwTIIQQhkLyvZp0AoQQAj76LctCCCGyFsn3arJEqBBCAIoOmy58fX2pUqUKOXLkwN7enubNmxMWFqYV8+rVK7y8vMiVKxdWVla0bNkyyYtgbt++jbu7O9myZcPe3p4hQ4YkefnfgQMHqFixIubm5hQpUgQ/Pz8dWyuEEPpPl3yvz90F6QQIIQTqOaIp3XRx8OBBvLy8OHbsGAEBAcTFxdGwYUNiYmI0MQMGDGDbtm2sX7+egwcPcu/ePVq0aKHZn5CQgLu7O69fv+bo0aMsX74cPz8/fHx8NDE3btzA3d2devXqERwcTP/+/enWrRu7d+vnqhZCCPGxdMn3+vz8gCwRKvSKLBFquFK7RGg1p7opjj1278BHH+fhw4fY29tz8OBBateuzbNnz8iTJw+rV6+mVatWAISGhlKyZEkCAwOpVq0aO3fu5Ouvv+bevXs4ODgAsHDhQoYNG8bDhw8xMzNj2LBhbN++nQsXLmiO1bZtW54+fcquXbs+ur1ZgeR8wyVLhBqm1C4Rqku+h9Tl/E+ZjAQIIQS63RmKjY0lKipKa4uNjU3RcZ49ewaAnZ0dAEFBQcTFxeHq6qqJKVGiBAUKFCAwMBCAwMBAypYtq+kAALi5uREVFcXFixc1MW/X8SbmTR1CCCHUZCRATToBQgiBerWIlP7H19cXGxsbrc3X1/eDx0hMTKR///7UqFGDMmXKABAeHo6ZmRm2trZasQ4ODoSHh2ti3u4AvNn/Zt/7YqKionj58uVH/SZCCKGPdMn3+rySkKwOJIQQ6PbymBEjRmheBf+Gubn5B7/n5eXFhQsX+Pvvv3VunxBCiLShhzPhP4p0AoQQAt1eHmNubp6iP/rf1rt3b/z9/Tl06BD58uXTlDs6OvL69WuePn2qNRoQERGBo6OjJubEiRNa9b1ZPejtmP+uKBQREYG1tTWWlpY6tVUIIfSZPk/x0YVMBxJCCNR3hlK66Vpv79692bx5M/v27cPZ2Vlrf6VKlTA1NWXv3r2asrCwMG7fvo2LiwsALi4unD9/ngcPHmhiAgICsLa2plSpUpqYt+t4E/OmDiGEEGq65Ht9HjWQkQAhhCD97gx5eXmxevVq/vzzT3LkyKGZw29jY4OlpSU2NjZ4enoycOBA7OzssLa2pk+fPri4uFCtWjUAGjZsSKlSpfj++++ZPHky4eHheHt74+XlpRmR6NmzJ3PnzmXo0KF07dqVffv2sW7dOrZv354u5yWEEFmVjASoSSdACCFIv9fIL1iwAIC6detqlS9btozOnTsDMGPGDIyMjGjZsiWxsbG4ubkxf/58TayxsTH+/v706tULFxcXsmfPjoeHB+PGjdPEODs7s337dgYMGMCsWbPIly8fS5Yswc3NLV3OSwghsip9fthXF/KeAKFX5D0Bhiu17wko41AtxbEXIo6l6lgibUnON1zyngDDlNr3BOiS70F/c76MBAghBJCgJGZ2E4QQQmQAyfdq0gkQQghkeFgIIQyF5Hs16QQIIQSQqH8zI4UQQiRD8r2adAKEEAK5MySEEIZC8r2adAKEEAK5MySEEIZC8r2adAKEEAK5MySEEIZC8r2adAKEEAJQZLUIIYQwCJLv1aQTIIQQyBskhRDCUEi+V5NOgBBCAHr43kQhhBDJkHyvJp0AIYRAXh4jhBCGQvK9mnQChBACWS1CCCEMheR7NekECCEEslqEEEIYCsn3atIJEEIIZI6oEEIYCsn3atIJEEIIZLUIIYQwFJLv1aQTIIQQyJ0hIYQwFJLv1aQTIIQQyINiQghhKCTfq0knQAghkDtDQghhKCTfq0knQAghkDmiQghhKCTfq0knQAghkDtDQghhKCTfq0knQAghkDdICiGEoZB8ryadACGEQB4UE0IIQyH5Xk06AUIIgQwPCyGEoZB8ryadACGEQF4jL4QQhkLyvZp0AoQQArkzJIQQhkLyvZp0AoQQArkoCCGEoZB8ryadACGEABkcFkIIAyH5Xk2lSHdIr8TGxuLr68uIESMwNzfP7OaIDCT/9kIYFvn/vOGSf3uRFqQToGeioqKwsbHh2bNnWFtbZ3ZzRAaSf3shDIv8f95wyb+9SAtGmd0AIYQQQgghRMaSToAQQgghhBAGRjoBQgghhBBCGBjpBOgZc3NzRo8eLQ8KGSD5txfCsMj/5w2X/NuLtCAPBgshhBBCCGFgZCRACCGEEEIIAyOdACGEEEIIIQyMdAKEEEIIIYQwMNIJEEIIIYQQwsBIJ0CPzJs3j88//xwLCwuqVq3KiRMnMrtJIgMcOnSIpk2b4uTkhEqlYsuWLZndJCFEBpCcb3gk34u0JJ0APbF27VoGDhzI6NGjOX36NOXKlcPNzY0HDx5kdtNEOouJiaFcuXLMmzcvs5sihMggkvMNk+R7kZZkiVA9UbVqVapUqcLcuXMBSExMJH/+/PTp04fhw4dncutERlGpVGzevJnmzZtndlOEEOlIcr6QfC9SS0YC9MDr168JCgrC1dVVU2ZkZISrqyuBgYGZ2DIhhBBpTXK+ECItSCdADzx69IiEhAQcHBy0yh0cHAgPD8+kVgkhhEgPkvOFEGlBOgFCCCGEEEIYGOkE6IHcuXNjbGxMRESEVnlERASOjo6Z1CohhBDpQXK+ECItSCdAD5iZmVGpUiX27t2rKUtMTGTv3r24uLhkYsuEEEKkNcn5Qoi0YJLZDRBpY+DAgXh4eFC5cmW+/PJLZs6cSUxMDF26dMnspol0Fh0dzdWrVzWfb9y4QXBwMHZ2dhQoUCATWyaESC+S8w2T5HuRlmSJUD0yd+5cpkyZQnh4OOXLl2f27NlUrVo1s5sl0tmBAweoV69eknIPDw/8/PwyvkFCiAwhOd/wSL4XaUk6AUIIIYQQQhgYeSZACCGEEEIIAyOdACGEEEIIIQyMdAKEEEIIIYQwMNIJEEIIIYQQwsBIJ0AIIYQQQggDI50AIYQQQgghDIx0AoQQQgghhDAw0gkQQgghhBDCwEgnQGSozp0707x5c83nunXr0r9//wxvx4EDB1CpVDx9+vSdMSqVii1btqS4zjFjxlC+fPlUtevmzZuoVCqCg4NTVY8QQnwKJOe/n+R8kZmkEyDo3LkzKpUKlUqFmZkZRYoUYdy4ccTHx6f7sTdt2sT48eNTFJuSJC6EEOL9JOcLIQBMMrsB4tPQqFEjli1bRmxsLDt27MDLywtTU1NGjBiRJPb169eYmZmlyXHt7OzSpB4hhBApJzlfCCEjAQIAc3NzHB0dKViwIL169cLV1ZWtW7cC/w7nTpw4EScnJ4oXLw7AP//8Q5s2bbC1tcXOzo5mzZpx8+ZNTZ0JCQkMHDgQW1tbcuXKxdChQ1EUReu4/x0ajo2NZdiwYeTPnx9zc3OKFCnCb7/9xs2bN6lXrx4AOXPmRKVS0blzZwASExPx9fXF2dkZS0tLypUrx4YNG7SOs2PHDooVK4alpSX16tXTamdKDRs2jGLFipEtWzYKFSrEqFGjiIuLSxL366+/kj9/frJly0abNm149uyZ1v4lS5ZQsmRJLCwsKFGiBPPnz9e5LUIIkRqS8z9Mcr7Qd9IJEMmytLTk9evXms979+4lLCyMgIAA/P39iYuLw83NjRw5cnD48GGOHDmClZUVjRo10nxv2rRp+Pn5sXTpUv7++28iIyPZvHnze4/bqVMn/vjjD2bPnk1ISAi//vorVlZW5M+fn40bNwIQFhbG/fv3mTVrFgC+vr6sWLGChQsXcvHiRQYMGEDHjh05ePAgoL5wtWjRgqZNmxIcHEy3bt0YPny4zr9Jjhw58PPz49KlS8yaNYvFixczY8YMrZirV6+ybt06tm3bxq5duzhz5gw//vijZv+qVavw8fFh4sSJhISE8PPPPzNq1CiWL1+uc3uEECKtSM5PSnK+0HuKMHgeHh5Ks2bNFEVRlMTERCUgIEAxNzdXBg8erNnv4OCgxMbGar6zcuVKpXjx4kpiYqKmLDY2VrG0tFR2796tKIqi5M2bV5k8ebJmf1xcnJIvXz7NsRRFUerUqaP069dPURRFCQsLUwAlICAg2Xbu379fAZQnT55oyl69eqVky5ZNOXr0qFasp6en0q5dO0VRFGXEiBFKqVKltPYPGzYsSV3/BSibN29+5/4pU6YolSpV0nwePXq0YmxsrNy5c0dTtnPnTsXIyEi5f/++oiiKUrhwYWX16tVa9YwfP15xcXFRFEVRbty4oQDKmTNn3nlcIYRIDcn5yZOcLwyNPBMgAPD398fKyoq4uDgSExNp3749Y8aM0ewvW7as1pzQs2fPcvXqVXLkyKFVz6tXr7h27RrPnj3j/v37VK1aVbPPxMSEypUrJxkefiM4OBhjY2Pq1KmT4nZfvXqVFy9e8NVXX2mVv379mgoVKgAQEhKi1Q4AFxeXFB/jjbVr1zJ79myuXbtGdHQ08fHxWFtba8UUKFCAzz77TOs4iYmJhIWFkSNHDq5du4anpyfdu3fXxMTHx2NjY6Nze4QQ4mNJzv8wyflC30knQABQr149FixYgJmZGU5OTpiYaP9PI3v27Fqfo6OjqVSpEqtWrUpSV548eT6qDZaWljp/Jzo6GoDt27drJWJQz3lNK4GBgXTo0IGxY8fi5uaGjY0Na9asYdq0aTq3dfHixUkuUMbGxmnWViGE+BDJ+e8nOV8YAukECECd8IsUKZLi+IoVK7J27Vrs7e2T3Bl5I2/evBw/fpzatWsD6rsfQUFBVKxYMdn4smXLkpiYyMGDB3F1dU2y/81dqYSEBE1ZqVKlMDc35/bt2++8m1SyZEnNA29vHDt27MMn+ZajR49SsGBBRo4cqSm7detWkrjbt29z7949nJycNMcxMjKiePHiODg44OTkxPXr1+nQoYNOxxdCiLQkOf/9JOcLQyAPBouP0qFDB3Lnzk2zZs04fPgwN27c4MCBA/Tt25c7d+4A0K9fPyZNmsSWLVsIDQ3lxx9/fO96z59//jkeHh507dqVLVu2aOpct24dAAULFkSlUuHv78/Dhw+Jjo4mR44cDB48mAEDBrB8+XKuXbvG6dOnmTNnjubBq549e3LlyhWGDBlCWFgYq1evxs/PT6fzLVq0KLdv32bNmjVcu3aN2bNnJ/vAm4WFBR4eHpw9e5bDhw/Tt29f2rRpg6OjIwBjx47F19eX2bNnc/nyZc6fP8+yZcuYPn26Tu0RQoiMJDlfcr7QQ5n9UILIfG8/JKbL/vv37yudOnVScufOrZibmyuFChVSunfvrjx79kxRFPVDYf369VOsra0VW1tbZeDAgUqnTp3e+ZCYoijKy5cvlQEDBih58+ZVzMzMlCJFiihLly7V7B83bpzi6OioqFQqxcPDQ1EU9YNtM2fOVIoXL66YmpoqefLkUdzc3JSDBw9qvrdt2zalSJEiirm5uVKrVi1l6dKlOj8kNmTIECVXrlyKlZWV8t133ykzZsxQbGxsNPtHjx6tlCtXTpk/f77i5OSkWFhYKK1atVIiIyO16l21apVSvnx5xczMTMmZM6dSu3ZtZdOmTYqiyENiQoj0Jzk/eZLzhaFRKco7ntgRQgghhBBC6CWZDiSEEEIIIYSBkU6AEEIIIYQQBkY6AUIIIYQQQhgY6QQIIYQQQghhYKQTIIQQQgghhIGRToAQQgghhBAGRjoBQgghhBBCGBjpBAghhBBCCGFgpBMghBBCCCGEgZFOgBBCCCGEEAZGOgFCCCGEEEIYmP8BBcMl9nqZF6YAAAAASUVORK5CYII=\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[1mModel performance:\u001b[0m\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7fe22e22d690>"
            ],
            "text/html": [
              "<style type=\"text/css\">\n",
              "#T_9d250 th {\n",
              "  max-width: 75px;\n",
              "}\n",
              "</style>\n",
              "<table id=\"T_9d250\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th class=\"blank level0\" >&nbsp;</th>\n",
              "      <th id=\"T_9d250_level0_col0\" class=\"col_heading level0 col0\" >Accuracy</th>\n",
              "      <th id=\"T_9d250_level0_col1\" class=\"col_heading level0 col1\" >Precision</th>\n",
              "      <th id=\"T_9d250_level0_col2\" class=\"col_heading level0 col2\" >Recall</th>\n",
              "      <th id=\"T_9d250_level0_col3\" class=\"col_heading level0 col3\" >NPV</th>\n",
              "      <th id=\"T_9d250_level0_col4\" class=\"col_heading level0 col4\" >Specificity</th>\n",
              "      <th id=\"T_9d250_level0_col5\" class=\"col_heading level0 col5\" >F1</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th id=\"T_9d250_level0_row0\" class=\"row_heading level0 row0\" >Training</th>\n",
              "      <td id=\"T_9d250_row0_col0\" class=\"data row0 col0\" >99.78%</td>\n",
              "      <td id=\"T_9d250_row0_col1\" class=\"data row0 col1\" >99.94%</td>\n",
              "      <td id=\"T_9d250_row0_col2\" class=\"data row0 col2\" >99.63%</td>\n",
              "      <td id=\"T_9d250_row0_col3\" class=\"data row0 col3\" >99.63%</td>\n",
              "      <td id=\"T_9d250_row0_col4\" class=\"data row0 col4\" >99.94%</td>\n",
              "      <td id=\"T_9d250_row0_col5\" class=\"data row0 col5\" >99.78%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_9d250_level0_row1\" class=\"row_heading level0 row1\" >Validation</th>\n",
              "      <td id=\"T_9d250_row1_col0\" class=\"data row1 col0\" >98.86%</td>\n",
              "      <td id=\"T_9d250_row1_col1\" class=\"data row1 col1\" >91.67%</td>\n",
              "      <td id=\"T_9d250_row1_col2\" class=\"data row1 col2\" >87.36%</td>\n",
              "      <td id=\"T_9d250_row1_col3\" class=\"data row1 col3\" >99.26%</td>\n",
              "      <td id=\"T_9d250_row1_col4\" class=\"data row1 col4\" >99.53%</td>\n",
              "      <td id=\"T_9d250_row1_col5\" class=\"data row1 col5\" >89.46%</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "\u001b[2;37;42mGradientBoostingClassifier:                                                                           \u001b[0m\n",
            "\tBest parameters are:\n",
            "\t\tsubsample: 0.5\n",
            "\t\tn_estimators: 125\n",
            "\t\tmax_features: 0.5\n",
            "\t\tlearning_rate: 1\n",
            "\tCV score=0.95786\n",
            "\tIteration duration: 615.83 seconds\n",
            "-----------------------------------------------------------------------------------------------------\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 900x300 with 4 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[1mModel performance:\u001b[0m\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7fe22f6643d0>"
            ],
            "text/html": [
              "<style type=\"text/css\">\n",
              "#T_76f0b th {\n",
              "  max-width: 75px;\n",
              "}\n",
              "</style>\n",
              "<table id=\"T_76f0b\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th class=\"blank level0\" >&nbsp;</th>\n",
              "      <th id=\"T_76f0b_level0_col0\" class=\"col_heading level0 col0\" >Accuracy</th>\n",
              "      <th id=\"T_76f0b_level0_col1\" class=\"col_heading level0 col1\" >Precision</th>\n",
              "      <th id=\"T_76f0b_level0_col2\" class=\"col_heading level0 col2\" >Recall</th>\n",
              "      <th id=\"T_76f0b_level0_col3\" class=\"col_heading level0 col3\" >NPV</th>\n",
              "      <th id=\"T_76f0b_level0_col4\" class=\"col_heading level0 col4\" >Specificity</th>\n",
              "      <th id=\"T_76f0b_level0_col5\" class=\"col_heading level0 col5\" >F1</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th id=\"T_76f0b_level0_row0\" class=\"row_heading level0 row0\" >Training</th>\n",
              "      <td id=\"T_76f0b_row0_col0\" class=\"data row0 col0\" >97.31%</td>\n",
              "      <td id=\"T_76f0b_row0_col1\" class=\"data row0 col1\" >97.48%</td>\n",
              "      <td id=\"T_76f0b_row0_col2\" class=\"data row0 col2\" >97.13%</td>\n",
              "      <td id=\"T_76f0b_row0_col3\" class=\"data row0 col3\" >97.14%</td>\n",
              "      <td id=\"T_76f0b_row0_col4\" class=\"data row0 col4\" >97.49%</td>\n",
              "      <td id=\"T_76f0b_row0_col5\" class=\"data row0 col5\" >97.31%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_76f0b_level0_row1\" class=\"row_heading level0 row1\" >Validation</th>\n",
              "      <td id=\"T_76f0b_row1_col0\" class=\"data row1 col0\" >94.54%</td>\n",
              "      <td id=\"T_76f0b_row1_col1\" class=\"data row1 col1\" >50.42%</td>\n",
              "      <td id=\"T_76f0b_row1_col2\" class=\"data row1 col2\" >86.64%</td>\n",
              "      <td id=\"T_76f0b_row1_col3\" class=\"data row1 col3\" >99.18%</td>\n",
              "      <td id=\"T_76f0b_row1_col4\" class=\"data row1 col4\" >95.00%</td>\n",
              "      <td id=\"T_76f0b_row1_col5\" class=\"data row1 col5\" >63.75%</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "\u001b[2;37;42mXGBClassifier:                                                                                        \u001b[0m\n",
            "\tBest parameters are:\n",
            "\t\tsubsample: 0.8\n",
            "\t\tscale_pos_weight: 10\n",
            "\t\tn_estimators: 250\n",
            "\t\tlearning_rate: 0.1\n",
            "\t\tgamma: 0\n",
            "\tCV score=0.99626\n",
            "\tIteration duration: 1767.25 seconds\n",
            "-----------------------------------------------------------------------------------------------------\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 900x300 with 4 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[1mModel performance:\u001b[0m\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7fe23170c820>"
            ],
            "text/html": [
              "<style type=\"text/css\">\n",
              "#T_2d79d th {\n",
              "  max-width: 75px;\n",
              "}\n",
              "</style>\n",
              "<table id=\"T_2d79d\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th class=\"blank level0\" >&nbsp;</th>\n",
              "      <th id=\"T_2d79d_level0_col0\" class=\"col_heading level0 col0\" >Accuracy</th>\n",
              "      <th id=\"T_2d79d_level0_col1\" class=\"col_heading level0 col1\" >Precision</th>\n",
              "      <th id=\"T_2d79d_level0_col2\" class=\"col_heading level0 col2\" >Recall</th>\n",
              "      <th id=\"T_2d79d_level0_col3\" class=\"col_heading level0 col3\" >NPV</th>\n",
              "      <th id=\"T_2d79d_level0_col4\" class=\"col_heading level0 col4\" >Specificity</th>\n",
              "      <th id=\"T_2d79d_level0_col5\" class=\"col_heading level0 col5\" >F1</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th id=\"T_2d79d_level0_row0\" class=\"row_heading level0 row0\" >Training</th>\n",
              "      <td id=\"T_2d79d_row0_col0\" class=\"data row0 col0\" >99.94%</td>\n",
              "      <td id=\"T_2d79d_row0_col1\" class=\"data row0 col1\" >99.88%</td>\n",
              "      <td id=\"T_2d79d_row0_col2\" class=\"data row0 col2\" >100.00%</td>\n",
              "      <td id=\"T_2d79d_row0_col3\" class=\"data row0 col3\" >100.00%</td>\n",
              "      <td id=\"T_2d79d_row0_col4\" class=\"data row0 col4\" >99.88%</td>\n",
              "      <td id=\"T_2d79d_row0_col5\" class=\"data row0 col5\" >99.94%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_2d79d_level0_row1\" class=\"row_heading level0 row1\" >Validation</th>\n",
              "      <td id=\"T_2d79d_row1_col0\" class=\"data row1 col0\" >97.98%</td>\n",
              "      <td id=\"T_2d79d_row1_col1\" class=\"data row1 col1\" >77.33%</td>\n",
              "      <td id=\"T_2d79d_row1_col2\" class=\"data row1 col2\" >89.89%</td>\n",
              "      <td id=\"T_2d79d_row1_col3\" class=\"data row1 col3\" >99.40%</td>\n",
              "      <td id=\"T_2d79d_row1_col4\" class=\"data row1 col4\" >98.45%</td>\n",
              "      <td id=\"T_2d79d_row1_col5\" class=\"data row1 col5\" >83.14%</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n"
            ]
          },
          "metadata": {}
        }
      ],
      "source": [
        "res_tuned_over = cv_tuned(models_tuned_grid, X_train_over, y_train_over, X_valid, y_valid, 'oversampled')"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "HtPIiIS7hKyr"
      },
      "source": [
        "### Tuning RF, GBM, and XGB models using the undersampled dataset"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 64,
      "metadata": {
        "id": "5pbdykhHhKyr",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "fdb69397-a6f5-4fe7-82b6-57adfc7c4535"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "\u001b[2;37;42mRandomForestClassifier:                                                                               \u001b[0m\n",
            "\tBest parameters are:\n",
            "\t\tn_estimators: 300\n",
            "\t\tmin_samples_leaf: 2\n",
            "\t\tmax_samples: 0.4\n",
            "\t\tmax_features: sqrt\n",
            "\tCV score=0.89676\n",
            "\tIteration duration: 25.02 seconds\n",
            "-----------------------------------------------------------------------------------------------------\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 900x300 with 4 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[1mModel performance:\u001b[0m\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7fe22e6b1750>"
            ],
            "text/html": [
              "<style type=\"text/css\">\n",
              "#T_f6367 th {\n",
              "  max-width: 75px;\n",
              "}\n",
              "</style>\n",
              "<table id=\"T_f6367\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th class=\"blank level0\" >&nbsp;</th>\n",
              "      <th id=\"T_f6367_level0_col0\" class=\"col_heading level0 col0\" >Accuracy</th>\n",
              "      <th id=\"T_f6367_level0_col1\" class=\"col_heading level0 col1\" >Precision</th>\n",
              "      <th id=\"T_f6367_level0_col2\" class=\"col_heading level0 col2\" >Recall</th>\n",
              "      <th id=\"T_f6367_level0_col3\" class=\"col_heading level0 col3\" >NPV</th>\n",
              "      <th id=\"T_f6367_level0_col4\" class=\"col_heading level0 col4\" >Specificity</th>\n",
              "      <th id=\"T_f6367_level0_col5\" class=\"col_heading level0 col5\" >F1</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th id=\"T_f6367_level0_row0\" class=\"row_heading level0 row0\" >Training</th>\n",
              "      <td id=\"T_f6367_row0_col0\" class=\"data row0 col0\" >96.04%</td>\n",
              "      <td id=\"T_f6367_row0_col1\" class=\"data row0 col1\" >98.85%</td>\n",
              "      <td id=\"T_f6367_row0_col2\" class=\"data row0 col2\" >93.16%</td>\n",
              "      <td id=\"T_f6367_row0_col3\" class=\"data row0 col3\" >93.53%</td>\n",
              "      <td id=\"T_f6367_row0_col4\" class=\"data row0 col4\" >98.92%</td>\n",
              "      <td id=\"T_f6367_row0_col5\" class=\"data row0 col5\" >95.92%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_f6367_level0_row1\" class=\"row_heading level0 row1\" >Validation</th>\n",
              "      <td id=\"T_f6367_row1_col0\" class=\"data row1 col0\" >93.82%</td>\n",
              "      <td id=\"T_f6367_row1_col1\" class=\"data row1 col1\" >46.99%</td>\n",
              "      <td id=\"T_f6367_row1_col2\" class=\"data row1 col2\" >90.25%</td>\n",
              "      <td id=\"T_f6367_row1_col3\" class=\"data row1 col3\" >99.40%</td>\n",
              "      <td id=\"T_f6367_row1_col4\" class=\"data row1 col4\" >94.03%</td>\n",
              "      <td id=\"T_f6367_row1_col5\" class=\"data row1 col5\" >61.80%</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "\u001b[2;37;42mGradientBoostingClassifier:                                                                           \u001b[0m\n",
            "\tBest parameters are:\n",
            "\t\tsubsample: 0.5\n",
            "\t\tn_estimators: 100\n",
            "\t\tmax_features: 0.5\n",
            "\t\tlearning_rate: 0.2\n",
            "\tCV score=0.90036\n",
            "\tIteration duration: 32.66 seconds\n",
            "-----------------------------------------------------------------------------------------------------\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 900x300 with 4 Axes>"
            ],
            "image/png": 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bb+natSuTJk3SKvPDDz/Qv39/evXqRalSpTh27BijRo3SKtO0aVPq1q1LjRo1yJo1a4LDlFpaWrJ7927CwsIoX748zZo1o2bNmsybN0+3L+MDLVu2ZNSoUQwZMoSyZcty584devbsqVVm2bJlPHv2jDJlytC+fXv69OmDg4ODVpkZM2bg6+tLzpw5KV26NPD5+0jGjBnZvHkz33//PUWKFGHRokX8+eefFCtWDIAJEyYwatQoPD09KVKkCHXr1mXHjh2a+0H27NkZN24cw4YNw9HRkV69eiXpuxACQKWkxkvXQqSAuLg4ihQpQosWLZgwYUJaV0cIIYQQ4qshrwOJr8adO3fYs2cP1apVIyoqinnz5nHr1i3atGmT1lUTQgghhPiqyOtA4qthZGSEt7c35cuXp1KlSly4cIF///1X8469EEIIIYRIHHkdSAghhBBCCAMjLQFCCCGEEEIYGEkChBBCCCGEMDCSBAghhBBCCGFgJAkQQgghhBDCwOjlEKHRT26mdRVEGrFwrpLWVRBpJObtgyTtr0vcyJAl7+cLiVQjMd9w5SsokygaorthF5K0v64xQ19jvl4mAUIIobO42LSugRBCiNQg8R6QJEAIIdRiY9K6BkIIIVKDxHtAkgAhhABAUeLSugpCCCFSgcR7NekYLIQQAHFxiV90EBsby6hRo3BxccHCwoJ8+fIxYcIE3p+nUVEURo8eTbZs2bCwsKBWrVpcu3ZN6zhhYWG0bdsWW1tbMmbMSJcuXYiIiEiWSxdCCIOiS7zXMeZ/TSQJEEIIACUu8YsOpkyZwsKFC5k3bx6BgYFMmTKFqVOnMnfuXE2ZqVOn4uXlxaJFizhx4gRWVla4ubkRGRmpKdO2bVsuXbqEr68vPj4+HDp0iO7duyfb5QshhMHQJd7rcauBSnn/cZSekJEiDJeMDmS4kjo60Ns7ZxJd1jR3mUSXbdiwIY6OjixbtkyzrmnTplhYWPDHH3+gKArOzs4MHDiQQYMGAfDixQscHR3x9vamVatWBAYGUrRoUU6dOkW5cuUA2LVrF/Xr1+f+/fs4Ozsnuj76SGK+4ZLRgQxTUkcH0iXeg24x/2siLQFCCAE6PRWKiooiPDxca4mKikrwsN999x179+7l6tWrAJw7d44jR45Qr149AG7dukVwcDC1atXS7GNnZ0eFChXw8/MDwM/Pj4wZM2oSAIBatWphZGTEiRMnUuobEUII/SQtAYAkAUIIoabD+6Genp7Y2dlpLZ6engkedtiwYbRq1YrChQuTIUMGSpcuTb9+/Wjbti0AwcHBADg6Omrt5+joqNkWHByMg4OD1nYTExPs7e01ZYQQQiSS9AkAZHQgIYQAdBstYvjw4QwYMEBrnZmZWYJlN2zYwJo1a1i7di3FihUjICCAfv364ezsjLu7e5LqLIQQQncyOpCaJAFCCAE6Pe0xMzP76I/+Dw0ePFjTGgBQokQJ7ty5g6enJ+7u7jg5OQEQEhJCtmzZNPuFhIRQqlQpAJycnAgNDdU6bkxMDGFhYZr9hRBCJJIeP93XhbwOJIQQALHRiV908Pr1a4yMtEOtsbExcf+/Cbm4uODk5MTevXs128PDwzlx4gSurq4AuLq68vz5c/z9/TVl9u3bR1xcHBUqVPjSKxZCCMOkS7zXMeZ/TaQlQAghIMU6fzVq1IhJkyaRK1cuihUrxtmzZ5k5cyadO3cGQKVS0a9fPyZOnEiBAgVwcXFh1KhRODs706RJEwCKFClC3bp16datG4sWLSI6OppevXrRqlUrgx8ZSAghdCavAwGSBAghhFoKNQ/PnTuXUaNG8csvvxAaGoqzszM///wzo0eP1pQZMmQIr169onv37jx//pzKlSuza9cuzM3NNWXWrFlDr169qFmzJkZGRjRt2hQvL68UqbMQQug1eR0IkHkChJ6ReQIMV1LnCYi66JvosmbFayfpXCJ5Scw3XDJPgGFK6jwBusR70N+YLy0BQggB8mRICCEMhcR7QDoGCyEEAIoSm+hFCCHE10uXeJ+UmD958mRNv693IiMj8fDwIHPmzFhbW9O0aVNCQkK09rt79y4NGjTA0tISBwcHBg8eTExMjFaZAwcOUKZMGczMzMifPz/e3t4610+SACGEAJk9UgghDEUqzBh86tQpFi9ezDfffKO1vn///mzfvp2//vqLgwcP8vDhQ3766SfN9tjYWBo0aMDbt285duwYK1euxNvbW6sf2a1bt2jQoAE1atTQzD3TtWtXdu/erVMdJQkQQgiQ2SOFEMJQpPCMwREREbRt25YlS5aQKVMmzfoXL16wbNkyZs6cyffff0/ZsmVZsWIFx44d4/jx4wDs2bOHy5cv88cff1CqVCnq1avHhAkTmD9/Pm/fvgVg0aJFuLi4MGPGDIoUKUKvXr1o1qwZs2bN0qmekgQIIQRIS4AQQhgKHVsCoqKiCA8P11qioqI+engPDw8aNGhArVq1tNb7+/sTHR2ttb5w4cLkypULPz8/APz8/ChRogSOjo6aMm5uboSHh3Pp0iVNmQ+P7ebmpjlGYkkSIIQQIBPHCCGEodBxsjBPT0/s7Oy0Fk9PzwQPvW7dOs6cOZPg9uDgYExNTcmYMaPWekdHR4KDgzVl3k8A3m1/t+1TZcLDw3nz5k2ivwYZHUgIIUBe8xFCCEOhY7wfPnw4AwYM0FpnZmYWr9y9e/fo27cvvr6+WvO8pFfSEiCEECCvAwkhhKHQ8XUgMzMzbG1ttZaEkgB/f39CQ0MpU6YMJiYmmJiYcPDgQby8vDAxMcHR0ZG3b9/y/Plzrf1CQkJwcnICwMnJKd5oQe8+f66Mra0tFhYWif4aJAkQQgiQjsFCCGEoUqhjcM2aNblw4QIBAQGapVy5crRt21bz5wwZMrB3717NPkFBQdy9exdXV1cAXF1duXDhAqGhoZoyvr6+2NraUrRoUU2Z94/xrsy7YySWvA4khBAgP+6FEMJQpFC8t7GxoXjx4lrrrKysyJw5s2Z9ly5dGDBgAPb29tja2tK7d29cXV2pWLEiAHXq1KFo0aK0b9+eqVOnEhwczMiRI/Hw8NC0PvTo0YN58+YxZMgQOnfuzL59+9iwYQM7duzQqb6SBAghBMgkYEIIYSDSMt7PmjULIyMjmjZtSlRUFG5ubixYsECz3djYGB8fH3r27ImrqytWVla4u7szfvx4TRkXFxd27NhB//79mTNnDjly5GDp0qW4ubnpVBeVoihKsl1ZOhH95GZaV0GkEQvnKmldBZFGYt4+SNL+bw4sT3RZi+qdk3Qukbwk5huufAUbp3UVRBq4G3YhSfvrEu9Bf2O+tAQIIQRIh18hhDAUEu8BSQKEEEJN+gQIIYRhkHgPSBIghBBqsTFpXQMhhBCpQeI9IEmAEEKoSfOwEEIYBon3gCQBQgihJs3DQghhGCTeA5IECCGEmtwUhBDCMEi8ByQJEEIINWkeFkIIwyDxHpAkQAgh1OTJkBBCGAaJ94AkAUIIoSZPhoQQwjBIvAckCRBCCDV5MiSEEIZB4j0gSYAQQqjJkyEhhDAMEu8BSQKEEEJNngwJIYRhkHgPSBIghBBqsbFpXQMhhBCpQeI9IEmAEEKoyZMhIYQwDBLvAUkChBBCTW4KQghhGCTeA5IECCGEmnQUE0IIwyDxHpAkQAgh1OTJkBBCGAaJ94AkAelebGwsC5atwWfPPp48fUbWLPY0qV+bnzu2RqVSER0Tw9zfV3LY7zT3Hz7C2sqKiuVL079HJxyyZtYc53LQdWYuWM6lK1cxMjKidvVKDOndHUtLizS8OpHchgz24LdJvzLHaykDB41J6+p8XRQlrWsgDNTS1RuYvWgF7Zo3Zli/HgmW8T1wlCWr1nPvwUNiYmLIlSM77q1/4oe6NTVlileql+C+A37pQue2zQDoNWQsV67fJOzZc2xtrKlYrjQDenbWul+ItNGuUwvad25JjlzOAFy9coM50xZx4N8jAKzfthzXyuW19vljxQZ+HThB89k5uxOTZoziu8rlefXqNRvXbWPK+DnESkdYbRLvAUkC0r1lf/zF+q07mDRyIPldcnPpylVGTpqFtbUV7Zo3JjIyistBN/i5Y2sK5c9L+MuXTJ6zmF5Dx7FhuRcAoY+f0rXvcOrWrMqIAb8Q8foVU+b8zohJM5g1aWQaX6FILuXKlqRb13acO385ravydZInQyINXAgM4q+//6FgfpdPlrOztaG7e0tccuckg4kJB4+dZNRvM8mcKSOVKpQF4MC2NVr7HD5+mtGes6ldvZJm3bdlStKtQ0uyZrEn5PFTps9bSv+Rk1izeGbyX5zQSfDDECaPm82tm3dQqVQ0a/UDS//won715ly9cgOAtSs3MsNznmafN28iNX82MjLCe/0CHoc+4ce67XFwysqsBZOIiY5h6kSvVL+edE3iPSBJQLoXcDGQGlUqUu27bwHIns2Rf3wPcuFyEAA21lYsnfOb1j6/DuhJ6679eBQcSjYnBw4eO4GJiQkjB3pgZGQEwOjBvfipwy/cvf+QXDmcU/eiRLKzsrJk1ap59Og5hF+H90nr6nyd5KYgUtnr128YNm4aY4f2ZfHKPz9Z9tsy32h9bt+iCdt2/suZc5c0SUCWzPZaZfYfPs63Zb4hZ/ZsmnUdWv2o+bOzkyNd27Wgz/DxRMfEkMFEfhKkpX93H9T6PG3SXNp3bknpct9okoA3b97wOPRpgvtX/f47ChTKS5sfu/Hk8VMuXwxixm/zGDa2P7OmLCA6OibFr+GrIfEeAKO0roD4tFLFi3DidAC3794H4Mq1m5w5f4kqFct9dJ+IiNeoVCpsbKwAePs2mgwZTDQJAIC5mRkAZ85dSsHai9Qy1+s3dv6zl737Dqd1Vb5eSlziFyGSwcQZ86nqWh7X8qV12k9RFI6fPsvtu/cpW6p4gmWehD3j0LGT/NTQ7aPHeRH+Ep89+ylVoogkAOmMkZERjX6qi4WlBWdOndOsb9KsAQHXDuF7dDNDR/XF3MJcs61M+ZJcuXyNJ4//SxIO7juGra0NBQvnT9X6p3u6xHs9jvnyrz6d69q+Ba9ev6ZRm+4YGxkRGxdHn+7uNHT7PsHyUVFvmbVwOfVrVcPaSp0EVChbimlzl7B8zUbat2jM6zeRzFq4HIDHT8NS7VpEymjR4gdKly5ORdcGaV2Vr5oSI+/MitTzz78HCLx6g3VL5yR6n5cRr/i+STui30ZjZGzEyIEefPdtmQTLbtv5L5aWFtSqVinetpkLlvHnpu28iYyiZLHCzJ827ouvQySvQkUKsHX3H5iZm/Lq1Wu6t+/HtaCbAPy96R/u33tIyKPHFClWkOFj+5M3fx5+du8PgINDFq0EAODx/z9ndcwCF1L3WtIzifdqkgSkc7v2HcJnz36mjB1CfpfcXLl2kylzFuOQxZ7G9WtrlY2OiWHgqN9QFIVRg3tp1ufPm5tJIwcyde4S5ixegZGREW2bNSazfSaMjFSpfUkiGeXI4cysGeOpW781UVFRaV2dr5seP+0R6cujkMdMnr2YJbN/w8zMNNH7WVlasMl7Pq9fv+G4fwDT5i4hh3O2eK8KAWzx2UPDOjUSPH6nNs34qaEbD4NDWbhiDcMnTGfBtHGoVHI/SGs3r9+ibrVm2NraUP+H2sxcMJEWjTpxLegma1du1JQLCrxGaMhj1v29jNx5cnDn9v00rPVXSOI9IElAujdj/jK6tmtB/VrVASiYz4VHwaEsXb1BKwl4lwA8DAlluddkTSvAOw3q1KBBnRo8CXuGpbk5qFSsWr+FHM7ZEF+vMmVK4OiYlVMndmnWmZiYUKVKRTx+6YiltQtx8u5j4sTJaBEidVwOukbYs+e06Pzfw5rY2Dj8Ay7y5+btnNm/DWNj43j7GRkZafpwFS6Yj5u377F09fp4SYB/wEVu3b3PtPHDEzx/pox2ZMpoR55cOcibJye1fuzAuUtXKFW8SDJepfgS0dEx3Ll1D4AL5y5TsnRxOv/cjuEDxscre9Zf/Wg/d95c3Ll9n9DQJ5Qso/16WNb/j/r0OORJCtf8KyPxHpAkIN2LjIxC9cHTeiMjI+LeG97qXQJw995Dls+dTEY7248eL4t9JgA2++zGzDSDzu+iivRl374jlCyt/WrY0iUzCQq6wbTp8yUB0IV8VyKVVCxbii2rF2qtGzlpJi65c9KlXfMEE4CExClxvI2Ojrd+s89uihYqQOECeT97DOX/P4bevo1/HJH2VEYqTE0Tbi0qVqIQAKHB6h/4Z06do/eAbmTOYs/TJ+pXfavUcCU8/CXXgm6kToW/FhLvAUkC0r3qlSqwZOU6sjk6kN8lN4FXr7Nq/WZ+bFAHUCcAA0ZM4vLV68yfOo64uDie/P89fztbGzJkyADA2o3bKFWiKJYW5vidOsuM+cvo17MTtjbWaXZtIukiIl5x6VKQ1rrXr17z9OmzeOvFZ8hNQaQSKytLCuTNo7XOwsKcjLY28da/s2TVeooVLkDO7Nl4Gx3NYb9T+Ozax8hBvbTKRbx6xZ79hxnUq1u8Y5y/dIWLgVcp800xbG2tuffgEXOXrCZn9myUKl44uS5PfKGho/qy/98jPLz/CCtrK5o0q49r5fK0b9aD3Hly0LhZA/b7HuZZ2HOKFCvI6ElDOH70NFcuXwXg0L5jXAu6yexFv/HbmJlkdczCoF97sWrpOknyPiTxHpAkIN37tX9P5i5ZxcTp8wl79pysWexp3rg+PTu1AdRzAOw/chyAZh09tPZdPneKppn4QuBV5i/7g9dv3uCSOyejh/TWmmRGCIMnk8eIdGTExBk8CA7Be95UAN5ERjJxxnxCQp9gZmaKS+6ceI4eTL1a1bT22/nvQRQF6teuHu+Y5uZm/HvwGPOX/cGbyEiyZranUoWy/Dxh+EefNovUkzmrPbMWTsLBMSsvw19y5dI12jfrweEDfmTL7kjlahXp0qMdFpYWPHoQzM7tvnjN+F2zf1xcHJ1aeTBpxii27v6D16/fsHHdNmZ4zk/Dq0qnJN4DoFIU/fsmop/cTOsqiDRi4Vwlrasg0kjM2wdJ2v/1zPhPTj/GcsCSJJ1LJC99jPkdPQZTvkxJPLq0S+uqpGv5CjZO6yqINHA3LGlDHekS70F/Y36atgQ8efKE5cuX4+fnR3BwMABOTk589913dOzYkaxZs6Zl9YQQhkQ6iqU4ifmJ8zLiFfcePGLBtPidQYUQyUDiPZCGk4WdOnWKggUL4uXlhZ2dHVWrVqVq1arY2dnh5eVF4cKFOX369GePExUVRXh4uNYiQyUKIXQmE8ekKIn5iWdjbcXerX9gaWmR1lURQj/JZGFAGrYE9O7dm+bNm7No0aJ4YxMrikKPHj3o3bs3fn5+nzyOp6cn48ZpT3QycnAfRg/pm+x1FkLoL5k8JmVJzBdCpBcS79XSrE+AhYUFZ8+epXDhhEckuHLlCqVLl+bNmzefPE5UVFS8p0BGLx9gZmaWbHUVXw/pE2C4kton4NWkDokuazViVZLOZYgk5ouUIH0CDFNS+wToEu9Bf2N+mrUEODk5cfLkyY/eEE6ePImjo+Nnj2NmZhYv+Ee/lUkxhBA60uMm3/RAYr4QIt2QeA+kYZ+AQYMG0b17d/r27cu2bds4ceIEJ06cYNu2bfTt25cePXowZMiQtKpeqli6egPFK9Vj8uxFmnV37z+kz/DxVGnQkgq1f2LgqN94Evbsk8ep09Sd4pXqxVsmztAeFizgYiCdew+jfM0mVKj9E+6/DCby/0/U3r59y7Dx06hQ+ycatOqK36mzWvsuX7OR32YuSKYrF+/r2cOd61ePExF+g2NHtlO+XKmPlu3SuQ0H9m3mccglHodcYvfOdZ8sP3/eZGLePqBP766adaampniv8CLsyRUuXzpMze+1W08GDujB7FkTknpZX584JfGLjh48eEC7du3InDkzFhYWlChRQuv9d0VRGD16NNmyZcPCwoJatWpx7do1rWOEhYXRtm1bbG1tyZgxI126dCEiIiLJl51aDDHmx8bGMvf3Vbg160jZGo2p27wTi1as5f0G+IRid/FK9Vi+ZmOizpHQfeQdifnpx9GAXdwNuxBvmTB1xEf3adC4DvuOb+Pqw9PsObKZGrXit3QPGO7B6cv7uPrgFGs3LyFP3lyabaamGZi98Dcu3fHjwMntVK5WUWvfn3t3ZNzkhGeV1nu6xHs97kScZi0BHh4eZMmShVmzZrFgwQJiY9XvZxkbG1O2bFm8vb1p0aJFWlUvxV0IDOKvv/+hYH4XzbrXbyLp3n8EhfLnZZnXZADmLVlNryFjWfv7LIyMEs7Z1i2dozUz7LWbd+jW71fq1PgvYARcDKTHgJF0bd+SX/v3xNjYmKDrNzH6/7u5f/29k8tB11izeBaHj59i6NgpHPT5E5VKxf2HwWzavov1y+akxFdh0Jo3/4Hp08bwi8cwTp46S5/eXflnxxqKFq/K48dP45WvVs2Vdev/xu/4aSIjIxk8yIOd/6zlm1Lf8/BhsFbZxo3rUqFCGR48eKS1vlvXtpQpU4LKVX+grlsNVq+ah3OOkgDkyZOTLl3aUqFivZS76PQqhSaPefbsGZUqVaJGjRrs3LmTrFmzcu3aNTJlyqQpM3XqVLy8vFi5ciUuLi6MGjUKNzc3Ll++jLm5OQBt27bl0aNH+Pr6Eh0dTadOnejevTtr165NkXonN0OM+cv++Iv1W3cwaeRA8rvk5tKVq4ycNAtrayvaNVe/xnJg2xqtfQ4fP81oz9nUrl7ps8dP6D7yjsT89KVRzdYYG/93Dy9UpABrtyxhx9+7Eyxf9tuSzF0yhSkT5rB390EaN2vAkj/mUL9GC64GXgegZ5/OdOrehgG/jOTenQcM+rUXf2xcTE3XxkRFvaWNe3NKlCrKj27tqF6rMl6/T6ZMoeoA5MyVndbtm9KwZqsUv/Z0SSYLA9J4iNCWLVvSsmVLoqOjefJE3ZybJUsWzSy3+ur16zcMGzeNsUP7snjln5r1Z89f4mFwKBu952FtZQXApJED+a5uc074n8O1fOkEj2efKaPW56WrN5AzezbKly6hWTd1zmLaNmtM1/b/3WRdcufQ/PnmnXvUqFyR/HlzkyO7EzPmL+PZ8xfYZ8rIhOnz6N+zk6ZOIvn079uNpcvWsnLVBgB+8RhG/Xo16dSxFVOnxZ/gpYN7b63P3X8exE8/1uf77yvzxx//PTl0dnZizqyJ1G/Yhm1btd9lLFy4AD4+e7h8+So3b95l6pTRZMliz5MnYcyf68nwXyfx8uXX84Q52aTQ054pU6aQM2dOVqxYoVnn4vLfjzZFUZg9ezYjR46kcWP1D8NVq1bh6OjI1q1badWqFYGBgezatYtTp05Rrlw5AObOnUv9+vWZPn06zs7OKVL35GZoMT/gYiA1qlSk2nffApA9myP/+B7kwuX/ZvPOktlea5/9h4/zbZlvyJk92yeP/bH7yDsS89OXsKfaLfq/9OvC7Zt3OX404RGxOv/cjoN7j7J4rjcAM36bR5XqFenYtTW/DlS31Hbp0Y65M37Hd+d+APr3/BX/oAPUafA92zfvIn9BF3x3HuDqlRvcuX2fkeMHYZ85E2FPnzFpxkg8x80i4uWrlLvo9EyPn+7rIs1eB3pfhgwZyJYtG9myZdPbm8H7Js6YT1XX8vF+1EdHR6NSgel734GZaQaMjFScOX8pUceOjo7GZ89+fmxQRzMCx9Nnzzl/OQj7THa0/XkAVRu2pqPHYM6cu6jZr1D+vJw5f4nIqCiOnvAna2Z7MmW0w2f3PsxMTalV7fNPpYRuMmTIQJky37B332HNOkVR2LvvCBUrlk3UMSwtLciQwYRnYc8161QqFStXeDFj5kIu/386+fedP3+ZSt99i7m5OXXqVOPhw2CePAmjdesfiYyK4u+/dyX52r5KOgwXp8swldu2baNcuXI0b94cBwcHSpcuzZIl/008c+vWLYKDg6lVq5ZmnZ2dHRUqVNCMlOPn50fGjBk1CQBArVq1MDIy4sSJEyn0haQcQ4n5pYoX4cTpAG7fvQ/AlWs3OXP+ElUqlkuw/JOwZxw6dpKfGrp99tgfu4+AxPz0LkMGE35s3pD1a7Z8tEyZ8iU5cvC41rpD+45Rpry61TZX7hw4OGXlyIH/yrx8GUGA/wXK/r9M4MWrlK9YGjNzM6p9X4mQR6GEPX1Gk2YNiIp8y+4d+1Lg6r4SMkQokE6SAEPyz78HCLx6g349OsXb9k2xwliYmzNzwXLeREby+k0k0+ctJTY2jidPwxJ1/L2H/HgZEUGT+rU16+7//3WQBcvX0OyHuiyeOYEiBfPTpe9w7txTj6jyY8M6FMqfl8Ztf+b3leuYMWE44S8jmLd0NcP798Tr95XUa9GZ7v1HEPJYOuElhyxZ7DExMSE0RPv7DA19jJNj4iZN8vxtBA8fhvDv3v8SiSGDPYiJiWHuvGUJ7rPCex3nzl/mwrn9DB/Wh9ZtepApU0bGjh5E336jGD9uCFcuH+EfnzU4Ozt9+QV+bXR4P9TT0xM7OzutxdPTM8HD3rx5k4ULF1KgQAF2795Nz5496dOnDytXrgTQTJr1YadYR0dHzbbg4GAcHBy0tpuYmGBvb68pI9Kfru1bUK9WNRq16U6pqg1p3qkX7Vs0oaHb9wmW37bzXywtLT77A/xT9xGQmJ/euTWoia2dDRv//PujZbI6ZOFxqPYroY9Dn5LVIYt6u2NmAJ588Nrok8f/lVm/ZguXL15lr99Weg/oxi+dB2GX0ZaBwz0YPew3Bv3am0Ond7B64yIcs2nHF70nfQKANH4dyNA8CnnM5NmLWTL7N8zMTONtt8+UkRkTfmXC9Hms2bgNIyMV9WpVp2ih/PHG1f6YzT67qVyxHA5ZM2vWxf2/E1rzxvX5sUEdAIoUzM9x/wA2++yhf89OZDAxYeRAD61jjZw0k7bNG3Pl6g32HfJj08oFLF/zF56zFjH7t5Ff+jWIZDJksActW/xAzdrNNU+hy5QuQe9eXShfoe5H94uJiaFPX+3OaEuXzGTe/OWUKlWMH35wo0y52gwe9AuzZ42nRcvuKXod6YWiwzuiw4cPZ8CAAVrrPjZEZVxcHOXKleO3334DoHTp0ly8eJFFixbh7u7+5RUW6d6ufYfw2bOfKWOHkN8lN1eu3WTKnMU4ZLGn8XsPat7Z4rOHhnVqJHh/eOdz9xGQmJ/etWz3Iwf+PUJI8OMUPU9MTAyjhkzSWjd93gRW/L6G4iWK4NagBm5Vm9GzTyfGTR5GD/cBHzmS/tEl3uszaQlIRZeDrhH27DktOveiZNUGlKzagNNnL7Bm4zZKVm1AbGwslSqUZddfKzjk8yeHd6xn8ujBhDx+Sg7nT78fCvAwOITjpwNo2kj7B2DW/79zms8ll9b6vLlzERwSmuCxTvqf4/qtO7Rp2ohTZ89TxbU8lhbm1P2+KqfOnv/Cb0C878mTMGJiYnBwzKK13sEhK8Ehn745DOj/M0MGe1CvfhsuXAjUrK9cuQIODlm4deMkka/vEPn6Dnny5GTa1NFcv3o8wWNVr/YdxYoWZP6CFVSv+h27du3j9es3/LVxO9Wqfpf0C/1axMQlejEzM8PW1lZr+VgSkC1bNooWLaq1rkiRIty9exdQD50JEBISolUmJCREs83JyYnQUO1/qzExMYSFhWnKiPRnxvxldG3Xgvq1qlMwnws/1K1Jh5Y/snT1hnhl/QMucuvufX5q9PEEHhJ3H5GYn35lz5GNytUq8ufqzZ8s9zj0CVkdMmuty+qQmceh6laZxyHqFoAsWbXLZMn6X5kPuVYuT8FC+fBe8icVK5dnv+9h3rx+g8/W3bhWKv+ll/R10iHeE6O/CYO0BKSiimVLsWX1Qq11IyfNxCV3Trq0a46xsbFmfaaMdgCc8A8g7NlzalTWHtorIVt2+GKfyY6qrt9qrc+ezRGHLJm5fee+1vo79+5TuWL8f/hRUW+ZOHM+U8YMwdjYmNi4OM2QdjExMVojEYkvFx0dzZkz5/m+RmW2bVOPEKFSqfi+RmUWLFzx0f0GDezJ8GF9qN+gLf5ntG/Of6zZpNXHAOAfnzWsWbsJ75Xxf3iYmZnh5TWJDu69iIuLw8jYiAwq9TvaGTJk0BrNQu+l0HuflSpVIigoSGvd1atXyZ07N6DuJOzk5MTevXspVaoUAOHh4Zw4cYKePXsC4OrqyvPnz/H396dsWXV/kX379hEXF0eFChVSpN4i6SIjo1AZabfiGhkZaZ7Uv2+zz26KFipA4QJ5P3nMxNxHJOanXy3aNuHp4zD27Tn0yXJnTp2jUtUKLFv0h2Zd5equnDl1DoC7d+4TGvyYStUqcPmiOr5Y21hRqmwJVq9YH+94ZmamTJw2gj7dhxEXF4exsRGq/8d6ExMTjAwp1oNev+evCwP7W09bVlaWFMibR2uxsDAno60NBfLmAWDLjj2cuxjI3fsP2b57HwNG/kaHlj9qjerQpc8w1m7cpnXsuLg4tu7wpXG9WpiYGGttU6lUdGrTlDUb/2bP/sPcvf+Qub+v4tad+/zUsE68ei7yXksV1/IUKZgfgNIlivLvwWMEXb/F2k3bKVWiaLx9xJeZNWcJXbu0oX375hQunJ/58yZjZWWB90p1EF+xfA6TJg7TlB886BfGjR1M1+4DuX3nHo6OWXF0zIqVlSUAYWHPuHQpSGuJjo4hOPgxV6/eiHf+kSP6sWvnPgIC1B3Pj/mdpkmTepQoUYRfenbk2LGER67QSyn0fmj//v05fvw4v/32G9evX2ft2rX8/vvveHioX8VQqVT069ePiRMnsm3bNi5cuECHDh1wdnamSZMmgLrloG7dunTr1o2TJ09y9OhRevXqRatWrb6akYEMUfVKFViych0Hj53kwaMQ/j14lFXrN1OzqqtWuYhXr9iz/zBNGyXcIfj9mJ+Y+4jE/PRJpVLRvE0TNq7bphki951ZCyYxdFRfzefli/+gWs1KdPPoQL4CLvQf2pNvShXDe+l/I0EtW/QHfQb+TO261SlUpACzFvxGaPBj9iTQ4bfPoJ/Z53uYSxeuAHD6RAB1G9akcNGCuHdrzekTASlz0emV9AkApCUg3bl99z6zF3nzIvwl2bM50t29FR1a/qhV5t6DRzx7Ea61zu/UWR6FhGre//xQ+5Y/EvU2milevxMe/pKC+fOyZPYkcuXQ/gFx7eZtdu87zEbv/4anrFOjMqfOnsf9l0HkyZWDqWOHJtPVir/+2kbWLPaMHT0IJ6esnDt3iQYN2xH6/+bcXDmdtZ7C/dy9A2ZmZvy1fonWccZPmMH4CTN1OnexYoVo1rQRZcv/927ypk0+VKvqyoF9m7l69QbtOvRKwtV9XZQUCvTly5dny5YtDB8+nPHjx+Pi4sLs2bNp27atpsyQIUN49eoV3bt35/nz51SuXJldu3Zp5ggAWLNmDb169aJmzZoYGRnRtGlTvLy8UqTOInn82r8nc5esYuL0+YQ9e07WLPY0b1yfnp3aaJXb+e9BFAXq166e4HESivmfIzE//alcvSI5cjonOCqQc45sxL0Xg/xPnqNP92EM+rUXQ0b25fbNO3Rr11czRwDAQq/lWFhZ4DlrDLZ2Npw+fpb2zXsQFfVW69gFi+SnYRM36lZrrlm34+89VKxUjo3/eHPz2m16dzesv+OUivcACxcuZOHChdy+fRuAYsWKMXr0aOrVU8+/ExkZycCBA1m3bh1RUVG4ubmxYMECrcEh7t69S8+ePdm/fz/W1ta4u7vj6emJicl/P9sPHDjAgAEDuHTpEjlz5mTkyJF07NhRp7qqFCWBdsmvXPSTm2ldBZFGLJzjz6goDEPM2wdJ2v9ln4aJLmvj5ZOkc4nkJTHfcOUr2DitqyDSwN2wC0naX5d4D7rF/O3bt2NsbEyBAgVQFIWVK1cybdo0zp49S7FixejZsyc7duzA29sbOzs7evXqhZGREUePHgXUM42XKlUKJycnpk2bxqNHj+jQoQPdunXTDDBx69YtihcvTo8ePejatSt79+6lX79+7NixAze3zw8x/I4kAUKvSBJguJKcBPSqn+iyNvP+SdK5RPKSmG+4JAkwTElOAnSI95D0mG9vb8+0adNo1qwZWbNmZe3atTRr1gyAK1euUKRIEfz8/KhYsSI7d+6kYcOGPHz4UNM6sGjRIoYOHcrjx48xNTVl6NCh7Nixg4sX/5v7o1WrVjx//pxduxI/14/0CRBCCJD3Q4UQwlDo2CdAlwki3xcbG8u6det49eoVrq6u+Pv7Ex0drTU5ZOHChcmVK5fW5JAlSpTQej3Izc2N8PBwLl26pCnz/jHelXl3jMSSJEAIIUCSACGEMBQ6JgG6TBAJcOHCBaytrTEzM6NHjx5s2bKFokWLEhwcjKmpKRkzZtQq/+HkkAlNHvlu26fKhIeH8+bNm0R/DdIxWAghAD18M1IIIUQCdI33ukwQCVCoUCECAgJ48eIFGzduxN3dnYMHD35RXVOSJAFCCAHyhF8IIQyFjvHezMzskz/6P2Rqakr+/Oohd8uWLcupU6eYM2cOLVu25O3btzx//lyrNeDDySFPnjypdbx3k0m+XyahCSZtbW2xsLBIdD3ldSAhhACUmLhEL0IIIb5eusT75Ij5cXFxREVFUbZsWTJkyMDevXs124KCgrh79y6urur5Q1xdXblw4YLWLPG+vr7Y2tpqZp93dXXVOsa7Mu+OkVjSEiCEECAtAUIIYShSMN4PHz6cevXqkStXLl6+fMnatWs5cOAAu3fvxs7Oji5dujBgwADs7e2xtbWld+/euLq6UrFiRQDq1KlD0aJFad++PVOnTiU4OJiRI0fi4eGhaY3o0aMH8+bNY8iQIXTu3Jl9+/axYcMGduzYoVNdJQkQQggAecAvhBCGIQXjfWhoKB06dODRo0fY2dnxzTffsHv3bmrXVk/MOWvWLM2Ej+9PFvaOsbExPj4+9OzZE1dXV6ysrHB3d2f8+PGaMi4uLuzYsYP+/fszZ84ccuTIwdKlS3WaIwBkngChZ2SeAMOV1HkCnrf9PtFlM67Zl6RzieQlMd9wyTwBhimp8wToEu9Bf2O+tAQIIQTI60BCCGEoJN4DkgQIIYSavA4khBCGQeI9IEmAEEIAoMiTISGEMAgS79UkCRBCCJAnQ0IIYSgk3gOJTAK2bduW6AP+8MMPX1wZIYRIK/JkSE3ivRBC30m8V0tUEtCkSZNEHUylUhEbG5uU+gghRJpQYtK6BumDxHshhL6TeK+WqCQgLk7aTYQQek7CHCDxXghhACTMAUnsExAZGYm5uXly1UUIIdKMIjeFT5J4L4TQFxLv1Yx03SE2NpYJEyaQPXt2rK2tuXlTPUnLqFGjWLZsWbJXUAghUkWcDouBkHgvhNBLusR7PY75OicBkyZNwtvbm6lTp2JqaqpZX7x4cZYuXZqslRNCiNSixCV+MRQS74UQ+kiXeK/PMV/nJGDVqlX8/vvvtG3bFmNjY836kiVLcuXKlWStnBBCpBa5IcQn8V4IoY8kCVDTuU/AgwcPyJ8/f7z1cXFxREdHJ0ulhBAitelzoP9SEu+FEPpI4r2azi0BRYsW5fDhw/HWb9y4kdKlSydLpYQQItUpqsQvBkLivRBCL+kS7/U45uvcEjB69Gjc3d158OABcXFxbN68maCgIFatWoWPj09K1FEIIVKcPBmKT+K9EEIfSbxX07kloHHjxmzfvp1///0XKysrRo8eTWBgINu3b6d27dopUUchhEhxcTGqRC+GQuK9EEIf6RLv9Tnmf9E8AVWqVMHX1ze56yKEEGlG0eMm36SQeC+E0DcS79W+eLKw06dPExgYCKjfGy1btmyyVUoIIVKbNA9/nMR7IYQ+kXivpnMScP/+fVq3bs3Ro0fJmDEjAM+fP+e7775j3bp15MiRI7nrKIQQKU6JkydDH5J4L4TQRxLv1XTuE9C1a1eio6MJDAwkLCyMsLAwAgMDiYuLo2vXrilRRyGESHGKkvjFUEi8F0LoI13ivT7HfJ1bAg4ePMixY8coVKiQZl2hQoWYO3cuVapUSdbKCSFEapEnQ/FJvBdC6COJ92o6JwE5c+ZMcJKY2NhYnJ2dk6VSQgiR2uSmEJ/EeyGEPpJ4r6bz60DTpk2jd+/enD59WrPu9OnT9O3bl+nTpydr5YQQIrVI03B8Eu+FEPpIXgdSUynK5y8vU6ZMqFT/ZU2vXr0iJiYGExN1Q8K7P1tZWREWFpZytU2k6Cc307oKIo1YOMsrCoYq5u2DJO1/s0SdRJfNe2FPks6Vnn1t8R4k5huyfAUbp3UVRBq4G3YhSfvrEu9Bf2N+ol4Hmj17dgpXQwgh0lZcrDQPg8R7IYT+k3ivlqgkwN3dPaXrIYQQaSpOJo8BJN4LIfSfxHu1L54sDCAyMpK3b99qrbO1tU1ShYQQIi3IDJKfJvFeCKEvJN6r6dwx+NWrV/Tq1QsHBwesrKzIlCmT1iKEEF8jJU6V6MVQSLwXQugjXeK9Psd8nZOAIUOGsG/fPhYuXIiZmRlLly5l3LhxODs7s2rVqpSooxBCpDgZKSI+ifdCCH0kowOp6fw60Pbt21m1ahXVq1enU6dOVKlShfz585M7d27WrFlD27ZtU6KeQgiRovT5ac+XkngvhNBHEu/VdG4JCAsLI2/evID6fdB3Q8RVrlyZQ4cOJW/thBAilcQpqkQvhkLivRBCH+kS7/U55uucBOTNm5dbt24BULhwYTZs2AConxhlzJgxWSsnhBCpRVFUiV4MhcR7IYQ+0iXe63PM1zkJ6NSpE+fOnQNg2LBhzJ8/H3Nzc/r378/gwYOTvYJCCJEa5P3Q+CTeCyH0kfQJUEvUjMGfcufOHfz9/cmfPz/ffPNNctUrSWT2SMMlMwYbrqTOGByQ+4dEly11Z1uSzvW1So/xHiTmGzKZMdgwJXXGYF3iPehvzE/SPAEAuXPnJnfu3MlRFyGESDNx0lHssyTeCyH0gcR7tUQlAV5eXok+YJ8+fb64MkIIkVb0ufOXLiTeCyH0ncR7tUS9DuTi4pK4g6lU3LyZ9s2yFhbypMpQvbjmk9ZVEGnENEeJJO1/KvuPiS5b/sGWJJ0rPfva4j2AiWn2tK6CSCOZLKzTugoiDTx+EZSk/XWJ96C/MT9RLQHvRocQQgh9lVpPhiZPnszw4cPp27cvs2fPBiAyMpKBAweybt06oqKicHNzY8GCBTg6Omr2u3v3Lj179mT//v1YW1vj7u6Op6cnJiZJfqtTi8R7IYS+k5YANZ1HBxJCCH2k6LB8qVOnTrF48eJ4nWr79+/P9u3b+euvvzh48CAPHz7kp59+0myPjY2lQYMGvH37lmPHjrFy5Uq8vb0ZPXp0EmojhBCGSZd4r8eDA0kSIIQQkPKThUVERNC2bVuWLFlCpkyZNOtfvHjBsmXLmDlzJt9//z1ly5ZlxYoVHDt2jOPHjwOwZ88eLl++zB9//EGpUqWoV68eEyZMYP78+bx9+zZZrl8IIQyFTBamJkmAEEKg2+QxUVFRhIeHay1RUVGfPL6HhwcNGjSgVq1aWuv9/f2Jjo7WWl+4cGFy5cqFn58fAH5+fpQoUULr9SA3NzfCw8O5dOlSMn4LQgih/2SyMDVJAoQQAojTYfH09MTOzk5r8fT0/Oix161bx5kzZxIsExwcjKmpabwZeB0dHQkODtaUeT8BeLf93TYhhBCJp0u8j0ujOqaG5O1RJoQQXymFxD/tGT58OAMGDNBaZ2ZmlmDZe/fu0bdvX3x9fTE3N09SHYUQQiSdLvFen31RS8Dhw4dp164drq6uPHignqVz9erVHDlyJFkrJ4QQqSVGUSV6MTMzw9bWVmv5WBLg7+9PaGgoZcqUwcTEBBMTEw4ePIiXlxcmJiY4Ojry9u1bnj9/rrVfSEgITk5OADg5ORESEhJv+7ttKUnivRBC3+gS72N0eB3I09OT8uXLY2Njg4ODA02aNCEoSHs408jISDw8PMicOTPW1tY0bdo0Xny/e/cuDRo0wNLSEgcHBwYPHkxMTIxWmQMHDlCmTBnMzMzInz8/3t7eOn8POicBmzZtws3NDQsLC86ePat5D/bFixf89ttvOldACCHSAwVVohdd1KxZkwsXLhAQEKBZypUrR9u2bTV/zpAhA3v37tXsExQUxN27d3F1dQXA1dWVCxcuEBoaqinj6+uLra0tRYsWTZ4vIAES74UQ+kiXeK9LzD948CAeHh4cP34cX19foqOjqVOnDq9evdKUSY7R4G7dukWDBg2oUaMGAQEB9OvXj65du7J7926dvodETRb2vtKlS9O/f386dOiAjY0N586dI2/evJw9e5Z69eqli/dTZbIwwyWThRmupE4W5uvYMtFla4esT9K5qlevTqlSpTTzBPTs2ZN//vkHb29vbG1t6d27NwDHjh0D1DeFUqVK4ezszNSpUwkODqZ9+/Z07do1RX+Mfw3xHmSyMEMmk4UZpqROFqZLvIcvj/mPHz/GwcGBgwcPUrVqVV68eEHWrFlZu3YtzZo1A+DKlSsUKVIEPz8/KlasyM6dO2nYsCEPHz7U9P1atGgRQ4cO5fHjx5iamjJ06FB27NjBxYsXNedq1aoVz58/Z9euXYmun84tAUFBQVStWjXeejs7u3jN2UII8bVIqZaAxJg1axYNGzakadOmVK1aFScnJzZv3qzZbmxsjI+PD8bGxri6utKuXTs6dOjA+PHjk70u75N4L4TQR7q2BHzJiHCgbjUFsLe3B5JvNDg/P794I825ublpjpFYOncMdnJy4vr16+TJk0dr/ZEjR8ibN6+uhxNCiHQhNUeAOHDggNZnc3Nz5s+fz/z58z+6T+7cufnnn39SuGbaJN4LIfSRrvHe09OTcePGaa0bM2YMY8eO/fg54uLo168flSpVonjx4kDyjQb3sTLh4eG8efMGCwuLRF2XzklAt27d6Nu3L8uXL0elUvHw4UP8/PwYNGgQo0aN0vVwQgiRLujzMHBfSuK9EEIf6RrvdRkR7h0PDw8uXryYrgdR0DkJGDZsGHFxcdSsWZPXr19TtWpVzMzMGDRokOY9ViGE+NrIkHHxSbwXQugjXeO9mZnZZ3/0v69Xr174+Phw6NAhcuTIoVnv5OSkGQ3u/daAD0eDO3nypNbxPhwN7mMjxtna2ia6FQC+oE+ASqVixIgRhIWFcfHiRY4fP87jx4+ZMGGCrocSQoh0I06V+MVQSLwXQugjXeK9LjFfURR69erFli1b2LdvHy4uLlrby5Ytmyyjwbm6umod412Zd8dIrC+eLMzU1DRFh6YTQojUFCctAR8l8V4IoU9SKt57eHiwdu1a/v77b2xsbDTv8NvZ2WFhYYGdnR1dunRhwIAB2Nvba0aDc3V1pWLFigDUqVOHokWL0r59e81ocCNHjsTDw0PTGtGjRw/mzZvHkCFD6Ny5M/v27WPDhg3s2LFDp/rqnATUqFEDlerjX96+fft0PaQQQqS52LSuQDok8V4IoY9SKt4vXLgQUA8D/b4VK1bQsWNHQD0anJGREU2bNiUqKgo3NzcWLFigKftuNLiePXvi6uqKlZUV7u7uWqPBubi4sGPHDvr378+cOXPIkSMHS5cuxc3NTaf66pwElCpVSutzdHQ0AQEBXLx4EXd3d10PJ4QQ6ULcJ37sGiqJ90IIfZRS8T4xU28l12hw1atX5+zZszrX8X06JwGzZs1KcP3YsWOJiIhIUmWEECKt6DRrooGQeC+E0EcS79V07hj8Me3atWP58uXJdTghhEhVcToshk7ivRDia6ZLvNfnmP/FHYM/5Ofnh7m5eXIdTgghUpUhjfqTVBLvhRBfM4n3ajonAT/99JPWZ0VRePToEadPn5bJY4QQXy0ZHSg+ifdCCH0k8V5N5yTAzs5O67ORkRGFChVi/Pjx1KlTJ9kqJoQQqUneEY1P4r0QQh9JvFfTKQmIjY2lU6dOlChRgkyZMqVUnYQQItVJ87A2ifdCCH0l8V5Np47BxsbG1KlTh+fPn6dQdYQQIm1IJzFtEu+FEPpKOgar6Tw6UPHixbl582ZK1EUIIdJMrCrxi6GQeC+E0Ee6xHt9jvk6JwETJ05k0KBB+Pj48OjRI8LDw7UWIYT4GslTofgk3gsh9JG0BKgluk/A+PHjGThwIPXr1wfghx9+0JpOXlEUVCoVsbEpNRmzEEKkHH0O9LqSeC+E0GcS79USnQSMGzeOHj16sH///pSsjxBCpAlFj5t8dSXxXgihzyTeqyU6CVAU9YBK1apVS7HKCCFEWpEnQ/+ReC+E0GcS79V0GiL0/eZgIYTQJ3JT0CbxXgihryTeq+mUBBQsWPCzN4awsLAkVUgIIdKCTB6jTeK9EEJfSbxX0ykJGDduXLwZJIUQQh/I5DHaJN4LIfSVxHs1nZKAVq1a4eDgkFJ1EUKINCPNw9ok3gsh9JXEe7VEJwHyfqgQQp/JTeE/Eu+FEPpM4r2azqMDCSGEPtLnWSF1JfFeCKHPJN6rJToJiIuTvEkIob8kwv1H4r0QQp9JhFPTqU+AEELoK3n2LYQQhkHivZokAUIIAcTJbUEIIQyCxHs1SQKEEAJpHhZCCEMh8V5NkgAhhECah4UQwlBIvFeTJEAIIZAnQ0IIYSgk3qtJEiCEEMgMkkIIYSgk3qtJEiCEEEhHMSGEMBQS79WM0roCQneDBv3CkSPbCA29xJ07/mzY8DsFCuTVKtO5c2t2715HSMhF3ry5g52dbRrVVnyp2NhY5q74k7ptf6FcvTbUa+fBotV/aU3k9O/h43QfMp7KTTpSomYzrly/pXWMF+Ev+W3uMhq596FcvTbUbt0Dz3nLeBnxKrUvJ92L1WERIrUMHdILv2M7ePY0iIf3z7Fp4zIKFsynVWbB/CkEBR7l5YvrPHpwns2bllOoUL6PHFGkV30HdGfP/o3cun+Gy9ePsXLNfPLld9Eqs9VnFY9fBGkt02aNS/B4mTJl5Nzlgzx+EYStnU1qXMJXQ5d4r88xX5KAr1CVKhVYtGgV1ao1oWHDdpiYZMDHZzWWlhaaMpaWFvj6HmTatPlpWFORFMvXbWXDtj382rsLf6+YTf9u7Vix/m/WbvlHU+ZNZBSlixehf7d2CR4j9OkzHj8NY+DPHdiybCYTh3hw9GQAY6YvTK3L+GrEoSR6ESK1VK1SkYULV1KpSiPq1m9NBpMM7NyxVivenzlznq7dBlD8m+rUb9AGlUrFzh1/YmQkt/ivyXeVvmX5kjXUrdWC5k06kSGDCX9tWab1dw2wyns9xQpU0izjRk9N8Hiz503i8qWg1Kj6V0eXeK/PMV9eB/oKNW7srvW5e/eB3Lt3ltKlS3D06EkA5s1bDkCVKhVTvX4ieQRcCqLGd+WpWrEsANmdHNi5/wgXrlzXlGlUuxoAD4JDEzxGAZdczBo7WPM5p7MTvbu0ZrinFzGxsZgYG6fgFXxd9DfMi69Zg0baCX7nrv0IfniBsmW+4fCREwAsXbZGs/3OnfuMHjOVs/7/kidPTm7evJOq9RVfrmXTrlqfe/ccxpWbxylZqhh+x05r1r95HUlo6JNPHqtjl9bY2dkwfeoCatWpliL1/ZpJvFeTxwR6wNZW3cz37NnztK2ISFalihXixNkL3L73EICgG7c5c+EKlb8tnaTjRkS8xtrSUhKAD8TpsAiRVt692hn2kXhvaWlBxw4tuXnzDvf+HzvE1+ndKzzPnr3QWt+0RSOu3DzOIb/tjBwzAAsLc63tBQvlY9CQX/DoMZS4OIlYCdEl3uvzNygtAV85lUrFtGljOHbsFJcvX03r6ohk1KX1j0S8fsMPnfpibGREbFwcfTq3pmGtql98zGcvwln8x0aaNaiVjDXVD/rc5Cv0g0qlYub0cRw9epJLH7zm0eNndyZ7jsDa2oorQdepW7810dHRaVRTkVQqlYqJnr9yws+fK4HXNOs3bfTh/r2HBD8KpWixQoweN4h8BVzo1K43AKamGVi8bCZjR03jwf1H5M6TM60uIV2TeK8mScBXbvbsCRQrVpCaNZuldVVEMtt94Bg79h5myq99yZcnJ0E3bjNl/gqyZransVt1nY8X8eo1Hr/+Rt7cOejp3iL5K/yVk1uCSO/mev1GsWKFqFbjx3jb1v65mX/3HiKbkwMDBvTgz7WLqFqtCVFRUWlQU5FUU2aMoXCRAjSs20Zr/WrvDZo/B16+SkjIY7ZsX0kel5zcvnWPkWMGcu3qDTZu2JbaVf6qSLxXkyTgKzZr1njq169JrVotePAgOK2rI5LZjN9X06VVE+p9XxmAgnlz8zDkMUv/3KxzEvDq9Rt6DJuIpaUFc8YPIYOJ/NP/kD43+Yqv35zZE2lQvxY1av7EgweP4m0PD39JePhLrl+/xfETZ3gSepkmTeqyfv3faVBbkRSTp42ijlt1fqjfjkcPQz5Z9szpcwC45M3N7Vv3qFK1IkWKFaRRYzdA3aIAEHTzOLOmL2Kq59yUrfxXQuK9mvwS+ErNmjWeH35wo06dlty5cy+tqyNSQGRkVLzRPYyNjFDidHuGEfHqNT8PnYipqQlzJwzDzNQ0OaupNxR5NiTSqTmzJ9KkcV1q1m7O7dufj/cqlQqVSoWZqVkq1E4kp8nTRlG/YW2aNGjP3Tv3P1u+eIkiAIQEPwagU4femJv/10egdJkSeC3wpFHdtty+dTdlKv0VknivJknAV2j27Im0bPkDzZt3IyLiFY6OWQF48SKcyEh106+jY1YcHbOSL18eAIoXL8TLl6+4d+9BvE5GIn2q5lqO39dsIptDFvLlycmV67dYtdGHJnVraMq8CH/Jo9AnhD59BqDpRJzFPiNZ7DP9PwGYwJvIKCb/OoRXr1/z6vVrADLZ2WIsnYM15MmQSI/mev1G61ZN+KlpZ16+jHgv3r8kMjISF5dctGj+A76+B3n85Ck5sjszZIgHb95EsnPX3jSuvdDFlBljaNqsIR3a/EJExCscHLIA6laeyMgo8rjk5KdmjfjX9yDPwp5TtFghJngO59iRk5qhQG/f0k4S7TNnAuDq1RuEv3iZuheUjkm8V1Mp7888pCcsLHKndRVS1Js3CQ/51q3bQP74YyMAI0b0Y+TI/p8so49eXPNJ6yokm1ev3zBvxTr2HjlB2PNwsmbORL3vK9OzfTMyZMgAwNZd+xmVwFwQPTs05xf3lpwKuEjngWMTPP6uNQvI7uSQkpeQqkxzlEjS/j3zJL6fxMLbGz5fSKQaE9PsaV2FFBPz9kGC6zt36c+q1RvIls2R3xdNo0yZb8iUyY6QkCccPnKciZNmc/XqjVSuberLZGGd1lVINo9fJDymf++ew1i3dgvO2Z1Y+Ps0ChctgKWlJQ8fPGKHz7/MnLaAiJcJTwD5XeVv+XvHavLlKqdXScDHvqvE0iXeg/7GfEkChF7RpyRA6CapScDPeZonuuzi238l6VwieelzEiA+TZ+SAJF4SU0CdIn3oL8xX14HEkIIpHlYCCEMhcR7NUkChBAC6SgmhBCGQuK9WrqeMfjevXt07tz5k2WioqIIDw/XWvTwDSchRApLqdkjPT09KV++PDY2Njg4ONCkSROCgrSbsiMjI/Hw8CBz5sxYW1vTtGlTQkK0hwa8e/cuDRo0wNLSEgcHBwYPHkxMTMwXXWt6JTFfCJEaZMZgtXSdBISFhbFy5cpPlvH09MTOzk5riYmR0W+EELpRdPhPFwcPHsTDw4Pjx4/j6+tLdHQ0derU4dWr/zry9e/fn+3bt/PXX39x8OBBHj58yE8//aTZHhsbS4MGDXj79i3Hjh1j5cqVeHt7M3r06GS7/vTgS2O+Eqc/HR6FEClPl3ivz60GadoxeNu2T89od/PmTQYOHEhsbOxHy0RFRcWbEdHBobhmggxhWKRjsOFKasdg9zxNE1125e1NX3yex48f4+DgwMGDB6latSovXrwga9asrF27lmbN1DN/X7lyhSJFiuDn50fFihXZuXMnDRs25OHDhzg6OgKwaNEihg4dyuPHjzH9SuZ+SKmYnylzYYn5Bko6BhumpHYM1iXeQ9JifnqWpn0CmjRpgkql+mRT7ucCu5mZGWZm2hOiyM1ACKGrOB2ehyT0QzShWJSQFy/ULZX29vYA+Pv7Ex0dTa1atTRlChcuTK5cuTRJgJ+fHyVKlNAkAABubm707NmTS5cuUbp06UTXPS1JzBdCpAe6xHtdHTp0iGnTpuHv78+jR4/YsmULTZo00WxXFIUxY8awZMkSnj9/TqVKlVi4cCEFChTQlAkLC6N3795s374dIyMjmjZtypw5c7C2/i/pPX/+PB4eHpw6dYqsWbPSu3dvhgwZolNd0/R1oGzZsrF582bi4uISXM6cOZOW1UsVlSp9y8aNy7h58yRv3tyhUaM6nyzfuHFdfHz+4O7dM4SEXOTAgS3UqlU1XjlnZ0eWL5/N/fsBhIUFcerUbsqU+e9Jab9+3blzx587d/zp27eb1r7ly5fi6FEfmUgqBS39cwslajZjyvwVmnVPwp4x3NOL6s268m2DtrT4eTC+h45/8jhubXpSomazeMvEOUvilVUUhR7DJlKiZjP2HjmpWf8i/CW9RnjybYN2NP95EIHXbmrtN3HOElZu+PQTXH2g6LAk9EqKp6fnZ88RFxdHv379qFSpEsWLFwcgODgYU1NTMmbMqFXW0dGR4OBgTZn3E4B3299t+1pIzFfr2cOd61ePExF+g2NHtlO+XKlE7deixQ/EvH3Apo3L4m0rXDg/Wzav4OnjQF48u4bfsR3kzOms2T596hhCgy9y68YpWrf+UWvfpk0bsnWLd1IuSXzG4GG9ePwiSGs5dmrnJ/f5oUldjp3ayb2Q8xw8to1atbXv9VZWlkyeNopzlw9yN/gcR07swL1zK60y4ycN4+rtEwRcOkDT5o3iHf+PdQuT5wK/MrrEe13ThVevXlGyZEnmz48/hw/A1KlT8fLyYtGiRZw4cQIrKyvc3NyIjIzUlGnbti2XLl3C19cXHx8fDh06RPfu3TXbw8PDqVOnDrlz58bf359p06YxduxYfv/9d53qmqYtAWXLlsXf35/GjRsnuP1zT4z0gZWVJRcuBLJq1QbWr//8X17lyt+yb99hxoyZyvPn4XTo0JxNm5ZRtWoTzp27BEDGjLbs27eJgwf9aNLEncePw8ifP49mpuDixQszatQAfvqpMyqVis2bl/Pvv4e4dCkIY2NjvLx+o1evYZ9skhdf7uKV62z08aVgXu35LH6dPJeXEa+ZO3EoGW1t+WffYQZNmMm6BZMpUiBvgsf6c8Fk4uL+67Z07dY9ug8Zj1s113hlV2/ySfCJ6e9rNvPqzRs2LJrK+u27GTtzEesXTgXg3OWrXLhyjeG9Pt1ZUx/E6tD9a/jw4QwYMEBrXWJaATw8PLh48SJHjhzRuX76QGI+NG/+A9OnjeEXj2GcPHWWPr278s+ONRQtXpXHj59+dL/cuXMwdfJoDh+O/2Agb97cHNy/lRXefzJu/HTCwyMoWrSgZgb5hg1q06pVE+rVb0P+Ai4s/X0Ge/Yc4OnTZ9ja2jBh/FDc6rZMsWsWaoGXr9KscSfN55iYj99jy39bmsXLZjBx3Ez27NpP0+aNWLl2PjWr/sSVwGsAjP9tGFWqVqRn98Hcu/uA6t9XYuqMMQQ/CmX3zn3UqVuDps0b0vzHLuTNm5s5839j/94jhIU9w8bWml9H9aPpe/UxJLrEe13Vq1ePevXqJbhNURRmz57NyJEjNXFw1apVODo6snXrVlq1akVgYCC7du3i1KlTlCtXDoC5c+dSv359pk+fjrOzM2vWrOHt27csX74cU1NTihUrRkBAADNnztRKFj4nTVsCBg8ezHfffffR7fnz52f//v2pWKPUt2fPAcaNm862bbsTVX7w4PHMnLkYf//z3LhxmzFjpnH9+m3q16+pKTNwYE/u33/Ezz8P5vTpc9y5c4+9ew9z69ZdAAoVysfFi4EcPHiMAweOcvFiIIUK5QOgf/+fOXr0BP7+55P/YgWv37xh2G9zGDOgB7Y2VlrbAi5dpc2P9ShRuAA5nR35uV0zbKwsuXz15keOBvYZ7chin0mzHDruT05nJ8qVLKZV7sr1W6z8azsTBv8S7xg3796nXo1K5MnpTPMGtbl1Vz1DaXRMDBNm/87oft0NolVIl5EizMzMsLW11Vo+lwT06tULHx8f9u/fT44cOTTrnZycePv2Lc+fP9cqHxISgpOTk6bMh6MFvfv8rszXQGI+9O/bjaXL1rJy1QYCA6/xi8cwXr9+Q6eOrT66j5GREatXzmPc+Onc/H8cf9+E8UPZuWsfw4ZPIiDgEjdv3sHHx1eTVBQunJ+Dh/zwP3Oe9ev/Jjw8Apc8uQCY7DmSxYtXce/ew5S5YKERGxNLaOgTzRIW9uyjZbv37MC+fw8z32sZ167eZPKkOZw/d5ku3dtpypT/tjTr1m7l2JGT3Lv7gNXeG7h08Qplyn4DQMFC+Th65CTnzl5ky6YdvHwZQa486tgzZvxgViz7kwf3H6XsRadTuo4OlNCoZB++EpoYt27dIjg4WOv1Tzs7OypUqICfnx8Afn5+ZMyYUZMAANSqVQsjIyNOnDihKVO1alWt/mBubm4EBQXx7NnH/7/6UJomAVWqVKFu3bof3W5lZUW1atVSsUZfH5VKhY2NleYpP0CDBrU5c+Y8a9Ys4M4df/z8/qFTp/9uMBcvBpE/f15y5nQmV67s5M+fl0uXruLikosOHZozduz0tLgUgzBpzlKqVCyD6/+D9PtKFSvIrv1HeRH+kri4OHbuO8Lb6GjKlyqWwJHii46OxuffQ/xYt4bWE/83kVEMnTSHEX26ksU+U7z9CuXLw4mzF4mJjeXo6QAKuKhbKFas/5vyJYtRrFD+L7zar0scSqIXXSiKQq9evdiyZQv79u3DxcVFa3vZsmXJkCEDe/fu1awLCgri7t27uLqqW3RcXV25cOECoaGhmjK+vr7Y2tpStGjRJFx16jL0mJ8hQwbKlPmGvfsOa9YpisLefUeoWLHsR/cbNbI/oY+fsMJ7XbxtKpWK+vVqcu3aTf7xWcPD++c4dmQ7P/zgpilz/vxlypb5howZ7ShTugQWFuZcv3GbSt+Vp3Tp4sydF//1IpH8XPLl5sKVw5w69y8Ll0wne45sHy1brnwpDh3w01q3f+8RypUvpfl86uRZ6tb/HqdsDgBUqlKBfPlcOLBP3dJ46eIVSpUujl1GW74pVQwLc3Nu3bxDhYpl+aZkMZYsWp38F/mV0CXex6F88SugH3r3+mZCr3e+//qng4OD1nYTExPs7e2T/RXRdD1EqPi8/v27Y2VlxaZN/42K4+KSk27d2nH9+i1++KEDS5asZsaMcbRtq+4NHxR0nTFjpuLj8wfbt69m9OgpBAVdZ948T0aM8KR27WqcPr0HP79/qFTp27S6NL2zc98RLl+/Rb+ubRPcPn30QGJiY6n8YyfK1m3N+Nm/M3vcYHJl//iN4n17j57iZcQrGrvV0Fo/dYE3pYoV4vuP/F12adUEY2Nj6rfzYO+Rk4wf1JM79x+xbfcBfm7XjPGzFlO33S8MHD+DlxGvEjyGPkip4eI8PDz4448/WLt2LTY2NgQHBxMcHMybN28A9VOgLl26MGDAAPbv34+/vz+dOnXC1dWVihUrAlCnTh2KFi1K+/btOXfuHLt372bkyJF4eHgk6jUkkT5kyWKPiYkJoSFPtNaHhj7GyTFrgvtU+q48nTq25ucegxPc7uCQBRsba4YM9mD3ngPUa9CGrX/vYuOGpVStov7/Z4/vQdb+uZnjx3awbNksOnXpx6tXr5k3zxMPj2H0+LkDly4e4tCBrRQtWjB5L1oAcOb0efr8MpyWTbsyZMBYcuXOzvada7CytkqwvINjFkJDtf8/efz4KQ6OWTSfhw+ewNUr17lw5TAPn1xk/aalDB00Dr9jpwF10vDX+m347t/I3AWe9Oo5lNev3jB15hgG9R9Dpy6t8Tu9ix27/6RQYcN42POOrkOEDh8+nBcvXmgtw4cPT+vLSDKZMfgr1rJlY379tR/Nm3fVepfUyMiIM2cuMGbMNADOnbtEsWKF6NatHWvWqIe5Wrp0DUuXrtHs07ZtUyIiIjhx4gznzu2jcuUfyJ49G6tXz6Nw4cq8ffs2dS9OzwSHPmHy/BX8PnUUZh8ZznHeinW8jHjFkmmjyWRny76jJxk0fibesyfE6z+QkC0791L529I4ZLHXrNt/7BQnAy7w1+JpH93PxtqKqSP6aa3rMnAsA35uz469h7j/KITt3l6MnbGIRas3Mrine+Iu+iuTUm+ILlyo7nhXvXp1rfUrVqygY8eOAMyaNUszAkRUVBRubm4sWLBAU9bY2BgfHx969uyJq6srVlZWuLu7M378+BSqtUgPrK2t8F7hRY+eg3n6NOEmfiMj9bO8bdt3M8dLPSDAuXOXcHUtR/fu7Tn0/z4E4yfMZPyEmZr9Ro3sz769R4iOieHX4X0pVaYmDerXYsXyOVSomPD7zOLL7f33kObPly8F4X/6HGcv7KfJj/VYs3rjFx2z68/tKVu+FG1b9uD+vYe4fleOKdPHEBwcqmlFmDZ5HtMmz9PsM2ioB4cO+BETHcOAwT2p6tqIOnVrMH/xFGpV023YzK+ZrvE+saO/fc671zdDQkLIlu2/B3whISGUKlVKU+b9Vl+AmJgYwsLCkv0VUUkCvlLNmzdiwYIptG37C/v3H9XaFhwcSuD/Ow69c+XKdZo0STiwZ86ciREj+lG7dnPKly/F9eu3uHHjNjdu3MbExIQCBVy4dClpY/IauktXbxL2/AUte/w3fFdsXBz+5wP5c+tOtq/04s+tO9mybBb58+QE1K/p+F8IZN3fuxjd/+dPHv9hyGOOn7nArLGDtNafPHuRew9D+O4H7R/uA8ZNp0yJwqyYGf9H5JZd+7CxtuT7St/Sb8xUvq/0LRlMTHCr5so87/Vf+hWkeynVITUxxzU3N2f+/PkfHU0CIHfu3Pzzzz/JWTWRyp48CSMmJkbraS6Ag0NWgkMexyufL18eXFxyaY3c8+5Hf+TrOxQtXpV79x4SHR2dQMy/RqXvEm79K1QoH21aN6Xct3Xo1LEVh4+c4MmTMP7auJ1lS2dhbW1FhB63+qUH4S9ecuPGbVzy5kpwe2jIExwctP8/yZo1s6YVydzcjBGj+9OxbS989xwE1MlF8W+K4NG7S7xXiQDyF8hL85Y/8H2VH2nTril+x07z9Okz/t6yE68FnlhZW/HKQP7e02oAAhcXF5ycnNi7d6/mR394eDgnTpygZ8+egPr1z+fPn+Pv70/ZsurXBPft20dcXBwVKlTQlBkxYgTR0dFkyJABUL8iWqhQITJliv/a78dIEvAVatHiBxYtmkaHDr3YtWtfvO1+fv4ULKg9mkyBAi7c/X+Hzw9NnTqauXOX8eBBMGXLlsTEJINmm4mJiUF0Ck1pFcuUYPPSmVrrRk2bj0vO7HRu1YQ3/x/Fw+iD0XuMjYwSNZ7x1l37sM9oS9UP3ivu0roJP73XaRzgp64DGNLTnWqu5fhQ2PMXLF69kZWzJwDqROXdCBbRMbFaIxHpG13f9RdCV9HR0Zw5c57va1TWDAahUqn4vkZlFixcEa/8lSvXKVn6e61148cNwcbamv4DR2sSgNOnz1GwYD6tcgUK5OXO3fsJ1mPh/CkMHjKOV69eY2xsTIYM6p8C735MSMxPeVZWluRxyclf6+InfwCnTwVQpVpFFi/8bwbtajW+4/SpAABMMphgampKXJx23IqNjUVllPC8GTNmj2PUr5N59eo1RsZGmJiYaI4FYGxsOG+Ip2S8j4iI4Pr165rPt27dIiAgAHt7e3LlykW/fv2YOHEiBQoUwMXFhVGjRuHs7KyZS6BIkSLUrVuXbt26sWjRIqKjo+nVqxetWrXC2Vk97G+bNm0YN24cXbp0YejQoVy8eJE5c+Ywa9YsneoqSUAas7KyJF++PJrPefLk5JtvivLs2XPu3XvI+PFDcHZ2omtX9XCELVs2ZsmSGQwaNI5TpwJw/P97pG/eRBIe/hKAuXOXsn//ZgYP9mDTJh/Kly9F585t6NUr/vtr339fmQIFXDTH9/c/R6FC+ahTpzo5cmQjNjaWq1dvpPC3oP+sLC0o4KL9xMfC3IyMtjYUcMlFdEwMubI7MW7WYgb16EBGWxv2HTmJn/955k367++t66CxfF+5Am3ea9WJi4tj6679/FCnOiYf3LzfjRr0ISeHrOTI5hhv/ZQFK+jQvBGOWTMDULpYYbb/e5DvypVk4w5fShUrlKTvIT3T3/RGpCez5ixhxbJZ+J85z6lTZ+nTuxtWVhZ4r1S3sq1YPoeHDx8xYuRkoqKi4rXCPn8eDqC1fvrMhfy5ZiGHDx/nwMFjuNWpTsMGtalZq1m883fp3IbHT8Lw2eELwLFjpxg9agAVvi1D3bo1uHQ5iBcvwlPq8g3W2IlD2LNzP/fuPcTJyYEhv/YmNjaOzRvV/fnmLZpC8KMQJo5TPyz6feEq/v5nNT17dcJ390F+bFqfUqWLM7DvaAAiXr7i6OETjJkwmDeRkdy/95DvKpWnRasmjB4xOd7527k35+nTMPbsUo++dfL4GYYM603ZciWpWbsqVwKvEf7iZSp9G2kvJeP96dOnqVHjv75574aTdnd3x9vbmyFDhvDq1Su6d+/O8+fPqVy5Mrt27cLc3Fyzz5o1a+jVqxc1a9bUvCrq5eWl2W5nZ8eePXvw8PCgbNmyZMmShdGjR+s0PChIEpDmypT5hj17/nvFYupU9T/w1av/onv3QTg5OWhN+NK5c2syZMjAnDkTmTNnomb9u/IA/v7nadmyO+PHD+XXX/tw+/Z9Bg8ex7p1W7XObW5uxqxZ42nfvpemaezBg2AGDBjD4sXTePv2Ld26DdSMNS1STgYTExb8NoLZS/+g14jJvImMJKezE5OG9qJqhTKacvcehvD8gxv08TPneRT6hB/rfv/hYXVy9FQA9x4E4zmsj2Zd6yb1uHT1Bm16Dad44fz07NAiSedIz3Tt8CvEl/jrr21kzWLP2NGDcHLKyrlzl2jQsJ2mE2iunM46t7j9/fcufvEYxtAhvZk9azxBV2/SvGU3jh47pVXOwSELw4f1oUq1/+ZpOHU6gFmzF7Pt71WEPn5C5879knyNIj5nZycWL5tJJvuMPH0Sxonj/tSr1ULT1yNHjmwo7/29nzp5lh5dBzF8ZD9GjB7AzRu3cW/joZkjAKB75wGMHDOARUumkzGTHffvPeS3CbPwXvan1rmzZs1M/4E9qF+ntWbd2TMXWDBvBWv/WsyTx2H06jE0hb+B9CUl43316tU/Oyv6+PHjP9mny97enrVr137yPN988w2HDx/+ZJnPUSl6ODOLhcXnO1EK/fTims/nCwm9ZJqjxOcLfUL9XPUTXfafu/JufnpiYpo9rasg0kgmC+u0roJIA49fJK2foi7xHvQ35ktLgBBCALH69zxECCFEAiTeq0kSIIQQyOtAQghhKCTeq0kSIIQQyOhAQghhKCTeq0kSIIQQpN240UIIIVKXxHs1SQKEEAJ5MiSEEIZC4r2aJAFCCIG8IyqEEIZC4r2aJAFCCAGJmplZCCHE10/ivZokAUIIAfJcSAghDITEezVJAoQQAnlHVAghDIXEezVJAoQQAohV4tK6CkIIIVKBxHs1SQKEEAJ5MiSEEIZC4r2aJAFCCIGMFiGEEIZC4r2aJAFCCIFMHiOEEIZC4r2aJAFCCIE0DwshhKGQeK8mSYAQQiBPhoQQwlBIvFeTJEAIIZAnQ0IIYSgk3qtJEiCEEEhHMSGEMBQS79UkCRBCCGQaeSGEMBQS79UkCRBCCGTyGCGEMBQS79UkCRBCCKR5WAghDIXEezVJAoQQAmkeFkIIQyHxXk2SACGEQJ4MCSGEoZB4ryZJgBBCIE+GhBDCUEi8V5MkQAghkCdDQghhKCTeq0kSIIQQgCKjRQghhEGQeK8mSYAQQiAzSAohhKGQeK8mSYAQQgCKvCMqhBAGQeK9miQBQgiBTB4jhBCGQuK9miQBQgiBjBYhhBCGQuK9miQBQgiBjBYhhBCGQuK9miQBQgiBvCMqhBCGQuK9miQBQgiBjBYhhBCGQuK9miQBQgiBPBkSQghDIfFeTZIAIYRAOooJIYShkHivJkmAEEIgT4aEEMJQSLxXkyRACCGQd0SFEMJQSLxXkyRACCGQJ0NCCGEoJN6rSRIghBDIDJJCCGEoJN6rSRIghBBIRzEhhDAUEu/VJAkQQgikeVgIIQyFxHs1SQKEEAKZRl4IIQyFxHs1SQKEEAJ5MiSEEIZC4r2aJAFCCIHcFIQQwlBIvFeTJEAIIUAah4UQwkBIvFdTKZIO6ZWoqCg8PT0ZPnw4ZmZmaV0dkYrk714IwyL/5g2X/N2L5CBJgJ4JDw/Hzs6OFy9eYGtrm9bVEalI/u6FMCzyb95wyd+9SA5GaV0BIYQQQgghROqSJEAIIYQQQggDI0mAEEIIIYQQBkaSAD1jZmbGmDFjpKOQAZK/eyEMi/ybN1zydy+Sg3QMFkIIIYQQwsBIS4AQQgghhBAGRpIAIYQQQgghDIwkAUIIIYQQQhgYSQKEEEIIIYQwMJIE6JH58+eTJ08ezM3NqVChAidPnkzrKolUcOjQIRo1aoSzszMqlYqtW7emdZWEEKlAYr7hkXgvkpMkAXpi/fr1DBgwgDFjxnDmzBlKliyJm5sboaGhaV01kcJevXpFyZIlmT9/flpXRQiRSiTmGyaJ9yI5yRCheqJChQqUL1+eefPmARAXF0fOnDnp3bs3w4YNS+PaidSiUqnYsmULTZo0SeuqCCFSkMR8IfFeJJW0BOiBt2/f4u/vT61atTTrjIyMqFWrFn5+fmlYMyGEEMlNYr4QIjlIEqAHnjx5QmxsLI6OjlrrHR0dCQ4OTqNaCSGESAkS84UQyUGSACGEEEIIIQyMJAF6IEuWLBgbGxMSEqK1PiQkBCcnpzSqlRBCiJQgMV8IkRwkCdADpqamlC1blr1792rWxcXFsXfvXlxdXdOwZkIIIZKbxHwhRHIwSesKiOQxYMAA3N3dKVeuHN9++y2zZ8/m1atXdOrUKa2rJlJYREQE169f13y+desWAQEB2NvbkytXrjSsmRAipUjMN0wS70VykiFC9ci8efOYNm0awcHBlCpVCi8vLypUqJDW1RIp7MCBA9SoUSPeend3d7y9vVO/QkKIVCEx3/BIvBfJSZIAIYQQQgghDIz0CRBCCCGEEMLASBIghBBCCCGEgZEkQAghhBBCCAMjSYAQQgghhBAGRpIAIYQQQgghDIwkAUIIIYQQQhgYSQKEEEIIIYQwMJIECCGEEEIIYWAkCRCpqmPHjjRp0kTzuXr16vTr1y/V63HgwAFUKhXPnz//aBmVSsXWrVsTfcyxY8dSqlSpJNXr9u3bqFQqAgICknQcIYRIDyTmf5rEfJGWJAkQdOzYEZVKhUqlwtTUlPz58zN+/HhiYmJS/NybN29mwoQJiSqbmCAuhBDi0yTmCyEATNK6AiJ9qFu3LitWrCAqKop//vkHDw8PMmTIwPDhw+OVffv2LaampslyXnt7+2Q5jhBCiMSTmC+EkJYAAYCZmRlOTk7kzp2bnj17UqtWLbZt2wb815w7adIknJ2dKVSoEAD37t2jRYsWZMyYEXt7exo3bszt27c1x4yNjWXAgAFkzJiRzJkzM2TIEBRF0Trvh03DUVFRDB06lJw5c2JmZkb+/PlZtmwZt2/fpkaNGgBkypQJlUpFx44dAYiLi8PT0xMXFxcsLCwoWbIkGzdu1DrPP//8Q8GCBbGwsKBGjRpa9UysoUOHUrBgQSwtLcmbNy+jRo0iOjo6XrnFixeTM2dOLC0tadGiBS9evNDavnTpUooUKYK5uTmFCxdmwYIFOtdFCCGSQmL+50nMF/pOkgCRIAsLC96+fav5vHfvXoKCgvD19cXHx4fo6Gjc3NywsbHh8OHDHD16FGtra+rWravZb8aMGXh7e7N8+XKOHDlCWFgYW7Zs+eR5O3TowJ9//omXlxeBgYEsXrwYa2trcubMyaZNmwAICgri0aNHzJkzBwBPT09WrVrFokWLuHTpEv3796ddu3YcPHgQUN+4fvrpJxo1akRAQABdu3Zl2LBhOn8nNjY2eHt7c/nyZebMmcOSJUuYNWuWVpnr16+zYcMGtm/fzq5duzh79iy//PKLZvuaNWsYPXo0kyZNIjAwkN9++41Ro0axcuVKnesjhBDJRWJ+fBLzhd5ThMFzd3dXGjdurCiKosTFxSm+vr6KmZmZMmjQIM12R0dHJSoqSrPP6tWrlUKFCilxcXGadVFRUYqFhYWye/duRVEUJVu2bMrUqVM126Ojo5UcOXJozqUoilKtWjWlb9++iqIoSlBQkAIovr6+CdZz//79CqA8e/ZMsy4yMlKxtLRUjh07plW2S5cuSuvWrRVFUZThw4crRYsW1do+dOjQeMf6EKBs2bLlo9unTZumlC1bVvN5zJgxirGxsXL//n3Nup07dypGRkbKo0ePFEVRlHz58ilr167VOs6ECRMUV1dXRVEU5datWwqgnD179qPnFUKIpJCYnzCJ+cLQSJ8AAYCPjw/W1tZER0cTFxdHmzZtGDt2rGZ7iRIltN4JPXfuHNevX8fGxkbrOJGRkdy4cYMXL17w6NEjKlSooNlmYmJCuXLl4jUPvxMQEICxsTHVqlVLdL2vX7/O69evqV27ttb6t2/fUrp0aQACAwO16gHg6uqa6HO8s379ery8vLhx4wYRERHExMRga2urVSZXrlxkz55d6zxxcXEEBQVhY2PDjRs36NKlC926ddOUiYmJwc7OTuf6CCHEl5KY/3kS84W+kyRAAFCjRg0WLlyIqakpzs7OmJho/69hZWWl9TkiIoKyZcuyZs2aeMfKmjXrF9XBwsJC530iIiIA2LFjh1YgBvU7r8nFz8+Ptm3bMm7cONzc3LCzs2PdunXMmDFD57ouWbIk3g3K2Ng42eoqhBCfIzH/0yTmC0MgSYAA1AE/f/78iS5fpkwZ1q9fj4ODQ7wnI+9ky5aNEydOULVqVUD99MPf358yZcokWL5EiRLExcVx8OBBatWqFW/7u6dSsbGxmnVFixbFzMyMu3fvfvRpUpEiRTQd3t45fvz45y/yPceOHSN37tyMGDFCs+7OnTvxyt29e5eHDx/i7OysOY+RkRGFChXC0dERZ2dnbt68Sdu2bXU6vxBCJCeJ+Z8mMV8YAukYLL5I27ZtyZIlC40bN+bw4cPcunWLAwcO0KdPH+7fvw9A3759mTx5Mlu3buXKlSv88ssvnxzvOU+ePLi7u9O5c2e2bt2qOeaGDRsAyJ07NyqVCh8fHx4/fkxERAQ2NjYMGjSI/v37s3LlSm7cuMGZM2eYO3eupuNVjx49uHbtGoMHDyYoKIi1a9fi7e2t0/UWKFCAu3fvsm7dOm7cuIGXl1eCHd7Mzc1xd3fn3LlzHD58mD59+tCiRQucnJwAGDduHJ6ennh5eXH16lUuXLjAihUrmDlzpk71EUKI1CQxX2K+0ENp3SlBpL33O4npsv3Ro0dKhw4dlCxZsihmZmZK3rx5lW7duikvXrxQFEXdKaxv376Kra2tkjFjRmXAgAFKhw4dPtpJTFEU5c2bN0r//v2VbNmyKaampkr+/PmV5cuXa7aPHz9ecXJyUlQqleLu7q4oirpj2+zZs5VChQopGTJkULJmzaq4ubkpBw8e1Oy3fft2JX/+/IqZmZlSpUoVZfny5Tp3Ehs8eLCSOXNmxdraWmnZsqUya9Ysxc7OTrN9zJgxSsmSJZUFCxYozs7Oirm5udKsWTMlLCxM67hr1qxRSpUqpZiamiqZMmVSqlatqmzevFlRFOkkJoRIeRLzEyYxXxgalaJ8pMeOEEIIIYQQQi/J60BCCCGEEEIYGEkChBBCCCGEMDCSBAghhBBCCGFgJAkQQgghhBDCwEgSIIQQQgghhIGRJEAIIYQQQggDI0mAEEIIIYQQBkaSACGEEEIIIQyMJAFCCCGEEEIYGEkChBBCCCGEMDCSBAghhBBCCGFg/gdmNB9QM/RG/gAAAABJRU5ErkJggg==\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[1mModel performance:\u001b[0m\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7fe22e50a080>"
            ],
            "text/html": [
              "<style type=\"text/css\">\n",
              "#T_920bb th {\n",
              "  max-width: 75px;\n",
              "}\n",
              "</style>\n",
              "<table id=\"T_920bb\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th class=\"blank level0\" >&nbsp;</th>\n",
              "      <th id=\"T_920bb_level0_col0\" class=\"col_heading level0 col0\" >Accuracy</th>\n",
              "      <th id=\"T_920bb_level0_col1\" class=\"col_heading level0 col1\" >Precision</th>\n",
              "      <th id=\"T_920bb_level0_col2\" class=\"col_heading level0 col2\" >Recall</th>\n",
              "      <th id=\"T_920bb_level0_col3\" class=\"col_heading level0 col3\" >NPV</th>\n",
              "      <th id=\"T_920bb_level0_col4\" class=\"col_heading level0 col4\" >Specificity</th>\n",
              "      <th id=\"T_920bb_level0_col5\" class=\"col_heading level0 col5\" >F1</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th id=\"T_920bb_level0_row0\" class=\"row_heading level0 row0\" >Training</th>\n",
              "      <td id=\"T_920bb_row0_col0\" class=\"data row0 col0\" >98.50%</td>\n",
              "      <td id=\"T_920bb_row0_col1\" class=\"data row0 col1\" >99.51%</td>\n",
              "      <td id=\"T_920bb_row0_col2\" class=\"data row0 col2\" >97.48%</td>\n",
              "      <td id=\"T_920bb_row0_col3\" class=\"data row0 col3\" >97.53%</td>\n",
              "      <td id=\"T_920bb_row0_col4\" class=\"data row0 col4\" >99.52%</td>\n",
              "      <td id=\"T_920bb_row0_col5\" class=\"data row0 col5\" >98.48%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_920bb_level0_row1\" class=\"row_heading level0 row1\" >Validation</th>\n",
              "      <td id=\"T_920bb_row1_col0\" class=\"data row1 col0\" >92.54%</td>\n",
              "      <td id=\"T_920bb_row1_col1\" class=\"data row1 col1\" >42.05%</td>\n",
              "      <td id=\"T_920bb_row1_col2\" class=\"data row1 col2\" >91.70%</td>\n",
              "      <td id=\"T_920bb_row1_col3\" class=\"data row1 col3\" >99.48%</td>\n",
              "      <td id=\"T_920bb_row1_col4\" class=\"data row1 col4\" >92.59%</td>\n",
              "      <td id=\"T_920bb_row1_col5\" class=\"data row1 col5\" >57.66%</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "\u001b[2;37;42mXGBClassifier:                                                                                        \u001b[0m\n",
            "\tBest parameters are:\n",
            "\t\tsubsample: 0.8\n",
            "\t\tscale_pos_weight: 10\n",
            "\t\tn_estimators: 200\n",
            "\t\tlearning_rate: 0.1\n",
            "\t\tgamma: 5\n",
            "\tCV score=0.92557\n",
            "\tIteration duration: 90.53 seconds\n",
            "-----------------------------------------------------------------------------------------------------\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 900x300 with 4 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[1mModel performance:\u001b[0m\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7fe22ef03250>"
            ],
            "text/html": [
              "<style type=\"text/css\">\n",
              "#T_32e8a th {\n",
              "  max-width: 75px;\n",
              "}\n",
              "</style>\n",
              "<table id=\"T_32e8a\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th class=\"blank level0\" >&nbsp;</th>\n",
              "      <th id=\"T_32e8a_level0_col0\" class=\"col_heading level0 col0\" >Accuracy</th>\n",
              "      <th id=\"T_32e8a_level0_col1\" class=\"col_heading level0 col1\" >Precision</th>\n",
              "      <th id=\"T_32e8a_level0_col2\" class=\"col_heading level0 col2\" >Recall</th>\n",
              "      <th id=\"T_32e8a_level0_col3\" class=\"col_heading level0 col3\" >NPV</th>\n",
              "      <th id=\"T_32e8a_level0_col4\" class=\"col_heading level0 col4\" >Specificity</th>\n",
              "      <th id=\"T_32e8a_level0_col5\" class=\"col_heading level0 col5\" >F1</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th id=\"T_32e8a_level0_row0\" class=\"row_heading level0 row0\" >Training</th>\n",
              "      <td id=\"T_32e8a_row0_col0\" class=\"data row0 col0\" >99.22%</td>\n",
              "      <td id=\"T_32e8a_row0_col1\" class=\"data row0 col1\" >98.46%</td>\n",
              "      <td id=\"T_32e8a_row0_col2\" class=\"data row0 col2\" >100.00%</td>\n",
              "      <td id=\"T_32e8a_row0_col3\" class=\"data row0 col3\" >100.00%</td>\n",
              "      <td id=\"T_32e8a_row0_col4\" class=\"data row0 col4\" >98.44%</td>\n",
              "      <td id=\"T_32e8a_row0_col5\" class=\"data row0 col5\" >99.23%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_32e8a_level0_row1\" class=\"row_heading level0 row1\" >Validation</th>\n",
              "      <td id=\"T_32e8a_row1_col0\" class=\"data row1 col0\" >85.22%</td>\n",
              "      <td id=\"T_32e8a_row1_col1\" class=\"data row1 col1\" >26.23%</td>\n",
              "      <td id=\"T_32e8a_row1_col2\" class=\"data row1 col2\" >92.06%</td>\n",
              "      <td id=\"T_32e8a_row1_col3\" class=\"data row1 col3\" >99.45%</td>\n",
              "      <td id=\"T_32e8a_row1_col4\" class=\"data row1 col4\" >84.82%</td>\n",
              "      <td id=\"T_32e8a_row1_col5\" class=\"data row1 col5\" >40.83%</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n"
            ]
          },
          "metadata": {}
        }
      ],
      "source": [
        "res_tuned_un = cv_tuned(models_tuned_grid, X_train_un, y_train_un, X_valid, y_valid, 'undersampled')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 65,
      "metadata": {
        "id": "QJqg6U61rDhJ"
      },
      "outputs": [],
      "source": [
        "res_tuned_orig['model'] += ' (original)'\n",
        "res_tuned_over['model'] += ' (oversampled)'\n",
        "res_tuned_un['model'] += ' (undersampled)'\n",
        "\n",
        "results_tuned = pd.concat([res_tuned_orig, res_tuned_over, res_tuned_un], axis=0).drop('best_params', axis=1)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "D9JNnpxa4jau"
      },
      "source": [
        "## Model performance comparison and choosing the final model"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 66,
      "metadata": {
        "id": "0WcygUP5ctJG",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 363
        },
        "outputId": "6e12bf21-2174-477d-f41d-6fa2a909a7a5"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7fe235a6c3d0>"
            ],
            "text/html": [
              "<style type=\"text/css\">\n",
              "</style>\n",
              "<table id=\"T_ca172\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th class=\"blank level0\" >&nbsp;</th>\n",
              "      <th id=\"T_ca172_level0_col0\" class=\"col_heading level0 col0\" >Accuracy</th>\n",
              "      <th id=\"T_ca172_level0_col1\" class=\"col_heading level0 col1\" >Precision</th>\n",
              "      <th id=\"T_ca172_level0_col2\" class=\"col_heading level0 col2\" >Recall</th>\n",
              "      <th id=\"T_ca172_level0_col3\" class=\"col_heading level0 col3\" >NPV</th>\n",
              "      <th id=\"T_ca172_level0_col4\" class=\"col_heading level0 col4\" >Specificity</th>\n",
              "      <th id=\"T_ca172_level0_col5\" class=\"col_heading level0 col5\" >F1</th>\n",
              "      <th id=\"T_ca172_level0_col6\" class=\"col_heading level0 col6\" >duration</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th class=\"index_name level0\" >model</th>\n",
              "      <th class=\"blank col0\" >&nbsp;</th>\n",
              "      <th class=\"blank col1\" >&nbsp;</th>\n",
              "      <th class=\"blank col2\" >&nbsp;</th>\n",
              "      <th class=\"blank col3\" >&nbsp;</th>\n",
              "      <th class=\"blank col4\" >&nbsp;</th>\n",
              "      <th class=\"blank col5\" >&nbsp;</th>\n",
              "      <th class=\"blank col6\" >&nbsp;</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th id=\"T_ca172_level0_row0\" class=\"row_heading level0 row0\" >XGBClassifier (undersampled)</th>\n",
              "      <td id=\"T_ca172_row0_col0\" class=\"data row0 col0\" >99.22%</td>\n",
              "      <td id=\"T_ca172_row0_col1\" class=\"data row0 col1\" >98.46%</td>\n",
              "      <td id=\"T_ca172_row0_col2\" class=\"data row0 col2\" >100.00%</td>\n",
              "      <td id=\"T_ca172_row0_col3\" class=\"data row0 col3\" >100.00%</td>\n",
              "      <td id=\"T_ca172_row0_col4\" class=\"data row0 col4\" >98.44%</td>\n",
              "      <td id=\"T_ca172_row0_col5\" class=\"data row0 col5\" >99.23%</td>\n",
              "      <td id=\"T_ca172_row0_col6\" class=\"data row0 col6\" >90.53</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_ca172_level0_row1\" class=\"row_heading level0 row1\" >XGBClassifier (original)</th>\n",
              "      <td id=\"T_ca172_row1_col0\" class=\"data row1 col0\" >99.96%</td>\n",
              "      <td id=\"T_ca172_row1_col1\" class=\"data row1 col1\" >99.28%</td>\n",
              "      <td id=\"T_ca172_row1_col2\" class=\"data row1 col2\" >100.00%</td>\n",
              "      <td id=\"T_ca172_row1_col3\" class=\"data row1 col3\" >100.00%</td>\n",
              "      <td id=\"T_ca172_row1_col4\" class=\"data row1 col4\" >99.96%</td>\n",
              "      <td id=\"T_ca172_row1_col5\" class=\"data row1 col5\" >99.64%</td>\n",
              "      <td id=\"T_ca172_row1_col6\" class=\"data row1 col6\" >866.32</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_ca172_level0_row2\" class=\"row_heading level0 row2\" >XGBClassifier (oversampled)</th>\n",
              "      <td id=\"T_ca172_row2_col0\" class=\"data row2 col0\" >99.94%</td>\n",
              "      <td id=\"T_ca172_row2_col1\" class=\"data row2 col1\" >99.88%</td>\n",
              "      <td id=\"T_ca172_row2_col2\" class=\"data row2 col2\" >100.00%</td>\n",
              "      <td id=\"T_ca172_row2_col3\" class=\"data row2 col3\" >100.00%</td>\n",
              "      <td id=\"T_ca172_row2_col4\" class=\"data row2 col4\" >99.88%</td>\n",
              "      <td id=\"T_ca172_row2_col5\" class=\"data row2 col5\" >99.94%</td>\n",
              "      <td id=\"T_ca172_row2_col6\" class=\"data row2 col6\" >1767.24</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_ca172_level0_row3\" class=\"row_heading level0 row3\" >RandomForestClassifier (oversampled)</th>\n",
              "      <td id=\"T_ca172_row3_col0\" class=\"data row3 col0\" >99.78%</td>\n",
              "      <td id=\"T_ca172_row3_col1\" class=\"data row3 col1\" >99.94%</td>\n",
              "      <td id=\"T_ca172_row3_col2\" class=\"data row3 col2\" >99.63%</td>\n",
              "      <td id=\"T_ca172_row3_col3\" class=\"data row3 col3\" >99.63%</td>\n",
              "      <td id=\"T_ca172_row3_col4\" class=\"data row3 col4\" >99.94%</td>\n",
              "      <td id=\"T_ca172_row3_col5\" class=\"data row3 col5\" >99.78%</td>\n",
              "      <td id=\"T_ca172_row3_col6\" class=\"data row3 col6\" >518.66</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_ca172_level0_row4\" class=\"row_heading level0 row4\" >GradientBoostingClassifier (undersampled)</th>\n",
              "      <td id=\"T_ca172_row4_col0\" class=\"data row4 col0\" >98.50%</td>\n",
              "      <td id=\"T_ca172_row4_col1\" class=\"data row4 col1\" >99.51%</td>\n",
              "      <td id=\"T_ca172_row4_col2\" class=\"data row4 col2\" >97.48%</td>\n",
              "      <td id=\"T_ca172_row4_col3\" class=\"data row4 col3\" >97.53%</td>\n",
              "      <td id=\"T_ca172_row4_col4\" class=\"data row4 col4\" >99.52%</td>\n",
              "      <td id=\"T_ca172_row4_col5\" class=\"data row4 col5\" >98.48%</td>\n",
              "      <td id=\"T_ca172_row4_col6\" class=\"data row4 col6\" >32.66</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_ca172_level0_row5\" class=\"row_heading level0 row5\" >GradientBoostingClassifier (oversampled)</th>\n",
              "      <td id=\"T_ca172_row5_col0\" class=\"data row5 col0\" >97.31%</td>\n",
              "      <td id=\"T_ca172_row5_col1\" class=\"data row5 col1\" >97.48%</td>\n",
              "      <td id=\"T_ca172_row5_col2\" class=\"data row5 col2\" >97.13%</td>\n",
              "      <td id=\"T_ca172_row5_col3\" class=\"data row5 col3\" >97.14%</td>\n",
              "      <td id=\"T_ca172_row5_col4\" class=\"data row5 col4\" >97.49%</td>\n",
              "      <td id=\"T_ca172_row5_col5\" class=\"data row5 col5\" >97.31%</td>\n",
              "      <td id=\"T_ca172_row5_col6\" class=\"data row5 col6\" >615.83</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_ca172_level0_row6\" class=\"row_heading level0 row6\" >RandomForestClassifier (undersampled)</th>\n",
              "      <td id=\"T_ca172_row6_col0\" class=\"data row6 col0\" >96.04%</td>\n",
              "      <td id=\"T_ca172_row6_col1\" class=\"data row6 col1\" >98.85%</td>\n",
              "      <td id=\"T_ca172_row6_col2\" class=\"data row6 col2\" >93.16%</td>\n",
              "      <td id=\"T_ca172_row6_col3\" class=\"data row6 col3\" >93.53%</td>\n",
              "      <td id=\"T_ca172_row6_col4\" class=\"data row6 col4\" >98.92%</td>\n",
              "      <td id=\"T_ca172_row6_col5\" class=\"data row6 col5\" >95.92%</td>\n",
              "      <td id=\"T_ca172_row6_col6\" class=\"data row6 col6\" >25.01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_ca172_level0_row7\" class=\"row_heading level0 row7\" >GradientBoostingClassifier (original)</th>\n",
              "      <td id=\"T_ca172_row7_col0\" class=\"data row7 col0\" >99.24%</td>\n",
              "      <td id=\"T_ca172_row7_col1\" class=\"data row7 col1\" >98.26%</td>\n",
              "      <td id=\"T_ca172_row7_col2\" class=\"data row7 col2\" >87.88%</td>\n",
              "      <td id=\"T_ca172_row7_col3\" class=\"data row7 col3\" >99.29%</td>\n",
              "      <td id=\"T_ca172_row7_col4\" class=\"data row7 col4\" >99.91%</td>\n",
              "      <td id=\"T_ca172_row7_col5\" class=\"data row7 col5\" >92.78%</td>\n",
              "      <td id=\"T_ca172_row7_col6\" class=\"data row7 col6\" >313.59</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_ca172_level0_row8\" class=\"row_heading level0 row8\" >RandomForestClassifier (original)</th>\n",
              "      <td id=\"T_ca172_row8_col0\" class=\"data row8 col0\" >99.11%</td>\n",
              "      <td id=\"T_ca172_row8_col1\" class=\"data row8 col1\" >99.72%</td>\n",
              "      <td id=\"T_ca172_row8_col2\" class=\"data row8 col2\" >84.27%</td>\n",
              "      <td id=\"T_ca172_row8_col3\" class=\"data row8 col3\" >99.08%</td>\n",
              "      <td id=\"T_ca172_row8_col4\" class=\"data row8 col4\" >99.99%</td>\n",
              "      <td id=\"T_ca172_row8_col5\" class=\"data row8 col5\" >91.35%</td>\n",
              "      <td id=\"T_ca172_row8_col6\" class=\"data row8 col6\" >351.69</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n"
            ]
          },
          "metadata": {},
          "execution_count": 66
        }
      ],
      "source": [
        "results_tuned[results_tuned['index']=='Training'].set_index('model').drop('index', axis=1)\\\n",
        "  .sort_values(by=['Recall', 'duration'], ascending=[False, True]).style\\\n",
        "  .format('{:.2f}')\\\n",
        "  .format('{:.2%}', subset=col_perc)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 67,
      "metadata": {
        "id": "77lcqhfu6oMc",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 363
        },
        "outputId": "1a032a8f-24cf-4e44-86f2-e89c6cda1048"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7fe22f12d2d0>"
            ],
            "text/html": [
              "<style type=\"text/css\">\n",
              "#T_2dbb1 th {\n",
              "  min-width: 75px;\n",
              "  text-align: right;\n",
              "}\n",
              "#T_2dbb1_row0_col2, #T_2dbb1_row1_col3, #T_2dbb1_row2_col6, #T_2dbb1_row4_col0, #T_2dbb1_row4_col5, #T_2dbb1_row8_col1, #T_2dbb1_row8_col4 {\n",
              "  background-color: lightgreen;\n",
              "}\n",
              "</style>\n",
              "<table id=\"T_2dbb1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th class=\"blank level0\" >&nbsp;</th>\n",
              "      <th id=\"T_2dbb1_level0_col0\" class=\"col_heading level0 col0\" >Accuracy</th>\n",
              "      <th id=\"T_2dbb1_level0_col1\" class=\"col_heading level0 col1\" >Precision</th>\n",
              "      <th id=\"T_2dbb1_level0_col2\" class=\"col_heading level0 col2\" >Recall</th>\n",
              "      <th id=\"T_2dbb1_level0_col3\" class=\"col_heading level0 col3\" >NPV</th>\n",
              "      <th id=\"T_2dbb1_level0_col4\" class=\"col_heading level0 col4\" >Specificity</th>\n",
              "      <th id=\"T_2dbb1_level0_col5\" class=\"col_heading level0 col5\" >F1</th>\n",
              "      <th id=\"T_2dbb1_level0_col6\" class=\"col_heading level0 col6\" >duration</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th class=\"index_name level0\" >model</th>\n",
              "      <th class=\"blank col0\" >&nbsp;</th>\n",
              "      <th class=\"blank col1\" >&nbsp;</th>\n",
              "      <th class=\"blank col2\" >&nbsp;</th>\n",
              "      <th class=\"blank col3\" >&nbsp;</th>\n",
              "      <th class=\"blank col4\" >&nbsp;</th>\n",
              "      <th class=\"blank col5\" >&nbsp;</th>\n",
              "      <th class=\"blank col6\" >&nbsp;</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th id=\"T_2dbb1_level0_row0\" class=\"row_heading level0 row0\" >XGBClassifier (undersampled)</th>\n",
              "      <td id=\"T_2dbb1_row0_col0\" class=\"data row0 col0\" >85.22%</td>\n",
              "      <td id=\"T_2dbb1_row0_col1\" class=\"data row0 col1\" >26.23%</td>\n",
              "      <td id=\"T_2dbb1_row0_col2\" class=\"data row0 col2\" >92.06%</td>\n",
              "      <td id=\"T_2dbb1_row0_col3\" class=\"data row0 col3\" >99.45%</td>\n",
              "      <td id=\"T_2dbb1_row0_col4\" class=\"data row0 col4\" >84.82%</td>\n",
              "      <td id=\"T_2dbb1_row0_col5\" class=\"data row0 col5\" >40.83%</td>\n",
              "      <td id=\"T_2dbb1_row0_col6\" class=\"data row0 col6\" >90.53</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_2dbb1_level0_row1\" class=\"row_heading level0 row1\" >GradientBoostingClassifier (undersampled)</th>\n",
              "      <td id=\"T_2dbb1_row1_col0\" class=\"data row1 col0\" >92.54%</td>\n",
              "      <td id=\"T_2dbb1_row1_col1\" class=\"data row1 col1\" >42.05%</td>\n",
              "      <td id=\"T_2dbb1_row1_col2\" class=\"data row1 col2\" >91.70%</td>\n",
              "      <td id=\"T_2dbb1_row1_col3\" class=\"data row1 col3\" >99.48%</td>\n",
              "      <td id=\"T_2dbb1_row1_col4\" class=\"data row1 col4\" >92.59%</td>\n",
              "      <td id=\"T_2dbb1_row1_col5\" class=\"data row1 col5\" >57.66%</td>\n",
              "      <td id=\"T_2dbb1_row1_col6\" class=\"data row1 col6\" >32.66</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_2dbb1_level0_row2\" class=\"row_heading level0 row2\" >RandomForestClassifier (undersampled)</th>\n",
              "      <td id=\"T_2dbb1_row2_col0\" class=\"data row2 col0\" >93.82%</td>\n",
              "      <td id=\"T_2dbb1_row2_col1\" class=\"data row2 col1\" >46.99%</td>\n",
              "      <td id=\"T_2dbb1_row2_col2\" class=\"data row2 col2\" >90.25%</td>\n",
              "      <td id=\"T_2dbb1_row2_col3\" class=\"data row2 col3\" >99.40%</td>\n",
              "      <td id=\"T_2dbb1_row2_col4\" class=\"data row2 col4\" >94.03%</td>\n",
              "      <td id=\"T_2dbb1_row2_col5\" class=\"data row2 col5\" >61.80%</td>\n",
              "      <td id=\"T_2dbb1_row2_col6\" class=\"data row2 col6\" >25.01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_2dbb1_level0_row3\" class=\"row_heading level0 row3\" >XGBClassifier (oversampled)</th>\n",
              "      <td id=\"T_2dbb1_row3_col0\" class=\"data row3 col0\" >97.98%</td>\n",
              "      <td id=\"T_2dbb1_row3_col1\" class=\"data row3 col1\" >77.33%</td>\n",
              "      <td id=\"T_2dbb1_row3_col2\" class=\"data row3 col2\" >89.89%</td>\n",
              "      <td id=\"T_2dbb1_row3_col3\" class=\"data row3 col3\" >99.40%</td>\n",
              "      <td id=\"T_2dbb1_row3_col4\" class=\"data row3 col4\" >98.45%</td>\n",
              "      <td id=\"T_2dbb1_row3_col5\" class=\"data row3 col5\" >83.14%</td>\n",
              "      <td id=\"T_2dbb1_row3_col6\" class=\"data row3 col6\" >1767.24</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_2dbb1_level0_row4\" class=\"row_heading level0 row4\" >XGBClassifier (original)</th>\n",
              "      <td id=\"T_2dbb1_row4_col0\" class=\"data row4 col0\" >98.98%</td>\n",
              "      <td id=\"T_2dbb1_row4_col1\" class=\"data row4 col1\" >92.80%</td>\n",
              "      <td id=\"T_2dbb1_row4_col2\" class=\"data row4 col2\" >88.45%</td>\n",
              "      <td id=\"T_2dbb1_row4_col3\" class=\"data row4 col3\" >99.32%</td>\n",
              "      <td id=\"T_2dbb1_row4_col4\" class=\"data row4 col4\" >99.60%</td>\n",
              "      <td id=\"T_2dbb1_row4_col5\" class=\"data row4 col5\" >90.57%</td>\n",
              "      <td id=\"T_2dbb1_row4_col6\" class=\"data row4 col6\" >866.32</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_2dbb1_level0_row5\" class=\"row_heading level0 row5\" >RandomForestClassifier (oversampled)</th>\n",
              "      <td id=\"T_2dbb1_row5_col0\" class=\"data row5 col0\" >98.86%</td>\n",
              "      <td id=\"T_2dbb1_row5_col1\" class=\"data row5 col1\" >91.67%</td>\n",
              "      <td id=\"T_2dbb1_row5_col2\" class=\"data row5 col2\" >87.36%</td>\n",
              "      <td id=\"T_2dbb1_row5_col3\" class=\"data row5 col3\" >99.26%</td>\n",
              "      <td id=\"T_2dbb1_row5_col4\" class=\"data row5 col4\" >99.53%</td>\n",
              "      <td id=\"T_2dbb1_row5_col5\" class=\"data row5 col5\" >89.46%</td>\n",
              "      <td id=\"T_2dbb1_row5_col6\" class=\"data row5 col6\" >518.66</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_2dbb1_level0_row6\" class=\"row_heading level0 row6\" >GradientBoostingClassifier (oversampled)</th>\n",
              "      <td id=\"T_2dbb1_row6_col0\" class=\"data row6 col0\" >94.54%</td>\n",
              "      <td id=\"T_2dbb1_row6_col1\" class=\"data row6 col1\" >50.42%</td>\n",
              "      <td id=\"T_2dbb1_row6_col2\" class=\"data row6 col2\" >86.64%</td>\n",
              "      <td id=\"T_2dbb1_row6_col3\" class=\"data row6 col3\" >99.18%</td>\n",
              "      <td id=\"T_2dbb1_row6_col4\" class=\"data row6 col4\" >95.00%</td>\n",
              "      <td id=\"T_2dbb1_row6_col5\" class=\"data row6 col5\" >63.75%</td>\n",
              "      <td id=\"T_2dbb1_row6_col6\" class=\"data row6 col6\" >615.83</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_2dbb1_level0_row7\" class=\"row_heading level0 row7\" >GradientBoostingClassifier (original)</th>\n",
              "      <td id=\"T_2dbb1_row7_col0\" class=\"data row7 col0\" >98.30%</td>\n",
              "      <td id=\"T_2dbb1_row7_col1\" class=\"data row7 col1\" >90.34%</td>\n",
              "      <td id=\"T_2dbb1_row7_col2\" class=\"data row7 col2\" >77.62%</td>\n",
              "      <td id=\"T_2dbb1_row7_col3\" class=\"data row7 col3\" >98.70%</td>\n",
              "      <td id=\"T_2dbb1_row7_col4\" class=\"data row7 col4\" >99.51%</td>\n",
              "      <td id=\"T_2dbb1_row7_col5\" class=\"data row7 col5\" >83.50%</td>\n",
              "      <td id=\"T_2dbb1_row7_col6\" class=\"data row7 col6\" >313.59</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_2dbb1_level0_row8\" class=\"row_heading level0 row8\" >RandomForestClassifier (original)</th>\n",
              "      <td id=\"T_2dbb1_row8_col0\" class=\"data row8 col0\" >98.44%</td>\n",
              "      <td id=\"T_2dbb1_row8_col1\" class=\"data row8 col1\" >98.54%</td>\n",
              "      <td id=\"T_2dbb1_row8_col2\" class=\"data row8 col2\" >72.92%</td>\n",
              "      <td id=\"T_2dbb1_row8_col3\" class=\"data row8 col3\" >98.44%</td>\n",
              "      <td id=\"T_2dbb1_row8_col4\" class=\"data row8 col4\" >99.94%</td>\n",
              "      <td id=\"T_2dbb1_row8_col5\" class=\"data row8 col5\" >83.82%</td>\n",
              "      <td id=\"T_2dbb1_row8_col6\" class=\"data row8 col6\" >351.69</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n"
            ]
          },
          "metadata": {},
          "execution_count": 67
        }
      ],
      "source": [
        "results_tuned[results_tuned['index']=='Validation'].set_index('model').drop('index', axis=1)\\\n",
        "  .sort_values(by=['Recall', 'duration'], ascending=[False, True]).style\\\n",
        "  .set_table_styles([dict(selector=\"th\", props=[('min-width', '75px'), \n",
        "                                                ('text-align', 'right')])])\\\n",
        "  .highlight_max(subset=col_perc, color='lightgreen', axis=0)\\\n",
        "  .highlight_min(subset=['duration'], color='lightgreen', axis=0)\\\n",
        "  .format('{:.2f}')\\\n",
        "  .format('{:.2%}', subset=col_perc)\n",
        "  "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xxDoVoRcjCiW"
      },
      "source": [
        "> Since we are focusing on recall, below is a summary of the top 3 models with the highest recall scores:\n",
        "\n",
        "\n",
        "1. XGBClassifier (undersampled):\n",
        "  - Recall: 92.06%\n",
        "  - F1 Score: 40.83%\n",
        "\n",
        "2. GradientBoostingClassifier (undersampled):\n",
        "  - Recall: 91.70%\n",
        "  - F1 Score: 57.66%\n",
        "\n",
        "3. RandomForestClassifier (undersampled):\n",
        "  - Recall: 90.25%\n",
        "  - F1 Score: 61.80%\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9ZlbxIbLq94y"
      },
      "source": [
        "* Even though these models trained on an undersampled dataset have a high Recall, their Precision, and consequently F1 score, is quite low. This indicates that the models have a high Type I error rate, meaning they produce many False Positive (FP) predictions. FP are detections where there is no failure, which result in inspection costs.\n",
        "\n",
        "* While inspection is the least expensive operation, a high number of such errors can still lead to significant overall costs. Moreover, there is a possibility that resources needed for more costly operations, such as replacement and repair, will be tied up in inspections, which may result in delays of urgent and important operations and additional expenses.\n",
        "\n",
        "* As a result, we need to strike a balance between Recall and Precision. Unfortunately, we lack specific information about the costs of various operations. We only know that repairing a generator costs significantly less than replacing it, and the cost of inspection is lower than the cost of repair.\n",
        "\n",
        "> Additionally, for double-check, let's assume that the cost of repair is 1/10 the cost of replacement, and the cost of inspection is 1/5 of the repair cost, and see what are the possible costs of different models."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 68,
      "metadata": {
        "id": "Q-bjtKgG0EBL",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 363
        },
        "outputId": "6a2b9619-a08a-4695-9871-cc666755babc"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                              duration  repair (TP)  \\\n",
              "model                                                                 \n",
              "XGBClassifier (oversampled)                1767.240445        249.0   \n",
              "XGBClassifier (original)                    866.321799        245.0   \n",
              "RandomForestClassifier (oversampled)        518.655441        242.0   \n",
              "GradientBoostingClassifier (undersampled)    32.658896        254.0   \n",
              "RandomForestClassifier (undersampled)        25.011586        250.0   \n",
              "GradientBoostingClassifier (oversampled)    615.831026        240.0   \n",
              "XGBClassifier (undersampled)                 90.525579        255.0   \n",
              "GradientBoostingClassifier (original)       313.589346        215.0   \n",
              "RandomForestClassifier (original)           351.694661        202.0   \n",
              "\n",
              "                                           replace (FN)  inspection (FP)  \\\n",
              "model                                                                      \n",
              "XGBClassifier (oversampled)                        28.0             73.0   \n",
              "XGBClassifier (original)                           32.0             19.0   \n",
              "RandomForestClassifier (oversampled)               35.0             22.0   \n",
              "GradientBoostingClassifier (undersampled)          23.0            350.0   \n",
              "RandomForestClassifier (undersampled)              27.0            282.0   \n",
              "GradientBoostingClassifier (oversampled)           37.0            236.0   \n",
              "XGBClassifier (undersampled)                       22.0            717.0   \n",
              "GradientBoostingClassifier (original)              62.0             23.0   \n",
              "RandomForestClassifier (original)                  75.0              3.0   \n",
              "\n",
              "                                            cost  \n",
              "model                                             \n",
              "XGBClassifier (oversampled)                56.55  \n",
              "XGBClassifier (original)                   57.45  \n",
              "RandomForestClassifier (oversampled)       60.30  \n",
              "GradientBoostingClassifier (undersampled)  65.90  \n",
              "RandomForestClassifier (undersampled)      66.10  \n",
              "GradientBoostingClassifier (oversampled)   72.80  \n",
              "XGBClassifier (undersampled)               83.35  \n",
              "GradientBoostingClassifier (original)      84.65  \n",
              "RandomForestClassifier (original)          95.35  "
            ],
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              "      <div>\n",
              "<style scoped>\n",
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              "      <th></th>\n",
              "      <th>duration</th>\n",
              "      <th>repair (TP)</th>\n",
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              "      <th>inspection (FP)</th>\n",
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              "      <th>XGBClassifier (oversampled)</th>\n",
              "      <td>1767.240445</td>\n",
              "      <td>249.0</td>\n",
              "      <td>28.0</td>\n",
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              "      <td>65.90</td>\n",
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              "    <tr>\n",
              "      <th>RandomForestClassifier (undersampled)</th>\n",
              "      <td>25.011586</td>\n",
              "      <td>250.0</td>\n",
              "      <td>27.0</td>\n",
              "      <td>282.0</td>\n",
              "      <td>66.10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>GradientBoostingClassifier (oversampled)</th>\n",
              "      <td>615.831026</td>\n",
              "      <td>240.0</td>\n",
              "      <td>37.0</td>\n",
              "      <td>236.0</td>\n",
              "      <td>72.80</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>XGBClassifier (undersampled)</th>\n",
              "      <td>90.525579</td>\n",
              "      <td>255.0</td>\n",
              "      <td>22.0</td>\n",
              "      <td>717.0</td>\n",
              "      <td>83.35</td>\n",
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              "    <tr>\n",
              "      <th>GradientBoostingClassifier (original)</th>\n",
              "      <td>313.589346</td>\n",
              "      <td>215.0</td>\n",
              "      <td>62.0</td>\n",
              "      <td>23.0</td>\n",
              "      <td>84.65</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>RandomForestClassifier (original)</th>\n",
              "      <td>351.694661</td>\n",
              "      <td>202.0</td>\n",
              "      <td>75.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>95.35</td>\n",
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              "        const buttonEl =\n",
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              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-4f5074bf-8b75-4ecd-94ff-2fad353c222a');\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",
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              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 68
        }
      ],
      "source": [
        "cost = results_tuned[results_tuned['index']=='Validation']\\\n",
        "  .set_index('model').drop('index', axis=1)\n",
        "\n",
        "length = y_valid.count()\n",
        "positive = y_valid.sum()\n",
        "negative = length - positive\n",
        "\n",
        "# FN (replacement) cost\n",
        "replace_cost = 1.0\n",
        "\n",
        "# TP (repair) cost\n",
        "repair_cost = replace_cost / 10\n",
        "\n",
        "# FP (inspection) cost\n",
        "inspection_cost = repair_cost / 2\n",
        "\n",
        "cost['repair (TP)'] = cost['Recall'] * positive\n",
        "cost['replace (FN)'] = positive - cost['repair (TP)']\n",
        "cost['inspection (FP)'] = negative * (1 - cost['Specificity'])\n",
        "cost['cost'] = cost['repair (TP)'] * repair_cost + \\\n",
        "               cost['replace (FN)'] * replace_cost + \\\n",
        "               cost['inspection (FP)'] * inspection_cost\n",
        "\n",
        "cost.iloc[:,-5:].sort_values('cost')"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "final_results = results_tuned[results_tuned['index']=='Validation'].set_index('model').drop('index', axis=1)\n",
        "final_results['cost'] = cost['cost']\n",
        "final_results['repair (TP)'] = cost['repair (TP)']\n",
        "final_results['replace (FN)'] = cost['replace (FN)']\n",
        "final_results['inspection (FP)'] = cost['inspection (FP)']\n"
      ],
      "metadata": {
        "id": "sjXoGMJbCuyh"
      },
      "execution_count": 69,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "final_results.sort_values(by=['cost'], ascending=[True]).style\\\n",
        "             .set_table_styles([{'selector': 'th.index_name', 'props': 'width: 100px;'},\n",
        "                                {'selector': 'th:first-child', 'props': 'width: 100px;'},\n",
        "                                {'selector': \"th\", \n",
        "                                 'props': [('width', '50px'),\n",
        "                                           ('text-align', 'right')]}])\\\n",
        "             .highlight_max(subset=col_perc, color='lightgreen', axis=0)\\\n",
        "             .highlight_min(subset=['duration', \n",
        "                                    'cost', \n",
        "                                    'repair (TP)', \n",
        "                                    'replace (FN)', \n",
        "                                    'inspection (FP)'], \n",
        "                            color='lightgreen', axis=0)\\\n",
        "             .highlight_max(subset=['duration', \n",
        "                                    'cost', \n",
        "                                    'repair (TP)', \n",
        "                                    'replace (FN)', \n",
        "                                    'inspection (FP)'],\n",
        "                            color='pink', axis=0)\\\n",
        "             .format('{:.0f}')\\\n",
        "             .format('{:.2%}', subset=col_perc)\n",
        "             "
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 519
        },
        "id": "GSkZqOLACooo",
        "outputId": "c39f841c-e273-4374-d478-b72afb42e3c3"
      },
      "execution_count": 70,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
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              "</style>\n",
              "<table id=\"T_4fadb\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th class=\"blank level0\" >&nbsp;</th>\n",
              "      <th id=\"T_4fadb_level0_col0\" class=\"col_heading level0 col0\" >Accuracy</th>\n",
              "      <th id=\"T_4fadb_level0_col1\" class=\"col_heading level0 col1\" >Precision</th>\n",
              "      <th id=\"T_4fadb_level0_col2\" class=\"col_heading level0 col2\" >Recall</th>\n",
              "      <th id=\"T_4fadb_level0_col3\" class=\"col_heading level0 col3\" >NPV</th>\n",
              "      <th id=\"T_4fadb_level0_col4\" class=\"col_heading level0 col4\" >Specificity</th>\n",
              "      <th id=\"T_4fadb_level0_col5\" class=\"col_heading level0 col5\" >F1</th>\n",
              "      <th id=\"T_4fadb_level0_col6\" class=\"col_heading level0 col6\" >duration</th>\n",
              "      <th id=\"T_4fadb_level0_col7\" class=\"col_heading level0 col7\" >cost</th>\n",
              "      <th id=\"T_4fadb_level0_col8\" class=\"col_heading level0 col8\" >repair (TP)</th>\n",
              "      <th id=\"T_4fadb_level0_col9\" class=\"col_heading level0 col9\" >replace (FN)</th>\n",
              "      <th id=\"T_4fadb_level0_col10\" class=\"col_heading level0 col10\" >inspection (FP)</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th class=\"index_name level0\" >model</th>\n",
              "      <th class=\"blank col0\" >&nbsp;</th>\n",
              "      <th class=\"blank col1\" >&nbsp;</th>\n",
              "      <th class=\"blank col2\" >&nbsp;</th>\n",
              "      <th class=\"blank col3\" >&nbsp;</th>\n",
              "      <th class=\"blank col4\" >&nbsp;</th>\n",
              "      <th class=\"blank col5\" >&nbsp;</th>\n",
              "      <th class=\"blank col6\" >&nbsp;</th>\n",
              "      <th class=\"blank col7\" >&nbsp;</th>\n",
              "      <th class=\"blank col8\" >&nbsp;</th>\n",
              "      <th class=\"blank col9\" >&nbsp;</th>\n",
              "      <th class=\"blank col10\" >&nbsp;</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th id=\"T_4fadb_level0_row0\" class=\"row_heading level0 row0\" >XGBClassifier (oversampled)</th>\n",
              "      <td id=\"T_4fadb_row0_col0\" class=\"data row0 col0\" >97.98%</td>\n",
              "      <td id=\"T_4fadb_row0_col1\" class=\"data row0 col1\" >77.33%</td>\n",
              "      <td id=\"T_4fadb_row0_col2\" class=\"data row0 col2\" >89.89%</td>\n",
              "      <td id=\"T_4fadb_row0_col3\" class=\"data row0 col3\" >99.40%</td>\n",
              "      <td id=\"T_4fadb_row0_col4\" class=\"data row0 col4\" >98.45%</td>\n",
              "      <td id=\"T_4fadb_row0_col5\" class=\"data row0 col5\" >83.14%</td>\n",
              "      <td id=\"T_4fadb_row0_col6\" class=\"data row0 col6\" >1767</td>\n",
              "      <td id=\"T_4fadb_row0_col7\" class=\"data row0 col7\" >57</td>\n",
              "      <td id=\"T_4fadb_row0_col8\" class=\"data row0 col8\" >249</td>\n",
              "      <td id=\"T_4fadb_row0_col9\" class=\"data row0 col9\" >28</td>\n",
              "      <td id=\"T_4fadb_row0_col10\" class=\"data row0 col10\" >73</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_4fadb_level0_row1\" class=\"row_heading level0 row1\" >XGBClassifier (original)</th>\n",
              "      <td id=\"T_4fadb_row1_col0\" class=\"data row1 col0\" >98.98%</td>\n",
              "      <td id=\"T_4fadb_row1_col1\" class=\"data row1 col1\" >92.80%</td>\n",
              "      <td id=\"T_4fadb_row1_col2\" class=\"data row1 col2\" >88.45%</td>\n",
              "      <td id=\"T_4fadb_row1_col3\" class=\"data row1 col3\" >99.32%</td>\n",
              "      <td id=\"T_4fadb_row1_col4\" class=\"data row1 col4\" >99.60%</td>\n",
              "      <td id=\"T_4fadb_row1_col5\" class=\"data row1 col5\" >90.57%</td>\n",
              "      <td id=\"T_4fadb_row1_col6\" class=\"data row1 col6\" >866</td>\n",
              "      <td id=\"T_4fadb_row1_col7\" class=\"data row1 col7\" >57</td>\n",
              "      <td id=\"T_4fadb_row1_col8\" class=\"data row1 col8\" >245</td>\n",
              "      <td id=\"T_4fadb_row1_col9\" class=\"data row1 col9\" >32</td>\n",
              "      <td id=\"T_4fadb_row1_col10\" class=\"data row1 col10\" >19</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_4fadb_level0_row2\" class=\"row_heading level0 row2\" >RandomForestClassifier (oversampled)</th>\n",
              "      <td id=\"T_4fadb_row2_col0\" class=\"data row2 col0\" >98.86%</td>\n",
              "      <td id=\"T_4fadb_row2_col1\" class=\"data row2 col1\" >91.67%</td>\n",
              "      <td id=\"T_4fadb_row2_col2\" class=\"data row2 col2\" >87.36%</td>\n",
              "      <td id=\"T_4fadb_row2_col3\" class=\"data row2 col3\" >99.26%</td>\n",
              "      <td id=\"T_4fadb_row2_col4\" class=\"data row2 col4\" >99.53%</td>\n",
              "      <td id=\"T_4fadb_row2_col5\" class=\"data row2 col5\" >89.46%</td>\n",
              "      <td id=\"T_4fadb_row2_col6\" class=\"data row2 col6\" >519</td>\n",
              "      <td id=\"T_4fadb_row2_col7\" class=\"data row2 col7\" >60</td>\n",
              "      <td id=\"T_4fadb_row2_col8\" class=\"data row2 col8\" >242</td>\n",
              "      <td id=\"T_4fadb_row2_col9\" class=\"data row2 col9\" >35</td>\n",
              "      <td id=\"T_4fadb_row2_col10\" class=\"data row2 col10\" >22</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_4fadb_level0_row3\" class=\"row_heading level0 row3\" >GradientBoostingClassifier (undersampled)</th>\n",
              "      <td id=\"T_4fadb_row3_col0\" class=\"data row3 col0\" >92.54%</td>\n",
              "      <td id=\"T_4fadb_row3_col1\" class=\"data row3 col1\" >42.05%</td>\n",
              "      <td id=\"T_4fadb_row3_col2\" class=\"data row3 col2\" >91.70%</td>\n",
              "      <td id=\"T_4fadb_row3_col3\" class=\"data row3 col3\" >99.48%</td>\n",
              "      <td id=\"T_4fadb_row3_col4\" class=\"data row3 col4\" >92.59%</td>\n",
              "      <td id=\"T_4fadb_row3_col5\" class=\"data row3 col5\" >57.66%</td>\n",
              "      <td id=\"T_4fadb_row3_col6\" class=\"data row3 col6\" >33</td>\n",
              "      <td id=\"T_4fadb_row3_col7\" class=\"data row3 col7\" >66</td>\n",
              "      <td id=\"T_4fadb_row3_col8\" class=\"data row3 col8\" >254</td>\n",
              "      <td id=\"T_4fadb_row3_col9\" class=\"data row3 col9\" >23</td>\n",
              "      <td id=\"T_4fadb_row3_col10\" class=\"data row3 col10\" >350</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_4fadb_level0_row4\" class=\"row_heading level0 row4\" >RandomForestClassifier (undersampled)</th>\n",
              "      <td id=\"T_4fadb_row4_col0\" class=\"data row4 col0\" >93.82%</td>\n",
              "      <td id=\"T_4fadb_row4_col1\" class=\"data row4 col1\" >46.99%</td>\n",
              "      <td id=\"T_4fadb_row4_col2\" class=\"data row4 col2\" >90.25%</td>\n",
              "      <td id=\"T_4fadb_row4_col3\" class=\"data row4 col3\" >99.40%</td>\n",
              "      <td id=\"T_4fadb_row4_col4\" class=\"data row4 col4\" >94.03%</td>\n",
              "      <td id=\"T_4fadb_row4_col5\" class=\"data row4 col5\" >61.80%</td>\n",
              "      <td id=\"T_4fadb_row4_col6\" class=\"data row4 col6\" >25</td>\n",
              "      <td id=\"T_4fadb_row4_col7\" class=\"data row4 col7\" >66</td>\n",
              "      <td id=\"T_4fadb_row4_col8\" class=\"data row4 col8\" >250</td>\n",
              "      <td id=\"T_4fadb_row4_col9\" class=\"data row4 col9\" >27</td>\n",
              "      <td id=\"T_4fadb_row4_col10\" class=\"data row4 col10\" >282</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_4fadb_level0_row5\" class=\"row_heading level0 row5\" >GradientBoostingClassifier (oversampled)</th>\n",
              "      <td id=\"T_4fadb_row5_col0\" class=\"data row5 col0\" >94.54%</td>\n",
              "      <td id=\"T_4fadb_row5_col1\" class=\"data row5 col1\" >50.42%</td>\n",
              "      <td id=\"T_4fadb_row5_col2\" class=\"data row5 col2\" >86.64%</td>\n",
              "      <td id=\"T_4fadb_row5_col3\" class=\"data row5 col3\" >99.18%</td>\n",
              "      <td id=\"T_4fadb_row5_col4\" class=\"data row5 col4\" >95.00%</td>\n",
              "      <td id=\"T_4fadb_row5_col5\" class=\"data row5 col5\" >63.75%</td>\n",
              "      <td id=\"T_4fadb_row5_col6\" class=\"data row5 col6\" >616</td>\n",
              "      <td id=\"T_4fadb_row5_col7\" class=\"data row5 col7\" >73</td>\n",
              "      <td id=\"T_4fadb_row5_col8\" class=\"data row5 col8\" >240</td>\n",
              "      <td id=\"T_4fadb_row5_col9\" class=\"data row5 col9\" >37</td>\n",
              "      <td id=\"T_4fadb_row5_col10\" class=\"data row5 col10\" >236</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_4fadb_level0_row6\" class=\"row_heading level0 row6\" >XGBClassifier (undersampled)</th>\n",
              "      <td id=\"T_4fadb_row6_col0\" class=\"data row6 col0\" >85.22%</td>\n",
              "      <td id=\"T_4fadb_row6_col1\" class=\"data row6 col1\" >26.23%</td>\n",
              "      <td id=\"T_4fadb_row6_col2\" class=\"data row6 col2\" >92.06%</td>\n",
              "      <td id=\"T_4fadb_row6_col3\" class=\"data row6 col3\" >99.45%</td>\n",
              "      <td id=\"T_4fadb_row6_col4\" class=\"data row6 col4\" >84.82%</td>\n",
              "      <td id=\"T_4fadb_row6_col5\" class=\"data row6 col5\" >40.83%</td>\n",
              "      <td id=\"T_4fadb_row6_col6\" class=\"data row6 col6\" >91</td>\n",
              "      <td id=\"T_4fadb_row6_col7\" class=\"data row6 col7\" >83</td>\n",
              "      <td id=\"T_4fadb_row6_col8\" class=\"data row6 col8\" >255</td>\n",
              "      <td id=\"T_4fadb_row6_col9\" class=\"data row6 col9\" >22</td>\n",
              "      <td id=\"T_4fadb_row6_col10\" class=\"data row6 col10\" >717</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_4fadb_level0_row7\" class=\"row_heading level0 row7\" >GradientBoostingClassifier (original)</th>\n",
              "      <td id=\"T_4fadb_row7_col0\" class=\"data row7 col0\" >98.30%</td>\n",
              "      <td id=\"T_4fadb_row7_col1\" class=\"data row7 col1\" >90.34%</td>\n",
              "      <td id=\"T_4fadb_row7_col2\" class=\"data row7 col2\" >77.62%</td>\n",
              "      <td id=\"T_4fadb_row7_col3\" class=\"data row7 col3\" >98.70%</td>\n",
              "      <td id=\"T_4fadb_row7_col4\" class=\"data row7 col4\" >99.51%</td>\n",
              "      <td id=\"T_4fadb_row7_col5\" class=\"data row7 col5\" >83.50%</td>\n",
              "      <td id=\"T_4fadb_row7_col6\" class=\"data row7 col6\" >314</td>\n",
              "      <td id=\"T_4fadb_row7_col7\" class=\"data row7 col7\" >85</td>\n",
              "      <td id=\"T_4fadb_row7_col8\" class=\"data row7 col8\" >215</td>\n",
              "      <td id=\"T_4fadb_row7_col9\" class=\"data row7 col9\" >62</td>\n",
              "      <td id=\"T_4fadb_row7_col10\" class=\"data row7 col10\" >23</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_4fadb_level0_row8\" class=\"row_heading level0 row8\" >RandomForestClassifier (original)</th>\n",
              "      <td id=\"T_4fadb_row8_col0\" class=\"data row8 col0\" >98.44%</td>\n",
              "      <td id=\"T_4fadb_row8_col1\" class=\"data row8 col1\" >98.54%</td>\n",
              "      <td id=\"T_4fadb_row8_col2\" class=\"data row8 col2\" >72.92%</td>\n",
              "      <td id=\"T_4fadb_row8_col3\" class=\"data row8 col3\" >98.44%</td>\n",
              "      <td id=\"T_4fadb_row8_col4\" class=\"data row8 col4\" >99.94%</td>\n",
              "      <td id=\"T_4fadb_row8_col5\" class=\"data row8 col5\" >83.82%</td>\n",
              "      <td id=\"T_4fadb_row8_col6\" class=\"data row8 col6\" >352</td>\n",
              "      <td id=\"T_4fadb_row8_col7\" class=\"data row8 col7\" >95</td>\n",
              "      <td id=\"T_4fadb_row8_col8\" class=\"data row8 col8\" >202</td>\n",
              "      <td id=\"T_4fadb_row8_col9\" class=\"data row8 col9\" >75</td>\n",
              "      <td id=\"T_4fadb_row8_col10\" class=\"data row8 col10\" >3</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n"
            ]
          },
          "metadata": {},
          "execution_count": 70
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "XDw5lDBxQ5QD"
      },
      "source": [
        "**Observations:**\n",
        "\n",
        "* Based on the table above, the **XGBClassifier** model trained on the oversampled dataset has the lowest cost considering our assumptions based on the provided data about relations between different costs for replacement, repair, and inspection.\n",
        "\n",
        "* When selecting a model, it's crucial to consider not only its performance metrics, such as Recall and Precision, but also the associated costs, as demonstrated in this table. Balancing these factors will help us choose the most appropriate model for our case.\n",
        "\n",
        "* The **XGBClassifier** trained on the oversampled data has a **Recall of 89.89%** and an **F1 score of 83.14%** on the validation dataset. There were **28** cases of FN on the validation dataset, which would have led to expensive replacement, and **73** cases of FP involving relatively inexpensive inspection.\n",
        "\n",
        "* The XGBClassifier trained on the original dataset achieves results that are quite similar to those of the oversampled model. However, the oversampled model takes more than twice as long to train, making it less time-efficient. Nevertheless, we will select the model with a lower number of false negative outcomes as it is  stated as a goal.\n",
        "\n",
        "* All three models trained on the undersampled dataset have very good Recall and a low number of Type II errors. However, they produce too many False Positive outcomes (Type I errors), leading to numerous inspections. Depending on resource availability and the cost of inspection, this could have a significant impact on overall efficiency and expenses. Particularly if we assume that the same resources are utilized for the inspection, repair, and replacement processes."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "d_pDMFAz4jav"
      },
      "source": [
        "## Test set final performance"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Nu4KTPFOSUQS"
      },
      "source": [
        "Considering the above, the **XGBClassifier** trained on the **oversampled** training dataset has been selected as the final model. The ultimate performance evaluation will be based on this chosen model."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 71,
      "metadata": {
        "id": "sHVsOad_LNzY",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "db008423-38c0-4261-b648-8e3887aaa6c7"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Best params for XGBClassifier (oversampled):\n",
            "\tsubsample: 0.8\n",
            "\tscale_pos_weight: 10\n",
            "\tn_estimators: 250\n",
            "\tlearning_rate: 0.1\n",
            "\tgamma: 0\n"
          ]
        }
      ],
      "source": [
        "best_params_final = res_tuned_over.loc[(res_tuned_over['model']=='XGBClassifier (oversampled)')&\n",
        "                                       (res_tuned_over['index']=='Validation'), 'best_params'].values[0][0]\n",
        "\n",
        "print('Best params for XGBClassifier (oversampled):')\n",
        "for e in best_params_final:\n",
        "  print(f'\\t{e}: {best_params_final[e]}')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 72,
      "metadata": {
        "id": "Ng87mtvF1-qa"
      },
      "outputs": [],
      "source": [
        "final_model = XGBClassifier(subsample=0.8,\n",
        "                            scale_pos_weight=10,\n",
        "                            n_estimators=250,\n",
        "                            learning_rate=0.1,\n",
        "                            gamma=0,\n",
        "                            random_state=42)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 73,
      "metadata": {
        "id": "IpUbbwGa3BxX",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 248
        },
        "outputId": "a6802fc9-8d9a-4e12-cb8c-d252afbe18ab"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "XGBClassifier(base_score=None, booster=None, callbacks=None,\n",
              "              colsample_bylevel=None, colsample_bynode=None,\n",
              "              colsample_bytree=None, early_stopping_rounds=None,\n",
              "              enable_categorical=False, eval_metric=None, feature_types=None,\n",
              "              gamma=0, gpu_id=None, grow_policy=None, importance_type=None,\n",
              "              interaction_constraints=None, learning_rate=0.1, max_bin=None,\n",
              "              max_cat_threshold=None, max_cat_to_onehot=None,\n",
              "              max_delta_step=None, max_depth=None, max_leaves=None,\n",
              "              min_child_weight=None, missing=nan, monotone_constraints=None,\n",
              "              n_estimators=250, n_jobs=None, num_parallel_tree=None,\n",
              "              predictor=None, random_state=42, ...)"
            ],
            "text/html": [
              "<style>#sk-container-id-1 {color: black;background-color: white;}#sk-container-id-1 pre{padding: 0;}#sk-container-id-1 div.sk-toggleable {background-color: white;}#sk-container-id-1 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-1 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-1 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-1 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-1 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-1 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-1 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-1 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-1 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-1 div.sk-item {position: relative;z-index: 1;}#sk-container-id-1 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-1 div.sk-item::before, #sk-container-id-1 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-1 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-1 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-1 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-1 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-1 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-1 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-1 div.sk-label-container {text-align: center;}#sk-container-id-1 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-1 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>XGBClassifier(base_score=None, booster=None, callbacks=None,\n",
              "              colsample_bylevel=None, colsample_bynode=None,\n",
              "              colsample_bytree=None, early_stopping_rounds=None,\n",
              "              enable_categorical=False, eval_metric=None, feature_types=None,\n",
              "              gamma=0, gpu_id=None, grow_policy=None, importance_type=None,\n",
              "              interaction_constraints=None, learning_rate=0.1, max_bin=None,\n",
              "              max_cat_threshold=None, max_cat_to_onehot=None,\n",
              "              max_delta_step=None, max_depth=None, max_leaves=None,\n",
              "              min_child_weight=None, missing=nan, monotone_constraints=None,\n",
              "              n_estimators=250, n_jobs=None, num_parallel_tree=None,\n",
              "              predictor=None, random_state=42, ...)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" checked><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">XGBClassifier</label><div class=\"sk-toggleable__content\"><pre>XGBClassifier(base_score=None, booster=None, callbacks=None,\n",
              "              colsample_bylevel=None, colsample_bynode=None,\n",
              "              colsample_bytree=None, early_stopping_rounds=None,\n",
              "              enable_categorical=False, eval_metric=None, feature_types=None,\n",
              "              gamma=0, gpu_id=None, grow_policy=None, importance_type=None,\n",
              "              interaction_constraints=None, learning_rate=0.1, max_bin=None,\n",
              "              max_cat_threshold=None, max_cat_to_onehot=None,\n",
              "              max_delta_step=None, max_depth=None, max_leaves=None,\n",
              "              min_child_weight=None, missing=nan, monotone_constraints=None,\n",
              "              n_estimators=250, n_jobs=None, num_parallel_tree=None,\n",
              "              predictor=None, random_state=42, ...)</pre></div></div></div></div></div>"
            ]
          },
          "metadata": {},
          "execution_count": 73
        }
      ],
      "source": [
        "final_model.fit(X_train_over, y_train_over)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 74,
      "metadata": {
        "id": "DsdFmyKNM4vq",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 444
        },
        "outputId": "bc539807-4078-46e1-8e34-7d67dd7e2cc5"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 900x300 with 4 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[1mModel performance:\u001b[0m\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7fe22eb25810>"
            ],
            "text/html": [
              "<style type=\"text/css\">\n",
              "#T_4ffda th {\n",
              "  max-width: 75px;\n",
              "}\n",
              "</style>\n",
              "<table id=\"T_4ffda\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th class=\"blank level0\" >&nbsp;</th>\n",
              "      <th id=\"T_4ffda_level0_col0\" class=\"col_heading level0 col0\" >Accuracy</th>\n",
              "      <th id=\"T_4ffda_level0_col1\" class=\"col_heading level0 col1\" >Precision</th>\n",
              "      <th id=\"T_4ffda_level0_col2\" class=\"col_heading level0 col2\" >Recall</th>\n",
              "      <th id=\"T_4ffda_level0_col3\" class=\"col_heading level0 col3\" >NPV</th>\n",
              "      <th id=\"T_4ffda_level0_col4\" class=\"col_heading level0 col4\" >Specificity</th>\n",
              "      <th id=\"T_4ffda_level0_col5\" class=\"col_heading level0 col5\" >F1</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th id=\"T_4ffda_level0_row0\" class=\"row_heading level0 row0\" >Train</th>\n",
              "      <td id=\"T_4ffda_row0_col0\" class=\"data row0 col0\" >99.94%</td>\n",
              "      <td id=\"T_4ffda_row0_col1\" class=\"data row0 col1\" >99.88%</td>\n",
              "      <td id=\"T_4ffda_row0_col2\" class=\"data row0 col2\" >100.00%</td>\n",
              "      <td id=\"T_4ffda_row0_col3\" class=\"data row0 col3\" >100.00%</td>\n",
              "      <td id=\"T_4ffda_row0_col4\" class=\"data row0 col4\" >99.88%</td>\n",
              "      <td id=\"T_4ffda_row0_col5\" class=\"data row0 col5\" >99.94%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_4ffda_level0_row1\" class=\"row_heading level0 row1\" >Test</th>\n",
              "      <td id=\"T_4ffda_row1_col0\" class=\"data row1 col0\" >97.80%</td>\n",
              "      <td id=\"T_4ffda_row1_col1\" class=\"data row1 col1\" >77.92%</td>\n",
              "      <td id=\"T_4ffda_row1_col2\" class=\"data row1 col2\" >85.11%</td>\n",
              "      <td id=\"T_4ffda_row1_col3\" class=\"data row1 col3\" >99.10%</td>\n",
              "      <td id=\"T_4ffda_row1_col4\" class=\"data row1 col4\" >98.56%</td>\n",
              "      <td id=\"T_4ffda_row1_col5\" class=\"data row1 col5\" >81.36%</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n"
            ]
          },
          "metadata": {}
        }
      ],
      "source": [
        "final_model_perf = model_performance(final_model,\n",
        "                                     X_train_over, y_train_over,\n",
        "                                     X_test, y_test)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "GdSTZ2MGJPmx"
      },
      "source": [
        "* The **Recall** score of **85.11%** on the test data validates that the chosen model performs well in identifying true positive cases. This high recall performance confirms that the model is a good final model, suitable for deployment and further evaluations in real-world scenarios. By maintaining an acceptable recall performance on unseen data, the model demonstrates its effectiveness in generalizing to new instances, making it a reliable choice for the given task."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "i6ha8SNjJjEU"
      },
      "source": [
        "### Feature Importance"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "- The performance on test data is generalised\n",
        "- Let's check the important features for prediction as per the the final model"
      ],
      "metadata": {
        "id": "0HAd2q2vFzoV"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 75,
      "metadata": {
        "id": "pc_VO4XDJgPI",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 872
        },
        "outputId": "cd11748b-82c0-4a57-a811-119f2ea72992"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x1000 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "feature_names = X_train.columns\n",
        "importances = (final_model.feature_importances_)\n",
        "indices = np.argsort(importances)\n",
        "\n",
        "plt.figure(figsize=(10, 10))\n",
        "plt.title(\"Feature Importance\")\n",
        "plt.barh(range(len(indices)), importances[indices], color=\"violet\", align=\"center\")\n",
        "plt.yticks(range(len(indices)), [feature_names[i] for i in indices])\n",
        "plt.xlabel(\"Relative Importance\")\n",
        "plt.show()\n"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "* V36 is the most important feature, followed by V26, V18, and V14."
      ],
      "metadata": {
        "id": "KkaGHMf5F-Vy"
      }
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "TM6VZTRn4jav"
      },
      "source": [
        "## Pipelines to build the final model\n"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Now that we have a final model, let's use pipelines to put the model into production. We know that we can use pipelines to standardize the model building, but the steps in a pipeline are applied to each and every variable."
      ],
      "metadata": {
        "id": "t56BVKHvGeCD"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 76,
      "metadata": {
        "id": "mHg95iKWgowz",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "b91a2398-e953-44a6-e2c2-d616cf3e987a"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Best params for XGBClassifier (oversampled):\n",
            "\tsubsample: 0.8\n",
            "\tscale_pos_weight: 10\n",
            "\tn_estimators: 250\n",
            "\tlearning_rate: 0.1\n",
            "\tgamma: 0\n"
          ]
        }
      ],
      "source": [
        "# Getting the best params from the previous steps\n",
        "print('Best params for XGBClassifier (oversampled):')\n",
        "for e in best_params_final:\n",
        "  print(f'\\t{e}: {best_params_final[e]}')\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 77,
      "metadata": {
        "id": "21R9t3ccJr8x"
      },
      "outputs": [],
      "source": [
        "pipeline_model = Pipeline(\n",
        "    [\n",
        "        ('Imputer', \n",
        "         KNNImputer(n_neighbors=5)),\n",
        "        ('Oversampler', \n",
        "         SMOTE(k_neighbors=5, sampling_strategy=1, random_state=42)),\n",
        "        ('XGBClassifier', \n",
        "         XGBClassifier(subsample=0.8,\n",
        "                       scale_pos_weight=10,\n",
        "                       n_estimators=250,\n",
        "                       learning_rate=0.1,\n",
        "                       gamma=0,\n",
        "                       random_state=42\n",
        "                       )\n",
        "         )\n",
        "    ]\n",
        ")"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "> Now we already know the best model we need to process with, so we don't need to divide data into 3 parts"
      ],
      "metadata": {
        "id": "9XPEGPsDHAUJ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Separating target variable and other variables\n",
        "X_train_final = train.drop('Target', axis=1)\n",
        "y_train_final = train['Target']\n",
        "\n",
        "X_test_final = test.drop('Target', axis=1)\n",
        "y_test_final = test['Target']"
      ],
      "metadata": {
        "id": "-V_SIT_kHX7u"
      },
      "execution_count": 78,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(X_train_final.shape, X_test_final.shape)\n",
        "print(y_train_final.shape, y_test_final.shape)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Ovv5nRKvH_yl",
        "outputId": "33121c2a-0e76-46b2-d8c6-ab41c514bac2"
      },
      "execution_count": 79,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "(20000, 40) (5000, 40)\n",
            "(20000,) (5000,)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 80,
      "metadata": {
        "id": "phpjMd63J0lj",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 162
        },
        "outputId": "01a79d34-7f0b-4dd1-af82-35ddc58e73e9"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Pipeline(steps=[('Imputer', KNNImputer()),\n",
              "                ('Oversampler', SMOTE(random_state=42, sampling_strategy=1)),\n",
              "                ('XGBClassifier',\n",
              "                 XGBClassifier(base_score=None, booster=None, callbacks=None,\n",
              "                               colsample_bylevel=None, colsample_bynode=None,\n",
              "                               colsample_bytree=None,\n",
              "                               early_stopping_rounds=None,\n",
              "                               enable_categorical=False, eval_metric=None,\n",
              "                               feature_types=None, gamma=0, gpu_id=None,\n",
              "                               grow_policy=None, importance_type=None,\n",
              "                               interaction_constraints=None, learning_rate=0.1,\n",
              "                               max_bin=None, max_cat_threshold=None,\n",
              "                               max_cat_to_onehot=None, max_delta_step=None,\n",
              "                               max_depth=None, max_leaves=None,\n",
              "                               min_child_weight=None, missing=nan,\n",
              "                               monotone_constraints=None, n_estimators=250,\n",
              "                               n_jobs=None, num_parallel_tree=None,\n",
              "                               predictor=None, random_state=42, ...))])"
            ],
            "text/html": [
              "<style>#sk-container-id-2 {color: black;background-color: white;}#sk-container-id-2 pre{padding: 0;}#sk-container-id-2 div.sk-toggleable {background-color: white;}#sk-container-id-2 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-2 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-2 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-2 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-2 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-2 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-2 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-2 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-2 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-2 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-2 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-2 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-2 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-2 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-2 div.sk-item {position: relative;z-index: 1;}#sk-container-id-2 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-2 div.sk-item::before, #sk-container-id-2 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-2 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-2 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-2 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-2 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-2 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-2 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-2 div.sk-label-container {text-align: center;}#sk-container-id-2 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-2 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-2\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>Pipeline(steps=[(&#x27;Imputer&#x27;, KNNImputer()),\n",
              "                (&#x27;Oversampler&#x27;, SMOTE(random_state=42, sampling_strategy=1)),\n",
              "                (&#x27;XGBClassifier&#x27;,\n",
              "                 XGBClassifier(base_score=None, booster=None, callbacks=None,\n",
              "                               colsample_bylevel=None, colsample_bynode=None,\n",
              "                               colsample_bytree=None,\n",
              "                               early_stopping_rounds=None,\n",
              "                               enable_categorical=False, eval_metric=None,\n",
              "                               feature_types=None, gamma=0, gpu_id=None,\n",
              "                               grow_policy=None, importance_type=None,\n",
              "                               interaction_constraints=None, learning_rate=0.1,\n",
              "                               max_bin=None, max_cat_threshold=None,\n",
              "                               max_cat_to_onehot=None, max_delta_step=None,\n",
              "                               max_depth=None, max_leaves=None,\n",
              "                               min_child_weight=None, missing=nan,\n",
              "                               monotone_constraints=None, n_estimators=250,\n",
              "                               n_jobs=None, num_parallel_tree=None,\n",
              "                               predictor=None, random_state=42, ...))])</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-2\" type=\"checkbox\" ><label for=\"sk-estimator-id-2\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">Pipeline</label><div class=\"sk-toggleable__content\"><pre>Pipeline(steps=[(&#x27;Imputer&#x27;, KNNImputer()),\n",
              "                (&#x27;Oversampler&#x27;, SMOTE(random_state=42, sampling_strategy=1)),\n",
              "                (&#x27;XGBClassifier&#x27;,\n",
              "                 XGBClassifier(base_score=None, booster=None, callbacks=None,\n",
              "                               colsample_bylevel=None, colsample_bynode=None,\n",
              "                               colsample_bytree=None,\n",
              "                               early_stopping_rounds=None,\n",
              "                               enable_categorical=False, eval_metric=None,\n",
              "                               feature_types=None, gamma=0, gpu_id=None,\n",
              "                               grow_policy=None, importance_type=None,\n",
              "                               interaction_constraints=None, learning_rate=0.1,\n",
              "                               max_bin=None, max_cat_threshold=None,\n",
              "                               max_cat_to_onehot=None, max_delta_step=None,\n",
              "                               max_depth=None, max_leaves=None,\n",
              "                               min_child_weight=None, missing=nan,\n",
              "                               monotone_constraints=None, n_estimators=250,\n",
              "                               n_jobs=None, num_parallel_tree=None,\n",
              "                               predictor=None, random_state=42, ...))])</pre></div></div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-3\" type=\"checkbox\" ><label for=\"sk-estimator-id-3\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">KNNImputer</label><div class=\"sk-toggleable__content\"><pre>KNNImputer()</pre></div></div></div><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-4\" type=\"checkbox\" ><label for=\"sk-estimator-id-4\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">SMOTE</label><div class=\"sk-toggleable__content\"><pre>SMOTE(random_state=42, sampling_strategy=1)</pre></div></div></div><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-5\" type=\"checkbox\" ><label for=\"sk-estimator-id-5\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">XGBClassifier</label><div class=\"sk-toggleable__content\"><pre>XGBClassifier(base_score=None, booster=None, callbacks=None,\n",
              "              colsample_bylevel=None, colsample_bynode=None,\n",
              "              colsample_bytree=None, early_stopping_rounds=None,\n",
              "              enable_categorical=False, eval_metric=None, feature_types=None,\n",
              "              gamma=0, gpu_id=None, grow_policy=None, importance_type=None,\n",
              "              interaction_constraints=None, learning_rate=0.1, max_bin=None,\n",
              "              max_cat_threshold=None, max_cat_to_onehot=None,\n",
              "              max_delta_step=None, max_depth=None, max_leaves=None,\n",
              "              min_child_weight=None, missing=nan, monotone_constraints=None,\n",
              "              n_estimators=250, n_jobs=None, num_parallel_tree=None,\n",
              "              predictor=None, random_state=42, ...)</pre></div></div></div></div></div></div></div>"
            ]
          },
          "metadata": {},
          "execution_count": 80
        }
      ],
      "source": [
        "# Training the pipeline on the training dataset\n",
        "pipeline_model.fit(X_train_final, y_train_final)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 81,
      "metadata": {
        "id": "KDmRC5f3J2M3",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 444
        },
        "outputId": "d00ee847-f9b4-4f7e-a7e0-2e6574c79c08"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 900x300 with 4 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[1mModel performance:\u001b[0m\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7fe22ee07430>"
            ],
            "text/html": [
              "<style type=\"text/css\">\n",
              "#T_6dbb3 th {\n",
              "  max-width: 75px;\n",
              "}\n",
              "</style>\n",
              "<table id=\"T_6dbb3\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th class=\"blank level0\" >&nbsp;</th>\n",
              "      <th id=\"T_6dbb3_level0_col0\" class=\"col_heading level0 col0\" >Accuracy</th>\n",
              "      <th id=\"T_6dbb3_level0_col1\" class=\"col_heading level0 col1\" >Precision</th>\n",
              "      <th id=\"T_6dbb3_level0_col2\" class=\"col_heading level0 col2\" >Recall</th>\n",
              "      <th id=\"T_6dbb3_level0_col3\" class=\"col_heading level0 col3\" >NPV</th>\n",
              "      <th id=\"T_6dbb3_level0_col4\" class=\"col_heading level0 col4\" >Specificity</th>\n",
              "      <th id=\"T_6dbb3_level0_col5\" class=\"col_heading level0 col5\" >F1</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th id=\"T_6dbb3_level0_row0\" class=\"row_heading level0 row0\" >Train</th>\n",
              "      <td id=\"T_6dbb3_row0_col0\" class=\"data row0 col0\" >99.77%</td>\n",
              "      <td id=\"T_6dbb3_row0_col1\" class=\"data row0 col1\" >96.02%</td>\n",
              "      <td id=\"T_6dbb3_row0_col2\" class=\"data row0 col2\" >100.00%</td>\n",
              "      <td id=\"T_6dbb3_row0_col3\" class=\"data row0 col3\" >100.00%</td>\n",
              "      <td id=\"T_6dbb3_row0_col4\" class=\"data row0 col4\" >99.76%</td>\n",
              "      <td id=\"T_6dbb3_row0_col5\" class=\"data row0 col5\" >97.97%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6dbb3_level0_row1\" class=\"row_heading level0 row1\" >Test</th>\n",
              "      <td id=\"T_6dbb3_row1_col0\" class=\"data row1 col0\" >97.72%</td>\n",
              "      <td id=\"T_6dbb3_row1_col1\" class=\"data row1 col1\" >76.42%</td>\n",
              "      <td id=\"T_6dbb3_row1_col2\" class=\"data row1 col2\" >86.17%</td>\n",
              "      <td id=\"T_6dbb3_row1_col3\" class=\"data row1 col3\" >99.17%</td>\n",
              "      <td id=\"T_6dbb3_row1_col4\" class=\"data row1 col4\" >98.41%</td>\n",
              "      <td id=\"T_6dbb3_row1_col5\" class=\"data row1 col5\" >81.00%</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n"
            ]
          },
          "metadata": {}
        }
      ],
      "source": [
        "# Evaluating the pipeline on the test dataset\n",
        "pipeline_model_perf_test = model_performance(pipeline_model, \n",
        "                                             X_train_final, y_train_final,\n",
        "                                             X_test, y_test,\n",
        "                                             verbose=True, sets=['Train', 'Test'])"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "- We trained the pipeline using the full training dataset, which yielded a slight increase in Recall but a small reduction in Precision on Test dataset when compared to the evaluation of the model that was previously trained on a preliminary dataset, where the original training data had been split into separate training and validation portions."
      ],
      "metadata": {
        "id": "BTTiiXApOB_1"
      }
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "c5hPmHyR4jaw"
      },
      "source": [
        "#Business Insights and Conclusions"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "XBeJdbA5J_ji"
      },
      "source": [
        "* Minimizing **False Negatives** is vital because of their high associated cost. As a result, we should focus on models with strong Recall and F1 scores. After tuning, the best models were:\n",
        "  - XGBClassifier with undersampled data,\n",
        "  - GradientBoostingClassifier with undersampled data,\n",
        "  - RandomForestClassifier with undersampled data.\n",
        "\n",
        "* These models, trained on undersampled data, have high Recall but low Precision and F1 scores. This indicates a high Type I error rate, which means they produce many False Positive (FP) predictions. FPs are detections where no failure occurs, resulting in inspection costs.\n",
        "\n",
        "* Although inspections are the least expensive operations, a high number of errors can still lead to significant overall costs. Additionally, resources needed for costlier operations, like replacement and repair, may be tied up in inspections. This could cause delays in urgent and important operations and additional expenses.\n",
        "\n",
        "* Therefore, we need to find a balance between Recall and Precision. Unfortunately, we don't have specific information about the costs of various operations. We only know that repairing a generator is much cheaper than replacing it, and inspection costs are lower than repair costs.\n",
        "\n",
        "* Among all evaluated models, the **XGBClassifier** with **oversampled** data achieved the best balance between Recall and F1 score after tuning, making it the recommended model for production.\n",
        "  * This model also showed excellent performance on test data, with a strong **Recall of 85.11%** and an **F1 score of 81.36%**, indicating effective generalization.\n",
        "  * On the test dataset, the pipeline achieves a Recall of 86.17% and an F1 score of 81% when trained on the entire training set.\n",
        "\n",
        "* In conclusion, the best model seems to be the **XGBClassifier tuned with oversampled data**. It generalizes well on test data and has the best overall performance for both training and validation data.\n",
        "\n",
        "* The top four important features are V36, V26, V18, and V14. It is recommended to further analyze each feature to understand the high number of outliers in the dataset.\n",
        "\n",
        "* In addition, we have designed a pipeline that, when implemented in future scenarios, can decrease processing time and minimize the risk of human errors at every step of the process."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "id": "sV6Ft_y9wpD0",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "cfd3bf10-e9b2-4488-eaac-0de52c4d8036"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[NbConvertApp] Converting notebook /content/project_6_at.ipynb to html\n",
            "[NbConvertApp] Writing 5839228 bytes to /content/project_6_at.html\n"
          ]
        }
      ],
      "source": [
        "!jupyter nbconvert --to html /content/project_6_at.ipynb"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "VB3eO21n_sgt"
      },
      "source": [
        "***"
      ]
    }
  ],
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "display_name": "Python 3",
      "language": "python",
      "name": "python3"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.8.8"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}