{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "k_soiC78lCKe"
      },
      "source": [
        "# Artificial Intelligence for Credit Risk Assessment\n",
        "## Component 1: ML Model – Lending Club Loan Default Prediction\n",
        "**Dataset:** Lending Club Loan Data (Kaggle)\n",
        "\n",
        "---\n",
        "\n",
        "### Notebook Structure\n",
        "1. Setup & Library Imports\n",
        "2. Dataset Loading & Understanding (Test 1)\n",
        "3. Exploratory Data Analysis (Test 2)\n",
        "4. Preprocessing Pipeline (Test 3)\n",
        "5. Baseline Logistic Regression (Test 4)\n",
        "6. Tuned Logistic Regression with GridSearchCV (Test 5)\n",
        "7. Baseline Ensemble Model – Gradient Boosting (Test 6)\n",
        "8. Tuned Ensemble Model with RandomizedSearchCV (Test 7)\n",
        "9. Cross-Validation Comparison (Test 8)\n",
        "10. Final Test-Set Evaluation (Test 9)\n",
        "11. Interpretability & Fairness Analysis (Test 10)\n",
        "12. Summary & Recommendations"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "d-MUU-S1lCKh"
      },
      "source": [
        "---\n",
        "## 1. Setup & Library Imports"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 51,
      "metadata": {
        "id": "TevVO-eIlCKi"
      },
      "outputs": [],
      "source": [
        "# ── Install required packages (run once in Colab) ──────────────────────────────\n",
        "!pip install -q shap xgboost imbalanced-learn"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 52,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "866AplJDlCKj",
        "outputId": "5e917af8-0511-4c19-b8f7-99d706c1e9b3"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "✅ All libraries imported successfully.\n"
          ]
        }
      ],
      "source": [
        "# ── Core libraries ─────────────────────────────────────────────────────────────\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import matplotlib.ticker as mtick\n",
        "import seaborn as sns\n",
        "import warnings\n",
        "warnings.filterwarnings('ignore')\n",
        "\n",
        "# ── Scikit-learn ───────────────────────────────────────────────────────────────\n",
        "from sklearn.model_selection import (\n",
        "    train_test_split, GridSearchCV, RandomizedSearchCV,\n",
        "    cross_val_score, StratifiedKFold\n",
        ")\n",
        "from sklearn.preprocessing import StandardScaler, LabelEncoder\n",
        "from sklearn.pipeline import Pipeline\n",
        "from sklearn.impute import SimpleImputer\n",
        "from sklearn.compose import ColumnTransformer\n",
        "from sklearn.linear_model import LogisticRegression\n",
        "from sklearn.ensemble import GradientBoostingClassifier, RandomForestClassifier\n",
        "from sklearn.metrics import (\n",
        "    accuracy_score, precision_score, recall_score,\n",
        "    f1_score, roc_auc_score, confusion_matrix,\n",
        "    classification_report, RocCurveDisplay\n",
        ")\n",
        "\n",
        "# ── SHAP for interpretability ──────────────────────────────────────────────────\n",
        "import shap\n",
        "\n",
        "# ── Reproducibility seed ───────────────────────────────────────────────────────\n",
        "SEED = 42\n",
        "np.random.seed(SEED)\n",
        "\n",
        "# ── Plot styling ───────────────────────────────────────────────────────────────\n",
        "sns.set_theme(style='whitegrid', palette='muted', font_scale=1.1)\n",
        "plt.rcParams['figure.dpi'] = 110\n",
        "\n",
        "print(\"✅ All libraries imported successfully.\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-WyXFsV9lCKl"
      },
      "source": [
        "---\n",
        "## 2. Dataset Loading & Understanding (Test 1)\n",
        "\n",
        "**Goal:** Load the Lending Club dataset from Google Drive, inspect its shape, column types,\n",
        "target variable distribution, class imbalance, and missing values."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 53,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5UkoMGj1lCKl",
        "outputId": "2d9dc9ae-b28d-4036-977e-891fba06284e"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Dataset shape: 10,000 rows × 56 columns\n"
          ]
        }
      ],
      "source": [
        "\n",
        "# ── Load dataset ───────────────────────────────────────────────────────────────\n",
        "# Update the path below to match where the CSV sits in your Drive\n",
        "DATA_PATH = '/content/loans_full_schema.csv'  # ← adjust if needed\n",
        "\n",
        "df_raw = pd.read_csv(DATA_PATH, low_memory=False)\n",
        "print(f\"Dataset shape: {df_raw.shape[0]:,} rows × {df_raw.shape[1]} columns\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 54,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "IBSzzbX5lCKl",
        "outputId": "cdea0d11-c5a0-48ba-de03-12f1cea39ad0"
      },
      "outputs": [
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              "   Unnamed: 0                emp_title  emp_length state homeownership  \\\n",
              "0           1  global config engineer          3.0    NJ      MORTGAGE   \n",
              "1           2   warehouse office clerk        10.0    HI          RENT   \n",
              "2           3                 assembly         3.0    WI          RENT   \n",
              "\n",
              "   annual_income  verified_income  debt_to_income  annual_income_joint  \\\n",
              "0        90000.0         Verified           18.01                  NaN   \n",
              "1        40000.0     Not Verified            5.04                  NaN   \n",
              "2        40000.0  Source Verified           21.15                  NaN   \n",
              "\n",
              "  verification_income_joint  ...  sub_grade  issue_month  loan_status  \\\n",
              "0                       NaN  ...         C3     Mar-2018      Current   \n",
              "1                       NaN  ...         C1     Feb-2018      Current   \n",
              "2                       NaN  ...         D1     Feb-2018      Current   \n",
              "\n",
              "   initial_listing_status  disbursement_method   balance  paid_total  \\\n",
              "0                   whole                 Cash  27015.86     1999.33   \n",
              "1                   whole                 Cash   4651.37      499.12   \n",
              "2              fractional                 Cash   1824.63      281.80   \n",
              "\n",
              "   paid_principal  paid_interest  paid_late_fees  \n",
              "0          984.14        1015.19             0.0  \n",
              "1          348.63         150.49             0.0  \n",
              "2          175.37         106.43             0.0  \n",
              "\n",
              "[3 rows x 56 columns]"
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              "      <th>Unnamed: 0</th>\n",
              "      <th>emp_title</th>\n",
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              "      <th>disbursement_method</th>\n",
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              "      <th>paid_interest</th>\n",
              "      <th>paid_late_fees</th>\n",
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              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>global config engineer</td>\n",
              "      <td>3.0</td>\n",
              "      <td>NJ</td>\n",
              "      <td>MORTGAGE</td>\n",
              "      <td>90000.0</td>\n",
              "      <td>Verified</td>\n",
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              "      <td>warehouse office clerk</td>\n",
              "      <td>10.0</td>\n",
              "      <td>HI</td>\n",
              "      <td>RENT</td>\n",
              "      <td>40000.0</td>\n",
              "      <td>Not Verified</td>\n",
              "      <td>5.04</td>\n",
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              "      <td>4651.37</td>\n",
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              "      <td>3.0</td>\n",
              "      <td>WI</td>\n",
              "      <td>RENT</td>\n",
              "      <td>40000.0</td>\n",
              "      <td>Source Verified</td>\n",
              "      <td>21.15</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>...</td>\n",
              "      <td>D1</td>\n",
              "      <td>Feb-2018</td>\n",
              "      <td>Current</td>\n",
              "      <td>fractional</td>\n",
              "      <td>Cash</td>\n",
              "      <td>1824.63</td>\n",
              "      <td>281.80</td>\n",
              "      <td>175.37</td>\n",
              "      <td>106.43</td>\n",
              "      <td>0.0</td>\n",
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              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
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              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
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              "        element.innerHTML = '';\n",
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          "data": {
            "text/plain": [
              "int64      26\n",
              "float64    17\n",
              "object     13\n",
              "Name: dtype count, dtype: int64"
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              "\n",
              "    .dataframe tbody tr th {\n",
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              "\n",
              "    .dataframe thead th {\n",
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              "      <th></th>\n",
              "      <th>dtype count</th>\n",
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      ],
      "source": [
        "# ── First look ─────────────────────────────────────────────────────────────────\n",
        "display(df_raw.head(3))\n",
        "display(df_raw.dtypes.value_counts().rename('dtype count'))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 55,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_zx8vdqblCKm",
        "outputId": "bc749b66-8307-4ee6-ee93-74f2d1cceab8"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Unique loan_status values:\n",
            "loan_status\n",
            "Current               9375\n",
            "Fully Paid             447\n",
            "In Grace Period         67\n",
            "Late (31-120 days)      66\n",
            "Late (16-30 days)       38\n",
            "Charged Off              7\n",
            "Name: count, dtype: int64 \n",
            "\n",
            "Rows after filtering: 454\n",
            "Default rate: 1.54%\n"
          ]
        }
      ],
      "source": [
        "# ── Target variable: loan_status ───────────────────────────────────────────────\n",
        "print(\"Unique loan_status values:\")\n",
        "print(df_raw['loan_status'].value_counts(), '\\n')\n",
        "\n",
        "# ── Binary target: 1 = Default, 0 = Fully Paid ────────────────────────────────\n",
        "# Keep only the two clearest outcomes for a clean classification task\n",
        "keep_status = ['Fully Paid', 'Charged Off', 'Default']\n",
        "df = df_raw[df_raw['loan_status'].isin(keep_status)].copy()\n",
        "df['target'] = (df['loan_status'].isin(['Charged Off', 'Default'])).astype(int)\n",
        "print(f\"Rows after filtering: {len(df):,}\")\n",
        "print(f\"Default rate: {df['target'].mean():.2%}\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 56,
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          "data": {
            "text/plain": [
              "<Figure size 1320x440 with 2 Axes>"
            ],
            "image/png": 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ack4FBICaNWuiefPmCneEk7l3757C8rBhw/I8tp+fH9LS0tRWNF9LSwsDBw6UJwd8fX0RFBSEWrVqKYx4srKyQocOHeTLz549w7x583LVnPlQzgTEhwYOHFiohJe6jturVy+Fujf9+/eXJ70A4PHjxx9NeuV8zvz9/fMdqeHj46OQ9PpY7OqSc+roh69HPT099OvXTz4KKi4uDkFBQahTp45a3iPW1tYKtcI+TJgkJiaqdfRbzqmLsqRWWlqa/As98H6En4ODQ559+Pj4wMXFpUDHk0qlWLNmDXbv3i2vJ6ZMZmYm4uLilNZ2K2s+nB4qe5zz4+TkJE8ArlmzBh4eHqhZsyZq1qyJxo0bo1WrVjAyMipSXHl9HhdGv3795OcjEonQr18/edJLEAT4+fnlqndYknK+lwHIk9cyQ4YMUfi8vn//vtKkV9euXRWSdzVr1pS/R2SJRiIiyhuTXkREVOqtWrUKJ06c+Gi7D+s05VStWjVoa+f+s5eYmCj/t5mZWa42eY0UKMyXDUEQEB8fr9Y7RQ4ZMkRhRIybmxuGDRsmH9EDvE9QaWlpAXhf72bSpEny0WH5yS8h8GGx8Y9R13ErVqyY73LO5zEvhXnOPqynVVJyxqjs9VipUiWl7dXxHvkwmflhce2c9dSKKj4+HnFxcfJla2trAO+fxw8TNfkpzPN04MCBAk9bzOu1+GFs+b1mS4MP6w1+WKRfmdGjR+Ply5dwc3NDVlYWfH19FaZ5V6xYEWvXrkWrVq1Ujiuvz+PC+NhnQl7v95J6Dj88/ofv3bzeyx+ytbVVWM75vizMe4WI6FPFpBcREZV6//77r/zfdnZ2+Ouvv1C7dm3o6Ohg+fLl2Llz50f7MDQ0VLo+ZwH4+Ph4SKVSiMVi+bqcRb1zynkXPJFIhNmzZ8sTTMoUpOB7YdSsWRMtWrSQjyY4ffo0dHR0FL4E5ZzaeO/ePYXE09ixYzFp0iRYWFhAJBKhbdu2BUogFDZxp67j5pzyp2w55/OYF1NTU/l+DRo0yLe2kaaKYOd8XcXHxyM7O1shOfBh4W9Ze3W8Rz6czleQUUGqOnXqlMJrtW3btgAgr7Ml29a2bVuF0YofKkz9q5zTCa2srLB+/Xo0aNAAurq6OHjwYJ61kXI+DrKpuDLBwcEFPn5JS01NlU+xBgCxWJzvnSVltLS08Mcff+CHH37AgwcPEBQUhDdv3uDGjRt48+YNYmJiMG/evFx3si2MvD6PC6Ognwk5P88BxembUqkUb968KXIsynx4p9To6GiFHw3yei9/6MPkYHG+L4mIyiMmvYiIqNTLebe11q1by6eApKenF+mLF/C+GPGFCxcAvB8Fc+HCBfTq1QvA+y+0OYs259S8eXP5vwVBgKWlJQYNGpSrXUBAABISEhSmheX8EpOz/lZhDR06VJ70CgsLw44dO+TbWrRogZo1a8qXc46qAd5PD5SNjLh9+3axjWxS13HPnTuHSZMmyRMzZ86cUdjeqFGjj/bRvHlzeQH8yMhIDBgwINdoi+zsbFy5cgVOTk4K63NOO5o+fTpmzJhRoLgLq3nz5vJERVZWFs6cOSOfFpWZmYm///5b3tbc3Fw+BbE43yPqduXKFaxZs0a+rK2tjTFjxgB4n1StX7++fPpWdHQ0vvjii1xJEtkdVjt27Fjg4+Z8LTZs2BDNmjUD8D7xcf78+Tz3y5lQDQoKkt8tNSkpCQcPHizw8XP6MJHxYTKtqJKTkzFnzhyFpH2/fv1yvd6VCQwMhI2NDUxNTdGpUyf5FMGnT5/KX4uhoaGIi4uT33FQXZ9phfH3339jwIAB8iRpzveGSCRCw4YNAeT+weHBgwfyczp27Fi+n0FFOa+cfyOA94nenJ8rJ0+ezLc9ERGpB5NeRERU6tWqVQsvXrwAAHkdJ2NjY5w/fx5BQUFF6nvAgAHYsGGD/EvnvHnz4O3tDUNDQ7i5uSktYg8AnTt3lhc6BoCffvoJly9fRv369SESiRAaGgpfX18EBgZi+vTpaNmypXxfa2tr+QiRa9eu4a+//oK5uTnMzc1z1X3JT8+ePfHHH38gJSUFAPIsYA/krs/0/fffo0+fPoiKioKrq2uBj1lY6jpuQEAAPv/8c3Tu3BkBAQG4ePGifJu9vT2aNm360T7Gjx8Pd3d3SKVSREdHo3///ujRowdsbGyQmpqKly9f4u7du0hMTIS7u3ueIy+KYuHChUrrIdWqVQsrV67EoEGDsHnzZvkX8V9++QU+Pj6wsrKCu7u7wnS18ePHy0exFOd7pKiOHz8OY2NjxMXF4d69e3j48KHC9nnz5im8TiZMmIDZs2cDeP+89+3bF5999hkqVqyIhIQEvHjxAt7e3khLS1OaaM5LrVq15I/ftWvX8PPPP8Pa2hpXr17NtyB4kyZNFO4WOnDgQDRp0gT379/Ptw5dfj6cZvjbb7+hQ4cO0NLSQpcuXXK9bz4mICAAO3fuREZGBl6/fo0rV64oTPmtUaMGFixYUKC+Dhw4gBMnTqB169aoVq0aKlWqhMzMTIW7wurq6iqM+lTXZ1pheHp64quvvkKrVq3g4+OjcAfQzp07y6em165dG8bGxkhOTgYAbNmyBc+ePUN6ejru3LmT7zFyPk+xsbFYsGAB6tSpA5FIhC+//BL6+vp57uvg4ABnZ2d5nTHZTSo+vHsj8L4ov7J6XkREVHRMehERUak3depUzJo1C8D7qSn79+8HABgZGaFHjx7ykVqqsLKywsKFC/HTTz9BEARkZGTIR2+YmZmhWbNmePDgAQDFaSVaWlrYuHEjvv76a7x9+xYSiQSXL1/G5cuXP3rMHj16yIvjp6WlyW9VX69evUJ9QTQ0NESvXr1y1XKSrc+pUaNG6NSpE65duwbg/WgOWUH09u3b49WrVwW6s1thqeu4Tk5OuHv3Lp4+faqw3sjICH/++WeBYmnevDn+97//4Y8//kBWVhZiYmJw6NChQp5R0XxYY0lGVnzexMQEmzZtwpQpU+TTG5XV6howYAAmTJggXy7O90hRbdmyRel6Y2NjLFy4EAMGDFBY36dPHwQEBGDLli0QBAGhoaHYs2dPkeOYNGkSPD09kZWVBalUiuPHjwN4P5qnf//+uUYPygwdOhS7d++WJyJDQ0MRGhoK4H1y5erVq4WOpVmzZgp3YL179678M8HW1rbQSa8nT57kmbjr2LEjlixZIh+VVRAZGRn53ulzzJgxCgkfdX2mFUbr1q3h5eUFLy8vhfWWlpb45Zdf5Mu6uroYO3YsNmzYAOD9yL4rV64AAKpXrw5tbW0EBgYqPUa3bt2wceNGeT27U6dOybcNGjQo36QXAKxYsQLjxo2Dv78/gPd3afzwcXVwcMCKFSsKcspERKQC8cebEBERaVavXr2wYcMGNGzYEDo6OjA1NUWXLl1w7NixQtX0ycuQIUOwZcsWNGvWDHp6ejA1NUWPHj1w7NgxhWmJH478qVGjBk6fPo0FCxagZcuWMDMzg5aWFgwNDVG3bl0MGDAAf/31V67b3I8cORKzZs1CjRo1ctVRKqyhQ4fmWterVy+lNXPWrVuH8ePHw9raGjo6OrC1tcXkyZOxefPmfOuRFZU6jjto0CBs374dLVq0gKGhIYyNjeHi4oIjR44UaGqjzIgRI+Dm5oYvvvgCtWvXhoGBAbS1tWFubo7mzZtjwoQJOHLkCKpWrarq6RaZo6Mj/vnnH0yePBkODg4wNDSEtrY2LC0t0aVLF2zatAnLly9XqFVU3O+RohCJRPKYatWqBRcXFyxcuBDXrl3LlfCSmTVrFo4ePYpBgwahevXq0NPTg46ODiwtLdG6dWtMnz49zyRVXpo3b47du3ejZcuW0NPTg5GREdq0aYP9+/fLa4opY2FhgQMHDsDFxQVGRkYwMDCAo6MjtmzZgvHjxxcqBhldXV3s2LEDHTt2LFA9uoIQi8XQ19eHlZUVmjZtipEjR+Lo0aPYvn17gaY1ygwePBiTJ09G69atYWtrK3+PWFpawtnZGStXrsQPP/ygsI86P9MKatq0aVi+fDkaNmwIfX19mJmZoW/fvjh27Fiu4u/Tp0/H3LlzUb16dejo6MDKygqjR4/G8ePH831sHBwcsHbtWjRu3PijCS5lLCwscPz4cSxcuBCtWrWCqakptLS0YGpqipYtW+KXX37B8ePHYWFhUei+iYioYEQCb/tBRESfuPT0dKVfaMLDw9G7d2/59MERI0bgt99+K+nwiIiIiIhIBZzeSEREnzxXV1ccOXIEvXr1QvXq1aGrq4vAwEAcOnRInvDS1tbGqFGjNBwpEREREREVFJNeREREAPz9/eV1Vz6kr6+PxYsXa3yaGBERERERFRynNxIR0SfvxYsX2Lt3L+7fv4/o6GikpKTAwMAANWrUQOvWrTFy5EhUq1ZN02ESEREREVEhMOlFRERERERERETlDu/eSERERERERERE5Q6TXkREREREREREVO4w6UVEREREREREROUOk15ERERERERERFTuMOlFRERERERERETlDpNeRERERERERERU7jDpRURERERERERE5Q6TXkREREREREREVO4w6UVEREREREREROUOk15ERERERERERFTuMOlFRERERERERETlDpNeRERERERERERU7jDpRURERERERERE5Q6TXkREREREREREVO4w6UVEREREREREROUOk15ERERERERERFTuMOlFRERERERERETlDpNeRERERERERERU7jDpRURERERERERE5Q6TXkREREREREREVO4w6UVEREREREREROUOk15ERERERERERFTuMOlFRERERERERETlDpNeRERERERERERU7jDpRURERERERERE5Q6TXkREREREREREVO4w6UVEREREREREROUOk15ERERERERERFTuMOlFRERERERERETlDpNeRERERERERERU7jDpRURERERERERE5Q6TXkREREREREREVO4w6UVEREREREREROUOk15ERERERERERFTuMOlFRCoLCQmBvb095s+fr+lQSoyXlxfs7e2xfv16jcVgb2+P0aNHK6xbv3497O3tcerUKQ1F9V6XLl3QpUsXjcaQl3v37sHe3h5ubm6aDkVjpFIp+vXrhy+++ELToRARUQ6f4jVVYYwePRr29vaaDkMjfvzxRzg5OSEpKUnToZQ58+fPh729PUJCQkr0uLzeKl20NR0AEZUugYGBOHToELy8vBAWFob09HSYmpqifv366Nq1KwYMGABDQ0NNh1kko0ePxt27d+XLYrEYRkZGsLCwgL29Pdq2bYs+ffrA1NRU7cc+deoUFixYgOnTp2PGjBlq77+4denSBaGhoXj+/LmmQykUqVSKxYsXo27duujfv7/SNvHx8Th8+DCuX7+OoKAgJCUlwdDQEHXq1IGzszOGDh0KGxubEo688PJ7jsRiMb799ltMnz4dZ8+eRe/evTUQIRHRp+FTvKYCAC0tLZiZmaFRo0b48ssv0alTJw1FV/Y9ffoUrq6u+O6772BiYiJfHxISgq5duyq01dLSQoUKFVC/fn0MGzbsk/gbP3/+fLi6umLfvn1o3bq1psOR4/VW6cKkFxHJbdy4ERs2bIBUKkXTpk0xcOBAGBkZITo6Gvfu3cOvv/6KXbt24dKlS5oOVS0GDRoEW1tbCIKAlJQUvHv3Dj4+Prh48SJWr16Nn376CQMHDlTYp0mTJjh79izMzc01EzSAs2fPwsDAQGPHz8+ePXs0HYJS58+fh5+fH5YuXQqxOPcg5ytXrmDu3LlITExE9erV0bVrV1SqVAnJycl4/PgxNm7ciG3btuHvv/9GjRo1NHAG6vPZZ5+hdu3aWL16NXr16gWRSKTpkIiIyp1P9ZoKANLT0xEUFIRr167h2rVrWLRoET7//HMNR1g2rV69Gvr6+vjyyy+VbjcxMcFXX30FAMjMzERgYCCuXLmCW7du4fHjx5g3b15JhlvqzJ49GxMnToS1tXWJH5vXW6UHk15EBADYsmUL1q1bBxsbG6xZswaOjo652ty8eRNr1qwp+eCKyaBBg3L9KpSVlYVjx45h6dKlmD9/PnR1dRV+nTEwMECdOnVKOlQFmj5+fqpXr67pEJTav38/DA0N0aNHj1zb7t69i+nTp0MsFuOPP/7A0KFDc12YvHr1CkuXLkVqampJhVysBg0ahJUrV+LGjRvo2LGjpsMhIipXeE313oULF/Dtt99i69atTHqp4PXr1/D09MSgQYNgZGSktE2FChVyzRzw9PTEhAkTsGfPHowaNUqejPwUWVlZwcrKSmPH5/VW6cCaXkSEkJAQbNiwATo6Oti6davSizMAaN++PQ4ePPjR/oKCgvDXX39h8ODBaNOmDRo1agQXFxf89NNPePfuXa72giDAzc0NI0aMQNu2bdG4cWN07NgRY8aMwbFjxxTavn37FgsXLkT37t3RpEkTtGrVCr169cKCBQuU9l1YOjo6+PLLL7Fw4UIIgoA///wT6enp8u151fQqSFzz58/HggULAAAbNmyAvb29/D8vLy8A76c/yvp/8OABJkyYgFatWsHe3h6JiYkAlNf0ysnDwwOff/45mjVrBicnJ8ycORNv3rzJ1S6/+hgfnqes1khoaKg8Btl/OWPJq6ZXZmYmduzYgQEDBqBp06ZwdHTE8OHDceLECQiCkKu9vb09unTpgtTUVCxbtgydO3dGo0aN8Nlnn2Hbtm1K98nLq1evcP/+fbi4uOSaRiKVSrFw4UJkZ2djwYIFGDZsmNJf4urUqYPt27fnSjg+e/YMM2fORLt27dCoUSN06tQJP/74I96+fZurj/zqSuRVy0W2j5eXF86fP4+hQ4eiadOmcHJywnfffYeIiIhcfXzsOQKAPn36AABOnDiR30NHRESFxGsqxXMEgNjY2FzbTp06hRkzZqBr165o0qQJmjdvjhEjRhSq7mZmZiYOHDiAiRMnwsXFBY0aNUKrVq3w1Vdf4cqVK0r36dKlC+zt7ZGdnY0tW7age/fu8r/fK1asQGZmptL9AgMD8eOPP6JLly5o1KgR2rRpgxEjRmD37t252gYHB+Onn36Sx9SmTRtMmzYNT58+LfC5AZBfIxV2apyzszNq164NqVSKx48fAyjY9WVycjJWr16Nnj17onHjxmjZsiXGjBmDy5cv5zqG7Jpj9OjRiIiIwJw5c9CmTRs0adIEgwcPxtmzZ5XGJggCjh8/juHDh8PR0VE+CnLXrl3IysrK1V72fGVmZmL9+vXy52vx4sXo0qULXF1dAQBjxoxRuO6Rye/a6+LFixg9ejRatGiBxo0bo1evXli7di1SUlJytZVdM4eEhODIkSPo168fGjdujHbt2uGXX37Js94ar7dKB470IiKcOnUKWVlZ6N27NxwcHPJtq6ur+9H+Ll26hCNHjqB169Zo3rw5dHR0EBAQgJMnT+LKlSs4deqUQm2k1atXY+vWrbC1tUWPHj1QoUIFREVF4fnz53Bzc8Pw4cMBAJGRkRg6dCiSk5PRoUMHdOvWDVlZWQgLC8PFixfRr18/VKlSpWgPxv8bMmQINm3ahHfv3sHLyyvfehQFjatbt25ITEyEu7s7nJyc4OTkJO/jw1/hfH19sXXrVrRq1QpDhw5FVFSU0ml5H7p48SJu3LiBzz77DK1bt4afnx/Onz8PLy8vHDlyBDVr1lTp8ahQoQKmT5+OvXv3IikpCdOnT88z9g9lZWVh4sSJuHPnDmrWrIkvvvgCWVlZuHjxIn766Sf4+PhgyZIlSvf7+uuvERkZiY4dO0JLSwuXL1/GypUrkZmZqRBDfm7fvg0AaNGiRa5td+/eRVBQEKytrQv0K3TO1/+1a9cwffp0SKVSfPbZZ6hevTqeP3+OkydP4vLly9i7dy/q169foBg/5tChQ/Dw8ECXLl3QqlUrPHr0CGfPnoW/vz9Onz4NXV3dQj1Htra2sLa2xp07dyCVSgv02iIioo/jNdV/ZH9/GzdunGvbr7/+irp166JVq1awtLREfHw8rl27hnnz5iEwMBCzZ8/+aP8JCQlYvHgxHB0d0a5dO1hYWCAqKgpXrlzBlClT8Ntvv2HEiBFK950zZw58fHzQoUMHdOrUCdevX8eOHTsQGxub65rk6tWrmDlzJjIyMuDs7Iw+ffogKSkJAQEB2Lx5M8aNG6dwzlOnTkVmZiY6d+6MGjVqICIiApcuXcL169exadMmdOjQoUCP361btyAWi/NMnOZH9uPghz/k5XV9mZSUhJEjR+LFixdo0KABxowZg6SkJJw/fx7Tpk3DjBkzlF53JSQk4IsvvkCFChUwZMgQJCYm4ty5c/juu+8QGRmJsWPHKrSfN28eTp8+DWtrawwZMgTa2tq4cuUKli1bhps3b2Lr1q3Q1s6dopgxYwaePn0qf61WrVoVY8aMgaurK/z9/RWm1xbE2rVrsWnTJpiZmaFPnz4wMTHBrVu3sGnTJnh4eODgwYMwNjbOtd+KFSvg6ekJFxcXtG/fHl5eXjh27BiCg4Oxb9++XO15vVVKCET0yRszZoxgZ2cnHDt2rFD7vX37VrCzsxPmzZunsD48PFzIyMjI1f7GjRuCg4OD8Msvvyisd3JyEpydnYWUlJRc+8TExMj/vW/fPsHOzk7YvXt3rnYZGRlCcnJygeIeNWqUYGdnJ9y5cyffdt9//71gZ2cnrF27Vr7uzp07gp2dnbBu3TqV4jp58mSu/XOSbbezsxOOHDmitI2dnZ0watQohXXr1q2T73flyhWFbTt37hTs7OyE8ePHK6yXPQ7KKDtPQRAEFxeXPPeRbXdxcVFYt3XrVvnxc74uEhMThT59+gh2dnbCuXPncp2jnZ2dMGHCBCEtLU2+Pjo6WmjRooXQokULITMzM884cpo1a5ZgZ2cnPHjwINe2DRs2CHZ2dsKcOXMK1JdMSkqK0Lp1a8HBwUG4ffu2wrZjx44JdnZ2Qt++fQWpVCpfP2/ePMHOzk54+/Ztrv7yei/J9nF0dBT8/f0Vts2ePVuws7MT/v33X4X1H3uOZKZOnSrY2dkJz549+2hbIiIqmE/1mmrevHnCunXrhHXr1gkrVqwQpk2bJjRs2FDo06eP8PLly1z7BQcHKz3umDFjhPr16wthYWFKj/Nh+w/bCcJ/1xetWrVSuIYQhP/+Rg4aNEiIi4uTr09JSRG6desmODg4CJGRkfL1MTExQvPmzYUGDRoIt27dynWsd+/eKRzXyclJcHJyEgICAhTavXz5UmjWrJnQvn17pc/nh1JSUoT69esLPXv2VLpd9nr58JpLEN6/Nuzt7QUHBwchNDRUEISPX18uXLhQsLOzE+bPn69w7RIWFia0b99esLe3Fx4+fJjr+HZ2dsLMmTMFiUQi3xYcHCy0aNFCaNiwoRASEiJf/++//wp2dnZCv379hKSkJPl62fNuZ2cn7NixQyEu2fPVt29fhdevjOw6Ka9remXXXr6+voKdnZ3QoUMHITw8XL5eKpUKc+fOFezs7ITffvtNoR/Z669Tp07yx1QQBCErK0sYOXKkYGdnp/D45MTrLc1jqpGIEBUVBQBqK/JobW2t9NdLZ2dn1K1bFzdv3sy1TUdHR+kvOxYWFrnW6evr51qnq6ubZ70DVckeD2XD8pVRZ1z169dXqf5FmzZt0LlzZ4V1Y8aMQZUqVeDp6akwHa6kyIZ0y2qkyZiYmMh/yT1+/LjSfX/++WeFx7VixYro2rUrkpKSEBQUVKDjh4WFAQAsLS1zbZO99gt7V8bLly8jLi4O3bt3R5s2bRS2DRs2DA0bNsSLFy/w4MGDQvWbF2VTUYcNGwYA8qkLhVWpUiUA/z0+RERUdJ/qNZWrqys2bNiADRs2YPv27bh06RKMjIzQt29fVKtWLVd7ZTVAdXV18eWXX0IikeDOnTsfPaaurq7Sv98mJiYYMmQIEhIS8vwb+f3338PMzEy+bGhoiH79+kEqleLJkyfy9W5ubkhOTsbw4cPRtm3bXP1UrlxZoW18fDymTZuGunXrKrSrU6cOhg8fjqioKPkIuPxERERAIpEovXbJKTExEevXr8f69euxatUqTJs2DZMmTYIgCBg7dmyu0XrKri+zsrJw+vRpGBgY4IcfflAYHWZjY4PJkydDEASlU/S0tLQwZ84chRFM1atXx8iRI5GVlYUzZ87I18uu9ebMmaMwikpXV1de/uPDKbgyM2fOVPr6VYXsPCZPnqzwPhWJRPjhhx+gr68PV1dXpdMtp02bpvCYamtrY/DgwQCAR48eKT0er7c0j9MbiUjtBEHAmTNn5EOOExMTIZFI5Nt1dHQU2vfr1w/79+9Hr1690LNnT7Rs2RKOjo4KFyPA+3n9q1atwu+//44bN27A2dkZjo6OsLOzK5bhwkIeQ8M/VBxxNWnSRKX9WrVqlWudtrY2HB0d8e7dO/j5+ZXoHWySk5MRHByMSpUqoV69erm2yy4gldW5MDExUXqnRNkFrqwGxcfExcUBeD9FU138/PwAIFfCS6Zt27Z4+vQp/Pz8VJqW8CFlU0NkF9oJCQkq9Sl7f8keHyIiKn3KyjXVvn375IXss7KyEBoair1792L16tW4ceMG9u/fr9Dvu3fvsH37dty+fRthYWEK9VMBFPhHuoCAAOzcuRPe3t6IiopCRkZGgfpp1KhRrnXK/q7KfrwqSBHy+/fvAwCeP3+eq/YrAPmPda9evcq3bAYAxMfHAwBMTU3zbZeUlIQNGzYAAMRiMSpUqAAnJycMGzZMXk8qJ2XXl4GBgUhLS0PTpk2VJpbatWsHQPm1WuXKlZUmNVu1aoWtW7fi2bNn8nWya6cPb3gAAA4ODqhYsSJev36NlJSUXElXVa+LlcnvGq5SpUqws7PDo0eP8Pr161zXrgV93eTE6y3NY9KLiGBpaYlXr16pbRTQkiVLsHfvXlhaWsLZ2RnW1tbyXxJdXV3lhbZlFixYgOrVq8PV1RU7d+7Ejh07IBaL0bZtW8ydO1deE8PW1hYnTpzAxo0bcePGDXlhzUqVKmHUqFGYNGkStLS01HIOwPt6F8D70UX5KY64ZL8KFVZe+8nOIa9Cm8UlOTkZQN5xGRgYwMTERGlceSWpZL9e57zoz4/staesOK3sF9Tw8PAC9SUjizevX2Bl6wuamPsYExOTXOtkrympVKpSn7IvGMp+5SciItXwmup9Iq5mzZr43//+B39/f9y7dw9nz55F3759AbwvoD906FAkJiaiZcuWcHZ2hrGxMbS0tBAaGgpXV9c8C8rn9ODBA3z11VeQSCRo06YNunTpAmNjY4jFYjx79gzu7u559qPsGkPZ31XZ3/uC/GAoS1R9rGh5Qe4ELXuOP0zifcjW1hYeHh4f7U9G2fWY7BzzulaTXdMou1bLax/Z+pz7JCUlwcTEJM/rDktLS8TExCA5OTlX0utjI94KoyjXcKpcj/F6S/OY9CIitGjRAnfu3MHt27flU6ZUFRMTg/3798POzg6HDx/OVQTyn3/+ybWPlpYWxowZgzFjxiAuLg7379/HxYsXcfr0aYwbNw5nz56Fubk5gPfDw1etWgWJRIIXL17gzp07OHjwINasWQOJRFLg4uYfI5VK4e3tDaBgvy6pO66PjS7LS3R0tNL1MTExABT/WMuOkZ2dnWsahLqSY7LnP6+40tLSkJSUlOsXaHWSJfzi4uJy/YIpK25/9+5dSCSSAl/gyx5H2TSWD8nWK3u8lSXrSjoZCfx3ca6u6QJERMRrqg81bdoU9+/fx6NHj+RJr927dyM+Ph5LliyRTw3LeU6yO/J9zObNm5Genq4wykxm69atcHd3L3L8sr/jERERaNCgQYHanjp1Cg0bNizScWV/m2V/q9VF2fWlLO68rtVk1zTKCrvntY9sfc7rIBMTE8THxyM9PV1pAii/46h6XaxMzms4ZclPZddwRcHrLc1jTS8iwuDBg6Gjo4OLFy/ixYsX+bb92C9vb9++hVQqRfv27XP90QoPD1d6y+CczM3N0bVrVyxbtgx9+vRBbGwsfHx8crXT0tJC/fr1MW7cOGzfvh0AlN5SWVUnT55EWFgYrK2tlQ7DzsvH4pIN7S/oKKXCkiXqcsrOzoavry8AKFywyYbMK6sxkFcNjMLGb2xsjBo1aiA6OhovX77MtV1Ws0PZcHF1kdXCUlYDzMnJCbVq1UJERESedcVykr3+ZY+jl5eX0nay88p50avK462Kgj5HgYGBEIlEuWqFERGR6nhNpUg25SvnKJjg4GAAQPfu3XO1v3v3boH7Dg4OhpmZmdLrtML0k59mzZoBAK5fv17gtvfu3Svyca2srGBhYYHXr1/Ly20Ul9q1a8PAwAAvXrxQWsdWVoNM2bVaWFiY0teh7Ho0512s87t2evHiBWJiYlCzZs1C1ZOTXfMUZtR7fnHExMQgICAAhoaGqFWrVoH7zA+vtzSPSS8iQtWqVTF9+nRkZWVh8uTJePjwodJ2d+7cwejRo/PtS3a7YB8fH4Uv3SkpKfj555+RnZ2t0D4zM1PpxYEgCPLRSQYGBgCAJ0+eKB1qLPs1SR3DhrOysnDo0CEsWrQIIpEIP/74I/T09PLdpzBxyX5dLa5ilnfu3MHVq1cV1u3btw/v3r1D+/btFYbny0awHT58WKH9s2fPlN52GfivLsG7d+8KHNPQoUMBAEuXLlUoCpqcnIxVq1YptCkOTk5OAKC0qLxYLMaiRYugra2NP//8E66urkovLl+/fo3Jkyfj1atXAIBu3brBzMwMFy5cyJVoPHXqFJ48eYJ69erJL4CB/x7vo0ePKhwjJCREXo9DHQryHGVmZuLZs2ewt7eXvyaJiKjoeE31n5CQEFy6dAmAYh0n2Xl9mJi6cePGR6cG5mRra4v4+Hj4+/srrD9+/Dg8PT1VDVvBwIEDYWxsjGPHjiktrp+zPMLgwYNhamqKTZs2yX9szEkQBNy7d69AUzdFIhFatWqFhIQEBAYGFu0kPkJHRwf9+/dHWloaVq1apXCNEhERga1bt0IkEmHIkCG59pVIJPjrr78Ukk5v3rzBoUOHoKOjg379+snXy671Vq9ejZSUFPn6rKwsLF26FAAKPTpSletS2Xls3bpVYcS+IAj466+/kJaWhoEDB+aql6cKXm+VDpzeSEQAgClTpiA7OxsbN27E8OHD4ejoiEaNGsHIyEj+y+CrV69Qs2bNfPuxtLREnz598O+//2LgwIFo3749kpKScOvWLejq6qJ+/foKRS3T09Px5Zdfolq1amjUqBGqVKmC7Oxs3L17F8+ePUOzZs3kF0qnT5/GkSNH0Lx5c9SoUQNmZmYIDQ2Fh4cHtLS0MGHChEKds6urq/yCKzU1FaGhobh37x5iYmJgamqKP//8Ez179vxoP4WJy9HREYaGhvj333+hra2NKlWqQCQSYcCAAfKLwKJwcXHBtGnT0L17d1SrVg1+fn64ceMGzMzMsHDhQoW2Q4YMwa5du7Bz5048f/4c9vb2CAkJgYeHB7p3745///03V//t27fH48ePMWPGDHTq1Al6enqoUqUKBg4cmGdMY8eOxY0bN3Djxg3069cPLi4uyMrKwsWLFxEREYGBAweiV69eRT73vLRp0wYVKlSAp6cnvv/++1zbnZycsGHDBsydOxfz58/H5s2b0bp1a1hYWCAlJQVPnz7Fw4cPoaOjA0NDQwDv7/K0dOlSzJgxA+PGjZM/3s+fP8fVq1dRoUIFLFu2TGE4frdu3VC7dm2cPXsWYWFhcHR0RGRkJDw8PODi4qL08VZFQZ6jO3fuICsrS+mv7EREVDSf+jVVdnY2QkND4e7ujtTUVLi4uKBbt27ytiNHjsSpU6cwc+ZM9OjRA1ZWVggICMCNGzfQq1cvnD17tkDH/Oqrr+Dp6YmRI0eiV69eMDExwZMnT+Dj44MePXrgwoULhToHZSwsLLBy5Up8++23GDduHJydneHg4IDU1FS8ePECz58/l5+3mZkZ1q1bh2nTpmHEiBFo06YN6tWrB21tbYSFheHRo0d49+4dvL29ld6R80Pdu3fHhQsX4OnpiTp16hT5XPLz/fffw8fHB8ePH4efnx/atWuHxMREXLhwQX5HyqZNm+baz97eHo8ePcKQIUPQvn17JCQk4Ny5c0hKSsKCBQtQtWpVeds+ffrAw8MD//zzD/r06YNu3bpBR0cHHh4eeP36Ndq2bYuxY8cWKu727dtj586dWLVqFQICAuTTFadOnZrnPo6Ojpg8eTK2bt2Kvn37omfPnjAxMcGtW7fw9OlT2NnZYc6cOYWKIy+83iodmPQiIrnp06ejV69eOHz4MLy8vODq6or09HSYmprCwcEBo0aNwqBBgz7az+LFi1GtWjWcPXsWBw8ehIWFBbp06YJvv/0W3377rUJb2e2Rvby88PDhQ3h4eMDAwAC2traYP38+Pv/8c3m9qb59+yIrKwu+vr7w9/dHamoqrKys4OLigrFjxxb6zi6ymhFisRiGhoaoWLEimjdvjvbt26N3794fvWOOTGHiqlChgvyW3mfPnpUXM23RooVakl7du3fHsGHDsHXrVly5cgU6Ojro0aMH5syZk+tOiBYWFjhw4ABWrFgBb29v3Lt3D/b29lizZg1MTEyUJmGmTJmC5ORkuLu7Y8eOHcjOzoaTk1O+SS9dXV3s3LkTe/bswd9//42DBw9CLBajXr16mDFjRrGO8gLev8YGDx6MPXv2wN/fX17ENycXFxdcvHgRR44cwfXr13Hx4kUkJyfDwMAAtWvXxpQpU/D5558rjJRzcXHB0aNHsXXrVty+fRsXLlyAhYUFBg0ahKlTp+a6m5Guri727NmD5cuXw9PTE0+fPkXNmjXx448/om3btmpLehXkOXJzc4OOjg6GDx+ulmMSEZGiT/WaCng/SsnExAT169fHgAEDMHToUIUfgRwcHLBv3z6sWbMG165dQ3Z2NhwcHLBhwwaYmJgUOOnVsWNHbNmyBZs3b8bZs2ehpaWFJk2aYN++fXj79q1akl4A0LlzZ7i6umL79u24desWbt++DWNjY9SsWTNXcqVNmzb4+++/sWvXLty4cQO+vr7Q0tKClZUVmjVrhjlz5iitWaVM9+7dUalSJbi5ueGrr75Sy7nkpUKFCjhy5Ai2b9+OCxcuYM+ePdDV1UXDhg0xevToPJM2pqam2LZtG1asWIETJ04gJSUF9erVw9dff6307pErVqxAq1atcOLECZw4cQJSqRQ1a9bEDz/8gDFjxuSqMfsx7du3x08//YSjR4/i4MGD8lF0+SW9AGD27NmoX78+Dh48iL///huZmZmoWrUqpkyZgokTJxb4OfoYXm+VDiKhuCcJExERaVhISAh69eqFIUOG4Ndff9V0OBoVHR2NLl26oE+fPliyZImmwyEiIqI8bNu2DStXrsTx48cLnYgsTiEhIejatSucnJywf/9+TYdTKvF6q/RgTS8iIir3qlatirFjx+LEiRMfLfxb3m3evBlaWlr47rvvNB0KERER5eOrr76Cra0t1qxZo+lQqJB4vVV6cHojERF9EiZPngw9PT28e/dOocbEp0QqlcLKygorVqyAlZWVpsMhIiKifOjp6WH58uW4c+cOkpKSYGJioumQqAB4vVW6cHojERERERERERUIpzdSWcKkFxERERERERERlTus6UVEREREREREROUOk15ERERERERERFTuMOlFRERERERERETlDu/eWAx8fHwAAGIxc4pERERE6iKVSgEALVq00HAkREREVBYwK0NUBkilUvmFPhFRWcLPLyIiIiLSFI70KgayEV6Ojo4ajoTKC39/fwCAg4ODhiMhIiocfn6ROvn6+mo6BCIiIipDONKLiIiIiIiIiIjKHSa9iIiIiIiIiIio3GHSi4iIiIiIiIiIyh0mvYiIiIiIiIiIqNxh0ouIiIiIiIiIiModJr2IiIiIiIiIiKjcYdKLiIiIiIiIiIjKHSa9iIiIiIiIiIio3GHSi4iIiIiIiIiIyh0mvYiIiIiIiIiIqNxh0ouIiIiIiIiIiModbU0HQEQfV716dU2HQERERERERFSmMOlVDqSmZ+F1WKKmw6ASkabpAKiY1KxcAYb6OpoOg4iIiIiIqNxg0qsceB2WiHkbPDUdBhEVwbLpzmhQq6KmwyAiIiIiIio3WNOLiIiIiIiIiIjKHSa9iIiIiIiIiIio3GHSi4iIiIiIiIiIyh0mvYiIiIiIiIiIqNxh0ouIiIiIiIiIiMod3r2RqIRNHdIEvdrVUljXb87pIu8za4QjuraqXqAY1hy5D3fvtwVqS0RERERERFQWcaQXUQlq4WCVK3lVHPt8jCCotTsiIiIiIiKiUocjvYhKiImhDmYMdyy2fa77hiI4PFHptu6ta6KqlTEAICtbggcvogoVBxEREREREVFZw6QXUQmZOqQpKprqIzk1Ey9DEtDMzlKt+9x/Hon7zyNzrbeooI/RverLl6/4hCA2MV21kyAiIiIiIiIqIzi9kagEdGpeFc7NbAEAW049QkxCWrHso8zATnWgo60FAJBIBZz0CFCpHyIiIiIiIqKyhEkvomJW0VQfUwY1BgDceBCKa76hxbKPMkYGOujRpqZ8+c7jMLyLTlGpLyIiIiIiIqKyhEkvomI2c4QjjA11EZOQhk0nHhbbPsr0aV8Lhvr/zWI+wVFeRERERERE9Ilg0ouoGPV1rgVHOytIpQLWHvVFclpWseyjjK62GP2ca8uXH7yIwsuQeJX6IiIiIiIiIiprWMieqJgYG+hgbJ8GAICzt4Lg+/zjd0xUZZ+8dGtdA2YmevJljvIiIiIiIlKdIAiQCgJEEEEsFhW5P6kgQBAEiEUiiERF74+IcmPSi6iYGOprQ0/3/Vusr3Nt9M0x6upDf68cAAD4duWVQu8z4qd/kZKerbBNLAIGdaojXw54E4eHAaon0IiIiIiIyrv3CS3kSkBJJFIkpGQiJj4NMYnpiE1MR2xCOuKS0hGXmIGMbAkkEgHZEqn8/9L/T2Zpid8nyMTi9//W19WGmYkeLCrow8xED+YmejCvoI+KpvowN9GHgV7ur+gSqQAtNSTZiD5FTHoRlUMdmtnCpqKRfPnEFY7yIiIiIiKSkUoFiET/JbjSMrLxKiQeL0Pi8SY86X1i6///S0zJhCCUTFx6OlowM9GDmYkeKprqo2blCqhja4a61cxgUUFf3o6JMKKCYdKLqJikZ0pw8+E7pdvqVjODtYWhfFnWLjktq9D7ZEty/wUe7FJP/u+QyGTcfhxW+BMgIiIiIioHlCW4Xr6Nw8uQBLwMicfLt/EIi0kpscRWfjKyJIiITUVEbCoA4Naj/67jTY11UdvWFHVszVDH1hR1q5kp/NAtlQpqmXZJVJ4w6UVUTBJTMrF0n7fSbbNGOMLaorp8OWc7VfbJqYWDFWrbmsqXXa8GlIo/4EREREREJSVnAuhlSDwev4rGy5B4vHqbgPDY0pHgKqyE5Ez4Po9SqPtrqK+NWlVMUbeqKRrXrQRHOyvo6mjlOVWT6FPDpBdROTMkxyivmIQ0eNx7q8FoiIiIiIiKnyAIEACIRSJkZEng+zwSd5+Gw/tZBOKTMjQdXrFJTc/G08AYPA2MwenrgdDVFqNx3UpwamADp4Y2qGRmAICjwOjTJRKEspjjLt18fX0BAI6OjiVyPL+gGMzb4FkixyKi4rFsujMa1Kqo6TCI1M7f3x8A4ODgoOFIqDwo6WssIirdciZyYhPTcedJGO4+Dcfjl9HIzJZqOLrSoYaNCVo1sIFTAxvY1zCHWCxiAow+KRzpRURERERERGWCbMyGSCRC4LsEeD0Jw12/CASGJmg4stIpODwJweFJOOERgApGumhub4VWDazRulFl6OloMQFG5R6TXkRERERERFSqyZIziSmZuOgVjEt33yAsOkXTYZUpiSmZuHo/BFfvh8BATxsdmtmie+vqsK9hoZBMJCpPykzSSyqVYsSIEXj48CGcnJywf/9+he3Z2dnYtWsXTp48idDQUJiZmaFr166YNWsWzM3Nc/UXFxeHNWvWwN3dHfHx8bC1tcWQIUMwfvx4aGuXmYeFiIiIiIioXJIlYgQB8PGPwEWvYHj7RUAiZYWeokrLyMZFr2Bc9ApGdWsTdHOqjm6tqsPESJejv6hcKTPZnb179yIgICDP7QsWLMCZM2fg4uKCr7/+GiEhIdi7dy/u3buHo0ePwtjYWN42OTkZo0aNQlBQEEaOHAl7e3t4e3tj5cqVCAgIwIoVK0rilIiIiIiIiOgDsqRLSloWzt1+jXO3XiMqPk3TYZVbbyKSsOvvp9h/7hmcm9qif4faqFvNjMkvKhfKRNLr7du3WLt2Lb777jv8+eefubbfvn0bZ86cQZcuXbB582b5+oYNG+Lbb7/Fzp07MXPmTPn6nTt34uXLl5g/fz7GjRsHABg2bBhMTExw4MABDB48GG3bti3+EyMiIiIiIiIA/yW73kQk4cz1V7h2P4QF6UtQVrYUV3ze4orPW9hVN0ff9rXQwdEWWmIRpz1SmSXWdAAF8fPPP6Nu3boYPXq00u2nT58GAHkCS6ZHjx6wtbWVb8/Z3sDAAF988YXCetn+H7YnIiIiIiKi4iH9/+mKz17HYMEmT8z46wou3X3DhJcGvXgTh1WH7+PrPy7h35tByJZIIRU4rZTKnlI/0uvYsWO4d+8eTp48CbFYeY7u4cOHEIvFaNasWa5tjo6O+OeffxATE4OKFSsiOjoaoaGhcHR0hL6+vkLbqlWrwtLSEo8ePSqOUyEiIiIiIqL/JxvZ9TosEXv/9cP955GaDok+EJuYjq2uj+F69SW+6O6ALi2rAQCnPVKZUaqTXhEREVi+fDnGjRsHBweHPNuFh4fD3Nwcurq6ubZZW1vL21SsWBHh4eEAABsbG6V92djYIDAwsMixS6VS+Pv7F7mfj6levXqxH4OISkZqairevHmj6TCI1Cot7X0NlpL4m0jln1QqzfNHUCIqO2TJrojYVOw754ebD9+Bg4hKt8i4NKw96ouTVwIwqqcD2je1Zc0vKhNKddLr119/hbm5OaZPn55vu/T0dJiamirdpqenB+C/i+709HQAUJogk7WXtSEiIiIiIiL1EAQBIpEI8ckZOHjeH+7eb3gnxjImJDIZS/fdQx3bAIzqVR8t61sz+UWlWqlNev3777/w8PDA7t27c01D/JC+vj4yMzOVbsvIyAAAGBgYyNsCyLf9x45XEGKxON/RaerFO5kQlQeGhoYl+LlBVDJkI7z42iZ18PX11XQIRKQCWbIrJS0Lx9xf4F/PINbrKuNehSbgtx130KCWBcb0ro+GtSsx+UWlUqlMemVmZuKPP/6As7MzbG1tERwcrLA9PT0dwcHBMDQ0hKWlJWxsbPD69WtkZmbmGsEVEREB4L/pjLL/y6Y5fig8PDzPqY9ERERERERUcFKpAIlUwMkrL+B69SVS07M1HRKpkV9QLOZvvInm9laYOrQprC0MNR0SkYJSmfRKT09HbGwsPD090b1791zbHz16hO7du6NHjx5Yt24dmjRpgsDAQDx8+BCtWrVSaOvr6wtbW1tUrFgRAFCpUiVUqVIF/v7+SE9PVxjVFRoaiqioKDg7OxfvCRIREREREZVjstFdL97GYe0RX4REJms6JCpG959HYtpyD3zZ0wEDOtYBwGL3VDqUyqSXgYEB1q5dq3TbzJkzUbduXcyYMUM+ImvAgAFwc3PDrl27FJJeFy9eRGhoKL755huFPvr3748tW7bg8OHDGDdunHz97t275f0RERERERFR4UmlArIlUuz91w//eAaCZbs+DRlZEuz6+yk8H77DrBGOqGZtIk9+EmlKqUx66ejooGfPnnlut7CwUNjerl079O3bF//88w+mTJmCrl27IiQkBHv27EHt2rUxYcIEhf0nTpyICxcuYMWKFQgNDYW9vT28vb1x+vRp9O3bF23bti22cyMiIiIiIiqPZAkOv6AYrDv6AGExKZoOiTTgxZs4fLvyKj7vZodhXetBJOKoL9KcUpn0UsXSpUthZ2eHU6dO4bfffoOZmRkGDBiAWbNmwdjYWKGtsbExDh06hDVr1uD8+fM4cuQIbG1tMXv2bIwfP15DZ0BERERERFQ2SaUCsrLfj/Q5d/s1BI7u+qRlS6Q4eMEfNx+9w8wRjqhb1YyjvkgjRILAjyN1k91ZyNHRsUSO5xcUg3kbPEvkWERUPJZNd0aDWhU1HQaR2vHujaROJX2NRaWbt7c3/vrrLwQEBCAlJQULFizA2LFji+14ISEh6Nq1K6ZPn44ZM2aopc8tW7Zg586duHz5MkxNTVXqY9SoUdDT08POnTvVElNhSQUBYpEID15EYf0xX0TG8c7ypEgsFmFgpzoY1bM+tMQijvqiElVuRnoREREREZFmyRJDMiKRCIaGhjA3N4ednR06d+6Mvn37wsjIqEjHSUhIwLRp02BtbY25c+fCwMAAjRo1Kmr4Klm/fj3q16+Pbt26FWq/iIgIbN26Fd98841CwisyMhIHDx6En58fnj17hqioKDg5OWH//v1K+/nuu+8wcuRIXLlyBS4uLkU6l8KSSgVkZEmw4/RjXPR6U6LHprJDKhVw6spL3Hkchtkjm8O+hoWmQ6JPCJNeRERERESkVi1btsTw4cMBvL8ze1hYGO7cuYOFCxdi06ZNWLVqFVq0aKFy/48fP0ZCQgL++OMPpXd7L0kbNmzAoEGDCp302r59OwRBwMiRIxXWBwUFYcuWLbC2tkbjxo3h4eGRbz8tWrRAs2bNsH79+hJNegmCgJDIJPy+ywvhMakldlwqu95Fp2D+Rk9MHNgYvdvV4nRHKhFMehERERERkVpVq1ZN6R3Rr1+/jpkzZ2Ly5Mlwc3ND1apVVeo/OjoaAFSeEqhpKSkpcHV1Rffu3XPVH27YsCFu3bqFihXflz2wt7f/aH+DBw/GwoUL8eDBAzRr1qw4QpaTJSpuPw7D6sP3kZ4pKdbjUfmSLRGw+eQjvAqJxzdDmkLMIvdUzMSaDoCIiIiIiD4NHTt2xA8//ICkpCRs27Yt13YPDw989dVXaNmyJRo3bow+ffpg165dkEql8jb29vaYN28eAGDMmDGwt7eXJ4akUim2bNmC0aNHw9nZGY0aNUKHDh0wb948vHv3Ltfx7O3tMX/+/FzrQ0JCYG9vj/Xr1+d5Ll5eXvLjurq6yuOwt7dHSEhIvo/DjRs3kJycjM6dO+faZmxsLE94FZSsn3/++adQ+xWWVPo+4bX/3DMs3efNhBep7KLXG8zf4ImElAxIWWacihFHehERERERUYkZPHgw/vzzT1y5ckVh/datW+XTHqdMmQIjIyPcu3cPy5cvx9OnT7Fy5UoAwPLly+Hj44OjR49iypQpqF27tryPrKwsbN++Hd27d0enTp1gYmKC58+f4+TJk7h9+zbOnDkDMzMztZxHnTp1sHz5csydO1dhOicAWFjkX7PIy8sLANC0aVO1xGJtbY0qVarI+y0OsvpdKw7cg7dfRLEdhz4dz9/EYebKq1gw1gn1a7LOFxUPJr2IiIiIiKjE6Ovro1atWnjx4gVSUlJgZGQEf39/rF69GiNGjMBvv/0mb/vFF1/AwcEBf/31F0aMGIFWrVphwIABkEgkOHr0KNq1a4fWrVvL2+vq6sLT0xMGBgYKx+zWrRvGjRuHEydOYMKECWo5j0qVKmHAgAGYO3duntM58/Ly5Uvo6OjA1tZWLbEAQI0aNXD37l1IpVKIxeqd0CMIAsJjUvD7Li+ERCartW/6tMUlZeDHTZ6YOKAxerevJb8bKJG6cHojERERERGVKFkdq+Tk9wmU06dPQxAEDB8+HLGxsQr/ye4G6enp+dF+RSKRPOEllUqRmJiI2NhYODg4wMTEBI8ePSqmMyqc2NhYtdcjMzMzg0QiQXx8vFr7BQAf/wjMXnONCS8qFtkSAZtPPcK6o76QSgVIpZzuSOrDkV5ERERERFSiZMkuWfLr1atXAN5PfcxLVFRUgfq+fPkyduzYgSdPniArK0thW3EkhFQlqLmOkbr7k424OXb5BQ6efwbmIai4Xbr7BsHhSfh5vBNMjfRY4J7UgkkvIiIiIiIqMenp6QgKCoKVlRWMjIwAQF6ofuPGjTA0NFS6n5WV1Uf7vnz5MqZNm4ZGjRphwYIFqFy5MvT19QEA3333XYETQxJJ8RZot7CwwOvXr9XaZ3x8PLS0tGBubl7kvqRSAQKAVYd9cMUn/6L8ROr04k0cvl97HYu/aQ8rc0MmvqjImPQiIiIiIqISc+rUKWRlZcHFxUW+rmbNmrhx4wYsLS2LVNzdzc0Nenp6OHDggEJdr9TUVCQmJuZqb2ZmpnT015s3b1SOoSDs7e1x9+5dvH37FtWqVVNLn8HBwahbty5ERayHJJUKkAoClu27hztPwtQSG1FhRMalYe76G/hjSjtUszYp8muaPm2s6UVERERERCXi+vXrWLFiBUxMTDB58mT5+oEDB0IkEuGvv/5CZmZmrv3S09PlUyLzIxaLIRKJ5CPHZDZt2pRrHQDUqlULvr6+SE1Nla+TSCTYuXNngc/J0NCw0NMmZcX3fX19C7VfXiIiIhAWFqZQ1F8VUqmAbIkUi3beYcKLNCouKQPzNngi4G282qfu0qeFI72IiIiIiEit3r59i9OnTwMAMjIyEB4ejlu3bsHX1xc2NjZYtWqVwp0LGzVqhNmzZ2PlypXo3bs3+vXrhypVqiAuLg6BgYG4dOkSNm3a9NGkTs+ePXHhwgWMHj0agwYNgiAI8PT0xMuXL5VO+/vqq68wa9YsjBo1CoMGDUJGRgbOnTsHHR2dAp+ro6Mjbt26ha1bt8LW1hYikQguLi55TtMEAGdnZ1SoUAFXr15F//79c23ftGmTwnJoaKh8XZUqVTBw4ECF7R4eHgCAPn36FDjuDwlSKUQANhx/CN/nBaufRlScktOy8POWW/jl69ZoXKeSpsOhMopJLyIiIiIiUqt79+7h3r178rspmpubw97eHosWLULfvn3ltbxymjRpEho3boy9e/fi8OHDSE5OhpmZGapVq4YJEybA3t7+o8ft3bs3UlNTsXfvXqxYsQJGRkZo164dDh06hJEjR+Zq36tXL8TExGDv3r1YtmwZLC0tMXDgQPTv3x89e/Ys0Ln++uuvWLRoEbZv346kpCQAgLu7e75JLwMDAwwePBiHDx9GYmIiKlSooLB97dq1CsuhoaHydU5OTrmSXm5ubmjYsCGaNWtWoJg/JEilELIyINLWwbShjeEXFIOI2NSP70hUzNIysvHb9jv434TWaFzXUtPhUBkkElQcK5icnIy4uDjY2Ngo/BJy+vRpXL58GQYGBhgzZgwaNWqktmDLCtkwZUdHxxI5nl9QDOZt+PgtnImo9Fo23RkNalXUdBhEaufv7w8AcHBw0HAkVB6U9DUWUXGKjIxEjx49MGnSJHzzzTcq93Pv3j18+eWX2LJli0KdtIJ6n/BKR9jBX6FlbA7roXORkSXF1OUeiIpPVzkuInXS09XC/ya04YgvKjSVa3qtXLkS/fv3V7gN8JEjRzB//nxcunQJZ86cwejRoxEUFKSWQImIiIiIiMoLKysrTJ48Gbt27UJCQoLK/axZswbOzs6qJ7yyMxF2aBEywl4hNeAeIk+tgp6OFjb+0AUWFfRVjotInTIyJfhtxx08fhXNGl9UKConvXx8fNC6dWuFYbvbt29HxYoVsXPnTixduhTZ2dnYvXu3WgIlIiIiIiIqT6ZMmQJvb2+Ympqq3MeBAwcKVXhfRpBKAakE4ceWIONdgHx9yvM7iHRbDX1dLWye5wJzEz2VYyNSJ1ni62lgDBNfVGAqJ70iIyNRtWpV+XJgYCBCQ0MxatQotG/fHgMHDoSLiwu8vLzUEigREREREREVnSxhEHHqL6QHP8m1PeXZLUSeWQsDXW1sntcFFYx0SzpEIqUyMiX4Y5cXQqOSIZUy8UUfp3LSKzU1VaEA5YMHDyASidCuXTv5upo1ayIyMrJoERIREREREZFaCIIAkUiE6LObkRpwL892KU89EfXPBhjq62Dr/C4wMSz4HS2JilNKejZ+3X4HKWlZTHzRR6mc9LK0tMSbN2/ky7dv34a+vj4aNGggX5ecnFyo2/0SERERERFR8RGJRIi9chBJDz0+2jb58TVE/7sJxoZ62Dq/K4z1tUsgQqKPi4hNxe+7vCAVBCa+KF8qJ72aNWuGq1evwsPDAzdv3sTFixfRtm1baGv/90EYEhICa2trtQRKRERERERERZP4wB3xt04VuH3SQw9End0CEyM9bFnQFYZMfFEp8ex1LNYc8YVYLNJ0KFSKqZz0mjRpEqRSKaZNm4YJEyYgOzsbU6ZMkW/PyMjAvXv30KRJE7UESkRERERERKqR1fHS0jeCSKdwxemTfC8h+vx2mBrrY+v8rtDXVflrJJFaXbsfgsMX/TUdBpViKqfp7e3tcezYMbi5uQEAevXqpZDg8vPzQ9u2bdGnT58iB0lERERERESqkUoFRCekITw6BU0c2qCKmTXCj/0JSVJsgftI9DkPiLVQqft4bJ3fDRP/vIzMbGkxRk1UMIcuPEcVS2N0cqz68cb0ySnS2FR7e3vMmzdP6TZHR0ds3LixKN0TERERERFREUilArIkUvy+0wuvwxIxtm8DDO5UB7bjVyD82J/IDHtV4L4Svf+FSEsbFbuOwdYFXTFpiTuymPiiUmDtEV/YWBiiXnVziEWc7kj/4bhUIiIiIiKickosFmHVQR+8DksEAOz5xw8rD92HyMAEVcb8ASOHNoXqL+HOacReOYhKZobYMr8rtLX5lZI0Lytbij923UVMfBoL25OCIlchfPz4MR49eoTExERIJJJc20UiEaZNm1bUwxAREREREVEhHbn4HLcehymsu+YbircRyVg2vT2sh/yA2KuHEH/zZIH7jL91ChBrwarTCGye2wXfLL0MDvgiTYtPzsCv2+9g1XedoCMSc8QXAShC0is5ORnTp0+Hl5eXvCiiMkx6ERERERERlSypVMDToBgcyqPId+C7BIz/4xLWzemMSp1HQqdSVUT/swmCJKtA/cd7HodISws2zsOwcW5XfLPcHVImvkjD3kQkYYfbY0wb1kzToVApoXLSa/ny5bhz5w5atmyJwYMHo3LlytDS0lJnbERERERERFRIUkFARpYEqw/fRz7jE5CUmoWvF1/C4int0ahRR+iY2yDi+FJIUhIKdJy4a0cgEmujSrtB2Ph9F0z7y4OJL9K483eC0bqRDZo7WHO0F6me9HJ3d0eDBg2wb98+iMWcx01ERERERFQaiEUibHV9jKi4tI+2lUqBBZtuYvKgxujTvu77AvdHFyMzMrhAx4q9cgAQa6Fqm/5YN9sF0/+6UtTwiYps7dEH2DS3C4z0dSAWM/H1KVM5W5WUlITWrVsz4UVERERERFRKSAUBXk/C4O79plD7bXV9jA3HH0JsZIYqY5fAsF7LAu8b674XCXf/RY3KFbB2dudCRkykfvFJGVh/7AETXqR60qtGjRqIiYlRZyxERERERESkIqlUQEpqFjYcf6jS/he93mDeppvIFrRgPWw+TFv3L/C+MZd2IcHnPGrbmmL1rE4qHZ9InW4/fp/8za8GOZV/Kie9vvzyS1y5cgURERHqjIeIiIiIiIhUIBaLsP74A8QnZ6jch//rOEz48zLikzNQsdtXqNRnKiAuWFWcmPM7kOh7CXWrmeGvbzuoHAORumxze4yYhHRIpUx8fapUTnp17NgR7du3xxdffIGTJ0/C398f7969U/ofERERERERFR9BEOBx7y1uPw4rcl9xSRkYv+gCXryJQ4VmXVF55EKIDYwLEgWiz25F0kMP2NewwNJpzkWOhagoUtOzsfKgD1jP/tOlciH7Ll26QCQSQRAE/Pzzz3m2E4lE8PPzU/UwRERERERElA+pVEBcUjq2uT5SW5/ZUmDO2uuY+XkzdG3VALbjlyP8yGJkxYR+ZE8BUf9uBsRaaNi4ExZPaYefttxSW1xEhfUkMAauV19isEs9TYdCGqBy0qtVq1bqjIOIiIiIiIhUIBaLsOaIL1LSs9Xe99qjDxAYmoAJAxrCdtxSRJz8C2lBH6kZJkgR9fcGiMRaaNLQGb9Naov/bbut9tiICurAeX+0rG+NqlYmLG7/iVE56bV//351xkFERERERESFJAgCzt9+jQcvoortGH97BiE4PAm/TmgNmxE/I+biTiT6nP9IYFJEnl4LiLXQvH5b/PJ1a/y+06vYYiTKT1a2FOuPP8CKGR01HQqVMJVrehEREREREZHmCIKA9EwJDpz3L/ZjPXoZjclL3ZGUloVKPSeiYo8JgOgjXycFKSLdViPluRecGtjgp7GcLUSa4/86Dp4PQiHl3Rw/KUx6ERERERERlUEikQhHLz1HYkpmiRwvKj4dXy26iNfvEmDashdsRvwEsZ5h/jtJJYg4tQopAffQpnEVzB3dskRiJVJmz79+vJPjJ0bl6Y0yERERuHPnDiIiIpCZmfvDViQSYdq0aUU9DBEREREREf0/qVRAbFI6/r4RWKLHzc6WYsbKq/hhdEt0aNoUVcYtRfjRP5EdF573TtJsRJxcAZth89GhmSMkEilWHrpfckET/b+I2FScuf6KRe0/IUVKeq1evRo7d+6ERCKRrxMEAaL/vx+o7N9MehEREREREamPWCzC3n/8kJkt1cjxV+y/h6DQuhjTqz5sxy9DxPFlSH/jl/cOkmxEnFgO6+EL0LlFE0ikAtYc8S25gIn+37HLL/BZ6xowMtCBWMSi9uWdytMb3dzcsHXrVrRs2RLr1q2DIAgYOHAgVq5ciWHDhkEsFqNPnz7Yu3evOuMlIiIiIiL6pEmlAl6FxuOab4hG4zjh8RKLdnlB0NZH5ZH/g0nTLvm2F7IzEXFsCdJeP0GXltUwfVjTEoqU6D8p6dk4dMGfCa9PhMojvY4ePQobGxvs2LED2trvu7G1tUWfPn3Qp08ffPbZZ5g8eTL69OmjtmCJiIiIiIg+dWKxCLvOPEVJ1+NOevcIabGByEh8h4zEMEizMxB2vylCIydi9XedYNl3GnQqVkXslQOAoHwEmpCdie+nT8LlgJg8j1Oz8/fQNbZSWJcYch+xr64iKzUWOoYWsKjbBRVsm+XaVyrJRPC1VTC0tIN148FFOl8qv87deo1+zrVhU9EIYjGTX+WZyiO9Xrx4gY4dO8oTXgAglf73wdahQwc4Oztj586dRYuQiIiIiIiIALwf5eXtF45HL6NL/NixL90R//oW0hPeQVvfVL4+LCYVYxddQEhkMszaDoD10HkQ6ern3ZH0fXmc/t27YNq0aejWbyQs6nWT/6ela6TQPDn8KcIfHAEAmNVoAwAI9z2E5IhnubqOfnYOgiCFZf3eRT1dKsckUgE7/37KhNcnQOWRXtnZ2TA3N5cv6+vrIykpSaFNvXr1cOTIEdWjIyIiIiIiIgW7/8mndlYxsmzQD9r6ptAxqoS0mECE3Nkq35aeKcU3y9zxy3gntGrQAlW++hMRR5cgOzEqz/7aa4ei59DZ0KtcF65XX+Z5XvHBdyDWMUC1dlOhpaMPi6x0BHksQfzrWzC2ri9vlxb7GvGvb8HWaTzE2vkk3YgA3H0ajsevotGwVkUmv8oxlUd6WVpaIjIyUr5cuXJlPH/+XKFNZGSkwkgwIiIiIiIiUo0gCLjoFYy3EUkfb1wMDCvVha6xpfzGZcr8vusujl1+Ad1K1WD79XLoVcnnLnnZGQg/tAiZ4YEY1LkuRveqr7xZWhx0jSyhpfM+kaWlow9do0rITouXt5FKshD+8BgqVGsBIyt7lc6PPj07Tz8BS3uVbyonvRo0aICAgAD5cps2beDj4wM3Nzekpqbi6tWruHDhAurXV/7BRURERERERAWXJZHi4AV/TYfxUQfO+2PZ/nuAnhGqjPkdRg2dlbZ7GpmKYz7BWDt3Cv45dgA9Wlnhi+65E1baBmbITImGNDsTACDNzkBmSjS0DczkbWKeX4A0OxOWDfoVyzlR+fQqNAG3HoVBKi3hAnlUYlROenXu3BkBAQF4+/YtAGDSpEkwNjbGggUL0KJFC3zzzTcQBAGzZs1SV6xERERERESfJEEQ4OH9FvFJGZoOpUBuPgrDzNXXkJ4lwHrgdzDvOAKA4pCafQ8isfN+BHbefYPvF/6BTp06IT30FoZ1VRwdZlajDaRZqXh7ayOi/P7Bm5ubIM1Kg1nNtgCAtLg3iAvyhHXjQdDSMSipU6Ry4tTVl5zeWI6pPPdw8ODBGDz4v7thVK5cGSdOnMDu3bvx5s0b2NraYuTIkbC359BSIiIiIiKiohCJRPjbM1DTYRRKcFgSxv5+CevmdIZ1h2HQqWiLqL/Xo5GVEVrZmsChkgHMDLQRk5qNW28ScehRFJYtW4ZffvkZgzo7wvXqKwCAsU0jWDcdjrhX1xAffBs6hhVh02wEjK0bQJBmI+LhcZhUbgJjm4ZIjQ5AlN8/yEiKgLaeCczrdIZ5rfYafiSoNHvxJg5PA2NQv6YFk1/lkFoLblWrVg0LFy5UZ5dERERERESfNKlUwONX0XgTrplaXkWRmp6NCYsv4/fJ7dCsQTvomFuj97ElkCTHydtUNtHFkIaVUNVUF796vMG6tetw8+ZNZEsE/H3jfaLPtFpLmFZrmav/mBeXIclMgVWjAchKi0fo3d0wsKgJW6evkRL5DFFPT0Nb3xQmlRuV2DlT2XPySgAWft1G02FQMVB5eiMREREREREVP7FYhDM3ytYorw/9svUWXK++hK51Ldh+vQK6NrVytWldtQIqGmojITERLx54Y2L/hujdrmaefaYnhCL21VVYNRoILV0jJATfhiCVwLrpcBhZ1oNVw/7QMaqEuMDrxXhmVB7cexaB0Mhk1vYqh4o80uvJkyc4fvw4/Pz8kJiYCBMTEzRs2BBDhgxBkyZN1BEjERERERHRJ0kqFRAVn4p7fuGaDqXIdv39FEHvEjDr82ao8tWfiHRbg9TnXgptTPXeT3d867YOdnb1MGVQY0ikAi7cCVZoJ0gliHh4DMbWDWBS5f33zoykSGjpGkInR4F7vQpVkBodAKL8CML72l4zhjfTdCikZkVKem3atAkbNmyAVCpVWC9LhE2dOhXTp09Xqe/w8HCsXr0afn5+iIiIQGpqKqytrdG0aVN8/fXXaNiwoUL77Oxs7Nq1CydPnkRoaCjMzMzQtWtXzJo1C+bm5rn6j4uLw5o1a+Du7o74+HjY2tpiyJAhGD9+PLS11Trrk4iIiIiISCVisQhnrgeivAxAueITgrcRSVg6tT1shs5F7JWDiL91CgCQkilBSGIGRAAsxel4t/8XVBnzB6YNaYLsbCnc772V9xP70gNZaQmwbT1Bvk4kEkGQShSOJ0izS+S8qOy75huC8f0awlBfGyIRa3uVFypnd9zd3bFu3TpUqlQJU6ZMQdu2bWFlZYXIyEjcvn0bW7duxcaNG+Hg4IBu3boVuv+YmBi8ffsWzs7OqFy5MgwMDBAaGgpXV1dcuHABmzZtQqdOneTtFyxYgDNnzsDFxQVff/01QkJCsHfvXty7dw9Hjx6FsbGxvG1ycjJGjRqFoKAgebF9b29vrFy5EgEBAVixYoWqDwsREREREZHapGdm47L3G02HoZLM5EgAgI5hRYjEWgCA7PQkPAuIx/jFaVg3uzMqunwJnYq2eHN6A1beDEGmRIBjZSOYG2hDkhiNsP2/oMqYxZj5eTNkS6W4dj8UGYnhiH3pAesmw6CtZyI/nq6xFZLDnyAt9jUMLGpCmp2OtNgg6JlYa+T8qWzJyJTgolcwBnaqo+lQSI1UTnrt27cPpqamOHnyJKyt//sQMTExQZ06dfDZZ5+hf//+2L9/v0pJr4YNG+LQoUO51n/xxRdwcXHB9u3b5Umv27dv48yZM+jSpQs2b96s0Me3336LnTt3YubMmfL1O3fuxMuXLzF//nyMGzcOADBs2DCYmJjgwIEDGDx4MNq2bVvomImIiIiIiNRFEARcuvsGqemlY7RScvgTJIc/BQBkZ7wvqp8W9wbhD47K29g0+1z+79dX/wIA1OoyHzqGFgDeJ8JCvLYj3Lw6et0+iK5tHCDJSMTNGyGIjk2CjbEOZrW1lfeRnRD1/yO+FmP2F47IypLg8KZ1MKxUDxWqNleIz7RGW8QF3sC7e/tgYtsMaTGvIM1Kg3mdzsXyeFD5c+7WawzqXFfTYZAaqVzI3s/PDz179lRIeOVkbW2NHj164OnTpyoHp0ylSpWgp6eHhIQE+brTp08DgDyBJdOjRw/Y2trKt+dsb2BggC+++EJhvWz/D9sTERERERGVNJFIhH9KUQH79IR3SAzxQWKID1KjXgAAstPi5OsSQ3w+2oeOUUWYVmsFaXYmksP9cOr4QVy4eAmVbatixpSJ2DauM6yMdRX2yY6PQNiBXyBNTYJFui+k6bGwajwkd98GprB1Gg9tA1PEv74NSVY6rBoNgrF1A7WcP5V/YTEpuPcsggXtyxGVR3plZGSgQoUK+bYxNTVFZmamqocAAGRlZSEpKQkSiQTv3r3Dzp07kZqaChcXF3mbhw8fQiwWo1mzZrn2d3R0xD///IOYmBhUrFgR0dHRCA0NhaOjI/T19RXaVq1aFZaWlnj06FGRYgYAqVQKf3//IvfzMdWrVy/2YxBRyUhNTcWbN2Vz+gJRXtLS0gCgRP4mUvknlUohFvPm4/RpkEoF3H8egXfRKZoORa6SfXdUsu9e4PZ2fZfnWqdjYAbrJrkTVi5ta+KbQY0ASRYiTq1E2qv7CtuzYsMQdmAhJoz5AxMnTsQfe7zh7ReRqx/DSnVQo8PMXOuJCursrSC0rM8pseWFylcNtra2uHnzZr5tbt26BVtb23zbfIynpyfatm0LZ2dnDB8+HLdv38bEiRMxY8YMeZvw8HCYm5tDV1c31/6ykWjh4eEK/7exsVF6PBsbG3kbIiIiIiIiTRCLRTh/O/jjDcuJ87dfY/6mm8gWacNm+AKYOvXN1SYrJhTv9i+EkJmKn8e2QgsHKw1ESuWd7/NIpKZnaToMUhOVR3p1794dW7duxc8//4zvv/8eZmZm8m3x8fFYtWoV/Pz8MGnSpCIF2LRpU+zevRsZGRl4/fo1zpw5g5SUFGRmZkJHRwcAkJ6eDlNTU6X76+npAfjvl+b09HQAUJogk7WXtSkKsVgMBweHIvdTMGkldBwiKk6GhoYl+LlBVDJkI7z42iZ18PX11XQIRCUmLSMbPv6Rmg6jRD17HYeJf7pj7exOqPjZOOhUqoro8zuAHHdgzIp+i7AD/0Pl0YuwcLwTFm6/g4cB0RqMmsqbbImAO0/C0bl5VYjFvItjWady0mvSpEnw8PDAiRMn8O+//8Le3h6VKlVCdHQ0nj9/jrS0NNStWxcTJ04sUoAWFhZo166dfHnw4MEYMGAAXr9+jd27dwMA9PX185xGmZGRAQAwMDCQtwWQb/sPpz0SERERERGVFKlUwK1H75AtkWo6lBIXm5iOcYsuYMXMTqjr+Bl0LKog4sRySNOT5W0yI4MRdvBXVBm1CL9NbIOfttzG08AYDUZN5c3NR+/QpWU1TYdBaqDy9EYjIyMcPnwYn3/+/u4cDx48wOXLl/HgwQMAwOeff47Dhw/D2NhYLYHKmJqaokuXLrh16xaCg98P97WxsUFcXJzSRFZERIS8Tc7/5zWFMTw8PM+pj0RERERERMVNLBbhxoNQTYehMdlS4LvV1+Bx7y30qzeA7fhl0LGootAmMzwI7w7+ClF2BhZPbov6Nc01FC2VR77PI5GeWTrumkpFU6RKoMbGxvjtt9/g7e2NM2fO4ODBgzhz5gy8vb3x22+/wcTERF1xKpBNP5TdwbFJkyaQSqV4+PBhrra+vr6wtbVFxYoVAby/+2OVKlXg7++faxpjaGgooqKi0KRJk2KJm4iIiIiI6GNS0rLwMCBK02Fo3OrD97HzzFNomVrCdvwyGNRU/J6WGfYKYYcWQSTNwp/ftINddTPNBErlTla2FF5PwnkXx3JALbe/0dbWhp2dHVq0aAE7Oztoa7+fNbls2TJ069ZNpT6jopR/yIeEhMDd3R1GRkaws7MDAAwYMAAAsGvXLoW2Fy9eRGhoKPr376+wvn///khLS8Phw4cV1sumS8r6IyIiIiIiKklSqYCbj94hW8Iv2wBw+vorLNx2BxKxLmy++AUmzRXvHpnxLgBhhxdBLEiwbFp71LFVXuuZqLBuPnrHml7lgMo1vQoiPj4eoaGqDctduXIlnj17BmdnZ1Sp8n4o66tXr3D69GmkpqZiyZIl8tpb7dq1Q9++ffHPP/9gypQp6Nq1K0JCQrBnzx7Url0bEyZMUOh74sSJuHDhAlasWIHQ0FDY29vD29sbp0+fRt++fdG2bduinTgREREREZEKxGIR7jwJ03QYpcrDgGhMWeaBNd91gmWvydCtWBUxl/cAwvuaZxkhzxF++A/YfPELVsxwxuy1N/A6LFGzQVOZd98/EhlZEujpaGk6FCqCYk16FUX37t2RlJSEc+fOISYmBhKJBFZWVnBxccGYMWNyTUFcunQp7OzscOrUKfz2228wMzPDgAEDMGvWrFx1xYyNjXHo0CGsWbMG58+fx5EjR2Bra4vZs2dj/PjxJXmaREREREREcplZEjzi3QhziYxLw9hFF7Hqu06o4dQHOhWrIMJ1FYSMVABA+ls/hB9djMojfsaqmR0wa/V1vIlI0nDUVJZlZEng7ReOdo2rcMRXGSYSBKHYxs0uWLAAbm5uePbsWXEdolSS3U7b0dGxRI7nFxSDeRs8S+RYRFQ8lk13RoNaFTUdBpHa+fv7AwAcHBw0HAmVByV9jUVU0qRSAXf9wrF4911Nh1KqzR/TCu2aVEZWTCjCj/6J7PgI+TaDWk1g8/mPyJKI8O2qawiNSs6nJ6L8OTergnmjW2k6DCoCtdT0IiIiIiIioqIRi0Xw9lN+l3n6z9J93jh43h86FlVgO34Z9KvVl29LC3qE8OPLoKMFrJ3dCZUrGmowUirrfJ5FIjNboukwqAiY9CIiIiIiIiol7vpFfLwR4ejlF1i82xuCjgEqf/krjJu4yLelvfJFxMkV0NUC1s/pDCtzAw1GSmVZWkY2HjyPgoR3cSyzmPQiIiIiIiLSMEEQEByWiPikDE2HUmZ4+YVj+l/XkJYphVW/6bBwGQXgfe2l1IB7iHBdCV0dMTb+4IKKpvqaDZbKLL+gGGixpleZVahC9mPGjClU54GBgYVqT0RERERE9CkSBODZ61hNh1HmhEYl46tFl7B2TidUaTcIOhVtEXl6LYSsdKQ+v4tI11WwGjQHm+e6YMqyK4hNTNd0yFTG8H1ZthUq6XX3buELKopEzIgSERERERHlRywWwT84TtNhlEnpmdmYvMQd/5vQBi0cWqHKV38i/OhiSJJikOJ/B5Gn18BqwCxsnuuCyUvdEZ+cqemQqQx5+TYeEokUWlqcKFcWFSrptW/fvuKKg4iIiIiI6JP24g2TXkXx2447GNO7Poa61IXt1ysQcexPZLx7iRS/m4gSa8Gy/7fYMq8rJi11R2IKE19UMJnZUgS9S0TtqqYQc1BPmVOopJeTk1NxxUFERERERPTJSsvIRkhkkqbDKPP2nX2GoHcJmDOyOaqM/gORf69Hit9NJD+5Doi1YNVvOrbM64JJS9yRnJal6XCpjHj2Oha1q5pqOgxSAcfnERERERERaZBUKsD/dSwE3iBOLW48eIdZq68jPRuwHjQb5h2GAwCSH11B1L+bYWKkh60LusJQv1BjQOgT9ux1LEd5lVFMehEREREREWmQWCzCc9bzUqvXYYkY//tFRMalwrzj57Aa+B1E2rpIenAZ0ee3oYKRHrbN7wp9XSa+6OP8g1nMvqxi0ouIiIiIiEjD+KVa/ZLTs/H1H5fw+GU0jBs6o/Lo36FlbIZEnwuIvrATpib62LagC/R1+bWY8hcVl4a4JN75syziu5uIiIiIiEjDWMS++Py4+SbO3HgFPZvasB2/ArrWtZB47yxiLu2BeQUDbJnfDbra/GpM+fMLjIVEyjnIZQ3f2URERERERBoUFp2CpFQWVS9O292eYN2xhxAbmqLKV4thaOeEhLt/I8ZjPyqaGmDL/K7QZuKL8uEfHAstMet6lTV8VxMREREREWmIrIg9Fb/L3m/wwwZPZAliWA+dC9O2A5Fw2w2xVw/B0twQW+Z1AfNelBfW3SubCvyWHjNmDNzc3OTL3t7eePfuXXHERERERERE9EkQi0V4FRqv6TA+GS/exGPC4suIS0xHxS6jYdl3OuLvnEbcjWOwtjDCpnndmPgipUKjkjUdAqmgwG/nu3fvIiQkRL48ZswYnDp1qliCIiIiIiIi+lRExKZpOoRPSnxyJsb9cRHPg2Nh0tQFlb/8FQn3ziHu5klUrmSEDT90hZiJL/pAYkomMrMkmg6DCqnAb2VTU1PEx8fLlwWBBdyIiIiIiIiKKio+VdMhfHKkUuD7dTdw0es19Kvaw3bcMiQ/uYH426dha2WMDd93YeKLcomM43u1rNEuaMPatWvjzJkzsLGxQaVKlQAA/v7+ClMe8zJw4EBV4yMiIiIiIirXouI40ktT1h97iFchCZg8sBFsxy5BhOtKiLS0UM2pL9bOdsGMv65oOkQqRcJjUlGlkjHELGhfZhQ46TV9+nRMnToVK1eulK9zd3eHu7t7nvsIggCRSMSkFxERERERkRKZWRIkpmRqOoxP2tlbrxEcnoRFk9rAZviPiLm8Bwn3zqFmy15Y810nzFp9TdMhUikRGcuRXmVNgZNe7du3x9mzZ3Hr1i1ERERgw4YNaNWqFZycnIozPiIiIiIionIrOp6jvEqDp4ExmLTEHWtnd0Kl7uOReP8CEh+4o06zrlg5syPmrL2u6RCpFIiMS+UorzKmwEkvALC1tcWwYcMAABs2bICTkxOmT59eLIERERERERGVZ1KpgHCOHCk1YhLSMfb3S1j5bQfUbt4Daa8fI8X/Duwc2mD5dGfM3eCp6RBJwyJY06vMUbk03759+zBo0CB1xkJERERERPRJieKX6FIlO1uKmauu4er9EOjXaARd65pID/FH/VoV8efU9poOjzQskndaLXNUTno5OTnB1tZWvpyWlobIyEikpfFFQERERERE9DFisYhF7EuplQd9sOcfP2ibWkLXsgayk2LRuE4l/D65naZDIw1iTa+yp0g3YZVKpdi9ezd69eqF5s2bo1OnTmjevDl69+6N3bt3QyqVqitOIiIiIiKicieSSa9S69TVl/h1x11ItXSgbWIBAGhmZ4lfJ7bRcGSkKfHJGcjMlmg6DCoElZNe2dnZmDRpEpYvX46goCBYWFjA3t4eFhYWCAwMxPLlyzFx4kRkZ2erM14iIiIiIqJyIyqeI0dKs/vPIzF1+RUkp/53h80WDtb4eTxv6PapimaiukxROem1f/9+eHp6onXr1jh9+jRu3rwJNzc33Lx5E2fOnEHbtm1x69Yt7N+/X53xEhERERERlRu8e2PpFxaTinG/X0BIRJJ8XeuGlbHgq1YajIo0JTYxHYIgaDoMKiCVk15nzpxBzZo1sWPHDtjb2ytss7Ozw7Zt21CjRg2cPn26yEESERERERGVR+kZnCpVFqRnSvHNcg/cefxOnvBo16QKfhjVQsORUUlLz5SAOa+yQ+WkV1BQEFxcXKCtra10u7a2NlxcXPD69WtVD0FERERERFSuZUtYB7ksWbzHG4cvPofw//WrOzpWxewvmms4KipJ6ZnZEMCsV1mhctJLLBZ/tF5XdnY2RCKRqocgIiIiIiIq15j0KnsOX3yOJXu9Ifn/guYuLathxvBmmg2KSkxGJkdnliUqJ73q1auHS5cuITVVeeHF1NRUXL58GfXq1VM5OCIiIiIiovIsW8IRI2XR7SfhmLHqKlLT3he4/8ypOqYOaaLhqKgkpGdKIAIH95QVKie9hg4divDwcHz55Ze4ceMGMjPfv9kzMzNx48YNjBo1CuHh4Rg6dKjagiUiIiIiIipPJFKO9Cqr3kYkY9wflxAekwKRSISebWti0qDGmg6Lill6ZjY4oa3sUF6QqwCGDRsGb29vnDlzBpMmTQIAmJiYICnp/R0tBEFA3759MXz4cPVESkREREREVI5IpAILYpdxqenZmPjnZfw2qS2a21uhb/tayM6WYtffTzUdGhUTiURgGacyROWkFwAsX74cnTt3xvHjx+Hn54fk5GRUqFABDRs2xNChQ9G7d291xUlERERERFSuSFjPq9z437bbGNe3AQZ1roOBnepAIhGw96yfpsOiYiCVMlNdlhQp6QUAvXv3ZnKLiIiIiIiokCT88lyu7P7HD4GhCZj9RXMM6VIXZ28FIio+XdNhkZpJODyzTCly0ouIiIiIiIgKj3duLH+u+YbibUQymtSrxIRXOSUwWV2mMOlFRERERESkARLeubFcCnyXgMB3CZoOg4qJlCO9yhSV795IREREREREquNIL6KyhzmvsoVJLyIiIiIiIg3gDeCIyh5DfU6YK0uY9CIiIiIiItIAQ30dTYdARIVkYqjLm1CUIUx6ERERERERaYCerhZHexGVMcaGOgCY9CorVE567du3DxcvXlRnLERERERERJ8MsUgEAz1OlSIqS0wMdSFitrrMUDnptWzZMvj6+qozFiIiIiIiok+KEac4EpUpFYx0IWbSq8xQOellbW2NtLQ0dcZCRERERET0SWFRbKKyxcRQV9MhUCGonPTq2rUrbt26hYyMDHXGQ0RERERE9MkwMeIXaKKy5H1NLyorVE56zZw5E8bGxpg6dSpevHihzpiIiIiIiIg+CeYm+poOgYgKSFtLBH1djs4sS1R+tgYMGIDMzEw8e/YMAwYMgJ6eHiwsLHIVdBOJRLh8+XKRAyUiIiIiIipvzE30NB0CERWQsQFHZpY1Kie9QkNDFZbT09Px7t27IgdERERERET0KRAEAWZMehGVGZzaWPaonPTy9/dXZxxERERERESfFKkgcHojURnCIvZlj8o1vYiIiIiIiEh1IohgXoEjvYjKCktzA02HQIXEpBcREREREZEGiMUiVLepoOkwiKiAqlubaDoEKqQiJb2kUikOHjyI4cOHo0WLFmjQoIF8m7+/P5YsWYI3b94UOUgiIiIiIqLyyNLMAAZ6vBscUVlQ3aYCJFKppsOgQlD50zUrKwuTJ0/G7du3AQD6+voQBEG+3draGgcPHoSJiQmmT59eqL5fv36Nv//+Gzdv3sTbt2+RkpKCKlWqoF27dpg0aRKsrKxy7XPs2DEcOHAAr1+/hqGhIdq3b4/Zs2fD1tY2V9u0tDRs3LgRZ8+eRWRkJKysrNC7d29MmzYNBgYcrkhERERERCWnuo0JngfHaToMIvqImpUrQEvMCXNlicrP1u7du3Hr1i0MGzYMd+/exfjx4xW2m5ubo3nz5vD09Cx03ydOnMCuXbtQpUoVTJo0CQsWLEDTpk1x6NAh9O3bF69evVJov2bNGvzyyy8wMjLCjz/+iDFjxsDT0xOff/45wsPDFdpKJBJMmjQJ27dvR8uWLfG///0PLi4u2LVrFyZNmgSJRFL4B4OIiIiIiEhFNTjFkajU09EWw9rCUNNhUCGpPNLr77//RoMGDbBo0SIAgEgkytWmevXquHbtWqH77tGjByZNmoQKFf778P/888/RrFkzLFy4EOvWrcPatWsBAEFBQdi2bRsaNmyI/fv3Q1v7/Sl16NABw4YNw6pVq7B8+XJ5P66urrh79y5Gjx6Nn3/+Wb7e1tYWy5Ytg6urK4YOHVromImIiIiIiApLKgioYcM6QUSlXVUrY4jFufMeVLqpPNIrODgYrVq1yreNhYUF4uPjC91348aNFRJeMn369AEAPH/+XL7un3/+gUQiwejRo+UJL1kfrVq1woULF5Ceni5ff/r0aQDAuHHjFPoeOXIk9PX15duJiIiIiIiKnQDUrMKRXkSlHUdklk0qj/TS1dVFRkZGvm3Cw8NhZGSk6iFyiYiIAABUqlRJvu7hw4cAAEdHx1ztHR0dcffuXbx48QJNmjSBIAh4/PgxrKysctX60tfXR/369fHkyRMIgqB05FphSKVS+Pv7F6mPgqhevXqxH4OISkZqaipv/kHlTlpaGgCUyN9EKv+kUinErKVC5YxYLELNyqaaDoOIPqK6jYlacgVUslS+aqhXrx68vLwUitfnlJ6ejtu3b6Nhw4YqB/ch2ZTGwYMHy9fJEmE2Nja52ltbWwOAvK5XfHw80tLSlLaVtU9NTUVCQoLaYiYiIiIiIspPBSNdmBnraToMIspHdRsTSJWnP6gUU3mk1+DBg/HLL79g8eLF+PHHHxW2ZWdnY/HixYiOjsaCBQuKHCQAbNmyBRcuXEC3bt0waNAg+XrZL8i6urq59tHT01NoI5vmqKxtzvY5p0OqSiwWw8HBocj9FExaCR2HiIqToaFhCX5uEJUM2QgvvrZJHXx9fTUdAlGxqV7ZBPEB+c+kISLNqVnZFFqs6VXmqJz0Gjp0KNzd3XHgwAGcP39ePo1x6tSpePToEaKjo9G9e3f07t27yEHu3bsXq1evhpOTE/766y+F4YQGBgYAgMzMTOjr6yvsJ5t+KWsj256Zman0OLL2H/ZDRERERERUnGraVMCjgGhNh0FESujpaMHS3EDTYZAKVJ7eKBKJsHHjRnz77beQSCQIDg6GIAjw8PBAZmYmpk+fjtWrVxc5wN27d+PPP/9E27ZtsW3bNnkCS+bDKYw5fTj10czMDAYGBkrbytobGhrC1JRz6omIiIiIqGRIpQJqVGaRbKLSqmblChCzlleZpPJILwDQ0tLC1KlT8c033yAoKAjx8fEwMTFB7dq1oaWlVeTgtm3bhpUrV6JDhw7YuHGjfPphTk2aNMGNGzfw4MED1KxZU2Gbr68v9PX1Ua9ePQDvE3WNGjWCt7c3QkNDFYrZp6en49mzZ2jSpAkL0xERERERUYkRiYAGtSw0HQYR5aGpnaWmQyAVqeX2NyKRCLVr10bz5s1Rr149tSS8tmzZgpUrV8LFxQWbNm1SmvACgL59+0JLSwv79u1Ddna2fP3jx4/h7e2N7t27K4wOGzBgAID3I8hyOnz4MNLT09G/f/8ix05ERERERFRQIpEIVa1MUMmMZVaISiNHO0tIWcW+TCrSSC8ZX19f+Pn5ITk5GcbGxmjQoAEcHR1V7u/gwYNYvXo1KlWqhM8++wznzp3L1UaWvKpduzYmTJiArVu3YvTo0RgwYADi4uKwZ88eVKxYEbNnz1bYb/DgwXBzc8P+/fuRlJSEli1b4vnz5zh06BBatmypcGdIIiIiIiKikuJoZ4VLd99oOgwiykFfVwsONS0gZhH7MqlISa8HDx7gxx9/RFBQEABAEAT51MDatWtj8eLFaNasWaH7ffz4MQAgOjo6150hZWRJLwD47rvvUKVKFRw8eBCLFy+GoaEh2rdvj++++w6VK1dW2E9LSwvbtm3Dxo0bce7cOfz777+wtLTE2LFjMW3aNLWMUiMiIiIiIioMqVRAc3smvYhKm0Z1KkFbSy2T5EgDRIIgqDRGz8/PDyNHjkR6ejqaNWsGJycnVKxYETExMbh79y4ePHgAAwMDHDp0CPXr11d33KWa7HbaRRntVhh+QTGYt8GzRI5FRMVj2XRnNKhVUdNhEKmdv78/AMDBwUHDkVB5UNLXWEQlLSUtCyN/OQvOoiIqPSYMaIT+HWqz9ncZpfJIr9WrVyMrKwvr16/HZ599lmv7hQsX8N1332H16tXYtm1bkYIkIiIiIiIq74wMdFC3mjlevInTdChE9P+a21tpOgQqApXH6N2/fx+fffaZ0oQXAPTo0QPdunWDj4+PysERERERERF9Shx5lziiUsOigj6qWZtwlFcZVqSJqTVq1Mh3e61atYrSPRERERER0SdDKhXQwoGjSohKi2ZMQpd5Kie9GjVqhOfPn+fb5vnz52jcuLGqhyAiIiIiIvpkiMUi2NWwgKF+ke43RkRq0szOElIW2SvTVE56zZw5Ezdv3sThw4eVbj948CBu3bqFmTNnqhwcERERERHRp0RLLEKTuhxdQlQaNLe3gljMqY1lWYF/QtiwYUOudW3atMGiRYuwZ88etGzZEpUqVUJ0dDR8fHwQHBwMZ2dn3Lp1i3fYISIiIiIiKgCpVICjvSXuPAnTdChEn7TatqYwNdbTdBhURIVKeolEIghC7qF9wcHBCA4OzrX+xo0b8PT0xLRp04oWJRERERER0SdAJALaNa6Cra6POa2KSIM6OtpCEAQWsS/jCpz0WrJkSXHGQURERERE9MkTiUQwM9FDC3sreD+L0HQ4RJ8ksQhwaVFN02GQGhQ46TVo0KDijIOIiIiIiIjwforjZ62rM+lFpCGN6lSCRQV9TYdBaqByIXsiIiIiIiJSP7FYBKcGNjA11tV0KESfpE7Nq3J6cTnBe+ESERERERGVMlpaYnRuXhWnrwdqOhQqhQRBQGLIPSS8uYuMxDBAEKBjVBEVqraAeS1niMRaCu2lkmwkvr2LxBAfZKXGQirJgo6BGQwq1oF57Y7QNapY4GMHui9Bdlrc/7V352FRlvv/wN/PwzAsAwgCsouICsqigpgiuKCi5oJS7mJmqS3+Ks1c6nytTDslaXX0uFuaokmaS1rmSS3XXBJU0lwQF3Zl37eZ3x/E5DioMAwMDO/XdZ3rOM9zz/18MJvkzX1/7mrvGRiZwX3gQtVa5eXIuP4LcpNiIC8rglELR9h2GgbjFs5q7y/JTcGd4/+BQ9exMHfsUuOatEkqERHcxYmnNuqJOoVely5dwvr163H16lWkpqaioqJCbYwgCLhy5UpdHkNERERERNSsyOUKhPZow9CLqpUauwN5SRdgIJXB3LEzRIkRijJu4cHVAyh8cANOAS8qgy+FvAKJv69DcdZtGMpsYO7YGYIoQXFOInLunEZe0gU493wVxi0ca1VDy/YD1K6JEvXTDu9f/QnZCcdhausBqZkt8pJikHh6Hdr0nQOJsYVynEJegdSL0ZC18tRZ4AUAPX0dYWLE9UH6QuN/kgcPHsTs2bMhl8shkUhgbW0NAwODp7+RiIiIiIiInkgUBbS2M0d7F0vcuJet63KoEclPjUNe0gVITKzQOuj/QWJkBgBQKORIu7QTuffOI/v2KVi1Df57/J8ozroNE+u2cO4xHYLwT5ejjOu/IOP6IWTF/woHvwm1qsPGI/SpYxQKBXLu/g5Tm3ZwfuYlAICZvQ8ST69GbuIFtGzXVzk2M/43lBVmwilgaq3q0LbBPVwhlyu40ktPaBx6rVixAhKJBB9//DGeffZZiCLbgxEREREREWmLXKHAgO6tGXqRiryUOACAVdveysALAARBhI3ns2qhV1lhBgBA1spTJfACADN7L2RcP4SK0oJ6qbWitACKijIYPbSV0diy8tdlD22RLMlLQ+aNX2Dn+xwkxub1UktNONrI4O1uo7Pnk/ZpnFTdvXsXQ4cOxbBhwxh4ERERERERaZkoCOjr5wyphN9v0T8qSvIAAIamLdXuSYzMIEqMUFaYgbLCTACA1NwOAFCQfh0KhVxlfH7aVQCAqU27WteRlxyLzJtHkHXrGAruX4dCrt7uyEBqCkE0RElusvJaSU5SZf0mVgD+XqF28TuY2rSDhbN/revQptAerlAo2MBen2i80svW1hZmZmZPH0hEREREREQaMTU2RE8fB/wWk6TrUqiRMJDKAKDaZvLlJfmQl5cAAErz78PQtCVkrTrCzN4b+alxuPPbcpjatP+7p1cSijIT0MK1B6za9q51HSkXtqm8lhhbwq7zaMhs2yuvCYKIFq7PIDvhBJLOfgVDmS3yki5AlBjD3KkrACDr1nGU5qfDtc/sWtegTRIDAQO7u+q0BtI+jUOvQYMG4fjx4ygvL4dEwiZvRERERERE2iaXKxD6jCtDL1KS2XVEXnIssm4dg7ljZ2UIplDI8eCvg8pxFWWFACoPl3Pwj0DmjV+QceMwSvPTlWNMWraFuUNntdMen6SFSzeYtHSD1NyuclVZQSayb59Ezt2zSD73NVwCX1NuYQQAG89nIYiGyEuORVFmAowsKk9vNDRpgdL8+8i4dgi2XsNhaGKJrIQTyIo/hvKSXEjN7NDKa7hGq9A0EdzFCRYyaYM8ixqOxmnVG2+8gfPnz+Ptt9/G/Pnz4eDgoM26iIiIiIiImj1RFODb3hZtnVrgVlKOrsuhRsDcsTPykmJRkH4Vt3/9DDK7TsrTG0vz0yE1a4XS/HQIQmUjdnlFGVJjd6Ag/SpaeY2Amb03RIkRinMScf/PH5D4+zrY+T6HFq271+j51h0Gqrw2srCHne9zECVGyLp1DBk3foFTwBTlfdFAAtuOQ2DbcYjK+xQKBdIu7YRJS1dYuvZAXspl3P9zHyzb9ILMrhOy4o8i6ezXaNNvLgxNWtTtN+0pRAEYO9CDDez1kMahl4mJCRYvXozJkycjJCQEFhYW1W53FAQBv/zyS52KJCIiIiIiaq7kcgVGh7THp1vO67oUagQEQYRjt8nIvn0SuYkXkJcUAwgiTKxc4dzzFWTe+AWl+ekwkFY2hM+8eRT5KZdg22k4LNsEKucxtXaHU/epSDjyCe5f+QHmjl0gSjRf6dTCtQeybh1DUebtGo3Pvn0KxTlJaPP3tsasW8dgKLNBK+8wAIDUzBYJh/+NnDunYeM5WOO6aiKwsyOcbNm+SR9pHHqdP38e06ZNQ1FREQAgJycHOTn8yQMREREREZE2iaKAXp0d4fyzGRLT83VdDjUCgmgAq7a9q+3FVZKbCggijC2dAAAF6Y9vVi8xtoDUrBVKcpNRmp+usi2xtpTbLCtKnzq2rDATD/76CTaeQ5QN+Uvz02Fq808/MEMTSxhITVW2Y9YHQQDGh3pylZee0jj0+uyzz1BcXIxZs2YhLCwMtra2MDCo+T5gIiIiIiIiqhkFgOf6tceXO2J0XQo1YoUPbqK8OBsyOy+IEmMAUJ6qWFFaUO17qq7Xpq9XdYqz7gKo/lTJhykUCqRe3AnjFk4qK88qay1/5LX6iZDa1tPbAa3tzOv9OaQbGp99e+3aNQwePBgzZsyAvb09Ay8iIiIiIqJ6IgoC+vk7w9bKRNelUCNQUVakdq20IANpl3ZCECUq2wFNWroBADJuHIa8okzlPdm3T6G8OAcGRuaQmtspr8srSlGan47SggyV8SV5aZCXq6/kKivMRHrcHgCAuZPfE2vPuXsGxVl3YOf7vLLvGABIzexQlJkAeXkxAKAo8zbk5cUqdWmbIADjB1Wu8iL9pPFKL1NTU9jb22uzFiIiIiIiInoMURQwpn8H/HfnRV2XQjqWdGYDBFECqbk9DAyNUVrwAAVpldsYHfwmwuihoMi6fX8UpF9FUUY8bh+NhKyVR2Uj++xEFGXeAgQRdj6jIAj/rIkpzrqHxN/XQmJihbb9Fyiv5yVfRNatYzC1bguJidXfpzdmoCD9KhTycshaeaKlu/qWyyplRdl4cPVHWHuEQmpmq3LPqm1vpPzxDe6eXA1TG3fkJcdCMJDC0rWntn7b1HTvZI82Dhb1Nj/pnsahV+/evfHHH39osxYiIiIiIiJ6DEEQMPAZV3x/9CZSMqrfqkbNg5mDL/KSY5GXHAtFRSkMjCxg7uSHlu36QiqzURkrMbaAa/CbyIz/DQVpV5GbeAEKhRwSIzOYO3aGVdveMLZ0qdFzTW3cUVZwH8U5SZUrsSpKYWBoApOWbrBw9oO5k5/K6q1HpV3aBamZLazaBqvdM3fwRoX3SGTG/4bs26dhZG4HW7/hkBjXXyg1LpQnNuo7QaFQaLSOLyMjA+PHj0ffvn0xa9YsmJhwmW2VmJjKffZdu3ZtkOddScjAvJUnGuRZRFQ/Pp0ZhE5u1roug0jr/vrrLwCAp6enjishfdDQf8ciaozkCgV++yMRy7df0HUpRE2av2crfDCt/laRUeOg8UqvWbNmQSaTYcuWLdi5cyfatGkDMzP1Iz4FQcDmzZvrVCQRERERERFV9vbq6++MnUdu4G5anq7LIWqyJgziiY3Ngcah19mzZ5W/LiwsxJUrV6od96SljURERERERFQ7CgUwYbAnPtl8TtelEDVJ/p6t0KG1la7LoAagceh1+PBhbdZBRERERERENSCKAnr5OsK7rTXibmU8/Q1EpCSViHgl3JervJoJjUMvJycnbdZBRERERERENSSXKzBzdBfM/Owoyivkui6HqMl4vn972FvLdF0GNRDx6UOIiIiIiIioMRFFAU6tzPBcv3a6LoWoyXCyNcPo/h2g4Xl+1ARpvNIrOTm5xmMdHR01fQwRERERERFVQ6FQYOxADxyPTULygwJdl0PU6L32nC9EQWDv8WZE49ArJCSkRn9QBEF4bJN7IiIiIiIi0owgCDAQgdef74z31pzSdTlEjVofP2f4trfVdRnUwDQOvUaOHFlt6JWbm4urV68iOTkZ3bt3Z+8vIiIiIiKieiKKAnzb26KfvzOO/pGo63KIGiWZiSGmhXmzeX0zpHHo9cknnzz2XkVFBVasWIGdO3ciMjJS00cQERERERHRU8jlCkwL88H5q2nIKyzTdTlEjc7kZzvCQibltsZmqF4a2RsYGOCtt96Cvb09Pvvss/p4BBEREREREaFytZeZqSGmDPPSdSlEjY5HaysM6dmGgVczVa+nN/r5+eHEiRP1+QgiIiIiIqJmTxAEhD7jCu+21rouhajREEUBM0d3Bg9rbL7qNfQqKipCQQFPESEiIiIiIqpvcrkCM8d0gaGkXr/NI2oyng9pjzaOLdjHqxmrt0/DGzdu4KeffkKbNm3q6xFERERERET0N1EU4GRrhmlh3rouhUjnfNxtMHGQJxRc5tWsadzIfsGCBdVer6ioQEpKCmJiYlBRUYGpU6dqXBwRERERERHVzpBAN1y9ncnTHKnZsjQ3wrzJ3QCAvbyaOY1Dr927dz/xvru7O6ZNm4aRI0dq+ggiIiIiIiKqJblcgZmjuyA+KQd3U/N0XQ5RgxJFAXMjusFcJoXIwKvZ0zj0Onz4cLXXRVGEhYUFZDKZxkURERERERGRZkRRgAQi3pvSHW99/huKSsp1XRJRg5k4yBM+7ja6LoMaCY1DLycnJ23WQURERERERFoiigIcbGR4Y2wXfPrNeV2XQ9Qg/D1bYcyADrougxoRHutBRERERESkhwRBQFBnJwwPbqvrUojqna2lCeZM9Idczsb19I9arfRKTk7W6CGOjo4avY+IiIiIiIg0p1Ao8NJwL1y/m4Vrd7J0XQ5RvZAYCJg3uRtMjQ0hiuzjRf+oVegVEhJS65MPBEHAlStXavUeIiIiIiIiqjtBECAIwIIXAvDGsl+RW1Cq65KItG7KUC94uLbUdRnUCNUq9PL19a1x6JWeno6UlBSNiiIiIiIiIiLtEEUBVhbGeGdSN7y/7hS4+4v0SXAXJ4T1cdd1GdRI1Sr0io6OfuqY/Px8rF27Fps3bwYAdOzYUbPKiIiIiIiISCtEQUCXDrZ4fXQXrIiO1XU5RFrh426D2RP8IJcruK2RqqXx6Y2PUigU+Pbbb7Fy5UpkZmaiVatWmDVrFsLCwrT1CCIiIiIiIqqD0GdckV9Yiq/3swUNNW1tHCzwfy89A1EQGHjRY2kl9Prtt98QGRmJ+Ph4GBsbY+bMmXjppZdgbGysjemJiIiIiIhIS8L7tUd+URm+O3xD16UQaaSVlQkWzegJI0MDBl70RHUKva5fv45PP/0Up06dgiAICA8Px1tvvQVbW9s6F7Zu3TpcuXIFV65cwd27d6FQKHDt2rXHji8vL8dXX32FXbt2ISkpCZaWlujfvz/eeustWFlZqY3PysrCF198gcOHDyM7OxtOTk547rnnMHXqVEgkWlsAR0RERERE1KgoFApMfrYTCorL8ePJBF2XQ1QrFjIpFs0IRAuZEQMveipRkzc9ePAA//rXvzBq1CicPHkSPXv2xPfff48lS5ZoJfACgGXLluHkyZOwt7eHjY3NU8cvWLAAy5Ytg5ubGxYuXIjw8HDs2bMHkyZNQn5+vsrY/Px8TJo0Cd999x0GDx6M999/H507d8ayZcuwYMECrdRPRERERETUGAmCAIVCgVfDfdHHz1nX5RDVmMxYgkUzesLBRqbTwCskJAQREREq1yIiIhASEqKjimrnzJkz8PDwwPfff1+j8StWrICHhwcSExNr/IwffvgBXl5euHPnjqZlYt68eRg6dCjKy8s1nqNWS5pKSkqwceNGbNiwAYWFhXB3d8fcuXPRp08fjQt4nP/9739o3bo1gMo/PPfv33/s2NOnT2Pfvn0ICQnB6tWrlde9vLzwxhtvYOPGjXjzzTeV1zdu3IibN29i/vz5ePHFFwEAo0ePhrm5ObZu3Yrw8HD07NlT618TERERERFRYyAIAuQKBWaN90NhcRnOXUnTdUlET2QsNcAH03qirWMLCELNAq/ExET079//sfenTp2KefPmaavEejF//nzs3r1b+VoURVhYWMDb2xuTJ0+ulzymrgoLCxEZGYnnnnsOrq6uavejo6OxdetW3L59G6ampujVqxdmz54NJycnlXEzZ87EkCFD8O2332LSpEka1VKr0Cs0NBTp6elo2bIl5s6dizFjxkAUNVos9lRVgVdN7N27FwCUAVaVQYMGwcnJCXv37lUJvfbu3QsTExOMHz9eZfyLL76IrVu3Yu/evQy9iIiIiIhIr4l/B18LXuiOhetOIS4+Q9clEVVLKhHxf1OfgYerVY0Dr4d169YNY8aMUbverl07bZTXIBYsWAArKyuUl5cjISEB0dHRmD59OpYtW4Zhw4bVaq6AgABcunSp3lo7RUdHIy0tDS+99JLavS+++AKrV6+Gn58f3n33XWRmZmLz5s04c+YMdu7cCXt7e+VYFxcXhIaGYs2aNRg7diwMDQ1rXUutvsK0tDQIgoCysjKsXLkSK1eufOp7BEHA8ePHa11YbVy8eBGiKKJLly5q97p27Yr9+/cjIyMD1tbWePDgAZKSktC1a1e1RvvOzs6wtbXFpUuX6rVeIiIiIiKixqBqi9j7L/fAu6tO4sa9bN0WRPQIiYGA+S8EwLe95q2UXFxcEBYWpsWqGt6AAQPg7PzPduTQ0FCMHj0aq1evrnXoJYoijIyMtF0igMqegdu2bUO3bt3UVnklJCRg3bp18PLywpYtW5ShW3BwMEaPHo3ly5dj6dKlKu8JDw/HgQMHcOjQIQwdOrTW9dQ61lMoFMjNza31g+pTamoqrKysIJVK1e7Z2dkpx1hbWyM1NRUAVNLDh9nb2+PWrVt1rkkul+Ovv/6q8zxPU5sVcUTUuBUWFuLu3bu6LoNIq4qKigCgQf6bSPpPLpfX2y4DouZMFAUYSgywaHpPLFx3msEXNRqmxhK8O6U7Otch8KqJiIgIJCUl4ciRI2r3QkJC4OTkhC1bttRqzkWLFiEqKgoHDhxQW1FWUVGBkJAQGBkZ4eeff9Zo9Zqvry8sLS2VPbPi4+OxdetWnDt3DikpKSgrK4OrqytGjhyJKVOmwMDAQPneM2fOYPLkyfj3v/+N8PBw5fX8/Hx88cUXOHjwIHJzc+Hu7o7p06fXqq64uDjcuXMHzz//vNq9/fv3o6KiAhERESqrzHx8fBAQEICff/4ZixYtUlmg1KNHDxgbG2P//v31H3o11r+wFhcXo0WLFtXeq0ovq/7SXVxcDADVBmRV46vGEBERERERNQcGogATY0P8+7VeWPL1WcRcf3xPZaKG0NLCGB9O7wlXe/M6z1VaWorMzEyVa4IgwMrKqs5zP864ceMQFRWFHTt24L333lO5d+zYMaSmpuKdd97RKPACgMzMTOTm5ioP/jt79izOnDmDvn37wtnZGaWlpfjtt9+wdOlS3Lt3Dx988MET5ysvL8e0adNw4cIFDBgwAIGBgUhJScF7772HNm3a1LiuM2fOAEC1O/EuXrwIoHJH3qO6du2Ks2fP4vr16/D19VVel0gk8PHxwfnz5zX64Vf9bOBsYMbGxigtLa32XklJCQDAxMREORbAE8c/uu1RE6IowtPTs87z1ExRAz2HiOqTqalpA35uEDWMqh+Y8c82aUNMTIyuSyDSawaiAEFigIUv98Dn2y/gWEySrkuiZsq5lRk+mhGIlhbGGodCDztw4AAOHDigck0qleLy5ct1nvtxOnToAH9/f+zbtw9z5sxR2U64Y8cOGBoaqqyyeprc3FxkZmYqe3p9/vnnkMvlGDlyJAAgLCxMrW/5lClT8PbbbyM6Ohqvv/46bG0fv2Juz549uHDhAiZOnIiFCxcqr4eGhlbbD+1xbt68CQDVNrBPS6s8MKO6nXcP79J7OPSqmqtqBdujze6fRi9CL3t7e9y+fRulpaVqK7ge/U2t+v+qbY6PSk1NfezWRyIiIiIiIn0migIgB96Z1A0tZEb44UTdW78Q1UbHNi3x/ss9YGIkUfacq6ugoCC1puoNsV1+/PjxmDNnDg4ePKjsKZaWloZjx45h8ODBaNmyZY3nGjVqlMprU1NTTJ06VXlon6mpqfJeaWkpCgsLIZfLERwcjP379yMuLg79+vV77PyHDh0CAMyYMUPluq+vLwIDA3Hy5Mka1Vm1os7S0lLtXtUOvOp23j26S+9hVXNlZGQ0z9DL19cXt27dwsWLFxEQEKByLyYmBk5OTrC2tgYA2NjYwNHREX/99ReKi4tVVnUlJSXh/v37CAoKatD6iYiIiIiIGgtRFKBQKDB9lA+sLY2x+cAVKBS6roqagx7eDpgb4Q8DUdRa4AUAtra2CAwM1Np8NTVo0CB8/PHHiI6OVoZeu3btQkVFBcaOHVuruSIjI2FjYwNRFGFhYQF3d3eV1WNFRUVYtWoVDhw4gKQk9VWaOTk5T5z/7t27sLCwUK64epi7u3uNQ68qimo+NKp24JWWlqrtsHt0l151c2my6k8vOoFW/eH56quvVK4fOnQISUlJGDFihMr1ESNGoKioCNu3b1e5/vXXX6vMR0RERERE1BxVfXP5XL/2mD85AEaGBk95B1HdPNvLDe9OCdB64FVX5eXlGr9XKpUiPDwc58+fR3x8PORyOXbu3Ak3Nzc888wztZrLz88PgYGB6NGjBzp16qR2+uKcOXOwfv169OrVC0uXLsX69evx9ddf4+233wZQeRhMQ6hacJSdna127+EtjI960tbHqrmq5q6NRrvSa8+ePUhOTgYAZUq5atUq5f3XXntN+evAwEAMGzYM+/fvxyuvvIL+/fsjMTERmzZtQtu2bfHyyy+rzD1t2jT8/PPPiIyMRFJSEjw8PHDu3Dns3bsXw4YNQ8+ePRvgKyQiIiIiImr8An0d0crKFIs2/o6svBJdl0N6KGJIR4wZ0AEKhUIngZeVlRX+/PNPtevFxcW4f/9+tf2pamrcuHHYuHEjoqOjERQUhKSkJMyfP78u5arJy8vD4cOHMWLECHz00Ucq927fvl2jOVq3bo2EhASkpaWprfaKj4+vcS0dOnRQPvfRAMvX1xfHjx9HbGysWnP8mJgYGBsbo3379mpz3rlzBxYWFhq1omq0K7127dqFL7/8El9++aUy9Kp6/eWXX6qN/+STTzB79mwkJCTgww8/xK5duxAWFoaoqCiYmZmpjDUzM8O2bdvw/PPP4+DBg/jwww9x8eJFzJ49G5988kmDfH1ERERERERNRVunFvh8Vh+0cbDQdSmkR4ykBpg9wQ9jBlQGJdpoWq8JNzc3FBQUIDY2VuX6hg0b6rxCysXFBUFBQdizZw+ioqIglUqVzee1per37dEthfn5+di0aVON5hg4cCAAYO3atSrXL126hFOnTtW4lqoVbNUdPjNs2DAYGBjgm2++UVlBd/nyZZw7dw6hoaFq2xvLysoQFxeHgIAAjfqwNdqVXlu2bKnVeENDQ8yYMUOt6drjtGzZEosWLcKiRYs0KY+IiIiIiKjZEEUBVubGWPZmb6zfcxkHf7+j65KoiWvjYIH5kwPg1Mrs6YPr2bhx4/D111/jtddew+TJk2Fubo7ff/8d165dg5WVlVbmP378OI4ePYrhw4drZc6HmZmZITg4GD/88AOkUik6d+6M9PR07Nq1q8ZbAkeNGoVdu3YhKioKaWlpCAwMREpKCrZt24ZOnTpVuxKuOh07doSbmxt+/fVXvPrqqyr3qnbirV27FhEREQgLC0NWVhY2bdoEa2trzJ49W22+06dPo7i4GEOHDq3R8x/VaFd6ERERERERUeMhigIMJSJeH90F704JgJmJoa5LoiZqaC83LH+rDxxsZLouBQDg4OCAtWvXwsnJCStXrsR//vMfGBsbIyoqSuVURE3169dPuTVv3LhxdZ6vOpGRkRgzZgyOHz+Ojz76CPv378fEiROVPb2eRiKRYMOGDZg0aRJiY2PxySef4MSJE1iyZMkTT318lCAImDBhAmJjY3Hrlvrpr7NmzcKHH36I/Px8LFmyBJs2bUKvXr3w7bffwsHBQW38nj17YGNjg9DQ0BrXoFKPorqW+lQnVcv4unbt2iDPu5KQgXkrTzTIs4iofnw6Mwid3GrfmJGosfvrr78AAJ6enjquhPRBQ/8di4geT6FQICuvBJFbzyMuPkPX5VATYW5qiDfGdkUPbwcoFAqdbWdsaHK5HAMHDoSRkRF+/PFHXZdT74qKijB48GAEBwdj8eLFGs9z7949DBkyBPPnz8ekSZM0moMrvYiIiIiIiKhWBEGApZkRPn61FyYN9oRBIzptjxonr7bWWDGnH57xqlzx1FwCLwA4fPgwEhMT622VV2NjYmKCOXPmYPfu3TVupF+dlStXwtXVtU6/b422pxcRERERERE1XlWn7I0d6IEuHWwRufUPpGUW6rgqamxEUcDYAR0wbqAHgOYVdh05cgQpKSlYvXo1WrVqhdGjR+u6pAYzfPhwDB8+vE5zfPrpp3Wug6EXERERERER1Ul7FyusmNMPK7+LxbGYJF2XQ42EjaUx5kzsBq+21s1qO2OVxYsXIy0tDR4eHnj//ffVTiak+sfQi4iIiIiIiOpEFAUYGRrgnUnd4OfRChv3xSGvsEzXZZGOCAIwsHtrvDjcC6ZGhn9fa16BF1C50ot0i6EXERERERER1VnVdseQbi54xsse3/x4FT//fhtyHp3WrHRobYVXw33RzsUScrlC+eeCSBcYehEREREREZHWCIIAUxNDvPZ8Zzzbyw1rv7+EuFs84VHftTCT4oWhnTCwuyvkfyedDLxI1xh6ERERERERkVaJf29la21njn+/HoRjMYn4ev+feJBdrOPKSNtEUcDQXm6YNNgTJkYS5TWixoChFxEREREREdWLqvAjqIsTeng7IPqX69j9602Ulst1XBlpg7e7NV4N90Vre4tm2aieGj+GXkRERERERFSvREGAoUTEpCEdEdrDFRv2xuH05RRdl0UasrE0xtTh3gju4qTcysjAixojhl5ERERERERU76pCEZsWJnh3SndcunEf2w9dY7+vJsTK3Aij+rbD0F5ukEhEANzKSI0bQy8iIiIiIiJqMFUhibe7Df79ui2u383CriM38HtcCk96bKRsLI0R3q89BvdoA4lB5T8/ruyipoChFxERERERETW4qvCrnbMlFkzpjpQHBdh19AaOnL+HMvb8ahQcrGUI79cOA7q3hoEoMOiiJoehFxEREREREelMVfhl19IUM0d3QcSQjth7LB4/nrqNgqIyHVfXPHVya4mRfdqhh7c9AK7qoqaLoRcRERERERHpXFX4ZSGTYvKznTB2QAf8dPo29h27hfvZRTquTv+JooBAXweM6tMOHVpbQS7naYzU9DH0IiIiIiIiokajKmgxkkoQ1tsdw4Pa4nRcCo6cu4cL19JRwcZfWtXexRJ9/JzR188ZLcyMlKcxskE96QOGXkRERERERNQoCYIAAwMBgT6OCOrshNyCUhz94x6Onr+H+KQcXZfXZDnYyNDXzxn9/F3gYCODQvFPkMiwi/QJQy8iIiIiIiJq1KqCGHNTQ4wIbouw3u64l5aHY7FJOHkxGffS8nRcYeNnaW6E3l2c0NffGe1drAAA8r/DLm5jJH3F0IuIiIiIiIiahIfDGSdbM0wc5ImJgzyRmJ6H438HYHdSGYBVMTMxRHcve/T1d0bndrYQRUG5fREARIZdpOcYehEREREREVGT8/A2PEdbM4wP9cT4UE9k5BThcvwDxMVn4M9bGUhMz9dhlQ3L3NQQXm1t4ONuDd/2tmjjYAEAkMsVyt8vbl+k5oShFxERERERETVpD69Ysm5hgt5dnNHXzwUAkJNfgsvxD/DnrQzExWfgTmouFHrSC99CJoVXW2v4uNvAt50NXP8OuRSPfIEMuqi5YuhFREREREREeuXhkKeFmZGyET4AFBSVIe5W5UqwG/eykXw/H1l5JboqtcZkxhI42prBydYMHVpbqYRccoUCD8da7NFFVImhFxEREREREem1h0MwmYkhunW0xzNeDsprxaXlSH5QgOT7+Ui+X4DkBwVIeZCP5AcFyG7AQMxQIsLBWvZ3uCVThlwudmawkBkpxz0acrE3F1H1GHoRERERERFRs2LwyHY/Y6kEbg4WcLU3h4EoqtwrKilHyoMCpDwoQEFxGYpLylFcWoHi0nIUl1SgqLRc+evikvLK1yUVUCgUkBoawMjQAFJDA0gNRRgZGsDUxBBmf//P3FQKmakhLGRSONmawcbSRCXAkssVgKAeajHkIqoZhl5ERERERETU7AmCAINqwiQTIwncHC3g6mCuHKet0EkuV0ABBQQI1fbdYi8uorph6EVERERERET0BI8LxOqqMtRisEVUX8SnDyEiIiIiIiIiImpaGHoREREREREREZHeYehFRERERERERER6h6EXERERERERERHpHYZeRERERERERESkdxh6ERERERERERGR3mHoRUREREREREREeoehFxERERERERER6R2GXkREREREREREpHcYehERERERERERkd5h6EVERERERERERHqHoRcREREREREREekdhl5ERERERERERKR3GHoREREREREREZHeYehFRERERERERER6h6EXERERERERERHpHYZeRERERERERESkdxh6ERERERERERGR3mHoRUREREREREREeoehFxERERERERER6R2GXkREREREREREpHcYehERERERERERkd5h6EVERERERERERHpHousCdOnQoUPYsGEDrl+/DkNDQ/j7++Ott96Cp6enrksjIiLSC61bt9Z1CURERETUTDXb0Ou7777Dv/71L3To0AFz5sxBSUkJtm7divHjx2P79u0MvoiIGoC8pBCl6Xd0XQbVo6ol5cUZOi2D6pG0lStEI1Ndl0FERESkplmGXjk5Ofjkk09gb2+P7du3w8zMDAAwZMgQDB06FB999BGioqJ0XCURkf4rTb+D5G/+pesyiKgOHCcvhrFLR12XQURERKSmWYZehw8fRn5+Pl588UVl4AUAjo6OGDRoEHbv3o3ExEQ4OzvrsEoiIqKmxXbYTJh37lejsek/rET+paP1XBERERERNWfNMvS6ePEiAKBr165q97p27Yrdu3fj0qVLGodecrkcAPDHH39oXmQNCYIACAI+mOBS788iovpTnH0XFy7cgUKh0HUpDUYQBAgCgCHv6roU0pIWzq41HlvkMxQ5Tj3rsRpqKDkPiqC4f6FZfX4RERFR09AsQ6+0tDQAgL29vdq9qmtVY+pCFBvucExBFBrsWURUTwShMshubprj16ynsrKyUVxcUu09a2trGBsbA6j84VBuXj4g8BBpfVH5M7j6/3e56geLRERERDXRLEOvoqIiAIBUKlW7V3Wtaowm/P39NX4vERGRvhNFET4+Proug4iIiIj0XLP8EauJiQkAoLS0VO1e1bWqMURERERERERE1PQ0y9DLzs4OAJCamqp2r+pa1RgiIiIiIiIiImp6mmXo5evrCwCIiYlRuxcbGwsA3HZBRERERERERNSENcvQa8CAAZDJZPjuu++Qn5+vvJ6cnIyDBw/C398fLi48DZGIiIiIiIiIqKkSFM30fOlvv/0W77//Pjp06ICxY8eitLQUW7duRVZWFqKiotCpUyddl0hERERERERERBpqtqEXABw8eBAbN27E9evXYWhoCH9/f8yaNQuenp66Lo2IiIiIiIiIiOqgWYdeRERERERERESkn5plTy8iIiIiIiIiItJvDL2IiIiIiIiIiEjvMPQiIiIiIiIiIiK9w9CLiIiIiIiIiIj0DkMvIiIiIiIiIiLSOwy9iIiIiIiIiIhI7zD0IqpGSEgIIiIiVK5FREQgJCRERxXVzpkzZ+Dh4YHvv/++RuNXrFgBDw8PJCYm1vgZP/zwA7y8vHDnzh1Ny8S8efMwdOhQlJeXazwHEWnPuXPnMHbsWPj5+cHDwwObNm2q1+clJibCw8MDK1as0Nqca9asQUBAAHJycjSeY9KkSXjppZe0VhMRERER6YZE1wUQ1UViYiL69+//2PtTp07FvHnzGrCi2ps/fz52796tfC2KIiwsLODt7Y3JkyejT58+OqyueoWFhYiMjMRzzz0HV1dXtfvR0dHYunUrbt++DVNTU/Tq1QuzZ8+Gk5OTyriZM2diyJAh+PbbbzFp0qSGKp+oSXn0c04QBJiamsLKygodOnRA3759MWzYMMhksjo9JycnB6+//jrs7Owwd+5cmJiYwNvbu67la2TFihXo2LEjBgwYUKv3paWlYe3atXj11VfRokUL5fX09HRERUXhypUruHr1Ku7fv4/u3btjy5Yt1c4za9YsTJgwAUePHkW/fv3q9LUQERERke4w9CK90K1bN4wZM0btert27XRQjWYWLFgAKysrlJeXIyEhAdHR0Zg+fTqWLVuGYcOG1WqugIAAXLp0CRJJ/fwrHh0djbS0tGpXQnzxxRdYvXo1/Pz88O677yIzMxObN2/GmTNnsHPnTtjb2yvHuri4IDQ0FGvWrMHYsWNhaGhYL/US6YOHP+eKi4uRkpKC33//HQsXLsSqVauwfPly+Pv7azz/5cuXkZOTg8WLFyM0NFRbZWtk5cqVGDVqVK1Dr/Xr10OhUGDChAkq1xMSErBmzRrY2dnBx8cHR44ceeI8/v7+6NKlC1asWMHQi4iIiKgJY+hFesHFxQVhYWG6LqNOBgwYAGdnZ+Xr0NBQjB49GqtXr6516CWKIoyMjLRdIgBAoVBg27Zt6Natm9oqr4SEBKxbtw5eXl7YsmWLMnQLDg7G6NGjsXz5cixdulTlPeHh4Thw4AAOHTqEoUOH1kvNRPrgcZ9zx44dw5tvvokZM2Zgz549Kp8jtfHgwQMAUFkh1ZQUFBRg9+7dCA0NhZmZmco9Ly8vnDp1CtbW1gAADw+Pp84XHh6OhQsXIjY2Fl26dKmPkomIiIionrGnFzULT+rHVV3/rppYtGgRPDw8cPPmTbV7FRUV6NOnD0JDQ6FQKGo9NwD4+vrC0tJS2TMrPj4eH374IYYNGwZ/f3/4+vpi+PDh2LhxIyoqKlTe+7ieXvn5+Vi8eDGCgoLg6+uLUaNG4aeffqpVXXFxcbhz50612y7379+PiooKREREqKwy8/HxQUBAAH7++WcUFxervKdHjx4wNjbG/v37a1UHEVXq3bs33nnnHeTl5WHdunVq948cOYIXXngB3bp1g4+PD4YOHYqvvvoKcrlcOcbDw0O5FXzy5Mnw8PBQBkNyuRxr1qxBREQEgoKC4O3tjeDgYMybNw/Jyclqz/Pw8MD8+fPVrtekf1fVZxcA7N69W1lHTXoOHj9+HPn5+ejbt6/aPTMzM2XgVVNV8/CziYiIiKjp4kov0gulpaXIzMxUuSYIAqysrOrtmePGjUNUVBR27NiB9957T+XesWPHkJqainfeeQeCIGg0f2ZmJnJzc2FjYwMAOHv2LM6cOYO+ffvC2dkZpaWl+O2337B06VLcu3cPH3zwwRPnKy8vx7Rp03DhwgUMGDAAgYGBSElJwXvvvYc2bdrUuK4zZ84AQLUrHy5evAgA6Nq1q9q9rl274uzZs7h+/Tp8fX2V1yUSCXx8fHD+/HnI5XKIIrN4otoKDw/Hxx9/jKNHj6pcX7t2rXLb4yuvvAKZTIbz589j6dKl+PPPP7Fs2TIAwNKlS/HHH39gx44deOWVV9C2bVvlHGVlZVi/fj1CQ0PRp08fmJub49q1a9i1axdOnz6Nffv2wdLSUitfh7u7O5YuXYq5c+eqbVtv2bLlE99b9dnUuXNnrdRiZ2cHR0dH5bxERERE1PQw9CK9cODAARw4cEDlmlQqxeXLl+vtmR06dIC/vz/27duHOXPmqGwn3LFjBwwNDREeHl7j+XJzc5GZmans6fX5559DLpdj5MiRAICwsDCMHz9e5T1TpkzB22+/jejoaLz++uuwtbV97Px79uzBhQsXMHHiRCxcuFB5PTQ0tNp+aI9TtbKtugb2aWlpAKDSt6uKnZ0dACA1NVUl9Kqa69y5c0hJSVFrdk9ET2dsbAw3Nzdcv34dBQUFkMlk+Ouvv/D5559j3Lhx+PDDD5Vjx48fD09PT3z22WcYN24cAgICEBYWhoqKCuzYsQOBgYF45plnlOOlUilOnDgBExMTlWcOGDAAL774Inbu3ImXX35ZK1+HjY0NwsLCMHfu3FpvW7958yYMDQ21+hni6uqKs2fPMpAnIiIiaqIYepFeCAoKUmuq3hDfoIwfPx5z5szBwYMHld+cpaWl4dixYxg8ePBTVyY8bNSoUSqvTU1NMXXqVLz55pvK11VKS0tRWFgIuVyO4OBg7N+/H3FxcU9suHzo0CEAwIwZM1Su+/r6IjAwECdPnqxRnVUr6qpb2VFUVASg8pvkR1WFglVjHlY1V0ZGBkMvIg1V9bHKz8+HTCbD3r17oVAoMGbMGLWVsP3798dnn32GEydOICAg4InzCoKgDLzkcjny8/NRXl4OT09PmJub49KlS/XzBdVSZmam1vuRWVpaoqKiAtnZ2bX6PCciIiKixoGhF+kFW1tbBAYGNvhzBw0ahI8//hjR0dHK0GvXrl2oqKjA2LFjazVXZGQkbGxsIIoiLCws4O7urrJ6rKioCKtWrcKBAweQlJSk9v6cnJwnzn/37l1YWFgoV1w9zN3dvcahV5XqepVVfWNcWloKY2NjlXslJSUqY6qbS9OtoERUGXYB/4Rf8fHxAPDEFaf379+v0dy//PILNmzYgLi4OJSVlancy87O1qDa+qFpD8WGmo+IiIiIGhZDL2r2ysvLNX6vVCpFeHg4NmzYgPj4eLi5uWHnzp1wc3NT2R5UE35+fk88dW3OnDk4fPgwRo8ejW7dusHKygoSiQRxcXFYtmyZSlPq+lTVDDo7O1ttG6OdnR2uX7+O1NRUtT5hT9r6WPVNc20bTRNRpeLiYiQkJKBVq1aQyWQAoPxM+O9//6uyUvRhrVq1eurcv/zyC15//XV4e3tjwYIFcHBwUIbas2bNqnEw9OiBG9rWsmVL3L59W6tzZmdnw8DAoF77QxIRERFR/WHoRc2ClZUV/vzzT7XrxcXFuH//frX9qWpq3Lhx2LhxI6KjoxEUFISkpKRqTy6ri7y8PBw+fBgjRozARx99pHKvpt/ktW7dGgkJCUhLS1Nb7VW1IqQmOnTooHzuowGWr68vjh8/jtjYWLXQKyYmBsbGxmjfvr3anHfu3IGFhUW1gRgRPd3333+PsrIylS3Obdq0wfHjx2Fra1un5u579uyBkZERtm7dqrJSs7CwELm5uWrjLS0tq139dffuXY1rqAkPDw+cPXsW9+7dg4uLi1bmvHPnDtq1a8dVqERERERNFLuyUrPg5uaGgoICxMbGqlzfsGFDnVdIubi4ICgoCHv27EFUVBSkUqmy+by2VH3D9eiKivz8fGzatKlGcwwcOBBA5WluD7t06RJOnTpV41qqVrDFxMSo3Rs2bBgMDAzwzTffqKygu3z5Ms6dO4fQ0FC17Y1lZWWIi4tDQEAAG0UTaeDYsWOIjIyEubm5Ss++kSNHQhAEfPbZZygtLVV7X3FxsXJL5JOIoghBENQ+K1etWlXt56ebmxtiYmJQWFiovFZRUYGNGzfW+GsyNTWt9bbJJ302aSItLQ0pKSm1XrVLRERERI0HV3pRszBu3Dh8/fXXeO211zB58mSYm5vj999/x7Vr17SybWXcuHE4fvw4jh49iuHDh2t9K4yZmRmCg4Pxww8/QCqVonPnzkhPT8euXbtqvCVw1KhR2LVrF6KiopCWlobAwECkpKRg27Zt6NSpU7Ur4arTsWNHuLm54ddff8Wrr76qcq9t27Z4+eWXsXbtWkRERCAsLAxZWVnYtGkTrK2tMXv2bLX5Tp8+jeLiYgwdOrRGzydqru7du4e9e/cCqOyRl5qailOnTiEmJgb29vZYvny5ykEQ3t7emD17NpYtW4Znn30Ww4cPh6OjI7KysnDr1i3873//w6pVq54a6gwePBg///wzIiIiMGrUKCgUCpw4cQI3b96s9rPuhRdewFtvvYVJkyZh1KhRKCkpwU8//QRDQ8Maf61du3bFqVOnsHbtWjg5OUEQBPTr1++x2zSBygNNLCws8Ouvv2LEiBFq91etWqXyOikpSXnN0dFR7YcVR44cAQB+NhERERE1YQy9qFlwcHDA2rVrsXz5cqxcuRIymQy9e/dGVFRUrRvOV6dfv36wt7dHamoqxo0bp4WK1UVGRmL58uX49ddfsW/fPjg5OWHixInw8vLClClTnvp+iUSCDRs24PPPP8fBgwdx7NgxuLu7Y8mSJbh582aNQy9BEDBhwgQsWbIEt27dQtu2bVXuz5o1C46OjoiKisKSJUtgamqKXr16YdasWXBwcFCbb8+ePbCxsUFoaGiNnk/UXJ0/fx7nz59XnqZoZWUFDw8PLFq0CMOGDVP28nrY9OnT4ePjg82bN2P79u3Iz8+HpaUlXFxc8PLLL8PDw+Opz3322WdRWFiIzZs3IzIyEjKZDIGBgdi2bRsmTJigNn7IkCHIyMjA5s2b8emnn8LW1hYjR47EiBEjMHjw4Bp9rR988AEWLVqE9evXIy8vDwBw+PDhJ4ZeJiYmCA8Px/bt25GbmwsLCwuV+19++aXK66SkJOW17t27q4Vee/bsgZeXF7p06VKjmomIiIio8REUPJqIqM7kcjkGDhwIIyMj/Pjjj7oup94VFRVh8ODBCA4OxuLFizWe5969exgyZAjmz5+PSZMmabFCImqO0tPTMWjQIEyfPl1tJWptnD9/HhMnTsSaNWtU+qQRERERUdPCBjpEWnD48GEkJibW2yqvxsbExARz5szB7t2763Ra2sqVK+Hq6tpsft+IqH61atUKM2bMwFdffYWcnByN5/niiy8QFBTEwIuIiIioieNKL6I6OHLkCFJSUrB69WoIgoBDhw6pNWonIiIiIiIioobH0IuoDkJCQpCWlgYPDw+8//776Ny5s65LIiIiIiIiIiIw9CIiIiIiIiIiIj3Enl5ERERERERERKR3GHoREREREREREZHeYehFRERERERERER6h6EXERERERERERHpHYZeRERERERERESkdxh6ERERERERERGR3mHoRUREREREREREeoehFxERERERERER6R2GXkREREREREREpHcYehERERERERERkd75/2Rc9Ch6sgECAAAAAElFTkSuQmCC\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Class imbalance ratio (Majority:Minority) = 63.9:1\n"
          ]
        }
      ],
      "source": [
        "# ── Class imbalance visualisation ──────────────────────────────────────────────\n",
        "fig, axes = plt.subplots(1, 2, figsize=(12, 4))\n",
        "\n",
        "counts = df['target'].value_counts()\n",
        "axes[0].bar(['Fully Paid (0)', 'Default (1)'], counts.values,\n",
        "            color=['#4C72B0', '#DD8452'], edgecolor='white')\n",
        "axes[0].set_title('Class Distribution (Count)')\n",
        "axes[0].set_ylabel('Number of Loans')\n",
        "for bar, v in zip(axes[0].patches, counts.values):\n",
        "    axes[0].text(bar.get_x() + bar.get_width()/2, bar.get_height()*0.98,\n",
        "                 f'{v:,}', ha='center', va='top', color='white', fontweight='bold')\n",
        "\n",
        "axes[1].pie(counts.values, labels=['Fully Paid (0)', 'Default (1)'],\n",
        "            autopct='%1.1f%%', colors=['#4C72B0', '#DD8452'],\n",
        "            startangle=140, wedgeprops={'edgecolor': 'white'})\n",
        "axes[1].set_title('Class Balance (Proportion)')\n",
        "\n",
        "plt.suptitle('Target Variable: Loan Default Distribution', fontsize=13, fontweight='bold')\n",
        "plt.tight_layout()\n",
        "plt.show()\n",
        "print(f\"Class imbalance ratio (Majority:Minority) = {counts[0]/counts[1]:.1f}:1\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 57,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 435
        },
        "id": "eqy7RWBFlCKn",
        "outputId": "005167da-21fc-4f9f-9cab-e1aa6722f195"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Columns with missing values: 10\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1320x440 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "# ── Missing value analysis ─────────────────────────────────────────────────────\n",
        "miss = (df.isnull().sum() / len(df) * 100).sort_values(ascending=False)\n",
        "miss = miss[miss > 0]\n",
        "print(f\"Columns with missing values: {len(miss)}\")\n",
        "\n",
        "fig, ax = plt.subplots(figsize=(12, max(4, len(miss[:30])*0.35)))\n",
        "miss[:30].plot.barh(ax=ax, color='#4C72B0')\n",
        "ax.axvline(50, color='red', linestyle='--', label='50% threshold')\n",
        "ax.set_xlabel('Missing (%)')\n",
        "ax.set_title('Top-30 Columns by Missing Data %')\n",
        "ax.legend()\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "iZkn_jU0lCKo"
      },
      "source": [
        "---\n",
        "## 3. Exploratory Data Analysis (Test 2)\n",
        "\n",
        "**Goal:** Correlation heatmap, default rate by key financial features (loan grade, income,\n",
        "interest rate, employment length, purpose), and bias indicators."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 58,
      "metadata": {
        "id": "bIGeo-GMlCKo"
      },
      "outputs": [],
      "source": [
        "# ── Select key numeric features for EDA ────────────────────────────────────────\n",
        "numeric_eda = [\n",
        "    'loan_amnt', 'funded_amnt', 'int_rate', 'installment',\n",
        "    'annual_inc', 'dti', 'open_acc', 'revol_bal', 'revol_util',\n",
        "    'total_acc', 'target'\n",
        "]\n",
        "# Keep only columns that exist in this dataset\n",
        "numeric_eda = [c for c in numeric_eda if c in df.columns]\n",
        "\n",
        "df_num = df[numeric_eda].copy()\n",
        "# Cap extreme outliers at 99th percentile for visualisation\n",
        "for col in df_num.columns:\n",
        "    if col != 'target':\n",
        "        df_num[col] = df_num[col].clip(upper=df_num[col].quantile(0.99))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 59,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 997
        },
        "id": "ZQDKXbEAlCKo",
        "outputId": "33ebe655-a40f-41e8-ef87-0e9fa4512e80"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1210x990 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "# ── Correlation heatmap ────────────────────────────────────────────────────────\n",
        "fig, ax = plt.subplots(figsize=(11, 9))\n",
        "corr = df_num.corr()\n",
        "mask = np.triu(np.ones_like(corr, dtype=bool))\n",
        "sns.heatmap(corr, mask=mask, annot=True, fmt='.2f', cmap='RdYlGn',\n",
        "            center=0, linewidths=0.5, ax=ax, square=True,\n",
        "            cbar_kws={'shrink': 0.8})\n",
        "ax.set_title('Correlation Heatmap of Key Numerical Features', fontsize=13, fontweight='bold')\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 60,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 433
        },
        "id": "asCxocXulCKp",
        "outputId": "e0c7f363-2607-41cb-c447-05f41fd3b578"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 880x440 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "# ── Default rate by loan grade ─────────────────────────────────────────────────\n",
        "if 'grade' in df.columns:\n",
        "    grade_default = df.groupby('grade')['target'].mean().sort_index()\n",
        "    fig, ax = plt.subplots(figsize=(8, 4))\n",
        "    bars = ax.bar(grade_default.index, grade_default.values * 100,\n",
        "                  color=plt.cm.RdYlGn_r(np.linspace(0.1, 0.9, len(grade_default))))\n",
        "    ax.set_ylabel('Default Rate (%)')\n",
        "    ax.set_xlabel('Loan Grade')\n",
        "    ax.set_title('Default Rate by Loan Grade')\n",
        "    ax.yaxis.set_major_formatter(mtick.PercentFormatter())\n",
        "    for bar in bars:\n",
        "        ax.text(bar.get_x() + bar.get_width()/2, bar.get_height() + 0.3,\n",
        "                f'{bar.get_height():.1f}%', ha='center', va='bottom', fontsize=9)\n",
        "    plt.tight_layout()\n",
        "    plt.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 61,
      "metadata": {
        "id": "2d8crJaulCKp"
      },
      "outputs": [],
      "source": [
        "# ── Default rate by loan purpose ───────────────────────────────────────────────\n",
        "if 'purpose' in df.columns:\n",
        "    purpose_default = (df.groupby('purpose')['target']\n",
        "                       .agg(['mean', 'count'])\n",
        "                       .sort_values('mean', ascending=True))\n",
        "    purpose_default = purpose_default[purpose_default['count'] > 500]  # filter small groups\n",
        "\n",
        "    fig, ax = plt.subplots(figsize=(10, 5))\n",
        "    ax.barh(purpose_default.index, purpose_default['mean'] * 100,\n",
        "            color='#4C72B0', edgecolor='white')\n",
        "    ax.set_xlabel('Default Rate (%)')\n",
        "    ax.set_title('Default Rate by Loan Purpose')\n",
        "    ax.xaxis.set_major_formatter(mtick.PercentFormatter())\n",
        "    plt.tight_layout()\n",
        "    plt.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 62,
      "metadata": {
        "id": "03OSiSdylCKp"
      },
      "outputs": [],
      "source": [
        "# ── Interest rate distribution by outcome ──────────────────────────────────────\n",
        "if 'int_rate' in df.columns:\n",
        "    fig, ax = plt.subplots(figsize=(9, 4))\n",
        "    for label, color in zip([0, 1], ['#4C72B0', '#DD8452']):\n",
        "        subset = df[df['target'] == label]['int_rate'].dropna()\n",
        "        ax.hist(subset, bins=50, alpha=0.6, color=color,\n",
        "                label='Fully Paid' if label == 0 else 'Default', density=True)\n",
        "    ax.set_xlabel('Interest Rate (%)')\n",
        "    ax.set_ylabel('Density')\n",
        "    ax.set_title('Interest Rate Distribution by Loan Outcome')\n",
        "    ax.legend()\n",
        "    plt.tight_layout()\n",
        "    plt.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 63,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 435
        },
        "id": "i1CImCrolCKq",
        "outputId": "a4423a47-7214-42a3-aded-b3724c4ef0ef"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1100x440 with 1 Axes>"
            ],
            "image/png": 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          },
          "metadata": {}
        }
      ],
      "source": [
        "# ── Default rate by employment length ──────────────────────────────────────────\n",
        "if 'emp_length' in df.columns:\n",
        "    emp_order = ['< 1 year', '1 year', '2 years', '3 years', '4 years',\n",
        "                 '5 years', '6 years', '7 years', '8 years', '9 years', '10+ years']\n",
        "    emp_default = df.groupby('emp_length')['target'].mean()\n",
        "    emp_default = emp_default.reindex([e for e in emp_order if e in emp_default.index])\n",
        "\n",
        "    fig, ax = plt.subplots(figsize=(10, 4))\n",
        "    ax.bar(range(len(emp_default)), emp_default.values * 100, color='#55A868', edgecolor='white')\n",
        "    ax.set_xticks(range(len(emp_default)))\n",
        "    ax.set_xticklabels(emp_default.index, rotation=30, ha='right')\n",
        "    ax.set_ylabel('Default Rate (%)')\n",
        "    ax.set_title('Default Rate by Employment Length')\n",
        "    ax.yaxis.set_major_formatter(mtick.PercentFormatter())\n",
        "    plt.tight_layout()\n",
        "    plt.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 64,
      "metadata": {
        "id": "3kHjz5AClCKq"
      },
      "outputs": [],
      "source": [
        "# ── Annual income distribution (log scale) by outcome ─────────────────────────\n",
        "if 'annual_inc' in df.columns:\n",
        "    fig, ax = plt.subplots(figsize=(9, 4))\n",
        "    inc_cap = df['annual_inc'].clip(upper=df['annual_inc'].quantile(0.99))\n",
        "    for label, color in zip([0, 1], ['#4C72B0', '#DD8452']):\n",
        "        subset = inc_cap[df['target'] == label]\n",
        "        ax.hist(np.log1p(subset), bins=60, alpha=0.6, color=color,\n",
        "                label='Fully Paid' if label == 0 else 'Default', density=True)\n",
        "    ax.set_xlabel('log(1 + Annual Income)')\n",
        "    ax.set_ylabel('Density')\n",
        "    ax.set_title('Annual Income Distribution by Loan Outcome (log scale)')\n",
        "    ax.legend()\n",
        "    plt.tight_layout()\n",
        "    plt.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 65,
      "metadata": {
        "id": "e_5jUx-IlCKq"
      },
      "outputs": [],
      "source": [
        "# ── Potential bias check: home ownership ──────────────────────────────────────\n",
        "if 'home_ownership' in df.columns:\n",
        "    ho = df.groupby('home_ownership')['target'].agg(['mean', 'count'])\n",
        "    ho = ho[ho['count'] > 100]\n",
        "    fig, ax = plt.subplots(figsize=(7, 4))\n",
        "    ax.bar(ho.index, ho['mean'] * 100, color='#C44E52', edgecolor='white')\n",
        "    ax.set_ylabel('Default Rate (%)')\n",
        "    ax.set_title('Default Rate by Home Ownership (Bias Indicator)')\n",
        "    ax.yaxis.set_major_formatter(mtick.PercentFormatter())\n",
        "    plt.tight_layout()\n",
        "    plt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2tHkn3l8lCKr"
      },
      "source": [
        "---\n",
        "## 4. Preprocessing Pipeline (Test 3)\n",
        "\n",
        "**Goal:** Select features, handle missing values, encode categoricals, scale numerics, split data."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 66,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ukjh60bQlCKs",
        "outputId": "425c8652-8b5b-4863-8a09-644eece5d754"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Dropping high-missing columns: []\n",
            "Final feature set (5 features): ['term', 'installment', 'grade', 'sub_grade', 'emp_length']\n",
            "Dataset shape: (454, 6)\n"
          ]
        }
      ],
      "source": [
        "# ── Feature selection ──────────────────────────────────────────────────────────\n",
        "# Chosen columns based on financial relevance and data availability\n",
        "CANDIDATE_FEATURES = [\n",
        "    # Loan characteristics\n",
        "    'loan_amnt', 'funded_amnt', 'term', 'int_rate', 'installment',\n",
        "    'grade', 'sub_grade',\n",
        "    # Borrower financials\n",
        "    'annual_inc', 'dti', 'emp_length',\n",
        "    # Credit history\n",
        "    'open_acc', 'pub_rec', 'revol_bal', 'revol_util', 'total_acc',\n",
        "    'delinq_2yrs', 'inq_last_6mths',\n",
        "    # Loan metadata\n",
        "    'purpose', 'home_ownership', 'verification_status',\n",
        "]\n",
        "\n",
        "# Keep only those that exist\n",
        "features = [f for f in CANDIDATE_FEATURES if f in df.columns]\n",
        "TARGET = 'target'\n",
        "\n",
        "# Drop rows where target is missing\n",
        "df_model = df[features + [TARGET]].dropna(subset=[TARGET]).copy()\n",
        "\n",
        "# ── Drop columns with >50% missing ────────────────────────────────────────────\n",
        "high_miss = [c for c in features if df_model[c].isnull().mean() > 0.5]\n",
        "print(f\"Dropping high-missing columns: {high_miss}\")\n",
        "features = [f for f in features if f not in high_miss]\n",
        "df_model = df_model[features + [TARGET]]\n",
        "\n",
        "print(f\"Final feature set ({len(features)} features): {features}\")\n",
        "print(f\"Dataset shape: {df_model.shape}\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 67,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cM0ul3YmlCKt",
        "outputId": "a40e9dcc-8cdd-45b4-8d84-ee932e1ed65c"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Numeric features (3): ['term', 'installment', 'emp_length']\n",
            "Categorical features (2): ['grade', 'sub_grade']\n"
          ]
        }
      ],
      "source": [
        "# ── Identify numeric vs categorical ───────────────────────────────────────────\n",
        "num_features = df_model[features].select_dtypes(include=['number']).columns.tolist()\n",
        "cat_features = df_model[features].select_dtypes(include=['object', 'category']).columns.tolist()\n",
        "print(f\"Numeric features ({len(num_features)}): {num_features}\")\n",
        "print(f\"Categorical features ({len(cat_features)}): {cat_features}\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 68,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "miT3hpODlCKt",
        "outputId": "c9a95907-e0ad-4070-f4b6-8177ca061067"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Column type cleanup done.\n"
          ]
        }
      ],
      "source": [
        "# ── Clean specific categorical columns ────────────────────────────────────────\n",
        "# Convert 'term' to numeric months if it's a string\n",
        "if 'term' in df_model.columns and df_model['term'].dtype == object:\n",
        "    df_model['term'] = df_model['term'].str.extract(r'(\\d+)').astype(float)\n",
        "    if 'term' in cat_features:\n",
        "        cat_features.remove('term')\n",
        "    if 'term' not in num_features:\n",
        "        num_features.append('term')\n",
        "\n",
        "# Convert 'int_rate' if stored as string '15.32%'\n",
        "if 'int_rate' in df_model.columns and df_model['int_rate'].dtype == object:\n",
        "    df_model['int_rate'] = df_model['int_rate'].str.replace('%', '').astype(float)\n",
        "\n",
        "# Convert 'revol_util' if stored as string\n",
        "if 'revol_util' in df_model.columns and df_model['revol_util'].dtype == object:\n",
        "    df_model['revol_util'] = df_model['revol_util'].str.replace('%', '').astype(float)\n",
        "\n",
        "print(\"Column type cleanup done.\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 69,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qlKj2HlblCKt",
        "outputId": "9a51ecb6-10d9-4880-dd69-ff55dbbfbb96"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Preprocessing pipeline defined:\n",
            "  Numeric  (3): median impute → StandardScale\n",
            "  Categorical (2): mode impute → OrdinalEncode\n"
          ]
        }
      ],
      "source": [
        "from sklearn.preprocessing import OrdinalEncoder\n",
        "\n",
        "# ── Preprocessing pipelines ───────────────────────────────────────────────────\n",
        "numeric_transformer = Pipeline(steps=[\n",
        "    ('imputer', SimpleImputer(strategy='median')),\n",
        "    ('scaler', StandardScaler())\n",
        "])\n",
        "\n",
        "categorical_transformer = Pipeline(steps=[\n",
        "    ('imputer', SimpleImputer(strategy='most_frequent')),\n",
        "    ('encoder', OrdinalEncoder(handle_unknown='use_encoded_value', unknown_value=-1))\n",
        "])\n",
        "\n",
        "preprocessor = ColumnTransformer(transformers=[\n",
        "    ('num', numeric_transformer, num_features),\n",
        "    ('cat', categorical_transformer, cat_features)\n",
        "], remainder='drop')\n",
        "\n",
        "print(\"Preprocessing pipeline defined:\")\n",
        "print(f\"  Numeric  ({len(num_features)}): median impute → StandardScale\")\n",
        "print(f\"  Categorical ({len(cat_features)}): mode impute → OrdinalEncode\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 70,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "DHaiNSxTlCKt",
        "outputId": "7c134984-23b7-43b0-bcd8-0e231789b5b3"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Train: 363 samples  |  Test: 91 samples\n",
            "Train default rate: 1.65%  |  Test default rate: 1.10%\n"
          ]
        }
      ],
      "source": [
        "# ── Train / test split (stratified) ───────────────────────────────────────────\n",
        "X = df_model[features]\n",
        "y = df_model[TARGET]\n",
        "\n",
        "# Sub-sample if dataset is very large (>200 k rows) for Colab speed\n",
        "if len(X) > 200_000:\n",
        "    print(f\"Large dataset detected ({len(X):,} rows). Sampling 200,000 rows (stratified)…\")\n",
        "    from sklearn.utils import resample\n",
        "    X, _, y, _ = train_test_split(X, y, train_size=200_000,\n",
        "                                   stratify=y, random_state=SEED)\n",
        "\n",
        "X_train, X_test, y_train, y_test = train_test_split(\n",
        "    X, y, test_size=0.20, random_state=SEED, stratify=y\n",
        ")\n",
        "\n",
        "print(f\"Train: {X_train.shape[0]:,} samples  |  Test: {X_test.shape[0]:,} samples\")\n",
        "print(f\"Train default rate: {y_train.mean():.2%}  |  Test default rate: {y_test.mean():.2%}\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 71,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3L7pKqS4lCKu",
        "outputId": "8f2a7d43-757f-49d6-d291-13e97d40a62e"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Processed training set shape: (363, 5)\n",
            "✅ Preprocessing pipeline fitted and applied.\n"
          ]
        }
      ],
      "source": [
        "# ── Fit preprocessor and transform data ───────────────────────────────────────\n",
        "X_train_proc = preprocessor.fit_transform(X_train)\n",
        "X_test_proc  = preprocessor.transform(X_test)\n",
        "\n",
        "# Preserve feature names for interpretability later\n",
        "feature_names_out = num_features + cat_features\n",
        "\n",
        "print(f\"Processed training set shape: {X_train_proc.shape}\")\n",
        "print(\"✅ Preprocessing pipeline fitted and applied.\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ZUlIkcr5lCKu"
      },
      "source": [
        "---\n",
        "## 5. Baseline Logistic Regression (Test 4)\n",
        "\n",
        "**Goal:** Train a default logistic regression with `class_weight='balanced'` to handle imbalance."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 72,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Zuo5eQLPlCKu",
        "outputId": "b32ea35a-e274-4b0e-ed51-642f7f59f132"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "=== Baseline Logistic Regression — Test Set Performance ===\n",
            "              precision    recall  f1-score   support\n",
            "\n",
            "  Fully Paid       0.98      0.54      0.70        90\n",
            "     Default       0.00      0.00      0.00         1\n",
            "\n",
            "    accuracy                           0.54        91\n",
            "   macro avg       0.49      0.27      0.35        91\n",
            "weighted avg       0.97      0.54      0.69        91\n",
            "\n",
            "ROC-AUC : 0.4667\n"
          ]
        }
      ],
      "source": [
        "# ── Baseline Logistic Regression ──────────────────────────────────────────────\n",
        "lr_base = LogisticRegression(\n",
        "    max_iter=1000,\n",
        "    class_weight='balanced',\n",
        "    random_state=SEED\n",
        ")\n",
        "lr_base.fit(X_train_proc, y_train)\n",
        "\n",
        "y_pred_lr_base   = lr_base.predict(X_test_proc)\n",
        "y_proba_lr_base  = lr_base.predict_proba(X_test_proc)[:, 1]\n",
        "\n",
        "print(\"=== Baseline Logistic Regression — Test Set Performance ===\")\n",
        "print(classification_report(y_test, y_pred_lr_base, target_names=['Fully Paid', 'Default']))\n",
        "print(f\"ROC-AUC : {roc_auc_score(y_test, y_proba_lr_base):.4f}\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 73,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 435
        },
        "id": "AkTB5p9zlCKv",
        "outputId": "8d65e0b0-99b9-4061-9b42-e637cefc8738"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 550x440 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "# ── Confusion matrix helper ────────────────────────────────────────────────────\n",
        "def plot_confusion_matrix(y_true, y_pred, title, ax):\n",
        "    cm = confusion_matrix(y_true, y_pred)\n",
        "    sns.heatmap(cm, annot=True, fmt='d', cmap='Blues', ax=ax,\n",
        "                xticklabels=['Fully Paid', 'Default'],\n",
        "                yticklabels=['Fully Paid', 'Default'])\n",
        "    ax.set_xlabel('Predicted')\n",
        "    ax.set_ylabel('Actual')\n",
        "    ax.set_title(title)\n",
        "\n",
        "fig, ax = plt.subplots(figsize=(5, 4))\n",
        "plot_confusion_matrix(y_test, y_pred_lr_base, 'Baseline LR – Confusion Matrix', ax)\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "1LesvlH6lCKv"
      },
      "source": [
        "---\n",
        "## 6. Tuned Logistic Regression with GridSearchCV (Test 5)\n",
        "\n",
        "**Goal:** Hyperparameter search over regularisation strength `C` and penalty type."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 74,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "UzMK52mBlCKv",
        "outputId": "b6c80e26-88a5-4dff-b27d-f776e809fde3"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Best params : {'C': 0.001, 'penalty': 'l1', 'solver': 'liblinear'}\n",
            "Best CV ROC-AUC: 0.5000\n"
          ]
        }
      ],
      "source": [
        "# ── GridSearchCV – Logistic Regression ────────────────────────────────────────\n",
        "lr_param_grid = {\n",
        "    'C':       [0.001, 0.01, 0.1, 1, 10],\n",
        "    'penalty': ['l1', 'l2'],\n",
        "    'solver':  ['liblinear']\n",
        "}\n",
        "\n",
        "cv_inner = StratifiedKFold(n_splits=5, shuffle=True, random_state=SEED)\n",
        "\n",
        "lr_gs = GridSearchCV(\n",
        "    LogisticRegression(max_iter=1000, class_weight='balanced', random_state=SEED),\n",
        "    param_grid=lr_param_grid,\n",
        "    scoring='roc_auc',\n",
        "    cv=cv_inner,\n",
        "    n_jobs=-1,\n",
        "    verbose=0\n",
        ")\n",
        "lr_gs.fit(X_train_proc, y_train)\n",
        "\n",
        "print(f\"Best params : {lr_gs.best_params_}\")\n",
        "print(f\"Best CV ROC-AUC: {lr_gs.best_score_:.4f}\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 75,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YtgXbYFClCKw",
        "outputId": "d1ffd9e4-ec5e-47ab-caa3-9850ecff1f04"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "=== Tuned Logistic Regression — Test Set Performance ===\n",
            "              precision    recall  f1-score   support\n",
            "\n",
            "  Fully Paid       0.99      1.00      0.99        90\n",
            "     Default       0.00      0.00      0.00         1\n",
            "\n",
            "    accuracy                           0.99        91\n",
            "   macro avg       0.49      0.50      0.50        91\n",
            "weighted avg       0.98      0.99      0.98        91\n",
            "\n",
            "ROC-AUC: 0.5000\n"
          ]
        }
      ],
      "source": [
        "# ── Best estimator evaluation ─────────────────────────────────────────────────\n",
        "lr_best = lr_gs.best_estimator_\n",
        "y_pred_lr_tuned  = lr_best.predict(X_test_proc)\n",
        "y_proba_lr_tuned = lr_best.predict_proba(X_test_proc)[:, 1]\n",
        "\n",
        "print(\"=== Tuned Logistic Regression — Test Set Performance ===\")\n",
        "print(classification_report(y_test, y_pred_lr_tuned, target_names=['Fully Paid', 'Default']))\n",
        "print(f\"ROC-AUC: {roc_auc_score(y_test, y_proba_lr_tuned):.4f}\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 76,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 435
        },
        "id": "cDkDd2bflCKx",
        "outputId": "a93e64f2-c433-44dc-b3b1-6e86524e4180"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 770x440 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "# ── Hyperparameter impact visualisation ───────────────────────────────────────\n",
        "cv_results = pd.DataFrame(lr_gs.cv_results_)\n",
        "pivot = cv_results.pivot_table(\n",
        "    values='mean_test_score',\n",
        "    index='param_C',\n",
        "    columns='param_penalty'\n",
        ")\n",
        "\n",
        "fig, ax = plt.subplots(figsize=(7, 4))\n",
        "for col in pivot.columns:\n",
        "    ax.plot(pivot.index, pivot[col], marker='o', label=f'penalty={col}')\n",
        "ax.set_xscale('log')\n",
        "ax.set_xlabel('C (Regularisation Strength)')\n",
        "ax.set_ylabel('Mean CV ROC-AUC')\n",
        "ax.set_title('GridSearchCV: Hyperparameter Impact on LR Performance')\n",
        "ax.legend()\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "uAbmew4OlCKx"
      },
      "source": [
        "---\n",
        "## 7. Baseline Gradient Boosting (Ensemble) Model (Test 6)\n",
        "\n",
        "**Goal:** Train a default GradientBoostingClassifier as the non-linear ensemble baseline."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 77,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Ke8VqbgolCKx",
        "outputId": "8945983e-98e7-4b7f-f351-e624b25b118e"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "=== Baseline Gradient Boosting — Test Set Performance ===\n",
            "              precision    recall  f1-score   support\n",
            "\n",
            "  Fully Paid       0.99      0.98      0.98        90\n",
            "     Default       0.00      0.00      0.00         1\n",
            "\n",
            "    accuracy                           0.97        91\n",
            "   macro avg       0.49      0.49      0.49        91\n",
            "weighted avg       0.98      0.97      0.97        91\n",
            "\n",
            "ROC-AUC: 0.7111\n"
          ]
        }
      ],
      "source": [
        "# ── Baseline Gradient Boosting ────────────────────────────────────────────────\n",
        "gb_base = GradientBoostingClassifier(\n",
        "    n_estimators=100,\n",
        "    learning_rate=0.1,\n",
        "    max_depth=3,\n",
        "    random_state=SEED\n",
        ")\n",
        "gb_base.fit(X_train_proc, y_train)\n",
        "\n",
        "y_pred_gb_base   = gb_base.predict(X_test_proc)\n",
        "y_proba_gb_base  = gb_base.predict_proba(X_test_proc)[:, 1]\n",
        "\n",
        "print(\"=== Baseline Gradient Boosting — Test Set Performance ===\")\n",
        "print(classification_report(y_test, y_pred_gb_base, target_names=['Fully Paid', 'Default']))\n",
        "print(f\"ROC-AUC: {roc_auc_score(y_test, y_proba_gb_base):.4f}\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 78,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 435
        },
        "id": "-23RjFEXlCKy",
        "outputId": "a2088c86-cffb-4c1e-8d63-dd9c47905a3b"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 550x440 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "# ── Confusion matrix ──────────────────────────────────────────────────────────\n",
        "fig, ax = plt.subplots(figsize=(5, 4))\n",
        "plot_confusion_matrix(y_test, y_pred_gb_base, 'Baseline GB – Confusion Matrix', ax)\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "etuarNBylCKy"
      },
      "source": [
        "---\n",
        "## 8. Tuned Gradient Boosting with RandomizedSearchCV (Test 7)\n",
        "\n",
        "**Goal:** Efficient hyperparameter optimisation over a broader search space."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 79,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "S9m3qNhslCKz",
        "outputId": "ea6dca2d-bcf8-40d9-93bf-9fb9cf534ac0"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Fitting 3 folds for each of 20 candidates, totalling 60 fits\n",
            "\n",
            "Best params : {'l2_regularization': np.float64(0.44975413336976566), 'learning_rate': np.float64(0.08507854484034473), 'max_depth': 5, 'max_iter': 113, 'max_leaf_nodes': 45, 'min_samples_leaf': 24}\n",
            "Best CV ROC-AUC: 0.4930\n"
          ]
        }
      ],
      "source": [
        "from sklearn.ensemble import HistGradientBoostingClassifier\n",
        "from scipy.stats import randint, uniform\n",
        "\n",
        "gb_param_dist = {\n",
        "    'max_iter':        randint(100, 300),\n",
        "    'learning_rate':   uniform(0.01, 0.19),\n",
        "    'max_depth':       randint(2, 6),\n",
        "    'min_samples_leaf': randint(10, 50),\n",
        "    'l2_regularization': uniform(0, 1),\n",
        "    'max_leaf_nodes':  randint(15, 63)\n",
        "}\n",
        "\n",
        "gb_rs = RandomizedSearchCV(\n",
        "    HistGradientBoostingClassifier(random_state=SEED),\n",
        "    param_distributions=gb_param_dist,\n",
        "    n_iter=20,          # reduced from 30\n",
        "    scoring='roc_auc',\n",
        "    cv=StratifiedKFold(n_splits=3, shuffle=True, random_state=SEED),  # 3 folds not 5\n",
        "    n_jobs=-1,\n",
        "    random_state=SEED,\n",
        "    verbose=1\n",
        ")\n",
        "gb_rs.fit(X_train_proc, y_train)\n",
        "\n",
        "print(f\"\\nBest params : {gb_rs.best_params_}\")\n",
        "print(f\"Best CV ROC-AUC: {gb_rs.best_score_:.4f}\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 80,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Rc19fLg_lCK0",
        "outputId": "cb21cde5-8100-45b3-8850-9774a138c9c6"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "=== Tuned Gradient Boosting — Test Set Performance ===\n",
            "              precision    recall  f1-score   support\n",
            "\n",
            "  Fully Paid       0.99      1.00      0.99        90\n",
            "     Default       0.00      0.00      0.00         1\n",
            "\n",
            "    accuracy                           0.99        91\n",
            "   macro avg       0.49      0.50      0.50        91\n",
            "weighted avg       0.98      0.99      0.98        91\n",
            "\n",
            "ROC-AUC: 0.5222\n"
          ]
        }
      ],
      "source": [
        "# ── Best estimator evaluation ─────────────────────────────────────────────────\n",
        "gb_best = gb_rs.best_estimator_\n",
        "y_pred_gb_tuned  = gb_best.predict(X_test_proc)\n",
        "y_proba_gb_tuned = gb_best.predict_proba(X_test_proc)[:, 1]\n",
        "\n",
        "print(\"=== Tuned Gradient Boosting — Test Set Performance ===\")\n",
        "print(classification_report(y_test, y_pred_gb_tuned, target_names=['Fully Paid', 'Default']))\n",
        "print(f\"ROC-AUC: {roc_auc_score(y_test, y_proba_gb_tuned):.4f}\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 81,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 434
        },
        "id": "7S_1cswAlCK2",
        "outputId": "eb402cef-7994-49a0-abb0-524ff509b627"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1320x440 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "# ── Hyperparameter impact: learning_rate vs ROC-AUC ──────────────────────────\n",
        "rs_results = pd.DataFrame(gb_rs.cv_results_)\n",
        "fig, axes = plt.subplots(1, 2, figsize=(12, 4))\n",
        "\n",
        "axes[0].scatter(rs_results['param_learning_rate'], rs_results['mean_test_score'],\n",
        "                alpha=0.7, c='#4C72B0')\n",
        "axes[0].set_xlabel('Learning Rate')\n",
        "axes[0].set_ylabel('Mean CV ROC-AUC')\n",
        "axes[0].set_title('Learning Rate vs ROC-AUC')\n",
        "\n",
        "axes[1].scatter(rs_results['param_max_iter'], rs_results['mean_test_score'],\n",
        "                alpha=0.7, c='#DD8452')\n",
        "axes[1].set_xlabel('max_iter (Number of Trees)')\n",
        "axes[1].set_ylabel('Mean CV ROC-AUC')\n",
        "axes[1].set_title('max_iter vs ROC-AUC')\n",
        "\n",
        "plt.suptitle('RandomizedSearchCV: Hyperparameter Impact (GB)', fontweight='bold')\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "8n61rJlclCK2"
      },
      "source": [
        "---\n",
        "## 9. Cross-Validation Comparison (Test 8)\n",
        "\n",
        "**Goal:** Compare all four models using stratified 5-fold CV across Accuracy, F1, and ROC-AUC\n",
        "to demonstrate generalisation, not just one random split."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 82,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "zIRxPYdblCK3",
        "outputId": "12c66bfa-9ef1-40eb-fef2-5baf9bb3b994"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "LR Baseline     | accuracy   | 0.6143 ± 0.0506\n",
            "LR Baseline     | f1         | 0.0000 ± 0.0000\n",
            "LR Baseline     | roc_auc    | 0.2059 ± 0.0549\n",
            "LR Tuned        | accuracy   | 0.9835 ± 0.0000\n",
            "LR Tuned        | f1         | 0.0000 ± 0.0000\n",
            "LR Tuned        | roc_auc    | 0.5000 ± 0.0000\n",
            "GB Baseline     | accuracy   | 0.9725 ± 0.0039\n",
            "GB Baseline     | f1         | 0.0000 ± 0.0000\n",
            "GB Baseline     | roc_auc    | 0.3887 ± 0.1016\n",
            "GB Tuned        | accuracy   | 0.9835 ± 0.0000\n",
            "GB Tuned        | f1         | 0.0000 ± 0.0000\n",
            "GB Tuned        | roc_auc    | 0.4930 ± 0.0248\n"
          ]
        }
      ],
      "source": [
        "cv_outer = StratifiedKFold(n_splits=3, shuffle=True, random_state=SEED)  # 3 not 5\n",
        "\n",
        "models_cv = {\n",
        "    'LR Baseline':   lr_base,\n",
        "    'LR Tuned':      lr_best,\n",
        "    'GB Baseline':   gb_base,\n",
        "    'GB Tuned':      gb_best,\n",
        "}\n",
        "\n",
        "cv_summary = []\n",
        "for name, model in models_cv.items():\n",
        "    for metric in ['accuracy', 'f1', 'roc_auc']:\n",
        "        scores = cross_val_score(model, X_train_proc, y_train,\n",
        "                                 cv=cv_outer, scoring=metric, n_jobs=-1)\n",
        "        cv_summary.append({\n",
        "            'Model': name,\n",
        "            'Metric': metric.upper().replace('_', '-'),\n",
        "            'Mean': scores.mean(),\n",
        "            'Std':  scores.std()\n",
        "        })\n",
        "        print(f\"{name:15s} | {metric:10s} | {scores.mean():.4f} ± {scores.std():.4f}\")\n",
        "\n",
        "cv_df = pd.DataFrame(cv_summary)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 83,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 545
        },
        "id": "ufj9PviwlCK4",
        "outputId": "84dc884f-6a48-4cbf-cc1b-8884e58dc1ed"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1210x550 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "# ── Grouped bar chart ──────────────────────────────────────────────────────────\n",
        "metrics_list = cv_df['Metric'].unique()\n",
        "model_list   = list(models_cv.keys())\n",
        "x = np.arange(len(metrics_list))\n",
        "width = 0.18\n",
        "colors = ['#4C72B0', '#55A868', '#DD8452', '#C44E52']\n",
        "\n",
        "fig, ax = plt.subplots(figsize=(11, 5))\n",
        "for i, (name, color) in enumerate(zip(model_list, colors)):\n",
        "    subset = cv_df[cv_df['Model'] == name].set_index('Metric')\n",
        "    vals = [subset.loc[m, 'Mean'] if m in subset.index else 0 for m in metrics_list]\n",
        "    errs = [subset.loc[m, 'Std'] if m in subset.index else 0 for m in metrics_list]\n",
        "    ax.bar(x + i*width, vals, width, label=name, color=color,\n",
        "           yerr=errs, capsize=4, alpha=0.85)\n",
        "\n",
        "ax.set_xticks(x + width*1.5)\n",
        "ax.set_xticklabels(metrics_list)\n",
        "ax.set_ylim(0, 1.05)\n",
        "ax.set_ylabel('Score')\n",
        "ax.set_title('5-Fold Cross-Validation Comparison (mean ± std)', fontweight='bold')\n",
        "ax.legend(loc='lower right')\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2euxVPLjlCK4"
      },
      "source": [
        "---\n",
        "## 10. Final Test-Set Evaluation (Test 9)\n",
        "\n",
        "**Goal:** Full evaluation of all four models on the held-out test set:\n",
        "Accuracy, Precision, Recall, F1, ROC-AUC, Confusion Matrices, and ROC curves."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 84,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2NezL51UlCK4",
        "outputId": "5408b132-7a86-4681-dcde-83860201f8bd"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "             Accuracy  Precision  Recall   F1  ROC-AUC\n",
            "Model                                                 \n",
            "LR Baseline    0.5385        0.0     0.0  0.0   0.4667\n",
            "LR Tuned       0.9890        0.0     0.0  0.0   0.5000\n",
            "GB Baseline    0.9670        0.0     0.0  0.0   0.7111\n",
            "GB Tuned       0.9890        0.0     0.0  0.0   0.5222\n"
          ]
        }
      ],
      "source": [
        "# ── Compute all metrics on test set ───────────────────────────────────────────\n",
        "all_models = {\n",
        "    'LR Baseline':  (y_pred_lr_base,  y_proba_lr_base),\n",
        "    'LR Tuned':     (y_pred_lr_tuned, y_proba_lr_tuned),\n",
        "    'GB Baseline':  (y_pred_gb_base,  y_proba_gb_base),\n",
        "    'GB Tuned':     (y_pred_gb_tuned, y_proba_gb_tuned),\n",
        "}\n",
        "\n",
        "results = []\n",
        "for name, (y_pred, y_proba) in all_models.items():\n",
        "    results.append({\n",
        "        'Model':     name,\n",
        "        'Accuracy':  accuracy_score(y_test, y_pred),\n",
        "        'Precision': precision_score(y_test, y_pred, zero_division=0),\n",
        "        'Recall':    recall_score(y_test, y_pred, zero_division=0),\n",
        "        'F1':        f1_score(y_test, y_pred, zero_division=0),\n",
        "        'ROC-AUC':   roc_auc_score(y_test, y_proba)\n",
        "    })\n",
        "\n",
        "results_df = pd.DataFrame(results).set_index('Model').round(4)\n",
        "print(results_df.to_string())"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 85,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 224
        },
        "id": "1M9yaXAZlCK5",
        "outputId": "a2a327ab-9bbb-490f-f099-9484f0aa2f35"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7b0c46c454f0>"
            ],
            "text/html": [
              "<style type=\"text/css\">\n",
              "#T_e4036_row0_col1, #T_e4036_row0_col2, #T_e4036_row0_col3, #T_e4036_row1_col0, #T_e4036_row1_col1, #T_e4036_row1_col2, #T_e4036_row1_col3, #T_e4036_row2_col1, #T_e4036_row2_col2, #T_e4036_row2_col3, #T_e4036_row2_col4, #T_e4036_row3_col0, #T_e4036_row3_col1, #T_e4036_row3_col2, #T_e4036_row3_col3 {\n",
              "  background-color: #d4edda;\n",
              "}\n",
              "</style>\n",
              "<table id=\"T_e4036\" class=\"dataframe\">\n",
              "  <caption>Test-Set Performance Metrics – All Models</caption>\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th class=\"blank level0\" >&nbsp;</th>\n",
              "      <th id=\"T_e4036_level0_col0\" class=\"col_heading level0 col0\" >Accuracy</th>\n",
              "      <th id=\"T_e4036_level0_col1\" class=\"col_heading level0 col1\" >Precision</th>\n",
              "      <th id=\"T_e4036_level0_col2\" class=\"col_heading level0 col2\" >Recall</th>\n",
              "      <th id=\"T_e4036_level0_col3\" class=\"col_heading level0 col3\" >F1</th>\n",
              "      <th id=\"T_e4036_level0_col4\" class=\"col_heading level0 col4\" >ROC-AUC</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th class=\"index_name level0\" >Model</th>\n",
              "      <th class=\"blank col0\" >&nbsp;</th>\n",
              "      <th class=\"blank col1\" >&nbsp;</th>\n",
              "      <th class=\"blank col2\" >&nbsp;</th>\n",
              "      <th class=\"blank col3\" >&nbsp;</th>\n",
              "      <th class=\"blank col4\" >&nbsp;</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th id=\"T_e4036_level0_row0\" class=\"row_heading level0 row0\" >LR Baseline</th>\n",
              "      <td id=\"T_e4036_row0_col0\" class=\"data row0 col0\" >0.5385</td>\n",
              "      <td id=\"T_e4036_row0_col1\" class=\"data row0 col1\" >0.0000</td>\n",
              "      <td id=\"T_e4036_row0_col2\" class=\"data row0 col2\" >0.0000</td>\n",
              "      <td id=\"T_e4036_row0_col3\" class=\"data row0 col3\" >0.0000</td>\n",
              "      <td id=\"T_e4036_row0_col4\" class=\"data row0 col4\" >0.4667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e4036_level0_row1\" class=\"row_heading level0 row1\" >LR Tuned</th>\n",
              "      <td id=\"T_e4036_row1_col0\" class=\"data row1 col0\" >0.9890</td>\n",
              "      <td id=\"T_e4036_row1_col1\" class=\"data row1 col1\" >0.0000</td>\n",
              "      <td id=\"T_e4036_row1_col2\" class=\"data row1 col2\" >0.0000</td>\n",
              "      <td id=\"T_e4036_row1_col3\" class=\"data row1 col3\" >0.0000</td>\n",
              "      <td id=\"T_e4036_row1_col4\" class=\"data row1 col4\" >0.5000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e4036_level0_row2\" class=\"row_heading level0 row2\" >GB Baseline</th>\n",
              "      <td id=\"T_e4036_row2_col0\" class=\"data row2 col0\" >0.9670</td>\n",
              "      <td id=\"T_e4036_row2_col1\" class=\"data row2 col1\" >0.0000</td>\n",
              "      <td id=\"T_e4036_row2_col2\" class=\"data row2 col2\" >0.0000</td>\n",
              "      <td id=\"T_e4036_row2_col3\" class=\"data row2 col3\" >0.0000</td>\n",
              "      <td id=\"T_e4036_row2_col4\" class=\"data row2 col4\" >0.7111</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e4036_level0_row3\" class=\"row_heading level0 row3\" >GB Tuned</th>\n",
              "      <td id=\"T_e4036_row3_col0\" class=\"data row3 col0\" >0.9890</td>\n",
              "      <td id=\"T_e4036_row3_col1\" class=\"data row3 col1\" >0.0000</td>\n",
              "      <td id=\"T_e4036_row3_col2\" class=\"data row3 col2\" >0.0000</td>\n",
              "      <td id=\"T_e4036_row3_col3\" class=\"data row3 col3\" >0.0000</td>\n",
              "      <td id=\"T_e4036_row3_col4\" class=\"data row3 col4\" >0.5222</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n"
            ]
          },
          "metadata": {}
        }
      ],
      "source": [
        "# ── Styled metrics table ───────────────────────────────────────────────────────\n",
        "display(results_df.style\n",
        "        .highlight_max(color='#d4edda', axis=0)\n",
        "        .format('{:.4f}')\n",
        "        .set_caption('Test-Set Performance Metrics – All Models'))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 86,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 879
        },
        "id": "tclxiQ1klCK5",
        "outputId": "6d13217a-44f1-42ec-f521-8fa5294a9fd3"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1210x880 with 8 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "# ── 4-panel confusion matrices ─────────────────────────────────────────────────\n",
        "fig, axes = plt.subplots(2, 2, figsize=(11, 8))\n",
        "for ax, (name, (y_pred, _)) in zip(axes.flat, all_models.items()):\n",
        "    plot_confusion_matrix(y_test, y_pred, name, ax)\n",
        "plt.suptitle('Confusion Matrices – All Models (Test Set)', fontsize=13, fontweight='bold')\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 87,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 655
        },
        "id": "YFsDYPTZlCK5",
        "outputId": "5d101c15-4a23-457b-affa-03e743ca763b"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 770x660 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "# ── ROC curves ────────────────────────────────────────────────────────────────\n",
        "from sklearn.metrics import roc_curve, auc as sk_auc\n",
        "\n",
        "fig, ax = plt.subplots(figsize=(7, 6))\n",
        "colors_roc = ['#4C72B0', '#55A868', '#DD8452', '#C44E52']\n",
        "for (name, (_, y_proba)), color in zip(all_models.items(), colors_roc):\n",
        "    fpr, tpr, _ = roc_curve(y_test, y_proba)\n",
        "    auc_val = sk_auc(fpr, tpr)\n",
        "    ax.plot(fpr, tpr, lw=2, color=color, label=f'{name} (AUC={auc_val:.3f})')\n",
        "\n",
        "ax.plot([0, 1], [0, 1], 'k--', lw=1.5, label='Random Classifier')\n",
        "ax.set_xlabel('False Positive Rate')\n",
        "ax.set_ylabel('True Positive Rate')\n",
        "ax.set_title('ROC Curves – All Models', fontweight='bold')\n",
        "ax.legend(loc='lower right')\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 88,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 655
        },
        "id": "ZqD4oPxolCK6",
        "outputId": "bb978741-beee-4643-f835-c222f983fa93"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 770x660 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "# ── Precision-Recall curves (better for imbalanced data) ──────────────────────\n",
        "from sklearn.metrics import precision_recall_curve, average_precision_score\n",
        "\n",
        "fig, ax = plt.subplots(figsize=(7, 6))\n",
        "for (name, (_, y_proba)), color in zip(all_models.items(), colors_roc):\n",
        "    precision_vals, recall_vals, _ = precision_recall_curve(y_test, y_proba)\n",
        "    ap = average_precision_score(y_test, y_proba)\n",
        "    ax.plot(recall_vals, precision_vals, lw=2, color=color,\n",
        "            label=f'{name} (AP={ap:.3f})')\n",
        "\n",
        "ax.set_xlabel('Recall')\n",
        "ax.set_ylabel('Precision')\n",
        "ax.set_title('Precision-Recall Curves – All Models', fontweight='bold')\n",
        "ax.legend(loc='upper right')\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "1GTbxnOOlCK6"
      },
      "source": [
        "---\n",
        "## 11. Interpretability & Fairness Analysis (Test 10)\n",
        "\n",
        "**Goal:**\n",
        "- Feature importances from Gradient Boosting\n",
        "- Logistic Regression coefficients\n",
        "- SHAP values for global and local explanations\n",
        "- Partial Dependence Plots (PDP)\n",
        "- Fairness: default rate comparison across demographic-like subgroups\n",
        "  (income group, loan purpose, home ownership, employment length)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 89,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 655
        },
        "id": "y7kYE9KLlCK7",
        "outputId": "f95ed7c4-4d62-4397-f8ba-2f9064d4a5a9"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 990x660 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "# ── 11a. Gradient Boosting feature importances ─────────────────────────────────\n",
        "from sklearn.inspection import permutation_importance\n",
        "\n",
        "perm = permutation_importance(\n",
        "    gb_best, X_test_proc, y_test,\n",
        "    n_repeats=10,\n",
        "    scoring='roc_auc',\n",
        "    random_state=SEED,\n",
        "    n_jobs=-1\n",
        ")\n",
        "\n",
        "fi_df = pd.DataFrame({\n",
        "    'Feature':    feature_names_out,\n",
        "    'Importance': perm.importances_mean,\n",
        "    'Std':        perm.importances_std\n",
        "}).sort_values('Importance', ascending=False).head(20)\n",
        "\n",
        "fig, ax = plt.subplots(figsize=(9, 6))\n",
        "ax.barh(fi_df['Feature'][::-1], fi_df['Importance'][::-1],\n",
        "        xerr=fi_df['Std'][::-1], color='#4C72B0', capsize=4)\n",
        "ax.set_xlabel('Permutation Importance (ROC-AUC drop)')\n",
        "ax.set_title('Top-20 Feature Importances – Tuned Gradient Boosting', fontweight='bold')\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 90,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 655
        },
        "id": "j__0Vc6slCK7",
        "outputId": "ff768967-685e-4764-d91e-38441a555cc4"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 990x660 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "# ── 11b. Logistic Regression coefficients ──────────────────────────────────────\n",
        "coef = lr_best.coef_[0]\n",
        "coef_df = pd.DataFrame({'Feature': feature_names_out, 'Coefficient': coef})\n",
        "coef_df = coef_df.reindex(coef_df['Coefficient'].abs().sort_values(ascending=False).index).head(20)\n",
        "\n",
        "fig, ax = plt.subplots(figsize=(9, 6))\n",
        "colors_coef = ['#DD8452' if c > 0 else '#4C72B0' for c in coef_df['Coefficient']]\n",
        "ax.barh(coef_df['Feature'][::-1], coef_df['Coefficient'][::-1], color=colors_coef[::-1])\n",
        "ax.axvline(0, color='black', linewidth=0.8)\n",
        "ax.set_xlabel('Log-Odds Coefficient')\n",
        "ax.set_title('Top-20 LR Coefficients (orange=increases default risk)', fontweight='bold')\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 91,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jzbJd6ValCK8",
        "outputId": "09ca288c-1d42-4eed-c406-7c6aea18bbee"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "SHAP values computed.\n"
          ]
        }
      ],
      "source": [
        "# ── 11c. SHAP values – Gradient Boosting ──────────────────────────────────────\n",
        "# Use a sample for speed (SHAP tree explainer is fast)\n",
        "X_shap_df = pd.DataFrame(X_test_proc, columns=feature_names_out)\n",
        "X_sample  = X_shap_df.sample(min(2000, len(X_shap_df)), random_state=SEED)\n",
        "\n",
        "explainer   = shap.TreeExplainer(gb_best)\n",
        "shap_values = explainer.shap_values(X_sample)\n",
        "\n",
        "print(\"SHAP values computed.\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 92,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 380
        },
        "id": "4Iv3qkTvlCK8",
        "outputId": "eea3c959-4efb-4891-f846-9c0f9de9d055"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 880x385 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "# ── SHAP beeswarm (summary) plot ───────────────────────────────────────────────\n",
        "plt.figure(figsize=(10, 7))\n",
        "shap.summary_plot(shap_values, X_sample, plot_type='dot', max_display=15, show=False)\n",
        "plt.title('SHAP Summary Plot – Tuned Gradient Boosting', fontweight='bold')\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 93,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 380
        },
        "id": "XoceQTkDlCK8",
        "outputId": "be420004-9320-4c3d-c809-90c59f7ad916"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 880x385 with 1 Axes>"
            ],
            "image/png": 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X/oPuvCwsLJSGps5//0hKSkqh6y6qyZMno0mTJti4cSOCg4OVuooBwNu3b7F7926Eh4fDy8tLknvD8srb5UxXVxf9+vUD8O7MqpGRkdjtZ//+/e8ttNQdcAPvDpb++OOPUg+E8eLFi0L3l6ZNmxbp3qe8pM5n3qt4tWrVEg8uAcDQ0BD9+vUTD7ATExPx9OlTfPjhhyrr6d+/v1K+3NzcxEILeHeVSFFoBQYG4vvvv1fqCqZOYft7WdLk57ismZqaYvz48Srt165dU/q7oCs2wLsTN+Hh4ZIWwbq6uhgwYID4d/5CJe+9WOq+2woqtPJevdHX10f//v3FZ7C9ffsWDx48QJs2bST7HAwdOlRtkVVU9+/fx9dff42wsLBC5ytsH7KzsxOLLKDgfF2/fl3sbg0AEyZMULmKX61aNfF+qxs3bijNv379eqxfv77AOEJCQlhoVVEstIioUBMnTsR3332Ht2/f4u3btwCAUaNGvfcG36SkpCJvIyEhQfz37NmzxS4thcl/v0heVlZWSn/nLxLyF0Sl4eLiAhcXF6SmpuLmzZu4desWAgIClA5Wrl+/juvXr6N9+/Zq11GU52jll5qaqtRts3PnzqhVqxaAdwcErq6u8PHxAQAEBATg1atXRXoelpaWFgwNDWFjY4POnTtjwoQJkjxHKzIyssBiDnh3EPi+QuuDDz5Q+vvJkydKf9epU0fsapa3a1JR5Z1f3T0V+Q+8Clp//mXz/60o9GNjYzFz5kxkZGS8N7bC9veSKsqznDT5OS4qxT2jxV1n/fr11V6JKs5rBpRftxRq1aqlFFf+7y8LCwvx3/mfD1fYd9v79kvF/izV50Bd8VVUmZmZmDZtGl69evXeeaX4Lcj/Gt5XIGp6H6HKg4UWERVq8ODBWL58uTgYgp6entitqDCmpqbij0uTJk0KHWZcUbQ9ffpU6eCsf//+WLhwIerVqwdtbW3MmzcPJ0+efO+28x88SX3lQx1jY2N06dIFXbp0waxZs7Bq1SrxbDHw7r6Hggqtkjhy5IjS87v8/PwK7A6Zm5uLAwcOYNasWQWurzI8GNbCwkK8wgq8O+N9584d8WpCzZo1xS5IebsmFVXekdfUDf6Rf9AEdSO1qVs2/9+KbqTnz59XKrIWLlyIjz/+WBwl8aOPPkJiYmIxXoH0NPk5Lkj+bmqKE0DAuwPn910dVCjoYd7539e5c+cWemJJ6mfkva8bYkm7KcbHx8PS0lLp77wUg2FI9TkozSAnwcHBSkXWhAkTMG3aNJibm0NLSwsff/wxbt++/d71FPW3IP9riI6OLnS9+ed3c3Mr9B5CPsev6mKhRUSF0tfXx5gxY8SuTwMHDizSwAj29vbiqIVxcXHo16+f0o888O6g6MqVK+LNz69fv1aa3rdvX/GM5KtXrxAYGFjq1yOVV69eYe3atRg9ejRkMpnK9PyDYBR3iPH32b9/f7Hm9/b2xsyZM8ul6FTHyclJkmLu008/xbfffiv+/dlnn2H9+vVo2LBhqddtb2+PW7duAXjXJercuXNit6mMjAycOHFCnLdWrVoq3ZAUjh8/jmnTpolnz/MOXQ0Abdq0AaC6v+ctsi5evKjxIgso/8+xrq7yYcmbN29UDtjz3+9448YNuLi4AAD27t1b6rzZ29tj48aN4t8mJiZquxhGRUUhIiIC9evXL9X2ysvBgwfFe7SysrKUuvLq6+uLJ2qk+hwUJu/7rO5Zd/n3oSFDhoi/O+Hh4bh//36xt1mYdu3aQU9PT+wOuH37dgwfPhy1a9cW58nKykJSUpI41Luurq444mtGRgYmTZqk8v2ampoKPz8/ODo6ShovVR4stIjovSZMmCD+CBf1zNykSZNw9uxZyOVyJCcnY+jQoeIDfTMzM/H06VNcu3YNCQkJ2LZtG+rXr4+GDRtCW1tb7M7xyy+/4N69e8jKysLhw4eL3V2jLGVnZ2PXrl3YtWsXGjZsiPbt28PKygo6Ojp4/Pix0hl7Y2NjSa9m3b9/X+mKQdOmTdWeTY2IiBBv6o+KikJgYCA++ugjyeLQBDc3N/j5+YndJp89e4aBAweiW7duaNasGXR0dBATE1Oi4ejHjh2rNELl/Pnz4ebmBjMzM5w5c0bpuWkFDQAAvBuUYOTIkejevTuio6Nx5MgRcZri2UWA6pWQqVOnonv37oiJicGhQ4eKHX9ZKO/Pcf7uoZ9//jns7Oygo6ODHj16oFGjRmjcuDFq1Kghjsq5du1ahIWFITMzU5KTMS4uLpDJZOKAHUuWLMHFixfRqlUr6Orq4uXLl7h16xbCwsLg5uamNFBGRebp6YknT56gQYMGuHDhgtLQ9UOHDhWv2kn1OShM3bp18ezZMwDvrsYvW7ZM7DI5YcIElc/GwoULMXDgQCQlJcHb21vp/igpGBsbY+zYsdiyZQuAd916+/Xrh759+6Ju3bp4+fIl/Pz8MH/+fAwbNgympqYYMWKEOCDGqVOn4Obmhi5dusDY2BiJiYm4d+8erl+/DgsLCwwcOFDSeKnyYKFFRO9lbGysNLhEUbRr1w4//fQTFi9ejOzsbCQnJ2PPnj2FLlOrVi2MHTtWHCEuNjYWa9euBfDuAKxLly7iw5IrEsUzVtTR1dXFzz//XGA3pZLI/9ylRYsWoUOHDirzPXz4UOkHfv/+/ZW+0NLW1sbvv/+OevXqYevWreKw6WfOnFF5no2CmZlZkdZdv359LF++HJ9//jkyMjLEwUzyGzZsWKGj4Tk6OuLatWsqN/Hr6uri119/FQcrUAwrriiab9++LXaH6tKlCx49eqTRwSKA8v8cOzs7w9DQUOxSmXcUTysrKzRq1Aj6+vqYOHGi+DBeuVwuDr1tY2MDXV1dlfv3ikNHRwdr1qzBlClTEBERAUEQ4OfnBz8/vxKvsyLo3r07jh49qtLeuHFjLFy4UPxbqs9BYfr27SsOlPLmzRvxCqKhoSEmTJiAli1bonv37uL7+vTpU7Ertq2tLXR1dYt0D2BxLFy4ELGxseKVvvft69988w1evHiBCxcuAADCwsLeO3AHVT0stIiozIwYMQL29vbYtWsXAgMD8fz5c7x9+xbGxsawsbGBnZ0devTooVQkfPvtt6hbty727duHmJgYmJiYoEuXLvj888+xfPlyDb4aZZaWltizZw+CgoIQHByM58+fIyEhASkpKTAwMIClpSUcHBwwbtw4SZ//8/btW6UrJA0bNlRbZAHvrnS1a9cO169fBwCcOXMGycnJBd5TUVno6+vjm2++wejRo7Fv3z4EBwcjIiICaWlp0NXVRc2aNdGoUSO0bdsWLi4uxRqavkePHjhy5Ai2b9+OS5cu4fnz58jOzkbNmjXRpk0bjBgxQumBw+q4ublhxowZWLt2Le7cuQMAaNu2LebMmQN7e3txPl1dXWzevBl//PEHfH19kZycjA8++AADBgzA7Nmz0bdv3xLlR2rl+TmuXbs2NmzYgJUrV+LOnTsqD8xV8PDwgKGhIXbv3o0XL16gZs2a6NOnjziwTGkKLeBdseHj44N9+/bhzJkzePDgAVJTU6Gvr48PPvgALVq0wEcfffTe0TwrEk9PT2zatAne3t6Ijo6GmZkZevfujblz56p8J0jxOSjM6NGjkZ6eLsai7grVX3/9BU9PTxw9ehTx8fGoXbs2evbsiQULFhR6v2lJ6enpYfny5Rg6dCi8vb1x69YtxMfHQ0dHB+bm5rCzs1Pq0WFgYIB169bh9OnT8PHxwZ07d5CYmAgtLS2Ym5ujSZMmcHR0rDCfY9IMLSH/cD1ERCT6+uuvcfDgQbi5ueG///2vpsOpEK5evYoJEyYAqByDaBBVRZ6enuJVP4CfVSJNKH7HWiIiIiIiIioUCy0iIiIiIiKJsdAiIiIiIiKSGAfDICIiIvqXmTNnDubMmaPpMIiqNA6GQUREREREJDF2HSQiIiIiIpIYCy0iIiIiIiKJsdAiIiIiIiKSGAstKjE/Pz8kJydrOoxK7f79+7h//76mw6j0mEdpMI/SYB6lwTxKg3mUBvMojaqWRxZaREREREREEmOhRUREREREJDEWWkRERERERBJjoUVERERERCQxFlpEREREREQSY6FFREREREQkMRZaREREREREEmOhRUREREREJDEWWkRERERERBJjoUVERERERCQxFlpEREREREQSY6FFREREREQkMRZaREREREREEmOhRUREREREJDEWWkRERERERBJjoUVERERERCQxFlpEREREREQSY6FFREREREQkMRZaREREREREEmOhRUREREREJDEWWkRERERERBJjoUVERERERCQxFlpEREREREQSY6FFREREREQkMRZaREREREREEmOhRUREREREJDEtQRAETQdBlVNycjKMjIygq6ur6VAqrYyMDACAoaGhhiOp3JhHaTCP0mAepcE8SoN5lAbzKI2qlkcWWlRiKW8F3IrTdBRERERE9G/Xpg5gYqCl6TCKhZciqMRuxQFdd+dqOgwiIiIi+pe7OEoHXaw1HUXx8B4tIiIiIiIiibHQIiIiIiIikhgLLSIiIiIiIomx0CIiIiIiIpIYCy0iIiIiIiKJsdAiIiIiIiKSmKSFVkxMDBwcHPDjjz9KudpyM23aNDg4OCi1BQcHw8HBAevWrdNQVEREREREVNlU6itaP/74IxwcHBATE6PpUCo8dUUkERERERGVDUkfWGxhYYH9+/ejRo0aUq6WiIiIiIioUpG00NLV1UXDhg2lXCUREREREVGlI2mhFRMTg8GDB2PgwIHifVrTpk1DaGgoAgMDsW3bNhw5cgQvX75ErVq10KdPH8ycORN6enpK6wkJCcH27dvx4MEDvH79GiYmJqhXrx66dOmCKVOmAIBSN7jBgweL/27fvj3Wr18P4N39VSdOnMDNmzcRGxuL3NxcNGjQAH379sWYMWOgq1vylz9o0CAAgJeXF9asWYPz588jJSUFTZo0gYeHBzp06IA3b97g77//hq+vL16/fo2GDRti7ty56Nixo8r6cnJysH//fhw/fhwRERGQy+Vo3Lgx3N3dMWDAAKV5161bhw0bNmDt2rVISkrCtm3b8PjxYxgYGMDJyQkLFiyAhYWF0nuikDdved8nIiIiIiKSjqSFVmH+85//4Pr16+jUqRNq1KiBS5cuYdu2bXj9+jUWLVokznfp0iXMnz8fNWrUgLOzMywsLJCcnIynT5/iwIEDYqE1depU+Pn54cGDBxg9erTYXdHS0lJc19atWxEZGYnWrVvD2dkZGRkZCA4OxsqVKxEWFoalS5eW6jVlZ2dj9uzZyMjIQI8ePZCeno5Tp05h3rx52LRpE5YuXYqMjAx069ZNnLZgwQLs378fVlZWSuuZN28egoKC0LhxY/Tv3x/a2toIDAzEokWL8PTpU3h4eKhsf//+/fD394ezszPs7e1x584dnDlzBg8fPsSuXbugr68PY2NjTJ06FUePHsWLFy8wdepUcXlbW9tSvX4iIiIiIlKv3Aqt6Oho7N27F6ampgCAWbNmYfTo0Th27Bhmz54Nc3NzAICPjw8EQcC6desgk8mU1pGUlCT+e/r06Xjx4oVYaOUtsBS+/vprWFpaQktLS2wTBAE//fQTjhw5gtGjR6NNmzYlfk3x8fFo3bo1li5dKl4d69ixI/7zn/9g5syZcHBwwK+//ipesVNM8/LywsKFC8X1bNy4EUFBQRg7dizmzZsHbe13Y5RkZWXhiy++wJYtW9CrVy80a9ZMaftXrlzBtm3b0KRJE7Htu+++w6lTp+Dn5wdXV1cYGxtj+vTpCAkJwYsXLzB9+vQSv14iIiIiIk3JyMhAZGSkRmPIfzxemHIbdXDOnDlikQUA1atXR79+/SCXyxEWFqYyv4GBgUqbmZlZsbZpZWWlVGQBgJaWFtzd3QEAV69eLdb61FmwYIFSF0RXV1fo6uoiNTUVCxYsUOoWqZj24MEDsU0ul2P//v2oU6cO5s6dKxZZAKCvry9eyTp16pTKtt3d3ZWKLABwc3MDANy9e7fUr42IiIiIiEqm3K5otWjRQqWtbt26AICUlBSxrV+/fjh//jwmTpwIV1dXODg4oG3btuK8xZGRkYFdu3bh/PnziIqKQkZGhtL02NjYYq8zL2NjY5UraTo6OqhVqxbevHlT4LS4uDix7dmzZ0hOToaNjQ02btyoso2cnBwAQEREhMq0ouaUiIiIiKiyMzQ0LNYVJU0rt0LL2NhYpU1HRwfAu6s6Cj169MCKFSuwY8cOHD58GN7e3gDeFRUeHh5wdHQs0vZycnIwY8YM3Lt3DzKZDH379oWZmRl0dHSQlpYGLy8vZGdnl+o1FTSMvY6OTqHTFMUTACQnJwMAIiMjsWHDhgK3lb9ILGj76nJKRERERETlq9wKreLo0qULunTpgjdv3uD27du4ePEiDhw4gAULFmDnzp1FGkL+woULuHfvHgYPHowffvhBadqtW7fg5eVVRtEXj6JY+uijj+Dp6anhaIiIiIiISAoVstBSqF69OhwdHeHo6AgTExOsW7cOV65cEQstxf1M6q7eREdHAwC6deumMu369etlFnNxNWzYEEZGRggPD8fbt2/V3psmBcWVrtzcXPHfRERERERUNsptMIyiCg0NVepap5CQkAAAqFatmtimGFzj5cuXKvPXq1cPgGpR9fDhQ2zZskWqcEtNV1cXI0eORGJiIpYtW4asrCyVeZ4/f46YmJhSbcfExAQA8OrVq1Kth4iIiIiI3q/CXdH6/fffERsbi7Zt28LS0hK6urq4d+8eQkJCYGVlBVdXV3FeBwcHbN++Hb/++it69OiBatWqoV69ehgwYAC6du0KKysrbN++HY8fP0aTJk0QExMjPnfq7NmzGnyVyqZNm4bw8HD4+PggMDAQDg4OqF27NhISEhAREYG7d+/il19+UTuEfVF16NABvr6++PLLL9GpUyfo6+tDJpPB2dlZwldCRERERERABSy0Jk6ciPPnz+P+/fsICgqCtrY26tati8mTJys9mBgAOnfujLlz58LHxwc7duxATk4O2rdvjwEDBsDQ0BBr167FypUrERoaipCQEDRo0ACfffYZOnXqVKEKLT09PaxYsQJHjhzBsWPH4Ofnh8zMTNSqVQvW1taYN28enJycSrWNoUOHIiYmBqdPn8bWrVuRm5uLgQMHstAiIiIiIioDWoIgCJoOgiqngGgBXXfnajoMIiIiIvqXuzhKB12std4/YwVS4e7RIiIiIiIiquxYaBEREREREUmMhRYREREREZHEWGgRERERERFJjIUWERERERGRxDjqIJVYylsBt+I0HQURERER/du1qQOYGFSuUQdZaFGJJScnw8jICLq6Fe5xbJVGRkYGAMDQ0FDDkVRuzKM0mEdpMI/SYB6lwTxKg3mURlXLI7sOUonduHED6enpmg6jUouMjERkZKSmw6j0mEdpMI/SYB6lwTxKg3mUBvMojaqWRxZaREREREREEmOhRUREREREJDEWWkRERERERBJjoUVERERERCQxFlpEREREREQSY6FFREREREQkMRZaREREREREEmOhRUREREREJDEWWkRERERERBJjoUVERERERCQxXU0HQJWXnZ0djIyMNB1GpWZjY6PpEP4VmEdpMI/SYB6lwTwSUWXHQotKTKuaCQJfAoCg6VAqserv/pfIHJYO8ygN5lEazKM0qlYe29QBTAy0NB0GEUmIhRaV2K04oOvuXE2HQUREVOldHKWDLtaajoKIpMR7tIiIiIiIiCTGQouIiIiIiEhiLLSIiIiIiIgkxkKLiIiIiIhIYiy0iIiIiIiIJMZCi4iIiIiISGKVvtAKDg6Gg4MD1q1bp+lQyl1MTAwcHBzw448/ajoUIiIiIiLKo9IXWkRERERERBUNCy0iIiIiIiKJsdAiIiIiIiKSmG55buzChQvYvXs3nj59ipSUFJiamsLGxga9e/fGxx9/DAAYNGgQAODIkSMqy69btw4bNmzA2rVr4eDgoDL91q1bWLt2Le7evQsAaNu2LWbNmoVmzZqVOOa0tDSsW7cOvr6+SEpKQr169eDm5oZu3bph6NChGDhwoNI9Uor4vby8sH79epw/fx6xsbGYNGkSpk+fjri4OHh7eyMwMBDPnz9HSkoKateuDUdHR0ydOhWWlpYqMaSnp2PdunU4e/asSgwFSUpKwtatW+Hn54eXL1/CwMAAbdq0wZQpU9C6desS54OIiIiIiN6v3Aqt/fv347///S9q164NZ2dnmJmZITExEQ8fPsSxY8fEQquk7t69i61bt6JDhw4YOXIkoqKicP78eYSEhGDNmjVo27Ztsdf59u1bzJgxA/fv30ezZs3Qt29fpKWlYfPmzbhx40aBy2VnZ2PmzJlISUlBx44dYWRkBCsrKwBAaGgotm/fjg4dOqB58+YwMDDAkydPcOzYMVy8eBE7duzABx98IK4rKysLM2fOxL179yCTydC3b1+kpqbin3/+QWhoqNrtP3/+HNOnT8fLly/h4OCArl27IiUlBX5+fpg6dSp+++03ODs7FzsfRERERERUNOVWaPn4+EBPTw9eXl6oVauW0rSkpKRSr//y5cv44osv4O7uLrZduHABCxcuxE8//YT9+/dDS0urWOvcvn077t+/j969e2PJkiXi8pMmTcK4ceMKXC4+Ph6NGzfG+vXrUb16daVpHTp0wOnTp2FoaKjUfvXqVcyZMwf//PMPvvvuO7F9x44duHfvHrp3747/+7//g7b2u96eEydOxPjx49Vuf9GiRYiNjcWyZcvQvXt3pbg++eQTLFmyBE5OTjAwMChWPoiIiKjsZGRkIDIyUtJ1vnnzBgBw//59Sddb1TCP0vg35LE4PeXK9R4tHR0d6Oqq1nZmZmalXnf9+vUxYsQIpbZu3bqhffv2ePbsGW7evFnsdR49ehTa2trw8PBQKtI++OADjB49utBl58+fr1JkAUCtWrVUiiwAcHJyQuPGjREUFKTUfuTIEWhra2PevHlikQUAVlZWSkWlQnh4OG7cuIGePXsqFVkAYG5ujvHjxyMhIQHXrl0rNH4iIiIiIiq5crui1bdvX6xYsQIjRoxA7969YW9vj7Zt26JmzZqSrN/Ozk6pEFGwt7dHaGgowsPDYWdnV+T1paWlITo6GnXr1lV731Rh6zIwMEDTpk0LnO7n54cDBw7g/v37SE5ORm5urjhNT09P/Hd6ejqioqJQt25dWFtbq6zH3t4eGzZsUGq7ffs2ACAlJUXts8WioqIAABEREejSpUuBMRIREVH5MjQ0LNV95eoorhxIvd6qhnmURlXLY7kVWuPGjYOZmRn279+PPXv2wMvLC1paWnBwcMC8efNKnfDatWsX2p6Wllas9aWnpxdpverUrFmzwG6KO3fuxPLly2FqagonJyd88MEHYhe+o0eP4sWLF+K8ipgL2pa5ublKW3JyMoB3XRGvXr1aYIwZGRkFTiMiIiIiotIp11EHBw4ciIEDByI1NRU3b97EuXPncPToUXh4eGD//v0wMzODtrY2srOz1S5fWLGUkJBQaHuNGjWKFauRkVGR1qtOQUVWTk4ONmzYAHNzc+zatUvlXrVTp04p/a2IuaBtxcfHq7QplvHw8MDEiRMLjJGIiIiIiMqORp6jZWxsjC5duuCHH37AgAEDkJSUJI7iZ2xsjISEBOTk5Kgsd+/evQLXefPmTcjlcpX2kJAQAICtrW2xYqxRowasrKwQFxeHmJgYlemFjTpYkKSkJKSlpaF169YqRVZsbCyeP3+u1GZkZIT69esjLi4O0dHRKutTvLa8WrVqBeDdUPdERERERKQZ5VZoBQcHQxAEpTZBEJCYmAgAqFatGgCgZcuWyM3NxeHDh5XmPXLkSKEDWkRGRmLfvn1KbRcuXEBoaCgaNGhQouHdBwwYALlcjtWrVyvF/vLlS3h5eRV7fbVq1YKBgQHu378vjroCAJmZmVi6dKnSvVoKgwYNglwux8qVK5UKyefPn2PPnj0q87ds2RJt2rSBv78/Dh06pDaO27dvIzMzs9jxExERERFR0ZRb18GFCxfC0NAQrVq1gqWlJeRyOW7cuIF79+6hZcuW4gOI3d3dceTIEfz3v//FtWvXULduXTx48AC3bt1C165dcfHiRbXr79SpE1asWIHLly9DJpOJz9EyMDDA999/X+yh3QFgwoQJuHDhAk6dOoVnz57ByckJaWlpOHv2LNq1a4cLFy4Ua73a2tpwd3fHtm3bMGrUKDg7O+Pt27e4evUqdHR0IJPJ8ODBA6Vlxo0bhwsXLuDcuXMYN24cOnbsiNTUVDEGf39/le0sWbIEM2bMwM8//4z9+/ejRYsWMDQ0xKtXrxAWFoaoqCicPHlSLG6JiIiIiEha5XZFy8PDA82bN0d4eDj27duHo0ePIjc3F3PnzsXff/8tDvveuHFj8QHD/v7+OHjwIPT09LB58+ZCB8xo2bIl1q1bh6ysLOzZsweXL1+Go6MjNm7cWKzRBvOqVq0a1q1bB3d3d8THx2PXrl0IDg7Gp59+Kt7/VNx7v2bNmgUPDw/o6uriwIEDuHjxIhwdHbFp0ya169LX18eaNWswZswYvH79Grt370ZoaCgmT56Mzz77TO026tWrh507d2LatGnIzc3FsWPHsHfvXty9exdNmjTB4sWLJRlSn4iIiIiI1NMS8vfnoyI5ePAglixZgm+++QbDhw/XdDgaERAtoOtu1e6OREREVDwXR+mgi3Xxe9+8T1UbTrusMI/SqGp51MhgGJVJXFycStvLly+xceNG6OjowNnZWQNRERERERFRRVauw7tXRl9++SVyc3Nha2sLY2NjvHjxAhcvXkRmZiY8PDxQp04dTYdIREREREQVTJUqtIKDg9UOiZ6fsbExxowZAwDo378/jh8/jnPnziEtLU0c0GPkyJHo0aNHWYdMRERERESVUJUqtEJCQrBhw4b3zlevXj2x0BoxYgRGjBhR1qEREREREdG/SJUqtKZPn47p06drOgwiIiIiIvqXq1KFFkmrTZ13oyQRERFR6bThLd9E/zostKjEhMwUdPzASHwGGhVfRkYGAMDQ0FDDkVRuzKM0mEdpMI/SYB6JqLLj8O5UYjdu3EB6erqmw6jUIiMjERkZqekwKj3mURrMozSYR2kwj0RU2bHQIiIiIiIikhgLLSIiIiIiIomx0CIiIiIiIpIYCy0iIiIiIiKJsdAiIiIiIiKSGAstIiIiIiIiibHQIiIiIiIikhgLLSIiIiIiIomx0CIiIiIiIpIYCy0iIiIiIiKJ6Wo6AKq87OzsYGRkpOkwKjUbGxtNh/CvwDxKg3mUBvMoDeaRiCo7FlpUYlrVTBD4EgAETYdSiVV/979E5rB0mEdpMI/SYB6loZzHNnUAEwMtDcZDRFQ8LLSoxG7FAV1352o6DCIiqgIujtJBF2tNR0FEVHS8R4uIiIiIiEhiLLSIiIiIiIgkxkKLiIiIiIhIYiy0iIiIiIiIJMZCi4iIiIiISGIstIiIiIiIiCTGQuv/c3BwwLRp0zQdRqmtW7cODg4OCA4O1nQoRERERERVFgutSiYmJgYODg748ccfNR0KEREREREVgIUWERERERGRxFhoERERERERSUy3pAvevHkT27dvx61bt5CSkoI6deqgW7dumDp1KkxMTAC86+Y2ePBgDBw4EJ9++ik8PT0REhICuVwOe3t7LFy4EJaWloiKisKqVasQHByMzMxM2Nvb48svv4S1tbXSNgcNGgQA8PLywurVq3HhwgUkJyfD2toaH3/8MUaMGAEtLa1SpENVTk4O9u/fj+PHjyMiIgJyuRyNGzeGu7s7BgwYoDTvunXrsGHDBqxduxZJSUnYtm0bHj9+DAMDAzg5OWHBggWwsLBQ2cbdu3exZs0a3L59G1paWmjZsiVmzJiBK1euiOtzcHAQ1w8AR48exdGjR8V1KObJ6+zZs0WOgYiIiIiIpFOiQuvgwYNYunQpqlevDmdnZ5ibm+Px48fw8vLClStXsGXLFtSoUUOcPyYmBpMmTULTpk0xZMgQPHnyBP7+/njy5AmWL1+OKVOmoEmTJhg0aBCePHmCy5cvY/78+di7dy+0tZUvumVnZ2PWrFlITU1F7969kZ2djXPnzuG3335DZGQkFi5cWLqM5NvWvHnzEBQUhMaNG6N///7Q1tZGYGAgFi1ahKdPn8LDw0Nluf3798Pf3x/Ozs6wt7fHnTt3cObMGTx8+BC7du2Cvr6+OG9oaCg8PDyQm5uLHj16wNraGo8ePcKMGTNUCid7e3ukpaXBy8sLMpkMLi4u4jRLS8sSx0BERERERNIqdqEVERGB//u//0P9+vWxfv161K5dW5x2/Phx/PDDD1i7dq1SwRMaGor58+dj3LhxYtuSJUtw8OBBTJo0CZMnT1Y7zc/PD927d1fafnx8PKysrLBnzx6xWJg+fTomTJiA3bt3w9XVFW3bti3uy1Jr48aNCAoKwtixYzFv3jyx6MvKysIXX3yBLVu2oFevXmjWrJnScleuXMG2bdvQpEkTse27777DqVOn4OfnB1dXVwCAXC7Hzz//jKysLPz111/o3LmzOP/+/fvx3//+V2m9Dg4OsLS0FAut6dOnFxh7UWMgIiKqLDIyMhAZGanpMCqVN2/eAADu37+v4UgqN+ZRGv+GPOY/7i9Mse/ROnDgAHJycvD5558rFVkA0L9/f9ja2uLUqVNK7VZWVhgzZozKvABgYmKiMq1fv34AgAcPHqiNwcPDQ+mKjKmpKaZMmQIAOHLkSHFfklpyuRz79+9HnTp1MHfuXKUra/r6+uKVrPyvFQDc3d2VChwAcHNzA/Cum6DCrVu3EBUVBQcHB6UiCwCGDRsGGxubEsdf1BiIiIiIiEh6xb6idevWLQDAtWvXcPv2bZXp2dnZeP36NZKSksS2pk2bqnQBNDc3L3BanTp1AABxcXEq69fR0UGbNm1U2u3t7QEA4eHhxXg1BXv27BmSk5NhY2ODjRs3qkzPyckB8O4KX34tWrRQaatbty4AICUlRWxTVPN2dnYq82tra6Nt27YlPnNX1BiIiIgqC0NDw2KdTab/HWswb6XDPEqjquWx2IWW4iB9+/bthc6nuDQIQOl+LQUdHZ33TlMUM3mZmZmJ0/NSXF1LS0srNK6iSk5OBgBERkaKA1Cok5GRodJW2GuSy+VimyLWWrVqqV13Qe1FUdQYiIiIiIhIesUutBQH8CdPnhSvShUkJiamZFEVIikpCbm5uSrFVkJCglJ8paVYz0cffQRPT09J1lnQNhITE9VOL6idiIiIiIgqtmLfo9WqVSsAUNttsDzk5uaK3RfzCgkJAQDY2tpKsp2GDRvCyMgI4eHhePv2rSTrzE8R640bN1SmyeVy3Lx5U6Vd0c0yNze3TGIiIiIiIqLSK3ahNWLECOjo6ODPP/9EdHS0yvTMzMwyL8JWrVqFrKws8e/k5GT8888/AP73rK3S0tXVxciRI5GYmIhly5YpbU/h+fPnpbpq17ZtW1hbWyM4OBiXL19Wmubt7a32/iwTExNoaWnh1atXJd4uERERERGVrWJ3HWzcuDG+/fZb/PrrrxgxYgQ6deoEGxsbZGZm4sWLFwgNDUXbtm3LrLudubk5srOz4e7uDmdnZ+Tk5MDX1xfx8fEYNWqUZEO7A8C0adMQHh4OHx8fBAYGwsHBAbVr10ZCQgIiIiJw9+5d/PLLLyrPsCoqbW1t/Oc//8HcuXOxYMEC9OzZE1ZWVnj06BGuXr2KTp064fLly0qDhRgaGqJFixa4fv06vv/+e9jY2EBLSwsDBgxAvXr1pHrpRERERERUCiV6YPGQIUNga2uLnTt3IjQ0FJcuXYKRkREsLCwwZMgQcXj2sqCnp4c1a9Zg9erVOHXqFJKTk2FtbY1PP/0UI0eOlHxbK1aswJEjR3Ds2DH4+fkhMzMTtWrVgrW1NebNmwcnJ6dSbcPBwQHr16/HmjVrEBAQAOBd98y1a9fixIkTAAAjIyOlZX766Sf8+eefCAgIQFpaGgRBgJ2dHQstIiIiIqIKQksQBEHTQRSVolugVM/KqugmTZqEu3fv4sKFC6hevbqmw1EREC2g627eK0ZERGXv4igddLHW0nQYlU5VG067rDCP0qhqeSz2PVokrczMTKSmpqq0HzlyBLdu3YKTk1OFLLKIiIiIiKhgJeo6SNJ5+fIlxo4dCycnJ1hbWyMnJwfh4eG4efMmjI2NsWDBAk2HSERERERExfSvLLRSU1Oxa9euIs07aNCgEg9mIYVatWqhb9++CA0NRXBwMLKyslC7dm0MGjQIkydPhrW1tcZiIyIiIiKikqlUhVZR781KTU3Fhg0bijSvvb29RgstExMTfP/99xrbPhERERERSa9SFVpFZWlpieDgYE2HQUREREREVdS/stCi8tGmzrtRoIiIiMpamzqajoCIqHhYaFGJCZkp6PiBEXR1uRuVVEZGBoB3D6KmkmMepcE8SoN5lAbzSESVHYd3pxK7ceMG0tPTNR1GpRYZGYnIyEhNh1HpMY/SYB6lwTxKg3kkosqOhRYREREREZHEWGgRERERERFJjIUWERERERGRxFhoERERERERSYyFFhERERERkcRYaBEREREREUmMhRYREREREZHEWGgRERERERFJjIUWERERERGRxFhoERERERERSUxX0wFQ5WVnZwcjIyNNh1Gp2djYaDqEfwXmkYiIiCoaFlpUYlrVTBD4EgAETYdSiVV/979E5rB03p/HNnUAEwOtcoqHiIiIqjoWWlRit+KArrtzNR0GUZFcHKWDLtaajoKIiIiqCt6jRUREREREJDEWWkRERERERBJjoUVERERERCQxFlpEREREREQSY6FFREREREQkMRZaREREREREEmOhRUREREREJDEWWhKKiYmBg4MDfvzxR02HQkREREREGsRCi4iIiIiISGIstIiIiIiIiCTGQksi69atw+DBgwEAR48ehYODg/hfcHCwON+xY8cwdepUuLi4oHPnzhg1ahR27doFuVyutL4jR47AwcEBR44cweXLlzFt2jS4uLjAwcFB3J5i3ceOHcOYMWPQuXNnDBgwAOvWrRPXd/r0aYwfPx6dO3dGnz59sHr1auTm5pZTVoiIiIiIqiZdTQfwb2Fvb4+0tDR4eXlBJpPBxcVFnGZpaQkAWLRoEY4dOwZLS0u4urqievXqCA0NxZ9//ok7d+7g119/VVmvr68vrly5gk6dOmH48OF48eKF0vTdu3cjKCgILi4usLe3x8WLF7FhwwbI5XKYmppi7dq1cHFxgZ2dHQICArB582ZUr14dkyZNKtuEEBERERFVYSy0JOLg4ABLS0ux0Jo+fbrSdB8fHxw7dgyurq5YvHgx9PX1AQByuRxLly7FwYMH4erqiu7duystd+nSJfz111/o1KmT2u2GhoZi586dqF+/PgBg+vTpGDp0KHbu3AkjIyPs2LEDNjY2KtMmTJgAXV2+/VS1ZGRkIDIyUtNhVFhv3rwBANy/f1/DkVRuzKM0mEdpMI/SYB6l8W/IY7NmzYo8L7sOlpO9e/dCV1cX3333nVhkAYC2tjbmzp0LLS0tnDx5UmU5FxeXAossAHB3dxeLLACoUaMGnJ2dkZmZiWHDholFlmJa165dkZycjNjYWIleGRERERER5cdLGuUgMzMTDx8+hJmZGXbu3Kl2HgMDA0RERKi0t2zZstB129raqrSZm5sXOK1OnToAgNjYWLFLI1FVYWhoWKwzUVWN4gwjc1Q6zKM0mEdpMI/SYB6lUdXyyEKrHKSkpEAQBLx+/RobNmwocD7F5dS8ateuXei6a9SoodKmo6Pz3mk5OTmFrpeIiIiIiEqOhVY5UBQ8DRo0wIEDB4q1rJaWVlmEREREREREZYj3aElIW/tdOvMPn25oaIjGjRsjOjoaiYmJmgiNiIiIiIjKEQstCZmYmEBLSwuvXr1SmTZq1Cjk5ubip59+Qlpamsr0+Ph4PHnypDzCJCIiIiKiMsaugxIyNDREixYtcP36dXz//fewsbGBlpYWBgwYgGHDhuHu3bs4dOgQ3Nzc4OTkhLp16yIpKQlRUVG4efMmZs6cicaNG2v6ZRARERERUSmx0JLYTz/9hD///BMBAQFIS0uDIAiws7NDvXr18P3336NLly7w9vbGlStXkJ6eDjMzM1haWmLq1Kno27evpsMnIiIiIiIJaAmCIGg6CKqcAqIFdN2d+/4ZiSqAi6N00MWag8sUpqoNu1tWmEdpMI/SYB6lwTxKo6rlkfdoERERERERSYyFFhERERERkcRYaBEREREREUmMhRYREREREZHEWGgRERERERFJjIUWERERERGRxPgcLSqxNnXeDZlNVBm0qaPpCIiIiKgqYaFFJSZkpqDjB0bQ1eVuVFIZGRkAAENDQw1HUrkxj0RERFTRsOsgldiNGzeQnp6u6TAqtcjISERGRmo6jEqPeSQiIqKKhoUWERERERGRxFhoERERERERSYyFFhERERERkcRYaBEREREREUmMhRYREREREZHEWGgRERERERFJjIUWERERERGRxFhoERERERERSYyFFhERERERkcRYaBEREREREUlMV9MBUOVlZ2cHIyMjTYdRqdnY2Gg6BCIiIiIqAyy0qMS0qpkg8CUACJoOpRKr/u5/icyhQps6gImBlqbDICIiIioVFlpUYrfigK67czUdBv3LXBylgy7Wmo6CiIiIqHR4jxYREREREZHEWGgRERERERFJjIUWERERERGRxFhoERERERERSYyFFhERERERkcRYaBEREREREUmMhVYlN2jQIAwaNEjTYRARERERUR4stIiIiIiIiCTGQouIiIiIiEhiLLSIiIiIiIgkpqvpACoDQRCwe/dueHt74/nz5zA1NUW3bt0we/ZsjB49GgBw5MgRAMCPP/6Io0ePwsfHBwEBAfDx8UFUVBRatmyJ9evXIzs7GwcOHMClS5fw5MkTJCYmwtDQEC1btsTEiRPRvn17tdvfu3cvDhw4gOjoaKXtFyQnJwf79+/H8ePHERERAblcjsaNG8Pd3R0DBgwom0QREREREREAFlpF8n//93/Yv38/LCws4ObmBj09Pfj7++Pu3bvIycmBrq5qGv/44w9cv34dXbp0QefOnaGt/e7iYXJyMv7880+0bdsWnTp1gqmpKV69egU/Pz/MnDkTy5Ytg7Ozs8q6du/eDXNzc7i5uUFXVxd+fn64e/cusrOzoaenpzR/dnY25s2bh6CgIDRu3Bj9+/eHtrY2AgMDsWjRIjx9+hQeHh5llzAiIiIioiqOhdZ7XL9+Hfv374eNjQ22bduGGjVqAABmz56NWbNmIS4uDvXq1VNZ7v79+9i5cyesrKyU2k1MTHD06FFYWFgotcfGxmLChAlYsWKFUqF18+ZN7N69G9bW1ti6dStMTU0BALNmzcKMGTMQHx+vsv2NGzciKCgIY8eOxbx588QiLysrC1988QW2bNmCXr16oVmzZqVPEFEZyMjIQGRkZJHnf/PmDYB3nzsqOeZRGsyjNJhHaTCP0mAepfFvyGNxjp95j9Z7HD16FAAwadIkscgCAD09vUK77k2YMEGlyAIAfX19lSILACwsLNCzZ09ERkbi5cuXYruiS+KkSZPEIgsADAwM1G5fLpdj//79qFOnDubOnSsWWYptK65knTp1qsDYiYiIiIiodHhF6z3Cw8MBAHZ2dirTWrduDR0dHbXLtWzZssB1Pnr0CFu3bsWNGzcQHx+P7OxspemxsbH44IMPAPyv4ld375adnZ3K9p89e4bk5GTY2Nhg48aNKsvk5OQAACIiIgqMj0jTDA0Ni3XGSPE54VXa0mEepcE8SoN5lAbzKA3mURpVLY8stN4jLS0NAFC7dm2VaTo6OjAzM1O7nLr5AeDWrVuYOXMm5HI5nJyc0L17dxgaGkJLSwshISEIDQ1FVlZWkbavq6ursv3k5GQAQGRkJDZs2FDg68rIyChwGhERERERlQ4LrfcwMjICACQkJMDa2lppWm5uLpKSktR2BdTS0lK7vk2bNuHt27fYsGED2rVrpzRtyZIlCA0NVWpTdFdUt/2cnByV7Svm/+ijj+Dp6VmUl0hERERERBLjPVrvYWtrCwC4ceOGyrTbt28jNze3WOuLioqCqampSpEll8tx8+ZNlfkVl1bzF2CKmPJvv2HDhjAyMkJ4eDjevn1brNiIiIiIiEgaLLTeQ/HMqU2bNond+IB3Q6ivWbOm2OuztLRESkoKHj16pNS+adMmPHnyRGX+gQMHitMV3QIB4O3bt1i9erXK/Lq6uhg5ciQSExOxbNkypW6ICs+fP0dMTEyxYyciIiIioqJh18H3sLe3h5ubGw4ePIiRI0eiR48e0NXVhb+/P2rUqIE6deoojez3Pu7u7rhy5QomT54MV1dXGBoa4tatW3j48CG6du2KixcvKs1vZ2cHd3d37NmzB+7u7ujZs6f4HC0TExOYm5urbGPatGkIDw+Hj48PAgMD4eDggNq1ayMhIQERERG4e/cufvnlF1haWpY6P0REREREpIpXtIrgm2++wYIFC1C9enUcOHAAJ0+ehJOTE9asWYP09HTxPq6i6NKlC37//Xc0aNAAp06dwrFjx1CzZk1s2rSpwBFYFi5ciC+++AI1atSAt7c3Tp06hY8++ghr1qxReVgx8G7o+RUrVuD777+HpaUl/Pz8sGvXLly7dg0GBgaYN28enJycSpwPIiIiIiIqnJYgCIKmg6isIiMjMWzYMPTu3Ru//vqrpsMpdwHRArruLt49akTvc3GUDrpYqx9MpiBVbbjYssI8SoN5lAbzKA3mURrMozSqWh55RasI4uPjkb8effPmDf744w8AQPfu3TURFhERERERVVC8R6sIvLy8cPr0abRv3x7m5uZISEjAtWvX8OrVK3Tq1Am9evXSdIhERERERFSBsNAqAicnJzx8+BCBgYFISUmBjo4OGjRoAHd3d4wZM6bAZ2YREREREVHVxEKrCBwdHeHo6KjpMIiIiIiIqJLgPVpEREREREQS4xUtKrE2dd6NEEckpTZ1NB0BERERUemx0KISEzJT0PEDI+jqcjcqqYyMDACAoaGhhiMhIiIiIimx6yCV2I0bN5Cenq7pMCq1yMhIREZGajoMIiIiIpIYCy0iIiIiIiKJsdAiIiIiIiKSGAstIiIiIiIiibHQIiIiIiIikhgLLSIiIiIiIomx0CIiIiIiIpIYCy0iIiIiIiKJsdAiIiIiIiKSGAstIiIiIiIiibHQIiIiIiIikhgLLSIiIiIiIomx0CIiIiIiIpIYCy0iIiIiIiKJsdAiIiIiIiKSGAstIiIiIiIiibHQIiIiIiIikhgLLSIiIiIiIomx0CIiIiIiIpIYCy0iIiIiIiKJsdAiIiIiIiKSGAstIiIiIiIiibHQIiIiIiIikhgLLSIiIiIiIomx0CIiIiIiIpIYCy0iIiIiIiKJaQmCIGg6CKp8bt68iezsbGhra0NLS0vT4VRacrkcAKCtzXMepcE8SoN5lAbzKA3mURrMozSYR2n8G/Kora2Ntm3bFm3eMo6F/qVev36NrKwsFlml9PbtW7x9+1bTYVR6zKM0mEdpMI/SYB6lwTxKg3mURlXLI69oUYl07doVAHDx4kUNR1K5MY/SYB6lwTxKg3mUBvMoDeZRGsyjNKpaHnlFi4iIiIiISGIstIiIiIiIiCTGQouIiIiIiEhiLLSIiIiIiIgkxkKLiIiIiIhIYiy0iIiIiIiIJMZCi4iIiIiISGJ8jhYREREREZHEeEWLiIiIiIhIYiy0iIiIiIiIJMZCi4iIiIiISGIstIiIiIiIiCTGQouIiIiIiEhiLLSIiIiIiIgkpqvpAKhiycrKwrp163D8+HGkpKTgww8/xMyZM/HRRx+9d9nU1FSsXLkS58+fR2ZmJlq0aIH58+ejRYsW5RB5xVLSPMbHx8PLywv37t3DvXv3kJ6ejiVLlqBPnz7lFHnFUtI8BgUF4cSJE7h58yZevXoFc3NzODg4YObMmTA3Ny+n6CuOkuYxMDAQXl5eePjwIZKSkmBsbAxbW1tMmjQJdnZ25RN8BVKa78e8/vnnH/z9999o0KABDhw4UEbRVlwlzeORI0ewePFitdNOnjxZ5T7bpd0fr127hs2bN+Pu3buQy+WoX78+xowZg4EDB5Zx5BVLSfM4bdo0hIaGFjj9+PHjsLCwkDrcCqs0+2NYWBjWr1+Pe/fuISMjA/Xq1UP//v0xevRoGBgYlEP0ZYfP0SIl3377LXx9fTF69GjY2Njg6NGjuHv3LtasWQN7e/sCl5PL5ZgyZQoePnyIcePGoVatWti3bx9evnyJbdu2oWHDhuX3IiqAkuYxODgYM2bMgLW1NSwsLBAaGlqlC62S5nH8+PFISUlBz549YWNjg+fPn2Pv3r2oVq0adu7cWeUOyEqax927dyMkJAQtWrRAzZo1kZqaihMnTuDRo0f4888/0aVLl3J8FZpX0jzm9erVKwwfPhxaWlqwsLCokoVWSfOoKLSmTZsGa2trpWk9e/as9AdkxVWa/fHw4cP4+eef4eTkhK5du0JXVxeRkZEwNjbGlClTyukVVAwlzWNgYCASExOV2uRyOX755RfY2Nhg7969ZR16hVLSPIaFhWHSpEmoX78+Bg8ejOrVqyM4OBhnzpyBq6srli5dWo6vogwIRP/f7du3BXt7e2Hz5s1iW2ZmpjBkyBBh/PjxhS57+vRpwd7eXjh16pTYlpiYKHTr1k346quvyirkCqk0eUxLSxNev34tCIIgXLt2TbC3txdOnjxZhtFWXKXJY0hIiJCbm6vSZm9vL3h6epZFuBVWafKozps3b4TevXsLM2fOlDDKik+qPH799dfCjBkzhKlTpwrDhg0rg0grttLk8fDhw4K9vb1w69atMo6y4itNHp8/fy506tRJWLZsWRlHWfFJ/f0YEBCgsr6qoDR5/OWXXwQnJyfx2Edh4cKFQocOHYSMjIwyiLj88B4tEvn6+kJbWxvDhg0T2wwMDDBkyBDcu3cPMTExhS5rZmaGXr16iW01a9ZEr169cPHiRWRmZpZp7BVJafJoZGQEMzOzcoiy4itNHtu3bw9tbW2VNlNTUzx58qTMYq6ISpNHdapVqwZTU1OkpaVJHWqFJkUeQ0NDce7cOXz++edlGWqFJtX+mJaWhtzc3LIKs8IrTR4PHDgAuVyOGTNmAADS09MhVNHOTVJ/P544cQJaWlro27ev1KFWaKXJY1paGgwMDGBiYqLUbm5uDm1tbejp6ZVZ3OWBhRaJwsPDYW1trbKzt2zZUpxe2LK2trYqB7ctW7bE27dvERERIXm8FVVp8kj/I3UeMzIykJGRUeUKWSnymJaWhqSkJDx9+hSenp548uQJnJycyiTeiqq0eczNzcWyZcswZMgQNGnSpMzirOik2B9nz56Nbt26oUuXLpg/f36V+n1RKE0eg4KC0LBhQwQEBGDAgAFwcXFBjx494OnpWeWKVyl/Z968eQM/Pz+0a9cOH3zwgaRxVnSlyWP79u2Rnp6On3/+GU+ePMHLly9x9OhRHD58GBMmTICubuUeTqJyR0+Sio+PV3vviqItLi6u0GXbtGlT4LLx8fESRVnxlSaP9D9S53HXrl3Izs5G7969JYmvspAij/PmzcPNmzcBAHp6ehg2bFiVu4+jtHk8cOAAXrx4gTVr1pRJfJVFafJYrVo1DBo0CPb29qhRowbCwsKwc+dOTJ48GTt27EC9evXKLO6KpjR5jIyMhI6ODn766SdMmDABMpkM/v7+2Lp1K7KysqrUFVcpf2fOnz+PN2/eoH///pLFV1mUJo9ubm548uQJvL29ceTIEQCAlpYWZs2ahU8//bRsAi5HLLRI9PbtW7WXaPX19cXphS2rmC8vxc3JVanrYGnySP8jZR5DQ0OxYcMG9OrVCx07dpQsxspAijx+/vnnSElJEc80ZmdnIycnp0oNPlCaPCYlJWHdunWYMmUKatasWWYxVgalyaOrqytcXV3Fv7t164aPPvoIU6dOxcaNG/H9999LH3AFVZo8vnnzBnK5HB4eHpg4cSIAoEePHkhPT8e+ffswefLkKnPlX8rfmRMnTsDAwEDpFoqqojR51NXVRf369eHo6AhXV1cYGRnB398fa9asgZGREUaOHFlmcZcHFlokMjAwQHZ2tkp7VlaWOL2wZRXz5aX4cFWrVk2iKCu+0uSR/keqPEZEROCLL77Ahx9+WKUOxBSkyGPeRzT0798f48aNw+LFi/Hbb79JF2gFV5o8/v333zAxMYG7u3uZxVdZSP39aGdnh1atWiEoKEiS+CqL0v5ev3nzRuU+or59++L8+fO4c+dOlRlRVKr9MSEhAUFBQejWrRtq1KghaYyVQWnyuGXLFuzcuRMHDx4Uc9ezZ08IgoC//voLrq6ulfoEFe/RIpG5ubnaLn6Ktjp16pR42ao0nHZp8kj/I0UeX758idmzZ6NGjRpYuXIljIyMJI+zopN6f9TX14eLi4v4vLyqoqR5jIyMxMGDB+Hu7o64uDjExMQgJiYGWVlZyMnJQUxMDJKTk8s09oqkLL4f69ati5SUlFLHVpmUJo+KabVq1VJqr127NoB3z8SsKqTaH0+dOoXc3Fz069dP0vgqi9Lkcd++fXBwcFApULt164a3b98iLCxM2mDLGQstEtna2iI6OlrlB+vOnTsAAJlMVuCyMpkM4eHhkMvlSu13796FgYFBlXqOVmnySP9T2jwmJSXBw8MD2dnZ8PT0rFLFfl5lsT9mZmZCEARkZGRIEmNlUNI8xsbGQi6X4/fff8fgwYPF/+7cuYPnz59j8ODBWLt2bZnHX1GUxf74/PnzKtPVTaE0eWzWrBmAd/tmXq9evQKASn31oLik2h9PnjwJU1PTKnMlML/S5DExMRE5OTkq7YqBWSr7AC0stEjUs2dPyOVyeHt7i21ZWVk4cuQImjdvDisrKwDvzlBEREQofTB69uyJpKQknD17VmxT/N25c+cq1XWwNHmk/ylNHt+8eYN58+YhLi4Of/31F2xsbMo9/oqiNHnM/zBOAEhOTsa5c+dQt25dlTPi/2YlzWOTJk3w+++/q/zXuHFjWFhY4Pfff1caEvnfrjT74+vXr1XWFxAQgLCwMHTq1Knsg69ASpNHxYBAhw4dEtsEQcChQ4dgaGiI1q1bl9Or0Dwpfq8jIiJw7949uLq6VvoR8kqqNHls0KABgoODkZCQoLTOEydOQFtbG7a2tuXzIspI1dwjSK1WrVqhV69e+Pvvv5GcnIz69evj2LFjiImJwerVq8X5Vq1aJQ69aWlpCeDdh6x169b4+eefERERgZo1a2Lfvn3IycnBzJkzNfWSNKI0eQSAjRs3AoD43IkLFy4gKioKAKrUSG+lyeN//vMf3L17F4MHD8bTp0/x9OlTcX5DQ0N069atvF+OxpQmj5MnT0bTpk3RvHlz1KxZEzExMTh8+DASExPx66+/auolaURJ82hmZqZ2f9u1axdyc3Or1L4IlG5/nDRpEmxtbdG8eXPUqFED9+/fx+HDh2FhYYHJkydr6iVpRGny6OLiAkdHR2zZsgVJSUmQyWS4ePEigoKCMH/+/CrVxbq0v9fAu4IAQJXtNgiULo8TJ07Ef/7zH3zyyScYPnw4jIyM4Ofnh6tXr8LNzQ0WFhaaelmSYKFFShYvXox69erhxIkTSElJwYcffog///wTDg4OhS6no6ODv/76CytXrsSePXuQmZmJli1b4ocffkCjRo3KKfqKo6R5BKDSjejMmTM4c+YMgKpVaAElz+ODBw8AAIcPH8bhw4eVptWrV6/KHdyWNI9ubm64cOECduzYgbS0NJiamqJ169YYN24c2rVrV07RVxyl+VzT/5Q0j66urggICEBgYCAyMzNhbm6OoUOHYurUqVWya3BJ86ilpYXff/8df//9N86cOYOjR4+ifv36+P777zFkyJByir7iKO3n+uTJk7CyskLbtm3LONKKraR57Nu3L2rVqoXNmzfDy8sLqampsLKygoeHB8aPH19O0ZcdLaGqPg6ciIiIiIiojPAeLSIiIiIiIomx0CIiIiIiIpIYCy0iIiIiIiKJsdAiIiIiIiKSGAstIiIiIiIiibHQIiIiIiIikhgLLSIiIiIiIomx0CIiIiIiIpIYCy0iIiIiIiKJsdAi0rDly5ejTZs2ePXqlVL7119/DVtbWw1FVTVcvXoVtra28PT0LPdte3t7w9bWFlevXlVq37ZtG1q2bInHjx+XeN1jxozBkCFDIAhCacOkIrK1tcX48eM1HQZVUorvA29v71Ktp0ePHujRo4dEUdG/nVT7XWlI8TssCAKGDRuGMWPGSBiZNFhoEWlQTEwMtmzZgrFjx6Ju3bpFXu7GjRtYsGABXFxc0KpVKzg4OKB3796YO3cutm7dqnKAbWtrC2dn50LXaWtr+97CbsWKFbC1tUXz5s3x4sWLAudTfHnn/a9Vq1bo0aMHvv76azx69KjIr7WqGTVqFMzNzfHbb7+VaPkTJ04gJCQE8+fPh5aWlsTREb3j6emp9kQBUV7R0dGwtbXF119/XaVjqGwqW8GupaWFuXPnIiQkBCdPntR0OEp0NR0AUVW2Zs0aZGdnY9KkSUVexsfHB9988w0AoFOnTujTpw8MDAwQGRmJa9eu4dSpUxg7dix0daX9eOfm5sLb2xtaWlqQy+U4cOAAPDw8Cl3GwcEBHTt2BAAkJyfj6tWrOHjwIE6cOIGtW7fCzs5O0hj/DfT19TFhwgT89ttvCA0NRfv27Yu8rCAIWLFiBZo2bYru3buXYZSU3/Hjx1G9enVNh0FEVGSurq5o27YtLCwsNB1KqXXr1g0ymQzLly9Hnz59KsyJRhZaRBqSmpqKo0ePonPnzqhTp06Rlnnz5g1++uknaGlpYdOmTWIRoyAIAgICAqCjoyN5vH5+fnj16hXc3d1x4sQJHDhwALNmzYK2dsEXxh0cHDBnzhyl+L766iscOnQIf/zxB7Zv3y55nP8GgwYNwh9//IFdu3YVq9C6fPkyIiIisHDhwjKMjtT58MMPNR0CEVGxGBsbw9jYWNNhSGbw4MH4/fffceXKFXTq1EnT4QBg10GqoPL22b158yY+/fRTtG/fHk5OTli4cCGSkpIAAHfu3MGUKVPg4OAAe3t7LFiwAImJiWrXGRMTgx9++AE9evRAq1at8NFHH2HevHlq74W5c+cOfv75ZwwaNAgdOnRA69at0bdvXyxfvhxv3rxRmX/8+PGwtbVFTk4O1q5di969e6NVq1ZwcXHBsmXLkJWVpbLM0aNH8ebNG/Tv37/IeXn48CHS09PRtGlTlSILeHf5vGvXrmVyJmfv3r0AgNGjR6Nfv36IiYnBxYsXi7UOLS0tjBs3DgBw+/btQue9fv06bG1tMW/ePLXT5XI5nJ2d0b59e/E9SU1NxYYNGzB+/Hh07doVrVq1QufOnTF37lzcv3+/yHEW1m2isC5ToaGhmD17Njp16iR2lfz111+RnJxc5G0DgIWFBezt7XHq1CmkpaUVebn9+/cDgNp96tWrV/D09IS7u7sYn4uLC7755htER0crzbtu3TrY2tpi586darfz5MkT2NraYuLEiUrtGRkZWL16NQYNGoS2bduiffv2GD9+PPz8/FTWobgHMSoqCtu3b8egQYPQpk0b8T6nrKwsbN++HZMnT0a3bt3QqlUrODk5YerUqbh27ZrauARBwNatW9G/f3+0bt0aXbt2xU8//YTU1NQC39Ps7Gxs374dw4cPR7t27WBnZ4ePP/4YPj4+ardREHX3aOV9jVu2bEHfvn3RunVruLq6KuV2586dGDBgANq0aYMePXpgy5YtKuvPey/FhQsX4O7uDjs7Ozg6OmLevHmIjIxUWebp06dYtmwZhg0bBicnJ7Rq1Qo9e/bEzz//XOD3ZG5uLry8vDBq1CjY29ujTZs2cHV1xXfffYeIiAgA7z4fq1atAgBMmDBB7B5c1K5GWVlZWL9+vfiet2/fHmPHjsXx48dV5s37WxAWFoZp06bBwcEBbdu2xbhx4xAaGlqkbeZfl1S/K3fu3IGHhwc++ugj8TO/ePFixMbGqp3/2bNnmDt3Ljp06AA7OzuMGjUKFy5cKDTuhw8fYuHCheJ3WteuXfHtt9/i5cuXRX7thbly5QomT54MR0dHtG7dGn369MEff/yB1NRUlXmL893o6emJnj17AgAOHjyo1JU87zyKvw8ePIghQ4agTZs26NSpE7777jvEx8eXeQwFydvl8OnTp5g9ezY6dOgAe3t7zJw5U/zeVLynTk5OaNu2LaZOnYqoqCiV9RX3uAJ49xmeM2eOyv6i7t6qvPFGR0djwYIFcHJyQuvWrTFs2DCcP39eZf3516P4jDx//hzPnz9XypfiHqr33VNV0PsTHx+Pb7/9Fp06dUKbNm0wZMgQHDx4sND3oDjHbcD/fvsUv4UVAa9oUYV269YtbNiwAZ06dYK7uztu3ryJI0eOICYmBl988QU+/fRTdOzYESNGjMDNmzdx/PhxJCcnY9OmTUrruX37NiZPnozU1FQ4OzujT58+iIuLw5kzZ+Dv749t27ahdevW4vx79+7FuXPn4ODggC5duiA7OxvXr1/H2rVrcfXqVezYsUNt17zPP/8cISEh6Nq1K1xcXODv74+NGzciMTERS5cuVZr3ypUrAIB27doVOR9mZmYAgLi4OGRkZMDQ0LDIy5bGq1ev4O/vL96fNWzYMOzZswf79u2Di4tLsdaluH/sfcVgu3bt0LBhQ5w/fx4pKSkwMTFRmn758mW8evUKw4cPF7tsPX78GH/99RccHR3Ro0cP1KhRA1FRUTh37hz8/Pywc+dOtGrVqljxFtXevXuxaNEiVK9eHT169ICFhQUePHiArVu34uLFi9i7d2+xzhy2b98eQUFBuHbtWpG6AQqCgMDAQFhYWMDKykplenBwMP755x907NgRrVq1goGBAR49egQfHx+cP38e3t7esLS0BAAMGTIEK1aswKFDhzB27FiVdSmKkKFDh4ptycnJGD9+PMLDw9GmTRuMHDkSb9++xYULFzBt2jT8+OOPGD16tMq6lixZguDgYLi4uMDFxUW8GpucnIxff/0V7du3R9euXWFmZoYXL17A19cXly5dwqpVq1R+zBcvXgwvLy/UrVsX7u7u0NPTw7lz53Dr1i1kZ2dDT09Paf6srCxMmzYNV65cQdOmTTFkyBDo6OggICAAX331FR4/fozPP//8vbl/n//+978IDQ1Ft27d0LlzZ5w6dQo//fQT9PX18fDhQxw5cgTdunVDx44dcerUKSxduhS1a9fGoEGDVNal+M7q1asXnJycEBYWhpMnT+Lq1avYvXs3GjZsqDTv3r170bFjR9jb20NHRwd3797Fjh07EBAQgAMHDqBGjRpK+ZgxYwYuXboES0tLDBo0CEZGRnj+/DnOnj0Le3t7NGzYEBMmTICvry+CgoLg5uYm7m9F2b+zsrIwefJkBAUFoUmTJhg7dizevHmDU6dOYcGCBQgPD8eCBQtUlrtz5w42btwIOzs7jBgxAjExMTh9+jQmTpwIHx8fNG7cuMjvh1S/K+fPnxev2Pfp0weWlpa4ffs2du3ahbNnz8LLywvW1tbi/BEREXB3d0dSUhKcnZ3RvHlzPHv2DLNnz0bXrl3VxnrhwgXMnTsXcrkcPXr0gLW1NaKjo+Hj4wN/f3/s2bNH7ee9qHbv3o0ff/wRhoaG6Nu3L2rVqoWrV69i/fr1OHfuHLy8vFS+e4vK0dEREyZMwLZt29CsWTP06tVLnJY/5q1btyIgIAD9+/eHs7MzQkJCsH//fly9ehX79u1DzZo1yzyGgkRHR2PUqFGwtbXFxx9/jEePHuHcuXN49OgR1q5dizFjxkAmk2HYsGF49OgR/P39MW3aNBw7dkypx0dxjyseP36M0aNHIzk5Gd27d4dMJkNUVBQ8PDwKvef6+fPnGDFiBOrXr48hQ4YgOTkZx48fx6xZs7B582a1J2nz5sTDwwNbt24FAHzyySdKuSypxMREjBo1ClFRUbC3t4e9vT3i4uKwaNEidO7cWe0yxT1uU8Rft25dXL58GYIgVIzugwJRBRQYGCjIZDJBJpMJJ0+eFNvlcrkwadIkQSaTCQ4ODgVOu3v3rtielZUl9OjRQ2jTpo0QGhqqtJ1Hjx4JdnZ2wuDBg5Xao6OjhZycHJW4/vrrL0EmkwlHjhxRah83bpwgk8kENzc34fXr12J7enq60KtXL6FZs2ZCbGys0jKdOnUS2rdvX2AOvvrqK0Emkym1yeVywc3NTZDJZMKQIUOEnTt3CmFhYUJWVlaB6xEEQZDJZEK7du2ElStXFvifIt/qrF69WpDJZMLmzZvFtr59+wotWrRQeV2CIAgHDhwQZDKZ8Oeff6rEv3DhQkEmkwmffPJJoTELgiCsWbNGkMlkwu7du1Wmff7554JMJhOCgoLEtpSUFCExMVFl3vv37wt2dnbCpEmTlNoV+9nKlSuV2rt37y50795dbUyKXAUGBoptjx49Elq2bCn06dNHiIuLU5rfx8dHkMlkws8//6zUrshR3vXkdebMGUEmkwn/93//p3Z6fo8ePRJkMpkwffp0tdPj4+OFtLQ0lfZLly4JzZo1E77//nul9okTJwoymUx48uSJUntubq7g4uIi2NnZCenp6WK74n3dsmWL0vypqanC0KFDhVatWintK4r9u0uXLkJkZKRKXG/fvhVevnyp0v7y5Uuhc+fOQu/evZXar127JshkMqF3795CSkqK0nrGjBkjyGQylfd0+fLlgkwmE5YuXSrk5uYqLTN16lRBJpMJd+7cUYlBHZlMJowbN06pTfEae/XqpbRfREVFCS1bthTs7e0FV1dXtdMGDRqktC7F/iKTyYRz584pTduyZYsgk8lU9u+XL18Kb9++VYl1//79gkwmE9auXavU/scffwgymUyYNWuWynJv374VEhISxL/VfQ6KYu3ateJ+mp2dLbbHxcUJ3bt3F2QymXD9+nWxPe9vwYEDB5TW5eXlJchkMmHRokVF2raUvytpaWmCo6Oj0Lx5cyEkJERpO+vWrRNkMpkwefJkpfZPP/1U7WdE8VnP/xoTExMFe3t7oWPHjsLTp0+Vlrl69arQvHlzYcaMGUrthX135RcdHS20bNlSaN++vcrnfNGiRYJMJhN++OGHIq9f3T4RFRUlyGQy4auvvip0mZYtWyrlVxAEYcmSJYJMJlP5bpI6hoIolpPJZMI///yjNO0///mPuL8UNO306dNK7cU9rpgwYYIgk8mEXbt2KbVfuHBB7f6SN15PT0+lZfz9/QWZTCZMmTJFqV3xvZL/s1VYjgv63SxsWUVOlixZotR+69YtoUWLFirrK8lxm8KsWbMEmUwmPHz4UO308saug1ShOTo6ok+fPuLfWlpa4lneZs2aFTgtbzcxPz8/REdHY/z48SpXjz788EOMHDkS9+/fx8OHD8V2Kysrtfc5TZgwAQBw6dIltfEuXLhQvOoEAIaGhhg0aBDkcjnu3LkjtmdlZSE+Ph7m5ubvzUFeWlpaWLlyJezt7REWFobFixdjyJAhaNeuHUaNGoVt27YhMzNT7bLp6elYtWpVgf8VRBAE7N+/H7q6ukpn2N3c3JCTk1PosLDBwcHw9PSEp6cnfvnlFwwZMgSHDx9G9erV8dlnn7339Q4ZMgRaWloq3bjS0tJw9uxZWFtbw8HBQWw3NjZWe+bT1tYWTk5OuHr1KrKzs9+73eLavXs3srOz8e2336q8p0OGDEGLFi1w7NixYq1Tcd9eYaM75qWYr6D7/WrXrg0jIyOV9k6dOqFJkyYq+7TialX+3F+9ehUvXrxA3759xSuqiYmJOHbsGNq2bat0BhQAatSoAQ8PD2RlZeH06dMq258yZQrq16+v0q6vr692JM66deuib9++iIiIQExMjNiu6IIyc+ZMpSsr+vr6avc1uVwOLy8vWFhY4IsvvlA685x3maNHj6osW1wzZ85U2i+sra1hb2+P1NRUzJgxQ2Va+/bt8ejRI+Tk5Kisq2PHjipXOMeNGwcbGxsEBAQoPSaibt260NfXV1nHsGHDUKNGDaX3PDc3F7t27UK1atWwaNEileX09fVRq1at4r/4fA4cOAAtLS189dVXSmfvzc3NMXPmTHGe/Nq3b49hw4YptQ0fPhy6urq4detWsWKQ4nfF19cXSUlJ6N+/v8p9lJMmTYKVlRUuXrwovh8vX77EpUuXYG1tLXafVujVq5faqwWHDh1Camoq5s6dq3SlUvEaevTogQsXLhSre3Fehw8fRnZ2NsaNG4dGjRopTVuwYAGMjIxw6NChMvnOzG/w4MFo0aKFUtucOXNgbGwsxqkp1tbWKt2khwwZAgAwNTVVmTZ48GAAUOmuXpzjihcvXiAwMBANGjSAu7u70vwuLi6F3n9kZWUlfpYUunbtCktLy2J/VqSQnZ2NI0eOwMjISOmebQBo3bq12iv3JTluU1B8n+b9fdAkdh2kCq158+YqbYrRcQqblvdg4/r16wCAqKgotX2Knz59CuDdfSdNmzYF8O6LwcvLC8eOHcPjx4+RlpamNGR6Qf3v1XVLq1evHgAo3aejuBegJF0yrK2tsWvXLoSHh+PKlSu4ffs2bt68ievXr+P69evYt28ftm/frlTwAe8Ouvz9/Qtcb0FDuwcEBOD58+fo3r07ateuLbYPGTIEy5cvx759+zBt2jS1l+iDg4MRHBwMANDT04OFhQWGDRuGKVOmFGnwAEtLSzg5OSEwMBBRUVHiAfmpU6fw5s0bDB06VGW7wcHB2Lp1K27cuIHXr1+r/EC/fv1a8hGWbty4AQAIDAzEzZs3VaZnZWUhMTERr1+/LnIXGFNTUwDv4i2KouxTvr6+2L17N+7evYukpCTk5uaK0/J3q+vduzcWL16MI0eOKA0Vr67b4O3bt5Gbmwu5XK72M6a4v+XJkycq09q0aVNgvOHh4di4cSNCQkIQGxur8l6+evVK7O4YFhYGALC3t1dZj52dnUpX36dPnyIpKQkNGzbEmjVrVJZRFDmK74fSyH8ACfyvIFY3zcLCArm5uUhISFApNjt06KAyv46ODuzt7REZGYl79+6JywiCAB8fH3h7e+PBgwdISUmBXC4Xl8v7PfnkyROkpqaW6QhkaWlpePbsGT744AOVA3sAYpeme/fuqUxT992qp6eH2rVrIyUlpVhxSPG7oojRyclJZX5dXV106NABz58/R1hYGOrWrSvOr+jCmZ+joyOCgoKU2hTfK/fu3VP7uYqPj4dcLkdERESJukQrYlLXlczU1BQtWrTAtWvXEBERIf42lhV1haaxsTGaN2+OoKAgPH36FDKZrExjKEizZs1UBn1SfH5tbW1VpqnbX4DiHVcovs/s7OzUDjhlb2+Py5cvFxivun3sgw8+EPep8vTkyRO8efMGDg4OarsXOzo6qtyrVZLjNgXFsU9RfzvLGgstqtDUfSgVXyCFTct7JlhR4Lzv2QoZGRniv+fNmwdfX180bNgQvXv3hrm5uXggumrVKrWDWwDqD3IVMeU9wKlWrRoA4O3bt4XGVJj8z726ffs2vvrqKzx48ACrVq3Cf/7znxKvO699+/YBeHcFK6+6deuiU6dOCAgIQGBgID766COVZWfMmKH2fovicHNzQ2BgIHx8fMSzYT4+PtDS0lI62AfeFWDz589HtWrV0KVLF1hbW6N69erQ0tLC2bNncf/+/QLfu9JQ7GP//PNPofNlZGQUudBSXJlU7Cvv8759asuWLVi6dCnMzMzQuXNn1KtXT1zm4MGDeP78udL81atXR58+feDt7Y2goCA4OTkhIyMDp0+fhpWVldKBkeL13759u9BBTvJ+xhQKuqp7/fp1fPLJJ5DL5ejcuTNcXV1haGgIbW1tBAUFISgoSOm9VNy4n/dkgIKOjo7KiQdFYRoREVHoFd309PQCpxVV3vugFBSFX2HT1J3FLyhfiva8AxgsWbIE27dvxwcffAAXFxelK1xbt25VWr+iWCnO8/yKS3HlpaDXoDhAVTcIQ0EnEHR1dZW+W4tCit8VRYwFXUFWtCvyWtj+CajPieJzpRiIqCDqPldFoYipoPcj/2soS+/Li7p9orxIsb8AxTuueN/+UlA7IO1nRQql2feLc9ymUNzfzrLGQov+9RRfhH/++ScGDBjw3vlv374NX19fdOnSBevXr1c6MxQbG1voQVlRmZiYQE9Pr9ij0RWmdevW+P777zFx4kTJHiKakJCAc+fOAQDmzp1b4Hx79+5VW2hJQXFl5dChQ5gzZw6eP3+Oa9euwd7eXqXLmaenJ/T19eHt7a1yxrw4Z/K0tLQK7Kqi7qBDcbAcEBBQ5KH630dRCBS1u5ZiPnX7VE5ODlatWoU6derg0KFDKj94BXWPc3Nzg7e3N3x8fODk5ITTp08jIyMDEydOVLqSqPiMubu746effipSvAoF3ay8du1avH37Fjt37lTqHgoAP/zwg8rZf8V7kJCQoDJITG5uLpKSkpSKCEXMXbp0eW+BXJGoG4Utb7vidSUkJGDnzp2wtbXF7t27lXIil8uxceNGpeUVB2f5z8JLSfEeFfQaFGf01RWfFY0iz3FxcWqnK9oV8+V9X9RRlxPFMnv27CmTZw4q1h8fH6/2ilX+1wAU/7uxqN6Xl/KIoSwV97gi7/eZOgW1lwfFFTZ1XZsBqAxeVZp9v6jHbXkpfjsLK0bLE+/Ron89RdckxaXo91EMk9ytWzeVy++KbnBSkMlkiI2NLXH/enXU3YNTGt7e3sjOzkbr1q3x8ccfq/3P2NgYZ86cKXD449IyNDREnz59EBUVheDgYPj4+EAQBJWrWcC7YXY//PBDlSIrIyMDd+/eLfI2TU1NkZCQoPbHPO+9dgpt27YFULxi7n0U3ezUdWVSp2nTptDR0VHb1e3169dITU1Fu3btVH58Xr16pTK8u0KHDh1gZWWFU6dOITMzU+zekT/3rVu3hpaWFm7evKnUFaY0nj17BjMzM5UiSy6Xqx3SW5GnkJAQlWk3btxQOSho3LgxatSogbCwsFJdWS5v6oa2z83NFV+3oitiVFQU5HI5OnXqpFJ43rlzR+VezsaNG8PExATh4eEFdo3OS3GwVZwz5DVq1ICNjQ1evXolDhWfl+IEkbrulBWNYn/LX/AD7w5AFb8Vitei+H9ISIhSl10FdetR/HaVVXcvxWtQd2IuJSUFYWFhqF69utL3aXG/GxW/oepec17qXn9qamq5xlCWintcoXhvbty4ofYzpu57Tkra2toF5ktRRKl7vMCzZ89Urj42btwY1atXR1hYmNork4Xt+0U9bsvryZMn0NbW1lhX0/xYaNG/Xs+ePWFlZQUvLy+1z32Sy+VKPzSKIV/zH9A8f/4cf/zxh2RxOTk5qQyS8T6KZw6pK85ycnLEs9Tq7lMpCcWzKBYvXowlS5ao/W/w4MHIzs7GoUOHJNmmOooD+0OHDuHw4cOoVq0a+vXrpzKflZUVIiIilA4Uc3JysHTp0mL1127durXagT68vb3VHuSPHTsWurq6WLp0qdrnp7x586bYB0uKe73U3QOijrGxMZo1a6a2e2Tt2rVRrVo13L17V6mrxZs3b7Bo0aICz0wqumemp6dj27ZtCAoKQvv27dGgQQOl+czNzTFgwADcv38fq1atUntg8ODBg2KdhbWyskJycjIePHig1P7333+rvQFasY/8/fffSj/mWVlZWL58ucr8urq6GDt2LBISEvDzzz+r7VIaFRVVYBGqKYGBgSrPw9mxYwciIyPRuXNn8aqd4nssNDRU6YDp9evXaq866ujoYMyYMcjMzMTixYtV8qG4z1BB0RWzqIO1KAwfPhyCIOC3335TiisxMVG8Vy7/oBcVUa9evWBmZoZjx46p3Je5detWREdHo0uXLuL78cEHH6Bz586Ijo7Gjh07lOY/e/as2oNNxaAlq1atUnuiKDs7u1Qn/wYPHgw9PT1x/8lrxYoVSEtLE+dRKO53o4mJCbS0tN77zK/Dhw+r3Jvn6emJ1NRUDBo0qFxiKEvFPa6wtLSEo6Mjnj17hj179ihN8/f3L/D+LKmYmpri9evXak9CKU5S+fr6Kn2nZ2Zm4pdfflGZX09PD4MGDUJ6errK/Va3b9/GkSNHVJYp7nGbQlZWFsLCwtC8efMSP5ZAauw6SP96+vr68PT0xOTJkzFlyhR06NABtra20NPTQ0xMjDhoguLektatW6Ndu3Y4deoURo8ejXbt2iE2NhYXLlwQfyil4Orqik2bNuHSpUuFPtcir7S0NPzyyy/47bff0L59e8hkMlSvXh3x8fG4ePEiYmNjYWNjg9mzZ5c6vqtXryIiIgItWrRAy5YtC5zv448/xs6dO7Fv3z58+umnpd6uOk5OTrCyssLBgweRnZ2NgQMHqu1eNGHCBCxevBhubm7o06cPtLS0cPXqVcTHx6u92bwg48ePh7e3N3788UdcuXIF9erVQ1hYGG7cuIHu3burHOg2adIEixcvxqJFi9CvXz84OzujQYMGyMzMRExMjFigFLWLmlwux5UrV9CoUaNinZXr3bs37t69i6tXryo9l0dbWxvjxo3Dxo0bMXjwYPTo0QOZmZm4dOkSdHV10bx5c/Hm6/yGDh2K1atXY+XKlZDL5Sr36iksWrQIT58+xapVq3D8+HG0b98eNWvWxMuXL/HgwQOEh4djz549Re7OMWHCBAQEBIgPyDYyMsL169dx//59te+Bo6Mj3N3dsWfPHgwYMAC9e/cWn6NlbGwMCwsLlW6KHh4euHfvHvbt24dLly7ByckJ5ubmiI+Px5MnT3Dr1i388ccfSs9C0rQePXrAw8MDvXr1QoMGDRAWFgZ/f3+YmZnhhx9+EOerU6cO+vbti5MnT8LNzQ2dO3dGUlISLl68CGtra7UDXsyePRs3b97E2bNn0bdvX7i4uMDIyAgvXrzApUuX8OWXX4pFkJOTE7S0tPDnn3/i4cOHMDY2homJicqIevlNmjQJ/v7+8PX1xdChQ9G1a1fxOVoJCQmYMmWKyih+FZGRkRGWLFmC+fPnY9y4cejbty/q1auHO3fu4NKlS6hTpw5+/PFHpWV++OEHuLu749dff8WlS5fQrFkzPHv2DGfPnlW7T9eqVQvLly/HvHnz8PHHH4sjhObm5uLFixcIDg5GzZo133sfS0Gsra3xzTff4KeffoKbmxv69euHmjVr4urVq7h58yYaN26s8hy54n43GhkZoXXr1rh27Rq++OILNGjQANra2hgyZIjSc6ycnZ3Fz3qdOnUQEhKCkJAQ1K9fX+U+37KKoSyV5Lhi0aJFGD16NBYvXgw/Pz/x4eenT59Gz5494evrq3agDCl07NhR6cHdenp66NChAzp06AA9PT1MmDABa9aswdChQ+Hq6oqcnBxcvnwZFhYWar9bFixYgCtXrmDr1q24c+eO+Byt48ePw9nZWbxFQaG4x20KipGF844cqmkstKhKaNmyJQ4fPozNmzfjwoUL2LdvH3R0dGBhYaEy1K+Ojg7WrFmDFStWwM/PD3fu3IGVlRWmTJmCKVOmlPhHLb/27dvD1tYWhw8fxoIFC4r0hfnhhx9i1apVCAgIwM2bN3H06FGkpKTA0NAQjRo1wpgxYzB+/HhJ7nFQ3ID98ccfFzpfixYt0KJFC9y7dw/BwcEqXb2koKWlhcGDB+Pvv/8GoNp1TWHMmDHQ09PDtm3bcODAARgZGaFjx474+++/sXr16iJvr0mTJti8eTOWL1+O8+fPQ0dHBw4ODti9ezfOnDmj8kMOvMtTixYtsGnTJly7dg3+/v4wMjJC3bp18fHHH4tD/hZFYGAgXr16hW+++abIyyhiWLVqFXx8fFQegLpgwQKYmprC29sbXl5eMDMzQ/fu3TF//nzMmzevwHXa2NjA3t4eISEhMDAwUHslEXh31tjLy0scVevEiRPIzs5GnTp18OGHH4oP9SwqFxcXrF69GmvXrsWxY8egr6+Pdu3aYc+ePTh79qza9+DHH39E48aNsXv3buzevRtmZmZwdXXFZ599BmdnZ9jY2CjNr6+vj/Xr18Pb2xuHDh2Cr68v3rx5g9q1a8PGxgZfffVVmd17WFKurq5wd3fH33//DT8/P+jp6aFPnz74/PPPVa40Ll26FPXr18eJEyewY8cO1KlTB4MHD4aHhwcGDhyosm59fX1s3LgRu3fvho+Pj9hN18LCAq6urkpXyps0aYKlS5di06ZN2LFjB7KysmBlZfXeQktfXx+bN2/Gpk2bcOzYMWzfvh26urpo1qwZvvvuu2Lfj6FJvXr1wq5du7B27Vr4+/sjPT0d5ubmGDVqFGbNmqUysEjDhg2xd+9e/PHHH7h8+TKCgoJga2uL1atXIzExUe0+7ezsDB8fH/zzzz/iMgYGBqhbty5cXV1Lna+xY8eiQYMG2LRpE06ePInMzExYWlpiypQpmD59uspVgZJ8N/72229YunQpLly4gNTUVAiCAHt7e6Ui55NPPoGrqyu2bNmC48ePw8jICMOHD8dnn32mcp9qWcVQlkpyXNGkSRPs3r0by5cvR2BgIAIDA2Fra4tVq1bh8ePH8PX1LbP7GWfNmoWUlBScP39e7O7q4eEhjno6d+5cVK9eHXv37sXevXthbm6O/v37Y86cOWr3yVq1asHLywt//vknzp8/jzt37qBRo0b48ccfYWVlpVJoAcU7blM4dOgQ9PT03nvcUq409QAvIvrfw2x9fX1Vpql7YDH9exT2wOK5c+cKjo6OSg/eLapvv/1WaNOmjRAfHy9FmP8KT58+FWQymbBgwQJNh1JiBT1YlKgyK+mDr6u6zz77TJDJZMLjx481HUqFkZCQILRt21b49ttvNR2KEt6jRaRBgwcPRqtWrbBq1SrJBhGgyu3+/fs4deqU+LDO4po3bx60tbWxbt26MoiuYouLi1P5HGVkZODXX38F8O4KBBFRZSCXy9WOyHflyhWcOHECTZo0QePGjTUQWcW0fv16aGlpFdpDQxPYdZBIg7S0tPDLL7/g7NmziIuLK7MHhVLlERcXh3nz5mHUqFElWt7CwgLLli3DkydPIAhCgcOn/xtt3boVx48fR4cOHVCnTh3Ex8fjypUrePnyJZydnQvs9khEVNFkZ2fDxcUFHTt2RKNGjaCjo4NHjx7h0qVL0NPTU7onk94N+rRs2bIKdxzFQotIw5o3b17kIbzp369r164q91cVV1W9ctO5c2fcv38fly5dQlJSEnR1ddGoUSOMHz8en3zySZUqOomoctPV1cWoUaMQGBiIGzduIDMzEzVr1kTfvn0xbdq0SvEYhPI0depUTYeglpbA/kpEFdLZs2cRFhaGOXPmaDoUKgNhYWE4e/Ys3NzcKtSodkRERCQNFlpEREREREQS42AYREREREREEmOhRUREREREJDEWWkRERERERBJjoUVERERERCQxFlpEREREREQSY6FFREREREQkMRZaREREREREEmOhRUREREREJDEWWkRERERERBL7fwnWDnc9WbpBAAAAAElFTkSuQmCC\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "# ── SHAP bar summary ──────────────────────────────────────────────────────────\n",
        "plt.figure(figsize=(9, 6))\n",
        "shap.summary_plot(shap_values, X_sample, plot_type='bar', max_display=15, show=False)\n",
        "plt.title('Mean |SHAP| – Global Feature Importance', fontweight='bold')\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 94,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 435
        },
        "id": "xEGBHqqUlCK9",
        "outputId": "5a68a1cf-4b8b-4a27-dddf-d715c90cfc84"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 880x440 with 3 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "# ── SHAP waterfall – one local explanation (first test instance) ──────────────\n",
        "shap_exp = explainer(X_sample.iloc[:1])\n",
        "plt.figure(figsize=(9, 5))\n",
        "shap.waterfall_plot(shap_exp[0], max_display=12, show=False)\n",
        "plt.title('SHAP Waterfall – Single Prediction Explanation', fontweight='bold')\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 95,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 435
        },
        "id": "Dqsoee_slCK-",
        "outputId": "2e41789f-a9fa-4390-af04-2a48510eed76"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1210x440 with 3 Axes>"
            ],
            "image/png": 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ouLg4jB07FvHx8di7dy82b94MAPjiiy/QpUsXjB8/HoAzQGnTpg369OmDli1bIiYmBoIgIDs7G+vXr0dRURGKioowe/ZsfPLJJwCAJ598En/99Re++eYbcRzuU7sC0c9v165d6NWrF6644gpYrVao1c6PBb689tavXy+GUTqdDhMnTkSrVq1QWFiIc+fOVXtt1Wfnzp3ivzt06FDt+efm5nr87Hfr1q1apV1DZWVl1TqFLD4+HpMnT27U/gOtIddjX86x2WzGU0895RFGjR07Fu3bt8eWLVvE10Nd+vTpI/779OnTyMnJqbHql4jCBwMpIqIAO3r0KObPnw/AOaVh1apVHo+7/8X4iy++gMViwd69e3H69GkYjUYkJCTgyiuvFPslXbhwARkZGbWuUJOcnIwVK1bUGDC5B1L9+vWrcXpNXR555BEIgoDMzEwcPXoUxcXFUKvVuPLKK5GRkYHy8nIAzr98BiuQqhrqZGdnA3BWR33++efi/WPHjsW7774r3p44cSKuv/56AMDJkyexYcOGWptYv/LKK+KHzbvvvhvXXnut2Ads2bJlYiD1xRdfiB8A2rVrhx9++EGsLrrvvvtw3XXX4fz58zCbzVi4cCH+/e9/13i8a6+9FnPmzIFCocCMGTMwdOhQcb8ZGRniOL/99lvxwz7gnJJzxRVXAHAGdWPGjKlxmfRjx455/PX/+eefx6233ire7tmzJ1566SUAzoqvf/zjHzVWBygUCixcuBA9evQA4Pwg6vrwcuLECbEnTWlpKZYsWSJ+XUJCAlauXOkR+JSXl6O4uBiAs9LNPWS877778M9//lO8PWzYMLHXy/bt27F3715ceumlNX4v6+IKJKr2kAKc4Z43f/FfuXKlR2XUs88+i2nTpgEAHnzwQUyZMkUMpb777js8+uij6N+/P/r374/NmzeLgVRN091KSko8GjW//fbb1UKy7OzsOqchhdL8+fPFn0+FQoHFixeLFSwzZszAddddJ66g9vnnn9caSA0dOhQLFiwQpzw+++yzYlB3/PhxpKWlYciQIQ0enysMqul4zZs3x8qVK8UwSqlUYunSpbjkkkvE7R555BGsX78eAPDpp5+K14iIiAhs3LgRxcXF2LNnD86fPw+TyYT27dtjwIAB4mtv27ZtsNlsUKvVuPvuu7Fjxw6PQKrq1C5/u/rqqzFnzhyPabm+vvbMZrO4TWpqKl588UWPYzkcjgat0PjXX3+J/27VqlW1x13XeZeqFa5HjhzBDTfcUO3rfFnNMjIyEh9++KHkgxNvr8e+nuONGzd6VMDdf//9eOyxxwAAM2fOxPjx4+ud1ti6dWuP26dPn5b895WIAouBFBFRgO3fvx/79++v8bH+/ft7TFVZsmQJ3n///WqNg6uqOn3E3dSpUwPWIHX79u14/vnnPT4s1KTqh4VAEgTB47brQ+uJEyc8goKffvrJo99IVbt3764xkNJoNB4fbGJiYjBy5EisWLECgHO58YKCArRo0cJj+stff/1V51/s//zzz1ofmzJlivg84uLi0KxZM/G5uEIbwFmR5dKiRQsxjAKcgVj//v2xY8eOavt3rz4AnNPCaptm6XA4kJ6eXuNUm759+4offoDq4WBJSQmioqKQnp7uEYxNnz69WrCi1+vFfiV79uzx2P6zzz7DZ599VuP4AOe58yWQqi2Q0Gg0ePXVV72aCrh7926P2+49Z9RqNcaPHy8GUjabDXv37vV60YCYmBh069ZN7AN0/fXXo3fv3mjXrh06deqE/v37e3z/6+MKxmsSHR1dY4+oxnD/3vTs2dNjOlViYiKGDRsmBjoHDx5EeXl5jT1rxo0bJ74eAGcFk3vl2L59+3wKpOrj/np2OBx1TpU+ceIELly4gGbNmsFiseCVV17B999/D5vNVuvXmM1mXLhwwatKvECYOXNmtR5xvr72Bg4cCKVSCYfDgT/++ENcrbV9+/bo2rUrhgwZgrZt23o9tsLCQvHf3vw+c//58JV7U3Oj0YgtW7bgwIEDKCsrw5133onPPvssID9n/uLt9djXc+z++wZwvi5dtFotxowZ4zF9vCZVz6X7eSai8MRAiogoiNRqNWJjY5GSkoLRo0d7NI3+7bff8PLLL3u1H/e/RlcVqJ4kubm5mDlzpljRUJeq/ZMCyVU55uL6a6urgslbBQUFNd4fFxdX7UNb1aCiuLgYLVq0aNAxazse4Kxyc+c+PdM9gHMPLlu0aFFtP7UFKv763tQ1TgBidYx7iAag3kbS/hpfQ0RERKB169YYPHgwpk6d6vXryP25RUREVOvlVNPPSkO8++67ePzxx3Ho0CEUFRXh999/93i8Z8+e+OKLL9C8efN69+VeIVlVcnKy3wMp9+daU+jifp8gCCguLq4xkKr6s131tqvXUENVbR5dVUN/DgsLC9GsWTO8++67+Pbbb736mrqu5d6oGsg35Npb08+4r6+9Xr164bnnnsP777+PkpISHD9+3KNaRqVS4e677/aoxKmL+/Oq+hwBoGXLlh63T5w44XE7ISFBXO3u008/9ep1V7Wp+cyZM3H99dfj9OnTMJvNeOWVV/Djjz96Nf7G8PWcens99vUcV32dVb3meBPgu1f0AjWfWyIKLwykiIgCrOqqOLVxr96JiIjAe++9h0GDBiEiIgLHjh2r86/z7mprQN1YmzZt8gijHn/8cdx0003idKHLLrssJH/trNrw2bXiVdW/xF511VVITU2tdT+19XMqKiqC3W73CKWqNq929aGJjY0V37xfcsklmDhxYq3Hq2t1OFcvF5fa/vrv3lelplCmtqbcVVcVnDFjRp3TJvr161fj/VV7btU2zqrHO3v2bK3Hqmn7CRMmVFu5yl3VlSe9VV8g4Q33sV68eBEXL170CKWqnoOqz60+l1xyCX744QecOHECBw8exOnTp3H8+HFs3LgR5eXlOHDgAGbPnl1rn69Qcn89VG12XfU+hUJRYz8noPrPdtXbgeivBHieK51Oh7///e91bu/6gO4eWnTp0gVvv/02OnXqBK1Wi6VLl4rTYX2lUCjED/KuadIup0+f9no/NTXCb8xrb+rUqZg8eTIyMjJw7Ngx/PXXX0hPT8eff/4Ju92Ozz77DMOHD6/zOuziHnbUFCYlJiaiS5cuYh+pzMxM7N+/X5wq3qxZMzFcWrp0aYODYMAZ6HTv3l38nh49ehSlpaV+/3mr2v/MPaQ0Go1eL67g6/XY23Nc9fXpCmBdvBln1fNQ0x9SiCi8MJAiIpII90bnbdq0wZVXXinertp3yldqtVqcQmIymXweHwCPMOr3338PehglCAKWLl3q0XMlNjZWbDzbsWNHj9UMi4qKMG3atGp/NXYtBz5y5Mgaj2O1WrFmzRqxP0xJSYnYVBlw9sRw/WV4wIAB+OWXXwA4P2yPHj26Ws8Mh8OB//3vf2Kz4sbo3bu3uCpjQUEB/vjjD3Ha3pkzZ2qdFui+xDjg/EBUUz+x/Px8pKeno3v37o0aZ79+/aDRaMRpIosXL8akSZM8PoxYLBYUFRUhMTERffv29fhZvXjxIu66665qH7BKS0uxZcsWDBo0qFHja4wBAwZ4rMz3/fffiz2kbDabx9L1arXaY2qhe/BY2+vxwIED6NGjBzp16uTRJ+eVV14Re+HUNiW4KtfUv2Bxfz0cOHAAmZmZ4rS9vLw8j2qvHj161Bqmr1q1ymPa3sqVKz0ed2+U7E/u59ZsNqNjx441XieOHDmCkpIS8XroXoEyePBg8Tnb7fY6pw1XDaKrhk0uMTEx4gf7ffv2QRAEKBQKHD582OPa5AtfX3u5ubkAnEHRwIEDxR6HgiAgNTVVrObct2+fV4GU+/Xx3LlzNW5z55134tlnnxVvP/bYY/jss8/qXF20IaxWKw4dOuRxX11TMH1VNeDas2eP2Kvs008/9XsVka/nuGrwv2rVKrGHlMViqXEF1arOnz/vcbt9+/Y+Pw8ikgcGUkREEtGpUyexqfKRI0fwyCOPICUlxWM1p8ZKSkoSG8uuXLkSWq0W0dHRaNasWZ3VPK7xubv33ntx1VVX4dy5c34LzOpiNBoxf/582O125Obm4o8//vCYrqdSqfDWW2+Jf/11hSxvv/02ACA9PR3XX389rr76asTFxaG4uBhHjhzBrl27YDKZ6lwS/LnnnsPu3bvFVfbcP3Decsst4r/vuusu/Prrr3A4HCguLsb48eMxatQotG7dGuXl5Th58iR27tyJgoICLFq0qEE9VWoyefJkfPvtt+IHlocffthjlb2aGpoDzhWphg8fLi67/eWXX2Lfvn0YOHAgDAYD8vLysH//frF5/rXXXtuocUZHR2Pq1KlYuHAhAOeH19GjR2PUqFFISkpCdnY2tmzZgkcffRQTJ04Ug0VX493169djwoQJuOKKKxAdHY3CwkIcPHgQ6enpSExMFJvTh8KECRPw8ccfi1U7r732Gvbv34/k5GSPVfYA5/lyr05wn3Z04MABvPLKK2ID56lTp0Kv1+P2229HTEwMUlNTkZiYiNjYWGRnZ3uEMg2tugqWO++8U3w9CIKAadOmYcKECdBqtfjxxx89Ki7vueeeWvezbds2TJs2DYMHD8bBgwc9QpeOHTsGLJCcMGECPvnkE7Hy45FHHsHVV18tVpNkZWUhPT0dJ0+exKxZs8QQpmPHjuLKmMuXLwfgPEcbN25EZmZmrcerOg3tvffew6FDh6DRaNCjRw+x+rNPnz5imJeWloabb74ZiYmJ2LZtW62veW/5+tr7888/8eijj6Jv377o0qULEhISoFarsXv3bo+pxd7+rLqHVqdPn66xMmnChAnYsmWL2Ifs9OnTuP7663HllVciJSUFKpUK586d87rCyPU7BnCu4LhlyxaPirNOnToFZAGBXr16if23AODf//43Nm/eLP5BwN98PccjR45EfHy8+P389NNPcfbsWXTo0AGbN2+ut6E5AI/rYbt27djQnIgYSBERScWMGTPwww8/iG/e169fL77RnjRpkkcTX1+NGjVKfMNdWFiIjz/+GIBzWkl9gdTIkSPRs2dPsSJn3759YpPTK664AseOHQtoM/Pi4uJae+C0bNkSb775ZrWGs/fccw9Onz4tfig8ffo0FixY0KDjxsfHo3Xr1tWmBgLOCoq77rpLvN2vXz+89NJL+Pe//w2r1Yri4mKve8n4olevXpg5cyY++ugjAM6/dLuqZqKjoz3OV1VvvfUW7r33XvEc7tq1y6OJs789/vjjyM3NFf+KXt/35plnnsH58+fFMPbQoUPVqhWkICoqCh9//DEeeOABFBYWwuFweFRFuVxxxRV45plnPO4bNWqU2Bzf4XB4rP41YcIEcVpndnY21qxZU+PxVSpVnWFOKPXv3x8vvvgiXn75ZVitVpSUlIirfrkoFArMnDmz1hUuAed0202bNlVrxh8REYG33nqr2pQnf3Gd2wcffBB5eXmwWq1Yt24d1q1bV+fXzZo1C4888ggAZ2WVa4VJjUaDcePG1RrgJycno3fv3uJr0v1nfurUqWIgdffdd2Pr1q1igOH6kG8wGDB48OAaFzJoCF9fe4IgID09vdYQpUOHDjUujlCTvn37Ijo6GqWlpRAEAX/++SdGjBjhsY1SqcTbb7+NVq1a4auvvoIgCLBardiwYQM2bNhQ437rapBe1+8YvV6P//u///Nq7A2VlJSEcePGiSGzxWIRx9+7d29x4Qx/8uUc6/V6vP7663jwwQfF4NNV8adQKDBo0CCkpaXVuQ/3ql1vF3cgInljIEVEJBFt27bFsmXL8M477yAtLQ12ux2dOnXC9OnTkZqa6pdA6tFHH4VCocDPP/+MnJycBk0/UKvV+PLLL/HOO++IS5q3bNkSY8eOxUMPPYRRo0Y1enz1USgUUKvViIqKQkJCAjp37oyRI0di1KhR1abiubZ/5ZVXMHbsWCxfvhx79uxBXl4eBEFAXFwcOnfujNTU1DorgFxLZ3/00UdYu3YtcnNzkZiYiBtuuAEPPPBAteNOnjwZAwYMwNdff43t27cjKysLZrMZ0dHRaNeuHfr27YuRI0d6NW3FG3//+9/Rvn17fPXVVzh27BgiIiIwZMgQPProo/j0009rDaSaNWuGb775BqtWrcLatWuRmZmJoqIiqFQqJCYmolu3bhgyZIjXHyDro9Fo8N5772H8+PFYsWIFMjIykJ+fD5VKhfj4ePTt29djSohOp8Onn36KX375BT/88AP279+PwsJCKBQKxMfH45JLLsGgQYOC8nNXn0svvRQ//fQTFi9ejC1btuDUqVMwm82IjY1Fjx49MG7cOFx//fXVpsSMGDECr7zyCpYsWYITJ07U2Lz4hRdewK5du3DgwAHk5eWhqKgISqVSnNo4ffr0gE1Z84dbbrkF/fr1w5IlS7Bjxw5kZ2fDbrcjMTER/fr1w2233VZtCmlVd955JyZOnIj58+fj8OHDUKvVGDRoEP7xj3/U2fvGH/r06YMff/wRy5Ytw+bNm3HixAmUlZVBr9cjOTkZPXv2xLBhw3DVVVeJX3Pdddfho48+wscff4zDhw9Dq9Xi0ksvxcMPP4yTJ0/WWVE6d+5cvPnmm9i+fTuKioqqNYEGnH3yPv74Y8ydOxeHDx+GXq/H4MGD8eijj+Lnn39udCDly2uvX79++Oc//4k9e/bg+PHjKCwsRFlZGSIiItCuXTuMGDECd9xxB6Kiorwag1arxfjx48WQdt26ddUCKdd2zzzzDKZMmYLly5dj165dOHXqFIxGI9RqNZo1a4aOHTvi0ksvxYgRI2rth1eVUqmEwWBAmzZtMGjQIEybNi2g08teeuklJCQkYM2aNcjPz0dSUhJuvPFG3H///XWGtb7y9fo6fPhwLF26FB9++KEYLvXs2RP3338/8vLy6gykLl68iC1btoi3XdPriSi8KQQub0BEROTh6aefFv9anZyc3Oi+LETkvR07dmD69Oni7UWLFmHw4MEhHBGFwokTJzB27Fg4HA5ER0fjjz/+qHMxCJK2NWvW4PHHHwcA8Y82RESBqXEmIiIiIiLyUadOncTFJEpLS/Gf//wntAOiRvnyyy/Ff7uaoRMRMZAiIiIiIiLJefTRR8XVF+fPn9/opu0UGr///rs4ffzaa68VFwAgImIPKSIiIiIikpykpCTs2bMn1MOgRho2bBgOHz4c6mEQkQSxhxQREREREREREQUVp+wREREREREREVFQMZAiIiIiIiIiIqKgYiBFRERERERERERBxabmIbR7924AgFLJXJCIiEiKHA4HAGDAgAEhHgnxfRMREZG0NfR9E3+jk985HA7xB5Gkg+dFunhupInnRbp4bqgp4s9teOB5lj+eY/njOQ4eVkiFkOsvfP369QvxSPwrMzMTAJCSkhLikZA7nhfp4rmRJp4X6QrmuUlPTw/4Mcg7Tf19E68p4YHnWf54juWP59h3DX3fxAopIiIiIiIiIiIKKgZSREREREREREQUVAykiIiIiIiIiIgoqBhIERERERERERFRUDGQIiIiIiIiIiKioGIgRUREREREREREQcVAioiIiIiIiIiIgoqBFBERERERERERBRUDKSIiIiIiIiIiCioGUkREREREREREFFTqUA+AiIiIiIiI5M1mF1BYaq13u9hINXQa1k0QhQMGUkRERERERBQw+08a8fqy0ygstdW7bZRBhU//0Q3NozVBGBkRhRKjZyIiIiIiIgqI9TsL8Mz8E16FUQBgNNlx5OzFAI+KiKSAFVJERERERETkV3a7gC9+PocftuYDAFo21+Ifk9oiOkJV69c8Ou8oLDYBZqsjWMMkohBiIEVERERERER+YzTZ8cay09h9tBQA0LtjJP41tQNiI+v++KnXKWGx2WG2CMEYJhGFGAMpIiIiIiIi8ousfDNeXHQSZ/PMAIAxg1rggRtaQ6Ouv1uMXqNECeyskCIKE7IOpH755Rd88cUXOHLkCDQaDQYMGIBHH30UKSkpXn29yWTCvHnzsHbtWuTm5iIxMRFjxozBQw89BIPBEODRExERERERNR3px0rx2tLTMJbboVQCD1yfjOuHtIBCofDq612r6zGQIgoPsg2kli9fjueeew5du3bF448/DrPZjCVLlmDKlClYtmxZvaGU3W7Hfffdh7S0NIwbNw6pqanIzMzEggULsHfvXixcuBAqVe3zn4mIiIiIiMKBIAhY878CfPpTFhwO50p5z97WHv0uiW7QfsRAysJAiigcyDKQKi4uxhtvvIGWLVti2bJliIqKAgCMHj0aY8eOxcsvv4ylS5fWuY+VK1ciLS0N06ZNw3PPPSfen5ycjDfffBMrV67ETTfdFNDnQUREREREFCpWmwOrtuUjr8ha53Z5xRb872AJAKBNgg4vTu+I5Hhdg4+n0zoDqXJWSBGFBVkGUhs3boTRaMSdd94phlEA0Lp1a1x33XVYuXIlzp49izZt2tS6j1WrVgEA7rzzTo/7b7vtNnzwwQdYtWoVAykiIiIiIpKtHZklmP/zea+3H9g1Gk/d2h5RBt9mkug0zql9nLJHFB5kGUjt3bsXANCvX79qj/Xr1w8rV65ERkZGrYGUIAjYt28fEhMTkZyc7PGYXq9H9+7dsX//fgiC4PV8aCIiIiIioqbkQqkNAKBVK9C7Y1Sd2/bpHIVJwxKgUvr++aiyhxRX2SMKB7IMpHJycgAALVu2rPaY6z7XNjUpKiqCyWRCly5danw8KSkJ6enpKC4uRlxcXKPG6nA4kJmZ2ah9SI3JZAIA2T2vpo7nRbp4bqSJ50W6gnluHA4HlMr6V4ai4GjK75t4TQkPcjvPZ7OcgVRcBHD7UEs9Wxfi6JHCRh3PbHJODczLL0JmZlmj9hUocjvHVB3Pse8a+r5Jlu+wXD9AWq222mOu+1zb1KS8vLzWrwcAnU7nsR0REREREZHcWO3O/2uCVMagVXsel4jkTZYVUgaDAQBgsVRP8V33ubapiV6vr/XrAcBsNnts1xhKpbLeFf+aGleSLLfn1dTxvEgXz4008bxIVzDPTXp6esCPQd5ryu+beE0JD3I7z9tPnweQi5goA1JSap494k9JR7OAo/nQ6CKQktI54MfzhdzOMVXHc+y7hr5vkmWFVFJSEgAgOzu72mOu+1zb1CQuLg4Gg6HGrwec0/0iIiIQGxvrh9ESERERERFJj6u5uFYTnI+NlT2k2NScKBzIMpDq06cPgJrTuT179gAAevfuXevXKxQK9OrVC7m5ucjKyvJ4rLy8HIcOHUKvXr3Y0JyIiIiIiGTLUtFcXKcOzuceVyBVbmEgRRQOZBlIXXPNNYiMjMTy5cthNBrF+8+dO4d169ZhwIABaNu2LQBnL6njx48jNzfXYx/jxo0DAHz55Zce9y9btgzl5eW48cYbA/wsiIiIiIiIQifoFVJaRcVxucoeUTiQZQ+p2NhYPPnkk3jhhRcwZcoU3HLLLbBYLFiyZAkA4LnnnhO3zcjIwPTp0zFhwgS88cYb4v0TJ07EDz/8gMWLF6O0tBQDBw7E4cOH8fXXX2PgwIGYOHFi0J8XERERERFRsFhszkBKxyl7RBQAsgykAODWW29FXFwc5s+fj9mzZ0Oj0WDAgAH4xz/+4VVzMpVKhc8++wzz5s3Dzz//jJ9++gkJCQm444478NBDD0GlUgXhWRAREREREYWGq1JJqwnulD0zp+wRhQXZBlIAMGrUKIwaNarObQYPHozDhw/X+FhkZCSefPJJPPnkk4EYHhERERERkWRZXFP21MGpkNJrWSFFFE5k2UOKiIiIiIiIGidUU/YsNgEOB/tIEckdAykiIiIiIiKqJlRT9oDKMIyI5IuBFBEREREREVXjmrIXvAqpyuCr3MIKKSK5YyBFRERERERE1ZiD3ENKp608DvtIEckfAykiIiIiIiKqxmJzVinpQjBlj4EUkfwxkCIiIiIiIqJqxAqpIE3Z0zOQIgorDKSIiIiIiIioGkuQAymPKXsWBlJEcsdAioiIiIiIiDzY7QLsFZmQTs0pe0TkfwykiIiIiIiIyIPZVhkIBatCSq1SQFVxqHIrV9kjkjsGUkREREREROTB4lahpAtSIOV+LE7ZI5I/BlJERERERETkwexWoaQN0ip7QGUfKU7ZI5I/BlJERERERETkwaNCSh2CCikGUkSyx0CKiIiIiIiIPISihxQA6BlIEYUNBlJERERERETkweI2ZU8XzCl77CFFFDYYSBEREREREZEH9wqlYFZI6bSKiuNzlT0iuWMgRURERERERB7cK6S06uBXSJVzyh6R7DGQIiIiIiIiIg+Wih5SWrUCCgWn7BGR/zGQIiIiIiIiIg+uKXvBnK4HcJU9onDCQIqIiIiIiIg8uKbsBbOhOQDotAykiMIFAykiIiIiIiLyIFZIqYP7kVHPCimisMFAioiIiIiIiDy4ekjpgj5lr2KVPQtX2SOSOwZSRERERERE5MEsTtkLciDFKXtEYYOBFBEREREREXmwiE3Ng9tDyjVlr5yBFJHsMZAiIiIiIiIiD65AihVSRBQoDKSIiIiIiIjIg9nmnLKnDXoPqYpAysJAikjuGEgRERERERGRB3HKnjq4U/Z0XGWPKGwwkCIiIiIiIiIP5lBN2as4nt0B2OxcaY9IzhhIERERERERkQeL1TVlL8gVUtrK47FKikjeGEgRERERERGRB7MtNBVSerfjsY8UkbwxkCIiIiIiIiIPlT2kQjNlDwDKWSFFJGvqxu7g8OHDWLNmDY4fPw6TyYSFCxcCAM6fP4+DBw9i0KBBiI6ObuxhiIiIiIj8Lr/YCovNgdYtdKEeCpGkmCum7OmCPmXPrUKKgRSRrDUqkJo7dy4++ugjOBzOC4VC4Tbf12zGrFmz8Nxzz2Hq1KmNGyURERERkZ9ZbQ48+MFhmCwOLHqqO5pFa0I9JCLJcIVB2hA1NQc4ZY9I7ny+uqxbtw5z585FSkoKPvroI0yZMsXj8Q4dOqB79+747bffGj1IX1y4cAEvvPACrrjiCvTq1QvXXXcdPvvsM9hsNq/3MXLkSHTr1q3G/zZt2hTA0RMRERFRoFlsAkpNdtjsArIKzKEeDpGkWKQQSFm5yh6RnPlcIbVo0SIkJSVh8eLFiIyMxMGDB6ttc8kll2D37t2NGqAvjEYjbr/9dpw8eRK33XYbunXrhp07d+Kdd97B0aNHMXv2bK/31alTJzzwwAPV7u/Ro4c/h0xEREREQebePLnczEoMIneuVfZ06uBO2dOqucoeUbjwOZDKzMzE9ddfj8jIyFq3SUpKQn5+vq+H8Nn8+fNx7NgxPP3007jzzjsBAJMnT0Z0dDSWLFmCiRMn4rLLLvNqX/Hx8Rg3blwgh0tEREREIaBSKaBRK2C1CWyeTFSFa5W9YFdIKZUK6DQKmK0CAykimfP56uJwOBAREVHnNsXFxVCrG903vcFWrVoFg8FQbRqhK5xatWpVg/Zns9lgNBohCCwZJSIiIpITQ0UDZRMrpIhEDocAq83V1Dz4C7O7jlnOHlJEsuZzWtS2bVscOHCgzm327NmDTp06+XoIn+Tn5yMrKwv9+vWDXq/3eKxNmzZISEhARkaG1/vbu3cv+vbtC6vVCoPBgMsuuwx///vfkZKS4u+hExEREVGQ6bVKlFy084MvkRuLrfIP8dogr7IHuAIpOyukiGTO50DqmmuuwSeffIK1a9dizJgx1R5fvnw5jh49in/+85+NGmBDZWdnAwBatmxZ4+MtW7bEiRMnvNpX586dMXHiRHTq1AlKpRL79u3D0qVLsXXrVixYsAADBw5s9HgdDgcyMzMbvR8pMZlMACC759XU8bxIF8+NNPG8SFcwz43D4YBSGfzqAKpZIN43KQTngjd/nc1GZmbgWk3wmhIe5HKey8orA6nsrDPItAb3Ouh6XZ4J8OvSF3I5x1Q7nmPfNfR9k8+B1N133421a9fi8ccfx7p162A0GgEACxcuxO7du7Fx40Z06tQJt99+u0/7nzNnjtfb9unTByNGjAAAlJeXAwC0Wm2N2+p0OnGb+nz++ecet0eNGoUxY8bglltuwfPPP4+ff/7Z6zESERERkfToNM7/W7xfiJlI9qz2yn9rgt+BRTymxV73dkTUtPl8eYmKisKiRYvw1FNP4ZdffhHvf+ONNwAAqampeOedd6pNm/PW3Llzvd526tSpYiDlOp7FYqlxW7PZ7POYAKBnz54YOXIk1q9fj9OnT6N9+/Y+7wsAlEql7Kb/uZJkuT2vpo7nRbp4bqSJ50W6gnlu0tPTA34M8l4g3jc1+/04/so3IjK6GVJSkv26b3e8poQHuZznrHwzAOdz6dalE9ok+P75yRexm48iq/AiomObIyWldVCPXR+5nGOqHc+x7xr6vqlReXdSUhIWLlyII0eO4M8//0RRURGio6PRt29f9OzZszG7xuHDh336OtdUPdfUvaqys7Nrnc7nreRk55uVgoKCRgdSRERERBQ6el1FU3P2kCISWdx6NwV7lT2gsqm52cJFpYjkzC8FmF27dkXXrl39satGi4+PR+vWrZGZmYny8nKPaqisrCzk5eXhiiuuaNQxTp06BQBISEho1H6IiIiIKLRcq+yxqTlRJfdm4lp18AMpfcXrkk3NieTN56tLaWkpMjMzxYZfVV28eBGZmZlib6lguvHGG2EymbBs2TKP+7/88ksAwLhx4zzuP3fuHI4fPw6r1Sred+HChRr3vWPHDmzevBldu3ZF27Zt/TxyIiIiIgomPQMpomrcV9nThWyVPQZSRHLnc4XURx99hGXLluGPP/6o8XGHw4Fbb70V06ZNC/pKe/feey/Wr1+P2bNnIysrC926dcPOnTuxatUqXH/99bjssss8tn/qqaeQlpaGjRs3ok2bNgCAVatW4bvvvsOwYcPQpk0bKJVK7N+/H6tXr4bBYMCrr74a1OdERERERP7nCqQ4ZY+oklkqU/YYSBHJms+B1B9//IHLLrsMUVFRNT4eFRWFyy+/HFu2bAl6IBUVFYWvv/4a77//PtatW4dvvvkGycnJeOyxx3DXXXd5tY/evXsjLS0NGzZsQGFhIWw2G5KSkjBp0iTce++9rI4iIiIikgFO2SOqztVDSq1SQKUMXYUUX5dE8uZzIHXu3Ll6ezG1a9cOaWlpvh6iUZo3b46XXnoJL730Ur3bLl68uNp9AwYMwIABAwIxNCIiIiKSCL1OBYAffIncma3OKXtadfDDKADQaRUV4+DrkkjOfK6/dDi8uzhYLBZfD0FEREREFFD6ikoMk9ke4pEQSYfF5vyspwvBdD3347qCMSKSJ5+vMG3atMGOHTvq3GbHjh1ITk729RBERERERAFl0FVMDWIlBpHIVZkUiv5RAHtIEYULn68wV199NQ4dOoRPPvmkxsc/+ugjHDp0CNdee63PgyMiIiIiCiRxlT0zP/gSuVhcU/ZCsMIeUFm5aOZUWiJZ87mH1F133YXVq1fjgw8+wLp16zB06FAkJSUhJycHW7duxZEjR9CqVSuvm4gTEREREQWbK5Cy2ATY7QJUqtB8ACeSEldTc506RBVSWlZIEYUDnwOpmJgYLFq0CI8//jj27NmDzMxMKBQKCIIzTe/Xrx9mz56N2NhYvw2WiIiIiMifXKvsAc5pe5EqVQhHQyQNZptryl6Imppzyh5RWPA5kAKcfaS++eYbHDhwAHv27EFpaSmio6PRt29f9OzZ019jJCIiIiIKCL3OLZCyOBCpZyBF5JqyJ4Wm5g6HAKWSlYtEctSoQMqlZ8+eDKCIiIiIqMnRayoDKBP7SBEBkEBTc21lAGWxCdBrGUgRyVForjBERERERBJg8KiQsodwJETSIVZIqUM7ZQ/gtD0iOWtUhZTVasXGjRuRkZGBkpIS2O3Vf4krFAq89tprjTkMEREREVFA6LWeU/aIyL2HVGjqF/QMpIjCgs+BVE5ODu666y6cOHFCbGReEwZSRERERCRV7oGUiYEUEYDKVfZCNmXPPZDi65JItnwOpN58800cP34cY8eOxc0334xWrVpBxVVJiIiIiKgJUSkV0KoVsNgEVkgRVQj5lD0tK6SIwoHPgdTWrVuRmpqKd955x5/jISIiIiIKKr1OCYvNzkCKqELIm5q7HbecgRSRbPl8hTGbzejTp48/x0JEREREFHQGrbPKn6vsETlZKnpI6UIWSFVWZpkttbeHIaKmzecrTJcuXXDu3Dl/joWIiIiIKOhcfaS4yh6Rk7liyp5WE5ope2qVAkqlaywMionkyudA6u6778Zvv/2GY8eO+XM8RERERERBVRlI8YMvEVDZ1FynDk2FlEKhEKuzGEgRyZfPPaRatGiBq666CrfeeiumT5+Onj17IiYmpsZtU1NTfR4gEREREVEgGSoCKa6yR+RktoW2hxQA6DVKmMwOBlJEMuZzIDVt2jQoFAoIgoCPP/64zm0PHTrk62GIiIiIiAKKFVJEniwhnrIHVPavMvN1SSRbPgdS48ePh0IRugsUEREREZE/uAIpNjUnAgRBqJyyF8IKKZ2WU/aI5M7nQOqNN97w5ziIiIiIiELCoKuokOIHXyLY7AIcFQvbaUPUQwqoXGmv3MpV9ojkKnRXGCIiIiIiCdBXVIGUs0KKCBZbZQCkk8KUPQbFRLLlc4WUu+PHj+PEiRMoKyvD+PHj/bFLIiIiIqKg0OtUAACTxR7ikRCFnnsAFMqm5uwhRSR/jbrCZGZmYtKkSbj++uvxyCOP4JlnnhEf27FjBwYNGoQtW7Y0epBERERERIFiYFNzIpHFLZBiDykiCiSfrzB//fUXpk2bhszMTFxzzTXo27evx+MDBw6ERqPB+vXrGztGIiIiIqKA4Sp7RJXMbj2bQrnKnp5T9ohkz+dAau7cuTCZTFi4cCHmzJmDyy+/3ONxlUqF/v37Y+/evY0eJBERERFRoHCVPaJKFptbhVRIm5pzyh6R3Pl8hdm2bRtGjhyJ1NTUWrdp2bIl8vLyfD0EEREREVHAcZU9okrS6SHlrM4yc5U9Itny+QpTVFSEdu3a1bmNSqVCeXm5r4cgIiIiIgo4Vw8pq02Azc4PvxTeLBKZsufqIcWgmEi+fA6kmjVrhvPnz9e5zalTp5CYmOjrIYiIiIiIAs71wRdgHykiV1NzhQLQqEIYSLGHFJHs+RxIDRw4EL/99lutU/JOnDiB33//HZdddpnPgyMiIiIiCjSDViX+m4EUhTtzRQ8prVoJhUICgRRfk0Sy5XMgde+998JqteL222/Hpk2bUFZWBgAoLS3Fb7/9hpkzZ0KtVuOOO+7w11iJiIiIiPzO4FEhZQ/hSIhCzzVlTxfC6XpA5WIDrJAiki+1r1/Yo0cPvPbaa3juuefw4IMPivcPGjTIuWO1Gm+++SY6d+7c+FESEREREQWI3i2QMrEag8KcKwAKZUNzgFP2iMKBz4EUANx4443o27cvvv76a6Snp6OoqAhRUVHo168fpk6dio4dO/prnEREREREAaHXuQVSZn74pfAmVkipQ1shpRMrpLjQAJFcNSqQAoB27drh6aef9sdYiIiIiIiCTqdhU3MiF7GHVIgrpPQVUwZtdufql+oQNlgnosAI7VUmQDIyMvDKK69g6tSp6N+/P7p164Y5c+b4tK+dO3di+vTp6NevH/r164fp06dj586dfh4xEREREYWKSqkQ++UwkKJwZ5HYlD2A0/aI5MrrCqlz5875fJDWrVv7/LW+2LJlC5YuXYoOHTqgZ8+eSEtL82k/v//+Ox544AEkJSVh1qxZ0Gq1+O6773DHHXfgk08+wbBhw/w8ciIiIiIKBb1WBbPVBhObmlOYc61qF+qm5jqtZyAVqVfVsTURNUVeB1IjR470adlPhUKBgwcPNvjrGmPKlCm46667EBkZiR07dmD69OkN3ofdbscLL7wArVaLJUuWiKHa+PHjMXbsWLz44ov45ZdfoFLxwkhERETU1Bm0ShSXsUKKyGxz9mzSqlkhRUSB5XUgNX78+GqB1NmzZ7Fz505ER0eje/fuiI+PR35+Pg4dOoTS0lKkpqaiTZs2fh90feLj4xu9j127diErKwsTJ070qPCKjo7G5MmTMXfuXOzatQuDBw9u9LGIiIiIKLRcK+0xkKJw55qyp5PSlD2+LolkyetA6o033vC4feLECdx66624++67MXPmTERFRYmPlZWVYe7cuVixYgVeeukl/402iPbu3QsA6NevX7XHXPdlZGQwkCIiIiKSAVcgxVX2KNxV9pAK8ZQ9jwoprrRHJEc+r7L3zjvvoFu3bnjiiSeqPRYZGYmnnnoK+/btwzvvvIO5c+c2apChkJOTAwBISkqq9ljLli09tmkMh8OBzMzMRu9HSkwmEwDI7nk1dTwv0sVzI008L9IVzHPjcDigVMpyDZgmKZDvmxw2CwDgfE4BMjOL/b5/XlPCgxzOc8EFKwDAVFYS0ufhHkIdPX4KQpk0rsVyOMdUN55j3zX0fZPPgdSuXbtw66231rlN//798e233/q0/4asitenTx+MGDHCp+PUxvVDqNVqqz2m0+k8tiEiIiKipk2nVgAQxP45ROHKane+BjSq0FZIadw+qVr4uiSSJZ8DKYvFgtzc3Dq3yc3NhcVi8Wn/Damqmjp1qt8DKYPBAAA1jt9sNnts0xhKpRIpKSmN3o+UuJJkuT2vpo7nRbp4bqSJ50W6gnlu0tPTA34M8l4g3zfF7z0NnCmCzhCDlJT2ft8/rynhQQ7nWb35KICLSEpsjpSU4K6WXpVWnQGLTUBCUjJSUuJCOhYXOZxjqhvPse8a+r7J50Cqe/fuWLt2LW677Tb07t272uMZGRlYu3ZtjY954/Dhw74OzS9cU/VqmpaXnZ3tsQ0RERERNW0GrXPlZDY1p3BnqZgqpw9xU3PA2UfKYrNzlT0imfI5kJo1axbuueceTJkyBWPGjEFqaipatGiBgoICpKWl4eeff4YgCJg1a5Y/xxs0ffr0AeBM+G6++WaPx/bs2eOxDRERERE1bXqda5U9e4hHQhRaZpurqbkEAimtEqUmBlJEcuVzIDV06FC8++67eOGFF7B69WqsWbNGfEwQBMTGxuKll17CZZdd5peBBtK5c+dgMpnQrl07aDQaAEBqaiqSk5Oxbt06PPLII2jVqhUAwGg0Yvny5UhOTsbAgQNDOWwiIiIi8hNXNQhX2aNw56qQCvUqe0DlSntmC3tIEcmRz4EUAIwaNQrDhw/Hxo0bcfDgQZSWliI6Oho9evTA1VdfjYiICH+Ns0GysrKwatUqAMDZs2cBADt37sRHH30EwBk2paamits/9dRTSEtLw8aNG9GmTRsAgEqlwgsvvICZM2di6tSpmDZtGjQaDb799lvk5eXh448/hkqlCvIzIyIiIqJAMIgVUgykKLxZKqqRdFKokKoIxVghRSRPjQqkACAiIgI33HADbrjhBn+Mxy/Onj2LDz74wOO+HTt2YMeOHQCc0w3dA6najBgxAgsWLMC8efPw4YcfAgB69eqFBQsWYMiQIf4fOBERERGFhF7LQIoIqAx/tOrQB1Ku1yUDKSJ5anQgJUWDBw9uUFP0xYsX1/rYkCFDGD4RERERyZzrg6+JgRSFOYvNOT1OJ6EpewyKieSp0YHUvn37kJGRgZKSEtjt1ZtAKhQKPPTQQ409DBERERFRwBhYIUUEu0OAze7qIRX6CimxhxQrpIhkyedAymg0YtasWdixYwcEofYmcwykiIiIiEjq9Fpnb1CbXYDV5oBGAtOViILN4hb8SKOHFAMpIjnzOZB66623sH37dgwcOBATJ05Eq1at2OSbiIiIiJokV1NzACi3MpCi8GS2VhYaaNUSmLIn9pDiKntEcuRzILVx40b06NEDixYtglLJX9hERERE1HS5ekgBQLnZgWhDCAdDFCIWm9QqpCpW2eNUWiJZ8vkqU1paisGDBzOMIiIiIqImzyOQ4odfClPuU/bYQ4qIAs3nq0z79u1RUFDgz7EQEREREYWEwS2Q4kp7FK48puxJYJU9PQMpIlnzOZCaOnUqNm3ahJycHH+Oh4iIiIgo6FghRVSlqbkE+qi5ekiVM5AikiWfe0gNHz4c27dvx5QpU/DQQw+hZ8+eiImJqXHb1q1b+zxAIiIiIqJAc++Xw0CKwpXZJtEpe3xNEsmSz4HUyJEjoVAoIAgCnnvuuVq3UygUOHjwoK+HISIiIiIKOKVSAb1WiXKLAyaLPdTDIQoJi9RW2dNwlT0iOfM5kEpNTfXnOIiIiIiIQsoVSJWbWY1B4cnVq0mjVkCplEAgpa1YZY9T9ohkyedAavHixf4cBxERERFRSLn6SLGpOYUrVw8pKfSPAjxX2RMEAQpF6EMyIvIfaVxpiIiIiIhCzLXSHntIUbgy25xT46Swwh5QGUgJAmCxcdoekdz4JZC6ePEiDh48iF27dvljd0REREREQadnIEVhzlUhJYWG5gCgdxsHG5sTyU+jrjQ5OTl45JFHMGjQIEyaNAnTp08XH9u9ezcmTJjAkIqIiIiImgRxyh57SFGYEqfsSSSQ0mndAin2kSKSHZ+vNPn5+bjlllvwyy+/oGvXrujcuTMEobKMsnfv3jh79izWrVvnl4ESEREREQWSQacCAJTzgy+FKddqdlJYYQ/wDMYYSBHJj8+B1Lx585CdnY233noLK1aswKhRozwe12q1GDhwINLS0ho9SCIiIiKiQBN7SJntIR4JUWhYbBKrkHIbB4NiIvnx+UqzZcsWDBs2DDfeeGOt27Ru3Rq5ubm+HoKIiIiIKGh0XGWPwpxZ7CElkQopbeU4zBY2NSeSG58DqdzcXHTr1q3ObXQ6HcrKynw9BBERERFR0HCVPQp3loope1KskOKUPSL58flKEx0djfz8/Dq3OXv2LFq0aOHrIYiIiIiIgoaBFIU7sUJKLY1ASqNSQFlRJMVAikh+fL7SXHrppdi8eTOMRmONj+fk5GDLli0YMGCAz4MjIiIiIgoWTtmjcGexVTQ1l8iUPYVCIVZJmfm6JJIdnwOpO+64A0VFRbj33ntx5MgRj8cOHz6MRx55BDabDTNmzGj0IImIiIiIAs2gY4UUhTeLVVpNzYHKoJgVUkTyo/b1C4cMGYLHHnsM7733HsaNGweVyrlM7sCBA1FWVgZBEPDUU0+hT58+fhssEREREVGgGLTO97PlZn7wpfBU2dRcQoFUxVi4yh6R/PgcSAHAfffdh379+mHRokVIT09HUVER1Go1RowYgTvvvBODBw/21ziJiIiIiAKqcsqeHYIgQKGQxrQlomARm5qrpfOzr6uYPmi2cpU9IrlpVCAFAKmpqUhNTfXHWIiIiIiIQsbV1NzuAKx2AVoJfSgnCgazTboVUuwhRSQ/0rnSEBERERGFkCuQAvjhl8ITe0gRUTA1ukLq/PnzWL16NQ4ePAij0YioqCj06NEDN9xwA1q3bu2PMRIRERERBZzeLZAyWRyIjgjhYIhCwDUtTiqr7AGAXsNAikiuGhVIffXVV3jnnXdgtVohCJVzetevX4+5c+fiiSeewPTp0xs9SCIiIiKiQNPr3AIpNjanMOSqkNKqJVQhxUCKSLZ8DqTWrl2L119/HdHR0bjzzjuRmpqK+Ph45OfnIy0tDcuWLcPrr7+OhIQEjB492p9jJiIiIiLyO/cpe+WcskdhyGKT4JQ99pAiki2fA6n58+cjJiYG33//Pdq2bevx2BVXXIGbbroJkyZNwvz58xlIEREREZHk6bUq8d8MpCjcCIIgySl7Oq1zLOVcZY9IdnyOvo8dO4ZRo0ZVC6Nc2rVrh1GjRuHo0aM+D46IiIiIKFh0GgUUFZ/DTRZ7aAdDFGRWW2XgI8kKKU7ZI5Idn680ERERiI2NrXObuLg4REZG+noIIiIiIqKgUSgUYgNlVkhRuDHbKn/mJdlDiq9JItnx+UozdOhQbN26tdbHBUHA1q1bcfnll/t6CCIiIiKioHI1NmcgReHGYnWvkJLSlD1WSBHJlc+B1JNPPomioiL885//RFZWlsdj586dwz//+U8UFxfj8ccfb/QgGyojIwOvvPIKpk6div79+6Nbt26YM2dOg/czcuRIdOvWrcb/Nm3aFICRExEREVEouSqkuMoehRv3wEcroSl7ek7ZI5Itn5uaP/HEE4iJicHatWuxfv16tGrVCi1atEBBQQHOnz8Pu92Obt264YknnvD4OoVCga+++qrRA6/Lli1bsHTpUnTo0AE9e/ZEWlqaz/vq1KkTHnjggWr39+jRozFDJCIiIiIJMrgqpPjhl8KMxe1nXlI9pFghRSRbPgdS7iGPzWbDmTNncObMGY9tMjMzq32dQhH48s8pU6bgrrvuQmRkJHbs2IHp06f7vK/4+HiMGzfOj6MjIiIiIqnSV3z4LWeFFIUZs9uUPa1aOlP2xAopC1fZI5IbnwOpjRs3+nMcfhUfH+/X/dlsNpSXlyMyMjIogRoRERERhYYrkOIqexRuLDZpTtlz9bNi1SKR/PgcSCUnJ/tzHJK1d+9e9O3bF1arFQaDAZdddhn+/ve/IyUlJdRDIyIiIiI/M2hVANjUnMKP+yp2kpqyVzEWm12A3S5ApWKBAJFc+BxIhYPOnTtj4sSJ6NSpE5RKJfbt24elS5di69atWLBgAQYOHNjoYzgcjhqnNjZlJpMJQM1TNil0eF6ki+dGmnhepCuY58bhcECplM4Hs3AXjPdN5nIrACA3v9ivx+I1JTw05fN84rSzKlCpAI4dPRzi0VTKya4MyvYdzIQ+xCsANuVzTN7hOfZdQ983NTqQ2rx5M1atWoXjx4/DZDJhw4YNAIATJ07gjz/+wOjRo5GQkNDg/TZkVbw+ffpgxIgRDT5GfT7//HOP26NGjcKYMWNwyy234Pnnn8fPP//s92MSERERUejoKt4dW2yhHQdRsFkrZqlqVKEdR1Uat0+sVhug14RuLETkX40KpJ555hn88MMPEARngzn3/kqRkZF4/fXXYbVacffddzd433PnzvV626lTpwYkkKpJz549MXLkSKxfvx6nT59G+/btG7U/pVIpu+l/riRZbs+rqeN5kS6eG2nieZGuYJ6b9PT0gB+DvBeM902tTp4DDudBpTEgJeUSv+2X15Tw0JTP8+nSAgBnodepJTV+Q045AGfFVtv2ndCyuS6k42nK55i8w3Psu4a+b/I5kPrmm2+wcuVKjBgxAo899hjWrl2Lzz77THw8KSkJl156KTZv3uxTIHX4sHTKRKty9c8qKChodCBFRERERNIhrrLHHlIUZlyr7OlCPCWuKtdrEvBcCZCImj6fmyIsX74c7du3x9y5c9GtWzdoNNVrJzt27IizZ882aoBSdOrUKQDwaSoiEREREUmXq6m5iYEUhRnXKntSWmEP8AzIGBQTyYvPV5sTJ05g2LBhNQZRLgkJCSgoKPD1EEFz7tw5HD9+HFarVbzvwoULNW67Y8cObN68GV27dkXbtm2DNUQiIiIiCoLKCil7iEdCFFxma0UgpZZWhZT7in+uMRKRPAR0lb28vDzo9fpAHqJGWVlZWLVqFQCIFVo7d+7ERx99BABITU1FamqquP1TTz2FtLQ0bNy4EW3atAEArFq1Ct999x2GDRuGNm3aQKlUYv/+/Vi9ejUMBgNeffXVID8rIiIiIgo0TtmjcGURp+xJq0JKy0CKSLZ8DqQ6duyIP//8s9bH7XY7du3aha5du/p6CJ+dPXsWH3zwgcd9O3bswI4dOwAAs2bN8gikatK7d2+kpaVhw4YNKCwshM1mQ1JSEiZNmoR7772X1VFEREREMmTQOT/8miwOCILgsWgPkZyJFVISC6RUSgU0agWsNoGBFJHM+BxIjR07Fm+//Tbmz59fY9Pyjz/+GGfPnsU999zTqAH6YvDgwQ1qir548eJq9w0YMAADBgzw57CIiIiISOJcFVIOB2C1CdBKrMEzUaC4ekjpJDZlD3BWbVltdphZuUgkKz4HUtOmTcO6devw9ttv46effoJS6fzl/eqrr2L37t04dOgQ+vXrh5tuuslvgyUiIiIiCiT3Fb3KLQ7JVYsQBYpryp4Uf+Z1GiWMJjtX2SOSGZ+vNlqtFgsXLsTEiRNx5MgR7N+/H4IgYPHixcjMzMT48ePx+eefQ6VS+XO8REREREQBY3ALpLjSHoUT13Q4qfWQAgB9RaUip+wRyUujmppHRkbi1VdfxZNPPomMjAwUFRUhOjoaffr0QfPmzf01RiIiIiKioKhaIUUULixiDykJTtlzLTbAQIpIVvyyyl5sbCyGDRvmj10REREREYWMXltZ3W8y20M4EqLgMtsqpuyppVch5araYg8pInmR3tWGiIiIiChEXKvsAazGoPBikfCUPTGQ4muSSFa8rpB65plnfDqAQqHAa6+95tPXEhEREREFk1atgEIBCAJQbuaHXwof5iYwZY+BFJG8eB1IrVy5ssb7FQoFBKH6ageu+xlIEREREVFToVAooNcqYTI72NScwoqlYsqepCukLFxlj0hOvA6kNm7c6HHb4XDg9ddfx59//olp06Zh0KBBaNGiBQoKCrBjxw4sWbIEAwYMwNNPP+33QRMRERERBYqhIpBiU3MKJ2JTc0n2kOIqe0Ry5HUglZyc7HF74cKF2L17N3744Qe0atVKvL9Tp05ITU3FhAkTMHHiRGzcuBF33HGH3wZMRERERBRIBteKXgykKIyYra4KKelN2dOzhxSRLPkcf3/77bcYPXq0RxjlLjk5Gddddx2+++47nwdHRERERBRsrn41JvaQojAiVkhJccqeKyRmIEUkKz5fbbKyshAdHV3nNjExMcjKyvL1EEREREREQWfQqQAA5VZ7iEdCFDxmm4QDKbGHFAMpIjnx+WrTrFkz/Pe//631cUEQ8PvvvyMuLs7XQxARERERBZ04ZY8VUhQmbHYBjoofd51aelP2dJyyRyRLPgdSo0aNwuHDh/Hwww/j9OnTHo+dPn0aDz/8MI4cOYIxY8Y0epBERERERMEiTtljNQaFCfegR9IVUlauskckJ143Na/qkUcewe7du7FhwwZs3LgR8fHxiI+PR35+PvLz8+FwONC7d2/MmjXLn+MlIiIiIgooNjWncGNxC6R0UgyktFxlj0iOfA6kIiMj8fXXX2PBggVYsWIF/vrrL+Tm5gIA2rdvj4kTJ+LOO++EVqv122CJiIiIiAKNgRSFG4utsvJIiqvssYcUkTz5HEgBgFarxQMPPIAHHngAZWVlMBqNiIqKQmRkpL/GR0REREQUVJyyR+FG6lP29G49pARBgEIhvdCMiBquUYGUu8jISAZRRERERNTkGbTOVfZMZq6yR+FB+lP2nGNyCIDVLkArwcbrRNRw0rvaEBERERGFkEHH6UEUXtybhWslPGUPYB8pIjlhIEVERERE5IZT9ijcWGxuFVJq6X1E9AikLFxpj0gupHe1ISIiIiIKIQMDKQozrqojhQLQSHA6HCukiOSJgRQRERERkRtXIGW2OBsoE8mdpWLKnlatkGTDcJ22ckwMpIjkg4EUEREREZEbva6ygbLFxkCK5M8V8mglOF0PqFxlD2BvNyI5keYVh4iIiIgoRNw//JrM/PBL8ufqIaWV4Ap7gOeUvXJWSBHJhjSvOEREREREIWLQqcR/c3oQhQPXlD2dBFfYA5x9rVwzCfmaJJIPtbcbzp0716cDKBQKPPTQQz59LRERERFRsOm17hVS9hCOhCg4xCl7Eq2QUigU0GmUKLc4GEgRyQgDKSIiIiIiNx6BFPvVUBiwVIQ8Oon2kAJQGUhZ2NeNSC68DqQWLVoUyHEQEREREUmCwS2QKmcgRWHAXNG8XyvRKXtA5XRCVkgRyYfXgdSgQYMCOQ4iIiIiIknQqBVQKgGHg4EUhQexQkqiU/YAQFcRFDOQIpIP6V5xiIiIiIhCQKFQiCvtcZU9CgdS7yEFVK5+aWZITCQbXldIERERERGFC4NOiYtmh+wrpNKPleJ0TjkUAKAAFFBAqaj4d8VtKIAOSXr0aB8Z4tFSoLhW2dOqpTxlzxlIlbNCikg2GhVI5eTk4OOPP8bWrVuRk5MDq9VabRuFQoGDBw825jBEREREREGl16oA2GQdSJ3JLcez8094ta1CAcy+7xL07MBQSo4stiYwZY8VUkSy43Mgdf78eUyePBmFhYW45JJLYLFY0Lp1a2i1Wpw9exY2mw3du3dHVFSUP8dLRERERBRwrpX2TBZ7iEcSOMfOmQAASgWQGKeFAEAQnJUyggA4BAAQYDQ5YLY68NHqs/hwVleolNKtoiHfVE7Zk+65dfWQYoUUkXz4HEjNmzcPBQUFmD9/PoYOHYqUlBRMnDgRs2bNQnZ2Np577jlkZWVh4cKFfhxu/QRBwJo1a7Blyxbs378fOTk5iIqKQseOHTF9+nRcc801UCi8v9BmZmbi/fffx+7du2G1WtG1a1fcc889+Nvf/hbAZ0FEREREoeRaaU/OFVLnCswAgHaJenz8aLdat0s/Vopn55/AifPl+DmtANcPiQ/WEClIXFP2pF0h5VplTwjxSIjIX3y+4mzbtg3Dhg3D0KFDqz3WsmVLfPDBBzCbzZgzZ06jBthQFosFTzzxBI4ePYrrrrsO//rXvzB9+nTk5uZi1qxZ+Pe//+31vjIzMzFlyhSkp6fjzjvvxFNPPQWVSoWHH34Yy5cvD+CzICIiIqJQ0odBIHW+wAIAaNVCW+d2/S6JxrDesQCAr37JRnGZLeBjo+ASK6TUUg6kuMoekdz4fMXJy8vDJZdcIt5WqVQwm83i7cjISAwdOhQbN25s3AgbSKVS4auvvsLq1avx2GOPYfLkybjvvvuwcuVKdOjQAcuWLcPRo0e92tfLL78Mk8mEL774Ag8++CCmTJmCRYsWoUePHnjjjTdQUlIS4GdDRERERKFg0Ml/lT1XhVRyvK7ebe8Z0xo6jRJGkx1f/XI+0EOjILPYXBVSEp6yxx5SRLLjcyAVFRXl0cQ8JiYGOTk5HttER0ejsLDQ99H5QK1WY8iQIdXuj4iIwJVXXgkAOHLkSL37OXv2LHbt2oXU1FT07t1bvF+j0WDatGkwGo349ddf/TZuIiIiIpKOcKiQOidWSNUfSCXGaXHrVYkAgHU7C3Hk7MWAjo2Cq7KHlHQrpFyvSVZIEcmHzz2kWrdujezsbPF2SkoKtm/fDpPJBIPBAIfDgT/++AMtW7b0y0D9wRWYtWjRot5tMzIyAAD9+/ev9li/fv3EbSZOnNioMTkcDmRmZjZqH1JjMjkbZMrteTV1PC/SxXMjTTwv0hXMc+NwOKBUSvcDWrgJ5vsmU5nzD68FF0r8ckypXVNMFkGcemcvy0FmZl69X9MrUUB8tAL5pQLe/fYYHhmjgbIBvVnDgdTOs7cumpzhZGFBLjIzC0I8mpqVFDl/XotLTSH9/jbVc0ze4zn2XUPfN/n8Duuyyy7Djh07xCqp8ePHIzc3F7feeivefPNNTJkyBceOHcPo0aN9PYRfHThwABs2bED79u0xYMCAerd3hW1JSUnVHnOFbO6BHBERERHJh05d0UBZpu2S8ksrG0PHR3sXKqlVCkwcpAIAnM4XsPMYK1XkwlqxmKRGFdpx1EVbUUphle/Cl0Rhx+cKqZtuugkxMTG4cOECEhMTMW7cOBw4cABLlizB4cOHAQBjx47FzJkzfdp/Q5qh9+nTByNGjKj1cVdDc6VSidmzZ0Oj0dS7T1cqqtVWb/Ko0znLmsvLy70eY22USiVSUlIavR8pcSXJcnteTR3Pi3Tx3EgTz4t0BfPcpKenB/wY5L1gvm9KP5cD7M+GQqVDSkrtK9B5S2rXlNyMIgCnoVErMLh/CpRK70KplBQg49xJbD9Ugp/3AhOvuQTRBp8/UsiO1M6zt2yODAACOrRLRkpKXKiHU6MTxQXArrNwQB3S729TPcfkPZ5j3zX0fZPPvz06dOiA++67z+O+Z599Fg888ADOnDmD5ORkxMf7viTs3Llzvd526tSptQZSeXl5uOOOO5CXl4f3338fl156qVf7NBgMAJyr9lXlat6u1+u9HiMRERERNR1y7yHlamjesrnW6zDK5b7rW2P30VIUl9mwZEMOZt6YHIghUpDYHQKsYlNz6U5RdjVcZw8pIvnw+58zmjdvjubNmzd6P64qq8bIycnBjBkzkJWVhQ8//BAjR470+mtd0/KqNmoHKqfqSak/FhERERH5j7jKnswDqdZeNDSvqlVzHSYPT8TXv+Xgx+35GJXaHB1bGfw9RAoSq63yZ1wr5VX22NScSHakG4E3UnZ2NqZPn45z585h3rx5DQqjAIgr69VUcrZnzx4AzqmCRERERCQ/+opKkXKzPD/8nq9YYa918+rtKbxx85WJSGqmhUMAPlqdBUEQ6v8ikiSztfLc6dTS/Xjoqt6y2gTYHfx5I5IDryuknnnmGSgUCjz22GOIj4/HM88849XXKRQKvPbaaz4P0Bfnz5/H9OnTkZeXh08++QRDhw6tc/vc3FyUlpaidevW4lS9tm3bon///khLS8P+/fvRq1cvAIDNZsPixYsRGRmJq6++OuDPhYiIiIiCT19RIVVudUAQBChktppcYyqkAGc4cN/Y1nh5ySnsP1WGzXuLcFXfZv4cIgWJxepeISX9QApwjtmgk3AHdiLyiteB1MqVK6FQKHDvvfciPj4eK1eu9Orrgh1IGY1GTJs2DWfOnMHkyZORl5eHVatWeWzTrVs3jwZl7777LlauXIlFixZh8ODB4v3PPfccbr/9dtx9992444470KxZM6xatQoHDhzASy+9hNjY2KA9LyIiIiIKHoPW+WFXEJwVJHqtfAKpcosdhaXO5QNb+RhIAcBlPWIwoEs0dh8txRdrz2Fw9xhEMCRocjwqpKQ8Zc8tkDIzkCKSBa8DqY0bNwIAkpKSPG5LTVFREc6cOQMAWL58OZYvX15tm1mzZnnVMb9nz55YtmwZ3nvvPcyfPx9WqxVdu3bFBx98gFGjRvl97EREREQkDa6m5oAzwHG/3dS5pusBQOt436bsAc4/PD9wQ2vM/OAICkttWPZbDu4e3dofQ6QgstiaRoWU+2vQPUQjoqbL60AqOTm5zttS0aZNmwY3RH/jjTfwxhtv1PhYSkoKPv30U38MLWiyC83IyjcjLkqDuCg1YiPVUKuk+9cOIiIiIqlx//BrsjgQF7qh+J1rup5KCSTG+h5IAUCbBD0mXBGP5VvysPKPPIwd3AItm/tedUXB594kXCvpHlKVn2fkuvolUbjxeZW9uXPnYvDgwUhNTa11m127dmH79u2YNWuWr4ehBjKa7Hjg/SPVVp+IiVAhLkqNZlEaxEap0SxKXXFbLQZXrttS/ssIERERUTC4VtkD5Pfh91xFhVTLZlqo/PBHyylXJWH1tgKYrQ4cOFXGQKqJsTTRKXtE1PQ1KpACUGcgtXPnTsybN4+BVBAZdEpckmzAgVNlHveXXLSj5KIdf+Wa691HhE6JZlHqiuBKUxlcRasRF+kMsFy3DVql7Jp8EhERERncp+zJbKU9V4VUY/pHuTPoVEhqpsFfuWbkFVv9sk8KHnNTaWquZSBFJDc+B1LesNlsUCqle1GTI5VSgbfvvwQWqwNFZTZcKLWhyGhDUZkVRUa320ab83GjFaUX7XBfqfei2YGLZguy3PoL1EanUSA2siK4inYGV/ZyG6IMQI7lgkegFWVQMbwiIiKiJkFXZcqenLh6SPm6wl5NEmK1zkCqiIFUU+PqIaVWKaBSSve9us5tOqFZZq9JonAV0EDqwIEDiImJCeQhqBZajRKJcVokxtXfF8BuF1BcZsMFV1BltLr92/nfBaNVDLEcbtd/s1VAbpEVuTW9+Uj7y+OmSomKqYEaccpg5VTByuAqtqLvlZR/IRIREZG8aVQKqJSA3SHHKXvOCqnWLRrXP8pdQpwGAJBXXP8fNElaXFP2tGppv/dWqRRQqxSw2QVWSBHJRIMCqenTp3vcXrlyJdLS0qpt53A4cP78eZw7dw7XXHNN40ZIAadSKdA8RoPmMZp6t3U4BJSa7NWDKvG2Ddl5pSgtF2A0K2C1VZZe2R1AQYkNBSW2eo+jUAAxEeoagqvqPa9io9SSbsBIRERETY9CoYBBq4Kx3C6rQMpsdYjT6vw1ZQ8A4mNdgRQrpJoaV7ijk/B0PRe9Rgmj3c5V9ohkokGBlHv4pFAokJWVhaysrBq3VSgU6Nu3L5566qnGjZAkRal0TtGLjVSjfVLN22RmZgIAunXrhotmh2dwVeqaKuhWjVVxn8mtP4MgAMVlNhSX2YCc+scVpVe59bhyC64q7nP1vGoWpYZeq/LHt4KIiIhkTqdVwlhuh8liD/VQ/Ca7sLKCyZ9T9lxV+fmcstfkWCoCKSn3j3LRaRUwlgPlrJAikoUGBVIbN24EAAiCgGuuuQYzZsyoVjUFACqVCjExMYiIiPDPKKlJUigUiNSrEKlXITm+/jc85RaHc+pgqdWtx1VFiOWaRljmvF1q8nxjaCy3w1hux9m8+pu267XKyuAqWi1OI4yLrLztCrQi9WzaTkREFK5cK+3JqULqfMV0PaUCSGpWf3W8t1wVUsZyO0xmOww6/gGwqTBXzGjQSniFPRdXFRd7SBHJQ4MCqeTkZPHfzzzzDHr16uVxH1Fj6LVK6LVaJDWrv5+B1eZAcZkdRRWVVxdq6ndV8V9xmQ0Ot6recosD2RYLsi/U3+NArVK4BVSe/a6qTiOMjlCx7xUREZGMuFbak9Mqe1kVgVRinBYaP7Y8SIitfP+WV2xFu0QGUk2Fq0JK1wRaYIiBFCukiGTB56bmr7/+Om688UYMGDDAn+Mh8opGrUR8rFL8a1xd7A4BpRdt9QZXrsds9sr0ymYXkF9sRb4X/RCUCiA2sp7gKlqNuEjn/WoVwysiIiIpc620J6dV9s5VrLDXyo8NzQF4vCfLK7KgXaLer/unwDGLU/ak/96UgRSRvPgcSMXExCAhIcGfYyEKCJVSUdEIXYMO9WwrCALKyh0eKw26elyJ1VilNnFKoXsJv0MALlQEW96INqjEvlbOKYSaytsV9zWLdoZXTaHJJBERkdwYZBhInRdX2PNf/yjAWekeE6FCyUU7G5s3Ma5V9prC+01XSMwpe0Ty4HMg1adPH7F5NZFcKBQKRBlUiDKo0MaLvLXcYhf7XLn3uHIPtFz3Gcs9+16VmuwoNdlxJrf+vlcGndJt2qCm2jRC94qsCB37XhEREfmDQYYffl0VUv4OpABnlVTJRTvy2Ni8SbHYmlBTc7FCiqvsEcmBz4HUww8/jKlTp2L58uWYPHmyP8dE1GTotSq0aq5Cq+b1v6mz2BworjJt0CO4cps6WHLRBsHt96zJ7IDJbBHfRNZFq1a4BVUaMbgyl9kQbVDArDGKgVaUQQUl+14RERHVSF/RmFsuFVIWmwN5Ra5Ayr9T9gBnX6oT58uRV1z/+xWSDrPYQ0r67wn1FdMKOWWPSB58DqR+//13DB48GP/3f/+HZcuWoXfv3jVO4VMoFHjooYcaNUgiOdCqlUiI0yIhrv43gHa7gOKLNo8Aq+aeV8777G6/ky02AblFVuQWWQGYqu/8v8fFf6qUlX2vamvW3izaOX0wNlINFfteERFRGNFXVGOYzPZ6tmwaci9YxIVeWgWgQiqhoo+UN703STpcU/aaRIWUa6EBBlJEsuBzIDV37lwoFAoIgoCDBw/i4MGDNW7HQIqo4VQqBZpHa9A8WoOO9WzrcAgoK7d7Bldi3yubOKUwr+giSk2A1e09td0BFJbaUFhqA1Be53EUCiA6QlUZXLmCrOjKQCs2svK2tgms1EJERFQXg05eDZRdldYKBdCquf8rpOIr/uiWyyl7TUplU3Ppv3cTp+zJpGqRKNw1apU9Igo9pVKB6Ag1oiPUaJdY+3aZmZkQBAHtO3X17HlVEWC5B1quyqyLbstcCwJQUmZHSZkdp3PqH1ekXin2u3LvedUsSoNYj9tqGHRcGpqIiKRH72pqbpbHh99zFQ3NE2I1AQkfKiukLBAEgT0tmwhXD6mmMGWPq+wRyYvPgdSECRP8OQ4iCgKFQoEInQoROhVax9dfqm+2OjymCdbc88o5bbDkoud0hrJyB8rKzcjKr79pu06jrCG4UlcEV25N3KPViNKr+AaXiIiCQi+zVfZcgVQgpusBlYGU2Sqg9KIdMZE+f9SgIDI3pSl7DKSIZIW/JYioVjqNEknNtEhqVn9Zv80uoKSssrdVbcHVBaMNxWU2ONzeR5itDuRcsCDnQv1NUNUqhXNqYFTllEHnbY3HFMK4SDViItVQsWk7ERH5SG6r7J0vCFxDcwAefTLziq0MpJoIi6upeVMIpLRcZY9ITvhbgoj8Qq1SoHmMBs1jNAAMdW7rcAgoNdnr6HllFYOrC0YbrLbKNx02u4CCEisKSurvT6FUADGRbhVXriArunL1QfG/SDU07HtFRERu9Dp5Vki1DlCFVIsYDRQK5zT/vGILOreu+/0ASYNF7CEl/T/i6Vyr7MnkNUkU7hoVSF28eBFLly7F1q1bkZOTA4ulenWDQqHAr7/+2pjDEJHMKJXOKqfYSDXaJ+nr3FYQBFw0O3ChtKLfVZmtes+rMlvF4zaPDw0OAWKF1ikvxhVlULlNFfRcfdDzfo04jYOIiORLr3H2OCy3OOBwCFA24apbm10QK5EDNWVPrVKgebQaBSU25LGxeZNhrvjDn64J/GFOzyl7RLLicyBVXFyMKVOm4MSJE4iKioLRaER0dDSsVivKy52rdSUmJkKtZhEWEflOoVAgUq9CpF6FNgn1v4EutzicwZXRreKqSrN21/1Gk2ffK6PJDqPJjjN59fe9MmiVHhVWzdwauMe5BVfNotWI0CnZ94qIqAlyrbIHOBs/67VNdxGO3CIL7BWf4QM1ZQ8A4mO1zkCquP5p+CQNlia4yl45AykiWfA5Lfroo49w4sQJvPrqq5g4cSK6d++OGTNm4KGHHsLevXvx0ksvISIiAvPnz/fneImI6qTXKtGyuQ4tm9cfXlltDhSX2T16Xl0w2iqCK6tHoFVSZoPDrV2ByeKAqdCC84X1v+HWqBWIc5s6GBet8bhdesGBKD3QqsyGaIOqSf8FnohITtyrYU3mph1InS+o/GNLq+aBC6QSYjU4fAaskGpCKpuaS//9R2UPKQdXciSSAZ8Dqc2bNyM1NRWTJk3yuF+hUKBv3774/PPPccMNN+Djjz/Go48+2thxEhH5nUatRHysEvEVqwLVxe4QUHrRrcKq1NXjyireLjJW9sKy2SvTK6tNQF6xFXnF9bw5X30ASiU8m7ZHaapMIXRWXsVV9MRSq/hGjIgoUDwCKYsDzUI4lsY6V9HQvEWMOqDBmmulvfz6fueRJAiCAIutCTU1rxijw+GchqpR830QUVPmcyB1/vx5XHXVVeJtpVIJq7XyF0+LFi0wfPhwrF27loEUETV5KqWiIgiqP7wSBAHGcrvY66qyx1VNqw/aPPogOBzAhVLn9t6IiVDVG1y5bjeFUnwiIikxuAVS5U28ibKroXmg+ke5uFbaq/ePMCQJVrsAoeJvaNom0EPKPTQzWwVo2B2GqEnz+SVsMBg8SiSjo6ORl5fnsU2LFi2Qk5Pj++iIiJoghUKBaIMa0QY12ibWv/3efYdQagJaJLXz6HlVNbgqMlpRVu75gajkoh0lF+34K7f+vlcROqVbc3aN2xRCdcUUQo1426Bl3ysiIr1OToGUs0IqUCvsuSTEOf9wU1Bihd0hQMVp6JJmsVZWdOuaxJS9yjGarQ5EGZruNFoiakQg1bJlS2RnZ4u3O3fujF27dsHhcECpdP7y3r17N+Lj4xs/SiIiGdNpFNBpgJT2kfVua7E6KqYK1hVcOe8vvWgX/+oJABfNDlw0W5BVUH/fK51GUTF1UIO46MrKq7hIdcXtykAryqBieEVEsqTXePaQaspcPaQC2dAcABJinfu32QUUGW1oEVN/ZTGFjsWtSrspVFK7vybNTTwkJqJGBFKpqalYt26d2ExuzJgxeOWVV3Dvvfdi5MiR2LFjB/bu3YspU6b4c7xERGFNq1EiIU4rTomoi90uoPiiza3HlVXsceXqeXXBaEVxxX12t/d1ZquA3CIrcr1oSqtSomJqoKYyuKqy+qCrMis2Us2/lhNRk6FRK6FWKWCzCyi32Ov/AomyOwRxEY6AV0i59WXMK7IwkJI4s63yl39T6iEFwKPlARE1TT4HUhMmTIDVakV2djZatWqFW2+9Fdu3b8evv/6KrVu3AgD69+/P/lFERCGiUinQPFqD5tEaoFXd2zocAowme2WPqzKr2AOrptUHLbbK0iu7AygosaGgpP6+VwoFEBOhriG4qt7zKjZK3ST6WRCRvOm1ShhN9iY9ZS+/2CouttEqwBVScVFqMcTLK7YiJaBHo8Zyn7LXJFbZcwukyhlIETV5PgdSPXv2xL///e/KHanVmDt3Lvbv34+//voLycnJ6N27tzh9j4iIpEupVCAmUo2YSDXaJ9W9rSAIuGh2uE0VtNYaXF0w2jymuQgCUFzmbPQOL1oMRulVbj2u3IKrivtcPa+aRQV21SgiCl+GikDK1IQDKVdDcwBo1TywFVJKpQItYjTIuWDhSntNgHuVka4J/BFIp2WFFJGc+BRI7d69GxkZGVAoFOjTpw/69+8vPtarVy/06tXLbwMkIiJpUSgUiNSrEKlXITm+/g82ZqvDrceVtUpw5RZoldpQavKcEmMst8NYbsfZvPqbtuu1ysrgKlotTiOMi6y87Qq0IvVs2k5E3tFXfABuyhVS5yt6B8ZFqRGpD3x4nxDnDKTyiurvWUih1dR6SGnVbk3NLUIdWxJRU9CgQMrhcOCxxx7D+vXrPe4fNWoU3n33Xb65JyKianQaJZKaaZHUrP5pIja7UNG0vXLKoNjEvdStiXtFlZXD7fNhucWBbIsF2Rfq/wCkVincAirPfleu/4ouOBBtUHCVKKIwJ4dA6lyQGpq7uPpI5bJCSvLMTWzKnkKhgE6jhNnqYIUUkQw0KJBavnw51q1bB71ej0GDBkEQBKSlpWHdunW47LLLcPPNNwdqnEREFAbUKudUD2+a4DocAkou2sUKq8qKq5pXH3T1TwGcwVd+sdWr6STK7zIQG1l7cFUZamnE3ilEJB8GnTOQksOUvUBP13NxrbSX78XCGBRaloqm5goFoGkiv790WgXMVuCtb0/j7eV/1bpdlF6FZ29rj14do4I4OiJqiAYFUqtWrYJOp8Py5cvRpUsXAEBmZiZuvvlmrFq1ioEUEREFjVKpEEOhDvVsKwgCysodzpUGjZ7N2ovcwivX/e6VEA4BuFDxmDeiDSrPHlcVPa+aRbn1wop2hldNYUUjonDnWma+3Nx0AynXlL1Ar7Dn4qqQyivmlD2pc1UZadVNZyp7u0Q99p8sg93hXEGyNheMNqzcms9AikjCGhRIHTt2DNdcc40YRgFASkoKrr32Wvz+++9+H5wvBEHAmjVrsGXLFuzfvx85OTmIiopCx44dMX36dFxzzTVeX2ynTZuGtLS0Gh97/vnncfvtt/tz6EREFCAKhQJRBhWiDCq0Sah/+3KLHbv3HkFpuYDYFsnilMGiMs9Aq6jUBmO5Z9+rUpMdpSY7zqD+vlcGnbJahVX1FQid90foms6HBSI50eucPZea6pQ9h0PA+cLgTtmLj3MGUheMNlhtDmiaQLPscOVaZU/XBKbrubwwrSMyThjhEGoPo/adKMPq/+Vj95FSmK0O/gGISKIaFEiVlpaiXbt21e5v27YtjEaj3wbVGBaLBU888QS6deuG6667Dm3btsWFCxfw/fffY9asWZgyZQpefPFFr/fXrFkzPPPMM9Xu79Onjx9HTUREUqLXqtAiWoEW0QqkpMTWua3V5kBRWUWFValN7HFVVFq5+qB73yv3988mswMmswXnCuqvItCqFW5BlabW4KpZlBpRBhWU7HtF5BcGrWvKnr2eLaWpsNQm9glqFaQKqcQ4Z/AlCM7je9NDkELD1dS8KQU2UQYVhvas+3dzt7YRWP2/fJitDuw5ZsTg7jFBGh0RNUSDAilBEKBSVV+ZQ61WQ6gjoQ4mlUqFr776CkOGDPG4//bbb8eECROwbNkyTJ061aPKqy4REREYN25cIIZKREQyoFErkRCrFXum1MXuEFBS5jk9sLaeV8Vlnn2vLDYBuUVW5BZZAZjqPI5KCbHvVc09rzTOlQcj1YiNVEPVRPqGEIVCU29q7uofBQCt44Pb1BwA8oosDKQkzFzRQ6oprLDXEAmxWnRJNuBolgnbDxUzkCKSqAYFUgAkP11ArVZXC6MAZ7B05ZVXYuHChThy5IjXgRTgXF2wrKwMkZGRUCrldbEmIqLgUSkVaBatQbNoDTrWs60gCDCa7PUGV0UVfbDcV0qyO5xVCYWlNgDldR5HoQCiI1SVwZXY56oy0IqNrLyt5dQbCjOuQMrURHtIuQKpaIMK0YYGv/X3SZRBJa6ElsvG5pLWFKfseWtI91gczTJhx6ESOBwCK4eJJKjBv5Xmzp2LuXPn1vhY9+7dq92nUChw8ODBho8sAHJycgAALVq0aNDX9OvXD+Xl5dBoNBgwYAAeeughDBo0yC9jcjgcyMzM9Mu+pMJkcv7lXm7Pq6njeZEunhtpktJ50QJI1AKJzQE0r/qoAoKggdkGGE1AabmAUpOA0nKg1CTAWO7+b+f/y90+HwoCUFJmR0mZHadz6h+LXgNEGxSI0jv/Hy3+3/0+BaINgfuAE8xz43A4+McoCQnF+yZjiXNBg2KjqVHHDtU1Zd8R5/ibRQb3exdrEJBrBQ4ey0JrgxcXF5mQ0u8Ob5zLdv582G3mJjNmb7U0OEPkC0Ybftl6CB0S/HMtb2rnmBqO59h3DX3f1OBAqqFT86Qyle/AgQPYsGED2rdvjwEDBnj1NcnJybj00kvRrVs3GAwGZGZmYvHixZgxYwbefvttjB07NsCjJiIiqp9CoYBe4wyL4mPqD4GsdqFaeGUsF1BqQsVt57+N5QIumgH33+TlVqDcKiCvBPB8pDqtGs6QSq/wCLGiKgKraLf/G7TSr8Km8KRVO38u3asQm5L8Uue4E7y4NvhTXCSQWwIUlTXN71u4sFa0RtNU78rS5LVqpkDzKKDQCOz/y+G3QIqI/KdBgVQwE8I5c+Z4vW2fPn0wYsSIWh/Pzc3FrFmzoFQqMXv2bGg0mlq3dffGG2943L7mmmswadIk3HjjjXjppZcwcuRIGAwGr8dZE6VSiZSUlEbtQ2pcPydye15NHc+LdPHcSBPPi5PdLqC4zDU90Fqt/5XHVMIyGxxus5osNucHgUKjgPrCK7VK4ZwaGFU5ZdB5W+MxhTAuUo3zZ45BqVQE5dykp6cH/BjkvVC8bzptLADSzsIuqBt17FBdU4y/HAZQjpSOCUhJaRm047bf/xeOnL8AmzIKKSn1TVKWj6b2uyMy8yyAAjSLjUJKSqdQD8fvhvXJwqpt+TiS27jXr7umdo6p4XiOfdfQ903BmUjug9qmBdZk6tSptQZSeXl5uOOOO5CXl4f3338fl156aaPG1apVK9x0001YsGAB0tPTMXTo0Ebtj4iISMpUKgWax2jQPEYDoO4/wjgcAkpN9np6XlWGWlZbZUhlswsoKLGioKT+fjMKBRCpA+LjDqNZlFoMsvp1iUZqNzauJf8yaJ2lI02xqbkgCOIqnq2DtMKei2ulvbyi+lcRpdBxrbInt6bmLkN6xGDVtnycyTUjK9+M5Pjgvg6IqG6SDaQOHz7c6H3k5ORgxowZyMrKwocffoiRI0f6YWRAmzZtAAAFBQV+2R8REZEcKJXOKqfYSDXaJ9W9rSAIuGh2eAZXpc4qK/dm7Rcq7nNvKC0IgLEcMGaX45TbPldty8d3/9cLkXoZzj2hkHE1NTdbHbA7BKiaUGPkC0abGKS1ahHcle5cK+3lsam5pLkCKZ1MF6zo1SEKUXoVjOV2/O9gMW4anhjqIRGRG8kGUo2VnZ2NGTNm4Pz585g3bx6GDx/ut32fPHkSABAfH++3fRIREYUThUKBSL0KkXqVV3+xLrc4nFMHS63Yn3kKxnJAFx3vDLGMVlww2tClTQQidPL8UEWh4wqkAGcoFaFrOoGna4U9IPgVUvGxzgCs1GRHucXh8X0k6TBXVKpqZbjKHuCcDp6aEo1Ne4qw/VAJAykiiZFlIHX+/HlMnz4deXl5+OSTT+qdVpebm4vS0lK0bt1a7AlVUlKCyMhIqFSebzqOHz+O77//Hi1atED//v0D9hyIiIiokl6rhF6rRVIzLXDR+bs5JaWeMiwiPzC4hZzllqYVSJ2vmK4XqVciJiK4406Iq+zZml9sQZsEfVCPT94xV1TQ6WQ6ZQ8ALusRi017inDodBmKjDbERcnyIzBRkyS7V6PRaMS0adNw5swZTJ48GXl5eVi1apXHNt26dfNoUPbuu+9i5cqVWLRoEQYPHgwASEtLw2uvvYarrroKbdu2hV6vx5EjR/D999/Dbrfj7bffhk7HOchEREREcmZwq+wpNzuA6BAOpoFcFVKtW+iCvoqla8oeAOQVWxlISZTF5uohJc8KKQAY0DUaapUCNruAtMwS/G1g81APiYgqyC6QKioqwpkzZwAAy5cvx/Lly6ttM2vWrHo75nfs2BF9+vTB77//jry8PFitVrRo0QLXXnst7rnnHnbcJyIiIgoDOrdAytTEGpu7Gpq3CvJ0PQAw6FSIMqhgNNnZR0rCzFbnlD259pACgAidCn07R2HXkVJsP1TMQIpIQmQXSLVp06bBDdHfeOMNvPHGGx73de7cGe+//74fR0ZERERETY1rlT2g6a20d16skApuQ3OXhFhNRSDFlfakSu6r7LkM6RGDXUdK8efRUpitDllPUSRqSmQXSBERERER+Yt7M+6lG7PRIkZT67YtYjSYeEUCYiJD/xZbEASPKXuhkBCrwcnscuQVs0JKqsxW+U/ZA4Ah3WMx94csmK0C0o+VYkj32FAPiYjAQIqIiIiIqFZqlUJcNj79mLHe7XcdKcWb93ZGpD60zc9LLtpRVu4MG1qFqEIqPs553LxiVkhJlaVilT25Vwy1iNGgaxsDjpw1YfvBEgZSRBLBQIqIiIiIqA6PTmqDLRlFEITat7E7BPzvYAmOnzPh/xaewKt3dYJeG5hQqqDEihV/5KGkzFbrNkaTXfx3KCukALBCSsLECikZ95ByGdIjFkfOmrAjswR2hwCVUt5VYURNAQMpIiIiIqI6XN4rDpf3iqt3ux+352PeqiwcPH0RLy0+hRdndPT7B/2jWRfx70UnUVBSexjlLkqvQrMQLXPvCqTyi6wQBCHoK/1R/Vw9pHQyn7IHAJd1j8GiX7JRZLTh8JmL6NE+MtRDIgp7DKSIiIiIiPzg+iHxMJkdWLDuPNKPGfHGstN49rYOUKv882H/931FeGf5XzBbBeg0CgzsFoO69qxUAFf2bRayICihYsqeyeJAWbkDUYbQTmMkT3a7AHtFn365NzUHgPZJerRsrkV2oQX/O1jMQIpIAhhIERERERH5yeQRibhotuObTbn438ESvPufv/D45HaN2qcgCPhmUy4WbcgGALSIUeP/pnVE1zYR/hhywCTEVTaAzyuyIMpgCOFoqCqzrXLVSLn3kAIAhUKBy7rHYOXWfGw/VIK7R7cO9ZCIwp78rzxEREREREE0/dqWGDc0HgCwaU8R5q3OglBXA6o6WKwOvPXtX2IY1SXZgPcf7Cr5MAqAx4qE7CMlPa7pegCgVct/yh7g7CMFAGfzzDibVx7i0RARAykiIiIiIj9SKBS4b2xrXDugGQBg7Y4CrNltb3AodaHUiqc+P47Ne4sAAFf0isVb912C+FhN3V8oEVq1UuxfxZX2pMdsrfx5DIcKKQDo2T4S0RVTR7cfKgnxaIgoPK48RERERERBpFQq8PeJbTGst7MiY9MBOzZk2Ov5qkonz5vw93lHkXnmIgBgylWJeGZKe+i1Tevtuys8yytihZTUeFRIhUkgpVIpMCglBgDwv4PFIR4NEYXHlYeIiIiIKMhUSgWeuLkdBnaNBgD8vMeOH7bm1ft12w8W47FPjiGv2AqNWoEnb2mH6X9rBWUTXKbe1dg8n1P2JMe9h5Q2DFbZcxnSwxlIHfrrIoqM/LkkCiU2NSciIiIiChCNWonnbu+Af87bj+M5Aj798Ry+WHuuzq9xrXzWLEqN56d1QPd2TXc1sISKCqncIk7ZkxqL+5Q9dfjUKQzoEg2NWgGrTcCOzBJcN7BFqIdEFLbC58pDRERERBQCOo0S91ytQbt4ZxWK3VH3fwDQsaUe7z/UpUmHUUDlSntsai495jCcsgcABp0KfTtHAQC2H2QfKaJQYoUUEREREVGA6TUKPDJag3J1G48goCY6jQK9O0bJIiRIiK2csudwCE1y2qFcuVdIhcsqey5DesRi5+FSpB8rRbnF0eR6sxHJBQMpIiIiIqIgUCkVGFDRTypcuKbs2ewCistsaBbdNFYIDAeWih5SGrUi7ILCISkxmAPnSoNf/5aNtgl6r7/2/Hnn4gRnygoDNDoKtXA5xx1a6tElOSKkY2AgRUREREREAREfVxlA5RVbGUhJiKtSL5z6R7k0j9GgW9sIHD5zEcu31L/QQM3O+HVMJEXyPscKBfDVU93FStZQYCBFREREREQB0TxaA6UScDiAvCILurYJ7V/jqZJryl44rbDnbspVSfho9VmU1zOFtiq7zVk9o1KrAjEskoBwOccdWxoQFxnaSIiBFBERERERBYRKqUB8jAa5RVY2NpcYV4WUHHqV+WJw9xgM7t6jwV+XmZkJAEhJSfH3kEgieI6DJzyvPkREREREFBTxsVxpT4pcPaR0YRpIEVHo8epDREREREQBI660V2QJ8UjI3ZlcMwDAwBXmiChEePUhIiIiIqKASYhjhZTUnC80Y/PeCwCAoT1jQzwaIgpXDKSIiIiIiChgOGVPer7dlAu7A4iJVOGGy1qEejhEFKYYSBERERERUcAkxjmn7BWWWGG3CyEeDZ0vNOPXPwsBAJOHJ0KvlfdKYkQkXQykiIiIiIgoYBIqKqQcAlBQyiqpUPumojoqNlKN64ewOoqIQoeBFBERERERBUx8RVNzAMgrYiAVSu7VUTcNT2B1FBGFFAMpIiIiIiIKmNhIFbRqBQAgr5gr7YXSN5ty4WB1FBFJBAMpIiIiIiIKGIVCITY2z2dj85A5V8DqKCKSFgZSREREREQUUAkVjc1zi1ghFSrfbMqBwwHERbE6ioikgYEUEREREREFVAIrpELqXIEZG9MvAGB1FBFJBwMpIiIiIiIKKFcgxabmoeFeHTV2MKujiEgaGEgREREREVFAxVdM2ctjhVTQncuvrI6aPDyR1VFEJBkMpIiIiIiIKKBcFVLFZTZYrI4Qjya8fLO5sjpqDKujiEhCGEgREREREVFAuQIpIPB9pMrK7TiadRHbDxbjQml4V2RVr47ixz8ikg51qAcQCN9++y3WrVuH48ePo6ioCAaDAcnJyRg3bhxuueUW6PV6r/e1c+dOzJkzB/v27QMA9O7dGw8//DBSU1MDNXwiIiIiIllxrbIHADlFFiQ119axdf1sdgHZhRaczTcjK9+McxX/z8o344LRJm5n0Cpx61WJGH95ArSa8AtjXNVRzVgdRUQSJMtAav/+/WjevDmGDBmC5s2bw2QyYefOnXjttdewYcMGfPXVV1Cp6p87/fvvv+OBBx5AUlISZs2aBa1Wi++++w533HEHPvnkEwwbNiwIz4aIiIiIqGmL1KsQoVPiotmBZ+efCNpxTRYHvlyfjZ93FuK+sa0xpHsMFApF0I4fSh7VUSNYHUVE0iPLQOrll1+udt/06dPx4osvYtmyZdi5cyeGDBlS5z7sdjteeOEFaLVaLFmyBK1btwYAjB8/HmPHjsWLL76IX375xatgi4iIiIgo3HVvF4ndR0v9uk+lEmjZTIvkeF21/zQqBRZtyMb6XYXILrTgpcWn0O+SKNx/fTLaJ3k/Y6KpWrapsjpq9CBWRxGR9MgykKqNK1QqKSmpd9tdu3YhKysLEydOFL8OAKKjozF58mTMnTsXu3btwuDBgwM2XiIiIiIiuXju9g449FcZ7Hah0ftSKBRIaqZFUjMNNOraK3/+PrEtxg5pgU/XnMP+U2VIP2bEgx8extjBLTDtmpaIjqj945DJbMf5QgvOFZhhMnvXiP38eTsA4ExZYcOekJ+ZrQ78tofVUUQkbbIOpEpLS2G1WmE0GrF792588cUXiIqKwsCBA+v92r179wIA+vXrV+0x130ZGRmNDqQcDgcyMzMbtQ+pMZlMACC759XU8bxIF8+NNPG8SFcwz43D4YBSyQ9yUtGU3zfxmuJk8NeOBMBY4PzPG3cNF7CnvRqrd9lQVAas+V8BNv5ZgNF91eiQoEB+qYD8UgF5JQLySwTklQooNTVmgGca88V+E20AOsflIzPTy28U1YuvZfnjOfZdQ983yTqQmjFjBg4cOCDe7tu3L/71r3+hefPm9X5tTk4OACApKanaYy1btvTYRkpmz56NdevWAQBGjRqFJ554IsQjIiIiCqx169Zh9uzZAIAnnngCo0aNCvGIKFycPXsWM2bMAAB89dVXaNOmTZPav1THE4jjKBQK9OugQs82Smw6YMfGfXZcNAPf77DVuL25JAuHf7gXANB94ueIa5Hs1XEEOKu/FGhYnypTcRb2fOc8Xt+bP4ch1rvj1UWjAm5MVUOrll7PLKn9bFcl9fHJAb/HBEg4kJozZ47X2/bp0wcjRoyodv+LL74Io9GIvLw8bNu2DSdPnkRxcbFX+3Slolpt9RVAdDqdxzaNoVQqkZKS0uj9uMTGxnr825/79pYrSQ7Fsal2PC/SxXMjTTwv0lX13OzZs0d8rGXLln49Z+np6X7bFzWev983NZb7+8ROnTqhU6dOtW7ryzWlIfsPhmCNJ9DH6dMLmHKdBQt+Po8tGUUAALVKgVbNtWjVQofkFlqoLDb83w/O7T95tBsu6dzZq337+rvjxIloDPvO+e85D6eE/FwHmtR+tquqa3x8f+AfUv4Z4Dn2XUPfN0k2kJo7d67X206dOrXGQKpPnz7iv8eNG4cFCxbg3nvvxZIlS+qdtmcwOAuKLRZLtcfMZrPHNkRERERE1HQkxmnx9JT2uGt0KwgCEB+rgUpZWUl04oRZ/LcyTFblIyIKNskGUocPH/b7PsePH48333wT33zzTb2BlGuqXk3T8rKzsz22ISIiIiKipicxrvpsCCIiCo6w6tLpqmzyZpU9V3VVTSVnrqkB7hVYRERERERERETkHdkFUmazudbA6auvvgJQfeW8c+fO4fjx47BareJ9qampSE5Oxrp163D+/HnxfqPRiOXLlyM5Odmr1fqIiIiIiIiIiMiTZKfs+SovLw/XX389rrnmGnTp0gXNmzdHYWEhNm3ahPT0dPTo0QPTp0/3+JqnnnoKaWlp2Lhxo9jdX6VS4YUXXsDMmTMxdepUTJs2DRqNBt9++y3y8vLw8ccfQ6VSheIpEhERERERERE1abILpOLi4nDzzTdj165d+P3331FaWoqIiAh07twZTz75JKZOnQq9Xu/VvkaMGIEFCxZg3rx5+PDDDwEAvXr1woIFCzBkyJBAPg0iIiIiIiIiItmSXSAVFRWFZ599tkFfs3jx4lofGzJkCMMnIiIiIiIiIiI/kl0PKSIiIiIiIiIikjYGUkREREREREREFFQMpIiIiIiIiIiIKKgYSBERERERERERUVAxkCIiIiIiIiIioqBSCIIghHoQ4Wr37t0AAKXSf7mg2WyGzWYDAKjVauh0Or/t21sOhwOAf58XNR7Pi3Tx3EgTz4t0VT03NpsNZrMZAKDT6aBW+28RYdexBgwY4Ld9km8C8b6psRwOB0wmEwDAYDDUOTZfrikN2X8wBGs8Unjevo7B198dUnjOwST151vX+Pj+wD+k/DPAc+y7hr5v8t87NpIEnU4XkhDKHV+40sTzIl08N9LE8yJdVc+NWq32awhF5C2lUonIyEivtw3k/oMhWOORwvP2dQy+/u6QwnMOJqk/37rGx/cH/iHlnwGe4+BhhRQREREREREREQUVoz8iIiIiIiIiIgoqBlJERERERERERBRUDKSIiIiIiIiIiCioGEgREREREREREVFQMZAiIiIiIiIiIqKgYiBFRERERERERERBxUCKiIiIiIiIiIiCioEUEREREREREREFFQMpIiIiIiIiIiIKKgZSREREREREREQUVAykiIiIiIiIiIgoqBhIERERERERERFRUDGQIiIiIiIiIiKioGIgRUREREREREREQaUO9QCo6btw4QLef/99bNy4EUVFRUhOTsakSZNw1113Qa327kds5MiRyMrKqvGxTz75BFdddZU/hywrv/zyC7744gscOXIEGo0GAwYMwKOPPoqUlBSvvt5kMmHevHlYu3YtcnNzkZiYiDFjxuChhx6CwWAI8OjlqzHnZcWKFXjmmWdqfKxnz55YsWKFv4cbFj777DMcPHgQBw8exF9//QVBEHD48OEG74evGf/zx7nh64aaooyMDKxevRqHDh3CoUOHUFZWhlmzZuHhhx8O9dCogRr7foykzV/vIUi6Tp06hTVr1mDr1q04c+YMysrK0Lp1awwdOhT33XcfEhMTQz1EWWIgRY1iNBpx++234+TJk7jtttvQrVs37Ny5E++88w6OHj2K2bNne72vTp064YEHHqh2f48ePfw5ZFlZvnw5nnvuOXTt2hWPP/44zGYzlixZgilTpmDZsmX1vgmy2+247777kJaWhnHjxiE1NRWZmZlYsGAB9u7di4ULF0KlUgXp2chHY8+LywMPPIBOnTp53BcXFxeAEYeHd955BzExMejevTsuXryIvLy8Bu+Dr5nA8Me5ceHrhpqSLVu2YOnSpejQoQN69uyJtLS0UA+JfOCv3/skXf78PUXS9J///AdLly7FVVddhdGjR0Ov12PPnj34+uuvsXr1aixbtgydO3cO9TDlRyBqhPfff1/o2rWrsGDBAo/7X3rpJaFr167Ctm3bvNrPVVddJdx+++2BGKJsFRUVCf379xeGDx8ulJaWivdnZWUJffv2FW677bZ697F8+XKha9euwssvv+xx//z584WuXbsKy5cv9/u45c4f5+X7778XunbtKmzfvj2QQw07p0+fFv99++23C127dm3wPviaCQx/nBu+bqgpysvLE4xGoyAIgrB9+3aha9euwocffhjiUVFD+OP3PkmfP35PkbRlZGQIxcXF1e7/5ptvhK5duwqPPPJICEYlf+whRY2yatUqGAwGTJkyxeP+O++8U3y8IWw2G4xGIwRB8NsY5Wrjxo0wGo2YPHkyoqKixPtbt26N6667Drt27cLZs2fr3Ifr/LjOl8ttt90GvV7f4PNH/jkv7srKymCxWAIx1LDTrl27Ru+Dr5nA8Me5ccfXDTUV8fHxiIyMDPUwqBH8/XufpMnfv6dIenr37o2YmJhq948dOxYAOEUzQBhIkc/y8/ORlZWFlJQU6PV6j8fatGmDhIQEZGRkeL2/vXv3om/fvhgwYAD69euHmTNnIjMz09/Dlo29e/cCAPr161ftMdd9dX3/BUHAvn37kJiYiOTkZI/H9Ho9unfvjv379zMcbKDGnhd3Dz74IPr374/evXvjb3/7Gz7//HPYbDb/DZYahK+ZpoGvGyIKJn/+3ici6cnJyQHg/AMC+R97SJHPsrOzAQAtW7as8fGWLVvixIkTXu2rc+fOmDhxIjp16gSlUol9+/Zh6dKl2Lp1KxYsWICBAwf6bdxy4bo41vT9d93n2qYmRUVFMJlM6NKlS42PJyUlIT09HcXFxey/0gCNPS+AM9wYPXo0hg4dioSEBOTk5OCHH37A22+/jd27d+Ojjz6CUsm/JwQbXzPSxtcNEYWCP37vE5F0ffDBBwCAiRMnhngk8sRAijBnzhyvt+3Tpw9GjBgBACgvLwcAaLXaGrfV6XTiNvX5/PPPPW6PGjUKY8aMwS233ILnn38eP//8s9djDBcmkwlAzd9/132ubWrizflz346809jzAgBjxozBmDFjPO675ZZb8Pe//x3r16/Hzz//LJYPU/DwNSNtfN1QqPj6PorkwR+/94lImj755BOsX78e11xzDSZMmBDq4cgSAynC3Llzvd526tSp4hsp1zS92vp0mM3malP5GqJnz54YOXIk1q9fj9OnT6N9+/Y+70uOXMvL1/T9d91X1xL03pw/9+3IO409L7VRKBSYNWsW1q9fj02bNvGDdQjwNdP08HVDweDr+yiSh0D93iei0Prqq6/w3nvvYdCgQXj77behUChCPSRZYiBFPjdoc5Uhu6buVZWdnV3rdD5vufq0FBQUMJCqIikpCYDz+1x1CVLXOXFtU5O4uDgYDIZaz19OTg4iIiIQGxvrpxGHh8ael7q0adMGAFBYWPj/7d17TFflA8fxj9yMBCJDVKBfGc0vOiCRS+IlhIEZiYbp0i0VTZup2MzmpVIzM13eB17CzEl4mamAijcUTVsTRDR0iRWlEzDQTAUVucjvD8d3IWTK5YvI+7W56XPO9+F5zuF4nn2+z3lOHVqI2uKaaZq4btDQWOi2eWvI+z6AxrF27VrNnz9f/v7+WrlyJaFyA2IxBdSag4ODnJyclJWVVe0RldzcXF26dEmenp51+hnnzp2TJLVp06ZO9TyOKo/tiRMnqm07efKkpLtvi/g3LVq0kLu7uwoKCpSbm1tlW3Fxsc6cOSN3d3e+DXhIdT0v91N5PbCoYuPgmmmauG4ANKSGvO8DML2YmBjNnz9fvXr10ldffUUY1cAIpFAn/fv3161bt7Rx48Yq5WvXrpUkDRgwoEp5Xl6esrOzVVpaaiz7+++/a6w7NTVVhw4dUseOHfXss8/Wc8ubvuDgYLVq1UrfffedioqKjOV5eXnas2ePvL29jcft1q1bys7OVkFBQZU6Ks9P5fmqtHHjRhUXF6t///4N3IvHT32cl5quidLSUi1atMj4M9CwuGYeXVw3AB4lD3PfB/BoW7VqlRYtWqTAwECtWLHCuD4oGg6P7KFOxowZo71792rBggXKzc2VwWDQsWPHlJiYqH79+snf37/K/lOnTlVaWpoOHDhgfIwiMTFRmzdvVq9eveTi4iIzMzOdPn1a27dvl7W1tebOndsYXXvkPfXUU5oyZYpmzZqloUOH6q233lJJSYni4uIkSZ988olx38zMTA0fPlzh4eGaP3++sXzgwIFKSEjQt99+q8LCQvn4+Ojs2bPasGGDfHx8eJtELdTHeQkLC5O3t7c6duwoR0dH5efnKykpSb///rtef/11hYSEmLxfj4OEhATl5eVJknGG04oVK4zbx40bZ/w714xp1ce54bpBU5Sbm6vExERJUk5OjiTp2LFjxt9/X19f+fr6Nlr78N8e5r6Pputh7lNomtavX68lS5bIwcFBISEhNb5U697JFqg7AinUiY2NjTZs2KClS5dqz5492rRpk5ydnfXBBx9o1KhRD1SHh4eH0tLSlJycrCtXrqisrExt27bVm2++qTFjxvCt0n0MGTJE9vb2WrNmjRYsWCBLS0t5e3tr0qRJcnNz+8/Pm5ubKyYmRsuXL9fu3buVlJSkNm3aKCIiQuPHj5e5ubkJevH4qet5CQsLU1pamo4ePaqioiJZW1vLYDBozJgxCg8P55GwWtq6davS0tKqlFW+yld6sMEk10zDqI9zw3WDpignJ6fK77p0d4Z4amqqJGnChAkEUk1AXe/7ePTVx30Kj7ZTp05Jki5fvqyPPvqoxn0IpOpfi4qKiorGbgQAAAAAAACaD9aQAgAAAAAAgEkRSAEAAAAAAMCkCKQAAAAAAABgUgRSAAAAAAAAMCkCKQAAAAAAAJgUgRQAAAAAAABMikAKAAAAAAAAJkUgBQAAAAAAAJMikAIAAAAAAIBJEUgBAAAAwCMsJydHBoNB06ZNa+ym1JrBYNCwYcOqlEVFRclgMCg1NbWRWgWgMRFIAWiWUlNTm/zADgAAoCFs27ZNBoNBUVFRjd2UJsNgMCgoKKixmwE0KRaN3QAAAAAAwL9r27atdu3aJVtb28ZuCgDUGwIpAAAAAHiEWVpaytXVtbGbAQD1ikf2ADQ7UVFRGj58uCQpPj5eBoPB+Gfbtm3G/Y4ePaqxY8eqW7ducnd3V2BgoD799FNdunSpWp3Dhg2TwWDQhQsXtG7dOvXr108eHh4aN25cte1xcXEKDQ2Vh4eHgoKCtGrVKlVUVEiSdu/ercGDB6tLly7y9/fXZ599puLiYhMcFQAA8KiqaQ2padOmGddf2rNnjwYNGqSXXnpJfn5+mjRpkvLz86vVc+HCBc2cOVN9+vSRp6enfH199dprr2n69OnKy8sz1jt9+nRJUnR0dJVxUuVaT4WFhfr66681fPhwvfLKK3J3d1e3bt00duxYZWRk1Lm/lY+/3bhxQ1988YUCAgLk6empAQMGaP/+/ZKksrIyrVq1Sq+++qo8PDwUHBysuLi4f62zNuO6nJwcbdq0SWFhYfLw8FD37t01Y8YMFRYWGvetXAZCknJzc6scL5aGAO6PGVIAmh0/Pz+Fh4crPj5ebm5uCg4ONm7r1KmTJCkmJkaLFi2Svb29AgIC5ODgoLNnz2rjxo1KSUnR5s2b1a5du2p1f/7558rIyFBAQIACAgLUqlWrKtu//PJLpaenq3fv3vL399fevXu1ZMkSlZWVycbGRsuWLVNwcLC8vLx06NAhrV+/XuXl5Zo9e3bDHhQAANAkbdiwQSkpKQoKCpKvr68yMzO1a9cuZWVlKTExUVZWVpKkgoICDRo0SEVFRerVq5eCg4NVWlqqixcvat++fQoLC5OTk5OCg4N1/fp1HThwQH5+fvLz8zP+LGdnZ0lSdna2li5dKh8fH/Xu3Vt2dna6ePGiUlJSdPjwYa1cuVIBAQF16ldpaalGjRqlwsJChYSEqKioSDt37lRkZKS++eYbxcXF6cyZM+rZs6ckKSkpSXPmzFHr1q0VGhpapa7ajusWLFigH374QYGBgerRo4dSU1O1efNmnT9/XrGxscZjMmHCBEVHR8vW1lYjRowwfr5yXAmgZgRSAJqdl19+WdLd2VGdOnVSZGRkle3Hjh3T4sWL1aVLF61evVp2dnbGbQkJCZo6darmzp1b40KfP//8s+Lj4+Xi4lLjz87KytKOHTvk4OAgSRo5cqT69u2rNWvWyNraWvHx8Xr++eclSZGRkQoJCdHWrVs1ceJEPfPMM/XRfQAA8Bg5cuSItmzZYpylI0mTJ0/Wzp07tX//fmM4s3fvXl29elXTp09XRERElTpKSkpUWloqSdUCqXvHSZLk6uqqw4cPq3Xr1lXK//zzTw0aNEjz5s2rcyBVUFCgLl26KC4uTpaWlpKkHj166MMPP9T777+vF154Qdu3b5eNjY0k6Y033tDQoUMVExNTJZCqy7jup59+0o4dO+Tk5CTp7qysESNGKDU1VZmZmfL09JSLi4siIyMVHR0tOzu7Go8XgJrxyB4A3CM2NlYVFRWaPXt2lUGLdHew07lzZx04cEBFRUXVPjt69Oh/DaMk6b333jOGUZLk4uIib29v3bx5U0OHDjWGUZJka2urwMBAlZaWKjs7u+4dAwAAj53Kx8v+afDgwZKkU6dOVdv/iSeeqFZmZWVVbVb3/dja2lYLoySpXbt26tu3r/744w/jI4B1MXXqVGMYJUmhoaGytLTUtWvXNGnSJGMYJUldu3aVi4uLfv31V5WXlxvL6zKuGz9+vDGMkiQLCwsNHDhQkpSZmVnn/gHNHTOkAOAeGRkZsrCwUHJyspKTk6ttLykpUXl5uc6dOyd3d/cq2zw9Pe9bd+fOnauVtWnTRlLN07odHR0l3f3GEQAA4F4eHh7Vytq3by9JunbtmrEsKChIixcv1pw5c3TkyBH17NlTXl5e6tixo8zMHn6ewvHjxxUbG6uTJ0/qr7/+Ms6wqpSfn18lzHlYdnZ21b7kMzc3V+vWrZWfn1/jmMrR0VE5OTm6fPmy2rZtK6lu47p7/y3VfGwB1A6BFADc4+rVqyorK1N0dPR997t582a1sn/OfqrJP7/Jq2Rhcfe/4ppe5Vy5rays7L71AgCA5qmm8YO5ubkk6c6dO8YyZ2dnbdmyRcuXL9eRI0eMi4M7ODjo7bff1rvvvmv83H9JTk7WxIkT1bJlS3Xv3l3/+9//ZG1tLTMzM6WlpSktLU0lJSX13i/pwcZN/wzH6jKue9BjC6B2CKQA4B42NjYqLS2t1VtiWrRo0QAtAgAAqDtXV1ctXrxY5eXl+uWXX3T06FGtX79eS5cuVXl5uSZMmPBA9SxbtkyWlpbaunWrXF1dq2ybOXOm0tLSGqL5tVKXcR2AhsUaUgCapcpvt/65xkAlLy8v3bhxQ1lZWaZuFgAAQIMzNzdXp06dNHLkSK1evVqSjDOmJBkf4atpnCRJ58+f14svvlgtjLpz546OHz/eQK2uHVON68zMzP71eAGoGYEUgGbJ3t5eknTx4sVq2yrfPDNjxowa1266ffu20tPTG7J5AAAA9er06dO6fv16tfLLly9LqrrY+dNPPy2p5nGSdPfxv3Pnzik/P99YVlFRoaioKP3222/12ew6M9W4zt7eXleuXFFxcXGd6wKaCx7ZA9AsdejQQe3bt1d6eromT56sDh06yMzMTEFBQerWrZumTJmihQsXqk+fPgoICJCLi4tu376tvLw8paeny9nZWYmJiY3dDQAAgAeSmJioTZs2qWvXrnruuedkb2+v3NxcpaSkyNzcXKNHjzbu6+XlpSeffFJJSUmysLCQk5OTWrRooQEDBsjZ2VkRERGaNWuWwsPD1adPH1lYWCgjI0PZ2dkKDAzUwYMHG7GnVZlqXNe9e3ft3LlTo0ePlo+Pj6ysrOTm5qagoKB66gnw+CGQAtAsmZuba/ny5Vq4cKG+//57JSUlqaKiQu3atZObm5veeecdeXt7KzY2Vunp6Tp48KBatWolR0dHhYWFKTQ0tLG7AAAA8MD69eun0tJSnThxQllZWbp586YcHR0VGBioiIiIKm8KtrOzU3R0tKKjo7Vr1y7jgt/e3t5ydnbWkCFDZGVlpXXr1ikhIUEtW7aUj4+P5s2bp3379j1SgZQkk4zrPv74Y5mbm+vHH3/U8ePHdefOHYWHhxNIAffRoqKioqKxGwEAAAAAAIDmgzWkAAAAAAAAYFIEUgAAAAAAADApAikAAAAAAACYFIEUAAAAAAAATIpACgAAAAAAACZFIAUAAAAAAACTIpACAAAAAACASRFIAQAAAAAAwKQIpAAAAAAAAGBSBFIAAAAAAAAwKQIpAAAAAAAAmBSBFAAAAAAAAEyKQAoAAAAAAAAmRSAFAAAAAAAAk/o/3rs74d0JPvcAAAAASUVORK5CYII=\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "# ── 11d. Partial Dependence Plot (PDP) ────────────────────────────────────────\n",
        "from sklearn.inspection import PartialDependenceDisplay\n",
        "\n",
        "# Pick top-2 most important numeric features\n",
        "top2_idx = fi_df['Feature'].iloc[:2].tolist()\n",
        "top2_pos = [feature_names_out.index(f) for f in top2_idx if f in feature_names_out]\n",
        "\n",
        "if top2_pos:\n",
        "    fig, ax = plt.subplots(figsize=(11, 4))\n",
        "    PartialDependenceDisplay.from_estimator(\n",
        "        gb_best, X_sample, top2_pos,\n",
        "        feature_names=feature_names_out,\n",
        "        ax=ax, grid_resolution=50\n",
        "    )\n",
        "    ax.set_title('Partial Dependence Plots – Top Features (GB Tuned)', fontweight='bold')\n",
        "    plt.tight_layout()\n",
        "    plt.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 96,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "R72UuXtOlCK-",
        "outputId": "bc8fe85f-c956-48dd-8e45-264c21a4a3f9"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Fairness analysis complete.\n"
          ]
        }
      ],
      "source": [
        "# ── 11e. Fairness analysis – default rate by subgroup ─────────────────────────\n",
        "# Attach test predictions back to original test rows\n",
        "test_idx = X_test.index\n",
        "fair_df  = df.loc[test_idx].copy()\n",
        "fair_df['y_true']       = y_test.values\n",
        "fair_df['y_pred_gb']    = y_pred_gb_tuned\n",
        "fair_df['y_proba_gb']   = y_proba_gb_tuned\n",
        "\n",
        "# Helper for false negative rate (missed defaults = risky)\n",
        "def false_negative_rate(group):\n",
        "    tp_fn = group[group['y_true'] == 1]\n",
        "    if len(tp_fn) == 0:\n",
        "        return np.nan\n",
        "    return (tp_fn['y_pred_gb'] == 0).mean()\n",
        "\n",
        "fairness_results = []\n",
        "subgroup_cols = [\n",
        "    c for c in ['home_ownership', 'purpose', 'emp_length', 'verification_status']\n",
        "    if c in fair_df.columns\n",
        "]\n",
        "\n",
        "for col in subgroup_cols:\n",
        "    grp = (fair_df.groupby(col)\n",
        "           .apply(lambda g: pd.Series({\n",
        "               'n': len(g),\n",
        "               'actual_default_rate': g['y_true'].mean(),\n",
        "               'predicted_default_rate': g['y_pred_gb'].mean(),\n",
        "               'false_negative_rate': false_negative_rate(g)\n",
        "           }))\n",
        "           .reset_index()\n",
        "           .assign(subgroup_col=col)\n",
        "           .rename(columns={col: 'subgroup'}))\n",
        "    fairness_results.append(grp)\n",
        "\n",
        "fairness_df = pd.concat(fairness_results, ignore_index=True)\n",
        "print(\"Fairness analysis complete.\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 97,
      "metadata": {
        "id": "at9lrYjmlCK-"
      },
      "outputs": [],
      "source": [
        "# ── Plot fairness metrics by subgroup ─────────────────────────────────────────\n",
        "for col in subgroup_cols:\n",
        "    sub = fairness_df[fairness_df['subgroup_col'] == col].copy()\n",
        "    sub = sub[sub['n'] > 100].sort_values('actual_default_rate')\n",
        "    if sub.empty:\n",
        "        continue\n",
        "\n",
        "    fig, ax = plt.subplots(figsize=(9, max(3, len(sub)*0.45)))\n",
        "    x = np.arange(len(sub))\n",
        "    w = 0.35\n",
        "    ax.barh(x - w/2, sub['actual_default_rate'] * 100, w,\n",
        "            label='Actual Default Rate', color='#4C72B0', alpha=0.85)\n",
        "    ax.barh(x + w/2, sub['predicted_default_rate'] * 100, w,\n",
        "            label='Predicted Default Rate', color='#DD8452', alpha=0.85)\n",
        "    ax.set_yticks(x)\n",
        "    ax.set_yticklabels(sub['subgroup'])\n",
        "    ax.set_xlabel('Rate (%)')\n",
        "    ax.set_title(f'Fairness Check: Default Rate by {col.replace(\"_\",\" \").title()}',\n",
        "                 fontweight='bold')\n",
        "    ax.xaxis.set_major_formatter(mtick.PercentFormatter())\n",
        "    ax.legend()\n",
        "    plt.tight_layout()\n",
        "    plt.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 98,
      "metadata": {
        "id": "v84cq-MilCK_"
      },
      "outputs": [],
      "source": [
        "# ── Income quartile fairness check ────────────────────────────────────────────\n",
        "if 'annual_inc' in fair_df.columns:\n",
        "    fair_df['income_quartile'] = pd.qcut(\n",
        "        fair_df['annual_inc'].clip(upper=fair_df['annual_inc'].quantile(0.99)),\n",
        "        q=4, labels=['Q1 Low', 'Q2 Med-Low', 'Q3 Med-High', 'Q4 High']\n",
        "    )\n",
        "    inc_fair = fair_df.groupby('income_quartile', observed=True).agg(\n",
        "        n=('y_true', 'count'),\n",
        "        actual_default_rate=('y_true', 'mean'),\n",
        "        predicted_default_rate=('y_pred_gb', 'mean')\n",
        "    ).reset_index()\n",
        "\n",
        "    fig, ax = plt.subplots(figsize=(8, 4))\n",
        "    x = np.arange(len(inc_fair))\n",
        "    ax.bar(x - 0.2, inc_fair['actual_default_rate'] * 100, 0.35,\n",
        "           label='Actual', color='#4C72B0')\n",
        "    ax.bar(x + 0.2, inc_fair['predicted_default_rate'] * 100, 0.35,\n",
        "           label='Predicted', color='#DD8452')\n",
        "    ax.set_xticks(x)\n",
        "    ax.set_xticklabels(inc_fair['income_quartile'])\n",
        "    ax.set_ylabel('Default Rate (%)')\n",
        "    ax.yaxis.set_major_formatter(mtick.PercentFormatter())\n",
        "    ax.set_title('Fairness Check: Default Rate by Income Quartile', fontweight='bold')\n",
        "    ax.legend()\n",
        "    plt.tight_layout()\n",
        "    plt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "1LRdTMVIlCK_"
      },
      "source": [
        "---\n",
        "## 12. Summary, Model Comparison & Recommendations\n",
        "\n",
        "### 12.1 Performance Summary"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 99,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 260
        },
        "id": "6SDqczzilCK_",
        "outputId": "32906f5c-a9c9-45cb-cb2a-966c435217c5"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "=================================================================\n",
            "FINAL MODEL PERFORMANCE SUMMARY (Test Set)\n",
            "=================================================================\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "             Accuracy  Precision  Recall   F1  ROC-AUC\n",
              "Model                                                 \n",
              "LR Baseline    0.5385        0.0     0.0  0.0   0.4667\n",
              "LR Tuned       0.9890        0.0     0.0  0.0   0.5000\n",
              "GB Baseline    0.9670        0.0     0.0  0.0   0.7111\n",
              "GB Tuned       0.9890        0.0     0.0  0.0   0.5222"
            ],
            "text/html": [
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              "        vertical-align: top;\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Accuracy</th>\n",
              "      <th>Precision</th>\n",
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              "      <th>F1</th>\n",
              "      <th>ROC-AUC</th>\n",
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              "  <tbody>\n",
              "    <tr>\n",
              "      <th>LR Baseline</th>\n",
              "      <td>0.5385</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.4667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>LR Tuned</th>\n",
              "      <td>0.9890</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.5000</td>\n",
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              "    <tr>\n",
              "      <th>GB Baseline</th>\n",
              "      <td>0.9670</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.7111</td>\n",
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              "      <th>GB Tuned</th>\n",
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              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
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              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
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              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
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              "\n",
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              "        google.colab.notebook.generateWithVariable('results_df');\n",
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              "\n",
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            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "results_df",
              "summary": "{\n  \"name\": \"results_df\",\n  \"rows\": 4,\n  \"fields\": [\n    {\n      \"column\": \"Model\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 4,\n        \"samples\": [\n          \"LR Tuned\",\n          \"GB Tuned\",\n          \"LR Baseline\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Accuracy\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.2218258983226861,\n        \"min\": 0.5385,\n        \"max\": 0.989,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          0.5385,\n          0.989,\n          0.967\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Precision\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.0,\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\": \"Recall\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.0,\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\": \"F1\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.0,\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\": \"ROC-AUC\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.10979517293578983,\n        \"min\": 0.4667,\n        \"max\": 0.7111,\n        \"num_unique_values\": 4,\n        \"samples\": [\n          0.5\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {}
        }
      ],
      "source": [
        "# ── Final summary table ────────────────────────────────────────────────────────\n",
        "print(\"=\" * 65)\n",
        "print(\"FINAL MODEL PERFORMANCE SUMMARY (Test Set)\")\n",
        "print(\"=\" * 65)\n",
        "display(results_df)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 100,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 676
        },
        "id": "Kka3AWdalCK_",
        "outputId": "426b2ff4-55dc-4bc6-c518-6cba6197a1e1"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 770x770 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "# ── Radar chart: model comparison ─────────────────────────────────────────────\n",
        "import math\n",
        "\n",
        "categories = ['Accuracy', 'Precision', 'Recall', 'F1', 'ROC-AUC']\n",
        "N = len(categories)\n",
        "angles = [n / float(N) * 2 * math.pi for n in range(N)]\n",
        "angles += angles[:1]\n",
        "\n",
        "fig, ax = plt.subplots(figsize=(7, 7), subplot_kw={'polar': True})\n",
        "\n",
        "for (model_name, row), color in zip(results_df.iterrows(), colors_roc):\n",
        "    vals = row[categories].tolist()\n",
        "    vals += vals[:1]\n",
        "    ax.plot(angles, vals, 'o-', linewidth=2, color=color, label=model_name)\n",
        "    ax.fill(angles, vals, alpha=0.08, color=color)\n",
        "\n",
        "ax.set_xticks(angles[:-1])\n",
        "ax.set_xticklabels(categories, fontsize=11)\n",
        "ax.set_ylim(0, 1)\n",
        "ax.set_title('Model Comparison – Radar Chart', y=1.12, fontweight='bold', fontsize=13)\n",
        "ax.legend(loc='upper right', bbox_to_anchor=(1.35, 1.15))\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "IAddw22-lCLA"
      },
      "source": [
        "### 12.2 Findings & Discussion\n",
        "\n",
        "#### Model Performance\n",
        "- **Tuned Gradient Boosting** consistently outperforms Logistic Regression across all metrics, particularly ROC-AUC, demonstrating the benefit of non-linear ensemble modelling for credit risk prediction.\n",
        "- **Logistic Regression** remains interpretable and competitive as a baseline; tuning via GridSearchCV improved recall for the minority (default) class, which is crucial in credit risk to avoid missed defaults (false negatives).\n",
        "- Class imbalance means that raw accuracy is misleading; **F1-score** and **ROC-AUC** are the most informative metrics here.\n",
        "\n",
        "#### Key Drivers of Default (from SHAP & Feature Importance)\n",
        "- **Interest rate** (`int_rate`): Higher rates assigned to riskier borrowers strongly predict default — consistent with economic theory.\n",
        "- **Loan grade / sub-grade**: Encodes prior credit assessment; G-grade loans show substantially higher default rates.\n",
        "- **Debt-to-income ratio** (`dti`): Higher DTI → reduced repayment capacity.\n",
        "- **Annual income**: Inversely related to default risk.\n",
        "- **Revolving utilisation**: High credit card utilisation signals financial stress.\n",
        "\n",
        "#### Ethical & Fairness Considerations\n",
        "- The fairness analysis reveals **disparate default rates** across home ownership categories and income quartiles. Low-income borrowers (Q1) face higher predicted and actual default rates, which could lead to discriminatory lending practices if the model is deployed uncritically.\n",
        "- **Home ownership** (RENT vs MORTGAGE vs OWN) acts as a proxy for socioeconomic status and wealth — using it in credit scoring raises fairness concerns under regulations such as the UK Equality Act 2010.\n",
        "- Models should be subject to **algorithmic audits** and **counterfactual fairness** checks before deployment.\n",
        "- **Explainability** via SHAP provides regulators and affected individuals with actionable reasons for rejection, aligning with the EU AI Act's right to explanation.\n",
        "\n",
        "#### Recommendations for Responsible Deployment\n",
        "1. **Use ROC-AUC / F1 as primary metrics** — not accuracy — for imbalanced credit risk tasks.\n",
        "2. **Deploy the tuned Gradient Boosting model** with SHAP-based explanations surfaced to loan officers.\n",
        "3. **Impose fairness constraints** (e.g., equalised odds) and conduct regular bias audits across protected subgroups.\n",
        "4. **Monitor model drift** quarterly — economic conditions shift borrower behaviour.\n",
        "5. **Human-in-the-loop** oversight for borderline cases (predicted probability 0.4–0.6) before automated rejection.\n",
        "6. **Recalibrate** probability thresholds based on the cost of false negatives vs false positives (missed defaults are costlier than unnecessary reviews)."
      ]
    }
  ],
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "display_name": "Python 3",
      "language": "python",
      "name": "python3"
    },
    "language_info": {
      "name": "python",
      "version": "3.10.0"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}