{
 "cells": [
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "",
   "id": "c2e58043"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-05-17T13:15:05.105911Z",
     "start_time": "2025-05-17T13:15:03.901417Z"
    }
   },
   "cell_type": "code",
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import os\n",
    "import glob\n",
    "from matplotlib.patches import Patch\n",
    "\n",
    "# Model list\n",
    "MODEL_TYPES = [\"fart\", \"mingru\", \"lru\"]  # Modify or expand this list as needed\n",
    "\n",
    "# Set style\n",
    "sns.set_style(\"darkgrid\")  # Classic Seaborn style with a light blue/grey background\n",
    "plt.rcParams['text.usetex'] = True\n",
    "plt.rcParams['font.family'] = 'sans-serif'\n",
    "plt.rcParams['font.sans-serif'] = ['Arial']\n",
    "plt.rcParams['axes.labelsize'] = 30\n",
    "plt.rcParams['axes.titlesize'] = 30\n",
    "plt.rcParams['xtick.labelsize'] = 30\n",
    "plt.rcParams['ytick.labelsize'] = 30\n",
    "plt.rcParams['legend.fontsize'] = 18  # Adjusted legend font size\n",
    "# plt.rcParams['axes.edgecolor'] = 'grey'  # Often handled by seaborn style\n",
    "plt.rcParams['text.latex.preamble'] = r'\\usepackage{amsmath} \\usepackage{amssymb} \\usepackage{amsfonts}'  # Add other packages as needed\n",
    "plt.rcParams['axes.linewidth'] = 1.2\n",
    "\n",
    "# Function: extract position value from position column name\n",
    "def extract_position(pos_col):\n",
    "    return float(pos_col.replace('pos_', ''))\n",
    "\n",
    "# Function: extract model type, environment, and partial observation from filename\n",
    "def extract_info_from_filename(filename):\n",
    "    base = os.path.basename(filename)\n",
    "    parts = base.replace('saliency_results_', '').replace('.csv', '').split('_')\n",
    "    model_type_from_file = parts[0]\n",
    "    env_name = parts[1]\n",
    "    partial_obs_str = parts[2].split('=')[1]\n",
    "    return model_type_from_file, env_name, partial_obs_str\n",
    "\n",
    "# --- Main loop: generate plots for each model type ---\n",
    "for current_model_type_from_list in MODEL_TYPES:\n",
    "    print(f\"\\n--- Starting processing model: {current_model_type_from_list} ---\")\n",
    "\n",
    "    display_model_name = current_model_type_from_list.upper()\n",
    "    if current_model_type_from_list.lower() == 'mingru':\n",
    "        display_model_name = 'MinGRU'\n",
    "\n",
    "    csv_files = glob.glob(f\"gradientdata/saliency_results_{current_model_type_from_list}_*.csv\")\n",
    "\n",
    "    if not csv_files:\n",
    "        print(f\"No CSV files found for model {current_model_type_from_list}. Skipping...\")\n",
    "        continue\n",
    "\n",
    "    print(f\"Found {len(csv_files)} files for model {current_model_type_from_list}\")\n",
    "\n",
    "    results = []\n",
    "\n",
    "    for csv_file in csv_files:\n",
    "        try:\n",
    "            model_type_in_filename, env_name, partial_obs_str = extract_info_from_filename(csv_file)\n",
    "\n",
    "            if model_type_in_filename.lower() != current_model_type_from_list.lower():\n",
    "                continue\n",
    "\n",
    "            df = pd.read_csv(csv_file)\n",
    "            pos_cols = [col for col in df.columns if col.startswith('pos_')]\n",
    "\n",
    "            if not pos_cols:\n",
    "                print(f\"CSV file {csv_file} does not contain 'pos_' column. Skipping.\")\n",
    "                continue\n",
    "\n",
    "            means_all_positions = df[pos_cols].mean().values\n",
    "\n",
    "            if len(means_all_positions) < 3:\n",
    "                print(f\"CSV file {csv_file} has less than 3 positions ({len(means_all_positions)}). Cannot split early/mid/late. Skipping.\")\n",
    "                continue\n",
    "\n",
    "            num_positions = len(means_all_positions)\n",
    "            early_mean_raw = np.mean(means_all_positions[:num_positions//3])\n",
    "            mid_mean_raw = np.mean(means_all_positions[num_positions//3 : 2*num_positions//3])\n",
    "            late_mean_raw = np.mean(means_all_positions[2*num_positions//3:])\n",
    "\n",
    "            total_mean = early_mean_raw + mid_mean_raw + late_mean_raw\n",
    "            if total_mean == 0:\n",
    "                early_mean_normalized = 0\n",
    "                mid_mean_normalized = 0\n",
    "                late_mean_normalized = 0\n",
    "            else:\n",
    "                early_mean_normalized = early_mean_raw / total_mean\n",
    "                mid_mean_normalized = mid_mean_raw / total_mean\n",
    "                late_mean_normalized = late_mean_raw / total_mean\n",
    "\n",
    "            results.append({\n",
    "                'file': csv_file,\n",
    "                'model_type': model_type_in_filename,\n",
    "                'env_name': env_name,\n",
    "                'partial_obs': partial_obs_str,\n",
    "                'n_seeds': len(df),\n",
    "                'early_mean': early_mean_normalized,\n",
    "                'mid_mean': mid_mean_normalized,\n",
    "                'late_mean': late_mean_normalized\n",
    "            })\n",
    "\n",
    "        except Exception as e:\n",
    "            print(f\"Error processing file {csv_file}: {e}\")\n",
    "\n",
    "    if not results:\n",
    "        print(f\"Model {current_model_type_from_list} has no valid data to plot.\")\n",
    "        continue\n",
    "\n",
    "    results_df = pd.DataFrame(results)\n",
    "\n",
    "    unique_envs = results_df['env_name'].unique()\n",
    "    fig_width_val = max(15, len(unique_envs) * 2.8)\n",
    "    fig_height_val = 8\n",
    "\n",
    "    fig, ax = plt.subplots(figsize=(fig_width_val, fig_height_val))\n",
    "\n",
    "    env_names = sorted(unique_envs)\n",
    "\n",
    "    time_keys = ['early', 'mid', 'late']\n",
    "    time_positions_display = {\n",
    "        'early': r\"$0 < \\tau < 0.33$\",\n",
    "        'mid':   r\"$0.33 \\leq \\tau < 0.66$\",\n",
    "        'late':  r\"$0.66 \\leq \\tau < 1.0$\"\n",
    "    }\n",
    "    n_time_pos = len(time_keys)\n",
    "\n",
    "    n_envs = len(env_names)\n",
    "    n_groups = 2\n",
    "\n",
    "    total_env_width = 0.7\n",
    "    group_width = total_env_width / n_groups\n",
    "    bar_width = group_width / n_time_pos\n",
    "\n",
    "    mdp_early_color = '#A9CCE3'\n",
    "    mdp_mid_color   = '#2471A3'\n",
    "    mdp_late_color  = '#154360'\n",
    "    pomdp_early_color = '#FAD7A0'\n",
    "    pomdp_mid_color   = '#E67E22'\n",
    "    pomdp_late_color  = '#935116'\n",
    "\n",
    "    mdp_color_map = {\n",
    "        'early': mdp_early_color,\n",
    "        'mid': mdp_mid_color,\n",
    "        'late': mdp_late_color\n",
    "    }\n",
    "    pomdp_color_map = {\n",
    "        'early': pomdp_early_color,\n",
    "        'mid': pomdp_mid_color,\n",
    "        'late': pomdp_late_color\n",
    "    }\n",
    "\n",
    "    x_base_pos = np.arange(n_envs)\n",
    "    legend_handles_for_this_plot = {}\n",
    "\n",
    "    for env_idx, env_name in enumerate(env_names):\n",
    "        for group_idx, partial_setting in enumerate(['False', 'True']):\n",
    "            subset = results_df[\n",
    "                (results_df['env_name'] == env_name) &\n",
    "                (results_df['partial_obs'] == partial_setting)\n",
    "            ]\n",
    "\n",
    "            if subset.empty:\n",
    "                continue\n",
    "\n",
    "            for time_idx, time_key in enumerate(time_keys):\n",
    "                mean_col = f'{time_key}_mean'\n",
    "                group_center_offset = (group_idx - 0.5) * group_width\n",
    "                time_pos_offset = (time_idx - (n_time_pos - 1) / 2) * bar_width\n",
    "                bar_exact_pos = x_base_pos[env_idx] + group_center_offset + time_pos_offset\n",
    "\n",
    "                if partial_setting == 'False':\n",
    "                    color = mdp_color_map[time_key]\n",
    "                else:\n",
    "                    color = pomdp_color_map[time_key]\n",
    "\n",
    "                condition_label = 'MDP' if partial_setting == 'False' else 'POMDP'\n",
    "                legend_label_key = f'{condition_label} {time_positions_display[time_key]}'\n",
    "\n",
    "                bar = ax.bar(\n",
    "                    bar_exact_pos,\n",
    "                    subset[mean_col].values[0],\n",
    "                    bar_width * 0.9,\n",
    "                    color=color,\n",
    "                    edgecolor='black',\n",
    "                    linewidth=0.7,\n",
    "                )\n",
    "                if legend_label_key not in legend_handles_for_this_plot:\n",
    "                    legend_handles_for_this_plot[legend_label_key] = bar[0]\n",
    "\n",
    "    ax.set_title(f'Recall Density of {display_model_name}', fontsize=30, pad=30, loc='center')\n",
    "    ax.set_ylabel(r'$\\mathbb{E}_{\\pi, f}[\\delta_Q(\\mathbf{x}, \\tau)]$', fontsize=30, labelpad=20)\n",
    "\n",
    "    ax.set_xticks(x_base_pos)\n",
    "    cleaned_env_names = [name.replace('Easy', '') for name in env_names]\n",
    "    ax.set_xticklabels(cleaned_env_names, rotation=45, ha='right', fontsize=30)\n",
    "\n",
    "    ax.set_ylim(0, 1.0)\n",
    "    ax.set_yticks(np.arange(0, 1.1, 0.2))\n",
    "\n",
    "    ordered_legend_labels = []\n",
    "    for time_key in time_keys:\n",
    "        ordered_legend_labels.append(f'MDP {time_positions_display[time_key]}')\n",
    "    for time_key in time_keys:\n",
    "        ordered_legend_labels.append(f'POMDP {time_positions_display[time_key]}')\n",
    "\n",
    "    final_legend_handles = []\n",
    "    final_legend_labels = []\n",
    "    for lbl in ordered_legend_labels:\n",
    "        if lbl in legend_handles_for_this_plot:\n",
    "            final_legend_handles.append(legend_handles_for_this_plot[lbl])\n",
    "            final_legend_labels.append(lbl)\n",
    "\n",
    "    if final_legend_handles:\n",
    "        legend = ax.legend(final_legend_handles, final_legend_labels,\n",
    "                           loc='upper center',\n",
    "                           ncol=2,\n",
    "                           fontsize=20,\n",
    "                           frameon=True,\n",
    "                           framealpha=0.9,\n",
    "                           edgecolor='grey')\n",
    "\n",
    "    ax.grid(True, axis='y', linestyle=':', color='darkgrey', alpha=0.6)\n",
    "    ax.grid(False, axis='x')\n",
    "\n",
    "    sns.despine(left=False, bottom=False, top=True, right=True)\n",
    "\n",
    "    ax.spines['left'].set_linewidth(1.5)\n",
    "    ax.spines['bottom'].set_linewidth(1.5)\n",
    "\n",
    "    plt.tight_layout(rect=[0, 0, 1, 0.96])\n",
    "\n",
    "    # Save as PDF\n",
    "    # output_filename_pdf = f'recall_density_{current_model_type_from_list}.pdf'\n",
    "    # plt.savefig(output_filename_pdf, dpi=300, bbox_inches='tight', format='pdf')\n",
    "    plt.show()\n",
    "    # print(f\"Figure saved as: {output_filename_pdf}\")\n",
    "\n",
    "    # Summary part remains the same\n",
    "    current_summary_df = results_df[results_df['model_type'].str.lower() == current_model_type_from_list.lower()].copy()\n",
    "    current_summary_df['Condition'] = current_summary_df['partial_obs'].apply(lambda x: 'POMDP' if x == 'True' else 'MDP')\n",
    "\n",
    "    pivot_summary = current_summary_df.pivot_table(\n",
    "        index=['env_name', 'Condition'],\n",
    "        values=['early_mean', 'mid_mean', 'late_mean', 'n_seeds'],\n",
    "        aggfunc={'early_mean': 'mean', 'mid_mean': 'mean', 'late_mean': 'mean', 'n_seeds': 'first'}\n",
    "    ).reset_index()\n",
    "\n",
    "    pivot_summary = pivot_summary[['env_name', 'Condition', 'n_seeds', 'early_mean', 'mid_mean', 'late_mean']]\n",
    "\n",
    "    print(f\"\\nStatistics summary for model {display_model_name}:\")\n",
    "    print(pivot_summary)\n",
    "    # summary_filename = f'summary_recall_density_{current_model_type_from_list}.csv'\n",
    "    # pivot_summary.to_csv(summary_filename, index=False, float_format='%.4f')\n",
    "    # print(f\"Summary saved as: {summary_filename}\")\n",
    "\n",
    "print(\"\\n--- All models processed ---\")"
   ],
   "id": "16409a64838b5322",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "--- Starting processing model: fart ---\n",
      "Found 14 files for model fart\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 1960x800 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Statistics summary for model FART:\n",
      "             env_name Condition  n_seeds  early_mean  mid_mean  late_mean\n",
      "0      AutoEncodeEasy       MDP        5    0.696837  0.234687   0.068476\n",
      "1      AutoEncodeEasy     POMDP        5    0.737510  0.229444   0.033046\n",
      "2      BattleShipEasy       MDP        5    0.242005  0.287641   0.470354\n",
      "3      BattleShipEasy     POMDP        5    0.357626  0.375312   0.267063\n",
      "4        CartPoleEasy       MDP        5    0.238619  0.372738   0.388643\n",
      "5        CartPoleEasy     POMDP        5    0.487072  0.356818   0.156110\n",
      "6     CountRecallEasy       MDP        5    0.484206  0.463624   0.052169\n",
      "7     CountRecallEasy     POMDP        5    0.473832  0.452395   0.073773\n",
      "8     MineSweeperEasy       MDP        5    0.348233  0.264910   0.386857\n",
      "9     MineSweeperEasy     POMDP        5    0.483055  0.343332   0.173613\n",
      "10      NavigatorEasy       MDP        5    0.907758  0.073230   0.019012\n",
      "11      NavigatorEasy     POMDP        5    0.805964  0.126837   0.067198\n",
      "12  NoisyCartPoleEasy       MDP        5    0.332301  0.368219   0.299480\n",
      "13  NoisyCartPoleEasy     POMDP        5    0.320325  0.396306   0.283368\n",
      "\n",
      "--- Starting processing model: mingru ---\n",
      "Found 14 files for model mingru\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 1960x800 with 1 Axes>"
      ],
      "image/png": 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     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Statistics summary for model MinGRU:\n",
      "             env_name Condition  n_seeds  early_mean  mid_mean  late_mean\n",
      "0      AutoEncodeEasy       MDP        5    0.179351  0.119488   0.701161\n",
      "1      AutoEncodeEasy     POMDP        5    0.087889  0.154487   0.757624\n",
      "2      BattleShipEasy       MDP        5    0.233474  0.137018   0.629508\n",
      "3      BattleShipEasy     POMDP        5    0.549307  0.237267   0.213425\n",
      "4        CartPoleEasy       MDP        5    0.133665  0.082163   0.784172\n",
      "5        CartPoleEasy     POMDP        5    0.102645  0.126996   0.770359\n",
      "6     CountRecallEasy       MDP        5    0.420535  0.177927   0.401538\n",
      "7     CountRecallEasy     POMDP        5    0.335672  0.099325   0.565003\n",
      "8     MineSweeperEasy       MDP        5    0.470100  0.080674   0.449226\n",
      "9     MineSweeperEasy     POMDP        5    0.393691  0.204866   0.401443\n",
      "10      NavigatorEasy       MDP        5    0.428518  0.129656   0.441826\n",
      "11      NavigatorEasy     POMDP        5    0.960711  0.023131   0.016158\n",
      "12  NoisyCartPoleEasy       MDP        5    0.134145  0.121249   0.744606\n",
      "13  NoisyCartPoleEasy     POMDP        5    0.403403  0.383830   0.212767\n",
      "\n",
      "--- Starting processing model: lru ---\n",
      "Found 14 files for model lru\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 1960x800 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Statistics summary for model LRU:\n",
      "             env_name Condition  n_seeds  early_mean  mid_mean  late_mean\n",
      "0      AutoEncodeEasy       MDP        5    0.397651  0.231490   0.370859\n",
      "1      AutoEncodeEasy     POMDP        5    0.179668  0.110780   0.709552\n",
      "2      BattleShipEasy       MDP        5    0.142878  0.190993   0.666129\n",
      "3      BattleShipEasy     POMDP        5    0.120225  0.158673   0.721102\n",
      "4        CartPoleEasy       MDP        5    0.032032  0.183633   0.784334\n",
      "5        CartPoleEasy     POMDP        5    0.102813  0.434936   0.462252\n",
      "6     CountRecallEasy       MDP        5    0.133504  0.212280   0.654215\n",
      "7     CountRecallEasy     POMDP        5    0.095992  0.299378   0.604630\n",
      "8     MineSweeperEasy       MDP        5    0.278916  0.086414   0.634670\n",
      "9     MineSweeperEasy     POMDP        5    0.376190  0.262754   0.361055\n",
      "10      NavigatorEasy       MDP        5    0.539231  0.148849   0.311920\n",
      "11      NavigatorEasy     POMDP        5    0.536897  0.231040   0.232063\n",
      "12  NoisyCartPoleEasy       MDP        5    0.130296  0.412996   0.456707\n",
      "13  NoisyCartPoleEasy     POMDP        5    0.174359  0.457109   0.368533\n",
      "\n",
      "--- All models processed ---\n"
     ]
    }
   ],
   "execution_count": 11
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-05-17T13:19:47.301903Z",
     "start_time": "2025-05-17T13:19:46.153158Z"
    }
   },
   "cell_type": "code",
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import os\n",
    "import glob\n",
    "import matplotlib.gridspec as gridspec\n",
    "\n",
    "# Set style\n",
    "plt.style.use('ggplot')\n",
    "sns.set()\n",
    "plt.rcParams['text.usetex'] = True\n",
    "plt.rcParams['text.latex.preamble'] = r'\\usepackage{amsmath} \\usepackage{amssymb} \\usepackage{amsfonts}'\n",
    "plt.rcParams['font.family'] = 'sans-serif'\n",
    "plt.rcParams['font.sans-serif'] = ['Arial']\n",
    "plt.rcParams['axes.labelsize'] = 30\n",
    "plt.rcParams['axes.titlesize'] = 30\n",
    "plt.rcParams['xtick.labelsize'] = 15\n",
    "plt.rcParams['ytick.labelsize'] = 15\n",
    "\n",
    "# Create color themes for different environments\n",
    "def get_env_colors(env_idx):\n",
    "    \"\"\"\n",
    "    Return the bar colors for MDP and POMDP for each environment.\n",
    "    Colors are based on seaborn palettes.\n",
    "    \"\"\"\n",
    "    # Define 7 sets of color themes; each set contains colors for MDP and POMDP\n",
    "    color_themes = [\n",
    "        # Theme 1: Blue-Orange contrast (high contrast)\n",
    "        {\"mdp\": \"#1F77B4\", \"pomdp\": \"#FF7F0E\"},\n",
    "        # Theme 2: Purple-Green contrast (high discernibility)\n",
    "        {\"mdp\": \"#7A0177\", \"pomdp\": \"#00A087\"},\n",
    "        # Theme 3: Red-Blue contrast (strong contrast)\n",
    "        {\"mdp\": \"#D62728\", \"pomdp\": \"#2C7FB8\"},\n",
    "        # Theme 4: Brown-Cyan contrast (vivid)\n",
    "        {\"mdp\": \"#8C564B\", \"pomdp\": \"#17BECF\"},\n",
    "        # Theme 5: Dark Yellow-Light Purple contrast (modern feel)\n",
    "        {\"mdp\": \"#9467BD\", \"pomdp\": \"#BCBD22\"},\n",
    "        # Theme 6: Dark Green-Bright Pink contrast (vivid contrast)\n",
    "        {\"mdp\": \"#2D6A4F\", \"pomdp\": \"#FF69B4\"},\n",
    "        # Theme 7: Navy Blue-Orange-Red (high saturation)\n",
    "        {\"mdp\": \"#1A374D\", \"pomdp\": \"#E85D04\"}\n",
    "    ]\n",
    "\n",
    "    # Get the corresponding color theme based on the environment index\n",
    "    theme_idx = env_idx % len(color_themes)\n",
    "    return color_themes[theme_idx]\n",
    "\n",
    "# Search for all CSV files\n",
    "csv_files = glob.glob(\"gradientdata/saliency_results_fart_*.csv\")\n",
    "print(f\"Found {len(csv_files)} CSV files\")\n",
    "\n",
    "# Function: extract environment and partial observation settings from filename\n",
    "def extract_info_from_filename(filename):\n",
    "    base = os.path.basename(filename)\n",
    "    parts = base.replace('saliency_results_fart_', '').replace('.csv', '').split('_')\n",
    "    env_name = parts[0]\n",
    "    partial_obs = parts[1].split('=')[1]\n",
    "    return env_name, partial_obs\n",
    "\n",
    "# Aggregate data\n",
    "file_data = []\n",
    "\n",
    "for csv_file in csv_files:\n",
    "    try:\n",
    "        # Extract environment and partial observation settings\n",
    "        env_name, partial_obs = extract_info_from_filename(csv_file)\n",
    "\n",
    "        # Read CSV file\n",
    "        df = pd.read_csv(csv_file)\n",
    "\n",
    "        # Get columns that start with \"pos_\"\n",
    "        pos_cols = [col for col in df.columns if col.startswith('pos_')]\n",
    "\n",
    "        # Sort the position columns to ensure the correct order\n",
    "        pos_cols.sort(key=lambda x: float(x.replace('pos_', '')))\n",
    "\n",
    "        # Extract position values and labels\n",
    "        positions_values = [float(col.replace('pos_', '')) for col in pos_cols]\n",
    "        pos_labels = [f\"{pos:.2f}\" for pos in positions_values]\n",
    "\n",
    "        # Get the mean value over seeds for each position\n",
    "        means = df[pos_cols].mean().values\n",
    "\n",
    "        # Print original data sum for verification\n",
    "        print(f\"Original data sum: {means.sum()}\")\n",
    "\n",
    "        # Store result\n",
    "        file_data.append({\n",
    "            'file': csv_file,\n",
    "            'env_name': env_name,\n",
    "            'partial_obs': partial_obs == 'True',  # Convert to boolean\n",
    "            'display_name': f\"{'POMDP' if partial_obs=='True' else 'MDP'}\",\n",
    "            'n_seeds': len(df),\n",
    "            'positions_values': positions_values,  # Store actual position values\n",
    "            'pos_labels': pos_labels,\n",
    "            'means': means\n",
    "        })\n",
    "\n",
    "        print(f\"Processed file: {csv_file}\")\n",
    "\n",
    "    except Exception as e:\n",
    "        print(f\"Error processing file {csv_file}: {e}\")\n",
    "\n",
    "# Set unified number of data points for all environments to 16\n",
    "target_data_points = 16\n",
    "print(f\"Set unified number of data points to: {target_data_points}\")\n",
    "\n",
    "# Function: average data points to the target size while preserving the total sum\n",
    "def average_to_target_size(values, target_size):\n",
    "    \"\"\"Average the values array to a target_size-length array while preserving the total sum\"\"\"\n",
    "    if len(values) <= target_size:\n",
    "        return values  # Return as-is if the original length is less than or equal to the target\n",
    "\n",
    "    # Record the original total sum\n",
    "    original_sum = np.sum(values)\n",
    "    print(f\"Original sum: {original_sum}\")\n",
    "\n",
    "    # Calculate how many original data points each bin should contain\n",
    "    bin_size = len(values) / target_size\n",
    "\n",
    "    result = []\n",
    "    for i in range(target_size):\n",
    "        start_idx = int(i * bin_size)\n",
    "        end_idx = int((i + 1) * bin_size)\n",
    "        # Ensure the last bin includes all remaining elements\n",
    "        if i == target_size - 1:\n",
    "            end_idx = len(values)\n",
    "        # Compute the average for this bin\n",
    "        bin_avg = np.mean(values[start_idx:end_idx])\n",
    "        result.append(bin_avg)\n",
    "\n",
    "    result = np.array(result)\n",
    "\n",
    "    # Adjust the result to preserve the original total sum\n",
    "    if np.sum(result) > 0:\n",
    "        result = result * (original_sum / np.sum(result))\n",
    "\n",
    "    return result\n",
    "\n",
    "# Average all data to 16 data points\n",
    "for data in file_data:\n",
    "    if len(data['means']) != target_data_points:\n",
    "        # Average the mean data while preserving the total sum\n",
    "        data['means'] = average_to_target_size(data['means'], target_data_points)\n",
    "        # Average the position values and labels\n",
    "        data['positions_values'] = np.linspace(0, 1, target_data_points)\n",
    "        data['pos_labels'] = [f\"{pos:.2f}\" for pos in data['positions_values']]\n",
    "\n",
    "    # Print verification\n",
    "    print(f\"{data['env_name']} - {data['display_name']} after averaging, total sum: {np.sum(data['means']):.6f}\")\n",
    "\n",
    "# Get unique environment names\n",
    "env_names = sorted(set(data['env_name'] for data in file_data))\n",
    "\n",
    "# Properties for the bar charts\n",
    "bar_width = 0.35\n",
    "alpha = 0.85\n",
    "\n",
    "# Create separate plots for each environment\n",
    "for env_idx, env_name in enumerate(env_names):\n",
    "    # Create a new figure for each environment\n",
    "    plt.figure(figsize=(6, 4.5))\n",
    "    ax = plt.gca()\n",
    "\n",
    "    # Get MDP and POMDP data for the current environment\n",
    "    env_specific_data = [d for d in file_data if d['env_name'] == env_name]\n",
    "\n",
    "    # Ensure order: MDP first, then POMDP\n",
    "    env_specific_data.sort(key=lambda x: x['partial_obs'])\n",
    "\n",
    "    # Remove the \"Easy\" suffix from title if present\n",
    "    plot_title = env_name.replace('Easy', '')\n",
    "\n",
    "    # Get the color theme for this environment\n",
    "    env_colors = get_env_colors(env_idx)\n",
    "\n",
    "    if len(env_specific_data) == 2:\n",
    "        mdp_data, pomdp_data = env_specific_data\n",
    "\n",
    "        plot_len = len(mdp_data['means'])  # Should be 16 now\n",
    "        current_pos_labels_for_ticks = mdp_data['pos_labels']\n",
    "\n",
    "        x_indices = np.arange(plot_len)\n",
    "\n",
    "        bars1 = ax.bar(\n",
    "            x_indices - bar_width/2,\n",
    "            mdp_data['means'],\n",
    "            bar_width,\n",
    "            alpha=alpha,\n",
    "            color=env_colors[\"mdp\"],\n",
    "            edgecolor='black',\n",
    "            linewidth=0.5,\n",
    "            label='MDP'  # Use plain text, not LaTeX\n",
    "        )\n",
    "\n",
    "        bars2 = ax.bar(\n",
    "            x_indices + bar_width/2,\n",
    "            pomdp_data['means'],\n",
    "            bar_width,\n",
    "            alpha=alpha,\n",
    "            color=env_colors[\"pomdp\"],\n",
    "            edgecolor='black',\n",
    "            linewidth=0.5,\n",
    "            label='POMDP'  # Use plain text, not LaTeX\n",
    "        )\n",
    "\n",
    "        ax.legend(fontsize=15, frameon=True, framealpha=0.7, loc='upper right')\n",
    "\n",
    "    elif len(env_specific_data) == 1:\n",
    "        data = env_specific_data[0]\n",
    "        plot_len = len(data['means'])\n",
    "        current_pos_labels_for_ticks = data['pos_labels']\n",
    "\n",
    "        if plot_len > 0:\n",
    "            x_indices = np.arange(plot_len)\n",
    "            color = env_colors[\"pomdp\"] if data['partial_obs'] else env_colors[\"mdp\"]\n",
    "\n",
    "            bars = ax.bar(\n",
    "                x_indices,\n",
    "                data['means'],\n",
    "                bar_width * 1.5,\n",
    "                alpha=alpha,\n",
    "                color=color,\n",
    "                edgecolor='black',\n",
    "                linewidth=0.5,\n",
    "                label=data['display_name']\n",
    "            )\n",
    "            ax.legend(fontsize=10, frameon=True, framealpha=0.7, loc='upper right')\n",
    "    else:  # No data for this environment\n",
    "        plot_len = 0\n",
    "        current_pos_labels_for_ticks = []\n",
    "\n",
    "    ax.set_title(plot_title, fontsize=30, pad=10)\n",
    "    ax.set_ylabel(r'$\\mathbb{E}_{\\pi, f}[\\delta_Q(\\mathbf{x}, \\tau)]$', fontsize=25)\n",
    "    ax.set_xlabel(r'Normalized Time Index $\\tau$', fontsize=25)  # Changed label since we use indices\n",
    "\n",
    "    if plot_len > 0:\n",
    "        n_ticks = min(8, plot_len)\n",
    "        tick_indices_numeric = np.linspace(0, plot_len - 1, n_ticks, dtype=int)\n",
    "        ax.set_xticks(tick_indices_numeric)\n",
    "        ax.set_xticklabels([current_pos_labels_for_ticks[idx] for idx in tick_indices_numeric], rotation=45, ha=\"right\")\n",
    "    else:\n",
    "        ax.set_xticks([])\n",
    "        ax.set_xticklabels([])\n",
    "\n",
    "    ax.grid(True, axis='y', linestyle='--', alpha=0.3)\n",
    "    ax.spines['top'].set_visible(False)\n",
    "    ax.spines['right'].set_visible(False)\n",
    "\n",
    "    plt.tight_layout()\n",
    "\n",
    "    # Remove the \"Easy\" suffix from filename if present\n",
    "    clean_env_name = env_name.replace('Easy', '')\n",
    "    # plt.savefig(f'fart_{clean_env_name}.pdf', dpi=300, bbox_inches='tight')\n",
    "\n",
    "    # Show the individual plot\n",
    "    plt.show()\n",
    "\n",
    "# Create a summary dataframe including early, mid, and late mean values\n",
    "summary_df = pd.DataFrame([{\n",
    "    'env_name': data['env_name'].replace('Easy', ''),  # Remove the \"Easy\" suffix from summary data\n",
    "    'model_type': 'POMDP' if data['partial_obs'] else 'MDP',\n",
    "    'n_seeds': data['n_seeds'],\n",
    "    'total_sum': np.sum(data['means']),\n",
    "    'early_mean': np.sum(data['means'][:len(data['means'])//3]) if len(data['means']) >= 3 else np.nan,\n",
    "    'mid_mean': np.sum(data['means'][len(data['means'])//3:2*len(data['means'])//3]) if len(data['means']) >= 3 else np.nan,\n",
    "    'late_mean': np.sum(data['means'][2*len(data['means'])//3:]) if len(data['means']) >= 3 else np.nan\n",
    "} for data in file_data])\n",
    "\n",
    "# print(\"\\nSummary data:\")\n",
    "# print(summary_df)\n",
    "# summary_df.to_csv('normalized_saliency_summary.csv', index=False)\n",
    "# print(\"Summary data saved to CSV file\")"
   ],
   "id": "4746451847969b5e",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Found 14 CSV files\n",
      "Original data sum: 0.9999999391962712\n",
      "Processed file: gradientdata/saliency_results_fart_AutoEncodeEasy_Partial=True.csv\n",
      "Original data sum: 0.9999999719206224\n",
      "Processed file: gradientdata/saliency_results_fart_CountRecallEasy_Partial=False.csv\n",
      "Original data sum: 1.0000000052154037\n",
      "Processed file: gradientdata/saliency_results_fart_CountRecallEasy_Partial=True.csv\n",
      "Original data sum: 0.9999999899882818\n",
      "Processed file: gradientdata/saliency_results_fart_NavigatorEasy_Partial=False.csv\n",
      "Original data sum: 0.9999999599240158\n",
      "Processed file: gradientdata/saliency_results_fart_CartPoleEasy_Partial=True.csv\n",
      "Original data sum: 1.0000000254251054\n",
      "Processed file: gradientdata/saliency_results_fart_MineSweeperEasy_Partial=False.csv\n",
      "Original data sum: 1.0000000548490693\n",
      "Processed file: gradientdata/saliency_results_fart_NoisyCartPoleEasy_Partial=True.csv\n",
      "Original data sum: 0.9999999894993317\n",
      "Processed file: gradientdata/saliency_results_fart_BattleShipEasy_Partial=False.csv\n",
      "Original data sum: 0.9999999876948908\n",
      "Processed file: gradientdata/saliency_results_fart_NoisyCartPoleEasy_Partial=False.csv\n",
      "Original data sum: 0.9999999981373541\n",
      "Processed file: gradientdata/saliency_results_fart_MineSweeperEasy_Partial=True.csv\n",
      "Original data sum: 1.0000000134110447\n",
      "Processed file: gradientdata/saliency_results_fart_NavigatorEasy_Partial=True.csv\n",
      "Original data sum: 1.0000000059721\n",
      "Processed file: gradientdata/saliency_results_fart_BattleShipEasy_Partial=True.csv\n",
      "Original data sum: 0.9999999642794052\n",
      "Processed file: gradientdata/saliency_results_fart_AutoEncodeEasy_Partial=False.csv\n",
      "Original data sum: 0.9999999804654991\n",
      "Processed file: gradientdata/saliency_results_fart_CartPoleEasy_Partial=False.csv\n",
      "Set unified number of data points to: 16\n",
      "Original sum: 0.9999999391962712\n",
      "AutoEncodeEasy - POMDP after averaging, total sum: 1.000000\n",
      "Original sum: 0.9999999719206224\n",
      "CountRecallEasy - MDP after averaging, total sum: 1.000000\n",
      "Original sum: 1.0000000052154037\n",
      "CountRecallEasy - POMDP after averaging, total sum: 1.000000\n",
      "Original sum: 0.9999999899882818\n",
      "NavigatorEasy - MDP after averaging, total sum: 1.000000\n",
      "Original sum: 0.9999999599240158\n",
      "CartPoleEasy - POMDP after averaging, total sum: 1.000000\n",
      "Original sum: 1.0000000254251054\n",
      "MineSweeperEasy - MDP after averaging, total sum: 1.000000\n",
      "Original sum: 1.0000000548490693\n",
      "NoisyCartPoleEasy - POMDP after averaging, total sum: 1.000000\n",
      "Original sum: 0.9999999894993317\n",
      "BattleShipEasy - MDP after averaging, total sum: 1.000000\n",
      "Original sum: 0.9999999876948908\n",
      "NoisyCartPoleEasy - MDP after averaging, total sum: 1.000000\n",
      "Original sum: 0.9999999981373541\n",
      "MineSweeperEasy - POMDP after averaging, total sum: 1.000000\n",
      "NavigatorEasy - POMDP after averaging, total sum: 1.000000\n",
      "Original sum: 1.0000000059721\n",
      "BattleShipEasy - POMDP after averaging, total sum: 1.000000\n",
      "Original sum: 0.9999999642794052\n",
      "AutoEncodeEasy - MDP after averaging, total sum: 1.000000\n",
      "Original sum: 0.9999999804654991\n",
      "CartPoleEasy - MDP after averaging, total sum: 1.000000\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 600x450 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 600x450 with 1 Axes>"
      ],
      "image/png": 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6WKLIFFVBj7vOykqgYzabHR59DYTFYlEfpwE9HZ+Li4vZp4eIiFQjR47CwYP7ceDAfpetKtu3b1W3c2XYsOEYPjxV/X348FRMnJiDiRNz8OCDv8J9992NtWtf9WrftLRRmDgxBy+++CxWrlyB0aPHxUSLT1SN3uro6AAAty05yjb+0N7ejilTpsBgMMBgMKC4uBj5+fl+Gb3Vs/7IhX/u3vP0vrfvOdvGH+n6M7/273uTriuBOofBSNeb8nibp1BeG3dlCvdr40tZe6fjr3RDWQ+9LR/1GDXqagwbNhxvv/2my23eeectZGdP6lf6Y8aMQ1nZEzh4cD+2b9/q076PPPIkALjNW6j5Wr/diaqWHnf6M2Tdk+XLlzv8LkkSMjIyUF5ejtra2gGl3TOr5QU2m1AXcOv9HgCcP98zP0ZCQjx6zwnW3W2DzSYQF6dBQoLjm/bpKmnHxV2oQRfSjXN43VO6QgBdXVaX+VWmKY+Pj0N8vGO6VquA1WqDRtN3X/t0ExLi+1T23unGx8epeRACLtO1L+ugQX3T9fYcur82vp1Dmw3o7u57DpUyKZyla7XaYLUKaDQaDBrk+tp4cw4d03V9bRzL6ixdG4QQDtflQlkvjEntXQcd0/X1HPb/2nh7Dj3Vb+V9pVwDq9/uz2Gg7xFKuvZ/V8p7CQlx0GjiHT6I7IcaO5QlEoIjJx+mSnmcfci6LCuApKQk3HxzNt555y08+uiTffZ9772eQOX22/OxcuUKhw/y3um6ytN//mc+Vq1agZUrV+CWW3I87mv/XlJSEo4cOez0/YEEsu7OkzfnUPk3aFA84uPjvKrfnkRV0JOcnAzAeYCjtPAo2wSKJEkOj7z6S7nxKewrQ+/37HV3W13+Udhswm26StpWa98FAru7bf1O11l+lfetVht6r0eovGf/AeCMEhC4S1f5MLUvl6d0u7r6fw7d59c/59A+QPCUrhB903XcNxTXRqiT2Nm/p3zYuqqDPen6tx56k66nc+ipfnd1XdjOfiHGQJxDd3myT3eg59D+7+pCujZ0d/cEe8o/V+kgEubzcVIG9S0P+XdW9uzsyVi//g/4+ONdGDNmnMP727ZtwciRo5CYmKRu7+wYrl5X3ps4MQfvvPMWZNmCpKQkr/a1WCywWCwYNmy4y2P2l7t9vTmHyr+eLxEXAh139duTqHq85U0HZX/1tykvL0dNTY3L9wfasmR/wZ39AfnyvrfvOdvGH+n6M7/273uTriuBOofBSNeb8nibp1BeG3dlCvdr40tZe6fjr3RDWQ+9LR9dkJY26t+PuBocXrdYLNixY5vL0Ve+UPrs7N/f6vU+K1f2PLG4/fY7Bnz8QPG1frsTVS09AKDX6532qZFlGZIk+W3k1qZNmzBlypQ+r7e3t0Or1XKEGBERObj55mysX/8Hh9fee28LAOCWW/rXn8fesGHDAQBHjhzu896RI4dx4MB+u997Rm/t2fMx5s6dFxOdmIEoDHry8vKctsAYjUbk5ub67TgFBQVO5/xpbm5GQUGB345DRETR4fbb87F+/R+wfftWTJzY0+9m+/atGD16bJ/HUf2hPGFQgh97e/Z8jFmz7lZ/V+bpWbr0d30et0WzqHq8BQAGgwFAT5CjMJvNMJvNfYKUnJwcVFZWukyrvb3d5XszZszoE1zV1NQgOTnZrxMgEhFRdBg+PBUjR45SH3FZLBbs2fOxXx5tAcCBA/sAOA96br45Gx9+uEf919i4HcuWvRxTAQ8QhS09ANDQ0IAlS5bAZDJBq9XCZDL5NJpKWU9r06ZNAIDCwkJIkoS8vDzo9XoAUH9XgiaLpafj2Natvg0XJCKi2JGdPQkrV66AxWLBO+/0BD9Kq89A7dnzMRITkxzm4yFHURn02K+f5Y6rAEXZ11MakiSxVYeIiLz285/3DEvfs2cXtm3bgptvzvZLutu3b8WRI4cdZmymvqLu8RYREVG4SkpKwujRY/H22w04eHC/Xx5tHTiwHy+88CyGDRvut0dl0SoqW3qIiIjC1cSJOaisfA6JiUk+9amRZRmHD7epvytrb73zzlsYPXosFi16wc3eBDDoISIiCqrbb8/HgQP7fO5EvGPHNuzYsc3htWHDhsfUgqEDxaCHiIiC6jLpcrwP/65i7hcaQKPRQAiBy1Iv90uSH364x+nryppX3myflJTkMh1PBrJvNGLQQ0REQVW5clmos+CUss6TsnYaRR92ZCYiIqKYwKCHiIiIYgKDHiIiIooJDHqIiIgoJjDoISIiopjAoIeIiIhiAoMeIiIiigkMeoiIiCgmMOghIiKimMCgh4iIiGICgx4iIiKKCQx6iIiIKCZwwVEiIqIAsFgsmDJlYp/XExOTMGrU1Zg7dz7S0ka53X/lyuV4772t6Oy0YNiw4Rg9eizmzp2PpKQkp/tcf/1oAMAvfnEPfvnL+W7zl5c3EZ2dFtx8czYWL37BY74B4Mrh/wvZYyche9wkp++f+fYMJkwY3ed1b8scaAx6iIgoqOY+/iDMp06EOhtOxWk0sAkB6dLLsPL5pX5Jc/TosSgrewIA0NnZiSNH2vD22w2YNetuzJ07D3fddW+ffQ4c2I+SkrnQarX4+c+n4eqr07FvXyveeect7NnzMRYtesFt8LBjxza3Qc/u3bvQ2WnxOt8AsHnjJvxr3xdY/VY1PtrbjCeLyv1a5mBg0ENEREFlPnUCJ+7MDXU2nNJoACEAvNbktzSHDRuO4cNT1d/T0kZh4sQcvPjis1i5cgVGjx7nEMAcOLAfs2bdjdGjx2LRohfUVp2JE3Pw3/9diJKSuZg1627U1f3RIV3FyJGjcPDgfhw4sN9lYLR9+1Z1O2/zfe1PfoqcqydhXGYWnltTgSdWPILn5r3olzIHC/v0EBERhcAjjzwJAHj77TcdXn/hhcVITEzCsmUv93mMlZSUhKqqlQCAysrnnKY7atTVGDZseJ907b3zzlvIznb+iMqTzKt+jKJps/HPw19g195mn/Z1VeZg8bqlZ9y4cYHMh9fWrVuHq6++OtTZICIiGrDExCQcOXJY/X337l04eHC/w2Ol3pKSkjB37jysXLnCaWtOYmISbr45G++885YaZNjbvn0rAODnP8/HypUr+pXv7HGT8NqmV7F+06sYl5nl0769yxxMXgc9HR0dKC0thU6nC2R+XBJC4L777gvJsYmIiPzNYrGoHZQVb7/dAKCnT4w7o0ePA7AC27ZtdvqYKDt7Mtav/wN2796FMWMcGy22bduCkSNHuewM7a3xP9Zj28dbcPrb07jkO5d4tY+zMgeTT316JkyYwFYWIiIiP1i5cjkA4Pbb71BfU1pAnPXVsacEDa765KSljfr3I64Gh6DHYrFgx45tbluSvDX0su8BAL5o+xyZV/3Yq32clTmY2JGZiIgogI4cOYwDB/bb/d4zkmnPno8xd+48h5aazk4LEhM9t8AorTSyLLvc5uabs7F+/R8cXnvvvS0AgFtu6V9/HnvfG9IT9Hx98lif93wpczB5HfQUFRVBkqRA5iUi8kBEROSLPXs+xqxZd6u/K3PWLF36uz6PnpT+LhaLxe3jp8OH2wAAWq3W5Ta3356P9ev/gO3bt2LixBwAPf15Ro8eO+BHWwDQeaYTADD038GPPV/KHExeBz2lpaWBzEfE5IGIiMgXvSf/c2fYsOE4eHA/jhw57LY1RHkM5q5vzPDhqRg5chTefrsBEyfmwGKx/HuOn9/4VgAX/nn4CwDOgx5fyhxMHLJOREQUJpRh5J6GdCsdnpUWHHfp7dnzMSwWC955x7t9vLX3s7/jkosvwfcu6xv0hCsGPURERGFi4sQcjBw5Cu+88xYsFuczJh8+3IYdO7Zh9OixHh8V/fzn+QCAPXt2Ydu2Lbj55my/5HPX3mZ8ffIY7pxyt+eNw4jfOzK3tbWhubkZLS0taGlpgcVigdls7rOdVqtFamoqMjIykJGRgaysLKSmuu+tTkREFO0effQpzJp1N0pK5qKqaqVD/5vDh9vw4IO/AgCvRmAlJSVh9OixePvtBhw8uB9z584bcP7+efgL1Ly5CkOHfM/lGlzhyi9BT1tbG+rq6lBfXw9ZliGEgCRJkCQJOp0O48ePh1arRUpKCtrb29Xe5m1tbTAajairq4NGo4FWq4XBYIDBYMDw4aEZw09ERBRKaWmjsHTp77Bw4WOYPv3n6tpbu3fvwnvv9UwsuGbNqx6HtSsmTsxBZeVzSExM8qkTsSzLaodpAPj0fz7Bv/Z9gW0fb0HGj36MBXc97FvBwsCAgp59+/bhySefxL59+5CVlYXi4mLo9Xqkp6f7nJbZbEZjYyOam5vxyiuvQKfT4dlnn8WoUaFbjZWIiCgUxowZh9dffwcrVy7HO++8hfXr/4Bhw4bjllty3K6y7sztt+fjwIF9Po+a2rFjG3bs2Obw2tAh38OdU+7Gz2/6T5/SChcaIYTwdafOzk412CkoKIDBYPDL8DeFxWLBhg0bUF9fD51Oh8WLFyMxMdFv6Yc7q9WGkydPB/WYCQlxuPTSS3Dq1Gl0d9uCeuxAisZyRWOZAJYrkrgqU1fXeZw6dRyXXno5Bg0a7HL/WFtlPVr87eO/4rLzQ9xuc+qiU/jJ2Gvhe2TRl7f1SXH55Z7jEJ9belpbW1FSUoIZM2agqqrK1929kpSUhOLiYhQXF6Ourg75+flYvnw5W32IiKJAuAYTGg0waFA8urqsfvnQpvDjU9DT1NSE+vp6NDQ0+LVlxx2DwYApU6ZgwYIFmDFjBiZPnhyU4xIREVF08XrIenNzM3bu3Ik1a9YELeBRaLVarF27Fn//+9/R3OzbMvZEREREgA9BT2pqKioqKgKZF49KS0s5rJ2IiIj6xeugJ1zWvAqXfBAREVFkCciMzJ2dnYFIloiIiKjfAhL0ZGdnY9asWYFImoiIiKhfAhL0dHR0OF16goiIopdGE+ocUDTyZ73igqNEROQXcXHxAACrtTvEOaFoYLVaAQAaTbzf0mTQQ0REfhEXF4/Bgy/CmTOdsNmiY/ZpCg0hBM6dO4OEhEGIj/df0OP3VdaJiCh2XXKJFh0dJ3Dq1Ne4+OLvYtCgwdBoIuP7dc9jFM7I7EpcvAYiwf2JiYvXoKvr/IDOn9VqxblzZ3D+/FkkJblf9sJXDHqIiMhvBg0ajEsvvRynT8v49tvTOH3aEuoseU2jAeLj42C12hj0OHH+/BmcsboPYM/hNE6dOj7g85eQMAhJSUNw8cXfGVhCvdP1a2pERBTz4uMToNUOgRACNpsVQkRGEJGQEIfk5O+io+NM1CwO608vVD+PsR2j3W7z18s+xW9qXur3+dNoevrw+PORlr2ABT1msxl33HEHMjIyMGHCBKSnp3M2ZSKiGKLRaBAfHznfrRMS4nDRRRdh0KBuaDQMeno79c0pnD35rdtt2nHq3480w/P8Baw2SpKEZcuWoampCatWrUJrays0Gg3S09MZCBEREVHQBTQElyQJRUVFKCoqgsViwcaNG9HU1IS6ujrU19er26Wnp2PChAkoKChgEEREREQBEbCgp6Ojw+H3pKQkGAwGGAwGAEBjYyM2btyIjz76CCaTCSaTCXV1ddi1a1egskREREQxLCBBjyRJkGXZ7TZ5eXnIy8sDALS2tmLjxo2ByAoRERERgAAFPZMnT8batWtx+PBhDB8+3OP26enpSE9PD0RWiIiIiAAEaEbmsrIyXH311SgvLw9E8kREREQ+C9g0mb///e9hs9mwYMGCQB2CiIiIyGsBC3qSkpJQW1sLnU7HwIeIiIhCLuCzRhUXFwf6EEREREQeRcYqcEREREQDxKCHiIiIYgKDHiIiIooJDHqIiIgoJjDoISIiopjAoIeIiIhiAoMeIiIiigkMeoiIiCgmBHxyQm90dnairq4Oe/fuBdCzSntmZib0ej0SExNDnDsiIiKKBiEPeiwWC3JyciDLMvR6PdasWQOLxYKWlha8+OKL0Gg0KC4uRmpqaqizSkRERBEs5EFPS0sLOjo61J+BnnW7srKykJWVBbPZjPLycsyYMQOTJ08OZVaJiIgogoW8T09WVhYmT54MrVbrdJ0uSZKwdu1aCCFCkDsiIiKKFiFv6QGA5cuXe9wmNzc3CDkhIiKiaBXylh4iIiKiYGDQQ0RERDGBQQ8RERHFhID06Wlra0NKSopPc+zU19dj9erV2Lx584CPL8syqqurkZKSAgAwm80oLS2FVqv1KR2TyYSFCxeioaEhoMchIiKiwAtI0DNp0iQUFxfjoYce8nofWZZhNpv9cvyZM2di0aJF0Ol0AHqCkfz8fDQ0NHgMSGRZxpIlSwD0DKE3mUwBOQ4REREFV0AebyUlJalz73jr0KFDfjl2XV0dAKiBCNAz7D09PR3V1dUe99dqtaioqEBFRQWmTJkSsOMQERFRcAWsT09bW5vX2z799NOor6/3y3EbGxuRkZHR5/XMzEw0NTX55RjBPA4RERH5R8CCHqPRiNdff93jdrNmzfJbwKMcV5KkPq9LkgSz2QxZliPqOEREROQfAQt6hBAoLy/H2rVrnb7f1taGyZMnw2g0+u2Y7gINpY+NP/oNBes4RERE5D8B6cgsyzLy8vIwfPhwvPjiizh06BB+/etfq+/v27cPM2fOREdHBzQaDYQQ0Gq1sFgsAzqu0o/IXSdiX/saheo4Go3j7/arcPR+z9P73r7nbBt/pOvP/Nq/72u69gJ1DoOZrr1gncNgpOvrccO9HtrTaEJ/bXzdN1D1MByuTbTfI/x+Dj1c/95CVb/dCUjQU1FRgYyMDKSnp2PEiBF4+umn0dHRgaVLl6KpqQkLFiwAADXgKS0thRACL730UiCyA8B960w4HmfQoHiH3202ge5um9P3AOD8eSsAICEhHnG92u+6u22w2QTi4jRISHB80z5dJe24uAs16kK6cQ6ve0pXCKCry+oyv11dVggBxMfHIT7eMV2rVcBqtUGj6buvfboJCfF9Kn/vdOPj49Q8CAGX6dqXddCgvul6ew7dXxvfzqHNBnR39z2HSpkUztK1Wm2wWgU0Gg0GDXJ9bbw5h47pur42jmV1lq4NQgiH63KhrBfuWL3roGO6vp7D/l8bb8+hp/qtvK+Ua2D12/05DPQ9QknX/u9KeS9S7xH2NHYbR/I9wpt0+3OP0Gg0biN3h/goAPcIb86hJwEJegoKCtSfDQYDkpOTsWDBAphMJpjNZofFQ6uqqtR1tZwtOOqL5ORkAM4DD6XlRdkm3I+jVDiFfR3r/Z697m6rywjZZhNu01XStlpt6K2729bvdJ3lV3nfarXBZnP+nv0fnjPKH7u7dJUPU/tyeUq3q6v/59B9fv1zDu0DBE/pCtE3Xcd9Q3FtBGy2vmVVbuiu6mBPuv6th96k6+kceqrfXV0XtrNabQE9h+7yZJ/uQM+h/d/VhXQj8x5hz/6DNpLvEb6k68s9QgjR90PD7nfR6+VQ1G9PgrLgaF5eHvR6vUP/Ha1Wi3Xr1iE9Pd1vx/FmbhxnnY/D8Tjumuo8NeMNZF932/Q33UDlN5DnIdzyFEvpBuq4oSqru21ZvyMz3XDMU1DS9aGuD+SYA93XnYAHPZ2dnbj33nvR2tqqPs7SaDSoqqrya8Cj0Ov1TjsRy7IMSZL8NmlgsI5DRERE/hGQ0VuzZs3Cli1b0NbWhuzsbLS2tkIIASEE9Ho9UlNTsWDBAuzfv9/vx87Ly3M6IsxoNKqP0SLpOEREROQfAQl6du7ciQ0bNmDSpEkOo5iKioqwdu1avPnmmxg+fDimTZuGjz76CEBPi9C+ffsGfGyDwQAADgGJ2WyG2WxGWVmZw7Y5OTmorKx0mVZ7e7tfjkNEREShF5DHW1qtFkajUe2wLIRARUWF2sFZq9WioaEBhYWFKCwsxPLly/HBBx/g9ddf90vg09DQgCVLlsBkMkGr1cJkMqG2ttbr/cvLywEAmzZtAgAUFhZCkiS1b5K/jkNERETBoxFiIF2CnBs7diwsFguU+XeqqqqQlZXldNv58+djy5Yt6u/+CHoindVqw8mTp4N6zISEOFx66SU4deq0wxD2SBeN5YrGMgEsVySJxjIB0Vsuf7lv6l246eT1brcxfq8Za/70akjO3+WXJ3ncJqAzMkuShDfffNNlwAMAy5cvx/Tp0xGA2IuIiIhIFbCgR6fToaGhwauh2xUVFQEZyUVERESkCFjQc+uttyIpyXNTk8K+rwwRERGRvwUk6OEK40RERBRuAjJ6y9vHWvZuvfVWjBgxIhDZISIiIgpM0NOf/jnp6ens10NEREQB4/XjrXAZSh4u+SAiIqLI4nXQk5iYiAULFgQwK549/fTTIT0+ERERRS6vgx5JklBcXIw77rgjIGtmudPW1oY77rgDeXl5uPrqq4N6bCIiIooOPvXp0el0WLZsGUpKSjBhwgTMnj0biYmJgcobOjs7sWrVKmzevBlr1qzxuXM0ERERkcLnIeuSJKGhoQE2mw233HILnn76aRw+fNivmWpra0N5eTmys7Oh0WiwefNmBjxEREQ0IP0evVVWVobZs2djyZIlyM7OxogRI5CVlYUJEyYgPT0dqampXqfV1taG1tZW7Ny5E83NzTCbzcjNzcUbb7zBYIeIiIj8YkBD1rVaLSoqKlBRUYG6ujr1n0ajAdDTKpSUlISUlBQkJSUhOTkZHR0dsFgsaG9vh8VigdlsBtCzVld6ejqKioowZcoUn2ZzJiIiIvLEb/P0GAwGGAwGAIDRaERraysOHTqEtrY2HDp0CADQ0dEBAEhOToYkSUhNTUVBQQF0Op3bRUmJiIiIBiogkxPq9XqupUVERBRgZXMX4IT5uMftLpMuR+XKZYHPUJgLSNBDREREgXfCfBw3nbze43bv48Mg5Cb8BWyVdSIiIqJwwqCHiIiIYkLQH28pw9M7OjqQnJzs8/B2IiIiov4IWtDT3NyMBQsWQJblPu+NGDECpaWlmDRpUrCyQ0RERDEmKEHP6tWrsWTJEqSnpyM3NxcjRoxAe3s7zGYzmpub8eWXX2L+/PnQ6XRYvHgxRo0ape7b2dkZ0KUuiIiIKDYEPOgxm82oq6tDbW2ty7l4WltbsWHDBtTX12PatGmora3F+PHjAQCnTp3CqlWrYLFYMGPGDC44SkRERP0S8I7Mq1evRlVVldvJB9PT01FRUYHdu3dj+vTpKCwsxEcffQSgZ1bn0tJSFBUVYf78+fj1r38d6CwTERFRFAp40KMsL+GNpKQkVFRUYOnSpSgpKUFnZ6f6niRJeOaZZ7BhwwYGPkREROSzgAc9Wq3W533y8vLwzDPP4KmnnnJ4PSUlBQCwadMmf2SNiIiIYkjA+/Qoi4/6Ki8vD5s2bcLrr7+O5ORk7N27F/X19QDAIe5ERBS2uDRE+Ap40KMsMuqLpqYmtLW1ITMzE6+99hr0ej1kWVZHfikLmxIREYUbLg0RvgIe9EyYMAGvv/46pk+f7vU+bW1tmDVrlvp7UVFRILJGRGHm7l/NxWfHjkII19tIl16Glc8vDV6miChqBDzoyc3NxaRJk6DX6zF8+HCv9jl16pT6c38fjxFR5PnXieM4MSMXbmIe4LWmYGWHiKJMUNbeevjhh1FYWOgwGsudW2+9FWvWrEFzczP27t0b4NwRERFRLAhK0JOXl4fx48cjOztbnX/HnfT0dBQUFAQhZ0RERBQrgrbKekVFBdLT01FYWIhZs2Zh//79brdPSkrC6tWrMWHChCDlkIiIiKJZUFdZr62tRWVlJdasWQOj0QhJkpCbm4vMzEykp6cjJSUFZrMZRqMRdXV1kCTJpw7QRETemvv4gzCfOuF2G3aaJoouQQ16AKCsrAy33norFi5ciNbWVqxevbrPNkII5ObmYvHixcHOHhHFCPOpEzhxZ677jdhpmiiqBD3oAQCdToeGhga0trZi48aNaG1thdlshiRJSE9Px4QJE9yu1UVERETkK5+Dnn379vltpfP09HSv1+UiIiIiGgifgp76+no8/fTTKCsrw3333ReoPBFRGPGm7wvA/i9EFP58Cnp27twJoKfPjTfa2tpgNpvR1taG5ORkSJIESZKQmJjoe06JKCS86vsCsP8LEYU9n4Ke1tZWaLVaj2tfbd68GdXV1WhtbXX6vrJ+VkFBAQMgIiIiCgqf5ukxm824//77XQYqnZ2duOOOO1BSUoLW1lYIIdR/qampSE1NhRACX375JV588UWMGTMGv/71r/1RDiIiIiK3fO7InJvrvJm7ubkZCxYsgCzL6uOvgoICzJgxo09nZYvFgo0bN6KxsREbNmxAc3Mz1q5d6/XaXERERES+8inoUSYQ7O3pp59GfX29GuwYDAaUlpYiKSnJaTpJSUkwGAwwGAyQZRlPPfUUCgsL0dDQwMddREREFBA+Pd6aPXs26urq1N83b96McePGoa6uDklJSSgtLUVFRQW0Wq3LgKc3rVaL5cuXY/r06aiurvYt90RERERe8qmlJzc3F6tXr0Z+fr7aSVmv1yMvL89hgdBJkyZhxowZPj2uKi4uxqxZs3zJDhERkdfK5i7ACfNx1xtogOE/GobnV7wUvExRUPncp6eoqAhFRUUet+HjKiIiCicnzMdx08nr3W5jTGgOUm4oFAKyyrrBYMCoUaOQnZ2Njz76yOv9vJ3/h4iIiMhXAVt7a/ny5SgsLERhYSF0Oh0MBgOmTJnisuVnwYIFmDBhQqCyQxRV7v7VXHx27Cg8fU/gLMlERBcEdMHR2tpalJeXo76+HiaTCeXl5UhPT4der8eIESMAAC0tLWhu7mlOXLZsWSCzQzHKmwAh0oKDf504jhMzcuGxbZSzJBMRqQK+ynpFRQWKi4tRXl6O5uZmmEwmmEwmaDQa9XFWbm4uFi9eHOisUIzyKkBgcEABFI2BN1EkCnjQAwCSJKG2thZmsxnNzc04dOgQZFlGRkYGMjIyuNI6EUU1Bt5E4SEoQY9CWXCUwhP7iRARUTTzOujp7OwM+fDzcMhDNGM/ESIiimZeD1kfM2YM9u3bF8i8REQeiIiIKDJ5HfSEwxw64ZAHIiIiikw+9enRaDSBygdRVJj7+IMwnzrhdhv2iSIiCg2fgp57770XycnJgcqLRwy6KNyZT53AiTtz3W/EPlFERCHhddBTVVUVyHx4jaO/ogNbRIiIKNi8Dnpycz18eyXyAVtEiIiiz+5jBzCl+O6wnfokqPP0EBFRdOC8XuTMmUGasJ76hEEPERH5jPN6USTyesg6ERERUSQLSksPZ1ImIgo8bwYIAOH1yKls7gKcMB93u81l0uWoXLksOBmiqBbwoKe+vh5PP/008vLysHRpePyRERFFI68GCABh9cjphPk4bjp5vdtt3seHQcoNRbuAP96SZRkPPfQQbDabw+tcToKIiIiCKeAtPXv37nU6x8+SJUuwZs2aQB+eiIiICEAQgp4pU6Zg8uTJyMrKQkZGBvR6PYYPHx7owxIRERE5CHjQk5eXB0mS8NJLL6Gurg4ajQZarRYA8Nvf/hYZGRmQJAlXX311oLNCREREMSwoo7d0Oh3Wrl0Li8WCnTt3wmg0or6+Hq+88gqAC2tqSZKE9PR0ZGZmqv/nqC8iIiLyh6BOTpiUlIS8vDzk5eWhra0Na9euhdlsRmtrK/bu3Quz2QyTyYTGxkYAUFuFsrKyMGPGDIwfPz6Y2SUiIqIoErIZmVNTUwH0tO5IktRnba/W1la0tLSo/2bOnInk5GRUVVUx+CEiIiKfhSzoqaiocPt+eno60tPTUVBQoL5mMplQV1cHk8mEWbNmBTqLRFHPm4nh/nXuSyQFKT9ERIEUUWtvXXHFFSgrK1P7AhFFI4+BiAb4/PwhJCJnwMfyZmK4nQmfDfg4QHDLFSzeBI2RWK5w89dv/oGpc+7xuF04zTRN4Smigp5p06ZBo9HAYDC43U6WZVRXVyMlJQUAYDabUVpaqo4a88Tb/fPz82EwGKDX6yFJEoxGI2pqalBRUQFJknwuHxHgXSBiHPT7IOXGf4JVLq8CEfinBcubMgGReb3CybeDNRE30zSFp4gKeh5++GHU19dDr9e73W7mzJlYtGgRdDodgJ6gJT8/Hw0NDV4FPt7ubzabUV5erv6u1WpRVVXFgIcohLwNRPzVgkVEkSOigh5l5Jc7dXV1AKAGLMCFofDV1dUoKyvz2/5ZWVnIzMxEe3s7MjMzodfrvW5NIiIKV9H4KJIIiLCgxxuNjY3IyMjo83pmZibq6uo8Bj2+7C9JEoqLiweeaSKiMBKtj1iJAr7gaLAZjUanj5ckSYLZbIYsywHdn4iIiMJTWLf0bN68GXv37kVKSgq0Wi0yMjLcLlfhLiBRHjuZzWaHR1cD2d9isaiPw4CeIfXFxcXs00NEfsfpBYgGLmyDntbWVsyfPx/JycnYtWsXAKC5uRkvvfQSDAaDOrmhvY6ODgBw269G2cbde97u397ejilTpjgEREqH54EGPv9emUMlhOv3PL3v7Xu+5q+/x/T1OL0paft6HgZyXH+fQyUNp+kOIN/ujmVPPa6fj+XumIFKv885DMCxPdU1fx7HVf0+0ebf6QVCfQ4Dcf6U47i8R3hRrt3HDmBK8d1u8yddehlW/cZxaLzD9t6eP83A7qU+nUONh2vei9NzGOB700A+U7w9F2Eb9CiTE9qP1MrKykJWVhaampqcBj3uDPSxlLP9ly9f7vC7JEnIyMhAeXk5amtrB3S8QYPiHX632QS6u21O3wOA8+etAICEhHjE9Xpo2d1tg80mEBenQUKC45v26QIANBpocKH2qBVf/Q8Qp9Fg0KB4t+kKAXR1WV3m1567yt17X/t0ExLi++zb1WWFEEB8fBzi4zWIj4+7cBC7hHvvF2f3wqBBfdP19hzGaTQuy6OcQ+X8uUpXo1HuhADQ987j9D7ez3OoHsvVzhoNNHaHd3fjsT+Hzq6NQx49HlM4fVsDx/MH9D2HDmVyk+E+93JX102jwaBBruu3pzuwsragUi5XWYrTaJCQEO+yfmt6H8fNOXT7IYaBn0ON/e//ft/dOfR0j/B4DnttEqhzqAFwJkGDEzNynX7Aq+XZsLnP35X9Oezzd+Uiw5p/X4cL9+84xMU5Htj9vcd1WXofV9PrmlutNlitwmP9tj+HF+5NLsrT6/DustS7DgJAV5cNQgjHe7daVu8+Az0J26AHABoaGpy+3nvJCkVycjIA5wGK0kKjbBOI/YGewMf+kVd/qTeDf7OvY73fs9fdbXV5L7TZhNt0lRecBcz2n782IdTgwpt03eXXaR7seCqrq7SsVhtstp68OTtI72Pa7F7o6ur/ObQJ4bI8yjlUzp+rdIUQfTNo93ufS+bsRTvuzqHTY/U6roDzTdydQ2fXxiGPXhzT6VtwPH/2SSnn0GWZeteB3j+7um6i7zV3l66z/ZXtnPy5qWxCOJy33udQuKkTvmTJH+dQ9N4R7s+hx3uPp3PoZhN/nkNvs9T7/Nlvb7MJ939X9uesVzrd3bb+37+9qIfOrrmn+m1/Dn2+N/XzHFqtAjZb/z9T3AnroMdX3gwXd/fYyZf9y8vL3Y7ekmV5QMPXPXwmBGxfb/lw/x3QMQN1HgJ53P6mr77mp2vk7lgX3vTvsbw6ZgDTFwIBKVOgy+PsOH2/kATuWH1e5zn06Th93/Q2keDdS50dy+djBvHeFKjzELLRW21tbQFJV6/Xw2w293ldlmVIkuQxEPF2/02bNjndrr29HVqtlvP1EBERhZmQtfRMmjQJa9euRVZWll/TzcvLQ01NTZ/XjUajy8di/dm/oKDA6Zw/zc3NDoukUnQI5tIGREQUGCELevo8W/UTg8GAmpoaGI1GtRO02WyG2Wzu07k4JycHubm5DsGLt/vPmDEDNTU1Do+3ampqkJyc7HECRPKPYC72yKUNiIgiX1T16VE0NDRgyZIlMJlM0Gq1MJlMPo2m8mZ/SZKQl5eHyspKAD1z9iQlJWHr1q1+LQu5xsUeiYjIFyENehobGwH0BBD2Q9D37duHlpYW7Ny5E5Ik4eGHH/YpXa1Wi4qKCo/buQpQvN1fkiS26hAREUWIkAY9GRkZkGUZGzZsQGtrK1paWmCxWBwefRkMhhDmkIiIiKJFSIOe1NRUZGVl9elgbLFYAABJSewSSkRERP4R0qDH1bB1BjtERETkbyENelpaWrB3717IsozMzEzo9Xq3C4oSERER9VdIg54JEyZg8uTJAICmpiasWrUKH330ETIyMtT3fF1ji4iIiMiZkM3ILEmSw4rlubm5qKqqwtatWzF+/HisWrUKkyZNwoIFC0KVRSIiIooiIWvpeeaZZ/DrX/8a06dPd3g9KSkJxcXFKC4uRmNjY8CWqyAiIgqlv37zD0ydc4/bbaRLL8PK55cGKUfRL2RBj16vx9KlSzFr1iw888wzTh9j5eXlhSBnREREgfftYA1O3OlheaTXmoKTmRgR0j49Op0Oa9ascbpwJ0Uub5aH4BpVREQUbGGxDIUkSaHOAvmRN8tDcI0qIiIKtqAHPRaLBWPGjEFycjJSU1ORkZGBjIwMpKamIjMzE4mJicHOEhEREcUAn4Oe119/HbIs93k9PT0dWVlZHvdPSkrCli1bsGHDBqxZswatra3Yu3cvWltbkZycjF27dvmaJSIiIiKPfA56Fi5ciPT0dAA9C4MKIaDVajF79myvgh7gwkKdt956KwoLC/Gzn/0MixYtwn/913/5mh0iIiLygCPFevTr8dazzz6LyspKJCUlYd26dWoQ5CudTodly5Zh1qxZXq1qTkRERL7jSLEe/Qp6nnrqKVgsFmzbtm3A62Tp9XpMmjQJS5YsGVA6RERERO70a0bm1tZWPPPMM35bGHTOnDkOszMTERER+Vu/WnokSXLov9Pc3Iy6ujqv9k1OTsYzzzzj8Fp6ejrS09Oxb9++/mSHiIiIyKN+tfTk5jo+F0xOToZWq4Usy2hsbERTU89zwdTUVAgh0NjYiMbGRgghXM7JM2XKlP5khYiIiMgr/WrpGTFihMPv6enpakdkWZYxc+ZMtLa2YvHixZg2bRr0ej2qqqrcPg7rnSYRERGRP/WrpcfZOlkKrVaLhoYGCCGQn58PWZaxdu1aj/1/OCszERERBVK/gp6UlBSP2xQUFODQoUNcNJSIiIjCQr+CHm8owc6ECRMCdQgiIiIir/WrT8+mTZtw9dVXu90mJSUFGo3G6746Gzdu7E9WyEseVz7XAJ+fP4RE5AQvU0REREHUr6DnlVdeQU1NDYCePjzOyLIMIQSmTZvmchtlOwAQQkCj0fQnO+QFb1Y+Nw76fZByQ0REFHz9CnreeustCCH8NqFgamoqZFnm2ltEREQUMP0KegD0e70tV1pbW/2aHhEREZG9gHVkJiIiIgon/Wrpqa6uhsVi8WtG/LWOFxEREZEz/Qp6WltbMXnyZK/m6/FGe3u7unQFERERUSD0K+gpLS3F5MmT/ZoRvV6PWbNm+TVNIiIiIkW/+vQEYsmIlJQUCCH8ni4RERER0I+gp6qqyuPEhP2Rnp6Oqqoqv6dLREREBPQj6MnNzQ1EPgKeNhEREcU2DlknIiKimMCgh4iIiGICgx4iIiKKCQx6iIiIKCYw6CEiIqKYwKCHiIiIYgKDHiIiIooJDHqIiIgoJjDoISIiopjAoIeIiIhiAoMeIiIiigkMeoiIiCgmMOghIiKimMCgh4iIiGICgx4iIiKKCQx6iIiIKCYw6CEiIqKYwKCHiIiIYgKDHiIiIooJDHqIiIgoJjDoISIiopjAoIeIiIhiAoMeIiIiigkMeoiIiCgmMOghIiKimMCgh4iIiGICgx4iIiKKCQx6iIiIKCYw6CEiIqKYwKCHiIiIYgKDHiIiIooJDHqIiIgoJjDoISIiopjAoIeIiIhiAoMeIiIiigkMeoiIiCgmMOghIiKimMCgh4iIiGICgx4iIiKKCQmhzkAgyLKM6upqpKSkAADMZjNKS0uh1Wr9uv9Aj0NERETBE5VBz8yZM7Fo0SLodDoAPcFIfn4+GhoavApIvN1/oMchIiKi4Im6x1t1dXUAoAYiACBJEtLT01FdXe23/Qd6HCIiIgquqAt6GhsbkZGR0ef1zMxMNDU1+W3/gR6HiIiIgivqgh6j0QhJkvq8LkkSzGYzZFn2y/4DPQ4REREFV1QFPe4CDaWPjdlsHvD+Az0OERERBZ9GCCFCnQl/MZvNyMnJQUVFBQwGg8N7RqMRhYWFqK2thV6vH9D+kiQN6DieCCFgs/n3shw/+jUutl3sdpt2WBB/aTI8HTn+9Bl8/z+GDvhYcZcmB/w4yrE8lcufxwpGucLtWvnzWNF2rZRjBaNc4Xat/HmscCpXpNbBSLo39Ud8vOd2nKgcveXMQB83ebu/Px5raTQaxMdrBpyOve8P/77HbVKQ4l1iie5HpvntWH44TrQeK+yuVTCPFWHXKpjHCrtrFa3HirB6Ecxj+etaBUpUPd5KTu6JYp0FHh0dHQ7bDGT/gR6HiIiIgi+qgh5v5sZx1vnY1/0HehwiIiIKvqgKegBAr9c77UQsy7JXAYu3+w/0OERERBRcURf05OXlwWg09nndaDQiNzfXb/sP9DhEREQUXFEX9CijqewDErPZDLPZjLKyModtc3JyUFlZ2a/9fTkOERERhV5Ujt5qaGjAkiVLYDKZoNVqYTKZUFtb6/f9B3ocIiIiCp6omqeHiIiIyJWoe7xFRERE5AyDHiIiIooJDHqIiIgoJjDoISIiopjAoIeIiIhiAoMeohDjAEoKNdZBihUMeqKQcgPjjSz8ff3113jnnXdCnQ2/Yx2MHKyDFEuicnLCWKfRaBz+H+m6u7shyzKGDBkCm82GuLjoiNUPHz6M3NxcdHd346c//SlSU1NDnSW/YR2MDKyD5E401XVFdJUmxn311VeYN28eJk6ciOnTp6OqqgonTpwIdbYG5NixY7jvvvuQnZ2NvLw8vPTSS+js7Ax1tgZM+bD5z//8T1xxxRU4evQogMj/Vso6GDlYB8mZc+fO4ZtvvsHhw4fR3d0d6uz4HYOeKHH06FFMmjQJiYmJuPPOO5GUlIQ//elP+K//+i/87W9/C3X2+uXIkSOYOnUqhg8fjrlz52LIkCFYs2YNNm/eHOqsDYjyYXPHHXfggQceQEJCApqbmwFE9rdS1sHIwTpIzrS1tWHq1Kn42c9+huzsbMyYMQOrVq0Kdbb8S1DEs1qt4r777hMLFiwQHR0d6usffvih+MUvfiGuvfZa8dZbb4nu7u4Q5tI3Z8+eFbfddpuorq4W3377rfr6hAkTxEMPPRTCnA1MW1ub0Ol04umnnxb/+te/hBBCPP744+KRRx4RQghhs9lCmb1+Yx2MHKyDkVMHg+mbb74RmZmZYtmyZeKTTz4RH3zwgXjooYfENddcI+bNmyeOHz8e6iz6BVt6okBcXBza2tpw3XXXQavVqk2SEyZMwK9//WtMmDABTz/9dER1Vuzo6MDZs2dxww034OKLL8b58+cBANdccw2+/vprAMD58+cjqim+ra0Nubm5KCgoQHFxMa644goAwLXXXoumpiZ8+eWXEfstm3UwMrAORlYdDKb169fjRz/6EaZPn47rrrsO119/PZ588kk88cQT+Oijj1BSUoIvvvgi1NkcMAY9UeLs2bM4fPgwACAhIQE2mw0AcNVVV+Gpp57CTTfdhEWLFmHPnj2hzKbXzpw5g0GDBuGyyy4DAAwePBhnzpzBiRMn8Pnnn2PJkiXIz8/Hfffdh08//TTEufXOli1bcPvtt+O+++7D8OHDAQBWqxVXX301hBDqDcVqtYYym/3GOhj+Nm/ezDoYQXUwGJSg/R//+AeGDRuGYcOGwWazwWazYciQIbjtttvwwgsv4Msvv8RTTz2lBvyRikFPhFIqqvLt87bbbsP777+P3bt3A+j51qP8wX/ve99DSUkJRo4ciYcffhjffPNNaDLtA41Gg2uuuQYpKSnqazt37sSnn36q3qCHDh2Kv/71r5gzZ45a7nCkXKt77rkHjz76qMMImfj4eGRkZOCqq67C6tWr1dciqfWgq6sLQHTUQeXvCYiuOqi0etx333147LHHoq4OKuWLhjoYbErL3lVXXYXdu3fj8OHDiIuLU1+/+OKLcdNNN+HZZ5/F559/joqKilBmd+BC9FiN/Ozjjz8W1113nXjggQfEZ599pr5utVrVnzdv3ixuuOEG8dxzzzm8Hi569yXo6uoSQvSUwWKxiAULFojHHnvMYZvGxkZx/fXXi+uvv16cPn06aHkdCPs+BcrPtbW1Ii0tTWzYsCFU2fLJqVOnRGtrq8Nrn3zySUTXwUOHDok5c+aIL7/8Un0tGurgkSNHxG9+8xvx+eefO30/Uuug1WpV++4o945du3ZFdB0MhXPnzgkhhDAajWLy5MliyZIlwmKxCCEc78lnz54Vr776qkhPTxcrVqwISV79gS09EebYsWN44oknMGXKFDzwwANYt24durq6MGbMGJSWlmLLli34v//3/+Krr74C0PNNR2mqzs7ORkZGBt5///2wmntBlmUAPd84hN23y4SEnmmk4uLikJiYiF/96ld4/vnnAVz4Rj5p0iTk5ubi+PHjYTcs9eTJk1i8eDEmT56MWbNm4bnnnkN3dzfi4+PVb5/x8fEAgNzcXKSkpODPf/4zTp48CSB8hw6fOHEC119/PV555RXs379fff26667Do48+ii1btuDVV1+NqDrY1taGKVOmIDMzE0OHDlVfj/Q6ePjwYUyaNAmXXHIJvvvd7zrdJhLr4NGjRzFv3jxMnjwZ06dPx5w5c3D+/HmMHTtWvQ9GWh0MpvPnz6OzsxNnzpxR63hWVhZGjRqF2tpabNy4EWfPnnW4J1900UXIyclBdnY2Nm7ciOPHj4dt/XAnNq94hPrqq6+QnZ2Nb7/9FjfeeCO+/PJLrF27FgUFBTCbzbjzzjvx8MMPY8OGDaipqcE///lPAD03tfPnzyMuLg633HILzGYzOjs7w6LCdnV1Yfr06SgrKwPQN/ABLtx4f/SjHwHomTBr8ODB6sRZer0eADBo0KAg5ty9trY23Hrrrfjggw/wgx/8AIcPH8Yf/vAHTJs2DadOnXJodrfZbPjBD36Axx57DJ988gn+9Kc/AXB+LsJBY2Mjuru78f7776OmpgYHDx5U3ysoKMCDDz6I1157DatXr46IOtjW1oa8vDzMnz8fhYWFuPjii/tsE4l1sLOzE3PnzsVTTz2F2bNn4/vf/36fbSKxDh45cgS33XYbfvjDH+Kxxx7DpEmT0Nraijlz5sBms+HOO++MuDoYTG1tbbjjjjtwyy234LrrrsN9992H119/HQBQVVWFa665BsuWLcOOHTtw7tw5aDQa2Gw2CCHwve99D/fccw+++OILHD58OCI7vXNG5gjR1dWFhx56CFOnTsWTTz6JpKQkfPvtt9ixYweWL1+Ou+66C4sXL0ZhYSGEEPjtb3+LI0eO4J577oFer8fgwYMBAJ9//jkyMzORmJgY4hL1UCbA+tOf/gSbzYaXXnpJvdG6mlFV+T0uLg7nz5/H//zP/+Cqq67CkCFDgp5/Z86cOYPCwkIUFBQgPz8fP/zhD2GxWPDqq6/i//yf/4OysjLU1NSo3zKV/48bNw4TJ07E888/j8suuwxTp04Ny5vKz3/+c3zwwQdISUnBH//4R3R3d+NXv/oVRo4cCQC4//77YbVasXz5chw+fDis66ASnM6fPx933XUXvvOd7zjdTqPRwGq1qq0i4V4HAWD//v04e/YsRo8erQZje/bsQVdXF1JTU5Gamoq4uDgIISKmDp47dw4PPPAA5s6di7vvvhuDBw9W+/Ns375dLcfs2bPR3d2NFStWhH0dDKbjx48jLy8PhYWFGDduHL766is0NTXhmWeewb59+/DEE0+gqqoKc+bMwaJFi9DZ2Ync3FwkJSWhu7sbCQkJuPTSSwH0tPxEpKA/UKN+mzhxonjjjTeEEBeew3d3d4tPP/1UGAwGMX78eLFjxw4hhBDr168XOp1O3HzzzeL5558X7777rvj9738vdDqd2LVrV8jKYM9isYjMzEzxxBNPiBUrVoi0tDSH+U9czReiPIdva2sTf/rTn8R1110ndu/eHZQ8e8NkMons7Ow+fSg6OzvFAw88IMaOHSu++eYbp/v+5S9/ETfeeKO4+uqrRWNjYzCy6xOr1Sra29vFz372M2E0GsW7774r0tLSRElJiThw4IDDtm+99ZZIT08XN910U1jWwc7OTpGZmSkKCgr6vLdnzx7x5ptvildffVV8/PHH6t+bfR8fIcK3DgohxO9//3sxadIk9feFCxeKa6+9VqSlpYkxY8aIe++9Vxw9erTPfuFcBw8dOiRuvPFGta4p1+Wjjz4SU6ZMETabzaHP3Pr168O6Dgbb4sWLxZ133imOHTumvtbW1iZWrlwpdDqdmDdvnjh69Kj4+uuvxV133SVGjRolKioqxKFDh4QQPfX/rbfeEuPHjxcnTpwIVTEGhC09EeL06dNob2+HxWIBcGFUQnx8PK655ho899xzeOqpp/DUU0/h97//Pe68805ceeWV2LJlCxobG7Fp0yb8x3/8B9asWYOxY8eGuDQ99u/fj0mTJuHZZ5/FqVOncPr0adTW1qotVb1bfICeobSLFy/G4MGD0dzcDKvViqqqKowePTqEJXH07bffAoDDCBmbzYZLLrkEjzzyCO644w4cO3ZMHQoNQC3nDTfcgAcffBCPPfaYQ9+ScBEXF4fk5GRkZ2fjxRdfxFtvvYVjx47hhRdegM1mw4MPPogrr7wSdXV16vIGf/7zn8OyDp49exZz5szBypUrsWrVKsyZMwcAUFNTg5deegmXX345jh8/DgD46U9/ipdffhnJyck4d+4cfvOb34R1HQR6vokr/Y7Wrl2L/fv3Y/78+dDpdGhqasLGjRtx55134rnnnsP48eNx/vx5DB48OKzr4OnTp3Hs2DH1PhgfHw+r1YrPPvsMgwcPxrJly/Dpp5/i0ksvxYMPPog777wTV111FTZt2hSWdTBYlPvLF198gSuvvBJDhw5VWy6HDx+Ou+++G5dffjkWL16MRYsWYcmSJXj11Vcxb948bN68GX/+858xceJEnD17Fh9++CGWLl0aVq2aPgltzEXeUL5VPvHEE+L2228X+/btU9+zbw35+9//LiZPnixuu+02tUd+d3e36O7uFmfPnlVfC1fHjh0TL774okhLSxMPPvig+nrvFp8///nP4qWXXhLvvvuuwzeWcHHgwAFx/fXXi7a2NofXz507Jzo6OsSNN94oDh482Gc/+5Ekzr6Bh5NNmzaJa6+9Vh2ttHbtWpGWliZKS0vFrFmzxMSJE8UXX3whhOgpV7jWwfb2dvHyyy+LtLQ0UVtbKw4cOCDS0tLEjh07RHd3t7BYLOKXv/ylSEtLE9OmTVPz/84774R1HRRCiH379om0tDSxc+dOsW7dOvHGG2+oM0t/++23Yvv27WLq1Kli4sSJ4uzZs0KICy1ZQoRfHbTZbOLYsWPiZz/7mSgpKRGffPKJOHXqlHj33XfF+PHjxT333CN+85vfiIcfflhkZWWJm266Sf07O3fuXNjWwWB66qmnRE5Ojjo6y/6ec+7cOdHQ0CAyMzNFeXm5+vp7770nXnjhBVFUVCQWLlwo/v73vwc93/7EoCeCbNu2TfzkJz8RCxcuFEeOHFFfV4KCrq4u8cYbb4hx48aJ3/3ud0IIIc6fPx+SvPpKKYOrwKf30NJwH2r6wgsviPXr1zsEbEqe8/LyxKeffup0v0i5IZ87d06MHTtWVFdXqx+U9fX1Ii0tTeh0OvH666+r24Z7HVQCn/T0dJGTkyOmTZsmhLhwLU6dOiUef/xxkZaWJpYtWxbKrHrNarWKEydOiOnTp4uf/exn4sYbb1TrnHK9uru7xfbt28Xo0aPFo48+Kmw2m7DZbGH/t/Xqq6+K3NxcMX78eDF16lQxZswYMX/+fIdtdu7cKSZOnCimTp0qhIjcpTX8RbmmW7ZsEbfccouoqalR67f99bZYLGpXg//3//5fSPIaaBy9FUFuueUW3Hvvvaivr8cbb7yhDitVetcnJCQgNzcXV1xxBXbu3AkgvEaTuKM8who6dCjuvfdezJo1Cxs3bsRDDz0E4EJnX7PZrI6YCUfKaJhHHnkEd955p8OjOSXP3/nOdxzyf/LkSfzxj3/EyZMn1Y6W4UwIAZvNhu9///v461//qg55bWlpwcUXX4zu7m785S9/wWeffQYg/OtgcnKyOuLHfhiuMjorJSUFjzzyCK644grs27cvxLn1TlxcHIYMGYI77rgDn332GY4dO6bOpKvMVBwfH4+srCxkZWXh4MGD0Gg00Gg0Yfu3pVyXu+66CzU1NVi/fj1effVV3HDDDbjtttsA9HR0BoDRo0dj6tSpMJvN+Oabb8KqM3YoKNf0pptuwrBhw1BTU4P33nsPVqvVYSRpYmIipk6dinHjxuHtt99Ge3u72lFc2SbShWftpj6UCqc8p161ahVee+01HDt2DEBPpe7q6kJiYiKys7PR2tqKc+fOReRwzN6Bz8MPPwwAaG5uRklJCY4ePRriHLrm7gNDWadJCIGkpCQAQHt7O95880089thjMJvNwcrmgF188cUoKCjAvn37cPbsWZSVlWHz5s1Yv349HnzwQWzevBnLly9Ha2trqLPqlZSUFEybNg2PPvooRo8eja6uLnVUk9VqRUpKCsaNG6eWJ9w/AJS/e4PBoH5xWLNmjTqvUlxcHLq7u3HRRRfhhhtuwJdffolz586Fdbnsh89LkoQrr7wSF110Ed577z20t7cD6OnHZLVaMXjwYIwaNUoNgqinzg4aNAgrV65ESkoKqqqqsGvXrj6Bzw9/+EMYDAb8z//8Dzo6OhzmqooG7MgcIZShpRqNBk888QSEEOpwzF/84hfIyMjAoEGDYLPZ1EX3InZIIS4EPnFxcVi9ejWOHj2KlpYWLF++HMOGDQt19vrFvmP2RRddhM7OTtTX12Pp0qVYu3YtfvKTn4Q6i15RvjWPGDECsizDYDDgm2++wcqVK5Geno709HR1yPr8+fNDnFvvXXbZZbjjjjsA9LROKR094+PjcfbsWbS3t+OGG24AEP4fAErrb1xcHO6//36cOXMGq1atwrJly1BUVITRo0cjISEBZ8+exeeff45rr702Iu4XvVtsBg8ejBEjRmDz5s346U9/iiuvvBLx8fHo7u7GP//5T1xzzTWR2+HWz5RANzExES+//DKKi4uxePFiPPjgg7jpppswePBgdHV1YdCgQRgxYgSA8A/u+yU0T9XIH37729+KtLQ0kZubK9auXSt27Ngh6uvrhU6nC7vhs/319ddfi6KiIpGWliaam5tDnR2/uOeee4TRaBSrVq0SaWlp4sMPPwx1lvrNYDCIyZMni7/97W993jt8+HAIcuR/x48fF++++66YMGFCn6U3wp19X5bq6mqRmZkp9Hq9WLFihXjzzTfFb3/7W/HTn/5UfPLJJyHM5cAofVDmzZsnPvnkE/Hll1+K+vp6kZWVFTX3wUD4xz/+ISZPnixGjx4tqqqqhCzLQoieOvPaa6+JG264QX0tmmiEiMDnH1Hm5MmT2LVrF1paWnDLLbdg6NChkCSpz3Bthf3rmzdvRmNjIz744AMMHjwYQ4YMwRNPPIGsrKxgF8OBr2VyZdeuXZg7dy5+97vfhbxMwMDKpbQc5OfnQ6fT4Y9//CNWrVqFCRMmBCn3rvW3XH/5y19wxRVX4IorrlBf8/UaB8pA6+DixYsxaNAgfPrppzh48CCqqqrUlp5Q8rVc9n3gtm7dih07dmDr1q2wWq0YMmQIKioqMG7cuGAXo4+B3Ad/97vfYcWKFQB6WoOGDRuGxYsXh8U9I5h8/duzWCwoLi7GoUOH1K4RnZ2d+POf/4wVK1bg+uuvD2BuQ4NBT4gpM8KOGDECR48exbfffgtJklBaWoqcnByX+9nfyLq6unDmzBloNBrEx8fjkksuCVb2nepvmXr79ttvMXXqVDz++OM+7RcoAy2X1WpFV1cXcnNzcezYMdTW1obFTdlf1yuc+KNM1dXV+OSTT/DjH/8YeXl56hIUoeSP+wUAdHR0hM39Auh/uew/5Pft24dz587hkksuwdChQ5GcnBys7IecxWJR+wl6G/goX8LOnz+PpqYmfPDBBzCbzfjBD36Ae++9N2Iet/ss6G1LpJJlWdx0003it7/9rTrXR2Njo5g3b55IS0sT1dXVbpsXlaZr+xlIQ22gZVIoZTtz5kxA8+stf5VLiJ7m+HB5pOXPcoWLgZbJfghvOA11jsb7hRADL5dSnnC6VsF0/vx5kZOTI5588kn1NW/PRbhPTxAI7MgcQocOHYLVasWNN96oznyam5uL9PR0DB06FEuXLkV7ezvmzJkDrVbbZ/+uri4MHjxYXQ8oHAy0TMqssEqnX1drIQWbv8oFAA888EBQ8+6OP8sVLgZapu7u7rArExCd9wtg4OVSWizC4ZFqKLS1tcFqteKNN96A1WrF888/73Q2e2eU1j9lXa1wng7EXxj0hNAXX3wBWZbVZkTlA0SSJMybNw/Jycl4+eWXkZiYiF/+8pcOlbilpQUffvghbr75ZowaNSqUxXDgzzKF000sGq8VEJ3lYh2MnGsFRG+5gqGzsxO33347pk6dissvvxzV1dUA4HXgc+rUKSQnJ0fdsHS3QtXEREJ89dVXYty4cWLp0qXqa/bNjR0dHeK5554TaWlpYvPmzUKIC82Wr732mkhLS3NYkiIcRGOZhGC5Iqlc0VgmIViuSCtXMBiNRrFgwQIhRM8ow0WLFom0tDTx2GOPqdu4etR18OBBMXv2bFFVVRVTjwYZ9IRQZ2eneOihh8SUKVMc+njY/8H/85//FPfdd5/DWkaKL7/8Mmh59VY0lkkIliuSyhWNZRKC5Yq0coXCkSNHxLPPPutV4CPLssjKyoqaqUC8xaAnxD777DORkZEhZsyY4bCQm/0f/Lvvvit0Op149913hRCOiwKGo2gskxAsVySVKxrLJATLFWnlCgVfAp9wXxcvEGLgAV54+9//+39jzZo1aG1txYoVK2AymQBcWFYCAG699VYMHToU27ZtA4Cw64jYWzSWCWC5Iqlc0VgmgOWKtHKFwg9+8AMUFhbinnvuwVtvvYXHH38cwIXZrA8fPqxuG+7r4gUCg54wMHbsWLz44ovYtWsXnn/+ebz//vsAeiqkEAKyLOPiiy+GTqcD0Hcq9nAUjWUCWK5IKlc0lglguSKtXKGgBD7//d//7RD4KOsXfvXVVyHOYQiFsJWJejEajSIjI0PccMMN4sUXXxRnz54VR44cEdu3bxc6nU4cOHAg1Fn0WTSWSQiWK5JEY5mEYLnIsyNHjqidwO+9917x4x//WOzYsSPU2QopzsgcZj777DMsXboUH3/8MeLj4/Hd734X58+fx3PPPYcbb7wx1Nnrl2gsE8ByRZJoLBPAcpFnR48exeOPP47m5uawmQU+lBj0hCGLxYKjR4/ib3/7G4YOHYr/9b/+FyRJCnW2BiQaywSwXJEkGssEsFzk3q5duzBnzhy8/PLLMR/wAAx6iIiIotLp06eRl5eHp59+OmLX0fM3Bj1ERERR6vTp02GxqGy4YNBDREREMYFD1omIiCgmMOghIiKimMCgh4iIiGICgx4iIiKKCQx6iIiIKCYw6CEiIqKYwKCHiIiIYkJCqDNABABpaWkOv5eWlqK4uNjjfmPGjIEsy9Dr9aitrQ1U9qJGTU0NlixZAgDYvXs3tFptiHM0cJWVlVi9ejUA4MCBA/1KIz8/H2az2S/5kSQJDQ0NfkkrEil/y5IkYevWrSHLhz/qBUUftvRQWHrllVdCnYWYNH/+fKSlpSEtLQ0mkynU2QkaWZb9+s9erJ5TonDElh4KS7Iso66uDgaDIdRZoRhQUVHRJ1gBoLaENTY2oq6uDgBgMBiQl5cHAG73IaLww6CHwoper0dLSwtkWUZNTQ2DniBLSUmJyQ9tvV7v9n37R1+SJHnc3l6snlOicMTHWxR27r//fgA9HzSNjY0hzk1sqaiowO7du7F7927odLpQZycq8JwShQ8GPRR27Dsws28PERH5C4MeCktFRUUAAJPJBKPRGOLcEBFRNGDQQ2Fp9uzZ6s81NTUhzAkREUULBj0UlrRardqJ2Wg0+m0OFSIiil0cvUVhq7i4WB0mXFlZieXLlw8ovZqaGmzatAlmsxmyLEOn0yErKwtlZWVOt29sbFT7FCmTzZlMJtTV1cFoNMJgMKj9j+rq6tS8NjQ0QJZlVFdXo6mpCWazGVqtFllZWZg9e7bamdXVNmVlZZAkyWU5zGYzNmzYgObmZsiyDLPZrI4oKi4udruvN+fI1eSF8+fPR1NTk1fpaLVa7N69u8/r3pwXZ5RrYTKZoNVqkZGRgby8vIgY3edpQshg1h13+3q6Bv7ibXm9KYs/6oW356Ourg7l5eUAeqYtqKiocJqe2WxGTk4OAP9M0FhZWanmzRtarRbbtm3jiEEXGPRQ2FI+yI1GI5qamiDLcr/+kM1mM0pKSvpMDGcymWAymdDU1ISqqqo+N/yOjg6HfexneAWA9vZ29WdZltVtjUYjSkpKHOZwkWUZTU1NaGpqUgOomTNnOt2mubkZDQ0NTm/49jfe3mVUPkyqqqrUeWRCJSMjo89rZrMZhYWFDjdv+/NSUVHh9MPKPmhQ9jEajTAajaipqRlQkBcOglV3gP5fA3+yL6/JZEJJSYnT/Hgqiz/qhS/nw2AwqF966urqoNPpnJ6rkpIS9eeBzBIvyzJmzpypBnRarRbJyclqvl2VT5IkBjxuMOihsFZaWor8/HwAQHV1tctWGVfsv3VptVqUlpaqH8gtLS1YsmQJzGYz8vPzUVtb63L+lfLycvXbqV6vh16vdxlYFBYWQpIkLFq0CDqdDmazGUuWLFFv9AsXLoTJZIJOp8P999/fZxtljiJX3ySBno7eEyZMUMuiBHbK/7du3er3YGD58uV9JuNTbq6yLCM7O1sNTKuqqhy2c3Yd9Hq9Q7nLy8uRkZHR59u1/QebMjGgJEnqh1s0dXQPZN3p7zUIpPz8fEiSpH7p8LYs/qgX/TkfFRUVaGlpcXmuysvL1WtVW1s7oL/BkpISJCcn9/lbVv7GY3mpkwERRGFg5MiRYuTIkWLmzJl93ps2bZr6fm+jR492uZ/9vtnZ2aKjo8PjNvY2bNigHnfkyJFi9OjRYufOnU7TeOWVVxy2c3as7Oxsj9so5Rk9erTT4xw6dMhlOTo6OtT0Fy5c6DGfztLx9L4r8+bNU/fbtGlTn/dnzpzpttzKNeh9He3PWUtLi9Nju6sf/mJfF1555RWf9vXlnAey7vT3GvhKyWfvvyeFN+X1VBZ/1Iv+no+Ojg41f/b3lU2bNvW7jvT2yiuviHnz5rl8z9XfN3nGjswU9pTJCgHfRnLV1dWp37qqqqpcNvkqrRJmsxmVlZUu01u3bp1XM/EWFBQ4PZb9vvfff7/TbbKysgA4X94AcN90rdVq1W+dwWz9qKurU/v62C/RoFAeOQDAokWLnOa/tLRU3VbR2NioPnYoKipy2frg7FFapApU3envNQg0V+WdMmUKAOdl8Ue9GMj50Gq1WLduHYC+LawA1L51A7F3716XfRg3bdrk04zg5IhBD4U9pdka8G2yQuVxlCRJbpvr7ZcVqK+vd7qNwWDwusl/woQJTl9PSkpSf3Z100pJSfHqGK4oz/w7OjoGlI63lGZ+oOc8OnsUocyqrdVqXT4StD8fyoeM/YeNr481I1Wg6k5/r0GgeVPe3vxRLwZ6PnQ6nfplyWg0OnRc7v1otz9cBTxKfyjO7N1/7NNDEaG4uBjl5eWQZRmNjY1eddRVWnnS09M9bqsEVcoq2b2/+fnyzcqb5/iutnF3s3dGGc5/6NAhmM1mtLS0+LT/QHnTaVP5wJBlGWlpaR7TVL7FK/+P9I7KvghU3envNQi0/lxbf9QLf5yPvLw8FBUVOQxuqK2tDWgn4k2bNgGIrb8Jf2PQQxHBYDBgyZIlkGUZS5Ys8Wl0kjetJ/Y3kY6Ojj43rnD6ZmU0GrFhwwavh48Hyvz589UPg4qKCpc3YvtWJ18+EJS0ORJl4Pp7DcKRP+qFv87HjBkz1KBHp9MFPBhpbGwMq3tRJGLQQxGjoKAAq1evhtlshtFo9Lr1xZtvrfbbKI+I7Dl7LRTsh81rtVoUFBQgMzNTveEWFhYG5dFEY2OjGnTl5uZ6NczZ3dwmzkiSBLPZzIkp/cjXaxCO/FkvBno+CgsL1Z9NJhMqKysD+ihWmR+M+o99eihi+Lo0hfKty5tHPso2ynwY4choNKoBT1FREXbv3o2ysjKHPk++Ph7rD/tOm5IkeZw00pfr4Gw/V526yXv9vQbhyB/1wh/nQ2nplCRJfbS7evVqtb+QvynpshPzwDDooYjRe2mK3pMN9qZsq/QDckWZpBC4MGokHNmXwdW3SYvFEvB82Pfj8abTpnJO7c+zN3rP1+OK/SSR5Fx/r0E48ke9GOj5qKmpUVs6q6qqoNfr1dFeziZC9YeNGzcCCK9H7ZGIQQ9FFPuhoNXV1R63Vb7RLVy40GlzuCzL6oe4MkFZuLJvxXH2LVeW5YB/k7effK20tNSrG7D9deg923Bv9oGdwWBQW93Ky8udXj+z2Rzyvk2RoL/XIBz5o14M5HwYjUZ1YkT7v4Hi4mK1Fab3jNn+0NzcDICdmAeKQQ9FFEmSkJubCwDq0hTuKC0RsiwjJycHlZWVaitRTU0NsrOz1Zumu7l8woH98N78/Hx1vhKz2ayWJZCPgoxGo/rNWpmCXxnt5uyfPfu5kLKzs1FTUwOTyaT2z6qpqUF+fn6fJQnsg9CcnByH/ZR9yDv9vQbhyB/1oj/nw/5Lkk6n6zMfj3IPUZaQ8Bdlhmq28gwcOzJTxJk9e7bX3+51Oh0aGhrUG9fq1asdhpgCUJdNCPdn5cryF8owdfvHTEBPOZROnoFgfzyTyYQxY8a43f7AgQPqz72vg/0SAvZ0Op1Dp3GDwYBDhw6p16z3fnq9HklJSWzt8UJ/r0E48ke96M/5sG/BcfZoV7mXFBYWqnNY+aPjuPJoS5mAkvqPQQ9FHJ1Op374e7v91q1b1VXWlcczSqvR7Nmzw7qFx15tbS3Ky8vVwKf3ytKBWovKWeuNr1xdB51Oh9TUVMyYMcNp4FlWVobMzMw+q2krjxPq6uqC0pcpGvT3GoQjf9QLX86H/aPdqqoql4+Z9Ho9DAaDx4VJfaXVajFjxowBpxPrNEIIEepMEBEREQUa+/QQERFRTGDQQ0RERDGBQQ8RERHFBAY9REREFBMY9BAREVFMYNBDREREMYFBDxEREcUEBj1EREQUExj0EBERUUxg0ENEREQxgUEPERERxQQGPURERBQTGPQQERFRTGDQQ0RERDGBQQ8RERHFBAY9REREFBP+P2ntKT9S6exvAAAAAElFTkSuQmCC"
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 600x450 with 1 Axes>"
      ],
      "image/png": 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5Wx/oOrXtIpFuJMvrvD6YdL3VL9JtGK90fdU3Um0Y63S9SYRjE6m6+lofrfJGuw298dcONKKkZAYGB23Yv3+fx7pdu97AxImTkJ0d3qD0m24qRV/fMdhsvscyObPZbBgctGHcuPFh5R0LofZRdyk3SNubWN3yilQ+I++pGeVwCAwPO1TXAcCZMyMz044Zkw73iWeHhx1wOATS0jQYM8Z1pVq6GRnpSEvTuKWbpiwLJF0hgKEhu9fyyi8pTE9PQ3q6a7p2u4Dd7oBG47mvc7pjxqR7dHZv6aanj5ZPLV3numZkeKYbbBuqpRtsGzocwPCw9zaU05XXO6dttztgtwtoNBpkZHg/NsG04Ui63o+Na13V0nVACIH0dI3L8Ripq2cbyttkZKQr64Jvw9CPTaBtGEr/lrkfN//HJrg2VK9r+OcI9XRH2tD5uDkcwku6rnVT+9BKpskkNRrX8vqqj791kyZNwrhx4/Haa+246qqrlXU2mw179uzCgw8+rKShFlA7/+wtz7y8PADA4cM9mDLl6oD23bBhHQDg3//9do+6q9XFX11H1msACC/rvO/rK8gZMybNo5/66t++pFSAlJOTA0A9SJGv6MjbJHo+8klS5txx3Nc5Gx62e+2wDocIKN2hITvsdodbuo6w01Vbb7c74HCor3P+sFAjBw+BpOtwuP4R+kp3aCj8NlQvb2Tb0L3MzsdstA0903UtUzyOjVBeNeG+DhhNVz5mzvlEqw19peuvDUPp3/JJWu1vbbRM4beht3Sj2YbOx03+2T1d97e4J1MwpMa9/L7q42+dEMCNN5bgxRd/5bLtm2++AQCYNm26y9+h+77uP6vl+Y1vjFwFkm+XOW9/7NgxHD48OhBbfortwIG3sXjxEo8B4qHWdWS98LpNqOkODzuQlqbeh9X6ty8pFSAFMveQ2sDqRMwnvE4X+r6+tgvnjz7YvOKZbiKWKZDjFukTTTj78tiEvz6V2zDZA6Jou+22Crz44q+we/dOTJtWCmBk/NHkyVeFfXsNGP1yr3a77MCBtzFv3uhTbvI8SGvW/AJTplwddt6xEInPQCDFAiQAMBgMqgOkrVYrdDpdxCZwjFU+RER0bhk/Pg8TJ07Cq6+2Y9q0UthsNhw48DZWrvx5RNI/cuQQAPUAyX3yyXNZSg3SBoDy8nKYzWaP5WazGWVlZUmXDxERnXtKSqbjwIG3YbPZ8NprI6+7kq8mhevAgbeRlZWN8ePzIpJeqkq5AMloNAKAS/AiSRIkSfKY3bq0tBQNDQ1e0+rv749IPkRERMGQH+U/cGAfdu16AzfeWBKRdHfv3om+vmNYvHhJRNJLZSl3iw0A2tvb0djYCIvFAq1WC4vFgtbW1oD3r6urAwBs374dAFBZWQmdTofy8nIYDIaI5UNERKQmOzsbkydfhVdfbcd77x2OSEBz5MhhPPXU4xg3brzXd7LRqJQMkJzfp+bLzp3qk3HJ+/pLI9B8iIiIgjVtWikaGp5AVlZ2UAOkrVYrjh3rVX6X38X22muvYPLkq7ByJccYBSIlAyQiIqJkd9ttFThy5FDQT4/t2bMLe/bsclk2btz4c+5ls+FigERERAlp7Ne+jvrPPvW5zUkIXBDDqbk1aRoIp3nVsiI0s/Sf/3xAdbn8DrRAts/Ozvaajj/h7JuqGCDROWPuoiX4n77PIHxMhDHuolysW706hqUiIm8W3l+Ly9yn/XbzN4cD+slXxaQ88gzy7hNdUmpigETnjN5/nMD5Ny2CgPczW9+uDTEsEVFyqVuyCIP+XlaqAS669JuoW/OL2BSKKEoYIBERUUAG+45hxdixvjfSAE+qTKJLlGxSbh4kIiIionDxChIREZ3zjhz8K4ZPn/K7Xeb5X8FEfVEMSkTxxgCJiIjOecOnT/kdEA4A75/0H0RRauAtNiIiIiI3vIJEcbP0wQfR92m/3+346D0REcUaAySKm75P+3F+ySL/2/HReyIiijHeYiMiIiJywwCJiIiIyA1vsRFFAcdXERElNwZIRFHA8VVERMmNARIREVEc2Ww2zJw5zWN5VlY2Jk26HIsXL0V+/iSf+69fvw5vvrkTg4M2jBs3HpMnX4XFi5ciOztbdZ9rr50MAPj+9+/Cj3601Gf5ysunYXDQhhtvLMGqVU/5LTcATJw4CbfdVoHbbqvwWuaSkus9lgda51hggERERAnpqfXNGBw86XObUwI4Pysr7Ly+HBzEeRr/250CcP4Fo/lF8jb55MlXobb2YQDA4OAg+vp68eqr7Zg374dYvHgJfvCDuz32OXLkMKqrF0Or1eK7352Fyy8vwKFDPXjttVdw4MDbWLnyKZ+Bxp49u3wGSPv378PgoC3gcgPAe+8dxv79+9DQ8AR2796JtWufi2idY4UBEhERJaRPbSfxtbJ7fW6TCSDzvPPCzmvMqVPICGC7TABjzzsP4uzvkbxNPm7ceIwfn6f8np8/CdOmlWL16sexfv2zmDz5apdg58iRw5g374eYPPkqrFz5lHK1aNq0UvzHf1Siunox5s37IUym37qkK5s4cRLee+8wjhw57DWI2r17p7JdoOUePz4P06aVYtq0Utx3349xzz0/xJYtL0SkzrHEp9jIxdxFSzDr7ip8754FXv9b+uCD8S4mEdE548EHHwEAvPrqb1yWP/XUKmRlZWPt2uc8bqVlZ2ejqWk9AKCh4QnVdCdNuhzjxo33SNfZa6+9gpKS6SGVe8qUq1Fb+zDee+8wdu/eGdS+3uocSwFfQbr66qujWY6APf/887j88svjXYyU1fuPEzj/pkUQyvcjTxxYTEQUW1lZ2ejrO6b8vn//Prz33mGXW1vusrOzsXjxEqxf/6zqVaKsrGzceGMJXnvtFSUgcSYHNd/9bgXWr382pHLfdtvIvuvXP4tp00qD2te9zrEWcIA0MDCAmpoa6PX6aJbHKyEE7rnnnrjkTUREFC82m00ZfC179dV2ACNjeHyZPPlqAM9i164dqreqSkpm4MUXf4X9+/dhyhTXCyG7dr2BiRMneR3oHaibbirFa6+9ApvNFnBaanWOtaDGIE2dOpVXb4iIEkjdkkUY9PMtO2vceNQ/yyu/yWr9+nUAgNtuu11ZJl9ZURtb5EwOMLyNIcrPn3T2Nlu7S4Bks9mwZ88un1eoAiWX8fDhHo8gzBu1OscaB2kTESWxwb5jWDF2rM9tVsbxNgUFrq/vGI4cOez0+8gTXQcOvI3Fi5e4XAEaHLQhK8v/1Rj5io3VavW6zY03luDFF3/lsuzNN98AANx0U2jjj5zJQZra7bJg6hxrAQdI8+fPh06ni2ZZkqIMRIlm7qIl+J++zyCE93FjAGftJkp0Bw68jXnzfqj8Ls8JtGbNLzyuvMjjc/zdtjp2rBcAoNVqvW5z220VePHFX2H37p3KOKHdu3di8uSrwr69BowGZ2q3y4Kpc6wFHCDV1NREsxxJUwaiRBPIwHqAg+uJEp37RIy+jBs3Hu+9dxh9fcd8XmWRr9r4GsszfnweJk6chFdfbce0aaWw2Wxn51D6eXAV8OLIkUNeyxBMnWONj/kTERElGfnRe3+PwcuDuf09QVZSMh0HDrwNm82G114LbJ9AHTjwNrKysv2Ol0o0DJCIiIiSzLRppZg4cZLydJiaY8d6sWfPLkyefJXf21Xf/e7IK0EOHNiHXbvewI03lkSknLt370Rf3zEsXrwkIunFUsQHaff29qKrqwvd3d3o7u6GzWaDJEke22m1WuTl5aGwsBCFhYUoLi5GXl5yRZdERETx8pOfLMe8eT9EdfViNDWtdxkvdOxYL+6778cAENCTaNnZ2Zg8+Sq8+mo73nvvcEQCmiNHDuOppx7HuHHjvb6TLZFFJEDq7e2FyWRCW1sbrFYrhBDQ6XTQ6XTQ6/W45pproNVqkZubi/7+fmXAVm9vL8xmM0wmEzQaDbRaLYxGI4xGI8aPj9/cB0RERIkuP38S1qz5BVaseAh33PFd5V1s+/fvw5tvjkzyuHnzCwHf2po2rRQNDU8gKys7qAHSVqtVGQwOjL6L7bXXXlFeg5KMwgqQDh06hEceeQSHDh1CcXExqqqqYDAYUFBQEHRakiSho6MDXV1d2LhxI/R6PR5//HFMmhTft/kSERElqilTrsZLL72G9evX4bXXXsGLL/4K48aNx003lWLx4qVBPYV2220VOHLkUNBPj+3Zswt79uxyWTZu3Pi4v2w2XCEFSIODg0pgNHv2bPzyl78M+1FAnU6HqqoqVFVVwWazYevWrViyZAn0ej1WrVqFrAi8rZmIiJLHRdlfweCO/+Nzm1MCOD8Cnw9fDg7iPI3/7U4BOP+C0fzGXZQbdt7Z2dn4858PhLX/gw8+ovq6EG+85ectDbXtwyl3dnY29u49AD+zk8RV0AFST08PqqurMWfOHDQ1NUWjTMjOzlaCJZPJhIqKCqxbt45Xk4iIziE/WbwQl6X5fpbobw4H9H5etxEIy4G3/eYFAO8LAf3kKQn9wU6REVSA1NnZiba2NrS3t0dk8qhAGI1GzJw5E8uWLcOcOXMwY8aMmORLRERE566AH/Pv6urC3r17sXnz5pgFRzKtVostW7bgr3/9K7q6umKaNxEREZ17Ag6Q8vLyUF9fH82y+FVTU8OpAIiIiCjqAg6QEuUdaIlSDiIiIkpdUZlJe3BwMBrJEhEREcVExGfSBoCSkhIUFhZi8+bN0UjeL6vViubmZuTm5gIYmWOppqbG59uMQ9nfebv+/n7YbDYYjUbo9fpIVoeIkkjdkkUYPPuCUK80wEWXfhN1a34Rm0IRUdCiEiANDAyovl4kVubOnYuVK1cqgYokSaioqEB7e3tAQVKg+zc2NnqMy6qsrERNTQ2DJKJz1GDfMawYO9b3RhrgyTieI+NNE8B8Q0ShiGTfSrmX1ZpMJgBwCVB0Oh0KCgrQ3Nwcsf1NJhMMBoPH/jU1NUoaRETkKS0tHQBgtw/HuSSUKuS+JPetSEi5AKmjowOFhYUey4uKitDZ2Rmx/Y8ePQqz2RxeYYmIzkFpaenIzByLL78chMPhiHdxKMk5HA58+eUgMjPHRjRAisottngym82oqanxWK7T6SBJEqxWq8/bbIHuX1RUhOrqamRnZ6O2tlbZrrm5GQsXLoxMZYiIUtQFF2gxMPAZTpz4B84773xkZGRCo3H9zq5JT8Own3smGk0ahobOhF2eQPICAI3QYGjoDGfSDsNIM6djaMgeVjsK4cDQ0BmcOvUlhBDIzs6NUAlHpFSAZLVava6TgyJJkryODwpm//LychgMBmzatAmdnZ2or69HR0cH5syZw/FHRER+ZGRk4qtf/Tq++MKKkye/wBdf2Dy2OX3mSwz4CVpOC4ETJz4JuzyB5AUApwGcOPEJA6QwaDRAenoa7HZH2O2YlpaGzMyxuOACLdLTIxvSpFSANDAwAAA+rxDJ20Ri/9bWVjQ0NGDTpk2orKyE0WhUHZcUCve/U+dOpPY37Gt9oOtc8pfXqyyT0wk1T4/17utU8nROQ9432HZwprbKJd8Q29B5nb829ChTGG3onrav4+a8byT7UjTTdRaJYxPJfcMdFOot33D6d6h5+lsXDrV009PHQKu9EICA3W6HEA6X9euXP4J7MzN9pvvamTN45LmNqmUOpg0DyQsa4Pf2YTzyi42w211vDcajH8arf4eb7pgxacjJOR8DA1+6tGOw6Wo0aUhPT4dGo4nY+cVZ1AIkSZJw++23o7CwEFOnTkVBQUFcZ8H2dXUo1P1NJhNsNhva29vR2NgIk8mE7u5uNDU1hT2hZUaG631Uh0NgeNihug4AzpyxAwDGjEmH+/sWh4cdcDgE0tI0GDPGdaVauhoNIOSP1bM9SwON8kmrSdMgIyPdZ7pCAENDdq/lldc5pyvTCEDIJdBolPzc0x0zJt2js8uXbNPT05CeProyPX20fHK6Hs7WNSPDM92g2zBN4xGNqNb17O/q6QLDw97bUD7mcjrCKXGNEBBudZXbMdQ2BAC7XeDHD9Sg79P+kTq6EY6Ruo6/+KtY/0yjW7oOCCGQnq5xOR4jdfVsQ3kbua+NlDcNaW75BntsnI3+3Xima7c7YLcLaDQaZGQE3r9d2kWj/M95b+WnjIx0l3z9HxvPNhzta2I0abcdncsUzjnCpV87F9qprvLajIx0OBwioHNEZuYYuH8cDQ3ZMfDZZ0g7byxU2/BsttahMzj//K+opqv2t+ytf1tPfI60zEyvbSjna7UP4ytfOQ8Oh2vkGGgbZmYG1w99pzt6jgg23WD6d7DnCLvdAY3G+9/cmDFpGDt2LM4/X7gESIGeIyLZhr5ELUDS6XRYu3YtOjs7sWHDBvT09ECj0aCgoCBqQVNOTg4A9WBGvvIjbxPu/iaTCUePHlUe829tbYXJZEJdXR2qq6vR3t4eRk1GO6fMOQJ2X+dseNju9fzlcIiA0h1Z5vrHLyCgObtInE0n2HTV1junO5rX6L8aIZT83MknBrV07XYHnMd+Op/M5HS9GRqKQBs6hMdXb9W6htGGntu61lH+V66rWjsG04byur5P+3F+ySKfV+GO7drgtT52u4DD4b+u8jFzTmd42BH2sVHjK10h1Puft3SF8wenyt8SAOXzfmjI7nElYrRMvo7NaBuq9TWPvudUpnDOEap5KStH/iec6iYfw3DOEV7b0KlM3o5PMP17pG5eCijTyOk6vF5BilY/jFf/DuUcIf/r77zl3v+DPUeolze4NvQlqrfYdDod5s+fj/nz58Nms2Hbtm3o7OyEyWRCW1ubsl1BQQGmTp2K2bNnhxUwBTLHka8rO8Hs39jYiP3797usMxqNKCwsREVFBSRJCusqkq/L2v4ueYezr7Kdn2V+zsdB5elrtXKOVNkorHbwvWvI9XH5MAky33CPm7dNQj1ufsvkrzwRaMNUSNcfr/FGGOUNNc9w041XnsnUhqnWv8M+b4Vw7GLxGQhEMUByH+uTnZ0No9EIo9EIYORx+m3btuGtt96CxWKBxWKByWTCvn37wsrXYDCoTlJptVqh0+n8BkGB7G+1Wr1eidLr9TAYDGHf0iMiIqL4iUqApNPp/AYI5eXlKC8vBwD09PRg27ZtEcm7vLwcLS0tHsvNZjPKysoisr9Wq8XAwIDXKQMGBgb4JBsREVESi8pEkTNmzIDVasWxY37eR3RWQUEBampqVOcfCpZ8hcp5EkdJkiBJkst8RQBQWlqKhoaGkPZfuXIlqqurPfJvaWnBggULwq4HERERxU9UriDV1taiq6sLdXV1cXlhrfxUmcVigVarhcViQWtra0T3Ly8vh06nQ11dHbKzswGAL6slIiK/AnqhMYCsceNR/+yGGJSI1ERtDNIvf/lLLF26FMuWLcPatWujlY0qrVbr8RJZNTt37gxrf71eH9B2REREsoBeaAxgZQBBFEVP1N7Flp2djdbWVuj1eixbtixa2RARERFFXNRn0q6qqop2FkREREQRFbUrSERERETJigESERERkRsGSERERERuGCARERERuWGAREREROQm6k+xERGFau6iJfifvs8g/LxhctxFuVi3enWMSkVE5wIGSESUsHr/cQLn37QIAr4DpL5dnG2YiCKLt9iIiIiI3CTEFaTBwUGYTCYcPHgQAKDT6VBUVASDwYCsrKw4l46IiIjONXEPkGw2G0pLS2G1WmEwGLB582bYbDZ0d3dj9erV0Gg0qKqqQl5eXryLSkREROeIuAdI3d3dGBgYUH4GRt7jVlxcjOLiYkiShLq6OsyZMwczZsyIZ1GJiIjoHBH3MUjFxcWYMWMGtFqt6nvbdDodtmzZ4vcpFiIiIqJIifsVJABYt26d323KyspiUBIiIiKiBLiCRERERJRoGCARERERuUmIW2xERIlg6YMPou/Tfp/bcNZuonNDVAKk3t5e5ObmBjWHUVtbGzZt2oQdO3ZEo0hERH71fdqP80sW+d6Gs3YTnROicott+vTp2LhxY1D7WK1WSJIUjeIQERERBSUqAVJ2drYyt1Ggjh49Go2iEBEREQUtaoO0e3t7A9720UcfRVtbW7SKQkRERBSUqAVIZrMZL730kt/t5s2bx+CIiIiIEkrUAiQhBOrq6rBlyxbV9b29vZgxYwbMZnO0ikBEREQUkqg8xWa1WlFeXo7x48dj9erVOHr0KH72s58p6w8dOoS5c+diYGAAGo0GQghotVrYbLZoFIeIiIgoKFEJkOrr61FYWIiCggJMmDABjz76KAYGBrBmzRp0dnZi2bJlAKAERzU1NRBC4Omnn45GcYiIiIiCEpUAafbs2crPRqMROTk5WLZsGSwWCyRJcnnxbFNTk/KeNbWX1RIRERHFWkxeNVJeXg6DwYCjR48qwZFWq0V7eztfQktEREQJJ+qvGhkcHMTdd9+Nnp4e5ZaaRqNBU1MTCgoKop09ERERUdCicgVp3rx5eOONN9Db24uSkhL09PRACAEhBAwGA/Ly8rBs2TIcPnw4GtkTERERhSUqAdLevXuxdetWTJ8+3WVG7fnz52PLli34zW9+g/Hjx2PWrFl46623AIxcaTp06FA0ikNEREQUlKgESFqtFmazWRlvJIRAfX09ampqlPXt7e245pprUFlZiTfeeAOrV69GRUVFNIpDREREFJSoj0HSarVoampCcXGxx7rW1lYsXboUS5cujXYxiIgSivnDjzDr7iqXp3rVjLsoF+tWr45RqYhIFrUASQgBnU6HLVu2QKfTed1u3bp1qKurQ1tbGzQaTbSKQ0SUUE6mZeL8mxZBwHeA1LdrQ4xKRETOovaYv16vR3t7u8/gSFZfX88n2oiIiChhRC1Auvnmm5GdnR3w9gaDIVpFISIiIgpKVAIkq9UajWSJiIiIYiIqY5ACvbXm7Oabb8aECRMikr/VakVzczNyc3MBAJIkoaamBlqtNir7NzQ0IDc3F/39/QCAhQsXBpwXERERJZ6oBEihjCcqKCiI2DikuXPnYuXKldDr9QBGApyKigq0t7cHFLgEur8kSairq0NNTY2ybUNDA5YvX45169ZFpC5EREQUewHfYkuUSRz9lcNkMgGAErAAgE6nQ0FBAZqbm/2mH8z+1dXVMBqNLtv29PQoV56IiIgoOQUcIGVlZWHZsmVRLIp/jz76qN9tOjo6UFhY6LG8qKgInZ2dEdu/o6MDkiShvLzcZbvW1lbU19f7zYeIiIgSV8ABkk6nQ1VVFW6//faYv0Ott7cXt99+O8rLy3H55Zf73NZsNquOf9LpdJAkye8A8kD3N5lMqoEUERERJb+gxiDp9XqsXbsW1dXVmDp1KhYuXIisrKxolQ2Dg4PYsGEDduzYgc2bN/sd+O0r+JHHDkmS5HJLLNT9u7u7MXPmTJjNZlgsFmWd+y03IiIiSj5BD9LW6XRob29HQ0MDbrrpJsycORMLFizA+PHjI1ao3t5ebNy4EZ2dnZg9ezZ27NgR0H7yi3F9DcR2fnluOPtbrVblilJVVZWyrKSkBM8//3zYQZL7pOLObyNQm3Dc1/pA17nkL69XWSanE2qeHuvd16nk6ZyGvG+w7eBMbZVLviG2ofM6f23oUaYw2tA9bV/HzXnfsPqS564Rb0M1PvtLBP5uAjluzv0/3BcAeKuPr+MWbr6ROEdEM89g8/WWdjjniFDzDHZdtPIMt0wROUcEct5SObeHm26k2j/kp9hqa2uxcOFCNDY2oqSkBBMmTEBxcTGmTp2KgoIC5OXlBZxWb28venp6sHfvXnR1dUGSJJSVleHll18OeroAb8Kdm8l5f0mSlH+dxyBptVrMnDkT1dXV2LlzZ1j5ZWSku/zucAgMDztU1wHAmTN2AMCYMelIc7txOjzsgMMhkJamwZgxrivV0tVoAAHXM7IGGuWMrUnTICMj3We6QgBDQ3av5ZXXOacr0whAyCXQaJT83NMdMybdo7MPDdkhBJCenob09NGV6emj5ZPT9XC2rhkZnukG3YZpGo9PNdW6nv1dPV1geNh7G8rHXE5HOCWuESMvsHCuq9yOobYhANjtcl3gsw2dj9loug4IIZCernE5HiN19WxDeRuXYES1v4ysDPTYOBv9u0lDWprG5biptaFctzFj0r32b02ae5TsPaRzP24jq10/mZzbUq0NR8ssnKIr1zSdyxTOOcKlX3uUd+R/8tqMjHQ4HCLsc4TXNpSzdetrofbvkbrBaxsq+WK0vzgL5hzh0Y5ubehcprQ0jY90AztHqJXXbnfAbhfQaDTIyPB+bEI5R9jtDmg0/s9bGRnpLuUK9hwRaF19HRtfwnrMX6vVor6+HvX19TCZTMp/8jvVdDodsrOzkZubi+zsbOTk5GBgYAA2mw39/f2w2WxKsCGEQEFBAebPn4+ZM2cGNQu3LCcnB4B6MCRf+ZG3CWd/eTu1aQmcxyqFMxeScnI4yzkCdl/nbHjY7vX85XCIgNIdWeYa5gsIaM4uEmfTCTZdtfXO6Y7mNfqvRgglP3fyiUEtXbvdAYdjdLnDMZqJnK43Q0MRaEOH8PiqpFrXMNrQc1vXOsr/ynVVa8dg2tB5nb82VMtrNF0Bh8N/XeVj5rzOV38Jpw2Hh0dO6M7HTa0N5bo5t5tHng6XAgNQaSeX2NlLO6ocN7U2VOtrHn3PqUzhnCNU81JWjvxPnE17aMiuHMNwzhFe29CpTN6ObTD9e6RuXgoo08jpOmC3u/5xBPO37LUd3f+OzwaYgabrjdy/1fYVwnv7jewb4jlC+D9vDQ3ZXdox2HOEenm911WtDX2J2DxIRqMRRqMRwMhA556eHhw9ehS9vb04evQoANcgQ6fTIS8vD7Nnz4Zer0dxcXHYZQgkIPF1RSrQ/X1tF8hYp0D4urzs79JzOPsq2/lZ5ud8HFSevlYr50i1c0k47eB715Dr4/phHly+4R43b5uEetz8lslfeSLQhsHmG4m/m0COm8txDvBvymu+ASwPpf87e6v3OL53zwK/2427KBfrVq8OPOEgROK8FOz+4fTvUPMMZ1208gxn32h/3oRy7GLxGQhEaaJIg8EQt3erGQwG5aqUM6vV6je4CWZ/vV4Pm82muh3gOxAjIoql0+mZOL9kkd/t+nZtiEFpiJJD1F5WGy/l5eUwm80ey81mM8rKyiK2v9FoRHd3t8d2Bw8ehF6v56tGiIiIkljKBUjOt/lkkiRBkiTU1ta6bFtaWoqGhoaQ9jcajdDpdMrM2wBgsVjQ1dWFlStXRq5CREREFHNRucUWb+3t7WhsbITFYoFWq4XFYkFra2vE95enO6irq3NZxttrREREyS3mAZL8SP/AwABycnKCnhIgEPLTdf54exQ/0P0BeFyVIiIiouQXswCpq6sLy5YtU32EfsKECaipqcH06dNjVRwiIiIir2ISIG3atAmNjY0oKChAWVkZJkyYgP7+fkiShK6uLnz44YdYunQp9Ho9Vq1ahUmTJin7Dg4ORvV1JkSU+uqWLMJg3zG/23342Ze4vCQGBSKihBf1AEmSJJhMJrS2tnqd66inpwdbt25FW1sbZs2ahdbWVlxzzTUAgBMnTmDDhg2w2WyYM2eO35fVEhG5G+w7hhVjx/rdrvTMiRiUhoiSQdSfYtu0aROampp8TgRZUFCA+vp67N+/H3fccQcqKyvx1ltvARiZT6impgbz58/H0qVL8bOf/SzaRSYiIqJzXNQDJPkVIoHIzs5GfX091qxZg+rqagwODirrdDodHnvsMWzdupVBEhEREUVV1AOkUCZMLC8vx2OPPYbly5e7LM/NzQUAbN++PRJFIyIiIlIV9TFIGtU3IvtXXl6O7du346WXXkJOTg4OHjyItrY2AIj4tABEREREzqIeIMkvqA1GZ2cnent7UVRUhF//+tcwGAywWq3KE3DybNdERERE0RD1AGnq1Kl46aWXcMcddwS8T29vL+bNm6f8Pn/+/GgUjYiIosD84UeYdXcVhI9Xp4+7KBfrVq+OYamIghP1AKmsrAzTp0+HwWDA+PHjA9rnxInRR21DvUVHRETxcTItE+fftAgC3gOkvl0bYlgiouDF5GW1DzzwACorK12eSvPl5ptvxubNm9HV1YWDBw9GuXRERERErmISIJWXl+Oaa65BSUmJMr+RLwUFBZg9e3YMSkZERETkKWbvYquvr4ckSaisrITBYEBtba3LK0XcZWdnY9OmTSgvL49VEYkSjt9XZGiADz4/iUnXx65MRETngpgFSADQ2tqKhoYGbN68GWazGTqdDmVlZSgqKkJBQQFyc3MhSRLMZjNMJhN0Ol1Qg7uJUo3fV2RogNLT/TErDxHRuSKmARIA1NbW4uabb8aKFSvQ09ODTZs2eWwjhEBZWRlWrVoV6+IRUYzw6hgRJbKYB0gAoNfr0d7ejp6eHmzbtg09PT2QJAk6nQ4FBQWYOnWqz3e3EVHy49Uxotjw+2UEQNa48ah/lk8WOgs6QDp06BAuv/zyiGReUFAQ8HvaiIiIKHh+v4wAWOkngDoXBfUUW1tbGyoqKrBly5ZolYeIiIgo7oK6grR3714A8Dk7qrPe3l5IkoTe3l7k5ORAp9NBp9MhKysr+JISERERxUhQAVJPTw+0Wq3fd6Ht2LEDzc3N6OnpUV0vv09t9uzZDJaIiIgo4QR1i02SJCxYsMBrUDM4OIjbb78d1dXV6OnpgRBC+S8vLw95eXkQQuDDDz/E6tWrMWXKFPzsZz+LRD2IiIiIIiboQdplZWWqy7u6urBs2TJYrVblFtzs2bMxZ84cj4HYNpsN27ZtQ0dHB7Zu3Yquri5s2bIl4He1EREREUVTUAGSPJmju0cffRRtbW1KYGQ0GlFTU4Ps7GzVdLKzs2E0GmE0GmG1WrF8+XJUVlaivb2dt9yI4iSQR4EB4MPPvsTlJTEoEBFRHAUVIC1cuBAmkwnz5s0DMDLWaMWKFRgYGIBWq8WCBQug1WohSZLX4MidVqvFunXr0NLSgubmZjzwwAPB14KIwhbIo8AAUHrmRAxKQ0QUX0EFSGVlZdi0aRMqKiqUAdgGgwHl5eUuL5edPn065syZE9Qts6qqKiXwIiIiIoqnoMcgzZ8/H/Pnz/e7DW+ZERERUbIK6im2QBmNRkyaNAklJSV46623At4v0PmViIiIiKIpau9iW7duHSorK1FZWQm9Xg+j0YiZM2d6vaK0bNkyTJ06NVrFIYoIDmQmIjo3RPVlta2trairq0NbWxssFgvq6upQUFAAg8GACRMmAAC6u7vR1dUFAFi7dm00i0MUNg5kJkosb/Uex/fuWeB3u3EX5WLd6tUxKBGliqgGSABQX1+Pqqoq1NXVoaurCxaLBRaLBRqNRrmlVlZWhlWrVkW7KERElGJOp2fi/JJFfrfr28U31VNwoh4gAYBOp0NrayskSUJXVxeOHj0Kq9WKwsJCFBYWekwkSRSMgG57aYAPPj+JSdfHpkxERJTcYhIgyeSX1RJFUkC3vTRA6en+mJSHiIiSX8BPsQ0ODkazHElTBiIiIkp9AQdIU6ZMwaFDh6JZlqQoAxEREaW+gAOkRJijKBHKQERERKkvqIkiNRpNtMpBRERElDCCGqR99913IycnJ1pl8YsBGhEREcVCwAFSU1NTNMsRsECegrNarWhubkZubi4AQJIk1NTUQKvVBpRHqPt3dHRAkiRUVVUFlA8RERElpoADpLKysmiWI6Lmzp2LlStXQq/XAxgJcCoqKtDe3h5QkBTK/larFStWrMCCBf5ndCUiIqLEFtN5kGLBZDIBgBLcACNXnQoKCtDc3Iza2tqo7C/vRyMCmbyR7ysjIqJEFdQg7WTQ0dGBwsJCj+VFRUXo7OyMyv5msxkGgyH4wqYwefJGX/85zpyOdzGJiIhUpVyAZDabVccp6XQ6SJIEq9Ua8f0tFovLFSciIiJKbjEJkGI1A7av4EceOyRJUkT3b2lpicqgbI3G9T9f6/ytD3Sdy3Zn//O2LNR0feXlLU/39N3zDIV7nh75hlEf9zx85RvJPH21oXs7quUZTn7B1iecB1LjfdzkfCKVp7f6+Dpu3paFm6dzuuGkH26ekTqH+Dpu7vkGK5xzcKjC+VwINv1A0w23TNFIN1LtH/UxSG1tbXj00UdRXl6ONWvWRDWvgYEBAPA5EFveJhL7R/PKUUZGusvvDofA8LBDdR0AnDljBwCMGZOONLewd3jYAYdDIC1NgzFjXFeqpavRAEI+pZydnFMDjXKW0aRpkJGR7jNdlykZ1HqkSrrK5gIQcgk0GiU/ebehodG6ajQj5VHykCcT1Sj/g+tPUNL1VqaMjHSP1XJd1esjAHkOU2WdZ5lU63r2d/Vjo7KhSnnl1cK5vkJAwLWucjuqtaG8fiQh9TZU6gr/beh8zGRDQw4IIZCerkF6eprrcVNpQ+cPtdEiqfWXkZX++rfPNlTqOlomtTaU6zZmTLrShu711KQ5933nmiiZjq52O26uZXI9boBnGyr5aTRQ74cuBTn7k3obirO7+Tr3uB4z9/IqqY8W4WyR1PqLczupndPk9vXahkoz+iqT63HLyBg5bkIA6elpSE93XY+zZXbf1yVfAGPGpCEtzXV9MOdZj3b0dt5K0yAtTeMjXWB4WL0fAqOfCyNd2/d5y9951pm3NgQAu13Abneo9iWXMp0ts3M7qvXv0boG+hkY3LHxJeoBktVqxf3334/u7m6X5YcOHcLll18e7exdyhHp/bdt2+Z30HeolJPDWc6TiLuvczY8bPd6rnA4REDpjixznbVcQEBzdpE4m47vdIXzL17L65zu6LLRfzVCKPm5k08MwiE883Crg9C4rtL4KNPQkPc29PzFjXAqvfDehu6b+zs2PvOE5zFzb0MAqu0ot6G83iUflX7gvMpXG6rlJW9utws4HHb14+a0oXzMXIvkvb+E1YZKXUfLpNaGct2c280jT0cAbehSNy/lUjlu7m2o5OfR/93TdO4bPv7mhO9zj9djpiQiXI6btzZU0jpL7e/b+U/JaxvJG3gtk+txcz5v2e0Oly8hI3VT31dxtm7Dww7Y7Q6XVcGcZ733feV/SpnkL2aBnr9VCS/1cUrI33lWLV/3NnRep9aX3A0N2V3aUa1/u6+T9/NmeNgR1GegL1EPkA4ePKg6h1JjYyM2b94c0bzkSSzVghn5yo+viS6D2d9kMmHhwoXhFdiHgD6Do7Cvsp2fZX7Px0Hwc+rzmn608gw3bV95+KxrmHl62z0ex81f2lHrLzE6bgHG/yHn5748lv0/Wm90inffV8snrDYMsX/HI89w0o/2500AsW3MyySLeoA0c+ZMzJgxA8XFxSgsLITBYMD48eOjklcgcxz5mmgy0P0lSUJOTk7AE08SERFRcol6gFReXg6dToenn34aJpMJGo1GCSyeeeYZFBYWQqfTRex2m8FgUB2IbbVaodPp/AY1gezf3d0Ns9kMs9nssc327dshSRIMBgPKy8vDqwwRERHFRUwmitTr9diyZQtsNhv27t0Ls9mMtrY2bNy4EcDogF55QsaioiLl36ysrKDyKi8vR0tLi8dys9kc0GzggexvMBhU5z0ymUyYOXMmXzVCRESU5GI6k3Z2djbKy8tRXl6O3t5ebNmyBZIkoaenBwcPHoQkSbBYLOjo6AAA5WpTcXEx5syZg2uuucZvHkajES0tLS6TN0qSBEmS0Nra6rJtaWkpysrKXAZaB7O/mv7+/kCbg4iIiBJU3F41kpeXB2DkqpFOp/O4utPT04Pu7m7lv7lz5yInJwdNTU1+A6X29nY0NjbCYrFAq9XCYrEEFNyEun9dXZ1yW66trQ02mw3l5eWcXZuIiChJxS1Aqq+v97m+oKAABQUFmD17trLMYrHAZDLBYrFg3rx5XvfVarV+0weAnTt3hrW/LJhtiYiIKPEl1atGLrnkEtTW1vI2FhEREUVV3K4ghWLWrFnQaDQwGo3xLgoRERGlsKQKkB544AG0tbVxbE8I6pYswmDfMd8baYAPPj+JSdfHpkxERESJKqkCJPkJOAreYN8xrBg71vdGGqD0dH9MykNERJTIkipAIiIiiifzhx9h1t1Vru+bdDPuolysW706hqWiaGCAREREFKCTaZk4/6ZFED7eLte3a0MMS0TRktAB0o4dO3Dw4EHk5uZCq9WisLAwYq8kISIiIvImYQOknp4eLF26FDk5Odi3bx8AoKurC08//TSMRqMy0SQRERFRpCVsgCRPFOn8xFpxcTGKi4vR2dnJAImIiIiiJmEDJGDklR9qAnnpLBEREVGokmombSIiIqJYiFuA1NvbG6+siYiIiHyKW4A0ffp0dHV1xSt7IiIiIq/iFiD5mmSLiIiIKJ44BomIiIjITVyfYuvo6AAA6HQ6l8f2Dx06hO7ubuzduxc6nQ4PPPBAvIpIRERE56C4BkiFhYWwWq3YunUrenp60N3dDZvN5nL7zWg0xrGEREREdC6Ka4CUl5eH4uJij3mNbDYbACA7OzsexSIiIqJzXFwDJG+P+jMwIiIioniKa4DU3d2NgwcPwmq1oqioCAaDgS+jJSIioriLa4A0depUzJgxAwDQ2dmJDRs24K233kJhYaGyju9cIyIioliL22P+Op0OAwMDyu9lZWVoamrCzp07cc0112DDhg2YPn06li1bFq8iEhER0TkqbleQHnvsMfzsZz/DHXfc4bI8OzsbVVVVqKqqQkdHB19JQkRElCTqlizCYN8x3xtpgIsu/Sbq1vwiNoUKUdwCJIPBgDVr1mDevHl47LHHVG+llZeXx6FkREREFIrBvmNYMXas7400wJOSFJsChSGuM2nr9Xps3ryZrx0hIiKihJIQrxrR6XTxLgIRERGRIua32Gw2G6ZMmYKcnBzk5eWhsLAQhYWFyMvLQ1FREbKysmJdJCIiIiIXQQdIL730EqxWq8fygoICFBcX+90/Ozsbb7zxBrZu3YrNmzejp6cHBw8eRE9PD3JycrBv375gi0RERJRy3uo9ju/ds8DvduMuysW61atjUKJzS9AB0ooVK1BQUABg5KWyQghotVosXLgwoAAJGLmlVltbi5tvvhmVlZX4zne+g5UrV+J73/tesMUhIiJKSafTM3F+ySK/2/Xt2hCD0px7QhqD9PjjjyM3NxfZ2dlob2/H22+/jXnz5gWdjl6vx9q1a9HY2Iienp5QikJEREQUcSGNQVq+fDlsNht27doV9nvTDAYDpk+fjsbGxrDSISIiIoqUkK4g9fT04LHHHovYS2UXLVrkMqs2ERERUTyFdAVJp9O5jDfq6uqCyWQKaN+cnBw89thjLssKCgpQUFCAQ4cOhVIcIiIioogK6QpSWVmZy+85OTnQarWwWq3o6OhAZ2cnACAvLw9CCHR0dKCjowNCCK9zHs2cOTOUohARERFFXEhXkCZMmODye0FBAerr6wEAVqsVc+fORU9PD1atWoVZs2bBYDCgqanJ5y059zSJiIiI4iWkK0hq702TabVatLe3QwiBiooKWK1WbNmyxe94Jc6mTURERIkipCtIubm5freZPXs2nn76aRiNxlCyCIvVakVzc7NSTkmSUFNTA61WG9H9JUnC1q1bYbPZIEkSsrOzUVtby2CPiIgoyUXtVSPl5eV4+umnMXXq1Ghl4dXcuXOxcuVK6PV6ACOBTEVFBdrb2wMKkgLZX5IktLS0KLcWAaChoQGlpaXYuXMngyQiIqIkFtIttu3bt/vdJjc3FxqNJuCxRdu2bQulKB7kp+nk4AYYuX1XUFCA5ubmiO3f0tKCmpoal31ra2uh1WpRXV0dVh2IiIgovkK6grRx40a0tLQAgNcrMlarFUIIzJo1y+dVG/m9bkIIaDSaUIrjoqOjA4WFhR7Li4qKYDKZUFtbG5H9t2/fjv7+fqxbt85lu+LiYuUpPiIiIkpOIQVIr7zyCoQQEZvcMS8vD1arNSLvYjObzR5XdoCRq0CSJMFqtfoM2ALdXy2IIiIiotQQ8hgk+YW1kRKJd7HJV6PUOI8dcr59Fur+ra2tqtv19PRw/BEREVGSi9og7XiQr2j5ukLk66pXuPubzWZIkuQ1eAqG+91GIbyv87feeV3A+cv7qiyT8/BXpmDzkqnl6Zy+nG8k8/TINwZt6LF9mHk67+7ruDmnHa82jFp/idFxc+7/4Y4M8FYfX8ct3Hyj3YaB5Omyzs85Ldi01dpQzicWbeiedjyOm3u+AaUf4Hk2UvXxlqdaupH6DAymvCEFSM3NzbDZbKHs6lWk3uvmja+rQ5Hav66uDvPnz4fBYAgrLwDIyEh3+d3hEBgedqiuA4AzZ+wAgDFj0pHmNvRe3g+ASu8Qyl+Z5uyfn0YDCLiekTXQKH+dmjQNMjLSMTzsgMMhkJamwZgxrpm6jCfz0Zud01U2F4CQS6DRKPnJuw0NjdZVoxkpj+cnv/I/uP4EJV1vZcrISPdYLddVvT7C6YyshHQeZVKt69nf1drQ4VDZUKW88mrhXF8hIOBaV7kd1dpQXu/6ya/8z7Wu8N+GzsdMNjTkgBAC6ekapKenuR43lTZ0Do6Fcx/16C8jK9XbcPTvxmcbKnUdLZNaG8p1GzMmXWlD93pq0pz7vnNNlExHV7sdN9cyuR43wLMNlfw0Gqj3Q5eCnP1JvQ3F2d18nXtcj5l7eZXUR4twtkhq/cW5ndTOaXL7em1DpRl9lcn1uGVkjBw3IYD09DSkp7uux9kyu+/rki/Uj5tzf3Hv/+7nb4929Po3p1GKpNqGZ8+Vcrru5M+FkUL5Pm/5O88689aGo3UYTdeD03krIyMdaU79QK1/ywL/DExzSROAz88qX0IKkHp6ejBjxoyA5kMKRH9/f0QGNufk5ABQD2bkKz/yNpHef+nSpTAYDH4HgQdKOTmc5RwBu69zNjxs9/0N0MdXCvkPbWQT4bFOc3aRcAjlDwQY6bie5RXOv/jMUyPcl43+qxFCyc/d8LBdKY9HHm51EBrXVRofZRoaCr0NR9d5lkm1rj7bMMA84XnM3NsQgGo7ym0or3fJR6UfOK/y1YZqecmb2+0CDodd/bg5bSgfM9ciee8vYbWhUtfRMqm1oVw353bzyNMRQBu61M1LuVSOm3sbKvl59H/3NJ37ho+/OeH73OP1mCmJCJfj5q0NlbTOUvv7dv5T8tpG8gZey+R63JzPW3a7w+VLyEjd1PdV+DhuzsV17//u52/vfd89XeG7DZ1+9vW5MFIo3+ctf+dZt80BeLahR6H8nLeGhuyw20cTUOvfakn5/gx0eD1/q50jfAkpQKqpqcGMGTNC2dUrg8GAefPmhZVGIHMc+RofFOr+LS0t0Ol0EQuOgAA/g0NcH1D+fpb5PR+HmZf7Oh+foxHPM9y0feXhs65h5ult93gcN39pR62/xOi4BRj/h5yf+/JY9v9I3VKLZZ6BtKFaPvHo/4l83ELpZ2EfuxDaKZwyBVPekOZBisYg5NzcXNerDiEyGAyQJMljudVqhU6n8xsEBbt/R0cHALgERxaLJZSiExERUYIIOkBqamrC5ZdfHvGCFBQUoKmpKex0ysvLYTabPZabzWaUlZVFdH+LxQJJklBVVeWxLRERESWvoAOkQIKMUEUibfndb85BiiRJkCTJ4xZYaWkpGhoaQtpfkiSsWLECwMgtNvm/hoYGBkhERERJLqUe85e1t7ejsbERFosFWq0WFoslqEfvA9m/srISkiSp3k6LZhBJRERE0ZeSAZJWq3V5iaw3O3fuDHl/b/sSERGRb+YPP8Ksu6t8jj0ed1Eu1q1eHcNSuUrJAImIiIgS18m0TJx/0yKniQw89e3aEMMSeQrpKTYiIiKiVMYAiYiIiMgNAyQiIiIiNwyQiIiIiNwwQCIiIiJywwCJiIiIyA0f8yciIjrHvdV7HN+7Z4Hf7eI9N1EsMUAiIiI6x51Oz8T5JYv8bhfvuYliibfYiIiIiNwwQCIiIiJywwCJiIiIyA0DJCIiIiI3DJCIiIiI3DBAIiIiInLDAImIiIjIDQMkIiIiIjcMkIiIiIjcMEAiIiIicsMAiYiIiMgNAyQiIiIiNwyQiIiIiNwwQCIiIiJywwCJiIiIyA0DJCIiIiI3DJCIiIiI3DBAIiIiInLDAImIiIjIDQMkIiIiIjcMkIiIiIjcMEAiIiIicsMAiYiIiMgNAyQiIiIiNwyQiIiIiNwwQCIiIiJywwCJiIiIyA0DJCIiIiI3Y+JdgGiwWq1obm5Gbm4uAECSJNTU1ECr1UZ0/3DzISIiosSUkgHS3LlzsXLlSuj1egAjgUtFRQXa29sDCl4C3T/cfIiIiCgxpdwtNpPJBABK0AIAOp0OBQUFaG5ujtj+4eZDREREiSvlAqSOjg4UFhZ6LC8qKkJnZ2fE9g83HyIiIkpcKRcgmc1m6HQ6j+U6nQ6SJMFqtUZk/3DzISIiosSVUgGSr6BEHhMkSVLY+4ebDxERESU2jRBCxLsQkSJJEkpLS1FfXw+j0eiyzmw2o7KyEq2trTAYDGHtr9PpwsrHHyEEHI7IHpbPjn+MXI3G73YfD9uRof2az23ESSv+6etfDzu/QPIKJL9Y1i2SeUUqv2Rsx0DzS8a6sY+wj7CPxK6PhCI9PbBrQyn5FJuacG95Bbp/JG6taTQapKf772DBuHjcuIC2mxDIRjlfiUh+AeUVQH6xrFtE84pQfsnYjoHml4x1Yx9hH2Ef8S9SfSSaUuoWW05ODgD1IGVgYMBlm3D2DzcfIiIiSmwpFSAFMveQ2sDqYPcPNx8iIiJKbCkVIAGAwWBQHSBttVoDCm4C3T/cfIiIiChxpVyAVF5eDrPZ7LHcbDajrKwsYvuHmw8RERElrpQLkOSnypyDF0mSIEkSamtrXbYtLS1FQ0NDSPsHkw8REREll5R8iq29vR2NjY2wWCzQarWwWCxobW2N+P7h5kNERESJKaXmQSIiIiKKhJS7xUZEREQULgZIRERERG4YIBERERG5YYBERERE5IYBEhEREZEbBkhECYQPlVIiYX+kcxkDpBQkn9R4cksu//jHP/Daa6/FuxhRwT6ZfNgf6VyXkhNFnus0Go3Lv6lieHgYVqsVF154IRwOB9LSUie+P3bsGMrKyjA8PIxvf/vbyMvLi3eRIop9MrmwP1KgUqnfu0vNWp2jPvroIyxZsgTTpk3DHXfcgaamJnz22WfxLlZEHD9+HPfccw9KSkpQXl6Op59+GoODg/EuVkTIH0b//u//jksuuQQff/wxgNT4dss+mXzYH8mf06dP49NPP8WxY8cwPDwc7+JEDQOkFPHxxx9j+vTpyMrKwp133ons7Gz87ne/w/e+9z385S9/iXfxwtLX14dbbrkF48ePx+LFi3HhhRdi8+bN2LFjR7yLFjb5w+j222/HvffeizFjxqCrqwtA8n+7ZZ9MPuyP5E9vby9uueUWfOc730FJSQnmzJmDDRs2xLtY0SEo6dntdnHPPfeIZcuWiYGBAWX5n//8Z/H9739ffOtb3xKvvPKKGB4ejmMpQ3Pq1Clx6623iubmZnHy5Ell+dSpU8X9998fx5KFr7e3V+j1evHoo4+K//mf/xFCCPHTn/5UPPjgg0IIIRwORzyLFxb2yeTD/pic/TGWPv30U1FUVCTWrl0r3nnnHfGnP/1J3H///eKKK64QS5YsEZ988km8ixhRvIKUAtLS0tDb24srr7wSWq1WueQ5depU/OxnP8PUqVPx6KOPJuWAy4GBAZw6dQrXXXcdzjvvPJw5cwYAcMUVV+Af//gHAODMmTNJd/m/t7cXZWVlmD17NqqqqnDJJZcAAL71rW+hs7MTH374YVJ/Y2efTK4+yf6YvP0xll588UX8y7/8C+644w5ceeWVuPbaa/HII4/g4YcfxltvvYXq6mp88MEH8S5mxDBAShGnTp3CsWPHAABjxoyBw+EAAFx22WVYvnw5brjhBqxcuRIHDhyIZzGD9uWXXyIjIwNf+9rXAACZmZn48ssv8dlnn+Hvf/87GhsbUVFRgXvuuQfvvvtunEsbuDfeeAO33XYb7rnnHowfPx4AYLfbcfnll0MIoZxk7HZ7PIsZFvbJ5OmTO3bsYH9M0v4YC3Kw/7e//Q3jxo3DuHHj4HA44HA4cOGFF+LWW2/FU089hQ8//BDLly9XvigkOwZISUrusPK311tvvRV/+MMfsH//fgAj35jkE8A//dM/obq6GhMnTsQDDzyATz/9ND6FDoFGo8EVV1yB3NxcZdnevXvx7rvvKifviy++GP/5n/+JRYsWKfVPVPJxu+uuu/CTn/zE5emg9PR0FBYW4rLLLsOmTZuUZcl0JQIAhoaGAKRWn5T/zoDU6pPylZR77rkHDz30UEr2R7mOqdQfY02+enjZZZdh//79OHbsGNLS0pTl5513Hm644QY8/vjj+Pvf/476+vp4Fjdy4nRrjyLs7bffFldeeaW49957xfvvv68st9vtys87duwQ1113nXjiiSdclica97EOQ0NDQoiRuthsNrFs2TLx0EMPuWzT0dEhrr32WnHttdeKL774ImZlDZfzmAf559bWVpGfny+2bt0ar2IF7cSJE6Knp8dl2TvvvJMSffLo0aNi0aJF4sMPP1SWpUKf7OvrEz//+c/F3//+d9X1ydwf7Xa7MtZIPp/s27cvJfpjPJw+fVoIIYTZbBYzZswQjY2NwmazCSFcz9enTp0SL7zwgigoKBDPPvtsXMoaSbyClGSOHz+Ohx9+GDNnzsS9996L559/HkNDQ5gyZQpqamrwxhtv4P/+3/+Ljz76CMDItyT5snhJSQkKCwvxhz/8ISHnrbBarQBGvq0Ip2+pY8aMTNeVlpaGrKws/PjHP8aTTz4JYPSb/fTp01FWVoZPPvkkIR/b/fzzz7Fq1SrMmDED8+bNwxNPPIHh4WGkp6cr32LT09MBAGVlZcjNzcXvf/97fP755wAS+xHrzz77DNdeey02btyIw4cPK8uvvPJK/OQnP8Ebb7yBF154ISn7ZG9vL2bOnImioiJcfPHFyvJk75PHjh3D9OnTccEFF+D8889X3SZZ++PHH3+MJUuWYMaMGbjjjjuwaNEinDlzBldddZVyjkzW/hhLZ86cweDgIL788kulvxcXF2PSpElobW3Ftm3bcOrUKZfz9dixY1FaWoqSkhJs27YNn3zySUL3FX/O7R6QZD766COUlJTg5MmTuP766/Hhhx9iy5YtmD17NiRJwp133okHHngAW7duRUtLC/77v/8bwMiJ7syZM0hLS8NNN90ESZIwODiYUB13aGgId9xxB2prawF4BknA6En5X/7lXwCMTFCWmZmpTFRmMBgAABkZGTEsuX+9vb24+eab8ac//Qnf+MY3cOzYMfzqV7/CrFmzcOLECZdL/Q6HA9/4xjfw0EMP4Z133sHvfvc7AOrtkSg6OjowPDyMP/zhD2hpacF7772nrJs9ezbuu+8+/PrXv8amTZuSqk/29vaivLwcS5cuRWVlJc477zyPbZKxTw4ODmLx4sVYvnw5Fi5ciH/+53/22CZZ+2NfXx9uvfVWfPOb38RDDz2E6dOno6enB4sWLYLD4cCdd96ZtP0xlnp7e3H77bfjpptuwpVXXol77rkHL730EgCgqakJV1xxBdauXYs9e/bg9OnT0Gg0cDgcEELgn/7pn3DXXXfhgw8+wLFjx5J6cD9n0k4SQ0NDuP/++3HLLbfgkUceQXZ2Nk6ePIk9e/Zg3bp1+MEPfoBVq1ahsrISQgg888wz6Ovrw1133QWDwYDMzEwAwN///ncUFRUhKysrzjVyJU849rvf/Q4OhwNPP/20chL2Nuut/HtaWhrOnDmD//qv/8Jll12GCy+8MObl9+bLL79EZWUlZs+ejYqKCnzzm9+EzWbDCy+8gP/zf/4Pamtr0dLSonxblf+9+uqrMW3aNDz55JP42te+hltuuSVhTzTf/e538ac//Qm5ubn47W9/i+HhYfz4xz/GxIkTAQALFiyA3W7HunXrcOzYsaTok3JQu3TpUvzgBz/AV77yFdXtNBoN7Ha7crUlGfrk4cOHcerUKUyePFkJ3A4cOIChoSHk5eUhLy8PaWlpEEIkVX88ffo07r33XixevBg//OEPkZmZqYw/2r17t1KXhQsXYnh4GM8++2zS9MdY+uSTT1BeXo7KykpcffXV+Oijj9DZ2YnHHnsMhw4dwsMPP4ympiYsWrQIK1euxODgIMrKypCdnY3h4WGMGTMGX/3qVwGMXFFKajG/qUchmzZtmnj55ZeFEKPjA4aHh8W7774rjEajuOaaa8SePXuEEEK8+OKLQq/XixtvvFE8+eST4vXXXxe//OUvhV6vF/v27YtbHdTYbDZRVFQkHn74YfHss8+K/Px8l/lkvM2/Io8R6O3tFb/73e/ElVdeKfbv3x+TMgfKYrGIkpISj3Eeg4OD4t577xVXXXWV+PTTT1X3/eMf/yiuv/56cfnll4uOjo5YFDdodrtd9Pf3i+985zvCbDaL119/XeTn54vq6mpx5MgRl21feeUVUVBQIG644YaE7pODg4OiqKhIzJ4922PdgQMHxG9+8xvxwgsviLffflv5O3QekyREYvfJX/7yl2L69OnK7ytWrBDf+ta3RH5+vpgyZYq4++67xccff+yxX6L3x6NHj4rrr79e6XfysXnrrbfEzJkzhcPhcBnz9+KLLyZFf4y1VatWiTvvvFMcP35cWdbb2yvWr18v9Hq9WLJkifj444/FP/7xD/GDH/xATJo0SdTX14ujR48KIUb+Fl555RVxzTXXiM8++yxe1YgIXkFKEl988QX6+/ths9kAjD6BkZ6ejiuuuAJPPPEEli9fjuXLl+OXv/wl7rzzTlx66aV444030NHRge3bt+Oiiy7C5s2bcdVVV8W5Nq4OHz6M6dOn4/HHH8eJEyfwxRdfoLW1VbkS5n4lCRh53HjVqlXIzMxEV1cX7HY7mpqaMHny5DjWxNPJkycBwOXpIIfDgQsuuAAPPvggbr/9dhw/flx5ZByAUtfrrrsO9913Hx566CGX8S+JJC0tDTk5OSgpKcHq1avxyiuv4Pjx43jqqafgcDhw33334dJLL4XJZFJeXfH73/8+ofvkqVOnsGjRIqxfvx4bNmzAokWLAAAtLS14+umn8fWvfx2ffPIJAODb3/42nnvuOeTk5OD06dP4+c9/nvB9cuzYsco4qS1btuDw4cNYunQp9Ho9Ojs7sW3bNtx555144okncM011+DMmTPIzMxM+P74xRdf4Pjx48o5Mj09HXa7He+//z4yMzOxdu1avPvuu/jqV7+K++67D3feeScuu+wybN++PaH7Y6zI550PPvgAl156KS6++GLl6uj48ePxwx/+EF//+texatUqrFy5Eo2NjXjhhRewZMkS7NixA7///e8xbdo0nDp1Cn/+85+xZs2ahLpyGpL4xmcUCPlb6cMPPyxuu+02cejQIWWd89WVv/71r2LGjBni1ltvVZ46GB4eFsPDw+LUqVPKskR3/PhxsXr1apGfny/uu+8+Zbn7laTf//734umnnxavv/66y7edRHLkyBFx7bXXit7eXpflp0+fFgMDA+L6668X7733nsd+zk/QqH2bTzTbt28X3/rWt5SntbZs2SLy8/NFTU2NmDdvnpg2bZr44IMPhBAjdUv0Ptnf3y+ee+45kZ+fL1pbW8WRI0dEfn6+2LNnjxgeHhY2m0386Ec/Evn5+WLWrFlKPV577bWE75OHDh0S+fn5Yu/eveL5558XL7/8sjIj+MmTJ8Xu3bvFLbfcIqZNmyZOnTolhBi9QiZEYvZHh8Mhjh8/Lr7zne+I6upq8c4774gTJ06I119/XVxzzTXirrvuEj//+c/FAw88IIqLi8UNN9yg/N2dPn064ftjLC1fvlyUlpYqT6k5n4tOnz4t2tvbRVFRkairq1OWv/nmm+Kpp54S8+fPFytWrBB//etfY17uaGCAlER27dol/u3f/k2sWLFC9PX1KcvlwGFoaEi8/PLL4uqrrxa/+MUvhBBCnDlzJi5lDZVcF29Bkvujt8nwKO5TTz0lXnzxRZcATy53eXm5ePfdd1X3S6aT9enTp8VVV10lmpublQ/TtrY2kZ+fL/R6vXjppZeUbZOlT8pBUkFBgSgtLRWzZs0SQowelxMnToif/vSnIj8/X6xduzaeRQ2Y3W4Xn332mbjjjjvEd77zHXH99dcr/U8+bsPDw2L37t1i8uTJ4ic/+YlwOBzC4XAkxd/aCy+8IMrKysQ111wjbrnlFjFlyhSxdOlSl2327t0rpk2bJm655RYhRHK/QiWS5OP7xhtviJtuukm0tLQofd352NtsNmUoxP/7f/8vLmWNFT7FlkRuuukm3H333Whra8PLL7+sPHIrP0EwZswYlJWV4ZJLLsHevXsBJNbTM4GQb6NdfPHFuPvuuzFv3jxs27YN999/P4DRQcySJClPCiUq+UmgBx98EHfeeafLLUK53F/5yldc6vD555/jt7/9LT7//HNl0GiiE0LA4XDgn//5n/Gf//mfyiPB3d3dOO+88zA8PIw//vGPeP/99wEkT5/MyclRnnpyflxZfkotNzcXDz74IC655BIcOnQozqUNTFpaGi688ELcfvvteP/993H8+HFl1mN5dun09HQUFxejuLgY7733HjQaDTQaTUL/rcnH5gc/+AFaWlrw4osv4oUXXsB1112HW2+9FcDIIG4AmDx5Mm655RZIkoRPP/004Qabx4t8fG+44QaMGzcOLS0tePPNN2G3212etM3KysItt9yCq6++Gq+++ir6+/uVwfDyNqkicXs8uZA7nnzvfMOGDfj1r3+N48ePAxjp3ENDQ8jKykJJSQl6enpw+vTppH5M1T1IeuCBBwAAXV1dqK6uxscffxznEvrm6wNFfleXEALZ2dkAgP7+fvzmN7/BQw89BEmSYlXMiDjvvPMwe/ZsHDp0CKdOnUJtbS127NiBF198Effddx927NiBdevWoaenJ95FDUpubi5mzZqFn/zkJ5g8eTKGhoaUp7vsdjtyc3Nx9dVXK/VK9A8I+XxgNBqVLx2bN29W5q9KS0vD8PAwxo4di+uuuw4ffvghTp8+nfD1cp52QKfT4dJLL8XYsWPx5ptvor+/H8DI2Cu73Y7MzExMmjRJCZholMPhQEZGBtavX4/c3Fw0NTVh3759HkHSN7/5TRiNRvzXf/0XBgYGXOYFSyUcpJ0k5MduNRoNHn74YQghlMdUv//976OwsBAZGRlwOBzKSxmT/hFLjAZJaWlp2LRpEz7++GN0d3dj3bp1GDduXLyLFzLngedjx47F4OAg2trasGbNGmzZsgX/9m//Fu8iBkz+Bj5hwgRYrVYYjUZ8+umnWL9+PQoKClBQUKA85r906dI4lzZ4X/va13D77bcDGLn6JQ9cTU9Px6lTp9Df34/rrrsOQOJ/QMhXm9PS0rBgwQJ8+eWX2LBhA9auXYv58+dj8uTJGDNmDE6dOoW///3v+Na3vpU05xH3K0GZmZmYMGECduzYgW9/+9u49NJLkZ6ejuHhYfz3f/83rrjiiuQfRBxhcoCclZWF5557DlVVVVi1ahXuu+8+3HDDDcjMzMTQ0BAyMjIwYcIEAIn/pSAs8bmzR5HwzDPPiPz8fFFWVia2bNki9uzZI9ra2oRer0+4R4vD9Y9//EPMnz9f5Ofni66urngXJ2LuuusuYTabxYYNG0R+fr7485//HO8ihcVoNIoZM2aIv/zlLx7rjh07FocSRc8nn3wiXn/9dTF16lSP16wkOudxN83NzaKoqEgYDAbx7LPPit/85jfimWeeEd/+9rfFO++8E8dShk8eK7NkyRLxzjvviA8//FC0tbWJ4uLilDtHRsPf/vY3MWPGDDF58mTR1NQkrFarEGKk//z6178W1113nbIsFWmESOJ7MCni888/x759+9Dd3Y2bbroJF198MXQ6ncej7TLn5Tt27EBHRwf+9Kc/ITMzExdeeCEefvhhFBcXx7oaqoKtmzf79u3D4sWL8Ytf/CIl6iZfhaioqIBer8dvf/tbbNiwAVOnTo1R6X0LtW5//OMfcckll+CSSy5RlgV7rKMt3D65atUqZGRk4N1338V7772HpqYm5QpSPAVbL+cxfDt37sSePXuwc+dO2O12XHjhhaivr8fVV18d62qoCucc+Ytf/ALPPvssgJGrTOPGjcOqVasS5jwSa8H+PdpsNlRVVeHo0aPKEI7BwUH8/ve/x7PPPotrr702iqWNLwZIcSbP2DthwgR8/PHHOHnyJHQ6HWpqalBaWup1P+eT29DQEL788ktoNBqkp6fjggsuiFXxfQq1bu5OnjyJW265BT/96U+D2i+awq2b3W7H0NAQysrKcPz4cbS2tibMCTtSxy0RRaJuzc3NeOedd/Cv//qvKC8vV14zEk+ROI8AwMDAQMqcR5wDgUOHDuH06dO44IILcPHFFyMnJydWxU8YNptNGe8YaJAkf5E7c+YMOjs78ac//QmSJOEb3/gG7r777qQaChCSmF+zIoXVahU33HCDeOaZZ5Q5Uzo6OsSSJUtEfn6+aG5u9nn5Ur5M7jw7bKIIt24yuY5ffvllVMsbjEjVTYiRWwCJdFstknVLNOHWzflR50R6NJznEe91k+uUSMcrHs6cOSNKS0vFI488oiwLtE2SYXqHaOEg7Tg6evQo7HY7rr/+emVm2rKyMhQUFODiiy/GmjVr0N/fj0WLFkGr1XrsPzQ0hMzMTOU9UIkk3LrJs/fKg5m9vQsrHiJVNwC49957Y1p2fyJZt0QTbt2Gh4cTsm48j3ivm3wFJJFu8cZDb28v7HY7Xn75Zdjtdjz55JOqbyhQI19hlN+zlujTq0QSA6Q4+uCDD2C1WpXLlPKHi06nw5IlS5CTk4PnnnsOWVlZ+NGPfuTSmbu7u/HnP/8ZN954IyZNmhTPaqiKZN0S7eTG48a6JVKf5DFLzrrFyuDgIG677Tbccsst+PrXv47m5mYACDhIOnHiBHJyclL2UX6f4nXpioT46KOPxNVXXy3WrFmjLHO+nDkwMCCeeOIJkZ+fL3bs2CGEGL0s+utf/1rk5+e7vHYkkbBurFuiSdW6pWq9hEjtusWK2WwWy5YtE0KMPHm5cuVKkZ+fLx566CFlG2+329577z2xcOFC0dTUdE7epmSAFEeDg4Pi/vvvFzNnznQZh+J8Avjv//5vcc8997i8y0r24YcfxqyswWLdWLdEk6p1S9V6CZHadYuXvr4+8fjjjwcUJFmtVlFcXJxSU6sEgwFSnL3//vuisLBQzJkzx+UFf84ngNdff13o9Xrx+uuvCyFcXxyZyFg31i3RpGrdUrVeQqR23eIlmCApWd6dGA3n0M3ExPS///f/xubNm9HT04Nnn30WFosFwOirQwDg5ptvxsUXX4xdu3YBQEIOplTDurFuiSZV65aq9QJSu27x8o1vfAOVlZW466678Morr+CnP/0pgNHZyI8dO6ZsmyzvTowGBkgJ4KqrrsLq1auxb98+PPnkk/jDH/4AYKRjCiFgtVpx3nnnQa/XA/CcUj+RsW6sW6JJ1bqlar2A1K5bvMhB0n/8x3+4BEnyuy4/+uijOJcwAcTx6hW5MZvNorCwUFx33XVi9erV4tSpU6Kvr0/s3r1b6PV6ceTIkXgXMWSsW3Ji3ZJPqtZLiNSuW7z09fUpA93vvvtu8a//+q9iz5498S5WQuBM2gnm/fffx5o1a/D2228jPT0d559/Ps6cOYMnnngC119/fbyLFxbWLTmxbsknVesFpHbd4uXjjz/GT3/6U3R1dSXUrP7xxgApAdlsNnz88cf4y1/+gosvvhj/63/9L+h0ungXKyJYt+TEuiWfVK0XkNp1i4d9+/Zh0aJFeO655xgcOWGAREREdI764osvUF5ejkcffTTp37UYaQyQiIiIzmFffPFFwrycOJEwQCIiIiJyw8f8iYiIiNwwQCIiIiJywwCJiIiIyA0DJCIiIiI3DJCIiIiI3DBAIiIiInLDAImIiIjIzZh4F4DIm/z8fJffa2pqUFVV5Xe/KVOmwGq1wmAwoLW1NVrFSxktLS1obGwEAOzfvx9arTbOJQpfQ0MDNm3aBAA4cuRISGlUVFRAkqSIlEen06G9vT0iaSUj+W9Zp9Nh586dcStHJPoFnTt4BYmSxsaNG+NdhHPS0qVLkZ+fj/z8fFgslngXJ2asVmtE/3N2rrYpUTLhFSRKGlarFSaTCUajMd5FoXNAfX29R2ADQLnC1tHRAZPJBAAwGo0oLy8HAJ/7EFHyYIBECc9gMKC7uxtWqxUtLS0MkGIsNzf3nPyANxgMPtc7337T6XR+t3d2rrYpUTLhLTZKCgsWLAAw8qHU0dER59KcW+rr67F//37s378fer0+3sVJCWxTosTHAImSgvPgbI5FIiKiaGOARElj/vz5AACLxQKz2Rzn0hARUSpjgERJY+HChcrPLS0tcSwJERGlOgZIlDS0Wq0yQNtsNkdsjhoiIiJ3fIqNkkpVVZXyaHVDQwPWrVsXVnotLS3Yvn07JEmC1WqFXq9HcXExamtrVbfv6OhQxkDJE/9ZLBaYTCaYzWYYjUZlvJTJZFLK2t7eDqvViubmZnR2dkKSJGi1WhQXF2PhwoXKQF1v29TW1kKn03mthyRJ2Lp1K7q6umC1WiFJkvJkVVVVlc99A2kjbxNJLl26FJ2dnQGlo9VqsX//fo/lgbSLGvlYWCwWaLVaFBYWory8PCmecvQ3OWcs+46vff0dg0gJtL6B1CUS/SLQ9jCZTKirqwMwMtVDfX29anqSJKG0tBRAZCbLbGhoUMoWCK1Wi127dvHJySAxQKKkIn/om81mdHZ2wmq1hvRHL0kSqqurPSbps1gssFgs6OzsRFNTk8eHw8DAgMs+zjPzAkB/f7/ys9VqVbY1m82orq52mSPHarWis7MTnZ2dSrA1d+5c1W26urrQ3t6u+uHgfJJ2r6P8wdPU1KTM0xMvhYWFHsskSUJlZaXLid65Xerr61U/2JwDDHkfs9kMs9mMlpaWsALCRBCrvgOEfgwiybm+FosF1dXVquXxV5dI9Itg2sNoNCpfkEwmE/R6vWpbVVdXKz+HM7u/1WrF3LlzleBPq9UiJydHKbe3+ul0OgZHIWCAREmnpqYGFRUVAIDm5mavV3u8cf42p9VqUVNTo3x4d3d3o7GxEZIkoaKiAq2trV7nt6mrq1O+9RoMBhgMBq9BSGVlJXQ6HVauXAm9Xg9JktDY2Kh8KKxYsQIWiwV6vR4LFizw2EaeA8rbN1RgZBD71KlTlbrIQaD8786dOyMeOKxbt85jYkT5RGy1WlFSUqIEsU1NTS7bqR0Hg8HgUu+6ujoUFhZ6fGt3/hCUJ2nU6XTKB2EqDeKPZt8J9RhEU0VFBXQ6nfIFJdC6RKJfhNIe9fX16O7u9tpWdXV1yrFqbW0N62+wuroaOTk5Hn/L8t/4ufw6m6gQRAlq4sSJYuLEiWLu3Lke62bNmqWsdzd58mSv+znvW1JSIgYGBvxu42zr1q1KvhMnThSTJ08We/fuVU1j48aNLtup5VVSUuJ3G7k+kydPVs3n6NGjXusxMDCgpL9ixQq/5VRLx996b5YsWaLst337do/1c+fO9Vlv+Ri4H0fnNuvu7lbN21f/iBTnvrBx48ag9g2mzaPZd0I9BsGSy+n+9yQLpL7+6hKJfhFqewwMDCjlcz6vbN++PeQ+4m7jxo1iyZIlXtd5+/um0HGQNiUleeJIILgn2kwmk/JtrqmpyetlZ/lqhyRJaGho8Jre888/H9AMyrNnz1bNy3nfBQsWqG5TXFwMQP0VFoDvy+darVb5NhvLqyomk0kZm+T8Gg6ZfNsDAFauXKla/pqaGmVbWUdHh3LrY/78+V6vaqjdzktW0eo7oR6DaPNW35kzZwJQr0sk+kU47aHVavH8888D8LxyC0AZCxiOgwcPeh1zuX379qBmcqfAMECipCRfOgeCmzhSviWm0+l83jJwfnVEW1ub6jZGozHg2w5Tp05VXZ6dna387O0El5ubG1Ae3shjFAYGBsJKJ1DyrQZgpB3VbofIs6FrtVqvtyWd20P+QHL+YAr21mqyilbfCfUYRFsg9XUXiX4Rbnvo9Xrli5XZbHYZlO1+ezkU3oIjefwWZ2SPPI5BoqRVVVWFuro6WK1WdHR0BDQIWb56VFBQ4HdbOQCT38bu/o0ymG9sgYw78LaNrw8GNfIUCEePHoUkSeju7g5q/3AFMiBV/nCxWq3Iz8/3m6Z8dUD+N9kHYQcjWn0n1GMQbaEc20j0i0i0R3l5OebPn+/y4EZra2tUB0hv374dwLn1NxErDJAoaRmNRjQ2NsJqtaKxsTGop7QCuSrjfMIZGBjwOMkl0jc2s9mMrVu3BvzIfbQsXbpU+eCor6/3etJ2vpoVzIeHnDafyAlfqMcgEUWiX0SqPebMmaMESHq9PuqBS0dHR0Kdi1IJAyRKarNnz8amTZsgSRLMZnPAV3UC+TbsvI18m8qZ2rJ4cJ5qQKvVYvbs2SgqKlJOzpWVlTG5PdLR0aEEaGVlZQE9Gu5r7hg1Op0OkiRxktAICvYYJKJI9otw26OyslL52WKxoKGhIaq3g+X51yjyOAaJklqwrx+Rv80FcttJ3kaebyQRmc1mJTiaP38+9u/fj9raWpcxWsHeoguF84BUnU7ndwLPYI6D2n7eBqxT4EI9BokoEv0iEu0hX0HV6XTK7eVNmzYp45siTU6XA7SjgwESJTX314+4T/zoTt5WHrfkjTxhJDD69Ewicq6Dt2+pNpst6uVwHncUyIBUuU2d2zkQ7vMheeM8YSepC/UYJKJI9Itw26OlpUW5gtrU1ASDwaA89aY2KW0kbNu2DUBi3e5PJQyQKOk5Pz7b3Nzsd1v5m+KKFStUL8lbrVblA1+eLC5ROV8dUvv2bLVao36FwHkivJqamoBO1s7HwX2WaHfOQaDRaFSu5tXV1akeP0mS4j4WKxmEegwSUST6RTjtYTablUkqnf8GqqqqlKs77jOdR0JXVxcADtCOFgZIlPR0Oh3KysoAQHn9iC/yFQ6r1YrS0lI0NDQoV59aWlpQUlKinGB9zZWUCJwfia6oqFDmg5EkSalLNG9Hmc1m5Ru7/JoF+ak/tf+cOc81VVJSgpaWFlgsFmU8WUtLCyoqKjxeO+EcsJaWlrrsJ+9DgQn1GCSiSPSLUNrD+QuVXq/3mO9IPofIrwmJFHlmcV49ih4O0qaUsHDhwoCvGuj1erS3tysnuU2bNrk8lgtAeTVGot/bl19xIj/a73yrCxiphzyANRqc87NYLJgyZYrP7Y8cOaL87H4cnF8T4Uyv17sMiDcajTh69KhyzNz3MxgMyM7O5lWkAIR6DBJRJPpFKO3hfGVI7fayfC6prKxU5giLxKB4+faaPBkoRR4DJEoJer1eCRQC3X7nzp1oaWnB9u3blVtE8tWohQsXJvSVI2etra2oq6tTgiT3N5hH691kaleFguXtOOj1euTl5WHOnDmqQWptbS2Kioo83tou39IwmUwxGXuVCkI9BokoEv0imPZwvr3c1NTk9VaXwWCA0Wj0+1LbYGm1WsyZMyfsdEidRggh4l0IIiIiokTCMUhEREREbhggEREREblhgERERETkhgESERERkRsGSERERERuGCARERERuWGAREREROSGARIRERGRGwZIRERERG4YIBERERG5YYBERERE5IYBEhEREZEbBkhEREREbhggEREREblhgERERETkhgESERERkZv/Dzff95lHQPwrAAAAAElFTkSuQmCC"
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 600x450 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 600x450 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 600x450 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 600x450 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "execution_count": 13
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-05-17T13:25:17.125272Z",
     "start_time": "2025-05-17T13:25:16.485167Z"
    }
   },
   "cell_type": "code",
   "source": [
    "#!/usr/bin/env python\n",
    "# -*- coding: utf-8 -*-\n",
    "\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import os\n",
    "import glob\n",
    "from matplotlib.patches import Patch\n",
    "\n",
    "# Set style\n",
    "sns.set_style(\"darkgrid\")\n",
    "plt.rcParams['text.usetex'] = True\n",
    "plt.rcParams['font.family'] = 'sans-serif'\n",
    "plt.rcParams['font.sans-serif'] = ['Arial']\n",
    "plt.rcParams['axes.labelsize'] = 30\n",
    "plt.rcParams['axes.titlesize'] = 30\n",
    "plt.rcParams['xtick.labelsize'] = 30\n",
    "plt.rcParams['ytick.labelsize'] = 30\n",
    "plt.rcParams['legend.fontsize'] = 18\n",
    "plt.rcParams['text.latex.preamble'] = r'\\usepackage{amsmath} \\usepackage{amssymb} \\usepackage{amsfonts}'\n",
    "plt.rcParams['axes.linewidth'] = 1.2\n",
    "\n",
    "# Model list\n",
    "MODEL_TYPES = [\"fart\", \"mingru\", \"lru\"]\n",
    "print(\"Start aggregating all model data...\")\n",
    "\n",
    "# Function: extract model type, environment and partial observation from filename\n",
    "def extract_info_from_filename(filename):\n",
    "    base = os.path.basename(filename)\n",
    "    parts = base.replace('saliency_results_', '').replace('.csv', '').split('_')\n",
    "    model_type_from_file = parts[0]\n",
    "    env_name = parts[1]\n",
    "    partial_obs_str = parts[2].split('=')[1]\n",
    "    return model_type_from_file, env_name, partial_obs_str\n",
    "\n",
    "# Collect all model data\n",
    "all_results = []\n",
    "\n",
    "for model_type in MODEL_TYPES:\n",
    "    csv_files = glob.glob(f\"gradientdata/saliency_results_{model_type}_*.csv\")\n",
    "\n",
    "    for csv_file in csv_files:\n",
    "        try:\n",
    "            model_type_in_filename, env_name, partial_obs_str = extract_info_from_filename(csv_file)\n",
    "\n",
    "            df = pd.read_csv(csv_file)\n",
    "            pos_cols = [col for col in df.columns if col.startswith('pos_')]\n",
    "\n",
    "            if not pos_cols or len(df[pos_cols].mean().values) < 3:\n",
    "                continue\n",
    "\n",
    "            means_all_positions = df[pos_cols].mean().values\n",
    "            num_positions = len(means_all_positions)\n",
    "\n",
    "            early_mean_raw = np.mean(means_all_positions[:num_positions//3])\n",
    "            mid_mean_raw = np.mean(means_all_positions[num_positions//3 : 2*num_positions//3])\n",
    "            late_mean_raw = np.mean(means_all_positions[2*num_positions//3:])\n",
    "\n",
    "            total_mean = early_mean_raw + mid_mean_raw + late_mean_raw\n",
    "            if total_mean == 0:\n",
    "                early_mean_normalized = 0\n",
    "                mid_mean_normalized = 0\n",
    "                late_mean_normalized = 0\n",
    "            else:\n",
    "                early_mean_normalized = early_mean_raw / total_mean\n",
    "                mid_mean_normalized = mid_mean_raw / total_mean\n",
    "                late_mean_normalized = late_mean_raw / total_mean\n",
    "\n",
    "            all_results.append({\n",
    "                'model_type': model_type_in_filename,\n",
    "                'env_name': env_name,\n",
    "                'partial_obs': partial_obs_str,\n",
    "                'n_seeds': len(df),\n",
    "                'early_mean': early_mean_normalized,\n",
    "                'mid_mean': mid_mean_normalized,\n",
    "                'late_mean': late_mean_normalized\n",
    "            })\n",
    "\n",
    "        except Exception as e:\n",
    "            print(f\"Error processing file {csv_file}: {e}\")\n",
    "\n",
    "# Convert to DataFrame\n",
    "all_results_df = pd.DataFrame(all_results)\n",
    "\n",
    "if all_results_df.empty:\n",
    "    print(\"No data collected. Please check if CSV files exist.\")\n",
    "else:\n",
    "    # Group by environment and partial observation and compute the average for all models\n",
    "    aggregated_results = all_results_df.groupby(['env_name', 'partial_obs']).agg({\n",
    "        'early_mean': 'mean',\n",
    "        'mid_mean': 'mean',\n",
    "        'late_mean': 'mean',\n",
    "        'n_seeds': 'sum'  # Total sample size\n",
    "    }).reset_index()\n",
    "\n",
    "    print(f\"Aggregated {len(all_results_df)} results covering {len(aggregated_results)} environment-observation combinations\")\n",
    "\n",
    "    # Create plot\n",
    "    unique_envs = aggregated_results['env_name'].unique()\n",
    "    fig_width_val = max(15, len(unique_envs) * 2.8)\n",
    "    fig_height_val = 8\n",
    "\n",
    "    fig, ax = plt.subplots(figsize=(fig_width_val, fig_height_val))\n",
    "\n",
    "    env_names = sorted(unique_envs)\n",
    "\n",
    "    time_keys = ['early', 'mid', 'late']\n",
    "    time_positions_display = {\n",
    "        'early': r\"$0 < \\tau < 0.33$\",\n",
    "        'mid': r\"$0.33 \\leq \\tau < 0.66$\",\n",
    "        'late': r\"$0.66 \\leq \\tau < 1.0$\"\n",
    "    }\n",
    "    n_time_pos = len(time_keys)\n",
    "\n",
    "    n_envs = len(env_names)\n",
    "    n_groups = 2\n",
    "\n",
    "    total_env_width = 0.7\n",
    "    group_width = total_env_width / n_groups\n",
    "    bar_width = group_width / n_time_pos\n",
    "\n",
    "    # Color definitions\n",
    "    mdp_early_color = '#A9CCE3'\n",
    "    mdp_mid_color = '#2471A3'\n",
    "    mdp_late_color = '#154360'\n",
    "    pomdp_early_color = '#FAD7A0'\n",
    "    pomdp_mid_color = '#E67E22'\n",
    "    pomdp_late_color = '#935116'\n",
    "\n",
    "    mdp_color_map = {\n",
    "        'early': mdp_early_color,\n",
    "        'mid': mdp_mid_color,\n",
    "        'late': mdp_late_color\n",
    "    }\n",
    "    pomdp_color_map = {\n",
    "        'early': pomdp_early_color,\n",
    "        'mid': pomdp_mid_color,\n",
    "        'late': pomdp_late_color\n",
    "    }\n",
    "\n",
    "    x_base_pos = np.arange(n_envs)\n",
    "    legend_handles_for_this_plot = {}\n",
    "\n",
    "    for env_idx, env_name in enumerate(env_names):\n",
    "        for group_idx, partial_setting in enumerate(['False', 'True']):\n",
    "            subset = aggregated_results[\n",
    "                (aggregated_results['env_name'] == env_name) &\n",
    "                (aggregated_results['partial_obs'] == partial_setting)\n",
    "            ]\n",
    "\n",
    "            if subset.empty:\n",
    "                continue\n",
    "\n",
    "            for time_idx, time_key in enumerate(time_keys):\n",
    "                mean_col = f'{time_key}_mean'\n",
    "                group_center_offset = (group_idx - 0.5) * group_width\n",
    "                time_pos_offset = (time_idx - (n_time_pos - 1) / 2) * bar_width\n",
    "                bar_exact_pos = x_base_pos[env_idx] + group_center_offset + time_pos_offset\n",
    "\n",
    "                if partial_setting == 'False':\n",
    "                    color = mdp_color_map[time_key]\n",
    "                    condition_label = 'MDP'\n",
    "                else:\n",
    "                    color = pomdp_color_map[time_key]\n",
    "                    condition_label = 'POMDP'\n",
    "\n",
    "                legend_label_key = f'{condition_label} {time_positions_display[time_key]}'\n",
    "\n",
    "                bar = ax.bar(\n",
    "                    bar_exact_pos,\n",
    "                    subset[mean_col].values[0],\n",
    "                    bar_width * 0.9,\n",
    "                    color=color,\n",
    "                    edgecolor='black',\n",
    "                    linewidth=0.7,\n",
    "                )\n",
    "                if legend_label_key not in legend_handles_for_this_plot:\n",
    "                    legend_handles_for_this_plot[legend_label_key] = bar[0]\n",
    "\n",
    "    ax.set_title(r'Aggregate Recall Density', fontsize=30, pad=20, loc='center')\n",
    "    ax.set_ylabel(r'$\\mathbb{E}_{\\pi, f}[\\delta_Q(\\mathbf{x}, \\tau)]$', fontsize=30, labelpad=20)\n",
    "\n",
    "    ax.set_xticks(x_base_pos)\n",
    "    cleaned_env_names = [name.replace('Easy', '') for name in env_names]\n",
    "    ax.set_xticklabels(cleaned_env_names, rotation=0, ha='center', fontsize=30)\n",
    "    ax.tick_params(axis='x', pad=5)  # Adjust x-axis tick label distance to x-axis\n",
    "\n",
    "    ax.set_ylim(0, 1.0)\n",
    "    ax.set_yticks(np.arange(0, 1.1, 0.2))\n",
    "\n",
    "    ordered_legend_labels = []\n",
    "    for time_key in time_keys:\n",
    "        ordered_legend_labels.append(f'MDP {time_positions_display[time_key]}')\n",
    "    for time_key in time_keys:\n",
    "        ordered_legend_labels.append(f'POMDP {time_positions_display[time_key]}')\n",
    "\n",
    "    final_legend_handles = []\n",
    "    final_legend_labels = []\n",
    "    for lbl in ordered_legend_labels:\n",
    "        if lbl in legend_handles_for_this_plot:\n",
    "            final_legend_handles.append(legend_handles_for_this_plot[lbl])\n",
    "            final_legend_labels.append(lbl)\n",
    "\n",
    "    if final_legend_handles:\n",
    "        legend = ax.legend(final_legend_handles, final_legend_labels,\n",
    "                          loc='upper center',\n",
    "                          ncol=2,\n",
    "                          fontsize=20,\n",
    "                          frameon=True,\n",
    "                          framealpha=0.9,\n",
    "                          edgecolor='grey')\n",
    "\n",
    "    ax.grid(True, axis='y', linestyle=':', color='darkgrey', alpha=0.6)\n",
    "    ax.grid(False, axis='x')\n",
    "\n",
    "    sns.despine(left=False, bottom=False, top=True, right=True)\n",
    "\n",
    "    ax.spines['left'].set_linewidth(1.5)\n",
    "    ax.spines['bottom'].set_linewidth(1.5)\n",
    "\n",
    "    plt.tight_layout(rect=[0, 0, 1, 0.96])\n",
    "\n",
    "    # Save as PDF\n",
    "    # output_filename_pdf = '../../popgym_arcade_plot/recall_density_aggregate_all_models.pdf'\n",
    "    # plt.savefig(output_filename_pdf, dpi=300, bbox_inches='tight', format='pdf')\n",
    "    # plt.show()\n",
    "    # print(f\"Figure saved as: {output_filename_pdf}\")\n",
    "\n",
    "    # Save aggregated results\n",
    "    # summary_filename = '../../popgym_arcade_plot/summary_recall_density_aggregate.csv'\n",
    "    # aggregated_results.to_csv(summary_filename, index=False, float_format='%.4f')\n",
    "    # print(f\"Aggregated results saved as: {summary_filename}\")\n",
    "\n",
    "print(\"\\n--- Process complete ---\")"
   ],
   "id": "748f421f5b94a4f3",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Start aggregating all model data...\n",
      "Aggregated 42 results covering 14 environment-observation combinations\n",
      "\n",
      "--- Process complete ---\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 1960x800 with 1 Axes>"
      ],
      "image/png": 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2xOnTpyMi4plnnllwIjFd3ktpY1nGWHleH66EMezo6Gj09vZGxPyLVpLj7evri4ipdjlfYDudtrOzs2GR2vR0y712XOpntGL8vNRjy7rAb6G+cb05dOhQvd49/fTTTTuvNfO6+oUXXlgwv2q1Grt3767/e3r/lKXvSh/7wMBA/diLxWJs27Ytjhw5Ep2dnVGr1eLcuXPx3HPPxfj4eFSr1Th8+PCs9X2p5bCS5hW1rdnl1XYSzV6MOV+9Hx4ejtHR0fqCtUKhEFu2bIlisRhdXV2xd+/e+nun182F2lPE/O1ztSwkt4i8ucyDZyfADDmoVCpzbo+d2Lt3b32SZTHbha0keU7AnTx5clHp77777jkvDvOYjFvuZFVEPuU32yRYtVqtnxg7Ozvj8OHDmT4rwuT5Up04cWLGz27duhXVanVGYCe50MkyQFkPk5zLrXODg4PR3d1d74Or1WoMDAzEwMBAUxZbJIaGhmYMjJs9qX/u3Ll6ORw5cmTGooRE8jeeO3cunnrqqbYv6lmvptfZLVu25JJPug/o7OyM7du3x+bNmyNiajyRXADt379/3oVoiWq1Gt3d3TOOP7nrLJmISc6fEVOT1bMFfNNbfC7HiRMn6sGIiKm/c74J4Nn6jWTV/s2bN+PChQtRq9Xq5+5mtM/pExeFQiF27doVd999d1y6dKl+bu/r64stW7bYRm2ZWtW+2lGXlioZhxYKhfpi1mq12jA2PX369IxJkDza9WyTUfPJUm7NaGO1Wq1hTBAR9Un4iKmxWXpcduHChRmf0ew+dz16+OGH6336QhPcyVgqYuo7z2s8m8f14Uoaw6bbQ3Kn0Fx1M33H+GzXtmnPPfdc/fVsd3A149pxuZ+R5/h5uce2Ghb4rUQ9PT0xMDBQP/8ODw8ve/5hudfVpVKpvnghYqodLTTWS7e15P1LkV5AkkiCbmNjYw13raY9//zzM362EuYXmjEvpm3NLo+2E9HaxZhzXasmf1My9u3r66uPw6bfvT08PLzgYqL0LqTT2+dqWUi+GtqBReRrkwAz5CDdWc7V4aS3yY7INiBtlmZMLOU9AZeeWM6iUChkWn281Mm4tGZMVuVRfidOnJgxGOns7IyOjo6GybjpFyNzMXm+dFnqb2dnZwwODi5qInK5k5xLbfutCjI1o84VCoUYGRmZMZCOaFxsETHVPx87dmzRF/fN6EcWK70jRfK9J6s3E0n7tqVieySrhRN5BfqTlbNHjhyZkcfx48cbLkx7e3vnvLsokb5gT+7kSdfbZByTbvvpny/WXBfNtVotnn/++fr5L9HZ2RlPPfXUnJ+XXDgn79mzZ0/9jqW09KKQ06dPx44dO5Z13kqfS3t6embcEZHuzx599FHnyGVqRftqV11aqnK5POsdhNPPpWfPnm0YQyZ37UU0r11nNVsfM5dmtLFHHnmkYYehp556ata7TiqVSj2IN12z+9z1KL17VzIhONfdP+3YgrIZ47qVOIZN3xE9OjqaaTF28u+5Js/Tgdrpf0MzyqDZ15/NHD83+9jmW+DHTIcPH66frwYGBpZ9vmrG4qG9e/fWP2d4eHjB7zzLPOFCyuVyw+4E+/btix07dkS1Wo1Tp07VA26FQiEOHz5c7yNqtdqs/cVyymGlzitqW42a3XZauRgzmXtN8krGZBGz38CR/o7Td29nCTCnz2/Ty2g1LiS3iHxpzIMvjQAz5CDLhfH0bbKfeeaZlgaYlzOxtNom4NKWOhmXttzJqjzKL1lJlUgGDNMnB2Zb7ToXk+f5Srax37dvX+ZA5HInOZfa9ls1Gd2sOpdM0I2Ojta3F5pNMlE3ODi4qPrbjH5kKY4dOzZjAD69TZfL5UzPNyR/c03kLNfIyMi8n3vs2LF6P5DsqDJf/5Kci5q99dVckgv9LGbrB6b72te+1nA+ffzxx2dNd+jQoejs7Ky30d7e3kzbpc3mxIkTDXnOdozJ7hR9fX1Rq9ViaGjINvZNlEf7akddWq7ZFl8kj2hJ+oHZFjo228GDB2f9+dNPP10v09nOYXNpRhsbGhqqX2cVi8U4c+bMvNsTnzlzZsYkXETz+9z1Kr171/Dw8Jx9ezMCMIvVjHHdShzDdnV11d9/7ty5Wdtf8vtisRgTExNRq9VidHR01vFA+liSCeq0ZpRBHtefzRo/N/vYFlrgR6NDhw7Vr0GTerqc+YdmLB5Kn2vL5fK8Y5P0LocRS9v+PzmWxMjIyIyA2u7du+tBqFKptOA14XLKYaXOK2pbjZrZdlo9Fzw8PJxpbF4ulxt2CIiY+u6T685k0dhc17rp9lkoFGYc62pcSG4R+dKYB1+aje0+AFhrkoFlxMLb3qSDz6tpm+zZJuBm+zsPHTrUsBK4t7d31omb2Vy8eDFeeOGFzP/N91yp6eabjEvMNRk3fbJqZGRkzkF7Mlk1fQVYHuU3NDRUf50c12yDp66urkzPnVnMxF5E1Cf2mDJXPT1//nwMDg7GwYMH61tqnT59Onbv3j3ngCxtZGQkjh8/Pme/kq5r0y9iV7o86lxXV1ecOXMmXnjhhRgcHIyenp5ZLy57e3tnXJAsZDn9yFL09/fPOjHY1dUV58+fb/jZYh8xQHNMr1vTL0SbZaEL2ulbik6/C2o2sy1IaodCoRCdnZ1x8ODBOH/+/ILnq2QrwOS93/rWt+ZNXyqV6qveI5bWVpJ+OzHXREdENDwPaqFtR5lf3u2rHXVpueZ73tj07XHzdvz48Vn/e+yxx+ppkjurFtKsNnbq1Kn662PHjmWaXJ6tPPPoc9ej9PgovRg7Lbm7OeL2+aBVljOuW6lj2On1crb2l7y3WCzW71Ca63yV3h473f9FNKcM8ijHZo2f8zi29AK/rI9LWu/Si5nSffxSNOO6urOzs+F7m6tvi5i6oSQxvf1kNTo6Wq83Bw8enLXOpI87nedc2jm/kNe8orY1U7PaTivmgtPS27o//PDDc6ab6/na6XN4egvs6dJzcVl2T8lrbN3M9tjqdtDX1zfrfwMDAzE2NtZQZj09PQsu4Gx1XYswD74cAszQZOkLvIVWskxfGbTYAEc7rMYJuLTlTsYtd7Iqj/Kr1WoNA6L+/v55T9QLHbPJ8/wUi8Xo6uqK48ePx8WLFxsGiH19fXH06NF5379WJzlbUeeSxRXnz5+P8+fPz7iw7+3tzXzB3I5J/fm2JSoWiw0XjdMH8LTG9L61ne0vfSyzPW8trbOzs6XPDzp//vy8i8WSC+ss59f0uGnv3r2ZVpOnJyeWsrgvPXmYbD8633/J3+EcuTx5t6921KXlyrooJK/FLll0dXXVg4S1Wi3TdUAz2lh6we9sd6I022L63PUqHTCu1Wqz9onp737fvn0tO7bljOtW8hh2+l3Gs+WZ/KxUKtUf95Q8y3W6dD/30EMP1V83owzyKsdmjJ/z/I5XygK/1eLIkSP115VKZVljq2ZdV6fH0PMtGH/66afrr+cLlM0nfX7ZsWPHrGnSC3OyLHZu1/xC3vOK2lajZrSdds8FL2VxQ7p9zjdHstDuKat1IflKaQcWka99tsiGJlvMc6OSTja9XdhK315hqRNwyclhbGysqVvGLtZyJuOaMVmVR/mlT2jTBxxLMdvE3nyKxeKyL/DWq+nbbI6NjcXw8PCygj3TJzlXep8S0fo6VywW4/HHH5+xPd6JEyfmHUimjzGLVk7qHz9+vGFAfOnSpRVxMbGeFIvF+s4EEVN9c7va382bNzOnbdUzLvOQ7gOy1vf0ZHOyheBitjlLX8gnAa6s8to2fT3Iu321oy4t13yLMPJ6NtxSHDt2rD7OWeg5thHNaWPpz2jWc+Pms5g+dz1Lb1d59uzZGW0tPcG71ADMUixnXLfSx7B79uypjw+nP5IrHUhOglJJ2unPbJ4edE6XWTPKoF3Xn1nGz3kdW6sX+K0FhUIh9uzZU58bGRoayvV6J8t1dU9PT3171mSngOljgenzSEs95nQbnGu8kT7/N2vBcR7zC3nOK2pbMzWj7bRjLnjHjh319yfjh8V8t52dnTPm3Gd7ZEIieZTldLMtdG3XnfFZ22M7FpE3q0zaUdfMgy+PADM0UXrgGBGxc+fOJb1/JU8+rsYJuLTlTMY1Y7Iqj/JLr2TdtWvXko4rzeR5a6WfIRgxNXDOOoiazWqc5GxXnevq6oqDBw/WJ5ay3oG2Uif10xdPq2l79LVk165d9Xp07ty5TI8kWI7koub555+Py5cv15+fuBir+XndWSbappuebmJiYlF9yHLa1mLzolGe7asddWm9KJVKDRM1Cy3makYbS39GMycAm9Hnrmd79+6tj3en31mX3h57tuf75qlZ14crcQz71a9+tZ5mepnPd11aLpcbJuHTaaffQd3sRSGtvv5caPyc17Gt5gV+7XTkyJF6fS+Xy7k+9z7LdXUSME7qxUIBrOXszpD+OyuVyqzzSZcuXaq/TnYlWK485hfynFfUtma33LbTjrngnp6ehkesJNsuF4vF+vhyoUdTHj58uL4ga7b2md5Kfq6A7GpcSL6a24FF5KuPLbKhieZ7pkNW8z23ZSVo1gTcatSMyao8yu/WrVvLPq605U7ssXjTt+bLMpipVCoxNDQUR48ejd27d8fOnTtj69atq+p57ol21rn0dlERq3uLm46Ojvrrl19+uY1Hsn599atfrb+eawvQZjhx4kTs3Lkzuru76881Si6kFmutPJdsqUGe5QSHkudjZv1vrZR1u7SqfbWjLi3FaprISC8GGBsby7zF5kppY83sc9ez9J1709tw+hp4Nd15ttLHsJ2dnfW+olarNRxvEvRKLzRLXk//rHSALN0XRzSnDNpZjguNn/M6ttW8wK+dOjs7GwIOzXj+5XKvq9OBptm2yU73b8vZnSHd9uaaN0y31fRW9lm0cn4hz3lFbWt2y2077ZgLLhQK8eyzz84Y31Wr1RgeHo7e3t7YuXNnnDhxYs7P6Orqqh9HtVqdMQZN1+/5xh/pm3laMW+/3Pa4mttBO+qaefDlcQczNFG6ox8cHMz8vlOnTjVs2bFaLqpXywRc2kqajFsN5XfmzBnb7LZI+s6s+ba6OXHiRDz99NNrdlKz1XWuUChEsVisDyizlOtK6kdYWbq6uhrq08DAQIyMjDTt86vVanR3dzfU02TldmdnZ/2ur76+vnmfA7dWTN/NI8tK8ukXj4sNSG3evLn+eq67R8hHnu2rHXVpPSkWiw1bMz766KNzfnfNaGPpz1jOhJE+t/m6urrqwcvR0dH695sOirT6rqBmjetW6hg2fY2R3vo6+R7Sdznt3bu3Pi9RLpfrf0/Wu4maUQYr+fqzmcfmnLF0hw4darhj+NixY0tqx826rk5v/59sJ598v+ldDpe7O0MSICyXy1GpVOLo0aPxrW99q/63Dw0N1c9Fi9ket93zC82eF9O25tasttPKucxCoRDnz5+P4eHhGB4ennWR4unTp6Narc65Q86+ffvqu3kMDw/XFz6mxx4L3Qn91a9+tX4uTRbJ5XGualZ7XCvtoF2LyFfqOGSlcgczNMn0E1NXV1fm/9IDv+S5LSvVXFszz2etTMA1Y7Iqj/JLH1f6bualmj6xR+vN9j1Wq9XYuXNnnD59ut5HlEqlOHbsWJw5cybOnz8fL7zwwqpZoJK2kurcag4eX758uf767rvvbt+BrHPHjh2rv65UKg3jg+Xav39/vf339PTExYsX48yZM3Ho0KEolUqr9vy6VOmV5On6P590H1MoFBbd5tN3g2Q9j9M8ebWvdtSltPWw8v1b3/pW/fV8310z2lj6M9LbhS6WPrf50sHM5A6g9N3MSeB+tVgNY9j0XY9JOaePNT2Jmn793HPPNbwnovGO6EQzyqCd5bjQ+HklfcdMmd7/njx5clHvz+O6Or11fHpnw/S5rhnX6en6ODY2Fjt37ozdu3fH1q1b68+CLhQKmW54aef8wnqeV2yn5bSddn9nPT09MTIyUh+L9fT0NHze2NjYnGPL9M4B6buPs2yPnUgWuiaS9tYsa3m+b7HaUdec65dHgBmaZDEnpummPxuhGSvg85qoavcEXDs1Y7Iqj/LbsWNH/XUztos0ed4e6eeizTYYWsuTnO2sc9O3C1zN5Zj+O1bzlkirXVdXV8MEbW9vb1MuUpJnZUVM1dP+/v45z6er8VnsSzF90jzL4q9Tp07VXy/l2VTp9yTb5NI6ebWvdtSltPUwkVEoFOLgwYP1f881MdeMNpa+C6VWqy1pIYI+Nx/Tt8lOnmudWG0Tp6thDJu+Izy5hk3KvFAozNgiO6nnybVJEmiOmL2va/aikFaX40LjZ9fGK1N6wdnTTz+9qPfmcV2dDmClr+ubuf1/tVqNsbGxGefTdB3es2fPrFsKz6ad8wvreV6x3ZbadlbKd5aMI/r7++P8+fMN7So9Nk9Lntkc0bioLbkjuVAoZNo9xULy1rCIfPURYIYmSW+PvdhtvaZf2DXjeQ55TVS1ewKunZoxWZVH+aUnWmd7psh0C90hb/K89YaGhhq+l+l9yFqf5GxWnTt69Oii+770qt3lbluWp4UWDU1/7pAtfdprcHCwoY0+8sgji6qbyTOX5rLQBdP4+HjmvJZipey0Mv1ZYr29vfOmn76tWnqSIKtCodAwkbFQnon1EEBslTzaV151KX2c87WbVjzLbSGtaNdHjhxpeA7ebItqm9XG9u3bV3/96KOPZvr75hrbt7vPXWvS3+8zzzzTsFB7tV0rrpYxbHpivVqt1ifX05O4ieRnyc5q6WDZbPMczSiDvK4/mzF+dm28MqWfq1qr1TLfpJHXdXV6rihpO+ntsRfafjeLpI/YtWtXHD9+PF544YUYGRmJ/v7+OHPmTFy8eDEef/zxTPm0e35hPc8rtttS285K/c7SY/D5jil5PETE1Hgvfc7NemwWkreGReSrjwAzNEH6hLzUSf3p22TP1ZnlOVGVZeKlHZO5K8lyJ6vyKL9CodCwJdOjjz4672emJ3FmY/K8tcrlcsNdPHv27Jl3giiPSc52Pw+8WXVubGwsuru7Z0wWzaVcLtefxROxsvun+dpXpVJZNX/HelEoFGJkZKTh4j2pm/O1m+R5at3d3TN2pNi+fXtDurkmA06cOJFLfzy975me/9DQUFNXcWeVPEMrYqpcuru7Zx1DnThxov58vIhY8jPHpr93vjwjpsYA3d3dC56byS6P9hWRT13asmVL/fVcu8z09fW1bQzV6nZdKBTi8OHD9X/PdRdzM9rY8ePH6+OpWq0WX/nKV+Ys59HR0di9e3fD+KPdfe5alg5SXrhwoR7AbEYAptVWyxg2ff1ZLpfrdzKnJ3ET6Z9dunSpfqxzBbGbUQZ5XX82Y/zs2njlSp9P5luYOZdmX1dPfwRA+u7/ZuzOkJwH08eVPGt5Of1ns8vBvOLKt5S2047vLEuQL72QKD3uni59F3C5XF7y7ilreSG5ReTO9UslwAxN0IznqkxfYTPXZE6zJ6qWMrHUjsnclWK5k1UR+ZTf8ePHF/zMWq0WfX19DXfbz8Xkef6S72P//v31nxUKhYZnFCbymORc6qRyXpPRy61z6bSnT5+OrVu3ztkXVqvVGWVfKpUWvftEKw0MDMxarsPDw9Hd3V3/d6FQaFidS/sUi8UYGRlpmIw9ffp07Ny5M7q7u+Po0aPR19dXr4vJz5M+evpdN+ltRSOmzvW7d++Ovr6+OHHiRBw9ejS2bt3aMFnabNPz379/f/3YBwYGFlzAlIdisRhnzpyp/7tSqcTu3btj9+7d9WDi9HLp6elZVjspFArx1FNPNfRZu3fvju7u7hnfabKy3Sro5mp2+0o+s9l1adu2bfXXAwMDcfTo0RgaGoqhoaHo6+uLnTt3xvDwcFvHx61u14cOHWpYHDBbQK1ZbezMmTMzFiLs3Lkzjh49GkePHo39+/fH1q1bo7e3t/7+ZHJtJfS5a1myODa50y9i9W2PnVgNY9j075977rmGuyqnS/8s/SzZ+RbSN+PaMY/rz2aNn10br0zp7yzZPnoheS4eSvdhzz333IJ3/y9WMuaZ77izanY5mFdcXZbSdiJa/50NDQ3Vx8pzBT/T48iFbvhK2mh6J49isbiox4uttYXkFpHf5ly/dJvafQCw2qWf3xCx9IFjMomRfNbw8PCsFznbtm2rd3ADAwPx/PPP15/BW61W49y5c1Gr1aJQKGRefZTOt6+vr37yuHTpUtRqtdizZ0/D35VMwCUXtsmkT7FYjG3btsX4+PiMk95iJ3MfeeSRBdPM9vcdOnQo98mJM2fORHd3d9RqtfpgolAo1LcTu3Xr1owBQ/KdRORTfsViMXp6euqDgeQzk1V6N2/ejAsXLmSuG8nE3iOPPFJ/Ptru3bujs7OzPvipVqv1OpK8hymjo6MzyqNWq8XExER9EnR6HUnqxWzlOL1/6Ovri6GhoSiVSrF58+ZFXRSkLbbtL/d981lunZveBiKm+tHk38kF+WwDxM7OzoagwkrV29tbL490m0577LHH2nR0zKZYLMb58+djaGio4U69SqUy78Xhnj17Zl1s0t/fXz//RMy+xWwyab+UPmEhPT09DX3X9H7s7rvvbnqeWZRKpRgZGWkIElWr1Vnbe39/f1PGCZ2dnfU8k+9yru+1WCzG4ODgsvOkUbPbV0Tz69KRI0ca2uLY2NiMtnnw4MH46le/2hDsaKV2tOvHHnusvgDz9OnTDVtnJ5rRxorFYjz77LPR29tb/7tqtdqs/WOxWJwxKdXuPncte/jhh2eU2Upe6Def1TCGTe4+rlar9aBX+nnL0/+ezs7OqFQqmQNkzbh2zOv6sxnjZ9fGK9fBgwfrC32yLObL67o6YqpNpdtZUhfSu80tRzoIliy2mk3yvNnk7ubZ5FEOK3Fekbkttu1EtP47S+pOUt8LhUJs3759xhxnYqE7V3t6eurXDEldXcp1YbLQdf/+/fWyO336dJw+fTo6Ozujo6OjPn6efm6ImHsheR79UhZ5zO8tVzv6B+f6pRNghmVKb0W93GdednV11Tv1ZDJr+jZUeUxULWViKe/J3KWuynr55ZeX9L7FWO5kVUQ+5dff3x83b95sOI7p3+XBgwdjx44dmbb7MHm+dFm3U4mYGpAcO3Zswe84j0nOpU4q5zUZvdw619/fH4cOHYoTJ07MKIO5Lpp6enoaVkeuVIODg/HMM8/E2NjYnP3j4ODgqp2cXeuSxU/nzp2L4eHhqFarMyY3Ozs7Y9euXfHwww/PuU1+cjF74sSJhkVD27dvr9/BVCwWG1YZJ4vQmqGrqyv6+/tjaGioPkbZtm1b7NixI3p6etp6gdXZ2Rnnz5+P0dHReOaZZxrKp1gsxt69e5t+jMn3US6X4+zZs3H58uWoVqsNkx/Tn9VF8zWrfaXTNqsuJee1gYGB+mREUj+6urpi79699YV/yTm81Qs12tGuu7q66gGsiIivfe1r8fjjj89I14w2VigU4syZMzM+I/n8bdu2xVe/+tVZz5/t7nPXsunfWbMCMO2yGsawe/bsidOnT9f7x/meUbhr166Gu8sjFp7raMa1Y7OvP5s5fnZtvDIdOXJk0TtJ5Ll4KAlgpdvOww8/vKjPmEsSOJ5rJ8NE+u8ZGBiIxx57bNY63uxyWInzisxtKW0norXf2fT2NP0Gr7TpW1fPJnm8YLo+L/X41tJCcovIb3OuX5oNk5OTk+0+CFjNuru76x3Ncif3a7Va7Ny5s/7vgwcPNmx9nKhUKpkmqr72ta9FxNTJYKGLz+Hh4SVPLDVjAm50dHRRQbm5zFZmW7durb8+f/78nBOLyRYYEVMDj4sXLy6Y31Imq6Zr9mT46OhoDA8P15+tVSwWGyZVK5VKnDx5MiKy1Y3Z/k6T540WW3+Tuwi6uroWNQiqVquZJjmT7Syz1MGltv3Fvi/dDi9evLhgvV5unavVavVnX12+fDkmJiYa2lfWQMNsx9+MfiRLeezcubN+gTEyMhKdnZ1RLpdjaGio3v8nEw2HDh3K/LewcqR3twCaS/uC1iqXy/U7TbJcS5XL5fo4J7nzby7VajV2795d//d8Y8ksY6xWXh+2eww7298ScXtsmSXtnj17Zl0EMpdmXDsu9TNaMX5uxrHNV+/Wo/T1dBK4yaqvr29GIKZUKs17d38e19URM+f0svYbEQv3XdMDWYtx5syZWetls8uhXfOK67lttbrtTM97uXOZWc7Z5XI5RkdH63140u8m58TZdsKZS3qsspi/dT7JeXu5C12X2x6X0w4W23anz4Hm3e5aVdfSzINnJ8AMALACzTZBBgAAzM74mbVo+gKexx57LEql0qyP5apWq/HMM8803J262MAjrFXphRp57gBnoSvrycZ2HwAAAAAAANBoaGio/joJis33DPXjx483BJTn2lYW1pvkju1CoZDr48UEl1lPBJgBAAAAAGCFSR5/FrHw89ATyVbwCQFm1rtKpVJvB3v37m3z0cDaIcAMAAAAAAArTPrZpuVyOfP70oHp9fRcYpjNyZMn668PHTrUxiOBtUWAGQAAAAAAVpjDhw/XX/f29i4YZK7VatHd3V1/HnmpVBJgZl2rVqsxNjYWEdoDNNumdh8AAAAAAADQqKurKw4ePBinT5+OWq0W+/fvj2KxGHv27IkHHnggisVi1Gq1qFarUS6XGwLQxWIxBgcH23j00Hp9fX1x6dKl2L59e0REnDt3rv67Y8eOteuwYE0SYAYAAAAAgBXo+PHjsWPHjhgYGIhqtRrVajVOnz49Z/pCoRD79u2L48ePt/AoYWUoFosxPDwclUql4efHjh2Lzs7ONh0VrE0CzAAAAAAAsEJ1dXVFV1dXVCqVGB4ergeaq9VqFAqFKBaL0dHREQ899FD09PS0+3ChbTo7O6NYLEa1Wo2IqYDzsWPHoqurq81HBmvPhsnJycl2HwQAAAAAAAAAK9/Gdh8AAAAAAAAAAKuDADMAAAAAAAAAmQgwAwAAAAAAAJCJADMAAAAAAAAAmQgwAwAAAAAAAJCJADMAAAAAAAAAmQgwAwAAAAAAAJCJADMAAAAAAAAAmQgwAwAAAAAAAJDJ/wdiXsoYinWkNAAAAABJRU5ErkJggg=="
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