Asignment.ipynb

asignment.ipynb

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  "metadata": {
    "colab": {
      "provenance": [],
      "authorship_tag": "ABX9TyOITrSXY7YOS5m+gAvnjn9X",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/gist/sahilkashyap64/701d1da7fecac3df063fc78320a26280/asignment.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import numpy as np\n",
        "from scipy import stats\n",
        "\n",
        "# Task 1: Load the CSV file and analyze the data\n",
        "file_path = '/content/CLAY_10_7490_TC304.csv'  # Update this with the correct file path\n",
        "df = pd.read_csv(file_path)\n",
        "\n",
        "# Clean column names by stripping spaces\n",
        "df.columns = df.columns.str.strip()\n",
        "\n",
        "# Task 1: How many soils are described in the database?\n",
        "num_soils = df.shape[0]\n",
        "print(f\"Number of soils in the database: {num_soils}\")\n",
        "\n",
        "# List of relevant Su columns (undrained shear strength from different tests)\n",
        "su_columns = [\n",
        "    'su,CIUC (kN/m2)', 'su,CK0UC (kN/m2)', 'su,DSS (kN/m2)',\n",
        "    'su,CIUE (kN/m2)', 'su,CK0UE (kN/m2)', 'su,UU (kN/m2)',\n",
        "    'su,UC (kN/m2)', 'su,VST (kN/m2)', 'remolded su,UU (kN/m2)',\n",
        "    'remolded su,UC (kN/m2)', 'remolded su,VST (kN/m2)', 'Remolded su (kN/m2)',\n",
        "    'su(mob) (kN/m2)'\n",
        "]\n",
        "\n",
        "# Convert all Su columns to numeric, forcing non-numeric values to NaN\n",
        "df[su_columns] = df[su_columns].apply(pd.to_numeric, errors='coerce')\n",
        "\n",
        "# Task 1: Count the number of soils with Su from any test\n",
        "num_with_su = df[su_columns].notna().any(axis=1).sum()\n",
        "print(f\"Number of soils with undrained shear strength (Su) from any test: {num_with_su}\")\n",
        "\n",
        "# Task 2: Plot Liquid Limit (LL) and Plasticity Index (PI) as a scatter chart and classify soils\n",
        "# Ensure that LL and PI columns are numeric, and handle non-numeric values\n",
        "df['LL (%)'] = pd.to_numeric(df['LL (%)'], errors='coerce')\n",
        "df['PI (%)'] = pd.to_numeric(df['PI (%)'], errors='coerce')\n",
        "\n",
        "# Drop rows where LL or PI is missing\n",
        "df_cleaned = df.dropna(subset=['LL (%)', 'PI (%)']).copy()  # Explicitly copy the DataFrame\n",
        "\n",
        "# Scatter plot of Liquid Limit (LL) vs Plasticity Index (PI)\n",
        "plt.figure(figsize=(8, 6))\n",
        "plt.scatter(df_cleaned['LL (%)'], df_cleaned['PI (%)'], color='blue', alpha=0.5)\n",
        "plt.title('Liquid Limit (LL) vs Plasticity Index (PI)')\n",
        "plt.xlabel('Liquid Limit (LL) (%)')\n",
        "plt.ylabel('Plasticity Index (PI) (%)')\n",
        "plt.grid(True)\n",
        "plt.show()\n",
        "\n",
        "# USCS classification function\n",
        "def classify_soil(ll, pi):\n",
        "    if ll > 50 and pi >= 4.5:  # Condition for CH and MH\n",
        "        if pi >= 7:  # Plasticity index threshold for CH\n",
        "            return 'CH'\n",
        "        else:\n",
        "            return 'MH'\n",
        "    elif ll <= 50 and pi >= 4:  # Condition for CL and ML\n",
        "        if pi >= 7:  # Plasticity index threshold for CL\n",
        "            return 'CL'\n",
        "        else:\n",
        "            return 'ML'\n",
        "    return 'Unclassified'\n",
        "\n",
        "# Apply classification and fix the warning using .loc and copying the DataFrame\n",
        "df_cleaned.loc[:, 'USCS'] = df_cleaned.apply(lambda row: classify_soil(row['LL (%)'], row['PI (%)']), axis=1)\n",
        "\n",
        "# Task 2: Count the number of soils in each classification\n",
        "classification_counts = df_cleaned['USCS'].value_counts()\n",
        "print(\"Soil classifications:\")\n",
        "print(classification_counts)\n",
        "\n",
        "# Task 3: Plot the histogram of Su for each soil type\n",
        "# Calculate the average Su for each row (soil) if multiple tests are available\n",
        "df_cleaned.loc[:, 'su_avg'] = df_cleaned[su_columns].mean(axis=1)\n",
        "\n",
        "# Plot histograms for each soil type based on the classification\n",
        "soil_types = ['CH', 'MH', 'CL', 'ML']\n",
        "plt.figure(figsize=(10, 6))\n",
        "\n",
        "for soil in soil_types:\n",
        "    soil_data = df_cleaned[df_cleaned['USCS'] == soil]['su_avg'].dropna()\n",
        "    plt.hist(soil_data, bins=20, alpha=0.5, label=f'Soil Type: {soil}')\n",
        "\n",
        "plt.title('Histogram of Su for Each Soil Type')\n",
        "plt.xlabel('Undrained Shear Strength (Su) [kN/m2]')\n",
        "plt.ylabel('Frequency')\n",
        "plt.legend()\n",
        "plt.grid(True)\n",
        "plt.show()\n",
        "\n",
        "# Task 3: Test for normality of Su data\n",
        "su_data = df_cleaned['su_avg'].dropna()\n",
        "k2, p = stats.normaltest(su_data)\n",
        "print(f\"Normality test p-value for Su: {p}\")\n",
        "if p < 0.05:\n",
        "    print(\"Su data is not normally distributed.\")\n",
        "else:\n",
        "    print(\"Su data is normally distributed.\")\n",
        "\n",
        "# Task 4: Plot the histogram of Overconsolidation Ratio (OCR)\n",
        "# Convert OCR to numeric\n",
        "df['OCR'] = pd.to_numeric(df['OCR'], errors='coerce')\n",
        "\n",
        "# Plot histogram of OCR\n",
        "plt.figure(figsize=(10, 6))\n",
        "ocr_data = df['OCR'].dropna()\n",
        "plt.hist(ocr_data, bins=20, alpha=0.7, color='green', edgecolor='black')\n",
        "plt.title('Histogram of Overconsolidation Ratio (OCR)')\n",
        "plt.xlabel('OCR')\n",
        "plt.ylabel('Frequency')\n",
        "plt.grid(True)\n",
        "\n",
        "# Calculate mean and standard deviation of OCR\n",
        "ocr_mean = ocr_data.mean()\n",
        "ocr_std = ocr_data.std()\n",
        "print(f\"OCR Mean: {ocr_mean}, OCR Standard Deviation: {ocr_std}\")\n",
        "\n",
        "# Add mean and standard deviation lines to the plot\n",
        "plt.axvline(ocr_mean, color='blue', linestyle='dashed', linewidth=2, label=f'Mean: {ocr_mean:.2f}')\n",
        "plt.axvline(ocr_mean + ocr_std, color='red', linestyle='dashed', linewidth=2, label=f'Standard Deviation: {ocr_std:.2f}')\n",
        "plt.axvline(ocr_mean - ocr_std, color='red', linestyle='dashed', linewidth=2)\n",
        "\n",
        "# Add legend\n",
        "plt.legend()\n",
        "plt.show()\n",
        "\n",
        "# Task 4: Test for normality of OCR data\n",
        "k2, p = stats.normaltest(ocr_data)\n",
        "print(f\"Normality test p-value for OCR: {p}\")\n",
        "if p < 0.05:\n",
        "    print(\"OCR data is not normally distributed.\")\n",
        "else:\n",
        "    print(\"OCR data is normally distributed.\")\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "QD8bmxWnfd1e",
        "outputId": "c128e67d-b5c2-48d7-84e0-c89f7d1f886d"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Number of soils in the database: 7709\n",
            "Number of soils with undrained shear strength (Su) from any test: 4351\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Soil classifications:\n",
            "USCS\n",
            "CH              2363\n",
            "CL              1541\n",
            "ML               141\n",
            "Unclassified      12\n",
            "Name: count, dtype: int64\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x600 with 1 Axes>"
            ],
            "image/png": 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PValSRR4eHoWeNwcHBwUGBto8rrvvvltNmjTRkiVLVK1aNaWkpGjevHkFjj148KA6duxoLl+4cEHHjx/XfffdJ+n/nV9fX99rXokEcHvhmS0AuAH/vH3O09NTd955p9V05nlfuP/5Rf++++5TTk6O3nrrLav22bNny2KxmDO/RURESJLefvttq3GFfTEsSN7Vin9enZgzZ06Rt3Ej8r6U/nN/s2bNkqSrzqxYmPT0dCUmJhbYl/e8W96tanlfhjdv3myOycnJ0aJFi657v3mqVq2qxo0bKz4+3iq3P/30k9auXWsesy0VlNdz584pNjbWalyXLl1Uvnx5xcTE6PLly1Z913vFqjAHDx5USkpKvvbU1FQlJiaqQoUKqlKlihwdHdWlSxetWLHCair+kydPaunSpWrTps1Nu+3u0Ucf1dq1azVnzhxVqlSp0NkWFy1aZDU76YIFC5SdnW31GfXy8tJrr71W4Cymp0+fts0BALB7XNkCgBtQr149dejQQc2aNVPFihW1c+dO/ec//9GoUaPMMc2aNZMkPfnkk4qIiJCjo6P69u2rBx98UB07dtQLL7ygI0eOqFGjRlq7dq1WrFihp556yiwQmjVrpl69emnOnDn666+/zKnff/nlF0lFuzXPy8tL7dq104wZM5SVlaU77rhDa9eu1eHDh21wVvJr1KiRBgwYoEWLFik1NVXt27fX9u3bFR8frx49elhdNSiq9PR0tWrVSi1btlRkZKQCAwOVmpqq5cuXa8uWLerRo4eaNGkiSapfv75atmypCRMm6MyZM6pYsaKWLVum7OzsGzqumTNnqmvXrgoLC9OQIUPMqd+9vb2tfv+suLZs2ZKvOJL+noSjYcOG6tKli1xcXPTggw/qscce04ULF/R///d/8vX1Na/qSX/nf/bs2Ro6dKjuuece87e+fvzxR6Wnpys+Pv6GY/3xxx/1yCOPqGvXrmrbtq0qVqyoP/74Q/Hx8Tp27JjmzJljFodTp05VQkKC2rRpoyeeeEJOTk565513lJGRUaTf9CopjzzyiJ599ll9/vnnGjFihNUkGFfKzMxUp06d9PDDDys5OVlvv/222rRpo27dukn6+/wuWLBAjz76qJo2baq+ffuqSpUqSklJ0ZdffqnWrVvn+0cVALeJUpwJEQBKVd60zjt27Ciwv3379tec+n3q1KlGixYtDB8fH8Pd3d246667jFdffdVqmujs7Gxj9OjRRpUqVQyLxWI1Dfz58+eNp59+2ggICDCcnZ2N2rVrGzNnzrSajtswDOPixYvGyJEjjYoVKxqenp5Gjx49jOTkZEOS1VTseVOMnz59Ot/x/O9//zN69uxp+Pj4GN7e3kbv3r2NY8eOFTp9/D+3UdiU7AWdp4JkZWUZkydPNoKDgw1nZ2cjMDDQmDBhgnH58uUi7aeg7f3f//2f0aNHD6NGjRqGq6ur4eHhYTRp0sSYOXOmkZGRYTX+0KFDRnh4uOHq6mr4+fkZEydONBISEm5o6nfDMIxvvvnGaN26teHu7m54eXkZDz74oLF//36rMVfLy9X2V9jrynytXLnSaNiwoeHm5mYEBQUZ06dPNxYvXlzgVPcrV640WrVqZcbaokUL46OPPjL7C8tlUaZbP3nypDFt2jSjffv2RtWqVQ0nJyejQoUKxr333mv85z//yTd+9+7dRkREhOHp6Wl4eHgYHTt2NLZu3VrgeSjpqd+vdN999xmS8u3bMP7f3xGbNm0yhg8fblSoUMHw9PQ0oqKirKb7vzLeiIgIw9vb23BzczNq1aplDBw40Ni5c+d1xQvg1mExjBK6fwAAcFMlJSWpSZMm+vDDD/P9CCuAounZs6f27t1b4DOQcXFxGjRokHbs2FHgjKUAcC08swUAZcClS5fytc2ZM0cODg5q165dKUQElH3Hjx/Xl19+qUcffbS0QwFwi+KZLQAoA2bMmKFdu3apY8eOcnJy0urVq7V69WoNHz78pszcBtxKDh8+rO+++07vvvuunJ2d9dhjj5V2SABuURRbAFAGtGrVSgkJCXrllVd04cIFVa9eXdHR0XrhhRdKOzSgzNm0aZMGDRqk6tWrKz4+vsDfxgKAksAzWwAAAABgAzyzBQAAAAA2QLEFAAAAADZQqs9sbd68WTNnztSuXbt0/Phxff755+rRo4fVmAMHDui5557Tpk2blJ2drXr16um///2vqlevLkm6fPmyxo0bp2XLlikjI0MRERF6++235efnZ24jJSVFI0aM0IYNG+Tp6akBAwYoJiZGTk5FP/zc3FwdO3ZM5cuXL9IPiAIAAAC4NRmGofPnzysgIEAODoVfvyrVYuvixYtq1KiRBg8erIceeihf/6FDh9SmTRsNGTJEkydPlpeXl/bt2yc3NzdzzNNPP60vv/xSn376qby9vTVq1Cg99NBD+u677yRJOTk5uv/+++Xv76+tW7fq+PHj6t+/v5ydnfXaa68VOdZjx44x4xcAAAAA09GjR1WtWrVC++1mggyLxZLvylbfvn3l7OysDz74oMB1zp07pypVqmjp0qX617/+JUn6+eefVbduXSUmJqply5ZavXq1HnjgAR07dsy82rVw4UI999xzOn36tFxcXIoU37lz5+Tj46OjR4/Ky8vrxg72BmVlZWnt2rXq0qWLnJ2dSzWW2x25sC/kw36QC/tCPuwHubAv5MN+lLVcpKWlKTAwUKmpqfL29i50nN1O/Z6bm6svv/xSzz77rCIiIvTDDz8oODhYEyZMMAuyXbt2KSsrS+Hh4eZ6d911l6pXr24WW4mJiWrQoIHVbYUREREaMWKE9u3bpyZNmhS4/4yMDGVkZJjL58+flyS5u7vL3d3dBkdcdE5OTvLw8JC7u3uZeDPeysiFfSEf9oNc2BfyYT/IhX0hH/ajrOUiKytLkq75eJHdFlunTp3ShQsXNG3aNE2dOlXTp0/XmjVr9NBDD2nDhg1q3769Tpw4IRcXF/n4+Fit6+fnpxMnTkiSTpw4YVVo5fXn9RUmJiZGkydPzte+du1aeXh43ODRlYyEhITSDgH/P3JhX8iH/SAX9oV82A9yYV/Ih/0oK7lIT08v0ji7LbZyc3MlSd27d9fTTz8tSWrcuLG2bt2qhQsXqn379jbd/4QJEzR27FhzOe9SYZcuXeziNsKEhAR17ty5TFT+tzJyYV/Ih/0gF/aFfNgPcmFfyIf9KGu5SEtLK9I4uy22KleuLCcnJ9WrV8+qvW7duvr2228lSf7+/srMzFRqaqrV1a2TJ0+avwbv7++v7du3W23j5MmTZl9hXF1d5erqmq/d2dnZbt4A9hTL7Y5c2BfyYT/IhX0hH/aDXNgX8mE/ykouihqj3RZbLi4uuueee5ScnGzV/ssvv6hGjRqSpGbNmsnZ2Vnr1q1Tr169JEnJyclKSUlRWFiYJCksLEyvvvqqTp06JV9fX0l/X5708vLKV8gBAADg1mQYhrKzs5WTk2O2ZWVlycnJSZcvX7Zqx81nb7lwdHSUk5PTDf/kU6kWWxcuXNCvv/5qLh8+fFhJSUmqWLGiqlevrmeeeUZ9+vRRu3bt1LFjR61Zs0ZffPGFNm7cKEny9vbWkCFDNHbsWFWsWFFeXl4aPXq0wsLC1LJlS0lSly5dVK9ePT366KOaMWOGTpw4oRdffFEjR44s8MoVAAAAbi2ZmZk6fvx4vudsDMOQv7+/jh49yu+oljJ7zIWHh4eqVq1a5NnLC1KqxdbOnTvVsWNHcznvGakBAwYoLi5OPXv21MKFCxUTE6Mnn3xSISEh+u9//6s2bdqY68yePVsODg7q1auX1Y8a53F0dNSqVas0YsQIhYWFqVy5chowYICmTJly8w4UAAAApSI3N1eHDx+Wo6OjAgIC5OLiYn6Zz83N1YULF+Tp6XnVH6aF7dlTLgzDUGZmpk6fPq3Dhw+rdu3axY6pVIutDh066Fo/8zV48GANHjy40H43NzfNnz9f8+fPL3RMjRo19NVXXxU7TgAAAJRNmZmZys3NVWBgYL4ZpXNzc5WZmSk3N7dS/4J/u7O3XORNQf/777+bcRVH6R8JAAAAYGP28AUeZUtJvGd41wEAAACADVBsAQAAAIAN2O3U7wAAAICtzE74RYZhKCMjQ66urjafAe/pznVsuv2CREdHa/ny5UpKSpIkDRw4UKmpqVq+fPlNj+V2xZUtAAAAwM6cPn1aI0aMUPXq1eXq6ip/f39FRETou+++K/I2xo8fr3Xr1hVp7MCBA2WxWAp9BQUFFfNISp5hGFq0aJFCQ0Pl6ekpHx8fNW/eXHPmzDGn94+Ojlbjxo3zrXvkyBFZLBazALU1rmwBAAAAdqZXr17KzMxUfHy8atasqZMnT2rdunX666+/irwNT09PeXp6Fmns3LlzNW3aNHO5atWqio2NVWRkpKS/f07JXjz66KP67LPP9OKLL+qtt95SlSpV9OOPP2rOnDkKCgpSjx49SjtEE8UWAAAAYEdSU1O1ZcsWbdy4Ue3bt5f0908ZtWjRwmpcSkqKRo8erXXr1snBwUGRkZGaN2+e/Pz8JOW/jfBqvL295e3tbdXm4+Mjf39/DR48WKdOndKqVavMvqysLN1xxx2KiYnRkCFD1KFDB919992SpA8++EDOzs4aMWKEpkyZYt6imZGRoRdeeEEfffSRUlNTdffdd2v69Onq0KFDkc/NJ598oiVLlmj58uXq3r272R4UFKRu3bopLS2tyNu6GbiNEAAAALAjeVekli9froyMjALH5Obmqnv37jpz5ow2bdqkhIQE/fbbb+rTp0+JxzN06FCtWbNGx48fN9tWrVql9PR0q/3Fx8fLyclJ27dv19y5czVr1iy9++67Zv+oUaOUmJioZcuWac+ePerdu7ciIyN18OBBc4yjo6Pi4uIKjWXJkiUKCQmxKrTyWCyWfAVjaaPYAgAAAOyIk5OT4uLiFB8fLx8fH7Vu3VoTJ07Unj17zDHr1q3T3r17tXTpUjVr1kyhoaF6//33tWnTJu3YsaNE42nVqpVCQkL0wQcfmG2xsbHq3bu31W2KgYGBmj17tkJCQhQVFaXRo0dr9uzZkv6+ChcbG6tPP/1Ubdu2Va1atTR+/Hi1adNGsbGx5jZCQkKuWjAdPHhQISEhRYp77969ZuGa96pfv/71Hv4NodgCAAAA7EyvXr107NgxrVy5UpGRkdq4caOaNm1qXvU5cOCAAgMDFRgYaK5Tr149+fj46MCBAyUez9ChQ82i6OTJk1q9erUGDx5sNaZly5ZWszqGhYXp4MGDysnJ0d69e5WTk6M6depYFT+bNm3SoUOHzHX279+vnj17FhqHYRhFjjkkJERJSUlWr6+++qrI65cEntkCAAAA7JCbm5s6d+6szp0766WXXtLQoUP18ssva+DAgTc9lv79++v5559XYmKitm7dquDgYLVt27bI61+4cEGOjo7atWtXvsk2ijqJhyTVqVNHP//8c5HGuri46M4777Rqc3K6ueUPV7YAAACAMqBevXq6ePGiJKlu3bo6evSojh49avbv379fqampqlevXonvu1KlSurRo4diY2MVFxenQYMG5Ruzbds2q+Xvv/9etWvXlqOjo5o0aaKcnBydOnVKd955p9XL39+/yHE88sgj+uWXX7RixYp8fYZh6Ny5c9d/cDbEla0ybP6GX2VYSn8aztL4kT4AAIBb1V9//aXevXtr8ODBatiwocqXL6+dO3dqxowZ5sQQ4eHhatCggaKiojRnzhxlZ2friSeeUPv27dW8eXObxDV06FA98MADysnJ0YABA/L1p6SkaOzYsXrssce0e/duzZs3T2+88Yakv69IRUVFqX///nrjjTfUpEkTnT59WuvWrVPDhg3VtWtXSX8XlDExMYXeSvjwww/r888/V79+/fTiiy+qS5cuqlKlivbu3avZs2dr9OjRTP0OAAAAlKanO9dRbm6u0tLS5OXlJQcH+7nhy9PTU6GhoZo9e7YOHTqkrKwsBQYGatiwYZo4caKkv2feW7FihUaPHq127dpZTf1uK+Hh4apatarq16+vgICAfP39+/fXpUuX1KJFCzk6OmrMmDEaPny42R8bG6upU6dq3Lhx+uOPP1S5cmW1bNlSDzzwgDkmOTn5qlenLBaLli5dqkWLFmnx4sV69dVX5eTkpNq1a6t///6KiIgo2YO+QRbjep4yu42lpaXJ29tb586dk5eXV6nGkpWVpa+++kqH3etwZauU5eXivvvuk7Ozc2mHc9sjH/aDXNgX8mE/yMXNd/nyZR0+fFjBwcFyc3Oz6rPXYsteXbhwQXfccYdiY2P10EMPWfV16NBBjRs31pw5c4q1bXvMxdXeO0WtDbiyBQAAAKBQubm5+vPPP/XGG2/Ix8dH3bp1K+2QygyKLQAAAACFSklJUXBwsKpVq6a4uLibPqNfWcaZAgAAAFCooKCga/6+1caNG29OMGWMfdwQCQAAAAC3GIotAAAAALABii0AAAAAsAGKLQAAAACwAYotAAAAALABii0AAAAAsAGmfgcAAMDtZ0OMLIYht4wMWVxdJYvFtvvrOMG22y9AdHS0li9frqSkJEnSwIEDlZqaquXLl9/0WG5XXNkCAAAA7Mzp06c1YsQIVa9eXa6urvL391dERIS+++67Im9j/PjxWrduXZHGDhw4UBaLpdBXUFBQMY+kZG3cuFEWi0UVKlTQ5cuXrfp27NhhxvvP8ampqfm2FRQUpDlz5tg0XootAAAAwM706tVLP/zwg+Lj4/XLL79o5cqV6tChg/76668ib8PT01OVKlUq0ti5c+fq+PHj5kuSYmNjzeUdO3YU6zhspXz58vr888+t2t577z1Vr169lCIqGMUWAAAAYEdSU1O1ZcsWTZ8+XR07dlSNGjXUokULTZgwQd26dTPHpaSkqHv37vL09JSXl5cefvhhnTx50uyPjo5W48aNi7RPb29v+fv7my9J8vHxkb+/vyZOnKhBgwZZjc/KypKvr6/ee+89SVKHDh00atQojRo1St7e3qpcubJeeuklGYZhrpORkaHx48frjjvuULly5RQaGqqNGzcW6xwNGDBAixcvNpcvXbqkZcuWacCAAcXanq1QbAEAAAB2xNPTU56enlq+fLkyMjIKHJObm6vu3bvrzJkz2rRpkxISEvTbb7+pT58+JR7P0KFDtWbNGvOKlyStWrVK6enpVvuLj4+Xk5OTtm/frrlz52rWrFl69913zf5Ro0YpMTFRy5Yt0549e9S7d29FRkbq4MGD5hhHR0fFxcVdM6ZHH31UW7ZsUUpKiiTpv//9r4KCgtS0adMSOOKSQ7EFAAAA2BEnJyfFxcUpPj5ePj4+at26tSZOnKg9e/aYY9atW6e9e/dq6dKlatasmUJDQ/X+++9r06ZNJX7LX6tWrRQSEqIPPvjAbIuNjVXv3r3l6elptgUGBmr27NkKCQlRVFSURo8erdmzZ0v6+ypcbGysPv30U7Vt21a1atXS+PHj1aZNG8XGxprbCAkJkbe39zVj8vX1VdeuXc3CbPHixRo8eHCh46tVq2YWsXmvvELNlii2AAAAADvTq1cvHTt2TCtXrlRkZKQ2btyopk2bmsXFgQMHFBgYqMDAQHOdevXqycfHRwcOHCjxeIYOHWoWRSdPntTq1avzFTctW7a0mpwiLCxMBw8eVE5Ojvbu3aucnBzVqVPHquDZtGmTDh06ZK6zf/9+9ezZs0gxDR48WHFxcfrtt9+UmJioqKioQsdu2bJFSUlJVq+AgIDrOQXFwtTvAAAAgB1yc3NT586d1blzZ7300ksaOnSoXn75ZQ0cOPCmx9K/f389//zzSkxM1NatWxUcHKy2bdsWef0LFy7I0dFRu3btkqOjo1XflVfHrkfXrl01fPhwDRkyRA8++OBVJwMJDg6Wj4+PVZuTk+1LIYotAAAAoAyoV6+e+RtZdevW1dGjR3X06FHz6tb+/fuVmpqqevXqlfi+K1WqpB49eig2NlaJiYn5JsyQpG3btlktf//996pdu7YcHR3VpEkT5eTk6NSpUwUWabm5udcdk5OTk/r3768ZM2Zo9erV173+zcBthAAAAIAd+euvv3Tvvffqww8/1J49e3T48GF9+umnmjFjhrp37y5JCg8PV4MGDRQVFaXdu3dr+/bt6t+/v9q3b6/mzZvbJK6hQ4cqPj5eBw4cKHDWv5SUFI0dO1bJycn66KOPNG/ePI0ZM0aSVKdOHUVFRal///767LPPdPjwYW3fvl0xMTH68ssvzW3Uq1cv35TuV/PKK6/o9OnTioiIuPEDtAGubAEAAOD203GCjNxcXU5Lk4uXlywO9nMNwtPTU6GhoZo9e7YOHTqkrKwsBQYGatiwYZo4caIkyWKxaMWKFRo9erTatWsnBwcHRUZGat68eTaLKzw8XFWrVlX9+vULfN6pf//+unTpklq0aCFHR0eNGTNGw4cPN/tjY2M1depUjRs3Tn/88YcqV66sli1b6oEHHjDHJCcn69y5c0WOycXFRZUrV76xA7Mhii0AAADAjri6uiomJkYxMTFXHVe9enWtWLGi0P7o6GhFR0eby0WZUj3Plb+PlefixYs6e/ashgwZUuA6zs7OmjNnjhYsWFBo/+TJkzV58uR8fXm3Eebk5MjhKoVvhw4dCowtT48ePaz6rzb+yJEjhW6npFBsAQAAAChUbm6u/vzzT73xxhvy8fGx+mFlXB3FFgAAAIBCpaSkKDg4WNWqVVNcXNxNmcXvVsGZAgAAAFCooKCgq966J0kbN268OcGUMfbzJCAAAAAA3EIotgAAAADABii2AAAAAMAGKLYAAAAAwAYotgAAAADABii2AAAAAMAGmPodAAAAt523k96WYRjKyMiQq6urLBaLTff3ROMnbLr9gkRHR2v58uVKSkqSJA0cOFCpqalavnz5TY/ldsWVLQAAAMDOnD59WiNGjFD16tXl6uoqf39/RURE6LvvvivyNsaPH69169YVaezAgQNlsVgKfQUFBRXzSEqeYRhatGiRQkND5enpKR8fHzVv3lxz5sxRenq6pL8LzcaNG5duoCrlYmvz5s168MEHFRAQIIvFctUq+/HHH5fFYtGcOXOs2s+cOaOoqCh5eXnJx8dHQ4YM0YULF6zG7NmzR23btpWbm5sCAwM1Y8YMGxwNAAAAUDJ69eqlH374QfHx8frll1+0cuVKdejQQX/99VeRt+Hp6alKlSoVaezcuXN1/Phx8yVJsbGx5vKOHTuKdRy28Oijj+qpp55S9+7dtWHDBiUlJemll17SihUrtHbt2tIOz0qpFlsXL15Uo0aNNH/+/KuO+/zzz/X9998rICAgX19UVJT27dunhIQErVq1Sps3b9bw4cPN/rS0NHXp0kU1atTQrl27NHPmTEVHR2vRokUlfjwAAADAjUpNTdWWLVs0ffp0dezYUTVq1FCLFi00YcIEdevWzRyXkpKi7t27y9PTU15eXnr44Yd18uRJs/96ru54e3vL39/ffEmSj4+P/P39NXHiRA0aNMhqfFZWlnx9ffXee+9Jkjp06KBRo0Zp1KhR8vb2VuXKlfXSSy/JMAxznYyMDI0fP1533HGHypUrp9DQUG3cuPG6zs0nn3yiJUuW6KOPPtLEiRN1zz33KCgoSN27d9f69evVsWPH69qerZVqsdW1a1dNnTpVPXv2LHTMH3/8odGjR2vJkiVydna26jtw4IDWrFmjd999V6GhoWrTpo3mzZunZcuW6dixY5KkJUuWKDMzU4sXL1b9+vXVt29fPfnkk5o1a5ZNjw0AAAAoDk9PT3l6emr58uXKyMgocExubq66d++uM2fOaNOmTUpISNBvv/2mPn36lHg8Q4cO1Zo1a8wrXpK0atUqpaenW+0vPj5eTk5O2r59u+bOnatZs2bp3XffNftHjRqlxMRELVu2THv27FHv3r0VGRmpgwcPmmMcHR0VFxdXaCxLlixRSEiIunfvnq/PYrHI29v7Bo+2ZNn1BBm5ubl69NFH9cwzz6h+/fr5+hMTE817NPOEh4fLwcFB27ZtU8+ePZWYmKh27drJxcXFHBMREaHp06fr7NmzqlChQoH7zsjIsHpzp6WlSfq7is/KyiqpQyyWvP1bjJxSjSNPaZ+P0pR37LfzObAn5MN+kAv7Qj7sB7m4+bKysmQYhnJzc5Wbm2u2G4ZhXnW58uqLrVy572txcHDQ4sWL9dhjj2nhwoVq2rSp2rVrpz59+qhhw4aSpISEBO3du1eHDh1SYGCgJCkuLk4NGjTQtm3bdM8995jHlbfvvGMuaix556xly5YKCQnR+++/r2eeeUaStHjxYv3rX/+Sh4eHub3AwEC98cYbslgsql27tvbs2aPZs2dryJAhSklJUWxsrI4cOWLerTZ27FitWbNGixcv1tSpUyVJISEhKl++fKExHjx4UHXq1LnmMfzz2IsjNzdXhmEoKytLjo6OVn1F/QzbdbE1ffp0OTk56cknnyyw/8SJE/L19bVqc3JyUsWKFXXixAlzTHBwsNUYPz8/s6+wYismJkaTJ0/O17527Vp5eHhc97HYQtDlQ6UdgiTpq69+Ke0QSl1CQkJph4ArkA/7QS7sC/mwH+Ti5nFycpK/v78uXLigzMxMs/3Kf1S/st1W8v7hvqg6d+6s/fv3KzExUTt37lRCQoJmzpypN998U4888oiSkpJ0xx13yNvb29x2tWrV5O3trR9++EEhISHKyMhQTk6O1UWD7OzsIsdy6dIlc2xUVJRZAJ46dUpr1qzRihUrzP7s7Gw1bdpU58+fN9dv1KiRZs2apbNnz2rbtm3KycnRXXfdZbWPjIwMeXl5met9//33Vz1fOTk5RTqGfx57cWRmZurSpUvavHmzsrOzrfryJuK4Frsttnbt2qW5c+dq9+7dNp+KsyATJkzQ2LFjzeW0tDQFBgaqS5cu8vLyuunxXCkrK0sJCQk64lZLhsXx2ivY2MiOd5Z2CKUmLxedO3fOd5srbj7yYT/IhX0hH/aDXNx8ly9f1tGjR+Xp6Sk3Nzez3dXVVYZhKDMzUy4uLjb/vlmc749eXl7q3r27unfvrldeeUXDhg3T9OnT9fjjj8vNzU0ODg75tmuxWOTm5iYvLy+5urrK0dHRHOPs7CwnJ6cix+Lu7m6OHTZsmCZPnqx9+/YpMTFRwcHBioyMNMc6OTnJ2dnZatvu7u7mceTm5srR0VE7duzId5XI09NT5cuX1/nz51W+fPmr5iIkJETJycnXPIZ/HntxXL58We7u7mrXrp3Ve0cqevFst8XWli1bdOrUKVWvXt1sy8nJ0bhx4zRnzhwdOXJE/v7+OnXqlNV62dnZOnPmjPlgn7+/v9WDgpLM5bwxBXF1dZWrq2u+dmdnZ7v5y9GwONpFsWUv56M02dP7AuTDnpAL+0I+7Ae5uHlycnJksVjk4OAgB4f/N13BlV/o86Y3t6Ur911c9evX14oVK+Tg4KB69erp6NGj+uOPP8zbCPfv36/U1FTdfffdcnBwMI8pb995x1nUWK48Z1WqVFGPHj0UHx+vxMREDRo0KN92tm/fbtW2fft21a5dW87OzmrWrJlycnL0559/qm3btvn2lXe737Xii4qKUt++ffXFF1/ke27LMAylpaXJ29s737EXR945LOjzWtTPr93+ztajjz6qPXv2KCkpyXwFBATomWee0ddffy1JCgsLU2pqqnbt2mWut379euXm5io0NNQcs3nzZqv7KhMSEhQSElLoLYQAAABAafnrr79077336sMPP9SePXt0+PBhffrpp5oxY4ZZYISHh6tBgwaKiorS7t27tX37dvXv31/t27e3ms+gJA0dOlTx8fE6cOCABgwYkK8/JSVFY8eOVXJysj766CPNmzdPY8aMkSTVqVNHUVFR6t+/vz777DMdPnxY27dvV0xMjL788ktzG/Xq1dPnn39eaAwPP/yw+vTpo379+um1117Tzp079fvvv2vVqlUKDw/Xhg0bzLGXLl2yqiWSkpJ06NDNfQynVK9sXbhwQb/++qu5fPjwYSUlJalixYqqXr16vt8FcHZ2lr+/v0JCQiRJdevWVWRkpIYNG6aFCxcqKytLo0aNUt++fc0H7x555BFNnjxZQ4YM0XPPPaeffvpJc+fO1ezZs2/egQIAAMCuPNH4CeXm5iotLU1eXl4lcuWppHh6eio0NFSzZ8/WoUOHlJWVpcDAQA0bNkwTJ06U9PcVoBUrVmj06NFq166dHBwcFBkZqXnz5tksrvDwcFWtWlX169cv8CeZ+vfvr0uXLqlFixZydHTUmDFjrH6SKTY2VlOnTtW4ceP0xx9/qHLlymrZsqUeeOABc0xycrLOnTtXaAwWi0VLly7VokWLtHjxYr366qtycnJS7dq11b9/f0VERJhjf/nlFzVp0sRq/U6dOumbb765kdNwXUq12Nq5c6fVXPh5z0gNGDDgqlM+XmnJkiUaNWqUOnXqJAcHB/Xq1Utvvvmm2e/t7a21a9dq5MiRatasmSpXrqxJkyZZJR4AAACwF66uroqJiVFMTMxVx1WvXl0rVqwotD86OlrR0dHmclG/X0sFz9B48eJFnT17VkOGDClwHWdnZ82ZM0cLFiwotH/y5MkFTkKXdxthTk7ONQtfBwcHPf7443r88ccLHfPPYy8tpVpsdejQ4bqm2jxy5Ei+tooVK2rp0qVXXa9hw4basmXL9YYHAAAA3PZyc3P1559/6o033pCPj4/VDyvj6ux2ggwAAAAApS8lJUXBwcGqVq2a4uLi5ORECVFUnCkAAAAAhQoKCrrm3WgbN268OcGUMfbzJCAAAAAA3EIotgAAAADABii2AAAAAMAGKLYAAAAAwAYotgAAAADABii2AAAAAMAGmPodAAAAt53T896SYRjKyMhQpqurLBaLTfdXZfQom26/INHR0Vq+fLmSkpIkSQMHDlRqaqqWL19+02O5XXFlCwAAALAzp0+f1ogRI1S9enW5urrK399fERER+u6774q8jfHjx2vdunVFGjtw4EBZLJZCX0FBQcU8kpK1ceNGWSwWVahQQZcvX7bq27FjhxnvP8enpqbe5Ej/RrEFAAAA2JlevXrphx9+UHx8vH755RetXLlSHTp00F9//VXkbXh6eqpSpUpFGjt37lwdP37cfElSbGysubxjx45iHYetlC9fXp9//rlV23vvvafq1auXUkQFo9gCAAAA7Ehqaqq2bNmi6dOnq2PHjqpRo4ZatGihCRMmqFu3bua4lJQUde/eXZ6envLy8tLDDz+skydPmv3R0dFq3Lhxkfbp7e0tf39/8yVJPj4+8vf318SJEzVo0CCr8VlZWfL19dV7770nSerQoYNGjRqlUaNGydvbW5UrV9ZLL70kwzDMdTIyMjR+/HjdcccdKleunEJDQ7Vx48ZinaMBAwZo8eLF5vKlS5e0bNkyDRgwoFjbsxWKLQAAAMCOeHp6ytPTU8uXL1dGRkaBY3Jzc9W9e3edOXNGmzZtUkJCgn777Tf16dOnxOMZOnSo1qxZY17xkqRVq1YpPT3dan/x8fFycnLS9u3bNXfuXM2aNUvvvvuu2T9q1CglJiZq2bJl2rNnj3r37q3IyEgdPHjQHOPo6Ki4uLhrxvToo49qy5YtSklJkST997//VVBQkJo2bVoCR1xyKLYAAAAAO+Lk5KS4uDjFx8fLx8dHrVu31sSJE7Vnzx5zzLp167R3714tXbpUzZo1U2hoqN5//31t2rSpxG/5a9WqlUJCQvTBBx+YbbGxserdu7c8PT3NtsDAQM2ePVshISGKiorS6NGjNXv2bEl/X4WLjY3Vp59+qrZt26pWrVoaP3682rRpo9jYWHMbISEh8vb2vmZMvr6+6tq1q1mYLV68WIMHDy6hIy45FFsAAACAnenVq5eOHTumlStXKjIyUhs3blTTpk3N4uLAgQMKDAxUYGCguU69evXk4+OjAwcOlHg8Q4cONYuikydPavXq1fmKm5YtW1pNThEWFqaDBw8qJydHe/fuVU5OjurUqWNeufP09NSmTZt06NAhc539+/erZ8+eRYpp8ODBiouL02+//abExERFRUWVwJGWLKZ+BwAAAOyQm5ubOnfurM6dO+ull17S0KFD9fLLL2vgwIE3PZb+/fvr+eefV2JiorZu3arg4GC1bdu2yOtfuHBBjo6O2rVrlxwdHa36rrw6dj26du2q4cOHa8iQIXrwwQeLPBnIzUSxBQAAAJQB9erVM38jq27dujp69KiOHj1qXt3av3+/UlNTVa9evRLfd6VKldSjRw/FxsYqMTEx34QZkrRt2zar5e+//161a9eWo6OjmjRpopycHJ06darAIi03N/e6Y3JyclL//v01Y8YMrV69+rrXvxm4jRAAAACwI3/99Zfuvfdeffjhh9qzZ48OHz6sTz/9VDNmzFD37t0lSeHh4WrQoIGioqK0e/dubd++Xf3791f79u3VvHlzm8Q1dOhQxcfH68CBAwXO+peSkqKxY8cqOTlZH330kebNm6cxY8ZIkurUqaOoqCj1799fn332mQ4fPqzt27crJiZGX375pbmNevXq5ZvS/WpeeeUVnT59WhEREVcdt3fvXiUlJZmvH3/8scj7uBFc2QIAAMBtp8roUcrNzVVaWpq8vLzk4GA/1yA8PT0VGhqq2bNn69ChQ8rKylJgYKCGDRumiRMnSpIsFotWrFih0aNHq127dnJwcFBkZKTmzZtns7jCw8NVtWpV1a9fXwEBAfn6+/fvr0uXLqlFixZydHTUmDFjNHz4cLM/NjZWU6dO1bhx4/THH3+ocuXKatmypR544AFzTHJyss6dO1fkmFxcXFS5cuVrjmvXrp3VsqOjo7Kzs4u8n+Ki2AIAAADsiKurq2JiYhQTE3PVcdWrV9eKFSsK7Y+OjlZ0dLS5XJQp1fNc+ftYeS5evKizZ89qyJAhBa7j7OysOXPmaMGCBYX2T548WZMnT87Xl3cbYU5OzlUL3w4dOhQYW54ePXpY9V9rvK1RbAEAAAAoVG5urv7880+98cYb8vHxsfphZVwdxRYAAACAQqWkpCg4OFjVqlVTXFycnJwoIYqKMwUAAACgUEFBQde8FW/jxo03J5gyxn6eBAQAAACAWwjFFgAAAG55pTlJAsqmknjPUGwBAADgluXs7CxJSk9PL+VIUNbkvWfy3kPFwTNbAAAAuGU5OjrKx8dHp06dkiR5eHjIYrFI+nuWvczMTF2+fNmufmfrdmRPuTAMQ+np6Tp16pR8fHzk6OhY7G1RbAEAAOCW5u/vL0lmwZXHMAxdunRJ7u7uZgGG0mGPufDx8THfO8VFsQUAAIBbmsViUdWqVeXr66usrCyzPSsrS5s3b1a7du1u6FYx3Dh7y4Wzs/MNXdHKQ7EFAACA24Kjo6PVF2hHR0dlZ2fLzc3NLr7g385u1VxwcyoAAAAA2ADFFgAAAADYAMUWAAAAANgAxRYAAAAA2ADFFgAAAADYAMUWAAAAANgAxRYAAAAA2ADFFgAAAADYAMUWAAAAANgAxRYAAAAA2ADFFgAAAADYAMUWAAAAANgAxRYAAAAA2ADFFgAAAADYAMUWAAAAANgAxRYAAAAA2ECpFlubN2/Wgw8+qICAAFksFi1fvtzsy8rK0nPPPacGDRqoXLlyCggIUP/+/XXs2DGrbZw5c0ZRUVHy8vKSj4+PhgwZogsXLliN2bNnj9q2bSs3NzcFBgZqxowZN+PwAAAAANzGSrXYunjxoho1aqT58+fn60tPT9fu3bv10ksvaffu3frss8+UnJysbt26WY2LiorSvn37lJCQoFWrVmnz5s0aPny42Z+WlqYuXbqoRo0a2rVrl2bOnKno6GgtWrTI5scHAAAA4PblVJo779q1q7p27Vpgn7e3txISEqza3nrrLbVo0UIpKSmqXr26Dhw4oDVr1mjHjh1q3ry5JGnevHm677779PrrrysgIEBLlixRZmamFi9eLBcXF9WvX19JSUmaNWuWVVEGAAAAACWpVIut63Xu3DlZLBb5+PhIkhITE+Xj42MWWpIUHh4uBwcHbdu2TT179lRiYqLatWsnFxcXc0xERISmT5+us2fPqkKFCgXuKyMjQxkZGeZyWlqapL9vb8zKyrLB0RVd3v4tRk6pxpGntM9Haco79tv5HNgT8mE/yIV9IR/2g1zYF/JhP8paLooaZ5kpti5fvqznnntO/fr1k5eXlyTpxIkT8vX1tRrn5OSkihUr6sSJE+aY4OBgqzF+fn5mX2HFVkxMjCZPnpyvfe3atfLw8Ljh4ykJQZcPlXYIkqSvvvqltEModf+8CovSRT7sB7mwL+TDfpAL+0I+7EdZyUV6enqRxpWJYisrK0sPP/ywDMPQggULbso+J0yYoLFjx5rLaWlpCgwMVJcuXcxir7RkZWUpISFBR9xqybA4lmoskjSy452lHUKpyctF586d5ezsXNrh3PbIh/0gF/aFfNgPcmFfyIf9KGu5yLvr7VrsvtjKK7R+//13rV+/3qrQ8ff316lTp6zGZ2dn68yZM/L39zfHnDx50mpM3nLemIK4urrK1dU1X7uzs7PdvAEMi6NdFFv2cj5Kkz29L0A+7Am5sC/kw36QC/tCPuxHWclFUWO069/Zyiu0Dh48qG+++UaVKlWy6g8LC1Nqaqp27dpltq1fv165ubkKDQ01x2zevNnqvsqEhASFhIQUegshAAAAANyoUi22Lly4oKSkJCUlJUmSDh8+rKSkJKWkpCgrK0v/+te/tHPnTi1ZskQ5OTk6ceKETpw4oczMTElS3bp1FRkZqWHDhmn79u367rvvNGrUKPXt21cBAQGSpEceeUQuLi4aMmSI9u3bp48//lhz5861ukUQAAAAAEpaqd5GuHPnTnXs2NFcziuABgwYoOjoaK1cuVKS1LhxY6v1NmzYoA4dOkiSlixZolGjRqlTp05ycHBQr1699Oabb5pjvb29tXbtWo0cOVLNmjVT5cqVNWnSJKZ9BwAAAGBTpVpsdejQQYZhFNp/tb48FStW1NKlS686pmHDhtqyZct1xwcAAAAAxWXXz2wBAAAAQFlFsQUAAAAANkCxBQAAAAA2QLEFAAAAADZAsQUAAAAANkCxBQAAAAA2QLEFAAAAADZAsQUAAAAANkCxBQAAAAA2QLEFAAAAADZAsQUAAAAANkCxBQAAAAA2QLEFAAAAADZAsQUAAAAANkCxBQAAAAA2QLEFAAAAADZAsQUAAAAANkCxBQAAAAA2QLEFAAAAADZAsQUAAAAANkCxBQAAAAA2QLEFAAAAADZAsQUAAAAANkCxBQAAAAA2QLEFAAAAADZAsQUAAAAANkCxBQAAAAA2QLEFAAAAADZAsQUAAAAANkCxBQAAAAA2QLEFAAAAADZAsQUAAAAANkCxBQAAAAA2QLEFAAAAADZAsQUAAAAANkCxBQAAAAA2QLEFAAAAADZAsQUAAAAANkCxBQAAAAA2QLEFAAAAADZAsQUAAAAANkCxBQAAAAA2QLEFAAAAADZAsQUAAAAANkCxBQAAAAA2QLEFAAAAADZQqsXW5s2b9eCDDyogIEAWi0XLly+36jcMQ5MmTVLVqlXl7u6u8PBwHTx40GrMmTNnFBUVJS8vL/n4+GjIkCG6cOGC1Zg9e/aobdu2cnNzU2BgoGbMmGHrQwMAAABwmyvVYuvixYtq1KiR5s+fX2D/jBkz9Oabb2rhwoXatm2bypUrp4iICF2+fNkcExUVpX379ikhIUGrVq3S5s2bNXz4cLM/LS1NXbp0UY0aNbRr1y7NnDlT0dHRWrRokc2PDwAAAMDty6k0d961a1d17dq1wD7DMDRnzhy9+OKL6t69uyTp/fffl5+fn5YvX66+ffvqwIEDWrNmjXbs2KHmzZtLkubNm6f77rtPr7/+ugICArRkyRJlZmZq8eLFcnFxUf369ZWUlKRZs2ZZFWUAAAAAUJJKtdi6msOHD+vEiRMKDw8327y9vRUaGqrExET17dtXiYmJ8vHxMQstSQoPD5eDg4O2bdumnj17KjExUe3atZOLi4s5JiIiQtOnT9fZs2dVoUKFAvefkZGhjIwMczktLU2SlJWVpaysrJI+3OuSt3+LkVOqceQp7fNRmvKO/XY+B/aEfNgPcmFfyIf9IBf2hXzYj7KWi6LGabfF1okTJyRJfn5+Vu1+fn5m34kTJ+Tr62vV7+TkpIoVK1qNCQ4OzreNvL7Ciq2YmBhNnjw5X/vatWvl4eFRjCMqeUGXD5V2CJKkr776pbRDKHUJCQmlHQKuQD7sB7mwL+TDfpAL+0I+7EdZyUV6enqRxtltsVXaJkyYoLFjx5rLaWlpCgwMVJcuXeTl5VWKkf1dSSckJOiIWy0ZFsdSjUWSRna8s7RDKDV5uejcubOcnZ1LO5zbHvmwH+TCvpAP+0Eu7Av5sB9lLRd5d71di90WW/7+/pKkkydPqmrVqmb7yZMn1bhxY3PMqVOnrNbLzs7WmTNnzPX9/f118uRJqzF5y3ljCuLq6ipXV9d87c7OznbzBjAsjnZRbNnL+ShN9vS+APmwJ+TCvpAP+0Eu7Av5sB9lJRdFjdFuf2crODhY/v7+WrdundmWlpambdu2KSwsTJIUFham1NRU7dq1yxyzfv165ebmKjQ01ByzefNmq/sqExISFBISUugthAAAAABwo0q12Lpw4YKSkpKUlJQk6e9JMZKSkpSSkiKLxaKnnnpKU6dO1cqVK7V37171799fAQEB6tGjhySpbt26ioyM1LBhw7R9+3Z99913GjVqlPr27auAgABJ0iOPPCIXFxcNGTJE+/bt08cff6y5c+da3SIIAAAAACWtVG8j3Llzpzp27Ggu5xVAAwYMUFxcnJ599lldvHhRw4cPV2pqqtq0aaM1a9bIzc3NXGfJkiUaNWqUOnXqJAcHB/Xq1Utvvvmm2e/t7a21a9dq5MiRatasmSpXrqxJkyYx7TsAAAAAmyrVYqtDhw4yDKPQfovFoilTpmjKlCmFjqlYsaKWLl161f00bNhQW7ZsKXacAAAAAHC97PaZLQAAAAAoyyi2AAAAAMAGKLYAAAAAwAYotgAAAADABii2AAAAAMAGKLYAAAAAwAYotgAAAADABii2AAAAAMAGKLYAAAAAwAYotgAAAADABii2AAAAAMAGKLYAAAAAwAYotgAAAADABii2AAAAAMAGKLYAAAAAwAYotgAAAADABopVbP32228lHQcAAAAA3FKKVWzdeeed6tixoz788ENdvny5pGMCAAAAgDKvWMXW7t271bBhQ40dO1b+/v567LHHtH379pKODQAAAADKrGIVW40bN9bcuXN17NgxLV68WMePH1ebNm109913a9asWTp9+nRJxwkAAAAAZcoNTZDh5OSkhx56SJ9++qmmT5+uX3/9VePHj1dgYKD69++v48ePl1ScAAAAAFCm3FCxtXPnTj3xxBOqWrWqZs2apfHjx+vQoUNKSEjQsWPH1L1795KKEwAAAADKFKfirDRr1izFxsYqOTlZ9913n95//33dd999cnD4u3YLDg5WXFycgoKCSjJWAAAAACgzilVsLViwQIMHD9bAgQNVtWrVAsf4+vrqvffeu6HgAAAAAKCsKlaxdfDgwWuOcXFx0YABA4qzeQAAAAAo84r1zFZsbKw+/fTTfO2ffvqp4uPjbzgoAAAAACjrilVsxcTEqHLlyvnafX199dprr91wUAAAAABQ1hWr2EpJSVFwcHC+9ho1aiglJeWGgwIAAACAsq5YxZavr6/27NmTr/3HH39UpUqVbjgoAAAAACjrilVs9evXT08++aQ2bNignJwc5eTkaP369RozZoz69u1b0jECAAAAQJlTrNkIX3nlFR05ckSdOnWSk9Pfm8jNzVX//v15ZgsAAAAAVMxiy8XFRR9//LFeeeUV/fjjj3J3d1eDBg1Uo0aNko4PAAAAAMqkYhVbeerUqaM6deqUVCwAAAAAcMsoVrGVk5OjuLg4rVu3TqdOnVJubq5V//r160skOAAAAAAoq4pVbI0ZM0ZxcXG6//77dffdd8tisZR0XAAAAABQphWr2Fq2bJk++eQT3XfffSUdDwAAAADcEoo19buLi4vuvPPOko4FAAAAAG4ZxSq2xo0bp7lz58owjJKOBwAAAABuCcW6jfDbb7/Vhg0btHr1atWvX1/Ozs5W/Z999lmJBAcAAAAAZVWxii0fHx/17NmzpGMBAAAAgFtGsYqt2NjYko4DAAAAAG4pxXpmS5Kys7P1zTff6J133tH58+clSceOHdOFCxdKLDgAAAAAKKuKdWXr999/V2RkpFJSUpSRkaHOnTurfPnymj59ujIyMrRw4cKSjhMAAAAAypRiXdkaM2aMmjdvrrNnz8rd3d1s79mzp9atW1diwQEAAABAWVWsK1tbtmzR1q1b5eLiYtUeFBSkP/74o0QCAwAAAICyrFhXtnJzc5WTk5Ov/X//+5/Kly9/w0EBAAAAQFlXrGKrS5cumjNnjrlssVh04cIFvfzyy7rvvvtKKjYAAAAAKLOKVWy98cYb+u6771SvXj1dvnxZjzzyiHkL4fTp00ssuJycHL300ksKDg6Wu7u7atWqpVdeeUWGYZhjDMPQpEmTVLVqVbm7uys8PFwHDx602s6ZM2cUFRUlLy8v+fj4aMiQIcyaCAAAAMCmivXMVrVq1fTjjz9q2bJl2rNnjy5cuKAhQ4YoKirKasKMGzV9+nQtWLBA8fHxql+/vnbu3KlBgwbJ29tbTz75pCRpxowZevPNNxUfH6/g4GC99NJLioiI0P79++Xm5iZJioqK0vHjx5WQkKCsrCwNGjRIw4cP19KlS0ssVgAAAAC4UrGKLUlycnLSv//975KMJZ+tW7eqe/fuuv/++yX9PQHHRx99pO3bt0v6+6rWnDlz9OKLL6p79+6SpPfff19+fn5avny5+vbtqwMHDmjNmjXasWOHmjdvLkmaN2+e7rvvPr3++usKCAiw6TEAAAAAuD0Vq9h6//33r9rfv3//YgXzT61atdKiRYv0yy+/qE6dOvrxxx/17bffatasWZKkw4cP68SJEwoPDzfX8fb2VmhoqBITE9W3b18lJibKx8fHLLQkKTw8XA4ODtq2bZt69uxZ4L4zMjKUkZFhLqelpUmSsrKylJWVVSLHV1x5+7cY+ScpKQ2lfT5KU96x387nwJ6QD/tBLuwL+bAf5MK+kA/7UdZyUdQ4i1VsjRkzJt/O0tPT5eLiIg8PjxIrtp5//nmlpaXprrvukqOjo3JycvTqq68qKipKknTixAlJkp+fn9V6fn5+Zt+JEyfk6+tr1e/k5KSKFSuaYwoSExOjyZMn52tfu3atPDw8bui4SkrQ5UOlHYIk6auvfintEEpdQkJCaYeAK5AP+0Eu7Av5sB/kwr6QD/tRVnKRnp5epHHFKrbOnj2br+3gwYMaMWKEnnnmmeJsskCffPKJlixZoqVLl6p+/fpKSkrSU089pYCAAA0YMKDE9lOQCRMmaOzYseZyWlqaAgMD1aVLF3l5edl039eSlZWlhIQEHXGrJcPiWKqxSNLIjneWdgilJi8XnTt3lrOzc2mHc9sjH/aDXNgX8mE/yIV9IR/2o6zlIu+ut2sp9jNb/1S7dm1NmzZN//73v/Xzzz+XyDafeeYZPf/88+rbt68kqUGDBvr9998VExOjAQMGyN/fX5J08uRJVa1a1Vzv5MmTaty4sSTJ399fp06dstpudna2zpw5Y65fEFdXV7m6uuZrd3Z2tps3gGFxtItiy17OR2myp/cFyIc9IRf2hXzYD3JhX8iH/SgruShqjMWa+r0wTk5OOnbsWIltLz09XQ4O1iE6OjoqNzdXkhQcHCx/f3+tW7fO7E9LS9O2bdsUFhYmSQoLC1Nqaqp27dpljlm/fr1yc3MVGhpaYrECAAAAwJWKdWVr5cqVVsuGYej48eN666231Lp16xIJTJIefPBBvfrqq6pevbrq16+vH374QbNmzdLgwYMl/f1jyk899ZSmTp2q2rVrm1O/BwQEqEePHpKkunXrKjIyUsOGDdPChQuVlZWlUaNGqW/fvsxECAAAAMBmilVs5RUyeSwWi6pUqaJ7771Xb7zxRknEJenvKdpfeuklPfHEEzp16pQCAgL02GOPadKkSeaYZ599VhcvXtTw4cOVmpqqNm3aaM2aNeZvbEnSkiVLNGrUKHXq1EkODg7q1auX3nzzzRKLEwAAAAD+qVjFVt5tfLZWvnx5zZkzR3PmzCl0jMVi0ZQpUzRlypRCx1SsWJEfMAYAAABwU5XoM1sAAAAAgL8V68rWlVOiX0veDxADAAAAwO2kWMXWDz/8oB9++EFZWVkKCQmRJP3yyy9ydHRU06ZNzXEWi6VkogQAAACAMqZYxdaDDz6o8uXLKz4+XhUqVJD09w8dDxo0SG3bttW4ceNKNEgAAAAAKGuK9czWG2+8oZiYGLPQkqQKFSpo6tSpJTobIQAAAACUVcUqttLS0nT69Ol87adPn9b58+dvOCgAAAAAKOuKVWz17NlTgwYN0meffab//e9/+t///qf//ve/GjJkiB566KGSjhEAAAAAypxiPbO1cOFCjR8/Xo888oiysrL+3pCTk4YMGaKZM2eWaIAAAAAAUBYVq9jy8PDQ22+/rZkzZ+rQoUOSpFq1aqlcuXIlGhwAAAAAlFU39KPGx48f1/Hjx1W7dm2VK1dOhmGUVFwAAAAAUKYVq9j666+/1KlTJ9WpU0f33Xefjh8/LkkaMmQI074DAAAAgIpZbD399NNydnZWSkqKPDw8zPY+ffpozZo1JRYcAAAAAJRVxXpma+3atfr6669VrVo1q/batWvr999/L5HAAAAAAKAsK9aVrYsXL1pd0cpz5swZubq63nBQAAAAAFDWFavYatu2rd5//31z2WKxKDc3VzNmzFDHjh1LLDgAAAAAKKuKdRvhjBkz1KlTJ+3cuVOZmZl69tlntW/fPp05c0bfffddSccIAAAAAGVOsa5s3X333frll1/Upk0bde/eXRcvXtRDDz2kH374QbVq1SrpGAEAAACgzLnuK1tZWVmKjIzUwoUL9cILL9giJgAAAAAo8677ypazs7P27Nlji1gAAAAA4JZRrGe2/v3vf+u9997TtGnTSjoeXIcfz3+mbOVe93pNvfrYIBoAAAAAVypWsZWdna3Fixfrm2++UbNmzVSuXDmr/lmzZpVIcAAAAABQVl1XsfXbb78pKChIP/30k5o2bSpJ+uWXX6zGWCyWkosOAAAAAMqo6yq2ateurePHj2vDhg2SpD59+ujNN9+Un5+fTYIDAAAAgLLquibIMAzDann16tW6ePFiiQYEAAAAALeCYv3OVp5/Fl8AAAAAgL9dV7FlsVjyPZPFM1oAAAAAkN91PbNlGIYGDhwoV1dXSdLly5f1+OOP55uN8LPPPiu5CAEAAACgDLquYmvAgAFWy//+979LNBgAAAAAuFVcV7EVGxtrqzgAAAAA4JZyQxNkAAAAAAAKRrEFAAAAADZAsQUAAAAANkCxBQAAAAA2QLEFAAAAADZAsQUAAAAANkCxBQAAAAA2QLEFAAAAADZAsQUAAAAANkCxBQAAAAA2QLEFAAAAADZAsQUAAAAANkCxBQAAAAA2QLEFAAAAADZAsQUAAAAANkCxBQAAAAA2QLEFAAAAADZg98XWH3/8oX//+9+qVKmS3N3d1aBBA+3cudPsNwxDkyZNUtWqVeXu7q7w8HAdPHjQahtnzpxRVFSUvLy85OPjoyFDhujChQs3+1AAAAAA3Ebsutg6e/asWrduLWdnZ61evVr79+/XG2+8oQoVKphjZsyYoTfffFMLFy7Utm3bVK5cOUVEROjy5cvmmKioKO3bt08JCQlatWqVNm/erOHDh5fGIQEAAAC4TTiVdgBXM336dAUGBio2NtZsCw4ONv9sGIbmzJmjF198Ud27d5ckvf/++/Lz89Py5cvVt29fHThwQGvWrNGOHTvUvHlzSdK8efN033336fXXX1dAQMDNPSgAAAAAtwW7LrZWrlypiIgI9e7dW5s2bdIdd9yhJ554QsOGDZMkHT58WCdOnFB4eLi5jre3t0JDQ5WYmKi+ffsqMTFRPj4+ZqElSeHh4XJwcNC2bdvUs2fPAvedkZGhjIwMczktLU2SlJWVpaysLFscbpHl7d+pmBcmLUZOSYZT6uejNOUd++18DuwJ+bAf5MK+kA/7QS7sC/mwH2UtF0WN066Lrd9++00LFizQ2LFjNXHiRO3YsUNPPvmkXFxcNGDAAJ04cUKS5OfnZ7Wen5+f2XfixAn5+vpa9Ts5OalixYrmmILExMRo8uTJ+drXrl0rDw+PGz20EvGAU73irXjplxKN46uvSnZ7ZVFCQkJph4ArkA/7QS7sC/mwH+TCvpAP+1FWcpGenl6kcXZdbOXm5qp58+Z67bXXJElNmjTRTz/9pIULF2rAgAE23feECRM0duxYczktLU2BgYHq0qWLvLy8bLrva8nKyvr7+bPs/cpW7nWv36j8QyUaz8iOd5bo9sqSvFx07txZzs7OpR3ObY982A9yYV/Ih/0gF/aFfNiPspaLvLversWui62qVauqXj3rqzd169bVf//7X0mSv7+/JOnkyZOqWrWqOebkyZNq3LixOebUqVNW28jOztaZM2fM9Qvi6uoqV1fXfO3Ozs528wbIVm6xii3D4liicdjL+ShN9vS+APmwJ+TCvpAP+0Eu7Av5sB9lJRdFjdGuZyNs3bq1kpOTrdp++eUX1ahRQ9Lfk2X4+/tr3bp1Zn9aWpq2bdumsLAwSVJYWJhSU1O1a9cuc8z69euVm5ur0NDQm3AUAAAAAG5Hdn1l6+mnn1arVq302muv6eGHH9b27du1aNEiLVq0SJJksVj01FNPaerUqapdu7aCg4P10ksvKSAgQD169JD095WwyMhIDRs2TAsXLlRWVpZGjRqlvn37MhMhAAAAAJux62Lrnnvu0eeff64JEyZoypQpCg4O1pw5cxQVFWWOefbZZ3Xx4kUNHz5cqampatOmjdasWSM3NzdzzJIlSzRq1Ch16tRJDg4O6tWrl958883SOCQAAAAAtwm7LrYk6YEHHtADDzxQaL/FYtGUKVM0ZcqUQsdUrFhRS5cutUV4AAAAAFAgu35mCwAAAADKKootAAAAALABii0AAAAAsAGKLQAAAACwAYotAAAAALABii0AAAAAsAGKLQAAAACwAYotAAAAALABii0AAAAAsAGKLQAAAACwAYotAAAAALABii0AAAAAsAGKLQAAAACwAYotAAAAALABii0AAAAAsAGKLQAAAACwAYotAAAAALABii0AAAAAsAGKLQAAAACwAYotAAAAALABii0AAAAAsAGKLQAAAACwAYotAAAAALABii0AAAAAsAGKLQAAAACwAYotAAAAALABii0AAAAAsAGKLQAAAACwAYotAAAAALABii0AAAAAsAGKLQAAAACwAYotAAAAALABii0AAAAAsAGKLQAAAACwAYotAAAAALABii0AAAAAsAGKLQAAAACwAYotAAAAALABii0AAAAAsAGKLQAAAACwAYotAAAAALABii0AAAAAsAGKLQAAAACwAYotAAAAALABii0AAAAAsAGKLQAAAACwgTJVbE2bNk0Wi0VPPfWU2Xb58mWNHDlSlSpVkqenp3r16qWTJ09arZeSkqL7779fHh4e8vX11TPPPKPs7OybHD0AAACA20mZKbZ27Nihd955Rw0bNrRqf/rpp/XFF1/o008/1aZNm3Ts2DE99NBDZn9OTo7uv/9+ZWZmauvWrYqPj1dcXJwmTZp0sw8BAAAAwG2kTBRbFy5cUFRUlP7v//5PFSpUMNvPnTun9957T7NmzdK9996rZs2aKTY2Vlu3btX3338vSVq7dq3279+vDz/8UI0bN1bXrl31yiuvaP78+crMzCytQwIAAABwi3Mq7QCKYuTIkbr//vsVHh6uqVOnmu27du1SVlaWwsPDzba77rpL1atXV2Jiolq2bKnExEQ1aNBAfn5+5piIiAiNGDFC+/btU5MmTQrcZ0ZGhjIyMszltLQ0SVJWVpaysrJK+hCvS97+nYpZK1uMnJIMp9TPR2nKO/bb+RzYE/JhP8iFfSEf9oNc2BfyYT/KWi6KGqfdF1vLli3T7t27tWPHjnx9J06ckIuLi3x8fKza/fz8dOLECXPMlYVWXn9eX2FiYmI0efLkfO1r166Vh4fH9R6GTTzgVK94K176pUTj+Oqrkt1eWZSQkFDaIeAK5MN+kAv7Qj7sB7mwL+TDfpSVXKSnpxdpnF0XW0ePHtWYMWOUkJAgNze3m7rvCRMmaOzYseZyWlqaAgMD1aVLF3l5ed3UWP4pKytLCQkJWpW9X9nKve71G5V/6NqDrsPIjneW6PbKkrxcdO7cWc7OzqUdzm2PfNgPcmFfyIf9IBf2hXzYj7KWi7y73q7FroutXbt26dSpU2ratKnZlpOTo82bN+utt97S119/rczMTKWmplpd3Tp58qT8/f0lSf7+/tq+fbvVdvNmK8wbUxBXV1e5urrma3d2drabN0C2cotVbBkWxxKNw17OR2myp/cFyIc9IRf2hXzYD3JhX8iH/SgruShqjHY9QUanTp20d+9eJSUlma/mzZsrKirK/LOzs7PWrVtnrpOcnKyUlBSFhYVJksLCwrR3716dOnXKHJOQkCAvLy/Vq1fM2/AAAAAA4Brs+spW+fLldffdd1u1lStXTpUqVTLbhwwZorFjx6pixYry8vLS6NGjFRYWppYtW0qSunTponr16unRRx/VjBkzdOLECb344osaOXJkgVeuAAAAAKAk2HWxVRSzZ8+Wg4ODevXqpYyMDEVEROjtt982+x0dHbVq1SqNGDFCYWFhKleunAYMGKApU6aUYtQAAAAAbnVlrtjauHGj1bKbm5vmz5+v+fPnF7pOjRo19NVXX9k4MgAAAAD4f+z6mS0AAAAAKKsotgAAAADABii2AAAAAMAGKLYAAAAAwAYotgAAAADABii2AAAAAMAGKLYAAAAAwAYotgAAAADABii2AAAAAMAGKLYAAAAAwAYotgAAAADABii2AAAAAMAGKLYAAAAAwAYotgAAAADABii2AAAAAMAGKLYAAAAAwAYotgAAAADABii2AAAAAMAGKLYAAAAAwAYotgAAAADABii2AAAAAMAGKLYAAAAAwAYotgAAAADABii2AAAAAMAGKLYAAAAAwAYotgAAAADABii2AAAAAMAGKLYAAAAAwAYotgAAAADABii2AAAAAMAGKLYAAAAAwAYotgAAAADABii2AAAAAMAGKLYAAAAAwAYotgAAAADABii2AAAAAMAGKLYAAAAAwAYotgAAAADABii2AAAAAMAGKLYAAAAAwAYotgAAAADABii2AAAAAMAGKLYAAAAAwAYotgAAAADABii2AAAAAMAGKLYAAAAAwAYotgAAAADABuy+2IqJidE999yj8uXLy9fXVz169FBycrLVmMuXL2vkyJGqVKmSPD091atXL508edJqTEpKiu6//355eHjI19dXzzzzjLKzs2/moQAAAAC4jdh9sbVp0yaNHDlS33//vRISEpSVlaUuXbro4sWL5pinn35aX3zxhT799FNt2rRJx44d00MPPWT25+Tk6P7771dmZqa2bt2q+Ph4xcXFadKkSaVxSAAAAABuA06lHcC1rFmzxmo5Li5Ovr6+2rVrl9q1a6dz587pvffe09KlS3XvvfdKkmJjY1W3bl19//33atmypdauXav9+/frm2++kZ+fnxo3bqxXXnlFzz33nKKjo+Xi4pJvvxkZGcrIyDCX09LSJElZWVnKysqy4RFfW97+nYpZK1uMnJIMp9TPR2nKO/bb+RzYE/JhP8iFfSEf9oNc2BfyYT/KWi6KGqfFMAzDxrGUqF9//VW1a9fW3r17dffdd2v9+vXq1KmTzp49Kx8fH3NcjRo19NRTT+npp5/WpEmTtHLlSiUlJZn9hw8fVs2aNbV79241adIk336io6M1efLkfO1Lly6Vh4eHLQ4NAAAAQBmQnp6uRx55ROfOnZOXl1eh4+z+ytaVcnNz9dRTT6l169a6++67JUknTpyQi4uLVaElSX5+fjpx4oQ5xs/PL19/Xl9BJkyYoLFjx5rLaWlpCgwMVJcuXa56Qm+GrKwsJSQkaFX2fmUr97rXb1T+oWsPug4jO95ZotsrS/Jy0blzZzk7O5d2OLc98mE/yIV9IR/2g1zYF/JhP8paLvLueruWMlVsjRw5Uj/99JO+/fZbm+/L1dVVrq6u+dqdnZ3t5g2QrdxiFVuGxbFE47CX81Ga7Ol9AfJhT8iFfSEf9oNc2BfyYT/KSi6KGqPdT5CRZ9SoUVq1apU2bNigatWqme3+/v7KzMxUamqq1fiTJ0/K39/fHPPP2QnzlvPGAAAAAEBJsvtiyzAMjRo1Sp9//rnWr1+v4OBgq/5mzZrJ2dlZ69atM9uSk5OVkpKisLAwSVJYWJj27t2rU6dOmWMSEhLk5eWlevXq3ZwDAQAAAHBbsfvbCEeOHKmlS5dqxYoVKl++vPmMlbe3t9zd3eXt7a0hQ4Zo7Nixqlixory8vDR69GiFhYWpZcuWkqQuXbqoXr16evTRRzVjxgydOHFCL774okaOHFngrYIAAAAAcKPsvthasGCBJKlDhw5W7bGxsRo4cKAkafbs2XJwcFCvXr2UkZGhiIgIvf322+ZYR0dHrVq1SiNGjFBYWJjKlSunAQMGaMqUKTfrMAAAAADcZuy+2CrKzPRubm6aP3++5s+fX+iYGjVq6KuvvirJ0AAAAACgUHb/zBYAAAAAlEUUWwAAAABgAxRbAAAAAGADFFsAAAAAYAMUWwAAAABgA3Y/GyFK3u60j29o/aZefUooEgAAAODWxZUtAAAAALABrmzhhs1O+KW0QzA93blOaYcAAAAASOLKFgAAAADYBMUWAAAAANgAxRYAAAAA2ADFFgAAAADYAMUWAAAAANgAxRYAAAAA2ADFFgAAAADYAMUWAAAAANgAxRYAAAAA2ADFFgAAAADYAMUWAAAAANgAxRYAAAAA2ADFFgAAAADYAMUWAAAAANgAxRYAAAAA2ADFFgAAAADYgFNpB4Dia7Vxn4ycrGKvv6VTwxKMBgAAAMCVuLIFAAAAADZAsQUAAAAANkCxBQAAAAA2QLEFAAAAADZAsQUAAAAANkCxBQAAAAA2QLEFAAAAADZAsQUAAAAANsCPGuO67U77+IbWb+rVp4QiAQAAAOwXV7YAAAAAwAa4soVbyuyEX27q/ixGjoIlzd/wqwyLo1Xf053r3NRYAAAAYF+4sgUAAAAANkCxBQAAAAA2wG2EuOmYYAMAAAC3A65sAQAAAIANUGwBAAAAgA1QbAEAAACADVBsAQAAAIANMEEGypwbmWCDyTUAAABws1BsAbeJm/2Dz1fDDz4DAIDbAcUWbis3c9p5eypuAAAAcPPdVs9szZ8/X0FBQXJzc1NoaKi2b99e2iEBAAAAuEXdNle2Pv74Y40dO1YLFy5UaGio5syZo4iICCUnJ8vX17e0w0MZ8c8rY05yULDT3frx/GfKVq7N988zZwAAAGXHbVNszZo1S8OGDdOgQYMkSQsXLtSXX36pxYsX6/nnny/l6EpH23V7bngbWzo1LIFIAAAAgFvPbVFsZWZmateuXZowYYLZ5uDgoPDwcCUmJha4TkZGhjIyMszlc+fOSZLOnDmjrKws2wZ8DVlZWUpPT9fl7FwZtr+YclX3rL3xgq2kbGtz103fZ64clO6UrtzsTOXehCtbO9M/sPk+CtPAs9sNrb/3wkrzz1HXeRhF3bfFyFH1jHTN+mKXDIvj9e3kKq6M/VYT+u3PV+33dSnaZCZH7u1htZyXi6HLphb7qm9x3nNB65cXa19X+uex3Aps9dmwZ8Pa1SztEAqU9//wv/76S87Ozjd9//+3+bebvs/C2EOOSjsfhbGnPN0sRfl7yh7eM3nOnz8vSTIM46rjLMa1RtwCjh07pjvuuENbt25VWFiY2f7ss89q06ZN2rZtW751oqOjNXny5JsZJgAAAIAy5OjRo6pWrVqh/bfFla3imDBhgsaOHWsu5+bm6syZM6pUqZIsFkspRialpaUpMDBQR48elZeXV6nGcrsjF/aFfNgPcmFfyIf9IBf2hXzYj7KWC8MwdP78eQUEBFx13G1RbFWuXFmOjo46efKkVfvJkyfl7+9f4Dqurq5ydXW1avPx8bFViMXi5eVVJt6MtwNyYV/Ih/0gF/aFfNgPcmFfyIf9KEu58Pb2vuaY22LqdxcXFzVr1kzr1q0z23Jzc7Vu3Tqr2woBAAAAoKTcFle2JGns2LEaMGCAmjdvrhYtWmjOnDm6ePGiOTshAAAAAJSk26bY6tOnj06fPq1JkybpxIkTaty4sdasWSM/P7/SDu26ubq66uWXX853myNuPnJhX8iH/SAX9oV82A9yYV/Ih/24VXNxW8xGCAAAAAA3223xzBYAAAAA3GwUWwAAAABgAxRbAAAAAGADFFsAAAAAYAMUW2XM/PnzFRQUJDc3N4WGhmr79u2lHdItJyYmRvfcc4/Kly8vX19f9ejRQ8nJyVZjOnToIIvFYvV6/PHHrcakpKTo/vvvl4eHh3x9ffXMM88oOzv7Zh7KLSE6Ojrfub7rrrvM/suXL2vkyJGqVKmSPD091atXr3w/YE4uSkZQUFC+XFgsFo0cOVISnwtb27x5sx588EEFBATIYrFo+fLlVv2GYWjSpEmqWrWq3N3dFR4eroMHD1qNOXPmjKKiouTl5SUfHx8NGTJEFy5csBqzZ88etW3bVm5ubgoMDNSMGTNsfWhlztVykZWVpeeee04NGjRQuXLlFBAQoP79++vYsWNW2yjo8zRt2jSrMeSiaK712Rg4cGC+cx0ZGWk1hs9GybhWLgr6f4jFYtHMmTPNMbfaZ4Niqwz5+OOPNXbsWL388svavXu3GjVqpIiICJ06daq0Q7ulbNq0SSNHjtT333+vhIQEZWVlqUuXLrp48aLVuGHDhun48ePm68oPek5Oju6//35lZmZq69atio+PV1xcnCZNmnSzD+eWUL9+fatz/e2335p9Tz/9tL744gt9+umn2rRpk44dO6aHHnrI7CcXJWfHjh1WeUhISJAk9e7d2xzD58J2Ll68qEaNGmn+/PkF9s+YMUNvvvmmFi5cqG3btqlcuXKKiIjQ5cuXzTFRUVHat2+fEhIStGrVKm3evFnDhw83+9PS0tSlSxfVqFFDu3bt0syZMxUdHa1FixbZ/PjKkqvlIj09Xbt379ZLL72k3bt367PPPlNycrK6deuWb+yUKVOsPi+jR482+8hF0V3rsyFJkZGRVuf6o48+surns1EyrpWLK3Nw/PhxLV68WBaLRb169bIad0t9NgyUGS1atDBGjhxpLufk5BgBAQFGTExMKUZ16zt16pQhydi0aZPZ1r59e2PMmDGFrvPVV18ZDg4OxokTJ8y2BQsWGF5eXkZGRoYtw73lvPzyy0ajRo0K7EtNTTWcnZ2NTz/91Gw7cOCAIclITEw0DINc2NKYMWOMWrVqGbm5uYZh8Lm4mSQZn3/+ubmcm5tr+Pv7GzNnzjTbUlNTDVdXV+Ojjz4yDMMw9u/fb0gyduzYYY5ZvXq1YbFYjD/++MMwDMN4++23jQoVKljl47nnnjNCQkJsfERl1z9zUZDt27cbkozff//dbKtRo4Yxe/bsQtchF8VTUD4GDBhgdO/evdB1+GzYRlE+G927dzfuvfdeq7Zb7bPBla0yIjMzU7t27VJ4eLjZ5uDgoPDwcCUmJpZiZLe+c+fOSZIqVqxo1b5kyRJVrlxZd999tyZMmKD09HSzLzExUQ0aNLD60eyIiAilpaVp3759NyfwW8jBgwcVEBCgmjVrKioqSikpKZKkXbt2KSsry+pzcdddd6l69erm54Jc2EZmZqY+/PBDDR48WBaLxWznc1E6Dh8+rBMnTlh9Fry9vRUaGmr1WfDx8VHz5s3NMeHh4XJwcNC2bdvMMe3atZOLi4s5JiIiQsnJyTp79uxNOppbz7lz52SxWOTj42PVPm3aNFWqVElNmjTRzJkzrW6pJRcla+PGjfL19VVISIhGjBihv/76y+zjs1E6Tp48qS+//FJDhgzJ13crfTacSjsAFM2ff/6pnJwcqy8pkuTn56eff/65lKK69eXm5uqpp55S69atdffdd5vtjzzyiGrUqKGAgADt2bNHzz33nJKTk/XZZ59Jkk6cOFFgrvL6UHShoaGKi4tTSEiIjh8/rsmTJ6tt27b66aefdOLECbm4uOT7AuPn52eeZ3JhG8uXL1dqaqoGDhxotvG5KD1556+g83vlZ8HX19eq38nJSRUrVrQaExwcnG8beX0VKlSwSfy3ssuXL+u5555Tv3795OXlZbY/+eSTatq0qSpWrKitW7dqwoQJOn78uGbNmiWJXJSkyMhIPfTQQwoODtahQ4c0ceJEde3aVYmJiXJ0dOSzUUri4+NVvnx5q1v/pVvvs0GxBVzFyJEj9dNPP1k9IyTJ6j7uBg0aqGrVqurUqZMOHTqkWrVq3ewwb2ldu3Y1/9ywYUOFhoaqRo0a+uSTT+Tu7l6Kkd3e3nvvPXXt2lUBAQFmG58LwFpWVpYefvhhGYahBQsWWPWNHTvW/HPDhg3l4uKixx57TDExMXJ1db3Zod7S+vbta/65QYMGatiwoWrVqqWNGzeqU6dOpRjZ7W3x4sWKioqSm5ubVfut9tngNsIyonLlynJ0dMw3y9rJkyfl7+9fSlHd2kaNGqVVq1Zpw4YNqlat2lXHhoaGSpJ+/fVXSZK/v3+BucrrQ/H5+PioTp06+vXXX+Xv76/MzEylpqZajbnyc0EuSt7vv/+ub775RkOHDr3qOD4XN0/e+bva/yP8/f3zTaiUnZ2tM2fO8HmxgbxC6/fff1dCQoLVVa2ChIaGKjs7W0eOHJFELmypZs2aqly5stXfTXw2bq4tW7YoOTn5mv8fkcr+Z4Niq4xwcXFRs2bNtG7dOrMtNzdX69atU1hYWClGdusxDEOjRo3S559/rvXr1+e7VF2QpKQkSVLVqlUlSWFhYdq7d6/VX955/7OtV6+eTeK+XVy4cEGHDh1S1apV1axZMzk7O1t9LpKTk5WSkmJ+LshFyYuNjZWvr6/uv//+q47jc3HzBAcHy9/f3+qzkJaWpm3btll9FlJTU7Vr1y5zzPr165Wbm2sWxmFhYdq8ebOysrLMMQkJCQoJCbG7W3PsWV6hdfDgQX3zzTeqVKnSNddJSkqSg4ODeTsbubCd//3vf/rrr7+s/m7is3Fzvffee2rWrJkaNWp0zbFl/rNR2jN0oOiWLVtmuLq6GnFxccb+/fuN4cOHGz4+PlYze+HGjRgxwvD29jY2btxoHD9+3Hylp6cbhmEYv/76qzFlyhRj586dxuHDh40VK1YYNWvWNNq1a2duIzs727j77ruNLl26GElJScaaNWuMKlWqGBMmTCitwyqzxo0bZ2zcuNE4fPiw8d133xnh4eFG5cqVjVOnThmGYRiPP/64Ub16dWP9+vXGzp07jbCwMCMsLMxcn1yUrJycHKN69erGc889Z9XO58L2zp8/b/zwww/GDz/8YEgyZs2aZfzwww/mDHfTpk0zfHx8jBUrVhh79uwxunfvbgQHBxuXLl0ytxEZGWk0adLE2LZtm/Htt98atWvXNvr162f2p6amGn5+fsajjz5q/PTTT8ayZcsMDw8P45133rnpx2vPrpaLzMxMo1u3bka1atWMpKQkq/+P5M2etnXrVmP27NlGUlKScejQIePDDz80qlSpYvTv39/cB7kouqvl4/z588b48eONxMRE4/Dhw8Y333xjNG3a1Khdu7Zx+fJlcxt8NkrGtf6eMgzDOHfunOHh4WEsWLAg3/q34meDYquMmTdvnlG9enXDxcXFaNGihfH999+Xdki3HEkFvmJjYw3DMIyUlBSjXbt2RsWKFQ1XV1fjzjvvNJ555hnj3LlzVts5cuSI0bVrV8Pd3d2oXLmyMW7cOCMrK6sUjqhs69Onj1G1alXDxcXFuOOOO4w+ffoYv/76q9l/6dIl44knnjAqVKhgeHh4GD179jSOHz9utQ1yUXK+/vprQ5KRnJxs1c7nwvY2bNhQ4N9NAwYMMAzj7+nfX3rpJcPPz89wdXU1OnXqlC9Pf/31l9GvXz/D09PT8PLyMgYNGmScP3/easyPP/5otGnTxnB1dTXuuOMOY9q0aTfrEMuMq+Xi8OHDhf5/ZMOGDYZhGMauXbuM0NBQw9vb23BzczPq1q1rvPbaa1Zf/g2DXBTV1fKRnp5udOnSxahSpYrh7Oxs1KhRwxg2bFi+f6jms1EyrvX3lGEYxjvvvGO4u7sbqamp+da/FT8bFsMwDJteOgMAAACA2xDPbAEAAACADVBsAQAAAIANUGwBAAAAgA1QbAEAAACADVBsAQAAAIANUGwBAAAAgA1QbAEAAACADVBsAQAAAIANUGwBwE0WFBSkOXPm3PB2Bg4cqB49etzwdq4lOjpajRs3LvVtoGBHjhyRxWJRUlLSda+7bt061a1bVzk5OSUWT2ZmpoKCgrRz586rjtu4caMsFossFovV+7hDhw566qmnSiyem6GwYwEAii0A+IfCvuzFxcXJx8fnpsdTmLlz5youLq60w5Akff7552rZsqW8vb1Vvnx51a9f366/MOfk5GjatGm666675O7urooVKyo0NFTvvvuuOcYev/SXdIH97LPP6sUXX5Sjo6Okop2Xa3FxcdH48eP13HPPFWl8cnLydb2Po6OjZbFY9Pjjj1u1JyUlyWKx6MiRI1btv//+u9zd3XXhwoUi7+NKR44c0ZAhQxQcHCx3d3fVqlVLL7/8sjIzM80xrVq10vHjx/Xwww8Xax8Abl1OpR0AAMBaVlaWnJ2drznO29v7JkRzbevWrVOfPn306quvqlu3brJYLNq/f78SEhJKOzRlZmbKxcUlX/vkyZP1zjvv6K233lLz5s2VlpamnTt36uzZs9e1fcMwlJOTIyensve/02+//VaHDh1Sr169zLaSOi9RUVEaN26c9u3bp/r16191rK+v73X/I4abm5vee+89jRs3TrVr177q2BUrVqhjx47y9PS8rn3k+fnnn5Wbm6t33nlHd955p3766ScNGzZMFy9e1Ouvvy7p7wLT399f7u7uysjIKNZ+ANyauLIFAMWUd5Xh9ddfV9WqVVWpUiWNHDlSWVlZ5phTp07pwQcflLu7u4KDg7VkyZJ827FYLFqwYIG6deumcuXK6dVXX1VOTo7Vv6aHhIRo7ty5Be4/T4cOHfTkk0/q2WefVcWKFeXv76/o6GirdVJTUzV06FBVqVJFXl5euvfee/Xjjz9ajZk2bZr8/PxUvnx5DRkyRJcvX77qefjiiy/UunVrPfPMMwoJCVGdOnXUo0cPzZ8/P9/YDz74QEFBQfL29lbfvn11/vx5sy83N1cxMTHmMTdq1Ej/+c9/zP7rOSevvvqqAgICFBISUmDMK1eu1BNPPKHevXsrODhYjRo10pAhQzR+/HhzO5s2bdLcuXPN28OOHDli3i62evVqNWvWTK6urvr222+vGXveeuvWrVPz5s3l4eGhVq1aKTk52SquqVOnytfXV+XLl9fQoUP1/PPPm7dfRkdHKz4+XitWrDBj2rhxo7nub7/9po4dO8rDw0ONGjVSYmLiVfO2bNkyde7cWW5ubkU+L1LBt8E2btzY6r1WoUIFtW7dWsuWLbtqDEXx5Zdfytvb2+qzExISoo4dO+qFF1645vorVqxQt27dJP2/98drr70mPz8/+fj4aMqUKcrOztYzzzyjihUrqlq1aoqNjTXXj4yMVGxsrLp06aKaNWuqW7duGj9+vD777LMbPjYAtz6KLQC4ARs2bNChQ4e0YcMGxcfHKy4uzuqWqIEDB+ro0aPasGGD/vOf/+jtt9/WqVOn8m0nOjpaPXv21N69ezV48GDl5uaqWrVq+vTTT7V//35NmjRJEydO1CeffHLVeOLj41WuXDlt27ZNM2bM0JQpU6yuMPXu3VunTp3S6tWrtWvXLjVt2lSdOnXSmTNnJEmffPKJoqOj9dprr2nnzp2qWrWq3n777avu09/fX/v27dNPP/101XGHDh3S8uXLtWrVKq1atUqbNm3StGnTzP6YmBi9//77Wrhwofbt26enn35a//73v7Vp0yZJKvI5WbdunZKTk5WQkKBVq1YVGvP69et1+vTpAvvnzp2rsLAwDRs2TMePH9fx48cVGBho9j///POaNm2aDhw4oIYNG14z9jwvvPCC3njjDe3cuVNOTk4aPHiw2bdkyRK9+uqrmj59unbt2qXq1atrwYIFZv/48eP18MMPKzIy0oypVatWVtseP368kpKSVKdOHfXr10/Z2dmF5mPLli1q3rz5dZ2X69GiRQtt2bLlhraxdOlS9evXT0uWLFFUVJRV37Rp0/Tf//73qs+Gpaam6ttvvzWLLUlav369jh07ps2bN2vWrFl6+eWX9cADD6hChQratm2bHn/8cT322GP63//+V+h2z507p4oVK97QsQG4TRgAACvt27c3xowZk689NjbW8Pb2NpcHDBhg1KhRw8jOzjbbevfubfTp08cwDMNITk42JBnbt283+w8cOGBIMmbPnm22STKeeuqpa8Y1cuRIo1evXlb77969u1Xcbdq0sVrnnnvuMZ577jnDMAxjy5YthpeXl3H58mWrMbVq1TLeeecdwzAMIywszHjiiSes+kNDQ41GjRoVGteFCxeM++67z5Bk1KhRw+jTp4/x3nvvWe3n5ZdfNjw8PIy0tDSz7ZlnnjFCQ0MNwzCMy5cvGx4eHsbWrVuttj1kyBCjX79+he67oHPi5+dnZGRkFLqOYRjGvn37jLp16xoODg5GgwYNjMcee8z46quvrMYU9D7YsGGDIclYvny52VaU2PPW++abb8z+L7/80pBkXLp0yTCMv8/zyJEjrbbRunVrq3P/z5wbhmEcPnzYkGS8++67VscnyThw4ECh58Db29t4//33r/u81KhRw+r9axiG0ahRI+Pll1+2aps7d64RFBRU6P7zzsnZs2et2vPO+1tvvWV4e3sbGzdutOp/+eWXzXPSt29f49577zUMwzB++OEHQ5Jx+PBhc+ySJUuM5s2bm8t5n9mcnByzLSQkxGjbtq25nJ2dbZQrV8746KOPCoz74MGDhpeXl7Fo0aJ8fQXlB8DtjStbAHAD6tevb04uIElVq1Y1r1wdOHBATk5Oatasmdl/1113Ffh8yj+vMEjS/Pnz1axZM1WpUkWenp5atGiRUlJSrhpPw4YNrZavjOfHH3/UhQsXVKlSJXl6epqvw4cP69ChQ2bMoaGhVtsICwu76j7LlSunL7/8Ur/++qtefPFFeXp6aty4cWrRooXS09PNcUFBQSpfvnyBsf36669KT09X586drWJ7//33zdiKek4aNGhQ4HNaV6pXr55++uknff/99xo8eLB5u+fQoUOvul6eK/NV1Ngl6/xUrVpVksxzkJycrBYtWliN/+fy1Vxt2wW5dOmS1S2E0o2flyu5u7tb5f96/Oc//9HTTz+thIQEtW/fvtBxU6dO1ZYtW7R27doC+6+8hTBP/fr15eDw/77++Pn5qUGDBuayo6OjKlWqVOC5++OPPxQZGanevXtr2LBh13tYAG5DZe+JXgCwMS8vL507dy5fe2pqar5JKf45kYXFYlFubu5177NcuXJWy8uWLdP48eP1xhtvKCwsTOXLl9fMmTO1bdu2q27navFcuHBBVatWtXrOJ09JzLJYq1Yt1apVS0OHDtULL7ygOnXq6OOPP9agQYOKFJv09/M5d9xxh9U4V1dXSUU/J/88l4VxcHDQPffco3vuuUdPPfWUPvzwQz366KN64YUXFBwcfNV1r9xHUWLPc+U5sFgsklSs90tBrnfblStXLnDii2udFwcHBxmGYbXOlc8p5jlz5oyqVKlSrGNp0qSJdu/ercWLF6t58+bm8fxTrVq1NGzYMD3//PN67733rPoyMzO1Zs0aTZw40aq9oPdhUT7Hx44dU8eOHdWqVSstWrSoWMcF4PZDsQUA/xASElLgv5Tv3r1bderUKfJ27rrrLmVnZ2vXrl265557JP199SI1NfWa63733Xdq1aqVnnjiCbPtn1dJrlfTpk114sQJOTk5KSgoqMAxdevW1bZt29S/f3+z7fvvv7/ufQUFBcnDw0MXL14s0vh69erJ1dVVKSkphV7JsMU5+WcMksyYXVxcivT7U0WJvShCQkK0Y8cOq3O/Y8cOqzFFjakomjRpov37919z3D/PS5UqVXT8+HGzPy0tTYcPH8633k8//aQmTZoUK7ZatWrpjTfeUIcOHeTo6Ki33nqr0LGTJk1SrVq18k3GsXHjRlWoUEGNGjUqVgxX+uOPP9SxY0c1a9ZMsbGxVlfGAOBqKLYA4B9GjBiht956S08++aSGDh0qV1dXffnll/roo4/0xRdfFHk7ISEhioyM1GOPPaYFCxbIyclJTz31lNzd3a+5bu3atfX+++/r66+/VnBwsD744APt2LHjmldcriY8PFxhYWHq0aOHZsyYoTp16ujYsWP68ssv1bNnTzVv3lxjxozRwIED1bx5c7Vu3VpLlizRvn37VLNmzUK3Gx0drfT0dN13332qUaOGUlNT9eabbyorK0udO3cuUmzly5fX+PHj9fTTTys3N1dt2rTRuXPn9N1338nLy0sDBgwo0XPyr3/9S61bt1arVq3k7++vw4cPa8KECapTp47uuusuSX8XjNu2bdORI0fk6elZ6IQIRYm9KEaPHq1hw4apefPmatWqlT7++GPt2bPH6twHBQXp66+/VnJysipVqnRD0/9HREQoPj7eqq0o5+Xee+9VXFycHnzwQfn4+GjSpElWt9Lm2bJli1555ZVix1enTh1t2LBBHTp0kJOTU6E/BO7n56exY8dq5syZVu0rV67Mdwthcfzxxx/q0KGDatSooddff91q8hB/f/8b3j6AWxv/NAMA/1CzZk1t3rxZP//8s8L/v/buHaSRII7j+C/Ypo0vAhZCEgURVEjnoihGNCCLsIqgsVCxFFchaLCwsLOxsrKwELQRRIv4QBCx0ypgIUoKQRDxURgL4a6QE3O+crJ7l7v7fmC73ZnZ7X47859palI4HNby8rJWVlYUiUR+qa2FhQWVlpbKMAyZpqnBwUEVFhZ++tzQ0JBM05RlWQqHw7q6usqa0fkKj8ejjY0N1dfXq7+/X4FAQF1dXUqn0yoqKpIkWZalRCKh8fFx1dbWKp1Oa3h4+MN2DcPQ6empent7FQqF1NraqouLCyWTyXe3Xn/L9PS0EomEZmZmVFFRoUgkovX19ecw5eQ3aWlp0dramqLRqAKBgPr6+hQKhZRMJp/PzLJtWwUFBaqsrJTP5/uwXu6zseeip6dH8Xhctm2rpqZGZ2dnisViWXVVAwMDCgaDqqurk8/n0/7+/pfe/0d/qVQqa/v5XL5LPB6XYRhqb29XW1ubOjo6VF5entX2wcGBbm9v1dnZ+eXxSU8/LHZ2drS0tKTR0dF377Nt+9U5Wk6Frc3NTZ2cnGh7e1t+v18lJSXPFwB8xvPt54XXAAAgLzQ3N6u4uFiLi4uutD82Nqa7uzvNz8872q5lWaqurn5VL/XS7u6uGhoadH197UjN4EuHh4dqbGzU5eVlTgeEOyUWi+nm5karq6u/rU8A+Y2ZLQAA8sD9/b1mZ2eVSqV0fHysqakpbW1t5bwM8SsmJiZUVlbm2CYd0tPGFFVVVRoZGcnpfr/fr+7ubsf6l6THx0fNzc39tqC1t7cnr9f75qHlAP5vzGwBAJAHMpmMotGojo6O9PDwoGAwqMnJSZmm+aeH5opMJqPz83NJktfr/avrn/6ldwHgLMIWAAAAALiAZYQAAAAA4ALCFgAAAAC4gLAFAAAAAC4gbAEAAACACwhbAAAAAOACwhYAAAAAuICwBQAAAAAuIGwBAAAAgAu+AwxFNMiIXqW0AAAAAElFTkSuQmCC\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Normality test p-value for Su: 0.0\n",
            "Su data is not normally distributed.\n",
            "OCR Mean: 3.808725639274967, OCR Standard Deviation: 6.451703880262324\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Normality test p-value for OCR: 0.0\n",
            "OCR data is not normally distributed.\n"
          ]
        }
      ]
    }
  ]
}