calc_gz.ipynb

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   "language": "python"
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 "cells": [
  {
   "source": [
    "# Calculate Grounding Zone Widths\n",
    "\n",
    "For a given region, group grounding lines together and create a polygon, then use the boundary of that polygon to get the width of the grounding zone.\n",
    "\n",
    "## NOTES\n",
    "Making buffer for lines individually (instead of converting to MultiLineString first) and then creating multi polygon might be faster than current way."
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import random\n",
    "import numpy as np\n",
    "import matplotlib\n",
    "import matplotlib.cm as cm\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "import geopandas as gpd\n",
    "import netCDF4 as nc\n",
    "import pyproj\n",
    "from shapely.geometry import Point,MultiPoint,LineString,MultiLineString,Polygon,MultiPolygon\n",
    "from shapely import ops\n",
    "from descartes import PolygonPatch"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "base_dir = os.path.expanduser('~')\n",
    "#-- specify GL file\n",
    "file_6d = os.path.join(base_dir,'GL_learning_data','6d_results','AllTracks_6d_GL.shp')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [],
   "source": [
    "gdf = gpd.read_file(file_6d)"
   ]
  },
  {
   "source": [
    "Read boundary of ice shelf in order to get intersection with lines:"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [],
   "source": [
    "basins = gpd.read_file(os.path.join(base_dir,'data.dir','basin.dir','Gates_Basin_v1.7','Basins_v2.4.shp'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "               NAME    Regions                Subregion2 Subregion     SLE  \\\n",
       "0           LarsenE  Peninsula         LarsenE_Ice_Shelf      I\"-J    0.77   \n",
       "1       Coats_Coast       East               Coats_Coast       K-A    4.94   \n",
       "2           Academy       East        Filchner_Ice_Shelf      J\"-K  247.33   \n",
       "3    Stancomb_Wills       East  Stancomb_Wills_Ice_Shelf       K-A   46.14   \n",
       "4     Riiser-Larsen       East   Riiser-Larsen_Ice_Shelf       K-A   19.00   \n",
       "..              ...        ...                       ...       ...     ...   \n",
       "196   Enderby_Land2       East            Enderby_Land_2      A'-B    0.00   \n",
       "197           David       East       Drygalski_Ice_Shelf      D'-E  117.99   \n",
       "198         Islands    Islands                   Islands   Islands    8.76   \n",
       "199         Islands    Islands                   Islands   Islands    0.00   \n",
       "200         Islands    Islands                   Islands  IslandsL    0.00   \n",
       "\n",
       "                                              geometry  \n",
       "0    POLYGON ((-1604213.024 911528.811, -1603107.44...  \n",
       "1    POLYGON ((-681761.563 1361890.885, -680167.251...  \n",
       "2    POLYGON ((-650545.636 590416.431, -644265.131 ...  \n",
       "3    POLYGON ((-549906.633 1305863.952, -572323.238...  \n",
       "4    POLYGON ((-418449.622 1964493.872, -417441.371...  \n",
       "..                                                 ...  \n",
       "196  POLYGON ((2120087.293 1409593.226, 2120761.769...  \n",
       "197  POLYGON ((1362451.207 -906394.029, 1362282.310...  \n",
       "198  MULTIPOLYGON (((-2630075.000 1586825.000, -262...  \n",
       "199  POLYGON ((-1453517.353 311789.988, -1453035.86...  \n",
       "200  POLYGON ((-1448381.432 309944.266, -1447498.69...  \n",
       "\n",
       "[201 rows x 6 columns]"
      ],
      "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>NAME</th>\n      <th>Regions</th>\n      <th>Subregion2</th>\n      <th>Subregion</th>\n      <th>SLE</th>\n      <th>geometry</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>LarsenE</td>\n      <td>Peninsula</td>\n      <td>LarsenE_Ice_Shelf</td>\n      <td>I\"-J</td>\n      <td>0.77</td>\n      <td>POLYGON ((-1604213.024 911528.811, -1603107.44...</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>Coats_Coast</td>\n      <td>East</td>\n      <td>Coats_Coast</td>\n      <td>K-A</td>\n      <td>4.94</td>\n      <td>POLYGON ((-681761.563 1361890.885, -680167.251...</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>Academy</td>\n      <td>East</td>\n      <td>Filchner_Ice_Shelf</td>\n      <td>J\"-K</td>\n      <td>247.33</td>\n      <td>POLYGON ((-650545.636 590416.431, -644265.131 ...</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>Stancomb_Wills</td>\n      <td>East</td>\n      <td>Stancomb_Wills_Ice_Shelf</td>\n      <td>K-A</td>\n      <td>46.14</td>\n      <td>POLYGON ((-549906.633 1305863.952, -572323.238...</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>Riiser-Larsen</td>\n      <td>East</td>\n      <td>Riiser-Larsen_Ice_Shelf</td>\n      <td>K-A</td>\n      <td>19.00</td>\n      <td>POLYGON ((-418449.622 1964493.872, -417441.371...</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>196</th>\n      <td>Enderby_Land2</td>\n      <td>East</td>\n      <td>Enderby_Land_2</td>\n      <td>A'-B</td>\n      <td>0.00</td>\n      <td>POLYGON ((2120087.293 1409593.226, 2120761.769...</td>\n    </tr>\n    <tr>\n      <th>197</th>\n      <td>David</td>\n      <td>East</td>\n      <td>Drygalski_Ice_Shelf</td>\n      <td>D'-E</td>\n      <td>117.99</td>\n      <td>POLYGON ((1362451.207 -906394.029, 1362282.310...</td>\n    </tr>\n    <tr>\n      <th>198</th>\n      <td>Islands</td>\n      <td>Islands</td>\n      <td>Islands</td>\n      <td>Islands</td>\n      <td>8.76</td>\n      <td>MULTIPOLYGON (((-2630075.000 1586825.000, -262...</td>\n    </tr>\n    <tr>\n      <th>199</th>\n      <td>Islands</td>\n      <td>Islands</td>\n      <td>Islands</td>\n      <td>Islands</td>\n      <td>0.00</td>\n      <td>POLYGON ((-1453517.353 311789.988, -1453035.86...</td>\n    </tr>\n    <tr>\n      <th>200</th>\n      <td>Islands</td>\n      <td>Islands</td>\n      <td>Islands</td>\n      <td>IslandsL</td>\n      <td>0.00</td>\n      <td>POLYGON ((-1448381.432 309944.266, -1447498.69...</td>\n    </tr>\n  </tbody>\n</table>\n<p>201 rows × 6 columns</p>\n</div>"
     },
     "metadata": {},
     "execution_count": 86
    }
   ],
   "source": [
    "basins"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [],
   "source": [
    "idx = basins.index[basins['NAME']=='Getz']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
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     },
     "metadata": {},
     "execution_count": 88
    }
   ],
   "source": [
    "#-- get polygon\n",
    "poly = basins['geometry'][idx[0]]\n",
    "poly"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [],
   "source": [
    "#-- add a 5km buffer to finding the corresponding GLs\n",
    "region_poly = poly.buffer(5e3)"
   ]
  },
  {
   "source": [
    "Go through lines and find those that intersect the region:"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {},
   "outputs": [],
   "source": [
    "lines = []\n",
    "dates = []\n",
    "for i in range(len(gdf)):\n",
    "    #-- extract geometry to see if it's in region of interest\n",
    "    ll = gdf['geometry'][i]\n",
    "    if ll.intersects(region_poly):\n",
    "        lines.append(ll)\n",
    "        dates.append(gdf['FILENAME'][i].split(\"_\")[2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [],
   "source": [
    "#-- merge all lines into linestring\n",
    "lm = ops.linemerge(lines)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [],
   "source": [
    "#-- read widths\n",
    "WIDTH_FILE = os.path.join(base_dir,'GL_learning_data',\\\n",
    "\t'6d_results','GZ_Getz_widths_400m.shp')\n",
    "df_w = gpd.read_file(WIDTH_FILE)    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [],
   "source": [
    "#-- get width lines\n",
    "ws = []\n",
    "for i in range(len(df_w)):\n",
    "    ws.append(df_w['geometry'][i])\n",
    "widths = MultiLineString(ws)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {},
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "-0.09962696069851518 0.009380881441757083 0.09965759376063943 -0.00938376598060131\n",
      "-0.010601837886497378 0.11208211735356599 0.010477564996108413 -0.11076831223908812\n",
      "-0.014966372167691588 -0.11492418916895986 0.016618878347799182 0.12761350022628903\n",
      "-0.10248263133689761 0.013347794068977237 0.11429087887518108 -0.01488575292751193\n",
      "-0.09408843400888145 -0.041665064985863864 0.09536979906260967 0.04223249037750065\n",
      "-0.01697298279032111 0.10333855636417866 0.01758238347247243 -0.10704884072765708\n",
      "-0.0875586592592299 0.06117592356167734 0.08241712534800172 -0.057583610876463354\n",
      "-0.04913579183630645 -0.08780831738840789 0.048900270368903875 0.08738742768764496\n",
      "-0.032365214079618454 -0.13964133895933628 0.02310266299173236 0.0996775982202962\n",
      "-0.09848960349336267 -0.018061092006973922 0.09872688422910869 0.018104604678228498\n",
      "-0.07637914805673063 -0.08794631122145802 0.06716728792525828 0.07733937015291303\n",
      "-0.030108352191746235 0.09678260225336999 0.030275954864919186 -0.09732135676313192\n",
      "-0.05901315878145397 -0.08080364519264549 0.060932841151952744 0.08343216637149453\n",
      "-0.06651398469693959 0.0804960431996733 0.06723012402653694 -0.08136272360570729\n",
      "-0.06916610710322857 -0.0728671564720571 0.0691277151927352 0.07282671029679477\n",
      "-0.08306226786226034 -0.0628855989780277 0.0811290864367038 0.061422006925567985\n",
      "-0.0427298650611192 -0.14796981762629002 0.032608125591650605 0.1129191117361188\n",
      "-0.09796953108161688 -0.05236510478425771 0.08819402824155986 0.047140059527009726\n",
      "-0.07869424787349999 -0.061734196497127414 0.07891260599717498 0.06190549454186112\n",
      "-0.07696904754266143 -0.0650315664242953 0.07754674111492932 0.06551966280676425\n"
     ]
    }
   ],
   "source": [
    "for _ in range(20):\n",
    "    i = random.randrange(0,len(widths))\n",
    "    pt0 = widths[i].interpolate(0,normalized=True)\n",
    "    pt1 = widths[i].interpolate(1,normalized=True)\n",
    "    pt_int = widths[i].intersection(lm)\n",
    "    x1,y1 = pt_int[-1].coords.xy\n",
    "    xx1,yy1 = pt0.coords.xy\n",
    "    x2,y2 = pt_int[0].coords.xy\n",
    "    xx2,yy2 = pt1.coords.xy\n",
    "    print(x1[0]-xx1[0],y1[0]-yy1[0],x2[0]-xx2[0],y2[0]-yy2[0])"
   ]
  },
  {
   "source": [
    "So `pt0` is the last intersection (`pt_int[-1]`) and `pt1` is the first intersection (`pt_int[0]`).\n",
    "Note they don't match exactly because of the 10cm buffer used in creating the GZ polygon.\n",
    "\n",
    "Now for each point, loop through elements of `ml` to see which LineStrings intersect with the first and last points to get their dates."
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {},
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "Found first date for point 0: 181120-181126-181126-181202\n",
      "Found second line for point 0: 181114-181120-181120-181126\n",
      "Found first date for point 1: 180727-180802-180808-180814\n",
      "Found second line for point 1: 180826-180901-180907-180913\n",
      "Found second line for point 2: 180115-180121-180121-180127\n",
      "Found first date for point 2: 180810-180816-180822-180828\n",
      "Found second line for point 3: 180715-180721-180727-180802\n",
      "Found first date for point 3: 180913-180919-180925-181001\n",
      "Found second line for point 4: 180418-180424-180424-180430\n",
      "Found first date for point 4: 180915-180921-180921-180927\n",
      "Found first date for point 5: 180406-180412-180418-180424\n",
      "Found second line for point 5: 180605-180611-180617-180623\n",
      "Found second line for point 6: 180605-180611-180611-180617\n",
      "Found first date for point 6: 180605-180611-180617-180623\n",
      "Found second line for point 7: 181124-181130-181130-181206\n",
      "Found first date for point 7: 180116-180122-180128-180203\n",
      "Found first date for point 8: 180909-180915-180921-180927\n",
      "Found second line for point 8: 180903-180909-180909-180915\n",
      "Found second line for point 9: 180820-180826-180826-180901\n",
      "Found first date for point 9: 180808-180814-180814-180820\n",
      "Found second line for point 10: 180826-180901-180907-180913\n",
      "Found first date for point 10: 180901-180907-180907-180913\n",
      "Found first date for point 11: 180913-180919-180925-181001\n",
      "Found second line for point 11: 180209-180215-180215-180221\n",
      "Found first date for point 12: 180822-180828-180828-180903\n",
      "Found second line for point 12: 181214-181220-181220-181226\n",
      "Found second line for point 13: 181120-181126-181126-181202\n",
      "Found first date for point 13: 180909-180915-180915-180921\n",
      "Found second line for point 14: 180820-180826-180826-180901\n",
      "Found first date for point 14: 180814-180820-180820-180826\n",
      "Found second line for point 15: 181118-181124-181124-181130\n",
      "Found first date for point 15: 180808-180814-180814-180820\n",
      "Found first date for point 16: 180528-180603-180603-180609\n",
      "Found second line for point 16: 180919-180925-180925-181001\n",
      "Found first date for point 17: 180103-180109-180109-180115\n",
      "Found first date for point 18: 180103-180109-180109-180115\n",
      "Found first date for point 19: 180808-180814-180814-180820\n",
      "Found second line for point 19: 180814-180820-180826-180901\n"
     ]
    }
   ],
   "source": [
    "for _ in range(20):\n",
    "    i = random.randrange(0,len(widths))\n",
    "    pt0 = widths[i].interpolate(0,normalized=True)\n",
    "    pt1 = widths[i].interpolate(1,normalized=True)\n",
    "    for c,l in enumerate(lines):\n",
    "        if l.distance(pt1) < 0.2:\n",
    "            print(\"Found first date for point {0:d}: {1}\".format(_,dates[c]))\n",
    "        elif l.distance(pt0) < 0.2:\n",
    "            print(\"Found second line for point {0:d}: {1}\".format(_,dates[c]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [],
   "source": [
    "pt_int = widths[0].intersection(lm)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "(array('d', [-1572472.7396068515]), array('d', [-736514.0770206411]))"
      ]
     },
     "metadata": {},
     "execution_count": 110
    }
   ],
   "source": [
    "pt_int[-1].coords.xy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "(array('d', [-1572472.719412035]), array('d', [-736514.1768916575]))"
      ]
     },
     "metadata": {},
     "execution_count": 111
    }
   ],
   "source": [
    "pt0.coords.xy"
   ]
  },
  {
   "source": [
    "** NOTE ** Creating a polygon out of GLs takes a long time, so if the GZ polygon has already been created, just load it in instead."
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "#-- convert to polygon with small buffer (10cm)\n",
    "ep = lm.buffer(1e-1)\n",
    "#-- get the boundary of the polygon containing all lines to make new polygon of just the envelope\n",
    "err_poly = []\n",
    "for ip in ep:\n",
    "    x,y = ip.exterior.coords.xy\n",
    "    err_poly.append(Polygon(zip(x,y)))\n",
    "#-- save the error polygon\n",
    "#-- first make DataFrame\n",
    "df = {'REGION':[],'center_x':[],'center_y':[]}\n",
    "out_geo = []\n",
    "for p in err_poly:\n",
    "    width = p.area/(p.length/2)\n",
    "    if width > 1:\n",
    "        df['REGION'].append('Getz')\n",
    "        x,y = p.centroid.coords.xy\n",
    "        df['center_x'].append(x[0])\n",
    "        df['center_y'].append(y[0])\n",
    "        out_geo.append(p)\n",
    "out_gdf = gpd.GeoDataFrame(df,geometry=out_geo,crs=gdf.crs)\n",
    "outfile = os.path.join(base_dir,'GL_learning_data','6d_results','GZ_Getz.shp')\n",
    "out_gdf.to_file(outfile,driver='ESRI Shapefile')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "#-- also save GZ widths to file\n",
    "fid = open(outfile.replace('.shp','.csv'),'w')\n",
    "fid.write('Center_X,Center_Y,WIDTH(m,LENGTH(m),AREA(m2)\\n')\n",
    "for i in range(len(out_gdf)):\n",
    "    fid.write('{0:.2f},{1:.2f},{2:.1f},{3:.1f},{4:.1f}\\n'.format(\n",
    "        out_gdf['center_x'][i],\n",
    "        out_gdf['center_y'][i],\n",
    "        out_gdf['geometry'][i].area/out_gdf['geometry'][i].length,\n",
    "        out_gdf['geometry'][i].length,\n",
    "        out_gdf['geometry'][i].area\n",
    "    ))\n",
    "fid.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "gz_file = os.path.join(base_dir,'GL_learning_data','6d_results','GZ_Getz.shp')\n",
    "gz_df = gpd.read_file(gz_file)\n",
    "gz_poly = []\n",
    "for i in range(len(gz_df)):\n",
    "    gz_poly.append(gz_df['geometry'][i])\n",
    "gz_poly = MultiPolygon(gz_poly)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
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440.417984 \nL 330.395571 438.650905 \nL 330.395605 438.65082 \nL 331.116432 436.924143 \nL 331.116468 436.924059 \nL 331.863559 435.241855 \nL 331.863597 435.241773 \nL 332.634109 433.605472 \nL 332.634147 433.605393 \nL 333.425974 432.014141 \nL 333.426013 432.014066 \nL 334.237811 430.464932 \nL 334.237849 430.46486 \nL 335.068825 428.953761 \nL 335.068862 428.953695 \nL 335.918453 427.475865 \nL 335.918489 427.475804 \nL 336.785935 426.026667 \nL 336.785968 426.026612 \nL 337.66986 424.602249 \nL 337.66989 424.6022 \nL 338.567682 423.200067 \nL 338.567708 423.200027 \nL 339.475538 421.818862 \nL 339.475559 421.81883 \nL 340.069525 420.933735 \nL 340.039472 419.595738 \nL 340.039471 419.595616 \nL 340.054744 417.643467 \nL 340.054747 417.643334 \nL 340.134168 415.702746 \nL 340.134176 415.702603 \nL 340.281005 413.782712 \nL 340.28102 413.782562 \nL 340.496739 411.891004 \nL 340.49676 411.89085 \nL 340.781059 410.033343 \nL 340.781085 410.03319 \nL 341.13191 408.213278 \nL 341.131942 408.213128 \nL 341.545744 406.432603 \nL 341.54578 406.43246 \nL 342.017843 404.691733 \nL 342.017882 404.6916 \nL 342.542764 402.990381 \nL 342.542805 402.990257 \nL 343.114746 401.328299 \nL 343.114787 401.328186 \nL 343.521941 400.251089 \nL 343.481118 400.314852 \nL 342.583166 401.71807 \nL 341.688723 403.114925 \nL 340.7983 404.503215 \nL 340.798298 404.503219 \nL 339.911999 405.881376 \nL 339.911996 405.881381 \nL 339.029041 407.249153 \nL 339.029036 407.249161 \nL 338.147757 408.607484 \nL 338.147751 408.607494 \nL 337.265409 409.958728 \nL 337.265401 409.95874 \nL 336.378287 411.306505 \nL 336.378278 411.30652 \nL 335.48182 412.655512 \nL 335.481809 412.655529 \nL 334.570926 414.011162 \nL 334.570913 414.011181 \nL 333.640442 415.379136 \nL 333.640428 415.379156 \nL 332.685567 416.765031 \nL 332.685554 416.765051 \nL 331.702471 418.1739 \nL 331.702459 418.173918 \nL 330.688786 419.609947 \nL 330.688775 419.609962 \nL 329.644137 421.076098 \nL 329.64413 421.076108 \nL 328.570442 422.573866 \nL 327.472122 424.103044 \nL 326.356041 425.661525 \nL 325.231211 427.245273 \nL 324.108148 428.848534 \nL 322.998224 430.463901 \nL 321.912651 432.083114 \nL 320.861486 433.697903 \nL 319.852753 435.300958 \nL 318.891658 436.887025 \nL 317.980034 438.453928 \nL 317.116118 440.00329 \nL 316.294658 441.540745 \nL 315.507277 443.075762 \nL 314.743233 444.620684 \nL 313.990388 446.189321 \nL 313.236233 447.795319 \nL 312.469145 449.450075 \nL 311.679291 451.161214 \nL 311.679289 451.161218 \nL 310.859656 452.931042 \nL 310.859649 452.931056 \nL 310.006309 454.756284 \nL 310.006299 454.756304 \nL 309.118542 456.62818 \nL 309.11853 456.628206 \nL 308.198551 458.533521 \nL 308.198536 458.533551 \nL 307.250634 460.456384 \nL 307.250617 460.456417 \nL 306.28046 462.379806 \nL 306.280442 462.379842 \nL 305.294139 464.287623 \nL 305.294119 464.287661 \nL 304.297417 466.16577 \nL 304.297395 466.165811 \nL 303.29517 468.003038 \nL 303.295147 468.003082 \nL 302.290949 469.791376 \nL 302.290922 469.791422 \nL 301.286769 471.525826 \nL 301.28674 471.525875 \nL 300.283199 473.203868 \nL 300.283166 473.203921 \nL 299.279367 474.825089 \nL 299.279331 474.825146 \nL 298.273207 476.390544 \nL 298.273167 476.390606 \nL 297.26185 477.902199 \nL 297.261805 477.902265 \nL 296.242018 479.362555 \nL 296.241967 479.362625 \nL 295.210576 480.774066 \nL 295.210521 480.774139 \nL 294.164899 482.138975 \nL 294.16484 482.139049 \nL 293.103279 483.458972 \nL 293.103218 483.459047 \nL 292.025149 484.735154 \nL 292.025085 484.735228 \nL 290.931063 485.968206 \nL 290.930998 485.968278 \nL 289.822419 487.158779 \nL 289.822354 487.158847 \nL 288.701389 488.307605 \nL 288.701326 488.307669 \nL 287.570523 489.415917 \nL 287.570463 489.415975 \nL 286.432454 490.485599 \nL 286.432397 490.485651 \nL 285.289678 491.519214 \nL 285.289626 491.519259 \nL 284.144527 492.519741 \nL 284.144481 492.51978 \nL 282.998913 493.490677 \nL 282.998873 493.490711 \nL 281.854308 494.435596 \nL 281.854274 494.435624 \nL 280.711694 495.358045 \nL 280.711665 495.358068 \nL 279.571395 496.261501 \nL 279.57137 496.26152 \nL 278.433129 497.149162 \nL 278.433108 497.149178 \nL 277.295799 498.024029 \nL 277.29578 498.024044 \nL 276.157665 498.888699 \nL 276.157647 498.888713 \nL 275.016178 499.74561 \nL 275.016159 499.745624 \nL 273.868232 500.59686 \nL 273.868212 500.596875 \nL 272.710325 501.444326 \nL 272.710303 501.444342 \nL 271.538756 502.289704 \nL 271.538732 502.289721 \nL 270.349836 503.13453 \nL 270.349811 503.134548 \nL 269.140042 503.980273 \nL 269.140016 503.980291 \nL 267.906009 504.828386 \nL 267.905982 504.828404 \nL 266.644313 505.680562 \nL 266.644286 505.68058 \nL 265.351338 506.53874 \nL 265.351312 506.538758 \nL 264.023065 507.405248 \nL 264.023039 507.405265 \nL 262.654999 508.282851 \nL 262.654974 508.282867 \nL 261.242486 509.174596 \nL 261.242463 509.174611 \nL 259.781284 510.083507 \nL 259.781264 510.083519 \nL 258.268456 511.012144 \nL 258.268439 511.012155 \nL 256.703485 511.961971 \nL 256.703471 511.96198 \nL 255.089041 512.93295 \nL 255.089031 512.932957 \nL 253.431593 513.923083 \nL 253.431587 513.923087 \nL 251.741508 514.928269 \nL 250.032391 515.942472 \nL 248.320027 516.95812 \nL 246.621089 517.966611 \nL 244.951616 518.95905 \nL 243.325604 519.926974 \nL 241.753968 520.863018 \nL 240.243943 521.761433 \nL 240.243938 521.761436 \nL 238.798677 522.61862 \nL 238.798669 522.618625 \nL 237.417177 523.433487 \nL 237.417165 523.433494 \nL 236.094605 524.207555 \nL 236.094591 524.207564 \nL 234.822493 524.945071 \nL 234.822478 524.94508 \nL 233.589135 525.652863 \nL 233.58912 525.652871 \nL 232.38015 526.340077 \nL 232.380139 526.340083 \nL 231.179464 527.017529 \nL 231.179458 527.017532 \nL 229.970234 527.697081 \nL 228.736062 528.390883 \nL 227.46244 529.110436 \nL 226.138115 529.865701 \nL 224.755949 530.664531 \nL 223.31362 531.512072 \nL 221.813458 532.410666 \nL 220.261822 533.360017 \nL 218.667876 534.357707 \nL 217.042227 535.399883 \nL 215.395639 536.481959 \nL 213.737819 537.599425 \nL 212.076863 538.748285 \nL 210.419227 539.925184 \nL 208.769891 541.1274 \nL 207.133067 542.352358 \nL 205.512637 543.597249 \nL 203.912595 544.858515 \nL 202.337145 546.131521 \nL 200.790611 547.41039 \nL 199.277017 548.688132 \nL 197.799731 549.956944 \nL 196.361014 551.208758 \nL 194.961915 552.435749 \nL 193.60217 553.630985 \nL 193.602165 553.630989 \nL 192.280469 554.788881 \nL 192.280456 554.788892 \nL 190.994644 555.905579 \nL 190.994624 555.905596 \nL 189.741965 556.979117 \nL 189.74194 556.979139 \nL 188.519395 558.009318 \nL 188.519366 558.009342 \nL 187.323537 558.997681 \nL 187.323505 558.997707 \nL 186.150658 559.946993 \nL 186.150625 559.94702 \nL 184.996631 560.86095 \nL 184.996597 560.860977 \nL 183.856603 561.74382 \nL 183.856568 561.743847 \nL 182.724991 562.600339 \nL 182.724955 562.600366 \nL 181.595497 563.435439 \nL 181.595459 563.435466 \nL 180.461106 564.254056 \nL 180.461067 564.254083 \nL 179.314507 565.061101 \nL 179.314468 565.061128 \nL 178.14863 565.861162 \nL 178.148591 565.861189 \nL 176.957151 566.658294 \nL 176.957112 566.658319 \nL 175.735319 567.455482 \nL 175.735282 567.455506 \nL 174.480492 568.254348 \nL 174.480455 568.254371 \nL 173.193229 569.054455 \nL 173.193193 569.054477 \nL 171.878089 569.852841 \nL 171.878053 569.852862 \nL 170.544458 570.643703 \nL 170.544423 570.643724 \nL 169.20745 571.418182 \nL 169.207415 571.418203 \nL 167.888402 572.16448 \nL 167.888367 572.164499 \nL 166.614865 572.868372 \nL 166.614832 572.86839 \nL 165.419972 573.51394 \nL 165.419941 573.513957 \nL 164.340973 574.084519 \nL 164.340945 574.084534 \nL 163.416657 574.563959 \nL 163.416634 574.563971 \nL 162.684308 574.937705 \nL 162.68429 574.937714 \nL 162.176038 575.193928 \nL 162.176027 575.193933 \nL 161.915606 575.324204 \nL 161.915245 575.324363 \nL 161.914871 575.324485 \nL 161.914487 575.32457 \nL 161.914096 575.324617 \nL 161.913703 575.324625 \nL 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212.072253 538.741697 \nL 212.072294 538.741669 \nL 213.733289 537.592781 \nL 213.733329 537.592754 \nL 215.391189 536.475262 \nL 215.391228 536.475236 \nL 217.037854 535.393135 \nL 217.037892 535.39311 \nL 218.663579 534.35091 \nL 218.663616 534.350887 \nL 220.257597 533.353175 \nL 220.257632 533.353153 \nL 221.809301 532.403782 \nL 221.809334 532.403762 \nL 223.309527 531.50515 \nL 223.309556 531.505132 \nL 224.751911 530.657576 \nL 224.751936 530.657562 \nL 226.134124 529.858718 \nL 226.134144 529.858707 \nL 227.458487 529.103432 \nL 227.458501 529.103424 \nL 228.732134 528.383865 \nL 228.732141 528.383861 \nL 229.966317 527.690057 \nL 231.175539 527.010509 \nL 232.376205 526.333068 \nL 233.585163 525.645869 \nL 234.818491 524.938095 \nL 236.090574 524.200596 \nL 237.413121 523.426543 \nL 238.794603 522.611686 \nL 240.239857 521.754506 \nL 241.749878 520.856094 \nL 243.321513 519.92005 \nL 244.947528 518.952125 \nL 246.617005 517.959683 \nL 248.315946 516.95119 \nL 250.028311 515.935541 \nL 251.737423 514.921341 \nL 253.427497 513.916163 \nL 255.084925 512.926041 \nL 256.699343 511.955078 \nL 258.264282 511.005271 \nL 259.777071 510.076657 \nL 261.238229 509.167774 \nL 262.650694 508.276059 \nL 264.018709 507.398489 \nL 265.34693 506.532016 \nL 266.639851 505.673873 \nL 267.901493 504.821734 \nL 269.135474 503.973657 \nL 270.345217 503.12795 \nL 271.534088 502.283158 \nL 272.705613 501.437812 \nL 273.863478 500.590377 \nL 275.011386 499.739156 \nL 276.152836 498.882272 \nL 277.290932 498.017631 \nL 278.428221 497.142796 \nL 279.56644 496.255171 \nL 280.706684 495.35176 \nL 281.849233 494.429364 \nL 282.99376 493.484509 \nL 284.139286 492.513648 \nL 285.284336 491.513209 \nL 286.427002 490.479696 \nL 287.564952 489.410127 \nL 288.695693 488.301939 \nL 289.816593 487.153246 \nL 290.925108 485.962815 \nL 292.019066 484.729909 \nL 293.097071 483.453877 \nL 294.158572 482.134029 \nL 295.204138 480.769267 \nL 296.235477 479.357898 \nL 297.255216 477.897676 \nL 298.26649 476.386147 \nL 299.272575 474.82081 \nL 300.27634 473.199697 \nL 301.279851 471.521756 \nL 302.283977 469.787399 \nL 303.28815 467.999149 \nL 304.290352 466.161964 \nL 305.287032 464.283895 \nL 306.273316 462.376151 \nL 307.243455 460.452796 \nL 308.191342 458.529995 \nL 309.111308 456.624707 \nL 309.999055 454.752853 \nL 310.852388 452.927641 \nL 311.672017 451.157826 \nL 312.461871 449.446687 \nL 312.461874 449.446681 \nL 313.228967 447.791913 \nL 313.228976 447.791895 \nL 313.983142 446.185873 \nL 313.983157 446.185842 \nL 314.73602 444.617167 \nL 314.73604 444.617125 \nL 315.500108 443.072155 \nL 315.500135 443.072102 \nL 316.287545 441.537029 \nL 316.287576 441.536969 \nL 317.109069 439.999452 \nL 317.109103 439.999389 \nL 317.973055 438.449963 \nL 317.973092 438.449899 \nL 318.884752 436.882933 \nL 318.884789 436.882871 \nL 319.84592 435.296745 \nL 319.845956 435.296687 \nL 320.854724 433.693576 \nL 320.854757 433.693524 \nL 321.905954 432.078687 \nL 321.905984 432.078642 \nL 322.991585 430.459386 \nL 322.991611 430.459348 \nL 324.101558 428.843948 \nL 324.101579 428.843918 \nL 325.22466 427.240631 \nL 325.224675 427.240609 \nL 326.349517 425.656845 \nL 326.349526 425.656832 \nL 327.465614 424.098342 \nL 327.465617 424.098337 \nL 328.563936 422.569162 \nL 329.637619 421.07141 \nL 330.682249 419.605285 \nL 331.69591 418.169272 \nL 332.67898 416.760442 \nL 333.633827 415.374586 \nL 334.564285 414.00665 \nL 335.475156 412.651035 \nL 336.371603 411.302059 \nL 337.258707 409.954308 \nL 338.141042 408.603085 \nL 339.022315 407.244771 \nL 339.905265 405.877006 \nL 340.79156 404.498854 \nL 341.681979 403.11057 \nL 342.57642 401.713717 \nL 343.474372 400.3105 \nL 343.535683 400.214737 \nL 343.728178 399.705506 \nL 343.728219 399.7054 \nL 344.378039 398.122608 \nL 344.378082 398.122508 \nL 345.060126 396.58066 \nL 345.06017 396.580564 \nL 345.771122 395.080824 \nL 345.771168 395.08073 \nL 346.508666 393.624147 \nL 346.508715 393.624054 \nL 347.270905 392.211367 \nL 347.270956 392.211275 \nL 348.056354 390.842744 \nL 348.056408 390.842653 \nL 348.863436 389.518111 \nL 348.863492 389.518023 \nL 349.690363 388.236845 \nL 349.69042 388.23676 \nL 350.535218 386.99783 \nL 350.535275 386.997749 \nL 351.396104 385.799274 \nL 351.39616 385.799199 \nL 352.271696 384.638391 \nL 352.271751 384.638321 \nL 353.161916 383.511045 \nL 353.161969 383.510979 \nL 354.068285 382.411448 \nL 354.068336 382.411387 \nL 354.99435 381.332222 \nL 354.9944 381.332165 \nL 355.945576 380.264817 \nL 355.945624 380.264764 \nL 356.928795 379.200181 \nL 356.928841 379.200131 \nL 357.951572 378.129711 \nL 357.951618 378.129664 \nL 359.021043 377.046446 \nL 359.021089 377.0464 \nL 360.055194 376.032067 \nL 360.62924 375.270394 \nL 360.62926 375.270368 \nL 361.919128 373.587122 \nL 361.919149 373.587095 \nL 363.245498 371.88616 \nL 363.24552 371.886132 \nL 364.604935 370.174329 \nL 364.604959 370.1743 \nL 365.99318 368.459192 \nL 365.993205 368.459161 \nL 367.404977 366.749055 \nL 367.405003 366.749024 \nL 368.834255 365.052748 \nL 368.834283 365.052716 \nL 370.274468 363.3793 \nL 370.274497 363.379267 \nL 371.719205 361.73742 \nL 371.719237 361.737385 \nL 373.162964 360.134811 \nL 373.162999 360.134774 \nL 374.601946 358.577616 \nL 374.601985 358.577575 \nL 376.034848 357.069761 \nL 376.034892 357.069716 \nL 377.463287 355.612696 \nL 377.463336 355.612647 \nL 378.891653 354.205468 \nL 378.891708 354.205414 \nL 380.326677 352.845141 \nL 380.326739 352.845084 \nL 381.776321 351.527668 \nL 381.776388 351.527608 \nL 383.248583 350.248756 \nL 383.248655 350.248695 \nL 384.750117 349.004826 \nL 384.750192 349.004766 \nL 386.285227 347.793715 \nL 386.285303 347.793657 \nL 387.855348 346.614798 \nL 387.855425 346.614742 \nL 389.459168 345.46885 \nL 389.459244 345.468798 \nL 391.093381 344.357288 \nL 391.093456 344.357239 \nL 392.445084 343.481384 \nL 391.283264 343.816952 \nL 389.510431 344.36123 \nL 387.732117 344.941477 \nL 385.946198 345.560094 \nL 384.152373 346.218388 \nL 382.352735 346.916312 \nL 380.551837 347.652338 \nL 378.756828 348.423463 \nL 376.977393 349.225212 \nL 375.225139 350.05194 \nL 373.512744 350.897251 \nL 371.852786 351.754563 \nL 370.256511 352.61777 \nL 368.732304 353.481909 \nL 367.284705 354.343849 \nL 365.913509 355.202736 \nL 364.613809 356.060141 \nL 363.376236 356.919969 \nL 362.188189 357.787942 \nL 361.0352 358.670802 \nL 359.902562 359.575421 \nL 358.777111 360.507768 \nL 357.6486 361.472015 \nL 356.510733 362.469876 \nL 355.361623 363.500515 \nL 354.2036 364.560886 \nL 353.042603 365.6462 \nL 351.887124 366.751124 \nL 350.747054 367.870898 \nL 349.632503 369.002401 \nL 348.552913 370.145077 \nL 347.516276 371.301324 \nL 346.529083 372.476654 \nL 345.596036 373.679431 \nL 344.720453 374.920247 \nL 343.904459 376.210819 \nL 343.149097 377.563004 \nL 342.454787 378.987504 \nL 341.82137 380.492351 \nL 341.248201 382.08164 \nL 340.734113 383.754287 \nL 340.277392 385.503325 \nL 339.875627 387.315472 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343.897519 376.206785 \nL 343.897631 376.206597 \nL 344.713737 374.915846 \nL 344.713851 374.915676 \nL 345.589546 373.674702 \nL 345.589654 373.674556 \nL 346.522805 372.471645 \nL 346.522903 372.471524 \nL 347.510188 371.296085 \nL 347.510273 371.295987 \nL 348.546989 370.139652 \nL 348.54706 370.139575 \nL 349.626714 368.99683 \nL 349.626773 368.996769 \nL 350.741376 367.865214 \nL 350.741423 367.865167 \nL 351.881536 366.74535 \nL 351.881574 366.745313 \nL 353.037089 365.640355 \nL 353.037123 365.640324 \nL 354.198151 364.55498 \nL 354.198181 364.554952 \nL 355.356235 363.494552 \nL 355.356266 363.494525 \nL 356.505408 362.463857 \nL 356.505441 362.463827 \nL 357.643344 361.465935 \nL 357.643383 361.465901 \nL 358.771937 360.501618 \nL 358.771984 360.501578 \nL 359.897487 359.569189 \nL 359.897542 359.569143 \nL 361.03024 358.664476 \nL 361.030305 358.664425 \nL 362.183362 357.781513 \nL 362.183435 357.781459 \nL 363.371557 356.913432 \nL 363.371634 356.913376 \nL 364.609285 356.053494 \nL 364.609365 356.05344 \nL 365.909146 355.195982 \nL 365.909225 355.195931 \nL 367.280499 354.336995 \nL 367.280576 354.336948 \nL 368.728251 353.474963 \nL 368.728324 353.47492 \nL 370.252603 352.61074 \nL 370.252673 352.610701 \nL 371.849017 351.747457 \nL 371.849084 351.747422 \nL 373.509108 350.890075 \nL 373.509173 350.890042 \nL 375.221632 350.0447 \nL 375.221696 350.044669 \nL 376.974014 349.217911 \nL 376.974078 349.217882 \nL 378.753577 348.416104 \nL 378.753642 348.416076 \nL 380.548715 347.644922 \nL 380.54878 347.644895 \nL 382.349745 346.908842 \nL 382.349812 346.908816 \nL 384.149518 346.210865 \nL 384.149586 346.210839 \nL 385.943479 345.55252 \nL 385.943548 345.552495 \nL 387.729536 344.933854 \nL 387.729604 344.933831 \nL 389.507986 344.353563 \nL 389.508053 344.353542 \nL 391.280952 343.809244 \nL 391.281016 343.809225 \nL 392.468407 343.466271 \nL 392.753668 343.281422 \nL 392.75374 343.281376 \nL 394.435683 342.241648 \nL 394.435752 342.241606 \nL 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43.317622 \nL 691.070254 42.032205 \nL 691.26654 40.910782 \nL 691.405172 40.0077 \nL 691.492831 39.373031 \nL 691.535098 39.045195 \nL 691.535167 39.044806 \nL 691.535275 39.044426 \nL 691.535419 39.044058 \nL 691.535598 39.043707 \nL 691.53581 39.043374 \nL 691.536054 39.043064 \nL 691.536327 39.04278 \nL 691.536626 39.042524 \nL 691.536949 39.042298 \nL 691.537293 39.042106 \nL 691.537654 39.041948 \nL 691.538028 39.041826 \nL 691.538412 39.041742 \nL 691.538803 39.041696 \nL 691.539196 39.041688 \nL 691.539589 39.04172 \nL 691.539976 39.04179 \nL 691.540354 39.041897 \nL 691.540721 39.042042 \nL 691.541071 39.042221 \nL 691.541402 39.042435 \nL 691.541711 39.04268 \nL 691.541994 39.042954 \nL 691.542249 39.043254 \nL 691.542474 39.043579 \nL 691.542666 39.043924 \nL 691.542823 39.044286 \nL 691.542944 39.044662 \nL 691.543028 39.045047 \nL 691.543074 39.04544 \nL 691.543081 39.045835 \nL 691.54305 39.046229 \nL 691.500781 39.374083 \nL 691.500776 39.374119 \nL 691.41311 40.008836 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676.007069 80.236701 \nL 675.628849 82.034071 \nL 675.299307 83.846969 \nL 675.013324 85.668688 \nL 674.762952 87.494424 \nL 674.537939 89.32241 \nL 674.326461 91.154783 \nL 674.116046 92.997561 \nL 674.116044 92.99758 \nL 673.894499 94.859799 \nL 673.894494 94.859838 \nL 673.650693 96.752052 \nL 673.650686 96.752106 \nL 673.375259 98.684228 \nL 673.37525 98.684292 \nL 673.061004 100.663466 \nL 673.060992 100.663534 \nL 672.703127 102.692412 \nL 672.703114 102.692482 \nL 672.299198 104.76834 \nL 672.299184 104.76841 \nL 671.848973 106.883253 \nL 671.848957 106.883321 \nL 671.354109 109.024851 \nL 671.354093 109.024917 \nL 670.817632 111.178516 \nL 670.817616 111.178581 \nL 670.243585 113.328987 \nL 670.243567 113.32905 \nL 669.905478 114.517153 \nL 670.552203 113.045177 \nL 671.372263 111.147846 \nL 672.187826 109.246572 \nL 673.006249 107.342911 \nL 673.006257 107.342894 \nL 673.835238 105.438231 \nL 673.835251 105.438202 \nL 674.682085 103.534215 \nL 674.682104 103.534174 \nL 675.553081 101.633247 \nL 675.553104 101.633196 \nL 676.453008 99.738798 \nL 676.453036 99.73874 \nL 677.384966 97.855436 \nL 677.384998 97.855372 \nL 678.350227 95.988853 \nL 678.350263 95.988785 \nL 679.34842 94.145516 \nL 679.348459 94.145446 \nL 680.377813 92.33224 \nL 680.377855 92.332167 \nL 681.435796 90.555456 \nL 681.43584 90.555382 \nL 682.519107 88.821013 \nL 682.519154 88.82094 \nL 683.624225 87.13368 \nL 683.624273 87.133608 \nL 684.747753 85.496677 \nL 684.747802 85.496606 \nL 685.886563 83.911407 \nL 685.886612 83.91134 \nL 687.037949 82.377143 \nL 687.037997 82.37708 \nL 688.19968 80.890745 \nL 688.199724 80.89069 \nL 689.369826 79.446538 \nL 689.369863 79.446493 \nL 690.546511 78.036646 \nL 690.546539 78.036614 \nL 691.72758 76.651304 \nL 691.727594 76.651287 \nL 692.910274 75.279342 \nL 693.492312 74.603916 \nL 694.33119 72.741412 \nL 695.397342 70.282692 \nL 696.42473 67.817564 \nL 697.406676 65.364163 \nL 698.338805 62.938869 \nL 699.218795 60.555745 \nL 700.046181 58.226204 \nL 700.822155 55.95879 \nL 701.54927 53.759294 \nL 702.231163 51.630733 \nL 702.872267 49.57355 \nL 703.477386 47.58575 \nL 704.051278 45.663212 \nL 704.598271 43.799968 \nL 705.121904 41.988814 \nL 705.62465 40.222002 \nL 706.107704 38.492106 \nL 706.570968 36.792909 \nL 707.013208 35.120055 \nL 707.432188 33.471878 \nL 707.825045 31.849477 \nL 708.18869 30.25691 \nL 708.520342 28.700716 \nL 708.81786 27.189868 \nL 709.080122 25.735275 \nL 709.307083 24.349947 \nL 709.499847 23.048591 \nL 709.660383 21.847826 \nL 709.791242 20.765972 \nL 709.895203 19.822479 \nL 709.974907 19.037131 \nL 710.032628 18.42864 \nL 710.070117 18.01305 \nL 710.088574 17.80211 \nL 710.088628 17.801719 \nL 710.088719 17.801335 \nL 710.088848 17.800961 \nL 710.089012 17.800603 \nL 710.089211 17.800262 \nL 710.089442 17.799942 \nL 710.089703 17.799646 \nL 710.089992 17.799378 \nL 710.090305 17.799139 \nL 710.090641 17.798933 \nL 710.090995 17.79876 \nL 710.091364 17.798623 \nL 710.091744 17.798523 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708.52819 28.70237 \nL 708.196525 30.258623 \nL 708.196512 30.258681 \nL 707.832854 31.851302 \nL 707.832842 31.851354 \nL 707.439974 33.473802 \nL 707.439963 33.473846 \nL 707.020973 35.122064 \nL 707.020963 35.122101 \nL 706.578714 36.794989 \nL 706.578706 36.795019 \nL 706.115434 38.494243 \nL 706.115428 38.494267 \nL 705.632368 40.224185 \nL 705.632362 40.224204 \nL 705.129611 41.991034 \nL 705.129607 41.99105 \nL 704.60597 43.80222 \nL 704.605965 43.802236 \nL 704.058967 45.665497 \nL 704.058962 45.665515 \nL 703.485064 47.588072 \nL 703.485058 47.588093 \nL 702.879931 49.575916 \nL 702.879923 49.575941 \nL 702.238811 51.633152 \nL 702.238801 51.633182 \nL 701.556897 53.761777 \nL 701.556886 53.761813 \nL 700.829759 55.961346 \nL 700.829745 55.961386 \nL 700.053757 58.228842 \nL 700.053742 58.228886 \nL 699.226339 60.558472 \nL 699.226322 60.558519 \nL 698.346314 62.941692 \nL 698.346295 62.941742 \nL 697.414147 65.367087 \nL 697.414126 65.367139 \nL 696.432159 67.820593 \nL 696.432137 67.820646 \nL 695.404728 70.285827 \nL 695.404705 70.28588 \nL 694.33853 72.744651 \nL 694.338507 72.744703 \nL 693.510748 74.582522 \nL 694.09095 73.909227 \nL 695.265009 72.530005 \nL 696.426956 71.132285 \nL 697.570658 69.7091 \nL 698.689499 68.256887 \nL 699.776625 66.776081 \nL 700.824905 65.272068 \nL 701.826677 63.756031 \nL 702.773609 62.245346 \nL 703.656342 60.764098 \nL 704.46454 59.342636 \nL 705.187012 58.016782 \nL 705.812119 56.826072 \nL 706.328547 55.811016 \nL 706.726045 55.009965 \nL 706.996073 54.455765 \nL 707.132658 54.172326 \nL 707.132847 54.171979 \nL 707.133068 54.171653 \nL 707.13332 54.171349 \nL 707.133601 54.171073 \nL 707.133907 54.170825 \nL 707.134236 54.170608 \nL 707.134585 54.170425 \nL 707.13495 54.170277 \nL 707.135327 54.170166 \nL 707.135714 54.170092 \nL 707.136106 54.170057 \nL 707.136499 54.17006 \nL 707.13689 54.170103 \nL 707.137275 54.170183 \nL 707.137651 54.170301 \nL 707.138013 54.170455 \nL 707.138358 54.170645 \nL 707.138684 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701.464979 69.785527 \nL 702.55149 67.888594 \nL 703.59281 65.904703 \nL 704.573937 63.845985 \nL 705.480888 61.730736 \nL 706.302025 59.582023 \nL 707.029266 57.425663 \nL 707.658717 55.28734 \nL 708.19079 53.18941 \nL 708.62967 51.14877 \nL 708.982676 49.174768 \nL 709.259093 47.268751 \nL 709.468887 45.424747 \nL 709.6217 43.630984 \nL 709.725871 41.872865 \nL 709.788051 40.136441 \nL 709.813166 38.412396 \nL 709.804988 36.699669 \nL 709.766998 35.008719 \nL 709.703452 33.363433 \nL 709.620418 31.80117 \nL 709.526116 30.37091 \nL 709.430758 29.129069 \nL 709.34566 28.133469 \nL 709.281643 27.436227 \nL 709.247266 27.076925 \nL 709.247248 27.076531 \nL 709.247268 27.076136 \nL 709.247327 27.075746 \nL 709.247423 27.075363 \nL 709.247557 27.074991 \nL 709.247726 27.074634 \nL 709.247929 27.074296 \nL 709.248164 27.073979 \nL 709.248429 27.073687 \nL 709.248721 27.073423 \nL 709.249037 27.073188 \nL 709.249375 27.072986 \nL 709.249731 27.072818 \nL 709.250102 27.072686 \nL 709.250484 27.072591 \nL 709.250873 27.072534 \nL 709.251266 27.072515 \nL 709.251659 27.072535 \nL 709.252048 27.072594 \nL 709.25243 27.072691 \nL 709.2528 27.072825 \nL 709.253155 27.072995 \nL 709.253492 27.073199 \nL 709.253808 27.073435 \nL 709.254099 27.073701 \nL 709.254362 27.073994 \nL 709.254596 27.074312 \nL 709.254797 27.074651 \nL 709.254965 27.075009 \nL 709.255096 27.075381 \nL 709.255191 27.075765 \nL 709.255248 27.076155 \nL 709.289625 27.435465 \nL 709.289627 27.43548 \nL 709.353646 28.132743 \nL 709.353648 28.132768 \nL 709.438748 29.128398 \nL 709.438751 29.128433 \nL 709.534112 30.370313 \nL 709.534115 30.370357 \nL 709.628421 31.800664 \nL 709.628424 31.800716 \nL 709.71146 33.363033 \nL 709.711463 33.363092 \nL 709.775011 35.00844 \nL 709.775013 35.008505 \nL 709.813005 36.699523 \nL 709.813006 36.699595 \nL 709.821185 38.412397 \nL 709.821184 38.412475 \nL 709.796067 40.136602 \nL 709.796065 40.136687 \nL 709.733882 41.873202 \nL 709.733878 41.873296 \nL 709.629701 43.631514 \nL 709.629693 43.631618 \nL 709.476872 45.42549 \nL 709.47686 45.425604 \nL 709.267052 47.269726 \nL 709.267037 47.26985 \nL 708.990602 49.175994 \nL 708.99058 49.176125 \nL 708.63755 51.150262 \nL 708.637523 51.1504 \nL 708.198612 53.191182 \nL 708.198578 53.191325 \nL 707.666469 55.289401 \nL 707.666429 55.289549 \nL 707.036934 57.42802 \nL 707.036886 57.42817 \nL 706.309594 59.584681 \nL 706.30954 59.584832 \nL 705.488345 61.733695 \nL 705.488285 61.733845 \nL 704.58127 63.849241 \nL 704.581204 63.849387 \nL 703.60001 65.908248 \nL 703.59994 65.908387 \nL 702.558549 67.892413 \nL 702.558478 67.892543 \nL 701.471896 69.7896 \nL 701.471825 69.789719 \nL 700.35446 71.594446 \nL 700.354393 71.59455 \nL 699.218822 73.307914 \nL 699.218761 73.308004 \nL 698.074607 74.936647 \nL 698.074553 74.936722 \nL 696.927995 76.491545 \nL 696.92795 76.491605 \nL 695.781825 77.986179 \nL 695.781789 77.986226 \nL 694.636081 79.435502 \nL 694.636053 79.435537 \nL 693.488763 80.854706 \nL 693.488745 80.854729 \nL 692.337011 82.258027 \nL 692.337 82.25804 \nL 691.178077 83.658153 \nL 691.178074 83.658156 \nL 690.010164 85.065768 \nL 688.832969 86.489348 \nL 687.647782 87.935257 \nL 686.457391 89.407861 \nL 685.636203 90.442869 \nL 684.771112 92.114462 \nL 683.858187 93.884893 \nL 682.970333 95.612012 \nL 682.096418 97.312289 \nL 682.096414 97.312295 \nL 681.224693 99.001069 \nL 681.224687 99.001082 \nL 680.344438 100.691069 \nL 680.344428 100.691088 \nL 679.447217 102.391452 \nL 679.447205 102.391474 \nL 678.527902 104.107098 \nL 678.527889 104.107122 \nL 677.584873 105.838794 \nL 677.58486 105.838817 \nL 676.619859 107.583617 \nL 676.619847 107.583638 \nL 675.637054 109.336239 \nL 675.637044 109.336257 \nL 674.642181 111.090017 \nL 674.642173 111.090031 \nL 673.641277 112.838638 \nL 673.641271 112.838648 \nL 672.639779 114.577149 \nL 672.639776 114.577155 \nL 671.641786 116.302939 \nL 670.650046 118.015476 \nL 669.665988 119.716038 \nL 668.690345 121.406685 \nL 667.723494 123.089436 \nL 666.765953 124.765279 \nL 666.14491 125.858948 \nL 665.539118 127.439572 \nL 665.539099 127.439622 \nL 664.80828 129.27246 \nL 664.80826 129.272509 \nL 664.067935 131.060124 \nL 664.067915 131.060172 \nL 663.31843 132.805265 \nL 663.31841 132.805312 \nL 662.559609 134.511661 \nL 662.559588 134.511706 \nL 661.790771 136.184215 \nL 661.790751 136.184259 \nL 661.010674 137.828913 \nL 661.010654 137.828955 \nL 660.217401 139.452769 \nL 660.217382 139.452809 \nL 659.408392 141.063362 \nL 659.408373 141.063401 \nL 658.580692 142.6681 \nL 658.580672 142.668138 \nL 657.731155 144.273516 \nL 657.731135 144.273553 \nL 656.856987 145.884229 \nL 656.856966 145.884266 \nL 655.956267 147.502125 \nL 655.956244 147.502165 \nL 655.028317 149.125718 \nL 655.028293 149.12576 \nL 654.073892 150.750123 \nL 654.073865 150.750168 \nL 653.094862 152.367632 \nL 653.094832 152.367682 \nL 652.093877 153.968583 \nL 652.093842 153.968638 \nL 651.073412 155.543019 \nL 651.073371 155.543081 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240.05923 \nL 601.500475 241.784056 \nL 601.500426 241.784122 \nL 600.244696 243.45212 \nL 600.244647 243.452184 \nL 598.976124 245.068887 \nL 598.976076 245.068947 \nL 597.690549 246.645264 \nL 597.690505 246.645317 \nL 596.381428 248.195775 \nL 596.381389 248.195821 \nL 595.040784 249.736574 \nL 595.04075 249.736612 \nL 593.660698 251.282807 \nL 593.660669 251.282839 \nL 592.234868 252.846424 \nL 592.234843 252.846451 \nL 590.759733 254.4348 \nL 590.759711 254.434823 \nL 589.235187 256.050244 \nL 589.235167 256.050265 \nL 587.664855 257.690107 \nL 587.664836 257.690127 \nL 586.05543 259.348131 \nL 586.055412 259.34815 \nL 584.415818 261.015889 \nL 584.415801 261.015906 \nL 582.755795 262.684589 \nL 582.755779 262.684604 \nL 582.699842 262.740236 \nL 581.544763 265.247463 \nL 581.544729 265.247536 \nL 580.193243 268.033476 \nL 580.19321 268.033541 \nL 578.784549 270.809101 \nL 578.784518 270.80916 \nL 577.329932 273.561858 \nL 577.329902 273.561913 \nL 575.841214 276.276125 \nL 575.841184 276.276179 \nL 575.72584 276.47909 \nL 576.416527 275.77504 \nL 577.775165 274.354686 \nL 579.115143 272.915255 \nL 580.430715 271.461764 \nL 581.71714 270.000033 \nL 582.971367 268.53569 \nL 584.192421 267.073386 \nL 585.381297 265.616463 \nL 586.540881 264.166562 \nL 587.675703 262.723439 \nL 588.791314 261.285391 \nL 589.893918 259.849373 \nL 590.989901 258.411455 \nL 592.085013 256.967649 \nL 593.184069 255.514266 \nL 594.290349 254.048737 \nL 595.405497 252.569794 \nL 596.529461 251.07768 \nL 597.660725 249.574041 \nL 598.797008 248.061211 \nL 599.935915 246.541583 \nL 601.075843 245.016563 \nL 602.216684 243.485767 \nL 603.360372 241.946322 \nL 604.511029 240.39276 \nL 605.67481 238.817171 \nL 606.859007 237.210325 \nL 608.071289 235.562589 \nL 609.318231 233.865764 \nL 610.604292 232.114238 \nL 611.930935 230.30593 \nL 613.296019 228.442932 \nL 614.693879 226.531172 \nL 616.115697 224.579826 \nL 617.550537 222.599918 \nL 618.986387 220.603175 \nL 620.411573 218.600431 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158.902181 \nL 656.291966 157.323813 \nL 656.292006 157.323756 \nL 657.368641 155.814021 \nL 657.368675 155.813975 \nL 658.433718 154.36419 \nL 658.433743 154.364156 \nL 659.483034 152.967025 \nL 659.483052 152.967002 \nL 660.512679 151.616951 \nL 660.512691 151.616936 \nL 661.519596 150.309883 \nL 661.519603 150.309873 \nL 662.501807 149.043048 \nL 662.501812 149.043041 \nL 663.458793 147.814225 \nL 663.458797 147.814219 \nL 664.39152 146.621235 \nL 664.391525 146.621228 \nL 665.302433 145.461296 \nL 665.30244 145.461287 \nL 666.195097 144.330972 \nL 666.195106 144.330961 \nL 667.074201 143.225714 \nL 667.074212 143.225701 \nL 667.945248 142.139859 \nL 667.94526 142.139844 \nL 668.814244 141.067036 \nL 668.814258 141.06702 \nL 669.68769 139.999975 \nL 669.687704 139.999958 \nL 670.572119 138.931183 \nL 670.572133 138.931167 \nL 671.473868 137.853272 \nL 671.473882 137.853257 \nL 672.398809 136.759088 \nL 672.398821 136.759074 \nL 673.351841 135.642359 \nL 673.351851 135.642347 \nL 674.336663 134.497683 \nL 674.33667 134.497674 \nL 675.35559 133.320577 \nL 675.355594 133.320571 \nL 676.409516 132.107314 \nL 677.498027 130.85473 \nL 678.619635 129.559881 \nL 679.77212 128.219774 \nL 680.952578 126.831499 \nL 682.157716 125.392135 \nL 683.383761 123.8992 \nL 684.626546 122.35086 \nL 685.881463 120.74643 \nL 687.143742 119.086365 \nL 688.408486 117.372676 \nL 689.671057 115.608766 \nL 690.927435 113.799244 \nL 692.174254 111.950013 \nL 693.408978 110.067973 \nL 694.629888 108.160655 \nL 695.835936 106.235938 \nL 697.026657 104.301461 \nL 698.20207 102.364056 \nL 699.362566 100.42929 \nL 700.508888 98.501048 \nL 701.642082 96.581375 \nL 702.763541 94.670555 \nL 703.87478 92.767641 \nL 704.977256 90.870946 \nL 706.072122 88.978876 \nL 707.160039 87.090302 \nL 708.240886 85.205039 \nL 709.313586 83.324018 \nL 710.375972 81.448987 \nL 711.424737 79.582063 \nL 712.455078 77.725313 \nL 713.460667 75.879936 \nL 714.433393 74.045756 \nL 715.36325 72.220978 \nL 716.238572 70.401529 \nL 717.046629 68.5809 \nL 717.774007 66.750738 \nL 718.408273 64.9007 \nL 718.939158 63.019591 \nL 719.359885 61.096486 \nL 719.668877 59.121587 \nL 719.870254 57.087862 \nL 719.974289 54.992227 \nL 719.997242 52.835986 \nL 719.960486 50.625398 \nL 719.889039 48.371798 \nL 719.809556 46.091633 \nL 719.809555 46.091602 \nL 719.747719 43.806613 \nL 719.747718 43.806544 \nL 719.725396 41.544233 \nL 719.725396 41.544135 \nL 719.757589 39.338606 \nL 719.757593 39.338488 \nL 719.850067 37.230936 \nL 719.850075 37.23081 \nL 719.997782 35.269781 \nL 719.997793 35.269657 \nL 720.184981 33.50962 \nL 720.184994 33.509507 \nL 720.387303 32.008029 \nL 720.387317 32.007935 \nL 720.575551 30.821287 \nL 720.575562 30.821217 \nL 720.720795 29.998878 \nL 720.720803 29.998835 \nL 720.799864 29.577756 \nL 720.799955 29.577372 \nL 720.800084 29.576999 \nL 720.800249 29.57664 \nL 720.800448 29.576299 \nL 720.800679 29.57598 \nL 720.80094 29.575684 \nL 720.801229 29.575416 \nL 720.801543 29.575178 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719.982306 54.992392 \nL 719.982302 54.992549 \nL 719.878258 57.088362 \nL 719.878243 57.08856 \nL 719.676845 59.122497 \nL 719.676816 59.122724 \nL 719.367788 61.097855 \nL 719.367743 61.098094 \nL 718.946964 63.021436 \nL 718.946905 63.021669 \nL 718.415957 64.903002 \nL 718.415891 64.903215 \nL 717.781557 66.75345 \nL 717.78149 66.753632 \nL 717.054047 68.583957 \nL 717.053985 68.584104 \nL 716.245871 70.404862 \nL 716.245819 70.404975 \nL 715.370451 72.224521 \nL 715.37041 72.224603 \nL 714.440516 74.049452 \nL 714.440486 74.049511 \nL 713.467734 75.883739 \nL 713.467713 75.88378 \nL 712.462105 77.72919 \nL 712.46209 77.729217 \nL 711.431736 79.58599 \nL 711.431726 79.586009 \nL 710.382953 81.452948 \nL 710.382946 81.452961 \nL 709.320553 83.328003 \nL 709.320547 83.328013 \nL 708.247842 85.209043 \nL 708.247838 85.209051 \nL 707.166986 87.094322 \nL 707.166982 87.094329 \nL 706.079061 88.98291 \nL 706.079057 88.982917 \nL 704.984187 90.874994 \nL 704.984183 90.875001 \nL 703.881704 92.771702 \nL 703.8817 92.771709 \nL 702.770456 94.67463 \nL 702.770451 94.674638 \nL 701.648988 96.585466 \nL 701.648982 96.585475 \nL 700.515783 98.505158 \nL 700.515776 98.505169 \nL 699.369447 100.433423 \nL 699.369439 100.433437 \nL 698.208934 102.368218 \nL 698.208924 102.368235 \nL 697.033498 104.30566 \nL 697.033484 104.305682 \nL 695.842748 106.240184 \nL 695.842731 106.240211 \nL 694.636665 108.164958 \nL 694.636644 108.164991 \nL 693.415711 110.072345 \nL 693.415687 110.072383 \nL 692.180937 111.954462 \nL 692.180909 111.954505 \nL 690.934059 113.80378 \nL 690.934028 113.803825 \nL 689.677619 115.613394 \nL 689.677586 115.613441 \nL 688.41498 117.377397 \nL 688.414946 117.377445 \nL 687.150167 119.091181 \nL 687.150132 119.091228 \nL 685.88782 120.751337 \nL 685.887786 120.75138 \nL 684.632837 122.355852 \nL 684.632805 122.355891 \nL 683.38999 123.904269 \nL 683.389962 123.904304 \nL 682.163891 125.397271 \nL 682.163866 125.397301 \nL 680.958706 126.836691 \nL 680.958686 126.836714 \nL 679.778211 128.22501 \nL 679.778196 128.225027 \nL 678.6257 129.565148 \nL 678.62569 129.565158 \nL 677.504075 130.860015 \nL 677.504071 130.86002 \nL 676.415559 132.112606 \nL 675.361639 133.32586 \nL 674.342727 134.50295 \nL 673.357925 135.647604 \nL 672.404916 136.764305 \nL 671.480002 137.858458 \nL 670.57828 138.936336 \nL 669.693878 140.005095 \nL 668.820459 141.072123 \nL 667.951487 142.144916 \nL 667.080462 143.230744 \nL 666.201376 144.335979 \nL 665.308726 145.466285 \nL 664.397825 146.626209 \nL 663.465107 147.819187 \nL 662.508131 149.047996 \nL 661.525934 150.314813 \nL 660.51904 151.621853 \nL 659.489427 152.971884 \nL 658.440158 154.368986 \nL 657.375145 155.818731 \nL 656.298546 157.328414 \nL 655.214241 158.906718 \nL 654.125509 160.562559 \nL 653.034794 162.303692 \nL 651.943668 164.134941 \nL 650.853025 166.056487 \nL 649.763322 168.062634 \nL 648.674875 170.141462 \nL 647.588019 172.275521 \nL 646.503023 174.443718 \nL 645.419989 176.62377 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214.614055 \nL 621.822525 216.605089 \nL 621.822508 216.605113 \nL 620.41812 218.60508 \nL 620.418105 218.605101 \nL 618.992905 220.607863 \nL 618.992894 220.607879 \nL 617.557034 222.604636 \nL 617.557025 222.604648 \nL 616.122178 224.584566 \nL 616.122172 224.584575 \nL 614.700349 226.535928 \nL 614.700345 226.535933 \nL 613.302481 228.447698 \nL 613.302479 228.447701 \nL 611.937393 230.310702 \nL 610.610748 232.119013 \nL 609.324684 233.870541 \nL 608.077741 235.567369 \nL 606.865456 237.215109 \nL 605.681255 238.821961 \nL 605.681252 238.821964 \nL 604.517468 240.397558 \nL 604.517465 240.397562 \nL 603.366805 241.951129 \nL 603.366801 241.951133 \nL 602.22311 243.490583 \nL 602.223106 243.490587 \nL 601.082262 245.021389 \nL 601.082258 245.021393 \nL 599.942327 246.546418 \nL 599.942324 246.546422 \nL 598.803414 248.066053 \nL 598.803412 248.066057 \nL 597.667126 249.578889 \nL 596.535859 251.082533 \nL 595.411892 252.574651 \nL 594.296741 254.053597 \nL 593.190458 255.51913 \nL 592.091397 256.97252 \nL 592.091394 256.972524 \nL 590.996278 258.416337 \nL 590.996272 258.416344 \nL 589.900281 259.854272 \nL 589.900273 259.854283 \nL 588.797659 261.290314 \nL 588.797646 261.29033 \nL 587.682021 262.728396 \nL 587.682005 262.728417 \nL 586.547164 264.171564 \nL 586.547143 264.17159 \nL 585.387537 265.621519 \nL 585.387512 265.62155 \nL 584.198609 267.078505 \nL 584.19858 267.07854 \nL 582.977495 268.540881 \nL 582.977463 268.54092 \nL 581.723202 270.005302 \nL 581.723167 270.005343 \nL 580.436706 271.467116 \nL 580.436668 271.467158 \nL 579.121059 272.92069 \nL 579.12102 272.920732 \nL 577.781005 274.360203 \nL 577.780967 274.360242 \nL 576.422293 275.780635 \nL 576.422258 275.780672 \nL 575.710333 276.506369 \nL 574.330458 278.933825 \nL 574.330426 278.933879 \nL 572.80974 281.515421 \nL 572.809706 281.515477 \nL 571.290854 284.0011 \nL 571.290817 284.001159 \nL 569.784729 286.372359 \nL 569.784687 286.372423 \nL 568.300882 288.613492 \nL 568.300835 288.613562 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279.998152 \nL 578.336901 279.998163 \nL 578.337291 279.998213 \nL 578.337675 279.9983 \nL 578.338048 279.998425 \nL 578.338407 279.998587 \nL 578.338749 279.998783 \nL 578.33907 279.999011 \nL 578.339367 279.99927 \nL 578.339637 279.999557 \nL 578.339878 279.999869 \nL 578.340088 280.000204 \nL 578.340264 280.000557 \nL 578.340404 280.000926 \nL 578.340508 280.001307 \nL 578.340574 280.001696 \nL 578.340601 280.002091 \nL 578.34059 280.002485 \nL 578.340541 280.002877 \nL 578.340454 280.003262 \nL 578.340329 280.003637 \nL 578.340168 280.003998 \nL 578.339973 280.004341 \nL 578.339746 280.004663 \nL 578.339488 280.004961 \nL 578.339202 280.005233 \nL 578.044594 280.258717 \nL 577.477068 280.75798 \nL 576.676237 281.488128 \nL 575.693551 282.427566 \nL 574.584585 283.549176 \nL 573.401737 284.821811 \nL 572.188481 286.212211 \nL 570.976155 287.687063 \nL 569.783163 289.215124 \nL 568.616338 290.769021 \nL 567.473691 292.326539 \nL 566.347785 293.871052 \nL 566.347774 293.871067 \nL 565.882267 294.50351 \nL 566.250304 294.621618 \nL 566.250696 294.621767 \nL 566.25107 294.621956 \nL 569.315343 296.377032 \nL 569.315657 296.377232 \nL 569.315951 296.37746 \nL 569.316223 296.377714 \nL 571.528154 298.647887 \nL 571.528434 298.648206 \nL 571.528679 298.648554 \nL 573.325487 301.507415 \nL 575.066331 302.672602 \nL 575.0666 302.672799 \nL 575.066851 302.673017 \nL 575.067084 302.673255 \nL 577.334725 305.196685 \nL 577.33497 305.196985 \nL 577.335184 305.197307 \nL 577.335367 305.197648 \nL 577.335516 305.198005 \nL 577.33563 305.198374 \nL 577.722175 306.700194 \nL 577.722255 306.700578 \nL 577.722296 306.700969 \nL 577.7223 306.701362 \nL 577.722265 306.701753 \nL 577.335722 309.505216 \nL 577.178511 310.726002 \nL 577.335521 311.164013 \nL 577.335636 311.164391 \nL 578.237116 314.750715 \nL 578.237199 314.75114 \nL 578.237236 314.751571 \nL 578.237227 314.752004 \nL 578.237171 314.752433 \nL 577.494537 318.776904 \nL 578.330743 322.801377 \nL 578.330804 322.801764 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362.659708 \nL 457.055661 362.330016 \nL 453.046582 362.235484 \nL 453.046442 362.235478 \nL 449.037251 362.000101 \nL 445.028061 361.775913 \nL 445.028012 361.77591 \nL 441.018816 361.502549 \nL 441.018442 361.502506 \nL 441.018074 361.502427 \nL 437.008985 360.449547 \nL 436.243667 360.293326 \nL 435.772432 360.383254 \nL 433.72213 360.78728 \nL 431.706197 361.195978 \nL 429.724261 361.607263 \nL 427.774591 362.018848 \nL 425.854282 362.428406 \nL 423.959591 362.833714 \nL 422.086082 363.232923 \nL 422.086074 363.232925 \nL 420.229075 363.624707 \nL 420.229064 363.624709 \nL 418.383869 364.008456 \nL 418.383856 364.008459 \nL 416.644625 364.364218 \nL 416.062896 364.669763 \nL 414.746143 365.37095 \nL 413.466452 366.056996 \nL 412.213936 366.729069 \nL 412.213931 366.729071 \nL 410.976122 367.390836 \nL 410.976112 367.390841 \nL 409.738463 368.04776 \nL 409.738448 368.047768 \nL 408.485378 368.706265 \nL 408.485361 368.706274 \nL 407.201534 369.372806 \nL 407.201514 369.372816 \nL 405.873985 370.052674 \nL 405.873964 370.052684 \nL 404.493385 370.749315 \nL 404.493363 370.749327 \nL 403.055661 371.463673 \nL 403.055639 371.463684 \nL 401.562596 372.194082 \nL 401.562574 372.194093 \nL 400.022108 372.936438 \nL 400.022088 372.936447 \nL 398.447702 373.684629 \nL 398.447685 373.684637 \nL 396.857904 374.430975 \nL 396.85789 374.430981 \nL 395.440775 375.089758 \nL 394.067596 376.082073 \nL 392.459484 377.303322 \nL 390.884457 378.564761 \nL 389.349161 379.865828 \nL 387.860239 381.205127 \nL 386.423819 382.580333 \nL 385.045166 383.988373 \nL 383.7281 385.425901 \nL 382.474974 386.888945 \nL 381.286579 388.373539 \nL 380.162583 389.875792 \nL 379.101915 391.392162 \nL 378.103482 392.919901 \nL 377.166658 394.457839 \nL 376.291638 396.007222 \nL 375.479513 397.572527 \nL 374.732248 399.162114 \nL 374.052155 400.788345 \nL 373.441677 402.466568 \nL 372.902726 404.213462 \nL 372.436173 406.044475 \nL 372.041543 407.970764 \nL 371.716745 409.996431 \nL 371.45801 412.116393 \nL 371.259886 414.315585 \nL 371.115562 416.569676 \nL 371.017185 418.847036 \nL 370.95619 421.111625 \nL 370.923724 423.326164 \nL 370.911263 425.454776 \nL 370.910974 427.464916 \nL 370.916292 429.327709 \nL 370.922259 431.018304 \nL 370.922259 431.018309 \nL 370.92578 432.514783 \nL 370.92578 432.514793 \nL 370.925592 433.797521 \nL 370.925591 433.797534 \nL 370.922098 434.848794 \nL 370.922098 434.848807 \nL 370.916786 435.652982 \nL 370.916786 435.652993 \nL 370.911679 436.197046 \nL 370.911679 436.197053 \nL 370.908583 436.471579 \nL 370.908559 436.471974 \nL 370.908497 436.472364 \nL 370.908397 436.472746 \nL 370.90826 436.473116 \nL 370.908088 436.473471 \nL 370.907882 436.473808 \nL 370.907644 436.474122 \nL 370.907376 436.474412 \nL 370.907082 436.474674 \nL 370.906763 436.474906 \nL 370.906423 436.475105 \nL 370.906066 436.47527 \nL 370.905694 436.475399 \nL 370.905311 436.47549 \nL 370.904921 436.475544 \nL 370.904528 436.475559 \nL 370.904136 436.475535 \nL 370.903747 436.475472 \nL 370.903366 436.475372 \nL 370.902998 436.475235 \nL 370.902644 436.475062 \nL 370.902309 436.474855 \nL 370.901995 436.474616 \nL 370.901707 436.474348 \nL 370.901446 436.474052 \nL 370.901215 436.473732 \nL 370.901017 436.473391 \nL 370.900852 436.473032 \nL 370.900724 436.472658 \nL 370.900633 436.472274 \nL 370.90058 436.471883 \nL 370.900565 436.471488 \nL 370.903661 436.196966 \nL 370.908768 435.652923 \nL 370.914079 434.84876 \nL 370.917573 433.797514 \nL 370.917762 432.514797 \nL 370.914241 431.018331 \nL 370.908274 429.327736 \nL 370.902955 427.464933 \nL 370.902955 427.464921 \nL 370.903245 425.454764 \nL 370.903245 425.454741 \nL 370.915705 423.326099 \nL 370.915706 423.326063 \nL 370.948173 421.111481 \nL 370.948174 421.111432 \nL 371.009171 418.846785 \nL 371.009173 418.84672 \nL 371.107553 416.569285 \nL 371.107557 416.569202 \nL 371.251888 414.315016 \nL 371.251896 414.314912 \nL 371.450029 412.115604 \nL 371.450043 412.115477 \nL 371.708795 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379.859714 \nL 390.879327 378.558573 \nL 390.879413 378.558503 \nL 392.454524 377.296996 \nL 392.454606 377.296933 \nL 394.062797 376.075624 \nL 394.062874 376.075567 \nL 395.402295 375.107647 \nL 395.275207 375.166726 \nL 395.275198 375.166731 \nL 393.725371 375.88219 \nL 393.725366 375.882192 \nL 392.236597 376.566803 \nL 390.838747 377.209078 \nL 389.562731 377.796482 \nL 388.902511 378.1016 \nL 388.669254 378.257309 \nL 387.300169 379.182827 \nL 385.959169 380.102956 \nL 384.647431 381.018987 \nL 383.364997 381.933256 \nL 382.111115 382.849023 \nL 380.884798 383.770196 \nL 379.684989 384.701204 \nL 378.510533 385.647068 \nL 377.360103 386.613275 \nL 376.231843 387.606179 \nL 375.123319 388.633077 \nL 374.031561 389.701937 \nL 372.953375 390.821383 \nL 371.885915 392.000055 \nL 370.827223 393.246154 \nL 369.777001 394.566465 \nL 368.736947 395.966181 \nL 367.710954 397.448333 \nL 366.70496 399.014093 \nL 365.726361 400.663421 \nL 364.783557 402.395929 \nL 363.885234 404.212075 \nL 363.039656 406.11392 \nL 362.254375 408.105706 \nL 361.535923 410.193459 \nL 360.889982 412.383721 \nL 360.321513 414.681656 \nL 359.834918 417.088644 \nL 359.434005 419.600195 \nL 359.121864 422.20459 \nL 358.900194 424.882514 \nL 358.76903 427.607848 \nL 358.726153 430.349756 \nL 358.766829 433.075434 \nL 358.883836 435.753027 \nL 359.06792 438.354409 \nL 359.308529 440.857259 \nL 359.594519 443.246633 \nL 359.915062 445.515146 \nL 360.26021 447.663092 \nL 360.621201 449.697904 \nL 360.990495 451.633213 \nL 361.361452 453.487958 \nL 361.727869 455.285142 \nL 361.727871 455.285151 \nL 362.083315 457.050707 \nL 362.083322 457.050744 \nL 362.420644 458.812049 \nL 362.420656 458.812116 \nL 362.731574 460.596411 \nL 362.731589 460.596505 \nL 363.006538 462.429454 \nL 363.006554 462.429572 \nL 363.234891 464.333809 \nL 363.234905 464.333946 \nL 363.405474 466.327641 \nL 363.405484 466.327789 \nL 363.507492 468.423462 \nL 363.507497 468.423615 \nL 363.531523 470.627243 \nL 363.531522 470.627394 \nL 363.470477 472.938055 \nL 363.470471 472.938199 \nL 363.320786 475.34719 \nL 363.320776 475.347324 \nL 363.082786 477.838761 \nL 363.082773 477.838882 \nL 362.761022 480.390151 \nL 362.761007 480.390259 \nL 362.363821 482.973641 \nL 362.363806 482.973737 \nL 361.902583 485.558082 \nL 361.902567 485.558166 \nL 361.390592 488.111782 \nL 361.390576 488.111857 \nL 360.841443 490.605214 \nL 360.841428 490.605281 \nL 360.267829 493.013506 \nL 360.267813 493.013568 \nL 359.679979 495.318656 \nL 359.679963 495.318717 \nL 359.084651 497.510643 \nL 359.084634 497.510705 \nL 358.484681 499.587467 \nL 358.48466 499.587536 \nL 357.878766 501.553961 \nL 357.878741 501.554039 \nL 357.262073 503.419963 \nL 357.262042 503.420054 \nL 356.627018 505.198061 \nL 356.626979 505.198166 \nL 355.96442 506.90137 \nL 355.964371 506.90149 \nL 355.264595 508.541937 \nL 355.264536 508.54207 \nL 354.518425 510.129618 \nL 354.518354 510.129761 \nL 353.717895 511.671882 \nL 353.717814 511.67203 \nL 352.856531 513.174378 \nL 352.856442 513.174526 \nL 351.929511 514.641544 \nL 351.929416 514.641688 \nL 350.93361 516.077417 \nL 350.933512 516.077552 \nL 349.8674 517.48603 \nL 349.867303 517.486153 \nL 348.731465 518.871481 \nL 348.731373 518.871589 \nL 347.528805 520.237256 \nL 347.528721 520.237348 \nL 346.265345 521.585412 \nL 346.26527 521.58549 \nL 344.950095 522.915558 \nL 344.950029 522.915623 \nL 343.595009 524.224453 \nL 343.59495 524.224509 \nL 342.214022 525.50555 \nL 342.213966 525.505601 \nL 340.821582 526.749648 \nL 340.821525 526.749698 \nL 339.430932 527.945902 \nL 339.430869 527.945955 \nL 338.052119 529.083306 \nL 338.052043 529.083366 \nL 336.690736 530.152048 \nL 336.690643 530.152118 \nL 335.347091 531.144887 \nL 335.346977 531.144969 \nL 334.016296 532.05797 \nL 334.016159 532.058059 \nL 332.689153 532.891177 \nL 332.688998 532.89127 \nL 331.353866 533.647802 \nL 331.353699 533.647891 \nL 329.997704 534.333906 \nL 329.997536 534.333986 \nL 328.609031 534.957535 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542.279691 \nL 289.524214 542.562216 \nL 287.372784 542.854787 \nL 285.204215 543.156178 \nL 283.03007 543.464357 \nL 280.861964 543.776931 \nL 278.710071 544.09167 \nL 276.581671 544.407064 \nL 274.480267 544.722713 \nL 272.404909 545.039543 \nL 270.350729 545.359595 \nL 268.309601 545.685772 \nL 266.27192 546.021035 \nL 264.228312 546.36783 \nL 262.171226 546.727476 \nL 260.096142 547.099889 \nL 258.001971 547.483709 \nL 255.890615 547.876934 \nL 253.765913 548.277856 \nL 251.632515 548.686242 \nL 249.494732 549.104287 \nL 247.356106 549.537361 \nL 245.219341 549.994008 \nL 243.373234 550.419422 \nL 245.162336 550.293041 \nL 245.162384 550.293038 \nL 246.898903 550.191248 \nL 246.898925 550.191246 \nL 248.592284 550.101439 \nL 250.254585 550.012931 \nL 251.897933 549.917538 \nL 253.533787 549.809659 \nL 255.172698 549.686119 \nL 256.824069 549.545769 \nL 258.495901 549.389071 \nL 260.194731 549.21765 \nL 261.925627 549.033869 \nL 263.692493 548.840379 \nL 265.498236 548.639844 \nL 267.344732 548.434742 \nL 267.344736 548.434741 \nL 269.232939 548.227187 \nL 269.232946 548.227186 \nL 271.162631 548.018885 \nL 271.16264 548.018884 \nL 273.132363 547.811017 \nL 273.132373 547.811016 \nL 275.139109 547.604347 \nL 275.139119 547.604346 \nL 277.178472 547.399154 \nL 277.178479 547.399154 \nL 279.244852 547.195315 \nL 279.244857 547.195314 \nL 281.332092 546.992322 \nL 283.433908 546.789436 \nL 285.544359 546.585797 \nL 287.658057 546.380578 \nL 289.769951 546.173142 \nL 291.875085 545.963153 \nL 293.968159 545.750555 \nL 296.043526 545.535424 \nL 298.094973 545.317844 \nL 300.116384 545.097579 \nL 302.102262 544.873865 \nL 304.048607 544.645207 \nL 305.95362 544.409381 \nL 307.818133 544.163475 \nL 309.645724 543.904104 \nL 311.442491 543.627644 \nL 313.21645 543.330449 \nL 314.976654 543.009105 \nL 316.7323 542.660415 \nL 318.491333 542.281606 \nL 320.259711 541.870217 \nL 322.040325 541.424128 \nL 323.8326 540.941526 \nL 325.632189 540.420929 \nL 327.431347 539.861343 \nL 329.219617 539.262201 \nL 330.985108 538.623349 \nL 332.715605 537.945051 \nL 333.698326 537.526566 \nL 334.45361 537.058621 \nL 335.708384 536.210201 \nL 336.942806 535.303741 \nL 338.160447 534.338685 \nL 339.363325 533.317008 \nL 340.551558 532.243149 \nL 341.723428 531.123791 \nL 342.875528 529.967101 \nL 344.003369 528.781719 \nL 345.102044 527.575541 \nL 346.167369 526.354358 \nL 347.196668 525.12109 \nL 348.189534 523.875185 \nL 349.147824 522.613076 \nL 350.075271 521.329072 \nL 350.976451 520.01706 \nL 351.855708 518.672247 \nL 352.715769 517.292817 \nL 353.557066 515.880816 \nL 354.377442 514.442264 \nL 355.172663 512.986426 \nL 355.937207 511.524309 \nL 356.665372 510.067095 \nL 357.352345 508.624528 \nL 357.994789 507.204346 \nL 358.590881 505.81257 \nL 359.140123 504.454628 \nL 359.642597 503.1374 \nL 360.098282 501.871246 \nL 360.50644 500.671846 \nL 360.865352 499.560851 \nL 361.172298 498.565448 \nL 361.423885 497.716461 \nL 361.616579 497.045118 \nL 361.747098 496.579584 \nL 361.813008 496.3411 \nL 361.813132 496.340725 \nL 361.813292 496.340364 \nL 361.813486 496.340021 \nL 361.813713 496.339698 \nL 361.81397 496.339399 \nL 361.814255 496.339127 \nL 361.814565 496.338884 \nL 361.814898 496.338673 \nL 361.815249 496.338495 \nL 361.815616 496.338354 \nL 361.815996 496.338248 \nL 361.816383 496.338181 \nL 361.816776 496.338152 \nL 361.817169 496.338162 \nL 361.81756 496.338211 \nL 361.817943 496.338298 \nL 361.818317 496.338422 \nL 361.818677 496.338582 \nL 361.819019 496.338777 \nL 361.81934 496.339005 \nL 361.819638 496.339263 \nL 361.819909 496.339549 \nL 361.820151 496.339861 \nL 361.820361 496.340195 \nL 361.820538 496.340548 \nL 361.820679 496.340917 \nL 361.820784 496.341297 \nL 361.820851 496.341687 \nL 361.82088 496.342081 \nL 361.82087 496.342475 \nL 361.820821 496.342867 \nL 361.820735 496.343253 \nL 361.754823 496.581744 \nL 361.754819 496.581758 \nL 361.624294 497.047312 \nL 361.624287 497.047336 \nL 361.431585 497.718707 \nL 361.431575 497.718741 \nL 361.179977 498.567765 \nL 361.179964 498.567808 \nL 360.873004 499.563257 \nL 360.872987 499.563309 \nL 360.514058 500.674359 \nL 360.514038 500.674419 \nL 360.105858 501.873882 \nL 360.105835 501.873949 \nL 359.650125 503.140172 \nL 359.650098 503.140244 \nL 359.147597 504.457545 \nL 359.147567 504.45762 \nL 358.598295 505.815637 \nL 358.598263 505.815712 \nL 358.002139 507.207563 \nL 358.002106 507.207638 \nL 357.35963 508.627893 \nL 357.359596 508.627965 \nL 356.672589 510.070602 \nL 356.672556 510.070671 \nL 355.944357 511.527952 \nL 355.944324 511.528018 \nL 355.179746 512.990201 \nL 355.179711 512.990265 \nL 354.384455 514.446168 \nL 354.384419 514.446232 \nL 353.564006 515.88485 \nL 353.563967 515.884916 \nL 352.722629 517.296985 \nL 352.722587 517.297054 \nL 351.862481 518.676556 \nL 351.862435 518.676629 \nL 350.983129 520.021516 \nL 350.983078 520.021592 \nL 350.081845 521.333682 \nL 350.08179 521.33376 \nL 349.154287 522.617841 \nL 349.15423 522.617918 \nL 348.195883 523.880103 \nL 348.195825 523.880177 \nL 347.2029 525.126155 \nL 347.202843 525.126226 \nL 346.173487 526.359562 \nL 346.173429 526.359629 \nL 345.108047 527.580878 \nL 345.10799 527.580942 \nL 344.009257 528.787184 \nL 344.009197 528.787248 \nL 342.881294 529.972695 \nL 342.88123 529.972761 \nL 341.729062 531.129519 \nL 341.728991 531.129589 \nL 340.557045 532.24902 \nL 340.556963 532.249096 \nL 339.368643 533.323033 \nL 339.368551 533.323115 \nL 338.165574 534.344875 \nL 338.165469 534.344961 \nL 336.947717 535.310106 \nL 336.9476 535.310195 \nL 335.713055 536.216745 \nL 335.712928 536.216834 \nL 334.458023 537.065343 \nL 334.457889 537.06543 \nL 333.747159 537.505771 \nL 334.400041 537.227746 \nL 336.02968 536.471759 \nL 337.598764 535.677316 \nL 339.104876 534.844226 \nL 340.548639 533.971921 \nL 341.933068 533.059474 \nL 343.262591 532.105771 \nL 344.541971 531.109634 \nL 345.775383 530.0699 \nL 346.966023 528.985097 \nL 348.115943 527.853105 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321.366183 542.794045 \nL 319.639819 543.296514 \nL 319.639753 543.296533 \nL 317.858124 543.78207 \nL 317.858067 543.782085 \nL 316.025976 544.252764 \nL 316.02593 544.252776 \nL 314.149786 544.711218 \nL 314.149751 544.711226 \nL 312.23765 545.160577 \nL 312.237627 545.160582 \nL 310.298727 545.604569 \nL 310.298717 545.604571 \nL 308.342672 546.047346 \nL 306.378777 546.493242 \nL 304.415305 546.946402 \nL 302.458672 547.41046 \nL 300.513276 547.888001 \nL 298.581387 548.3803 \nL 296.663486 548.887038 \nL 294.758855 549.406187 \nL 292.866052 549.934165 \nL 290.983149 550.466223 \nL 289.108108 550.996904 \nL 289.108097 550.996907 \nL 287.238579 551.520698 \nL 287.238558 551.520704 \nL 285.372291 552.032568 \nL 285.372261 552.032576 \nL 283.506771 552.528468 \nL 283.506734 552.528478 \nL 281.639859 553.005543 \nL 281.639818 553.005553 \nL 279.769953 553.462202 \nL 279.76991 553.462212 \nL 277.896502 553.897909 \nL 277.89646 553.897919 \nL 276.020238 554.312932 \nL 276.020198 554.31294 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562.614628 \nL 230.232323 563.152996 \nL 229.030973 563.695902 \nL 227.941127 564.225499 \nL 226.9848 564.720249 \nL 226.184555 565.156305 \nL 225.561912 565.509688 \nL 225.135339 565.758963 \nL 224.918466 565.887961 \nL 224.918118 565.888146 \nL 224.917753 565.888295 \nL 224.917376 565.888408 \nL 224.91699 565.888483 \nL 224.916598 565.88852 \nL 224.916205 565.888518 \nL 224.915814 565.888477 \nL 224.915428 565.888398 \nL 224.915052 565.888281 \nL 224.914689 565.888128 \nL 224.914343 565.88794 \nL 224.914017 565.887719 \nL 224.913715 565.887467 \nL 224.913438 565.887186 \nL 224.91319 565.886879 \nL 224.912973 565.88655 \nL 224.912789 565.886201 \nL 224.91264 565.885835 \nL 224.912528 565.885456 \nL 224.912453 565.885068 \nL 224.912417 565.884675 \nL 224.912419 565.88428 \nL 224.912459 565.883887 \nL 224.912538 565.8835 \nL 224.912654 565.883123 \nL 224.912807 565.882759 \nL 224.912994 565.882411 \nL 224.913214 565.882084 \nL 224.913465 565.88178 \nL 224.913745 565.881502 \nL 224.91405 565.881253 \nL 224.914379 565.881035 \nL 225.131266 565.752029 \nL 225.131292 565.752014 \nL 225.557901 565.502718 \nL 225.557945 565.502693 \nL 226.180639 565.14928 \nL 226.1807 565.149246 \nL 226.981013 564.713153 \nL 226.981089 564.713112 \nL 227.937499 564.218319 \nL 227.937588 564.218274 \nL 229.02753 563.688631 \nL 229.027631 563.688584 \nL 230.229086 563.145631 \nL 230.229195 563.145583 \nL 231.521564 562.607169 \nL 231.521677 562.607124 \nL 232.886579 562.086772 \nL 232.886693 562.086731 \nL 234.308046 561.59374 \nL 234.308158 561.593703 \nL 235.772041 561.133724 \nL 235.772148 561.133692 \nL 237.266797 560.709437 \nL 237.266898 560.70941 \nL 238.782399 560.3215 \nL 238.782492 560.321477 \nL 240.311129 559.968986 \nL 240.311214 559.968968 \nL 241.847487 559.649925 \nL 241.847564 559.64991 \nL 243.388558 559.361502 \nL 243.388627 559.36149 \nL 244.933768 559.100265 \nL 244.933828 559.100256 \nL 246.484885 558.862103 \nL 246.484934 558.862096 \nL 248.045273 558.64241 \nL 248.045311 558.642405 \nL 249.619295 558.436065 \nL 249.619321 558.436061 \nL 251.21146 558.237793 \nL 251.211473 558.237791 \nL 252.825872 558.042207 \nL 254.465639 557.84405 \nL 256.132731 557.63864 \nL 257.828032 557.421982 \nL 259.551397 557.191007 \nL 261.30206 556.943532 \nL 263.078692 556.678249 \nL 264.879456 556.39456 \nL 266.702 556.092359 \nL 268.543335 555.771773 \nL 270.399857 555.432944 \nL 272.267417 555.075817 \nL 274.141693 554.700059 \nL 276.018533 554.305065 \nL 277.894714 553.890061 \nL 279.768079 553.454374 \nL 281.637902 552.997736 \nL 283.504738 552.520681 \nL 285.370194 552.024798 \nL 287.236435 551.512941 \nL 289.105937 550.989154 \nL 290.980974 550.458474 \nL 292.863886 549.926414 \nL 292.863899 549.92641 \nL 294.756719 549.398427 \nL 294.756742 549.398421 \nL 296.6614 548.879265 \nL 296.66143 548.879257 \nL 298.579364 548.37251 \nL 298.579398 548.372502 \nL 300.51132 547.880193 \nL 300.511354 547.880185 \nL 302.456783 547.402636 \nL 302.456813 547.402629 \nL 304.413474 546.938565 \nL 304.413497 546.938559 \nL 306.376987 546.485394 \nL 306.377001 546.485391 \nL 308.340904 546.039493 \nL 310.296948 545.596719 \nL 312.235833 545.152735 \nL 314.147907 544.703391 \nL 316.024011 544.244959 \nL 317.856051 543.774293 \nL 319.637619 543.288772 \nL 321.363913 542.786324 \nL 323.032016 542.265089 \nL 324.640765 541.723128 \nL 326.190662 541.158093 \nL 327.683742 540.566927 \nL 329.123515 539.945737 \nL 330.514625 539.289768 \nL 331.862636 538.593605 \nL 333.173582 537.851677 \nL 333.653184 537.554534 \nL 332.718683 537.952485 \nL 332.718575 537.952529 \nL 330.987975 538.630868 \nL 330.987876 538.630905 \nL 329.222291 539.269791 \nL 329.222201 539.269823 \nL 327.433843 539.868993 \nL 327.433761 539.86902 \nL 325.634523 540.42863 \nL 325.634447 540.428653 \nL 323.834785 540.949273 \nL 323.834713 540.949292 \nL 322.042368 541.431913 \nL 322.0423 541.43193 \nL 320.26162 541.878036 \nL 320.261554 541.878052 \nL 318.493111 542.289456 \nL 318.493047 542.289471 \nL 316.73395 542.668293 \nL 316.733887 542.668306 \nL 314.97818 543.017009 \nL 314.978119 543.017021 \nL 313.217856 543.338375 \nL 313.217799 543.338385 \nL 311.443785 543.635589 \nL 311.443732 543.635597 \nL 309.646916 543.912065 \nL 309.64687 543.912072 \nL 307.819236 544.171449 \nL 307.819197 544.171454 \nL 305.954649 544.417365 \nL 305.954617 544.417369 \nL 304.049576 544.653198 \nL 304.049551 544.653201 \nL 302.103185 544.881862 \nL 302.103166 544.881864 \nL 300.117271 545.10558 \nL 300.117257 545.105582 \nL 298.095833 545.325848 \nL 298.095821 545.32585 \nL 296.044363 545.54343 \nL 296.044354 545.543431 \nL 293.968978 545.758564 \nL 293.96897 545.758564 \nL 291.875889 545.971163 \nL 291.875882 545.971164 \nL 289.770741 546.181153 \nL 289.770735 546.181154 \nL 287.658835 546.388591 \nL 287.658831 546.388591 \nL 285.54513 546.593811 \nL 283.434675 546.79745 \nL 281.332864 547.000335 \nL 279.245633 547.203327 \nL 277.179267 547.407165 \nL 275.139923 547.612356 \nL 273.133196 547.819024 \nL 271.163483 548.02689 \nL 269.233807 548.23519 \nL 267.345611 548.442744 \nL 265.499118 548.647846 \nL 263.693371 548.848381 \nL 263.693365 548.848381 \nL 261.92649 549.041872 \nL 261.926477 549.041874 \nL 260.195564 549.225657 \nL 260.195543 549.225659 \nL 258.496689 549.397082 \nL 258.496661 549.397085 \nL 256.824797 549.553787 \nL 256.824762 549.55379 \nL 255.173356 549.694142 \nL 255.173318 549.694145 \nL 253.534368 549.817688 \nL 253.534331 549.817691 \nL 251.898443 549.925572 \nL 251.898411 549.925574 \nL 250.255039 550.020969 \nL 250.25502 550.02097 \nL 248.592708 550.109478 \nL 246.899359 550.199285 \nL 245.162875 550.301073 \nL 243.371732 550.427599 \nL 243.316329 550.432536 \nL 243.086995 550.485383 \nL 240.962096 551.024004 \nL 238.848726 551.622253 \nL 236.752208 552.290827 \nL 234.678529 553.037405 \nL 232.633576 553.86595 \nL 230.62183 554.776832 \nL 228.645714 555.767246 \nL 226.704849 556.832485 \nL 224.796253 557.967016 \nL 222.915124 559.165688 \nL 221.05587 560.424439 \nL 219.213531 561.740494 \nL 217.385082 563.112054 \nL 215.569896 564.53781 \nL 213.770213 566.016114 \nL 211.990776 567.544381 \nL 210.237574 569.118509 \nL 208.517277 570.732631 \nL 206.836148 572.37939 \nL 205.199218 574.050061 \nL 203.610038 575.734964 \nL 202.070927 577.423739 \nL 200.583218 579.105644 \nL 199.14828 580.76964 \nL 197.768307 582.404281 \nL 196.447066 583.997411 \nL 195.190359 585.535946 \nL 194.006298 587.005351 \nL 192.905205 588.389348 \nL 191.899163 589.669694 \nL 191.00159 590.826106 \nL 190.226306 591.836948 \nL 189.586774 592.680103 \nL 189.095165 593.334525 \nL 188.761461 593.78209 \nL 188.59277 594.009426 \nL 188.59252 594.00973 \nL 188.592241 594.010009 \nL 188.591936 594.010259 \nL 188.591609 594.010478 \nL 188.591261 594.010663 \nL 188.590897 594.010814 \nL 188.590521 594.010928 \nL 188.590135 594.011004 \nL 188.589743 594.011042 \nL 188.58935 594.011041 \nL 188.588958 594.011001 \nL 188.588572 594.010923 \nL 188.588196 594.010808 \nL 188.587833 594.010656 \nL 188.587486 594.010469 \nL 188.58716 594.010249 \nL 188.586856 594.009997 \nL 188.586579 594.009718 \nL 188.58633 594.009412 \nL 188.586112 594.009083 \nL 188.585927 594.008734 \nL 188.585777 594.008369 \nL 188.585664 594.00799 \nL 188.585588 594.007603 \nL 188.58555 594.00721 \nL 188.585551 594.006815 \nL 188.58559 594.006422 \nL 188.585668 594.006034 \nL 188.585783 594.005657 \nL 188.585934 594.005292 \nL 188.586121 594.004944 \nL 188.58634 594.004616 \nL 188.755033 593.777277 \nL 188.755039 593.77727 \nL 189.08875 593.329694 \nL 189.088759 593.329683 \nL 189.580378 592.675248 \nL 189.580389 592.675233 \nL 190.219933 591.832062 \nL 190.219946 591.832045 \nL 190.995244 590.821185 \nL 190.995258 590.821167 \nL 191.892846 589.664736 \nL 191.892861 589.664717 \nL 192.898917 588.384353 \nL 192.898932 588.384333 \nL 194.00004 587.000317 \nL 194.000056 587.000298 \nL 195.184134 585.530873 \nL 195.18415 585.530852 \nL 196.440875 583.992294 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555.760077 \nL 230.618319 554.769594 \nL 230.618461 554.769526 \nL 232.630353 553.858578 \nL 232.630501 553.858514 \nL 234.675601 553.02991 \nL 234.675748 553.029854 \nL 236.74957 552.283224 \nL 236.74971 552.283177 \nL 238.846361 551.61456 \nL 238.846487 551.614522 \nL 240.959973 551.016241 \nL 240.960079 551.016212 \nL 243.085074 550.477567 \nL 243.085158 550.477546 \nL 243.257886 550.437743 \nL 241.516109 550.592945 \nL 239.589 550.811443 \nL 237.58767 551.09653 \nL 235.514867 551.45935 \nL 233.379625 551.907855 \nL 231.197258 552.446059 \nL 228.988485 553.07386 \nL 228.246318 553.31343 \nL 228.000971 553.494893 \nL 226.495642 554.612027 \nL 225.00263 555.721064 \nL 223.523072 556.819414 \nL 222.058176 557.905387 \nL 220.609553 558.97767 \nL 219.179465 560.034947 \nL 217.7705 561.075851 \nL 216.385147 562.099035 \nL 215.024851 563.103615 \nL 213.689335 564.089529 \nL 212.375994 565.057889 \nL 212.37599 565.057892 \nL 211.079687 566.011079 \nL 211.079679 566.011085 \nL 209.79322 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655.150042 \nL 98.63452 655.150055 \nL 97.067826 656.535595 \nL 97.067798 656.53562 \nL 95.540507 657.861201 \nL 95.540467 657.861235 \nL 94.054694 659.117073 \nL 94.054645 659.117114 \nL 92.611545 660.298486 \nL 92.611492 660.298529 \nL 91.211702 661.40547 \nL 91.21165 661.40551 \nL 89.855578 662.442054 \nL 89.855531 662.442089 \nL 88.544018 663.41476 \nL 88.543981 663.414787 \nL 87.27881 664.330986 \nL 87.278785 664.331004 \nL 86.063123 665.197403 \nL 86.063111 665.197411 \nL 84.902279 666.018273 \nL 83.804522 666.794057 \nL 82.781282 667.520699 \nL 81.847775 668.189132 \nL 81.022538 668.785825 \nL 80.326372 669.294051 \nL 79.780486 669.695904 \nL 79.404126 669.974725 \nL 79.211957 670.117651 \nL 79.211629 670.117871 \nL 79.211282 670.118057 \nL 79.210919 670.118208 \nL 79.210542 670.118322 \nL 79.210156 670.118399 \nL 79.209765 670.118438 \nL 79.209371 670.118437 \nL 79.20898 670.118398 \nL 79.208594 670.118321 \nL 79.208217 670.118206 \nL 79.207854 670.118055 \nL 79.207507 670.117868 \nL 79.20718 670.117649 \nL 79.206876 670.117398 \nL 79.206598 670.117119 \nL 79.206349 670.116813 \nL 79.20613 670.116484 \nL 79.205945 670.116136 \nL 79.205795 670.115771 \nL 79.205681 670.115393 \nL 79.205604 670.115005 \nL 79.205566 670.114612 \nL 79.205566 670.114217 \nL 79.205605 670.113824 \nL 79.205682 670.113437 \nL 79.205796 670.113059 \nL 79.205947 670.112694 \nL 79.206132 670.112346 \nL 79.206351 670.112017 \nL 79.206601 670.111712 \nL 79.206879 670.111433 \nL 79.207184 670.111183 \nL 79.399356 669.968254 \nL 79.399362 669.968249 \nL 79.77573 669.689423 \nL 79.77574 669.689415 \nL 80.321637 669.287554 \nL 80.32165 669.287544 \nL 81.01783 668.779308 \nL 81.017845 668.779297 \nL 81.843097 668.182593 \nL 81.843112 668.182583 \nL 82.776633 667.51414 \nL 82.776646 667.514131 \nL 83.799895 666.787481 \nL 83.799903 666.787476 \nL 84.897662 666.011691 \nL 86.058488 665.190834 \nL 87.274131 664.324448 \nL 88.539272 663.408271 \nL 89.850744 662.435631 \nL 91.206767 661.399125 \nL 92.606504 660.292225 \nL 94.049554 659.110894 \nL 95.535283 657.855094 \nL 97.06254 656.529541 \nL 98.629213 655.14402 \nL 100.232122 653.712777 \nL 101.867204 652.253137 \nL 101.867219 652.253124 \nL 103.529216 650.783991 \nL 103.529243 650.783967 \nL 105.212431 649.323522 \nL 105.21247 649.323489 \nL 106.910977 647.887311 \nL 106.911024 647.887272 \nL 108.618798 646.48712 \nL 108.618849 646.487079 \nL 110.329992 645.130088 \nL 110.330042 645.130049 \nL 112.039001 643.818667 \nL 112.039047 643.818632 \nL 113.74078 642.551218 \nL 113.740818 642.55119 \nL 115.431219 641.322811 \nL 115.431246 641.322791 \nL 117.107591 640.126225 \nL 117.107607 640.126213 \nL 118.768997 638.952946 \nL 118.769003 638.952941 \nL 120.416885 637.793888 \nL 122.054844 636.640308 \nL 123.68837 635.484378 \nL 125.324208 634.319709 \nL 126.969019 633.141991 \nL 128.62848 631.949181 \nL 130.306114 630.741673 \nL 132.002837 629.522036 \nL 132.002843 629.522032 \nL 133.716733 628.29463 \nL 133.716742 628.294624 \nL 135.443473 627.064958 \nL 135.443484 627.064951 \nL 137.177036 625.838905 \nL 137.177047 625.838897 \nL 138.910658 624.622141 \nL 138.910671 624.622132 \nL 140.637996 623.419391 \nL 140.638008 623.419383 \nL 142.353879 622.234162 \nL 142.353891 622.234154 \nL 144.054985 621.068429 \nL 144.054997 621.068421 \nL 145.740166 619.922589 \nL 145.740177 619.922581 \nL 147.410452 618.795436 \nL 147.410463 618.795428 \nL 149.068711 617.684361 \nL 149.06872 617.684354 \nL 150.718925 616.585679 \nL 150.718933 616.585674 \nL 152.365453 615.494901 \nL 152.365458 615.494898 \nL 154.012272 614.407118 \nL 155.662096 613.317377 \nL 157.316013 612.220904 \nL 158.973423 611.113151 \nL 160.63231 609.98978 \nL 162.289867 608.846436 \nL 163.943353 607.678416 \nL 165.590522 606.480767 \nL 167.22999 605.248319 \nL 168.861141 603.976042 \nL 170.48363 602.659662 \nL 172.097012 601.296076 \nL 173.700044 599.883929 \nL 175.290438 598.423886 \nL 176.86497 596.918533 \nL 178.419952 595.372053 \nL 178.692875 595.090156 \nL 178.148278 595.524417 \nL 178.148198 595.52448 \nL 176.83708 596.516663 \nL 176.837004 596.516719 \nL 175.464424 597.505185 \nL 175.464354 597.505234 \nL 174.024136 598.49669 \nL 174.024075 598.496731 \nL 172.513958 599.496051 \nL 172.513907 599.496085 \nL 170.935921 600.506085 \nL 170.93588 600.506111 \nL 169.296523 601.527281 \nL 169.29649 601.527301 \nL 167.606363 602.557767 \nL 167.606338 602.557782 \nL 165.879124 603.593707 \nL 165.879106 603.593718 \nL 164.130569 604.629572 \nL 164.130555 604.62958 \nL 162.377137 605.658766 \nL 162.377126 605.658772 \nL 160.634572 606.674424 \nL 160.634564 606.674429 \nL 158.916719 607.669991 \nL 158.916711 607.669996 \nL 157.234494 608.640015 \nL 157.234486 608.640019 \nL 155.595297 609.580604 \nL 155.595289 609.580609 \nL 154.002608 610.489812 \nL 154.002599 610.489817 \nL 152.456172 611.367684 \nL 152.456163 611.367689 \nL 150.952121 612.216287 \nL 150.952111 612.216292 \nL 149.4837 613.039257 \nL 149.483689 613.039263 \nL 148.041857 613.841561 \nL 148.041846 613.841567 \nL 146.616127 614.628964 \nL 146.616116 614.62897 \nL 145.195713 615.40745 \nL 145.195702 615.407456 \nL 143.770353 616.182817 \nL 143.770343 616.182823 \nL 142.331461 616.960056 \nL 142.331452 616.960061 \nL 140.872819 617.743044 \nL 140.872811 617.743048 \nL 139.390992 618.53441 \nL 139.390987 618.534412 \nL 137.885417 619.335616 \nL 136.357997 620.147292 \nL 134.812558 620.969724 \nL 133.253796 621.803568 \nL 131.68667 622.650251 \nL 130.115795 623.512301 \nL 128.545261 624.393193 \nL 126.978687 625.296861 \nL 125.419799 626.22678 \nL 123.872997 627.184978 \nL 122.344002 628.170942 \nL 120.84011 629.181 \nL 119.370491 630.207809 \nL 117.94591 631.240526 \nL 116.578535 632.265202 \nL 115.281085 633.265872 \nL 114.066615 634.225358 \nL 112.947853 635.126433 \nL 111.936948 635.952682 \nL 111.045343 636.689122 \nL 110.283547 637.322718 \nL 109.661109 637.842551 \nL 109.186246 638.239952 \nL 108.865678 638.50845 \nL 108.704169 638.643751 \nL 108.703855 638.643989 \nL 108.703519 638.644195 \nL 108.703165 638.644366 \nL 108.702796 638.644502 \nL 108.702415 638.644602 \nL 108.702026 638.644663 \nL 108.701633 638.644685 \nL 108.70124 638.644669 \nL 108.70085 638.644614 \nL 108.700468 638.644521 \nL 108.700097 638.644391 \nL 108.69974 638.644225 \nL 108.6994 638.644025 \nL 108.699083 638.643792 \nL 108.698789 638.64353 \nL 108.698522 638.643239 \nL 108.698285 638.642924 \nL 108.69808 638.642587 \nL 108.697909 638.642231 \nL 108.697774 638.64186 \nL 108.697675 638.641478 \nL 108.697614 638.641087 \nL 108.697592 638.640693 \nL 108.697608 638.640298 \nL 108.697662 638.639907 \nL 108.697755 638.639523 \nL 108.697884 638.63915 \nL 108.69805 638.638792 \nL 108.698249 638.638451 \nL 108.698481 638.638132 \nL 108.698743 638.637837 \nL 108.699032 638.63757 \nL 108.860541 638.502268 \nL 109.18111 638.23377 \nL 109.655977 637.836366 \nL 109.65598 637.836363 \nL 110.278422 637.316526 \nL 110.278429 637.316521 \nL 111.040233 636.682918 \nL 111.040243 636.682909 \nL 111.931862 635.946459 \nL 111.931877 635.946445 \nL 112.942802 635.12018 \nL 112.942824 635.120162 \nL 114.061612 634.219067 \nL 114.061642 634.219043 \nL 115.276145 633.259531 \nL 115.276182 633.259502 \nL 116.573673 632.2588 \nL 116.573717 632.258767 \nL 117.941139 631.234055 \nL 117.94119 631.234018 \nL 119.365825 630.201262 \nL 119.365882 630.201221 \nL 120.83556 629.174371 \nL 120.835621 629.17433 \nL 122.339575 628.16423 \nL 122.339637 628.164189 \nL 123.868694 627.178185 \nL 123.868756 627.178146 \nL 125.415617 626.219911 \nL 125.415675 626.219876 \nL 126.974617 625.289925 \nL 126.974667 625.289895 \nL 128.541287 624.386201 \nL 128.541329 624.386177 \nL 130.1119 623.505264 \nL 130.111933 623.505246 \nL 131.682836 622.643181 \nL 131.682859 622.643168 \nL 133.250003 621.796475 \nL 133.250018 621.796467 \nL 134.808791 620.962617 \nL 134.808799 620.962613 \nL 136.354243 620.140179 \nL 137.881663 619.328502 \nL 139.387229 618.527301 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577.842786 \nL 193.282428 578.053151 \nL 191.835086 578.962464 \nL 190.381435 579.879465 \nL 188.916723 580.811146 \nL 187.43531 581.764612 \nL 185.931811 582.746063 \nL 184.40207 583.759966 \nL 182.844024 584.808322 \nL 181.258326 585.890147 \nL 179.648266 587.001538 \nL 178.019395 588.136079 \nL 176.378903 589.285547 \nL 174.734752 590.440901 \nL 173.095048 591.593212 \nL 173.095044 591.593214 \nL 171.467502 592.734478 \nL 171.467497 592.734482 \nL 169.85918 593.85826 \nL 169.859174 593.858264 \nL 168.276542 594.959818 \nL 168.276538 594.959821 \nL 166.725191 596.036267 \nL 165.209949 597.086338 \nL 163.734461 598.110004 \nL 162.301036 599.108152 \nL 160.910238 600.082195 \nL 159.560855 601.033709 \nL 158.249737 601.964202 \nL 156.97202 602.875208 \nL 155.721248 603.768371 \nL 154.489855 604.645886 \nL 154.489846 604.645892 \nL 153.269179 605.510958 \nL 153.269167 605.510966 \nL 152.049804 606.368328 \nL 152.049791 606.368338 \nL 150.821555 607.224524 \nL 150.821543 607.224532 \nL 149.57414 608.087619 \nL 149.574132 608.087624 \nL 148.297138 608.966736 \nL 148.297135 608.966738 \nL 146.981025 609.870684 \nL 145.617685 610.806449 \nL 144.200901 611.777589 \nL 144.200894 611.777594 \nL 142.726985 612.782873 \nL 142.726967 612.782885 \nL 141.194899 613.815487 \nL 141.194865 613.815509 \nL 139.606503 614.863094 \nL 139.606451 614.863128 \nL 137.966482 615.90871 \nL 137.96641 615.908755 \nL 136.282471 616.932455 \nL 136.282377 616.93251 \nL 134.565221 617.913576 \nL 134.565109 617.913639 \nL 132.829378 618.832573 \nL 132.82925 618.832638 \nL 131.093609 619.673131 \nL 131.093471 619.673194 \nL 129.381486 620.423382 \nL 129.381345 620.423441 \nL 127.721448 621.076506 \nL 127.721311 621.076557 \nL 126.146655 621.630558 \nL 126.146528 621.6306 \nL 124.693984 622.087701 \nL 124.693873 622.087734 \nL 123.402532 622.453078 \nL 123.402438 622.453103 \nL 122.311203 622.733477 \nL 122.311129 622.733496 \nL 121.456088 622.936013 \nL 121.456035 622.936025 \nL 120.867544 623.067049 \nL 120.867512 623.067056 \nL 120.567507 623.131314 \nL 120.567118 623.131377 \nL 120.566726 623.131402 \nL 120.566332 623.131388 \nL 120.565942 623.131335 \nL 120.56556 623.131245 \nL 120.565187 623.131117 \nL 120.564829 623.130953 \nL 120.564489 623.130754 \nL 120.56417 623.130524 \nL 120.563875 623.130262 \nL 120.563606 623.129973 \nL 120.563368 623.129659 \nL 120.563161 623.129323 \nL 120.562988 623.128969 \nL 120.56285 623.128599 \nL 120.562749 623.128217 \nL 120.562686 623.127827 \nL 120.562661 623.127433 \nL 120.562675 623.127038 \nL 120.562728 623.126646 \nL 120.562818 623.126262 \nL 120.562945 623.125888 \nL 120.563109 623.125529 \nL 120.563306 623.125187 \nL 120.563536 623.124867 \nL 120.563796 623.12457 \nL 120.564084 623.124301 \nL 120.564397 623.124061 \nL 120.564731 623.123854 \nL 120.565085 623.12368 \nL 120.565453 623.123542 \nL 120.565834 623.12344 \nL 120.865824 623.059186 \nL 121.454273 622.928171 \nL 122.309252 622.725669 \nL 123.400403 622.445316 \nL 124.691642 622.080001 \nL 126.144067 621.622938 \nL 127.71859 621.068984 \nL 129.378348 620.415973 \nL 131.090194 619.665847 \nL 132.825702 618.825418 \nL 134.561312 617.906548 \nL 136.278364 616.92554 \nL 137.96222 615.901891 \nL 139.602126 614.856349 \nL 141.190446 613.808792 \nL 142.722489 612.776208 \nL 144.196384 611.770937 \nL 145.613161 610.799802 \nL 146.976498 609.864039 \nL 148.292606 608.960095 \nL 149.569594 608.080987 \nL 150.816988 607.217907 \nL 152.045211 606.361729 \nL 153.264561 605.504376 \nL 154.485218 604.639318 \nL 155.716602 603.761809 \nL 156.967374 602.868647 \nL 158.245098 601.957636 \nL 158.245105 601.957631 \nL 159.556232 601.027131 \nL 159.556242 601.027124 \nL 160.905635 600.075603 \nL 160.905645 600.075596 \nL 162.296453 599.101547 \nL 162.296462 599.10154 \nL 163.729895 598.103387 \nL 163.7299 598.103383 \nL 165.205391 597.079714 \nL 166.720633 596.029643 \nL 168.271977 594.9532 \nL 169.854602 593.85165 \nL 171.462914 592.727876 \nL 173.090451 591.586615 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6/qvjfmET4CdbfgLA2+e9fdx9jJfCuIiIiIjExb7WfQAjBunDbYd5tvkB1iyYRshajlb76O33Y63l1jW3kupKHXcN7e522vrbuGHxDWEF+vHSbioiIiIiEhcH2w6O+Izb7+Y3B37K8vm5pCYlsb+uDpenmE46efeCd1OaWRpWDT969UcALCleElY/46WZcRERERGJi7ruOlJcKed85k+H/kB6YRvleXkEgkH2HO4miTSWFC8J+4TMfS0DM/OfX/v5sPoJh8K4iIiIiMTN7LzZw97b17KPHd3PsGJmJQB7amrJpQqAGxbfENa41lp+v/v35KTmUJheGFZf4VAYFxEREZG4Ge6kS0/Aw32H7mT5vDxcTie+QIAjJzy4SOVfL/vXsMd97OBjAHzu/M+F3Vc4FMZFREREJG6m50wf8vqTRx8nNb+VktxcAO59+WVymcFXLvwKDhNehPUFfWyu38y6ynVjOvkzGhTGRURERCTmPAEPACWZJWfdq++p56WWP7N85sCWh16/n2wqeN+i95OVkhX22Cdf2nzb3LeF3Ve4FMZFREREJOZqumoAzprlttbyx4O/ZU5VCilJAwfw7K1t4LKyd7KsZFnY4zb2NtLr6+X9S98fdl+RoDAuIiIiIjFX21075PWdTTtptLuYUzowY+72+WhqcLKh6uqIjPuTzQMH/MwvnB+R/sKlMC4iIiIiMXei68RZ1/xBP3869luWzC44dQDP3poGLi6+hpzUnLDH3Fy3GYB/uPAfwu4rUhTGRURERCTmjnceP+vaK7Uv48hsoiRnIHj3eb20NiVz+YwNYY8XsiEePfgoM3JnkJ2SHXZ/kaIwLiIiIiIxZ609YycVt9/NkzUPsGTmGy907q1u5LLSd0Tkpc1f7/g1AB9d8dGw+4okhXERERERiYuZeTNPffxC9bNkF/aRk54OQK/HQ0dLKpdMvzzscbq93RzrOMa1864Ne1vESEusakRERERkypiTPweAPl8fzzY8wqLppafu7TnRyJXl7yYjOSPscb7/yvcBOL/i/LD7ijSFcRERERGJqV5fLwCV2QPH3L9Y/Rx5RV4yU1MB6Orvp6ctk/XTLw17rL0tewH4zJrPhN1XNCiMi4iIiEhM7W/dDwzsMd7v7+e5xkdZOO20teInmrmq8npSXalhjWOt5b7d95Gflj/k4UKJQGFcRERERGLq5Gw1wMbaV8gtcJ+aFW/v7cXTmctF0y4Ke5z799wPwGfP/2zYfUWLwriIiIiIxNSR9iMkO5PxBX38re5h5k8rPnVvz7EWrpl+I8nO5LDG6PX1srdlLxtmbcDlcIVbctQojIuIiIhIzC0rWcbW+q2k5nSf2kGlqbMTR38ZayrWhN3/f778nwCsn7E+7L6iSWFcRERERGLGWgvAitIV/LXuEeZW5p+6vudYO++ouinsmew9zXuAxH1p83QK4yIiIiISM7XdtcDAMhJvUgPFg6dt1rS1kReay7LSZWH1b63l/j33U5RRlLAvbZ5OYVxEREREYua1utcA+GvNY8ysGFieEgyF2H+sh3fNvjnsQ3nu3n43ALeuvjWsfmJFYVxEREREYmZX0y4Aary7mV5UBMChxkZmpaxhdt7ssPpu6WvheOdx3rXgXTgdzrBrjQWFcRERERGJqSA+KsqcOIzBFwhw7ISfd855L8aYsPq9fdPtAKwsWxmJMmNCYVxEREREYsIT8ADQQz1zy0oB2FNdz9qCqynNLA2r76ePPA3AbRfdFl6RMaYwLiIiIiIx8Wrtq1hClJUaUpKS6HG7aWlM5uqZ14bVb5+vj5eqX2JtxVoykzMjVG1sKIyLiIiISEw8e+xZ+mhmTkUhALuONfKWihvISskKq9/vvvxdAK6Zd03YNcaawriIiIiIxEw3deRnZtLU2Umop4T10y8Jq7+Xq18G4O/X/n0kyos5hXERERERiboebw8eulg1r4KQtew60s67Z36QJGfSuPvs8/Xx1JGnWFG6goL0gghWGzsK4yIiIiISdb/e8Wu6qWVOaSmHGxupcK5gacnSsPo8uTzluoXXRaLEuFAYFxEREZGocyVBVm6AQDDIkeM+rpt7U1hbGT55+EkAvrjuixGqMD4UxkVEREQkqjo9nRzp28YVi5ec2sqwPKt83P219rfySs0rrJ+xnry0vAhWGnsK4yIiIiISVc+eeIaSUovb56O1MZW3znr7uPuy1vI/r/0PABtmbYhUiXGjMC4iIiIiUdPW38bGlr+wcFoZO4808rZpN4a1F/jJUza/tv5rkSoxrhTGRURERCRqnjz2GOUV0NbTQ5J7OhdOu2jcfW1r2EZrfysfWv4hUlwpEawyfhTGRURERCQqGnsbeb3zWRZUlLH3SBfvmf1BXA7XuPrq9HTy8P6HWVi0kDn5cyJcafwojIuIiIhIVDx+9E9UTXdxtKmZ2annM79w/rj6CdkQP9z4QwBuWnJTJEuMO4VxEREREYm46q5qDvS9yozCQo5XB3nnnBvGvZXhd176DgBfv+TrkSwxISiMi4iIiEhEWWt57OgfmT0jlT3VjawvegfFGcXj6usvh/6CN+Dlk6s+SbIzOcKVxp/CuIiIiIhE1NGOo1T7tpOfmUlPayZXznzLuPo51HaIV2tf5arZV1GRXRHhKhODwriIiIiIRIy1lj8ffYC5MzLYfbSFa6ffTHpS+pj76fJ08Zudv6E8q5yLp18chUoTg8K4iIiIiETMvpZ9NNu9pCQlkeKdxvkVa8fcRyAU4AcbfwDAp1Z/KtIlJhSFcRERERGJiJAN8djxB5hflcOJxm4uK78Wp8M5pj6stfy/5/8fAP9y6b9Eo8yEojAuIiIiIhGxq2kXXc4jFGdn09nuYnnp8jH38T+bBo66//IFXx73nuQTicK4iIiIiIQtGAry6PH7WDQznyNNTZxXsH7Ma8X/fODPtPW38dEVHyUnNSdKlSYWhXERERERCdvWhq34U+soycmhriHAheWXjqn9toZtbKnfwtvmvo2ZeTOjVGXiURgXERERkbD4g34eP3E/C6sKaOzsJN9UMT1n+qjbV3dV8/D+h1lWsox1leuiWGniURgXERERkbC8VvcqjswWirKzOVrXxWUV1476tM0uTxd3bruT7JRsrl90fZQrTTwK4yIiIiIybp6AhydqHmDxzGJ63G7c3ZmjfnHTF/Sd2sLwyxd8OZplJiyFcREREREZt78df4b0vG7yMjI4UNfMpWXXjOrYemst33zhmwD830v/76hn0icbhXERERERGZfmvmaea3yI5bPK8fr9tDQ7uaBydKdlfvPFgSB+20W3jXkv8slEYVxERERExsxayx8O/IaqKidpyckcbGjk/IIryU7JHrHtvbvuxR/086nVnyIzOTMG1SYuhXERERERGbOtDVupC21nXlkZgWCQ2roQl06/csR2r9a+yv7W/Vy/6HrKs8pjUGliUxgXERERkTHp9fXy0LFfcd68YhzGcKixkSXZF1KcUXzOdic6T/CXQ39hTfkalpUsi1G1iU1hXERERETG5KGD91NQ2k9+ZibBUIgTNX6uqrr2nG16fb3c9fpd5KTm8Pb5b49RpYlPYVxERERERm1302529z3L0hkVABxqbGRB5tpzLjkJ2RD/+fJ/AvCldV+KSZ0ThcK4iIiIiIxKn6+P+w7/gpXzi3A6HARDIY5Ve7m66p3nbPdvz/0bAF+/5OtTdgvD4SiMi4iIiMiIrLU8ePD35JZ0U5Q9sGPKwYYGFmVdREV2xbDt/rD3DwB8Zs1nRrX/+FSjMC4iIiIiI3q98XX29j/PsqpKAPzBIMer/bxt5vCz4rubd7OraRfvnP9OSjJLYlXqhKIwLiIiIiLn1O5u54EjP2fVgmKcjoH4uK+2nvNyr6A0s3TINp2eTh7Y8wCz82ezqnxVLMudUBTGRURERGRYwVCQ3+69i4rpAfIzBw7o8fj91NcZrp459A4qIRvihxt/CMCHl384ZrVORArjIiIiIjKsvx57ilbnDhZWvLFbyu4T9VxYdA0F6QVDtvn/nv//APjnS/45JjVOZGGFcWPMDcaYPcaYkDFm9Tmeu8sY02yM2T3Evc8bYw4M9vPdN92bbozpNcZ8JZw6RURERGTsDrcd5umm+zh/wbRTu6B09ffT2ZzOVTOvHrLNYwcfw1rLp1d/miRnUizLnZDCnRnfDbwHeGGE5+4G3vrmi8aYy4F3AcustYuB773pkR8CfwmzRhEREREZo25vN7/afzvnLcglLfmNXVB2HW3i6mk3kJGccVabYx3H2FS3iatmX0VZVlksy52wXOE0ttbuA0bcL9Ja+4IxpmqIW7cC37HWegefaz55wxjzbuAo0BdOjSIiIiIyNsFQkHv2/Jyiil5KcytPXa/v6MDRX8FFSy4+q43b7+bu7XeTn5bPxdPPvi9Di/ea8XnAemPMa8aY540xawCMMRnA/wH+baQOjDGfNMZsMcZsaWlpiXK5IiIiIpPf44f/TKtrB4unvbF/eDAUYs+RDt4z64O4HGfP537npe8A8Pdr/z5mdU4GI86MG2OeAYbas+br1tqHIzB+HrAOWAPcb4yZxUAI/6G1tncUs+53AHcArF692oZZj4iIiMiUtq1hGy+2/5ErVs44Y/XDwfoGZiafz8KihWe1uXPbnQDcdtFtOmFzjEYM49baDVEcvxZ40FprgU3GmBBQCKwF3jv4QmcuEDLGeKy1t0exFhEREZEp7Uj7EX5/5CesW15KsuuNmNjv9XKi2vKPK286K2xvb9xOdVc1Ny25iczkzFiXPOGFtWY8Av4EXAE8Z4yZByQDrdba9ScfMMZ8A+hVEBcRERGJDk/Aw+OH/8zG9kc5b1EeuRlnvpy5/Ug9G8pupjC98IzrXZ4uHtr3EPML5w85Yy4jC3drw+uMMbXABcBjxpgnB6+XG2MeP+25e4GNwHxjTK0x5pbBW3cBswa3PPw98JHBWXIRERERiTJrLdsbtvOt177KIR7nytXTKM3NPeOZmrY2HL2VXF515Vltf7DxBwC8f+n7Y1XypBPubioPAQ8Ncb0euOa0z28epr0P+OAIY3wjnBpFRERE5Gx13XU8dPheGkI7Wba4kKLsGWc94wsE2HO4h1sXfPmsPcN/tvVnAHx1/VdjUu9kFe9lKiIiIiISQ52eTv5y9M+83vlXZs9I4YrSmcO+dPn6kVrW5l3DzLyZZ1zf07yHhp4G3r/0/aS6UmNR9qSlMC4iIiIyBfT7+3n2+F95vukRysqDXLlmGklO57DP17a14e8s4e1r3nXGdW/Ay/177mdazjTmF86PdtmTnsK4iIiIyCTmC/p4ueZlnq79AzlF/Vy6uuyMEzWH4vb52H2oh1sXfpkUV8oZ97714rcAuOW8W4ZqKmOkMC4iIiIyCQVCATbXbeYv1feRnNPB+eeVkp1WNGI7ay1bDtRyRfGNZy1PeaXmFQA+d/7ntJ94hCiMi4iIiEwiIRvi9YbXeezEfdj0JpYtLSI/c+bIDQftra0nP7CMq2a99YzrnoCHJw8/ydKSpRRljBzqZXQUxkVEREQmAWstu5t38+jx+3AnV7NoQQHFOaMP4QANHR0012bwlVWfwOk4cz35t1/8NgDvXfTeiNUsCuMiIiIiE5q1lkPth/jz0ftoN4dYOCePstzhd0gZTo/bzY79PXxq4dfJSc05497elr0AfGr1pyJWtwxQGBcRERGZoI53HufPR/9AfWAX86uyWFEw9hAO4PX72bi7nuum38rs/Nln3LPWct/u+yhML6Q8qzxSpcsghXERERGRCaa+p57Hjj7E4f5NzKlK58riKhzjfKEyGArxyt5qLs5/LxdMu/Cs+/fvuR+AW9fcGlbNMjSFcREREZEJot3dzl+OPsKOruepmp7EhsUzcDoc4+4vZC2v7D3OwuSruGbOO8667/a72duylytmXoHLodgYDfpdFREREUlwvb5enjn2FK+0PE55heXKeZXnPLBnNELW8uq+Y0zjIm5c+AEc5uxQ/8NXfwjApVWXhjWWDE9hXERERCRB+YI+Xqp+kafr/kBesYfL1pSTmpQUdr/BUIjX9h+nNLiODy+95aydUwBa+lrwBrx8aPmHwh5PhqcwLiIiIpJgrLVsb9zOn479huTsNtadV0JWWklE+g6GQmzcd5xKexEfXnrLsMtPbt90OwBz8udEZFwZmsK4iIiISAI53nmchw7/jjazn6WLCinKropo/3tr6ikPXXDOIF7dVQ3AZ9Z8JqJjy9kUxkVEREQSQKenk0cPP8TO7ueYPyuDZUXj26bwXPq8XurqDF9dddM5X8i8c9udAJRkRmY2XoanMC4iIiISR/6gnxerX+DJuvspqwiwYf50XGG+nDmcXcfq2VB2M3lpecM+c7j9MABfXPfFqNQgZ1IYFxEREYmTg60HeeDw3QQz6rhoZRmZqalRG6uluxtPZwGXnn/5OZ+7Z8c9OIzjnIFdIkdhXERERCTGur3dPHLoj+zqfZYlc3KpyJ8Z1fGstew62sp1VV8gxZUy7HMH2w4CmhWPJYVxERERkRix1rK5fjN/OvYrCsvcXDl/RtSWpJyuurWVvOBczis775zP/Xbnb3E6nOSk5kS9JhmgMC4iIiISAx3uDu4/cA/Vgc2sWl5KXkZRTMYNhkIcONbLx+fdPOTBPiednBX/wtovxKQuGaAwLiIiIhJF1lq2Nmzlj0fvpHyan8srZ+GI8C4p53KosZFZqWuYnTf7nM/9dudvcRiHZsVjTGFcREREJErcfjd/OHAve93PsXp5CXkZGTEd3x8Mcrzaz5eWXn/ObRIPtR0CtFY8HhTGRURERKKgtruWu/b8D2kFzVyxoAqnY/glItGyv66eFTmXUZZVds7nfrPzNxhjNCseBwrjIiIiIhFkreW1uld58MQvWDw3jWmFM+JSh9fvp7bW8sGVbz/nc9pXPL4UxkVEREQiJBAK8KeDf2Br92NctKKcrLS0uNWyr7aBtYVvoSC94JzP3bPjHowx5KbmxqYwOYPCuIiIiEgEuP1u7t79M1pc27jsvCqSYrBl4XA8fj8NDQ4+tvqt53zu5A4qX1r3pViUJUNQGBcREREJU6enk5/t+CHO/BoumjXznC9LxsL+2kYuLHrbiLPdv935W1wOl9aKx1Hs3yQQERERmURa+lr479e/RWZZAytnT497EB+YFTdcPmPDOZ/b07wH0FrxeNPMuIiIiMg4Nfc1c/v2bzNtpofZpeXxLgeA/bUNXFA48qz4/XvuJysli6yUrNgUJkPSzLiIiIjIOAwE8W8xY7aX2aUl8S4HAF8gQOMoZsU31W0C4LNrPhuLsuQcFMZFRERExqjD3cGPd3yX6bO8zCwujnc5p+yva2BVwRXkpeUN+4y1lscOPkZFdgVpSfHb7UUGKIyLiIiIjEGvr5cf7/gepdN7mFWSGDPiAIFgkLr6EFdMf8s5n3vyyJMAfOy8j8WiLBmBwriIiIjIKPmDfu7a9WMyihuZV37uUy1j7VBjI0tzLqIoo2jYZ4KhIBtrNrKidAUuh14dTAQK4yIiIiKjYK3l9/vuoTdtD0tnVMa7nDOErOVErY8rpp97X/G7t98NwLsXvDv6RcmoKIyLiIiIjMKzx//KAe/fWDNvRty3L3yz483NVKUupzJ7+G8Sen29VHdVc+28axOu/qlMYVxERERkBAdaD/BEw29Yt2gaTkdixSdrLcdq+9kw/e3nfO4/X/5PAM6vOD8WZckoJdafJhEREZEE0+Xp4p4Dt7NyYR7pKSnxLucsjZ2dZIVmMDd/7rDPnOg8AcDHV348VmXJKCmMi4iIiAwjZEP8du+dFFe4Kc5JzCPjD9d2saHynedcenLX63dhjGFazrQYViajoTAuIiIiMoxnj/+VJsfrLJ5WEe9ShtTV34+/N4flpcuHfeb5488D8I8X/WOsypIxUBgXERERGUJ9Tz1P1v+eNfMrE/aFx4O1LVxW9naSnElD3g+EAvzt2N9YXLyY9KT0GFcno6EwLiIiIvImgVCA3+z7OfNmJSfkOnEAj99PW4uLdZUXDPvMTzb/BIAbFt0Qq7JkjBTGRURERN7kueN/w5N6JKGOun+zQw2NrCm8gszkzCHvt/S10Nrfyg2Lb0jYmX1RGBcRERE5Q3NfM0/V3895cysSNsQGQyHq6oOsn3b5sM/cvul2AJYUL4lVWTIOCuMiIiIig6y1/PHgb6mqcpCRoMtTYOCQn1np51GaWTrk/ddqXwPgyxd8OZZlyTgojIuIiIgM2tW0i5rA68wrK4t3KcOy1nK8zs0V09425P1gKMjjhx5nbsFcclITcztGeYPCuIiIiAjgDXh58OivWTanAEeCLk8BaOrqIis0fdhDfn68+ccAfGDpB2JZloyTwriIiIgI8EL1cyTntCbs4T4nHarp4MphDvlp7G2ktb+VG5fcmLDr3eVMCuMiIiIy5XV7u3mm/kGWzBx6DXaiGDjkJ5cVpSuGvH9yK8NFRYtiWJWEQ2FcREREprynj/2F4lI/mamp8S7lnA7WtnB5+TuGPOTn6SNPAzppc6JRGBcREZEpra2/jVdbn2TRtMR9aRPA7fPR3prMuoqzD/nxBDy8VP0Sq8tXk5GcEYfqZLwUxkVERGRKe+r4Y1RUGFKShj5SPlHsr23gwuKrhwzb337x2wC8Y/47Yl2WhElhXERERKaslr4WtnU8y4KKxJ4V9wUCNDU6uGSIQ352N+8G4FOrPxXrsiQCFMZFRERkyvrriSeorHCQ7HLFu5RzOlDfwMr8y8lLyzvjejAU5IE9D1CWVUZ5VnmcqpNwKIyLiIjIlNTubmdb+3PML0/sWXF/MEhtXYgrZrzlrHsnj7z/5KpPxrosiRCFcREREZmSnq/+G6VlNuFnxQ81NLI8Zz3FGcVnXD/WcYx2dzsfWPYBHEaRbqLSfzkRERGZcvp8fWxsfor5FYm9r3ggGKS6NsCGqmvOuB6yIe7efjfpSenMK5gXp+okEhTGRUREZMp5re418gt9pCUnx7uUczrU0MiS7IspzTzzm4afbfkZAP9w4T/EoyyJIIVxERERmVICoQDP1T/C3MqieJdyTv5gkOM1Ad5Sde0Z1491HKOxt5Ebl9yIy5HYS2xkZArjIiIiMqXsbd6LI72TvIzEPhznYH0DK3IvPWNW/OTylIzkDB15P0kojIuIiMiU8nz9k8woT+wg7gsEqKkNnTUr/l+v/hcA/3CBlqdMFgrjIiIiMmU09TZR49nDtMLCeJdyTvtq61mdv4GijDeW0uxp3kOXp4uPrPgIToczjtVJJCmMi4iIyJSxueE1SkscOIyJdynDcvt81Nc7uKrqbaeu+YI+7t9zPxXZFczKmxXH6iTSFMZFRERkSgiEAmxseprZpYn94ube6gbWF197xmmb33zhmwB8YuUn4lWWRInCuIiIiEwJB9sO4sroISstLd6lDKvH7aatOZUrqq46de25488B8NnzP4tJ4Bl9GR+FcREREZkSNje9TFlxSrzLOKc9x5vYUP4eMpMzAehwd/DssWdZW7H2rBM4ZXJQGBcREZFJz+13s7tjE1VFibtEpb23F09nLuunXwKAtfbU7inXzLvmHC1lIlMYFxERkUlvf+t+snP8JLsS95Cc3UdbuGbGTaS4Bmbv73z9TgC+uv6r8SxLokxhXERERCa97a2vUVqUuGvF69vbSfZUsqZ8DQAHWg9Q01XD+xa/j1RXapyrk2hSGBcREZFJzRf0sbdzG9MKCuJdypBC1rL3WCfvmvV+nA4n3oCX3+36HaWZpSwuXhzv8iTKFMZFRERkUjvacZTMzEDCLlE52tREuXPZqePtv/XitwD49OpPx7MsiRGFcREREZnU9rbuJL8gMbcE9AeDHD7u4V2zb8QYw2MHHwPgC+u+oG0MpwiFcREREZm0rLXs6thMRV5+vEsZ0r7aepbnXMa0nGnU99SzqW4TG2ZtID8tMeuVyAsrjBtjbjDG7DHGhIwxq8/x3F3GmGZjzO4h7n3eGHNgsJ/vnnZ9mTFm4+D1XcYYvb0gIiIiY9Lh6aDPtpKTnh7vUs7S5/XSUOfg2tnvJhgK8rMtP8NhHKyfsT7epUkMhTszvht4D/DCCM/dDbz1zReNMZcD7wKWWWsXA98bvO4CfgN8evD6ZYA/zFpFRERkijneeZycHBJyyceuY/VcWfYeclNz+fZL3wbgny/55zhXJbEW1psM1tp9MPIfcGvtC8aYqiFu3Qp8x1rrHXyuefD6W4Cd1todg9fbwqlTREREpqbDnfvJz0mKdxlnaenuxttZyKXnX8HL1S/jD/r5xKpP4HQ4412axFi814zPA9YbY14zxjxvjFlz2nVrjHnSGLPNGPOPw3VgjPmkMWaLMWZLS0tLTIoWERGRieFozz4Ks7LiXcYZQtay43Ar1838EH3+Pp468hSrylZRmV0Z79IkDkYM48aYZ4wxu4f48a4IjO8C8oB1wG3A/WZgmt0FXAx8YPDn64wxVw7VgbX2Dmvtamvt6qIEPuJWREREYssb8NLiqSMvMzPepZzhcGMjFY4VLC9dzo9e/REA71zwzjhXJfEy4jIVa+2GKI5fCzxorbXAJmNMCCgcvP68tbYVwBjzOLAS+GsUaxEREZFJpKmviYx0cCTQenGP38/R436+vPz9/HjzjwH42vqvxbkqiad4L1P5E3AFgDFmHpAMtAJPAsuMMemDL3NeCuyNV5EiIiIy8TT1NpGeYeNdxhl2HK3j0uLraOptormvmQ8u+yAprpR4lyVxFO7WhtcZY2qBC4DHjDFPDl4vH5zNPvncvcBGYL4xptYYc8vgrbuAWYNbHv4e+Igd0AH8ANgMbAe2WWsfC6dWERERmVoa+mrJyIj3vOMbGjo68HUWc0HlRTy470Hm5M9hbsHceJclcRbubioPAQ8Ncb0euOa0z28epr0P+OAw937DwPaGIiIiImPW4D5BTl5i7C8eCAbZeaiDv5vztVPrxD+0/ENxrkoSQeJ8uygiIiISQU39dWQnyGE/u07UsSzrSrY0bAHgtotui3NFkigUxkVERGTSCYaCdPjayEiJ/3rslu5uOpuyWFKwgkNth7hu4XVkJifWDi8SPwrjIiIiMul0ebtISQanI75Rxx8Msm1/K9fN/AgP7nuQoowiVpSuiGtNklgUxkVERGTS6fJ0kZoa/y0Ntx+tZWXO1Tx84GEAPrvms3GuSBKNwriIiIhMOl3eLlJS4rutYXVrK772Umxw4Ij7L677IiaB9jyXxKAwLiIiIpNOh7uD5JRQ3Mbv9XjYe6ifKyrezr6Wfbxt7tvIS8uLWz2SuBTGRUREZNJp9zaTnpIcl7GDoRCb9tVxdfkHeOrIU2QkZ7Cucl1capHEpzAuIiIik06btyluO6lsP1rD7KT1vHD8BQC+cuFX4lKHTAwK4yIiIjLptHmbSY9DGD/S1IS/vYJsVwEAn1/7eRxGcUuGpz8dIiIiMqlYa2n3tJCZmhrTcVt7ejhyxPLWGe9hZ9NONszaQGF6YUxrkIlHYVxEREQmlX5/P9bhI9nlitmYfV4vm/e08v45n+Hh/Q+T7Exm/Yz1MRtfJi6FcREREZlUOj2dpKXELuL4g0E27q7h7RV/xx/3/RGAr67/aszGl4lNYVxEREQmlXZ3OympsdljPGQtr+49wcqst9Pn7Qfgc+d/TuvEZdT0J0VEREQmldb+VtLSo7/HuLWWLYdOUG7Xsqb0Al6re40NszZQlFEU9bFl8lAYFxERkUml0V1DVlr0X97cXV1Hcs883r/oo9z1+l2kuFK0TlzGTGFcREREJpX6/uPkpKdHdYxDDY30NpXwiWWf57svfxeAf7r4n6I6pkxOCuMiIiIyaYRsiMb+2qiG8eMtLdSdSOfTy77Mc8efA7SfuIyf/tSIiIjIpNHh7sCZHIjatob1HR0cPmy4delt9Pn72FK/hbfMfov2E5dxUxgXERGRSaOxt5GMKE2KN3d1sWufm08tvo2C9ALu3HYnGckZXDT9ougMKFOCwriIiIhMGjXdJ8jKivy2hu29vWzb283HF97GjNwZfPOFbwJw24W3RXwsmVoUxkVERGTSONqzl8KsrIj22dnXx2u72vjI3C8zt2AuD+17CIAvrPsCxpiIjiVTj8K4iIiITAohG+JE72EKIhjGu/r7eXVXC++f9fcsLl7M0Y6jbG/czrXzriU/LT9i48jUpTAuIiIik0JDTwOuFB8pSUkR6a/H7WbjzibeV/U5zis7D0/Aw6+2/4r8tHzOrzg/ImOIKIyLiIjIpHC88zg5OZFZL97r8fDyzgaun34rq8tXA/DtF78NwN+v/fuIjCECCuMiIiIySezv3EFhbvhbqfR6PLy0o553V36KtZXrAPj1jl8D8A8X/oPWiUtEKYyLiIjIhBcMBTnUtYvS3Nyw+hkI4nW8s+ITXDhtYMvCnU07OdJ+hPcuei/ZKdkRqFbkDQrjIiIiMuGd6DpBUrqH1DDWi1tr2bSvnmvLb+Hi6esB6PR08se9f2RO/hyWliyNVLkipyiMi4iIyIS3t3U3BfnhLR9p7u4mzV/J+umXAAO7s/xw4w8B+NDyD4Vdo8hQFMZFRERkQrPWsqP9VSry88Lq51BNBxsq34XDDMSjf3vu3wD4+iVfD7tGkeEojIuIiMiE1tTXRHeogfzMzHH30d7bS6Anj5VlKwF4cN+DANy65laSnckRqVNkKArjIiIiMqHtbNpBURFh7XJyoLqVqyqvI8mZxK6mXexo3ME75r+D0szSCFYqcjaFcREREZmwrLVsbnme6UXjPw2zq78fd1c2ayvX0dzXzB/2/oH5hfNP7S8uEk0K4yIiIjJh1ffU00M9BWEsUdlzvIkNFe8hGAryv5v+F4D3L31/pEoUOSeFcREREZmwNjVspKzUOe4lKh19fXi6cllXuY7vvPQdAL5x2TciWKHIuSmMi4iIyITkD/rZ1PIss0qKx93HnuPNXF15/amj7r+6/qs6YVNiSmFcREREJqS9LXtJyewjIyVlXO1bursJ9hTycs0rAHxh3RdIdaVGskSRESmMi4iIyIT0fN0TVJWPf634vuNt4M3E7Xfz8ZUfJz9t/C+BioyXwriIiIhMOHXdddT59lFZUDCu9vUdHfR1ZAFw05KbmJYzLZLliYyawriIiIhMOC/VPUdluQvHONZ3W2t5cedx0ingHfPfwcKihVGoUGR0FMZFRERkQun2drO17VnmlJaMq/2j27aSxyyumn2V9hKXuFMYFxERkQnlpZoXKCwOkpKUNOa2/mAQb286a0sv4eLpF0ehOpGxURgXERGRCcPtd/NC42MsnDa+Y+r31dRzcfHbuW7hdRGuTGR8FMZFRERkwnil9mWy893j2s6w1+Ohod7BNbPfGYXKRMZHYVxEREQmBLffzV/rHmLRjPGtFd95tIGrym8gNzUXgNcbXud3u34XwQpFxk5hXERERCaEF6ufJ7ugj+y0tDG3bezsJNRTyqUzLgfgqcNP8af9f6IwrTDSZYqMicK4iIiIJLw+Xx9/a3iYRTPGvlY8GAqx63A718/+MEnOJB7a9xAv17zMVbOv4i1z3hKFakVGzxXvAkRERERG8vSxJyko9pCZOvYlKvvr6pmTcgGLihbxp/1/Ynvjdt45/52sKl8VhUpFxkYz4yIiIpLQWvtbeaXlMRbPKB9z216Ph9oaB9fNu5GnjzzN6w2vK4hLQlEYFxERkYT26JEHmTbNkDrGfcWttWw7VM/bKm/mWMcxXq55mQ2zNiiIS0JRGBcREZGEdbj9MPt6X2JBxdhnxY+3tJDpnUNV7kweOfAIy0uXs37G+ihUKTJ+CuMiIiKSkAKhAH849CsWzcnB6RhbZHH7fOw/4uYds27kl6//kszkTN6z8D1RqlRk/BTGRUREJCG9XPMS3tQTTCsoGHPb1w/XcXnJ9af2Ef/KhV+JdHkiEaEwLiIiIgmnw93BX2ruZfmcsjG3Pd7cjKtvBvuaDwDwTxf/E8aYSJcoEhEK4yIiIpJQrLU8ePBeyiuDYz7gp9/rZf8RD/Ozz6Pb281HVnyEtKSxHxIkEisK4yIiIpJQdjbt5LD3VRZWju2lTWstmw/Usjb/bWxv3M6ykmXMypsVpSpFIkOH/oiIiMSJ3w9tbQM/enrA47F4fODxgLWQmgppKZCSYsjKgoICyM+HlJR4Vx5ZgVCA6q5q6rrrCNogz9Q9yIrFhWN+aXNvbR0loZXsbNwNwPWLro9GuSIRpTAuIiISA9ZCSwscO2Y5eNRytNrS3WvJyLGk51iS00M4k8GVZHElgzEQ8IC/2xDyg7ffQX+Xob/TkJlumFFpmD/bMHOmobR04PmJxO13s6NxB7s7tnKwaycp6T6yc0I4HIbZczIoys4fU3/NXV001qaRSwCAr67/ajTKFok4hXEREZEosRZqa2HbdsvWnSECDkteeZDCihCrl4fIzIHRT/4GT/XZ2w0tDYZXjjh4/CUn1uvgvCWGVSscVFUldjB3+928VPMCf6t/mMy8fsqK07l8fiEpYzzQ5812HWklPbSA3kAvNy25iVRXaoQqFokuhXEREZEI6++H1zZZXtkSoj8YomxekLXXBcnOC79vYyArB7JyLLMWBIEgvd1w/ICTXz7oxOl3sG6lgwsvGFjakiistWxr2MZDx35FZkE3684rISutOGL9L59bzI5jO+jscLK7dTuV2ZVkpSTQb4DIMIy1Nt41RMzq1avtli1b4l2GiIhMUd3d8OJLlpe2hMivCjBnaZCCEhvTmeqOVji800nzERfnL3Ny2SWG/LGt+Ii4bm83D+z/LUf8GzlvbhEFUfwuwRcIsKe6npbGFN427UYumX6ptjWUqDDGbLXWrg67H4VxERGR8Hi98Ne/WV7YFKRkXoCFq4JkxHlS1t0PB153Urt3IJS/7S2G9PTY1mCtZWfTTu4/8nOKyt0snlYx5pcyx6vH7WbTvjouyHkf1855hwK5RJzC+BAUxkVEJJashV27LA8+FiKjPMDyiwOkxTjwjsTrgV0bnbQfS+Kdb3GwapUZwzr18ev19fKngw+wu/9ZVs2P7mz4cLx+Py/uPMEleTdz9exrFMgloiIVxrVmXEREZBx6euD3D4Q40R5kxVV+SioSc3IrJRVWXx6kbXGIR59z8dpWFx+40UFeBNavD6W1v5UXqp/l1ZanKSkLcOWCqpjNhr9ZSlISFy+bwbPbf09F1nSWliyNSx0i56KZcRERkTE6fNjymwdCFM73s3RtMCYzzZFgLezb5qRmRxI3v9vB4sWRmSnu9fVypP0I25o3srfnNSrKHMwtLyEtOTki/YerpbubPXvhq2u+qdM4JWI0My4iIhJj1g6sDX96Y5CVV/konz6xJrSMgUWrghSVh7jnkSQuPObi2rcZnM7R9xGyITrcHTT3NVPTXc2ujk00uI+Rm2spKkjmqoWVuMbSYQwUZWeTUXCCx448wvXz36flKpJQNDMuIiIyCsEg/OGhEHtqA1z0dj/pGfGuKDxeD2z8SxLTslx84CYHw23zHQgFqO2uZV/rHvZ1bqOhvwZnUoCMdEjPtJTn5VCYnR23pSij5QsEeH7HceamXMx757+f7JTseJckE5xe4ByCwriIiESDzwe//X2I2r4AF1/rxxXe+TQJIxiE1552kelP4gPvc9De7eZIXQfHGro41tjOiaYO6lr6CbjTsd4MQv15zFnazsf+7YV4lz4uwVCI3dV19DQV8cWVX1Mgl7BomYqIiEgM+Hzwi1+F6E3ys/4dgTEt6YiXYBB6u6C709DTaejuNHR3QHeHOeNaVzt0t4TobAryz18O4k/xYRzpGJOGMWU4jMHpNGTkeMku6KejKRMXKfH+5Y2b0+FgedU09jhruWPHj/jcytt0UqfEncK4iIjIMIJB+N19IXpcfi54SyAux8xbC+4+BgP1YKg+I2Sffa23e6DdUFJTLFlpAXJcfgodIaYnuXEUdpKdDIWzM8n84IvklvWQle8mK99NZo4XpysEwA8+9Q5qDhbE8FcfHYsqK9jmPcqvdv+cT634fLzLkSlOYVxERGQI1sKDD1tqegKsf2fkgrjfxxsz1YNheiBEnzlz3dVh6Bl8JhAYui+XC7JzLVl5Az9XzQ8NfJ5ryc4dvJcTIiPQR257N2UtAVI9fprqGmmua6aloxVfwAuDm54sT16L69ACHG9/BMdgAD9dVr6bnvaJvxuJMYaVs6fzxKvb6HB3kJcWpX0eRUZBYVxERGQIzz5v2XnCz+Xv8Q+7NGXI5SCd0N1uzr42GLQ9/cOPmZnNqTBdUh5izuKBz7NzLdl5dvAepz5Oz+TsbxJClkC3B5r7cR7vJ2efob+jl7pDNWxpaaC3v3fY8Xft28SqlEvw3nUlaZ98+qz7WfluejrSCIUMDsfEfufMGENWhqG5r1lhXOIqrDBujLkB+AawEDjfWjvk25PGmLuAtwPN1tolb7r3eeBzQAB4zFr7j8aYJOAXwMrBGn9trf12OLWKiIici7XQ2wvt7bB7N9zzQJBZywI8/nvXaTPYDMxYj2Y5SBpk5Vpy8gYCdMWMwVnrvDeunR60M7IHZrrHI9jtJVTTTfKRfrJanIT6/bS1tNFY28y2tkbcXs+o+glheX3nRi7JfgtNzy0i87K9Z9zPynNjQ4b+7hQyc0fXZyLz+Yxe4pS4C3dmfDfwHuBnIzx3N3A78OvTLxpjLgfeBSyz1nqNMcWDt24AUqy1S40x6cBeY8y91trjYdYrIiJT2GOPwf79A4G7tdXS1h6io91Be7uhvR38fkswGMLbb0kC/vbHZKyxOJIgKydEdv7ArPX06ZC9AnKKDNn55lTIHgjWkJVjSYnWe4EhS7DXi233YBrdpB/xkdIJjbUN1NY20tbVjsc3/qAcCPnYuuUV1qRdRtvcRpIr2k/dy853A9Ddnjbhw7i1ln5PkPy0/HiXIlNcWGHcWrsPGHHzfGvtC8aYqiFu3Qp8x1rrHXyu+WQTIMMY4wLSAB/QHU6tIiIi998PTz8NGdk+gqnNkNFCerab7PkBFueHcGZ0MPvwEsq6vLS37oNABwUZTkpz0sjNzyWzIJvklCSSk5NxuZJIdiXTnRTAW5IKlRk4C9Ixzgjut30yeDe7cTS4SanzkdGTRMDjo6uri46GdvY3N9HR0xG5MYGu/naO7NxDyV0bCH39fszgLylrMIz3tKfBrMiOGWsev580RxYprom7O4xMDvFeMz4PWG+M+SbgAb5ird0M/IGBGfMGIB34krW2fagOjDGfBD4JMH369JgULSIiE1NuXoDU3B7ec+eXmFuVxsziYgKhEB6fD4/fT+i15czo8/Hi0SfINRaSIOiDuhaoa6k7qz+Xw0V+bj4lpSWUTCslPT0Db3IAT0YIf44DcpKxLoNxOrAOwGGwTgMnf1iL8YYwvQHo9uPsC+H0Wlw+gyvgIDngxO/10d7eTktdKx1dHXT19eAP+KL+e3Ws4QBlNZX0/GUVmdduBd4I491tE/8lTl8gQJIjGWutTuSUuBoxjBtjngFKh7j1dWvtwxEYPw9YB6wB7jfGzALOB4JA+eD9F40xz1hrj765A2vtHcAdMHDoT5j1iIjIJGSt5UjHEfa4j9HRdR6XrawkJWngr8Akp5OktDTSySLz+QvZufMVQozur5NAKEBzezPN7c3s2rsLhzGkpqSRnppGWmo6qckpGOPA4RgI5M4kJ06Xc/BnFxaLt9eDp9eN1+fD6/fi9/vxB/0DP/v9BG0wmr8157Rr1zbOL7iczov24sp1n1qmMhl2VMlOS6Ofajo9nXqBU+JqxDBurd0QxfFrgQftwDGgm4wxIaAQeD/whLXWDzQbY14GVgNnhXEREZFzqe+p59Ejf+SoZwvls65hu00h5EuDJP8Zz3n+eCGhE8209zQP09PIQtbS7+mn39MPtIVZefz1eDpoPHwC572X4Lr1yTdmxjsmfhg3xpCbYzjeeVxhXOIqggvbxuVPwBUAxph5DOx02gpUA1eYARkMzJzvj1eRIiIy8XR7u/ndnl/zX7u+TrBwF1eunsGM6QN/7b15ZtffkUH5rir2Htgeh0oT24Gjuyg9Woy3Np+UND9JKYFJMTMOkJ/rYn/H7niXIVNcWGHcGHOdMaYWuAB4zBjz5OD1cmPM46c9dy+wEZhvjKk1xtwyeOsuYJYxZjfwe+Ajg7Pk/wtkMrBby2bgl9baneHUKiIiU0dTbxM/2PpvNKY+x5VrKplfXo7T4TjzBcTT+B5bTcOJajz+c2wCPkUFQj6OHzpE6NE1GAPZBZPj4B+AvIxMavv0j+4SX+HupvIQ8NAQ1+uBa077/OZh2vuADw5xvZeB7Q1FRETGpKarhp/u/g9mzQ4xs/jMF/tP35rvpGBfCqV7pvPKsbMPuZEBx+sOctmxa2ltzSIrz33G799E1u12U5K2KN5lyBQX791UREREIuZQ2yHu3P89Fs9PoSK/8Kz7Q82Mu59aTqiuiX5fT8zqnGh8AS91R09gHls1cArnJAnjXX0eVmfOiXcZMsXFe824iIhIROxv2c/P93+HFYvSqcgf+iCXocJ4zvaZHD9+KCY1TmQnag9TdLBycGY8Pd7lRER/r6E8qzzeZcgUpzAuIiITXm13LXcf+CGrFudQnJMz7HPpWT4cztCpMOk5UkJaj4P27vHvoDJV9Hq6CHZ5SPOnTJqZcbcXclNz412GTHEK4yIiMqG19rfys13fY+H8ZIqys8/5rMNhyczznFrzHHx5EXXHq0FnvoxK7dFjZLVn09+dQsA/8SNERho09+kbMYmvif//JBERmbK6vd38ZMf3mTbTw7SCglG1yT5tzXP+wTLqG6ujWeKkUt9aTYV34F8VejtT41xN+DKzoab7eLzLkClOYVxERCYkt9/NHTv+m9yyVuaUDnVQ9NCy8gbCuK8pm1SPk253exSrnFw8/n4yHB5swDEplqoUZmZypGdfvMuQKU67qYiIyITS5+tja8MWnq9/nPTCFhZNmzam9ln5buqP5OPfXUVba0uUqpy8bF8LNlA8KbY3zEpL42B/XbzLkClOYVxERCaE1v5Wnqt+hk0tfyWv0M+8hfkUZk3DmLEt+M7Kd9O9OQ3H/nJaGxqiVO3kFehtwgSWTYqZ8eauLmbnrIp3GTLFKYyLiEhCa+pt4pkTj7Oj80XKywyXnV9KalLSuPvLLuintyOVjIZcjvfsiWClU0PA14gjZCZHGG/38tb8lfEuQ6Y4hXEREUlIrf2tPHnsUbZ3Ps/0SidXzqsgyekMu9/sPDehoANnfxp9nu4IVDq1OEIdAHQ2ZsW5kvCErKWjE+bOnRvvUmSKUxgXEZGE0u3t5uljf+HV1ieprDRsmFcZkRB+Ula+GxsytHWHCNpAxPqdKlyOEKmuIF3Hhz5YaaJo7uqiLHUW2Snn3g5TJNoUxkVEJCG4/W6eO/FXnmt8hOLSAFesKSMljOUow8nKd0PQQVOHJ+J9TxWZST66G3LjXUZYmru7WZizId5liCiMi4hIfPmCPl6ueZmna/9AdmEf61eVkZ6SErXxsvPdEHLQ2hlIyP19bcji9/oIBoI4XU6SUpIxjsQ6lSjd4aG3LT3eZYSlpwuqymfFuwwRhXEREYkPf9DPprrXeKLmD6TkdLBmRQk56UVRHzcr3w0WOvsh0RZaBHwBuls7CQWDp645nE6yC3NxJSfOX9kZLi893RP3BU5rLd09lsrsyniXIqIwLiIisRUIBdhct5knah7AmdnG8qVF5GfOjNn4WfluwNDV7yQ/gabGbcjS3doJ1uJKfmN5TigQpLu1k7yygjFv4xgt6U4vjd058S5j3Dr7+8lyFmm9uCQEhXEREYkJf9DP5vrNPFnzBxyZbSxZXEhBVuxC+Emp6X5cDkuXxwEJtNLC7/URCgbPCOIADpeTgM+P3+MjOS16y3fGIt3lpbcn8uv5Y+V4UxvnF7033mWIAArjIiISZb6gj9dqX+Xp2gdxZXXELYSfZAxkZvjp9SdWmAwGgmHdj6UMlxevz4HP4yI5dWLtSBOylqZmy4eXr4l3KSKAwriIiESJJ+BhY+1G/lr3EKk5XSyL8XKUc8nK8tPXmRizzCc5XefevnGk+7GUnRwAAz0dqRSU9ca7nDGpa2+nImU+RRnRfz9BZDQUxkVEJKL6/f28XPMiz9Y/QmZ+H6uWF5OTnlivSmZm++hrS6wwnpSSjMPpJBQI4jgteIcCQRxOJ0mpyXGs7kxZKSEwlp72tAkXxmube7iq5Ip4lyFyisK4iIhERJ+vj5dqnufZhj+TW+Dm/PNKyE5LzNnHzBwP7f68eJdxBuMwZBfm0t3aScDnP3X95G4qifLyJkBumgUD3e0Ta0cVay2dnYa5s3TqpiQOhXEREQlLv7+fF6uf49mGR8gt9HDhylIyU0viXdY5ZRf20xtIvBpdyS7yygrwe07bZzw1OaGCOEB+rgM7ODM+kXS73WQ6CshNzY13KSKnKIyLiMi4eAIeXqx+nr/W/4m8Qg8XriwhMzU13mWNSk5lB+7AXILW4DQ23uWcwRiTMLumDKekIA3jCE24MN7U1cm8nPUJ982NTG0K4yIiMib+oJ+Nta/wZO0fyMjrmRAz4W+WM7MNg8EXTCPN1R/vciac0rw0jCtId8fECeMha6lrdrO2dEm8SxE5g8K4iIiMirWWHY07ePj47zAZTaxaVkxuRkG8yxqX3OI+QgaCznxAYXwsXI5kklKcZOR5JszMeMhaXt1/jBmOC1hWsize5YicQWFcRERGVNNVw4OHfksze1myoICSnMTYonC8svLdWBPC4SqCYG28y5lQcjPy6EzrJzvfSXdbAp2aNIyTQbw0sI6PLPkETkfibBEpAgrjIiJyDn2+Ph478jBbOp5i7sw0riieOSnW22blu7GuEM6MYuiOdzUTS35eMX2zmsnKcyX8zHjIWl7bf5wS/1o+svQTJDkT66AnEVAYFxGRIbT1t/FC9QtsafsbecV9XLG6kmTX5PkrIzvfjXEFIa1AYXyMCstL6Vmwi6z8PFrrsuNdzrB8gQCbDpygLLiWjy79pIK4JKzJ85VVRETCcrzzOH/c+0e6vd346KOVA1y9aj75mRNzXfi5ZOa5Ma4QvaEUspPS8fq1bnw0nMZFdnYOvsUnyC6YzdFdifnibkdfH5v2NLIu7128Y+67cTkUdyRx6U+niMgUVt9Tz7277qXbe3J62NJFDdOmw5VVK3FMgiUpQ0lOCZKa4aPB5WVVQSXHGw/Gu6QJoTi3gta8bpxpAbLz3fS0p2EtJNIfkyNNTRw+EuKm2V/mvLLz4l2OyIgUxkVEphhPwMOD+x7kQOuBU9dWlq2kxVvPUd8rXLKglNyMjDhWGBtZ+W66s3upLJipMD5K02bOpP/8I2QAWXluAj4nnv4k0jL8I7aNNo/fz67j9YQ6Kvnyis9RkpmYs/Yib6YwLiIyRRxsO8hvd/721OcLChfw7gXvprmvmV/uvZ2s4jYuXzwTp8MRxypjJyvPjdvlIzkng/SULPq9PfEuKaElu1LJLSogdMFTwMA3MwA97WlxDeNev59dJ+ppbXKxtuitXLv6XaS6JsbhUyKgMC4iMqlZa3nyyJNsrNl46tpHVnyEWXmzsNbyUs2L/LnmbpbMy6CyYHocK4297Hw3PR1ptFxez7R9MzlwfGe8S0poFUUzaC5rIyVtIHifHsaLp8X+LdiQtRysb+B4dZALCq/lM2vfSmZyZszrEAmXwriIyCTkC/r43a7fcazjGABVuVXcvPTmUzOG/qCfB/bfy27301x8XsWEOcY+krLy3dQdycf11tcp238tR6r3Ewj54l1WQnLgYNb8+bRc/cKpa9mDYbw7Dtsb9no8bN5fT4VZxVdW3ExxRnHMaxCJFIVxEZFJxBPw8Ittv6ClrwWAi6dfzIZZG87YG7zH28Ndu35Mb9peLl8xdZalvFnW4AuIyRXtNFd2ML1sNkfr9sW7rIRUXjiDrmIvaQvqTl3LLhgM4zE++OdESwv7Dnu4tvJjrJ9+CQ4zNf/8yuShMC4iMgn4gj7u3HYnjb2NAFw771rOrzj/rOea+5r56c7vk1vWxrppVZPiAJ/xysp34+lLxud1Erp2C7Orr+R4/UFCNhjv0hKLhTkLF9F29RZOj92nL1OJNl8gQENHB7XNvTj7KvnC0s9QkV0R9XFFYkFhXERkAgvZEPftvo/9rfsBePu8t7OmYs2Qz57oPMEde/6TmbNCzCqpjGWZCSk7byBM9nakkT+nkbbyHmZVzOdw7d44V5ZYppfMxl1iSVtx9Izr6VleHM4QPR2RD+PWWtp6e6lra6ejw+DuczEvZylX5a9h5aKVJDuTIz6mSLwojIuITFAbazbyxOEnALis6jIun3n5sM8eaD3ALw98nyXzUynPL4xViQkt67Q1z/mlvYRufoGZze+gtukEHn9fnKtLDEnOFOYvXUrTDX8j7U2rQYwZ3B4yAjPjIWvp9Xjo6O2lqb2PtnZDvquCFQXXM3/WIqbnTNfBPTJp6U+2iMgE09LXwu2bbgdgVt4sPrT8Q+dcN7u7aTe/PvxDVi3OoSg7cY8vj7U3L7NIKe+kYflxFjeex9adL8WztIQxf84ymuY1kzavAWstbp+Prv5+ut1uevp92ORODh0O8uzWGgJBSygELqfB6QKXExwOSyhkCAYZ+GHB6Rj84RwYw+0Fr8eSm1xAWfoCLs1fzfyq+eSn5cf3Fy8SIwrjIiIThLWWX+341akdUr5y4VfISsk6Z5tdTbv49eEfsHZpAfmZ2vbtdCdfQDx9zXPa9RtJ2/c+SqoraeqsjVdpcWcwFOWWUVBVzotr/pu+1/vp6w+RarIoTa+kPL2KZemVPFNSjglM49YFc0hxpuByuPAGvXgDXjwBD/6Qn2Rn8qkfLocLf9CPP+THF/RhrSU3NZe8tDzNfMuUpT/5IiITQENPAz/d8lMA3rXgXawsWzlim5NBfN2yQvKmwImaY3Vqa762N8K4IyVAx00vssx9KS++0DFllqs4jZOcrBzycnIpnl5Kfn4hzW4nJ9bWcUXpRyjKKKI4o5j0pDN3TplRBocOQXmW/nyJjJfCuIhIgntk/yNsbdgKwD9f8s8kOZNGbLO3eS/3HP4ha5cWKIgPIzPXA0D3m15ATF9cQ8PaI6zquYCNm/5KCBuP8qImyZVMdkYmWRlZ5BbmkVdaQGZGJr3ZfrzlSQQr03l0Wx6rFqRz81vmnLOv/Hxob49R4SKTlMK4iEiC8gf9/PsL/w7A1XOu5sJpF46q3aG2Q9x96PusWZKnpSnn4HSFyMjxDLk1X/r1G/Eeu44FbSvYe+T1OFQXGQ7jICczh/zcPAori8kvKMCR6qQvM4Cv2IUtScVdmIqvIA3jcuIAdm10kpOazIYrR972Mj8fOjogFIIpul29SNgUxkVEElBTbxM/3vxjAL6w7gujfpmtuquaX+z7HisXZ1OQde715PLGwT9vZhxgP/0E+X3vZpbHzdG6/XGobuySXSkU5OZRUFhAQUUx2VnZ9GX5cU9Lxlak0lmcgTMjGRyGobLzwZ0Ouo8m8flPOU69YBkMQlfXwAx4ezu0tb3x8ebNA/d7eiAnJ6a/VJFJQ2FcRCTBbG/czkP7HgLgXy/711GfMNjU28TPdv8nSxakUDxFklHIWjr7+mjv7aXf6yU/M5OS3FySTibJEWTlDR3GAVzZbvpufZzpt78Dr8dDXdvxCFYeGRmp6eTnFFBQWkhhWREpman0FATxVaXhLUmjrTANR7KLk78b1kJ/P/R0GLo6DD2d0N1p6O401BwxVO91MWu6gw996I3g3dk50G4o6elQWQm9vQrjIuOlMC4ikkD+fODPbKnfwqKiRdy45MZRt+v0dPKTnd9j5qwAFfklUawwfqy1dLvdtPb00NHjpq/HQW8f5KeUUpW5lmkpJRyr3cfOffvJyAySmwv5WRmkuFwku1ykJCWR7HLhPG09RVa+m7b64f8FIbm0i85bnmJh6GqCrwZp7KiJwa90aA7jIDszm/ycfAoriygoKsSX7KA+y0FDdgaHXOn0hVLp7nTQ/Rr0dJ4M3IM/dwwE70Dg7L6DAQgFDJUVhoakgeUnCxcO/HzyR0HBmZ/n50Nqaux/H0QmG4VxEZEE8ePNP6apt4lr5l7D2sq1o27n9ru5Y+ePKKrsYlZJeRQrjC23z0drdzetPX30dht6ei3ZrkJmZq/mwsz5VBZXUppZSqrr9ER4Df6gn+quag61H6C24Qgd/h76Aj24A730+/uwJkiSa2AZRpe/mYa6XF7ZXYPLZXE4LcYBxliMw+JyOElJbaDx3T3M5z2kvJ5KU3sNwVCIUDBI0AYj9usNWfAEU3EHU/GTTcCRRciRSygll2ByDp5QOm1uQ0dfEt3HXfT0u3C7h1/XnZEF2bmW7DxLcXmIOYsgK9eeujbwM3S2GloOJPHZjzuYPj1ivxwRGSWFcRGROLPW8o3nvgHAh5d/mNn5s0fdNhAKcPfun2HyjrOwckaUKow+fzBIe08PrT09dPdYenrABNOYlTWf5VmLmD59OhVZFWQkj7wzTJIzidn5s4f8fbTWErRBPAEP3oCX4JwkfvdyGu8p/QreoAdf0EfQBgmGggRCATwBN93uDnrSO9h0+VPMDl7BrKTFpKeFcIQcOK0Z7DNEKBQkGAoNfB4K0eeFjj5DZx909EJ7j6G730mPN4ken4tuTxK9/uTBH0n0+ZKw1mCMAQMWi3UATkNyGuQUQnYeZOdCea4lOzdIdr4lO3cgdJ8etDNzwDXC3/DWwr7XnbjrkviHzzkpLh7XfzoRCZPCuIhIHAVCAf7f8/8PgM+d/zmKMopG3dZaywP776XFtY2LZs2MVolREbKWY83NtHV66OkxeD1OKjOqmJV1KTMKZ1E5q5L8tPyBYBpBxhhcxkVmciaZyZlUlUEoADMyFnKuHSB9PugogdpC+M3vQzR3BCmrCuHug+4O6GofWIfd3TmwLKS7yxDww6ldEe2p/8HpgKysEFk5IbKzgszIsWTnhcjK85BdYMgpcZBT5BicvYasHEtK+CfOn8Hvg01/deHqTeLvP+XQem+ROFIYFxGJE2/Ay7de/BYAt110G5nJY9uG8K/Hnma3+ykuXVYV8dAaLdZaTrS2cuh4LzOSz2NDycWUV5ZTklGC0zG6ly4jKX9wk5rbb4eMjDN3Cjl995De3tNbOfB6DT4/JKVYsnIHl4PkWoqnWeYstWTlhs5aDnLy4/RMOPM/lxn8cbpQ1H7Nbc2G1/6SxOoFLt75IUPSyNvWi0gUKYyLiMRBv7+f/3jpPwD42vqvkeJKGVP77Y3bearpN1x63jRco9w5JN4aOjrYe6yDAjufW+beyOy82XH/JmLVqoFg/KMfDXyelnbmC4szZw73AqOhvd3y6NOW4gV+lq4NkpQc11/KiAIB2LvFSd3uJG56p4PlyyfGN3Aik53CuIhIjPX5+vjuy98F4F8u/RdcjrF9Ka7truXeI//L2mUlpCUneAIE2nt72X20BZenghurbmFpydK4h/CT5s6F7dvB74e8vIEwPnqGJUucPP6k4anfhFh8sY8Zcy0J8ks7Q+0xw64Xklgwzck/ft5Bbm68KxKRkxTGRURi6PQg/n8v/b9jXprR7e3m57t/yKJ5qQl/zH1Xfz97jjfh68rjmhm3sqZ8TVyWooykaPTL9M+SlQU3vtfBuhMOHnjYwdGdAeavDlA+IzFCeVOdYd9mF84+Jx+5zsH8+QlQlIicQWFcRCRG3H73qSA+lsN8TvIH/fxy108oKO9iWkFlNEqMiF6Ph70nGuluy+Cqyo9y0cKLSHYm/gx+OGbMgC991sGuXUk89ZyLPRuDzFvtZ/psG/Nj4q2FuuOGg1tduLxO3nqpg/POMyPuriIi8aH/a4qIxEAgFOA7L30HGJgRH2sQt9by0MEH6EndwwXTEnPnlD6vl73VjXS0pHBF2U2sX3spaUkR3gYkgTmdsGKFYflyw4EDDp5+zsnu50OUzglQtTBEQXF0Z8s72+DYPif1h1wUZTl49yWGpUtNzL8ZEJGxURgXEYkya+2p7Qv/+ZJ/HtdSjVdrN/J671+4fEXi7ZzS6/Gwr6aJjpYULit9L+vPv2xU+4FPVsbAggWwYIGD1lYH23c6ee2ZEP3BEHkVQUqmhSiptKSlhzeO1w2NtYbmWgcd9U5cAQdrz3Nw4y2Gksl5CKvIpKQwLiISZSeXptx20W0kOce+j9yJzhM8VP0LLlpRnlA7p/S43eyraaKzNVUhfBiFhbDhCsOVlztpaHBy7JiL/Yctzz5ncaaGyMizpGaHyMqzpGdakpPBlQxJSQOz6H4/+L0Gvx/6ewf2MPd0OejrNPh6HcyuMqyebZi53lBRgWbBRSYghXERkSh68vCT9Pv7+cSqT4x5H3GAHm8Pd+39EUvnZ5I1tq0+oqazr4/9NS30tKdzedlNXLz2EtKTwpzmneSMgfJyKC83XHSRIRSC1lYnbW3Q2mpparW014PHC16fxesdWPudkgypqYbUFMjJgjklhsLFhoKCgRdPE+h7MxEZJ4VxEZEoaext5JWaV7h85uVUZo/9hctgKMhv9t5JXlkXFfnTolDh2LR0d3Oguh1fTw4bKj7KunnrSHWlxrusCcnhgOJiBo+gH+rQHxGZKhTGRUSiwFrLTzb/BIDLqi4bVx9PHX2CRrOVS6bPimBlY2OtZdPhwxyt72J66hLeMu3TrFq8alzLbURE5GwK4yIiUfDHfX8E4OuXfH1c7Xc27uTZ5vu5bNX0uLywGQyFONbczLYDTeQwnXLm8PV1Y9+OUUREzk1hXEQkwjwBD7uadnFZ1WXj2l97e+N2fnf0R6xdWkxqUmxnoH2BAIcaGjlS7SEtUEIJy3jPwvewvHR5TOsQEZkqFMZFRCLs51t/DsDlMy8fc9tdTbsGg3hhTE/YDFnLvpp6qmuDlCUtICfQB8A/XPgPZKdkx6wOEZGpRv/eKCISQf6gn9b+Vt4+7+1jbru/ZT/3HP4vzl9SENMg3tXfz7OvHyW1czlvLf8AXf19OB1O/vWyf1UQFxGJMs2Mi4hE0MMHHgZgTcWaMbU70XmCuw/+gFWLc8jPHPsWiONhreVAfQPVJwzXVX2W1v42XjjxAkuKl3DD4htiUoOIyFSnMC4iEkG7mnYxt2DumNo09zVzx57/ZMmCNIqyYzMT3e/1svlALYXBZdy28mM8fuhxDrcf5q1z3soF0y6ISQ0iIqIwLiISMU29TQBct+C6Ubfp9fXys50/pGpWkPK8wmiVdoaatjb2HOzj6vIPc3nVldyx9Q4aehq4ccmNLCpaFJMaRERkgMK4iEiEPHLgEYBRHwkfCAX41e6fkVnSzOyS6B/qEwyF2H6sBndrMZ9d/BVm5M7gJ5t/QmNvIx9e/mFm58+Oeg0iInImhXERkQip7a5lXsG8UT//yMGHaEvawUUzZkaxqgF9Xi+v7a1ldtJ6blz9QdKT0rl7+90K4iIicaYwLiISAYFQAIANszaM6vmt9Vt5resRLj9vRtQP9Wnq7OT1/Z1cU/4xLp1xGcYYHtn/CMc6jnHz0psVxEVE4khhXEQkAnY27QSgJLNkxGdb+lp44OgdnL+8lGRXdL8MH2popPq4i08s+PqpF0u31G9ha8NWrp13LQsKF0R1fBEROTeFcRGRCHil5pVRPRcMBbln78+pmklU9xK31rLzeC3uljK+dN4XKUwfeDm0vqeePx/4MytKV3B+xflRG19EREZHYVxEJAJa+looyyob8bm/HX+GnpT9LC+N3jrxkLVsPniCjP7FfGHlZ069UOoL+vjZlp+R5EziuoWj3/FFRESiJ6wTOI0xNxhj9hhjQsaY1ed47i5jTLMxZvebrt9njNk++OO4MWb7afe+aow5bIw5YIy5Opw6RURi4bzS8855v7G3kacb7mfV3IqorRMPWcur+45R6F3Np1d84YydXb75wjcB+Nr6r0VlbBERGbtwZ8Z3A+8BfjbCc3cDtwO/Pv2itfbGkx8bY74PdA1+vAi4CVgMlAPPGGPmWWuDYdYrIhJxwdDAl6bFxYuHfcZay/0Hfs2sKhfpKSlRqeNkEC8LXsBHln0Cl+ONL/GP7B/YdvGL676Iw4Q1DyMiIhEU1ldka+0+a+2BUTz3AtA+3H0zMEX0PuDewUvvAn5vrfVaa48BhwEtbhSRhHS88zgAmcnDH2O/tWErzexmbmlpVGqw1rLl0AmKA2v4yNIzg3hzXzNbG7ayYdYG8tLyojK+iIiMT6JMj6wHmqy1hwY/rwBqTrtfO3jtLMaYTxpjthhjtrS0tES5TBGRsx1qP3TO+96Al0eO/YZlc4qitjxl14la0noX8pElnzwjiAP876b/BWD9jPVRGVtERMZvxDBujHnGGLN7iB/vimAdN/PGrDjAUH9b2aEaWmvvsNauttauLioqimBJIiKjc7Tj6Dnvv1j9PKl5HRRmZUVn/KZmepqKuWXZZ0lxnbkE5k/7/wTAP138T1EZW0REwjPimnFr7ehOsBgnY4yLgXXnq067XAucfjZ0JVAfzTpERMarqbeJVFfqkPf6fH08U/8gF64ceaeV8Wjr6eHwkRBfWvHFs5bJ9Pn6eL3hdS6tupS0pLSojC8iIuFJhGUqG4D91tra0649AtxkjEkxxswE5gKb4lKdiMgozMidMeT1F6ufI6/IS2bq0GE9HL5AgM17W/jA3M8OedjQd1/+LgBXzLwi4mOLiEhkhLu14XXGmFrgAuAxY8yTg9fLjTGPn/bcvcBGYL4xptYYc8tp3dzEmUtUsNbuAe4H9gJPAJ/VTioiksimZU8765rb7+a5xkdZOG3kUznHY8vBai7IfxdLS5aeda++Z+AfEz923seiMraIiERGWFsbWmsfAh4a4no9cM1pn998jj4+Osz1bwLfDKc+EZFYKc8qP+vaq3Wvkp3vJjM18mH8aFMTyf2zePuqdw55/2dbBnacHW7GXkREEkMiLFMREZmwrB14t/zNp28GQ0Geq/8z8yoLIz6m2+fj4FEvH1z4SZKcSWfdr+uuA+Bz538u4mOLiEhkKYyLiIShy9sFQHpS+hnX97fuh7R28jOH33t8vHYcqefykuuHnI0HuGPrHQAUZWiHKRGRRKcwLiIShsbexrOuWWv5/b5fMb0sfYgW4Wnq7CTQXcyVM68a8n6frw+Avzvv7yI+toiIRJ7CuIhIGJr7ms+6dufrd9IRqqWyoCCiY1lr2XWknffM+jDJzuQhn7lvz30AVOVWRXRsERGJDoVxEZEwvDmMd7g7qO6qpo8WkpzOiI51tLmZMsdSFhcvHvaZE50nWF66PKLjiohI9CiMi4iEobW/9YzP/+vV/8JDB1ctHz4wj0fIWg6f6Ofts96LMUMdUjxw+BDAtXOvjejYIiISPWFtbSgiMtWtLl+Nx+8B4LnjzwHQTyvFOfMiOs6x5mZmpKxgZt7MYZ/588E/A5DiSono2CIiEj0K4yIiYVhdvhoYOODn2WPPAlBRkopjmNnr8bDWcqymn4/Necc5n6vpqtFacRGRCUZhXEQkAr7z0ncAqCosI5h39kud4Wjs7CSXKmbnzR72mZP7nV8+8/KIji0iItGlNeMiImHa1rANgM+s+QwHOndRlpcX0f6PNXRxWfm1w64VBzjRdQKAGTk6cVNEZCJRGBcRCYM/6Ofh/Q8zK28WACapn7TkobcdHA+P3093RzLLSped87mt9VsHxo/g8hgREYk+hXERkTB89+XvAvDh5R+mvqeerKzIhuETLS2syL+QVFfqOZ/b3bw7ouOKiEhsKIyLiIzTvpZ9+II+bll5C8YYantOkJUZ2TDe2OJnZcm6EZ8L2RCz84dfUy4iIolJYVxEZByCoSC/3/17SjJLmJ4zHYC6/mPkpKdHbAyv34+7N/mcL26ebrTPiYhI4lAYFxEZhx9s/AEAn1796VPXmtx1ZEcwjNe1t7Mw9zySnEmjev7kNwUiIjJxKIyLiIzR/tb99Pp6+ciKj+AwA19GQzZEl6+djJTIHbjT2ulhcd7KEZ8LhoIAlGaWRmxsERGJDYVxEZExCIQC3LvrXooyik7toALQ6+vF5QKnI3JfVju7OOeJmye1udsARj2DLiIiiUNhXERkDE7unvKZNZ8543q/v5/kpMi9vNnv9eIMZFKYXjjis239bREbV0REYkthXERklLY3bscb8HLLyltOLU85ye1344rgxHRbTw9VWXNHtW94h6cjcgOLiEhMKYyLiIyCJ+DhoX0PMStv1pAvSvpDfpyOyM2Mt/X2MSNzwaie7fJ0RWxcERGJLYVxEZFR+PaL3wYGDvcZij/ox+GwERuvv89QnlU+qmf7/H0RG1dERGJLYVxEZATPHH0GgM+v/fywy0YsFiJ43o+7n1GtFwfo8ymMi4hMVArjIiLn0NbfxosnXuTCaReOOhyHy1qL22MpSCsY1fPeoDfKFYmISLQojIuIDMNay3+/9t8AXD3n6nM+OzA7HYrIuG6fj3RX9qi3KvQGFMZFRCYqhXERkWH8fNvPAfja+q+d87k+Xx+PnvgdcyrzIjJun9dLfsroZ+EDoUBExhURkdhTGBcRGcL+1v3Udddx45IbSXGd+1TNPx16gNySHoqysyMydr/XS67CuIjIlKAwLiLyJt6Al3t33UtZVhmLihad89l9LfvY2fM3ls6oiOD4fnKS8kf9fNAGIza2iIjElsK4iMibfOvFbwHwqVWfOudz3oCX+w7dxfJ5+biczoiN7/H7yUrKHfXzIRuZteoiIhJ7CuMiIqd5+sjTwLm3MTzpmWNPkZzbTGlubkRrCAYgzZUe0T5FRCQxKYyLiAxq62/jpeqXuHj6xSNuY9jU28TzzX9i+azILU85KRg0I65TFxGRyUFhXESEM7cxvGr2VSM++6fD91E13UFacnLEawmFwOVwRbxfERFJPArjIiLAr3f8GoCvrv/qiM/ub93Pcd9W5pWP7rj6MbMGp4ncGnQREUlcCuMiMuVVd1VztOMo71n4HlJdqed8NhgK8qejv2PRrBwcI6wpHy9rwWFG/+XZEJ06REQk+hTGRWRKs9Zy57Y7SXYms7x0+YjPb2vYhie5mvK8yBzwM1xNYzHSi6YiIpK4FMZFZEq7Y+sdAPyfi//PiM8GQgEeO3Efi2YWRDUAGzO27Qo1My4iMnEpjIvIlFXTVUN9Tz3vW/y+Ub0wuaV+CyajJWInbQ5nrGFcREQmLoVxEZmSrLX8YtsvcBgHi4sXj/h8MBTkyZoHWTCjIOq1GYfVEfciIlOEwriITEl/3PdHYHS7pwDsbNqJTW2K+qw4gMNp8QV9o37eMrY15iIikji0ka2ITDk93h52Ne3iyllXkuwceZ9way3P1DzCnFk5MagOnE7wBDyjfj4rOWvML32KiEhiUBgXkSnne698D4BLZlwyquePdR6jg2OszJsRzbJOSUly0evuGvXzb5v7NvxBfxQrEhGRaFEYF5Ep5VDbIQBuXXPrqNu8WPtXppUnx2wLwWRXEn2B7lE/PytvVhSrERGRaNKacRGZUn6z8zekJaVRmlk6que7vd3s7nqVWSUlUa7sDWlJSXT7OmI2noiIxI/CuIhMGS+ceAGAL6774qjbbG3YSmFhiCRn7I6nT01OpsvXHrPxREQkfhTGRWRKsNby16N/ZU7+nBGPvD+9zSuNT1NVGr3TNoeSnpJCp8K4iMiUoDAuIlPCowcfBeD9S98/6ja13bX0mnoKs7KiVdaQUlwuvKH+MW1vKCIiE5PCuIhMetZattRvYUXpCpyO0S832d60lZJiR8xe3DzJGENKiqHLM/odVUREZGJSGBeRSe/hAw8D8O4F7x51G2stm1tfYEZRYZSqOre0FEOHRy9xiohMdgrjIjKpWWt5veF1lpcuH9MMd213LQFXBznp6VGsbnipaSHa3Vo3LiIy2SmMi8ik9vTRp4GxzYoD7GnZSVFhbJennC4j3UlDX23cxhcRkdhQGBeRSe3l6peZkz8Hhxnbl7vt7a9Snp8bnaJGISctnYb+43EbX0REYkNhXEQmrddqXwPg5qU3j6ldp6eTNn9tzHdROV1ORgb1/TVxG19ERGJDYVxEJq3HDz1OQXoBLodrTO2OtB8hN5eY76JyuvTkZDy2m15fb9xqEBGR6FMYF5FJ6UDrAQBuOe+WMbc92LmbwtzkSJc0JsYYMjMMTb1Nca1DRESiS2FcRCal3+36HQAZyRljametZV/nDkpzc6NQ1dikZ4Ro6GmIdxkiIhJFCuMiMumcDLCfO/9zY27b4enAQweZqamRLmvM8jJTOdF7KN5liIhIFCmMi8ik89MtPwWgKKNozG1rumrIyTZxXS9+Un5WFsd6DsS7DBERiSKFcRGZVE4eIf935/3duNof6zpCdnb8gzhATno67b4mPAFPvEsREZEoURgXkUnlJ1t+AkBVbtW42h/t2UthVnYEKxo/hzFkZRrqe+rjXYqIiESJwriITBpuvxu3380Ni28YV/tgKEh9/wnyMzMjXNn4ZWRa6rsVxkVEJiuFcRGZNO58/U4AlhQvGVf7lv4WUlKCJDmdkSwrLHlZqRzr1bpxEZHJSmFcRCYFX9BHS18L18y9Ztx9NPY2kpE4k+IAFGRmcqJHO6qIiExWCuMiMin8avuvAFhbuXbcfdT11JBAK1QAyB58idMb8Ma7FBERiQKFcRGZ8PxBP7XdtVw1+6qw+qnpO0xu+tgOCYo2hzFkpDto6W+JdykiIhIFCuMiMuH9esevAbh4+sVh9VPXd4LcjMQK4wDp6SGa+5rjXYaIiESBwriITGj+oJ/qruqwZ8X7/f24Q11kpKREqLLISUuH5r6meJchIiJRoDAuIhPaXa/fBYQ/K97c10xGemKcvPlm2alpNHlq4l2GiIhEgcK4iExYnoCH+p76sHZQOamlr4W0dBuBqiIvIzWVNo9mxkVEJiOFcRGZsP530/8C4e2gclJDXy0ZGYn5JTE9JYVOX3u8yxARkShIzL95RERG0O3tptvbzfsWvy8i/dX2HSUvwXZSOSk1KYlefw/WJubMvYiIjJ/CuIhMSN9/5fsALC5eHJH+6vuryUnAnVQAnA4HmAD+kD/epYiISIQpjIvIhFPXXQfAx1d+PCL99fn68IS6SE9Ojkh/0eByOvAFffEuQ0REIiysMG6MucEYs8cYEzLGrD7Hc3cZY5qNMbvfdP0+Y8z2wR/HjTHbB69fZYzZaozZNfjzFeHUKSKTyx1b7wBgWs60iPTX3NdMRoYjIXdSOcnhGNjGUUREJhdXmO13A+8BfjbCc3cDtwO/Pv2itfbGkx8bY74PdA1+2gq8w1pbb4xZAjwJVIRZq4hMAlvrtwLwDxf+Q8T6bOxtJD0jwddjG7AkeI0iIjJmYYVxa+0+YMTZJGvtC8aYquHum4EO3gdcMfj866fd3gOkGmNSrLXecOoVkYnNWssjBx5hes50slOyI9Zvbd9xsjOTItZfNBjQC5wiIpNQoqwZXw80WWsPDXHveuD14YK4MeaTxpgtxpgtLS0tUS1SROLrnp33APB35/1dRPut6T1MXoK+vHlSKAQuR7j/mCkiIolmxDBujHnGGLN7iB/vimAdNwP3DjH2YuA/gE8N19Bae4e1drW1dnVRUVEESxKRRNLl6eJI+xGumXsNDhO5eYRgKEh9fzV5mZkR6zMarAWnwxnvMkREJMJGnGax1m6IZgHGGBcD685Xvel6JfAQ8GFr7ZFo1iAiie8HG38AROaAn9O19LeQnBIgyZnYQTcQsKS6UuNdhoiIRFgiLFPZAOy31taevGCMyQUeA75qrX05XoWJSGLYVLcJgC+s+0LE+67vqScrK+LdRlQgGMSBS8tUREQmoXC3NrzOGFMLXAA8Zox5cvB6uTHm8dOeuxfYCMw3xtQaY245rZubOHuJyueAOcC/nLb1YXE4tYrIxOQL+njs4GPML5xPflp+xPs/0X2U7KzEnhX3BgKkJyX2MhoRERmfcHdTeYiBpSRvvl4PXHPa5zefo4+PDnHt34F/D6c2EZkcvvnCNwG4ecmwX0bCcrh7D9NLIrczSzT0e73kJOfFuwwREYmCRFimIiIypJN7in9q9aeiciCPN+Cl0V1NfoK/vOn2+chNLoh3GSIiEgUK4yKSkPr9/Txy4BEWFC6gPKs8KmPU9dSRmWlxOhL7S2Gf10Nhalm8yxARkShI7L+BRGTK+o+X/gOAm5dGZ3kKwNGOo2TnJP5BOv2eIIWpJfEuQ0REokBhXEQSzr27Bt7pjuSR90M50PU6xTkJvpUK4HE7ovLyqoiIxJ/CuIgklL0te9nfup/rFl4X0SPv38wf9HOs5yDFOTlRGyNS+t1QmF4Y7zJERCQKFMZFJGF0ejq5b/d9zMybyYrSFVEdq7qrmozMYMIf9hMMhfB6LHlp2k1FRGQyUhgXkYTgD/r54cYfAvDRFR+N+ngH2/eRNwHybVd/P8Vp5TrwR0RkklIYF5G4s9by7y8MHC3wL5f+S0zG3Nm+ibK83JiMFY6Ovj6mZcyOdxkiIhIlCuMiEnffeO4bANx20W0xmQHu9HTS6q+hICvxX97s7HVTmTEr3mWIiEiUKIyLSFx9/5XvA/DZ8z9LZnJsDt850HqAvDyLIwoHCUVaX6+DiuyKM675gj5+u/O3capIREQiSWFcROLmf177H7q93dyy8haKM4pjNu721lcpK8iI2XjjZa2lt9eedejRiyde5GDbwThVJSIikaQwLiJx8V+v/het/a18dMVHmZ4zPWbj9vv7OdSzk/L8xN+3u6u/n5ykYtKT0s+4/sKJF/RCp4jIJKGv5iISUydf1gyEAnzsvI8xI3dGTMff17KP3NxQwm9pCNDS3c2c7IvOuGbtwImh717w7jhUJCIikaYwLiIxE7Ih/u25fwPg06s/TVlWWcxr2NL8EuVl6SM/mAA6un2syJ5/xrVtDdsAWFK8JB4liYhIhGmZiojEhNvvPhXEv3TBl+ISxLu93Rzu3UHlBFiiAtDVxVn/cvDIgUcAMBPg5VMRERmZZsZFJOoaexv5yeafAPC19V8jxZUSlzpeb9hGQWEI1wRYouL2+bD+tDNebD25ROW6hdfFqywREYkwhXERiaptDdt4eP/DGGP410v/NW4zutZaXmx8grkLJsaseGNnJ/Nzl+Ewb/wD5qu1rwKwvGR5vMoSEZEIUxgXkaj53a7fcaD1AEuKl3DD4hviWsvh9sO4nQ0UZlXFtY7Rau10sz5n2RnXnjj8BA7j0BIVEZFJRGFcRCLOH/SfOt7++kXXs6xk2Qgtou9vNX+hqiJtwgTZzk6YVTmLmq4a0pLSyEnJAeCDyz4Y38JERCSiFMZFJKIaehr46ZafAvCFdV8gPy3+y0Iaeho40r+Nq4pjt595OHrcbpKCOZRklPCN577BVbOvotPTCcDs/NnxLU5ERCJKu6mISMQ8d/w5frrlpwPrwy/714QI4gBPn3ic6ZUunI6J8SWvrqOdxfmr6ff3A7C0eCmb6zZTmlka58pERCTSNDMuImEL2RDffOGbBEIBLpx2IVfPuTreJZ1S113Hru4XuWr+tHiXMmqtbQEuKVvB00efBgZ+fwFuWnJTPMsSEZEoUBgXkbA09Tbx480/BuCTqz5JRXZFnCt6g7WWPx/5A7OmJ0+I7QwBAsEg3d0OZi+azQN7HiA/LZ/f7/49AHlpeXGuTkREIm1i/JutiCSkpw4/dSqI/8ul/5JQQRxgT/MeTvi3Mrcs9gcMjVdDRwezMhfjdAx883D9outp7G1kXeW6OFcmIiLRoJlxERkzb8DLt178FgCXzLiEK2ddGeeKzub2u3ngyC9ZtiAfxwTZQQWgrrWXywsv4MnDTwIDp4YCXDX7qniWJSIiUaIwLiJjsq9l36llE59f+3kK0wvjXNHQHj38J9Ly2yjJrYp3KaMWDIVobzcsnr2Y77/yfYozirlv930AuBz6ci0iMhlpmYqIjErIhvivV/+L3+/+PeVZ5Xzjsm8kbBDf3bSbLV1/4bzZE+elTYD6jg5mpC8kGAoC8N5F7wXgA8s+EM+yREQkijTVIiIjOt55nF++/ksAPrT8Q8zJnxPniobX1t/G7w7/hJWLC0maIC9tnlTb1MNVxZdxz857AHi55mUA5hXMi2dZIiISRQrjIjKskA3x0y0/pam3ifSkdL5y4VdOvViYiDwBD3ftvp3pMwIUZRfFu5wx8fr9dHUksWT+Eh479BiXz7ycZ489q0N+REQmOYVxERnS4fbD3LNjYIb2xiU3sqhoUZwrOrdgKMg9u+/E5hxjbtmMeJczZkeamliRv55Xal4BoGpwrfsNi26IY1UiIhJtCuMicgZ/0M/3N34ft99Ndko2X1z3xYSeDYeBGfx7995Dg+M1LpwzEzOBdk+Bgf3Qa+sDvHPh5dy57U6m5Uw7tSwoLSktztWJiEg0KYyLyCmv1b7G44ceB+AjKz7CrLxZca5oZMFQkN/v+w2HAn/l4iUzJ9Q2hifVtrVR4ppLp6cTgBsX38j3XvmeTtwUEZkCFMZFhE5PJz/c+ENg4GXB9y99/4SYXfYGvPx2793U8DIXL5mJ0zHxNoiy1nKopoebpn2aB/Y+QHpSOo8efBSAhUUL41ydiIhEm8K4yBRmreWenfdwpP0IAF9c98UJc+R6p6eTX+76MZ7Mg1w4t2pCBnGAuvZ2soMzcQzW/5k1n+F7r3yPZSXL4lyZiIjEgsK4yBS1u3k3D+x5AIBr5l7D2sq1ca5o9A62HuSeA/9LybR+llXMmBCz+EMJWcu+Y118qOpW7tt9H6muVA60HQDgXQveFefqREQkFhTGRaaYbm8333/l+wAUZxTz6dWfTvgXNE/yBX08eeRxXmx7iBUL8yjNrYh3SWE51NDA9KSVeIIeAP5+7d/z3Ze/S2Zypk7cFBGZIvTVXmSKePOSlM+d/zmKMibOXtyH2w9z38G7IKuOy1dWkpKUFO+SwtLv9XL0eICvrLiZH2/+MSWZJbT0twDwyVWfjHN1IiISKwrjIlPA9sbtPLTvIQDeNvdtrKtcF+eKRq+1v5VHjzzEvr6XWDw7m8qCmfEuKWzWWrYdquOqspvZXLcZgE+s/AT//sK/A5CTmhPP8kREJIYUxkUmsXZ3Oz969UcAlGeV8/GVH58wS1La3e387cRT/3979x0eV3H2ffx71Hvv1U2y5SL3XunE1IfeCTXUhE4CSSBPeMNDCCH0EnozhBAgCQRDKAZjY1s2cq9yUe91VVfaef+QLCRUbUleSf59rkuXd2dmz7nP2NK5NZ4zw5riT0mId+H4lMQh+5Dmj+3Oz8evfiwLUhbz0MqHmBU7q3VU/IaZNzg5OhEROZKUjIsMQw7j4MUNL5JdmQ00z0UO9Ql1clQ9M8aQU5XDiqzPSC/7htgYi2NnRg/5KSltldps7N9ncfvUa1t/UVqatJT7v7ofgEi/SCdGJyIiR5qScZFhpu3GPWeOO5Op0VOdHFHP6hrr2FKwhW/yPiXfvou4WDeOS4rBw214/Yiqs9tZu7WQi8bcRrW9mrrGOi6bfBn7y/cDcOOsG50boIiIHHHD604nchQrqi7iybVPAjAqeBSXTb5sUC/5Z2+yk1GWwYaC79hYuhr/oAYSEv1IDRm6SxV2p8nhYPW2TI4Jv4DJkZO5/6v78XTzZHTIaO778j5cLBcifCOcHaaIiBxhSsZFhrhGRyPPrHuG4ppiAG6be9ugfQCwqr6KPaV72FSSxray9Xj71RMZ7s7iMeF4DaOpKD9mjGHNjv2MdT+Ok0cv5ZX0VwC4c96drNi/ovn1/DudGKGIiDiLknGRIWxl5ko+y/gMgHMnnMvEiIlOjqi9yvpKsiqyyCjfxbbyDRQ3ZBMcBOEhniwaE4K3h4ezQxxwxhjS9mQSap/O+akXk1mRyf7y/Zw9/mwMhi/2fUFqZCo+7j7ODlVERJxAybjIEJRXlcezac8CkBKewvkTznfq1A5jDLYGG/m2fHKrctlv28W+yh1UO0oJCLAIDLQYmRzIDP8EXIbhFJSuGGPYsDcTr6pxXDnlOizL4qXvX8LH3YfUyFTu+/I+AM5KOcvJkYqIiLMoGRcZQhqaGnjsu8ewNdiA5qkNfh5+R+z8xhhq7DUU1RRRXFNMri2LnJp9ZNv20YANP18LHz9DcKgXU0YG4O+VMCznf/fGwUTcvWIs107+OZ5unq3J953z72R11moArptx3VHbRyIiomRcZMj4ZM8nrQncxakXkxyaPGDnanI0UVZXRnFNMcXVxeTVZpFXc4D8mmwaqMbX28Lbx+Dr60JwiC9zff3w9ghRUtni4NQUb9t4rpl8E97u3vx757+B5hVTyuvK+WTPJ0yNnkq0f7SToxUREWdSMi4yyO0s3slbm98CYGbMTE5JPqXfkt76xvrWUe6C6nzyag6QW5NJSV0+Hp4GH2/w8jH4+7sTHuHDaJ8AvNxDlXR3o8nhYO3OA4Q0TOPKydfh6ebJzuKdrMtdx8ljTibUO5T/XfG/QPPSkyIicnRTMi4ySLXdPdPPw49fzPkFHq6H98DjwaS7sLqQPFsO2TV7ya3OxNZYio+3hbcP+PgYAsK9GevrS4B37LDZ7fJIamhsZPW2A4xyXcxFqZfj7upOaW0pb21+i7iAOObEzWnd3Oc3i3/j3GBFRGRQUDIuMsg0NDXw9LqnKastA+CmWTcR7hve68/bGmzkVuWSU5lDZvVuMm0ZlDUU4utt4eNr8PW1CAzyZbqvL76eR++c7v5WXV/Pqi3ZzPQ/gzPHnoWL5UJ9Y33rL1TXTL+GB75+AGheftLNRT9+RUREybjIoGGM4cOdH/J93vdA75YqbHI0kWfL40D5ATIqt7O3cjs2RykBfha+foagMG8mJPoS4HN0rWJypBVXVbFuazGnxl7FooTFWJZFk6OJP3zzBwDuW3Ifj6x6BHuTnetmXDdo14EXEZEjT8m4yCCQnp/O+9vfB2Be/DxOGnNSp+2MMRTVFLGrZBfby9LZU7kFN88GAgINIVrBxCn2FhSwJ8NwRfLdjI8YDzT/PR2cF37Pwnv4wzd/wN5k5+ppV+uBTRERaUfJuIgTFVYX8tTapwCI9Ivk2unXdpi+YIwhuzKbjYXfs6F4JdUUEhJsERHlw5JxoXgO450rB7Mmh4Pv92bRWBrLLVNuIsovCmj++zo4L/zWube2jo7/bMbPiPGPcVa4IiIySCkZF3ECe5OdJ9c+SXldOdCctAV5BbVrU1FXQVpeGqvyP6XWpZDwcIvxE0II9k3UyLeTlVdXk7YjnxTvYzhn+oV4u3sD7RPxy6dczqOrHwU6//sVEREBJeMiR9zXB77m872fA3DBxAtICU9pV59TmcMXmcvZVP4t4eFNjBsfSoifpp4MBk0OBztycsnJcuOskTczM2Zm699Lk6OpdWrKvPh5vJr+KtC8aooe1hQRka7oDiFyhBRVF/Hk2icBmBgxkXPGn9Muwc6tyuWjve+zu2YdiXHuHJccjYebvkUHi9yyMrZmlDHaczZ3Tb+QEO+Q1roaew0PrXyo9f2qrFVMipzEOePPcUaoIiIyhOhOLzLAjDG8nP4yB8oPAHDHvDvw9/Rvrbc12Pg445+klX3GiAR3TpiQoDW+BwljDPnl5ezKLMezPo5LR/2MlPCUDr9EPZf2XLvPXTP9GuIC4o50uCIiMgQpGRcZQHvL9rZOVzhz3JlMjZ7aWmeMIS03jff3vUpoVA3HzojVSPggUW+3s6+okOzcBgIZwRlxlzMlegouVvtfkr458A3/3fvf1vfjwsZxwcQLNKVIRER6TXd+kQHgMA4eX/M4ZbVl+Hn4cevcW9vNG66qr+JvO94gw76aaakRhPiFOTFaAahtaCCntJSC4noqK9yZHDKPq8YsYlTwqA7Jtb3J3rKBjwGa6+6cfyd+Hn5HPnARERnSlIyL9LOM0gxe2/gaAJekXkJSaFK7+l3Fu3h959OERFdxTMKIIzolpc5uJ7ukhOr6OiYnjjhi5x2MGpuaKKqsJL+8kvIyaKj1ZHzwdE6PmMXY8WPxcvPq9HOvbXyNjNIMDibih7pDqoiISFtKxkX6iTGG59c/T25VLgGeAdwy5xZcXVxb6x3Gwef7PuOz/GVMSQkiKih+QONxGEN5dTWFlRWUVzSSXWjDDW8aqMLFo/6oSsaNMVTX11NcVUVJZTW2Shds1RaJfklMClxK0uhk4gPju1z1pKq+iifWPkF9Yz0Hk/Bb5txKsHfwEb0OEREZfpSMi/SDtpv3nD/xfMaHj29XX2uv5a1tr7DfsYrF0+Lx9vDo9xgcxlBqs1FQXk55uaGi0kGwRzReJglbbTEu1DEy0Y3kmJQBOf9g0eRwUFVbS1l1NeXVNVRXuVBVbfAkgJH+E5gZMJ4Ro0cQ4x+Dh2vX/VDfWM/yjOWsz13fUnJwJPxmjYSLiEi/UTIu0kef7vmUb7O+BeDeRfd2SPAKqwt5YfPjuIfmsHjUKFz68eG+6vp6ckpLKC61U14BYR5xpATN55joZGpCa1hd8CW59q2MSPJkdOQY3Fxdez7oEGCMob6xkcqaGqpqa6msraO2xoXaWovaWgchnpHE+01hqu9oYuPiiPKLIsAzoMcHK0trS1m+Zzk7ind0qLtq2tUkBCYM1CWJiMhRSsm4yGH64SE+WDxiMceOPLZDm53FO3llx18YNQpGRyX2+ZzGGEpsNrKLyygpMZgGXyYGz2NO+BRGJY/C282bDXkb+HDvW9S65zA6zo8JYSP69ReAI6WxqQlbXV3rV3Wdnfo6F+rrLGrqHLjjQ4R3FJHecYz2SSQ8Ipxw33BCvUNxd3Xv1TnqG+tZk7OmdROmH7Msi+tnXE+kX2R/XpqIiEgrJeMihyG7Mpu/rv8rQKcP8BljWJn1Df/MfokZE0MIDwg47HMZYyiqrCSzqJySEkOgSyzTQs9h/NiJxAXE4WK5UGOv4bvs7/gi90M8/CtIGhtMZODIPl3jQDPGUNPQgK22lqq6Oqpq69ol245GV0K8wgnzGkO0VwxhXlGEBIYQ5BVEiHdI6xb0hyKvKo+1OWvZkLeh23bTY6azNGmpds4UEZEBpzuNyCE6OC3Fy82Luxfc3WHt6SZHEx/seo+0qn+xcEosfl6dr8rRk7LqavYXFFNYBMGuccwMP5VJqZMI9wlvnW5RXlfON5lf8W3hJwSG1jEtNZwg3xF9vcR+4zCGmvp6KmtqqKyrpbq2kbpaF+pqoaauCT+3IMK9o4jwjmO0ZzRhoWEEeQUR7B2Mv4f/Ya/XXWOvYVfJLrYWbmVXya5efSYpNInTkk8j0CvwsM4pIiJyOJSMi/SSwzh48JsHaWhq4JiRx7BkxJIObWrttby+9QXyXNaxZMoI3A9xjnZtQwP7CgvJK2jC3R7KnIhzuWTSdCJ8I9olpgW2Ar7M/Iz1pV8SFWWYPz0SX0/Pvl7iYTHGUGe3U1lTQ0VtLbbaeuoOzt+uc+DvHkKUTyJRXvFEeMcQGhRKiHcIwd7B3T5A2R2HcVBgKyCzIpP95fvZW7aXusa6Ltu7WC44jKND+bz4eSwesbjLZQxFREQGmpJxkV6oqq/iT6v+BMC1068lNiC2Q5vS2lKe3/QYriGZzB81stfztB3GkFtayoH8KmzlnkwNXcLSMfMYGTSyw8hwZkUmnx/4D9uqviM+1pXjxkQfsV07HcZQVVtLRU0N5TXV1NZAbY1FTa3Bw/IlyieOSO94xnvHExYdRqh3c9Ld2/nbB9mb7OTb8smpyiG3KpecyhyKa4p7/FyUXxSjgkcR4x9DQXUBq7NW0+hobIm9ORFPDk3mmJHHEOMfc+gdICIiMgCUjIv0oO2W9vcsvAdPt44j0JkVmfx1y5+JSaxlbEzvHtSsbWhgd14BuflNRLsnc3L0ZaSmpHY4vjGGPaV7+PTAP8ms38SIeE9OHB8/YJsFGWOoqqujvLqasupqaqstqmugttYQ7BlBjE8KY31GEBUcQ2hsKGE+Yfi4+/R43PrGevJt+eTZ8siryiPflk++Lb9XMXm4ehAfGE9cQBzxAc1/ert7Y4whqzKLVVmr2F60vcPxpkRNYX7CfCJ8Iw6rL0RERAaaknGRbqzYv4Iv9n1BuG84N868sdM5zOn56SzLeIqJY72JDYnu8ZhFlZXsySmlstST2eEnc/7EBUT7d/ycwzjYWriVTzM/pMTsZlS8DydE9O/KKA2NjZRVV1Nms1FV3Uh1tYWt2hDoHkqs7zjG+44hOjyGcJ9wwnzCOh3lrrXXklGaQW5VbutXeV15r85vWRYx/jHE+McQ7RdNtH80kb6R7TZLassYw7aibbyc/jIFtoJ2db4evsyPn8/0mOmadiIiIkOGknGRLry44UUyKzJZmLCQ40cf36HeGMMX+//L8vzXmZ0aSbCvb5fHMsaQVVJCRlYVnvZojom5huljO08amxxNbMzfyPKsf1DjlsWYEQFMCRlx2A8zHlTb0EBJVRWlNhs2m0V1NTQ2uBHjm0iC7xxm+I8kMiqSSL9IvNy8MMZQWV9JdmU2mwo2kV2ZTWZFZq/O5eXm1Zxg+0e3Jtkh3iEdHnbtycH/Ffhs72cdku/EoEQWJixkTMiYPveNiIiIsygZF/kRh3Hwu69+B8BFky5ibNjYDm0aHY38fcfbbK75hMVTE7rc0dIYw/6iIjIyqwl3GcsFCWeQEp7SaVLa6GgkLTeNT7P+QZNXAWOTgokMPLwkvLahgeKqKkqrbNiqLKqqwc3hQ4LfaJJ8x+DnH4BboBtNpomi6iLyK/PZlLetV8eO8Y8hLiCO2IBY4gLiCPUO7ddkuLS2lP/u/S9bC7e2Kx8VPIpjRh6jjXdERGRY6VMyblnWucD9QAowyxiT1kW7l4BTgUJjzMQ25e8ABzOdIKDcGDOlTX0CsA243xjzp77EKtIbtfZa/m/l/wFw8+ybCfMJ69CmuqGaV7Y8S6nHJhZPHtnlrpa5ZWVs21tGhDWeK0af3eUIrr3JzrrctSzPeg9Xv1LGpoQQHtDzGuEOY6htaKC6ro7tOTnsLyrEDS88CWj58seDOCxcOLgid15ZOXllnX6b4uriSqx/bLtEO9AzcMBHnR3Gwfrc9Xy8++N2K54Eewdz0uiTGBc2TiPfIiIybPV1ZHwLcBbwXA/tXgGeBF5rW2iMOf/ga8uyHgEqfvS5R4H/9DFGkV4prinmiTVPAPCrhb/qdApJYXUhz296FJ+IAuaN6HzU2lZXx/d7cnGriePiUdcyPnx8l0n42pw1LM96D/eAUiZOCCPUf0SHdsYYbHV1FFdVUV5dQ021C3klVbjhjRueuOKJG/HEMwZX3LEsi0jfSAK9AgnwDMDfwx9/T3+CvIII9AwkyCuoyznZR0q+LZ9PMz4lozSjXfnCxIUsSFigOd8iInLU6FMybozZDvQ4amWM+dqyrBFd1VvNBzgPOLZN2ZnAXqC6LzGK9EZGaQavbWz+XfG+Jfd1Oo1kZ/FOXt35GCNHGUZHdpwq4TCG7dm5ZGe5cHLcT1k4cVGnOzg2OZpIy03j48y/4epXTOqkcEL8fhgJN8ZQUVNDblkZ5eVNVFSCj0sIfi6x2GrrAYuD+30mBCZw4ugTiQ+M75d+GCi2BhsrM1eyOmt1u/LYgFhOHnOypp6IiMhRa7DMGV8IFBhjdgNYluUL3A2cANzR3Qcty7oWuBYgIUE3dDl0a3PW8tGuj4j0i+SGmTd0qD+4tf2/sl9i2vhgIgI77tBYUVPD+p35xLlM5+7plxLiHdLpcbYUbuHDfcto9MphwoQwwvx/SMJrGxrYmplHSYnBh3AmBZ/IgohkttK8i6SNBsBiVuwsjh91fKdLLA4W5XXlrM5azXfZ37Urd3Vx5fhRxzMrdpa2mhcREaEXybhlWf8FojqputcY82E/xXEhsKzN+98BjxpjbL0YdX8eeB5gxowZpp/ikaPEhzs+ZEPeBqZHT+f0cad3qLc32Xl/17uk2/7Dgk62tjfGsDs/n337DGcmXsecuLmd/k9RTmUO/9j9FvlmM+OTgokObj8nPK+sjI07K1gSfg4zU2fj5ebFXzf8lY15zQ8xjggawXkTzsPXo+sVW5yl0dHItqJtrM1ZS1ZFVof6RYmLmBs/t1drkYuIiBxtekzGjTEd13TrR5ZludE873x6m+LZwDmWZf2R5gc7HZZl1RljnhzIWOTo8sSaJyiuKebU5FOZGTuzQ31FXQWvbHmWKq+tLJkyosODmg2NjaTtysS7Npnbp17b6cYytfZaPs74F2tK/8OYEZ4cG9l+V02HMWw+kE1ZfiDXpfyWUO9QHlvzGE2OJoAuY3OWGnsNWwu3srFgY6eJd5hPGPPi55EamXrIO2+KiIgcjQbD/xMfD+wwxmQfLDDGLDz42rKs+wGbEnHpL02OJv53xf8C8NMpP2VkcMeVS/aV7ePlbY8RHmdjblzHbelLbTbWbitgbvCZnJpyeqeJ57bCbby95wV8Q8s4dkZsh23rq+vrWbs9mwSX2Vw+9SJeTX+1dbOci1MvJjk0uZ+u+NBVN1Szq2QX24u3s7N4Z6dtAr0CmRY9jWnR0wjwDDjCEYqIiAwPfV3a8H+AJ4Bw4CPLstKNMSdZlhUDvGCMWdrSbhmwBAizLCsbuM8Y82LLYS6g/RQVkQFja7Dx8LcPA3DLnFsI9g5uV2+M4ZvMr/lX9itMHhdATHBch2Pszstn3z64ZMydpEaldqivb6znw93vsb7iE6akhBIZmNihTXZJCZt32VgaewXV9TU89t1jAJw74VwmRkzs0L6/GWMorC5kf/l+9pfvJ6Msg/rG+i7bT4iYwMSIiSSFJGnEW0REpB9ZxgyfadYzZswwaWmdr6EsklmRyYsbmn8HvHfRvXi4tt+op9Zey992vMmuhhXMTuk4P7zJ4WD9nkysihFcOfFGwn3D+bF8Wz6vbH0KE5DFtDHxuP9oakuTw8Gm/dlUFYZyYvz/sHzPcgDmxM3hJ0k/6bdrNcZQVFNERmkGe8v2sq98H/Yme7efifGPYUzIGEaHjCYhMOGQd8sUERE5mliWtd4YM6OvxxkM01REBtzKzJV8lvEZ/p7+3D739g7TTnIqc3hl21O4h+SxJGUkri7tE9Hq+nq+25pNitexnDv9ok5XMknPT2fZnqdJGu3KqMgRHeptdXWs2Z7DaPcFWFZ1ayJ+z8J7+rQySlF1ERvyNpCen06NvabLdtH+0SQGJpIYlEhCYAJ+Hn6HfU4RERHpH0rGZVgzxvBM2jMU2Ao6HX02xrA6exUfZr7M2DGejAjvOKWkoLyc73dUcErsVSxKWNwhkTfGsDzjY74oeofZkyMJ9u244smBoiK276ljetApbCvcDsB5E85jQsSEQ76eXSW7+Hzf5xTYCjrUJwQmkBKewriwcZ0urygiIiKDi5JxGbZq7DU8tPIhAC5JvYSk0KR29bX2Wt7d8SY76lcwb0oM/t7eHY6xKzePrAPuXDPung6fh+alD9/e/jq7Gr5kybQEvNzbz6ducjjYkJFFY1k0sa7JbCvcjquLK/csvKfX62w3Ohr5ct+XrMxc2a48MSiRefHzSA5N1pQSERGRIUrJuAxLu0p28eamNwG4a/5dHdbnzq7M5uWtT+EVms8xnUxLOZhEU57IbVNvJtQntMM5au21vLT5Gco801mU2vEYFTU1rN2eR5LHAg7U5lJKKUuTljI7bnavriE9P533t7/f+t7b3ZvTkk9jfPj4Hne9FRERkaFBybgMO29seoPdJbuJ8oviuhnXtUtcjTF8m7WSf2a9QsoYLxI7mZZSb7ezelsmI1wXcNH0y/Fy8+rQpqq+iuc2/gUTvJe5ozoufZiRX8CevU1MDTqF7UXN01Jum3sbgV4dd+9sq9HRyN+3/b31MwCXT7mcUcGjDqkPREREZGhQMi7DRmV9JY+segSAs1LOYnLU5Hb1dY11/G37G+ysX8GCqR1XS4Hm0ezVW/JYEnY+J49e2un0j/K6cp5O/xN+UflMiE9ol4jbm5pYvzsTN9soxvkmsL1oOyHeIfx89s+7Hc1udDTy+sbX2V++H4ApUVM4bexp2jJeRERkmNOdXoaFrw98zed7Pwc6n5aSV5XHS1ufxD0kt9PVUgByy8rYtMPGeSN/wYyYzlcqKq0t5cn0hwiLK2NcbPs1yEttNtZtK2Bm0Clsr93N/ur9nDD6BBYkLOgybmMM/9nzH9ZkrwHg2JHHsihxkaahiIiIHCWUjMuQ1vYhzenR0zl93Okd2qzPXc/f9j5L8hh3RkZ0nJYCsCsvj+z9Hlw//ted7sgJBxPx/yMyoZKk6JjWcmMMO3PzyDrgyjkjf86/d/0bgGumX0NcQMdNg9raVLCJNdlrmBEzg1OTT1USLiIicpRRMi5D1or9K/hi3xcA3Dz7ZsJ8wtrVNzma+OfuD/iu/ANmT44iqJMlB40xpO/LoqE4llun3tLpg5oAZbVlPJn+UEsiHtVaXme3k7Yzi4CGFK5MOYc3Nr0BwN0L7sbH3afHa5gUOYlJkZO0GoqIiMhRSsm4DDmltaWt28dPjZ7KmePO7NDG1mDj1S3PUeK2kWOmJuLh1vGfemNTE9/tOEB44zSun35tl8lzRV0FT6X/kfD4cpKio1vL88vLSd9ZzpLw80iJn8Ar6a8AcN+S+3qdXCsJFxERObopGZchwxjDaxtfY2/ZXqDr1Ulyq3J5YctfCIgsYX5ix5VOAGrq61m1NYspvks5a8J5XT4oaWuw8czGRwiKLWZsTCzww5b2lYVBXDP2Xuqb6nkl/RWCvIK4de6t/XjFIiIiMtwpGZchYWP+Rv6x/R8AnJJ8CrNiZ3XabmvhVl7b9TjjktxIDI/vtE2pzcbaLYX8JOZKliQe0+U87brGOp7b+Bhe4TmMj2s+Vnl1NWk78knyXMh1My5ma9FWPtr1EcmhyVycenE/XKmIiIgcTZSMy6BWXFPME2ueACDaP5prpl2Dq4trh3bGGL7OXMG/c15m1qQwQv39Oz1eVkkJ23fVc+mYO5kUOanL89qb7Ly06RkcgXuYkpiAMYYdOblkZbpy1sibmRkzk1VZq/g049MuHxwVERER6YmScRmU6hrreGLNE9gabAD8Ys4vCPEO6bStwzj4YOd7rKv6kEVT4/H19OzQxhjD9pxcirL9uWnS3d2ucuIwDt7a9iplnunMGT2C6vp60nbmEGGmcNf0KwjxDmldSnF+/HxOHHNi/1y0iIiIHHWUjMug0uRo4s3Nb5JRmgHAhZMuZFzYuC7bNzQ18MbWlzngWMniySM6fVCzyeFg/Z5M3KvGcOu0mwjyCuryeMYYPtj5HnubVrAgZSS78vLYv99wSvzVLEhYiIvlwsrMlXy+93MWJizk+NHH9/maRURE5OilZFwGBWMMH+78kO/zvgfguFHHsShxUbefqW6o5oVNT1Lju50FSZ1v5FNnt7N6ayZj3BdzwdRL8XTrOGre1lcHviSt6p9MGxvJ15v3EeFI5Y6pPyXcNxyANdlr+CzjM+bHz1ciLiIiIn2mZFycLq8qj2fTngVgesx0Tks+rcfNb8rrynl245/xDMth1ojETtuX2mys21rIsREXcuKon/R4zPT8dD7KfZmIcIu0TVWcknAN8+MXtC4/uLlgMx/v/piZMTM1NUVERET6hZJxcTrLsjh5zMnMjpvdq3W3i6qLeHrjHwmPr2BcbOcrphwoKmLHbjsXj7mD1KjUHo95oPwAb+15ElfvWvyq5nP19MvbzVHfW7aXv2/7O+PCxnHq2FN7f3EiIiIi3VAyLk4X5RdFlF9Uzw2BnMocntn8RxJHNTA6MqZDvcMYNu/PpqowjF9M/gUx/h3b/FhpbSkvbP0zLr6lRDXN5OopN+Lh6tFaX2Ar4NX0V4n0i+TCSRf2/sJEREREeqBkXIaM/eX7eX7rHxmb5EJ8WGSH+nq7nTU7sohyzODa6Vfh6+Hb4zHf3fouaYXfYAKz8KtL5qppN7VLxG0NNp5e9zQAN8y8of8uRkRERAQl4zJE7C7ZzQvbHyY1xZvo4OAO9SVVVazbVsTisHM5efTSTtcibyu3Kpfn0p7DTg2FbCOyJolrp9yKv+cP65M3Ohp5+NuHAbh/yf39ej0iIiIioGRchoBthdt4dfefmTrBn4jAwHZ1xhh25+ezf58LlyXdxcTIid0ey2EcPJf2HPm2fBw0Uum+i1ArjivH3tpuqowxht+v+D0Av1706x4f/hQRERE5HErGZVDbXLCZ1/c8ysyJwR121WxobGT97iw8q8dwx7TrCfMJ6/ZYO4p3sGzzMgBGBo9kY/UneODNOYk/IzksuV3bv3z3FwBum3sb7q7u/XdBIiIiIm0oGZdBa0PeBt7e9zizU8MJ9m0//7ukqoq07YXMDDqFM6af3W3CbG+y8/Cqh6lvrCfUJ5TTkk/jqa2/x+HSwPFhlzEnbm679v/e+W/K68q5cuqVBHoFdnFUERERkb5TMi6D0tqcNbx74GnmpUYS6OPTWn5wW/ucTHcuHnNnj8sWbirYxHvb3gNoTa4fWX8/dS6FTPc7nVOSTm/XfkvhFtblruMnST8hMSix/y9MREREpA0l4zLorMr6lg+yn2P+5GgCvL1by6vr61m3I5twx2Tumn4Vwd4dH+Q8yN5k5/9W/h+NjkbiA+O5aupVNDQ18OT3D1NsdjLWcxEXT/hpu3XNi2uKeXfru4wJGcOcuDkDeo0iIiIioGRcBpkVB77i47yXWDA5Bj8vL6B5NHxvYSG79zZwcsxPWTLimG43B9petJ23t7wNwNXTriY+MB6HcfD29tfZUbOSBI+pXDWp/RKG9iY7T6x5AoBLJ186gFcoIiIi8gMl4zIoGGP4775P+W/RGyycHIePpycAtQ0NrN+VjXfdaG5JvabbTXwcxsFfvvsLFXUVRPtH87PpP2tdBWV5xn/4pvgfRLiP4brU29otYQjwwNcPAPDbxb8doCsUERER6UjJuDidMYaP9vyTb8v/zqLJ8Xh7eGCMIaOggD377BwfdSHHTjwBN5eu/7lmVmTy4oYXAbhs8mWMDhndWpeWm8aHWS/iZ0Vw3aS7CPcNb/fZl79/GYBb597a4/rkIiIiIv1Jybg4lcM4eG/HO2ys/Q+LJyfi4eZGZW0t3+/KI7BxHLemXkG0f3SXnzfG8ObmN9ldshtPN0/unn93u4Q6ozSDV3c+ihteXD/xVyQEJrT7fFpuGvvL93P+xPMJ8goaqMsUERER6ZSScXEae5Odt7a9yt6mFSycNAIXy2LzgWzyctxYGn8VCxIWdjs3vKy2rHU98DPHncnU6Knt6gurC3ly44M4aOS68b9mbNjYdvVF1UX8a+e/SI1MZXz4+H6/PhEREZGeKBkXp6ix1/Dy5mcp99zIgpSRFJSXs3lPOSm+C7l8xrk9jlJ/se8LVuxfAcAvF/wSb3fvdvVV9VU8vPZ31FPF1ePuZlLkpHb1TY4mnlz7JABnjz+7/y5MRERE5BAoGZcjrqy2jOc2/QX30CwmRkfx3fYDuFTHcuWYGzuMXv9YfWM9f/jmDwDMjZvLyUknd2hT11jHg6vvo5ZSrhp7F9Oip3Vo878r/heA3yz+TT9ckYiIiMjhUTIuR1RmRSZ/3fJnwmOrsDfC6u8rOSnupyycsLDbBzQBNhds5u/b/g7AzbNvJswnrEMbe5OdB1f9Dpsp5pqUXzI5anKHNh/v+hiAG2be0OM5RURERAaSMhE5YtbnrmdZxlN4BVaSlePPrJATuXbmqR2WGfwxh3Hw6OpHqayvJDEokSumXNG6ZGFbTY4mfvfNb6gxpdww8R7GhY/r0CarIos1OWs4ftTxRPpF9tu1iYiIiBwOJeMy4JocTfxz9wcsz30DsEh2HMNpqed0u0rKQVkVWbyw4QUALp9yOaOCR3XazmEc3L/itzRSxy+m3tvlVvYf7/6YcN9wFiYuPOzrEREREekvSsZlQJXXlfPQ6t9TSTYjvSdzTvKl7dYA70pPSxa2Vd1QzR+//SNguH3WvR3WEW/rokkX4efhd7iXIyIiItKvlIzLgHAYB0+ufZK8mkwMTdw44T5SwlM6nV7yYyU1JTy+5nEAzhh3RqcPYB60o3gHyzYvA+C2OXcS7B3c7bF7mhIjIiIiciQpGZd+VddYx9PrnqairgKA4xJP5riRx/UqCQf4z+7/8F32d0DnSxYeZIzhhQ0vkF2ZBVjcOf9OjXiLiIjIkKNkXPpF27ndYACL2+fdToBnQK8+X2Ov4aGVDwGwKHERx406rsu2hdWFPLX2qZZ3FnfNvwtfD9/DD15ERETESZSMy2FrdDTyn93/IS03rV35zJhZnDr21F4fZ13OOv69698A3Dr31i43/DHGsGzLMnYW72wt+9XCX+Hl5nXowYuIiIgMAkrG5ZAYY9hUsIl/bP9Hp/W3zb2NQK/AXh2r0dHIg988SKOjkfHh4zl/4vldtm0/8t7sN4t/o3XCRUREZEhTJiO9srN4J+9sfYcmR1Nr2ajgUewt2wvAqcmnMjN2Zq+Pt69sH6+kvwLANdOvIS4grtN2jY5GHl/zeOsc9IPuX3J/r+ehi4iIiAxWSsalU8YY0vPT+WDHB+3KTxx9IpF+kby+8XX2lu1lRNAILp9yOS6WS6+P+8amN9hTugc/Dz9un3d7l59dnbWaT/Z8AkBcQBzZldnEBsRy7fRr+3RtIiIiIoOFknFpVd9Yz4oDK/g289t25SeNOYk5cXPIt+XzXNpzALi6uHL73NsP6cHJiroK/rz6zwD8T8r/MCVqSqft2j6gOTZsLOV15WRXZrMwYSHHjz7+MK5MREREZHBSMn6UK7AV8NHujzhQfqC1zNPNk9PHns6E8AlYlkVeVR6/++p3rfU3zbqp2411OvNt5rd8mvEpAHcvuBsfd58ObRodjTy19ilKa0tbz/Pk2icBuHTypYwJGXPI1yciIiIymCkZP8oYY9hWtI0PdnxAQ1NDa/nokNH8ZMxP2iXZB8oP8NL3L7W+v27Gdb3awr4te5OdB75+AIBp0dM4Y9wZnbb7av9XfLnvSwDOm3Aevh6+rYn4HfPu0GY9IiIiMiwpGT8KGGNYn7eef+38V7vyhYkLWZS4CA9Xj3bl24q28c6Wd1rf3zDzBiL9Ig/5vLtKdvHmpjcBuH7m9UT5RXVo0zbhnxQ5ibNTzubDnR/yfd73BHgGcNvc2/SgpoiIiAxbSsaHse1F23l7y9vtys4YdwZTo6Z2muCuylrF8j3LAXBzceOmWTf1uL18Z4wxPJv2LPm2fMJ8wrhp1k0dztd2kx/Lsrh7/t1YlsX9X90PwE+SfsKcuDmHfG4RERGRoUTJ+DBTWV/Jss3LyK3KbS07c9yZTIma0mkC7jAOPtr1UevGPRG+EVw59cout6HvSW5VbutDnhdMvICU8JR29T/euOeqaVeREJjApoJNvLftPaD7jX9EREREhhMl48PEjuIdLNu8rPX9nLg5nDj6RFxdXDttb2+y8+bmN9lXtg+AlPAUzhl/Tp820Xl7y9tsL9oOwK8X/Rp3V/d29W132jxh9AksSFhAk6OJh799GFuDjZHBI7l88uWaliIiIiJHDSXjQ1zbqSUAP5vxM2L8Y7psX2uv5YUNL1BcUwzAgoQFHD/q+D4lwKW1pTz23WMAnJJ8CrNiZ7Wrz6nM4fn1zwOQEJjAFVOvwMVyYW/ZXl5NfxWAn075KSODRx52DCIiIiJDkZLxIWpl5ko+y/gMgEi/SK6YckW3U0tq7DU8s+4ZKusrAViatJTZcbP7HMfHuz5mTc4aAH654JftYqix1/Dwtw/jMA7gh1VRHMbB0+uepsBWgL+nP7fOubXLEXwRERGR4UzJ+BCzpXAL7259F2geZb5s8mUdpoO0Vd9Yz7Npz7au3d3dZjuHoqq+ij+t+hMAi0cs5tiRx7bWOYyjdYdOgCumXsGIoBEA7CvbxyvprwCdzykXEREROZooGR8iiqqLWtfdDvYO5voZ1+Pp5tlle4dx8NrG11rnhPdXEg6wYv8Kvtj3BQC3zb2NQK/ATutOHH0i8xPmt8bzzLpnKKwuxMfdh9vn3d6n+ekiIiIiw4GyoUGuydHEM2nPUFRdBMAtc27pcbnBL/d9yVf7vwJ+eFCyP9gabDz87cMAzIiZwWljT2uta/sA6biwcVww8YLWeegZpRm8tvE1AC6cdCHjwsb1SzwiIiIiQ52S8UEsPT+d97e/DzTvSjkhYkK37bMqsnhhwwsATIiYwLnjz+23lUk+2f0Jq7NXA+1/Ici35fPMumcA8PPw4+bZN+Pl5gU0/yLxxNonKKst09xwERERkU4oGR+E6hrrePCbB4HmeeFXTr2y26S60dHIo6sfxdZgAzo+SNkXeVV5PJv2LADz4udx0piTgPZzxgF+MecXhHiHtL5vu/vmxakXkxya3C/xiIiIiAwnSsYHmbTctNZt63uzDX3b0fNLJ1/KmJAx/RJHfWM9j615jOqGagDumn8Xvh6+NDQ18Gzas5TUlADtH86E5tHwx9Y8RkVdBcHewfx89s9xsVz6JSYRERGR4UbJ+CDR6Gjkga8fwBjTYc51Z+xNdv7fN/8PYwyJQYlcMeWKfpmS4jAOlm1exq6SXQBcNOkixoaNxWEcvLHpDXaX7AbgrJSzmBw1ud1nd5fs5o1NbwD9+4uBiIiIyHClZHwQaLvc37XTryU2ILbb9juLd/LW5rd63b43Gh2N/G3r31q3qV8yYgnHjDwGYwwf7/6YNdnNa4kfM/IYloxY0u6zDuPg8TWPU1ZbRoh3CDfPvlmj4SIiIiK9oGTcyd7d+i5bCrfg7+nPbXNv6zaJNcbwwoYXyK7MJtIvkutnXN/n0fDimmJeSX+FqvoqAObGz+Wk0SdhWVa73T2nRE3hzHFndjhf218kLkm9hKTQpD7FIyIiInI0UTLuJPWN9fzhmz8AcGryqcyMndlt+8r6Sh5Z9QgA5088n/Hh4w/73HWNdSzfs5wNeRtay9rG0HZjocSgRC6ffHmHVVCMMfx1w1/JqczBz8OP2+beppVSRERERA6RknEnaLsE4a1zbyXIK6jb9m0f0jyclVKMMewv38/n+z4nqyKrtTzaP5rzJ5zfukxh27gCvQK5YeYNrcsUttV2hZXeLLkoIiIiIp1TMn6EHdyQx9vdm7vn393jNJOXvn+JA+UHGBs2losmXXTI52u7PjjAyOCRLE1aSoRvRGtZRV0Ff17959b3P95Vs62D02oAfr3o17i7uh9yTCIiIiLSTMn4EWKM4Ym1T1BSU8KChAWcMPqEbtu3ncbSl2kpqVGpJIUmMSp4VIfEv9HRyHNpz1FYXQh0/zBo24R9adJSZsfNPqx4REREROQHSsaPgIamBv7f1/8PgMunXM6o4FHdts+tyuW5tOcAuH3e7QR4Bhz2uWP8YzotPzhCD50vU9jWiv0r+GLfF8AP642LiIiISN8pGR9gRdVFPLn2SQDunH8nfh5+3bZfnbWaT/Z8grurO/cuvLfftrM/qG2inxqZylkpZ3V5jra/RMyMmcmpY0/t11hEREREjnZKxgfQtqJtvLPlHQDuW3Jfj2tvv7jhRTIrMgck8XUYB0+ve5qi6iIA7l5wNz7uPl2231G8g2WblwFw46wb280xFxEREZH+oWR8gCzfs5xVWasYFTyKy6dc3m3bRkcjv1/xewAunHQh48LG9WssbTcJumDiBaSEp3TZ1hjD8+ufJ7cqt9/WMhcRERGRzikZHwBPrX2KwupCjh91PAsTF3bbtqSmhMfXPA70bpnDQ9F2Z8xQn1BumnVTt6PzbWPpKWkXERERkb7rUzJuWda5wP1ACjDLGJPWRbuXgFOBQmPMxDbl7wBjW94GAeXGmCktdanAc0AA4ABmGmPq+hLvQGs7wn3Z5MsYHTK62/ZtN9f57eLf9uumOW3nhl86+VLGhIzptv0X+75gxf4VANyz8B483Tz7LRYRERER6VxfR8a3AGfRnDR35xXgSeC1toXGmPMPvrYs6xGgouW1G/AGcKkxZqNlWaGAvY+xDqjyunIeXf0o0LsR7oPrdY8JGcOlky/t11j+vfPfrMtdh4vlwr2L7sXNpeu/ZnuTnQe+fgCAuXFzOTnp5H6NRURERES61qdk3BizHehxTrEx5mvLskZ0VW81H+A84NiWohOBTcaYjS2fL+lLnAOt7cOOv1n8m26T37aj52eMO4Np0dP6LY62ifUJo09gQcKCbtvvKd3D6xtfB/SQpoiIiIgzDJY54wuBAmPM7pb3yYCxLGs5EA68bYz5Y2cftCzrWuBagISEhCMRazvvb3+f9Px0EgITuGraVd22bTt15ObZNxPmE9ZvceTb8nlm3TO9OrYxhlc3vsq+sn2E+oRy86yb9ZCmiIiIiBP0mIxblvVfIKqTqnuNMR/2UxwXAst+FNcCYCZQA3xuWdZ6Y8znP/6gMeZ54HmAGTNmmH6Kp0dtR6FPST6FWbGzum3/8a6PWZOzBhfLhV8v+nW/zg8/uDY59LyEYtvpNGePP5vUyNR+i0NEREREDk2Pybgx5viBDKBlfvhZwPQ2xdnACmNMcUubj4FpQIdk3Bn2l+/n5e9fBnoeha5uqOaP3zYP6h836jgWJS7q11gOrk0+PXo6p487vdu2Xx/4ms/3NnfhLxf8Em93736NRUREREQOzWCYpnI8sMMYk92mbDlwl2VZPkADsBh41BnBtWWM4a3Nb7GrZBd+Hn7cPu/2bkeh2245f8ucWwj2Du63WA5lbfK2o/jaSVNERERk8Ojr0ob/AzxB87zujyzLSjfGnGRZVgzwgjFmaUu7ZcASIMyyrGzgPmPMiy2HuYD2U1QwxpRZlvVnYB1ggI+NMR/1Jda+Kqwu5Km1TwE9P3hZYCvg6XVPAzAtehpnjDujX2NpO9WkpyS/7YY/N8y8gUi/yH6NRUREREQOn2XMEZtmPeBmzJhh0tI6Xer8sLUdDYfup3fU2mv5y3d/oa6xeTn0O+bdgb+nf7/G0/Yh0O5WbjHG8Gzas+Tb8rWTpoiIiEg/a3mecUZfjzMYpqkMWvvK9vFK+isALE1ayuy42Z22q2+s58XvX6TAVgDAJamXkBSaNCAx7Sze2eNoe9uR+Z6msIiIiIiI8ygZ70R9Yz0Pr3oYe5MdTzdP7px3J+6u7h3a1dhreHHDixTXFANwavKpzIydOaCxHTPymG7rP9r1EWtz1gJw76J78XD1GNB4REREROTwKRlvwxjDR7s+Yl3uOgCumHoFI4JGdGhXVlvGU+uewt7UvClob5Y2HGh1jXU8+M2DwMCs2iIiIiIi/U/JeIttRdt4Z8s7AMyOnc3S5KUd2uRU5vD8+udb35834TwmREw4YjF2pW3s/b1qi4iIiIgMnKM+GW87vzrIK4gbZ93YYWpHRmkGr218rfX91dOuJj4w/ojG2RljDC+nv8yB8gPEBcRx9bSr9ZCmiIiIyBBy1CbjVfVVPLL6EQ6uJvPz2T8n1Ce0XZvdJbt5Y9Mbre87a+MsNfYaHlr5EDB4RuhFRERE5NAcdcl4XWMdz6x7hvK6cgAun3I5o4JHtWuTWZHJixual0F3sVy4Zc4tBHoFHulQu7SndA+vb3wdgLvm34Wvh6+TIxIRERGRw3HUJOP1jfW8sOEFCqsLATh7/NmkRqa2a1NaW8pj3z3W+n4wzr8+uFpKhG8EN8y8QdNSRERERIawYZ+M19pr+euGv1JSUwJ0vvxgQ1MDT6x5gsr6SgCum3Ed0f7RRzzW7hhjeOjbh6i113Li6BOZnzDf2SGJiIiISB8N22S8oq6CZ9KeodZeC3SehBtj+OfOf7IhbwMA5088n/Hh4494rD2pb6znD9/8AYBrpl9DXECckyMSERERkf4w7JJxYwxvbn6T3SW7AThn/DlMipzUod32ou28veVtAObFz+OkMScd0Th7q7immCfWPAHA3Qvuxsfdx8kRiYiIiEh/GX7JOIYYvxgWJCzodMOeyvpKHln1CNC8lOFNs27qdHfNwWBXyS7e3PQmAPctuQ8Xy8XJEYmIiIhIfxp2ybiL5cKxo47tUP7jEfMbZt5ApF/kkQ6v11ZnreaTPZ8QGxDLtdOvdXY4IiIiIjIAhl0y3pkthVt4d+u7AJw85mTmxs91ckTde3/7+6Tnp3e5E6iIiIiIDA/DOhlvOyUlwjeC62Zch6uLq5Oj6t7T656mwFbA6WNPZ3rMdGeHIyIiIiIDaFgm48YYlm1Zxs7inQDcOOtGInwjnBxV94wx3P/V/UDnGxGJiIiIyPAz7JLxtqukDJX1uO1Ndh74+gEAbpp1E+G+4U6OSERERESOhGGVjBdWF/L2lrcJ8Q7hxlk34uYy+C+vqr6KP636E6Ct7UVERESONoM/Wz0E7q7uXD/zeqL8opwdSq/kVObw/PrnAfjN4t8MiV8eRERERKT/DKvsL9greMgk4t/nfc8HOz7A292bu+ffjWVZzg5JRERERI6wYZWMDxUHly6cEDGB8yac5+xwRERERMRJlIwfQQ7j4IGvH6DJ0cSpyacyM3ams0MSERERESdSMn6EVNRV8OfVfwbguhnXEe0f7eSIRERERMTZlIwfAen56by//X0A7l10Lx6uHk6OSEREREQGAyXjA8gYw1PrnqKouoixYWO5aNJFzg5JRERERAYRJeMDpLimmCfWPAHAJamXkBSa5OSIRERERGSwUTI+AD7L+IyVmSsBuGfhPXi6eTo5IhEREREZjJSM96O6xjoe/OZBABYkLOCE0Sc4OSIRERERGcyUjPeTrYVb+dvWvwHw89k/J9Qn1MkRiYiIiMhgp2S8j9o+pJkQmMCVU6/UbpoiIiIi0itKxvugpKaEx9c8DsDFqReTHJrs5IhEREREZChRMn6YqhuqWxNxrR0uIiIiIofDMsY4O4Z+Y1lWEXCgnw8bBhT38zGPJuq/vlMf9o36r2/Uf32j/usb9V/fqQ/7prv+SzTGhPf1BMMqGR8IlmWlGWNmODuOoUr913fqw75R//WN+q9v1H99o/7rO/Vh3xyJ/nMZyIOLiIiIiEjXlIyLiIiIiDiJkvGePe/sAIY49V/fqQ/7Rv3XN+q/vlH/9Y36r+/Uh30z4P2nOeMiIiIiIk6ikXERERERESdRMi4iIiIi4iRHbTJuWda5lmVttSzLYVlWl0vWWJb1kmVZhZZlbflR+WTLslZblrXZsqx/WZYV0FJ+gmVZ61vK11uWdexAX4szDFT/tdT9yrKsPZZl7bQs66SBvA5n6Yf+m2JZ1neWZaVblpVmWdaslnJ3y7JebenX7ZZl/Wqgr8UZBqr/WupSW/5tbm3pR6+BvBZnGcg+bKlPsCzLZlnWHQN1Dc40gN/Duoe0b3c438O6h/zQrqv+e6el79Ity9pvWVZ6S7nuIe3bHVL/tdQd+j3EGHNUfgEpwFjgK2BGN+0WAdOALT8qXwcsbnl9JfD7ltdTgZiW1xOBHGdf6xDrv/HARsATGAlkAK7Ovt5B2H+fAj9peb0U+Krl9UXA2y2vfYD9wAhnX+8Q6j83YBMwueV96HD89zeQfdim/j3gXeAOZ1/rUOo/3UP63H+6h/Si/37U5hHgty2vdQ/pW/8d1j3kqB0ZN8ZsN8bs7EW7r4HSTqrGAl+3vP4MOLul/ffGmNyW8q2Al2VZnv0Q8qAyUP0HnEHzD4J6Y8w+YA8wq5PPD2n90H8GOPi/CYFAbptyX8uy3ABvoAGo7HvEg8sA9t+JwCZjzMaWz5cYY5r6IeRBZwD7EMuyzgT20vwzcFgaqP7TPaRDu0P996d7SPt2XfUfAJZlWcB5wLKDH0H3kLbtDrX/Duse4tarqKUzW4DTgQ+Bc4H4TtqcDXxvjKk/koENEV31XyzwXZt22S1l0t4twHLLsv5E83SzeS3lf6f5ZpRH86jGrcaYLn+QHMVuofP+SwaMZVnLgXCab+p/dE6Ig94tdNKHlmX5AncDJwDDcopKP7mFzv8NtqV7SNduofP+0z3k0CwECowxu1ve6x5yaH7cf4d1DxnWybhlWf8FojqputcY82EfD38l8LhlWb8F/knzb49tzz0BeIjm35KGJCf1n9VJ2yG5/uYA99/1NP+QfM+yrPOAF4HjaR4BagJigGDgG8uy/muM2dvH8x1xTuo/N2ABMBOoAT63LGu9MebzPp7PKZzUh78DHjXG2JoHjYYuJ/XfwXPrHtK9rvpP95BDcyE/jOqC7iGH6sf9d1j3kGGdjBtjju+51WEfewctPyQty0oGTjlYZ1lWHPA+cJkxJmOgYhhoTuq/bNr/L0Mcbf77eygZyP4DLgd+0fL6XeCFltcXAZ8YY+xAoWVZ3wIzaJ4yMKQ4qf+ygRXGmGIAy7I+pnm+4JBMxp3Uh7OBcyzL+iMQBDgsy6ozxjw5gLEMCCf1n+4hvdPd97DuIb3QMhXlLGB6m2LdQ3qpi/47rHvIUTtnvK8sy4po+dMF+DXwbMv7IOAj4FfGmG+dFuAg11X/0TxKfoFlWZ6WZY0EkoC1zolyUMsFFre8PhY4+F9kmcCxVjNfYA6wwwnxDXZd9d9yINWyLJ+WH7SLgW1OiG8o6LQPjTELjTEjjDEjgL8AfxiKifgR0Gn/6R7Sa119D+se0nvHAzuMMdltynQP6b3O+u/w7iE9PeE5XL+A/6H5N5h6oABY3lIeA3zcpt0ymudO2VvaX9VS/gtgV8vX//HDbqa/BqqB9DZfEc6+3qHSfy1199L8BPxOWp6WH25f/dB/C4D1NK8asAaY3lLuR/Mo0daWHwB3Ovtah1L/tdRd0tJ/W4A/Ovtah2Iftvns/Qzf1VQG6ntY95C+fw/rHtJD/7XUvQJc96Pj6h7Sh/5rKT/ke8jBBFJERERERI4wTVMREREREXESJeMiIiIiIk6iZFxERERExEmUjIuIiIiIOImScRERERE5aliW9ZJlWYWWZW3pZfvzLMvaZlnWVsuy3ur3eLSaioiIiIgcLSzLWgTYgNeMMRN7aJsE/A041hhTZllWhDGmsD/j0ci4iIiIiBw1jDFfA6VtyyzLGm1Z1ieWZa23LOsby7LGtVRdAzxljClr+Wy/JuKgZFxERERE5HngZmPMdOAO4OmW8mQg2bKsby3L+s6yrJP7+8Ru/X1AEREREZGhwrIsP2Ae8K5lWQeLPVv+dAOSgCVAHPCNZVkTjTHl/XV+JeMiIiIicjRzAcqNMVM6qcsGvjPG2IF9lmXtpDk5X9efJxcREREROSoZYyppTrTPBbCaTW6p/gA4pqU8jOZpK3v78/xKxkVERETkqGFZ1jJgNTDWsqxsy7KuAi4GrrIsayOwFTijpflyoMSyrG3Al8CdxpiSfo1HSxuKiIiIiDiHRsZFRERERJxEybiIiIiIiJMoGRcRERERcRIl4yIiIiIiTqJkXERERETESZSMi4iIiIg4iZJxEREREREn+f91VZoU7k/P2gAAAABJRU5ErkJggg==\n"
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "source": [
    "fig = plt.figure(1,figsize=(12,12))\n",
    "ax = fig.add_subplot(111)\n",
    "pp = PolygonPatch(gz_poly[1],alpha=0.5,fc='lawngreen',ec='green',zorder=1)\n",
    "ax.add_patch(pp)\n",
    "\n",
    "x0,y0 = -1.18163e6,-1.16854e6\n",
    "ax.scatter(x0,y0,s=50,color='black',alpha=0.5,zorder=3)\n",
    "p0 = Point(x0,y0).buffer(1e3)\n",
    "tpp = PolygonPatch(p0,alpha=0.5,fc='skyblue',ec='blue',zorder=2)\n",
    "ax.add_patch(tpp)\n",
    "\n",
    "int_poly = gz_poly[1].intersection(p0)\n",
    "pp = PolygonPatch(int_poly,alpha=0.8,fc='purple',ec='violet',zorder=4)\n",
    "ax.add_patch(pp)\n",
    "\n",
    "bb = int_poly.minimum_rotated_rectangle\n",
    "pp = PolygonPatch(bb,alpha=0.9,fc=None,ec='blue',fill=False,linewidth=1.5,zorder=5)\n",
    "ax.add_patch(pp)\n",
    "\n",
    "x,y = gz_poly[1].exterior.coords.xy\n",
    "ax.set_xlim([np.min(x),np.max(x)])\n",
    "ax.set_ylim([np.min(y),np.max(y)])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "[1999.613739483217, 1399.4155234524128]"
      ]
     },
     "metadata": {},
     "execution_count": 40
    }
   ],
   "source": [
    "x, y = bb.exterior.coords.xy\n",
    "el = [Point(x[0], y[0]).distance(Point(x[1], y[1])), Point(x[1], y[1]).distance(Point(x[2], y[2]))]\n",
    "el"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "<shapely.geometry.polygon.Polygon object at 0x7f8cfcc301d0>"
      ],
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     },
     "metadata": {},
     "execution_count": 38
    }
   ],
   "source": [
    "gz_poly[1].buffer(-10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "area:  73697762.17590474\nLength:  117256.65723412731\nWidth:  628.5166566598588\n"
     ]
    }
   ],
   "source": [
    "print('area: ',out_geo[0].area)\n",
    "print('Length: ',out_geo[0].length)\n",
    "print('Width: ',out_geo[0].area/out_geo[0].length)"
   ]
  },
  {
   "source": [
    "# Approach 2: velocity-based intersection width\n",
    "\n",
    "Use the velocity vector at a given coordinate to get the downstream direction, make a line segment, and get the intersection point of the line with the GL MultiLines."
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [],
   "source": [
    "#-- read velocity file\n",
    "vel_file = os.path.join(base_dir,'data.dir','basin.dir','ANT_velocity.dir','antarctica_ice_velocity_450m_v2.nc')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [],
   "source": [
    "vel_fid = nc.Dataset(vel_file,'r')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [],
   "source": [
    "x = vel_fid['x'][:]\n",
    "y = vel_fid['y'][:]\n",
    "vx = vel_fid['VX'][:]\n",
    "vy = vel_fid['VY'][:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "#-- also read lat and lon\n",
    "vel_lat = vel_fid['lat'][:]\n",
    "vel_lon = vel_fid['lon'][:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [],
   "source": [
    "vel_fid.close()"
   ]
  },
  {
   "source": [
    "For a given coordinate, get the flow angle and then the intersecting line"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "ii = np.argmin(np.abs(x - (-1512947)))\n",
    "jj = np.argmin(np.abs(y - (-799396)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "Angle: -23.4\n"
     ]
    }
   ],
   "source": [
    "ang = np.arctan(vy[jj,ii]/vx[jj,ii])\n",
    "print(\"Angle: {0:.1f}\".format(np.degrees(ang)))"
   ]
  },
  {
   "source": [
    "Now constuct a line of a given length, centered at the chosen coordinates, with the angle above"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "(5505.3040981292725, -2385.7128024101257)"
      ]
     },
     "metadata": {},
     "execution_count": 48
    }
   ],
   "source": [
    "d = 6000\n",
    "dx,dy = d*np.cos(ang),d*np.sin(ang)\n",
    "dx,dy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "<shapely.geometry.linestring.LineString object at 0x7f8d177cf4d0>"
      ],
      "image/svg+xml": "<svg xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\" width=\"300\" height=\"300\" viewBox=\"-1518945.7284259796 -802376.1371302605 11891.456851959229 5652.274260520935\" preserveAspectRatio=\"xMinYMin meet\"><g transform=\"matrix(1,0,0,-1,0,-1599100.0)\"><polyline fill=\"none\" stroke=\"#66cc99\" stroke-width=\"79.27637901306153\" points=\"-1518505.3040981293,-797164.2871975899 -1513000.0,-799550.0 -1507494.6959018707,-801935.7128024101\" opacity=\"0.8\" /></g></svg>"
     },
     "metadata": {},
     "execution_count": 49
    }
   ],
   "source": [
    "transect = LineString([[x[ii]-dx,y[jj]-dy],[x[ii],y[jj]],[x[ii]+dx,y[jj]+dy]])\n",
    "transect"
   ]
  },
  {
   "source": [
    "Now get the intersection of the transect with the MultiLine representing GLs"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "pts_ll = transect.intersection(gz_poly)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "<shapely.geometry.multilinestring.MultiLineString object at 0x7f8d177cf690>"
      ],
      "image/svg+xml": "<svg xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\" width=\"300\" height=\"300\" viewBox=\"-1513889.433360011 -799792.1660040272 1381.3595599106047 656.5909612429095\" preserveAspectRatio=\"xMinYMin meet\"><g transform=\"matrix(1,0,0,-1,0,-1598927.7410468115)\"><g><polyline fill=\"none\" stroke=\"#66cc99\" stroke-width=\"9.209063732737365\" points=\"-1513838.271894829,-799186.7365079662 -1513000.0,-799550.0 -1512770.087015214,-799649.6323439119\" opacity=\"0.8\" /><polyline fill=\"none\" stroke=\"#66cc99\" stroke-width=\"9.209063732737365\" points=\"-1512559.4980417446,-799740.8906651775 -1512559.2352652824,-799741.0045388454\" opacity=\"0.8\" /></g></g></svg>"
     },
     "metadata": {},
     "execution_count": 62
    }
   ],
   "source": [
    "pts_ll"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "(array('d', [-1513838.271894829, -1513000.0, -1512770.087015214]), array('d', [-799186.7365079662, -799550.0, -799649.6323439119]))"
      ]
     },
     "metadata": {},
     "execution_count": 63
    }
   ],
   "source": [
    "pts_ll[0].coords.xy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "1393.657206291748"
      ]
     },
     "metadata": {},
     "execution_count": 41
    }
   ],
   "source": [
    "#-- construct a line from the intersection points to get the length\n",
    "ll_int = LineString(pts_ll)\n",
    "ll_int.length"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "<shapely.geometry.multilinestring.MultiLineString at 0x7fa559b8d2d0>"
      ],
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     },
     "metadata": {},
     "execution_count": 36
    }
   ],
   "source": [
    "pts = transect.intersection(ep)\n",
    "pts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "<shapely.geometry.multilinestring.MultiLineString at 0x7f857b93f590>"
      ],
      "image/svg+xml": "<svg xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\" width=\"100.0\" height=\"100.0\" viewBox=\"-0.08 -0.08 2.16 1.1600000000000001\" preserveAspectRatio=\"xMinYMin meet\"><g transform=\"matrix(1,0,0,-1,0,1.0)\"><g><polyline fill=\"none\" stroke=\"#66cc99\" stroke-width=\"0.0432\" points=\"0.0,0.0 0.0,1.0\" opacity=\"0.8\" /><polyline fill=\"none\" stroke=\"#66cc99\" stroke-width=\"0.0432\" points=\"2.0,0.0 2.0,1.0\" opacity=\"0.8\" /></g></g></svg>"
     },
     "metadata": {},
     "execution_count": 2
    }
   ],
   "source": [
    "l1 = LineString([[0,0],[0,1]])\n",
    "l2 = LineString([[2,0],[2,1]])\n",
    "ll = MultiLineString([l1,l2])\n",
    "ll"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "0.6"
      ]
     },
     "metadata": {},
     "execution_count": 14
    }
   ],
   "source": [
    "pt = Point(0.6,0.7)\n",
    "ll.distance(pt)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "1.1"
      ]
     },
     "metadata": {},
     "execution_count": 6
    }
   ],
   "source": [
    "l2.distance(pt)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "mid_pt1 = l1.interpolate(0.5, normalized = True)\n",
    "mid_pt2 = l2.interpolate(0.5, normalized = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "0.6324555320336759 0.6\n1.414213562373095 1.4\n"
     ]
    }
   ],
   "source": [
    "print(mid_pt1.distance(pt), l1.distance(pt))\n",
    "print(mid_pt2.distance(pt), l2.distance(pt))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ]
}