modeling.ipynb

{
  "cells": [
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {},
      "outputs": [],
      "source": [
        "import pandas as pd"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "px3kUhbUSAPy"
      },
      "source": [
        "# Reading cleaned dataset file"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "id": "nJbbTmFiSAPz"
      },
      "outputs": [],
      "source": [
        "df = pd.read_csv('./kdd-cleaned.csv')"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "8NyYDtazSAPz"
      },
      "source": [
        "# DELIVERABLE TWO STARTS FROM HERE\n",
        "\n",
        "- Apply at-least 3 Machine Learning algorithms.\n",
        "- Compare results of all models.\n",
        "- How results helped in addressing the problem?"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 226
        },
        "id": "yUx1ewO_SAPz",
        "outputId": "375ed9cc-a16a-4277-8e6a-9a33b62c0355"
      },
      "outputs": [
        {
          "data": {
            "text/html": [
              "<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>duration</th>\n",
              "      <th>protocol_type</th>\n",
              "      <th>flag</th>\n",
              "      <th>src_bytes</th>\n",
              "      <th>dst_bytes</th>\n",
              "      <th>land</th>\n",
              "      <th>wrong_fragment</th>\n",
              "      <th>urgent</th>\n",
              "      <th>hot</th>\n",
              "      <th>num_failed_logins</th>\n",
              "      <th>...</th>\n",
              "      <th>rerror_rate</th>\n",
              "      <th>same_srv_rate</th>\n",
              "      <th>diff_srv_rate</th>\n",
              "      <th>srv_diff_host_rate</th>\n",
              "      <th>dst_host_count</th>\n",
              "      <th>dst_host_srv_count</th>\n",
              "      <th>dst_host_diff_srv_rate</th>\n",
              "      <th>dst_host_same_src_port_rate</th>\n",
              "      <th>dst_host_srv_diff_host_rate</th>\n",
              "      <th>class</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0.0</td>\n",
              "      <td>tcp</td>\n",
              "      <td>SF</td>\n",
              "      <td>491.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>150.0</td>\n",
              "      <td>25.0</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>normal</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0.0</td>\n",
              "      <td>udp</td>\n",
              "      <td>SF</td>\n",
              "      <td>146.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.08</td>\n",
              "      <td>0.15</td>\n",
              "      <td>0.0</td>\n",
              "      <td>255.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.02</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>normal</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0.0</td>\n",
              "      <td>tcp</td>\n",
              "      <td>S0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.05</td>\n",
              "      <td>0.07</td>\n",
              "      <td>0.0</td>\n",
              "      <td>255.0</td>\n",
              "      <td>26.0</td>\n",
              "      <td>0.05</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>anomaly</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0.0</td>\n",
              "      <td>tcp</td>\n",
              "      <td>SF</td>\n",
              "      <td>232.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>30.0</td>\n",
              "      <td>255.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.04</td>\n",
              "      <td>normal</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0.0</td>\n",
              "      <td>tcp</td>\n",
              "      <td>SF</td>\n",
              "      <td>199.0</td>\n",
              "      <td>420.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>255.0</td>\n",
              "      <td>255.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>normal</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 33 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "   duration protocol_type flag  src_bytes  dst_bytes  land  wrong_fragment  \\\n",
              "0       0.0           tcp   SF      491.0        0.0     0             0.0   \n",
              "1       0.0           udp   SF      146.0        0.0     0             0.0   \n",
              "2       0.0           tcp   S0        0.0        0.0     0             0.0   \n",
              "3       0.0           tcp   SF      232.0        0.0     0             0.0   \n",
              "4       0.0           tcp   SF      199.0      420.0     0             0.0   \n",
              "\n",
              "   urgent  hot  num_failed_logins  ...  rerror_rate  same_srv_rate  \\\n",
              "0     0.0  0.0                0.0  ...          0.0           1.00   \n",
              "1     0.0  0.0                0.0  ...          0.0           0.08   \n",
              "2     0.0  0.0                0.0  ...          0.0           0.05   \n",
              "3     0.0  0.0                0.0  ...          0.0           1.00   \n",
              "4     0.0  0.0                0.0  ...          0.0           1.00   \n",
              "\n",
              "   diff_srv_rate  srv_diff_host_rate  dst_host_count  dst_host_srv_count  \\\n",
              "0           0.00                 0.0           150.0                25.0   \n",
              "1           0.15                 0.0           255.0                 1.0   \n",
              "2           0.07                 0.0           255.0                26.0   \n",
              "3           0.00                 0.0            30.0               255.0   \n",
              "4           0.00                 0.0           255.0               255.0   \n",
              "\n",
              "   dst_host_diff_srv_rate  dst_host_same_src_port_rate  \\\n",
              "0                    0.03                         0.00   \n",
              "1                    0.02                         0.00   \n",
              "2                    0.05                         0.00   \n",
              "3                    0.00                         0.03   \n",
              "4                    0.00                         0.00   \n",
              "\n",
              "   dst_host_srv_diff_host_rate    class  \n",
              "0                         0.00   normal  \n",
              "1                         0.00   normal  \n",
              "2                         0.00  anomaly  \n",
              "3                         0.04   normal  \n",
              "4                         0.00   normal  \n",
              "\n",
              "[5 rows x 33 columns]"
            ]
          },
          "execution_count": 3,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "df.head()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "GM1_OUPcSAPz"
      },
      "source": [
        "# Some Features Analysis"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "z8Co4B_jSAP0",
        "outputId": "fec41ab8-9f94-4c5d-be5d-21b2692b77a3"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "   flag  Class_0_Count-Normal  Class_1_Count-Suspicious  Total_Count\n",
            "0   OTH                  33.0                       7.0         40.0\n",
            "1   REJ                7748.0                    2504.0      10252.0\n",
            "2  RSTO                1266.0                     142.0       1408.0\n",
            "3  RSTR                 816.0                       3.0        819.0\n",
            "4    S0               34470.0                     329.0      34799.0\n",
            "5    S1                   2.0                     317.0        319.0\n",
            "6    S2                   2.0                      44.0         46.0\n",
            "7    S3                   0.0                      29.0         29.0\n",
            "8    SF                8809.0                   55066.0      63875.0\n",
            "9    SH                 269.0                       0.0        269.0\n"
          ]
        }
      ],
      "source": [
        "# Checking relationship of flag categories with class label\n",
        "\n",
        "class_counts = df.groupby(['flag', 'class']).size().reset_index(name='count')\n",
        "class_pivot = class_counts.pivot(index='flag', columns='class', values='count').fillna(0)\n",
        "\n",
        "class_pivot = class_pivot.reset_index()\n",
        "\n",
        "class_pivot.columns.name = None\n",
        "class_pivot.rename(columns={class_pivot.columns[1]: 'Class_0_Count-Normal',\n",
        "                            class_pivot.columns[2]: 'Class_1_Count-Suspicious'}, inplace=True)\n",
        "\n",
        "class_pivot['Total_Count'] = class_pivot['Class_0_Count-Normal'] + class_pivot['Class_1_Count-Suspicious']\n",
        "pd.set_option('display.max_rows', None)  # Show all rows\n",
        "pd.set_option('display.max_columns', None)  # Show all columns\n",
        "\n",
        "print(class_pivot)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "TqXAV3G6SAP0"
      },
      "source": [
        "# Feature Mapping (cat to num)\n",
        "\n",
        " - flag\n",
        " - protocol_type"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {
        "id": "kfoKSohQSAP0"
      },
      "outputs": [],
      "source": [
        "pmap = {'icmp':0, 'tcp':1, 'udp':2}\n",
        "df['protocol_type'] = df['protocol_type'].map(pmap)\n",
        "\n",
        "fmap = {'SF':0, 'S0':1, 'REJ':2, 'RSTR':3, 'RSTO':4, 'SH':5, 'S1':6, 'S2':7, 'RSTOS0':8, 'S3':9, 'OTH':10}\n",
        "df['flag'] = df['flag'].map(fmap)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "X3qFj4HeSAP0"
      },
      "source": [
        "# X/y split"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {
        "id": "Gm6AkQcFSAP0"
      },
      "outputs": [],
      "source": [
        "X = df.drop(columns=['class'])\n",
        "y = df['class']"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "vlkG_CTuSAP1"
      },
      "source": [
        "### Imports For data split and feature scaling"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {
        "id": "_BwsDlubSAP1"
      },
      "outputs": [],
      "source": [
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.preprocessing import MinMaxScaler"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {
        "id": "n2P-W-EoSAP1"
      },
      "outputs": [],
      "source": [
        "scaler = MinMaxScaler()\n",
        "X = scaler.fit_transform(X)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "PWaNkrukSAP1"
      },
      "source": [
        "### Train-Test Split = 70/30"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "gXpKo0PvSAP1",
        "outputId": "e1eed2c5-493b-425d-b2b1-f5cc0d8ceebb"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Training set size: (78299, 32)\n",
            "Test set size: (33557, 32)\n"
          ]
        }
      ],
      "source": [
        "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, random_state=42, stratify=y)\n",
        "\n",
        "print(f\"Training set size: {X_train.shape}\")\n",
        "print(f\"Test set size: {X_test.shape}\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "FFs3Qk6SSAP2"
      },
      "source": [
        "# Import for models and metrices"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {
        "id": "Y6XD5OLnSAP2"
      },
      "outputs": [],
      "source": [
        "# METRICES and FOLDS\n",
        "from sklearn.model_selection import cross_validate, StratifiedKFold\n",
        "from sklearn.metrics import confusion_matrix, ConfusionMatrixDisplay, accuracy_score, precision_score, recall_score, f1_score, roc_curve, auc\n",
        "\n",
        "# VISUALIZATION\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "# MODELS\n",
        "from sklearn.naive_bayes import GaussianNB\n",
        "from sklearn.tree import DecisionTreeClassifier\n",
        "from sklearn.ensemble import RandomForestClassifier, GradientBoostingClassifier\n",
        "from sklearn.linear_model import LogisticRegression\n",
        "from sklearn.svm import SVC\n",
        "\n",
        "# OTHERS\n",
        "import time\n",
        "import numpy as np"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "IMfjU18lSAP3"
      },
      "source": [
        "> common variables and structures for help in code + kfold cross validator initialization"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "metadata": {
        "id": "Jo-vZOviSAP3"
      },
      "outputs": [],
      "source": [
        "scoring = {\n",
        "    'accuracy': 'accuracy',\n",
        "    'precision': 'precision_weighted',\n",
        "    'recall': 'recall_weighted',\n",
        "    'f1': 'f1_weighted'\n",
        "}\n",
        "# training time for all models\n",
        "TRAINING_TIME = {}\n",
        "# StratifiedKFold for consistent cross-validation\n",
        "# 5 folds\n",
        "kfold = StratifiedKFold(n_splits=5, shuffle=True, random_state=42)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "KpkMuQ5ZSAP4"
      },
      "source": [
        "# Understanding `compute_train_metrics` and `compute_test_metrics`\n",
        "\n",
        "## Training Metrics (`compute_train_metrics`)\n",
        "- Uses `cross_validate`, which splits the data, trains, and validates the model internally across k-folds.\n",
        "- No need to call `model.fit` explicitly, as `cross_validate` handles it automatically.\n",
        "\n",
        "## Test Metrics (`compute_test_metrics`)\n",
        "- Requires the model to be explicitly trained using `model.fit`.\n",
        "- Evaluates the trained model on the test set using metrics like accuracy, precision, recall, and F1 score.\n",
        "\n",
        "## Key Workflow\n",
        "1. **Training Metrics**: Computed via cross-validation (no manual fitting required).\n",
        "2. **Test Metrics**: Computed after fitting the model on the entire training set.\n",
        "\n",
        "These functions are used in each model evaluation"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 12,
      "metadata": {
        "id": "Y8NqsQWESAP4"
      },
      "outputs": [],
      "source": [
        "\"\"\"\n",
        "Below function calculates values of different train metrices for\n",
        "certain model after apply k-fold cross validation\n",
        "\"\"\"\n",
        "def compute_train_metrics(model, X_train, y_train):\n",
        "    scores = cross_validate(model, X_train, y_train, cv=kfold, scoring=scoring)\n",
        "    mean_train_scores = {metric: np.mean(scores[f'test_{metric}']) for metric in scoring}\n",
        "    return mean_train_scores\n",
        "\n",
        "\"\"\"\n",
        "Below function calculates values of different test metrices for\n",
        "certain model and plots its confusion matrix\n",
        "\"\"\"\n",
        "def compute_test_metrics_and_plot_cm(model, X_test, y_test, model_name):\n",
        "    y_test_pred = model.predict(X_test)\n",
        "    test_metrics = {\n",
        "        'accuracy': accuracy_score(y_test, y_test_pred),\n",
        "        'precision': precision_score(y_test, y_test_pred, average='weighted'),\n",
        "        'recall': recall_score(y_test, y_test_pred, average='weighted'),\n",
        "        'f1': f1_score(y_test, y_test_pred, average='weighted')\n",
        "    }\n",
        "    cm = confusion_matrix(y_test, y_test_pred)\n",
        "    disp = ConfusionMatrixDisplay(confusion_matrix=cm, display_labels=model.classes_)\n",
        "    disp.plot(cmap='Blues', colorbar=True)\n",
        "    plt.title(f'{model_name} Confusion Matrix')\n",
        "    plt.show()\n",
        "    return test_metrics"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "I9HJcJQpSAP4"
      },
      "source": [
        "### Function: `plot_metrics`\n",
        "\n",
        "This function creates a bar chart to compare training and testing metrics for any model.\n",
        "\n",
        "#### What it Does:\n",
        "- Takes training and testing metrics as input.\n",
        "- Plots bars for each metric (e.g., accuracy, precision).\n",
        "- Labels each bar with its exact value for clarity.\n",
        "- Customizes colors and layout for easy understanding.\n",
        "\n",
        "#### Output:\n",
        "- A clear chart showing how the model performed on both training and testing data.\n",
        "\n",
        "#### Example Use:\n",
        "```python\n",
        "plot_metrics(train_metrics, test_metrics, \"Gaussian NB\")\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 13,
      "metadata": {
        "id": "MH9769FESAP4"
      },
      "outputs": [],
      "source": [
        "\"\"\"\n",
        "Below function plots train and test metrics for different models,\n",
        "it is a common function that will be used for all models\n",
        "\"\"\"\n",
        "def plot_metrics(train_metrics, test_metrics, model_name):\n",
        "    metrics = list(train_metrics.keys())\n",
        "    train_values = list(train_metrics.values())\n",
        "    test_values = [test_metrics[metric] for metric in metrics]\n",
        "\n",
        "    x = np.arange(len(metrics))  # Label locations\n",
        "    width = 0.45  # Bar width\n",
        "\n",
        "    fig, ax = plt.subplots()\n",
        "    train_bars = ax.bar(x - width / 2, train_values, width, label='Train', color='skyblue')\n",
        "    test_bars = ax.bar(x + width / 2, test_values, width, label='Test', color='orange')\n",
        "\n",
        "    for bar in train_bars:\n",
        "        height = bar.get_height()\n",
        "        ax.annotate(f'{height:.5f}',\n",
        "                    xy=(bar.get_x() + bar.get_width() / 2, height),\n",
        "                    xytext=(0, 3),\n",
        "                    textcoords=\"offset points\",\n",
        "                    ha='center', va='bottom')\n",
        "\n",
        "    for bar in test_bars:\n",
        "        height = bar.get_height()\n",
        "        ax.annotate(f'{height:.5f}',\n",
        "                    xy=(bar.get_x() + bar.get_width() / 2, height),\n",
        "                    xytext=(0, 3),\n",
        "                    textcoords=\"offset points\",\n",
        "                    ha='center', va='bottom')\n",
        "\n",
        "    ax.set_xlabel('Metrics')\n",
        "    ax.set_ylabel('Scores')\n",
        "    ax.set_title(f'{model_name} Train vs Test Metrics')\n",
        "    ax.set_xticks(x)\n",
        "    ax.set_xticklabels([metric.capitalize() for metric in metrics])\n",
        "    ax.legend()\n",
        "\n",
        "    plt.ylim(0, 1.3)\n",
        "    plt.tight_layout()\n",
        "    plt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "cEARDyLoWLHf"
      },
      "source": [
        "# FUNCTION TO PLOT ROC_CURVE"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 14,
      "metadata": {
        "id": "u0cRZDfuWKZH"
      },
      "outputs": [],
      "source": [
        "def plot_roc_curve(model, X_test, y_test, model_name):\n",
        "    if hasattr(model, \"predict_proba\"):\n",
        "        y_scores = model.predict_proba(X_test)[:, 1]\n",
        "    elif hasattr(model, \"decision_function\"):\n",
        "        y_scores = model.decision_function(X_test)\n",
        "    else:\n",
        "        raise ValueError(f\"{model_name} does not support probability or decision score predictions.\")\n",
        "\n",
        "    fpr, tpr, _ = roc_curve(y_test, y_scores)\n",
        "    roc_auc = auc(fpr, tpr)\n",
        "\n",
        "    plt.figure(figsize=(8, 6))\n",
        "    plt.plot(fpr, tpr, color='darkorange', lw=2, label=f'ROC Curve (AUC = {roc_auc:.4f})')\n",
        "    plt.plot([0, 1], [0, 1], color='navy', lw=2, linestyle='--', label='Chance Line')\n",
        "    plt.xlim([0.0, 1.0])\n",
        "    plt.ylim([0.0, 1.05])\n",
        "    plt.xlabel('False Positive Rate')\n",
        "    plt.ylabel('True Positive Rate')\n",
        "    plt.title(f'{model_name} ROC Curve')\n",
        "    plt.legend(loc='lower right')\n",
        "    plt.grid()\n",
        "    plt.tight_layout()\n",
        "    plt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "r64kAvc1SAP5"
      },
      "source": [
        "# MODEL TRAINING\n",
        "\n",
        "> Models used:\n",
        "- **Gaussian Naive Bayes (GNB):** A simple model that predicts by assuming all features are independent of each other.\n",
        "- **Decision Tree (DT):** A model that splits data into branches to make decisions based on features.\n",
        "- **Random Forest (RF):** A collection of many decision trees that work together to improve accuracy.\n",
        "- **Support Vector Machine (SVM):** A method that draws the best line or boundary to separate different classes.\n",
        "- **Logistic Regression (LR):** A model that predicts categories using a straight line and probability.\n",
        "- **Gradient Boosting Classifier (GBC):** A technique that builds models one by one, each trying to fix the mistakes of the previous one.\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "dhoiEMMXSAP5"
      },
      "source": [
        "# LOGISTIC REGRESSION"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 15,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 472
        },
        "id": "2-SWzRnxSAP5",
        "outputId": "574b6c5d-cf61-46a2-fbaf-cde3453b2da9"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 640x480 with 2 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "lr = LogisticRegression(random_state=42, max_iter=1000)\n",
        "\n",
        "start_time = time.time()\n",
        "train_metrics = compute_train_metrics(lr, X_train, y_train)\n",
        "TRAINING_TIME['Logistic Regression'] = time.time() - start_time\n",
        "\n",
        "lr.fit(X_train, y_train)\n",
        "test_metrics = compute_test_metrics_and_plot_cm(lr, X_test, y_test,\"LR\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 16,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 487
        },
        "id": "aOUZAhzfSAP5",
        "outputId": "2f9dd4fe-6f7e-49f0-d96f-7dd432bbd2d5"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "plot_metrics(train_metrics, test_metrics, \"Logistic Regression\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 17,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 607
        },
        "id": "th-pRg_DWrMW",
        "outputId": "322eb247-2bb3-4ca7-ec76-39d931577b54"
      },
      "outputs": [
        {
          "ename": "ValueError",
          "evalue": "y_true takes value in {'anomaly', 'normal'} and pos_label is not specified: either make y_true take value in {0, 1} or {-1, 1} or pass pos_label explicitly.",
          "output_type": "error",
          "traceback": [
            "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[1;31mValueError\u001b[0m                                Traceback (most recent call last)",
            "Cell \u001b[1;32mIn[17], line 1\u001b[0m\n\u001b[1;32m----> 1\u001b[0m \u001b[43mplot_roc_curve\u001b[49m\u001b[43m(\u001b[49m\u001b[43mlr\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mX_test\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43my_test\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mLogistic Regression\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n",
            "Cell \u001b[1;32mIn[14], line 9\u001b[0m, in \u001b[0;36mplot_roc_curve\u001b[1;34m(model, X_test, y_test, model_name)\u001b[0m\n\u001b[0;32m      6\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m      7\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mmodel_name\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m does not support probability or decision score predictions.\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m----> 9\u001b[0m fpr, tpr, _ \u001b[38;5;241m=\u001b[39m \u001b[43mroc_curve\u001b[49m\u001b[43m(\u001b[49m\u001b[43my_test\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43my_scores\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m     10\u001b[0m roc_auc \u001b[38;5;241m=\u001b[39m auc(fpr, tpr)\n\u001b[0;32m     12\u001b[0m plt\u001b[38;5;241m.\u001b[39mfigure(figsize\u001b[38;5;241m=\u001b[39m(\u001b[38;5;241m8\u001b[39m, \u001b[38;5;241m6\u001b[39m))\n",
            "File \u001b[1;32mc:\\Python312\\Lib\\site-packages\\sklearn\\utils\\_param_validation.py:213\u001b[0m, in \u001b[0;36mvalidate_params.<locals>.decorator.<locals>.wrapper\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m    207\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m    208\u001b[0m     \u001b[38;5;28;01mwith\u001b[39;00m config_context(\n\u001b[0;32m    209\u001b[0m         skip_parameter_validation\u001b[38;5;241m=\u001b[39m(\n\u001b[0;32m    210\u001b[0m             prefer_skip_nested_validation \u001b[38;5;129;01mor\u001b[39;00m global_skip_validation\n\u001b[0;32m    211\u001b[0m         )\n\u001b[0;32m    212\u001b[0m     ):\n\u001b[1;32m--> 213\u001b[0m         \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    214\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m InvalidParameterError \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[0;32m    215\u001b[0m     \u001b[38;5;66;03m# When the function is just a wrapper around an estimator, we allow\u001b[39;00m\n\u001b[0;32m    216\u001b[0m     \u001b[38;5;66;03m# the function to delegate validation to the estimator, but we replace\u001b[39;00m\n\u001b[0;32m    217\u001b[0m     \u001b[38;5;66;03m# the name of the estimator by the name of the function in the error\u001b[39;00m\n\u001b[0;32m    218\u001b[0m     \u001b[38;5;66;03m# message to avoid confusion.\u001b[39;00m\n\u001b[0;32m    219\u001b[0m     msg \u001b[38;5;241m=\u001b[39m re\u001b[38;5;241m.\u001b[39msub(\n\u001b[0;32m    220\u001b[0m         \u001b[38;5;124mr\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mparameter of \u001b[39m\u001b[38;5;124m\\\u001b[39m\u001b[38;5;124mw+ must be\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[0;32m    221\u001b[0m         \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mparameter of \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mfunc\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__qualname__\u001b[39m\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m must be\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[0;32m    222\u001b[0m         \u001b[38;5;28mstr\u001b[39m(e),\n\u001b[0;32m    223\u001b[0m     )\n",
            "File \u001b[1;32mc:\\Python312\\Lib\\site-packages\\sklearn\\metrics\\_ranking.py:1145\u001b[0m, in \u001b[0;36mroc_curve\u001b[1;34m(y_true, y_score, pos_label, sample_weight, drop_intermediate)\u001b[0m\n\u001b[0;32m   1043\u001b[0m \u001b[38;5;129m@validate_params\u001b[39m(\n\u001b[0;32m   1044\u001b[0m     {\n\u001b[0;32m   1045\u001b[0m         \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124my_true\u001b[39m\u001b[38;5;124m\"\u001b[39m: [\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124marray-like\u001b[39m\u001b[38;5;124m\"\u001b[39m],\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m   1054\u001b[0m     y_true, y_score, \u001b[38;5;241m*\u001b[39m, pos_label\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, sample_weight\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, drop_intermediate\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m\n\u001b[0;32m   1055\u001b[0m ):\n\u001b[0;32m   1056\u001b[0m \u001b[38;5;250m    \u001b[39m\u001b[38;5;124;03m\"\"\"Compute Receiver operating characteristic (ROC).\u001b[39;00m\n\u001b[0;32m   1057\u001b[0m \n\u001b[0;32m   1058\u001b[0m \u001b[38;5;124;03m    Note: this implementation is restricted to the binary classification task.\u001b[39;00m\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m   1143\u001b[0m \u001b[38;5;124;03m    array([ inf, 0.8 , 0.4 , 0.35, 0.1 ])\u001b[39;00m\n\u001b[0;32m   1144\u001b[0m \u001b[38;5;124;03m    \"\"\"\u001b[39;00m\n\u001b[1;32m-> 1145\u001b[0m     fps, tps, thresholds \u001b[38;5;241m=\u001b[39m \u001b[43m_binary_clf_curve\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m   1146\u001b[0m \u001b[43m        \u001b[49m\u001b[43my_true\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43my_score\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mpos_label\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mpos_label\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43msample_weight\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43msample_weight\u001b[49m\n\u001b[0;32m   1147\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m   1149\u001b[0m     \u001b[38;5;66;03m# Attempt to drop thresholds corresponding to points in between and\u001b[39;00m\n\u001b[0;32m   1150\u001b[0m     \u001b[38;5;66;03m# collinear with other points. These are always suboptimal and do not\u001b[39;00m\n\u001b[0;32m   1151\u001b[0m     \u001b[38;5;66;03m# appear on a plotted ROC curve (and thus do not affect the AUC).\u001b[39;00m\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m   1156\u001b[0m     \u001b[38;5;66;03m# but does not drop more complicated cases like fps = [1, 3, 7],\u001b[39;00m\n\u001b[0;32m   1157\u001b[0m     \u001b[38;5;66;03m# tps = [1, 2, 4]; there is no harm in keeping too many thresholds.\u001b[39;00m\n\u001b[0;32m   1158\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m drop_intermediate \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(fps) \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m2\u001b[39m:\n",
            "File \u001b[1;32mc:\\Python312\\Lib\\site-packages\\sklearn\\metrics\\_ranking.py:834\u001b[0m, in \u001b[0;36m_binary_clf_curve\u001b[1;34m(y_true, y_score, pos_label, sample_weight)\u001b[0m\n\u001b[0;32m    831\u001b[0m     y_score \u001b[38;5;241m=\u001b[39m y_score[nonzero_weight_mask]\n\u001b[0;32m    832\u001b[0m     sample_weight \u001b[38;5;241m=\u001b[39m sample_weight[nonzero_weight_mask]\n\u001b[1;32m--> 834\u001b[0m pos_label \u001b[38;5;241m=\u001b[39m \u001b[43m_check_pos_label_consistency\u001b[49m\u001b[43m(\u001b[49m\u001b[43mpos_label\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43my_true\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    836\u001b[0m \u001b[38;5;66;03m# make y_true a boolean vector\u001b[39;00m\n\u001b[0;32m    837\u001b[0m y_true \u001b[38;5;241m=\u001b[39m y_true \u001b[38;5;241m==\u001b[39m pos_label\n",
            "File \u001b[1;32mc:\\Python312\\Lib\\site-packages\\sklearn\\utils\\validation.py:2503\u001b[0m, in \u001b[0;36m_check_pos_label_consistency\u001b[1;34m(pos_label, y_true)\u001b[0m\n\u001b[0;32m   2495\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m classes\u001b[38;5;241m.\u001b[39mdtype\u001b[38;5;241m.\u001b[39mkind \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mOUS\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m (\n\u001b[0;32m   2496\u001b[0m         np\u001b[38;5;241m.\u001b[39marray_equal(classes, [\u001b[38;5;241m0\u001b[39m, \u001b[38;5;241m1\u001b[39m])\n\u001b[0;32m   2497\u001b[0m         \u001b[38;5;129;01mor\u001b[39;00m np\u001b[38;5;241m.\u001b[39marray_equal(classes, [\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m, \u001b[38;5;241m1\u001b[39m])\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m   2500\u001b[0m         \u001b[38;5;129;01mor\u001b[39;00m np\u001b[38;5;241m.\u001b[39marray_equal(classes, [\u001b[38;5;241m1\u001b[39m])\n\u001b[0;32m   2501\u001b[0m     ):\n\u001b[0;32m   2502\u001b[0m         classes_repr \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m, \u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;241m.\u001b[39mjoin([\u001b[38;5;28mrepr\u001b[39m(c) \u001b[38;5;28;01mfor\u001b[39;00m c \u001b[38;5;129;01min\u001b[39;00m classes\u001b[38;5;241m.\u001b[39mtolist()])\n\u001b[1;32m-> 2503\u001b[0m         \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[0;32m   2504\u001b[0m             \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124my_true takes value in \u001b[39m\u001b[38;5;130;01m{{\u001b[39;00m\u001b[38;5;132;01m{\u001b[39;00mclasses_repr\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;130;01m}}\u001b[39;00m\u001b[38;5;124m and pos_label is not \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m   2505\u001b[0m             \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mspecified: either make y_true take value in \u001b[39m\u001b[38;5;124m{\u001b[39m\u001b[38;5;124m0, 1} or \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m   2506\u001b[0m             \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m{\u001b[39m\u001b[38;5;124m-1, 1} or pass pos_label explicitly.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m   2507\u001b[0m         )\n\u001b[0;32m   2508\u001b[0m     pos_label \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1\u001b[39m\n\u001b[0;32m   2510\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m pos_label\n",
            "\u001b[1;31mValueError\u001b[0m: y_true takes value in {'anomaly', 'normal'} and pos_label is not specified: either make y_true take value in {0, 1} or {-1, 1} or pass pos_label explicitly."
          ]
        }
      ],
      "source": [
        "plot_roc_curve(lr, X_test, y_test, \"Logistic Regression\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ZL1hK3c8SAP6"
      },
      "source": [
        "# DECISION TREES"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 97,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 472
        },
        "id": "SOloHa4ySAP6",
        "outputId": "dca3756f-40d0-4a5b-a5b2-c31e58a305c4"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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BiIjkgUMSksj76YmIiCpJfHw8+vXrB0dHRygUCkRGRpark5KSgv79+0OtVsPGxgbt27dHenq6eD4/Px/jx49H3bp1UatWLQwaNAgZGRl6baSnp6Nv376oWbMm7O3tMW3aNBQXF+vViYuLwwsvvABLS0s0bdoUERERRj8PEwYiIpKHsiEJKYcR8vLy4OXlhTVr1jz0/O+//47OnTvDzc0NcXFxOHPmDObMmQMrKyuxzuTJk7F3717s3LkThw4dwvXr1zFw4EDxfElJCfr27YvCwkIcO3YMmzZtQkREBEJCQsQ6aWlp6Nu3L7p3746kpCRMmjQJI0eOxI8//mjcj08QBMGoK54gOp0OarUalp6joDBXVnc4RJXi9onV1R0CUaXR6XRwqKtGTk4OVCpVpd1DrVbDsvt8KCysDF/wCEJxPgoOhjxWrAqFArt378aAAQPEssGDB6NGjRr48ssvH3pNTk4O6tevj61bt+KNN94AAJw/fx7u7u5ISEhAx44d8cMPP+C1117D9evX4eDgAAAIDw/HjBkzcPPmTSiVSsyYMQP79u1DcnKy3r2zs7Oxf//+Cj8DexiIiEgeqriH4d+UlpZi3759aN68OXx9fWFvb48OHTroDVskJiaiqKgIPj4+YpmbmxucnZ2RkJAAAEhISICnp6eYLACAr68vdDodzp07J9Z5sI2yOmVtVBQTBiIiIiPodDq9o6CgwOg2MjMzkZubi//+97/o1asXDhw4gNdffx0DBw7EoUOHAABarRZKpRK2trZ61zo4OECr1Yp1HkwWys6Xnfu3OjqdDvfu3atwzEwYiIhIHspWSUg5ADg5OUGtVotHWFiY0aGUlpYCAPz8/DB58mS0bt0aM2fOxGuvvYbw8HCTPrapcFklERHJg4n2Ybh69areHAZLS0ujm6pXrx4sLCzg4eGhV+7u7o4jR44AADQaDQoLC5Gdna3Xy5CRkQGNRiPW+eWXX/TaKFtF8WCdf66syMjIgEqlgrW1dYVjZg8DERGREVQqld7xOAmDUqlE+/btkZqaqld+4cIFuLi4AADatm2LGjVqICYmRjyfmpqK9PR0eHt7AwC8vb1x9uxZZGZminWio6OhUqnEZMTb21uvjbI6ZW1UFHsYiIhIJiRu3GTk79i5ubm4dOmS+DktLQ1JSUmws7ODs7Mzpk2bhrfeegtdu3ZF9+7dsX//fuzduxdxcXEAALVajcDAQAQHB8POzg4qlQoTJkyAt7c3OnbsCADo2bMnPDw88M4772DhwoXQarWYPXs2xo8fLyYyY8aMwerVqzF9+nSMGDECsbGx2LFjB/bt22fU8zBhICIieajiraFPnjyJ7t27i5+Dg4MBAAEBAYiIiMDrr7+O8PBwhIWF4f3330eLFi3wzTffoHPnzuI1y5Ytg5mZGQYNGoSCggL4+vris88+E8+bm5sjKioKY8eOhbe3N2xsbBAQEID58+eLdVxdXbFv3z5MnjwZK1asQMOGDbF+/Xr4+voa9/jch4HoycZ9GOhZVqX7MLz6KRQ1JOzDUJSPgugZlRrrk4w9DEREJA8KhcR3SfDlU0RERM8+vnxKEnk/PREREVUIexiIiEgeqnjS47OGCQMREckDhyQkYcJARETywB4GSeSdLhEREVGFsIeBiIjkgUMSkjBhICIieeCQhCTyTpeIiIioQtjDQEREsqBQKKBgD8NjY8JARESywIRBGg5JEBERkUHsYSAiInlQ/H1IuV7GmDAQEZEscEhCGg5JEBERkUHsYSAiIllgD4M0TBiIiEgWmDBIw4SBiIhkgQmDNJzDQERERAaxh4GIiOSByyolYcJARESywCEJaTgkQURERAaxh4GIiGTh/tutpfQwmC6WpxETBiIikgUFJA5JyDxj4JAEERERGcQeBiIikgVOepSGCQMREckDl1VKwiEJIiIiMog9DEREJA8ShyQEDkkQERE9+6TOYZC2wuLpx4SBiIhkgQmDNJzDQEREVAni4+PRr18/ODo6QqFQIDIy8pF1x4wZA4VCgeXLl+uVZ2Vlwd/fHyqVCra2tggMDERubq5enTNnzqBLly6wsrKCk5MTFi5cWK79nTt3ws3NDVZWVvD09MT3339v9PMwYSAiInlQmOAwQl5eHry8vLBmzZp/rbd79278/PPPcHR0LHfO398f586dQ3R0NKKiohAfH4/Ro0eL53U6HXr27AkXFxckJiZi0aJFCA0Nxbp168Q6x44dw5AhQxAYGIjTp09jwIABGDBgAJKTk416Hg5JEBGRLFT1kETv3r3Ru3fvf63z559/YsKECfjxxx/Rt29fvXMpKSnYv38/Tpw4gXbt2gEAVq1ahT59+mDx4sVwdHTEli1bUFhYiA0bNkCpVKJly5ZISkrC0qVLxcRixYoV6NWrF6ZNmwYAWLBgAaKjo7F69WqEh4dX+HnYw0BERGQEnU6ndxQUFDxWO6WlpXjnnXcwbdo0tGzZstz5hIQE2NraiskCAPj4+MDMzAzHjx8X63Tt2hVKpVKs4+vri9TUVNy+fVus4+Pjo9e2r68vEhISjIqXCQMREclCWQ+DlAMAnJycoFarxSMsLOyx4vn0009hYWGB999//6HntVot7O3t9cosLCxgZ2cHrVYr1nFwcNCrU/bZUJ2y8xXFIQkiIpIFUw1JXL16FSqVSiy3tLQ0uq3ExESsWLECp06dempWX7CHgYiIyAgqlUrveJyE4fDhw8jMzISzszMsLCxgYWGBK1euYMqUKWjUqBEAQKPRIDMzU++64uJiZGVlQaPRiHUyMjL06pR9NlSn7HxFMWEgIiJZMNWQhCm88847OHPmDJKSksTD0dER06ZNw48//ggA8Pb2RnZ2NhITE8XrYmNjUVpaig4dOoh14uPjUVRUJNaJjo5GixYtUKdOHbFOTEyM3v2jo6Ph7e1tVMwckiAiInmo4pdP5ebm4tKlS+LntLQ0JCUlwc7ODs7Ozqhbt65e/Ro1akCj0aBFixYAAHd3d/Tq1QujRo1CeHg4ioqKEBQUhMGDB4tLMIcOHYp58+YhMDAQM2bMQHJyMlasWIFly5aJ7U6cOBHdunXDkiVL0LdvX2zbtg0nT57UW3pZEexhICIiqgQnT55EmzZt0KZNGwBAcHAw2rRpg5CQkAq3sWXLFri5uaFHjx7o06cPOnfurPdFr1arceDAAaSlpaFt27aYMmUKQkJC9PZqeOmll7B161asW7cOXl5e2LVrFyIjI9GqVSujnkchCIJg1BVPEJ1OB7VaDUvPUVCYKw1fQPQUun1idXWHQFRpdDodHOqqkZOTozeR0NT3UKvV0Iz4CmbKmo/dTmnhXWg3vF2psT7JOCRBRESywHdJSMOEgYiIZIEJgzScw0BEREQGsYeBiIjkoYpXSTxrmDAQEZEscEhCGg5JEBERkUHsYXjGvdSmCSa84wMvN2c0qK+G/9R1+P7QGfH8o5bshazYjVVf6e8MpqxhgZ8ipsKzeUN08Q9D8oU/xXMDfNogeLgvmjjb46/bufhixyG96zt6NUboBD80c9HA2qoGrmqzEPHtUaz9+qCJn5jIsP/tOowN3xzG1RtZAAC3xhpMC+yNVzvdf2Ng2rWbmLNiN35O+gOFRcXo4e2OT6f+B/Z15beU7lnCHgZpnoiEYc2aNVi0aBG0Wi28vLywatUqvPjii9Ud1jOhprUlki/8ia/2JOCrRaPLnW/Ra5beZ5+XWmLV7KHYczCpXN157/tBezMHns0b/uMaD6xbMAwzFu1E7PEUtGikwfIPhyK/oAhf7IwHAOTdK8QXO+Jx7tKfyLtXCO/WTbB01mDczS/Ept1HTffARBXgaG+LuUF+aOJUH4Ig4Ot9x+E/dR0OfTUTzo52GBi0Bq2aPYfv1k4AAHwSvg9Dgj9H9MYpMDNjx+zTSgGJCYPMJzFUe8Kwfft2BAcHIzw8HB06dMDy5cvFd3n/87WeZLyfjv2Gn4799sjzmX/d0fvcp6snDidexJU//9Ir93nJA907uCNgxnrxt7Ayb/V+EfvifsXGb48AAK78+ReWRRzAxIBXxYTh7IVrOHvhmnjN1RtZeK27F7xbN2HCQFWud1dPvc9zxvXHhm+O4GRyGm7czEb6jb9w6KsZUNWyBgB8FvoOXF+ZjvgTF/ByB7fqCJmo2lV7qrx06VKMGjUKw4cPh4eHB8LDw1GzZk1s2LChukOTnfp2tdGzcyt89V1CufLlHwzBmLmbcTe/sNx1SqUFCgqL9cryCwrxnEMdODWwe+i9PJs3xIvPN8bRUxdN9wBEj6GkpBTfHDiJu/cK0d7TFQWFxVAoFLBU/v/vU1ZKC5iZKfDzr79XY6Qk1ZP08qmnUbUmDIWFhUhMTISPj49YZmZmBh8fHyQkJPzLlVQZhvTtgNy8fOz9x3DEZ3PfxsZvjyApJf2h18X+nILXunuha/vmUCgUaOJsj/H+PQAAmnpqvbrJUQugPboMBzdPx/qd8fjyO/7/TNXj3KU/0bBrMBw6TUJw2HZ8uWgU3Bo3QHvPRqhppUToqu9wN78QefcKMGfFbpSUlEJ7S1fdYZMUChMcMlatQxK3bt1CSUkJHBwc9ModHBxw/vz5cvULCgpQUFAgftbp+B+vKfn374id+0/q9RaMfqsbatW0wrKIA4+8btPuo3B9rh62LR2DGhbmuJOXj/BtcZj1Xl+Ulpbq1e0zejlqWVuinWcjzB3vh7SrN/HNgcRHtExUeZq5OCB+yyzocu/hu5jTGBf6JaI+nwi3xg0Q8d9ATPnvdny+/RDMzBQY1LMtvNycYGYm828MkrVqn8NgjLCwMMybN6+6w3gmebduguaNNAj8YKNeedd2zdHe0xUZR5frlR/cNB0795/EuHlfAgBCV3+H+Z/tgUNdFW7dzkW3F++/nvXyP+ZCpF+///m336+jvl1tzBjdhwkDVQtlDQs0dqoPAGjt7ozTv6UjfFscln8wBK90dMfpyFD8lZ0LC3MzqGvXRAvfWWjUs201R01ScJWENNWaMNSrVw/m5ubIyMjQK8/IyIBGoylXf9asWQgODhY/63Q6ODk5VXqccvC2nzdO/5aO5It/6pXPXLwLH4dHiZ819dT4dnUQRnywEYnnLuvVLS0VcONmDgBgUM+2+OXMH/grO/eR9zQzU8CyxlOVs9IzrFQQUPiPuTh1bWsBAOJPpOLm7Vz07uL5sEvpKcGEQZpq/dtaqVSibdu2iImJwYABAwAApaWliImJQVBQULn6lpaWsLS0rOIon2421kq4/v1bFAC4ONZFq+bPITvnLq5l3AYA1Laxgl+PNpizfHe5669l3AYeyOdy794fEkr78yauZ2YDAOzUNvDr0QZHEi/C0tIC/v06wq9HG7z23grxupH/6Ypr2ixcuHy/sZfaNEWQfw+s237I1I9MZNC81d/B56WWcNLUwZ27+di1/ySOJF7EN6vGAQC27ElAc1cN6tWphV/OpGHW0l0YN6Q7mjVyMNAyPckUivuHlOvlrNp/vQsODkZAQADatWuHF198EcuXL0deXh6GDx9e3aE9E1q7uyDq84ni50+CBwEAtkb9jPHzvgIADOzZFgqFAt/8ePKx7zO4bwfMn/g6FArgxNk09BuzAqd+uyKeVygUCBnfH86OdVFSUoq0a7cwb/V32Pgtl1RS1bt1OxdjQzcj45YOqlpWaNn0OXyzahy6d3AHAFy8kon5a/bgtu4unB3tMGW4L8YNfaWaoyaqXgpBEITqDmL16tXixk2tW7fGypUr0aFDB4PX6XQ6qNVqWHqOgsJcWQWRElW9R+3GSfQs0Ol0cKirRk5ODlSqytlJs+y7ovGEXTCztHnsdkoL8vDHqjcqNdYnWbX3MABAUFDQQ4cgiIiITEbikITcl1VW+8ZNRERE9OR7InoYiIiIKhtXSUjDhIGIiGSBqySk4ZAEERERGcQeBiIikgUzM4Wk7b0FmW8NzoSBiIhkgUMS0nBIgoiIiAxiDwMREckCV0lIw4SBiIhkgUMS0jBhICIiWWAPgzScw0BEREQGsYeBiIhkgT0M0jBhICIiWeAcBmk4JEFERFQJ4uPj0a9fPzg6OkKhUCAyMlI8V1RUhBkzZsDT0xM2NjZwdHTEu+++i+vXr+u1kZWVBX9/f6hUKtja2iIwMBC5ubl6dc6cOYMuXbrAysoKTk5OWLhwYblYdu7cCTc3N1hZWcHT0xPff/+90c/DhIGIiGRBAYU4LPFYh5Hvt87Ly4OXlxfWrFlT7tzdu3dx6tQpzJkzB6dOncK3336L1NRU9O/fX6+ev78/zp07h+joaERFRSE+Ph6jR48Wz+t0OvTs2RMuLi5ITEzEokWLEBoainXr1ol1jh07hiFDhiAwMBCnT5/GgAEDMGDAACQnJxv38xMEQTDqiieITqeDWq2GpecoKMyV1R0OUaW4fWJ1dYdAVGl0Oh0c6qqRk5MDlUpVafdQq9V4ftYemFvZPHY7Jfl5OBPW/7FiVSgU2L17NwYMGPDIOidOnMCLL76IK1euwNnZGSkpKfDw8MCJEyfQrl07AMD+/fvRp08fXLt2DY6Ojli7di0+/PBDaLVaKJX3vwdnzpyJyMhInD9/HgDw1ltvIS8vD1FRUeK9OnbsiNatWyM8PLzCz8AeBiIiIiPodDq9o6CgwCTt5uTkQKFQwNbWFgCQkJAAW1tbMVkAAB8fH5iZmeH48eNina5du4rJAgD4+voiNTUVt2/fFuv4+Pjo3cvX1xcJCQlGxceEgYiIZEHScMQDKyycnJygVqvFIywsTHJs+fn5mDFjBoYMGSL2Xmi1Wtjb2+vVs7CwgJ2dHbRarVjHwcFBr07ZZ0N1ys5XFFdJEBGRLJhqlcTVq1f1hiQsLS0lxVVUVIQ333wTgiBg7dq1ktqqTEwYiIiIjKBSqUw236IsWbhy5QpiY2P12tVoNMjMzNSrX1xcjKysLGg0GrFORkaGXp2yz4bqlJ2vKA5JEBGRLJhqSMJUypKFixcv4qeffkLdunX1znt7eyM7OxuJiYliWWxsLEpLS9GhQwexTnx8PIqKisQ60dHRaNGiBerUqSPWiYmJ0Ws7Ojoa3t7eRsXLhIGIiGShbEhCymGM3NxcJCUlISkpCQCQlpaGpKQkpKeno6ioCG+88QZOnjyJLVu2oKSkBFqtFlqtFoWFhQAAd3d39OrVC6NGjcIvv/yCo0ePIigoCIMHD4ajoyMAYOjQoVAqlQgMDMS5c+ewfft2rFixAsHBwWIcEydOxP79+7FkyRKcP38eoaGhOHnyJIKCgox6Hg5JEBGRLFT11tAnT55E9+7dxc9lX+IBAQEIDQ3Fnj17AACtW7fWu+7gwYN4+eWXAQBbtmxBUFAQevToATMzMwwaNAgrV64U66rVahw4cADjx49H27ZtUa9ePYSEhOjt1fDSSy9h69atmD17Nj744AM0a9YMkZGRaNWqlVHPw30YiJ5w3IeBnmVVuQ9D25B9kvdhSJzft1JjfZKxh4GIiORB4ioJIzd6fOYwYSAiIlng2yql4aRHIiIiMog9DEREJAt8vbU0TBiIiEgWOCQhDYckiIiIyCD2MBARkSxwSEIaJgxERCQLHJKQhkMSREREZBB7GIiISBbYwyANEwYiIpIFzmGQhgkDERHJAnsYpOEcBiIiIjKIPQxERCQLHJKQhgkDERHJAockpOGQBBERERnEHgYiIpIFBSQOSZgskqcTEwYiIpIFM4UCZhIyBinXPgs4JEFEREQGsYeBiIhkgaskpGHCQEREssBVEtIwYSAiIlkwU9w/pFwvZ5zDQERERAaxh4GIiORBIXFYQeY9DEwYiIhIFjjpURoOSRAREZFB7GEgIiJZUPz9j5Tr5YwJAxERyQJXSUjDIQkiIiIyiD0MREQkC9y4SZoKJQx79uypcIP9+/d/7GCIiIgqC1dJSFOhIYkBAwZU6Hj99dcrO14iIqKnQnx8PPr16wdHR0coFApERkbqnRcEASEhIWjQoAGsra3h4+ODixcv6tXJysqCv78/VCoVbG1tERgYiNzcXL06Z86cQZcuXWBlZQUnJycsXLiwXCw7d+6Em5sbrKys4Onpie+//97o56lQwlBaWlqho6SkxOgAiIiIqkLZ662lHMbIy8uDl5cX1qxZ89DzCxcuxMqVKxEeHo7jx4/DxsYGvr6+yM/PF+v4+/vj3LlziI6ORlRUFOLj4zF69GjxvE6nQ8+ePeHi4oLExEQsWrQIoaGhWLdunVjn2LFjGDJkCAIDA3H69Gnxl/zk5GSjnkchCIJg1BUPyM/Ph5WV1eNeLplOp4NarYal5ygozJXVFgdRZbp9YnV1h0BUaXQ6HRzqqpGTkwOVSlVp91Cr1ei3Og41rGs9djtF93KxN+jlx4pVoVBg9+7dGDBgAID7vQuOjo6YMmUKpk6dCgDIycmBg4MDIiIiMHjwYKSkpMDDwwMnTpxAu3btAAD79+9Hnz59cO3aNTg6OmLt2rX48MMPodVqoVTe/x6cOXMmIiMjcf78eQDAW2+9hby8PERFRYnxdOzYEa1bt0Z4eHiFn8HoVRIlJSVYsGABnnvuOdSqVQt//PEHAGDOnDn43//+Z2xzREREVaJs0qOUw1TS0tKg1Wrh4+MjlqnVanTo0AEJCQkAgISEBNja2orJAgD4+PjAzMwMx48fF+t07dpVTBYAwNfXF6mpqbh9+7ZY58H7lNUpu09FGZ0wfPzxx4iIiMDChQv1AmzVqhXWr19vbHNERERPFZ1Op3cUFBQY3YZWqwUAODg46JU7ODiI57RaLezt7fXOW1hYwM7OTq/Ow9p48B6PqlN2vqKMThg2b96MdevWwd/fH+bm5mK5l5eX2P1BRET0pClbJSHlAAAnJyeo1WrxCAsLq94HqyJG78Pw559/omnTpuXKS0tLUVRUZJKgiIiITO1xJi7+83oAuHr1qt4cBktLS6Pb0mg0AICMjAw0aNBALM/IyEDr1q3FOpmZmXrXFRcXIysrS7xeo9EgIyNDr07ZZ0N1ys5XlNE9DB4eHjh8+HC58l27dqFNmzbGNkdERPRUUalUesfjJAyurq7QaDSIiYkRy3Q6HY4fPw5vb28AgLe3N7Kzs5GYmCjWiY2NRWlpKTp06CDWiY+P1/uFPTo6Gi1atECdOnXEOg/ep6xO2X0qyugehpCQEAQEBODPP/9EaWkpvv32W6SmpmLz5s16MzCJiIieJIq/DynXGyM3NxeXLl0SP6elpSEpKQl2dnZwdnbGpEmT8NFHH6FZs2ZwdXXFnDlz4OjoKK6kcHd3R69evTBq1CiEh4ejqKgIQUFBGDx4MBwdHQEAQ4cOxbx58xAYGIgZM2YgOTkZK1aswLJly8T7Tpw4Ed26dcOSJUvQt29fbNu2DSdPntRbelkRRvcw+Pn5Ye/evfjpp59gY2ODkJAQpKSkYO/evXj11VeNbY6IiKhKVPUqiZMnT6JNmzZi73twcDDatGmDkJAQAMD06dMxYcIEjB49Gu3bt0dubi7279+vt13Bli1b4Obmhh49eqBPnz7o3Lmz3he9Wq3GgQMHkJaWhrZt22LKlCkICQnR26vhpZdewtatW7Fu3Tp4eXlh165diIyMRKtWrYz7+UnZh6G6cR8GkgPuw0DPsqrch2FQ+GHJ+zB8M6ZLpcb6JHvsl0+dPHkSKSkpAO7Pa2jbtq3JgiIiIjI1vt5aGqMThmvXrmHIkCE4evQobG1tAQDZ2dl46aWXsG3bNjRs2NDUMRIREUnGt1VKY/QchpEjR6KoqAgpKSnIyspCVlYWUlJSUFpaipEjR1ZGjERERFTNjO5hOHToEI4dO4YWLVqIZS1atMCqVavQpUsXkwZHRERkSjLvJJDE6ITBycnpoRs0lZSUiMs8iIiInjQckpDG6CGJRYsWYcKECTh58qRYdvLkSUycOBGLFy82aXBERESmUjbpUcohZxXqYahTp45eZpWXl4cOHTrAwuL+5cXFxbCwsMCIESPEDSeIiIjo2VGhhGH58uWVHAYREVHl4pCENBVKGAICAio7DiIiokpV1VtDP2see+MmAMjPz0dhYaFemRx3vyIiInrWGZ0w5OXlYcaMGdixYwf++uuvcudLSkpMEhgREZEpmer11nJl9CqJ6dOnIzY2FmvXroWlpSXWr1+PefPmwdHREZs3b66MGImIiCRTKKQfcmZ0D8PevXuxefNmvPzyyxg+fDi6dOmCpk2bwsXFBVu2bIG/v39lxElERETVyOgehqysLDRu3BjA/fkKWVlZAIDOnTsjPj7etNERERGZSFW/3vpZY3TC0LhxY6SlpQEA3NzcsGPHDgD3ex7KXkZFRET0pOGQhDRGJwzDhw/Hr7/+CgCYOXMm1qxZAysrK0yePBnTpk0zeYBERERU/YyewzB58mTx3318fHD+/HkkJiaiadOmeP75500aHBERkalwlYQ0kvZhAAAXFxe4uLiYIhYiIqJKI3VYQeb5QsUShpUrV1a4wffff/+xgyEiIqos3BpamgolDMuWLatQYwqFggkDERHRM6hCCUPZqognVXrcYm5JTc+sOn2XVHcIRJVGKM6vsnuZ4TFm+v/jejmTPIeBiIjoacAhCWnknjARERFRBbCHgYiIZEGhAMy4SuKxMWEgIiJZMJOYMEi59lnAIQkiIiIy6LEShsOHD+Ptt9+Gt7c3/vzzTwDAl19+iSNHjpg0OCIiIlPhy6ekMTph+Oabb+Dr6wtra2ucPn0aBQUFAICcnBx88sknJg+QiIjIFMqGJKQccmZ0wvDRRx8hPDwcX3zxBWrUqCGWd+rUCadOnTJpcERERPRkMHrSY2pqKrp27VquXK1WIzs72xQxERERmRzfJSGN0T0MGo0Gly5dKld+5MgRNG7c2CRBERERmVrZ2yqlHHJmdMIwatQoTJw4EcePH4dCocD169exZcsWTJ06FWPHjq2MGImIiCQzM8EhZ0Y//8yZMzF06FD06NEDubm56Nq1K0aOHIn33nsPEyZMqIwYiYiInjolJSWYM2cOXF1dYW1tjSZNmmDBggUQBEGsIwgCQkJC0KBBA1hbW8PHxwcXL17UaycrKwv+/v5QqVSwtbVFYGAgcnNz9eqcOXMGXbp0gZWVFZycnLBw4UKTP4/RCYNCocCHH36IrKwsJCcn4+eff8bNmzexYMECkwdHRERkKmVzGKQcxvj000+xdu1arF69GikpKfj000+xcOFCrFq1SqyzcOFCrFy5EuHh4Th+/DhsbGzg6+uL/Pz/fymXv78/zp07h+joaERFRSE+Ph6jR48Wz+t0OvTs2RMuLi5ITEzEokWLEBoainXr1kn+mT3osXd6VCqV8PDwMGUsRERElcYM0uYhmMG4a48dOwY/Pz/07dsXANCoUSN8/fXX+OWXXwDc711Yvnw5Zs+eDT8/PwDA5s2b4eDggMjISAwePBgpKSnYv38/Tpw4gXbt2gEAVq1ahT59+mDx4sVwdHTEli1bUFhYiA0bNkCpVKJly5ZISkrC0qVL9RILqYxOGLp37/6vm1fExsZKCoiIiOhJptPp9D5bWlrC0tKyXL2XXnoJ69atw4ULF9C8eXP8+uuvOHLkCJYuXQoASEtLg1arhY+Pj3iNWq1Ghw4dkJCQgMGDByMhIQG2trZisgAAPj4+MDMzw/Hjx/H6668jISEBXbt2hVKpFOv4+vri008/xe3bt1GnTh2TPLfRCUPr1q31PhcVFSEpKQnJyckICAgwSVBERESmZqpllU5OTnrlc+fORWhoaLn6M2fOhE6ng5ubG8zNzVFSUoKPP/4Y/v7+AACtVgsAcHBw0LvOwcFBPKfVamFvb6933sLCAnZ2dnp1XF1dy7VRdq7aEoZly5Y9tDw0NLTcJAwiIqInhalePnX16lWoVCqx/GG9CwCwY8cObNmyBVu3bhWHCSZNmgRHR8en8hdsk60Sefvtt7FhwwZTNUdERPREUqlUesejEoZp06Zh5syZGDx4MDw9PfHOO+9g8uTJCAsLA3B/XyMAyMjI0LsuIyNDPKfRaJCZmal3vri4GFlZWXp1HtbGg/cwBZMlDAkJCbCysjJVc0RERCalUEjbvMnY4Yy7d+/CzEz/a9bc3BylpaUAAFdXV2g0GsTExIjndTodjh8/Dm9vbwCAt7c3srOzkZiYKNaJjY1FaWkpOnToINaJj49HUVGRWCc6OhotWrQw2XAE8BhDEgMHDtT7LAgCbty4gZMnT2LOnDkmC4yIiMiUqnpr6H79+uHjjz+Gs7MzWrZsidOnT2Pp0qUYMWLE3+0pMGnSJHz00Udo1qwZXF1dMWfOHDg6OmLAgAEAAHd3d/Tq1QujRo1CeHg4ioqKEBQUhMGDB8PR0REAMHToUMybNw+BgYGYMWMGkpOTsWLFikdOIXhcRicMarVa77OZmRlatGiB+fPno2fPniYLjIiI6Gm2atUqzJkzB+PGjUNmZiYcHR3x3nvvISQkRKwzffp05OXlYfTo0cjOzkbnzp2xf/9+vR77LVu2ICgoCD169ICZmRkGDRqElStXiufVajUOHDiA8ePHo23btqhXrx5CQkJMuqQSABTCg1tOGVBSUoKjR4/C09PTpN0cj0un00GtViPjrxy9CShEz5I6fZdUdwhElUYozkdB7Gzk5FTe3+Nl3xWzvzsFK5vaj91Oft4dfOT3QqXG+iQzag6Dubk5evbsybdSEhHRU0dhgn/kzOhJj61atcIff/xRGbEQERFVmrJllVIOOTM6Yfjoo48wdepUREVF4caNG9DpdHoHERERPXsqPOlx/vz5mDJlCvr06QMA6N+/v94W0YIgQKFQoKSkxPRREhERSWSqjZvkqsIJw7x58zBmzBgcPHiwMuMhIiKqFAqF4l/fhVSR6+WswglD2WKKbt26VVowRERE9GQyah8GuWdXRET09OKQhDRGJQzNmzc3mDRkZWVJCoiIiKgyVPVOj88aoxKGefPmldvpkYiIiJ59RiUMgwcPLvdebiIioqdB2UukpFwvZxVOGDh/gYiInmacwyBNhTduMuKVE0RERPSMqXAPQ9n7u4mIiJ5KEic9yvxVEsa/3pqIiOhpZAYFzCR860u59lnAhIGIiGSByyqlMfrlU0RERCQ/7GEgIiJZ4CoJaZgwEBGRLHAfBmk4JEFEREQGsYeBiIhkgZMepWHCQEREsmAGiUMSMl9WySEJIiIiMog9DEREJAsckpCGCQMREcmCGaR1q8u9S17uz09EREQVwB4GIiKSBYVCAYWEcQUp1z4LmDAQEZEsKCDthZPyTheYMBARkUxwp0dpOIeBiIiIDGIPAxERyYa8+wikYcJARESywH0YpOGQBBERUSX5888/8fbbb6Nu3bqwtraGp6cnTp48KZ4XBAEhISFo0KABrK2t4ePjg4sXL+q1kZWVBX9/f6hUKtja2iIwMBC5ubl6dc6cOYMuXbrAysoKTk5OWLhwocmfhQkDERHJQtmySimHMW7fvo1OnTqhRo0a+OGHH/Dbb79hyZIlqFOnjlhn4cKFWLlyJcLDw3H8+HHY2NjA19cX+fn5Yh1/f3+cO3cO0dHRiIqKQnx8PEaPHi2e1+l06NmzJ1xcXJCYmIhFixYhNDQU69atk/5DewCHJIiISBaqeqfHTz/9FE5OTti4caNY5urqKv67IAhYvnw5Zs+eDT8/PwDA5s2b4eDggMjISAwePBgpKSnYv38/Tpw4gXbt2gEAVq1ahT59+mDx4sVwdHTEli1bUFhYiA0bNkCpVKJly5ZISkrC0qVL9RILqdjDQEREZASdTqd3FBQUPLTenj170K5dO/znP/+Bvb092rRpgy+++EI8n5aWBq1WCx8fH7FMrVajQ4cOSEhIAAAkJCTA1tZWTBYAwMfHB2ZmZjh+/LhYp2vXrlAqlWIdX19fpKam4vbt2yZ7biYMREQkC6YaknBycoJarRaPsLCwh97vjz/+wNq1a9GsWTP8+OOPGDt2LN5//31s2rQJAKDVagEADg4Oetc5ODiI57RaLezt7fXOW1hYwM7OTq/Ow9p48B6mwCEJIiKSBVPt9Hj16lWoVCqx3NLS8qH1S0tL0a5dO3zyyScAgDZt2iA5ORnh4eEICAiQEEn1YA8DERGREVQqld7xqIShQYMG8PDw0Ctzd3dHeno6AECj0QAAMjIy9OpkZGSI5zQaDTIzM/XOFxcXIysrS6/Ow9p48B6mwISBiIhkoapXSXTq1Ampqal6ZRcuXICLiwuA+xMgNRoNYmJixPM6nQ7Hjx+Ht7c3AMDb2xvZ2dlITEwU68TGxqK0tBQdOnQQ68THx6OoqEisEx0djRYtWuityJCKCQMREcmCmQkOY0yePBk///wzPvnkE1y6dAlbt27FunXrMH78eAD3E5hJkybho48+wp49e3D27Fm8++67cHR0xIABAwDc75Ho1asXRo0ahV9++QVHjx5FUFAQBg8eDEdHRwDA0KFDoVQqERgYiHPnzmH79u1YsWIFgoODJfy0yuMcBiIikoWqfr11+/btsXv3bsyaNQvz58+Hq6srli9fDn9/f7HO9OnTkZeXh9GjRyM7OxudO3fG/v37YWVlJdbZsmULgoKC0KNHD5iZmWHQoEFYuXKleF6tVuPAgQMYP3482rZti3r16iEkJMSkSyoBQCEIgmDSFquQTqeDWq1Gxl85ehNQiJ4ldfouqe4QiCqNUJyPgtjZyMmpvL/Hy74rvjp6ATVr1X7sdu7m3sHbnZpXaqxPMvYwEBGRLJhqlYRcMWEgIiJZ4MunpOGkRyIiIjKIPQxERCQLZlDATMLAgpRrnwVMGIiISBY4JCENhySIiIjIIPYwEBGRLCj+/kfK9XLGhIGIiGSBQxLScEiCiIiIDGIPAxERyYJC4ioJDkkQERHJAIckpGHCQEREssCEQRrOYSAiIiKD2MNARESywGWV0jBhICIiWTBT3D+kXC9nHJIgIiIig9jDQEREssAhCWmYMBARkSxwlYQ0HJIgIiIig9jDQEREsqCAtGEFmXcwMGEgIiJ54CoJaTgkQURERAaxh4HK+d+uw9jwzWFcvZEFAHBrrMG0wN54tVNLAMBr7y3H0VOX9K4ZNrATls0aUuWxEr3U8jlMGNQeXk0d0KBuLfgv+A7f//z/fz7XTPbFUJ9Wetf8lJiG/4R8K35+vok9Qod3xQvNHFBSKmDPsYuY/UUc8vKLxDpdvZzx4Tud4O5SD3cLirAt5hwWbDqCklJBrNOyUT0sGtsDbZpr8FfOPazbexorvzlRiU9PxuAqCWmqNWGIj4/HokWLkJiYiBs3bmD37t0YMGBAdYZEABztbTE3yA9NnOpDEAR8ve84/Keuw6GvZsK9SQMAQMCAlzDrvdfEa6ytalRXuCRzNa1qIDntJr6KTsZXs/0eWuenk2kYv3y/+LmgqET8d42dDSI/fgO741MxfW0MatdUImx0d6yZ3AvDwvYCAFq51seOea9jyfbjGLPkBzSoWwtLg3xgZmaGkP8dAgDUtlbim4/ewKGkKwhe8xM8GtXDqom+yMnLx6b9ZyvxJ0AVxVUS0lRrwpCXlwcvLy+MGDECAwcOrM5Q6AG9u3rqfZ4zrj82fHMEJ5PTxITB2koJh3qq6giPSM9PiZfxU+Llf61TUFSCzNt3H3rO98XGKCouxdS1MRD+7iwIXv0Tjn4WANcGtki7kY3Xu7TAubRbWPT1zwCAtBvZCN0Qjw0zX8PCrceQe68I/+nuDqWFGYKW/4ii4lKcT/8Lno3tMW5AOyYMTwgFpE1clHm+UL0JQ+/evdG7d+/qDIEMKCkpRWTMKdy9V4j2nq5i+c79J7HjhxOwr6tCry6tMG1kb9S0UlZjpESP1tmzIS5sGYvs3Hwc/jUdH315FLfv5AMAlDUsUFRcKiYLAHCvsBgA0LHlc0i7kQ1lDXMU/F32YB1ryxrwauqAo2evob1bAxxL/hNFxaVinZhTlzHpPy9CXcsSObkFlf+gRJXoqZrDUFBQgIKC//+PTqfTVWM0z7Zzl/6E74glyC8sho21Jb5cNApuje/3Lrzh2w5ODeygqa/GuYvXMW/1d7h0JRNfLhpVzVETlReTeBlRxy7hijYHjRrYYk5AZ+ycNxA9p36N0lIBh39Nx8cju2HCwHYI33MKNa1qYO6wLgAATR0bAEDsqcsY6/cCBnVzw+7DqXCoY4PpQ7zv17GrBQCwr2OD9IwcvXvfvJ0HAHCoY8OE4QlgBgXMJIwrmMm8j+GpShjCwsIwb9686g5DFpq5OCB+yyzocu/hu5jTGBf6JaI+nwi3xg0wbGBnsV7Lps9BU08Fv3GrkHbtJlwb1q/GqInK+zY+Vfz3367cwrnLN5H0v5Ho7OmE+F/TcT79L4xbuh8fjXoZIcO6oKS0FOv2nEbG7TyU/t3tcPD0FYRsiMfS8T4In9IbBUUlWLztZ7zUqiFKH5j0SE82DklI81QlDLNmzUJwcLD4WafTwcnJqRojenYpa1igsdP9L//W7s44/Vs6wrfFYfkH5VdCtG3VCADwx1UmDPTku6LNwa2cu2jcwBbxv6YDAHYdOo9dh86jvm1N3M0vgiAIGDegLS5r/7/H4LPIRHwWmQiNnQ2ycwvg7KDC3GFdcFmbDQDIvJ2H+rY2eveq/3cPRcbfPQ1ET7OnKmGwtLSEpaVldYchS6WCgMJ/jOGWOXvhGgDAoZ66KkMieiyOdWvBrrb1Q7/Eb2bfnxjp/2or5BeV4ODpK+XqaLPuXzeomxuuZerw6++ZAIAT529g9rudYGFuhuKS+/MYurd2wYWrWRyOeFKwi0GSpyphoKoxb/V38HmpJZw0dXDnbj527T+JI4kX8c2qcUi7dhO79p/Eq51awk5tg+SLf+LDZd/ipTZN0arZc9UdOsmQjVUNuDraip9dNCq0alwf2XfycftOPmYM9caeoxeRcTsPrg1sMW9EV/xx4zZiHlhZMeq11jiech1594rQvY0L5o3oinkRh6HL+/8v+gkD2yEm8TJKBQGvvdQMk954EcP/GyUOSeyKS8H0od5YNbEnVuw6AXeXenjP7wV8+MXBqvpRkAHch0Gaak0YcnNzcenS/2+wkpaWhqSkJNjZ2cHZ2bkaI5O3W7dzMTZ0MzJu6aCqZYWWTZ/DN6vGoXsHd1zT3kbcL6lYu+0g7t4rxHMOddDvldaYOsK3usMmmWrdzAFR/31L/PzJqO4AgK0/JWPKmhh4NKqPwT1aQm1jCW1WLmJPX8EnXx5FYfH/78XwQnMNZvq/BBvrGrh4NQvBq6Ox/WCK3n182rliylsdoKxhjuS0m/BfEKm3nFN3txCDZu/CorE9cHDF2/hLdw+Lvk7gkkoCAPz3v//FrFmzMHHiRCxfvhwAkJ+fjylTpmDbtm0oKCiAr68vPvvsMzg4OIjXpaenY+zYsTh48CBq1aqFgIAAhIWFwcLi/7++4+LiEBwcjHPnzsHJyQmzZ8/GsGHDTP4MCkEQqm3GTlxcHLp3716uPCAgABEREQav1+l0UKvVyPgrByoV9wSgZ1OdvkuqOwSiSiMU56MgdjZycirv7/Gy74qYpHTUqv3498i9o0OP1s5Gx3rixAm8+eabUKlU6N69u5gwjB07Fvv27UNERATUajWCgoJgZmaGo0ePAgBKSkrQunVraDQaLFq0CDdu3MC7776LUaNG4ZNPPgFw/xftVq1aYcyYMRg5ciRiYmIwadIk7Nu3D76+pv1Frlp7GF5++WVUY75CREQyUh1TGHJzc+Hv748vvvgCH330kViek5OD//3vf9i6dSteeeUVAMDGjRvh7u6On3/+GR07dsSBAwfw22+/4aeffoKDgwNat26NBQsWYMaMGQgNDYVSqUR4eDhcXV2xZMn9Xyzc3d1x5MgRLFu2zOQJA18+RUREVEnGjx+Pvn37wsfHR688MTERRUVFeuVubm5wdnZGQkICACAhIQGenp56QxS+vr7Q6XQ4d+6cWOefbfv6+optmBInPRIRkTyYqIvhn5sGPmoF37Zt23Dq1CmcOFH+BWRarRZKpRK2trZ65Q4ODtBqtWKdB5OFsvNl5/6tjk6nw71792BtbV3x5zOAPQxERCQLChP8AwBOTk5Qq9XiERYWVu5eV69excSJE7FlyxZYWVlV9aNWCvYwEBGRLJjqbZVXr17Vm/T4sN6FxMREZGZm4oUXXhDLSkpKEB8fj9WrV+PHH39EYWEhsrOz9XoZMjIyoNFoAAAajQa//PKLXrsZGRniubL/LSt7sI5KpTJp7wLAHgYiIiKjqFQqveNhCUOPHj1w9uxZJCUliUe7du3g7+8v/nuNGjUQExMjXpOamor09HR4e99/T4m3tzfOnj2LzMxMsU50dDRUKhU8PDzEOg+2UVanrA1TYg8DERHJQlWukqhduzZatWqlV2ZjY4O6deuK5YGBgQgODoadnR1UKhUmTJgAb29vdOzYEQDQs2dPeHh44J133sHChQuh1Woxe/ZsjB8/XkxSxowZg9WrV2P69OkYMWIEYmNjsWPHDuzbt0/Ckz4cEwYiIpKHJ2xr6GXLlsHMzAyDBg3S27ipjLm5OaKiojB27Fh4e3vDxsYGAQEBmD9/vljH1dUV+/btw+TJk7FixQo0bNgQ69evN/mSSqCaN26Sihs3kRxw4yZ6llXlxk2Hzl6VvHFTN0+nSo31ScYeBiIikgW+S0IaJgxERCQLplolIVdcJUFEREQGsYeBiIhk4Qmb8/jUYcJARETywIxBEg5JEBERkUHsYSAiIlngKglpmDAQEZEscJWENEwYiIhIFjiFQRrOYSAiIiKD2MNARETywC4GSZgwEBGRLHDSozQckiAiIiKD2MNARESywFUS0jBhICIiWeAUBmk4JEFEREQGsYeBiIjkgV0MkjBhICIiWeAqCWk4JEFEREQGsYeBiIhkgaskpGHCQEREssApDNIwYSAiInlgxiAJ5zAQERGRQexhICIiWeAqCWmYMBARkTxInPQo83yBQxJERERkGHsYiIhIFjjnURomDEREJA/MGCThkAQREREZxB4GIiKSBa6SkIYJAxERyQK3hpaGQxJERERkEBMGIiKSBYUJDmOEhYWhffv2qF27Nuzt7TFgwACkpqbq1cnPz8f48eNRt25d1KpVC4MGDUJGRoZenfT0dPTt2xc1a9aEvb09pk2bhuLiYr06cXFxeOGFF2BpaYmmTZsiIiLCyGgNY8JARETyUMUZw6FDhzB+/Hj8/PPPiI6ORlFREXr27Im8vDyxzuTJk7F3717s3LkThw4dwvXr1zFw4EDxfElJCfr27YvCwkIcO3YMmzZtQkREBEJCQsQ6aWlp6Nu3L7p3746kpCRMmjQJI0eOxI8//mj0j+jfKARBEEzaYhXS6XRQq9XI+CsHKpWqusMhqhR1+i6p7hCIKo1QnI+C2NnIyam8v8fLvivOpmWidu3Hv8edOzp4uto/dqw3b96Evb09Dh06hK5duyInJwf169fH1q1b8cYbbwAAzp8/D3d3dyQkJKBjx4744Ycf8Nprr+H69etwcHAAAISHh2PGjBm4efMmlEolZsyYgX379iE5OVm81+DBg5GdnY39+/c/9vP+E3sYiIiIjKDT6fSOgoKCCl2Xk5MDALCzswMAJCYmoqioCD4+PmIdNzc3ODs7IyEhAQCQkJAAT09PMVkAAF9fX+h0Opw7d06s82AbZXXK2jAVJgxERCQLCvz/SonHOv5ux8nJCWq1WjzCwsIM3ru0tBSTJk1Cp06d0KpVKwCAVquFUqmEra2tXl0HBwdotVqxzoPJQtn5snP/Vken0+HevXtG/pQejcsqiYhIFky10ePVq1f1hiQsLS0NXjt+/HgkJyfjyJEjEiKoXuxhICIiMoJKpdI7DCUMQUFBiIqKwsGDB9GwYUOxXKPRoLCwENnZ2Xr1MzIyoNFoxDr/XDVR9tlQHZVKBWtr68d6xodhwkBERLIgaTjiMTZ9EgQBQUFB2L17N2JjY+Hq6qp3vm3btqhRowZiYmLEstTUVKSnp8Pb2xsA4O3tjbNnzyIzM1OsEx0dDZVKBQ8PD7HOg22U1Slrw1Q4JEFERDJRtW+fGj9+PLZu3YrvvvsOtWvXFuccqNVqWFtbQ61WIzAwEMHBwbCzs4NKpcKECRPg7e2Njh07AgB69uwJDw8PvPPOO1i4cCG0Wi1mz56N8ePHiz0bY8aMwerVqzF9+nSMGDECsbGx2LFjB/bt2yfhWctjDwMREVElWLt2LXJycvDyyy+jQYMG4rF9+3axzrJly/Daa69h0KBB6Nq1KzQaDb799lvxvLm5OaKiomBubg5vb2+8/fbbePfddzF//nyxjqurK/bt24fo6Gh4eXlhyZIlWL9+PXx9fU36PNyHgegJx30Y6FlWlfswpFy5idoS7nFHp4O7S/1KjfVJxiEJIiKShaodkHj2cEiCiIiIDGIPAxERyQJfby0NEwYiIpIFxd//SLlezpgwEBGRPHASgyScw0BEREQGsYeBiIhkgR0M0jBhICIiWeCkR2k4JEFEREQGsYeBiIhkgaskpGHCQERE8sBJDJJwSIKIiIgMYg8DERHJAjsYpGHCQEREssBVEtJwSIKIiIgMYg8DERHJhLRVEnIflGDCQEREssAhCWk4JEFEREQGMWEgIiIigzgkQUREssAhCWmYMBARkSxwa2hpOCRBREREBrGHgYiIZIFDEtIwYSAiIlng1tDScEiCiIiIDGIPAxERyQO7GCRhwkBERLLAVRLScEiCiIiIDGIPAxERyQJXSUjDhIGIiGSBUxikYcJARETywIxBEs5hICIiIoPYw0BERLLAVRLSMGEgIiJZ4KRHaZ7qhEEQBADAHZ2umiMhqjxCcX51h0BUacr+fJf9fV6ZdBK/K6Re/7R7qhOGO3fuAACaujpVcyRERCTFnTt3oFarK6VtpVIJjUaDZib4rtBoNFAqlSaI6umjEKoiraskpaWluH79OmrXrg2F3PuKqohOp4OTkxOuXr0KlUpV3eEQmRT/fFc9QRBw584dODo6wsys8ubh5+fno7CwUHI7SqUSVlZWJojo6fNU9zCYmZmhYcOG1R2GLKlUKv6FSs8s/vmuWpXVs/AgKysr2X7RmwqXVRIREZFBTBiIiIjIICYMZBRLS0vMnTsXlpaW1R0KkcnxzzfRoz3Vkx6JiIioarCHgYiIiAxiwkBEREQGMWEgIiIig5gwEBERkUFMGKjC1qxZg0aNGsHKygodOnTAL7/8Ut0hEZlEfHw8+vXrB0dHRygUCkRGRlZ3SERPHCYMVCHbt29HcHAw5s6di1OnTsHLywu+vr7IzMys7tCIJMvLy4OXlxfWrFlT3aEQPbG4rJIqpEOHDmjfvj1Wr14N4P57PJycnDBhwgTMnDmzmqMjMh2FQoHdu3djwIAB1R0K0ROFPQxkUGFhIRITE+Hj4yOWmZmZwcfHBwkJCdUYGRERVRUmDGTQrVu3UFJSAgcHB71yBwcHaLXaaoqKiIiqEhMGIiIiMogJAxlUr149mJubIyMjQ688IyMDGo2mmqIiIqKqxISBDFIqlWjbti1iYmLEstLSUsTExMDb27saIyMioqpiUd0B0NMhODgYAQEBaNeuHV588UUsX74ceXl5GD58eHWHRiRZbm4uLl26JH5OS0tDUlIS7Ozs4OzsXI2RET05uKySKmz16tVYtGgRtFotWrdujZUrV6JDhw7VHRaRZHFxcejevXu58oCAAERERFR9QERPICYMREREZBDnMBAREZFBTBiIiIjIICYMREREZBATBiIiIjKICQMREREZxISBiIiIDGLCQERERAYxYSCSaNiwYRgwYID4+eWXX8akSZOqPI64uDgoFApkZ2c/so5CoUBkZGSF2wwNDUXr1q0lxXX58mUoFAokJSVJaoeIqhcTBnomDRs2DAqFAgqFAkqlEk2bNsX8+fNRXFxc6ff+9ttvsWDBggrVrciXPBHRk4DvkqBnVq9evbBx40YUFBTg+++/x/jx41GjRg3MmjWrXN3CwkIolUqT3NfOzs4k7RARPUnYw0DPLEtLS2g0Gri4uGDs2LHw8fHBnj17APz/MMLHH38MR0dHtGjRAgBw9epVvPnmm7C1tYWdnR38/Pxw+fJlsc2SkhIEBwfD1tYWdevWxfTp0/HP3dX/OSRRUFCAGTNmwMnJCZaWlmjatCn+97//4fLly+L7C+rUqQOFQoFhw4YBuP820LCwMLi6usLa2hpeXl7YtWuX3n2+//57NG/eHNbW1ujevbtenBU1Y8YMNG/eHDVr1kTjxo0xZ84cFBUVlav3+eefw8nJCTVr1sSbb76JnJwcvfPr16+Hu7s7rKys4Obmhs8++8zoWIjoycaEgWTD2toahYWF4ueYmBikpqYiOjoaUVFRKCoqgq+vL2rXro3Dhw/j6NGjqFWrFnr16iVet2TJEkRERGDDhg04cuQIsrKysHv37n+977vvvouvv/4aK1euREpKCj7//HPUqlULTk5O+OabbwAAqampuHHjBlasWAEACAsLw+bNmxEeHo5z585h8uTJePvtt3Ho0CEA9xObgQMHol+/fkhKSsLIkSMxc+ZMo38mtWvXRkREBH777TesWLECX3zxBZYtW6ZX59KlS9ixYwf27t2L/fv34/Tp0xg3bpx4fsuWLQgJCcHHH3+MlJQUfPLJJ5gzZw42bdpkdDxE9AQTiJ5BAQEBgp+fnyAIglBaWipER0cLlpaWwtSpU8XzDg4OQkFBgXjNl19+KbRo0UIoLS0VywoKCgRra2vhxx9/FARBEBo0aCAsXLhQPF9UVCQ0bNhQvJcgCEK3bt2EiRMnCoIgCKmpqQIAITo6+qFxHjx4UAAg3L59WyzLz88XatasKRw7dkyvbmBgoDBkyBBBEARh1qxZgoeHh975GTNmlGvrnwAIu3fvfuT5RYsWCW3bthU/z507VzA3NxeuXbsmlv3www+CmZmZcOPGDUEQBKFJkybC1q1b9dpZsGCB4O3tLQiCIKSlpQkAhNOnTz/yvkT05OMcBnpmRUVFoVatWigqKkJpaSmGDh2K0NBQ8bynp6fevIVff/0Vly5dQu3atfXayc/Px++//46cnBzcuHFD75XeFhYWaNeuXblhiTJJSUkwNzdHt27dKhz3pUuXcPfuXbz66qt65YWFhWjTpg0AICUlpdyrxb29vSt8jzLbt2/HypUr8fvvvyM3NxfFxcVQqVR6dZydnfHcc8/p3ae0tBSpqamoXbs2fv/9dwQGBmLUqFFineLiYqjVaqPjIaInFxMGemZ1794da9euhVKphKOjIyws9P+429jY6H3Ozc1F27ZtsWXLlnJt1a9f/7FisLa2Nvqa3NxcAMC+ffv0vqiB+/MyTCUhIQH+/v6YN28efH19oVarsW3bNixZssToWL/44otyCYy5ubnJYiWi6seEgZ5ZNjY2aNq0aYXrv/DCC9i+fTvs7e3L/ZZdpkGDBjh+/Di6du0K4P5v0omJiXjhhRceWt/T0xOlpaU4dOgQfHx8yp0v6+EoKSkRyzw8PGBpaYn09PRH9ky4u7uLEzjL/Pzzz4Yf8gHHjh2Di4sLPvzwQ7HsypUr5eqlp6fj+vXrcHR0FO9jZmaGFi1awMHBAY6Ojvjjjz/g7+9v1P2J6OnCSY9Ef/P390e9evXg5+eHw4cPIy0tDXFxcXj//fdx7do1AMDEiRPx3//+F5GRkTh//jzGjRv3r3soNGrUCAEBARgxYgQiIyPFNnfs2AEAcHFxgUKhQFRUFG7evInc3FzUrl0bU6dOxeTJk7Fp0yb8/vvvOHXqFFatWiVOJBwzZgwuXryIadOmITU1FVu3bkVERIRRz9usWTOkp6dj27Zt+P3337Fy5cqHTuC0srJCQEAAfv31Vxw+fBjvv/8+3nzzTWg0GgDAvHnzEBYWhpUrV+LChQs4e/YsNm7ciKVLlxoVDxE92ZgwEP2tZs2aiI+Ph7OzMwYOHAh3d3cEBgYiPz9f7HGYMmUK3nnnHQQEBMDb2xu1a9fG66+//q/trl27Fm+88QbGjRsHNzc3jBo1Cnl5eQCA5557DvPmzcPMmTPh4OCAoKAgAMCCBQswZ84chIWFwd3dHb169cK+ffvg6uoK4P68gm+++QaRkZHw8vJCeHg4PvnkE6Oet3///pg8eTKCgoLQunVrHDt2DHPmzClXr2nTphg4cCD69OmDnj174vnnn9dbNjly5EisX78eGzduhKenJ7p164aIiAgxViJ6NiiER83WIiIiIvobexiIiIjIICYMREREZBATBiIiIjKICQMREREZxISBiIiIDGLCQERERAYxYSAiIiKDmDAQERGRQUwYiIiIyCAmDERERGQQEwYiIiIyiAkDERERGfR/7XiLwBnTkuMAAAAASUVORK5CYII=",
            "text/plain": [
              "<Figure size 640x480 with 2 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "dt = DecisionTreeClassifier(random_state=42)\n",
        "\n",
        "start_time = time.time()\n",
        "train_metrics = compute_train_metrics(dt, X_train, y_train)\n",
        "TRAINING_TIME['Decision Tree'] = time.time() - start_time\n",
        "\n",
        "dt.fit(X_train, y_train)\n",
        "test_metrics = compute_test_metrics_and_plot_cm(dt, X_test, y_test, \"DT\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 98,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 487
        },
        "id": "n3q884IsSAP6",
        "outputId": "16c16321-97ea-42c1-ace7-b356671b3b2e"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "plot_metrics(train_metrics, test_metrics, \"Decision Tree\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 99,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 607
        },
        "id": "X88mYcxfWxV0",
        "outputId": "2ff91b1c-d272-49a2-dba3-e1e5e3f153cb"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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Dzp07ERwcLP7/7t27NyZPnowvv/wSY8aMQXx8PNasWYOKFSvi6tWrWv0MXF1dsWLFCnh6eqJGjRriFLCP+vfvjx07dmDYsGE4fvw4mjRpgtTUVAQHB2PHjh04cuQI6tWrp9VzEhEB4CVliahg+3hJ2Y9/DA0NhaJFiwrt2rUTvLy8xEux/ldISIjg5uYmFC1aVDAwMBBKlCghdOnSRdi1a5fGehEREcKoUaOEEiVKCIaGhkLJkiUFd3d3ITw8XBCEtJeUDQ8PF0aOHClUrlxZMDMzE6ysrISGDRsKO3bs0Njvfy8pKwiCEBYWJnh4eAi2traCoaGhUKNGDXG/H318vvQuWQtA8PT0zPTPLqNLypqZmWW4zbp164S6desKJiYmgoWFhVCjRg1h0qRJwqtXrzTWO378uODs7CxYWVkJxsbGQrly5YQBAwYIly9f/mRPGd1R+6OWLVsKlpaWQlRUlEbd399faNeunWBjYyMYGRkJ5cuXFyZMmCC8ffs2w+cKDAwUunfvLtjZ2Qn6+vpCkSJFhK5duwp79+79ZI8fpaSkCBs2bBCaNWsmWFlZCQYGBkLp0qUFDw+PNJebPXr0qFC9enXB0NBQqFSpkvDrr79meEnZkSNHZvicarVacHBwEAAI8+bNS3ed5ORkYdGiRUK1atUEIyMjwcbGRqhbt64wZ84cITo6OlOvjYjovxSCkANn7RERERERkWzxnAoiIiIiIsoWhgoiIiIiIsoWhgoiIiIiIsoWhgoiIiIiIsoWhgoiIiIiIsoWhgoiIiIiIsoW2d38Tq1W49WrV7CwsIBCoZC6HSIiIiKiXCUIAt6/f4/ixYtDTy9nxhhkFypevXoFBwcHqdsgIiIiIpLU8+fPUbJkyRzZl+xChYWFBQDg8ePHKFSokMTdUH6hUqlw9OhRtG/fHgYGBlK3Q/kAjxnKCh43pC0eM5QVkZGRKFOmjPi5OCfILlR8nPJkYWEBS0tLibuh/EKlUsHU1BSWlpZ806ZM4TFDWcHjhrTFY4ayQqVSAUCOngrAE7WJiIiIiChbGCqIiIiIiChbGCqIiIiIiChbGCqIiIiIiChbGCqIiIiIiChbGCqIiIiIiChbGCqIiIiIiChbGCqIiIiIiChbGCqIiIiIiChbGCqIiIiIiChbGCqIiIiIiChbGCqIiIiIiChbGCqIiIiIiChbGCqIiIiIiChbGCqIiIiIiChbGCqIiIiIiChbGCqIiIiIiChbJA0Vp06dQteuXVG8eHEoFAr4+/t/dpsTJ06gTp06MDIyQvny5eHr66vzPomIiIiIKGOShoq4uDg4OTlh1apVmVr/8ePH6Ny5M1q1aoXr169j7Nix+Pbbb3HkyBEdd0pERERERBnRl/LJO3bsiI4dO2Z6fW9vb5QpUwZLliwBAFSpUgWnT5/GsmXL4OzsrKs2iYiIiIhyjyD8+0HGtayum5KQ/R7/Q9JQoa1z586hbdu2GjVnZ2eMHTs2w22SkpKQlJQkPo6JiQEAqJKToUqM+1DM6Aef6f+Jn/kfy31JsK9/+1BXZKOv1JQU2CQEI/W5BRT6+jnzGtNbN1/t61/1PLEvpK1ncV/pHita7ktITUWZqGAIVx4gVanMkb7y7s9eV/v6xP4l7SsL7ymZ7EuhVqNO2CsoDm+HWk9P968x2+/BGa2LzyzP4mvIp/vS6j1Fy76UAtA69j2UW8z/v5Y2+0Lm182nP/v8sC+F5v8IndtzqzJC3xvk+H7zVagIDQ2Fvb29Rs3e3h4xMTFISEiAiYlJmm0WLlyIOXPmpKkrNleDgf47nfVKBYs+gOYAsEfiRijfUAKoCQDhEjdC+YoeAAcAeC9xI5RvKABYAAA/0lAmbb1aE3/eLQXgVo7uN1+FiqyYOnUqxo8fLz6OiYmBg4MDTFLeyeDVExERkS4JUHz4i0Lxr+q//i7WP7f8X3Ut95WSkgJ9ff0c2dcnl+fZfSHtuhntPyt9ZXFfQlb29dmfS/b3tWr0O5yY4IDEHP7yIl99rC5atCjCwsI0amFhYbC0tEx3lAIAjIyMYGRk9Okdl2im3cGd7rrZfYPIxLo5uS9dvwHk+del3b5S1Wo8efwYjmXKQqnU+8+6ufAz0skxl4m+c3JfcvpdUnz4R/7GjRtwqlUL+kr9z+//E/vKdC86OebywHGi69+lPPS6VCkpOHnyJFq0aAEDA8PsPW8+fs/N0va5epyk34EUVCoVDh48iE6dOsHAIOentFDWSX1sAMD790m4dy8C9eoVF2v2AAIbPEGtWkty9LnyVaho1KgRDh48qFELCAhAo0aNsr5T17+Bkk2z2RkVdGqVCkGxB1GqeSco+aZNmSCoVHjxyBo1K3UCeMxQZqlUiDN8CNhU5HFDRNly4sQTeHjsRVxcMm7fHoEiRczEZSVLWuT480l6SdnY2Fhcv34d169fB/DhkrHXr1/Hs2fPAHyYuuTm5iauP2zYMDx69AiTJk1CcHAwVq9ejR07dmDcuHFZbyKDbx6IiIiIiPKb+HgVxo49jFat/PDkSRTevo3HuHG6v/2CpCMVly9fRqtWrcTHH899cHd3h6+vL16/fi0GDAAoU6YM/vzzT4wbNw5eXl4oWbIkNmzYkM3LyTJUEBEREVH+d/78C7i7++P+/Qix1rx5acyd2+oTW+UMSUNFy5YtIWR4CTqke7fsli1b4tq1azrsioiIiIgo/0hKSsGcOSexaNEZqNUfPlsbG+tj4cI2GDOmIfT0dP8ler46p0InOP2JiIiIiPKpa9dew93dH7duvRFrDRqUgJ+fCypXts21PhgqOP2JiIiIiPKhhAQVOnTYijdvPtzQ2cBAD7Nnt8SkSU2gr5+7p05LeqJ2nsCRCiIiIiLKh0xMDLB0aXsAgJOTPS5fHoJp05rleqAAOFIBjlQQERERUX6QmqpGYmIKzMz+uY9N3741oFAo0LNnVRgaKiXrjSMVHKkgIiIiojzu4cNItGjhi+HD/9SoKxQK9O1bQ9JAATBUEBERERHlWWq1gNWrL8HJyRtnzjzHli03sWfPXanbSoPTnzj9iYiIiIjyoGfPojFw4F4EBj4Wa2XL2sDOzuwTW0mDoYLTn4iIiIgoDxEEAb6+1zF27BHExCSJ9eHD6+Gnn9rB3NzwE1tLg6GCIxVERERElEe8fv0eQ4YcwIED98VayZKW8PHphnbtyknY2acxVDBUEBEREVEe8OjRO9Srtw7v3iWKtQEDamHZMmdYWxtL2Nnn8URtTn8iIiIiojygTBlrNGxYEgBgb2+GvXt7Y9Om7nk+UAAMFUREREREeYJCocCGDV3h4VELQUEj0K1bJalbyjSGCk5/IiIiIqJcFhWVCHd3fxw58lCjXqKEJXx8usPW1lSizrKGoYLTn4iIiIgoFx058hDVq6/G5s03MGjQPkRFJX5+ozyOoYIjFURERESUC96/T8KwYQfQocNWvHz5/v+1ZNy8GSZxZ9nHqz9xpIKIiIiIdOzkySfw8NiLx4+jxFrbtmXh49MNDg5W0jWWQxgqOFJBRERERDqSkKDCtGmB8PK6AEH4UDM1NcDPP7fDsGH1oCggX3AzVBSQ/5FERERElLfcuBEKV9dduHcvQqw1a1YKmzZ1R7lyhSTsLOcxVBARERER6YCFhRFevIgBABgZKbFgQRt8911DKJUF77RmhgpOfyIiIiIiHShb1gZLlzpjw4ar8PNzQZUqRaRuSWcKXkzSGkMFEREREWVPSooaXl7nERubrFEfPLgOzp4dVKADBcCRCp5TQURERETZcvfuW7i7++PSpVe4dy8Cq1d3FpcpFAro6xf8z5scqeBIBRERERFlQWqqGkuXnkPt2mtx6dIrAMC6dVfw6NE7iTvLfRyp4EgFEREREWkpJCQSAwbsxenTz8RapUqF4efngrJlbSTsTBoMFUREREREmSQIAry9L2PixADEx6sAfPiOety4LzBvXmuYmBhI3KE0GCo4/YmIiIiIMuH582gMGrQPAQGPxFrZsjbw9e2OZs1KS9iZ9BgqOP2JiIiIiDJh9+67GoFi+PB6+OmndjA3N5Swq7yBoYIjFURERESUCaNGNcAff9zF48dR2LixG9q3Lyd1S3kGQwVHKoiIiIgoHTdvhqFmTXvxsVKph99+6wFzc0NYWxtL2Fnew0vKcqSCiIiIiP4lPDwerq67UKuWN86ceaaxrGRJSwaKdDBUEBERERH9375991C9+mrs2HEbggC4u/sjMTFF6rbyPE5/4vQnIiIiItmLikrE2LGH4ed3Q6wVKmSC+fNbw9iYH5k/hz8hTn8iIiIikrWjR0MwaNA+vHgRI9a6dKmIdeu6oFgxCwk7yz8YKhgqiIiIiGQpNjYZ339/FN7eV8SahYUhvLw6YMCAWlBwRkumMVTwYCEiIiKSJQ+Pvdi16474uE2bMvDx6Y5Spawk7Cp/4onaHKkgIiIikqU5c1rCyEgJU1MDrFrVCUeP9megyCKOVHCkgoiIiEgWkpNTYWioFB9XrVoEmzd/iTp1iqF8+UISdpb/caSCiIiIiAq05ORUzJhxDPXrr09zedivv67GQJEDGCo4/YmIiIiowLpxIxT166/H/Pl/4+bNMHh6Hpe6pQKJ0584/YmIiIiowElJUWPRotOYM+ckVCo1AEBfXw9WVrwbti4wVHCkgoiIiKhACQ4Oh5vbHly69Eqs1ahhBz8/F9SuXUzCzgouhgqOVBAREREVCGq1AC+v85g27Zh47oSengJTpjTBrFktYGTEj766wp8sRyqIiIiI8j21WkD79lsQGPhYrFWsWBibN7ugYcOSEnYmDzxRm4iIiIjyPT09BZo3Lw3gw0SUsWMb4tq1oQwUuYQjFRypICIiIioQpk5tilu33mDUqPpo0cJR6nZkhaGC51QQERER5SuCIGDLlpt48yYOEyc2FusGBkrs3NlLws7ki6GCIxVERERE+UZYWCyGDj2AvXvvQV9fD61aOaJu3eJStyV7PKeCIxVERERE+cLOnbdRrdpq7N17D8CHe1Hs339f4q4I4EgFOFJBRERElLdFRMRj1KhD2LYtSKzZ2Zlh7doucHGpLGFn9BFDBRERERHlWQcO3MfgwfsRGhor1nr0qII1azqjSBEzCTujf2Oo4PQnIiIiojwnNjYZ3313CD4+18WajY0xVq3qhN69q0PBz3B5CkMFpz8RERER5Tn6+nq4cOGl+Lhz5wpYt64rihe3kLAryghP1GbKJSIiIspzjI314efngkKFTLBxYzfs39+HgSIP40gFRyqIiIiIJHf69DMULmyCKlWKiLW6dYvj2bOxMDMzlLAzygyOVHCkgoiIiEgyiYkpmDjxKJo33wQ3N3+oVKkayxko8geGCo5UEBEREUni0qWXqFNnLZYsOQdBAC5ffgVf3+tSt0VZwOlPRERERJSrkpNTMW/eKSxY8DdSUwUAgKGhEvPmtcLAgbUl7o6ygqGCIxVEREREuebmzTC4u/vj+vVQsVa3bjH4+bmgWjU7CTuj7GCo4DkVRERERDqXkqLG4sVn4Ol5AiqVGsCHy8bOnNkcU6c2hYGBUuIOKTsYKjhSQURERKRzN26EYvr0YxA+zHZCtWpFsHnzl6hTp5i0jVGO4InaHKkgIiIi0rm6dYtj4sTG0NNTYMqUJrhyZQgDRQHCkQqOVBARERHluOfPo1G8uAWUyn++w547txV69aqK+vVLSNgZ6QJHKoiIiIgoxwiCgHXrrqBKlVVYvvy8xjJjY30GigKKoYLTn4iIiIhyxIsXMejYcSuGDj2AuDgVpk8/hrt330rdFuUCTn/i9CciIiKibBEEAb/+ehOjRx9CdHSSWHdzc0LJkpYSdka5haGCIxVEREREWRYWFothw/6Ev3+wWCte3AIbNnRFx44VJOyMchNDBUcqiIiIiLJk1647GD78T4SHx4u1b76piV9+6QAbGxMJO6PcxlDBkQoiIiIirW3adA0DB+4THxcpYoq1a7vgyy+rSNgVSYUnahMRERGR1nr1qoZy5WwAAF99VQW3b49goJAxjlQQERER0Wep1QL09P6Z4WFubgg/Pxc8fRqNPn2qQ8HZH7Im85EKHvxEREREnxMY+Ag1aqxBSEikRr1Jk1Lo27cGAwXJPFTwF4CIiIgoQ3FxyRg9+iDatt2CO3fewsNjL9RqQeq2KA+S+fQnhgoiIiKi9Jw58wwDBuzFw4f/jE7o6+shOjqRV3aiNDhSQURERESixMQUTJoUgGbNNomBwsREHytWdMRff7kxUFC6OFJBRERERACAy5dfwd3dH3fuvBVrjRqVhJ+fCypUKCxhZ5TXyTxUEBEREREA/PLLBYwffwSpqR/OmTA0VOKHH1phwoRGUCrlPbmFPk/eoYLTn4iIiIgAAFWq2IqBok6dYvDzc0H16nYSd0X5hbxDBac/EREREQEA2rUrhzFjGqBQIRNMm9YMBgZKqVuifETeoYIjFURERCRD9+9HYMOGq1i0qK3GPSaWL+/Ae05Qlsg7VHCkgoiIiGRErRawYsUFTJkSiMTEFJQvXwhDhtQVlzNQUFbJ/Kwb/uIQERGRPDx+/A6tW/th7NgjSExMAQB4e1/mzewoR8g8VBAREREVbIIgYN26K6hZ0xsnTz4V66NHN8Dff3tAT49fslL2yXv6E4f4iIiIqAB7+TIGgwbtw5EjIWKtdGkr+Ph0R+vWZSTsjAoaeYcKTn8iIiKiAurXX29i9OhDiIpKFGuDB9fBzz+3h6WlkYSdUUEk71DBkQoiIiIqoAICHomBolgxc2zc2A0dO1aQuCsqqCQ/p2LVqlVwdHSEsbExGjZsiIsXL35y/eXLl6NSpUowMTGBg4MDxo0bh8TExE9ukzGGCiIiIiqYvLw6oGRJS/TrVwNBQSMYKEinJB2p2L59O8aPHw9vb280bNgQy5cvh7OzM+7duwc7u7R3cPztt98wZcoU+Pj4oHHjxrh//z4GDBgAhUKBpUuXat8ARyqIiIioAIiMTMD9+6/QrFlpsWZtbYxr14bC1tZUws5ILiQdqVi6dCkGDx4MDw8PVK1aFd7e3jA1NYWPj0+66589exZNmjRB37594ejoiPbt26NPnz6fHd0gIiIiKqguX45B7drr0bXr73jxIkZjGQMF5RbJRiqSk5Nx5coVTJ06Vazp6emhbdu2OHfuXLrbNG7cGL/++isuXryIBg0a4NGjRzh48CD69++f4fMkJSUhKSlJfBwT888vmwAFUlSqHHg1VNCp/n+cqHi8UCbxmKGs4HFD2oiJScLEiQHw9X0k1saNO4zffvtSwq4oP9DFe4xkoSI8PBypqamwt7fXqNvb2yM4ODjdbfr27Yvw8HA0bdoUgiAgJSUFw4YNw7Rp0zJ8noULF2LOnDnpLlOpUnDo4MGsvwiSnYCAAKlboHyGxwxlBY8b+pybN99jxYpnePv2nw+HdepYoGNHBQ7ysw19Rnx8fI7vM19d/enEiRNYsGABVq9ejYYNG+Lhw4f47rvv8MMPP2DmzJnpbjN16lSMHz9efBwTEwMHBwcAgIGhITp16pQrvVP+plKpEBAQgHbt2sHAwEDqdigf4DFDWcHjhj4nPl6F6dOPY9Wqf+47YWyshyVL2uHbb+tAwfNFKRMiIiJyfJ+ShQpbW1solUqEhYVp1MPCwlC0aNF0t5k5cyb69++Pb7/9FgBQo0YNxMXFYciQIZg+fTr09NKeImJkZAQjo/SvxayAgm/apBUDAwMeM6QVHjOUFTxuKD1nzz7HgAH+ePAgUqy1aFEKffuawcOjLo8ZyjRdHCuSnahtaGiIunXrIjAwUKyp1WoEBgaiUaNG6W4THx+fJjgolUoAH25BrzWmeSIiIsoHEhNT0LPnDjFQmJjow8urA44c6Qd7e97IjqQn6dWfxo8fj/Xr18PPzw93797F8OHDERcXBw8PDwCAm5ubxoncXbt2xZo1a7Bt2zY8fvwYAQEBmDlzJrp27SqGC+0wVBAREVHeZ2ysj9WrOwMAvviiJK5fH4YxYxpCT4+fZShvkPScCldXV7x9+xazZs1CaGgoatWqhcOHD4snbz979kxjZGLGjBlQKBSYMWMGXr58iSJFiqBr166YP3++VC+BiIiIKMepVKmIj1fByspYrLm4VMa+fb3RqVMFKJWS37+YSIPkJ2qPGjUKo0aNSnfZiRMnNB7r6+vD09MTnp6eOfPknP5EREREeUxQ0Bu4u/vD0dEau3b10jj5umvXShJ2RpQxmcdchgoiIiLKG1JT1Vi06DTq1l2Hq1dfY/fuu/j99yCp2yLKFMlHKiTFkQoiIiLKA+7fj8CAAf44d+6FWKtatQgqVSosYVdEmSfvUMGRCiIiIpKQWi1g5cqLmDLlLyQkpAD48J3nxImNMXduKxgby/yjGuUb8j5SOVJBREREEnnyJAoeHntx4sQTsVaunA38/FzQpEkp6RojygJ5hwoiIiIiCTx69A5OTt6IjU0Wa6NG1cePP7aFmZmhhJ0RZQ1P1CYiIiLKZWXKWKN9+3IAgFKlrPDXX/2xYkUnBgrKt2Q+UsFQQURERLlPoVBgzZrOKFnSAnPnttK4HwVRfiTvkQqeU0FEREQ69uZNHHr02IE9e+5q1O3szODl1ZGBggoEjlQQERER6cju3XcxbNgBvH0bj9Onn6Fp01IoUsRM6raIchxHKoiIiIhy2Lt3Cfjmm93o0WMH3r6NB/Dh8rH370dI3BmRbnCkgoiIiCgHHTr0AN9+ux+vXr0Xay4uleHt3Rn29uYSdkakOzIPFUREREQ54/37JEyYcBTr118Va1ZWRlixoiO++aYmFJwhQQWYvEMFf7mJiIgoB1y58go9e+7EkydRYs3ZuRw2bOiGkiUtpWuMKJfIO1Rw+hMRERHlgKJFzREVlQgAMDc3xNKl7fHtt3U4OkGyIe9QwV90IiIiygElSlhixYqO2LDhKjZt6o4yZWykbokoV8n76k8cqSAiIiItJSWlYN68U+LIxEf9+tXAsWPuDBQkSxypICIiIsqkq1dfw93dH0FBb/DgQST8/FzEZQqFgh8tSLZkPlJBRERE9HkqVSrmzj2Jhg03ICjoDQBg27YghIREStwZUd4g75EKTn8iIiKiz7h9+w3c3f1x5cprsVarVlFs3uyCcuUKSdgZUd7BUEFERESUjtRUNZYuPYcZM44jOTkVAKBUKjB9ejNMn94choZKiTskyjvkHSo48ZGIiIjS8fBhJNzd/XH27HOxVqWKLTZv/hL16hWXsDOivEnm51QwVBAREVFax449FgOFQgFMnNgIV68OZaAgygBHKoiIiIj+Y/DgOvjjj7sICYmEr68LmjYtJXVLRHmavEMFERERyZ4gCDh37gUaN3YQawqFAlu2fAlTUwOYmxtK2B1R/sDpT0RERCRbr169R5cuv6NJEx8EBIRoLLOzM2OgIMokeYcKTn8iIiKSJUEQ8Ntvt1C9+mocPPgAADBo0D4kJKgk7owof5L59CeGCiIiIrl5+zYOw4f/iT/+uCvWihY1x+rVnWFiYiBhZ0T5l7xDBUcqiIiIZMXfPxhDhuzH27fxYq137+pYubIjChc2lbAzovxN3qGCIxVERESy8O5dAsaMOYxff70p1goXNsGaNZ3Rq1c1CTsjKhgYKoiIiKjAGzbsT+zYcVt83K1bJaxb1wX29uYSdkVUcMj7RG0iIiKShQULWsPU1ABWVkbw83OBv78rAwVRDpL3SAXPqSAiIiqQ4uKSYWb2z+Vgy5UrhO3be8LJyR4ODlYSdkZUMMl8pIKhgoiIqCCJj1dh7NjDqFVrLeLikjWWdelSkYGCSEfkHSo4UkFERFRgnD//ArVrr4WX1wU8fBiJyZP/krolItmQ9/QnjlQQERHle0lJKZgz5yQWLToDtVoAABgb66N8+UISd0YkH/IOFRypICIiyteuXXsNd3d/3Lr1Rqw1aFACfn4uqFzZVsLOiORF3qGCiIiI8iWVKhU//ngac+eeQkqKGgBgYKCH2bNbYtKkJtDXl/cMb6LcJvNQwZEKIiKi/EatFtC69WacPv1MrDk52cPPzwVOTkUl7IxIvuQd4zn9iYiIKN/R01PAxaUSAECpVGDGjGa4eHEwAwWRhDhSQURERPnO2LFf4Pbttxg+vB7q1y8hdTtEssdQQURERHmWWi3A2/sy3ryJw+zZLcW6UqkHH5/u0jVGRBrkHSo4/YmIiCjPevYsGgMH7kVg4GMoFED79uXQuLGD1G0RUTrkfU4FERER5TmCIGDTpmuoUWMNAgMf/78GHD/+WOLOiCgj8h6p4PQnIiKiPOX16/cYMuQADhy4L9ZKlrSEj083tGtXTsLOiOhT5B0qOP2JiIgoz9i+PQgjRhxEZGSCWBswoBaWLXOGtbWxhJ0R0efIO1RwpIKIiEhyMTFJ+Pbbfdi5845Ys7c3w7p1XdGtWyUJOyOizJJ3qOBIBRERkeRMTPTx6NE78fHXX1fDqlWdYGtrKmFXRKQNmZ+ozVBBREQkNQMDJfz8XFC8uAW2beuB7dt7MlAQ5TMcqSAiIqJcdfRoCIoUMUXt2sXEWrVqdnj0aAyMjOT90YQov5L5SAURERHlltjYZAwffgDOzr+if/89SEpK0VjOQEGUf8k8VHCkgoiIKDecOvUUNWuugbf3FQDA7dtvsXnzDYm7IqKcIu9QwelPREREOpWQoML48UfQsqUvHj+OAgCYmRlgzZrO+PbbOtI2R0Q5RubjjAwVREREunLhwgu4u/vj3r0IsdasWSls2tQd5coVkrAzIsppDBVERESUo5KSUjB37kn8+OMZqNUCAMDISIkFC9rgu+8aQqmU90QJooJI3qGC05+IiIhy3L17Efjpp7NioKhfvzj8/FxQpUoRiTsjIl3hVwVERESUo2rWtMf06c1gYKCHefNa4ezZQQwURAWcvEcqOP2JiIgo2x48iICjozUMDJRibfr0ZujZsyqqV7eTsDMiyi3yHqng9CciIqIsS01VY+nSc6hRYw0WLjytsczAQMlAQSQj8g4VHKkgIiLKkpCQSLRq5YcJE44iKSkVP/xwCjduhErdFhFJRN7TnzhSQUREpBVBEODtfRnffx+AuDgVgA//nI4e3QAVKxaWuDsikoq8QwVHKoiIiDLt+fNoDBq0DwEBj8RamTLW8PV1QfPmpSXsjIikJvNQQURERJ8jCAL8/G7gu+8OIyYmSawPG1YXixe3h7m5oYTdEVFeIO9QwelPREREn+Xrex0DB+4TH5coYYGNG7vB2bm8hF0RUV7CE7WJiIjok/r0qYGqVT/cZ8Ld3QlBQSMYKIhIQ7ZGKhITE2FsbJxTvUiAoYKIiOi/UlLU0Nf/53tHY2N9bNnyJZ4/j0b37pUl7IyI8iqtRyrUajV++OEHlChRAubm5nj06MPJWjNnzsTGjRtzvEGd4vQnIiIiDfv23UOFCitw9+5bjXqdOsUYKIgoQ1qHinnz5sHX1xc//fQTDA3/OTGrevXq2LBhQ442p3sMFURERAAQHZ0ID4+96N59G548iYK7uz9SUtRSt0VE+YTWoWLz5s1Yt24d+vXrB6VSKdadnJwQHByco83pHEcqiIiIcPRoCKpXXwNf3+tizd7eHLGxydI1RUT5itbnVLx8+RLly6c9OUutVkOlUuVIU0RERKR7sbHJ+P77o/D2viLWLC2N4OXVAe7uTlDwyzciyiStQ0XVqlXx999/o3RpzZvc7Nq1C7Vr186xxnIH3yyJiEieTp16Cg+PvXj06J1Ya9OmDHx8uqNUKSsJOyOi/EjrUDFr1iy4u7vj5cuXUKvV2L17N+7du4fNmzfjwIEDuuhRd/gNDBERydDPP5/FpEkBEIQPj01NDbB4cTsMG1YPenr8t5GItKf1ORXdu3fH/v378ddff8HMzAyzZs3C3bt3sX//frRr104XPeoQ3ziJiEh+vviipPj3Jk0ccOPGMIwYUZ+BgoiyLEv3qWjWrBkCAgJyupfcx5EKIiKSoaZNS2HatGawtjbGuHFfQKmU+b1wiSjbtH4XKVu2LCIiItLUo6KiULZs2RxpKvcwVBARUcF240Yohg07ALVa0KjPm9caEyc2ZqAgohyh9UjFkydPkJqamqaelJSEly9f5khTRERElD0pKWosWnQac+achEqlRqVKhTFuXCOp2yKiAirToWLfvn3i348cOQIrq3+uDJGamorAwEA4OjrmaHO6x5EKIiIqeIKDw+HmtgeXLr0Sa9u23caYMQ05MkFEOpHpUOHi4gIAUCgUcHd311hmYGAAR0dHLFmyJEeb0zmeU0FERAWIWi3Ay+s8pk07hsTEFACAnp4Ckyc3gadnCwYKItKZTIcKtVoNAChTpgwuXboEW1tbnTWVexgqiIioYHj06B08PPbi1KmnYq1ixcLYvNkFDRuW/MSWRETZp/U5FY8fP9ZFH9LgSAURERUAa9dexoQJRxEXpxJrY8c2xPz5bWBqaiBhZ0QkF1m6pGxcXBxOnjyJZ8+eITk5WWPZmDFjcqSx3MFQQURE+d+NG2FioChTxhqbNnVHixaO0jZFRLKidai4du0aOnXqhPj4eMTFxaFQoUIIDw+Hqakp7Ozs8lmoICIiyv9++qkdjh4NQdu2ZbF4cTtYWBhJ3RIRyYzWZ2yNGzcOXbt2xbt372BiYoLz58/j6dOnqFu3Ln7++Wdd9Kg7nP5ERET5TGhoLI4ceahRMzc3xNWrQ+Ht3YWBgogkoXWouH79OiZMmAA9PT0olUokJSXBwcEBP/30E6ZNm6aLHnWIoYKIiPKPnTtvo3r11ejRYwcePXqnsczSkmGCiKSjdagwMDCAnt6Hzezs7PDs2TMAgJWVFZ4/f56z3ekaRyqIiCgfiIiIR+/eu/D117sQEZGAuDgVJk0KkLotIiKR1udU1K5dG5cuXUKFChXQokULzJo1C+Hh4diyZQuqV6+uix51iKGCiIjytv3772HIkAMIDY0Vaz16VMGaNZ0l7IqISJPWIxULFixAsWLFAADz58+HjY0Nhg8fjrdv32Lt2rVaN7Bq1So4OjrC2NgYDRs2xMWLFz+5flRUFEaOHIlixYrByMgIFStWxMGDB7V+XgAcqSAiojwrOjoRAwfuRbdu28RAYWNjjN9++wo7d/ZCkSJmEndIRPQPrUcq6tWrJ/7dzs4Ohw8fzvKTb9++HePHj4e3tzcaNmyI5cuXw9nZGffu3YOdnV2a9ZOTk9GuXTvY2dlh165dKFGiBJ4+fQpra+ssdsBQQUREeU9g4GMMGfInnj+PEWudO1fAunVdUby4hYSdERGlT+uRioxcvXoVXbp00WqbpUuXYvDgwfDw8EDVqlXh7e0NU1NT+Pj4pLu+j48PIiMj4e/vjyZNmsDR0REtWrSAk5NTTrwEIiIiySUnqzF48AExUFhYGGLjxm7Yv78PAwUR5VlajVQcOXIEAQEBMDQ0xLfffouyZcsiODgYU6ZMwf79++Hs7JzpfSUnJ+PKlSuYOnWqWNPT00Pbtm1x7ty5dLfZt28fGjVqhJEjR2Lv3r0oUqQI+vbti8mTJ0OpVKa7TVJSEpKSksTHMTH/fOujFgSkqlTpbUakQfX/40TF44UyiccMZYVKpYKhoR5WrnSGi8sutGpVGuvWdUHp0lZISUmRuj3Kg/heQ1mhi+Ml06Fi48aNGDx4MAoVKoR3795hw4YNWLp0KUaPHg1XV1cEBQWhSpUqmX7i8PBwpKamwt7eXqNub2+P4ODgdLd59OgRjh07hn79+uHgwYN4+PAhRowYAZVKBU9Pz3S3WbhwIebMmZPusufPX+B6Vs/HIFkKCODVVkg7PGboc5KT1UhMVMPS8t//JD/EDz+UQ7Vq5rh9+wxu35asPcon+F5D2oiPj8/xfWY6VHh5eWHRokX4/vvv8ccff6BXr15YvXo1bt26hZIlS+Z4Y+lRq9Wws7PDunXroFQqUbduXbx8+RKLFy/OMFRMnToV48ePFx/HxMTAwcEBAODgUArF23bKld4pf1OpVAgICEC7du1gYGAgdTuUD/CYocy4fPkVBg7cj9KlrbBvnytSUlLE46ZTJx439Hl8r6GsiIiIyPF9ZjpUhISEoFevXgCAr776Cvr6+li8eHGWA4WtrS2USiXCwsI06mFhYShatGi62xQrVgwGBgYaU52qVKmC0NBQJCcnw9DQMM02RkZGMDJK/4ZAekol9PgLSFowMDDgmzZphccMpSc5ORXz5p3CggV/IzVVQHBwBPz8bmHAgJoAeNyQ9njMkDZ0caxk+kTthIQEmJqaAgAUCgWMjIzES8tmhaGhIerWrYvAwECxplarERgYiEaNGqW7TZMmTfDw4UOo1Wqxdv/+fRQrVizdQPF5vPoTERHlrlu3wtCw4Qb88MMppKYKAIC6dYuhcWMHiTsjIso6rU7U3rBhA8zNzQEAKSkp8PX1ha2trcY6Y8aMyfT+xo8fD3d3d9SrVw8NGjTA8uXLERcXBw8PDwCAm5sbSpQogYULFwIAhg8fjpUrV+K7777D6NGj8eDBAyxYsECr5yQiIpJCSooaixefgafnCahUH74c09fXw8yZzTF1alMYGCh5si0R5VuZDhWlSpXC+vXrxcdFixbFli1bNNZRKBRafcB3dXXF27dvMWvWLISGhqJWrVo4fPiwePL2s2fPoKf3z2CKg4MDjhw5gnHjxqFmzZooUaIEvvvuO0yePDnTz/mfhrO2HRERkRaCg8Ph7u6PixdfirXq1e2webMLatfO+qg/EVFekelQ8eTJE500MGrUKIwaNSrdZSdOnEhTa9SoEc6fP59Dz85QQUREuvXkSRRq116LxMQPl4TV01Ng0qTGmD27JYyMtL4HLRFRnpRjN7/LlzhSQUREOuboaI2ePasCACpWLIwzZwZi4cK2DBREVKDI/B2NoYKIiHKWIHw4+Vrxry+ufvmlA0qXtsK0ac1gasor9BBRwSPvkQqGCiIiykEvXsSgY8et+O23Wxp1GxsTzJvXmoGCiAosmY9UEBERZZ8gCPj115sYPfoQoqOTcOHCS7RqVQbFi1tI3RoRUa6Qd6jgORVERJRNYWGxGDbsT/j7B4s1U1MDPHsWzVBBRLKRpelPISEhmDFjBvr06YM3b94AAA4dOoTbt2/naHO6x1BBRERZt2vXHVSvvkYjUHzzTU0EBQ3HF1+UlLAzIqLcpXWoOHnyJGrUqIELFy5g9+7diI2NBQDcuHEDnp6eOd6gTnGkgoiIsiAyMgF9+/6BXr12Ijw8HgBQpIgpdu/+Glu2fAkbGxOJOyQiyl1ah4opU6Zg3rx5CAgIgKGhoVhv3bp1Dt4/IrcwVBARkXYuXnyJatVW4/ffg8TaV19Vwe3bI/Dll1Uk7IyISDpan1Nx69Yt/Pbbb2nqdnZ2CA8Pz5Gmcg1HKoiISEuOjtZITVUDAKytjbFqVSf06VNd4xKyRERyo/VIhbW1NV6/fp2mfu3aNZQoUSJHmso9/AeAiIi0Y2dnBm/vLujUqQJu3x6Bvn1rMFAQkexpHSp69+6NyZMnIzQ0FAqFAmq1GmfOnMHEiRPh5uamix6JiIgkEReXjMmTA/D2bZxG/auvquDAgT68uhMR0f9pHSoWLFiAypUrw8HBAbGxsahatSqaN2+Oxo0bY8aMGbroUXf4zRIREWXgzJlncHLyxk8/ncXw4X+Kd8r+iKMTRET/0PqcCkNDQ6xfvx4zZ85EUFAQYmNjUbt2bVSoUEEX/ekY/0EgIiJNiYkpmDXrOH7++Sw+5oiDBx8gJOQdypcvJG1zRER5lNah4vTp02jatClKlSqFUqVK6aKnXMRQQURE/7h8+RXc3f1x585bsdaoUUn4+bkwUBARfYLW059at26NMmXKYNq0abhz544ueso9HLomIiIAycmp8PQ8ji++2CAGCkNDJRYtaou///ZAhQqFJe6QiChv0zpUvHr1ChMmTMDJkydRvXp11KpVC4sXL8aLFy900Z+OMVQQEcldUNAbfPHFBsydewqpqR/mO9WpUwxXrgzBpElNoFRq/U8lEZHsaP1OaWtri1GjRuHMmTMICQlBr1694OfnB0dHR7Ru3VoXPRIREenMtWuvce1aKABAX18Ps2e3wPnzg1C9up3EnRER5R9an1Pxb2XKlMGUKVPg5OSEmTNn4uTJkznVV+7g9CciItn75pua2L07GA8eRMDPzwV16xaXuiUionwny2O6Z86cwYgRI1CsWDH07dsX1atXx59//pmTveUChgoiIjlRqwUcPRqiUVMoFPDx6YbLl4cwUBARZZHWoWLq1KkoU6YMWrdujWfPnsHLywuhoaHYsmULOnTooIsedYcjFUREsvHkSRTatNkMZ+dfsW/fPY1lNjYmMDbO1uA9EZGsaf0OeurUKXz//ff4+uuvYWtrq4uechFDBRFRQScIAjZsuIrx448iNjYZADB06AG0a1cWJiYGEndHRFQwaB0qzpw5o4s+pMGRCiKiAu3lyxh8++1+HD78UKyVLm0FH5/uDBRERDkoU6Fi37596NixIwwMDLBv375PrtutW7ccaYyIiCirBEHA1q23MHr0IURFJYr1b7+tjSVLnGFpaSRhd0REBU+mQoWLiwtCQ0NhZ2cHFxeXDNdTKBRITU3Nqd5yAUcqiIgKmjdv4jBs2AHs2RMs1ooVM8eGDd3QqVMFCTsjIiq4MhUq1Gp1un/P9zj9iYiowBk79rBGoOjbtwZWrOiIQoVMJOyKiKhg0/rqT5s3b0ZSUlKaenJyMjZv3pwjTeUehgoiooLmp5/awcrKCLa2pti1qxe2bv2KgYKISMe0DhUeHh6Ijo5OU3///j08PDxypKncw1BBRJTfvXuXoPG4ZElL7N7titu3R6BHj6oSdUVEJC9ahwpBEKBIZ9rQixcvYGVllSNN5RpOfyIiyrdiYpLw7bf74OTkjejoRI1lrVuXgZ2dmUSdERHJT6YvKVu7dm0oFAooFAq0adMG+vr/bJqamorHjx/nv5vfcaSCiChfOnbsMTw89uLZsw8j5+PGHYGPT3eJuyIikq9Mh4qPV326fv06nJ2dYW5uLi4zNDSEo6MjevTokeMNEhERfRQXl4wpU/7CypWXxJq5uSG++KKkhF0REVGmQ4WnpycAwNHREa6urjA2NtZZU7mG05+IiPKNs2efw93dHw8fRoq1li0dsWlTdzg6WkvXGBERaX9HbXd3d130IRGGCiKivC4xMQWensfx88/noFYLAABjY30sWtQWo0Y1gJ4e38uJiKSWqVBRqFAh3L9/H7a2trCxsUn3RO2PIiMjM1yW53CkgogoT1OrBbRs6YsLF16KtS++KAlf3+6oVMlWws6IiOjfMhUqli1bBgsLC/HvnwoV+UtBeR1ERAWTnp4C7u5OuHDhJQwNlZg7tyUmTmwMpVLrixcSEZEOZSpU/HvK04ABA3TVS+4rMOGIiKjgGjasHu7di8CgQbVRo4a91O0QEVE6tP6q5+rVq7h165b4eO/evXBxccG0adOQnJyco80REZF8pKaqsWjRaUyYcESjrlAosHx5BwYKIqI8TOtQMXToUNy/fx8A8OjRI7i6usLU1BQ7d+7EpEmTcrxB3eJIBRFRXnD/fgSaNduEKVMCsXTpeQQGPpK6JSIi0oLWoeL+/fuoVasWAGDnzp1o0aIFfvvtN/j6+uKPP/7I6f50jKGCiEhKarWAFSsuoFYtb5w79wLAh5mpV6++lrgzIiLShtaXlBUEAWq1GgDw119/oUuXLgAABwcHhIeH52x3usZzKoiIJPPkSRQGDtyL48efiLXy5QvB17c7mjQpJV1jRESkNa1DRb169TBv3jy0bdsWJ0+exJo1awAAjx8/hr19fpvvylBBRJTbBEHAxo3XMG7cEcTG/nMu3qhR9fHjj21hZmYoYXdERJQVWoeK5cuXo1+/fvD398f06dNRvnx5AMCuXbvQuHHjHG9QpzhSQUSUq6KjE9Gnzx84dOihWCtVygo+Pt3Qpk1ZCTsjIqLs0DpU1KxZU+PqTx8tXrwYSqUyR5oiIqKCydzcEDExSeLjQYNqY+lSZ1haGknYFRERZZfWoeKjK1eu4O7duwCAqlWrok6dOjnWVO7hSAURUW5SKvXg6+uCjh23YvlyZ3TuXFHqloiIKAdoHSrevHkDV1dXnDx5EtbW1gCAqKgotGrVCtu2bUORIkVyukfd4fQnIiKd2r37LooVM0ejRg5irXz5QggOHsm7YhMRFSBav6OPHj0asbGxuH37NiIjIxEZGYmgoCDExMRgzJgxuuhRhxgqiIh04d27BHzzzW706LEDbm7+iIvTvDkqAwURUcGi9bv64cOHsXr1alSpUkWsVa1aFatWrcKhQ4dytDmd40gFEVGOO3ToAapXX4OtWz+cf/fwYaT4dyIiKpi0nv6kVqthYGCQpm5gYCDevyL/YKggIsop798nYcKEo1i//qpYs7IywooVHfHNNzUl7IyIiHRN65GK1q1b47vvvsOrV6/E2suXLzFu3Di0adMmR5vTOY5UEBHliBMnnqBmTW+NQOHsXA5BQSPQv78TFHy/JSIq0LQOFStXrkRMTAwcHR1Rrlw5lCtXDmXKlEFMTAxWrFihix6JiCiPio9X4bvvDqFVKz88eRIF4MNlY9eu7YJDh/qhZElLaRskIqJcofX0JwcHB1y9ehWBgYHiJWWrVKmCtm3b5nhzusdvzoiIsuPp0yisXXtFfNyiRWls2tQdZcrYSNgVERHlNq1Cxfbt27Fv3z4kJyejTZs2GD16tK76yiUMFURE2VGlShH88EMrzJp1Aj/+2AajRzeEnh7fW4mI5CbToWLNmjUYOXIkKlSoABMTE+zevRshISFYvHixLvvTLc7xJSLSys2bYahUqTCMjP7552P8+Ebo0aMqypbl6AQRkVxl+pyKlStXwtPTE/fu3cP169fh5+eH1atX67K3XMBQQUSUGSpVKubMOYG6ddfB0/OExjKlUo+BgohI5jIdKh49egR3d3fxcd++fZGSkoLXr1/rpLFcwZEKIqLPun37Db74YiNmzz6JlBQ1Fi8+i8uXX31+QyIiko1MT39KSkqCmZmZ+FhPTw+GhoZISEjQSWNERCSt1FQ1li49hxkzjiM5ORUAoFQqMH16M9SsaS9xd0RElJdodaL2zJkzYWpqKj5OTk7G/PnzYWVlJdaWLl2ac93pHEcqiIjS8+BBBAYM2IuzZ5+LtSpVbLF585eoV6+4hJ0REVFelOlQ0bx5c9y7d0+j1rhxYzx69Eh8nO9ubpTf+iUi0jG1WsDq1ZcwaVIAEhJSAHx4q5wwoRF++KE1jI21vhI5ERHJQKb/dThx4oQO25AKQwUR0b/5+V3H6NGHxMflytnA19cFTZuWkrArIiLK67S+o3aBwpEKIiIN33xTE7VrFwUAjBxZHzduDGOgICKiz5L5ODZDBRHJW2JiisaUJgMDJbZs+RKvX8eibduyEnZGRET5ibxHKoiIZEoQBPz++y04Oi7HtWualwavVs2OgYKIiLQi81DBkQoikp+3b+Pw9de70LfvboSFxcHd3R9JSSlSt0VERPmYvKc/8ZwKIpIZf/9gDBmyH2/fxou1atXskJSUCiMjef+TQEREWZelkYq///4b33zzDRo1aoSXL18CALZs2YLTp0/naHO6x1BBRPLw7l0C3Nz24Msvt4uBonBhE+zY0RO//94DlpZGEndIRET5mdah4o8//oCzszNMTExw7do1JCUlAQCio6OxYMGCHG9QpzhSQUQycPjwQ1SvvgZbttwUa926VcLt2yPQq1c1CTsjIqKCQutQMW/ePHh7e2P9+vUwMDAQ602aNMHVq1dztDndY6ggooJtwYK/0bHjVrx69R4AYGVlBD8/F/j7u8Le3lzi7oiIqKDQOlTcu3cPzZs3T1O3srJCVFRUTvSUezhSQUQFnLNzOSiVH97r2rUri1u3hsPNzQkKvv8REVEO0vqsvKJFi+Lhw4dwdHTUqJ8+fRply/IShEREeUndusUxb15r2NgYY8iQugwTRESkE1qPVAwePBjfffcdLly4AIVCgVevXmHr1q2YOHEihg8frosedYj/uBJRwXH+/Av07fsHUlLUGvUpU5pi6NB6DBRERKQzWo9UTJkyBWq1Gm3atEF8fDyaN28OIyMjTJw4EaNHj9ZFj7rDf2CJqABISkrB7Nkn8NNPZ6FWC6hWrQimT087TZWIiEhXtB6pUCgUmD59OiIjIxEUFITz58/j7du3+OGHH3TRn44xVBBR/nbt2mvUq7ceP/54Bmq1AAA4dOghUlPVn9mSiIgo52T5TkeGhoaoWrVqTvaS+zhSQUT5lEqVioULT+OHH06J050MDPQwe3ZLTJrUBEpllm5DRERElCVah4pWrVp9cl7usWPHstVQ7mKoIKL8586dt3Bz24MrV16LNScne/j5ucDJqaiEnRERkVxpHSpq1aql8VilUuH69esICgqCu7t7TvVFRETpWLr0HKZNC0RSUioAQKlUYOrUppg5swUMDZUSd0dERHKldahYtmxZuvXZs2cjNjY22w3lLo5UEFH+8urVezFQVK5sCz8/FzRoUELiroiISO5ybNLtN998Ax8fn5zaXe7gORVElM/Mm9ca1aoVwYQJjXD16hAGCiIiyhOyfKL2f507dw7GxsY5tbtcwlBBRHnXs2fRuHLlFb78sopYMzbWx+XLQ2BsnGNv30RERNmm9b9KX331lcZjQRDw+vVrXL58GTNnzsyxxnIFRyqIKA8SBAG+vtcxduwRJCen4tq1oahc2VZczkBBRER5jdb/MllZWWk81tPTQ6VKlTB37ly0b98+xxrLHQwVRJS3vH79HkOGHMCBA/fF2rRpgdi921XCroiIiD5Nq1CRmpoKDw8P1KhRAzY2NrrqiYhIlrZvD8KIEQcRGZkg1jw8amHZMmcJuyIiIvo8rUKFUqlE+/btcffu3YIRKjj9iYjygPDweIwY8Sd27rwj1uztzbB+fVd07VpJws6IiIgyR+vpT9WrV8ejR49QpkwZXfSTyxgqiEha+/bdw+DB+/HmTZxYc3WthlWrOqFwYVMJOyMiIso8rS8pO2/ePEycOBEHDhzA69evERMTo/EnX+FIBRFJKCkpBePGHREDRaFCJti2rQe2bevJQEFERPlKpkPF3LlzERcXh06dOuHGjRvo1q0bSpYsCRsbG9jY2MDa2jofToliqCAi6RgZ6WPTpu5QKIBu3Srh9u0RcHWtLnVbREREWsv09Kc5c+Zg2LBhOH78uC77yWUMFUSUe2Jjk/H+fRKKFbMQa82bl8aFC9+iXr3iUHD0lIiI8qlMhwpBEAAALVq0yPEmVq1ahcWLFyM0NBROTk5YsWIFGjRo8Nnttm3bhj59+qB79+7w9/fX/on5DzgR5ZJTp55iwAB/lCplhWPH3KGn98/7T/36vCs2ERHlb1qdU6GLb9G2b9+O8ePHw9PTE1evXoWTkxOcnZ3x5s2bT2735MkTTJw4Ec2aNcvxnoiIckpCggrjxx9By5a+ePw4CidPPsWKFRekbouIiChHaRUqKlasiEKFCn3yj7aWLl2KwYMHw8PDA1WrVoW3tzdMTU3h4+OT4Tapqano168f5syZg7Jly2r9nP/gSAUR6c79+3GoX38jli07j/8P9qJZs1Lo0qWitI0RERHlMK0uKTtnzpw0d9TOjuTkZFy5cgVTp04Va3p6emjbti3OnTuX4XZz586FnZ0dBg0ahL///jvrDXD6ExHpQFJSCjw9T2Dx4gdQqz/UjIyUWLCgDb77riGUSq0vvEdERJSnaRUqevfuDTs7uxx78vDwcKSmpsLe3l6jbm9vj+Dg4HS3OX36NDZu3Ijr169n6jmSkpKQlJQkPv73ZW9TUlMhqFTaN06yo/r/caLi8UKfceNGGAYO3I9bt/6ZwlmvXjFs3NgVVarYQq1OhVqdKmGHlJfxvYa0xWOGskIXx0umQ0VeuCrJ+/fv0b9/f6xfvx62traZ2mbhwoWYM2dOussuX76CsLvSvy7KPwICAqRugfKwN2+SMWLEXaSkfJjrpK+vgKurPb76yg6PH1/E48cSN0j5Bt9rSFs8Zkgb8fHxOb5Pra/+lJNsbW2hVCoRFhamUQ8LC0PRokXTrB8SEoInT56ga9euYk39/7kF+vr6uHfvHsqVK6exzdSpUzF+/HjxcUxMDBwcHAAA9erXh+DYMcdeDxVcKpUKAQEBaNeuHQwMDKRuh/KwS5eMsH79NVSvXgQDB9pg6NDuPGYo0/heQ9riMUNZERERkeP7zHSo+PjhPScZGhqibt26CAwMhIuLi/g8gYGBGDVqVJr1K1eujFu3bmnUZsyYgffv38PLy0sMC/9mZGQEIyOjdJ9fX6kP8BeQtGBgYMA3bRKlpqqhp6fQGMldssQZZcsWwqhRdREYeJTHDGUJjxvSFo8Z0oYujhWtzqnQhfHjx8Pd3R316tVDgwYNsHz5csTFxcHDwwMA4ObmhhIlSmDhwoUwNjZG9eqad5u1trYGgDT1TMkDU7qIKH8KCYnEgAF74e7uhG+/rSPWLSyMMGVKU85vJiIiWZE8VLi6uuLt27eYNWsWQkNDUatWLRw+fFg8efvZs2fQ09PVlVIYKohIO4IgwNv7MiZODEB8vArXr4eibduycHS0lro1IiIiyUgeKgBg1KhR6U53AoATJ058cltfX9+sPzFHKohIC8+eRWPQoH34669HYq1IEVOEh8czVBARkazliVAhHYYKIvo8QRDg53cD3313GDEx/1yieujQuli8uB0sLNI/b4uIiEguGCqIiD4hNDQWQ4bsx/7998VaiRIW2LixG5ydy0vYGRERUd4h71DB6U9E9Annzj1Hly6/IzIyQay5uTnBy6sDrK2NJeyMiIgob5F3qCAi+oTKlW1hbPzhbdLOzgzr1nVB9+6VJe6KiIgo75F5qOBIBRFlzMbGBBs3doOPzzWsXt0ZtramUrdERESUJ+nqWq35A6c/EdH/RUcnYuTIP/Hq1XuNeocO5bFjRy8GCiIiok/gSAURyV5AQAgGDtyHFy9i8ORJNA4c6KNxl2wiIiL6NI5UEJFsxcYmY8SIP9G+/a948SIGAHD69DM8fBgpcWdERET5C0cqiEiWTp16Cg+PvXj06J1Ya9u2LDZu7IZSpawk7IyIiCj/kXmoICK5SUhQYcaMY1i27DwE4UPN1NQAixe3w7Bh9aCnxy8biIiItCXvUMHpT0SycunSS7i5+SM4OFysNW1aCps2dUf58oUk7IyIiCh/k3eo4PQnIll5/jxGDBRGRkrMn98aY8d+AaVS3qeXERERZRdDBRHJxldfVUG/fjVw714E/PxcULVqEalbIiIiKhDkHSo4/YmowEpJUcPfPxg9elTRuDyst3cXGBkpYWCglLA7IiKigkXmY/4MFUQF0d27b9G48Ub06rUT27ff1lhmbm7IQEFERJTDZB4qiKggSU1VY+nSc6hdey0uXXoFABgz5hDi41USd0ZERFSwcfoTERUIISGR8PDYi7//fibWKlYsDD8/F5iaGkjYGRERUcEn71DB6U9E+Z4gCFi79gomTjyKuLh/RiTGjm2I+fPbMFAQERHlAnmHCo5UEOVrz59HY9CgfQgIeCTWHB2tsWlTd7Rs6ShdY0RERDIj71DBkQqifG3atGMagWLo0LpYvLgdLCyMJOyKiIhIfuQdKjhSQZSv/fxzOxw+/BBGRkps3NgNzs7lpW6JiIhIluQdKjhSQZSvhIbGomhRc/Gxvb05Dhzog0qVbGFtbSxhZ0RERPLGS8oSUZ4XERGP3r13oVYtb4SHx2ssa9iwJAMFERGRxOQdKjj9iSjP27//HqpXX4Pt228jLCwOI0celLolIiIi+g9OfyKiPCk6OhHjxh3Bpk3XxZqNjTG+/LIyBEGAgl8KEBER5RkMFUSU5/z11yMMHLgXz5/HiLXOnStg/fquKFbMQsLOiIiIKD3yDhX8ppMoT4mLS8akSQFYvfqyWLOwMISXVwcMGFCLoxNERER5lLxDBUcqiPIMQRDQooUvrlx5LdZaty4DH59uKF3aWrrGiIiI6LPkfaI2EeUZCoUCo0c3AACYmhpg5cqOCAjoz0BBRESUD8h7pIJTKYgk9d8Trt3cnPDwYSTc3JxQoUJhCTsjIiIibcg7VHD6E5EkkpNTMW/eKbx+/R7r13cT6wqFAj/80FrCzoiIiCgr5B0qOFJBlOtu3QqDm5s/rl8PBQB061YJXbtWkrgrIiIiyg55hwqOVBDlmpQUNRYvPgNPzxNQqdQAAH19PTx69E7izoiIiCi75B0qOFJBlCvu3QuHu7s/Llx4KdaqV7eDn58L6tQpJmFnRERElBPkHSqISKfUagG//HIBU6cGIjExBQCgp6fApEmNMXt2SxgZ8S2IiIioIJD5v+gcqSDSlejoRHTvvg0nTz4VaxUrFoafnwu++KKkhJ0RERFRTmOoICKdsLQ0gqGhUnz83XcNsWBBG5iaGkjYFREREemCvG9+x3MqiHRGoVBg48ZucHKyx7Fjbli+vAMDBRERUQHFkQoiyjZBELBly004OFiiVasyYt3BwQrXrg3VuMEdERERFTzyDhX8oEOUbWFhsRg69AD27r2HUqWscPPmMFhZGYvLGSiIiIgKPnlPf+JIBVG27Np1B9WqrcbevfcAAM+eRWPnzjsSd0VERES5Td4jFUSUJZGRCRg16iB+/z1IrBUpYgpv7y746qsqEnZGREREUpB3qOC0DCKtHThwH4MH70doaKxY++qrKlizpjPs7Mwk7IyIiIikIu9QwelPRJkWHZ2I8eOPwMfnuliztjbGqlWd0KdPdZ47QUREJGPyDhX8EESUaW/fxmPbttvi444dy2PDhm4oXtxCwq6IiIgoL+CJ2kSUKeXLF8Lixe1gYWGIDRu64s8/+zJQEBEREQCOVEjdAVGedf78C9SoYQczM0OxNmxYPbi4VGaYICIiIg0yH6kgov9KTEzBpEkBaNx4I6ZODdRYpqenYKAgIiKiNGQeKjhSQfRvly+/Qt2667B48VkIArBixUWcP/9C6raIiIgoj5P39CeGCiIAQHJyKubPP4X58/9GaqoAADA0VGLevFaoX7+4xN0RERFRXifvUMFzKohw61YY3N39ce1aqFirU6cYNm92QbVqdhJ2RkRERPmFvEMFRypIxlJT1fj557OYNesEkpNTAQD6+nqYMaMZpk1rBgMDpcQdEhERUX4h71DBkQqSsV9/vYkpU/45EbtatSLYvPlL1KlTTMKuiIiIKD+S+YnaRPL1zTc10bixA/T0FJg8uQmuXBnCQEFERERZIu+RCk5/IhmJiUmCpaWR+Fip1IOfnwvevIlD48YOEnZGRERE+Z28Ryo4/YlkQBAErF9/BaVKLcO5c881lpUvX4iBgoiIiLJN3qGCIxVUwL18GYNOnX7DkCEHEB2dBHd3f8THq6Rui4iIiAoYeU9/4kgFFVCCIGDr1lsYPfoQoqISxXqLFqWhVgsSdkZEREQFkbxDBUcqqAB68yYOw4YdwJ49wWKtWDFzbNjQDZ06VZCwMyIiIiqoGCqICpBdu+5g+PA/ER4eL9b69q2BFSs6olAhEwk7IyIiooJM5qGCqOCYM+cEZs8+KT62tTWFt3dn9OhRVcKuiIiISA7kfaI2z6mgAqRHj6owNPxwF2wXl8q4fXsEAwURERHlCpmPVDBUUMFRvbodlixpD2trY/TrVwMKhmYiIiLKJRypIMqHjh17jK5df0dSUopGfdSoBvjmm5oMFERERJSr5B0qOFJB+UxcXDJGjz6INm0248CB+5gz5+TnNyIiIiLSMXlPf+K3uZSPnD37HO7u/nj4MFKsXbr0CqmpaiiVMv9+gIiIiCTFTyJEeVxiYgomTw5As2abxEBhYqIPL68OOHLkGwYKIiIikpy8Ryo4/YnyuCtXXsHd3R+3b78Va198URJ+fi6oWLGwhJ0RERER/UPeX3Fy+hPlYfPnn8IXX2wUA4WhoRI//tgGp097MFAQERFRnsKRCqI8KikpFSkpagBA7dpFsXnzl6he3U7iroiIiIjSkneo4EgF5WEzZjTH4cMP0alTBUyf3gwGBkqpWyIiIiJKl7xDBUcqKI948CAC58+/QP/+TmLN0FCJs2cHQV9f3rMUiYiIKO+TeaggkpZaLWDVqouYPPkvpKSoUaOGPWrVKiouZ6AgIiKi/EDmn1g4UkHSefo0Cm3bbsaYMYeRkJAClUqNuXN5MzsiIiLKf+QdKnhOBUlAEARs3HgVNWqswfHjT8T6qFH1sWXLl9I1RkRERJRFMp/+xFBBuevVq/cYPHg/Dh58INZKlbKCj083tGlTVsLOiIiIiLJO3qGCIxWUSwRBwO+/B2HUqIN49y5RrA8aVBtLlzrD0tJIwu6IiIiIskfeoYIjFZRLVCo15s07JQaKYsXMsX59V3TuXFHizoiIiIiyj+dUEOUCQ0Ml/PxcoFQq0LdvDQQFjWCgICIiogJD5iMVRLrx7l0CoqOT4OhoLdbq1y+BmzeHo2rVItI1RkRERKQD8h6p4PQn0oFDhx6gevU1cHXdhZQUtcYyBgoiIiIqiOQdKjj9iXJQTEwSBg/eh06dfsOrV+9x8eJLLFlyVuq2iIiIiHRO5tOfGCooZxw//hgeHnvx9Gm0WHN2Lod+/WpK2BURERFR7pB3qOBIBWVTfLwKU6f+hV9+uSjWzMwMsHSpMwYPrgMFjzEiIiKSAXmHCqJsOHfuOdzd/fHgQaRYa968NDZt6o6yZW0k7IyIiIgod+WJcypWrVoFR0dHGBsbo2HDhrh48WKG665fvx7NmjWDjY0NbGxs0LZt20+uT6QLz55Fo3lzXzFQGBvrY9kyZxw/7s5AQURERLIjeajYvn07xo8fD09PT1y9ehVOTk5wdnbGmzdv0l3/xIkT6NOnD44fP45z587BwcEB7du3x8uXL7V6XiEnmifZKlXKCqNHNwAANGxYAtevD8XYsV9AT4/TnYiIiEh+JA8VS5cuxeDBg+Hh4YGqVavC29sbpqam8PHxSXf9rVu3YsSIEahVqxYqV66MDRs2QK1WIzAwULsn5lx30oJKlQq1WjOKzp/fGitXdsTp0wNRqZKtRJ0RERERSU/SUJGcnIwrV66gbdu2Yk1PTw9t27bFuXPnMrWP+Ph4qFQqFCpUSMtnZ6igzLl9+w2aNfPDn3+Ga9RNTAwwcmQD6OtLns2JiIiIJCXpidrh4eFITU2Fvb29Rt3e3h7BwcGZ2sfkyZNRvHhxjWDyb0lJSUhKShIfx8TEfPiLQgGVSpW1xkkWUlPVWL78Ijw9TyI5ORVBQQqMGhWGatXsP78xyd7H9xe+z5A2eNyQtnjMUFbo4njJ11d/+vHHH7Ft2zacOHECxsbG6a6zcOFCzJkzJ01dUAMHDx7UdYuUT716lYRffnmG4OA4sWZnZ4gTJ07j6VMTCTuj/CYgIEDqFigf4nFD2uIxQ9qIj4/P8X1KGipsbW2hVCoRFhamUQ8LC0PRokU/ue3PP/+MH3/8EX/99Rdq1sz4BmNTp07F+PHjxccxMTFwcHCAQk+BTp06Ze8FUIGjVgvw9r6CqVOPISEhBcCH02/GjKmPJk2S0LmzMwwMDCTukvIDlUqFgIAAtGvXjscMZRqPG9IWjxnKioiIiBzfp6ShwtDQEHXr1kVgYCBcXFwAQDzpetSoURlu99NPP2H+/Pk4cuQI6tWr98nnMDIygpGRUTpLFPzlIw1Pn0Zh4MB9OHbssVgrV84Gvr4uaNiwGA4ePAgDAwMeN6QVHjOUFTxuSFs8ZkgbujhWJJ/+NH78eLi7u6NevXpo0KABli9fjri4OHh4eAAA3NzcUKJECSxcuBAAsGjRIsyaNQu//fYbHB0dERoaCgAwNzeHubl55p+YV3+ifzl9+hk6ddqK9++TxdrIkfWxaFFbmJkZcq4qERER0SdIHipcXV3x9u1bzJo1C6GhoahVqxYOHz4snrz97Nkz6On9c3WdNWvWIDk5GT179tTYj6enJ2bPnq3FMzNU0D+cnOxRuLAp3r9PhoODJXx8uqNt27JSt0VERESUL0geKgBg1KhRGU53OnHihMbjJ0+e5MyTcqSC/sXCwgi+vt2xefMNLF3qDCur9E/8JyIiIqK0ZHyBfYYKuXr7Ng5ubnvw5EmURr1FC0ds3NidgYKIiIhIS3lipEISHKmQJX//YAwZsh9v38bj+fMYBAa6QU+PxwIRERFRdsh4pILk5N27BPTvvwdffrkdb99+uDbzrVthePgwUuLOiIiIiPI/+Y5UcPqTbBw+/BCDBu3Dq1fvxVq3bpWwbl0X2NtrccUwIiIiIkoXQwUVWO/fJ2HixKNYt+6qWLOyMsIvv3RE//41oeAUOCIiIqIcwVBBBdLffz+Fm5u/xsnY7dqVxcaN3eDgYCVdY0REREQFEEMFFUhxcSoxUJiZGWDJkvYYMqQuRyeIiIiIdEC+oYIfLgu0Dh3KY/DgOggODoevrwvKlrWRuiUiIiKiAku+oYIKjKSkFPz22y0MGFBLYyTCy6sDjIz0eclYIiIiIh2TcajgB82C4Nq113Bz80dQ0Buo1QIGDaojLjMxMZCwMyIiIiL5kO99Kjj9KV9TqVIxd+5JNGiwAUFBbwAAkyf/hbi4ZIk7IyIiIpIfGY9UUH51585buLntwZUrr8Wak5M9/PxcYGZmKGFnRERERPIk41DBkYr8JjVVjWXLzmPGjGNISkoFACiVCkyd2hQzZ7aAoaFS4g6JiIiI5Em+oYLTn/KVhw8jMWCAP86ceS7WKle2xebNLqhfv4SEnRERERGRfM+poHxlwYK/xUChUAATJjTC1atDGCiIiIiI8gD5jlRw+lO+8vPP7XH48EOYmBjAz88FTZuWkrolIiIiIvo/+YYKTn/KswRBwJMnUShT5p8b1hUqZIJDh/qhXLlCMDfnydhEREREeYmMpz8xVORFr1+/R7du21C37jq8fv1eY5mTU1EGCiIiIqI8SL6hgiMVec727UGoXn0NDhy4j3fvEjF48H4IgiB1W0RERET0GfKd/sSRijwjPDweI0b8iZ0774g1e3szDB1aFwqGPyIiIqI8j6GCJLVv3z0MHrwfb97EiTVX12pYtaoTChc2lbAzIiIiIsosGYcKklJUVCLGjj0MP78bYq1QIROsXt0Jrq7VJeyMiIiIiLQl31DBaTWSEQQBrVv74dq1ULHWtWtFrFvXFUWLmkvYGRERERFlhXxP1Ob0J8koFApMm9YMAGBpaQRf3+7Yu7c3AwURERFRPsWRCsoVarUAPb1/fuY9e1bFTz+1Re/e1eHgYCVhZ0RERESUXfINFRypyBUJCSpMmxaI0NA4/P57D41l33/fRKKuiIiIiCgnyTdUcKRC5y5ceAF3d3/cuxcBAHBxqcSTsImIiIgKIPmGCtKZpKQUzJ17Ej/+eAZq9Yeb1xkZKREVlShxZ0RERESkCzIOFRyp0IXr10Ph7u6PmzfDxFr9+sXh5+eCKlWKSNgZEREREekKQwXliJQUNX788TTmzDmJlBQ1AMDAQA+eni0weXJT6OvL+EJjRERERAWcfEMFz6nIMVFRiWjffgsuXXol1mrWtIefnwtq1SoqYWdERERElBtk/PUxQ0VOsbIyQrFiFgAAPT0Fpk1riosXv2WgICIiIpIJGY9USN1AwaFQKLB2bRdERMRjyZL2aNiwpNQtEREREVEukm+ooCwRBAHe3pdRqpQVOneuKNaLFjXH6dMDJeyMiIiIiKTCUEGZ9vx5NAYN2oeAgEewtzfD7dsjULiwqdRtEREREZHE5HtOBU/UzjRBEODrex3Vq69BQMAjAEBYWBz27bsncWdERERElBfIeKSCoSIzQkNjMWTIfuzff1+slShhgY0bu8HZubyEnRERUW5LTU2FSqWSug36F5VKBX19fSQmJiI1NVXqdiiPMDAwgFKpzNXnZKigDG3fHoQRIw4iMjJBrLm7O2H58g6wtjaWsDMiIspNgiAgNDQUUVFRUrdC/yEIAooWLYrnz59DwVkY9C/W1tYoWrRorh0X8g0V/MXLUEREPEaMOIgdO26LNTs7M6xb1wXdu1eWsDMiIpLCx0BhZ2cHU1NTfnjNQ9RqNWJjY2Fubg49PfnOaqd/CIKA+Ph4vHnzBgBQrFixXHle+YYKjlRkKD5ehcOHH4qPe/WqitWrO8PWlidlExHJTWpqqhgoChcuLHU79B9qtRrJyckwNjZmqCCRiYkJAODNmzews7PLlalQPPooDQcHK3h5dUChQibYtq0HduzoxUBBRCRTH8+hMDXlvwNE+cnH39ncOg9KviMVHLoVBQY+Qv36JWBpaSTW3N2d0LVrRV4yloiIAIBTnojymdz+nZXxSAXfHGNjkzF8+AG0bbsF48Yd1limUCgYKIiIiIgoU+QbKmT+jcupU0/h5OQNb+8rAAAfn+s4ffqZxF0RERFRXhEREQE7Ozs8efJE6lboX5KTk+Ho6IjLly9L3YoG+YYKmY5UJCSoMGHCEbRs6YtHj94BAExNDbBqVSc0buwgcXdEREQ5Y8CAAVAoFFAoFDAwMECZMmUwadIkJCYmpln3wIEDaNGiBSwsLGBqaor69evD19c33f3+8ccfaNmyJaysrGBubo6aNWti7ty5iIyM/GQ/x48fR6dOnVC4cGGYmpqiatWqmDBhAl6+fJkTL1cn5s+fj+7du8PR0THNMmdnZyiVSly6dCnNspYtW2Ls2LFp6r6+vrC2ttaoxcTEYPr06ahcuTKMjY1RtGhRtG3bFrt374YgCDn0StI6ceIE6tSpAyMjI5QvXz7D/9//tmPHDtSqVQumpqYoXbo0Fi9enGadVatWoUqVKjAxMUGlSpWwefNmjeUtW7YUj8t//+ncubO4TmxsLEaNGoWSJUvCxMQEVatWhbe3t7jc0NAQEydOxOTJk7P+A9ABhgoZuXjxJerUWYelS8/j4+9p06alcOPGMIwYUR96evL7mRARUcHVoUMHvH79Go8ePcKyZcuwdu1aeHp6aqyzYsUKdO/eHU2aNMGFCxdw8+ZN9O7dG8OGDcPEiRM11p0+fTpcXV1Rv359HDp0CEFBQViyZAlu3LiBLVu2ZNjH2rVr0bZtWxQtWhR//PEH7ty5A29vb0RHR2PJkiVZfn3JyclZ3vZz4uPjsXHjRgwaNCjNsmfPnuHs2bMYNWoUfHx8svwcUVFRaNy4MTZv3oypU6fi6tWrOHXqFFxdXTFp0iRER0dn5yVk6PHjx+jcuTNatWqF69evY+zYsfj2229x5MiRDLc5dOgQ+vXrh2HDhiEoKAirV6/GsmXLsHLlSnGdNWvWYOrUqZg9ezZu376NOXPmYOTIkdi/f7+4zu7du/H69WvxT1BQEJRKJXr16iWuM378eBw+fBi//vor7t69i7Fjx2LUqFHYt2+fuE6/fv1w+vRp3L79z+X/JSfITHR0tABAiFpTXepWck1SUoowfXqgoFTOEYDZAjBbMDL6Qfj55zNCSkqq1O3lC8nJyYK/v7+QnJwsdSuUT/CYoazIi8dNQkKCcOfOHSEhIUHqVrTi7u4udO/eXaP21VdfCbVr1xYfP3v2TDAwMBDGjx+fZvtffvlFACCcP39eEARBuHDhggBAWL58ebrP9+7du3Trz58/FwwNDYWxY8d+cjtPT0/ByclJY9myZcuE0qVLp3lN8+bNE4oVKyY4OjoKU6ZMEerWrSukpmr+e16zZk1hzpw54uP169cLlStXFoyMjIRKlSoJq1atSrefj3bu3CkUKVIk3WWzZ88WevfuLdy9e1ewsrIS4uPjNZa3aNFC+O6779Jst2nTJsHKykp8PHz4cMHMzEx4+fJlmnXfv38vqFSqT/aYVZMmTRKqVaumUXN1dRWcnZ0z3KZPnz5Cz549NWq//PKLULJkSUGtVguCIAiNGjUSJk6cqLHO+PHjhSZNmmS432XLlgkWFhZCbGysWKtWrZowd+5cjfXq1KkjTJ8+XaPWqlUrYcaMGRnu+1O/u+Hh4QIAITo6OsPttcWrP8nAjh23MX/+3+LjevWKw8/PBVWrFpGwKyIiyrd+rQfEheb+85oVBb7J2jzyoKAgnD17FqVLlxZru3btgkqlSjMiAQBDhw7FtGnT8Pvvv6Nhw4bYunUrzM3NMWLEiHT3/99pPR/t3LkTycnJmDRpklbbZSQwMBCWlpYICAgA8OE+FT/++CNCQkJQoUIFAMDt27dx8+ZN/PHHHwCArVu3YtasWVi5ciVq166Na9euYfDgwTAzM4O7u3u6z/P333+jbt26aeqCIGDTpk1YtWoVKleujPLly2PXrl3o37+/Vq9DrVZj27Zt6NevH4oXL55mubm5eYbb/v333+jYseMn97927Vr069cv3WXnzp1D27ZtNWrOzs7pTtn6KCkpKc1llU1MTPDixQs8ffoUjo6OSEpKgrGxcZp1Ll68CJVKBQMDgzT73bhxI3r37g0zMzOx1rhxY+zbtw8DBw5E8eLFceLECdy/fx/Lli3T2LZBgwb4+++//7tLycg3VMho+lPfvjXg63sdJ08+xaxZzTFlSlMYGOj+JihERFRAxYUCsXn3XICPDhw4AHNzc6SkpCApKQl6enoa01Xu378PKyurdO84bGhoiLJly+L+/fsAgAcPHqBs2bLpfjD8lAcPHsDS0jLH7mpsZmaGDRs2wNDQEMCHD+fVq1fH77//jlmzZgH4ECIaNmyI8uXLAwA8PT2xZMkSfPXVVwCAMmXK4M6dO1i7dm2GoeLp06fpftj/66+/EB8fD2dnZwDAN998g40bN2odKsLDw/Hu3TtUrlxZq+0AoF69erh+/fon17G3t89wWWhoaJrl9vb2iImJQUJCgnjjuH9zdnbGuHHjMGDAALRq1QoPHz4Up669fv0ajo6OcHZ2xoYNG+Di4oI6dergypUr2LBhA1QqFcLDw9McAxcvXkRQUBA2btyoUV+xYgWGDBmCkiVLQl9fH3p6eli/fj2aN2+usV7x4sXx9OnTT/4ccpNsQ4VQgEcqwsPjNW5Wp6engI9Pd0RExKN27dy5VTsRERVgZkXzxfO2atUKa9asQVxcHJYtWwZ9fX306NEjS08tZPGkYUEQcvR+ATVq1BADxUe9evUSQ4UgCPj9998xfvx4AEBcXBxCQkIwaNAgDB48WNwmJSUFVlZWGT5PQkJCmm/dAcDHxweurq7Q1//wEbJPnz74/vvvERISgnLlymX6dWT15wl8+Pb/Y2DKLYMHD0ZISAi6dOkClUoFS0tLfPfdd5g9e7Z4J/OZM2ciNDQUX3zxBQRBgL29Pdzd3fHTTz+le7fzjRs3okaNGmjQoIFGfcWKFTh//jz27duH0qVL49SpUxg5ciSKFy+uMcJiYmKC+Ph43b5wLcg2VBTEkQq1WoCX13lMn34Mf/7ZF61alRGXlSplhVKlMn7zICIiyrQsTkHKbWZmZuKHTx8fHzg5OWmcfFyxYkVER0fj1atXab6VT05ORkhICFq1aiWue/r06QynsWTk43O8fv36k6MVenp6aT5op3cn5H9Pk/moR48emD17Nq5evYqEhAQ8f/4crq6uAD5cSQgA1q9fj4YNG2psp1RmPGvB1tYW796906hFRkZiz549UKlUWLNmjVhPTU2Fj48P5s+fDwCwtLRM9yTrqKgoMcgUKVIE1tbWCA4OzrCHjGR3+lPRokURFhamUQsLC4OlpWW6oxTAh/t3LVq0CAsWLEBoaCiKFCmCwMBAAEDZsmUBfPiQ7+Pjg7Vr1yIsLAzFihXDunXrYGFhgSJFNKecx8XFYdu2bZg7d65GPSEhAdOmTcOePXvEK0LVrFkT169fx88//6wRKiIjI9PsV0ryvfpTARupePToHVq18sP48UeRkJACD4+9iIlJkrotIiKiPEFPTw/Tpk3DjBkzkJCQAODDh3EDA4N0r8Dk7e2NuLg49OnTBwDQt29fxMbGYvXq1enuPyoqKt16z549YWhoiJ9++umT2xUpUgShoaEaweJzU3w+KlGiBFq0aIGtW7di69ataNeuHezs7AB8mNZTvHhxPHr0COXLl9f4U6ZMmQz3Wbt2bdy5c0ejtnXrVpQsWRI3btzA9evXxT9LliyBr68vUlNTAQCVKlXC1atX0+zz6tWrqFixIoAP/z969+6NrVu34tWrV2nWjY2NRUpKSrq9fZz+9Kk/3bp1y/C1NWrUSAwEHwUEBKBRo0YZbvORUqlEiRIlYGhoiN9//x2NGjVK88HewMAAJUuWhFKpxLZt29ClS5c0IxU7d+5EUlISvvnmG426SqWCSqVKs75SqYRardaoBQUFoXbt2p/tOdfk2Cnf+cTHqz+9W1f78yvnA2q1Wliz5pJgZjZfvLITMFsYO/aQEB+fd64ekt/lxSuyUN7GY4ayIi8eNwXp6k8qlUooUaKEsHjxYrG2bNkyQU9PT5g2bZpw9+5d4eHDh8KSJUsEIyMjYcKECRrbT5o0SVAqlcL3338vnD17Vnjy5Inw119/CT179szwqlCCIAirVq0SFAqFMHDgQOHEiRPCkydPhNOnTwtDhgwRrzx1584dQaFQCD/++KPw8OFDYeXKlYKNjU26V3/6t9TUVOHdu3fC2rVrheLFiwu2trbCli1bNNZZv369YGJiInh5eQn37t0Tbt68Kfj4+AhLlizJsOebN28K+vr6QmRkpFhzcnISJk+enGbdqKgowdDQUDhw4IAgCIIQEhIiGBsbC6NHjxZu3LghBAcHC0uWLBH09fWFQ4cOidtFREQIlStXFkqWLCn4+fkJt2/fFu7fvy9s3LhRKF++fIZX1MquR48eCaampsL3338v3L17V1i1apWgVCqFw4cPi+usWLFCaN26tfj47du3wpo1a4S7d+8K165dE8aMGSMYGxsLFy5cENe5d++esGXLFuH+/fvChQsXBFdXV6FQoULC48eP0/TQtGlTwdXVNd3+WrRoIVSrVk04fvy48OjRI2HTpk2CsbGxsHr1ao31SpcuLWzevDnD15nbV3+ScaioI3Ur2fbsWZTQvv0WjTDh6LhcOH78sdStFTh58R96ytt4zFBW5MXjpiCFCkEQhIULFwpFihTRuITn3r17hWbNmglmZmaCsbGxULduXcHHxyfd/W7fvl1o3ry5YGFhIZiZmQk1a9YU5s6d+9kPwAEBAYKzs7NgY2MjGBsbC5UrVxYmTpwovHr1SlxnzZo1goODg2BmZia4ubkJ8+fPz3SoiIiIEIyMjARTU1Ph/fv3aZ5/69atQq1atQRDQ0PBxsZGaN68ubB79+5P9tygQQPB29tbEARBuHz5sgBAuHjxYrrrduzYUfjyyy/FxxcvXhTatWsnFClSRLCyshIaNmwo7NmzJ812UVFRwpQpU4QKFSoIhoaGgr29vdC2bVthz5494qVadeH48ePiz6Ns2bLCpk2bNJZ7enpq/Ozfvn0rfPHFF4KZmZlgamoqtGnTRrzc8Ed37twRatWqJZiYmAiWlpZC9+7dheDg4DTPHRwcLAAQjh49mm5vr1+/FgYMGCAUL15cMDY2FipVqiQsWbJE4+dx9uxZwdraOs3lfP8tt0OFQhB0eLvCPCgmJgZWVlZ4t64urAfnjzmh/yUIAjZvvoExYw5rTHEaOrQuFi9uBwsLIwm7K5hUKhUOHjyITp06aX3lD5InHjOUFXnxuElMTMTjx49RpkyZdE/cJWmp1WrExMTA0tIy3ZOBs+PPP//E999/j6CgoBzfN2WPq6srnJycMG3atAzX+dTvbkREBGxtbREdHQ1LS8sc6UnGJ2rnX7NmHce8ef9cl7hECQts2NANHTrk7pUQiIiIqODq3LkzHjx4gJcvX8LBwUHqduj/kpOTUaNGDYwbN07qVjTIOHbm3xO13dycYGLyIQ/2718Tt24NZ6AgIiKiHDd27FgGijzG0NAQM2bMyPBKVVKR70hFPrr6k/Cfa1xXqFAYq1Z1go2NCVxctL9pDBERERFRTuJIRR63f/89tGzph/h4zWtVe3jUZqAgIiIiojxBxqEib4uOTsTAgXvRrds2nDr1FFOn/iV1S0RERERE6eL0pzzor78eYeDAvXj+PEasPXoUhZQUNfT1mQOJiIiIKG+Rb6jIg9Of4uKSMWlSAFav/udStxYWhli+vAM8PGppnFdBRERERJRXMFTkEadPP8OAAf4ICXkn1lq3LgMfn24oXdpausaIiIiIiD5DvnNp8tC3/jNmHEPz5pvEQGFqaoCVKzsiIKA/AwUREZEOKRQK+Pv7S91GjhswYABcXFykboNkRL6hIg+NVFhYGOLjfc0bN3bA9etDMXJkA+jp5Z0eiYiI8pvQ0FCMHj0aZcuWhZGRERwcHNC1a1cEBgZK3Vq2nThxAgqFAlFRUeku9/Lygq+vb672RPIm4+lPecfEiY1x+HAIOneugHHjvoBSKeOsR0RElAOePHmCJk2awNraGosXL0aNGjWgUqlw5MgRjBw5EsHBwVK3qFNWVlZSt0AyI99PrxJNf7p5Mwze3pc1akqlHgID3TBxYmMGCiIiohwwYsQIKBQKXLx4ET169EDFihVRrVo1jB8/HufPn9dYNzw8HF9++SVMTU1RoUIF7Nu3T1yWmpqKQYMGoUyZMjAxMUGlSpXg5eWlsf3HqUY///wzihUrhsKFC2PkyJFQqf65x1RSUhImT54MBwcHGBkZoXz58ti4caO4PCgoCB07doS5uTns7e3Rv39/hIeHZ/n1/3f6U8uWLTFmzBhMmjQJhQoVQtGiRTF79myNbaKiovDtt9+iSJEisLS0ROvWrXHjxo0s90DyIuNPsLkbKlJS1Fi48G/Uq7cOI0cexPnzLzSWc6oTERFRzoiMjMThw4cxcuRImJmZpVlubW2t8XjOnDn4+uuvcfPmTXTq1An9+vVDZGQkAECtVqNkyZLYuXMn7ty5g1mzZmHatGnYsWOHxj6OHz+OkJAQHD9+HH5+fvD19dWYfuTm5obff/8dv/zyC+7evYu1a9fC3NwcwIcP861bt0bt2rVx+fJlHD58GGFhYfj6669z9Ofi5+cHMzMzXLhwAT/99BPmzp2LgIAAcXmvXr3w5s0bHDp0CFeuXEGdOnXQpk0b8WdB9Cnynf6UiyMVwcHhcHf3x8WLL8XaTz+dwe7drrnWAxERUU5auvQcli4999n16tQphn37+mjUunX7HVevvv7stuPHN8L48Y207u3hw4cQBAGVK1fO1PoDBgxAnz4felywYAF++eUXXLx4ER06dICBgQHmzJkjrlumTBmcO3cOO3bs0PjQb2Njg5UrV0KpVKJy5cro3LkzAgMDMXjwYNy/fx87duxAQEAA2rZtCwAoW7asuO3KlStRu3ZtLFiwQKz5+PjAwcEB9+/fR8WKFbX+GaSnZs2a8PT0BABUqFABK1euRGBgINq1a4fTp0/j4sWLePPmDYyMjAAAP//8M/z9/bFr1y4MGTIkR3qggku+oSIXRirUagFeXucxbdoxJCamAPgwIjFpUmPMnt1S589PRESkKzExSXj58v1n13NwSDu3/+3b+ExtGxOTlKXehI9XP8mkmjVrin83MzODpaUl3rx5I9ZWrVoFHx8fPHv2DAkJCUhOTkatWrU09lGtWjUolUrxcbFixXDr1i0AwPXr16FUKtGiRYt0n//GjRs4fvy4OHLxbyEhITkaKv6tWLFi4uu8ceMGYmNjUbhwYY11EhISEBISkiPPTwUbQ4WOPHr0Dh4ee3Hq1FOxVrFiYfj5ueCLL0rq9LmJiIh0zdLSCCVKWHx2vSJFTNOtZWZbS0ujLPVWoUIFKBSKTJ+MbWBgoPFYoVBArVYDALZt24aJEydiyZIlaNSoESwsLLB48WJcuHAh0/swMTH55PPHxsaia9euWLRoUZplxYoVy9RryIxP9RgbG4tixYrhxIkTabb773QxovTIOFTohiAIWLfuCiZMOIq4uH9O0Pruu4ZYsKANTE0NPrE1ERFR/pDVqUkA0kyHymmFChWCs7MzVq1ahTFjxqQ5ryIqKirTH5TPnDmDxo0bY8SIEWJN22/ua9SoAbVajZMnT4rTn/6tTp06+OOPP+Do6Ah9fWk+mtWpUwehoaHQ19eHo6OjJD1Q/ibfE7V1dE5FSooa3t5XxEBRurQVjh1zw/LlHRgoiIiIcsmqVauQmpqKBg0a4I8//sCDBw9w9+5d/PLLL2jUKPNhqEKFCrh8+TKOHDmC+/fvY+bMmbh06ZJWvTg6OsLd3R0DBw6Ev78/Hj9+jBMnTogne48cORKRkZHo06cPLl26hJCQEBw5cgQeHh5ITU395L5v3bqFW7du4fr167h+/XqWr9bUtm1bNGrUCC4uLjh69CiePHmCs2fPYvr06bh8+fLnd0CyJ+ORCt2ECgMDJTZvdkG9euvh7u6EJUvaw8Iia8O3RERElDVly5bF1atXMX/+fEyYMAGvX79GkSJFULduXaxZsybT+xk6dCiuXbsGV1dXKBQK9OnTByNGjMChQ4e06mfNmjWYNm0aRowYgYiICJQqVQrTpk0DABQvXhxnzpzB5MmT0b59eyQlJaF06dLo0KED9PQ+/f1vy5YtNR4rlUqkpKRo1RvwYSrUwYMHMX36dHh4eODt27coWrQomjdvDnt7e633R/KjELQ9mymfi4mJgZWVFd75tYG121/Z3l9YWCyiohJRqZKtRv3Jkyg4Olpne/+UN6hUKhw8eBCdOnVKMyeVKD08Zigr8uJxk5iYiMePH6NMmTIwNjaWuh36D7VajZiYGFhaWn42gJC8fOp3NyIiAra2toiOjoalpWWOPJ+Mj77sj1Ts2nUH1aqtxtdf70JysubwJAMFEREREcmFfENFNjJFZGQC+vb9A7167URERAJu3gzDokWnc643IiIiIqJ8hOdUaOnPP+/j22/3IzQ0Vqx99VUVDBtWL6caIyIiIiLKV2QcKrQTHZ2I8eOPwMfnulizsTHGypWd0KdPdShy8Q7dRERERER5CUNFJgQGPoKHx148fx4j1jp1qoD167uiePHP37yHiIiIiKggk2+oyOTIwvPn0ejQYStSUj7ccdLCwhDLljlj4MDaHJ0gIiLZkNnFIonyvdz+nZXvidqZPKfCwcEKU6Y0AQC0bl0Gt24Nx6BBdRgoiIhIFj5e2jY+Pl7iTohIGx9/Z3Pr8tQcqfiPxMQU6OvrQV//n7w1c2YLVKxYGP361YSeHsMEERHJh1KphLW1Nd68eQMAMDU15RdreYharUZycjISExN5nwoC8GGEIj4+Hm/evIG1tTWUSmWuPK98Q0U6IxWXL7+Cm9se9O9fE1OnNhPrhoZK9O/vlJvNERER5RlFixYFADFYUN4hCAISEhJgYmLCsEcarK2txd/d3CDjUPGP5ORUzJt3CgsW/I3UVAGenifQuXNF1KzJ29ITEREpFAoUK1YMdnZ2UKlUUrdD/6JSqXDq1Ck0b948z9yFnaRnYGCQayMUH+WJULFq1SosXrwYoaGhcHJywooVK9CgQYMM19+5cydmzpyJJ0+eoEKFCli0aBE6deqk3ZP+P83fuhUGNzd/XL8eKi6qUcMeBgYcQiQiIvo3pVKZ6x9U6NOUSiVSUlJgbGzMUEGSkvyT8/bt2zF+/Hh4enri6tWrcHJygrOzc4ZDrGfPnkWfPn0waNAgXLt2DS4uLnBxcUFQUJBWz5uSqsCPP55G3brrxEChr6+H2bNb4Pz5QahSpUi2XxsRERERkRxIHiqWLl2KwYMHw8PDA1WrVoW3tzdMTU3h4+OT7vpeXl7o0KEDvv/+e1SpUgU//PAD6tSpg5UrV2r1vB3mlMPUqYFQqT5cKrZatSK4cOFbeHq2hIEBv4UhIiIiIsosSUNFcnIyrly5grZt24o1PT09tG3bFufOnUt3m3PnzmmsDwDOzs4Zrp+RKyGm/38+BSZPboIrV4agTp1iWr4CIiIiIiKS9JyK8PBwpKamwt5e84Roe3t7BAcHp7tNaGhouuuHhoamu35SUhKSkpLEx9HR0R+XoGxZG6xc2QENGpRAbGw0YmOz/lqoYFOpVIiPj0dERATnrFKm8JihrOBxQ9riMUNZERkZCSBnb5CXJ07U1qWFCxdizpw56SxZhkePgE6dJud6T0REREREUouIiICVlVWO7EvSUGFrawulUomwsDCNelhYWIbX1S1atKhW60+dOhXjx48XH0dFRaF06dJ49uxZjv0QqeCLiYmBg4MDnj9/DktLS6nboXyAxwxlBY8b0haPGcqK6OholCpVCoUKFcqxfUoaKgwNDVG3bl0EBgbCxcUFwIc7QwYGBmLUqFHpbtOoUSMEBgZi7NixYi0gIACNGjVKd30jIyMYGRmlqVtZWfGXj7RmaWnJ44a0wmOGsoLHDWmLxwxlRU7ehV3y6U/jx4+Hu7s76tWrhwYNGmD58uWIi4uDh4cHAMDNzQ0lSpTAwoULAQDfffcdWrRogSVLlqBz587Ytm0bLl++jHXr1kn5MoiIiIiIZEvyUOHq6oq3b99i1qxZCA0NRa1atXD48GHxZOxnz55ppKjGjRvjt99+w4wZMzBt2jRUqFAB/v7+qF69ulQvgYiIiIhI1iQPFQAwatSoDKc7nThxIk2tV69e6NWrV5aey8jICJ6e/2vvToOauto4gP8JGII0qFQRorgLOi5VRC0u46ulBVfqBq2MxYpLBaSjrcuoFdGi1iqtOu5WsZYRl3EbQVDa0gJd3EAdQRABlynaUVtXKEue90OHTCOghmgS8f+byYd77jnnPjc+hjw59yYR1V4SRVQT5g0ZijlDtcG8IUMxZ6g2XkTeWMnz/C4pIiIiIiJ65Zj9F7WJiIiIiOjlxqKCiIiIiIiMwqKCiIiIiIiMUieLinXr1qFVq1ZQqVTo3bs3Tpw48cT+e/fuRYcOHaBSqdClSxckJCSYKFKyJIbkzZYtW9C/f380atQIjRo1gre391PzjOoeQ19rKsXFxcHKykr3+zz0ajE0b/7++2+EhobCxcUFtra2cHNz49+pV4yhOfP111/D3d0ddnZ2cHV1xYwZM1BSUmKiaMkS/Pzzzxg+fDg0Gg2srKxw8ODBp45JSUmBh4cHbG1t0a5dO8TExBh2UKlj4uLiRKlUyrZt2+TChQsyefJkadiwody8ebPa/unp6WJtbS0rVqyQrKwsWbBggdSrV0/Onz9v4sjJnAzNm3Hjxsm6deskIyNDsrOzZcKECdKgQQO5fv26iSMnczE0ZyoVFBRIs2bNpH///uLn52eaYMliGJo3//zzj3h6esqQIUMkLS1NCgoKJCUlRTIzM00cOZmLoTkTGxsrtra2EhsbKwUFBZKUlCQuLi4yY8YME0dO5pSQkCDz58+X/fv3CwA5cODAE/vn5+dL/fr1ZebMmZKVlSVr164Va2trSUxMfOZj1rmiolevXhIaGqrbrqioEI1GI8uWLau2v7+/vwwdOlSvrXfv3jJ16tQXGidZFkPz5nHl5eWiVqtlx44dLypEsjC1yZny8nLp06ePbN26VYKCglhUvIIMzZsNGzZImzZtpLS01FQhkoUxNGdCQ0Nl0KBBem0zZ86Uvn37vtA4yXI9S1Exe/Zs6dSpk15bQECA+Pj4PPNx6tTlT6WlpTh9+jS8vb11bQqFAt7e3vj111+rHfPrr7/q9QcAHx+fGvtT3VObvHnco0ePUFZWBkdHxxcVJlmQ2ubM4sWL4eTkhODgYFOESRamNnlz+PBheHl5ITQ0FE2bNkXnzp2xdOlSVFRUmCpsMqPa5EyfPn1w+vRp3SVS+fn5SEhIwJAhQ0wSM72cnsf7YYv48bvn5datW6ioqND9Gnelpk2b4uLFi9WOuXHjRrX9b9y48cLiJMtSm7x53Jw5c6DRaKr8h6S6qTY5k5aWhm+++QaZmZkmiJAsUW3yJj8/Hz/88AMCAwORkJCAvLw8hISEoKysDBEREaYIm8yoNjkzbtw43Lp1C/369YOIoLy8HB999BHmzZtnipDpJVXT++F79+6huLgYdnZ2T52jTq1UEJnD8uXLERcXhwMHDkClUpk7HLJA9+/fx/jx47FlyxY0btzY3OHQS0Sr1cLJyQmbN29Gjx49EBAQgPnz52Pjxo3mDo0sVEpKCpYuXYr169fjzJkz2L9/P+Lj47FkyRJzh0Z1XJ1aqWjcuDGsra1x8+ZNvfabN2/C2dm52jHOzs4G9ae6pzZ5U2nlypVYvnw5kpOT0bVr1xcZJlkQQ3Pm8uXLKCwsxPDhw3VtWq0WAGBjY4OcnBy0bdv2xQZNZleb1xoXFxfUq1cP1tbWuraOHTvixo0bKC0thVKpfKExk3nVJmc+++wzjB8/HpMmTQIAdOnSBQ8fPsSUKVMwf/58KBT8PJmqqun9sIODwzOtUgB1bKVCqVSiR48e+P7773VtWq0W33//Pby8vKod4+XlpdcfAI4fP15jf6p7apM3ALBixQosWbIEiYmJ8PT0NEWoZCEMzZkOHTrg/PnzyMzM1D1GjBiBgQMHIjMzE66urqYMn8ykNq81ffv2RV5enq4IBYDc3Fy4uLiwoHgF1CZnHj16VKVwqCxK/71nl6iq5/J+2PB7yC1bXFyc2NraSkxMjGRlZcmUKVOkYcOGcuPGDRERGT9+vMydO1fXPz09XWxsbGTlypWSnZ0tERER/ErZV5ChebN8+XJRKpWyb98+KSoq0j3u379vrlMgEzM0Zx7Hb396NRmaN1evXhW1Wi1hYWGSk5MjR44cEScnJ/n888/NdQpkYobmTEREhKjVatm1a5fk5+fLsWPHpG3btuLv72+uUyAzuH//vmRkZEhGRoYAkOjoaMnIyJArV66IiMjcuXNl/Pjxuv6VXyk7a9Ysyc7OlnXr1vErZUVE1q5dKy1atBClUim9evWS3377TbdvwIABEhQUpNd/z5494ubmJkqlUjp16iTx8fEmjpgsgSF507JlSwFQ5REREWH6wMlsDH2t+S8WFa8uQ/Pml19+kd69e4utra20adNGoqKipLy83MRRkzkZkjNlZWWyaNEiadu2rahUKnF1dZWQkBD566+/TB84mc2PP/5Y7fuUylwJCgqSAQMGVBnTrVs3USqV0qZNG9m+fbtBx7QS4VoYERERERHVXp26p4KIiIiIiEyPRQURERERERmFRQURERERERmFRQURERERERmFRQURERERERmFRQURERERERmFRQURERERERmFRQURERERERmFRQUR0UsoJiYGDRs2NHcYtWZlZYWDBw8+sc+ECRPw7rvvmiQeIiIyDosKIiIzmTBhAqysrKo88vLyzB0aYmJidPEoFAo0b94cH374If7888/nMn9RUREGDx4MACgsLISVlRUyMzP1+qxevRoxMTHP5Xg1WbRoke48ra2t4erqiilTpuDOnTsGzcMCiIhedTbmDoCI6FXm6+uL7du367U1adLETNHoc3BwQE5ODrRaLc6ePYsPP/wQf/zxB5KSkoye29nZ+al9GjRoYPRxnkWnTp2QnJyMiooKZGdnY+LEibh79y52795tkuMTEdUFXKkgIjIjW1tbODs76z2sra0RHR2NLl26wN7eHq6urggJCcGDBw9qnOfs2bMYOHAg1Go1HBwc0KNHD5w6dUq3Py0tDf3794ednR1cXV0RHh6Ohw8fPjE2KysrODs7Q6PRYPDgwQgPD0dycjKKi4uh1WqxePFiNG/eHLa2tujWrRsSExN1Y0tLSxEWFgYXFxeoVCq0bNkSy5Yt05u78vKn1q1bAwC6d+8OKysr/O9//wOg/+n/5s2bodFooNVq9WL08/PDxIkTdduHDh2Ch4cHVCoV2rRpg8jISJSXlz/xPG1sbODs7IxmzZrB29sbY8eOxfHjx3X7KyoqEBwcjNatW8POzg7u7u5YvXq1bv+iRYuwY8cOHDp0SLfqkZKSAgC4du0a/P390bBhQzg6OsLPzw+FhYVPjIeI6GXEooKIyAIpFAqsWbMGFy5cwI4dO/DDDz9g9uzZNfYPDAxE8+bNcfLkSZw+fRpz585FvXr1AACXL1+Gr68vRo8ejXPnzmH37t1IS0tDWFiYQTHZ2dlBq9WivLwcq1evxqpVq7By5UqcO3cOPj4+GDFiBC5dugQAWLNmDQ4fPow9e/YgJycHsbGxaNWqVbXznjhxAgCQnJyMoqIi7N+/v0qfsWPH4vbt2/jxxx91bXfu3EFiYiICAwMBAKmpqfjggw/w8ccfIysrC5s2bUJMTAyioqKe+RwLCwuRlJQEpVKpa9NqtWjevDn27t2LrKwsLFy4EPPmzcOePXsAAJ9++in8/f3h6+uLoqIiFBUVoU+fPigrK4OPjw/UajVSU1ORnp6O1157Db6+vigtLX3mmIiIXgpCRERmERQUJNbW1mJvb697jBkzptq+e/fulddff123vX37dmnQoIFuW61WS0xMTLVjg4ODZcqUKXptqampolAopLi4uNoxj8+fm5srbm5u4unpKSIiGo1GoqKi9Mb07NlTQkJCRERk+vTpMmjQINFqtdXOD0AOHDggIiIFBQUCQDIyMvT6BAUFiZ+fn27bz89PJk6cqNvetGmTaDQaqaioEBGRt956S5YuXao3x86dO8XFxaXaGEREIiIiRKFQiL29vahUKgEgACQ6OrrGMSIioaGhMnr06BpjrTy2u7u73nPwzz//iJ2dnSQlJT1xfiKilw3vqSAiMqOBAwdiw4YNum17e3sA/35qv2zZMly8eBH37t1DeXk5SkpK8OjRI9SvX7/KPDNnzsSkSZOwc+dO3SU8bdu2BfDvpVHnzp1DbGysrr+IQKvVoqCgAB07dqw2trt37+K1116DVqtFSUkJ+vXrh61bt+LevXv4448/0LdvX73+ffv2xdmzZwH8e+nS22+/DXd3d/j6+mLYsGF45513jHquAgMDMXnyZKxfvx62traIjY3Fe++9B4VCoTvP9PR0vZWJioqKJz5vAODu7o7Dhw+jpKQE3333HTIzMzF9+nS9PuvWrcO2bdtw9epVFBcXo7S0FN26dXtivGfPnkVeXh7UarVee0lJCS5fvlyLZ4CIyHKxqCAiMiN7e3u0a9dOr62wsBDDhg3DtGnTEBUVBUdHR6SlpSE4OBilpaXVvjletGgRxo0bh/j4eBw9ehQRERGIi4vDyJEj8eDBA0ydOhXh4eFVxrVo0aLG2NRqNc6cOQOFQgEXFxfY2dkBAO7du/fU8/Lw8EBBQQGOHj2K5ORk+Pv7w9vbG/v27Xvq2JoMHz4cIoL4+Hj07NkTqamp+Oqrr3T7Hzx4gMjISIwaNarKWJVKVeO8SqVS92+wfPlyDB06FJGRkViyZAkAIC4uDp9++ilWrVoFLy8vqNVqfPnll/j999+fGO+DBw/Qo0cPvWKukqXcjE9E9LywqCAisjCnT5+GVqvFqlWrdJ/CV16//yRubm5wc3PDjBkz8P7772P79u0YOXIkPDw8kJWVVaV4eRqFQlHtGAcHB2g0GqSnp2PAgAG69vT0dPTq1UuvX0BAAAICAjBmzBj4+vrizp07cHR01Juv8v6FioqKJ8ajUqkwatQoxMbGIi8vD+7u7vDw8NDt9/DwQE5OjsHn+bgFCxZg0KBBmDZtmu48+/Tpg5CQEF2fx1calEpllfg9PDywe/duODk5wcHBwaiYiIgsHW/UJiKyMO3atUNZWRnWrl2L/Px87Ny5Exs3bqyxf3FxMcLCwpCSkoIrV64gPT0dJ0+e1F3WNGfOHPzyyy8ICwtDZmYmLl26hEOHDhl8o/Z/zZo1C1988QV2796NnJwczJ07F5mZmfj4448BANHR0di1axcuXryI3Nxc7N27F87OztX+YJ+TkxPs7OyQmJiImzdv4u7duzUeNzAwEPHx8di2bZvuBu1KCxcuxLfffovIyEhcuHAB2dnZiIuLw4IFCww6Ny8vL3Tt2hVLly4FALRv3x6nTp1CUlIScnNz8dlnn+HkyZN6Y1q1aoVz584hJycHt27dQllZGQIDA9G4cWP4+fkhNTUVBQUFSElJQXh4OK5fv25QTERElo5FBRGRhXnjjTcQHR2NL774Ap07d0ZsbKze17E+ztraGrdv38YHH3wANzc3+Pv7Y/DgwYiMjAQAdO3aFT/99BNyc3PRv39/dO/eHQsXLoRGo6l1jOHh4Zg5cyY++eQTdOnSBYmJiTh8+DDat28P4N9Lp1asWAFPT0/07NkThYWFSEhI0K28/JeNjQ3WrFmDTZs2QaPRwM/Pr8bjDho0CI6OjsjJycG4ceP09vn4+ODIkSM4duwYevbsiTfffBNfffUVWrZsafD5zZgxA1u3bsW1a9cwdepUjBo1CgEBAejduzdu376tt2oBAJMnT4a7uzs8PT3RpEkTpKeno379+vj555/RokULjBo1Ch07dkRwcDBKSkq4ckFEdY6ViIi5gyAiIiIiopcXVyqIiIiIiMgoLCqIiIiIiMgoLCqIiIiIiMgoLCqIiIiIiMgoLCqIiIiIiMgoLCqIiIiIiMgoLCqIiIiIiMgoLCqIiIiIiMgoLCqIiIiIiMgoLCqIiIiIiMgoLCqIiIiIiMgoLCqIiIiIiMgo/wc0jTgEu3X2+wAAAABJRU5ErkJggg==",
            "text/plain": [
              "<Figure size 800x600 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "plot_roc_curve(dt, X_test, y_test, \"Decision Tree\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "tFZbA0VZSAP6"
      },
      "source": [
        "# RANDOM FOREST"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 100,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 472
        },
        "id": "z6v_vnqKSAP7",
        "outputId": "3ccfee36-0560-423d-ba01-ac85258daaf6"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 640x480 with 2 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "rf = RandomForestClassifier(random_state=42)\n",
        "\n",
        "start_time = time.time()\n",
        "train_metrics = compute_train_metrics(rf, X_train, y_train)\n",
        "TRAINING_TIME['Random Forest'] = time.time() - start_time\n",
        "\n",
        "rf.fit(X_train, y_train)\n",
        "test_metrics = compute_test_metrics_and_plot_cm(rf, X_test, y_test, \"RF\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 101,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 487
        },
        "id": "UJIsSCeGSAP7",
        "outputId": "fcf7dfd5-2abd-4145-e52b-1ab48dde9a9c"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "plot_metrics(train_metrics, test_metrics, \"Random Forest\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 102,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 607
        },
        "id": "2vzb5PsjWzpi",
        "outputId": "d875a5ea-7235-4e31-c907-e8614ef7d11f"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 800x600 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "plot_roc_curve(rf, X_test, y_test, \"Random Forest\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "fftNJiJ9SAP7"
      },
      "source": [
        "# GAUSSIAN NAIVE BAYES"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 103,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 472
        },
        "id": "UntzmDCvSAP7",
        "outputId": "754fbe68-516a-40ed-875f-e532becbb125"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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9GDAQERGRXgwYiIiISK+X+uCmwsJC3L59G9bW1kY9PpaIiMqHIAh48OABHBwcxLeXloXs7Gzk5uZKrsfMzAwWFhZGaNHL56UOGG7fvg1HR8eKbgYREUl08+bNEp0KWxrZ2dmwtK4K5D+UXJdGo0FSUpIsg4aXOmAoesWymZs/FCYlf70t0cvkWtSCim4CUZl58ECLBnVri3+fl4Xc3Fwg/yHM3fwBKb8VBblIvrARubm5DBheNkXTEAoTMwYM9MpSqVQV3QSiMlcu08qmFpJ+KwSFvJf9vdQBAxERUYkpAEgJTGS+VI4BAxERyYNC+fiScr+Mybv3REREVCIcYSAiInlQKCROSch7ToIBAxERyQOnJCSRd++JiIjKSHR0NHr27AkHBwcoFAqEh4cXK5OQkIBevXpBrVbDysoKrVq1wo0bN8T87OxsjB49GlWrVkWVKlXQv39/pKSk6NRx48YN+Pj4oHLlyqhRowYmT56M/Px8nTIHDhxA8+bNYW5ujnr16mHDhg0G94cBAxERyUPRlISUywBZWVlwd3fHqlWrnpp/9epVtGvXDg0bNsSBAwdw5swZzJgxQ+eMh4kTJ2Lnzp3Yvn07Dh48iNu3b6Nfv35ifkFBAXx8fJCbm4uYmBhs3LgRGzZsQFBQkFgmKSkJPj4+6Ny5M+Lj4zFhwgQMHz4ce/fuNezrEwRBMOiOF4hWq4VarYZ5kxE8h4FeWfeOrqjoJhCVGa1Wi5rVbZCRkVFmZ46IvxUtxkNhal7qeoT8HOTELStVWxUKBXbs2IE+ffqIab6+vqhUqRI2bdr01HsyMjJQvXp1bNmyBe+88w4A4OLFi3B1dUVsbCzefPNN/Pbbb+jRowdu374Ne3t7AEBYWBimTp2Ku3fvwszMDFOnTsWuXbtw7tw5nWenp6djz549Je4DRxiIiIjKWWFhIXbt2oUGDRrA29sbNWrUgIeHh860RVxcHPLy8uDl5SWmNWzYELVr10ZsbCwAIDY2Fk2aNBGDBQDw9vaGVqvF+fPnxTJP1lFUpqiOkmLAQERE8mCkKQmtVqtz5eTkGNyU1NRUZGZm4osvvkC3bt2wb98+9O3bF/369cPBgwcBAMnJyTAzM4ONjY3Ovfb29khOThbLPBksFOUX5T2vjFarxaNHj0rcZgYMREQkD0W7JKRcABwdHaFWq8UrJCTE4KYUFhYCAHr37o2JEyeiadOmmDZtGnr06IGwsDCjdttYuK2SiIjIADdv3tRZw2Bubvi6iGrVqsHU1BRubm466a6urvjzzz8BPH4zZm5uLtLT03VGGVJSUqDRaMQyx44d06mjaBfFk2X+vbMiJSUFKpUKlpaWJW4zRxiIiEgejDQloVKpdK7SBAxmZmZo1aoVEhMTddIvXboEJycnAECLFi1QqVIl7N+/X8xPTEzEjRs34OnpCQDw9PTE2bNnkZqaKpaJjIyESqUSgxFPT0+dOorKFNVRUhxhICIieSjng5syMzNx5coV8XNSUhLi4+NhZ2eH2rVrY/LkyRgwYAA6dOiAzp07Y8+ePdi5cycOHDgAAFCr1QgICEBgYCDs7OygUqkwduxYeHp64s033wQAdO3aFW5ubhg8eDBCQ0ORnJyM6dOnY/To0WIgM2rUKKxcuRJTpkzBsGHDEBUVhW3btmHXrl0G9YcBAxERyUM5Hw194sQJdO7cWfwcGBgIAPD398eGDRvQt29fhIWFISQkBOPGjYOLiwt++ukntGvXTrxnyZIlUCqV6N+/P3JycuDt7Y0vv/xSzDcxMUFERAQ++ugjeHp6wsrKCv7+/pg9e7ZYxtnZGbt27cLEiROxbNky1KpVC+vWrYO3t7dh3ec5DEQvNp7DQK+ycj2H4c0p0s9hOBJapm19kXGEgYiI5IHvkpCEAQMREcmDQiExYJD32yrlHS4RERFRiXCEgYiI5EGpeHxJuV/GGDAQEZE8cA2DJPLuPREREZUIRxiIiEgeyvkchlcNAwYiIpIHTklIIu/eExERUYlwhIGIiOSBUxKSMGAgIiJ54JSEJAwYiIhIHjjCIIm8wyUiIiIqEY4wEBGRPHBKQhIGDEREJA+ckpBE3uESERERlQhHGIiISCYkTknI/L+xGTAQEZE8cEpCEnmHS0RERFQiHGEgIiJ5UCgk7pKQ9wgDAwYiIpIHbquURN69JyIiohLhCAMREckDFz1KwoCBiIjkgVMSkjBgICIieeAIgyTyDpeIiIioRDjCQERE8sApCUkYMBARkTxwSkISeYdLREREVCIcYSAiIllQKBRQcISh1BgwEBGRLDBgkIZTEkRERKQXRxiIiEgeFP+9pNwvYwwYiIhIFjglIQ2nJIiIiEgvjjAQEZEscIRBGo4wEBGRLBQFDFIuQ0RHR6Nnz55wcHCAQqFAeHj4M8uOGjUKCoUCS5cu1UlPS0uDn58fVCoVbGxsEBAQgMzMTJ0yZ86cQfv27WFhYQFHR0eEhoYWq3/79u1o2LAhLCws0KRJE+zevdugvgAMGIiISCbKO2DIysqCu7s7Vq1a9dxyO3bswJEjR+Dg4FAsz8/PD+fPn0dkZCQiIiIQHR2NkSNHivlarRZdu3aFk5MT4uLisGDBAgQHB2Pt2rVimZiYGAwcOBABAQE4deoU+vTpgz59+uDcuXMG9YdTEkRERGXg7bffxttvv/3cMn///TfGjh2LvXv3wsfHRycvISEBe/bswfHjx9GyZUsAwIoVK9C9e3csXLgQDg4O2Lx5M3Jzc/HNN9/AzMwMjRo1Qnx8PBYvXiwGFsuWLUO3bt0wefJkAMCcOXMQGRmJlStXIiwsrMT94QgDERHJg8IIlxEVFhZi8ODBmDx5Mho1alQsPzY2FjY2NmKwAABeXl5QKpU4evSoWKZDhw4wMzMTy3h7eyMxMRH3798Xy3h5eenU7e3tjdjYWIPayxEGIiKSBWMtetRqtTrJ5ubmMDc3N7i6+fPnw9TUFOPGjXtqfnJyMmrUqKGTZmpqCjs7OyQnJ4tlnJ2ddcrY29uLeba2tkhOThbTnixTVEdJcYSBiIjIAI6OjlCr1eIVEhJicB1xcXFYtmwZNmzYIC2IKUccYSAiIll4/HZrKSMMj//PzZs3oVKpxOTSjC4cOnQIqampqF27tphWUFCASZMmYenSpbh27Ro0Gg1SU1N17svPz0daWho0Gg0AQKPRICUlRadM0Wd9ZYryS4ojDEREJAsKSNwl8d+IQaVS6VylCRgGDx6MM2fOID4+XrwcHBwwefJk7N27FwDg6emJ9PR0xMXFifdFRUWhsLAQHh4eYpno6Gjk5eWJZSIjI+Hi4gJbW1uxzP79+3WeHxkZCU9PT4PazBEGIiKiMpCZmYkrV66In5OSkhAfHw87OzvUrl0bVatW1SlfqVIlaDQauLi4AABcXV3RrVs3jBgxAmFhYcjLy8OYMWPg6+srbsEcNGgQZs2ahYCAAEydOhXnzp3DsmXLsGTJErHe8ePHo2PHjli0aBF8fHzwww8/4MSJEzpbL0uCIwxERCQL5X0Ow4kTJ9CsWTM0a9YMABAYGIhmzZohKCioxHVs3rwZDRs2RJcuXdC9e3e0a9dO54derVZj3759SEpKQosWLTBp0iQEBQXpnNXQpk0bbNmyBWvXroW7uzt+/PFHhIeHo3Hjxgb1RyEIgmDQHS8QrVYLtVoN8yYjoDAx038D0Uvo3tEVFd0EojKj1WpRs7oNMjIydNYFGPsZarUatr7roDCrXOp6hNyHuP/D8DJt64uMIwxERESkF9cwEBGRPEg8h0F4SbY/lhUGDEREJAtSD256Wc5LKCsMGIiISBYYMEjDNQxERESkF0cYiIhIHqS+QEreAwwMGIiISB44JSENpySIiIhIL44wEBGRLHCEQRoGDEREJAsMGKThlAQRERHpxREGIiKSBY4wSMOAgYiI5IHbKiXhlAQRERHpxREGIiKSBU5JSMOAgYiIZIEBgzQMGIiISBYYMEjDNQxERESkF0cYiIhIHrhLQhIGDEREJAuckpCGUxJERESkF0cYXnFtmr2OsYO94N6wNmpWV8Pvk7XYffCMTpkGdewRPLYP2javBxMTJRKTkuE/ZR1updwHAOwMG492Lerr3LP+pz8R+MUPAIDG9V/DBP+38GbT12GntsKNO2lY//OfWPPDgae2yeONuohYMx4Jf91BB78vjN9pkrWYU1ew8rv9iL94Ayn/aPFt6HD4dHQX8wVBwBdrd2PTLzHIyHyE1m84Y+GUAXi9dg2xzP2MLExb9CP2HDoHpVKBnp3dMS/wHVSpbC6WiTqSgC/W7sbFpDuwMKsEz6avY874vqjtULVc+0slxxEGaV6IEYZVq1ahTp06sLCwgIeHB44dO1bRTXplVLY0x7lLf2Ny6Nan5td5rRp++yoQl68lo8eHy9BuYAgWfr0H2bl5OuU27DgMl26fitfMFeFinntDR9y9/wAjgzbC0/dzLF6/F0Gje2HEux2KPU9VxRKrZw3GweOXjNpPoiIPH+WgUf3XEDr5vafmL9/0O9ZuO4iFUwdg39eTUNnCHO+O/xLZOf/7M//hzI24+Ncd/LRiNL5f9CFiT11FYMj3Yv712//g/clr0b5lfRzcNBXbl32MtIws+E9bV+b9o9JTQCEGDaW6ZL6IocJHGLZu3YrAwECEhYXBw8MDS5cuhbe3NxITE1GjRg39FdBz/R5zAb/HXHhm/oyPeyIy5jxmrvhFTLv29z/Fyj3KzkXqvQdPrWPzziM6n6//fQ+tmjijR2d3fLU9Widvyae++HHvCRQUCPDp9IYhXSEqEa82jeDVptFT8wRBwJofDmDSUG907/j4z9/q4MFo+PZ/sPvgGfTr2gKJScnYH5uA3zdMRjPX2gCALz55BwMmhmHWuL6oWV2N0wk3UVBQiM9G9YBS+fi/u0b7/R/en/wV8vILUMnUpHw6S1SOKnyEYfHixRgxYgSGDh0KNzc3hIWFoXLlyvjmm28qummvPIVCgbfaNsKVG6n4cfloXNobgsj1n4h/kT7p3W4tcSXyC8T88B8Eje4FS/NKz61bVcUC97UPddIG9XwTTq9VxfyvfjNqP4hK6vrte0i5p0XH1i5imqqKJVo0qoPjZ5MAACfOJkFtbSkGCwDQsZULlEoF4s5fAwC4uzpCqVRiS8RRFBQUQpv5CNt+O46OrVwYLLzAJI0uSJzOeBVUaMCQm5uLuLg4eHl5iWlKpRJeXl6IjY2twJbJQ3W7KrC2ssAE/7ewP/YC+o1diV0HTmNT6HC0aV5PLPfj3hP4MOhb9Bq1HEs27MN7b7fCmjn+z6y39RvO6PtWC2zccVhMq+tYHTNH98KHQd+ioKCwTPtF9Cyp97QAgOp21jrp1e2skZr2OC8lTYtqtrr5pqYmsFVVFu93cqiGH5d/jLlf7kTN9hPh3GUKbqem45t5Q8uhF1RqCiNcMlahUxL//PMPCgoKYG9vr5Nub2+PixcvFiufk5ODnJwc8bNWqy3zNr7KlIrH8eJvB89i9fd/AADOXfobrd+oi2H92iHm5BUA0Pnhv3D1NpL/0eLX1eNQ57VqxaYvXF+vic0LR2L+V7vxx9HH/xsqlQp8NXcIvli7G1dvpJZH14jKVMo9LSbO+x6+Pq3Rr2sLZD7MwRdrd2HIp1/j5xVjZP9fovRqqvA1DIYICQnBrFmzKroZr4x76ZnIyy/AxaQ7OumXkpLxZtO6z7wv7tw1AI9HDZ4MGFycNQhfNRYbd8Rg0Td7xfQqlS3Q3M0JbzSohdDJ7wJ4HEQolUrcjV2GfmNX4dAJLoKkslejqgoAcDftATTV1GL63bQHaFz/NQCAvZ0K/9zXXa+Tn1+A+9qH4v1fb4+GdRVLBI/tI5ZZHfwB3ugVhBPnrqFVE+cy7gmVBndJSFOhAUO1atVgYmKClJQUnfSUlBRoNJpi5T/99FMEBgaKn7VaLRwdHcu8na+qvPwCnLpwHfWddEd4Xq9dAzfv3H/mfU0a1AIApPyTIaY1rKvBL1+Oww+7jmLu6p065R9kZaON7+c6aQHvtEf7lg0wZNrXuP73PaldISoRJ4eqsK+qQvTxRPHPsTbzEeLOX8PQfu0AAC2bOCPjwSPEJ9xA0/+uYzh04hIKCwW0aFQHAPAoJxdKpe6Ph4nJ4xE7QRDKqTdkKAYM0lRowGBmZoYWLVpg//796NOnDwCgsLAQ+/fvx5gxY4qVNzc3h7m5ebF0ejYrSzM4O1YXPzs5VEXjBq8hPeMhbqXcx/JNv+ObecMQc+oKDp24BC9PN3Rr3xg9Ry0D8Hjb5TvdWiLy8HmkZWShcf3X8PnEfjh88jLOX7kN4PE0xC9fjkPUkQSs2hKFGlUfz/8WFAi4l54JQRCQcFV3FONuWiZycvOLpRNJlfkwB0m37oqfb9y+h7OXbsFWVRm1NHb40LcTFq3fi7qONeDkUBXz1kRAU00tLvZ1cdagi6crJoZ8j4VTByA/vxBTF25Hv7eao2b1x6MSb7VthNXfH8CCdb+JUxJzV++EY007MRChF49C8fiScr+cVfiURGBgIPz9/dGyZUu0bt0aS5cuRVZWFoYO5eIhY2jq6oSINePFz/MC+wMAtkQcwehZ32HXgTMIDPkBE4d0xReT3sGVG6n4YOo6HDn9FwAgLz8fnVq74CPfzqhsaYa/U+5jZ1Q8Fj4x5dDr/5qhup01BnRvjQHdW4vpN27fg3vvmeXUU6LH4hNuoPfHy8XP05fuAAD4+rTGqqDBGDfYCw8f5SIw5HtkZD6Ch3tdbFv2MSye2PmzZpY/pi7cjr5jVkKpUKBn56YImfSOmN+hpQvWzvbHiu9+x4rvfoelhRlaNnbGtqUfwdLCrPw6S1SOFMILMH62cuVKLFiwAMnJyWjatCmWL18ODw8PvfdptVqo1WqYNxkBhQn/n5ReTfeOrqjoJhCVGa1Wi5rVbZCRkQGVSlVmz1Cr1ag79kcoza1KXU9hThb+WvFOmbb1RVbhIwwAMGbMmKdOQRARERmNxCkJuW+rrPCDm4iIiOjF90KMMBAREZU17pKQhgEDERHJAndJSMMpCSIiItKLAQMREcnC4xNmpV2GiI6ORs+ePeHg4ACFQoHw8HAxLy8vD1OnTkWTJk1gZWUFBwcHfPDBB7h9+7ZOHWlpafDz84NKpYKNjQ0CAgKQmZmpU+bMmTNo3749LCws4OjoiNDQ0GJt2b59Oxo2bAgLCws0adIEu3fvNqgvAAMGIiKSiaIpCSmXIbKysuDu7o5Vq1YVy3v48CFOnjyJGTNm4OTJk/j555+RmJiIXr166ZTz8/PD+fPnERkZiYiICERHR2PkyJFivlarRdeuXeHk5IS4uDgsWLAAwcHBWLt2rVgmJiYGAwcOREBAAE6dOoU+ffqgT58+OHfunGHf34twDkNp8RwGkgOew0CvsvI8h8Fl0s8wkXAOQ0FOFhIX9StVWxUKBXbs2CGeavw0x48fR+vWrXH9+nXUrl0bCQkJcHNzw/Hjx9GyZUsAwJ49e9C9e3fcunULDg4OWL16NT777DMkJyfDzOzx7+C0adMQHh4uvsRxwIAByMrKQkREhPisN998E02bNkVYWFiJ+8ARBiIikoWiXRJSLuBxAPLk9eRblKXIyMiAQqGAjY0NACA2NhY2NjZisAAAXl5eUCqVOHr0qFimQ4cOYrAAAN7e3khMTMT9+/fFMl5eXjrP8vb2RmxsrEHtY8BARESyYKwpCUdHR6jVavEKCQmR3Lbs7GxMnToVAwcOFEcvkpOTUaNGDZ1ypqamsLOzQ3JysljG3l73BYJFn/WVKcovKW6rJCIiWTDWOQw3b97UmZKQ+lLEvLw8vPfeexAEAatXr5ZUV1liwEBERGQAlUpltPUWRcHC9evXERUVpVOvRqNBamqqTvn8/HykpaVBo9GIZVJSUnTKFH3WV6Yov6Q4JUFERLJgrDUMxlIULFy+fBm///47qlatqpPv6emJ9PR0xMXFiWlRUVEoLCwUX9Do6emJ6Oho5OXliWUiIyPh4uICW1tbscz+/ft16o6MjISnp6dB7WXAQEREslDe2yozMzMRHx+P+Ph4AEBSUhLi4+Nx48YN5OXl4Z133sGJEyewefNmFBQUIDk5GcnJycjNzQUAuLq6olu3bhgxYgSOHTuGw4cPY8yYMfD19YWDgwMAYNCgQTAzM0NAQADOnz+PrVu3YtmyZQgMDBTbMX78eOzZsweLFi3CxYsXERwcjBMnThj80kcGDERERGXgxIkTaNasGZo1awYACAwMRLNmzRAUFIS///4bv/76K27duoWmTZuiZs2a4hUTEyPWsXnzZjRs2BBdunRB9+7d0a5dO50zFtRqNfbt24ekpCS0aNECkyZNQlBQkM5ZDW3atMGWLVuwdu1auLu748cff0R4eDgaN25sUH94DgPRC47nMNCrrDzPYWgy7VeYWEg4hyE7C2e/6FWmbX2RcdEjERHJAl8+JQ2nJIiIiEgvjjAQEZEsGOscBrliwEBERLLAKQlpOCVBREREenGEgYiIZIFTEtIwYCAiIlnglIQ0DBiIiEgWOMIgDdcwEBERkV4cYSAiInmQOCUBeQ8wMGAgIiJ54JSENJySICIiIr04wkBERLLAXRLSMGAgIiJZ4JSENJySICIiIr04wkBERLLAKQlpGDAQEZEscEpCGk5JEBERkV4cYSAiIlngCIM0DBiIiEgWuIZBGgYMREQkCxxhkIZrGIiIiEgvjjAQEZEscEpCGgYMREQkC5ySkIZTEkRERKQXRxiIiEgWFJA4JWG0lrycGDAQEZEsKBUKKCVEDFLufRVwSoKIiIj04ggDERHJAndJSMOAgYiIZIG7JKRhwEBERLKgVDy+pNwvZ1zDQERERHpxhIGIiORBIXFaQeYjDAwYiIhIFrjoURpOSRAREZFeHGEgIiJZUPz3Hyn3yxlHGIiISBaKdklIuQwRHR2Nnj17wsHBAQqFAuHh4Tr5giAgKCgINWvWhKWlJby8vHD58mWdMmlpafDz84NKpYKNjQ0CAgKQmZmpU+bMmTNo3749LCws4OjoiNDQ0GJt2b59Oxo2bAgLCws0adIEu3fvNqwzYMBARERUJrKysuDu7o5Vq1Y9NT80NBTLly9HWFgYjh49CisrK3h7eyM7O1ss4+fnh/PnzyMyMhIRERGIjo7GyJEjxXytVouuXbvCyckJcXFxWLBgAYKDg7F27VqxTExMDAYOHIiAgACcOnUKffr0QZ8+fXDu3DmD+qMQBEEw8Dt4YWi1WqjVapg3GQGFiVlFN4eoTNw7uqKim0BUZrRaLWpWt0FGRgZUKlWZPUOtVuPtZX+gkmWVUteT9ygTv43vXKq2KhQK7NixA3369AHweHTBwcEBkyZNwieffAIAyMjIgL29PTZs2ABfX18kJCTAzc0Nx48fR8uWLQEAe/bsQffu3XHr1i04ODhg9erV+Oyzz5CcnAwzs8e/g9OmTUN4eDguXrwIABgwYACysrIQEREhtufNN99E06ZNERYWVuI+lGgNw6+//lriCnv16lXiskREROXFWLsktFqtTrq5uTnMzc0NqispKQnJycnw8vIS09RqNTw8PBAbGwtfX1/ExsbCxsZGDBYAwMvLC0qlEkePHkXfvn0RGxuLDh06iMECAHh7e2P+/Pm4f/8+bG1tERsbi8DAQJ3ne3t7F5si0adEAUNRRKSPQqFAQUGBQQ0gIiJ6mTg6Oup8njlzJoKDgw2qIzk5GQBgb2+vk25vby/mJScno0aNGjr5pqamsLOz0ynj7OxcrI6iPFtbWyQnJz/3OSVVooChsLDQoEqJiIheNMZ6vfXNmzd1piQMHV14WUla9PjkwgwiIqIXWdGUhJQLAFQqlc5VmoBBo9EAAFJSUnTSU1JSxDyNRoPU1FSd/Pz8fKSlpemUeVodTz7jWWWK8kvK4IChoKAAc+bMwWuvvYYqVargr7/+AgDMmDEDX3/9taHVERERlYuit1VKuYzF2dkZGo0G+/fvF9O0Wi2OHj0KT09PAICnpyfS09MRFxcnlomKikJhYSE8PDzEMtHR0cjLyxPLREZGwsXFBba2tmKZJ59TVKboOSVlcMDw+eefY8OGDQgNDdVZZNG4cWOsW7fO0OqIiIheSZmZmYiPj0d8fDyAxwsd4+PjcePGDSgUCkyYMAFz587Fr7/+irNnz+KDDz6Ag4ODuG7Q1dUV3bp1w4gRI3Ds2DEcPnwYY8aMga+vLxwcHAAAgwYNgpmZGQICAnD+/Hls3boVy5Yt01nkOH78eOzZsweLFi3CxYsXERwcjBMnTmDMmDEG9cfggOHbb7/F2rVr4efnBxMTEzHd3d1d3MJBRET0ojHWlERJnThxAs2aNUOzZs0AAIGBgWjWrBmCgoIAAFOmTMHYsWMxcuRItGrVCpmZmdizZw8sLCzEOjZv3oyGDRuiS5cu6N69O9q1a6dzxoJarca+ffuQlJSEFi1aYNKkSQgKCtI5q6FNmzbYsmUL1q5dC3d3d/z4448IDw9H48aNDfv+DD2HwdLSEhcvXoSTkxOsra1x+vRp1K1bFxcuXEDr1q2LnUBVlngOA8kBz2GgV1l5nsPQd3W05HMYdnzUoUzb+iIzeITBzc0Nhw4dKpb+448/ilEUERERvVoMfvlUUFAQ/P398ffff6OwsBA///wzEhMT8e233+qcIkVERPQiUfz3knK/nBk8wtC7d2/s3LkTv//+O6ysrBAUFISEhATs3LkTb731Vlm0kYiISLIXaZfEy6hUr7du3749IiMjjd0WIiIiekGVKmAAHq/+TEhIAPB4XUOLFi2M1igiIiJjK80rqv99v5wZHDDcunULAwcOxOHDh2FjYwMASE9PR5s2bfDDDz+gVq1axm4jERGRZFKnFeQ+JWHwGobhw4cjLy8PCQkJSEtLQ1paGhISElBYWIjhw4eXRRuJiIioghk8wnDw4EHExMTAxcVFTHNxccGKFSvQvn17ozaOiIjImGQ+SCCJwQGDo6OjzpnVRQoKCsSjKomIiF40nJKQxuApiQULFmDs2LE4ceKEmHbixAmMHz8eCxcuNGrjiIiIjKVo0aOUS85KNMJga2urE1llZWXBw8MDpqaPb8/Pz4epqSmGDRsmvjSDiIiIXh0lChiWLl1axs0gIiIqW5ySkKZEAYO/v39Zt4OIiKhM8WhoaUp9cBMAZGdnIzc3VydNjm/wIiIietUZHDBkZWVh6tSp2LZtG+7du1csv6CgwCgNIyIiMialQgGlhGkFKfe+CgzeJTFlyhRERUVh9erVMDc3x7p16zBr1iw4ODjg22+/LYs2EhERSaZQSL/kzOARhp07d+Lbb79Fp06dMHToULRv3x716tWDk5MTNm/eDD8/v7JoJxEREVUgg0cY0tLSULduXQCP1yukpaUBANq1a4fo6Gjjto6IiMhI+HpraQwOGOrWrYukpCQAQMOGDbFt2zYAj0ceil5GRURE9KLhlIQ0BgcMQ4cOxenTpwEA06ZNw6pVq2BhYYGJEydi8uTJRm8gERERVTyD1zBMnDhR/HcvLy9cvHgRcXFxqFevHt544w2jNo6IiMhYuEtCGknnMACAk5MTnJycjNEWIiKiMiN1WkHm8ULJAobly5eXuMJx48aVujFERERlhUdDS1OigGHJkiUlqkyhUDBgICIiegWVKGAo2hXxorpxYCGPpKZXlq3PoopuAlGZEfKzy+1ZSpRipf+/7pczyWsYiIiIXgackpBG7gETERERlQBHGIiISBYUCkDJXRKlxoCBiIhkQSkxYJBy76uAUxJERESkV6kChkOHDuH999+Hp6cn/v77bwDApk2b8Oeffxq1cURERMbCl09JY3DA8NNPP8Hb2xuWlpY4deoUcnJyAAAZGRmYN2+e0RtIRERkDEVTElIuOTM4YJg7dy7CwsLw1VdfoVKlSmJ627ZtcfLkSaM2joiIiF4MBi96TExMRIcOHYqlq9VqpKenG6NNRERERsd3SUhj8AiDRqPBlStXiqX/+eefqFu3rlEaRUREZGxFb6uUcsmZwQHDiBEjMH78eBw9ehQKhQK3b9/G5s2b8cknn+Cjjz4qizYSERFJpjTCJWcG93/atGkYNGgQunTpgszMTHTo0AHDhw/Hhx9+iLFjx5ZFG4mIiF46BQUFmDFjBpydnWFpaYnXX38dc+bMgSAIYhlBEBAUFISaNWvC0tISXl5euHz5sk49aWlp8PPzg0qlgo2NDQICApCZmalT5syZM2jfvj0sLCzg6OiI0NBQo/fH4IBBoVDgs88+Q1paGs6dO4cjR47g7t27mDNnjtEbR0REZCxFaxikXIaYP38+Vq9ejZUrVyIhIQHz589HaGgoVqxYIZYJDQ3F8uXLERYWhqNHj8LKygre3t7Izv7fS7n8/Pxw/vx5REZGIiIiAtHR0Rg5cqSYr9Vq0bVrVzg5OSEuLg4LFixAcHAw1q5dK/k7e1KpT3o0MzODm5ubMdtCRERUZpSQtg5BCcPujYmJQe/eveHj4wMAqFOnDr7//nscO3YMwOPRhaVLl2L69Ono3bs3AODbb7+Fvb09wsPD4evri4SEBOzZswfHjx9Hy5YtAQArVqxA9+7dsXDhQjg4OGDz5s3Izc3FN998AzMzMzRq1Ajx8fFYvHixTmAhlcEBQ+fOnZ97eEVUVJSkBhEREb0K2rRpg7Vr1+LSpUto0KABTp8+jT///BOLFy8GACQlJSE5ORleXl7iPWq1Gh4eHoiNjYWvry9iY2NhY2MjBgsA4OXlBaVSiaNHj6Jv376IjY1Fhw4dYGZmJpbx9vbG/Pnzcf/+fdja2hqlPwYHDE2bNtX5nJeXh/j4eJw7dw7+/v5GaRQREZGxGWtbpVar1Uk3NzeHubl5sfLTpk2DVqtFw4YNYWJigoKCAnz++efw8/MDACQnJwMA7O3tde6zt7cX85KTk1GjRg2dfFNTU9jZ2emUcXZ2LlZHUV6FBQxLlix5anpwcHCxRRhEREQvCmO9fMrR0VEnfebMmQgODi5Wftu2bdi8eTO2bNkiThNMmDABDg4OL+V/YBvtbZXvv/8+WrdujYULFxqrSiIiohfOzZs3oVKpxM9PG10AgMmTJ2PatGnw9fUFADRp0gTXr19HSEgI/P39odFoAAApKSmoWbOmeF9KSoo4mq/RaJCamqpTb35+PtLS0sT7NRoNUlJSdMoUfS4qYwxG21YaGxsLCwsLY1VHRERkVAqFtMObiqYkVCqVzvWsgOHhw4dQKnV/Zk1MTFBYWAgAcHZ2hkajwf79+8V8rVaLo0ePwtPTEwDg6emJ9PR0xMXFiWWioqJQWFgIDw8PsUx0dDTy8vLEMpGRkXBxcTHadARQihGGfv366XwWBAF37tzBiRMnMGPGDKM1jIiIyJjK+2jonj174vPPP0ft2rXRqFEjnDp1CosXL8awYcP+W58CEyZMwNy5c1G/fn04OztjxowZcHBwQJ8+fQAArq6u6NatG0aMGIGwsDDk5eVhzJgx8PX1hYODAwBg0KBBmDVrFgICAjB16lScO3cOy5Yte+YSgtIyOGBQq9U6n5VKJVxcXDB79mx07drVaA0jIiJ6ma1YsQIzZszAxx9/jNTUVDg4OODDDz9EUFCQWGbKlCnIysrCyJEjkZ6ejnbt2mHPnj06I/abN2/GmDFj0KVLFyiVSvTv3x/Lly8X89VqNfbt24fRo0ejRYsWqFatGoKCgoy6pRIAFMKTR07pUVBQgMOHD6NJkyZGHeYoLa1WC7VajZR7GTrzSUSvElufRRXdBKIyI+RnIydqOjIyyu7v8aLfium/nISFlXWp68nOeoC5vZuXaVtfZAatYTAxMUHXrl35VkoiInrpKIzwj5wZvOixcePG+Ouvv8qiLURERGWmaFullEvODA4Y5s6di08++QQRERG4c+cOtFqtzkVERESvnhIvepw9ezYmTZqE7t27AwB69eqlc0S0IAhQKBQoKCgwfiuJiIgkMtbBTXJV4oBh1qxZGDVqFP7444+ybA8REVGZUCgUz30XUknul7MSBwxFmyk6duxYZo0hIiKiF5NB5zDIPboiIqKXF6ckpDEoYGjQoIHeoCEtLU1Sg4iIiMpCeZ/0+KoxKGCYNWtWsZMeiYiI6NVnUMDg6+tb7L3cREREL4Oil0hJuV/OShwwcP0CERG9zLiGQZoSH9xkwCsniIiI6BVT4hGGovd3ExERvZQkLnqU+askDH+9NRER0ctICQWUEn71pdz7KmDAQEREssBtldIY/PIpIiIikh+OMBARkSxwl4Q0DBiIiEgWeA6DNJySICIiIr04wkBERLLARY/SMGAgIiJZUELilITMt1VySoKIiIj04ggDERHJAqckpGHAQEREsqCEtGF1uQ/Jy73/REREVAIcYSAiIllQKBRQSJhXkHLvq4ABAxERyYIC0l44Ke9wgQEDERHJBE96lIZrGIiIiEgvjjAQEZFsyHuMQBoGDEREJAs8h0EaTkkQERGRXhxhICIiWeC2SmkYMBARkSzwpEdp5N5/IiIiKgGOMBARkSxwSkIaBgxERCQLPOlRGk5JEBERlZG///4b77//PqpWrQpLS0s0adIEJ06cEPMFQUBQUBBq1qwJS0tLeHl54fLlyzp1pKWlwc/PDyqVCjY2NggICEBmZqZOmTNnzqB9+/awsLCAo6MjQkNDjd4XBgxERCQLRVMSUi5D3L9/H23btkWlSpXw22+/4cKFC1i0aBFsbW3FMqGhoVi+fDnCwsJw9OhRWFlZwdvbG9nZ2WIZPz8/nD9/HpGRkYiIiEB0dDRGjhwp5mu1WnTt2hVOTk6Ii4vDggULEBwcjLVr10r/0p7AKQkiIpKF8t4lMX/+fDg6OmL9+vVimrOzs/jvgiBg6dKlmD59Onr37g0A+Pbbb2Fvb4/w8HD4+voiISEBe/bswfHjx9GyZUsAwIoVK9C9e3csXLgQDg4O2Lx5M3Jzc/HNN9/AzMwMjRo1Qnx8PBYvXqwTWEjFEQYiIpIFY40waLVanSsnJ+epz/v111/RsmVLvPvuu6hRowaaNWuGr776SsxPSkpCcnIyvLy8xDS1Wg0PDw/ExsYCAGJjY2FjYyMGCwDg5eUFpVKJo0ePimU6dOgAMzMzsYy3tzcSExNx//59o31/DBiIiIgM4OjoCLVaLV4hISFPLffXX39h9erVqF+/Pvbu3YuPPvoI48aNw8aNGwEAycnJAAB7e3ud++zt7cW85ORk1KhRQyff1NQUdnZ2OmWeVseTzzAGTkkQEZEsGGuXxM2bN6FSqcR0c3Pzp5YvLCxEy5YtMW/ePABAs2bNcO7cOYSFhcHf319CSyoGRxiIiEgWil4+JeUCAJVKpXM9K2CoWbMm3NzcdNJcXV1x48YNAIBGowEApKSk6JRJSUkR8zQaDVJTU3Xy8/PzkZaWplPmaXU8+QxjYMBARERUBtq2bYvExESdtEuXLsHJyQnA4wWQGo0G+/fvF/O1Wi2OHj0KT09PAICnpyfS09MRFxcnlomKikJhYSE8PDzEMtHR0cjLyxPLREZGwsXFRWdHhlQMGIiISBaUUEi+DDFx4kQcOXIE8+bNw5UrV7BlyxasXbsWo0ePBvB4EeaECRMwd+5c/Prrrzh79iw++OADODg4oE+fPgAej0h069YNI0aMwLFjx3D48GGMGTMGvr6+cHBwAAAMGjQIZmZmCAgIwPnz57F161YsW7YMgYGBRv3+uIaBiIhk4clphdLeb4hWrVphx44d+PTTTzF79mw4Oztj6dKl8PPzE8tMmTIFWVlZGDlyJNLT09GuXTvs2bMHFhYWYpnNmzdjzJgx6NKlC5RKJfr374/ly5eL+Wq1Gvv27cPo0aPRokULVKtWDUFBQUbdUgkACkEQBKPWWI60Wi3UajVS7mXoLEAhepXY+iyq6CYQlRkhPxs5UdORkVF2f48X/VZsjb2MylWsS13Pw8wHGOBZv0zb+iLjCAMREcmC4r//SLlfzhgwEBGRLJT3lMSrhoseiYiISC+OMBARkSwoSrHT4d/3yxkDBiIikgVOSUjDgIGIiGSBAYM0XMNAREREenGEgYiIZIHbKqVhwEBERLKgVDy+pNwvZ5ySICIiIr04wkBERLLAKQlpGDAQEZEscJeENJySICIiIr04wkBERLKggLRpBZkPMDBgICIieeAuCWk4JUFERER6cYRB5goKCvHF2t3Ytuc4Uu9poammxqAeHvgkoBsU/13hk/kwB7NW/oLdB88gLSMLTg5VMXJARwzr375YfYIg4N3xq7E/9gK+WzACPp3cy7tLJDNtGr2Gsf1bwb2ePWpWrQK/Ob9g95ErYv6qid4Y5NVY557f45LwbtDP4udJAzzQtVVdNHaujrz8AtQZsOqZz7O1tsChlR/gtWrWcHpvJbRZOQAAe1srzB3eEU3r26NuTVus+fUk/vPVAeN2liThLglpKjRgiI6OxoIFCxAXF4c7d+5gx44d6NOnT0U2SXaWfhuJb346hC+DB8O1bk2cSriBMbO/g6qKJT707QQAmL7kJ0SfuIQ1sz9A7ZpVEXUkAZ+EboOmmhrdO76hU9/q7/+Q/UpiKl+VLSrhXNJdfBd5Dt9N7/3UMr+fSMLopXvEzzl5BTr5lUxNEP5nIo4l3Mbgro3/fbuOFeO9cSHpLl6rZq2TblbJBP9kPMLCH47i4z4tStkbKkvcJSFNhU5JZGVlwd3dHatWPTuap7J17Mxf6N7xDXi3a4zaDlXRu0szdPZoiLjz18UyR88kYaCPB9q1aIDaDlUxpF87NK7/Gk5euK5T19nEW1i1OQorZ7xf3t0gGfs97ho+33QYu2KvPLNMTl4BUu8/FK+MzByd/C82x2B1+ElcuP7Pc581rLs71FbmWPHziWJ5N1O1+HTtH9gadUEcdaAXi8IIl5xVaMDw9ttvY+7cuejbt29FNkPWWr9RFwePJ+LK9RQAwNlLt3Dk9F/wauMmlvF4wxm/RZ/F7dR0CIKAQycu4eqNVHT2cBXLPMzOxYgZG7Bgynuwr6Yq934QPU+7JrVwafNHOLZmKBZ93AW21hYG1+HiaIfJA9/ER4t/Q6EglEEriV5sL9UahpycHOTk/C9y12q1FdiaV8NE/7fwIDMbrd+dCxOlAgWFAqZ/1APvvd1KLDN/8ruYMO97NPKZDlMTJZRKJZZ9NhBtm9cTy/xn8U9o/YZzsSkKooq2P+4aImKu4HpyBurUtMEM/3bYPqsfun7yPQoLS/bDb2ZqgnVTfDDzm2jcuvsAThp1GbeayoISCiglzCsoZT7G8FIFDCEhIZg1a1ZFN+OVsuP3k9i+5zi+muuPhnVr4uylv/GfxT+iZnU1BvZ4EwCwdutBnDh7DVsWfQjHmnaIOXUFk/+7hqGTR0PsPngGh05cwsHvplVwb4iK+zk6Ufz3C9f/wflrdxH/9XC0a+KI6NM3SlRH0JB2uHQzDdv+SCirZlI5kDqtIO9w4SULGD799FMEBgaKn7VaLRwdHSuwRS+/oGXhmOD/Fvp3bQkAaFTvNdy6k4YlGyIxsMebeJSdizlf7sSmBSPg3e7xYrDG9V/DuUu3sPK7/ejk0RCHTlxC0q1/UOf/JuvU/cHUdfBs+joi1kwo724RPdP15Az8k/EQdWvalDhg6OBeG25O1dCrXQMA//vhuPr9x1i09Si+2BxTRq0lenG8VAGDubk5zM3NK7oZr5RHOblQKnWXsiiVChQKhQCAvPwC5OUXFBvGUyqV4jzuBP+uGNy7jU5+24HzMG9if3Rr//wV50TlzaFqFdhZWyLlflaJ7/ng819haf6/vy6b1ddg1cRu6D7lByTdSS+DVlKZ4BCDJC9VwEDG161dEyxevxe1NLZwrVsTZxJv4cstf8Cv1+PpCFUVS7RtXg9By8NhaVEJjho7HD55BVt3H8PcCf0AAPbVVE9d6FhLYwun16qVa39IfqwsKsHZwUb87KRRoXHd6kh/kI37D7IxdZAnfj18GSn3s+Bc0wazhnXAX3fuY3/cNfGeWtWtYWNtgVrVraFUKtG4bnUAQNLtdGRl5+FacobOM+1UlgCAxJtpOjsiiu6zsqyEaurKaFy3OvLyCpB4M62Mek+G4DkM0lRowJCZmYkrV/63FSopKQnx8fGws7ND7dq1K7Bl8jF/8ruYFxaBT+ZvxT/3M6GppsaQfm0xZfjbYpmvPx+G2at+wcgZG3Ff+xCOGjtM/6gHhvVvV4EtJ3qsaX17RHwxQPw8b0RnAMCW389h0qr9cKtTHb5dGkFtZY7ktExEnbqOeZsOIzf/f2cxfPp+G53DnQ6t+AAA0GPaVhw+e6vEbSm6D3g8CvFuZ1fcSMmA+7B1pe4f0YtCIQgVtz/owIED6Ny5c7F0f39/bNiwQe/9Wq0WarUaKfcyoFJxKx+9mmx9FlV0E4jKjJCfjZyo6cjIKLu/x4t+K/bH30AV69I/I/OBFl2a1i7Ttr7IKnSEoVOnTqjAeIWIiGSESxik4cuniIiISC8ueiQiInngEIMkDBiIiEgWuEtCGgYMREQkC3xbpTRcw0BERER6cYSBiIhkgUsYpGHAQERE8sCIQRJOSRAREZFeDBiIiEgWFEb4p7S++OILKBQKTJgwQUzLzs7G6NGjUbVqVVSpUgX9+/dHSkqKzn03btyAj48PKleujBo1amDy5MnIz8/XKXPgwAE0b94c5ubmqFevXolOSi4NBgxERCQLRbskpFylcfz4caxZswZvvPGGTvrEiROxc+dObN++HQcPHsTt27fRr18/Mb+goAA+Pj7Izc1FTEwMNm7ciA0bNiAoKEgsk5SUBB8fH3Tu3Bnx8fGYMGEChg8fjr1795ausc/BgIGIiKiMZGZmws/PD1999RVsbW3F9IyMDHz99ddYvHgx/u///g8tWrTA+vXrERMTgyNHjgAA9u3bhwsXLuC7775D06ZN8fbbb2POnDlYtWoVcnNzAQBhYWFwdnbGokWL4OrqijFjxuCdd97BkiVLjN4XBgxERCQLCiNcwOOXWT155eTk4FlGjx4NHx8feHl56aTHxcUhLy9PJ71hw4aoXbs2YmNjAQCxsbFo0qQJ7O3txTLe3t7QarU4f/68WObfdXt7e4t1GBMDBiIikgcjRQyOjo5Qq9XiFRIS8tTH/fDDDzh58uRT85OTk2FmZgYbGxuddHt7eyQnJ4tlngwWivKL8p5XRqvV4tGjR3q/EkNwWyUREZEBbt68qfN6a3Nz86eWGT9+PCIjI2FhYVGezSszHGEgIiJZMNYuCZVKpXM9LWCIi4tDamoqmjdvDlNTU5iamuLgwYNYvnw5TE1NYW9vj9zcXKSnp+vcl5KSAo1GAwDQaDTFdk0UfdZXRqVSwdLS0ijfWxEGDEREJAvluUuiS5cuOHv2LOLj48WrZcuW8PPzE/+9UqVK2L9/v3hPYmIibty4AU9PTwCAp6cnzp49i9TUVLFMZGQkVCoV3NzcxDJP1lFUpqgOY+KUBBERyUJ5HvRobW2Nxo0b66RZWVmhatWqYnpAQAACAwNhZ2cHlUqFsWPHwtPTE2+++SYAoGvXrnBzc8PgwYMRGhqK5ORkTJ8+HaNHjxZHNUaNGoWVK1diypQpGDZsGKKiorBt2zbs2rVLQk+fjgEDERFRBViyZAmUSiX69++PnJwceHt748svvxTzTUxMEBERgY8++gienp6wsrKCv78/Zs+eLZZxdnbGrl27MHHiRCxbtgy1atXCunXr4O3tbfT2KgRBEIxeaznRarVQq9VIuZehswCF6FVi67OooptAVGaE/GzkRE1HRkbZ/T1e9FsRm/A3qliX/hmZD7TwdH2tTNv6IuMIAxERyYLU452l3Psq4KJHIiIi0osjDEREJAtS3gdRdL+cMWAgIiJZKM9dEq8iTkkQERGRXhxhICIieeAQgyQMGIiISBa4S0IaTkkQERGRXhxhICIiWeAuCWkYMBARkSxwCYM0DBiIiEgeGDFIwjUMREREpBdHGIiISBa4S0IaBgxERCQPEhc9yjxe4JQEERER6ccRBiIikgWueZSGAQMREckDIwZJOCVBREREenGEgYiIZIG7JKRhwEBERLLAo6Gl4ZQEERER6cURBiIikgWueZSGAQMREckDIwZJGDAQEZEscNGjNFzDQERERHpxhIGIiGRBAYm7JIzWkpcTAwYiIpIFLmGQhlMSREREpBdHGIiISBZ4cJM0DBiIiEgmOCkhBackiIiISC+OMBARkSxwSkIaBgxERCQLnJCQhlMSREREpBdHGIiISBY4JSENAwYiIpIFvktCGk5JEBGRPCiMcBkgJCQErVq1grW1NWrUqIE+ffogMTFRp0x2djZGjx6NqlWrokqVKujfvz9SUlJ0yty4cQM+Pj6oXLkyatSogcmTJyM/P1+nzIEDB9C8eXOYm5ujXr162LBhg2GNLQEGDERERGXg4MGDGD16NI4cOYLIyEjk5eWha9euyMrKEstMnDgRO3fuxPbt23Hw4EHcvn0b/fr1E/MLCgrg4+OD3NxcxMTEYOPGjdiwYQOCgoLEMklJSfDx8UHnzp0RHx+PCRMmYPjw4di7d69R+6MQBEEwao3lSKvVQq1WI+VeBlQqVUU3h6hM2PosqugmEJUZIT8bOVHTkZFRdn+PF/1WXL75D6wlPOOBVov6jtVK3da7d++iRo0aOHjwIDp06ICMjAxUr14dW7ZswTvvvAMAuHjxIlxdXREbG4s333wTv/32G3r06IHbt2/D3t4eABAWFoapU6fi7t27MDMzw9SpU7Fr1y6cO3dOfJavry/S09OxZ8+eUvf33zjCQEREslC06FHKBTwOQJ68cnJySvT8jIwMAICdnR0AIC4uDnl5efDy8hLLNGzYELVr10ZsbCwAIDY2Fk2aNBGDBQDw9vaGVqvF+fPnxTJP1lFUpqgOY2HAQEREZABHR0eo1WrxCgkJ0XtPYWEhJkyYgLZt26Jx48YAgOTkZJiZmcHGxkanrL29PZKTk8UyTwYLRflFec8ro9Vq8ejRo1L18Wm4S4KIiGTBWLskbt68qTMlYW5urvfe0aNH49y5c/jzzz9L/fyKxhEGIiKSByPtklCpVDqXvoBhzJgxiIiIwB9//IFatWqJ6RqNBrm5uUhPT9cpn5KSAo1GI5b5966Jos/6yqhUKlhaWur9WkqKAQMREVEZEAQBY8aMwY4dOxAVFQVnZ2ed/BYtWqBSpUrYv3+/mJaYmIgbN27A09MTAODp6YmzZ88iNTVVLBMZGQmVSgU3NzexzJN1FJUpqsNYOCVBRESyUN7vkhg9ejS2bNmCX375BdbW1uKaA7VaDUtLS6jVagQEBCAwMBB2dnZQqVQYO3YsPD098eabbwIAunbtCjc3NwwePBihoaFITk7G9OnTMXr0aHFkY9SoUVi5ciWmTJmCYcOGISoqCtu2bcOuXbsk9LY4BgxERCQL5X009OrVqwEAnTp10klfv349hgwZAgBYsmQJlEol+vfvj5ycHHh7e+PLL78Uy5qYmCAiIgIfffQRPD09YWVlBX9/f8yePVss4+zsjF27dmHixIlYtmwZatWqhXXr1sHb27tU/XwWnsNA9ILjOQz0KivPcxiSbt+TfA6Ds0PVMm3ri4wjDEREJBPSdknI/QXXDBiIiEgW+LZKabhLgoiIiPRiwEBERER6cUqCiIhkgVMS0jBgICIiWTDW0dByxSkJIiIi0osjDEREJAuckpCGAQMREclCeR8N/arhlAQRERHpxREGIiKSBw4xSMKAgYiIZIG7JKThlAQRERHpxREGIiKSBe6SkIYBAxERyQKXMEjDgIGIiOSBEYMkXMNAREREenGEgYiIZIG7JKRhwEBERLLARY/SvNQBgyAIAIAHWm0Ft4So7Aj52RXdBKIyU/Tnu+jv87KklfhbIfX+l91LHTA8ePAAAFDP2bGCW0JERFI8ePAAarW6TOo2MzODRqNBfSP8Vmg0GpiZmRmhVS8fhVAeYV0ZKSwsxO3bt2FtbQ2F3MeKyolWq4WjoyNu3rwJlUpV0c0hMir++S5/giDgwYMHcHBwgFJZduvws7OzkZubK7keMzMzWFhYGKFFL5+XeoRBqVSiVq1aFd0MWVKpVPwLlV5Z/PNdvspqZOFJFhYWsv2hNxZuqyQiIiK9GDAQERGRXgwYyCDm5uaYOXMmzM3NK7opREbHP99Ez/ZSL3okIiKi8sERBiIiItKLAQMRERHpxYCBiIiI9GLAQERERHoxYKASW7VqFerUqQMLCwt4eHjg2LFjFd0kIqOIjo5Gz5494eDgAIVCgfDw8IpuEtELhwEDlcjWrVsRGBiImTNn4uTJk3B3d4e3tzdSU1MrumlEkmVlZcHd3R2rVq2q6KYQvbC4rZJKxMPDA61atcLKlSsBPH6Ph6OjI8aOHYtp06ZVcOuIjEehUGDHjh3o06dPRTeF6IXCEQbSKzc3F3FxcfDy8hLTlEolvLy8EBsbW4EtIyKi8sKAgfT6559/UFBQAHt7e510e3t7JCcnV1CriIioPDFgICIiIr0YMJBe1apVg4mJCVJSUnTSU1JSoNFoKqhVRERUnhgwkF5mZmZo0aIF9u/fL6YVFhZi//798PT0rMCWERFReTGt6AbQyyEwMBD+/v5o2bIlWrdujaVLlyIrKwtDhw6t6KYRSZaZmYkrV66In5OSkhAfHw87OzvUrl27AltG9OLgtkoqsZUrV2LBggVITk5G06ZNsXz5cnh4eFR0s4gkO3DgADp37lws3d/fHxs2bCj/BhG9gBgwEBERkV5cw0BERER6MWAgIiIivRgwEBERkV4MGIiIiEgvBgxERESkFwMGIiIi0osBAxEREenFgIFIoiFDhqBPnz7i506dOmHChAnl3o4DBw5AoVAgPT39mWUUCgXCw8NLXGdwcDCaNm0qqV3Xrl2DQqFAfHy8pHqIqGIxYKBX0pAhQ6BQKKBQKGBmZoZ69eph9uzZyM/PL/Nn//zzz5gzZ06JypbkR56I6EXAd0nQK6tbt25Yv349cnJysHv3bowePRqVKlXCp59+Wqxsbm4uzMzMjPJcOzs7o9RDRPQi4QgDvbLMzc2h0Wjg5OSEjz76CF5eXvj1118B/G8a4fPPP4eDgwNcXFwAADdv3sR7770HGxsb2NnZoXfv3rh27ZpYZ0FBAQIDA2FjY4OqVatiypQp+Pfp6v+eksjJycHUqVPh6OgIc3Nz1KtXD19//TWuXbsmvr/A1tYWCoUCQ4YMAfD4baAhISFwdnaGpaUl3N3d8eOPP+o8Z/fu3WjQoAEsLS3RuXNnnXaW1NSpU9GgQQNUrlwZdevWxYwZM5CXl1es3Jo1a+Do6IjKlSvjvffeQ0ZGhk7+unXr4OrqCgsLCzRs2BBffvmlwW0hohcbAwaSDUtLS+Tm5oqf9+/fj8TERERGRiIiIgJ5eXnw9vaGtbU1Dh06hMOHD6NKlSro1q2beN+iRYuwYcMGfPPNN/jzzz+RlpaGHTt2PPe5H3zwAb7//nssX74cCQkJWLNmDapUqQJHR0f89NNPAIDExETcuXMHy5YtAwCEhITg22+/RVhYGM6fP4+JEyfi/fffx8GDBwE8Dmz69euHnj17Ij4+HsOHD8e0adMM/k6sra2xYcMGXLhwAcuWLcNXX32FJUuW6JS5cuUKtm3bhp07d2LPnj04deoUPv74YzF/8+bNCAoKwueff46EhATMmzcPM2bMwMaNGw1uDxG9wASiV5C/v7/Qu3dvQRAEobCwUIiMjBTMzc2FTz75RMy3t7cXcnJyxHs2bdokuLi4CIWFhWJaTk6OYGlpKezdu1cQBEGoWbOmEBoaKubn5eUJtWrVEp8lCILQsWNHYfz48YIgCEJiYqIAQIiMjHxqO//44w8BgHD//n0xLTs7W6hcubIQExOjUzYgIEAYOHCgIAiC8Omnnwpubm46+VOnTi1W178BEHbs2PHM/AULFggtWrQQP8+cOVMwMTERbt26Jab99ttvglKpFO7cuSMIgiC8/vrrwpYtW3TqmTNnjuDp6SkIgiAkJSUJAIRTp04987lE9OLjGgZ6ZUVERKBKlSrIy8tDYWEhBg0ahODgYDG/SZMmOusWTp8+jStXrsDa2lqnnuzsbFy9ehUZGRm4c+eOziu9TU1N0bJly2LTEkXi4+NhYmKCjh07lrjdV65cwcOHD/HWW2/ppOfm5qJZs2YAgISEhGKvFvf09CzxM4ps3boVy5cvx9WrV5GZmYn8/HyoVCqdMrVr18Zrr72m85zCwkIkJibC2toaV69eRUBAAEaMGCGWyc/Ph1qtNrg9RPTiYsBAr6zOnTtj9erVMDMzg4ODA0xNdf+4W1lZ6XzOzMxEixYtsHnz5mJ1Va9evVRtsLS0NPiezMxMAMCuXbt0fqiBx+syjCU2NhZ+fn6YNWsWvL29oVar8cMPP2DRokUGt/Wrr74qFsCYmJgYra1EVPEYMNAry8rKCvXq1Stx+ebNm2Pr1q2oUaNGsf/KLlKzZk0cPXoUHTp0APD4v6Tj4uLQvHnzp5Zv0qQJCgsLcfDgQXh5eRXLLxrhKCgoENPc3Nxgbm6OGzduPHNkwtXVVVzAWeTIkSP6O/mEmJgYODk54bPPPhPTrl+/XqzcjRs3cPv2bTg4OIjPUSqVcHFxgb29PRwcHPDXX3/Bz8/PoOcT0cuFix6J/svPzw/VqlVD7969cejQISQlJeHAgQMYN24cbt26BQAYP348vvjiC4SHh+PixYv4+OOPn3uGQp06deDv749hw4YhPDxcrHPbtm0AACcnJygUCkRERODu3bvIzMyEtbU1PvnkE0ycOBEbN27E1atXcfLkSaxYsUJcSDhq1ChcvnwZkydPRmJiIrZs2YINGzYY1N/69evjxo0b+OGHH3D16lUsX778qQs4LSws4O/vj9OnT+PQoUMYN24c3nvvPWg0GgDArFmzEBISguXLl+PSpUs4e/Ys1q9fj8WLFxvUHiJ6sTFgIPqvypUrIzo6GrVr10a/fv3g6uqKgIAAZGdniyMOkyZNwuDBg+Hv7w9PT09YW1ujb9++z6139erVeOedd/Dxxx+jYcOGGDFiBLKysgAAr732GmbNmoVp06bB3t4eY8aMAQDMmTMHM2bMQEhICFxdXdGtWzfs2rULzs7OAB6vK/jpp58QHh4Od3d3hIWFYd68eQb1t1evXpg4cSLGjBmDpk2bIiYmBjNmzChWrl69eujXrx+6d++Orl274o033tDZNjl8+HCsW7cO69evR5MmTdCxY0ds2LBBbCsRvRoUwrNWaxERERH9F0cYiIiISC8GDERERKQXAwYiIiLSiwEDERER6cWAgYiIiPRiwEBERER6MWAgIiIivRgwEBERkV4MGIiIiEgvBgxERESkFwMGIiIi0osBAxEREen1/0s0A11t95kSAAAAAElFTkSuQmCC",
            "text/plain": [
              "<Figure size 640x480 with 2 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "gnb = GaussianNB()\n",
        "\n",
        "start_time = time.time()\n",
        "train_metrics = compute_train_metrics(gnb, X_train, y_train)\n",
        "TRAINING_TIME['Gaussian NB'] = time.time() - start_time\n",
        "\n",
        "gnb.fit(X_train, y_train)\n",
        "test_metrics = compute_test_metrics_and_plot_cm(gnb, X_test, y_test, \"GNB\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 104,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 487
        },
        "id": "zz1PnQpZSAP8",
        "outputId": "0f5c9dd1-1a81-4d55-bc15-ee56e41959df"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "plot_metrics(train_metrics, test_metrics, \"Gaussian Naive Bayes\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 105,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 607
        },
        "id": "dQQBAHvMW15z",
        "outputId": "5808f004-29b3-43e5-8c51-864abfedb5c2"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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aScuenp4oXbo0Bg4cqDPguEyZMti2bRuuXLmCBg0apHispHu5lC1bFgCkgdVXr15F/fr108wjNaVLl8alS5cQFxf3SVMK//f3Lcl/iycgcQB50riIpUuXIiQkBMePH8fs2bOlbZJ+nqNHj4anp2eKxy5evHiG8yWirMOigogyTZs2bbBq1SqcOXMGNWrU+Oj2b9++RUBAAKZPn44pU6ZI8aRvxj9kb2+f4oDZhw8fJosplUo0bdoUTZs2xfz58zF79mxMmjQJhw4dkj74WVlZwdvbG97e3oiLi8Nnn32GWbNmYcKECTA3N092zMOHD+P169fYunWrzofB+/fvf/R5fqpixYqhR48eWL58eYqD4Lds2QIfHx/MmzdPisXExKR7gPEXX3yBRYsWITw8HJs3b4a7u7vUBS3p/ADg5OSk88E5M8THxwN438K1c+dOxMbGYseOHShUqJC0XWpdrHr16oVRo0bh+fPn+O2339CmTRudgdHFihWDEAJFihSRvh1PS4UKFVChQgVMnjwZJ06cQN26deHr64uZM2fq9bxcXV0xcuRITJ8+HadOnZJez7Zt22LOnDlYv359ikVFQkICfvvtN9jb26Nu3boAgHbt2mHOnDn49ddfM1xUtGvXDidPnsRff/2Frl27fnT7lH7f4uLiUm0tS423tzf8/PwQEBCAmzdvQgihU7AWLVoUAGBqaprp1xYRZS12fyKiTDN27FhYWlqib9++CAkJSbb+v9/SJ31z/N/4woULk+1brFgxhIWF6dyR+/nz58lmh3nz5k2yfStVqgQAiI2NBYBk09Wq1WqULVsWQogUpyhNLde4uDgsXbo0xe0z2+TJk6HRaFKcllalUiV7DRcvXpzqt8r/5e3tjdjYWPj5+WHfvn063/QDid+629jYYPbs2Sm+Ph92XdLXrl27AAAeHh4AUn6dw8LCsHbt2hT379q1KxQKBYYPH46goCCdcSwA8Nlnn0GlUmH69OnJXiMhhHQthIeHSwVOkgoVKkCpVErXjb6GDh0KS0tLnfEwderUQbNmzbB27VrpuX9o0qRJuHPnDsaOHSt9+1+7dm20bNkSq1atwrZt25LtExcXh9GjR6eZy6BBg+Dq6opvvvkmxbtvv3jxQqdwKlasGI4ePaqzzYoVK9J9TSVp1qwZ8ubNi82bN2Pz5s2oUaOGTlcpJycnNGrUCMuXL0+xYPmUa4uIshZbKogo05QoUQK//fYbunbtilKlSkl31BZC4P79+/jtt9+gVCqlriQ2NjZo0KABfvzxR2g0GhQoUAAHDhxI8dv/Ll26YNy4cejYsSOGDRuGqKgoLFu2DCVLltQZjDxjxgwcPXoUbdq0QeHChfHixQssXboUBQsWlAYet2jRAi4uLqhbty6cnZ1x8+ZN/PLLL2jTpk2qg1nr1KkDe3t7+Pj4YNiwYVAoFNiwYUOGujNlRFJrhZ+fX7J1bdu2xYYNG2Bra4uyZcvi5MmT+Oeff5AvX750HbtKlSooXrw4Jk2ahNjYWJ1vkoHEn9OyZcvQs2dPVKlSBV26dIGjoyMePXqE3bt3o27duvjll18+ep5///0XMTExABKLvx07duDIkSPo0qWL1MWnRYsWUKvVaNeuHQYOHIiIiAisXLkSTk5OKX7odHR0RMuWLfHnn3/Czs4Obdq0Sfa6zZw5ExMmTMCDBw/g5eWFPHny4P79+/j7778xYMAAjB49GgcPHsSQIUPQuXNnlCxZEvHx8diwYQNUKlWK94ZIj3z58qFPnz5YunQpbt68iTJlygAA1q9fj6ZNm6JDhw7o1q0b6tevj9jYWGzduhWHDx+Gt7c3xowZo3Os9evXo0WLFvjss8/Qrl07NG3aFFZWVrh79y42bdqE58+fp3mvCnt7e/z9999o3bo1KlWqpHNH7QsXLuD3339H7dq1pe2//PJLDBo0CJ06dULz5s1x+fJl7N+/Hw4ODnq9Bqampvjss8+wadMmREZGppjjkiVLUK9ePVSoUAH9+/dH0aJFERISgpMnT+LJkye4fPmyXuckIpnIMOMUEeVygYGB4quvvhLFixcX5ubmwsLCQpQuXVoMGjRIXLp0SWfbJ0+eiI4dOwo7Oztha2srOnfuLJ49e5bilJYHDhwQ5cuXF2q1WpQqVUr8+uuvyaaUDQgIEB06dBD58+cXarVa5M+fX3Tt2lXcuXNH2mb58uWiQYMGIl++fMLMzEwUK1ZMjBkzRoSFhUnbpDSl7PHjx0WtWrWEhYWFyJ8/vxg7dqzYv3+/zjStQiROKZvSlLWpTYv7Xx9OKfuhu3fvCpVKlWzq07dv34o+ffoIBwcHYW1tLTw9PcWtW7eSTf/53yllPzRp0iQBQBQvXjzVvA4dOiQ8PT2Fra2tMDc3F8WKFRO9e/cW586dS/P5pDSlrFqtFqVLlxazZs0ScXFxOtvv2LFDVKxYUZibmwt3d3fxww8/iDVr1iT7eSRJmgJ3wIABqebw119/iXr16gkrKythZWUlSpcuLb7++mtx+/ZtIYQQQUFBom/fvqJYsWLC3Nxc5M2bVzRu3Fj8888/aT43IVK+o3aSe/fuCZVKpfNzECJxmt5p06aJcuXKCQsLC5EnTx5Rt25dsW7dOp0paD8UFRUlfvrpJ1G9enVhbW0t1Gq1KFGihBg6dKgIDAz8aJ5CCPHs2TMxcuRIUbJkSWFubi4sLS1F1apVxaxZs3Su/4SEBDFu3Djh4OAgLC0thaenpwgMDEx1StmzZ8+mek5/f38BQCgUCvH48eNUX6devXoJFxcXYWpqKgoUKCDatm2b4h3EiSh7UgiRRV+zERERGcD27dvh5eWFo0ePZnjMARERfRoWFURElKO1bdsWN2/eRGBgYKqzhBERkWFxTAUREeVImzZtwpUrV7B7924sWrSIBQURkYzYUkFERDmSQqGAtbU1vL294evr+0n3yyAiok/Dd2AiIsqR+J0YEVH2wftUEBERERHRJ2FRQUREREREn8Touj9ptVo8e/YMefLk4aA+IiIiIjI6Qgi8e/cO+fPnh1KZOW0MRldUPHv2DG5ubnKnQUREREQkq8ePH6NgwYKZciyjKyry5MkDALh//z7y5s0rczaUU2g0Ghw4cAAtWrSAqamp3OlQDsBrhjKC1w3pi9cMZcSbN29QpEgR6XNxZjC6oiKpy1OePHlgY2MjczaUU2g0GlhaWsLGxoZv2pQuvGYoI3jdkL54zVBGaDQaAMjUoQAcqE1ERERERJ+ERQUREREREX0SFhVERERERPRJWFQQEREREdEnYVFBRERERESfhEUFERERERF9EhYVRERERET0SVhUEBERERHRJ2FRQUREREREn4RFBRERERERfRIWFURERERE9ElYVBARERER0SdhUUFERERERJ+ERQUREREREX0SFhVERERERPRJWFQQEREREdEnYVFBRERERESfRNai4ujRo2jXrh3y588PhUKBbdu2fXSfw4cPo0qVKjAzM0Px4sWxbt06g+dJRERERESpk7WoiIyMhIeHB5YsWZKu7e/fv482bdqgcePGuHTpEkaMGIEvv/wS+/fvN3CmRERERESUGhM5T96qVSu0atUq3dv7+vqiSJEimDdvHgCgTJkyOHbsGBYsWABPT09DpUlERERE2Z0Q6dnoE4+RjnN86jGy4nnER6fjHPqRtajQ18mTJ9GsWTOdmKenJ0aMGJHqPrGxsYiNjZWWw8PDAQAajQYajcYgeVLuk3StZPo1E3Yfijc3ACggvUFIbwSpLCeLp7HtR/fVd78PzqfVQBHxDLB0/s9+aRwrzfOklUsaeaV2zPhoKEIDIeyK/We7tHJK7ZypPL8P9lX855gKrRaVQp5AceAviFeXIKzdALU1kknxjT+VPwap/pFIIa7Ptnqf05D5pSa75Pdpr58i7B6giYKwL5Hi5kqtFvXDQqHcPAdahSKd505+nnTvl8nHVL64AGFqBajtUtgujfeujMQz/XgpyQYf/j6yvwmAtgkJUP6iTGPLnPFBWZGePOiT/X21NILfmWb6cXNUUREcHAxnZ2edmLOzM8LDwxEdHQ0LC4tk+8yZMwfTp09PFj906BAsLS0NlivlTv7+/plynLzR11H/6aRMORZlT0oAhQHgVuKy4tVVGbOh7Ebx/FWq6/ICQEyWpZLpFJpIQBMpdxpGRQUAWrmzoJxi44WK2H2zEIDM/buUo4qKjJgwYQJGjRolLYeHh8PNzQ2NGzdGvnz5ZMyMchKNRgN/f380b94cpqafVt0rj42HKnB+JmVGRPRxAv9t9fhAshYRnZV676fQxiee07pg8mNI+6QU++/50rGNQo9t07VNCtJ8fdKxf6YcI/X1AgLh4e9gY2MDRUZ/lgDER3P8+DEy5bXKCT+PzHitsuIcqRxjydC3OPyNG2LepeMUeshRRYWLiwtCQkJ0YiEhIbCxsUmxlQIAzMzMYGZmlixuamr6yR8Oyfh88nXzz9fA5aW6MRt3IH8dIF8ZSG8Qyf7wphJP6Q9jqttk9NhpLMfHAAlxgKWT7vo0z5HW8dPIMa18Ulsn/v/Vnam17vH/u4++j1PN+f1jTXw8/j36L+o3aABTUzUAAZik0jqa4ht/an8sUonrc4xU/1hl9bGzeX6ZkkdK2ysAk+R/l4DELzD27NmL1q1bp/xek64PGh/PICvIcU5jFK/R4MiePalfM+nEn1fu9O5dLG7ffo1q1fJLMWcAATUeoFKleZl6rhxVVNSuXRt79uzRifn7+6N27doyZURGSQhAJADa+MT/42MATVRic//zk8D9PYCFIxDzFnh2AshXFgi7D7y9nfxYXxwC3Bpl+VOgLKDR4J3Zw8SfP7/AoPRSKBMLh6R/REQZdPjwA/Tpsx2RkXG4fn0wHB2tpHUFC+bJ9PPJWlREREQgMDBQWr5//z4uXbqEvHnzolChQpgwYQKePn2K9evXAwAGDRqEX375BWPHjkXfvn1x8OBB/PHHH9i9e7dcT4EMQRMFhD8CYl4nfmAXWkDEA9r/f5DXxgHvHgNmdv9fjk9cH/4Y0GqAyOeJ/5vZvt8nqQh4fCjxQ57SVDcecg5QqQHrgv+PJST+///HpjGv0QGAWKxKjOnj3aOU44NfARbsgkdERESZJypKg4kTA7Bo0WkpNnLkfvz662cGPa+sRcW5c+fQuHFjaTlp7IOPjw/WrVuH58+f49Gj9x/IihQpgt27d2PkyJFYtGgRChYsiFWrVnE62Zws4jmw3Qt4eyexG018lOHP+exEyvGEOCAsKM1dFfoWFClx9AA6/M2CgoiIiDLVqVNP4OOzDXfuvJZiDRoUxowZjdPYK3PIWlQ0atQIIo0pxlK6W3ajRo1w8eJFA2ZFWSYyGFie/+PbGZpCCShNgAQNAJE4RapSBSj+/0+pgoACkZFRsNY8A1xrJW6vUL3/P+QsUKQNYG4PuFQH8hQCzPMmtohY5Evs029ilnguIiIiokwUGxuP6dOP4IcfjkOrTfxsbW5ugjlzmmLYsJpQKg3fnTJHjamgXEII4PQs4Pi3ydc5V038IP7yMlC2FxDxFLAvCahtdD/IC23iGAbbIonLSeu0cYCVK6Ay//+HepP3BULSNiozwMT8/XI6+i3HazQIyISBcERERESZ6eLF5/Dx2YarV19IsRo1CsDPzwulSztkWR4sKsgwhADi3iUWBaH3gJeXgKA9iR/6Q84n377eHKDm+CxPk4iIiCinio7WoGXLjXjxIvHeMKamSkyb1ghjx9aFiUnW9o5gUUGfJuYtcPO3xGlSTSwTBzzrq84MFhREREREerKwMMX8+S3Qo8ff8PBwxvr1HVGxovPHdzQAFhXGShuf2JLw7nHiDEuRwYnxhFgg/GHijEVKk8QWh/AHwJOjgIUDYGKR2DXJyhWIjwZiQzN2/rylE4/dekPiGAQiIiIiSlNCghYxMfGwslJLsW7dKkChUODzz8tCrVbJlhuLitwsQQMcGpE4vWp8FPDk39SnN02PmDfvH0c+//j2LtUTZ3eyckmc8ahAXcChPOBUJXGcAxERERGlS2DgG/TuvQ1Fi9pj/fqOUlyhUKBbtwoyZpaIRUVutlD98W0yQp0nsZXDxOL/sxzZA0VaAYVbAM5VEu/3QERERESfTKsV8PU9hzFj/BEVpcHx44/RsWNpdOxYRu7UdLCoyK0Chnx8m8LNATN7wNIJMLUEwh4ALtUSZ07SxiVOrWpbNHGmJJUZYJ0/sYAgIiIiIoN79CgMfftuR0DAfSlWtKg9nJys0thLHiwqchNNNHDqO+DMnOTr+t5NLA4sHBPvl0BERERE2ZIQAuvWXcKIEfsRHh4rxb/6qhp+/LE5rK2zX68QFhU52YtLQPBZ4N0T4NSM1Lfr/wCwKZxVWRERERFRBj1//g4DBuzCrl13pFjBgjZYs6Y9mjcvJmNmaWNRkRNFBgO+runbdkgYYGZj2HyIiIiI6JMFBb1FtWor8PZtjBTr3bsSFizwhJ2duYyZfVzW3hWDMseOz9NeX3sqMOg58I1gQUFERESUQxQpYoeaNQsCAJydrbB9exesXdsh2xcUAFsqcpY3d4BNdYHoV7rxxosSp2y1LQLYFJInNyIiIiL6JAqFAqtWtcO33x7Cjz82h4ODpdwppRuLipzi3HzgyDe6sSKtgc92y5MPEREREWVYaGgMhg/fh27dysPTs7gUL1DABmvWdJAxs4xh96ec4PSc5AWFygxoukSefIiIiIgow/bvD0T58kuxfv1l9Ou3A6GhMR/fKZtjUZHdnZ4NHJuoG/tsLzAiBrB1lyUlIiIiItLfu3exGDRoF1q23IinT9/9PxaHK1dCZM7s07H7U3YWMAS49J/WiAGPgTwF5cmHiIiIiDLkyJEH6NNnO+7fD5VizZoVxZo17eHmZitfYpmERUV2dXFJ8oKi3Z8sKIiIiIhykOhoDSZODMCiRachRGLM0tIUP/3UHIMGVYNCoZA3wUzCoiI72twIeHJENzYiFlBlv7snEhEREVHKLl8Ohrf3Fty+/VqK1a9fCGvXdkCxYnllzCzzsajIbrQJyQuKQc9ZUBARERHlMHnymOHJk3AAgJmZCrNnN8Xw4TWhUuW+Yc0sKrKbdeV0lwe/AizyyZMLEREREWVY0aL2mD/fE6tWXYCfnxfKlHGUOyWDyX1lUk4WHwO8vf1+uc4MFhREREREOUB8vBaLFp1CREScTrx//yo4caJfri4oALZUZC+LLHSXa38rTx5ERERElG43b76Ej882nD37DLdvv8bSpW2kdQqFAiYmuWMwdlrYUpFdPDulu1xrijx5EBEREVG6JCRoMX/+SVSuvBxnzz4DAKxYcR5BQW9lzizrsaUiu/i9tu5y3eny5EFEREREH3Xv3hv07r0dx449kmKlSuWDn58Xiha1lzEzebCoyI46H5Q7AyIiIiJKgRACvr7nMHq0P6KiNAAAhQIYObIWZs5sAgsLU5kzlAeLiuzg5Azd5UKN5cmDiIiIiFL1+HEY+vXbAX//IClWtKg91q3rgPr1C8uYmfxYVMjt/l7gxNT3yzbusqVCRERERKnbuvWmTkHx1VfV8OOPzWFtzfuJsaiQ29bW7x9bOAD97sqXCxERERGlasiQGvjrr5u4fz8Uq1e3R4sWxeROKdtgUSGnd091l784BCj5IyEiIiLKDq5cCUHFis7SskqlxG+/dYK1tRp2duYyZpb9cEpZOf0z8P1jUyvAobx8uRARERERAODVqyh4e29BpUq+OH78kc66ggVtWFCkgEWFnIJ2v3/cYpV8eRARERERAGDHjtsoX34p/vjjOoQAfHy2ISYmXu60sj32tZHLwwDd5VLe8uRBRERERAgNjcGIEfvg53dZiuXNa4FZs5rA3JwfmT+Gr5Bc/vJ8/1idJ3GCYyIiIiLKcgcO3EO/fjvw5Em4FGvbtiRWrGgLV9c8MmaWc7CokIM2HhAJ75e9/5UvFyIiIiIjFRERhzFjDsDX97wUy5NHjUWLWqJ370pQ8EvfdGNRIYdH/+n65OQhTx5ERERERqxPn+3YsuWGtNy0aRGsWdMBhQrZyphVzsSB2nL4Z/D7x9XHyZcHERERkRGbPr0RzMxUsLQ0xZIlrXHgQE8WFBnElgo5mFi8f1ywvnx5EBERERmRuLgEqNUqablsWUesX98RVaq4onjxvDJmlvOxpUIOr6+/f1ygnnx5EBERERmBuLgETJ58ENWrr0w2PewXX5RjQZEJWFRktRu/6i6bsYmNiIiIyFAuXw5G9eorMWvWv7hyJQRTpx6SO6Vcid2fstKLy8Denu+X85aWLxciIiKiXCw+XosffjiG6dOPQKPRAgBMTJSwteXdsA2BRUVWOjJad7nWFHnyICIiIsrFbt16hV69/sbZs8+kWIUKTvDz80Llyq4yZpZ7sajISo/+ef+43mygTFf5ciEiIiLKZbRagUWLTmHixIPS2AmlUoHx4+tiypSGMDPjR19D4SubVSJDdJdrTpAnDyIiIqJcSKsVaNFiAwIC7kuxkiXzYf16L9SsWVDGzIwDB2pnlXvb5c6AiIiIKNdSKhVo0KAwAEChAEaMqImLFweyoMgibKnIKo8Pv3/c4Ee5siAiIiLKtSZMqIerV19gyJDqaNjQXe50jAqLiqwSeu/9Y8dKsqVBRERElNMJIbBhwxW8eBGJ0aPrSHFTUxX+/LOzjJkZLxYVWSX4zPvH9sXly4OIiIgoBwsJicDAgbuwffttmJgo0bixO6pWzS93WkaPYyqywsurust53OTJg4iIiCgH+/PP6yhXbim2b78NIPFeFDt33pE5KwLYUpE1Qs69f2zhACj5shMRERGl1+vXURgyZC82bbomxZycrLB8eVt4efFmwtkBP91mhTM/vH9cb5Z8eRARERHlMLt23UH//jsRHBwhxTp1KoNly9rA0dFKxszoQywqssLb2+8f25eSLw8iIiKiHCIiIg7Dh+/FmjWXpJi9vTmWLGmNLl3KQ6FQyJccJcOiwtAig3WXCzaQJw8iIiKiHMTERInTp59Ky23alMCKFe2QP38eGbOi1HCgtiEJLeDrqhtjVU1ERET0UebmJvDz80LevBZYvbo9du7syoIiG2NLhaFoooGfLXVj9WbLkwsRERFRNnfs2CPky2eBMmUcpVjVqvnx6NEIWFmpZcyM0oMtFZkt5i0wT5G8oACAKsOyPh8iIiKibCwmJh6jRx9AgwZr0avXNmg0CTrrWVDkDCwqMpM2AViSN3m8cAtglBYw5QwFREREREnOnn2KKlWWY968kxACOHfuGdatuyR3WpQB7P70qaJfJ04Ze25uyuu7HAcK1El5HREREZERiotLwMyZRzF79r9ISBAAALVahZkzG6Nv38oyZ0cZwaIio7QJwIqCyWd3SuJYEeh1OWtzIiIiIsrmrlwJgY/PNly69P4zVNWqrvDz80K5ck4yZkafgt2fMmpt6dQLisrDWFAQERERfSA+Xos5c/5FtWorpILCxESJ6dMb4eTJfiwocji2VGTEg/1AaKBurPZUoEJ/IE8BeXIiIiIiysYuXw7GpEkHIRJ7O6FcOUesX98RVaq4pr0j5QhsqdCXEMBfLd8vm1oB3wigzjQWFERERESpqFo1P0aPrgOlUoHx4+vi/PkBLChyEbZU6CP4HLCxum6s50V5ciEiIiLKxh4/DkP+/HmgUr3/DnvGjMbo3LksqlfnF7G5DVsq0iP4HLCpQfKCosGPgH0JeXIiIiIiyoaEEFix4jzKlFmChQtP6awzNzdhQZFLsaj4GKFNLCae/pt8XbXRWZ8PERERUTb15Ek4WrXaiIEDdyEyUoNJkw7i5s2XcqdFWYDdnz7mw/ETSVr/BpTpmvW5EBEREWVDQgj8+usVDB26F2FhsVK8Vy8PFCxoI2NmlFVYVHzM89PvH9cYD9SfI18uRERERNlMSEgEBg3ajW3bbkmx/PnzYNWqdmjVit3EjQWLirSEPwbiwt8v15stXy5ERERE2cyWLTfw1Ve78epVlBTr0aMifv65JeztLWTMjLIai4q0PNj3/nH+uoBCIV8uRERERNnI2rUX0bfvDmnZ0dESy5e3RceOZWTMiuTCgdppeX3j/WPXmvLlQURERJTNdO5cDsWK2QMAPvusDK5fH8yCwoixpSIt6g8GFjlVli8PIiIiIplptQJK5fteG9bWavj5eeHhwzB07VoeCvboMGpsqUiLVvP+sXV++fIgIiIiklFAQBAqVFiGe/fe6MTr1i2Ebt0qsKAgFhWpigkFrq97v6w0lSsTIiIiIllERsZh6NA9aNZsA27ceIk+fbZDqxVyp0XZELs//VdkCODrkjyuUmd9LkREREQyOX78EXr33o7AwPetEyYmSoSFxXBmJ0qGLRX/9ZdnynGHClmbBxEREZEMYmLiMXasP+rXXysVFBYWJli8uBX++acXCwpKEVsqPhT+EHh5WTfm3hKo+x1gailPTkRERERZ5Ny5Z/Dx2YYbN15Ksdq1C8LPzwslSuSTMTPK7lhUJIkMAVa6v182zwt8/Vq2dIiIiIiy0s8/n8aoUfuRkJA4ZkKtVuG77xrjm29qQ6Vi5xZKG4uKJP8dR1FxoDx5EBEREcmgTBkHqaCoUsUVfn5eKF/eSeasKKdgUQEA19frLlcbA9SfLU8uRERERDJo3rwYhg2rgbx5LTBxYn2YmqrkTolyEBYVkSHAPh/dWMMf5cmFiIiIKAvcufMaq1ZdwA8/NNO5x8TChS15zwnKEBYVgX/rLo+IkycPIiIiIgPTagUWLz6N8eMDEBMTj+LF82LAgKrSehYUlFEcdaOJev+45iRAxZvcERERUe5z//5bNGnihxEj9iMmJh4A4Ot7jjezo0zBokIkvH/sVFm+PIiIiIgMQAiBFSvOo2JFXxw58lCKDx1aA//+2wdKJVsn6NOx+5M2/v1jBQckERERUe7x9Gk4+vXbgf3770mxwoVtsWZNBzRpUkTGzCi3YVHxYUuFkkUFERER5Q6//noFQ4fuRWhojBTr378KfvqpBWxszGTMjHIjFhXaD4sKvhxERESUO/j7B0kFhaurNVavbo9WrUrInBXlVrKPqViyZAnc3d1hbm6OmjVr4syZM2luv3DhQpQqVQoWFhZwc3PDyJEjERMTk+Y+afqwpYLdn4iIiCiXWLSoJQoWtEH37hVw7dpgFhRkULJ+Nb9582aMGjUKvr6+qFmzJhYuXAhPT0/cvn0bTk7J7+D422+/Yfz48VizZg3q1KmDO3fuoHfv3lAoFJg/f37GkmBRQURERDncmzfRuHPnGerXLyzF7OzMcfHiQDg4WMqYGRkLWVsq5s+fj/79+6NPnz4oW7YsfH19YWlpiTVr1qS4/YkTJ1C3bl1069YN7u7uaNGiBbp27frR1o00aTmmgoiIiHKuc+fCUbnySrRr9zuePAnXWceCgrKKbC0VcXFxOH/+PCZMmCDFlEolmjVrhpMnT6a4T506dfDrr7/izJkzqFGjBoKCgrBnzx707Nkz1fPExsYiNjZWWg4PT/xl02g00Gg0UCZokFRKxCcICI3m058c5Tqa/18XGl4flE68ZigjeN2QPsLDYzF6tD/WrQuSYiNH7sNvv3WUMSvKCQzxHiNbUfHq1SskJCTA2dlZJ+7s7Ixbt26luE+3bt3w6tUr1KtXD0IIxMfHY9CgQZg4cWKq55kzZw6mT5+eLH7o0CFYWlqi3MtAFP9/7MSpM3hrEZ5sW6Ik/v7+cqdAOQyvGcoIXjf0MVeuvMPixY/w8uX7D4dVquRBq1YK7NmzR8bMKCeIior6+EZ6ylHTHR0+fBizZ8/G0qVLUbNmTQQGBmL48OH47rvv8O2336a4z4QJEzBq1ChpOTw8HG5ubmjcuDHy5csH5ZF/gMuJ6+rUrQfhUiMrngrlMBqNBv7+/mjevDlMTXnXdfo4XjOUEbxu6GOiojSYNOkQlix5f98Jc3Ml5s1rji+/rAKFgjeyo497/fp1ph9TtqLCwcEBKpUKISEhOvGQkBC4uLikuM+3336Lnj174ssvvwQAVKhQAZGRkRgwYAAmTZoEpTL5EBEzMzOYmSWfi9nU1DTxDVvx/tb0JqZmAN/EKQ3SdUOUTrxmKCN43VBKTpx4jN69t+Hu3TdSrGHDQujWzQp9+lTlNUPpZohrRbaB2mq1GlWrVkVAQIAU02q1CAgIQO3atVPcJyoqKlnhoFIljogQQqS0y8dx9iciIiLK5mJi4vH5539IBYWFhQkWLWqJ/fu7w9mZN7Ij+ck6+9OoUaOwcuVK+Pn54ebNm/jqq68QGRmJPn36AAB69eqlM5C7Xbt2WLZsGTZt2oT79+/D398f3377Ldq1aycVF3rj7E9ERESUzZmbm2Dp0jYAgFq1CuLSpUEYNqwmlEp2d6LsQdYxFd7e3nj58iWmTJmC4OBgVKpUCfv27ZMGbz969EinZWLy5MlQKBSYPHkynj59CkdHR7Rr1w6zZs3KeBJsqSAiIqJsRqNJQFSUBra25lLMy6s0duzogtatS0Clkv3+xUQ6ZB+oPWTIEAwZMiTFdYcPH9ZZNjExwdSpUzF16tTMS4BFBREREWUj1669gI/PNri722HLls46g6/btSslY2ZEqWOZy+5PRERElA0kJGjxww/HULXqCly48Bxbt97E779fkzstonSRvaVCdmypICIiIpndufMavXtvw8mTT6RY2bKOKFUqn4xZEaUfiwq2VBAREZFMtFqBX345g/Hj/0F0dDwAQKEARo+ugxkzGsPcnB/VKGfglcqWCiIiIpLBgweh6NNnOw4ffiDFihWzh5+fF+rWLSRfYkQZwKKCRQURERFlsaCgt/Dw8EVERJwUGzKkOr7/vhmsrNQyZkaUMRyoze5PRERElMWKFLFDixbFAACFCtnin396YvHi1iwoKMdiSwVbKoiIiCiLKRQKLFvWBgUL5sGMGY117kdBlBOxpYJFBRERERnQixeR6NTpD/z9902duJOTFRYtasWCgnIFtlSw+xMREREZyNatNzFo0C68fBmFY8ceoV69QnB0tJI7LaJMx5YKtlQQERFRJnv7Nho9emxFp05/4OXLKACJ08feufNa5syIDIMtFSwqiIiIKBPt3XsXX365E8+evZNiXl6l4evbBs7O1jJmRmQ4LCrY/YmIiIgywbt3sfjmmwNYufKCFLO1NcPixa3Qo0dFKBQKGbMjMiwWFSL+/WO2VBAREVEGnD//DJ9//icePAiVYp6exbBqVXsULGgjX2JEWYRFhdRSoQD4DQIRERFlgIuLNUJDYwAA1tZqzJ/fAl9+WYWtE2Q0WFQkjalQ8qUgIiKijClQwAaLF7fCqlUXsHZtBxQpYi93SkRZirM/SUUFuz4RERHRx8XGxmPmzKNSy0SS7t0r4OBBHxYUZJT49XxS9yeOpyAiIqKPuHDhOXx8tuHatRe4e/cN/Py8pHUKhYI9qclosaVCsKggIiKitGk0CZgx4whq1lyFa9deAAA2bbqGe/feyJwZUfbAlgp2fyIiIqI0XL/+Aj4+23D+/HMpVqmSC9av90KxYnllzIwo+2BRwe5PRERElIKEBC3mzz+JyZMPIS4u8fOCSqXApEn1MWlSA6jV/OxAlIRFBbs/ERER0X8EBr6Bj882nDjxWIqVKeOA9es7olq1/DJmRpQ9cUyFlt2fiIiISNfBg/elgkKhAEaPro0LFwayoCBKBVsq2FJBRERE/9G/fxX89ddN3Lv3BuvWeaFevUJyp0SUrbGoYFFBRERk1IQQOHnyCerUcZNiCoUCGzZ0hKWlKayt1TJmR5QzsPsTuz8REREZrWfP3qFt299Rt+4a+Pvf01nn5GTFgoIonVhUsKWCiIjI6Agh8NtvV1G+/FLs2XMXANCv3w5ER2tkzowoZ2L3JxYVRERERuXly0h89dVu/PXXTSnm4mKNpUvbwMLCVMbMiHIuFhXs/kRERGQ0tm27hQEDduLlyygp1qVLefzySyvky2cpY2ZEORuLCrZUEBER5Xpv30Zj2LB9+PXXK1IsXz4LLFvWBp07l5MxM6LcgUUFiwoiIqJcb9Cg3fjjj+vScvv2pbBiRVs4O1vLmBVR7sGB2uz+RERElOvNnt0ElpamsLU1g5+fF7Zt82ZBQZSJjLulQggAIvExWyqIiIhyjcjIOFhZvZ8OtlixvNi8+XN4eDjDzc1WxsyIcifjbqlI6voEsKggIiLKBaKiNBgxYh8qVVqOyMg4nXVt25ZkQUFkIMZdVGg/KCrY/YmIiChHO3XqCSpXXo5Fi04jMPANxo37R+6UiIyGkXd/YksFERFRThcbG4/p04/ghx+OQ6tN7NZsbm6C4sXzypwZkfFgUZGERQUREVGOc/Hic/j4bMPVqy+kWI0aBeDn54XSpR1kzIzIuBh3UcHuT0RERDmSRpOA778/hhkzjiI+XgsAMDVVYtq0Rhg7ti5MTIy7hzdRVjPuooItFURERDmOVivQpMl6HDv2SIp5eDjDz88LHh4uMmZGZLyMu4zXxr9/zKKCiIgoR1AqFfDyKgUAUKkUmDy5Ps6c6c+CgkhGbKlIwu5PREREOcaIEbVw/fpLfPVVNVSvXkDudIiMnnEXFTpjKoz7pSAiIsqOtFoBX99zePEiEtOmNZLiKpUSa9Z0kC8xItJh3J+kOaaCiIgo23r0KAx9+25HQMB9KBRAixbFUKeOm9xpEVEKjHtMBYsKIiKibEcIgbVrL6JChWUICLj//xhw6NB9mTMjotQYd0sFp5QlIiLKVp4/f4cBA3Zh1647UqxgQRusWdMezZsXkzEzIkqLcRcVbKkgIiLKNjZvvobBg/fgzZtoKda7dyUsWOAJOztzGTMjoo9hUZGERQUREZEswsNj8eWXO/DnnzekmLOzFVasaIf27UvJmBkRpZdxFxXs/kRERCQ7CwsTBAW9lZa/+KIclixpDQcHSxmzIiJ9cKB2ErZUEBERycLUVAU/Py/kz58HmzZ1wubNn7OgIMphjLulgkUFERFRljtw4B4cHS1RubKrFCtXzglBQcNgZmbcH02Icirjbqlg9yciIqIsExERh6++2gVPz1/Rs+ffiI2N11nPgoIo5zLuooItFURERFni6NGHqFhxGXx9zwMArl9/ifXrL8ucFRFlFhYVSVhUEBERZbroaA1GjdqPRo3W4f79UACAlZUpli1rgy+/rCJvckSUaYy7nZHdn4iIiAzm9Okn8PHZhtu3X0ux+vULYe3aDihWLK+MmRFRZjPuooItFURERJkuNjYeM2YcwfffH4dWKwAAZmYqzJ7dFMOH14RKZdwdJYhyIxYVSVhUEBERZYrbt1/jxx9PSAVF9er54efnhTJlHGXOjIgMxbi/KmD3JyIiokxXsaIzJk2qD1NTJWbObIwTJ/qxoCDK5dhSkYQtFURERBly9+5ruLvbwdT0/d/SSZPq4/PPy6J8eScZMyOirMKWiiQsKoiIiPSSkKDF/PknUaHCMsyZc0xnnampigUFkREx7qJCsPsTERFRRty79waNG/vhm28OIDY2Ad99dxSXLwfLnRYRyYTdn5KwpYKIiOijhBDw9T2HMWP8ERmpAQAoFMDQoTVQsmQ+mbMjIrkYd1HBgdpERETp9vhxGPr12wF//yApVqSIHdat80KDBoVlzIyI5GbcRQVbKoiIiD5KCAE/v8sYPnwfwsNjpfigQVUxd24LWFurZcyOiLIDFhVJWFQQERGlaN26S+jbd4e0XKBAHqxe3R6ensVlzIqIshPjHqjN7k9EREQf1bVrBZQtm3ifCR8fD1y7NpgFBRHp+KSWipiYGJibm2dWLllPxL9/zJYKIiIiAEB8vBYmJu+/dzQ3N8GGDR3x+HEYOnQoLWNmRJRd6d1SodVq8d1336FAgQKwtrZGUFDiYK1vv/0Wq1evzvQEDYr3qSAiItKxY8dtlCixGDdvvtSJV6niyoKCiFKld1Exc+ZMrFu3Dj/++CPU6vcDs8qXL49Vq1ZlanIGp3OfCuMeXkJERMYtLCwGffpsR4cOm/DgQSh8fLYhPl4rd1pElEPoXVSsX78eK1asQPfu3aFSvf9238PDA7du3crU5AyOA7WJiIhw4MA9lC+/DOvWXZJizs7WiIiIky8pIspR9P56/unTpyhePPngLK1WC41GkylJZRkO1CYiIiMWERGHMWMOwNf3vBSzsTHDokUt4ePjAYVCIWN2RJST6F1UlC1bFv/++y8KF9a9yc2WLVtQuXLlTEssS7ClgoiIjNTRow/Rp892BAW9lWJNmxbBmjUdUKiQrYyZEVFOpHdRMWXKFPj4+ODp06fQarXYunUrbt++jfXr12PXrl2GyNFwOFCbiIiM0E8/ncDYsf4QInHZ0tIUc+c2x6BB1aBUsnWCiPSn95iKDh06YOfOnfjnn39gZWWFKVOm4ObNm9i5cyeaN29uiBwNR7D7ExERGZ9atQpKj+vWdcPly4MweHB1FhRElGEZmvKofv368Pf3z+xcsh67PxERkRGqV68QJk6sDzs7c4wcWQsqlXHfC5eIPp3e7yJFixbF69evk8VDQ0NRtGjRTEkqy3CgNhER5XKXLwdj0KBd0GqFTnzmzCYYPboOCwoiyhR6t1Q8ePAACQkJyeKxsbF4+vRppiSVZdhSQUREuVR8vBY//HAM06cfgUajRalS+TByZG250yKiXCrdRcWOHTukx/v374et7fuZIRISEhAQEAB3d/dMTc7gWFQQEVEudOvWK/Tq9TfOnn0mxTZtuo5hw2qyZYKIDCLdRYWXlxcAQKFQwMfHR2edqakp3N3dMW/evExNzuDY/YmIiHIRrVZg0aJTmDjxIGJi4gEASqUC48bVxdSpDVlQEJHBpLuo0Gq1AIAiRYrg7NmzcHBwMFhSWYYtFURElEsEBb1Fnz7bcfToQylWsmQ+rF/vhZo1C6axJxHRp9N7TMX9+/cNkYc8WFQQEVEusHz5OXzzzQFERmqk2IgRNTFrVlNYWprKmBkRGYsMTSkbGRmJI0eO4NGjR4iLi9NZN2zYsExJLEuw+xMREeUCly+HSAVFkSJ2WLu2Axo2dJc3KSIyKnoXFRcvXkTr1q0RFRWFyMhI5M2bF69evYKlpSWcnJxyVlHBlgoiIsoFfvyxOQ4cuIdmzYpi7tzmyJPHTO6UiMjI6D1ia+TIkWjXrh3evn0LCwsLnDp1Cg8fPkTVqlXx008/GSJHw2FRQUREOUxwcAT27w/UiVlbq3HhwkD4+rZlQUFEstC7qLh06RK++eYbKJVKqFQqxMbGws3NDT/++CMmTpxoiBwNh92fiIgoB/nzz+soX34pOnX6A0FBb3XW2diwmCAi+ehdVJiamkKpTNzNyckJjx49AgDY2tri8ePHmZudobGlgoiIcoDXr6PQpcsWfPHFFrx+HY3ISA3GjvWXOy0iIoneYyoqV66Ms2fPokSJEmjYsCGmTJmCV69eYcOGDShfvrwhcjQcFhVERJTN7dx5GwMG7EJwcIQU69SpDJYtayNjVkREuvRuqZg9ezZcXV0BALNmzYK9vT2++uorvHz5EsuXL9c7gSVLlsDd3R3m5uaoWbMmzpw5k+b2oaGh+Prrr+Hq6gozMzOULFkSe/bs0fu8ANj9iYiIsq2wsBj07bsd7dtvkgoKe3tz/PbbZ/jzz85wdLSSOUMiovf0bqmoVq2a9NjJyQn79u3L8Mk3b96MUaNGwdfXFzVr1sTChQvh6emJ27dvw8nJKdn2cXFxaN68OZycnLBlyxYUKFAADx8+hJ2dXcYSYEsFERFlQwEB9zFgwG48fhwuxdq0KYEVK9ohf/48MmZGRJQyvVsqUnPhwgW0bdtWr33mz5+P/v37o0+fPihbtix8fX1haWmJNWvWpLj9mjVr8ObNG2zbtg1169aFu7s7GjZsCA8Pj4wlzaKCiIiymbg4Lfr33yUVFHnyqLF6dXvs3NmVBQURZVt6tVTs378f/v7+UKvV+PLLL1G0aFHcunUL48ePx86dO+Hp6ZnuY8XFxeH8+fOYMGGCFFMqlWjWrBlOnjyZ4j47duxA7dq18fXXX2P79u1wdHREt27dMG7cOKhUKRcFsbGxiI2NlZbDwxPfpDUaDbQJGqmq0iRoAY0mhSMQJV4vH/5P9DG8ZigjNBoN1GolfvnFE15eW9C4cWGsWNEWhQvbIj4+Xu70KBview1lhCGul3QXFatXr0b//v2RN29evH37FqtWrcL8+fMxdOhQeHt749q1ayhTpky6T/zq1SskJCTA2dlZJ+7s7Ixbt26luE9QUBAOHjyI7t27Y8+ePQgMDMTgwYOh0WgwderUFPeZM2cOpk+fnix+6NAhNAp7Dtf/LwccPIxYE7t050/Gyd+fs62QfnjN0MfExWkRE6OFjc2Hf5ID8d13xVCunDWuXz+O69dlS49yCL7XkD6ioqIy/ZgKIYRIz4YVK1ZEz549MWbMGPz111/o3LkzatWqhT/++AMFCxbU+8TPnj1DgQIFcOLECdSuXVuKjx07FkeOHMHp06eT7VOyZEnExMTg/v37UsvE/PnzMXfuXDx//jzF86TUUuHm5obnz5/D6XhfKB/sBQBo+j8DLBz0fh5kHDQaDfz9/dG8eXOYmprKnQ7lALxmKD3OnXuGvn13onBhW+zY4Y34+HheN6QXvtdQRrx+/Rqurq4ICwuDjY1Nphwz3S0V9+7dQ+fOnQEAn332GUxMTDB37twMFRQA4ODgAJVKhZCQEJ14SEgIXFxcUtzH1dUVpqamOl2dypQpg+DgYMTFxUGtVifbx8zMDGZmyW8IZGpqCiW075fV5gB/GekjTE1N+aZNeuE1QymJi0vAzJlHMXv2v0hIELh16zX8/K6id++KAHjdkP54zZA+DHGtpHugdnR0NCwtLQEACoUCZmZm0tSyGaFWq1G1alUEBARIMa1Wi4CAAJ2Wiw/VrVsXgYGB0GrfFwN37tyBq6trigXFR+lMKav3RFhERER6u3o1BDVrrsJ33x1FQkJiZ4GqVV1Rp46bzJkREWWcXp+kV61aBWtrawBAfHw81q1bBwcH3S5Dw4YNS/fxRo0aBR8fH1SrVg01atTAwoULERkZiT59+gAAevXqhQIFCmDOnDkAgK+++gq//PILhg8fjqFDh+Lu3buYPXu2XufUwdmfiIgoi8THazF37nFMnXoYGk3il2MmJkp8+20DTJhQD6amKg62JaIcK91FRaFChbBy5Upp2cXFBRs2bNDZRqFQ6PUB39vbGy9fvsSUKVMQHByMSpUqYd++fdLg7UePHkGpfN+Y4ubmhv3792PkyJGoWLEiChQogOHDh2PcuHHpPqcOFhVERJQFbt16BR+fbThz5qkUK1/eCevXe6Fy5Yy3+hMRZRfpLioePHhgkASGDBmCIUOGpLju8OHDyWK1a9fGqVOnMufkvKM2EREZ2IMHoahceTliYhKnhFUqFRg7tg6mTWsEMzN2vSWi3CHTbn6XI7GlgoiIDMzd3Q6ff14WAFCyZD4cP94Xc+Y0Y0FBRLmKcb+jSUWFAlAoZE2FiIhyh6SZ2hUf/F35+eeWKFzYFhMn1oelJWfoIaLcx7hbKpK6P7HrExERZYInT8LRqtVG/PbbVZ24vb0FZs5swoKCiHIttlQA7PpERESfRAiBX3+9gqFD9yIsLBanTz9F48ZFkD9/HrlTIyLKEiwqABYVRESUYSEhERg0aDe2bbslxSwtTfHoURiLCiIyGhnq/nTv3j1MnjwZXbt2xYsXLwAAe/fuxfXr1zM1OYNj9yciIvoEW7bcQPnyy3QKih49KuLata9Qq1ZBGTMjIspaehcVR44cQYUKFXD69Gls3boVERERAIDLly9j6tSpmZ6gQbGlgoiIMuDNm2h06/YXOnf+E69eRQEAHB0tsXXrF9iwoSPs7S1kzpCIKGvpXVSMHz8eM2fOhL+/P9RqtRRv0qRJ5t0/IquwqCAiIj2dOfMU5cotxe+/X5Nin31WBtevD0bHjmVkzIyISD56j6m4evUqfvvtt2RxJycnvHr1KlOSyjLs/kRERHpyd7dDQoIWAGBnZ44lS1qja9fyOlPIEhEZG71bKuzs7PD8+fNk8YsXL6JAgQKZklSWYUsFERHpycnJCr6+bdG6dQlcvz4Y3bpVYEFBREZP76KiS5cuGDduHIKDg6FQKKDVanH8+HGMHj0avXr1MkSOhsOigoiI0hAZGYdx4/zx8mWkTvyzz8pg166unN2JiOj/9C4qZs+ejdKlS8PNzQ0REREoW7YsGjRogDp16mDy5MmGyNFw2P2JiIhScfz4I3h4+OLHH0/gq692S3fKTsLWCSKi9/QeU6FWq7Fy5Up8++23uHbtGiIiIlC5cmWUKFHCEPkZFlsqiIjoP2Ji4jFlyiH89NMJJNURe/bcxb17b1G8eF55kyMiyqb0LiqOHTuGevXqoVChQihUqJAhcso6gi0VRET03rlzz+Djsw03bryUYrVrF4SfnxcLCiKiNOjd/alJkyYoUqQIJk6ciBs3bhgip6yjZUsFEREBcXEJmDr1EGrVWiUVFGq1Cj/80Az//tsHJUrkkzlDIqLsTe+i4tmzZ/jmm29w5MgRlC9fHpUqVcLcuXPx5MkTQ+RnWOz+RERk9K5de4FatVZhxoyjSEhI7O9UpYorzp8fgLFj60Kl0vtPJRGR0dH7ndLBwQFDhgzB8ePHce/ePXTu3Bl+fn5wd3dHkyZNDJGj4bD7ExGR0bt48TkuXgwGAJiYKDFtWkOcOtUP5cs7yZwZEVHOofeYig8VKVIE48ePh4eHB7799lscOXIks/LKGuz+RERk9Hr0qIitW2/h7t3X8PPzQtWq+eVOiYgox8lwm+7x48cxePBguLq6olu3bihfvjx2796dmbkZHrs/EREZFa1W4MCBezoxhUKBNWva49y5ASwoiIgySO+iYsKECShSpAiaNGmCR48eYdGiRQgODsaGDRvQsmVLQ+RoGEIAQpv4mN2fiIhyvQcPQtG06Xp4ev6KHTtu66yzt7eAufknNd4TERk1vd9Bjx49ijFjxuCLL76Ag4ODIXLKGkmtFABbKoiIcjEhBFatuoBRow4gIiIOADBw4C40b14UFhamMmdHRJQ76F1UHD9+3BB5ZD0tiwoiotzu6dNwfPnlTuzbFyjFChe2xZo1HVhQEBFlonQVFTt27ECrVq1gamqKHTt2pLlt+/btMyUxg/uwpULJJm8iotxECIGNG69i6NC9CA2NkeJfflkZ8+Z5wsbGTMbsiIhyn3R9mvby8kJwcDCcnJzg5eWV6nYKhQIJCQmprs9W2P2JiChXevEiEoMG7cLff9+SYq6u1li1qj1aty4hY2ZERLlXuooKrVab4uMcTXzwPDhQm4go1xgxYp9OQdGtWwUsXtwKefNayJgVEVHupvfsT+vXr0dsbGyyeFxcHNavX58pSWUJjqkgIsqVfvyxOWxtzeDgYIktWzpj48bPWFAQERmY3kVFnz59EBYWliz+7t079OnTJ1OSyhLs/kRElCu8fRuts1ywoA22bvXG9euD0alTWZmyIiIyLnoXFUIIKBSKZPEnT57A1tY2U5LKEjoDtVlUEBHlNOHhsfjyyx3w8PBFWFiMzromTYrAyclKpsyIiIxPuqc9qly5MhQKBRQKBZo2bQoTk/e7JiQk4P79+znr5nfs/kRElGMdPHgfffpsx6NHiS3nI0fux5o1HWTOiojIeKW7qEia9enSpUvw9PSEtbW1tE6tVsPd3R2dOnXK9AQNh0UFEVFOExkZh/Hj/8Evv5yVYtbWatSqVVDGrIiIKN1FxdSpUwEA7u7u8Pb2hrm5ucGSyhKc/YmIKEc5ceIxfHy2ITDwjRRr1Mgda9d2gLu7nXyJERGR/nfU9vHxMUQeWY8DtYmIcoSYmHhMnXoIP/10ElqtAACYm5vghx+aYciQGlAqk4/zIyKirJWuoiJv3ry4c+cOHBwcYG9vn+JA7SRv3rxJdV22ouVAbSKi7E6rFWjUaB1On34qxWrVKoh16zqgVCkHGTMjIqIPpauoWLBgAfLkySM9TquoyDHYUkFElO0plQr4+Hjg9OmnUKtVmDGjEUaPrgOVSu/JC4mIyIDSVVR82OWpd+/ehsola7GoICLKEQYNqobbt1+jX7/KqFDBWe50iIgoBXp/1XPhwgVcvXpVWt6+fTu8vLwwceJExMXFZWpyBsXuT0RE2UpCghY//HAM33yzXyeuUCiwcGFLFhRERNmY3kXFwIEDcefOHQBAUFAQvL29YWlpiT///BNjx47N9AQNRSHEBwssKoiI5HTnzmvUr78W48cHYP78UwgICJI7JSIi0oPeRcWdO3dQqVIlAMCff/6Jhg0b4rfffsO6devw119/ZXZ+hsPuT0REstNqBRYvPo1KlXxx8uQTAIBCAVy48FzmzIiISB96TykrhIBWm3iPh3/++Qdt27YFALi5ueHVq1eZm50hCXZ/IiKS04MHoejbdzsOHXogxYoXz4t16zqgbt1C8iVGRER607uoqFatGmbOnIlmzZrhyJEjWLZsGQDg/v37cHbOQf1dtWypICKSgxACq1dfxMiR+xER8X4s3pAh1fH9981gZaWWMTsiIsoIvYuKhQsXonv37ti2bRsmTZqE4sWLAwC2bNmCOnXqZHqCBsPuT0REWS4sLAZdu/6FvXsDpVihQrZYs6Y9mjYtKmNmRET0KfQuKipWrKgz+1OSuXPnQqXKQR/O2f2JiCjLWVurER4eKy3361cZ8+d7wsbGTMasiIjoU+ldVCQ5f/48bt68CQAoW7YsqlSpkmlJZYn/jwsBwJYKIqIsolIpsW6dF1q12oiFCz3Rpk1JuVMiIqJMoHdR8eLFC3h7e+PIkSOws7MDAISGhqJx48bYtGkTHB0dMztHA2H3JyIiQ9u69SZcXa1Ru7abFCtePC9u3fqad8UmIspF9H5HHzp0KCIiInD9+nW8efMGb968wbVr1xAeHo5hw4YZIkfDYPcnIiKDefs2Gj16bEWnTn+gV69tiIzUvTkqCwoiotxF73f1ffv2YenSpShTpowUK1u2LJYsWYK9e/dmanIGpY1//5gtFUREmWbv3rsoX34ZNm5MHH8XGPhGekxERLmT3t2ftFotTE1Nk8VNTU2l+1fkCJz9iYgoU717F4tvvjmAlSsvSDFbWzMsXtwKPXpUlDEzIiIyNL1bKpo0aYLhw4fj2bNnUuzp06cYOXIkmjZtmqnJGZSW3Z+IiDLL4cMPULGir05B4elZDNeuDUbPnh5QKBQyZkdERIamd1Hxyy+/IDw8HO7u7ihWrBiKFSuGIkWKIDw8HIsXLzZEjoYhPmhVUWZ4EiwiIqMWFaXB8OF70bixHx48CAWQOG3s8uVtsXdvdxQsaCNvgkRElCX0/jTt5uaGCxcuICAgQJpStkyZMmjWrFmmJ2dQ7P5ERPTJHj4MxfLl56Xlhg0LY+3aDihSxF7GrIiIKKvpVVRs3rwZO3bsQFxcHJo2bYqhQ4caKi/DY1FBRPTJypRxxHffNcaUKYfx/fdNMXRoTSiV7OpERGRs0l1ULFu2DF9//TVKlCgBCwsLbN26Fffu3cPcuXMNmZ/hfDionGMqiIjS5cqVEJQqlQ9mZu//fIwaVRudOpVF0aJsnSAiMlbpHlPxyy+/YOrUqbh9+zYuXboEPz8/LF261JC5GRZbKoiI0k2jScD06YdRteoKTJ16WGedSqVkQUFEZOTSXVQEBQXBx8dHWu7WrRvi4+Px/PlzgyRmaAoWFURE6XL9+gvUqrUa06YdQXy8FnPnnsC5c88+viMRERmNdHd/io2NhZWVlbSsVCqhVqsRHR1tkMQMjt2fiIjSlJCgxfz5JzF58iHExSV+EaNSKTBpUn1UrOgsc3ZERJSd6DVQ+9tvv4WlpaW0HBcXh1mzZsHW1laKzZ8/P/OyMyS2VBARperu3dfo3Xs7Tpx4LMXKlHHA+vUdUa1afhkzIyKi7CjdRUWDBg1w+/ZtnVidOnUQFBQkLeeomxuxqCAiSkarFVi69CzGjvVHdHQ8AEChAL75pja++64JzM15Xx8iIkou3X8dDh8+bMA05MA7ahMR/Zef3yUMHbpXWi5WzB7r1nmhXr1CMmZFRETZnd531M41tGypICL6rx49KqJyZRcAwNdfV8fly4NYUBAR0UcZbzs2uz8RESEmJl6nS5OpqQobNnTE8+cRaNasqIyZERFRTmK8LRWCsz8RkfESQuD336/C3X0hLl7UnRq8XDknFhRERKQX4y0q2P2JiIzUy5eR+OKLLejWbStCQiLh47MNsbHxcqdFREQ5GLs/ASwqiMhobNt2CwMG7MTLl1FSrFw5J8TGJsDMzHj/JBAR0afJUEvFv//+ix49eqB27dp4+vQpAGDDhg04duxYpiZnUIKzPxGR8Xj7Nhq9ev2Njh03SwVFvnwW+OOPz/H7751gY2Mmc4ZERJST6V1U/PXXX/D09ISFhQUuXryI2NhYAEBYWBhmz56d6QkaDFsqiMhI7NsXiPLll2HDhitSrH37Urh+fTA6dy4nY2ZERJRb6F1UzJw5E76+vli5ciVMTU2leN26dXHhwoVMTc6gtB8M1GZRQUS51OzZ/6JVq4149uwdAMDW1gx+fl7Yts0bzs7WMmdHRES5hd5Fxe3bt9GgQYNkcVtbW4SGhmZGTlmD3Z+IyAh4ehaDSqUAADRvXhRXr36FXr08oFAoZM6MiIhyE71H5bm4uCAwMBDu7u468WPHjqFo0Rw0BaFgSwUR5X5Vq+bHzJlNYG9vjgEDqrKYICIig9C7paJ///4YPnw4Tp8+DYVCgWfPnmHjxo0YPXo0vvrqK0PkaBhatlQQUe5y6tQTdOv2F+LjtTrx8ePrYeDAaiwoiIjIYPRuqRg/fjy0Wi2aNm2KqKgoNGjQAGZmZhg9ejSGDh1qiBwNgwO1iSiXiI2Nx7Rph/Hjjyeg1QqUK+eISZOSd1MlIiIyFL1bKhQKBSZNmoQ3b97g2rVrOHXqFF6+fInvvvvOEPkZjIJFBRHlAhcvPke1aivx/ffHodUKAMDevYFISNB+ZE8iIqLMk+E7HanVapQtWzYzc8la4oO7x7L7ExHlMBpNAubMOYbvvjsqdXcyNVVi2rRGGDu2LlSqDN2GiIiIKEP0LioaN26cZr/cgwcPflJCWYYDtYkoh7px4yV69fob588/l2IeHs7w8/OCh4eLjJkREZGx0ruoqFSpks6yRqPBpUuXcO3aNfj4+GRWXobH7k9ElAPNn38SEycGIDY28T1MpVJgwoR6+PbbhlCr+V5GRETy0LuoWLBgQYrxadOmISIi4pMTyjI6sz9luBcYEVGWevbsnVRQlC7tAD8/L9SoUUDmrIiIyNhlWqfbHj16YM2aNZl1OMNjSwUR5UAzZzZBuXKO+Oab2rhwYQALCiIiyhYy7Sv6kydPwtzcPLMOZ3i8ozYRZXOPHoXh/Pln6NixjBQzNzfBuXMDYG7OFlYiIso+9P6r9Nlnn+ksCyHw/PlznDt3Dt9++22mJWZwWrZUEFH2JITAunWXMGLEfsTFJeDixYEoXdpBWs+CgoiIshu9/zLZ2trqLCuVSpQqVQozZsxAixYtMi0xg+PsT0SUDT1//g4DBuzCrl13pNjEiQHYutVbxqyIiIjSpldRkZCQgD59+qBChQqwt7c3VE5Z48Oigt2fiCgb2Lz5GgYP3oM3b6KlWJ8+lbBggaeMWREREX2cXkWFSqVCixYtcPPmzZxfVLD7ExFlE69eRWHw4N34888bUszZ2QorV7ZDu3alZMyMiIgoffTu/lS+fHkEBQWhSJEihsgn63CgNhFlAzt23Eb//jvx4kWkFPP2LoclS1ojXz5LGTMjIiJKP72nlJ05cyZGjx6NXbt24fnz5wgPD9f5l2NwSlkikllsbDxGjtwvFRR581pg06ZO2LTpcxYURESUo6S7qJgxYwYiIyPRunVrXL58Ge3bt0fBggVhb28Pe3t72NnZ5awuUSwqiEhmZmYmWLu2AxQKoH37Urh+fTC8vcvLnRYREZHe0t39afr06Rg0aBAOHTpkyHyyjpbdn4goa0VExOHdu1i4uuaRYg0aFMbp01+iWrX8UCgUMmZHRESUcekuKoQQAICGDRtmehJLlizB3LlzERwcDA8PDyxevBg1atT46H6bNm1C165d0aFDB2zbtk3Ps344pWym3ViciChFR48+RO/e21CokC0OHvSBUvm+gKhenXfFJiKinE2vT9OG+BZt8+bNGDVqFKZOnYoLFy7Aw8MDnp6eePHiRZr7PXjwAKNHj0b9+vUzduKk7k/s+kREBhQdrcGoUfvRqNE63L8fiiNHHmLx4tNyp0VERJSp9CoqSpYsibx586b5T1/z589H//790adPH5QtWxa+vr6wtLTEmjVrUt0nISEB3bt3x/Tp01G0aFG9zwkAiqTuT+z6REQGcudOJKpXX40FC07h/429qF+/ENq2LSlvYkRERJlMryllp0+fnuyO2p8iLi4O58+fx4QJE6SYUqlEs2bNcPLkyVT3mzFjBpycnNCvXz/8+++/GTs5WyqIyEBiY+MxdephzJ17F9r/97Q0M1Nh9uymGD68JlQqdrkkIqLcRa+iokuXLnBycsq0k7969QoJCQlwdnbWiTs7O+PWrVsp7nPs2DGsXr0aly5dStc5YmNjERsbKy0nTXsr/t9SIRQqxGs0GciejInm/9eIhtcKfcTlyyHo23cnrl5934WzWjVXrF7dDmXKOECrTYD2w4kiiD7A9xrSF68ZyghDXC/pLiqyw6wk7969Q8+ePbFy5Uo4ODika585c+Zg+vTpyeKRke9gpwLiE7TYs2dPZqdKuZS/v7/cKVA29uJFHAYPvon4+MS+TiYmCnh7O+Ozz5xw//4Z3L8vc4KUY/C9hvTFa4b0ERUVlenH1Hv2p8zk4OAAlUqFkJAQnXhISAhcXFySbX/v3j08ePAA7dq1k2La//ctMDExwe3bt1GsWDGdfSZMmIBRo0ZJy+Hh4XBzc4OVhTkQB5iozdG6devMfFqUC2k0Gvj7+6N58+YwNTWVOx3Kxs6eNcPKlRdRvrwj+va1x8CBHXjNULrxvYb0xWuGMuL169eZfsx0FxVJH94zk1qtRtWqVREQEAAvLy/pPAEBARgyZEiy7UuXLo2rV6/qxCZPnox3795h0aJFcHNzS7aPmZkZzMzMksUVIvH5KBQq/hJSupmamvJ6IUlCghZKpUKnJXfePE8ULZoXQ4ZURUDAAV4zlCG8bkhfvGZIH4a4VvQaU2EIo0aNgo+PD6pVq4YaNWpg4cKFiIyMRJ8+fQAAvXr1QoECBTBnzhyYm5ujfHndu83a2dkBQLL4RwnO/kREGXfv3hv07r0dPj4e+PLLKlI8Tx4zjB9fj/2biYjIqMheVHh7e+Ply5eYMmUKgoODUalSJezbt08avP3o0SMolQaYKUXL2Z+ISH9CCPj6nsPo0f6IitLg0qVgNGtWFO7udnKnRkREJBvZiwoAGDJkSIrdnQDg8OHDae67bt26jJ2UU8oSkZ4ePQpDv3478M8/QVLM0dESr15FsaggIiKjli2KClmw+xMRpZMQAn5+lzF8+D6Eh7+fonrgwKqYO7c58uRJPm6LiIjImBhvUaFNSLyfOFsqiCgNwcERGDBgJ3buvCPFChTIg9Wr28PTs7iMmREREWUfxltUsPsTEX3EyZOP0bbt73jzJlqK9erlgUWLWsLOzlzGzIiIiLIX4y0qwO5PRJS20qUdYG6e+Dbp5GSFFSvaokOH0jJnRURElP0Yb1GhTQBUAJTG+xIQUdrs7S2wenV7rFlzEUuXtoGDg6XcKREREWVLBpirNYdg9yci+kBYWAy+/no3nj17pxNv2bI4/vijMwsKIiKiNBjv1/QsKojo//z976Fv3x148iQcDx6EYdeurjp3ySYiIqK0GW1LhUKIxAccU0FktCIi4jB48G60aPErnjwJBwAcO/YIgYFvZM6MiIgoZzHelookbKkgMkpHjz5Enz7bERT0Voo1a1YUq1e3R6FCtjJmRkRElPOwqGBRQWRUoqM1mDz5IBYsOIWkBktLS1PMndscgwZVg1LJbk9ERET6YlHB7k9ERuPs2afo1Wsbbt16JcXq1SuEtWs7oHjxvDJmRkRElLOxqGBLBZHRePw4XCoozMxUmDWrCUaMqAWVymiHlxEREWUKFhUsKoiMxmeflUH37hVw+/Zr+Pl5oWxZR7lTIiIiyhVYVLD7E1GuFB+vxbZtt9CpUxmd6WF9fdvCzEwFU1P+7hMREWUWtvmzpYIo17l58yXq1FmNzp3/xObN13XWWVurWVAQERFlMhYVLCqIco2EBC3mzz+JypWX4+zZZwCAYcP2IipKI3NmREREuRu7P7H7E1GucO/eG/Tpsx3//vtIipUsmQ9+fl6wtDSVMTMiIqLcj0UFWyqIcjQhBJYvP4/Row8gMvJ9i8SIETUxa1ZTFhRERERZgEUFiwqiHOvx4zD067cD/v5BUszd3Q5r13ZAo0bu8iVGRERkZFhUsPsTUY41ceJBnYJi4MCqmDu3OfLkMZMxKyIiIuPDooItFUQ51k8/Nce+fYEwM1Nh9er28PQsLndKRERERolFBYsKohwjODgCLi7W0rKzszV27eqKUqUcYGdnLmNmRERExo1TyrL7E1G29/p1FLp02YJKlXzx6lWUzrqaNQuyoCAiIpIZiwq2VBBlazt33kb58suwefN1hIRE4uuv98idEhEREf0Huz+xqCDKlsLCYjBy5H6sXXtJitnbm6Njx9IQQkChUMiXHBEREelgUcHuT0TZzj//BKFv3+14/DhcirVpUwIrV7aDq2seGTMjIiKilLCoYEsFUbYRGRmHsWP9sXTpOSmWJ48aixa1RO/eldg6QURElE2xqGBRQZQtCCHQsOE6nD//XIo1aVIEa9a0R+HCdvIlRkRERB/Fgdrs/kSULSgUCgwdWgMAYGlpil9+aQV//54sKIiIiHIAtlSwpYJINv8dcN2rlwcCA9+gVy8PlCiRT8bMiIiISB8sKpR8CYiyWlxcAmbOPIrnz99h5cr2UlyhUOC775rImBkRERFlBD9Rs6WCKEtdvRqCXr224dKlYABA+/al0K5dKZmzIiIiok/BooJjKoiyRHy8FnPnHsfUqYeh0WgBACYmSgQFvZU5MyIiIvpULCrYUkFkcLdvv4KPzzacPv1UipUv7wQ/Py9UqeIqY2ZERESUGVhUsKggMhitVuDnn09jwoQAxMTEAwCUSgXGjq2DadMawcyMb0FERES5Af+is/sTkUGEhcWgQ4dNOHLkoRQrWTIf/Py8UKtWQRkzIyIioszGooItFUQGYWNjBrX6/e/X8OE1MXt2U1hamsqYFRERERkCb37HooLIIBQKBVavbg8PD2ccPNgLCxe2ZEFBRESUS7Glgt2fiD6ZEAIbNlyBm5sNGjcuIsXd3Gxx8eJAnRvcERERUe7DooItFUSfJCQkAgMH7sL27bdRqJAtrlwZBFtbc2k9CwoiIqLcj92fWFQQZdiWLTdQrtxSbN9+GwDw6FEY/vzzhsxZERERUVZjSwW7PxHp7c2baAwZsge//35Nijk6WsLXty0++6yMjJkRERGRHFhUsKWCSC+7dt1B//47ERwcIcU++6wMli1rAycnKxkzIyIiIrmwqGBLBVG6hIXFYNSo/Viz5pIUs7Mzx5IlrdG1a3mOnSAiIjJiLCrYUkGULi9fRmHTpuvScqtWxbFqVXvkz59HxqyIiIgoO+BAbRYVROlSvHhezJ3bHHnyqLFqVTvs3t2NBQUREREBYEsFuz8RpeLUqSeoUMEJVlZqKTZoUDV4eZVmMUFEREQ62FLBlgoiHTEx8Rg71h916qzGhAkBOuuUSgULCiIiIkqGRQWLCiLJuXPPULXqCsydewJCAIsXn8GpU0/kTouIiIiyOXZ/YvcnIsTFJWDWrKOYNetfJCQIAIBarcLMmY1RvXp+mbMjIiKi7I5FBVsqyMhdvRoCH59tuHgxWIpVqeKK9eu9UK6ck4yZERERUU7BooJFBRmphAQtfvrpBKZMOYy4uAQAgImJEpMn18fEifVhasrfDSIiIkofFhXs/kRG6tdfr2D8+PcDscuVc8T69R1RpYqrjFkRERFRTsSB2mypICPVo0dF1KnjBqVSgXHj6uL8+QEsKIiIiChD2FLBooKMRHh4LGxszKRllUoJPz8vvHgRiTp13GTMjIiIiHI6tlSw+xPlckIIrFx5HoUKLcDJk4911hUvnpcFBREREX0yFhVKNtZQ7vX0aThat/4NAwbsQlhYLHx8tiEqSiN3WkRERJTL8BM1uz9RLiSEwMaNVzF06F6EhsZI8YYNC0OrFTJmRkRERLkRiwoWFZTLvHgRiUGDduHvv29JMVdXa6xa1R6tW5eQMTMiIiLKrVhUcEwF5SJbttzAV1/txqtXUVKsW7cKWLy4FfLmtZAxMyIiIsrNWFSwpYJyienTD2PatCPSsoODJXx926BTp7IyZkVERETGgAO1WVRQLtGpU1mo1YnXs5dXaVy/PpgFBREREWUJtlSw+xPlEuXLO2HevBawszNH9+4VoFAo5E6JiIiIjARbKthSQTnQwYP30a7d74iNjdeJDxlSAz16VGRBQURERFmKRQWLCspBIiPjMHToHjRtuh67dt3B9OlHPr4TERERkYGx+xO7P1EOceLEY/j4bENg4BspdvbsMyQkaKFS8fsBIiIikg8/ibClgrK5mJh4jBvnj/r110oFhYWFCRYtaon9+3uwoCAiIiLZsaWCRQVlY+fPP4OPzzZcv/5SitWqVRB+fl4oWTKfjJkRERERvcevONn9ibKpWbOOolat1VJBoVar8P33TXHsWB8WFERERJStsKWCLRWUTcXGJiA+XgsAqFzZBevXd0T58k4yZ0VERESUHIsKFhWUTU2e3AD79gWidesSmDSpPkxNea0SERFR9sSigt2fKBu4e/c1Tp16gp49PaSYWq3CiRP9YGLCXopERESUvbGoYEsFyUirFViy5AzGjfsH8fFaVKjgjEqVXKT1LCiIiIgoJ+AnFgVfApLHw4ehaNZsPYYN24fo6HhoNFrMmMGb2REREVHOY9yfqBVKQKGQOwsyMkIIrF59ARUqLMOhQw+k+JAh1bFhQ0f5EiMiIiLKIOPu/sSuT5TFnj17h/79d2LPnrtSrFAhW6xZ0x5NmxaVMTMiIiKijDPuooKDtCmLCCHw++/XMGTIHrx9GyPF+/WrjPnzPWFjYyZjdkRERESfxriLCrZUUBbRaLSYOfOoVFC4ulpj5cp2aNOmpMyZEREREX06Ix9TwaKCsoZarYKfnxdUKgW6dauAa9cGs6AgIiKiXMO4WyrY/YkM5O3baISFxcLd3U6KVa9eAFeufIWyZR3lS4yIiIjIANhSQZTJ9u69i/Lll8Hbewvi47U661hQEBERUW7EooIok4SHx6J//x1o3fo3PHv2DmfOPMW8eSfkTouIiIjI4Iy8+5NxP33KPIcO3UefPtvx8GGYFPP0LIbu3SvKmBURERFR1jDuT9VsqaBPFBWlwYQJ/+Dnn89IMSsrU8yf74n+/atAwZsrEhERkREw7qKCA7XpE5w8+Rg+Pttw9+4bKdagQWGsXdsBRYvay5gZERERUdbKFmMqlixZAnd3d5ibm6NmzZo4c+ZMqtuuXLkS9evXh729Pezt7dGsWbM0t08TWyoogx49CkODBuukgsLc3AQLFnji0CEfFhRERERkdGQvKjZv3oxRo0Zh6tSpuHDhAjw8PODp6YkXL16kuP3hw4fRtWtXHDp0CCdPnoSbmxtatGiBp0+f6n9yFhWUQYUK2WLo0BoAgJo1C+DSpYEYMaIWlEp2dyIiIiLjI3tRMX/+fPTv3x99+vRB2bJl4evrC0tLS6xZsybF7Tdu3IjBgwejUqVKKF26NFatWgWtVouAgAD9T87uT5ROGk0CtFqhE5s1qwl++aUVjh3ri1KlHGTKjIiIiEh+shYVcXFxOH/+PJo1aybFlEolmjVrhpMnT6brGFFRUdBoNMibN6/+CbClgtLh+vUXqF/fD7t3v9KJW1iY4uuva8DERPbanIiIiEhWsg7UfvXqFRISEuDs7KwTd3Z2xq1bt9J1jHHjxiF//vw6hcmHYmNjERsbKy2Hh4dLjwWUiNdoMpA5GYOEBC0WLjyDqVOPIC4uAdeuKTBkSAjKlXP++M5k9DT/f2/R8D2G9MDrhvTFa4YywhDXS46e/en777/Hpk2bcPjwYZibm6e4zZw5czB9+vQU14W9i8CRPXsMmSLlUM+exeLnnx/h1q1IKebkpMbhw8fw8KGFjJlRTuPv7y93CpQD8bohffGaIX1ERUVl+jFlLSocHBygUqkQEhKiEw8JCYGLi0ua+/7000/4/vvv8c8//6BixdRvMDZhwgSMGjVKWg4PD4ebmxsAwMYuL1q3bv0Jz4ByG61WwNf3PCZMOIjo6HgAgEIBDBtWHXXrxqJNG0+YmprKnCXlBBqNBv7+/mjevDmvGUo3XjekL14zlBGvX7/O9GPKWlSo1WpUrVoVAQEB8PLyAgBp0PWQIUNS3e/HH3/ErFmzsH//flSrVi3Nc5iZmcHMzCzFdUqlCZT8BaT/e/gwFH377sDBg/elWLFi9li3zgs1a7piz549MDU15Zs26YXXDGUErxvSF68Z0ochrhXZuz+NGjUKPj4+qFatGmrUqIGFCxciMjISffr0AQD06tULBQoUwJw5cwAAP/zwA6ZMmYLffvsN7u7uCA4OBgBYW1vD2tpav5Nz9if6v2PHHqF164149y5Oin39dXX88EMzWFmp2VeViIiIKA2yFxXe3t54+fIlpkyZguDgYFSqVAn79u2TBm8/evQISuX72XWWLVuGuLg4fP755zrHmTp1KqZNm6bfyTn7E/2fh4cz8uWzxLt3cXBzs8GaNR3QrFlRudMiIiIiyhFkLyoAYMiQIal2dzp8+LDO8oMHDzLvxGypoP/Lk8cM69Z1wPr1lzF/vidsbVMe+E9EREREyRn3BPtsqTBKL19Golevv/HgQahOvGFDd6xe3YEFBREREZGeskVLhWxYVBidbdtuYcCAnXj5MgqPH4cjIKAXlEqF3GkRERER5WjG3VLB7k9G4+3baPTs+Tc6dtyMly8T52a+ejUEgYFvZM6MiIiIKOdjSwXlevv2BaJfvx149uydFGvfvhRWrGgLZ2c9ZwwjIiIiomRYVFCu9e5dLEaPPoAVKy5IMVtbM/z8cyv07FkRCgW7PRERERFlBuMuKtj9Kdf699+H6NVrm85g7ObNi2L16vZwc7OVLzEiIiKiXMi4iwq2VORakZEaqaCwsjLFvHktMGBAVbZOEBERERkAiwrKlVq2LI7+/avg1q1XWLfOC0WL2sudEhEREVGuZdxFBbs/5QqxsfH47ber6N27kk5LxKJFLWFmZsIpY4mIiIgMzLiLCrZU5HgXLz5Hr17bcO3aC2i1Av36VZHWWViYypgZERERkfEw7vtUsKjIsTSaBMyYcQQ1aqzCtWsvAADjxv2DyMg4mTMjIiIiMj7G3VLB7k850o0bL9Gr1984f/65FPPwcIafnxesrNQyZkZERERknIy7qFAY99PPaRIStFiw4BQmTz6I2NgEAIBKpcCECfXw7bcNoVazSCQiIiKSg3F/qmZLRY4RGPgGvXtvw/Hjj6VY6dIOWL/eC9WrF5AxMyIiIiLimArKEWbP/lcqKBQK4JtvauPChQEsKIiIiIiyAeNuqWBRkWP89FML7NsXCAsLU/j5eaFevUJyp0RERERE/2fcRQW7P2VLQgg8eBCKIkXe37Aub14L7N3bHcWK5YW1NQdjExEREWUn7P5E2crz5+/Qvv0mVK26As+fv9NZ5+HhwoKCiIiIKBsy7qKCLRXZyubN11C+/DLs2nUHb9/GoH//nRBCyJ0WEREREX2EcXd/YktFtvDqVRQGD96NP/+8IcWcna0wcGBVKBQKGTMjIiIiovRgUUGy2rHjNvr334kXLyKlmLd3OSxZ0hr58lnKmBkRERERpZdxFxXs/iSb0NAYjBixD35+l6VY3rwWWLq0Nby9y8uYGRERERHpy7iLCrZUyEIIgSZN/HDxYrAUa9euJFasaAcXF2sZMyMiIiKijDDugdosKmShUCgwcWJ9AICNjRnWreuA7du7sKAgIiIiyqGMu6WC3Z+yjFYroFS+H3T9+edl8eOPzdClS3m4udnKmBkRERERfSrjLirYUmFw0dEaTJwYgODgSPz+eyeddWPG1JUpKyIiIiLKTCwqyGBOn34CH59tuH37NQDAy6sUB2ETERER5ULGXVSw+5NBxMbGY8aMI/j+++PQahNvXmdmpkJoaIzMmRERERGRIRh3UcGWikx36VIwfHy24cqVEClWvXp++Pl5oUwZRxkzIyIiIiJDYVFBmSI+Xovvvz+G6dOPID5eCwAwNVVi6tSGGDeuHkxMjHuiMSIiIqLczLiLCnZ/yhShoTFo0WIDzp59JsUqVnSGn58XKlVykTEzIiIiIsoKxv31MVsqMoWtrRlcXfMAAJRKBSZOrIczZ75kQUFERERkJIy7pYJFRaZQKBRYvrwtXr+Owrx5LVCzZkG5UyIiIiKiLGTcRQW7P+lNCAFf33MoVMgWbdqUlOIuLtY4dqyvjJkRERERkVyMu6hgS4VeHj8OQ79+O+DvHwRnZytcvz4Y+fJZyp0WEREREcmMYyroo4QQWLfuEsqXXwZ//yAAQEhIJHbsuC1zZkRERESUHRh3SwW7P31UcHAEBgzYiZ0770ixAgXyYPXq9vD0LC5jZkRElNUSEhKg0WjkToM+oNFoYGJigpiYGCQkJMidDmUTpqamUKmy9nOucRcVbKlI0+bN1zB48B68eRMtxXx8PLBwYUvY2ZnLmBkREWUlIQSCg4MRGhoqdyr0H0IIuLi44PHjx1AoFHKnQ9mInZ0dXFxcsuy6MO6iQmncTz81r19HYfDgPfjjj+tSzMnJCitWtEWHDqVlzIyIiOSQVFA4OTnB0tKSH16zEa1Wi4iICFhbW0OpNO5e7ZRICIGoqCi8ePECAODq6pol5zXuT9VsqUhRVJQG+/YFSsudO5fF0qVt4ODAQdlERMYmISFBKijy5csndzr0H1qtFnFxcTA3N2dRQRILCwsAwIsXL+Dk5JQlXaGM++rjmIoUubnZYtGilsib1wKbNnXCH390ZkFBRGSkksZQWFry7wBRTpL0O5tV46DYUkEICAhC9eoFYGNjJsV8fDzQrl1JThlLREQAwC5PRDlMVv/OGndLhZEXFRERcfjqq11o1mwDRo7cp7NOoVCwoCAiIiKidDHuosKIuz8dPfoQHh6+8PU9DwBYs+YSjh17JHNWRERElF28fv0aTk5OePDggdyp0Afi4uLg7u6Oc+fOyZ2KDuMuKoywpSI6WoNvvtmPRo3WISjoLQDA0tIUS5a0Rp06bjJnR0RElDl69+4NhUIBhUIBU1NTFClSBGPHjkVMTEyybXft2oWGDRsiT548sLS0RPXq1bFu3boUj/vXX3+hUaNGsLW1hbW1NSpWrIgZM2bgzZs3aeZz6NAhtG7dGvny5YOlpSXKli2Lb775Bk+fPs2Mp2sQs2bNQocOHeDu7p5snaenJ1QqFc6ePZtsXaNGjTBixIhk8XXr1sHOzk4nFh4ejkmTJqF06dIwNzeHi4sLmjVrhq1bt0IIkUnPJLnDhw+jSpUqMDMzQ/HixVP9eX/ojz/+QKVKlWBpaYnChQtj7ty5ybbZuHEjPDw8YGlpCVdXV/Tt2xevX7/W2SY0NBRff/01XF1dYWZmhpIlS2LPnj062yxZsgTu7u4wNzdHzZo1cebMGWmdWq3G6NGjMW7cuIw9eQNhUWFEzpx5iipVVmD+/FNI+j2tV68QLl8ehMGDq0OpZH9ZIiLKPVq2bInnz58jKCgICxYswPLlyzF16lSdbRYvXowOHTqgbt26OH36NK5cuYIuXbpg0KBBGD16tM62kyZNgre3N6pXr469e/fi2rVrmDdvHi5fvowNGzakmsfy5cvRrFkzuLi44K+//sKNGzfg6+uLsLAwzJs3L8PPLy4uLsP7fkxUVBRWr16Nfv36JVv36NEjnDhxAkOGDMGaNWsyfI7Q0FDUqVMH69evx4QJE3DhwgUcPXoU3t7eGDt2LMLCwj7lKaTq/v37aNOmDRo3boxLly5hxIgR+PLLL7F///5U99m7dy+6d++OQYMG4dq1a1i6dCkWLFiAX375Rdrm+PHj6NWrF/r164fr16/jzz//xJkzZ9C/f39pm7i4ODRv3hwPHjzAli1bcPv2baxcuRIFChSQttm8eTNGjRqFqVOn4sKFC/Dw8ICnp6c0RSwAdO/eHceOHcP16++n/5edMDJhYWECgAibCSFeXJY7nSwRGxsvJk0KECrVdAFME8A0YWb2nfjpp+MiPj5B7vRyhLi4OLFt2zYRFxcndyqUQ/CaoYzIjtdNdHS0uHHjhoiOjpY7Fb34+PiIDh066MQ+++wzUblyZWn50aNHwtTUVIwaNSrZ/j///LMAIE6dOiWEEOL06dMCgFi4cGGK53v79m2K8cePHwu1Wi1GjBiR5n5Tp04VHh4eOusWLFggChcunOw5zZw5U7i6ugp3d3cxfvx4UbVqVZGQoPv3vGLFimL69OnS8sqVK0Xp0qWFmZmZKFWqlFiyZEmK+ST5888/haOjY4rrpk2bJrp06SJu3rwpbG1tRVRUlM76hg0biuHDhyfbb+3atcLW1lZa/uqrr4SVlZV4+vRpsm3fvXsnNBpNmjlm1NixY0W5cuV0Yt7e3sLT0zPVfbp27So+//xzndjPP/8sChYsKLRarRBCiLlz54qiRYsm26ZAgQLS8rJly0TRokXT/B2vUaOG+Prrr6XlhIQEkT9/fjFnzhyd7Ro3biwmT56c6nHS+t199epV4ufhsLBU99cXZ38yAn/8cR2zZv0rLVerlh9+fl4oW9ZRxqyIiCjH+rUaEBmc9ee1cgF6ZKwf+bVr13DixAkULlxYim3ZsgUajSZZiwQADBw4EBMnTsTvv/+OmjVrYuPGjbC2tsbgwYNTPP5/u/Uk+fPPPxEXF4exY8fqtV9qAgICYGNjA39/fwCJ96n4/vvvce/ePZQoUQIAcP36dVy5cgV//fUXgMQuOVOmTMEvv/yCypUr4+LFi+jfvz+srKzg4+OT4nn+/fdfVK1aNVlcCIG1a9diyZIlKF26NIoXL44tW7agZ8+eej0PrVaLTZs2oXv37sifP3+y9dbW1qnu+++//6JVq1ZpHn/58uXo3r17iutOnjyJZs2a6cQ8PT1T7LKVJDY2Ntm0yhYWFnjy5AkePnwId3d31K5dGxMnTsSePXvQqlUrvHjxAlu2bEHr1q2lfXbs2IHatWvj66+/xvbt2+Ho6Ihu3bph3LhxUKlUiIuLw/nz5zFhwgRpH6VSiWbNmuHkyZM6569Rowb+/fdfZBcsKoxAt24VsG7dJRw58hBTpjTA+PH1YGpqHM+diIgMIDIYiMi+YwGS7Nq1C9bW1oiPj0dsbCyUSqVOd5U7d+7A1tY2xTsOq9VqFC1aFHfu3AEA3L17F0WLFoWpqaleOdy9exc2NjaZdldjKysrrFq1Cmq1GkDih/Py5cvj999/x5QpUwAkFhE1a9ZE8eLFAQBTp07FvHnz8NlnnwEAihQpghs3bmD58uWpFhUPHz5M8cP+P//8g6ioKHh6egIAevTogdWrV+tdVLx69Qpv375F6dKl9doPAKpVq4ZLly6luY2zs3Oq64KDg5Otd3Z2Rnh4OKKjo6Ubx33I09MTI0eORO/evdG4cWMEBgZKXdeeP38Od3d31K1bFxs3boS3tzdiYmIQHx+Pdu3aYcmSJdJxgoKCcPDgQXTv3h179uxBYGAgBg8eDI1Gg6lTp+LVq1dISEhIMb9bt27pxPLnz4+HDx+m+TpkJeMuKnLp7E+vXkXp3KxOqVRgzZoOeP06CpUrZ82t2omIKBezcskR523cuDGWLVuGyMhILFiwACYmJujUqVOGTi0yOGhYCJGp9wuoUKGCVFAk6dy5s1RUCCHw+++/Y9SoUQCAyMhI3Lt3D/369dPp2x8fHw9bW9tUzxMdHQ1zc/Nk8TVr1sDb2xsmJokfIbt27YoxY8bg3r17KFasWLqfR0ZfTyCxhSCpYMoq/fv3x71799C2bVtoNBrY2Nhg+PDhmDZtmnQn8xs3bmD48OGYMmUKPD098fz5c4wZMwaDBg3C6tWrASQWgU5OTlixYgVUKhWqVq2Kp0+fYu7cucnG+3yMhYUFoqKiMv25ZpRxFxW5rKVCqxVYtOgUJk06iN27u6Fx4yLSukKFbFGoUOpvHkREROmWwS5IWc3Kykr68LlmzRp4eHjoDD4uWbIkwsLC8OzZs2TfysfFxeHevXto3LixtO2xY8eg0Wj0aq1IOsfz58/TbK1QKpXJPmindCdkKyurZLFOnTph2rRpuHDhAqKjo/H48WN4e3sDACIiIgAAK1euRM2aNXX2U6lS/xzk4OCAt2/f6sTevHmDv//+GxqNBsuWLZPiCQkJWLNmDWbNmgUAsLGxSXGQdWhoqFTIODo6ws7OLtm37+nxqd2fXFxcEBISohMLCQmBjY1Niq0UQOL9u3744QfMnj0bwcHBcHR0REBAAACgaNGiAIA5c+agbt26GDNmDACgYsWKsLKyQv369TFz5ky4urrC1dUVpqamOq99mTJlEBwcjLi4ODg4OEClUqWYn4uLblH95s0bODpmn67sxj37Uy5qqQgKeovGjf0watQBREfHo0+f7QgPj5U7LSIiomxBqVRi4sSJmDx5MqKjowEkfhg3NTVNcQYmX19fREZGomvXrgCAbt26ISIiAkuXLk3x+KGhoSnGP//8c6jVavz4449p7ufo6Ijg4GCdwuJjXXySFChQAA0bNsTGjRuxceNGNG/eHE5OTgASu83kz58fQUFBKF68uM6/IkWKpHrMypUr48aNGzqxjRs3omDBgrh8+TIuXbok/Zs3bx7WrVuHhIQEAECpUqVw4cKFZMe8cOECSpYsCSDx59GlSxds3LgRz549S7ZtREQE4uPjU8wtqftTWv/at2+f6nOrXbu2VBAk8ff3R+3atVPdJ4lKpUKBAgWgVqvx+++/o3bt2tIH+6ioKKnV4sPtgfctM3Xr1kVgYCC0Wq20zZ07d+Dq6gq1Wg21Wo2qVavq5KfVahEQEJAsv2vXrqFy5cofzTnLZNqQ7xxCZ/an8Mdyp/PJtFqtWLbsrLCymiXN7ARMEyNG7BVRUdln9pCcLjvOyELZG68ZyojseN3kptmfNBqNKFCggJg7d64UW7BggVAqlWLixIni5s2bIjAwUMybN0+YmZmJb775Rmf/sWPHCpVKJcaMGSNOnDghHjx4IP755x/x+eefpzorlBBCLFmyRCgUCtG3b19x+PBh8eDBA3Hs2DExYMAAaeapGzduCIVCIb7//nsRGBgofvnlF2Fvb5/i7E8fSkhIEG/fvhXLly8X+fPnFw4ODmLDhg0626xcuVJYWFiIRYsWidu3b4srV66INWvWiHnz5qWa85UrV4SJiYl48+aNFPPw8BDjxo1Ltm1oaKhQq9Vi165dQggh7t27J8zNzcXQoUPF5cuXxa1bt8S8efOEiYmJ2Lt3r7Tf69evRenSpUXBggWFn5+fuH79urhz545YvXq1KF68eKozan2qoKAgYWlpKcaMGSNu3rwplixZIlQqldi3b5+0zeLFi0WTJk2k5ZcvX4ply5aJmzdviosXL4phw4YJc3Nzcfr0aWmbtWvXChMTE7F06VJx7949cezYMVGtWjVRo0YNaZtHjx6JPHnyiCFDhojbt2+LXbt2CScnJzFz5kxpm02bNgkzMzOxbt06cePGDTFgwABhZ2cngoODdZ5H4cKFxfr161N9nlk9+5NxFxXvnsmdzid59ChUtGixQaeYcHdfKA4dui93arlOdvxDT9kbrxnKiOx43eSmokIIIebMmSMcHR1FRESEFNu+fbuoX7++sLKyEubm5qJq1apizZo1KR538+bNokGDBiJPnjzCyspKVKxYUcyYMeOjH4D9/f2Fp6ensLe3F+bm5qJ06dJi9OjR4tmz959Fli1bJtzc3ISVlZXo1auXmDVrVrqLitevXwszMzNhaWkp3r17l+z8GzduFJUqVRJqtVrY29uLBg0aiK1bt6aZc40aNYSvr68QQohz584JAOLMmTMpbtuqVSvRsWNHafnMmTOiefPmwtHRUdja2oqaNWuKv//+O9l+oaGhYvz48aJEiRJCrVYLZ2dn0axZM/H3339LU7UawqFDh6TXo2jRomLt2rU666dOnarz2r98+VLUqlVLWFlZCUtLS9G0aVNpuuEP/fzzz6Js2bLCwsJCuLq6iu7du4snT57obHPixAlRs2ZNYWZmJooWLSpmzZol4uPjdbZZvHixKFSokFCr1aJGjRrJznXixAlhZ2eXbDrfD2V1UaEQwoC3K8yGwsPDYWtri7CZgM3IEMDSSe6U9CaEwPr1lzFs2D6dLk4DB1bF3LnNkSePmYzZ5U4ajQZ79uxB69at9Z75g4wTrxnKiOx43cTExOD+/fsoUqRIigN3SV5arRbh4eGwsbFJ1vXmU+3evRtjxozBtWvXMv3Y9Gm8vb3h4eGBiRMnprpNWr+7r1+/hoODA8LCwmBjY5MpOXGgdg40ZcohzJz5fl7iAgXyYNWq9mjZMmtnQiAiIqLcq02bNrh79y6ePn0KNzc3udOh/4uLi0OFChUwcuRIuVPRYdxlZw4tKnr18oCFRWI92LNnRVy9+hULCiIiIsp0I0aMYEGRzajVakyePDnVmarkYtwtFTlk9ifxnzmuS5TIhyVLWsPe3gJeXvrfNIaIiIiIKDOxpSKb27nzNho18kNUlO5c1X36VGZBQURERETZAouKbCosLAZ9+25H+/abcPToQ0yY8I/cKRERERERpYjdn7Khf/4JQt++2/H4cbgUCwoKRXy8FiYmxl0HEhEREVH2Y9xFRTZrqYiMjMPYsf5YuvScFMuTR42FC1uiT59KOuMqiIiIiIiyi/+1d+dxUVf7/8BfwwDDIou4AYoLCug1N0QMzDSiQM0wS7jKQxFxuQHhlUzNDckr7pQLuVSIt8sNlwz9JUJKkoIrCGiBkAhpN8GEK4SCLHN+f/h1biOgDCCDzOv5eMzj0ZzPOZ/P+zOdwc97zjmfj8YmFQIA2tBFenLyDcycGYu8vP8qylxc+iAy8k306mWqvsCIiIiIiJ5Cc+fStKGpT8uXf4+XX96jSCgMDHSwffs4HD8+nQkFERHRMySRSBAbG6vuMFrczJkzMWnSJHWHQRpEc5MKSdsZpDEy0sWj55o7O1shI2MeAgIcoaXVdkZSiIiInjeFhYV47733YG1tDZlMBisrK0ycOBGJiYnqDq3ZkpKSIJFIcPfu3Xq3b9myBVFRUa0aE2m2tnNl3dra0EjFwoXOiI/Pw4QJNliw4EVIpZqb6xEREbWEgoICjBo1Cqampti4cSMGDRqE6upqJCQkICAgAFevXlV3iM+UiYmJukMgDaPBV6/qSSouXy7Czp2pSmVSqRYSE2dg4UJnJhREREQtwN/fHxKJBBcuXMDbb78NW1tbDBw4EMHBwTh37pxS3Tt37uCtt96CgYEBbGxscOTIEcW22tpa+Pn5oU+fPtDX14ednR22bNmi1P7RVKNNmzbBwsICnTp1QkBAAKqr//eMqQcPHmDx4sWwsrKCTCZDv3798MUXXyi2//jjjxg3bhw6dOiAbt26Yfr06bhz506Tz//x6U9jx45FUFAQFi1aBDMzM5ibm2PVqlVKbe7evYvZs2ejS5cuMDY2houLCzIzM5scA2kWzb2CbeU7P9XUyLF27Wk4OOxGQEAczp37VWk7pzoRERG1jJKSEsTHxyMgIACGhoZ1tpuamiq9Dw0NhaenJy5fvozx48fD29sbJSUlAAC5XI4ePXrgwIEDyMrKwsqVK7F06VLs379faR8nT55EXl4eTp48ib179yIqKkpp+tGMGTPw1VdfYevWrcjOzsauXbvQoUMHAA8v5l1cXDBs2DCkpqYiPj4eRUVF8PT0bNHPZe/evTA0NMT58+exYcMGfPTRRzh+/Lhi+5QpU3D79m0cO3YMaWlpsLe3x6uvvqr4LIieRHOnP0laL5+6evUOfHxiceHCfxRlGzak4NAhr1aLgYiIqCWFh59FePjZp9azt7fAkSNTlcrefPMrXLp066ltg4OdEBzspHJs165dgxAC/fv3b1T9mTNnYurUhzGGhYVh69atuHDhAtzd3aGjo4PQ0FBF3T59+uDs2bPYv3+/0kV/x44dsX37dkilUvTv3x8TJkxAYmIi5syZg9zcXOzfvx/Hjx+Hq6srAMDa2lrRdvv27Rg2bBjCwsIUZZGRkbCyskJubi5sbW1V/gzqM3jwYISEhAAAbGxssH37diQmJuK1115DcnIyLly4gNu3b0MmkwEANm3ahNjYWBw8eBBz585tkRio/dLcpKIV1lTI5QJbtpzD0qXfo7Ky5uFhtSRYtMgZq1aNfebHJyIielbKyh7gP//546n1rKzqzu3//ff7jWpbVvagSbGJR3c/aaTBgwcr/tvQ0BDGxsa4ffu2oiwiIgKRkZG4ceMGKioqUFVVhaFDhyrtY+DAgZBK/3dtYWFhgStXrgAAMjIyIJVKMWbMmHqPn5mZiZMnTypGLv4sLy+vRZOKP7OwsFCcZ2ZmJsrLy9GpUyelOhUVFcjLy2uR41P7prlJxTOe/nT9+n/h63sYp079oiizte2EvXsn4cUXezzTYxMRET1rxsYydO9u9NR6XboY1FvWmLbGxrImxWZjYwOJRNLoxdg6OjpK7yUSCeRyOQAgJiYGCxcuxObNm+Hk5AQjIyNs3LgR58+fb/Q+9PX1n3j88vJyTJw4EevXr6+zzcLColHn0BhPirG8vBwWFhZISkqq0+7x6WJE9WFS0cKEENi9Ow3vv/8d7t373wKt+fNHIizsVRgY6DyhNRER0fOhqVOTANSZDtXSzMzM4ObmhoiICAQFBdVZV3H37t1GXyinpKTA2dkZ/v7+ijJVf7kfNGgQ5HI5fvjhB8X0pz+zt7fH119/jd69e0NbWz2XZvb29igsLIS2tjZ69+6tlhjo+aa5C7Wf0fSnmho5du5MUyQUvXqZ4PvvZ+CTT9yZUBAREbWSiIgI1NbWwtHREV9//TV+/vlnZGdnY+vWrXByanwyZGNjg9TUVCQkJCA3NxcrVqzAxYsXVYqld+/e8PHxwaxZsxAbG4v8/HwkJSUpFnsHBASgpKQEU6dOxcWLF5GXl4eEhAT4+vqitrb2ifu+cuUKrly5goyMDGRkZDT5bk2urq5wcnLCpEmT8N1336GgoABnzpzBsmXLkJqa+vQdkMbjSEUL09GR4p//nAQHh8/g4zMEmze/DiOjpg3fEhERUdNYW1vj0qVLWLNmDd5//33cunULXbp0wfDhw7Fjx45G72fevHlIT0+Hl5cXJBIJpk6dCn9/fxw7dkyleHbs2IGlS5fC398fxcXF6NmzJ5YuXQoAsLS0REpKChYvXozXX38dDx48QK9eveDu7g4trSf//jt27Fil91KpFDU1NSrFBjycChUXF4dly5bB19cXv//+O8zNzfHyyy+jW7duKu+PNI9EqLqa6TlXVlYGExMT3N1mDZPA5i88Kioqx927lbCz66xUXlBwF717mzZ7/9Q2VFdXIy4uDuPHj68zJ5WoPuwz1BRtsd9UVlYiPz8fffr0gZ6enrrDocfI5XKUlZXB2Nj4qQkIaZYnfXeLi4vRuXNnlJaWwtjYuEWOp7m9rwVGKg4ezMLAgZ/C0/MgqqqUhyeZUBARERGRptDcpKIZaypKSiowbdrXmDLlAIqLK3D5chHWr09uweCIiIiIiJ4fXFOhoqNHczF79v9DYWG5omzy5AH4298cWioyIiIiIqLnCpOKRiotrURwcAIiIzMUZR076mH79vGYOvUFSCSSFg6QiIiIiOj5oLFJhVBh+lNi4nX4+h7GzZtlirLx423w2WcTYWn59If3EBERERG1ZxqbVDR2OcnNm6Vwd49GTc3DJ04aGeni44/dMGvWMI5OEBGRxtCwm0USPfda+zuruQu1Gzn9ycrKBEuWjAIAuLj0wZUr78LPz54JBRERaYRHt7a9f/++miMhIlU8+s621u2pNXekooGkorKyBtraWtDW/l++tWLFGNjadoK392BoaTGZICIizSGVSmFqaorbt28DAAwMDPjDWhsil8tRVVWFyspKPqeCADwcobh//z5u374NU1NTSKXP5oHPj9PcpKKeNRWpqb9hxoxvMH36YHz44WhFua6uFNOnD2nN6IiIiNoMc3NzAFAkFtR2CCFQUVEBfX19JnukxNTUVPHdbQ2am1T8aaSiqqoW//jHKYSFnUZtrUBISBImTLDF4MF8LD0REZFEIoGFhQW6du2K6upqdYdDf1JdXY1Tp07h5ZdfbjNPYSf109HRabURikfaRFIRERGBjRs3orCwEEOGDMG2bdvg6OjYYP0DBw5gxYoVKCgogI2NDdavX4/x48erdtD/SyquXCnCjBmxyMgoVGwaNKgbdHQ4hEhERPRnUqm01S9U6MmkUilqamqgp6fHpILUSu1Xzvv27UNwcDBCQkJw6dIlDBkyBG5ubg0OsZ45cwZTp06Fn58f0tPTMWnSJEyaNAk//vijSsetEVpYty4Zw4fvViQU2tpaWLVqDM6d88OAAV2afW5ERERERJpA7UlFeHg45syZA19fX/zlL3/Bzp07YWBggMjIyHrrb9myBe7u7vjggw8wYMAArF69Gvb29ti+fbtKx3VfPQAffpiI6uqHt4odOLALzp+fjZCQsdDR4a8wRERERESNpdakoqqqCmlpaXB1dVWUaWlpwdXVFWfPnq23zdmzZ5XqA4Cbm1uD9RuSdt3w/44nweLFo5CWNhf29hYqngEREREREal1TcWdO3dQW1uLbt2UF0R369YNV69erbdNYWFhvfULCwvrrf/gwQM8ePBA8b60tPTRFlhbd8T27e5wdOyO8vJSlJc3/Vyofauursb9+/dRXFzMOavUKOwz1BTsN6Qq9hlqipKSEgAt+4C8NrFQ+1lau3YtQkND69nyMa5fB8aPX9zqMRERERERqVtxcTFMTExaZF9qTSo6d+4MqVSKoqIipfKioqIG76trbm6uUv0PP/wQwcHBivd3795Fr169cOPGjRb7EKn9Kysrg5WVFW7evAljY2N1h0PPAfYZagr2G1IV+ww1RWlpKXr27AkzM7MW26dakwpdXV0MHz4ciYmJmDRpEoCHT4ZMTExEYGBgvW2cnJyQmJiIv//974qy48ePw8nJqd76MpkMMpmsTrmJiQm/fKQyY2Nj9htSCfsMNQX7DamKfYaaoiWfwq726U/BwcHw8fGBg4MDHB0d8cknn+DevXvw9fUFAMyYMQPdu3fH2rVrAQDz58/HmDFjsHnzZkyYMAExMTFITU3F7t271XkaREREREQaS+1JhZeXF37//XesXLkShYWFGDp0KOLj4xWLsW/cuKGURTk7O+Pf//43li9fjqVLl8LGxgaxsbF44YUX1HUKREREREQaTe1JBQAEBgY2ON0pKSmpTtmUKVMwZcqUJh1LJpMhJCSk3ilRRA1hvyFVsc9QU7DfkKrYZ6gpnkW/kYiWvJcUERERERFpHLU/UZuIiIiIiJ5vTCqIiIiIiKhZmFQQEREREVGztMukIiIiAr1794aenh5GjhyJCxcuPLH+gQMH0L9/f+jp6WHQoEGIi4trpUipLVGl33z22WcYPXo0OnbsiI4dO8LV1fWp/YzaH1X/1jwSExMDiUSieD4PaRZV+83du3cREBAACwsLyGQy2Nra8t8pDaNqn/nkk09gZ2cHfX19WFlZYcGCBaisrGylaKktOHXqFCZOnAhLS0tIJBLExsY+tU1SUhLs7e0hk8nQr18/REVFqXZQ0c7ExMQIXV1dERkZKX766ScxZ84cYWpqKoqKiuqtn5KSIqRSqdiwYYPIysoSy5cvFzo6OuLKlSutHDmpk6r9Ztq0aSIiIkKkp6eL7OxsMXPmTGFiYiJ+/fXXVo6c1EXVPvNIfn6+6N69uxg9erTw8PBonWCpzVC13zx48EA4ODiI8ePHi+TkZJGfny+SkpJERkZGK0dO6qJqn4mOjhYymUxER0eL/Px8kZCQICwsLMSCBQtaOXJSp7i4OLFs2TJx6NAhAUB88803T6x//fp1YWBgIIKDg0VWVpbYtm2bkEqlIj4+vtHHbHdJhaOjowgICFC8r62tFZaWlmLt2rX11vf09BQTJkxQKhs5cqSYN2/eM42T2hZV+83jampqhJGRkdi7d++zCpHamKb0mZqaGuHs7Cw+//xz4ePjw6RCA6nab3bs2CGsra1FVVVVa4VIbYyqfSYgIEC4uLgolQUHB4tRo0Y90zip7WpMUrFo0SIxcOBApTIvLy/h5ubW6OO0q+lPVVVVSEtLg6urq6JMS0sLrq6uOHv2bL1tzp49q1QfANzc3BqsT+1PU/rN4+7fv4/q6mqYmZk9qzCpDWlqn/noo4/QtWtX+Pn5tUaY1MY0pd8cOXIETk5OCAgIQLdu3fDCCy8gLCwMtbW1rRU2qVFT+oyzszPS0tIUU6SuX7+OuLg4jB8/vlVipudTS1wPt4mH37WUO3fuoLa2VvE07ke6deuGq1ev1tumsLCw3vqFhYXPLE5qW5rSbx63ePFiWFpa1vlCUvvUlD6TnJyML774AhkZGa0QIbVFTek3169fx/fffw9vb2/ExcXh2rVr8Pf3R3V1NUJCQlojbFKjpvSZadOm4c6dO3jppZcghEBNTQ3+9re/YenSpa0RMj2nGroeLisrQ0VFBfT19Z+6j3Y1UkGkDuvWrUNMTAy++eYb6OnpqTscaoP++OMPTJ8+HZ999hk6d+6s7nDoOSKXy9G1a1fs3r0bw4cPh5eXF5YtW4adO3eqOzRqo5KSkhAWFoZPP/0Uly5dwqFDh3D06FGsXr1a3aFRO9euRio6d+4MqVSKoqIipfKioiKYm5vX28bc3Fyl+tT+NKXfPLJp0yasW7cOJ06cwODBg59lmNSGqNpn8vLyUFBQgIkTJyrK5HI5AEBbWxs5OTno27fvsw2a1K4pf2ssLCygo6MDqVSqKBswYAAKCwtRVVUFXV3dZxozqVdT+syKFSswffp0zJ49GwAwaNAg3Lt3D3PnzsWyZcugpcXfk6muhq6HjY2NGzVKAbSzkQpdXV0MHz4ciYmJijK5XI7ExEQ4OTnV28bJyUmpPgAcP368wfrU/jSl3wDAhg0bsHr1asTHx8PBwaE1QqU2QtU+079/f1y5cgUZGRmK15tvvolXXnkFGRkZsLKyas3wSU2a8rdm1KhRuHbtmiIJBYDc3FxYWFgwodAATekz9+/fr5M4PEpKH67ZJaqrRa6HVV9D3rbFxMQImUwmoqKiRFZWlpg7d64wNTUVhYWFQgghpk+fLpYsWaKon5KSIrS1tcWmTZtEdna2CAkJ4S1lNZCq/WbdunVCV1dXHDx4UNy6dUvx+uOPP9R1CtTKVO0zj+PdnzSTqv3mxo0bwsjISAQGBoqcnBzx7bffiq5du4p//OMf6joFamWq9pmQkBBhZGQkvvrqK3H9+nXx3Xffib59+wpPT091nQKpwR9//CHS09NFenq6ACDCw8NFenq6+OWXX4QQQixZskRMnz5dUf/RLWU/+OADkZ2dLSIiInhLWSGE2LZtm+jZs6fQ1dUVjo6O4ty5c4ptY8aMET4+Pkr19+/fL2xtbYWurq4YOHCgOHr0aCtHTG2BKv2mV69eAkCdV0hISOsHTmqj6t+aP2NSoblU7TdnzpwRI0eOFDKZTFhbW4s1a9aImpqaVo6a1EmVPlNdXS1WrVol+vbtK/T09ISVlZXw9/cX//3vf1s/cFKbkydP1nud8qiv+Pj4iDFjxtRpM3ToUKGrqyusra3Fnj17VDqmRAiOhRERERERUdO1qzUVRERERETU+phUEBERERFRszCpICIiIiKiZmFSQUREREREzcKkgoiIiIiImoVJBRERERERNQuTCiIiIiIiahYmFURERERE1CxMKoiInkNRUVEwNTVVdxhNJpFIEBsb+8Q6M2fOxKRJk1olHiIiah4mFUREajJz5kxIJJI6r2vXrqk7NERFRSni0dLSQo8ePeDr64vbt2+3yP5v3bqFcePGAQAKCgogkUiQkZGhVGfLli2IiopqkeM1ZNWqVYrzlEqlsLKywty5c1FSUqLSfpgAEZGm01Z3AEREmszd3R179uxRKuvSpYuaolFmbGyMnJwcyOVyZGZmwtfXF7/99hsSEhKavW9zc/On1jExMWn2cRpj4MCBOHHiBGpra5GdnY1Zs2ahtLQU+/bta5XjExG1BxypICJSI5lMBnNzc6WXVCpFeHg4Bg0aBENDQ1hZWcHf3x/l5eUN7iczMxOvvPIKjIyMYGxsjOHDhyM1NVWxPTk5GaNHj4a+vj6srKwQFBSEe/fuPTE2iUQCc3NzWFpaYty4cQgKCsKJEydQUVEBuVyOjz76CD169IBMJsPQoUMRHx+vaFtVVYXAwEBYWFhAT08PvXr1wtq1a5X2/Wj6U58+fQAAw4YNg0QiwdixYwEo//q/e/duWFpaQi6XK8Xo4eGBWbNmKd4fPnwY9vb20NPTg7W1NUJDQ1FTU/PE89TW1oa5uTm6d+8OV1dXTJkyBcePH1dsr62thZ+fH/r06QN9fX3Y2dlhy5Ytiu2rVq3C3r17cfjwYcWoR1JSEgDg5s2b8PT0hKmpKczMzODh4YGCgoInxkNE9DxiUkFE1AZpaWlh69at+Omnn7B37158//33WLRoUYP1vb290aNHD1y8eBFpaWlYsmQJdHR0AAB5eXlwd3fH22+/jcuXL2Pfvn1ITk5GYGCgSjHp6+tDLpejpqYGW7ZswebNm7Fp0yZcvnwZbm5uePPNN/Hzzz8DALZu3YojR45g//79yMnJQXR0NHr37l3vfi9cuAAAOHHiBG7duoVDhw7VqTNlyhQUFxfj5MmTirKSkhLEx8fD29sbAHD69GnMmDED8+fPR1ZWFnbt2oWoqCisWbOm0edYUFCAhIQE6OrqKsrkcjl69OiBAwcOICsrCytXrsTSpUuxf/9+AMDChQvh6ekJd3d33Lp1C7du3YKzszOqq6vh5uYGIyMjnD59GikpKejQoQPc3d1RVVXV6JiIiJ4LgoiI1MLHx0dIpVJhaGioeL3zzjv11j1w4IDo1KmT4v2ePXuEiYmJ4r2RkZGIioqqt62fn5+YO3euUtnp06eFlpaWqKioqLfN4/vPzc0Vtra2wsHBQQghhKWlpVizZo1SmxEjRgh/f38hhBDvvfeecHFxEXK5vN79AxDffPONEEKI/Px8AUCkp6cr1fHx8REeHh6K9x4eHmLWrFmK97t27RKWlpaitrZWCCHEq6++KsLCwpT28eWXXwoLC4t6YxBCiJCQEKGlpSUMDQ2Fnp6eACAAiPDw8AbbCCFEQECAePvttxuM9dGx7ezslD6DBw8eCH19fZGQkPDE/RMRPW+4poKISI1eeeUV7NixQ/He0NAQwMNf7deuXYurV6+irKwMNTU1qKysxP3792FgYFBnP8HBwZg9eza+/PJLxRSevn37Ang4Nery5cuIjo5W1BdCQC6XIz8/HwMGDKg3ttLSUnTo0AFyuRyVlZV46aWX8Pnnn6OsrAy//fYbRo0apVR/1KhRyMzMBPBw6tJrr70GOzs7uLu744033sDrr7/erM/K29sbc+bMwaeffgqZTIbo6Gj89a9/hZaWluI8U1JSlEYmamtrn/i5AYCdnR2OHDmCyspK/Otf/0JGRgbee+89pToRERGIjIzEjRs3UFFRgaqqKgwdOvSJ8WZmZuLatWswMjJSKq+srEReXl4TPgEioraLSQURkRoZGhqiX79+SmUFBQV444038O6772LNmjUwMzNDcnIy/Pz8UFVVVe/F8apVqzBt2jQcPXoUx44dQ0hICGJiYvDWW2+hvLwc8+bNQ1BQUJ12PXv2bDA2IyMjXLp0CVpaWrCwsIC+vj4AoKys7KnnZW9vj/z8fBw7dgwnTpyAp6cnXF1dcfDgwae2bcjEiRMhhMDRo0cxYsQInD59Gh9//LFie3l5OUJDQzF58uQ6bfX09Brcr66uruL/wbp16zBhwgSEhoZi9erVAICYmBgsXLgQmzdvhpOTE4yMjLBx40acP3/+ifGWl5dj+PDhSsncI21lMT4RUUthUkFE1MakpaVBLpdj8+bNil/hH83ffxJbW1vY2tpiwYIFmDp1Kvbs2YO33noL9vb2yMrKqpO8PI2Wlla9bYyNjWFpaYmUlBSMGTNGUZ6SkgJHR0elel5eXvDy8sI777wDd3d3lJSUwMzMTGl/j9Yv1NbWPjEePT09TJ48GdHR0bh27Rrs7Oxgb2+v2G5vb4+cnByVz/Nxy5cvh4uLC959913FeTo7O8Pf319R5/GRBl1d3Trx29vbY9++fejatSuMjY2bFRMRUVvHhdpERG1Mv379UF1djW3btuH69ev48ssvsXPnzgbrV1RUIDAwEElJSfjll1+QkpKCixcvKqY1LV68GGfOnEFgYCAyMjLw888/4/Dhwyov1P6zDz74AOvXr8e+ffuQk5ODJUuWICMjA/PnzwcAhIeH46uvvsLVq1eRm5uLAwcOwNzcvN4H9nXt2hX6+vqIj49HUVERSktLGzyut7c3jh49isjISMUC7UdWrlyJf/7znwgNDcVPP/2E7OxsxMTEYPny5Sqdm5OTEwYPHoywsDAAgI2NDVJTU5GQkIDc3FysWLECFy9eVGrTu3dvXL58GTk5Obhz5w6qq6vh7e2Nzp07w8PDA6dPn0Z+fj6SkpIQFBSEX3/9VaWYiIjaOiYVRERtzJAhQxAeHo7169fjhRdeQHR0tNLtWB8nlUpRXFyMGTNmwNbWFp6enhg3bhxCQ0MBAIMHD8YPP/yA3NxcjB49GsOGDcPKlSthaWnZ5BiDgoIQHByM999/H4MGDUJ8fDyOHDkCGxsbAA+nTm3YsAEODg4YMWIECgoKEBcXpxh5+TNtbW1s3boVu3btgqWlJTw8PBo8rouLC8zMzJCTk4Np06YpbXNzc8O3336L7777DiNGjMCLL76Ijz/+GL169VL5/BYsWIDPP/8cN2/exLx58zB58mR4eXlh5MiRKC4uVhq1AIA5c+bAzs4ODg4O6NKlC1JSUmBgYIBTp06hZ8+emDx5MgYMGAA/Pz9UVlZy5IKI2h2JEEKoOwgiIiIiInp+caSCiIiIiIiahUkFERERERE1C5MKIiIiIiJqFiYVRERERETULEwqiIiIiIioWZhUEBERERFRszCpICIiIiKiZmFSQUREREREzcKkgoiIiIiImoVJBRERERERNQuTCiIiIiIiahYmFURERERE1Cz/Hwi64ol6HHkuAAAAAElFTkSuQmCC",
            "text/plain": [
              "<Figure size 800x600 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "plot_roc_curve(gnb, X_test, y_test, \"Gaussian Naive Bayes\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "l-z1dKNkSAP8"
      },
      "source": [
        "# SUPPORT VECTOR MACHINE"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 106,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 472
        },
        "id": "YKETBM8YSAP8",
        "outputId": "a77d78e5-f47d-4482-8412-41ea5e9f6616"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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tBCsrK0Gr1YrTcv/9+WVlZQn9+/cX7O3tBQDicxZ/1ps2bSpxv3//d1iyZIkAQNi8ebNeuevXrwtqtVro2rXrU+MnIkFQCIKRo5qIiIhIdjiGgYiIiAxiwkBEREQGMWEgIiIig5gwEBERkUFMGIiIiMggJgxERERk0Au9cFNRURFu3boFOzs7ky4fS0REz4YgCLh//z60Wq1R74kxVk5ODvLy8iTXo1KpYGlpaYKIXjwvdMJw69Ytk63tT0REFefGjRuoWbNmudSdk5MDK7sqQMEDyXU5OzsjOTlZlknDC50wFL+6V1U/EAozVQVHQ1Q+rh/6vKJDICo393U61HFzKfEqdlPKy8sDCh7Aon4gIOW7ojAPKb99i7y8PCYML5ribgiFmYoJA720TPXCK6Ln2TPpVja3lPRdISjkPezvhU4YiIiISk0BQEpiIvOhckwYiIhIHhTKh5uU62VM3k9PREREpcIWBiIikgeFQmKXhLz7JJgwEBGRPLBLQhJ5Pz0RERGVClsYiIhIHtglIQkTBiIikgmJXRIyb5SX99MTERFRqbCFgYiI5IFdEpIwYSAiInngLAlJ5P30REREVCpsYSAiInlgl4QkTBiIiEge2CUhCRMGIiKSB7YwSCLvdImIiIhKhS0MREQkD+ySkIQJAxERyYNCITFhYJcEERER0VOxhYGIiORBqXi4SblexpgwEBGRPHAMgyTyfnoiIiIqFSYMREQkD8XrMEjZjBATE4Nu3bpBq9VCoVAgKiqqRJkLFy6ge/fu0Gg0sLGxQbNmzXD9+nXxfE5ODkaMGIEqVarA1tYWvXv3Rmpqql4d169fh5+fH6ytreHo6IgJEyagoKBAr8yhQ4fQpEkTWFhYoE6dOoiIiDDqWQAmDEREJBfFXRJSNiNkZ2fD09MTK1aseOz5K1euoHXr1nB3d8ehQ4dw9uxZTJ06FZaWlmKZ4OBg7NixA5s2bcLhw4dx69Yt9OrVSzxfWFgIPz8/5OXlITY2Ft9++y0iIiIQGhoqlklOToafnx/at2+PhIQEjB07FkOGDMG+ffuM+/gEQRCMuuI5otPpoNFoYOExFAozVUWHQ1Qu7p1YXtEhEJUbnU4HpyoaZGZmQq1Wl9s9NBoNLNpNg8Lc0vAFTyAU5CD38IwyxapQKLB161b4+/uLx/r27YtKlSph7dq1j70mMzMT1apVQ2RkJPr06QMAuHjxIurVq4e4uDi0aNECe/bswdtvv41bt27ByckJABAeHo5Jkybhzp07UKlUmDRpEnbt2oXExES9e2dkZGDv3r2lfga2MBARkTyYqEtCp9Ppbbm5uUaHUlRUhF27duH111+Hr68vHB0d0bx5c71ui/j4eOTn58PHx0c85u7ujlq1aiEuLg4AEBcXBw8PDzFZAABfX1/odDqcP39eLPNoHcVliusoLSYMREQkDybqknBxcYFGoxG3efPmGR1KWloasrKy8Omnn6Jz587Yv38/evbsiV69euHw4cMAgJSUFKhUKtjb2+td6+TkhJSUFLHMo8lC8fnic08ro9Pp8Pfff5c6Zk6rJCIieTDRy6du3Lih1yVhYWFhdFVFRUUAgB49eiA4OBgA0KhRI8TGxiI8PBzt2rUre5zlhC0MRERERlCr1XpbWRKGqlWrwtzcHPXr19c7Xq9ePXGWhLOzM/Ly8pCRkaFXJjU1Fc7OzmKZf8+aKN43VEatVsPKyqrUMTNhICIieXjGsySeRqVSoVmzZkhKStI7funSJbi6ugIAvLy8UKlSJRw4cEA8n5SUhOvXr8Pb2xsA4O3tjXPnziEtLU0sEx0dDbVaLSYj3t7eenUUlymuo7TYJUFERPJgoi6J0srKysLly5fF/eTkZCQkJMDBwQG1atXChAkT8O6776Jt27Zo37499u7dix07duDQoUMAAI1Gg6CgIISEhMDBwQFqtRqjRo2Ct7c3WrRoAQDo1KkT6tevj4EDByIsLAwpKSmYMmUKRowYIbZ8DB8+HMuXL8fEiRMxePBgHDx4EBs3bsSuXbuMeh4mDEREROXg5MmTaN++vbgfEhICAAgMDERERAR69uyJ8PBwzJs3D6NHj0bdunWxefNmtG7dWrxm0aJFUCqV6N27N3Jzc+Hr64uVK1eK583MzLBz5058+OGH8Pb2ho2NDQIDAzFz5kyxjJubG3bt2oXg4GAsWbIENWvWxFdffQVfX1+jnofrMBA957gOA73Mnuk6DD6fQlFJwjoM+TnI/Wlyucb6PGMLAxERycMz7pJ42XDQIxERERnEFgYiIpIHhULi663l3cLAhIGIiORB6tRIE06rfBHJ++mJiIioVNjCQERE8sBBj5IwYSAiInlgl4QkTBiIiEge2MIgibzTJSIiIioVtjAQEZE8sEtCEiYMREQkD+ySkETe6RIRERGVClsYiIhIFhQKBRRsYSgzJgxERCQLTBikYZcEERERGcQWBiIikgfF/zYp18sYEwYiIpIFdklIwy4JIiIiMogtDEREJAtsYZCGCQMREckCEwZpmDAQEZEsMGGQhmMYiIiIyCC2MBARkTxwWqUkTBiIiEgW2CUhDbskiIiIyCC2MBARkSw8fLu1lBYG08XyImLCQEREsqCAxC4JmWcM7JIgIiIig9jCQEREssBBj9IwYSAiInngtEpJ2CVBREREBrGFgYiI5EFil4Qg8y4JtjAQEZEsFI9hkLIZIyYmBt26dYNWq4VCoUBUVNQTyw4fPhwKhQKLFy/WO56eno6AgACo1WrY29sjKCgIWVlZemXOnj2LNm3awNLSEi4uLggLCytR/6ZNm+Du7g5LS0t4eHhg9+7dRj0LwISBiIhk4lknDNnZ2fD09MSKFSueWm7r1q04duwYtFptiXMBAQE4f/48oqOjsXPnTsTExGDYsGHieZ1Oh06dOsHV1RXx8fGYP38+pk+fjtWrV4tlYmNj0a9fPwQFBeH06dPw9/eHv78/EhMTjXoedkkQERGVgy5duqBLly5PLfPnn39i1KhR2LdvH/z8/PTOXbhwAXv37sWJEyfQtGlTAMCyZcvQtWtXfP7559BqtVi3bh3y8vLwzTffQKVSoUGDBkhISMDChQvFxGLJkiXo3LkzJkyYAACYNWsWoqOjsXz5coSHh5f6edjCQERE8qAwwYaH/6p/dMvNzS1TOEVFRRg4cCAmTJiABg0alDgfFxcHe3t7MVkAAB8fHyiVShw/flws07ZtW6hUKrGMr68vkpKScO/ePbGMj4+PXt2+vr6Ii4szKl4mDEREJAum6pJwcXGBRqMRt3nz5pUpns8++wzm5uYYPXr0Y8+npKTA0dFR75i5uTkcHByQkpIilnFyctIrU7xvqEzx+dJilwQREZERbty4AbVaLe5bWFgYXUd8fDyWLFmCU6dOSVyu+tlhCwMREcmCqVoY1Gq13laWhOHIkSNIS0tDrVq1YG5uDnNzc1y7dg3jxo1D7dq1AQDOzs5IS0vTu66goADp6elwdnYWy6SmpuqVKd43VKb4fGkxYSAiIll41rMknmbgwIE4e/YsEhISxE2r1WLChAnYt28fAMDb2xsZGRmIj48Xrzt48CCKiorQvHlzsUxMTAzy8/PFMtHR0ahbty4qV64sljlw4IDe/aOjo+Ht7W1UzOySICIiKgdZWVm4fPmyuJ+cnIyEhAQ4ODigVq1aqFKlil75SpUqwdnZGXXr1gUA1KtXD507d8bQoUMRHh6O/Px8jBw5En379hWnYPbv3x8zZsxAUFAQJk2ahMTERCxZsgSLFi0S6x0zZgzatWuHBQsWwM/PD+vXr8fJkyf1pl6WBlsYiIhIFp51C8PJkyfRuHFjNG7cGAAQEhKCxo0bIzQ0tNR1rFu3Du7u7ujQoQO6du2K1q1b633RazQa7N+/H8nJyfDy8sK4ceMQGhqqt1ZDy5YtERkZidWrV8PT0xM//vgjoqKi0LBhQ6OeRyEIgmDUFc8RnU4HjUYDC4+hUJipDF9A9AK6d2J5RYdAVG50Oh2cqmiQmZmpN5DQ1PfQaDRwGrQWSpV1mespynuA1DUDyzXW5xlbGIiIiMggjmEgIiJZkDpw8UWZ/lhemDAQEZEsMGGQhgkDERHJAhMGaTiGgYiIiAxiCwMREcnDIy+QKvP1MsaEgYiIZIFdEtKwS4KIiIgMYgvDS65l41cxaqAPPN1roXo1DQLGr8buw2fF809aFCh0yVYs+/7h2uORCz6Ax+s1ULWyHTLuP8DhX5Mwfdk2pNzNBAC4VHfA2e0zS9TRcdDnOJl4FQCwI3wMWnu9VqLM/l8S8W5wuNTHJHqqo6cuY9nan3Dm4nWk3NXh+/lD4feWp3i+crORj71uxmh/jB7oAwB4o3sobtxO1zsfOqI7gt/vVH6Bk0mxhUGa5yJhWLFiBebPn4+UlBR4enpi2bJlePPNNys6rJeCtZUFEi/9ie+3x+H7+cNKnK/b+WO9fZ+WDbBsSn9s/zlBPHbk5CUsXLMPqXczUd3RHrPG9MS3nwXBN2ih3rU9PlqKi3/cFvfTM7LFnwdO/BKqSmbivoPGBkfWfYyoA6elPiKRQQ/+zkXD12tgQHdvDJz4ZYnzF/fM1dv/KfY8Rs2ORPf2jfSO/98HfnjPv5W4b2tj/FsKqeIoIDFhkPkghgpPGDZs2ICQkBCEh4ejefPmWLx4MXx9fZGUlARHR8eKDu+F91Psb/gp9rcnnk/7677efte2HjgS/zuu/fmXeGzVDz+LP99IuYfF30bj+/lDYW6mREFhkXguPTO7RH3FMnQP9PZ7dfLCg5w8bPuJCQOVv46tGqBjqwZPPO9UVX+Z390x59DG6zXUrllV77ittWWJskRyUeFjGBYuXIihQ4di0KBBqF+/PsLDw2FtbY1vvvmmokOTnWoOdujUuiG+3xb3xDL2amv06dwUv55N1ksWAOCHBR/g0r552PNlMLq09XjqvQZ2b4kt0afwICfPJLETmUraXzrs/yURA3qUfPXv4m/34xWfiWgb8CmWrv0JBQWFFRAhldXz9HrrF1GFtjDk5eUhPj4eH3/8T7O4UqmEj48P4uKe/KVF5aOfX3NkZedgxyPdEcWmj+yBIe+0hY2VBX49m4y+If+MO8h+kItPFm3B8TNXUCQI6P6fRvh+/lAMmPAl9sScK1FXk/quqF9Hi1Gz1pXn4xCVyQ+7jsPWxhLd/tUd8cG77eDp7gJ7tQ1+PfsHZq7YjtS7mZgT3LtiAiXjcVqlJBWaMNy9exeFhYVwcnLSO+7k5ISLFy+WKJ+bm4vc3FxxX6fTlXuMchLQvQU27T2J3LyCEueWrv0Ja7fHwcXZAZOGdkH49IHiYMX0zGysjDwolj3923U4V9Vg1IAOj00YBvbwxvnf/8Sp366V38MQldG67cfw385NYWlRSe/4iIAO4s8NX6sBVSVzBM/9AaEjusNCVenf1RC9dCq8S8IY8+bNg0ajETcXF5eKDuml4d3oVbxe2xlrt8U+9nx6ZjauXE/DoV8vIuiTNejUuiGaebg9sb7489fg5lKtxHFrSxV6dfLC2u1sQaLnT+zpy/j9WioG9mhpsKxXg9ooKCzC9VvpBsvS84FdEtJUaMJQtWpVmJmZITU1Ve94amoqnJ2dS5T/+OOPkZmZKW43btx4VqG+9Ab08Mbp364j8fc/DZZV/u//NKpKT26gavh6DaTeLdkC1MOnMVSVzLFxz4myB0tUTr7fFodG9Vzg8XpNg2XPXboJpVKBag52zyAyMgUmDNJUaJeESqWCl5cXDhw4AH9/fwBAUVERDhw4gJEjS86LtrCwgIUFpzEZw8ZKpfcvfVdtFTR8vQYyMh/gZuo9AICdjSV6dGiMqYu3lrjeq4ErmtR3RdyZK8jUPUDtmtXwyXA//HHjDk6cSwYA9PVrjvz8ApxNugkA6NbeEwO6eWP0nMgS9Q3s7o3dh8/iXmZ2iXNE5SXrQS6Sb9wR96/d+gvnkm7CXmMNF2cHAIAu629sO3Aas8b2LHH9r2f/QHziNbRu+hrsrC3x67lkfLJoM97p0gz2autn9hwkjULxcJNyvZxV+LTKkJAQBAYGomnTpnjzzTexePFiZGdnY9CgQRUd2kuhUT1X7PxijLg/N+ThAK3InccwYsb3AB5OcVQoFNi872SJ6//Oycfb7T0xeZgfrK1USL2biQNxF/D5N98gL/+fsQ7jgzrDpboDCguLcOlqKgb/3zfYfjBBr646ro7wblwHPUc8frEoovKScOEaug1fKu5/smgLgIcDfVdOHwgA2LI/HoIgoLdv0xLXW6gqYUt0PD79cjfy8gvgqq2CD/u1x4iA/zybByB6DigEQRAqOojly5eLCzc1atQIS5cuRfPmzQ1ep9PpoNFoYOExFAoz1TOIlOjZe9JqnEQvA51OB6cqGmRmZkKtLp81Loq/K14Z9SOUFjZlrqcoNxt/LOtTrrE+zyq8hQEARo4c+dguCCIiIpOR2CUh92mVL9QsCSIiIqoYz0ULAxERUXnjy6ekYcJARESywFkS0rBLgoiIiAxiCwMREcmCUqmAUln2ZgJBwrUvAyYMREQkC+ySkIZdEkRERGQQWxiIiEgWOEtCGiYMREQkC+ySkIYJAxERyQJbGKThGAYiIiIyiC0MREQkC2xhkIYtDEREJAvFYxikbMaIiYlBt27doNVqoVAoEBUVJZ7Lz8/HpEmT4OHhARsbG2i1Wrz33nu4deuWXh3p6ekICAiAWq2Gvb09goKCkJWVpVfm7NmzaNOmDSwtLeHi4oKwsLASsWzatAnu7u6wtLSEh4cHdu/ebdzDgAkDERFRucjOzoanpydWrFhR4tyDBw9w6tQpTJ06FadOncKWLVuQlJSE7t2765ULCAjA+fPnER0djZ07dyImJgbDhg0Tz+t0OnTq1Amurq6Ij4/H/PnzMX36dKxevVosExsbi379+iEoKAinT5+Gv78//P39kZiYaNTzKARBEIz8DJ4bxe84t/AYCoWZqqLDISoX904sr+gQiMqNTqeDUxUNMjMzoVary+0eGo0GHpO3w8zSpsz1FOZk49yn3csUq0KhwNatW+Hv7//EMidOnMCbb76Ja9euoVatWrhw4QLq16+PEydOoGnTpgCAvXv3omvXrrh58ya0Wi1WrVqFTz75BCkpKVCpHn4PTp48GVFRUbh48SIA4N1330V2djZ27twp3qtFixZo1KgRwsPDS/0MbGEgIiJZMFWXhE6n09tyc3NNEl9mZiYUCgXs7e0BAHFxcbC3txeTBQDw8fGBUqnE8ePHxTJt27YVkwUA8PX1RVJSEu7duyeW8fHx0buXr68v4uLijIqPCQMREZERXFxcoNFoxG3evHmS68zJycGkSZPQr18/sfUiJSUFjo6OeuXMzc3h4OCAlJQUsYyTk5NemeJ9Q2WKz5cWZ0kQEZEsmGqWxI0bN/S6JCwsLCTFlZ+fj3feeQeCIGDVqlWS6ipPTBiIiEgWTLXSo1qtNtl4i+Jk4dq1azh48KBevc7OzkhLS9MrX1BQgPT0dDg7O4tlUlNT9coU7xsqU3y+tNglQUREVAGKk4Xff/8dP/30E6pUqaJ33tvbGxkZGYiPjxePHTx4EEVFRWjevLlYJiYmBvn5+WKZ6Oho1K1bF5UrVxbLHDhwQK/u6OhoeHt7GxUvEwYiIpKF4i4JKZsxsrKykJCQgISEBABAcnIyEhIScP36deTn56NPnz44efIk1q1bh8LCQqSkpCAlJQV5eXkAgHr16qFz584YOnQofv31Vxw9ehQjR45E3759odVqAQD9+/eHSqVCUFAQzp8/jw0bNmDJkiUICQkR4xgzZgz27t2LBQsW4OLFi5g+fTpOnjyJkSNHGvU8TBiIiEgWnvXCTSdPnkTjxo3RuHFjAEBISAgaN26M0NBQ/Pnnn9i+fTtu3ryJRo0aoXr16uIWGxsr1rFu3Tq4u7ujQ4cO6Nq1K1q3bq23xoJGo8H+/fuRnJwMLy8vjBs3DqGhoXprNbRs2RKRkZFYvXo1PD098eOPPyIqKgoNGzY07vPjOgxEzzeuw0Avs2e5DoNX6C7J6zDEz/Qr11ifZ2xhICIiIoM4S4KIiORB4iwJyPvdU0wYiIhIHvi2SmnYJUFEREQGsYWBiIhkwVQLN8kVEwYiIpIFdklIwy4JIiIiMogtDEREJAvskpCGCQMREckCuySkYZcEERERGcQWBiIikgW2MEjDhIGIiGSBYxikYcJARESywBYGaTiGgYiIiAxiCwMREckCuySkYcJARESywC4JadglQURERAaxhYGIiGRBAYldEiaL5MXEhIGIiGRBqVBAKSFjkHLty4BdEkRERGQQWxiIiEgWOEtCGiYMREQkC5wlIQ0TBiIikgWl4uEm5Xo54xgGIiIiMogtDEREJA8Kid0KMm9hYMJARESywEGP0rBLgoiIiAxiCwMREcmC4n9/pFwvZ0wYiIhIFjhLQhp2SRAREZFBbGEgIiJZ4MJN0pQqYdi+fXupK+zevXuZgyEiIiovnCUhTam6JPz9/Uu19ezZs7zjJSIieiHExMSgW7du0Gq1UCgUiIqK0jsvCAJCQ0NRvXp1WFlZwcfHB7///rtemfT0dAQEBECtVsPe3h5BQUHIysrSK3P27Fm0adMGlpaWcHFxQVhYWIlYNm3aBHd3d1haWsLDwwO7d+82+nlKlTAUFRWVaissLDQ6ACIiomeh+PXWUjZjZGdnw9PTEytWrHjs+bCwMCxduhTh4eE4fvw4bGxs4Ovri5ycHLFMQEAAzp8/j+joaOzcuRMxMTEYNmyYeF6n06FTp05wdXVFfHw85s+fj+nTp2P16tVimdjYWPTr1w9BQUE4ffq0+I/8xMREo55HIQiCYNQVj8jJyYGlpWVZL5dMp9NBo9HAwmMoFGaqCouDqDzdO7G8okMgKjc6nQ5OVTTIzMyEWq0ut3toNBp0W34Ilaxsy1xP/t9Z2DHyrTLFqlAosHXrVvj7+wN42Lqg1Woxbtw4jB8/HgCQmZkJJycnREREoG/fvrhw4QLq16+PEydOoGnTpgCAvXv3omvXrrh58ya0Wi1WrVqFTz75BCkpKVCpHn4PTp48GVFRUbh48SIA4N1330V2djZ27twpxtOiRQs0atQI4eHhpX4Go2dJFBYWYtasWahRowZsbW3xxx9/AACmTp2Kr7/+2tjqiIiInoniQY9SNuBhAvLolpuba3QsycnJSElJgY+Pj3hMo9GgefPmiIuLAwDExcXB3t5eTBYAwMfHB0qlEsePHxfLtG3bVkwWAMDX1xdJSUm4d++eWObR+xSXKb5PaRmdMMyZMwcREREICwvTC7Bhw4b46quvjK2OiIjoheLi4gKNRiNu8+bNM7qOlJQUAICTk5PecScnJ/FcSkoKHB0d9c6bm5vDwcFBr8zj6nj0Hk8qU3y+tIyeVvndd99h9erV6NChA4YPHy4e9/T0FJs/iIiInjemmiVx48YNvS4JCwsLiZG9GIxOGP7880/UqVOnxPGioiLk5+ebJCgiIiJTK8vAxX9fDwBqtVryeAtnZ2cAQGpqKqpXry4eT01NRaNGjcQyaWlpetcVFBQgPT1dvN7Z2Rmpqal6ZYr3DZUpPl9aRndJ1K9fH0eOHClx/Mcff0Tjxo2NrY6IiEh23Nzc4OzsjAMHDojHdDodjh8/Dm9vbwCAt7c3MjIyEB8fL5Y5ePAgioqK0Lx5c7FMTEyM3j/Yo6OjUbduXVSuXFks8+h9issU36e0jG5hCA0NRWBgIP78808UFRVhy5YtSEpKwnfffac3ApOIiOh5ovjfJuV6Y2RlZeHy5cvifnJyMhISEuDg4IBatWph7NixmD17Nl577TW4ublh6tSp0Gq14kyKevXqoXPnzhg6dCjCw8ORn5+PkSNHom/fvtBqtQCA/v37Y8aMGQgKCsKkSZOQmJiIJUuWYNGiReJ9x4wZg3bt2mHBggXw8/PD+vXrcfLkSb2pl6VhdAtDjx49sGPHDvz000+wsbFBaGgoLly4gB07dqBjx47GVkdERPRMmGqWRGmdPHkSjRs3FlvfQ0JC0LhxY4SGhgIAJk6ciFGjRmHYsGFo1qwZsrKysHfvXr3lCtatWwd3d3d06NABXbt2RevWrfW+6DUaDfbv34/k5GR4eXlh3LhxCA0N1VuroWXLloiMjMTq1avh6emJH3/8EVFRUWjYsKFxn5+UdRgqGtdhIDngOgz0MnuW6zD0Dj8ieR2GzcPblGusz7Myv3zq5MmTuHDhAoCH4xq8vLxMFhQREZGp8fXW0hidMNy8eRP9+vXD0aNHYW9vDwDIyMhAy5YtsX79etSsWdPUMRIREUnGt1VKY/QYhiFDhiA/Px8XLlxAeno60tPTceHCBRQVFWHIkCHlESMRERFVMKNbGA4fPozY2FjUrVtXPFa3bl0sW7YMbdq0MWlwREREpiTzRgJJjE4YXFxcHrtAU2FhoTjNg4iI6HnDLglpjO6SmD9/PkaNGoWTJ0+Kx06ePIkxY8bg888/N2lwREREplI86FHKJmelamGoXLmyXmaVnZ2N5s2bw9z84eUFBQUwNzfH4MGDxQUniIiI6OVRqoRh8eLF5RwGERFR+WKXhDSlShgCAwPLOw4iIqJy9ayXhn7ZlHnhJgDIyclBXl6e3jE5rn5FRET0sjM6YcjOzsakSZOwceNG/PXXXyXOFxYWmiQwIiIiUzLV663lyuhZEhMnTsTBgwexatUqWFhY4KuvvsKMGTOg1Wrx3XfflUeMREREkikU0jc5M7qFYceOHfjuu+/w1ltvYdCgQWjTpg3q1KkDV1dXrFu3DgEBAeURJxEREVUgo1sY0tPT8corrwB4OF4hPT0dANC6dWvExMSYNjoiIiITedavt37ZGJ0wvPLKK0hOTgYAuLu7Y+PGjQAetjwUv4yKiIjoecMuCWmMThgGDRqEM2fOAAAmT56MFStWwNLSEsHBwZgwYYLJAyQiIqKKZ/QYhuDgYPFnHx8fXLx4EfHx8ahTpw7eeOMNkwZHRERkKpwlIY2kdRgAwNXVFa6urqaIhYiIqNxI7VaQeb5QuoRh6dKlpa5w9OjRZQ6GiIiovHBpaGlKlTAsWrSoVJUpFAomDERERC+hUiUMxbMinlfXD33OJanppVXZb0FFh0BUboSCnGd2LyXKMNL/X9fLmeQxDERERC8CdklII/eEiYiIiEqBLQxERCQLCgWg5CyJMmPCQEREsqCUmDBIufZlwC4JIiIiMqhMCcORI0cwYMAAeHt7488//wQArF27Fr/88otJgyMiIjIVvnxKGqMThs2bN8PX1xdWVlY4ffo0cnNzAQCZmZmYO3euyQMkIiIyheIuCSmbnBmdMMyePRvh4eH48ssvUalSJfF4q1atcOrUKZMGR0RERM8Howc9JiUloW3btiWOazQaZGRkmCImIiIik+O7JKQxuoXB2dkZly9fLnH8l19+wSuvvGKSoIiIiEyt+G2VUjY5MzphGDp0KMaMGYPjx49DoVDg1q1bWLduHcaPH48PP/ywPGIkIiKSTGmCTc6Mfv7Jkyejf//+6NChA7KystC2bVsMGTIEH3zwAUaNGlUeMRIREb1wCgsLMXXqVLi5ucHKygqvvvoqZs2aBUEQxDKCICA0NBTVq1eHlZUVfHx88Pvvv+vVk56ejoCAAKjVatjb2yMoKAhZWVl6Zc6ePYs2bdrA0tISLi4uCAsLM/nzGJ0wKBQKfPLJJ0hPT0diYiKOHTuGO3fuYNasWSYPjoiIyFSKxzBI2Yzx2WefYdWqVVi+fDkuXLiAzz77DGFhYVi2bJlYJiwsDEuXLkV4eDiOHz8OGxsb+Pr6Iifnn5dyBQQE4Pz584iOjsbOnTsRExODYcOGied1Oh06deoEV1dXxMfHY/78+Zg+fTpWr14t+TN7VJlXelSpVKhfv74pYyEiIio3Skgbh6CEcdfGxsaiR48e8PPzAwDUrl0bP/zwA3799VcAD1sXFi9ejClTpqBHjx4AgO+++w5OTk6IiopC3759ceHCBezduxcnTpxA06ZNAQDLli1D165d8fnnn0Or1WLdunXIy8vDN998A5VKhQYNGiAhIQELFy7USyykMjphaN++/VMXrzh48KCkgIiIiJ5nOp1Ob9/CwgIWFhYlyrVs2RKrV6/GpUuX8Prrr+PMmTP45ZdfsHDhQgBAcnIyUlJS4OPjI16j0WjQvHlzxMXFoW/fvoiLi4O9vb2YLACAj48PlEoljh8/jp49eyIuLg5t27aFSqUSy/j6+uKzzz7DvXv3ULlyZZM8t9EJQ6NGjfT28/PzkZCQgMTERAQGBpokKCIiIlMz1bRKFxcXvePTpk3D9OnTS5SfPHkydDod3N3dYWZmhsLCQsyZMwcBAQEAgJSUFACAk5OT3nVOTk7iuZSUFDg6OuqdNzc3h4ODg14ZNze3EnUUn6uwhGHRokWPPT59+vQSgzCIiIieF6Z6+dSNGzegVqvF449rXQCAjRs3Yt26dYiMjBS7CcaOHQutVvtC/gPbZLNEBgwYgG+++cZU1RERET2X1Gq13vakhGHChAmYPHky+vbtCw8PDwwcOBDBwcGYN28egIfrGgFAamqq3nWpqaniOWdnZ6SlpemdLygoQHp6ul6Zx9Xx6D1MwWQJQ1xcHCwtLU1VHRERkUkpFNIWbzK2O+PBgwdQKvW/Zs3MzFBUVAQAcHNzg7OzMw4cOCCe1+l0OH78OLy9vQEA3t7eyMjIQHx8vFjm4MGDKCoqQvPmzcUyMTExyM/PF8tER0ejbt26JuuOAMrQJdGrVy+9fUEQcPv2bZw8eRJTp041WWBERESm9KyXhu7WrRvmzJmDWrVqoUGDBjh9+jQWLlyIwYMH/68+BcaOHYvZs2fjtddeg5ubG6ZOnQqtVgt/f38AQL169dC5c2cMHToU4eHhyM/Px8iRI9G3b19otVoAQP/+/TFjxgwEBQVh0qRJSExMxJIlS544hKCsjE4YNBqN3r5SqUTdunUxc+ZMdOrUyWSBERERvciWLVuGqVOn4qOPPkJaWhq0Wi0++OADhIaGimUmTpyI7OxsDBs2DBkZGWjdujX27t2r12K/bt06jBw5Eh06dIBSqUTv3r2xdOlS8bxGo8H+/fsxYsQIeHl5oWrVqggNDTXplEoAUAiPLjllQGFhIY4ePQoPDw+TNnOUlU6ng0ajQepfmXoDUIheJpX9FlR0CETlRijIQe7BKcjMLL/f48XfFVO2nYKljV2Z68nJvo/ZPZqUa6zPM6PGMJiZmaFTp058KyUREb1wFCb4I2dGD3ps2LAh/vjjj/KIhYiIqNwUT6uUssmZ0QnD7NmzMX78eOzcuRO3b9+GTqfT24iIiOjlU+pBjzNnzsS4cePQtWtXAED37t31logWBAEKhQKFhYWmj5KIiEgiUy3cJFelThhmzJiB4cOH4+effy7PeIiIiMqFQqF46ruQSnO9nJU6YSieTNGuXbtyC4aIiIieT0atwyD37IqIiF5c7JKQxqiE4fXXXzeYNKSnp0sKiIiIqDw865UeXzZGJQwzZswosdIjERERvfyMShj69u1b4r3cREREL4Lil0hJuV7OSp0wcPwCERG9yDiGQZpSL9xkxCsniIiI6CVT6haG4vd3ExERvZAkDnqU+askjH+9NRER0YtICQWUEr71pVz7MmDCQEREssBpldIY/fIpIiIikh+2MBARkSxwloQ0TBiIiEgWuA6DNOySICIiIoPYwkBERLLAQY/SMGEgIiJZUEJil4TMp1WyS4KIiIgMYgsDERHJArskpGHCQEREsqCEtGZ1uTfJy/35iYiIqBTYwkBERLKgUCigkNCvIOXalwETBiIikgUFpL1wUt7pAhMGIiKSCa70KA3HMBAREZFBbGEgIiLZkHcbgTRMGIiISBa4DoM07JIgIiIig5gwEBGRLBRPq5SyGevPP//EgAEDUKVKFVhZWcHDwwMnT54UzwuCgNDQUFSvXh1WVlbw8fHB77//rldHeno6AgICoFarYW9vj6CgIGRlZemVOXv2LNq0aQNLS0u4uLggLCysbB/SUzBhICIiWVCaYDPGvXv30KpVK1SqVAl79uzBb7/9hgULFqBy5cpimbCwMCxduhTh4eE4fvw4bGxs4Ovri5ycHLFMQEAAzp8/j+joaOzcuRMxMTEYNmyYeF6n06FTp05wdXVFfHw85s+fj+nTp2P16tXGfkRPxTEMRERE5eCzzz6Di4sL1qxZIx5zc3MTfxYEAYsXL8aUKVPQo0cPAMB3330HJycnREVFoW/fvrhw4QL27t2LEydOoGnTpgCAZcuWoWvXrvj888+h1Wqxbt065OXl4ZtvvoFKpUKDBg2QkJCAhQsX6iUWUrGFgYiIZMFUXRI6nU5vy83Nfez9tm/fjqZNm+K///0vHB0d0bhxY3z55Zfi+eTkZKSkpMDHx0c8ptFo0Lx5c8TFxQEA4uLiYG9vLyYLAODj4wOlUonjx4+LZdq2bQuVSiWW8fX1RVJSEu7du2eyz48JAxERyYLCBBsAuLi4QKPRiNu8efMee78//vgDq1atwmuvvYZ9+/bhww8/xOjRo/Htt98CAFJSUgAATk5Oetc5OTmJ51JSUuDo6Kh33tzcHA4ODnplHlfHo/cwBXZJEBERGeHGjRtQq9XivoWFxWPLFRUVoWnTppg7dy4AoHHjxkhMTER4eDgCAwOfSaymxBYGIiKSBVN1SajVar3tSQlD9erVUb9+fb1j9erVw/Xr1wEAzs7OAIDU1FS9MqmpqeI5Z2dnpKWl6Z0vKChAenq6XpnH1fHoPUyBCQMREcnCs54l0apVKyQlJekdu3TpElxdXQE8HADp7OyMAwcOiOd1Oh2OHz8Ob29vAIC3tzcyMjIQHx8vljl48CCKiorQvHlzsUxMTAzy8/PFMtHR0ahbt67ejAypmDAQEZEsPOt1GIKDg3Hs2DHMnTsXly9fRmRkJFavXo0RI0aI8YwdOxazZ8/G9u3bce7cObz33nvQarXw9/cH8LBFonPnzhg6dCh+/fVXHD16FCNHjkTfvn2h1WoBAP3794dKpUJQUBDOnz+PDRs2YMmSJQgJCTHp58cxDEREROWgWbNm2Lp1Kz7++GPMnDkTbm5uWLx4MQICAsQyEydORHZ2NoYNG4aMjAy0bt0ae/fuhaWlpVhm3bp1GDlyJDp06AClUonevXtj6dKl4nmNRoP9+/djxIgR8PLyQtWqVREaGmrSKZUAoBAEQTBpjc+QTqeDRqNB6l+ZegNQiF4mlf0WVHQIROVGKMhB7sEpyMwsv9/jxd8V645egrWtXZnreZB1HwGtXi/XWJ9nbGEgIiJZ4MunpOEYBiIiIjKILQxERCQLSiigRNmbCaRc+zJgwkBERLLALglp2CVBREREBrGFgYiIZEHxvz9SrpczJgxERCQL7JKQhl0SREREZBBbGIiISBYUEmdJsEuCiIhIBtglIQ0TBiIikgUmDNJwDAMREREZxBYGIiKSBU6rlIYJAxERyYJS8XCTcr2csUuCiIiIDGILAxERyQK7JKRhwkBERLLAWRLSsEuCiIiIDGILAxERyYIC0roVZN7AwISBiIjkgbMkpGGXBBERERnEFgbC0VOXsWztTzhz8TpS7urw/fyh8HvLUzyf9SAXM5Zvw+7DZ5GemQ1XbRUMe7cdBvduI5Z5+4PFOHrqsl697/dqhUUf93tmz0Hy1LJBDYzq3QyedZxQvYotAmZtw+5j//xdXBHsi/4+DfWu+Sk+Gf8N3SLuv6qtjJlBbdG8Xg1UqqTEb8l3Mef7o/jl7I0S96tsZ4kjy99Djap2cH1nOXTZueK5Vh41MWfIW3B3rYI/79zH5xuO44efzpfDU1NZcJaENBWaMMTExGD+/PmIj4/H7du3sXXrVvj7+1dkSLL04O9cNHy9BgZ098bAiV+WOD9l0WbEnLyEL2a+h1rVq+DgsQsYH7YRzlU16NruDbFcoH9LfPzB2+K+lWWlZxI/yZu1ZSUkJt/B99GJ+H5Kj8eW+elkMkYs3ivu5+YX6p1fP90ff9zKQI//24i/8wrwYQ8vrJ/WE02GfIW0ew/0yi4b44vfku+gRlU7veO1nNTYML0X1uw+g2Gf70Y7z1pYOroTUtOzcPDUNRM9LUnBWRLSVGjCkJ2dDU9PTwwePBi9evWqyFBkrWOrBujYqsETzx8/m4x+fs3R2ut1AMD7vVojYutRnPrtml7CYGWpglNVdbnHS/Son+Kv4qf4q08tk5tfWOKLv5iD2gp1ajhg9JL9OH/1LgBgRkQMhrzdCPVcqyLt3nWx7OCuntDYWCDshzh0bPaKXj2Du3riekompn59GABw6UY6WtSvgQ/9vZgwPCcUkDZwUeb5QsWOYejSpQtmz56Nnj17VmQYZEDzN9ywJ+YcbqVlQBAEHDl5CVeup6F983p65TbtPYlXfSbB+905mLF8Gx7k5FVQxET6WnvUxKV1H+LXLwZhwUcdUNnOUjyXrvsbl26k493/1Ie1hTnMlAq838UTafeykXA5VSxX18UBE/q1wIcL96BIEErco5m7FocS9BODA6eu4k13bfk9GNEz9EKNYcjNzUVu7j/9hTqdrgKjkY/PJvwXY+f+gAZ+U2BupoRSqcSST/qhVZM6Ypk+vk3hUt0BztU0OP/7LcxYvg2Xr6Vh7fyhFRg5EXAg/ip2xl7GtZRM1K5uj6mBrbFpRi90Gv8DiooefvH3/GQTvp/aAzd+HI0iQcCdjAfoE7oFmVkPf9+ozM3w1UQ/TPsmBjfv3Iers6bEfRwrW+NOhn4rxp2MB1DbWMBSZY6cvILyf1h6KiUUUEroV1DKvI3hhUoY5s2bhxkzZlR0GLKzesNhnDx3FZELPoBLdQfEnr6MCf8bw/BWc3cAD7spijWoUwPOVdXo8dEyJN+8A7ea1SoqdCJsiUkSf/7t2l2cv3oHCV8PQWsPF8ScedjdMP+jDrib8QBdJ67H33kFeM/XAz9M80eHseuQei8boe+3xqUb6dj484WKegwyAXZJSPNCTav8+OOPkZmZKW43bpQcwUym9XdOHmat3IHZwb3Qpa0HGr5WA8PeaYeeHZtg+fcHnnidV8PaAIA/btx5RpESlc61lEzczXyAV6rbAwDaetaCb7NXEPTZLhy/cAtnr6Rh/MoDyMktQD+fBmKZHq1fx53twbizPRjb5vwXAHDlh48wOaAlACDt3gNUs7fWu1c1e2vosnPZukAvhReqhcHCwgIWFhYVHYas5BcUIr+gsEQznlKpfGw/brFzl24CAJyqlmy6JapI2iq2cLCzQuq9bACAtcXDX4P//vtcJAjiQj3vzdkOK4t/fl02fs0ZK4I7o+vE9Ui+nQEAOHHxFjo2ddOro31jV/x68VY5PQkZjU0MkrxQCQOVj6wHuUh+pCXg2q2/cC7pJuw11nBxdkCrJnUQujQKVpaV4OLsgKOnLmPD7l8xe+zDmS3JN+/gx70n0bFVAzhobJD4+5/4ZNEWtGxcBw1fq1FRj0UyYWNZCW5ae3Hf1VmNhq9UQ8b9HNy7n4NJ/b2x/ejvSL2XDbfq9pgxuC3+uH0PB/43s+LXi7eRkZWLlSGdMf+HY/g7twCBnT3g6qTB/hPJAICrKZl693RQWwEAkm6ki+swfLP7DIa83RgzBrXF99GJaOvpAv82dfHu9C2g5wPXYZCmQhOGrKwsXL78zwIrycnJSEhIgIODA2rVqlWBkclLwoVr6DZ8qbj/yaKHv+D6+TXHyukD8fWcwZi5YhuGTf0W93QP4OLsgCkfvo3BvR+OW6hkbo5DvyZh1fqf8eDvPNRwqoxu/2mE8YN9K+R5SF4aveaEnZ++K+7PHdoeABD5UyLGrTiA+rWroW+HBtDYWCAlPQsHT1/D3LVHkVfwcC2GdN3f6BO6GVPea41tc/8Lc3MlLl77CwGzopCYXPouteupOrw7fQvmDm2PD3o0xq27WRi9dD+nVNJLQyEIT2lXLmeHDh1C+/btSxwPDAxERESEwet1Oh00Gg1S/8qEWs35//Ryquy3oKJDICo3QkEOcg9OQWZm+f0eL/6uOJBwHbZ2Zb9H1n0dOjSqVa6xPs8qdNDjW2+9BUEQSmylSRaIiIiMoTDBVlaffvopFAoFxo4dKx7LycnBiBEjUKVKFdja2qJ3795ITU3Vu+769evw8/ODtbU1HB0dMWHCBBQU6A+iPXToEJo0aQILCwvUqVOn3L5DX6hZEkRERC+aEydO4IsvvsAbb7yhdzw4OBg7duzApk2bcPjwYdy6dUtv1ePCwkL4+fkhLy8PsbGx+PbbbxEREYHQ0FCxTHJyMvz8/NC+fXskJCRg7NixGDJkCPbt22fy52DCQERE8lABTQxZWVkICAjAl19+icqVK4vHMzMz8fXXX2PhwoX4z3/+Ay8vL6xZswaxsbE4duwYAGD//v347bff8P3336NRo0bo0qULZs2ahRUrViAv7+FKuuHh4XBzc8OCBQtQr149jBw5En369MGiRYvK9BE9DRMGIiKSBYUJ/gAPx0Q8uj26AvG/jRgxAn5+fvDx8dE7Hh8fj/z8fL3j7u7uqFWrFuLi4gAAcXFx8PDwgJOTk1jG19cXOp0O58+fF8v8u25fX1+xDlNiwkBERLJQ/LZKKRsAuLi4QKPRiNu8efMee7/169fj1KlTjz2fkpIClUoFe3t7veNOTk5ISUkRyzyaLBSfLz73tDI6nQ5///230Z/R03AdBiIiIiPcuHFDb5bE4xYUvHHjBsaMGYPo6GhYWlqWOP8iYgsDERHJgqmGMKjVar3tcQlDfHw80tLS0KRJE5ibm8Pc3ByHDx/G0qVLYW5uDicnJ+Tl5SEjI0PvutTUVDg7OwMAnJ2dS8yaKN43VEatVsPKyqoMn9KTMWEgIiJ5eIaDHjt06IBz584hISFB3Jo2bYqAgADx50qVKuHAgX/eyZOUlITr16/D29sbAODt7Y1z584hLS1NLBMdHQ21Wo369euLZR6to7hMcR2mxC4JIiIiE7Ozs0PDhg31jtnY2KBKlSri8aCgIISEhMDBwQFqtRqjRo2Ct7c3WrRoAQDo1KkT6tevj4EDByIsLAwpKSmYMmUKRowYIbZqDB8+HMuXL8fEiRMxePBgHDx4EBs3bsSuXbtM/kxMGIiISBaet3dJLFq0CEqlEr1790Zubi58fX2xcuVK8byZmRl27tyJDz/8EN7e3rCxsUFgYCBmzpwplnFzc8OuXbsQHByMJUuWoGbNmvjqq6/g62v6pfkrdGloqbg0NMkBl4aml9mzXBr6SOJNyUtDt2lYk0tDExERET0JuySIiEgWpL4PQt4vt2bCQEREcsGMQRJ2SRAREZFBbGEgIiJZeN5mSbxomDAQEZEsPPo+iLJeL2dMGIiISBY4hEEajmEgIiIig9jCQERE8sAmBkmYMBARkSxw0KM07JIgIiIig9jCQEREssBZEtIwYSAiIlngEAZp2CVBREREBrGFgYiI5IFNDJIwYSAiIlngLAlp2CVBREREBrGFgYiIZIGzJKRhwkBERLLAIQzSMGEgIiJ5YMYgCccwEBERkUFsYSAiIlngLAlpmDAQEZE8SBz0KPN8gV0SREREZBhbGIiISBY45lEaJgxERCQPzBgkYZcEERERGcQWBiIikgXOkpCGCQMREckCl4aWhl0SREREZBBbGIiISBY45lEaJgxERCQPzBgkYZcEERHJgsIEf4wxb948NGvWDHZ2dnB0dIS/vz+SkpL0yuTk5GDEiBGoUqUKbG1t0bt3b6SmpuqVuX79Ovz8/GBtbQ1HR0dMmDABBQUFemUOHTqEJk2awMLCAnXq1EFERESZPqOnYcJARERUDg4fPowRI0bg2LFjiI6ORn5+Pjp16oTs7GyxTHBwMHbs2IFNmzbh8OHDuHXrFnr16iWeLywshJ+fH/Ly8hAbG4tvv/0WERERCA0NFcskJyfDz88P7du3R0JCAsaOHYshQ4Zg3759Jn0ehSAIgklrfIZ0Oh00Gg1S/8qEWq2u6HCIykVlvwUVHQJRuREKcpB7cAoyM8vv93jxd0VichrsJNzjvk6Hhm6OZY71zp07cHR0xOHDh9G2bVtkZmaiWrVqiIyMRJ8+fQAAFy9eRL169RAXF4cWLVpgz549ePvtt3Hr1i04OTkBAMLDwzFp0iTcuXMHKpUKkyZNwq5du5CYmCjeq2/fvsjIyMDevXvL/Lz/xhYGIiKSBYUJNuBhAvLolpubW6r7Z2ZmAgAcHBwAAPHx8cjPz4ePj49Yxt3dHbVq1UJcXBwAIC4uDh4eHmKyAAC+vr7Q6XQ4f/68WObROorLFNdhKkwYiIiIjODi4gKNRiNu8+bNM3hNUVERxo4di1atWqFhw4YAgJSUFKhUKtjb2+uVdXJyQkpKiljm0WSh+HzxuaeV0el0+Pvvv8v0jI/DWRJERCQLplq46caNG3pdEhYWFgavHTFiBBITE/HLL7+UPYAKxhYGIiKSCdN0SqjVar3NUMIwcuRI7Ny5Ez///DNq1qwpHnd2dkZeXh4yMjL0yqempsLZ2Vks8+9ZE8X7hsqo1WpYWVkZ/lhKiQkDERFRORAEASNHjsTWrVtx8OBBuLm56Z338vJCpUqVcODAAfFYUlISrl+/Dm9vbwCAt7c3zp07h7S0NLFMdHQ01Go16tevL5Z5tI7iMsV1mAq7JIiISBae9bskRowYgcjISGzbtg12dnbimAONRgMrKytoNBoEBQUhJCQEDg4OUKvVGDVqFLy9vdGiRQsAQKdOnVC/fn0MHDgQYWFhSElJwZQpUzBixAixZWP48OFYvnw5Jk6ciMGDB+PgwYPYuHEjdu3aVfaHfQwmDEREJAvPeqHHVatWAQDeeustveNr1qzB+++/DwBYtGgRlEolevfujdzcXPj6+mLlypViWTMzM+zcuRMffvghvL29YWNjg8DAQMycOVMs4+bmhl27diE4OBhLlixBzZo18dVXX8HX17csj/lEXIeB6DnHdRjoZfYs12G4eO2O5HUY3F2rlWuszzO2MBARkSzw9dbSMGEgIiJZKMv7IP59vZwxYSAiInng2yol4bRKIiIiMogtDEREJAtsYJCGCQMREckCBz1Kwy4JIiIiMogtDEREJAucJSENEwYiIpIHDmKQhF0SREREZBBbGIiISBbYwCANEwYiIpIFzpKQhl0SREREZBBbGIiISCakzZKQe6cEEwYiIpIFdklIwy4JIiIiMogJAxERERnELgkiIpIFdklIw4SBiIhkgUtDS8MuCSIiIjKILQxERCQL7JKQhgkDERHJApeGloZdEkRERGQQWxiIiEge2MQgCRMGIiKSBc6SkIZdEkRERGQQWxiIiEgWOEtCGiYMREQkCxzCIA0TBiIikgdmDJJwDAMREREZxBYGIiKSBc6SkIYJAxERyQIHPUrzQicMgiAAAO7rdBUcCVH5EQpyKjoEonJT/Pe7+Pd5edJJ/K6Qev2L7oVOGO7fvw8AqOPmUsGREBGRFPfv34dGoymXulUqFZydnfGaCb4rnJ2doVKpTBDVi0chPIu0rpwUFRXh1q1bsLOzg0LubUXPiE6ng4uLC27cuAG1Wl3R4RCZFP9+P3uCIOD+/fvQarVQKstvHH5OTg7y8vIk16NSqWBpaWmCiF48L3QLg1KpRM2aNSs6DFlSq9X8hUovLf79frbKq2XhUZaWlrL9ojcVTqskIiIig5gwEBERkUFMGMgoFhYWmDZtGiwsLCo6FCKT499void7oQc9EhER0bPBFgYiIiIyiAkDERERGcSEgYiIiAxiwkBEREQGMWGgUluxYgVq164NS0tLNG/eHL/++mtFh0RkEjExMejWrRu0Wi0UCgWioqIqOiSi5w4TBiqVDRs2ICQkBNOmTcOpU6fg6ekJX19fpKWlVXRoRJJlZ2fD09MTK1asqOhQiJ5bnFZJpdK8eXM0a9YMy5cvB/DwPR4uLi4YNWoUJk+eXMHREZmOQqHA1q1b4e/vX9GhED1X2MJABuXl5SE+Ph4+Pj7iMaVSCR8fH8TFxVVgZERE9KwwYSCD7t69i8LCQjg5Oekdd3JyQkpKSgVFRUREzxITBiIiIjKICQMZVLVqVZiZmSE1NVXveGpqKpydnSsoKiIiepaYMJBBKpUKXl5eOHDggHisqKgIBw4cgLe3dwVGRkREz4p5RQdAL4aQkBAEBgaiadOmePPNN7F48WJkZ2dj0KBBFR0akWRZWVm4fPmyuJ+cnIyEhAQ4ODigVq1aFRgZ0fOD0yqp1JYvX4758+cjJSUFjRo1wtKlS9G8efOKDotIskOHDqF9+/YljgcGBiIiIuLZB0T0HGLCQERERAZxDAMREREZxISBiIiIDGLCQERERAYxYSAiIiKDmDAQERGRQUwYiIiIyCAmDERERGQQEwYiid5//334+/uL+2+99RbGjh37zOM4dOgQFAoFMjIynlhGoVAgKiqq1HVOnz4djRo1khTX1atXoVAokJCQIKkeIqpYTBjopfT+++9DoVBAoVBApVKhTp06mDlzJgoKCsr93lu2bMGsWbNKVbY0X/JERM8DvkuCXlqdO3fGmjVrkJubi927d2PEiBGoVKkSPv744xJl8/LyoFKpTHJfBwcHk9RDRPQ8YQsDvbQsLCzg7OwMV1dXfPjhh/Dx8cH27dsB/NONMGfOHGi1WtStWxcAcOPGDbzzzjuwt7eHg4MDevTogatXr4p1FhYWIiQkBPb29qhSpQomTpyIf6+u/u8uidzcXEyaNAkuLi6wsLBAnTp18PXXX+Pq1avi+wsqV64MhUKB999/H8DDt4HOmzcPbm5usLKygqenJ3788Ue9++zevRuvv/46rKys0L59e704S2vSpEl4/fXXYW1tjVdeeQVTp05Ffn5+iXJffPEFXFxcYG1tjXfeeQeZmZl657/66ivUq1cPlpaWcHd3x8qVK42OhYieb0wYSDasrKyQl5cn7h84cABJSUmIjo7Gzp07kZ+fD19fX9jZ2eHIkSM4evQobG1t0blzZ/G6BQsWICIiAt988w1++eUXpKenY+vWrU+973vvvYcffvgBS5cuxYULF/DFF1/A1tYWLi4u2Lx5MwAgKSkJt2/fxpIlSwAA8+bNw3fffYfw8HCcP38ewcHBGDBgAA4fPgzgYWLTq1cvdOvWDQkJCRgyZAgmT55s9GdiZ2eHiIgI/Pbbb1iyZAm+/PJLLFq0SK/M5cuXsXHjRuzYsQN79+7F6dOn8dFHH4nn161bh9DQUMyZMwcXLlzA3LlzMXXqVHz77bdGx0NEzzGB6CUUGBgo9OjRQxAEQSgqKhKio6MFCwsLYfz48eJ5JycnITc3V7xm7dq1Qt26dYWioiLxWG5urmBlZSXs27dPEARBqF69uhAWFiaez8/PF2rWrCneSxAEoV27dsKYMWMEQRCEpKQkAYAQHR392Dh//vlnAYBw79498VhOTo5gbW0txMbG6pUNCgoS+vXrJwiCIHz88cdC/fr19c5PmjSpRF3/BkDYunXrE8/Pnz9f8PLyEvenTZsmmJmZCTdv3hSP7dmzR1AqlcLt27cFQRCEV199VYiMjNSrZ9asWYK3t7cgCIKQnJwsABBOnz79xPsS0fOPYxjopbVz507Y2toiPz8fRUVF6N+/P6ZPny6e9/Dw0Bu3cObMGVy+fBl2dnZ69eTk5ODKlSvIzMzE7du39V7pbW5ujqZNm5boliiWkJAAMzMztGvXrtRxX758GQ8ePEDHjh31jufl5aFx48YAgAsXLpR4tbi3t3ep71Fsw4YNWLp0Ka5cuYKsrCwUFBRArVbrlalVqxZq1Kihd5+ioiIkJSXBzs4OV65cQVBQEIYOHSqWKSgogEajMToeInp+MWGgl1b79u2xatUqqFQqaLVamJvr/3W3sbHR28/KyoKXlxfWrVtXoq5q1aqVKQYrKyujr8nKygIA7Nq1S++LGng4LsNU4uLiEBAQgBkzZsDX1xcajQbr16/HggULjI71yy+/LJHAmJmZmSxWIqp4TBjopWVjY4M6deqUunyTJk2wYcMGODo6lvhXdrHq1avj+PHjaNu2LYCH/5KOj49HkyZNHlvew8MDRUVFOHz4MHx8fEqcL27hKCwsFI/Vr18fFhYWuH79+hNbJurVqycO4Cx27Ngxww/5iNjYWLi6uuKTTz4Rj127dq1EuevXr+PWrVvQarXifZRKJerWrQsnJydotVr88ccfCAgIMOr+RPRi4aBHov8JCAhA1apV0aNHDxw5cgTJyck4dOgQRo8ejZs3bwIAxowZg08//RRRUVG4ePEiPvroo6euoVC7dm0EBgZi8ODBiIqKEuvcuHEjAMDV1RUKhQI7d+7EnTt3kJWVBTs7O4wfPx7BwcH49ttvceXKFZw6dQrLli0TBxIOHz4cv//+OyZMmICkpCRERkYiIiLCqOd97bXXcP36daxfvx5XrlzB0qVLHzuA09LSEoGBgThz5gyOHDmC0aNH45133oGzszMAYMaMGZg3bx6WLl2KS5cu4dy5c1izZg0WLlxoVDxE9HxjwkD0P9bW1oiJiUGtWrXQq1cv1KtXD0FBQcjJyRFbHMaNG4eBAwciMDAQ3t7esLOzQ8+ePZ9a76pVq9CnTx989NFHcHd3x9ChQ5GdnQ0AqFGjBmbMmIHJkyfDyckJI0eOBADMmjULU6dOxbx581CvXj107twZu3btgpubG4CH4wo2b96MqKgoeHp6Ijw8HHPnzjXqebt3747g4GCMHDkSjRo1QmxsLKZOnVqiXJ06ddCrVy907doVnTp1whtvvKE3bXLIkCH46quvsGbNGnh4eKBdu3aIiIgQYyWil4NCeNJoLSIiIqL/YQsDERERGcSEgYiIiAxiwkBEREQGMWEgIiIig5gwEBERkUFMGIiIiMggJgxERERkEBMGIiIiMogJAxERERnEhIGIiIgMYsJAREREBjFhICIiIoP+H8zf+ubkA1nhAAAAAElFTkSuQmCC",
            "text/plain": [
              "<Figure size 640x480 with 2 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "svm = SVC(random_state=42)\n",
        "\n",
        "start_time = time.time()\n",
        "train_metrics = compute_train_metrics(svm, X_train, y_train)\n",
        "TRAINING_TIME['SVM'] = time.time() - start_time\n",
        "\n",
        "svm.fit(X_train, y_train)\n",
        "test_metrics = compute_test_metrics_and_plot_cm(svm, X_test, y_test, \"SVM\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 107,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 487
        },
        "id": "y7nhehFbSAP8",
        "outputId": "c2878bd6-1c11-4fa7-c557-e7b18969dcba"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "plot_metrics(train_metrics, test_metrics, \"SVM\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 108,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 607
        },
        "id": "gfVOvbatW37a",
        "outputId": "560dc3bd-ecfd-47ad-e9b0-48f6e1f56f83"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 800x600 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "plot_roc_curve(svm, X_test, y_test, \"SVM\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "e_gs_CP6SAP9"
      },
      "source": [
        "# GRADIENT BOOSTING CLASSIFIER"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 109,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 472
        },
        "id": "XbAEnwS4SAP9",
        "outputId": "a895d1f3-3fdf-48b0-8457-63deccbdacbd"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 640x480 with 2 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "gbc = GradientBoostingClassifier(random_state=42)\n",
        "\n",
        "start_time = time.time()\n",
        "train_metrics = compute_train_metrics(gbc, X_train, y_train)\n",
        "TRAINING_TIME['Gradient Boosting Classifier'] = time.time() - start_time\n",
        "\n",
        "gbc.fit(X_train, y_train)\n",
        "test_metrics = compute_test_metrics_and_plot_cm(gbc, X_test, y_test, \"GBC\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 110,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 487
        },
        "id": "QXmVGQPuSAP9",
        "outputId": "8f3f7f14-0350-4ea9-d920-11de2e928442"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "plot_metrics(train_metrics, test_metrics, \"Gradient Boosting Classifier\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 111,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 607
        },
        "id": "W5SB8BrHW53a",
        "outputId": "b0467f04-56eb-4853-a09c-f3bde99aef09"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 800x600 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "plot_roc_curve(gbc, X_test, y_test, \"Gradient Boosting Classifier\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "dqyxZJr3SAP9"
      },
      "source": [
        "# TRAINING TIME COMPARISON"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 112,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hb1VRvTxSAP-",
        "outputId": "4c377dda-7ae1-49fe-b05c-6a85ae9d21ad"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "+------------------------------+-----------------+\n",
            "| Model                        | Training Time   |\n",
            "+==============================+=================+\n",
            "| Logistic Regression          | 2.36 seconds    |\n",
            "+------------------------------+-----------------+\n",
            "| Decision Tree                | 1.01 seconds    |\n",
            "+------------------------------+-----------------+\n",
            "| Random Forest                | 18.12 seconds   |\n",
            "+------------------------------+-----------------+\n",
            "| Gaussian NB                  | 0.55 seconds    |\n",
            "+------------------------------+-----------------+\n",
            "| SVM                          | 115.63 seconds  |\n",
            "+------------------------------+-----------------+\n",
            "| Gradient Boosting Classifier | 53.84 seconds   |\n",
            "+------------------------------+-----------------+\n"
          ]
        }
      ],
      "source": [
        "from tabulate import tabulate\n",
        "table_data = [[model, f\"{time:.2f} seconds\"] for model, time in TRAINING_TIME.items()]\n",
        "headers = [\"Model\", \"Training Time\"]\n",
        "print(tabulate(table_data, headers=headers, tablefmt=\"grid\"))"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "JUFyBfDXSAP-"
      },
      "source": [
        "# VISUALIZATION OF TRAINING TIME FOR BETTER INSIGHTS"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 113,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 607
        },
        "id": "v-mSqAXSSAQB",
        "outputId": "54f9e0ac-d968-4ab2-fea5-56c423ef1467"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 1000x600 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "plt.figure(figsize=(10, 6))\n",
        "plt.bar(TRAINING_TIME.keys(), TRAINING_TIME.values(), color='lightcoral', log=True)\n",
        "\n",
        "for i, (model, time) in enumerate(TRAINING_TIME.items()):\n",
        "    plt.text(i, time, f\"{time:.2f}\", ha='center', va='bottom', fontsize=10)\n",
        "\n",
        "plt.xlabel(\"Models\")\n",
        "plt.ylabel(\"Training Time (log(seconds))\")\n",
        "plt.title(\"Relative Training Time for Models (Log Scale)\")\n",
        "plt.xticks(rotation=45)\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ]
    }
  ],
  "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": "3.12.6"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}