{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "92131bc1",
   "metadata": {},
   "source": [
    "# Apple Health export.zip to pandas\n",
    "\n",
    "Reads the file the iPhone Health app writes with **Export All Health Data** (Apple's iPhone User Guide: \"You can export all of your health and fitness data from Health in XML format\"), streams its `Record` and `Workout` elements into pandas DataFrames, and charts three things: daily steps, resting heart rate and nightly sleep.\n",
    "\n",
    "**The input here is synthetic.** It is `apple-health-export-synthetic.zip` from [https://aifitnessapi.com/own-your-data](https://aifitnessapi.com/own-your-data#notebooks): 120 made-up days from a \"Synthetic Watch\", a \"Synthetic Phone\" and a \"Synthetic Scale App\", generated from a fixed seed. Point `EXPORT` at your own `export.zip` (or the `export.xml` inside it) to run it on your data, which never leaves your machine.\n",
    "\n",
    "Apple publishes no schema for `export.xml` that we could find, so this notebook reads elements and attributes by the names the file uses (`Record`, `type`, `sourceName`, `unit`, `startDate`, `endDate`, `value`). Only pandas, matplotlib and the standard library are used."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "e28aa400",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'../samples/apple-health-export-synthetic.zip'"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import os, urllib.request\n",
    "\n",
    "def local_or_download(path, url):\n",
    "    \"\"\"Use the file next to this notebook if it is there (a clone of the repo),\n",
    "    otherwise download the synthetic sample once (Colab).\"\"\"\n",
    "    if os.path.exists(path):\n",
    "        return path\n",
    "    name = os.path.basename(path)\n",
    "    if not os.path.exists(name):\n",
    "        urllib.request.urlretrieve(url, name)\n",
    "    return name\n",
    "\n",
    "# Your export: a path to export.zip or export.xml.\n",
    "EXPORT = local_or_download(\"../samples/apple-health-export-synthetic.zip\",\n",
    "                           \"https://aifitnessapi.com/samples/apple-health-export-synthetic.zip\")\n",
    "EXPORT"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "12f282fe",
   "metadata": {},
   "source": [
    "## Stream the XML\n",
    "\n",
    "`iterparse` hands over one element at a time and `elem.clear()` frees it, so memory stays flat even for an export of hundreds of megabytes. Inside a ZIP, the file to read is the shallowest one named `export.xml`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "47ca9ba7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "12,880 records, 69 workouts\n"
     ]
    }
   ],
   "source": [
    "import zipfile\n",
    "import xml.etree.ElementTree as ET\n",
    "import pandas as pd\n",
    "\n",
    "def open_export(path):\n",
    "    if path.lower().endswith(\".zip\"):\n",
    "        z = zipfile.ZipFile(path)\n",
    "        names = [n for n in z.namelist() if n.split(\"/\")[-1].lower() == \"export.xml\"]\n",
    "        return z.open(min(names, key=lambda n: n.count(\"/\")))\n",
    "    return open(path, \"rb\")\n",
    "\n",
    "RECORD_COLS = [\"type\", \"sourceName\", \"unit\", \"startDate\", \"endDate\", \"value\"]\n",
    "WORKOUT_COLS = [\"workoutActivityType\", \"sourceName\", \"duration\", \"durationUnit\", \"startDate\", \"endDate\"]\n",
    "records, workouts = [], []\n",
    "with open_export(EXPORT) as f:\n",
    "    for _, elem in ET.iterparse(f, events=(\"end\",)):\n",
    "        if elem.tag == \"Record\":\n",
    "            records.append([elem.get(c) for c in RECORD_COLS])\n",
    "            elem.clear()\n",
    "        elif elem.tag == \"Workout\":\n",
    "            workouts.append([elem.get(c) for c in WORKOUT_COLS])\n",
    "            elem.clear()\n",
    "\n",
    "df = pd.DataFrame(records, columns=RECORD_COLS)\n",
    "wo = pd.DataFrame(workouts, columns=WORKOUT_COLS)\n",
    "print(f\"{len(df):,} records, {len(wo):,} workouts\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ce6ec817",
   "metadata": {},
   "source": [
    "## Dates: keep the day where it happened\n",
    "\n",
    "Each timestamp is written with its UTC offset, for example `2026-06-01 07:13:00 -0700`. The first ten characters are the local calendar day, which is the day a person means by \"Monday's steps\". Converting to UTC first would push late-evening samples into the next day, so the day comes straight from the string."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "343f60a3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>rows</th>\n",
       "      <th>first</th>\n",
       "      <th>last</th>\n",
       "      <th>units</th>\n",
       "      <th>sources</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>short</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>HeartRate</th>\n",
       "      <td>6120</td>\n",
       "      <td>2026-06-01</td>\n",
       "      <td>2026-09-28</td>\n",
       "      <td>count/min</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ActiveEnergyBurned</th>\n",
       "      <td>1800</td>\n",
       "      <td>2026-06-01</td>\n",
       "      <td>2026-09-28</td>\n",
       "      <td>kcal</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DistanceWalkingRunning</th>\n",
       "      <td>1800</td>\n",
       "      <td>2026-06-01</td>\n",
       "      <td>2026-09-28</td>\n",
       "      <td>km</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>StepCount</th>\n",
       "      <td>1800</td>\n",
       "      <td>2026-06-01</td>\n",
       "      <td>2026-09-28</td>\n",
       "      <td>count</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SleepAnalysis</th>\n",
       "      <td>1080</td>\n",
       "      <td>2026-05-31</td>\n",
       "      <td>2026-09-28</td>\n",
       "      <td></td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RestingHeartRate</th>\n",
       "      <td>120</td>\n",
       "      <td>2026-06-01</td>\n",
       "      <td>2026-09-28</td>\n",
       "      <td>count/min</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HeartRateVariabilitySDNN</th>\n",
       "      <td>120</td>\n",
       "      <td>2026-06-01</td>\n",
       "      <td>2026-09-28</td>\n",
       "      <td>ms</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BodyMass</th>\n",
       "      <td>40</td>\n",
       "      <td>2026-06-01</td>\n",
       "      <td>2026-09-26</td>\n",
       "      <td>kg</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          rows      first       last      units  sources\n",
       "short                                                                   \n",
       "HeartRate                 6120 2026-06-01 2026-09-28  count/min        1\n",
       "ActiveEnergyBurned        1800 2026-06-01 2026-09-28       kcal        1\n",
       "DistanceWalkingRunning    1800 2026-06-01 2026-09-28         km        1\n",
       "StepCount                 1800 2026-06-01 2026-09-28      count        2\n",
       "SleepAnalysis             1080 2026-05-31 2026-09-28                   1\n",
       "RestingHeartRate           120 2026-06-01 2026-09-28  count/min        1\n",
       "HeartRateVariabilitySDNN   120 2026-06-01 2026-09-28         ms        1\n",
       "BodyMass                    40 2026-06-01 2026-09-26         kg        1"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "for frame in (df, wo):\n",
    "    frame[\"start\"] = pd.to_datetime(frame[\"startDate\"], format=\"%Y-%m-%d %H:%M:%S %z\", utc=True)\n",
    "    frame[\"end\"] = pd.to_datetime(frame[\"endDate\"], format=\"%Y-%m-%d %H:%M:%S %z\", utc=True)\n",
    "    frame[\"day\"] = pd.to_datetime(frame[\"startDate\"].str[:10])\n",
    "df[\"num\"] = pd.to_numeric(df[\"value\"], errors=\"coerce\")\n",
    "df[\"short\"] = df[\"type\"].str.replace(r\"^HK(Quantity|Category)TypeIdentifier\", \"\", regex=True)\n",
    "\n",
    "summary = (df.groupby(\"short\")\n",
    "             .agg(rows=(\"type\", \"size\"), first=(\"day\", \"min\"), last=(\"day\", \"max\"),\n",
    "                  units=(\"unit\", lambda u: \", \".join(sorted(set(u.dropna())))),\n",
    "                  sources=(\"sourceName\", \"nunique\"))\n",
    "             .sort_values(\"rows\", ascending=False))\n",
    "summary"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "92c7d9fa",
   "metadata": {},
   "source": [
    "## Daily steps, and the double-count trap\n",
    "\n",
    "Steps can arrive from more than one source. When a phone in a pocket and a watch on the wrist both count the same walk, summing every row adds the two counts together. HealthKit's statistics queries are built to merge overlapping sources; a raw export is not, so look at the sources side by side before trusting a sum. In this synthetic file the phone and watch rows cover different hours, so the sum happens to be right; check your own file the same way."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "d2f0f08b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 720x230.4 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>sourceName</th>\n",
       "      <th>Synthetic Phone</th>\n",
       "      <th>Synthetic Watch</th>\n",
       "      <th>all sources summed</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>120.0</td>\n",
       "      <td>120.0</td>\n",
       "      <td>120.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>2274.0</td>\n",
       "      <td>4698.0</td>\n",
       "      <td>6973.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>607.0</td>\n",
       "      <td>1021.0</td>\n",
       "      <td>1298.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>838.0</td>\n",
       "      <td>1996.0</td>\n",
       "      <td>3301.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1827.0</td>\n",
       "      <td>4140.0</td>\n",
       "      <td>6553.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>2268.0</td>\n",
       "      <td>4829.0</td>\n",
       "      <td>7290.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>2704.0</td>\n",
       "      <td>5380.0</td>\n",
       "      <td>7715.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>3849.0</td>\n",
       "      <td>6437.0</td>\n",
       "      <td>9290.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "sourceName  Synthetic Phone  Synthetic Watch  all sources summed\n",
       "count                 120.0            120.0               120.0\n",
       "mean                 2274.0           4698.0              6973.0\n",
       "std                   607.0           1021.0              1298.0\n",
       "min                   838.0           1996.0              3301.0\n",
       "25%                  1827.0           4140.0              6553.0\n",
       "50%                  2268.0           4829.0              7290.0\n",
       "75%                  2704.0           5380.0              7715.0\n",
       "max                  3849.0           6437.0              9290.0"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "plt.rcParams.update({\"figure.figsize\": (10, 3.2), \"axes.spines.top\": False, \"axes.spines.right\": False,\n",
    "                     \"axes.grid\": True, \"grid.alpha\": 0.3, \"figure.dpi\": 72})\n",
    "\n",
    "steps = df[df[\"type\"] == \"HKQuantityTypeIdentifierStepCount\"]\n",
    "by_source = steps.pivot_table(index=\"day\", columns=\"sourceName\", values=\"num\", aggfunc=\"sum\").fillna(0)\n",
    "by_source[\"all sources summed\"] = by_source.sum(axis=1)\n",
    "ax = by_source.plot(title=\"Steps per day (synthetic)\", lw=1)\n",
    "ax.set_ylabel(\"steps\"); ax.set_xlabel(\"\")\n",
    "plt.show()\n",
    "by_source.describe().round(0)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "17130d42",
   "metadata": {},
   "source": [
    "## Resting heart rate and nightly sleep\n",
    "\n",
    "Resting heart rate is one value per day here, so a 7-day rolling mean shows the trend. Sleep is a category type: each row is a stretch of time with a stage in `value`. Summing the stretches whose value starts with `HKCategoryValueSleepAnalysisAsleep` gives hours asleep. A night straddles midnight, so each stretch is assigned to a night by shifting its local start time forward 12 hours and taking the date: a stretch starting at 23:00 or at 02:00 both land on the morning the night ended."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "12670928",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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XUUSuKF5DRfQVxWuoCCUMqACstbV1b29CEQMMCTPhIoroLYrXUBF9RfEaKkIJAyoAK6KIIooooogiivgqoBiAFVFEEUUUUUQRRfQzigFYEUUUUUQRRRRRRD/D3B9fEolEWLFiBeXl5YwdOzb5ejAY5IsvvqC+vp5Ro0b1x6YUUUQRBUQ4HGbHjh1Jo+avAqLRKC0tLXt7MzJgt9sZOnRoUei2iCIGKAoegHV0dHDaaacxevRoVq9ezVVXXcWNN95Ia2src+bMYcqUKaxfv57zzz+f2267rdCbU0QRRRQQO3bsoLS0lJEjR2IwGPb25uQF4XB4nwtyJEmitbWVHTt2FCevRRQxQFHwEuSDDz7I3Llz+ec//8mSJUvYvHkzkiTxv//9j3POOYdnnnmGhQsX8re//S3ndftCkQJs8b7zffmEN7jvbXskGiMYie7VbQiEo0RjRTOIfCEQCFBdXf2VCb7yiXxeZwaDgerq6mSmMRaTCEfz02nnD0WJDYB7IhyNEYp8vboLQ5FY3s5zEXsfBc+AvfPOO9x9993cfPPNlJWVcffdd2MwGLj88suTy+zevZvhw4crfv7hhx/m4YcfBqClpQW325187/KnVvPPy/Yv7A7IcP0L6/jtWeMosfVL5TZviMQkznt8Ba9cM21vb0oK3lzrxu0Nc9mhgwv2HR0dHZrv/33xdiYPcjFrbFXBtuHrhGg0SiSy7wX7fUE0mp9Jwta2AMOr7OQzNI1Go7jdbt7/so3Vu7r53rHK42gu+MlrG7l0+mD2H1yShy0sHF5b3YI3FOWigwft7U3JimzjkF688MVu7GYTZx5Qm5f1FVF41NTUqL5X8Ehi165d3Hvvvdxyyy3Mnz+fM844g0WLFiXf93q9XHrppfzmN79R/Py1117LtddeC8C0adOSOyNJEk1dIc2dyzf8UQNWVzk1FY5++8584OOGNnZ39u+x0oOumIeo0VDw7dJaf8y4h5aAaZ87NgMVLS0t+1y5Lh/Ixz7FpABGowmzKX+FB5NJXLuxLT6WNDbxi3P7dh2HozGWNnZy5dHj9v17wtJFILjvjWtqyMd2xkztGKzmAbPPRWij4AFYVVUVP/7xj5kzZw4nnHACI0aMwO12U1NTQzgc5rzzzuPb3/42s2bNymm9vlCUrkD/zrQD4eg+WcrLhvkbmonEJKIxCZNx3ykNNXcG9/YmEAhHaXR79/ZmFPE1QEySKFRlzxuMsLXVx9ZWLyOqXb1ez6eN7XQFIwQHQGnPF4ri8Yf29mb0K7qDUUzGonjBVwUFP5OHHnooq1atAqC5uZnOzk7KysqIxWJcdtllnHjiiVx11VU5r7fdFyIaDyr6C4FIFG9o73KWeoMPN7mZPLhsn+NLtHQH9zqvLhCO0lAMwL6yePrpp1XfkySJ22+/Hb/fz+eff87atWsLui0xSQRhhYA3GOXIsTXMX9/cp/Us2NDMtGEVAyIAC4SjtPvCe3sz+hW+UIRAeOA9g4pQRsEDsNtvv50nn3yS2bNnM23aNO6//36sVit//etfef3113nnnXc45ZRTOOWUU2hu1j94eOI3Xn8GFYFwbMBlwJo8fsocFipdln0vAOsM4g3ubRJ+jK1txQDsq4qf/OQnqu8ZDAZGjBiBxWLhzTffTKFGFAIxSUIqVAAWinD6AYOZv6Fvchkfbm5l1oRaQgOA6O0LRen4mgVg3cEIgb3cuFRE/lDwEmRdXR2fffYZjY2NDBo0CJdLpMevvvpqLrroopRlc6lrJwKwYCSKw2rK3wZrIBAaeCXIBRtamD2hjkUbW+Idh/sOP6elO4jT1j/nTg3+cBSn1Ux3MDLgmiuKyIQkSTz66KOsWLEiZXyRJIlHHnmEzz//nEMPPZSrrroKg8HAjh07MJt7zvvixYtxu92cffbZALz99tvEYjFOOeWUPm9XoUuQ4+pLaF8WwheK4LTmfi1vb/NRXWKl3GEhOACyLL5QlHbf16sE6QtGCdj2/XNThD70SzHZZDIxZsyYZPAFUFJSQn19fcqPMYfaduLG69cMWCSKb4CVIOetb2b2xDpsZtM+V1YwIAaUvYlAOMrEQaVFHthXBH/4wx94//33ueqqq3j55Zfp7u4G4KWXXmLt2rV861vf4s033+Spp54C4Mknn0z5/IgRI7j77ruT///iF79gyJAhfd6uROKrUCVIXyhKic3MzDHVfLS5tVfrWLChmdkTxFgxEDJggXA0ORH/usAbihAI7/vnpgh9GLBTfo8/kQHrn4sxEo0Rjkp0D6AMWDASpcnjZ1SNC6vZuE8FYN3BCNUlVvx7eaYdiMSYNLiMxlYv++9Xvle35auIyx//mHZv/rIUlS4r/7zqMNX3n3vuOZ588kn2339/Bg8enJSwOe+885g1axYfffQRJpOJFStWKH5+2LBh1NfXs3z58iRXdfLkyX3e7kTgVagArDsYwWkzM3tCHa+vbGLOpPqc1zF/Qws/O2MKHze20enf9wMbXyiy1zmk/Q1vsQT5lcLADcC8IeyW/gsqAvHvGUg3/McNbRw+Wuhb2czGfYoD1tIVpK7MztbWvZt5ikRjjK0rYXNz917djq8qtIKlQsDn8yWpDOXl5Un5iJ/97GcsXLiQc889l6lTp6boCabjyiuv5Omnn6aioqJXDUJKSAZgBboFfaEIJVYzh4yo5Gf/XYMkSTmJ4QbCUZq7AgyvdrJih2dAZMB8oShlDsFttZq/Hp2BvlAU/wCrwhShjgF71Xr8YepK7f2mpJ7oPOneyyWzXDBvvSgpAPEM2L6z7c2dAepKbXt7MzAYYGS1i4a9HAgWkR/MmDGDl156CYD//ve/hMMik/Pmm2/y5z//meuvv56tW7dqruMb3/gGCxYs4O233+bCCy/My3bFClyC7A5GcdpMWExGxtSWsDHHCcVHW1qZMaoaiI8VA6DMFQhHGVxu/1pJUXhDkWQyoIiBjwEbgLX7QtSX2fotqxMIRymzm/ENoBLksi09GTDrPpYBa+4KUrsPBGCSBCNrnGxt9e3tTSkiD/jVr37FK6+8wsyZM1m9ejUHH3wwAHfeeSfXXXcdRx99NA6Hg6oqcV8MHToUENmy0tJSQJhcT58+nbFjxyZf6ytikoTRYCgYCT8ai2GJC7zOmlDLvBzlKBasb+a4iT2TtVCe1P8LiUA4xqAy+9eKB2Y2GosyFF8hDNwSpC9MfZm9/0qQ4Sg1JbYBowPW4PYypMKBzSy6DPc1En5zV5C6Urt4KMUkjHtRINZpNRcHta8IBg8ezLvvvpvx+hlnnMEZZ5yR8fpHH30EwI033pjy+vbt27njjjvytl2xGJhNhoJlwOSYNaGOm/71Od85doyu5SVJ4uPGdu44TXDdbAMkAyYhUemy5pVjuK/DbjEVx6qvEAZsBszjC1FXau/HDFiMKpd1wMhQzF/fzOyJPX5h+14GTJQgHRYTvr04oCRoMqV289dOU6iITEQiEWbMmMGBBx7IEUcckbf1xiQJs9HYLwFYbamNYCRGh04i/eYWLyOqnEkelc1sHBAcMIAKhzXZkPVVRyQaw9pPQXwR/YMBG4CFojFK7eZ+LUFWl1gHDAl//oYe/hfse4NqS2eQujIbLtveK+vGYhKGuDXyqJoiD6wIMJvNLF26lHvvvTev6xUBmIH+enYePa6WxRvVGw3kWLAhdbJmM5v2qcmaFipdFjxfEy0wbyjaK323IvZdDNgADMDWn12Q4RjVJbYBIUPhDUbo9IcZIjMNt+1jJPyWblGCdFpNe+2YBiJRbPFZ/8hqV1ELrIiCISaBySjK7flGMBJN8r8SOG5inW4e2PwNzcySTdb2NckaLVQ4rV8bOyJvMIKrKBb9lcKADMASmQurqf/Iov5wlGqXNasQq6TTbqRQliQg7ESOGJvqKrCvyVC0+0JUOCyU2Mx7Tdw2EI4lXRRG1biKnpBFFAySJMU5YPlfty8YzXBxmLpfOat3dmQN+LoCYbzBKPVl9uRr+9pYoYRoTMJkMFDhsHxtSPi+UATXXnYO+bogEo1l/PR2PVoYkAFYVyBCqd2MzWLqN7JoIG5Zk63+/vaa3Ty2uEFzmQ5/mPMf+qhgQdinW9uYMbo65bV9bVYrSWA0GnBazQXj1V34fx9pvh8IR5NNCqNqXDT2QwnylS928uKn2wv+PUUUDltaunO+dxMlyELwd7yhCM40Ozaj0cDYuhK2ZJlUrNjewaEjK1Ne29cka5TgC0WwW0xUOq1fnxJkMFrMgPUD3l+3h2N+O59zH/oo+TPjvvd7NUH/+etrNd8fkGfT4w9R6bRiMxn7TRU4EI7isGSPV3d6AryxahfXHD1adZnFG918tq2dBreX0bUl+dxMQKSqy+ypp9ZmNtEV2DfKp6FIDHO8ZFJiM+EtAK/O4wuxemeH5jKBcBR7/JwOq+ofKYqmDj/GHAQyi9j3EIzECEdjWM36sxExCawmIzEp/9e6NxjFpcANqi21ZfVKbPUKKoAc+1rHtBKEh6uJCufXJwPmDUZwWU0YDQaRAdyLneNfZbR5Q1x7zGiuOHJU8rW7X11Na3eQUTUujU9mIhu9ZkBmwNp9Ycqdln4VDBQP6+wDblcgzKqdHbRptEbP39DMRYcOy1mrRy/8oVjGtu5LGbCW7iC1JUIDzGkz4y2AuG2D24s/HNXMVPjDURzx42S3COJxIUvDIORTikrWAxsxScr5XopJEqYClSC9IWVuUIXTklWiod0botxpSXltXxor1OCPE9IrnJavjSG3NyQyYHZzUYqikAiEo0lqSgKldkuvEhjZvI4HZADm8YWodFr6tbMvEBZBjSRp87e6AhEOH1XNB1+2KL4fi0ms3tnBTceNY8EG5WX6vK2RnsAiAds+NKgKGyIRgLlshSlBNrZ6iUkQiqqfq8Q5TaDKZdUMnPMBjy+01/0vi+gbJImcOVKxGJgMhoIE+N5gBKcCN6jSmV2iweMPU+m0prw2EDhgvpCYEJfYzAOiMSofEBkwMzZLUYy1kPCFojjSMsoldjOdgdwzrdmqOwOzBOkLU+GwxjNg/VeCtFtM2C0iPa+WDesKhDnzwCHM39DM2Qftl/H+6qYOJg8pY0iFg65gpCCdLUGFbN2+pAMmtyFyWU0F6WJqcPswGNAMdoKyEiT08MCqSwqn0N/uC39tfOv2Bt55552k/RBARUUFRx55ZNbPffrpp4wbN47ycm1DdkmSep0BK1Tp2RuMUqJQgqxwWtjTGdD8rMcXpiItA2Y2GogUyrQyT0iUIHPxuxzo8IZEoO2wmIp2RAWELxTFaUnPgPUu0M+WXBiQT4J2X4gKp0VwFfopA+aPP6yzZWy6gxEOG1XFht1dRBXqDXJ/xqPGVrN4kz6tnt5sqxxW075DrJXbEDmthdEBa3R7GVntIqBRopaXIAFG1rhocBeWB+bxhfCHioNnobBs2TIWL17M4sWLefLJJ7n77rt1fe5Xv/oVmzZtyrqcFOdy5ZwBkySMBRptRQZMKQDLLtHQHq8myDEQghp/KLVMVGjqwL6ARLer3WIq0hgKiHyWILNN1AZsBmxYpbNfszqJcpXLasIbjFKtwp3vCkQoc1g4cGgFy7e3c8iIqpT3F210c+URgtw3e0IdL32+g5OmDCrItsphs+w74orNXUEO2E9kGkpsZroLQMLf2uZjQn2pZgAWCMewyY7TqBonn2/15H1b5PD4wtSWfj1KJnsDP/3pT5N/X3DBBRkWQ3KsXLmS119/nZkzZ6a8/sUXX/DWW28xfPhwzj33XJqbm/nwww+56KKLiEkS7j1NfPHpJ9x0zWXJz6xZs4a2tjbWrFlDLBbj2muv5R//+Ader5fLLruMmGTFaDDw+SfL+NfnHzJp0iTOO+88DAYD0WiUF154gYaGBubMmcPhhx9OMBjkhRdeYNy4cbzzzjuccMIJGduZgC8kyNnpqNRBUBcZMKvmMvsi/KGeyZPDYopnxAbk40w3uoMRRlpd2IslyILCF1IKwMx09aIEmQ0DMgPmSWbA+lGINc6rctnMmnXdzrhExuyJmYa47u4gZqMhSXqdNqyCL7Z58j57C0ViSYHRBEQGbN8IwFq6ekqQTpspK1ExV0iSRDgSo8Jpwa8ZgKWWakdWF14LrDsY2Wu6Z/2On5UX5kcHVq9ezZYtWzjrrLMU31+7di0XXHAB48aN44MPPuDDDz8EYMuWLdx0002MGzeOpUuX8uMf/5ja2lpuv/12uru7iUnwwtNP4m5pTrlvly9fzne/+13KyspYtGgRc+bMwWAwsH37dr71rW8RkyT+9/pr/PbndzJu3Diee+45fvaznwFw77338tFHHzFp0iSuvfZaVq1aRSAQ4JZbbuGVV15h6NChnHvuuTQ1NSnuS4KcnY4KR3aJBo8/TLnDornMvghfvAQJItP3deiETOiACRrM12QM2QvwhaIZsi5ldnNBVAQG5JTB4xeztnA01q9WRD0ZMPUTEY3FsJiMHDm2hgcXbuFHJ/W8t3BDS4ritNlkZHx9Ket2dTF5SFnetlVCyigj2Cz7Egesh4RfUgASfqs3RHWJFYfVpClTkl6qHVblZEd74UqQkiQVywf9hJ/97GfcfffdGAwGQqFQSinylltu4amnnuKaa67h/PPPB+CJJ54AYPTo0SxevJiNGzfS0tLC448/jtls5hvf+AYvv/wyF1x0CW++9govvfEeoWgsqSMHMHPmTC655BImTJjAHXfcwVVXXYXf7+fAAw9EkiQeevBBLrniW0ycNImbbrqJb33rW9xzzz389Kc/xe/3s2LFCvbbbz8+/vhjhg8fDojgzGg0smjRIpYvX86QIUMy9lXwSDMzYBWu7BmwxHg10OAPRZJZisp4J6Tc+eOriO643IjDYtLM7BfRNwTCmU1svS1BZsOADMDa48TRTn+4H62IxMPaaTPj1fEALbVbKLGZ2N0RYFC50NmZt6GZm44bm7Lc7Im1zN/QnNcATAn7EgfM7Q1Rk5ChsOZfByzB/xKlCe0MWJWrp/xiMRmJxISTQSF4MN6QcFP42nRB/kxbh61QWLVqFdu2beOMM84AwGQyMWvWrOT7DoeDtrY2DjnkkORrI0aMAGDp0qVcf/31zJw5k4kTJxKJiGvzyiuv5Ac/+AH7DRvB5P0PoLamOp5p7hmoEwR+s9mMwyGCAavVGnfHALfbzadLl9C0eR1Go4FzzjkHgB/+8Id88cUXHH300VRWVia/s66uDmOcOFZRUZHSXCCHmg5Y6Ve4Q9Avy/pVOC10fI0yYLbiJK6g8MmC+wR6U4IMR2OYs2i1DcgArCNuYxMIRwn1mxBrDEe87VkvaXz2hDoWbGjmosOGE4nG2NzczYT60pRljh1fx3ee+owbZo9VWUt+sC9lwCLRnlm3y5p/K6IGt5eRNS78oYhmAKbUzVpbaovLZNhVPtV7tMczczs9/ryvu4geJLJfCZhMJk466aSUZQ466CDeeustzjvvPDweD8uWLQPg5Zdf5qqrruLGG2/k7bffTi6///7709XVxZNPPM7Fc7+ZFCtNvZu1ccghhzBs7CR+/P3v0tHeysKFCwH4xz/+wbZt23A6nXzjG9/IeX/VOqkNBgMS6vSGSDSGaQAQ7pXgC0epjQvIfl38IBNK+HZL/wmQfx3hCylnwDpzzID5VKgBcgy83DMQlSTMJmO/CgYGwlFsFpOmeXQ4GsMka3WaNaGO+RsED+zzbR4OHlGZkVmpclmRkLIKJvYVNtO+oW4di0nID4GrALP0BreX0TUuHFazJlk1oNAtWkgeWIdfyKcUUTisWrWKXbt2cdppp2kud8UVV9DU1MRRRx3FN7/5TY4++mhAEPefeuop5syZw7PPPovJ1DMQX3bZZXywcCFHHTs7g39qMBiS2Sog5e/EOu655x5efvE5jph5OKeddloyS3bDDTdw/PHHc+SRRxKJRJJjhPy7jUajalZWyYpIDzrjDUNKMBkMvfa/6w+ILsh4dvBrIsbqDUZwFkuQBUdAoaHDZTXhy7FSkzhfWhiQGbAEbOb+6+yTy1CoZWy6AqkWQGNqXWxr8xOMRFPkJ9JxzLhaPtjYwlnTMnXDcoUaoX9fyYC1+UIpwo9Ws5Fwngf6xlYv508fxq6OAJ0BDRmKUKZeWsKU+/A0L818oN0XosI18AjPAwkHHHBAklCvBbvdzhtvvIHX68XlSrUXWbZsGT6fD6fTCZAs/YXDYS6ZexlmkymjA/uSSy5J/n3ggQfy0ksvASKIWr9+PRv3dDFo0CBefWseVilIXXWP/+I999zD7bffjsViSQncli9fnvz7D3/4g+q++EKZZtwJ2OKq6Uq6hULOR3lCYDObCEV7LMP2NYguSLHPlU5rwZtn9gUkul3t8a7PIgqDqJRp82QwGMi1V06Pefq+eXdpQJ42788uyHA0htVkxGVVz9h0BcIpA6HBYOCwkZV82tjOh5vdHDlW+aE+e2Id8/NkSxSOSoqkWqup/1wDtNDcmek9l2/saPcztNKB06otWBiIqARgBTLlbvdlqo4XsXeRHnwlkAi+EvjWt77FSy+9xA3fvRmjIS5WqvN+kk+KjEYDrpLMwqXNZksJvnJBt4oOGPQQ1JXg8YUzNMAS6E+bt94gtQsyu+XSVwGRmKj82C39J0BeRA9yrdZ36zBPL3gA1tnZybnnnsvEiRM57LDD2L59OwChUIgrr7ySAw44gJkzZ7JhwwZd6+vwhymPP8R6I4jYFxgMBiGboJKK7IpLUMgxa2IdzyzbSoXTqpqOnDKkjPUqwq25IhCJYlcwCTYaDcT2AbHClu6eDshCQJIkIvEg1GHVTtUHwrGMYzWqxkVjoUqQce6iAQOxQpgCFlEw/P3vf+eDDz7A6SrBYDDEf9B1T0kSSRV8vZ/JBX4F5e4EtCQaPPHrUQnWfrR56w0CMq2mCsfXgwOWgChBFgOwQsGAeqSVi2SUL6iszydHwQOwO+64g7POOov169dzxx13JFPpDzzwANXV1axatYo//elPXHnllbrW1+4LJwcNo1GbZFoIlGiYR4sALHVAmzm6Ol5+rFVdp8FgYOrQcpZv9/R5+wKhTF7TvgS5DVFB1t8VpD4e4DmypOr9CorHQyocNHm07Vt6i/a46GWRRDvwYLGI+1pYConX9E4AY1IP79FoyL8ht1DZV35oVDjUM2DtGiKs+7ofpJwoXemy0OH/6mfAEteQrViCLCjUYopsz5N0qOnzyVHwJ/X8+fM5+eSTeemllxg7diz3338/AK+88grXXXcdADNmzMDv97Nnz56s6+vwZ1pnaOG5j7fx2dZ2zWXc3UHue3OdrvU5NXTAugLhjAyY3WLi/EOGcfykes31HjWulqVbWnVtgxaUVPD3JTR3ZZYgzcb88cC2tIgOSBDnSisDlu4FCWDSmSl8dflOluRoI5Xw3XNYzXlpI//92xvY1dF/HZXPLNvKZ1vbsi7XG2HhaExiZ/u+3x0ak2WzrDo5qDEZp0QEYPmJwPQc50qXVVWiweMLUanCSRQNTvvuQ94X1pcBC0dj/PCFFf22XZIkccOznxdkvQnYzV8dEv4tL+bn3HQFwtz675V9Xo8kSaoZsFy1wBLm6VooKAnf5/PR2trKBRdcwFFHHcUdd9zBnXfeydy5c2lqamLYsGHJZYcOHcqOHTuor08NVB5++GEefvhhAFpaWti6uxUrEdxu8fCLRHr+VsKa7W7CAR8jXOqDyYZmLyu2tmquJ/E9YV+A9i6f4rJN7naM0czt+d5RgyDmw63hM2iN+tnV2qG5DXqwy+3DEFM+JtmOVX9gW7OH8ZXGlO2wGmJs39Wc0sDQW6ze2kytXcLtdhPweunwBlT3udMXwNvpwR1OLTlK0Sh7mlsyiJhyrNnWQn2plQkV+rdtd3sXBEswSRF27nEjBXqfCYzGJJ76qJHpQ2xYBqv4YuUZi9bvwhAOMMKlPvgbjUaam5uprMzs+NVCIBLDF4qoal3tTUSj0ZS/TQYj4XAYs1HCHwrjyHLZhqMSSJLYNylGJEKf91OSJNrb2zEajUQVxpwETNEg25tDuN2ZgVZTawc1tlLFz0qRMHvcbVQYg33azkKhyxfA3+nBHRBBWLc/qLgfW9v8vPT5Dq4+tJa60sLzLze7fbyzZnfGtnR09E0TLxiJYZRiuN1ugr5uPF3evT6W5wPvr93N7j2D+9zssasjyEuf7+CGI+p71RGcQCAcxURM8dhaDVG27WrBFNIn+LunzZN1mYIGYEajkZaWFhYvXsyYMWO44IILmDt3LnPnzqW0tBSv14vVKm4Kn89HWVmmGOm1117LtddeC8C0adOImuwMqTFTU1MjdsDc87fiNph3g8WuucymTgOhmEF1GUmSkt8j2YKEaVJe1tzFoGrt7VHDYL+ZaKOvV5+VoyngobykQ3E92Y5Vf6ArspVxQ+upqekhP1eUOLCVlFOTByVrd6CFI8fWU1NTwxDJTtSgcq6AKCb2q6/LFN1z2nCVV6p2lgEYLC1Y7I6cjqc/uoXR+9VRUdKGvaSMmppcVKRS8dnWNjoCEazOkn47p7u61mOxOzW/r7y8nB07dtDWlj1TJocvFKUrECbSVtgGjd4gGo0mJSE6/WGsZiP2uLeqLxShLUtjRSgSwxuK4HNa8YUiRGNkZMp7A7vdzqhRozCbm1XPybC6MI2tXsX3Q+xixKBqamoqM94rK9mFo6RM8b19ARHJyH6D6pKlV7WxbaV7D5VOCytaIlw8KtNFIN/495rNhKMSlVXVGRO4vtynrd1Byl3iOTYoYgWT8hg/kCBJEp3BKNaSihRB7N7AE+smEpNY1y5x0pS+HedSp03x2NaU78LkKNF9TxgtnVn5zgUNwOx2OyNHjkwGWWK2JmaTBx54IIsWLeLMM88kEAiwefPmpP2GFjr84aSKuh74w9GsAmpdAW1/vmBEdECC4IBpkfATqve5wqWx3lzg3+c5YJkkfFcO4rbZ0OD2MneGUDV3Ws2aXZDBSDTDM1N8TjRaaAVg/lA05zKixx+m3GnBYe27kvX89S1MqC/tN0VsSZJocHuzkn8tFgujRo3Kef1/eX8jL33ewsIfze7tJhYMbrc7OSD/6n9rmT2hjoPG1tDuDXHjvz7nmWsO1Pz80i2tvNe4h7vOmMRbq3ex0d3NTXPG5WXbfKEITov6dVrptLBih3K2TZsD1n8SP72BRCbvTcnBosHt45LDhzN/fTMXH5b9+dJXLNjQzOgaF4Fwdv5PLpBLjdjNXw0SflcwQjQm0RUI9zkAC4SjjKl1sWBDMydNGdTr9fjDmT6QCeRagkyYp2uh4Dpgd955J2effTYXXHABzzzzDD/84Q8BYb9x0UUX0dDQwFtvvcUNN9yAzZY9sGr3hRhTp7/kEgjHsh60rkBY0w4nGI4lsyR2i1GViNcVzCTh64XLZlIl9+eCQCSWoeIrR6FsdvTCryByJ+yI8jOgNHX4k55w2QQLJQlF8rLDaiIQ0n74+EPRnHkYCesah8XUZ/X/RZvcHD+5rt/IuO2+MJ2BSMG4J406grt9AYFwDFuS/G2l3Zu9lCgf1B1WM7487qeQoFC/38s1JBo8PnU+bX+KXOcDpXYzXcEIZWnjb6Pby9kHDWHe+pb4hKtw/NgOf5hQJMZ+lY68B2BCbDcegH1FuiA98XsnHx6LgXCUmWOq+bSxvU/POH8o8/mUQK52RPuEDtgVV1zBgw8+SHl5OU888QRXXXUVIKw9XnvtNVwuFz/5yU/40Y9+pGt9njQtJQMGTTJqIBzNetC6AhHN4Ecu7aB1YpVI+HrhtObHlFpNdBH2vhaY2nnKlyF3LCY89xKp/2wyFGpwWMz4wtrb4wtHe93JKJoDej+A7u4IUGIzUVtiy7uNkxoa3N3UldoKNvA3tnp7PXnpT6S7J9gsxqzHxC+TTHDmIfsphy+L1lClhk1Ppz8zYElgX++CTEeFw5p8oMvR4PYyqqaEw0dV8UmDdjNWX7F4o5ujx9WKACnPx05uuO6wmL4SXdSeeOdqZ44ei0oIhGO4rGbG1ZeybldXr9fjUxDnTqDUZqY7pwyYskerHP2ihH/YYYdx2GGHZbw+atQorrnmmpzW5ZHJUABYTAZFT78E/OFoVqub7mBEMwBQUkxXQmdAu2ylhd5YHShByV4ngYR6dyFngVroDiofn3wFn00dfgaX9/DIrGYj4VgvAjCrMWtgk2sJMhaTkt1zDmvfMmALNghXBWeeuin1oMHtY+LgsoJl3ET37r5bOk/AH071iRtR5WRrq48Jg9T5fHLJBEeejZS9IW2toQqnukSDUhkvgX29CzIdlS4LHn+I4aQK6LbHs3yzJ9Yxb30zR40rHG9q/oZm5s4YQYPbm/f70isLtG0W41fCjLvdF8ZgIKegRg3+eOLhuIm1zN/QzOQhmXxyvevRKkG2dOlvStknMmD5RnualU3CMkMNQR0lyM5AmGAkpqpsHYhEsel4OHQr6IDphdlkJJqH9vRAONNINAGree/6QTZ3BalV0ABz2UyaJWC9aHT7GFXjzL5gHGrJTKfVTEBHAJbLA6ozEKYs3i4nSpC939/5G5qZNaEOu7X/9IAa3V4mDS4tSAnS4wtR7rAIiYZ9XKA2XeZlZE1279DUEqQpryVIb1C9ZAK5axcl0N8i17kgKpvMJKBkyB0IR7GahYfm4aOqWNbQd5kfNcRiEqt3djB1v3Kh85fn+9IrE/W07eMiuXrh8YUYVGbPWwnSbjFxzLhaFn7Z0uv1iBKkWgCWWwnSuy8o4ecb6Wrz2SwzAhF9JUiXBg8pEE7lVRkNBkXV+r6UIPMFOUclHXu7rKBmQ+TSELfNBQ2totygB5IkqXp76eFo+cK5ccBE5lZMHPpSggxFYmxr8zOm1oUzD1wyvWho9TJpUFlBSh8Nbi+jal39ai3WWwTT7KtG6QnAQpGClSC9WZpF1CgToUgMs5r1UftWSvDtswGYX4FmUeGw4EkTnN3e5mN4lZiQ2S0mBpfbC+Zysbqpg8lDyjAaDdgtprxnD+WinnuTw5tPeHxhhlU6cwpq1JCo/FSX2IjFpIxrQS+Urq0ESu2WrA19cugx4x5wAVh62jzbbCAak7I+KLsCEerL7apZiXReldqsMhTd+yKoWhfQ3ibWqtkQOfNUfm1o8TJSZwZMzTMT9GUp/KFITg9SYXxsia9f3dA9Gz5pbOOwkUJjSzzM89M9mg3b23yMqy/JmhnsDRrcXkZVuwaEybA/lJph1mNdlVGCzMIvzAXeLCT8BNL5l6oE/I4d8MBhHP/5Dfus36BSlqJSwXKpwe1lZHVPF9qsCXXM35Afz910CLeTOiBRZs7vOCuMuPfu5D7faPeFGFrlyFsGLHGPHTO+91kwX9YMmP5t9WWhB8AADMDSYc2S1TEY1K0FEugKhBlUZlflIfnTeFWuPJHGldAbFXE5tEqQez8DpmxDVGIz052HDFhjq5dRNZltv0rHVBhxK1/+TqspewkyRxJ+QgUf9GXY1DB/fTOzJoqBvr9KkAl/zVKbpSAZsEa3cC8YCN1dwUgsRbpkpA7zdnnnbz4kSOTwBaNZeacuqzmDB+vxqxjDb/0QIgFq2pdT3tZ3ZfFCQCkAK1cwHW9wexld2zMeJHhghcCijW6OGSfs5mwFuI6zdbsORHh8YYZXOenKS/NZT/Jj9oQ6FmzoXQDmD0XyVoJMmKdrYUAFYJJERtbCZu57ujeh36VWBgumBTWFCsBseeBoaZGZbXuZWNuiYEMEgnOVDx2wPZ0B6tPWr9b5qdUtqoejZTIYchpkPf4e7mJfSpAfbWll5ujq5Hr6owTZEufuCW5L/gP4hlbB3RsIAVh6Br7MbslKIhZdkOKezHcnslyeQA1K2aF2b4hypQxY0xfJPyfseDEv25hv+MKRjHtXaR8bW1MzYPtVOOjwh/OSbZfD3R3EbDQkj2chvF6zdbsORHh8obyXIAGmDClj3a5ORZpQNmQrQeYjWyfHgArAopKUMWvLlgEDIVWhRe4NhKNUOa2qQVU68dZlzdTsUiKG5gotn0m90Aos9ra4YnOXcgmyxGbuMwk/Eo1hNBgyurrsZuWOoUAolpQWSYfDasKfJdAQ5TL9x7Ld2yN62dsuyK2tXurL7Mnz67SY+yVgEa38LmECXICAb1ubj2FVTnGu9vUATGEYyXbfirJlYfg7cnK2GiqclozgRDUDJgvAxrW8A/7CSjf0BsolyEwOWIO7xxc2gSPG1LBkU37J+As3tDArXn6Ewng1div4Cva1WrK30e4LM7zamROvSg3+cDTJfTYaDRywXzkrdnhyXo9PQwcs1+eUnlt9QIXU0ZiULOMkoIe4K4Q+tTsUXTazKglffnJ7lk09Ed25SFDsWQuL/wTR1AHj5vZ2HK+UQWJwMRjgwEtg/In61ks8AFMJLPQEq4VEc1eAWgUXA2ceRGh3evwMrcy0MrJbhKRERRo1LBCJZlgQJbcnC7dKkiTMJgPRHCQuPP5wkhDc2xLk/PXNzJ5Qm/zfrkMuIx9IBGCF0B+SJKlHoLaXum17G4lOyP33K1d836fR2t5XyMnZaqhwWpOaSwl4ZJzEJGJR2CXMkbuqDqC0bRUs/xfMvD6v29xXKIllihJkapDZ6Y9Q7kjdx9kTanl1RRMnTE71HO4L5m9o5sbjxib/dxSAGpAuaWCJZ1L3lqRQPuDxJ0j4+SlByqtUx02sY8H6Zg4enpuVVjrHUw6T0UBMZ9CrNzgeWBmwmJTsJEtAi9eUyEqV2i1ZtcC0xEDTeVVKml2duXRAvvczWPUCrH0l5eeQ7oU4N73W89qal+GV6yCiv6MjEO4pd6Rjb3eZyXlQcrisfbdh2qIw2wX1hgktvTR7lgApGFHPnqnB4wtR6RL73tsS5Py0mbazD2T+XNDQKo6txWQgEs3vrNvdHaKmRNzTdotpnyV+J6A0qx1V46JRgwcmF2LNN+QCnWqoUAhOFG2I3F9C2AcVw9l94A3itU8fV0777UUoiWVWOKx4/GHZMhHFY37wiEo+39qet+xRJBpjU3M3E+p7dODsFmPer2NvmqhnIbJs/Y1INEaly5KfEmRad/KR42r4YGPuZuX+cH7u1aBOvc2BlQGTpIzOHS3BwEQ5rizevTBYYYKaEMh0amhRBcIxakt7HtZOBdJ4VyBCiU2HBpi/HTbPA4MRzn4QTD2D4POfbufQkZWMTkgpLPg1uDfA+tdg/3Ozrzu+rWon3mra+23+SiUYl82UNUDOhsZ4J1067Cqihf6Qui2J02rWnMEmHqi5ZIPafWHK45OH3uiA+UNRWr1BhlX1pPIc/cSZanR7ufSwERgMhqwNLTmvW9Y4YTfnnzuTbyg9t0dWu2hwd6t+RikAy5clmB6tIaXynMcXZkq6WGWi/DjkIHwjT6DDXEN560ZoXAyjju7ztuYLSmKZVrMxRcex0e1L4X8lYDEZGVNXwoY9XUwc1DuxTjk+3+bh4BGVKeeyEF6N3lAqCd9hjU9WHPu+e4QWbGYT4TxwItMn1GV2Cw6LSTR+len3Z9bqgswFQoLiqxaAxVAsQaplwBKEOq3uhe54atdlNauq3PrTynpK5tHdwYi+DNi61yEWhlHHwoEXpbzVuGM9g4dUM3p8vMzkb4P//RA+fUJ3AJZdhmLvPOBCkZiq7EM+MjlbW32csn+mCatDxbszEIllKUGqb48vnhHNhR0jb/vPVqKIxSSufPKTlG3whiIcN7EuZblcUuJ9QZMnwJAKfYNYhz/Md576LIMA+/0TxjNzTHXG8nKpALs1e/v+o4u2cN4hQ1VNpAuJcDSm2NU0otqpKW/gS8ugW0xGwlEJqzkfAVh2eYIKp5UNu1PtWTy+UEY1gZ2fi99DDsJqtbK04nROcj8psmA6ArDXVzYxtq4kL4GNFrTEMhMQgb2yJM2x42tZ9KU7L9u5eGMLx46vTXmtt93Jf3z3S743Z1zSSk2O9G5XLU/igYBoTErup4G+3wdK3f/HjK9lyWY33zhoqO71aJUgQSQxtHjWCfhC2W2IYMAFYFLGwKulbSX4UEZNAbWuuHq9y2ZWFVQMpqUlXVYTbWkGt12BMGV6ArA1/xG/9z8n4y1XOpn3gAvgnbugcRG0fAm147OuPqCRQt2bMhRCCV55tpaPQMLjC1Hlynwoq/GttLhy2ThafpXyhhY6/OEkHyWbHU13KII/HOUfV6Xad8nlDxIodPwVi0nEpJ526myDpbs7SJXLyu/PPzD52tpdnTz1UaNiANbo9nLoqCpAX+ZgySY3R46t2SsBWGI8SUdtqY3WbnWLkmgsdfKROP9WhXXlCq9G23wCFY5MiQZFOoAsA2YzG1lcdiontf4T1r0G3c1QkjoBSMeSTa2YDIbCB2AqY1xCINtkNCgS8BMYXePitRVNedmWXR0BTt5/cMprvSkPtnlD/HXeRi6bMULRLcQXjqQEBgO9BNnhD6v6kPYG6Y1yAIPL7TlZB4G2FRH0dEJmC8C8oYiurtUBxwFL79zRkm4IhEWWQ0tALaFer+XFmJ7edNkyMzZdemyIvG7YshCMZph0ZsbbGY0A9jKYer74+9PHtded2NZITPEhAXvXiijdwaAw6888/jazUZFQr8UBy5ah8odiOK2mrN21ckRlmjDZbKe6AhEqHBYcVlPKj5pvXyGxqzPA4PKe7Fe2EqQ/FKXUbk7Z7oOGVbBuV5diW3iDrHRs10Hy94WieW8F1wulQR7iXYZ+/TwWp9WU1exdL3w6SPiVLgUZinQSfjQMu1eJvwcfiNVsZA/VMP4UkbH/4ums29LSFegXTqJamajcYaEjfh4a00RY5agttdGc44NZDe0KgWxvrIg++LIFA6JRSQ0pZc4+SNnsC5A3gRgN9EoyQg6lCbVSs1w2qHEHE9CrBaaHmwkDLQCTMrsgtTr7EielROOgdQUilMUzYGpioOm8Kpc188TqsiFa9xpIURg9C5xVGW8rktGnXyV+r3gWQj7t9SNm22rib3szA6Y7Q9jr9SsHeKolSI1MYdYSZCiCw2IuWFODuJb0zQ4L7Uqi9CDTIjArlcCNRgNTh5azfLsnY/kd7T3dqw5rdpPhQDi7tVihoCZynKu8iz2Pch7BSFQxMyqHkk1PhoVR8zqIBqFqNDgqezx2E+PPZ09Alq7f5q5gv5TF/KGI4nmokImxNraqZ8DqSu15C8A8ad7E0LsuyHnrmzlmfK3qdqXfcnbzvu8aoYV2X48Mistm7rMhtz8cxZ7WfObqhdyPP62bMh16tcD0cDNhoAVgOcpQJLIcWgctmQGzqWfA0h8qQjYhvQtSRwYsUX6ckll+TKw3g4w++EDY7xAIdIiuyD5gb1oR6ckQ9qUzyRdWLsUkZCjSEQirdzLazdqZGF+801SvcGg4GsOcQ/Yql2xhLlm43iC9lJNNLFgtO3HcxDoWpPGkJElKyQzadWRo924GTD1rmgvyLaCbjcyvZFSd8blk+fFgQOaxO+Y4qBgOnm3w2PHwxGk9P/+5FkI9tI3mzmBBdOLSoVaClOudeTUcAhx5zB4pydnYzSZNf+J0RGMSX+7p4phxtbR06gsMC2H43Z/o8PdkwErtZjr7OKkKR2NY0xIPolkut7FCK4EBJBv6skGPPh8MuACMnIRYA+EYdqs2Cb8rrt+lZQidni0psZnxKXRBaj40u5tFN5HRAhNPU1zEpbBeoGcWqrMMqYa9nQEr1ZgR6Hn4ZoPSg0iNbxUIR7GpPEyNRoMmtyoQ1yHSUzKDOP8rB85SLqbuhVDdlqPRnWrvJFrs1c+TmpXHkeNqWJTWFr6nM0i9TJhXT0ArArC9lQFT93o1GpQDYaVJhdOaPwFdPXMWq9lIRJa9UpzoyPhfIPPYNRrh8O+I93Z+BlsX9/ysfB7evRsQXEF3d7AfS5CZ94dQww/RFQhTouP+KZSQaa6ODl9sa2fasArqy+y0KHAJYwoi3+I7Bi4HTC5MnQ+FeUnKHP9LbKa8OKzIUWo30x3UUYLUEHSVY0AFYDFJymw/Nql39iW6F7Wi1kTmymnV0AFL41U5rZmZqqwPzbWvghSDsXPAUaG4iJJnGyAyZvZy2PlpUiixN7CajYSie2fW1JklQHX1YraiBw41GYosnSxaXKeEubKaxEU61IyP1R4AuWTA+mLsrQcN6QFYltKH2nEts1twWk3s6ezhuGxxdzMqIbkC2HQcz0A4mhfl7N4gXWtIDrVZvJIeUDaduUIjXbQSyAjArCbZZO3w6+CaefDN13t+zn9STCY/eQS2LEiW/vqnBKlcCq6I2xE1un2KkjRylNrNffYgVLt/c50Uzd/QzKwJddSV2WjuzOSA+RQyfg5L3y349ibaZWNirh6LeuG05sdjWA6thj45fOklfhUMqAAMMqNcm0Wdf5FoFy3V8Gvrjj/sNEn4acJ/Jb0h4a/WLj8C6mVQq1Mo4oOQpOglbDmmxvOJbMfHZTMpZ/90QGsmazcb8SlywLRr/VpIDIh6Z6HtvjAVaR2gWl1Muho64nAWyB4ogd2dAQbJdHSykX+1rDxmTahlocwkt9HtS5EK0KO07wtFCxKo64FfQQA0ASUvwsRn0ieN+SpBRnIobSc6BEE8/MrlEhSRIOxZAxhg8FSxvFGm+WY0wtBDhBRF4mfKN+DYW8X7r96I293CsCqnpoNEvqDWqZbo9mzQ4H8lUFtqp1lnuU8NSvZAkDvHb/GmVo4aV0OdSnOAL5j5MNc7+dtX0eEPy0qQfc+AKVXhRbNcfq/HEpu+EqRe8/QBF4ClQ0tcVJBmjfHZqTYHzGwyElHh0qTPfJ25kvA7m2DbR2CywYRTVPdFkPtVbqrpV4rfK1+AQKfiIrGYpCkTYDXn1wg4F3Rnyeo41bJ/OuALRXFaFNYd7NIsQWZrJVZDIBSlxBShxBTTNdP1KKiOaxF1c8uAFY6Mq+SvmY0fJzeeTsdxE+uYt76HB5ZOlM4W0MZiEoHI3iXhq3HA5ARwOdI1wKBvZuxy6C1zgMhAJo5be3pGds8a0elYMx5spSprUMBR3xecsY7tlH1wN8OrnP1WglTigFW6BAesoUVdAywBEeyodxzqgcen7Kdpy2Gc3d0RoMRmosRmVu3O7FYQ9bQNAON6LYguXHHsyux9r36oerTmcD3qKUnrzdbpNU8fUAGYktm1zZKlCzKeAdPigGXLNsQkKUUcz2o2Zqj3agqxrnkFkGDcCUJaQgVK5P4kaifAiKMg7IVPH1NcJBiJaZKEbWZt/k4hkY2XUdKH2YpiwLLq33DfUIbvfE0jAFM/VvKMQTpCfi9z5p3BtZuuI6Bj4Mho+SeRBdGaFOjLgPXW2FsPlARYBflXiwPWYzydjjG1JTS2epP3a0Nah2U27kwwEqPSad17JPyIOgdMyfAalDXj8lWC9OnUGoJUr8QOX5hKuWZeWvlRN0xm+MZDYLIxeMu/OcH8Rf+UIFW6UcsdwvNSiLCWKHyyB3Wltpw1otLh8YWT9mJyGAzaHFI5FmxoZnbcXsxpNSuOVb5QZkOByBYPYA6YrCrQ1xKkWuBkMRlz8uvVYzGnN1unlh1Nx4AKwJSaE7Q4YAnSrFY7qlweoS8t/WqDAqApviqHErk/BUd9X/yef58QZlXYBq2sTi4zs3wjIfehhlxnK6nrVsg+xnWLhm14XDHQUZMUSEArGBjSshCndwdDfOswta7Lun0dCjNlLTHWnDJgBSxBpnO09HyflvG0wWDg0JFVfLq1DYAmj58hFT0G6tmslXyhCHWltr0XgGmoZFcqGF5Dj2acHFrBdy7QqzUktq8nQydssWT3YlOPAn7OqJ0Ac34KwDk7fovR35b7OnKE2r1bGQ8yt7Z6GVGdJQNW1vcALKOU2wvMW9/M7DSHi/SAQtjapJcgC0s9KDTkY6JeXpUaBM+y76GMWmZVDt0ZMB0CyTDgArDMCMmeNQNm1PSwk2fAJKlvnTEGgwHevgP+dmjqz45PwOKE8Sdrft5hySLQOO54mHap0Ot55TsQTV1WtazWsAiePJ3Sls/2GnGzK6jdpODSMEPPhgwJkGA3bF0CgKOzgeGdn2d8RrWjrXk9PHk6B8VWqwbt493vJf8u3zE/6/YpZcAcGn6TuWimOa0m/HkS9UyH6IBMfZBl6/zMZjx93MQ65q9vJhqTMBhS7+ls2TVfKEpdmX3vlSAj6lnTcoeFdm/mdiU04+TIWwkyqL8EWeGw0hHPgHn8adpVTcvF794EYAAzrmer60CcITfnuf/eu3XkgJgkKYoSVzrFPmp1qyaQDy0wjz+s2FwD+ibzwUiU7e1+RsvK8ErNAd5QZqBd6O7nQqPD3+OMopdXpYagjvOtB5pJlDjK9OqAKWQtlTCwAjCFq9pqMqlmdbS6lhKQZxvUNMV0e1V5W+Gjv4H7y9QfEF6OVm1iqC5z3pPvg7KhoiV8yf0pbykGYJvnwTPnQeMiylf/Yy/KUGQh4afbMOW07rTgrmEhRHuyEUd1/DfjM341GYq3boPGRVzkeVR5hhnsZlzHh8l/a5oWZt2+dgUOmBYROxcSfiFLkI2tmYbGQoYiSwCmcc/NGF3NR1taafL4GVzuSHkvWwkyEI5S5bTsNQFKLd6gyIApBGDhTE5cvkqQQkxV34NHzlFLsSEK+YQIq8EEgw7o3YYYTTxR8yMAZvg/gEhmJrA/UOawsLXNm2mxpIC6UuWOw1zgUZhY5YJPG9s5fFRVyrhfV5bZHKAk6mm37L2GqnxATuvpawky23Neb1JFTUJHDi1XHTm8Okn4A8oLUikDZtPQJfKHUiNjSZIyghy5l1oiC5N+MpWyZ2ajyLxZzcYe8vuOT8Sb+02Hs2UzQYNJKEznA/ZyOOtv8NTZsODXMP6k5MDpT/eq2/gePHeJyJgB1l2fEizbW16QWUj4fciAZQQsX74tfh9yBdLn/2S6f0mGl51iGWPrh7BFZLRGBdfT2LQcqo9IXebLt7BKQYLVk7G0fUlV+3Lwt4OjUnX7OvyZMhTZSpB6Zk/Z1tNXpEtQQLz0oVUmzOKl5rCaqC2xsWijO2Pd2ZwFRIlg7w1ZWpkVQQDPDDwCCkT5fJjPQ24ZMHmXZrs3xEHDK8Qbe1YLd476/UW3tQwJkV89FlhrgtXEqsdjbf0Sdq+EodNz2pd8wGQ00OmPMHKc9kQXdNgRde6Cz/8pOLdyVI6EQ64Eg4F2b5iJg9WbFpSeN3LMW9/MrAmpRt6J5oCxdT2lfyVRz0Le9/0B+WHpaxek1qTPahK0m3QpGCXoGV9KdMqXpJunq6HgGbAdO3Zw/vnnJ39+/etfJ9978MEHOfXUU7n22mvZsWNH1nUpBWCJA6wEeWTs0HhwJG4Sl8LAGI1Jipk3OWk8GcRtXybeHHW04EYkfmrGilbufGHMbJh+tehcevm65Iwz4X0JwIa34LmLRfA1/SqwlmLq2IYz2KKx4sIh3ZA4HSXpPpg5IIUzJUmw8V3x9yFXEhoxGwsR+OKplM8oEqrn3yt+O2vENq36Z+aXxeVEggdcQmvVQRilqMgyakAuOpiAVveimqq/EpwF7IJs7gpmGANn61TMVoIEmD2xjieWNGRk17JlgLMZ5RYaWhzLcoey2rxPQboiG9dNL/RqDUGiSSCeAfPLOIlJAv60jM/k0jXtC0UxDj9c/JMYB/cCKpyWlJKeGuS+kRlob4THToQF98KSP6f+vP795FiSUcqVwaLxXEpg6ZZWZoxONahXag7wKvh9DuQSZCgSwyx7HpblIQOmJqqtJbCejmzZexDnVY/ziC8cyUroh34IwDZs2IDBYOCXv/wlv/zlL5k7dy4Ar7zyCs899xx//etfOeyww7jkkkuyrsukMD5bNTr75FkOPVG2khioUEzPPJBy0ngyA7P9Y/HmsMOz7YoqdFvLnPBzMRvbswre/SlsW4p15zLGBlbD50/B83NFGe6wb8Npf0zOSEcH1vR62wqJvhCTU0qQe1ZDVxOUDILBBxI44FLx+mdPQqznRoxE0wLChg+gcZHIMF78HACVW14VFlAJBDph07vEMMDks3APniVeTwR8atsXzHQByKYFpascTeGEWEORGBaTIWM7spUJ/eGIsiSIDLMn1LGxuTs1AxaLQtsWTQHchKZWoe2X1BBIzzDLUOlUzoClBI2tmyEWzVvZWK/WEKTaEaWUzjQ6ILUkfuSQJEl0/Q0rfACmpAovR4XTqmrCLYfq/dW2BZ48HTq2CYmN43/W83PYt8Uyb/0E2remlnITkCRo3YzDhOZEZWurl0Fl9ozgvFYhAPPJSfi+NvC1YTMPXBkKjz+1dNvXDJhWZtqlIbCejmzZ+wS0xqjkMhK6MscFz+dv27aN/fffn9raWkpKSrBaxYzB7XYzY8YMxowZQ1lZGX/605+yrkuxBGk2ElTLgMmkBhK123qZCoRIEff8rySEqsb7kJPGuwIRKmzA5jjZe+hhWfdFDQ6rCV9YR/rSVgJnPwhPnArLHoJlD3EAcABAojFvxg1w0q9EvnfY4bBlPuNDa3u9bX1BtjJ8icpMRZIknl62jctmjFD9bHdQ1mG58R3xe9zxYDAQHn40u431DPJsE5mqcScob1wi+zXzJhh2KNvLDmFY52dCd+2wb4n3NrwB0RBrLQcwoXooHcNmw+rfiQAsFlPNcirdjKKE0HfyfKFKEdvavAyryuwks1uMNHdpC7Fmy4ANq3IycVApo2vjD0pJgpeuhjUvc1Dpz4GjVddtt5hE8KrnHsmCe99YhzvtYXfilHpO3n+w4vJaA71aRsUfilJXZoMNb8K/LoKpF+E87v68ZC19wfi6daDCaUly1FL0qxK0icGZAZiWxI8c3lBUSMwkA7CPE94wurYtF2Tr9K5xWXuuqyywmY2p43vrZhF8dTWJfbn036myQZIEXbtg3X/h1RvoiN2ZGoDFovDad+GLpzmj8tsEw4eAQ5kj9sGXLRnlRxDNAet3d6W81p0g4YcD8OCRYDThuHJJQayInv9kGxceOjzv65UjXT8tWzbv44Y2KpwWxtcrl3u1MldOmylDs1MNerL3eqH30i94ALZr1y6eeeYZPvjgA1auXMnjjz/O6aefzgUXXMDcuXO57LLLWL9+Pb///e8VP//www/z8MMPA+DtaMftdmcsEwyFFF/v9AbwdXXglvxYpAg79ripMPYQL32hKBaDlPysIRpiV0sbblfPhb2rI4gxFslYvykWpqm5lSpTkO17uhga+BLCPiIVo/D4JfBnbo8eWA0xduxqpqZER3uzazz2Y+7C9uVrAHj8EULRGHWlNkKjT8Q/7WpobQXAUjaBcmBCeJ3isSokItEYUiyq+b0hn5fWTm/GMh5fmL++t4FTxqoPqs3tXUTrrLjdbsrXvoEF6Bx0BCG3m47OLhZaTuSq4FMEP3yIrkrxoIlEes6pZdtiyrd9RMxWQfu485DcbpbXnMGwzs+ILHsEz6izwWCg7PPnsAILTDMZ1N5Gu7medks9lb49eNbNJ1J/oPL+RzKvn0jQh7s7nPG6JElEI9rHSo6wv5u2ju68n9N3V+xhSq01Y71hv5f2jszzlIA/GKKjvTVrBu/RCydgCnXjdndj2/AqpXGj+TmBd3C7L1X8TEubBykcxWqMsbVpD/Wl+oIPJQTCMRau383PTx2TfG1rW4D/Ld/O9EGpD82ODpEF9XR7CXg7cbuVB/RgKPN8uj2dVFqcBFc8ig1g5XMYambQ4R3b53PW4umkyurStR7JH6bZI66T7kCQ7o52/K0bqGzdRMxWQZtlCKSvJxphd7MbQ1D7OG9t81NuBTcVWA2llHXtoq1hJbGy/fqye4po9YYxS+r3x09PGEaJIYDbnZ1gX24z8OW23Qwpt2Fq30LZy5di8jUTHnIonac8jNQdgu7U7zEccSeVjYsxNi7iMMe/ifpG4w52QyxKyfu3Yt8gruNDfEtoanZjDAkdvcQ1lMCW3e0cPLQ0Yz8sUR/bWzpSXm/r6Cbit9OxajHlXU3ixRXP0+WbmNf7PhiJ8ZP/rGL6ICvljsKFBlt3dWIzpI6JSmNkAq9/vo1R1Q6qTJkBK0Bzq4dYOKj4eVMsQlNzKzXm7I0hzW0eYqHsY68UjbJ7T7Omabd8f2pqalSXK3gAdvvtt3PrrbdiMplYuXIlZ5xxBqeffjoffvghnZ2dXHjhhQwePJi///3vnHJKpkr8tddey7XXXgvAtGnTFHfGbDYrvh4zbGJIfS3lDgu1lW6MNlfKcrs7AlSVOJKv1Va0Y0pbxhPrprzEQQ3t8OKVcMSNcOBFVJe3YHGUUFNTg6k1xv5sEtsyYqbmAc+GipJt2ErKqdHBYwDguB+IH+CDz3bQ4Q9z1VGjsAApa3AdB68ZGBfdjKW8BCx2pbUVBO3eUMpxVoLX4CBqcGcss3VrOx2BqOZnw4YdDB1UTY0zArs/B6OZsgPPSM5e5zlP5Mrwc9ga52GzBKB8aM81I0nwyt8AMB59M9VDRgHgGX06gR1/wd66gRr/ZsHl274YDEaWOo7mxpoa6n0mviw/ksPd/6Gi+WOYMidj2wLhKC67VfZd10M0RN3EX+IOdmXslzcYodRp030NDfKZYLu/T9ecEj7esYV7ztyfmjQ9pToPrG+NqH6f2WymtlZ5oFREZxMsuif574zwJ9hK7RhsmUKaJls3tS4jNe0RLM4yampyUG1Pw4bdXUzer5LDJ/bM9oe0+Zi3OfOcQHwQNW5lcG1NxjFJQGkcMljcDCkzY9v2QfK1QUt/gcv51z6fM8nUzOCaSuX1eN3w7AXCMuiIm6iMSfijm6mpqenZzpUPAWCcchY19ZlZvxLnNlxl5dRkETXd1NnKsJpyamrr+NQykemhT6jyboTRyhOSvsBv9InxWOXY6Tqir90Ma1/hgVAU6wtGYecU8grKxsijsVzyPNWqHes1cOZf4Pm5XOH/J3bTdwQV5JXvwIaXhdxQ2M/o4Hq22Kwp2yn/WzLtYXBtFTU1VSlrNztDdCxqSlk2atjBkLoayr9YmnytetO/iXJXXu/73R0BYhKsbo1y1rRBeVtvOmJ7IgyuSh3T1Z7hAN2RHRit6ufctjtMVZmk+H51uRuzvUTXcTLZvNQ6DFmXrSp1YC2poMqlnCSJxSQsZouu7yw4B+zLL7+ks1NY50yaNInu7m6i0SiPPPIIt99+O5deeim//e1vaWxsZNOmTXn9br9CCVKOdPkCp4IVUCBu6M27dwu+1cLfgCSl8MW6AhFG+FaLDwzrffkREqW43pWmNNtxHRVQN0kQ0vtg6N0b6BEWVSNLNri9BCMxTb5DkoO3eZ4wPB8+M6V04LVUE5t4unjv8zRi/cZ3RRnGWQOHfiv5ss1uZ+N+Z4t/Pn0c1v9PND2MPBqPUXQ82s0mVjvjZZeNbytuW0q6vXUTrHgWVv+b6sA2xTKUEKzVPy9yFMDYORCO0tIdZLhCoGG3GPNH+pck+O93Bc9u3Imw33TsBIluUD6WiRJkPsx7G9zdGVwhocGkvt5s7glmoyHDIcMfijB49/vi4T7iSBg9C4OvlWs7/pK9Lp8FSuTsJFb8S0jVzL8PAp2YjAZiktTTki9JMn/abyiuwmZWl/iRQ96sscW+v3gxwYfNM/SUuDXh2Q6fPQH+dpzRTsxBj+hijoaETuMlL2SVC2LSGTD1QuwE4ZXr4OVrYdWLYC2Buf+BQQdgJoJpp/ox6FYQVwXlUnZSByxBrzAYMWxfxtBwQ657rwmPP8SE+lIWyPxaCwGPL5ThIKDF62zuCmpaFfkVzMoT0PJ4zliPgmuFErKNP0rm6WooeAD2zjvvcNlll/HZZ59x++23c8wxx2AymZgyZQqPPvooK1as4LnnnsPtdlNfX5/X7w5HY1jjacJSW+ZBSxfwVAp+AuEoo8Jfwob/iRfatsCuFSmk8a5AmCGdK8X7fSDgQzwI7GUAJsyCNU5pIjjs5y6lTi2fzDhEB2rmfje6vVjNRkWfvQSSgXRigBp/Usr7TqsJ/9QrxD8fP4L08nf4vvdPooP0jVvE60fdLHh1cTgsJlbUfQMwCCuphAm6zM3AbjGy2joVzHZBZu7u8TlMoN0XojzBE/myJ7CoaV2myN3KxYYouW95FmL9aHMrM9O6sxLIRsLPCZ//Eza9C/YKOOMvyWMrJQKDNAhCu1nT21UvGtw+RqaJzJbYzHRrrNcfjmLXGFjLndaMh6cvFKVm6xvin/3PgTP/BrYyZoaXCn5hH6CphJ84hmEvrHw++XJXwth590po2ywmHiOVOXdaDU5yNHcGqIsHYNtcU8SLBRpj9IhlaiJe6mbi6fzn+EU8P3sh/LgBbm2ES57PkOJQQ/Sk39BqrIYdH8Pql8BaCpe9DCNmwqhjALDvXKL6ebUOViUbI18oSmn3VvHscVTCwd8E4JTAm7q2VS/avWGOGFvNul2dqjZs+YAn3YmBRFOb8r3X0hXUDKIC4Zhioxzk2gUZ03VtldosBFoa4d27hPZnGnwKsiFqKHgAdsMNN3Daaafxu9/9DpfLxVNPiRbeu+66i2OOOYb77ruPJUuWsGDBAkpLe19SUEOCi6LUaZHuT6hE2AuEYxy/J+69aI1v35r/xDNg4sTGPDtxBXaBrQxqJ/Zpe105kAbTEYxkuYD6oUtJCXqERdUyKw2tXvYfUqbos5eANxilxGyATXGF+nEnprzvsJjoGnQY1E0GfxuGFf/i+OD7Ihvl2So6JqdfnfIZp9VEs3kQjD1eSHns/BSMZqSJZ/Ss12qiK2rteYApdEOmZMASASJQsWeZYuaqMwcNsMS+5ZuEP1/mT5cOLRmKnFwk2rfC27eLv0/9PZQNhslnA2De8h4EuzI+kuiC7GvXFCRU/lMzHWaTkYjGgycQ1vaKq3AodEIGPJTsWAQGI0w6CyqGCTFlgDd/JEqwvYSSQCcAbQ099kIgJg+ShMloxN0VFNdjIkCbfJbwdFSAXuuylq5gshlgd8lkJIMJdq8SZb08Q6/FiyoStnBTL6Cipp4dQQc4qzR1/JTQZXDxWJWgfmArh8tf7ZngxseDkl0fqX6+OxhV7WC1WYwpk5zuYATXtvfFP2PmJJuCjgvNE64feUKHP0SV08oB+5WzYocnb+tNR7uCNZvWPd3cFdAMorS6k3N5ngr5n+xjb6ndTP2CW4QsyYJ7M97XzEynoeABmMFg4LrrruO5557jZz/7GSUlIstgNpu58cYbk1IUEyZMKOh2KKUN00tjLmumF6N192eM9XwIFhec/YB4cc3LIrUZz1SVtcZbuYce2me9r1wi9nRoKXUDmV1K/QRFr8Y0qJG2t7f5mDq0QjMDJiFh3PUF+FqhYgTUjE95X9j+xER54ewH6T7lL/xf5S1w1t/Fz5VvZMx8HdZ4l+L0q3peHD2LoLUiKepnT7SCJwI+WYCVgMcXEqazwS4h9BpHya6PFLsg9Ryr9O1MBnLB7j6fW0mS+KSxnekjqxTf18qAhdKlPdQQi8GrN0CoGyadCQecJ14v349N9gMwRAJCxy4NeS1BtnoZqZdnGUckJqQ51FCpYMg92bMQQywssiIlcW7ctEtZZjlUlF7/e1Ovz5cIRhSulbWviN+TzgRXLTSvge0fU+GwsLXVR4XDrMuf1qYzA9bSFaSuVHBKzfZSAlWThLjrzkwLsL5Cj1aTKtq2iEy1tQTGnSjsiDo1xFg10O4Ls7XqCLh2AVz/EQw9pOfNETOJYaS0dZVqgOQLqk+0aktSpSjC0RjmzfHJ5fiToH4KDJuBU/LD6n/3avuV0O4LU+GyctzEOhasz8zm5wseX6Z+WpmKwnwoEsMfjmpWhVL0L9OQy/M0EMp0rVDCxOBKKnbHx/IVz2ecY69OI27IMQBramri3HPP5YADDkj+HH/88bmsomDINvtWMvxMz8wo6YCNXPVn8ceM78DE00W2xLONwd1rknyx2vblYpk+lh+hb5Y8/pC6IB0AVaPpMJSBt1mIDfYTcrHWkUOSJMJRidpSm2YGDJDJT5yY0QPsTPCkKobBtEvonHABn1ScAgddKn6qx2SsLsmtGnciJLq5pnwj5QGQDEYS0hab50M0dTs9fjGosWWB4JANPQxKh2Dyt1Ll3ZzxvbkeK4fFJIK7RX+A+w+Ax06ApQ/q/nw6Nrd0M6LKiVVlRqklaBxQMJ5WxMrnheaaswZO/1PK+VpZPlv8sSazDJnQ1MpHBqw7izm8GrS6O+VaWwkc3L1A/CHnWRkM/K3kJlF63fSeYuCuB0oK6UBPduvAi+Cgy8Tfnz5GpdPCFreXidJm8GwTY9nwmarrFxmw7A+v5q5gsgTpsJrorD1YvFGATLvg+/Syd2zNK+L3hFPA4kiqzvcG7b64u8WQg6A8rdvTXo67bDJGKQLblip+PhCJqhpI15WlqvTbJX/c29YgMmDQMzH85LG8TaYT+3TkuBoWbSpcp7ySfprapKqlO8iIKpcmz9Wf4GkrICcdsFA0w7c1A5LEkduFKgNGM4S6MoJgQQ0oQAD2wAMPMG3aNJYsWcLSpUtZunQp//1vps9ef8Nk1C4dgDjB6cFVdzDV9DhDDHTrR9Q1LyFkcsHMG8FogilnA7Bf01vJE7tf1yqxfB8J+BCP2HtZUgpEsswODQa+tE4WfxeIJKuEXLM6CbTEyb3ljszMQgLJwDtBgk8rP0Km6nw2MjUILp4/HBXlmW88BEd8Fw44P4VgmbTOqRolsm7BjoyHTnKgTvC/xp8onBKA0d2ZGQLNhoVoJPXH14Z58e95tP1KeP/n4G8Tyy17SGSZeoH561s4bqJy+RESXpDK6/aFM42nM/chDAvjbhgn/BxcqZ1C66uOQyJeTvZ7Ut5LBL99zYB1a3CnLCZjrw3r5X6LAHjd7B/8AsloFtkoGbrMNURm3iT+WfVir74vKkmZrfCtmwW/y1YmyueHfJMEj3GI1Uej28u0jrhzw5SzxZimAr0cMLmwpsNiorVymnijAGOML9QHN4REUB8PhqtcVlq9vfOt7FAoo8nRXH2o+KPxA9Vl1IL5ulI7LbLA8MDwCtEkMHQ6uOLczMln0WkoE+e6KT+Zxg5fmAqHlTK7BYfF1GevTDW0K3hoqk2qmjsDjKxxapLwgxqVHy1uWTp0kecbFjLY8xlBcxmcHB/H0oJgJfN0NeQUgNlsNg499FDKyspwuVy4XC6cTn2kxULCZs4UDEzPiOkpQWaIgcbru1+OukzwBACmiJR9zdY38AdDEPazX2AjksEI+8nS0L2E02pOljZzhZZQZAKb7YUlySpBb2ef0WBIIX82uL2MrnFR6bSqliCDkRj1hg7R2Wm2J4MbOUQ5UR6AZT9OTvlnRh0DJ/4CzLYkDwmEuGpSFTkR+K1/I2U9Hl+YCrulhx827qQkR2RiILMbVTVY/dcl8Ivq1J/fjoL5v6JU6obhR4gOrPLhgteWxR5JDfM3NHOsgkBkAnazSVU0UZeQ4Yp/iexr9ViYemHG22FnHV2DDhcPnA2pxzKZActCls+GRreXESpq6aX23q+70mmlQz5RWPcaJmIYRs/qGT/icFhM+MafJf7Z8CaE/b36zgwksl8TTwOzTUgkxHmMMzrfZqu7i7Et8Wtxinr5EfR3QQrNVRFMOK0mmivi8hM7Pu71REANvS5BujcJXloiMEVw/npLNm/3hTKI5HK01s4QfzQsynnd6Wr4h4biYrnjZM1FFjsLHPHM+yeP5/wdSpAHRrMm1BasG9Kr0IAgGmsUMmBdQUbVlGQh4atPqF22TFqR6nqyBfcywe7P95srssuOqowgOBeP1pwCsB/84AfcddddnHvuuVx88cVcfPHF3HDDDbmsoiBQMvENRno6IEGNhJ9a7kkh4TcsgoYPCJpL2Tr+ip4PDT0UyoZi9e6ixrMSmpZjJkKsZlKqanIv4bKZ6O4lCT+bSjRAo6OwbeJK6A5GKLFlL/ekZyAbW72MrHZS6VT3besMhJkVjdfjR88GiyNjmXSpBr+ODJia6bTqAyDxMPv8H8IuJA6PL8SgwEbo3g2lg4VxejxI3D+8MuMB1aVUGnNv7OnCNZh6foxmGHUMPym7F656E8bOiWc8ENIZOaIrEMYXilJfpq4RZ4zLGSjBF4ri1Lr+IiFY+Dvx97G3KZK/7RYTu4edKv5J64b0xdvE+1qCbGzNJOAnUNaHdWdkwJIZl8xAx2k14XMOEyWsUHevy5AZUPrOeLnqwOaXcTV/jiuwG8qGirFMA3oyYMFINIX357CaaTPXi2vd3y6kV/IILckBTaxJC0zjMBkNvQrC0tXc09FdfwhRgxl2LU+1M9OBOplReDgSZXr4U/FGmovHB2Wniz9WvySOdR8hLw0eN7GO+RsKxwNLz/6V2i2KWa7mriDDqhya0jdazz2Xzaz7eZpV4mTz+7B9GWFbJUtqzhVamgfFRaNlQbDocI2vJ6r93TkFYH/84x+ZOnUqt9xyCzfffDM333wz11xzTS6rKAiUMmDBtCxHiQK/K10eoSQRLadEupdicso6ZIzGZBlyquf9ZCYpaUTbR+QSsacjqKNFu8k5UZREmtcodpoVAp06dMAg0wxdSAW4KHdaaFcpFXQFIhwRiKf5VQjFTmsqcVzPcVLzalR9AAw9RMysQ93w4V+SL7f7wtTuWiD+GXeC4DtVjoTy4SJztWdVymq6gwrHKtE6f+AlcHdbz89drfDN11hlmdqz7MGXi8DsyzehY6fmPqZjySY3R4/rvbBj1ofjF08Jj73aiarnymExsWPwCSLA3DI/JZiVlyCTfM5ty4SwZscO3dup1AGZgJJeIGThmG58F177HkO8a3s4YN3N0LiYMGbx0E/fz8RkIxEoJc5xOvwesX9pmZSk/6Iczeuhea3glo2e1fP6+JOgbCjlvm1cH4jzV6acnbVhyKph85aAuzuUYtjusJjwhWM9wV2eM+29LkGuVg6GRRkydyK+R6GMJofVUcaekslCe1DWfAMQzeJnKW8OCOxYSU2sNeltK0eHcziB4cdAxA/L/5XzPqRDHlSOqS2hsdWXoWvXVyhet0CJyn3XLGvwUIOmF6TNpLui5NN6LshiAveB36E1HA++D7lS/JYFwd2JDFiwG/55luZ35hSAhUIh5s6dy8yZMzn88MM5/PDDOeigTA+x/obVnMnbSOdDmRRm7ukZMLvZhC8cgT1rYNuH4Kjk47rzM7Ml8YfHId6FsE20GhvyFYD1QQdMXIjap9RodRCsmSIGhp2f9ep7coVeDpgzLUhucAvD5koFcnMCgdYdjPGvApNNkGsVkG5+rClYG4dat58vFFG/SWfFZRWWPQzdIn3f4QtTsm2+eF3OT0uUStMerJ1KOmCJh4dK0JIiYlhSJ4QilURns2De+mZmqchP6IFmCTIcEI0CALNuU+Ue2S1Guozlouwbi8D615PvJThPSTrB5vligPvsCXjpmhSzdS00uH2qhs1q/LJgJJbsfk1BJCTcDT57kvH/PYu5m74viNdrXwUpxueWg4UIchqSzQzxyRxfvq0s27Do92L/XvteCs9EbE/avZ4I4iadDmZZdsZoSmZGDzA2iteylB9BeWKbDrkGGMgmOwWSvAn0RgeseR20rMsMTIlnm3rRCdnuC1OhkQGzW4w0lMabEdLucW8WKQ1Bwhf8q9iXqd62qd9hwjPlcvHPwt9A1+4c9yIV8u0yGAxMH1HJJ41tWT6VGwJhZakkVRJ+V+r1pbxOjRKkVX8XZDSm0cX95dvieemqJXjQ1T0TwOox4pqK+EVHJKLDtcwYgKfPha2LNb8zpwDsiCOO4Ic//CG33nor99xzD/fcc48uE+1Cw2Y2ZQwU/lD2h2xXIJxSizYa4yJ4g/aH7yyBM/9Kp+TMXM+Qg5EqRlAZa+8pHeSBgA990wHTU4K0mo1018W5av1UhtTb2VdiM6Vk/3Z6/OxX4aDCaaHDr5wBs2+MN4GMOwFsyjpyogTZc0z9oewcMKWAXXxWYwY+9BChph32wpL7ATAG2jA2fQpGS+rgn9AOa0wdnLsCkRRtOq2HRwJ2S1oJPtEh9fk/Mroy1SBJEit3dDBtWIWu5ZWgWYL8/J/QuRPq9xd6WCpIBr6JrsFVL2Z0ebmsZiZ2L4NnLxQDn9EsJkJL/65rOxtbvRkirAkodUuDxiC/4X+iq9hVi2RxMcX3CTx+ErzzUwAW2ZRFTpMcw4rhIlsU9sGXadIbXXvg40fF322boaGH0O1L1xqSJM2SJwddJvS5gGj5cNjvYMXtkkNpYpuO9AyFPVHul0ve5BE+nWrlKUhMYCadkRqYkiC89yID5g+L5hoV2C0mNjnjxziNiO8LRjNlCmJRWPc6dOykWtYcYN0i446mwWEx0jr0BNEZGfAIVwm1TG3Ll4IDlwXy0uBxE+vyzgMTPLPMwFVNhqK5M5jVcF5VnHf3KhzuVX137pAkmP8r8fdR36ektCyVJ5oYbz99HCSJsM/D4Uuuhu1LezroVZBTAFZVVcX111/P+PHjGTp0KEOHDmXQoMJ5RumF1ZTJAQtEskgyEBfwVGsXHbQ/TDpDWVvLYMCQeEBIMdoNFVA5qpdbn4r0MlwuCGq0NidgM5vorClcm7gSdGfArOZk8BmLScRigiirJX1Q1RDPkGjoGaWXILPqpWkgvQ3eZDSmpuln/UT8/uRR6NrNweHPMUgxGHFEaoAYz4BJWz9M4QlkHCv5w8OkPODb0wJMRh4tSO5duzIf6ipY09TJxEGlmIzaJtpa8IdVHo5hvyz79RPN0ldS6HXSGSJobfgA/u8YWPe6OI6AcdO73Nn1CyGQO/0quPBp8eH3fwEtG7JvZ0idJKs2E1cd5BNcu2N+jPS9VTznuFAQvSN+JLOd5Q5lmQdHossWegKmdAeAxX8SAabFmfpdKGgN7VkD7i/BWQ2jjs38wrLB+EfHH+JTvpGRTVGC0sQ2HXIbIpCV7gdPFVlp94aUMnJf4dM4d4qQpJ7MoILlUm0vpSg8KoFEAg6LSXScm6ywezWGgCf5nuiSS9uH9+6G5y+Fv0zD/OYPqQrvAV8b9j2fETGYFSdfdouJQCQGZ/0N7OWiE3z5M5kbs+51ePAIeHi26JJVgFKJfcboaj7anKn03hcku8LToMbrdHcHqSmxZTRoyZFONwIg0AmPn4zxsRMYEdnSt43+4ilBtC+ph+lXZY4RE04VJWL3BtjwBhesu4ky93LREHXlG6qrhRwDsBkzZnD55ZczadIkhg0bxhlnnMHFF1/cm13KK6wKJHylVKfVlKowHJOkrA8c1YFX9sDfaJ2ka0DTA6fNpNlymw1aOkUgjpWnOl423v5J3ruUlBCKZs84QUI0T+z77s4Ag8vFzFp1nzzbqGxbQdhkF5knFTjSglpRguydYK4vjYTvSFOtZsg0oRcXCSAt/hOHhuMdTGn2SJQPZZdpMIZgJ+zu6Yb0BqOUJB4w8qxGlgAzJWg3GFJnZTowf30zszXkJ+QwqQyG/pCKIOKnj4smhMEHKvKh5EhmwJxVQv6jpF4Mfs9fyl86vgsLfgPPXSI8TQ+7Fk77oyg9HzRXBGQvf1uT+NrhD1PmUH+Al9iUZ+KKdifujSJAtDjhwAsxllTzlOMyuHklnHQf3Wc9LoIxBaQ0hkw5GzAILllA+ObS2dRz7i54SnDi1r+eLDNlPMQT18mkM1WV7aMn/4a/S+dhOuYW1f2XQ2lcTUeLWgnSbBMNBpBXqkPOJcg9q6F1o2pgWpfWcagXHf5MOx057BYj3TGz0P1DwrKzZ7KbYSG19SP48G+AQWSsP32cRzu+hfSvizFIMXaUTlNs8EpOVsqGwCm/FS++eZvwu0xgzSvw4jeFBmEsDAt/q7i9vlBmVs5hNVFTYmV7my/L0dCPDgUNMFCf+ERiEhaTMVMiSgZFSsmGNwUfNxbmB91/FFSB3sCzDd6KU0tO/CVYHNjMJsJR2fhnsgjuLcDzcxnqW0eodDhc8brg+2ogp6fQzp07mTZtGnfeeSePPfYYhxxySNJaaG9CiaugVILU0z1lNKSaggbVeFWDprLTOASARuf+vdzyTIiTqz7ovbd2Tx/Xb6TLVi+6oIIdory1j8BlNSU10BrdmUrlGbO0+Mx2T/0sTQPdjC7IkLpwXzaklyAVuyUTWbBPn+CwZAdTpj7Zevs08YeMIyIhYUxMCnavEl1kzhoYeYzqNjmt5ky+2oEXC1mOzfOEAngWLNro5phx6vITctg0+HEZ5dloGBbfL/6efUfWiYrdbOyxOjrgPPjeCjjlt0ilQxgVbRTSMLEwr9jPQjr5Nz3rO+k+KB8mlM4Xq9MitAj4oD5GBJTEHpP+oOeKDEQCjkqYeT1dw45TLZelyJyUDRGCqNFgT8Zy0R/F/5PP5iPjQcTGnyI4cV+I8TblIR72w8q4lphGoF5SM4wXSubq7tbWxQHrSi0RpWRjE7SMhoW6vk8PcjbjToivqgSm6aKncizQ6ALMNnm3JVwy4pluy84eQVavvAQZ8gpDbyQ4+gdwwzKYeiFGJAzbxWe2VR2l+B3iXolfQ1MvFBO/UBfSqzcyb90uQQz/91XiujnoMlGqX/WCKEemQUmbC2D2xDrN45DAuzqfS2rcOaXSf0zWrKBVGYrGFM5FYkJiMDE62gAf/E5zuxSbbJKOHV0iI3/A+eorOPhyYTcmxWg2D8F93n+gcoTmd0KOAdhf/vIX7rjjDubNm8fzzz/PqlWruO+++3JZRUGgRsJPD5zkYqxqXU0OqwmfnnKVwcBTzsvw1x/C6qrMh2shEItJ/OTl7HV8LVgTg+rI+E3dS72oXKBXqFmeAduSFoC5rJldrImSTetI7axKRhdkRN26Qo70YBwyO/3sZlNmq/6g/WHy2RiiQVySV5Snq8dmrH+zK54hSOOBJZEonUxWz2qAjHcjh7Oqp7SVCBQ04A1FqHSpl1TkUCsJK0p0bF8mOFLV4xSD0Ix1p4nmYnHA4d8mcN1nPFx6o5DxmPUTnin/NoGI7NzYy0QpBoTQ666ViusX0ibqAViZ3Ux3MHMmHgin2ZSE/T3lnkOvTr5skz0U07OlctjT93N/WRnSs13w9zDArNu4/70vWT3kXPH+Z/+AWDRVa2jeL3u6S0ccqbpvBoOBf1yln6uqhwPWksYBS8nGJrKdn/0jb2XInAOwxPimknlVsyPa3ubjuqc/z7j/9cJhjWen4lxPyw55ABbBmchevns3tDcIbuSxt0LtBDjnYX439inax1+Au3o624adofgddqvMl9VgEK4SzmoMDQsw/eca0ZgiReHoW+DMv4ogTIoJwn4a1GQ1pg2rYE1Tp+a+hqMxfvzvTE1DJchFe+VwKWS42mRBodOm3pyWMafzt8Om90VAdN7jxDAgLfqDZiZWscnm08dEhttZA6elOnYk9R8TqBgGR94MI4/ml7W/x1GTPfiCHAOwiooKBg8enPy/rKyMESP0fVEhocRVCCrMWMXsVgyuwYhyWUzu8QjaxPbPSmbxxYkvEC0ZrPh+vtHmC9HaHez1oADiWAUjMvuchEJ7gZCt5VoOl63HhqkxLsKaQEW6z17bFti1nKDRSWDkHM31ZnRB6tABA2XR0YwSpFXFG3HWbULRHRTtkQC2lcWbIbZ+BNFw6qQgG6laBjXJjGQZ8ounIaJeZgmEs3MH5bCnl13jULSJSToAnKSrTK/WfeqXzCyqOBO+sxhm3UaJ7F5OYvQsOPRbYsb/8ncU93lLi7YHpFoGLMPuZM0rgvg85KCeUhvCjihxnQbC6g0bzvSgedKZ4oGx6T149y4hRLv/uVA3ia5AhJc940Q5o2M7bHqvR2uocQl89IAoUZ79oKayPaAqQKsEPRkwwdHpeXCnZGOHzxDnJNgptjEPyKkEGegQOlxGs6rlkhoHbMGGZgKRKHsU3gtHY5iySHgkM+NDp4PZjrntS1EWkyRRPraaRBfvJ48IruM3HkrRJzPWjmX5wb/irUMfx1SqTA2wm9OC+JI6UZIHjg0vFsHWsbfBcXeKe+/oHwpO2uqXYM/alHUp2QMBjKxxscWtbaq+vc1Huy+sS7JCLdBTopk0d/YE9yU2k36P5PX/E+XWkUfBlLP5n+sbGKQovHyd6MZWQEZzVetmcR+CCGxLUqsDipy04++GK15ne7RC1Wg9HTkFYDNnzuTmm2/mtttu4/e//z2zZs1i+PDh/OMf/+Bf/+q7DklvocoBSxv85J0W6RpgCaT7QWo9rJ1WM3s6A73yOewNWrqCxCRy1ymSIZkBG3OcGPC3fdTDOykAujVMZ9PhlKWZG9PMkitlDzYgmR1aU3pk0uBdDekZG70lyPTATXw2klaClJXM5KibhHvcBcQw9phNpyHsrCNQPkZ0TTZ9IWREEtvV9IVQjC+pFwT+LPunGAQOnQ51k4VFkVqWjcwsRjYkuSdpUMz4JBwA0jlwautOTBAy1p0q/6HWrcgJ94iMY/MaxZl+Y2tqYJ8ONR2wDKJvgp8lN2snPlGId+xqZWucCbP35BfXi+xVLCwCb4NRyHUgyl3LGj1ICc2hTx+nOxilzBiSla9+qKuzMRfoCcAisVQ7pPRyP7PvEL+XPQTevhO69fB2k9j6kQhChhwMNuUxwm4xKfLc5q1v5vhJ9TQoBB8eX5gKDf4XiPJgMMGFmxgXTP3XRfDwLCq3v0eF0Qev3iheP/ZWkdmVIdGdqVjWl217xn0/5WyaRooJW3TWHTD7Jz0Tn4phcPA3AanHDiwO9e5ES1ZZpMZWcYzUxLJTvserrZ8mR3NXIFneljdoZUWa5ttrVVcRqRonSPLzf6n4EZ880RKLivsq7IMDLhAViDSUaLhxhNJE4LWQUwDm8/k488wzsVgsdHR0cOyxx1JXV8emTZvYsqWPnQZ9gCIHLBzNIM0Kgq24SNSkEdJrzaGo+sEssZnZ3RHslc+hFjI66+JIcBU8CpIM4aiEOcusDGSuAc4q0SoeiwjBywIhFx/IElmaeVdHgMEyRfaKdDui1SIA+8hxbFZT5RS+DfHytI4yhsOS+jnILEHa0mehMqw+6B4eOuS/qhIlDouZjvq4ZcnGd1KPVSL7NfnsrFkNpUAREANvQhstEQgpQD7Q6YHdrJKlSp9FerYJjqG1FIbN0LduizHjmCutW9UP0uoS2QQMggu249OUt7e1+RhWpW6fpmaJEpCf992rhM2OrUxkqWSodFpp94rPa2nGZZQgIZW/NfVCqBkHgNlkYGilg63DvyEyGF++jaFjG0dsuV/YTg06AI75keo+9RYiW64egEVjUkZSM6OEPOwwGHtCXKD4z3nfRk0kJh0K9mTpkE9gA+EoLd1BjhlXQ6M7k4De4Vfu5JPDbJL5E5/5V7xH/gRcdbBrOcd89l2+8cGp0LlDBIdHfT/j84nMXLdGp77DqpyJXjjpZxwSeJDmg27K/NDRPxDdqWtfTZGl8PiVM2AQ91PUCMIa3D5MRoOqX68cHr/wm1SD/Dy0yEzeXRolyBT42mDLApERjvuvWhwu9sy5X0xqPvybCMzTkDK+fPSAoE6UDoZTlZsW1MYJEMNutma4BHIKwE499VR+8YtfcN1113HZZZdx11138Ytf/IJf/OIX3HHHHbmsKq9QzoBFsaeVVeQK2l0B5cxMegYM1A+m02pid4dfl89hLkjXw0qguTOAwYCiKGlWI+44rPJgNVGGzJcNigL0aoBBj3FqYmA3yma6IrMQ32/3RqEgbyvnY9OBWQO8dJmGlExTlu1Jf0jqLkECnaEYxrIhqut3WI0018c5Ox/8jpIXz+fA2Lp4+fEV8boGqVprO5NI6Ad9+bYqGa+5M0htif4ATG2fM5TwE9fVmFkZ+ktqUMuupZc3NRtqhs+AI24U2Y+Xv5P0WZQkiZAK9SDbev3yMm2CU3fgRRnNHxUOC574RCGnEiQIfTSjRTw84gFV4oF03MQ63tsahclnARKHr/wpY7e9EC9f/Z/u45sLrFkyYG3eEFWu1OvGalaYPM6ON6V8/IhwCOgDDOjMfkGPbtpI7QCsLC2b+tHmVmaOrmZkjSuZ3ZEjmwhrBqxO/AddIxpKTv413dZarOFOEQh94yHl5oC4HZEvGFGV3VCbCDV3hcBVqywwWzakh7M4v4e/7fGqB5UjqpWPQwKNbi+TBpcmr3steHwhKl3K35NeqZBrzMkbtOTIoLis+6/gvY2elTQuL7Gaaa84IB7oSoIzmYZkABb293SKnvlX0VCjADXrpFyRUwDW0dHBrFmzOOqoo7jssssYOXIk77xTuIe3XogMWBoJX6EEKR9cuwJhxcDJZUt9WGvd8C6bmd0FKEE6rcr+Vc1dQUZUORWNqfXymmxyYm3i4bzx3YLJUaQbnmshYYa+s93PkPJUT8dKZ8+DrUcb63Q8QWPWEqfNbEwxFdZ7rJRLkKk6RGqDIGTfd6fVzI7a2UJB31qKc/sH3Lz9u0L3qmO7EPEbmp00LTJ1KoPB0OliEGlvUNUASu9kywabStk1owQpNyDXCaFtpFSCjKaVIJVLhUnMvhNqJggJgvd/AYgHp5Z/H4gAIqJwLyTtToJdsFIoXqeXHwEqXNbkREGUIJXPv9Nqzsz0uaph7ktw2ctCYZseGZxZE+KimPHvHOqJZ/Zm/wTqp2juU2+hpK8oR7MOlXIA9jsExp8iSjpL+pYFyyA/q8HXJjI8JmuPKKwK6spstMi4XvM3NDN7Qh2jalxsaVEIwHSW0TLm7VYnzLiOB6b+my+P+D1c/oog3SttU7w5QMiNaJUglSolAabsV67a3cmRN4PZIUSEm74Q+6QWVIZ8TKiIKZZiE2hwe5k2rELVrUSODA5YZ1NyYpg++WmRjUtOm1nRUiijO1nBNcSZ4BYfebMIercugc5dKevxhSLi/t74ruh6HHJwhvemHFnHH53I2QvynHPOYcuWLSxbtowPP/yQH/7wh33eiL5CKQOWQZoltWyh9nB05mBd4LKZ2N2Z/xJkicrF1tIVZHx9KR1KGTAd6u6QVq6tnyIe8t17hNZSAaAW6Coh0enS0OplVG1qZqHcEeeAtW8V1iwAU76RtKfRQnoGU68Qa7qCPmTqwtktRtXsU7bsX9I3b9at8P1VbD3gJgKmkp5zMfnsrH59oFGCBFG+HHu8+HujcsOFeJDmwAFTKbumZHzCftgSlx/QGMgy1q1WgkzLJpWplSATsNhFdsFgEgr5jUtocHerKuDLoZQoTGbU3/+5KKcNPwLqJmUsV+HoMeTW6oJ0WFWum9HHip84EtfQoHI7XcEI3fWHim5HoLtmGhzxvaz701vYLNoZMHmJKCsSWbBPHs14+OlFLCbpz4Bt/RCQhMuAVfucy+2IJEni44Y2po+sYki5g10d/ozlhQp+9gyYGi23M2zCO/E8TW5nwo7IG4xmirbGodaw0twVZP8hZeoCs6X1cFjcw/mZC+CjB/B6O1ODSl+bmLj8YQKXf3oOu3ep+8q2ekOMqS3RlQFL0exa/R/446Qk2T2dVtDcFUhm5ktU9DH9YRmdpLtZlJ2NlpSu1xJbnFZkL4uPhZIowaatx2k1yRqfMkV75ShVagJCX4OGHDkFYJIkMX369OT/I0aMoL6+PpdVFATKZtzaOmBdSp57JLotek601ozLaTWzu8NfgAyYcro1EYApZsB6U4I0GGRlSHWOUF+QSwnSFQ8kGt1eRqV1a1U6LUjtDfDkaULhfeihqtY82aDmR5aOdPkKyCRW2y0KMhRxdAe1+W8pkieOStaMv4GnZrwusjfjT4GZN+jYm3g2RctuIyH/oFJqbklTM88GtRJkik1M4xKh4j74QCjV75aRVPdOQ7rPpB5NP/Y7WJDTkeCV69i2u4VRNdoNG2rwhyJMX3sffPywGOATAUUaKnV2QaaLA6tBTpU4amw1Sza3wkn3sq5kBk1z/qIpT9JXiAyY+jY25xKADT5QaClFApo6bVrQO8YBusuPEM82xbNFm1u6GVntwmo2YjQaMBjI6HbLZsSdDb6QhgNLHInmAF8okmlblFxGOYhv6QoyZUi5tsflUT8QmUlvM7x9O7d/eSH7rXlENP68ezfcf4DwIQ12Ygu24di6QHE1gXAUq9mY2SSlgpSg9LMnxe8P/wINi1IoQpBqQ+RUuV9SqEZx/1XGHJdSOkwh8CcyY4lAKw5/KEqZKdzTtZ0lAFOzThI2U/plUnQFYLt372bhwoVMnDiR2267jYceeoh///vfzJ07lyOPVNed6S/YzKaUEhMo6PYQ1wGTccBUM2DxE52ts7DEZqalqzAZMCXCYXNXgPGDSpU5YApNB0rIINYmH86FkaPIhYTvjGt9NSiIsNZFdnL5+utFaW7oYaJUo2LNkw26M2AKN30kFsMq4xY6VEpmIK4xreyf02oiIFt/VyCMraQSjv0RXPIclGv7iMm3QSlrlMTY4wGDCIqCXRlv51qCTBGAlCGlYSUR7OnQ/pLDYjISVSgBKpcgdfhcHvMjQVL3bOWkd0/g0iUnwx8ni5+/HQbrM61CzEZDKo9JinHUhl8xcsszooRx0bPCLFwBFbJSuVYXpGrnahrk98/sCXXMX98MY+fwtyH3Ya3N1JbLJ8wmI1GNMVAE7sqZU8Wxc9ZPAIPIYHc25bw9OWmA5UDAl0tRzFvfzHEyR4jB5Q6aPKlZMI9ODpiafU63XAcsC7rTVfNlUCtBhqMx9qt00NKtEYA5q+Ca9+Hi52HIwZTHPJQu+jn8+UDhYxvqFuPGIVcAMLxN2VR6e5uPEVXOlO5fNUiSrGmjuyW1M/vV66m2hFKCGpGVEsdJ7ZkYkHcnJ3QT03izcnkjxp8syq/bl0HHjpTvGudZIsrkQw8THaMaUBt/FG2mNKArAFu/fj2PPvoob775JiNGjGDJkiW8+uqrGAwG2tvbdX9ZoaBWgkwXViuzW+gKZumClJ1orQ5IEA/QmETeAzBRBlWIrkNR9quw06HIAVNR7E9DxrEadazgSez4NC9t4unozCEDluDfNKSrlbs3MfzV86mMtAg9n8v+A/ZyQpGYrs7PdAR0eGaCsBnKlqWwqZTMQGcJMiUA08+XS1mPVgkSxGA79FAhcZAoC8rQ2h2i2pVDAKYRPBgMBjHNTQT0OQZgakgvQZbYzHTpIcGarXD2Q2Bx4Yx0YPfvFqbgnTtFW/oLl/U0PCTWbZfdf7EYJfPv4MA9LxM12eDiZ2G8+j5VOC3JCZJWCVJVuy0N8mvooOGVLN/uQZKkuJhnDoKkBUBzp3L3rNVkzJgQA4LyMPlMoXGWyH7kAEWhXyV43dC8VjhBDD006+JyO6IFG1qYNaFH82mUAhG/XYcMBYgMlZqkSolKVkuOUruZPZ1BdRK+wuQvEfjKy6qqMBhgwsnwrXncVXpPD990/MlwzTwxyT3iuwBMC36qaPGVmCyLLnXtCVGXXJJoXTxbNXo2DJoKnm2cuOOBZFCTHsAnGrTSkdSF69wlys4mm/BmlMElpxXZSnru30TAhrhXx7XEJ406Gp/UZHCER6v++1LXaD9r1ixmzZqle6X9DaUSZEDBoFNOnFN72LlsPSdaaR1yJC6mUlt+S5DybUhAkiQkSXChlC50LcFYOWzpAZitROgPbZkvRCAPvLDnPV+b6Fw64LwkKThXdAUilOQYVKSUNlo2wD/OwOTdw2rLAex/6b+Tmj65ZNfMcWkPi8mIJKV2WKpB0eInDWqzUD3bJ0qQPee5MxDRVGlX306NLsgExp8opBM2vg2TTk95qzTajmnhr2HsHFXJDPztsOI5qJuEwzqOrk6N4Kd1kyhlOKpEmSMP8IcilMlkSXSVIBMYtD/csoGrH3qPhy47BEtiUvXxw4IUnrBrieu1ldrEuiukLnjrVuxrXyRksNF4/GOMT/DpVFDptCY5mlolSJtKFjEd8nHKZDQwvr6Utbs68WnIE/QX1EqQjrjsS4ayOAj/zrWvCnX8Y36UUxY7PQhXRSKzMuywFHFTNSTsiDoDYXyhKHWy62xUjYsGt5ejZTZdHl9IFwcsMTakL9odjOoKnutK7azZ2amqe+awmITWmAwJQdWaEpt2BkwOg4HPLIfA1d8TQZFc9qZ6DFSNprRtC91bllIyLtUWSUyWnalNUirweGXcubiMEFMvFMbtD89iyq6XaN5+Aky9uEc/MtABy5+ljhp8wXEZ60w2VK19FZAEpSbNastlM6VmMaecI5Zf8zIcIaQ6Ir5OhrQsAgzxTmNtqHnGekPqnD0l9M6ReB+DohVReks8YmbbmcIBU5ahSEhAZFNdTqSRcw0wssFly2wESFyQlXI5Bhn0KkQrtpYnRDLlHKHuFnjydOG997/eN1pk40GlIxKVsJgMIpPSvE5wvrr3wKhjuKvk7hRBRVHi0y9xoSfjIEfWzBLaJchOFakT+TallyB7lQHLVoIEWan53RQiRiQS4Vbv74Qw42MnwD/PEqXKBLytgnj+pwPgrdvg+cuxGyXt4CHBoxh7fFYNMyUoEa17XYKMQ7KWsNtQg6VqOJQPFT/H3yOCACkK//kWrHwBgMHmThwLfiZ4MKteRDI7eGzEbwmPUPfjTEA+U092Vinto06doPQmltkTa1mwoUWxyai/oSbg67Bo8NtGHAk144U5+4Y3c/o+X0iffl/SW1XDP1WO2njH4ZKNbo4eV5Py3shqV0YHoMcXpkJFSkEORZ9YIBqL9UwCNFBXasOmUdVQ4oAlpBusZiMRHcr0EG9uMCAyYkr3a7yL2bs6s1yfsPaqcGTngCVtiDp3iU5EkxUmnioyo3H/3ENX3gV+D+6WPXwz+K/kuDPk7Wup7chsFAuEY5QbZN21Ctwtl82cyqkedyJYXMKaqL0RgMF75mOKhUSFRUM6KAHVEmSwACXIfR1KgoF+BR0wOb+kKxBRzFy5ZOW/bFwhl9WEy2rSr8ysE0rO7y1dQWrLbJQ7LColSL0yFApK44mH86b3RJq5aw/843ShJg4iO6YiYZAN2XhQ6YhJEsMqnbB7tQi+vC0iTX3x84SMqYN9LiW7dDFWPUgPbJR4LXaN4EeLQCvWb84oQfYmmFe6XjIwaCqUDBINDDIBRv+HD3NgeIUwk7aWChHDJ0+FJ06Dt34SJ+P+QbRmG80Q7KCme51q0An0BPI61e/TodT4IueDQJxOkEMbuGKjgcEgbFpm/UTM/P9zLbx4Jbd/eSE1K/9POBSMOxHPuS+w1nagrgyzPLDyh2OaGRs9MVh6GfvY8XUs3NCSatq+lxCIKHOyNDOyBkOPfEfCTUAn/KEoTj0lyBz4XyAI1Z2BsJCfkPG/IF6CTAvAuoJhSnU8ZNVK9Xq9cevKbKrlx571pz735NIgBgO6bOuyTmTjjVr2hvcy3krQRfTIMiSlLhLZqrEn9JjYH/FdOqqnURJshn+exbB/Hs6pbf+AYAeUD8Mgxbii+TcQShXG9YejnLz9fuhqEuVmhQAsg9JjdYrSKyTLkKP36C8/gnoG3htUdy5QQsEDsPb2dv7v//4v+fP22z1k7+bmZh5++GEef/xx/P7Mdl+9UOKAZViHpKFLJTMjn8EGwjHNGYjLZi6IDVGJzUx3UGlmY1MlxuollitmwOJpZgIeWP+aCHxa1ot29wkJQ90ne7UvuXRBgjimhzm2iwDQ1yqyKBc/B1YnBlJJrblkjNRmo1pIf5AEFSwm1HgeQNZSZ7pqeHcOGb2UbdBTgkzpeI0PNq2bcX3wc/H3mX+Fm1cK7zhbOWxdLOQbwl4xUF79Lhw0F4DalmX4Q6nXUJKPF+wSXAyDUXQj9QIGFEzQQ6lNNSV2BXN2DTS4NUy4Z8X98hD+mxYpSPOQOfCt+XDpi0RrJ+fmQYgI1oVtlfr1qedBnH6NV7msxCRJUai5P5GgRCgha0b2wIsEPyvHiZ0/rOPh1rUb3F+KDMcQfdZMBoMBSYKVOzo4cGhFynv1ZTb2KHCp9GQw1ZpV9KKu1K6ZTbEpVH7kE43KdPcQFXj8WUqqI44kYnJQ3rkho3mi0x+hwmnFaDQQy3JBi9KtRZksbzKz9eg/EDbYYNdyzOFudlQeDle8ATd+SqxmIoMjO0Q2Xobyre8wueV/glh/9kOKGTwlSk/SX3f1f8DvYVTHR0gGo67yI4igXWn80dPhKkfBA7CVK1fyz3/+k0gkQiQSIRoVF0xraysnn3wyfr+flStXcvnll/f6OxQ5YBHtgKRbJdtQIiv/pWs+pcNlNeedgA/xltu0k9usku5PIBtfLQFVgmxCLPPfVwnxyropcMX/hHUFZDV0VkOuZbX92cLF624UnKPxJ4uOM4vY7zJHato3F4K/PEuks/qD3ZquoJ8543docMD0bJP8QaU2Kci6Hj0lSEgtQ8ai8Mr1GCN+1tacJAYeZ5WQV/j+Kphzt8hUfGsezP234NPEW/orm5dlZMCSStJbFgiy/9DDxPp6ARHUph5TUYLsOTYmHQO+HI2taY0d6TjmR3DGn+Ggy/jPYc+xePpfUrwV9U5wIJ5FD0U1Sfh6oXSNHzu+Vq8caV6glPlNIVSnIcOOKGOByh4Lpxwmdv5QLHsJsjHerTd8Rk7uAHaLkYmDSjOqGQaDAVN6V6xOqMm16B1/akttmoRuRQNrWQBWW6qPB9buC1OuJathsRMYFs8mymgqosSuP4Tw+MIMphW2LxUB0/iTU7+mfjxPDb0Lps3lv9Of5OOjH4eRR4LFjvGch4hihGUP9pSYva1M/SJumH383VCj3BXsspozJyxjjxdWYrtXwod/wSxF8A6eIQzNdUBNB6xbw7lACQUPwLZt28acOXO44YYbuOGGGzj1VNGh8Nhjj3H99dfzve99j/vvv5/TTz+dYDD3BzwoZ8DUTFsTPouRmKRYh3emkPCzlCBtpoIEYEoRe3NnT2rZZDBk1Pf1PiBsFqOyblUiOyLFRNv+N18DVw2rGYs0aKowdF7735z3JVsQmwL3Jn7ivlXYdEw4DS54KoVEm95p0x3UX4JMzMpzEcoTAVLPsUoPAkCrzJD9EWlP64LszsIZU0M2uYAkRs8SGlY7PhZ2HNuX4rfVsvKANBsxe7kIvE//UyqJPh6AufZ8QjiUKvKYJEgn+F85iK+mQ+mY6iZgI2baL366PeXn3bXNGdImGTjkCjjrb0Rq988oL+gt8UOPFEWGNVMazCZlz1c5lCzTZk+sU5UmyDfMRpmnoQxCo0l5QqiHO8n0q8XvL55mT1uHLhFPXyjSU4KUJHj+MnjoKNEckujQa4h3+eosPyZQV2rPKD8mMKzKwY52UaEJKHTXq0GpRBiMRHXxv8Q22XLiE0H8vMQn6rV6OiERRtzZvC1tk+LBkkwvstHtE1nlda/BHyYyI/qZZsav3RdifOv74p/xJ2YYpJfazSy1zICzH2CNcWJqwmHIQTzviDeIvXq9yLT/7wfYQ200V02Hw76t+r2CA5aWrbLYe7ol47p0gfFnqx+ANKhpsPk0nAuUUPA2mm3btrF48WJmzpxJTU0Nf/7znxk9ejQff/wxxx13HLNnzyYWi3Hvvfdis2V2rDz88MM8/PDDALS0tOB2uzOW6Q5G8PoDKe9FIhHFZe3GGFt37lF9H8AfDOF2u2lu9RALB1WXi0kSNxw5RPX93iLk89PW6UtZ79ZmD4NGlON2u3GaYcuOPVTJiKCtHV1U26JZtyUYieENKOxT6UQqqici2UrpPPUhJL8Efjc3PruClw45j+rdKwkv/T86hszOaV8ikQitrTrkLWJRyl+6BmfMi3/kHLzH/QE8nSmL2A1Rtu5qoRQxGO5u9VBiNWnuc0dHh/gjGmK3u50aSwiTlP04AQS6A3i6e85DU6sfk5R63Xi9ITq8/oz1+UNRLAZJ83si0Rhdsus2GA7jaW/Lul2K69K4nuUoGzId646PYPEfAXht2C0YLQ6d17CJisqxmNs3UdW2Ard7VPKdnW1+TNEgsXWvYwTa62YS7eV9YYhF2LmnhahM4qCj24+/uwM3PVQFtX1+fXULi7d4mDa0NPnawUPsjCyJ6drPWMjH7vae89LR0YHXH6K7ox2fntKTMUZjUwv+YIhOj/r5NBNlx65mzUlEW5eXiL8Lt7snQKmzSvx49rC8jztKMEpRmva0ZGRiGpo6cZmU7yMpHGSPux13lcaxsg2nonYK5pY1LP3vw6yqOIHvHDVUc1ta2juwmY243W5MzaupXBefEL78baLzfoXvkOtxblqACfBUTiWSw/G5YnotQyssivtT7zSyYssuSqmguSuE06x9XycQCwVpbm3HXdEzDnn8YawGfddhqUHiium12mNI2j2w3d2BJVqK2y3hMkbY0uRmstZ5AHbsacMSC2t+j7HuUKqA2Ob5tO3ZCSYbKxtaGW12E3vleozBTq4xPUzD9nOoLVN2Htjp7mTQntcB6Bx+PKG07wsHIrR1ibF0m7sDy2hXyjY9YzmXC0pWYm5ZQ+TRkzC3rCFkdLBkwh0c3aZ+n4UiMTq8gYz9sww/nvKVz4EUI4qR1vqjIIdrJhaJsmPXnpTER0t7FzW21PNbU1Oj9HGgHwKwSy65hNmzZ3PIIYfwyCOPcPnll7N48WLcbjevvfYaL7zwAhs2bOC8885j8+bNOJ2pJ+/aa6/l2muvBWDatGmKO1MaiSIZNqe8ZzabFZetLnNidZWrvg9gMon3rLsjVJdLmgdwTm2t6nu9RcQSIGrYnfK93sgOxg6tpaamjLoKF0ZHKTUyVW+jxU19daXmtkKcu2H4Unm5G5cCUC17yLT6IgT2vxiW/Q5L0yfUxFoULVjUkDiWWbH4T7DnCygdguPCx3AomKAOrmpFsjiT64uZ2hlcW5p1/TU1NVSXt2NxuHCWVVDmsuvappgtQNTQlFx2d7CDipL2lM9aS8LEDFsz1renM0BVqSP79xg3JJfRuiazQfdnJ58OOz4Sfx90Gaukozh7v1pqapRNZzMwdhZ8sokJwVXU1FyTfHlPqIPphnUYA+1QM57KCUfor7WkobxkO87S8pTrO8om9htUm8KRc9qslJRXZmR+3cFWLp45mjmTeufSsV+7REOHO+V4Gs1N1Om81wdXtSBZnVnPSbnLgbOsghqVTBJAMLaJEYPrMkpEerelr3A5bJSWV1LlSi3nxfZEGFwVVdy/mopOLA5r9uvx8G/B6zdzYMt/eaRrBndmWd5k7aC2In5PfTFPvDj8COjejaltC6XzbhOvWUupmHhsTi4BWl89aZiftkCEmpoaWsKd1JWX6LrXqio8WBw941VNTQ3+Nh8VJTrGhTgG1Wmf5/RrrCO0kQnDB1FqtzBqUIjt7b6s3xUxdbFfrUt7uZoatllGMTzcQE33lzBmNq0r27mg+X6MQTFRHhzdibT9PWqOzfRIBbD6llHevhosLsoOPi/DIqoyJhGSNlFTU0NnaBPjhw2iUnbdGSx2zOc9Ag/PwtwiGsQWj/4+jv0maW67JElE2ZC5TMVZ8N4PIdDBGttBjBg5nnId+m4JHD2xng0emDOpZ72SqZlBNdmfwwkUvAQ5atQojjjiCGw2G9dddx2rV69GkiSGDBnCVVddRW1tLUcddRRjxoxh48aNvfoOVV6TAkptFlq9QV1p4Fx4H/mES8H3Ss4Bq3Bkaq7o3VaDwaBur2QwpDw0A+EoXYEI7REbTL1AvJhD51KyvTkb9qyF+feKv8/6q6oDvRC57NnvroC+biToKUEGwzHd7fvphslKStxqHLDeSkoUHBNOEd2M5cPhpHv1GyonEC9DjvcvT3nZH4pySPcC8c+Uc3odfEGCvJzGAVMoZZfYLYpE2IbWTCeFXFBqt+gTeVVBhU5bFj2luu5g7zpj8wUlojdAhy9MpYoUg64SJAjdNWspI70rqfVtoblTxbswDl+iC1KSeojcx90JN3wC5zwi5C1AlLfyaNEkF2MVZtL6HtJ2c+bY4AtFNTujewM53cEr4+bpEmNFwSBbBY2Vce/KeBmybuPz1O1ZBPYKwRkFqj69H6LK1/6E1nj5csLJiv6cJmNPk1VCz0wOi8lIqHoSzL5dvDD2eD6rOTPrc0+1YcJshQPOB+Bd65yc+ZqzJ9Qxf0NzymvefY2Ef9ttt/Hzn4vOhddee41x48ZhMBg46aSTeOGFF/D5fKxZs4Yvv/yS0aNH9+o79GrqgOie2tUR0PVw1Gvvk28o+V6JThVxQSoN8MFI/nWBEurQHl8Ypl8pXlzxHIS8Gp/qgS9NOkAR0TC8/G2hjn3IFT3G0QpI3+9cOiwTxGB/DlweR1rnpBIPyWIS6v3p6MxR1T4Xboga9PDOqB4D1y4U5Hp7Wc4+kMkALLgGwj0PTL/fz2RPnH+js5VbDUodq0raSWqt7zvafELKpJfQ01KvhQodopSgbPaeDjUua3/BZjYpGnK3+0Kq2QLdki+20uTE7vuVS1iwoUVz8SSnbudn4NkGpYOFbpPJLNZz/VKh4H76/dm/OwfItcBy8YFU4jLmalWTDUJgOvW+TzwP68rsukj4evepY2i8q3nj29C+ldN3/038f9of4Ijv0u4Yjr1rq3hGKOCIQNyfc4q+8SH9ue6ymsX9cuTNojvygqfwhyWdiQeVN078FVz9HvMtR6dYzOnBISMq+bSxPSMA3qdI+LfeeitffPEF48aN449//CP//Oc/AbjssssYNmwYU6dO5eKLL+bpp5+mtLQ0y9r0IRqTMKoc8VK7mSaPX/PhaDaJrsoUo89+hFKHlyT1XJDpmSAQGYhcOlL0IOGP1u4LCWL+0MMg2AmrX9L1+XQRSUV88HvRiVIxHE78peai6WrLueqA+UJRxU5GNaSfB38oonuWlKv8hhLZOhcozbZVMWh/KBGljWBEX/dsEq5qpLrJWAnDjk+SLzt3LsIe7RLds7UTctn0DDismQrfSihTEEOUJIlwVMp5MJUjV5HXdFTK7Ii0oGT2vq9BUbYG0TmnljVxWMz6NffimmBT3G+ycL22P2TSkH113Eh58tkgb6gxmmDoIRlK6H1FTYkVd7cYd9p1+kACOKyZMhT5tpCSC0H70sanulIbLbpI+Pr2yTVmJgFTqXC6eO4SHJJfdE/vfy6YzKwed51YcOFvIZL6fJKWPsTY6GahNZjFTSIYiSrev0IiKiqiqZFHgtWZVe0gKyx2GHZorzL2FpORMbUlbGzuTr7mC+U2jhc8uqisrOTll19m48aNfPDBB0yaJPhDRqORP/7xj2zatImVK1dy4on58YwD7XJcqd3CTo9f0z6oxCZmpv5wTL/5awERjEQxy2b/Ss7zemUockFzZ5D9Khw9yvuHxjuXPnkM/J7UH4UsUNYgpOkL+OB34u+zHxQzYg1UpLkAdOZQ5kuYHwfCMd1dTOnIxQy4KxDWfSNKkpSTqr8Ssrb+q3xvb2AYdaz4Q2amW7s1rpKtIISYK+xmo7bQaxxKYog5Z/QUkKvIazrKHVaauwKaPrKQQ6luLyLDuiyODr961kRYbOnbL6l+CttMwzCFOnHt+VSzK1SUIA2qpsuFgsFgSLqtZNXMkkFMitIDsKguH0i9sFuMSTcN0Znac+0rdv8pwOPPLPcpYWRdOaud08U/e1bjMVbAaX9MBi+e0WfQ5hwFHdtg+dM9H/zoAQxv3Sr+PvEXSVkhJdjMRna0+6ktybyHlQy59XYnJ9QP8o1ZE2qZt76nDNmdY4D9lVDCT4eWL6KeDJgzruMT2AfsPgDc3aGUC1LJeT6XmYCS1YsSmruCjK8vweONf9fkswQ/a9dy+M2I1J9Hj8sIwrLyoF67WdjAzLgeRh6lvlwc6TIUuZYgRVDd+xlTuhq7FvQ6ACRcHPrKGdNTzkpHhz+cE+k0iUSLf0KPJxxg0K54e3keHoo2ndpqpbbMTFWGkXtvvj+N9xSJSZhymCFXuizs8gSyBuvZBEsD4WjWIK7QUJL4AWj3qmfAcnGd8PjCrHIcDsAZztV80qjezRYIR6lwfy5Uz8uH6TLazheGVznZ3uZT5CapQUmGQmTA8hmA9XxHNq1INXT4QrrMxYdVOVksHZT8/9WhPwJXD9m80uVg4eD4JP2D3wvdyMX3w9uCs/VC/fd7qCwqKLVb2NLiVTR5d9pMigGYnqqEy2oqiHjxrAl1LJDxwJI8RZ34SgZgWqXDMruZJk9A88EtTlak7+nNPiKRoWjuDKRckErO87mUIFVJ+Glo6QoyflBpT9bJ4hC2LY5KoZae+DEYRTZrd6pXlyYPyusWgZzFBcf9VNf2iMxfT+AZicV0l5ocFlkJsrcBWJoauxa6dQaHiYdVd46cMaX15FrO6nW2aMQRxDCIEmTIB5vfxxrpxlM+qdem7XLosYACMZnqTMtUCW+63vO/IJN7kmuZttJppakjkKEZl45sJuq5lrELAatJmYTv0cqA6RUGRgQNW6uOBODgwMeaPDBfKELZFiFjwJSz+9TokStGVTtpcPto9+rngNksmSVIYU9WmBKk0v3ssmZ3jIhKUkqFRQ0Wk5HF5sOR9pvOpnFX4R2dKqRa4bSw1H6UoCF07oSnvgHv3Q0Y2HT4vWwcfkHW7yi1m/n/9s48So7qvvffrr23mR7Non0Z7UYghIQkJAQIkIMFFnZiBCRgk2CBlxwbv4MxxuCckBiHYDvEEByjc+wDARLICZaxsMmTAAnFj+UhbIGAp9FoGQltM9Oz9b73+6O6eqp7qqqruqu6arrv5xwOo97qdvWtW7/7W76/o4MRdPomGpJKPZL1Rn5Ep4ryeag2EgCIWmupTA5jhXtkTue5lGhQA0w9dOgX2IoeMC8vTtqEgRuu2Qiy/pZSGyIJpc7zCQM3CaVWL0oMhBNY3OUvzTdb+xXg3j7gvpPj/130RfE5mUgfUOEGcuaA+P/pFypWxCjRIjDFiS59D714OKYQgjSWKyc/V0pCrOWvkdDr0ZISzo2o+itRTTirfF7pP1gbjtHzRcX7T94u5uT0z77W+GcpIJQ1OE9mlMPGSiHI48FYTRWQEvI12Wh4v9XN4uxYvKJwrFuh2EZOOJG2tQISEI0IpRywSAUlfL0hyIFwAuGpqwHOD2/oCI4e/lj1tfFkCsJhyQCrPdRthHkdXhwPRgrhOp05YArFJNFU1tQkfF5m7A6EExMMsM4WvmJ1qRG8LVMweNNv8dupX0d3WWuvgIfFSDwrdtMAxIbbcAGf/xk+nPZ5XZs9v8Di6EBE0QPmVTCi9EappLQiJZRazBnhskWd+H1vdZp8DWOAyW+CWj+KX2AwFE1VNMBEb0n1+UK14uHHdy7lrmWlKkilKjE1OEafbMdAOIkl0/yVS+qlpsu9/7vkYU0j5Mwfxf/PuEj5eQUYmirpBWkEtywJ38jNVGDH85HUlM2V8mT0GlRScUDtIUjtm7kSogSF8ZAFAHzALhf/6N0N9LwCABjpvq6qzypHYEtlKGIpZRV8pWT548EI5sv0w6qFco2XxIseMP1LpcDSSKZzFT2tlTxFRhvZWwFH04ohSHlRUDlGQpADoSQ6Wn3AAlHg+Qrqj/hkOKb42gWxD0BF+4G2ebr7PJqFaIDFxvsZ6kAtBGlmFwNB5mVT2lB1+fliNbsSmWzOUHi9u0OsCO1TkHop5iYv/Sww+xLARQN/+iSw4i90rzUtAoNjwajixlDeTk4ins5C0OEk8Sj0V5ZIGEgtUeLKpV0leWBGaBgDjJcZFVpeDummqB2CLHjAbAxB+vjxmPVgqFSrScx9qT5JWC2xtpzhaArzO72VS+q7rwBoDji1H4iOq95re8D+IP7fgAEmJ5PNwUh1/rgBZuxm6pZpgcVVDAGlcnO9FZrSTbjWcFOlcJYS5Um7Rvh//IXiH+/+AkhHcdrzKVBTurXfpJPy86nWzkrJA3ZmNIEZgeqMSjlyLT7DlaIQvQGVcsAq/WZiqy17Q5BqHjAtRM+PvvWpaDQUNnFX0QcmaCtJXJos5Bwu+9O6hh8BYH6HF33BqKHWauWeXEBMwjdTB0w8RiFSEpqYA9bp5zGgYYCNxdNoMZAHKmminRia2NxerFLMiL/Nl14C7u4BLhTbBw3q9LZLIUglY82nYESls/q8Vz5+Yn9liViqtvv88pmt+PD0GHI59Qb1ajSMAcYx4z0OtUIGkttca2fpLbgrjUgWmI08Zj0YKY3tU5SGmKoO1ErLy8nm8vBwTGVjjfcBcy8FkAeOvFp8WFMoVfKAzTS2k5X65xkVqPQUqyCNXWweWb/G8jJvCaWFVq9HS6peNCKpofo5VYQgq60YPO5djryLBrLi4n6g5aqaG09LuMsNsFRG8Tr0CwwiMgMsl8sbzsFQQ95sN5mp7M0qJ+DhKocgKxROGBEatgoxB6z0+o9XaDJuJBxezFtaKPYOnTHyLn7/8ScTX5jNYH3q/4h/69SRMpOAhyumP+jVnXSzdLFCUUL0gJn3m7rLQpDlG6ouv6BpgGnJiSgheQKV0nxcLte4XcwKRakbcWz6Nns+nsFoLK2ShK9sROn5PTzcRHFzCTUPu14oyoVlM1vwbt+wYUOuYQwwnqGQzIoTUVuGQpz8WjdvKdkvns7ZogMGlJbc6vFUGMmHUlO3lpPJ5owJQC4qyIj07io+pJpYHjoLhM+KCfxtxrwmYheAtGiwaEiJlFPqAdN/kcjlHdRkScpDZoD+BGrJrV7rzdbNGs8B07srVSLPtSAzdXnx3+94rjBts1KevKwZgkyOhyDPhRKYptHWxwh+YTwFoBqJlzYPWzkEWdbsvRyjYr5WoOQBExPw1W/anI4m4xLFTgz+qcD0FaAyCUwf3T9xM9G3D4H8GNC+UNQktAGBpZTUdjRfP8EDlsrUdLNXOoa0lo/EUphS9rt0+fminqMSY3H9IVUA6G734o8nR1Srp/N55aT2gVASnTpCkH6BhcsFtHsnzi+fQhWkXny8eopGQkFg2yhXLunCbw+eNWxcN4wBJveAaUkNCCwNjqY0b44eTvyh7WpFVBxDYcIEI0l0lOmicHTpTcqIR4xTUbeWMxxNFS8ClwuVk/YlA+zIq0BOHJeqEXL2gPj/GReWCinqIOBhMRZPGdIAA8aNTqMyFHLPUlxl8RQUcnm0kpRLPt/OEGQ4oWtRVEJgacRmFFqTzF6Ls2g3zQArV8KPq4QIykOQfcHaWhDJkWuBJTI58AZFjvWHILU8YPaHIDmaQqrMiBiJaksxGOlMInpGCnOwsIZ81v0h3j42VPrC954S/19jm6tamNvuNeR1V8oBixlsVaPvGOLvk8+L3hg5XS3aYqwj0TRaDXjAZgQEfHBqTPU686oUloT0iHJD3Pi0ezlFL7YkD1UNWlWQtYYgAeDyRZ3Y9VG/4QrXhjHAeIbWlQMGiD+yZhJ+4YdO2miAeWUesEwuPyHBvk3mEs/l8lV4wLQNMHniv5/XIUzZsRCYMh9IjBYV0lV38FUk4Eu0FSQ4jN6cXC4XXHAZlqEoDUFm4VGoglTa6eptIePmGDEEmawxCZ+jETeoA1ZLkrfA0gguvUVsTXTVA2J+nKkhSFkSvsoOtVyG4pgJGmDyz641BKlHB6xSFaT9HrCJSfhGEtErUaIcXjDALoi9gz2H+sdf9PFLwMcvIQkeuOgWU45bDfPavYa+t1KkIWKRDlg6mwOjsN5UDkEa+y0ZmsL0gIDuDuXKdaUuLRJ6DHO/wKpuCoutiKrAq+E9U2oxZ5RWD4s5UzzEAwaIO1atBbOiAVYwfnJ52NaHzVvwwmVVGlq3yia60SotPTlg8nyCNu9E4VdFysKQqjeQGgywVjeLkWiqKt2sPPJiz0xDSfjjO0y1ipvynCUjjFdB1pgDVkUIEjDmrZAjsBTC7pnAX74MdF+uWiFa3WeXns9ESrlKiaUpZGUxoT7TDbBxD5jhJHw3q0OGonIVpDM8YOUhSP1SDJUoiVbNXAl42iFEPsGZox/g7WND2P9RD9IvfQsA8Kz/drEC0ia6O70IuPV/b6Vry8yNCjDuLVaKkgCFlA2NtXtMpwq+nPkdXnSrVBqLfVDLu7RkwetM5fELjGpahFgYU1kfUPG93EQNMQm1yIZRNi7tbGYPmKwKsoJL8e4/WaIpL+HV0AypF55CzHoklsIU78QJKW9HZDRUytGVZSjEmL14XCXhV0UkA+ywaIDFUgoVP/l8jR4wsR1RtR4jtXCWGvKE4pSKXoxSFaTuzy+8t1YdME/Bk6YXo+ehnPKwazKjf5Gt/NkTc8D0jFWpNL5a/AJb9K4lq8gFvWbZNKyaM0XzNS1utkTXrhxHeMAUvOUjOps3V7pBio2LZb8rRRf7BH5z9nHs/ugcvLu/AzY5jOP+VWjb+HXjX8BELpk/BZ+7aEZNn5HL5yeECWtBYMRrRS1PmKJcmpV54m9pzJj+0rp5uHhum+JzSm3yBg0o9Hd3eHHb+rmKz3nLkvCN6HcpqehLmBGCBIAbVs7C9StmGnqPvVe3iYgeMHkSvvoPs+VC7YtISXG33vh4BoPhpGgIqe1sCh6weDprSK+MZ8e9hWpIbYjKj6XJ3EsB1gP0HwRCZ5CHwmITOg1EB0U1/YDyhaZFm5dDfygBgaWr6p2Y0KHPJKe8Uk1pV1ue62FkxycZeJmsflV/5c+hDFVBDoaV55Xu4ylUflbrTVP8bB0hyHLOjiUw3cQk/JMFPapkJocpPmML9IWzA5WPwWurlNfqFTUDXkEzcDSWruhpZAubPK11SfHGvOhPgA9ewPL4O1i+dDHw3l6A86P7y0+hOzCn2q9hCl1+oWrdPKsQPfS5QkWz8tiYghdTaX0ZNVgFCQCXL+5UfU7crJfeK5SqM9Xw8gyuWjpV9Tn59ZI0UBzj49Xzx4y0mNOiq0UYz2fUScN4wOTiorXqd4nuSps9YIXqOLXJG/COe6WMymXwNIVUVvtmPSi7oJV2NYqwAjB/o/h37y7lnZfc+1XFDbtVXgVp8OZEUxQiyYyhhGp5ix+14ZZ7wAz1qCyEDmu1XdwsY8gAM7IoKiGw4xses1EOQSrPb6nJrhSqN8u74ONrC0HqweXS9k44IgTJTPydR3X0DhQlGCpv8ibIoCy4SmxtduJN4HffFh/7zA8Bm40vpyJdK1ptxTp9PAYjynlgo7G0rj6QegkUIhRy1JwIRinvLGDkPu/RyB9T03esBw1jgPEMPV4FmaptwfTwtK4u8lYieeHU2sW0yWLtCYMhEp6ldXjAxsVftRIrJ7BI1PPJy+QoSqgh/AiMJ+GHqmjT4mFpDEdTBkOQ41U9ajdLgaVKFgYjoSPJwKuhHVlhnPrbvwA1tCEqoFThZRblYS+tEIEkSnx6JI6ZAbdpYyjXAbOqI4bAqnsuw0kneMDoCR6wkVjlHDAPRyNWQYxVcRPgmQLMXgvkMkBiTPSISa3OJilSKDanks9bCwIjrh/y9bqcLo12RGISvjn5fEDhvhQt94BVL/gsh6ZcyMkWykp6dHK0kvDNCkFWQwMZYOZ6wCLJjF3VzsUxRJMZ1fh5wM2VhCDNzgGT76iUWh+pIuWBHd0LP6NwYzldmwK+1JC7Gu+Ah6MxGkvp6h0mIXmotPJZxEVw/Hwa8oBxNEKJtGIFkxGMtH8BCg3eawin8Ap97szC5SoVGo6l1ZNkJTHW4ybmfwGiULPkATNa5GKELr+g2irGSHsxq5AXN0mMxionblfqcwkoK7cDKG7iIASALY/ZJjthBgxFIZ0ttMjLKFdR14KUL6m1odJqR2R2mLvVPTFf2EgOmBESmazuaIZWWpEZVZDV0lgGWGZchqIWVW6aciGWtM8qBqRCANG1rBiClFdBGg1B6sgBk7dfUWr+rUrrLKBrGVzpKFbhUOlzJQn41fVya/VUH4IUOBqhRAYsbaSJt7jDTGnkaMkrJQFj8g5ulsZgOFlz02WjSvgD4SQ6a9iVyis/xRJ465aShMZOV5SiSIsVkO3mGWB+gS2q7Feqqq6FrhZtoUy7EQWulWQotL0mbg3PnkR5h48iK/8SOO/zwI1PAy3TDY7YWchzJUUJCnPnkVQFKSbhKxs5WlIUinm6NaBUMa/UJNwMjAgkezS6TsRT9nW8aRgDjJNprlRKwteDnSKswHjC4UA4oZyELw9BZrKGQpAcPXFRlVPu7RGNPZ0eMKC4g70k9Wbp4yN9ok6Ytwtoqa6aqKWgfl5NhZiHpZHP5w0li0tJ8lp5AuVVe8ZCkAz6QwlDqv6K42SNhSBrTcKXq//HDIQCqiGmsUBKYqzHTRRhFT9XlgNWhRK+Xroq9OqzGyXJmkSm8g1LT1Wu6AFTmIPedtH4kvJJJzECSxXbEcWSWVPbEImfL3rfByNJdPiUjeJK/SDNRClf2KwQJCB2fJHuT0ZCkAxNIasSxVBrMVcPGsYAK/WA1b5gMjRlWxsiYFx0Tq28WD7R46kceAPft1KD3bF4uqTVRMDDTUis1OT8P0MeLqwffXk85AjUnIAPjCcuRxIZw1WQHo42PC+kxE+tJrxSHoaE0RDkQDhZcxigXBOrErUuigIja9FkcRJrTKNKSRJM7RsyTwMMKM1hqqYZt166/IJifk46mwNtoVdRL3pEm5XQ45HVyltqFOS5kpFkxrBOVOXPFzd/aY08RTEEOXGOJTNZ00PcrQoV80ORFNoVpJSqQb7xSxjUdFTLIomncyQEWSucbKFIpLOG8nyU8HC0bW5JYDyxW61EVn6DMBpy5WhasxdkeY/AgJvFmN4QJABMvxCnl9wGGllgx1eBdOHirzEBX8LlkhKjjU1foQoDTMqtEr0wykYAX5aQHtbZhggQDbzRWLru1W5iq6kaQpAcXayOEwVqrbtWtEOQogdM1ZtSJXIvaTVK+HrpbFH2TtTSpcBMRA+YcfFLPcLA1UggTDbkIciYiqBwLUhVkFr7WTEJf+Ics+L8CwqdE/R2BdGDvKVQ0oT7PCAKsZIQZI3wDF1qgCkolhvBxzOm/LjVUqlEXX6DMFp0UEkJv6Q/G0RvYKZSL8gyDi79Fkbcc4FgD7DnIfFBkwwwnpEWHWMXtYdlDIemJR0w0d2tkgM2QYZCfwiSYygwlKvu1W61LorysGsslTFV3RuQkpdlIU6NJPyRWAoM7TJNh6wc0aNuzVLZ6VNOkHaCCCtQurEFJC9O5XFV6nMJmJ9/5ER4mWBxNKV/Y6YXlqYQjGjn5HX4eAQVZCj0FFPUSjZnnvEFFPS8kuOpAUYMJ5dLeQMRT5tfHKGXhjHAOHp8oUhl9SvkquHhjd+szUZP49Z8Pm/4BlEprGBGaGAsTePt5T8QNX3efFzU9Tn7vvjkjBU1fXbAzVas4lSiqhAkR2t6IgElGQpjFZpujq7rzTaTzdW8KPKyEGTCgioi+TnVqlJqERh8fDaE2W3KvelqJZ/Pi95WS5PwlT1gZt+sq4Gjxw1hQL/XRAxBql+jTgmxWo18oxK1IAkfAELxtOZ6zapsoEdiKUOtlfTicomSGwAwFEmi3WveMTwcXaxmjKezxlJvmIneOUB7g2c1DXMFlHt1at0N+3ja0rCKHlwuaFaPeAql3oZbEVXygIUmVifRlAsZA0ZPOJFBctoq4NJvAcgDL3wRSIYA/wzAP0335ygR8HBVGSwCRxsOJblZeQhSLQm/XIbCmPfCXaWqvxJ6QkRD0VTNi6KkwA0UdHRMvlbkXsWMhhyDX2Bx8NQY5qk0B64FDyuqZ1sZgmz38hiOTgzvhxL1D0srUb6OjsbSaPNWHld5B4lygpEkOlWSxhsJMQRZuE6SlTfU1cCzdMWKZrlRJCEa0+bPsZZCWgAg6Q2aJ0Hh5cdDkGKqkX4TxssrC6ynszlDlfFm0jAGmFLn+VrwcPaGIAExEV9r8gbcohSF0RywSudKSaG6tULfunLCibS42Gz8LtC1DIgFxSdqDD8CYlVmNQuZhzXuAZOqZ+IalTJutjSnLmywQMDD0TXLUADqO7xyVPWXDCBXq4+lrNA3qiwWDIghiSODEcwzUYJCQkrwT+esW6DLxSUlqmk2Xw9GYim06vCaVNKlEzd5zmrrYwXynqmRZMb0HDDxGFTFiuY2D4fhsjzeUZ09PY0iquGLxzJbgkIuqGo0BOmVec/KsSp9oRKWG2Cjo6Po6ekp/jcyMjLhNUeOHEEsFqvpOJW8Okbx8YytMhSAONm0KtWkSshEWr8gHVD5XCkJ57XpbchdICTdQBge+NOfA1Rh4THBAGvzsFV5B9wcXXVYWSsMVt6Y2qhGmcCaE4LUK8ZaaxsioNAEWJZzaX4IUl+Dc7/AIJ+HqRWQ8s+WdvJWLtBK3mUntCFSQlROrzwuSZ9KjVo7MUwWBHZ8sxtLmV8FKR6DrtiDUKy2LQ116+loUA0B2b1CTceyWrz8uMBv3GASvjyB3ylYboA9+eSTuPXWW/HAAw/ggQcewJtvlmpD7dq1C4sWLcJbb71V03F4hjbVAPPUcLM2C9EDpj55JS0wo0r4lTwlSjfogIfFWFx/JWQkKbuBTF8OfOZhoHU2cN7ndH+GGtWGIN0cXXUuj1YIsjynLpzMGPJoeTjalJutoFMLzIybn8DS4/pGFoQgy/Pq1JDOmzUG2HgoxUravRyGysKQTknCL2csri9x21NBCd+MTcBkQL6RiKbM1wETj0FVvJ6VBH9H4+a2IZKQIjOAhtZblUhdaoBCFaSB9dzHa4fF7cDyK/zkyZN48MEHce211054Lh6P4/7778dnP/vZmo8jVevoLZOuhJdnbBNnk/DwFUKQhc7zibSxHBW+ggcsnMjAX7ZQBDwcRqLGQpAlN5A1d4j/mUDAw1aVM+VhjeeAScRTWUxRyZuiqNLWOUZbyHg4xkQPWOUFZiCUxJJp/pqOJZSV15vZ0Lf4+Wnxeta6pP2CeO7UfptakEKQViN5J6bKvBjhRAbTWp0XohuJprF0euW5U8kbOxhOYtmMVjOH5kjk3vFoMgOvBUn4bpaubID5efT2R7Cwy1d87MxowpIQZJuHw1jBAzYQTmL9wg7TPltMwpflgBlwknh4BpGyEKRZ9kK11MUA++CDD/DKK69gw4YNuOmmm4rP/d3f/R2+9rWvaXq/tm/fju3btwMABgcHEQwGFV8XCycRjsVxpn8QVD6n+jq9LApQcLP5mj+nFtbMdKODS6mOgc0lcXowgbFIDPFICMGgPg9VNJJCJJZQ/dxMJoOhoaGyY6XwycAwgl36FpBTQxG4kmEEg7WFlpWY4c5h+VRO128zNjZW/LuFSuGi6YLh3zSbySI4GkYL7dY8Z9Jz8r/1cHm3H2w6imCwtpY0VC6NswPDCFDaqtd9AyO4cCpb89xOpdMIBoMYGg3B6zJ+XrXIp5MYGBrGGXcGNLSv59vXzpgwX82AyqZwZnAE2WzW0nXAx2Rx5PQApgvjxt7ASBgLApSt64+EfD6fGw7hvA664rgSkThGIzHV150cHMMKndfwZCadiCEYSmJsLIvhUBTpWATBoLlN7K9a0Ao+G9NcPxa2UvjlO6fxZu+54mOUywVPPo5g0NxNBpNL4tRgDMEgj1NDIbCZNgSD5uRn51JxDIzEEQwGMRKOIREN6z6frkwS54IjCE4ZTycYjKTgY12WzsOODnUD1HIDbMuWLUin07j22mvx4IMPIhwOY9u2bTh48CD279+PH/7wh5oG2J133ok777wTALBixQrVL5PjEgB1Gr6WNvjcvOaX1sOf1Ph+M/ji5dpjmNWVRm9/BHmKwfSudnS0unV9LuNJIU99oniO4qms4vmb1ZXAUCSl67z2hxII+ATMmj5V13iM0tEBGOkkKY25owP41Dzjx/O5OSTBYGpHm+r3Zxim+Jz8bz3cebU5cy3g7wfn8aGjo13zdWcjvbhowUy01rj7lb6niw1qnptqaGsZAev2weMPoMUjaH72/9pszbU6rT2KvAugadrU71bOvKkRJFxUyTEy1BnMmtqOjo6AZcfVC8eyaJvSDppyIZE/hbnTO9HRoe0FSzFxZF39quctlOrD4tlT0RHQt2ZNVjrbMhhMhNDa2ooMRjFzagc6pphbsfu1T1eem5d1dOCy8+eaelw1ZnVl8eHpMXR0dGAs2YPFc6aZlk89bTiPE6GcOK/oTzCtsx0dHb7KbwTQ2RYGxZWuza8dP4lNy2ZYen1rYbkBJhlPAMDzPB555BF8+ctfxle/+lXcfffd+PjjjzE8PIzjx48jGo3C660ul4NnaKSyOcOipJMZKdnRaAhSKwlfTQMs4OFwZCCi6/P39gxg4+Iu3eNxOgJLYzia0nWO7dQ3ErsjVN5phuKZmo0vOWIVpMkyFJyonxQz2GjeTPwCgxNDsZo1BSvR6RfQcy5c8ljIQUn4HC2uF26OFrWjdOWAaRdRBCNJdNTQi3SyIJdriaYytrW8qSdtnvF2RGa38RLzuKrr+exVyEt8/dAA7rlmqWnjM4rld4o77rgDJ0+eBAAcP34cXV1dyGQymD9/Pnbs2IGHH34Y77//Pp5//nn09fVVfRyOoZBM5wxLMkxmpHJfwzpgtLoMRXkbouKx3OyEJqtq7Dk0iCuXNo4B5uFEA0zP4mlnCxkPxxQT49WIpTKmF5ckLDCSJBkKIw13zcYvMBgMJy3vCdvVwmMwUho+cooQK1DaO3Y0ltYl3ilU0AHL5HLgbOy1Wy9KkvCTGUuS8J2G5BjI5/PVtvxVxSNLwk8Y1OeTa4gBQCqTw8nhOBZ0ml/AoxfLZ8MVV1yBTZs2YenSpejp6cHLL78MlmXxzDPPFF9zxx134Oabb8ayZcuqPg7HUEhlcwV13Ma/sIFxGQqjfRG1OsOXtyEqP1YlUpkcTgzHbJ3UZuNmaZwcjmsauXShdY6d1WuCjv57fcGY6ZpZMQuacUvNvq1u9K2FX2AxGE4a7jlqlE7fxF59TqqCHN+wsboNJ76wHiuRy+XhQmO3IJIQmHEDrJr+tZMR0TGQRihuTA9RD6IXq2CApYw5HjwyDTEAeLdvGGvmtdmmAQbUwQC79dZbcd111+HMmTNYtGgROG7i7unhhx+uOvQoQVMuZHNSW57m8IC1Fsp988ibNokGQglFUb+2QsVlJfY7YFKbjZtjMBxNahoCAiOGzMQKUntCR3pCkH1DUdMkG2iXeM1pNSqvFqEQ7orZ2CjXLzAYCCfQ7rY6BMljsKxXX8rk0E0t6BX4laN1/Y/qlLJoBKRQOiCq0TfSuqhGwM1iLJYypaVdOV6eLlYyGk03EvtIjq+Pew4NYKPNkZq6mONtbW1YtmyZovEFAO3t7RCE2kuuXS40VQhSYEXts2p2k2rvGQgnFdtayEUptdjTY/+kNhs9IUgp1yNko+fCw9EVQ5DHg1HMM8kA4wvhFSuuOdGgFT3a9oUgWQxGrPeASdexHCfdpyWJn2wuD8qEgZmtju5k5D1TbVY8qBtMofekUkeVWvHyDGIFL1Yub6zRt1zCAgDeOjaEdfO1C5aspuH8oXGDiXmNgFyDqlbURDoplZYp5ThhUpuNm6WRzuY1d1tSqMFOBXN9IUjzPGCS2rklIUjWCSFIpi4hSAm7NYnUkHQDQ/G0oZCS2tcxoxXWZKG8T2yz4HIpd1SplXLRayP4ZCr6J4aimNoi2O5lbjhLJWmwPcFkR2yyat7n1dI89eRQDF1++ye12bg5GpQLmjdigRVDDXb28PNw2u1fADEEaZYHTAq7JjNZ040UKXnZaJcHM/FxTN3ydsROE2KOpVmeJrOQ8mvNCh02SxsiYHxdyOTyYAx4ayY7tMuFM2Nx07sduFyuqh0O8lZEe3ucUSjWcAaY0Qadk50WgdXlmdLLSDSlqirOVWjivffwAK5c0mnaWJyCh6Ph4RjN/A0pBGln8rQeJfxIMmtadZ28xN7s3BapwbnoXbPnfFKUCz6OqYtHvdPHYyAs5oFFHFQBCRRywNJZ3RIUEiytLHdjdn9AJyN2jMgVPLnO+U2tpsXN4kh/xFGhZnkj79cPDWDjYvvvVQ1ngIlVkM1jgLV5uKo9BEohD624eqVKyNcPDWDjEvt3FWbjZumK51jK9XByCDKcSE9oMVXT8QphVysiZ6LnIGdrCBIQw5D18IB1tYw3S7Yzj1AJyQM2Fksb6h2o1o5oIKxc6NOIsDSFbC6HWNqaPpBOpc3D4fBA2FGhZrcsrWE4msJskwVxq6HxDLBU1nLdHifR6mGr2qEztAuZXOmdM5PNaSY1ammBxVNZDEWcManNxs3RFY0AKWQWTtoZgmQ0Q5B9wRjmdZj3+0jhFSuQeujZGYIExET8uhhg/vFmyXYa8UrwBY3FkVgKrQZ6fko3vHLUpG4amVgqZ0kfSKcS8LDotcgDRrtcSGVyhsP0kpf+zaNBrF/gjDzlhrJUWJpCOGFf2bodtHnYqqrERG2f0vBAMJLSVKcOaEhRvHXMOZPabNw6mni7JQPMRu+Fm9VugHzcxPwvQJSKSKRzllTsSc2+rUjwN4JPYOqyoev08xgshCDDibSjQpCSB2zEoAfMzSmLsQ6GmicHTMLOULodBArzxApRag/HYCSWqjrXe0+PcyI1DWWAcTSFsXi6qZLwqw1BKrUjqqTbEvCoe8D2HBp0zKQ2Gw/HVDTqBZZCPJ21tYWMeMPTMMAGo+g2UYRVYGhEkmlLWi9J3rW4ze1b/HUywLr8QjEHzM5uCkrwhdzPsVgKbV79c1utKCSWbg5FeDmxdBa+JvKAtXlYdLXwluieeXkawUgSQhXrQj4P7O8bwcXz2kwfVzU0lAHGszRCiXTDVeFp0epmq/q+orhi6eKo1oZIQt7jS04+n8f+E86Z1GajNwSZTOcK4SNnVkH2DUXRbWKHArFHZhpuC5LURRmKXPOEIFtkSfhJ54UgUxnRA9aqow2RRCWPbDMRS+WazAPGWpb/5eEYDEVSVW2MXC5gfqcXrMX9XfXijFGYBEdTCMXTTaUDVq0HjFf0gCXRqZGbIfX4KufIQATdHR7HTGqz0R2CzNgbgmRpChkNTZITQ1HMnWKeAeZmKYzEUpbcWIrJyw5Iwq9LFaSfx0BIygFzXhJ+MiPKULQZqIJ0KzQ/jiYzTWWIAKLodTRlXvXxZCDg4SwLM3t5BsPRVFX3PS/HOCpS01B3TJ4thCCbyAPW3enFBTNbDb9PyQDrG4piZkDLABObf5fjpJi6FUxt4bGqgnePZynEU1mksznwNobAM9m8qqCn2RItogcsZWnOpd3l+ytmBTC9DpIJfn68ybCdYWwleEZU6h+NpYq5PXpQSsIX1xi32UN0NAJLYSSWhqeJQpDd7V5cYpEgt5cTQ5DV5D5vXNKFqxyg/yXRWAYY3XwG2IJOH/5i7RzD7+MUFIXfPjqENd3qF02bh8NodKIHbG/PIDY2oP6XRLuPx9c3LtR8jaR4bXeT4aXT/PjoTGjC4yNRYxVsehBYGiPRlKWtguxsRQQAN66ejYWd1lf2ynNl7AxjKyGtFWPxtKE5pCRD8cbhQWxY2GH2EB2NwNIYiTmrsMJq5nV4cdv6eZZ8tpdnMBRNVeWZ/trGBZqFZvWmsQwwtvlCkNVS3tLh7FgcfoHVXCSk5t9yQok04umso/Re7ECq2rObK5d2Yc+hgQmPHzc5/wuQdvbaPTJrRWz03RwbKilnymkhSGmtMNp7T6ko5I2eQVzRwJs1JXiGxki8+UKvVuHlaQxHqgtBOo2GslSkKshmacZdC+Wq9nq8WG1eDqPxUg/Y73uDuGxRcy2oSrhZGrFkBnZ3G7l8USfeODw44fG+oLkVkEAhBBmz9npLZ3Ng6eZo4SIm4iccpwOmVDGth/IQ5FgsjUwu7ygPRD1wc+J14m2SjYTVeDgGQ9EkMcCcBs/SiKbsrZqaLEh5HRKvHxqoGBv3lnWTB4A9hxqz/ZBRBJZCMJKyvby+zcuBcrkwHC31VPYFzdUAA2QhSItuLC64kM+b3+bIqUjtiMKJtMNkKMTr3qjcSHlrrH29g7i8CTdrAiPmgNm9NjQKPp5BkHjAnAdXqMJrhB/GauQ5YMlMFqdG4uiucIMuvxHmcnkcPD2G5bMCVg1z0iCwNAbDSUeEjq5Y0ol9ZV6w40MxdJuogg+MG2BWhSD5Cr1HGw2pHVE4kYHPAfNIgmMoDIQTCBjMISwPQe7pGcCVS5vQAGNpjMQyTaWEbyUeji54wCa/+TL5v4EMjqHA0ZShPIVmRR5W+L/Hh7G2e4puT4NUZffRmRDOm95CzjfEcMtAOOGI0NHGJZ14vSwP7ORwzPQ2UW6WRjiZsSwE6eZoZHMWNJp0KKIafsL2woNyOJpCfyhpSIICKA1B5nJ5fHwmhPNnGK/Ynuy4OZp4wEzExzMYjlhb/FMvGsoA4xkKfANYxfVAnoS/59AgrtRZmuuR7Wr39Axgo4NKeu2EZynHeMDOm96Cw/3hovGSz+eRypgvjyHtQN0WJRfzTOUm6I2E2A9SFGN1UtiVZykMhBKGJCiAQm/SwlrxwekxnD+zFVQTbtYEhkIs3VxCrFbi4ZmGSTVqKGuFY6iG+FHqgdwD9vaxIaztnqLrfQHPeCL+vsODuKIJczqUEAr5h07wgLlcLqyYHcAfT44AkHp8Grt56kG61qwKQQosZasIa72R2hE5yPYCIHrABsJJBIx6wGSdGfTkmDYqfOE6IUn45iCdRxKCdBg8U1mxnCAiJuFncTwYxYyAoNtwbfOwGImmMBRJgqJcaDW4KDcq0rxzSvL0xiVd2NMjhiH7hqIV8/uqQZozloUgWbppJCgAsQqyP5SwXUuuHJ6lkMnlDTXiBkpzwP6ndxAbFjWX/peEm6XBMy4wDdoppN5IodxGcLY01IwQPWAN9ZUsQ0rC32tQxT7g4TAWT+ONw40tvmoUtpB76IQQJABsWNSB3x8ZAgAcD0Yxz2QJCkAegrTKA0bDzTrjfNaDKR4Op0bijvP68bQ4HqMeME9B12wwnITA0GhxgHfYDgQdrcwI+vFyxABzJDwJQepGakX0+qEB3flfgLgIj8RS2NMziCsbuP1QNQgM5YgQJCAmqvp5BufGEqIGmMkirIAYmnK5rPOACSzVVB4winIhmXZGGFuOlFdrNAdMCkGKm7zm3awJLEXCjyYitXRqhHt9QxlgHENBsLEP32SCK2jTjMXThnqztXk4BMNJ9PaHsXSa38IRTj4ElnaMBwwQqyH39gzguAUirICYayYwtIU5YDQ8DbDIGqHdxzsmjC0hyfsYrYKUZET29ugv8mlERA9YQ91qbYWlqYaJdk3+byCDZygIZKehC56hsLdnAOsXGMvLCLhZ7OkZxEVz2hxVqeUEBJZ2VL+3K5d24fVDAzg1EsesNmsaILs56/K0hCbLAQPESkgnGfGA6JljaRcCbmMeMJfLhXQmj2PBKBZ1+SwanfNxs9ZtUpoVL9cYYV3LDbChoSHMmTMHF1xwAS644ALcfPPNAIBcLoevfOUrWLRoEc4//3zs2bOn5mOJHrCGsiktg2coHAtGDavYBzwc/qd3kKjfKyCwzglBAsD8Di8+GYkjm8tblgAsMJSFIcgmNMBaeEeJsEpwNIWA1/jcHoomsWpuoKk3a3yTVfPWAy/PNEQI0vIr/cSJE1i9ejVefPHFksdfeOEFjIyMoKenB729vbjuuutw5MiRmo5FcsD0w9FiuGzV3DZD7wt4WDAUhUsXNmdFkxYCSzsqfORyubC2ewpODEUtO4bA0pbpGwks1XQhyE4fD4+DvKgSbk7MKTT+Prpp5SckSAjSfLwc0xDpRpZf6SdPnsT06dOxa9cuuN1uXHbZZQCATZs24ZprrgFFUZg+fTp4vvYGre1eHnPbzVX7blTavCw+t2KGYc/ItBYBf7ZyJlF1VmDptBa0GGzXYjXXLZ+O/X0jln3+spmtluViTG8VGiLMYIRFU/2O7CxxyXz9nTLkrJ47BevmN/dmrdPHY26bYPcwGoplM1oawjvuykt9ZSxi586dePTRR3HppZdi9+7dWLt2LX7605+WvGbbtm04//zz8a1vfWvC+7dv347t27cDAM6ePYv333/fyuESGoyxsTG0tjZf+xOCeZA5RKgVMoeal44O9Q2I5QaYnFgshpkzZ+KTTz6BzycmZT700EM4fPgwnn766YrvX7FiBQ4cOGDxKAmNRDAY1LwACIRKkDlEqBUyhwhKWB5H2rdvHwRBwJo1a8BxHHieRzYrqiP//Oc/x7vvvov/+q//snoYBAKBQCAQCI7B8sxAnudxyy234NFHH8UNN9yAa6+9Fq2trXj55Zfxne98B+vWrcMTTzyBn/70pwiHw1YPh0AgEAgEAsF2LPeArV27Fr/97W+xe/dubNu2Dddddx0AYObMmXj88cdLXktRpFKEQCAQCARC41OXUrbFixdj8eLFJY9ddNFFuOiii+pxeAKBQCAQCARHQVxOBAKBQCAQCHWGGGAEAoFAIBAIdaauMhS14vP5sHTpUlvHYLeei93Hn2xjGBwcRGenNW2TJtN5aOQxWH18PXPI7nNAxuDsMVi5Duk5vh2QMYjE43F89NFHyk/mJxGrVq2yewj5O+64o6mPP9nGYOWcmUznoZHHYPXx9cwhu88BGYOzx1Dve5cTz0GzjkHrtychSINs2bKlqY9PxkDG4LQx2H18MgYyBqeNwe7jkzHoY1KFIC+++GLs37/f7mEQJhFkzhBqhcwhQq2QOdS8aP32k8oDduedd9o9BMIkg8wZQq2QOUSoFTKHmhet335SecAIBAKBQCAQGoFJ5QEjEAgEAoFAaASIAUYgEAgEAoFQZ4gBRiAQCARCjeTzeUQiEbuHQZhEONIAy2azmD59ut3DIExC7rjjDrz00kuqzx89ehRXXnllHUdEcDq5XA7d3d2499577R4KYZLy2GOPYc6cOdiwYQNWrVqFw4cP2z0kwiTAkQaYnKGhIQwNDRX/LU3sc+fOIRwOo6+vD729vXYNj+BQcrlcybw4d+4cQqGQjSMiOJU9e/bg6quvxs6dO5HL5YqP9/T0FP8uX4eOHTuGM2fOIBwO49y5c3UdL8FZnD17Fj/+8Y/R29uLAwcO4Hvf+x7+9V//tfj82NgY3nvvPUSj0eJjvb29yOfz+PDDDxEOh+0YNsEBON4Ae+qpp/Dss88W/33NNdcAAH7yk5/gr/7qr3Dvvfdi8+bNeOKJJ+waIsGBxONxXH/99cV//+QnP8Hu3bttHBHBqTzzzDPYunUrVq5ciddee634+KZNm4p/P/vss8V16Lvf/S5uu+023Hfffdi6dSv+8R//se5jJjiH1tZW5PN5HDlyBADwhS98AY8++igAYNeuXVi9ejX++Z//GStXrsShQ4cAAFdddRVuuukmPPbYY1izZg3RCGtSHG+AabF48WK88MIL+NWvfoXnnnvO7uEQCIRJRiwWwxtvvIGrr74af/7nf45/+7d/03z9qVOn8Pzzz+ONN97A008/jYULF9ZppASn4vF48O///u/4+te/josvvhhPPPEEEokEAOCee+7Ba6+9hmeeeQYPPfRQ0VgfHR3FPffcg+3bt+PHP/4xHnzwQTu/AsEmHGOABYNB9Pf3G3rP8uXLAQALFiwgbtwmJZ/Pqzc6JRAq8Otf/xoulwv33HMPXnnlFezYsUMzkfrYsWNYtWoVKEpcOtesWVOvoRIczGWXXYZ9+/Zhx44dOHDgAP76r/8a+XweR48exe23345Pf/rTJYYZy7JYuXIlAGD9+vUl4W5C8+AYA+w3v/kNHnjgAQDiLrOlpQUA4Ha7cebMmeLj8ji6y+Wq/0AJjiKfz2PDhg3FeSHNHY7jEAwGkclkAIAscARFnnnmGdx33334/Oc/j61bt2LLli148cUXi8+PjIwAGJ8/8+bNw7vvvlvMFXvrrbfqP2iCo3jvvffwox/9CAAwe/Zs/M3f/A3+8Ic/wOVyoaurC08//TR2796NnTt34sknnwQApNPpYjjywIEDmDVrlm3jJ9gHY/cAJDZv3owf/OAHuPvuu/H222/ji1/8IgAxD2Pjxo3I5XIYGhqCz+ezeaQEJ0FRFL7whS/ghhtuwIIFC3Dy5EmsXbsWLMti9erV2Lp1K6ZOnYrh4WG7h0pwGP39/Th06BC2bdtW3MzxPI/7778ft912GzZv3owbbrgBy5YtQ29vL5YsWYI5c+bg1ltvxbp169DS0gKapvGpT33K5m9CsJMFCxbg1ltvxaFDhzBjxgzs2LEDd911FwDg+9//Pq6//nrccMMN2LlzJ+666y7ceOONcLvd+Pu//3usWbOmGJ4kNB+OakUUDAaxd+9ezJo1C5dccknx8RMnTuDjjz/G+vXrcfDgQWzYsAE9PT1obW3FtGnTkM1m8fbbb+PSSy+1cfQEu8jn89izZw9CoRA2bdpUNNJTqRRef/11zJ07FwzDoKWlBX6/Hx999BFWr15t86gJdjMwMIAzZ85gxYoVJY+/+uqr2LRpE3K5HF5//XVMmTIFnZ2dyOVymDt3LtLpNIaHhyEIAv7zP/8Tx44dwz/8wz/Y8yUIjiCZTGLXrl0YGxvD6tWrsWTJkuJzH374IQ4ePIjVq1cXcwZnz56NgwcP4tVXX8V5552H8847z66hE2zEUQYYgUAgOJ3Nmzdj5cqVmDZtGv7lX/4FTz31FNatW2f3sAiTiNmzZ+OTTz6xexgEmyEGGIFAIBggFoth3759OHXqFK644gosWrTI7iERJhm/+93vcO2119o9DILNEAOMQCAQCAQCoc44pgqSQCAQCAQCoVmw1QDr7+/H5s2bsWjRImzatAmnT58GILaR+fa3v43ly5dj/fr1JTpPjzzyCBYvXowlS5bgP/7jP4qPHzhwAOvWrcPChQvxjW98o+7fhUAgEAgEAkEvthpgf/u3f4trrrkGvb292Lp1K77//e8DAJ577jkMDAzggw8+wM9+9jPccsstAEQj6/nnn8f777+Pt956C3fffTcikQiy2Sxuv/12PPfcczh06BDGxsZKWooQCAQCgUAgOAlbdcC+/e1vY+bMmQCA+fPn45133gEA/OpXv8L3vvc9AMCKFSvQ2tqKw4cPo7u7Gzt37oTb7Ybb7UYgEAAAvPnmm1izZg2y2Sz++7//G48//jhaW1tt+U4EAoFAIBAIlbDVA7ZgwQIIgoBYLIb7778fX/3qVwGIauZz584tvm7OnDk4deoUWltbiwbbP/3TP2HDhg3w+Xzo6+vD/v378c1vfhM7d+7ExRdfjLNnz9rynQgEAoFAIBAqYXsSfiaTwc0334xt27YV+6r5fD7EYrHia2KxWIkC/osvvohf//rXeOyxxwCILYkymQxeeeUVPPnkk7jxxhvxi1/8or5fhEAgEAgEAkEnthpg+Xwet99+O9avX48777yz+Pjy5cvx5ptvAhAT8t9///2i1s5rr72GRx55BL/5zW8gCAIAYOnSpSUGmiAISKVSdfwmBAKBQCAQCPqxVQfsvvvuw44dO4pVi36/H1/60pfQ29uLz33uc/jGN76Bffv2YdasWfjRj36Ejz76COvXr8ddd92FqVOnAgC2bNmCOXPm4DOf+QxmzZqFuXPn4pe//CVeffVVLFiwwK6vRiAQCAQCgaCKrQbYyy+/jP7+/uK/fT4fbrrpJgDA8ePH8corr2D27NnYsmULAODo0aPYu3dvyWdcc801mDVrFtLpNF544QWEQiFcf/31pLs8gUAgEAgEx0KU8AkEAoFAIBDqjO1J+AQCgUAgEAjNBjHACAQCgUAgEOoMMcAIBAKBQCAQ6gwxwAgEAoFAIBDqDDHACAQCgUAgEOoMMcAIBAKBQCAQ6gwxwAgEAoFAIBDqDDHACAQCgUAgEOrM/wcWdPYcpbsE6gAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 720x230.4 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 720x230.4 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "count    120.00\n",
       "mean       5.55\n",
       "std        0.57\n",
       "min        3.85\n",
       "25%        5.20\n",
       "50%        5.55\n",
       "75%        5.97\n",
       "max        6.80\n",
       "Name: hours, dtype: float64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rhr = (df[df[\"type\"] == \"HKQuantityTypeIdentifierRestingHeartRate\"]\n",
    "       .groupby(\"day\")[\"num\"].mean())\n",
    "ax = rhr.plot(lw=0.8, label=\"daily\", title=\"Resting heart rate (synthetic)\")\n",
    "rhr.rolling(7).mean().plot(ax=ax, lw=2, label=\"7-day mean\")\n",
    "ax.set_ylabel(\"bpm\"); ax.set_xlabel(\"\"); ax.legend()\n",
    "plt.show()\n",
    "\n",
    "sleep = df[(df[\"type\"] == \"HKCategoryTypeIdentifierSleepAnalysis\")\n",
    "           & df[\"value\"].str.startswith(\"HKCategoryValueSleepAnalysisAsleep\")].copy()\n",
    "sleep[\"hours\"] = (sleep[\"end\"] - sleep[\"start\"]).dt.total_seconds() / 3600\n",
    "sleep[\"night\"] = (pd.to_datetime(sleep[\"startDate\"].str[:19]) + pd.Timedelta(hours=12)).dt.normalize()\n",
    "per_night = sleep.groupby(\"night\")[\"hours\"].sum()\n",
    "ax = per_night.plot(kind=\"bar\", width=0.9, title=\"Hours asleep per night (synthetic)\")\n",
    "ax.set_xticks(range(0, len(per_night), 14))\n",
    "ax.set_xticklabels([d.strftime(\"%b %d\") for d in per_night.index[::14]], rotation=0)\n",
    "ax.set_ylabel(\"hours\"); ax.set_xlabel(\"\")\n",
    "plt.show()\n",
    "per_night.describe().round(2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ca9ce897",
   "metadata": {},
   "source": [
    "## Workouts\n",
    "\n",
    "`Workout` elements carry the activity type and a duration with its unit."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "efcae7f5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>sum</th>\n",
       "      <th>mean</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>activity</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Cycling</th>\n",
       "      <td>17</td>\n",
       "      <td>763.9</td>\n",
       "      <td>44.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Running</th>\n",
       "      <td>35</td>\n",
       "      <td>1729.7</td>\n",
       "      <td>49.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TraditionalStrengthTraining</th>\n",
       "      <td>17</td>\n",
       "      <td>761.7</td>\n",
       "      <td>44.8</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                             count     sum  mean\n",
       "activity                                        \n",
       "Cycling                         17   763.9  44.9\n",
       "Running                         35  1729.7  49.4\n",
       "TraditionalStrengthTraining     17   761.7  44.8"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wo[\"minutes\"] = pd.to_numeric(wo[\"duration\"], errors=\"coerce\").where(wo[\"durationUnit\"] == \"min\")\n",
    "wo[\"activity\"] = wo[\"workoutActivityType\"].str.replace(\"HKWorkoutActivityType\", \"\", regex=False)\n",
    "wo.groupby(\"activity\")[\"minutes\"].agg([\"count\", \"sum\", \"mean\"]).round(1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "342e8730",
   "metadata": {},
   "source": [
    "## Save one type as CSV\n",
    "\n",
    "```python\n",
    "df[df[\"type\"] == \"HKQuantityTypeIdentifierHeartRate\"][RECORD_COLS].to_csv(\"heart_rate.csv\", index=False)\n",
    "```\n",
    "\n",
    "The browser version of this notebook, with no Python at all, is the [Apple Health export explorer](https://aifitnessapi.com/tools/apple-health-explorer)."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
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   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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