new-systemmetrics.ipynb

{
 "cells": [
  {
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   "id": "d6b718f5",
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   "outputs": [
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      "investigation\\Quest-Pro\\BeatSaber\\PopStars-Medium\\stationary_boundary0.0\\logcat_VrApi.log\n",
      "investigation\\Quest-Pro\\BeatSaber\\PopStars-Medium\\stationary_boundary0.1\\logcat_VrApi.log\n",
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      "investigation\\Quest-Pro\\BeatSaber\\PopStars-Medium\\stationary_boundary0.4\\logcat_VrApi.log\n",
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      "investigation\\Quest-Pro\\BeatSaber\\PopStars-Medium\\stationary_boundary_redo0.0\\logcat_VrApi.log\n",
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      "    CPU Level  GPU Level  CPU Frequency (MHz)  GPU Frequency (MHz)  FPS  Prd  \\\n",
      "0           3          4                 1382                  525   73  0ms   \n",
      "0           3          4                 1382                  525   73  0ms   \n",
      "0           3          4                 1382                  525   73  0ms   \n",
      "0           3          4                 1382                  525   73  0ms   \n",
      "0           3          4                 1382                  525   73  0ms   \n",
      "..        ...        ...                  ...                  ...  ...  ...   \n",
      "0           3          4                 1382                  525   73  0ms   \n",
      "0           3          4                 1382                  525   73  0ms   \n",
      "0           3          4                 1382                  525   62  0ms   \n",
      "0           4          4                 1478                  525   67  0ms   \n",
      "0           3          4                 1478                  525   55  0ms   \n",
      "\n",
      "   Tear Early Stale Stale2/5/10/max  ... altered_bandwidth altered_dropchance  \\\n",
      "0     0     0     0         0/0/0/0  ...              True               True   \n",
      "0     0     0     2         0/0/0/1  ...              True               True   \n",
      "0     0     0     0         0/0/0/0  ...              True               True   \n",
      "0     0     0     2         0/0/0/1  ...              True               True   \n",
      "0     0     0     0         0/0/0/0  ...              True               True   \n",
      "..  ...   ...   ...             ...  ...               ...                ...   \n",
      "0     0     0    24        0/1/1/13  ...              True               True   \n",
      "0     0     0     1         0/0/0/1  ...              True               True   \n",
      "0     0     0    19        0/0/1/16  ...              True               True   \n",
      "0     0     0    14        2/0/1/10  ...              True               True   \n",
      "0     0     0    23        0/0/2/12  ...              True               True   \n",
      "\n",
      "   bandwidth dropchance     device              app  \\\n",
      "0     999999          0  BeatSaber  PopStars-Medium   \n",
      "0     999999          0  BeatSaber  PopStars-Medium   \n",
      "0     999999          0  BeatSaber  PopStars-Medium   \n",
      "0     999999          0  BeatSaber  PopStars-Medium   \n",
      "0     999999          0  BeatSaber  PopStars-Medium   \n",
      "..       ...        ...        ...              ...   \n",
      "0     999999          0  BeatSaber  PopStars-Medium   \n",
      "0     999999          0  BeatSaber  PopStars-Medium   \n",
      "0     999999          0  BeatSaber  PopStars-Medium   \n",
      "0     999999          0  BeatSaber  PopStars-Medium   \n",
      "0     999999          0  BeatSaber  PopStars-Medium   \n",
      "\n",
      "                    app_details  is_record is_wireless       repetition  \n",
      "0                no_boundary0.0      False       False  ogcat_VrApi.log  \n",
      "0                no_boundary0.0      False       False  ogcat_VrApi.log  \n",
      "0                no_boundary0.0      False       False  ogcat_VrApi.log  \n",
      "0                no_boundary0.0      False       False  ogcat_VrApi.log  \n",
      "0                no_boundary0.0      False       False  ogcat_VrApi.log  \n",
      "..                          ...        ...         ...              ...  \n",
      "0   stationary_boundary_redo0.4      False       False  ogcat_VrApi.log  \n",
      "0   stationary_boundary_redo0.4      False       False  ogcat_VrApi.log  \n",
      "0   stationary_boundary_redo0.4      False       False  ogcat_VrApi.log  \n",
      "0   stationary_boundary_redo0.4      False       False  ogcat_VrApi.log  \n",
      "0   stationary_boundary_redo0.4      False       False  ogcat_VrApi.log  \n",
      "\n",
      "[22153 rows x 45 columns]\n"
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       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>999999</td>\n",
       "      <td>0</td>\n",
       "      <td>BeatSaber</td>\n",
       "      <td>PopStars-Medium</td>\n",
       "      <td>stationary_boundary_redo0.4</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>ogcat_VrApi.log</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>1382</td>\n",
       "      <td>525</td>\n",
       "      <td>62</td>\n",
       "      <td>0ms</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>19</td>\n",
       "      <td>0/0/1/16</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>999999</td>\n",
       "      <td>0</td>\n",
       "      <td>BeatSaber</td>\n",
       "      <td>PopStars-Medium</td>\n",
       "      <td>stationary_boundary_redo0.4</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>ogcat_VrApi.log</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>1478</td>\n",
       "      <td>525</td>\n",
       "      <td>67</td>\n",
       "      <td>0ms</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>14</td>\n",
       "      <td>2/0/1/10</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>999999</td>\n",
       "      <td>0</td>\n",
       "      <td>BeatSaber</td>\n",
       "      <td>PopStars-Medium</td>\n",
       "      <td>stationary_boundary_redo0.4</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>ogcat_VrApi.log</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>1478</td>\n",
       "      <td>525</td>\n",
       "      <td>55</td>\n",
       "      <td>0ms</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>23</td>\n",
       "      <td>0/0/2/12</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>999999</td>\n",
       "      <td>0</td>\n",
       "      <td>BeatSaber</td>\n",
       "      <td>PopStars-Medium</td>\n",
       "      <td>stationary_boundary_redo0.4</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>ogcat_VrApi.log</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>22153 rows × 45 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    CPU Level  GPU Level  CPU Frequency (MHz)  GPU Frequency (MHz)  FPS  Prd  \\\n",
       "0           3          4                 1382                  525   73  0ms   \n",
       "0           3          4                 1382                  525   73  0ms   \n",
       "0           3          4                 1382                  525   73  0ms   \n",
       "0           3          4                 1382                  525   73  0ms   \n",
       "0           3          4                 1382                  525   73  0ms   \n",
       "..        ...        ...                  ...                  ...  ...  ...   \n",
       "0           3          4                 1382                  525   73  0ms   \n",
       "0           3          4                 1382                  525   73  0ms   \n",
       "0           3          4                 1382                  525   62  0ms   \n",
       "0           4          4                 1478                  525   67  0ms   \n",
       "0           3          4                 1478                  525   55  0ms   \n",
       "\n",
       "   Tear Early Stale Stale2/5/10/max  ... altered_bandwidth altered_dropchance  \\\n",
       "0     0     0     0         0/0/0/0  ...              True               True   \n",
       "0     0     0     2         0/0/0/1  ...              True               True   \n",
       "0     0     0     0         0/0/0/0  ...              True               True   \n",
       "0     0     0     2         0/0/0/1  ...              True               True   \n",
       "0     0     0     0         0/0/0/0  ...              True               True   \n",
       "..  ...   ...   ...             ...  ...               ...                ...   \n",
       "0     0     0    24        0/1/1/13  ...              True               True   \n",
       "0     0     0     1         0/0/0/1  ...              True               True   \n",
       "0     0     0    19        0/0/1/16  ...              True               True   \n",
       "0     0     0    14        2/0/1/10  ...              True               True   \n",
       "0     0     0    23        0/0/2/12  ...              True               True   \n",
       "\n",
       "   bandwidth dropchance     device              app  \\\n",
       "0     999999          0  BeatSaber  PopStars-Medium   \n",
       "0     999999          0  BeatSaber  PopStars-Medium   \n",
       "0     999999          0  BeatSaber  PopStars-Medium   \n",
       "0     999999          0  BeatSaber  PopStars-Medium   \n",
       "0     999999          0  BeatSaber  PopStars-Medium   \n",
       "..       ...        ...        ...              ...   \n",
       "0     999999          0  BeatSaber  PopStars-Medium   \n",
       "0     999999          0  BeatSaber  PopStars-Medium   \n",
       "0     999999          0  BeatSaber  PopStars-Medium   \n",
       "0     999999          0  BeatSaber  PopStars-Medium   \n",
       "0     999999          0  BeatSaber  PopStars-Medium   \n",
       "\n",
       "                    app_details  is_record is_wireless       repetition  \n",
       "0                no_boundary0.0      False       False  ogcat_VrApi.log  \n",
       "0                no_boundary0.0      False       False  ogcat_VrApi.log  \n",
       "0                no_boundary0.0      False       False  ogcat_VrApi.log  \n",
       "0                no_boundary0.0      False       False  ogcat_VrApi.log  \n",
       "0                no_boundary0.0      False       False  ogcat_VrApi.log  \n",
       "..                          ...        ...         ...              ...  \n",
       "0   stationary_boundary_redo0.4      False       False  ogcat_VrApi.log  \n",
       "0   stationary_boundary_redo0.4      False       False  ogcat_VrApi.log  \n",
       "0   stationary_boundary_redo0.4      False       False  ogcat_VrApi.log  \n",
       "0   stationary_boundary_redo0.4      False       False  ogcat_VrApi.log  \n",
       "0   stationary_boundary_redo0.4      False       False  ogcat_VrApi.log  \n",
       "\n",
       "[22153 rows x 45 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "import os\n",
    "import re\n",
    "\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "\n",
    "def find_clumsy_directories(root='.'):\n",
    "    res = []\n",
    "    for dirpath, dirnames, filenames in os.walk(root):\n",
    "        for dirname in dirnames:\n",
    "            if 'clumsy' in dirname.lower() or 'validation' in dirname.lower():\n",
    "                res.append(os.path.join(dirpath, dirname))\n",
    "    return res\n",
    "\n",
    "def reset_timestamp(df):\n",
    "    # df['timestamp'] = df['timestamp'] - df['timestamp'][0]\n",
    "    #reset timestamp to 0\n",
    "    df['timestamp'] = df['timestamp'] - df['timestamp'].min()\n",
    "    return df\n",
    "\n",
    "def process_line(line):\n",
    "    timestamp = line.split(' ')[1]\n",
    "    content = line.split('  : ')[1]\n",
    "#     print(content)\n",
    "    pairs = content.split(',')\n",
    "#     print(pairs)\n",
    "    d = {}\n",
    "    cpugpu = re.search(\"CPU4/GPU=\\d+/\\d+,\\d+/\\d+\", content).group()\n",
    "    cpugpu = cpugpu.split('=')[1]\n",
    "    cpugpu = cpugpu.split('/')\n",
    "    d['CPU Level'] = int(cpugpu[0])\n",
    "    d['GPU Level'] = int(cpugpu[1].split(',')[0])\n",
    "    d['CPU Frequency (MHz)'] = int(cpugpu[1].split(',')[1])\n",
    "    d['GPU Frequency (MHz)'] = int(cpugpu[2])\n",
    "    for x in pairs:\n",
    "        tmp = x.split('=')\n",
    "        if tmp[0] == 'CPU4/GPU' or len(tmp) < 2:\n",
    "            continue\n",
    "        if tmp[0] == 'FPS':\n",
    "            d[tmp[0]] = int(tmp[1].split('/')[0])\n",
    "        elif tmp[0] == 'Free':\n",
    "            d[tmp[0]] = int(tmp[1][:-2])\n",
    "        else:\n",
    "            d[tmp[0]] = tmp[1].strip()\n",
    "#     print(pairs[0].split('='))\n",
    "#     d = {x.split('=')[0] : x.split('=')[1] for x in pairs}\n",
    "#     print(d)\n",
    "    d[\"timestamp\"] = pd.to_datetime(timestamp, format='%H:%M:%S.%f')\n",
    "    d[\"timestamp\"] = d[\"timestamp\"].timestamp()\n",
    "#     print(d)\n",
    "    return pd.DataFrame(d, index=[0])\n",
    "\n",
    "def add_to_dataframe(df, timestamp, key, value):\n",
    "    if key not in df.columns:\n",
    "        df[key] = np.nan\n",
    "    df.loc[timestamp, key] = value\n",
    "    return df\n",
    "\n",
    "def create_dataframe(file_path):\n",
    "    df = pd.DataFrame()\n",
    "    for line in open(file_path, 'r', encoding='utf-16'):\n",
    "        if len(line) < 300:\n",
    "            continue\n",
    "        new_d = process_line(line)\n",
    "        df = pd.concat([df, new_d])\n",
    "\n",
    "#     df.index.name = 'timestamp'\n",
    "#     df = df.reset_index()\n",
    "    if len(file_path.split('\\\\')[1].split('-')) == 3:\n",
    "        df['altered_bandwidth'] = file_path.split('\\\\')[1].split('-')[1] == 'bandwidth'\n",
    "        df['altered_dropchance'] = file_path.split('\\\\')[1].split('-')[1] == 'dropchance'\n",
    "        df['bandwidth'] = int(file_path.split('\\\\')[1].split('-')[2][:-4]) if file_path.split('\\\\')[1].split('-')[1] == 'bandwidth' else 999999\n",
    "        df['dropchance'] = float(file_path.split('\\\\')[1].split('-')[2]) if file_path.split('\\\\')[1].split('-')[1] == 'dropchance' else 0\n",
    "    else:\n",
    "        df['altered_bandwidth'] = True\n",
    "        df['altered_dropchance'] = True\n",
    "        df['bandwidth'] = 999999\n",
    "        df['dropchance'] = 0\n",
    "    df['device'] = file_path.split('\\\\')[2]\n",
    "    df['app'] = file_path.split('\\\\')[3].strip('-W')\n",
    "    df['app_details'] = file_path.split('\\\\')[4]\n",
    "    df['is_record'] = 'record' in file_path.split('\\\\')[5]\n",
    "    df['is_wireless'] = '-W' in file_path.split('\\\\')[3]\n",
    "    df['repetition'] = file_path.split('\\\\')[5].strip('record') if 'record' in file_path.split('\\\\')[5] else file_path.split('\\\\')[5].strip('replay')\n",
    "\n",
    "    df.to_csv(f'.\\\\{file_path.strip(\".log\")}.csv', index=False)\n",
    "\n",
    "    return df\n",
    "\n",
    "clumsy_dirs = find_clumsy_directories()\n",
    "\n",
    "df_aggregated = pd.DataFrame()\n",
    "\n",
    "# for clumsy in clumsy_dirs:\n",
    "for root, dirs, files in os.walk('investigation', topdown=False):\n",
    "    for name in files:\n",
    "        if name == 'logcat_VrApi.log': #and 'edge' in os.path.join(root, name):\n",
    "            print(os.path.join(root, name))\n",
    "            df_aggregated = pd.concat([df_aggregated, create_dataframe(os.path.join(root, name))]) \n",
    "                \n",
    "print(df_aggregated)\n",
    "df = df_aggregated\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "a2ce5649",
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.rcParams['font.family'] = 'Arial'\n",
    "custom_params = {\"axes.spines.right\": False, \n",
    "                 \"axes.spines.top\": False,\n",
    "                 \"axes.spines.left\": True,\n",
    "                 \"axes.spines.bottom\": True,\n",
    "                 \"xtick.bottom\": True,\n",
    "                 \"ytick.left\": True,\n",
    "                 \"axes.edgecolor\": \"black\",\n",
    "                 \"axes.grid\": True,\n",
    "                 \"axes.linewidth\": 1.5, \n",
    "                 \"axes.facecolor\": \"white\", \n",
    "                 \"grid.color\": \"lightgray\"}\n",
    "\n",
    "# sns.set_theme(style=\"whitegrid\", rc=custom_params)\n",
    "# sns.set_palette(\"deep\")\n",
    "# sns.set(font_scale=1.7)\n",
    "\n",
    "custom_mean = {\"marker\":\"d\",\n",
    "                \"markerfacecolor\":\"white\", \n",
    "                \"markeredgecolor\":\"black\",\n",
    "                \"markersize\":\"7\"}\n",
    "\n",
    "custom_outliers = {'marker': 'o', \n",
    "                   'markerfacecolor': 'grey'}"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b27fde87",
   "metadata": {},
   "source": [
    "## Bandwidth experiments"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "6e431792",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([   100,     30,     50,     80, 999999], dtype=int64)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[(df['altered_bandwidth'] == True) & (df['is_record'] == False) & (df['device'] == 'Quest-Pro')]['bandwidth'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "1bec20bf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 576x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(figsize=(8, 3), ncols=2, sharey=True)\n",
    "sns.set_theme(style=\"whitegrid\", rc=custom_params, font_scale=1.7)\n",
    "\n",
    "to_plot = df[(df['altered_bandwidth'] == True) & (df['is_record'] == False) & (df['device'] == 'Quest-Pro')]\n",
    "\n",
    "sns.boxplot(y=to_plot['FPS'], x=to_plot['bandwidth'], showmeans=True, meanprops=custom_mean, palette=\"colorblind\", ax=axes[0], flierprops=custom_outliers)\n",
    "axes[0].axline((0, 72), slope=0, color='red', linestyle='--', linewidth=1.5)\n",
    "\n",
    "labels = [item.get_text() for item in axes[0].get_xticklabels()]\n",
    "labels[4] = 'N/A'\n",
    "axes[0].set_xticklabels(labels)\n",
    "axes[0].set_yticks([0, 20, 40, 60, 80])\n",
    "axes[0].set_xlabel('Bandwidth Limit [Mbps]')\n",
    "axes[0].set_ylim(0, 80)\n",
    "axes[0].set_title('MQP')\n",
    "\n",
    "\n",
    "to_plot = df[(df['altered_bandwidth'] == True) & (df['is_record'] == False) & (df['device'] == 'Quest-2')]\n",
    "\n",
    "sns.boxplot(y=to_plot['FPS'], x=to_plot['bandwidth'], showmeans=True, meanprops=custom_mean, palette=\"colorblind\", ax=axes[1], flierprops=custom_outliers)\n",
    "axes[1].axline((0, 72), slope=0, color='red', linestyle='--', linewidth=1.5)\n",
    "\n",
    "labels = [item.get_text() for item in axes[1].get_xticklabels()]\n",
    "labels[4] = 'N/A'\n",
    "axes[1].set_xticklabels(labels)\n",
    "axes[1].set_xlabel('Bandwidth limit [Mbps]')\n",
    "axes[1].set_ylim(0, 80)\n",
    "axes[1].set_title('MQ2')\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.savefig('./figures/bandwidth_exp/fps_vs_bandwidth.pdf', dpi=300, format='pdf')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "d36887ce",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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ZMmQI9+7do2LFimzYsIEaNWoAOSvPvv3220RFReHl5cXnn3+uxgV55T127Bhjx45Vr+Orr76ibdu2QE4AHhgYyKJFi9T0KVOmMHToUDV98+bNfPLJJ2r6e++9p3ZZ/uKLL1izZo2aNnLkSCZOnKjm1c9nr6coCv/88w9Llixh2rRpPPnkk6xatYpnn33WYBHNffv2ER8fz9ixY9X6WrVqVamORfNFsdGmTZuUhg0bKu+++66thygVPvjgA0Wr1Sp+fn5GaX5+fopWq1U+/fRTk3nPnTunaLVaRavVKpcvX1a3BwcHK1qtVmnSpIly584dk3nHjx+vaLVaZfLkyTaVOzk5WQEUQImNjbXpGGVNSkqK8s8//ygpKSklXZSHgtRX/kh9WU/qKn+kvvJH6it/ClRfv/+uKLt35/z7/9LT05UGDRoogFKhQgVl9uzZhVbWklYcbcrmPvYvv/wynTp1Ytu2bbz//vvqE2Txr969ewOwZcsW9Wl+bitWrADA19fXYBGrNm3a4OnpSVZWFl9//bVRvrCwMH7//XeAMrXqrxBCCCFKka5d4Zlncv79f05OTixduhRvb2+8vLzMrtMjTLO5K87ChQupU6cOx44d48cff+THH3/E1dUVNzc3i/OvazQafvzxR1tP+1B54YUX+O6777h69SqjRo1i/vz5NG7cmMTERD7//HN2796NnZ2d0bz+dnZ2TJ48mRkzZrB69WoqVqzIiBEjKF++PMHBwUyfPh2dTkeHDh3Ur8yEEEIIIUqD3r178/XXX/P+++9Tr169ki7OQ8XmwH7NmjVGc9jfvXuXu3fvWsz3MM5jbysnJyc+//xzhg8fTlhYGP3798fFxYWUlBR1/teZM2fSrl07o7wDBgwgJCSE77//nqVLl+Lv74+Tk5O6EEWdOnVYtmxZcV6OEEIIIYR4gNkc2MuTYus0bNiQHTt2sHLlSn7//Xeio6OpWLEizZs3Z9SoUepMOqbMmTOHjh07smHDBkJDQ0lLS6N27do89dRTjBs37qGbOlQIIYQQQvXHH5CeDuXKGXTHEbazObBfv359YZbjoTVnzhx1GiZzqlWrxsyZM5k5c2a+j//ss8/y7LPP2lo8IYQQQogHk58fREZCjRoQEVHSpSkVbB48K4QQQgghhHhwSGAvhBBCCCFEKWBVV5x169YB4Orqqq6+qt9mi1dffdXmvEIIIYQQonSrW7curVu3NpgOXOTNqsD+k08+QaPR8Oijj6qBvX5bfmk0GgnshRBCCCGEWY0aNTK5lo+wzOrBs7mntbS0TQghhBBCCFH8rArs9+/fn7Ozg4PRNiGEEEIIIUTJsyqwr1GjhlXbhBBCCCGEECVDZsURQgghhBCiFLDqiX1ycnKhnrRSpUqFejwhhBBCCPFwyszK4tK5c0bb3dzc8Pb2LoESPbysCuzbtm1baCfUaDSEhoYW2vGEEEIIIcTD59axY7wwoD9p6RkwZIhRur29HWvXrqNp06YlULqHk1WBvcx+I4QQQgghCtOdO3dIS8/g1fb38HLNNkg7e8uBnf84c/36dQns88GqwH7ChAlFXQ4hhBBCCFEGeblmU9NdZ7AtKlGGgdpCAnshhBBCCCFKAbkdEkIIIYQQxa7a8uVMiYzksUPxJV2UUkMC+wK4du0aLVq04LXXXrO4X0xMDLNnz6Z79+489thjdOzYkTfeeIOjR4/meY5du3bh5+fH448/TosWLejduzdffPEFKSkphXUZQgghhBBFIiEhwWya25Yt+MXGUu90YqEfu6ySwN5GycnJvPPOO6SlpVncLzw8nAEDBrBhwwYiIyMpX748CQkJ/Pbbb7z66qt8++23ZvPOnz+fyZMnc+zYMTIyMrCzs+PSpUv4+/szYMAA4uLiCvuyhBBCCCEKRUREBD179iQiIgKAnTt30qhRI3bt2lXoxxY5JLC3wZ07dxg7dixnz561uF9WVhZjx44lLi6OZs2asWvXLo4fP05wcDDDhg1DURTmz5/P8ePHjfJu27aNNWvWYGdnx3/+8x9OnjxJSEgI69at45FHHuHatWtMmzatqC5RCCGEEKJAkpKSyM7OJikpiYyMDCZPnkxYWBiTJ08mIyOj0I4t/mXV4Fnxr5CQEKZMmUJkZGSe+27fvp0rV65QsWJFVq1ahbu7OwCurq7MnDmT+Ph4du7cydKlSwkMDFTz6XQ6/P39ARg9ejTDhw9X03x9fVm1ahX9+vXj8OHDHDlyhA4dOhTyVQph2d27d3n77beJiorCy8uLzz//nMqVK5d0sR5YOp2OkJAQYmNj8fDwoFWrVtjb25d0sUolS3Wd1+tQkNcpIyODzZs3Ex4eTs2aNRk4cCBOTk5qenJyMh988AERERH4+Pgwd+5cdbHG1NRUli1bxo0bN3j00UeZNGkSzs7OVpXLmrwnT54kNDSUu3fv0r59e6uvuSTb7YNYrqI8b1Ee21Lby6vdRkVF4efnR2JiIq6urgQEBODl5WWQPmTIEJKSknBxcWHDhg0G6bn5+/tz+fJlNm7cyNChQ1m+fDkyNUvhk8DeSsnJycyePZvt27ejKAq1a9fGw8ODY8eOmc2zadMmAPr3768G9bmNHTuWnTt3cvz4cfUNB3D48GGuX7+ORqNhxIgRRvkaNGhA9+7d2bt3Lz///LME9qJY9e3bl4iICHV9i+joaLp164aPjw/btm0r4dI9ePbv38+iRYuIiopSt3l5eTF16lR69OhRgiUrfSzVNWDxdSjI67Rs2TICAgLQ6f6drm/p0qX4+fkxadIk/Pz8CA0NVd8zly5donPnzjRp0gQPDw8OHDigpgUFBbF582a6dOnC0qVLLZZrx44dNufN65rzqq+i9CCWqyjfx0V5bEttr02bNhbbbYcOHUhPT1fz3r59m169elGuXDn1oWLu9ISEBIP03OLj45kzZw6vv/46gwYN4uDBg8yePZtBTk7IurKFS6M8BKtPnT9/vljO06hRI7Np586do3///mg0Gl5++WXeffddPv74Y7Zu3UqnTp345ptvDPZPSUmhdevWZGdns3z5cnr27GnyuB06dCA+Pp6PPvqIwYMHAzkfWqtXr6ZRo0b8/PPPJvMFBgYyZ84cqlWrxqFDh/J9rffu3VPv2GNjY6lWrVq+j1HWpKamcvnyZerVq2fwRKws6du3L+Hh4Xh5eaHVanF1dSUxMZGwsDCio6OpWbOmGtxLfeX8wZ42bRqenp4G9XXhwgWio6NZuHCh+odb6st6purKUl3rA6b7263+dXj11VdZt26dVa/T/ZYtW8batWvNvieqVq3K7du3zaabKpc+rWnTpoSGhubrmqzJm9c151VfluqjoAryOhZWue5vX/l5Hxfm9Rb02H5+fpw9e9amtmdvb49Op7OY11L+8uXLc+TIEc6dO8eQIUNo2LAhu3fv5tKlS1SrVo3Y2FgaNGjAoIwMVqamklLJnpMzaxqU/9g1R9YFVWTevHn06tXL6Pr0x96wYQONGze2qY6KW2pqapF/vj8UT+z1AXVR0mg0hIaGWkzv1q0bEydOtGoFtKtXr5KdnbOKWt26dc3uV6tWLeLj47l06ZK6Tf97vXr1zOarXbs2AHFxcSQkJFClSpU8yyREQdy9e5eIiAi8vLzw9fVV35Pu7u60b9+eoKAgIiIiuHv3rnTLIeer9UWLFuHp6WlUX76+vgQHB7N48WK6du0q3XIKKK+6DgoK4vbt27Rr1w47OzuDtODgYAIDA6levXq+X6eMjAy1a4Kp98SRI0eIjY21+J6Ji4szKpc+rz4wvz9vu3bt2LlzJ9WqVTN73NDQULPXFBQURGBgoM31VVTt1tLrqL9mDw+PYn0/FeX7uCiPnZycTGhoqE1t79ChQ+rNqLm8MTExajnNpetvxFJTU9m8eTOLFi1SHyJ6eHgwa9Yspk2dygTAfJQk8uuhGTyrKEqR/1jSqFEjVq5cafWyxjExMerv5vqbAXh6egI5T83vz6tPs5Tv/rz369Gjh8mf3r17530RQuTy9ttvoygKWq3W6EZbo9HQsGFDFEXh7bffLqESPlhCQkKIiooyW19arZZbt24REhJSQiUsPfKq64YNG5KVlcXt27eN0rRaLVlZWXh6eub7ddq8eTM6nc7seb28vPJ8z+h0OpPlspT39u3b6HQ6GjZsaPG9aO6aPD09ycrKsrm+iqrdWnod9ddc3O+nonwfF+WxP/jgA5vbnqOjo1Wf9RkZGRbT/fz8UBSFW7duUbduXd58802DfSdMmEDdWrWYbGdnMQaLjIzk3LlzRj9Xr17Nd72UBQ/FE3vIaSwfffSRwaCOwpCRkcGHH35YqMeEnLtlPUtfu5QvX95o/3v37gFQoUIFs/nKlStn8lxCFBX90xdXV1eT6S4uLgb7lXX6G+686svSjbmwjrV1nZ6ebjbN3BNRS69TeHi4xfPqn4TaUi5LefX753Vcc9dUkHIVZbu19Dpae82FXa6ifB8X5bH1U0Da8hpnZmZalVe/n7n0xMRErly5QmJiIh9++KFR/Obk5MQbEycyZcoULijmnzN/+eWXfPnll2bThaECB/Y7duzg119/JTw8nHv37hkMwjBFo9Gwb98+m87Vt2/fQu+blJKSUiSBvb4eHB0dLXYj0jf0rKwsdZv+d0dHxzzz5T6XKfv37ze5PXcfeyGs4eXlRXR0NImJiSYHg+unHLP0DVVZ4uHhAZBnfen3E7aztq5zPxC5P83c56il16lmzZoWz6vvjmlLuSzl1e+f13HNXVNBylWU7dbS62jtNRd2uYryfVyUx/bx8eHSpUs2vcb62COvvOZiFH26q6srdevWpXLlyqxYsYIJEyYYxC4ZGRms8PennaMjbo86cc/MtYwfP55OnToZbb969Srvv/++mVxlV4G64rz99ttMmzaNvXv3cu7cOW7cuEFkZGSeP2WB/s2SmZlp8Ssm/Tyuud8g+qf45u6Gc+e7P68QReXzzz9Ho9EQFhZm1KYVRSEsLAyNRsPnn39eQiV8sLRq1QovLy8uXLhgsr4uXLiAt7c3rVq1KqESlh551XVYWBgODg5UrVrVKO3ChQs4ODgQHR2d79dp4MCB2Nvbm31PREVF5fmesbe3N1kufV5T11S1alWL59W/F81dU3R0NA4ODjbXV1G1W0uvY17XXFTlKsr3cVEee+7cuTa3vczMTKs+6/VddsylBwQEqN3Krly5wvLlyw329ff358r169ytW5egvuYfCNWoUYPGjRsb/dSpUyff9VIW2BzY/+9//2PPnj0oioKdnR2PPfYYXbt2NdunW//TvXv3fJ/r008/5ZNPPjF5Z1lQ5cqVU49fmCpWrKj+buqrLr3U1FQAg6fn+ryWVrXNnSZP3kVxqFy5Mj4+PkRHRxMUFER8fDyZmZnEx8cTFBREdHQ0Pj4+MnD2/9nb2zN16lSio6MJDg42qK/g4GCio6OZMmWKDJwtBNbUdVZWFkePHjWZNnToUGJiYvL9Ojk5OeHn52f2PaEfYGjpPaPT6YzOq8/bpEkTk9d09OhRdDqdxeM2adLE7DXFxMQwdOhQm+urqNqtpdcx9zUX5/upKN/HRXnsSpUqqe0nv20vLi4OOzs7i3kVRVH/byq9XLly6re3zs7ODBw4kNmzZxMXFwfkdC+aM2cOL7/8sswCVshs7orz448/Ajmzunz99dfqV5JFYcCAATbnzcrKwsHB/GXa29sX6PjmeHv/OzNrdHQ0tWrVMrmffqBs9erV1W1eXl6cPn3aYEqp++VOk6/yRXHZtm2bOo997jao0WgMproUOXr06MHChQtZtGgRBw8eVLd7e3sX6ZSBZZGlul60aBGAxdehWbNmNr1OkyZNAiAgIMDgPeHg4MDw4cMN5rG//z3TtGlTdR77+9O6du1qMBe9qWvSz2Of37x5XbM19VVUCvo6FneZCnreojx2QECAxbann8feXLvt0KEDMTExRnn1U1nmlZ7bxIkT2b17Nx9++CHLly9Xu0BPnDjRaFCtKBibA/vLly+j0Wh47733ijSoz0tSUhJ//PEHPXv2NLjrW7NmDWvWrOH27dt4e3szfPhwgxVci1rt2rVxdHQkMzOTa9eumQ3sr1+/DkD9+vXVbQ0aNGDPnj1cu3bN7PH1+Tw8POQJqShW27Ztk5Vn86FHjx507dpVVp4tBnnVtaW0grxOkyZNYvz48WZX8AwICLB55VlL5erRo4dVefXTXzZp0sRg5dmC1FdRehDLVZTv46I8dl5tz1K7PXLkiMWVZ/Xp1qw86+7unjO95bRpPPnkk3z11VcsWrRIpuouAjYH9vouJI899lihFSa/9u7dy8yZM0lMTGTr1q3qAlNff/01ixYtQqPRoCgKN2/e5LPPPuPq1at89NFHxVI2R0dHWrVqxdGjRzly5AhdunQx2uf8+fPEx8cD0LZtW3W7r68v/v7+nDt3zuyc4IcPHwagXbt2RXQFQphXuXJlvvvuu5IuxkPD3t6eNm3alHQxygRLdZ3X61CQ18nJyYmhQ4eaTa9UqRJLly41mebs7Mx7771nU7msyfv4449TuXJl6tWrZxQsFqS+itKDWK6iPG9RHttS28ur3Xp5eVmc8MTLy4udO3datbjehAkTWLlyJYMHD0ar1fLmm2+S2bkzW86fp1I8XBwvEy8UBpv72NeoUQP4d/RzcQsPD2fy5MncvXsXRVHUQblpaWmsXLkSyBmR7efnR5s2bVAUhe+//55jx44VWxn1c8Vv2bJF7VeW24oVK4CcQD73IlZt2rRR5xn++uuvjfKFhYXx+++/A6ir1QohhBBCPEhcXFyws7PDxcUFJycnli5dSsOGDVm6dClOTk44XbtGvbQ0XOLNTxZizbHFv2wO7Hv06IGiKOzcubMwy2O1gIAAsrKycHd3Z82aNWo/tD///JPk5GQ0Gg2LFi1i5syZBAQE8NRTT6EoCv/73/+KrYwvvPACderUISkpiVGjRnHu3DkgZwqpuXPnsnv3buzs7JgwYYJBPjs7OyZPngzA6tWrWblypTpYNjg4mHHjxqHT6ejQoYPBk34hhBBCiAeFj48P+/btw8fHB8h54Hn+/Hl69epV6McWOWwO7EePHk21atVYtWqVwYCP4hIUFIRGo2HKlCl07NhR3X7gwAEAqlWrxpNPPqluHzlyJADHjx8vtjI6OTnx+eefU6VKFcLCwujfvz9t2rShffv2BAQEADBz5kyT3WkGDBjAK6+8gqIoLF26lDZt2vD444/z6quvcuvWLerUqcOyZcuK7VqEEEIIIfKrKPvRSx99Y1b1sV+3bp3J7U8++SRbt25l3LhxPP7447Rq1YoqVarkOa/6q6++mv+S3ufWrVsAtG/f3mD74cOH0Wg0BsE+oA5eNdUlpig1bNiQHTt2sHLlSn7//Xeio6OpWLEizZs3Z9SoUTzxxBNm886ZM4eOHTuyYcMGQkNDSUtLo3bt2jz11FOMGzdOvn4SQgghhBAqqwL7Tz75xOzqqfoBqidPnuTkyZN5Hkuj0RRKYJ+SkgIYzhd/7do1bt68iUajMQr49Qs6WVosKr8+++wzPvvsszz3q1atGjNnzmTmzJn5Psezzz7Ls88+a0vxhBBCCCFEGWJ1VxxFUcz+5JVuav+C0i9zHBUVpW7766+/1N/vf2J//vx5ICfIFkIIIYQQorSx6on9/v37i7oc+daiRQv27dvHli1bmDlzJllZWWzZsgWNRkPjxo3x9PRU901LS+PLL79Eo9HQvHnzEiy1EEIIIYTITadoCI83nIr19j2bh4GWaVYF9vqpLR8k/fr1Y+/evQQGBnL58mXu3LnD+fPn0Wg0vPjii+p+gYGBbNq0iYsXLxqlCSGEEEKIkmFnlxO8p2RoWPCr8bhBe3s7swt8CtNsXqDqp59+AqBv377qC2NJamoq3333HXfv3mXGjBm2nlbVs2dPXnjhBX788UeDpYvbtGljMLf7qlWriImJAWDgwIF06tSpwOcWQgghhBAFY///8aO7uzsbNmwwSndzc8Pb27u4i/VQszmwnzFjBnZ2djzzzDMWVxrTy8rK4vPPP8fV1bVQAnvIGdT75JNPsnv3bjIyMvD19WXIkCEGNxp16tTB3t6eMWPGyGJOQgghhBAPilmzIDkZx0qVaNy4cUmXplSwObCHnAGz5mbLuV9ISAgA6enpBTmlkeeee47nnnvObPrSpUtlnlMhhBBCiAfN2LElXYJSJ8/APjs7m5EjRxIREWEyvVevXnkG95mZmcTFxaHRaHj00UdtK6mNJKgXQgghhBBlQZ6BvZ2dHcOGDWPChAlGaYqicPPmzXydcNSoUfna3xrx8fHs3buXQ4cOERUVRVJSEu7u7tSoUYOuXbvSrVs3q7oLCSGEEEII8bCyqitOz549ef3114mOjla3bd26FY1GQ58+fXBwsHwYR0dH3Nzc6Nixo9HCUQW1atUqVq5cSWpqKvDvAlRXr17l5MmTbN++napVq/L+++9b7LIjhBBCCCGK0a1bRN+8SeK9e2R5eBgly+DZ/LO6j/2kSZMM/r9161YA5syZU2JPwz/++GMCAwPVYN7T05PatWvj7OzMvXv3uHr1KnFxccTFxfHOO++QmJjIK6+8UiJlFUIIIYQQ/9K1bo3nrVvg6MizTZsapdvZ27Nu7VqamkgTptk8ePbNN99Eo9Hg6OhYmOWx2uHDhwkICECj0dCmTRvee+89ky/86dOn+eSTTzh9+jRz586lTZs21KtXrwRKLIQQQggh9LKzs7EHsp0ciHnOcAHRcpEJVP47nOvXr0tgnw82L+s1ceJEJkyYkGc3nKKybt06AFq3bs23335r9kVv0aIF69evp3nz5uh0OtauXVucxRRCCCGEEJbYach0r2Two6tUrqRL9VB6aNfr1a8yO3ny5Dy/NXBycmLy5MkoikJwcHAxlVAIIYQQQojiY9Xj9sJcNECj0RAaGlrg4yQkJABQv359q/Zv0qQJAFFRUQU+txBCCCGEEA8aqwJ7/eDUB4m3tzfXr1/n+vXrNG/ePM/9Y2NjAahevXpRF81Ieno6AQEB7Ny5k6tXr5KVlcUjjzzCk08+yejRo/Hy8jKb9+rVq6xcuZLDhw+TkJBAlSpVaNeuHWPGjKFRo0bFeBVCCCGEEPmjj11E8bAqsDc1hz3AjRs32LZtG5Dz5Lxnz57Uq1cPFxcX0tPTCQ8P58CBAxw7dgwHBwfGjx9faANXe/XqxZdffsny5cv56quv8tx//fr1AMU+5WVSUhLDhw/n7NmzADg4OODg4MC1a9e4du0aP//8MytXrqR169ZGef/++2+GDx9OSkoKAC4uLsTGxrJjxw727NnDggUL6NWrV7FejxBCCCGENSIiIujXrx8///wzPj4+7Ny5kylTprBkyZI84xdNWiYAt2/fLo6ilho2B/YJCQn069cPOzs73nvvPYYNG2Yy7+jRo9mzZw9Tp05l3bp1/PTTTwUqsN7rr7/OgQMHOHjwIG+//TYfffSRyTtCnU7Hl19+yffff0/t2rUZN25coZzfWrNnz+bs2bO4urry0Ucf8fTTT+Pg4MDJkyeZOXMmV65c4e2332b37t1UqlRJzXf37l3GjRtHSkoKnTt3Zs6cOXh7exMbG8u8efP45ZdfmDFjBk2bNqVWrVrFek1CCCGEEHlJSkoiOzubpKQkMjIymDx5MhcvXmTy5Mn07NkTjYW8dlk6ANLS0oqnsKWEzVParFixgtjYWEaMGGE2qNd75plnuHjxIv7+/vj7+/Pxxx/belpVYGAg3bp148qVK/z666/88ccfdOjQgYYNG+Li4kJaWhrh4eEcOnSI27dvo9FocHNzY/r06SaPp9Fo+OKLLwpcrtzu3LnDrl27AHj//ffp3bu3mta6dWtWrFjBM888Q2xsLL///jvPP/+8mr5+/Xri4+OpUaMG/v7+lCuXMzrcw8ODxYsXEx0dzcmTJ1m+fDkLFiwo1HILIUoHnU5HSEgIsbGxeHh40KpVK+zt7Uu6WA+svOorIyODzZs3Ex4eTs2aNRk4cCBOTk5AzvgtPz8/EhMTcXV1JSAgwKCbZWpqKsuWLePGjRs8+uijTJo0SV0DxlJaXue1lKZP37RpE+fOnaNx48YMHTrUIP1hbCMFKfODer0FKVdebaAgeW/cuMHgwYNJTU3F2dmZjRs38uijj6rp586dY+jQoSiKgkajITAw0Oy4TH9/fy5fvszGjRsZOnQoy5cvx3R/EFEQGsXGDvQ9evTg5s2b7Ny5k7p16+a5f3h4OE899RSenp4cOHDAllMaaNSoERrNv/d6+kZ1P/3lmUq7P++5c+cKXK7cTp06pS6ItWfPHmrXrm20z5NPPklMTAxTpkxh7NixanmefPJJYmNjeffdd3nttdeM8u3fv5/x48fj7OzMkSNH8r1I2L1799RvCGJjY6lWrVo+r67sSU1N5fLly9SrV6/EFmV7mEh95U9h19f+/ftZtGiRwYQBXl5eTJ06lR49ehT4+CWpKNpWXvW1bNkyAgIC0Ol0arq9vT1+fn58//33pKenG4xH02g0lCtXjiNHjjB58mQOHDhglN6lSxcAs2lLly61eF7AbNqkSZMs5p00adJD2UYKUmZr8xb3Z1dBrimv17ggedu0aUN2drZR27Szs+P48eO0atUKjUZjlK4oCiEhIUBO4D9kyBD8/f3p3bu3GtCPHz+eDRs2cM7JCe/YWG65VKDFrBEG5av0zw0q/x3B+PHjGTNmjMVreVjob5CKks1P7PWDUatWrWrV/hUrVgRyupgUhkceeaRQjlOUXF1d1d9PnTplFNjfunWLuLg4AIPuNFeuXFHrt2PHjiaP7evri52dHampqRw7dozOnTsXcumFEA+r/fv3M23aNDw9PencuTOurq4kJiZy4cIFpk2bxsKFCx/YwK0k5FVfXbp04Y8//sDLywutVqumh4WFqWujmEqLjo6mdevWZGdnm0z/448/zOb9448/6Nu3L+Hh4fk+79q1azl+/Dhnz541m379+nUOHDjwULWRgrTrB/U9UZByLVu2jLVr11psH+aC+7zyrlu3DkVRzLbrVq1aAeDp6Wk2XR/cA2qPiNmzZ6v/btiwgalt25J2+TKxXWQykMJi8xP7nj17EhkZyZo1a+jQoUOe++/du5eJEydSu3Ztdu/ebcspHzrZ2dk899xzXLt2DTc3N+bMmUP37t1xcHDg7NmzzJw5U/16dMuWLepiX7/++isTJ05Eo9Fw+vRptRvO/fRP+6dPn86oUaPyVTZ5Yp9/8gQ6f6S+8qew6kun09GnTx8g5wHA/d9sBgcHo9Fo2L59+wPRBcEWhdm2rKmv6OhoqlevTvv27Q3S09LS2LNnD56enibzBgUFERMTg7u7O506dTKZHhcXR+/evbGzszNIO3LkCLGxsSaPnZ2dzc6dO6lWrZpRmfLKa036g9hGCtKu85u3uD67CnJNGRkZdOzYEQ8PD7Nt7/bt2xw6dMioW05eef/8808SEhLMto/Dhw8TFxeXZ7sPDAwEYMCAAVy8eJFFixYxefJkdd8lS5Ywbdo0GjRoQNILvmS6/zvOEOSJva1sXqCqRYsWKIrC4sWL8xzYcOfOHRYtWoRGozH7BLo0srOzY/78+bi4uHDnzh3eeustWrZsSatWrXjxxRe5ePEiAwYM4LvvvjNYwTcmJgYANzc3s0E95Nwpw7/fnpjSo0cPkz+5+/sLIUqPkJAQoqKi0Gq1Rl0QNRoNWq2WW7duGTxNK8usqS9FUfD09DRK/+OPP1AUxWzehg0boigKGRkZZtN1Op3RrB8ajQYvLy+zx759+zY6nY6GDRuaPK6lvNakP4htpCDt+kF9TxSkXJs3b0an01lse1lZWWzevDnfeTMzMy22DxcXF6vavZ+fH4qicOvWLerWrcubb75psO+ECROoU6cOUVFRD+S06g8rmwP7ESNGoNFoOHv2LIMHD+bgwYNkZmYa7JOens6uXbt46aWXuH79OuXKlWPkyJEFLrQlSUlJxMbGkp6eXqTnsVbLli3ZunWrOtgkKyuL1NRUIOepi06nU/+vl5ycDECFChUsHrt8+fIG+wshhP5GP3dXwNxcXFwM9ivrrK0vU0+u9X/z8sp7/9/G+9NN/b3SP8E3dWz9/ubOaymvNekPYhspSLt+UN8TBSlXeHi4VXn1++Unb17tWt8nP69zZ2dnc+XKFRITE3njjTeMvjlwcnJi/Pjx3L17l6z4RJPHEvlncx/7Zs2aMXnyZJYsWcL58+cZN24cDg4OeHt7U758eVJSUoiKikKn06mDU+fPn0/NmjULs/xATjef//3vf5w8eZKkpCR1u4eHB23btmXw4MG0adOm0M9rjQMHDvDuu++q16/vinP06FHmz5/Ptm3bOHHiBBs3blSfwGdlZQHg6Oho8dj6N4l+f1P2799vcnvurjhCiNLDw8MDgMTERNzd3Y3S9Z+R+v3KOmvrK/cAQz1HR0d0Ol2eec19luvTTX0zm52dbbZc+v3NnddSXmvSH8Q2UpB2/aC+JwpSLn0slVdeUzFXXnkdHR1JS0szm66/yc3r3HZ2dtStW5fKlSuzYsUKJkyYYDRj05fLl1Pf2ZmnbsWxpUENo2OJ/LP5iT3A2LFjWbBgAdWqVUNRFDIzM7lx4wYXLlwgIiKCrKwsFEWhTp06rF+/nmeeeaawyg3kzKU/bNgw3nrrLQ4cOEBiYiKKoqg/MTEx7Nq1i2HDhvHee++RkZFRqOfPy9mzZ3nzzTdJSUnhu+++o3///ri6ulKhQgW6du3Kxo0bqVGjBpGRkSxatEjNp38Sb+4pj57+evK6ARBClB2tWrXCy8uLCxcuGH29rSgKFy5cwNvbWx38VtZZU18ajcZkd4GuXbui0WgICwszmTcsLAyNRoOjo6PZdHt7e6NJKBRFISoqyuyxq1atir29vdnzWsqbO/1haiMFadcP6nuiIOUaOHCgxTYQFhaGg4MDAwcOzHdeR0dHi+0nKSnJqnYfEBCgdv26cuUKy5cvN9jX39+fq1evsjU1lQ/+eHC6fT3sChTYA/Tt25f9+/ezevVqRo4cyXPPPccTTzxB7969GTNmDAEBAezatavQn5jrdDpee+01jh8/jqIouLm58fzzzzNhwgTeffddJkyYwHPPPUfFihVRFIWffvrJ7Bz2RWXlypVkZmby/PPP06iR8YhvNzc33njjDQB27drFvXv3gH9nEMpr7IK+C488eRdC6Nnb2zN16lSio6MJDg4mPj6ezMxM4uPj1YGgU6ZMeWAGRZY0a+qrS5cuxMTEEBQUZJAeEhKCoihER0cbpQUFBREdHY1Go1H/bypdp9MZnVc/+NDHx8fksYODg9HpdGbPGxMTQ5MmTSymd+nS5aFqIwVp1w/qe6Ig5XJycsLPz89i27t/zQJr88bHxwOYTY+Njc2z3SuKos5n7+zszMCBA5k9e7Y6E2BsbCxz5sxhTPnyPFaEdVwW2dwVJzcnJyeefPJJnnzyycI4nFV++OEHQkND0Wg0jBs3jgkTJph8cp2SksKnn37K5s2b2b17N8899xxPP/10sZTx9OnTABafAuhveLKysoiIiKBhw4Z4e3sDOd9IZGRkmF1oIjo6GoDq1asXZrGFEA+5Hj16sHDhQhYtWsTBgwfV7d7e3g/kNIYlzZr60s/5rf/cBXBwcGD48OF8//33xMTEGKRpNBrKly9vMI/9/eldu3YFMJuWex57U+cFzKblnsfeXLp+/vSHpY0UpF0/qO+JgpRLP5Wlpde4IHnbtGljsl3b29ur89ibSgeMBvxOnDiR3bt38+GHH7J8+XI+/PBDAD6sVAnuG2coCsbm6S5L2uDBg9UFoD766KM89580aRK7d+/miSee4Jtvvin6ApIzDiEjI4O5c+fy8ssvm9wnIiJCfeNu3ryZ5s2bG2zbuXMn9evXN8qXnJxM27Ztyc7O5ptvvqFTp075KptMd5l/Mn1j/kh95U9R1NeDuspmQRVV2yqtK88GBgbKyrP5yFsSn12ldeVZ/QJVGzZs4JdffmHatGkEBgYydOhQFi1axIT583GMjpYFqgqRVYG9fgBmhQoV1DnrzQ3KtEZh3Bm3bduW5ORkduzYQb169fLc/9y5cwwYMIDKlSsTHBxc4PNb46mnnuLGjRu88MILfPrppyb32bNnD2+99RZ2dnYcOXIENzc3ALp3705kZCQzZ85k2LBhRvn27dvHm2++iaOjI0FBQfnujiOBff5JoJo/Ul/5I/VlPamr/JH6yh+pr/yxVF+5A/t69erx2GOPcfHiRbRaLf/88w+aRx+VwL6QWdUV580330Sj0fDoo4+yZ88eg235pdFoCA0NzXe+++lnKLB25Vt995biHEDbtWtX1q1bx86dOxk9erTRDUhmZiarVq0Cchan0Af1AL1792bVqlWsW7eOl156yaAh6HQ6vv76awCef/556WMvhBBCiAeOi4sLdnZ2uLi44OTkxNKlS5kyZQpLlizByckJS1OEZDvkfGOhn1BEWMfqwbOmHuznnoEmPz+FQavVAnDmzBmr9r906RIAtWvXLpTzW2PMmDFUqVKF9PR0RowYwb59+9QbksuXLzN27FjOnDmDo6MjU6dONcj72muv4ebmxo0bNxg7dqw672xsbCzvvPMOISEhODs7M3bs2GK7HiGEEEIIa/n4+LBv3z58fHyAnIeW58+fp1evXnnmVcrnjJu09gGuyGHVE/t169YBhndN+m0lxc/Pj1OnTrF48WIef/xxi4s5KYrCf//7XzQajdm+7kWhevXqfPXVV4wfP56YmBi160z58uXVeV6dnZ1ZsGABjz1mOC7czc2NZcuW8frrr3P06FF69uyJq6srSUlJKIqCvb09ixcvpk6dOsV2PUIIIYQQ+VGlSpWSLkKZYlVg365dO6u2Fac+ffqoCzsNHTqU//znP7Rt29Zov8uXL/Pxxx9z7NgxnnvuOQYPHlys5WzRogXbt29n3bp1/P7779y4cYP09HRq1arFE088wahRo8wu2tWhQwe2bdvGypUrOXToEPHx8bi5udG2bVvGjBlD8+bNi/VahBBCCCHEg8vm6S5XrlxJ9+7d1S4xRSmvm4jz58/z6quvUrlyZerWrYuzszNpaWlEREQQExMD5MwXGxsby/Dhw1m7dm2Rlzk3d3d3Jk2aZHHqKXNq1aplduCtEEIIIcTDKqtaNeLj44mpKIOUC4vNgf2yZcv4/PPPqVGjBt27d6d79+60a9cOO7sCr3llJDEx0WK6vt/+nTt3OHnypMl9srKyOHbsmE0DfoUQQgghROG6tnkzQ4YMIeY56YFQWGwO7N3c3Lhz5w4RERGsX7+e9evX4+rqypNPPkmPHj3o3LmzuoJqQQ0YMKBQjiOEEEIIIR4sDneNF6myT04vgZI8/GwO7I8cOcLff//NgQMHOHDgAKGhody9e5cdO3awc+dOHBwcaNeuHd27d6dHjx4GC3Xkl3RFEUIIIYQoXdzc3HAqVw73wxdNptvZ21OrVq1iLtXDzebAXqPR0KJFC1q0aMFbb71FXFwcBw8e5MCBAxw+fJikpCQOHTrE4cOH+fjjj2ncuLHaZadJkyaFeQ1CCCGEEOIh4+3tzU9bt3Lnzh2T6W5ubuo6RMI6Ngf296tWrRovvPACL7zwAjqdjpMnT/LHH39w4MABLl26xLlz5zh37hxffvlloSxQJYQQQgghHmLjxuEdH4+3uzt89VVJl6ZUKLTAPjd7e3saNGhAQkICKSkpJCQkEB8fb/PiVD/99FOhlq9///6FejwhhBBCCJFPO3dCZCTUqFHSJSk1Ci2wT0pK4ujRoxw9epTg4GAuXLigBvL6fytXroyvr2++jz1jxoxCm81Go9FIYC+EEEIIIUodmwP75ORkTpw4QVBQEMHBwYSFhZGdnQ38G8g7Ozvz+OOP06FDBzp06ECTJk0KFKDb+sRfCCGEEEKI0s7mwL59+/bodDrg34Db0dGRZs2aqYF8ixYtcHR0LJySkvO0vVq1avTu3Zunnnqq0KbTFEIIIYQQtomLiyMrK4ty5crlK1/9rCwcgcysLC6dO2eULoNn88/mwD4rK0t9+u7m5oafnx+vvvoqrq6uhVY4vTlz5rBjxw6OHz9ObGwsa9euZdOmTXTv3p0+ffrQuXNnHByKZLiAEEIIIYQwIyoqiunvTiMjMyvfeQMTEzno5UXnu3cZOmSIUXr5ck78uPUnCe7zweZouGXLlvzzzz/odDru3LnD8uXLWbVqFS1atMDX15cOHTrQsmVL7O3tC1zIl19+mZdffpmYmBh27tzJ9u3bCQ0NZdeuXfzyyy+4urry7LPP0qdPH9q2bVvg8wkhhBBCiLzdvXuXjMwsBtVKpHp5Xb7ypl2z4ysvL9qlJfFWwwSDtJg0ezZdd+XOnTsS2OeDzYH9pk2bSE5OJjg4mCNHjnDo0CGuXr3KsWPHOH78OMuXL6d8+fK0bt2a9u3b0759e5o2bVqgPvbVq1dn5MiRjBw5kuvXr7N9+3Z27tzJ1atX+f777/nhhx/w8vKid+/e9OnTh0aNGtl8LiGEEEIIYZ3q5XX4VMjfU3t7zb//5jevMK1A/VcqVapEjx496NGjBwDR0dEcPnyYQ4cOERQURFxcHH/99ReHDh0CwMXFhXbt2uHv71/ggteqVYsJEyYwYcIEQkND2b59O7/88gu3bt3im2++4ZtvvqF+/fo8//zz9O7dmxoylZIQQgghhCjFCrVjuqenJwMGDGDAgAEAXL58mWPHjrF582bOnj1LYmIi+/fvL8xTAtCkSROaNGnCu+++y/Hjx9m+fTt79uzh4sWLLF26lKVLl9KyZUv69u3Ls88+S5UqVQq9DEIIIYQQQpSkIhlxmpiYSFBQEH/99ReHDx8mMjISjUZT5NNVajQa2rZtS9u2bZk1axaHDh1i165d7N+/n1OnTnHq1Ck++eQT/vnnnyItx/1eeOEFzp49a3GfCRMmMHHiRINtV69eZeXKlRw+fJiEhASqVKlCu3btGDNmjHQzEkIIIYRKHyc8TOJqlDf4VxRcoQT2WVlZnDp1ikOHDnHo0CHOnj1rMKe9RqOhWbNmdOvWjW7duhXGKfPk4OBAp06d1PLt2rULRVHIyirePlxZWVlcvHgRAHd3d+zs7EzuV6FCBYP///333wwfPpyUlBQgpxtTbGwsO3bsYM+ePSxYsIBevXoVbeGFEEII8cCLiIigX79+/Pzzz/j4+BTZeXbu3MmUKVNYsmRJocQgN5pWgrCcf30wjM/uZuTES9HR0TRu3LjA5yorbA7sL1++rPanP3bsmBqA5l6cqmPHjnTr1o2uXbtSrVq1wilxHhRFISgoiJ07d7J3714SExPV7Q4ODnTo0KFYyqF3+fJlMjIycHBw4MCBAzg5OeWZ5+7du4wbN46UlBQ6d+7MnDlz8Pb2JjY2lnnz5vHLL78wY8YMmjZtSq1atYrhKoQQQgjxoEpKSiI7O5ukpKQiO0dGRgaTJ0/m4sWLTJ48mZ49e1oV09gqPTtnZK0+vhTWsTmw7927tzrDjT6Y9/LyomvXrnTr1o0OHToU6Qt+v2PHjrFr1y5+/fVX4uPj1XJpNBpat25Nr169ePbZZ3F3dy+2MgGc+/8FF+rWrWt1faxfv574+Hhq1KiBv7+/uuCDh4cHixcvJjo6mpMnT7J8+XIWLFhQZGUXQpRdOp2OkJAQYmNj8fDwoFWrVoUyffHDLCMjg82bNxMeHk7NmjUZOHCg+rl+48YNBg8eTGpqKs7OzmzcuJFHH31UzRsZGcmQIUO4d+8eFStWZMOGDeqkDpcuXWLIkCFkZmbi6OjIhg0bqF+/vpo3Pj6esWPHqq/FqlWr1L9lqampLFu2jBs3bvDoo48yadIknJ2dDfKOHj2amJgYqlevztdff23wd9DSNVlKg5wV6D/44AMiIiLw8fFh7ty5VKpUCci7/eRV7oK0v4KUKyMjg02bNnHu3DkaN27M0KFD1Wu2Jq+l+rK1zNakFwd/f38uX77Mxo0bGTp0KMuXL2fy5MnFWgaRN41iY8f3Ro0aodFoaNq0Kd26daN79+7F/lXJqVOn2LVrF7t37yY2Nhb49yajadOm9OnTh169euHp6Vms5crts88+49tvv6Vfv35WBeGKovDkk08SGxvLu+++y2uvvWa0z/79+xk/fjzOzs4cOXLE4MPQWvfu3VM/FGJjY4vtG5WHWWpqKpcvX6ZevXo21XlZI/WVPw9Sfe3fv59FixYRFRWlbvPy8mLq1KnqLGglqSTqatmyZQQEBKgrrgPY29vj5+dHQEAA2dnZBuPINBoNdnZ2HD9+nHbt2pGVlWWU7uDgoHYPvT8N4OTJk/Ts2ZP4+HijdHd3d5o1a8aBAweM0rp06cLSpUst5t23b5/FawLMpk2aNAk/Pz9CQ0ONjt2kSRNGjhxpsf1MnjzZYrkL0v4KUi5L9dGsWTOb806aNMnmMgcEBOSZDjkPEYcMGcKGDRuKJBaLjY2lQYMGakA/fvx4NmzYwKVLl4iIiGDkyJG81TAh31NWRqQ48N+wKibznowvx6brrsybN6/UdD3W3/gXJZsD+82bN9O1a1c8PDwKu0wWnT17lp07d7J7925u3boF/PuBWL9+fXr16kWfPn0MnpSUpOHDhxMUFMSMGTMYOXJknvtfvnxZbcA//fSTyTdocnIybdu2JTs7m9WrV9O5c+d8l0sC+/x7kAKvh4HUV/48KPW1f/9+pk2bhqenJ1qtFldXVxITE7lw4QLR0dEsXLiwxIP74q6rZcuWsXbtWry8vAzqJCwsjOjoaACLaXmlF0VeR0dHMjMzzaaXL1+etLQ0m45dtWpVbt++na+8+vbTpEkTzp49azZv06ZNCQ0Ntan9+fn5WTy2pXJ16dKFP/74o0jyDh8+3Gxwn1eZ83qdmjZtSkBAQJEH9m+88QYbN27k0qVLVKtWTQ30hwwZwtixY20O7KvuuMtrNerzTeQlbvepbJAmgb1tTI/ktMLAgQOLLagPCwtj6dKlPPPMM7z00kt8++233Lx5E0VRqFGjBuPGjePnn39mx44djB8//oEJ6gHOnz8P5Hwg+Pv788orr9C1a1f69evH3LlzCQ8PN9j/8uXLQM7deN26dU0es1KlSmogfunSpSIsvRCiLNHpdCxatAhPT098fX1xd3fHwcEBd3d3fH198fT0ZPHixQZPJUu7jIwMAgIC8PLyMlkn9vb2Juurffv2VK9eHY1GYzJv+/bt8fT0VGdzszVvmzZtjNLc3d3JysqymDc9PZ2qVavm+5o8PDyIj4/P9zX5+vpSvXp1QkNDzebVp9vS/pKTky0e21K5PDw8OHDggMW8Dg4OtGvXzmSZDhw4YLa+PD09CQwMJCMjw6Yyp6en4+HhYTY9NDSU5OTkIn0P/PPPP6xatYoPP/xQjT08PDyYNWsWX331VYHiEPssxeBfUXBW9bH/6aefCvWk/fv3z9f+/fr1M5gu08PDg169etGrVy9atGhRqGUrTLdu3eLOnTsATJ8+nfT0dIO08+fP88MPP/DZZ5/Ru3dvAGJiYgBwc3NT+9ab4unpSUxMjNoFyRxzTzbK0h9mIYR1QkJCiIqKonPnzkarhGs0GrRaLQcPHiQkJIQ2bdqUUCmL1+bNm9HpdGi1WqM6uX37NjqdjoYNG5qsLy8vL2JiYkzm1Wg0NGzYkOjoaK5evWrQpz4/ec+cOUPLli0N0jIzM1EUJc+8GRkZ+b4m/QxttlyTp6cn0dHRZvPmdc2W2t8HH3xg1TWbKlelSpXyrOuDBw9y+/Ztgwea+jJFRUWpNw7m8m7evJmhQ4faVGYHBweL6R988AFjx44FcqbJLkyKojB27Fjq1q3Lm2++aZA2YcIEVqxYwccff1yo5xQFY1VgP2PGDKNGZSuNRpPvwD533oYNG9K2bVsAdu3axa5du/J9nPfee8+m8+eXfuAs/NsXz9fXFycnJ0JCQli0aBFnz57l3XffxcvLi9atW6t33vdPf3m/8uVz5nwt6jt1IUTZoX9Q4OrqajLdxcXFYL+yQP+tqqk60T+sMVdf+umN86rPe/fuFWrezMxMq/Lq98str2vSPxQqimuy9ppNtb+IiAiby2XtNeV+OHd/mrmBvfr0+7+dz0+ZTb1OudP1xwF4//33Te5rq7S0NM6fP8/ixYuNBgI7OTnxxhtvMGXKFFlb5wFi9aw41nbFd3R0pGLFiqSnp5Oamqpu12g0ajBaEGFhYYSFhRXoGMUV2Ds5OdG5c2fS0tLw9/encuV/+4917NiRwMBAXn75ZS5cuMD8+fP54Ycf1IFUjo6OeR4byHNefnMr/ebuYy+EEID6NDIxMdHkDGL6qfSKe2xVSapZsyZguk7036qaqy/9ei551WfFihULNa+joyNpaWl55jX1dyava9IHsEVxTdZes6n25+Pjw6VLl2wql7XXZOpbdH2auW/B9en6dmRLmc3FA/r03PPWz5s3jzp16pjc3xaKojB69GhWrFjBhAkTDIL7jIwMVqxYQcuWLf8/Rkw1fyBRbKzqY79//36TP/oZWypXrszUqVP59ddf+eeffwgKCiIkJITDhw/zySef8Mgjj6DRaBg/fjwhISE2FVRRlEL7KS6dOnVi9erVrF+/3iCo13N2dlZXmz19+jQ3b95Ub37M3aHr6fvr5XUDIIQQ1mrVqhVeXl5cuHDB6LNSURQuXLiAt7c3rVq1KqESFr+BAwdib29PWFiYUZ1UrVrVbJqiKERFRaHRaMymh4WFodFojAKx/OR97LHHjNIcHR2tyuvo6Jjva0pKSrL5mqKjoy3m1V+zLe1v7ty5NpcrOTk5z7z29vZUrVrVZJk0Gg1RUVFm8zo4ODBw4ECby6zvWmUufe7cuer2OnXq0Lhx40L7adKkCV999RVXrlxh+fLlBmXw9/fnypUrvP/++4XWq0MUnFVP7PVz7eZ2/Phx1qxZQ/Xq1dmwYYPJlc7c3d154YUX6NatG4MGDWLJkiU0aNCArl275quQ+gGopVHufoKXLl1SnyakpaVZzKf/NkSeugshCou9vT1Tp05l2rRpBAcHo9VqcXFxISkpyWBWkrI0n72TkxN+fn6sXbuWoKAgGjZsqNZJWFgYOp2O6Ohok2n6MVPm0vWzrRw9etTmvMeOHTNKi4+Px9HR0WLe8uXLEx8fn+9rio2NpWrVqlaV6/72ExMTo86KY66+9LPi5Lf9VapUyeKxLZUrNjZWndkmr9fJVJnyyjt8+HCT89lbU+by5csTFxdnNr1p06ZFHgc0a9aMsWPHMnv2bIYNG6bOijNnzhzGjRtnMGZBlDybF6j6+uuvAZgyZUqeyxdXqVKFqVOnMnHiRL799tt8B/b6wbt9+/ZV++AVFp1Ox/bt24H8D+otDPo+cpDTf8/b2xuAhIQEMjIyzC5uof+gqV69etEXUghRZvTo0YOFCxeyaNEiDh48qG739vZ+IKa6LAn6qQoDAgIMpqF0cHBg+PDhBAQEEBMTY5Cm0Wiwt7dX57E3le7o6EhWVpbJNI1Go85jbyq9atWq6jz296d17dpVncfeXN7c89ibuiZL15t7Hvv7j920aVN1vnhz7Uc/j725cuvnsc9v+8s957st5bJUH/p57G3Ja2ke+7zKbE16cZgzZw4bN27kww8/ZPny5Xz44Yfq9tx9/EXJs3kee19fXxITE/nrr7+Mvp4yJT4+no4dO+Li4sKxY8fyda5GjRphZ2fHiRMnCn3+z5SUFB5//HHs7OwIDQ0t1GPv2LGDiIgIGjRoYPbDKCoqii5dugCwadMmPDw81H137txp8k449zz233zzDZ06dcp32WQe+/x7UOYZf1hIfeXPg1ZfD/LKsyVVV7LybNlYeTYwMPChW3m2qOexB1iyZAnTpk0jMDCQoUOHsmjRIiZPnsypU6dsnse++k93GFGrAd9dv0hMfzeDNJnH3jY2P7HX9wHPa/Cmnn4kuq39sIq6b3xRHH/jxo0cP36cVq1amQ3s//rrLyBnlpsmTZpQrlw5atSoQWRkJEeOHDEZ2AcFBZGdnY2jo6PBNGdCCFFY7O3ty8yUltZycnIymrJQ79FHH+XQoUNm89aoUYMDBw6YTKtfvz5Hjx41m9fd3Z0tW7aYTHN2drY4IYS7uzuBgYFmb4QsXZOlNMjpSrJ06VKTaXm1n7zKXZD2V5ByOTk5MWjQILW+cgfm1uS1VF+2ltma9OIwYcIEVq5cyeDBg9FqtUbTX4oHg82Bfc2aNblw4QK//vorw4YNy3P/n3/+GYDatWvbeko2bNhQ6INF8xqkWhDdunXj+PHjnDp1iqNHj9KuXTuD9KSkJFasWAHkdDPSj7jv3bs3q1atYt26dbz00ktGTzH03aCef/556WMvhBBClHEuLi7Y2dkZdO8tbE5OTixdupQpU6awZMkSq7+NsORqi0pwJ+ff++crKmeX88A1r+m/hSGbA/unnnqKsLAwli1bRuPGjS3exf7666+sXLmyQHPYAyxatMjmvCVh8ODBBAQEcOvWLSZPnsysWbPo1q0bTk5OnDp1io8++oiIiAiqVatm0Afvtdde44cffuDGjRuMHTuWTz75hJo1axIbG8vHH39MSEgIzs7O6oIUQgghhCi7fHx82LdvH1WqVCnS8/Tu3VtdULMwJHiWhzs5/1bEsAdIZaec6U89PT0L7Xxlgc2BvZ+fH5s2beL27dsMHz6cp556is6dO1OrVi2cnZ1JSUnhypUr7N27l7/++gtFUWjUqBEvvfSSTecrzmkqC0vFihVZuXIlY8eOJTo6mrfeegtHR0ccHR1JSUkBcubj/frrrw3GKbi5ubFs2TJef/11jh49Ss+ePXF1dSUpKQlFUbC3t2fx4sWFOletEEIIIR5eRR3Ui4eDzYG9m5sbq1evZtSoUSQkJLBnzx727Nljcl9FUahfvz5fffWVTV/dmFtk6WHQqFEjfv75Z9auXcv+/fu5ceMGAFqtlp49ezJy5EiTq8516NCBbdu2sXLlSg4dOkR8fDxubm60bduWMWPG0Lx58+K+FCGEEEII8QCzObAHaNy4MXv27OHLL79k586dJpd5rlmzJi+99BKjRo2yuX+8qXn0HyZVqlRh0qRJFqe8MqVWrVp8+umnRVMoIYQQQogSVPFO5r//VpBFrgpDgQJ7AFdXV2bMmMGMGTO4ePEit27dIjExETc3Nx555BHq1q1bGOUUQgghhBClSMOjd6FWdRoevWs03aWwTYED+9waNGhAgwYNCvOQQgghhBDiAReTlv91Lqr+//BJnQIRKYYhqS3HE4Uc2AshhBBCiLKjcuXKODk6sOm68XjBvASmxzAuKory6dn8N8x48G/5ck64ubkVQinLjgIH9pGRkezdu5eIiAhSU1PJzs62uL9Go+GTTz4p6GmFEEIIIUQJ8/LyYv6Chbi5uanr8VirfrduNImKItPTkw0bNhilu7m54e3tXVhFLRMKFNivWbOGJUuWoNPp8pVPAnshhBBCiNKhWrVqJlc2zpNDThjq6OBA48aNi6BkZY/NgX1QUBALFixAo9Goc8yXK1euUFYiE0IIIYQQQuSPzYF9QEAAkLPU7wcffEDPnj2pVKlSoRVMCCGEEEIIYT2bA/uQkBA0Gg3Tp0+nf//+hVgkIYQQQgghRH7ZHNgnJiYC0K1bt0IrjBBCCCFEbrdu3eLOnTvFdr709HQiIiLIysrK92DQsiiv+pIBsMXL5sC+WrVqREVFFWZZhBBCCCFUt27d4oUBL5CWnlbSRRE2Kl+uPD9u/VGC+2Jic2Dfvn17fvrpJ4KDg+nTp09hlkkIIYQQgjt37pCWnsawNgPxcvEo6eKUSdFJsaw7vplX2wzEM5+vQVRSLOuPb+bOnTumA/tz50BRQKMppNIKmwP7kSNHsn37dpYtW0bHjh1xd3cvzHIJIYQQQgDg5eJBzSo1SroYZZpnUbwGLi6Fezxhe2Cv1WpZsGAB06dPp2/fvrzyyiu0aNECd3d3HBwsH7ZRo0a2nlYIIYQQQghhgs2Bfbt27QBQFIW4uDi+/PJLq/JpNBpCQ0NtPa0QQgghhBDChALPiqOnX6RKGEtOTuabb75h79693Lhxg/Lly1O/fn0GDBjAiy++iJ2dncl8V69eZeXKlRw+fJiEhASqVKlCu3btGDNmjHzrIYQoFvrPHiGEKHRLlkBiIri6wjvvGCXL50/+2RzYf/rpp4VZjlIrMjKS4cOHEx4eDoCTkxMpKSmcOHGCEydOsHXrVlavXk3FihUN8v39998MHz6clJQUAFxcXIiNjWXHjh3s2bOHBQsW0KtXr2K/HiFE2REREUG/fv34+eef8fHxKeniCFEqHQk7ypd71zD+6dfooG1b0sUpXkuWQGQk1KhhFNjL549tbA7sBwwYUJjlKJWys7N56623CA8Pp3r16nz88cd06tSJ7Oxs9u7dy6xZszhx4gSzZ89mwYIFar67d+8ybtw4UlJS6Ny5M3PmzMHb25vY2FjmzZvHL7/8wowZM2jatCm1atUqwSsUQpRmSUlJZGdnk5SUVNJFEaJUyszKxP/XrwmPjWT5nq9pU7cljg6OJV2sB4J8/tjGdB8QUSgOHDjAmTNnAFi6dCldunTB3t4eR0dHevXqxfvvvw/Ajh07iImJUfOtX7+e+Ph4atSogb+/vzpFlIeHB4sXL+bxxx8nPT2d5cuXF/9FiTLj7t27jBgxgmeffZYRI0Zw9+5dNS01NZVPP/2UN954g08//ZTU1FSDvBkZGWzatIl169axadMmMjIyirv4Jul0Oo4fP84vv/zC8ePH0el0D0RenU7HyZMnOXLkCCdPnszXsS3JyMggMDCQzz77jMDAQKPXIa90IUTR+jF4B5G3b7Fx40Yibt9k69EdJV0k8ZCz+Ym9LXQ6HX/88Qc9evQoztOWmEOHDgE5swC1adPGKL179+5ATr2cO3eO6tWroygKmzZtAmDo0KFGq7jZ29szevRoxo8fz6+//srs2bNxdnYu4isRZU3fvn2JiIhQx85ER0fTrVs3fHx8qFevHgcOHFDTgoKC2Lx5M126dGHp0qUsW7aMgIAANTjdu3cvy5cvx8/Pj0mTJpXUJbF//34WLVpksLCel5cXU6dOzfMzqSjzFuTYltz/OkDOAwb965BXuhCiaN25d5e1Bzcxbtw4Bg0axIEDB/hubQBPt+iOW8XKJV088ZAqUGCvKArbt2/n4MGDJCQkkJWVZTSIVlEUMjMzuXfvHhEREaSnp5eZWXFmzpzJmDFjSE5ONpme+w+qk5MTAFeuXCE2NhaAjh07mszn6+uLnZ0dqampHDt2jM6dOxdyyUVZ1rdvX8LDw/Hy8kKr1eLq6kpiYiJhYWGEh4ebTfvjjz8s5l27di1AiQSN+/fvZ9q0aXh6etK5c2e1XBcuXGDatGksXLjQbBBdlHlfffVV1q1bZ9OxLVm2bBlr1641+zocP36cs2fPPnCvkxBlyTe/BWDvaMecOXMAmDNnDhs3bGDNbwG88/ybJVw68bCyuSuOTqdj7NixTJ8+nZ07d3L48GGOHj3KsWPH1H+PHTvG8ePHOX36NBcvXiQ1NbXMzZ7j6elJvXr1TKZ9//33QM7A2GbNmgFw+fJlIGda0Lp165rMV6lSJapVqwbApUuXCrvIogy7e/cuEREReHl54evrq65L4e7uTvv27fH09ESj0dC2bVuTaREREXh4eJjNWxLdPXQ6HYsWLcLT09OoXL6+vnh6erJ48WKT3V+KOm9gYCDVq1fP97EtycjIICAgwOxr6OHhQWhoqMXXWLrlCFG0LkdfY/uJ3Xz40Ufq33MPDw9mffgh207s5kr0tZItoHho2fzEfvv27fz5558A2NnZ4e3tTVZWFtHR0VSvXp3KlSsTHx/P7du3gZxA9ZlnnuHFF18snJI/pFJSUrh8+TIbNmxg69atALz77rtUqlQJQO1r7+bmZtQNJzdPT09iYmLUp/vmmHvaV1h9eEXp8vbbb6MoClqtFs19S3xrNBoaNmxIdHQ0V69epX79+ibTHBwczOY9ePAgmzdvZujQocVyPQAhISFERUXRuXNnk+XSarUcPHiQkJAQoy5zRZ03KipKvVnKz7Et2bx5MzqdzuxrqJ9hy9JrrH+dHn/8cSBn6t0HSXp6OhEREWRlZVn8nBQ5Hub6etDaXmFQFAX/3aupW6cub75p+GR+woQJfLn8S/z3fM3iYXON3qMPK3OvY/2sLByBzKwsLp07Z1UeYZnNgf0vv/wCwKOPPso333xDzZo1OXLkCCNHjsTX15eFCxcCcP78eT744AP++ecfbty4QYcOHQqn5A+hkJAQBg0apP7f0dGRzz77jD59+qjb9N12KlSoYPFY5cuXN9hfiMKg7+ft6upqMt3l/5f/vnfvntm0zMxMi3n1U78WF/3Nb17XZOomuTjy2tvb5/vYlujr19x59Tf1eZUrPDxcDez1A/2FEAV3PS6cE5dPsXjxYrUbrp6TkxPj3xzPlClTuBEXQS2PmiVUysJl7jNkd3w8nkB8fDxDhgwp3kKVUjYH9qGhoWg0GsaPH0/NmjkNr2XLltjZ2REcHKzu16hRI7799lv69+/PuXPn2LFjB/379y9wwR9GN2/exMnJCQcHB1JSUsjMzGTevHmkpKTw8ssvA5CVlQXkBP2W6D8M9Pubs3//fpPb7927p35LIISel5cX0dHRJCYm4u7ubpSun3bs/nUXcqeZa7v6dP3nRXHx8PAAyPOa9PsVd15z355ZOrYl+vo1d179jURe5cr9Os2bN486derkqxxFSf8E2sfH56F7Al0SHub6unr1aqm7saxVrSZt6rdixZcrmDBhgkFwn5GRwZfLv6Rt/VY8Wq30zN1u7jPEvVs3iI7G3d2dDRs2GKSVxte+ONgc2OunvmvZsqW6zdnZmZo1a3Ljxg1iYmKoXr06kNMnfNSoUcyZM6dMB/bdunXj9OnTaDQarl27xuLFi9m7dy8ffPABTk5O9O/fX30Sb+6pp56+/2teNwBC5Mfnn39Ot27dCAsLo3379gZfAyuKQlhYGBqNxugDOndaZmYmiqKYzOvg4MDAgQOL7XoAWrVqhZeXFxcuXMDX19eoXBcuXMDb25tWrVoVe14HBweio6OpU6dOvo5tycCBA1m6dKnZ1zApKQmNRmPxNda/TvoxP3Xq1KFx48b5KkdRSk1NxcHBgXr16smsYFaQ+nqwaDQa3nxmNK+tmMjy5cuZPHmymubv78/Va1f54I0vSk03HLDwGdKuHcTG4ujh8UB9xjzMbB48q3/qc/9Sv7Vr1wb+HQSqp5/h5cKFC7ae8qFXoUIF7Ozs1MDI39+fnj17AjmzWCiKoj4JTUtLs3gs/bzh8tRdFKbKlSvj4+NDdHQ0QUFBxMfHk5mZSXx8PEFBQURHR6MoCkePHjWZ5uPjQ1xcnNm8Q4cONfrquajZ29szdepUoqOjCQ4ONihXcHAw0dHRTJkyxWSXmKLOO3ToUGJiYvJ9bEucnJzw8/Mz+xrGxsbSpEkTi69xSbxOQpQl9Txr83zrZ5n90UfExcUBOd3u5syeTd/Wz1LXs3bJFrC4bNsGR47k/CsKhc1P7KtUqcKtW7e4ffs2lSv/O9+q/uvbS5cuGfSnd3NzA+DOnTu2nrJUGj58OPv27ePWrVvExMSoi1ElJCSQkZFh9o9rdHQ0gPqtiBCFZdu2beo89vp2BjlPmWrWrKnOY39/WteuXQ3msc+d7uDgwPDhw0tsCsUePXqwcOFCFi1axMGDB9Xt3t7eeU4pWdR5mzVrZtOxLdHXs6XX4UF8nYQoS17r7sf+MweZNWsWX375JbNmzUKXmc2o7n4lXTTxELM5sH/ssce4desWf/zxh8G0jLVr10ZRFP755x+D/W/evAlQqr5aysuVK1e4ceOGGgyZkrv/bEJCgjrTSHZ2Njdu3DCYeUQvOTlZnW3IVLoQBbVt2zbu3r3L22+/TVRUFF5eXnz++efqTXxqairLli3jxo0bPProo0yaNEn9in/SpEmMHz+ewMBAzp07R+PGjR+IJ8A9evSga9euhISEEBsbi4eHB61atbLqiXhR5tWnBwUFERoaSpMmTWjfvn2+n9TfT/86bN68mfDwcGrWrMnAgQPV1yGvdCFE0XKrWJnhnQex4quv6Ny5M6tWrWL806NkcSpRIDYH9t27d+fXX3/liy++oGrVqjz//PPY2dnRvHlzAPbt26f+sQBYvXo1ADVq1CiEYj8c3nnnHc6dO8cLL7zAp59+anIffZclOzs7vLy8cHNzo0aNGkRGRnLkyBGTgXtQUBDZ2dk4OjoajHEQojBVrlyZ7777zmSas7Mz7733ntm8Tk5ODBo0iMuXL1OvXr0HJli0t7fP19SRxZXX3t6exx9/nMqVK1OvXr0CB/V6Tk5OFqcWzStdCFG0XvDtw7aTvzB48GAe9fBhQLs+eWcSwgKb+9j36dOHunXrkpqayowZM5g2bRoAzZs3p169eqSmpvLCCy8wadIk+vbty+7du9FoNHTp0qXQCv+g068I+8svvxAZGWmUnpGRwYoVKwBo166d2l2pd+/eAKxbt07tS6+n0+n4+uuvAXj++eelj70Qosi4uLhgZ2enToEphChcjg6OTHh6NLWq1+TNZ0bj6FDGJsTo2xc6dMj59z7y+WMbmwN7BwcHVq9eTZMmTVAURV05DWD27Nk4ODiQlJTEnj17uHjxIoqi4OXlxdixYwul4A+DESNG4ObmRmpqKqNGjeLQoUPq1HZnz55l5MiRnDlzhnLlyjF9+nQ132uvvYabmxs3btxg7Nix6rzUsbGxvPPOO4SEhODs7Fym6lIIUfx8fHzYt28fPj6lZ9o9IR40HRq2Y/2ElXTQti3pohS/kychKCjn3/vI549tbO6KAzndav73v//x559/Giyo1KZNGwIDA1m2bBkhISE4ODjQuXNnpk6dajSLTmnm7u7OqlWreP3117l27RqjRo3C0dERR0dHUlJSgJw70sWLF9OkSRM1n5ubG8uWLeP111/n6NGj9OzZE1dXV5KSklAUBXt7exYvXvxAzSsthCidytJnthDiwSKfP/lXoMAecgbD6ruc5Na8eXPWrFlT0MM/9Fq0aMGOHTv47rvv+O233wgPDyc7O5v69evTpUsXhg8fjqenp1G+Dh06sG3bNlauXMmhQ4eIj4/Hzc2Ntm3bMmbMGHUsgxBCCCGEEFAIgb3IW9WqVZkyZQpTpkzJV75atWqZHXQrhBBCCCFEboUe2Ot0Og4fPszVq1fRaDTUq1cPX1/fQpvlQQghhBBCCGEs34H9yZMn+eeff6hQoQKdO3c26EZy5MgRZs2aRUREhEGeqlWrMnXqVPr371/gAgshhBCibIlKii3pIpRZ0f9f99E2vAbyuhU/qwP7hIQE3n77bY4dO6Zuc3R05N1338XPz48TJ07w+uuvk5GRgaIoBnnj4uJ47733iImJkZlchBBCCGEVNzc3ypcrz/rjm0u6KGXeOhtfg/LlyqvTeYuiZ1Vgn52dzciRIwkLCzMI2jMyMpg3bx6enp6sXr2a9PR0KlWqxKBBg2jZsiX29vb8888/bNiwgTt37vDf//6Xp59+mtq1axfV9Qgr5X4d7927p64aKsxLTU0lJSWFe/fukZ2dXdLFeeBJfeWP1Jf1pK7y52GuL1dXVwICA7hz506xnTMjI4PIyEhq1KjxwCyu9yDLq77c3NxwdXXl3r17xpn17TE7G0yllzKpqalkZ2dToUIFNBpNkZxDo9z/eN2EH3/8kf/85z9oNBr8/Pzo168fDg4O/Prrr6xcuZIKFSqQnJxMlSpV2LBhg9E0jLGxsQwaNIibN28yevTofA8iFYUvJibG5Gw8QgghhBCi6CQnJ1OxYsUiObZVT+x/++03NBoNQ4cO5f3331e3N2rUiNTUVL799ls0Gg2jR482Obe6h4cHb7zxBjNnzuT48eOFV3ohhBBCCCEEYGVgHxoaCsDzzz9vlPbiiy/y7bffAjlzr5vTvn17AG7cuJHvQorCV61aNTp16gTAL7/8UmRfCZUmvXv3BmDnzp0lXJKHg9RX/kh9WU/qKn+kvvJH6it/pL6sp6+r3Iu6FjarAvu7d+8C8Mgjjxil5V7q18PDw+wx9AMnkpKS8lM+UUTs7OzUvnCVKlUq4dI8HPRTthbV12eljdRX/kh9WU/qKn+kvvJH6it/pL6sp6+ronyYamfNTvoBD6YGWJYvX1793dKLameXc6rMzMx8FVAIIYQQQgiRN6sCe728FpmS7hxCCCGEEEKUjHwF9kIIIYQQQogHkwT2QgghhBBClAL5Cuzz6mojXXGEEEIIIYQoGVYtUNWoUSM0Gg3e3t4mg/fIyEiL6ZCz0unNmzfRaDScO3eu4CUXQgghhBBCqKya7lLv5s2bJrfrg3lz6UIIIYQQQoiiZVVgb2r+eiGEEEIIIcSDw6quOEIIIYQQQogHm8yKI4QQQgghRCkggb0QQgghhBClQL4Gz4rSYdeuXWzYsIHQ0FB0Oh0+Pj48++yzvPbaa1SoUKGki1firl27Rr9+/WjTpg3ffPON2f1iYmJYsWIFBw4cICYmBldXV1q0aMHIkSNp165dMZa4eCUlJbF+/Xr27dvHtWvXyMjIoHr16vj6+jJy5Ei0Wq3JfGWxvpKTk/nmm2/Yu3cvN27coHz58tSvX58BAwbw4osvYmdn+tnK1atXWblyJYcPHyYhIYEqVarQrl07xowZQ6NGjYr5KkrW0qVLWblyJe3atWP9+vUm9ymLbQvghRde4OzZsxb3mTBhAhMnTjTYVlbb18WLF1mzZg1BQUHExsZSoUIFmjVrxpAhQ+jRo4fZfGWpfQ0bNoyjR49avf+6devw9fVV/19W21Z6ejoBAQHs3LmTq1evkpWVxSOPPMKTTz7J6NGj8fLyMpu3sOtM+tiXMfPnz2fNmjUAODo64ujoSEpKCgC1a9cmMDCQatWqlWQRS1RycjKvvvoqZ8+epVOnTmYD+/DwcAYNGkRcXBwALi4u3Lt3j+zsbDQaDdOnT2fkyJHFWfRicfXqVV577TUiIyMBKFeuHHZ2dqSmpgI5bWrevHn069fPIF9ZrK/IyEiGDx9OeHg4AE5OTiiKQmZmJgCtW7dm9erVVKxY0SDf33//zfDhw9X3pYuLC8nJySiKgqOjIwsWLKBXr17FezEl5MSJEwwbNgydTmc2sC+LbQsgKyuLVq1akZGRgbu7u9mbxFGjRvHaa6+p/y+r7evHH39k1qxZ6vuvYsWK3Lt3T01/9dVXef/9943ylbX2NWHCBEJCQizuk5iYSEZGBnZ2dvz888/qw5yy2raSkpIYPny4epPt4OCAg4MDaWlpALi6urJy5Upat25tlLdI6kwRZcbPP/+saLVapVGjRsp3332npKenK4qiKEFBQUrXrl0VrVarjBgxooRLWXISEhKUwYMHK1qtVtFqtcqoUaNM7peZmak8++yzilarVV588UXl0qVLiqIoyt27d5W5c+cqWq1WadiwoXLs2LHiLH6Ry8zMVJ577jlFq9Uq3bt3V/766y9Fp9Mp2dnZyvnz5xU/Pz9Fq9UqTZs2Vc6cOWOQr6zVl06nU1544QVFq9UqnTp1Uv744w8lKytLycjIUHbu3Km0bt1a0Wq1yrRp0wzy3blzR2nfvr2i1WqV0aNHKzdv3lQURVFiYmKUt99+W9FqtUqzZs2Ua9eulcRlFaukpCSle/fu6vvRz8/PaJ+y2Lb0zp8/r2i1WqVJkybqZ3leymr7Onr0qNKwYUNFq9Uq06dPV2JiYhRFUZTY2FjlvffeU9vY3r17DfKV5fZlztWrV5WWLVsqWq1WWbVqlbq9rLYtRVGUKVOmKFqtVmnTpo2yY8cOJSMjQ8nOzlaOHz+utp8nnnhCSUpKMshXVHUmgX0ZkZWVpTz11FOKVqtVFi1aZJR+4cIFpXHjxopWq1UOHz5cAiUsWSdPnlS6deumfsBbCux//PFHRavVKq1atVJu375tlD558mRFq9UqQ4YMKepiF6vt27crWq1Wady4sRIaGmqUnpaWpgb+EydOVLeXxfr67bff1HZk6o++vk4aN26sREdHq9u/+OILRavVKt26dVPS0tIM8mRlZSmDBg0yeUNQGs2YMUPRarVK8+bNzQb2ZbFt6W3dulXRarVKnz59rM5TVttXnz59FK1Wq8yYMcNkuv6hxOjRow22l+X2ZUpGRoYyYMAARavVKq+99pqSnZ2tppXVtpWQkKDGTlu3bjVKv3r1qvq3YNu2bQZpRVVnMni2jDh8+DDXr19Ho9EwYsQIo/QGDRrQvXt3AH7++ediLl3JSU5OZtq0aQwePJjIyEhq165N27ZtLebZtGkTAP3798fd3d0ofezYsQAcP36ciIiIwi90CTlw4AAAvr6+NG7c2Ci9XLly9O3bF4Bjx46p28tifR06dAjIWbW7TZs2Run695pOp1NX4lYURa2roUOHUq5cOYM89vb2jB49GoBff/1V7f5UGu3du5cff/yRxo0bW/wauiy2Lb3z588DmHwvmlJW29epU6e4cOEClSpVYvr06Sb3mTJlCu+99x4vv/yywfay3L5M+eqrrzh79iyVKlVi3rx56uKkZbVtQc6YPJ1OB0DLli2N0mvXrk316tUBuHXrlrq9KOtMAvsyIjg4GICGDRtStWpVk/t06NABgD///LPYylXSwsPD2bZtGwCvvPIK//vf//Dx8TG7f0pKCn///TcAHTt2NLlPo0aN1D8CpakumzRpwjPPPEPnzp3N7uPh4QHk3DBB2a2vmTNncvDgQZYsWWIyXf+HAHL63gNcuXKF2NhYwHxd+fr6qmMact88lSaxsbF88MEHODk5sWDBAhwdHU3uV1bblp7+htDawL6stq/9+/cD0KVLF9zc3Ezu07JlS0aMGMFTTz2lbivr7et+0dHRfP311wC89dZbeHp6qmlltW1BTv95vVOnThml37p1Sx2fUatWLXV7UdaZBPZlxKVLlwCoV6+e2X1q164NQFxcHAkJCcVRrBKn0Wjo1q0b//vf/5gzZw6VKlWyuP/Vq1fJzs4GoG7dumb307+B9fVeGowcOZL//ve/FgeKnTx5EkCdAaAs15enp6fZ99v3338P5AyUatasGQCXL18GctqkubqqVKmSOri9NNVVbv/5z39ISEjg7bffNjvDEpTttgX/PrH38vLC39+fV155ha5du9KvXz/mzp2rDtrWK6vtS19PjRo1QlEUduzYwZgxY+jZsye9e/dm1qxZXL9+3ShfWW9f91u6dCmpqanUrl2bIUOGGKSV1bYFOXGTPnb69NNP2bNnD5mZmSiKwpkzZ3jjjTfIzs6mcePGBjMvFWWdyXSXZURMTAyAwV32/XKnxcbGUqVKlSIvV0lr1KgRK1eutHp/fT0CFqev0tel/o68LAgPD2fHjh1AztMxkPrKLSUlhcuXL7Nhwwa2bt0KwLvvvqveTOrrys3Nzehr2dw8PT2JiYkplXUVGBjIwYMHadOmDaNGjbK4b1luW7du3eLOnTsATJ8+nfT0dIO08+fP88MPP/DZZ5/Ru3dvoOy2rytXrgA5N9FjxowxerJ+6dIlfvrpJ5YsWULPnj3V7WW5fd3vxo0bahfdN954w+hbtLLatgDs7OyYP38+o0eP5s6dO7z11ls4ODjg6OhIamoqDg4ODBgwgBkzZuDg8G/IXZR1Jk/sywj9tF6W5qnP3bj0XSmEodz14uzsbHa/8uXLG+1fmqWnpzNlyhTS0tIoV66cGpRJfeUICQmhVatWvPTSS/z44484ODiwePFigz69+mvPay2J0lpXV65cYeHChVSoUIHPPvvM7PSNemW5bem74UBO0PnFF19w9OhRTp06xbfffkvTpk3JyMjg3Xff5cSJE0DZbV9JSUkALF++nD///JOhQ4eyb98+/vnnHzZu3EjTpk3Vz6+LFy+q+cpy+7rf+vXryc7OpkaNGvTp08covay2Lb2WLVuydetWHn30USBnKlp9n/js7Gx0Op1RH/mirDMJ7MuIrKwsALP9VeHfvr5g2AdY/EtfL46OjurAIVP0damv99IsIyODiRMncvr0aSCnf/kjjzwCSH3p3bx5EycnJ/VDPDMzk3nz5vHDDz+o+1jzHoXSWVdZWVlMmzaN1NRU/vOf/1CzZs0885TltuXk5ETnzp1p164dmzdv5umnn6Zy5co4OzvTsWNHAgMD0Wq1ZGVlMX/+fKDsti/9/OCxsbGMGjWKWbNmUbNmTZycnHj88cdZt24dNWvWJC0tjc8//1zNV5bbV27Jycn873//A3K6Y+Z+6qxXVtuW3oEDB3jppZdISkpi/vz5HDt2jJCQEL766itq167Ntm3bGDp0KNHR0WqeoqwzCezLCP1dn35xDlMyMjLU3/NqbGWV/lsNfR86c/R1Wdrr8d69e4wbN06dMWfkyJEGT6GlvnJ069aN06dPc/LkSXbv3s1TTz1FfHw8H3zwAT/99BNg3XsUSmdd+fv7c+bMGbp168bAgQOtylOW21anTp1YvXo169evp3Llykbpzs7O6mqzp0+f5ubNm2W6fUHOk9EJEyYYba9UqZL6DeMff/yhLipUlttXbr/88gv37t3D2dmZF1980eQ+ZbltnT17ljfffJOUlBS+++47+vfvj6urKxUqVKBr165s3LiRGjVqEBkZyaJFi9R8RVlnEtiXEfrVLfUfWqbkTstrEGlZlXuV0Nz9Wu+n/9qtNNdjTEwMfn5+HD58GIARI0YwY8YMg32kvnJUqFABOzs7NBoNderUwd/fX+3Pu2zZMhRFseo9CqWvrkJCQli1ahVVqlRh7ty5VueTtmVZ7mlWL126VGbbl/66mzRpYrTKs55+RdDMzEyuXbtmkA/KdvvKPauQuW4jZbVtAaxcuZLMzEyef/55GjVqZJTu5ubGG2+8AcCuXbvUbtFFWWcyeLaM8PLy4vTp0wZfBd0vd5p+2kJhyNvbW/09OjraYPqq3PQDY/Tz15Y2ly5dYsyYMdy8eRPImf7szTffNNpP6su84cOHs2/fPm7dukVMTIxaVwkJCWRkZBh0jctN/z4tLXX1ww8/oNPpSElJoX///kbp+r6lISEhPPHEEwB88cUX0rby4OLiov6enp5eZttX1apVuXPnjsW+zLm/9dAHWtK+crox6R/cWFpPoqy2LUDtgtqqVSuz++hvsrOysoiIiKBhw4ZFWmfyxL6MaNCgAYD6NMIU/ZRfHh4eJr/eFTlTW+m/ErOmLuvXr18cxSpWp06dYsiQIdy8eRN7e3s+/vhjk0E9lN36unLlCn/88Yc6pZkpuW+eExIS1GvPzs7mxo0bJvMkJydz+/ZtoPTUlb6bQ3p6OnFxcUY/+kArMzNT3ZaZmVlm2xbAjh07WLlypfo01RR9OwGoVq1amW1f+ilTo6KizO6jn2EIUKcXLMvtS+/o0aOkp6dTvnx5daYzU8pq2wLUqcEtddfK3Y1G/+1PUdaZBPZlhK+vL5Azm8Ldu3dN7qO/M2/Xrl2xleth4+joqN6ZHzlyxOQ+58+fJz4+HiDPVWwfNufPn2fMmDHcvXuX8uXL4+/vb7FPdFmtr3feeYdx48apC7qYog/67ezs8PLywsfHhxo1agDm6yooKIjs7GwcHR1NrnL4MPrss88ICwsz+/PKK68AOZ9L+m2+vr5ltm0BbNy4kaVLl7J69Wqz+/z1119ATl/eJk2alNn2pf97dvHiRYOVP3PTzxxUpUoV9UlqWW5fevoFuho3bqz2CTelrLYt+Hcq1JCQELP7nD17Fsj5rNfPnFOUdSaBfRnRpk0bPD09ycrKMhlshIWF8fvvvwMwePDg4i7eQ0U/L/SWLVvUFeVyW7FiBZBzM2VpYZOHzb1795g4cSKJiYk4OzuzevVqunfvnme+slhf+tV5f/nlFyIjI43SMzIy1Otu166duiKmvq7WrVtnND2aTqdT37vPP/98qeqnaquy2LYgZzA25Hx7dvToUaP0pKQk9dr79u2rDgQti+3rueeeo3z58iiKwrJly4zSU1NTWbt2rbqvvb29mlZW25eePiB97LHH8ty3LLYtgK5duwKwc+dOk9/QZmZmsmrVKiCnneRe/bio6kwC+zLCzs6OyZMnA7B69WpWrlypfsUdHBzMuHHj0Ol0dOjQoVQ+eShML7zwAnXq1CEpKYlRo0apc0onJiYyd+5cdu/ejZ2dnckZGB5mK1euVL8y/Oijj6z+Zqcs1teIESNwc3MjNTWVUaNGcejQIXX6vLNnzzJy5EjOnDlDuXLlmD59uprvtddew83NjRs3bjB27Fh19dDY2FjeeecdQkJCcHZ2ZuzYsSVyXQ+asti2IOfhi7e3N4qiMHnyZPbs2aPOnnHq1CmGDRtGREQE1apVY9KkSWq+sti+qlSpwltvvQXATz/9xKxZs9TuDfp6uH79OpUrVzbqUlhW25deWFgYYHnFer2y2LYAxowZQ5UqVUhPT2fEiBHs27dP/ay/fPkyY8eO5cyZMzg6OjJ16lSDvEVVZxrFUscgUerMmjVLXc7e0dERJycndZR2nTp12LRpk8EdZVk0Y8YMtm7dSqdOnfjmm29M7hMWFsbw4cPV/nUuLi6kpKSob+hZs2YxdOjQYitzUcvIyKBDhw4kJyej0WioWrVqnnm2bNmifq1d1uoLcgZVvf766+pX9Y6Ojjg6Oqrzaru4uLB48WKjvqtHjhzh9ddfV2+8XV1dSUpKQlEU7O3t+eKLLwyWJi/t9J9Z7dq1Y/369UbpZbFtQU43kLFjx6qD6+5vXx4eHnz99ddGM3WUxfalKAqffvqp+mQectqJfvEqV1dXvvjiC9q3b2+Ut6y2L8h5Up+ZmcmSJUvUp8uWlMW2BTmf9ePHj1e/1XF0dKR8+fJq+3J2dmbBggU8/fTTRnmLos4ksC+Ddu/ezYYNGwgNDSUtLY0aNWrw1FNPMW7cOIOZFMoqawJ7gLi4OFauXMnvv/9OdHQ0zs7ONG/enFGjRqmzd5QWZ86cMTuHsTn79+/Hx8dH/X9Zqi+927dv89133/Hbb78RHh6ORqPBx8eHLl26MHz4cHU5+vtdv36dlStXcujQIeLj46lUqRJt27ZlzJgxNG/evJivomTlFdhD2WxbkDNwb+3atezfv58bN25gZ2eHj48PPXv2ZOTIkbi6uprMV1bb15EjRwgICCAkJISkpCQ8PT3p3Lkzo0aNMvisul9ZbF/JycnqNKCrV69Wuxfmpay2rfj4eNatW8fvv//OjRs3yMrKwtvbmyeeeIJRo0ZZXHSvsOtMAnshhBBCCCFKAeljL4QQQgghRCkggb0QQgghhBClgAT2QgghhBBClAIS2AshhBBCCFEKSGAvhBBCCCFEKSCBvRBCCCGEEKWABPZCCCGEEEKUAhLYCyGEEEIIUQpIYC+EEEIIIUQpIIG9EEIIIYQQpYBDSRdACCGKwowZM9i6dWu+8x07dgxXV9ciKJEQIi/du3cnMjKSAQMG8Nlnn5V0cYR46MgTeyGEEEIIIUoBeWIvhCj1du7cibe3t1X7VqxYsYhLI4QQQhQNCeyFEKVe+fLlJWAXQghR6klXHCGEEEIIIUoBeWIvhBBmDBs2jKNHj/Lqq68yePBgZs+ezalTp3BycqJevXosWrQIHx8fAFJTU/nxxx85cOAA58+f586dO2g0Gtzc3GjWrBn9+/enZ8+eRuf44osv8Pf3p2nTpvz4448cPnyYtWvX8vfff5OSksIjjzxC7969GTNmDOXKlSM7O5vvv/+eH3/8kUuXLgFQv359hgwZwoABA8xeS3JyMoGBgezfv5+rV6+SlpZGtWrVaNu2LX5+fjRv3txs3uDgYDZv3szJkyeJiYnByckJT09P2rZty5AhQ2jUqFG+67Zhw4YAfP7553To0AF/f3/2799PbGwsHh4eNG/enFGjRlksF+QMdt60aRMnTpzg9u3blC9fnrp16/L0008zZMgQnJ2djfLo67xRo0YEBgYyb9489u7dS1ZWFj4+PkyZMoVu3bpZdR379u3jp59+4vTp0yQkJODs7Iy3tzft27fHz8+PRx991Gze8PBw1q5dy6FDh4iKigLgkUce4cknn2TEiBF4eXlZPPfx48fZvHkzp06d4tatWzg4OFC/fn2effZZhg4dSrly5Uzmu3btGgEBARw5coTIyEgAPD096dChA8OGDaNevXpGeSIiIujRowcAP/30E97e3nz99dfs379fPXfDhg3p378/L7zwAvb29ibPnZGRwfbt2/nf//7HlStXSE9Pp379+gwaNIgXX3zR4vUKIfKmURRFKelCCCFEYcs9K87+/fvVADw/9IH9M888w4kTJ4iLi1PTatSowb59+7CzsyM0NJRx48YRExNj8XgvvfQS8+bNM9iWO7Dv3r07X3zxhcm8vr6+rFq1ijfffJO//vrL5D7jxo3jnXfeMdp+6tQpJkyYQGxsrNmyjR49mqlTp6LRaAy2L1++nP/+979m82k0Gt577z2GDx9udh9T9IH9Bx98wLfffktERITJ/aZMmcLYsWONtmdmZjJnzhx++OEHs+eoUaMGX331FQ0aNDDYrq/zBg0aUKVKFY4ePWpwPXv27KFWrVp5XsN//vMf/ve//5lNd3R0ZPHixTzzzDNGaT/88ANz5swhMzPTZF5nZ2c+++wznn32WaO0jIwM5s2bx6ZNm8yeu379+qxZswZPT0+D7d999x2LFi0ye157e3veeecdRo8ebbA9d2C/ePFiPvvsM7PtqVu3bnz55ZfY2Rl2Crhz5w5vvPEGJ0+eNJmvT58+nDhxglu3bsmsOELYSJ7YCyFEHvbs2UO5cuX45JNP6NKlCzdv3iQuLg47Ozvu3bvH66+/TkxMDFWqVOHtt9+mffv2uLm5ERcXR3BwMF9++SW3b99my5YtDBgwgDZt2hid49KlS5w9e5bmzZvz9ttv07hxYyIjI5kzZw7//PMPwcHBDBgwgKtXrzJixAhefvllqlSpwunTp/noo4+Iiorim2++YejQoQbB3NWrVxk1ahT37t3D09OTiRMn8sQTT+Ds7Mzly5f5+uuv+f333/n6669xdnZmwoQJat6///5bvdHo1asXw4cPx8fHh8zMTE6dOsWiRYuIiIhgwYIFdOnShdq1a+e7bhcvXkxKSgp9+/bltddeo3r16pw5c4aFCxdy4cIFFi9ejLe3N88//7xBvrlz56pB/fPPP4+fnx+1a9cmKSmJP/74A39/fyIjIxk5ciRbt27Fw8PD6NwXL14EYMSIEYwYMYK0tDSOHz9uVVD/yy+/qEH90KFDGThwIJ6enty7d4+goCAWL15MQkICM2fOpH379lSuXFnNu2PHDj744AMAWrZsyeuvv07z5s3Jzs7m5MmTfPHFF1y8eJF33nmHypUr06FDB4NzL1iwQA3qn3jiCcaNG0eDBg1ISEhg69atfPPNN1y6dIm3337bIPjfuHEjn376KQC1a9fmrbfeok2bNtjb23PixAn++9//cunSJRYuXIijo6PZm7WZM2cCOTddzzzzDC4uLvzzzz988sknXLt2jd9//53t27fTr18/g3yTJ09Wg/phw4YxaNAgqlatyvnz51myZAk7duzIs96FEHlQhBCiFJo+fbqi1WoVrVarXLx4UUlOTrb4k56ebnQMPz8/9RirV682eZ7AwEB1n+DgYJP7BAUFqfssXrzYIO2///2vmvbcc88pqampBulXrlxRGjZsqO6zYsUKo+P/9ttvavrWrVsN0oYPH65otVqlS5cuSkxMjMnyvffee4pWq1UaN26s3LhxQ93+2WefKVqtVunZs6eSnZ1tlO/y5ctq2ZYvX27y2Oboy6vVapV58+YZpScmJipPP/20otVqlSeffNLg9Tl27JjF+lAURbl06ZLSokULRavVKu+9955BWu46HzNmTL7KrTdx4kRFq9Uqr776qsn0v/76Sz3HTz/9pG5PSkpS2rRpo2i1WmX06NFKZmamUd7k5GTl+eefV7RarfL0008rOp1OTTt37pzSqFEjRavVKpMnTzZI0/P391fPffjwYUVRFOX27dtKq1atFK1Wq/Tp00dJTEw0ypeUlKQMGDBA0Wq1StOmTZWoqCg1LTw83OA1CwoKMsp/48YNpXHjxopWq1XGjRtnkLZ//341r7+/v1HetLQ05eWXX1b3mT59uqlqFULkQQbPCiFKvd69e/P4449b/Jk1a5bFY/Tq1cvkdi8vL4YOHcqgQYNo166dyX1at26Ng0POF6Tx8fFmzzF8+HDKly9vsK1OnTpUrVoVgHLlypl8itqqVSv19+joaPX3y5cvc+TIEQDefPNNk0+tAaZPn46joyM6nY4tW7ao2/XdNVJSUrh3755Rvrp16/LVV1+xefNm/Pz8zF6XJR4eHkydOtVou4uLi9qtKDo6mqCgIDUtMDAQyOmPPmbMGJPHrVevHkOGDAFg27ZtpKSkmNzP3Oual4yMDCCne4mpbi0dO3Zk+fLlbN261WBsxfbt20lMTATg/fffV9tFbhUrVmTKlClATn/43Ne+Y8cOsrOzcXR05P333zfq7gI57ahevXp06tRJve4dO3aor+EHH3yAi4uLUb5KlSoxZ84cIOe1//77701ee5s2bfD19TXaXrNmTbRaLYBR16rt27cDOa/3uHHjjPKWK1eO999/3+T5hBDWk644QgiRBzc3Nx555BGTad27d6d79+5m8yYlJXHy5Ens7e3JyspCp9OZ3bdFixYmt7u7uxMXF0fdunVNDgbNHaTpA07IGfSq17BhQ5PBOYCDgwNarZazZ89y/PhxdXu7du1Yv349cXFx9O/fn5dffpnOnTvTsGFDtS9+ly5dzF6PNZ5++mmcnJxMpnXt2hUHBweysrI4fPgwnTt3BlD7xDdp0oS0tDSzx9bXZ2ZmJqdPnzbq0gLQuHFjm8rt6+vL77//zvnz53nppZd46aWX6NSpE3Xq1AFy+uqbGiytf03c3Nzw8PAw+5o0adIEOzs7srOzOXbsGB07dgTg8OHDADRv3ly94btfpUqV2LVrl8nzVq1a1ewNKMBjjz1G7dq1uXbtmkH7yc1cOwWoVq0akDOYPDd9uTt27GjyZgZyrsnT09Pg5lQIkT8S2AshSj1bB8/qValSJc99dDodJ06c4MyZM9y4cYPw8HCuXr3KzZs3UXLNUaBYmK/A3Hn0T2VNPWUFzM5AcuPGDfX3gQMH5nkNALdu3VJ/f+qpp3juuef45ZdfCA8PZ/HixSxevJhq1arRvn17OnfuTLdu3XB1dbXq2Kbon/CaUq5cOby8vIiIiFDLlZycrA5i3rdvH48//ni+rys3d3f3fJY4x5AhQ9i3bx/Hjx/n/PnzfPzxx0DOtwgdO3akS5cuPPnkk0Y3YvrX5M6dOzaVXR/05nc8g/4Ypma8uV/9+vW5du2aTXWmv0nL3c7T0tK4c+cOQJ7jF+rVqyeBvRAFIIG9EELkwdy0gXp79+5l3rx5JgOhGjVq0LFjR7Zv327x6TJg8ml8QSQnJxcoj0ajYenSpXTr1o1NmzZx6tQpsrOziYuLY8eOHezYsQMnJyf8/PyYMmWK2SexluR1U6CvE325zD3hzou5usjrtTWnXLlyrF27lk2bNrFlyxbOnTsHwM2bN9myZQtbtmyhUqVKvP766wbdhQr6mugD5Py2Ff0xrFmoTX9sS9/w5Mfdu3eNjm2OuZtXIYR1JLAXQogC2LdvHxMnTkRRFNzc3Hjqqado0qQJ9erVo0GDBurTzZ07dxZ72XIHUX///bdNQaxGo6Ffv37069eP+Ph4Dh8+THBwMIcOHSIyMpKMjAzWrFlDWloaH374Yb6Pn9fNjr6PuP7bjNzXNGbMGJP984uLg4MDfn5++Pn5ERUVxaFDhwgKCuLIkSPExsaSnJzMokWL0Gg06vSR+vK3aNHC4lSd5jg7O5OUlGTU1SUvFSpUAKy7MdLvo89TUG5uburv5sY66KWnpxfKOYUoq2TwrBBCFMDChQtRFIUaNWrwyy+/8PHHHzNkyBB8fX3VoD4tLS3PgKYo5B4XYG6eeD1LXYT03N3d6dOnD3PnzuW3337j+++/V8/xww8/2PQ0Ond3ofulpqaq34LUqFEDyHmiq3+qWxjXVFi8vLx48cUXWbhwIX/++SerVq1Sp7hcs2aNup+3tzeAujCUJabKr89vqd4gZ4Dx6tWrOXToEPBv/V2+fDnP8+oXPtPnKahy5cqpfe+vXLlicd/w8PBCOacQZZUE9kIIYaP4+HiuXbsGwDPPPGO277E+uALIzs4ujqIB0LZtW/X3vXv3mt0vMTGR9u3b061bN2bPng3kjBl4/fXX6d69O/PnzzeZr2XLlrz66qsAZGVlWVwAy5wDBw6YTfv999/V+tKvBKvRaNR1AA4fPmzxhumLL76gdevWPP/885w/fz7fZTMnPj6eESNG0LlzZwICAozSNRoNXbp0oW/fvgDcvn1bHdSsH7gaFxdndqEmgKCgIFq0aMEzzzxjsAhW69atATh9+rTaLed+WVlZLF26lEWLFqlzw+vbwu3btw0W5Lrf2bNn1ZsGa8cAWEM/yPqvv/4y+y1NeHh4noG/EMIyCeyFEMJGufsa659y3i8mJoZPPvlE/b+5FT+LwmOPPUazZs0AWL16tdkyLliwgDt37nDz5k11MKu9vT1JSUlERkaybds2s0H72bNngZxBk+ZmDrIkNDTUYIpNvTt37rBkyRIAGjRoYDATy6BBg4CcvtuffPKJySfbly5dYu3atSQnJ5OYmGjVoFFrubu7c/36daKjo9m4caPJmwtFUdR+94888og6qLR///7qlKZz5841+S3HvXv3mD9/Punp6dy4ccPg2l966SUgZ/ajRYsWmSzfN998Q1JSEpAz1av+vPquNXPnzlXTc0tNTeWjjz4CclbNfeGFF/KuDCu9+OKLQM5rtnDhQqP07Oxss6+lEMJ6EtgLIYSNXF1dadmyJQAHDx5kzpw5XLx4kYSEBC5dusTXX39Nv379DLqM2Dr401YfffQRTk5OJCcnM3jwYL755huuX79OfHw8J0+e5K233mLz5s0ANG3aVA0cAcaOHQvkPF0eNmwYO3bsIDw8nPj4eM6cOcOsWbPU+clfeeUVmweizpo1i6VLl6rl2rdvH4MGDSI8PBw7Oztmz56tTq8JOdNgPvPMMwBs3ryZ0aNHc+TIEeLj4wkPD2fTpk0MHz5cDZrff/99HB0dbSqbOfoBsZcuXeLVV1/lt99+U1ckPnHiBG+99ZY6daj+Ww3IuSmYNm0akHNT89JLL7Fjxw6io6OJiYlh//79+Pn5ERoaCuSsalu/fn01/2OPPcbLL7+sXvtbb73FqVOnSEhI4Pz583z66ad8/vnnADz55JN06tQJyOnn/u677wJw4cIFXnrpJXbt2kVMTAy3b99m3759vPLKK/z9998AvPPOOzatJGxO69at1ZmZAgICmDJlCqGhody5c4eTJ08yZswYfvvtN7MzPAkhrCODZ4UQogA+/PBDXn31VZKSkggMDFQXT8qtQ4cOKIpCUFAQ1/+vvbsHaSyNwjj+JJCgYhcrBYs0ahBEtFGDIkIKC02CUQS/OxVEKxHRagqNkQhapJeIEoKNILERMaiVKQLGzkylQUEFNYXobjFMmBk/mHV3ZuHO/1fevOGe3DQPL+e+5/Pn31pfZWWlQqGQJiYmdHt7K7/fL7/f/+a6bwNwU1OTxsbGtLy8rLOzs9zQpB81NzfnQuM/5XQ6lUqlFAqFFAqFvvusoKBACwsLufaTb83Pz8tsNmt7e1vxeFzxePzFGovFoqmpKblcrg/V9p7u7m6dnJwoEokomUxqeHj41XVdXV0aGBj47lpPT4+y2ayCweC7z9Xr9WpycvLF9ZmZGT08PGhra0uxWEyxWOzFmtraWgWDwRc1Z7NZBQIBpdNpTUxMvPiexWLR+Pi4BgcH3/rpHzY7O6tsNps7Uelrm9BXTU1Nen5+1v7+/n9+b+BPQbAHgH/B4XBoc3Mz96JiJpORyWRSUVGRysvL5Xa75XK5tL6+rqOjI6XTaaVSqQ8PRvqIhoYG7ezsKBwOa29vT+l0Wvf39yosLJTD4VBra6s8Hs+rxxiOjo6qvr5eGxsbOj4+ViaT0dPTk2w2m6qqqtTW1vbqIKafZbfbNTc3p5WVFe3u7urm5kbFxcVqbGxUf3//my9w5ufna2lpST6fT9FoVIlEQldXVzKZTCouLlZdXZ16e3tlt9s/XNt7TCaTPn36JJfLpWg0qmQyqcvLy9x/X1NTo46OjlcntEpfdvxbWloUDod1eHio8/NzPT4+ymazqbq6Wp2dnbmhVD+yWq1aXFyU2+1WJBJRIpHQ9fW18vLyVFFRofb2dnk8nld3v4eGhtTc3KzV1VUdHBzo4uJCZrNZJSUlcjqd8vl8v+yZWa1WBQIBtba2am1tTaenp7q7u1Npaam8Xq/6+vo0MjLyS+4N/ClMf9HQBgD4zcrKyiR9aVOZnp7+n6sBAGOgxx4AAAAwAII9AAAAYAAEewAAAMAACPYAAACAARDsAQAAAAPgVBwAAADAANixBwAAAAyAYA8AAAAYAMEeAAAAMACCPQAAAGAABHsAAADAAAj2AAAAgAEQ7AEAAAADINgDAAAABvA3gCoT+jaoaQoAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 800x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(8, 3))\n",
    "sns.set_theme(style=\"whitegrid\", rc=custom_params, font_scale=1.7)\n",
    "\n",
    "to_plot = df[(df['altered_bandwidth'] == True) & (df['is_record'] == False) & (df['device'] == 'Quest-Pro')]\n",
    "to_plot['bw_text'] = to_plot['bandwidth'].apply(lambda x: '400' if x == 999999 else str(x))\n",
    "to_plot.sort_values('bandwidth', ascending=False, inplace=True)\n",
    "\n",
    "sns.boxplot(x=to_plot['FPS'], y=to_plot['bw_text'], showmeans=True, meanprops=custom_mean, palette=\"colorblind\", ax=ax, flierprops=custom_outliers)\n",
    "# ax.axline((0, 72), slope=0, color='red', linestyle='--', linewidth=1.5)\n",
    "ax.axvline(x = 72, color = 'red', linestyle='--', linewidth=2, label='72 FPS')\n",
    "# labels = [item.get_text() for item in ax.get_xticklabels()]\n",
    "# labels[4] = 'N/A'\n",
    "# ax.set_xticklabels(labels)\n",
    "# ax.set_xticks([0, 20, 40, 60, 80])\n",
    "ax.set_xlabel('Frames per second')\n",
    "ax.set_ylabel('Bandwidth limit\\n[Mbps]')\n",
    "ax.set_xlim(0, 80)\n",
    "ax.set_xticks([0, 10, 20, 30, 40, 50, 60, 70, 80])\n",
    "# ax.set_title('Quest Pro')\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.savefig('./figures/bandwidth_exp/Quest-Pro_fps_vs_bandwidth.pdf', dpi=300, format='pdf')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "a94e53c9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 576x216 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(8, 3))\n",
    "sns.set_theme(style=\"whitegrid\", rc=custom_params, font_scale=1.7)\n",
    "\n",
    "to_plot = df[(df['altered_bandwidth'] == True) & (df['is_record'] == False) & (df['device'] == 'Quest-Pro')]\n",
    "to_plot['bw_text'] = to_plot['bandwidth'].apply(lambda x: '400' if x == 999999 else str(x))\n",
    "to_plot.sort_values('bandwidth', ascending=False, inplace=True)\n",
    "\n",
    "sns.boxplot(x=to_plot['FPS'], y=to_plot['bw_text'], showmeans=True, meanprops=custom_mean, palette=\"colorblind\", ax=ax, flierprops=custom_outliers)\n",
    "# ax.axline((0, 72), slope=0, color='red', linestyle='--', linewidth=1.5)\n",
    "ax.axvline(x = 72, color = 'red', linestyle='--', linewidth=2, label='72 FPS')\n",
    "# labels = [item.get_text() for item in ax.get_xticklabels()]\n",
    "# labels[4] = 'N/A'\n",
    "# ax.set_xticklabels(labels)\n",
    "# ax.set_xticks([0, 20, 40, 60, 80])\n",
    "ax.set_xlabel('Frames per second')\n",
    "ax.set_ylabel('Bandwidth limit\\n[Mbps]')\n",
    "ax.set_xlim(0, 80)\n",
    "ax.set_xticks([0, 10, 20, 30, 40, 50, 60, 70, 80])\n",
    "# ax.set_title('Quest 2')\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.savefig('./figures/bandwidth_exp/Quest-Pro_fps_vs_bandwidth.pdf', dpi=300, format='pdf')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fffba19a",
   "metadata": {},
   "source": [
    "## Dropchance experiments"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "c04aabcf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x300 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(figsize=(8, 3), ncols=2, sharey=True)\n",
    "sns.set_theme(style=\"whitegrid\", rc=custom_params, font_scale=1.7)\n",
    "\n",
    "to_plot = df[(df['altered_dropchance'] == True) & (df['is_record'] == False) & (df['device'] == 'Quest-Pro')]\n",
    "\n",
    "sns.boxplot(y=to_plot['FPS'], x=to_plot['dropchance'], showmeans=True, meanprops=custom_mean, palette=\"deep\", ax=axes[0], flierprops=custom_outliers)\n",
    "axes[0].axline((0, 72), slope=0, color='red', linestyle='--', linewidth=1)\n",
    "\n",
    "labels = [float(item.get_text()) for item in axes[0].get_xticklabels()]\n",
    "labels = [str(x*100) for x in labels]\n",
    "labels[0] = '0'\n",
    "axes[0].set_xticklabels(labels)\n",
    "axes[0].set_yticks([0, 20, 40, 60, 80])\n",
    "axes[0].set_xlabel('Drop Chance [%]')\n",
    "axes[0].set_ylim(0, 80)\n",
    "axes[0].set_title('Quest Pro')\n",
    "\n",
    "\n",
    "to_plot = df[(df['altered_dropchance'] == True) & (df['is_record'] == False) & (df['device'] == 'Quest-2')]\n",
    "\n",
    "sns.boxplot(y=to_plot['FPS'], x=to_plot['dropchance'], showmeans=True, meanprops=custom_mean, palette=\"deep\", ax=axes[1], flierprops=custom_outliers)\n",
    "axes[1].axline((0, 72), slope=0, color='red', linestyle='--', linewidth=1)\n",
    "\n",
    "labels = [float(item.get_text()) for item in axes[1].get_xticklabels()]\n",
    "labels = [str(x*100) for x in labels]\n",
    "labels[0] = '0'\n",
    "axes[1].set_xticklabels(labels)\n",
    "\n",
    "axes[1].set_xlabel('Drop Chance [%]')\n",
    "axes[1].set_ylim(0, 80)\n",
    "axes[1].set_title('Quest 2')\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.savefig('./figures/dropchance_exp/fps_vs_dropchance.pdf', dpi=300, format='pdf')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "08e4fe59",
   "metadata": {},
   "source": [
    "## Workload Offloading Experiment Graphs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7e64b687",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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