{
  "cells": [
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_gwwsDZScgbp",
        "outputId": "00247869-13de-45e6-cdcd-c54a419f200a"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: gdown in /usr/local/lib/python3.12/dist-packages (5.2.0)\n",
            "Requirement already satisfied: beautifulsoup4 in /usr/local/lib/python3.12/dist-packages (from gdown) (4.13.5)\n",
            "Requirement already satisfied: filelock in /usr/local/lib/python3.12/dist-packages (from gdown) (3.20.0)\n",
            "Requirement already satisfied: requests[socks] in /usr/local/lib/python3.12/dist-packages (from gdown) (2.32.4)\n",
            "Requirement already satisfied: tqdm in /usr/local/lib/python3.12/dist-packages (from gdown) (4.67.1)\n",
            "Requirement already satisfied: soupsieve>1.2 in /usr/local/lib/python3.12/dist-packages (from beautifulsoup4->gdown) (2.8)\n",
            "Requirement already satisfied: typing-extensions>=4.0.0 in /usr/local/lib/python3.12/dist-packages (from beautifulsoup4->gdown) (4.15.0)\n",
            "Requirement already satisfied: charset_normalizer<4,>=2 in /usr/local/lib/python3.12/dist-packages (from requests[socks]->gdown) (3.4.4)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.12/dist-packages (from requests[socks]->gdown) (3.11)\n",
            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.12/dist-packages (from requests[socks]->gdown) (2.5.0)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.12/dist-packages (from requests[socks]->gdown) (2025.11.12)\n",
            "Requirement already satisfied: PySocks!=1.5.7,>=1.5.6 in /usr/local/lib/python3.12/dist-packages (from requests[socks]->gdown) (1.7.1)\n"
          ]
        }
      ],
      "source": [
        "# Install the necessary library\n",
        "!pip install gdown     # I have used this library for downloading the dataset that I have uploaded on google drive after download it form kaggle"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [],
      "metadata": {
        "id": "1N6BgFOihLuV"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "id": "Eho7xJ_bYzyk"
      },
      "outputs": [],
      "source": [
        "# General-purpose libraries for data handling and numeric operations\n",
        "import pandas as pd              # Used for loading, cleaning and manipulating datasets\n",
        "import numpy as np               # Used for numerical operations and array handling\n",
        "import time                      # Used to measure model training time\n",
        "\n",
        "# Visualisation libraries\n",
        "import matplotlib.pyplot as plt  # For creating plots such as bar charts and line plots\n",
        "import seaborn as sns            # For statistical visualisations (heatmaps, count plots etc.)\n",
        "\n",
        "# All scikit-learn functions\n",
        "from sklearn.model_selection import train_test_split, GridSearchCV   # For splitting data and tuning models\n",
        "from sklearn.preprocessing import OneHotEncoder, StandardScaler, LabelEncoder  # For encoding and scaling features\n",
        "\n",
        "from sklearn.compose import ColumnTransformer   # For applying different preprocessing to numerical and categorical features\n",
        "from sklearn.pipeline import Pipeline           # For linking preprocessing and model steps together\n",
        "from sklearn.metrics import precision_score, recall_score, f1_score  # For evaluating model performance\n",
        "\n",
        "# Machine learning models\n",
        "from sklearn.ensemble import RandomForestClassifier   # Random Forest classifier\n",
        "from sklearn.metrics import classification_report, confusion_matrix, accuracy_score   # Extra evaluation tools\n",
        "from xgboost import XGBClassifier                     # XGBoost classifier\n",
        "\n",
        "# For downloading files directly from Google Drive (if needed)\n",
        "import gdown\n",
        "\n",
        "# Optional: Make plots prettier\n",
        "sns.set(style=\"whitegrid\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YZEov46edqk3",
        "outputId": "86f8af20-1b9f-43fa-cde9-b6f698b904f1"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Downloading...\n",
            "From: https://drive.google.com/uc?id=16OQ3urEequeQiLyjzpCGJJ5YicDIAIPv\n",
            "To: /content/KDDTest.csv\n",
            "100%|██████████| 3.11M/3.11M [00:00<00:00, 16.4MB/s]\n",
            "Downloading...\n",
            "From: https://drive.google.com/uc?id=1SWzL0MPumSpp_-M3-2G4oTf7jL9ILkkm\n",
            "To: /content/KDDTrain.csv\n",
            "100%|██████████| 14.4M/14.4M [00:00<00:00, 49.8MB/s]\n"
          ]
        }
      ],
      "source": [
        "# Function to download a file from Google Drive\n",
        "def download_file_from_google_drive(url, destination):\n",
        "    try:\n",
        "        # Use gdown to download the file to the given destination path\n",
        "        gdown.download(url, destination, quiet=False)\n",
        "    except Exception as e:\n",
        "        # Print an error message if the download fails\n",
        "        print(f\"Download failed: {e}\")\n",
        "\n",
        "# Direct download links for the NSL-KDD datasets stored on Google Drive\n",
        "test_data_url = \"https://drive.google.com/uc?id=16OQ3urEequeQiLyjzpCGJJ5YicDIAIPv\"\n",
        "train_data_url = \"https://drive.google.com/uc?id=1SWzL0MPumSpp_-M3-2G4oTf7jL9ILkkm\"\n",
        "\n",
        "# Downloading the test and train CSV files to the working directory\n",
        "download_file_from_google_drive(test_data_url, \"KDDTest.csv\")\n",
        "download_file_from_google_drive(train_data_url, \"KDDTrain.csv\")\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Nrmp0-maaJzr",
        "outputId": "9ba70417-6028-477f-acd3-05976398d4e4"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Loading the training dataset....\n",
            "Index(['duration', 'protocol_type', 'service', 'flag', 'src_bytes',\n",
            "       'dst_bytes', 'land', 'wrong_fragment', 'urgent', 'hot',\n",
            "       'num_failed_logins', 'logged_in', 'num_compromised', 'root_shell',\n",
            "       'su_attempted', 'num_root', 'num_file_creations', 'num_shells',\n",
            "       'num_access_files', 'num_outbound_cmds', 'is_host_login',\n",
            "       'is_guest_login', 'count', 'srv_count', 'serror_rate',\n",
            "       'srv_serror_rate', 'rerror_rate', 'srv_rerror_rate', 'same_srv_rate',\n",
            "       'diff_srv_rate', 'srv_diff_host_rate', 'dst_host_count',\n",
            "       'dst_host_srv_count', 'dst_host_same_srv_rate',\n",
            "       'dst_host_diff_srv_rate', 'dst_host_same_src_port_rate',\n",
            "       'dst_host_srv_diff_host_rate', 'dst_host_serror_rate',\n",
            "       'dst_host_srv_serror_rate', 'dst_host_rerror_rate',\n",
            "       'dst_host_srv_rerror_rate', 'labels'],\n",
            "      dtype='object')\n",
            "Total number of columns: 42\n",
            "\n",
            "Loading the test dataset....\n",
            "Index(['duration', 'protocol_type', 'service', 'flag', 'src_bytes',\n",
            "       'dst_bytes', 'land', 'wrong_fragment', 'urgent', 'hot',\n",
            "       'num_failed_logins', 'logged_in', 'num_compromised', 'root_shell',\n",
            "       'su_attempted', 'num_root', 'num_file_creations', 'num_shells',\n",
            "       'num_access_files', 'num_outbound_cmds', 'is_host_login',\n",
            "       'is_guest_login', 'count', 'srv_count', 'serror_rate',\n",
            "       'srv_serror_rate', 'rerror_rate', 'srv_rerror_rate', 'same_srv_rate',\n",
            "       'diff_srv_rate', 'srv_diff_host_rate', 'dst_host_count',\n",
            "       'dst_host_srv_count', 'dst_host_same_srv_rate',\n",
            "       'dst_host_diff_srv_rate', 'dst_host_same_src_port_rate',\n",
            "       'dst_host_srv_diff_host_rate', 'dst_host_serror_rate',\n",
            "       'dst_host_srv_serror_rate', 'dst_host_rerror_rate',\n",
            "       'dst_host_srv_rerror_rate', 'labels'],\n",
            "      dtype='object')\n",
            "Total number of columns: 42\n",
            "\n",
            "Train and test datasets have the same features.\n"
          ]
        }
      ],
      "source": [
        "# Function to load the NSL-KDD dataset from a CSV file\n",
        "def load_nsl_kdd(path):\n",
        "    # Read the CSV file into a pandas DataFrame\n",
        "    df = pd.read_csv(path)\n",
        "\n",
        "    # Print all column names to verify the structure of the dataset\n",
        "    print(df.columns)\n",
        "\n",
        "    # Print the total number of columns for quick checking\n",
        "    print(f\"Total number of columns: {len(df.columns)}\\n\")\n",
        "\n",
        "    # Return the loaded DataFrame\n",
        "    return df\n",
        "\n",
        "# Load the training dataset\n",
        "print(\"Loading the training dataset....\")\n",
        "df_train = load_nsl_kdd(\"KDDTrain.csv\")\n",
        "\n",
        "# Load the testing dataset\n",
        "print(\"Loading the test dataset....\")\n",
        "df_test = load_nsl_kdd(\"KDDTest.csv\")\n",
        "\n",
        "# Check whether both files have the same set of features\n",
        "if df_train.columns.equals(df_test.columns):\n",
        "    print(\"Train and test datasets have the same features.\")\n",
        "else:\n",
        "    print(\"Train and test datasets DO NOT match.\")\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5LuIc9sEmEJs",
        "outputId": "904f30c1-8bc9-4b89-9788-8e305eed32aa"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 125973 entries, 0 to 125972\n",
            "Data columns (total 42 columns):\n",
            " #   Column                       Non-Null Count   Dtype  \n",
            "---  ------                       --------------   -----  \n",
            " 0   duration                     125973 non-null  int64  \n",
            " 1   protocol_type                125973 non-null  object \n",
            " 2   service                      125973 non-null  object \n",
            " 3   flag                         125973 non-null  object \n",
            " 4   src_bytes                    125973 non-null  int64  \n",
            " 5   dst_bytes                    125973 non-null  int64  \n",
            " 6   land                         125973 non-null  int64  \n",
            " 7   wrong_fragment               125973 non-null  int64  \n",
            " 8   urgent                       125973 non-null  int64  \n",
            " 9   hot                          125973 non-null  int64  \n",
            " 10  num_failed_logins            125973 non-null  int64  \n",
            " 11  logged_in                    125973 non-null  int64  \n",
            " 12  num_compromised              125973 non-null  int64  \n",
            " 13  root_shell                   125973 non-null  int64  \n",
            " 14  su_attempted                 125973 non-null  int64  \n",
            " 15  num_root                     125973 non-null  int64  \n",
            " 16  num_file_creations           125973 non-null  int64  \n",
            " 17  num_shells                   125973 non-null  int64  \n",
            " 18  num_access_files             125973 non-null  int64  \n",
            " 19  num_outbound_cmds            125973 non-null  int64  \n",
            " 20  is_host_login                125973 non-null  int64  \n",
            " 21  is_guest_login               125973 non-null  int64  \n",
            " 22  count                        125973 non-null  int64  \n",
            " 23  srv_count                    125973 non-null  int64  \n",
            " 24  serror_rate                  125973 non-null  float64\n",
            " 25  srv_serror_rate              125973 non-null  float64\n",
            " 26  rerror_rate                  125973 non-null  float64\n",
            " 27  srv_rerror_rate              125973 non-null  float64\n",
            " 28  same_srv_rate                125973 non-null  float64\n",
            " 29  diff_srv_rate                125973 non-null  float64\n",
            " 30  srv_diff_host_rate           125973 non-null  float64\n",
            " 31  dst_host_count               125973 non-null  int64  \n",
            " 32  dst_host_srv_count           125973 non-null  int64  \n",
            " 33  dst_host_same_srv_rate       125973 non-null  float64\n",
            " 34  dst_host_diff_srv_rate       125973 non-null  float64\n",
            " 35  dst_host_same_src_port_rate  125973 non-null  float64\n",
            " 36  dst_host_srv_diff_host_rate  125973 non-null  float64\n",
            " 37  dst_host_serror_rate         125973 non-null  float64\n",
            " 38  dst_host_srv_serror_rate     125973 non-null  float64\n",
            " 39  dst_host_rerror_rate         125973 non-null  float64\n",
            " 40  dst_host_srv_rerror_rate     125973 non-null  float64\n",
            " 41  labels                       125973 non-null  object \n",
            "dtypes: float64(15), int64(23), object(4)\n",
            "memory usage: 40.4+ MB\n",
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 22544 entries, 0 to 22543\n",
            "Data columns (total 42 columns):\n",
            " #   Column                       Non-Null Count  Dtype  \n",
            "---  ------                       --------------  -----  \n",
            " 0   duration                     22544 non-null  int64  \n",
            " 1   protocol_type                22544 non-null  object \n",
            " 2   service                      22544 non-null  object \n",
            " 3   flag                         22544 non-null  object \n",
            " 4   src_bytes                    22544 non-null  int64  \n",
            " 5   dst_bytes                    22544 non-null  int64  \n",
            " 6   land                         22544 non-null  int64  \n",
            " 7   wrong_fragment               22544 non-null  int64  \n",
            " 8   urgent                       22544 non-null  int64  \n",
            " 9   hot                          22544 non-null  int64  \n",
            " 10  num_failed_logins            22544 non-null  int64  \n",
            " 11  logged_in                    22544 non-null  int64  \n",
            " 12  num_compromised              22544 non-null  int64  \n",
            " 13  root_shell                   22544 non-null  int64  \n",
            " 14  su_attempted                 22544 non-null  int64  \n",
            " 15  num_root                     22544 non-null  int64  \n",
            " 16  num_file_creations           22544 non-null  int64  \n",
            " 17  num_shells                   22544 non-null  int64  \n",
            " 18  num_access_files             22544 non-null  int64  \n",
            " 19  num_outbound_cmds            22544 non-null  int64  \n",
            " 20  is_host_login                22544 non-null  int64  \n",
            " 21  is_guest_login               22544 non-null  int64  \n",
            " 22  count                        22544 non-null  int64  \n",
            " 23  srv_count                    22544 non-null  int64  \n",
            " 24  serror_rate                  22544 non-null  float64\n",
            " 25  srv_serror_rate              22544 non-null  float64\n",
            " 26  rerror_rate                  22544 non-null  float64\n",
            " 27  srv_rerror_rate              22544 non-null  float64\n",
            " 28  same_srv_rate                22544 non-null  float64\n",
            " 29  diff_srv_rate                22544 non-null  float64\n",
            " 30  srv_diff_host_rate           22544 non-null  float64\n",
            " 31  dst_host_count               22544 non-null  int64  \n",
            " 32  dst_host_srv_count           22544 non-null  int64  \n",
            " 33  dst_host_same_srv_rate       22544 non-null  float64\n",
            " 34  dst_host_diff_srv_rate       22544 non-null  float64\n",
            " 35  dst_host_same_src_port_rate  22544 non-null  float64\n",
            " 36  dst_host_srv_diff_host_rate  22544 non-null  float64\n",
            " 37  dst_host_serror_rate         22544 non-null  float64\n",
            " 38  dst_host_srv_serror_rate     22544 non-null  float64\n",
            " 39  dst_host_rerror_rate         22544 non-null  float64\n",
            " 40  dst_host_srv_rerror_rate     22544 non-null  float64\n",
            " 41  labels                       22544 non-null  object \n",
            "dtypes: float64(15), int64(23), object(4)\n",
            "memory usage: 7.2+ MB\n"
          ]
        }
      ],
      "source": [
        "# Display summary information about the training and test dataset\n",
        "# This shows column names, data types, non-null counts and memory usage\n",
        "df_train.info()\n",
        "\n",
        "df_test.info()"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# ================================\n",
        "# 1. CLASS DISTRIBUTION (TRAIN)\n",
        "# ================================\n",
        "\n",
        "# Plot the distribution of attack types in the training dataset.\n",
        "# This helps us understand class imbalance and see which labels appear more oft\n",
        "plt.figure(figsize=(14, 8))\n",
        "sns.countplot(y=df_train[\"labels\"])   # Use label column\n",
        "plt.title(\"Distribution of Attack Types (Training Set)\", fontsize=16)\n",
        "plt.xlabel(\"Count\", fontsize=12)\n",
        "plt.ylabel(\"Attack Type\", fontsize=12)\n",
        "plt.tight_layout()\n",
        "plt.show()\n",
        "\n",
        "\n",
        "# ===================================\n",
        "# 2. CORRELATION HEATMAP (NUMERIC)\n",
        "# ===================================\n",
        "\n",
        "# Select all numerical columns (excluding the target label)\n",
        "numeric_cols = df_train.select_dtypes(include=['int64', 'float64']).columns.tolist()\n",
        "numeric_cols = [col for col in numeric_cols if col != 'labels']   # remove target\n",
        "\n",
        "# Create a correlation matrix and visualise it as a heatmap.\n",
        "# This shows how strongly numerical features are related.\n",
        "plt.figure(figsize=(15, 12))\n",
        "corr = df_train[numeric_cols].corr()\n",
        "sns.heatmap(corr, cmap=\"coolwarm\", annot=False)\n",
        "plt.title(\"Correlation Heatmap of Numeric Features\", fontsize=18)\n",
        "plt.show()\n",
        "\n",
        "# Identify columns that contain only one unique value.\n",
        "# These are constant features and cannot contribute to correlation or learning.\n",
        "nunique = df_train[numeric_cols].nunique()\n",
        "constant_cols = nunique[nunique == 1].index.tolist()\n",
        "\n",
        "print(\"\\nColumns with only ONE unique value (constant features):\")\n",
        "print(constant_cols)\n",
        "\n",
        "# Show summary statistics for constant features.\n",
        "# These features will have std = 0 and identical min/max values.\n",
        "# Correlation cannot be calculated with constant features.\n",
        "if constant_cols:\n",
        "    print(\"\\nDescriptive statistics for constant features:\")\n",
        "    display(df_train[constant_cols].describe().T[[\"mean\", \"std\", \"min\", \"max\"]])\n",
        "    print(\"It tells taht if we try to find correlation using this our correlation will be undefined.\")\n",
        "else:\n",
        "    print(\"No constant features found.\")\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "C3yEJ3FiyL5U",
        "outputId": "eac9d9eb-e5fb-4646-a6fb-0577e9ce651a"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1400x800 with 1 Axes>"
            ],
            "image/png": 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tVb58ed26dStdOYrMJCQkaMWKFZLuliS4d/ecra2t3nrrLbm5ueny5cvasmVLtu7xQb777jtJ/1frMU3a7tm083mhQoUK8vf3T9detGhRU53lzZs3m53bsWOHjh8/Lnd3d82dOzfdrtHChQurYcOGmV4zNjZWvXr10oYNGxQSEqLly5en2y2eW9LKOaR9b++1fPlySXdfCPjvHcFpJk6caLZb1cnJSZMmTZKVlZV+/PFHXblyxXRu2bJliomJ0SuvvKKuXbua7VgtVqyYpk+fLltbW61YsUJGo1FS7n9+nDp1StLd72tuqV27tl555ZUMz5UoUUJ16tRJtzvX3t5eEydOVKFChdKtn6yoVq2aXn/9dbNdzl5eXnrxxRclSbt27crWfFZWVpo6darZZ2nhwoU1dOjQDOdbvXq14uLiVL16ddMaShMYGKjOnTtn6/rS3RdtLVy40LSr9dixY1qwYIEGDRqkhg0bqlmzZlq0aJHu3LljNi4mJkZLly5V4cKFFRYWlu6llM2bN9fLL7+s2NhYff/999mOS5KcnZ3l5uam+Ph4/f777zmaAwDw+CExCwAALCI1NVXS3f+Yf5Bq1arJxsZG3333nVasWKFr167lWhyurq4KCAjI8fg2bdpk2N62bVtJd19Gk5KSkuP5H9aVK1d08eJFSen/1Fa6+/zT/tw3s7q3/07KpklLTP27Lmxmjh07pri4ODk7O5vVYE1jb29vqvuaWSw5kZycbKpZmZaITdO2bVsVKlRIERERpueUF1JSUrR7927Nnz9fEydO1Lhx4zR27FgtWLBAktLV+f3ll18kSa1bt9bTTz+drWtdvnxZnTt31r59+/Tqq69q/vz5efoyvaZNm6pkyZLavXu3WS3RW7duacOGDbKxsVGXLl0yHFu5cmWzXxakMRgMqlq1qlJTUxUREWFqDw8PlyS1aNEiw/nSykVER0fr/PnzknL/8yMt0ZvV0gdZ0axZswf2OXjwoBYtWqRJkyaZ1s+kSZNka2ur6Ojo+9bkzUjjxo0z/PzN7s91mmeeeUaVK1fO8nxp39fMynGkJYizy8PDQ4sXL9bGjRs1YsQINW7cWMWLF5cknT9/XjNnztTLL79sVpt37969unPnjmrUqGHq+29BQUGSpEOHDuUoLun/fiF5/fr1HM8BAHi8UGMWAABYxI0bNyTd3TX4IKVLl9a4ceM0ffp0TZ48WZMnT5anp6f8/f3VqFEjNW/ePNPdeA/i6emZo3Fp/l0z8d/td+7cUUxMjFxdXR/qOjmVlgxxdnbOcLegdPf53tv335555pkM29Pmu9/Lq+6VlhC73zN/UCw58dNPPykqKkrFixdXcHCw2Tk3Nzc1aNBAO3bs0Hfffafhw4fn2nXTnD9/XoMHD9bZs2cz7XP79m2z4z///FNS9uvoSnd3gCcnJ6tTp056++23sz0+uwoVKqSuXbtq5syZWrFihSZMmCDp7ovq4uLiTInbjGT285N27sSJE2Y7Zi9duiRJme4uvVd0dLTKlSuX658fad+rzH6ecuJ+PxPXr1/XkCFDdODAgQfGlZXP0zSZfU/S7iujF4Dl5nxp39fM7v1hP5srVaqkSpUqmY7PnTunr776SitWrNDp06c1e/ZsvfPOO5L+b13t3r37gS8bi46OznFMab9kyW4SHQDw+CIxCwAA8p3RaDT9ObCXl1eWxoSGhqpFixbasWOHDhw4oAMHDmjTpk3atGmTwsLCtGLFCnl4eGQ7lntf+JRX0v6kOivSdhIXJFnZ1VyQpb30KyEhIcMXUKUlgdesWaOhQ4dm+AKrhzF06FCdPXtWjRs3Vu/evVWhQgU5ODjI1tZWiYmJ8vHxydXrvfjii1q3bp02bNigpk2b3rfkQW7p1KmT5s+fr3Xr1mnEiBF6+umnTS/9ykoS9X7u/flJ+/n490v9MnLvjtbc/PxwdHRUdHR0umT6w7jf59D48eN14MABVa9eXUOGDFHlypXl5ORkerlZcHCwoqKisvU5IynXXlz2sPNl9vmS2587FSpU0Ntvvy0rKyt9+eWX2rZtmykxm7auypQpoxo1atx3npz8siRN2prJTgIdAPB4IzELAADyXXh4uGnH0L93MN6Pm5ubXnrpJb300kuS7u6AGj9+vA4dOqSZM2fqgw8+yJN47+fy5csZtkdGRkq6W2Px3gRRWjLln3/+yXBc2k7J3JL2Z7kxMTG6fft2hrv80naLZfYnvLklLfGV9mwyktuxXLt2TT///LOku8/g4MGD9+37yy+/qFGjRrlybenuGj1z5oxcXV01b948FSpk/n+/L1y4kOG4tN2HOalF2bZtW9WvX1+jR4/WoEGDNHPmzCz9qfzDKFasmFq3bq1vv/1W69evV9myZfXHH3+oYsWKqlOnTqbjMvv5ufdciRIlTG0lS5bU+fPn1adPn2wntHPr88PV1VXR0dFZqo/9sOLi4vTzzz/L2tpaixYtkpOTU7rzaaUVHjXFixfXH3/88cDP0NwWHBysL7/80vRXG9L//byVK1dO06ZNy5PrSv9XU91Sf0EBACh4qDELAADy1a1btzR16lRJUr169TKsL5lVFSpUUO/evSX93wt50qQlQPO6vmtmL4JJq2las2ZNs2RcWsLx3lqcaeLj4zOtrZp2P8nJydmKr0SJEqbyAGvWrEl33mg0au3atZKkWrVqZWvu7PLx8VGRIkUUExOj7du3pzt/584d/fDDD7kay9q1a5WSkiI/Pz+dOXMm06+0dZS2uzbNg577g86n/QLCw8MjXVJWynz9pL28aOPGjYqLi3vQbabTsmVLzZs3T9bW1ho+fLhpPeal0NBQSXdfApb20q+0l+Bl5syZMzp9+nS69rNnz+rkyZOytrZWYGCgqb1+/fqSpB9//PGh473f58f9VK1aVVLGP8O57datW0pJSZGDg0O6pKx0d/1kd6dsQZH2fd20aVOG5zds2JDtObPyLNJ++XVvwr9OnTqytbXVvn37sl3/NaufzTdu3FBUVJTs7e1z9cVxAIBHG4lZAACQL4xGo8LDw9WxY0edP39e7u7umjJlSpbG7t69W+Hh4UpKSko3508//SQpfR3UtATo/ep65oYTJ05o8eLFZm379+83/Rl3jx49zM6l7R786quvzOqoxsXF6e2339Zff/2V4XXSkgg5SQb17NlTkvTxxx+bJcGMRqM+/vhjnTp1Sk5OTqadhHmlcOHCpj9r/+CDD8x2xCUlJem9995TVFSUSpUqlWs7PL/77jtJ//cytsyknf/pp5/MakimraPffvstw3Fp35cLFy6kW5+SVLZsWdnY2OjXX39Nl3TfsWOHli5dmuG8ISEhqlq1qq5du6Zhw4aZ7e6T7pZlSHsRVmYaNWqkRYsWqXDhwho7dqxWrFhx3/4Py2AwqHbt2jp37px27NghBweHBz53o9GoiRMnmtXcvHXrliZOnCij0ajnn3/erHZp79695eTkpKVLl+qzzz7LsA7qpUuXtH79etNxTj4/7iftlwYP8xKorHJzc1PRokV18+bNdMn1w4cPa9asWXkeQ17p2LGj7O3tdeDAgXRr88CBA6bP0OzYsWOHBg4cqJ07d2b4S7m9e/dq3rx5kqQXXnjB1O7m5qbQ0FDFxcWpf//+OnPmTLqxiYmJ2r59e7rP4Ad9RqRJWy81a9Y0JXMBAKCUAQAAyHXffvut9u3bJ+nuf8zeuHFDJ0+eNP0ZZ1BQkN5///0sv9zlzJkzmjp1qhwcHFS1alV5eHgoISFBJ0+eVGRkpBwdHTVs2DCzMc2aNdPevXv1xhtvKDg42LTbrFevXg9VI/DfQkNDNWvWLK1fv14Gg0HXrl3T/v37lZqaqm7duqWr79miRQstW7ZMx48f1wsvvKCaNWsqNTVVx48fl62trTp06GBKJt7Lz89PHh4eOnnypNq1aycvLy8VKlRI5cqVM+36y0znzp116NAhrV+/Xh06dFBgYKBcXV114sQJ/fHHH3rqqac0Y8YMubi45NpzyczQoUN1/Phx7d69Wy1btlStWrX09NNP6/Dhw/rzzz/l7Oysjz76KMcvc7vXvn37dOHCBdnZ2ZklYTJSqVIlVatWTSdOnNC6detMyeznn39en332mXr06KHatWubXt4zatQoFStWTM8884y8vb11/PhxtW7dWt7e3ipcuLCKFSumUaNGycXFRa+88oq++OIL9ejRQwEBAfLw8NAff/yhEydOaMCAAfrkk0/SxWNtba158+apV69e+vnnn9W4cWPVrFlTzs7Ounr1qk6fPi0nJyft2LHjvvdVu3ZtLV26VH369NHkyZP1zz//qG/fvjl8og8WGhqqPXv2SJLatWtnel6ZCQkJ0dmzZ/Xcc8+pVq1asrKy0r59+xQTE6OyZcuaXiSWpkSJEvr44481ZMgQffDBB/r0009VqVIlubu76/bt2zp37pwuXrwoPz8/tWnTRlLOPj/up2HDhrK1tdWePXuUkpKS6zWJ72VjY6OBAwdq6tSpGjNmjL766is9++yz+vPPP3Xo0CG9+OKL2r9/f5792X9eKlGihCZNmqSxY8dq8uTJWrVqlSpVqmT6DO3Ro4c+++yzbCUxjUajtm/fru3bt8vR0VFVq1aVu7u74uLidP78eVNpkLp166p///5mY0eOHKlr165p48aNatu2rSpXrqxnn31WNjY2unLlik6fPq24uDgtXrzYbMfrgz4j0uzatUuS1KRJkxw/MwDA44fELAAAyHUHDx401fIsUqSIHBwc5OXlJW9vb7Vo0UK+vr7Zmi8kJES3b9/W/v37deHCBR05ckRPPfWUSpQoob59++qVV14x+7NUSerSpYv++ecfff/99woPD1dCQoKkuy9Gys3EbNOmTdWkSRMtXLjQtCuvatWqevXVV9WuXbt0/W1tbfX555/ro48+0rZt27Rz5065uLioadOmGjZsWKa7xOzs7LRkyRLNnj1bhw8f1unTp5WamqqgoKAHJmatrKw0ffp0NWjQQKt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          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1500x1200 with 2 Axes>"
            ],
            "image/png": 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\n"
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          "text": [
            "\n",
            "Columns with only ONE unique value (constant features):\n",
            "['num_outbound_cmds']\n",
            "\n",
            "Descriptive statistics for constant features:\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "                   mean  std  min  max\n",
              "num_outbound_cmds   0.0  0.0  0.0  0.0"
            ],
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              "                                                    [key], {});\n",
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              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
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              "summary": "{\n  \"name\": \"    print(\\\"No constant features found\",\n  \"rows\": 1,\n  \"fields\": [\n    {\n      \"column\": \"mean\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0.0,\n        \"max\": 0.0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"std\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0.0,\n        \"max\": 0.0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"min\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0.0,\n        \"max\": 0.0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"max\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0.0,\n        \"max\": 0.0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "It tells taht if we try to find correlation using this our correlation will be undefined.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_6sEAnwOm_-m",
        "outputId": "af049ebf-f88e-4787-989d-9ee68c36fe68"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Training labels: {'portsweep', 'smurf', 'warezmaster', 'perl', 'guess_passwd', 'multihop', 'teardrop', 'ipsweep', 'spy', 'warezclient', 'land', 'nmap', 'rootkit', 'loadmodule', 'imap', 'normal', 'neptune', 'ftp_write', 'pod', 'phf', 'satan', 'buffer_overflow', 'back'}\n",
            "Test labels: {'mailbomb', 'portsweep', 'smurf', 'warezmaster', 'perl', 'xlock', 'guess_passwd', 'multihop', 'ipsweep', 'teardrop', 'httptunnel', 'warezclient', 'named', 'snmpguess', 'land', 'ps', 'sendmail', 'saint', 'mscan', 'xsnoop', 'xterm', 'nmap', 'rootkit', 'processtable', 'loadmodule', 'imap', 'normal', 'neptune', 'snmpgetattack', 'pod', 'phf', 'ftp_write', 'satan', 'buffer_overflow', 'back', 'apache2'}\n",
            "\n",
            "\n",
            "Missing in test: {'spy'}\n",
            "Missing in train: {'mailbomb', 'httptunnel', 'xterm', 'named', 'processtable', 'snmpguess', 'ps', 'sendmail', 'snmpgetattack', 'saint', 'mscan', 'xlock', 'xsnoop', 'apache2'}\n",
            "\n",
            " Categorical columns: ['protocol_type', 'service', 'flag']\n",
            "Number of numerical columns: 38\n",
            "\n",
            " Pipeline for Preprocessor (ColumnTransformer) created.\n"
          ]
        }
      ],
      "source": [
        "# ============================================\n",
        "# 1. DEFINE TARGET AND FEATURES\n",
        "# ============================================\n",
        "\n",
        "# Select the target column (attack labels)\n",
        "target_col = 'labels'\n",
        "\n",
        "# Split the training data into features (X_train) and labels (y_train)\n",
        "X_train = df_train.drop(columns=[target_col])\n",
        "y_train = df_train[target_col]\n",
        "\n",
        "# Split the test data into features (X_test) and labels (y_test)\n",
        "X_test = df_test.drop(columns=[target_col])\n",
        "y_test = df_test[target_col]\n",
        "\n",
        "# ============================================\n",
        "# 2. CHECK OVERLAP OF LABELS BETWEEN TRAIN & TEST\n",
        "# ============================================\n",
        "\n",
        "# Get all unique labels present in the training and testing sets\n",
        "train_labels = set(y_train.unique())\n",
        "test_labels = set(y_test.unique())\n",
        "\n",
        "print(\"Training labels:\", train_labels)\n",
        "print(\"Test labels:\", test_labels)\n",
        "print(\"\\n\")\n",
        "\n",
        "# Labels that appear only in the test set (unseen during training)\n",
        "extra_in_test = test_labels - train_labels\n",
        "\n",
        "# Labels that appear only in the training set but not in the test set\n",
        "missing_in_test = train_labels - test_labels\n",
        "\n",
        "print(f\"Missing in test: {missing_in_test}\")\n",
        "print(f\"Missing in train: {extra_in_test}\")\n",
        "\n",
        "# NSL-KDD is designed this way on purpose.\n",
        "# Some attacks appear only in the test set to mimic real-world unseen attacks.\n",
        "\n",
        "#  Create a combined sorted list of all labels from both sets\n",
        "all_labels = sorted(list(train_labels.union(test_labels)))\n",
        "\n",
        "# =============================\n",
        "# 3. DEFINE CATEGORICAL & NUMERICAL COLUMNS\n",
        "# ==============================\n",
        "# Identify the categorical columns that store string values.\n",
        "# These must be encoded before they can be used by machine-learning models.\n",
        "\n",
        "categorical_cols = ['protocol_type', 'service', 'flag']\n",
        "\n",
        "# All remaining columns are treated as numeric features\n",
        "numeric_cols = [col for col in X_train.columns if col not in categorical_cols]\n",
        "\n",
        "print(\"\\n Categorical columns:\", categorical_cols)\n",
        "print(\"Number of numerical columns:\", len(numeric_cols))\n",
        "\n",
        "# ============================================\n",
        "# 4. BUILD PREPROCESSOR (ENCODER + SCALER)\n",
        "# ============================================\n",
        "# Create a ColumnTransformer that:\n",
        "# - Applies OneHotEncoder to categorical features\n",
        "# - Applies StandardScaler to numerical features\n",
        "# This ensures both types of data are preprocessed correctly before training.\n",
        "preprocessor = ColumnTransformer(\n",
        "    transformers=[\n",
        "        (\"cat\", OneHotEncoder(handle_unknown=\"ignore\"), categorical_cols),\n",
        "        (\"num\", StandardScaler(), numeric_cols)\n",
        "    ]\n",
        ")\n",
        "\n",
        "print(\"\\n Pipeline for Preprocessor (ColumnTransformer) created.\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {
        "id": "_S24lIrSAO-o"
      },
      "outputs": [],
      "source": [
        "def encode_labels(y_train, y_test):\n",
        "    \"\"\"\n",
        "    Encode string labels into two formats:\n",
        "      - Sparse labels: global label space (0..n_classes-1) for evaluation\n",
        "      - Dense labels: consecutive labels (0..num_classes_xgb-1) needed specially for XGBoost\n",
        "\n",
        "    Parameters:\n",
        "      y_train, y_test: original string labels\n",
        "\n",
        "    Returns:\n",
        "      y_train_sparse, y_test_sparse: global encoded labels\n",
        "      y_train_xgb                       -> dense labels for XGBoost\n",
        "      le                                 -> fitted LabelEncoder\n",
        "      sparse_to_dense, dense_to_sparse  -> mapping dictionaries\n",
        "      num_classes_xgb                   -> number of classes seen in training\n",
        "    \"\"\"\n",
        "\n",
        "    # Combine all labels from train and test so that LabelEncoder learns every class\n",
        "    all_labels = pd.concat([y_train, y_test], axis=0)\n",
        "    le = LabelEncoder()\n",
        "    le.fit(all_labels)\n",
        "\n",
        "    # Convert string labels into integer labels using the global encoder\n",
        "    y_train_sparse = le.transform(y_train)    # includes all possible classes\n",
        "    y_test_sparse  = le.transform(y_test)\n",
        "\n",
        "    # XGBoost only supports label values that are consecutive (0..n_classes_in_train-1)\n",
        "    # So we create a mapping from sparse global labels -> dense XGBoost labels\n",
        "    unique_train_labels = np.unique(y_train_sparse)\n",
        "    sparse_to_dense = {s: d for d, s in enumerate(unique_train_labels)}  # old -> new\n",
        "    dense_to_sparse = {d: s for s, d in sparse_to_dense.items()}         # new -> old\n",
        "\n",
        "    # Create dense labels for XGBoost training (only train labels are remapped)\n",
        "    y_train_xgb = np.array([sparse_to_dense[s] for s in y_train_sparse])\n",
        "    num_classes_xgb = len(unique_train_labels)\n",
        "\n",
        "    # Return everything needed for training and reverse-mapping predictions later\n",
        "    return (y_train_sparse, y_test_sparse,\n",
        "            y_train_xgb, le, sparse_to_dense, dense_to_sparse,\n",
        "            num_classes_xgb)\n",
        "\n",
        "\n",
        "# Calling the encoding fucntion\n",
        "y_train_sparse, y_test_sparse, y_train_xgb, le, sparse_to_dense, dense_to_sparse, num_classes_xgb = \\\n",
        "    encode_labels(y_train, y_test)\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "metadata": {
        "id": "ZuaxNlpdxPVt"
      },
      "outputs": [],
      "source": [
        "# ============================================================\n",
        "# Creating Pipelines for XGBoost and Random Forest\n",
        "# ============================================================\n",
        "# A Pipeline allows preprocessing (encoding + scaling) and the model\n",
        "# to run together in one unified workflow. This ensures that the same\n",
        "# transformations are consistently applied during training, testing,\n",
        "# and hyperparameter tuning, preventing data leakage and errors.\n",
        "\n",
        "# ---------------------------\n",
        "# XGBoost Pipeline\n",
        "# ---------------------------\n",
        "gb_pipeline = Pipeline(steps=[\n",
        "    (\"preprocessor\", preprocessor),    # Apply One-Hot Encoding + Standard Scaling\n",
        "    (\"clf\", XGBClassifier(\n",
        "        tree_method=\"hist\",            # Efficient histogram-based tree building (faster training)\n",
        "        predictor=\"auto\",              # Automatically selects the best predictor for the system\n",
        "        random_state=42,               # Ensures reproducible results\n",
        "        verbosity=2,                   # Shows training progress in detail\n",
        "        num_class=num_classes_xgb      # Number of classes XGBoost should expect (dense label format)\n",
        "    ))\n",
        "])\n",
        "\n",
        "# ---------------------------\n",
        "# Random Forest Pipeline\n",
        "# ---------------------------\n",
        "rf_pipeline = Pipeline(steps=[\n",
        "    (\"preprocessor\", preprocessor),    # Apply the same preprocessing to ensure fairness in comparison\n",
        "    (\"clf\", RandomForestClassifier(\n",
        "        random_state=42,               # Ensures results can be reproduced\n",
        "        n_jobs=-1,                     # Use all available CPU cores for faster training\n",
        "        verbose=2                      # Print progress messages during training\n",
        "    ))\n",
        "])\n"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def fit_with_timing(model, X_train, y_train, name=\"Model\"):\n",
        "    \"\"\"\n",
        "    Train a given model and measure how long the training process takes.\n",
        "\n",
        "    This function fits the model on the training data, records the start\n",
        "    and end time, and calculates the total training duration in seconds.\n",
        "    It is helpful for comparing the computational efficiency of different\n",
        "    algorithms such as Random Forest and XGBoost.\n",
        "\n",
        "    Parameters:\n",
        "        model : sklearn estimator or Pipeline\n",
        "        X_train : The training feature set.\n",
        "        y_train : The training labels.\n",
        "        name : str, optional\n",
        "            A friendly name used when printing the training time.\n",
        "\n",
        "    Returns:\n",
        "        fitted_model : The model after being fitted on the training data.\n",
        "        train_time : Total time taken (in seconds) to train the model.\n",
        "    \"\"\"\n",
        "\n",
        "    # Record the start time before training\n",
        "    start = time.time()\n",
        "\n",
        "    # Fit the model using the given training data\n",
        "    fitted_model = model.fit(X_train, y_train)\n",
        "\n",
        "    # Record the end time after training completes\n",
        "    end = time.time()\n",
        "\n",
        "    # Calculate total training time\n",
        "    train_time = end - start\n",
        "\n",
        "    # Print the training duration in a readable format\n",
        "    print(f\"{name} training time: {train_time:.2f} seconds\")\n",
        "\n",
        "    # Return the trained model and the time taken\n",
        "    return fitted_model, train_time\n",
        "\n"
      ],
      "metadata": {
        "id": "ZwJInoPbDUu6"
      },
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "metadata": {
        "id": "GoSrARqsDMAQ"
      },
      "outputs": [],
      "source": [
        "def evaluate_model(model, X_test, y_test_sparse, dense_to_sparse_map, le_original, name=\"Model\"):\n",
        "    \"\"\"\n",
        "    Evaluate a trained model on the test set and measure prediction time.\n",
        "\n",
        "    This function:\n",
        "      - Measures how long the model takes to make predictions (computational efficiency)\n",
        "      - Converts predictions back into the original label format\n",
        "      - Computes standard evaluation metrics: accuracy, precision, recall and F1-score\n",
        "      - Prints a full classification report\n",
        "      - Displays a confusion matrix heatmap for detailed error analysis\n",
        "\n",
        "    Parameters:\n",
        "        model : The trained model being evaluated.\n",
        "        X_test : Test features.\n",
        "        y_test_sparse : True labels encoded using the global LabelEncoder.\n",
        "        dense_to_sparse_map : Mapping that converts dense labels back to sparse global labels.\n",
        "        le_original : The global LabelEncoder used earlier for decoding labels back to strings.\n",
        "        name : Name displayed in printed outputs (default: \"Model\").\n",
        "\n",
        "    Returns:\n",
        "        dict :\n",
        "            A dictionary containing accuracy, precision, recall, F1-score,\n",
        "            and the prediction time (seconds). These values can later be used\n",
        "            for model comparison.\n",
        "    \"\"\"\n",
        "\n",
        "    # -----------------------------------------------------------\n",
        "    # Measure prediction time (important for efficiency comparison)\n",
        "    # -----------------------------------------------------------\n",
        "    start_pred = time.time()\n",
        "    y_pred_dense = model.predict(X_test)\n",
        "    end_pred = time.time()\n",
        "    pred_time = end_pred - start_pred\n",
        "    print(f\"{name} prediction time on test set: {pred_time:.4f} seconds\")\n",
        "\n",
        "    # -----------------------------------------------------------\n",
        "    # Convert dense predictions back to sparse labels\n",
        "    # (These are the global label IDs used for evaluation)\n",
        "    # -----------------------------------------------------------\n",
        "    y_pred_sparse = np.array([dense_to_sparse_map[d] for d in y_pred_dense])\n",
        "\n",
        "    # Decode both true and predicted labels back into original strings\n",
        "    y_true_names = le_original.inverse_transform(y_test_sparse)\n",
        "    y_pred_names = le_original.inverse_transform(y_pred_sparse)\n",
        "\n",
        "    # -----------------------------------------------------------\n",
        "    # Compute standard evaluation metrics\n",
        "    # macro = each class treated equally (important for imbalance)\n",
        "    # zero_division=0 avoids errors when a class has no predictions\n",
        "    # -----------------------------------------------------------\n",
        "    precision = precision_score(y_true_names, y_pred_names, average='macro', zero_division=0)\n",
        "    recall = recall_score(y_true_names, y_pred_names, average='macro', zero_division=0)\n",
        "    f1 = f1_score(y_true_names, y_pred_names, average='macro', zero_division=0)\n",
        "    acc = accuracy_score(y_true_names, y_pred_names)\n",
        "\n",
        "    # Print classification report\n",
        "    print(f\"\\n================= {name} – Test Performance =================\")\n",
        "    print(\"Accuracy:\", acc)\n",
        "    print(\"\\nClassification Report:\")\n",
        "    report_labels = sorted(list(le_original.classes_))\n",
        "    print(classification_report(\n",
        "        y_true_names, y_pred_names,\n",
        "        labels=report_labels,\n",
        "        zero_division=0\n",
        "    ))\n",
        "\n",
        "    # -----------------------------------------------------------\n",
        "    # Confusion Matrix visualisation\n",
        "    # Shows how each class is being predicted\n",
        "    # -----------------------------------------------------------\n",
        "    cm_labels = sorted(list(le_original.classes_))\n",
        "    cm = confusion_matrix(y_true_names, y_pred_names, labels=cm_labels)\n",
        "\n",
        "    plt.figure(figsize=(12, 10))\n",
        "    sns.heatmap(cm, cmap=\"Blues\",\n",
        "                xticklabels=cm_labels, yticklabels=cm_labels,\n",
        "                fmt='g', annot=True)\n",
        "    plt.title(f\"{name} – Confusion Matrix (Test Set)\")\n",
        "    plt.xlabel(\"Predicted label\")\n",
        "    plt.ylabel(\"True label\")\n",
        "    plt.xticks(rotation=90)\n",
        "    plt.yticks(rotation=0)\n",
        "    plt.tight_layout()\n",
        "    plt.show()\n",
        "\n",
        "    # Return metrics for comparison across models\n",
        "    return {\n",
        "        \"model_name\": name,\n",
        "        \"accuracy\": acc,\n",
        "        \"precision\": precision,\n",
        "        \"recall\": recall,\n",
        "        \"f1_score\": f1,\n",
        "        \"test_pred_time_sec\": pred_time\n",
        "    }\n"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# =============================================================\n",
        "# Train baseline models (before applying any hyperparameter tuning)\n",
        "# =============================================================\n",
        "\n",
        "# This function call will train model and also return the training time with trained mdoel  this is for  Random forest\n",
        "print(\"\\nFitting baseline Random Forest (before hyperparameter tuning)...\")\n",
        "baseline_rf, baseline_rf_train_time = fit_with_timing(\n",
        "    rf_pipeline,          # Random Forest pipeline with preprocessing\n",
        "    X_train,              # Training features\n",
        "    y_train_xgb,          # Dense labels\n",
        "    name=\"Baseline Random Forest\"\n",
        ")\n",
        "\n",
        "# This function call will train model and also return the training time with trained mdoel  this is for XGBoost\n",
        "print(\"\\nFitting baseline XGBoost (before hyperparameter tuning)...\")\n",
        "baseline_xgb, baseline_xgb_train_time = fit_with_timing(\n",
        "    gb_pipeline,          # XGBoost pipeline with preprocessing\n",
        "    X_train,              # Training features\n",
        "    y_train_xgb,          # Dense labels\n",
        "    name=\"Baseline XGBoost\"\n",
        ")\n",
        "\n",
        "\n",
        "# =============================================================\n",
        "# Evaluate baseline models using the evaluation function\n",
        "# =============================================================\n",
        "\n",
        "# Evaluate the baseline Random Forest model on the test set.\n",
        "# This prints accuracy, precision, recall, F1-score and displays a confusion matrix.\n",
        "print(\"\\n--- Baseline Random Forest performance ---\")\n",
        "baseline_rf_metrics = evaluate_model(\n",
        "    baseline_rf,          # Trained Random Forest model\n",
        "    X_test,               # Test features\n",
        "    y_test_sparse,        # True labels (global sparse format)\n",
        "    dense_to_sparse,      # Mapping from dense → sparse labels\n",
        "    le,                   # LabelEncoder to decode labels back to text\n",
        "    name=\"Baseline Random Forest\"\n",
        ")\n",
        "\n",
        "# Evaluate the baseline XGBoost model in the same way.\n",
        "print(\"\\n--- Baseline XGBoost performance ---\")\n",
        "baseline_xgb_metrics = evaluate_model(\n",
        "    baseline_xgb,         # Trained XGBoost model\n",
        "    X_test,               # Test features\n",
        "    y_test_sparse,        # True labels\n",
        "    dense_to_sparse,\n",
        "    le,\n",
        "    name=\"Baseline XGBoost\"\n",
        ")\n",
        "\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "Yx-kPEcGa5dT",
        "outputId": "75601a17-5322-437f-8c4f-39fa021db451"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "Fitting baseline Random Forest (before hyperparameter tuning)...\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "[Parallel(n_jobs=-1)]: Using backend ThreadingBackend with 2 concurrent workers.\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "building tree 1 of 100\n",
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        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "[Parallel(n_jobs=-1)]: Done  37 tasks      | elapsed:    6.4s\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
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            "building tree 40 of 100\n",
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            "building tree 99 of 100\n",
            "building tree 100 of 100\n",
            "Baseline Random Forest training time: 15.17 seconds\n",
            "\n",
            "Fitting baseline XGBoost (before hyperparameter tuning)...\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "[Parallel(n_jobs=-1)]: Done 100 out of 100 | elapsed:   14.0s finished\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[07:00:45] INFO: /workspace/src/data/iterative_dmatrix.cc:56: Finished constructing the `IterativeDMatrix`: (125973, 122, 15368706).\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.12/dist-packages/xgboost/training.py:199: UserWarning: [07:00:45] WARNING: /workspace/src/learner.cc:790: \n",
            "Parameters: { \"predictor\" } are not used.\n",
            "\n",
            "  bst.update(dtrain, iteration=i, fobj=obj)\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Baseline XGBoost training time: 55.35 seconds\n",
            "\n",
            "--- Baseline Random Forest performance ---\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "[Parallel(n_jobs=2)]: Using backend ThreadingBackend with 2 concurrent workers.\n",
            "[Parallel(n_jobs=2)]: Done  37 tasks      | elapsed:    0.1s\n",
            "[Parallel(n_jobs=2)]: Done 100 out of 100 | elapsed:    0.2s finished\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Baseline Random Forest prediction time on test set: 0.2262 seconds\n",
            "\n",
            "================= Baseline Random Forest – Test Performance =================\n",
            "Accuracy: 0.9139017033356991\n",
            "\n",
            "Classification Report:\n",
            "                 precision    recall  f1-score   support\n",
            "\n",
            "        apache2       0.00      0.00      0.00       228\n",
            "           back       0.92      1.00      0.96       227\n",
            "buffer_overflow       1.00      0.41      0.58        17\n",
            "      ftp_write       1.00      0.50      0.67         2\n",
            "   guess_passwd       1.00      0.02      0.04       411\n",
            "     httptunnel       0.00      0.00      0.00        41\n",
            "           imap       1.00      1.00      1.00         2\n",
            "        ipsweep       0.99      1.00      0.99       479\n",
            "           land       1.00      1.00      1.00         2\n",
            "     loadmodule       1.00      0.75      0.86         4\n",
            "       mailbomb       0.00      0.00      0.00        94\n",
            "          mscan       0.00      0.00      0.00       310\n",
            "       multihop       1.00      0.11      0.20         9\n",
            "          named       0.00      0.00      0.00         2\n",
            "        neptune       0.99      1.00      1.00      6654\n",
            "           nmap       0.89      0.99      0.94       206\n",
            "         normal       0.87      0.99      0.93     11245\n",
            "           perl       0.00      0.00      0.00         1\n",
            "            phf       1.00      1.00      1.00         1\n",
            "            pod       0.89      0.94      0.92        35\n",
            "      portsweep       0.96      1.00      0.98       371\n",
            "   processtable       0.00      0.00      0.00       211\n",
            "             ps       0.00      0.00      0.00         9\n",
            "        rootkit       1.00      0.25      0.40         4\n",
            "          saint       0.00      0.00      0.00        93\n",
            "          satan       0.86      1.00      0.92       698\n",
            "       sendmail       0.00      0.00      0.00         8\n",
            "          smurf       0.99      1.00      1.00       540\n",
            "  snmpgetattack       0.00      0.00      0.00        43\n",
            "      snmpguess       0.00      0.00      0.00        99\n",
            "            spy       0.00      0.00      0.00         0\n",
            "       teardrop       0.89      1.00      0.94       104\n",
            "    warezclient       0.76      1.00      0.86       107\n",
            "    warezmaster       0.75      0.01      0.02       279\n",
            "          xlock       0.00      0.00      0.00         4\n",
            "         xsnoop       0.00      0.00      0.00         1\n",
            "          xterm       0.00      0.00      0.00         3\n",
            "\n",
            "       accuracy                           0.91     22544\n",
            "      macro avg       0.53      0.43      0.44     22544\n",
            "   weighted avg       0.87      0.91      0.88     22544\n",
            "\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x1000 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "--- Baseline XGBoost performance ---\n",
            "Baseline XGBoost prediction time on test set: 0.8980 seconds\n",
            "\n",
            "================= Baseline XGBoost – Test Performance =================\n",
            "Accuracy: 0.9140791341376863\n",
            "\n",
            "Classification Report:\n",
            "                 precision    recall  f1-score   support\n",
            "\n",
            "        apache2       0.00      0.00      0.00       228\n",
            "           back       0.70      0.99      0.82       227\n",
            "buffer_overflow       1.00      0.41      0.58        17\n",
            "      ftp_write       1.00      0.50      0.67         2\n",
            "   guess_passwd       1.00      0.02      0.04       411\n",
            "     httptunnel       0.00      0.00      0.00        41\n",
            "           imap       0.67      1.00      0.80         2\n",
            "        ipsweep       0.93      1.00      0.96       479\n",
            "           land       1.00      0.50      0.67         2\n",
            "     loadmodule       1.00      0.75      0.86         4\n",
            "       mailbomb       0.00      0.00      0.00        94\n",
            "          mscan       0.00      0.00      0.00       310\n",
            "       multihop       1.00      0.11      0.20         9\n",
            "          named       0.00      0.00      0.00         2\n",
            "        neptune       0.99      1.00      0.99      6654\n",
            "           nmap       1.00      0.99      1.00       206\n",
            "         normal       0.88      0.99      0.93     11245\n",
            "           perl       1.00      1.00      1.00         1\n",
            "            phf       1.00      1.00      1.00         1\n",
            "            pod       0.89      0.97      0.93        35\n",
            "      portsweep       0.97      1.00      0.98       371\n",
            "   processtable       0.00      0.00      0.00       211\n",
            "             ps       0.00      0.00      0.00         9\n",
            "        rootkit       1.00      0.25      0.40         4\n",
            "          saint       0.00      0.00      0.00        93\n",
            "          satan       0.85      1.00      0.92       698\n",
            "       sendmail       0.00      0.00      0.00         8\n",
            "          smurf       1.00      1.00      1.00       540\n",
            "  snmpgetattack       0.00      0.00      0.00        43\n",
            "      snmpguess       0.00      0.00      0.00        99\n",
            "            spy       0.00      0.00      0.00         0\n",
            "       teardrop       0.89      1.00      0.94       104\n",
            "    warezclient       0.74      1.00      0.85       107\n",
            "    warezmaster       0.75      0.01      0.02       279\n",
            "          xlock       0.00      0.00      0.00         4\n",
            "         xsnoop       0.00      0.00      0.00         1\n",
            "          xterm       0.00      0.00      0.00         3\n",
            "\n",
            "       accuracy                           0.91     22544\n",
            "      macro avg       0.55      0.45      0.45     22544\n",
            "   weighted avg       0.87      0.91      0.88     22544\n",
            "\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x1000 with 2 Axes>"
            ],
            "image/png": 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3biE7OxujRo2SOs1u0KBBUFdX59+nAiX5fv8SRUVF9OjRA6dPnwYAnDx5Eg0aNJC6o9mnPv3zn5WVhYSEBBgYGAAAHj9+XOLtGhsbo2XLliVa19nZGS1btsTcuXOxbNkymJiYYNSoUV98XmJiIgBIvdclec7t27fRs2dP/mi3hIQEfPz4ERYWFnj16hWio6MB5L/Hz58/x6tXr0qc/yWurq5YvHgxGjVqhAsXLmDNmjWws7PD6NGj+e0C+Z9j7du3R40aNaQ+x8zNzZGbmyvzPV+cGjVqSJ3eRgghhE10ehQhhFRy+vr6Uhe+dXBwQN++fbF8+XJ07dqVv8PNlStXsHXrVjx9+lTqeigKCgr8/9vZ2eHIkSNYuHAh1q9fDzMzM9jY2KBHjx78L6ORkZF48eIFf82Fz8XHx3/1a6hfv75UDyD/F7Znz57xX5fVds+fP48rV65AJBIhICAAd+/elflFt1q1akhPT5d57rRp0zBy5EgAshMpBUryfrx9+xZ169aVOYWo4Po5b9++5f9bpUoVmVN8tLS0UKNGDX49ExMT2NrawsPDAz4+PjAxMYG1tTV69epVqjsc5ebmFnnxVFVV1SIv8lvwetLS0kq0nbdv36Jp06ZSEx3A//fDu3fvpMYbNGgg9XXBL/WfXzfmW4wfPx63bt3CoEGD0LRpU/4C1u3bty/yOQU9f/rpJ6lxZWVlNG7cmH+fCpTk+70kevXqhb179yI8PBynTp2CnZ2dTG6BxMREeHh44MyZMzJ/VlJSUkq8zUaNGpV4XWVlZfz+++8YOHAgVFRU8PvvvxfZrzDcZ9d3Ks7r16/BcRw2b96MzZs3F7pOfHw86tWrh2nTpmHy5MmwtbWFSCSChYUF+vTpI3Wh469VpUoVjBgxAiNGjMDHjx9x//59HDp0CH///TdmzpyJAwcOAMj/HHv27FmRn2Nfc9FijuO+an8SQgiRTzRpQwgh35kqVarA1NQUe/bsQWRkJFq1aoW7d+9i0qRJMDY2xpIlS6ClpQUlJSUcO3ZM6mKmqqqq2L9/P4KCgnD16lVcv34dZ86cga+vL/78808oKioiLy8PIpGIv07F5+rXr//VnUtyJ56y2G5qaipWrlwJHR0d7NmzB71798bSpUvh5+cndc2Rn376CeHh4cjOzpYaL80vdYW9H1/rS7+YKSgowM3NDQ8ePMCVK1dw/fp1zJ8/H7t27YKvr2+Jj3wp8P79+yJvJdyvXz+sXr260GUFkxb//PPPV22vpIr6PvmaX+4/l5ubK5XbokULBAQE8N//58+fx4EDBzBlyhRMmzat1Nv5VFndecrAwABNmjTBqlWrEBUVVew1d2bMmIGQkBA4OTmhdevWqFq1KvLy8jBu3Liv2n+fHrFTEjdu3ACQf3RPZGRkie50pKGhASD/iMCSfp4UHBk4duxYdOrUqdB1CiY/jY2NceHCBVy6dAk3b97E0aNHsXv3bixbtgyDBg0q0faKU6tWLVhZWcHKygqOjo64c+cO3r59i4YNGyIvLw8dO3bEuHHjCn1us2bNSryd5ORk/rpDhBBC2EWTNoQQ8h0quDNLwdEi586dg4qKCnbu3Cl15MWxY8dknlulShX+9J958+Zh27Zt2LhxI4KCgmBubo4mTZogPDwcZmZm5fqvvGWx3U2bNiE2NhZbtmyBuro6Fi1ahIkTJ2LXrl2YMGECv17Xrl3x4MEDXLhwAXZ2dt/c/fP3o2HDhggMDERqaqrU0TYRERH88oL/5uXlITIyUuouVnFxcUhOTpa5CKyhoSEMDQ0xc+ZM+Pv7Y/bs2Thz5gwGDRr0VftMS0sLu3btKnRZ3bp1i3xe8+bN0bx5c1y6dAlpaWlfnCxq2LAhnj17hry8PKmjbQr2Q8EFXstCzZo1Cz0i5927dzITCVWrVoWdnR3s7OwgkUgwdepUbNu2Db/88kuht7Yu6BkRESGVJZFIEBUVVaq7IJWUvb09tm7dihYtWqB169aFrpOUlITAwEBMnToVzs7O/HhhpweV5Z/p8PBweHp6on///ggPD8fChQvh7+//xduxF0z+Fdw1rCQK9ruSklKJ9reGhgYGDBiAAQMGIC0tDSNHjoS7uzs/aVNW+0FXVxd37txBbGwsGjZsiCZNmiA9Pf2LHUuy/aioqG86OogQQoh8oGvaEELIdyY7Oxs3b96EkpIS/4u+oqIiFBQUpG6zGxUVJXO72IJrSXyq4BfBglOqevbsiejoaBw+fFhm3czMzEJPKyoL37rdR48e4cCBAxgxYgR0dXUBAN26dYONjQ22bNkidQrLsGHDoKmpCVdXV7x8+VIm62uOTCjs/ejcuTNyc3P52woX8PHxgYKCAjp37gwA/J2Edu/eLbVewYRKwfKkpCSZTp+/bwV3tCnJqUQqKiowNzcv9PGl65lMmzYNiYmJWLhwIXJycmSW37hxA1euXAGQvx9iY2Nx5swZfnlOTg727t2LqlWrwtjY+ItdS6px48Z4+PCh1KmBV65cwfv376XW+/waIcrKymjRogU4jivyekHm5uZQUlLC3r17pd6Ho0ePIiUlpcR3hCqNQYMGwdnZmb/VeWGKOrLn8+8r4P/fJ19zylRhsrOzMW/ePNStWxcLFiyAq6sr4uLi8Pvvv3/xubq6ulBSUsKjR49KvL06derAxMQEvr6+iImJkVn+6WlHn7/H1apVQ5MmTaS+N77mz0tsbCz+/fdfmXGJRILAwECpUxx79uyJkJAQ/lbpn0pOTub/zHxp+ykpKXj9+jXatm37xX6EEELkGx1pQwghldzff//NH5mQkJAAf39/vHr1ChMmTOCP4ujSpQt27dqFcePGwcHBAfHx8Thw4ACaNGkidR0NT09P3L17F126dEHDhg359erXr89f06NPnz44e/YslixZgqCgILRr1w65ubmIiIhAQEAAduzYIXVNl7LyLdvNzc3F4sWLoampiRkzZkgtW7BgAezs7LBixQps27YNQP6/wnt4eGDixIno06cP7O3t+V8k379/j4CAAACy11gBSvZ+WFpawtTUFBs3bsTbt28hFotx8+ZNXLp0CaNHj+Z/wdPW1ka/fv3g6+uL5ORkGBsbIywsDH5+frC2tuYvwuzn54eDBw/C2toaTZo0QVpaGg4fPgx1dXV+AkhVVRUtW7bE2bNn0axZM2hoaKBVq1YQiUTf+M5Is7Ozw7Nnz7Bt2zY8efIEDg4O+PHHH5GYmIjr168jMDAQ69evBwAMGTIEvr6+cHFxwePHj9GwYUOcO3cO9+/fx/z580t02/CSGjRoEM6dO4dx48ahZ8+eeP36Nfz9/WWuF+Tk5ARNTU20a9cOderUQUREBPbt24cuXboU2ad27dr45Zdf4OHhgXHjxsHS0hIvX77EgQMHoKenJ3W797LWsGFDTJ06tdh11NXVYWxsjB07diA7Oxv16tXDzZs3ERUVJbOujo4OAGDjxo2ws7ODkpISunXrVuiFuYtTcP0sHx8fqKurQ1tbG1OmTMGmTZvQo0ePYieyVFRUYGFhgcDAQEyfPr3E21yyZAmGDx+OXr16YfDgwWjcuDHi4uLw4MEDfPjwASdPngSQf3SSiYkJdHR0oKGhgbCwMJw7d46/XtWn+2HlypWwsLCAoqIi7O3tC93uhw8fMGjQIHTo0AFmZmbQ1NREfHw8Tp8+jfDwcIwePZq/bbqTkxMuX76MiRMnol+/ftDR0UFGRgb++ecfnDt3DpcuXULt2rW/+Of11q1b4DiuyNMYCSGEsIMmbQghpJJzc3Pj/19FRQU//fQTli5diqFDh/LjZmZmWLVqFbZv347ff/8djRo1wuzZs/H27VupSRtLS0u8ffsWx44dw8ePH1GrVi2YmJhg6tSp/CkNVapUgaenJ3x8fHDixAlcuHABampqaNSoERwdHdG8eXNBXue3bHfv3r14/Pgx3NzcZH7xbtCgAaZOnYo1a9bgwoULsLGxAQC0bdsWp06dwq5du3Dt2jWcOXMGeXl5qFevHtq3b48VK1YUeqeekrwfVapUwdatW+Hm5oYzZ87g+PHjaNiwIebMmcPfGarAypUr0ahRI/j5+eHixYvQ1NTEL7/8InWai4mJCcLCwnDmzBnExcWhevXq0NfXx7p166RO11m5ciVWrFgBV1dXZGdnw9nZucwnbQBg5syZ6NChA/bu3YuDBw8iKSkJNWrUgIGBAbZs2cL/oqmqqoq9e/di3bp18PPzQ2pqKpo3bw5XV1f079+/TDt16tQJLi4u2LVrF37//Xfo6upi27ZtWLNmjdR6Q4YMgb+/P3bt2oX09HTUr18fjo6OmDx5crH5U6dORe3atbFv3z64urqiZs2aGDx4MH799Vep6yJVlPXr12PFihU4cOAAOI5Dx44dsX37dpnrv+jr62P69Ok4dOgQrl+/jry8PFy6dOmrJm0eP34MLy8vjBw5kp9YBIAJEybg0qVLWLhwIU6fPs3fra4wAwYMwNSpU/H+/ftCJ0cL07JlSxw7dgweHh7w8/NDYmIiateujTZt2mDKlCn8eo6Ojrh8+TJu3rwJiUSCH3/8ETNmzICTkxO/Tvfu3eHo6IjTp0/j5MmT4DiuyEmb5s2bY/78+bh27RoOHDiA+Ph4KCsrQyQSYeXKlRg4cCC/rpqaGvbu3QsvLy8EBATgr7/+grq6Opo1ayb1OQsU/+e14C5Un086EkIIYY8C9y1X5yOEEEIIIaSc5ebmws7ODj179pQ5Ou57FxsbCysrK2zYsAHW1tYVXYcQQsg3omvaEEIIIYQQpigqKmL69Ok4cOBAiW8h/73YvXs3RCIRTdgQQkglQUfaEEIIIYQQQgghhMghOtKGEEIIIYQQQgghRA7RpA0hhBBCCCGEEEKIHKJJG0IIIYQQQgghhBA5RJM2hBBCCCGEEEIIIXKIJm0IIYQQQgghhBBC5NAPFV2AkMJk5giTmyfQzdKqKCgIkksIIeWBPhsJIYSQwqlWot+Y1do6V3SFImWEeFR0BblFR9oQQgghhBBCCCGEyCGatCGEEEIIIYQQQgiRQzRp8x1ycXGBg4NDmWTdunULM2fOhKWlJQwMDGBnZ4cdO3YgOzu7TPKLIpFIsHH9H7DuagGTdvoYMXQQAm/dLPHznzx+hCm/jIOFaXt0NGmHSePH4ln4U5n1xo1xRFtdbZnHlF/GlVtXyi3/XJa6Uq58d01PS8MWDzdMmuCETmYmMNAR44Tf8ULXzcvLw+FDBzC4fx+YtNNHZ3NTjPt5FJ6FhwvS99NuXcxN0VZXGyf/ku32KCwUv69YhuGD+8PYUBdtdbULzTv513GZz0oDHTH/OH3qZKm7fg3KFS6Xpa6s5bLUlXLZ60q5wnZlikIV+X2QItHeId/k0KFDSEtLw7Rp0+Dt7Y2+ffvC3d0dixcvFnS7i+a7YN8eH9g59MIclwVQVFSE86QJuH/v7hef+/TJY4wdNQJRUW8wYdIUTJg4Ba9fR2LcGEe8ehkhs369evWx0nWt1GP02JJP2nxLV8qtmFyWulKufHf9mPgRXls98TIiAiKxuNh1lyycjzWuq9BaRwcu8xfhl0mT0aDBj0hIiBekb0m73fj7GvyOHQWggIaNGhW5Xrv2xjKflatWr0XrNjpQVFSEqalZqbt+DcoVLpelrqzlstSVctnrSrnCdiVEcBz57sydO5ezt7cvk6z4+HiZsa1bt3JisbjQZSWVkV304869h5xIJOK2ee/gxxJTMzkrK2tu0OAhxT43TZLHjXUazxkZGXNvY+K5NEkelybJ4169/cAZGhpyEydP4cfSJHncsOEjuJ529lJjhT2E6CrUPqDcytOVcuW/a1JaFvfmXQyXkc1xd0NCOZFIxB06fExmvb/8T3MikYg7dfZ8ufX9tNud+/nPPXj4qMzn2+t3MVx8cjqXJsnjFi1ZyolEoi9+JhY8PqZkcG3btuVGjfmZmfeMctnvylouS10pl72ulPvtmZWJatupcvsgRaMjbcpBSEgIJk6cCAsLCxgaGqJPnz7466+/+OVBQUEQi8W4du0anJ2dYWhoCAsLC2zbtk0q58WLF5g5cya6dOnCn4r0559/Ii8vT2o9iUSCjRs3wsrKCrq6uujcuTNcXFxkegUFBaFv374wNDTEwIED8ejRI6nlHMdh586dsLW1ha6uLqysrODj4yO1Tu3atWVyW7duDY7jEBsb+5V7qmQung+AoqIiBgwawo+pqKig34CBePggBB/evy/2+SH378LUzAwaGrX4MS2tumhvZIzr164iPT1N5jk5OTmFjgvdlXLLP5elrpQr/12VlZWhqaX1xfX27vaBrp4+rKxtkJeXh/T0dMH7lrRbHU1NqKqqfnUfALh29TLS0tJgb9/rm7qWFOUKl8tSV9ZyWepKuex1pVxhuzJHQUF+H6RINGlTDt69e4d27dph1apV2Lp1K7p3746FCxfCz89Par1FixahcePGcHd3R69evbBx40YcPHiQXx4TE4PmzZtjyZIl8Pb2xuDBg+Hp6YktW7ZI5UydOhU+Pj4YMGAAvL29MWfOHJlfAGJjY7Fy5Uo4OTlh06ZNyMrKgrOzs9S1aFatWgU3Nzf07dsX3t7e6NevH9atWyfVqTD379+HsrIyGhVzGP23CA9/iqZNm0FdXV1qXFdPn19eHIlEAhUVFZlxVTU1ZGdn49/nz6XGI1+9grlxW3Q0aQ/rLhbwdN9c4mv2fGtXyi3/XJa6Ui57XQuTmpqKR2Gh0NHVg9umDeho2h5mxm1hZ2uFcwFn5K7v1zhzyh+qqqqwsrGRGmftPaNctrqylstSV8plryvlCtuVkPJQie46L7/s7e35/+c4DsbGxoiOjoavry/69evHL+vQoQPmzp0LAOjUqRPi4+OxdetWDBkyBFWqVIGZmRnMzMz4nPbt2yMzMxP79u2Ds7MzAODmzZu4evUq1q9fL3Wx4c8vPJyUlIR9+/ahVatWAAA1NTWMGjUKDx8+hJGREV6/fo19+/Zh2bJlGDIkf0ba3NwcmZmZ8PT05Dt97tWrV9izZw+GDh2KatWqlcXukxEbG1vovw5ramr9tzym2Oc3a9YcYaEPkZubC0VFRQBAdrYEYaGhAICYmGh+3UaNm8DYxBQtW4mQkZGBixfOYYfXVrx+9Qpr1m8UvCvlln8uS10pV7hMIXM/9+bNa3Ach3NnT0NR8QfMnPUb1NWrY/++PZg7+1eoV1NHx06d5aZvSSUlJeLmjevoZmWNatWk/5LM2ntGuWx1ZS2Xpa6UK1wm5QqbK28/Iwn5GjRpUw6SkpLg7u6OS5cuITo6Grm5uQAADQ0NqfVsPvuXSFtbW5w4cQIfPnzAjz/+iKysLHh5ecHf3x/v37+XOtojLS0N1apVQ2BgINTU1KQmigpTt25dfsIGAFq2bAkAiI7On7C4desWAKB79+7Iycnh1zM3N8f27dvx/v17NGzYUCozNTUVU6dORaNGjTBz5syS7JpSycrKhLKyssx4wdEzWZmZxT5/0NDh+H3FUixbvACjx44Dl5eH7V7bEPff6VxZmVn8uktXrJJ6rkPvPlixdBGOHz2CEaNGQ9/AUNCulFv+uSx1pVzhMoXM/VzGf0dCJiYmYu/Bw9DXNwAAdO1mCTtbK3h7bS3RpE159S2pi+fPITs7W+bUKIC994xy2erKWi5LXSlXuEzKFTZX3n5GEvI1aNKmHLi4uCAkJARTpkxBy5Ytoa6ujoMHD+Ls2bNS631+fRhNTU0A+TPDP/74I/744w8cOXIEU6ZMga6uLqpXr45Lly5h69atyMrKQrVq1ZCYmAgtLS0ofOG8wBo1akh9raSkBADIysqfsPj48SM4jkOHDh0Kff7nkzYSiQRTpkxBUlISfH19UbVq1RLsmdJRUVGFRCKRGS/orvKFay8MGjIU0R/eY/euP+F/4i8AQBsdXYwZ64Qd3tu+2N1x9M84fvQIgm4HfnHS5lu7Um7557LUlXKFyxQyV3Y7+X9hbNioET9hAwBVq1VD567dcNrfHzk5Ofjhh+J/ZJdX35I6c9ofNWtqFDrhxNp7RrlsdWUtl6WulCtcJuUKmytvPyMrDN1am0k0aSOwrKwsXL16FS4uLnB0dOTHDxw4ILNuQkKC1NdxcXEAAK3/DuULCAjAkCFDMGHCBH6da9euST1HQ0MDsbGx4DjuixM3xalZsyYUFBRw4MABfkLnU82bN+f/Py8vD7Nnz8bjx4+xf/9+NGjQoNTbLQktLS3EREfLjMfFxf63vO4XM5ynz8SoMWPx4sW/UFdXRyuRGO6bNgAAmjRrVuxz69XPf31JSYnl0pVyyzeXpa6UK1ymkLky26mbn1OnjqbMstq16yAnJxsZGRmoXr168Tnl1Lck3r9/h5B79zBg0OBCf4aw9p5RLltdWctlqSvlCpdJucLmytPPSEK+Fk21CUwikSAvL0/qL62pqam4fPmyzLoXLlyQ+vrcuXOoW7cu6tevDyB/AujTnNzcXJw+fVrqOebm5sjIyJA5iudrFVw7JzExEXp6ejKPTy/itWzZMly5cgVbtmyBWCz+pu2WhFhbG5GRr5Camio1Hhb6EACgrd26RDk1atZE23bt0UqU3znodiDq1auP5s1/KvZ5b6PeAABq1ZK9c5ZQXSm3/HJZ6kq57HUtTN269aCpWfhfJmNjY6CiolKia4SVV9+SCDhzGhzHwd6hd6HLWXvPKJetrqzlstSVctnrSrnCdiWkPNCkjcCqV68OPT09bN++HQEBAbh48SLGjh0rc+VyALh9+zbWrFmDGzduYM2aNThx4gQmTpzIX/DX3NwcR44cgZ+fH65evYpJkybJHOZnbm6OLl26YP78+di2bRsCAwNx9uxZzJgx46t6N2/eHCNGjMCcOXOwdetW3Lp1C9euXcPu3bsxefJkfr1t27bh0KFDcHR0hLKyMh48eMA/Pv9QLCvW3XsgNzcXx4748mMSiQQn/I5DT98A9UtxpM+5s2fw+FEYhjuO4vd3amqqzP7lOA7bvfJvxW7e0aJCulKusLksdaVc9roWxbZHT3z48B6Bt27yYx8/JuDq5UswMe1Q6IXfK7Lvl5w9fQr1G/yItu3aF7qctfeMctnqylouS10pl72ulCtsV+ZU9G296ZbfpUKnR5WD9evXY/HixXBxcYGGhgYcHR2Rnp6OP//8U2q95cuXw9fXFwcPHkS1atUwffp0jBgxgl++aNEiLFmyBCtWrICamhr69esHGxsbLFy4UCrH3d0dHh4e8PX1hYeHB+rUqYOOHTt+de+FCxeiefPm8PX1haenJ6pVq4bmzZujR48e/Do3b+b/grFz507s3LlT6vl79uyBqanpV2/3S/T1DdDdtgfcNm1AQnw8GjdpCv8Tfnj37q3MhYMLc+9uMLy3bYGZeUfUrKmBsNCHOPnXcZhbdMLwkaP49cKfPMa8ObNha2eHJk2aIjMzE1cuXcSDkPsYMGgwWrfREbwr5ZZ/LktdKZeNrgf370NKSjJiY/LvTHHt6hVER38AAAwb4Yjq1avDafwvOH/uLGbNmArH0T9DXb06jhw+iJycHEyd/qtgfQu6xUh1yz/iZ+jwkahevTrevXuL0/4nAQBPHj8GAGz32goAaNDgRzj07iOV+e/zf/D8n2f42Wl8kafpyvt7Rrlsd2Utl6WulMteV8oVtish5UGB4ziuokt874KCgjBq1CgcPXoUenp6FV1HLmTmFL88KysLnu6bcNrfH8nJSWglEmPK1OnoaNGp2OflcRzevH4N15XL8PTpE6SnpaFhw0Zw6NMXjqPHQEnp/1eVfxsVhc0b1+HxozDEx8VBoUoVNG/+E/oPHIQBg4ZI/TJSpZjZ4dJ2/RLKFS6Xpa6UK/9de9pY4t27t4UuO3P+Eho2bAQAiHrzBuvXrcGd24HIycmBvoEhps+cBV09fcH6Ftft9LmL+LFhI9y9E4TxY0cXuk57I2Ps8NkrNea2cT127dyOw8dPQCzWLrOuJUW5wuWy1JW1XJa6Ui57XSn32zJVK9FhDmrGJfuHoIqQEbyhoivILZq0kQM0aSPrS5M2pZUn0Ld7cZM2hBAi7+izkRBCCClcpZq0MZld0RWKlHFnXUVXkFt0TRtCCCGEEEIIIYQQOVSJ5g3ZZWpqimfPnlV0DUIIIYQQQgghhMgRmrQhhBBCCCGEEEIqOzptmUl0ehQhhBBCCCGEEEKIHKJJG0IIIYQQQgghhBA5RKdHke9KXp4wuVUUhcklhJDyQHd5IoQQQr4DCnTMBovoXSOEEEIIIYQQQgiRQzRpQ5gkkUiwcf0fsO5qAZN2+hgxdBACb92UWe9RWCh+X7kc/Xrbw9TIEHbdu2Hu7BmIfPWSXycvLw8nTxzHzKmTYGfTFR1N2mJwv17Y4b0VWVlZMpnt9bVlHgY6Yuzc7v1NXYXaB5QrH5mUK2wuS11Zy/38c9TWqit++3U6Xn3yOSovXSlX2FyWurKWy1JXymWvK+UK25UQoSlwHMdVdAlS9lxcXPDo0SOcOnVK8G2JxWLMmTMHTk5OZZaZmVP88rmzf8XFC+cwwnEUmjRphpMn/PD4URi2/7kb7dob8evNmjEND0Luw8a2B0QiMWJiY3H44H6kp6fDZ98htGwlQnp6Gjp1aA89fQN06twNtWrXRljoA5w6+RfatjeC147dUPjk1IH2+towNTOHQ6++/FiVKoB26zZo2bJVqbt+LcoVLpelrpTLXlfWcj//HI2Li8WhA/mfo3sP+qJVK5HcdKVcYXNZ6spaLktdKZe9rpT7bZmqleiCImpmLhVdoUgZgasruoL84kilNHfuXM7e3r5ctiUSibgdO3aUaWZGdtGPO/ceciKRiNvmvYMfS0zN5KysrLlBg4dIrRt45x6XnJbFf52Smcc9fhbB6erqctNnzuJSMvO4hJRM7sbtu1xKZp7UY/0md04kEnEXr96QGheJRNzCxUulxsqi69c8KFe4XJa6Ui57XVnM/fxzNCOb48L/fcnp6upyM36dJVddKVe4XJa6spbLUlfKZa8r5X57ZmWi2mGu3D5I0ej0KMKci+cDoKioiAGDhvBjKioq6DdgIB4+CMGH9+/5ccO27aCkrCz1/CZNm+GnFi3xMuIFAEBJSRkGhu1kttPN0hoA+PU+l5mZWejpU6Xt+jUoV7hclrpSLntdWcwt7HO0adNmaNGyFV5GRMhVV8oVLpelrqzlstSVctnrSrnCdiWkPNCkTSV37do1ODg4QE9PD/3798eDBw/4ZX/99ReGDRsGExMTGBsbw9HREaGhoTIZL168gLOzM0xMTGBgYIDevXsXe9rVmzdvYG1tjXHjxiEzM7PMX1N4+FM0bdoM6urqUuO6evr88uJwHIeE+Hho1KpV7Hrx8XEAAA0N2fX8T/wFC9O2MDc2wMC+9jhzyl+QrkWhXOFyWepKuex1ZTG3MBzHIT4+rtDPx5JgbR9QLltdWctlqSvlsteVcoXtyhyFKvL7IEWqRGfokc/FxsZi2bJlmDp1KmrUqIHt27fDyckJ58+fR506dRAVFYW+ffuiSZMmkEgkOH36NEaMGIGTJ0+iefPmAIBXr15hyJAhaNCgARYsWAAtLS38888/ePfuXaHbjIiIwJgxY2BgYID169dD+bN/nS2r16WppSUzrqmp9d/ymGKff/a0P2JiojFxyrRi19uzayeqqaujo0VnqXEDw7aw7t4TDRs2QmxsDA4f2o95c2cjNTUFg4cOL9OuRaFc4XJZ6kq5wmVSbvFOnzqJmOhoTHYu/nO0KKztA8plqytruSx1pVzhMilX2Nzy/BlJSFmjSZtKLDExEZs2bYKZmRkAwMTEBF26dIGPjw9mzZoFZ2dnft28vDx07NgRoaGh8PPzw6+//goAcHd3h5KSEg4ePMjPTJubmxe6vfDwcIwdOxYWFhZwdXWFoqKiIK8rKyuz0MkgFRWV/OXFHN3z8mUEVv++HPoGhnDo3bfI9f7cvg1Bt2/BZcESVK9RQ3rZnoNSX/fp1x8jhw6E2+aN6N23P1RVVcuka3EoV7hclrpSrnCZlFu0lxEv4LpyOQwM26J3n36lymBtH1AuW11Zy2WpK+UKl0m5wuaW189IQoRAxyFVYtWrV+cnbAq+Njc3x8OHDwHkn/Y0ZcoUmJubo3Xr1tDR0cHLly/x6tUr/jm3b9+Gra2tzKGEnwsLC4OjoyNsbGywZs0awSZsAEBFRRUSiURmvOD6MiqfTJp8Ki42FtOn/AJ19epYu35zkR3PB5zBFo/N6NNvIAYNGfbFPkpKyhg6fARSkpPx5PGjMun6JZQrXC5LXSlXuEzKLVxcbCycJ+d/jq7bWPTn6Jewtg8ol62urOWy1JVyhcukXGFzy+NnJBMUFOT3QYpEkzaVWO3atWXG6tSpg9jYWKSmpmLs2LF49+4dXFxcsH//fhw9ehTa2tpSF9dNTExE3bp1v7itwMBAZGRkYODAgVK3xxaClpYW4mJjZcbj4mL/Wy7bNyUlBZMnjkdqSjI8tm6HVt16hWbfDryJxQvmwqJTF8xftLTEnerXbwAASE5K+uauJUG5wuWy1JVyhcukXFkFn6MpySnY4rUDdYv4HC0J1vYB5bLVlbVclrpSrnCZlCtsrtA/IwkREk3aVGIJCQkyY/Hx8dDS0sKDBw/w4cMHuLq6onfv3jAyMoKenh5SUlKk1tfQ0EBMzJfP8XRycoKlpSXGjRuHZ8+eldlrKIxYWxuRka+QmpoqNR4Wmn8EkbZ2a6nxrKwsTJsyEZGRr7DJYxt+atGy0Nyw0IeYPWMq2ujoYvW6Tfjhh5KfPRj15g0AoNZnE2Vf27WkKFe4XJa6Ui57XVnMBaQ/R923bEOLloV/jlZ0V8oVLpelrqzlstSVctnrSrnCdiWkPNCkTSWWkpKCwMBAqa9v3boFAwMD/q5OSkpK/PL79+/j7du3UhlmZmY4d+6czAfc5xQVFbF+/Xq0bdsWP//8MyJKeRvYkrDu3gO5ubk4dsSXH5NIJDjhdxx6+gao36ABP56bm4s5s2Yg9OEDrNuwGfoGbQvNfBnxAtOdf8GPPzbEJo9tUtel+dTHQibC0tJSsX/vbtSqVQtt2uiUuuvXoFzhclnqSrnsdWUx9/PPUQPDwj9H5aEr5QqXy1JX1nJZ6kq57HWlXGG7Mqei7xBFd48qFboQcSWmoaGBBQsWYNq0aahevTq2b98OjuMwevRoAEDVqlWxbNkyTJgwAdHR0XB3d0e9etKHuzs7O+Pq1asYPnw4xo0bBy0tLbx48QIZGRkYP3681LpKSkpwc3PDxIkTMWbMGOzfvx+NGzcu89elr2+A7rY94LZpAxLi49G4SVP4n/DDu3dvsXTFKql1169djatXLqNL125ISkrEmVMnpZbbOfRGWloqpkwch5TkZIwa44Qbf1+TWqdR48b8ZM/hQ/tx9coldOrSDfXrN0BcXCxO/nUMH96/x6rVa6H02QXOvqarUPuAcis+k3KFzWWpK4u5n3+OnvI/IbXcoVcfuelKucLlstSVtVyWulIue10pV9iuhJQHBY7juIouQcqei4sLHj16hNmzZ2Pt2rV4/fo1WrVqhUWLFqFdu3YAgL///ptf1qxZM8yaNQs7duxA1apV4eXlxWf9+++/WL9+Pe7cuYPc3Fw0a9YMEyZMgJ2dHQBALBZjzpw5cHJyAgB+Qufdu3fYv38/GpRi5jozp/jlWVlZ8HTfhNP+/khOTkIrkRhTpk5HR4tOUus5jXHE3eA7RebcCw3Hu7dR6NXTush1HHr3xbKVqwHkX/Nmj89O/Pv8OZISE6GmpgYdPT2MdRoP0w5m39T1a1GucLksdaVc9rqylvulz9GHj0t3SixL+4By2evKWi5LXSmXva6U+22ZqpXoMAc1i0UVXaFIGTdWVHQFuUWTNkQufWnSprRycoX5dv9Bka54TgghhBBCSGVTqSZtOi2u6ApFyri+vKIryC06eYwQQgghhBBCCCFEDtGkDSGEEEIIIYQQQogcqkQHexFCCCGEEEIIIaRQdJcmJtG7RgghhBBCCCGEECKHaNKGEEIIIYQQQgghRA7R6VHku0J3eSKEEEIIIYR8l+j0KCbRu0YIIYQQQgghhBAih2jShjBJIpFg4/o/YN3VAibt9DFi6CAE3ropl7mL5rvAQEdc5CM6OlpuulIue10pl72u8pybnpaGLR5umDTBCZ3MTGCgI8YJv+OFrhvx4gUmTXBCB6O26GRmgvkuvyEhIaHculJu+eey1JW1XJa6Ui57XSlX2K6ECE2uJm1cXFzg4OBQJlmPHz/G4MGDYWBgALFYjOTkZEgkEsybNw8dOnSAWCyGj49PmWyLFWvXroWFhQW0tbWxatUqHD9+HGKx+Kv+ki0vFs13wb49PrBz6IU5LgugqKgI50kTcP/eXbnLHTh4CFatXiv1WOm6BqpqavipRUvUq1dPbrpSLntdKZe9rvKc+zHxI7y2euJlRAREYnGR60V/+ICxo0fgzevXmDpjJkb/PBbXr13DxHE/I1siKZeulFv+uSx1ZS2Xpa6Uy15XyhW2K1OqKMjvgxSNkyNz587l7O3tyyRr6NChXP/+/bnAwEAuJCSEy8nJ4Q4fPsy1bt2aO3HiBBcSEsLFxMSUybZYcPPmTU4kEnG7du3i7t+/z0VFRXHHjh3jRCIRFx8fX9H1ZGRkF/24c+8hJxKJuG3eO/ixxNRMzsrKmhs0eEixz62I3MIeN28HcyKRiHP33CpXXSmXra6Uy15Xec9NSsvi3ryL4TKyOe5uSCgnEom4Q4ePyay3cNESTl9fn4uIfMuPXfk7/+fM3v2HmN4HlMt+V9ZyWepKuex1pdxvz6xMVLsul9sHKZpcHWlTliIiItC5c2d06NABhoaGUFRUREREBOrWrYvevXvD0NAQWlpapc7PzMwsw7bCKegZEREBABg1ahTatm2Lhg0bVmStb3LxfAAUFRUxYNAQfkxFRQX9BgzEwwch+PD+vVzlFubs6VNQUFBAT/vSHVnG2j5gKZelrpTLXld5z1VWVoZmCX42Xrx4Hp27dEWDH3/kxzqYmaNps2Y4f+5suXSl3PLNZakra7ksdaVc9rpSrrBdCSkPcjlpc+3aNTg4OEBPTw/9+/fHgwcP+GVisRg7d+6UWt/Hxwfi/w7jDgoKglgsRmJiIrZs2QKxWAxHR0dYWlrizz//xPv37yEWiyEWixEVFQUAePHiBSZNmoT27dvD0NAQEyZMwOvXr6W2IRaL4e3tjT/++AMdO3aEmZlZiV5LVlYWXF1dYWFhAT09PfTp0wcXLlzglx8/fhxt2rRBXFyc1PMSExOhq6uLQ4cO8WMhISEYNWoUDA0N0b59e8yaNQvx8fH88qioKIjFYhw/fhwLFy6EqakpBg0aBEdHR6xYsQIA0Lp1a4jFYgQFBRXaNzExEfPmzYOpqSn09fUxdOhQBAcH88v/+usv6OrqSk1a9erVC23atEFqaio/NmTIECxbtqxE++hrhYc/RdOmzaCuri41rqunzy+Xp9zPZWdn4/y5szAwbIuGDRuVKoO1fcBSLktdKZe9rizmfi46OhoJ8fFoo6Mrs0xXTx/hT7+8Hdb2AeWy1ZW1XJa6Ui57XSlX2K7MUagivw9SJLnbO7GxsVi2bBmcnJywadMmKCsrw8nJSWpyojg6Ojrw9fVF1apVMXDgQPj6+mLJkiXw8PCAnZ0dtLS04OvrC19fX9StWxdv3rzB0KFDkZSUhNWrV2PdunVISEjAmDFjIPnsvPw9e/bg1atXWLVqFf74448S9Zk9ezZ8fX0xbtw4eHp6omXLlpg6dSouXboEALCxsYGioiICAgKknnf+/HkAQI8ePQDkT9g4OjqievXq2LhxI1asWIGwsDBMnjxZZpsbNmwAx3FYv349fvvtNyxZsgSjR48GAP616+joyDwvNzcX48ePx5UrVzB79mxs3rwZVatWxc8//4xHjx4BAIyNjZGdnc1PpH38+BHPnz/HDz/8gHv37gEAMjIy8PjxYxgbG5doH32t2NjYQv8lWFNT67/lMXKV+7lbN28gMTER9g69Sp3B2j5gKZelrpQrXCblFi3uv5zCtqWlqYWkpESZn5+fY20fUC5bXVnLZakr5QqXSbnC5pbXz0hChPBDRRf4XGJiIjZt2sQfyWJiYoIuXbrAx8cHs2bN+uLz1dXV+dOh6tevD0NDQ36ZpqYmlJWVpcY8PDxQs2ZN7Nq1CyoqKgCAdu3awcrKCkeOHMGIESP4dWvWrAkPDw8oKJTsQknh4eE4f/48li1bhqFDhwIAOnfujLdv38LT0xNWVlaoXr06unTpglOnTmHkyJH8c0+dOoWOHTtCQ0MDALB+/Xro6upKbV8kEsHBwQHXrl1Dly5d+OcWXGj4Uz/+dwj7p6/9c1evXkVoaCh27NiBTp06AQAsLCzQvXt3eHl5wd3dHQ0bNsSPP/6Iu3fvokOHDrh37x7q1q0LfX19BAcHo0uXLggJCUF2djaMjIxKtJ++VlZWJpSVlWXGC96/rFKeuiZU7ufOnj6FH35QQvcePUudwdo+YCmXpa6UK1wm5Ra3nSwAKHRbyv9tKzOz8C7/z2BrH1AuW11Zy2WpK+UKl0m5wuaW189IQoQgd0faVK9eXerUo+rVq8Pc3BwPHz4UZHs3b96EpaUlFBUVkZOTg5ycHNSoUQNt2rThjy4p0Llz5xJP2ADgjzwpOFqmQM+ePfHkyROkp6cDAOzt7fHgwQO8e/cOABATE4Pg4GDY29sDyD9y5f79++jRowdyc3P5ns2aNUODBg0QFhYmld+1a9ev2gcF7t69C3V1dX7CBgCUlJRgY2PDvxYAMDIy4k+ZCg4OhrGxMYyNjaXGmjZtirp165aqx5eoqKgW+q+4Bb9IqKiqylXup9LT0nDlyiWYd7SAhkatUuewtg9YymWpK+UKl0m5xW0n/y+4hW1L8t+2VL+wLdb2AeWy1ZW1XJa6Uq5wmZQrbG55/YyUewoK8vsgRZK7SZvatWvLjNWpUwexsbGCbO/jx4/YvXs3dHR0pB53797F+88uSFWnTp2vyk5KSoKSkhJ/tEwBTU1NcByHlJQUAEC3bt2gpqaG06dPAwDOnj0LFRUVWFtbAwCSk5ORm5sLV1dXmZ7v3r375p4FkpOTC32upqYmkpKS+K9NTEzw8OFDZGdnIzg4GEZGRjA2Nsbjx4+RkZGBu3fvCnaUDQBoaWkhrpDvh7i42P+Wl26ySKjcT12+fBGZGRmw+4ZTo/K7sLUPWMplqSvlCpdJuUXT/C+nsG3FxsWiZk2NYo+yye/C1j6gXLa6spbLUlfKFS6TcoXNLa+fkYQIQe4mbRISEmTG4uPj+Ts9KSsrIzs7W2p5cnJyqbdXs2ZN9O/fH0ePHpV5LF68WGrdrznKpiA7OztbasIDAOLi4qCgoIDq1asDyP8XSWtra5w5cwYAcObMGXTr1g1Vq1YFkH+0kYKCAiZOnFhoz0mTJn1Tz0/7FnbtoLi4ONSsWZP/2sjICBkZGQgKCkJ4eDiMjY2hra0NVVVVBAUF4eHDh4JO2oi1tREZ+UrqwscAEBaafzSWtnZrucr91JlT/qhatSq6drP8phzW9gFLuSx1pVz2urKY+7l69eqhVu3aePL4kcyyR2GhEGtrV1hXyhUul6WurOWy1JVy2etKucJ2JaQ8yN2kTUpKCgIDA6W+vnXrFgwMDAAA9evXx4sXL6Sec+vWrVJvz8zMDM+fP0ebNm2gp6cn9fjpp59KnQsA7du3BwCZiwwHBASgTZs2/KQMADg4OODJkye4fv06Hjx4wJ8aBQBVq1aFoaEhIiIiZDrq6emhUaPS3YGosL6pqam4ceMGP5aTk4OLFy/yrwUAmjdvDi0tLXh5eaFmzZpo2bIlqlSpgvbt22Pnzp3IysoS7CLEAGDdPf80sWNHfPkxiUSCE37HoadvgPoNGshVboGEhAQE3Q6EpbUN1NTUvimLtX3AUi5LXSmXva4s5ha6LZvu+PvaValbpAbdDkTkq1ewse1RzDOF7Uq5wuWy1JW1XJa6Ui57XSlX2K6ElAe5uxCxhoYGFixYgGnTpqF69erYvn07OI7j735ka2uL3bt3Q09PD82bN8fJkycRHR1d6u1NmzYNAwcOhJOTEwYPHgxNTU3ExcXhzp07MDIygoODQ6mztbW10b17d6xevRqZmZl835CQEGzZskVqXXNzc2hoaGD+/PmoUaMGOnfuLLV8zpw5GD16NGbMmAF7e3vUqFEDHz58wK1bt9C/f3+YmpqWumeBrl27Ql9fH7/99htmzZoFTU1N7N27FzExMXBzc5Nat3379ggICED37t35MSMjI6xbtw7169dH48aNv7lPUfT1DdDdtgfcNm1AQnw8GjdpCv8Tfnj37i2Wrlj15YByzi1w7uwZ5OTkwM7+206NErIr5bLVlXLZ68pC7sH9+5CSkozYmPw7aVy7egXR0R8AAMNG5N/FcNz4ibhwLgDjfh6F4Y6jkJGeDp8/d6KVSIS+/QaUW1fKLb9clrqylstSV8plryvlCtuVOXRrbSYpcBzHVXSJAi4uLnj06BFmz56NtWvX4vXr12jVqhUWLVqEdu3aAQDS09OxYsUKXL58GQoKChgyZAg0NDSwevVqPHv2jM8yMjLC6NGjMXXqVH5s1apVuHTpEi5fviy13VevXmHTpk0IDAxEeno6tLS0YGxsjHHjxqFVq1YAALFYjDlz5sDJyemrXlNmZiY2bNiAM2fOIDExET/99BOcnZ2lJjsKLF68GL6+vhg4cKDM3Z8AICwsDO7u7rh//z6ys7NRv359dOjQAZMmTUL9+vURFRUFKysrbN68Webixz4+PnB1dZXaR8ePH8e8efMQGBjIX0vo48ePWLt2LS5fvoz09HTo6Ojg119/hYmJiVTe/v37sXz5csyfP5+fUHv48CEGDx4MBwcHrF+//qv2k8x+yyl+eVZWFjzdN+G0vz+Sk5PQSiTGlKnT0dGiU/FP/AKhcgHAcfgQREW9wcUr16GoqPjNeaztA5ZyWepKuex1lffcnjaWePfubaHLzpy/hIYN84/u/Pff51i3ZjVCQu5BSUkJnTp3wezfXFBHU7PculJu+eay1JW1XJa6Ui57XSn32zJV5e4wh9JTs15d0RWKlHHRpaIryC25mrQhpMCXJm0IIYQQQgghRGg0aVM+aNKmaJXoW5AQQgghhBBCCCGFoltrM4kmbb5BTk7Rh4MoKCiUySkwhBBCCCGEEEII+T7RpE0pFVw/pigmJibYu3dvOTYihBBCCCGEEEJIZUKTNqVUt25dHD16tMjl1apVK8c2hBBCCCGEEEJIMejuUUyiSZtSUlZWhp6eXkXXIIQQQgghhBBCSCVFU22EEEIIIYQQQgghcoiOtCGEEEIIIYQQQio7unsUk+hIG0IIIYQQQgghhBA5RJM2AvPx8UHXrl3RunVrGBkZYdu2bRVd6YuCgoIgFosRFhbGj7m7u+P+/fsV2EqaRCLBxvV/wLqrBUza6WPE0EEIvHVTLnOF6pqeloYtHm6YNMEJncxMYKAjxgm/49+cy9K+FSqXpa6Uy15X1nLps4ZyWezKWi5LXSmXva6UK2xXQoRGkzYCevXqFVavXo1evXph//796NKlC7y8vCq61hfp6OjA19cXLVq04Mc8PDwQEhJSga2kLZrvgn17fGDn0AtzXBZAUVERzpMm4P69u3KXK1TXj4kf4bXVEy8jIiASi78p61Ms7VuhclnqSrnsdWUtlz5rKJfFrqzlstSVctnrSrnCdmWKQhX5fZCicUQwly9f5kQiEff69WuO4zjOzc2NMzQ0rOBWRcvLy+OysrIKXSYSibgdO3aUW5eM7KIfd+495EQiEbfNewc/lpiayVlZWXODBg8p9rnlnStU14xsjktKy+LevIvhMrI57m5IKCcSibhDh499UyZL+5a194xy6T1jNZc+ayiXta6s5bLUlXLZ60q5355ZmajarpfbBykaTWkJxMXFBRMnTgQAWFtbQywWw8PDA+np6RCLxRCLxXB0dASQf+pR27ZtERoaioEDB0JPTw89e/bElStXSry90aNH47fffuO/fvToEcRiMaZNm8aPRUREQCwWIzQ0lO/o4OCAa9euoXfv3tDT08Ply5dlTo8S//cvq2vXruW7BwUFAQA4jsPOnTtha2sLXV1dWFlZwcfHp/Q7rgQung+AoqIiBgwawo+pqKig34CBePggBB/ev5ebXKG6Avm3ndfU0ir18wvD0r4VKpelrpTLXlcWc+mzhnJZ68paLktdKZe9rpQrbFdCygNN2ghk8uTJmD17NoD8U4v279+PAQMGQFVVFb6+vvD19cWSJUv49bOzszFz5kz069cPHh4eaNq0KZydnfHs2bMSbc/Y2Bh37/7/0L7g4GCoqKjg3r17UmNVq1aFjo4OPxYTE4OVK1dizJgx2L59O1q3bi2T7evrCwBwdHTkuxdkrFq1Cm5ubujbty+8vb3Rr18/rFu3DgcPHvyKvfV1wsOfomnTZlBXV5ca19XT55fLS65QXYXC0r4VKpelrpTLXlcWc4XA2j6gXLa6spbLUlfKZa8r5QrblTkKCvL7IEWiW34LpEmTJmjevDkAoHXr1mjUqBECAwNRpUoVGBoayqyfnZ2NSZMmYeDAgQAACwsLdO/eHV5eXtiwYcMXt2dkZAR3d3e8ffsWDRs2RHBwMAYMGIBDhw7hxYsXaNGiBYKDg9GuXTsoKiryz0tKSsL27dthYGDAj3348EEqu6BvgwYNpLq/fv0a+/btw7JlyzBkSP6stbm5OTIzM+Hp6YkhQ4agSpWynxeMjY0t9F99NTW1/lseIze5QnUVCkv7VqhclrpSrnCZlCss1vYB5bLVlbVclrpSrnCZlCtsLks/Iwn5HB1pI0dsbGz4/1dUVIS1tTUePnxYoucaGhpCSUkJwcHB4DgO9+7dg5WVFcRiMYKDgwEA9+7dg5GRkdTzNDQ0pCZsvsatW7cAAN27d0dOTg7/MDc3R2xsLN4LdJhhVlYmlJWVZcZVVFTyl2dmyk2uUF2FwtK+FSqXpa6UK1wm5QqLtX1AuWx1ZS2Xpa6UK1wm5Qqby9LPSEI+R0fayAklJSXUrFlTaqxOnTqIjY0t0fNVVVWhp6eHu3fvok2bNkhNTUXbtm1hZGSE4OBgWFhY4N27dzA2NpZ6nqamZqk7f/z4ERzHoUOHDoUuf//+PRo2bFjq/KKoqKhCIpHIjGdlZeUvV1WVm1yhugqFpX0rVC5LXSlXuEzKFRZr+4By2erKWi5LXSlXuEzKFTaXpZ+RgqK7NDGJJm3kRHZ2NpKSkqQmbuLj46H1FRd/NDY2xrlz59C6dWu0bt0a1apVg7GxMVatWoW7d+9CWVkZ+vr6Us9R+IbzB2vWrAkFBQUcOHAASkpKMssLTg8ra1paWoiJjpYZj4uL/W95XbnJFaqrUFjat0LlstSVcoXLpFxhsbYPKJetrqzlstSVcoXLpFxhc1n6GUnI52iqrRwpKSkVOsNb4MKFC/z/5+bm4uLFi1916pKRkRFevXqFgIAA/ogaY2NjREdH49ixY9DX1y/0sMCSdi+YiS5gZmYGAEhMTISenp7M4/MLfZUVsbY2IiNfITU1VWo8LDT/VDJtbdmLKVdUrlBdhcLSvhUql6WulMteVxZzhcDaPqBctrqylstSV8plryvlCtuVyIfIyEgsXrwYffr0QZs2beDg4FDoekeOHIGtrS309PTQu3fvQu/WnJKSgvnz58PExARt27bFtGnTEBMje82j+/fvY8iQIdDX10e3bt3g7e0NjuOk1uE4Dt7e3ujatSv09fUxZMgQPHjw4KtfH03alKMWLVogJycHu3fvRmhoKCIiIvhlSkpK2Lp1K/bv349r165hypQp+PDhAyZMmFDi/IKLDN+5c4eftKlduzZatGiBO3fuyFzP5mv89NNPuHTpEu7cuYOwsDCkpqaiefPmGDFiBObMmYOtW7fi1q1buHbtGnbv3o3JkyeXeltfYt29B3Jzc3HsiC8/JpFIcMLvOPT0DVC/QQO5yRWqq1BY2rdC5bLUlXLZ68pirhBY2weUy1ZX1nJZ6kq57HWlXGG7Mqei7xAl0N2jnj9/jmvXrqFp06Zo0aJFoeucPn0aixYtQs+ePbF9+3YYGhrC2dlZZhJlxowZuHnzJpYuXYp169bh5cuXGD9+PHJycvh1IiMj4eTkBC0tLXh5eWH06NFwc3PDn3/+KZW1fft2uLm5YcyYMfDy8oKWlhbGjh2LN2/efNXro9OjylG3bt0wfPhweHt7Iz4+HsbGxti7dy+A/EmbDRs2YNmyZfjnn3/QqFEjuLm5QVtbu8T56urqaN26NZ48eYL27dvz48bGxnjx4oXM9Wy+xuLFi/H7779j/PjxyMzMxJ49e2BqaoqFCxeiefPm8PX1haenJ6pVq4bmzZujR48epd7Wl+jrG6C7bQ+4bdqAhPh4NG7SFP4n/PDu3VssXbFKrnKF6lrg4P59SElJRux/s7/Xrl5BdHT+3b+GjXBE9erV5aIvS7ksdaVc9rqymAvQZw3lstWVtVyWulIue10pV9iuRD5YWlrC2toaAODi4oJHjx7JrOPm5gZ7e3vMmDEDANChQwf8888/8PT0xPbt2wEAISEhuHHjBnbu3AkLCwsA+Zf8sLOzw/nz52FnZwcA2LlzJ2rVqoUNGzZAWVkZZmZmSEhIwLZt2+Do6AhlZWVkZWXBy8sLY8eOxZgxYwAA7du3R48ePbBz504sXbq0xK9Pgfv8GB5S7tzd3fHnn38iJCSkoqvIjcyc4pdnZWXB030TTvv7Izk5Ca1EYkyZOh0dLTp903aFyBWqKwD0tLHEu3dvC1125vwlNGzY6KszWdq3QuWy1JVy2evKYi591lAua11Zy2WpK+Wy15Vyvy1TtRId5qBm71bRFYqUcXpameQUTNqcOnWKH3vz5g2sra3h6enJT+4AwJ49e7B27Vrcv38fysrK2Lx5M/bt24c7d+5IXfu1X79+EIvFWL16NQCga9eusLGxwYIFC/h1wsPD0adPH/7ghsDAQIwZMwZ//fUXWrf+/+l3rq6uuHDhAi5fvlzi10STNnKAJm1kfWnShhBCCCGEEEKEVqkmbRw8KrpCkTJOOZdJTmGTNteuXcOECRNw5swZqdOnbt68ibFjx/Lj06dPx/v373H48GGpzFmzZuHNmzc4fPgw0tPT0bZtWyxduhTDhg3j15FIJNDX18eSJUswbNgw7N+/H8uXL0doaCh/a3kAOHz4MBYvXowHDx5AtYR3LatE34KVF8dxyM3NLXJ5lSpVUKUKXZ6IEEIIIYQQQgh7rKysil1+6dKlUmcnJSUBAGrUqCE1XvB1wfLk5ORCT/muWbMmf8pVSkpKoVnKyspQU1OTylJWVpaasCl4HsdxSEpKokkblkydOhVTp04tcvmdO3cwatSoIpf369ePP1SLEEIIIYQQQgghlQNN2jBAR0cHR48eLXJ5rVq1yrENIYQQQgghhBDmKMjv2RnfciTNl9SsWRNA/lEyWlpa/HhycrLU8ho1auDDhw8yz09KSuLXKTgSp+CImwISiQQZGRlSWRKJBFlZWVJH2yQnJ0NBQYFfryRo0oYB6urq0NPTq+gahBBCCCGEEEIIU3766ScAQEREBP//BV8rKSmhcePG/HqBgYHgOE7qQsQvX76ESCQCAFStWhUNGjRARESE1DZevnwJjuP4/IL/vnz5UuqO0BEREfjxxx9LfGoUAMjvVBshhBBCykVWdp4gD0IIIYSQita4cWM0a9YMAQEBUuNnzpyBmZkZlJWVAQCdO3dGUlISAgMD+XVevnyJJ0+eoHPnzvxY586dcenSJWRnZ0tl1ahRA23btgUAtGvXDurq6jh79iy/TnZ2Ns6fPy+VVRJ0pA0hhBBCCCGEEFLZfXL0SGWSkZGBa9euAQDevn2L1NRUfoLGxMQEtWvXxtSpUzF79mw0adIEpqamOHPmDEJDQ7Fv3z4+p23btrCwsMD8+fMxd+5cqKioYOPGjRCLxejevTu/npOTE/z9/TFr1iwMGzYM//zzD3bu3ImZM2fyE0AqKir45Zdf4O7ujtq1a0MkEuHgwYNITEyEk5PTV70+uuU3kUt0y29CCCk/Qh0Vo6JEB/QSQghhW6W65XfvrRVdoUgZJyeV+rlRUVFF3n1qz549MDU1BQAcOXIE27dvx7t379C8eXP8+uuv6Natm9T6KSkpcHV1xYULF5CTkwMLCwssXLgQ9erVk1rv/v37WL16NZ4+fYratWtjxIgRGD9+vNRpVRzHwdvbGwcOHEBCQgJat26NefPm8UfjlBRN2hBBGBkZYfTo0cXeFas4X5q0kUgk8HTfjNP+J5CcnIxWIjGcp82AmXnHUm1PyFyWugJAZOQreLpvRsj9e0hOSkL9Bg3Q084Bo392gpqamtz1pfeMclnrKo+5Wdl5+HP7Nmzz3IyfWrTEoWP+UstDH4TAfdM6hIc/QbVq6rDu3gOTp85A1arV+HVe/Psc27d5IvzpY8THx0FVVRUtWrTE6J+d0LWbpdzvA8qtXF1Zy2WpK+Wy15Vyvy2TJm3Kx7dM2lR29E9ghEmL5rtg3x4f2Dn0whyXBVBUVITzpAm4f++u3OWy1PXD+/cYMXQQwh4+xNBhI/Hb3PnQN2iLrZ7ucPntV7nrK1QuS10pl72u8pgbHf0BPju9oaZWVWbZP+FPMeWXn5GZmYEZs+aiT78B+OvYYcz7babUeh/ev0N6ehrse/XFrN/mwWl8/l++pjtPwtHDvmXW9UsoV7hclrqylstSV8plryvlCtuVKQpV5PdBisYRIoD27dtzbm5upX5+RnbRjzv3HnIikYjb5r2DH0tMzeSsrKy5QYOHFPvc8s5lqWtGNse5e27lRCIRF/b0H6nxWbPncCKRiIuOS5SrvvSeUS5rXeU1d8rU6dzwkaO4ocNGcD162nGJ6bn8Y8zPTpx5x45cVEwSP+az7xAnEom4gIt/S637+SM1M4fr1as3193WVu73AeVWnq6s5bLUlXLZ60q5355Zmaj23ia3D1I0Zqe0Dh06hG7dusHAwAA///wznjx5ArFYjOPHjwMAxGIxdu7cKfUcHx8fiMViqbHk5GQsXboUFhYW0NXVRf/+/XHjxg2pde7du4cRI0agffv2aNu2LXr16gU/P78SLy9OVFQUxGIx/Pz8MH/+fLRv3x4mJiZwdXVFTs7/zxGKiYnBvHnzYGVlBX19fXTv3h0bNmyARCKRyjt69Cjs7e2hr68PU1NTDBs2DKGhoSVaPn/+fAwfPpxfNyEhAdra2hgwYAA/lpaWBh0dHamrYF+8eBE9evSAnp4eBg4cKLU9IVw8HwBFRUUMGDSEH1NRUUG/AQPx8EEIPrx/Lze5LHUFgNTUVABAnTp1pMY1tbRQpUoV/KCkJFd96T2jXNa6ymPuvbvBuHzxPH79bZ7MstTUVAQFBaKHXS+oq6vz4/a9+qBq1aq4eOGszHM+paioiHr1GyAlOaVMun4J5QqXy1JX1nJZ6kq57HWlXGG7ElIemJy0uXTpEpYsWYKOHTvCw8MDZmZmmDFjxlfnSCQS/Pzzz7h69SpmzJiBrVu3okWLFvjll1/w7NkzAPl/Yf3ll1+grq6ODRs2YMuWLRg8eDCSk5NLtLykNmzYAI7jsGnTJjg5OWHfvn3YtGkTv/zjx4/Q0NDAvHnzsGPHDowbNw5+fn5YsmQJv05wcDAWLFiAzp07w9vbG2vWrIGZmRlSUlJKtNzY2BhhYWHIysoCANy9exfKysp4+vQp/8t8SEgIcnJyYGxsDAB4+vQppk2bhmbNmsHDwwP9+vXDjBkzZCaTylJ4+FM0bdpM6hcIANDV0+eXy0suS10BwNjYBACwdNEChD99ig/v3yPg7Bkc8T2I4SMcUbWq7KkTFdmX3jPKZa2rvOXm5uZi9aoV6N1vIFq2Esksf/H8H+Tm5KB1G12pcSUlZbQSt8Y/hWRmZKQj8eNHRL15jb27fXDzxt8w7dDhm7uWBOUKl8tSV9ZyWepKuex1pVxhuzJHQUF+H6RITF5WaevWrejQoQNWrlwJAOjUqRNycnKwefPmr8rx9/dHeHg4Tpw4gZYtW/JZkZGR2LJlCzZv3oyXL18iJSUFv/76K3+UjpmZGZ/xpeUl1aRJE7i6uvIdMjMzsWvXLowfPx41a9aEWCzG3Llz+fXbtWsHNTU1uLi4YPHixVBTU0NoaCg0NDSk1uvatSv//19abmRkBIlEgocPH8LExATBwcGwsbHBjRs3cP/+fXTu3BnBwcFo1qwZNDU1AQDe3t5o0KABPD09oaioCCB/1nrBggVfvQ9KKjY2FppaWjLjmppa/y2PkZtclroCQMdOnTFl6nTs3O6Fq1cu8+PjJ0yE8/SZxTyzeCztB5a6Uq5wmd9L7hHfQ3j//h3ct/1ZaGZcXGx+RhG5D0JkrwOwaf1a+B3Nv4ZNlSpVYGVtg3kLFn9z15KgXOFyWerKWi5LXSlXuEzKFTZXqK6ElAfmjrTJzc3F06dPYWkpfSeKom7xVZybN29CJBKhWbNmyMnJ4R/m5uYICwsDkD+Zoq6ujqVLl+LMmTNISEiQyvjS8pKysbGR+trW1hYZGRn4559/AOTfLszHxwd2dnbQ19eHjo4OZs+ejZycHLx58wYA0KZNGyQmJsLFxQU3b95ERkaGVOaXljdu3Bj169dHcHAwgPwjbUxMTGBkZCQ1VnCUDQA8fPgQ3bp14ydsAKBHjx6l2gcllZWVCWVlZZlxFRWV/OWZmXKTy1LXAj82bIh27Y2weOkKrN/kjr79B2DHdi8c3L+v1Jks7QeWulKucJnfQ25i4kds8XDD+ImTUat27SIzAUBZSTZXWUUZWZlZMuPDRoyCx7adWLLCFR07dUZuXh6ys7O/qWtJUa5wuSx1ZS2Xpa6UK1wm5QqbK+TfnQkRGnNH2iQkJCAnJwe1P/sL5ufX4CiJjx8/4smTJ9DR0ZFZVjAJUbNmTezatQtubm6YM2cOcnNzYWRkhIULF0IsFn9xeUl9/noKjmSJjc3/V87du3djzZo1GDduHExNTVGjRg2EhYVh+fLl/OlMZmZmWLt2Lfbs2QMnJyeoqKjA1tYW8+fPh4aGxheXA/mnSN29exepqakIDw+HkZERMjIyEBAQAIlEgtDQUAwaNIjvGRsbK7Pv1dXV+Q9AIaioqBZ6+lXBflBRVZWbXJa6AsDZM6exYulinDx9DvXq1wcAWNt0R14eh00b16GnvT00NGrJTV96zyhXqMzvIdfDbRNq1qyJ4cNHIq+YTACQZMvmSrIkUFGV/axv1vwnNGv+EwCgf//++GX8WEydMhH7Dx2Bwn+HP8vLPqDcis2kXOEyKVfYXJa6Uq5wmUyiuzQxiblJm9q1a+OHH36QOaIlPj5e6mtlZWWZf9n7/DozBacdrVq1qtht6uvrY8eOHcjMzERQUBDWrFmDKVOm4OLFiyVaXhKfv564uDgAgNZ/h/EFBATA0tISs2bN4td58eKFTE6fPn3Qp08fJCQk4NKlS3B1dcUPP/yA33//vUTLjY2NsXr1agQFBaFWrVpo0aIFMjIysG7dOty+fRsSiQRGRkb89rS0tGT2fWpqKv8BKAQtLS3EREfLjBccxq+lVVduclnqCgCHDx2AtnZrfsKmQNduljj513GEP32KDmbmctOX3jPKFSqzsudGRr7CsSOH8ZvLfMTExkCSzQEAJJIs5OTk4N3bt6imXo0/bDzuv39A+Dy3JF1tbGyxYtliRL56yU/myMM+oNyKz6Rc4TIpV9hclrpSrnCZhJQX5qbaFBUV0bp1a1y6dElq/PMJkvr168tMaty6dUvqa3Nzc7x58wZ169aFnp6ezONzqqqq6NKlC4YNG4aoqCiZiYkvLS/OhQsXpL4+d+4c1NTUIBLlXxgyMzMTSp/ducff37/IvNq1a2PQoEHo2LEjIiIiSrzcyMgI6enp8PHx4SdnWrduDRUVFWzfvh0NGjRAo0aN+PX19fVx5coV5Obm8mMBAQElft2lIdbWRmTkK/7iyAXCQh8CALS1W8tNLktdASA+Pg65ebL/5p6Tkz8BmvvJHc2+Bkv7gaWulMteV3nJjYmORl5eHtb8vhJ23a3Q194afe2t8SgsFK8jX6GvvTV2em1Bi5atoPjDD3j65JFUZna2BM+fPUUrsfYXexWcYpWS8v9e8rAPKLfiMymXva6Uy15XyhW2KyHlgblJGwCYNGkSgoKCsHDhQty4cQPe3t7466+/AORf9BDIvyZMQEAA9uzZg+vXr+O3335D9Gezq3379kXz5s0xatQo+Pr6IigoCBcvXoSbmxvWr18PALh69SqcnZ3x119/4c6dOzhz5gz27duHdu3aQUVF5YvLS+r169eYN28erl+/Di8vL3h7e2P48OGoWbMmgPwJposXL2Lfvn24ceMG5syZg8jISKkMNzc3LF++HAEBAQgODsb+/ftx/fp1dPjvrh1fWg4ALVq0QJ06dXDnzh3+2jWKiopo164d7ty5I3WUDQBMmDAB79+/x5QpU3Dt2jXs378fW7ZsEfT0KOvuPZCbm4tjR3z5MYlEghN+x6Gnb4D6DRrITS5LXQGgadPmCH/6BK9evZQaP3vmNKpUqYJWX3HKX3n0pfeMclnrKi+5LVu1wkY3T/6xdoM71m5wx08tWqJ+gwZYu8EdvfsNhHr16jAxNUPAGX+kpaXxzz9z6iTS09NhbfP/a5glJEgfdQkA2dnZ8D95AqqqqmjRooVc7QPKrfhMymWvK+Wy15Vyhe1KSHlg7vQoIP+iw0uXLoWXlxdOnjwJAwMDLF26FGPHjuVv4zZ58mTEx8fD09MTCgoKGDJkCEaNGoXVq1fzOcrKytizZw/c3d2xbds2xMbGQkNDA23atMHw4cMB5F9ouEqVKti0aRPi4+OhoaEBCwsL/PrrryVaXlIzZ87EnTt3MH36dCgqKmL48OGYOfP/d+uZMmUKPn78CDc3NwD5k1ILFy7ExIkT+XX09PSwe/dunD17Fqmpqahfvz6cnJwwadKkEi0vYGRkhHPnzkldcNjY2Bh///231BiQf3HjzZs3Y926dXB2dkarVq2wceNGODk5fdXr/xr6+gbobtsDbps2ICE+Ho2bNIX/CT+8e/cWS1cUf6pbeeey1BUAxox1ws0bf+PnUSMwdNgIaGho4O9rV3Hj+t/oP2AQ6tatJ1d96T2jXNa6ykturVq1YWllzX+dlZ1/hN2h/XsAAF0t/79skvN0jBs9HBOdHNF3wGDERH/Agb0+MDXrCLOOnfj1XFcsQVpaGtq2M4JW3bqIj4/D+bOn8DIiArN+c0HVatXkah9QbsVnUi57XSmXva6UK2xX5tCttZmkwHEcV9ElysKRI0ewcOFCXLp0Ser0HXkXFRUFKysrbN68WfC7LrEk8wtn4WRlZcHTfRNO+/sjOTkJrURiTJk6HR0tOhX/xC8QIpelrgAQFhqKbVvcEf70KRITE9GwUUP07tMPY8aOww8/lH6el6X9wFJXymWvqzzmFkzaTHQahcTEjzh0TPr02wch9+CxaT2ehT9B1arVYN29ByZP+xXVPpmIOR9wGif9juHff58jKSkR1apWQxsdHQwbPhJdLWXv8Chv+4ByK1dX1nJZ6kq57HWl3G/LVGXyMIfCqfXfWdEVipRxXLh/9Gcdk5M2iYmJ8PDwQIcOHVCtWjWEhYVh27Zt6NChA7Zs2VLR9b4KTdoU7kuTNoQQQspOwaRNWVNRYvIsbEIIIYRHkzblgyZtisbkt+APP/yAN2/e4NSpU0hJSUGtWrXQp08fzJ49u6KrSeE4TuoCvZ8ruP4OIYQQQgghhBAiJAU6PYpJTB5pw4qgoCCMGjWqyOX9+vWTusYO+T860oYQQsoPHWlDCCGEFK4yHWlTdcCfFV2hSOnHxlZ0BblVib4F5Y+Ojg6OHj1a5PJatWqVYxtCCCGEEEIIIYSwhCZtBKSurg49Pb2KrkEIIYQQQggh5DtHp0exiSZtCCGEkO8cncZECCGEECKf6G9phBBCCCGEEEIIIXKIjrQhhBBCCCGEEEIqOzo7ikl0pA1hkkQiwcb1f8C6qwVM2uljxNBBCLx1Uy5zWepKuex1pVz2urKUu91rKwx0xOjfx0Fq/NbNG1iyaD7693FAW73W6GljWeFdKVf4XJa6spbLUlfKZa8r5QrblRCh0aRNCbm4uMDBwaHYddzd3XH//v0Sj5dEVFQU3N3dER0dXarnVwRLS0ssX75c0G0smu+CfXt8YOfQC3NcFkBRURHOkybg/r27cpfLUlfKZa8r5bLXlZXc6A8fsGO7F9TUqsosO3v6FM6ePoXq6urQqlu3wrtSbvnkstSVtVyWulIue10pV9iuhAiOIyUyd+5czt7evth1RCIRt2PHjhKPl8Tt27c5kUjEhYaGlur5FaFbt27csmXLvikjI7vox517DzmRSMRt897BjyWmZnJWVtbcoMFDin1ueeey1JVy2etKuex1ZSl36vQZ3EjHUdzwESO5nnb2Ussi337gktMlXEY2xzmNn8B17dqtUu4DymWzK2u5LHWlXPa6Uu63Z1Ym1QbtktsHKRodaUOYc/F8ABQVFTFg0BB+TEVFBf0GDMTDByH48P693OSy1JVy2etKuex1ZSX33t1gXDx/DnNc5he6vG7delBSUipVz7LuSrnlk8tSV9ZyWepKuex1pVxhuxJSHmjS5isFBQWhb9++MDQ0xMCBA/Ho0SMAgFgsBgCsXbsWYrEYYrEYQUFBRY4XPMfb2xtr165Fhw4d0LZtW7i4uCA1NZXf1qhRowAAAwcO5J8PAMePH4dYLEZCQoJUvz59+sDFxYX/uuC0rqJ6FxCLxdi+fTvc3d1hbm4OU1NTzJs3D+np6VLrffjwAbNnz4apqSn09fUxYsQImSyhhYc/RdOmzaCuri41rqunzy+Xl1yWulIue10pl72uLOTm5uZi9aoV6DdgIFqJxKXq8iXyvg8ol+2urOWy1JVy2etKucJ2JaQ80KTNV4iNjcXKlSvh5OSETZs2ISsrC87OzsjOzoavry8AwNHREb6+vvD19YWOjk6R4wX27t2LiIgIrFmzBrNnz8a5c+ewaNEiAICOjg4WL14MAHB1deWfX5a9P7V//368evUKq1evxpQpU+Dv748tW7bwy5OSkjB8+HCEh4dj0aJFcHd3h5qaGkaPHo34+Piv7lVasbGx0NTSkhnX1NT6b3mM3OSy1JVyhcukXGFzWerKQu4R30N4//4dpkydUaoeJSHv+4ByyyeTcoXLpFxhc1nqSrnCZbJIQUFBbh+kaHTL76+QlJSEffv2oVWrVgAANTU1jBo1Cg8fPoSRkREAoEGDBjA0NOSfU/D/n48XUFZWhqenJxQVFQHkH6a3cOFCODs7o0WLFmjZsiUAoFWrVtDT0xOsNwBoaWlh/fr1AIDOnTvjyZMnOHfuHGbPng0A2L17N5KTk3HkyBHUqVMHAGBmZgZbW1vs3LkTc+bMKVW/r5WVlQllZWWZcRUVlfzlmZlyk8tSV8oVLpNyhc1lqau85yYmfsQWDzeMnzgZtWvXLlWPkpDnfUC55ZdJucJlUq6wuSx1pVzhMgkpL3SkzVeoW7cuP/EBgJ9Q+ZY7O3Xr1o2fsAGAHj16gOM4hIWFlb7oZ0ra29zcXOrrFi1a4MOHD/zXN2/ehKmpKWrWrImcnBzk5OSgSpUqMDY2LtO+X6KiogqJRCIznpWVlb9cVVVuclnqSrnCZVKusLksdZX3XA+3TahZsyaGDx9Zqg4lJc/7gHLLL5NyhcukXGFzWepKucJlElJe6Eibr1CjRg2prwsuwljwh700Co5YKaCurg4VFRXExJTdIXol7V3Yep9+uH38+BEPHjyQOr2rQJMmTcqq7hdpaWkhppCJsri42P+Wl+72s0LkstSVcoXLpFxhc1nqKs+5kZGvcOzIYfzmMh8xnxwmnpWVhZycbLx9GwX1auqoqaFRqn5l2ZVyyz+Xpa6s5bLUlXKFy6RcYXOF6soaOg2JTXSkTQX7/FowqampyMrKQt26xX9wFBzK9/l1aZKTk8u24Cdq1qyJTp064ejRozIPDw8Pwbb7ObG2NiIjX/EXbC4QFvoQAKCt3VpuclnqSrnsdaVc9rrKc25MdDTy8vKw5veVsOtuxT/CQh8i8tUr2HW3gtdWz1J1K+uulFv+uSx1ZS2Xpa6Uy15XyhW2KyHlgSZtypCSklKhR90UNQ4AV65cQW5uLv91QEAAFBQU+OvXFHVUTL169QAAERER/NiLFy/wXsDb1Zmbm+PFixdo0aIF9PT0pB4Fd7UqD9bdeyA3NxfHjvz/oswSiQQn/I5DT98A9Rs0kJtclrpSLntdKZe9rvKc27JVK2x085R5tGjZCg0a/IiNbp7oN2BgqbqVdVfKLf9clrqylstSV8plryvlCtuVkPJAp0eVoZ9++gmXLl2CkZER1NTU0Lx5c6irqxc5DuR/WEyZMgXDhg1DVFQU1q1bB1tbW7Ro0QIA0KxZMygqKuLYsWP44YcfoKioCD09PRgYGKBBgwb4/fffMWvWLKSmpsLb2xsaZXDYelHGjBkDf39/jBw5EqNGjcKPP/6IhIQEPHz4EPXq1cOYMWME2/an9PUN0N22B9w2bUBCfDwaN2kK/xN+ePfuLZauWCVXuSx1pVz2ulIue13lObdWrdqwtLKWGd+/dzcASC3751k4rl65DAB48zoSKakp8N6Wf7dBkVgbXbtZCtqVcss/l6WurOWy1JVy2etKucJ2ZQ2dHsUmBY7juIouwQIXFxc8evQIp06d4seSk5NhbGwMV1dX9O/fH3fv3sXvv/+OFy9eIDMzE3v27IGpqWmR42KxGLNmzUJCQgL8/PwgkUhgY2ODxYsX85M6AHDo0CHs2LED79+/R05ODp49ewYAePToEZYuXYrnz5+jSZMmmD9/PlavXo3WrVtj9erVJe4NAGKxGHPmzIGTkxO/no+PD1xdXfntAfm3y9u0aROuXbuGxMRE1KlTBwYGBhgzZgzatWsHALC0tETXrl3525WXRmZO8cuzsrLg6b4Jp/39kZychFYiMaZMnY6OFp1KvU2hclnqSrnsdaVc9rqylus0xhEfP37E8RP//zlywu84Fi+cV+j6vfv0w4rfV1dIV8oVNpelrqzlstSVctnrSrnflqlaiQ5zqDlsb0VXKFLSQceKriC3aNKmAhU2UULyfWnShhBCCCGEEEKERpM25YMmbYpWib4FCSGEEEIIIYQQUig6O4pJdCFiQgghhBBCCCGEEDlER9pUoE+vFUMIIYQQQgghhBDyKZq0IYQQQgghhBBCKjm6exSb6PQoQgghhBBCCCGEEDlEkzaEEEIIIYQQQgghcohOjyKEEEIIIYQQQio5Oj2KTXSkDWGSRCLBxvV/wLqrBUza6WPE0EEIvHVTLnNZ6spa7qOwUPy+cjn69baHqZEhbK264rdfp+PVq5dy15Vyhc1lqSvlsteVctnrylouS10pl72ulCtsV0KERpM2lYyLiwscHBwquobgFs13wb49PrBz6IU5LgugqKgI50kTcP/eXbnLZakra7m7du7ApQvnYdrBDHNdFmDAoMG4d/cuhg7sj+fP/5GrrpQrbC5LXSmXva6Uy15X1nJZ6kq57HWlXGG7EiI4jlQqkZGR3NOnTyu6xjfLyC76cefeQ04kEnHbvHfwY4mpmZyVlTU3aPCQYp9b3rksdWUxN/DOPS45LUtqLPzfl5yuri4349dZctWVcoXLZakr5bLXlXLZ68paLktdKZe9rpT77ZmVSa2R++X2QYpGR9pUMk2aNIG2tnZF1xDUxfMBUFRUxIBBQ/gxFRUV9BswEA8fhODD+/dyk8tSVxZzDdu2g5KystRY06bN0KJlK7yMiJCrrpQrXC5LXSmXva6Uy15X1nJZ6kq57HWlXGG7ElIeaNKmkvn09Kjjx49DLBYjLCwMY8eOhYGBAWxtbXHr1i3k5eVh48aNMDc3h7m5OdavX4+8vDw+58WLF5g5cya6dOkCAwMD2NnZ4c8//5RaJyoqCmKxGH5+fpg/fz7at28PExMTuLq6IicnR7DXGB7+FE2bNoO6urrUuK6ePr9cXnJZ6spibmE4jkN8fBw0NGqV6vms7QPKZasr5bLXlXLZ68paLktdKZe9rpQrbFdCygPdPeo7MHfuXAwdOhQ///wzvL294ezsjH79+iE1NRVr1qzBw4cP4e7uDpFIhF69egEAYmJi0Lx5c/Tq1QvVqlXD06dP4e7ujvT0dDg7O0vlb9iwARYWFti0aROePHkCNzc3KCkpYfbs2YK8ntjYWGhqacmMa2pq/bc8Rm5yWerKYm5hTp86iZjoaEx2nlaq57O2DyiXra6UK1wm5Qqby1JX1nJZ6kq5wmVSrrC55fl3UXlGd49iE03afAdGjhyJ4cOHAwDq1auHXr164dGjR/D19QUAdOrUCZcvX0ZAQAA/aWNmZgYzMzMA+UcutG/fHpmZmdi3b5/MpE2TJk3g6urKZ2VmZmLXrl0YP348atasWeavJysrE8qfnRID5B/iCABZmZlyk8tSVxZzP/cy4gVcVy6HgWFb9O7Tr1QZrO0DymWrK+UKl0m5wuay1JW1XJa6Uq5wmZQrbG55/V2UECHQpM13oGPHjvz/N2vWDADQoUMHqXWaN2+Oly//f5vkrKwseHl5wd/fH+/fv0d2dja/LC0tDdWqVeO/trGxkcqytbXFli1b8M8//8DY2LgsXwoAQEVFFRKJRGY8Kysrf7mqqtzkstSVxdxPxcXGwnnyL1BXr451GzdDUVGxVDms7QPKZasr5QqXSbnC5rLUlbVclrpSrnCZlCtsbnn8XZQQodA1bb4D1atX5/+/YIa5Ro0aUusoKSlJfZD98ccf2LlzJwYNGgRvb28cPXoUkyZNAvD/D7cCtWvXlvpaU1MTQP5hiELQ0tJCXCHZcXGx/y2vKze5LHVlMbdASkoKJk8cj5TkFGzx2oG6deuVOou1fUC5bHWlXOEyKVfYXJa6spbLUlfKFS6TcoXNFfrvosxQkOMHKRJN2pBCBQQEYMiQIZgwYQLMzc2hp6eHH34o/MCshIQEqa/j4uIA5H84CkGsrY3IyFdITU2VGg8LfQgA0NZuLTe5LHVlMRfIn0ScNmUiIiNfwX3LNrRo2bLUWUJ2pVzhclnqSrnsdaVc9rqylstSV8plryvlCtuVkPJAkzakUFlZWVBSUuK/zs3NxenTpwtd98KFC1Jfnzt3DmpqahCJRIJ0s+7eA7m5uTh2xJcfk0gkOOF3HHr6BqjfoIHc5LLUlcXc3NxczJk1A6EPH2Ddhs0wMGxbqpzy6Eq5wuWy1JVy2etKuex1ZS2Xpa6Uy15XyhW2KyHlga5pQwplbm6OI0eOoGXLlqhVqxYOHDhQ6HmgAPD69WvMmzcPdnZ2ePLkCby9vTF69GhBLkIMAPr6Buhu2wNumzYgIT4ejZs0hf8JP7x79xZLV6ySq1yWurKYu37taly9chldunZDUlIiTvmfkFru0KuP3HSlXOFyWepKuex1pVz2urKWy1JXymWvK+UK25U1dPcoNilwHMdVdAlSdlxcXPDo0SOcOnUKx48fx7x58xAYGCh13RmxWIw5c+bAycmp0OcB+ac4LVmyBIGBgVBTU0O/fv3QtGlTLFy4kM+LioqClZUVXF1dcefOHZw/fx6Kioro27cv5syZI3WkztfKzCl+eVZWFjzdN+G0vz+Sk5PQSiTGlKnT0dGiU6m3KVQuS11Zy3Ua44i7wXeKXP7w8bNS5bK0DyiXva6Uy15XymWvK2u5LHWlXPa6Uu63ZapWosMcNMccqugKRYrzGVrRFeQWTdqQUiuYtNm8eTN69OhRptlfmrQhhBBCCCGEEKHRpE35oEmbotE1bQghhBBCCCGEEELkUCWaNySEEEIIIYQQQkhh6Jo2bKJJG1JqjRo1wrNnpbtmCCGEEEIIIYQQQopHp0cRQgghhBBCCCGEyCE60oYQQgghhBBCCKnk6PQoNtGkDSHku5SZnVvmmapKimWeSQghhBBCCPl+0elRhBBCCCGEEEIIIXKIjrQhhBBCCCGEEEIqOzo7ikl0pE05cnFxgYODQ0XXqBQkEgk2rv8D1l0tYNJOHyOGDkLgrZtymctS1+8td9f2bTA1bINhA3rzY+/evoWpYZsiH78vWyyV8TryFRbMnQWH7t1g2t4AfRx6YNsWD2RkZJRp1+JQLltdKZe9rpTLXlehctPT0rDFww2TJjihk5kJDHTEOOF3XC67Uq6wuSx1pVxhuxIiNJq0KUeTJ0/GunXrKrpGpbBovgv27fGBnUMvzHFZAEVFRThPmoD79+7KXS5LXb+n3OjoD/DZuR1qampS47Vq18LSVatlHj3s8idcTc3M/5/x4T3GjhyKx6EPMWjocPw2dz70Ddpiq6c7XH77Ve73QWXKZakr5bLXlXLZ6ypU7sfEj/Da6omXEREQicXf1E/orpQrbC5LXSlX2K6ECI4jRA5lZBf9uHPvIScSibht3jv4scTUTM7KypobNHhIsc8t71yWun5vuZOnTueGj3Tkhg4bwfXoacd9TM8p9jHCcRTXtl077sPHNH5so5snJxKJuHuhT7mP6Tl89qzZcziRSMRFxyXK9T6oLLksdaVc9rpSLntdhcxNSsvi3ryL4TKyOe5uSCgnEom4Q4ePlTqPxX1AuWx1pdxvz6xM6jodltsHKRodaVOOPj096vjx4xCLxXjw4AFGjRoFAwMDWFpa4ujRo1LPef78OcaPHw9TU1MYGBjA1tYW27dvBwDcvXsXYrEYr1+/5tefOHEixGIxnj9/zo/9+uuvmDBhAv+1RCLBhg0b0K1bN+jq6qJnz57w9/eX6RsSEoJRo0bB0NAQ7du3x6xZsxAfH88vj4qKglgshp+fH+bPn4/27dvDxMQErq6uyMnJKZudVoiL5wOgqKiIAYOG8GMqKiroN2AgHj4IwYf37+Uml6Wu31PuvbvBuHLxPGb+Nq9E24mLjcW94DvoamkNFRUVfjwtLQ0AULuOptT6mlpaqFKlCn5QUvrmrl9CuWx1pVz2ulIue12FzFVWVoamllapnlsU1vYB5bLVlXKF7UpIeaBJmwr266+/omPHjvDw8ICpqSkWLFiAv//+m18+ceJEJCcnY9WqVfDy8oKTkxN/rQx9fX2oqKggODgYAJCXl4d79+5JjQFAcHAwjIyM+K+nT58OX19f/Pzzz/Dy8kKnTp3w22+/4dq1a/w6ISEhcHR0RPXq1bFx40asWLECYWFhmDx5ssxr2LBhAziOw6ZNm+Dk5IR9+/Zh06ZNZb2reOHhT9G0aTOoq6tLjevq6fPL5SWXpa7fS25ubi5Wr1qB3v0GoGUrUYm2cyHgDPLy8vhTpAq0MzIGAKxcthD/hD/Fh/fvEXD2DI74HsTwEY6oWrXqN3UtCcplqyvlsteVctnrKmSuEFjbB5TLVlfKFbYrIeWB7h5Vwfr06YNffvkFANCpUye8efMGnp6e6Ny5MxISEhAVFYUFCxbA0tISANChQwf+ucrKytDX18fdu3cxYMAAPHv2DBkZGejfvz+Cg4MxfPhwREZGIiYmBsbG+b9c3r59G5cvX8bOnTthYWEBAOjYsSNiY2Ph7u6OLl26AADWr18PXV1deHh4QEEh/zLjIpEIDg4OuHbtGr8eADRp0gSurq78a8jMzMSuXbswfvx41KxZs8z3WWxsbKH/yqWpqfXf8hi5yWWp6/eSe8T3EN6/fwe3bTtLvJ2As6egqaUFI5MOUuNmHTvhlynT4LPTG9evXuHHx0+YCOfpM7+5a0lQLltdKVe4TMoVNpelrkLmCoG1fUC5bHWlXOEyWVTwex1hCx1pU8FsbGykvu7evTseP36M3Nxc1KpVCw0bNsSGDRvg5+eHDx8+yDzfyMiIP6omODgYurq66Ny5s9SYmpoadHV1AQA3b96EhoYGOnTogJycHP5hbm6Op0+fIjc3FxkZGbh//z569OiB3Nxcfp1mzZqhQYMGCAsLK/Y12NraIiMjA//880+Z7adPZWVlQllZWWa84LSVrMxMucllqev3kJuY+BFbPNwwfuJk1Kpdu0TbeB35CuFPHsPG1g5Vqsh+ZDb48Ue0bWeEeYuWYf0md/TtPwA7tnvh4P5939S1pCiXra6UK1wm5Qqby1JXIXOFwNo+oFy2ulKucJmElBc60qaC1alTR+prTU1NZGdn4+PHj9DU1MTOnTuxceNGLF++HOnp6dDR0cG8efP4I2dMTEywdetWREdH4+7duzAyMoKRkRHi4uLw6tUr3L17FwYGBlD679oaHz9+RGJiInR0dArtExsbCwUFBeTm5sLV1ZU/guZT7z8757P2Z7/8ampq8llCUFFRhUQikRnPysrKX66qKje5LHX9HnI93DahZs2aGD58JHJLuI2A0/nXe7L97NQoADgfcAauK5biyIkzqFevPlSVFGFt0x15eRw2bVyHnvb20NCoVaquJUW5bHWlXOEyKVfYXJa6CpkrBNb2AeWy1ZVyhcskpLzQpE0Fi4+PR7169fiv4+LioKSkhFq18n/Ra968Odzc3JCdnY2QkBBs2LABEydOxN9//41q1arB0NAQSkpKCA4O5k+T0tDQQKtWrRAcHIzg4GD07duXz69ZsyZq164Nb2/vQvvUrl0bOTk5UFBQwC+//AJra2uZdQq6FUhISJD6Oi4uDgCgVcYX6iugpaWFmOhomfG4uNj/lteVm1yWulb23MjIVzh25DB+c5mPmNgYZGXnAQCyJFnIycnBu7dvUU29GmrW1JDKOnf2NJo2a47WbWQnOo8dPgixuDXq1asvNd61myVO/nUc4U+fosN/twiXh31QWXNZ6kq5wmVSrrC5LHUVMlcIrO0DymWrK+UKl8kiOj2KTXR6VAW7cOGC1Nfnz5+Hjo4OFBUVpcaVlJRgYmKCCRMmIDU1FTEx+eddVq1aFW3atIGvry8SExPRvn17AICxsTFOnjyJqKgoqYsQm5ubIyEhAUpKStDT05N5KCsro2rVqjA0NERERESh6zRq1KjY13Du3DmoqalBJCrZRV6/llhbG5GRr5Camio1Hhb6EACgrd1abnJZ6lrZc2Oio5GXl4c1v6+EXXcr9LO3QT97GzwOC8XryFfoZ2+DnV5bpXIehT1E1JvXhR5lAwAJ8fHIzZM9ZicnJxsAkPvJXdTkYR9U1lyWulIue10pl72uQuYKgbV9QLlsdaVcYbsSUh5o0qaCnThxAl5eXrh+/TrmzZuH4OBg/g5N4eHh+Pnnn3HkyBHcvn0bFy9exNatW9GwYUM0adKEzzAyMsKdO3egra3NXxG9YExJSQlt27bl1+3YsSO6deuGcePGwcfHB4GBgbh8+TK8vb2xYMECfr05c+bg6tWrmDFjBi5cuICgoCCcOHECc+fORVBQkNRreP36NebNm4fr16/Dy8sL3t7eGD58uCAXIQYA6+7519o5dsSXH5NIJDjhdxx6+gao36CB3OSy1LWy57Zs1Qob3Tz5x9oNbli7wQ0/tWiJ+g0aYO0GN/TuN0Aq/9yZ0wAA2572hW6/SdNm+Cf8KV5HvpIaP3vmNKpUqYJWYrFc7YPKmstSV8plryvlstdVyFwhsLYPKJetrpQrbFdCygOdHlXB1q9fjw0bNsDT0xN16tTBihUr+DszaWlpQVNTE15eXoiOjkb16tVhZGSEP/74Q+pIHBMTE+zcuVPqiJqCa97o6upC9bNzNN3c3ODt7Y2DBw/i7du3qF69Olq1aoX+/fvz67Rr1w4HDhyAu7s75s2bh+zsbNSvXx8dOnRA06ZNpfJmzpyJO3fuYPr06VBUVMTw4cMxc6b0nXPKkr6+Abrb9oDbpg1IiI9H4yZN4X/CD+/evcXSFavkKpelrpU9t1at2rC0+v/pfpnZ+UfIHNq/FwDQxVL6VMDc3FxcPH8WuvoGaNS4CQozcvRYBN68jgk/O2LQ0OHQrF0Lf1+7ihvX/0b/AYNQt+7/T32Uh31QWXNZ6kq57HWlXPa6CpkLAAf370NKSjJi/zvq+drVK4iOzr9ZxLARjqhevbpcdKVc4XJZ6kq5wnZlDZ0exSYFjuO4ii7xPTp+/DjmzZuHwMBAmQv5siIqKgpWVlbYvHkzevToUabZmTnFL8/KyoKn+yac9vdHcnISWonEmDJ1OjpadPqm7QqRy1LX7ym3YNJmktNoJCZ+xMFjJ6WW3751A9MnT8CsufMxeNjIInMeh4Vi+zZP/PPsKZISk9CwUUP07tMPY8aOww8/SM+Ly9s+qEy5LHWlXPa6Ui57XYXM7WljiXfv3ha67Mz5S2jYsFGhyyqiK+UKl8tSV8r9tkzVSnSYw4+/HK/oCkV659X/yyt9p2jSpoLQpE3xvjRpQ8i3Kpi0KUuqSopfXokQQgghhDCDJm3KB03aFK0SfQsSQgghhBBCCCGkUHR2FJPoSBsil+hIGyI0OtKGEEIIIYR8SaU60maiHB9ps42OtCkK3T2KEEIIIYQQQgghRA5VonlDQgghhBBCCCGEFIbuHsUmmrQhhHyX6FQmQgghhBBCiLyj06MIIYQQQgghhBBC5BAdaUMIIYQQQgghhFRydHoUm+hIm++Ai4sLHBwcym17ffr0gYuLi6DbkEgk2Lj+D1h3tYBJO32MGDoIgbduymUuS10pV9iu6Wlp2OLhhkkTnNDJzAQGOmKc8Pv2q/iztG+FymWpK2u59H1LuSx2ZS2Xpa6Uy15XyhW2KyFCo0kbwqRF812wb48P7Bx6YY7LAigqKsJ50gTcv3dX7nJZ6kq5wnb9mPgRXls98TIiAiKx+JuyPsXSvhUql6WurOXS9y3lstiVtVyWulIue10pV9iuhAiOI5Xe3LlzOXt7+3LbXu/evbm5c+d+U0ZGdtGPO/ceciKRiNvmvYMfS0zN5KysrLlBg4cU+9zyzmWpK+UK2zUjm+OS0rK4N+9iuIxsjrsbEsqJRCLu0OFj35TJ0r5l7T2jXPq+pVw2u7KWy1JXymWvK+V+e2Zl0mjyX3L7IEWjI22+MzExMZg3bx6srKygr6+P7t27Y8OGDZBIJFLricVibN++He7u7jA3N4epqSnmzZuH9PR0qfXu37+P/v37Q09PDw4ODrh27Zrgr+Hi+QAoKipiwKAh/JiKigr6DRiIhw9C8OH9e7nJZakr5QrbFQCUlZWhqaVV6ucXhqV9K1QuS11ZzKXvW8plrStruSx1pVz2ulKusF0JKQ80afOd+fjxIzQ0NDBv3jzs2LED48aNg5+fH5YsWSKz7v79+/Hq1SusXr0aU6ZMgb+/P7Zs2cIvj42NhZOTE5SVlbFp0yY4OTlh2bJliI6OFvQ1hIc/RdOmzaCuri41rqunzy+Xl1yWulKusF2FwtK+FSqXpa4s5gqBtX1AuWx1ZS2Xpa6Uy15XyhW2KyHlge4e9Z0Ri8WYO3cu/3W7du2gpqYGFxcXLF68GGpqavwyLS0trF+/HgDQuXNnPHnyBOfOncPs2bMBALt374aCggK2b9+O6tWrAwDq16+PMWPGCPoaYmNjC/1XX01Nrf+Wx8hNLktdKVe4TCGxtG+FymWpK4u5QmBtH1AuW11Zy2WpK+UKl0m5wuay9DNSUHTzKCbRpM13huM47N69G4cPH0ZUVBSysrL4ZW/evIFIJOK/Njc3l3puixYtcPr0af7rhw8fwtTUlJ+wAQAzMzNoaGgI9wIAZGVlQllZWWZcRUUlf3lmptzkstSVcoXLFBJL+1aoXJa6spgrBNb2AeWy1ZW1XJa6Uq5wmZQrbC5LPyMJ+RxN2nxndu/ejTVr1mDcuHEwNTVFjRo1EBYWhuXLl0tN4ABAjRo1pL5WUlKSuvZNbGwsmjZtKrON2rVrC1P+PyoqqjLX4AHA91dRVZWbXJa6Uq5wmUJiad8KlctSVxZzhcDaPqBctrqylstSV8oVLpNyhc1l6WckIZ+jSZvvTEBAACwtLTFr1ix+7MWLF6XK0tLSQnx8vMx4QkJCqfuVdLsxhVw3Jy4u9r/ldeUml6WulCtcppBY2rdC5bLUlcVcIbC2DyiXra6s5bLUlXKFy6RcYXNZ+hkpJAUFOj+KRXQh4u9MZmYmlJSUpMb8/f1LlaWvr4+goCCkpKTwY4GBgUhMTPyWil8k1tZGZOQrpKamSo2HhT4EAGhrt5abXJa6Uq6wXYXC0r4VKpelrizmCoG1fUC5bHVlLZelrpTLXlfKFbYrIeWBJm2+M+bm5rh48SL27duHGzduYM6cOYiMjCxV1ujRo8FxHMaPH49Lly7Bz88PCxYsEPyaNtbdeyA3NxfHjvjyYxKJBCf8jkNP3wD1GzSQm1yWulKusF2FwtK+FSqXpa4s5gqBtX1AuWx1ZS2Xpa6Uy15XyhW2KyHlgU6P+s5MmTIFHz9+hJubGwDA1tYWCxcuxMSJE786q27duti+fTtWrlyJ6dOno0mTJli8eDE2btxY1rWl6OsboLttD7ht2oCE+Hg0btIU/if88O7dWyxdsUquclnqSrnCdi1wcP8+pKQkIzYm/y4F165eQXT0BwDAsBGOUhf2rsi+LOWy1JXFXIC+bymXra6s5bLUlXLZ60q5wnZlDZ0exSYFjuO4ii5ByOcyc4pfnpWVBU/3TTjt74/k5CS0EokxZep0dLTo9E3bFSKXpa6UK2xXAOhpY4l3794WuuzM+Uto2LDRV2eytG+FymWpK4u59H1Luax1ZS2Xpa6Uy15Xyv22TNVKdJhD02mluyxGeYh061XRFeQWTdoQufSlSRtCCCGEEEIIERpN2pQPmrQpGl3ThhBCCCGEEEIIIUQOVaJ5Q0IIIYQQQgghhBSGrmnDJjrShhBCCCGEEEIIIUQO0aQNIYQQQgghhBBCiByi06MIIYQQQgghhJBKjk6PYhMdaUMIIYQQQgghhBAih2jShhBCCCGEEEIIIUQO0aQNYZJEIsHG9X/AuqsFTNrpY8TQQQi8dVMuc1nqSrnsdf333+eYPXMa7GytYNreAF06muLnUSNw9cpluewrVC5LXVnLTU9LwxYPN0ya4IROZiYw0BHjhN9xuexKucLmstSVtVyWulIue10pV9iuTFGQ4wcp0nc/aePi4gIHB4dy2VZycjLEYjGOH//2v+xWRI+goCCIxWKEhYUJ1KzkFs13wb49PrBz6IU5LgugqKgI50kTcP/eXbnLZakr5bLX9f27d0hLS0PvPv0wx2UBJkycDACY7jwJRw/7yl1foXJZ6spa7sfEj/Da6omXEREQicXf1E/orpQrbC5LXVnLZakr5bLXlXKF7UqI4Ljv3Ny5czl7e/ty2VZSUhInEom4Y8eOlcv2yrrH7du3OZFIxIWGhgrU7P8ysot+3Ln3kBOJRNw27x38WGJqJmdlZc0NGjyk2OeWdy5LXSmXva5FPVIzc7hevXpz3W1t5a4vvWfs5SalZXFv3sVwGdkcdzcklBOJRNyhw8e+6XuUtX1AuWx1ZS2Xpa6Uy15Xyv32zMqk2YxTcvsgRfvuj7Qh7Ll4PgCKiooYMGgIP6aiooJ+Awbi4YMQfHj/Xm5yWepKuex1LYqioiLq1W+AlOSUUmewtB9Y6spirrKyMjS1tEr13KKwtg8ol62urOWy1JVy2etKucJ2ZY2CgoLcPkjRaNLmM8+ePYOTkxMMDQ3Rvn17TJs2De/evZNa588//8SAAQPQvn17mJmZ4ZdffsHLly9lsg4fPgxLS0sYGBhg9OjRiIyMlFnH0tISy5cvh4+PD7p06YK2bdvCxcUFEokET58+xdChQ2FoaIiBAwfi2bNnUs/NysqCq6srLCwsoKenhz59+uDChQul6iH+H3vnHV/T/f/xZxIZRoiQoLR2EiPD3jMRoVSpWWKl9mrNtFqt0fI1g1CjWpSf0lo1a5W2qKIERYctiAhZIjfr/P6I3LqSGJGT3I++n9/HeXx7P59znueVz703N973cz7H1ZVly5aZtC1fvhzXp0yF1zSNZcuW0bJlS6pWrYq3tzfLly9/4jEvyvnz5yhdugwFChQwaa/q7mHsNxevSlnFq17WR4mLi+Pevbtcu3qVr1cs5+AvP1Gnbt0s+1QaB5WyqujVA9XGQLxqZVXNq1JW8aqXVbz6ZhWEnCBPbgcwJ27evEmPHj149dVXmTFjBgaDgTlz5tCjRw++//5745v81q1b9OjRg1deeYXY2Fi++eYbunbtyg8//ICDgwMAP/74Ix999BEdOnSgdevW/PHHH4wYMSLD8+7du5eKFSsyadIkrl27xrRp07C2tubkyZP07t2bokWLMnPmTEaMGMH27duxtEyttY0ePZqff/6Zd999l3LlyrF582aGDRvGggUL8Pb2fu4cWeHTTz/l22+/ZeDAgXh6evL7778zc+ZMbG1t6datW7ad51HCw8Mz/Na3aFGnh/23zcarUlbx6ufU05vGrBnTjGvYWFpa4u3TgvfHT8iyT6VxUCmril49UG0MxKtWVtW8KmUVr35O8errVekzUhAeR4o2j7B8+XKSkpL48ssvjcWXSpUq8frrr7Nx40b8/f0B+OCDD4zHJCcn06BBA+rVq8cPP/xAly6pU+4+//xzatasydSpUwFo1KgRBoOBhQsXZnjuhQsXYmNjA8Bvv/3GunXrWLp0KY0bNwYgJSWFgQMH8tdff+Hm5sb58+fZtWsXEydOpGvXrgA0btyY0NBQk6LN8+Z4Hq5evcqqVauYOHGi8eeuX78+8fHxLFiwgC5duhgLTNmJwRBvHKtHsbW1Te2Pjzcbr0pZxaufU09vGj38e9HC14/w27f54YcdJKekkJiYmGWfSuOgUlYVvXqg2hiIV62sqnlVyipe/Zzi1der0meknshlSGoil0c9wrFjx6hTp46xYANQvnx53NzcOH78uLHt5MmT9OnThzp16lC5cmU8PT2Ji4vj8uXLQGoh548//qBFixYm/pYtW2Z43lq1apn8EilTpgyWlpbUfeTShjJlygCps4EAYx4/Pz8TV6tWrTh79ixxcXHPneN5OXToEAC+vr4kJSUZt/r16xMeHm7Mmt3Y2tqRkJCQrt1gMKT229mZjVelrOLVz6mnN42y5cpTt1592rZ7k+CFi4mLi2PYkIFommZWeeU5U8+rB6qNgXjVyqqaV6Ws4tXPKV59vSp9RgrC48hMm0eIjo6mUqVK6dqLFClCVFQUADdu3KBv375UrVqViRMn4uzsjLW1NQMGDDC+6e/evUtSUhKOjo4mnqJFi2Z43oIFC5o8tra2xs7OzqSQY21tDfz7iyUqKgpra2uTAlPaOTRNIyYmhvv37z9Xjufl3r17aJpmUlx6lJs3b1KyZMlsOdejODk5cTssLF37nTvhD/udzcarUlbx6ufU05sZLVq0ZPLECVy5fIkyZcs99/EqjYNKWVX06oFqYyBetbKq5lUpq3j1c4pXX69Kn5GC8Dgy0+YRChUqRERERLr2iIgIChUqBMDPP/9MXFwcwcHB+Pn5Ub16dSpVqmQs6gA4OjqSJ08e7t69a+K5c+dOtmZNTEw0OW/aOSwsLLC3t3+uHDY2NukupYiOjn5qBgsLC9asWcN3332XbnNzc8viT/dkXN3cuHLlMrGxsSbtp0+FAODmlr7wlltelbKKV72sT8JgSJ3mGxMT+5Q9M0alcVApq4pePVBtDMSrVlbVvCplFa96WcWrb1bVsLAw303IHCnaPEKNGjX49ddfTQohFy9e5M8//6RGjRoAxMfHY2FhQZ48/05S2rFjB0lJScbHVlZWVK5cOd2dnH744YdszQqwc+dOk/adO3dSuXJl8uXL91w5ihcvzoULF0za0i5/yox69eoBEBkZibu7e7rt8dXZswsfXz+Sk5NZ/+1aY1tCQgKbN27A3cOT4iVKmI1XpaziVS8rkGGhOTExkS3fb8bOzo7y5cubVV55ztTz6oFqYyBetbKq5lUpq3jVyypefbMKQk4gl0c9Qu/evdmwYQN9+/Zl0KBBGAwGgoKCKFGiBO3btwcwXgr0/vvv07VrV/7++2+++uqrdJc4DRw4kMGDB/P+++8b79q0efPmbMvq5uaGr68v06ZNIz4+nrJly/L9999z4sQJk0WGnzVHy5YtWbFiBe7u7kZXWAZTCB+lbNmydO/enbFjxxIQEICnpyeJiYlcvnyZI0eOZMtixxnh4eGJb0s/5gXN5m5EBK++Vpotmzdy40Yon0z+1Ky8KmUVr3pZASZPnMD92Fhq1KyFs3Mx7twJZ/u2LVy6eJFRYwLJlz+/WeWV50w9L8Ca1auIiYkm/Hbq3TUO7P+RsLBbAHTr7o+9vb1ZZBWvfl6VsqrmVSmreNXLKl59swpCTmChZXWVypeEwMBAzpw5w9atWwE4f/4806dP5/fff8fS0pIGDRoQGBhosjbLpk2bCA4O5vbt21SqVInx48fz7rvv0rRpUyZM+PcWu9988w2LFi3i7t27eHp6MmbMGDp16sTUqVPp0KEDAM2bN0933Pz58/nyyy85ceKEse369et4e3szd+5c4+LD8fHxzJ49m+3btxMZGUm5cuUYOnQovr6+Jj/js+SIi4tj8uTJ7Nu3DwsLC7p06YKDgwPTpk3jzz//BODIkSP07NmT7777Dnd3dwA0TWP16tWsXbuWS5cukT9/fsqWLYufnx+9e/fO8vMSn/TkfoPBwIL5QWzbsoXo6CgqurgyZNgIGjRslOVz6uVVKat41cu6Y/s2Nm34jr//+ouoqEjy5ctP5SpV6PZ2D5o29za7vHp5VcqqordVi+bcuBGaYd/2XXspWbKU2WQVr35elbKq5lUpq3jVyyreF3PavUTTHCqO2fn0nXKJv2f4PX2n/yj/+aKNYJ48rWgjCIIgCIIgCIKgN1K0yRmkaJM5sqaNIAiCIAiCIAiCIAiCGfIS1Q0FQRAEQRAEQRAEQcgIuUuTmshMG0EQBEEQBEEQBEEQBDNEijaCIAiCIAiCIAiCIAhmiFweJQiCIAiCIAiCIAgvORZyfZSSSNFGEARBEP7jpOh0I0lL+eNQEARBEAThhZDLowRBEARBEARBEARBEMwQKdoISpKQkMCcWTPwadqQ2tU96N61E4cPHTRLr0pZxateVvGql9WcvWf/OMOQAe/QsE4NGtSuzqB+ffnz/LknHhMTHU3zxvWpVtWN3bt25lhW8ea8V6WsqnlVyipe9bKKV9+sKmFhYb6bkDlStDFDNmzYgKurK3fv3gXg+vXruLq6snPnv38MN2/enEmTJuVWxFzP8dEHgaxauZzWbdoyNnA8VlZWDB3Un9+PHzM7r0pZxateVvGql9VcvefO/kHfnt25fv0a/QcNof/AIVy9eoV3evtz+dLFTI9bGDyP+AfxOZpVvLnjVSmral6VsopXvazi1TerIOiOJpgdERER2okTJ7TExERN0zTt2rVrmouLi7Zjxw7jPs2aNdMmTpyYWxF1z/EgMfPtt+MhmouLi7ZoyRfGtsjYeM3b20fr1LnLE4/Naa9KWcWrXlbxqpfVXL33E1K0vgH9tJo1a2mhtyO0+wkp2v2EFO1y6C3Ny8tLGzh4iLHt0S3kj/Na5cqVtTnzgjUXFxdt09btJv0qjYF4X56sqnlVyipe9bKK98WdLxOu43aa7fYi7NmzR+vYsaPm5eWlNWjQQBs+fLh29erVdPutW7dO8/X11apWraq1bdtW27dvX7p9oqOjtffff1+rVauW5uXlpQ0bNkwLCwtLt9/x48e1zp07a+7u7lrTpk21xYsXaykpKS/0c2SGzLQxQxwdHfHy8iJPHlknOiP27NqJlZUVb3XqYmyztbWl/VsdCTl5gls3b5qNV6Ws4lUvq3jVy2rO3hO/H6NOvXo4OBQ2tjk5OVOjZi1+PrCfuLj76Y6ZMe0zmnn7UL16jRzNKt6c96qUVTWvSlnFq15W8eqbVTUsLS3MdssqR44cYejQoVSoUIEFCxbwwQcfcP78efr27Ut8/L8zgbdt28ZHH31Eq1atWLp0KV5eXgwdOpSTJ0+a+N59910OHjzIJ598wsyZM7l06RL9+vUjKSnJuM+VK1cICAjAycmJxYsX06tXL+bNm8eXX36Z5Z/jSUjRJosEBgbSpk0bDh06RNu2bfHw8KBHjx5cv36dyMhIRowYQfXq1fHx8WH79u3G4/bv30+fPn2oV68e1atXp1OnTvz0008m7scvj3oSX3zxBY0aNcLT05NBgwZx+/Ztk/7IyEjef/996tSpg4eHB127duXo0aMm+/j7+zNgwAC2bt2Kr68vnp6eDBw4kKioKEJDQwkICKBatWq8/vrrHDlyJEs5spPz589RunQZChQoYNJe1d3D2G8uXpWyile9rOJVL6s5exMSErC1tU3Xbpc3L4mJifzz998m7bt/2EnIyRO8O3J0jmcVb857VcqqmlelrOJVL6t49c0q5D7btm3jlVde4bPPPqN+/fq0bt2aiRMncvXqVc6cOWPcb968ebz++uu8++671K1bl0mTJuHu7s6CBQuM+5w4cYJffvmFTz/9lNatW+Pt7c3cuXP5888/2bVrl3G/ZcuWUbhwYWbPnk29evXo3bs3ffv2ZdGiRSQkJGT7zyhFmxcgPDycadOmMWjQIGbOnMnVq1cZPXo07733Hi4uLsyfP58qVaowZswYQkNDgdT1aZo1a8b06dOZP38+1atXp3///pkWQ57E7t272bNnD5988gmffPIJp06dYtiwYcb+5ORk+vXrx48//sjo0aOZO3cu+fLlo0+fPiYvYICzZ8+ycuVKxo4dy8SJEzl27BgfffQRw4cPp2nTpsyfPx9HR0eGDRvG/fv3nytHdhMeHk5RJ6d07UWLOj3sz1rBSA+vSlnFq59TvPp6Vcpqzt4yZcpy+lQIycnJxrbExAROnzoFwO3bYcb2+Ph4Zs+cTnf/XrxSslSOZxVvzntVyqqaV6Ws4tXPKV59vXplFXKfpKQk8ufPj8Ujqxnb29sDoGkaANeuXePy5cu0atXK5NjWrVtz+PBhY6Hlp59+omDBgjRo0MC4T7ly5ahUqZLJRIuffvoJb29vbGxsTFzR0dGcOHEi239Guf7mBYiKimLVqlVUrFgRgNu3bzN58mT69evHkCFDAHB3dzcWNXr16kWPHj2Mx6ekpFCnTh3++ecf1q1bR506dZ7r/Pfv32fp0qXGF2Xx4sXp3bs3P//8M40aNWL//v2cOnXKOAsGoGHDhvj6+rJ48WLmz59vdMXGxrJo0SIcHR0B+PPPP/nyyy/55JNP6NatGwDOzs60bduWw4cP4+Pj88w5shuDId7kDZJG2jfEhvjnXxBTL69KWcWrn1O8+npVymrO3k5d3+azyZ8wccJ4evV9By0lhaWLF3EnPPzh8Qbjvl99sYSkpEQC+g/IlazizXmvSllV86qUVbz6OcWrr1evrKrxMt6lqUOHDmzevJnVq1fzxhtvEBkZyezZs6lcuTLVq1cH4OLF1BsqlC1b1uTY8uXLk5iYyLVr1yhfvjwXL16kbNmyJgUgSC3cpDni4uK4efMm5cqVS7ePhYUFFy9efO5/1z8NKdq8AM7OzsaCDUCZMmUAqF+/vrGtYMGCODo6cuvWLQBu3brFnDlzOHToEOHh4cbqX5UqVZ77/HXq1DEWSgDq1auHg4MDISEhNGrUiGPHjlGgQAGTwom1tTUtWrRg69atJi43NzdjwSaznyWtLe1nedYc2Y2trV2G084MhtR/UNja2ZmNV6Ws4tXPKV59vSplNWdvpy5dCbt1kxVffcmWzZsAqFylKr37BvDFkkXky5cPgBuh11m5/EsCx39Evnz5cyWreHPeq1JW1bwqZRWvfk7x6uvVK6uQfXh7ez+xf+/evRm216xZk+DgYEaNGmW8q3GlSpX44osvsLKyAlInW0Dqv80fJe1xWn90dLTJv2vTKFSokPFKlZiYmAxdNjY25M2b1+jKTqRo8wI8/kRZW1sDpHuibWxsMBgMpKSkMGjQIGJiYhg+fDilS5cmb968zJs3j5tZWPyqSJEi6docHR0Jf/itaHR0dIb7FC1aNN2L6Vl+lrTqdNovt2fNkd04OTlxOywsXfudO+EP+53NxqtSVvHq5xSvvl6Vspq7d+iI9+jZuy8XLvxDgQIFqOjiyvyg2QC89rBwvzB4Pk7OxahZqw43Qq8/PMcdAO7dvceN0OsUL/EKlpaZX4FtzmMg3pxzilc/p3j19aqUVbz6OQXz4Pfff2fs2LF07tyZpk2bEhkZycKFC+nfvz//93//h91LUJCTNW1ykCtXrnD27FkCAwPp1KkTtWvXxt3d3WRV6+chIiIiXdvdu3dxeni9ZqFChTLc586dOxQqVChL58xKjuzG1c2NK1cuExsba9J++lQIAG5ulczGq1JW8aqXVbzqZVXBW7BQIapVr0FFF1cAjvx6mGLFilO2bOo04Fs3b3Dt6hXa+PnwesvU7f2xowCYOmUir7f04f5jGfTKKt6c86qUVTWvSlnFq15W8eqbVTUsLCzMdtu7d+8Tt8yYMmUKdevWJTAwkLp16+Ln58eSJUs4e/YsmzdvBjD+2zdtlkwa0dHRJv0FCxZM9xqB1Jk4afukTWp43JWQkMCDBw+y9d/ZaUjRJgdJm6GSNosFIDQ0NMuLFR05csTkxXL48GEiIyPx9PQEoEaNGsTGxvLLL78Y90lKSmLPnj3UqPF8t2d9kRzZjY+vH8nJyaz/dq2xLSEhgc0bN+Du4UnxEiXMxqtSVvGql1W86mVVzfvDju38ceY0b/v3NM6cGTL8XWbPDTbZBg8bAUDvvu8we24wdnnz5nhW8errVSmral6VsopXvazi1TerkPtcuHABNzc3k7bixYtTuHBhrl69CmBcfyZtXZo0Ll68iLW1Na+++qpxv0uXLhmXMEnj0qVLRke+fPkoUaJEOlfacY+vdZMdyOVROUi5cuUoXrw4s2bNIiUlhbi4OObNm4ezc9am4+XPn59+/frRr18/YmJimDlzJh4eHsZ1ZJo2bYqHhwdjxoxh1KhRFC1alK+//prbt28zb968bPu5npYju/Hw8MS3pR/zgmZzNyKCV18rzZbNG7lxI5RPJn9qVl6VsopXvaziVS+rOXuPHzvKkkULqVe/AYUKOXD6VAjfb9pA/YaNeLtHT+N+1aqnL/qnfetUuWpVmnn7pOvP7qzizXmvSllV86qUVbzqZRWvvlmF3OeVV17h7NmzJm2hoaHcu3ePkiVLAvDqq69SpkwZdu7caXJDne3bt1OvXj3jMiCNGzdm4cKFHD582Li266VLlzh79izvvPOO8bjGjRuzd+9exowZY5yQsX37dgoWLEi1atWy/We00B4vIwnPRGBgIGfOnDFZ0PfIkSP07NmT7777Dnd3d2N78+bNadq0KRMmTODUqVNMmjSJv/76ixIlSjBo0CB+/fVXE9eGDRt4//33OXz4MI6Ojly/ft14j3g/Pz8TZ/HixVm5ciXR0dHUr1+fiRMnUqxYMeO57927x/Tp09m3bx9xcXFUqVKFkSNHUrt2beM+/v7+5MuXj8WLFxvbHs+QhqurK2PHjiUgIOC5cjwv8UlP7jcYDCyYH8S2LVuIjo6ioosrQ4aNoEHDFysU6eFVKat41csqXvWymqM3RdO4dvUqU6dM5Ny5s8Tdv0/JkqVo0+5N/Hv1xto6/R03HuXYb0fo17cX02cH0cLXz9hu+YTbVJjbGIj35cqqmlelrOJVL6t4X8xp9xJNc3D/aHduR8iU05NbZOm4FStW8Nlnn+Hv70/z5s2JjIzk888/5+7du2zdupXChQsDsHXrVkaPHs3gwYOpU6cO27dv57vvvmPVqlUmhZaAgAAuXLjAuHHjsLW1Zc6cOVhaWrJ+/Xry5El9MVy5coU333yTRo0a0a1bN/766y9mzJjBe++9Z/x3cnYiRRvBLHla0UYQBEHIPlJ0+lPgSUUbQRAEQVABKdrkDFkt2miaxjfffMOaNWu4du0a+fPnx8vLi/fee4/y5cub7Pvtt9+ydOlSbty4QdmyZRk5ciTNmjUz2ScmJoapU6eye/dukpKSaNiwIR9++GG6CQm///4706ZN49y5czg6OtK9e3f69euX7nbh2YEUbQSzRIo2giAIOYcUbQRBEAQhY6RokzNktWjzX+AlegkKgiAIgiAIgiAIgpAReswCEfRH7h4lCIIgCIIgCIIgCIJghkjRRhAEQRAEQRAEQRAEwQyRoo0gCIIgCIIgCIIgCIIZImvaCIIgCEI2o9cS/3pdip6Soo/X0kofryAIgiAIz4+saaMmMtNGEARBEARBEARBEATBDJGijaAkCQkJzJk1A5+mDald3YPuXTtx+NBBs/SqlFU1b9z9+ywMnseg/gE0qlcbzyqubN64wSyzildfr7lmPfrbEbyquma4nQo5adzviyWL8H+7M80a1aV2dXfatvZl+rRPuXv3ri55z5w+xWdTJtH+jdepU9OL1r7NGDf6Xa5cvpSpOzExkY5vvk4NDzdWLl+Wrj88/DZTJn5EWz9v6tfy5I3WLZjxv6lERt57oazPi0pevX6H6ZVXpbHVy/vRB4F4VnHNdAsLCzObrOLV16tSVvHqm1UQ9EaKNoKSfPRBIKtWLqd1m7aMDRyPlZUVQwf15/fjx8zOq1JW1bz3Iu+x+PMFXLp4ERdX1xfKp3dW8errNfes3br78+nU6Sbbq6+9Zuw/d/YPXF3dCOg/kPfHT6BZM2++37SBXj268iAuLtvzfrXsC/bu3kWduvUYFzieDh07c+L4Mbp3eYt//v4rQ/faNau4dfNmhn1xcffp49+VH/ft4fW27RgT+CENGzXmm/9bTf+APqRkcP2VuT9nOeHV63cY/DffZznh7di5C59Om26yTZn6P+zy5qVc+QoUK1bMbLKKV1+vSlnFq29WlbCwMN9NeAKaIJghDxIz3347HqK5uLhoi5Z8YWyLjI3XvL19tE6duzzx2Jz2qpRVRW/UfYN27cZt7UGiph07cUpzcXHRvlm3Pss+FcdAvOaZNS4hdTvwy6+ai4uLtnnrDmPbs27fb9upubi4aBs2bTW2ZVfew78d16LvG4yPY+JTtD/+vKhVrVpVG/HeKC0mPsVkuxIarlWvUUObPTdYc3Fx0RYsWmrSv279Zs3FxUXbvmufSfusOXM1FxcX7fdTf5j9c5YbXj1+h/2X3me54c1oO/jrUc3FxUWbv+Bzs8oqXnk/iDd7nC8Tnh/vMdtNyByZaSMox55dO7GysuKtTl2Mbba2trR/qyMhJ09k+k1wbnhVyqqi18bGhqJOTlk6NjNUGwPxqpP1/v1YkpKSnnn/V14pCUBMTHS25/WqVh1rGxuT418rXYZy5Stw6eKFdO75c2dRunRZWr/+Robnvn//PgBFihQxaU97f9rZ2mY56/OgmleP32Hw336f6e3NiB3btmJhYUGr19tk6XjVxkC8amUVr75ZBSEnkKKNmRMYGEibNm04dOgQbdu2xcPDgx49enD9+nUiIyMZMWIE1atXx8fHh+3btxuPO378ON27d6dGjRpUq1aNtm3bsnHjRhP3/v376dq1K56entSqVQt/f3/Onj0LQFxcHJMmTaJly5Z4enrSvHlzJkyYQExMjImjefPmTJo0idWrV9OsWTNq1KjB4MGDn3sdhufh/PlzlC5dhgIFCpi0V3X3MPabi1elrCp69UC1MRCvGlk//vB9GtSpQZ0aHrzTx58/zpxOt4+mady7d5c7d8L5/fgx/jd1ClZWVtSsVTtH8mqaxt2ICBwKFzZpP3P6FFu/38Toce9nOn25eo2aWFpaMvN/n3E65CRht27xy88H+GLJIpp5+1C2XPlszZoZqnn14r/6PssJ7+MkJiay64cdeHpVo2TJUllyqDYG4lUrq3j1zaoaFhYWZrsJmSO3/FaA8PBwpk2bxqBBg8iTJw9Tpkxh9OjR5M2bl5o1a9K5c2fWrVvHmDFj8PT0pFChQgwYMIAaNWowe/ZsbGxs+Oeff4iO/vfb2u3btzNy5Ei8vb2ZNWsW1tbW/P7774SFhVG5cmXi4+NJTk7mvffew9HRkZs3b7Jo0SIGDx7M119/bZJv3759XLlyhQkTJnDv3j2mTp3K5MmTmTNnjm7jkdE3k0WLOj3sv202XpWyqujVA9XGQLzmndXa2hqfFi1p2KgxDoULc/HCBVYuX0bfXt1Zseob3CpVNu4bEXEHn6YNjY+LFSvOZ/+bma7goVfeHdu2cPt2GAOHDDe2aZrG9KlTaNGyFR6e1bgRej3DY8uVr8D4CZMImjWd3v5dje1vtGvPx5OmZHvWzFDNqxf/tfdZTnof59DBX4iMjOT1Nm2z7FBtDMSrVlbx6ucUhJxCijYKEBUVxapVq6hYsSIAt2/fZvLkyfTr148hQ4YA4O7uzu7du9mzZw/Vq1cnJiaGkSNH4vpwYcN69eoZfZqm8b///Y8GDRqwYMECY3uTJk2M/+3o6MjEiRONj5OSkihVqhRvv/02ly5domzZsia+zz//HJuHU+1DQ0NZvHgxKSkpWFpm/2QugyHeeK5HsX04/d4QH282XpWyqujVA9XGQLzmndWrWnW8qlU3Pm7azBsf35Z07vAG84JmsXDxv3dhKlSoEIuWfkWCwcD582fZu2f3cy1C/CJ5L126yLTPJuHh6UWbN940tm/ZvIF//vmL6bPnPvX8zs7FqOLuToOGTSjxyiuc+P0Ya/9vFQ6FCzNqzLhsy/okVPPqxX/tfZaT3sfZsW0refJY4+vXKssO1cZAvGplFa9+TkHIKaRoowDOzs7Ggg1AmTJlAKhfv76xrWDBgjg6OnLr1i1ee+01ChQowCeffIK/vz9169bF0dHRuO/Fixe5desW48aZ/hH9OJs2bWL58uVcuXKFuEf+4XD58mWTok2tWrVMfgmWL1+exMREIiIicNLhWn1bWzsSEhLStRsMhtR+Ozuz8aqUVUWvHqg2BuJVKyvAa6+Vpmkzb/bu2UVycjJWVlYAWFvbULde6u/1xk2bUbtOPXr7d8PRsQiNmzbTLe+d8HBGDBlAgQL2TJ8115gnNjaW4Llz6NmrL8WLl3jiuU+e+J13hw1k+apvqFzFHYBmzX0oaG/PooXBvNn+LcpXqPDCWZ+Gal69kPdZzjxncffv8+OPe6nfoCEODoWffkAmqDYG4lUrq3j1c6qIXIWkJrKmjQIULFjQ5LG1tTUA9vb2Ju02NjYYDAYKFSrEV199Rf78+Rk7diwNGjTA39+fP//8E4DIyEggtRiUGbt372bcuHF4eHgQFBTEunXrjLNy0n65ZZYvrYDz+H7ZhZOTE3fCw9O137kT/rA/858rp70qZVXRqweqjYF41cqaRrHixUlMTOTBgweZ7uNVrTpOTk5s37blmZxZyRsTE8Pggf2IjYkm+POlODkXM/Z9veJLEhMT8fVrzY3Q69wIvU5YWFjqcdHR3Ai9TmJi6h/AG75di2ORIsaCTRpNmjVH0zRCTp544azPgmpevZD3Wc48Z/v27SH+wQNav8ClUalZ1BoD8aqVVbz6OQUhp5CizUuKh4cHX3zxBceOHWPRokVEREQYL6VycHAAUi+zyoydO3dSqVIlJk2aRJMmTfD09ExXnMktXN3cuHLlMrGxsSbtp0+FAODmVslsvCplVdGrB6qNgXjVyppG6PXr2Nraki9fvifuZzAkEBMb88R90njevAaDgeFDBnLlymWCghdRrnwFk/5bN28QHR1Fp/ZtaNvKh7atfHind3cAvvxiMW1b+XDxQuqdpiLu3iElOSVdpqTE1LtlJSWb3jVLtedMpd9hIO8zPb2Psn3rFvLly0fTZs1fyKPaGIhXrazi1TerIOQEUrR5ybGzs6NJkyZ069aN69evYzAYKFeuHMWLF2fDhg2ZHhcfH2+c0ZPGli3P9m2v3vj4+pGcnMz6b9ca2xISEti8cQPuHp4UL/Hkafw56VUpq4pePVBtDMRr3lkzupPen+fPs//HfdSr3wBLS0sexMVlOONmz+4fiI6OokqVqtmeNzk5mbGj3uVUyElmzp6Lh2e1dL6ub/szMyjYZBs/IXWts7bt2jMzKJhXHt4tp3TpMkRE3OHY0SMmjp3btwKYLLj8vFmfB9W8evFfe5/lpDeNu3fvcuTXwzT3aUHevHlfyKXaGIhXrazi1TerauT2HaLk7lFZQ9a0eQnZv38/3333HT4+PrzyyivcuXOHVatWUb16deNiW+PGjWPkyJEMGzaMdu3aYWNjw8mTJ3F3d6dZs2bUr1+fSZMmsWDBAqpVq8aBAwc4fPhwLv9kqXh4eOLb0o95QbO5GxHBq6+VZsvmjdy4Econkz81K69KWVX0AqxZvYqYmGjCH84cO7D/R8LCbgHQrbt/ussIcyurePXzmnPWcaPfxdbWDk+vajgWKcLFC/+w/rt12OW1Y/i7owG4cvUKA9/pja9fa8qWLYeFpSVn/zjD9q3f80rJkrzdo2e25501fRr7f9xHk6bNiIqKZPvW7036W7d5g0qVq1CpchWT9rS7R5UrX4FmzX2M7Z27duf7TRt5b9ggunTrQYlXXuH4saP8sGMbdes3wMPDM9vH9kXHwBy8kP2/w/TKq9rY6vmcAfywYztJSUm0fv3FLo3SM6t49fOqlFW8+mYVhJzAQtM0LbdDCJkTGBjImTNn2Lp1q7HtyJEj9OzZk++++w5393/XD2jevDlNmzalR48eBAUFcerUKSIiInBwcKBhw4aMHDnSZGHgffv2sWjRIs6fP4+trS2VK1cmMDCQSpUqkZyczMyZM9m0aRMGg4GGDRsSEBBA586dmTt3Ln5+fibnnDBhgtG7Z88ehgwZwt69eylVqlSWfu74pCf3GwwGFswPYtuWLURHR1HRxZUhw0bQoGGjLJ1PT69KWVX0tmrRnBs3QjPs275rLyVLPv9rULUxEK/5ZU37ZP2/VSvZvm0L165e5f79WAoXLkztOvUYMHgor71WGoB79+4SPC+I348d5datWyQlJVLilZI0atyEd/oPpHDhfxeSf9oXUc+aN6C3P8eO/pap5/ip8xm23wi9TttWPowYOYaevQNM+i5fusjC4LmcOX2KiDt3cHJ2wrelH4OGDM9wJoK5PWe55dXjdxj8N95nueUF8H+7C9evX2PPjz8bF+82x6zi1c+rUlbxvpjT7iWa5lBj8o+5HSFTjn/09Jsu/FeRoo1gljytaCMIgmDO6PXJqtfs4aRkfQLnsZLpzoIgCILavExFm5pTzLdoc+xDKdpkhqxpIwiCIAiCIAiCIAiCYIZI0UYQBEEQBEEQBEEQBMEMeYkmewmCIAiCIAiCIAiCkBFylyY1kZk2giAIgiAIgiAIgiAIZogUbQRBEARBEARBEARBEMwQuTxKEARBELIZ1WYfy12eBEEQBOHlR7W/T4RUZKaNIAiCIAiCIAiCIAiCGSJFG0EQBEEQBEEQBEEQBDNEijaKcv36dVxdXdm5c6exbfny5Rw4cCDdvs2bN2fSpEnGx4GBgbRp0yZHcupFQkICc2bNwKdpQ2pX96B7104cPnTQLL0qZRWvelnFm0rc/fssDJ7HoP4BNKpXG88qrmzeuMEss6rovXLlMmNHv0eL5o2pU8OTdm38WLQwmAcPHphdVvHq51Upq2pelbKKV72s4tU3q0pYWFiY7SZkjhRtXiJWrlyZYdEmODiYvn375kIi/fjog0BWrVxO6zZtGRs4HisrK4YO6s/vx4+ZnVelrOJVL6t4U7kXeY/Fny/g0sWLuLi6vlA+vbOq5r118ybdu3bidEgIXbv1YMy4D/DwrMbnC+YTOGakWWUVr75elbKq5lUpq3jVyypefbMKgu5ogpJcu3ZNc3Fx0Xbs2GFsa9asmTZx4sSnHjtu3Djt9ddf1zPeC/MgMfPtt+MhmouLi7ZoyRfGtsjYeM3b20fr1LnLE4/Naa9KWcWrXlbx/rtF3Tdo127c1h4katqxE6c0FxcX7Zt167PsU3EM9PLOX/C55uLiop0+95dJ+6jRYzUXFxct7E6k2WQVr35elbKq5lUpq3jVyyreF3e+TNT+bL/ZbkLmyEwbHUm7DOnQoUO0bdsWDw8PevTowfXr14mMjGTEiBFUr14dHx8ftm/fbjzu8cuZAPbs2YOrqyvXr1/P8FzNmzcnNDSU1atX4+rqiqurKxs2bMjUB3DkyBHefPNNvLy86NixI2fOnDHpNxgMTJ06lYYNG+Lu7k67du3YvXt3hj/jgQMHaNOmDe7u7nTo0IGTJ09mZcieiT27dmJlZcVbnboY22xtbWn/VkdCTp7g1s2bZuNVKat41csq3n+xsbGhqJNTlo7NDNXGQC9vbGwsAEWKFDFpL+rkhKWlJXmsrc0mq3j186qUVTWvSlnFq15W8eqbVTUsLMx3EzJHijY6Ex4ezrRp0xg0aBAzZ87k6tWrjB49mvfeew8XFxfmz59PlSpVGDNmDKGhoVk+T3BwME5OTrRs2ZK1a9eydu1amjZt+sRcU6ZMISAggKCgIAwGA0OHDiUxMdG4z+jRo1m7di3vvPMOCxYsoEKFCgwbNoy9e/emc02cONHosrGxISAggIiIiCz/PE/i/PlzlC5dhgIFCpi0V3X3MPabi1elrOJVL6t49UW1MdDLW6tWbQA++Wg858+d49bNm+zcsZ1v167h7e7+5MuXz2yyilc/r0pZVfOqlFW86mUVr75ZBSEnyJPbAV52oqKiWLVqFRUrVgTg9u3bTJ48mX79+jFkyBAA3N3d2b17N3v27KFXr15ZOk/lypVTv2kuWhQvL6/nzpU3b1569uxJSEgINWvW5Pz58+zatYuJEyfStWtXABo3bkxoaCgLFizA29vb6IqMjCQoKIh69eoBULt2bZo0acLy5csZNWpUln6eJxEeHp7hN+pFizo97L9tNl6VsopXP6d49ffqgWpjoJe3QaPGDBk2gmVLF7P/x33G9n79BzJ0xHtmlVW8+nlVyqqaV6Ws4tXPKV59vSr9/SEIjyNFG51xdnY2FkYAypQpA0D9+vWNbQULFsTR0ZFbt27lWq4KFSoAEBYWBsDx48cB8PPzMzmuVatWTJ06lbi4OOO3q/b29saCTdrj+vXrExISokt2gyEeGxubdO22trap/fHxZuNVKat49XOKV3+vHqg2BnqO7SslS1K9Rk18WrSkkIMDP/+0ny+WLqZIUSe6de9hNlnFq59XpayqeVXKKl79nOLV16vS3x96IndpUhMp2uhMwYIFTR5bP7z2397e3qTdxsYGg8GQ67nSMkRFRWFtbY2Dg4PJfkWLFkXTNGJiYoxFG0dHx3T+IkWKcOHCBR2Sg62tHQkJCena07Lb2tmZjVelrOLVzyle/b16oNoY6OXdsX0bkz+ZwPfbfqBY8eIA+LTwJSVFI2jOTFq9/joODoXNIqt49fOqlFU1r0pZxaufU7z6elX6+0MQHkfWtDFDbGxsTNaWgdQiSk5SqFAhEhMT0533zp07WFhYmBSd7t69m+74iIgInLJ5UdA0nJycuBMenq79zp3wh/3OZuNVKat49XOKV3+vHqg2Bnp5133zf7i5VTIWbNJo2qw58Q8ecP7c868DoNoYiFetrKp5VcoqXv2c4tXXq9LfH4LwOFK0MUOKFy+ebpbKwYMHn3qctbV1ts3WqVGjBgA7d+40ad+5cyeVK1c2WXgyJiaGw4cPmzw+dOgQnp6e2ZLlcVzd3Lhy5bLxjiZpnD6VejmWm1sls/GqlFW86mUVr76oNgZ6eSMi7pCckpKuPSkp9cuF5KSk53aqNgbiVSural6VsopXvazi1TerauT2HaLk7lFZQ4o2ZkjLli05fvw4wcHBHDx4kM8+++yZbqFdrlw5fv31Vw4ePMjp06e5d+9eljO4ubnh6+vLtGnTWLFiBT/99BOjR4/mxIkTDB061GRfBwcHxo8fz6ZNm9i7dy/9+vVD07QsL6r8NHx8/UhOTmb9t2uNbQkJCWzeuAF3D0+KlyhhNl6VsopXvazi1RfVxkAvb+nSZTl/7iyXL18yad+xfRuWlpZUdHU1m6zi1c+rUlbVvCplFa96WcWrb1ZByAlkTRszpFOnTly9epU1a9awfPlyWrduzciRI596J6aRI0fyySefMGzYMO7fv8/UqVPp0KFDlnPMmDGD2bNns3TpUiIjIylXrhzz5s2jefPmJvs5OTkxevRopk+fztWrV6lYsSLLli2jaNGiWT73k/Dw8MS3pR/zgmZzNyKCV18rzZbNG7lxI5RPJn9qVl6VsopXvaziNWXN6lXExEQTfjv1DhAH9v9IWFjqAu/duvunW0sst7Kq5u3dN4CDv/xEn57d6dqtOw4ODvx0YD+//PwTHd7qhLNzMbPJKl79vCplVc2rUlbxqpdVvPpmFYScwELTNC23QwjqEhgYyJkzZ9i6dWu2euOfMtveYDCwYH4Q27ZsITo6ioourgwZNoIGDRu90Hn18KqUVbzqZRXvv7Rq0ZwbN0Iz7Nu+ay8lS5Yym6yqeU+fOsWihfM5f+4ckZGRlCxVkjfatad333fIkydr3/+oNgbiVSural6VsopXvazifTGn3Us0zaHBjJ9zO0KmHBzzYq+Zlxkp2ggvRG4VbQRBEARBEARBEPRGijY5gxRtMkfWtBEEQRAEQRAEQRAEQTBDXqK6oZAbTJs2LbcjCIIgCIIgCIIgCE9B7tKkJjLTRhAEQRAEQRAEQRAEwQyRoo0gCIIgCIIgCIIgCIIZIkUbQRAEQRAEQRAEQRAEM0TWtBEEQRAEQRAEQRCElxwLWdRGSWSmjSAIgiAIgiAIgiAIghkiRRsh2xk8eDD+/v66niMhIYE5s2bg07Qhtat70L1rJw4fOmiWXpWyile9rOJVL6tq3jOnT/HZlEm0f+N16tT0oqV3U8aMHMHly5fMLqt49fWqlFU1r0pZxateVvHqm1UQ9EaKNoKSfPRBIKtWLqd1m7aMDRyPlZUVQwf15/fjx8zOq1JW8aqXVbzqZVXN+9WyL9i7exd16tZjXOB43urUmePHjtG1Ywf+/vsvs8oqXn29KmVVzatSVvGql1W8+mZVCQsLC7PdhCegCUI2M2jQIK1Hjx4v5HiQmPn22/EQzcXFRVu05AtjW2RsvObt7aN16tzlicfmtFelrOJVL6t41cuqovfwb8e16PsGk7bz/1zSqlatqr07cpRZZRWvfl6VsqrmVSmreNXLKt4Xd75MNJr1i9luQubITBszJDAwkDZt2nDkyBHefPNNvLy86NixI2fOnDHu8+WXX/LWW29Ro0YN6tWrx4ABA7h06VKGnkOHDtG2bVs8PDzo0aMH169fJzIykhEjRlC9enV8fHzYvn17uhz79++nU6dOeHh4ULduXT7++GPi4uJM9rlw4QI9evTA3d0dHx8fNm7cqM+gPMKeXTuxsrLirU5djG22tra0f6sjISdPcOvmTbPxqpRVvOplFa96WVX0elWrjrWNjUlb6dJlKF+hIpcuXjSrrOLVz6tSVtW8KmUVr3pZxatvVkHICaRoY6aEh4czZcoUAgICCAoKwmAwMHToUBITEwG4desWPXr0YOHChUyZMoWUlBS6du1KZGRkOs+0adMYNGgQM2fO5OrVq4wePZr33nsPFxcX5s+fT5UqVRgzZgyhoaHG43bu3MmgQYNwcXEhODiYMWPGsHv3bsaPH2/cx2Aw0LdvX+7cucP06dMZNWoUS5Ys4fTp07qOzfnz5yhdugwFChQwaa/q7mHsNxevSlnFq15W8aqXVUVvRmiaRkTEHRwcCmfpeNXGQLxqZVXNq1JW8aqXVbz6ZlUNCwvz3YTMkVt+mylRUVGsWrWKihUrApA3b1569uxJSEgINWvW5IMPPjDum5ycTIMGDahXrx4//PADXbp0ydRz+/ZtJk+eTL9+/RgyZAgA7u7u7N69mz179tCrVy80TWP69Om0bt2aTz/91OhycnKif//+DB48mIoVK7JhwwZu377Njh07KFOmDACVK1fGz8/P+FgPwsPDKerklK69aFGnh/23zcarUlbx6ucUr75elbKq6M2IbVu/53ZYGIOHDs/S8aqNgXjVyqqaV6Ws4tXPKV59vTn5GSkI2Y0UbcwUZ2dnY6EFoEKFCgCEhYUBcPLkSebOncvZs2dNZtdcvnz5iZ60Ykr9+vWNbQULFsTR0ZFbt24BcOnSJUJDQ/nggw9ISkoy7le7dm0sLS05c+YMFStW5NSpU1SsWNGkQFO6dGnc3Nxe6Gd/GgZDPDaPTdWH1CmOAIb4eLPxqpRVvPo5xauvV6WsKnof59LFC0ydMglPr2q80a59lhyqjYF41cqqmlelrOLVzylefb059RkpCHogRRszpWDBgiaPra2tgdRLkm7cuEHfvn2pWrUqEydOxNnZGWtrawYMGIDBYHgmj729vUm7jY2N8dh79+4BGGfiPM7Nh9d83r59myJFiqTrL1KkSLoc2YmtrR0JCQnp2tPOaWtnZzZelbKKVz+nePX1qpRVRe+j3AkPZ+jgARQoYM/MOXOxsrLKkke1MRCvWllV86qUVbz6OcWrrzcnPiNVQO7SpCZStFGQn3/+mbi4OIKDg41FmaSkJKKiorLF7+DgAMCECRPw8PBI1+/s7Gz8/z/++CNdf0RERLrrRbMTJycnbj+ccfQod+6EP+x3NhuvSlnFq59TvPp6VcqqojeNmJgYBg/sR0x0DF+tXI2zc7Esu1QbA/GqlVU1r0pZxaufU7z6evX+jBQEPZGFiBUkPj4eCwsL8uT5t+a2Y8cOk0uZXoRy5cpRvHhxrl27hru7e7qtWLHUP9Td3d35+++/uXLlivHYK1eucP78+WzJkRmubm5cuXKZ2NhYk/bTp0IAcHOrZDZelbKKV72s4lUvq4peSP0mcviQgVy5cpn5CxdR/uElu1lFtTEQr1pZVfOqlFW86mUVr75ZBSEnkKKNgtStWxeA999/n8OHD7Ny5Upmz56d7lKorGJhYUFgYCBff/01EyZMYN++fRw+fJj169czfPhw463FO3ToQNGiRRkwYAA7duxgx44dDBw4kKJFi2ZLjszw8fUjOTmZ9d+uNbYlJCSweeMG3D08KV6ihNl4VcoqXvWyile9rCp6k5OTGTvqXU6FnGTm7Ll4elXLkicnsopXP69KWVXzqpRVvOplFa++WVUjt+8QJXePyhpyeZSCuLq6MnXqVIKDgxkwYACVKlVi7ty5vPvuu9l2jlatWlGwYEEWLVrEli1bAChZsiSNGjUyFmXs7Oz48ssv+eSTTxgzZgzFihVj8ODB7N27l5iYmGzL8jgeHp74tvRjXtBs7kZE8OprpdmyeSM3boTyyeRPny7IQa9KWcWrXlbxqpdVRe+s6dPY/+M+mjRtRlRUJFu3bDbpb9O2ndlkFa9+XpWyquZVKat41csqXn2zCkJOYKFpmpbbIQThceKfcqWXwWBgwfwgtm3ZQnR0FBVdXBkybAQNGjZ6ofPq4VUpq3jVyype9bKq5g3o7c+xo79l2h/yx59Z8qo0BuJVL6tqXpWyile9rOJ9MafdSzTNodncQ7kdIVN+HFH/6Tv9R5GijWCWPK1oIwiCIAiCIAiCoDcvU9Gm+bzDuR0hU/YNr5fbEcwWWdNGEARBEARBEARBEATBDJGijSAIgiAIgiAIgiAIghnyEk32EgRBEARBEARBEAQhI+QuTWoiM20EQRAEQRAEQRAEQRDMECnaCIIgCIIgCIIgCIIgmCFyeZQgCIIgZDMdlx3VxftdQC1dvIIgCIIgvPxYyvVRSiIzbQRBEARBEARBEARBEMwQKdoISpKQkMCcWTPwadqQ2tU96N61E4cPHTRLr0pZxateVvHmXlYLwNoSbK1SNxsrsHrsC6w8lhZ0qlaCzztXZUNADb729+Jjv4oUyW9t3Me9hD1bB9TKcHN1zm/is7JIPc+j58zzyCe5HuMQd/8+C4PnMah/AI3q1caziiubN254IadeWcWrr1elrKp5VcoqXvWyilffrIKgN1K0eYnZsGEDW7Zsye0YuvDRB4GsWrmc1m3aMjZwPFZWVgwd1J/fjx8zO69KWcWrXlbx5k7WC//8hY1V6l0YklJStxTN9K4MVpYWfNyqIl2qleD361F8/ssVNoTcJD4phfw2VunO9f3pMGbuu2iy3Yw2mOxjaZF6nkfPmVbI0Wsc7kXeY/HnC7h08SIurq5Z9jyOSq8v8aqXVTWvSlnFq15W8eqbVSUsLMx3EzLHQtM0LbdDCPrg7+9Pvnz5WLx4cW5HeW7ikzLvO33qFD26dWLk6LH06hMAgMFg4K12bXAsUoSVq7/J0jn18KqUVbzqZRVv7mT179aZlStXYF/QgcSUjI/tuOwob3kWp0etkozbfJ6/wu9neh73EvZMfcONqbv+4eCle0/MlNGaNpYPizbHT5zi7a7ZPw4JCQlER0VR1MmJP86c5u0uHZk0ZSrt2nfIkg/Uen2JV72sqnlVyipe9bKK98Wddi/RKrC+C37N7QiZsmtI3dyOYLbITBtBOfbs2omVlRVvdepibLO1taX9Wx0JOXmCWzdvmo1XpaziVS+reHMn68hRo3BwcOBWWHimx1oAb7gX4/DlSP4Kv4+lBdjmefpHbl5rSyyf89umtK9edus0DjY2NhR1csrSsZmh0utLvOplVc2rUlbxqpdVvPpmFYScQIo2OUhgYCBt2rThyJEjvPnmm3h5edGxY0fOnDlj3EfTNJYtW0bLli2pWrUq3t7eLF++3MQzf/58qlWrxqlTp+jYsSPu7u60atWKH3/80biPv78/v/32G/v378fV1RVXV1fmz58PQPPmzZk0aZKJc8+ePbi6unL9+nUArl+/jqurK5s3b2bSpEnUqlWLhg0b8r///Y+kJNNpMBcuXGDQoEHUqFEDLy8v+vfvz9WrV7Nz6Ew4f/4cpUuXoUCBAibtVd09jP3m4lUpq3jVyyre3MlapUoVYmJiuHHjOjZWqd/A2T62tsxrhfNSJL8NlyPiGNq4NOsDarA+oAbzO1bB/RX7DM83omlZvu1bg43v1OSzNq5UKJrvqRktAGur1MLNuXP6jIMeqPT6Eq96WVXzqpRVvOplFa++WVXDwsLCbDchc6Rok8OEh4czZcoUAgICCAoKwmAwMHToUBITEwH49NNPmTdvHm+++SZLliyhffv2zJw5kzVr1ph4EhMTee+992jfvj3BwcGULl2aoUOH8ueffwLw8ccfU7lyZapXr87atWtZu3YtnTp1eu68QUFBWFpaEhQURNeuXfnyyy/59ttvjf3Xrl2ja9euREVFMW3aNGbOnMndu3fp3bs3CQkJLzBSmRMeHp7ht75Fizo97L9tNl6VsopXP6d49fXmdFb7AgWwsrKimqc7KRokJEOyllq0sX74qfpKIVsA2rkXw71EQYJ/usycHy9iY2XJpNYulHHMa/QlpmgcvHiXpYeuMmnn33x99DqlHfPyv3aVKFck48KNXZ6HxaI8qYWbxBT9xkEPVHp9iVc/p3j1c4pXX69KWcWrn1MQcoqX6Ao9NYiKimLVqlVUrFgRgLx589KzZ09CQkJwdnZm1apVTJw4kS5dUqfu1a9fn/j4eBYsWECXLl2wtEz9F0FiYiKDBg2iY8eOADRs2BBfX18WL17M7NmzqVChAgUKFCBfvnx4eXllOa+HhwcffvghAA0aNODIkSP88MMPdOvWDYDg4GAKFSrEV199ha1t6j9Sqlevjre3N99++y3du3fP8rkzw2CIx8bGJl172vkN8fFm41Upq3j1c4pXX29OZ7WyssLOzpZz585TtqIbkLogMKQWbpJSwM46dWXgfDZWjFh/ljv3U4vYp27EsKSrO295lWDWvosAnA+LZeruWKP/tytw8OI95nesQq86pfh4+1/pMiQkp/6/BWBlmfr/eo2DHqj0+hKvfk7x6ucUr75elbKKVz+nIOQUMtMmh3F2djYWbAAqVKgAQFhYGIcOHQLA19eXpKQk41a/fn3Cw8O5+di1li1atDD+t5WVFT4+PoSEhGRr3oYNG5o8Ll++PLdu3TI+PnjwIM2bN8fKysqYt2DBglSuXNnksq/sxNbWLsNZPAZD6l1WbO3szMarUlbx6ucUr77enM6anJJaMbl6PfSx9tT/t7CAhKTUB2dvxRoLNgDhsQmcvRVLpWKmt/J+nJvRBo5cicTjFfsM17hJ0VK3ZA0Sk1MvkbLTaRz0QKXXl3j1c4pXP6d49fWqlFW8+jlVxNLCfDchc2SmTQ5TsGBBk8fW1tZA6i+Me/fuoWkadetmvHL2zZs3KVmypPG4QoUKmfQXKVKE8PDMF8bMCvb2pmsvWFtbm/zCu3fvHitWrGDFihXpjk372bIbJycnboeFpWu/cyf8Yb+z2XhVyipe/Zzi1deb01nj4h5gZ2tLvnwZF14sgIi41EteIx8kpuuPepBI+WdYr+ZObALWVpbY5rHkQWa3qQI0Ute0cXJyIkyHcdADlV5f4tXPKV79nOLV16tSVvHq5xSEnEJm2pgRhQoVwsLCgjVr1vDdd9+l29zc3Iz7JiYmEhUVZXJ8REQETs9whw8bGxvjGjppPO56nswdOnTIMO+ECROy5Hwarm5uXLlymdjYWJP206dSZxm5uVUyG69KWcWrXlbx5k7WS5dSL2t6dNYkpM6wgdQiypW7cSQmp1Akf/qp2I75bYh6kJSu/XGKF7TFkJRC/BMKNo/iVkmfcdADlV5f4lUvq2pelbKKV72s4tU3qyDkBFK0MSPq1asHQGRkJO7u7um2x1c73717t/G/k5OT2bNnD56ensY2a2tr45S/RylevDgXLlwwaTt48GCWM//9999Urlw5Xd5y5cplyfk0fHz9SE5OZv23a41tCQkJbN64AXcPT4qXKGE2XpWyile9rOLNnaxLlywFwKloEZP9rSxSZ7ykaPAgMYVjV6OoVKwApRz+nXJdysGOSsUKcCL030J5Qbv0k17LOualdmkHTlyP4uFyOZneMtzSIrVg5KvTOOiBSq8v8aqXVTWvSlnFq15W8eqbVTVy+w5RcveorCGXR5kRZcuWpXv37owdO5aAgAA8PT1JTEzk8uXLHDlyhIULFxr3tba25vPPP8dgMFCqVCnWrFnDrVu3WLBggXGfcuXKsWnTJvbt24eTkxPOzs4UK1aMli1b8sknnxAcHEy1atU4cOAAJ0+ezFLm4cOH07FjRwICAujcuTNFixblzp07/Pbbb9SsWZM2bdq86LCkw8PDE9+WfswLms3diAhefa00WzZv5MaNUD6Z/KlZeVXKKl71soo3d7KeOXOasNvhFHNOndmYoqUWTqweLkKcxsrfruNZsiCftnFly5nUKdltqxYjxpDEt7//u0bZOJ/yJCSlcC4slqgHibxaOC9+lZwwJKWw/Mh1436vFLLF1ip1HRvtYSXHwiK1WJSiQWV3fcYBYM3qVcTERBN+O/XuGgf2/0hYWOr6Zt26+6e7lPZpqPT6Eq96WVXzqpRVvOplFa++WQUhJ7DQtLQ//QS9CQwM5MyZM2zdutXYFh0dTa1atZg6dSodOnRA0zRWr17N2rVruXTpEvnz56ds2bL4+fnRu3dvAObPn8+XX37J8uXLmThxIn/99RelSpVizJgxeHt7G91hYWF89NFHnDhxgujoaIYOHcqwYcNISkpi1qxZfP/99xgMBlq3bk3t2rUZNWoUe/fupVSpUly/fh1vb2/mzp2Ln5+f0fnpp5+yd+9e9u3bZ2y7fPkyQUFBHD58mLi4OJycnKhVqxbvvPNOussHnpX4p1w5YDAYWDA/iG1bthAdHUVFF1eGDBtBg4aNsnQ+Pb0qZRWvelnFm3tZrSxS7xYFqZdEJaekFlQAOi47CkD5ovnoXacUbsUKoGkQEhrNV79e40b0v7Mg21Z1pmmFIpQoZEc+a0ui4pMICY1mzfEb3Hxkv4J2eVjpXy11Zg3/njdF+7dYpNc4tGrRnBs3QjPs275rLyVLlnpup0qvL/Gql1U1r0pZxateVvG+mDODCbHK0nrRb7kdIVO2D6yd2xHMFinaKEha0ebEiRO5HUU3nla0EQRBMGfSijbZzXcBtXTxCoIgCIKQMS9T0eb1xeZbtNk2QIo2mSFr2giCIAiCIAiCIAiCIJghUrQRBEEQBEEQBEEQBEEwQ6RooyDDhg17qS+NEgRBEARBEARBELIXCzP+n5A5UrQRBEEQBEEQBEEQBEEwQ6RoIwiCIAiCIAiCIAiCYIa8RGthC4IgCIJ5oNddnpJT9Lnho5WlTEsWBEEQhJcd+bhXE5lpIwiCIAiCIAiCIAiCYIZI0UZQkoSEBObMmoFP04bUru5B966dOHzooFl6Vcoq3lTOnD7FZ1Mm0f6N16lT04uW3k0ZM3IEly9fMrus4lUv6/N4H38ttm7RjHGj3uVKBq/FixcvMGTgOzSoXZ2mDerw4ftjuXf37hNzbN+6herubtStWS1b8j4PuT224jUPp3jVyype9bKKV9+sgqA3UrQRlOSjDwJZtXI5rdu0ZWzgeKysrBg6qD+/Hz9mdl6Vsoo3la+WfcHe3buoU7ce4wLH81anzhw/doyuHTvw999/mVVW8aqX9Xm8j78WO3TszO/Hj/F257f455HXYtitW7zTuwfXrl5l6Ih38e/dh19+OsCg/n1JTEzIMENc3H3mzplB3rz5cmUccntsxWseTvGql1W86mUVr75ZBUF3NEEwQx4kZr79djxEc3Fx0RYt+cLYFhkbr3l7+2idOnd54rE57VUpq3j/3Q7/dlyLvm8waTv/zyWtatWq2rsjR5lVVvGqlfV5vY+/FmMNKdrZvy5qVatW1Ua8N0qLNaRosYYUbfxHH2seHh7a35evG9v27v9Fc3Fx0VasWmNse3T7bNoMzde3pTbivVGap6eXPGfifWmyquZVKat41csq3hd3vky8seSo2W5C5shMG0E59uzaiZWVFW916mJss7W1pf1bHQk5eYJbN2+ajVelrOL9F69q1bG2sTFpK126DOUrVOTSxYtmlVW8amV9Xm9Gr8XXSpehXPkKXLp4wdi2d/cuGjVuSokSrxjb6tSrT+kyZdj9w850Ga5euczqr5czckwgeayssi3vs2IOYyve3HeKV72s4lUvq3j1zSoIOYEUbRQmMDCQNm3acOTIEd588028vLzo2LEjZ86cMe7j6urKkiVLmDNnDvXq1aNmzZpMnz4dTdM4fPgw7dq1o1q1avTq1Yubj/2ymjlzJm3btqVatWo0atSIkSNHcvv2bZN9/P39GTBgAJs2bcLHxwcPDw/8/f25mMV/2D4L58+fo3TpMhQoUMCkvaq7h7HfXLwqZRXvk9E0jYiIOzg4FM7S8aqNgUpelbJmh1fTNO5GROBQOPW1eDssjLt3I6hUpWq6fatU9eDP82fTtc/831Rq1q5Dw8ZNdM+bU07x6utVKatqXpWyile9rOLVN6sg5ARyy2/FCQ8PZ8qUKfTv3x97e3tmzZrF0KFD2b17N9bW1gCsXr2a2rVrM336dEJCQpg/fz4pKSkcPHiQQYMGYW1tzZQpUxg/fjxffvml0R0REcGAAQNwdnbm7t27fPXVV/j7+7Nt2zby5Pn3pfPHH39w9epVRo0aBUBQUBDvvPMOO3fuxOaxb4iz62cu6uSUrr1oUaeH/bfT9eWWV6Ws4n0y27Z+z+2wMAYPHZ6l41UbA5W8KmXNDu/2rVu4fTuMgQ9fi3fupO6fodPJiaioKBISEoy/j3/+aT+/Hj7IN99typG8OeUUr75elbKq5lUpq3j1c4pXX29O/s1ozljILb+VRIo2ihMVFcWqVauoWLEiAHnz5qVnz56EhIRQs2ZNAJydnZkxYwYAjRo1Yt++fSxfvpxt27ZRvnx5AMLCwpg8eTLR0dEULFgQgKlTpxrPk5ycTLVq1WjcuDG//vorDRs2NPZFRESwatUqypQpA0DlypXx8/Njw4YNdO3aNdt/ZoMhPsNikK2tbWp/fLzZeFXKKt7MuXTxAlOnTMLTqxpvtGufJYdqY6CSV6WsL+q9dPEi//tsEh6eXrR9400A4uMNANhYZ+C0+ddpY2NDYmICs6ZP5a1OXShXvoLueXPSKV59vSplVc2rUlbx6ucUr77enPqbURD0QC6PUhxnZ2djwQagQoXUP8LDwsKMbfXr1zc5pmzZsjg7OxsLNoCx4HLr1i1j24EDB+jatSs1atSgcuXKNG7cGIDLly+b+CpWrGg8HqB06dK4ubkREhLyQj9bZtja2pGQkP5uKAZD6j9cbO3szMarUlbxZsyd8HCGDh5AgQL2zJwzF6unrP+RGaqNgUpelbK+iPdOeDgjhqS+FmfM/ve1aGeX+gdnQgZ3iTIkmDpXr1xB5L1IBg4ZpnvenHaKV1+vSllV86qUVbz6OcWrrzcn/mYUBL2QmTaKkzYrJo20S6LSfgFlts/Tjjt16hSDBw/G29ubfv36UaRIESwsLOjcubOJG6BIkSLpchUpUoTw8PAs/lRPxsnJiduPFKXSuHMn/GG/s9l4Vcoq3vTExMQweGA/YqJj+Grlapydi2XZpdoYqORVKWtWvcbXYkw0y1asxumR12LRoqn738ngd+6d8HAKFSqEjY0NMTExfLHkczp1eZv7sbHcj40FIO5BHBoaoaHXsbPLm+53ujxn4tXLKV79nOLV16tSVvHq51QRS7k+Sklkpo2QIXv27KFAgQIEBQXh7e2Nl5cXRYsWzXDfiIiIDNucMrhuNDtwdXPjypXLxD78B0cap0+lzuxxc6tkNl6VsorXFIPBwPAhA7ly5TLzFy6ifIVnu5Qkp7OKV62sWfE++loMCl6U7rIm52LFKOzoyLk/zvA4f5w5hctDX0x0FHFxcaz46gva+PkYt727dxH/4AGtfb2Z/MlHL5z3WTCXsRXvy5lVNa9KWcWrXlbx6ptVEHICKdoIGRIfH4+1tTUWj1Rjt2zZkuG+f//9N1euXDE+vnLlCufPn8fT01OXbD6+fiQnJ7P+27XGtoSEBDZv3IC7hyfFS5QwG69KWcX7L8nJyYwd9S6nQk4yc/ZcPL2qZcmTE1nFq1bW5/U+62vR28eXn3/az61b/94F8Mivh7ly+TItfP0AKOxYhFlBwem2mrXrYGtry5x5C+jbb0COjIM5jK14c98pXvWyile9rOLVN6sg5ARyeZSQIQ0aNGDFihVMnjyZFi1acOLECTZv3pzhvkWKFGHgwIEMH556J5O5c+dSrFgxOnTooEs2Dw9PfFv6MS9oNncjInj1tdJs2byRGzdC+WTyp2blVSmreP9l1vRp7P9xH02aNiMqKpKtW0xf+23atjObrOJVK+vzeh9/LW7b8r1J/+tt3wCgb78B7Nm1k/59e/F2d3/iHsSx8qsvqVDRhTfeTP1dnDdvXpp5+6TLs3/fHv44fZrmGfTpNQ7mMLbizX2neNXLKl71sopX36yqIVdHqYmFpmlabocQskZgYCBnzpxh69atxrbo6Ghq1arF1KlT6dChA66urowdO5aAgIAnHnfkyBF69uzJd999h7u7OwBLly5l1apVREVFUb16dSZMmEDLli1NfP7+/uTLlw9fX18WLFhAeHg4np6eTJw40WSh4+clPunJ/QaDgQXzg9i2ZQvR0VFUdHFlyLARNGjYKMvn1MurUlbxphLQ259jR3/LtD/kjz+z5FVpDFTzqpT1ebxPey3+fvq88b8v/PM3s2ZM4+SJ37HOY03Dxk0YOXocRTK5tDWNj8cHsmf3Ln49duKF8z4PuT224jUPp3jVyype9bKK98Wcdi/RNIe3vjye2xEyZX3fGrkdwWyRoo3wQqQVbRYvXpyt3qcVbQRBEP6LJKfo85FtZSlfvQmCIAhCRkjRJmeQok3mvEQvQUEQBEEQBEEQBEEQMsJCro9SElmIWBAEQRAEQRAEQRAEwQyRmTbCC/H111/ndgRBEARBEARBEARBeCmRoo0gCIIgCIIgCIIgvOTI1VFqIpdHCYIgCIIgCIIgCIIgmCEy00YQBEEQFEGvuzwVrjVUF++9o8G6eAVBT/S6r6p8wy0IgiBkBSnaCIIgCIIgCIIgCMJLjqVUj5VELo8SBEEQBEEQBEEQBEEwQ6RoI2Q7R44cwdXVldOnT+t2joSEBObMmoFP04bUru5B966dOHzooFl6VcoqXvWyile9rHp7jx05RMjxIxjuR2GXBy5d+DvdfhZAHkuwsQJbK3hwIvPLmPp1asjq6X35a/skHpwIZsnEHk/M0KyOKzsWD+PWTzOwtUo9x+NXddlagWVKAvPn/DsG/t068dth8x3bx1m6+HM8q7jSoV2bZ9o/7v59FgbPY1D/ABrVq41nFVc2b9xgsk9KSgqbN25g+JCB+Ho3oU5NLzq0a8OSRQsxGAzPlU/eZy/uPfrbEbyquma4nQo5abLvyRO/09u/G3VreuLdpAH/+2wKcXH3cyxrZjzL6y4rmOtzppf3Wcdx/bfr6NurB80a16emV1Va+Tbno/HvExp6PceyijfnswqC3kjRRlCSjz4IZNXK5bRu05axgeOxsrJi6KD+/H78mNl5VcoqXvWyile9rHp658z8Hw0b1MfNzY0H8fEArFq5PJ3XyhKsHhZSnrZ8x6jeLWhSy5WzF2+SmJj8xH3936jL1oVDSExK4ePgLSSlQIqWWiR6nHHjAlm+fDmvt2nLuPfHY2FpxaCB5ju2jxJ26xZfLF1M3rz5nvmYe5H3WPz5Ai5dvIiLq2uG+8Q/eMCED9/n3r17dOrclbHjPqCquzufL5jP4AHvoD3HYivyPss+b7fu/nw6dbrJ9uprrxn7z58/x4B3ehMfH8+oMYG0f6sj679by5iRI3I86+M8y+suK5j7c5bd3mcdx/PnzlKyZCl6932H8RM+4fU2b3Dw55/o3qUjt2+H5UhW8eZ8VpWwMONNeAKa8J8hJSVFMxgMup/n119/1VxcXLRTp05l2fEgMfPtt+MhmouLi7ZoyRfGtsjYeM3b20fr1LnLE4/Naa9KWcWrXlbxqpdVb2+VKlW0FV+v1h4kalp8Yurv0//9b/oTvYnJqfvZeQ3JcHNp9aHxv2Pux2srNx/OZL+PtPtxBi149T5jW2bnPHlSrbF9fBs24l2th39P7e3uPbRWrV9/pmOi7hu0azduaw8SNe3YiVOai4uL9s269Sb7RN83aId/O57u2Dlz52suLi7ajz8dzLVxUPH9kFVvXELqduCX1L9nNm/dYWzLaOsT8I7WoEED7fbdGGPbqv9bp7m4uGh7fvzZ2JYbr9tned29DM+Z3t4XGcfjJ09rLi4uWvDCxUqPgereF3G+THRZ/rvZbkLmyEwbMyQwMJA2bdpw5MgR3nzzTby8vOjYsSNnzpwx7mMwGJg6dSoNGzbE3d2ddu3asXv37gw9Bw4c4I033sDd3Z19+/Yxf/58qlWrxtmzZ+nSpQseHh60b9+es2fPYjAY+Pjjj6lVqxaNGzdm+fLlJs4TJ04wcOBAGjZsiJeXF+3atWPTpk05MCr/smfXTqysrHirUxdjm62tLe3f6kjIyRPcunnTbLwqZRWvelnFq15Wvb0pKSm0bvOGSXuNmjVfyHv15r1n2q9fp4ZYWVkw6fNtAOTPa5Ppvj/8oNbYPsrxY0fZs+sHxgZ+8FzH2djYUNTJ6Yn7WNvY4FWterp2b58WAFy8eOGZziXvs+z33r8fS1JSUrr22NhYjhw+ROs2b1CgQAFje9t27ciXLx+7f9iR41kf5Vled8+LKs9ZdnpfZBxfKVkSgJiY6BzJKt6czSoIOYEUbcyU8PBwpkyZQkBAAEFBQRgMBoYOHUpiYiIAo0ePZu3atbzzzjssWLCAChUqMGzYMPbu3WviuX37NlOmTKF3794sXbqUSpUqAZCYmMi4cePo3Lkz8+fPJykpiaFDhzJ+/Hjs7OwICgrCx8eHqVOn8vvvvxt9N27coHr16nz66ad8/vnn+Pr68uGHH7Jx48YcG5vz589RunQZkz+OAKq6exj7zcWrUlbxqpdVvOplzQ1vyVKvvpD3WWlWx40/L4fh17AK/+yczJ1Ds7G1Sl0753HOnTtHmTJlKFKoAHZ5Ute4sbIw37FNIzk5mWmfTqb9Wx2p6JJ9l5o8jTt37gBQ2KHwM+0v77Ps9X784fs0qFODOjU8eKePP3+c+XfNvr//+pOkpCQqV6lqcoy1tQ2ubpWe6Tx6v26zGxWes5zwPonIyHtERETwx5nTTBj/PgB16tbLtaziVe99phcWFhZmuwmZI7f8NlOioqJYtWoVFStWBCBv3rz07NmTkJAQChQowK5du5g4cSJdu3YFoHHjxoSGhrJgwQK8vb1NPEuXLsXT09PEn5iYyOjRo2nSpAmQuvjhwIED8fT05P33Uz9c6taty86dO9m5cyfVq6d+8/f6668bHZqmUatWLcLCwli7di3t27fXb0AeITw8PMNvO4oWdXrYf9tsvCplFa9+TvHq61Upa2547e3tX8j7rFR41YnklBQWf9KD2Sv2cPqvUFZNf8dYtElK+Xff27fDKVrUicSU1OvYrSzB2gqKOZvn2Kbx7dpvuHnzBouXLX8hz/Oy/MsvKFCgAA0aNX6m/eV9lj1ea2trfFq0pGGjxjgULszFCxdYuXwZfXt1Z8Wqb3CrVJk7d8IBcHJyTn8uJydOHD+eI1lzEnN+znLS+yRaNGtMQkICAA4ODoz74EPq1W/w1ONUGwOVvKq9zwThUaRoY6Y4OzsbCzYAFSpUACAsLIw///wTAD8/P5NjWrVqxdSpU4mLiyNfvtTFER0cHNIVbAAsLS2pV+/fin+ZMmUAqF+/vrHNysqK1157jVu3bhnboqKimD9/Pnv37iUsLIzk5GTjeXIKgyEeG5v00+5tbW1T+x8uvmkOXpWyilc/p3j19aqUNTe8efLkeSHvs1Igny1WVpZ8OHcTs5bvASDxYaHGygIevbAk3hCPtY0NKQ/X1U1OBmtLyGdnnmMLqd+cLwyeR7+Bg3F0dMyy53n5Yskifj18iPEffUzBggWf6Rh5n2WP16tadZPL1Zo288bHtyWdO7zBvKBZLFy8zOixzuhcNrbEG55+Hj1ft3pgzs9ZTnqfxIJFS0lIMHDxwkW2bf2eB3EPnuk41cZAJa9q7zNBeBQp2pgpj/9hZm1tDaSuZRMVFYW1tXW6QknRokXRNI2YmBhj0aZo0aIZ+u3s7Ex+caX5076RfbT90duMBgYGcuLECYYMGUKFChUoUKAAa9asYceOp1+znV3Y2toZv714lLSctnZ2ZuNVKat49XOKV1+vSllzw5u2DkdWvc/KA0MiBfLZsm6n6cyCZC11Jo0F/96pKqOsyRokJJjn2AIEzwuiUKFCvP32k295np3s3LGd4HlBtH+rI527vv3Mx8n7TD/va6+Vpmkzb/bu2UVycrLRk5jRuRIM2Nk+/Tx6vm71QLXnLDfGt3adugA0bNSEZs29eevNNuTLl49u3Z/8+0O1MVDJq9r7TC8s5SokJZE1bRSkUKFCJCYmEhUVZdJ+584dLCwsTAov2Xl9oMFgYP/+/QwaNAh/f3/q1auHu7v7c92CNDtwcnLiTnh4uvYnTVHOLa9KWcWrn1O8+npVypob3piYmBfyPis3w1M/k8IiYjLsf/TjKKOsmpY6fT2137zG9sqVy6z/dh3devhzO/w2oaHXCQ29jsFgICkpkdDQ60RFRmbJnRmHDx3kw/fH0qhxUz6cMPG5jpX3mX5egGLFi5OYmMiDBw+eeGnFnfBwnJyffh49s+qBas9Zbo/vq6+9hlulymzftuWp+6o2Bip5c/t1IAgvghRtFKRGjRoA7Ny506R9586dVK5c2TjLJrtJSEggJSXFOCsHUu+asG/fPl3Olxmubm5cuXKZ2NhYk/bTp0IAcHOrZDZelbKKV72s4lUva254r1+79kLeZ+XEuasAvOJcyKQ9rVbzaH0/o6wWFhASYp5jezssjJSUFP732RRa+3obt9OnQrhy+TKtfb1Z/PmCLLkz4tSpEN4bPpQqVaoyY3aQ8RK3Z0XeZ/p5AUKvX8fW1pZ8+fJRoaILefLk4ewfZ0z2SUxM4M/z53B1dcvVrHqg2nNmDuMbHx9PbEzGBe1HUW0MVPKaw+tAELKKFG0UxM3NDV9fX6ZNm8aKFSv46aefGD16NCdOnGDo0KG6ndfe3h53d3eWLl3Kzp072bNnD3379k23Crve+Pj6kZyczPpv1xrbEhIS2LxxA+4enhQvUcJsvCplFa96WcWrXtac9gKc+P3YC3mfle9+SL3TYO8365u0W1mmFmwenZOZUdaUpAQ2bDDPsa1QsSJz5i1It5WvUJESJV5hzrwFtH+rY5bcj3PxwgWGDerPKyVLMn/hYuyyMGVf3mfZ47179266tj/Pn2f/j/uoV78BlpaW2NvbU6duPbZv/Z779//9x+DW7zcTFxdHi5Z+6Rx6ZM1JzPk5y0nv4yQlJRH92Cx4gNOnTvHP339RuWrVDI7KmaziVe99phe5fYcouXtU1nimr26OHj2aJXmtWrWydJzwdGbMmMHs2bNZunQpkZGRlCtXjnnz5tG8eXNdzztr1iwmTJhAYGAgDg4O+Pv7ExcXx5dffqnreR/Fw8MT35Z+zAuazd2ICF59rTRbNm/kxo1QPpn8qVl5VcoqXvWyile9rDnhvXP7FkcO/Uzx4iVwdamAl5cXnbt2w8oidd2YNKwe/n2Udn37uHdaAnD15l3WbPv3c79146q4u5QEwDqPJVUrljTuu+3Aac78fQOALftPse/Iecb0bUERh/yc/isUa8tUf2Ky6XlrVvOkpV/qGNy7G0GZ0qXZtGkjoaGhfDzJ/Ma2cGFHmnv7pGtf/fUKgAz7MmLN6lXExEQTfjv1UpoD+38kLCx1sf9u3f2xtLRgUP8AoqOj6dUngJ9+2m9y/KuvvoanV7WnnkfeZ9njHTf6XWxt7fD0qoZjkSJcvPAP679bh11eO4a/O9q439Dh79GrR1cCevvzVsfOhIXd4usVX1GvfkMaNHz6Hb/0GoM0nva6e3w9w9zKa+7ep42jpmn4ejelZatWlC9fkbz58vL3X3+xedMGChSwp//AwTmWVbw5l1UQcgIL7RkWJHFzc3uu6pemaVhYWHDu3H/jfvdC9hOf9OR+g8HAgvlBbNuyhejoKCq6uDJk2AgaNGz0QufVw6tSVvGql1W86mXV26slxeNQqFDG/UmpM14sLcDGKmPHT8f+pmW/ucbHSyb2wP+Nuhnu22/C16zacsT4OH9eGz4Z0pa3fKvjWCgf1tbWJKVgvEsUpF4ulccSEhMMzJ0bxJYtW4iKisLF1ZXBQ813bDMioLc/9+7dY8Pmrc+0f6sWzblxIzTDvu279gLQ2tc70+PfaNeeyZ9Ne6Zzyfss6960v4z/b9VKtm/bwrWrV7l/P5bChQtTu049BgweymuvlTY55sTvxwiaPZPz586SL39+fFu2Yvi7I8mf/9/ZyE/6U1rP1+3TXnclS5Z6bqe5PWc54X3aODo7OTNn1gyO/naEGzdCiY834OzsTJ169eg3YNAzj7M5j4Hq3qw67V6iW/f0WBWS2xEyZVWP9Hc8FlJ5pqLNb7/9liV57dq1s3ScIDytaCMIgiBkH4Vr6XNp7b2jwbp4BUFP9Lq/gsz+FwQ1eZmKNv6rzbdo83V3KdpkxjO9BKX4IgiCIAiCIAiCIAiCkLO88ELEt2/f5vz588TFxWVHHkEQBEEQBEEQBEEQhGdm48aNvPnmm7i7u1OnTh3eeecd4uPjjf379u3jjTfewN3dnZYtW7J+/fp0joSEBP73v//RoEEDvLy86NOnDxcvXky334ULF+jTpw9eXl40aNCA6dOnk5CQoNvPluWizZ49e/Dz86NJkya0b9/eeJvOu3fv8uabb7Jnz55sCykIgiAIgiAIgiAIQtbJ7TtE6XX3qM8//5zJkyfTunVrli1bxqRJkyhVqhTJyal3Qjh27BhDhw7Fy8uLpUuX0qpVK8aPH8/OnTtNPFOmTOHbb7/lvffeY/78+SQkJNC7d29iYmKM+0RFRdGrVy8SExOZP38+7733HuvWrWPatGdbcy4rZOkKvX379jFs2DC8vLxo06YNwcH/XrPu6OhIsWLFWL9+PT4+z3Y3BUEQBEEQBEEQBEEQhOfh4sWLBAcHs3DhQpo0aWJsb9mypfG/P//8czw8PJg0aRIAdevW5dq1a8ybNw8/Pz8Abt26xXfffcfHH39Mx44dAXB3d6dZs2Z888039OvXD4BvvvmG+/fvExwcjIODAwDJyclMnDiRAQMGUKxYsWz/GbNUtFmwYAE1a9bk66+/5t69eyZFGwAvLy/Wrl2bLQEFQRAEQdAXWTBYEP5FFgwWBEFQhw0bNlCqVCmTgs2jJCQkcOTIEUaPHm3S3rp1a7Zu3cr169cpVaoUv/zyCykpKcYiDoCDgwMNGjTgp59+MhZtfvrpJ+rVq2cs2AC0atWKjz/+mIMHD9KhQ4ds/xmzdHnU33//TatWrTLtL1q0KBEREVkOJQiCIAiCIAiCIAhC9mFpYb5bVgkJCcHFxYWFCxdSr149qlatSteuXY3Lt1y9epXExETKlStnclz58uUBjGvWXLx4kSJFilCoUKF0+z26rs3FixfTuQoWLIiTk1OG699kB1maaZM3b14ePHiQaf+1a9dMKk+CIAiCIAiCIAiCIAgZ4e3t/cT+vXv3ZtgeHh7OmTNn+Ouvv/j444/JmzcvixYtom/fvuzatYuoqCggtbDyKGmP0/qjo6Oxt7dP5y9YsKBxn7T9HncBFCpUyGS/7CRLM23q1KnDpk2bSEpKStcXHh7OunXraNiw4QuHE9TE1dWVZcuW6XqOhIQE5syagU/ThtSu7kH3rp04fOigWXpVyipe9bKKV72s4k0l7v59FgbPY1D/ABrVq41nFVc2b9xgllnFq15W1bwqZRWvelnFq29WIXfRNI24uDjmzp1rvFHS559/jqZprFq1KrfjZQtZKtq8++673Lp1i44dO7J27VosLCz45ZdfmDNnDm3btkXTNIYMGZLdWQXByEcfBLJq5XJat2nL2MDxWFlZMXRQf34/fszsvCplFa96WcWrXlbxpnIv8h6LP1/ApYsXcXF1faF8emcVr3pZVfOqlFW86mUVr75ZVSK37xD1pG3v3r1P3DKjYMGCODg44ObmZmxzcHCgcuXK/PPPP8bLnR69AxSkzpgBjP0FCxYkNjY2nT86OtrkkqmCBQumc0HqjJ3HL63KNrQs8tdff2m9evXS3NzcNFdXV+Pm7++v/fPPP1nVCgrz4MEDTdM0zcXFRfviiy9ezJWY+fbb8RDNxcVFW7TkC2NbZGy85u3to3Xq3OWJx+a0V6Ws4lUvq3jVyyref7eo+wbt2o3b2oNETTt24pTm4uKifbNufZZ9Ko6BSl6VsqrmVSmreNXLKt4Xd75M9F5zymy3rBIYGKjVrl07XXv37t21fv36aQaDQatSpYq2fPlyk/69e/dqLi4u2rVr1zRN07Rvv/1Wc3V11SIjI032Gzp0qNajRw/j47ffflsbPHiwyT7R0dGaq6urtn79+iz/HE8iSzNtACpWrMjy5cv59ddfWbduHWvXruXQoUOsXLnSuKiPYH4EBgbSpk0bDhw4QJs2bXB3d6dDhw6cPHnSZL8NGzbQtm1b3N3dadSoEXPmzDHe5z6t39XVlRMnTtCnTx+8vLyYPn16jvwMe3btxMrKirc6dTG22dra0v6tjoScPMGtmzfNxqtSVvGql1W86mUV77/Y2NhQ1MkpS8dmhmpjoJJXpayqeVXKKl71sopX36xC7tOsWTMiIyM5d+6cse3evXv88ccfVKlSBRsbG+rUqcMPP/xgctz27dspX748pUqVAqBhw4ZYWlqya9cu4z5RUVH88ssvNG7c2NjWuHFjDh06ZJypA7Bz504sLS1p0KCBLj9jlos2aRQqVAgPDw88PT1xdHTMjkyCzoSHhzNx4kQCAgIICgrCxsaGgIAA4x2/vvrqKz788EMaNmzIokWL6NevHytXrmTOnDnpXKNGjaJu3bosWrSIdu3a5Uj+8+fPUbp0GQoUKGDSXtXdw9hvLl6VsopXvaziVS+rePVFtTFQyatSVtW8KmUVr3pZxatvViH38fHxwd3dneHDh7N9+3b27t3LwIEDsbGx4e233wZg0KBBnDx5kk8++YQjR44wb948tm7dyrBhw4ye4sWL07FjR6ZPn8769ev55ZdfGDp0KPb29nTt2tW4X9euXcmfPz9Dhgzhl19+Yf369UyfPp2uXbtSrFgxXX7GLN09CuDu3bssXbqUAwcOEBoaCkDJkiVp0qQJAQEBFC1aNNtCCtlLZGQkQUFB1KtXD4DatWvTpEkTli9fzoABA5g3bx7vvPMOI0eOBKBBgwZYW1szbdo0AgICKFy4sNHVtWtX+vfvn6P5w8PDM/x2tmhRp4f9t83Gq1JW8ernFK++XpWyildfVBsDlbwqZVXNq1JW8ernFK++XpU+y/TkBe6sbbZYWlqyZMkSpk6dyoQJE0hMTKRmzZqsXr0ap4fPec2aNZk/fz5BQUF89913vPLKK0yZMoVWrVqZuD788EPy58/PrFmzuH//PtWrV+err74yuatUoUKFWLFiBZMnT2bIkCHkz5+fjh078t577+n2M2apaPP333/Tu3dvIiIi8PT0xM/PD4DLly/z1VdfsXnzZpYvX46Li0u2hhWyB3t7e2PBJu1x/fr1CQkJ4cSJE8TFxeHn52dyd7D69esTHx/P33//Te3atY3tTZs2zcnoABgM8djY2KRrt7W1Te2Pjzcbr0pZxaufU7z6elXKKl59UW0MVPKqlFU1r0pZxaufU7z6elX6LBOeH0dHR2bMmPHEfby9vZ96W3EbGxvGjRvHuHHjnrhf+fLlWb58+fPGzDJZKtpMmjSJ5ORk1q1bh4eHh0nfqVOn6NevH5MnT+brr7/OlpBC9pLRZWxFihThwoUL3Lt3D4D27dtneOzNx673zI0ZVba2diQkJKRrNxgMqf12dmbjVSmrePVzildfr0pZxasvqo2BSl6VsqrmVSmrePVzildfr0qfZYLwOFkq2pw6dYoBAwakK9gAeHh40LNnT5YsWfLC4QR9uHv3brq2iIgInJycjLcpCw4Opnjx4un2S1uoKTdxcnLidlhYuvY7d8If9jubjVelrOLVzylefb0qZRWvvqg2Bip5VcqqmlelrOLVzylefb0qfZbpiaXFy3iB1MtPlhYiLlKkiHEqWUbY2tpSpEiRLIcS9CUmJobDhw+bPD506BCenp5Uq1aNvHnzcuvWLdzd3dNtj65nk1u4urlx5cplYmNjTdpPnwoBwM2tktl4VcoqXvWyile9rOLVF9XGQCWvSllV86qUVbzqZRWvvlkFISfIUtGmZ8+erFmzhvDw8HR9YWFhrFmzhp49e75wOEEfHBwcGD9+PJs2bWLv3r3069cPTdPo1asXBQsWZPjw4cyYMYMZM2Zw4MABfvnlF9asWcM777zDgwcPcjs+Pr5+JCcns/7btca2hIQENm/cgLuHJ8VLlDAbr0pZxateVvGql1W8+qLaGKjkVSmral6VsopXvazi1TerIOQEz3R51FdffZWuLV++fPj6+uLj40Pp0qWB1IWI9+7dy2uvvZa9KYVsxcnJidGjRzN9+nSuXr1KxYoVWbZsmXF9mr59+1KsWDG++uorVq1aRZ48eXjttddo2rQp1tbWuZwePDw88W3px7yg2dyNiODV10qzZfNGbtwI5ZPJn5qVV6Ws4lUvq3jVyypeU9asXkVMTDTht1Pv2nFg/4+Ehd0CoFt3f5O7NeRmVvGqlVU1r0pZxateVvHqm1U15OooNbHQNE172k5ubm7PL7aw4Nw5ud+9uREYGMiZM2fYunVrbkd5IvFJT+43GAwsmB/Eti1biI6OoqKLK0OGjaBBw0YvdF49vCplFa96WcWrXlbx/kurFs25cSM0w77tu/ZSsuTzr6Om2hio5FUpq2pelbKKV72s4n0xp12WVoE1T/qtO5PbETJlaeequR3BbHmmok1oaMZ/UD2NkiVLZuk4QT9elqKNIAiCIAiCIAiC3kjRJmeQok3mPNNLUIovgiAIgiAIgiAIgqAuFnJ9lJK8RHVD4VmYNm1abkcQBEEQBEEQBEEQBOEZyHLR5vz586xatYqzZ88SExNDSkqKSb+FhQV79ux54YCCIAiCIAiCIAiCIAj/RbJ0y+8jR47QqVMn9u/fj7OzM9euXePVV1/F2dmZGzdukC9fPmrVqpXdWQVBEARBEARBEARByAIWFua7CZmTpaLNvHnzePXVV9m5cyefffYZAAMGDGDNmjV88803hIWF4efnl61BBUEQBEEQBEEQBEEQ/ktkqWhz9uxZOnbsSIECBbCysgIwXh7l6elJly5dmDt3bvalFARBEARBEARBEARB+I+RpTVtrKysyJ8/PwAFCxYkT548REREGPtfffVVLly4kD0JBUEQBEEQBEEQBEF4ISzlOiQlydJMm9dee43Lly8DqQsOlytXzmTR4f3791O0aNFsCSgIGZGQkMCcWTPwadqQ2tU96N61E4cPHTRLr0pZxateVvGql1W8+maNu3+fhcHzGNQ/gEb1auNZxZXNGze8sFelsdXLq1JW1bwqZRWvelnFq29WQdCbLBVtmjRpwrZt20hKSgKgT94hQ7AAAQAASURBVJ8+7Nq1C19fX3x9fdm3bx9dunTJ1qBC7tO8eXMmTZr01P3++OMPOnfujKenJ66urkRHR2d7lo8+CGTVyuW0btOWsYHjsbKyYuig/vx+/JjZeVXKKl71sopXvazi1Tfrvch7LP58AZcuXsTF1fWFXI+i0tjq5VUpq2pelbKKV72s4tU3qyDojpYFEhIStLt372opKSnGtk2bNmmDBw/Whg0bpq1fvz4rWsHMadasmTZx4sSn7te1a1etQ4cO2uHDh7UTJ05oSUlJz32uB4mZb78dD9FcXFy0RUu+MLZFxsZr3t4+WqfOXZ54bE57VcoqXvWyile9rOLVN+uDRE2Lum/Qrt24rT1I1LRjJ05pLi4u2jfr1r+QU6WxVe05E69aWcWrXlbxvrjzZWLQ+j/MdhMyJ0szbaytrSlcuDAWj1wT165dOxYsWMC8efPo0KFDthWVBPW4ePEijRs3pm7dunh5eRkXq84u9uzaiZWVFW91+nc2l62tLe3f6kjIyRPcunnTbLwqZRWvelnFq15W8eqbFcDGxoaiTk5ZPj4jVBpbvbwqZVXNq1JW8aqXVbz6ZhWEnCBLRRvh5SMwMJA2bdpw4MAB2rRpg7u7Ox06dODkyZPp9l29ejXNmjWjRo0aDB48mLt37wJw5MgRXF1diYyMZOHChbi6uuLv75/tWc+fP0fp0mUoUKCASXtVdw9jv7l4VcoqXvWyile9rOLVN6teqDS2enlVyqqaV6Ws4lUvq3j1zSoIOcEz3T2qZ8+ezy22sLBgxYoVz32ckHuEh4czceJEhg0bRsGCBVm6dCkBAQHs2rWLIkWKALBv3z6uXLnChAkTuHfvHlOnTmXy5MnMmTOHKlWqsHbtWvr06UPr1q3p1KlTul+M2ZUzo29RixZ1eth/22y8KmUVr35O8errVSmrePVz6olKY6uXV6WsqnlVyipe/Zzi1der2ueOXljI3aOU5JmKNpqmPbc4K8cIuUtkZCRBQUHUq1cPgNq1a9OkSROWL1/OqFGjgNTn9fPPP8fGxgaA0NBQFi9eTEpKCgUKFDBeDlW8eHG8vLx0yWkwxBvP/yi2trap/fHxZuNVKat49XOKV1+vSlnFq59TT1QaW728KmVVzatSVvHq5xSvvl7VPncE4VGeqWjz9ddf651DMAPs7e2NBZu0x/Xr1yckJMTYVqtWLZNfeOXLlycxMZGIiAicsnkNgcywtbUjISEhXbvBYEjtt7MzG69KWcWrn1O8+npVyipe/Zx6otLY6uVVKatqXpWyilc/p3j19ar2uSMIjyJr2ghGHB0d07UVKVKE8PBw4+OCBQua9KcVcNJ+4eUETk5O3HkkUxp37oQ/7Hc2G69KWcWrn1O8+npVyipe/Zx6otLY6uVVKatqXpWyilc/p3j19ar2uaMXlma8CZkj4yMYSVtQ+FFycgbNs+Lq5saVK5eJjY01aT99KnVGkJtbJbPxqpRVvOplFa96WcWrb1a9UGls9fKqlFU1r0pZxateVvHqm1UQcgIp2ghGYmJiOHz4sMnjQ4cO4enpmYup0uPj60dycjLrv11rbEtISGDzxg24e3hSvEQJs/GqlFW86mUVr3pZxatvVr1QaWz18qqUVTWvSlnFq15W8eqbVRBygmda00b4b+Dg4MD48eMZPnw49vb2LF26FE3T6NWrV25HM8HDwxPfln7MC5rN3YgIXn2tNFs2b+TGjVA+mfypWXlVyipe9bKKV72s4tU3axprVq8iJiaa8NupdwM5sP9HwsJuAdCtuz/29vZmkVclr0pZVfOqlFW86mUVr75ZVUPuHqUmFprc5kkAAgMDOXPmDKNHj2b69OlcvXqVihUr8tFHH1G9enUAmjdvTtOmTZkwYYLxuD179jBkyBD27t1LqVKlAKhZsya9evVi2LBhWc4Tn/TkfoPBwIL5QWzbsoXo6CgqurgyZNgIGjRslOVz6uVVKat41csqXvWyilffrACtWjTnxo3QDPu279pLyZKlntup0tjq5VUpq2pelbKKV72s4n0xp91LNM1h+KbzuR0hU+a96ZbbEcwWKdoIwL9Fm61bt+Z2FODpRRtBEARBEARBEAS9kaJNziBFm8x5oZdgWFgYR48eJSIigpYtW1K8eHGSk5OJiYnB3t4eKyur7MopCIIgCIIgCIIgCEIWsZSro5QkS0UbTdOYNm0aq1evJikpCQsLC1xcXChevDhxcXE0b96c4cOH07t372yOKwiCIAiCIAiCIAiC8N8gS3eP+uKLL1i5ciV9+/blq6++4tErrOzt7fH19WXXrl3ZFlLQn2nTppnNpVGCIAiCIAiCIAiCIGRxps23337Lm2++yciRI7l37166fldXV3766acXDicIgiAIgiAIgiAIwosjl0epSZZm2ty8eZNq1apl2p83b15iY2OzHEoQBEEQBEEQBEEQBOG/TpaKNkWKFOHmzZuZ9v/xxx+UKFEiy6EEQRAEQRAEQRAEQRD+62SpaNOiRQu++eYbrl27ZmyzsEida/XLL7+wceNG/Pz8siehIAiCIAiCIAiCIAgvhIWFhdluQuZkqWgzfPhwnJycaNeuHePGjcPCwoKlS5fSrVs3+vXrh4uLCwMHDszurIJgJCEhgTmzZuDTtCG1q3vQvWsnDh86aJZelbKKV72s4lUvq2reuPv3WRg8j0H9A2hUrzaeVVzZvHGDWWbNDu8///zN6PeG07qlN3VqeNKkQR369OzO/h/3ZXpMYmIi7du2xrOKKyu+WpajeXPSq1JW1bwqZRWvelnFq29WQdCbLBVt7O3tWbduHe+88w5hYWHY2tpy9OhRYmJiGDJkCP/3f/9H3rx5szuroAg1a9Zk/vz5up7jow8CWbVyOa3btGVs4HisrKwYOqg/vx8/ZnZelbKKV72s4lUvq2ree5H3WPz5Ai5dvIiLq+sL5dM7a3Z4b964wf3793mjXXvGBo6n/8DBAIwYOojv1q3N8Jg1q1c98bJxPfPmpFelrKp5VcoqXvWyilffrIKgO5ogZDM1atTQ5s2b90KOB4mZb78dD9FcXFy0RUu+MLZFxsZr3t4+WqfOXZ54bE57VcoqXvWyile9rCp6o+4btGs3bmsPEjXt2IlTmouLi/bNuvVZ9qk4BrHxSVrbtm9ovi1bpuu7fuuOVqNGDS1oXnC6c79M46BSVtW8KmUVr3pZxfvizpeJ0VvOm+0mZE6WZtoIQm6yZ9dOrKyseKtTF2Obra0t7d/qSMjJE9zK4redenhVyipe9bKKV72sKnptbGwo6uSUpWMzQ7UxsLKyoljxEsREx6TrmztnJqXLlOX1tm+YTV55n6nlVSmreNXLKl59swpCTpClos3777//1O2DDz7I7qxCNhEYGEibNm04cOAAbdq0wd3dnQ4dOnDy5EnjPikpKSxcuJDmzZtTtWpV/Pz8+Oabb9K59uzZg5+fH+7u7nTs2JFTp07pnv/8+XOULl2GAgUKmLRXdfcw9puLV6Ws4lUvq3jVy6qiVw9UGIO4uDju3bvLtatX+XrFcg7+8hN16tY12ef0qVNs2byJsYEfZGkRRRXGQcWsqnlVyipe9bKKV9+sgpAT5MnKQUeOHEnXlpKSQnh4OMnJyTg6OsqaNmZOeHg4EydOZNiwYRQsWJClS5cSEBDArl27KFKkCNOnT2flypUMGjSIatWqsX//fj7++GOSkpLo0aMHAOfOnWP48OE0btyY999/n+vXr/Puu++SkJCge/aMvvUtWtTpYf9ts/GqlFW8+jnFq69XpawqevVAhTGYNWOacQ0bS0tLvH1a8P74CcZ+TdOY9tlkWvq1xtOrGqGh13M1r95elbKq5lUpq3j1c4pXX69Kn5GC8DhZKtrs25fxHRQSExNZu3YtK1as4Msvv3yhYIK+REZGEhQURL169QCoXbs2TZo0Yfny5fTp04dVq1YREBDAsGHDAGjYsCH37t1jwYIFdOvWDSsrK5YsWUKJEiVYsGABVlZWQOo0w/Hjx+ua3WCIx8bGJl27ra1tan98vNl4VcoqXv2c4tXXq1JWFb16oMIY9PDvRQtfP8Jv3+aHH3aQnJJCYmKisX/zpg388/dfzJozL0tZszuv3l6VsqrmVSmrePVzildfr0qfkXoid9ZWk2xd08ba2poePXrQoEEDJk+enJ1qIZuxt7c3FmzSHtevX5+QkBBOnTpFYmIifn5+Jse0atWKu3fvcvnyZQBCQkJo1qyZsWADpDtGD2xt7TKczWMwGFL77ezMxqtSVvHq5xSvvl6Vsqro1QMVxqBsufLUrVeftu3eJHjhYuLi4hg2ZCCaphEbG8u8ObPp1SeA4iVKZClrdufV26tSVtW8KmUVr35O8errVekzUhAeR5eFiN3c3Dh69KgeaiGbcHR0TNdWpEgRwsPDiYqKAqBo0aIm/WmPIyMjgdRphkWKFDHZp0CBAsaKtV44OTlxJzw8XfudO+EP+53NxqtSVvHq5xSvvl6Vsqro1QMVx6BFi5b8ceY0Vy5fYsVXy0hMTKSlX2tCQ68TGnqdsFu3AIiOjiY09DqJz3CpsErjoFJW1bwqZRWvfk7x6utV6TNSEB5Hl6LNoUOHZE0bM+fu3bvp2iIiInBycsLBwcH4+FHu3LkDYOx3cnJKt09sbKyxYq0Xrm5uXLlymdjYWJP206dCAHBzq2Q2XpWyile9rOJVL6uKXj1QcQwMhtSp8zExsdy6eZPo6Cg6tHud1r7etPb1pk/P7gB8sWQRrX29uXDhQq7llfeZWl6VsopXvazi1TeralhaWJjtJmROloo2wcHBGW5Tp06lQ4cO7Nq1i44dO2Z3ViEbiYmJ4fDhwyaPDx06hKenJ+7u7lhbW7Nz506TY3bs2EGRIkUoU6YMAB4eHvz4448kJycb93n8GD3w8fUjOTmZ9d+uNbYlJCSweeMG3D08szxVXQ+vSlnFq15W8aqXVUWvHpjzGDz+ZQSkrtm35fvN2NnZUb58ed7u4c+ceQtMto8+ngTAG292YM68BZQsVSpH8uaUV6WsqnlVyipe9bKKV9+sgpATZGkh4uDg4AzbCxUqxKuvvsrEiRPp3LnzCwUT9MXBwYHx48czfPhw7O3tWbp0KZqm0atXLxwdHenRowfLli3DxsYGLy8vDhw4wNatW/noo4+Ma9j079+fjh07MmTIELp168b169dZtmyZ7pdHeXh44tvSj3lBs7kbEcGrr5Vmy+aN3LgRyieTPzUrr0pZxateVvGql1VFL8Ca1auIiYkm/Hbq3TUO7P+RsLDUy4G6dffH3t7eLLJmh3fyxAncj42lRs1aODsX486dcLZv28KlixcZNSaQfPnzU6lyFSpVrmJyXNrdoypUqEBzb58cy5tTXpWyquZVKat41csqXn2zCkJOYKFpmpbbIYScJTAwkDNnzjB69GimT5/O1atXqVixIh999BHVq1cHUm/h/vnnn/Pdd98RHh5OyZIl6dOnD127djVx7d69m5kzZ3Ljxg0qVqzIxx9/TEBAAL169TLeeSorxCc9ud9gMLBgfhDbtmwhOjqKii6uDBk2ggYNG2X5nHp5VcoqXvWyile9rCp6W7Vozo0boRn2bd+1l5Ilnz6rJKeyvqh3x/ZtbNrwHX//9RdRUZHky5efylWq0O3tHjRt7p3pcaGh12nt683I0WPp1Scgx/LmpFelrKp5VcoqXvWyivfFnHZZmuZgnnyw/a/cjpApn7V2ye0IZstzF23i4+OZM2cOderUoXnz5nrlEnQkrWizdevW3I6SKU8r2giCIAiCIAiCIOiNFG1yBinaZM5zr2ljZ2fH2rVrM7zmWxAEQRAEQRAEQRAEQcgeslQ3rFKlCn/9Zb5VOkEQBEEQBEEQBEEQ/kVu0qQmWSrafPDBB/Tv3x8XFxfat29Pnjwv0Zyx/wDTpk3L7QiCIAiCIAiCIAiCIDyFZ17T5ujRo5QvXx5HR0fatm3LvXv3iIiIwMbGhmLFiqW7Y5CFhQXff/+9LqGFlx9Z00YQBEEQBEEQhNzmZVrTZvwO871a5tNWsqZNZjzzS7Bnz57MmDGDNm3a4ODggIODA2XLltUzmyAIgiAIgiAIgiAI2YClXB+lJM9ctNE0jbRJOV9//bVugQRBEARBEF4WEpJSdPHa5Hnue0kIgiAIgqAg8okvCIIgCIIgCIIgCIJghjzXFXoWMp1KEARBEARBEARBEJRD/jmvJs8102bMmDFUqlTpmbbKlSvrlfmlJDo6mvnz5/PPP//kdhQlSEhIYM6sGfg0bUjt6h5079qJw4cOmqVXpaziVS+reNXLKl71sj6P959//mb0e8Np3dKbOjU88WlSj/59evDT/h9N9qvlWSnTbciAvib7pqSksPKrL2jXyocGtTzp1rEdO7ZtzfFxyO2xNQdv3P37LAyex6D+ATSqVxvPKq5s3rjBLLOKV1+vSlnFq29WQdCbZ757lJubGw0aNKBMmTLPLP/oo4+ymus/x/Xr1/H29mbu3Ln4+fnldpxc52l3jxo3eiR7dv9Ad/+evPZaGb7fvJE/zpxm6ZcrqF6jZpbPq4dXpaziVS+reNXLKl71sj6P9+efDvB/q1bi6VUNJydnYuPi+HHPLk78fpz3P5pIh46dAdi+Nf0dNs+dPcM3q79m+Huj8e8dYGwPnjubFV8u5c23OlG5SlV++nEfv/x8gGkzZtOq9es5Ng65Pbbm4A0NvU5rX29KlHiFkqVKcezob0yaMpV27TtkOadeWcWrr1elrOJ9MefLdPeoCT/8ndsRMmVSy4q5HcF80Z4RV1dX7fvvv3/W3YXn4MGDB9q1a9c0FxcXbceOHbkdxyx4kJj59tvxEM3FxUVbtOQLY1tkbLzm7e2jderc5YnH5rRXpaziVS+reNXLKl71sr6oN+pBsnY3NkF7ve0bWgvfllrUg+RMtzHj3tdcXV21vy6HGtv+vnxDq1y5ijb+o0+MbZFxSVrXbm9rjRo31mLjk+Q5y0Fv1H2Ddu3Gbe1BoqYdO3FKc3Fx0b5Ztz7LPhXHQLxqZRXviztfJj7+4S+z3YTMkYWIn5HAwEDatGnDgQMHaNOmDe7u7nTo0IGTJ08a90lJSWHhwoU0b96cqlWr4ufnxzfffGPimT9/PtWqVePUqVN06dIFd3d3Vq9ejbe3NwAjRozA1dUVV1dXrl+/DsCSJUto0aIF7u7u1K1bl969e3Pt2jUAevXqxZgxY4z+M2fO4OrqyvDhw41tFy9exNXVlVOnThnbTpw4Qc+ePfHy8qJGjRqMGjWKiIgIk6wJCQnMnj2bZs2aUbVqVVq1asWWLVuee1yymz27dmJlZcVbnboY22xtbWn/VkdCTp7g1s2bZuNVKat41csqXvWyile9rNnhtbKyolix4sTExGS6T0JCAvv27KZ6jVoUK1bc2H5g/16SkhLp2KWbsc3CwoLOXboRdusWISdPZHvejDDXsc1pr42NDUWdnLJ0bGaoNgbiVSurePXNKgg5gRRtnoPw8HAmTpxIQEAAQUFB2NjYEBAQYCx2TJ8+neDgYNq3b8+iRYto2LAhH3/8MatWrTLxJCYmMmrUKN544w2WLl1KgwYNCA4OBmDkyJGsXbuWtWvX4uzszKZNm5g7dy4dO3bkiy++YMqUKVSqVIn79+8DUKtWLY4dO2Z0Hz16FFtbW44fP27Sli9fPqpUqQKkFmz8/f2xt7dnzpw5TJ48mdOnTzN48GCTnCNGjGDt2rX06dOHxYsX06hRI8aMGcOBAweea1yym/Pnz1G6dBkKFChg0l7V3cPYby5elbKKV72s4lUvq3jVy5pVb1xcHPfu3eX6tav839fLOXzwZ2rVqZvpOQ7+fICYmGj8Xm9j0v7n+XPkzZuPsuXKP/O55TnTz6sHqo2BeNXKKl59swpCTvASXaGnP5GRkQQFBVGvXj0AateuTZMmTVi+fDl9+vRh1apVBAQEMGzYMAAaNmzIvXv3WLBgAd26dcPKygpILdq89957tG7d2uhO+wVSunRpvLy8jO2nTp3C1dWVAQMGGNt8fHyM/12zZk3mz59PaGgoJUuW5OjRo7z11lt88803XLhwgfLly3P06FGqV69uPP+sWbOoWrUqwcHBxjuCubi4GGfMNGnShF9//ZV9+/axbNkyGjZsCECDBg0IDw9n/vz5NGnS5JnGZdSoUdkz+I8QHh6e4bdcRYs6Pey/bTZelbKKVz+nePX1qpRVvPo5zc07a8Y0vlu3FgBLS0uaebdg7PsfZnqOndu3YmNjg7dPS5P2iPBwHIsUSXcHz7Q84bfTn1ueM/28eqDaGIhXrazi1c+pIpZy+ygleeaZNufPn6dt27Z6ZjF77O3tjYWJtMf169cnJCSEU6dOkZiYmG4R4VatWnH37l0uX75s0v5o0eNJVK5cmbNnzzJ16lSOHTtGYmKiSb+XlxfW1tYcPXoUTdM4fvw43t7euLq6cvToUQCOHz9OzZqpi2s9ePCA33//HT8/P5KTk0lKSiIpKYkyZcpQokQJTp8+DcDBgwdxcHCgbt26xn2SkpKoX78+586dIzk5+ZnGRQ8MhnhsbGzStdva2qb2x8ebjVelrOLVzylefb0qZRWvfk5z8/bw78XiL77ikylTqd+gEcnJyek+w9OIjY3l4M8HqN+wMfYFC5r0xRsMz31uec708+qBamMgXrWyilc/pyDkFDLT5jlwdHRM11akSBEuXLhAVFQUAEWLFjXpT3scGRlpbMubNy/58+d/pnN26NCB+/fvs27dOpYvX469vT1vvvkmo0ePxs7ODjs7O9zd3Tl27BiVK1cmNjaWatWqUbNmTY4ePUrDhg25ceMGtWrVAlJvLZ6cnMzUqVOZOnVquvPdfHg9571794iMjDReUvU44eHhFC9e/Knjoge2tnYkJCSkazcYDKn9dnZm41Upq3j1c4pXX69KWcWrn9PcvGXLladsufIkJKXwets3GToggJHDBrN89dp0s2b27dmFwWCg1evpvxyzs7V97nPLc6afVw9UGwPxqpVVvPo5BSGnkKLNc3D37t10bRERETg5OeHg4GB8XKxYMWP/nTt3AIz9QLo/1p6EpaUlvXr1olevXoSFhbFt2zZmzZpF4cKFGTJkCJC6rs0PP/xApUqVqFSpEvnz56dWrVp8+umnHDt2DBsbGzw8Uq/XtLe3x8LCggEDBphcZpVG4cKFAShUqBCOjo4sWbIkw1yPFmqeNC564OTkxO2wsHTtd+6EP+x3NhuvSlnFq59TvPp6VcoqXv2c5u5t3qIlUyd/zJUrlylTpqxJ387tWyhgb0/Dxk3THVfEyYljR39D0zSTvx/uhD88t3P6c8tzpp9XD1QbA/GqlVW8+jlVRK6OUhNZiPg5iImJ4fDhwyaPDx06hKenJ+7u7lhbW7Nz506TY3bs2EGRIkUoU6bME93W1tbAv9XejChWrBh9+/bF1dWVixcvGttr1qzJ5cuX2blzp3FGTa1atQgLC2P9+vV4eHgYpwPmy5cPLy8vLl68iLu7e7qtVKlSANSvX5+7d+9ibW2d4X6PTi980rjogaubG1euXCY2Ntak/fSp1Mux3NwqmY1XpaziVS+reNXLKl71smaX12BInXp//7E7SN0Jv83xo7/R3LtFhlP3XVzdiI9/wKWLprNXn3Ruec708+qBamMgXrWyilffrIKQE0jR5jlwcHBg/PjxbNq0ib1799KvXz80TaNXr144OjrSo0cPli1bRnBwML/88guffvopW7duZfDgwcZFgDPDycmJggULsm3bNo4fP87p06dJSEhgwoQJzJw5kz179vDbb7+xaNEizp8/T926/96BIm2R4d9++81YtHF0dKR8+fL89ttvxvVs0hg7diz79+/n3XffZffu3Rw5coTNmzczbtw4jhw5AqQuOtysWTPeeecdli9fzuHDh9m3bx9Llixh/PjxzzwueuDjm7oez/pv1xrbEhIS2LxxA+4enhQvUcJsvCplFa96WcWrXlbxqpf1eb0Z3TkxKTGR7Vs2Y2tnR9nypneB2rVzOykpKfi1znjdwCbNvMmTx5rv1q4xtmmaxrfrvsG5WDE8vaq9UN5nxRzG1hy8eqDaGIhXrazi1TerIOQEcnnUc+Dk5MTo0aOZPn06V69epWLFiixbtsy4bs3YsWOxt7fnu+++Y9GiRZQsWZKJEyfStWvXp7otLS2ZOnUqs2fPpnfv3iQkJLB3716qVavGunXr+Pbbb3nw4AGvvvoq77//Pp06dTIeW6BAASpVqsTZs2epUaOGsb1WrVpcuHDBWMhJo3r16vzf//0f8+fP5/333ycxMZHixYtTt25dSpcubdxv3rx5LFmyhDVr1hAaGoq9vT0VK1akQ4cOzzUu2Y2Hhye+Lf2YFzSbuxERvPpaabZs3siNG6F8MvlTs/KqlFW86mUVr3pZxate1uf1Tp44gfuxsdSoWQtn52KE3b7Nzu1buXzpIu+OGke+fKZr2u3cvhUnJ2dq1Kqd4bmLFStOtx7+fL38S5KSkqhctSoH/p+9846rsvrj+BuIoYETSHNrgqksBy5coOIst6aiJqm4Z4aZlprpT1NJNEOjtPRX5s5talq5B67UspyIDEEZyub+/kDuzxvg5IF76Pvu9bzynnOe9/O5BxL63nOeZ99eTp08wez/fJrjh0LyNdPOC/Dd6lXEx8fpn9x1YP/PRESEA/BWXx9sbGyMIqt4tfOqlFW82mZVDVPZHqUkJjqdTlfQIVTA39+f8+fPs3Xr1oKOYlRoNS9JaY/vT05OZklgANu2bCEuLpbqDo6MGDWGJh5NX+i6WnhVyipe9bKKV72s4lUv67N4d2zfxqYN67j855/Ext6jaNGXqVGzJj3f6kfzFp4GY69du0qPN9vTx2cg4ya+l+u1MzIyWPn1l2xct4Y7UVFUqFiJd4YMpUPHN/J1Hgp6bo3F2661J2Fht3Ls2757L+XKlTearOLVzqtSVvG+mNOqEC1zmLX3r4KOkCtTvF4r6AhGixRtnhIp2uRMQRVtBEEQBEEFUtIyNPFavCQ73AVBEPIDKdrkD1K0yZ1C9C0oCIIgCIIgCIIgCEJOmCD7o1REVtoIRomstBEEQRAKA7LSRhAEQW0K00qbT/b+/eRBBcT7XtWePOhfivzEFwRBEARBEARBEARBMEIKUd1QEARBEARBEARBEISckKdHqYkUbQRBEAThX056hjY7pc3kt0PZxiQIgiAIwgshv0kIgiAIgiAIgiAIgiAYIbLSRhAEQRAEQRAEQRAKObIAVk1kpU0h4ejRo3zxxRfPdW5oaCiOjo7s3LnzseM2bNiAo6MjMTExz3WdvCQlJYWF8+fRqoUH7nWc6du7B4cPHTRKr0pZxateVvGql9UYvOfPneWTj2fQ5Y0ONKjnSvvWLXlvwliuX7uabeyVK38zwu8dmrjXoUWTBnwweRJ3c/k5cPPmDd6fNAGv5o1pVM+FTu3aEPjZwhfK+qyIVzuvSlm18h4/dhSXWo45HmfPnDaqrOLV1qtSVvFqm1UQtEaKNoWEY8eOERQUVNAx8o2p7/uz6psVtO/YiUn+UzAzM2PksCGcOnnC6LwqZRWvelnFq15WY/B+Hfwle3/aTYOGjXjPfwpdu/fk1MkT9OnZjb8u/6kfFxEezjsD+3Hzxg1GjhmLz8C3+e2XAwwbMojU1BQD5x+XLtK3Vzf+/PMPfPq/zaTJH9C2fQciIyONcg7EaxxOFb0Affr5MGvOXIOjQsWKRpdVvNp5VcoqXm2zCoLm6IRsJCcn69LT0ws6xjOxaNEinaur63Ode/PmTZ2Dg4Nux44djx23fv16nYODgy46Ovq5rvMsJKbmfhw7eUbn4OCg+2LZl/q2ewlJOi+vVroePXs99tz89qqUVbzqZRWvelmNxXv42Eld3P1k/euE5AzdhT+v6GrXrq0bM26CLiE5Q5eQnKGbMvVDnbOzs+7ytVB92979v+kcHBx0K1d9p2+LS0zTtW/fQde1ew/dndgH+nZjngPxFrxTRe8vB4/oHBwcdD9u3fHcDtXnQLxqZRXvizsLE3N//ttoDyF3Cv1KG39/fzp27MiBAwfo2LEjTk5OdO3aldOnT+vHeHp6MmPGDJYvX07Lli1xdnbm3r17ZGRk8Pnnn+Pp6Unt2rVp27Yt33//fbZr/P3334wcORJ3d3dcXFx444032Lp1q75fp9MRHByMt7c3tWvXxsvLixUrVhg4wsPDGTNmDI0bN8bJyQlPT08++eSTp+oPDAxk8eLFPHjwAEdHRxwdHfHx8dFnGzduHM2bN8fFxYX27dvz1VdfkZGRke19JCYm8v7771O3bl3c3d2ZPXs2aWlpj53flJQUFixYQMuWLalduzbt2rVjy5YtT/y6vAh7du/EzMyMbj166dssLS3p0q07Z06HEH77ttF4VcoqXvWyile9rMbidXWrg7mFhcH5FStVpmq117h65W99296fdtO0WQvKln1V39agUWMqVa7MT7v+v6X28KGD/PXXZYb6jcDKyorExETS09ONeg7EW/BOFb2Pcv9+whN/T3oaVJsD8aqVVbzaZhWE/OBfcSPiqKgopk+fzqhRoyhWrBjLly/H19eX3bt3U7p0aQB2795NpUqVmDJlCqamphQtWpS5c+fyzTffMGzYMNzc3Ni/fz8ffvghaWlp9OvXD4Br167Rq1cvypYty5QpU7Czs+PPP/8kLCxMf/1Zs2axdu1a/Pz8cHFx4dSpU3z66adYWlry1ltvATBp0iQiIyP54IMPKF26NLdv3+b8+fN6x+P6e/ToQXh4OFu3bmXlypUAWFtbAxAZGUmVKlXo1KkTL7/8MhcvXiQwMJAHDx4wcuRIg3lasGABHh4eBAQEcOHCBRYtWoS5uTkTJ07MdW7HjBnDqVOnGDFiBNWqVePAgQO8++67FCtWjObNm7/oly5HLl26SKVKlfXvMYvaTs76/jJlyxqFV6Ws4lUvq3jVy2rMXp1OR0x0NFVfew2AyIgIYmKieb1W7Wxja9V25uCvB/Svjx05BIC5hQV9e3Xj4oXfMTc3x7NVa6Z88CHFS5TI06y5IV7tvCpl1dKbxbQPJvPgwQPMzMxwq1OX8RMnUau203O5VJsD8aqVVbzaZhWE/OBfUbS5d+8eAQEBNGrUCAB3d3eaN2/OihUrmDBhAgCpqaksX76cokWLAhATE8OqVavw9fVl1KhRAHh4eHD37l2WLFnCW2+9hZmZGYGBgZibm/Pdd9/p/xJo3Lix/to3btxg1apVTJ8+nV69eun7k5KSWLJkCb169cLU1JRz584xfvx42rdvrz+3c+fO+j8/rr9MmTKUKVMGU1NTXF1dDd57o0aN9O9bp9NRt25dkpKSWLVqVbaiTcWKFZk9ezYATZs2JSkpia+//prBgwdTvHjxbPN65MgR9u3bR3BwMB4eHgA0adKEqKgoAgMDNSvaREVFYWtnl63d1tbuYX/O908oCK9KWcWrnVO82npVymrM3u1btxAZGYHfyNEA3LmTOT5Hp50dsbGxpKSkYGFhwY3r1wHwnziWRk2aMuidIfz5xx98HbyMiNu3WbHqO0xM/v/ICmOdA/Hmr1NFr7m5Oa1ae+PRrBklS5Tk77//5psVwbzdvy8rV3/P66/XNJqs4tXOq1JW8WrnVBF5epSaFPrtUQA2Njb6wkXW68aNG3PmzBl9W4MGDfQFG4CzZ8+SmppK27ZtDVzt2rUjJiaGa9euAZmFC29v72xV2ywOHcr89LFNmzakpaXpj8aNGxMVFcXth0vxatasyVdffcV///tfrj/85fdRntSfG8nJySxatIjWrVvj5ORErVq1WLhwIVFRUdy/f99gbOvWrQ1ee3t7k5iYyJ9//klOHDx4kBIlStCwYcNs7+3ixYuPXRr/IiQnJ2Hxj2X9kLnEESA5KclovCplFa92TvFq61Upq7F6r165wn8+mYGziyud3ugMQFJSMgAW5jk4LQydDxIfAFCzlhOz5szDq7U3w0aOZvjIMZw+HcLRI4fzLOvjEK92XpWyaul1davD/IBFdOnanRaeXvgOHsK3//0BExMTFi2cb1RZxaudV6Ws4tXOKQj5xb+iaFOqVKlsbaVLlyYqKsrg9aPExsYCYGtra9Ce9frevXv6f9vb2+d67bt376LT6WjYsCG1atXSH2+//TaAvmizcOFCGjZsSEBAAG3atKFt27bs3r1b73lSf27MmzeP4OBgevTowbJly1i3bh3Dhg0DMgs6j/LPecp6r4/O0z/f27179wzeV61atfjggw9IS0vL9bwXxdLSipSUlGztWe/H0srKaLwqZRWvdk7xautVKasxeu9ERTFmxFCsrW2Yt+AzzMzMALCyyvxFNiU1B2eKoTPrl9627TsYjGvfoSMAp0NO5UnWJyFe7bwqZdXSmxMVK1WiRUsvjh87+lwfWKk2B+JVK6t4tXMKQn7xr9geFRMTk60tOjoau0eWyD26bBugxMP999HR0bzyyiv69jt37hj0lyhRItfHmQIUL14cExMT/vvf/2Jubp6tv0qVKgDY29sze/ZsMjIyOH/+PEuXLmXcuHHs3LmTChUqPLE/N3bu3EmvXr0YMmSIvu3AgQM5jv3nPGW9V7sclhJmvbdSpUqxbNmyHPtzKpblBXZ2dkRGRGRrv3Mn6mF/7kW0/PaqlFW82jnFq61XpazG5o2Pj2e432Di4+MIXrkaO/v//7yztc0cfyeHAvydqCiKFy+u/9Qyy13qHx+AZL2Oj4t74axPg3i186qUVUtvbpQpU4bU1FQSExNzXX2dG6rNgXjVyipe7ZyCkF/8K1baxMfHc/jwYYPXhw4dwsXFJddznJycMDc3Z+fOnQbtO3bsoHTp0lSuXBnIvGfMrl27SEhIyNGTtS3r3r17ODk5ZTv++YPd1NQUZ2dnxo4dS1paWratULn1m5ub51o9frRYlJ6ezrZt23LM+tNPPxm83rVrF0WKFMHBwSHH8Y0bNyYmJgZzc/Mc31tOSxDzAscaNbh+/Vq2OT93NnO7W40arxuNV6Ws4lUvq3jVy2pM3uTkZEaP8OP69WsELP6CqtVeM+i3f+UVSpYqxcXfz/NPfj9/FodHfK/XrAWQ7UOMqIevS/6jiG8scyDewplVS29uhIaGYmlpabDV/mlRbQ7Eq1ZW8WqbVTVMTIz3EHLnX1G0KVGiBFOmTGHTpk3s3buXwYMHo9PpGDBgQK7nlCpVin79+hEcHMzixYv57bffmDVrFlu3bmX48OH65eMjR44kNTWVPn368OOPP3L48GFWrVrF8uXLgcyVNH379mXSpEksXbqUQ4cOceDAAVauXMnw4cOBzCJSz549Wb16tb5/3rx5FCtWjJo1az6xH6BatWqkpaWxcuVKzp49y5UrV4DMwsratWvZuHEj+/fvZ9iwYTkWdyDzpsmTJ0/m119/JSgoiGXLltGnT58cb0IMmTcdbtmyJe+88w4rVqzg8OHD7Nu3j2XLljFlypTn+2I9Ba3atCU9PZ31a9fo21JSUti8cQNOzi7Pfed3LbwqZRWvelnFq15WY/Gmp6czacJYzp45zacLPsPF1S1Hp1erNvz6y37Cw///KNSjRw5z/do1Wrf5/z3fWnh6YWFhwY+bNpCRkaFv37B+LQANG/3/Bv3GMgfiLXinit6cVm//cekS+3/eR6PGTTA1ffZfrVWbA/GqlVW82mYVhPzgX7E9ys7OjokTJzJ37lxu3LhB9erVCQ4Ozna/mn8yadIkbGxsWLduHV988QXlypVj+vTp9O7dWz+mcuXKfP/998yfP5/p06eTnp5O5cqVDbYjffDBB1SpUoU1a9awZMkSXn75ZapUqaK/ybGlpSUODg58++233L59GysrK2rXrk1wcDClSpUiJSXlsf0ALVu2pE+fPixbtozo6Gjq16/Pt99+y9SpU/nwww+ZOXMmRYoUoUuXLrRu3ZoPPvgg2/sdN24cx44dY8yYMZiZmdGnTx/GjRv32DlatGgRy5Yt47vvvuPWrVvY2NhQvXp1unbt+tRfn2fF2dmFNt5tWRSwgJjoaCpUrMSWzRsJC7vFRzNnGZVXpaziVS+reNXLaize+XPnsP/nfTRv0ZLY2Hts2/KjQX+HTm8AMGjwUPbs3smQQQPo09eHB4kP+Obrr3itugNvdP7/3/O2tnb4DvZj6ZJFjPR7hxaerfjzj0tsXL+Wdu076h+pakxzIN6Cd6ronTRhLFZWVri4ulGqVGmu/P0X69b9QJEiVowZN9GosopXO69KWcWrbVZByA9MdDqdrqBDaIm/vz/nz59n69atBR1FeAaS0h7fn5yczJLAALZt2UJcXCzVHRwZMWoMTTyavtB1tfCqlFW86mUVr3pZjcHrO9CHE8eP5eo5de6S/s9//3WZ+fPmcDrkFOYvmePRrDnjJ75H6X988KHT6Vjz3WrWfLeKW6G3sLW1pdObnRk6bESO93Qr6DkQr3E4VfOuXvUN27du4eaNG9y/n0DJkiVxb9gIv2EjqVipklFlFa+2XpWyivfFnFaFaJlDwK9XCzpCroxtWqWgIxgtUrQRjJInFW0EQRCEvCM9Q5tfBcxMZZO6IAiCoDZStMkfpGiTO/+Ke9oIgiAIgiAIgiAIgiCoRiGqG+bMnDlzCjqCIAiCIAiCIAiCIBQosgBWTWSljSAIgiAIgiAIgiAIghEiRRtBEARBEARBEARBEAQjpNBvjxIEQRAE4fHIDYMFQRAEofBjIj/ulURW2giCIAiCIAiCIAiCIBghUrQRBEEQBEEQBEEQBEEwQqRoIyhJSkoKC+fPo1ULD9zrONO3dw8OHzpolF6VsopXvaziVS+rit7r168xaeI4Wns2o0FdF97s2JYvPl9MYmKi0WUVr3ZelbKq5lUpq3jVywrw4P59Pl+8iGFDfGnayB2XWo5s3rjBaPOq9DVTCVNMjPYQckeKNoKSTH3fn1XfrKB9x05M8p+CmZkZI4cN4dTJE0bnVSmreNXLKl71sqrmDb99m769e3DuzBl6v9WPd997H2cXN5YuCcT/3fFGlVW82npVyqqaV6Ws4lUvK8Dde3cJWrqEq1eu4ODo+EKuR1FpHrTKKgiaoxMEIyQxNffj2MkzOgcHB90Xy77Ut91LSNJ5ebXS9ejZ67Hn5rdXpaziVS+reNXLqqI3cMlSnYODg+7cxT8N2idMnKRzcHDQRdy5ZzRZxaudV6WsqnlVyipe9bJmHbH3k3U3wyJ1iak63YmQszoHBwfd9z+sfyGnSvPwIs7CxOLfrhrtIeSOrLQRlGPP7p2YmZnRrUcvfZulpSVdunXnzOkQwm/fNhqvSlnFq15W8aqXVUVvQkICAKVLlzZot7Wzw9TUlJfMzY0mq3i186qUVTWvSlnFq17WLCwsLLC1s3vu83NCpXnQcm5VwsTEeA8hd6RoIzwRf39/OnbsyIEDB+jYsSNOTk507dqV06dP68fs3buXrl274ubmRr169ejatSsHDhzQJM+lSxepVKky1tbWBu21nZz1/cbiVSmreNXLKl71sqrorV/fHYCPpk7h0sWLhN++zc4d21m75jv69PWhaNGiRpNVvNp5VcqqmlelrOJVL6uWqDQPqs2tIDzKSwUdQFCDqKgopk+fzqhRoyhWrBjLly/H19eX3bt3c//+fcaMGUOHDh2YMGECGRkZXLp0idjYWM2y5PRJga2t3cP+SKPxqpRVvNo5xautV6WsKnqbNG3GiFFjCF4exP6f9+nbBw/xY+SYcUaVVbzaeVXKqppXpazi1c6ppVcrVJoH1eZWEB5FijbCU3Hv3j0CAgJo1KgRAO7u7jRv3pwVK1ZQq1YtUlNTmTp1qr563bRpU82yJCcnYWFhka3d0tIysz8pyWi8KmUVr3ZO8WrrVSmril6AV8uVo07derRq7U3xEiX49Zf9fLk8iNK2drzVt5/RZBWvdl6VsqrmVSmreLVzaunVCpXmQbW51QpT2YakJFK0EZ4KGxsbfcEm63Xjxo05c+YMXbt2xczMjIkTJ9KzZ0/q16+PjY2NZlksLa1ISUnJ1p6cnJzZb2VlNF6VsopXO6d4tfWqlFVF747t25j50TR+3LaLV8qUAaBV6zZkZOgIWPgp7Tp0oESJkkaRVbzaeVXKqppXpazi1c6ppVcrVJoH1eZWEB5F7mkjPBWlSpXK1la6dGmioqKoUqUKX3zxBfHx8YwcOZJGjRrh5+dHWFiYJlns7Oy4ExWVrf3OnaiH/fZG41Upq3i1c4pXW69KWVX0/vD9f6lR43V9wSaLFi09SUpM5NLFZ78PgGpzIF61sqrmVSmreLVzaunVCpXmQbW5FYRHkaKN8FTExMRka4uOjsbu4d7QZs2asXr1ao4dO8bcuXP5/fffmTx5siZZHGvU4Pr1a/onmmRx7uwZAGrUeN1ovCplFa96WcWrXlYVvdHRd0jPyMjWnpaWCkB6WtozO1WbA/GqlVU1r0pZxateVi1RaR5Um1utMDUxMdpDyB0p2ghPRXx8PIcPHzZ4fejQIVxcXAzGWVtb0759ezp06MDff/+tSZZWbdqSnp7O+rVr9G0pKSls3rgBJ2cXypQtazRelbKKV72s4lUvq4reSpWqcOniBa5du2rQvmP7NkxNTanu6Gg0WcWrnVelrKp5VcoqXvWyaolK86Da3ArCo8g9bYSnokSJEkyZMoXRo0djY2PD8uXL0el0DBgwgO+//57Tp0/TtGlT7OzsCA0N5ccff6RJkyaaZHF2dqGNd1sWBSwgJjqaChUrsWXzRsLCbvHRzFlG5VUpq3jVyype9bKq6B04yJeDv/3C2/370vutvpQoUYJfDuznt19/oWu3Htjbv2I0WcWrnVelrKp5VcoqXvWyPsp3q1cRHx9HVGTmk5IO7P+ZiIhwAN7q6/PM96RUaR60nltB0BITnU6nK+gQgnHj7+/P+fPnmThxInPnzuXGjRtUr16dqVOnUqdOHUJCQvjiiy/4/fffuXfvHnZ2drRq1YoxY8bonyb1rCQ9YbV9cnIySwID2LZlC3FxsVR3cGTEqDE08Xixp1Zp4VUpq3jVyype9bKq6D139ixffB7IpYsXuXfvHuXKl+ONN7swcNA7vPTS833+o9ociFetrKp5VcoqXvWyZtGutSdhYbdy7Nu+ey/lypV/ZqdK8/C8TqtCtMxh+dHrBR0hVwY3qFTQEYwWKdoITySraLN169Z8u+aTijaCIAiCIAiCIAhaI0Wb/EGKNrkj97QRBEEQBEEQBEEQBEEwQgpR3VAQBEEQBEEQBEEQhJyQpzSpiRRthCcyZ86cgo4gCIIgCIIgCIIgCP86ZHuUIAiCIAiCIAiCIAiCESIrbQRBEARBEARBEAShkCO7o9REVtoIgiAIgiAIgiAIgiAYIVK0EQRBEARBEARBEARBMEKkaCMoSUpKCgvnz6NVCw/c6zjTt3cPDh86aJRelbKKV72s4lUvq2rev/66zMRxo2nv7UWDui40b9KAt/v3Zf/P+4wuq3i19WqV9cH9+3y+eBHDhvjStJE7LrUc2bxxwwt7ZW7Fq6VXpazi1TarSpga8SHkjszPv5wVK1Zw4MCBbO2enp7MmDHjsec6OjoSHBysf71hwwa2bNmS5xlzYur7/qz6ZgXtO3Zikv8UzMzMGDlsCKdOnjA6r0pZxateVvGql1U17+2wMO7fv88bb3Zhkv8UhvgNB2DMyGGs+2GNUWUVr7ZerbLevXeXoKVLuHrlCg6Oji/kehSZW/Fq6VUpq3i1zSoImqMT/tW0bNlSN3369Kduf5SQkBBdRESE/nW/fv10Q4YMyZNciam5H8dOntE5ODjovlj2pb7tXkKSzsurla5Hz16PPTe/vSplFa96WcWrXlYVvTkdCUlpuk6d3tC18fY2qqzi1c6r5fdX7P1k3c2wSF1iqk53IuSszsHBQff9D+tfyClzK175mok3r5yFia+PXTfaQ8gdWWmjGDqdjpSUlIKOAYCrqyv29vb5ft09u3diZmZGtx699G2WlpZ06dadM6dDCL9922i8KmUVr3pZxateVhW9OWFmZsYrZcoSHxf/XOerNgfi1fb7y8LCAls7u+c+PydkbsWrpVelrOLVNqtqmJiYGO0h5I4UbYwcf39/OnbsyIEDB3jjjTdwcnJi37597N69mzfffBMnJyc8PDyYPXs2ycnJBufeunWL0aNHU7duXVxdXfH19eWPP/7Q93t6enLr1i1Wr16No6Mjjo6ObNiQ8x7yu3fv0q1bN7p27UpMTAxguD3Kx8eHY8eOsX//fr0rMDBQkzm5dOkilSpVxtra2qC9tpOzvt9YvCplFa96WcWrXlYVvVk8ePCAu3djuHnjBt+uXMHB336hQcOGRpVVvNp5tf7+ymtkbsWrpVelrOLVNqsg5AcvFXQA4clERkby8ccfM2zYMMqWLcvly5f55JNP6NChAxMmTODKlSssXLiQ27dvs2jRIgASEhLw8fHB1NSU6dOnY2lpydKlS+nXrx8//vgjZcuWZfHixQwZMoQ6deowaNAgACpWrJjt+lFRUQwaNAhra2uWLVuGjY1NtjEffvgh7777LlZWVrz33nsAlClTRpP5iIqKyvETOVtbu4f9kUbjVSmreLVzildbr0pZVfRmMX/eHP09bExNTfFq1ZrJU6Y9l0u1ORCv9t9feY3MrXi19KqUVbzaOQUhv5CijQLExsayfPlyXFxcAJg7dy6urq7Mnz8fgGbNmlGkSBGmTZvGH3/8oV8xExYWxrZt26hWrRoA9evXp2XLlqxcuRJ/f39q1qyZuSTZ1hZXV9ccrx0WFsbAgQMpV64cS5YsoWjRojmOe+2117C2tqZo0aK5uvKK5OQkLCwssrVbWlpm9iclGY1Xpazi1c4pXm29KmVV0ZtFP58BtG7TlqjISHbt2kF6RgapqalGlVW82nm1/v7Ka2RuxaulV6Ws4tXOqSKyCUlNZHuUApQoUUJfsLl//z4XL17E29vbYEz79u0BOHnyJAAnTpygevXq+oJNlqdx48b6MU/ixo0b9O3bl2rVqhEUFJRrwSa/sbS0yvG+PlnbwyytrIzGq1JW8WrnFK+2XpWyqujNokrVajRs1JhOb3Zm8edBPHjwgFEj/NDpdEaTVbzaebX+/sprZG7Fq6VXpazi1c4pGCf379+nWbNmODo6cu7cOYO+tWvX4u3tjZOTE2+88QY///xztvPj4+N5//33cXd3x83NjdGjRxMZmX0l1qlTp+jVqxfOzs60bNmSZcuWPdfvRE+DFG0UwNbWVv/n+Ph4dDodpUuXNhhjY2ODhYUFsbGxAMTFxRmcl0Xp0qX1Y57EuXPnCAsLo1u3bjlWpgsKOzs77kRFZWu/cyfqYf/z3RxZC69KWcWrnVO82npVyqqiNzdat/bm9/PnuH7t6jOfq9ociDf/v79eFJlb8WrpVSmreLVzCsbJ559/Tnp6erb2bdu2MXXqVNq1a8fy5ctxdXVl5MiRnD592mDc2LFjOXjwIB999BGffvopV69eZfDgwaSlpenHXL9+HV9fX+zs7AgKCmLAgAEsWrSIr776SpP3JEUbBXj0bto2NjaYmJjobwacRXx8PCkpKRQvXhyA4sWLEx0dnc0VHR2tH/MkOnToQP/+/Rk/fjyHDx9+gXeQtzjWqMH169dISEgwaD939gwANWq8bjRelbKKV72s4lUvq4re3EhOzlxKHh+f8ISR2VFtDsSb/99fL4rMrXi19KqUVbzaZhWMi7///pv//ve/jBo1KlvfokWL6NChA2PHjqVhw4bMmDEDJycnlixZoh8TEhLCb7/9xqxZs2jfvj1eXl589tln/PHHH+zevVs/Ljg4mJIlS7JgwQIaNWrEwIEDGTRoEF988YUmT3qWoo1ivPzyy7z++uvs3LnToH3Hjh0A1K1bV//vP//8kytXrujHxMbGcujQIf0YAHNz82xPnXqUKVOm0LlzZ4YPH/7EbVVPcuUVrdq0JT09nfVr1+jbUlJS2LxxA07OLpQpW9ZovCplFa96WcWrXlYVvTl9AJCamsqWHzdjZWVlsA23oLOKVzuvVlm1QuZWvFp6VcoqXm2zqoapiYnRHnnBxx9/TO/evalSpYpB+82bN7l27Rrt2rUzaG/fvj2HDx/WF1p++eUXihUrRpMmTfRjqlatyuuvv84vv/yib/vll1/w8vIy2I3Svn174uLiCAkJyZP38ihyI2IFGTlyJCNGjGDixIm88cYbXL16lYULF+Lt7Y2joyMAXbt2ZcWKFQwdOpSxY8fqnx710ksvMWDAAL2ratWqHDlyhIMHD1KsWDHKly9PyZIlDa43ffp0kpOTGTJkCF9//TXOzs455qpatSqbNm1i37592NnZYW9vzyuvvJLn79/Z2YU23m1ZFLCAmOhoKlSsxJbNGwkLu8VHM2cZlVelrOJVL6t41cuqonfm9GncT0igbr362Nu/wp07UWzftoWrV64w4V1/ir78stFkFa92Xq2yZvHd6lXEx8cR9fC+AQf2/0xERDgAb/X1yfHJlQWRV6W5Fa92XpWyilfbrILxsHPnTv78808CAwP5/fffDfqyFjL8s5hTrVo1UlNTuXnzJtWqVePKlStUqVLFYKcLZP5/bpbjwYMH3L59m6pVq2YbY2JiwpUrV2jQoEGevjcTnVZ3yxHyBH9/f86fP8/WrVsN2nft2sWSJUu4cuUKJUqUoH379kyYMEF/B3SAW7duMWfOHA4ePEhGRgZ16tThvffe0xd2AC5fvsxHH33ExYsXuX//PrNnz6Zr1654enrSokULpk3LfJxreno6EydO5ODBg3zzzTfUqFEDR0dHJk2ahK+vLwARERFMnTqVkJAQ4uLiGDlyZI5L056GpLTH9ycnJ7MkMIBtW7YQFxdLdQdHRowaQxOPps91PS29KmUVr3pZxateVtW8O7ZvY9OGdVz+809iY+9RtOjL1KxVi7f69KOFp5dRZRWvtl6tsgK0a+1JWNitHPu2795LuXLln9kpcyteLb0qZRXvizmtCtEyh1UnQws6Qq58PWnAY/v37t2ba19iYiLt2rVj5MiRdO/enaNHj9K/f3/WrVuHk5MTP/74I++++y6//fYbdo88+v3cuXN0796d7777jjp16vD2229jampKcHCwgX/GjBkcPHiQXbt2ERERQbNmzViwYAEdOnQwGOfm5sbQoUPx8/N7jhnIHSnaCEbJk4o2giAIgiAIgiAIWlOYijarjbho89ULFG0WLFjAwYMHWbduHSYmJoWuaFOIvgUFQRAEQRAEQRAEQVCNxxVlHsetW7f46quvWLJkCfHx8UDmFqasf9+/f1//IJ74+HiDok1cXByAvr9YsWKEh4dnu0ZsbKx+TNZ23axrZZGSkkJiYuJTP/TnWZCijSAIgiAIgiAIgiAIyhEaGkpqaipDhgzJ1te/f39cXFyYP38+kHlvm0fvRXPlyhXMzc2pUKECkHlfmsOHD6PT6Qzua3P16lUcHBwAKFq0KGXLljV44E/WGJ1Ol+1eN3mBPD1KEARBEARBEARBEAo5JibGezwvr7/+Ot98843BMXnyZCDzgToffvghFSpUoHLlytmewLx9+3YaNWqkfwpUs2bNiI2N5fDhw/oxV69e5cKFCzRr1kzf1qxZM/bu3UtqaqqBq1ixYri5uT3/m8kFWWkjCIIgCIIgCIIgCIJyFCtWLNenNdWqVYtatWoBMGrUKCZOnEjFihVp0KAB27dv5+zZs6xatUo/3s3NDQ8PD95//33ee+89LC0tWbhwIY6OjrRp00Y/ztfXly1btjBhwgTeeust/vzzT4KDgxk3bpzBY8DzCinaCIIgCIIgCIIgCIJQaOnYsSOJiYksX76cZcuWUaVKFRYvXpxtZUxAQACzZ89m2rRppKWl4eHhwQcffMBLL/2/dFKpUiWCg4OZM2cOQ4YMoVSpUowePZpBgwZpkl2eHiUYJfL0KEEQBEEQCgKtfjN+keX/giAUHIXp6VHfhdwq6Ai58pZbuYKOYLTIPW0EQRAEQRAEQRAEQRCMECnaCEqSkpLCwvnzaNXCA/c6zvTt3YPDhw4apVelrP82719/XWbiuNG09/aiQV0XmjdpwNv9+7L/530G486dPcusGR/Ru0dX6rrUwqWWY75nFW/hyaqa9/y5s3zy8Qy6vNGBBvVc8fZqwbvjx3Dt2lWjyypebb0qZc0r78ULvzNmpB/NGrvTsJ4L3Tp35L+rvjEYczrkFAN93qJhPRe8mjfhP598zIMH9/M9q3jz16tSVvFqm1UQtEaKNkI2jh49iqOjI+fOnXum8y5evEhgYCCJiYkaJfs/U9/3Z9U3K2jfsROT/KdgZmbGyGFDOHXyhNF5Vcr6b/PeDgvj/v37vPFmFyb5T2GI33AAxowcxrof1ujH/fbrATasX4eJCZQrX75Asoq38GRVzft18Jfs/Wk3DRo24j3/KXTr0ZOTJ07Qu3tXLl/+06iyildbr0pZ88J76OBv9O/bi5iYGAb7Dedd/yk0a96CiIhw/ZhLly4y9J2BJCUlMeFdf7p06876dWt4d/yYfM0q3vz3qpRVvNpmVQlTIz6Ex6AThH8QHx+vCwkJ0d2/f/+Zzlu/fr3OwcFBFx0d/cIZElNzP46dPKNzcHDQfbHsS33bvYQknZdXK12Pnr0ee25+e1XKKt7MIyEpTdep0xu6Nt7e+rbQ21G6u/GJusRUnW7qh9N1Dg4ORpFVvOplVdF7+NhJXdz9ZIO2S39d1dWuXVs3dvwEo8oqXu28KmV9Ue+DFJ0uMiZe16hRY53fsBG6hKR03YMUXY7H277v6Jo0aaKLjInXt6367w86BwcH3Z6ffzUYq9IciLfwZBXvizsLE9+fCjXaQ8gdKWoJ2bC2tsbV1ZWiRYsWdJQc2bN7J2ZmZnTr0UvfZmlpSZdu3TlzOoTw27eNxqtSVvFmYmZmxitlyhIfF69vK21ri5WV1XNl1DKreNXLqqLX1a0O5v94fGWlSpWp9lp1rl65YlRZxaudV6WseeHdsW0L0dF3GDl6HKampiQ+eEBGRobBmISEBI4ePkT7jm9gbW2tb+/05psULVqUn3btyJes4s1/r0pZxattVkHID6RoUwi5fPkygwcPpkGDBri4uODt7c3y5csBCAkJwc/PDw8PD1xdXXnzzTfZtGmTwfk5bY9ydHRk+fLlBAYG0rhxYxo0aMDkyZN58OABABs2bGDy5MkANGrUCEdHRzw9PTV5f5cuXaRSpcoGvyAB1HZy1vcbi1elrP9m74MHD7h7N4abN27w7coVHPztFxo0bPhcmbTOKl61s6rozQmdTkd09B1KlCj5XOerNgfiVStrXniPHjmMtbU1kZERvNnRm0bubjRpUJdZMz4kOTkZgMt//kFaWho1a9U2ONfc3ALHGq8/dXZjnQPxFo6s4tU2q2qYmJgY7SHkTiF6gJmQhZ+fH7a2tsyaNQtra2tu3LhBeHjm/uuwsDDq1KnDW2+9hYWFBadOneKDDz5Ap9PRpUuXx3pXr15N3bp1mTNnDteuXWPu3LmULl2aiRMn0qJFC4YNG8bSpUv58ssvsbGxweIfn8zmFVFRUdja2WVrt7W1e9gfaTRelbL+m73z583R38PG1NQUr1atmTxl2nNlyg1jnwOVvSplVdGbE9u2/khkRATDR45+rvNVmwPxqpU1L7w3rl8jLT2dsaOH06VLd0aPmcCJ48f47r/fEh8fz5x5C7hzJwoAOzv77NexsyPk5Ml8ySre/PeqlFW82jkFIb+Qok0hIyYmhtDQUKZMmaJf6dLwkRUDHTp00P9Zp9NRv359IiIiWLNmzROLNnZ2dsyfPx+AZs2aceHCBXbt2sXEiRMpVaoUFStWBKBWrVqUKlUqr9+anuTkpBwLQpaWlpn9SUlG41Up67/Z289nAK3btCUqMpJdu3aQnpFBamrqc2XSOqt488cp3ty5euVvZn88AxdXN9548/E/N3JDtTkQr1pZ88L74MEDkhIT6dGzN++9/wEAXq3bkJqawrq1axg2crTe8c/tgwCWFpYkJT9ddmOdA/Hmr1O82nrz62ekIGiBFG0KGSVLlqRcuXIsWLCA2NhYGjVqRJkyZfT9sbGxBAYGsnfvXiIiIkhPTwegRIkST3Q3btzY4HW1atXYtm1bnuZ/GiwtrUhJScnWnrVc2fI57z2ihVelrP9mb5Wq1ahStRoAnd7szNDBgxg1wo/V36/Ns+Waxj4HKntVyqqi91HuREUxcvhQrK1t+HThZ5iZmT2XR7U5EK9aWfPCm9Xftn1Hg/Z2HTqxbu0azp4+jVWRzDGpOV0nJRkry6fLbqxzIN78dYpXW29+/IxUAdmEpCZyT5tChomJCcHBwVStWpUZM2bQvHlzunbtyvHjxwHw9/dn69atDBo0iODgYNatW0e3bt1y/EvsnxQrVszgtbm5+VOdl9fY2dlxJyoqW/vjlikXlFelrOL9P61be/P7+XNcv3b1uc7PCdXmQCWvSllV9GYRHx/PcL/BxMfF83nQl9jbv/LcLtXmQLxqZc0Lb1Z/6dKlDdqzVhLHxcU+dlvFnago7OyfLruxzoF489cpXm29Wv+MFAQtkaJNIaRKlSosWrSIY8eO8e2332JhYYGfnx/3799n//79DBs2DB8fHxo1aoSTkxM6na6gIz8TjjVqcP36NRISEgzaz509A0CNGq8bjVelrOL9P8kPl7THxyc8YeTTo9ocqORVKauKXsj8JHL0CD+uX79G4OdfUO21157bpWVW8WrnVSlrXnhr1qwFQGRkhEF7VoGmZKlSvFbdgZdeeokLv583GJOamsIfly7i6FgjX7KKN/+9KmUVr7ZZBSE/kKJNIcbc3Bx3d3eGDBlCQkICN2/eJCMjA3Nzc/2YhIQE9u3bl2fXAzRffdOqTVvS09NZv3aNvi0lJYXNGzfg5OxCmbJljcarUtZ/ozc6OjpbW2pqKlt+3IyVlRXVqlV7rlxaZBVv4ciqojc9PZ1JE8Zy9sxpPl3wGS6ubs/lyY+s4tXOq1LWvPC2adsOgI0b1hm0b1i/jpdeeol69d2xsbGhQcNGbN/6I/fv//9/BLf+uJkHDx7Q2rttvmQVb/57VcoqXm2zqkZBPyFKnh71fMg9bQoZly5d4j//+Q/t27enQoUKJCQkEBQURLly5ahevTpOTk4sX76cUqVK8dJLL7Fs2TKsra2JiYl54Wtn/Q/u6tWradWqFVZWVjg6Or6w9584O7vQxrstiwIWEBMdTYWKldiyeSNhYbf4aOYso/KqlPXf6J05fRr3ExKoW68+9vavcOdOFNu3beHqlStMeNefoi+/DEBY2C22/rgZQP+J6rIvPgeg7Kuv0umNzppnFW/hyKqid/7cOez/eR/NW7QkNvYeW7dsNujv2OlNo8kqXu28KmXNC2+N12vSuUs3Nm1cT3paOnXr1+fE8WP8tGsng94Zqt8eOHL0OAb0643vQB+6de9JREQ43678mkaNPWji0UzpORBv4cgqXm2zCkJ+YKJTbW+M8Fiio6OZM2cOISEhREREYGNjQ7169Rg/fjyVK1fm+vXrTJs2jTNnzlCiRAl8fHx48OABX331FSEhIQAcPXqU/v37s27dOpycnABwdHRk0qRJ+Pr66q+1YsUKZs+ezR9//KFvW7x4MWvXriUyMpKyZcs+9yqepLTH9ycnJ7MkMIBtW7YQFxdLdQdHRowaQxOPps91PS29KmX9t3l3bN/Gpg3ruPznn8TG3qNo0ZepWasWb/XpRwtPL/2448eO8s7b/XN01KvvTvCKbzXPKt7Ck1U1r+9AH04cP5Zr/5nf/8i173GoNAfiVS/ri3izfjNOTU0leHkQmzdtICoykrKvvkqvt/rQz2egwfiQUycIWPAply5eoOjLL9PGux2jx47n5ZetDcY97oNkY5sD8RaurOJ9MadVIVrmsO7M7YKOkCvdXf4dq52eBynaCEbJk4o2giAIgiAIWqDVb8ay+l8Q1KQwFW02GHHRpqsUbXJF7mkjCIIgCIIgCIIgCIJghEjRRhAEQRAEQRAEQRAEwQgpRIu9BEEQBEEQBEEQBEHICXlKk5rIShtBEARBEARBEARBEAQjRIo2giAIgiAIgiAIgiAIRohsjxIEQRAEQRCEhyQka/MIS5vC9AgaQRCURDZHqYmstBEEQRAEQRAEQRAEQTBCpGgjCIIgCIIgCIIgCIJghEjR5l9OaGgogYGBREREFHSUZyIlJYWF8+fRqoUH7nWc6du7B4cPHTRKr0pZxateVvGql1W86mUVr3pZn8d78cLvjB7hR7uWjfBqXBefnm+y9rtV+v601FS+WvY5Pd7wpmVDV3q84c2KL78gLS37dqqbN67z4eSJdGnniVfjuvTp2pEvPl9MYmKiUc+BeAtnVvFqm1UlTEyM9xByR4o2/3Ju3brF4sWLiYyMLOgoz8TU9/1Z9c0K2nfsxCT/KZiZmTFy2BBOnTxhdF6VsopXvaziVS+reNXLKl71sj6r99DB3/Dp04uYmBgGvuPHmIn+NPZoTlRkuH7MjKn+fL3sc+rWa8CYiZNxdavLl0sDmT9npoErIvw2g/v35vdzZ+ja8y1GT3yP2s4uLF0SiP+74412DsRb8E7xauvVKqsgaI5O+Fdz5MgRnYODg+7s2bMFHcWAxNTcj2Mnz+gcHBx0Xyz7Ut92LyFJ5+XVStejZ6/HnpvfXpWyile9rOJVL6t41csqXvWyPqs36m68rlGjxjq/4SN095PTdZHxqdmOA0dO6RwcHHSfzF1g0D5txic6R0dH3aFT5/Vtn362ROfg4KA7cvqiwdgJEyfpHBwcdBF37hndHIi34J3iNd6vWWFi09nbRnsIuSMrbRTn8uXLDB48mAYNGuDi4oK3tzfLly8HICQkBD8/Pzw8PHB1deXNN99k06ZN+nOPHj1K//79AejevTuOjo44OjoC8ODBA2bMmIG3tzcuLi54enoybdo04uPjDa7v6enJjBkzWL16NS1btqRu3boMHz6cmJgYzd7znt07MTMzo1uPXvo2S0tLunTrzpnTIYTfvm00XpWyile9rOJVL6t41csqXvWyPqt3+7YtREffYdTocZiampKY+ICMjAwD35mQkwB4ebczaG/l3Q6dTsfe3Tv1bfcTEgAoVaq0wVhbOztMTU15ydz8ubM+C+LVzqtSVvFqm1U1TDEx2kPIHSnaKI6fnx9xcXHMmjWLoKAgfH199fulw8LCqFOnDrNmzWLp0qW0adOGDz74gI0bNwJQq1Ytpk2bBsDs2bNZs2YNa9asASApKYn09HTGjRvH8uXLGTNmDMePH2f48OHZMuzbt499+/Yxbdo0pkyZwvHjx5k5c2a2cXnFpUsXqVSpMtbW1gbttZ2c9f3G4lUpq3jVyype9bKKV72s4lUv67N6jx4+jLW1NZGREbzRwZvWHvXxbubOp5/MIDk5GYDUlFQALC2tDHyWVpmv/7j4u77NrV59AObMnMrlPy4SEX6bvbt3sHbNd/Tp60PRokWNbg7EW/BO8Wrr1SqrIOQHLxV0AOH5iYmJITQ0lClTpuDp6QlAw4YN9f0dOnTQ/1mn01G/fn0iIiJYs2YNXbp0wdramtdeew2A6tWr4+TkpB9fqlQppk+frn+dlpZG+fLl6dOnD1evXqVKlSoG7qVLl2JhYQFk3icnKCiIjIwMTE3zvi4YFRWFrZ1dtnZbW7uH/c93fx4tvCplFa92TvFq61Upq3i1c4pXW69KWZ/Ve+P6NdLS0xkzajhdunZnyIixhJw4zro1q4lPiGP6J59SsXJlAM6dCeHVcuX1554JOQXAnUfuDdiwcVPeGTaKb79azm8Hfta3Dx7ix8gx414o67MgXu28KmUVr3ZOQcgvpGijMCVLlqRcuXIsWLCA2NhYGjVqRJkyZfT9sbGxBAYGsnfvXiIiIkhPTwegRIkST+XftGkTK1as4Pr16zx48EDffu3aNYOiTf369fUFG4Bq1aqRmppKdHQ0djn85fiiJCcnGVwvC0tLy8z+pCSj8aqUVbzaOcWrrVelrOLVzilebb0qZX1W74PEByQlJtKjV2/83/+A+KQ0mnu2JjUtlc3rf+Adv1E0bNKMMmVfZUnAPKysrHB8vRa/nzvL8iWfYWb2EsnJhjnLvloOlzp1aeHZmuIlSnDot1/4cnkQpW3teKtvP6ObA/EWvFO82nq1yqoa8pQmNZGijcKYmJgQHBzMwoULmTFjBg8ePKBWrVpMnjyZ+vXr4+/vT0hICCNGjOC1117D2tqa7777jh07djzR/dNPP/Hee+/Rq1cvxo0bR4kSJYiKimLEiBH6pcJZFCtWzOB11l+I/xyXV1haWpGSkpKtPet6WUuVjcGrUlbxaucUr7ZelbKKVzuneLX1qpT1Wb1ZW57ate9oMLZ12w5sXv8D58+epl3HN5n72VKm+Y9nyrtjgczfd4aNnsA3Xy2jyCNbnvbs2s7cjz/iu43bsH8l88O05p6tMTOBgIWf0q5DB0qUKPlcWZ8F8WrnVSmreLVzCkJ+Ife0UZwqVaqwaNEijh07xrfffouFhQV+fn7cv3+f/fv3M2zYMHx8fGjUqBFOTk7odLqn8u7cuZPXX3+dGTNm0Lx5c1xcXLIVZwoKOzs77kRFZWu/cyfqYb+90XhVyipe7Zzi1darUlbxaucUr7ZelbI+q9fOPvPPpUsb3ji4ZMlSAMTHxQFQtdprfPvDZr75YTNLvvyGTTt/5o0u3Ym9d5cKFSvrz9u49nscatTQF2yyaNHSk6TERC5dNLx3hjHMgXgL3ilebb1aZRWE/ECKNoUEc3Nz3N3dGTJkCAkJCdy8eZOMjAzMH3lCQUJCAvv27ct2HmRfFZOUlGRwLsCWLVs0Sv9sONaowfXr10h4+HSGLM6dPQNAjRqvG41XpaziVS+reNXLKl71sopXvazP6q1ZsxYAERERBmPvPLzHRYmS/18VY2JiQtVqr+HiVpdixUtw6sQxMjIyqNfg//cUjImJJj3d8OlTAGlpmTczTk9Le+6sz4J4tfOqlFW82mZVDRMj/kfIHSnaKMylS5d4++23Wbt2LUeOHGHPnj0sXbqUcuXK6W8svHz5cnbu3MmePXsYNGhQtjumV65cGTMzM9avX8/p06c5d+4cAI0bN+bs2bMsWbKEQ4cOMXv2bA4fPlwQbzMbrdq0JT09nfVr1+jbUlJS2LxxA07OLpQpW9ZovCplFa96WcWrXlbxqpdVvOplfVZvm7btANi0YZ2BY8um9ZiZvUSdeu45XiM5KYnlSwMpbWtHa+//P/yhQsVKXP7jIjeuXzMYv2P7NkxNTanu6PjcWZ8F8WrnVSmreLXNKgj5gdzTRmHs7OywtbUlKCiIiIgIbGxsqFevHvPmzcPMzIz58+czbdo0/P39KVGiBD4+Pjx48ICvvvpK7yhVqhTTpk3jyy+/5McffyQtLY0//viD3r17ExoayqpVqwgODsbDw4P58+fTs2fPAnzHmTg7u9DGuy2LAhYQEx1NhYqV2LJ5I2Fht/ho5iyj8qqUVbzqZRWvelnFq15W8aqX9Vm9r79ek85du7Fpw3rS0tOp7VKXkJPH+XnPLnzeHoztw20TU98bj62dHZWrVuN+wn22/7iBsFuhzP1sKUVfflnv69N/EEcP/caId/rTredbFCtegkO/HeDIwV/p2q0H9vavGN0ciLfgneLV1qtVVkHID0x0T3uTE0HIR5LSHt+fnJzMksAAtm3ZQlxcLNUdHBkxagxNPJq+0HW18KqUVbzqZRWvelnFq15W8aqX9Vm9qampBC8PYvPGDURGRlCm7Kt07fkWPfv0149ZvTKY7T9u4vbtW1haWuLiVhffoSOo7ph9W8WF82f5atnnXL50kdjYe5QtV57OnbswcNA7vPRS9s9MjWEOxFvwTvFq631ep1UhWuaw7bzxPtq8Q225r1BuSNFGMEqeVLQRBEEQBEHQgniNfgmxKUz/5ycI/yIK03+623833qJN+1pStMkNuaeNIAiCIAiCIAiCIAiCESJFG0EQBEEQBEEQBEEQBCOkEC32EgRBEARBEARBEAQhJ0zl0dpKIittBEEQBEEQBEEQBEEQjBBZaSMIgiAIgiAID5EbBguCIAjGhPxUEgRBEARBEARBEIRCjonsjlIS2R4lCIIgCIIgCIIgCIJghEjRphBSr149AgMD8+16gYGBuLm56V8fPXoUR0dHzp07p9k1U1JSWDh/Hq1aeOBex5m+vXtw+NBBo/SqlFW86mUVr3pZVfRev36NSRPH0dqzGQ3quvBmx7Z88fliEhMTjS6reLXzqpRVNa9KWcWrXlbxaptVELRGijbCC9OjRw9WrlyZr9ec+r4/q75ZQfuOnZjkPwUzMzNGDhvCqZMnjM6rUlbxqpdVvOplVc0bfvs2fXv34NyZM/R+qx/vvvc+zi5uLF0SiP+7440qq3i19aqUVTWvSlnFq15W8WqbVSVMTIz3EB6DTih01K1bV7do0aICu/6RI0d0Dg4OurNnzz63IzE19+PYyTM6BwcH3RfLvtS33UtI0nl5tdL16Nnrsefmt1elrOJVL6t41cuqojdwyVKdg4OD7tzFPw3aJ0ycpHNwcNBF3LlnNFnFq51XpayqeVXKKl71sor3xZ2FiV0XIo32EHJHVtpowOXLlxk8eDANGjTAxcUFb29vli9fru8PCQmhf//+uLq6UrduXSZMmEB0dLS+PzQ0FEdHRzZv3syMGTOoX78+Hh4e/Oc//yEtLc3gWnv27KFt27Y4OTnRvXt3zp49my2Pj48PQ4cOZevWrbRp0wYXFxf8/PyIjY3l1q1b+Pr64ubmRocOHTh69KjBuZs2beKtt97C3d2d+vXr4+Pjk+0a/9wepTV7du/EzMyMbj166dssLS3p0q07Z06HEH77ttF4VcoqXvWyile9rCp6ExISAChdurRBu62dHaamprxkbm40WcWrnVelrKp5VcoqXvWyilfbrIKQH0jRRgP8/PyIi4tj1qxZBAUF4evrq9/3HxISgo+PDzY2NixcuJCZM2dy7tw5hg8fns0TEBCAqakpAQEB9O7dm6+++oq1a9fq+y9evMjo0aOpXLkyixcvpkuXLowdO5aUlJRsrgsXLvDNN98wadIkpk+fzokTJ5g6dSqjR4+mRYsWBAYGUqpUKUaNGsX9+/f154WGhtK5c2c+++wzPv30U8qWLUvfvn25evWqBjP3dFy6dJFKlSpjbW1t0F7byVnfbyxelbKKV72s4lUvq4re+vXdAfho6hQuXbxI+O3b7NyxnbVrvqNPXx+KFi1qNFnFq51XpayqeVXKKl71sopX26yqYWLE/wi5I4/8zmNiYmIIDQ1lypQpeHp6AtCwYUN9//z586lduzaLFy/G5OHmPQcHBzp27MiBAwdo3ry5fqyzszMffPABAE2aNOHo0aPs2rWLt956C4Bly5ZRtmxZlixZgpmZGZBZMZ4yZUq2XAkJCXzxxReUKlUKgD/++IOvvvqKjz76SO+zt7enU6dOHD58mFatWgEwcuRIvSMjI4MmTZpw9uxZNm7cyPjxz38vgxchKioKWzu7bO22tnYP+yONxqtSVvFq5xSvtl6VsqrobdK0GSNGjSF4eRD7f96nbx88xI+RY8YZVVbxaudVKatqXpWyilc7p3i19WqVVRDyAyna5DElS5akXLlyLFiwgNjYWBo1akSZMmUASExM5NSpU0yaNIn09HT9OZUrV6Zs2bKcO3fOoGjj4eFh4K5WrRpHjhzRvz5z5gyenp76gg1A27Ztcyza1KhRQ1+wybomQOPGjbO1hYeH69v+/vtvFixYQEhIiMEWrmvXrj3NdGhCcnISFhYW2dotLS0z+5OSjMarUlbxaucUr7ZelbKq6AV4tVw56tStR6vW3hQvUYJff9nPl8uDKG1rx1t9+xlNVvFq51Upq2pelbKKVzuneLX1avkzUhC0Roo2eYyJiQnBwcEsXLiQGTNm8ODBA2rVqsXkyZOpWLEi6enpzJ49m9mzZ2c79/Y/9lLa2NgYvDY3NzfY+hQVFZXtHgPW1tb6v3wepVixYtlc/7xG1l9kycnJQObqnEGDBlGqVCn8/f159dVXsbS05IMPPtCPKQgsLa1y3AKWlcnSyspovCplFa92TvFq61Upq4reHdu3MfOjafy4bRevPPwQolXrNmRk6AhY+CntOnSgRImSRpFVvNp5VcqqmlelrOLVzilebb1aZVUNU9mFpCRStNGAKlWqsGjRIlJTUwkJCWHBggX4+fmxf/9+TExMGDp0qH770aOULPlsv/Ta2dkZrH6BzEJLXhVUTp8+TXh4OEFBQdSoUUPfHh8fr189VBDY2dkRGRGRrf3OnaiH/fZG41Upq3i1c4pXW69KWVX0/vD9f6lR43V9wSaLFi09+XHTBi5dvEjDRo1zOTt/s4pXO69KWVXzqpRVvNo5xautV6usgpAfyI2INcTc3Bx3d3eGDBlCQkICd+7cwdXVlStXruDk5JTtKF++/DP5nZ2d+fnnnw22Wu3cuTPP8ic9XCZo/siTQU6dOsWtW7fy7BrPg2ONGly/fk3/RJMszp09A0CNGq8bjVelrOJVL6t41cuqojc6+g7pGRnZ2tPSUgFI/8dTDZ8G1eZAvGplVc2rUlbxqpdVvNpmFYT8QIo2ecylS5d4++23Wbt2LUeOHGHPnj0sXbqUcuXKUbFiRSZNmsT+/fsZO3YsP/30E0ePHmXz5s2899572R63/SSGDBnC7du3GTFiBAcOHGD16tV8/vnnOW6Peh5cXV0pWrQo06dP57fffmP9+vWMHz+eV155JU/8z0urNm1JT09n/do1+raUlBQ2b9yAk7MLZcqWNRqvSlnFq15W8aqXVUVvpUpVuHTxAteuGT41cMf2bZiamlLd0dFosopXO69KWVXzqpRVvOplFa+2WVWjoJ8QJU+Pej5ke1QeY2dnh62tLUFBQURERGBjY0O9evWYN28eZmZm1KlTh//+978EBgYyefJkUlNTKVOmDA0bNqRSpUrPdK2aNWvqH8U9cuRIqlevzsKFC/H19c2T92Jra8tnn33G3LlzGT58OJUrV2b69Ol8+eWXeeJ/XpydXWjj3ZZFAQuIiY6mQsVKbNm8kbCwW3w0c5ZReVXKKl71sopXvawqegcO8uXgb7/wdv++9H6rLyVKlOCXA/v57ddf6NqtB/b2z17IV20OxKtWVtW8KmUVr3pZxattVkHID0x0Op2uoEMIwj9JesJq++TkZJYEBrBtyxbi4mKp7uDIiFFjaOLR9IWuq4VXpaziVS+reNXLqqL33NmzfPF5IJcuXuTevXuUK1+ON97swsBB7/DSS8/3+Y9qcyBetbKq5lUpq3jVyyreF3NaFaJlDvsuRT95UAHhWaP0kwf9S5GijWCUPKloIwiCIAiCIAiCoDWFqWjz8x/GW7Rp6ShFm9yQe9oIgiAIgiAIgiAIgiAYIVK0EQRBEARBEARBEARBMEIK0WIvQRAEQRAEQRAEQRByQp7SpCay0kYQBEEQBEEQBEEQBMEIkaKNIAiCIAiCIAiCIAiCESLbowRBEARBEARBURJT0vPcWcTCLM+dgiAUPKayO0pJZKWNIAiCIAiCIAiCIAiCESJFG0FJUlJSWDh/Hq1aeOBex5m+vXtw+NBBo/SqlFW86mUVr3pZxateVvGql1U177M4jx87ikstR/3R0K2m/jh/9kyO58THx9HO04OGbjXZ99OuHK+/+LP5dGzdnOYN3Z74nlSaW628KmUVr7ZZBUFrpGgj5Dlz587Fw8ODGjVqMGvWLE2uMfV9f1Z9s4L2HTsxyX8KZmZmjBw2hFMnTxidV6Ws4lUvq3jVyype9bKKV72sqnmfx9mnnw+z5szlw4/n6I/yFSrmOHbZ54EkJSXm6po57X2+W7US7/YdGffu5CdeX6W51cqrUlbxaptVJUyM+B/hMegEIQ85ePCgzsHBQff111/rTp06pQsNDX0uT2Jq7sexk2d0Dg4Oui+Wfalvu5eQpPPyaqXr0bPXY8/Nb69KWcWrXlbxqpdVvOplFa96WVXzPqvzl4NHdA4ODroft+7QJabqdDH30x57HD9zUfd6zZq6TxcG6hwcHHTrNm0z6P/16Cmdg4ODLnDpMn3b466v0tway9dMvAXvfRFnYeKXP2KM9hByR1baCHlCUlISAFeuXAGgf//+uLm5Ua5cuTy/1p7dOzEzM6Nbj176NktLS7p0686Z0yGE375tNF6VsopXvaziVS+reNXLKl71sqrmfRHn/fsJpKWlPda/cN4ntGjphUudujn279uzGzMzMzp37flU11dpbrXyqpRVvNpmFYT8QIo2inL58mUGDx5MgwYNcHFxwdvbm+XLlwPg7+9Px44dOXToEJ06dcLZ2Zl+/foRGhrKvXv3GDNmDHXq1KFVq1Zs377dwOvp6cmMGTMM2vbs2YOjoyOhoaEAhIaG4ujoyIYNG/jggw9o0KABPXr0wMfHh5kzZwLw+uuv4+joyNGjR/P8vV+6dJFKlSpjbW1t0F7byVnfbyxelbKKV72s4lUvq3jVyype9bKq5n1e57QPJtPYvS7NG7oxfPBALv5+PtuYvT/t5NyZ04wYOzHX6/956SIVKlbi5ae8vkpzq5VXpazi1TarapiYGO8h5I488ltR/Pz8sLW1ZdasWVhbW3Pjxg3Cw8P1/VFRUcyZM4dhw4bx0ksv8fHHHzNx4kSKFClCvXr16NmzJz/88APvvvsuLi4uz7UiZsGCBTRv3pz58+eTkZHBq6++yg8//MDKlStZs2YNAK+99lqevecsoqKisLWzy9Zua2v3sD/SaLwqZRWvdk7xautVKat4tXOKV1uvSllV8z6r09zcnFatvfFo1oySJUryx5+XWf3t1/j5+rBsxWoca9QEMldBBy6YR+++/Xn11XLcDruV4/Wj7zzb9VWaW628KmUVr3ZOQcgvpGijIDExMYSGhjJlyhQ8PT0BaNiwocGY2NhYVq1aRfXq1QGIjIxk5syZDB48mBEjRgDg5OTETz/9xJ49exgwYMAz58jpRsOvvvoqAK6urs/se1qSk5OwsLDI1m5paZnZ/3CrljF4VcoqXu2c4tXWq1JW8WrnFK+2XpWyquZ9VqerWx1c3eroXzfwaEHLVm3o16sLSwMDCFiyDIBvv15OWloaA3yHPOH6yZibP/31VZpbrbwqZRWvdk5ByC9ke5SClCxZknLlyrFgwQI2btxosMImC3t7e33BBqBy5coANG7cWN9WrFgxSpUqleP5T0OLFi2e67wXxdLSipSUlGztycnJmf1WVkbjVSmreLVzildbr0pZxaudU7zaelXKqpo3L5wVKlaiWXNPTh4/Snp6OmFht1j1zdf4jRxD0aIvP+H6lqSmPv31VZpbrbwqZRWvdk4VMTHiQ8gdKdooiImJCcHBwVStWpUZM2bQvHlzunbtyvHjx/VjihUrZnCOubk5ADY2NgbtFhYW+r+snpXSpUs/13kvip2dHXeiorK137kT9bDf3mi8KmUVr3ZO8WrrVSmreLVzildbr0pZVfPmldO+TBlSU1NJSkxk+eeB2NnZU6eeO2FhtwgLu0XMnTsA3L17l7CwW2RkZABQ2vbZrq/S3GrlVSmreLVzCkJ+IUUbRalSpQqLFi3i2LFjfPvtt1hYWODn58f9+/dfyGthYUFqaqpBW2xsbI5jTQrojlGONWpw/fo1EhISDNrPnT0DQI0arxuNV6Ws4lUvq3jVyype9bKKV72sqnnzyhkWGoqlpSVFihYlPPw2oTdv0LVjG7p2aE3XDq2ZOjnzZsTzZs+ga4fW3L+feT0HxxrcvHGd+095fZXmViuvSlnFq21WQcgPpGijOObm5ri7uzNkyBASEhKIjHyxm2iVKVOGv//+26Dt4MGDL+TMa1q1aUt6ejrr167Rt6WkpLB54wacnF0oU7as0XhVyipe9bKKV72s4lUvq3jVy6qa91mdMTEx2RyX/7jErwf24d6wMaampgwdMZr/LFhkcAwZPhqAfgN9+c+CRRSxKgJAy1ZtSE9PZ9OGH57q+irNrVZelbKKV9usqmFqYmK0h5A7ciNiBbl06RL/+c9/aN++PRUqVCAhIYGgoCDKlStHxYoVX8jt7e3NRx99xOLFi3Fzc+PAgQOcPn06b4LnEc7OLrTxbsuigAXEREdToWIltmzeSFjYLT6aOevJgnz0qpRVvOplFa96WcWrXlbxqpdVNe+zOidNGIuVlRUurm6UKlWaPy9fZtP6tVhZFWH46PEAuLrVzXaetU3m1vmaNWvTvGUrfXttJxe8WnvzeWAAMTExVKhQkZ1bN+d6fZXmViuvSlnFq21WQcgPTHQ6na6gQwjPRnR0NHPmzCEkJISIiAhsbGyoV68e48ePp3Llyvj7+3P+/Hm2bt2qP+fo0aP079+fdevW4eTkpG/39PSkRYsWTJs2DYC0tDTmz5/Pjz/+SHJyMu3bt8fd3Z0JEyawd+9eypcvT2hoKF5eXnz22We0bdvWINuKFSuYPXs2f/zxxwu9x6S0x/cnJyezJDCAbVu2EBcXS3UHR0aMGkMTj6YvdF0tvCplFa96WcWrXlbxqpdVvOplVc37LM7Vq75h+9Yt3Lxxg/v3EyhRoiT1GjTEd8hwKlSslOs1Tp44xojBA/lk7kI8W3tnu/6yzxexc/sW4uPinvieVJpbrbwqZRXvizmtCtEyh8N/3SvoCLnS6LUSBR3BaJGijWCUPKloIwiCIAiCIEBiSnqeO4tYmOW5UxBUpTAVbY4YcdGmoRRtckXuaSMIgiAIgiAIgiAIgmCESNFGEARBEARBEARBEATBCJGijSAIgiAIgiAIgiAIghFSiHboCYIgCIIgCIIgCIKQI/JkbSWRlTaCIAiCIAiCIAiCIAhGiKy0EQRBEARBEARFkSc9CYIgFG6kaCMIgiAIgiAIgiAIhRwT2R+lJLI9SlCSlJQUFs6fR6sWHrjXcaZv7x4cPnTQKL0qZRWvelnFq15WlbzLg5biUsuRrm92NGj/ctkX9HurJy08GlLfzYlO7dowd/YsYmJiCiyreLX3qpRVNa9KWcWrXlbxaptVELRGijZGRFxcHIGBgfz111/Pdf6GDRvYsmXLU7fnFZ6ensyYMUMzf05Mfd+fVd+soH3HTkzyn4KZmRkjhw3h1MkTRudVKat41csqXvWyquKNCA/ny+VBFClSNFvfhd9/x7FGDd4Z4sfkD6bRwtOLzZs2MKBvbx48eJDvWcWbP16VsqrmVSmreNXLKl5tswqC5ugEo+HmzZs6BwcH3Y4dO57r/H79+umGDBny1O15RcuWLXXTp0/PU2diau7HsZNndA4ODrovln2pb7uXkKTz8mql69Gz12PPzW+vSlnFq15W8aqXVSXvqDFjdf18+uv69O2na9e+wxPHb9m2U+fg4KDbsHlroZkD8aqZVTWvSlnFq15W8b64szBx9O97RnsIuSMrbQTl2LN7J2ZmZnTr0UvfZmlpSZdu3TlzOoTw27eNxqtSVvGql1W86mVVxXvyxHH27N7FJP/3n/qcV8uVAyA+Pi5fs4o3f7wqZVXNq1JW8aqXVbzaZhWE/MCoizaXL19m8ODBNGjQABcXF7y9vVm+fDkA/v7+dOzYkaNHj9K5c2dcXV3p3r0758+fN3A4OjqybNkyFi5cSKNGjahXrx5z585Fp9Nx+PBh3nzzTdzc3BgwYAC3H/mPNTQ0FEdHRzZu3Mj7779P3bp1cXd3Z/bs2aSlpRlc48SJE3Tu3BknJyc6derEwYMHefPNN/H39zcYFxISQv/+/XF1daVu3bpMmDCB6Oho/fW8vLwAGDNmDI6Ojjg6OhIaGgrAp59+SqdOnXBzc6Np06aMHz+eyMhIvdvHx4djx46xf/9+/bmBgYG5tgPs37+ft99+m0aNGlGnTh169OjBL7/8ku3rEBERwaRJk2jcuDHOzs60bduWlStX5vp1u3v3Lt26daNr167PdH+Dp+XSpYtUqlQZa2trg/baTs76fmPxqpRVvOplFa96WVXwpqenM2fWTLp06051B8dcx+l0Ou7ejeFOVBSnTp7gP598jJmZGfXru+dbVvHmn1elrKp5VcoqXvWyilfbrIKQHxj106P8/PywtbVl1qxZWFtbc+PGDcLDw/X9UVFRfPzxxwwZMgQbGxvmz5/PyJEj+emnnzA3N9ePW716Ne7u7sydO5czZ84QGBhIRkYGBw8eZNiwYZibm/Pxxx8zZcoUvvrqK4MMCxYswMPDg4CAAC5cuMCiRYswNzdn4sSJAERGRjJ48GBq1qxJQEAA8fHxfPTRR8THx/P666/rPSEhIfj4+NC8eXMWLlxIYmIiAQEBDB8+nDVr1mBvb8/ixYsZOXIk48ePp0GDBgDY29sDEB0dzdChQ7G3tycmJoavv/4aHx8ftm3bxksvvcSHH37Iu+++i5WVFe+99x4AZcqUoV27djm2Q2ahqGXLlgwaNAhTU1N++eUXhgwZwsqVK/XXv3v3Lr16ZVakx40bR/ny5bl+/To3btzI8WsWFRXFoEGDsLa2ZtmyZdjY2DznVz93oqKisLWzy9Zua2v3sD8yW19BeVXKKl7tnOLV1qtSVhW8a9d8z+3bYQQFr3jsuOg7d/Bq4aF//UqZMsye+ylVqlbLt6zizT+vSllV86qUVbzaOcWrrVerrKohz45SE6Mt2sTExBAaGsqUKVPw9PQEoGHDhgZjYmNjWbVqFdWrVwegSJEi9O/fnzNnzlCvXj39OHt7e+bNmwdA06ZN2bdvHytWrGDbtm1Uq5b5y2VERAQzZ84kLi6OYsWK6c+tWLEis2fP1p+blJTE119/zeDBgylevDgrVqzAzMyMoKAgfeW2fPny9O3b1yDr/PnzqV27NosXL8bEJPM/FwcHBzp27MiBAwdo3ry5vshTqVIlXF1dDc7PygCZn4K6ubnRrFkzjhw5goeHB6+99hrW1tYULVo027m5tffr10//54yMDBo0aMBff/3FDz/8oC/arFixgujoaHbs2EH58uUBaNSoETkRFhbGwIEDKVeuHEuWLKFo0ew3r8wLkpOTsLCwyNZuaWmZ2Z+UZDRelbKKVzuneLX1qpTV2L337t3l88WLGOw3nFKlSj12bPHixQn68muSk5O5dPECe/f89NQ3ITbmORBv/jnFq51TvNp6VcoqXu2cgpBfGG3RpmTJkpQrV44FCxYQGxtLo0aN9CtEsrC3t9cXbABee+01ILMA8yiNGzc2eF2lShXu3LmjL9gAVK5cGYDw8HCDok3r1q0NzvX29ubzzz/nzz//pH79+pw7d44GDRoYLLWrV68eJUqU0L9OTEzk1KlTTJo0ifT0dINrli1blnPnztG8efPHzseBAwdYunQply9fJiEhQd9+7do1PDw8HnNm7oSHh7Nw4UIOHTpEVFQUOp0OgFq1aunHHD58mIYNG+oLNrlx48YN+vbtS40aNfjss89y/Esxr7C0tCIlJSVbe3Jycma/lZXReFXKKl7tnOLV1qtSVmP3Ll4UQPHixenTp98Tx5pbWNCwUebP1+YtWtKgYSMG9HuLUqVK07xFS82zijd/vSplVc2rUlbxaucUr7ZerbIKQn5gtPe0MTExITg4mKpVqzJjxgyaN29O165dOX78uH7Mo8UVQL8lKus/vseNe9pz//lJo62tLZC5xC7r3zl9GvloW1xcHOnp6cyePZtatWoZHGFhYQb30smJs2fPMnz4cOzt7Zk7dy5r1qzhhx9+yDHv05KRkcGwYcM4efIko0eP5ptvvmHdunU0a9bM4C+0e/fu6bdoPY5z584RFhZGt27dNC3YANjZ2XHn4fw/yp07UQ/7n5w3v7wqZRWvdk7xautVKasxe69fv8b6tT/wVj8fIqMiuXUrlFu3QklOTiYtLZVbt0KJvXcv1/Nd3epgZ2fH9q1bNM8q3vz3qpRVNa9KWcWrnVO82nq1yqocJkZ8CLlitEUbyFwRs2jRIo4dO8a3336LhYUFfn5+3L9/P98y/PNGunfu3AEy/8PP+ndON9t9tM3GxgYTExP8/PxYt25dtmPYsGGPzbBnzx6sra0JCAjAy8sLV1dXffHoebl+/ToXLlzA39+fHj164O7ujpOTE0n/WBpYokQJgxse50aHDh3o378/48eP5/Dhwy+U7Uk41qjB9evXDFYcAZw7ewaAGjVez+m0AvGqlFW86mUVr3pZjdkbGRFBRkYG//nkY9q38dIf586e4fq1a7Rv40XQ0iWPdSQnp5CQEK95VvHmv1elrKp5VcoqXvWyilfbrIKQHxh10SYLc3Nz3N3dGTJkCAkJCU9VRMgrfvrpJ4PXu3btokiRIjg4OADg5OTEkSNHDP4COHHiBPce+TQy634yV65cwcnJKduRtfUot9U+SUlJmJub6++FA7BlS/ZPMs3NzXNceZNTe9brR2/YfOvWLUJCQgzGNWrUiCNHjhAWFpbN+0+mTJlC586dGT58OCdPnnzi+OelVZu2pKens37tGn1bSkoKmzduwMnZhTJlyxqNV6Ws4lUvq3jVy2rM3teqV2fhoiXZjmqvVads2VdZuGgJXbp158GDByQmJmY7f8/uXcTFxVKzVm3Ns4o3/70qZVXNq1JW8aqXVbzaZhWE/MBo72lz6dIl/vOf/9C+fXsqVKhAQkICQUFBlCtXjooVK+Zbjhs3bjB58mTat2/PhQsXWLZsGQMGDKB48eIADBw4kO+++46hQ4fi6+tLXFwcS5YsoWTJkgZFlkmTJjFgwADGjh1Lhw4dKFasGOHh4Rw6dIiuXbvSoEED7OzsKFasGNu2baN8+fJYWFjg6OhIkyZNWLlyJTNnzqR169aEhISwefPmbFmrVq3Kpk2b2LdvH3Z2dtjb2/PKK6/k2F61alXKlCnD/PnzycjI4MGDByxatCjbVqiBAweyefNm+vXrx7Bhw6hQoQI3b97k2rVrvPvuu9kyTJ8+neTkZIYMGcLXX3+Ns7NzHn9FwNnZhTbebVkUsICY6GgqVKzEls0bCQu7xUczZxmVV6Ws4lUvq3jVy2rM3pIlS+Hp1Spb++pvVwLo+y5dvMjQdwbi3bY9latWxdTElN9/P8/2rT/yarly9PXpr3lW8ea/V6WsqnlVyipe9bKKV9usqmEi+5CUxESXdfdZIyM6Opo5c+YQEhJCREQENjY21KtXj/Hjx1O5cmX8/f05f/48W7du1Z8TFxdH/fr1mT17Nl27dgXA0dGRSZMm4evrqx+X07lHjx6lf//+rFu3DicnJ0JDQ/Hy8mL27NkcO3aM3bt3Y2ZmRufOnZk0aZLBCpUTJ07w8ccf89dff1GxYkUmTZrEjBkzaNWqFe+//75+3Llz5wgMDOTUqVOkpqZSpkwZGjZsyLBhw/Q3Wd6zZw8LFizg5s2bpKSksHfvXsqXL8/y5ctZtWoVsbGx1KlTh2nTpuHt7W3w3iIiIpg6dSohISHExcUxcuRIRo0alWv72bNnmTFjBn/++Sdly5Zl2LBhHDlyJNvc3L59m/nz5/Prr7+SmJhIuXLl6NOnDz4+PgB4enrSokULpk2bBmQ+3WrixIkcPHiQb775hho1ajzz1z8p7fH9ycnJLAkMYNuWLcTFxVLdwZERo8bQxKPpM19La69KWcWrXlbxqpdVNa/vQB/u3r3Lhs2ZPxfu3o0h8LMATp08TvjtcNLSUin7ajmaNWvOO0P9KFny8U+d0jKreLX1qpRVNa9KWcWrXlbxvpjTymiXOTw7J67GFXSEXKlXpdiTB/1LMdqiTUGTVbT57LPPaNu27TOde+3aNdq1a8cnn3xCly5dNEpYuHlS0UYQBEEQBEEQBEFrpGiTP0jRJncK0bdgwTF//nwcHR2xt7fn5s2bBAUFYWdnR5s2bQo6miAIgiAIgiAIgiBgIrujlESKNnlAamoqn376KXfu3MHKygp3d3cmTZrEyy+/XNDRBEEQBEEQBEEQBEFQFNkeJRglsj1KEARBEARBEISCpjBtjzp5zXi3R9WtLNujcqMQfQsKgiAIgiAIgiAIgpATsjtKTUwLOoAgCIIgCIIgCIIgCIKQHVlpIwiCIAj/cjI02iltKnc8FARBEARBeCGkaCMIgiAIgiAIgiAIhR35LEVJZHuUIAiCIAiCIAiCIAiCESJFG0FJUlJSWDh/Hq1aeOBex5m+vXtw+NBBo/SqlFW86mUVr3pZjdl74ffzjBj6Dh4N6tLEvQ7DBg/ij0sXs41LTU0l6PPFdGzbCnc3Jzq2bcXyoKWkpT39o/+MdQ7EWziyquZVKat41csqXm2zCoLWSNFGUJKp7/uz6psVtO/YiUn+UzAzM2PksCGcOnnC6LwqZRWvelnFq15WY/VevPA7g/r3JTT0JkOGjWCI3whu3LjOOwN9uHb1isHYD/wnEbR0CfXdG/Ku/xTq1K3H54GfMfvj6fmSVbwF41Upq2pelbKKV72s4tU2q0qYGPE/wmPQCYIRkpia+3Hs5Bmdg4OD7otlX+rb7iUk6by8Wul69Oz12HPz26tSVvGql1W86mU1Vu/9lAzdIN/Bunr16utuRUbr7qdk6O6nZOiu3QrXubq66vyGj9C3ZV1n3oIAfdv9lAzdzFmzdY6OjrqQcxf1bSrNgXgLT1bVvCplFa96WcX74s7CxKlrcUZ7CLkjK23+weXLlxk8eDANGjTAxcUFb29vli9fDoC/vz8dO3bk6NGjdO7cGVdXV7p378758+cNHI6OjixbtoyFCxfSqFEj6tWrx9y5c9HpdBw+fJg333wTNzc3BgwYwO3bt/XnhYaG4ujoyMaNG3n//fepW7cu7u7uzJ49O9uS8xMnTtC5c2ecnJzo1KkTBw8e5M0338Tf318/xsfHh6FDhxqcd/HiRRwdHTl69Ki+TafTERwcjLe3N7Vr18bLy4sVK1YYnBceHs6YMWNo3LgxTk5OeHp68sknnzx1f16yZ/dOzMzM6Najl77N0tKSLt26c+Z0COGPzGlBe1XKKl71sopXvazG7A05dYIGjRpRokRJfZudnT1169Xn1wP7efDgPgCnTmV+Iundrr3B+d7t2qPT6di9c7vmWcWb/16VsqrmVSmreNXLKl5tswpCfiBFm3/g5+dHXFwcs2bNIigoCF9fXxITE/X9UVFRfPzxx/j6+hIQEEBycjIjR44kNTXVwLN69WrCwsKYO3cuAwcOJDg4mP/85z988sknDB06lLlz53Lt2jWmTJmSLcOCBQvQ6XQEBATg6+vLqlWrCAgI0PdHRkYyePBgXn75Zf2Yjz76iIiIiOd6z7NmzWLRokV07tyZZcuW0aVLFz799FO+++47/ZhJkybxxx9/8MEHH/Dll18yevRoMjIynro/L7l06SKVKlXG2traoL22k7O+31i8KmUVr3pZxateVmP2pqSkYGlpma3dqkgRUlNT+evyZf04ACtLq2zjIHObldZZxZv/XpWyquZVKat41csqXm2zqoaJifEeQu7II78fISYmhtDQUKZMmYKnpycADRs2NBgTGxvLqlWrqF69OgBFihShf//+nDlzhnr16unH2dvbM2/ePACaNm3Kvn37WLFiBdu2baNatWoAREREMHPmTOLi4ihWrJj+3IoVKzJ79mz9uUlJSXz99dcMHjyY4sWLs2LFCszMzAgKCtL/xVO+fHn69u37zO/5xo0brFq1iunTp9OrV2bluXHjxiQlJbFkyRJ69eqFqakp586dY/z48bRv//9PVjt37qz/85P685KoqChs7eyytdva2j3sjzQar0pZxaudU7zaelXKaszeypWrcO7sGdLT0zEzMwMgNTWFc2fPAhAZGaEfB3A65BTlypfXnx/y8J4AWeO0zCre/PeqlFU1r0pZxaudU7zaerXKKgj5gay0eYSSJUtSrlw5FixYwMaNGwkPD882xt7eXl+wAXjttdcAsq1yady4scHrKlWqYG9vry/YAFSuXBkg23Vat25t8Nrb25vExET+/PNPILNA0qBBA4NKcb169ShRosRTvtP/c+jQIQDatGlDWlqa/mjcuDFRUVH67Vs1a9bkq6++4r///S/Xr1/P5nlSf16SnJyEhYVFtvasT4iTk5KMxqtSVvFq5xSvtl6Vshqzt0fvPly/do3p06bw999/8dflP/lgsj93oqIenp8MgEez5pR99VUWfjqXvT/tJizsFrt37mDJogBeeukl/Tgts4o3/70qZVXNq1JW8WrnFK+2Xq2yCkJ+IEWbRzAxMSE4OJiqVasyY8YMmjdvTteuXTl+/Lh+zKMrYgDMzc0BSE42/CU1p3FPe26pUqUMXtva2gKZFeKsf/9zTE7nPQ13795Fp9PRsGFDatWqpT/efvttAH3RZuHChTRs2JCAgADatGlD27Zt2b17t97zpP68xNLSSr88/1Gy5tHSyipbX0F5VcoqXu2c4tXWq1JWY/b26NUb38FD2bFtG93f7EiPLm8QevMGAwf5AlC0aNGH17Ek8PMgipcowcRxo+nQxoup77/HYL/hFCtWnCIPx2mZVbz571Upq2pelbKKVzuneLX1apVVNUyM+BByR7ZH/YMqVaqwaNEiUlNTCQkJYcGCBfj5+fHLL7/kW4aYmBiD13fu3AHA7uGSPjs7u2xjcjrPwsIi2712YmNjDV4XL14cExMT/vvf/+qLSI9SpUrmMnh7e3tmz55NRkYG58+fZ+nSpYwbN46dO3dSoUKFJ/bnJXZ2dkTmcP+eO3eiHvbbG41Xpazi1c4pXm29KmU1du/IMePoP3AQf//9F9bW1lR3cCQwYAEAFR+uDgWo9lp11m3awpW//yIuLo6q1aphaWnF/LlzqFu/fr5kFW/+elXKqppXpazi1c4pXm29WmUVhPxAVtrkgrm5Oe7u7gwZMoSEhAQiI/Nvn+NPP/1k8HrXrl0UKVIEBwcHAJycnDhy5AgJCQn6MSdOnODevXsG55UpU4arV6+i0+n0bQcPHjQY06hRIwDu3buHk5NTtuOfN+syNTXF2dmZsWPHkpaWlm0r1JP68wLHGjW4fv2awfsHOHf2DAA1arxuNF6VsopXvaziVS+rCt5ixYvjVqcu1R0cATh65DCvvFKGKlWqGowzMTGh2mvVcatTl+LFS3D82FEyMjJo0LBRvmUVb/55VcqqmlelrOJVL6t4tc0qCPmBFG0e4dKlS7z99tusXbuWI0eOsGfPHpYuXUq5cuWoWLFivuW4ceMGkydP5tdffyUoKIhly5bRp08fihcvDsDAgQPJyMhg6NCh7Nu3j02bNjF58mRKliyJySO33vb29iYsLIyZM2dy6NAhFi9ezK5duwyuVaVKFfr27cukSZNYunQphw4d4sCBA6xcuZLhw4cDEB8fT8+ePVm9erW+f968eRQrVoyaNWs+sT+vadWmLenp6axfu0bflpKSwuaNG3BydqFM2bJG41Upq3jVyype9bKq5t21Yzu/nz9HH5/+mJrm/itDUlISSxd/hq2dHW3bdyiQrOLV1qtSVtW8KmUVr3pZxattVuUo6D1Qsj/quZDtUY9gZ2eHra0tQUFBREREYGNjQ7169Zg3b57+SRr5wbhx4zh27BhjxozBzMyMPn36MG7cOH2/vb09y5cv5+OPP2b06NFUrFiRKVOmMGPGDGxsbPTjmjVrxrvvvsuqVavYuHEjzZo1Y/r06QwcONDgeh988AFVqlRhzZo1LFmyhJdffpkqVarQtm1bIPP+BQ4ODnz77bfcvn0bKysrateuTXBwMKVKlSIlJeWx/XmNs7MLbbzbsihgATHR0VSoWIktmzcSFnaLj2bOMiqvSlnFq15W8aqX1Zi9J08cZ9kXn9OocROKFy/BubNn+HHTBhp7NKVPv/4GYydNGIudnT1Vq1XjfkICmzZu4FboTRZ9HsTLL1vncgXjnwPxFo6sqnlVyipe9bKKV9usgpAfmOge3TsjFCihoaF4eXnx2Wef6QsmT8u1a9do164dn3zyCV26dNEoYf6RlPb4/uTkZJYEBrBtyxbi4mKp7uDIiFFjaOLR9IWuq4VXpaziVS+reNXLaozeDJ2OmzduMPvj6Vy8eIEH9+9Trlx5Or7ZGZ8BAzE3N3zixoqvvuTHjRsIC7uFpaUVbnXrMmzEKBz/sbzc1CT3j86MbQ7EW7iyquZVKat41csq3hdzWhWiZQ5nbsYXdIRccalg8+RB/1KkaGNEPEvRZv78+Tg6OmJvb8/NmzcJCgoiKSmJHTt28PLLL+dTYu14UtFGEARByDsyNPpV4HFFG0EQBEFQgcJUtDl7M+HJgwoI5wpPXqn7b6UQfQv+u0hNTeXTTz/lzp07WFlZ4e7uzqRJkwpFwUYQBEEQBEEQBEEQBFlpIxgpstJGEAQh/5CVNoIgCIKQM7LSJn+QlTa5I0+PEgRBEARBEARBEARBMEIKUd1QEARBEARBEARBEISckAWwaiJFG0EQBEH4lyPbmARBEARBEIwT2R4lCIIgCIIgCIIgCIJghEjRRhAEQRAEQRAEQRAKOSZGfDwvO3bsYNiwYTRr1gxXV1fefPNN1q1bxz+ft7R27Vq8vb1xcnLijTfe4Oeff87mio+P5/3338fd3R03NzdGjx5NZGRktnGnTp2iV69eODs707JlS5YtW5btenmJFG0EJUlJSWHh/Hm0auGBex1n+vbuweFDB43Sq1JW8aqXVbzqZRWvelnFq15W1bwqZRWvelnFq21WoWBZsWIFRYoUwd/fn6VLl9KsWTOmTp3KkiVL9GO2bdvG1KlTadeuHcuXL8fV1ZWRI0dy+vRpA9fYsWM5ePAgH330EZ9++ilXr15l8ODBpKX9/9HG169fx9fXFzs7O4KCghgwYACLFi3iq6++0uw9yiO/BaPkSY/8fm/iePb8tIu+Pv2pWLEyP27eyO/nz7H8q5XUqVvvua+rhVelrOJVL6t41csqXvWyile9rKp5VcoqXvWyivfFnIXpkd/nQ433kd+1yz/fI79jYmIoVaqUQdvUqVPZvn07x48fx9TUFG9vb2rXrs38+fP1Y3r37o2NjQ3Lly8HICQkhN69exMcHIyHhwcAV65coX379ixYsID27dsDMG3aNH777Td27tyJhYUFAAsWLOC7777j4MGD+rY8RScIRkhiau7HsZNndA4ODrovln2pb7uXkKTz8mql69Gz12PPzW+vSlnFq15W8aqXVbzqZRWvellV86qUVbzqZRXvizsLE+dC4432yEtWr16tc3Bw0MXHx+tu3Lihc3Bw0P30008GY1auXKmrVauWLjk5WafT6XQBAQG6evXq6TIyMgzGde7cWffee+/pXzdv3lz38ccfG4y5ePGizsHBQXfkyJE8fR9ZyPaofzmXL19m8ODBNGjQABcXF7y9vfXVRn9/fzp27MiBAwfo2LEjTk5OdO3a1WAZ2Zw5c2jRogUZGRkG3gMHDuDo6Mhff/2V55n37N6JmZkZ3Xr00rdZWlrSpVt3zpwOIfz2baPxqpRVvOplFa96WcWrXlbxqpdVNa9KWcWrXlbxaptVME5OnjzJK6+8grW1NVeuXAGgSpUqBmOqVatGamoqN2/eBDJX1VSpUgWTfzxRs2rVqnrHgwcPuH37NlWrVs02xsTERD8ur5Gizb8cPz8/4uLimDVrFkFBQfj6+pKYmKjvj4qKYvr06fj6+hIQEICFhQW+vr5ER0cD0KNHD27fvs3Bg4b7QdevX4+rqyuvvfZanme+dOkilSpVxtracAldbSdnfb+xeFXKKl71sopXvaziVS+reNXLqppXpaziVS+reLXNKuQdXl5ejz2elhMnTrB9+3YGDRoEQGxsLADFihUzGJf1Oqs/Li4OGxubbL7ixYvrx8THx+fosrCwoEiRIvpxeU0h2qEnPCsxMTGEhoYyZcoUPD09AWjYsKHBmHv37hEQEECjRo0AcHd3p3nz5qxYsYIJEyZQrVo16taty/r162natCkAd+/eZd++fUybNk2T3FFRUdja2WVrt7W1e9if/Q7fBeVVKat4tXOKV1uvSlnFq51TvNp6VcqqmlelrOLVzilebb1aZVUNkxd6TpPxEx4ezrhx42jQoAH9+/cv6Dh5hhRt/sWULFmScuXKsWDBAmJjY2nUqBFlypQxGGNjY6Mv2GS9bty4MWfOnNG39ezZk6lTp3Lv3j1KlCjBli1bMDc319+sKa9JTk7K8QZPlpaWmf1JSUbjVSmreLVzildbr0pZxaudU7zaelXKqppXpazi1c4pXm29WmUV8o69e/e+0PlxcXEMHjyYEiVKEBgYiKlp5qai4sWLA5mrZOweKdzFxcUZ9BcrVozw8PBs3tjYWP2YrJU4WStuskhJSSExMVE/Lq+R7VH/YkxMTAgODqZq1arMmDGD5s2b07VrV44fP64f8887cQOULl2aqKgo/eu2bdtiZWXFjz/+CMCGDRvw9vbOtvwwr7C0tCIlJSVbe3Jycma/lZXReFXKKl7tnOLV1qtSVvFq5xSvtl6VsqrmVSmreLVzildbr1ZZBeMgKSmJoUOHEh8fz5dffmmwzSnr/jP/vN/MlStXMDc3p0KFCvpxV69eRfePh2tfvXpV7yhatChly5bN5so675/3uskrpGjzL6dKlSosWrSIY8eO8e2332JhYYGfnx/3798HMrdQ/ZPo6GiDKqWVlRWdOnViw4YN/P7771y8eJHu3btrltnOzo47jxSNsrhzJ+phv73ReFXKKl7tnOLV1qtSVvFq5xSvtl6VsqrmVSmreLVzildbr1ZZVcPExHiP5yUtLY2xY8dy5coVvvzyS1555RWD/goVKlC5cmV27txp0L59+3YaNWqkX4HVrFkzYmNjOXz4sH7M1atXuXDhAs2aNdO3NWvWjL1795KammrgKlasGG5ubs//Rh6DFG0EAMzNzXF3d2fIkCEkJCQQGZm5rzM+Pt7gGzc+Pp5Dhw7h4uJicH7Pnj25ePEis2fPpnLlytSrV0+zrI41anD9+jUSEhIM2s+dzdyyVaPG60bjVSmreNXLKl71sopXvaziVS+ral6VsopXvazi1TarUPBMnz6dn3/+GT8/PxISEjh9+rT+yFpdNWrUKLZu3cqiRYs4evQoH374IWfPnmX48OF6j5ubGx4eHrz//vvs2LGDffv2MXr0aBwdHWnTpo1+nK+vLzExMUyYMIHDhw+zcuVKgoOD8fPzy3ELXl4gRZt/MZcuXeLtt99m7dq1HDlyhD179rB06VLKlStHxYoVAShRogRTpkxh06ZN7N27l8GDB6PT6RgwYICBq0aNGjg5OXH8+HG6deumae5WbdqSnp7O+rVr9G0pKSls3rgBJ2cXypQtazRelbKKV72s4lUvq3jVyype9bKq5lUpq3jVyypebbMKBU/WU4znzJlDr169DI6shQgdO3Zk5syZbN26FV9fX06dOsXixYuzrYwJCAigcePGTJs2jQkTJlC5cmWWLVvGSy/9/1bAlSpVIjg4mPDwcIYMGcJXX33F6NGj9U+r0gK5EfG/GDs7O2xtbQkKCiIiIgIbGxvq1avHvHnzMDMz04+ZOHEic+fO5caNG1SvXp3g4GBsbW2z+Vq3bs2FCxfo3LmzprmdnV1o492WRQELiImOpkLFSmzZvJGwsFt8NHOWUXlVyipe9bKKV72s4lUvq3jVy6qaV6Ws4lUvq3i1zaoahfHZUfv27XuqcT169KBHjx6PHWNjY8Mnn3zCJ5988thxderU4YcffnjqjC+Kie6fd9oRhIf4+/tz/vx5tm7d+lTj+/bti42NDV988cULXzsp7fH9ycnJLAkMYNuWLcTFxVLdwZERo8bQxKPpC11XC69KWcWrXlbxqpdVvOplFa96WVXzqpRVvOplFe+LOa0K0TKHi2H3CzpCrrz+6ssFHcFokaKNkCtPW7Q5d+4cJ0+eZPbs2Xz99dc0btz4ha/9pKKNIAiCIAiCIAiC1kjRJn+Qok3uFKJvQaGg6N69OzY2NgwfPjxPCjaCIAiCIAiCIAhCHlMY90f9C5CVNoJRIittBEEQBEEQBEEoaArVSpvbRrzSpqystMkNeXqUIAiCIAiCIAiCIAiCEVKI6oaCIAiCIAiCIAiCIOSEieyPUhIp2giCIAiCIAiCIPyDDA3uImFqIv/TLAjCsyHbowRBEARBEARBEARBEIwQWWkjCIIgCIIgCIIgCIUcWeilJrLSRlCSlJQUFs6fR6sWHrjXcaZv7x4cPnTQKL0qZRWvelnFq15W8aqXVbzqZVXNq1LWwu59cP8+ny9exLAhvjRv3AC32jX4cdOGHMde+ftvRgx9h8b169C8cQM+8J9ETEzMY7Ns2/ojLrUcaVjP7YWzPgvi1S6rIGiNFG00Zs+ePaxevbqgYwAQFxeHo6MjGzbk/INHJaa+78+qb1bQvmMnJvlPwczMjJHDhnDq5Amj86qUVbzqZRWvelnFq15W8aqXVTWvSlkLu/fuvbsELV3C1StXcHB0zNUZER6O78B+3Lxxg5FjxtJ/4Nv8+ssBhg0eRGpqSo7nPHhwn4Xz51GkSNE8yfosiFe7rIKgOTpBU9577z1dhw4dCjqGTqfT6WJjY3UODg669evXF3SUJ5KYmvtx7OQZnYODg+6LZV/q2+4lJOm8vFrpevTs9dhz89urUlbxqpdVvOplFa96WcWrXlbVvCpl/Td4Y+8n626GRWaeeyrz3O9+WKe7n5JhcEyZ+qHO2dlZ99f1UH3b3gO/6RwcHHTfrP4u2/j7KRm6T/4zT9fG21s3dvwEnYuLq9HOQWH0voizMPHH7ftGewi5IyttChnp6emkpqY+9/kpKSlkZGTkYaK8Z8/unZiZmdGtRy99m6WlJV26defM6RDCb982Gq9KWcWrXlbxqpdVvOplFa96WVXzqpT13+C1sLDA1s7uid69P+2mafMWlC37qr6tYaPGVKpcmd27dmYbf/36NVZ/s4KJkybzklnOtxU1ljkojF6tsgpCfiBFGw3x9/dn48aNXL58GUdHRxwdHfH39wcgJCSE/v374+rqSt26dZkwYQLR0dEG53/66ad06tQJNzc3mjZtyvjx44mMjDQY4+Pjw9ChQ9m4cSPe3t44OTlx6dIlAH744Qc8PT1xcXFhwIABXL9+PVtGT09PZsyYwfLly2nZsiXOzs7cu3ePjIwMPv/8czw9PalduzZt27bl+++/Nzg3MDAQNzc3zp49S/fu3XFycqJdu3b8/PPPeTmN2bh06SKVKlXG2traoL22k7O+31i8KmUVr3pZxateVvGql1W86mVVzatSVvFmEhkRQUxMNDVr1c7WV7u2M39cvJCt/dM5s6nv3oCmzZrna1bxaptVEPIDeXqUhgwfPpyYmBiuXLnCp59+CkCpUqUICQnBx8eH5s2bs3DhQhITEwkICGD48OGsWbNGf350dDRDhw7F3t6emJgYvv76a3x8fNi2bRsvvfT/L9358+e5desWY8aMoVixYpQtW5aff/6ZqVOn0rVrV9q3b8/vv//OmDFjcsy5e/duKlWqxJQpUzA1NaVo0aLMnTuXb775hmHDhuHm5sb+/fv58MMPSUtLo1+/fvpzU1NTGTduHIMGDaJ8+fJ89913jBw5kg0bNuD4mH3AL0JUVFSOn4DY2to97I/M1ldQXpWyilc7p3i19aqUVbzaOcWrrVelrKp5Vcoq3ixnpIHDwGtnR2xsLCkpKVhYWADw64H9HDl8kO/Xb8r3rOLVzqkk8vQoJZGijYZUrFiRUqVKERYWhqurq779/fffp3bt2ixevBiTh89dc3BwoGPHjhw4cIDmzTMr8LNnz9afk56ejpubG82aNePIkSN4eHjo+2JjY1m3bh1ly5bVty1dupR69erpHU2bNiU5OZnPP/88W87U1FSWL19O0aKZN0WLiYlh1apV+Pr6MmrUKAA8PDy4e/cuS5Ys4a233sLMzEx/7rBhw+jevbt+XJs2bQgKCmLBggUvPIc5kZycpP8h+CiWlpaZ/UlJRuNVKat4tXOKV1uvSlnFq51TvNp6VcqqmlelrOLNciYD5Oi1eMRrYWFBamoKn86dTbeevahW7bV8zype7ZyCkF/I9qh8JjExkVOnTtG2bVvS09NJS0sjLS2NypUrU7ZsWc6dO6cfe+DAAXr37k3dunWpWbMmzZo1A+DatWsGTgcHB4OCTXp6Or///jutW7c2GOft7Z1jpgYNGugLNgBnz54lNTWVtm3bGoxr164dMTEx2a7/6HXMzMxo1aoVZ86cefJkPCeWllakpGS/K3/WD1BLKyuj8aqUVbzaOcWrrVelrOLVzilebb0qZVXNq1JW8WY5M/9HPydvyj+8q75Zyb279xg2YlSBZBWvdk5ByC9kpU0+ExcXR3p6OrNnzzZYSZPF7Yc3wTp79izDhw/Hy8uLwYMHU7p0aUxMTOjZs6f+L5csbG1tDV7HxMSQlpZGqVKlHjsui9KlSxu8jo2NzXF81ut79+7p28zNzSlevHg2X1RUVI7Xygvs7OyIjIjI1n7nTtTDfnuj8aqUVbzaOcWrrVelrOLVzilebb0qZVXNq1JW8WY57Q0cBt6oKIoXL46FhQXx8fF8GbSUnr37cD8hgfsJCZiYmPDgwQN06Lh1KxQrqyL638VVmgPVvFplVQ0T2R+lJLLSJp+xsbHBxMQEPz8/1q1bl+0YNmwYAHv27MHa2pqAgAC8vLxwdXXNteiStcUqi1KlSvHSSy8RExNj0H7nzp2nOr9EiRIA2W6MnHV+Vj9kbo/KKvJkER0djd1T3HX/eXGsUYPr16+RkJBg0H7ubObqnho1Xjcar0pZxateVvGql1W86mUVr3pZVfOqlFW8mdi/8golS5Xiwu/ns/WdP38Wx4fO+LhYHjx4wIqvvqSDdys6eLeifRsv9vy0i6TERNq38WLmR1M1zSpebbMKQn4gRRuNMTc3N1gZU7RoUVxdXbly5QpOTk7ZjvLlywOQlJSEubm5QUFly5YtT3VNMzMzatasyU8//WTQvmvXrqc638nJCXNzc3buNHxc4Y4dOyhdujSVK1c2aH/0Ounp6ezZswcXF5enutbz0KpN5tay9Wv/f9PmlJQUNm/cgJOzC2Ue2SpW0F6VsopXvaziVS+reNXLKl71sqrmVSmreP+PV6s2/Hpgv8Gjoo8eOcz1a9do1SbzFgMlS5VmwWeLDY6Fi5ZQ370BlpaWLFy0hEGDh2qeVbzaZRWE/EC2R2lMtWrVWL9+PVu3bqVSpUqULFmSSZMmMWDAAMaOHUuHDh0oVqwY4eHhHDp0iK5du9KgQQOaNGnCypUrmTlzJq1btyYkJITNmzc/9XX9/PwYPnw4kydP1j896mnPL1WqFP369SM4OBgLCwtcXV05cOAAW7duZerUqfqbEENmUWrp0qUkJyfrnx4VHh7OkiVLnnmunhZnZxfaeLdlUcACYqKjqVCxEls2byQs7BYfzZxlVF6VsopXvaziVS+reNXLKl71sqrmVSnrv8X73epVxMfHERmZ+UShA/t/JuLh1preffphY2OD7+Ch7Nm9kyGDBvBWPx8ePHjAN19/RfXqDrzZpSsARYoUoaVXKwO3qYkJP+/dw/lz5/D8R58xzUFh82qVVTX+scFCUAQTnU6nK+gQhZmEhASmTZvGwYMHuXfvHl26dGHOnDmcO3eOwMBATp06RWpqKmXKlKFhw4YMGzaMMmXKALB8+XJWrVpFbGwsderUYdq0aXh7ezNp0iR8fX0B8PHxoWjRogQFBWW79vfff88XX3xBTEwMLi4uvPvuu/To0YPZs2fTtWvmDxNPT09atGjBtGnTDM7NyMhg6dKlrFu3jqioKMqVK8fbb79N79699WMCAwP56quvWLFiBdOnT+fPP/+kfPnyvPvuu3h5eb3QvCWlPb4/OTmZJYEBbNuyhbi4WKo7ODJi1BiaeDR9oetq4VUpq3jVyype9bKKV72s4lUvq2pelbL+G7ztWnsSFnYrx75tu/bwarnMlfF//3WZ+XPnEBJyCnNzc5o2bc74d9+jdC63NIDMos3U9/35afcujpwIeeGsT4t4n99pVYiWOfwVmVjQEXLlNfsiBR3BaJGijfDcZBVtQkKy/8B5UZ5UtBEEQRAEQRAELcnQ4H+TTGWpg3JI0SZ/kKJN7hSib0FBEARBEARBEARBEHJCSoZqIjciFgRBEARBEARBEARBMEJke5RglMj2KEEQBEEQBKEgke1RAhSu7VF/G/H2qGqyPSpXCtG3oCAIgiAIgiAIgiAIOSI1QyWR7VGCIAiCIAiCIAiCIAhGiKy0EQRBEARBEARB+AdabGXSYssVyLYrQSjMyEobQRAEQRAEQRAEQRAEI0SKNoKSpKSksHD+PFq18MC9jjN9e/fg8KGDRulVKat41csqXvWyile9rOJVL6tqXpWyivfZnQ/u3+fzxYsYNsSX5o0b4Fa7Bj9u2pDj2Ct//82Ioe/QuH4dmjduwAf+k4iJiTEY88WSQNxq1zA4XGo56o+QUyfzZQ5U82qVVSVMjPgfIXekaFPI8fHxYejQofrXgYGBuLm5aXKtuLg4AgMD+euvvzTxP8rU9/1Z9c0K2nfsxCT/KZiZmTFy2BBOnTxhdF6VsopXvaziVS+reNXLKl71sqrmVSmreJ/deffeXYKWLuHqlSs4ODrm6owID8d3YD9u3rjByDFj6T/wbX795QDDBg8iNTVFP86zVRs+nj3X4Jg1Zy5lypSlWLHi1K7tlC9zoJpXq6yCoDk6oVDTr18/3ZAhQ/Svb9++rTtz5owm17p586bOwcFBt2PHjhd2Jabmfhw7eUbn4OCg+2LZl/q2ewlJOi+vVroePXs99tz89qqUVbzqZRWvelnFq15W8aqXVTWvSlnF+3zO2PvJupthkZnnnso897sf1unup2QYHFOmfqhzdnbW/XU9VN+298BvOgcHB903q7/LNv7R4+qNMJ2jo6Nu8vsfKD23xvI1e/QoTPwdmWi0h5A7stImn0lPTyc1NbXArl+mTBmcnZ0L7Pp5wZ7dOzEzM6Nbj176NktLS7p0686Z0yGE375tNF6VsopXvaziVS+reNXLKl71sqrmVSmreJ/PaWFhga2d3RO9e3/aTdPmLShb9lV9W8NGjalUuTK7d+187Lk7tm9Fp9PRvmOnF877tKjk1SqrapiYGO8h5I4UbR5y4sQJHB0duXHjhr7Nz88PR0dHLl++rG8bP348Q4YMAeDTTz+lU6dOuLm50bRpU8aPH09kZKSBN2t70saNG/H29sbJyYlLly4BsH//fnr06IGzszMNGzbkww8/5MGDBwbnOjo6Zjt8fHz0Y+Li4pg5cybNmjWjdu3aeHp6Mn/+/FzfZ07bo+Li4vjoo4/w8PCgdu3adO3ald9++y3H97Fz5068vb1xc3Ojf//++vkKDQ3Fy8sLgDFjxuizhoaGPnnyn5FLly5SqVJlrK2tDdprOznr+43Fq1JW8aqXVbzqZRWvelnFq15W1bwqZRWvds7IiAhiYqKpWat2tr7atZ354+KFx56/fesWypQpS9169fMlr2perbIKQn4gj/x+iLOzM5aWlhw/fpyKFSuSkZHByZMn9W3Vq1cH4Pjx4/qiSXR0NEOHDsXe3p6YmBi+/vprfHx82LZtGy+99P+pPX/+PLdu3WLMmDEUK1aMsmXLsnPnTsaNG0fXrl0ZNWoUUVFRzJ8/n7i4OBYuXAjAhx9+SEJCgt4TERHBxIkTqVKlCpB5M60BAwZw69YtRowYgYODA+Hh4Zw8mf3mY7mRkpLC22+/TXR0NGPHjuWVV17hxx9/ZOjQoWzYsAHHR/bdXrx4kZiYGCZOnEh6ejpz5szh3XffZc2aNdjb27N48WJGjhzJ+PHjadCgAQD29vbP+RXJnaioqBw/rbC1tXvYH5mtr6C8KmUVr3ZO8WrrVSmreLVzildbr0pZVfOqlFW8WjojDRwGXjs7YmNjSUlJwcLCIlv/339d5s8//2DgoHcwyWHJgkpzq5VXq6yCkB9I0eYhFhYWODs7c+LECbp168Yff/xBYmIiXbt25fjx4/Tp04fr168TGRlJ/fqZFezZs2frz09PT8fNzY1mzZpx5MgRPDw89H2xsbGsW7eOsmXLAqDT6Zg7dy7t27dn1qxZ+nF2dnYMGTKE4cOHU716dV577TV9X3JyMjNnzqRq1apMnjwZgE2bNnHhwgW+//57g9UzXbp0eer3vWXLFi5dusTmzZv112vatCnXr1/n888/57PPPtOPjY+PZ9OmTZQqVQqABw8eMHnyZMLDwylTpgyvv/46AJUqVcLV1fWpMzwryclJOf7AsrS0zOxPSjIar0pZxaudU7zaelXKKl7tnOLV1qtSVtW8KmUVr5bOZIAcvRaPeHPq3751CwAdctgapVVe1bxaZVUN2YWkJrI96hHq1avH8ePHgcwVNbVr16ZZs2YGbUWKFKF27cxliwcOHKB3797UrVuXmjVr0qxZMwCuXbtm4HVwcNAXbACuXr3KrVu3aNeuHWlpafrD3d0dU1NTzp8/ny3blClTCA0NZcmSJRQpUgSAw4cPU61atRd6GtTBgwdxcHCgcuXKBlkaN27MuXPnDMbWqFFDX7AB9EWe8PDw577+82BpaUVKSkq29qwfdpZWVkbjVSmreLVzildbr0pZxaudU7zaelXKqppXpazi1dKZWTzIyZvyGK9Op2PH9q28Vt0BB8ca+ZZXNa9WWQUhP5CVNo/g7u7O0qVLiYiI4MSJE9SrV4969epx584drl27xokTJ3BxccHc3JyzZ88yfPhwvLy8GDx4MKVLl8bExISePXvq/+PPwtbW1uD13bt3ARgxYkSOOW7/40ZYy5cvZ/v27QQHB1O+fHl9+7179154+9Hdu3e5cOECtWrVytZnZmZm8LpYsWIGr83NzQGyvV+tsbOzIzIiIlv7nTtRD/ufb0608KqUVbzaOcWrrVelrOLVzilebb0qZVXNq1JW8WrptDdwGHijoihevHiOK0VOh5zidlgYo8dOyNe8qnm1yioI+YGstHkEV1dXzM3NOX78OCdOnKB+/fqUKFGC6tWrc/z4cY4fP069evUA2LNnD9bW1gQEBODl5YWrq2u24kwW/9xbWqJECQCmTZvGunXrsh3dunXTjz1w4AALFixg0qRJNGrUKJvnnzc+flaKF/8fe2ceV8P+//HXkUqkskT2FC2iQoVcsme91nAthWwle5It+1aEFrJE6N4rZMkWct3sKiHL5VIhSWVp03Jazu+Pfs3t6ERnOqMzvu/n93Ee32tmzmteZ840Z+b9eX/eb3Xo6+tL9BEUFFQpba7QNzDA69evxOr9AMCjmIcAAAMDQ7nR5ZNX0uWfV9Lln1fS5Z9X0uWfV77p8skr6XKn2aBhQ9SpWxdPn5TNuH/8OAb65WieP3sGAoEAAwcN/qF++abLlVfeIZDjF1EuFLQpRc2aNdGmTRsEBQUhLS0NHTt2BACYm5sjJCQEb9++ZYI2ubm5UFRUFAvInDlzpkL70dHRgZaWFhISEtCuXbsyr4YNGwIA4uLisHDhQgwZMgSTJk0qo2NpaYnY2Fg8fPiQ9We2tLREQkICGjRoINGLNPyozJs+/fqjsLAQwcf+CyoJhUKcPnkC7YxNoFVqKlpV6/LJK+nyzyvp8s8r6fLPK+nyzyvfdPnklXS59dq7Tz9cD/9brP303Tu38frVK/Tp17/M9vn5+Qi7FArTDh3RqHHjMuu59ssnXa68EsSPgKZHfYWZmRn8/f1hZGTEtIQzMzPD77//DkVFRaZ+TNeuXXHw4EGsXbsWffv2xf3793H69OkK7UMgEMDV1RXOzs7Izs5Gjx49oKKignfv3iE8PBzz589Hy5Yt4eDggBo1amDkyJF48OAB835VVVW0atUKQ4cOxR9//IHp06fDyckJrVu3ZqZ2rV27tkJehg0bhiNHjsDW1hZTpkyBtrY2MjMz8fTpU+Tn52PhwvJTLb9GU1MTampqOHfuHJo2bQolJSXo6+tLTOWsDMbGJuhn3R9e2z3x6eNHNGveAmdOn8S7d4lYtXb99wV+oC6fvJIu/7ySLv+8ki7/vJIu/7zyTZdPXkmXveafvwciMzODyZIP//sqkv9/us7YcRNQu3Zt2E+bgbBLoZg+xQ6/TZiI7OxsHDqwH61b62Ho8BFlNG/fvIG0tLRvZtlwdQz4psuVV4L4EQhEIpGoqk3IE3///TdmzJgBOzs7LF26FEBxi7hffvkF7du3x5EjR5ht9+7di8DAQKSnp6NDhw5wc3ODtbU1XFxcYG9vDwCYOHEiatasid27d5fZ182bN+Hn58cUHm7SpAm6desGR0dH1K5dW6zddmksLCxw+PBhAMWdqbZt24awsDCkpaVBS0sLgwYNwvz58yXu39vbG/v378f9+/cZvaysLHh7e+PSpUtITU2FhoYG2rRpg3HjxqFHjx7lfo5//vkHw4YNw6FDh5gW32FhYfD09ERCQgKEQiGuXLkiVoenouQWfHt9Xl4efL2349yZM8jISEdrPX3Mmj0XXX/pJvW+uNblk1fS5Z9X0uWfV9Lln1fS5Z9XvunyySvpstMc0LcX3r1LlLju3MUwNG5SfL8c+/IFtrpvwv370VBUVES3blZYsGgx6kkow+C6aAGuXL6MsPDrqKNRR6Z+KwqfdNlq1viJ0hxef+R2RkRlaFFPuaotyC0UtCHkku8FbQiCIAiCIAiCbxRx9OhVTUBFQbiCgjY/BgralA/VtCEIgiAIgiAIgiAIgpBDfqK4IUEQBEEQBEEQBEEQkqCELH5CmTYEQRAEQRAEQRAEQRByCAVtCIIgCIIgCIIgCIIg5BCaHkUQBEEQBEEQBEEQPzk0O4qfUNCGIAiCIP7HKSjkpptJdQW6PSQIgigNdXkiCEJaaHoUQRAEQRAEQRAEQRCEHEKZNgRBEARBEARBEATxk0OJXvyEMm0IMby9vREdHV3VNr6LUCjEtq0e6NPjF1h0MMb4sTa4feumXOryySvpFvP4UQw2rFuD4b8OQiczU1j37oFFC+bi1at4ufNKuvzzKg+6X5/jA/v1xGLneXj91Tl+4vhRTJs8AX17dEXnju0wpH9vrFqxBO8S34ptF3L6BDoaG5R5mRjpw8RIH+fOhsjdMSBd+dAkXf55JV3ZaL58+QLO8+dgoHVvdOpoAquunTDZdjz+vvqX2HYl11FJrxlTJ8t0X2z4X/rOCKKqEIhEIm4mshO8RF9fHy4uLrC3t69SH7kF316/2HkBwi5fxPiJtmjeXBshp0/iyeNH2Lv/IDp0NGO9Xy50+eSVdItZOG8OHtyPRl/r/tDT08eHD6k48sfvyM7OxuE/g9C6tZ7ceCVd/nmVB92vz/GU1FQc/bP4HA8IPIJW/3+Ob1y3Grm5OWjVWg9qaupITHyLU8HHUFhUiCPHTkGzQUMAwNu3CYh5cL+Mnz8CD+Lf589w6Uo46mtqytUxIF350CRd/nklXdloXr8Wjj8CD8HEtD00NRsgNzcHYZcvIfpeFFasXINRo8cAAM6eOV3mvU8fP8bvgYcwf+EiTJoyVWb7YsP/wndW4yeam/L2c15VWyiXpnWUq9qC/CIiKkVBQYFIKBRWtQ2ZoaenJ9q3b5/M9HJycti9L7/8V8S9hyI9PT2R3559zLK0rFxR7959RDajx3zzvT9al09eSfe/1+2Ie6KML3liy569jBe1bdtWNG/BQrnySrr88iovul+f45m5RaInz+NEbdu2Fc2dv1CUmVtU7isiOkakp6cn8vL1++Z2qWnZovbt24tsJ02Wy2NAulWvSbr880q63HrNyi0QDRnyq6iftfU3t1u8ZKlIX19f9CohifN90Xcms8ciuSDhU57cvojy+WmnR0VFRUFfXx9v3rxhls2cORP6+vp48eIFs2zBggWYPn06AGDLli0YMmQI2rdvj27dumHBggVISUkR0504cSJmzJiBkydPwtraGu3atcOzZ88AAH///TdsbGxgbGyMzp07Y+XKlcjOzhZ7r76+fpnXxIkTAQB3796Fvr4+rl+/jrlz56J9+/bo0aMHzpw5AwA4dOgQevToAQsLCyxbtgxCoZDRTklJwZIlS9C7d28YGxujX79+8PT0FNsGAI4fP45BgwbB2NgYnTp1wm+//YaYmBgAxVk2AODu7s54u3v3LgBAJBLB398f1tbWaNu2LXr37o2AgAAxbW9vb7Rv3x4xMTEYM2YM2rVrh99//13Kb+77hF0KhYKCAkba/DcqoKysjOEjR+Hhg/t4n5QkN7p88kq6/2HavgMUlZTElrVooQ3dVq0RHxcnV15Jl19e5UVX0jnevIU2dHRbIT4u9pv7adS4CQAgMzPzm9tdC7+KL1++YNCgIZXyKg2ky50un7zyTZdPXkmXW68KCgpoqNUImRnlX1+FQiHCLl9CRzNzNNTSYrWfiu7re9B3RhA/hp82aGNsbAxlZWVERkYCAIqKinDv3j2xZQAQGRkJM7PidLiPHz9ixowZ2L17N5YtW4bExERMnDgRBQXic3UeP34Mf39/zJ07F3v27EGjRo0QGhoKBwcH6OnpwcfHB4sWLcLly5exbNky5n0rV65EUFAQ8/Ly8oKSkhJatmwppr9q1Sq0bt0aPj4+MDExgYuLCzw8PHDjxg2sXr0ac+bMwenTp7F//37mPZ8/f4aGhgaWLFmCffv2YerUqTh58iRWrlwp9lmXLVuG7t27Y8+ePdi8eTO6dOnC3HgHBQUBKA4ulXg0MjICAKxfvx5eXl4YNmwY9uzZg+HDh2PLli34888/xbzn5+dj4cKF+PXXX7F371507dqV3Rf4DZ49+wctWmhDVVVVbHnbdsbMennR5ZNX0v02IpEIHz9+gIZGHVbv59sx4JMun7zKs65IJMKnjx+hUafsOZ6W9hmfPn7E0yePsHrFUgCARafO39QLPXcGNWrUQO++fWXutTxIlztdPnnlmy6fvJKu7DWzs7Px+fMnJLx5g8MHA3DzxjV06lz+9fX6tXBkZmRg0OBfpfYt7b6+x//qd0YQP5qfaIaeOEpKSjA2NkZUVBRGjhyJ58+fIycnByNGjEBkZCTGjRuH169fIyUlBebm5gCAjRs3Mu8vLCxE+/bt0b17d9y5cwe//PILsy49PR3Hjx9Ho0aNABTf6Lq7u2PgwIFYv349s52mpiamT58OR0dHtG7dGq1atWLW5eXlYe3atdDR0cGSJUvEvPfv3x9OTk4AioNPly9fxrlz53D58mUoKioCACIiIhAaGoqZM2cCKM6SWbx4MaPRoUMHqKiowNXVFW5ublBRUUFMTAw0NDTEtuvRowfz36ampgCARo0aMf8NAG/evEFgYCBWr16NMWOKo9OWlpbIzc2Fr68vxowZg2rViuN/+fn5mD9/PgYOHFiRr4kVqampZWojAED9+pr/vz6lzLqq0uWTV9L9NufOhiAlORmOTnNYvZ9vx4BPunzyKs+6F86dQUpKMmbOKnuOD+hjxWRuqmtoYJHrMnTuUn5QPj09DbduXkfP3n1Qq5ZqmfXyegxI98dqki53mqTLra4sNbd6bMLxo8UDp9WqVUPvPn2xZJlbudufP3sGSkpK6NPPWkrX0u/re/yvfmd8hrpH8ZOfNmgDAGZmZjh79iyA4iyTtm3bonv37li1ahWzTEVFBW3btgUAhIeHY9euXXjx4gWysrIYnVevXokFbfT09JiADQDEx8cjMTERS5cuFcvKsbCwQLVq1fD48WO0bt1azNuyZcvw9u1bBAcHQ0VFRWxd6eyU2rVro27dujAzM2MCNgCgra3NTF0CigNHBw8exNGjR/H27Vvk5f1XZCohIQF6enpo06YN0tLS4OrqiiFDhjCBne9x69YtAEC/fv3EPp+lpSX27t2LpKQkNGnShFluZWX1Xc3KkJeXC6Wv0vqB4hRHAMjLzZUbXT55Jd3yiY+LxcZ1a2Bi2h6/Dh3OSoNvx4BPunzyKq+68fFx2LRhDYxNTDH412Fl1nvt3ANhnhDx8bE4f/YMcnJyvunlyuWLyM/Plzg1qrJevwXpcqfLJ6980+WTV9KVveaEiXbo268/UlNScPHiBRQWFSE/P1/itllZWbh+7W/80t0KampqUvuWZl8V4X/1OyOIH81PHbSxsLDArl27kJycjKioKJiZmcHMzAwfPnzAq1evEBUVBRMTEygqKiImJgaOjo7o3bs3pk2bhnr16kEgEGD06NFiARAAqF+/vti/P3/+DACYNWuWRB9JX82R3Lt3L86fPw9/f380bdq0zPa1a9cW+7eSklKZC7OioqJYvZqDBw9i8+bNmDp1Kjp16gQ1NTU8evQIa9asYfx36dIF7u7uOHToEOzt7aGsrAxra2ssXboUGhoa5R7Hz58/QyQSoXM56ZOlgzYqKiqoVatWuVqyQFm5RplaPQCYz6lco4bc6PLJK+lK5kNqKpwcZ0BVtTa2bNsBBQUFVjp8OwZ80uWTV3nU/ZCairmzis9x962Sz3Fzi+Lrf9du3WHVszfGjBiCmjVrYsxvEyRqXjh3Burq6ujarbtMvX4P0uVOl09e+abLJ6+kK3vNljq6aKmjCwAYMnQYZkybgtmzZuL3I8cg+CotIuzyReTl5ZUbEJflvirC/+p3RhA/mp86aGNqagpFRUVERkYy06Q0NDTQunVrREZGIjIyEsOGDQMAhIWFQVVVFdu3b2em+iQmJkrU/fqiVhLwcHNzg7GxcZntGzRowPx3eHg4PD09sXjxYnTp0kUGn7KY0NBQ9OrVCwsXLmSWxcaWLSY5dOhQDB06FJ8+fcKVK1ewceNGVK9eHRs2bChXW11dHQKBAH/88YdYtk8JpWvysLngS4umpiZSkpPLLP/wIfX/1zcos66qdPnklXTLkpmZCceZ05CZkYkDh35Hg/9vb8wGvh0DPunyyau86Zac41mZGdgX8DvTwvtbNGvWHPoGhrhw7ozEoE1S0jvcj76HEaNGS/zNYOu1IpAud7p88so3XT55JV3uNEvo29caa1e74fWreGi31BFbd/7sGdSuXRvde/RkrV/RfVUE+s74B82O4ic/bSFiAKhZsybatGmDoKAgpKWloWPHjgAAc3NzhISE4O3bt0wR4tzcXCgqKooFHUq6Nn0PHR0daGlpISEhAe3atSvzatiw+CY4Li4OCxcuxJAhQzBp0iSZftYS/6X5lv+6devCxsYGXbt2RVypbjiKioplMotKgktpaWkSP9/XBb24Rt/AAK9fvxKbwgYAj2IeAgAMDAzlRpdPXklXnLy8PMyZNROvX7+C904/6JaqSSVPXkmXX17lSbf0Ob7dxw86uhU/x/Py8srsp4SLF85BJBJhwMDyR4Ll5RiQ7s/plW+6fPJKutx6BYqn8QBAZqa4dmpqCiIj7qJ3334Sp/nIcl8Vhb4zgvgx/NRBG6C4rk1ERAQMDAyY4ELJMkVFRbRv3x5AcR2Z1NRUrF27Frdv38bOnTtx8uTJCu1DIBDA1dUVhw8fhpubG/766y/cvn0bwcHBmDNnDuLj4wEADg4OqFGjBkaOHIkHDx4wr5cvX1b6c1paWiIsLAyBgYG4ceMGXFxc8Pr1a7FtvLy8sGbNGoSGhiIyMhK///47rl+/LjbtSUdHB1euXEFERAQePXqErKwstGzZEuPHj4eLiwt27dqFW7duITw8HAcPHoSjo2OlvUtLn379UVhYiOBjQcwyoVCI0ydPoJ2xCbRK1Ruqal0+eSXd/ygsLITLwnmIefgAWzx3wMS0PSudH+GVdPnlVV50vz7HjU3KnuMFBQXIyEgvs/zxoxi8fPEv2rRpK9FH6Pmz0GrUGKYdOsrEqzSQLne6fPLKN10+eSVd2Wl+/PixzLL8/HycCTmNGjVqQFdXV2xd6PnzKCoqwkAWU6Ok3VdF+V/7zgiiqvipp0cBxXVt/P39mYwaAEy3qLZt26LG/89ftLKygrOzMwIDA3HixAl06NABu3fvhrV1xSqzDxgwAGpqavDz82MyXJo0aYJu3boxNXBevXoFALC1tS3j8fDhw5X6nLNmzcLnz5/h5eUFALC2tsby5cuZ7lIA0K5dOxw8eBAXLlxAVlYWtLS0YG9vDwcHB2YbNzc3bNiwAdOmTUNubi4OHTqETp06Yfny5WjZsiWCgoLg6+uLWrVqoWXLlujfv3+lfLPB2NgE/az7w2u7Jz59/IhmzVvgzOmTePcuEavWrv++wA/U5ZNX0v2Pre6b8PfVv2DVoyfS09Nw9sxpsfWDhwyVG6+kyy+v8qL79Tl+/myI2PqBg39FTnY2BvbtiX79B0BHtxVUVFTw8sW/CDl1Eqqqqpg6wwFf8/LFv3jx73NMsp/2zemy8nAMSLfqNUmXf15JV3aaa1e74UtWFjqamaNBg4b48CEV58+dQXxcHBYuckXNr2pEnj8XAs0GDWBu0Ulqv9Luq6L8r31nPwPUPYqfCEQikaiqTRDE1+QWfHt9Xl4efL2349yZM8jISEdrPX3Mmj0XXX/pVqn9cqHLJ6+kW4z9pImIiowod/3DJ89Z6fLpGPBNl09e5UH3e+f4vZhnyM8XYofnFkRF3sW7d4nIy82DZgNNWHSyxNTpM9G4SdlC+t47tiLAfy+OHD+N1nr6qK5Q/t1hVR8D0pUPTdLln1fSlY3mhfPncOrEcbz491+kp6ehZs1aaGNkhN/GTUCPXr3Ftn0VH4ehgwdgot1kOLu4Su1Vmn1Jy//Cd1bjJ0pzSEovW4xZXmikLptpfz8jFLQh5JLvBW0IgiAI2VFQyM2twLeCNgRBEATBByho82OgoE35/ESnIEEQBEEQBEEQBEEQkhBQ/yhe8tMXIiYIgiAIgiAIgiAIguAjFLQhCIIgCIIgCIIgCIKQQ2h6FEEQBEEQBEEQBEH87NDsKF5CQRuCIAiC+B+HCgYTBEEQBEHIJzQ9iiAIgiAIgiAIgiAIQg6hoA1BEARBEARBEARBEIQcQkGb/xFcXV0xePBgmet6e3ujffv2Mtf9HkKhENu2eqBPj19g0cEY48fa4Patm3KpyyevpMs/r6TLP6981C3N3t27YGKkjxFDK/ebwrdjQLr88so3XT55JV3+eSVdbr3yCYEcv4jyoaANwUtWLHVF4KEADBw8BC6uy6CgoAAnh+mIvhcld7p88kq6/PNKuvzzykfdEpLfv8e+vbuholKz0lp8Owakyy+vfNPlk1fS5Z9X0uXWK0Fwjoj4n2Dx4sWiQYMGyVzXy8tLZGpqKnPdnPzyXxH3Hor09PREfnv2McvSsnJFvXv3EdmMHvPN9/5oXT55JV3+eSVd/nnlo27p1+y580QTJtqKxo2fIBowcJDceSVd7nT55JVvunzySrr880q6ldf8mXifLpTbF1E+lGnzE5CVlYWePXtizpw5Ysvd3NzQqVMnJCcnS3zf8+fPYW9vD1NTU3Ts2BFz5szBu3fvxLYpKirCgQMHMGDAALRt2xZdu3bFnDlzkJmZWa4fHx8fmJiYIDw8vPIfTgJhl0KhoKCAkTZjmGXKysoYPnIUHj64j/dJSXKjyyevpMs/r6TLP6981C3hXlQkwi5dhIvr0krpAPw7BqTLL6980+WTV9Lln1fS5dYr3xAI5PdFlA8FbX4CVFVVsWHDBly6dAmnTp0CAISHhyMoKAgrV65Ew4YNy7wnKSkJEyZMwOfPn+Hh4YHVq1fjyZMnmDBhArKyspjt1q5dCw8PD/To0QN+fn5wc3NDrVq1kJ2dLdHL5s2b4e/vjz179sDKyoqTz/vs2T9o0UIbqqqqYsvbtjNm1suLLp+8ki7/vJIu/7zyURcACgsLsWn9WgwfOQqt9fRZ65TAt2NAuvzyyjddPnklXf55JV1uvRLEj6B6VRsgZEOXLl0wYcIErFu3Dvr6+li2bBkGDx6MgQMHStw+ICAABQUF2L9/PzQ0NAAAhoaGGDRoEE6ePImJEyciPj4ef/75J+bPn48ZM2Yw77W2ti6jJxKJsGrVKly4cAEBAQEwMTHh5HMCQGpqKuprapZZXr++5v+vT5EbXT55JV3uNEmXW10+eeWjLgAcCzqCpKR32O0fwFqjNHw7BqTLL6980+WTV9LlTpN0udXl8jeSILiGMm1+IpydnaGpqYnRo0ejWrVqcHNzK3fbqKgodOrUiQnYAICuri4MDAxw7949AMCdO3cgEokwatSob+5XJBLBxcUFly9fxqFDhzgN2ABAXl4ulJSUyixXVlYuXp+bKze6fPJKutxpki63unzyykfdtLTP2OnjhWkzHVG3bl1WGl/Dt2NAuvzyyjddPnklXe40SZdbXa688g2BHP+PKB8K2vxE1KhRA3369IFQKMTgwYOhrq5e7rYZGRmoX79+meX16tVDeno6ACAtLQ3Vq1dHvXr1vrnf/Px8/PXXX+jYsSP09PQq9yEqgLJyDQiFwjLL8/LyitfXqCE3unzySrrcaZIut7p88spHXR+v7VBXV8e4cRNYvV8SfDsGpMsvr3zT5ZNX0uVOk3S51eXKK0H8CCho8xPx7NkzHDhwAG3atEFgYCBiY2PL3VZdXR0fP34ss/zjx49MsEdDQwMFBQUStyuNkpISdu/ejRs3bmDVqlWV+gwVQVNTEx9SU8ss//Ah9f/XN5AbXT55JV3uNEmXW10+eeWb7uvXrxB87Ch+mzARKakpSEx8i8TEt8jLy0NBQT4SE98iPS1NLrySLre6fPLKN10+eSVd7jRJl1tdrrwSxI+AgjY/CUKhEC4uLjA2NkZQUBBat24NFxcXFBQUSNy+Y8eOuHPnDpNVAwBxcXF4/vw5OnbsCADo3LkzBAIBgoODv7t/MzMz7Ny5E6dOncL69etl86HKQd/AAK9fvxIrmAwAj2IeAgAMDAzlRpdPXkmXf15Jl39e+aabkpyMoqIibN6wDgP79WZej2Ie4vWrVxjYrzd27/KVC6+ky60un7zyTZdPXkmXf15Jl1uvvEMgxy+iXCho85Pg5eWFhIQEbNq0CUpKSnB3d8eLFy+wa9cuidtPmjQJ1atXx5QpUxAWFoZz585hxowZaNSoEYYPHw4AaNmyJcaOHYsdO3bAw8MDN27cQFhYGJYvXy6xjXiXLl3g7e2NP//8E56enpx91j79+qOwsBDBx4KYZUKhEKdPnkA7YxNoNWokN7p88kq6/PNKuvzzyjfdVq1bY5uXb5mXbqvWaNSoMbZ5+WL4yG/XPftRXkmXW10+eeWbLp+8ki7/vJIut14J4kdA3aN+AqKjo+Hv74+VK1eiefPmAIqLCi9YsIBp1/01jRo1wuHDh+Hu7g5nZ2dUq1YNXbt2haurq1grPDc3NzRt2hTHjh3DwYMHoaGhAXNzc9SqVUuiFysrK2zfvh1z586FsrIyZs2aJfPPa2xsgn7W/eG13ROfPn5Es+YtcOb0Sbx7l4hVa9ln+XChyyevpMs/r6TLP698061Tpy569e5TZvnvhw8CgMR1VeWVdLnV5ZNXvunyySvp8s8r6XLrlSB+BAKRSCSqahME8TW5kmd1MeTl5cHXezvOnTmDjIx0tNbTx6zZc9H1l26V2i8XunzySrr880q6/PPKR92vsZ80EZ8/f8aJ02dZa/DtGJAuv7zyTZdPXkmXf15Jt3KaNX6iNIcPWd95yKpC6qv+RAdaxlDQhpBLvhe0IQiCIAiCIAiC4BoK2vwYKGhTPlTThiAIgiAIgiAIgiAIQg6hcBZBEARBEARBEARB/OQIqEsTL6FMG4IgCIIgCIIgCIIgCDmEgjYEQRAEQRAEQRAEQRByCE2PIgiCIAiCIAiCIIifHAFofhQfoUwbgiAIgiAIgiAIgiAIOYSCNgRBEARBEARBEARBEHIIBW0IXiIUCrFtqwf69PgFFh2MMX6sDW7fuimXunzySrr880q6/PPKN93sL1+w08cLDtPt0a2LBUyM9HH65Am59Eq63OryySvfdPnklXT555V0ufXKJwQC+X0R5UNBG4KXrFjqisBDARg4eAhcXJdBQUEBTg7TEX0vSu50+eSVdPnnlXT555Vvup/TPmP3Ll/Ex8VBT1+/Uv649kq63OryySvfdPnklXT555V0ufVKEJwjIgg5JCe//FfEvYciPT09kd+efcyytKxcUe/efUQ2o8d8870/WpdPXkmXf15Jl39e+aib/iVPlPAuRZSTLxJF3Y8R6enpiY4cDWatx8djQLr88so3XT55JV3+eSXdymv+THz6UiC3L6J8KNOG4B1hl0KhoKCAkTZjmGXKysoYPnIUHj64j/dJSXKjyyevpMs/r6TLP6981FVSUkJ9TU1W7y0Pvh0D0uWXV77p8skr6fLPK+ly65UgfgQUtJETsrKy0LNnT8yZM0dsuZubGzp16oTk5GS8ePEC06ZNQ6dOnWBiYgJra2vs3buX2dbV1RWDBw/G3bt3MWzYMJiammLUqFF4/PixmGZeXh42btyIX375Be3atcPQoUNx+fLlMp4uXbqEoUOHol27dvjll1+wceNG5OXlMevv3r0LfX19hIeHw8nJCaampvjll1/g5+cn46MjzrNn/6BFC22oqqqKLW/bzphZLy+6fPJKuvzzSrr888pHXS7g2zEgXX555Zsun7ySLv+8ki63XgniR0BBGzlBVVUVGzZswKVLl3Dq1CkAQHh4OIKCgrBy5Uo0bNgQM2fOREZGBtavX4/du3fD3t4eOTk5YjqpqalYt24d7O3tsX37duTl5cHJyQn5+fnMNs7OzggKCsLUqVPh6+uLVq1aYfbs2bhy5QqzzZUrVzBnzhy0atUKvr6+mDp1Ko4cOYJFixaV8b5ixQo0a9YM3t7eGDJkCLZt24Y///yTmwP1/59R0qhv/fqa/78+RW50+eSVdLnTJF1udfnklY+6XMC3Y0C6/PLKN10+eSVd7jRJl1tdPv1GEsTXVK9qA8R/dOnSBRMmTMC6deugr6+PZcuWYfDgwRg4cCA+ffqEt2/fYtmyZejVqxcAoHPnzmU00tPTERgYiNatWwMAVFRUYGtri4cPH8LMzAzPnj3DpUuXsHr1aowdOxYA0L17dyQmJsLX1xe9e/cGAPj4+MDU1BRbt25ltlFRUYGbmxueP38O/VLFKDt37ozFixcDALp164aPHz9i165dGDNmDKpVk31cMC8vF0pKSmWWKysrF6/PzZUbXT55JV3uNEmXW10+eeWjLhfw7RiQLr+88k2XT15JlztN0uVWl0+/kVxCXZr4CWXayBnOzs7Q1NTE6NGjUa1aNbi5uQEA6tSpgyZNmsDT0xMnT57E+/fvJb6/QYMGTMAGAFq1agUASE5OBgDcu3cPANC/f3+x9w0YMABPnz5FdnY2vnz5gn/++QfW1tZi2wwcOFBMo4S+ffuK/dva2hrJycnleqwsyso1IBQKyywvmbqlXKOG3OjyySvpcqdJutzq8skrH3W5gG/HgHT55ZVvunzySrrcaZIut7p8+o0kiK+hoI2cUaNGDfTp0wdCoRCDBw+Guro6AEAgEMDf3x86OjpYs2YNrKysMGLECERGRoq9X01NTezfioqKAP67IKWnp0NRUREaGhpi29WvXx8ikQiZmZnIzMyESCRCvXr1xLapXbs2lJSUkJ6eLra8bt26ZbSA4jRELtDU1MQHCdofPqT+//oGcqPLJ6+ky50m6XKryyevfNTlAr4dA9Lll1e+6fLJK+lyp0m63Ory6TeSIL6GgjZyxrNnz3DgwAG0adMGgYGBiI2NZda1bNkSXl5eiIiIwOHDh6GkpISZM2fiy5cvFdZXV1dHfn5+mcDLhw8fIBAIULt2bdSuXRsCgQCfPn0S2yYzMxNCoZAJJJXw9XYfPnwAUHxx5AJ9AwO8fv0KWVlZYssfxTwEABgYGMqNLp+8ki7/vJIu/7zyUZcL+HYMSJdfXvmmyyevpMs/r6TLrVe+IZDj/xHlQ0EbOUIoFMLFxQXGxsYICgpC69at4eLigoKCArHtFBUVYWFhgenTpyMrKwspKRUvnNWxY0cAQGhoqNjy0NBQtGnTBjVr1kStWrVgaGhYZpsLFy6IaZTwdeepixcvokGDBtDS0qqwL2no068/CgsLEXwsiFkmFApx+uQJtDM2gVajRnKjyyevpMs/r6TLP6981OUCvh0D0uWXV77p8skr6fLPK+ly65UgfgRUiFiO8PLyQkJCAk6fPg0lJSW4u7tj+PDh2LVrF/r27YvNmzdj4MCBaNasGbKysrB79240adIEzZs3r/A+DAwM0K9fP2zatAm5ublo2bIlQkJCcP/+fezcuZPZzsnJCbNmzYKzszN+/fVXxMfHY9u2bbC2thYrQgwAd+7cwebNm9G1a1fcvHkTp0+fhpubGydFiAHA2NgE/az7w2u7Jz59/IhmzVvgzOmTePcuEavWrpcrXT55JV3+eSVd/nnloy4A/Pl7IDIzM5D6/4ME4X9fRXJycd2y38ZPRO3ateXCK+lyp8snr3zT5ZNX0uWfV9Ll1itB/AgEIpFIVNUmCCA6Ohrjx4/HypUrma5OABAQEAAPDw/8+eefOHz4MO7fv4/k5GTUrl0bZmZmWLBgAbS1tQEArq6uePz4Mc6ePcu8PyMjA+bm5ti4cSNGjBgBAMjNzYWnpyfOnz+PtLQ06OjowMnJCf369RPzdPHiRfj6+iIuLg4aGhoYOHAgFi5cyFRZv3v3LmxtbbF7924EBQXh9u3bqFWrFsaPHw9HR8dKHY/cgm+vz8vLg6/3dpw7cwYZGeloraePWbPnousv3Sq1Xy50+eSVdPnnlXT555WPugP69sK7d4kS152/dAVNmjSVG6+ky50un7zyTZdPXkmXf15Jt3KaNX6iNIeM3KKqtlAuajVoElB5UNCGYE1J0Ob48eNo166dTLW/F7QhCIIgCIIgCILgGgra/BgoaFM+dGQIgiAIgiAIgiAIgiDkkJ8obkgQBEEQBEEQBEEQhCSoRxM/oelRhFxC06MIgiAIgiAIgqhqfqbpUZlyPD2qNk2PKhc6MgRBEARBEARBEARBEHLITxQ3JAiCIAiCIAiCIAhCIjQ/ipdQpg1BEARBEARBEARBEIQcQkEbgiAIgiAIgiAIgiAIOYSCNgQvEQqF2LbVA316/AKLDsYYP9YGt2/dlEtdPnklXf55JV3+eeWb7suXL+A8fw4GWvdGp44msOraCZNtx+Pvq3/JnVfS5VaXT175pssnr6TLP6+ky61XPiGQ4/8R5UNBm5+QsLAw/P7771Vtg1NWLHVF4KEADBw8BC6uy6CgoAAnh+mIvhcld7p88kq6/PNKuvzzyjfdpHfv8OXLF/w6dDhcXJdh+kxHAMBcJwccPxokV15Jl1tdPnnlmy6fvJIu/7ySLrdeCYJzRMRPx+LFi0WDBg2qahuVIie//FfEvYciPT09kd+efcyytKxcUe/efUQ2o8d8870/WpdPXkmXf15Jl39e+agr6ZWVWyAaMuRXUT9ra7nySrrc6fLJK990+eSVdPnnlXQrr/kzkZlbJLcvonwo04b4Lrm5uVVtQYywS6FQUFDASJsxzDJlZWUMHzkKDx/cx/ukJLnR5ZNX0uWfV9Lln1c+6kpCQUEBDbUaITMjk9X7+XYMSJdfXvmmyyevpMs/r6TLrVeC+BFQ0IZnZGVloWfPnpgzZ47Ycjc3N3Tq1AlTpkzByZMn8eLFC+jr60NfXx+urq7Mdvfv34etrS1MTU3RsWNHLFy4EB8/fmTWv337Fvr6+jhx4gSWL1+OTp06wcbGBgCgr6+PPXv2YNu2bejSpQvMzMzg7u4OkUiE27dvY+jQoWjfvj3s7OyQxOGF79mzf9CihTZUVVXFlrdtZ8yslxddPnklXf55JV3+eeWjbgnZ2dn4/PkTEt68weGDAbh54xo6de4sV15JlztdPnnlmy6fvJIu/7ySLrde+YZAIL8vonyqV7UBQjpUVVWxYcMGTJ48GadOncKwYcMQHh6OoKAgbNu2DW3btsW6desQFxeHLVu2AADq1q0LoDhgM3HiRFhZWWHbtm3IycnB9u3b4ejoiKAg8boEnp6esLKywtatW1FUVMQs//3332FhYQF3d3c8fPgQ3t7eKCoqws2bN+Hg4ABFRUWsW7cOy5Ytw/79+zk5BqmpqaivqVlmef36mv+/PkVudPnklXS50yRdbnX55JWPuiVs9djE1LCpVq0aevfpiyXL3Fhp8e0YkC6/vPJNl09eSZc7TdLlVpfr30iC4BIK2vCQLl26YMKECVi3bh309fWxbNkyDB48GAMHDgRQHKR59+4dTE1Nxd63detWtG3bFj4+PhD8fzhTT08PgwcPRnh4OKysrJhtDQwMsH79+jL7btCgATw8PAAA3bp1w19//YWAgACcO3cOurq6AIDk5GSsXbsWGRkZUFNTk/nnz8vLhZKSUpnlysrKxetZTufiQpdPXkmXO03S5VaXT175qFvChIl26NuvP1JTUnDx4gUUFhUhPz9frrySLne6fPLKN10+eSVd7jRJl1tdrn8jCYJLaHoUT3F2doampiZGjx6NatWqwc3t26OdOTk5iI6ORv/+/VFYWIiCggIUFBRAW1sbjRo1wqNHj8S279Gjh0QdS0tLsX+3bNkSDRo0YAI2AKCtrQ0AeP/+vfQfrAIoK9eAUCgsszwvL694fY0acqPLJ6+ky50m6XKryyevfNQtoaWOLjp3scSQocPgs3M3srOzMXvWTIhEIrnxSrrc6fLJK990+eSVdLnTJF1udbn+jeQLAjl+EeVDQRueUqNGDfTp0wdCoRCDBw+Gurr6N7fPyMhAYWEhNm7cCCMjI7HXu3fvytSgqVevnkSdrzNnFBUVJS4D/rsIyhpNTU18SE0ts/zDh9T/X99AbnT55JV0udMkXW51+eSVj7rl0bevNZ48foTXr+Klfi/fjgHp8ssr33T55JV0udMkXW51f/RvJEHIEgra8JRnz57hwIEDaNOmDQIDAxEbG/vN7WvXrg2BQICZM2fi+PHjZV4ODg5i2wvkuBqUvoEBXr9+haysLLHlj2IeAgAMDAzlRpdPXkmXf15Jl39e+ahbHnl5xankmZlZ39myLHw7BqTLL6980+WTV9Lln1fS5dYrQfwIKGjDQ4RCIVxcXGBsbIygoCC0bt0aLi4uKCgoAFCc6fJ1lkvNmjVhamqKuLg4tGvXrsyradOmVfFRWNGnX/EUr+Bj/xVPFgqFOH3yBNoZm0CrUSO50eWTV9Lln1fS5Z9XPuqW7jBYQn5+Ps6EnEaNGjXEpsdWtVfS5U6XT175pssnr6TLP6+ky61X3lHVc6BofhQrqBAxD/Hy8kJCQgJOnz4NJSUluLu7Y/jw4di1axdmz54NXV1dBAcH4+zZs2jRogXq1KmDpk2bwsXFBXZ2dpg3bx4GDRoENTU1vH//Hrdu3cKIESPQqVOnqv5oFcLY2AT9rPvDa7snPn38iGbNW+DM6ZN49y4Rq9aWLZ5clbp88kq6/PNKuvzzykfdtavd8CUrCx3NzNGgQUN8+JCK8+fOID4uDgsXuaJmrVpy45V0udPlk1e+6fLJK+nyzyvpcuuVIH4EAhGbCoJElREdHY3x48dj5cqVGDt2LLM8ICAAHh4eOHLkCFq2bAk3NzfcvHkTaWlpGD58ODZt2gQAePToEby9vREdHY38/HxoaWmhc+fOcHBwgJaWFt6+fYvevXtjx44d6N+/v9i+9fX14eLiAnt7e2aZq6srHj9+jLNnzzLL7t69C1tbWxw/fhzt2rVj9TlzC769Pi8vD77e23HuzBlkZKSjtZ4+Zs2ei66/dGO1Py51+eSVdPnnlXT555VvuhfOn8OpE8fx4t9/kZ6ehpo1a6GNkRF+GzcBPXr1liuvpMutLp+88k2XT15Jl39eSbdymjV+ojSH7Hz5ffSvqUjpNuVBQRtCLvle0IYgCIIgCIIgCIJrfqagTU5+VTsoHxVF9u+NjY3FunXrcP/+fdSqVQtDhw7FvHnzJLZ55yM/0SlIEARBEARBEARBEMT/Cunp6bCzs4O2tja8vb2RnJyMTZs2ITc3F25ublVtTyZQ0IYgCIIgCIIgCIIgCN5x5MgRfPnyBT4+PtDQ0AAAFBYWYvXq1ZgxYwYaNmxYtQZlAHWPIgiCIAiCIAiCIIifHIFAfl9suXbtGrp06cIEbABgwIABKCoqws2bNyt/0OQACtoQBEEQBEEQBEEQBME74uLioKOjI7ZMTU0NmpqaiIuLqyJXsoWmRxEEQRAEQRAEQRAEUWX07v3tjpRXrlyRuDwjIwNqampllqurqyM9PV0m3qoaCtoQcsnPVKWdIAiCIAiCIAiiqqFnLH5CXxtBEARBEARBEARBEFVGeZk030NNTQ2ZmZlllqenp0NdXb2ytuQCqmlDEARBEARBEARBEATv0NHRKVO7JjMzE6mpqWVq3fAVCtoQBEEQBEEQBEEQBME7unfvjlu3biEjI4NZFhoaimrVqqFr165V6Ex2CEQikaiqTRAEQRAEQRAEQRAEQUhDeno6Bg0ahJYtW2LGjBlITk7Gpk2bMGTIELi5uVW1PZlAQRuCIAiCIAiCIAiCIHhJbGws1q5di/v376NWrVoYOnQo5s+fDyUlpaq2JhMoaEMQBEEQBEEQBEEQBCGHUE0bgiAIgiAIgiAIgiAIOYSCNgRBEARBEARBEARBEHIIBW0IgiAIgiAIgiAIgiDkEAraEARBEARBEARBEARByCEUtCEIgiAIgiAIgiAIgpBDKGhDEARBEARBEARBEAQhh1DQhiAIgiAIgiAIgiAIQg6hoA1BEARBEARB/ARs3LgRSUlJAIDIyEh8+fKlih0RBEEQlYWCNgTBY5KSkhAdHY3s7OyqtkIQBFElZGVlQSQSVbUNQo7o3bs3nj17JnHdv//+i969e1d6Hx8/fsS7d+/KvKqaQ4cOITU1FQBga2uL2NhYme8jLS3tm+v//fdfmezn7du3uHXr1nf39y24+Pxc8u7dO+Tn50tcV1BQIPU5lpeXhwMHDsjsOynNtWvXvrl+165dld7H+/fvERMTg/fv31daiyD4TPWqNkAQFSUtLQ2pqalo2rQpVFRUyqzPysrCP//8A3Nzc1b6QqEQSkpK5a5PTk5Gw4YNpdJcu3YtzM3NYWZmhvr167PyJYmgoCD4+Pjgw4cPAIDjx4/DyMgIs2bNgoWFBezs7Cqk4+PjI9V+nZycpPb6I8jMzMTz58+RmpoKTU1N6Ovro3bt2nKnyTVJSUlISkqCgYEBatasWdV2vsvHjx+Rl5dXZnnjxo2rwA3BV8zNzREUFARjY2PY2tpi5cqV0NXVrWpbcoNIJEJKSgrq1auH6tXl77bPx8cHNjY2En9fU1JScPToUal/exITEyEUCiWuy83NZf0A+PnzZ6xbtw6XLl1CQUGB2DqRSASBQIB//vmnQlpPnjyRat9GRkYV2q5evXp4+PAhjI2NOQtm2tvb49ChQ6hVq1aZdY8ePcLUqVNx9+5dqTQ3bdqEwsJCLFu2DABw+fJlzJ8/HwUFBVBXV4e/vz/atm0rtddBgwbB1NQUo0aNwsCBA2X22/jixQv4+fkhJiaGuU8wMTHBjBkz0Lp1a9a6vXv3Zq5nX/Ps2TPY2NhU+BwDAGVlZWzfvr3C5480zJkzB/v27YOZmVmZddu2bYO/vz8cHBxYaQcFBWHXrl1ITk5mljVo0AAODg4YO3Ysa89ZWVl4//69xHsPLo4RQcgK+fv1JoivKCgogJubG06dOgWRSAQlJSX89ttvmDdvHmrUqMFsFxsbC1tbW6l+zErj5OSEnTt3SrypTUhIwOTJkxEWFiaV5uPHjxEUFITCwkI0b96cCeCYmZmhadOmrHwGBARgy5YtmDx5Mrp06YIpU6Yw6ywsLBAaGlrhoM3BgwfF/p2fn4/c3FwAxT/0JT9qNWrUgJKSklQ3zuvWravwtgCwfPlyqbYHgKKiImzfvh2HDx9GTk4Os1xFRQUTJkzAvHnzoKCgUGWaS5YskWrfGzdulGr7EmQVxJPEzZs38fDhQ+am1NTUFJaWlqz1ZPnQU5pPnz7h4MGDYl5NTExgZ2eHunXrVljH1tZWqv0eOnRIWqsAiv/Wjh8/jkePHuH9+/dwc3ODtrY2zp8/D319fdZBh/z8fJw8ebLMdzZs2DAoKipWWIeLB8oDBw5UWE8gEGDSpEkV2rb0tSoiIkJm00F+VFBbVufu11y/fh3e3t54+vQpioqKcOzYMRgZGWHFihUwNzfHr7/+KpXetWvXkJGRgcGDBwMoDhIvXboUsbGxsLS0hJubG6sHYl9fX3Tv3r3coI2vr2+Fjm1eXh5ycnKYQEVWVlaZDI28vDyEhYWhQYMGUvsEin+nIiMjMWPGDOjq6kr1N/U1I0eOhEAg+O520l4Xf/31V6xfvx4bNmyAQCDAmDFjvrk923umGTNmYN++fWL3Yffv38e0adPQvXt3qfUuX76MOXPmMP/29PSElZUV5s6dC3d3d2zfvh379u2TWnf37t04ceIEVq9ejQ0bNqB///4YNWoUOnToILVWCX///TecnJygpaWFPn36oF69evj48SPCwsIwfPhw+Pj4oEePHqy0vxVo+97gYnkYGhri5cuXsLCwYOWpPKZOnYoZM2YgICAA7dq1Y5Zv2LABR44cwfbt21np7t69G9u2bcPQoUNhbW2N+vXr48OHDwgNDcXq1auRnp6OGTNmSKWZnJyMpUuX4tatW2XWVebegyB+FBS0IeSegwcP4vz585g7dy4MDQ1x7949HDp0CLdv38aePXukzn4pj/j4eCxcuBDbt28Xu5F69eoV7Ozs0Lx5c6k1g4KCkJubi+joaERGRiIqKgpnzpyBUCiElpYWzMzM4OHhIZVmYGAgHB0d4ejoiMLCQrF1LVu2RHx8fIW1IiMjmf9+9OgR5s2bB0dHR1hbW0NVVRVZWVkIDQ3Frl27sG3bNql8/vXXXxXeViAQsArauLu7IzAwENOnTy/zw753717k5+fD1dW1yjS/vgFITk7G58+foa6uztzkpaeno06dOtDS0pLKZwmyDOKVJjU1FbNnz8aDBw/E/Hp5ecHU1BTe3t7Q1NSUWleWDz0lPHz4EFOnTkVRUREsLS2hra2Njx8/IjAwEIGBgdi/fz9MTEwqpKWqqir29//o0SN8+PABBgYGzDF49uwZNDU1xW5SpSEhIQGTJk3C58+f0aZNG9y7d48JNERGRuL69eusAnjx8fGYOnUqk21Vr149/PPPPzh58iR27dqFffv2QUdHp0JaXDxQbt68uUL7BqQL2ujr68Pd3Z15UDx27Fi5afsCgQCzZs2qkC6XQe0SZHnulubs2bNYtGgRBgwYABsbG6xYsYJZ16xZM5w4cULqoI2XlxcGDBjA/HvNmjWIjY3FoEGDEBISAi8vL6mvt8C3H1JTU1OhpqZWIZ29e/fC19cXQPH3bG9vX+62bANsd+/exfLlyzFs2DBW7y8N24Dv93BxcUG3bt0QGxuLdevWwc7OTubZi/v27YOtrS1mzZoFPz8/KCoq4s6dO3BwcIC1tTU2bNggtWZqairj882bN4iPj4eHhwf09PQwceJELF68mJVXKysrWFlZIS0tDSEhITh58iTGjRsHbW1tjBo1CsOGDZM6E9rd3R3dunWDr68vqlX7r9KEi4sLHB0d4e7uLlXQJjY2Vmwa1927d8tkg+Xl5eHcuXNo1qyZVF4BYOnSpVi0aBHq1q0LKysridnqbHBycsKXL18wdepUHD58GHp6enBzc8Pp06fh4+PDKngHAIcPH4a9vT0WLVoktrxXr16oV68eDh8+LHXQZvHixXj16hWWL18ObW1tmdx7EMQPRUQQcs7AgQNFe/bsEVsWHx8vGjx4sMjKykr04sULkUgkEj148EBkYGDAej9v3rwRde/eXeTq6sos+/fff0WWlpaiKVOmiHJyclhrl5Cbmyv6+++/RRMmTBDp6+uz8tu2bVvRrVu3RCKRSFRQUCDS19cXPX78WCQSiUS3bt0StWvXjpU3Gxsb0e+//y5xXWBgoGjkyJGsdLnEwsJCtHv3bonr/Pz8RBYWFnKhKRKJROHh4aKePXuKbt++Lbb81q1bop49e4r+/vtvVrq9e/cW+fr6ikSisudDeHi4qFOnTqx0HRwcRF27dpXot2vXriJHR0dWuh07dhSdPHmS1XvLY/jw4aKxY8eKMjMzxZZnZGSIxowZIxoxYgQr3ZMnT4oGDBggev36tdjyV69eiQYMGCA6ceIEK93p06eLRo0aJfr48aMoPz9f7Ds7d+6cqHfv3qx0J0yYILK2tpbot3///qKJEydWWOvu3btSvaqSJ0+eiH777TdRp06dRAYGBqL27duLzMzMJL7Mzc1Z7SMmJkbUq1cv0fHjx5nzLDMzU3Ts2DFRr169RA8fPmSly9W5O2DAANHGjRtFIlHZ68Jff/0lsrS0lFrTzMxMdOPGDZFIVPzZjYyMRBcuXBCJRCJRcHCwqGfPnhXWOnPmjGjGjBmiGTNmiAwMDETjxo1j/l3ymjx5ssjc3Fw0Y8aMCmn+888/ohMnToiCg4NF+vr6ou3bt4tOnDgh9jpz5ozo6dOnUn/2Eipzra4KJkyYIHr58iUn2ikpKaJ+/fqJZs2aJbpy5YrI2NhY5ObmxlrP0tKSOZ/++OMPsd/aW7duiUxNTSvtuYQnT56IJkyYIDIwMBAZGRmJZs6cWea37lu0a9dOFB4eLnFdeHi41Pdh3t7eIn19fea+sOS/v36Zm5uLwsLCpNIWiUQiU1NTkZGRkcjAwEBkYGAgMjU1FbVv3555dejQQWrN0ri5uYm6du0qmj17tsjU1FSqY1me35JrzdfcuHGD1blgamoqunz5cqV8EURVQpk2hNyTmJgIU1NTsWXa2tr4888/MWvWLIwbNw47d+6sdNS8WbNmOHDgACZOnIg1a9Zg5MiRmDJlCtq3bw8vLy9WKalfvnxhsmwiIiLw5MkTqKiooEOHDnB2dmaVqtq4cWM8evQIXbp0KbPu4cOH0NbWlloTKJ4rXd6UrWbNmuHFixesdLmksLCw3GkZRkZGZTKRqkoTADw8PDBnzhx07txZbHmXLl0we/ZseHh4wMrKSmrd5ORktG/fXuI6RUVF1kWqb926hVWrVkn06+zsjFWrVrHSVVNTQ506dVi9tzxevnyJHTt2QFVVVWx57dq1MW3aNMyfP5+V7s6dO7Fw4cIyWXYtWrTA7Nmz4enpieHDh0utGxERga1bt6Ju3bplzidNTU2miKi0xMTEwN3dXaLfOXPmSJUFIes0+tLk5eXBw8MDv/76q8S6DdLSpk0b/PHHHwAAAwMDBAQEyES3NGvXroW9vT1GjhzJLFNVVcWoUaOQl5eHNWvW4Pjx41LrcnXuJiQklHs9UVFRQWZmptSaBQUFTFZBSZZmt27dABT/RpRMz6wI+fn5THaZSCRCTk6OWMYCACgpKWHo0KGYOnVqhTQNDAxgYGAAoDjTxsrKqlLTyyRhb2+Pw4cPo2vXrnJZH6g0eXl5SE9PR1JSEic1njQ1NREQEIDx48fjypUrsLW1lXpKcGnMzMzg5eWFjx8/wt/fH3369GHWxcXFoVGjRpX2nJGRgZCQEJw4cQJPnz5Fu3bt0LdvX1y7dg2TJ0/GrFmzKpSFpa+vj7dv30pc9/btW6lr2tjZ2WH48OEQiUTo06cPfHx8YGhoKLaNoqIiNDU1K5QB+TVTpkxh9b6Ksnr1auTk5ODq1avw9/ev1NQzAPjll19w69YtdO3atcy6mzdvSrz//R4tWrQoMyWbIPiEfP/iEASAunXrSqyWr6qqin379mHhwoWwt7fHxIkTK70vHR0d+Pv7w9bWFseOHUOvXr3g6ekpdV2UEiwsLKCoqIju3btj0KBBWLlyJQwMDCr14zl69Gj4+PigTp066NevH4Dim+m///4b/v7+mDdvHivdJk2a4MiRI+jWrZuYP5FIhD/++KPS6dWfPn3C/v37mRoePj4+aN26NQ4ePAgTE5MygbmKYG1tjXPnzkn8YT937hz69u0rF5oA8Pr1a2hoaEhcp66ujjdv3rDS5SqIp6amBnV19XLXsS3KzMVDT4sWLZCRkSFxXWZmJqt0cqC4a0V5f6sCgUCsQKI0KCgolDsl5MOHD6wLZTZo0OCbfmVZDL0yKCsrIzg4mLl+yZJDhw5x8oDKVVCbq3NXU1MTcXFxEq8Lz58/Z3U919HRQUhICExMTBAUFIT27dszhWhTU1PLvb5JYvjw4UzAc+LEiVi1apVMvzc2wdSKEBcXh9jYWPTt2xfm5uYSp25VdKpvhw4dcOjQIbRt2xbt27f/7n1BdHS0VF6VlZWRnJxcJhjGlvLq1Onq6iI7OxuFhYVi20g75blkCs+WLVtgZGQkFrAMCQmRWOy2oty8eRPBwcG4cuUKlJWVMWTIEGzYsIEJ8k2fPh0BAQHYuXNnhYI2bm5uWLBgAVRUVNCnTx/Url0bmZmZuHz5Mg4cOICtW7dK5a927drMb+qVK1egqanJaqCwPGbPni0zrfLOVZFIhPz8fLEgq0AgwL1796Tex6hRo7By5Up8+vQJvXv3FqsZdOfOHaxevVqs7lpFaqotXrwYmzZtgr6+Plq2bCm1J4KoaihoQ8g9pqamuHDhAoYOHVpmnaKiInbs2IFVq1Zh3759UgdDyiuM2bVrV9y+fRvt2rVj5p1LU2OhBB0dHbx8+RIxMTFQUlKCkpISlJWVK1xXQhL29vZISkqCm5sbVq5cCQD47bffAADjxo3D+PHjWekuXLgQc+fORb9+/dCzZ0/mR/Lq1at49+4dduzYwdrzkydPMGnSJNSuXRvm5uaIiIhgOnskJycjICCAVcE6c3NzbNu2DRMnTixTDPDNmzeYP38+Ll26xGxfkYdELjQBoFWrVtizZw/Mzc3FOm5kZWVhz549aNWqlRSf/D+4CuLZ2dlhz549sLCwKON37969UhfsLUGWDz0lLFq0CGvWrEGjRo3EMkTu3r0LHx8fsXoe0mBsbIzt27fD0NBQ7OE5ISEBO3bsYFVrBCg+xw4cOIDu3bszD1QCgQAikQhHjx5lNYoIALNmzcKOHTsk+vX29q5U97dTp04hKCgIr169kth1Q9oHyvbt2+PBgwcyz+gprSfL7mRcBbW5OncHDx4Mb29v6OjoMLoCgQD//vsv9u3bx/xmSIOjoyPmzp2LU6dOoVq1ati9ezez7vr162jTpg0rr4cPH2b1vm+Rm5uLnTt34uLFi3j//r3ETlJsio5evXqV+f6joqLKrJemPtuUKVOYumBcZUL069cPFy5cqFTx+BK+VaeuZs2aYuvZ1Klr2LBhuXV+/P39WQcxevbsiffv36NDhw5YvXo1BgwYAGVl5TLbmZmZlRtA/RpbW1sUFBRg6dKlWLp0KapXr85kcVSvXl3sXlHawEWTJk0AFN8bJScnS7yGse2SClS+yyTXWTsAmHo1J0+exMmTJ5nfxxJmzpwJQLqaal26dIGlpSUGDRqEBg0alBl4EggECAkJkeGnIAjZIhCVN9xHEHLC7du3ceTIEaxevfqbI3l+fn64efOmVDeAJaMsFYFtZfm0tDRERUUhKioKkZGRePbsGTQ0NNCxY0dYWFhgwoQJUmsCxQ9it27dYgrbdunShXVWRQn//PMP9uzZI9bC0tjYGNOnTy+TqisNEyZMgIqKCnbu3AmBQIC2bdsiODgYRkZGuHjxIjZt2oSrV69KrcvF98fVOREdHY2pU6eiWrVq6NSpExMMunv3LgoLC7Fv3z507Nixwvsuzbp16/D7779DIBCgqKiICQSMGzdOqhvnr0dSL126hOzs7DJ+a9Wqhb59+7IqHt2rV69vrhcIBLhy5YpUmkOGDEFKSgoyMjJQu3Zt1KlTB58/f0ZmZibU1NTEOsVIc2MWGxuLKVOm4MOHD2jdujVzDF68eIF69erhwIEDrLIDYmNj8dtvv0FDQwO9evXCwYMHMWLECLx48QKvX7/GsWPHWBU+nzlzJp48eYJPnz5J9Fv6oVogEGDXrl0V0j19+jSWL1+O4cOH4+jRoxg5ciSKiorw119/QU1NDUOHDpU6IPTgwQM4Ozvjt99+g5WVFerVq1fmQUCazI0SuOpOFhYWhrlz56Jx48blBrVLT+eoKFydu0KhEHPnzsXVq1ehoaGBtLQ01KtXD58+fUKPHj3g7e3NKtMtISEBT58+hYGBAVq0aMEsDwoKgr6+foUzJg8cOIAhQ4agfv363+0qxmbAZMmSJTh79iwGDx5cbsHzynTV4wsnT56Ep6cn2rRpg+7du6N+/fpl/s64yHiTFW/fvsWbN2/Qpk0bVtcDoLgA+qhRo2SayeXt7S1V4EKa62NCQgIWLVqEhw8fAihbqJvtNayky2RqaioEAoFMu0zKmoiICKm2r0jw38PDA/7+/jAyMoK2trbEICDbDp4E8SOgoA1B/EAKCgpw9+5d+Pn5ITIyktWPb2RkJNq0aSOW/VBCdnY2njx5UqlRGC4wMTGBt7c3unfvztSMKQnaREZGwt7eHjExMVLrJiYmSrV9yQjWj9Ys4cOHDwgICCgTFLOzs2PViak0CQkJuHnzJtLS0lgH8b4XUCkNm+AKV7i6ukp1Ay3NjZlQKERwcHCZ72zEiBESR2srSkJCAnx8fMp8Z3PmzGEVsAEg9RTRiga4hw0bBmtra0yfPl3sbzcrKwv29vbo378/Jk+eLNW+SwdHy/vu2DyYzJo1C5GRkbC1tS33YZ1NcKXEj6yD2lyeuwBw584dseC+paVlpbIuZNWe3MDAAEePHoWxsfF3A+Vsfic7d+4MJycn1oMiPwtcHFuu2LRpEwoLC7Fs2TIAxS3A58+fj4KCAqirq8Pf3x9t27atYpfcY2dnhzdv3mDOnDnQ1dWVGFyQZnAJkNxlsuQ6fvDgQYSGhuLPP/+U2mtWVhays7PFgsslpKSkoFatWhLvVasCc3NzTJ48GY6OjlVthSBYQUEbgrdUNsXzRyAUCvHgwQOm3feDBw+Qm5uLevXqwczMDObm5lJPZzI0NERQUJDEQpuPHz+GjY0Nq5uwixcvwtzcXOaFG4HiG2g3NzcMHDiwTNDm9OnT2Lp1a7ktegmCqFrat28PPz8/dOrUCUZGRti/fz86deoEoDgDZcOGDd+cOiGJEydOfDdYwaYuiZmZmcxaMhPifN2evCTb6NatWxAIBPD392c9ZVDWdO3aFZs3b8Yvv/zCif7r16/LnSrINnPl9evXOHHiRLm6fn5+UmtWZBBCmoGHEg4fPozk5GQ4OzuXWbdlyxY0atRI6nub3r17Y86cOcxU+AEDBkBHRwdz586Fu7s7gOJW42yQVbDxa0QiEeLj45Geng51dXW0bNmy0lOH2rdvj82bN8s0A6pPnz4YMWIEHB0dy9yDXbt2DS4uLrhz547UuvPmzUOtWrWwfv36MutWrFiB7Oxsqev7lObFixe4d+8ec3w7duwodZHnEiwtLeHh4SGxXiFB8AGqaUPwjpIUz5JOFbJK8Tx//jzevXsnsVPFvn370KRJEwwYMEAqzY4dO6KgoACNGjWCmZkZli5dCnNz80pNY/pWnDUnJwc1atRgpbtw4UIUFhZCW1sb5ubmMDMzg5mZWaULEAPFnQB27dqFLl26MDVMBAIBcnNzcejQIVZdk74mJydH4o0u25Tqa9euMUWTHRwc0LhxY0RGRqJ58+Zo2LBhJd1WjtIF+CpCRYr0/Wi4eOgBimtZZGRkQE1NjfXfwtfExsYy58LIkSOhqamJ169fo169emW6/vyMqKqqMjVBGjZsiJcvXzJBm8LCQnz+/FlqzREjRsjUYwlcdCcrTemHNA0NDWhra8usvoNIJEJKSgrq1avHaupSWlqaVNtLe21cvXo1WrVqhb1794qd95mZmZg2bRrWrFmD4OBgqTSBYt/f8vLvv/9CT09PKs3ffvsNp0+flnnQJisrC7NmzWKmb5T8Hpc+B9gMmsTExGDixIlo3LgxXr16BX19fWRmZiIxMRFaWlqss+/YBGQqwh9//FFudp22tjYOHDggddAmNTWVud948+YN4uPj4eHhAT09PUycOBGLFy9m5fXrYKO2tjY+fvyIwMBABAYGYv/+/ayCjb///jt27tyJT58+MVMv69WrB0dHR4wbN46VV6D4Giur4tElcNVlMioqiqmt+DVWVlZYvXo1K12hUIhFixbh0qVLEIlEUFJSglAohEAggLW1Ndzd3aWucWRjY4OQkBAK2hC8hYI2BK+QlOJZgoWFBUJDQ1kHbfbs2VPug4SKigr27t0rddBm3bp1MDc3r3Tg48GDB7h//z7z7zNnzpQpbJeXl4crV66wLnIcERGB6Ohopv7OqVOnkJ+fzwSczM3NYWNjw0p70aJF+O2332BtbY1OnTpBIBBg+/btePnyJQQCAetiuSKRCDt37kRQUFC5bZKlvYH+9OkTHB0d8fDhQzRq1AhJSUkYO3YsGjdujODgYKioqJR7k/ItZFkYc+TIkRV6UKxMDQ+gOBB2+/ZtJCUllfHLps4EwN1Dz9WrV+Hj44N//vmH+dyGhoaYM2cO66BgTk4Oli9fjvPnz6NatWooKipCt27doKmpia1bt6Jp06ZwcXGRWreoqAjHjh1jzoWvA1cCgQBhYWGsPBcVFeHOnTuIj4+XeI5JO40JANq2bYvnz5+jW7du6NWrF3x9fSESiVC9enXs2bOHVee3EtLT0/HixQskJSWhe/fuUFdXR15eHhQVFVk9uHDZkpmrh7Tr16/D29sbT58+RWFhITMQsWLFCpibm+PXX3+tkE7nzp2lCiBJ+3fGVXtye3t7HDp0SOI0ikePHmHq1Km4e/euVJo1atTAvXv3MHbsWLHBghLYXr88PDzw4cMH/P777xg3bhx8fHygrq6OkJAQ3Llzh3VWgYeHBwYMGID169fDyMiI+f/o6GgsXLgQ06ZNY6UrqfPm17C5P3n37p1YTaPSNGvWTOppxkDxefTx40cAxd2e1NXVmelQSkpKEgP8FYGLYGNQUBDWrl2LQYMGYeDAgahfvz4+fPiA8+fPY+3atVBUVGR9vzR//nzs3bsXZmZmrAedvoarLpPp6enlTn9SUVGROpBcgqenJ8LDw7F69WoMHDgQqqqqyMrKwvnz57Fx40Zs27ZN6iCeqqoqIiIiZH5NIIgfBQVtCF4RGBgIR0dHJsWzNC1btkR8fDxr7VevXpWbdqmrq8tKW1LHKzbcuHEDPj4+AIp/WCTVoqhevTp0dXVZBRSA4u4Pv/zyCzMyKRQKcffuXezZswchISE4c+YM65uQhg0b4tSpUwgICMCtW7fQvHlzpKWlYciQIZg8eTLrG5OAgAAEBARg6tSp2LZtGxwcHKCgoIBz584hPz+f6TAgDevXr8fnz59x9uxZtGjRQmwOfZcuXSpcvPVrVq9e/d3CmBWlvA4bsiQiIgKzZ89Genq6xPXy9NATFhaG2bNnw8TEBK6urqhfvz5SU1MRGhoKBwcHeHl5sapjsnnzZty5c4e5gS4dnLCyskJAQACroI2HhwcOHDgAc3NzdOrUqVLnQmlSU1MxceJEvHr1SqzbRukHeTZBmxkzZjAPf3PmzEFiYiI2bNiAoqIitGvXDmuBV4ZAAACFL0lEQVTWrJFas6ioCNu3b8fhw4eRk5PDFMZUV1eHk5MTTExMKly88+sC2rLuTgZw95B29uxZLFq0CAMGDICNjY1Yt6hmzZrhxIkTFQ7abNiwgdOuLly1JweKz7F9+/aJZcfdv38f06ZNQ/fu3aXW27JlC4Di4MKDBw/KrGd7/bp+/Trmz5/PZGY0aNAAxsbGMDc3x6ZNm3DgwAFs27ZNat3nz59j+vTpTKCyJEDRoUMHODk5YevWrejWrZvUur169fruOcEmSK6qqoq3b98yGXelSUhIYJXlaGZmBi8vL3z8+BH+/v5i1+y4uDg0atRIak2Am2BjQEAAJk6cyNTfKaF3796oW7cu/P39Wd8vnTx5Eu/fv0evXr1gaGgoscuRtPchXHWZbNasGW7duiWxTtbt27dZZ3qdO3cOCxYswOjRo5llqqqqGD16NHJycrBv3z6pgzYl9xZJSUkyvSYQxI+CgjYEr+AqxRMAlJWVmVGer0lNTWU9avv06VP4+fkhOjqaSQPv2LEjZs6cWeHilU5OTswDTOkCjrImOzsb0dHRiIyMRGRkJB49egRlZWV079690sWN1dTUMGfOHMyZM0dGbounxs2ePRvjx4/Htm3b0KdPHxgZGcHR0REODg548+aN1Jrh4eFYu3YtdHV1ywQGGzVqhOTkZFZer169isWLF8ukMKas2yRLYs2aNdDX18eKFSugra0ts8ACFw89Pj4+GDRoEPOgVoKdnR2cnZ3h4+PDKmhz8eJFuLi44JdffilzLjRp0oTVaDJQnCk3e/ZszJo1i9X7y2PTpk3Q0NBAeHg4rKyscPToUdSvXx8hISE4deoU9uzZw0rX1NSUCVipqalh165dEAqFEAqFrKeH7dixA4GBgVi8eDG6dOkCa2trZl2vXr1w7NixCgdtvq6nI6uWzKXh6iFt586dsLOzg6urKwoLC8WCNq1bt8bBgwcrrMXVlLMSuGpPvm/fPtja2mLWrFnw8/ODoqIi7ty5AwcHB1hbW2PDhg1Saz579oyVl+/x6dMnNGrUCAoKCmUyCaysrDB79mxWugKBAIqKikz21rt379ChQwcAgJaWFl69esVKt2SwpzQZGRm4ceMG08GNDV27doWvry8sLS3Fginv37/Hzp07WQXali5dikWLFmHLli0wMjISC6aEhITAzMyMlVcugo1v375Fz549Ja7r0aMHjhw5IrVmCV++fBGbDvflyxfWWiXY29sjKSkJbm5uzMDeb7/9BqC4y6S0U9lKsLGxwdatW6Guro6RI0eibt26+PTpE06cOIGAgAAsWLCAlW56enq5WeM6OjrlDiZ9C66uCQTxo6CgDcEruErxBIory+/Zswe9evUSK2ycnZ2Nffv2sXpQjoqKwuTJk6GpqYlBgwYxhRsvX76MMWPGYP/+/VLfiHD1w1NSwLh27dowMzNDv379sGzZMhgaGsp8frWsSExMhKGhIRQUFFC9enXmxqxatWoYN24cli1bJvVNQ2FhYbmFrTMyMlgHLxQUFCrdkv1HkpiYiKVLl7Iu+lceXDz0xMXFlfvwMXToUNbBkezs7HK7euXk5LDSBIqz2EoeyGRJZGQkli9fLua5cePGmDlzJkQiEdasWcO6kOfXKCkpSV1ToDQnT57EggULMHbs2DIBsebNmyMhIaHCWtIWQWYDVw9pCQkJ5U7fU1FRQWZmJivdEjIzM/H8+XOm+Kq+vn6ZkfuK4uHhgczMTNjZ2UlsT75lyxYmcCpNe/I6depg//79mDBhAubPn48RI0Zg/vz5GDZsGOuaGFyhpaXF1HDS1tbGX3/9xQQo7t+/z7qjnK6uLhISEtC5c2eYmppi//790NPTY6Ygss1iKi9YPWLECGzcuBEREREYOHCg1LoLFy7EmDFj0L9/f3Tu3BkNGjRASkoK7ty5g7p162LhwoVSazZs2LDcLFJ/f3/W1xsugo2ampq4f/++xAyTBw8eVKobZEW7+knL8uXLYWdnJ9ZNjk2XydJMmjQJb968gaenJzw9PaGgoMBcz8eOHStWwkAadHR0yq1JFRISInUZgLy8PNjY2DCDMATBRyhoQ/AKrlI8geJ5xGPHjkXfvn1hbW3N3IRcvHgR+fn58PT0lFpzy5YtsLCwwO7du8UydVxcXDB9+nRs3bq1Qm0Wnzx5Al1dXdSoUaNCRWjZFJ4tyarp2rUrOnXqBDMzM7Rs2VJqHUnIsp5LaTQ0NJjsqsaNG+Pp06dMQO/z58/Izc2VWtPY2BjBwcESH6TOnTvH+mGbq8KYBgYGnKS/d+jQAfHx8ZVqDywJLh561NXVER8fL/HYxsfHQ11dnZVXfX19XLp0SaLu33//zbr97JAhQ/DXX39JDD5XhszMTNStWxfVqlWDqqqqWOagqakp60wboPhBJDQ0FElJSRJr8Eibrp+WlgZdXV2J6woLC1FQUMDaKxedYrh6SNPU1ERcXJzEc+H58+es66F9Pf2sBBUVFUyYMAHz5s2DgoKCVJpGRkactVzW1NREQEAAxo8fjytXrsDW1hZLliyRSuNH/E527doVt27dQt++fZkMqZiYGCgqKiImJobV9EOg+N6mZAriggULMGXKFGZ6tYqKCry8vFjpfgsrKyvMmzcPq1atkvq9JVOeDxw4gDt37uDVq1fQ0NDA5MmTMWnSpErXYvm6O2hlCr5zEWwcNWoUdu7cCaFQiP79+6NevXr49OkTLly4AH9/f5lnUVaWyMhItGnTBs2aNcOYMWPE1mVnZ+PJkyessqkFAgFWrlwJOzs73L59mynQ3rlz50oFgxwdHTF37lwkJiaiX79+qF+/Pj5+/IiLFy/iwYMH2LFjh1R6ysrKSE5OltsBSIKoCBS0IXgFVymeQPFI1/Hjx+Hl5YVLly4xU5ksLS3h5ORUbtG9b/HPP//Ay8urzNQqBQUF2NraVniq0MiRI5kpUd8qQluZwrO3b99GVFQUIiMj8eeff2LlypWoW7cuU4TYzMwM+vr6UusCsq3nUpoOHTrg0aNHsLKywuDBg5muYtWrV8fRo0dZPRTPmzcPtra2GD9+PKytrZmisLt370Z4eDj++OMPVl65Kozp6upa5nzIyMjAzZs3kZKSAltbW1Z+16xZg7lz50JRURFdunSRODrP5saci4eegQMHwtPTEzVq1IC1tTXU1NSQmZmJ0NBQbN++XWxevDSU1M/KyclB//79IRAIEBMTg7NnzyI4OBh79+5lpWtiYoLt27fj48ePsLS0lFh3hU0HraZNmyIlJQUA0KpVK5w+fZrJDgkLC2P9IHXw4EFs3LgR9erVQ7NmzWTy96utrY2bN29K/BuNiIhgneHFVacYrh7SBg8eDG9vb+jo6DBZAAKBAP/++y/27dvH/L5Ji7u7OwIDAzF9+nRYW1szNXhCQ0Oxd+9e5Ofnw9XVVSrNTZs2sfIiia/rEJWgq6uL7OxsFBYWim1TkSltP+J30tnZmQmCDRs2DLVq1UJoaCjy8vKwYsUKjB07VmrNEq0SdHV1cf78edy/fx95eXkwNTVFvXr1WOl+i+jo6Eply2loaLAuPl0eJd1BU1NTmTpXle0OykWw0cHBARkZGfD39xcLhisoKGDixIlwcHColP6LFy+wc+dOpmthUFAQjIyMsG3bNnTo0EHq4vq2trYICgqSOK0+Li4Otra2rBsWAMXXc1lmEvfr1w8+Pj7w9fXF5s2bxZoL+Pj4oFevXqw0L1y4IPOBKIL4UQhE3+ofTBBySkJCAm7evIm0tDSZpHhyRefOneHi4iKx1kBwcDA8PDxw586d7+pERETAyMgItWrVYrrufAtZ1DzJyspCREQEDhw4gKioKAgEAjx9+pSVVufOneHk5CSTei6liYuLQ3JyMrp06QKhUAh3d3dcvHgReXl5sLS0xIoVK1jd7N6/fx9bt27F/fv3UVhYCIFAAFNTU7i4uJRbU+l7GBgYfHN9Zbo8lYeLiwuaNGmCuXPnSv3ezMxMLFu2DJcuXSr34YeN35ycHOTk5DAZD5cvX2YeeiwtLTF27FipR8OEQiEWLlyIy5cvQyAQoHr16igoKIBIJEK/fv2wZcsW1g8noaGhcHd3F+vCoqWlBVdXV/Tv35+VJlfnwtatW/Hp0yesX78e4eHhmDVrFmrXro3q1avjw4cPcHZ2hr29vdS6VlZW6Nu3L5YuXSqzkcoTJ05gxYoVmDZtGvr3749hw4bB19cX79+/h7u7OzZu3Mhq2saIESOgrKxcbqeY/Px8Vm2pRSIRNm/ejMDAQCb9v6SDVmXaEQuFQsydOxdXr16FhoYG0tLSmIBQjx494O3tzaqeWqdOnWBvb4/p06eXWbd7927s379f6o5MskSahy6BQIArV658d7uq+J2UdyQFx4RCIeLi4nDv3j1MmTIFixYtqgJnZZHUHTQ4OBhGRkY4ePAgQkNDK5SZXBFycnKQkpKC5s2bS128WyQSIT09HSoqKsjOzkZMTAzS09Ohrq4OY2Nj1KlTp1Lebt68iRkzZsDIyAiWlpbYtWsXcxy8vb3x5MkT+Pn5SaX5rVqIkZGRmD59uliHUmnIzs7GyZMnce/ePeY4dOzYEcOHDy93qrm0+pmZmahdu3al9E6ePAlPT0+0adMG3bt3R/369ct892wGSwjiR0FBG4LgkCVLliA8PBxbtmwRi+7funULixYtgpWVlVRFFoVCIf7++28YGhpWqlPHt/RjYmIQGRmJqKgo3L9/H9nZ2ahXrx7MzMykTkktoWvXrti8eTPv5hLn5uYiPT0dampqUFFRqWo7UnPjxg24uLjg1q1bUr935syZiI6OxsiRI9GyZUuJ2RXDhw+XhU2Z8fz5c0RFRSEjI4O5cWSbHfY18fHxTB2A8qb1VJSKFDBm23WjNDExMbhy5Qpyc3NhaWnJuvW5hYUFduzYIfPpXAcOHIC3tzdycnKYTlcqKiqYM2cO62kmxsbG2LFjh8T6M1euXMH8+fMRExPD2vPnz59l/pAGAHfu3BGrNWFpaVmpEeGS63XXrl3LrLtx4wbmzZsnsVAz8W0MDQ3LzVh4/PgxUxuODTk5Obh9+zaSkpLKTCFmm4kpKTimrKwMLS0tWFtbw8bGRuppciVERkYiKCgIr169ktiO+8yZM1Lp9enTByNGjGC6gxoZGTHBimvXrsHFxaVCg1xf4+/vj5ycHKaweVRUFBwcHJCVlYWmTZti//79Ut1PCYVCmJqaYufOnejRo4fUfr7HiBEj0KpVK7i7u6OgoABt27ZljkNYWBjWrFmDa9eufVfnwYMHTCBm8+bNmDhxYpnplnl5ebhy5QqKiopYBbOTkpIwceJEJCYmwsDAgKnb+Pz5czRp0gSHDh1i3fWrhNzcXGRkZEBNTY1VV7ISqmLgjCBkCU2PInhHYWEhHj58WG5tlNJpxtLy+vVrnDhxotybEGlHN1xdXfHy5UvY29tDVVWVqayflZWFdu3aST06q6SkhIULF2Lfvn0yD9qMHz8ejx8/Rl5eHrS0tGBubg5XV1eYmZlJXfTta7iq58I1JfVVZDWd60cTHx+PoqIiVu+9c+cOVq9eLbO29SU8e/YMycnJEgMI4eHhaNiw4XdvrspDX19fZkGar2nZsqXMajzJIiBTEYyNjWXSZW7AgAG4du2azIM2kydPxujRo3H//n0mWNG+fXvWhXIBbttSc1Erp4TOnTujc+fOldIojbW1Nc6dOycxaHPu3Dn07dtXZvuqLKdOnYKVlZXE4FdaWhr+/vvvSv2uy5JvjXMWFhayDoBERERg9uzZ5XbFYRu04apI9/Xr1zFjxgx06dIFjx8/Rvfu3ZGbm4vo6Gjm/kFauOoOeuzYMbEMw40bN6JVq1aYPn06du3ahS1btkg1IKWkpAQtLa0yBdRlxYsXL5hCzl9ngqipqTE14b7HjRs3mO5hAoFAYoHj6tWrQ1dXlyk3IC0bN24EUHxNKX2fGBcXh5kzZ2LTpk2sB/uuXr0KHx8f/PPPP2LTo+bMmcNqAKIi2XoEIc9Q0IbgFU+ePMHs2bORlJQk8eZJIBCwvrmLiYlhRiJevXoFfX19ZGZmIjExEVpaWmItGCuKuro6goKCcPXqVdy7d08sA6BHjx6sphro6OggKSlJ6vd9D21tbdjY2MDMzAxNmzaVqTZX9VyA4puFbxVIrWgHk9Jcv34d3t7eePr0KYqKinDs2DEYGRlhxYoVMDc3x6+//srKK1A8spWQkCAxKMimMOaBAwfKLMvPz0dsbCxCQ0MxePBgVj4bNmxYqYfn8tiwYUO5c/JjYmIQHR0t8TN9D66CuUlJSQgLC5M4+g1UrNbG15SealUebAvQAsVTG9+/fy+zc2zZsmVYtmwZFi5cKPHvF2CXVs5FEISrttRc1cop4dq1a0z9CgcHBzRu3BiRkZFo3rw5GjZsWCGNS5cuMf9tbm6Obdu2YeLEiejTpw8zAh4WFoY3b97IvBZJZViyZAmCgoIkBm3evn2LJUuWsPr7PXXq1DczQaKjoyukk5qaytSKAoofSL8OzuTl5SE4OJj13+2aNWugr6+PFStWQFtbW+4HCry9vWFnZwdnZ2cYGRlh7ty5MDIyQmJiIuzt7VkFILnqDvr+/XumJmFycjKePHmCwMBAmJmZobCwkFUh5nHjxiEgIAC//PIL645h5aGuri52vpXm1atXFS567uTkxGQXfWt6VGW4desW1qxZU2ZgT0dHB3PnzmUdDAoLC8Ps2bNhYmICV1dX1K9fH6mpqQgNDYWDgwO8vLzK7YxWHj9qsIQguIKCNgSvWLVqFVRVVXHw4EG0atVKpjc2Hh4eGDBgANavXw8jIyPm/6Ojo7Fw4UJMmzaNlW61atXQu3dv9O7dWyY+FyxYgA0bNkBXVxft2rWTiSYArF+/XmZaX1PSmeHdu3d48OBBmfVsgzaenp7Ys2cPjIyMoK2tXamiiiWcPXsWixYtwoABA2BjYyP2kNesWTOcOHGCVdBGKBRi1apVCAkJKXeEjk1q7ubNm8ssKxkJtLW1haOjo9SaADBnzhzs2bMHHTt2ZN19SRLPnj3D1KlTJa4zNTVFYGCg1JpcBXPPnz8PFxcXiEQi1K1bt8z1RiAQsAra9OrVi5OOX8nJyVi6dKnE6XCVKb4aFxeH6OhoJCYm4ty5c2XWs9HlKgjCVVvq1atXo1WrVuXWylmzZg2r6QWfPn2Co6MjHj58iEaNGiEpKQljx45F48aNERwcDBUVlQo/+EgqbJ+cnIzIyMgyy9kGQrjgW9krGRkZqFWrltSap0+fxooVKzB8+HDcv38fI0eORFFREf766y+oqalJlUFYUhxXIBBAIBBI7GolEomgoKDA+iE1MTERS5cuZV2A+1twEXiOjY3F/PnzUa1aNQgEAqY4c5MmTTB79mx4e3tLnaXJVXdQZWVlZGVlAShuuFCzZk0mo6d27drIzMyUWjMpKQnx8fHo0aMHLCwsJNZHYXNcgeJpYt7e3jAxMWGCTQKBAKmpqfD394e1tbXUms+ePWPl5XsUFhaWG7RSVlZmnY3k4+ODQYMGMdfqEkoChT4+PlIHbUqQRYCcIKoCCtoQvOLly5fYvn07JwUEnz9/junTpzPZLyUjcx06dICTkxO2bt2Kbt26fVcnLS1Nqv1K29Fly5YtSEtLw+jRo6GhoYH69euLrWebXfL48WNkZmYyo1zp6enw8PBAbGwsLC0tMWvWLNZFSLm6YQgODsacOXNYByYksXPnTqarUWFhoVjQpnXr1jh48CArXV9fX9y8eRObNm2Cs7Mz3NzcULNmTYSEhODNmzesMwC4OrZnzpzBu3fv0LNnTxgaGpbJumHT5hkoDl7l5+eXu07SiPj34CqYu23bNvTp0wdr166VadZRScp6aTIyMnDjxg08ePAAzs7OrHQXL16MV69eYfny5TIdrV+6dClq1qwJPz8/melyFQThqi31y5cvsWPHjjKth2vXro1p06axzlxZv349Pn/+jLNnz6JFixZi3rt06SLV3xif0v/Dw8Nx/fp15t/79+8v81uWl5eHO3fuwNDQUGr9AwcOwNHREdOnT8fRo0cxbtw4GBkZISsrC/b29lIFgoYPHw4LCwuIRCLY2dnBzc0NrVq1EttGUVER2trarOsbdejQAfHx8TLvbMNV4FlZWRlFRUUQCATQ1NTEmzdvYGZmBgCoVasW3r9/L7UmV91BjY2NsWfPHlSrVg3+/v7o3r07kyn15s0bVg/qV69eZQaJHj16VGY92+MKAAsXLsSjR4/w66+/Qk9PD0DxNTghIQEtW7Zksmekgav7uw4dOmDXrl2wsLAQ+43MzMyEn58fOnToILUmUDxQUN7v4NChQ1l165NlgJwgqgIK2hC8QltbG1++fOFEWyAQQFFREQKBAPXq1cO7d++YHxwtLS28evWqQjqdO3eWqhuBtCPUXD2UbNy4EV26dGF+1Dds2ICwsDB07doV+/fvR7Vq1Vi3teWSykxJkERCQkK586VVVFRYjcoBxV2InJycMGDAADg7O8PY2Bht27bFsGHDsHjxYvz111+sC8VywZcvX8Ta3Mvq787Q0BCnT5+WmHl2+vRpVvVsuArmfvr0CWPGjJH5NLHyRghHjBiBjRs3IiIiglXnpIcPH8LDw4P1CGR5xMbGwtvbG927d5eZJldBEFm2pS4NV7VywsPDsXbtWujq6pYZlW7UqBGSk5MrrMWn9P9Xr14x9VYEAgGioqLKZEoqKiqidevWWLBggdT6r1+/RocOHaCgoAAFBQUm00JVVRXTpk3Dhg0bKlzsukmTJsyxPXToENq0aVPmvK0sa9aswdy5c6GoqIguXbpIvOZIO8ADcBd4NjAwQHx8PLp27YouXbrAz88PderUQfXq1bF9+3Ym2CAty5cvh52dnUy7gy5evBgzZszAzJkz0bhxY7Fry4ULF1h1hOSqVhBQfA08cuQIQkJCcOvWLWhoaEBdXR3jx4/H0KFDWWUUb9iwAZaWljK/v1u8eDEmTJgAKysrdO7cGfXr18fHjx9x+/ZtKCoqStVoozTq6uqIj4+XWAcxPj6eVfavLAPkBFEVUNCG4BVLlizB+vXroa+vX+kOLl+jq6uLhIQEdO7cGaampti/fz/09PRQvXp17Nmzp8I35SWF2biCq4eSly9fMu1hc3NzcfHiRaxYsQIjR47E77//jkOHDlUqaMNFzZFRo0bh7NmzEottskVTUxNxcXES59U/f/6cdc2C9+/fo2XLllBQUICysrLYA+Cvv/6KBQsWYPXq1RXSOnXqlFT7ZnNsJRUtlAUzZsyAg4MDpk+fjhEjRqBBgwZISUnBiRMncOPGDezcuVNqTa6Cud26dcODBw9kXoD3W1hZWWHevHms6iy0aNECBQUFMvdkaGiIjx8/ylSTy4LBXMBVrZzCwsJy29hmZGTIJKspJydHYgYbmyCArLCzs4OdnR2A4umCO3fuZF2AXBKqqqrM70zDhg3x8uVLdOrUCUDxMa9oMdev4apNuJqaGho3bgw3N7dyB33YTG3kKvBsZ2eHt2/fAiiesj1z5kw4ODgAKB7kkpRNWFGaNWuGsWPHysQnALRq1QpXrlzB58+fy2RCLV68uMI1Yn4kioqKGDlyJEaOHCkTvdjYWMyYMQOAbO/v9PT0EBISggMHDuDevXt4+fIl1NXVMXr0aEyaNAlaWlqs/A4cOBCenp6oUaMGrK2toaamhszMTISGhmL79u0YPXq01JqyDJATRFVAQRtC7hkyZIjYv1NTUzFkyBA0aNBA4pQNNlODgOL51CUFQhcsWIApU6Zg6NChEIlEqFmzJry8vCqk8+zZM0yaNAmNGjVCZGQk2rRpw2pOfnk8fvwYRkZGUmXzVITc3FymrXV0dDSEQiGTDaGvr88q3bkErmqOzJs3D+vXr5dpgePBgwfD29sbOjo6zA26QCDAv//+i3379jHp2tKiqanJPKQ2bdoUd+/eZVLhK5rFVYKrq6vYv0vOhdLHtvT5IS+1KwCgR48e2Lp1K9zd3TFv3jwIBAKIRCJoaWlhy5YtrFqochXMXb16NebPn4/c3Fx07txZYgFeNoV9v0V0dDTr2kyLFy/Gpk2boK+vL7NOVwCwcuVKuLq6QlNTE507d0b16pW/deAqCMIVXNXKMTY2RnBwsMQsu3PnzrGeXiASibBz504EBQUhNTVV4jby0t6Wi6yFtm3b4vnz5+jWrRt69eoFX19fiEQiZhDG1NSUtbasChyXZtGiRYiOjsbkyZPRsmVLmU1t5CrwXPp8bdiwIU6cOIHXr18jNzcXOjo6rK5hkmovfQ2brlQlSJq6Jk23wR8xWMIVXN7faWlpSazzVBkWLlyId+/eYcWKFXBzc0P16tVRUFAAkUiEfv36scq++xEBcoLgEgraEHIPFwEKSZT+gdXV1cX58+fx4MED5ObmwtTUFPXq1auQzuHDhzFo0CA0atQItra2CAoKkmnF/lGjRqFWrVpo3749zM3NYWZmBmNj40r/4DRr1gzXrl2DhYUFzpw5AyMjI2Yk9uPHj5VKB+eq5sidO3dw8uRJfPnyRWYFjp2cnPDixQtMnjyZ+fzTpk3Dp0+f0KNHDyYbSVosLCwQFRWFXr16wcbGBu7u7oiLi4OioiLCwsKk6vJU+ub29evXmDt3LoYOHQpra2vUr18fHz58QGhoKEJCQrB9+3ZWfgHg6dOn8PPzQ3R0NNLS0qChoYGOHTtixowZaNOmDWvdgQMHYuDAgYiLi2N0pW0r/yOCuV++fEFOTg52796NPXv2iK2rTGHfdevWlVkmFAoRFxeHe/fuYcqUKVJrAsUp3paWlhg0aJBMj8O4ceNQUFCAadOmoVq1amUKTwoEAty7d08qTa6CIFzB1bTUefPmwdbWFuPHj4e1tTUEAgHCwsKwe/duhIeH448//mClGxAQgICAAEydOhXbtm2Dg4MDFBQUcO7cOeTn52PmzJky/iSVIzk5GQEBAWWuNXZ2dqxqjsyYMYMZhJkzZw4SExOxYcMGFBUVoV27dlizZg0rn7IscFyaO3fuYPXq1azfXx5cBZ59fHxgY2PDfDcCgYCZwpSSkoKjR49KXXtl4sSJTBC/hK/v/aoy0MjlYEmHDh1w6NAhtG3bFu3bt//mPS+b6y2X93dcoKSkBG9vbzx//hxRUVFinVelCbSVhqsAOUH8KChoQ8g9XE0HkkR5LWilmfNct25dPHz4EMbGxt/sisGWCxcuICIiAlFRUQgKCsK2bdugrKwMY2NjmJmZwdzcnFUxw0mTJmH58uU4fvw40tPT4e7uzqyLiIhg/UMJcFdzZPXq1Wjbtq1MC68qKSlh165duHPnDm7duoXPnz9DXV0dlpaWlSoSOX/+fCYlvySQFBoairy8PEycOFGq1OTSD+Nbt27FmDFjxIJJ9erVg76+PmrUqIEtW7awKp4cFRWFyZMnQ1NTE4MGDWJaBl++fBljx47F/v37mcKTbCkdqBEKhVKNzv6IYO7ixYuRlJQk8za8kjILlJWVoaWlhZUrV8LGxoaVroeHBw4cOCDTbmpAcYFQWcNVEIQruPodat++PQ4dOoStW7di8+bNEIlE8PPzg6mpKQICAlhnch0/fhyzZ8/G+PHjmbomRkZGcHR0hIODA968eSPjT8Kef//9FxMmTEB+fj66du0KAwMDfPz4EUeOHEFwcDACAwOl7qpkamrKZNOoqalh165dyM7ORkJCAvT09FhfO2RZ4Lg0DRs2lPkUJoC7wLOvry+6d+8uMaCWkpICX19fqYM2kjJZ0tPTcePGDVy6dKnC04e5gsvBkilTpjDTtKZMmSLz3zZZ3t99PWDyPc6cOSPV9qXR19ev1L1nabgKkBPEj0Ig4uKpkiB4yNctaEseUkva51a0Ba27uzv2799f4R/dyo4cJSYmIjIyEsHBwYiMjGR9EwYU35Q8evQIbdq0QefOnZnl3t7eaNeuHaupK0Bx941p06axKq76LUxNTeHr6yvTmjZ841vH4MaNG3BycpKYhfQ9xo4di1q1amH37t1i02EKCwsxffp0ZGdn488//5Ra99SpU8jMzMTEiRMBFD+wOTk54e3bt+jYsSO2b99e4aw2rjExMcHWrVtlXtiXK8zNzTF58mSZdlMTCoX4+++/YWhoKHd1Zn42cnNzkZ6eDjU1NWYqA1tMTU2xd+9emJubo23btti7dy8zRSY8PBzLli3DjRs3ZGG70tjb2yMtLQ379+8XKzCanp6OKVOmoE6dOti3b59Umv7+/sjJyWECB1FRUXBwcEBWVhaaNm0Kf39/NG/eXGqv7du3h5+fHzp16gQjIyPs37+fqZUTFhaGDRs2sJrude7cORw+fBi7d+9mVWS1PCZOnIiEhARMmzat3MAzm8EUAwMDHD16VGIW8dWrV+Hq6oq7d++y8iwJX19fvHz5Etu2bZOZZmWYPHkyunTpIjHzdvfu3bh16xbrTpNcIav7O1dXV6mCSmzrPHJRB/H+/fvYunUr7t+/j8LCQggEApiamsLFxYVVQWqC+JFQpg3BK5YsWYKcnByJoxjz58+Hqqoq1q5dy0pbVi1oXVxc0K1bN8TGxmLdunWws7NjXbz2W8THxyMyMhKRkZGIiIhAcnIydHV1KzXn29zcXOL7Z8+eXRmrnNUc6dixI9PBQlbMnDmTmXbWtm1bpjUoG6QZkWI7BaRu3bo4f/68xGNw7tw51K1bV2pNoDiY6OXlVaZ+iYKCAmxtbTFnzhxWuv7+/mJFJteuXQtFRUUsXboUhw8fhqenJ9avX89KW9ZwVdj366kFpWE7tQAoLl4p625qSkpKWLhwIfbt20dBGw4oXaOsRo0aqFGjhkx0NTQ0kJ2dDQBo3Lgxnj59ygRtPn/+jNzcXJnsRxZER0fDw8OjTLBCXV0dDg4OWLRokdSax44dE8sQ27hxI1q1aoXp06dj165d8PT0ZDV1lKsCx2fOnMG7d+/Qs2dPGBoaSpzayKa7TUxMjMwCz2fPnsXZs2cZP5s3by7jUygU4vHjxzKfatKhQwf4+/vLVLMy3L9/H1OnTpW4zsjISC47Ecnq/q501mFJRnp5PHnyRCrt0u/jog5i+/btERgYKNMAOUH8KChoQ/CKW7duYfHixRLX9evXTyzlU1pk2YK2pHX2xYsXMXr0aJkGKubNm4eoqCh8/vwZenp6MDMzw7Jly2BmZsb6AR0ofnjIzMxkbuzT09Ph4eGB2NhYWFpaYtasWahWrRor7bVr13JSc2T+/PlwdXWFoqIiLC0tZdImtWbNmjh48CA8PDygoqICU1NTdOzYEebm5mjfvr3cTeGZOXMm3Nzc8ObNG/Tp04fJEAsLC0NkZCTr2g0qKirldgz68OED6xudxMRE5u/h06dPuHfvHvz8/NC9e3fUrVsXmzdvrpDOunXrMGXKFDRu3FhijZivWb58udRelyxZgs2bN6N169Yy/RvmYmoBANjY2CAkJETmmWc6OjpISkqSqSZRDFc1yjp06IBHjx7BysoKgwcPho+PDz58+IDq1avj6NGjP7Qj2vdQUFCQOJIOFAcB2ATO379/jxYtWgAorpfz5MkTBAYGwszMDIWFhay6swHcFTj+8uUL47fk37JAloHn/Px8xpdIJEJOTk6ZewIlJSUMHTq03IAGW8LCwqq029nXyHqwRJoaU2wDeACQl5eHhIQEiQW02UzFHDJkCFatWoX+/fuLLS8qKsLOnTvh5+eHx48fS63LRR3EJUuWwNHREc2aNSsTIE9MTISPjw/n3V8JojJQ0IbgFZ8+fZLYAQAofjj/8OEDa21Zt6DNy8tDeno6kpKSZPrAFxoaCmVlZYwdOxa9e/dG+/btZTJSsHHjRibYBAAbNmxAWFgYunbtiv3796NatWqsW35zFbwYNWoUgOLuNrJqk+rp6QmgeM56ZGQk7t27h1OnTsHX1xfVq1dHu3btKjz3+UfUYxo9ejQ0NTXh5+cHDw8PFBQUoHr16mjTpg127tyJXr16sdLt2bMntmzZAi0tLbFaPrdu3YKnpydr3WrVqiE/Px9Acaeg6tWrM6nampqaSEtLq5DOX3/9hVGjRqFx48bfnY4gEAhYBW02bNjASbDxW7OSU1NTJRYLrQiqqqqIiIiQaTc1oLib3oYNG6Crq4t27dqx8kZIhqsaZU5OTkwL25kzZyIjIwNnz55FXl4eLC0t5ao7l6WlJbZv3w5DQ0OxrmevXr3Cjh07WH1+ZWVlZGVlAQBu376NmjVrMtMfateujczMTFZeuSpwfPjwYVbv+x6yDDwPHz4cw4cPB1A87WrVqlUyvbeRFLjIz89HfHw8kpKSWGVccYWsB0tkFaQrD6FQiFWrViEkJKRMu+sS2Eyr79evH+bNm4chQ4bAzc0NtWvXRlxcHBYvXox///2X9XfGRR3EkydP4rfffpN4L//582ecOnWKgjaEXENBG4JXNGzYEDExMRJHCWNiYr6Zpvk9ZN2CVllZGcnJyayzU8qjpHZNZGQkFixYgKysLLRp04ZJfe3YsSOrgoYvX75k5mfn5ubi4sWLWLFiBUaOHInff/8dhw4dYh204Sp4sWHDBs4yWVq0aIEWLVrAwsICHTp0wJkzZxAREYH79+9zsr/K0LNnT/Ts2RNFRUX49OkT6tatW+nzztXVFS9fvoS9vT1UVVVRt25dfPr0CVlZWWjXrl25GW/fw8DAAH/88Qe0tLRw+PBhdO7cmcleevfuXYXr2ZQO1HDRMhiQbbDxR0wt2Lp1KwAgKSlJZt3UAGDLli1IS0vD6NGjoaGhgfr165fRreruTnylZcuWaNmyJcaMGQNAvEbZrl274Ofnx+phSkdHhyn0raSkhOXLl7MKXP4IXF1dMWHCBAwaNAitW7dG/fr18fHjR/z7779o1KgRq3bCxsbG2LNnD6pVqwZ/f390796dydh58+YNq45UAHcFjrmCq8Bzp06dyu04xHaKp6TAhbKyMiwtLWFtbY1u3bpJ7ZMrZD1YwlXQrgRfX1/cvHkTmzZtgrOzM9zc3FCzZk2EhITgzZs3rIO4a9asQe/evbF8+XIMGTIEgwcPRmBgIFq1aoUTJ06wDuppa2tzHsgqzevXr+Uqk4sgJEFBG4JXDBo0CH5+fmjWrJlYUdsLFy7Az88Ptra2Uul9XXPkey1oJbUK/Bb9+vXDhQsXKtV16GuMjIxgZGTEPHy9ePECkZGRuHDhAvbv3w8FBQVW6ai5ublMxk50dDSEQiF69+4NoLiC//v372X2GWTFiBEjZK4ZGxvLBMUiIyPx4cMHtGrVCubm5vjtt98qVTOIa4RCIYqKiiAUCitdG0NdXR1BQUG4evUq7t27J9Zys0ePHqyDQvPnz8fMmTMxZMgQqKqq4sCBA8y6sLAwVpkcp06dgpWVlcQsvLS0NPz999+s5r/LMtj4I6YWPHv2rNI+JcG3Tk98RNY1ymxtbbFy5UqJD03x8fFYuXIlDh06VFnbMqFx48Y4c+YMgoODmWuNtrY2Ro4ciREjRrDqyLR48WLMmDEDM2fOROPGjcWmN1+4cIF10VFZFjj28fGRat9spkxyleXKxRRPrgMXsqKgoADPnz+HiYkJgoKCZDpYwhWhoaFwcnLCgAED4OzsDGNjY7Rt2xbDhg3D4sWL8ddff0l9f1uClZUV9u7di9GjR8Pf3x+GhoY4cuRImXp40iCrOoh//PEH0zBBIBDA2dkZysrKYtsIhUIkJibC2tqa9X4I4kdA3aMIXiEUCjF79myEh4dDRUUFDRo0QEpKCnJzc9G9e3d4e3tLVXOE6yr4J0+ehKenJ9q0aYPu3bujfv36ZfbXr18/qTRLSEpKQmRkJKKiohAZGYn4+HgoKCjA0NAQx48fl1pv8ODB6NGjB5ydnbFkyRK8fPkSx44dAwBcvHgRa9aswc2bN1l5rchIaUWP7ZAhQ7B161bo6el9t9Avm1FEAwMD1KhRA8OGDUP37t3RsWNHmXbz4IKrV6/Cx8cH//zzD9PG1dDQEHPmzGF9I8YlWVlZePXqFZo3by42hSc8PBwtWrSAtra2VHqGhoYICgqS2Mnk8ePHsLGxqXSXNlnCxdSCErjouEFwh6QaZSW1bSpTo+xb3X0ePXqEMWPG4OnTp5Wxzgs+f/5cJpj7/PlzaGpqsjq+/fv3h729PWxsbAAAI0eOhJKSElPguHHjxhUucPx1QC4/P58pEK2srMzUHalRowaUlJQQEREhtV9J5OTkICUlBc2bN2cd0PnR3aPkiaKiIiaTS5YDciVs27YNnz9/ljjFys3NDfXq1cPcuXOl0jQxMYG/vz/MzMxgYmKCXbt2Md5v3ryJBQsWsP6+QkJCsG7dOtSvXx99+vTBgQMHYGpqio0bN6Jp06asNIcMGYLU1FRkZGRUKkMsLCwMV65cAVB8P25lZVXm715RURE6OjoYNWpUudljBCEPUKYNwSuUlJSwe/du3Lx5E3fu3EFaWho0NDRgaWnJqrAi1zVHSoIV4eHhCA8PL7OeTXvuxYsXIzIyEklJSUyNlX79+sHMzAwdOnRgNSoJAJMmTcLy5ctx/PhxpKenixV1joiIgL6+PitdQPJc6YyMDCQlJaFOnTpSpaq3bduWyQjiYhSxR48eiI6OxvHjx/H8+XM8ePAA5ubmlTq2XBIWFobZs2fDxMQErq6uqF+/PlJTUxEaGgoHBwd4eXlVqnPIzZs38fDhQ6ZLhKmpaaVvVDMzM3H//n2cP3++TGDh+vXrUk/j+NbYQ0ZGRqW+t4yMDFy8eBHx8fESgyBsppxwNaLMVceN0uTm5iIjIwNqamoy63T0vwxXNcq+xf379ysVEOKKFy9e4N69e0hPT4eGhgY6dOiA1q1bV0pTUvZdZX7LZFngODIykvnvR48eYd68eXB0dIS1tTVUVVWRlZWF0NBQ7Nq1i3Wr6+9lBu3fv7/C9fq4nuL5rcGdatWqoXbt2jA0NES/fv2qtONPtWrV0LRpU6Snp3Oif/bs2XI7OnXs2BG+vr5SB200NTWZmo1NmzbF3bt3md/xV69esfY6Z84cXL58GRMmTGCyWAYOHAgXFxf8+uuvWLJkCRPglAZZ3dv16dOHuf9JSUnB8uXLyz3fnzx5wqoYM0H8KChoQ/CSrl27yrxDCheURPhlSXJyMkaMGAFzc3OYmpqWSfVky6hRo9CiRQs8evQIbdq0YYrDAsVFnqWdelaaU6dOSVweGxuLBQsWSFUfpXRGDhdBNz8/P4hEIjx//pyZrhAcHIz09HTo6+vDwsKCdT0XLvDx8cGgQYOwZcsWseV2dnZwdnaGj48Pq6BNamoqZs+ejQcPHkBdXZ0ptOjl5QVTU1N4e3uzqiF1/vx5uLi4QCQSoW7dumW6QlS0aHB4eDiuX7/O/Hv//v1laq3k5eXhzp07MDQ0lNonUHwzO3bsWAiFQuTk5KBu3bpIT09HQUEB1NXVoaqqyrpOyIsXL+Dn54eYmBgmIGZiYoLp06dDT0+PlSYXHTdK4Fs2F1+QZY2y3bt3Y/fu3QCK/47s7OzKPPgIhUIUFhZi3LhxMv8sbBEKhVi0aBEuXboEkUgEJSUlCIVCCAQCWFtbw93dXaoMWi7hqsDx2rVrYW9vj5EjRzLLVFVVMWrUKOTl5WHNmjWsMmi/1/p8y5Yt2LFjR4W0uJ7i+c8//yAlJQWfPn0S+81JT09H3bp1oaKigkOHDmH79u04ePBghaehccHMmTOxc+dOdOjQgXV9pPJISUlBo0aNJK7T0tJiNVXdwsICUVFR6NWrF2xsbODu7o64uDgoKioiLCwMgwcPZuX18ePHOHDggNj9ooGBAYKDg7Fjxw6sWrWKVdCGi3u7x48f48mTJ2WCNpXtdEUQPwqaHkXwlpycHIltC6mY2H+IRCIsXboUs2fPRuPGjavajkTOnj2LvXv34vTp01VtRSIpKSmIjIzEkSNHEBkZySo7ikuMjY2xc+dO/PLLL2XWXb9+HbNmzUJMTIzUuo6OjoiJicGWLVvEbshu376NRYsWwcTEBL6+vlLr9u3bF0ZGRli7di2rgtklHDx4EAcPHgRQPFWwXr16ZR7sFBUVoauriwULFqBVq1ZS72PmzJkQiUTYsWMHTE1NERwcDAMDA5w/fx7btm2Dl5cXq1ovf//9N5ycnKClpVWm88j79+/h4+ODHj16SK3bvn17bN++XeZBlNLZXAMHDhTL5nr48GGls7mI/yhdoywqKkqqGmURERGIiIiASCSCr68vRo0aBS0tLbFtSv4mevbsyaqVNhds2rQJR44cwdKlSzFw4EAmy+T8+fPYuHEjxo4dKzeB8mnTpiEzMxMzZ87E1q1boaury0yHOnbsGPbu3YtLly5JrWtsbAwfHx907969zLpr165h9uzZePjwodS6pqam2LNnDywsLJCcnAwrKysmMygsLAyrVq3CjRs3pNblYornrVu3sGrVKmzcuBEdO3ZklkdFRWHp0qVYtmwZWrRogRkzZkBPTw/e3t4y27e0zJw5E48fP2YGcyQVZ2fbltvKygrTpk3DhAkTyqwLDAzE7t27xQYsKkJqaiozBRMAAgICEBoaynSTmzVrFmrWrCm116ysrG9OKbp//z7r+lFfU9lpfW5ubjh69Gi5na4WLFgAOzs7mXglCC6gTBuCV4hEIuzcuRNBQUFITU2VuI08PVCXcO3aNTx69Ajv37+Hg4MDGjdujMjISDRv3lzmozSlKSoqwqlTpzBhwoQKB23y8vKQkJAgMSDGRepo7dq18ebNG5nrsiUhIYGpExQVFYWEhASmK4S9vb1MW1DKAnV1dcTHx0sM2sTHx7Oux1NyA106YAMAXbp0gbOzs1TTAErz6dMnjBkzplIBG6A4k6jkBqtXr17YuXMnDAwMKqX5NTExMVi/fj0TDMrPz4eCggKGDBmCz58/Y926dThy5IjUuu7u7ujWrRt8fX3FRqpdXFzg6OgId3d3VkEbrjpucJXNRfxHeTXKpDmnLSwsmOuTQCCAjY0Np78vsuLcuXNYsGABRo8ezSxTVVXF6NGjkZOTg3379slN0IarAsdNmjTBkSNH0K1bN7EHUpFIhD/++IP1oAtXmUFcTPHcvHkznJycxAI2AGBmZgZHR0d4eHjg7NmzmD59OjZv3izz/UvDly9fxNrTy/K626dPH3h7e8PY2FisZlBMTAx8fX0xYMAAqTU1NTXFMmMnTZrEqpPg13yvBow8FPwugatOVwTxo6CgDcErAgICEBAQgKlTp2Lbtm1wcHCAgoICzp07h/z8fMycObOqLYrx6dMnODo64uHDh2jUqBGSkpIwduxYNG7cGMHBwVBRUcHKlSs59VDRZDqhUIhVq1YhJCQEhYWFErdhGxBLS0srsyw/Px+xsbHw9PSsdN0CWdK3b18oKyvD2NgYgwYNgoWFBUxNTat0Dv23GDhwIDw9PVGjRg1YW1tDTU0NmZmZCA0Nxfbt28UehKRBTU2t3ICPmpoa66BLt27d8ODBA1Y1qMqDq5bfQqEQqqqqqFatGtTV1ZGSksKsa926NetuTW/fvoWrq2uZqQXVqlXDuHHjWHWJAWTXceNr4uLi4OzsLHHd0KFDMWvWLJnt638NrmqUSTqH3r59izdv3qBNmzZylZGanp7OtCf/Gh0dHc5qh7ChVatWuHLlisQCx4sXL2Y1ZRQAFi5ciLlz56Jfv37o2bMnk3139epVvHv3rsJTmL6Gq9bnQPGg0J07dyTW+xIIBFIHBeLj48UK05dGXV2dGdxp3rw5U7C5quCy09W8efMQHR2NMWPGQFdXl2m4ERsbC0NDQ7FA4c/K96b1eXp6Vrjgd2m46HRFED8KOksJXnH8+HHMnj0b48ePx7Zt29CnTx8YGRnB0dERDg4OcpWxAQDr16/H58+fcfbsWbRo0UJsKkWXLl1Yp89yga+vL27evIlNmzbB2dkZbm5uqFmzJkJCQvDmzRusWLGCtXbnzp0lprOKRCI0atSI1TQbrggMDISxsbHc1FD4HgsXLsS7d++wYsUKuLm5oXr16igoKIBIJEK/fv2wYMECVrp2dnZMWn3pB8esrCzs3buXdY2j1atXY/78+cjNzUXnzp0l3qRXJKNL2ikIbLq0aWtrIzExEebm5mjTpg3++OMPWFpaonr16ggKCkKDBg2k1gSKC6G+fftW4rq3b9+yDmKuXbsWqampGDJkSKU6bnwNV9lcBHc1yjZt2oTCwkIsW7YMAHD58mXMnz+fqcfk7+8vN23cdXR0cPr0aYnnV0hISLkBnapE1gWO+/Tpg+PHj2PPnj24cuUKU+fK2NgYXl5erOtycZUZlJqaigkTJuD169cQCATM4FDp33lpgzY6Ojrw9/dHp06dxAZJsrOz4e/vz0xxTUlJKTMd6Weidu3aCAoKwqlTp5iGG3p6erCzs8PQoUNZ3Zvk5+fjwIEDCA0NRVJSUplMaoFAgHv37snqI1QaWRb8Lk1Jp6umTZsyna4mT55cqU5XBPGjoKANwSsSExNhaGgIBQUFVK9enamGXzJCvWzZMtYPqVwQHh6OtWvXQldXt0z2SqNGjZCcnFxFzsoSGhoKJycnDBgwAM7OzjA2Nkbbtm0xbNgwLF68GH/99RfrWhkbNmwoE7RRVlZGw4YNYWJiIlejHGZmZmWWyaJFKlcoKSnB29sbz58/R1RUFDIyMqCuro6OHTtK/RCxbt06sX8nJibCysoKnTp1YkZ+7969i1q1arE+d798+YKcnBzs3r0be/bsEVtXUuC2Ihldc+bMqfA+2dYhGjRoEJNNM3fuXGZ6XMlDCttiiW5ubliwYAFUVFTQp08fZprC5cuXceDAAWzdupWVLhfd1ADusrmI4uxRLrh8+bLY34inpyesrKwwd+5cuLu7Y/v27di3bx8n+5YWR0dHzJ07F4mJiejXrx/q16+Pjx8/4uLFi3jw4AHrLBO+YWhoyLpLVHlwlRm0adMm1KlTB4cOHYKVlRWOHj2K+vXrIyQkBKdOnSpzba8Iy5cvx7Rp05jfnDp16uDz58+4c+cOCgoKmPP1+fPnsLa2ZuVblnwr0wgAJk+ezFpbSUkJo0ePltm1dfXq1Th16hR69eqFbt26ybRIPRdwMa2Pq05XBPGjkJ8nJYKoABoaGsjOzgYANG7cGE+fPmWmWXz+/LnKU2a/prCwsNzibhkZGXL1w/n+/Xu0bNkSCgoKUFZWZgJiAPDrr79iwYIFWL16NSvtESNGyMom53Axl/pHoK+vX6mRXqDsNKPq1atDTU1NLOBRkhlz9epVVp2TFi9ejKSkJKxYsQLa2tqs/wa46Mz2NaVvuk1NTXH27Flcv36dyRJi2+XJ1tYWBQUFWLp0KZYuXcpkRwHFx7z0CLU0I6BcdNwAuMvmIooDo1lZWczfbl5eHvbv34/Y2FhYWlqyvnampqYydVDevHmD+Ph4eHh4QE9PDxMnTpSbGjElD7tLly7FyZMnsXnzZrHuZD4+PujVq1cVu+Q/ss4MioyMxPLly8WCPo0bN2aKt69Zs0bqoKCZmRkuXbqEAwcO4PHjx3j58iU0NTUxevRoTJo0idmXPFxvUlNTMXHiRLx69arcTCO2QRtbW1vo6OhgyZIlZTLvYmNjsXr1ahw6dEgqzcuXL2PJkiUYP348K08/Gi6m9XHV6YogfhQUtCF4RYcOHfDo0SNYWVlh8ODB8PHxwYcPH1C9enUcPXpUpnUyZIGxsTGCg4MlZqicO3cOHTp0qAJXktHU1GQCNU2bNsXdu3dhaWkJoLj1cWUwNDREUFCQWFG9Eh4/fgwbGxu5KSDN1Vxqrnn+/Dnev38vsYB0RacGcVUbpjQxMTHYunVrpQvXNmnSREaOvk1hYSEePnyI9+/fQygUQklJCUpKSnj69CmePn2KYcOGSa05ZcoUucvY+hayzOYixFmxYgUMDAzg4uICANiyZQv+/PNP6OnpITQ0FDk5OawetGrXro2PHz8CAG7evAl1dXVmOpSSkpLE60RVoKSkhIULF2Lfvn04ceIEsrOzkZmZidq1a7PqZsNXioqKcOzYMVy8eFHidVwgECAsLKyK3JUlMzMTdevWRbVq1aCqqsqca8B/HavYoKmpyfwtyDObNm2ChoYGwsPDZZZpVEJERAQePHjAFB4u3f47KysLkZGRUmvWrFmzTKtreYaLaX0hISESCycrKirC2dkZvXv3rpRnguAaCtoQvMLJyYmZljFz5kxkZGTg7NmzTNvCytRd4YJ58+bB1tYW48ePh7W1NXPjtXv3boSHh+OPP/6oaosMFhYWiIqKQq9evWBjY/N/7d17XMz59wfw13SPLnQTotAqIt0pl1wiX227WPevlI1Urq22RJLCoiIrSTaJXHdbicjKbX+u5VIs1rpEum1R2026zu+PHn2+ZmeipplmRuf5eOzjoc9nes+ZluYz53Pe52Dr1q148eIFZGVlkZqaii+//JLvtT/WDLm+vl5sRs8CwttLLSx//fUXVqxYgaysLJ4/Z3EbUa6rq8tUlQhKXl7eJx/Dz/SVhw8fYunSpcjPz2/2Z8tP0mbp0qWt/h5Rq6+vR2VlJbp27cr0OHr8+DHzd4ufnwNp/Bk2jfatq6tDYmIivL294eLigqioKBw9epSvpI2FhQV+/PFHvH37FjExMRxJ0hcvXnB8EBS1vn37Ij8/H0Djh8uOlKxpEhISgtjYWFhaWmLo0KFiVYXLi46ODtOYXV9fHydPnsSYMWMAAKmpqW1qdF1eXo4nT56gqKgIWlpa6N+/f5unDQqaMCqNPhQaGoo9e/Zg6tSpCA8Px9ChQ9sU7/z583H48GEMHz5crK63mqOqqvrRbX28tqN9irAmXRHSXihpQyRK3759maaEcnJy8Pf352uLRnsxNTXFgQMHEBYWxpR9R0VFwcTEBPv37xfKCO0PSUtL48CBAxyjKZvj5eWFkpISAP9rIJiSkoLq6mo4OTm1ekJMUVERx7SdFy9ecF0sVFdXIyEhge9xpsIgrBGpwrJmzRpIS0tj9+7dbdpuBLRPc18/Pz9s2bIFX3zxhcAmHI0dO/aTlSv8JK4CAwOhpKSEuLg46OvrC+WDVH5+PvLz82FoaCi2H1aFlbwijT2emj6QZmZmoqKiApMmTQIAmJubIyoqiq91V69eje+//x6hoaEwMjLiuFOdlJTEs3eXqHz33XfYtGkT+vXrh8GDB4s6HJE4deoUli5dKjGT2EaPHo1r165h0qRJ8PDwwOLFi2FtbQ0ZGRm8efOm2WlzH9PQ0IDw8HAcPHgQVVVVzHFFRUXMnTsXK1asEJuEg7AqjZpoa2vjyJEjWL16NVxdXeHj48N383+gcctVYWEhxo8fDwsLC54DAMTpWtrR0RGBgYGYOHEix/GGhgacP38eUVFR+OOPP0QUHSGiQUkbIrEKCgpQWFiIbt26tWlspbCZmpoiPj4e79+/R2lpKVRUVNo8Pvrp06eIiorC/fv3mSkTQ4YMwaJFi7gmz1hZWbVoTU1NTY67Ri4uLq2e/vChY8eOISIiAiwWCywWC35+flyPYbPZkJaWFvrY89YQ5ohUYXj27Bl27NiBUaNGtXmt9mjuu2nTJoFPOIqIiOA6VlZWhqtXryIjI4OvDxBA4882PDy8xf+GWqPp30dRURFYLBZ++eUXGBkZYfHixbCysoKzs7PAn5Nf7ZG86qi0tbWRkZEBS0tLnD9/Hvr6+sxUstLSUigoKPC1brdu3ZrtexETEyNW0/FCQ0Pxzz//YMaMGejSpQvXZCB+p55JkpqaGrHaLv0pK1euZP5sa2uLI0eOIDU1Fe/fv4eNjQ1fQwu2bt2K+Ph4uLm5wd7eHhoaGnjz5g1SUlKwd+9e1NbWYtWqVYJ8GXwTZqVREzk5OYSGhsLAwACbN2/G48ePMWXKFL7WOn36NPbt2wcWi4UbN25w/Q5nsVhilbSZMGECVqxYAUdHRwQEBEBZWRkvXryAr68v/vrrL3z//feiDpGQdkdJGyJxjh07ht27d3NMr9HS0oKHhwdmzZolwsi4HT9+HBMnToSKigoUFBT4vgD/0OXLl7FkyRJoa2vDzs6OmeqTmpqKKVOmICIiAqNHj+Z7fUGVJk+ZMgVWVlZgs9lwdnZGQEAAM7KziaysLPT09Hg2SRQVYY1IFRZDQ0MUFxcLZK32aO4rjAlHzfXHmTp1Kn744QekpaUx1Qutoaenh8rKyraGx2X//v0IDQ3F/PnzYW1tjW+//ZY5Z2VlhZSUFLFK2ggzedXRTZs2DTt27EBKSgoeP37MkdzOzMwUWDUa0DhOPjs7GwMHDvzkVoH2ZGRkJDbjx0XF0dERFy9eFLu+fM3Jy8uDpqYm8+F/8ODBTJVUbW0t8vLyWl1Be+LECSxbtgxubm7MMXV1dRgYGEBBQQH79u0Tm6SNMCqNmrNw4UL0798f3t7euHr1Kl9rhIWFwd7eHsHBwWL1b785QUFBGDduHPz9/eHo6Igvv/wS8fHx0NfXx6+//irQ34uESAoW+2PNJggRM3v27MH27dvx9ddfc92JOXXqFFasWIFFixaJOkzGoEGDwGKxMHz4cDg6OmLcuHFtTtxMmjQJurq62LVrF6SkpJjjDQ0N8PT0RHZ2Ns6cOdPqdYVZmpyWliZ2HxQ+hdde6idPnkBTUxNqamoiiorb48eP4evrC19fXwwdOlSsxqeLg+vXr2PFihVIS0tr9fempaVh48aN2LZtm0AvEu3s7DB16lR4enqivr4eRkZGSEhIgJGREX7//Xf4+Pjg5s2bAnu+tpoyZQoWLlzIV+KLfFpiYiIePHiAgQMHYurUqUxSMyAgAGZmZnxtPdu8eTPq6+uxZs0aAI3TY7y8vFBXVwdVVVXExMR0+ESJOElKSkJ4eDhMTExgY2PDc/sKP9tRhUUYwwUsLCywY8cODB8+nOvc1atXsWLFCty+fZvvmIXp/v37uHDhQpsqjZo4OTkhMDCQ6z3nxYsX8PDwQHZ2dqt/tqampoiMjJSYpGCTP//8EzNmzEBtbS0GDBiA48eP0zUO6bDobz6RKAcPHoSrqytXaeTYsWOhrq6OgwcPilXS5tq1azh37hySk5Px/fffQ15eHmPHjsWXX36JkSNH8vXmk5OTg1WrVnEkbABASkoKc+bMYUZVt5YwS5Ob7tBnZWVxbOkaPHgw06NI3HTt2hVsNptJ3rBYLLGclNOvXz+YmJhgwYIFkJKS4hoR2pqR0f/88w9UVFQgJSWFf/7555OPF0QJuLDdvXuX760gwcHBAt/KBTQ2uG6uYktWVhbv3r3jK15h8fPzw8aNG2FgYEB3OAUsLy8PDg4OPBMza9euRVFREV/rnj9/nmO747Zt22Bra4vly5dj69atCA8Pb1OjVCJYTROT8vLyeN50EbeG8h+739s0Za+17O3tkZyczDNpk5ycjPHjx7d6zfZibGzMM4HFj4MHD/I83rdvX5w7d46vNW1tbXHv3j2JStokJSVhw4YN0NHRgZ2dHWJjYzF//nz88MMP0NHREXV4hLQ7StoQiVJZWcmMof63ESNG4OjRo+0c0cepqqpixowZmDFjBoqKinDmzBmcPXsWHh4eUFVVhb29PYKCglq1poGBAXJycniey8nJ4epp01LCLE1+9+4d1q5di7Nnz6KhoQHy8vKorq6GlJQUJk6ciODgYGYijTi4evUqIiIi8PDhQ9TV1UFGRobpNzJy5EhRh8dh3bp1OH36NMaPH48+ffq0qd+ItbU1c/d02LBhQmnuKwwbNmzgOlZTU4MXL17gzp07HNuPWkMYW7mAxikjDx484HkBnZmZCT09PYE/Z1sIK3lFgHHjxjVbsfDkyRO+KhaAxkbwTdtTsrOzkZWVhZCQEPTv3x9OTk7w9fVtc+xEcNpja2pbPX/+HM+fP2e+vnXrFgoKCjgeU11djeTkZL7GS1taWmL79u1wcnLi2vqdnZ0NLy8vjmb54lB59Pvvv+PBgwcoKCiAh4cHevTogfT0dPTu3bvN/e+eP3/OrP3NN99AU1MTr169grq6equrlqdNm4b169fj/fv3sLa25lnJJezBGK2xbNkynD9/HnPnzoW3tzfk5eUxadIk+Pj44KuvvoKfnx+mT58u6jAJaVeUtCESZcSIEbh+/TrPOzHXrl0T67sImpqacHZ2hrOzM65evYrVq1fj559/bnXSJiAgAN999x0UFRVhZ2fHTDQ6f/48YmNjERYWxld8Tds0eDEyMkJ9fT1f6wKNH/ouXbqE4OBg2NvbQ0lJCRUVFUhJScGmTZuwYcMG/PDDD3yvL0gJCQnw9/eHhYUFfHx8mAvHc+fOwc3NDcHBwZg2bZqow2ScO3cOq1at4mss8L9t2rSJudjetGmTUBIWwnDx4kWuY/Ly8tDW1sa6dev4vrjbvHlzW0PjacaMGYiIiEDXrl2ZDx51dXW4fPkyYmJisGLFCqE8L7+ElbwiwqlYABon3TVNtLl27RpUVVWZ7VBycnKorq7ma10iHD179hR1CJ909uxZpuk7i8Vq9lpDRUWFr/fzpptCf//9N9LT05s93/T8orxpUFxcDE9PT2RmZqJ79+7Iz8/HrFmz0KNHDyQkJEBRUZHvAQtVVVXw9/fH2bNnwWKx0NDQgJEjR0JTUxNhYWHQ0dFhKrNaasGCBQCA6OhoREdHc/w+Z7PZIv95/tsff/yB2NhYDBs2jDlmaGiIhIQE7NixA4GBgZS0IR0O9bQhEuXKlStYt24drK2tMW7cOI47MTdv3sT69es5Jk+I052DgoICJCcnIzk5GY8fP2YqbdavX9+qdUxNTVFXV4e6ujoAgIyMDMefP6y0aM3WmDVr1oDNZmPTpk1c55qaY/KbWDEzM4O3tzfmzJnDde7QoUPYtm1bi+MUtrFjx2LYsGHN/hxu3brFM0kgKqNHj0ZQUJBApkeR9rNhwwYcOnSIuShv2u44Z84csZriQQTvw4qFZcuWYeXKldDV1eV4TFPFQk5ODk6fPt3q51i+fDmePn2K//73v4iJiYG1tTU2btwIoPF37qFDh/jqfUaES5iVG21VXl6OsrIysNls2NnZISIiAgMGDOB4jKysLDQ1NflK8ubm5rbq8aJMdK1cuRJ//PEHIiMjoauri0GDBjF9yU6ePIndu3cjJSWFr7UDAwNx/vx5bNmyBRYWFjAxMWHWTkhIwP79+3Hq1KlWrXnr1q1P/j8Rp0bzFRUVH60munfvntgNhSBE2KjShkiUpn41J06cwIkTJ8BisTjuVLq7uwMQnzsHxcXFOHv2LJKTk5GRkQEFBQXY2dlh+fLlGD58OF89bb799luh3PUWZmmyvLx8s3uQe/XqJVaN5YqLi+Hg4MDznIODA86ePdvOEX3c/PnzER8fDxsbG7H6Oba3/Px8pKamIj8/HzU1NVznxS0R4u/vD2dnZ1y/fh0lJSVQVVWFtbW12G2NIoIn7IoFAFi9ejW+//57hIaGwsjIiGMKXlJSEiwsLPhalwiHMCs3BEVZWZnZGnnhwgVoamoKdHS8JFQbNbly5QqCg4PRr18/rirk7t27c0w3ba1z587Bx8cHI0aM4Fq7Z8+erU5uAcDQoUP5jkcUPrX9ixI2pCPquFf4RCIdOHBA1CG0ysiRIyEtLQ1bW1ts27YNY8aM4WoU21pLly4VUHSchFmaPHXqVBw5cgQjR47kKss9fPgwpk6d2obIBWvIkCF4+PAhzy14jx49Ysaaiovs7Gz89ddfGD9+PCwtLXnuVec3YZGeno5jx47h5cuXPLdTtPZun7CcOXMGPj4+YLPZUFNT4+rrw2KxxC5pU19fj6KiIigrKzO/EzIyMpCRkQEAfE0MIpLB2dkZU6ZMEVrFAgB069at2ffLmJgYgX7YJm23ceNGlJSU4PTp00zlRhNra2vs3r1bhNFxa0qwCKMyqKKiAgUFBTzfc8Slerq+vh6dOnXiea6srKxNveXevXsHTU1Nnuc+nOzZGvPmzUPfvn3h5+fHdQ36/PlzrF+/XuKurwnpaChpQySKOJVvtsSGDRswfvx4gY66njdvHtatW8dziktWVhbWrVvH15uvMBshqqqq4tGjR5gwYQLGjBnDVPFcunQJNTU1MDc3R2xsLIDGD9guLi5Ci+VTvvvuO3z33XeoqamBnZ0d1NTUUFxcjPPnzyMxMRHbtm3jmKwk6glKly5dYrbW8BqHym/C4v/+7/+waNEiWFtb448//sCoUaPw/v173L17F9ra2rC0tGxz7IKyfft22NnZITg4mKtJrjh6+PAhli5divz8fJ49TVgsFiVtPmNNFQvV1dXw8fFBr169hFplkJ+fj/z8fBgaGqJTp04CfT8igiHMyg1hEEZl0N9//43Vq1fj+vXrXOfEpXq6ibGxMRISEniO9k5OToaZmRnfaxsYGOC3337DiBEjuM5dvnyZI6HXUmlpacjIyMD9+/exa9cudO/enTlXUVHB80YdIUS8UNKGSJzExMSP3v2/e/euCKLibcqUKcyf379/j7KyMqioqEBBQYHvNdPS0lBZWcnzXEVFBc8P7i3Rmg8NbDYbfn5+WLp0KTOh5GO2bdvG/JlXQunD7QGiTtrMnDkTABAREYFdu3Yxx5s+XM+aNYvj8aK+iBRWf52dO3fC2dkZ3t7eMDIywvLly2FkZITc3Fy4urpyNAgUteLiYsycOVMiEjZAY88CJSUlxMXFQV9fv013ZYnkkpeXx44dO/j6ENYSx44dQ0REBIqKisBisfDLL78wU/CsrKzg7OwslOclrSfMyg1hEEZlkK+vL16+fAl/f3/o6emJ3Wv+0IoVKzBv3jz897//hb29PVgsFlJTU7Fnzx5cvnwZR44c4XttT09PeHp6oqqqChMnTgSLxcL9+/dx+vRpJCQkYO/evXytGxoaij179mDq1KkIDw+XuC1ThHR0lLQhEuXkyZNYu3YtpkyZgnv37uGbb75BQ0MDLl68CBUVFXz99deiDpHLpUuXEBERgcePHzN3iwYMGIBly5bxvEvTFvfu3YOamppA1+SloaEBiYmJmDt3bouSNn/++afQYxIUSZqaJEzPnz+Hl5cXpKSkwGKxmLLsnj17YunSpdi5c6fY/HsbOXIkMjIyxHp63IeePXuG8PBwiascJII3YMAAPHv2TOB/F/bv34/Q0FDMnz8f1tbWHGPvrayskJKSQkkbMSLMyg1hEEZlUGZmJkJCQmBnZyeoMIXG1NQUBw4cQFhYGLZs2QI2m42oqCiYmJggLi6uTdu4Ro8ejW3btmHr1q3MFuT169dDW1sboaGhfL/PaWtr48iRI1i9ejVcXV3h4+ODefPm8R0nIaR9UdKGSJTY2Fh4enrCzc0Nx48fx5w5c2BkZISKigq4urqic+fOog6RQ2pqKpYuXYohQ4Zg1apV0NDQQFFREVJSUuDh4YEff/yxRRcoe/bswZ49ewA0VqI4OztzJRZqampQX1/Pc0KTMLRm8Fx6ejoGDhzI8//Pu3fv8PDhQ7HZbiNO/XWak5iY2KrH87PVRl5eHg0NDWCxWNDU1ER2djbTvLRz584oKCho9ZrCsn79enh5eeH9+/cYNmwYz74+4tILAQD09PSarZYjHUtTw2A1NTXY2tpCUVFRIOvGx8czd+z//aG6T58+yMrKEsjzEMH4WOXGlStXcPjwYVGHyEEYlUG6urrMJExx5+fnB09PT8THx+P9+/coLS2FiooKFBUVkZubCz8/P76aiNfV1eHJkyewsrLCxYsXkZWVxTSq57UlvrXk5OQQGhoKAwMDbN68GY8fP+aoCCeEiC9K2hCJ8urVK5iZmUFaWhrS0tKoqKgA0NhpfuHChdi0aRPmz58v4ij/JyIiAg4ODggNDeU43rTtJCIiokVJm59++gljxoyBnp4edu3ahUmTJnHsSQYaG1f269cPY8aMEehrEIR58+bh2LFjMDY25jr34sULzJs3T6TbjBwdHREWFob+/fvD0dHxo49lsVhISkpqp8h4+7ApNAAmgfdhIu3DpB4/SRtDQ0NkZWVh+PDhsLa2RlRUFLp27QoZGRmEh4ejf//+/AUvBJWVlaiqqsKePXsQHR3NcU7ceiEAjRf8GzduhIGBgUAuxInkcnZ2Rm1tLTPdSUFBgePfLovFwp07d1q97t9//93shBVZWVm8e/eOv4CJUHyscmP//v1ilXQGhFMZ5Ovri82bN8PAwAB9+vQRRJhCc+LECcyePRu9evWCgoICx5b3kpISJCYm8pW0kZKSwsyZMxEdHQ0bGxv06dNHKD+LhQsXon///vD29sbVq1cFvj4hRPAoaUMkipKSEjPOt1u3bnj27BmzL7e+vh4lJSWiDI/Lixcv4O3tzfPc119/jcWLF7doncrKSjg5OcHExAS7du3CN998I3bl0h/zsaqcqqqqNvX4EYRBgwYxd7iNjIzEfnvUh00DX716heXLl+Prr7+Gvb09NDQ08ObNG6SkpCApKQnh4eF8PYezszNycnIANDZndnd3h4eHB4DGMuudO3e2+XUIiq+vL/Lz87F27Vqx74UAAMHBwSgqKoKjoyO0tLS4evGIQ2KQtI9vv/1WKL9vevTogQcPHvDcSpGZmUmj5cWQqakpR+VG586d8fbtW/Tu3VvUoXERRmWQtbU1bGxs4ODgING/F1+9esX3gAIpKSno6OigtLRUoDFZWlpyVTrb2tri2LFjzPs6IUS8UdKGSJRBgwbhyZMnGDlyJMaOHYtdu3aBzWZDRkYG0dHRMDExEXWIHFRVVZGVlcVzCkBWVhZUVVVbtE63bt1w6dIlaGhoAGi8k5OXl9fs41vSZ0bYMjIycO/ePebrU6dOcd0xrq6uxoULF9C3b9/2Do/Dh3fENm/eLMJIWubDi9mwsDDMnDkTbm5uzDF1dXUYGBhAQUEBoaGhiIuLa/VzfHgHtVu3bvj111/x6tUrvH//Hn379hWrkcH3799HWFiYRPRCACQjMUjax9KlS4Wy7owZMxAREYGuXbtiwoQJABq3Xly+fBkxMTFYsWKFUJ6X8CcmJgZVVVVYsmQJFBQU8Mcff8DDwwMVFRXQ0dFBTEyMWCVvhFEZFBISgtjYWBgZGUFPT0+s3mMA4PDhw0yDYRaLBW9vb67x2TU1NcjNzYW9vT3fz+Pu7o7IyEiYmZnxPTb93w4ePMjzeN++fXHu3DmBPAchRLgoaUMkyqJFi5hkxbJly5Cbm4tNmzahoaEBgwcPRlBQkIgj5DRp0iRs27YNCgoKsLe3h4qKCsrLy5GSkoLw8HDMmDGjRes4Oztjy5YtiI6OBovFwpIlS3g+Tpy2gly9ehUREREAGi9weF00yMjIoF+/fggICGjv8D4b9+7dw4IFC3ieMzIy4muKR5P8/HykpqYiPz+fqXD7ED+jxIVBknohAJKRGCTti81mIysrC6WlpVBVVUWfPn3alNhzdXVFfn4+AgICmNHLs2fPBgDMmTMH//3vfwUSNxGMn3/+Ga6urszXP/zwA/T19eHm5obdu3dj27ZtfFdNCsu/K4Oaerrw6/jx41i2bBk8PT0FGKXgaGlpMVOynj59ij59+nANfpCVlUXfvn0xbdo0vp8nJSUFJSUlsLOzg4GBAXOzrgmLxeL7ff358+d48OABCgoK8M0330BTUxOvXr2Curo6lJSU+I6ZECJ8lLQhEsXExISpplFRUcHu3btRU1ODmpoasXzDWblyJfLy8rB27VoEBARARkYGdXV1YLPZmDBhAr777rsWrePi4oIxY8bgxYsX8PDwgLe3t9iXty9ZsoRJLhkaGuL48eM8e9qQtlFTU8OZM2cwfPhwrnPJycl8TxM7c+YMfHx8wGazoaamxrXliMViiU3Sxs/PD1u2bMEXX3xBPWKIxDl06BAiIyNRXFzMJN7V1dXh6enZpsby/v7+cHZ2xvXr15lmptbW1mL/3tERFRQUQFdXF0BjP6KHDx8iPj4eFhYWqK+vR2BgoGgD/Ih/93Thl6ysLIYMGSKAiITDzs6Oo5rT09MTvXr1EvjzVFZWcvSxEUTT+qqqKvj7++Ps2bNgsVhoaGjAyJEjoampibCwMOjo6MDHx6fNz0MIER5K2hCJJycnJ3ZltE3k5OSwc+dOPHnyBLdv30ZZWRlUVVVhbm4OAwODVq2lq6sLXV1dTJkyBfb29kK5WOClpqaG6+crLS2NAwcOtLhB3oEDB5r9MC1u06Mkjbu7OwICApCdnQ07Ozuoq6vj7du3SE1NRXp6Ot/VZ9u3b4ednR2Cg4O5eguIm02bNlGPGCKRjh07huDgYDg4OGDSpElMT6ozZ84gODgYsrKymD59Ot/r9+rVCzNnzhRgxEQY5OXlmcEKN27cQKdOnZhG0srKyigvLxdleFz8/PyaPSclJQVlZWUMGDAAEyZMaHH1zfTp05GUlMTzBoS44afJcEs1t5WpLbZs2YKbN28iOjoaFhYWHK0EbG1tsX//fkraECLmKGlDSDswMDD4ZJKmoaEBLi4uCAoK+uidUGFdLCQmJqK8vBxOTk4AgL/++gtLlixBTk4OzM3NER4eDnV1debxVlZWLV7b2dlZrKdHSbIZM2ZAU1MTUVFRCAkJQV1dHWRkZDBw4EBERkZi7NixfK1bXFyMmTNnin3CBqAeMURy7d+/H05OTlizZg3H8XHjxkFNTQ0xMTF8JW3OnDmDvLw8nlsnY2Ji0KNHD/znP//hO24iWMbGxoiOjoaUlBRiYmIwatQoSEtLAwCys7MF1ttEUB4/fozCwkIUFxdDVVWVuVlQWloKNTU1KCoq4sCBAwgPD0dcXFyL+vEoKSkhLS0Ns2bNgrW1NVRUVDjOs1gsuLi4COkVfd7OnTsHHx8fjBgxAvX19RznevbsidzcXBFFRghpKUraECIm2Gw20tLSBFIKy4+YmBjMmjWL+brpLu/q1atx8OBBbNu2DRs3buRrbXGfHiXpxowZgzFjxqChoQHFxcVQU1ODlJRUm9YcOXIkMjIyeE6fETfUI4ZIqpycHIwZM4bnudGjR+Po0aN8rRsdHY2pU6fyPKegoIC9e/dS0kaM+Pr6YtGiRXB3d0ePHj2YEfAAcPbs2WbHt4uKj48PAgMDsXPnTpibmzPHb9++jdWrV2PNmjXQ1dXFokWLEBIS0qJpg2FhYQAae6llZGRwne9ISZuGhgbcvHkTWVlZPPvJzZ8/v1XrvXv3DpqamjzPVVVV8RUjIaR9UdKGEAIAyM3NZbYwFRcX486dO4iKisKoUaOgpqaGLVu2tGo9SZoe9bmQkpLialrIr/Xr18PLywvv37/HsGHDuO56AuBrQggh5H80NTVx79492NjYcJ3LyMho9oPWp7x8+RJffPEFz3P9+vVDVlYWX+sS4dDX18eFCxdQUlKCrl27cpzz9fXl+++BsGzZsgVLlizhSNgAgIWFBTw9PRESEoLTp0/Dzc2txdcOf/75pzBClThFRUVwcnLCy5cvwWKxmJteH1aTtjZpY2BggN9++43nJNPLly8zDZYJIeKLkjaEEACNH/hra2sBALdu3YKMjAyGDRsGoPGDxT///NOq9Wh6VPspKyvDuXPnmr0rx0/D4MrKSlRVVWHPnj2Ijo7mOCdOU8oIkWTTpk1DZGQkampqMHHiRKirq6O4uBhnz55FTEwMFi9ezNe68vLyePv2Lc9zRUVFkJGhyz9x9O+EDYBW979rD1lZWTwT+QCgqqqK7OxsAEDv3r3x/v379gxN4m3evBldunTBlStXYGtri+PHj0NDQwNJSUlITEzkej9uCU9PT3h6eqKqqgoTJ04Ei8XC/fv3cfr0aSQkJGDv3r1CeCWEEEGid21CCIDGCU+HDx+GtrY2Dh48iGHDhjENiPPy8jj62bTEv6dHHTt2TKwnQ0iqly9fYtasWaipqUFVVRXU1NRQWlqKuro6qKqqQklJia+kja+vL/Lz87F27Vro6elxTY8ihLSdh4cHysrKEBMTw3wYY7PZkJGRgZOTEzw8PPha19LSEtHR0Rg7diw6derEHH/37h1++umnVvUkI+Tf+vbti5iYGAwdOpSj0fC7d+8QExMDfX19AEBhYWGrqj/r6+uRmZmJgoICnjcgJk+e3ObYxV16ejr8/f05qqt69OgBd3d3sNlsBAUF4aeffmrVmqNHj8a2bduwdetWnDp1CkBjNa22tjZCQ0MlYhs0IR0dJW0IIQAALy8vuLu746uvvkLnzp0RGxvLnEtNTcXgwYP5XvvPP/9EfX097t6926EvxoRh8+bNGDJkCHbs2AETExNER0fD0NAQZ86cwfbt27Fjxw6+1r1//z7CwsI4RpwSQgSLxWJh1apVWLRoEe7fv4/S0lKoqqrC2NiYZ9VFS3l5eWHWrFkYP3487O3toaWlhcLCQpw7dw61tbXYtm2bAF8F6Wj8/f2xcOFC2NraYujQoejatStKSkpw8+ZN1NXVMUmFJ0+ewN7evkVrPnz4EEuXLkV+fj7PPngsFqtDXCeUl5czfemUlJQ4Kuaa3uNbo66uDk+ePIGVlRUuXryIrKwslJSUQFVVtdmpnoQQ8UNJG0IIAMDc3ByXLl3Cy5cv0bt3b47S52nTprVo+kNzHj16hCVLlnT4izFhuH//PjZu3MhURdXW1kJaWhqOjo4oKSnBhg0b+Gpmqquri7q6OkGHSwj5l+LiYsTFxSEzMxNFRUXQ1NTEkCFD4OzsDDU1Nb7W7NevH3755Rf8+OOP+O233/DPP/+gS5cusLGxwZIlS6CrqyvgV0E6EgsLC/z222+IjY3FH3/8gWfPnkFTUxMzZsyAi4sLUyXy3XfftXjNwMBAKCkpIS4uDvr6+h22ulNHRweFhYUAGnsdnTx5kmlWnpqaii5durRqPSkpKcycORPR0dGwsbFBnz590KdPH0GHTQgRMkraEEIYSkpKXA3pampqYGtr26Z1161bRxdjQlJTUwMlJSVISUlBVVWVudgDgC+++ILv5o5+fn7YsmULvvjiC7obR4iQZGZmYsGCBWhoaICNjQ309PTw9u1bxMfHIz4+Hvv27eN7W6muri4zkYcQQdPU1ISPj4/A1nv27BnCw8M7/NY9W1tbXLt2DZMmTYKHhwcWL14Ma2tryMjI4M2bN/D29m7VelJSUtDR0UFpaamQIiaEtAcW+2OzeAkhfKuuroaNjQ1CQkIwduzYFn1Pbm4utLS0RJLUSExMRHl5OZycnAAAf/31F5YsWYKcnByYm5sjPDy81X1tmpiamiI8PLzNyR/Cbdq0aZg7dy4mT56M+fPng81mIyIiAjIyMli1ahUePXqE3377rdXrOjo6oqioCGVlZdDS0oKysjLHeRaLhaSkJEG9DEI6pKlTp0JeXh579+6FkpISc7y8vBwLFy5EbW0tEhIS+F6fzWYjKysLpaWl6NKlC/T09Dim0BDSFuXl5Xjy5AmKioqgpaWF/v37c71XtNSUKVOwcOFCTJo0ScBRSrb79+8jNTWVuabk5zoqMTERMTEx+Omnn9CtWzchREkIETaqtCFESOTl5aGoqAhpaekWf0/Pnj2FGNHHxcTEYNasWczXwcHBkJWVxerVq3Hw4EFs27YNGzdu5GttPT09VFZWCipU8gEHBwemmmb58uVwdXWFlZUVMyp08+bNfK1rZGREH+4IEbJnz55hx44dHAkbAFBWVsbChQvh5eXF99qHDh1CZGQkiouLmYlv6urq8PT0xJw5c9oaOunAGhoaEB4ejoMHD6Kqqoo5rqioiLlz52LFihWtuvYBGqs7N27cCAMDgw5d3enu7g5LS0tYWFhg0KBBMDY2hrGxcZvWTElJQUlJCezs7GBgYMDVHJrFYmH37t1teg5CiHBR0oYQIZo8eTJ++eUXiagwyc3NZS6UiouLcefOHURFRWHUqFFQU1PDli1b+F6bLsaEZ/78+cyfTUxMcPr0afz++++orq7GsGHD0L9/f77W5TfZQwhpOV1dXZSVlfE8V15ejl69evG17rFjxxAcHAwHBwdMmjQJGhoaePPmDc6cOcMk5KdPn96W0EkHtnXrVsTHx8PNzQ329vbM36+UlBTs3bsXtbW1WLVqVavWDA4ORlFRERwdHTt0dWenTp0QFxeHkJAQKCoqwsTEBObm5rC0tISpqSnTv641KisrOfrY0E00QiQPJW0IESIVFRVkZGTA0dERI0eOhIaGBkf1AovFgouLi+gC/ICUlBRqa2sBALdu3YKMjAyGDRsGoHHv+j///NOq9RwdHTm+poux9tG9e3fMnDlT1GEQQlrg+++/R1BQELp3787Ry+PWrVuIiIjA2rVr+Vp3//79cHJywpo1aziOjxs3DmpqaoiJiaGkDeHbiRMnsGzZMri5uTHH1NXVYWBgAAUFBezbt6/VSRuq7mzUNNnt1atXSE9Px507d5CYmIhdu3ZBRkYGgwcPxuHDh1u15sGDB4URKiGkHVHShhAhanrzLSoqwtOnT7nOi1PSxtDQEIcPH4a2tjYOHjyIYcOGMXd08vLyWt3Phi7A2s+7d+9w4sQJ3LlzhxkZbG5ujilTpqBTp06iDo8Q0oyQkBCUl5fD2dkZysrKzOjk8vJyqKioIDQ0FKGhoQBal9zOyclhJs782+jRo/maKEdIk/r6ehgZGfE8Z2RkhPr6+lavyau6s6qqCoWFhejdu3eHu57Q1dWFrq4urKysYGZmhlOnTiEtLQ337t0TdWiEEBGgpA0hQsTv5B5R8PLygru7O7766it07twZsbGxzLnU1FQMHjy4VevR9pr2kZ+fDycnJ+Tm5sLQ0BDq6urIyspCSkoK9u/fjwMHDqB79+6iDpMQwoORkRHXxD5B0NTUxL1792BjY8N1LiMjgxnJTAg/7O3tkZycjOHDh3OdS05Oxvjx41u9ZkxMDKqqqrBkyRIAwO3bt+Hh4YGKigro6Ohg3759fG8XlCTPnz9Heno689+bN2+gr68PS0tLzJ49G5aWlnyt29DQgJs3byIrKws1NTVc5z/cak0IET80PYoQwqioqMDLly/Ru3dvqKioMMevXLmC3r17c+yJJuJh2bJlePToEaKjo9G3b1/m+IsXL+Du7o4BAwZgx44dIoyQENLeIiMjERkZCVdXV0ycOBHq6uooLi7G2bNnERMTg8WLF8PDw0PUYRIJlZiYiO3bt6N3796ws7ODuro63r59i9TUVGRnZ8PLy4ujynPChAmfXHPixIlwdXVltu198803kJOTg5ubG3bv3o3u3bt3iPcyQ0NDKCgoYPLkyRg1ahTMzc2hqqrapjWLiorg5OSEly9fMkMKAHBULz1+/LhNz0EIES5K2hAiZLW1tfjll1/w4MEDFBQUICAgAHp6ejhz5gw15iVtZmFhgaCgIJ5jUpOTk7Fu3Trcvn1bBJERQkSFzWZjy5YtiI+P59iqIi0tDScnJ/j6+oowOiLpDA0NW/xYFovVooSAiYkJoqOjYWVlhb///hu2traIj4+HhYUFUlNTERgYiKtXr7YlbIng7u6Ou3fv4t27dxg8eDAsLS1haWkJMzMzdO7cma81V65cidzcXOzYsQO2trY4fvw4NDQ0kJSUhMTERERHR6N3794CfiWEEEGi7VGECNHr16/h4uKCkpISDBw4EHfu3GG69qenp+P//u//8MMPP4g4yv95+vQpIiMjmQTTsWPHYGRkhO3bt8PMzEwipmB1NPX19ZCXl+d5Tl5enq/eAoQQycVms1FaWgovLy8sWrQI9+/fZ3pdGRsbo2vXrqIOkUi4CxcuCHxNeXl5VFRUAABu3LiBTp06wdTUFACgrKyM8vJygT+nOIqKigKbzcaTJ0+YLVIJCQkoLS2FgYEBrKysWp10TU9Ph7+/P8e2yB49esDd3R1sNhtBQUH46aefBP1SCCECREkbQoRow4YNUFNTw88//wwVFRWO3gWWlpZMo2JxcO3aNSxatAhGRkZwdHTE7t27mXMyMjI4cuQIJW3EkJmZGXbv3g0rKyuOqVzl5eWIioqCmZmZCKMjhLS32tpa2NjYIDIyEqNHj6bf20TgevbsKfA1jY2NER0dDSkpKcTExGDUqFGQlpYGAGRnZ6Nbt24Cf05xxWKxYGhoCENDQ9jb2yM9PR1Hjx5Feno6Hj161OqkTXl5OdTU1CAlJQUlJSW8ffuWOddU4UQIEW+UtCFEiNLS0hAWFgY1NTWuigdNTU0UFRWJKDJuYWFhmDRpErZu3Yq6ujqOpM2AAQPw888/izA60hxfX1/MnTsXtra2GDZsGDQ0NPD27VvcuHEDsrKy2LRpk6hDJIS0Izk5OWhra1OVHRG6iooKFBQUoLq6mutcc9OlmuPr64tFixbB3d0dPXr0gJeXF3Pu7NmzTNXN5+7169e4ffs20tPTcfv2bbx+/RoyMjIYOHAgXF1dYWVl1eo1dXR0UFhYCADQ19fHyZMnmelyqamp6NKliyBfAiFECChpQ4gQSUtLo7m2UW/evBGrccxPnz7FypUrAYBrtKaKigpKSkpEERb5hP79++PkyZPYv38/7ty5g2fPnkFVVRUzZsyAi4sLtLW1RR0iIaSdzZkzB/v378eIESOa3T5JCL/+/vtvrF69GtevX+c6x2azW9zH5kP6+vq4cOECSkpKuLbw+fr6dpiJZ+PHj4e8vDyMjY3h4OAAKysrmJiYQFFRke81bW1tce3aNUyaNAkeHh5YvHgxrK2tISMjgzdv3sDb21uAr4AQIgyUtCFEiCwtLREbG4tRo0ZBSkoKAJjO/cePH4e1tbWII/wfVVVV5k7Mv718+bLDXDBJou7du8PPz0/UYRBCxER+fj6ysrIwevRoWFlZQUNDgysZ7+/vL6LoiKTz9fXFy5cv4e/vDz09PcjKygpsbV49lwwMDAS2vriLj4+HsbEx5OTkBLbmh0kZW1tbHD58GKmpqaiuroaNjQ1toSREAlDShhAh8vb2xuzZs+Hg4ICxY8eCxWLh0KFDePr0KV69eiVWW47s7Oywc+dODBkyBLq6ugAaE0xFRUWIiYmBvb29iCMkTRwdHVv8WBaLhaSkJCFGQwgRN5cuXWI+9D148IDrPIvFoqQN4VtmZiZCQkJgZ2cn6lA+OxYWFgJf093dHZaWlrCwsMCgQYNgbGwMY2NjgT8PIUR4KGlDiBD169cPCQkJiIiIwOnTpyEtLY3Lly/D2toaoaGhYjViceXKlXjw4AG++uor9O/fHwCwevVqvH79Gn369MGSJUtEHCFpYmRkxHXXnBBCmly8eFHUIZDPmK6uLurq6kQdBmmhTp06IS4uDiEhIVBUVISJiQnMzc1haWkJU1NTgVb1EEKEg8VuruEGIYQvBw4cgIODA9TV1ZGXlwdNTU2Blg4LU21tLZKSknD9+nWUlJRAVVUVNjY2+Prrr+lNnRBCJEhxcTHi4uKQmZmJoqIiaGpqYsiQIXB2doaampqowyMS7MaNG9i8eTPCw8PRp08fUYdDWujVq1dIT0/HnTt3kJ6ejtzcXMjIyGDw4ME4fPiwqMMjhHwEJW0IEbABAwbg2LFjMDY25vgzIYQQ0h4yMzOxYMECNDQ0wMbGBurq6nj79i3TOHbfvn0YMmSIiKMkkmzLli2Ii4uDlpYWlJWVOc7Rtlzxlp2djVu3buHUqVNIS0vjq3E0IaR90fYoQgSsS5cueP36NYyNjZudHEUIIYQIy/r166Gvr4+9e/dCSUmJOV5eXo6FCxciKCgICQkJIoyQSLKQkBDExsbCyMgIenp6VIkr5p4/f4709HTmvzdv3kBfXx+WlpaYPXs2LC0tRR0iIeQTqNKGEAHz8/PDqVOnoKWlhfz8fGhoaDR7QcNisZCamtrOEfJmaGj4yT4pdCeGEELEn7GxMXbs2IExY8Zwnbtw4QK8vLxw//59EURGPgeWlpaYP38+PD09RR0KaQFDQ0MoKChg8uTJGDVqFMzNzaGqqirqsAghrUCVNoQIWFBQEMzMzPDixQvExsbC0tISGhoaog7rk1atWsWVtCkrK8O1a9dQWFiIefPmiSgyQgghraGrq4uysjKe58rLy9GrV692joh8TmRlZWl7nQQZPXo07t69i19++QVPnjxBRkYGLC0tYWZmhs6dO4s6PEJIC1ClDSECVlFRgc6dO4PFYmHs2LGIjIyEoaGhqMNqEx8fH/Ts2RPLly8XdSiEEEI+4ffff0dQUBA2bdoEKysr5vitW7ewZs0arF27Fra2tiKMkEiy7du3o6CgAFu2bBF1KKSF2Gw2njx5wmyRunPnDkpLS2FgYAArKyv4+vqKOkRCyEdQ0oYQAfuw+bCTkxMCAwPRr18/UYfVJlevXoWPjw/TxJIQQoj4cnR0RGFhIcrKyqCsrIyuXbuipKQE5eXlUFFRgZaWFvNYahpLWmvv3r04fPgwunXrBmtra6ioqHCcZ7FYcHFxEU1w5JMKCwuRnp6Oo0ePIj09nRoREyIBaHsUIQImLy+P6upqAEB6ejoqKytFHFHbZWVloaGhQdRhEEIIaQEjIyMMGjRI1GGQz1RYWBgAID8/HxkZGVznKWkjXl6/fo3bt28jPT0dt2/fxuvXryEjI4OBAwfC1dWVoxqPECKeqNKGEAGbOXMmGhoaMGrUKOzatQvTp09Ht27deD6WxWJh8eLF7Rwhb7GxsVzHamtr8fz5c6SkpODLL7/Exo0bRRAZIYQQQgjhh6GhIeTl5WFsbAwLCwtYWVnBxMQEioqKog6NENJClLQhRMAePXqEDRs24MWLFygtLYWioiKkpaV5PpbFYiEtLa2dI+SNV98dOTk5aGtrw97eHp6envQGTwghhBAiQW7fvg1jY2MazU6IBKOkDSFCZGhoiOPHj8PY2FjUoRBCCCGECER9fT0yMzNRUFCAmpoarvOTJ09u/6AIIeQzRUkbQoQoLS0NRkZGEjFSMTExsdlzLBYLysrKMDQ0RI8ePdovKEIIIYSIlYcPH2Lp0qXIz88Hr48R1NiWEEIEi5I2hBAAjVVBLBYLADguwj48xmKxYGdnh61bt9JWKUIIIaQDmj59Oqqrq+Hv7w99fX3IyspyPUZZWVkEkRFCyOeJkjaECNGHiZDmiMvdqMePH2PFihWYPHkyxo0bB3V1dbx9+xbnz5/HyZMnsX79euTk5GDz5s2YMmUK/P39RR0yIYQQQtqZqakpwsPDYWtrK+pQCCGkQ6CR34QI0apVq7iSNmVlZbh27RoKCwsxb948EUXGLTQ0FNOnT8eCBQuYY+rq6ujfvz/k5OQQFRWFuLg4lJSUID4+npI2hBBCSAekp6eHyspKUYdBCCEdBiVtCBEiFxcXnseXLl0KHx8flJaWtm9AH3Hnzh18++23PM8NHDgQu3btAgAYGxujuLi4PUMjhBBCiJjw8/PDxo0bYWBggH79+ok6HEII+exR0oYQEfnqq6/g4+OD5cuXizoUAICamhrOnTuH4cOHc51LSUmBmpoaAKCyshIqKirtHR4hhBBCxEBwcDCKiorg6OgILS0trv41LBYLSUlJIoqOEEI+P5S0IUREsrKy0NDQIOowGG5ubggMDEROTg7GjBkDNTU1FBcX48KFC7h58ybWr18PALh58yaNMCeEEEI6KCMjo0/26yOEECI41IiYECGKjY3lOlZbW4vnz58jJSUFX375JTZu3CiCyHi7cOECoqKi8PjxY9TV1UFGRgYDBgyAh4cHxo4dCwAoLS2FjIyMRIwxJ4QQQojwVVVVobCwEL1796aEDiGECBglbQgRIkNDQ65jcnJy0NbWhr29PTw9PcVydHZDQwOKi4uhpqYGKSkpUYdDCCGEEDERExODqqoqLFmyBABw+/ZteHh4oKKiAjo6Oti3bx969eol4igJIeTzQUkbQgghhBBCSItMnDgRrq6umD59OgDgm2++gZycHNzc3LB79250794dO3bsEHGUhBDy+aCeNoQIWXFxMeLi4pCZmYmioiJoampiyJAhcHZ2Zpr7EkIIIYRIgoKCAujq6gIA/v77bzx8+BDx8fGwsLBAfX09AgMDRRsgIYR8ZmjfAyFClJmZiQkTJiA+Ph7KysqwtLSEsrIy4uPjMX78eGRmZoo6REIIIYSQFpOXl0dFRQUA4MaNG+jUqRNMTU0BAMrKyigvLxdleIQQ8tmhShtChGj9+vX44osvsHfvXigpKTHHy8vLsXDhQgQFBSEhIUGEERJCCCGEtJyxsTGio6MhJSWFmJgYjBo1CtLS0gCA7OxsdOvWTcQREkLI54UqbQgRomfPnsHNzY0jYQM03olauHAhnj59KqLICCGEEEJaz9fXF0VFRXB3d0dlZSW8vLyYc2fPnmWqbgghhAgGVdoQIkS6urooKyvjea68vJymKxBCCCFEoujr6+PChQsoKSlB165dOc75+vpCU1NTRJERQsjniSptCBGi77//Hjt37kRaWhrH8Vu3biEiIgI+Pj4iiowQQgghhH//TtgAgIGBAQ1ZIIQQAaOR34QImKOjI8fXhYWFKCsrg7KyMrp27YqSkhKUl5dDRUUFWlpaOHXqlIgiJYQQQgghhBAizmh7FCECZmRkBBaLJeowCCGEEEIIIYRIOKq0IYQQQgghhBBCCBFD1NOGEEIIIYQQQgghRAxR0oYQQgghhBBCCCFEDFHShhBCCCGEEEIIIUQMUdKGEEIIIYQQQgghRAxR0oYQQggh7Wbs2LFYtWoV8/WtW7dgYGCAW7duiTAqTv+OsTkGBgbYuXNnq9f/9ddfYWBggAcPHvATHk87d+6EgYGBwNYjhBBCiHigpA0hhBDSQTQlC5r+Gzx4MOzt7REUFIQ3b96IOrxWuXLlCl8JE0IIIYQQSSIj6gAIIYQQ0r6WLVsGHR0d1NTU4M6dOzhy5AiuXLmC06dPQ1FRsV1jsbS0xP379yErK9uq77ty5QoOHTqEpUuXCikyQgghhBDRo6QNIYQQ0sGMGjUKgwcPBgBMnz4dXbp0QWxsLC5cuIAvv/yS5/e8e/cOnTp1EngsUlJSkJeXF/i6hBBCCCGfA9oeRQghhHRww4YNAwDk5OQAAFatWgVTU1NkZ2dj4cKFMDU1hbe3NwCgoaEB+/fvh4ODAwYPHgwbGxsEBASgtLSUY002m43IyEiMGjUKQ4YMgZOTE54+fcr13M31tMnMzMTChQthaWkJExMTODo6Ii4ujonv0KFDAMCx3auJoGNsqdzcXAQGBsLe3h7GxsYYOnQoli1bxvxc/+39+/cICAjA0KFDYWZmBh8fH64Ygcaqojlz5sDExASmpqZwc3NrU5yEEEIIkRxUaUMIIYR0cNnZ2QCALl26MMfq6urg6uoKc3Nz+Pr6QkFBAQAQEBCAEydOYOrUqXByckJOTg4OHTqER48e4ciRI8w2px07dmD37t2wtbWFra0tHj58iG+//Ra1tbWfjOfatWtYtGgRtLS0MG/ePGhoaOD58+e4fPkynJ2dMXPmTBQWFuLatWvYunUr1/e3R4y8PHjwAPfu3YODgwO0tbWRm5uLI0eOYN68eUhOTubaehYUFAQVFRUsWbIEWVlZOHLkCPLy8nDw4EGwWCwAQGJiIlatWoURI0bA29sbVVVVOHLkCObMmYMTJ05AR0eHr1gJIYQQIhkoaUMIIYR0MBUVFSguLkZNTQ3u3r2LXbt2QUFBAWPGjGEeU1NTg4kTJ2LlypXMsdu3b+Pnn39GaGgoHB0dmeNDhw7FggULkJKSAkdHRxQXF+Onn37C6NGjERUVxSQgtm/fjqioqI/GVl9fj4CAAGhpaSExMREqKirMOTabDQAwNTWFnp4erl27hq+//prj+9sjxuaMHj0aEydO5Dg2ZswYzJw5E+fOncPkyZM5zsnKymL//v1MEqlHjx4ICQnBxYsXMW7cOFRWVmLjxo2YPn06goODme+bMmUKJk6ciD179nAcJ4QQQsjnh7ZHEUIIIR2Mi4sLrK2tYWtrCy8vL3Tu3BkRERHo1q0bx+Nmz57N8XVKSgqUlZUxfPhwFBcXM/8ZGRmhU6dOzBan69evo7a2FnPnzmWSIQDg7Oz8ydgePXqEnJwczJs3jyNhA4Bjrea0R4zNaapGAoDa2lqUlJSgd+/eUFFRwaNHj7geP3PmTI4GzLNnz4aMjAyuXLnCxFhWVgYHBweO1yIlJYUhQ4aI1Zh0QgghhAgHVdoQQgghHUxAQAD69OkDaWlpaGhooE+fPpCS4ryPIyMjA21tbY5jr169Qnl5OaytrXmu+/btWwBAXl4eAEBPT4/jvJqaGlRVVT8a2+vXrwEA/fv3b/Hrae8Ym/P+/Xvs2bMHv/76K/7++2+mMggAysvLuR6vq6vL8XXnzp2hqamJ3NxcAMDLly8BNJ9IUlJS4itOQgghhEgOStoQQgghHYyxsTEzPao5cnJyXImchoYGqKurIzQ0lOf3qKmpCSxGfokyxuDgYPz6669wdnaGiYkJlJWVwWKx4OXlxZHAaamm79m6dSs0NTW5zktLS7c5ZkIIIYSIN0raEEIIIaRFevfujRs3bsDMzIxjK9C/9ejRA0BjpUivXr2Y48XFxTynI32o6fF//fUXbGxsmn1cc1ul2iPG5jT1rVm1ahVzrLq6mmeVDdBYFdQ0uQsAKisrUVRUhFGjRgH4389CXV39oz8LQgghhHy+qKcNIYQQQlrkP//5D+rr6xEZGcl1rq6uDmVlZQAAGxsbyMrKIj4+nqPCpGlk98cYGRlBR0cHBw4cYNZr8uFaTZOY/v2Y9oixObwqXw4ePIj6+nqejz927BjHpKojR46grq6OSdqMHDkSSkpK2LNnD8+JVsXFxXzHSgghhBDJQJU2hBBCCGkRKysrzJw5E3v27MHjx48xfPhwyMrK4uXLl0hJScGaNWswceJEqKmp4dtvv8WePXuwaNEi2Nra4tGjR/j999/RtWvXjz6HlJQUAgMD4eHhgcmTJ2Pq1KnQ1NTEixcv8OzZM8TExABoTO4AwIYNGzBixAhIS0vDwcGhXWJszujRo3Hy5EkoKSlBX18fGRkZuH79Osco9Q/V1tbCxcUF//nPf5CVlYXDhw/D3Nwc48aNA9DYsyYwMBA+Pj6YOnUqJk2aBDU1NeTl5eHKlSswMzNDQEAAX7ESQgghRDJQ0oYQQgghLRYUFIRBgwbh6NGj2L59O6SlpdGzZ0989dVXMDMzYx63YsUKyMnJ4ejRo7h16xaMjY2xb98+LFq06JPPMXLkSMTFxWHXrl3Yt28f2Gw2evXqhRkzZjCPmTBhApycnJCcnIykpCSw2Ww4ODi0W4y8rFmzBlJSUjh16hSqq6thZmaG2NhYLFiwgOfjAwICcOrUKfz444+ora2Fg4MD/P39ObZ+OTo6QktLC9HR0YiJiUFNTQ26desGCwsLTJ06la84CSGEECI5WGx+OuMRQgghhBBCCCGEEKGinjaEEEIIIYQQQgghYoiSNoQQQgghhBBCCCFiiJI2hBBCCCGEEEIIIWKIkjaEEEIIIYQQQgghYoiSNoQQQgghhBBCCCFiiJI2hBBCCCGEEEIIIWKIkjaEEEIIIYQQQgghYoiSNoQQQgghhBBCCCFiiJI2hBBCCCGEEEIIIWKIkjaEEEIIIYQQQgghYoiSNoQQQgghhBBCCCFiiJI2hBBCCCGEEEIIIWKIkjaEEEIIIYQQQgghYuj/AWKCrCPYlwYwAAAAAElFTkSuQmCC\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# ============================================================\n",
        "# Hyperparameter Grids for Both Models\n",
        "# ============================================================\n",
        "\n",
        "# Parameter grid for Random Forest:\n",
        "# - n_estimators: number of trees in the forest\n",
        "# - max_depth: maximum depth of each tree\n",
        "# - min_samples_split: minimum samples needed to split a node\n",
        "rf_param_grid = {\n",
        "    \"clf__n_estimators\": [50, 100],\n",
        "    \"clf__max_depth\": [10, 20],\n",
        "    \"clf__min_samples_split\": [2, 5],\n",
        "}\n",
        "\n",
        "# Parameter grid for XGBoost:\n",
        "# - n_estimators: number of boosting rounds\n",
        "# - max_depth: depth of each tree\n",
        "# - learning_rate: step size for updating weights\n",
        "xgb_param_grid = {\n",
        "    \"clf__n_estimators\": [50, 100],\n",
        "    \"clf__max_depth\": [3, 5],\n",
        "    \"clf__learning_rate\": [0.05, 0.1],\n",
        "}\n",
        "\n",
        "\n",
        "# ============================================================\n",
        "# Function to Tune Both Models Using GridSearchCV\n",
        "# ============================================================\n",
        "def tune_models(rf_pipeline, gb_pipeline, X_train, y_train_xgb,\n",
        "                rf_param_grid, xgb_param_grid):\n",
        "    \"\"\"\n",
        "    Tune Random Forest and XGBoost models using GridSearchCV.\n",
        "\n",
        "    The function performs a full grid search over the provided\n",
        "    hyperparameter ranges for both models. It evaluates each combination\n",
        "    using 3-fold cross-validation and selects the best-performing model\n",
        "    according to the macro F1-score (better for imbalanced datasets).\n",
        "\n",
        "    Parameters:\n",
        "        rf_pipeline : Preprocessing + Random Forest pipeline.\n",
        "        gb_pipeline :  Preprocessing + XGBoost pipeline.\n",
        "        X_train : Training features.\n",
        "        y_train_xgb : Dense labels\n",
        "        rf_param_grid : Hyperparameters to search for Random Forest.\n",
        "        xgb_param_grid : Hyperparameters to search for XGBoost.\n",
        "\n",
        "    Returns:\n",
        "        best_rf : Tuned Random Forest pipeline with the best parameters.\n",
        "        best_xgb :Tuned XGBoost pipeline with the best parameters.\n",
        "        rf_grid : Full Random Forest grid-search object (for inspection).\n",
        "        xgb_grid : Full XGBoost grid-search object.\n",
        "    \"\"\"\n",
        "\n",
        "    # Grid search for Random Forest\n",
        "    rf_grid = GridSearchCV(\n",
        "        estimator=rf_pipeline,\n",
        "        param_grid=rf_param_grid,\n",
        "        cv=3,                 # 3-fold cross validation\n",
        "        scoring=\"f1_macro\",   # macro F1 works better for imbalance\n",
        "        n_jobs=-1,            # use all CPU cores\n",
        "        verbose=2             # show progress\n",
        "    )\n",
        "\n",
        "    # Grid search for XGBoost\n",
        "    xgb_grid = GridSearchCV(\n",
        "        estimator=gb_pipeline,\n",
        "        param_grid=xgb_param_grid,\n",
        "        cv=3,\n",
        "        scoring=\"f1_macro\",\n",
        "        n_jobs=-1,\n",
        "        verbose=2\n",
        "    )\n",
        "\n",
        "    # Fit both models using the dense training labels\n",
        "    rf_grid.fit(X_train, y_train_xgb)\n",
        "    xgb_grid.fit(X_train, y_train_xgb)\n",
        "\n",
        "    # Extract the best models\n",
        "    best_rf = rf_grid.best_estimator_\n",
        "    best_xgb = xgb_grid.best_estimator_\n",
        "\n",
        "    print(\"Best RF params:\", rf_grid.best_params_)\n",
        "    print(\"Best XGB params:\", xgb_grid.best_params_)\n",
        "\n",
        "    return best_rf, best_xgb, rf_grid, xgb_grid\n",
        "\n",
        "\n",
        "# ============================================================\n",
        "# Run Hyperparameter Tuning for Both Models\n",
        "# ============================================================\n",
        "best_rf, best_xgb, rf_grid, xgb_grid = tune_models(\n",
        "    rf_pipeline, gb_pipeline,\n",
        "    X_train, y_train_xgb,\n",
        "    rf_param_grid, xgb_param_grid\n",
        ")\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "a6lrlOEe73HM",
        "outputId": "2467f2fc-581a-4a4f-98bf-4bf1663d1220"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Fitting 3 folds for each of 8 candidates, totalling 24 fits\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.12/dist-packages/sklearn/model_selection/_split.py:805: UserWarning: The least populated class in y has only 2 members, which is less than n_splits=3.\n",
            "  warnings.warn(\n",
            "[Parallel(n_jobs=-1)]: Using backend ThreadingBackend with 2 concurrent workers.\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "building tree 1 of 50building tree 2 of 50\n",
            "\n",
            "building tree 3 of 50\n",
            "building tree 4 of 50\n",
            "building tree 5 of 50\n",
            "building tree 6 of 50\n",
            "building tree 7 of 50\n",
            "building tree 8 of 50\n",
            "building tree 9 of 50\n",
            "building tree 10 of 50\n",
            "building tree 11 of 50\n",
            "building tree 12 of 50\n",
            "building tree 13 of 50\n",
            "building tree 14 of 50\n",
            "building tree 15 of 50\n",
            "building tree 16 of 50\n",
            "building tree 17 of 50\n",
            "building tree 18 of 50\n",
            "building tree 19 of 50\n",
            "building tree 20 of 50\n",
            "building tree 21 of 50\n",
            "building tree 22 of 50\n",
            "building tree 23 of 50\n",
            "building tree 24 of 50\n",
            "building tree 25 of 50\n",
            "building tree 26 of 50\n",
            "building tree 27 of 50\n",
            "building tree 28 of 50\n",
            "building tree 29 of 50\n",
            "building tree 30 of 50\n",
            "building tree 31 of 50\n",
            "building tree 32 of 50\n",
            "building tree 33 of 50\n",
            "building tree 34 of 50\n",
            "building tree 35 of 50\n",
            "building tree 36 of 50\n",
            "building tree 37 of 50\n",
            "building tree 38 of 50\n",
            "building tree 39 of 50\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "[Parallel(n_jobs=-1)]: Done  37 tasks      | elapsed:    4.0s\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "building tree 40 of 50\n",
            "building tree 41 of 50\n",
            "building tree 42 of 50\n",
            "building tree 43 of 50\n",
            "building tree 44 of 50\n",
            "building tree 45 of 50\n",
            "building tree 46 of 50\n",
            "building tree 47 of 50\n",
            "building tree 48 of 50\n",
            "building tree 49 of 50\n",
            "building tree 50 of 50\n",
            "Fitting 3 folds for each of 8 candidates, totalling 24 fits\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "[Parallel(n_jobs=-1)]: Done  50 out of  50 | elapsed:    5.4s finished\n",
            "/usr/local/lib/python3.12/dist-packages/sklearn/model_selection/_split.py:805: UserWarning: The least populated class in y has only 2 members, which is less than n_splits=3.\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.12/dist-packages/joblib/externals/loky/process_executor.py:782: UserWarning: A worker stopped while some jobs were given to the executor. This can be caused by a too short worker timeout or by a memory leak.\n",
            "  warnings.warn(\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[07:13:17] INFO: /workspace/src/data/iterative_dmatrix.cc:56: Finished constructing the `IterativeDMatrix`: (125973, 122, 15368706).\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.12/dist-packages/xgboost/training.py:199: UserWarning: [07:13:17] WARNING: /workspace/src/learner.cc:790: \n",
            "Parameters: { \"predictor\" } are not used.\n",
            "\n",
            "  bst.update(dtrain, iteration=i, fobj=obj)\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Best RF params: {'clf__max_depth': 20, 'clf__min_samples_split': 2, 'clf__n_estimators': 50}\n",
            "Best XGB params: {'clf__learning_rate': 0.1, 'clf__max_depth': 5, 'clf__n_estimators': 100}\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def show_grid_search_results(grid, model_name=\"Model\"):\n",
        "    \"\"\"\n",
        "    Display all GridSearchCV hyperparameter combinations and their\n",
        "    cross-validation scores in a clear, readable table.\n",
        "\n",
        "    This function extracts the full cv_results_ dictionary from a\n",
        "    GridSearchCV object, converts it into a DataFrame, and displays\n",
        "    only the most useful columns:\n",
        "      - Hyperparameter values\n",
        "      - Mean and standard deviation of test scores\n",
        "      - Rank of each hyperparameter combination\n",
        "      - Scores for each CV fold\n",
        "\n",
        "    Parameters:\n",
        "        grid : The fitted GridSearchCV object containing the results.\n",
        "        model_name : Used to label the output for easier identification.\n",
        "\n",
        "    Returns:\n",
        "        clean_results : A filtered and sorted table of the GridSearchCV results.\n",
        "    \"\"\"\n",
        "\n",
        "    print(f\"\\n================= All Grid Search Results for {model_name} =================\\n\")\n",
        "\n",
        "    # Convert GridSearchCV results to a DataFrame\n",
        "    results = pd.DataFrame(grid.cv_results_)\n",
        "\n",
        "    # Ensure full column visibility when printing the table\n",
        "    pd.set_option(\"display.max_columns\", None)\n",
        "    pd.set_option(\"display.width\", 200)\n",
        "\n",
        "    # Select only the hyperparameter columns (param_*)\n",
        "    # and the most informative score columns\n",
        "    param_cols = [col for col in results.columns if col.startswith(\"param_\")]\n",
        "    score_cols = [\n",
        "        \"mean_test_score\",\n",
        "        \"std_test_score\",\n",
        "        \"rank_test_score\",\n",
        "        \"split0_test_score\",\n",
        "        \"split1_test_score\",\n",
        "        \"split2_test_score\",\n",
        "    ]\n",
        "\n",
        "    # Combine selected columns into a clean table and sort by rank\n",
        "    clean_results = results[param_cols + score_cols].sort_values(\"rank_test_score\")\n",
        "\n",
        "    # Display the organised table for inspection\n",
        "    display(clean_results)\n",
        "\n",
        "    return clean_results\n",
        "\n",
        "\n",
        "# Show the Random Forest and xgb  fores tuning results in a cleaner format\n",
        "rf_results = show_grid_search_results(rf_grid, model_name=\"Random Forest\")\n",
        "\n",
        "xgb_results = show_grid_search_results(xgb_grid, model_name=\"XGBoost\")"
      ],
      "metadata": {
        "id": "ApofNMuUK2Be",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 687
        },
        "outputId": "f85be09d-0b82-454c-e0f0-05c64acf252d"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "================= All Grid Search Results for Random Forest =================\n",
            "\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "   param_clf__max_depth  param_clf__min_samples_split  param_clf__n_estimators  mean_test_score  std_test_score  rank_test_score  split0_test_score  split1_test_score  split2_test_score\n",
              "4                    20                             2                       50         0.760948        0.015812                1           0.776156           0.767541           0.739147\n",
              "5                    20                             2                      100         0.731704        0.034586                2           0.778242           0.721471           0.695399\n",
              "6                    20                             5                       50         0.717750        0.014848                3           0.727450           0.729029           0.696771\n",
              "7                    20                             5                      100         0.703434        0.011215                4           0.697629           0.719118           0.693555\n",
              "2                    10                             5                       50         0.567640        0.015610                5           0.586480           0.568186           0.548255\n",
              "0                    10                             2                       50         0.567410        0.005123                6           0.561096           0.567489           0.573644\n",
              "3                    10                             5                      100         0.554365        0.010162                7           0.568522           0.549428           0.545144\n",
              "1                    10                             2                      100         0.549675        0.017034                8           0.564788           0.525873           0.558366"
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              "      <th></th>\n",
              "      <th>param_clf__max_depth</th>\n",
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              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
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              "  @keyframes spin {\n",
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              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
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              "    20% {\n",
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              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
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              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "      <script>\n",
              "        async function quickchart(key) {\n",
              "          const quickchartButtonEl =\n",
              "            document.querySelector('#' + key + ' button');\n",
              "          quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "          quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "          try {\n",
              "            const charts = await google.colab.kernel.invokeFunction(\n",
              "                'suggestCharts', [key], {});\n",
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              "            console.error('Error during call to suggestCharts:', error);\n",
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              "          quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "          quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
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              "\n",
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              "type": "dataframe",
              "summary": "{\n  \"name\": \"xgb_results = show_grid_search_results(xgb_grid, model_name=\\\"XGBoost\\\")\",\n  \"rows\": 8,\n  \"fields\": [\n    {\n      \"column\": \"param_clf__max_depth\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 5,\n        \"min\": 10,\n        \"max\": 20,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          10,\n          20\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"param_clf__min_samples_split\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1,\n        \"min\": 2,\n        \"max\": 5,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          5,\n          2\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"param_clf__n_estimators\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 26,\n        \"min\": 50,\n        \"max\": 100,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          100,\n          50\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"mean_test_score\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.09178288033523442,\n        \"min\": 0.5496754515167311,\n        \"max\": 0.7609481749497258,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          0.7317039077748685,\n          0.5674095833535971\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"std_test_score\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.008632768430730698,\n        \"min\": 0.0051228289695938786,\n        \"max\": 0.03458572241591314,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          0.03458572241591314,\n          0.0051228289695938786\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"rank_test_score\",\n      \"properties\": {\n        \"dtype\": \"int32\",\n        \"num_unique_values\": 8,\n        \"samples\": [\n          2,\n          6\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"split0_test_score\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.0971091320856716,\n        \"min\": 0.5610961291722026,\n        \"max\": 0.7782415923152233,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          0.7782415923152233,\n          0.5610961291722026\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"split1_test_score\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.09901988285368174,\n        \"min\": 0.5258727192908536,\n        \"max\": 0.767540963221364,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          0.7214712164229148,\n          0.567488927269885\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"split2_test_score\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.08182279600163095,\n        \"min\": 0.5451438969094963,\n        \"max\": 0.73914714808842,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          0.6953989145864672,\n          0.573643693618704\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "================= All Grid Search Results for XGBoost =================\n",
            "\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "   param_clf__learning_rate  param_clf__max_depth  param_clf__n_estimators  mean_test_score  std_test_score  rank_test_score  split0_test_score  split1_test_score  split2_test_score\n",
              "7                      0.10                     5                      100         0.764638        0.018262                1           0.784251           0.769383           0.740279\n",
              "5                      0.10                     3                      100         0.754356        0.014364                2           0.771459           0.736311           0.755297\n",
              "4                      0.10                     3                       50         0.694921        0.008791                3           0.698578           0.703383           0.682802\n",
              "1                      0.05                     3                      100         0.692963        0.009691                4           0.696055           0.702981           0.679855\n",
              "6                      0.10                     5                       50         0.691025        0.010703                5           0.678015           0.704230           0.690830\n",
              "3                      0.05                     5                      100         0.689617        0.009147                6           0.677820           0.700112           0.690918\n",
              "2                      0.05                     5                       50         0.657790        0.015190                7           0.673327           0.662868           0.637174\n",
              "0                      0.05                     3                       50         0.645434        0.018023                8           0.665196           0.649493           0.621612"
            ],
            "text/html": [
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>param_clf__learning_rate</th>\n",
              "      <th>param_clf__max_depth</th>\n",
              "      <th>param_clf__n_estimators</th>\n",
              "      <th>mean_test_score</th>\n",
              "      <th>std_test_score</th>\n",
              "      <th>rank_test_score</th>\n",
              "      <th>split0_test_score</th>\n",
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              "      <th>split2_test_score</th>\n",
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              "  <tbody>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>0.10</td>\n",
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              "      <th>5</th>\n",
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              "      <td>0.736311</td>\n",
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              "    <tr>\n",
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              "      <td>0.700112</td>\n",
              "      <td>0.690918</td>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
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              "      <td>0.657790</td>\n",
              "      <td>0.015190</td>\n",
              "      <td>7</td>\n",
              "      <td>0.673327</td>\n",
              "      <td>0.662868</td>\n",
              "      <td>0.637174</td>\n",
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              "            title=\"Convert this dataframe to an interactive table.\"\n",
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              "\n",
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              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
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              "        await google.colab.output.renderOutput(dataTable, element);\n",
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              "  @keyframes spin {\n",
              "    0% {\n",
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              "      border-bottom-color: var(--fill-color);\n",
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              "    20% {\n",
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              "      border-left-color: var(--fill-color);\n",
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              "      border-top-color: var(--fill-color);\n",
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              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
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              "      border-bottom-color: var(--fill-color);\n",
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              "\n",
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              "          try {\n",
              "            const charts = await google.colab.kernel.invokeFunction(\n",
              "                'suggestCharts', [key], {});\n",
              "          } catch (error) {\n",
              "            console.error('Error during call to suggestCharts:', error);\n",
              "          }\n",
              "          quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "          quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "        }\n",
              "        (() => {\n",
              "          let quickchartButtonEl =\n",
              "            document.querySelector('#df-c7391594-9352-46de-925d-ffffed880b62 button');\n",
              "          quickchartButtonEl.style.display =\n",
              "            google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "        })();\n",
              "      </script>\n",
              "    </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"xgb_results = show_grid_search_results(xgb_grid, model_name=\\\"XGBoost\\\")\",\n  \"rows\": 8,\n  \"fields\": [\n    {\n      \"column\": \"param_clf__learning_rate\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.02672612419124244,\n        \"min\": 0.05,\n        \"max\": 0.1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          0.05,\n          0.1\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"param_clf__max_depth\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1,\n        \"min\": 3,\n        \"max\": 5,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          3,\n          5\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"param_clf__n_estimators\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 26,\n        \"min\": 50,\n        \"max\": 100,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          50,\n          100\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"mean_test_score\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.04165294182486241,\n        \"min\": 0.645433656001048,\n        \"max\": 0.7646379300785431,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          0.7543556982831099,\n          0.6896168138708897\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"std_test_score\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.003934548649950455,\n        \"min\": 0.008790915711229417,\n        \"max\": 0.018262273861061974,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          0.01436435130711,\n          0.009146936643853142\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"rank_test_score\",\n      \"properties\": {\n        \"dtype\": \"int32\",\n        \"num_unique_values\": 8,\n        \"samples\": [\n          2,\n          6\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"split0_test_score\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.046090698604663,\n        \"min\": 0.6651956229854993,\n        \"max\": 0.7842510603163256,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          0.7714589171600984,\n          0.6778203821781766\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"split1_test_score\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.037791086837408804,\n        \"min\": 0.6494931040197347,\n        \"max\": 0.7693833342961874,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          0.736311364749527,\n          0.7001120749029456\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"split2_test_score\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.04529128023643285,\n        \"min\": 0.62161224099791,\n        \"max\": 0.7552968129397043,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          0.7552968129397043,\n          0.6909179845315466\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# After finding the best hyperparameters from GridSearchCV,\n",
        "# we fit the models on the FULL training set.\n",
        "# This ensures the final model benefits from all available data\n",
        "# and allows us to measure the training time of the tuned versions.\n",
        "\n",
        "print(\"\\nRefitting best Random Forest on full training set (for efficiency)...\")\n",
        "best_rf, tuned_rf_train_time = fit_with_timing(\n",
        "    best_rf,          # The best Random Forest model returned by GridSearchCV\n",
        "    X_train,          # Full training features\n",
        "    y_train_xgb,      # Dense training labels\n",
        "    name=\"Tuned Random Forest\"\n",
        ")\n",
        "\n",
        "print(\"\\nRefitting best XGBoost on full training set (for efficiency)...\")\n",
        "best_xgb, tuned_xgb_train_time = fit_with_timing(\n",
        "    best_xgb,         # The best XGBoost model returned by GridSearchCV\n",
        "    X_train,          # Full training features\n",
        "    y_train_xgb,      # Dense training labels\n",
        "    name=\"Tuned XGBoost\"\n",
        ")\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "e26bqPF_D6xe",
        "outputId": "0a7c14b7-cf46-47c8-ba73-1baf6a8584aa"
      },
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "Refitting best Random Forest on full training set (for efficiency)...\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "[Parallel(n_jobs=-1)]: Using backend ThreadingBackend with 2 concurrent workers.\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "building tree 1 of 50\n",
            "building tree 2 of 50\n",
            "building tree 3 of 50\n",
            "building tree 4 of 50\n",
            "building tree 5 of 50\n",
            "building tree 6 of 50\n",
            "building tree 7 of 50\n",
            "building tree 8 of 50\n",
            "building tree 9 of 50\n",
            "building tree 10 of 50\n",
            "building tree 11 of 50\n",
            "building tree 12 of 50\n",
            "building tree 13 of 50\n",
            "building tree 14 of 50\n",
            "building tree 15 of 50\n",
            "building tree 16 of 50\n",
            "building tree 17 of 50\n",
            "building tree 18 of 50\n",
            "building tree 19 of 50\n",
            "building tree 20 of 50\n",
            "building tree 21 of 50\n",
            "building tree 22 of 50\n",
            "building tree 23 of 50\n",
            "building tree 24 of 50\n",
            "building tree 25 of 50\n",
            "building tree 26 of 50\n",
            "building tree 27 of 50\n",
            "building tree 28 of 50\n",
            "building tree 29 of 50\n",
            "building tree 30 of 50\n",
            "building tree 31 of 50\n",
            "building tree 32 of 50\n",
            "building tree 33 of 50\n",
            "building tree 34 of 50\n",
            "building tree 35 of 50\n",
            "building tree 36 of 50\n",
            "building tree 37 of 50\n",
            "building tree 38 of 50\n",
            "building tree 39 of 50\n",
            "building tree 40 of 50\n",
            "building tree 41 of 50\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "[Parallel(n_jobs=-1)]: Done  37 tasks      | elapsed:    4.6s\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "building tree 42 of 50\n",
            "building tree 43 of 50\n",
            "building tree 44 of 50\n",
            "building tree 45 of 50\n",
            "building tree 46 of 50\n",
            "building tree 47 of 50\n",
            "building tree 48 of 50\n",
            "building tree 49 of 50\n",
            "building tree 50 of 50\n",
            "Tuned Random Forest training time: 6.12 seconds\n",
            "\n",
            "Refitting best XGBoost on full training set (for efficiency)...\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "[Parallel(n_jobs=-1)]: Done  50 out of  50 | elapsed:    5.8s finished\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[07:14:13] INFO: /workspace/src/data/iterative_dmatrix.cc:56: Finished constructing the `IterativeDMatrix`: (125973, 122, 15368706).\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.12/dist-packages/xgboost/training.py:199: UserWarning: [07:14:13] WARNING: /workspace/src/learner.cc:790: \n",
            "Parameters: { \"predictor\" } are not used.\n",
            "\n",
            "  bst.update(dtrain, iteration=i, fobj=obj)\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Tuned XGBoost training time: 50.31 seconds\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# =============================================================\n",
        "# Evaluate the tuned models on the test set\n",
        "# =============================================================\n",
        "\n",
        "# Evaluate the tuned Random Forest model.\n",
        "# This prints accuracy, precision, recall, F1-score and displays the confusion matrix.\n",
        "tuned_rf_metrics = evaluate_model(\n",
        "    best_rf,              # Tuned Random Forest model\n",
        "    X_test,               # Test features\n",
        "    y_test_sparse,        # True labels (global sparse format)\n",
        "    dense_to_sparse,      # Mapping from dense → sparse labels\n",
        "    le,                   # LabelEncoder for decoding labels back to text\n",
        "    name=\"Tuned Random Forest\"\n",
        ")\n",
        "\n",
        "# Evaluate the tuned XGBoost model in the same way.\n",
        "tuned_xgb_metrics = evaluate_model(\n",
        "    best_xgb,             # Tuned XGBoost model\n",
        "    X_test,               # Test features\n",
        "    y_test_sparse,        # True labels (sparse format)\n",
        "    dense_to_sparse,      # Needed to convert XGBoost predictions\n",
        "    le,                   # LabelEncoder to get original class names\n",
        "    name=\"Tuned XGBoost\"\n",
        ")\n"
      ],
      "metadata": {
        "id": "i0mLH7f2F4TS",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "1794040d-526d-4800-a92e-a407d3319ff4"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Tuned Random Forest prediction time on test set: 0.1432 seconds\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "[Parallel(n_jobs=2)]: Using backend ThreadingBackend with 2 concurrent workers.\n",
            "[Parallel(n_jobs=2)]: Done  37 tasks      | elapsed:    0.1s\n",
            "[Parallel(n_jobs=2)]: Done  50 out of  50 | elapsed:    0.1s finished\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "================= Tuned Random Forest – Test Performance =================\n",
            "Accuracy: 0.9133694109297374\n",
            "\n",
            "Classification Report:\n",
            "                 precision    recall  f1-score   support\n",
            "\n",
            "        apache2       0.00      0.00      0.00       228\n",
            "           back       0.70      1.00      0.82       227\n",
            "buffer_overflow       1.00      0.35      0.52        17\n",
            "      ftp_write       1.00      0.50      0.67         2\n",
            "   guess_passwd       1.00      0.02      0.04       411\n",
            "     httptunnel       0.00      0.00      0.00        41\n",
            "           imap       1.00      1.00      1.00         2\n",
            "        ipsweep       0.96      1.00      0.98       479\n",
            "           land       1.00      0.50      0.67         2\n",
            "     loadmodule       1.00      0.75      0.86         4\n",
            "       mailbomb       0.00      0.00      0.00        94\n",
            "          mscan       0.00      0.00      0.00       310\n",
            "       multihop       1.00      0.11      0.20         9\n",
            "          named       0.00      0.00      0.00         2\n",
            "        neptune       0.99      1.00      1.00      6654\n",
            "           nmap       0.95      1.00      0.97       206\n",
            "         normal       0.88      0.99      0.93     11245\n",
            "           perl       0.00      0.00      0.00         1\n",
            "            phf       1.00      1.00      1.00         1\n",
            "            pod       0.89      0.94      0.92        35\n",
            "      portsweep       0.97      1.00      0.98       371\n",
            "   processtable       0.00      0.00      0.00       211\n",
            "             ps       0.00      0.00      0.00         9\n",
            "        rootkit       1.00      0.25      0.40         4\n",
            "          saint       0.00      0.00      0.00        93\n",
            "          satan       0.86      1.00      0.92       698\n",
            "       sendmail       0.00      0.00      0.00         8\n",
            "          smurf       0.99      1.00      1.00       540\n",
            "  snmpgetattack       0.00      0.00      0.00        43\n",
            "      snmpguess       0.00      0.00      0.00        99\n",
            "            spy       0.00      0.00      0.00         0\n",
            "       teardrop       0.89      1.00      0.94       104\n",
            "    warezclient       0.75      0.95      0.84       107\n",
            "    warezmaster       0.75      0.01      0.02       279\n",
            "          xlock       0.00      0.00      0.00         4\n",
            "         xsnoop       0.00      0.00      0.00         1\n",
            "          xterm       0.00      0.00      0.00         3\n",
            "\n",
            "       accuracy                           0.91     22544\n",
            "      macro avg       0.53      0.42      0.42     22544\n",
            "   weighted avg       0.87      0.91      0.88     22544\n",
            "\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x1000 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Tuned XGBoost prediction time on test set: 0.7477 seconds\n",
            "\n",
            "================= Tuned XGBoost – Test Performance =================\n",
            "Accuracy: 0.9138573456352023\n",
            "\n",
            "Classification Report:\n",
            "                 precision    recall  f1-score   support\n",
            "\n",
            "        apache2       0.00      0.00      0.00       228\n",
            "           back       0.70      1.00      0.83       227\n",
            "buffer_overflow       1.00      0.41      0.58        17\n",
            "      ftp_write       0.00      0.00      0.00         2\n",
            "   guess_passwd       1.00      0.02      0.04       411\n",
            "     httptunnel       0.00      0.00      0.00        41\n",
            "           imap       0.50      0.50      0.50         2\n",
            "        ipsweep       0.94      1.00      0.97       479\n",
            "           land       1.00      0.50      0.67         2\n",
            "     loadmodule       1.00      0.75      0.86         4\n",
            "       mailbomb       0.00      0.00      0.00        94\n",
            "          mscan       0.00      0.00      0.00       310\n",
            "       multihop       1.00      0.11      0.20         9\n",
            "          named       0.00      0.00      0.00         2\n",
            "        neptune       0.99      1.00      1.00      6654\n",
            "           nmap       1.00      1.00      1.00       206\n",
            "         normal       0.88      0.99      0.93     11245\n",
            "           perl       1.00      1.00      1.00         1\n",
            "            phf       1.00      1.00      1.00         1\n",
            "            pod       0.87      0.94      0.90        35\n",
            "      portsweep       0.97      0.99      0.98       371\n",
            "   processtable       0.00      0.00      0.00       211\n",
            "             ps       0.00      0.00      0.00         9\n",
            "        rootkit       1.00      0.25      0.40         4\n",
            "          saint       0.00      0.00      0.00        93\n",
            "          satan       0.85      1.00      0.92       698\n",
            "       sendmail       0.00      0.00      0.00         8\n",
            "          smurf       1.00      1.00      1.00       540\n",
            "  snmpgetattack       0.00      0.00      0.00        43\n",
            "      snmpguess       0.00      0.00      0.00        99\n",
            "            spy       0.00      0.00      0.00         0\n",
            "       teardrop       0.89      1.00      0.94       104\n",
            "    warezclient       0.76      1.00      0.86       107\n",
            "    warezmaster       1.00      0.01      0.02       279\n",
            "          xlock       0.00      0.00      0.00         4\n",
            "         xsnoop       0.00      0.00      0.00         1\n",
            "          xterm       0.00      0.00      0.00         3\n",
            "\n",
            "       accuracy                           0.91     22544\n",
            "      macro avg       0.52      0.42      0.42     22544\n",
            "   weighted avg       0.87      0.91      0.88     22544\n",
            "\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x1000 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# ======================================================================\n",
        "# Build a summary table showing efficiency and key hyperparameters\n",
        "# for all models (baseline and tuned versions).\n",
        "# ======================================================================\n",
        "\n",
        "def build_efficiency_row(model_name, model, train_time, metrics):\n",
        "    \"\"\"\n",
        "    1) Creates one row of the efficiency summary table.\n",
        "    2) Each row includes:\n",
        "      - model name\n",
        "      - training time\n",
        "      - prediction time\n",
        "      - important hyperparameters for that model\n",
        "\n",
        "    The function automatically detects whether the classifier is\n",
        "    a Random Forest or an XGBoost model and extracts the relevant\n",
        "    hyperparameters.\n",
        "    \"\"\"\n",
        "\n",
        "    # Extract the classifier object inside the pipeline\n",
        "    clf = model.named_steps[\"clf\"]\n",
        "\n",
        "    # Base information added for all models\n",
        "    row = {\n",
        "        \"Model\": model_name,\n",
        "        \"Train_time_sec\": train_time,                       # Time taken to train the model\n",
        "        \"Test_pred_time_sec\": metrics[\"test_pred_time_sec\"], # Time taken to make predictions\n",
        "    }\n",
        "\n",
        "    # Add hyperparameters depending on the model type\n",
        "    if isinstance(clf, RandomForestClassifier):\n",
        "        row[\"n_estimators\"] = clf.n_estimators\n",
        "        row[\"max_depth\"] = clf.max_depth\n",
        "        row['min_samples_split'] = clf.min_samples_split\n",
        "\n",
        "    elif isinstance(clf, XGBClassifier):\n",
        "        row[\"n_estimators\"] = clf.n_estimators\n",
        "        row[\"max_depth\"] = clf.max_depth\n",
        "        row[\"learning_rate\"] = clf.learning_rate\n",
        "\n",
        "    return row\n",
        "\n",
        "\n",
        "# ======================================================================\n",
        "# Build the full efficiency table for all models\n",
        "# ======================================================================\n",
        "\n",
        "efficiency_summary = pd.DataFrame([\n",
        "    build_efficiency_row(\n",
        "        \"Baseline Random Forest\",\n",
        "        baseline_rf,\n",
        "        baseline_rf_train_time,\n",
        "        baseline_rf_metrics\n",
        "    ),\n",
        "    build_efficiency_row(\n",
        "        \"Baseline XGBoost\",\n",
        "        baseline_xgb,\n",
        "        baseline_xgb_train_time,\n",
        "        baseline_xgb_metrics\n",
        "    ),\n",
        "    build_efficiency_row(\n",
        "        \"Tuned Random Forest\",\n",
        "        best_rf,\n",
        "        tuned_rf_train_time,\n",
        "        tuned_rf_metrics\n",
        "    ),\n",
        "    build_efficiency_row(\n",
        "        \"Tuned XGBoost\",\n",
        "        best_xgb,\n",
        "        tuned_xgb_train_time,\n",
        "        tuned_xgb_metrics\n",
        "    ),\n",
        "])\n",
        "\n",
        "# Set model names as the table index for easier reading\n",
        "efficiency_summary.set_index(\"Model\", inplace=True)\n",
        "\n",
        "# Print the final summary table\n",
        "print(efficiency_summary)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "EyuBwwdMIFcf",
        "outputId": "56bf7a30-a761-426e-ab31-edc5066373c5"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "                        Train_time_sec  Test_pred_time_sec  n_estimators  max_depth  min_samples_split  learning_rate\n",
            "Model                                                                                                                \n",
            "Baseline Random Forest       15.168768            0.226234         100.0        NaN                2.0            NaN\n",
            "Baseline XGBoost             55.354499            0.897974           NaN        NaN                NaN            NaN\n",
            "Tuned Random Forest           6.118925            0.143187          50.0       20.0                2.0            NaN\n",
            "Tuned XGBoost                50.311098            0.747739         100.0        5.0                NaN            0.1\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def plot_feature_importance(model, top_n=20, title=\"Feature Importance\"):\n",
        "    \"\"\"\n",
        "    Plots the top-N most important features from a trained model that is built\n",
        "    inside a preprocessing pipeline.\n",
        "\n",
        "    This function:\n",
        "      1) extracts the feature names created by the ColumnTransformer\n",
        "        (including one-hot encoded categorical features),\n",
        "      2) retrieves the feature-importance values from the classifier,\n",
        "      3) sorts the features in descending order of importance,\n",
        "        and displays the top-N features as a horizontal bar chart.\n",
        "\n",
        "    Parameters:\n",
        "      model : Pipeline\n",
        "          A fitted pipeline containing both the preprocessor and classifier.\n",
        "      top_n : int, optional (default=20)\n",
        "          The number of top features to show in the plot.\n",
        "      title : str, optional\n",
        "          The title displayed above the chart.\n",
        "\n",
        "    The output is a clean and readable plot that helps interpret which features\n",
        "    the model relies on most when making predictions.\n",
        "    \"\"\"\n",
        "\n",
        "    pre = model.named_steps[\"preprocessor\"]\n",
        "    clf = model.named_steps[\"clf\"]\n",
        "\n",
        "    feature_names = pre.get_feature_names_out()\n",
        "    importances = clf.feature_importances_\n",
        "\n",
        "    idx = np.argsort(importances)[::-1][:top_n]\n",
        "\n",
        "    plt.figure(figsize=(10, 6))\n",
        "    plt.barh(range(len(idx)), importances[idx])\n",
        "    plt.yticks(range(len(idx)), [feature_names[i] for i in idx])\n",
        "    plt.gca().invert_yaxis()\n",
        "    plt.title(title)\n",
        "    plt.xlabel(\"Importance\")\n",
        "    plt.tight_layout()\n",
        "    plt.show()\n",
        "\n",
        "plot_feature_importance(best_rf,  title=\"Random Forest Feature Importance\")\n",
        "plot_feature_importance(best_xgb, title=\"XGBoost Feature Importance\")"
      ],
      "metadata": {
        "id": "muEg_xXnQFgj",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "a0f54356-1623-4f0c-f7df-58277d22b9ea"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x600 with 1 Axes>"
            ],
            "image/png": 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9738xY8aMqh1EOVq2bAkA0NPTK/UOd3Hffvstunbtio8//lhteXZ2tjAoFlD63dIixe+QFvf3338LsWgSr6GhYYXxvm6lXe+3b98WrmFtXEtA2ef322+/Rb169bB582a1Xir79+/XKP6XmZqawtDQEDdv3iy3XatWrZCXl1fj8kFUG3GaLiIiolqmaPqe7du34/nz5wD+705W8TtXly5dwsWLF6u0DwsLC7Rv3x4HDhwQppcCgNOnT+PWrVtqbT09PVFQUCBMPVRk27Zt0NHRgaenZ5Vi0JaiYzl48KBaYfjHH3/g9OnT6NGjR4Xb6Nu3L3R1dRETE1Pi7qBKpRKeJc7NzcWLFy/U1tva2kIikah1923QoIHGXd8rYmZmhnfeeQd79uzBgwcPSqwv3r1XV1e3RPzHjh1DRkaG2rKiZ8dLi7Fly5a4dOmS2vGcOHGixHRlZbG3t0erVq2wZcsWPH36tNx4X7fvv/9e7VxcvnwZly5dEq5hbVxLQNnnV1dXFzo6Ompd99PS0kpMt6YpiUSC3r1748SJE0hOTi6xvuhaeO+99/Dbb7/hf//7X4k22dnZJa5pIiob72ATERHVQuPHj0doaCji4+Px/vvvo2fPnvjuu+8wbdo09OzZE2lpadi9ezfatm2LvLy8Ku0jLCwMkyZNQkBAAP71r3/hyZMniIuLg42Njdo2vb290bVrV6xatQrp6emQyWQ4ffo0EhMTMWbMGI2moKpuc+bMwQcffIDhw4djyJAhwtRKRkZGCA4OrvD9rVq1wocffoioqCikp6ejd+/eaNiwIdLS0vD9999j2LBhGD9+PM6ePYslS5bg3XffRevWrVFQUICvv/4aurq68PHxEbbXoUMH/PTTT9i6dSssLCxgZWUlDPZWFR999BECAgLQv39/DBs2DC1btsQ///yDixcv4v79+zh06BAAoGfPnli7di3mz5+PTp064Y8//sDhw4dL3Hlu1aoVjI2NsXv3bjRs2BANGjRAx44d0bJlSwwdOhTffvstJkyYgPfeew93797F4cOHNc6zRCJBREQEPvjgA/Tr1w/+/v6wtLRERkYGzp07B0NDQ2zYsKHK5+JVtGrVCu+//z7ef/99KBQK7NixA40aNVLrOv2q1xJQmH+gcFoxd3d36Orqws/PDz169MDWrVsxYcIE9OvXD5mZmfjyyy/RqlUrYa74ygoLC8Pp06cRGBiIYcOGoU2bNnj48CESEhLw5ZdfwtjYGOPHj0dSUhImT56MwYMHo0OHDpDL5fjjjz/w7bffIjExUZjyjojKxwKbiIioFurbt69wF3DYsGHw9/cX5jT+8ccf0bZtW3z66adISEjA+fPnq7QPT09PrF69Gp9//jmioqLQqlUrREZGIjExUW2bEokE69evx5o1a/DNN98gPj4eLVq0wJw5cxAUFKStQ34lrq6u+OKLL7BmzRqsWbMGb731FlxcXDB79myNujUDwMSJE9G6dWts27YNa9euBVA4MJubmxu8vb0BFHYNd3d3x4kTJ5CRkQEDAwPIZDJs2rQJTk5OwrbmzZuHhQsX4vPPP8ezZ88wePDgVyqw27Zti/379yMmJgYHDhzAkydPYGpqCjs7O0ybNk1oN3nyZMjlchw+fBjffPMN7OzsEBsbi6ioKLXt6enpYfny5fjss8+waNEivHjxApGRkWjZsiU8PDwwb948bN26FR9//DHs7e2xYcMGrFixQuN4u3btij179mDdunWIi4tDXl4ezM3N0bFjRwwfPrzK5+FVDRo0CBKJBNu3b0dmZiY6duyI8PBwWFhYCG20cS317dsXgYGBOHr0KA4dOgSVSgU/Pz90794dy5Ytw6ZNm/Dxxx/DysoKs2bNQnp6epULbEtLS3z11VdYvXo1Dh8+jNzcXFhaWsLT01N4Pt7AwAA7d+5EbGwsEhIScPDgQRgaGqJ169YICQl55QH6iOoSHZUYI4cQEREREdUQaWlp6NWrF+bMmYPx48eLHQ4R1WJ8BpuIiIiIiIhIC1hgExEREREREWkBC2wiIiIiIiIiLeAz2ERERERERERawDvYRERERERERFrAApuIiIiIiIhICzgPNhHVKL/99htUKhX09PTEDoWIiIiICPn5+dDR0UGnTp0qbMs72ERUo6hUKuGHxKNSqaBQKJgHETEH4mMOxMcciI85EB9zIL7KfDblHWwiqlH09PSgUCjQtm1bNGjQQOxw6qy8vDxcu3aNeRARcyA+5kB8zIH4mAPxMQfiS05O1rgt72ATERERERERaQELbCIiIiIiIiItYIFNREREREREpAUssImIiIiIiIi0gAU2ERERERERkRawwCYiIiIiIiLSAhbYRERERERERFrAApuIiIiIiIhIC1hgExEREREREWkBC2wiIiIiIiIiLWCBTURERERERKQFLLCJiIiIiIiItIAFNhEREREREZEWsMAmIiIiIiIi0gIW2ERERERERERawAKbiIiIiIiISAtYYBMRERERERFpAQtsIiIiIiIiIi1ggU1ERERERESkBSywiYiIiIiIiLSABTYR1Ug6Ojpih1Cn6ejowMDAgHkQEXMgPuZAfMyB+JgD8TEHtYuOSqVSiR0EEVGR5ORkAICDg4PIkRARERFRTaFUqiCRiPMlQ2U+n75V3cEQEVXFyl0XkJaRI3YYRERERCQyK0sjzBrpLHYYGmGBTUQ1UlpGDlLSs8QOg4iIiIhIY3wGm6iWSktLg0wmQ0JCwitv69q1a4iOjoZcLtdCZEREREREdRMLbCLCtWvXEBMTwwKbiIiIiOgVsMAmEsGzZ8/EDoGIiIiIiLSMBTaJbt68eejXrx/OnTuHQYMGwcnJCUOGDMGVK1cAlN0VetmyZfD29hZex8fHQyaTITk5GUFBQXB0dISPjw/OnDkDpVKJVatWwdXVFa6uroiKioJSqdRK/Pn5+VixYgV69uwJe3t7uLu7Y/LkycjJKRyg69y5c5DJZPjhhx8wffp0dO7cGaGhoQCA7OxsLF26FJ6enrC3t4e3tzeioqIqtX+5XI5///vfcHZ2xjvvvIPIyEi8ePECAPDo0SPY29vjq6++KvG+oUOHIjQ0FPHx8Zg/fz4AoHv37pDJZGrn9f79+5g1axa6du2Kjh07YuTIkUJuiiQmJsLf3x+dOnVCly5d4O/vj5MnT1bqOIiIiIiIajsOckY1wsOHDxEREYGJEyfCyMgIUVFRCA4OxvHjxyu9rblz52LEiBEYN24cNm7ciODgYAwePBi5ublYsWIFLl26hOjoaNja2qJ///6vHHtsbCx2796NWbNmwcbGBo8fP8bp06ehUCjU2oWHh2PAgAFYu3YtJBIJFAoFxowZg/T0dEybNg22tra4f/8+Lly4UKn9f/bZZ3B3d8fnn3+Oq1evYs2aNdDT08OsWbNgamqKPn36YP/+/Rg2bJjwnps3b+Ly5cuYPn06OnTogClTpmD9+vX44osvYGRkBH19fQBAVlYWAgIC0KBBA4SHh8PIyAg7d+7EmDFj8N1338HMzAx3795FaGgo/Pz8MHPmTCiVSly/fh1ZWRygjIiIiIjqFhbYVCNkZWUhLi4ONjY2AAADAwOMHj0aly5dQtOmTSu1rVGjRiEgIAAAYGlpif79++PKlSvYs2cPAMDDwwNJSUlISEjQSoGdnJwMd3d3jBw5Uljm4+NTop23tzdmz54tvP7qq69w9epV7N69G506dRKWDx48uFL7b9WqFSIjIwEUHtuzZ8+wdetWfPDBBzAxMcGwYcMwduxYpKSkoE2bNgCA/fv3o1mzZnBzc4NEIkGrVq0AAB06dICpqamw7e3btyM7Oxt79+6FmZkZgMK73D4+Pti8eTPmzJmDq1evIj8/H+Hh4TA0NBTiICIiIiLSJrlcDpVK9dr3q1KpoKOj2RzcLLCpRrCwsBCKawBo27YtACAjI6PSBbabm5vwe+vWrQEA3bp1U2sjlUqRmppaxWjV2dnZYfPmzYiOjkaPHj1gb28PiaTk0xc9e/ZUe/3TTz+hTZs2asV1VfTp00fttY+PD9atW4c//vgDLi4u6NatG1q2bIl9+/Zh7ty5ePHiBQ4dOoThw4eXGmdxp0+fRteuXWFiYiJ0O5dIJHBxcUFycjIAQCaTQVdXF7NmzcKwYcPg4uICIyOjVzomIiIiIqKXpaamijYob1EPz4qwwKYawdjYWO21np4eAOD58+eV3lbx4q7oD6G07b/chbuqpkyZAolEggMHDiAmJgampqYYOXIkpk2bpvZNV9Ed4CJPnjyBhYXFK++/+B1nAGjSpAmAwm73AKCjo4OhQ4dix44dmDlzJn744Qc8evQI/v7+FW778ePHuHjxIjp06FBiXdFdb6lUig0bNiA2NhbBwcGQSCRwd3fHwoUL0bx581c9PCIiIiIiAIWfO8W4g33r1i2N27LAphqvXr16AAoHEysuOztbjHBK0NfXR0hICEJCQnDnzh3s378f0dHRsLKywqBBg4R2L3cradSoEW7cuPHK+3/06JHa63/++QcAYG5uLizz9/fHmjVr8MMPP2Dfvn3o2rUrWrZsWeG2TUxM4OHhIQzKVlzxb/E8PT3h6emJ3NxcnDp1CpGRkZg/fz62b99e1cMiIiIiIlJjYGAgyn417R4OcBRxqgXMzMygp6eHlJQUYZlCocDPP/8sYlSls7a2RlhYGBo1aoQ///yz3Laurq5ISUnBpUuXXmmfLw8E9+2338LAwAC2trbCMnNzc/Ts2RNffPEF/ve//+Ff//qX2nuKegy8fFe/KMY2bdrAwcFB7Ucmk5WIxdDQEL6+vvDz81PLFxERERFRXcA72FTjSSQS9OnTB7t27YK1tTUaN26MuLi4Sg02UJ2mTp2KDh06wM7ODgYGBjhx4gSysrJKPPf9soEDB+LLL7/ExIkTERwcDBsbG2RkZOCXX37B0qVLNd7/3bt3MX/+fPj6+uLq1avYuHEjxowZAxMTE7V2w4YNw8SJE2FsbFxiELaiwc927dqF3r17o379+pDJZBg7diwOHz6MUaNGYfTo0WjevDkePXqES5cuwdLSEmPHjsXu3btx8eJFeHh4wNzcHGlpaTh06JDas/BERERERHUBC2yqFcLDwxEeHo6IiAg0bNgQ48ePh1QqRWJiotihoXPnzjh27Bi2bt2KgoICSKVSrFy5Eq6uruW+T19fH9u2bcOqVasQGxuLJ0+eoGnTpvDz86vU/mfMmIHz588jNDQUurq6CAgIwIwZM0q0c3d3h4GBAfz8/IRu90Xs7OwQEhKCvXv34osvvkCzZs2QlJSExo0bY8+ePfj888+xcuVKPHnyBGZmZnB0dBQGV5PJZDhx4gQiIyPx5MkTmJubw8/Pr9Ru5UREREREbzIdlRhPiRPRa/fTTz9h7Nix2L9/P+zt7cUOp0xFo5NvPp6JlHTOpU1ERERU17VpYYLPw3qKtv+iz6cODg4VtuUdbKI3XEZGBu7evYtPP/0UnTt3rtHFNRERERFRbcYCm+q8ovmdS6Ojo1PuVAASiaTCuaSrQqVSoaCgQCv7/eqrr7Bu3Tq0b98eERER2gqx2llZci5tIiIiIqpdnwvZRZzqvNJGwy7SokULpKenl7k+ODgYISEhWo/p3LlzGD16dJnrBw8ejOXLl2t9vzVBZbrgEBEREVHdoFSqIJGIM8Axu4gTVcK+ffvKXCeXy8udb8/CwqI6QkKHDh3Kjatx48bVst+aQqFQVHjuqXrJ5XKkpqZCKpUyDyJhDsTHHIiPORAfcyA+5qCQWMV1ZbHApjqvJt4pNTQ0rJFxvU7sXCMulUoFuVzOPIiIORAfcyA+5kB8zIH4mIPaRfsPjxIRaUFNmOO8LtPR0YGBgQHzICLmQHzMARERVRbvYBNRjaOvr1+nu0DVBAYGBrCzsxM7jDqNORBfdedAzOcJiYioerDAJqIaaeWuC0jLyBE7DCKiamFlaYRZI53FDoOIiLSMBTYR1UhpGTlISc8SOwwiIiIiIo3xGWwSTJ06FYGBgRq3P3fuHDZs2FDp/Xh7e2PJkiWVfl9VbNu2DSdPnnwt+3qTVTXXRERERER1CQtsqrLz588jNjZW7DDKtWPHDhbYWlAbck1EREREJDYW2ESvSUFBAfLz80ssV6lUUCgUVd7us2fPXuv7iIiIiIiodCywq2DevHno168fzp07h0GDBsHJyQlDhgzBlStXAABpaWmQyWRISEhQe9+yZcvg7e0tvI6Pj4dMJkNycjKCgoLg6OgIHx8fnDlzBkqlEqtWrYKrqytcXV0RFRUFpVKptWNISUnBqFGj4ODggN69e+PAgQMl2ty/fx+hoaFwdXWFg4MDvL298fHHHwMAoqOjERMTg7y8PMhkMshkskp1LweAXbt2wcvLC87Ozpg6dSoePXqktj49PR3Tp0+Hs7MznJycMH78eNy4cUOtTWJiIvz9/dGpUyd06dIF/v7+wh1rb29vpKenY9euXUKM8fHxFcaVn5+PFStWoGfPnrC3t4e7uzsmT56MnJz/G3ArOzsbixYtgru7O+zt7eHv748ff/xRbTuBgYGYNGkSDhw4AB8fHzg4OOD69evC9XPy5EkMGDAADg4OSEpKAgB89913GDhwIBwcHODu7o7IyEg8f/5c2Oa5c+cgk8nwww8/YPr06ejcuTNCQ0MrPKby3nfw4EG8//77eOedd+Di4oLAwEBcvnxZeG9FuU5JScGUKVOEPE2cOBF3796tMCYiIiIiojcNBzmroocPHyIiIgITJ06EkZERoqKiEBwcjOPHj1d6W3PnzsWIESMwbtw4bNy4EcHBwRg8eDByc3OxYsUKXLp0CdHR0bC1tUX//v1fOfbnz58jKCgIBgYG+OSTTwAAa9asQW5uLlq3bi20mzNnDh48eIAFCxbAzMwM9+7dE75EGDp0KO7fv48jR45g+/btAABDQ0ONY0hKSsKdO3ewcOFCPH78GJGRkVi6dClWrVoFAMjNzUVgYCAkEgkWL16MevXqYf369Rg1ahQOHTqEZs2a4e7duwgNDYWfnx9mzpwJpVKJ69evIyurcGCsmJgYTJw4EZ07d0ZQUBAAoFWrVhXGFhsbi927d2PWrFmwsbHB48ePcfr0aeEus0KhwLhx45CZmYkPP/wQlpaWOHToECZNmiR8aVLkypUrSE9PR2hoKIyNjdGsWTMAwIMHDxAREYEpU6agWbNmaN68ORITEzF9+nTheP7880+sWrUK9+7dw5o1a9RiDA8Px4ABA7B27VpIJJp/T1ba+9LS0jBo0CC0atUKCoUCR48exciRI3Ho0CFIpdJyc/3XX39hxIgRsLGxwfLly6Gjo4MNGzZg7NixSEhIgL6+vsaxERERERHVdiywqygrKwtxcXGwsbEBUDhX5ujRo3Hp0iU0bdq0UtsaNWoUAgICAACWlpbo378/rly5gj179gAAPDw8kJSUhISEBK0U2PHx8Xjw4AGOHTsmFNR2dnZ499131Qrs5ORkhIWFwdfXV1g2aNAgAEDTpk3RtGlTSCQSODk5VToGlUqF9evXCwVYeno6YmNjoVQqIZFIEB8fj7///htHjx5FmzZtAAAuLi7w8vLC9u3bMW/ePFy9ehX5+fkIDw8XCj4PDw9hH3Z2dtDX10eTJk0qFWNycjLc3d0xcuRIYZmPj4/w++HDh3H9+nV8/fXXaNu2rbDfO3fuYN26dVi9erXQNisrC/v27RMK6+LLN23aBEdHR2HZhx9+CCcnJ0RFRQEAPD09YWBggIULF+LGjRtqhbu3tzdmz56t8TGV977g4GDhd6VSCTc3N1y+fBkHDhxAWFhYubmOiYmBiYkJtm7dinr16gEAOnfujF69emHv3r1q55CIiEqSy+VQqVRih1FjyeVytf/S68cciI85EJ9KpYKOjo5GbVlgV5GFhYVQXAMQCq2MjIxKF9hubm7C70UFbrdu3dTaSKVSpKamVjFadZcvX4aNjY1aMW1tbY127dqptbOzs8OWLVugq6sLNzc3WFtba2X/QGGxXPzuZps2bZCfn4/MzEyYm5vjl19+gY2NjVBcA0CjRo3g6uqKCxcuAABkMhl0dXUxa9YsDBs2DC4uLjAyMnrl2Ozs7LB582ZER0ejR48esLe3V7tLfPr0adja2qJ169Z48eKFsNzV1RWHDh1S25atrW2J4rroWIoX10+fPsW1a9cwd+5ctXa+vr5YuHAhLly4oFZg9+zZs0rHVtr7UlJS8Nlnn+G3335DZmamsPz27dsVbu/06dPw9fWFrq6ucC6MjY1hZ2cn9HYgIqKypaam8kOzBjT5fxJVL+ZAfMyBuDTtmckCu4qMjY3VXuvp6QGA2vOymipeFBYlrrTtv8pAWMU9ePAAZmZmJZabmZmpxb9q1SqsWrUKn3/+ORYvXgypVIqwsDD07dv3lWN4+fiKjrto/9nZ2WjSpEmpMd68eRNA4ZcOGzZsQGxsLIKDgyGRSODu7o6FCxeiefPmVY5typQpkEgkOHDgAGJiYmBqaoqRI0di2rRp0NHRwePHj3H16lV06NChxHt1dXXVXpd2DKUtz8nJgUqlKpEXIyMj6OvrC93ei5SWP028/L7c3FwEBQXB1NQU8+bNQ/PmzVGvXj0sWLBAo2v58ePH2L59u9B1vLiivwkiIiqbVCrlHexyyOVy3L59G61bt4aBgYHY4dRJzIH4mAPx3bp1S+O2LLCrQVFX2ZdHjM7OzhYjnBIsLCzw+++/l1iemZmp9hy1hYUFIiMjoVQqceXKFaxfvx4zZsxAQkICWrZsWa0xmpiYlHrHPjMzEyYmJsJrT09PeHp6Ijc3F6dOnUJkZCTmz59fasGnKX19fYSEhCAkJAR37tzB/v37ER0dDSsrKwwaNAgmJiaQyWRYtmxZhdsqqyvJy8uNjIygo6NTYqC3nJwcKBQKtWMub7uVjefixYu4f/8+YmNj1Xow5OTkaNQTw8TEBD169BAecSiuYcOGVYqRiKgu4YdlzRgYGKBBgwZih1GnMQfiYw7EU5nP3hxFvBqYmZlBT08PKSkpwjKFQoGff/5ZxKj+j4ODA27evIk7d+4Iy+7cuYPr16+X2l4ikaBjx4748MMP8eLFC+F92ryr/jJnZ2f88ccf+PPPP4VlWVlZOHPmDJydnUu0NzQ0hK+vL/z8/NTOu56eXpV6FRSxtrZGWFgYGjVqJMTi6uqKv/76CxYWFnBwcCjxUxUNGzZE+/btS4w8f+zYMQAo9Zi1oWiqruJ3m3/99Vekp6ertSsr1927d8fNmzdhZ2dX4jy8/fbb1RIzEREREVFNxTvY1UAikaBPnz7YtWsXrK2t0bhxY8TFxVXq4fjq5O/vj/Xr12PSpEnCVE1r1qxR67ack5OD8ePHY+DAgZBKpcjPz8fOnTuF52uBwuemX7x4ge3bt6NTp04wNDTUWlHl7++Pbdu2YdKkSfjwww+FUcTfeustjBkzBgCwe/duXLx4ER4eHjA3N0daWhoOHTqk9kz722+/jbNnz+L06dMwNjaGlZUVGjduXO6+p06dig4dOsDOzg4GBgY4ceIEsrKyhOfiBw0ahN27d2P06NEICgpC69atkZOTIwy6NnPmzCodc3BwMKZNm4ZZs2ZhwIABSE1NxapVq+Dj46P2/LU2OTk5oUGDBli8eDEmTpyIjIwMREdHw9LSUq1dWbmePn06hgwZgvHjx2PYsGFo0qQJ/vnnH5w/fx5dunRBv379qiVuIiIiIqKaiAV2NQkPD0d4eDgiIiLQsGFDjB8/HlKpFImJiWKHhvr162PLli1YtGgRZs+eDUtLS0ydOhWJiYnCXM/16tWDra0tdu7ciXv37qF+/fqwt7fH5s2bYWpqCgDw8vJCQEAANm7ciMzMTLi4uGDnzp1aidHQ0BA7d+7E8uXLER4eDqVSic6dOyMuLk4YNEwmk+HEiROIjIzEkydPYG5uDj8/P7V5ocPCwrBo0SKEhITg6dOniIyMhL+/f7n77ty5M44dO4atW7eioKAAUqkUK1euhKurK4DCLuQ7duxAdHQ0NmzYgIcPH6JRo0aws7Mrtau0pnr16oXVq1dj7dq1mDp1Kho1aoRhw4ZVuWDXRJMmTbB69Wp88sknmDp1Klq3bo3Fixfjiy++UGtXVq6tra2xd+9e4Tn9vLw8mJubw8XFpdq+FCAiIiIiqql0VBxZg4hqkOTkZADA5uOZSEnPqqA1EVHt1KaFCT4P6yl2GDVeXl4erl27hvbt2/PZU5EwB+JjDsRX9PlUk8dB+Qw2ERERERERkRawi3gtVHzu5Zfp6OiUO92HRCJRm9NZ2yqK7eVprF43lUqFgoKCMtdX9/mpDm/iMQGAleWrz2lORFRT8d84IqI3EwvsWqi0+ZeLtGjRosQI0MUFBwcjJCSkOsICUHFsSUlJ1bZvTRw4cADz588vc311n5/q8CYeEwDMGlk9I6cTEdUUSqUKEon4g58SEZH2sMCuhfbt21fmOrlcXu6cmhYWFtURkqC82PT19at135rw8vIqN8bqPj/V4U08JoVCUeG1TNVLLpcjNTUVUqmUeRAJcyC+6s4Bi2siojcPC+xaqKpzLb8ONTk2AGjcuHGF03TVNm/iMQEo91EHqn4qlQpyuZx5EBFzID7mgIiIKqv2PZhJREREREREVAOxwCaiGklHh10nxaSjowMDAwPmQUTMgfiYAyIiqix2ESeiGkdfX5/PnIrMwMAAdnZ2YodRpzEH4nuVHHAAMyKiuokFNhHVSCt3XUBaRo7YYRARVZqVpRFnQiAiqqNYYBNRjZSWkYOU9CyxwyAiIiIi0hifwSYircjOzkZ0dDRu3boldihERERERKJggU1EWpGdnY2YmBgW2ERERERUZ7HAJiIiIiIiItICFthUJ82bNw/9+vXDuXPnMGjQIDg5OWHIkCG4cuUKACAtLQ0ymQwJCQlq71u2bBm8vb2F1/Hx8ZDJZEhOTkZQUBAcHR3h4+ODM2fOQKlUYtWqVXB1dYWrqyuioqKgVCq1dgzZ2dlYunQpPD09YW9vD29vb0RFRam12b17N3x8fIT169atU4shOjoanTp1KrHtLl26IDo6WngdGBiISZMmISEhAT4+PujUqRNGjx6Nu3fvAig8X7169QIAhIaGQiaTQSaTIS0tTWvHS0RERERU03GQM6qzHj58iIiICEycOBFGRkaIiopCcHAwjh8/XultzZ07FyNGjMC4ceOwceNGBAcHY/DgwcjNzcWKFStw6dIlREdHw9bWFv3793/l2BUKBcaMGYP09HRMmzYNtra2uH//Pi5cuCC02blzJyIiIhAYGIiePXvit99+Q0xMDHJycjB37txK7/PatWt49OgRZs2ahYKCAixfvhyzZ8/Gnj17YGFhgZiYGAQHByMsLAxdu3YFAFhYWLzysRIRERER1RYssKnOysrKQlxcHGxsbAAUznc6evRoXLp0CU2bNq3UtkaNGoWAgAAAgKWlJfr3748rV65gz549AAAPDw8kJSUhISFBKwX2wYMHcfXqVezevVvtDvTgwYMBAAUFBVi7di38/PywYMECAIC7uzvy8/OxZcsWTJw4EY0bN67UPnNycnDw4EGYmpoCAPLy8jB//nzcv38fTZs2Rfv27QEA1tbWcHJyeuVjJCKq7eRyOVQqldhh1GpyuVztv/T6MQfiYw7Ep1KpoKOjo1FbFthUZ1lYWAjFNQC0bdsWAJCRkVHpAtvNzU34vXXr1gCAbt26qbWRSqVITU2tYrTqfvrpJ7Rp06bU7t0A8Oeff+Lx48d499131Zb7+voiNjYWly9fRo8ePSq1z3bt2gnFNfB/56uowCYiInWpqan8QKwlt2/fFjuEOo85EB9zIC59fX2N2rHApjrL2NhY7bWenh4A4Pnz55XelpGRkfB70R9fadtXKBSV3nZpnjx5Um7366yswvmjzczM1JYXvS5aXxnaPF9ERHWBVCrlHexXJJfLcfv2bbRu3RoGBgZih1MnMQfiYw7EV5lZclhgE5WiXr16AID8/Hy15dnZ2WKEU0KjRo1w48aNctcDwKNHj9SWZ2ZmAgBMTEwAFB7ny8eYn5+PvLw8LUZLRFQ38YOw9hgYGKBBgwZih1GnMQfiYw7Eo2n3cICjiBOVyszMDHp6ekhJSRGWKRQK/PzzzyJG9X9cXV2RkpKCS5culbpeKpXC1NS0xCjox44dg56eHjp27Aig8Hnx/Px8YTRwADh79iwKCgoqHRPvaBMRERFRXcc72ESlkEgk6NOnD3bt2gVra2s0btwYcXFxlRrgoDoNHDgQX375JSZOnIjg4GDY2NggIyMDv/zyC5YuXQpdXV1MnToVERERMDU1RY8ePXDx4kVs2rQJY8aMEQY48/T0RIMGDbBgwQJ88MEHuH//Pnbs2CHcwa8Mc3NzGBsb4+jRo7CysoK+vj5kMpnGz6sQEREREdV2vINNVIbw8HC88847iIiIwMKFC+Hh4YHevXuLHRaAwue8t23bhvfeew+xsbGYMGECoqOj1QYhCwwMxKJFi3Dq1ClMnjwZ+/fvR3BwMGbPni20ady4MdasWYNHjx5h2rRp2LdvHz755JMqFcUSiQSRkZFIS0vD2LFjMWTIEDx48EArx0tEREREVBvoqDj6BhHVIMnJyQCAzcczkZJe+cHYiIjE1qaFCT4P6yl2GG+EvLw8XLt2De3bt+ezpyJhDsTHHIiv6POpg4NDhW15B5uIiIiIiIhIC/gMNpEIXrx4UeY6HR2dcqd1kUgkkEje/O/GrCyNKm5ERFQD8d8vIqK6iwU2kQg6dOhQ5roWLVogPT29zPXBwcEICQmpjrBqlFkjncUOgYioypRKFSQS8QfFJCKi14sFNpEI9u3bV+Y6uVxe7typFhYW1RFSjaJQKCo8D1S95HI5UlNTIZVKmQeRMAfie5UcsLgmIqqbWGATiUCTARLqOo6/KC6VSgW5XM48iIg5EB9zQERElfXmP8hJRLVSTZhvvC7T0dGBgYEB8yAi5oCIiKj24R1sIqpx9PX12SVWZAYGBrCzsxM7jDqNOdAOPgtNRESvEwtsIqqRVu66gLSMHLHDIKJazMrSiAMmEhHRa8UCm4hqpLSMHKSkZ4kdBhERERGRxvgMNhFVKDs7G9HR0bh165bYoRARERER1VgssImoQtnZ2YiJiWGBTURERERUDhbYRDWYQqGAUqmsddsmIiIiIqqLWGDXEfPmzUO/fv1w7tw5DBo0CE5OThgyZAiuXLkCAEhLS4NMJkNCQoLa+5YtWwZvb2/hdXx8PGQyGZKTkxEUFARHR0f4+PjgzJkzUCqVWLVqFVxdXeHq6oqoqCitFXD5+flYsWIFevbsCXt7e7i7u2Py5MnIySkcBCsvLw9LliyBj48PHB0d4e3tjYULFwrri3h7e2PJkiXYtm0bevTogU6dOmHevHlQKBS4du0aRowYIZybGzduqL1XpVJh8+bN8PHxgb29PXr16oVt27ZV6jgSExPh7++PTp06oUuXLvD398fJkydLxLdp0yZ4eXmhY8eO+O6774RzXlxBQQHc3NwQFRWl0b5L2/aTJ0+QkpKCGTNmoEePHnB0dISvry+2bNki5C4tLQ29evUCAISGhkImk0EmkyEtLQ1AYaH+2WefwcvLC/b29njvvfdw+PDhSp0XIiIiIqI3AQc5q0MePnyIiIgITJw4EUZGRoiKikJwcDCOHz9e6W3NnTsXI0aMwLhx47Bx40YEBwdj8ODByM3NxYoVK3Dp0iVER0fD1tYW/fv3f+XYY2NjsXv3bsyaNQs2NjZ4/PgxTp8+DYVCAQB49uwZCgoKMGPGDJiamuLevXvYsGEDpk6dip07d6ptKzExETY2NliyZAn++usvLF++HHp6erh48SLGjh2LJk2aYOXKlQgNDcU333wDiaTwe6hly5Zh7969mDx5MhwdHfHrr79i5cqVqFevHt5///0Kj+Hu3bsIDQ2Fn58fZs6cCaVSievXryMrS30gr++++w7W1tb4z3/+A4lEgm7dusHCwgLffPMNHBwchHZnz57FP//8g379+ml8Hl/edoMGDXDjxg1IpVL0798fDRs2xLVr1xAdHY28vDwEBwfDwsICMTExCA4ORlhYGLp27QoAsLCwAFBYdP/666+YNm0a2rRpg5MnT2L27NkwNjZGjx49NI6NiIiIiKi2Y4Fdh2RlZSEuLg42NjYACudYHT16NC5duoSmTZtWalujRo1CQEAAAMDS0hL9+/fHlStXsGfPHgCAh4cHkpKSkJCQoJUCOzk5Ge7u7hg5cqSwzMfHR/jd1NQUixcvFl6/ePECVlZWCAgIQGpqKqRSqdr21q1bB319fQDA+fPn8dVXX2HTpk3w9PQEACiVSkyePBl//PEH2rVrh7t37yIuLg6LFy/G8OHDAQCurq549uwZ1q5di+HDhwuFeFmuXr2K/Px8hIeHw9DQEEDheXpZfn4+Nm3ahAYNGgjLfH198c0332DOnDnQ0Smcz/XIkSOwsbGBTCar+ASWs+3u3buje/fuAArv0js7O+PZs2eIi4tDcHAw9PX10b59ewCAtbU1nJychPeePXsWSUlJ2Lx5M9zd3QEAbm5uePjwIaKjo1lgE1GNIJfLoVKpqvS+4v+l1485EB9zID7mQHwqlUr4DF4RFth1iIWFhVBcA0Dbtm0BABkZGZUusN3c3ITfW7duDQDo1q2bWhupVIrU1NQqRqvOzs4OmzdvFoo2e3v7EgXtwYMHsW3bNty5cwd5eXnC8tu3b6sV2C4uLkJxXRR/0Z3il4/p3r17aNeuHc6cOQMA6Nu3L168eCG0c3V1xaZNm3Dv3j20aNGi3GOQyWTQ1dXFrFmzMGzYMLi4uMDIyKhEu65du6oVwADg5+eHbdu24cKFC+jSpQsUCgW+//57BAUFlbtPTbb9/PlzxMbG4vDhw7h37x7y8/OFdU+fPkXDhg3L3N7p06fRqFEjdOvWrcR5WbRoEQoKCqCrq1upGImItC01NfWVPpjevn1be8FQlTAH4mMOxMcciKt4/VAeFth1iLGxsdprPT09AIUFVmUVLwyLLrbStl/UhftVTZkyBRKJBAcOHEBMTAxMTU0xcuRITJs2DTo6Ojh+/Djmzp2L4cOHY8aMGWjUqBEePnyIadOmlTi+0uKsX7++2h/Ny+fm8ePHUKlUJb5EKKJJgS2VSrFhwwbExsYiODgYEokE7u7uWLhwIZo3by60MzMzK/Hejh07olWrVjhy5Ai6dOmCU6dOITs7u1Ldw8va9qeffoq9e/di2rRpsLe3h5GRERITE7F+/Xo8f/683AL78ePHePLkCTp06FDq+ocPH1b6yxsiIm2TSqVVvoN9+/ZttG7dGgYGBtUQGVWEORAfcyA+5kB8lZlJhwU2AQDq1asHAGp3L4HC6ZlqAn19fYSEhCAkJAR37tzB/v37ER0dDSsrKwwaNAgJCQlo3749lixZIrzn/PnzWtu/iYkJdHR08OWXXwrFd3Evd0Evi6enJzw9PZGbm4tTp04hMjIS8+fPx/bt24U2ZXU/8fPzw549e7BgwQJ88803cHR0RMuWLSt1HKVtOyEhAcOHD8fEiROFZcUHXiuPiYkJTE1NsXHjxlLXm5qaVio+IqLq8KofSA0MDEr0/qHXizkQH3MgPuZAPJp2DwdYYNP/Z2ZmBj09PaSkpAjLFAoFfv75ZxGjKp21tTXCwsKwZ88e/PnnnwAKBzl7ufDV5kjWRc8oP3nyRG1U9aoyNDSEr68vLl++jCNHjmj0nn79+mH9+vVISkpCUlISZsyY8cpxAIV36Yufu4KCAhw9elStTVm9HVxdXfHFF19AT08P7dq100o8RERERES1FQtsAgBIJBL06dMHu3btgrW1NRo3boy4uLhKPdBfnaZOnYoOHTrAzs4OBgYGOHHiBLKysoQu266urliyZAnWrl2LTp064eTJk/jpp5+0tn+pVIqRI0dizpw5GD9+PBwdHZGfn4/bt2/j3LlzWLduXYXb2L17Ny5evAgPDw+Ym5sjLS0Nhw4dUnuevTxt27aFTCbD0qVL8fz5c/j6+r7qYQEoPHd79+5F27Zt0bhxY3z55Zcluvabm5vD2NgYR48ehZWVFfT19SGTyeDm5gYvLy9MmDABEyZMgEwmg1wux61bt3Dnzh0sW7ZMKzESEREREdUGLLBJEB4ejvDwcERERKBhw4YYP348pFIpEhMTxQ4NnTt3xrFjx7B161YUFBRAKpVi5cqVcHV1BQCMGDECaWlpiIuLE0a0joqKwrBhw7QWw4IFCyCVSrFnzx6sXbsWDRs2hFQqxbvvvqvR+2UyGU6cOIHIyEg8efIE5ubm8PPzQ2hoqMYx9OvXD1FRUejevTvMzc2reihqwsPD8dFHH2Hp0qUwMDDA4MGD0adPHyxYsEBoI5FIEBkZic8++wxjx46FQqFAYmIirKyssGbNGmzcuBH//e9/kZ6eDiMjI9jY2MDf318r8RERERER1RY6qqqM+kFEVE2Sk5MBAJuPZyIlPauC1kREZWvTwgSfh/Ws8vvz8vJw7do1tG/fns89ioQ5EB9zID7mQHxFn08dHBwqbFv+xL1EREREREREpBF2EafXovgcyS/T0dEpd/oUiURSYs7rmqiiY6zO+aDF3Hd1sbIsOUc4EVFl8N8RIiJ63Vhg02tR1jzJANCiRQukp6eXuT44OBghISHVEZZWVXSMSUlJb+S+q8uskc5ih0BEbwClUgWJRPzBOomIqG5ggU2vxb59+8pcJ5fLy52j1MLCojpC0rryjlFfX/+N3Xd1UCgUFV4XVL3kcjlSU1MhlUqZB5EwB9rB4pqIiF4nFtj0WmgyIEBtJ+Yxvonnl+MvikulUkEulzMPImIOiIiIap+a/2ArERERERERUS3AApuIaiQdHXbrFJOOjg4MDAyYBxExB0RERLUPu4gTUY2jr6/PZ05FZmBgADs7O7HDqNNqew44uBgREdVFLLCJqEZauesC0jJyxA6DiKrAytKIMwEQEVGdxAKbiGqktIwcpKRniR0GEREREZHG+Ax2DTN16lQEBgZq3P7cuXPYsGFDpffj7e2NJUuWVPp9VbFt2zacPHnyteyLqkdVrzMiIiIiorqEBXYtd/78ecTGxoodRrl27NjBAruWqw3XGRERERGR2Fhg0xvj2bNnYodQroKCAuTn55dYrlKpoFAoqrzdqh53TT9fRERERES1Ta0tsOfNm4d+/frh3LlzGDRoEJycnDBkyBBcuXIFAJCWlgaZTIaEhAS19y1btgze3t7C6/j4eMhkMiQnJyMoKAiOjo7w8fHBmTNnoFQqsWrVKri6usLV1RVRUVFQKpVaO4aUlBSMGjUKDg4O6N27Nw4cOFCizf379xEaGgpXV1c4ODjA29sbH3/8MQAgOjoaMTExyMvLg0wmg0wmq1T3cgDYtWsXvLy84OzsjKlTp+LRo0dq69PT0zF9+nQ4OzvDyckJ48ePx40bN9TaJCYmwt/fH506dUKXLl3g7+8v3LH29vZGeno6du3aJcQYHx9fYVz5+flYsWIFevbsCXt7e7i7u2Py5MnIySkc9OrcuXOQyWT44YcfMH36dHTu3BmhoaHCdfGyEydOQCaT4c8//3zlfQNAdnY2Fi1aBHd3d9jb28Pf3x8//vij2nYCAwMxadIkHDhwAD4+PnBwcMD169eFGE+ePIkBAwbAwcEBSUlJAIDvvvsOAwcOhIODA9zd3REZGYnnz58L2yzruCtS3vsOHjyI999/H++88w5cXFwQGBiIy5cvC++t6DpLSUnBlClThGtk4sSJuHv3boUxERERERG9aWr1IGcPHz5EREQEJk6cCCMjI0RFRSE4OBjHjx+v9Lbmzp2LESNGYNy4cdi4cSOCg4MxePBg5ObmYsWKFbh06RKio6Nha2uL/v37v3Lsz58/R1BQEAwMDPDJJ58AANasWYPc3Fy0bt1aaDdnzhw8ePAACxYsgJmZGe7duyd8iTB06FDcv38fR44cwfbt2wEAhoaGGseQlJSEO3fuYOHChXj8+DEiIyOxdOlSrFq1CgCQm5uLwMBASCQSLF68GPXq1cP69esxatQoHDp0CM2aNcPdu3cRGhoKPz8/zJw5E0qlEtevX0dWVuHgVDExMZg4cSI6d+6MoKAgAECrVq0qjC02Nha7d+/GrFmzYGNjg8ePH+P06dMl7vSGh4djwIABWLt2LSQSCRQKBQ4cOIA//vgDtra2QrsjR46gQ4cOePvtt1953wqFAuPGjUNmZiY+/PBDWFpa4tChQ5g0aZLwhU2RK1euID09HaGhoTA2NkazZs0AAA8ePEBERASmTJmCZs2aoXnz5khMTMT06dOFc/nnn39i1apVuHfvHtasWVPucWuqtPelpaVh0KBBaNWqFRQKBY4ePYqRI0fi0KFDkEql5V5nf/31F0aMGAEbGxssX74cOjo62LBhA8aOHYuEhATo6+trHBsRERERUW1XqwvsrKwsxMXFwcbGBkDhnKGjR4/GpUuX0LRp00pta9SoUQgICAAAWFpaon///rhy5Qr27NkDAPDw8EBSUhISEhK0UmDHx8fjwYMHOHbsmFBQ29nZ4d1331UrsJOTkxEWFgZfX19h2aBBgwAATZs2RdOmTSGRSODk5FTpGFQqFdavXy8UQenp6YiNjYVSqYREIkF8fDz+/vtvHD16FG3atAEAuLi4wMvLC9u3b8e8efNw9epV5OfnIzw8XCi6PDw8hH3Y2dlBX18fTZo0qVSMycnJcHd3x8iRI4VlPj4+Jdp5e3tj9uzZwusXL17A1NQUR48eFQpsuVyOpKQkBAcHa2Xfhw8fxvXr1/H111+jbdu2AAqP+c6dO1i3bh1Wr14ttM3KysK+ffuEwrr48k2bNsHR0VFY9uGHH8LJyQlRUVEAAE9PTxgYGGDhwoW4ceOGWuH+8nFrqrT3FT8vSqUSbm5uuHz5Mg4cOICwsLByr7OYmBiYmJhg69atqFevHgCgc+fO6NWrF/bu3at2Domo7pHL5VCpVGKHUWVyuVztv/T6MQfiYw7ExxyIT6VSQUdHR6O2tbrAtrCwEIprAEKxk5GRUekC283NTfi9qMDt1q2bWhupVIrU1NQqRqvu8uXLsLGxUSumra2t0a5dO7V2dnZ22LJlC3R1deHm5gZra2ut7B8oLJaL32Fs06YN8vPzkZmZCXNzc/zyyy+wsbERimsAaNSoEVxdXXHhwgUAgEwmg66uLmbNmoVhw4bBxcUFRkZGrxybnZ0dNm/ejOjoaPTo0QP29val3qnt2bOn2uu33noL7777Lr755hvMmDEDQGH3cLlcDj8/P63s+/Tp07C1tUXr1q3x4sULYbmrqysOHTqkti1bW9sSxTVQeB6LF9dPnz7FtWvXMHfuXLV2vr6+WLhwIS5cuKBWYL983Joq7X0pKSn47LPP8NtvvyEzM1NYfvv27Qq3d/r0afj6+kJXV1c4F8bGxrCzsxN6WhBR3ZWamvpGfCDU5N9Dql7MgfiYA/ExB+LStGdmrS6wjY2N1V7r6ekBgNozq5oqXhQWnbzStv8qg1EV9+DBA5iZmZVYbmZmphb/qlWrsGrVKnz++edYvHgxpFIpwsLC0Ldv31eO4eXjKzruov1nZ2ejSZMmpcZ48+ZNAIVfOmzYsAGxsbEIDg6GRCKBu7s7Fi5ciObNm1c5tilTpkAikeDAgQOIiYmBqakpRo4ciWnTpql9e1TaOfTz88OXX36Jy5cvo2PHjjh69Ci6dOmi8ZcuFe378ePHuHr1Kjp06FDivbq6umqvSzt/pS3PycmBSqUqcTxGRkbQ19cXutyXd9yaePl9ubm5CAoKgqmpKebNm4fmzZujXr16WLBggUZ/R48fP8b27duFruPFFf09ElHdJZVKa/0d7Nu3b6N169YwMDAQO5w6iTkQH3MgPuZAfLdu3dK4ba0usMtT1F315VGbs7OzxQinBAsLC/z+++8llmdmZqo9R21hYYHIyEgolUpcuXIF69evx4wZM5CQkICWLVtWa4wmJial3rHPzMyEiYmJ8NrT0xOenp7Izc3FqVOnEBkZifnz55dadGlKX18fISEhCAkJwZ07d7B//35ER0fDyspK6CIPoNSuGs7OzmjWrBmOHj0KqVSKU6dO4d///rfW9m1iYgKZTIZly5ZVuK2yupK8vNzIyAg6OjolBpnLycmBQqFQO9/lbbey8Vy8eBH3799HbGysWu+JnJwcjb6QMDExQY8ePYTHK4pr2LBhlWIkojfHm/JB0MDAAA0aNBA7jDqNORAfcyA+5kA8lfnsXWtHEa+ImZkZ9PT0kJKSIixTKBT4+eefRYzq/zg4OODmzZu4c+eOsOzOnTu4fv16qe0lEgk6duyIDz/8EC9evBDep8276i9zdnbGH3/8oTbydlZWFs6cOQNnZ+cS7Q0NDeHr6ws/Pz+1866np1elXgVFrK2tERYWhkaNGmk0CriOjg58fX1x7NgxfPvtt1AqlaU+v13Vfbu6uuKvv/6ChYUFHBwcSvxURcOGDdG+ffsSo94fO3YMAEo939pQNFVX8bvNv/76K9LT09XalXWdde/eHTdv3oSdnV2J86DJgHJERERERG+SN/YOtkQiQZ8+fbBr1y5YW1ujcePGiIuLq9QD6tXJ398f69evx6RJk4TpktasWaPWdTgnJwfjx4/HwIEDIZVKkZ+fj507dwrPuAKFz02/ePEC27dvR6dOnWBoaKi1wsbf3x/btm3DpEmT8OGHHwqjiL/11lsYM2YMAGD37t24ePEiPDw8YG5ujrS0NBw6dEjtmfa3334bZ8+exenTp2FsbAwrKys0bty43H1PnToVHTp0gJ2dHQwMDHDixAlkZWWVeC6+LP369cPmzZuxevVquLm5wdTUVOPjrmjfgwYNwu7duzF69GgEBQWhdevWyMnJEQZ8mzlzpsb7Ki44OBjTpk3DrFmzMGDAAKSmpmLVqlXw8fFRe/5am5ycnNCgQQMsXrwYEydOREZGBqKjo2FpaanWrqzrbPr06RgyZAjGjx+PYcOGoUmTJvjnn39w/vx5dOnSpdQp04iIiIiI3lRvbIENFE5JFB4ejoiICDRs2BDjx4+HVCpFYmKi2KGhfv362LJlCxYtWoTZs2fD0tISU6dORWJiojDfcr169WBra4udO3fi3r17qF+/Puzt7bF582ahYPTy8kJAQAA2btyIzMxMuLi4YOfOnVqJ0dDQEDt37sTy5csRHh4OpVKJzp07Iy4uThi4SyaT4cSJE4iMjMSTJ09gbm4OPz8/tbmZw8LCsGjRIoSEhODp06eIjIyEv79/ufvu3Lkzjh07hq1bt6KgoABSqRQrV66Eq6urRrHb2dkJg9LNmjWrUsdd0b719fWxY8cOREdHY8OGDXj48CEaNWoEOzu7UrtKa6pXr15YvXo11q5di6lTp6JRo0YYNmxYlQt2TTRp0gSrV6/GJ598gqlTp6J169ZYvHgxvvjiC7V2ZV1n1tbW2Lt3rzBGQF5eHszNzeHi4lJtXwoQEREREdVUOqraPPoIEb1xkpOTAQCbj2ciJT2rgtZEVBO1aWGCz8N6ih3GK8vLy8O1a9fQvn17PvcoEuZAfMyB+JgD8RV9PtXkcdA39hlsIiIiIiIiotfpje4iXp2Kz3/8Mh0dnXKnJZFIJKXO6awtFcX28lRSr5tKpUJBQUGZ66vz/Ii57+ryJh4TAFhZvvp86kQkDv79EhFRXcUCu4pKmwO5SIsWLUqMwlxccHAwQkJCqiMsABXHlpSUVG371sSBAwcwf/78MtdX5/kRc9/V5U08JgCYNbJ6Rk4notdDqVRBIhF/UFEiIqLXiQV2Fe3bt6/MdXK5vNy5Py0sLKojJEF5senr61frvjXh5eVVbozVeX7E3Hd1eROPSaFQVPh3RNVLLpcjNTUVUqmUeRBJbc8Bi2siIqqLWGBXUVXnO34danJsANC4ceMKp+l6E/ddXd7EYwJQ7mMWVP1UKhXkcjnzICLmgIiIqPapfQ9mElGdUBPmq6/LdHR0YGBgwDyIiDkgIiKqfXgHm4hqHH19/VrZJfZNYmBgADs7O7HDqNNqew74DDYREdVFLLCJqEZauesC0jJyxA6DiKrAytKIAxUSEVGdxAKbiGqktIwcpKRniR0GEREREZHG+Aw21XlTp05FYGCg8Do6OhqdOnVSa/P7779j2LBhcHR0hEwmQ3Z2NhQKBebPn49u3bpBJpNh27Ztrzny1yc7OxvR0dG4deuW2KEQEREREdVYvINN9JKhQ4eiR48eassiIiJQUFCA2NhY1K9fHw0bNkR8fDy+/vprLF++HK1atUKLFi1Eirj6ZWdnIyYmBjY2Nmjbtq3Y4RARERER1UgssIle0rRpUzRt2lRt2Z9//omAgAB069ZNbZmFhQUGDBhQbbEoFAq89dZbkEi039mkOrdNRERERFQX8ZM1aWzevHno168fzp07h0GDBsHJyQlDhgzBlStXAABpaWmQyWRISEhQe9+yZcvg7e0tvI6Pj4dMJkNycjKCgoLg6OgIHx8fnDlzBkqlEqtWrYKrqytcXV0RFRUFpVKptWNISUnBqFGj4ODggN69e+PAgQMl2hTvIn7u3DnIZDI8efIE69atg0wmQ2BgILy9vbFlyxbcu3cPMpkMMpkMaWlpFe4/MTER/v7+6NSpE7p06QJ/f3+cPHlSWO/t7Y0lS5Zg06ZN8PLyQseOHfHdd98J56u4goICuLm5ISoqSqNjL23bT548QUpKCmbMmIEePXrA0dERvr6+2LJli3De09LS0KtXLwBAaGhoieNVKBT47LPP4OXlBXt7e7z33ns4fPiwRjEREREREb1JeAebKuXhw4eIiIjAxIkTYWRkhKioKAQHB+P48eOV3tbcuXMxYsQIjBs3Dhs3bkRwcDAGDx6M3NxcrFixApcuXUJ0dDRsbW3Rv3//V479+fPnCAoKgoGBAT755BMAwJo1a5Cbm4vWrVuX+p4OHTpgz549GDduHHx9fTF06FAYGhpCoVBg06ZN+PnnnxETEwMAsLCwKHf/d+/eRWhoKPz8/DBz5kwolUpcv34dWVnqA3l99913sLa2xn/+8x9IJBJ069YNFhYW+Oabb+Dg4CC0O3v2LP755x/069dP43Pw8rYbNGiAGzduQCqVon///mjYsCGuXbuG6Oho5OXlITg4GBYWFoiJiUFwcDDCwsLQtWtXteMNDQ3Fr7/+imnTpqFNmzY4efIkZs+eDWNj4xJd7YmIiIiI3mQssKlSsrKyEBcXBxsbGwCF87SOHj0aly5dKtGtuiKjRo1CQEAAAMDS0hL9+/fHlStXsGfPHgCAh4cHkpKSkJCQoJUCOz4+Hg8ePMCxY8eEgtrOzg7vvvtumQW2oaEhnJycoKuri6ZNm8LJyUlY16RJE+jr66stK8/Vq1eRn5+P8PBwGBoaAig8xpfl5+dj06ZNaNCggbDM19cX33zzDebMmQMdncJ5ZY8cOQIbGxvIZDKN9l/Wtrt3747u3bsDAFQqFZydnfHs2TPExcUhODgY+vr6aN++PQDA2tpa7XjPnj2LpKQkbN68Ge7u7gAANzc3PHz4ENHR0Sywieo4uVwOlUoldhhVJpfL1f5Lrx9zID7mQHzMgfhUKpXwGbwiLLCpUiwsLITiGoAw4FVGRkalC2w3Nzfh96ICt/gzzgAglUqRmppaxWjVXb58GTY2NmrFtLW1Ndq1a6eV7VdEJpNBV1cXs2bNwrBhw+Di4gIjI6MS7bp27apWAAOAn58ftm3bhgsXLqBLly5QKBT4/vvvERQUVKkYStv28+fPERsbi8OHD+PevXvIz88X1j19+hQNGzYsc3unT59Go0aN0K1bN7x48UJY7urqikWLFqGgoAC6urqVipGI3hypqalvxAfC27dvix1CnccciI85EB9zIC59fX2N2rHApkoxNjZWe62npwegsEirrOLFZdEFW9r2FQpFpbddmgcPHsDMzKzEcjMzsyrFX1lSqRQbNmxAbGwsgoODIZFI4O7ujoULF6J58+Zq8bysY8eOaNWqFY4cOYIuXbrg1KlTyM7OrlT38LK2/emnn2Lv3r2YNm0a7O3tYWRkhMTERKxfvx7Pnz8vt8B+/Pgxnjx5gg4dOpS6/uHDh5X+4oWI3hxSqbTW38G+ffs2WrduDQMDA7HDqZOYA/ExB+JjDsRXmalqWWCT1tSrVw8A1O6AAoVTPNUEFhYW+P3330ssz8zMFLpsVzdPT094enoiNzcXp06dQmRkJObPn4/t27cLbcrqfuLn54c9e/ZgwYIF+Oabb+Do6IiWLVtWav+lbTshIQHDhw/HxIkThWXFB14rj4mJCUxNTbFx48ZS15uamlYqPiJ6s7wpHwQNDAxK9P6h14s5EB9zID7mQDyadg8HOIo4aZGZmRn09PSQkpIiLFMoFPj5559FjOr/ODg44ObNm7hz546w7M6dO7h+/fprj8XQ0BC+vr7w8/NTO1/l6devHx49eoSkpCQkJSXBz89PK7E8f/5c6IkAFI5OfvToUbU2ZfVUcHV1xaNHj6CnpwcHB4cSP5p2pSEiIiIiehPwDjZpjUQiQZ8+fbBr1y5YW1ujcePGiIuLq9SgANXJ398f69evx6RJkxAaGgqgcBTxJk2avJb97969GxcvXoSHhwfMzc2RlpaGQ4cOqT2LXp62bdtCJpNh6dKleP78OXx9fbUSl6urK/bu3Yu2bduicePG+PLLL0t0yzc3N4exsTGOHj0KKysr6OvrQyaTwc3NDV5eXpgwYQImTJgAmUwGuVyOW7du4c6dO1i2bJlWYiQiIiIiqg14B5u0Kjw8HO+88w4iIiKwcOFCeHh4oHfv3mKHBQCoX78+tmzZAjMzM8yePRsrV67EhAkT1Ka+qk4ymQyPHz9GZGQkgoKCEB0dDT8/P3z00Ucab6Nfv3548OABunbtCnNzc63EFR4eDhcXFyxduhT/+c9/YGtri8mTJ6u1kUgkiIyMRFpaGsaOHYshQ4bgwYMHAAq/pBgxYgT++9//4oMPPsB//vMf/Pjjj3BxcdFKfEREREREtYWOqjaPPkJEb5zk5GQAwObjmUhJz6qgNRHVRG1amODzsJ5ih/HK8vLycO3aNbRv357PPYqEORAfcyA+5kB8RZ9PNbkxxzvYRERERERERFrAZ7Cp1ig+z/LLdHR0yp0KRiKRQCKp3u+TKoqvOueDFnPf1cXKsuQc4URUO/Dvl4iI6ioW2FRrlDXXMgC0aNEC6enpZa4PDg5GSEhIdYQlqCi+pKSkN3Lf1WXWSGexQyCiV6BUqiCRiD/AJRER0evEAptqjX379pW5Ti6XlzvfqoWFRXWEpKa8+Kp7uiox910dFApFhTml6iWXy5GamgqpVMo8iKS254DFNRER1UUssKnWeF2jfVeVmPHV9HNTFRx/UVwqlQpyuZx5EBFzQEREVPtwkDMiIiIiIiIiLWCBTUQ1ko4Ou5eKSUdHBwYGBsyDiJgDIiKi2oddxImoxtHX16+Vz5y+SQwMDGBnZyd2GHVabcsBBzUjIiJigU1ENdTKXReQlpEjdhhEpAErSyOO/E9ERAQW2ERUQ6Vl5CAlPUvsMIiIiIiINMZnsImqID4+HocPH9b6dg8fPoy+ffuiQ4cOGDhwINLS0iCTyZCQkKD1fWni3r17mD9/Pry9veHg4AB3d3eMHTsWX3/9tdDm3LlzkMlkpf48evRIlLiJiIiIiMTAO9hEVXDgwAE0aNAA/fv319o2nz59in//+9/o168fIiMjYWhoqLVtV0V2djaGDRsGExMThISEoHnz5rh//z7Onj2L//3vfxg4cKBa+8jISLz99ttqy4yNjV9nyEREREREomKBTVRDpKenQ6FQYMCAAXB2LnyWMS0tTbR4vv32Wzx48AB79uxB8+bNheUDBw6EUqks0d7GxuaNnI+biIiIiEhT7CJOddJvv/2GoKAgdO7cGZ06dcLQoUNx+vRpAMDKlSvRv39/dOrUCR4eHggLC8ODBw+E9wYGBuL8+fP44YcfhK7Q0dHRrxRPdHS0cDd87Nix5W7z4MGDeP/99/HOO+/AxcUFgYGBuHz5col2x48fh4+PDxwcHDBs2DD8/vvv6NKli8axZmVlQSKRwMzMrMQ6iYT/dBARERERvYx3sKnOuXDhAsaMGQMnJydERETA2NgYV65cwd9//w0AyMzMxKRJk2BhYYFHjx5h69atCAwMxNGjR/HWW2/ho48+wuzZs1G/fn3MnTsXANC0adNXimno0KFo2bIl5s6di4ULF6JDhw5o2rQpXrx4UaJtWloaBg0ahFatWkGhUODo0aMYOXIkDh06BKlUCgC4evUqQkND4eXlhX//+99IT0/HjBkzoFAoNI6pQ4cOUCqVmDVrFoKCguDg4IC33ir7nwylUqkWr0QiYSFORERERHUKC2yqcz799FNYW1tj+/bt0NXVBQC4u7sL6yMjI4XfCwoK0KlTJ3h6euLs2bNwd3dH27ZtYWhoiAYNGsDJyUkrMTVt2hQymQwA0LZtW2G7pXURDw4OFn5XKpVwc3PD5cuXceDAAYSFhQEAYmNjYWVlhejoaKHIbdiwIebMmaNxTN27d8f48eOxdetWfPfdd6hfvz6cnZ0xYMAADBw4EDo66vPdDhs2TO31kCFDsGzZMo33R0S1n1wuh0qlEjsMrZHL5Wr/pdePORAfcyA+5kB8KpWqxGffsrDApjpFLpfj0qVLCAsLE4rrl508eRLr16/HzZs3kZubKyy/ffu2WiEulpSUFHz22Wf47bffkJmZKSy/ffu28HtycjJ69+6tdge5V69eld7XnDlz8P777yMxMREXLlzATz/9hNOnT+P06dP49NNP1dquWLECbdq0EV6bmppWen9EVLulpqa+kR8Ai//7SuJgDsTHHIiPORCXvr6+Ru1YYFOdkp2dDaVSCQsLi1LXX758GVOnTkWvXr3wwQcfwMzMDDo6Ohg2bBieP3/+mqMtKTc3F0FBQTA1NcW8efPQvHlz1KtXDwsWLFCL7+HDhyUKXENDQ9SrV6/S+2zZsiXGjh2LsWPH4unTpwgNDcWhQ4cwfvx4tGvXTmjXpk0bDnJGVMdJpdI37g727du30bp1axgYGIgdTp3EHIiPORAfcyC+W7duadyWBTbVKUZGRpBIJGqDlhX3/fffw9DQEJ9//rlw9zc9Pf11hliuixcv4v79+4iNjVUrbnNyctSeAzc3Ny8xB3Vubu4rf0nQsGFDBAQE4H//+x/+/PNPtRiIiN7UD34GBgZo0KCB2GHUacyB+JgD8TEH4tG0ezjAUcSpjil6bvrrr79GQUFBifXPnj2Dnp6e2h/R4cOHS7TT09MT5Y72s2fPhP0X+fXXX0t8CeDg4IAffvhBbTqt77//vlL7evToUal3ooq6JzVp0qRS2yMiIiIietPxDjbVOTNnzhS6PAcEBMDExAS///47GjduDDc3N2zfvh1Lly5Fnz598Ntvv+Hrr78usY23334bBw8eRFJSEszNzWFhYQFLS8tqj93JyQkNGjTA4sWLMXHiRGRkZCA6OrrEvidNmoQhQ4YgJCQEw4YNw99//40tW7agXr16Gn8Dd+DAAXz99dcYOHAg7OzsoFQq8dtvv2HTpk3o0KGDMFc3EREREREV4h1sqnO6dOmCHTt2QEdHB/Pnz0dwcDC+//57tGjRAj169MCsWbOQmJiIKVOm4JdffkFsbGyJbXzwwQfo3Lkz5s6diyFDhuCrr756LbE3adIEq1evxqNHjzB16lRs374dixcvhrW1tVo7Ozs7fP7557h16xaCg4Oxd+9eLF++HAUFBTAyMtJoXz169ICLiwsOHjyI4OBgBAcH49ixYwgKCsK2bdvKHCSOiIiIiKiu0lG9SaOREFGZfvrpJ4wdOxY7d+7EO++8I3Y4ZUpOTgYAbD6eiZT0LJGjISJNtGlhgs/Deoodhtbl5eXh2rVraN++PZ97FAlzID7mQHzMgfiKPp9qMqAvu4gTvaEWLVqE7t27o1GjRrh16xbWrVsHOzs7dOnSRezQiIiIiIjeSCywibRApVKVOmhaEYlEojbg2Mt0dXUrNTqhJrKzs7F06VI8efIEhoaG8PDwwNy5cyGRSDSKt/gc2mKwstSsKzsRiY9/r0RERIVYYBNpwfnz5zF69Ogy1w8ePBgHDhwoc/2OHTvQtWtXrcb02WeflblOk3iXL1+u1Xgqa9ZIDqJGVJsolSpIJNr9opCIiKi2YYFNpAUdOnTAvn37ylzfuHFjjBw5ssz1Uqm0OsIqkybxikmhUEAul7+xc+rWBnK5HKmpqZBKpcyDSGpbDlhcExERscAm0gpDQ8MKBz2wsrJ6TdFUTJN4xcbxF8WlUqkgl8uZBxExB0RERLUPp+kiohpJ28+kU+Xo6OjAwMCAeRARc0BERFT78A42EdU4+vr6taJL7JvMwMAAdnZ2YodRp1UmB3z+mYiIqGZggU1ENdLKXReQlpEjdhhENZ6VpREHBSQiIqohWGATUY2UlpGDlPQsscMgIiIiItIYn8GuA6ZOnYrAwECN2587dw4bNmyo9H68vb2xZMmSSr+vKrZt24aTJ09qZVsvn5/o6Gh06tRJrc3vv/+OYcOGwdHRETKZDNnZ2VAoFJg/fz66desGmUyGbdu2aSWemig7OxvR0dG4deuW2KEQEREREdVYvINNJZw/fx5btmzB5MmTxQ6lTDt27EDPnj3Ro0cPrW976NChJbYbERGBgoICxMbGon79+mjYsCHi4+Px9ddfY/ny5WjVqhVatGih9VhqiuzsbMTExMDGxgZt27YVOxwiIiIiohqJBTbRS5o2bYqmTZuqLfvzzz8REBCAbt26qS2zsLDAgAEDqi0WhUKBt956CxKJ9jubVOe2iYiIiIjqIn6yLmbevHno168fzp07h0GDBsHJyQlDhgzBlStXAABpaWmQyWRISEhQe9+yZcvg7e0tvI6Pj4dMJkNycjKCgoLg6OgIHx8fnDlzBkqlEqtWrYKrqytcXV0RFRUFpVKptWNISUnBqFGj4ODggN69e+PAgQMl2ty/fx+hoaFwdXWFg4MDvL298fHHHwMo7B4dExODvLw8yGQyyGSySnUvB4Bdu3bBy8sLzs7OmDp1Kh49eqS2Pj09HdOnT4ezszOcnJwwfvx43LhxQ61NYmIi/P390alTJ3Tp0gX+/v5Cl3Bvb2+kp6dj165dQozx8fFaOz/Fu4ifO3cOMpkMT548wbp164Tz4e3tjS1btuDevXtCDGlpaRXuv7zjKjq2JUuWYNOmTfDy8kLHjh3x3XffCddTcQUFBXBzc0NUVJRGx17atp88eYKUlBTMmDEDPXr0gKOjI3x9fbFlyxbhukxLS0OvXr0AAKGhoSWOV6FQ4LPPPoOXlxfs7e3x3nvv4fDhwxrFRERERET0JuEd7Jc8fPgQERERmDhxIoyMjBAVFYXg4GAcP3680tuaO3cuRowYgXHjxmHjxo0IDg7G4MGDkZubixUrVuDSpUuIjo6Gra0t+vfv/8qxP3/+HEFBQTAwMMAnn3wCAFizZg1yc3PRunVrod2cOXPw4MEDLFiwAGZmZrh3757wJcLQoUNx//59HDlyBNu3bwcAGBoaahxDUlIS7ty5g4ULF+Lx48eIjIzE0qVLsWrVKgBAbm4uAgMDIZFIsHjxYtSrVw/r16/HqFGjcOjQITRr1gx3795FaGgo/Pz8MHPmTCiVSly/fh1ZWYUDXsXExGDixIno3LkzgoKCAACtWrXS2vkprkOHDtizZw/GjRsHX19fDB06FIaGhlAoFNi0aRN+/vlnxMTEAAAsLCzK3X9Fx1Xku+++g7W1Nf7zn/9AIpGgW7dusLCwwDfffAMHBweh3dmzZ/HPP/+gX79+FR57Wdtu0KABbty4AalUiv79+6Nhw4a4du0aoqOjkZeXh+DgYFhYWCAmJgbBwcEICwtD165d1Y43NDQUv/76K6ZNm4Y2bdrg5MmTmD17NoyNjaulCz8RERERUU3FAvslWVlZiIuLg42NDYDCeUhHjx6NS5culeg2XJFRo0YhICAAAGBpaYn+/fvjypUr2LNnDwDAw8MDSUlJSEhI0EqBHR8fjwcPHuDYsWNCwWhnZ4d3331XrYBMTk5GWFgYfH19hWWDBg0C8H/doyUSCZycnCodg0qlwvr166Gvrw+g8G51bGwslEolJBIJ4uPj8ffff+Po0aNo06YNAMDFxQVeXl7Yvn075s2bh6tXryI/Px/h4eFCce/h4SHsw87ODvr6+mjSpEmlYtT0/BRnaGgIJycn6OrqomnTpmr7a9KkCfT19TWOoaLjKpKfn49NmzahQYMGwjJfX1988803mDNnDnR0Cue6PXLkCGxsbCCTyTTaf1nb7t69O7p37w6gMH/Ozs549uwZ4uLiEBwcDH19fbRv3x4AYG1trXa8Z8+eRVJSEjZv3gx3d3cAgJubGx4+fIjo6GgW2ESvkVwuh0qlEjuMN4pcLlf7L71+zIH4mAPxMQfiU6lUwmfwirDAfomFhYVQXAMQBnTKyMiodIHt5uYm/F5UwBV/hhcApFIpUlNTqxitusuXL8PGxkatWLS2tka7du3U2tnZ2WHLli3Q1dWFm5sbrK2ttbJ/oLBYLiquAaBNmzbIz89HZmYmzM3N8csvv8DGxkYorgGgUaNGcHV1xYULFwAAMpkMurq6mDVrFoYNGwYXFxcYGRm9cmyanp/qoulxde3aVa0ABgA/Pz9s27YNFy5cQJcuXaBQKPD9998Ld/A1Vdq2nz9/jtjYWBw+fBj37t1Dfn6+sO7p06do2LBhmds7ffo0GjVqhG7duuHFixfCcldXVyxatAgFBQXQ1dWtVIxEVDWpqan88FVNbt++LXYIdR5zID7mQHzMgbiK1zjlYYH9EmNjY7XXenp6AAqLkMoqXjwVJaS07SsUikpvuzQPHjyAmZlZieVmZmZq8a9atQqrVq3C559/jsWLF0MqlSIsLAx9+/Z95RhePr6i4y7af3Z2Npo0aVJqjDdv3gRQ+KXDhg0bEBsbi+DgYEgkEri7u2PhwoVo3rx5lWPT9PxUF02Pq7QYO3bsiFatWuHIkSPo0qULTp06hezs7Ep1Dy9r259++in27t2LadOmwd7eHkZGRkhMTMT69evx/Pnzcgvsx48f48mTJ+jQoUOp6x8+fFjpL6aIqGqkUinvYGuZXC7H7du30bp1axgYGIgdTp3EHIiPORAfcyC+ykxVywK7EurVqwcAanf4gMKisSawsLDA77//XmJ5Zmam2nPUFhYWiIyMhFKpxJUrV7B+/XrMmDEDCQkJaNmyZbXGaGJiUuod+8zMTJiYmAivPT094enpidzcXJw6dQqRkZGYP3++8Fx4VWh6fqqTJsdVVvcTPz8/7NmzBwsWLMA333wDR0fHSuertG0nJCRg+PDhmDhxorBM0znGTUxMYGpqio0bN5a63tTUtFLxEVHV8UNX9TEwMCjR+4deL+ZAfMyB+JgD8WjaPRzgKOKVYmZmBj09PaSkpAjLFAoFfv75ZxGj+j8ODg64efMm7ty5Iyy7c+cOrl+/Xmp7iUSCjh074sMPP8SLFy+E92nzrvrLnJ2d8ccff+DPP/8UlmVlZeHMmTNwdnYu0d7Q0BC+vr7w8/NTO+96enqVvutc2fNTnco6rvL069cPjx49QlJSEpKSkuDn56eVWJ4/fy701AAKRyc/evSoWpuyenK4urri0aNH0NPTg4ODQ4kfTbvSEBERERG9CXgHuxIkEgn69OmDXbt2wdraGo0bN0ZcXFylHnqvTv7+/li/fj0mTZqE0NBQAIWjZBfvkp2Tk4Px48dj4MCBkEqlyM/Px86dO2FsbAw7OzsAhc9Nv3jxAtu3b0enTp1gaGiIt99+W2sxbtu2DZMmTcKHH34ojCL+1ltvYcyYMQCA3bt34+LFi/Dw8IC5uTnS0tJw6NAhtWfa3377bZw9exanT5+GsbExrKys0Lhx41c+P9VJk+MqT9u2bSGTybB06VI8f/5cbZC6V+Hq6oq9e/eibdu2aNy4Mb788ssSX7CYm5vD2NgYR48ehZWVFfT19SGTyeDm5gYvLy9MmDABEyZMgEwmg1wux61bt3Dnzh0sW7ZMKzESEREREdUGLLArKTw8HOHh4YiIiEDDhg0xfvx4SKVSJCYmih0a6tevjy1btmDRokWYPXs2LC0tMXXqVCQmJiInJwdAYTd3W1tb7Ny5E/fu3UP9+vVhb2+PzZs3C915vby8EBAQgI0bNyIzMxMuLi7YuXOnVmI0NDTEzp07sXz5coSHh0OpVKJz586Ii4tDs2bNABQOBnbixAlERkbiyZMnMDc3h5+fn1AUA0BYWBgWLVqEkJAQPH36FJGRkfD393/l81OdNDmuivTr1w9RUVHo3r07zM3NtRJXeHg4PvroIyxduhQGBgYYPHgw+vTpgwULFghtJBIJIiMj8dlnn2Hs2LFQKBRITEyElZUV1qxZg40bN+K///0v0tPTYWRkBBsbmwrzQURERET0ptFRcUQUIqpBkpOTAQCbj2ciJT2rgtZE1KaFCT4P6yl2GG+kvLw8XLt2De3bt+dzjyJhDsTHHIiPORBf0edTBweHCtvyGWwiIiIiIiIiLWAX8Rqk+DzCL9PR0Sl3+hWJRAKJpPq+L6koNrHnOlapVCgoKChzfXWfH0Dcc1TT81MVVpavPvc5UV3AvxUiIqKagwV2DVLWXMIA0KJFC6Snp5e5Pjg4GCEhIdURFoCKY0tKSqq2fWviwIEDmD9/fpnrq/v8AOKeo5qen6qYNbLkqPJEVDqlUgWJRPzBNomIiOo6Ftg1yL59+8pcJ5fLy53j1MLCojpCEpQXW02YisnLy6vcGKv7/ADinqOanp/KUigUFV7zVL3kcjlSU1MhlUqZB5FUJgcsromIiGoGFtg1iCYPzYulJscGAI0bN65wmq7qJuY5qun5qQqOvygulUoFuVzOPIiIOSAiIqp9OMgZERERERERkRawwCaiGklHh11exaSjowMDAwPmgYiIiKgS2EWciGocfX19PvcrMgMDA9jZ2YkdxhuPg5MRERG9WVhgE1GNtHLXBaRl5IgdBlG1sbI04mj5REREbxgW2ERUI6Vl5CAlPUvsMIiIiIiINMZnsAFMnToVgYGBGrc/d+4cNmzYUOn9eHt7Y8mSJZV+X1Vs27YNJ0+efC37otcnLS0N0dHRyMjIeK375fVERERERFQxFthVcP78ecTGxoodRrl27NjBgugNlJ6ejpiYGDx48OC17pfXExERERFRxVhgU52nUCigVCrFDqNcKpUKCoWixm6PiIiIiIgqWWDPmzcP/fr1w7lz5zBo0CA4OTlhyJAhuHLlCoDC7qsymQwJCQlq71u2bBm8vb2F1/Hx8ZDJZEhOTkZQUBAcHR3h4+ODM2fOQKlUYtWqVXB1dYWrqyuioqK0WvykpKRg1KhRcHBwQO/evXHgwIESbe7fv4/Q0FC4urrCwcEB3t7e+PjjjwEA0dHRiImJQV5eHmQyGWQyWaW6lwPArl274OXlBWdnZ0ydOhWPHj1SW5+eno7p06fD2dkZTk5OGD9+PG7cuKHWJjExEf7+/ujUqRO6dOkCf39/4Q6jt7c30tPTsWvXLiHG+Pj4CuPKz8/HihUr0LNnT9jb28Pd3R2TJ09GTk7hQFN5eXlYsmQJfHx84OjoCG9vbyxcuFBYX6SoK/y2bdvQo0cPdOrUCfPmzYNCocC1a9cwYsQI4dp5+bhUKhU2b94MHx8f2Nvbo1evXti2bVulzm9556Z4fJs2bYKXlxc6duyIJ0+eAAAOHjyIQYMGwcHBAV27dsUHH3yA9PR0jfYbGBiISZMm4eDBg+jduzc6duyIwMBA/Pnnn2rtnj9/jsjISLi7u8PBwQEDBw7E8ePH1doU/a2dPHkSAwYMgIODA5KSkjB69GgAwJAhQ4TcaqKs7WmS04qup/j4ePTv3x8ODg7w8PDAqlWrUFBQoFFcRERERERvkkoPcvbw4UNERERg4sSJMDIyQlRUFIKDg0sUCJqYO3cuRowYgXHjxmHjxo0IDg7G4MGDkZubixUrVuDSpUuIjo6Gra0t+vfvX+ntv+z58+cICgqCgYEBPvnkEwDAmjVrkJubi9atWwvt5syZgwcPHmDBggUwMzPDvXv3hC8Rhg4divv37+PIkSPYvn07AMDQ0FDjGJKSknDnzh0sXLgQjx8/RmRkJJYuXYpVq1YBAHJzcxEYGAiJRILFixejXr16WL9+PUaNGoVDhw6hWbNmuHv3LkJDQ+Hn54eZM2dCqVTi+vXryMoqHBAqJiYGEydOROfOnREUFAQAaNWqVYWxxcbGYvfu3Zg1axZsbGzw+PFjnD59WrjT+ezZMxQUFGDGjBkwNTXFvXv3sGHDBkydOhU7d+5U21ZiYiJsbGywZMkS/PXXX1i+fDn09PRw8eJFjB07Fk2aNMHKlSsRGhqKb775BhJJ4Xc9y5Ytw969ezF58mQ4Ojri119/xcqVK1GvXj28//77FR5DReemyHfffQdra2v85z//gUQiQYMGDfDFF1/g008/xZAhQzBjxgzk5+fj7NmzePToEVq0aFHhvgHg999/x927dzFz5kwAwOeff44JEyYgISEB+vr6AIBZs2bhf//7Hz788EO8/fbb+PrrrxESEoK1a9eiV69ewrYePHiAiIgITJkyBc2aNUPjxo2xcOFCLFmyBJGRkXj77bc1iqms7TVv3lyjnJZ3PW3duhWffvopxowZg3nz5iElJUUosGfNmlWp+IiIiIiIartKF9hZWVmIi4uDjY0NgMK5UkePHo1Lly6hadOmldrWqFGjEBAQAACwtLRE//79ceXKFezZswcA4OHhgaSkJCQkJGilwI6Pj8eDBw9w7NgxoaC2s7PDu+++q1ZgJycnIywsDL6+vsKyQYMGAQCaNm2Kpk2bQiKRwMnJqdIxqFQqrF+/Xii20tPTERsbC6VSCYlEgvj4ePz99984evQo2rRpAwBwcXGBl5cXtm/fjnnz5uHq1avIz89HeHi4UNx7eHgI+7Czs4O+vj6aNGlSqRiTk5Ph7u6OkSNHCst8fHyE301NTbF48WLh9YsXL2BlZYWAgACkpqZCKpWqbW/dunXCcZ4/fx5fffUVNm3aBE9PTwCAUqnE5MmT8ccff6Bdu3a4e/cu4uLisHjxYgwfPhwA4OrqimfPnmHt2rUYPny4UIiXpaJzUyQ/Px+bNm1CgwYNAAA5OTmIiYnB8OHD1Qai6927d8UnrpjMzEzExcWVuL7i4+MxYsQIXL9+Hd999x0WL16MESNGAAA8PT2Rnp5eosDOysrCpk2b4OjoqLYMAGxsbODg4FCp2ErbHoAKc1rW9ZSbm4s1a9ZgwoQJCAsLAwC4ublBT08Py5cvx/jx49G4ceNKxUhUF8nlcqhUqlKXF/8vvX7MgfiYA/ExB+JjDsSnUqmgo6OjUdtKF9gWFhZCcQ0Abdu2BQBkZGRUusB2c3MTfi8qSLp166bWRiqVIjU1tbJhlury5cuwsbFRK6atra3Rrl07tXZ2dnbYsmULdHV14ebmBmtra63sHygslouKTgBo06YN8vPzkZmZCXNzc/zyyy+wsbERimsAaNSoEVxdXXHhwgUAgEwmg66uLmbNmoVhw4bBxcUFRkZGrxybnZ0dNm/ejOjoaPTo0QP29vYlCtqDBw9i27ZtuHPnDvLy8oTlt2/fViuwXz7O1q1bQyKRqOW3KA/37t1Du3btcObMGQBA37598eLFC6Gdq6srNm3ahHv37lV4J1nTc9O1a1ehuAaA3377DXK5HEOGDCl3+xUp6/q6dOkSRowYIeTw3XffVXvfe++9h8jISOTl5QlxNWrUqEQx/CrK2p6mOX3Zb7/9hry8PLz77rsl8vXs2TPcvHkT77zzjtbiJ3pTpaamlvuh6fbt268vGCoVcyA+5kB8zIH4mANxFa9tylPpAtvY2FjttZ6eHoDC7teVVbzwKQq4tO1razCmBw8ewMzMrMRyMzMztfhXrVqFVatW4fPPP8fixYshlUoRFhaGvn37vnIMLx9f0XEX7T87OxtNmjQpNcabN28CKPzSYcOGDYiNjUVwcDAkEgnc3d2xcOFCNG/evMqxTZkyBRKJBAcOHEBMTAxMTU0xcuRITJs2DTo6Ojh+/Djmzp2L4cOHY8aMGWjUqBEePnyIadOmlch/aXmsX7++2oX58rXz+PFjqFSqEl+yFNGkwNb03Lx8HRQ9g21hYVHu9itS1vX18OFDAIV3kfX09NCoUSO1Nk2aNIFKpUJOTo5QYJd2HbyK0rZXmZy+7PHjxwCAwYMHl7r+3r17rx40UR0glUrLvIN9+/ZttG7dGgYGBiJERsyB+JgD8TEH4mMOxHfr1i2N21a6wC5PvXr1ABR2vy0uOztbm7upMgsLC/z+++8llmdmZqo9R21hYYHIyEgolUpcuXIF69evx4wZM5CQkICWLVtWa4wmJial3rHPzMyEiYmJ8NrT0xOenp7Izc3FqVOnEBkZifnz5wvPhVeFvr4+QkJCEBISgjt37mD//v2Ijo6GlZUVBg0ahISEBLRv316tC/X58+ervL+XmZiYQEdHB19++aVQfBdX3t3U4jQ5Ny938SgqeB88eFDpnhjFZWZmlrqsqJeEiYkJ8vPzkZWVpZbPf/75Bzo6OmpfOmnaDUVTpW3vVXJaFH9MTEyp58zKyqqKkRLVLRV9WDIwMFDrcUOvH3MgPuZAfMyB+JgD8VTmc7lWp+kyMzODnp4eUlJShGUKhQI///yzNndTZQ4ODrh58ybu3LkjLLtz5w6uX79eanuJRIKOHTviww8/xIsXL4T3afOu+sucnZ3xxx9/qI08nZWVhTNnzsDZ2blEe0NDQ/j6+sLPz0/tvOvp6VWpV0ERa2trhIWFoVGjRkIsz549K1H4Hj58uMr7eFn37t0BFN5NdnBwKPFTmcHkgLLPTWk6deoEAwMD7N+/v8rxAyjz+irqml2Uw5dH2k9ISICdnV2F/2i+So+R0mia09Kup6Jzdv/+/VLzxeeviYiIiKiu0eodbIlEgj59+mDXrl2wtrZG48aNERcXV6mHwquTv78/1q9fj0mTJiE0NBRA4SjixbvO5uTkYPz48Rg4cCCkUiny8/Oxc+dOGBsbw87ODkDhc9MvXrzA9u3b0alTJxgaGlZ6ROfyYty2bRsmTZqEDz/8UBhF/K233sKYMWMAALt378bFixfh4eEBc3NzpKWl4dChQ2rPtL/99ts4e/YsTp8+DWNjY1hZWVVY8EydOhUdOnSAnZ0dDAwMcOLECWRlZQldtl1dXbFkyRKsXbsWnTp1wsmTJ/HTTz9p5biBwjvUI0eOxJw5czB+/Hg4OjoiPz8ft2/fxrlz57Bu3boKt6HJuSmNkZERpk2bhpUrV0KlUqFXr15QKpU4d+4c/Pz8NB5QzMzMDJMnT8b06dMBAKtXr4alpSX8/f0BAO3atUPfvn2xfPlyPHv2DFKpFIcOHcJvv/2m0fG1bt0aurq62L9/P9566y3o6upWerCz4jTNaVnX0/Tp0/Hpp5/i/v37eOedd6Crq4u//voLiYmJiI6OZjcmIiIiIqpTtFpgA0B4eDjCw8MRERGBhg0bYvz48ZBKpUhMTNT2riqtfv362LJlCxYtWoTZs2fD0tISU6dORWJiojDvb7169WBra4udO3fi3r17qF+/Puzt7bF582aYmpoCALy8vBAQEICNGzciMzMTLi4uJaapqipDQ0Ps3LkTy5cvR3h4OJRKJTp37oy4uDg0a9YMQOFAXidOnEBkZCSePHkCc3Nz+Pn5CV8aAEBYWBgWLVqEkJAQPH36FJGRkUKRV5bOnTvj2LFj2Lp1KwoKCiCVSrFy5Uq4uroCAEaMGIG0tDTExcVh8+bNcHd3R1RUFIYNG6aVYweABQsWQCqVYs+ePVi7di0aNmwIqVRaYlCwsmhybsrywQcfwNTUFNu2bUN8fDwaNmyITp06lfpcdVk6dOiAvn374tNPP8XDhw/h6OiIxYsXqz17/umnn+Kzzz7Dpk2b8OTJE7z99ttYs2aN2lzxZTE1NcXChQvxxRdf4NChQ3jx4kWJucQrQ9OclnU9BQUFwdLSElu3bkVcXBzeeusttGrVCj179iy1mz8RERER0ZtMR1XayCpEVGmBgYFo0KABYmNjxQ6lVktOTgYAbD6eiZT0rApaE9VebVqY4POwnmWuz8vLw7Vr19C+fXs+cycS5kB8zIH4mAPxMQfiK/p8qknPUa0+g01ERERERERUV2m9i3h1Kj7X7st0dHRKneakiEQiKTGnszZVFJuurm617VsTKpUKBQUFZa6v7vOjLWKd54KCgnKvr7feEu9PqSbH9iqsLF99bneimozXOBER0ZunVn3y7tChQ5nrWrRogfT09DLXBwcHIyQkpDrCAlBxbElJSdW2b00cOHAA8+fPL3N9dZ8fbRHrPPfp06fc6+vGjRtaew6/ssaOHVvu1FqJiYm1csqsWSNLjppP9KZRKlWQSMQfBJSIiIi0o1YV2Pv27StznVwuL3fEYgsLi+oISVBebMUHuBKLl5dXuTFW9/nRFrHO8/r166ttarZXtXjxYjx9+rTM9bUlt8UpFIoK/6apesnlcqSmpkIqlTIP1YjFNRER0ZulVhXYrzIdUXWrybEBQOPGjd+IeYnFOs8ymUyU/WpCW1PE1TQcf1FcKpUKcrmceSAiIiKqhJr/0C0R1Uk6OryzJyYdHR0YGBgwD0RERESVUKvuYBNR3aCvr89uySIzMDCAnZ2d2GG80fj8NRER0ZuHBTYR1Ugrd11AWkaO2GEQVQsrSyMO5EdERPQGYoFNRDVSWkYOUtKzxA6DiIiIiEhjfAb7FU2dOhWBgYEatz937hw2bNhQ6f14e3tjyZIllX5fVWzbtg0nT558LfuqTi/nJjo6Gp06dVJr8/vvv2PYsGFwdHSETCZDdnY2FAoF5s+fj27dukEmk2Hbtm0V7utNz09Vr1siIiIiorqEBfZrdv78ecTGxoodRrl27NjxRhTYLxs6dCi2b9+utiwiIgIFBQWIjY3Fnj170LBhQ3z99df4+uuv8e9//xt79uyBn5+fSBGXToz81IbrloiIiIhIbOwiTqJ59uwZ6tev/9r217RpUzRt2lRt2Z9//omAgAB069ZNbZmFhQUGDBjw2mITw+s+/0REREREb7rXdgd73rx56NevH86dO4dBgwbByckJQ4YMwZUrVwAAaWlpkMlkSEhIUHvfsmXL4O3tLbyOj4+HTCZDcnIygoKC4OjoCB8fH5w5cwZKpRKrVq2Cq6srXF1dERUVBaVSqbVjSElJwahRo+Dg4IDevXvjwIEDJdrcv38foaGhcHV1hYODA7y9vfHxxx8DKOyiHBMTg7y8PMhkMshkskp1LweAXbt2wcvLC87Ozpg6dSoePXqktj49PR3Tp0+Hs7MznJycMH78eNy4cUOtTWJiIvz9/dGpUyd06dIF/v7+wh1Rb29vpKenY9euXUKM8fHxFcaVn5+PFStWoGfPnrC3t4e7uzsmT56MnJzCQarOnTsHmUyGH374AdOnT0fnzp0RGhoqXBcvO3HiBGQyGf7880+NzosmuSneRbwonidPnmDdunVCLry9vbFlyxbcu3dPOP60tDSNYgBqbn7KOv8AcPDgQbz//vt455134OLigsDAQFy+fFntvJV33aakpGDKlCnCMU2cOBF3797V+JwREREREb0pXusd7IcPHyIiIgITJ06EkZERoqKiEBwcjOPHj1d6W3PnzsWIESMwbtw4bNy4EcHBwRg8eDByc3OxYsUKXLp0CdHR0bC1tUX//v1fOfbnz58jKCgIBgYG+OSTTwAAa9asQW5uLlq3bi20mzNnDh48eIAFCxbAzMwM9+7dE75EGDp0KO7fv48jR44IXZUNDQ01jiEpKQl37tzBwoUL8fjxY0RGRmLp0qVYtWoVACA3NxeBgYGQSCRYvHgx6tWrh/Xr12PUqFE4dOgQmjVrhrt37yI0NBR+fn6YOXMmlEolrl+/jqyswsGkYmJiMHHiRHTu3BlBQUEAgFatWlUYW2xsLHbv3o1Zs2bBxsYGjx8/xunTp6FQKNTahYeHY8CAAVi7di0kEgkUCgUOHDiAP/74A7a2tkK7I0eOoEOHDnj77bcr3LemuSmuQ4cO2LNnD8aNGwdfX18MHToUhoaGUCgU2LRpE37++WfExMQAACwsLCqMAajZ+Sny8vkHCr/cGjRoEFq1agWFQoGjR49i5MiROHToEKRSabnX7V9//YURI0bAxsYGy5cvh46ODjZs2ICxY8ciISEB+vr6GsdGRERERFTbvdYCOysrC3FxcbCxsQFQOM/q6NGjcenSpRJddysyatQoBAQEAAAsLS3Rv39/XLlyBXv27AEAeHh4ICkpCQkJCVopsOPj4/HgwQMcO3ZMKNrs7Ozw7rvvqhVxycnJCAsLg6+vr7Bs0KBBAP6vi7JEIoGTk1OlY1CpVFi/fr1QtKSnpyM2NhZKpRISiQTx8fH4+++/cfToUbRp0wYA4OLiAi8vL2zfvh3z5s3D1atXkZ+fj/DwcKFI8vDwEPZhZ2cHfX19NGnSpFIxJicnw93dHSNHjhSW+fj4lGjn7e2N2bNnC69fvHgBU1NTHD16VCiw5XI5kpKSEBwcrNG+Nc1NcYaGhnBycoKuri6aNm2qdqxNmjSBvr5+pXNUk/NT5OXzD0DtPCuVyv/H3v3H1Xz//+O/dVKJfqcfaKuDOqToh5jKjzLLq5gfX/PyQlgNkxKNYW+M4RUbQllifiQ2Xqz8nF6zMl4vhs38athIZTVhoR/r0I9zvn/06fly9OtEx7Mft+vlsovO8/l4Pp/35/N+Wud+no/H4wkvLy9cuXIFSUlJiIiIqPV9GxMTA2NjY2zfvh16enoAADc3NwwaNAj79u1TeT8QUVVyuRxKpbLGdc/+S68ecyA+5kB8zIH4mAPxKZVKaGlpqdX2lRbYlpaWQnENAF26dAEA3Lt3r94FtpeXl/BzZRH17DhaAJBKpcjIyHjBaFVduXIF9vb2KgWbra0tunbtqtLO0dER27Ztg7a2Nry8vGBra9sgxwcqirFn7wh27twZpaWlyMvLg4WFBX766SfY29sLxRsAmJiYwNPTExcuXAAAyGQyaGtrY86cORgzZgw8PDxgaGj40rE5Ojpi69atiI6OxoABA+Dk5CTcIX3WwIEDVV63atUKQ4YMwTfffIPZs2cDqOgeLpfL1Z5cTN3caFpjzk+l568/UNHFe+3atbh48SLy8vKE5ZmZmXXu7/Tp0/D394e2tjbKysoAAEZGRnB0dBR6bhBRzTIyMur8wKTO7yJpFnMgPuZAfMyB+JgDcanbM/OVFthGRkYqr3V0dABUdPGtr2eLjsqTrW7/z3dRflH379+Hubl5leXm5uYq8UdFRSEqKgrr1q3D0qVLIZVKERERgbfeeuulY3j+/CrPu/L4BQUFaNeuXbUx3rx5E0DFlw6bNm1CXFwcQkNDIZFI4O3tjcWLF6NDhw4vHNv06dMhkUiQlJSEmJgYmJmZYfz48ZgxY4bKtz3VXcOAgAB8+eWXuHLlCnr06IGjR4+iV69ean/pom5uNK0x5+fZYz2rqKgIQUFBMDMzw/z589GhQwfo6elh4cKFal27R48eIT4+vsrs7MD/fr+JqGZSqbTWO9iZmZmws7ODvr7+K46MAOagMWAOxMcciI85EN+tW7fUbttoZhGv7F5aWlqqsrygoECMcKqwtLTEL7/8UmV5Xl6eyjhqS0tLREZGQqFQIC0tDbGxsZg9ezaSk5Px2muvaTRGY2Pjau/Y5+XlwdjYWHjdv39/9O/fH0VFRTh16hQiIyOxYMGCaoskdenq6iIsLAxhYWHIysrC119/jejoaNjY2Ahd5AFU27XC3d0d7du3x9GjRyGVSnHq1Cl89NFHah9b3dyITcz8VHr++l+6dAm5ubmIi4tTueNfWFio1hccxsbGGDBggDBc41lt27Z96XiJmjt1Pijp6+ujTZs2ryAaqglzID7mQHzMgfiYA/Go2z0caETPwTY3N4eOjg7S09OFZSUlJfjxxx9FjOp/nJ2dcfPmTWRlZQnLsrKycOPGjWrbSyQS9OjRA7NmzUJZWZmwXUPeVX+eu7s7fvvtN5WZt/Pz83HmzBm4u7tXaW9gYAB/f38EBASoXHcdHZ2XuvNra2uLiIgImJiYqDULuJaWFvz9/XHs2DH8+9//hkKhqHb8dk3qmxuxNJb8POvJkyfCPiv9/PPPyMnJUWlX0/u2b9++uHnzJhwdHeHs7KzynzoT1BERERERNSeN5g62RCLB4MGDsXv3btja2sLU1BS7du2q14ByTRo1ahRiY2Mxbdo04fFGGzZsUOnyW1hYiODgYAwfPhxSqRSlpaVISEgQxqQCFeNyy8rKEB8fD1dXVxgYGDRYITJq1Cjs2LED06ZNw6xZs4RZqlu1aoVJkyYBAPbs2YNLly6hX79+sLCwQHZ2Ng4dOqQypr1Tp044e/YsTp8+DSMjI9jY2MDU1LTWY4eEhKB79+5wdHSEvr4+Tpw4gfz8/Crj4msydOhQbN26FevXr4eXlxfMzMzqdd515aYxEDM/NXFxcUGbNm2wdOlSTJ06Fffu3UN0dDSsrKxU2tX0vp05cyZGjx6N4OBgjBkzBu3atcOff/6J8+fPo1evXtU+go2IiIiIqLlqNAU2UPEIoUWLFmH58uVo27YtgoODIZVKkZKSInZoaN26NbZt24YlS5Zg7ty5sLKyQkhICFJSUoRnPevp6cHBwQEJCQm4e/cuWrduDScnJ2zdulUoGH18fDBu3Dhs3rwZeXl58PDwQEJCQoPEaGBggISEBKxcuRKLFi2CQqGAm5sbdu3ahfbt2wOomETrxIkTiIyMxOPHj2FhYYGAgAChMAWAiIgILFmyBGFhYfjrr78QGRmJUaNG1XpsNzc3HDt2DNu3b0d5eTmkUilWr14NT09PtWJ3dHQUJqWbM2dOvc5bndw0BmLmpybt2rXD+vXr8emnnyIkJAR2dnZYunQpvvjiC5V2Nb1vbW1tsW/fPmHOgeLiYlhYWMDDwwMymezFLxYRERERUROkpaxpdhUiIhFcvXoVALD1eB7Sc/JFjoZIMzp3NMa6iIG1tikuLsb169fRrVs3jrkTCXMgPuZAfMyB+JgD8VV+PnV2dq6zbaMZg01ERERERETUlDWqLuKaVPmM3upoaWnV+JgUoGJ8eHXPdG4odcWmra2tsWOrQ6lUory8vMb1mrw+Yh67EvMjDhurhnv+N1Fjw/c3ERFR89RiCuzu3bvXuK5jx45VZk1+VmhoKMLCwjQRFoC6Y0tNTdXYsdWRlJSEBQsW1Lhek9dHzGNXYn7EMWd81ZnViZoThUIJiUT8STyJiIio4bSYAnv//v01rpPL5bU+i9TS0lITIQlqi01XV1ejx1aHj49PrTFq8vqIeexKzM+rV1JSUufvJWmWXC5HRkYGpFIp86AhLK6JiIianxZTYKszIF0sjTk2ADA1NX3hx0A15WNXYn7EwfkXxaVUKiGXy5kHIiIionpoegMziYiIiIiIiBohFthE1ChpabH7rJi0tLSgr6/PPBARERHVQ4vpIk5ETYeuri7H/YpMX18fjo6OYofxSnHSMSIiInpZLLCJqFFavfsCsu8Vih0GtRA2VoacuZ6IiIheGgtsImqUsu8VIj0nX+wwiIiIiIjUxjHYRPWUmJiIw4cPN/h+Dx8+jLfeegvdu3fH8OHDkZ2dDZlMhuTk5AY/ljru3r2LBQsWwNfXF87OzvD29sbkyZNx8OBBlXaFhYX46KOP0Lt3b7i6umLmzJm4f/++KDETEREREYmJd7CJ6ikpKQlt2rTBsGHDGmyff/31Fz766CMMHToUkZGRMDAwaLB9v4iCggKMGTMGxsbGCAsLQ4cOHZCbm4uzZ8/iP//5D4YPHy60nTVrFm7duoUlS5ZAT08P69atw5QpU/D111+jVSv+L4aIiIiIWg5++iVqBHJyclBSUoK3334b7u4V40Czs7NFi+ff//437t+/j71796JDhw7C8uHDh0OhUAivL168iP/+97/YunUrvL29AQBSqRT+/v749ttv4e/v/8pjJyIiIiISC7uIU4tz8eJFBAUFwc3NDa6urnjnnXdw+vRpAMDq1asxbNgwuLq6ol+/foiIiFDp7hwYGIjz58/j+++/h0wmg0wmQ3R09EvFEx0dLdwNnzx5cq37PHDgAP7xj3+gd+/e8PDwQGBgIK5cuVKl3fHjx+Hn5wdnZ2eMGTMGv/zyC3r16qV2rPn5+ZBIJDA3N6+yTiL53/82Tp06BSMjI3h5eQnLOnXqhG7duuHUqVNqHYuIiIiIqLngHWxqUS5cuIBJkybBxcUFy5cvh5GREdLS0vDHH38AAPLy8jBt2jRYWlri4cOH2L59OwIDA3H06FG0atUKH3/8MebOnYvWrVtj3rx5AABra+uXiumdd97Ba6+9hnnz5mHx4sXo3r07rK2tUVZWVqVtdnY2RowYgddffx0lJSU4evQoxo8fj0OHDkEqlQIArl27hvDwcPj4+OCjjz5CTk4OZs+ejZKSErVj6t69OxQKBebMmYOgoCA4OztX29379u3bkEqlVZ6V3KlTJ9y+fbueV4KIiIiIqGljgU0tymeffQZbW1vEx8dDW1sbAISuzQAQGRkp/FxeXg5XV1f0798fZ8+ehbe3N7p06QIDAwO0adMGLi4uDRKTtbU1ZDIZAKBLly7CfqvrIh4aGir8rFAo4OXlhStXriApKQkREREAgLi4ONjY2CA6Olq429y2bVt8+OGHasfUt29fBAcHY/v27fj222/RunVruLu74+2338bw4cOFgrqgoACGhoZVtjc2NkZaWpraxyNqLORyOZRKpdhhAKiI5dl/6dVjDsTHHIiPORAfcyA+pVJZ5YZSTVhgU4shl8tx+fJlRERECMX1806ePInY2FjcvHkTRUVFwvLMzEyVQlws6enpWLt2LS5evIi8vDxheWZmpvDz1atX8eabb6p05R40aFC9j/Xhhx/iH//4B1JSUnDhwgX88MMPOH36NE6fPo3PPvvspc6DqLHKyMhodB9gnv39JnEwB+JjDsTHHIiPORCXrq6uWu1YYFOLUVBQAIVCAUtLy2rXX7lyBSEhIRg0aBCmTJkCc3NzaGlpYcyYMXj69OkrjraqoqIiBAUFwczMDPPnz0eHDh2gp6eHhQsXqsT34MEDmJmZqWxrYGAAPT29eh/ztddew+TJkzF58mT89ddfCA8Px6FDhxAcHIyuXbvCyMgIubm5VbbLz8+HsbFx/U+SSGRSqbRR3cHOzMyEnZ0d9PX1xQ6nRWIOxMcciI85EB9zIL5bt26p3ZYFNrUYhoaGkEgkNT6j+bvvvoOBgQHWrVsn3P3Nycl5lSHW6tKlS8jNzUVcXBy6du0qLC8sLFQZB25hYYGHDx+qbFtUVPTSXxK0bdsW48aNw3/+8x/cvn0bXbt2RadOnfDDDz9U6TaTkZEBBweHlzoekRga4wcXfX19tGnTRuwwWjTmQHzMgfiYA/ExB+JRt3s4wFnEqQWpHDd98OBBlJeXV1n/5MkT6OjoqPwCHT58uEo7HR0dUe5oP3nyRDh+pZ9//rnKlwDOzs74/vvvVR6n9d1339XrWA8fPqz2Ll5l16R27doBAPr374/8/Hz88MMPQpuMjAxcu3YN/fv3r9cxiYiIiIiaOt7Bphblgw8+ELo8jxs3DsbGxvjll19gamoKLy8vxMfHY9myZRg8eDAuXryIgwcPVtlHp06dcODAAaSmpsLCwgKWlpawsrLSeOwuLi5o06YNli5diqlTp+LevXuIjo6ucuxp06Zh9OjRCAsLw5gxY/DHH39g27Zt0NPTU/vbt6SkJBw8eBDDhw+Ho6MjFAoFLl68iC1btqB79+7Cs7pdXV3h7e2Njz76CPPmzYOenh6ioqIgk8nw1ltvNfg1ICIiIiJqzHgHm1qUXr16YefOndDS0sKCBQsQGhqK7777Dh07dsSAAQMwZ84cpKSkYPr06fjpp58QFxdXZR9TpkyBm5sb5s2bh9GjR+Nf//rXK4m9Xbt2WL9+PR4+fIiQkBDEx8dj6dKlsLW1VWnn6OiIdevW4datWwgNDcW+ffuwcuVKlJeXVzvjd3UGDBgADw8PHDhwAKGhoQgNDcWxY8cQFBSEHTt2qEwSt27dOnh6emLx4sX44IMPYGdnh82bN1f7WC8iIiIiouZMS9lYZnMhIo354YcfMHnyZCQkJKB3795ih1Orq1evAgC2Hs9Dek6+yNFQS9G5ozHWRQwUOwwVxcXFuH79Orp168YxdyJhDsTHHIiPORAfcyC+ys+nzs7OdbblLSaiZmjJkiXo27cvTExMcOvWLXz++edwdHREr169xA6NiIiIiKjZYoFN9JKUSmW1k6ZVkkgkKhOOPU9bW7teMxOqo6CgAMuWLcPjx49hYGCAfv36Yd68eZBIJGrF++wztMViY6Ved3aihsD3GxERETUEFthEL+n8+fOYOHFijetHjhyJpKSkGtfv3LkTffr0adCY1q5dW+M6deJduXJlg8bzIuaMdxc7BGphFAolJJKG/bKLiIiIWhYW2EQvqXv37ti/f3+N601NTTF+/Pga10ulUk2EVSN14hVbSUkJ5HJ5o3wmcUshl8uRkZEBqVTaYvLA4pqIiIheFgtsopdkYGBQ54QHNjY2ryiauqkTb2PA+RfFpVQqIZfLmQciIiKiehB/oCURUTUaelw61Y+Wlhb09fWZByIiIqJ64B1sImp0dHV1W0y35MZKX18fjo6OYofxynD8NRERETUEFthE1Cit3n0B2fcKxQ6DWgAbK0NOqkdEREQNggU2ETVK2fcKkZ6TL3YYRERERERq4xjsRi4kJASBgYFqtz937hw2bdpU7+P4+vrik08+qfd2L2LHjh04efLkKzkWNYyCggJER0fj1q1bYodCRERERNRoscBuZs6fP4+4uDixw6jVzp07WWA3MQUFBYiJiWGBTURERERUCxbYRI1YSUkJFApFk9s3EREREVFL1GwK7Pnz52Po0KE4d+4cRowYARcXF4wePRppaWkAgOzsbMhkMiQnJ6tst2LFCvj6+gqvExMTIZPJcPXqVQQFBaFnz57w8/PDmTNnoFAoEBUVBU9PT3h6emLNmjUNWqCkp6djwoQJcHZ2xptvvomkpKQqbXJzcxEeHg5PT084OzvD19cX//znPwEA0dHRiImJQXFxMWQyGWQyWb26lwPA7t274ePjA3d3d4SEhODhw4cq63NycjBz5ky4u7vDxcUFwcHB+PXXX1XapKSkYNSoUXB1dUWvXr0watQo4Y61r68vcnJysHv3biHGxMTEOuMqLS3FqlWrMHDgQDg5OcHb2xvvv/8+CgsrJsEqLi7GJ598Aj8/P/Ts2RO+vr5YvHixsL5SZVf4HTt2YMCAAXB1dcX8+fNRUlKC69evY+zYscJ75/nzUiqV2Lp1K/z8/ODk5IRBgwZhx44d9bq+tV2bZ+PbsmULfHx80KNHD3z77bfCe/JZ5eXl8PLywpo1a9Q6dnX7fvz4MdLT0zF79mwMGDAAPXv2hL+/P7Zt2ya8t7OzszFo0CAAQHh4uJC37OxsABWF+tq1a+Hj4wMnJyf87W9/w+HDh+t1XYiIiIiImoNmNcnZgwcPsHz5ckydOhWGhoZYs2YNQkNDcfz48Xrva968eRg7dizeffddbN68GaGhoRg5ciSKioqwatUqXL58GdHR0XBwcMCwYcNeOvanT58iKCgI+vr6+PTTTwEAGzZsQFFREezs7IR2H374Ie7fv4+FCxfC3Nwcd+/eFb5EeOedd5Cbm4sjR44gPj4eAGBgYKB2DKmpqcjKysLixYvx6NEjREZGYtmyZYiKigIAFBUVITAwEBKJBEuXLoWenh5iY2MxYcIEHDp0CO3bt8edO3cQHh6OgIAAfPDBB1AoFLhx4wby8ysmq4qJicHUqVPh5uaGoKAgAMDrr79eZ2xxcXHYs2cP5syZA3t7ezx69AinT59GSUkJAODJkycoLy/H7NmzYWZmhrt372LTpk0ICQlBQkKCyr5SUlJgb2+PTz75BL///jtWrlwJHR0dXLp0CZMnT0a7du2wevVqhIeH45tvvoFEUvE91IoVK7Bv3z68//776NmzJ37++WesXr0aenp6+Mc//lHnOdR1bSp9++23sLW1xf/93/9BIpHgjTfegKWlJb755hs4OzsL7c6ePYs///wTQ4cOrfPYNe27TZs2+PXXXyGVSjFs2DC0bdsW169fR3R0NIqLixEaGgpLS0vExMQgNDQUERER6NOnDwDA0tISQEXR/fPPP2PGjBno3LkzTp48iblz58LIyAgDBgxQOzYiIiIioqauWRXY+fn52LVrF+zt7QFUPMd14sSJuHz5Mqytreu1rwkTJmDcuHEAACsrKwwbNgxpaWnYu3cvAKBfv35ITU1FcnJygxTYiYmJuH//Po4dOyYU1I6OjhgyZIhKgX316lVERETA399fWDZixAgAgLW1NaytrSGRSODi4lLvGJRKJWJjY6Grqwug4m51XFwcFAoFJBIJEhMT8ccff+Do0aPo3LkzAMDDwwM+Pj6Ij4/H/Pnzce3aNZSWlmLRokVCcd+vXz/hGI6OjtDV1UW7du3qFePVq1fh7e2N8ePHC8v8/PyEn83MzLB06VLhdVlZGWxsbDBu3DhkZGRAKpWq7O/zzz8XzvP8+fP417/+hS1btqB///4AAIVCgffffx+//fYbunbtijt37mDXrl1YunQp/v73vwMAPD098eTJE2zcuBF///vfhUK8JnVdm0qlpaXYsmUL2rRpIyzz9/fHN998gw8//BBaWhXP6j1y5Ajs7e0hk8nqvoC17Ltv377o27cvgIr3gLu7O548eYJdu3YhNDQUurq66NatGwDA1tZWJW9nz55Famoqtm7dCm9vbwCAl5cXHjx4gOjoaBbY1KTI5XIolUqxwxDI5XKVf+nVYw7ExxyIjzkQH3MgPqVSKXwGr0uzKrAtLS2F4hoAunTpAgC4d+9evQtsLy8v4efKAveNN95QaSOVSpGRkfGC0aq6cuUK7O3tVYppW1tbdO3aVaWdo6Mjtm3bBm1tbXh5ecHW1rZBjg9UFMuVRScAdO7cGaWlpcjLy4OFhQV++ukn2NvbC8U1AJiYmMDT0xMXLlwAAMhkMmhra2POnDkYM2YMPDw8YGho+NKxOTo6YuvWrULR5uTkVKWgPXDgAHbs2IGsrCwUFxcLyzMzM1UK7OfP087OTrhT/OwyALh79y66du2KM2fOAADeeustlJWVCe08PT2xZcsW3L17Fx07dqz1HNS9Nn369FEpgAEgICAAO3bswIULF9CrVy+UlJTgu+++E3oBqKu6fT99+hRxcXE4fPgw7t69i9LSUmHdX3/9hbZt29a4v9OnT8PExARvvPFGleuyZMkSlJeXQ1tbu14xEoklIyOjUX54yczMFDuEFo85EB9zID7mQHzMgbierR9q06wKbCMjI5XXOjo6ACoKiPp6tvCpvJjV7b+yi/LLun//PszNzassNzc3V4k/KioKUVFRWLduHZYuXQqpVIqIiAi89dZbLx3D8+dXed6Vxy8oKEC7du2qjfHmzZsAKr502LRpE+Li4hAaGgqJRAJvb28sXrwYHTp0eOHYpk+fDolEgqSkJMTExMDMzAzjx4/HjBkzoKWlhePHj2PevHn4+9//jtmzZ8PExAQPHjzAjBkzquS/ujy2bt1a5Zfm+ffOo0ePoFQqq3zJUkmdAlvda1Pd+6BHjx54/fXXceTIEfTq1QunTp1CQUFBvbqH17Tvzz77DPv27cOMGTPg5OQEQ0NDpKSkIDY2Fk+fPq21wH706BEeP36M7t27V7v+wYMH9f5yi0gsUqm00d3BzszMhJ2dHfT19cUOp0ViDsTHHIiPORAfcyC++jxJp1kV2LXR09MDAJW7c0BF0dgYWFpa4pdffqmyPC8vT2UctaWlJSIjI6FQKJCWlobY2FjMnj0bycnJeO211zQao7GxcbV37PPy8mBsbCy87t+/P/r374+ioiKcOnUKkZGRWLBggTAu/EXo6uoiLCwMYWFhyMrKwtdff43o6GjY2NhgxIgRSE5ORrdu3VSe5X3+/PkXPt7zjI2NoaWlhS+//FIovp/1fBf0mqhzbWrqfhIQEIC9e/di4cKF+Oabb9CzZ89657y6fScnJ+Pvf/87pk6dKixT9zFqxsbGMDMzw+bNm6tdb2ZmVq/4iMTUWD+06OvrV+l5Qq8WcyA+5kB8zIH4mAPxqNs9HGhGs4jXxdzcHDo6OkhPTxeWlZSU4McffxQxqv9xdnbGzZs3kZWVJSzLysrCjRs3qm0vkUjQo0cPzJo1C2VlZcJ2DXlX/Xnu7u747bffcPv2bWFZfn4+zpw5A3d39yrtDQwM4O/vj4CAAJXrrqOj80K9CirZ2toiIiICJiYmQixPnjypUvg25EzWlWOUHz9+DGdn5yr/1WcyOaDma1OboUOH4uHDh0hNTUVqaioCAgLqfR7Vefr0qcq1Ky8vx9GjR1Xa1NQbxNPTEw8fPoSOjk6110XdrjRERERERM1Bi7mDLZFIMHjwYOzevRu2trYwNTXFrl276jVgXZNGjRqF2NhYTJs2DeHh4QAqZhF/tkt2YWEhgoODMXz4cEilUpSWliIhIQFGRkZwdHQEUDFuuqysDPHx8XB1dYWBgQE6derUYDHu2LED06ZNw6xZs4RZxFu1aoVJkyYBAPbs2YNLly6hX79+sLCwQHZ2Ng4dOqQypr1Tp044e/YsTp8+DSMjI9jY2MDU1LTWY4eEhKB79+5wdHSEvr4+Tpw4gfz8fKHLtqenJz755BNs3LgRrq6uOHnyJH744YcGOW+g4g71+PHj8eGHHyI4OBg9e/ZEaWkpMjMzce7cOXz++ed17kOda1ObLl26QCaTYdmyZXj69KnKRHcvw9PTE/v27UOXLl1gamqKL7/8ssqXNBYWFjAyMsLRo0dhY2MDXV1dyGQyeHl5wcfHB++99x7ee+89yGQyyOVy3Lp1C1lZWVixYkWDxEhERERE1BS0mAIbABYtWoRFixZh+fLlaNu2LYKDgyGVSpGSkiJ2aGjdujW2bduGJUuWYO7cubCyskJISAhSUlKEZznr6enBwcEBCQkJuHv3Llq3bg0nJyds3bpV6Irr4+ODcePGYfPmzcjLy4OHh0eVx1S9KAMDAyQkJGDlypVYtGgRFAoF3NzcsGvXLrRv3x5AxUReJ06cQGRkJB4/fgwLCwsEBAQIXxoAQEREBJYsWYKwsDD89ddfiIyMxKhRo2o9tpubG44dO4bt27ejvLwcUqkUq1evhqenJwBg7NixyM7Oxq5du4QZrdesWYMxY8Y0yLkDwMKFCyGVSrF3715s3LgRbdu2hVQqxZAhQ9TaXp1rU5ehQ4dizZo16Nu3LywsLF70VFQsWrQIH3/8MZYtWwZ9fX2MHDkSgwcPxsKFC4U2EokEkZGRWLt2LSZPnoySkhKkpKTAxsYGGzZswObNm/HVV18hJycHhoaGsLe3rzOnRERERETNjZayMc3oQkQt3tWrVwEAW4/nIT0nv47WRC+vc0djrIsYKHYYVRQXF+P69evo1q0bx9yJhDkQH3MgPuZAfMyB+Co/nzo7O9fZtsWMwSYiIiIiIiLSpBbVRVyTnn0G8PO0tLRqffSLRCKp8kznhlRXbGI/p1ipVKK8vLzG9Zq+Pg1FzOvc2HP8ImysXv756UTq4HuNiIiIGgoL7AZS03OAAaBjx47IycmpcX1oaCjCwsI0ERaAumNLTU3V2LHVkZSUhAULFtS4XtPXp6GIeZ0be45fxJzxVWemJ9IUhUIJiUT8CS+JiIioaWOB3UD2799f4zq5XF7r81UtLS01EZKgttgaw2OUfHx8ao1R09enoYh5nRt7juurpKSkzt8b0iy5XI6MjAxIpdIWkQcW10RERNQQWGA3EHUGvIulMccGAKampnU+pqspEPM6N/YcvwjOvygupVIJuVzOPBARERHVQ+Mf2EpERERERETUBLDAJqJGSUuLXXbFpKWlBX19feaBiIiIqB7YRZyIGh1dXd0WMe63MdPX14ejo6PYYTQ4TmZGREREmsQCm4gapdW7LyD7XqHYYVAzYmNlyNnpiYiISKNYYBNRo5R9rxDpOflih0FEREREpDaOwSbSgJCQEAQGBqrd/ty5c9i0aVO9j+Pr64tPPvmk3ts9r6CgANHR0bh169ZL74uIiIiIqKVigU3UCJw/fx5xcXGiHb+goAAxMTEssImIiIiIXgILbCIiIiIiIqIGwAKbRDV//nwMHToU586dw4gRI+Di4oLRo0cjLS0NAJCdnQ2ZTIbk5GSV7VasWAFfX1/hdWJiImQyGa5evYqgoCD07NkTfn5+OHPmDBQKBaKiouDp6QlPT0+sWbMGCoWiwc4hPT0dEyZMgLOzM958800kJSVVaZObm4vw8HB4enrC2dkZvr6++Oc//wkAiI6ORkxMDIqLiyGTySCTyerVvRwAvvjiC/Tr1w89e/bE9OnTcf/+fWHdqFGj8MEHH1TZ5rPPPoO3tzfu3LmDQYMGAQDCw8OFGLKzswEAJSUlWLt2LXx8fODk5IS//e1vOHz4sMq+bt68iSlTpqBPnz7Ctd+yZUu9zoGIiIiIqKnjJGckugcPHmD58uWYOnUqDA0NsWbNGoSGhuL48eP13te8efMwduxYvPvuu9i8eTNCQ0MxcuRIFBUVYdWqVbh8+TKio6Ph4OCAYcOGvXTsT58+RVBQEPT19fHpp58CADZs2ICioiLY2dkJ7T788EPcv38fCxcuhLm5Oe7evSt8ifDOO+8gNzcXR44cQXx8PADAwMBA7RiOHz+Ojh07YsmSJSgoKMDq1asRFhaGvXv3CvtfuXIlCgsLYWhoCAAoLy/HwYMHMXLkSFhbWyMmJgahoaGIiIhAnz59AACWlpYAKorun3/+GTNmzEDnzp1x8uRJzJ07F0ZGRhgwYAAA4P3330e7du2wYsUKGBgY4M6dO8jNzX2JK0tERERE1PSwwCbR5efnY9euXbC3twdQ8fzdiRMn4vLly7C2tq7XviZMmIBx48YBAKysrDBs2DCkpaUJxWa/fv2QmpqK5OTkBimwExMTcf/+fRw7dkwoqB0dHTFkyBCVAvvq1auIiIiAv7+/sGzEiBEAAGtra1hbW0MikcDFxaXeMfz111/YsmWLUDxbW1tj8uTJ+M9//oN+/fph2LBhWLVqFQ4fPixcm5MnT+LBgwf4//6//w+6urro1q0bAMDW1lYlhrNnzyI1NRVbt26Ft7c3AMDLywsPHjxAdHQ0BgwYgIcPHyI7Oxv/93//J/QqeOONN+p9HkSvilwuh1KpFDuMOsnlcpV/6dVjDsTHHIiPORAfcyA+pVIJLS0ttdqywCbRWVpaCsU1AHTp0gUAcO/evXoX2F5eXsLPlQXu88WeVCpFRkbGC0ar6sqVK7C3t1cppm1tbdG1a1eVdo6Ojti2bRu0tbXh5eUFW1vbBjk+APTp00corgGgb9++MDExweXLl9GvXz8YGBjgb3/7G77++muhwE5MTESvXr1U4q7O6dOnYWJigjfeeANlZWXCck9PTyxZsgTl5eUwNTVFx44dsXbtWuTn56Nv3771zhvRq5SRkdGkPqRkZmaKHUKLxxyIjzkQH3MgPuZAXLq6umq1Y4FNojMyMlJ5raOjA6Ci+3V9PVtoVv4SVLf/kpKSeu+7Ovfv34e5uXmV5ebm5irxR0VFISoqCuvWrcPSpUshlUoRERGBt95666VjqO74ZmZmePDggfB6zJgxGDt2LG7cuAFLS0t8//33aj3e69GjR3j8+DG6d+9e7foHDx7A2toaW7duRVRUFD755BMUFxeje/fuWLBgATw8PF78xIg0RCqVNpk72JmZmbCzs4O+vr7Y4bRIzIH4mAPxMQfiYw7EV58n7bDApkZNT08PAFBaWqqyvKCgQIxwqrC0tMQvv/xSZXleXp7KOGpLS0tERkZCoVAgLS0NsbGxmD17NpKTk/Haa6+9VAx5eXlVlj18+BAWFhbCa1dXV9jb2+Prr79Ghw4doKuriyFDhtS5b2NjY5iZmWHz5s3VrjczMwNQUbBs2LABpaWluHjxItauXYv3338fp06dQtu2bV/wzIg0o6l9ONHX10ebNm3EDqNFYw7ExxyIjzkQH3MgHnW7hwOcRZwaOXNzc+jo6CA9PV1YVlJSgh9//FHEqP7H2dkZN2/eRFZWlrAsKysLN27cqLa9RCJBjx49MGvWLJSVlQnbvcxd9XPnzqGwsFB4/cMPP+Dx48fo2bOnSrt33nkHhw8fxv79++Hv76/yP+iaeg14enri4cOH0NHRgbOzc5X/nu8qo6Ojg969e2Pq1KkoKipSmc2ciIiIiKi54x1satQkEgkGDx6M3bt3w9bWFqampti1a1e9JhrQpFGjRiE2NhbTpk1DeHg4gIpZxNu1aye0KSwsRHBwMIYPHw6pVIrS0lIkJCTAyMgIjo6OAIDOnTujrKwM8fHxcHV1hYGBATp16qRWDG3btsWUKVMwZcoUFBYWYvXq1ejRowf69eun0m748OFYvXo1Hj16hBUrVqiss7CwgJGREY4ePQobGxvo6upCJpPBy8sLPj4+eO+99/Dee+9BJpNBLpfj1q1byMrKwooVK3Djxg2sWrUK/v7+eO2111BUVIS4uDh07NgRr7/++stcXiIiIiKiJoUFNjV6ixYtwqJFi7B8+XK0bdsWwcHBkEqlSElJETs0tG7dGtu2bcOSJUswd+5cWFlZISQkBCkpKcJdZT09PTg4OCAhIQF3795F69at4eTkhK1btwpdrH18fDBu3Dhs3rwZeXl58PDwQEJCgloxDB48GNbW1vj4449RUFAAT09PLF26tEo7ExMT9O7dG7m5uVVmK5dIJIiMjMTatWsxefJklJSUICUlBTY2NtiwYQM2b96Mr776Cjk5OTA0NIS9vT1GjRoFoKI4b9euHeLi4nDv3j0YGhqiV69e+Oyzz6Ctrf0SV5eIiIiIqGnRUjaFmV6I6KUVFRWhX79+CAsLQ1BQkNjh1Ojq1asAgK3H85Ceky9yNNScdO5ojHURA8UOQ23FxcW4fv06unXrxjF3ImEOxMcciI85EB9zIL7Kz6fOzs51tuUdbKJmrqioCOnp6fjyyy+hpaUl3HkmIiIiIqKGxQKbWrRnn+38PC0trVof5SORSCCRaG6ewLpiU7f79S+//IKJEyeiffv2WLVqFUxMTBooQs2ysTKsuxFRPfA9RURERJrGAptatJqe7wwAHTt2RE5OTo3rQ0NDERYWpomwANQdW2pqqlr76dOnD3799deGCuuVmTPeXewQqBlSKJSQSMSfIJGIiIiaJxbY1KLt37+/xnVyubzW5+VaWlpqIiRBbbE9/3is5qakpKTO60+aJZfLkZGRAalU2qzywOKaiIiINIkFNrVo6kxUIJbGHNurwPkXxaVUKiGXy5kHIiIionrQ3ABSIqKX0Biec96SaWlpQV9fn3kgIiIiqgfewSaiRkdXV7dZdUtuivT19eHo6Ch2GPXGMdZEREQkJhbYRNQord59Adn3CsUOg5oQGytDTo5HREREomKBTUSNUva9QqTn5IsdBhERERGR2jgGm4jqdO7cOWzatEnsMIiIiIiIGjUW2ERUp/PnzyMuLk7sMIiIiIiIGjUW2NRsPHnyROwQalVeXo7S0tIqy5VKJUpKSl54vy963o39ehERERERNTUssJup+fPnY+jQoTh37hxGjBgBFxcXjB49GmlpaQCA7OxsyGQyJCcnq2y3YsUK+Pr6Cq8TExMhk8lw9epVBAUFoWfPnvDz88OZM2egUCgQFRUFT09PeHp6Ys2aNVAoFA0Sf2lpKVatWoWBAwfCyckJ3t7eeP/991FYWDHp1blz5yCTyfD9999j5syZcHNzQ3h4uHDezztx4gRkMhlu37790scGgIKCAixZsgTe3t5wcnLCqFGj8N///ldlP4GBgZg2bRqSkpLg5+cHZ2dn3LhxQ4jx5MmTePvtt+Hs7IzU1FQAwLfffovhw4fD2dkZ3t7eiIyMxNOnT4V91nTedaltuwMHDuAf//gHevfuDQ8PDwQGBuLKlSvCttHR0YiJiUFxcTFkMhlkMhkCAwOF9enp6Zg+fTrc3d3h4uKCqVOn4s6dO3XGRERERETU3HCSs2bswYMHWL58OaZOnQpDQ0OsWbMGoaGhOH78eL33NW/ePIwdOxbvvvsuNm/ejNDQUIwcORJFRUVYtWoVLl++jOjoaDg4OGDYsGEvHXtcXBz27NmDOXPmwN7eHo8ePcLp06er3OldtGgR3n77bWzcuBESiQQlJSVISkrCb7/9BgcHB6HdkSNH0L17d3Tq1Omlj11SUoJ3330XeXl5mDVrFqysrHDo0CFMmzZN+EKiUlpaGnJychAeHg4jIyO0b98eAHD//n0sX74c06dPR/v27dGhQwekpKRg5syZCAgIwAcffIDbt28jKioKd+/exYYNG2o9b3VVt112djZGjBiB119/HSUlJTh69CjGjx+PQ4cOQSqV4p133kFubi6OHDmC+Ph4AICBgQEA4Pfff8fYsWNhb2+PlStXQktLC5s2bcLkyZORnJwMXV1dtWMjIiIiImrqWGA3Y/n5+di1axfs7e0BVDzXduLEibh8+TKsra3rta8JEyZg3LhxAAArKysMGzYMaWlp2Lt3LwCgX79+SE1NRXJycoMU2FevXoW3tzfGjx8vLPPz86vSztfXF3PnzhVel5WVwczMDEePHhUKbLlcjtTUVISGhjbIsQ8fPowbN27g4MGD6NKlC4CK88/KysLnn3+O9evXC23z8/Oxf/9+obB+dvmWLVvQs2dPYdmsWbPg4uKCNWvWAAD69+8PfX19LF68GL/++qtK4f78eauruu2evS4KhQJeXl64cuUKkpKSEBERAWtra1hbW0MikcDFxUVl25iYGBgbG2P79u3Q09MDALi5uWHQoEHYt2+fyjUkelXkcjmUSqXYYbw0uVyu8i+9esyB+JgD8TEH4mMOxKdUKqGlpaVWWxbYzZilpaVQXAMQisF79+7Vu8D28vISfrazswMAvPHGGyptpFIpMjIyXjBaVY6Ojti6dSuio6MxYMAAODk5VXunduDAgSqvW7VqhSFDhuCbb77B7NmzAVR0D5fL5QgICGiQY58+fRoODg6ws7NDWVmZsNzT0xOHDh1S2ZeDg0OV4hoATExMVIrrv/76C9evX8e8efNU2vn7+2Px4sW4cOGCSoH9/Hmrq7rt0tPTsXbtWly8eBF5eXnC8szMzDr3d/r0afj7+0NbW1u4FkZGRnB0dBSGIxC9ahkZGc3qQ4g6v4ukWcyB+JgD8TEH4mMOxKVuz0wW2M2YkZGRymsdHR0AUBnTqy5DQ0Ph58o3V3X7f5nJup41ffp0SCQSJCUlISYmBmZmZhg/fjxmzJih8u2Rubl5lW0DAgLw5Zdf4sqVK+jRoweOHj2KXr16qf2lQl3HfvToEa5du4bu3btX2VZbW1vldbt27ao9xvPLCwsLoVQqq5yPoaEhdHV1kZ+v+jzo6s5bHc9vV1RUhKCgIJiZmWH+/Pno0KED9PT0sHDhQrXeJ48ePUJ8fLzQdfxZle83oldNKpU2mzvYmZmZsLOzg76+vtjhtEjMgfiYA/ExB+JjDsR369YttduywG6hKrvzPj+rdUFBgRjhVKGrq4uwsDCEhYUhKysLX3/9NaKjo2FjY4MRI0YI7arrquHu7o727dvj6NGjkEqlOHXqFD766KMGO7axsTFkMhlWrFhR575q6kry/HJDQ0NoaWnh4cOHKssLCwtRUlICY2NjtfZb33guXbqE3NxcxMXFoWvXrirHVecLCWNjYwwYMEAYPvCstm3bvlCMRC+ruX340NfXR5s2bcQOo0VjDsTHHIiPORAfcyCe+nz2ZoHdQpmbm0NHRwfp6enCspKSEvz4448iRlU9W1tbREREYO/evWrNAq6lpQV/f38cOXIE9vb2UCgU1Y7fftFje3p64uTJk7C0tISVldUL7fd5bdu2Rbdu3ZCcnIzJkycLy48dOwag4ksDTah8VNezd5t//vln5OTkqAwvqKl3Qt++fXHz5k04OjpWuXtPRERERNTSsMBuoSQSCQYPHozdu3fD1tYWpqam2LVrV70G8GtSSEgIunfvDkdHR+jr6+PEiRPIz8+vMu67JkOHDsXWrVuxfv16eHl5wczMrMGOPWLECOzZswcTJ05EUFAQ7OzsUFhYiGvXrqG0tBQffPDBC51zaGgoZsyYgTlz5uDtt99GRkYGoqKi4OfnpzL+uiG5uLigTZs2WLp0KaZOnYp79+4hOjq6yhcHnTt3RllZGeLj4+Hq6goDAwN06tQJM2fOxOjRoxEcHIwxY8agXbt2+PPPP3H+/Hn06tWr2kemERERERE1VyywW7BFixZh0aJFWL58Odq2bYvg4GBIpVKkpKSIHRrc3Nxw7NgxbN++HeXl5ZBKpVi9ejU8PT3V2t7R0VGYdG3OnDkNemxdXV3s3LkT0dHR2LRpEx48eAATExM4OjpW21VaXYMGDcL69euxceNGhISEwMTEBGPGjHnhgl0d7dq1w/r16/Hpp58iJCQEdnZ2WLp0Kb744guVdj4+Phg3bhw2b96MvLw8eHh4ICEhAba2tti3bx/WrVuHpUuXori4GBYWFvDw8NDYlwJERERERI2VlrI5zARDRM3G1atXAQBbj+chPSe/jtZE/9O5ozHWRQwUO4wGU1xcjOvXr6Nbt24ccycS5kB8zIH4mAPxMQfiq/x86uzsXGfbqs89IiIiIiIiIqJ6Yxdx0ohnnw/9PC0trVofoSORSKp95nVDUCqVKC8vF+XYmtIczwkAbKwM625E9Ay+Z4iIiEhsLLBJI6p7RnSljh07Iicnp8b1oaGhCAsL00RYSEpKwoIFC0Q5tqY0x3MCgDnjNTNzOjVvCoUSEon4EzUSERFRy8QCmzRi//79Na6Ty+W1PqfW0tJSEyEBqJisq7bYNHlsTWmO51RSUlLn+4Q0Sy6XIyMjA1KptEnlgcU1ERERiYkFNmmEOhMAiMHU1BSmpqZih9GgmuM5Aah1GAFpnlKphFwuZx6IiIiI6qHpDcwkIiIiIiIiaoRYYBNRo6Slxa6+YtLS0oK+vj7zQERERFQP7CJORI2Orq5ukxr32xzp6+vD0dFR7DDqhROcERERkdhYYBNRo7R69wVk3ysUOwxqImysDDnzPBEREYmOBTYRNUrZ9wqRnpMvdhhERERERGrjGGxqtBITE3H48GGxw2hw8+fPx9ChQ1/5cQMDAzFt2rRa2xQUFCA6Ohq3bt1SazkREREREf0P72BTo5WUlIQ2bdpg2LBhYofSoEJCQlBcXCx2GNUqKChATEwM7O3t0aVLlzqXExERERHR/7DAJmoAT548QevWrdVq+/rrr2s4GiIiIiIiEgO7iJPGXLx4EUFBQXBzc4OrqyveeecdnD59GgCwevVqDBs2DK6urujXrx8iIiJw//59YdvAwECcP38e33//PWQyGWQyGaKjo186ptzcXISHh8PT0xPOzs7w9fXFP//5T5U26enpmD59Otzd3eHi4oKpU6fizp07Km1kMhk2b96Mzz77DF5eXujbty8SExPh6OiIP//8U6Xt48eP4eTkhD179gCovov4vXv38OGHH8LT0xM9evTAkCFDEB8fr9ImMTERw4YNg7OzM/r164eoqCiUl5fX+xokJyfDz88Prq6umDhxonBu2dnZGDRoEAAgPDxcuO61Lc/OzoZMJkNSUhI++ugjuLu7o3fv3oiMjERZWVm9YyMiIiIiasp4B5s04sKFC5g0aRJcXFywfPlyGBkZIS0tDX/88QcAIC8vD9OmTYOlpSUePnyI7du3IzAwEEePHkWrVq3w8ccfY+7cuWjdujXmzZsHALC2tn7puD788EPcv38fCxcuhLm5Oe7evYu0tDRh/e+//46xY8fC3t4eK1euhJaWFjZt2oTJkycjOTkZurq6QtudO3eiZ8+eWLFiBcrKytCnTx98/PHHSE5OxoQJE4R23377LQBgyJAh1cb06NEj/P3vfwcAzJ49GzY2NsjKylIp6rdv347PPvsMkyZNwvz585Geni4U2HPmzFH7/K9fv46HDx9izpw5KC8vx8qVKzF37lzs3bsXlpaWiImJQWhoKCIiItCnTx8AqHV55Zcia9euhbe3N9atW4dr165hw4YN0NHRqVdsRERERERNHQts0ojPPvsMtra2iI+Ph7a2NgDA29tbWB8ZGSn8XF5eDldXV/Tv3x9nz56Ft7c3unTpAgMDA7Rp0wYuLi4NFtfVq1cREREBf39/YdmIESOEn2NiYmBsbIzt27dDT08PAODm5oZBgwZh3759GD9+vNDW2NgYMTEx0NL633N3BwwYgCNHjqgU2EeOHIGXlxdMTEyqjWnHjh3Iy8vDsWPHYGNjAwDo27evsL6oqAgbNmzAe++9h4iICACAl5cXdHR0sHLlSgQHB8PU1FSt8y8sLMSBAwdgZmYGACguLsaCBQuQm5sLa2trdOvWDQBga2urct1rWl7p9ddfF3Lar18/PHnyBNu3b8eUKVNgbGysVmxEDUEul0OpVIodRoOQy+Uq/9KrxxyIjzkQH3MgPuZAfEqlUuUzf21YYFODk8vluHz5MiIiIoTi+nknT55EbGwsbt68iaKiImF5ZmamSiHe0BwdHbFt2zZoa2vDy8sLtra2KutPnz4Nf39/aGtrC12cjYyM4OjoqHKnGwD69+9f5RctICAAs2fPxh9//IEOHTrg/v37+PHHH7Fq1aoaY/rhhx/wxhtvCMX18y5evIji4mIMGTJEpdu1p6cnnjx5gps3b6J3795qnX/Xrl2F4hqAMGFZZYH9ogYPHqzy2s/PD59//jl+++03eHh4vPB+ieorIyOj2X0AyczMFDuEFo85EB9zID7mQHzMgbie7claGxbY1OAKCgqgUChgaWlZ7forV64gJCQEgwYNwpQpU2Bubg4tLS2MGTMGT58+1WhsUVFRiIqKwrp167B06VJIpVJERETgrbfeAlDRXTs+Pr7K+GcA0NHRUXltbm5epY2Pjw/09fVx9OhRTJkyBceOHYOenh7efPPNGmN6/Pgx7O3ta1z/6NEjAMDIkSOrXX/37t0at32ekZGRyuvKc3rZ6/5s0Q4A7dq1AwA8ePDgpfZLVF9SqbRZ3cHOzMyEnZ0d9PX1xQ6nRWIOxMcciI85EB9zIL76PKqWBTY1OENDQ0gkEpVJy5713XffwcDAAOvWrYNEUjHPXk5OziuJzdLSEpGRkVAoFEhLS0NsbCxmz56N5ORkvPbaazA2NsaAAQMwbty4Ktu2bdtW5XV13URat26NN998E9988w2mTJmCb775Bj4+PmjTpk2NMZmYmNR4rQAIXaxjYmKqvctc053vV+nhw4cqrysnerOwsBAjHGrBmuMHD319/Vr/H0KaxxyIjzkQH3MgPuZAPOp2Dwc4izhpQOW46YMHD1Y7y/WTJ0+go6Oj8kY9fPhwlXY6Ojoau6MtkUjQo0cPzJo1C2VlZcjKygJQMfb55s2bcHR0hLOzs8p/nTp1UmvfQ4cOxbVr1/Cf//wHly5dQkBAQK3t+/bti7NnzwoTwD3P1dUV+vr6yM3NrRKTs7Oz2uOv1VHTHe267nQfP35c5fW///1v6Ovrw8HBocFiIyIiIiJq7HgHmzTigw8+wOTJkzF58mSMGzcOxsbG+OWXX2BqagovLy/Ex8dj2bJlGDx4MC5evIiDBw9W2UenTp1w4MABpKamwsLCApaWlrCysnrhmAoLCxEcHIzhw4dDKpWitLQUCQkJwhhrAJg5cyZGjx6N4OBgjBkzBu3atcOff/6J8+fPo1evXlUer1UdT09PmJiY4KOPPoKRkRH69+9fa/vJkyfj4MGDmDBhAqZPn47XXnsNv//+OzIzMzF37lwYGRlh5syZ+Oyzz5Cbm4vevXtDW1sbv//+O1JSUhAdHd1gd+0sLCxgZGSEo0ePwsbGBrq6upDJZDUur3Tnzh0sWLAA/v7+uHbtGjZv3oxJkyZxgjMiIiIialFYYJNG9OrVCzt37sS6deuwYMECSCQS2NvbY9asWejbty/mzJmDXbt2ITExEW5uboiLi4Ofn5/KPqZMmYI7d+5g3rx5KCgoQGhoKMLCwl44Jj09PTg4OCAhIQF3795F69at4eTkhK1btwpjiG1tbbFv3z5hjHZxcTEsLCzg4eGhUlDWRkdHB35+fti7dy9Gjx5d54QIpqam+Oqrr7BmzRqsXr0acrkcHTt2VOmmHhQUBCsrK2zfvh27du1Cq1at8Prrr2PgwIFVxoa/DIlEgsjISKxduxaTJ09GSUkJUlJSYGNjU+3ySrNnz8b58+cRHh4ObW1tjBs3DrNnz26wuIiIiIiImgItZXOZDYaIXrns7GwMGjQI69evr/E53/V19epVAMDW43lIz8lvkH1S89e5ozHWRQwUO4wGVVxcjOvXr6Nbt24ccycS5kB8zIH4mAPxMQfiq/x86uzsXGdbjsEmIiIiIiIiagDsIk5NhlKprHbStEoSiQQKhaLG9dra2vWaAbApKS8vr/XRRK1aNb1fdRsrQ7FDoCaE7xciIiJqDJrep25qsc6fP4+JEyfWuH7kyJFISkqqcf3OnTvRp08fTYQmusGDB9f6qLNff/1VI8e1sbHR2L7njHfXyH6p+VIolJBImueXaERERNQ0sMCmJqN79+7Yv39/jetNTU0xfvz4GtdLpVJNhNUoxMbGoqSkROwwGkxJSQnkcnmzfKZxUyGXy5GRkQGpVNpk8sDimoiIiMTGApuaDAMDgzonFrCxsXlF0TQu6s5w3pRw/kVxKZVKyOVy5oGIiIioHjjJGRE1Ss11vHxToaWlBX19feaBiIiIqB54B5uIGh1dXd0m0y25udLX14ejo2OtbTjmmYiIiEgVC2wiapRW776A7HuFYodBNbCxMuREdERERETPYYFNRI1S9r1CpOfkix0GEREREZHaOAabmpSQkBAEBgaq3f7cuXPYtGlTvY/j6+uLTz75pN7bvYgdO3bg5MmTr+RYmlRQUIDo6GjcunVL7FCIiIiIiETBApuatfPnzyMuLk7sMGq1c+fOZlNgx8TEsMAmIiIiohaLBTYRERERERFRA2CB3UzNnz8fQ4cOxblz5zBixAi4uLhg9OjRSEtLAwBkZ2dDJpMhOTlZZbsVK1bA19dXeJ2YmAiZTIarV68iKCgIPXv2hJ+fH86cOQOFQoGoqCh4enrC09MTa9asgUKhaLBzSE9Px4QJE+Ds7Iw333wTSUlJVdrk5uYiPDwcnp6ecHZ2hq+vL/75z38CAKKjoxETE4Pi4mLIZDLIZLJ6dS8HgN27d8PHxwfu7u4ICQnBw4cPVdbn5ORg5syZcHd3h4uLC4KDg/Hrr7+qtElJScGoUaPg6uqKXr16YdSoUcIda19fX+Tk5GD37t1CjImJiWrFVlBQgGXLlqF///5wcnKCr68v1qxZo9Jmz5498PPzE9Z//vnnKjmKjo6Gq6trlX336tUL0dHRwuvAwEBMmzYNycnJ8PPzg6urKyZOnIg7d+4AqHg/DRo0CAAQHh4unEt2drZa50JERERE1BxwkrNm7MGDB1i+fDmmTp0KQ0NDrFmzBqGhoTh+/Hi99zVv3jyMHTsW7777LjZv3ozQ0FCMHDkSRUVFWLVqFS5fvozo6Gg4ODhg2LBhLx3706dPERQUBH19fXz66acAgA0bNqCoqAh2dnZCuw8//BD379/HwoULYW5ujrt37wpfIrzzzjvIzc3FkSNHEB8fDwAwMDBQO4bU1FRkZWVh8eLFePToESIjI7Fs2TJERUUBAIqKihAYGAiJRIKlS5dCT08PsbGxmDBhAg4dOoT27dvjzp07CA8PR0BAAD744AMoFArcuHED+fkVk3fFxMRg6tSpcHNzQ1BQEADg9ddfrzO2kpISTJo0CTk5OZgxYwYcHByQm5uLCxcuCG0SEhKwfPlyBAYGYuDAgbh48SJiYmJQWFiIefPmqX0dKl2/fh0PHz7EnDlzUF5ejpUrV2Lu3LnYu3cvLC0tERMTg9DQUERERKBPnz4AAEtLy3ofh4iIiIioqWKB3Yzl5+dj165dsLe3B1DxXNuJEyfi8uXLsLa2rte+JkyYgHHjxgEArKysMGzYMKSlpWHv3r0AgH79+iE1NRXJyckNUmAnJibi/v37OHbsmFBQOzo6YsiQISoF9tWrVxEREQF/f39h2YgRIwAA1tbWsLa2hkQigYuLS71jUCqViI2Nha6uLoCKu9VxcXFQKBSQSCRITEzEH3/8gaNHj6Jz584AAA8PD/j4+CA+Ph7z58/HtWvXUFpaikWLFgnFfb9+/YRjODo6QldXF+3atatXjAcOHMC1a9ewZ88elTvQI0eOBACUl5dj48aNCAgIwMKFCwEA3t7eKC0txbZt2zB16lSYmprW63oUFhbiwIEDMDMzAwAUFxdjwYIFyM3NhbW1Nbp16wYAsLW1faHrTU2TXC6HUqkUO4xmSS6Xq/xLrx5zID7mQHzMgfiYA/EplUpoaWmp1ZYFdjNmaWkpFNcA0KVLFwDAvXv36l1ge3l5CT9XFrhvvPGGShupVIqMjIwXjFbVlStXYG9vr1JM29raomvXrirtHB0dsW3bNmhra8PLywu2trYNcnygoliuLK4BoHPnzigtLUVeXh4sLCzw008/wd7eXiiuAcDExASenp7CnWSZTAZtbW3MmTMHY8aMgYeHBwwNDV86th9++AGdO3eutns3ANy+fRuPHj3CkCFDVJb7+/sjLi4OV65cwYABA+p1zK5duwrFNfC/91NlgU0tU0ZGBv/ga1hmZqbYIbR4zIH4mAPxMQfiYw7E9WxdUBsW2M2YkZGRymsdHR0AFd2v6+vZorDyzVXd/ktKSuq97+rcv38f5ubmVZabm5urxB8VFYWoqCisW7cOS5cuhVQqRUREBN56662XjuH586s878rjFxQUoF27dtXGePPmTQAVXzps2rQJcXFxCA0NhUQigbe3NxYvXowOHTq8cGyPHz+utft1ZRf0569h5evK9fXRkO8naj6kUinvYGuIXC5HZmYm7OzsoK+vL3Y4LRJzID7mQHzMgfiYA/HV5yk5LLBbKD09PQBAaWmpyvKCggIxwqnC0tISv/zyS5XleXl5KuOoLS0tERkZCYVCgbS0NMTGxmL27NlITk7Ga6+9ptEYjY2Nq71jn5eXB2NjY+F1//790b9/fxQVFeHUqVOIjIzEggULhHHhL8LExKTKZGrPrwdQZVK2vLw8IXag4n3w/HugtLQUxcXFLxwbtSz8Q695+vr6aNOmjdhhtGjMgfiYA/ExB+JjDsSjbvdwgLOIt1jm5ubQ0dFBenq6sKykpAQ//vijiFH9j7OzM27evImsrCxhWVZWFm7cuFFte4lEgh49emDWrFkoKysTtmvIu+rPc3d3x2+//Ybbt28Ly/Lz83HmzBm4u7tXaW9gYAB/f38EBASoXHcdHZ163wX29PREeno6Ll++XO16qVQKMzOzKrPEHzt2DDo6OujRoweAivH0paWlwmzgAHD27FmUl5fXKx6Ad7SJiIiIiHgHu4WSSCQYPHgwdu/eDVtbW5iammLXrl31GsCvSaNGjUJsbCymTZuG8PBwABWziD/bJbuwsBDBwcEYPnw4pFIpSktLkZCQACMjIzg6OgKoGDddVlaG+Ph4uLq6wsDAAJ06dWqwGHfs2IFp06Zh1qxZwizirVq1wqRJkwBUPCbr0qVL6NevHywsLJCdnY1Dhw6pjGnv1KkTzp49i9OnT8PIyAg2NjZ1TkA2fPhwfPnll5g6dSpCQ0Nhb2+Pe/fu4aeffsKyZcugra2NkJAQLF++HGZmZhgwYAAuXbqELVu2YNKkScL++/fvjzZt2mDhwoWYMmUKcnNzsXPnTqGHQ31YWFjAyMgIR48ehY2NDXR1dSGTydQer0JERERE1NSxwG7BFi1ahEWLFmH58uVo27YtgoODIZVKkZKSInZoaN26NbZt24YlS5Zg7ty5sLKyQkhICFJSUlBYWAigonuzg4MDEhIScPfuXbRu3RpOTk7YunWrMBmXj48Pxo0bh82bNyMvLw8eHh5ISEhokBgNDAyQkJCAlStXYtGiRVAoFHBzc8OuXbvQvn17ABWTnJ04cQKRkZF4/PgxLCwsEBAQIHxpAAARERFYsmQJwsLC8NdffyEyMhKjRo2q9di6urrYsWMHoqKiEBcXh8ePH8Pa2hoBAQFCm8DAQLRq1Qo7duzAV199BQsLC4SGhuL9998X2piammLDhg1YtWoVZsyYgW7duuHTTz+t9/PCgYovbSIjI7F27VpMnjwZJSUlSElJgY2NTb33RURERETUFGkpOTsNETUiV69eBQBsPZ6H9Jz6T8ZGr0bnjsZYFzFQ7DCateLiYly/fh3dunXjmDuRMAfiYw7ExxyIjzkQX+XnU2dn5zrbcgw2ERERERERUQNgF3HSiLKyshrXaWlp1fpYH4lEAolEc9/91BWbtra2xo6tDqVSWeskY5q+Po2FjdXLPy+cNIf5ISIiIqqKBTZpRPfu3Wtc17FjR+Tk5NS4PjQ0FGFhYZoIC0DdsaWmpmrs2OpISkrCggULalyv6evTWMwZX3UmdmpcFAolJBLxJ0UkIiIiaixYYJNG7N+/v8Z1crm81mfnWlpaaiIkQW2xNYYZr318fGqNUdPXpzEoKSmp831CmiWXy5GRkQGpVFpjHlhcExEREaligU0aoc4EAGJpzLEBFTN71/WYrpaA8y+KS6lUQi6XMw9ERERE9dD8B3ISERERERERvQIssImoUdLSYvdjMWlpaUFfX595ICIiIqoHdhEnokZHV1eX469Fpq+vD0dHx2rXcXIzIiIiouqxwCaiRmn17gvIvlcodhj0HBsrQ87wTkRERFQDFthE1Chl3ytEek6+2GEQEREREamNY7Cp3kJCQhAYGKh2+3PnzmHTpk31Po6vry8++eSTem/3Inbs2IGTJ0++kmM1VwUFBYiOjsatW7fEDoWIiIiISBQssEnjzp8/j7i4OLHDqNXOnTtZYL+kgoICxMTEsMAmIiIiohaLBTbRK/TkyROxQyAiIiIiIg1hga1B8+fPx9ChQ3Hu3DmMGDECLi4uGD16NNLS0gAA2dnZkMlkSE5OVtluxYoV8PX1FV4nJiZCJpPh6tWrCAoKQs+ePeHn54czZ85AoVAgKioKnp6e8PT0xJo1a6BQKBrsHNLT0zFhwgQ4OzvjzTffRFJSUpU2ubm5CA8Ph6enJ5ydneHr64t//vOfAIDo6GjExMSguLgYMpkMMpmsXt3LAWD37t3w8fGBu7s7QkJC8PDhQ5X1OTk5mDlzJtzd3eHi4oLg4GD8+uuvKm1SUlIwatQouLq6olevXhg1apRwx9rX1xc5OTnYvXu3EGNiYmKdcZWWlmLVqlUYOHAgnJyc4O3tjffffx+FhRUTc507dw4ymQzff/89Zs6cCTc3N4SHhwvvi+edOHECMpkMt2/fVuu6FBQUYNmyZejfvz+cnJzg6+uLNWvWqLTZs2cP/Pz8hPWff/65yvsjOjoarq6uVfbdq1cvREdHC68DAwMxbdo0JCcnw8/PD66urpg4cSLu3LkDoOK9PGjQIABAeHi4cB2zs7PVOhciIiIiouaAk5xp2IMHD7B8+XJMnToVhoaGWLNmDUJDQ3H8+PF672vevHkYO3Ys3n33XWzevBmhoaEYOXIkioqKsGrVKly+fBnR0dFwcHDAsGHDXjr2p0+fIigoCPr6+vj0008BABs2bEBRURHs7OyEdh9++CHu37+PhQsXwtzcHHfv3hW+RHjnnXeQm5uLI0eOID4+HgBgYGCgdgypqanIysrC4sWL8ejRI0RGRmLZsmWIiooCABQVFSEwMBASiQRLly6Fnp4eYmNjMWHCBBw6dAjt27fHnTt3EB4ejoCAAHzwwQdQKBS4ceMG8vMrJtCKiYnB1KlT4ebmhqCgIADA66+/XmdscXFx2LNnD+bMmQN7e3s8evQIp0+fRklJiUq7RYsW4e2338bGjRshkUhQUlKCpKQk/Pbbb3BwcBDaHTlyBN27d0enTp3qPHZJSQkmTZqEnJwczJgxAw4ODsjNzcWFCxeENgkJCVi+fDkCAwMxcOBAXLx4ETExMSgsLMS8efPqvvjPuX79Oh4+fIg5c+agvLwcK1euxNy5c7F3715YWloiJiYGoaGhiIiIQJ8+fQAAlpaW9T4OEREREVFTxQJbw/Lz87Fr1y7Y29sDqHi27MSJE3H58mVYW1vXa18TJkzAuHHjAABWVlYYNmwY0tLSsHfvXgBAv379kJqaiuTk5AYpsBMTE3H//n0cO3ZMKKgdHR0xZMgQlQL76tWriIiIgL+/v7BsxIgRAABra2tYW1tDIpHAxcWl3jEolUrExsZCV1cXQMXd6ri4OCgUCkgkEiQmJuKPP/7A0aNH0blzZwCAh4cHfHx8EB8fj/nz5+PatWsoLS3FokWLhOK+X79+wjEcHR2hq6uLdu3a1SvGq1evwtvbG+PHjxeW+fn5VWnn6+uLuXPnCq/LyspgZmaGo0ePCgW2XC5HamoqQkND1Tr2gQMHcO3aNezZs0flDvTIkSMBAOXl5di4cSMCAgKwcOFCAIC3tzdKS0uxbds2TJ06FaampmqfKwAUFhbiwIEDMDMzAwAUFxdjwYIFyM3NhbW1Nbp16wYAsLW1faFcU9Mil8uhVCrFDqNZk8vlKv/Sq8cciI85EB9zID7mQHxKpRJaWlpqtWWBrWGWlpZCcQ0AXbp0AQDcu3ev3gW2l5eX8HNlgfvGG2+otJFKpcjIyHjBaFVduXIF9vb2KsW0ra0tunbtqtLO0dER27Ztg7a2Nry8vGBra9sgxwcqiuXK4hoAOnfujNLSUuTl5cHCwgI//fQT7O3theIaAExMTODp6SnczZXJZNDW1sacOXMwZswYeHh4wNDQ8KVjc3R0xNatWxEdHY0BAwbAyckJEknVURcDBw5Ued2qVSsMGTIE33zzDWbPng2gonu4XC5HQECAWsf+4Ycf0Llz52q7dwPA7du38ejRIwwZMkRlub+/P+Li4nDlyhUMGDBArWNV6tq1q1BcA/97L1cW2NSyZGRk8A/9K5KZmSl2CC0ecyA+5kB8zIH4mANxPVuT1IYFtoYZGRmpvNbR0QFQ0f26vp4tCisTXN3+n++i/KLu378Pc3PzKsvNzc1V4o+KikJUVBTWrVuHpUuXQiqVIiIiAm+99dZLx/D8+VWed+XxCwoK0K5du2pjvHnzJoCKLx02bdqEuLg4hIaGQiKRwNvbG4sXL0aHDh1eOLbp06dDIpEgKSkJMTExMDMzw/jx4zFjxgyVb7iqu4YBAQH48ssvceXKFfTo0QNHjx5Fr1691C5UHz9+XGv368ru788fu/J15fr6aMj3MjV9UqmUd7A1TC6XIzMzE3Z2dtDX1xc7nBaJORAfcyA+5kB8zIH46vOUHBbYItLT0wNQMVnWswoKCsQIpwpLS0v88ssvVZbn5eWpjKO2tLREZGQkFAoF0tLSEBsbi9mzZyM5ORmvvfaaRmM0Njau9o59Xl4ejI2Nhdf9+/dH//79UVRUhFOnTiEyMhILFiwQxoW/CF1dXYSFhSEsLAxZWVn4+uuvER0dDRsbG6GLPIBqu5O4u7ujffv2OHr0KKRSKU6dOoWPPvpI7WObmJhUmcjt+fUAqkwIl5eXBwDCtdHT06vy/istLUVxcbHasVDLxD/wr46+vj7atGkjdhgtGnMgPuZAfMyB+JgD8ajbPRzgLOKiMjc3h46ODtLT04VlJSUl+PHHH0WM6n+cnZ1x8+ZNZGVlCcuysrJw48aNattLJBL06NEDs2bNQllZmbBdQ95Vf567uzt+++03lZm38/PzcebMGbi7u1dpb2BgAH9/fwQEBKhcdx0dnZe6E2tra4uIiAiYmJioNQu4lpYW/P39cezYMfz73/+GQqGodvx2TTw9PZGeno7Lly9Xu14qlcLMzKzKDPXHjh2Djo4OevToAaBiLH9paakwGzgAnD17FuXl5WrHUol3tImIiIiopeMdbBFJJBIMHjwYu3fvhq2tLUxNTbFr1656DaLXpFGjRiE2NhbTpk1DeHg4gIpZxJ/tkl1YWIjg4GAMHz4cUqkUpaWlSEhIgJGRERwdHQFUjJsuKytDfHw8XF1dYWBgoNZM2erGuGPHDkybNg2zZs0SZhFv1aoVJk2aBKDiUVWXLl1Cv379YGFhgezsbBw6dEhlTHunTp1w9uxZnD59GkZGRrCxsalzErCQkBB0794djo6O0NfXx4kTJ5Cfn19lXHxNhg4diq1bt2L9+vXw8vJSGd9cl+HDh+PLL7/E1KlTERoaCnt7e9y7dw8//fQTli1bBm1tbYSEhGD58uUwMzPDgAEDcOnSJWzZsgWTJk0Szq1///5o06YNFi5ciClTpiA3Nxc7d+4UelfUh4WFBYyMjHD06FHY2NhAV1cXMplM7fEqRERERERNHQtskS1atAiLFi3C8uXL0bZtWwQHB0MqlSIlJUXs0NC6dWts27YNS5Yswdy5c2FlZYWQkBCkpKQIz3rW09ODg4MDEhIScPfuXbRu3RpOTk7YunWrUDD6+Phg3Lhx2Lx5M/Ly8uDh4YGEhIQGidHAwAAJCQlYuXIlFi1aBIVCATc3N+zatQvt27cHUDHJ2YkTJxAZGYnHjx/DwsICAQEBwpcGABAREYElS5YgLCwMf/31FyIjIzFq1Khaj+3m5oZjx45h+/btKC8vh1QqxerVq+Hp6alW7I6OjsKkdHPmzKnXeevq6mLHjh2IiopCXFwcHj9+DGtra5VJ0gIDA9GqVSvs2LEDX331FSwsLBAaGor3339faGNqaooNGzZg1apVmDFjBrp164ZPP/203s8qByq+MIqMjMTatWsxefJklJSUICUlBTY2NvXeFxERERFRU6Sl5Cw1RNSIXL16FQCw9Xge0nPqPxkbaVbnjsZYFzFQ7DBahOLiYly/fh3dunXjmDuRMAfiYw7ExxyIjzkQX+XnU2dn5zrb8g42ETVKNlYv/yg1anjMCxEREVHNWGA3Y2VlZTWu09LSqvUROxKJpNpnOjeUumLT1tbW2LHVoVQqa53oS5PXR8xjNyZzxledpI4aB4VCCYlE/HkiiIiIiBobFtjNWPfu3Wtc17FjR+Tk5NS4PjQ0FGFhYZoIC0DdsaWmpmrs2OpISkrCggULalyvyesj5rEbi5KSEsjlcj4KSkRyuRwZGRmQSqVV8sDimoiIiKh6LLCbsf3799e4rq7ixdLSUhMhCWqLrTHMOu3j41NrjJq8PmIeuzHh9BDiUiqVkMvlzAMRERFRPbDAbsbUGYQvlsYcG1Axu3Zdj+lqjscmIiIiIqIX1/wHchJRk9QYngVPRERERFQfLLCJqNHR1dXl+GsRKRRKfsFBRERE9ALYRZyIGqXVuy8g+16h2GG0ODZWhpzBnYiIiOgFscAmokYp+14h0nPyxQ6DiIiIiEht7CJOVYSEhCAwMFDt9ufOncOmTZvqfRxfX1988skn9d7uRezYsQMnT558Jcdqjl40x0RERERELQkLbHpp58+fR1xcnNhh1Grnzp0ssF9CU8gxEREREZHYWGAT1cOTJ09eeNvy8nKUlpZWWa5UKlFSUvLKY3qZcyEiIiIioqpYYL+E+fPnY+jQoTh37hxGjBgBFxcXjB49GmlpaQCA7OxsyGQyJCcnq2y3YsUK+Pr6Cq8TExMhk8lw9epVBAUFoWfPnvDz88OZM2egUCgQFRUFT09PeHp6Ys2aNVAoFA12Dunp6ZgwYQKcnZ3x5ptvIikpqUqb3NxchIeHw9PTE87OzvD19cU///lPAEB0dDRiYmJQXFwMmUwGmUxWr+7lALB79274+PjA3d0dISEhePjwocr6nJwczJw5E+7u7nBxcUFwcDB+/fVXlTYpKSkYNWoUXF1d0atXL4waNUq4Y+3r64ucnBzs3r1biDExMbHOuM6dOweZTIbvv/8eM2fOhJubG8LDwwEABQUFWLJkCby9veHk5IRRo0bhv//9r8r2gYGBmDZtGpKSkuDn5wdnZ2fcuHFDeN+cPHkSb7/9NpydnZGamgoA+PbbbzF8+HA4OzvD29sbkZGRePr0qVoxvei5HDhwAP/4xz/Qu3dveHh4IDAwEFeuXBG2rSvH6enpmD59upCfqVOn4s6dO3XGRERERETU3HCSs5f04MEDLF++HFOnToWhoSHWrFmD0NBQHD9+vN77mjdvHsaOHYt3330XmzdvRmhoKEaOHImioiKsWrUKly9fRnR0NBwcHDBs2LCXjv3p06cICgqCvr4+Pv30UwDAhg0bUFRUBDs7O6Hdhx9+iPv372PhwoUwNzfH3bt3hS8R3nnnHeTm5uLIkSOIj48HABgYGKgdQ2pqKrKysrB48WI8evQIkZGRWLZsGaKiogAARUVFCAwMhEQiwdKlS6Gnp4fY2FhMmDABhw4dQvv27XHnzh2Eh4cjICAAH3zwARQKBW7cuIH8/IoJsmJiYjB16lS4ubkhKCgIAPD666+rHeOiRYvw9ttvY+PGjZBIJCgpKcG7776LvLw8zJo1C1ZWVjh06BCmTZsmfFlSKS0tDTk5OQgPD4eRkRHat28PALh//z6WL1+O6dOno3379ujQoQNSUlIwc+ZM4Txu376NqKgo3L17Fxs2bKg1phc9F6Dii6ARI0bg9ddfR0lJCY4ePYrx48fj0KFDkEqlteb4999/x9ixY2Fvb4+VK1dCS0sLmzZtwuTJk5GcnAxdXV21YyMiIiIiaupYYL+k/Px87Nq1C/b29gAAfX19TJw4EZcvX4a1tXW99jVhwgSMGzcOAGBlZYVhw4YhLS0Ne/fuBQD069cPqampSE5ObpACOzExEffv38exY8eEgtrR0RFDhgxRKbCvXr2KiIgI+Pv7C8tGjBgBALC2toa1tTUkEglcXFzqHYNSqURsbKxQiOXk5CAuLg4KhQISiQSJiYn4448/cPToUXTu3BkA4OHhAR8fH8THx2P+/Pm4du0aSktLsWjRIqHw69evn3AMR0dH6Orqol27di8Uo6+vL+bOnSu8/vrrr3Hjxg0cPHgQXbp0EY6XlZWFzz//HOvXrxfa5ufnY//+/UJh/ezyLVu2oGfPnsKyWbNmwcXFBWvWrAEA9O/fH/r6+li8eDF+/fVXlcL9+Zhe9FwAIDQ0VPhZoVDAy8sLV65cQVJSEiIiImrNcUxMDIyNjbF9+3bo6ekBANzc3DBo0CDs27cP48ePr3eM1DhU9pyQy+UiR9JyVV575kA8zIH4mAPxMQfiYw7Ep1QqoaWlpVZbFtgvydLSUiiuAQgF17179+pdYHt5eQk/Vxa4b7zxhkobqVSKjIyMF4xW1ZUrV2Bvb69STNva2qJr164q7RwdHbFt2zZoa2vDy8sLtra2DXJ8oKJYfvYuZ+fOnVFaWoq8vDxYWFjgp59+gr29vVBcA4CJiQk8PT1x4cIFAIBMJoO2tjbmzJmDMWPGwMPDA4aGhg0W48CBA1Venz59Gg4ODrCzs0NZWZmw3NPTE4cOHVJp6+DgUKW4rjyHZ4vrv/76C9evX8e8efNU2vn7+2Px4sW4cOGCSoH9fEwvei5ARRfvtWvX4uLFi8jLyxOWZ2Zm1rm/06dPw9/fH9ra2sK1MDIygqOjo9DLgZqmP/74A4B67wPSLOZAfMyB+JgD8TEH4mMOxKVuz0wW2C/JyMhI5bWOjg4AqIybVdezRWFlAqvb/8tMiPWs+/fvw9zcvMpyc3NzlfijoqIQFRWFdevWYenSpZBKpYiIiMBbb7310jE8f36V5115/IKCArRr167aGG/evAmg4kuHTZs2IS4uDqGhoZBIJPD29sbixYvRoUOHl47x+Wv06NEjXLt2Dd27d6/SVltbW+V1dbFXt7ywsBBKpbLKsQwNDaGrqyt0d68pJnU9v11RURGCgoJgZmaG+fPno0OHDtDT08PChQvVeg8/evQI8fHxQtfxZ1X+LlDT1KFDB6Snp8POzg76+vpih9MiyeVyZGZmMgciYg7ExxyIjzkQH3Mgvlu3bqndlgW2BlV2mX1+5uiCggIxwqnC0tISv/zyS5XleXl5KuOoLS0tERkZCYVCgbS0NMTGxmL27NlITk7Ga6+9ptEYjY2Nq71jn5eXB2NjY+F1//790b9/fxQVFeHUqVOIjIzEggULqi386uv57iDGxsaQyWRYsWJFvbetabmhoSG0tLSqTPBWWFiIkpISlXOtbb/1jefSpUvIzc1FXFycSs+FwsJCtXpgGBsbY8CAAcLQhme1bdv2hWKkxqHy/1/6+vpo06aNyNG0bMyB+JgD8TEH4mMOxMcciKc+n705i7gGmZubQ0dHB+np6cKykpIS/PjjjyJG9T/Ozs64efMmsrKyhGVZWVm4ceNGte0lEgl69OiBWbNmoaysTNiuIe+qP8/d3R2//fYbbt++LSzLz8/HmTNn4O7uXqW9gYEB/P39ERAQoHLddXR0XqhXQXU8PT3x+++/w9LSEs7OzlX+exFt27ZFt27dqsw4f+zYMQCo9lwbQuWjup692/zzzz8jJydHpV1NOe7bty9u3rwJR0fHKtehU6dOGomZiIiIiKix4h1sDZJIJBg8eDB2794NW1tbmJqaYteuXfUaJK9Jo0aNQmxsLKZNmyY8smnDhg0q3ZcLCwsRHByM4cOHQyqVorS0FAkJCcI4W6Bi3HRZWRni4+Ph6uoKAwODBiuuRo0ahR07dmDatGmYNWuWMIt4q1atMGnSJADAnj17cOnSJfTr1w8WFhbIzs7GoUOHVMa0d+rUCWfPnsXp06dhZGQEGxsbmJqavlBMI0aMwJ49ezBx4kQEBQXBzs4OhYWFwmRrH3zwwQvtNzQ0FDNmzMCcOXPw9ttvIyMjA1FRUfDz81MZf92QXFxc0KZNGyxduhRTp07FvXv3EB0dDSsrK5V2NeV45syZGD16NIKDgzFmzBi0a9cOf/75J86fP49evXph6NChGombiIiIiKgxYoGtYYsWLcKiRYuwfPlytG3bFsHBwZBKpUhJSRE7NLRu3Rrbtm3DkiVLMHfuXFhZWSEkJAQpKSkoLCwEUNFN1MHBAQkJCbh79y5at24NJycnbN26FWZmZgAAHx8fjBs3Dps3b0ZeXh48PDyQkJDQIDEaGBggISEBK1euxKJFi6BQKODm5oZdu3YJk4fJZDKcOHECkZGRePz4MSwsLBAQEKDyfOiIiAgsWbIEYWFh+OuvvxAZGYlRo0a9UEy6urrYuXMnoqOjsWnTJjx48AAmJiZwdHSstqu0ugYNGoT169dj48aNCAkJgYmJCcaMGfPCBbs62rVrh/Xr1+PTTz9FSEgI7OzssHTpUnzxxRcq7WrKsa2tLfbt2yeMzy8uLoaFhQU8PDw09qUAEREREVFjpaVUKpViB0FEVOnq1asAgK3H85Cek19Ha2ponTsaY13EQMjlcly7dg3dunXjeC+RFBcX4/r168yBiJgD8TEH4mMOxMcciK/y86k6w0E5BpuIiIiIiIioAbCLeBP27DOYn6elpYXaOidIJBJIJJr7fqWu2J5/nNWrplQqUV5eXuN6TV+fhtSczuVZNlYN9yxzUh+vOxEREdGLY4HdhFX3HOZKHTt2rDIT9LNCQ0MRFhamibAA1B1bamqqxo6tjqSkJCxYsKDG9Zq+Pg2pOZ3Ls+aM18zM6VQ3hYIjh4iIiIheBAvsJmz//v01rpPL5bU+iN7S0lITIQlqi01XV1ejx1aHj49PrTFq+vo0pOZ0LpVKSkrqfA+T5kgktfeAISIiIqLqscBuwl70mcuvQmOODQBMTU1f+DFdjU1zOpdnscAjIiIioqam6Q3MJKIWoTE8K56IiIiIqD5YYBNRo6Orq8vu4a8Yx10TERERvTx2ESeiRmn17gvIvlcodhgtgo2VISeVIyIiImoALLCJqFHKvleI9Jx8scMgIiIiIlIbu4gTERERERERNQAW2E1cYmIiDh8+LHYY9Xb9+nVER0dDLpeLFkN2djZkMhmSk5PVbh8dHY179+5pOLKXk5iYCJlMhocPH4odChERERFRi8ICu4lLSkrCkSNHxA6j3q5fv46YmBhRC+z6ysnJQUxMDO7fvy92KLUaOHAg9u7dCyMjI7FDISIiIiJqUTgGmxpMeXk5FAoFdHR0xA6lRTMzM4OZmZnYYRARERERtTi8gy2yixcvIigoCG5ubnB1dcU777yD06dPAwBWr16NYcOGwdXVFf369UNERITK3dPAwECcP38e33//PWQyGWQyGaKjo186pujoaLi6uuLKlSsYPXo0nJ2d8be//Q0nTpxQaRcYGIhp06YhKSkJfn5+cHZ2xo0bNwAAe/bsgZ+fH5ycnODr64vPP/8cCoUCQEUX5gULFgAA+vbtC5lMBl9fX2G/v/76K4KDg+Hi4gJ3d3fMnDkTf/zxh8qxFQoFtm/fjr/97W9wcnKCl5cXZs6cicLC/806/eOPP2Ls2LHo0aMH+vTpgwULFuDx48cvdE3OnTuHiRMnAgBGjx4tXO/S0lJ4eXkhKiqqyjazZs3C6NGjhe1lMhlOnjyJ0NBQuLi4wNvbG5s2baqyXXp6OqZPnw53d3e4uLhg6tSpuHPnjtqxVtdFvKSkBFFRURg0aBCcnJzQv39/zJ8/X1g/f/58DB06FGfOnMGwYcPQo0cPTJgwAdnZ2Xj8+DHCw8Ph5uaGN998E998843K8SrfBwcOHMCbb76JHj16IDAwELdv31Y7ZiIiIiKi5oB3sEV04cIFTJo0CS4uLli+fDmMjIyQlpYmFJN5eXmYNm0aLC0t8fDhQ2zfvh2BgYE4evQoWrVqhY8//hhz585F69atMW/ePACAtbV1g8RWWlqK2bNnIygoCDY2Nvjqq68QGhoqFG+V0tLSkJOTg/DwcBgZGaF9+/ZISEjA8uXLERgYiIEDB+LixYuIiYlBYWEh5s2bh4EDB2L69OmIjY3FF198AUNDQ+jq6gIA7t69iwkTJuC1117DZ599hqdPnyIqKgoTJkzAoUOHYGBgAABYtmwZ9u7di0mTJsHLywt//fUXvv/+exQXF8PQ0BBpaWl499130adPH6xfvx5//vkn1qxZg1u3bmHPnj3Q1tau1/Xo3r07Fi9ejE8++QSRkZHo1KkTAEBHRwcjR47EgQMHEB4eDomk4jurx48fIyUlBf/3f/+nsp9FixYhICAA0dHROHPmDKKiomBsbIx//OMfAIDff/8dY8eOhb29PVauXAktLS1s2rQJkydPRnJysnCd6issLAxnz57FtGnT4OLigocPH+Lbb79VafPgwQOsXLkS06dPR6tWrbB8+XLMmTMH+vr66NWrF8aMGYN//etfmDt3Lnr27ImOHTsK2/7yyy+4c+cOPvjgAwDAunXr8N57771UzPTqyeVyKJVK4edn/6VXjzkQH3MgPuZAfMyB+JgD8SmVSmhpaanVlgW2iD777DPY2toiPj5eKPi8vb2F9ZGRkcLP5eXlcHV1Rf/+/XH27Fl4e3ujS5cuMDAwQJs2beDi4tKgsZWWlmL69OnCHVhvb2+89dZbiIuLw9q1a4V2+fn52L9/P9q3by/EuXHjRgQEBGDhwoXCtqWlpdi2bRumTp0KMzMzvP766wAqCtdnuzPv2LEDZWVl2LZtG0xMTAAA3bp1Q0BAAJKSkhAYGIiMjAx89dVXmD17NqZNmyZs6+fnJ/y8adMmWFhYYNOmTUKX9fbt2yM4OBgnT55UuWOuDgMDA3Tp0gUAYG9vD2dnZ2HdO++8gy+++AL/+c9/MGDAAADA4cOHIZFIMHToUJX9vPHGG8KXIf369UNeXh5iY2Px97//HRKJBDExMTA2Nsb27duhp6cHAHBzc8OgQYOwb98+jB8/vl5xA8Dp06fx/fffY82aNSrxPB9bfn4+du3aBXt7ewDA/fv3sWzZMkyZMgUzZswAADg7O+P48eP47rvvMGnSJGHbvLw87Nq1C3Z2dgAAR0dHDBkyBImJiRg7dmy9YyZxZGRkVPnjnZmZKU4wJGAOxMcciI85EB9zID7mQFzq3jRigS0SuVyOy5cvIyIiosa7qSdPnkRsbCxu3ryJoqIiYXlmZqZKIa4pgwcPFn7W1tbGm2++ie+++06ljYODg1BcA8Dt27fx6NEjDBkyRKWdv78/4uLicOXKFaEIrc5PP/2EPn36CMU1AHTu3Bldu3bFhQsXEBgYiLNnz0KpVArFf037GTp0qMp4cG9vbxgZGeHChQv1LrBrY2tri969e+Prr78Wzi0xMRF+fn7CHfdKz15ToOJLgYMHDyI3NxcdOnTA6dOn4e/vD21tbZSVlQEAjIyM4OjoiLS0tBeK74cffoC+vj4CAgJqbWdpaSkU1wCEYtnT01NYZmRkBDMzM+Tm5qpsa29vL7QHKq5J165dcfnyZRbYTYhUKlW5g52ZmQk7Ozvo6+uLHFnLxByIjzkQH3MgPuZAfMyB+G7duqV2WxbYIikoKIBCoYClpWW1669cuYKQkBAMGjQIU6ZMgbm5ObS0tDBmzBg8ffpU4/Hp6OjA2NhYZZm5uTkePHigsqxdu3Yqr/Pz84W2z2/77PqaFBQUoFu3blWWm5ubC9s+fvwYrVq1qnKM5/dT3fpn99OQxowZg/nz5+Phw4e4f/8+rl27pjLGudLzk49VXr8HDx6gQ4cOePToEeLj4xEfH19l2xedPO7x48ewsLCos1vL87OOVx7P0NBQZbmurm6V92BN1/r59ws1btX90dbX10ebNm1EiIYqMQfiYw7ExxyIjzkQH3MgHnW7hwMssEVjaGgIiURS4yOfvvvuOxgYGGDdunXCuN6cnJxXFl9paSny8/NViuy8vDxYWFiotHv+zVZ55/n5ZzDn5eUBQJWi/XnGxsZC2+e3r7xDamJigrKyMuTl5dVYZNe2n7pieBFvvfUWli1bhkOHDiE7Oxuvv/46evfuXaXd89flzz//BADhuhobG2PAgAEYN25clW3btm37QrGZmJjgwYMH9Ro7Ul81XeuuXbtq5HhERERERI0RZxEXSeW46YMHD6K8vLzK+idPnkBHR0elIDp8+HCVdjo6Ohq7o338+HHh5/Lycnz33Xfo2bNnrdtIpVKYmZkhOTlZZfmxY8ego6ODHj16APjf3dGSkhKVdu7u7jh79qzKXebbt2/j119/hbu7O4CKccxaWlr4+uuva4zD3d0dKSkpQjdroGIsckFBgbCf+qqMubrrrauri+HDh2Pfvn04fPgwRo0aVW0x++w1BYB///vfsLS0FCan69u3L27evAlHR0c4Ozur/Fc5sVp9eXp6Qi6X49ixYy+0vTpu3ryJrKws4XVWVhZu3LhR5/uFiIiIiKg54R1sEX3wwQeYPHkyJk+ejHHjxsHY2Bi//PILTE1N4eXlhfj4eCxbtgyDBw/GxYsXcfDgwSr76NSpEw4cOIDU1FRYWFjA0tISVlZWLx2bjo4OYmNj8fTpU2EW8dzcXGzcuLHW7bS1tRESEoLly5fDzMwMAwYMwKVLl7BlyxZMmjQJpqamACrGVQPA7t278eabb6J169aQyWSYPHkyEhMTERQUhOnTp+Pp06dYt24d2rdvj5EjRwKoKOLHjh2L9evXIz8/H3379sWTJ0/w/fffIywsDFZWVnj//fcxduxYTJs2DYGBgcIs4j169Kh1DHht7OzsoK2tja+//hqtWrWCtra2ymRnY8aMESasGzVqVLX7OHv2LFatWgUvLy+cPn0aBw8exOLFi4VeCjNnzsTo0aMRHByMMWPGoF27dvjzzz9x/vx59OrVq8rEZOrw9PTEgAED8NFHH+HOnTvo2bMnHj9+jH//+99Yt27dC12L55mbm+P999/HzJkzAQDr16+HlZVVjdeBiIiIiKg5YoEtol69emHnzp1Yt24dFixYAIlEAnt7e8yaNQt9+/bFnDlzsGvXLiQmJsLNzQ1xcXEqM2UDwJQpU3Dnzh3MmzcPBQUFCA0NRVhY2EvHpqOjg7Vr12Lp0qX47bffYGNjgw0bNqjV5TcwMBCtWrXCjh078NVXX8HCwgKhoaF4//33hTaOjo4ICwvDvn378MUXX6B9+/ZITU0VHvP16aefYs6cOZBIJPDy8sL8+fNVJgxbvHgxbGxssG/fPsTHx8PExAQeHh5CN2onJyds27YNa9euRVhYGNq0aQNfX1/Mmzev3o/oqmRmZobFixfjiy++wKFDh1BWVoZff/1VWN+lSxfY2dnh9ddfr/FLjk8++QR79+7FV199hbZt2yI8PFxlZnBbW1vs27cP69atw9KlS1FcXAwLCwt4eHioPB6tvqKjoxETE4O9e/ciJiYG5ubm8PLyeuH9Pa979+5466238Nlnn+HBgwfo2bMnli5dykd0EREREVGLoqWsnDKW6P+Jjo7Gtm3bcPHiRbFDaVLu3LmDt956C+vXr6/yRci5c+cwceJE7N+/X+Wud3MQGBiINm3aIC4urkH2d/XqVQDA1uN5SM9p+AnpqKrOHY2xLmKgyrLi4mJcv34d3bp144QqImEOxMcciI85EB9zID7mQHyVn0/V+RzPO9hEL+nRo0fIyMjAxo0b0aFDBwwaNEjskJoFGyvDuhtRg+C1JiIiImoYLLCbGaVSWe2kaZUkEgkUCkWN61+0+3RTp851qxwn/bwTJ07go48+gq2tLT777DO0aqW5XyuFQlFn/jQ1U/irNmf8i01GRy9GoVBCImke7x0iIiIisbDAbmbOnz+PiRMn1rh+5MiRSEpKqnH9zp07ERYW1iDjuJuSpKQkLFiwoMb1tY1tHzVqVJ2TefXp00dlvPaL2rhxI2JiYmpcHxkZ+conFktISGjwfZaUlEAul1f7XGbSDBbXRERERC+PBXYz0717d+zfv7/G9aampiqTaj1PKpVqIqxGz8fHp9brZmlp+QqjqdmYMWMwcODAGtfb2Ni8umA0jNNDEBEREVFTwwK7mTEwMKhz8H1zKsIaiqmpqfAIscbMysqqQR7DRkREREREDa/6QaVERCJrLmPJiYiIiKjlYIFNRI2Orq4ux1+rSaFgV3oiIiKixoJdxImoUVq9+wKy7xWKHUajZmNlyNnWiYiIiBoRFthE1Chl3ytEek6+2GEQEREREamNXcSJqEEUFBQgOjoat27dEjsUIiIiIiJRsMAmogZRUFCAmJgYFthERERE1GKxwCZ6hZ48eSJ2CEREREREpCEssEk08+fPx9ChQ3Hu3DmMGDECLi4uGD16NNLS0gAA2dnZkMlkSE5OVtluxYoV8PX1FV4nJiZCJpPh6tWrCAoKQs+ePeHn54czZ85AoVAgKioKnp6e8PT0xJo1a6BQKBok/tLSUqxatQoDBw6Ek5MTvL298f7776OwsGJirnPnzkEmk+H777/HzJkz4ebmhvDwcOG8n3fixAnIZDLcvn1breMXFBRg2bJl6N+/P5ycnODr64s1a9aotNmzZw/8/PyE9Z9//rnK+UdHR8PV1bXKvnv16oXo6GjhdWBgIKZNm4bk5GT4+fnB1dUVEydOxJ07dwBU5GrQoEEAgPDwcMhkMshkMmRnZ6t1LkREREREzQEnOSNRPXjwAMuXL8fUqVNhaGiINWvWIDQ0FMePH6/3vubNm4exY8fi3XffxebNmxEaGoqRI0eiqKgIq1atwuXLlxEdHQ0HBwcMGzbspWOPi4vDnj17MGfOHNjb2+PRo0c4ffo0SkpKVNotWrQIb7/9NjZu3AiJRIKSkhIkJSXht99+g4ODg9DuyJEj6N69Ozp16lTnsUtKSjBp0iTk5ORgxowZcHBwQG5uLi5cuCC0SUhIwPLlyxEYGIiBAwfi4sWLiImJQWFhIebNm1fv871+/ToePnyIOXPmoLy8HCtXrsTcuXOxd+9eWFpaIiYmBqGhoYiIiECfPn0AAJaWlvU+DhERERFRU8UCm0SVn5+PXbt2wd7eHgCgr6+PiRMn4vLly7C2tq7XviZMmIBx48YBAKysrDBs2DCkpaVh7969AIB+/fohNTUVycnJDVJgX716Fd7e3hg/frywzM/Pr0o7X19fzJ07V3hdVlYGMzMzHD16VCiw5XI5UlNTERoaqtaxDxw4gGvXrmHPnj0qd6BHjhwJACgvL8fGjRsREBCAhQsXAgC8vb1RWlqKbdu2YerUqTA1Na3X+RYWFuLAgQMwMzMDABQXF2PBggXIzc2FtbU1unXrBgCwtbWFi4tLvfZNL0cul0OpbNjnYcvlcpV/6dVjDsTHHIiPORAfcyA+5kB8SqUSWlpaarVlgU2isrS0FIprAOjSpQsA4N69e/UusL28vISf7ezsAABvvPGGShupVIqMjIwXjFaVo6Mjtm7diujoaAwYMABOTk6QSKqOuhg4cKDK61atWmHIkCH45ptvMHv2bAAV3cPlcjkCAgLUOvYPP/yAzp07V9u9GxvEnQgAABgFSURBVABu376NR48eYciQISrL/f39ERcXhytXrmDAgAFqHatS165dheIa+F+uKgtsEk9GRobG/uhmZmZqZL+kPuZAfMyB+JgD8TEH4mMOxKWrq6tWOxbYJCojIyOV1zo6OgCAp0+f1ntfhoaGws+VvwDV7f/5Ltwvavr06ZBIJEhKSkJMTAzMzMwwfvx4zJgxQ+UbLnNz8yrbBgQE4Msvv8SVK1fQo0cPHD16FL169VK7UH38+HGt3a/z8/OrPXbl68r19dGQuaKGJZVKNXIHOzMzE3Z2dtDX12/QfZN6mAPxMQfiYw7ExxyIjzkQX32eksMCmxotPT09ABWTiT2roKBAjHCq0NXVRVhYGMLCwpCVlYWvv/4a0dHRsLGxwYgRI4R21XUncXd3R/v27XH06FFIpVKcOnUKH330kdrHNjExwa+//lrregB4+PChyvK8vDwAgLGxMYCKa/z89S0tLUVxcbHasZD4NPnHVl9fH23atNHY/qluzIH4mAPxMQfiYw7ExxyIR93u4QBnEadGzNzcHDo6OkhPTxeWlZSU4McffxQxqurZ2toiIiICJiYmas0CrqWlBX9/fxw7dgz//ve/oVAoqh2/XRNPT0+kp6fj8uXL1a6XSqUwMzOrMgP7sWPHoKOjgx49egCoGKteWloqzAYOAGfPnkV5ebnasVTiHW0iIiIiaul4B5saLYlEgsGDB2P37t2wtbWFqakpdu3aVa9JBjQpJCQE3bt3h6OjI/T19XHixAnk5+dXGfddk6FDh2Lr1q1Yv349vLy8VMY312X48OH48ssvMXXqVISGhsLe3h737t3DTz/9hGXLlkFbWxshISFYvnw5zMzMMGDAAFy6dAlbtmzBpEmThAnO+vfvjzZt2mDhwoWYMmUKcnNzsXPnTqH3QH1YWFjAyMgIR48ehY2NDXR1dSGTydQer0JERERE1NSxwKZGbdGiRVi0aBGWL1+Otm3bIjg4GFKpFCkpKWKHBjc3Nxw7dgzbt29HeXk5pFIpVq9eDU9PT7W2d3R0FCZdmzNnTr2Oraurix07diAqKgpxcXF4/PgxrK2tVSZJCwwMRKtWrbBjxw589dVXsLCwQGhoKN5//32hjampKTZs2IBVq1ZhxowZ6NatGz799FMEBgbWKx6g4guRyMhIrF27FpMnT0ZJSQlSUlJgY2NT730RERERETVFWsqGnhmHiOglXL16FQCw9Xge0nPqPxlbS9K5ozHWRQzUyL6Li4tx/fp1dOvWjeO9RMIciI85EB9zID7mQHzMgfgqP586OzvX2ZZjsImIiIiIiIgaALuIU4tVVlZW4zotLa1aH3skkUiqfeZ1Q1AqlbVOMqbJYzcmNlaGdTdq4XiNiIiIiBoXFtjUYnXv3r3GdR07dkROTk6N60NDQxEWFqaJsJCUlIQFCxaIcuzGZM54d7FDaBIUCiUkEvEn/SMiIiIiFtjUgu3fv7/GdXK5vNZnC1taWmoiJACAj49PrbFp8tiNRUlJSZ05oAosromIiIgaDxbY1GKpM0mBGExNTYXHaLVknH+RiIiIiJqa5j+Qk4iIiIiIiOgVYIFNRERERERE1ABYYBMRERERERE1ABbYRERERERERA2ABTYRERERERFRA2CBTURERERERNQAWGATERERERERNQAW2EREREREREQNgAU2ERERERERUQNggU1ERERERETUAFhgExERERERETUAFthEREREREREDYAFNhEREREREVEDYIFNRERERERE1ABYYBMRERERERE1ABbYRERERERERA2ABTYRERERERFRA2CBTURERERERNQAtJRKpVLsIIiIKv38889QKpXQ0dGBlpaW2OG0WEqlEqWlpcyDiJgD8TEH4mMOxMcciI85EF9JSQm0tLTg5uZWZ9tWryAeIiK1Vf7h4B8QcWlpaUFXV1fsMFo05kB8zIH4mAPxMQfiYw7Ep6WlpfZnU97BJiIiIiIiImoAHINNRERERERE1ABYYBMRERERERE1ABbYRERERERERA2ABTYRERERERFRA2CBTURERERERNQAWGATERERERERNQAW2EREREREREQNgAU2ERERERERUQNggU1ERERERETUAFhgExERERERETUAFthEREREREREDYAFNhFpTHp6Ot599124uLjAy8sLn376KUpKSurcTqlUYvPmzRg4cCB69OiBv//977h06VKVdvfu3UNYWBhcXV3Ru3dv/N///R+Kioo0cCZNlyZzcObMGcyePRu+vr7o2bMn/P398cUXX6C0tFRDZ9M0afr3oJJCocCoUaMgk8mQnJzcgGfQ9L2KHHz//fcYO3YsXFxc4OHhgcDAQOTm5jbwmTRdms7BTz/9hMDAQHh4eKBPnz547733cP36dQ2cSdP1ojnYvXs3pk2bhjfeeKPW/7/wb3LdNJkD/k1uPFhgE5FG5OfnY9KkSSgtLUV0dDRmz56Nf/3rX1i5cmWd227ZsgUbNmzA5MmTERcXBwsLCwQFBeH3338X2pSWluK9995DZmYm1qxZgyVLluC///0vPvjgA02eVpOi6Rzs2bMHf/31F2bOnInNmzdjxIgRiI6OxuLFizV5Wk2KpnPwrD179uDevXsNfQpN3qvIwcGDBxEaGorevXtj06ZNWLlyJZycnPD06VNNnVaToukc3L59G8HBwWjTpg3WrFmDFStWID8/H5MnT8aDBw80eWpNxsvk4ODBg3j06BEGDBhQYxv+Ta6bpnPAv8mNiJKISAM2bdqkdHFxUT569EhYtmfPHmW3bt2Uubm5NW735MkTpZubm3LNmjXCsqdPnyp9fHyUH3/8sbDs8OHDSplMpkxPTxeW/ec//1E6ODgoL1++3KDn0lRpOgd5eXlVto2NjVXKZLJq17VEms5Bpby8PGXv3r2V+/fvVzo4OCiPHTvWkKfRpGk6B48ePVK6ubkpd+/erYnwmwVN5yAuLk7p7OyslMvlwrI7d+4oHRwclElJSQ15Kk3Wi+ZAqVQqy8vLlUqlUvn777/X+P8X/k2um6ZzwL/JjQfvYBORRpw6dQp9+/aFiYmJsOxvf/sbFAoFTp8+XeN2P//8M4qKivC3v/1NWKarq4vBgwfj1KlTKvuXyWTo1KmTsMzLywsmJiY4efJkw55ME6XpHJiZmVXZtlu3blAqlbxr9P9oOgeV1q5diz59+qBPnz4NGn9zoOkcHDt2DAqFAqNHj9ZI/M2BpnNQWloKXV1d6OnpCcsMDQ0b9iSauBfNAQBIJHWXC/ybXDdN54B/kxsPFthEpBG3b99W+UMLAEZGRrCwsMDt27dr3Q5AlW07d+6MP/74A0+ePKlx/1paWpBKpbXuvyXRdA6q8/PPP0NXVxc2NjYvEXnz8SpycOXKFRw5cgQffvhhA0befGg6B5cvX4ZUKsWBAwfg4+MDR0dHDB8+nEXFMzSdg4CAAJSXl2PdunV49OgR7t27h8jISLRv3x6DBg1q4LNpml40By+zf/5NVqXpHFSHf5PFwQKbiDSioKAARkZGVZYbGxsjPz+/1u2evxMBVPwRUiqVwrYFBQXV3qGoa/8tiaZz8LzMzEzs3LkTY8eORdu2bV8u+GZC0zlQKBRYunQp3n33XX6AqoGmc/DgwQNkZGRg/fr1CA8Px5YtW9CxY0eEhITg5s2bDXsyTZSmc2BnZ4cdO3Zg//79eOONN9C/f3/8+OOP2L59O+9k/z8vmoP67J9/k2un6Rw8j3+TxcMCm4iIXlpRURHCwsJgY2OD2bNnix1Oi7Fv3z78/+3dfUyV5R/H8TcoKGiHRJBE0emclEQCCioK+TBTMsThNLDAphI6IpejFFeamLasMEINRS0hQZeikynZg9VWVvpHNsvMJ3xAlkl4RJSC8Pz+8Mf983TUlN85POjntbFxLq77uq8v3x2ufbnu+9wVFRU8++yzzT2Ve5bFYuHKlStkZGQwYcIEhg4dSlZWFj4+PuTm5jb39O4JpaWlpKamMnToUN5//31ycnLo1q0bSUlJVFRUNPf0RJqc1uTmpQJbRBzCZDJx6dIlm/aLFy/i4eFxy+Nqa2ttPn23qqoKJycn41iTyXTDx3/82/j3EkfnoEFtbS0pKSlcvHiRNWvW4O7ubp8A7gKOzMHly5fJzMxk1qxZ1NXVUVVVZbwn/vzzTz0e57+a4m8RwODBg40+Li4uhIaGcuzYMXuE0Oo5OgfLly/Hy8uLZcuWER4ezogRI8jJyaGqqoq8vDz7BtNKNTYHdzK+1uRbc3QOGmhNbn4qsEXEIXr37m1zT9GlS5c4f/68zT1I/zwOru1IXO/EiRP4+vrSvn37m45vsVgoLS295fj3EkfnAK5dopyWlsbPP/9Mbm4uXbt2tWMErZ8jc3DhwgXMZjMLFy4kNDSU0NBQYmJiAJg7dy5jxoyxczStk6PfB3369LnpGHpM1zWOzsGxY8d48MEHrfp06NCBHj16cPr0aXuE0Oo1Ngf/z/hak605OgegNbmlUIEtIg4RGRnJ3r17qaqqMto+/vhjnJ2dGTp06E2PCwkJoWPHjpSUlBhtdXV1fPLJJ0RGRlqNf/jwYU6ePGm0ffvtt5jN5ls+J/Je4ugcACxatIgvvviCVatW4e/vb/8gWjlH5sDb25u8vDyrr8zMTABSU1PJzs52UFSti6PfByNGjACu/f1pUFtby/79+wkICLBnKK2Wo3Pg6+vLL7/8gsViMdqqq6s5deoU3bp1s3M0rVNjc3An42tNvjVH5wC0JrcUbZt7AiJyd4qLiyM/P5+UlBSSk5M5d+4cy5YtIy4uDh8fH6Pf1KlTKS8v59NPPwWgXbt2JCcnk52djaenJ3379qWwsBCz2cz06dON48aMGcPq1atJTU1lzpw51NTUsGzZMoYPH84jjzzS5PG2RI7OQU5ODps2bWL69Om4urpy4MAB42d9+vShY8eOTRZrS+XIHLRr187msVxlZWXAtd9/SEhIE0XZsjn6fRAQEMCYMWN45ZVXMJvNeHt7U1BQQEVFhVW/e5mjcxAXF0dKSgppaWnExMRQW1vL+vXrqa2tZdKkSU0eb0vU2BwAHDx4kLNnz1JZWQlc++R8uPZYqLCwMEBr8u1wdA60JrccTpbr/90nImJHx48fZ/Hixfzwww906NCBmJgYXnjhBVxdXY0+CQkJnD17lj179hhtFouFNWvWUFBQQGVlJQ899BDp6ekEBwdbjX/u3Dlee+01vv76a9q2bcvo0aOZP3++FpHrODIHCQkJ7Nu374bnzcvL0zOZ/8vR74PrlZWVMWrUKLKyshg7dqxD42pNHJ2DK1eukJmZyc6dO6muriYgIIAXX3yRAQMGNFmMLZ2jc1BSUsK6desoLS3FxcWFfv36MXv2bPr3799kMbZ0jc3BvHnz2LZtm814YWFh5OfnG6+1Jv87R+ZAa3LLoQJbRERERERExA50D7aIiIiIiIiIHajAFhEREREREbEDFdgiIiIiIiIidqACW0RERERERMQOVGCLiIiIiIiI2IEKbBERERERERE7UIEtIiIiIiIiYgcqsEVERERERETsQAW2iIiIiIiIiB2owBYRERH5F0VFRfj7+3Pw4MHmnkqjbNy4kaKiouaehojIXU8FtoiIiMhdrrCwkG3btjX3NERE7noqsEVERETuUjU1Nc09BRGRe4oKbBEREZE7NG/ePIKDgykvLyc5OZng4GAiIiLYuHEjAL/++iuJiYkEBQUxYsQIiouLrY5vuOR8//79LFiwgEGDBhESEsJLL73ExYsXbc63ceNGxo0bx8MPP8ywYcNYtGgRVVVVVn0SEhJ44okn+Omnn3jqqafo378/mZmZjBw5kqNHj7Jv3z78/f3x9/cnISEBALPZzBtvvEF0dDTBwcGEhIQwY8YMDh8+bDX2999/j7+/P7t27eK9994jMjKSwMBApk6dyqlTp2zm++OPP5KUlERoaChBQUFER0ezYcMGqz7Hjx/n+eefJywsjMDAQGJjY/n888/vPBkiIi1I2+aegIiIiEhrVF9fT1JSEgMHDiQtLY3i4mIyMjJwc3Nj+fLlREdH89hjj7Fp0ybmzp1LUFAQfn5+VmNkZGRgMpl47rnnKC0tpbCwkPLycvLz83FycgIgOzubFStWEB4eTnx8vNHv4MGDFBYW4uLiYoxnNptJSkpi3LhxjB8/ns6dOzNo0CAWL16Mu7s7M2fOBMDLywuAM2fO8NlnnzF27Fi6d+9ORUUFmzdv5umnn2bnzp34+PhYzTc3NxcnJyemTZtGdXU1a9euJS0tjY8++sjo880335CcnEyXLl1ITEzEy8uL48eP8+WXXzJ16lQAjh49Snx8PD4+PiQlJeHu7k5JSQkpKSlkZ2czevRo+ydMRKQJqMAWERERaYS//vqL8ePHk5ycDEB0dDQRERHMnz+fzMxMHn/8cQDCw8OJiopi+/btpKamWo3h4uLCBx98YBTJvr6+vPnmm+zZs4dRo0ZRWVnJ6tWrGTZsGLm5uTg7X7v4sHfv3mRkZLBjxw4mTpxojHf+/HkWLVpEXFyc1XneeecdOnXqRExMjFW7v78/u3fvNsYFiImJISoqii1btpCSkmIT8/bt23F1dQXAZDKxZMkSjhw5Qt++famvr2fBggV06dKF7du3YzKZjGMtFovx/ZIlS+jatStbt241xpoyZQrx8fG89dZbKrBFpNXSJeIiIiIijTRp0iTje5PJRK9evXBzcyMqKspo7927NyaTiTNnztgc/+STT1rtQMfHx9O2bVu++uorAPbu3UtdXR2JiYlWRfCkSZPo2LGj0a+Bq6srsbGxtz1/V1dXY9z6+nouXLiAu7s7vXr14tChQzb9Y2NjjYIYYODAgQBGbIcOHaKsrIzExESr4howduTNZjPfffcdUVFRVFdXU1lZSWVlJRcuXGDYsGGcPHmSc+fO3XYMIiItiXawRURERBqhXbt2eHp6WrXdd999PPDAA0YxeX37P++ZBujZs6fV6w4dOuDt7c3Zs2cBKC8vB64V6ddzdXXFz8/P6NfAx8fHqgD+N1evXiUvL4+CggLKysqor683fnb//ffb9Pf19bV63VBEN8TWUGj37dv3puc8ffo0FouFrKwssrKybtjnjz/+sLk8XUSkNVCBLSIiItIIbdq0uaP26y+RdpT27dvfUf+cnByysrKYOHEis2fPxsPDA2dnZ5YuXXrD+V6/i369O4nt6tWrAEybNo2IiIgb9unRo8dtjyci0pKowBYRERFpJqdOnWLw4MHG68uXL3P+/HkiIyOB/+0YnzhxwuoD0mpraykrKyM8PPy2zvPPHfUGu3fvZtCgQSxdutSqvaqqik6dOt1RLIAxxyNHjtx0bg19XFxcbnv+IiKthe7BFhEREWkmmzdvpq6uznhdWFjI33//bRTY4eHhuLi4kJ+fb7VLvGXLFi5dusSjjz56W+dxc3O74SXqbdq0sdl9LikpafQ90AEBAXTv3p28vDyb8zWcp3PnzoSFhbF582Z+//13mzEqKysbdW4RkZZAO9giIiIizaSuro5nnnmGqKgoSktLKSgoYMCAAYwaNQoAT09PkpOTWbFiBTNmzGDkyJFGv8DAQMaPH39b5wkICKCwsJBVq1bRs2dPPD09GTJkCMOHD2flypWkp6cTHBzMkSNHKC4utnmc2O1ydnbm1VdfZdasWUyYMIHY2Fi8vb05ceIEx44dY926dQAsXLiQKVOmEB0dzeTJk/Hz86OiooIDBw7w22+/sWPHjkadX0SkuanAFhEREWkmCxYsoLi4mHfffZe6ujrGjRvHyy+/bHVJd2pqKp6ennz44Ye8/vrreHh4MHnyZObMmWP1CeS3kpKSQnl5OWvXruXy5cuEhYUxZMgQZs6cSU1NDcXFxezatYt+/fqxevVq3n777UbHFBERwYYNG1i5ciXr16/HYrHg5+fH5MmTjT59+vRh69atrFixgm3btmE2m/H09KRfv342jwYTEWlNnCxN8YkbIiIiImIoKioiPT2dLVu2EBgY2NzTERERO9E92CIiIiIiIiJ2oAJbRERERERExA5UYIuIiIiIiIjYge7BFhEREREREbED7WCLiIiIiIiI2IEKbBERERERERE7UIEtIiIiIiIiYgcqsEVERERERETsQAW2iIiIiIiIiB2owBYRERERERGxAxXYIiIiIiIiInagAltERERERETEDlRgi4iIiIiIiNjBfwB9eai9rkxY8AAAAABJRU5ErkJggg==\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def get_importance_df(model, name):\n",
        "    \"\"\"\n",
        "    Extract feature-importance values from a trained model and return them\n",
        "    in a clean, well-labelled DataFrame.\n",
        "\n",
        "    This function retrieves:\n",
        "      - the transformed feature names produced by the preprocessing pipeline,\n",
        "      - the feature-importance scores learned by the classifier,\n",
        "    and combines them into a single table that can be easily merged,\n",
        "    compared or sorted when analysing multiple models.\n",
        "\n",
        "    It is especially useful when comparing Random Forest and XGBoost,\n",
        "    as both models produce importance scores but may rank features differently.\n",
        "\n",
        "    Parameters:\n",
        "        model :  A fitted pipeline containing both the preprocessor and classifier.\n",
        "        name : A short identifier (e.g., \"rf\" or \"xgb\") used to label the\n",
        "            importance column clearly.\n",
        "\n",
        "    Returns:\n",
        "        pandas.DataFrame\n",
        "            A table with:\n",
        "              - \"feature\": the full list of encoded/scaled feature names,\n",
        "              - \"importance_<name>\": the importance score from the given model.\n",
        "    \"\"\"\n",
        "    # Extract the fitted preprocessor and classifier from the pipeline\n",
        "    pre = model.named_steps[\"preprocessor\"]\n",
        "    clf = model.named_steps[\"clf\"]\n",
        "\n",
        "    # Get all transformed feature names (after encoding/scaling)\n",
        "    feature_names = pre.get_feature_names_out()\n",
        "\n",
        "    # Build and return a DataFrame with feature names and importance values\n",
        "    return pd.DataFrame({\n",
        "        \"feature\": feature_names,\n",
        "        f\"importance_{name}\": clf.feature_importances_\n",
        "    })\n",
        "\n",
        "    # ================================\n",
        "# RUN: Generate Feature Importance Tables\n",
        "# ================================\n",
        "\n",
        "# Get feature importance tables for both models\n",
        "rf_imp = get_importance_df(best_rf, \"rf\")\n",
        "xgb_imp = get_importance_df(best_xgb, \"xgb\")\n",
        "\n",
        "# Merge RF and XGBoost importance results\n",
        "merged_imp = rf_imp.merge(xgb_imp, on=\"feature\")\n",
        "\n",
        "# Add combined importance score\n",
        "merged_imp[\"combined_importance\"] = (\n",
        "    merged_imp[\"importance_rf\"] + merged_imp[\"importance_xgb\"]\n",
        ")\n",
        "\n",
        "# Sort features by combined importance (highest first)\n",
        "merged_imp = merged_imp.sort_values(\"combined_importance\", ascending=False)\n",
        "\n",
        "# Display the top 20 most important features across both models\n",
        "print(\"\\nTop 20 Combined Feature Importances:\\n\")\n",
        "merged_imp.head(20)\n",
        "\n"
      ],
      "metadata": {
        "id": "CDrNODYKRJS3",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 728
        },
        "outputId": "56d87bba-9d70-465a-feeb-38741f1f01fd"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "Top 20 Combined Feature Importances:\n",
            "\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                              feature  importance_rf  importance_xgb  combined_importance\n",
              "109                num__same_srv_rate       0.056716        0.374036             0.430752\n",
              "85                     num__src_bytes       0.133325        0.041148             0.174473\n",
              "77                     cat__flag_RSTR       0.009384        0.157273             0.166658\n",
              "18                 cat__service_ecr_i       0.013229        0.089384             0.102612\n",
              "110                num__diff_srv_rate       0.049736        0.029343             0.079078\n",
              "27                  cat__service_http       0.029142        0.049046             0.078188\n",
              "103                        num__count       0.063029        0.013238             0.076268\n",
              "118         num__dst_host_serror_rate       0.064725        0.010129             0.074854\n",
              "119     num__dst_host_srv_serror_rate       0.049794        0.012948             0.062742\n",
              "117  num__dst_host_srv_diff_host_rate       0.038170        0.021819             0.059989\n",
              "115       num__dst_host_diff_srv_rate       0.042200        0.010260             0.052460\n",
              "82                       cat__flag_SF       0.048914        0.000831             0.049745\n",
              "116  num__dst_host_same_src_port_rate       0.038495        0.005925             0.044420\n",
              "114       num__dst_host_same_srv_rate       0.032295        0.004558             0.036854\n",
              "93               num__num_compromised       0.006474        0.030042             0.036516\n",
              "78                       cat__flag_S0       0.032551        0.003592             0.036143\n",
              "88                num__wrong_fragment       0.005791        0.029216             0.035007\n",
              "86                     num__dst_bytes       0.030968        0.002768             0.033736\n",
              "106              num__srv_serror_rate       0.029432        0.002118             0.031550\n",
              "17                 cat__service_eco_i       0.013207        0.012117             0.025324"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-3c2bf57a-2aa7-40ae-8459-55fe8fc9505e\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>feature</th>\n",
              "      <th>importance_rf</th>\n",
              "      <th>importance_xgb</th>\n",
              "      <th>combined_importance</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>109</th>\n",
              "      <td>num__same_srv_rate</td>\n",
              "      <td>0.056716</td>\n",
              "      <td>0.374036</td>\n",
              "      <td>0.430752</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>85</th>\n",
              "      <td>num__src_bytes</td>\n",
              "      <td>0.133325</td>\n",
              "      <td>0.041148</td>\n",
              "      <td>0.174473</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>77</th>\n",
              "      <td>cat__flag_RSTR</td>\n",
              "      <td>0.009384</td>\n",
              "      <td>0.157273</td>\n",
              "      <td>0.166658</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>cat__service_ecr_i</td>\n",
              "      <td>0.013229</td>\n",
              "      <td>0.089384</td>\n",
              "      <td>0.102612</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>110</th>\n",
              "      <td>num__diff_srv_rate</td>\n",
              "      <td>0.049736</td>\n",
              "      <td>0.029343</td>\n",
              "      <td>0.079078</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>cat__service_http</td>\n",
              "      <td>0.029142</td>\n",
              "      <td>0.049046</td>\n",
              "      <td>0.078188</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>103</th>\n",
              "      <td>num__count</td>\n",
              "      <td>0.063029</td>\n",
              "      <td>0.013238</td>\n",
              "      <td>0.076268</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>118</th>\n",
              "      <td>num__dst_host_serror_rate</td>\n",
              "      <td>0.064725</td>\n",
              "      <td>0.010129</td>\n",
              "      <td>0.074854</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>119</th>\n",
              "      <td>num__dst_host_srv_serror_rate</td>\n",
              "      <td>0.049794</td>\n",
              "      <td>0.012948</td>\n",
              "      <td>0.062742</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>117</th>\n",
              "      <td>num__dst_host_srv_diff_host_rate</td>\n",
              "      <td>0.038170</td>\n",
              "      <td>0.021819</td>\n",
              "      <td>0.059989</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>115</th>\n",
              "      <td>num__dst_host_diff_srv_rate</td>\n",
              "      <td>0.042200</td>\n",
              "      <td>0.010260</td>\n",
              "      <td>0.052460</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>82</th>\n",
              "      <td>cat__flag_SF</td>\n",
              "      <td>0.048914</td>\n",
              "      <td>0.000831</td>\n",
              "      <td>0.049745</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>116</th>\n",
              "      <td>num__dst_host_same_src_port_rate</td>\n",
              "      <td>0.038495</td>\n",
              "      <td>0.005925</td>\n",
              "      <td>0.044420</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>114</th>\n",
              "      <td>num__dst_host_same_srv_rate</td>\n",
              "      <td>0.032295</td>\n",
              "      <td>0.004558</td>\n",
              "      <td>0.036854</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>93</th>\n",
              "      <td>num__num_compromised</td>\n",
              "      <td>0.006474</td>\n",
              "      <td>0.030042</td>\n",
              "      <td>0.036516</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>78</th>\n",
              "      <td>cat__flag_S0</td>\n",
              "      <td>0.032551</td>\n",
              "      <td>0.003592</td>\n",
              "      <td>0.036143</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>88</th>\n",
              "      <td>num__wrong_fragment</td>\n",
              "      <td>0.005791</td>\n",
              "      <td>0.029216</td>\n",
              "      <td>0.035007</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>86</th>\n",
              "      <td>num__dst_bytes</td>\n",
              "      <td>0.030968</td>\n",
              "      <td>0.002768</td>\n",
              "      <td>0.033736</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>106</th>\n",
              "      <td>num__srv_serror_rate</td>\n",
              "      <td>0.029432</td>\n",
              "      <td>0.002118</td>\n",
              "      <td>0.031550</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>cat__service_eco_i</td>\n",
              "      <td>0.013207</td>\n",
              "      <td>0.012117</td>\n",
              "      <td>0.025324</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
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              "        async function quickchart(key) {\n",
              "          const quickchartButtonEl =\n",
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              "          quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
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              "\n",
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            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "merged_imp",
              "summary": "{\n  \"name\": \"merged_imp\",\n  \"rows\": 122,\n  \"fields\": [\n    {\n      \"column\": \"feature\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 122,\n        \"samples\": [\n          \"num__srv_serror_rate\",\n          \"cat__service_other\",\n          \"cat__service_IRC\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"importance_rf\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.01847352219230205,\n        \"min\": 0.0,\n        \"max\": 0.13332472869486395,\n        \"num_unique_values\": 119,\n        \"samples\": [\n          0.0004705213742169728,\n          5.312188292097966e-06,\n          0.04973576969500258\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"importance_xgb\",\n      \"properties\": {\n        \"dtype\": \"float32\",\n        \"num_unique_values\": 69,\n        \"samples\": [\n          0.0022235149517655373,\n          0.3740358352661133,\n          0.001190642942674458\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"combined_importance\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.047486469253475765,\n        \"min\": 0.0,\n        \"max\": 0.43075178846059686,\n        \"num_unique_values\": 119,\n        \"samples\": [\n          0.0005524962780952629,\n          5.312188292097966e-06,\n          0.07907835586960986\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 20
        }
      ]
    }
  ],
  "metadata": {
    "colab": {
      "provenance": [],
      "gpuType": "T4"
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    "kernelspec": {
      "display_name": "Python 3",
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    "language_info": {
      "name": "python"
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    "accelerator": "GPU"
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  "nbformat": 4,
  "nbformat_minor": 0
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