preprocess-redlining.ipynb

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     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2024-12-02 22:03:04.459 No runtime found, using MemoryCacheStorageManager\n"
     ]
    }
   ],
   "source": [
    "import ibis\n",
    "from ibis import _\n",
    "import streamlit as st\n",
    "\n",
    "con = ibis.duckdb.connect(\"duck.db\", extensions=['httpfs', 'spatial', 'h3'])\n",
    "\n",
    "# Local cloud\n",
    "minio_key = st.secrets[\"MINIO_KEY\"]\n",
    "minio_secret = st.secrets[\"MINIO_SECRET\"]\n",
    "query=   f'''\n",
    "CREATE OR REPLACE SECRET secret2 (\n",
    "    TYPE S3,\n",
    "    KEY_ID '{minio_key}',\n",
    "    SECRET '{minio_secret}',\n",
    "    ENDPOINT 'minio.carlboettiger.info',\n",
    "    URL_STYLE 'path',\n",
    "    SCOPE 's3://cboettig/gbif'\n",
    ");\n",
    "'''\n",
    "con.raw_sql(query)\n",
    "\n",
    "## Limits are sometimes good \n",
    "#con.raw_sql(\"SET memory_limit = '20GB';\")\n",
    "#con.raw_sql(\"set threads=40;\")\n",
    "\n",
    "gbif = con.read_parquet(\"s3://cboettig/gbif/2024-10-01/**\")\n",
    "\n",
    "# can/should we add explicit spatial index to gbif first?  using RTree takes too much memory"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2e1f1ee1-8048-4f2b-83a0-ca8cc8fc9067",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Copy to local cloud as parquet\n",
    "\n",
    "(con\n",
    " .read_geo(\"/vsicurl/https://data.source.coop/cboettig/us-boundaries/mappinginequality.json\")\n",
    " .to_parquet(\"s3://cboettig/gbif/mappinginequality.parquet\")\n",
    ")\n",
    "\n",
    "# can/should we add explicit spatial index to mappinginequality polygons first? \n",
    "# would local duckdb table version be even better/faster? \n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3891abb6-3652-4217-8615-106d354ff131",
   "metadata": {},
   "source": [
    "We iterate through the city list to do this efficiently.  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "32a2b4c1-e08b-4fbb-b891-ac19053a4585",
   "metadata": {},
   "outputs": [],
   "source": [
    "## select cities from the list we haven't yet written (allows resume).\n",
    "import minio\n",
    "import re\n",
    "\n",
    "minio_key = st.secrets[\"MINIO_KEY\"]\n",
    "minio_secret = st.secrets[\"MINIO_SECRET\"]\n",
    "mc = minio.Minio(\"minio.carlboettiger.info\", minio_key, minio_secret)\n",
    "obj = mc.list_objects(\"cboettig\", \"gbif/redlined/\", recursive=True)\n",
    "\n",
    "pattern = r\"gbif/redlined/|\\.parquet$\"\n",
    "finished_cities = [re.sub(pattern, \"\",  i.object_name) for i in obj if not i.is_dir]\n",
    "\n",
    "mappinginequality = con.read_parquet(\"s3://cboettig/gbif/mappinginequality.parquet\")\n",
    "all_cities = (mappinginequality.select(_.city, _.state)\n",
    "              .distinct()\n",
    "              .mutate(index = \"state=\" + _.state + \"/\" + \"city=\" + _.city)\n",
    "              .execute()[\"index\"]\n",
    "             )\n",
    "\n",
    "remaining_cities = set(all_cities) - set(finished_cities)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "58e4a062-8f7e-45d2-a41f-fdc49b1c9f03",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'state=SC/city=Sumter'}"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(remaining_cities)\n",
    "remaining_cities"
   ]
  },
  {
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   "execution_count": 26,
   "id": "c3a4005c-1e8c-4f2a-a93c-1c158c9c26ab",
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     "text": [
      "state=SC/city=Sumter\n"
     ]
    },
    {
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     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 15min 54s, sys: 4min 38s, total: 20min 33s\n",
      "Wall time: 48.8 s\n"
     ]
    }
   ],
   "source": [
    "%%time \n",
    "\n",
    "## And here we go, long-running loop over each city\n",
    "for i in remaining_cities:\n",
    "    gdf = (mappinginequality\n",
    "           .mutate(index = \"state=\" + _.state + \"/\" + \"city=\" + _.city)\n",
    "           .filter(_.index == i)\n",
    "           .mutate(area = _.geom.area())\n",
    "    )\n",
    "\n",
    "    print(i)\n",
    "    \n",
    "    bounds =  gdf.execute().total_bounds\n",
    "    points = (gbif\n",
    "           .filter(_.decimallongitude >= bounds[0], \n",
    "                   _.decimallongitude < bounds[2], \n",
    "                   _.decimallatitude >= bounds[1], \n",
    "                   _.decimallatitude < bounds[3])\n",
    "             )\n",
    "                  \n",
    "    (gdf\n",
    "     .join(points, gdf.geom.intersects(points.geom))\n",
    "     .to_parquet(f\"s3://cboettig/gbif/redlined/{i}.parquet\")\n",
    "    )\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7e0ed68d-e6ba-44c8-b7a0-1f284b11cb96",
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   "execution_count": 89,
   "id": "976eb48e-eaf1-45db-9034-84ac33eeb506",
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   ],
   "source": [
    "# standardize grades and consolidate to single parquet?\n",
    "\n",
    "(con.read_parquet(\"s3://cboettig/gbif/redlined/**\")\n",
    "  .mutate(grade=_.grade.strip())\n",
    "  .mutate(grade=_.grade.cases((('A', 'A'), ('B', 'B'), ('C', 'C'), ('D', 'D')), default = \"None\" )  )\n",
    "  .to_parquet(\"s3://cboettig/gbif/redlined_cities_gbif.parquet\")\n",
    ")\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "id": "5ce74a60-c30b-4a78-9653-b34e788227b3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 2.59 s, sys: 22.9 s, total: 25.5 s\n",
      "Wall time: 700 ms\n"
     ]
    },
    {
     "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>grade</th>\n",
       "      <th>n</th>\n",
       "      <th>area</th>\n",
       "      <th>density</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>A</td>\n",
       "      <td>3048483</td>\n",
       "      <td>1008.034173</td>\n",
       "      <td>3024.186167</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>B</td>\n",
       "      <td>5506468</td>\n",
       "      <td>2517.018555</td>\n",
       "      <td>2187.694639</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>D</td>\n",
       "      <td>3491760</td>\n",
       "      <td>1896.670719</td>\n",
       "      <td>1840.994309</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>C</td>\n",
       "      <td>6353620</td>\n",
       "      <td>3539.963360</td>\n",
       "      <td>1794.826487</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>None</td>\n",
       "      <td>6021724</td>\n",
       "      <td>16665.329460</td>\n",
       "      <td>361.332431</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  grade        n          area      density\n",
       "0     A  3048483   1008.034173  3024.186167\n",
       "1     B  5506468   2517.018555  2187.694639\n",
       "2     D  3491760   1896.670719  1840.994309\n",
       "3     C  6353620   3539.963360  1794.826487\n",
       "4  None  6021724  16665.329460   361.332431"
      ]
     },
     "execution_count": 96,
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    }
   ],
   "source": [
    "%%time\n",
    "# con.read_parquet(\"s3://cboettig/gbif/redlined/**\")\n",
    "## Testing\n",
    "\n",
    "(con\n",
    "  .read_parquet(\"s3://cboettig/gbif/redlined_cities_gbif.parquet\")\n",
    "#  .filter(_.city == \"Los Angeles\")\n",
    "  .filter(_[\"class\"] == \"Aves\")\n",
    "  .group_by(_.grade)\n",
    "  .agg(n = _.count(),\n",
    "       area = _.area.sum())\n",
    "  .mutate(density = _.n /_.area)\n",
    "  .order_by(_.density.desc())\n",
    "  .execute()\n",
    ")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "9f3b24a1-e14c-4d09-b6be-f04b269b67f3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 57.9 ms, sys: 20.2 ms, total: 78.1 ms\n",
      "Wall time: 126 ms\n"
     ]
    }
   ],
   "source": [
    "%%time \n",
    "\n",
    "## mean & sd within grade\n",
    "\n",
    "df = (con\n",
    " .read_parquet(\"s3://cboettig/gbif/redlined_cities_gbif.parquet\")\n",
    " .filter(_[\"class\"] == \"Aves\")\n",
    "# .filter(_.city == \"Los Angeles\")\n",
    " .group_by(_.city, _.grade)\n",
    " .agg(n = _.count(), area = _.area.sum())\n",
    " .mutate(density = _.n /_.area)\n",
    "# .group_by(_.grade)\n",
    "# .agg(mean = _.density.mean(),sd = _.density.std())\n",
    "# .order_by(_.mean.desc())\n",
    "# .execute()\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "72ccbf88-62ed-4633-8510-7cb38a60c6da",
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   "outputs": [
    {
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97XQru09l9+8Bay2vfvWrAfjiF794p1D7WT7/+c/f+fi1r33t/RyaiIiIiIiIyM4wxuDVEfolRYGre+R1r3sdACklHnvssY3f+/GPf/zOx4888sh9HZeIiIiIiIjIroipsB4Sw5gpG+pHy+5Q4Ooe+cZv/MY7H3/kIx858/uGYeCP/uiPAHjwwQd5/etff9/HJiIiInIvDTFztBq5vRxZ9pFc1LhFRETur1orJ+vI7eXArZOBW8uB2ycDUd0Ed54CV/fI2972NryfSoY9+uijjOP4vN/3oQ99iOPjYwC+5Vu+5a66EIqIiIhsi1WfOF6NHC9Hjk4GjpYjR8uRpK7DIiJyH/VjZj1ElusETJlXJ+vIyToq82rHKXB1jzz88MO8853vBOCzn/0sP/3TP039S5PnU5/6FD/7sz8LQAiB97znPS/6OEVERES+UqVU+jGxXEe8s8y6QCmV9ZDpR514i4jI/RNToR8z887TNf60m6Ah5UJKOjzZZeoqCHzyk5/kt3/7t7/sc8/4tV/7NT760Y9+ydd/5Ed+5Mte533vex8f+chH+NznPscv//Iv89hjj/H2t7+d/f19PvnJT/Loo4+yXC4B+OEf/mFe+cpX3od/jYiIiMj9kXIh5YJ3liY4ALrGs1yPZGVciYjIfVRP/+e5d5asMZQKSrjabab+5bSgl6Df+I3f4P3vf/8L+jNnFWD/9Kc/zQ/8wA/w+OOPP+/XrbW8973vfd7A12Vw48ZSC1MREZGXqJgyt5cjqz6xP2+AKZjVD4mDvZbDRXPBIxQRkV216iO3lyMpV7rGkUtlHBN784bDvQZndaFsGzhnuXZtcU9fUxlX99gjjzzChz70IR599FF+67d+i8cff5zVasWDDz7IN3zDN/Dud7+bN7/5zRc9TBGRl7xSKjEVKpXgrRY7InfBO0vwDmczJ+uIs4aYCvPO0XjNIRERuX+6xk8dBcfEMCaMMcxngVnrtY7bccq4khdEGVcisguGMbPsIzEXqBC8ZdZ6Zq3Oc0TOk3JhuY6sx0TOlS442taz6LyazoiIyH1VSmWImZgL1hga/+zVddkOyrgSERH5/yjlwrKPp9kiFmNgWI3UWk+zSXRiJ7KJNQZrzZ06I5WKd0ZBKxERue+sNdNh40UPRF5UClyJiMhLSkyFIeapI9pphlVvYIiFMWUFrkTOcdJHluvIGAvGQBoymIgxhlan3iIiInKPaXUuIiIvKfW084x9TnaIs4ZaqzrSiJwj5cIYM/2Q8d7incUYw7qPDDFf9PBERERkBynjSkREXlK8MzTBslwnrDUYA/2Y6RqHd7rqJLJJKZVhzPRjIqZCqRXnDCllFnN1FBQREZF7T4ErERF5SWmCow2OWivDmKhA2zi6xuuak8g5jIEYC8fryLwLNN5wvBzxzpCSmreIiIjIvafAlYiIvOTszQLBW9pm2mgHZ2kbp+LSInfDMgV5a2GMhhAspk5XbkVERETuNQWuRETkJccYQ9d4Ot1sEnlBaoV560jJ4b2jnnYWzGXqyikiIiJyrylwJSIiIiJ3xXtL8I4meLwzOGsZU6FtDF4dOUVEROQ+UOBKRERERO6KNYZ5G6gF+phJudB4S9d6Zo2WlSIiInLvaYUhIiIiInetbRzOGdqYqae1rdrGYVUjTkRERO4DBa5ERERE5AXxzqqmlYiIiLwotOIQEREREREREZGtpMCViIiIiIiIiIhsJQWuRERERERERERkKylwJSIiIiIiIiIiW0mBKxERERERERER2UoKXImIiIiIiIiIyFZS4EpERERERERERLaSAlciIiIi8oKVWimlXvQwREREZMf5ix6AiHxlaq2MsZBKwQBNcHinWLSIiNxfpVbWQ2IYM1Rw3tI1jja4ix6aiIiI7CAFrkQuoVorx+vIMCZiKoChC45Z55m1mtYiInL/LNeRVZ/oxwQYrIWUPGbe0Ch4JSIiIveYdrgil1A/Zvoh0Y+ZNjhKrZysRzDQBIuzyrwS2eSZjMUxZQCCt7TBYYy54JGJbLeUC2PM9GNmb9ZgrWEYp983IStwJSIiIvecAlcil1A83TjMWn/nemApEFMhpoJrFLgS2WTZJ9ZDYoyZWitNcHStZ38WFLwS2aCUSi4V7yzWTnMlBMu4SmTVuxIREZH7QIErkR1j0KZbZJOYMv2YWPWJWesAQz8mjIHWO9pGGSMiZ7HW4KxhnTOlVKw1xFhwzwlkichmz2Qt5lJx1tCqRpzIC5JLIaWKMVPWvA4dd58CVyKXUHCWJjjWQ6IJ7vQEvDBrA8Er20pkk5ima4JtcAQ/bRRqdYyxEHOhRZsHkbP40+dPmwvLPgJggHnn6bTxFjnXMGZO1iPrId0JXHXJU2eBrtHWTOQ8qz7SD5lYCtYYGm9ZzIKaVO04vTuKXEJd40jZY4whpowxhr0uMO+8TrxFzmHM9KvUZ6811frs50Vks8XpldrRT1dtvbN0jVd9K5Fz1FrvZPwG75h3lpjK9HunWosi5xnGfKfcg7OWUqfyKQAHi0bzZ4cpcCVyCRlj2JsFrDH0ZurotOiCNg0idyF4S+vddOJ9+rmUC4vO0yhjUeRc9vQZVDpPrRVrjDYLInehVsi5Uip3rqU3wTHETMrltH6c5pLIWYaUGcZE1zybNX+yjoyndX61F9pdClyJXEK1VpanrchjmtJka40sQDUSRM7hnWU+82CmhgaVyl4IdK2/swgSkfNZpSmKvCDGgLFgqHeuCZbTpgbGGGXNi5yjVigV7HM6qFtjKLVS1R9kpylwJXIJDTGzHqZU8yZYUq6MMU4FClUgV+RcXeMJfrqiUeuUhaXaCCIicj8ZY2iDY2w9y3XEO0PKla5xNMFNwWAROZN3huAtw5hoG/9snV8bcMpW3GkKXIlcQmMqDOPUEe2ZDJFV/2yarLqiiZzPWYtrFKwSEZEXz6z1lArBWnItzBpL0zjmnbZlIufpGscYHf2YWfURa6Y51bVOB5A7Tu+QIpdUhS+pKWKMgQoV5cmKiIiIbKNn6pTmduoKbYzRhlvkLjlrOVg0NCGTcsUATbDqyPkSoJ+wyCUUnKXx02lDG6buaCkXuqBWsCIiIiLbzlmLlmwiL5yzlkWnyfNSo8CVyCXUNo4ueTCJmDLGwLzzdK1X4EpERERERER2hgJXIpeQNYb9eaDxlpQLxhgab9UCVkRERERERHaKAlcil5Q1hlmrKSzylSq1klKhMnUVVDcnEREREZHto12viIi85Iwxs+wjKRdqBe/sdN1WxT1FRERERLaKVugiIvKSkkvhZB1ZriPGGgzQjxlOA1iqEyciIiIisj0UuBIRkZeUMRbGlLF2yrIC6MdEHzNdzApciYiIiIhsEa3ORUTkJaVWKAWcfbamlbOGWiulXuDARERERETkyyjjSuSSqrUyxEzKFWOg8Y7gFYsWOY9zhuAt6yHh3HRVcIiFJli8U4F2EREREZFtosCVyCVUauVkFenHREwFY6ANjnkX1GlQ5ByNt7SNo9RKPyQq0ARL13ia4C56eCIiIiIi8hza4YpcQsOYWY+JYcx0jSOXOhWaNoYmWJxV5pXIWYwx7M0CwVnGpgAQnKFrPNYo40pEREREZJsocCVyCcVc6IeEMdAPCYwhlcoYMzEVXKPAlcgm1hhmrWfWXvRIRERERERkEwWuRC6hUgrLPlLrVOvKWEMtFWMMV1HGiIiIiIiIiOwGpWWIXEK1QKmw6hPOOaiw7DOlTPWuREREREREdlHKhf60bEqpagn9UqCMK5FLyFpDsJawaKgVvLPszwPBW715i4iIiIjIzqm1suwTw5iIuWDN1Cl6b9aou/qOU+BK5BKy1rA3D5QKzhqMgSFmusZjlHIlIiIiIiI7ZoiZ9RBZ9ZngLakWxpgxxnC4aLQP2mEKS4pcQm1wtI2jlkKtlZQrwVkab3XaICIiIiIiO2eMhX7Mpw12PIsuUDHENDWokt2ljCuRS6gJjkUXsMaQcsEYQ+Mt89PPiYiIiIiI7JIK1Ar2OdsdawylTp+X3aXAlcglNWs9bXCn97unOldKjxURERHZbqVWxjGTSsVbQ9M4HTyK3IXgpppWfcy0QCmVXAozF/Bec2iXKXAlcolZa2itu+hhiIiIiMhdyKXw1K2ek/XIGAshTIWlHzjs8E7lHkQ26RpPTIXVkOjHhDWGeefpGo+zmj+7TIErERERERGRF8GNo4GnjtYs1wlvDSd9pR8z1sBDV+cXPTyRrWatYX/eELwjlYJhKqHSBh3k7zoFrkRERETkrtU6bbTHNDUIcdYwa72yRUTOkUvhpI8cryLX9ztCsKRUePr2mpPWc+0g45024CKbWDtlWclLi37iIiIiInLXVkNi1Uf6IVNqJXhLTIWDRaPglcgGtUDJFVO5U4/HewvGUEsll4pX3EpE5MtodSEiIiIidyWXwjBm1kOmaz178wYw9GOiH/NFD09kqzlnCN5grWG5TqRUOFlFrDGEYAmKWomIPC9lXImIiIjIXcm5knLBWXMnu6oNjuV6JOVywaMT2W7GGK7ud4yxcLQcWQ9Tbasr+w2Hi1adBUVEzqDAlYiIiIjcFWOmbJFcKrVWjDHkUjDWaNMtchf2ZgGuLZh3npgLwVn25830eREReV4KXIlcYrVO9RCMQS1gRV6AUiurPrHqEwCzxrKYNVirjbfIJsFbGu8YXeZkHacgVi4sZoEm6Dkkch5jDPvzwGLmKaViFfQVETmXAlcil9QQM/2QiLlgmWojzDuvAJbIOWqtPH2754u3VpwsR2qF/XnggSszHro61wZC5ByL2bR8HFOeugq2nq6ZfonI3bHGYJ2eNyIid0MrDJFLKKbCyWrk1skzNUUq8zZQKhzMA0Ybb5EzrYfEF55e8sVbS4LzYOCLN1fEXJi3noNFe9FDFNlqzloOFg0plylwZa2yFUVEROS+UeBK5BJaj4mnjwZiyneyQ26dDADMGkcT1JVG5CzHq8it5UhJENpp/sQRjk5GjpZRgSuRu/RMcXYRERGR+0mBK5FLqB8SqyFijGHROnKpjH1mNSRizgpciWyQcmE9RMZYGGOBOl15GlMhF3VFExGR+2uMmX7M5FJx1tA2jlZrNxGRMylwJXIJlQqlVNpgcW7q8FQxlFLRvltks+At1hhO+ohxYA0crSNXFy1e9UZEROQ+GsbMyXpkPaQ7gasueeosqE6ciMgZ9O4ocgk1wdIESy6Vk3XEYKZOT42j8TqxE9mkazz780A/Jpw11AIHXcP+PDDTpkFERO6TWiv9OHW0Dd4x7ywxlen3ztIGpzqlIueotTLGQioFg6EJVlfXXwK0Qhe5hOat5/pBx5M3e6iQKTTecbhoCF5v3CKbeGd54HBO2zhinFIUg7fszQKNAlciInKf1Ao5V0qFtpkOGpvgGGIm5UIuVZm/IhuUWjlZRYaYiKlgjKH1jsUs3JlTspu0Qhe5hBpvMcYw6zyrdcTaaQHUeqfOTiLnCN5yZa/BAGZuwFRqrRwsWhoFfkXuSq2VlAulgncGZzV3RM5jDBgLhmn+GAOUZ75mtIYTOccwZtZDYoiZNkx1fk/6CAZCsHeaVsnuUeBK5BKKqWKNwRrYXzTUOi14UimUWvWmLbJB8JZZ64kps+wztVTmnacN6sgpcjdSLiz7REyZUireWbrGMe/CRQ9NZKsZY2i8pQJ/8fRyqlFaYW8e7tRfFJGzxVQYY2bW+jvXA1d9JOVCTEVNDnaYAlcil9CYMjEV9ucN4bSm1aqPjKkQY1GqrMg56nM+Nmb6hDGGWqvqi4icY9knluuRlKfC0s90R7PWqLi0yLlOnzG1kvPUIIRa0aNHRORsWl2IXEKV6Y73czfYxhioUL9kSy4if1lMhX5IjKmy6AKYZ1PPg7c6rRPZIKZCTJmUK3uzgDFmmlNjog2OrrnoEYpsr1orY8oY4KFrC+zpgUk/JsZYKJ2y5kU2Cd7SBMd6SDTBUUoll8rcW9X53XEKXIlcQsFZGu/ox0zXQC5TrYQuBHXVEDlHTIUxlSlIdZqdaIB4msmowJXI2WqtlDJlWj1zeDJ155xqxYnI2WqFWqBivuRZM8R8Z25ZFWcXOVPbOJro6GPi6GTAWsOiC8zboKDvjtMOV+QSahtH0zhqqdw86jlejQRv6J5z31tE7p622yJ3xzmDd5ZcKjEVSqn0Y8Z7i9PzR2QjY6Y5ZMx0WALTYQqAtQan4uwiG9VaqaWc3jIBMGAgl3LBI5P7TRlXIpfUtLSpz36snbfIXWmCpfGWZZ+ABEwbh3nn1VVQ5BzOToXYc5muN9VS8acNDzrVVxTZyBhD2zjm2bPuE+shYw3MO0/XeNVYFDlHP2aGWPDOcvUgUEthiIV+yLSNU4fbHabAlcglNIyZYcxgDFf2O0qZaib0Q6JtrN60RTbwzjJrp+5nYyrUOm0aZq1XV0GRuzDvAtZOV51qrbjTroLK+BU53zMNDMJp5qKzhiY4Zq22ZSLnSbmyXMcp6/dkwJnp2noIlpQqTnUWd5beIUUuoZgLY/rSVrClVuJpK1jXaPMgssm88zTBMsYptTx4c6dDp4icr2u8CrGLfIWa4DAYYikEawlB6zaRuxFj5unjNX2fiBmcnTKBjalc3+8uenhyHylwJXJJnXZPvqPWCsZgUJq5yN0opVJOJ1EpU2cnXdMQuTu5FMZYpowra2mC1fwRuQu5FE7WiWFMpFxxztAFx2KmBjsi51mPiZN15PgkMu88Y6wMcWR/HtQgZMcpcCVyCTWn3dBWfSIXSynTJjw4tYIVuRvLPrIeEmPM1MqdaxqLTjVGRM4zxszJOk41rmqlCY42ePbm6uokcp5Vn+5cdQpuyvzNuWCs4WCuNEaRTVIqjGNl1jgw4L2hFMsQp8OUVlNoZylwJXIJtcGR2oAxhjFmnDPM2sBiNtUdEZGzxZRZD4lVn06va0wbCYDg7Ze0KBeRL1Vq5WQ98vTtnlymLMW8jBzMp2yReaelpchZSp26ccZU7gR6m2o5XkVSLORSVKdUZINUKs7BLHgWs4ZaK0/cWmHUWXDnaXUhcgkZY+gaxxjznc8Fr2wrkbsR07Rx8M7yTJy3DZaYMjEVBa5ENkipcLSKrIbMdKvJUKncOh7oWq/Alcgmz7nJ9Mwxo7J8Re7erA10jZ9qlA6RlCvBO1rvaBs9f3aZfroil1DKhePVSD8mxlSwcKe21b7SzEXONcbM0XKkUqkVrDUsuobDvYsemch2S7kQx8IYM9cOZzgL6z6x7NPU7VZEzmStwXuLd4b1kAjenR6kGJxXV2iR8xwuAg8cdJysI1Rog4FaeejqTAf4O06BK5FLaIiZ9ZCpdaqHUCos13Eq8JmK3rhFNnAOjpcjX7yxogDWGEopPHy18PBVdaQR2cRaA3a6IhhTolhDqhVr0FV1kbswbz05F/oxE1PGWkPXeOattmUi55m1npddX3D7ZKAfM9bAwV7Lnpob7Dy9Q4pcQjlXci7M2qmQtDPTVcGUp/oIAb1xi5ylHzOxFKyz7J9ea+qHRMyVMRYWswseoMgW886y1wXW/dTYIKUp+LuYBWbaeIucyzvLwaKhDYVSK9YY2kbZViJ3wzvL/jzgvSWlgrWGxls6PX92nn7CIpeQtQbnDP2YcW4qRBhzYe6dOjqJnCOlaaNwfb+laz2Vyrz1xFwYswp7imzinWUxb8i1slwnqoHGWg73GgWuRO5SrVOh9lIqWCgFlCwicneCdwTvKLViUJ24lwqtMEQuoTZYcqncPB7IpQJTW9h5q/vdIudxzhC8Yz2kKa3cGNbDQOMtwWnxI3KevW7qhjZvM6VWvLN0jVNjA5G7EFPmeBXpx0TOdSrzEDx780CjOSRy13RY/9KiwJXIJVTK1I3GGnDeMbWpsZjTj/Q2LnK2RedZzDzDmLh10k+zxxgW85bFTM0NRM5jrWFvFiitp9SKs0Yn3iJ3aTVkVn3EWsusdcRcWA4Rd9odWnNJROTLKXAlcgmNKWOM4cErM6y1GDPV7ckVYiy0jU7sRM4SvOOhK3O8tfRjptbKrHVc2euUMSLyAlhrTo9MRORulFLJqZALLGbTNsw5y/FqJKVMqR6nwJWIyJdR4ErkEnqmNoK17k4HDWsKtVYq9YJHJ7L9Zq3nZdfmrIZErTDrHMEpaCUiIveRmX4Zw53C7KVWap3q9BgFgkXOVUrlZD1dt3XWMu+8aiy+BOgnLHIJeTelk/djpmumN/CUC3tBrWBF7sYYM8erkeV6BGCIgYN5q2xFERG5b6wxNMERYma5jng3dYRuwrSus1aBK5FNUs48cbPn1snAMCacsyw6z4NXZhws2osentxHClyJXEJd44g5ANNpgzWGeefpWqfAlcg5cik8cXPF559e0o8FYyqNd7z86oJXPLTQHBIRkftm3npKqYwpk3Jh5j1tcCy6cNFDE9l6t08it056luvEovOkXHn6qMdYw6zzyp7fYQpciVxC1hr2Z4HGW2IuGKAJ6ugkcjeWq8hf3Fhy63igaTymwu3lQK2wvwhcPegueogiIrKjrJ0OG8u6UKshOMOsdcq2ErkL/ZhYrhOHey1NmA4a41FhGBL9kAlz7YV2lQJXIpeUtYY2uNNuTihLROQuLfvEep3wznH9YEorv3lcWQ+Ro3VU4EpERO6bmDLHqzg11SmFaAulwt5sOoQUkbM9U8m31ufU9K2GikFlfnebAlcil9Sqj9xejgxjxljDXuc53GsVwBI5xzPrmpzLaY0rwzhmrDMYrXpEROQ+Wg+Z9ZAwxtA1npgKyz7inFXgSuQci9Yz6zy3liN7OZByoZTMvGuZdZo/u0yBK5FLqB8TT9xcc+u4pwClwHHriCnz8LUFRq2URc60N/M4bzk56jnpR2qdglkPXulUY0TkLvVjYoxTN1vnLF2jGosi5ymlklIh5crBYnreeGc5Xo2kNGVgOat5JHKWg0XDOmagZ9WPeGe5ut9ybb/Dq77VTlPgSuQSOl6OHK0GUql0jadSWa0SR95ysJeZqyWsyJmaYJm1nlIrqz5TgXljmQXHrNHcETnPqo8s+0Q/JmqpeG+JybM/bxS8EtnETL+MgVIr1hhKrdQKxhgMOngU2cQ5y8EskGLGG4N1lv1Fw7zT+m3X6ScscgmNqXD7ZKQNjn7MWANjnlorj1GBK5FNYgJLZdYGgvMYKs4bqrGMuTC/6AGKbLFcCv04XXXyzmIdpFxZD4ngHXszBa5EzmKNoQmOEKc1W/CWmArBW4K3KtAuco5hzKzHDMawv2gpdcpiXK4jB4tGt052mHa3IpdQLpVcK8fLkYO9liFVTtYjbeNxWvSIbNQPkdUwbRQeOGwxBm4ve4YxsR4SV/baix6iyNbKuTLEaa54b6mlYowh56qrtiJ3Yd56SqkMMZNyYdZ6muCUMSJyF4aUGcZE1ziCn64GnqwjY8rEVFQnbofpHVLkEmqDo/WOda70Y6ZQT0/rwKs2gsi5SqlYpo6cANZaSq2UquLsIpsYY+jHwsl6pAkOby1DylhjGFO+6OGJbD1rDfvzQJccuVScNQRvlSkichdqhVKnQ/w0pNN1XKXU6WuyuxS4ErmEutZxuNcybx0xg7XgTMPVvRajuJXIRsE75jNPypUhFUydAr6zNtAFPRZFzlep9bQejwGKAVehauMtcjfM6ZVBEXlhnIUYM0erEXdaI66UyoNXZnivZ9Au0wpd5BJqvOP6QceyT3hrKEyFPfdmKowrcp5Z69ibBY5PRlZ9xBjwFhazTlc1RM5Ra6ULjv15wDtLrZVm4Ugp0wQ9f0RE5H4ypFI4Xo7kUjFAe9pwR1mLu00rdJFLqG0cXfJgIKWCPz2561qvwJXIOZyztMExmzlctJjTz3WNR9NHZDPnDG3jmeU6FWe3EFNl1jqcJpCIiNxHMWVSqjTBTldtjcUYiKkQU6FVJuPOUuBK5BKyZqqP0HhLymVKOfdWaecid+GZDk4PXZ3jraUy1UoIzhBzpVF9aZEzOWvpmqk2Tz8mYppqLHatp2v0DBK5WymXqd6iNTp0FLlLw5gZUqYJnlnjKKVyezUyjJlcCqDn0K5S4ErkkrLGMGs1hUVeqKl4p6ELgfZ0oz3GacGjwp4i55u1HmunTN9ap8yrrnHafIvchVoryz4xjplUCs5OWYzzzmN11Ulks9MutjFFYsrUWqc1HBWjOos7TbteERF5SQne0ATLcp2YmnAahpiZtY6gjbfIuYwxdI2nay56JCKXz2pILPtIP2S8M6xzJeYCwN5MKb8imzhjqFSGMbPup66C1lgMBucUuNplClyJiMhLSvCOrvHUOmVaAXSNo228ikuLiMh9U+q04e6HxGLW4KyhlMqyj4w+U5R1JbKRtYZZ68i50p5eW8+p0Iap1pXsLgWuRC6xlAs5VzAQvNViR+QuLTpPcJaYC7VONXra4NSRRkRE7p96+guDs9Pzxp7+f611qnmlrBGRMzlnCN7zwJWGWirWTvuhxjtKuejRyf2kwJXIJbU6TTOPuWBOA1d7s0DwKkooch5jDG3jaFXEU0REXiTWTteZrIV+TDg31esB8M7eCWaJyPNz1rA/C9Q6zZlKZYiZtnGn5R9kVylwJXIJDTGzGhKrPuGdnVLPT688He4p80rkPM9c1xjTdDwXnKVrneaOiIjcV23jMCvDzeOemAreWQ4XDU2wyvoVOUcbHF3jpgYHKVMrNN7ReKfD+x2nwJXIJTTGzDBm2uBowvQmvewjMRViKrRBb9wiZ6m1crKOrIepqxNACJaYA/vzoOCViIjcN6WAtWCYMkaeeeKoq63I+Zrg2Js1OGdJuWAxhGBZdGpssOsUuBK5hGqdMkbsc1LKrTGUWqla+YhsFFNhGKfgb9c4DNDHgjGJNli6Ro9GERG592qtDDGRUuGBK3O8s+RcWPWRIWa6VsXZRc7jvcFnQynTtdvGuy/ZE8lu0upc5BLyzhK8pR8zs2YKYqVc2AsB73TBW2STlCv9mFmtEzeOewC64KjVk3RiJyIi90mtUAtUzJ31mnMWzNRdUMXZRTbLpXC8HFmPmZgK1kzrulw8c63hdpoCVyKXUNc41oNl2Y/cXg44Y1h0gaaxClyJnKNSefLWii/eWJFypdRC4y3X9juu7rUXPTwREdlRxkxd0YyBMSaCc6RS4DSLXsXZRTbrx8x6zORSmXeBUgqrPmGZmu44VWjfWQpciVxCdeqljKFipw8wVvURRO7GMCSOTgZunvTszxqcMdw6HmicYzUk9hcKXomIyL1njKEJDmfh6aOeXMBZ2J81dI1XcXaRc6Rciakwaz1QcdbgrCWWQkoV11z0COV+UeBK5BLqT7uhtcFzuNdRS2XZp6k+QioEr9MGkbOsx0TKlSuLlv35tMLx3hFLZX1arF1EzldrpVZUW0TkBaoYqAZqoVZ1ExS5W+b0auDRyQDWYDGMMXFlv0XTaLcpcCVyCeVcSanQNY5SKgYIfuqukUshoMCVyNkMwRtyNVMtkQreTlmLWvOInK/Uyu3jkeN+pJRKGxyHi0b1RUTOUWtljJlSKtcPW7xz5FLoh0Q/pqlhiHbfImerkHPmxvGAc4aSIXjDYtbo4H7HKXAlcglZa0i5cOsk3znpjqlwZb/RgkfkHAfzBu8dR7d6Vn0CDDkVHrrWsT/TxlvkPE/d6rlxtOZ4FSm1EpxlPSRefn3OrNUcEjlLrdPhY63QhGkbZq2jH6dgVi4Vr+LsImcyZrpyezhv7zQyiKng/bQ3Ct5d8AjlflHgSuQSMkAplZvHPcZOnWgab9mbeYIWPCIbtY3l6n7LySoSc6EWmC08V/Y6ZYyInGOMmePVyFO31iy6gPWevo/cOBqYd0GBK5ENjHkmu3fqBu2dJedni7Pr2q3IZqVCExz7c0euFXd6ddBgKOWiRyf3kwJXIpdQBawzHO63eGuowBgLzllSrjTKlBU5U8pwuGhpX+WJKVMqBGfpWkcq6nAgsskYM8fLkVwKsVTKEDHGcHTSsz5UYwORTYwxtMGTusK6j2AMtVZmracNDquseZGNnJ3mzO3liDst9xBT4fphO/1edpYCVyKXUCkVby17e+G0KI8hpoIxU+0RETnblGY+LX6a2VScvZSKPf28iJzNGMi1crxO7M0bWuc4Wo6kOgWFRWSzWeuAZsq2KhVrDF3jTrukicgm1hhSqZysRsZUMMDePJByxTud3O8yvUOKXELOGZyzxFzpGketkHJhHjxOaeYiGwVvybny1O2eMWWMAW8tD17tdNVW5BzeWZrgmDeeW8cj1hpymZqFdEr3FTmXMYZ55+naqcGOtUaZViJ3qdSKt4b9ecCdBqpiyndqXCl4tbsUuBK5hNrgaBvL7ZORo+WIobI3b2iCU1FCkXPUWhlipo+RWioVyFT6oag+gsg5rDVc3W84OulJZarT0wbLogvsz5uLHp7IpWGNuVNcWkTuTi4VYwxXD2Y8c1bfj5mSp8YH2gbtLgWuRC4haw1UQzVQasEaQ6lV2VYid2E9ZIaU6RpP13io0I+JlDOrIdHpuobImbyzGGNZzAInq0gIHgzszTx6AoncnSFmhjFPVwWtoQuOttGOW+Q89rTUQ0yZ4C21TgcoTfBqbrDjtDoXuYSGMZNKIVjL3kFHLpDStAjqGoezSpMVOUtMhZIrjXPszaYOaAaIOZOyUq5ENsml4iwE53jZ9YZapxpxGKMacSJ3YRgzJ+uR9ZBIZTp0jK2n1KA6VyLnaIPDGLhx3JNPuwnOW4efNwSv/c8u07ujyCUUc2GMmVnr79zlXjNtyGMqONUZETlT4y3eWU7WkePlSGU6uetaRxN04i2ySTktJn2419IES61gLPR9Qk05RTartdKPiVWfCMGxCI6YMqs+4Z2laxxGEWCRjQxANRhTqaWiI8eXBgWuRC4pw1SQPZeCwVBKwTmH0WUNkY1mnWfeem4crTlajUAleMfhXsNcp90iG1lr8NayTAmMwRpIsWCt0XV1kXPUOtXhKXXKHAEI3tGPmZwLuVS86l6JnGmImVLh2n6LP82wmrIXy+n1QR1A7iqt0EUuocZPLZRvHvcYc3rEbeDBKzOlyYqcw5ipK02tkEuBCsFXaq066RY5h3cWYw2xZG7e6E834IbDRUcT9PwR2cSYKUPRUMm54Ny0nnvm+aMaPSKblTpdWffBklLB2qnmVc5VDXZ2nAJXIpdRBU4Ls1OnEzzvDfX08yJytlWf6MdMCI5rrT/NXqyMqbDsI1f22oseosjWqrUCFVOn7EVrzHR90ELOQLjoEYpsL2MMbXDE1rMa0nSQUqBrPG3jsDo8EdnIWcOqjzxxYzVth8x0ZfAVDy5wylbcaQpciVxCMRecMezPG1LOGGNxbmqtHGNRZxqRDcZYWA2JXCrNaYZiyYXlOjLGfMGjE9luKZfTDk6OhTPkCtZCTJWo5gYi55q1nn5IU2fBmGicZzFzKswuchdiKpysE0/d7qlM2fOLznO8jLzsqgJXu0zvkCKXUCmVG7d71jHRj1NtkcZbzBXDwaK56OGJbDVj6rTwWY1AgwVO1iOLLlCqqkuLbFIrjGPhZJXw/plsK0MulcO5Alci51kNkduryHI9MsRC9AXvDbPGs5hpDSeyST8mai1cO2zpGg8Vbp+M5FJZ9YnFTGm/u0qBK5FLqB8TTx/3PHV7oPGWUuudzcMrHlhc9PBEtpqzlhAs3jlKqRQDzlm8d6oRJ3IO6wwxZ5ZDpC2ONliOVpEuTLV6RORstVZun0RuHPU4Z7myF1iPmZtHA01wzLugWosiG+RSqRiu7nc4N7WkKrVSatUzaMdphS5yCS3XifWQaINh1npm7XQ1cN1H+kFXnUQ2Cd6x6ALz1pNSJsXMrHXszTyNutGIbFRyJXjLvHU4axhiZt55nLPqKihyjlzq1AEtF/Y6j7OGvc6TS2EYMjEpa1Fkk+AswRluHfes1omj5TjtibxTg5Adp4wrkUsolYLBcLjf0QY3FSakx1hDnzKHFz1AkS1mLQRnwEDbeKaOBpXgjDbeIndhmieGlAu5VKwpBG/VEU3kHNMMqaz7zA3TQ52KS6+GxDUKRvtukY32F4H6ROGzT56wXCesNTx0dcYr/GK6Oig7Sz9dkUuoDY5Z68g5E9pwmiJb6IKjDcoYEdmoAtbQNvbZ3xuDNQ4lmYts5pyZrjYdD8Rc8NZwK2eu7XdqRS5yDucs1hjGlHjyC2vaYBljYW/mqBiC0xpOZJNhzNw+iSxXiT4lnDHcXg6c9JFSqzpz7jDF9UUuoasHLYcHLWC4edxz+2Rk0Qau7Hfsz1WUUGSTUivOgLd2Ov024K2hmqk7jYicrRSIsVDKFLQyBoK3DLEwJl1VF9mk1IoxU+bvonM4B/POYa3F2aoGISLn+MKNJbdWI13nee3LDnjF9QVDLDx9Y8XRarzo4cl9pIwrkUtof9bwyusLcqrcXo5Ya3no6oxXPrDAWcWjRTapwLrP3F4OtGHKslrGhLWQszYNIpuMMVNqJQTLrPFTlmKtjKkQFbgS2aiUSinQNZ4re55UKt4a+iFTqyGlQqPMeZEzrfrMeohc3W+x1uBah10almNhvYpcWbQXPUS5TxS4ErmEcqkMsWCtwVvwDqqB9ZCYd8q4EtmklsqyjxytIrmMUKeMq+AtBd11EtnEWki5sFwnxjFTMdRacMbqqq3IOawx1FoZ01QbzjoYU2HMmVxAt5xENnN2ahJy+2Rk1hZqhXWfOFgEmlaH97tMgSuRS+j2yciTt9YcLUe6JlBK4Ys3VngMe/NAGzS1Rc4ypsKYKqVUWj8tclIuDGMiRQWuRDbxzhJT4Wg1QIVKASwH8waMQlcim1hrsNZggH5MeG9JqWDMVD/OO228RTY5WLQs5oEnb/QMMZNzoQJ7XWCvay56eHIfaXcrcgmdrCO3TgacgVKnN+xcKjdWPQ/0MwWuRDZIqVDy1ImmbR0GOF6V6RQ8K3Alsskz12kthmqgVoehkkpRcXaRc5RSmbeeg3lDNZBTZd5Ngax5405rMCrtSuQsh3sNe/PAesj0w7SWO5g3XD/seKZvp+wm7W5FLqGYMushEU5bjxsDy1UkeKcaPSLnsLaSC+RcuH0yFfI0GFKeTsNF5GwpF1IuBO/YmweMgTFWUs7EqBpXIhsZCMFxZb8leEut0xouxkLbeIw23iIbjWOeasQtGvK8wQDBGUqBqgvrO02BK5FLyDlLLpWnj3s678mlkEvlcNHQNkozF9nEe4dzhtWY73RFS6lwsPAEo/kjsokxYE7r9NRaAUOu+ZkvXPTwRLaaNYYmOOadJ6ZCE6art7POE7zV4YnIOcZUSanQtYG9uSflwtEyMp5eG5TdpcCVyCUUvMFiCMZQqVhrqaUQvNVpncg5rDEYY7C10vcZTmuLGAxWzZxENvLOTnV4DBytxjtBrHnj79SME5GzzVtPKZX1kBhTpg2OrvXMO23LRM5j7fQcmjUBc/pxzoUQLLp0stv0DilyCdUK+/PArLXU01BVqZW28RS9aYtsNKZCjIVSKtYaaplqSg9DJiWd1olsYqxh0XlmrcN7hzWGmDPzNhC8Ir8i5zEGMJV+TIynz6JZM80lEdms8Y6DRUPMhTZ4Si00wTNvA42aG+w0Ba5ELqHgHfOuATJt46kVln2k66xuaoicI+XKahhZj5k2GIyFPlZWY6ZXjR6RzSp0redl1/YotVJKwfsOCzRBgSuR8xyvI0/eXHO0jFQqZm0YY6YaOFy0Fz08ka12sGhYDYnbxwMxZSqwPwvsLxraRs+gXabAlcglNO88+3NPP07Xm4yBWevZmzV0etMW2SimzDhmUimE08dgyoUxJnJSyqLIJtYa5q1njIUmuKlGXC44a/C6KiiyUa2V2ycDN48HQnA0zhFT4fZypA2O/XmjzCuRDWat56GrM7rG0ceMN7CYNRwsGozmzk5T4ErkEpq3nuuHHbeOB4ZYMMDV/ZYre62uaojchWIMFqhlumxr6tSNJqGrgiKbeGcJzykuXetUN27WelplXIlslEtlGDOrPnHoLUNMGGNY99O1wZgybdD2TGSTRReYNVNhdmOm55KCVrtP74wil5B3lit7HW3jSWl6026CY9ZqSoucxzuLtwaqYcwFDFTAO0PjtPEWOc9eF4ipMMZMqXV6/jROgSuRcxgglcIQ850sqzEW1jHfyVwUkc1yKSzXkX4sOAuLWaBrtAfadfoJi1xSwVtqdYzW3KktovRykfO1wdK2DmMMzk1zJrtK6z2tMhZFztWPmVorhqlZiKmVMRXaXKaOgyLyvKw1eGvxDlKqWAopTZtv5wzWav6IbJJz4Qs3VxydjPRjwjnDomt44EqnGnE7ToErkUuo1srJOjLEzBinjKs2OBZdUGFCkXPUCq13zGaOWioYaCyExlEV+xXZKJdCPyZWfaJrPc5a+jGzHhLBO/Zm2niLnKXWqbj03qwh5so4ZtrWEbxnf9FM3W6dHkQiZ7m9HLl1MnC0HOkaxxgz636NsdMVQh2e7C4FrkQuoSFm+jFxvBoxxgKV4bQbWvAWq1RzkXM13pFLPb0mCMGpK6fIeXKud640PVNTsWscy/VIzqoRJ7KJMVPWVds4ypBpGouzhsZbLOiqoMg5Vv3UldMYQz9knDPEVJivLOthxv68ueghyn2iwJXIJTTGzM3jkUqFmk+7OlW8Mcq6EjmXAQzDOM0dY2BIkOZlOg4XkTMZY7DWMMTpumAFSnn2ayJyNmMMKVf6PrEeE2CoZGr1ZD1+RM61HjJPH63oh0IFLFAqeGt4zcs0iXaZAlcil9AQM+thZBjLnRPvISWcNVwrBVDgSuQstVbGmEjp2eyQUitjLNo4iJzDO0POldWYuHGUMBbAcGXRoN4GIpuVUkkxU4BZG7Bm2nSXUolpanbgFAAWOdN6SNw6Hrl1PBC8vTN/9vc8mjm7TYErkUso18rJaroqiAFzWphn3gbQ27bIRjEVVkPi6aM1MU2RKt8Y5qetlUXkbLWCNWArzLuAYXomTdlWev6IbFKojLlgjOH64Qx72tX2yZtrYq7UwpRCIiLPa51GlusIFXKFWqZ13bpP9DFzcNEDlPtGgSuRS6iUws2TkdV6JJWKBayFvUVDrdp4i2zSx5EvPL3i1slAKmW6OLi0eGNYrdNFD09kq6U8Xc84WDRYayml4p39sixGEflyFkNwFmrlyVtraqkYazCm4q05zWAUkbOM/XRQ0naOWRuoBW4ve0qFIWoNt8sUuBK5hFbrRC6ZXCsH84ZUKst1ZIyJMVUWFz1AkS12+yRyvBrpx8x85jDAqi8s1yO3lv1FD09kq5nTq03H60TjLbVCJU2pWLriJLKRtQbnDH3MnKwiqRYclv3Z1A3Nag6JbOS9gVoZRyh5oFRDrRVnLd4q8rvLFLgSuYTyaVqsM4aT9Yg102ldLoWY80UPT2Sr9UNiTBlnDeX0mq1zhjEWhkHzR2QT7ywpZfohcryuBGsZYubKXkNVcwORjWqtpFQxgLeWYC1UqKYyav0mcq5F68DC8cmAqVDNlMVoDex14aKHJ/eRAlcil5Bh2nwfLUdKqWAsjsLhXkOwqo4rsol1FmcsKVcaKsZacsrY0KDDOpHNUq5Ya6gVgp0aG7TBkqsqXImcJ5dKyoVc4Mp+S64Va6ZOaTkVYio0Qes4kbMUDN5YOu+w1jKFgQvutF6c7C4FrkQuoVIKY6ysh0TbOEopDDEzjAnj9LYtssnhXiB4izGVYSxAoRhoguVg0V308ES2Wq2VMRUqlSFWcko0jcOlTFRzA5GNDFNn6JQzuVism+rEpZzpY1H0V+QcpcCs8yzmHc5OBymrdaQJgX5IHCzaix6i3CcKXIlcQkMqGFM5mLcUChZLEyzOWvo+oyJXImdrvefhqwvGmJm23+CwPHg4Y97psSiykams+sSt44Gu9ThvWa4TY8w8EBW4EtnEWoN3llIrx+uRxrspEFwr3hmcVeRKZBPrDF3jCd4xax2lQi6FtrEYdTfYaVqhi1xK02b7mU13tZU81tPWsMq4EtmkbQJda5nPAsOQqMCs9XStp2t0RUNkk5IhpTw9g2qlZrDGkNN0BUpEzlYrdI3FYlgNmdsnI01wzBvPrHFoCSey2dVFw6z13Fz2LPvp2rq3hnkXOFioxtUuU+BK5BKyWPoxcuP2QPCOAtRSuXbQMtPGW2QjayqFyhgzITgq0I9JtRFE7kIulSZYmsbSNX7aaPtKzkUd0UTOYQyMqVINBG9oQkMt08HjGAtWGVciG+3PWw4WDUfLkZSnCldt57g6b/BeGVe7TIErkUuoUHEY2sYTvKUAMWWcgVi0/RbZZEiZkirz9plHoKHxllwrg646iWzUhOk6Rs2w7hMAtRTa1hOcNg0im5RSiblgMOzNAk3jpy6dY2LMlVIK1ukAUuQsuVYab+k6Txwzzhm6JuC8nTquN3oO7SoFrkQuoVIKXRvYX7RThzTgZEiExjOO2niLbJJSwRhL20xXA40xjGPCYEhJ7chFNrHW0HiDwVCB4AxDMQTvdNotco5n5oxz4Kyh79NU28o4Wm8oBVDcSuRMx6uBJ26uKalQKpgKJ/3IE7dWvOLBPbrmokco94sCVyKXUNd49ueBmCuzzlMLtKmwNw+0OmkQ2chZR3CWWmHWhjutyOenRXNF5Gw5V9rGc/1KRymVXAtX9z3GGDR9RDZzdgr5jmPlZDkAFWMM1rupQLuCvyIb3T4ZOOkTOWcO9lpSrNxa9ux3gajDx52mwJXIJfTAlRltG7hx44SjkxEMtN6x3wWu7KkNrMgm+/PA/qLhZIycrCKlQhsMi0XgYKGjOpFNjDn9hcE6IAHUZ78gImcyxlCqIebEch1xzlJKYTELTBcIRWQjY0ipEIKjHzLWTPMmA1HlHnaaAlcil1Dwlv255+kjx5gT1RlmrWE+CyrsKXKOJliuHXasY2LVJ6gway0PHc7oWj0WRTZx1jCmws2Tnn7MeGvJuef6lRlFNRZFNkq5nNYktVy/0jGmQuMtYyqnXys0QXcFRc7inMGZSj8kMFNx9lINwRnNnR2nFbrIJbTqE2B4+MqMVKZ6PYZKKZV1n9ifK2tE5CzWGBadZ68L7M8DFkilMu+CzrtFzpFLpe+nbJGUCmumYNbRyUi6rtNukfPEXChUFrOWA2PIBcblmpQKqL+tyEad9/jgePpkTesdpVbA4IyhU2f1nabAlcgl1A+Zm0c9KWe8c0Cmj4lZ64hJGweR81Rgbx6IMZ/WuvJTkU/FrUQ2iqmw7BMpV5rgsA7GWBlS4mQdeejqRY9QZHtZY/DGklPlCzdWOGvIuWDttPG2VjWuRDYJjaVxlmt7LZXp+q2h0rWBlBX43WUKXIlcQsOYWQ+J43XkcNYw5un3e10ztdcQkTPl8mxw93CvA2A1JJwzWvSInCPnyhATR6uBLjiwhpIrzlRGFcYV2cyA85ZCYRinzCtbDW1rcc5gdXoislFKlcW8ZW/eYN00X/o+0jaWXHV4v8sUuBK5hIwzpFJw1rKKCYwFpi5pWfsGkY0MFmsgOIuxYIDGWwzKuBI5j7WwWo8crSJLk4E6NThoLFk1rkTOVWpl1ga6AN5bcipMlwQN9fTak4g8v+AslekQxZSpxhXGUKvBW10V3GUKXIlcRhVmwWPJhOAoFZyptI3RxlvkHNYaZm2YWpCfThhnLW1jCWpFLrJRNZALlFJovcV7y2rIGCCOOu0W2aTkSvCWWePZXzSkPB1Cnqwi/plDSafnkMhZmmCZNY6jVaHzhlimLrez1tEEzZ1dpsCVyCXUtZbZzOOdpWs9pVZO1pV5G7TxFjlHEyyz1rHqI0POGAzWQtc0BG0YRDYax4xvLIuuoW0sJVcOFo6cC05dbUU2ss4QrMUYw7pPGGeIKYGdOkYHp4wRkU3axnNlr6H1lj5mOmNoW8fePKi1wY5T4ErkEtqfNezNAk+uV3zh6R7vDYeLjv15S6tWsCIbWWsoFWqd6sVRYTbz1FLxClyJbBS8w1uHcwZvDHhLLoUQHF6n3SIbWWMIjSUEy63jHmMstRYOFy3BOayCvyIbeWvwzmLN6dVaazAYuuB0yXbHKXAlcgkZY8i5cnuViLliUgVGKjrxFjlPjIVaKhWYdx7DVFukUBliZtbq0ShyliZY5qcbhDEXvDOMqXK459WKXOQcpVYaZ6nVAJYxZprgqBiaYCmlKnglskHMhaPVwBNPryhM1wSbxrM/Dzx8fXHRw5P7SEdjIpfQ0XLg1nIAU9lrA7Nmuqbx5NFAP6aLHp7IVks5c7SM5FIo5dl6PUcnkZhUo0dkE4Nh1gUO5w3OGGKqLDrHvPF0rQJXIhtVuH0ycPN4zdFJz9Fy5NZxz+2jnpvHA6XqspPIJst15PbJyFjqaVOqwnI9crKOjKM6VO0yHSuLXEJHy5FxKFzfnzGfeWqtPH3UM46Jo1Vkf95e9BBFtlYqlVSmVuRX9xuMgdsnkeqLAlci5yi1TtcEg+UwNJRspi6dwVE0fUQ2MgaevLnmL548wVpHaCzrPnO0XHJ40PC6Vx1e9BBFttrJOnG0jFArETCmMsbK0WpkPWbmXbjoIcp9osCVyGVkLJVKLIk4GiqVlAqlFIwO60Q2csZMC56c+NyTIwDeGfZ9S/C6oiGyiQFO+sjTt3vGIZExOFu5ut9R8sFFD09kq8VYOF5F+ljYmzlqKRgLccwcrUaGmJm3uhAjcpb1EDlZD5QCTfDUCqth5OjET8VLZWcpcCVyCS1mjloLf/FUj79TK6Hw4GHH/qK56OGJbDVrDalWjpeRnKdaV94ZZq3HGm0YRDYptXLreOB4FcFMhXLXQ8bZyO3VyKsveoAiW6yaSjUVA+zNPE3jSSlzshqxGG28Rc4xHS9acs04CyllcikYa1B19t2mwJXIJTRvHG3jcViGWDAGZsHRtp7Ga+MtskkulWHI9GPGGIO10MfCkPLUlhylmYucZdUn+iFjDDxw0GG9Zb2OrPvMaq0aiyKbOGtZzFr25p71UIhpJOfK/iKw6BqcOtuKbDRrPW1j8QliKRhjmLeeRecxilztNAWuRC6hYaws2sCrHtwDa3DG0MdEGyzrIdE2mtoiZxnGTIyZppnaKQP4WhmHwpBVpEdkk1orjbfMW0/XOQwGMwukVLHac4ts5KzhFdfnPHFryclqZIxgHezPW17+wJzGq8GByCZN4ziYB24tRxoMFQjOMe90eL/rtLsVuYRSLVQD+4uWtrWnXWoMFUMqSjMX2SSVQqZijeX6YYepcONkoNSp/oiInG0+CxwsGm4uB8hgvCHnwsHe9HkROZsxhr154FXX9/iCXRIj+AAvuzpn0QWMUcaIyCZdcDSNI6wdxlRKheAtbeNpggJXu0yBK5FLqAsOawxHqwHTT4mxuYKthjbotE5kk9Y7vLNQM+s+YTjNImmc5o/IOeZt4OFrM26c9HzhxoqUCntd4LWvOOBl1+YXPTyRrVZqxRpD0zgeujJniIUQDE1wBG8ppWKtglciZ3HO0gbPYl7IKWOqwTWWNlhyRtUedpgCVyKXUNc49meBYcw4O3UYNBUWc502iJynaz0PHLRTwOo0zfxg1nC417Do9FgUOU/TOII1gAFrsN5gvSXompPIZhWW68TxKmFqBQw5wUnOHK9Gruy3qMK0yNlSKqRUINfpqroFylRGpaBbJ7tMK3SRSyh4x8F+S9c5hrHiLARnOVi0akgjco42OK4edCyHxNEqAZWu9Vw/6FQfTuQcY0p88ekVN49H9uceYyDGyo1bPU/eXPGalx1c9BBFtpYxsBoiJ6sB56cs+fWYiamyOmgvengiWy+mwmqIrFKhMYZKJY6JPkaqyqXsNKVmXAKf+cxneNOb3sTrX/96fuAHfuCihyNbwFpD6y0116leT6lgoPFWHTVEzmEM9ENmGArrPrJaJ9YpsxqzrmiInGO5ijxxc83xOtLHzDBWhlz44s0lT95aX/TwRLZaLpVSp4338Unk808uOTqJ9GOm5EJSgxCRjVKp1ALOAA6MsVimTKyswNVO09HyJfCTP/mTDMNw0cOQLVJq4YlbPV98ekkulUph3rYEZ3lYNUZENloNiRtHPbdPBpyBamC1jDwd1hwuAlf2uoseosjWGlPheD1y86RnP3kwjpwSqVSWfbro4YlsNQOsh8zJOlFPrzUNqUCF9ZhxOjwR2ahSKNUQrKHxngrEPM2dorjvTlPG1Zb7r//1v/I//sf/4J3vfOdFD0W2yMkqcvtkzXqcNgm1Gm4dD9xejfSDNg4imxwvR546WtPHjLEW4yzDWHjq9pqTVbzo4YlstcY7Vn1ktY48dXvgxq0VTx31LIdEqdo1iGxijGEYM2PMpFRxQMqFMWaGqPWbyHm8M3TBEHNhzIUhZrw1WGNpggK/u0yBqy12fHzMz/zMz/AN3/AN/N2/+3cvejiyRW6fRFZ9Zr9rOVg0XNlraVvDyTpystLCR2STMWbWfWbMGe8MwRliKazHzHrUxltkk1IL3hgK07V15x3OTh+ryKLIZikXap2uOc1bT2FquOMsmAJRVwVFNuqaQNc5muCwgHMQgjutuajA1S7TVcEt9q//9b/m1q1bfOADH+Cpp5666OHIFsmlkGvFecPePFAr3DwZqBUKWvSIbBJON9rrdeKJvAYq/Zi5ut8QvBY9IpuUCl0XuLrX0gU3xapqIJWM91pWimxiLHgHzhush73QkGomJYNxFW+UUyCyiXeWimFMmdUqYZ3hcNFgrMFZzZ9dphUGMI4jjz32GB/72Mf42Mc+xsc//nE+/elPk3MG4Jd+6Zd4y1vectevt16vefTRR/nwhz/M448/zmq14qGHHuLrv/7r+a7v+i6+5mu+5tzX+F//63/xq7/6q7znPe/hkUceUeBKvsTe3DNvPLeXPas+UqqhlkIXHHuz5qKHJ7LV5p3HWktMhZNhKibdWgN2xqJzFzw6ke0WrOFg0dLc6nHOUGqlVsO8dezPtKwU2cQZS9P46crtMmFcomSYdY62CRjVuBLZaN0njk4GbtzqqcZgEgxj5sHD2Z26cbKbtMIA3v3ud/OJT3zinrzWpz/9aX7wB3+QP//zP/+Sz3/mM5/hM5/5DB/60If4/u//ft73vved+RopJf7Fv/gXvOxlL+MHf/AH78m4ZLdc3e84WDSsxkQ/ZowxLGaBqwcdXaNpLbJJrRVnDCkXnglTxQqWaQMuImdbzBvaYPHWMIwJYw25Fg4XMxazcNHDE9lylUUXaIIDLLkUvDd4b6aDEz2CRDa6fdLz1K2eMZdputTKaAxP3l6zHpL2QTtMP1m4k1n1jJe//OWklHjyySdf0OvcuHGD9773vXz2s58F4Gu/9mt5+9vfzsHBAZ/4xCf41V/9VZbLJT//8z/PwcEB3/d93/e8r/Mf/sN/4LHHHuPnfu7nmM1mX9k/Snaas4Z5F5g1HkvEGkfXOOatprTIedZj5ngdybUS4/T+H7xluYr0o2rEiWxSCuzNPIuZ45lbGd4FFrOGtlHGoshmhlLqtLmuGWPsdP22tZRqUcKIyGa3ltNaLXjLYhYouXLzeGA5RE5WI1f31Rl6V2mXC/z1v/7X+eZv/mbe+MY38tVf/dVcv36dH/uxH+ODH/zgC3qdf/fv/t2doNW73/1uPvCBD9wpEvf2t7+dd73rXXz3d383t2/f5t/8m3/Dt33bt/Hyl7/8S17js5/9LD/3cz/HW9/6Vt72trfdm3+g7Jx1n0/ftB3BWqoxWOBkPRJzJnjd8RY5y7qP3DoZOFlFnDMYYFhHvIPlWl0FRTaJKVMKLNpAGxyxVGanta1iVI1FkU1qrZRaKMUwn3mCc8ScialSctFVJ5HznPYBSakw9BmMIdc6BX1VnH2naXcLvP/97+eHfuiHeOtb38r169e/otd44okn+PVf/3UAXvWqV/HjP/7jX9bZ4HWvex0/+qM/Ckx1tX7xF3/xy17np37qp6i18hM/8RNf0TjkpWE5RFZDwlBZLBoWM88wZtZDZhjy+S8g8hI2xMzxamS5Hlj3kXUfp46c60IfFbgS2cjAasysxsx81vDQ4YxSDTEVdeUUOccUlrJ4UzEGYkoYmLoKWmVciZxnr7NQDbeWA5+/ecJf3DxmGCLBOfY65eTsMv1075Hf+Z3fIZ5ueL7zO7+Tpnn+Atnf/u3fzr/6V/+K4+NjPvzhD39ZgOv3f//3uXLlCv/8n//zL/lzR0dHAPzxH/8x3/M938MDDzzAv/23//Y+/Wtk2+Vc6YdMSoWTPmHq1KJ8HLPqI4icI+VCKoVCpRqodbq6EWMi6aagyGa14qyh9dPmYYwV76Bg8LopKLKRNYbgDEMpxGUm54p1hsY7rKlfdugtIl/KW0cuiX5IGAyVSvBTh9ugh9BOU+DqHvnoRz965+Nv+qZvOvP72rbl677u6/i93/s9nnzySR577DHe8IY3fMn33Lp1iz/8wz983j//zNde+cpX3puBy6XkrCGlxO1VxFow1ZJy4YEr4LTmEdmo1Io1BofDYzDOkp3Dny58RORsxliu7DWnRXAdpQDGUXJVnUWRc1hriHk6aOxjwlnHOCaokEtFTQVFNlsNCeMsi67BGKhUapmusa+HxN5c3dV3lVYY98if/dmfAeC9/7JA1F/2xje+kd/7vd8Dpi6Ez/3+xx577Hn/zP/8n/+Tf/gP/yF/+2//bX7+53/+Ho1aLqtaKynV6bTBmKnAp4X1ENGqR2SzWePpvMEHi/UWMARvaINlpo23yEaz1rM3azjcy9RScc6QUmVxEJjPtGEQ2SSdBq1yqThryXnKYExlahaScqVRIReRM62HKVOxax3BW6yB42Wi1MpJn3jwogco941W6PdAKYXPfOYzADz88MM4tzlN8RWveMWdjx9//PH7ObR77uBAnRq2QXtjRTsLXHOWRRfItbBcJRaLhtm84erV+UUPUWRrvWxIvPLhKxR7jD0tzp5T4eHrC1724L7mj8g5QusIreepW2vGlDk8bHjZ9T1e8/A+zmnXLXKWMWZ84/HBs7+YirOnUjg6GXFN4MrhjFYHKCJnmi8CJcEqR4wxmAqZSq6Vhx5YaA23w/TOeA8sl0tyngpiX7ly5dzvf+73HB8f36dR3R9ed4e3gnWGJjia4HHOgPEYIHiPMUY/J5ENDvc6Hrg6Yz1G1mMGKu2i5YErHVcPO80fkXM453DOUqsBDM5YnLNYZzV/RDaoGIKzWAelQLaQ81SY3TmDC05zSGSD1luKqYxDxgeLqZWYwDrHrPWaPztMgat7YLVa3fm4bdtzv7/rns1aeu6fvQxSUse6beBPrwM+dWuNMZVawVp42bU9nLX6OYlsYGrlYOHATr0MKgZrKofzFmuM5o/IBjkX/uLJJZ9/4gRqxVs4Wo5gT+gax0M67RY5U84F3zisMayHTO0TFrAOGm+ouegZJLJBLgbnDHuzhkoFAz5M+6BlHzV/tsi9DiIqcHWP3U03kPoVVP99y1vecmb9qxfT0VFPzmp3fdH69cCt2z03bq0opZ5mWRluHq7olwM39TMSOdPRcuDxzx7z9I2e4+UAFRazgLe3eeUDc2zR/BE5y3Id+fPP3eILN09og6NiqKXw1M0lrkK46AGKbLFaK2mIUAxxHKkFMNC1jjRmbh+tcVbXbUXOslyOeGcwxWC9xRQYUsGUys2bS/YbhTe2gXOWa9cW9/Q19c54D8znz54u9n1/7vcPw/C8f1bkbq37QqkVMDhvMbZSKuSUGaJOGkQ2uXHUc3PZc7Qa2Z93HOx3rMbM7ZOBp2+d/x4u8lKWcmG1Hjk6Hun7RBwLy1XkaBVZ9vGihyey1WqdNnTOTh0GKxXrDN656ffqbCuyUQhTtnwsUEol1kIuFVNh0enoZJcpJHkPLBYLnHPknLl169a53//c79nf379/A5OdtVyPrIbIYuaxxmCsYd1HVn3hpE9c0X9WImc6WibWfeZgHrh2EACDNdDHzPFqvOjhiWw1aw1jygyxYMeMtYUYM6ZArspWFNmkUhljZjXEqRN0BYZIzpUUK+oLLbLZomuYzTwxJZyt2GKwTWUxD6pvteMUuLoHrLW8+tWv5vHHH+eLX/wiOeeNnQU///nP3/n4ta997YswQtk1MRdyrlTgYC9QS+E4F2LOUHRcJ7KJd4bgLRhDE/zp5yyuVrxXIrLIZpUmOEIwNM5irIFcMN7QatMgslGtU9bvjaOeISZqnbqihVR56mhFqVfQLBI5W9d6ri06FiGRC3hryRSu7rUU7YF2mlbo98jrXvc6AFJK59ai+vjHP37n40ceeeS+jkt2U9cGutZjqZTTIJYPjnnraBoteUQ2uX6l4/pBR87T9cDj5ciQEtcOWx64Mrvo4YlsNW8tB3stDxzM2J8FFq3ncK/l2kHLvNU1DZFNaq0cr0ZO1hGqIXiDsbBaRo77qDqyIudovGE+8yxmga51dK1jf94QGkdwCm3sMv1075Fv/MZvvPPxRz7ykTO/bxgG/uiP/giABx98kNe//vX3fWyye67tN1zb71jMAjFOta725w3XDxd0rRIpRTZ58MqMR155hQcPZ+RciSlxbb/jr7zsgJdfv7eFJEV2jfeOw72GxSxQgVIM3jsO5h17s+aihyey1UqujHG6XluopFzJpTLmPNWMy6pTKrJJ4z3OGJ68NXDzZODJozVHy5EuOLzXZdtdpsDVPfK2t70N76eAwaOPPso4Pn+dlA996EMcHx8D8C3f8i131YVQ5C+btQ3XD55Jia3EXGi9ZX/umSnjSmQjA7zs2pzX/5Ur/P9eccBrX36F/+c1V3jNwwd6TxY5h3eG4BxQ6YfEECNjTHhnaRstK0U2MRZyKZRSSbEQUyHlZxruoI6CIucoJfPErZ7lqufp2z03j3qOVyM3jnuMQhs7TT/de+Thhx/mne98JwCf/exn+emf/mnqX2oN8qlPfYqf/dmfBSCEwHve854XfZyyG4yBIZbTOiOOWeMwBmo1ut8tco4xFVIp7M873vCaa/w/f+Uah/szUioMo067RTYptTKOiVwMhwct1w87uiaQS9X8ETmHNYZZG+gaj7FTvUVjLTPn6Bo31YwTkTN97uk1J6uBMcFi5mmc5XgVuXF74HitztC7THeKgE9+8pP89m//9pd97hm/9mu/xkc/+tEv+fqP/MiPfNnrvO997+MjH/kIn/vc5/jlX/5lHnvsMd7+9rezv7/PJz/5SR599FGWyyUAP/zDP8wrX/nK+/CvkZeC28uBfsy0wTFrpnbKqcDJamA9JtpGU1vkLDkX1kNmPSZO8pS1GJyllMpipho9Ipv0Q2JMhVnnOJgFUgFTK8s+sRoy1y96gCJbrFa4ttdwsNdQqJRc6VqDKYbrhx1GfQVFNjo6Gbh1MmKMZRynw/qUCjeOe46XkQcOL3iAct9odwv87//9v/mFX/iFM7/+n//zf/6yzz1f4Or69ev8+3//7/mBH/gBHn/8cf7kT/6EP/mTP/mS77HW8t73vpd/9I/+0f/3gctL1rpP9GPEW8eVg5aS4Qs3l6xjZowq7CmySa1w62Tg1tGAsYYpObZysJiu4IrIJoZcCsv1SIyZXCrWQs5Qq54/IptYZ5jPAoeLlmFMFF+xQHOaheVVXFpko5gyw1gwJJomAIX1mE6v3F706OR+UuDqHnvkkUf40Ic+xKOPPspv/dZv8fjjj7NarXjwwQf5hm/4Bt797nfz5je/+aKHKZecc/ZOHYR1n6BWvDUYY7Cq0SOyUS6Vccyshsi8C2AM6z7Rto6ojk4iG7WNpY+FLz61JpUMxlBK4YHDBWjTILKRNYam8cy7QCkFg6HWyix4Zm3A6qqgyEY+GKBwtBzxKVPz1KSKWulUZ3GnKXAFvOMd7+Ad73jHPXu92WzG937v9/K93/u99+w1RZ5rfx6Yt57bq5G4Lhg7ZfMdzhtm6iooslFMBQzMu0Dwp80MOo+hknRcJ7JRLpVhiKzGSM6VylQwdTUMJAV+RTaqFVpvmTUWZ1tyAWeh8VPN0lIq1il4JXKW1gdyASyMfQFT8cZinVFzgx33ou1wP/OZz/DqV7/6xfrrRHbavPVc2W9YDenO1cBF61jMAp26CopsZK0h58LRcqAUKBWCNwTbYBS3EtlouY4s+4QBFvOAYcq46sfE7VW86OGJbLVKJddKqeCswTqgVlKulFJQ2qLIZqthxFowxtC2DkolV0h5qmEqu+tFC1x967d+K295y1t417vexTd/8zfTNM2L9VeL7BznLMZYGmfJpeKMmVqRe0cqFafYlciZgjfcXg18/qnlafZVxTlLZcHrdU1DZKNSp+6BuVTmjcdaw6pP9ENhGNNFD09kqxkMfZ/oYyLFgrOWXArOOdZ9xqjcg8hGKZWpqUHweD/VKR3GPDXeiepsu8tetMBVKYU/+IM/4A/+4A84ODjg7W9/O+9617t4wxve8GINQWRnLPvI0bKnj5laKxEwY+bGcc/LHpjTBkWuRM5ysk4s14n1mHEWKDCkzHKdOVlHrh3OLnqIIlvLO4d3lpTh5smAAWKqeGfo9OwR2ajWCsZgsRzsBxpnibmwWmcsU2BYs0jkbN46grcYB8E5KoZcoPUGxX1324t2EfSBBx6g1kqtldu3b/P//r//L9/xHd/BO9/5Th599FFOTk5erKGIXHpHJyNHq0gfE03wBGu4vew5WY0Mo9JkRTY5Wg4cLQeoBWsM1hqMhePVwO3leNHDE9lqXXC0jcUZWPeRk3UkpkzwllY1FkU2qhWCs7SNJTjHmKZsq661d2pcicjZ9maBdhZICXIppJTw3tC1gb02XPTw5D560QJX//2//3d+4Rd+gbe97W147+8EsT75yU/ygQ98gL/xN/4G73//+/mjP/qjF2tIIpdWKoXjk0RKhRvHPcerSEpwMiRS0qJHZJOcypR1NSTGXIi5sOzTac04XXUS2aSaStc4FovAlf2OBw5nHC4aDhYB71QYV2QT5wzOW3KuPHFrxa3jgadvrRhjwTqebRgiIs/rgaszri0a9rpAcI5Z69mbtTx4paPrdHiyy160n661lre+9a289a1v5caNG3zwgx/kgx/8IJ/61KcAWK/XfOhDH+JDH/oQr3nNa/h7f+/v8R3f8R1cv379xRqiyKWRc8XYyqqvHO45Uqr0YyKnDEYZVyKbGAfGVHKu0/G3mQp6GsCoI43IRjlV2iZwZd5hHKRcaJy9k0kiImczxlByoR8zxycjmIphyvzNpaKbTiKbda3n4QcWtG1DTYlqofWOB67McEbPoF12IT/da9eu8Z73vIf/8l/+C7/yK7/Cu971LhaLxZ0srP/7f/8vP/uzP8vf/Jt/kx/6oR/i93//96c74SICQPCWECzzzoIxOG+Yd45Z0+BUXFpko9Z7DhYtV/ZbujbQhMDhfsf+vGWh0zqRjbyzOGPAQLCWvVmgAk2jZ4/IeXKeOnCOsbCYB+Ztw3weSKmyHhKp6PBRZJPWO/balsM9z96i43Desj9vmc8arA4fd9qFr9Df/OY38+Y3v5kf//Ef5zd/8zf5jd/4Df74j/8YgJQSv/u7v8vv/u7v8uCDD/KOd7yDd77znbz61a++4FGLXKy9WeDqQcfxSSTGMnUU3Gu5dtji3YVPa5Gttph5Xn51MdW3Oj2dq1Su7ncsOtVHENnEOYu1hpQrq2G4Uww3hIYmaNMgskmulZN1pI+Zg4XHYqkUbi8j/3/27jzYuv2u6/z7N6xhT2d4hjtmBNNGGUQIYBLsQAtKdVc0ikFaEJqyWqWDBsS2FLuru9oUgt0qVhEascAB2kg38QYtjWha0AKx0jSmOwRIIwTMcHPvM51p773W+k39xzr3gWvu2edevM+Z7udFhZy7z9nn+d16svZav+/vOyzXAykWNONA5GTOGlIKdF0ipIIzkHIhxYKSfq+2C7PDnUwmfMVXfAVf8RVfwUc+8hHe/e538yM/8iPcunULgKeffpq/8Tf+Bt/7vd/L53/+5/NVX/VVfNmXfRneX5h/BZEz09aeyjq6sCbEDBEmOJwzTFo98Yhssj1vePjmbOxvFQulgK/gsWsTrm215708kQutlAIlM8TI0TpQcqapPTGqzEnkNNYYhpRZ9wNdHzAGSh6nCaYAShgR2Wx13M835MKk9sTjXqXrIZKUsXilXcioz6tf/Wq+4iu+gpQSP/ADP0BKCeB+KeH73/9+3v/+9/PII4/wtre9jT/4B//gOa9Y5GylnFn1gcN1IA6RUiCnmqFPKqsVOUVTeR7aarm333H7YE3JsKhrrm1PmSrjSmSjmDP3lgOrLlI5sN4Tc+FgOU7lfPTGea9Q5OIygC2FbkjjwSMWYzLWWbLJKPorslmMhVgMj12bjsMMDNw76Ci5sB4yU50/XlkXKnC1Xq9573vfyw//8A/zb//tv73/+jMb8c/5nM/h7t27/Pt//+8BePLJJ/nv//v/nve9731813d9l7Kv5CVj77Dn6btLlkc9fcoYLCF13NrrOFoFmm1dCyIniSlx92hgCAmTLZhCSon9o56bOy1NretH5CR9SKxWgZQzs0mNtdD1mXWfWa7DeS9P5MKLCby1GF+w3pITmGJIaZwXIiInMxZqZ8gZcs4UM5YPWjcOOZCr60I8nX/gAx/gh3/4h3nve9/LarUCfi1Ytb29ze/9vb+Xr/zKr+Q1r3kNAD/90z/ND/7gD/LP/tk/I+fMv/yX/5K///f/Pl/zNV9zbv8OImfpE/dWPHmno4/heIpTYm9Z+PdP7/Pb1je5vn3eKxS5uPaOeu7sr1l2gd3tFkNhfzVw53DNtYOWR29ciFujyIWUUsZ7S11ZtqbN2KTdJA7WPcZo0yCySUoZY8bN96I5Tg2px8nQxkDMheZ8lyhyoU0aTyHzibsdphSKGQNZD12bMWv0/HaVndvf7t27d3nPe97Du9/9bn75l38Z4FklTp//+Z/PW9/6Vr78y7+cuq6f9d7Xve51vO51r+MDH/gAX//1X0/Xdbz73e9W4EpeMo6OevoQMMBiVpNSYXVvTR8yh6sOWJz3EkUurHU3ZldZDOG4FN0Ww/7RwKqP57w6kYttUnumrad2jlU3YDCkXJhNPbOJSm1FNjF2zAoxBdYhYIy5v/+xpuAV/BXZqKoMqUCKkSEWrDVUU4+hKOPqijvTwNUz2VHvfve7+fEf//Fn9a4C2N3d5S1veQtf+ZVfyatf/epTf9/nfM7n8Af+wB/gf/vf/rf75YMiLwWVd1hjcdawWo2ndJW3OHd8jCciG6UC+8uBm7XFYDhYDUwnjoLqNEQ2mbYV17YmPHV3zb3lgCngrOVlD025tqVcEZFNnDU4a8Ea+iFRO0vMmcpZnLd4r2c4kU2Wq0DlHDd3pzTekQushwgFVn0YM4HlSjqzwNVf/at/lSeeeILbt28DvxasMsbw+te/nre+9a182Zd9GVX1wk7rXvnKVwLcLzEUeSnYXTRMG8u9ZY+zdhxckDKL6YLduU68RTaZtR5vDSkVPvH0ksIY792a1SxapZmLbFKApnbMphVYQ8mFyhkmbUNVaaqtyCY5Q11ZvLM0PhPTGLSqvKXxFTHlMbAlIs8ppMIQM9PG45zBGkPMiSElQtDh41V2Zk/o3/u93/usdNgbN27wB/7AH+Ctb30rL3/5y3/Dv9c5PSTJS8+1RU1VVeTY0ROxuVBXnspbthc6aRDZxDrL7rzmYDkADlOA48CVNt4imw1DIsbM9rTh4d0ppRRyNuScWa8jOzPdg0ROUkwh5YQ1hUnjMcZRciJSCDFqqKDIKbw1xJj45LLHewNl/OetaUPtdQVdZWd6tGyM4Yu+6Iv4Q3/oD/ElX/IlL0rQ6S1veQtf/MVf/B+/OJFLpA+F2kFdOSrG6clV7Wkry6pLzDQKVuREFnDOsrOoCbGM14831JVFlYIim6WcSblgnWFaV6SSKblwuM7ErAtIZBOLISawWOraU3tLTJaui6RiMOrRI7KRdeMEwXUfqbMj5XG6uveGSqW2V9qZBa7+m//mv+Gtb30rjz766Iv6e2ezGbPZ7EX9nSIX3d2jjmUfaWqHsRYDhJTZOxpYLgM3d857hSIXVyoFbw0Gw2zioUBKCVOM4lYip6i8xRrYO+i5dW9NzhnnLfPWUzltukU2KQXmTcV8WtM2Y1/Fpji8NSwmnpwLKPFX5ETOWpyx7C4ahpBoqgrnLJWzxHTeq5MH6cwCV3/qT/2ps/qjRK68dRc5WgdizFSVo+RCFyIHnSdmfWqLbOKsoY+JIWRWXQQD1ozT0owmOols5J1l1Sc+eW/F/mFHoeCs4RUPL9DlI7KZsbCY11zbqvH+OEJVCqF1bM0avPpbiWw0hASmkAo0taeUMRN4iIlcdPx4lZ1Z4OrP//k/D8B/8V/8F3zRF33RC3rvT/3UT/EP/+E/xBjDt33btz2I5YlcKilnSoaUy1gqaMaGnyYXFLYS2SylQsyFdR+p6jF7pB/GJrkx5fNensiF1ofM7YMlewcrQixgIAK39tfc2V/z8DVlwYucxFnLzrzloZ3A7YOOlMdm7Dd3JuwsGpxT4Epkk5QL6y7SD5HkxgFVIRb6kFDc92o7s7/eJ554gve85z384i/+4gt+7y//8i/zxBNP8MQTTzyAlYlcPpOJp6kctR/LBI2ztLWlcU7TaEROEXMmhEJTjddPKdBUliFnUlbgSmSTg2XP03c7lkPCWos73jjcOxj45L31eS9P5MJbTCumk4rFpKGtPItJw6ypWUw1FVrkNIaxHakxlpghM/aGM2acFi1Xl+Z+i1xC06piPvOkZcFbRykFW3nmi4ZZq8taZJOUwVqIpTCtPRjDuovjQ4+aS4tsFGJkf9mzWkf81OCMowuZECPLLpz38kQuvC4krIGmcbSNHTfhdsz8bRS7EtmoFDAUCgVrLM9M1Sl5zACWq+tS7HDz8Qn4izGFUOQq2N1qWUwbUgIoFAzOenZmNW11KS5rkXNTOUMpYI1hCInC2OOKUvAq0xDZyDhHKYZcMiEVEpkhJwoGo4RFkY1yLizXgf3lQCkQ09gj7jAOTOqK2cQrc17kFDkbhiHhfRl7XJVCLuPUTrm6LsUO99atWwBMp9NzXonIxdBUlhvbEwyFnAED3hpubE9wXh/aIps4a5i2nlUX8N6OUwVzZto0eE1FE9nIG1jMHP6eZYiBPBiMgYk3zFXqJLJRodD1kaf31lTOYrBkMjFm5tOaUtrzXqLIhWYo5JLJZbyWrDU4a/m13Cu5qi584OrWrVv8k3/yTzDG8IpXvOK8lyNyIXjnqCrHtPFjPbcxVJXFOoPRaYPIRs5bZpOKlAvWmPvDDeatp1Jmr8hG07ZmWlc4AzGOJ93eQd14FrP6vJcncqEZDAergeUqMMSEs4aYCk3lOVwNqNZJZLOYMiFlQsgYa0ghE0xmyHksF5Qr64EErjY1Un/Xu97Fj/3Yj536O3LO7O/v85GPfIQ01kPxxje+8UVdp8hllXIm58gQC2Us9iaHREl65BE5jbeWeVux7gIpQ8ngHUzbisqrRENkE2vHMlvn3fEEp0IuhdpZtGcQ2SyXTIyJ/dUAuZCLwdrCsg88HqfkootIZJM+ZoYQCTnjseRSKDnT9ZGsnKsr7YEErj7+8Y/z/ve/H2OevYUupfDRj36Uj370o8/7d5XjD/AbN27wtV/7tS/qOkUuqxgL3ZDJhXF08nGpUxcCUVPRRDaqvKELkYPVwOFRpFCYTTzTtsapVFBko1U3lma0taPxnpgzzo39rTSVU+QUxbDsIst1JISMtWOzaW/haBXv73tE5LnFXBjSGCMIKWEopDI2Z49R189V9kBLBZ/rw/eFfiA/9NBDfPEXfzFve9vbuH79+ou1NJFLbYiRFAveGdraUwoc9YE+ZH1oi5yiHxKrVWC1TtTVmGG1HhKHq4FuSDQacCByokI+3nAbrDPU3pHj2G8kBN1/RDYpprDqIv0QqSvLpKno+sh6iKz7+CmH/iLybCVn1uvA/rIfJwxacNaxWgfU5epqeyBP51/3dV/H7//9v//+P5dS+NIv/VKMMfzxP/7Heetb33r6wrxnsVioIbvIcygFrIdyPIIcM6afO2sp+tAW2ehoHVl2kcobrB1HkbsM6yFytBzYnjXnvUSRC6uuPMUU+i6TcsRQiClT1x4N5RTZLKWCteC9Y9aMEzqnjRsnollDDInaq9eiyEmOVoGj1cC6j1hjjlumHJffypX2QAJXi8WCxWLxKa+XUtje3ubxxx9/EH+syEtGW3tiGMsFh1XAWqi9p2TUXFrkFDEV7h72fOL2ESWP53PWwY2thlc/snXeyxO50CyGylkgs+4zOWW8czS1oWmUrSiyibeW2aSm9oacwdhMxuCdYTrxWJWri2x0tA6EVHDWUlWWUmAIiT4WjlY9N3eV9HJVndkTxt/9u38XQJMBRV4EKReMMaxDovWWmDLrIeIsGKuMK5FNisl84vYhH7+9whQDpkAZe8f1MZ738kQutFzGoSDOOyoD1lakmPAWQlCPK5FNvLdMak/lLYergZwLBtiaNcxar1J1kVOkDFjDvKmYHrdLubsMmJLpVK5+pZ3Zp+MXfMEXnNUfJXLl5ZQZQqByhj4moFBVni7G8QNdRE50b79nCAVrYHteYzHsrTqGlNg76M97eSIXWoyJMsZ6cc4eZywaUoakUnWRjXIu1N4wxMSyGzNHKmeoK4e3hlwKTn2uRE40n3imTQU5kw3kkvC2MGkr5hNVnVxlCuuLXEJdTIRUyKlgMRhrWfeREAt9n+BTK3VF5FgfMsbA9UXLfDr2s/KVIeZCSNp4i2xijaWPhW5ILFcDuRS8d7RVxmgimshGmcKT91YcrQIpMQarEhx1gafurfmtaexXKiLP7fEbU35x5rm13xPWgUyhqR0P7U65tjU57+XJA6TAlcglFEJmuQrsHQ2Y41HK1hoOVwGnUkGRjWYTx3xasX8YaJsxY+Sog9mkYtbqtiiyibGWvg/0faSpLJW19EMh2nFamoicLITE03dX7C176spjMGRTOFwNPHVvxRAzdXXeqxS5uHbmEx67PiNTCAGsMSwmnsduzKk02OBKe9Gf0H/X7/pd9782xvC+973vU17/jfr1v0/kpWyIhfWQiClhsZSc6UOhHyK9agVFNnr5Q3N+5RMT1n3k6XtrALyzPLI95ZVqzi6yUTcEjLFMWj8Geg20VSIlxlMUETlRTpl1H4mhMK3HZu3kdPxcFwkhwqQ+72WKXFzGcG1nynRaUzIYC6YYZq0npqLA7xX2ogeuPv7xj2OOR1OaX1ej/czrv1H/4e8TeSnrhkBIGazBGwvekofIEDJxUOBKZJP5pOFzXvMQxlhu7a0pwLVFw2d+2jV2F+15L0/kwptNa+aTikXrMNaRcqELiarWabfIJs5amsqBgVWfsCaRGWeEVN6hoYIip6srS+2b47LaQtcnrDXkrMOTq+yB1ESUE07cTnpdRF6YkgvGjA9AdeOOM64MxhSSrjORjXIu1LXj1Y9usT0fj+Z25mO/q5TVX0Rkk515y7z15AL3VgFnxqEgu/Oa3Vlz3ssTudCcMzSVJefCYd+Ri8WQaauK2huqRukiIps4CyUZDlcdpZhxP+QMOTfUlZ7frrIXPXD1C7/wCy/odRF54dq2oqkdZsg4a8BYmsoyaTytTrxFNupD5N5Bz/5qLHkywMEqYG1H23jmrR58RE7S1o7FtMY7w8FRAgMWaKsJOwsFrkQ2cc4SM1AKpoA3kAsUCiaPzdpF5GTWGIrJpALOjJM4yYXK69q56tSFVuQS2p7XbM9qbvdrVuuIsQXvDDvzmrZRbwSRTdZ94u5hx3IdqCsPxjD0kVwKu1sN81Yn3iInWXURZ2ExqZhUDigYa2gaxxBUqi6ySd8nUkr4yjGfVVgMBeiGRMyZVTewPdf2TOQkuYx9r701pJIx1uCdJeVCUqnglaZPRpFLaNp4nLGkUuhiwgL1tMF7T1srW0RkkxAzQxj/MzvOrlqnzDDAoB5xIhv1IXKwCphimE8rCoaSM8sucbAK5708kQstkSlA4wzX5y0YQymZu4f9OGFQtyCRjUJMHK0H1kMilYLFsC6R3UWtHldXnAJXIpfQch3oQsQAi7YiUxhCZN0H+pCYT857hSIXl3OGXMbJTv1wRAEKsJhWSjUXOY2BVRc4WA1suxpvLcsukUthiOm8VydyoTWVZ2vWYK3h1mGHt5aYMxaYTSumrbLmRTbpQmL/cGz3UFlDAsiwvahBj3BX2oUMXH34wx/ml3/5l2nbls/5nM9hd3f3vJckcqHsHfX0ITObVNRVRaFw1AeW68jheuD6liJXIiep/Jhqvu4Dv3Y4Z5hPGqwas4tsZDE4a/DOkJIh5Uw2YI3684icxjvLje0JTePZXw7E4wysrUnFze2WulKfUpFNunXkYDVwtIxYW8bDx2JYrweGkJip3cOVdWaBq/V6zT/4B/8AgNe+9rV83ud93qf8zO3bt3n729/Oz/zMz9x/zTnHH/2jf5Rv/uZvPqulilx4KYHDMGkrdrcaSoHwdMIaQ1Cpk8hGKRkshZAKOY2bhnGictT0W5FTWGvY3ZpwtIr4ylKAWSk4Y5hNtGEQ2STlQuUtu4uWSe2JpeCNoa09dV0RU6byCl6JnORoGDhcDnRDIhXwZsyiv3c4kKL2QFfZmQWu3v/+9/MX/+JfxBjD93//93/K90spfMM3fAMf/OAHn/V6jJHv/d7vJefMt3zLt5zVckUutK1ZxXTiWA+Zg+VAygXjDE1r2ZorzVxkk5QLe4eBdRfpQhz7jVSevaOgUieRUzS1Y2fRsO7D8XQnoBQa59maKnAlsklOhZgKdeXZmTfkVDAW1kMmxUJMSYErkQ2W68ByyAwh0XhLLLDuI10X9Qx3xZ1ZTcRP/MRPALC1tcXv+B2/41O+/973vpcPfvCDGGOo65rf+Tt/J7/zd/5OnHOUUvhbf+tv8ZGPfOSslityob3s5oKXP7Rg3nrA4L3l2qLl0x/dYXumceQimxwuB+4e9Owth/slT4frnr2jnoNlf97LE7nQau94aGfCzZ0JTV0xqTyztuLhGzO25+15L0/kQrPOQCl0XeBg2bPsAwfLgXUXxkbTKlcX2SjlQooJciEXKClRMvQ5EZU1f6WdWcbVM0Gpz/3cz8WYT+2B8EwZoXOOv/23/zaf+7mfC8CP/uiP8va3v52UEk888QR/+k//6bNassiFtbto+M2vvM504rl9r6OuLC+7OeeR63Pa+kK2rhO5MNZDZEgR7wzN8fUyhEIfMt2g0zqRTYwxbM0qjlY1IfaEmJhNPItpxbTV/UdkE2vMOBE6RI4OxhYPBZjWhpwz3ilwJbKJxVA7Q7COtvaUXIg5UjtH0VTBK+3MPh3v3r0LwKd/+qd/yvf6vuf9738/xhje9KY33Q9aAfye3/N7eM1rXgOM5YYiAt5bKmcIQyHlQsiFri/MVKYhciproPGOtjZU3lEdf11XBqvm0iKnWnWJZT+W2qZSWHWZro/0QzzvpYlcaLkUQsjkDHU19lesXaGUQp8SKalHj8gm87ZiNq1oKoezFutg2jhm01qHJ1fcmf3tPhO42tra+pTvffCDH2QYBowxfOmXfumnfP8Lv/AL+cVf/EV+9Vd/9YGvU+QyuHvQ8fO/epePPX1IH8aHnK5PGAef+5obOKf+CCIn2Z7XtK3l7hGk49LAmDO784YtldqKbDSExNN7a27vdzgzThjsQ+ST99ZMW8+k0QGKyElSzAwxE3NmUnmMM5Rc6IZEiIUhJupKm2+Rk9y8NuXa1pSDVU8pBWNqKJlHrk1pK91/rrIz+2Tsug7gOSc2feADH7j/9Rd8wRd8yvevX78OwOHh4YNZnMgl87FbR3z01pIwFLbmDSknbu+taWvHKx6a8fC1+XkvUeTCmk9qtuctd/Z6wvFUwdpZFpNaPeJETtGHOE506iOLSU0uhZQSB0PiYNny8LXzXqHIxWWsIcRMionOGNzYqoeUMjEknFGpoMgmk6biod0WYxj7whVoas/uvKVtdHB/lZ1Z4GqxWLC3t8cnP/nJT/ne//V//V8APPzwwzz++OOf8v2cx4wSNSwUGe0d9Rwe9bSNowsZciGlPL6+Cto4iGyQM9xYTMiPJmI0YKByhq1Fc/9+IyLPLWcYYuTe0UAIGQzklAm5EFXmJLKZKXgHqUAJmeQgpbG/lbNW5eoip5g0ju1FTR8z6/XYr3Q+rVjMa9Sb/Wo7s8DVp33ap/F//9//N//m3/ybZ71+cHDAv/k3/wZjDJ/3eZ/3nO+9ffs2ANvb2w98nSKXgaHQh0IXAosJ5Jw4XA7MJhVGp3UiG6VcaBrLI9fnTI6bs3chQdGGQeQ0tbf0fWLdBY6WPcZAobCY1gr8ipzCYqmdY9ZUpJwxGLwvGFtReYv23SKbpVRYrxM5QcmFZAshQtdHBa6uuDPb4b7hDW8A4Fd+5Vf4nu/5HkopxBh5xzveQd+PPUbe9KY3Ped7f+EXfgGAl73sZWezWJELbtp6nE8crQZu7624vd8RyzitZmdRn/fyRC60trbU3lMKFAxgyBkmtaOplGYuskkqhVQKB0cde0c9d/Y69o4CB8senZuIbFYoNK2nbSuubbdsLWp2Fy3TpmLaOopCVyIb7S17DpaBo3VPUzsohruHa/YPO1LR4clVdmYZV29961v5vu/7PtbrNX/9r/91vv/7v58QAl3XYYzhxo0bfPmXf/mnvO/g4IAPfvCDGGP4jM/4jLNarsiFNmtrttoJpIEhBqy1VM5zfauFrKwRkU0mTcXOrOZoNXDnoKOQaauKrXnFtFVjT5FNUs7c2e9YDen4FUMKgVVn2DsaznVtIhedwVBXFkPmzn4gpoI3hsWsonYep1JBkY2GmDlaD3hriblgjaXkcdLtuktMNSDkyjqzs7GHHnqId7zjHVhrKaVwcHDAer2mlIJzjne84x3U9admivzoj/4oMY7jlT//8z//rJYrcqFZA1vzmmvbLTd3JlxftGwvWiatB6vTOpFNrDUUDKkUlqvAapXIMZEy2jSInGLZDfRDoBS4sd3yyO6EaVsTYuZwqcCVyCbOGYY+04XMeojkVOhiZNVnViFQaSq0yEbheJp6MQbnHdab+5mKzzUETq6OM523+p//5/85r3rVq/g7f+fv8HM/93PknHnta1/Lf/Vf/Vd81md91nO+5wd+4AfGhXrPG9/4xrNcrsiF5b2llEQ/jPXcGfAlQinUTrUaIpt0feD23or9ZY/3FmvgsIvcPejYnbfMpzqtEzlJTmDtWFabciHESO0NKYLREB2RjWLKrPpAipkbWxN87YhDYn2cLdL3gbZVyweRk9SVwVhD1wdyKuSSSalggabSPegqO9PAFcBv/a2/le/4ju943j//D//hP3yAqxG5pIqhYClmPL1zBWIe+46MPXtE5CQHq8Dessdg2Jk3GGB/NbB31LN/1CtwJbLBfFozrR0hJo5WBWvG0o35xLOYnPljpcilEsO4yfbeMp/WDDExb2tizlCgT5n2vBcpcoHN24pp7emGSB8SUPDOMJ3VeK+MxatMTxgil9AQE7W37M4qqqai5ELXR2rnGWIEdFoncpLheONQOYf39n6mYh8DIamxp8gms7Zi0lQ03rEcAqYYjIXKe7YU9BXZyNcWTOFoNXCw7MdptgaMAWMKbaWtmcgm1lqmE083VOSSAUNTO1rv0Nn91aZPR5FLyDmLd5a2bqm8xRhwGLw3FDVnF9lo2ni8M9ze7+hjxGBY94GdRUPb6LYosknXJ7a3Gna3G7ZyTY7gvGE+8Viv60dkk8qNJbYxZQ6WAWMMpRRmrWeImVqTbUU2yqWQc6GpHQWHM4ZcCikXclKPq6tMTxgil9C08bS142A5HGeMQC6ZuvZMJ3roEdlkNq2YtZ47h4ajZQRTcM4wrSsWyhgR2SiVTMqJxaShrgwpF5y1hBDJKZ3+C0Rewro+kHPGGsu17QZrHJlMiuPGe9UFZhNlzYucJKXCEDLrPuKsYWAMWIWYUNjqaju3wNUv/dIv8XM/93PcuXOH1WpFzs+vPOMbv/EbH/DKRC6+aevZmtSsu3GTYDBUlWMx9TqtEzlFKYWtecONIdMPYRxPXju2F9osiJymdpaQCncP1lhnsUDKmUlToToNkc1yLoQhYy1cW7TElLGuYv+wJ8XMEBOz816kyAUWYmTZB47W4/NbIWMN9DFRskJXV9mZB67+8T/+x7zzne/kIx/5yG/o/QpciYylgjtbDb6y9CHj7FjfvTNrj3v3nPcKRS6unAs5w7R2GDNutFtvKXn8noiczFhDCokQMyEkHBAzVN4yzrgVkZPUlQNnCLHwyTtLnHfklMiMJYMTlauLbNSHzHodCDFhj5/hQs4cLQOp6B50lZ3pp+N3fMd38Lf/9t8GxhPvF+qZDYbIS10phZgKuUAuYHIhxsQQE0Yn3iIbpVRYrgc+fmeFs+McznsJHro+4yEFrkQ26kPEWEtVObYqT6aQS8EYQ4jnvTqRC85Ae3y6OISMiZlSwHtHO6nw1p7zAkUutn5IxFSgQFM7UimsukTMiRBVrn6VnVng6id/8if5W3/rb91vQvjoo4/yn/1n/xmvetWrmM1mCkqJvABDSBytA3f213hnKRQKhqZymBvnvTqRiy1TuLPfc7DsiHEMVFlrsM7wqofn57w6kYstJ4gx45wBa6CAK1AYG06LyMlyhto7tqYVsXWkBM6BsfZ4um3Ge6XNi5zIQEiFYgrrkLEmU0qhFChFgd+r7MwCV+9617vuf/21X/u1/Nk/+2fxmj4j8hsSYmLZBdzxyZzBElMmxEQfkvpciWxwtBpYdYFVn5g3FcbAsg90Q+JwFbmxc94rFLm4nDdgxmwRb8ZAVR8T3luc1SGkyEalYKyhqT2Pbrc0lSXGwq39DmMNGGX9imxSWYM1sBoK1kQoY9avtZZa258r7cwiRx/4wAcwxvCf/Cf/Cd/6rd96Vn+syJU0hELKmUzBG4cxhRIKIUJ8noMORF6qQsx0IWKtBTNmK3pj6frIoDRzkY28c0xqz2zix7ImA94ZvLe02jWIbGSdZTapmE1rSoGYIOXCfFKxmNQqFRQ5hXWOurIMMeGdI5cx46pyFut0/VxlZxa42t/fB+BNb3rTWf2RIldXKYQhseoTVZ2gwNAn+lBj1eNKZCNrLQZD3w+Qx9tgHyI7VYN3un5ENipwbathNSS8NeNJt7FYC9NWkzlFNnHW8Nj1GfcOe9ZdxBqwxrI1r3nkxpRaZYIiG3lvaBtP4x2MZyeEkJg17n77B7mazixwtbu7y61bt5jNNORV5D+WtYZYxl5XMeVxjlMGDOiwQWSzpnbjNZQLuQtgDLnkMc3c6wIS2aSuHItZy40+YZzBMl5Lk9oxbbXpFtnEGMP17QmvfHjBJ+8s6UKmrSwPX5vy0PZEPX9FTuGdZdpWdH3EO0PO43AD5x1VpWe4q+zMAlevec1ruHXrFh//+MfP6o8UubIKMGkcOVe0tSfnTDckGmdJOmwQ2azArK3YmlT440BVTDBtK20aRE5RecvWtOJgWbF32FFKwVeOm5OWrWlz3ssTufCctSxmNTEWUik4Y1jMGpU5iTwPbe2Z1mMIo3aWUgp9zEybCq9r6Eo7s8DVW97yFn7yJ3+SH/uxH2MYBupa6eQiv1HeW2rncVNLLhlXearK4dWUXeRU1kJdO7YXLTkVCuDcOJVTGweR0xkDIUZWfWCImfmkZogZVaqLbFZKoQ8RU+BlD82x1pByYdUF+iExaTxWBygiJ5o0nuvbLfOQ6YaIM4Zr9Vhuq2vnajuzJ/Q3v/nNvOENb+DWrVt8+7d/+1n9sSJXkneWyhtCzOQEIZaxMaG36o8gcgprDY23lAyLWc32vIYCTWVx2nmLbBRT4ul7HXcPe8DSek8/JO4erLl70J/38kQutFKgZCgYnLMYY/DH/11KIWelzYtsUnvLtPXElIg5E3OCYphNPFaTba+0Mz1a/mt/7a/xhV/4hbzrXe/iG77hG/jwhz98ln+8yJVRe0vbeJyHpnHU3mDNmDGiceQim9XO0TaenUU9hqkKbM0aJq2nqZVxJbLJuovcPVhxsAxgCplxFPnT99bsH3XnvTyRC82YMcPXGsYsq5BY9wEA56ye4UROkXPh9n7PU3fX3Lq74qm7K+4ddewdBir1Kb3SzqxU8Gu/9msBSClRSuHHf/zH+fEf/3Fu3LjB448//rxKB40x/J2/83ce9FJFLjxrDM4aZk3Nqo9UzrCYeCpnyUWndSKbOGfZmTfElOnDOJWzrj3XFjVeGYsiGw0pc7SOHCyHMXXEGEJIhFRY9fG8lydyoRljqCrLkBJ37w6EFKmcZXerpTrOvBKRk+0fDay7gco7drcaYsgsu8hq3bPsArO2Ou8lygNyZoGr97///fc/jJ/571IKt2/f5vbt26e+v5SiD3ORYzEVYsocrnsohpQhpMzONKGwlchm3hlyKfQh0ccMQO4judQ67RY5ReUsQ0is+gClYK1hHTKVM5DzeS9P5MIbhsy6j/RDpJhCSpl1FxliRrPXRTZbDZGQ4JFrE+p6bPBwa29NF8brSoGrq+vMAlcwBp+ez2sislk/RO4d9hwtA+64V0+mMG96Xv6wrimRTVIudEMi5oJl7CedTWHVRfUXETmFgeMgFSy7CCZDMTTOa0CIyClyKRwse5brQF07njkrWfWB/WXP9qxWnx6RDZwxODse4k+sIedCSJmFSm2vvDMLXP2f/+f/eVZ/lMiV14fEEAtt45k0ngLsH/YMJdMPkalOG0ROtO4jpRS2JhVt4zFAN6Txe0NkNtH1I3IiYyjW4D3kAmQLrmCtRSm/IpvlVFh3kTt7PW3jiKngvWHdJ7YmNTEnanumeQUil8rOomG2X/HJOyuevjceRraNYzatWEz1/HaVndkn4+OPP35Wf5TIlZcLeAfGeJy1YApNY/FYlDAicppCKeCcux/kTRliyigJWGSzXAreGCrv2JrWWGdZdxFjQEM5RTazzrDsI0frgSF5Zo3ncBVYd5GjdcIZNZcW2WR7VlM7h7OFo3XEW0s1q9meVHinrN+rTCF9kUuobRzGGNbrgRVgjlNlrTU0lS5rkU3a2lPXlrsHPd0QsMYQUmFnXtOq1ElkIwNMG8/OvKVtHKVAVVtyyNQabiCyUS7lOMhriDGyFxOGjLUGa8cJnbqKRE52uAq0leP6YspDu4WSDcUYQi6ElKgUvLqytMMVuYTaytE4w90hkrPBkKkqR1M56lqndSKbNLWjdpYYx14jpRgW04rGO9pWDzwim1TesT2vuXcU8L+un0g9r1VmK3KaDFVtCCGyHgJ9gEltqSqP95aieluRjbohctQF2nY8OLG1oevHgSHrPlFN9Rx3VZ174OrJJ5/k7t27rNdrXv7yl/Pwww+f95JELryxnMngnSOQMRicsxg7ThvUqbfIyVIqpAI5JawzlAwpJ2LOxJh1WieywaTxNE3NtO3ZX/aMySOWa1uNAlcip/DecnAU2F/13DsMVK6wdwhbs5qjZdD9R+QUMWb2jwaKAQpYAyEmam9UrX7FnUvg6iMf+Qjf933fx4/92I9x9+7d+6//2T/7Z/n6r//6Z/3sX/krf4X1es2rXvUqvuZrvuaslypyIS27wKqLFMAYsMaSS+ZgFYkhQ3PeKxS5uFZd5M7emqMuYu34oNP3mdt7Hde3J0wabb5FTpJyZt56nIPaOXLJVN5Se6dDE5FThJjYO+y4s99RiiEmMJTxtcMVQ0o0/tzzCkQurJgLMWcOVwOLaU0fC10f2J1HvFfo6io780/GH/zBH+Q7vuM7iHGc6vQMY577f2jr9Zof/MEfpGkaft/v+30sFouzWqrIhbXuA3eX3Xg6VzlKyfShMK08Qd3ZRTZa94G9o4GjdWDaVlhjWHYDqWQO1wM3tifnvUSRCyulwt2Dnn7I9DES43iAcu+w42g1MFfWlciJnskWibGwmHqsc+ScOFgGDo4ifR8VuBLZoPIGZyxb05oQ0zhoZ1LR1p4YC9TnvUJ5UM60Gc673vUu3vGOdxBCoJTCK1/5Sr78y79843v+4B/8gwAMw8CP//iPn8EqRS6+fkgcLgcOVwN7Rx37y4FVFzhYDaSUznt5IhdaSOPpXB8iXR9ZdYE+JrohkaICvyKbhJi4vb/ik3eWlFxoGsPBKnDnoOPuYX/eyxO52Mo4wZZiwBia2mKNpxRDLulZh/oi8qkKhrax1LUdA1aNHYdWOYuKBa+2MwtcPfXUU3z7t387ANvb2/yv/+v/yo/+6I/ynd/5nRvf99rXvpbHHnsMgJ/6qZ960MsUuRT6kBhCHnv1xEwKiT4k+pgZYj7v5YlcaN5CMYY+JLqQxqBVlygUvNNwA5FNhphZdoGUCn0qrLtILpllNwaCReRk1hsWE4+1cLjqefrumv2jFdbCpPV4TYYW2cg7cM5SkmHWVlTOk1PBW0NVKXB1lZ3Zp+Pf+3t/j77vMcbw1//6X+d3/I7f8bzf+9mf/dl84hOf4MMf/vADXKHI5RFzZrkaOFwPFGMxFCiGrg86rRM5hbeWtnJUzuGsxVrwlaWpPM7poUdkk1IKFktIiSkeYy0lZVIsmogmcorKO+bzhrZx7K8SOUesMcxaw/aspVWfOJGNpk3N1qSi8YZln/DWcG27ZT5rxkxGubLOLHD1Ez/xExhjeN3rXveCglYAr3jFKwD4+Mc//iCWJnLpdF2iT5lQDLWBnMdpgqsuUdTjSmQj5y3zSc31rYy1hlJg3lbMp5660qZBZJOmcscBXsPBqsdZyxAzs4mnUuBXZLMCjXMYA7U1RAzegrWGxo+DdtzZdnIRuVS8M1gLR+tIH9J4PzKGxo+vy9V1ZoGrj33sYwB87ud+7gt+73w+B+Do6OhFXZPIZRVTwVrDrHbUlcNaWC4Dxoz9r0TkZJV37CxqhpxIYcwR8c5ybVFTeT31iGxijGXeeowprLpIKoW28lTWMJ+oK67IJjFlDlaBISYwBu+gFMgpsb8KxFRQtaDIydZ95N7RwNP3lqQ0Hj4uZoGtac0j16bnvTx5gM7so3G5XAIwm81e8Hu7rgOgrvVAJAJQV+PY8WTGTXcpBl9Zpq1Dxw0im7X1mFU1DPm4vBamjSeVhmmtHYPIJtYc91kcEv2QiLlQSqEbHEkZvyIbZTL3jtash0zj7XGpbWLZF+4t1yq2FTnFwTpwe29NyuA9GAx7y8hyFVh2ia2ZMuevqjPb4e7s7ABw7969F/zeX/3VXwVgd3f3xVySyKW1M/fUlaUPiRgjQ0iknKkqz+5cAV6RTXLODDFyeDSw7ALrPrJ3NDCEQNBwA5GN+hC5tb/izmHHOiRyLhwuA/eOeu4caKqgyCYlQkqQUyEWMCWT8tg7LgdDjMqaF9nk4KjnaJUwxuC9xThLKYU7R2vWfTjv5ckDdGaBq1e84hWUUvjABz7wgt7X9z0/+ZM/iTGG3/JbfsuDWZzIJTOdVGy1FXVlcc7iDEzbmmnj72eTiMhz218G7uz1JArOOqwZb4X3DnoOVsM5r07kYlt2kdsHPeshMYTEeoiElLi733F3vzvv5YlcaNYaKm8x1lBZg7X2+J+h1kQ0kVPFWMhlnAQ9qWuayjKERMmglMWr7cxqIt74xjfyMz/zM3zgAx/gQx/6EJ/xGZ/xvN73N//m32Rvbw9jDG94wxse8CpFLgljubYzYTFvSCmDAQrc3J6w7BNzlXiLnGg9RI66QIiJrVmNMYbD1cDBMrLsFbgS2aQbIoeHPet1pKkcGIglQzYcrpRxJbKJdYZFW7M18eOzGxZjCrO2YtpWNCpXF9loa+bw3jEMkU/cPcIAlbU0jadtdP1cZWeWcfXWt76Vtm0B+JZv+RaeeuqpU9/zAz/wA3z3d383xhi2trZ4y1ve8oBXKXI5WGOpfcVi1vDI9RmPXJsxbWu8t3ijHlcim5RS6IfM3kHP7b2O23tr7u33dDGCKgVFNrKGcbBBTgwxE1Im9GPJYFCZk8hGxhgevjHl5u6MxbRhPqnYntfc3J7y6M0Z1ijrSmST6aTmxlaD85ZZ5WgrR1Ubri9amkp7oKvszMKSDz30EN/wDd/AX/trf41f/dVf5c1vfjNf/dVfzRvf+Mb7P7NcLvn5n/95fuZnfoZ3v/vd/PzP/zylFIwx/Jk/82eYTpVGIgIwbRxNbbi119FUllQKJRecbZlNddogsknjHaVkQk4crDLGQMkcX0N66BHZyIC3lgxkEiaPGSPYcWKniJzMWsPN7QmPXGu5dzSQU8E5w9a04eGdqe5BIqdovaOtHfNJRdcnvB0n3ba1xer6udLOdIf7x//4H+djH/sY/8f/8X9weHjI93zP9/A93/M9mOPThXe+8528853vvP/zpYyFqn/kj/wR3vrWt57lUkUutGnr2Z03xJg5Wgdqb5nMK65vt/evJxF5bpmCd46mchgzjlIutlB7i7W6fkQ2qayjrSpa73DO4YxhSFBVFq/AlchG1hiqyuGcJ+eBlAvGGpwfe5bqHiSyWSpgnaNyDjex477HGnIpmmx7xZ15asZf/It/kc/6rM/iO7/zO7l79+7918fNw7P/x7a9vc03f/M381Vf9VVnvUyRC80wfkAXUzCmkMvYKsEaPuU6EpFnM0BbOxrvqI/TyvtUaCqLtgwim1kH21sNdw9rqmrcNLTJ4Z1jZ66MX5FNSikcrQf6IeIseOcowNAnlquBXIrKBUU26Idxkvp8WrE1HXv93jnsCWmcGi1X17k8YXzlV34lv+/3/T7e+9738lM/9VP8wi/8Ant7e6SU2NnZ4dM+7dN4wxvewJvf/GZms9l5LFHkQjtaBe4d9uwd9EzbmpgKd/Y7po3j8ZuL816eyIXmrBknOlUe68ZDk6YwTuj02jCIbDJrG65vtewfdsQIqWQmjWPaeHa3Jue9PJELLaTMweE4wbapLCkXKms47AYOVj3DkNRgWmQDa8EUKAXuHq6xzlC5gjVjNpZcXef2ydg0DW95y1vUcF3kN2DVB9Z9Ynve0DQeQ2HvEIaQWa0jk6Y67yWKXFjejVkifQykNWAK1ll2TYN36o8gsklbW25uT7h7sCamgmGcaXB9q2V33p738kQutlw46iP3jgamtccZQyyFro8cLAOaECKymbOWkMZWKaUcB7KM4foWVHqGu9IU0he5hDJQe8tsVlF7hwFizDhriKrvFtmolIKzYIvB1QbDM6d0FmWZi5zGcGOnpQ9brEMmp8KkcbSVZTHVoYnIJs5Zuj4SQuIwZurK0odMLoU+JoyaS4tslDPkUlh1kcpbciyAIaaMLp+rTYErkUto1nhmU89qNeDmDTFk+pi4sTVlNtFlLbJJTIUQC5OmojrucZVSJuVASOmcVydysRkDW7OGgsEYyLngjMEel9+KyMlSzrS1w1vw3pIZ+yvGmKi9I+vwUWSjVDI5ZWZtTciJ2lpMLmOvuCGjopOr60V/wnjPe97zYv/KZ1FpoQhc32n55N0lh8uBj37yEOdhdz5lPquYT+rzXp7IhZZKwTuD94bZ1GMwHC0Dzjm0ZxDZzDtLUzkmtaNgcJbjQLCj9jruFtnEYKgrh3ceQ6ZkMKbgvb9/kCIiJxtiYoiZkCIGS8mFPmaGMDZtl6vrRQ9c/bk/9+fGsZQPgDFGgSsRxgefR65NSRl2FhmDYdZ6ri0aci4apyyyQeMdTeWwxhAjcDzFqa08k1oZIyKbGGOYNJ6D1cD+sifGzLTxLKaetnbnvTyRC817i7UGw7jRds4xpIw34K2lrnQNiWySYuZgNXC4DHhnSKZgMmzPGpzT/ucqeyBP6KU8vyNrY8yJP7vpeyIvdUPMgOHVj25THZ9wr7pAKhBiptHmQeREbeOZtp47B3C0HqAUfGVpG8tU147IqY7WgWUXWK4GUh6f+5qlYzapabTxFjlRSgWLwVlDBmJIGGtoKoOxYymhU6MekROFVBhCIuaMsQ4y9CFRciZExQ6ushc9cPWN3/iNG7//iU98gieeeOJ+UOqzPuuzeO1rX8vu7i6lFPb29viFX/gFfvZnfxYAay2///f/fh599NEXe6kil1ph7DXyDGMMFBirvEXkJNaAd4a68jhXMKVgLDTej98UkRMNMbF/2LN3MFB5S10Zhpi4d9TRtp6Hd6fnvUSRC6uYwhATGcP2tAYMuWRCghCyytVFThFipmQzThC0QLHUFfSpkKL6lF5lZxq4+umf/mne9ra3UUrhzW9+M9/8zd/MY4899pw/++STT/Kd3/md/MiP/Ajve9/7eOc738nrXve6F3u5IpdS5Sy1d6z7SFt7ci7ElGmr6n4Glog8txAz3lp2Fg2mZDBAMVhrCVH9EUQ2GYbEwWrgYNlTV55MxmI4WA7sLNrzXp7IhWaKIedMSol1NlhvyKmQUxn786jaRGSjnAvWQWM9i2lNypk7B2u85dkn+nLlnFkzjzt37vBN3/RNHBwc8La3vY0/+Sf/5Maff/TRR/mO7/gOXv7yl/Nd3/VdfNM3fRPvec97uHHjxhmtWOTiampHPVi6IXL3oMMaw3ziaBqnFHORU+RynGreh3H0uCmkXPDeac8gchoD+6uB2wdrnHM4C0NITGrLqovnvTqRC61QiGls+ZCzoXQZjMWQSXnsYSoiJ5u2nllbEVMml0wxsD1vxknROry/0s7sb/dd73oXt2/f5tWvfvWpQatf721vexuf9mmfxp07d3jXu971AFcocokcb65jyvQhMcQIxmjTLfI8OAfLfuDe4cDhKnC4jOztB7o+qtBW5HlY94F7hx139tc8vbdmb7/j3jKQs8o0RDYyAONAkKq2zGc1TWXwzlDICluJnGJn0XDz2pSdectiWrEzb9hdtDx8baLhBlfcmQWu3ve+92GM4U1vetMLet8z7yml8L73ve8BrU7kcumGyO29Nbf3O/ohsuojH7+95GDZEZNKnUQ2CaFQWUNTe2atY9p42onDO8hJG2+RTWLKdEMixEJKmRgioWT6ITEE3X9ENikJKm+pvGNSO0optI2nrjy19wQ1uRLZaHtW8/Ibc3a2aiaNZ9pUPHZ9xvXtKW2jydBX2Zn97X7iE58AYGdn5wW/95n3PPnkky/iikQur4PlwJN3luwvh7FJO2PfK2cMO/MG7+rzXqLIhWUMeO+Yt55CIQOL1mOtHUsHReREQ0qkkEk509YV1nmGPpBjYjUo8CuyifMG7xzOWUwpOMvY18oaaueoVeokstGsrdia1fQxsvYJbyzzWcX1rQarHldX2pkFrkIIAHzsYx97we/9+Mc//qzfIfJSd7gauLW/JsVC3Tgohf3lgPeWbkhM1R9X5ETOWXIu3D5Y03hPMYUQE49cm+mhR+QUrlhSGUudcoESEsVYSs5nl8YvckkZDM6CNYWjLoGBUgqTxoMpWE22FdkoxIy1Bmss9XEkwxtLiIW2LuOUdbmSzuwZ47HHHrtf7nd4ePi833d4eMg//+f/HGPMiRMIRV5q1kNi3UXWfSLETB8yYUgsu6CpaCKnsKawHgIpFfaWA/tHgSGOpU5KuBLZzHnDbOKpnKWtLZNJRW0Ns0lFpf4iIhvlUrBmPECZTyq2pzWLaY23BmcNWaWCIhut+sid/Y5cCt5bKm85XA/sL3u1S7nizuwR/Yu/+IsB2Nvb48/8mT9D3/envmcYBv7b//a/5d69e8/6HSIvdc4awGBswWSgQMgFZ60ae4qcYt1nvHNM2oob2xNu7kyYtzXOG7peU9FENqmcYzFtmE9rLJaSoW080+NNuIicrJRCKoa2Gu8/N3Ym3NxumbQVJUMq2niLbLLuE6s+khI4Y6AYhpBZrSMhKvB7lZ1Z4Orrvu7rWCwWAPyrf/WvePOb38wTTzzBwcHBp/zs4eEhTzzxBG9+85v5l//yXwIwn8/5uq/7urNarsiF1taOpjYMMXP7oGP/qKfxhrqyNLUaE4psknMhhIKzhmnrmTYe7y0hFJKeeUQ28s6wNauZTT3WgXdgHVxftLSt7j8imxhjaCqLtRBLoQ+JGAsWQ+0tVgW3Ihvlkln3gfUQOFoHVn1kuQ6EHCkar36lndkTxkMPPcS3f/u38/a3v52UEh/96Ef51m/9VgAeffTR+w3Y9/b2ntWEvZSC956/9Jf+Eg899NBZLVfkQqsrR+0cKQWc4zjjCprGH2djichJvDdYa1gPkVwKGBiGxO6ioXLaNIhsYozBmIIzDu8SYDDGknLB6/YjspGzhklTMWkdKUFTe/qQmDaGtq3wTheRyCbWGAyG5SpQV46cMyEXcjY4XT9X2pkejf2u3/W7+Jt/82/yF/7CX7g/ZRDGaYH/YbDqGY8++ijf9m3fxutf//qzXKrIhZZzwR73R3AWCma8blKm6DNbZKOmGic3VcfNPMngnaWqLHWtwJXIJjkXhgClZOrKY4CSCwXoo6YKimxSCmxNK25emxFDog+J+aSi9patWYXyRUQ289YyaT3WHgeqiiPkzKx1apdyxZ15TvfrX/96/vE//sf8g3/wD/hH/+gf8aEPfehTpgVWVcVnfMZn8Ht/7+/lLW95C9Pp9KyXKXKhxVRoKstDuy1t46EY9pcd3luGIcPkvFcocoEZQ9s45rMKZw0FyHkcsWwV+RXZaIiZPgRyyUzrmkIhJ+iGSNdr2y2ykYFJW/HQdgsYUip4a0gU5pMao623yEZ17Zi3FVuTmlTG/r4xZdqmAk0UvNLOpRnBZDLhq7/6q/nqr/5qhmHg4x//+P1eV1tbWzz++OPUtRp8ipyk9pbKOwqQYsGYQlN7au/xqtUQ2ahkmDSena2GSe0BQ99H2sahtrgimxnGw5M+FKyNGAwxFiBTijKuRDaxxlBXjvmkJsSMb8dNd+UtdeWwavcgslHlDFvzmm5ITJwlZ6gcTGqvdg9X3Ll30azrmle/+tXnvQyRS2U6qZg0ntv73XHGSIZsmVx3xxtxETlJ5S21d5gS2F8GKIW6sng3NscVkZNZW7DHJ9yHq4x1hhQyi1mFsbp+RE4zbfxYchsTMWWmlaf2jmmj5zeR07S1J6QyHpqkjHMwbWsmjVfg94rTJ6TIJdR4y7SpmE+Om0sXS+Ut07pSY0KRU3hnCDFxa2/N4XIgFdiaeSb1lhrjipzCGEspmRwLIafj0nVHCGPJk4hsZu04mTPERMrjhFvvLEZlTiKnstawmI594WLK9yd1Vt6d99LkAVPgSuQSysDWrGI2qYgpY63FmMK09YSYcWowLXKiISSevLPiY7dXxGEAYLnyVN7xsofmTJrqnFcocnGVUggh0cdELgVjDN0QqL0jBJUKijxflXfobiPywhnGAJYr5njSrYK+LwUKXIlcUuPpHFjL/Waexho19hQ5xe2Djk/eXTN0AVc5bBmDWU/dOeLpe9vsLjTdQOQkISaWfaSPibb2WANDNqyGyLJX4EpERB6cXAr7Rz1P3VtxsBzw1nF9t+aR3TlNpayrq0yBK5FLyFs4XA3c2l8TY8YYaGrPy27Mqba16RbZZH/Zs+oHrLM8emOcWvvU7Y5ll9lbdue8OpGLLaZCPC4LNMaQ85j1m3MmRAWuRETkwTlaDnz439/j1r2OmCPWWG7te4Yh8+mP72CVfXVlKXAlcgn1IXPnsOejt1aUlCilMGkcW9OKnOdqTiiygXcWiwWb6bpxjmAh472jtjqtE9nEWCgUjpYB6wIUQy6Ztq1wuveIiMgD9OTdJU/dWxFiYWvWEGPi7n5HUzkeuTZjMa3Pe4nygKgRjsgldOeg48nbR8QQCbEQM6z7xCdur1h24byXJ3Kh3Vi0XN9uMRj6IdCHBMawO6+5saOMRZFNWu8JMdGFyMFq4HDdc7QOhJiIOZ/38kRE5ApbriOrLrIzr1lMK3a3Wry3dH3kaDWc9/LkAVLGlcgltHc4cLQKeGe5vlOTCjx1e8XhauBgNbA9b857iSIX1vWdCa9+dAtjCnvLQCmFR65NeOXDWzx0TYErkU3WQyTEDBmayh6XCxZCzIRBgSuRF6IcDzgQkefHOYOzln5I1JWjlELJBevG6ZxydSlwJXIJlZIJKZMLHKwjORdizuNmQkQ28s7ympdvM2k8T945Ihd46FrLqx7epql0WxTZpI8RythXcTqtcMbQx0hImT7pHiTyfOwfDdw5WNMPiaZ2XFs07Cza816WyIV3Y6fl6b2au4c9qRRSLFhvub5o2V6oTPAq0xO6yCU0aT1N5elDJKcCFDAwqT2TWpe1yGnWXaKLCWvGOZwpFI7WgWmr4eQimzjj8N5Q1ZbdeYN1hcO1Yegjtddpt8hp7h50/MqT+zy9v6bvMk1tubkz4VWPFa5vKetXZJOHd6YcPhSwBg5XkcpbHt1peOWjW9Ree6CrTH+7IpfQ7rzl4WsTbu2tKblQDFxbTLh5bcKk0cZBZJOuD/zKUwd87NaSkgvGwt3Djj4WJo1XY0+RDeaTimvbU+4dDNw77MgUKmPZmtfc1FRbkY1KKTx5Z8VHnzoCW6hrRx8T//6pQ5rKjcFgq+c4kZNYa3l4d4YphsOuH9umbE2Y6eDxylPgSuQSWsxqHrsxZzGtCCFj7VjX/bIbM7zTZS2yyd3Djtt7a3LKbM0bCoXlKvD03pobuxMFrkQ2mDSeR3YnPHVnycFqgAzWWa5vT7m5q8CVyCYhZPYO19w76tma1qxjwlrDwWrg7rKjC4mpDiBFTtQNiT5EppOxMXvOhSFE1n2kqZwmq19h2uGKXEK1tzx6fcpiWpFLwRhwxjKf1lQq1RDZqA+JbkiAofYGjGFlYBgCfR/Pe3kiF1oxUHnLte0J02kFJWPxbM9qynkvTuSCK7aw6gf2lgPdEPHWkUpiPSQeWmkqtMhpQsoMQ6LylpgyZnyMI6Sx/29j3XkvUR4QBa5ELqGmcsSmwhjDEMYP7aZyzNpKJw0ip6idp/aW/dXAEGuMgfWQmdZOgV+RU3RdpBjDrPXsLmpSAmchpUIIas4usokzliFA30eWXaGylpjH57iYCpWmoolsVgrrPrEOiZLBWgixsKPpnFeeAlcil5AxhvmkovaWmMaMq7qyOPVFEDnVzqJmZ9ESU2bvaA0F2mqc6nR9qznv5YlcaMZAPyRCzEzaisobuj7Sp8SgybYiG5VcaLzBWUvrDM4ZcraEVKitJeWCOvWInCyXQi6Fg8OBaVMRUyamzKx1OKfg1VWmwJXIJVZXDu/GiYJWJw0iz0vbeF792ILKWVZ9oBRoG8crHpozbdXfSmQT5yzWGFIpdH3Ae0c3BKrK4ZTxK7JRAerGs72o2JpVkB2YzNFqoG4cOavgVmQTawzGws58PGhsakdMico7Uioocf7qUuBK5JIKMXG0jvRDxBiYtpVKBUWeB2ctO/OW2juGkACovGPaepUKipzCGsN86mkPHf2QOFwNTNuK2jnmM+WKiGzirGExqbk2b3BuDPaWMjaU3po2VJXuQSIbGcOsqfDOwvGWJ0aH1/PblafAlcglFFPm6Xtr9pY9w5AwxjBtPTe2J1zbas97eSIXXlON/azCcWlT5ayCviLPg3MGYywhJA5WPRRDSIXZNY+6s4ts5pzl4d0JB8ueu4c9MRUKcHO75eHrEyqnxtIim1TOYiwcrAacNeRSoDAePqpH3JWmwJXIJXSwHLh3sOZgFahrR46ZZRexBmYTT1Pp0hbZpJRyv09PAZIrtI1Tya3IKXKGO/tr7h31dEMGCiZant7vePRm4Mb25LyXKHKh7S5atmY1qyHTdYFJU7GYNVxbqMeiyGm8N+QMQ0x0fcJaw2Iy7nt0AHm1aXcrcgmtusjdwx7nxnpuYyDEzP4y8NCQFLgS2aCUMgZ/j3pWXSSXwrSp2F3UbM8bBa9ENlh3A6v1wBAKO1stlTMs15GujxwcBXj4vFcocrEdrsfecPPWM28roOCt5Wgd1WdR5BRDyDg3DqnamTeUUgixYDDElMcSQrmStLsVuYRCygwp4zDM2pqcC/3QMaktKalWQ2STISTuHPbsHXQ4CxjD3mFHKZmmckxb9ekROcmQCiEX6sqyPakwxuAM3D3oGWI67+WJXGgpZVZ95Ggd2Jk3eGeJOXO0HjhaB65tJbzKBUVOlHIhpcJi2twfCLLuIyHlsTm7Lp8rS4ErkUuo9pbaWbqQ2DvqyTkDBucc3itbRGSTdZ9YdQMYWMxaMGP57XIdWfVRgSuRDWpvaZwjxMTeUQcYQko4Z5g02jGIbFLKeHhycBQIIZEzWAtdyOzOEylr4y2yiTHjkIOUMs46SinElKm8xyrZ6kpT4ErkEpq1nrqy3DvsudNFnDPMJp7ZxFGrTFBko5QzOYN39v5DTuUMISY0iVxks/mkZjqpqSvP/tFwPNXJ8MjOlPlUQV+RTZwzdGE8PFl10FSePmQKmS4kKkWtRDZqKsdQO1brQEiZnAveGerKqUzwitMOV+QSKhhW68jdg46YM4ZxM9514X7arIg8t6b2NJXjcBVYdRFjxiysWetpNE5ZZKOUC9cWFZ9sPTmPGSN15WgnjoX684hsVApU1uKcxRiDsVB5S0yFyhhyzliVCoqcqKkcua2wxpByxhhD7R3T1mPUo/RKU+BK5BK6e9hxb9mRc6HxngIsu8Tdw55lF9ieaTKNyEmmjWdnXpNSYggJYwxtY9lZNMwmyhgR2aSUwqof+8GZaQOlYKzBUFj1kd3zXqDIBZZLofaWWVtReUvICW8NIVma2qtUUOR5mDTjAeQzgStlWr00KHAlcgkdHPUcrSPztqJpPBi4d9RzsA4crRS4EtnEWsO1rQl17Vl3AYBJ7ZlNKj38iJwixMQwJFZ9YHfe4r3laBVYD4n1EM97eSIXmrUGDBhrCDFj7ZhtZS0Ug0oFRZ6HUspxM/Z8P8tKz29XnwJXIpdQzIWcCslD21hygZgg50IuatIjchrnDLWz5NpDGSek6aFH5HSlwBATzlgOVwMxFxo/jiEvahInspFhLHWqK0MM470oHfdcbCuLCp1ENsulcLQO9EMixDFrvqkcs0lFUynwe5UpcCVyCW1Pa2aTir5PHKwSJWU8hUVbM9NENJGNyvFDz7qLDCFRgJAyMcNiOvZNEJHnZqyh8o5lH9lqPbW3rPpIXTmsUfBXZJNSoK091xYTnDGElHHOQCm0zTOlgroHiZykHxLrPtIPibpy5Dw+0xkz9ovTM9zVpcCVyCV0c3fCY9dn3DnsGELGOsND16Y8emPGXD16RDYaYqYfEn1ITBsPxrDuI8ZEmsrS1ro1ipykcpZcCo2DO4c9MGaNTGqP89owiGxizHi9zFtPU3uMAQp0IeGsHUsJReREIeaxzYMx9EPCmPG1ISRCzMq6usL0dC5yCc0nFZ/2sm1mdz3rIWNLYWvW8Oj1KZWmoolslFIhxEztHe64PLCpLCFmYlKpk8gmMRUqWzgaEikncgGDJaSM9twimz1T1rT2lr3DHmMhZ9iaVcdZi7qIRDaJKbNcB1IphFRwxmANOGvYWZz36uRBUuBK5BKqvGMxqYlbmT6Mm4VpWzOb1hoFK3IKY8DaMYD1jJQL5vjhR0ROZijcPRqIcbx+rDH0MeG6wHIVznl1Ihefd5aQC8tuoA+J2jsmraNSxqLIqWLOLPvEah1oGkdJhS5G2tqrR9wVp8CVyCUUUybEfLzRPp5QYwrdMD4AicjJ6spSe8cyhPt9EXIuzNvxxFtETtaHRC6FnAs3d6ZU3nC4DAwh0cV83ssTufAO14E799YcdRFKJqREuQezpqLZ0dZMZJOcCymPe6CUCgVwdsz6zRoQcqXp01HkEupDohvGfgi7i4pSYNkFvBsnbGicssjJnLXMJxXGjEHgUsaGntOm0mRBkVNkxpKMWevIpbDuE1VtySXjlLIoslHOhdt7a+4crqEYam8JodD1HbO2YnerwVndh0ROkjM4Y5hNKqwds35XXcQ7Q1Lg6kpT4ErkEkqpkFJm0niMMRgzpp7HlEm5oPbsIpvVlcN7SzzOEPGaRCPyvExqR1t7YiwcpYABYslsTTzTWocmIpvEkjnqBvaWgZuLmlIK3hZuHwys+kCMGVcrcCVyEusMIWaOVj2ZjMXivGEnNzo8ueIUuBK5hKw1OPfMGGVLKYWYMhPvtfkWeZ6sMSoNFHmB6srR1uPxyHI9kClUzmKnDdOJHitFNrHFkBMMfeZ26amcJeZCH45bQChmJbKRpbAeAncP1mPTUmPw3nJjJ2qy7RWnJwyRS6ipHG3lWXaBwzjcL3WqK6epgiIi8sDEmDGmMJ06nDOYscEITe3uN2wXkedmncEZgEI/JLJ3xJgAgzMWp8iVyEbrLhEitO3xYb0ZSwTXfWYImcrpQPKqUuBK5BKqvGU2re5nXVkMVWWZtl5TBUWep1IKKRdKAe+Mrh2R5+GZzJDKOx7enQKWIUTWXWY9pPNensiFVnJhMqlYTP395tLTpiKVxGTiyRS07RY5WRfG+8y1rZa2qSiljNlXpdD3iVmrhilXlQJXIpdUUzlqb0m5YAxq5inyAoSYWfWREMcHoMpZJo1X6aDIKaw57rMY4eAoYgykXIjH9yIROZkxhmnt2Zo2pHI8Bc1YvPXMWodBF5HIJt7b40E6luq4IbszFmeNBuxccQpciVxixhi800OOyAuRc+FoPbBcB3IZr6M1kZQLW3rwEdnIV2NZYMr5eMNt6YZE2zgFfkVOYQw4Z6g8pFCODx0z3jmssVg1lxbZaHteszXz7B0O9EOglLH37/a8pm10D7rK9HQuIiIvKX1IDCFjjGExrZlPKpy1x6+r1ElkE4thNvFsL2r6IXGw6rHWMp9UTGudh4qcxjmDs3bMrjIA4z/rIFLkdIu2ZnvaUHvDkDKQ2ZrXLGaNDk+uOD1hiIjIS8ozva3cr8us8sfjlbN6S4s8D4aSwRlDNgbvClA0EU3kFKVAyWCtY9Y6UilYM2aM5FzIuWAVwBI5UcqZ2cTz8PUZDkOmYKw9bp+S1TrlClPgSkREXlKctVTesO4TlbNgxobTtR97JIjIZusuMAyZ+bSm9paDdSCloubsIqca+8FhYGtaUdeeGCJ7R8P9nqUicrKQCgXDQzvT46mCsO7T2GsxFlx93iuUB0WBK5FLrpSiaWgiL0BdWerKE9PY6wqg8o62djRKMxfZaAgJay3TmWfqK0LO7M4b1n2gKGVR5BQGb83YJ64U1l0AA5PGU3lH0SUkspFh7BWXy1h2C5BLwRqjwO8Vp8CVyCUVU2bdR0LMWGuovaVt/Hj6ICInMsawmFT3ywNLgcpbJo1TY1yRU1hrsNbQd5FgEzFkXGWpnX1W+a2IfCpjYDqpmHaRTKHkgrEG4w3T1useJHKKurK0tWPVRWKy5DKWqntnqbzuQVeZAlcil1BMmcPVwKqLDDFjDbS1J+XCYqocWZHTWGuYtdV5L0Pk0mlrx2o98Ml7a1ZdxJqx58jjN2fkpFJBkU2MMdTO4ivLwVFHiuA8bM1aKu90+ChyiqZyDJXjaB25e9jhjGFn3jCfVKpAueIUuBK5hPqQOFoF1kPEO0sqsH/UY+wYwNKJg4iIPAh9SKy7RNcNpAypjFkky1Vg1cfzXp7IhZcBU8A7R+UNOWegUFQnKHKqlDMHy4Gj1cCyC3hn8G7MWNyeq93DVabAlcgl1A+J/VUPxTCE8YEnFzhcBramNRUKXImIyItvuQ7sr3pCzHjvxt4iFg7Xgf1lOO/liVxouZTjPnGGh3enGGMoFFbd2Poh56JyQZEN9o8G9pY9XUhszRpiLNw77HHeMp14Kqfg1VWl3a3IJRRTJsZxbPJsUjFpKrohEVMmpXzeyxMRkSuq5Mz+cuBwFYmpYLCsu8hyHThaKXAlstHYjodSxi9DyvcbspdSKCjrSmSTbhizfndmDdPWszWv8N7S9ZF1r3L1q0wZVyKXkLMWZw2lFFZ9oGSovb3fNFdEROSBsJaSIedCSImYx4OU8Vu6/4hsYq3BOEPXB5bdgDWWXDL2eGiIelyJbPZMaDf/utLa8UuDrp6rTYErkUuoqR2LaUUfM96OiZN9SCwmFc4qkVJERB4MZwyzacVs4nHGAAZTWbyzNI1KNEROY0oh5sLeYUcuBkNhZ96Ova8UuBLZaNaM95/95cA0+uMS28y09UwbhTauMv3tilxCTWXZmjYcrQdiHk8cduY1k7ZSY3YREXlg6spybatl76inrS0Gw5AyjXdsT5vzXp7IhZZLoQ+JfkhU3jGkTO0dISZCSOpxJXKKrVlFFyY429MPkcobtmct1xYtzmkPdJUpcCVyCVXeMZuAc4aQMhaDryyz1uu0TkREHpi68lzfbtg/aln1gVRg1ni25w3XFvV5L0/kYiuw6iJH60jTOCaVIxU4WA9s9/VYNogyF0VO4pzl4WsTFhNPHzLWwrT1NJXCGled/oZFLqmmdtSVJR1nXHmdMoiIyAPmvWV71rC7aHDWkDNU3nBje8Kkrc57eSIXXjdk+hCAQqk9wxDph8R6UGNpkefDGsN8WjM/74XImVLgSuQSM8bgnTKsRETkbDxTymSNofLj4UnlHcaqMa7IaTIFZwsGQ11ZoFB7SwjHw3WKriIRkeeiwJWIiIiIPC8pF+4d9OwfRZb9QC7Q1An2DA/vTNieq8+VyEkshmlT3b9OjDUUm9ma18waj6K/IiLPTYErEREREXleQkzcO+i4tb9ke15Re8/BaiCENXcPJzx6Q8UbIiex1jCb1Sy6QC4FZy05F4yBxaTGqTG7iMhzUuBK5BIrpZCOH3icVY8rERF5sIaQWPURY6EfMv0wQCms+0zX5/NensiFN208D+1MOVwPhJBoW898UjFtKw3YERE5gQJXIpfUuo/sH/Wsh4Q140SN3UWDd5pGI/J8DCExxHGjXXlL7a02DSKnMIAxheU64qeGgiHETCkZY8p5L0/kwmsqh51BVR1nW1lDWznqSs9vIiInUeBK5BLqh8RTd1fcPexIadx4T9qKEAuPXp9q8y1yimUXWPeRIYxTnCrvmDSeWet1/Yhs0NaOWIBSuHvQY5whpsz2tB6bS4vICzIGg897FSIiF5sCVyKX0MFqYO+oI+fCtK3IGQ5XA423rPuaqUaSi5woxMS6j6y6SF05DLDqIjBmXjU69RY5UcqFeePAgK8MFPDe4gw0tR4rRU4zhMTRKnC0HgipUDnDbFIxn9Q0te4/IiLPRU8YIpdQP0QOloG28ay6iDGGGAuH64EhZqbnvUCRCyzEwhASpRTCcamgMTCESIhegSuRjQwxwWJS0YVMyeBdoaodOalUUOQ0qz5ya39NKeAsrCNj2wdrqCuVrIuIPBcFrkQuoZyhlMzhamBnXpNy5mgdaGuL1QOPyKnWfaQLCXM8e7wAtTNsz7XxFtkkl4K1hpgLj+xOqLznYNmTS0FxK5HNci4crQZWfaRyllIMKRdizByuAotpjXd6jhN5PlLOGGO093mJUOBK5BKqa4v3jvVq4PZeRwG8HcucKq/pgiKbGFMoGY5WgVlbYQwcdYGdWUPRxltkI2sMdeW4vjXBAH2ITBtHwtBU2jyIbFIoDDEzDJH59pTKG1Iq3O7WhKSpnCLPxxAS6yGRYgYDdeWYtl4BrCtOgSuRS2jaeNrak2KmTwljoHae+bRWg0+RU5RicN6yM2s4TrhiZ9bgnFGJhsgpnLNcW7TcO+ypnMEVKKUwazyLaXPeyxO50AyG2jsq7+iHSExjxlXlLZUyrUROFWJm/2jg3lFHiAVrx8nqubRsTevzXp48QApciVxCKRfaxtEPlrb1kAsZxnRZJVyJbGTMOBnNO4N3llKOy5+MJjuJnGbSeJyzLCYVB8thvOcUw3xSUyvjV2Qjaw2ziWe69pRisAaw43W1mNQ4TeYU2WjVR+4crBhixlpLSrB32GONYVJ7VZ5cYQpciVxC1hpiTFTeEY4/uK0BU8b+VyJysspbamfZP+qJx015nDXc2Gm18RY5RYiZrannbu3YdQ05gassbW2pNdhA5FTTpuLmzoT95cAwJOrKsD1vmbReWb8ip1h1kWWXaGrPtHHkXNhfJlbrSAhJgasrTIGrCybGyHd/93fz//6//y+//Mu/zN27d8k58/jjj/MlX/Il/Nf/9X/N7u7ueS9TzlmIeaxwKoZJ6ygFYszEnNWjR+QUzhrWIbF/NLC/6imlsD1rmLaeG9uT816eyIVWSmEdMrO2IpdMTFD5MV1xCOm8lydy4dWVxXYGZw1VNWb/muPecSKyWSllnMhpxoN8jKEc/1/WHuhKU0jygun7nne+853823/7b3n44Yd505vexOtf/3oODg74vu/7Pt7ylrfw5JNPnvcy5ZyVAhiDrwyzpmbaVBj7zHw0Edlk3Uf2DjsO1mNqubOWg+XYL+FoHc57eSIXWqGQY+FoFTDGMqkdIYxT0aKaS4ucat1HhpQBQ1M7wBBjZtXF816ayIXX1uN9p4+Jo3Vg1QWcMdS1p64U2rjKlHF1wTRNw9/7e3+P3/bbfhve/9pfzzAM/Hf/3X/Hj/zIj/BX/+pf5X/+n//nc1ylnLfaWxrvgUJIEWsM87airpx69Iic4mgd2D8aMBh25i0AB6uB/aOBg6OBhZp7ipzIMJ5uYwr7RwMplXHSrQWr5tIiG5VS6EOi7yOz455WOReWXaDylqzJaCIbzdqanUVi76gHoADzSc3urFaZ4BWnv90LxnvP533e5z0raAVQ1zV/+k//aQDe//73n8fS5AKpvKVtHEPK5AIhjWWCk9bhnS5rkU2GMGaGeGdp6vE/lbOkPF5HIrKZMWM/xbZ2LGYVhrEEt+jyEdmoFCgZCuZ+I3Z7/N+lFLJqnUQ2amrH7qLhkWtTdrcabu5MeGh3wmJWq0fcFaeMq0vkmWBWXSsb4KXOWUMpEEImHj/kTBtHTGgijcgppo2naTx7hz2Hy4AxsO4Ds2lFU+u2KLKJMYwlgm1F5QzGmuMePShTROQUxoBz4zTBfkjUlSXEMeLrndUznMjzMG0rmtoRY8GY8UBfQaurT0/ojGV4H/7wh/ngBz/IBz/4QX72Z3+WX/qlXyKlscno3/27f5cv/MIvfN6/b71e80M/9EP803/6T/mVX/kVVqsVDz30EJ//+Z/Pf/lf/pd89md/9gteY4yRd77znQD8p//pf/qC3y9XS0gF5ww7iwbvLKUUhpjx1hBiVoNPkQ0Ws5obWy0hJoaUMGUcRX5ja8LOXAcDIpuUAtPGcriClAvlOHvRWav+IiKnMMbQ1p6YMus+0oWIt4Zp62lqp823yPPkrMXpke0lRYEr4Ku+6qv40Ic+9KL8rl/6pV/ibW97Gx/5yEee9fpHP/pRPvrRj/Ke97yHP/En/gRvf/vbT/1d73jHOzg6OuLg4IAPfehDfPKTn+R1r3vd83qvXG05FyiwNa1xx6WB6z6SSyFrrKDIRpW3PHJ9Sls7DpbD2B9hWnNt0dAo6CuykfeWmMd7zXjabYgpMZ8oaCXyfIwBqprKO1IuODs2adf9R0TkZApcwf3Mqmc8+uijxBi5devWC/o9d+/e5Y/9sT/Gxz72MQB++2//7bz5zW9ma2uLD33oQ/zv//v/znK55Lu/+7vZ2tri67/+6zf+vve+973cvn37/j9/wRd8Ad/+7d/O1tbWC1qXXD3OGZyzDDHTHpcNxpSZVl5p5iLPw3xSU3vH7lZLKWMwq1aqucipci44Y/HW0bRjiWDKBaN7j8jzVldO2fEiIi+AKUXpGX/pL/0lFosFn/mZn8lnfdZncf36df7cn/tzPPHEE8DzLxX8H/6H/4G///f/PjBmcf2P/+P/+KxN0L/7d/+OP/yH/zD7+/vUdc0/+2f/jEcfffTU33vr1i1+5md+hv/lf/lfuHPnDu985zt5/etf/xv8t/2Pc/fukqRx1+cupszBamDdRWIqGApN7Zm0ni1NRBMRkQdkCOM0p9UQybmQU6GuLLnAzrxhZ96c9xJFRETkHDlnuXZt9qL+TuV1A3/+z/95vvEbv5Ev/uIv5vr167+h3/H000/z7ne/G4CXvexl/IW/8Bc+5eT+N/2m38S3fMu3AGNfre/7vu97Xr/75s2b/J7f83v4/u//fkopfOu3fivDMPyG1ilXg3eWxaRmMatZTCsWs5r5tGI+qc57aSIicoVZa4i5cPvumnv7HfcOe27trVmuA0q6EhGRBy2XwrqPHK0Dyy7cH3AgV5sCVy+S973vfYQQAPhDf+gPnTj57y1veQuLxQKAf/pP/ykvJOHt5S9/OZ/92Z/NJz7xCf6//+//+49ftFxqzhkqZ/He4t1Y5qSJTiIi8iA5a1guB5brgU/eW3Nnv+Opux2rLjIEbR5EROTByaVwuAocrAb2j3r2j3oOlj3rPp730uQBU+DqRfKv//W/vv/1G9/4xhN/rmkaXve61wFjCeCHP/zhF/TnTCYTAO7du/cbWKVcFbkUjo4/tA+XA4ergf3lwKrTh7aIiDw4/RBJBYyzPH5jyiM3JtzYaYkp0+vUW0REHqCuT6z7wBAy1XFv0uU6jEOq8ku+A9KVpsDVi+QXf/EXAfDe89rXvnbjz37mZ37m/a9/6Zd+6Xn/GV3X8bM/+7MAvOIVr/gNrFKuin5IrPtIPyQq77DGsuoiXR9JWRsHERF5MGIqlFJYTCpmk4ZpXbE7r7HGqAemiIg8UCFlQshMakflHW3tcc6Or+sedKVpquCLIOfMRz/6UQAefvhhnNs8JeSxxx67//Wv/MqvPOt7/+Jf/AvquuaLvuiLnvX6/v4+/9P/9D9x69Ytfvtv/+288pWvfHEWL5dSSJkhJiaNx7sx/pxLGT+0Y8bVikmLiMiLr64c3lkOlgNDzFhjGGLCW0flde8REZEHxxz/v1+fW1WeeV2uNAWuXgTL5ZKUEgA7Ozun/vyv/5nDw8Nnfe9DH/oQ3/Vd38Wjjz7Ka1/7WmazGU8//TQf+tCHWC6XPPbYY/zlv/yXX8zlvyBbW+25/dnya2zlwFna49MGAL8OVM6yu9XQ1rq0RUTkwTjoIrcOOz55bw0F6tryiocnPPbQgh09J4g8LyFmci5Yy/1nORHZrJ3W1JOKro80tSOlwryybE1rdhctVlNCriztbl8Eq9Xq/tdNc/oY6Lb9tYe6X/9egC/7si/j8PCQn/7pn+b/+X/+Hw4ODphMJrzmNa/hS77kS/iar/ka5vP5i7f4F8jrxnohTCc1IRWWXaBgyLlgMEzaiklb4/ShLbJROZ5I80wz6bqytLXXA4/IKULMZAMhJKyz5FSwBoaQiOg5QeQ0ORcOVwPDkAg5462lqQvzqZ7fRE4zd5ZcoK48XR+pKsu8atia19SV7j9XmQJXLzLzPKa6bZok+NrXvpZv/dZvfTGX9KKKMZ33EgTwFmpvybUjhIQxhknjmNSOkjPqjytysnI8kWbZBfohUoCmckzbiq1preCVyAbL1cBTt5esusi08UAhlsTtg45bd1bcUMaVyEZHq4GD1cC6j1hjyKUwqT0pZbZmzz2VXER+jbcwDIFVF/DW0FYWU4r2qRfMi32QpcDVi2A6nd7/uuu6U3++7/vnfO9lcHDQqfnqRRITJheggIXVsme1PO9FiVxsQ0jsL8dNw6QZb4MH+x1t7VjPapXaimywd9Dx1K1Dnr675NrWBGsKqz7RD4mbi4ZHdhS4EjlJLoV7Bx2399Y4a0ml4Kwh5cKN7ZbQqdRJZJMQM0/dXXFnf806RJwxbM8abu5M2NXByYXhnOXatdmL+jv1dP4imM1mOOdIKbG3t3fqz//6n1ksFg9uYXLlVd5R6SoWeUFiKoSYqb27P9ygrR0hZmLSKGWRjex4DeUCqz7i7dicPZdC3pBRLiJAgXUX2TsaiKVgxpdwxjBtHNvzBqs20yIn2j/qefLOkqMuUDtHyJnlegkUZpNK5YJXmMa/vAistbz85S8H4KmnnrrfqP0kn/jEJ+5//apXvepBLk1ERP4Dxoz/yaVQciHnTMoFYwzPo9pb5CXNO8t04vGVhVIIKWEKzFpPW2vDILKJMbAcIgfrnn5IWGMIIXO46ll1UfcgkVPsLwf2lx3OGJra0TaeISb2lgPrIZ738uQBUuDqRfKbftNvAiDGyIc//OGNP/uzP/uz97/+9E//9Ae6LhEReba6sjhn2F/2fPLeiqfurrl32GMt1GosLbJR5SyLSU1lDd2QWfcJSqH2nh315xHZKOeCyQWLZdI4cs40tT3udQUpK2tRZJOUCjGNvUmb2tLUhnL/dV0/V5kCVy+SN7zhDfe//omf+IkTf67ve376p38agJs3b/Kbf/NvfuBrExGRX2OMwRQwFPoh0YdIoVAKWN0VRTZyzmCdoXKWprbMJxXGWpp23HiLyGZ17XF2zPrluDm7s4a6MioSFDlF23omtWPVBw5Xgf3lgGXMvnqmb6lcTXpEf5F86Zd+Kd6PF8sP/dAPMQzDc/7ce97zHg4PDwH43b/7dz+vKYQiIvLiGUIiA5O25tHrUx65PmNrMmaK9IOGT4hsEmLGlMLWvOHxmzMe3p3w6PUptXPKFhE5hbUGYwzOW5arQDdEVuuAdWCMvd93UUSe2+684cZ2i/eOGDMUw9a04ub2hFb9ra40fTq+SB5++GG+4iu+AoCPfexjfNu3fRvlP2hS+u/+3b/jr/yVvwJAVVX80T/6R898nSIiL3U5F1LKx2nmnrb2NLUnZzWXFjlNSgXvHU3lqJzFGEPbeKy1OowTeR7a2jFpHItZTVs75tOaSeWZNB7dgUQ2m7Wem9dmXFvUNLVj2jgeujbh+rYmcl51yqcDfu7nfo4f/dEf/ZTXnvHDP/zD/Ot//a+f9f1v/uZv/pTf8/a3v52f+Imf4OMf/zjvete7+PCHP8yb3/xmFosFP/dzP8cP/dAPsVwuAfimb/omHn/88QfwbyMvJbkUUioYg07pRJ4naw3OWYaQqf143YSYxtf10COyUV07UszsH/U4Y4FMyjCbem0aRE5RytgnbnvW0lSOmPLYoP3/b+/O4+Qq63yPf5/nLFXV1Z2FQJAEBpAlILtiQMCLkjDOBIJMlCFsM4BCEEYRGV+A6B3uOCNch1VwuzNeFfBqEEmirA57IiCgyB6JSCAkEAJZOt21nXOe5/5RSZlA0l2B7lR15/N+vWJOVZ06/StidZ3zref5PVn988g5LxvwPgI2pn7tk6lSzVSupgoDqyRxjPjdAhj/9mFBW6BbbrlFF1100SY9Z2MN2F988UWdffbZWrhw4QYft9bqzDPP3GDwNRQsX96rLGMqTTuo1FKVq6nSNcFVHAbqyIcEWEA/nPda3VtTbyVRktY/AsPAqCMfakQxVkCjK2Cj0szpuZeWa+Hr3arWssYqaKNHxNpzxzEat3VnawsE2pj3Xqt6a+rurSkfhwoCI+e8ypVEXcVYIztzsoxcBDZqxeqy/vTqKvVUEnknyUthaLXdmA7tPG4k10FtIgisttqqOKDHZMTVANtll100e/ZszZw5U3fccYcWLlyoUqmkbbbZRhMnTtT06dO1//77t7pMDHFJmqm3nKi38pdlX2tBJu+9RhRjpmsAfbDGqFiIZK1RkrrGSU9HPiS0AvpRSzJFgdSRC9RVjOSck7WBrPE0Zwf6YYxRLqo3kS5X15zDea9CPlIuCgmtgH6sWF3VqlJVoQk0siunLHN6q7uslT01laqJRnTkWl0iBgkjrrBJGHHVHnrKiZZ3l5Wkvt7oU1ItdRrZGWl0Z14xzQmBprg1V9pMcQKa01tOtODVFVq2qqxcHMk7JyOj1Dnt9L6Rev+4Ea0uEWh75WqqapLJZV7GSvk4VD4O+OIR6McfX1mhl17r1uiuvDrygbz3ev2tsoodofbYYSuNGZlvdYkQI64ArJEkmVb31uSNkfdeRvW/e8rSyCLfNADNSNJMtbQexIeBVRzSXBroTxAYeS/1llIlNa8gNKpUUxXyoWjNAzSnkKsHVc57WWP47AGalIsDxZFVuZLImL8sqlOIAsUh76PhjOAKGIJS55Q6L+e8RnbGypy0vLtcPwliQBzQr95KonI1VS3JJElxFCgfhyrmQy4ggD4YrQl6c/Um7VliZQOj0BoFXDQATTPGKODzBtgkW3Xl1T2ypjdXllQup0oldeRDbTWioGIhanV5GEQEV8AQFFirIDAKA6PeSiIjqSMfyVorWvQAfUtSp0o1VamSKg4DyUi95bS+2lNolWOqLbBRzku5yKorH6sjF8h7ycnLe8kYPoAAAINnRDHWuDFFdeRC9VYTRdaoqyOnbUYXZLkIGtYIroAhKI4CjeiIlaROQWAl75WkXp0dNPYE+pOkTrXU1UOqOFjn/kxJ6giugD4E1sgGVlFkVU0yyUhWRkEYKGauINCUWpKpkmTKMq/AGuXigM8eoElbjcgrDI2KlUhBYDSyGCkXE2sMd/wLA0NQLrIq5iP1VlIZU19KuVgwyseRopBvGwAAgyMMrEJrVK2mqqaZjIzkpTGjDMuQA02o1jL1lGuq1DKlmVNgjfJpKF+IlOfiG+iTc17dpZp6SokqNSdrJS+vEd6okOP9M5zxrwsMQVEYqLMQKwis0szJrLmvg/48QL/iqN6IvbeSSqovR56kTh35UDHBL9An570y52UCozCzcvIKA6Mk9XKeJotAfyq1+lT1KAxUyIWqpa5+O6hPVec8Dti4cjXRW6vKKlUz1d8pXr2VRN5LuShglehhjOAKGKLWrqqRZl7GiG+6gSaFgVUhV2/gWUudvK839izkQsVM1QD6lKZOznm51MlYo/onj1fmpEriW1wd0N6c88oyX+8Vt2aqei4KVEvqo68yVw+CAWxYTzlVTzmRjFEhCpU5r1K1ptW9NY3szKnAqMVhi39ZYAgzxihiFSdgk3XkQ0WhVZLWR4hEoVEUEloB/fHea1VvVW91V2UkeUnWGEVRovFjiq0uD2hrxkgyklF95GJg6+0e6o8ZRosA/Ugzp1riNKIYK47rX530Vo3SzCtNnRS3uEAMGoIrAMAWKQotPeGATWWk7p6aunuqiqJAxkq1NFMhCrW6krS6OqCtGWOUjwMlWajecqIwqF9w5+NAcRSwwA7QjzCst3uo1DJJ9enrxktBaBRyTjesEVwBAACgKZVaKm+kIDDK5wJZaxUYIy+nLKPHFdCfQi6U81JkrTLvVIit4rjepxRA3zrzkbqK9QWq0szJe69cZDWyI6ccI+eHNX5DAgAAoClG9VUFw7D+dyVNlYsCVRMpYJoT0C9jjOLQKsmcfFqfPhiFltFWQBMK+VBjRnYoF9dUqWay1qgzH6qrGDPVdpgjuAIAAEBT8rn6BXZPuaaeUqoglFYmVY3qzDH1FmhCNcnUU6qpUqs3ZK9ZI+e9fCFSnsbSQJ+sMerqiJRbZ4GqOAz4/NkC8NsRAAAATTEy8pJCK1WSTFlS7zZtjMTitkD/KtVUpWqqKAiUz4VKUqfeSqowsMpFgQwjr4A+WWMIebdA/IsDAACgKeVapiiyKnbkNSaycl6S8zLWKs1aXR3Q3pzzyjIv56Rcod6PJxcFqiX10VeZ8woDgisAeDuCKwAAADTFGilJ3Jo+V4Gsrd/OnBe92YF+mDV/5JU5r8AaOefrDxlDjx4A2AiCKwAAADQlDq3ycSjnvSJrFYZWSVJTFBrlY+YKAn2xxigXB0qyUL3lRGFglGZeudgqjgIatAPARhBcAQAAoCnGWo0oxtp2VFGVJFU1zdY0yg3VmY9aXR7Q9gq5UN5LkbVKnVM+NoqjQB15LssAYGP4DQkAAICmBNZo61F5ZVl9epOXlzdSRxyqUCC4AvpjjVFnIVIaB3LOy1qjkJUNAKBPBFcAAABoSn3ls1BjRuVVS5y897LGqCMfKh8FrS4PGDLCwEq8ZQCgKQRXAAAAaFqxEMkYo1qYyXuvMKj3vYoJrgAAwCAguAIAAEDT1k51crl6k/bAGhmaSgMAgEFCcAUAAIBNZq2RFYEVAAAYXARXAIAtUi3JVEudJCkKreLQMmoEAAAAaDMEVwCALU5vJVG5mqqWZPJeiqNAhVyoYj4kvAIAAADaCMEVAGCLkqSZytVUpUqqOApkJJUqqaT6yKscDaaBfpVrqUrlVM47xWGgzo5IgbWtLgsAAAxDBFcAgC1KknolqXtHSJWkmZLUEVwB/VhdqmnZipJ6Koky55WPAnUVc9p2dEFRyPsHAAAMLL4aAwBs8fyav5klCPQty5ze6q7ore6qnDeKw1A95VQrV1e0qrfW6vIAAMAwxIgrAMAWJY6scmGgnkoiqT5FMEmdOvKhooDvc4C+VGqpKtVUxhqN6owlSXFotWJ1VeVq1uLqAADAcERwBQDYooSBVSFf//irpvUL7WI+VD4XKmaaINCPNcMSvW/c49f8r5Hf0BMAAADeE4IrAMAWp5ALFYVWSerkfb0pexQy2groTz4OlM+FWl1KtKK7qjCwKlcTdeQj5XOcVgIAgIHHGQYAYIsUBlYhUwOBTRIEVqO7cipVEq1cXVWaORVykYr5oDF1EAAAYCARXAEAAKBp1hh1FSJlmZdzUhwZFTsiOSeJ2bYAAGCAEVwBAACgKWnmVEsypc5rdFde1kpJ5lStOVXijD5xAABgwBFcAQAAoCnOeZWrqcrVTDXr5L1XYI1qmVcxH7W6PAAAMAwRXAEAAKA5RqqmTqt7q8rlAgXWanU5VRRYJWtW6QQAYLBlzskYI2tMq0vBZkBwBQAAgOZ4yTlXnx7Y6+SdURBILpS4dgA2jfOei25gE9WSTOVapix1kpHiKFBHPuS9NMwRXAEAAKAp3nsZGVVrTs47eS+Z1CowRs5x0QA0o1rLVEkyZZlTYI1ycaB8zGUZ0J8kdeopJeqtJnKu/oVJnGZy3mtEByvbDmf8hgQAAEBzjNRTrqm3mkjeyzvJWC8vpyRjqiDQn0otVU85UbmSynnJGqmQhfJeKuS4NAP6Uk0yVZJUYWCVL4Ryzqu3kigMMiWpUxTaVpeIQcK/LAAAAJqSZU61xClNnKIwVCEfycgqSVPVEoIroC/ee1VrmcqVVHEUaEQxVi4OVaqkqiaZvPetLhFoa5nzSjOvKKyvYGutURhYZZmXc7x/hjOCKwAAADQlzeoXBoVcqJGdkbqKkbqKsUIbKMu4aAD64r3qF9i+3pdHUmOESJY5ZVx4A30KrFFgTWMxEOe90swpCIysZbr6cMZ4VAAAADQlsFaFfKhcJVBgrJz3ykWBjAw9eoB+GCMZKxn5en+rwCpzvt47znDhDfQnF1kV4lC91USrSzVJ9fA3jgKmCQ5znGEAAACgKYV8qK5CrOWrKlpZqsrKyDmvsaML6uyIWl0e0NaMMcpFoZKcU6mayhgj773yuVC5OGBVNKAfURio2CEFoVWaZjLG1FcVpD/csMe/MAAAAJpijVEhF6hYiOXLNTlXH3GVjwMaSwNNKOQCSZHCoD5i0Zr6qoJceAPNyUWB4tDK+bA+UpHAd4vAb0gAAAA0JV0zvWnMyJy2HpmTZCTjZI1VkjoVcq2uEGhvxhh15CPl41CZ8wosUwSBTWWMUUBgtUUhuAIAAEBTnKuv3BSHoTry9dNI5716SzU5VkQDmmYJrACgaXQwAwAAQFOsNQqtVZo5ZZmT9161JFMQWAVchAMAgEHAiCsAAAA0JQys4jhQwdWbSzvvFQVWhVzIqoIAAGBQcIYBDGHeeznvZcRwcwDA5lHMh7LGKI4yZZlTFAYq5FiKHAAADA6CK2CIqiWZyrWssRRsFFoV8xEBFgBg0BkjGdX/iI8dAAAwiAiugCEoSZ16Sol6q4m8l7yX4sjKe6mrI5JhlQ0AwCDpKSdasbqinnIq55xyUaiRXbFGd+YZdQUAAAYcwRUwBFWTTJUkVRhY5eOwvqJTOVE1yVTIAkVh0OoSAQDDUJo5dfdUtby7Ji8neSlJa0oypyiwGt2Vb3WJAABgmOFrMWAIcs4ry+oNcSXJGqMwsMqcU+ZYjhwAMDiSNFNPJdHqUlXerb3PaWVPVaVq1triAADAsERwBQxB1hoFgVEtrV81OO+VZk4hy5EDAAaRc1JPNVWllqmaZKplXpVaqkotUbVGcAUAAAYeUwWBISgfB6oloUqVRN29NRkjRaFVHAYKA/JoAMDgMMbIqv6FiZNXIC/nJHkjI0b8AgCAgUdwBQxBYWDV1REpDKzS1ElGiqNAHbmQxuwAgEETBkZdhVjlSirJKHNecWQVBkYd+ajV5QEAgGGI4AoYoqKw3oTdOS+Zep8rAAAGk7VGI4s51RInayQvycsrFwXqyHNaCQAABh5nGMAQZ+lpBQDYTMLAqpAPtfWovHrKiTLnlY8CFQuR8jGnlQAAYOBxhgEAAICmFfOhrDGKo0AucwqjQIU4UBTSYxEAAAw8gitgiHKuvpJTknkZI8WhVS4K6HEFABh0xkhm7Ub9nhZWAwAAhjOCK2AIcs5rdammUjVVmjoZI+XiUGnOq7NAc1wAwODpraQqVxOVq5mc94rWLBTS1REz6goAAAw4gitgCKrUMpWqqTLnVciFcl4qV1NZI+XjQGHAhQMAYOBlzqlWy1SuZopCK2ukJK2PAI4jpgsCAAaf817ZmlknXPdsGQiugCEozZzSNJOxRtUka8zUSDKnNHP8AgcADIos86qmmcrVVElq5b2XMUZZlqkjz4hfAMDgKldTVWqp0szLGimKAhXzoQLL9c9wRnAFDEFeXqVKfYqGVG8xkmZeI4oRPa4AAIPGGKNqLdPqUqJcHCgMjKrVTEEgJYlrdXkAgGGslmTqrSQqlRMZa+WcV5Rk8l4a0cF10HBGcAUMRV5KvdOKVVXFkVXmvOTXrPTElw0AgEHktaYVu/dy3kjGS8bSnx0AMKiqSaZqLVMch8pFgbz36iknStJMaRYoCoNWl4hBQnAFDEHe1L/ZjiOrJPOyxsgEvjHfO+J3NgBgEHjvVYgDdRYjRYGV91IhDpRmXjH9rQAAg8h5KXNeubj+eWOMURhYZZmXY9DvsEZwBQxBtVomI68oDNTZUb9wKFUSpfzSBgAMoiAwiqNAhTiUMb7+TYqR8rFRQH9FAMAgCqxRGBjVkkz5OJBzXknqlCuECgKG/Q5nBFfAEGSMZKyRdVJoAznvZRpzBH1LawMADF+BtQoDo95KohXdVTnnlc+F2mZ0XvmY4b4AgMGTjwPVklDlaqruUk1WUj4XKheHLE41zBFcAUNQLgqUjyN5eTlXXwq2IxeqmGNFDQDA4OopJyqVa+opVSVjlLhMI/KhKtVUnR1xq8sDAAxTYWDV1RErCq2S1MlaozgMVMjxxclwR3AFDEFxFGh0V6zu3ppsYOXllbNGxY5IET1GAACDpFxN1b26omWrqspHobRmVdvXVpRULEYEVwCAQRWFVlEYy3vPKoJbEIIrYAjKRYHSXH3J1yR1ssYoCq068pGs5Rc4AGBwpGmmZd1V9ZYTZc4pMEa1zCnLnLpLHRrf6gIBAFsEQqstC8EVMAQZY9RZiOoBVlbvxh5HlmmCAIBBlTmvNHWq1FKNGZlXHFmtWFVVJXWq1lgdBAAADDyCK2AIqw+VJawCAGweYWAVxYE6O2J1l2r1qRoyysUhPUYAAMCg4IoXAAAATYmjQGNG5mStkfVSYKyMNRrZEWtEkf5WAABg4BFcAQAAoClxFCgXhhrVGcmGVtZK8ZpVnvKMuAIAAIOAqYIAAABoSpI6dXZEGt1Z0OhOL+e9AhMoiowCw/ehAABg4BFcAQAAoCnee8lLo7tyysdh/bakUiVpbAMAAAwkvhoDAABAU4LAKAysMueVOS9jjWqpUxhaBQGnlQAAYOAx4goAAABNCaxVPg6UOa9KLZWrekWhVT4XKh/T4woAAAw8gisAAAA0rSMfyVqjOArkvVcY1MOskBFXAABgEBBcAQAAYJPk41D5uNVVAACALQFfjQEAAGCTOeeVZo6m7AAAYFAx4goAsMXx3quaZKqlTpIUBVa5OJA1psWVAe3Pea9SJVUtyeS8b7x/8jGnlQAAYOBxhgEA2KJ479VTTlSpparWMnlJcRSokIbq6ohkCK+APvWWE/VWEtWSevBrJHVkoayp970CAAAYSARXAIAtSpI6VZNM5WqmfBzKGKlcTWUkxZFl1AjQhzRzqiWZqjWnzkK9SXs1yVSpZYqijOAKAAAMOM7OAQBblDTzqiVOcRgoCuutHvNxoCR1SjN69QB9cc4rc/WVBK2tj06MQqtaLZVzvH8AAMDAozk7AGCLYkz9j1unoXTmvIwxYpYg0DdrjQJrlGZO2ZqgqpZkCgKrwPIGAgAAA48RVwCALUoUWuWiQD3lRKVKIskoyzIVC5HikGlOQF/CwCoXh0ozr1K5Ji8ja6ViLlI+5v0DAAAGHsEVAGCLEgZWxXwkSUoyJ3mpkItVyIWNqYMANq4jX+8NF4VW8lIQWuXjQBHBLwAAGAQEVwCALU4urve3SlInL68otAosoRXQDGuMivlIcWiVZV5xFDT6XQEAAAw0gisAwBbJWqMcU5uATZY5p95yqlqayXuvoFpfjbMjz2klAAAYeJxhAAAAoGm95VQ95ZqqiasvaOC9nPeyVsrHnFoCAICBxbwIAAAANCVJnSq1VKt6a3LOK8u8ksxpZU9VtcS1ujwAADAM8bUYAAAAmuK9V085UbWWKcu8jJWyzEveqdIRa0QxbnWJAABgmGHEFQAAAJri5eWdVzXNlI8DFXKRjIxSJ2XOt7o8AAAwDDHiCgCwxXHeq1JNVUvrU5ui0KoQh6yMBvTDyCgIrYq5SNUkk6+lCgMjGaso5PtQAAAw8AiugCHKOa9KLVOa1ZvjxmHACmlAE7z36iklKlUT1WqZJCmKAqWpU1cxljWEV8DGWGvUVaiHVnFoZSSlmVcxtMpFfAYBAICBR3AFDEHOea0uJypXEyWpkzVGuThQ6kIV81GrywPaWi11qiapaolTRyGWkVSqpqrUMsVRpkKOj0ZgY8LAKheHGt2ZU6WWyXmvQi5QIReyoiAAABgUnGEAQ1Cllq0JrbzycSjvvUqVVFZGuShQGDBdA9iYLHNKUq84DBSsmRqYi6yS1NGjB2hCMR/KGiNrEznnFIehioWQqYIAAGBQcIYBDEFp5pSkTvm4HlJFYf3vWlafOghg44wxslbK3F/eK2nmZa0RLa6A/jnv1/uscd4rSQl9AQDA4GDEFTAEGSNZY+T9Xy4UnPcKjZURV95AX3JRoFwUqCdN1FNO6nd6r2IhUkyPHqBfveVUPeVaI/AtV2ty3iuwhl6LAABgwBFcAUPQ2kbspUqqNPNy3st7ryi0iiIGUgJ9sdaosxDJGrP+qoK5kGm2QD+S1KmWZkozr85CJGOMkjRTpZqySAgAABgUBFfAELS2EbuVUS3LFK5ZhnztxTiAvkVhoBFFqzTzkrzCwMrw3gH65b2Xc/XRVWvfM4G1ci6V80wXBAAAA4/gChiiivlIuShQmjkZGUWRJbQCNoExRlHIewbYFEFgFFqrnlqt/vljpCT1ykWWEYsAAGBQEFwBQ1gYcKEAANh8Amvl5ZVmXit6KnLOKRcHCoIcQTAAABgUBFcAAABoinP16YDGSCM6YllrlDqnwBqlmVcuanGBAABg2CG4AgAAQFPSzClzXoV8pGK+nlI559Vbrilds9gBAADAQGKOEQAAAJpiTL0/3Lp92J339Ubt9FkEAACDgBFXAAAAaEoYWMWhVbWWqreSKLBGtcSpkAsUh3wfCgAABh7BFQAAAJpijFFHPpLzXrXUyTmvYiFULgqUj4NWlwcAAIYhgisAAAA0LQqtRnbmlCROznuFgVEUEloBAIDBQXAFAACATWKNUY4RVgAAYDOgGQEAAAAAAADaEiOuAAAAsMky5+S9ZK2RZUVBAAAwSAiuAAAA0DTnvHorSb3HlbwCa5SPQxVynFYCAICBxxkGAAAAmtZTSdRbTlRLnKw18t4rc17WGuUi+l4BAICBRXAFAACApqSZUy3JlKROnR2RrDGqJZkq1VRxFBBcAQCAAUdzdgAAADQlc17OeQXWNvpahaGVW3M/AADAQCO4AgAAQFMCaxRaqzRzyjInSaolmYLAKrA0aAcAAAOPqYIAAABoShhYxXGggnMqVRJ5GQVW6shFysdMEwSa5b2X95IxkmFVTgDoE8EVAAAAmlbMh7LGKI4COecVBlb5OFAUElwBzShXU9WSTFnmZYP6ogasygkAG8dvSAAAADTNGKOOfKiCD+SlRq8rAP0rV1P1VhKVKmljxNXa0IrwCgA2jN+OAAAA2GTGGBFZAc3z3quaZCpVUuXjUFFY7xdXriQKA6N8HDBtEAA2gOAKAAAAm6SWZKqlTs57hdYoFwcKLGv+AH3xXnJZvbdVFNbfL2FgJWPknFfmvMKA4AoA3o7gCgAAAE1bO9WpWsvqwVVgVUgCdRVjwiugD8ZIxkpGXmnmFAa2vjqn97LWyLIyJwBsEMEVAAAAmuKcV7maqlROFMehYmvqU5+qmcIwU2eB4ArYGGOM8nGoNPMqV5J6kuW9CvlQuSigXxwAbATBFQAAAJqSZk5p5hQEVrmovoqgNUa95Vp95AiAPuXjQN5LYWCUOa/AsqogAPSH35AAAABoijH1USPO/+U+5329oTSjRYB+rV2VM58L5NyaKYK8dwCgTwRXAAAAaEoYWMWhVS3J1FNOFFijJHUq5ALFIdMEgWZZY2RpxA4ATSG4AgAAQFOMMSoWInnvG6sKdhZC5eJQ+ThodXkAAGAYIrgCAABA08LAakRnTknq5L1XYK0iRlsBAIBBQnAFAACATWKNaTRnBwAAGEx8PQYAAAAAAIC2RHAFAAAAAACAtkRwBQAAAAAAgLZEcAUAAAAAAIC2RHAFAAAAAACAtkRwBQAAAAAAgLZEcAUAAAAAAIC2RHAFAAAAAACAtkRwBQAAAAAAgLZEcAUAAAAAAIC2RHAFAAAAAACAtkRwBQAAAAAAgLZEcAUAAAAAAIC2FLa6AAAAAADYUjjnVU0yZc4rsEa5KJC1ptVlAUDbIrgCAAAAgM0gzZxWl2r14CrzCoJ6cNXVESsMmAwDABvCb0cAAAAA2AxK1VTlaqo084pCqyzzKlVSlSppq0sDgLZFcAUAAAAAg8w5rzR1SlKvjlyoKAxUyIVKs/r9mXOtLhEA2hLBFQAAAAAMNtpYAcC7Qo8rAAAAABhk1hhFoVUUGvVWUkWhVZo5hYFRGFoFljEFALAhBFcAAAAAsBkUcqGc86okmbLMKQqs4siqI89lGdCsJHVKM1cPgyMraxjOONzxGxIAAAAANoMwsOoqxso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",
      "text/plain": [
       "<seaborn._core.plot.Plot at 0x7fa6375e94c0>"
      ]
     },
     "execution_count": 13,
     "metadata": {
      "image/png": {
       "height": 378.25,
       "width": 509.15
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import seaborn.objects as so\n",
    "\n",
    "so.Plot(df, x = \"grade\", y = \"density\").add(so.Dots(marker=\".\", alpha=0.1, fillalpha=0.1)).scale(y=\"log\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "873af64f-59fe-46a3-9a0a-0f9b08629e9e",
   "metadata": {},
   "outputs": [],
   "source": [
    "## Overture-based areas\n",
    "overture = (\n",
    "    con.read_parquet('s3://overturemaps-us-west-2/release/2024-11-13.0/theme=divisions/type=division_area/*', \n",
    "                     filename=True, hive_partitioning=1)\n",
    "usa = overture.filter(_.subtype==\"country\").filter(_.country == \"US\").select(_.geometry).execute()\n",
    "ca = (overture\n",
    "       .filter(_.country == \"US\", _.subtype == \"region\")\n",
    "       .select('region', 'geometry')\n",
    "       .filter(_.region == \"US-CA\")\n",
    "       .execute()\n",
    "      )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "128e0aed-e386-4b81-bbf1-ee7a9ea85860",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "## export in gdal formats?  not working?\n",
    "\n",
    "# Workaround for generic DuckDB writes (e.g. ~ to_geo() )\n",
    "# query = ibis.to_sql(sel)\n",
    "# con.raw_sql(f\"COPY ({query}) TO 's3://{bucket}/{dest2}'  WITH (FORMAT GDAL, DRIVER 'FlatGeoBuf');\")\n",
    "# con.raw_sql(f\"COPY ({query}) TO 's3://{bucket}/{dest2}'  WITH  (FORMAT GDAL, DRIVER 'GeoJSON', LAYER_CREATION_OPTIONS 'WRITE_BBOX=YES');\")\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "base",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}