{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "004d166b",
   "metadata": {},
   "source": [
    "# `osbng` Overview\n",
    "\n",
    "* The `osbng` Python package supports geospatial grid indexing and interaction with Ordnance Survey's British National Grid (BNG) index system.\n",
    "* `osbng` relies on [`Shapely`](https://github.com/shapely/shapely) for geospatial operations, with [`GeoPandas`](https://github.com/geopandas/geopandas) an optional dependency for `GeoDataFrame` indexing. \n",
    "* The `osbng` package is structured into modules supporting different interactions with the BNG index system (e.g. indexing, hierarchy, traversal).\n",
    "* This notebook provides an overview of the package functionality, including example usage."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "5b071df2",
   "metadata": {},
   "outputs": [],
   "source": [
    "import geopandas as gpd\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.lines import Line2D\n",
    "from shapely import wkt\n",
    "from shapely.geometry import Point\n",
    "\n",
    "from osbng.bng_reference import BNGReference\n",
    "from osbng.grids import BNG_BOUNDS, bbox_to_bng_iterfeatures, bng_grid_100km\n",
    "from osbng.indexing import (\n",
    "    PREFIXES,\n",
    "    bng_to_bbox,\n",
    "    geom_to_bng,\n",
    "    geom_to_bng_intersection,\n",
    "    xy_to_bng,\n",
    ")\n",
    "from osbng.resolution import BNG_RESOLUTIONS"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cd6bc3f9",
   "metadata": {},
   "source": [
    "## BNG Index System\n",
    "\n",
    "* The OS BNG index system, also known as the OS National Grid, is a rectangular \n",
    "Cartesian 700 x 1300km grid system based upon the transverse Mercator projection. In the BNG, locations \n",
    "are specified using coordinates, eastings (x) and northings (y), measured in meters from a defined \n",
    "origin point (0, 0) southwest of the Isles of Scilly off the coast of Cornwall, England. Values increase \n",
    "to the northeast, covering all of mainland GB and surrounding islands.\n",
    "* The BNG is structured using a hierarchical system of grid squares at various resolutions. At its highest level, the grid divides GB into 100 km by 100 km squares, each identified by a two-letter code. Successive levels of resolution further subdivide the grid squares into finer detail, down to individual 1-meter squares."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "a1b11ac9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0, 0, 700000, 1300000)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "BNG_BOUNDS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "368668a2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([['SV', 'SW', 'SX', 'SY', 'SZ', 'TV', 'TW'],\n",
       "       ['SQ', 'SR', 'SS', 'ST', 'SU', 'TQ', 'TR'],\n",
       "       ['SL', 'SM', 'SN', 'SO', 'SP', 'TL', 'TM'],\n",
       "       ['SF', 'SG', 'SH', 'SJ', 'SK', 'TF', 'TG'],\n",
       "       ['SA', 'SB', 'SC', 'SD', 'SE', 'TA', 'TB'],\n",
       "       ['NV', 'NW', 'NX', 'NY', 'NZ', 'OV', 'OW'],\n",
       "       ['NQ', 'NR', 'NS', 'NT', 'NU', 'OQ', 'OR'],\n",
       "       ['NL', 'NM', 'NN', 'NO', 'NP', 'OL', 'OM'],\n",
       "       ['NF', 'NG', 'NH', 'NJ', 'NK', 'OF', 'OG'],\n",
       "       ['NA', 'NB', 'NC', 'ND', 'NE', 'OA', 'OB'],\n",
       "       ['HV', 'HW', 'HX', 'HY', 'HZ', 'JV', 'JW'],\n",
       "       ['HQ', 'HR', 'HS', 'HT', 'HU', 'JQ', 'JR'],\n",
       "       ['HL', 'HM', 'HN', 'HO', 'HP', 'JL', 'JM']], dtype='<U2')"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "PREFIXES"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c4dcfc3b",
   "metadata": {},
   "source": [
    "## Resolutions\n",
    "\n",
    "* `osbng` supports the 'standard' BNG metre-based resolutions, which represent powers of ten from 1m to 100km `(1m, 10m, 100m, 1km, 10km, 100km)`. \n",
    "* It also supports the 'intermediate' quadtree resolutions `(5m, 50m, 500m, 5km, 50km)`, identified by an ordinal `(NE, SE, SW, NW)` BNG reference direction suffix.\n",
    "* The `resolution` function arguments can be expressed as a metre-based integer or as a label."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "37b2c3df",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{100000: {'label': '100km', 'quadtree': False},\n",
       " 50000: {'label': '50km', 'quadtree': True},\n",
       " 10000: {'label': '10km', 'quadtree': False},\n",
       " 5000: {'label': '5km', 'quadtree': True},\n",
       " 1000: {'label': '1km', 'quadtree': False},\n",
       " 500: {'label': '500m', 'quadtree': True},\n",
       " 100: {'label': '100m', 'quadtree': False},\n",
       " 50: {'label': '50m', 'quadtree': True},\n",
       " 10: {'label': '10m', 'quadtree': False},\n",
       " 5: {'label': '5m', 'quadtree': True},\n",
       " 1: {'label': '1m', 'quadtree': False}}"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "BNG_RESOLUTIONS"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6054d9ac",
   "metadata": {},
   "source": [
    "## `BNGReference`\n",
    "\n",
    "* The BNG index system uses BNG references, also known more simply as grid or tile references, to identify and index locations across Great Britain (GB) into grid squares at various resolutions. \n",
    "* The `osbng.bng_reference` module implements a custom `BNGReference` object. This object validates and encapsulates a BNG reference, providing properties and methods to access and manipulate the reference.\n",
    "* All functions accepteding or returning BNG references enforce the use of this class.\n",
    "* These functions are available both as instance methods of the `BNGReference` object and as standalone functions, providing users with the flexibility to either:\n",
    "    * Create a `BNGReference` object and pass it to a function.\n",
    "    * Create a `BNGReference` object and use one of its instance methods."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "6bf8e18e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "BNGReference(bng_ref_formatted=SU 372 155, resolution_label=100m)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Convert a BNG reference string into a BNGReference object\n",
    "bng_ref = BNGReference(bng_ref_string=\"SU 372 155\")\n",
    "\n",
    "bng_ref"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "caa6c094",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('SU372155', 'SU 372 155')"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# The BNG reference string, as a compact string and formatted string\n",
    "bng_ref.bng_ref_compact, bng_ref.bng_ref_formatted"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "bccdfce0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(100, '100m')"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# The BNG resolution expressed in metres and as a descriptive label\n",
    "bng_ref.resolution_metres, bng_ref.resolution_label"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "1f352ea9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'type': 'Feature',\n",
       " 'properties': {'bng_ref': 'SU372155'},\n",
       " 'geometry': {'type': 'Polygon',\n",
       "  'coordinates': (((437300.0, 115500.0),\n",
       "    (437300.0, 115600.0),\n",
       "    (437200.0, 115600.0),\n",
       "    (437200.0, 115500.0),\n",
       "    (437300.0, 115500.0)),)}}"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# The BNGReference object can be converted to a GeoJSON-like Feature object\n",
    "# Uses the __geo_interface__ protocol\n",
    "# https://gist.github.com/sgillies/2217756\n",
    "bng_ref.__geo_interface__"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "869973a2",
   "metadata": {},
   "source": [
    "## Indexing\n",
    "\n",
    "* The `osbng.indexing` module provides the ability to index and work with coordinates and geometries against the BNG index system. This includes:\n",
    "\n",
    "    * Encoding easting and northing coordinates into `BNGReference` objects at a specified resolution.\n",
    "    * Decoding `BNGReference` objects back into coordinates, bounding boxes and grid squares as `Shapely` geometries.\n",
    "    * Indexing bounding boxes and `Shapely` geometries into grid squares at a specified resolution for spatial analysis."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "ddaac874",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "BNGReference(bng_ref_formatted=SU 37 15, resolution_label=1km)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Easting and northing coordinates\n",
    "x, y = 437293, 115543\n",
    "\n",
    "# Convert easting and northing to BNGReference at 1km resolution\n",
    "bng_ref = xy_to_bng(easting=x, northing=y, resolution=\"1km\")\n",
    "\n",
    "bng_ref"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "03e1beb9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(437000, 115000)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Decode BNGReference back into coordinates\n",
    "# Default 'position' is 'lower-left\n",
    "bng_ref.bng_to_xy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "13f83ed5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(437500, 115500)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Decode BNGReference back into coordinates\n",
    "# Centroid of the grid square\n",
    "# position can be one of:\n",
    "# 'lower-left', 'upper-left', 'lower-right', 'upper-right', 'centre'\n",
    "bng_ref.bng_to_xy(position=\"centre\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "308c1129",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(437000, 115000, 438000, 116000)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Return the grid square bounding box coordinates for the BNGReference object\n",
    "# Instance method\n",
    "bng_ref.bng_to_bbox()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "e15ba505",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(437000, 115000, 438000, 116000)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Return the grid square bounding box coordinates for the BNGReference object\n",
    "# Function that takes a BNGReference object\n",
    "bng_to_bbox(bng_ref)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "2a83f71a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/svg+xml": [
       "<svg xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\" width=\"300\" height=\"300\" viewBox=\"436960.0 114960.0 1080.0 1080.0\" preserveAspectRatio=\"xMinYMin meet\"><g transform=\"matrix(1,0,0,-1,0,231000.0)\"><path fill-rule=\"evenodd\" fill=\"#66cc99\" stroke=\"#555555\" stroke-width=\"7.2\" opacity=\"0.6\" d=\"M 438000.0,115000.0 L 438000.0,116000.0 L 437000.0,116000.0 L 437000.0,115000.0 L 438000.0,115000.0 z\" /></g></svg>"
      ],
      "text/plain": [
       "<POLYGON ((438000 115000, 438000 116000, 437000 116000, 437000 115000, 43800...>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Return the grid square as a Shapely geometry object for the BNGReference object\n",
    "bng_ref.bng_to_grid_geom()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b3f90919",
   "metadata": {},
   "source": [
    "### Indexing Shapely Geometries\n",
    "\n",
    "The `geom_to_bng` and `geom_to_bng_intersection` functions enable the indexing of geometries, represented using `Shapely` Geometry objects, into grid squares at a specified resolution. Both functions accept `Shapely` Geometry objects of the following types: `Point`, `LineString`, `Polygon`, `MultiPoint`, `MultiLineString`, `MultiPolygon`, and `GeometryCollection`. The geometry coordinates must be encoded in the [British National Grid (OSGB36) EPSG:27700](https://epsg.io/27700) coordinate reference system.\n",
    "\n",
    "These functions facilitate grid-based spatial analysis, enabling applications such as statistical aggregation, data visualisation, and data interoperability. The two functions differ in their operation: \n",
    "\n",
    "* `geom_to_bng` returns the BNG grid squares intersected by the input geometry.\n",
    "* `geom_to_bng_intersection` returns the intersections (shared geometries) between the input geometry and the grid square geometries.\n",
    "\n",
    "See `examples/notebooks/osbng_indexing_polygon_examples.ipynb` for more examples and detail on the operation of the two functions."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a540f69d",
   "metadata": {},
   "source": [
    "##### Point"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "8b5b4735",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[BNGReference(bng_ref_formatted=SU 3 1 NE, resolution_label=5km)]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Point\n",
    "# Easting and northing coordinates\n",
    "x, y = 437293, 115543\n",
    "\n",
    "# Construct a Shapely Point geometry from easting and northing coordinates\n",
    "geom = Point(x, y)\n",
    "\n",
    "# Return the BNGReference object for the geometry at a 5km resolution\n",
    "geom_to_bng(geom=geom, resolution=\"5km\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "91c4655a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[BNGIndexedGeometry(bng_ref=BNGReference(bng_ref_formatted=SU 3 1 NE, resolution_label=5km), is_core=False, geom=POINT (437293 115543))]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Return the BNGIndexedGeometry object for the geometry at a 5km resolution\n",
    "# For a Point geometry, the intersection geometry is the same as the original geometry\n",
    "# The is_core property will always be False for a Point geometry\n",
    "geom_to_bng_intersection(geom=geom, resolution=\"5km\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "832852aa",
   "metadata": {},
   "source": [
    "##### LineString"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "2575041c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[BNGReference(bng_ref_formatted=SU 37 15, resolution_label=1km),\n",
       " BNGReference(bng_ref_formatted=SU 37 16, resolution_label=1km),\n",
       " BNGReference(bng_ref_formatted=SU 36 14, resolution_label=1km),\n",
       " BNGReference(bng_ref_formatted=SU 36 15, resolution_label=1km)]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# LineString\n",
    "# Create a Shapely LineString geometry from Well Known Text (WKT)\n",
    "geom = wkt.loads(\"LINESTRING (436171.8 114893.7, 437861.3 116130.0)\")\n",
    "\n",
    "# Return a list of the BNGReference object(s) intersected by the geometry\n",
    "# at a 1km resolution\n",
    "geom_to_bng(geom=geom, resolution=\"1km\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "e8af93eb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[BNGIndexedGeometry(bng_ref=BNGReference(bng_ref_formatted=SU 37 15, resolution_label=1km), is_core=False, geom=LINESTRING (437000 115499.7394554602, 437683.64490010514 116000)),\n",
       " BNGIndexedGeometry(bng_ref=BNGReference(bng_ref_formatted=SU 37 16, resolution_label=1km), is_core=False, geom=LINESTRING (437683.64490010514 116000, 437861.3 116130)),\n",
       " BNGIndexedGeometry(bng_ref=BNGReference(bng_ref_formatted=SU 36 14, resolution_label=1km), is_core=False, geom=LINESTRING (436171.8 114893.7, 436317.06720860634 115000)),\n",
       " BNGIndexedGeometry(bng_ref=BNGReference(bng_ref_formatted=SU 36 15, resolution_label=1km), is_core=False, geom=LINESTRING (436317.06720860634 115000, 437000 115499.7394554602))]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Return a list of the BNGIndexedGeometry object(s) for the geometry at a 1km resolution\n",
    "# The is_core property will always be False for a LineString geometry\n",
    "geom_to_bng_intersection(geom=geom, resolution=\"1km\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "2c79cd87",
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_aesthetics(ax: plt.Axes) -> None:\n",
    "    \"\"\"Set the aesthetics for the matplotlib axes.\n",
    "\n",
    "    Sets the axis labels, removes the figure frame,\n",
    "    rotates x-axis tick labels, and adds whitespace between labels and ticks.\n",
    "\n",
    "    Args:\n",
    "        ax (plt.Axes): The matplotlib axes to set aesthetics for.\n",
    "    \"\"\"\n",
    "    # Set axis labels\n",
    "    ax.set_xlabel(\"Easting\", fontsize=14)\n",
    "    ax.set_ylabel(\"Northing\", fontsize=14)\n",
    "\n",
    "    # Remove the figure frame but keep the ticks and tick labels\n",
    "    for spine in ax.spines.values():\n",
    "        spine.set_visible(False)\n",
    "\n",
    "    # Rotate x axis tick labels by 90 degrees anticlockwise\n",
    "    plt.xticks(rotation=90)\n",
    "\n",
    "    # Add whitespace between x and y axis labels and tick labels\n",
    "    ax.xaxis.labelpad = 20\n",
    "    ax.yaxis.labelpad = 20"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "8ff243ef",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create matplotlib figure and axis\n",
    "f, ax = plt.subplots(figsize=(10, 10))\n",
    "\n",
    "# Return a list of the BNGIndexedGeometry objects for the geometry at a 1km resolution\n",
    "bng_idx_geoms = geom_to_bng_intersection(geom=geom, resolution=\"1km\")\n",
    "\n",
    "# Extract bng_ref and geom from each BNGIndexedGeometry object\n",
    "bng_refs = [bng_idx_geom.bng_ref for bng_idx_geom in bng_idx_geoms]\n",
    "geoms = [bng_idx_geom.geom for bng_idx_geom in bng_idx_geoms]\n",
    "\n",
    "# Categorical colours\n",
    "colours = [\"#FF1F5B\", \"#009ADE\", \"#FFC61E\", \"#AF58BA\"]\n",
    "\n",
    "# Plot geometries representing the intersection between the geometry\n",
    "# and the BNG grid squares\n",
    "gpd.GeoSeries(geoms, crs=27700).plot(\n",
    "    ax=ax, color=colours, edgecolor=\"#fff\", linewidth=2\n",
    ")\n",
    "# Plot intersected BNGReference grid squares for context\n",
    "gpd.GeoSeries([bng_ref.bng_to_grid_geom() for bng_ref in bng_refs], crs=27700).plot(\n",
    "    ax=ax, color=\"none\", edgecolor=\"#00000075\", linewidth=1, linestyle=\"--\"\n",
    ")\n",
    "\n",
    "# Set the title\n",
    "ax.set_title(\n",
    "    \"Decomposition of LineString Geometry into BNG Grid Squares at a 1km Resolution\",\n",
    "    fontsize=16,\n",
    ")\n",
    "# Set the aesthetics for the matplotlib axes\n",
    "plot_aesthetics(ax)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3c6dcec2",
   "metadata": {},
   "source": [
    "##### Polygon"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "03edc2a8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[BNGReference(bng_ref_formatted=SU 36 15 NE, resolution_label=500m),\n",
       " BNGReference(bng_ref_formatted=SU 37 14 NW, resolution_label=500m),\n",
       " BNGReference(bng_ref_formatted=SU 37 15 NE, resolution_label=500m),\n",
       " BNGReference(bng_ref_formatted=SU 37 16 SE, resolution_label=500m),\n",
       " BNGReference(bng_ref_formatted=SU 38 16 SW, resolution_label=500m),\n",
       " BNGReference(bng_ref_formatted=SU 37 15 SW, resolution_label=500m),\n",
       " BNGReference(bng_ref_formatted=SU 37 15 NW, resolution_label=500m),\n",
       " BNGReference(bng_ref_formatted=SU 37 14 NE, resolution_label=500m),\n",
       " BNGReference(bng_ref_formatted=SU 38 15 SW, resolution_label=500m),\n",
       " BNGReference(bng_ref_formatted=SU 38 15 NW, resolution_label=500m),\n",
       " BNGReference(bng_ref_formatted=SU 37 16 SW, resolution_label=500m),\n",
       " BNGReference(bng_ref_formatted=SU 37 15 SE, resolution_label=500m),\n",
       " BNGReference(bng_ref_formatted=SU 38 14 NW, resolution_label=500m),\n",
       " BNGReference(bng_ref_formatted=SU 36 15 SE, resolution_label=500m)]"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Polygon\n",
    "# Create a Shapely Polygon geometry from Well Known Text (WKT)\n",
    "geom = wkt.loads(\n",
    "    (\n",
    "        \"POLYGON ((436661.45305455 115784.01571607, 437629.10896848 116112.11767069, \"\n",
    "        \"438229.486575 115953.45344189, 437990.51082297 114935.84767816, \"\n",
    "        \"436630.11197232 115085.69722758, 436661.45305455 115784.01571607))\"\n",
    "    )\n",
    ")\n",
    "\n",
    "# Return a list of the BNGReference objects intersected by the geometry\n",
    "# at a 500m resolution\n",
    "geom_to_bng(geom=geom, resolution=500)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "477620ba",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[BNGIndexedGeometry(bng_ref=BNGReference(bng_ref_formatted=SU 37 15 NE, resolution_label=500m), is_core=True, geom=POLYGON ((438000 115500, 438000 116000, 437500 116000, 437500 115500, 438000 115500))),\n",
       " BNGIndexedGeometry(bng_ref=BNGReference(bng_ref_formatted=SU 37 15 SE, resolution_label=500m), is_core=True, geom=POLYGON ((438000 115000, 438000 115500, 437500 115500, 437500 115000, 438000 115000))),\n",
       " BNGIndexedGeometry(bng_ref=BNGReference(bng_ref_formatted=SU 36 15 NE, resolution_label=500m), is_core=False, geom=POLYGON ((437000 115898.80643137876, 437000 115500, 436648.7062061439 115500, 436661.45305455 115784.01571607, 437000 115898.80643137876))),\n",
       " BNGIndexedGeometry(bng_ref=BNGReference(bng_ref_formatted=SU 37 14 NW, resolution_label=500m), is_core=False, geom=POLYGON ((437408.1083717418 115000, 437500 115000, 437500 114989.87802798908, 437408.1083717418 115000))),\n",
       " BNGIndexedGeometry(bng_ref=BNGReference(bng_ref_formatted=SU 37 16 SE, resolution_label=500m), is_core=False, geom=POLYGON ((437629.10896848 116112.11767069, 438000 116014.10079123633, 438000 116000, 437500 116000, 437500 116068.34084433317, 437629.10896848 116112.11767069))),\n",
       " BNGIndexedGeometry(bng_ref=BNGReference(bng_ref_formatted=SU 38 16 SW, resolution_label=500m), is_core=False, geom=POLYGON ((438053.3566977039 116000, 438000 116000, 438000 116014.10079123633, 438053.3566977039 116000))),\n",
       " BNGIndexedGeometry(bng_ref=BNGReference(bng_ref_formatted=SU 37 15 SW, resolution_label=500m), is_core=False, geom=POLYGON ((437000 115044.95362194022, 437000 115500, 437500 115500, 437500 115000, 437408.1083717418 115000, 437000 115044.95362194022))),\n",
       " BNGIndexedGeometry(bng_ref=BNGReference(bng_ref_formatted=SU 37 15 NW, resolution_label=500m), is_core=False, geom=POLYGON ((437298.445509846 116000, 437500 116000, 437500 115500, 437000 115500, 437000 115898.80643137876, 437298.445509846 116000))),\n",
       " BNGIndexedGeometry(bng_ref=BNGReference(bng_ref_formatted=SU 37 14 NE, resolution_label=500m), is_core=False, geom=POLYGON ((437990.51082297 114935.84767816, 437500 114989.87802798908, 437500 115000, 438000 115000, 438000 114976.25446067557, 437990.51082297 114935.84767816))),\n",
       " BNGIndexedGeometry(bng_ref=BNGReference(bng_ref_formatted=SU 38 15 SW, resolution_label=500m), is_core=False, geom=POLYGON ((438005.5764307944 115000, 438000 115000, 438000 115500, 438122.99702752626 115500, 438005.5764307944 115000))),\n",
       " BNGIndexedGeometry(bng_ref=BNGReference(bng_ref_formatted=SU 38 15 NW, resolution_label=500m), is_core=False, geom=POLYGON ((438229.486575 115953.45344189, 438122.99702752626 115500, 438000 115500, 438000 116000, 438053.3566977039 116000, 438229.486575 115953.45344189))),\n",
       " BNGIndexedGeometry(bng_ref=BNGReference(bng_ref_formatted=SU 37 16 SW, resolution_label=500m), is_core=False, geom=POLYGON ((437500 116068.34084433317, 437500 116000, 437298.445509846 116000, 437500 116068.34084433317))),\n",
       " BNGIndexedGeometry(bng_ref=BNGReference(bng_ref_formatted=SU 38 14 NW, resolution_label=500m), is_core=False, geom=POLYGON ((438000 114976.25446067557, 438000 115000, 438005.5764307944 115000, 438000 114976.25446067557))),\n",
       " BNGIndexedGeometry(bng_ref=BNGReference(bng_ref_formatted=SU 36 15 SE, resolution_label=500m), is_core=False, geom=POLYGON ((436630.11197232 115085.69722758, 436648.7062061439 115500, 437000 115500, 437000 115044.95362194022, 436630.11197232 115085.69722758)))]"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Return a list of the BNGIndexedGeometry objects for the geometry at a 500m resolution\n",
    "geom_to_bng_intersection(geom=geom, resolution=500)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "bc8b5c5a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA8sAAALWCAYAAABxzgFeAAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjUsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvWftoOwAAAAlwSFlzAAAPYQAAD2EBqD+naQAA6odJREFUeJzs3Xd8Tff/B/DXvdl7RxKJhEhIRLYRCSESs0XRUqp0KLWrWrRVSovW6NBqtVpUlcSoPWvUJkbsTcQIMbP3/fz+8Lvnm705N8nr+Xjk0Trrvs+5537OeZ/P53w+CiGEABERERERERFJlHIHQERERERERKRpmCwTERERERERFcBkmYiIiIiIiKgAJstEREREREREBTBZJiIiIiIiIiqAyTIRERERERFRAUyWiYiIiIiIiApgskxERERERERUAJNlIiIiIiIiogKYLFO1smfPHigUCrRt2/aFrlsdPHr0CIMHD0bdunWhpaUFhUKBKVOmyB2WZMqUKRoXE1FVq+nlDJWfi4sLFAoFYmNjy7XeoEGDoFAosHjx4ucSFxFRXhUtq6rbZ5ZXjU6W1V+A+k+pVMLU1BROTk6IiIjAZ599hvPnz8sdJlWRKVOm1OpErHv37li4cCFSU1MRGBiI4OBg1KtXr9T11Ddkef90dHRgb2+Pbt26YcuWLS8g+totOzsbixcvxiuvvAJnZ2cYGhrC0NAQzs7O6NatG3766Sc8ePBA7jA1yp49ezBlyhTs2bNH7lCeOznKNvXDrYJ/enp6cHJyQp8+fXDw4MEi11U/MFAoFLC3t0d6enqRy92+fVtariQXL17EuHHj4O/vD2tra+jo6MDS0hKBgYEYMWJEpc+B1NRUzJs3D507d0bdunWhr68PY2NjuLq6onfv3li0aBGSkpIq9RkvWmRkJDp37ow6depAV1cXVlZW8PT0xKuvvoqffvoJ8fHxcodIBSxevBhTpkzRqKSh4H10wb+WLVuWuP5ff/2FVq1awczMDKampmjVqhWWLVtW6udu3rwZ4eHhsLS0hJGREfz9/TFv3jyoVKqq2rVKK+p4GBoawt3dHUOGDMGlS5fkDlF2a9euxZQpUxATEyN3KJUjajBnZ2cBQLi5uYng4GARHBwsAgICpOnqv169eomHDx/KHS6VwZEjR0SjRo3EgAEDCs1Tf58VWbe6O3XqlAAg6tatK54+fVqudQcOHCgACFtb23y/ExMTE+mYTpw4sdIxTp48WQAQkydPrvS2apLjx4+LBg0aSMfa0tJS+Pj4CH9/f1GnTh1puqGhofjjjz/kDldjaOr59DzKmdLKtudBfXxNTU2lciE4OFg0adJEGBgYCABCoVCIX375pdC6u3fvzneNnTNnTpGfcevWrRL3LScnR4wZM0YolUoBQCiVSuHm5iaaN28uGjVqJPT09KT1mzVrJpKTk8u9n9u2bRO2trbSdurUqSP8/f2Fj4+PsLKyyve73LJlS7m3L4QQYWFholGjRuL27dvlWk9dNi9atKjM62RlZYkePXpIcZuZmQlvb2/h5+cnzMzMpOnz5s0r517Q8xYaGioAiN27d8sdikR9vxwYGJivHFD/vffee8WuO2TIEOl8a9y4sfDw8JD+PXz48GLXmzFjhrRcgwYNhLe3t1QGdOvWTeTm5j6PXS03dYxeXl7S8WjUqJHQ0dERAISBgYH4999/5Q6zXNTf940bN6pke2UpwypaPr5ItSJZLupLevDggfjuu++EtbW19EMub5JBmkWOG0pNERkZKQCI1157rdzrqguzgQMH5puemZkpxo0bJx3XgwcPVipGTU1u5HTs2DFhaGgoAIiIiAhx+PBhoVKp8i1z4cIF8dFHHwljY2MxZMgQmSLVPLXpfJIzWQ4NDS0078mTJ+L111+XbggLPmxWJ8taWlrSg7jU1NRC2yktWe7Tp4+UsM+dO1c8fvw43/yUlBSxevVq0bJlSwFAxMfHl2sf169fL8XYt29fcfbs2XzzVSqVOHHihHjvvfeErq6umDFjRrm2X1kVSZanT58ufS/Lli0TOTk50jyVSiWio6PFqFGjxJIlS55DxFQZmpwslzd5Wr58uQAgjIyMxM6dO6Xp//77rzAyMhIAxMqVKwutd/DgQaFQKIRSqRR///23ND0mJkZ6eDxr1qwK709VUpddBb+v27dvizZt2ggAwtnZWWRnZ8sTYAXIkSxXBzW6GXZJrK2tMXr0aBw7dgz29va4ePEixowZI3dYRBWibuZoYGBQZdvU1dXFN998A19fXwDAihUrqmzbBGRmZuLVV19FWloa3nzzTWzduhUtWrQo1CS1cePG+Oabb3D27FkEBQXJFC3R/5ibm+PXX3+FUqlEeno6Dhw4UORyLi4uCAoKQkJCAn766adyfcZvv/2GyMhIGBkZYe/evfjggw9gYWGRbxkjIyP07NkThw4dwo8//ggdHZ0ybz8hIQEDBw5Ebm4uPvvsMyxfvhxNmjTJt4xCoYCfnx8WLFiA6OhoNGrUqFz7IIclS5YAAD799FP069cPWlpa0jyFQoHAwEB8//33ePPNN+UKkWqBL7/8EsCz8zAsLEya3r59e3zyyScAgGnTphW5nhAC7777Ll5//XVpuo+PD+bOnQsAmDlzJrKzs59n+JVSt25d/PHHHwCAmzdv4vjx4zJHRJUmd7b+PJVUs5zXP//8IwAIbW1tERcXV2i+SqUSy5cvF+Hh4cLS0lLo6uqK+vXri5EjR5b4JPvRo0fi888/F76+vsLExEQYGRmJxo0biyFDhogTJ04UWv7hw4fio48+Eu7u7kJfX1+Ym5uL0NBQ8ddffxWqbRJCiEWLFkk1gmlpaWLChAmifv36Ql9fX7i7u4sffvgh37ZHjRol6tWrJ/T09ISnp2exxyXv080jR46ILl26CAsLC2FoaCiCgoLEP//8U+w+q1QqsXTpUtGmTRthZmYm9PX1RaNGjcTHH38sHj16VOQ6sbGx4r333hP169cXurq6wtjYWNSvX1/06NFDLF++PN+y6hqLvLUd6hqQ4v7UT8iKWjevmzdviqFDhwoXFxehq6srrKysRKdOncTmzZuLXD5vzdbTp0/F6NGjhZOTk9DV1RWurq5i6tSpFX6ieODAAfHKK68IW1tboaOjI+rWrSsGDBggzp8/X+TxKO6vLIqrWVYbMWKEACA6d+6cb/rZs2fFG2+8IerWrSt0dHSEra2t6Nmzpzh06FCR2ymqJnD8+PECgBgxYkSx8UVHRwsAws7OLl8tiRDPnlK3a9dOmJiYCDMzMxEWFiZ27twpbty4IT3VLYomfNe//fab1OwzJSWlXOsWlJqaKmbOnCk1nzcwMBA+Pj7im2++ERkZGcWut3HjRtGxY0dhZWUldHV1hYuLi3j//feLLAeFyP/Uec+ePaJ9+/bCzMxMWFhYiB49eojLly9Ly65bt06EhIQIExMTYW5uLvr27Svu3LlTbCyPHj0Sn3zyiWjSpIkwNDQUxsbGokWLFuLXX38t1OyupHM+73mcN95du3aJTp06SU1rd+/eLVq0aCEAiFWrVhUb16xZswQA0bt372KXyau4cqbgObl06VIREBAgDAwMhIWFhejdu7e4du1avnXKWraplbXcKIuSapbV1C2zCtYQqY+Bq6ur2L59uwAgrK2tCzWTLq5mOScnR/ruZs+eXe7Yy+LTTz8VAISPj0+Fm3Xm/a6zs7PF119/Lby8vISBgUG+sqek2pqUlBQxYcIE4eLiIvT09ISzs7MYO3asSE5OrlCtjLoJ6MaNGyu0T2vWrBFBQUHC0NBQWFpaiq5du4ro6Ohiz+u89yFFKem6u337djF8+HDh7e0tLCwshJ6enmjQoIEYOnSouHnzZpHby3tMrl+/LgYOHCgcHByElpZWvmtLRe7b9u3bJ3r06CHq1KkjtLW1hYWFhWjcuLF45513ir2uFSUtLU38/fffok+fPsLd3V0YGRkJIyMj4ePjI6ZNm1aovC/tOl7W7//MmTPi888/Fy1bthR2dnZCR0dH2NnZiVdeeUUcOHCgzPHnVZGaxosXL0qx37t3r9D8+Ph4af6lS5ek6YmJiUJXV1cAEEeOHCm0XlZWljA1NRUAxLZt24qNs6qvTcVR70NxLQEsLCwEALFixYpC817E+VmR+/Hivu/SzoOCrSLU17vi/vL+VkvadlZWlvjhhx9Es2bNhImJiTA0NBTe3t7iyy+/LLK1UkWus2XBZFkIkZubKxwcHAQAsXDhwnzzsrKyxKuvvip9wQ4ODsLHx0dqOmlvb5/vx64WExMjbVOpVApPT0/h6+sr/dALXliuXLkinJycBAChq6sr/P39873H+OabbxZKmNUXqddff10EBQUJLS0t4e3tLVxcXKT1vvjiC3H//n3h5uYmdHV1hZ+fnxQXgCLfgVSf9FOnTpWS18DAQGFvby+tV9Q7aCqVSvTr109apkGDBsLf318q/JydnQudpDdu3JBuuAwNDUXTpk2Fr6+vsLS0lG5k8irqwvv777+L4OBg6XMLvlOjLnhKumgfPnxYmJubC+BZs6GAgADh6OgobXPSpEmF1lHfTI4ZM0Z4eHgIbW1t4evrm+/4v/vuu4XWK838+fOFQqEQwLPmi4GBgVJs+vr6+W6CTpw4IYKDg4Wbm5u0fN59L4vSkuXhw4cXSpbXrVsnvS9obm4uAgMDhY2NjXS+//rrr4W2U1SyfOnSJQFAWFlZiczMzCI/X52sjxs3Lt/0JUuWSMfJ2tpaNGvWTFhZWQmlUiklOEUly5ryXUdERAgA4qOPPirXegXdvn1beHp6CuDZA7+GDRtKMQIQISEhIi0trdB6EyZMkGJ3dHQUAQEBUrlmYWEhoqOjC62jLlPnzp0rtLS0hK2trfD395ea1dnb24v4+Hgxd+5cabs+Pj7SudKoUSORnp5eaLtnz54VdevWlco/T09P4erqKn2/vXv3zlf+BQcHS+Wlk5NTvnP+q6++KhTv9OnThVKpFBYWFqJZs2bC0dFR7N69WyxYsEAAEC+//HKxx9fLy6tcyUdZkmX1sXd2ds53fOzt7cWDBw+kdcpatglRvnKjLEpLlmNjY6W4zpw5U+QxcHV1FUIIERISIn0PeRWXLB84cEAAEDo6Os/t9Sh1mfnTTz9VeBvq/WzTpo3o2rWrtM8BAQGiSZMm0nLF3QympKSI5s2bC+DZ+99eXl7C09NTKBQK4e/vL/r27VvuZFn9MOjzzz8v9/58/fXX0vdhb28vAgIChLGxsdDT0xPTpk2r8mRZS0tLKBQKYWtrK3x9fYWXl5dUllhZWYlz584VWkd9vZowYYIwNzcXenp6wt/fXzRu3FhMmTJFCFGx+7a1a9dK78VaWVlJ21THM3r06DIfx3379knlsaOjowgMDBRubm5Smezv75+vTFZfx9X3h3nfgQ0ODi72IW5B7du3l67JHh4ewt/fX7q/0tLSEsuWLSvzPqipz923335bdOrUSYSHh4u3335brFixotDDa7XFixcLAKJhw4bFbtfV1VUAEH/++ac0bc+ePVJ5VdzDZ/U+Tp06tcg4q/raVBL1+VVUsqxSqaS+HdavX59v3os4PytyP573OFY2WY6PjxfBwcFSfxB5+44KDg4Wv//+e6nbTktLE2FhYdI+eHh45Ht/3dfXt9ArQBW5zpYFk+X/16tXLwGg0DuB6oPt5+cnTp48KU1PS0sTw4YNE8Czjg/ySkxMFPXq1RMARKdOncStW7fyzd+7d6/466+/pH+rVCoRGBgoXVDyPonbsmWL9GOYP39+vu2oL1I6OjqiadOm4vr169I89fsiBgYGokOHDqJdu3bi/v370vyvvvpKOmkKFnjqk15bW1v07dtXegqqUqnEDz/8IM2LiYnJt968efMEAGFiYiK2b98uTVf/aACIFi1a5FtHnQgNHDiwUK3DhQsXxIIFC/JNK+nCW9RNV1nWTU1Nlb6v1157TSQlJUnzFi9eLL3TVvCCpb6Z1NHREW3atMn3ZDLvu3AXLlwoNqaCTp48KV1Qv/nmG6nGIyMjQzrfzMzMxN27d/OtV9oNS0lKSpZVKpXw9fUVAMTIkSOFEELcuXNHuqiPHj1aSnJzc3Ol80pHR0ecOnUq37aKe8dUfW6sWbOm0OdnZWVJN3953ye8efOmdGH57LPPpHM4OztbTJgwQapdKZgsa9J3bWxsLACIdevWlXmdgnJzc0WrVq0E8Oydy7xlx61bt0Tr1q0FUPhBw4YNG6Tfcd6yKDExUbzyyisCgHBxcSmUZKvLVB0dHTFnzhzp/Hzy5In03mjXrl2FoaFhvhuzuLg46eFfwXIsJSVFunEaNWqUSExMlOadO3dONGnSRAAQP/74Y771yvLOsjpeLS0t8cUXX0g3YCqVSmRkZIjExERhaGgotLW185WPasePHxdA0a0ailNasqytrS1MTU3znWPx8fHC29tbABDjx48vtM3SyraKlhslKS5Zfvr0qdi9e7fw9/cXQNEPGgomyzt37hTAs06y8v7mikuW1Q+7/Pz8yhxveTx48ED63ILlVHnkfTfb1tY2X78OeW+8i7sZ/OCDD6RyKm/5FhMTI7XYKW+y3L9/f+k3OmHCBHHmzJkiW6YVdOLECSl5/fHHH6V1kpOTRZ8+faRYqjJZXrBgQaEavbS0NOk60rZt20LrqK9XWlpaolu3bvlqyNTHvCL3beqHYvPnzy/0nvfu3bsLJTwliY2NFVFRUYXuaeLj40Xv3r0FACmxz6uy7yyvXLlSnD59Ot80lUol1q5dK4yNjYWpqWm+319ZFOwQN++fl5eXuHr1aqF11K02OnToUOx21Q+L8z6cVre2cnd3L3a9wYMHCwCFOlB8Htem0pSULO/atUsAzyoPYmNj8817EednRe7Hhai6ZFmtLK1jitv2hx9+KD1MOH78uDT9ypUronHjxtJ9XF6Vuc6WhMny/xszZowAIF555RVpWkJCgtDT0xOmpqaFEl4hnt2oNmvWTAAQe/fulaZ/88030lOQkppAqu3YsUMAEHp6ekU2v1Bvz9nZOd9FT32RUigURTbrDgoKkhLmgheknJwcqSan4Lrqk97W1rbIJ209e/YUwLPabjWVSiXV9Hz77beF1rl9+7b0RCtvZw8dO3Ys1w3L80iW8zaHLWp/1YVX69at801X30waGBgUeX6oj9PcuXPLtG9C/O9Gp3v37oXmqVQqKXEoWPv5PJLlgh187du3Twjxvwuhr69vkdvr0qVLkRez4pKb33//vdh9XrNmTZEXDvXFJjw8vMgY1OdwwWRZU77rp0+fVsnN+vr16wXwrCfgop7E3717VxgbGwtjY+N8ia/6YllUbUlqaqpUG5H36a8Q/ytTi/qutm3bJu1TUdv95ZdfBPCsN9O81A/g8pa9eZ06dUooFArRoEGDfNPLkyyXVHM8YMCAYsutUaNGFfmwoSSlJctA0S1z1N+lt7d3oXmllW0VLTdKUloTcDMzMzF9+vQiW4QUTJaF+N9vctq0adK04pLloq7HVSkmJkb63LwPZ8orb/PZ1atXF7tcUTeDSUlJ0gO/TZs2FVpHXfaVN1m+ffu2qF+/fqHvKiwsTEyZMkVcvHixyPXeeOMNAUC8+uqrhealp6dLNURVmSyXRN0aoWAPuerrlZ2dXZGvr1T0vk1PT09YWFiUK8aKSEtLE7q6usLNza3QvOfZwddnn30mAJS7drlfv35i0aJF4tKlSyI9PV0kJCSIJUuWSC0UGzRoUKj1h/o62qdPn2K3+9prrwkg/ytY6nvdopI4tY8//lgAEC+99FK+6c/j2lSaopLlhw8fitWrV0ut1fr3759vnRdxflb0flwIzUmW1Q+yART56ufRo0el/CfvA5vKXGdLUms7+CrIyMgIAJCcnCxN27x5MzIzM9GxY0c4OjoWWkepVOKll14CAPz333/S9HXr1gEARo8eDT09vVI/e/v27QCAV199FXZ2doXmDx06FHp6erh582aR47b5+fnBz8+v0HR1x0ydO3eGg4NDvnlaWlrw9vYGAFy/fr3IuN555x3o6+sXmj5s2DAAwLZt26RpFy5cwK1bt6Cvr4/BgwcXWqdu3bro1atXvv0FACcnJwDAqlWrIIQoMo7nTR3P4MGDi9zf0aNHAwAOHjyI1NTUQvM7depU5PnRrFkzAMUf35JiGTlyZKF5CoUCo0aNyrdcVdqyZQtCQkIQEhKCwMBAWFtbY/bs2QCADz74ACEhIfk+e8SIEUVuR328yhrja6+9BmNjY2zevLnQWMLqzmoGDRqUb/qOHTsAAG+99VaR2yxuuqZ813nLGXXZU9RnFTWOY15r1qwB8Oz4aGtrF9qGvb09mjVrhpSUFKmTkZSUFBw6dAhA0eeZoaGh9Bsu7jt85513Ck1TlzfFzVeXUQWPkXof3n333SI/y9vbGy4uLrh+/Tpu375d5DKlKakzo7fffhvA/841tezsbCxfvhxA4fOvsoo6PhUpL9SeZ7lhamqK4OBg6S8gIABWVlZITEzEH3/8gf3795dpO1988QUAYO7cuUhMTCxxWfXvo7jfxuHDh4v8bZR1LOqy/P4aN25caPsuLi5FLmtmZobu3buX6bPV9u3bh7S0NDg7O6Nz586F5nfv3h1169Yt1zaBZ9fakydPYvLkyVK8iYmJ2LVrF6ZMmQIPDw8MHjwYmZmZ+dZTnxvvv/9+oW3q6+tLv5OqduzYMUyYMAHdunVDaGiodA26fPkyAOD06dNFrterV68iv7uK3rc5OTnh6dOn0rWlslQqFdatW4fhw4ejc+fOaN26NUJCQhAREQGFQoErV64gLS2tSj4rr7i4OMycOROvvfYawsLCpOMZGRkJADh16lS5trds2TIMGjQI7u7u0NfXh42NDd58800cOHAA5ubmuH79On744Yd862RkZAB41klocdT3xnnHYK/oenlV5bWprNq1ayeVEdbW1ujVqxcePHiAoUOH4vfff8+37Is4Pyt6P65J9u/fj7S0NNSrV6/IsrVZs2YICgqCEKLYY1KV19nCd1e1VEpKCoBnNwZqZ86cAfDswqxOFAq6f/8+AODOnTvStAsXLgBAqYO1q6kvCp6enkXONzExgZOTE65evYrLly+jcePG+ea7uroWuZ6NjU2Z5qv3vSAPD48Sp9+/fx9JSUkwNTWV9qFevXrF3nyoexpVLwsAw4cPx5IlSzBt2jT8+eef6NSpE1q3bo127doVSvCfl9KOv5ubG3R1dZGVlYVr165JDxnUiju+tra2AIo/vgU9ffpUShaLi6WoY1hVEhISkJCQAODZwxRLS0uEhITgvffeQ48ePaTlSjte6hjznh8lMTY2xquvvopFixZh+fLl0o39w4cPsXnzZujq6ubrFRMArly5AgCFvgu14qZryndtYmIi/X9RSTkAeHl5SdvLyspCdHR0oWXUZdTPP/+Mv//+u8jtqPdZXUZdvXoVKpUKenp6aNCgQZHrlHaeFXUc1OVJafMLHiP1Pnz++eeYPn16kZ/38OFDaR+KusEoTXFlGQCEhobC1dUVMTExOH36tPSdqx/eBAYGFuoluTKsra1hZmZWaHp5zyG1511u+Pn5Yc+ePYWmR0ZG4s0330Tnzp1x8OBBBAQElLid0NBQhIWFYdeuXfjuu+8wefLkYpdV/z6K+22oE3i1q1evStfisij4+yuqjAoICIC1tTUAICkpSTpPi+Lm5pav1+myUH8X6qS8IKVSCXd393z3FmVlZmaGKVOmYMqUKbhx4waOHj2K3bt3Y926dbh37x4WLlyI3Nxcqcfep0+fSmV/adf9qiKEwIgRIzB//vwSl3v8+HG54qnofdsHH3yA4cOHo0OHDggICEB4eDhCQkIQGhqa73wpi6dPn6JLly7SQ8niPHnyBIaGhuXadkmWLFmCoUOHSklnUYo7nuXl4uKC999/HzNmzMCaNWswadIkaZ76QXRWVlax66sf1uQdwaOi6+VVldemsvLy8oKZmRlUKhVu3bqF27dvQ19fH61bty5UYfYizs+K3o9rktLKR+DZPhw6dKjIfajq6yyT5f8XFxcH4H8HEoD09PvWrVu4detWievnfcqVlJQE4NnwGmWh/tLyfnZBderUwdWrV/M9EVcrrrBVn2ClzS+uRre4ePJOT05OhqmpaZn3Qb2Omq+vL/bu3YvJkydj165dWLBgARYsWACFQoGIiAh89913VX6RLqi02BUKBWxsbHDnzp0ij39xhZFS+azhRllrzPP+eIuLpahjWFUGDhyIxYsXl7pcacdLHSPwv/OjNG+//TYWLVqEJUuWSMny33//jezsbPTu3RuWlpb5llffRBd3E1PcdE35rs3MzGBsbIyUlBTExsYWmdyra/UB4Pbt21IrjLzUZdTZs2dL/Ux1GaU+BjY2NsVehEo7z4oqU/Juq6T5BY+Reh/KMrxGcbUJpSnue1PHNWjQIEyaNAlLlizBnDlzABTfqqGySjuHykuucqNPnz6Ijo7GnDlzMG3aNKxdu7bUdaZOnYpdu3bh22+/lVpxFEVdoxobG1vkfE9Pz3w12u+++26hGpyS5K2xLe73t2zZMun/9+/fj9atWxe7vZLOr+Lk/R0WJ29ZWlH169dH/fr10adPH8ydOxfvvvsuli9fjsWLF+OLL76Ak5NTvnOouHiqIpa8li5divnz58PIyAizZs1CREQE6tatKyVBb7zxBpYtW1bsEEHFHfOK3rcNGzYMJiYmmDNnDo4fP47jx4/j66+/hr6+PgYMGIBZs2YVefNdlLFjx+LQoUNo1KgRpk+fjpYtW8La2lqqMXV0dMSdO3eqdPija9euYfDgwcjOzsaHH36IN954A66urjA2NoZCocDChQul+VVFPZTh1atX801XD/H25MmTYtdVz8s7HFxF18urKq9NZTVv3jy0bdtW+ve6devQt29fDBgwAHXr1kVoaKg070WcnxW9H9ckld2Hqr7Oshk2njWXUT8BbN68uTTd2NgYwLNx4sSz97uL/cubZKhv1J8+fVqmz1d/jvrJblHUT5rK+4SzMgo2iS1qujqeyuxDy5YtsW3bNjx58gRbt27F+PHj4ejoiO3btyMiIqLMx7GiSotdCCHt8/M8/uo4SopFjvOgoNKOV94anrLGGRISAnd3d5w4cUJK/EpKVtQFYXFPB4u7AGjKdw38r+XJvn37KrwN9f7s2LGj1DJKfRzV6zx48KDYm4MXeZ6p47ly5Uqp+5D3hqQqDRo0CEqlEsuWLUNOTg4ePXqETZs2FdmqQdPIWW60atUKAHD06NEyLR8cHIyIiAgkJiZKDyWKor4JP3v27HMp/62trdGwYUMAlfv9VUbe32FxSrqeVoShoSEWLFgApVIJIQSOHTuWL5aS4ikultISjeJaB6gfRsyZMwfvv/8+GjZsmK+2sLREojgVvW8DgAEDBiAmJgbx8fFYsWIF3nnnHWhra+O3337DG2+8UabPz8nJQVRUFIBnSVPPnj3h4OAgJco5OTm4d+9ehfatJFFRUcjOzkbfvn0xe/Zs+Pr6wsTERPp+Kno8S6Ie1zwnJyffdDc3NwAlN3VVz1Mvm/f/4+LiCm2zpPU0Tffu3TFjxgyoVCoMGTIEubm50rwXcX4+j5yior/zitK0vIjJMoC1a9fi3r170NHRQYcOHaTp6iZtZam1yUvdvOHw4cNlWt7d3R0AcP78+SLnJycnSwWdetkXQd2cvLjpderUkWoN1XHFxcUVm8CcO3cu37IFGRsbo2PHjpg5cyYuXrwIV1dX3LlzB1u2bKnUfpSmtON/5coVZGVlQUtLq9hmuFXB3NxceqpfXCylHcMXobTjpY4x7/lRFur3jBcvXoyzZ8/ixIkTsLOzQ6dOnYqNobj32YprMqkp3zXw7F1t4FkNS0UvNBUpoxo2bAilUonMzMxib2Ze5HlW0XK2uFrxinB0dERERATu37+PrVu34u+//0ZWVha6detWqFWDppGz3FCpVADK17Rz6tSpAIDvv/++2PVatGiBevXqITs7GwsXLqx8oEVQ//5+/fVXaT9eJPV3cenSpSJvQFUqVZF9lFSWiYmJdL6om7uam5tLNTgXL14scr3i7gfUDy6LS7IL1jqqqVsNqB+45JWdnV3s55WmouVJXnZ2dujTpw8WLlyII0eOQKlUYuPGjYiPjy913QcPHiA1NRWWlpZo1KhRoflnz57NlzzlVZkyraTjCZT/XeWyUJcrBV+NadGiBYDiX4+4d+8erl27lm9Z4NkrHzo6OsjIyMCJEycKrZednS29jpR3PU00bNgw1KtXD5cuXcLSpUul6S/i/KyK+/GCSvudq7/Pgip6TqvjunDhQrEJ+ou8T6n1yfLNmzeljorefPPNfM2zunbtCl1dXWzevFl6R7Is1O93zps3r8R3L9Q6duwIAFi5cmWRTxwXLFiAzMxMODs7F1n4Pi+///57oU5AAEjvGOV9sODh4YF69eohIyOjyJubu3fvYvXq1QD+t78lMTQ0RNOmTaV1y0L9VLq8TTXV8fz2229Fvuuj7rwiODi4Qs3tKhLLvHnzCs0TQkjTy3IMnxf1Z//4449Fzlcfr/LGOHDgQGhpaWHZsmXSOfTGG28U+S5gREQEABTbbLy46Zr0Xb/55ptwcXHB/fv3MWzYsArdsPfs2RPAszKipPfU8jI2NpZuqIo6z9LT06Xj/yLOM/U+/PDDD+VqBlfR33tx8nb09byaYFdUafsqV7lx8OBBACj23feitGzZEp07d0ZycnK+Vw3y0tbWxieffAIAmDJlynO50R81ahTMzc1x+vTpEt+ffl5CQkJgaGiI2NjYfJ1lqq1fv75C7yuXVht99epVaZm8tXPqMvWXX34ptE5mZqb0fnNB6u8+JiamUG2gSqXCokWLilxPfU4XlUwtWrSoxBr3klT0vq04np6eUvPWstyLqPcrKSmpyN/rN998U+q6FSnTSjqeFy9exIYNG8q9zZKkpaVJ50p4eHi+eY0bN5ZenyvqvFFPa9q0ab5Ex9TUVNpWUa9VrFy5EklJSbCysnpurYyqiq6uLsaOHQsAmDlzpnR9fxHnZ1XfjwP/+50X1XfK6tWri206X9FzWl0+3rp1S+o0Oa9jx47h0KFD0iubz125+s6uZkoaOurBgwfi+++/l4ZI8fT0LHIICXU39fXr1y/UJbpKpRJHjhwRQ4cOzTe4d1JSkvTZXbt2LTT0wb59+wqNs6zuKr5t27b5xvvctm2bNB7rzz//nG87pQ3ZUNrQKsV16Z53nOX+/fvnG2f5p59+EgqFQmhpaeUbH06I/43rZmpqKv79919p+r1796TxXlu2bJlvnaFDh4oVK1aI1NTUfNP/++8/YWJiIgCIXbt2SdNLGoZCPTzKli1bitzfsoyz3KdPn3xjIy5dulQav7S4sXeLO74VGc4p73ips2fPlsYKzMzMFCNHjpSGASk4xNjzGme5KHnHWR4zZky+cZa//vprAZRvnOW8unbtKp17QP6xlfPKO87y5MmT842z/Omnn5ZpnGW5v2shhDhy5IgwMDAQwLNhsA4dOlRoTNT4+HhpuK6CRXZubq40hmR4eLi4cuVKvvkZGRli48aN4q233so3XT3Oso6OTr6hRJKSkqRxQEsaZ7m44SOKilFNPaRDwe8kOTlZGufy9ddfLzQWcHJysoiMjBQffPBBvukrV64UAERISEiRw2aVJd68MjMzhZWVlXQOlGds5bxKGzqq4P7nVdzxK61sq2i5UZLixlkW4tm14O+//5Z+Z9OnT883v6iho/JSD/uhHp+8uHOmV69e0jVlzpw54vHjx4Xi2Lp1q3R8SipbirJ27Vophj59+hQao1YIIa5duyaN7VrwuyvrsEjFnYejR4+W7i/Onz8vTT916pRwcnKq0DjLdnZ2YujQoeLw4cPSeaD233//SeO1+vj45Ctrjh07JpRKpVAoFOLnn3+W5qWkpIh+/foVO85yTk6ONIzQJ598Iq2Xnp4uRo4cWex6w4cPF/j/YYISEhKk6Vu2bBGmpqZCX1+/yH0vy1A05b1vS0xMFH369BG7d+/Od8xycnLE999/LwAIIyOjQuMmF0d9Pg4ZMkS6Pubk5IiZM2cKpVIpDdtT8HxQH5PyjgErxP/KQwsLi3z3ZpcuXRJeXl7S8SzPNWr27Nli/vz54smTJ/mmX7t2TbRt21YAEIaGhkWOtbxs2TLpuOUdnmjnzp3CyMhIABCRkZGF1tu/f79QKBRCqVSKv//+W5oeExMj6tSpIwCIr7/+utB6z+PaVBr1Nosb6islJUVYWloKACIqKkqa/iLOz4rcjwtR/HGcP3++ACDq1asnLl++LE0/evSocHBwkH7nBfdn1qxZAoDo27dvseO9lzbOct26dfMNcXv16lXh6ekpldt5VeY6W5JakSy7ubmJ4OBgERwcLAIDA4WLi4t0sIBn4wrmHdg+r+zsbGn8QfUNVPPmzYWPj4+UzAEQFy5cyLdeTEyMsLOzE8CzQcmbNGkifH19hZmZWZEF1pUrV6Rx2fT09IS/v79o2LChtP0BAwYUOtGed7I8depUoaurK0xMTERgYKB0QQQgvvnmm0LbU6lUol+/ftIyDRs2FP7+/tKFoV69evkeKgghhI+Pj5QceXh4iObNm0vfGwDxxhtv5Fu+pJuTqVOnSjdgfn5+IjQ0VISGhko3iCWte/jwYem7MTIyEoGBgdI4dQDEZ599Vu7jW9EEav78+UKhUAjg2XjAzZo1E+bm5tK5sXHjxir7LCHKnywLIcS6deuk79XCwkI0a9ZMGodTqVSKBQsWFFqnLMny6tWrpWNecGzlghYvXiwdJxsbG9GsWTNhbW0tlEqlNF5jwbF5hdCs71qIZxebvGWShYWF8PX1Ff7+/sLBwUEolUoBPBvjuahxcu/evSv8/Pzy/e5atGghPD09pe+oTp06hdZTj1UNQDg5OYnAwEDpJsbCwkIcPXq00DrP64bkwoUL0tiwSqVSeHh4iBYtWgh3d3cpmSk49mZiYqKwsLAQAIS9vb0IDg4WoaGhYsaMGWWOtyB1YgmUb2zlvJ5Hslxa2SZExcqNkqjPeVNTU+n6GRwcLAICAqQbQACiS5cuhcZaLi1ZFkKIl156Kd91uCjZ2dli5MiR0m9AqVQKNzc30bx5c9GoUaN81+BmzZpVaMzyTZs2SQ/NAQhbW1vh7+8vfH19RZ06daRjam5uLubPn1/kflY0WU5OThYBAQECeDZeaNOmTYWXl5dQKBTC399f9O3bt9TEsCD1dw5AmJiYCG9vb+Hv7y9sbGyk6Y6OjoXuWYQQYvr06dIyDg4OIjAwUJiYmAg9PT0xbdq0Yvd16dKl0no2NjYiMDBQmJqaCmNjYzF79uwi17t586Z0HhkYGAhfX1+pHGzXrp00dnhFkuXy3rc9efJEmmZkZCR8fHxEYGCgdF4oFArx22+/lfk7WL9+vXTeWFpa5tvWpEmTij0f9u7dK8Xh7u4u2rRpI0JDQ4t9SFZwn9UPTrW0tISHh4d0Ltnb24svv/yy3Nco9cMcpVIpXVcaNWok7ZuxsbHYsGFDseurHzIBEB4eHsLDw0P699ChQ4tdTx2r+hru7e0tlQFdu3Yt8iGmJibLQggxadIkAUD4+vpK017E+VmR+3Ehij+O6enp0kMgbW1t4eXlJdzd3QXwLBEubpzlq1evSp/p7OwsWrduLUJDQ/P9fov7zLS0NNGuXTtpHzw9PYWPj490T+Dj4yMePnyYbx0myxWQN+lS/xkbGwtHR0cRHh4uPv3003xPc0uyadMm0aNHD2FnZyd0dHSEra2tCAgIECNGjBB79uwp9ARXiGeDk0+cOFE0adJEGBoaChMTE+Hh4SHef/99ERMTU2j5Bw8eiHHjxgk3Nzdp0PI2bdqIpUuXFvlE5nkny7t37xZHjhwRnTt3Fubm5sLAwEC0bNlSrFmzptjjpFKpxJ9//ilat24tTE1NhZ6ennBzcxMfffRRoZNaCCF27dolRo8eLV3MdXV1hbOzs+jYsaNYv359of0u6eYkKytLTJ48WTRq1Ejo6elJ37n6B1jajU1sbKwYMmSIcHZ2Frq6usLCwkJ06NBBbNq0qcjln2cCtX//ftGjRw9hY2MjdHR0hIODg3jjjTfEuXPnqvyzKpIsCyHEmTNnRP/+/YW9vb3Q0dERNjY24pVXXhEHDx4scvmyJMtZWVnSBeDHH38sNYYdO3aItm3bCmNjY2FiYiJCQ0PF9u3bxdmzZ6XCtCia9F0L8awG8PfffxfdunUTjo6OQl9fX+jr6wsnJyfx0ksvie+//148ePCg2PUzMjLE/PnzRZs2bYSFhYXQ1dUVTk5OIiQkRHzxxRfFlnMbNmwQERER0jrOzs5i6NChIi4ursjln+cNSVJSkpg5c6Zo0aKFVHa4uLiIsLAwMXv27CI/Mzo6WnTu3FlYWlpKN1N5v4PyJssnTpyQ9qG4Vg2leR7Jcmllm1p5y42SqM/5gn9aWlrC2tpahIeHiyVLlhR5bSpLsnz8+PFSk2W1c+fOiQ8++ED4+voKCwsLoa2tLSwsLISfn58YNmyY2LNnT7n3L6/k5GTx/fffiw4dOgh7e3uhq6srDA0NRf369UWvXr3EwoULRVJSUrH7WdFkWf3Z48ePl8oiZ2dnMXbsWJGcnFymxLCgW7duiQULFoiePXuKJk2aCHNzc6GtrS2srKxE69atxTfffFPkvqitWrVKtGjRQhgYGAgLCwvRpUsXER0dXeq+RkVFiYCAAKGvry8sLS3FK6+8Is6dO1fiepcuXRI9e/YUZmZmQl9fXzRu3Fh88cUXIjMzs9h9L88xKet9W05Ojli6dKkYMGCAaNy4sTAzMxMGBgbC3d1dvPHGG0Xer5Vm69atolWrVsLAwECYmJiIli1bSi0KSzof/v77b9G8eXPpwWV5vv/ExEQxcuRIqabP0dFRvPvuu+Lu3bsVukYdOnRIjBw5UjRv3lz6XRgbG4umTZuKcePGiZs3b5a6jSVLloiWLVsKY2NjYWxsLFq2bCn+/PPPUtfbsGGDCAsLE2ZmZsLQ0FD4+PiI7777rtjWPpqaLCckJEitxwreXzzv87O89+NClHwc79+/L9555x1ha2sr9PT0ROPGjaWWTMUly0I8ayEbGhoqTE1NpQctee+lSvrMrKws8f3330sP8w0MDETTpk3Fl19+WahFqhDPL1lW/P+KRJK2bdviv//+w+7duzX+vRCqWZ4+fQo7OzsIIRAfH1/hzpVWr16N3r17o3v37mUa0oYIALZu3YrOnTsjMDCwyHeziGqrPXv2oF27dggNDS1y3G0iopqq1nfwRUSaY9myZcjMzET37t0r1QuxulOZ4ODgqgqNagF1pzLqntmJiIiodmOyTEQa4fHjx1JPocOGDSt1+dWrV2Pz5s35huFIS0vDxx9/jE2bNsHIyAgDBgx4bvFSzXLkyBH8888/MDU1Rf/+/eUOh4iIiDSAttwBEFHtNnPmTGzatAlnz57F06dP0aFDhzI1/z9z5gy++OIL6Ovrw9XVFXp6erhw4QLS09OhpaWFBQsWwM7O7vnvAFVrffv2RWxsLE6cOIHc3FxMmDBBGoqDiIiIajcmy0Qkq4sXL2L//v2wsrLCgAED8O2335Zpve7du+P27dvYu3cvbt26hfT0dNjY2KBbt2748MMP0axZs+ccOdUEhw8fRlxcHBwdHfHuu+9i/PjxcodEREREGoIdfBEREREREREVwHeWiYiIiIiIiApgskxERERERERUAJNlIiIiIiIiogKYLBMREREREREVwGSZiIiIiIiIqAAmy0REREREREQFMFkmIiIiIiIiKoDJMhEREREREVEBTJaJiIiIiIiICmCyTERERERERFQAk2UiIiIiIiKiApgsExERERERERXAZJmIiIiIiIioACbLRERERERERAUwWSYiIiIiIiIqgMkyVYm2bdtizJgxcodBRERERERUJRRCCCF3EFT9PX78GDo6OjAxMZE7FCIiIiIiokpjskw1VlZWFnR1deUOg4iIiIiIqiE2w6YqkbcZ9vz58+Hm5gZ9fX3UqVMHvXv3LtM2VCoVvv76azRs2BB6enqoV68evvrqK2n+mTNnEBYWBgMDA1hZWeG9995DSkqKNH/QoEHo0aMHZsyYAQcHB7i7uwMA7ty5gz59+sDCwgJWVlbo3r07YmNjq2zfiYiIiIio5mGyTFXq2LFjGDVqFKZOnYpLly5h69ataNOmTZnWnThxIr7++mtMmjQJ58+fx99//406deoAANLS0tCpUydYWFggOjoaK1euxL///osRI0bk28bOnTtx4cIF7NixAxs3bkRaWhratWsHY2Nj7N27F/v374exsTE6deqErKysKt9/IiIiIiKqGdgMm6pE27Zt4evrizZt2uCtt97C7du3y/X+cnJyMmxsbPDjjz/i3XffLTT/t99+w/jx43Hr1i0YGRkBADZv3oyXX34Zd+/eRZ06dTBo0CBs3boVcXFxUvPrP/74A9988w0uXLgAhUIB4FnzbHNzc6xduxYdOnSogr0nIiIiIqKahjXLVKUiIiLg7OyMBg0aYMCAAVi2bBnS0tJKXe/ChQvIzMxE+/bti53v4+MjJcoAEBwcDJVKhUuXLknTmjZtmu895ePHj+Pq1aswMTGBsbExjI2NYWlpiYyMDFy7dq0Se0pERERERDWZttwBUM1iYmKCEydOYM+ePdi+fTs+//xzTJkyBdHR0TA3Ny92PQMDgxK3K4SQaoYLyjs9bzINPHsPOiAgAMuWLSu0no2NTYmfSUREREREtRdrlqnKaWtrIzw8HN988w1Onz6N2NhY7Nq1q8R13NzcYGBggJ07dxY539PTEzExMUhNTZWmHThwAEqlUurIqyj+/v64cuUKbG1t0bBhw3x/ZmZmFdtBIiIiIiKq8ZgsU5XauHEjfvjhB8TExODmzZv4888/oVKp0KhRoxLX09fXx/jx4/Hxxx/jzz//xLVr13D48GH8/vvvAID+/ftDX18fAwcOxNmzZ7F7926MHDkSAwYMkDoBK0r//v1hbW2N7t27Y9++fbhx4wb+++8/jB49Grdv367SfSciIiIiopqDzbCpSpmbm2PNmjWYMmUKMjIy4ObmhuXLl6NJkyalrjtp0iRoa2vj888/x927d2Fvb4+hQ4cCAAwNDbFt2zaMHj0azZo1g6GhIXr16oW5c+eWuE1DQ0Ps3bsX48ePR8+ePZGcnIy6deuiffv2MDU1rZJ9JiIiIiKimoe9YRMREREREREVwGbYRERERJWwe/duXLx4Eax/ICKqWZgs0wsRFxcnDd1U1F9cXJzcIRIREZUqOTkZy5YtQ+9XX0XK/w+N+P7778PDwwOOjo4YOHAgli5diqdPn8obKBERVRqbYdMLkZOTg9jY2GLnu7i4QFubr9ATEZFmWrVqFf5evhxbNm9GRkYGvAJaIGD8j/g32xaPk1Lg8SAGxlcPIeHkPlw8cwoxMTHwbOqNbZs3ITc3F23btuUoDERE1QyTZSIiIqIC0tPTsWPHDnTp2hUKhRJtQ9vgcUo6bFp3w5WGEbhrYFfsupZZT9De3QHhjob4Z/xAbN2wFkqlEoHNmiEiPBwDBw6Em5vbC9wbIiKqCCbLRERERAAyMzOxbds2REZFYf26dUhJScGKnYcQY+yOFRceIjZLp0LbdUy7A5fb0cg5vx9Xju7FiuXL0S6sPdavW4erV68gPDwcPj4+UCr5dhwRkSZhskwly1UBWlV48a7q7REREVVCTk4OtLW1IYRAYLNmOHH8OBo29kTd0O642bgjYo3qVe0HqlTwttBBRD0j3I+ai9W/fIv09HRYWVmhXVgYhg8bhrZt21btZxIRUYUwWabSjZ4PXL1b+e00dAC+H1b57RAREVVCTk4Odu/ejRUrVmDt2rU4evQoYFMPU5dtxP4MU1w3bvDCYtHJzYTHk/OwuHYQj0/tx8SxY/D6632xdv1GbFj3DyIiIhAWFgZbW9sXFhMRET3DZJlK1/Uz4Fxs5bfTxAXY9GXlt0NERFRBEyZMwB9//IEHDx6gnksD1G/XHQlB/XEBlnKHBgAw1VEg1N4A5qc24tCiObh68QIAoKm3N8aMHo23335b5giJiGoPdj9MRERENZJKpcLBgwcRGRmJSVO+gK2VJdJyFfDs0hf3vTrjomkjxCkUcoeZT1K2wIa4NMAiDBgbBtvMh2h4NxrKSweRnP2sfmPX7t2YPHkyIsLD0b59ezRv3hw6OhV7n5qIiIrHmmUqHWuWiYioGomOjsby5cuxcuVK3L59G/YOdfHarD9x2KgxjiRkyh1epbib6cDryRncXjMfl47sQ2JiIoyNjfHekCGYM3s21Ld1Cg17CEBEVB2xZpmqjdIu/AMHDsTixYtfTDBERKQxhBA4ceIEvL29AS1tTJ48GcdOnIBH+26waNoFZyya4vtUJZBavRNlALicmI3LysZA7x+g7JkDj8RLsI09Ai2HushSCVw8ewYdOnRA+/btEf7/Nc/16lVxJ2VERLUEa5apdBpSs3zv3j3p/yMjI/H555/j0qVL0jQDAwOYmZlJ/87OzmazNCKiGkoIgdOnTyMqKgqRkZG4du0aotZvxEPX1vjrxE0cSjOAUGjJHeYLpa+lgD8SoLPvbzyI2Y8Lp05ACIF2Ye2xa+e/AIDExMR810oiIioex/ChasPOzk76MzMzg0KhkP6dkZEBc3NzREVFoW3bttDX18dff/2FKVOmwNfXN992vvvuO7i4uOSbtmjRInh4eEBfXx+NGzfG/PnzX9yOERFRufV+9TX4+vpi/s8/w943GH5fLkffu+4YduARDqYb17pEGQAycgUO5trgv1ajcX7YSpj+eBItJi1EvQ59cCMpG/Hx8bC0tERgs2aYOHEi/v33X6Snp8sdNhGRxmIzbKpRxo8fjzlz5mDRokXQ09PDr7/+Wuo6v/32GyZPnowff/wRfn5+OHnyJAYPHgwjIyMMHDjwBURNREQluXz5MiIjI7EiMhLL/voLDZt4o17HPgjw7oFTdZphv5KtiIqSqGOKI05hOAJgSeRt1FWkIeijbyHOH8Dvf/yBmTNnwsbGBnfuxkNHWwsXL16Em5sbtLRq34MGIqKiMFmmGmXMmDHo2bNnudaZNm0a5syZI61Xv359nD9/HgsWLGCyTEQko19//RXzf/4Zp2JiYGxsDO92XfDBkUQcPH4TWQgA7OWOsHq5Iwxxx/VlwPVl4CUB15Tr8MiKx/a7mWhhroKPjw8MDQ3Rtl07hP//O8/u7u7sLIyIai0my1SjBAYGlmv5Bw8e4NatW3jnnXcwePBgaXpOTg7f6SIiesHi4uIQFRWFV/u+DmfHurhy/QYMHOqj+csjcMohGAe19J4tqJI3zhpBocA1E1dcgys2brsPLZELj6lRsLpxGDdi9mHMmDFQqVS4l/AQ1pbm2L9/P9zc3GBnZyd35ERELwyTZapRjIyM8v1bqVSiYB922dnZ0v+rVM/uuH777Te0aNEi33JshkZE9PzduXMHK1euxIrISBw5fBh6enp4bO6Ma/VDsbHREKS5sh/SFyFXoYWzlt6ApTcQ8B4MB6ahaepV/HlHiY6KLPTu3RsJCQnwbNJEqnVu3749DA0N5Q6diOi5YbJMNZqNjQ3u3bsHIYTUjCwmJkaaX6dOHdStWxfXr19H//79ZYqSiKh2uX//PkxNTaGjp48PP/wQa9asgV9oBIIm/oTTTm0wQxgB11PlDrNWS9M2xBEzbxw58hjjjgBWn29GUPwxaF08iDVr1+GHH37AlatX4VK/AbZt2QxjY2O0bNkSenp6codORFRlmCxTjda2bVs8ePAA33zzDXr37o2tW7diy5YtMDU1lZaZMmUKRo0aBVNTU3Tu3BmZmZk4duwYnjx5grFjx8oYPRFRzfHw4UOsWbMGKyIj8d+ePVj61zJYhnRDdo+PYdDmExzVMZE7RCrBI11LHHLuADh3ADoIOGXEY9ZdM4QrUjHnq+k4cuggDA0N0bp1G4SHt0e/fv3g4OAgd9hERJXCoaOoRvPw8MD8+fPx008/wcfHB0ePHsW4cePyLfPuu+9i4cKFWLx4MZo2bYrQ0FAsXrwY9evXlylqIqKa5aOPP4adnR3ef/99JGYDrT6cjeFPPNB5632sSbZAEhPl6kWhwC0DB/x6MRmv7XyAIwP/RKNZW9Ds7Y/xMD0Hn3/+OW7duoVslcCq1auxcOFC3LhxQ+6oiYjKTSEKvtBJVFDXz4BzsZXfThMXYNOXld8OERFprMTERKxbtw6RkVEYP2E8glqFYPbSVdh8JhbnG4Thsa6l3CHSc6aTm4kge2NE1DPGqXkTsGbJb1CpVKjfoAHah4Xh/fffh7+/v9xhEhGVis2wiYiIqNK2bNmCn3/5Bdu2bkVWVhZ8WrTC6QcZCBQCn2QHAo3LN1oBVV/ZWnrYm5CNvQlPgKDxMA0chkYJJ2Fw5QB27d2Ll19+Gf7+/li5eg2OHj6E9u3bo3Xr1oU66SQikhuTZSIiIiq3tLQ0bNq0CQGBgXB2dsHhw4dx4849tBw6CZcbRuCUvi0S61vIHSZpgCQdE0TXbQPUbQO0nYihSUqs3P0AOH0D/y77G7Nnz4aOjg5aBgXhgzFj8Morr8gdMhERACbLREREVEYZGRnYsmULIqOisHHDBqSmpuLTWfOQ1bofIt3fRpzjILlDpGogPl2Fv66mAI49gSmvwCXlJpxuH0Hm2QN4mpIGANiwcRN+++1XaZgqDw8PaVQLIqIXhckyla5hFfVmWVXbISKiFyYrKwsqlQp6enr4YOxY/PLzz3Bv0hSBb47BjUYd8ZWhI3A6Ue4wqbpSKBBr4oJYDxfAow+OZwK/rL2LBnHpuP0oER999BGysrJgb2+P0aNHY/z48XJHTES1CJNlKlmuCvh+WNVuT4udsBMRabLs7Gzs3LkTkZGRWLt2Lb755huEvjYI2h3egYvba7hs7IzLcgdJNVKuAI4+yMRRgwBg4CLo98+A/+PTMLl6ENkm1lAJgUMHD+Ltd96Rap3btm0LCws2+SeiqsfesKlEuSoBLWXVNXuq6u0REVHV+umnn/D555/j8ePHcHFtCOe23XHHpzuu6juWe1tfBlrgg6amMFp08zlESrWRpZ4SAVmxyNixBHHRe3HzxjUolUr0fb0flv21FEIIZGZmQl9fX+5QiagGYM0ylUhLqUD/XQm48DS70tvyMNfBsjDbKoiKiIiqQm5uLvbv348VK1ag+ys90alDBAxtHdG0+5uIb9IZl00aIpbviZIGeZypwg7UA8InAeFA3fR41L9zFGY2RnickYtHt67D29sbISGtER7+rObZ19cXWlpacodORNUQa5apVP5r7uDko6xKb8fPShcnetatgoiIiKgyYmJisGjRIqxcuRLx8fFwcHRC2xGTcdm9E449rHx5r8aaZXqRFAAaayXC9tRGpJ3dj/NH9iM1NRWenp44c/YslAoF4uLi4OTkxM7CiKhMWLNMRERUwwkhEB0dDRsbGzg6u+Dff/9F1MpVcA/rDqumnXHWvAn+ViqBKkyUiV40AeBCrhkuePUHvPpD+7UsNH1yAY2ViTiSkAlXrVS4uLjAyckJYWFhiIiIQFhYGOzs7OQOnYg0FHtaolpj8eLFMDc3lzsMIqIXQgiBEydOYMKECXB1dUWLFi3w44Lf8OuFZKyt3wv3Ju/F3tCPcdayKaDk7QDVPDlKXZyx8sFKizZotT4eDf55iIApf8KlTVccOBKN/v37o0GDBkhJzwQAHD16FMnJyTJHTUSahDXLVO0MGjQIS5YsKTT9ypUraNiwoQwRERFpBiEEcnNzoa2tjWlffYXJkybB0soKTcJehtm7X+M7az+oDj56tjATZKplUqGLY/bBgH0w0OYjWGc+QtOMWETGZaF9nVy0a9cOWVlZaN6iBSLCw9G+fXu0bNkSOjo6codORDJhskzVUqdOnbBo0aJ802xsbGSKhohIXhcuXEBkZCRWREZi8LvvYvDID6DT/CX4f9kQp6z8sU+LN/tEBT3Us8JuPSvs3vsQEAL1pm+F860jyD63H9//8AO++OIL3Im/hzq2ttixfRscHBzg5eUFJR80EdUa/LVTtaSnpwc7O7t8f99//z2aNm0KIyMjODk5YdiwYUhJSSl2G6dOnUK7du1gYmICU1NTBAQE4NixY9L8gwcPok2bNjAwMICTkxNGjRqF1NTUF7F7RERlsn79ejT19oanpye+/fZbWDf2wyq4wXrpTXxy0wwnbFsgl4kyUekUCsQZOmJfo1443PNbJM48Co9v/8X3cTrYHZ+BESNHwsfHB3Z2duj7+uv4/fff8fjxY7mjJqLnjDXLVGMolUr88MMPcHFxwY0bNzBs2DB8/PHHmD9/fpHL9+/fH35+fvj555+hpaWFmJgYqanVmTNn0LFjR0ybNg2///47Hjx4gBEjRmDEiBGFarSJiF6UGzduICoqCk2aeuOlLp0BbR2YODdG854fIsa+JQ4odZ8tqJI3TqLqTii0cMGoAS6cSsQ3pxKhO24jfB+dhunVQzgTsw8ro6IQFBQEYzMLbFi7BiqVCmFhYbCyspI7dCKqQkyWqVrauHEjjI2NpX937twZK1eulP5dv359TJs2De+//36xyXJcXBw++ugjNG7cGADg5uYmzZs1axb69euHMWPGSPN++OEHhIaG4ueff4a+vv5z2CsiosLu3LmDFStWYEVkJI5FR8PAwAC9Rn6Cxbr+2HzPA+ndvpY7RKIaL0upixibQMAmEAgaCdPsZEy8ZYkIkYwNS/7C9g1roVAo4Ovnh4jwcLzzzjtwd3eXO2wiqiQmy1QttWvXDj///LP0byMjI+zevRvTp0/H+fPnkZSUhJycHGRkZCA1NRVGRkaFtjF27Fi8++67WLp0KcLDw/Hqq6/C1dUVAHD8+HFcvXoVy5Ytk5YXQkClUuHGjRvw8PB4/jtJRLVWfHw8srOz4eDohE2bNuHTTz+Fb2gEgj79BafqhuAvbUPgRprcYRLVWkk6Jlgfl471cenAy3NhFzEBrneOAhcPYcmfS9GlSxe4urlhZdRKXLt6BeHh4QgICIC2Nm+9iaoTvrNM1ZKRkREaNmwo/WVlZaFLly7w8vLC6tWrcfz4cfz0008AgOzs7CK3MWXKFJw7dw5du3bFrl274OnpiX/++QcAoFKpMGTIEMTExEh/p06dwpUrV6SEmoioKiUkJODnn39GaNu2qFu3LqZ9+SW23U7HLscI6HwbjSO9f8Ah5w5I0zaUO1QiKuCevi0OuL6EA12/wv0v9mPovfr44NBjrD98Cl9//TVatmwJKysrdO/RA7t375Y7XCIqIz7eohrh2LFjyMnJwZw5c6ReKqOiokpdz93dHe7u7vjggw/w+uuvY9GiRXjllVfg7++Pc+fOcSgqInohFi9egnfeeftZM86Qdmj18XeIqtcWC7fdf7aAtnHJGyAizaFQ4GJSLi6eSwI834Vy1iB4Pr0A6xuHEXd6Px4+fgIAWLl6DTasW4vw/x+mqm7dujIHTkQFsWaZagRXV1fk5ORg3rx5uH79OpYuXYpffvml2OXT09MxYsQI7NmzBzdv3sSBAwcQHR0tNa8eP348Dh06hOHDhyMmJgZXrlzB+vXrMXLkyBe1S0RUQz158gSLFi1Cp06dMW3aNKiEgE6jZmj1wSyYfh+N4/1/xQHXl5GkYyJ3qERUBVRKbZy3bIq9AYMR89YSDEryR8ct97D22lNEnzqDgQMHwtHRER6envj999/lDpeI8mDNMtUIvr6+mDt3Lr7++mtMnDgRbdq0wYwZM/Dmm28WubyWlhYePXqEN998E/fv34e1tTV69uyJL774AgDg7e2N//77D59++ilat24NIQRcXV3Rp0+fF7lbRFSDHDlyBNO+/BLbt21DTk4OfFqGYJ+wh/2yOCSkGwCNXpE7RCJ6AdJyBLbfTgcs2gEj2sEy6wnc7x2HzqWDSFU869F+27Zt+HzyZESEhyM8PBxBQUHQ09OTOXKi2kchhBByB0GazX/NHZx8lFXp7fhZ6eJETzYxIqLaISUlBRs3boSZuTk6dOyIA/v2YcS48bAI7oaLruFI0LOWO8Tn7stAC3zQ1BRGi27KHQpRteFioo2mT87i4abfcfnIf3j08CEMDAwwZOhQfDt3LlSqZ2PDqV87I6LnhzXLREREVSQtLQ2bN29GZFQUNm3ciPT0dPQe9B7+NW+GlbddcGvw33KHSEQaLjY5B7HajYHus4CXVXBLvgb7uMPQdXFEeo4K52JOoFOnTmgXFobw9u0RHh6OBg0aQKFQyB06UY3DZJmIiKgSMjIy8PTpU9jWqYO169ajf7/X0bipL5q//RGuunfAKgMH4EyS3GESUXWkVOKKmRuuNHXDXgDfLrkJXwg0eeUtXDq1H/8MH47c3Fy0C2uPnf/ugEKhwKNHj2BlZSV35EQ1ApNlIiKicsrKysKOHTsQGRmJdevWoUuXLpg0fwliHENQ79v/cNHICRflDpKIapxsFRANa6D5MKD5MBjnpKBxwknUMxa4m5aL3Ed34ezsjKbe3oj4/16227RpA2Nj9qhPVBFMlqlUHuY6GrUdIiI5bd++HX369MHTp0/RwL0R/PoMxRGPTmiy6s6zBYyc5A2QiGqNFG1jHHNojWMArM8k4nNPc3SePB9Jpw9geWQU5s6dizp16uDWnbvQ0VLi1KlT8PT0hI4O78mIyqLWJMt79+7FrFmzcPz4ccTHx+Off/5Bjx49pPlr1qzBggULcPz4cTx69AgnT56Er69voe0cOnQIn376KY4cOQIdHR34+vpiy5YtMDAwAPBsSJBRo0Zh/fr1AIBu3bph3rx5MDc3l7YRFxeH4cOHY9euXTAwMEC/fv0we/Zs6OrqSsucOXMGI0aMwNGjR2FpaYkhQ4Zg0qRJL/x9lFyVwLIw2yrdnpaS79QQUfWQm5uL//77DytWrIB93br4YvJkmDi7w6fXO7jj0RFXTVxxne8JEpGGMDU1xflGL+Fm3U5AJwHntDg0ybmHjbfS0dwkB4GBgdDX10eb0FDpfWcvLy++70xUjFrTjV5qaip8fHzw448/Fjs/ODgYM2fOLHYbhw4dQqdOndChQwccPXoU0dHRGDFiRL7eCPv164eYmBhs3boVW7duRUxMDAYMGCDNz83NRdeuXZGamor9+/djxYoVWL16NT788ENpmaSkJERERMDBwQHR0dGYN28eZs+ejblz51bBkSifqk5smSgTUXVw9epVDBs2DA4ODmjfvj22bt+B6KcK+K+5g1Z7Bf5rMRxXTRsCvMEkIk2lUOCmkTM2m7VAzx0JcFr9AG5frUXAgDG4l5iGiRMnwt/fH0+TUyCEwM6dOxEXFyd31EQapVYOHaVQKArVLKvFxsaifv36RdYst2zZEhEREZg2bVqR271w4QI8PT1x+PBhtGjRAgBw+PBhBAUF4eLFi2jUqBG2bNmCl156Cbdu3YKDgwMAYMWKFRg0aBASEhJgamqKn3/+GRMnTsT9+/elMfVmzpyJefPm4fbt23z6R0RUxVQqFQ4fPoz09HS0aReGs6di0PXlbnAL644HXp1wwdyTiXEFcOgoohfnw6ammN3SCi7Lb+FmSk6py+vlZsI7/QZeaReEDg566ODhiMePH6Ohm5tU69ypUycYGRm9gOiJNFOtaYZdWQkJCThy5Aj69++PVq1a4dq1a2jcuDG++uorhISEAHhW82xmZiYlysCzBNvMzAwHDx5Eo0aNcOjQIXh5eUmJMgB07NgRmZmZOH78ONq1a4dDhw4hNDQ03+DzHTt2xMSJE6VknoiIKkcIgWPHjiEyMhJRUVG4desWwiM6ILVhS6x47AC9b/bjpuJZyyFnmWOtrsx1lVAAcDbm7QbR82ap96y8CrTWhaORVhnW0APgg01xadgUlwb/X/bD6uZRpJ85gH937sQvv/yCmzdvQtfAEBvXrYWxsTFCQkKkVw+JagNevcro+vXrAIApU6Zg9uzZ8PX1xZ9//on27dvj7NmzcHNzw71792BrW/j9XltbW9y7dw8AcO/ePdSpUyfffAsLC+jq6uZbxsXFJd8y6nXu3btXbLKcmZmJzMzMfNP09PTyJd1ERLWZEALJyckwNTXFth3/onPHDrCxsUHv3r3Rp08fhISEQEtLC92cWZNSVbJyBWJfZ6dnRC/Kqog6pS9UJAcAHgAGAgDu3LmDunXrAgBmzZqFQ4cOQU9PD62CgxHevj3efPNNODo6VknMRJqKyXIZqVQqAMCQIUPw1ltvAQD8/Pywc+dO/PHHH5gxYwYAFNlEWgiRb3pFllG3li+pCfaMGTPwxRdf5Js2efJkTJkypaRdIyKq8c6ePYvIyEisiIyEW8OG+PufDbhh54/X5q1BXd9WUGprYwOADdFP5Q61RunsZIjWdvpyh0FUq/TflYB76blVsCUlEBMPAND/ZBVa3LwEvSuHkHJ2P2bMmIFOnTrBzqEuoiJX4MnjxwgPD4e7uztfF6QahclyGdnb2wMAPD0980338PCQOkOws7PD/fv3C6374MEDqWbYzs4OR44cyTf/yZMnyM7OzreMupZZLSEhAQAK1UrnNXHiRIwdOzbfNNYqE1FtdurUKbzerx8unD8PM3NzeIW9hAT/l2CzNA45AoCeL3AhTe4waywLPa1nyfLo+cDVu3KHQ1SzdWkGDO+OA/czy/TOcrnpugBNXIAmr0OrdzaG3zREhOopzm7/Dxv++h05OTlwdHRE+/btMXLkSAQEBFR9DEQvGJPlMnJxcYGDgwMuXbqUb/rly5fRuXNnAEBQUBASExNx9OhRNG/eHABw5MgRJCYmolWrVtIyX331FeLj46UEfPv27dDT05MKlaCgIHzyySfIysqShpPavn07HBwcCjXPzotNromotrt69SqioqKQnZuLyZMmwcreERZu3gjsMwExdZrjgPL/h+irdV1byuzqXeBcrNxRENVsPg1e2Eflaung8MNsHH74FGg1HobNR8LnQQyMrh7CoWN78frDhwCAZctX4MihgwgPD0doaCjMzMxeWIxEVaHWJMspKSm4evWq9O8bN24gJiYGlpaWqFevHh4/foy4uDjcvfvsybc6Kbazs4OdnR0UCgU++ugjTJ48GT4+PvD19cWSJUtw8eJFrFq1CsCzWuZOnTph8ODBWLBgAQDgvffew0svvYRGjRoBADp06ABPT08MGDAAs2bNwuPHjzFu3DgMHjwYpqamAJ4NP/XFF19g0KBB+OSTT3DlyhVMnz4dn3/+OZu2EBEV8PDhQ/zxxx9YERmJkydOwMjICEHd+6LH9vvYejsdmV2nyx0iEVGNlqZtiOP2rQD7VkDrDzEgQYl2OxOgfeEu9q5bj3nz5kFLSwuBzZrh448+Qs+ePeUOmahMak2yfOzYMbRr1076t7q58sCBA7F48WKsX79eehcZAPr27Qsg/zu/Y8aMQUZGBj744AM8fvwYPj4+2LFjB1xdXaX1li1bhlGjRqFDhw4AgG7duuUb21lLSwubNm3CsGHDEBwcDAMDA/Tr1w+zZ8+WljEzM8OOHTswfPhwBAYGwsLCAmPHji3UxJqIqLa6ffs2bt68iRZBrfD06dNnDzLbdkSLz4bilEMI/tXWB26yeTURkRweZKgQdT0VcHoF+LQHHNPvwOV2NHLO70dK1rP3qf/5Zy0WLFiA8PBnw1R5e3tDqVTKHDlRfrVynGUiIqp+4uPjsWrVKqyIjMTBAwfg4emJGZuOYsX1VKy//AhpWuxIStN8GWiBj7zNoNttEpthEz1v/cKA6W+XeZxluSgA+FjpwvXWIcSuWYDz0QeQnp4Oa2trfPjhh5gwYUKhjm+J5FJrapaJiKj6ycnJgba2Nk6eOo0AP19oaWnBt3V7tJowD2ec2qDHjmedH4KJMhFRtSAAxDzKQoxhAPDGr9B5PRM+T87B7Noh5FrWRa4Q2LtnD95+5x2Et39W6xwWFgYbGxu5Q6daiMkyERFplMePH2PNmjWIjIxCdnYWdu7ajfsWrgiZOA+nHEJwTNdU7hCJiKiKZGvp4ZS1P2Dtj70AvllyE/5ZWqgXFIHd+/Zi4cKFAIDX+/XH38v+ghACaWlpMDIykjdwqhWYLBMRkUaIi4vDkCFD8e+/O6BSqeAT1AbGrbrDdulNPM4SgEsXuUMkIqLnLClbYI/CCWg7AWg7AbYZD9DwbjTM6xjjfloOHt64BD8/PwS1aiXVPDdr1gza2kxrqOrxrCIiIlkkJSVhw4YNuHX7Nj76+GNYWlnhUVoWgkZ+ifMNwnBSz/rZglnsWoOIqLZK0LdBQoMuOAjg52W34KrIQcsR05B5bj/mzJmDzz//HE2aNMHpM2egVChw5coVNGzYkO88U5VgskxERC9Meno61q9fjxWRkdiyeTMyMzMR2Lod7oa8g9Wxabj7xm9yh0hERBrsmjDFNY/XAI/XoOyZA4/Ei/DQTsa+exlwRSLc3d1hZ2eH9v9f69y+fXs4OTnJHTZVU0yWiYjouUpPT8fly5fR1Nsbj588Rb9+/dDY2w8tBk/EFbcOOGZgh2Pnk+UOk4iIqhmVUhsXLLxwAcCqjfegr8qC35fLYXr1EE6c2Ie///4bRkZGuP/gEQz1dbFv3z54eXnBwsJC7tCpmmCyTEREVS4zMxPbtm3DishIbFi/HkZGRth65gZW3NZD3R+P4Ly2ldwhEhFRDZOh1MVJ2xaAbQug1RiYZyfCJ/MmllzPQJhNJjp06ICsrCz4BwQgIjwc4eHhaN26NXR0dOQOnTQUk2UiIqpSd+7cgaenJ5KSkuDm0QT+/UfiZuMO8Ft779kCTJSJiOgFeKpjhv90vPHfgUcAAIevd6H+naNQnT+A3xYuxMyZM5Hw4CEsLCywccN61K1bF35+ftDS0pI5ctIUTJaJiKjCcnJysHv3bqxYsQLXrl/Hnt27kWZkg6B3x+NK3Ra4YtIAV+QOkoiICMBdAzvcbdgNaNgNeEkFt8w7+OqyQETddHwwdixuXL8OCwsLtG3XDhHh4XjttddgZcUHvLUZk2UiIiq3p0+fYvz48VizZg0ePnyIei4N4NKuO5pG3sDZJACNX5c7RCIiouIplbhi4ITvzibhu7NJ0P54M5o+uQCL64dw7fR+bBg1ChERETC1sMSqyBUQQqB9+/aoU6eO3JHTC8RkmYiISqVSqXDgwAHExMRg6PARMDY2xuFjx9Gk6+u479UZF00bIU6hAJLkjpSIiKj8cpS6OGPlA1j5AM2GwmhQGkZeMUJEehK2Ll+JHRv+AQA08fJCRHg4hg4dikaNGskcNT1vTJaJiKhIQggcOXIEkZGRWLlyJe7cuQMnZxekt+qD1bdycHroSrlDJCIiei5StQyx9XYGtt7OAF6eA+uOn8At/hi0Lh5E1KrVePXVV6ESAkuX/oXr164iPDwcLVq0gK6urtyhUxViskxERBIhBOLi4uDs7IxHTxMRGhoKcwtLNG7fDZZNO+OMRVOMP5Eqd5hEREQv1ENdKzx07gg4dwQ6CAyI00aE6hGenLyE7UvmY+rUqTAyMkLr1m3w0UfjEBYWJnfIVAWYLBMR1XJCCJw+fRqRkZGIiorCgwcPcOHmXayLV8J77lYc13FCgoI9gxIREQEAFApcT87FggvJgOc7UMwchMZJV2B74zASzh5Acmo6AOCvv5dj29Yt+Hn+fBgbG8scNFUEk2UiolosNTUVAYGBuHTxIiwsLdEk7GWY+HSCU1Q8VAotQNdF7hCJiIg0mlBo4aJZY1z0bQz4DkKfBwoEbYxHneMXEbl0KaZNncpkuZpiskxEVItcunQJUVFROHDgILZs2QyVrgE8InrC+HVPxNg2w34tHblDJCIiqtYycwX2xGcg9EkS7O3t4ezsLHdIVEFMlomIarjMzEzMnTsXKyIjcfrUKRgbG8M7rCs6/3MVu59oI6vpu3KHSEREVOM8PX8UwSEhUCgUcodCFcRkmYioBrp58yb+++8/vP7GAOjq6uKvZctg5tIYLbqPRox9EA5q6QGP5I6SiIioZtIV2bh8+iTe7tdH7lCoEpgsExHVEHfu3MHKlSuxIjISRw4fhoGBAVRNQrH5qQFufLAe6So+2SYiInoRmtkZY8OdO6xVruaYLBMRVWNJSUkwNTVFemYWvLy8kJqaCr/QCARN/AmnndrgrRMqAKkAeLEmIiJ6UULs9GFiZg5tJa+/1RmTZSKiaubhw4dYvXo1IqOicOTwYcTdvoPoFF20+OJPHNJ2xlEdE7lDJCIiqtVOzPkAM73d8dmnn8odClUCk2UiomoiNzcXL7/cDdu3bwMA+AS3hf+Ir9BwVTyeQh8w8JI5QiIiIoJKhaPb16O111i5I6FKYrJMRKShEhMTsW7dOmzatBlL/1oKbW1tmNdvjFZj2uFc/TCc0LWQO0QiIiIqwDX1Bq49fYqQkBC5Q6FKYrJMRKRBhBBYvnw5VkRGYtvWrcjKyoJ3i1Z4b9NFbE0xw33fEXKHSERERCVwuBuDm9raaN68udyhUCUxWSYikllqaip2796Nzl26AFDg66+/hkrHAC3f/xyXG0bgtJ4NTj8AgFyZIyUiIqLS5F6Ohp+/P4yMjOQOhSqJyTIRkQwyMjKwZcsWrIiMxMYNG5CWloa1h89gPxzw+IOVuJ2tI3eIREREVAGzvpoK7fREucOgKsBkmYjoBcnJyYG2tjZyVSr4+Pjg8uXLaOTljWYDP8CNRh3R47QRgEQATJSJiIiqIycjLbRq2kjuMKiKMFkmInqOsrOzsXPnTkRGRmL9+vU4d+4cEvUtETBsGrJUtrhk7IxLcgdJREREVaLB7cMYNWo2vv32W2hpackdDlUSk2Uioudk1KhRWLZsGR4/fgwX14bweuUttN10D5dU6YBhM7nDIyIioiqmOrkD207uY6JcQzBZJiKqArm5udi3bx9WrVqF6V9/A1MjQ6SpFGja/U3Ee3bGZdOGiFUoAJXckRIREdHzcv/MEYQEB8sdBlURJstERJVw4MABrFixAqtWrcK9e/dQ16ke9Nr1w39KZxz3GSN3eERERPSCmGYn48r5s5g4bqzcoVAVYbJMRFQOQggcO3YMAQEByIUC48ePx7XrN+Ae/gqsvDrhnIUX5j5WAMiSO1QiIiJ6gdwensFxIRASEiJ3KFRFmCwTEZVCCIGTJ08iMjISUVFRiI2Nxcad/+FGHV9kv/cT7qUb455SKXeYREREJKNQvyZ4bdYsuLq6yh0KVREmy0REpejUqTO2b98GK2treIa9DPPBnfHyVQeIa48AmALMk4mIiGq9ns0aI+glHygUCrlDoSrCZJmIKI/z588jKioKkVFR2LB+PWzrNUDDl9/Ew9aDcMomAPuULDaJiIgoP53cTOz8bTacBr6JevXqyR0OVRHe9RERAfjhhx/w62+/4dzZszA1NUXTsK54578EHIIWsvWCgDpyR0hERESaqlHiJUz+fBK6dO7EZLkGYbJMRLXS9evXERUVhbcHvwdbK0tcunIVZvU90bz3R4ixa4EDSl0O80RERERlYnnrJIyMjODr6yt3KFSFmCwTUa1x69YtREVFYUVkJI5FR8PAwADpjk1xtk4gtviNRbq3kDtEIiIiqoYyLkWjRcuW0NZmelWTsFsaIqrR7t69i+zsbOSoBIYMGYJPP/0UZrb2CPr0FyjmRGNquifWxKYhPZeJMhEREVWASoUrJw6jNYeMqnGYLBNRjXP//n389NNPaBMaCkdHR2zdvgNbb6VBp/8UXL19D6/P+QuHnDsgTdtQ7lCJiIiommtkmIs3BwxAly5d5A6FqhjbCRBRjTJs+HAs+OUXKJVK+Ia0Q6uPv8cbNx2RdDcBgA2WmJgAj9LkDpOIiIhqiDYulpj7xrdQcsioGofJMhFVW0+ePMHatWuxYkUkZsycAV9fX1g1DULQWFecqx+GYzpmcodIRERENZzVzaO4Yt8IjRq6yh0KVTEmy0RU7axbtw6//vobduzYjpycHPi0DMGXR+9j/9k4PNAKBtzljpCIiIhqi78njUBGj+749ttv5Q6FqhiTZSLSeCkpKdi4cSPahIaijp0d9uzZg1sPHqHl8C9wsUE4YvStEQMAGRzriYiIiF4cu8wHiIu9gRB27lUjMVkmIo2UlpaGzZs3Y0VkJDZv2oT09HRM+3kxHvm8hJUBo3HHc5TcIRIREVEtV//+KdwDEBwcLHco9BwwWSYijZGRkQGlUgltHR0Mfm8I/l72Fzy8/dDs7Y9xzb0DJmnZA2eT5A6TiIiICACgc/0YXBs2hJ2dndyh0HPAZJmIZJWVlYUdO3YgMjLy/99F/hVeHV6BcffhcAocjAtGTrggd5BERERERXCvY4HmPXrIHQY9J0yWiUg2s2fPxldffYWnT5+igXsj+PYZiokPnHBj1R0AdQAjuSMkIiIiKpqpjgK/zJkBLQ4ZVWMxWSaiFyInJwf//fcfIiMjMWDgILQObgU9awd493oHdzw64pqJK67zYkNERETVhL9+ChKfPIGlpaXcodBzwmSZiJ6r6OhoLFq0CKtXr0ZCQgIcnV2Q7hGKUfedEZMdBLQIkjtEIiIionIT/y6Gx+iluHfvHhR84F8jMVkmoiqlUqlw+PBhODs7w9beARs3bsS6DRvRuNNrsGzSERfNPfGXQgE8ypI7VCIiIqIKS7oQjVbBwUyUazAmy0RUaUIIHDt2DJGRkYiKisKtW7fw6bTpsO4+DFubvIm7n72Ju0ql3GESERERVQltVRYunozGG19+KXco9BwxWSaiChFCQKVSQUtLCx9PmIDZ33wDG1tbNA7rBgvvLvjKsilw+DEAJcA8mYiIiGoQ98TLOJ+ejpCQELlDoeeIyTIRlcvZs2cRGRmJFZGR+GjcOLw28B0YBveE75cBOG3th31KFitERERUs7lkxCPB2hp+fn5yh0LPEet7iKhMoqKi4NmkCZo2bYp5P/6IOk1b4I80J9gsjcPU+7aIsW0GFRNlIiIiqgXee7M/bt+Nh46Ojtyh0HPEO1siKtLVq1cRGRmJlq2C0b5dW+RACQs3bwT2mYiYOs1wQKn7bEEha5hEREREL5YQaGWtBT0dplI1Hb9hIpLExcVhxYoVWBEZiZMnTsDIyAivjpuKedke2JoSiMyuAXKHSERERCQrl9Q4uNRpiv/++w+BgYFyh0PPEZNlolru1q1bUCqVsLV3wMqVKzFlyhT4tO2IFpPexyn7YCzW1gdupskdJhEREZFGcIw/ibiMDDRq1EjuUOg5Y7JMVAvFx8dj5cqVWBEZiUMHD+KDsWMROnIqDrn3gGJOJxzWNpQ7RCIiIiKNJK4eg4+vL0xMTOQOhZ4zJstEtcy8n37C6JEjoa2tDd/W7dFqwo9Y6NQa3+5IAKAEmCgTERERFetWzGH0ePklucOgF4DJMlEN9ujRI/zzzz9YsSISXbt2wajRY2Dg2QqtPvoWZ5zbIVqHT0SJiIiIyso2+wniblzn+Mq1BJNlohpo7969mD59Bnbu/BcqlQo+QW2wJd0aX/0Vh0eZ5kDDbnKHSERERFTttHGvi/kJCTA0ZEu82oDJMlENkJSUhA0bNsDOwQHt2rZFYlIS7j1NRtDIL3HBtT1O6lo9WzBTJW+gRERERNVYiJ0+zCxNoaulkDsUegGYLBNVU6mpqdiwYQMio6KwZfNmZGZm4o0RY7FezxurEr1x952lcodIREREVKOs/egN6HXviqFDh8odCr0ASrkDIKKyS09PR0JCAlRC4K+/luH111/H5dhbaPHeJ7D//iD+8h6BH84l4W5artyhEhEREdUoRjmp2Lt9M7S1Wd9YW/CbJtJwmZmZ2Lp1KyKjorBh/Xq8/vrrGDFjHi66dYDjd/tw3rCu3CESERER1Xjuj8/ipErFzr1qESbLRBps7dq1GDhwIJKSkuDm0QT+/Udiu0cn/Lbm7rMFmCgTERERvRAmscdhZWWFRo0ayR0KvSBMlok0RE5ODnbt2oXIyEg09vDAR+PGwdi5EXz7DMFtj064YlwfV+QOkoiIiKiWSr4QjeCQECgU7NyrtmCyTCSzCxcu4LvvvsOaNWvw8OFDONd3RYJ1IyxdfRtnHusDzd6XO0QiIiKiWk1bAfzxy3wocrPlDoVeICbLRC+YSqXCgQMHIIRAUEhrJCQkYPPWbWjyUj/c8+yES2aNcFOhAB6zMCYiIiLSBH7WuvD1qi93GPSCMVkmegGEEDh8+DAiIyOxcuVK3L17Fy+90gvtLHyw4nFD3P50F26zSQ8RERGRRrI5sxkTj97AjOnT5Q6FXiAmy0TPiRACKSkpMDExwcrVa9Dn1d6wrWOHxu27wdK7Czaae2Hj4cfPFmaiTERERKSxHh3YgEOZyXKHQS8Yk2WiKiSEwOnTpxEZGYnIyEg0a9YM8xcvwx2XVvCZvhqnrbyRoNCSO0wiIiIiKishcO3EYQwdMkTuSOgFY7JMVEUOHz6MgYMG4fKlS7CwtESTsJdxxedl2P4Vh1wBwNpP7hCJiIiIqJyc027h5oMHHF+5FmKyTFRBly5dQmRkJPQNDfHxuHGwtHeEjWcgjPt/jlM2gdivpfNsQSFvnERERERUcY7xMbilVCIoKEjuUOgFY7JMVA737t3DokWLsCIyEqdPnYKxsTFavzoI+7bdw/bb2cjqPE3uEImIiIioCnVsHYS+9ebB1NRU7lDoBWOyTFSKmzdv4t69e/Bv1hzx8fH48ssv4dOuM5p3H41T9kHYoqUHxKXLHSYRERERPQcDQv3gYtJc7jBIBkq5A3hR9u7di5dffhkODg5QKBRYu3Ztvvlr1qxBx44dYW1tDYVCgZiYmELbaNu2LRQKRb6/vn375lvm8uXL6N69O6ytrWFqaorg4GDs3r073zJxcXF4+eWXYWRkBGtra4waNQpZWVn5ljlz5gxCQ0NhYGCAunXrYurUqRCC7XlflNu3b+Pbb79Fi5Yt4eLigtGjx2D9zTRMf+QAMecYDnWfhaOObZGppSd3qERERET0nNjkJCLq52/x4MEDuUMhGdSaZDk1NRU+Pj748ccfi50fHByMmTNnlridwYMHIz4+XvpbsGBBvvldu3ZFTk4Odu3ahePHj8PX1xcvvfQS7t27BwDIzc1F165dkZqaiv3792PFihVYvXo1PvzwQ2kbSUlJiIiIgIODA6KjozFv3jzMnj0bc+fOreRRoJLk5OQAAPbuPwAnJydMmDABMLFG0CfzcXbgb+j9bwJW3UhDupa+zJESERER0YvQ4N4JjB8/HpmZmXKHQjKoNc2wO3fujM6dOxc7f8CAAQCA2NjYErdjaGgIOzu7Iuc9fPgQV69exR9//AFvb28AwMyZMzF//nycO3cOdnZ22L59O86fP49bt27BwcEBADBnzhwMGjQIX331FUxNTbFs2TJkZGRg8eLF0NPTg5eXFy5fvoy5c+di7NixUHBM3irz4MEDrF69GisiI2FsZIS16zcg0cELwRPm4YxTGxzVMZE7RCIiIiKSif6N43B2cYGjo6PcoZAMak3NclVZtmwZrK2t0aRJE4wbNw7Jyf8bnNzKygoeHh74888/kZqaipycHCxYsAB16tRBQEAAAODQoUPw8vKSEmUA6NixIzIzM3H8+HFpmdDQUOjp6eVb5u7du6Um81Q2V65cQUREB9jb22PEiBFIVmkhybsjbP+KQ7edj3GgQVckMVEmIiIiqtUenDmC1hwyqtaqNTXLVaF///6oX78+7OzscPbsWUycOBGnTp3Cjh07AAAKhQI7duxA9+7dYWJiAqVSiTp16mDr1q0wNzcH8Kw35Tp16uTbroWFBXR1daWm2vfu3YOLi0u+ZdTr3Lt3D/Xr1y8yvszMzEJNRPT09PIl3bVVYmIi1q1bh8dPnmDUqFGwtLLCk8xcBI2ZifP1w3BC1+LZgpkqeQMlIiIiIo1gmJOGS2diMGroYLlDIZkwWS6HwYP/90Px8vKCm5sbAgMDceLECfj7+0MIgWHDhsHW1hb79u2DgYEBFi5ciJdeegnR0dGwt7cHgCKbUQsh8k0vuIy6c6+SmmDPmDEDX3zxRb5pkydPxpQpU8q9rzVBamoq1q1bhxWRkdi2dSuys7MR3KErrgb2x6obabg/YKHcIRIRERGRhvI3VaHpe+8hLCxM7lBIJkyWK8Hf3x86Ojq4cuUK/P39sWvXLmzcuBFPnjyRxmGbP38+duzYgSVLlmDChAmws7PDkSNH8m3nyZMnyM7OlmqP7ezspFpmtYSEBAAoVCud18SJEzF27Nh802pbrXJqaipu3LgBzyZNcOduPPr37w+vgBZo+f7nuOQagf36Nth/Prn0DRERERFRrRbW2BGfvf4TdJTsL6i24jvLlXDu3DlkZ2dLNcZpaWkAAKUy/2FVKpVQqZ417w0KCsLZs2cRHx8vzd++fTv09PSk95qDgoKwd+/efMNJbd++HQ4ODoWaZ+elp6cHU1PTfH+1IVlOT0/HmjVr0KdvX9ja2qJHjx449TATvz22hMNPR3F2yHLsbdIP9/Vt5A6ViIiIiKoJw0v7EH/nttxhkIxqTbKckpKCmJgYafzkGzduICYmBnFxcQCAx48fIyYmBufPnwcAXLp0CTExMVIN77Vr1zB16lQcO3YMsbGx2Lx5M1599VX4+fkhODgYwLMk18LCAgMHDsSpU6dw+fJlfPTRR7hx4wa6du0KAOjQoQM8PT0xYMAAnDx5Ejt37sS4ceMwePBgqTa6X79+0NPTw6BBg3D27Fn8888/mD59OnvCLsKly5dha2uLXr164dS5C2g2cCyyRi6C/9p4zD6diLs61nKHSERERETVjJYqB9Pe64cVy5fLHQrJqNY0wz527BjatWsn/VvdXHngwIFYvHgx1q9fj7feekua37dvXwD/e+dXV1cXO3fuxPfff4+UlBQ4OTmha9eumDx5MrS0tAAA1tbW2Lp1Kz799FOEhYUhOzsbTZo0wbp16+Dj4wMA0NLSwqZNmzBs2DAEBwfDwMAA/fr1w+zZs6XPNjMzw44dOzB8+HAEBgbCwsICY8eOLdTEurbJzs7Gv//+i6ioKCQkPMCmTRuhsq6HFm+Pw7X6bXHJqB4uyR0kEREREVV7bslXcTE1FSHsCbtWUwh1z1FEGiohIQGffPIJ/vnnHzx+/Bj1G7qhXrseSIgYiQtPc+QOj6qZJ2/Ww+rYNLy796HcoRDVeF8GWuAjbzPodpsEnIuVOxyimq1fGDD9bbgsv4WbKbw/qqw25/7GkV+mITExsVa81khFqzU1y1Q9ZasETExMcPBoNJr2GIh4j064bNoQNxQKgIkyERERET0HWZei0bxFCybKtRyTZdJoG9evxz5tF1wYuRYX5A6GiIiIiGqFRo510MQ9WO4wSGZMlkljCSHQq+crCP5wNuD+itzhEBEREVEt4GqqjcW/LZA7DNIAtaY3bKp+0tPTIYSAStdA7lCIiIiIqJbw13qKxMREucMgDcBkmTRWamoqACBbx1DmSIiIiIiotohfMRttQkPlDoM0AJNl0lgpKSkAgBwd1iwTERER0Ytx9/RhhATzfWViskwaTKVSoUmTJsg2NJc7FCIiIiKqBayyHuP6lcscX5kAMFkmDebq6oqzZ88CTp5yh0JEREREtYBrwmkAYLJMAJgsUzWQkiPkDoGIiIiIagH7jAS4ubvDyclJ7lBIAzBZJo21fv16mJiYIPnxI7lDISIiIqJaYNK4MTh/7pzcYZCG4DjLpLGSk5ORkpKCHKW+3KEQERERUQ1noFTBy1wL2tpMkegZ1iyTxkpNTYVCoUCGUlfuUIiIiIiohnO/fxK21la4efOm3KGQhmCyTBorJSUFxsbGgEIhdyhEREREVMOZx52AUqnk+8okYbJMGis1NRUGRkZyh0FEREREtUDyhaNoFRwMpZIpEj3DM4E01pAhQ/DXui1yh0FERERENZxSlYPLJ46gNYeMojyYLJPGsrW1RV03jrFMRERERM+Xe2osUlJS0Lp1a7lDIQ3Crt5IYy1cuBBn7j4C7F+TOxQiIiIiqsEiWvrj3zt3YGtjI3copEFYs0waa9u2bTiw61+5wyAiIiKiGi7ETg917Oyho6MjdyikQZgsk8ZKSU2Ftp6B3GEQERERUU0mBOa80RH/rF4ldySkYZgsk8ZKSUmBlj57wyYiIiKi58cx/S6OHjoIQ0NDuUMhDcNkmTRWamoqtAxYaBERERHR81Mv/iQAoFWrVjJHQpqGHXyRxurX/w2c1aqDfXIHQkREREQ1lvLaMTTx8oKFhYXcoZCGYc0yaaxRo8fAJaSz3GEQERERUQ129zTHV6aisWaZNNaBfXtxP9UGADv5IiIiIqKqZ62vxJqoSOjr68sdCmkg1iyTRhJCICK8Pc7t2iR3KERERERUQ7Wqow8fHx80atRI7lBIAzFZJo2UlZWF3NxcqPTYwRcRERERPR9a//2FmV9/I3cYpKHYDJs0UkpKCgAgW4dNsImIiIjo+biybSX03OrLHQZpKNYsk0ZKTU0FAOTosmaZiIiIiKqefk4GLp0+gRB27kXFYLJMGik7Oxt169ZFtq6x3KEQERERUQ3k/vQCsrOzmSxTsZgsk0ZydXXF7du3oWzgJ3coRERERFQDWcQdh5mZGby8vOQOhTQU31kmjZaSo5I7BCIiIiKqgXq/1BkDW7hBS0tL7lBIQ7FmmTTS9u3b4ejoiORHD+UOhYiIiIhqGKUCeKtDK7w1aJDcoZAGY7JMGunJkye4c+cOUhU6codCRERERDWMe+Zd/Prj90hOTpY7FNJgTJZJI6mHjkrT0pc5EiIiIiKqaWyv7cf48eOhrc23Uql4TJZJI6WmpsLAwABCwXdIiIiIiKhqZV+ORkBgIAwMDOQOhTQYk2XSSCkpKTA0MpI7DCIiIiKqaYTAjROH0JpDRlEpmCyTRhowYAAWrlgtdxhEREREVMPUzbiHe/F30bp1a7lDIQ3HRvqkkZycnJBmYgdcvy13KERERERUgwRYaaPzu++iVatWcodCGo7JMmmkFStW4NSth4B5V7lDISIiIqIapLN/Y7zd91foainkDoU0HJthk0Zau3Yttq9fI3cYRERERFTTxPyLp48eyB0FVQNMlkkjpaSkQFvfUO4wiIiIiKgGMc9Owvv9emHbtm1yh0LVAJNl0kgpqanQNmBv2ERERERUddwenAIAhLAnbCoDJsukkVJTUqHU57h3RERERFR1DGOPw8HBAS4uLnKHQtUAO/gijfTSyy/jqp4D9ssdCBERERHVGI/PHUVI69ZQKNi5F5WONcukkSZ++hncI3rKHQYRERER1RB6SsCtniM6d+okdyhUTbBmmTTSqVMxePjIBICW3KEQERERUQ3QzFYPq1etlDsMqkZYs0waqXWrIJzcskruMIiIiIiohmgqHiIxOUXuMKgaYbJMGicnJweZmZlQ6XLoKCIiIiKqGse+/xh9Xn1V7jCoGmGyTBonNTUVAJCrw96wiYiIiKjyFCIXl48fRkhIsNyhUDXCZJk0jjpZztZhzTIRERERVZ5r8g0kJiaidevWcodC1QiTZdI46enpMDY2ZrJMRERERFXC/u5J6OjooFmzZnKHQtUIk2XSOK6urkhOToZ24+Zyh0JERERENYBl+gM0b9EChoasjKGy49BRpLFSsoXcIRARERFRDfDz7Bmoo896QiofnjGkcf777z94eXkh6fEDuUMhIiIiomrOUU+FOvpKKJVMfah8eMaQxnnw4AHOnTuHNJWW3KEQERERUTXndHEbbG1tkZLCMZapfJgsk8ZRF2SpSn2ZIyEiIiKi6k7r+nFY29jA2NhY7lCommGyTBonNTUVurq6yNXSkTsUIiIiIqrm7p8+gpBgjq9M5cdkmTROSkoKjPjkj4iIiIgqyTQ7GVcunEObNm3kDoWqIfaGTRqnV69ecHRvgjceyh0JEREREVVnjZ6cRzSAkJAQuUOhaog1y6RxGjZsiJbtO8odBhERERFVc6907YRrsTdRv359uUOhaog1y6RxNmzYgFO3EgCdMLlDISIiIqJqLNReHy62ZlAoFHKHQtUQa5ZJ40RGRmL1X0vkDoOIiIiIqjFdVRaGdmiB3bt2yR0KVVNMlknjpKSkQMfASO4wiIiIiKgac396EWdOn4aFhYXcoVA1xWSZNE5KSiq09A3lDoOIiIiIqjGrWydgbGwMb29vuUOhaorJMmmclNQUaLNmmYiIiIgqIe1iNFq2DIK2Nrtpoophskwap02bUNT1CpQ7DCIiIiKqrlQqXDlxGK1bc8goqjg+ZiGN8+X0GZhzJhGR0U/kDoWIiIiIqiFPCx0s2b4dNjY2codC1RiTZdI4N2/G4nGiltxhEBEREVE11drBEP4BAVByyCiqBDbDJo3j29QLR//5S+4wiIiIiKiaevzPj/j119/kDoOqOSbLpFFUKhXS0tKg0mNv2ERERERUMYdWLcblSxflDoOqOSbLpFHS0tIAALk6BjJHQkRERETVkV3GfdyOu4mQEHbuRZXDZJk0SkpKCgAgR5c1y0RERERUfvXvnwIAJstUaUyWSaOoa5azWbNMRERERBWgff043NzdYWtrK3coVM2xN2zSKA0aNEBOTg5arr0DPM6VOxwiIiIiqmbefaMv9HuEyx0G1QBMlknjaGlpIU0oATBZJiIiIqKyM9NV4o3O7ThkFFUJNsMmjXL48GEEBwcj8eEDuUMhIiIiomqmSfJlzP/pJ2RnZ8sdCtUATJZJo8THx+PgwYNIY6UyEREREZWTzsmtmDZtGrS12YCWKq/WJMt79+7Fyy+/DAcHBygUCqxduzbf/DVr1qBjx46wtraGQqFATExMoW20bdsWCoUi31/fvn0LLbdp0ya0aNECBgYGsLa2Rs+ePfPNj4uLw8svvwwjIyNYW1tj1KhRyMrKyrfMmTNnEBoaCgMDA9StWxdTp06FEKLSx0HTpaamPvuvNnvDJiIiIqLyeXr+KEJat4aCzbCpClTqkUuDBg1KXUapVMLU1BSNGjXCK6+8gtdee60yH1lhqamp8PHxwVtvvYVevXoVOT84OBivvvoqBg8eXOx2Bg8ejKlTp0r/NjDI32vz6tWrMXjwYEyfPh1hYWEQQuDMmTPS/NzcXHTt2hU2NjbYv38/Hj16hIEDB0IIgXnz5gEAkpKSEBERgXbt2iE6OhqXL1/GoEGDYGRkhA8//LCyh0KjpaSkQKlUIkuhI3coRERERFSN6ORm4lLMMQzqM0PuUKiGqFSyrFKpkJOTg7t37z7bmLY2rK2t8fDhQ+Tk5AAAHBwckJCQgJiYGERFRWHhwoXYuHEjdHV1Kx99OXTu3BmdO3cudv6AAQMAALGxsSVux9DQEHZ2dkXOy8nJwejRozFr1iy888470vRGjRpJ/799+3acP38et27dgoODAwBgzpw5GDRoEL766iuYmppi2bJlyMjIwOLFi6GnpwcvLy9cvnwZc+fOxdixY2v0k7LU1FQYGxsjqQbvIxERERFVPffEyziXkcHxlanKVKoZdkxMDOzt7REeHo5Dhw4hMzMTd+/eRWZmJg4ePIj27dvDwcEBcXFxuHz5Mrp06YKdO3dizpw5VRX/C7ds2TJYW1ujSZMmGDduHJKTk6V5J06cwJ07d6BUKuHn5wd7e3t07twZ586dk5Y5dOgQvLy8pEQZADp27IjMzEwcP35cWiY0NBR6enr5lrl7926pyXx116lTJ8ya97PcYRARERFRNRNY1wJvvf02fHx85A6FaohKJcvjx49HZmYmtm7dihYtWkg1ngqFAi1btsTWrVuRkZGBCRMmoGHDhli5ciWcnZ2xYsWKKgn+Revfvz+WL1+OPXv2YNKkSVi9enW+95GvX78OAJgyZQo+++wzbNy4ERYWFggNDcXjx48BAPfu3UOdOnXybdfCwgK6urq4d+9escuo/61epiiZmZlISkrK95eZmVn5HX+BmjRpgg6vvCp3GERERERUzfRs7Y/fflsIHR2+zkdVo1LJ8rp169ClSxcolUVvRktLC126dMG6desAAPr6+ggLC8PVq1cr87GyGTx4MMLDw+Hl5YW+ffti1apV+Pfff3HixAkAz5qlA8Cnn36KXr16ISAgAIsWLYJCocDKlSul7RTVjFoIkW96wWXUnXuV1AR7xowZMDMzy/c3Y0b1emdj586dWLvmH7nDICIiIqLqRKVC4pEtSEp8KnckVINUKllW116WJDExEYmJidK/ra2tK/ORGsXf3x86Ojq4cuUKAMDe3h4A4OnpKS2jp6eHBg0aIC4uDgBgZ2dXqHb4yZMnyM7OlmqPi1omISEBAArVOOc1ceJE6Xir/yZOnFjJvXyxlixZgsU/fy93GERERERUjTRIu4k3+7wqvdZIVBUqlSx7enoiMjISN2/eLHJ+bGwsIiMj8yWPcXFxsLGxqczHaoxz584hOztbSpIDAgKgp6eHS5cuSctkZ2cjNjYWzs7OAICgoCCcPXsW8fHx0jLbt2+Hnp4eAgICpGX27t2bbzip7du3w8HBAS4uLsXGo6enB1NT03x/ed97rg5SU1OhY2AkdxhEREREVI043I2BlpYWWrZsKXcoVINUqjfsTz75BL1794aPjw8GDx6MoKAg2NjY4MGDBzh48CAWLlyI5ORkfPLJJwCArKwsbN++HR06dKiS4MsjJSUlX/PvGzduICYmBpaWlqhXrx4eP36MuLg4qWdvdcJrZ2cHOzs7XLt2DcuWLUOXLl1gbW2N8+fP48MPP4Sfnx+Cg4MBAKamphg6dCgmT54MJycnODs7Y9asWQCAV1999h5uhw4d4OnpiQEDBmDWrFl4/Pgxxo0bh8GDB8PU1BQA0K9fP3zxxRcYNGgQPvnkE1y5cgXTp0/H559/XqN7wgaA5JQUaOlzjGUiIiIiKjvVlWj4+vnB2NhY7lCoBqlUstyzZ08sXLgQY8aMwZw5c/IlckIIGBsbY8GCBVInWGlpafj999/RpEmTykVdAceOHUO7du2kf48dOxYAMHDgQCxevBjr16/HW2+9Jc3v27cvAGDy5MmYMmUKdHV1sXPnTnz//fdISUmBk5MTunbtismTJ0NLS0tab9asWdDW1saAAQOQnp6OFi1aYNeuXbCwsADw7D3uTZs2YdiwYQgODoaBgQH69euH2bNnS9swMzPDjh07MHz4cAQGBsLCwgJjx46VYq7JUlNToW1bc5rqExEREdHzd+vUEfTq0V3uMKiGUQh1z1GVkJiYiHXr1uHUqVNISkqCqakpfHx80L17d5iZmVVFnFRLjBg1CvcM62K162tyh0I11JM362F1bBre3ftQ7lCIarwvAy3wkbcZdLtNAs7Fyh0OUc3WLwyY/jZclt/CzZQcuaN5oey1s+ETNRrDhw/HSy+9JHc4VINUqmZZzczMDG+++WZVbIpqubnffo/vziZi9dEncodCRERERNVASD1zRG3ZIncYVANVqoMvoqr25MkTJKZnlb4gERERERGAxlnxSEpNlzsMqoEqXbOclZWFtWvXIjo6Gk+fPkVubm6hZRQKBX7//ffKfhTVAm4NXOA3aBzQdIDcoRARERFRNbBy/EDcCvDDokWL5A6FaphKJcs3b95EREQErl27hpJefWayTGUhhEBqaipUuhw6ioiIiIhKZ5KdjMvnzuCjMaPkDoVqoEolyx988AGuXr2KAQMG4O2334ajoyO0tavkNWiqhTIyMqBSqaDSNZA7FCIiIiKqBtwen8MJlQohISFyh0I1UKUy2127dqF9+/ZYsmRJVcVDtVhqaioAIEeX4ywTERERUelMYo/DxsYGbm5ucodCNVClOvhSqVTw8/OrqliolktJSQEAZOvoyxwJEREREVUHxumP0CY0FAqFQu5QqAaqVM1yUFAQLly4UFWxUC1Xr149PHr0CJ13JQIcOYqIiIiISqCjBFb9+Qd0FcX3nURUGZWqWZ45cyZ2796NVatWVVU8VIsplUpYWloiXaEjdyhEREREpOF8TBXQUz67hyR6HipVs7xhwwa0a9cOffr0QWhoKPz8/GBmZlZoOYVCgUmTJlXmo6gWOHHiBCZN+r/27js8qjJ///g9aZNGepkUIEDoIL2DlEWKLC6LZV0UwQKL+ltU0F2xgSjqWrDv2sXCqqtgbyCCWOhNeodk0qhJmAnp5/cHMl8TikJy5qS8X9eV63LOeWbmns+yTD485zzPvcq75EHJJ8LqOAAAAKjBgpe+oWb/fEO7du2iYYYpqtQsz5gxw/PfS5Ys0ZIlS047jmYZv4fT6dQXX3yhmIvvlwKsTgMAAICarHD7ajVOSaFRhmmq1CwvXry4unIAntWw3b6shg0AAICzMAztWrtMN990k9VJUIdVqVnu379/deUAPKthH7fZLU4CAACAmizFnaZ9hw+zvzJMxTULqDHcbreCg4MlLqUBAADAWTQ6uFE+Pj7q2bOn1VFQh53TzHJaWpokKSkpSb6+vp7Hv0ejRo3OLRnqnf79++v+Rx7THVYHAQAAQI02ftw4vf63PyksLMzqKKjDzqlZTklJkc1m09atW9WiRQvP499is9lUWlp63iFRP3Tq1EnRzdvrjnfSrY4CAACAGmxQYpAaN6BRhrnOqVm+5pprZLPZPNtDnXwMVIfly5drY8YhSW2tjgIAAIAaKrbokEb2+ZPmzJmjzp07Wx0Hddg5Nctz5sw562OgKl566SWt3rhFmviO1VEAAABQQzU9sEErNm5UQkKC1VFQx7GSEmoMt9st/6AQq2MAAACgBrPvWaMmTZvSLMN0NMuoMY65XPILYo9lAAAAnNmhTSvVjy2j4AVV2mdZkrZs2aLnnntOq1atUm5ursrKyk4ZY7PZtHv37qq+Feo4t9stv3CH1TEAAABQQ4WUurVt43rdevMkq6OgHqhSs/zdd99p2LBhKioqkp+fn+Lj4+Xnd+pLGoZRlbdBPdGsWTMdDk20OgYAAABqqB7J4Xrwhx/UrFkzq6OgHqhSs3znnXeqtLRUr7zyisaNGydfX9/qyoV66IWXXtGzm/P1yYojVkcBAABADXRhYqi6duopfx925IH5qnTP8oYNG3TllVfquuuuo1FGlZWVlclVUm51DAAAANRQ2157UPPe/5/VMVBPVKlZbtCggeLi4qorC+q5xPhYLX7jWatjAAAAoAbyLSvRJ3NekDM93eooqCeq1CyPGDFC33//fXVlQT3ndrtV7me3OgYAAABqoBb5O1VQUKC+rIQNL6lSs/zoo48qLy9PkydPVkFBQXVlQj1UXFyskpISlQewdRQAAABOFZuxToGBgercubPVUVBPnNMCX4MGDTrlWEhIiJ5//nnNmTNHzZs3V3h4+CljbDabFi1adP4pUee53W5JUql/kMVJAAAAUBMVbV+l7j16KCAgwOooqCfOqVlesmTJGc+5XC6tW7futOdsNlarw9m5XC5JUgkzywAAADiN2//f3xTiS18B7zmnZrm8nJWKYY6EhATt3r1bV60ul/KsTgMAAICapHm4ny7748VWx0A9U6V7loHq4ufnp6ZNm6rQj8uwAQAAUFFq1lq9/PLLVsdAPVOlZnnQoEF68803zzrmnXfeOe29zsCvbdq0SVdddZVyDx2wOgoAAABqmPylH+i555+3OgbqmSo1y0uWLNG+ffvOOiYtLU3fffddVd4G9UBaWpr++9//qqC41OooAAAAqGEyNizXhf36WR0D9Yzpl2G73W75+/ub/Tao5U4u8HXcN9DiJAAAAKhJYooPa9/uXeyvDK87pwW+pBMzgL+Wm5t7yjFJKisrk9Pp1Pvvv6+UlJTzDoj64eTWUW5f7lkGAADA/2l64GcdktSnTx+ro6CeOedmOSUlxbMVlM1m09NPP62nn376jOMNw9Bjjz12/glRL7hcLgUGBqrQ5mt1FAAAANQg3Zslqev/+39KTk62OgrqmXNulq+55hrZbDYZhqE333xTHTp0UMeOHU8Z5+vrq6ioKA0aNEjDhg2rjqyow7p3765/3nOf7rc6CAAAAGqU6y4eoI5jh1gdA/WQzTAM43yf3KRJE912222aPHlydWZCPVVcZqj0/P84Ar+Lr80mGYYOFrJvPGC2sAAfBfraFDD7fSn9oNVxgLptSBfpjz2VXVCqkjr0FVfgdmvLssW6aPBghYaGWh0H9cw5zyz/2vjx4xUVFVVdWVCP/fzzz0o/lKv1kRdYHQV13HUtQ5UQ7KfkULaZB7zmjiusTgDUG053mYrK6s7kw44Vy3Tdn/+szZs3q02bNlbHQT1TpWZ51qxZuu2226orC+qxZ599VsvWrNfmG/9ndRTUcUOSg5QQ7Kervj2grbklVscB6rTWEf6aOyhOeux/0pKfrY4D1G0Xd5Nu/pMu++aA9rvqzlac/VcvUVRUlFq1amV1FNRDVWqWGzdurCNHjlRXFtRjLpdL/kHBVsdAPbI1t0TrDhdbHQOoH9IPSpv3WZ0CqNs6NLU6gSmObV2l3n36yMeHK8LgfVX6U/fXv/5VX3/9tfLy8qorD+opt9st/6AQq2MAAACghvAtL9X2tSvUj/2VYZEqNcv33HOPLrjgAg0aNEiff/65Dhw4UF25UM8cc7nkG8jMMgAAAE5oG+BWz549NWDAAKujoJ6q0mXYQUFBkk7spXzJJZeccZzNZlNpad25dwLVLz7eobxQh9UxAAAAUEMMbNVQTyxceGInC8ACVWqW+/XrJxt/eFEN3nx7rv69JV9fLeceeAAAAEipx50qKgpVcKDd6iiop6rULC9ZsqSaYgCSu7TubHMAAACAKjAMzRwzVFnXX69Zs2ZZnQb1FMvKoUZo0ayJFr/1H6tjAAAAoAZodDxDB3Ny1JfFvWChKs0s/1pGRoY2bNigvLw8hYWFqWPHjkpKSqqul0cdl5OTo8ZMLAMAAEBSw6z1SrfZ1KtXL6ujoB6rcrO8Z88eTZo0SYsWLTrl3B/+8Af9+9//VmpqalXfBnVYWVmZCgsLVRbAatgAAACQbLtXq1379oqIiLA6CuqxKjXLTqdTffr0UU5Ojlq3bq0LL7xQDodDOTk5+v777/XNN9+oX79+WrlypRo2bFhdmVHHuN1uSVKZf5DFSQAAAFATBBYcUYd+/ayOgXquSs3yjBkzlJOTo5deekk33HDDKedfffVVTZw4UTNnztTLL79clbdCHXayWS5lZhkAAKDeiw300cLPP1V5ebnVUVDPVWmBr6+//lqXXHLJaRtlSbr++us1cuRIffnll1V5G9Rx0dHRWrt2rewtu1kdBQAAABbrGWWTYRjy8WEtYlirSn8CDxw4oLZt2551TNu2bXXw4MGqvA3quICAAHXq1EmFAaFWRwEAAIDF8t57VL1797E6BlC1Zjk2NlabN28+65gtW7YoNja2Km+DOm779u266aablHeYf1QBAACo7w5vXqlmzZpaHQOoWrM8dOhQffrpp3r11VdPe/61117Tp59+qmHDhlXlbVDH7d27V//5z3/kKjhudRQAAABYKKjsuLb/vE59+jCzDOtVeYGvzz77TBMnTtRTTz2l/v37Kz4+Xjk5OVq6dKk2b96smJgYTZ8+vbryog46ucDXcT8W+AIAAKjPWhzZog2lperbt6/VUYCqNcsNGzbUjz/+qL/97W9avHjxKZdkDxw4UP/5z3/YNgpn5XK5JEluH7vFSQAAAGCl6MyNCg8P/811kQBvqFKzLEmpqalatGiRnE6n1q1bp/z8fIWFhaljx440yfhd3G63/Pz8VOoTYHUUAAAAWOjOO/+plndOYCVs1AhVbpZPSk5OVnJycnW9HOqR9u3b6++3TtGTNpvVUQAAAGARX5vUxxGoYD96CtQM59ws33TTTef8JjabTc8///w5Pw/1Q79+/dSia289+Xaa1VEAAABgkdTcHerX4zJ98MEHatKkidVxgHNvll944YXfPdb2q5lCmmWcyc6dO7XjQJ6kaKujAAAAwCLxGWu1fNMmJSQkWB0FkHQezfLixYt/17i0tDTNnDlTu3fvrtA0A5U98cQTWrpspfT/5lkdBQAAABYp3rFKXbt1U2BgoNVRAEnn0Sz379//rOePHj2qhx56SM8//7wKCwvVq1cv/etf/zrvgKj73G63AoJDrI4BAAAAqxiG9q5drvHjrrE6CeBRbQt8FRYW6qmnntKjjz6q3NxctWrVSg899JBGjRpVXW+BOsrtdss/iD2WAQAA6qvk45lyZmexvzJqlCqvyW4Yhl555RU1b95cd911l4KDg/XSSy9p06ZNNMr4XY4dc8kviJllAACA+urC1in67rvvfvMqVsCbqjSz/NFHH+muu+7S9u3bFRYWpoceeki33nor9xngnASHhMgIjbU6BgAAACwyoFG4ejbvpwBf1jpCzXFeM8s//PCD+vTpo0svvVR79+7Vbbfdpj179ujOO++kUcY5e3/efP1p2qNWxwAAAIBFvn10qr5d+LXVMYAKznlm+ZJLLtHnn38uHx8fjRs3TjNnzlRyMhuHo2rcJYbVEQAAAGCBqJJcvfv6y/rjH7gEGzXLOTfLn332mWw2mxo1aqTs7GxNnDjxN59js9n0+eefn1dA1H3du3aW46IxUvPLrI4CAAAAL0s9uFErJRb3Qo1zXvcsG4ahvXv3au/evb9rPPss42x27dyp8AuLrI4BAAAACwTtXa3k5GQ1atTI6ihABefcLP/eBhn4PcrLy1VQUKByf7aOAgAAqI+ObF6lvn37MsGGGuecm+XGjRubkQP11PHjx2UYhsrsQVZHAQAAgJcF+dp0zz9vlyOOnVFQ81Rp6yigqtxutySplJllAACAeqdbrF1XjLzU6hjAaZ3X1lFAdQkPD9e3334re4suVkcBAACAlzl2fae5/33H6hjAadEsw1J2u10DBw5UcXCU1VEAAADgZXs+eU1vv/WW1TGA06JZhqX27t2ru+66S3mHD1odBQAAAF5kM8q0Y+0K9evHllGomWiWYandu3fr4YcfluuXe5cBAABQPzQ/tlf5+fnsr4waq940y0uXLtXIkSOVmJgom82mjz76qML5+fPna+jQoYqJiZHNZtP69etPeY0BAwbIZrNV+LnyyitP+35FRUXq2LHjaV8rLS1NI0eOVEhIiGJiYjR58mQVFxdXGLNx40b1799fQUFBSkpK0syZM2UYRlVKUCOdXODruG+gxUkAAADgTfEZa+Tv769u3bpZHQU4rXrTLLvdbnXo0EHPPffcGc/36dNHjzzyyFlfZ8KECcrKyvL8vPjii6cd949//EOJiYmnHC8rK9OIESPkdrv1ww8/6N1339W8efM0depUz5j8/HxddNFFSkxM1KpVq/Tss8/q8ccf1+zZs8/hE9cOLpdLkuT2ZTVsAACA+qR3u5a6/Y47FBTEFqKomerN1lHDhw/X8OHDz3h+7NixkqR9+/ad9XWCg4PlcDjOOubLL7/UggULNG/ePH355ZcVzi1YsEBbtmxRenq6p5l+4oknNH78eM2aNUthYWGaO3euCgsLNWfOHNntdrVr1047duzQ7NmzNWXKlDq1Ybvb7ZbNZlORT4DVUQAAAOBFt/31EsUH/dnqGMAZ1ZuZ5eoyd+5cxcTEqG3btrr99tt17NixCudzcnI0YcIEvfXWWwoOPnW2dNmyZWrXrl2FWeehQ4eqqKhIa9as8Yzp37+/7HZ7hTGZmZm/2czXNqmpqbr2hglSHfoHAAAAAJxdcnme1iz+WoWFhVZHAc6o3swsV4errrpKTZo0kcPh0KZNmzRt2jRt2LBBCxculCQZhqHx48dr0qRJ6tq162kb2+zsbMXHx1c4FhkZqYCAAGVnZ3vGpKSkVBhz8jnZ2dlq0qTJafMVFRWpqKiowjG73V6h6a5pBg0apAt699drb6VZHQUAAABe0mj/Txox6WYdOnRIgYGsXYOaiZnlczBhwgQNHjxY7dq105VXXqkPPvhA33zzjdauXStJevbZZ5Wfn69p06ad9XVOdxm1YRgVjlcec3Jxr7Ndgv3www8rPDy8ws/DDz/8uz+fFTIyMrR1xy6rYwAAAMCLfHevVus2bRQdHW11FOCMaJaroHPnzvL399fOnTslSd9++62WL18uu90uPz8/paamSpK6du2qcePGSZIcDodnBvmko0ePqqSkxDN7fLoxBw4ckKRTZqV/bdq0acrLy6vw81uNu9UeeughTbjqCqtjAAAAwIuyf16hvn36WB0DOCua5SrYvHmzSkpKlJCQIEl65plntGHDBq1fv17r16/XF198IUl67733NGvWLElSr169tGnTJmVlZXleZ8GCBbLb7erSpYtnzNKlSytsJ7VgwQIlJiaecnn2r9ntdoWFhVX4qcmXYEsnFvgKCGIlbAAAgPoioiRfO7dtUb9+/ayOApxVvbln2eVyadeu/7vcd+/evVq/fr2ioqLUqFEjHTlyRGlpacrMzJQkbd++XdKJWV6Hw6Hdu3dr7ty5uvjiixUTE6MtW7Zo6tSp6tSpk/r88q9ijRo1qvCeoaGhkqRmzZopOTlZkjRkyBC1adNGY8eO1WOPPaYjR47o9ttv14QJExQWFiZJGjNmjO6//36NHz9ed911l3bu3KmHHnpI9913X51aCVs68b9LQFCI1TEAAADgJR0Djqn8wgvVt29fq6MAZ1VvZpZXr16tTp06qVOnTpKkKVOmqFOnTrrvvvskSZ988ok6deqkESNGSJKuvPJKderUSS+88IIkKSAgQIsWLdLQoUPVsmVLTZ48WUOGDNE333wjX1/f353D19dXn3/+uQIDA9WnTx9dccUVGjVqlB5//HHPmPDwcC1cuFBOp1Ndu3bVTTfdpClTpmjKlCnVVY4aw+V2yzeQmWUAAID6Yli3dvpm8ZIzLloL1BT1ZmZ5wIABnkWyTmf8+PEaP378Gc83bNhQ33333Tm9Z0pKymnfs1GjRvrss8/O+tz27dtr6dKl5/R+tVF5WbkCQhtYHQMAAABekuJOk1HWWvLxtzoKcFb1ZmYZNdNnX36lvz74H6tjAAAAwAvsZUUaO6CrXnrxRaujAL+JZhmWc5eUWx0BAAAAXtAid6tKSkq4Xxm1As0yLDV08B+09P05VscAAACAF0Slr1WDBg3Uvn17q6MAv4lmGZZat26t8vPyrI4BAAAAL3BvXalevXqf0wK5gFVolmEZwzDkcrlk2Nk6CgAAoK7zsUmGK1f9+nEJNmqHerMaNmqe4uJilZWVqcw/yOooAAAAMFnbSH+tXrlC5eWsV4PagZllWMblckmSygLYZxkAAKCu6xVpU7lhyMeHFgS1A39SYZmQkBB9+OGHsjfvbHUUAAAAmGzjk7dp9OhLrY4B/G40y7BMYGCgRo0apdKwWKujAAAAwGT71y9X89RmVscAfjfuWYZlnE6n5s6dq9y4iyWFWh0HAAAAJkk4nq1MZzr7K6NWYWYZltm5c6fuvPNOufJzrY4CAAAAEzXJWS9J6t27t7VBgHNAswzLnFzgq8A30OIkAAAAMFNA2s9q2aqVYmO5/Q61B5dhwzJut1uSdNyXraMAAADqsuefflIRhUesjgGcE5plWIaZZQAAgLovIsBHbaICJSVaHQU4J1yGDcs0bNhQoy+7XIbN1+ooAAAAMElz50/q2bOncnNzrY4CnBOaZVhm6NChevntd6yOAQAAABMF716p/fv3Kzw83OoowDnhMmxY5siRI0rLK7Q6BgAAAEx0dMtK9e3bVzabzeoowDlhZhmWuf/++3XFiCFWxwAAAIBJAsqLtW3davZXRq1EswzLuFwu2YNDrI4BAAAAk7TI3abi4mKaZdRKNMuwjNvtVkAQzTIAAEBdNaRXF3319QJ16NDB6ijAOeOeZVjG5XLJLzDY6hgAAAAwyaCUKA1OHixfH+5XRu3DzDIs43K75cfMMgAAQN1UXq7X77hOK5YvszoJcF5olmGZL79eqDEPPGd1DAAAAJigWcE+zfvfeyosZPcT1E40y7CMr6+vinwCrI4BAAAAEyRmrpevr6969OhhdRTgvHDPMixz+aWj5dtxsJR0sdVRAAAAUM3Kd6xWp86dFRLCbXeonZhZhmW+X/qdDh/MsToGAAAATLB//TL1Y8so1GLMLMMybrdbhp3VsAEAAOqapCCbHnlollq3bm11FOC80SzDEiUlJSouLlaZP80yAABAXdMvMVhXDbrK6hhAlXAZNizhdrslSeUBQRYnAQAAQHULXPOZPvz4U6tjAFVCswxL2O12vf7667I362h1FAAAAFSzZW8+rU8//tDqGECV0CzDEkFBQRo/frzKo5OtjgIAAIBqFFbq0o7NG9WvXz+rowBVQrMMS+Tk5OiFF15Q7pHDVkcBAABANWp+8GcZhqG+rISNWo5mGZbYsWOHbrzxRh07SrMMAABQl4TuX6u4uDilpqZaHQWoElbDhiVcLpck6bgvC3wBAADUJX/o2VnDW8TJZrNZHQWoEpplWOLkatjHfQMtTgIAAIDqEuAj/WP8GNl9aZRR+3EZNixxcmbZ7UOzDAAAUFe0LT+opd9+o9LSUqujAFVGswxLxMbG6g+DL1KZr7/VUQAAAFBNwn7+Un/+85+tjgFUC5plWGLEiBGa9/lXVscAAABANTq+bZV69OwpPz/u9kTtR7MMSxQUFOiIq8DqGAAAAKgu5eXauXaZ+rFlFOoImmVY4p577tHgXl2tjgEAAIBq0rRgv44eOcL+yqgzuD4ClnC5XAoMDrU6BgAAAKpJ++ASOXr3Vs+ePa2OAlQLZpZhCbfbrYCgYKtjAAAAoJqMHtRbS77/QaGhTIigbqBZhiVcLpf8gkKsjgEAAIBqkpS3V74yrI4BVBuaZVjC5XbLL5CZZQAAgLogvvCgBnfroA8//NDqKEC14Z5lWOJ/H8zT3B15Wr6hzOooAAAAqKKmBzYoR1KfPn2sjgJUG2aWYYkGDcJkBIdbHQMAAADVwH/PKjVLTZXD4bA6ClBtmFmGJSbecJ2ON+8txQ62OgoAAACq6MDGleyvjDqHmWVY4ovPP1eOc7/VMQAAAFBFDWwlKj3uZn9l1DnMLMMSbrdbRgALfAEAANR2vZLC9PXOnSovL7c6ClCtmFmG15WXl6ugoEDldpplAACA2q5npFRSbsjHh9YCdQt/ouF1BQUFkqQy/yCLkwAAAKCqPpn6F02++SarYwDVjmYZXufr66unnnpK9qbtrY4CAACAKvArL9b2davUvHlzq6MA1Y5mGV4XFBSkW265RYprYnUUAAAAVEGLvJ06fvw4i3uhTmKBL3jd4cOHtXDhQuWWXiCJS7EBAABqq1jnWgUFBalTp05WRwGqHTPL8Lpt27bpr3/9q/IPZlsdBQAAAFVQumeDevTsKX9/f6ujANWOmWV4ndvtliQd9wm0OAkAAACq4qP3/qsyV67VMQBT0CzD61wulyTpuD9bRwEAANRWLcP9FRNil0LirY4CmILLsOF1J2eW3cwsAwAA1Frx6z/SgAEDVFZWZnUUwBQ0y/C6Bg0aqGvXrirxCbA6CgAAAM5T2bZlysvPl6+vr9VRAFPQLMPrRo0apcU/rZBsNqujAAAA4Dw5169QP7aMQh1GswyvMwxDBaWG1TEAAABwnmKLDmn/3t3sr4w6jWYZXvePf/xDfTu3tzoGAAAAzlOzAxskiWYZdRrNMrzO7XbLN8BudQwAAACcp1EXD9WXXy9UYmKi1VEA07B1FLzO5XIpIIhtowAAAGqrYc3jdEFUstUxAFMxswyvc7vdCggKsToGAAAAzkNIWYEemHS1Nm/ebHUUwFQ0y/C6Yy6XfAOZWQYAAKiNWhzepHkffMCWUajzuAwbXvfyq69p3p5jWrHd6iQAAAA4V2H71yg6OlqtWrWyOgpgKmaW4XUJCYmyR7MYBAAAQG2Uv2WVevfpI5vNZnUUwFQ0y/C626fcpmVffmh1DAAAAJwj37ISbV+3Uhf262d1FMB0NMvwuvf/956cO7dZHQMAAADnqGOUr55//nn96U9/sjoKYDruWYbXud1uGfYgq2MAAADgHF3YKEJje4yTL5dgox5gZhleZRiGXC6XygPYOgoAAKC2KVz8jr5d9K3VMQCvoFmGVxUWFsowDJX5M7MMAABQqxiGPnjqAX23ZLHVSQCvoFmGV9lsNt1///0KbNLG6igAAAA4B42PO3XwwAH17dvX6iiAV9Asw6sCAwN13333ySeppdVRAAAAcA6SM9fJZrOpV69eVkcBvIIFvuBVeXl5WrZsmfLym0gKsDoOAAAAfq9dq3VBhw4KDw+3OgngFcwsw6u2bdum4cOHKzczzeooAAAAOAd/HNhPN06aZHUMwGuYWYZXuVwuSVKhHwt8AQAA1BZxQT66c8JEq2MAXlVvZpaXLl2qkSNHKjExUTabTR999FGF8/Pnz9fQoUMVExMjm82m9evXn/IaAwYMkM1mq/Bz5ZVXes7v27dP119/vZo0aaKgoCA1a9ZM06dPV3FxcYXXSUtL08iRIxUSEqKYmBhNnjz5lDEbN25U//79FRQUpKSkJM2cOVOGYVRbPazidrslScdplgEAAGqNC4rStGTJkjrx+yjwe9WbmWW3260OHTro2muv1aWXXnra83369NHll1+uCRMmnPF1JkyYoJkzZ3oeBwX9X9O3bds2lZeX68UXX1Rqaqo2bdqkCRMmyO126/HHH5cklZWVacSIEYqNjdUPP/ygw4cPa9y4cTIMQ88++6wkKT8/XxdddJEGDhyoVatWaceOHRo/frxCQkI0derU6iqJJU7OLBf40iwDAADUFiXfvavxD36hfXv3Wh0F8Jp60ywPHz5cw4cPP+P5sWPHSjoxO3w2wcHBcjgcpz03bNgwDRs2zPO4adOm2r59u/7zn/94muUFCxZoy5YtSk9PV2JioiTpiSee0Pjx4zVr1iyFhYVp7ty5Kiws1Jw5c2S329WuXTvt2LFDs2fP1pQpU2Sz2c7lo9codrtdTZs21R6b3eooAAAA+J0OblyhfmwZhXqm3lyGXV3mzp2rmJgYtW3bVrfffruOHTt21vF5eXmKioryPF62bJnatWvnaZQlaejQoSoqKtKaNWs8Y/r37y+73V5hTGZm5lmb+aKiIuXn51f4KSoqOs9Pao5LL71Um7bvlHz4owcAAFAbBJcWaPvG9eyvjHqHjuUcXHXVVXrnnXe0ZMkS3XvvvZo3b55Gjx59xvG7d+/Ws88+q0m/WjUwOztb8fHxFcZFRkYqICBA2dnZZxxz8vHJMafz8MMPKzw8vMLPww8/fM6f02wFpdzrAgAAUFu0OLJZZWVl6tevn9VRAK+qN5dhV4df38vcrl07NW/eXF27dtXatWvVuXPnCmMzMzM1bNgwXX755brhhhsqnDvdZdSGYVQ4XnnMycUUznYJ9rRp0zRlypQKx349O10TzJgxQx9++pk06X2rowAAAOB3aBNmU+SgQWrVqpXVUQCvYma5Cjp37ix/f3/t3LmzwvHMzEwNHDhQvXr10ksvvVThnMPhOGV2+OjRoyopKfHMHp9uzIEDByTplBnnX7Pb7QoLC6vwU9Oa5SNHjqiwsGZdGg4AAIAzu270H/XNN9/Ih9voUM/wJ74KNm/erJKSEiUkJHiOZWRkaMCAAercubNef/31U/5S6dWrlzZt2qSsrCzPsQULFshut6tLly6eMUuXLq2wndSCBQuUmJiolJQUcz+UyVwul+zBIVbHAAAAwO/gU16qqCN7VHuXlwXOX71pll0ul9avX+/ZP3nv3r1av3690tLSJJ2Y8Vy/fr22bNkiSdq+fbvWr1/vmeHdvXu3Zs6cqdWrV2vfvn364osvdPnll6tTp07q06ePpBMzygMGDFDDhg31+OOP6+DBg8rOzq4wSzxkyBC1adNGY8eO1bp167Ro0SLdfvvtmjBhgsLCwiRJY8aMkd1u1/jx47Vp0yZ9+OGHeuihh2r9StjSiS26/INolgEAAGqDFsd2qfMF7bRs2TKrowBeV2/uWV69erUGDhzoeXzy3t5x48Zpzpw5+uSTT3Tttdd6zl955ZWSpOnTp2vGjBkKCAjQokWL9PTTT8vlcqlhw4YaMWKEpk+fLl9fX0knZn937dqlXbt2KTk5ucL7n7zn2NfXV59//rluuukm9enTR0FBQRozZoxnaylJCg8P18KFC3XzzTera9euioyM1JQpU065H7k2OuZyyS8o2OoYAAAA+B3inOu091dXQAL1ic042cUBXrB1+w59ut+tf+6PsDoK6qmVoxLVLdauzvMztO5w8W8/AcB56xQdoLWjk6TJz0ufMCsFmGrMIOmh65TyTrr2u0qr7WV7zr9Nfu4j+n7p0mp7TaC2qDeXYaNmaJbaXGENm1kdAwAAAL/FMLR73XL1Y39l1FP15jJs1AwP3D9DGTGtpaAeVkcBAADAWTRWnkr9/NSXZhn1FDPL8Ko5r7+mPZvWWh0DAAAAv2FAi2SlpaVp2LBhVkcBLEGzDK9yuVwy7KyGDQAAUNP1iLKp1LCxvzLqLf7kw6vcbreMgCCrYwAAAOA3PHF5Xz384EyrYwCWoVmG1xQXF6ukpERlAWwdBQAAUJNFFR/V7h3b1aJFC6ujAJahWYbXlJeX67bbbpO9YUurowAAAOAsUg/+LEks7oV6jWYZXhMYGKjZs2fLv0l7q6MAAADgLIL2rlGjRo3UsGFDq6MAlmHrKHiN2+3Wzz//rPxjsZJ8rY4DAACAMzi2cz2zyqj3aJbhNdu2bVPv3r3V/NGvpAjufwEAAKiJgv1s+mHxIrny86yOAliKZhle43K5JElF/qyGDQAAUFN1j7UryB6goNhYq6MAluKeZXiN2+2WJB33pVkGAACoqfy+eUV//vNoq2MAlqNZhtecnFk+7hdocRIAAACcydF1S1VUXGR1DMByNMvwqqioKLl9aJYBAABqIp/yUm1fu1z9WNwLoFmG91xxxRXKPHBIhg+3ygMAANREzY/tkcvlUr9+/ayOAliOZhleVVBabnUEAAAAnEF8xjoFBASoa9euVkcBLEezDK959NFHNeKiP1gdAwAAAGcwbuwYffX1AgUGctscwPWw8JrMzEwdOnjQ6hgAAAA4gz+2TlJcUCOrYwA1AjPL8Bq3262A4BCrYwAAAOA0kguzdev1Y7V//36rowA1As0yvMblcikgiGYZAACgJmqctVbvvPOOGjRoYHUUoEagWYbXuN1u+QUFWx0DAAAAp2HbtUpt2rZVVFSU1VGAGoF7luE10++fqa/T3Fp1wOokAAAAqCzr5xW6aOAAq2MANQYzy/CaCy7ooNiWF1gdAwAAAJVEFudq9/Zt6tu3r9VRgBqDmWV4zVNPPandoU0kn45WRwEAAMCv9ExsoFEvvqhBgwZZHQWoMZhZhtc8/+wz2rbqR6tjAAAAoJKBTWN07fUTlJCQYHUUoMagWYbXuN1uKSDI6hgAAACoJPPjl7Vm1QqrYwA1Cs0yvMblcqnczmrYAAAANUlgWZGef/BurVmzxuooQI1CswyvKCsrU2FhocoDaJYBAABqkhZHt6ikpET9+vWzOgpQo9AswytKS0t17bXXKiAp1eooAAAA+JXItDUKDw9X27ZtrY4C1Cg0y/AKu92u1157TUEtulgdBQAAAL/i3rZKvXr1lq+vr9VRgBqFraPgFYWFhdq7d6/y3YFWRwEAAMAvfGzS6IuHqknDJKujADUOzTK8YuvWrercubNaPfq5FNHa6jgAAACQ1D4yQNNumGp1DKBG4jJseIXb7ZYkFfqxwBcAAEBN0TJvm35atszqGECNxMwyvMLlckmSCv24DBsAAKCmSJ//H009kqllP/1kdRSgxmFmGV5xcma5wJeZZQAAgBrBMLR37TL169vX6iRAjUSzDK8oKiqSr6+vCnztVkcBAACApKTCbGVnZbK/MnAGNMvwijFjxqigqFilPgFWRwEAAICkxtnrJUm9e/e2NghQQ3HPMrymqMzqBAAAADipVXSg4v48WtHR0VZHAWokZpbhFc8//7xG/2mk1TEAAADwi39cf7Xmz/vA6hhAjUWzDK/Yu3ev9uzeZXUMAAAASIpUoXwPpVkdA6jRaJbhFS6XS/agEKtjAAAAQFJq5io1b95c+/btszoKUGPRLMMr3G63AoJplgEAAGqC4H1rlJiYqJSUFKujADUWzTK8wuVyacPyH9Qqd6tiig5L5eVWRwIAAKi3jmxeqT59+8pms1kdBaixWA0bXnHjjTfqo48+0rZ/jJAk+fv76+lX3lCHoX/WFwu/1fcLv5QiE1QYFq9jofE6HJqoQwGRKjcsDg4AAFDH2MuKtG39Gk0YO8bqKECNRrMMr7jooouUk5Mjp9Op9PR0OZ1ODe7VVc3jA7WlKFvv/PilMpxOFRUVSZIuu+wyvfve/7R5f6au/stlColNlD0mUUakQ8Vh8SrvOFQZhYay3KUqF/8iCgAA8Hu1Lc9RRlSU+vbta3UUoEajWYZX2Gw2xcXFKS4uTp07d65w7obrr9MN118nwzB0+PBhOZ1O+fv7y9fHpugAqVPrFkp3OuVcvknO9HQZhqGCggLZbDZ179FDTmeGYhKSFRKXoIDoBKUMv0qF8c21JyNLGUfdOmCPUZmvv0WfHAAAoGYZ0rW9ZmZkys+HCQfgbGiWUWPYbDbFxMQoJibGcywpKUlvvPGG57FhGMrPz/fcX3PL5Mnavn270tPTlZ7ulHP1Ys24/i8aOCBO06c/r5kzZ8pmsyk+3qGYhCR1GfZndR5zs3YfOKrV334lVwOHjgTHKScgWqU+AV7/zAAAAN7WI1Lysdm4Xxn4DTTLqFVsNpvCw8M9j6+66qozjr3hhhvUq1cvOZ1Oz+XfXRtG6frWYVpbsEPPzrqxwvjGKU308eqt2nusVK89/ZjySwwVh8XL3cCho8GxygmKV7GNGWoAAFCLlZfrup7NNevBB3XjjTf+9nigHqNZRp3VsGFDNWzY8LTnenbvpry8PGVkZHgaaZfLpQ7RdrWPCtBT677Thg3rlZub63nOokWL1LFPfz353H/09VdfKjA6QT5RDpWEO1Sc3Fa5ManKcJfpeBmrkgEAgJqpuXuPdh45olatWlkdBajxaJZRb4WFhSksLEytW7eucNzHZtOSJYslndjyKiMjQ+np6ercubMi7L5qHhumtXab0reuUobTqSNHjui2227T7Jtna+XKlRp+8cWKTUhSWFyiAmMSFJDQRMmjJindXaq9e/cp2y9cx32DrPjIAACgnnNkrNdePz/16NHD6ihAjUezDJxFaGioWrZsqZYtW3qOXXPNNbrmmms8jwsKClRSUiJJcjgcun3q1BP3UDudcu5cr8D0bZrz1L2SpNjYC3T80CFFREQoLjFZYfGJGnn7QyqNa6r169YqI+egjobE6UBgnNx+Id79sAAAoM4r27lanbt0UXBwsNVRgBqPZhmool9/2TRq1EjTpk0749h58+Z5ts46+fPXVtFKSYnQxOff1qdz5njGhoWFacKUf2rI9bdq9ZadWvDBf1UWmaDjDeKVGxKnA/ZYHfNvYOZHAwAAdUz21nX6858usToGUCvQLANedOGFF57x3AsvvKD77ruvQiPdrVs39U8KkrHloJ777C1lZ2fLME7cE92yZUut3bRFmQVluvbKy6WgBvKNcqgs4kRDfbxpV2WVB+poUbm3Ph4AAKjBGob4avPGn3X8+HGrowC1As0yUEPY7XY1adJETZo0OeXc0CGDlZmZqZKSEmVlZcnpdKqoqEjBfj5qGio5QvyV7tylfSuXKDMzU+Xl5dq5c6dSUxtr4qQb9c2iRYqIT1JwbIL8ohIU0W2wSpt0Utphl5y5Lh31C5PYPgIAgDqtryNQgYEnfgD8NpploBbx9/dXo0aN1KhRI88xHx8fvf/++57HpaWlys7OlsPhkCQNvWiwGoQEn1j127lfe9b8oDs6pujvQ4frgw8+0OU3X67AwEA5EpMV4UhUUtsu6nPTfXK6S7X626+VFxStQ0GxOuwXIfn4ePsjAwCAanJo7kO64d0CvfLSS1ZHAWoFmmWgjvHz81NycrLn8aWXXqpLL730tGP79OmjefPmebbPcjqdigsu19T24SouLFCDvld7xgYEBMiRlKyn5i1QQYN4fT7/f3JmHVBRWLzyQ+J0KDheh/wjaagBAKih9i9fpIY9u1sdA6g1aJaBeiwhIUGjR48+7Tn/4GBlZ2dXaKSdTqeGt06SX4Bdn61fpBXzPlBxcbHnOU88+aT+MuH/6aOvFmnu66/IP9ohRSaoKNwhd2QjHY5toZzjZSpnK2oAALwqrOSYdm7drLv+cbvVUYBag2YZwGnZbDbFx8crPj5eXbp0OeX8O/+dq/Lyt3To0CFPI922bVslhfipWYihAPchObevV4bTqcLCQg0ePFgbFy7UMZdbrVq3VrQjUaFxSfKPTpAiHYq66Cpll9mVduCwsssDVe7DX08AAFSXFoc2arVhqG/fvlZHAWoNfhsFcN58fHwUFxenuLg4de7c2XN82LBhGjZsmCTJMAwdOXJEBQUFJx6Xl+nacdf8cg+1U86Vm5XhdOrQv25XYGCgBg26WtnffacER4KiE5IUEpugbldMVEDrHtqxN0370tJ0JDheOf5RKvP1t+RzAwBQ24TsXyOHw6GmTZtaHQWoNWiWAZjKZrMpOjpa0dHRkk7sH/3ggw9WGGMYhmy/rMY9ffp0bd++3TNbnZ7u1MWJ/rqoe5Se+ekNTb1zqud14+MdGjBilK64+zHtOXxMn855QSURDrlC43UkOE4HAqJV4mv37gcGAKAGuuO2WxV1w+We71sAv41mGYDlfv3F3b9/f/Xv3/+04yZOnKihQ4f+qpFOV0pKikalBGtX+QE9+PZTysvL84z38fFR5lGXDpT46MHp9yrnSK4+zErR9qaNpPQgKaiZFBJu+ucDAMBKdl+bLmrTUAE+jX57MAAPmmUAtUZoaKjatm2rtm3bnnKuRbMmys3N1bFjx5SRkaH09HQdOHBACWFBSpAUXnhE2zat1H++fF+5ubmSpP/Nm6+eQ0bqmX+/oPffeEXBsQnyjUxQWYRDJSkdlN+spw64S6SSYske5N0PCwBANWmZt10Trp2uJ598UlFRUVbHAWoNmmUAdUqDBg3UqlUrtWrVqsLxV155xfPfLpdLGRkZSkhIUFion4Z0aqn8PT2Vnu5U5t61ynI6NWrUKL0y/S/6efNWdWjXVmGRUYqIT1RQTIL8YpLUbNLDchaUae+mdTpqBEqRDikwxNsfFwCA3xS5+yfNnz9fr776qtVRgFqFZhlAvRMaGqqWLVt6Hl900UW66KKLKowpLy+XJDVMdOitt95Senq60tLT5XRm6LjLqY+HOiRJqXf019Hdu0+8bniEIuITNfKu2fJJ7aKfV63Q/l3blBcSp7wQxy8NdaiXPiUAACcUbFulnj17yc+PX/2Bc8H/YwDgNHx8fCRJkZGRuvrqq884buHChUpLS/PcR52Wnq6bejRR65bRuveLn/T98w9VGP/n8X/TpXc/ro079+iT5/+l8sgEHW8Qr7zQXxrqxBamfi4AQD1TXq6da5frtltvtToJUOvQLANAFTRp0kRNmjQ57blZs2Zp+vTpyszM9DTTjRo1UvemIWqZX67FB3fJuW6JsrKyZBiGHA6HVu5MV5qrVJMuG6HC0nL5RTtUHnGioS5oN0hH7DEySoslX3+JFU0BAL+hWcE+7T56lP2VgfNAswwAJgoICFBKSopSUlIqHO/auaNWrFghSSopKVF2draOHDmihqF+ahjqp2G9u2jPnr3KzNin9A3fKysrSytXrlT7jima9PfJemfOa4pwJCokNlF+UQ6F9xiu0g4XKe1Qrg6l75MiHFJoJA01ANRzfVITdeuzz6pHjx5WRwFqHZplALCYv7+/GjZsqIYNG3qOPfbooxXGlJaWymazydfXpgljx+iCFs2Ulp5+YlGyDKf+EpWvyX9O0sKFWzRk4h8lSQF2uyLikxTfor0unPGKnO4ybfjsHR31DVFeSPyJe6hDo6VfLjkHANQ9F7VqqL+MuFn+PvzjKXCuaJYBoBb49aIsvXr1Uq9evU47rlevXlq5cqVnH+q09HT5+wdoVu9o2SSFX3afjh075hnvHxCgmR9+L1tSCy18f67279iqorB45Z+8hzq2MXtRA0At9vNbs9XxitFq166d1VGAWodmGQDqkNDQUHXr1k3dunU77fnc3FwdPHhQ6enpnvuox/RuqdAGYTr2fpb2rvlSOU6niouLJUlT7p6u0Vfeqa8Wf6e3Hp0u/+gEGREOFYU7dCyqsfJb9JchSeXlzFADQA3jKMzRYw9MV8+O7WiWgfNAswwA9YiPj4/i4+MVHx+vrl27Vjj34IMP6sEHH5RhGDp06JCcTqeio6PVyBEov9Ro7W3XQpkZTjl/3qxD6elq3769fnhknLLcJWoZH6GQiCiFxiXKPzpBikxQyMiblO0XrgPpaSca6fA4yZevHQDwliY5G5QtsbgXcJ74rQUAUIHNZlNsbKxiY2M9x3p066oeb73peWwYhgoKChTga1NikE1PPTnbsw91ZoZTzs1L9M0LDyg2NlZ/GnWrPvn4I/n4+Cg81qHQuES1uXySAnv8Ubv37FHapjXKD4mXIhNONNR+/lZ8bACoc/z2rFHzFi0UFxdndRSgVqJZBgCcM5vNppCQEEknFiibNGnSGcc+/tijmvS3iZ59qJ1Op/7SPVnDhsTrtdc+1/XP/73C615w4UX669PvKS2/WF/NvltFDeJ0LDT+l4baIUUnST6+pn9GAKjtDmxcob59+lgdA6i1aJYBAKZq3ry5mjdvftpz1113nS677DLP/dPp6ekKDgnVpe3C5crP1Xc7l+mw06n8vDzPcz7blK5ce4RefGCa0vfskiIdKgl3nGioG3WRYpIlw2DbLAD1Wpi/TX8ZPeqMC0IC+G00ywAAS4WFhalNmzZq06ZNheNRkZHatGmTJOnYsWOehnpwmySVGdLeFgn66dAeOfetkdPpVP7Ro3rltdc15PJeev7Fl/XvWfcqNC5R9piEE/tON+2sgu6jdMBdKh3cJ0UkSPYgCz4xAJivd3yg7h9/v9UxgFqNZhkAUOM1aNBArVu3VuvWrSVJfjbpnrvvqjDG7XbLx8dHQUF+uvIPvRRaeJvS0tOVmZGhDOfP6poQoJevvkVpGVlqnDxYkhQSHqkG8YmyRyeo3Z0vKbssQLtXLFFuUdmJe6gjE6TAEK9/XgCoqobZ67VyTZy6d+lsdRSg1qJZBgDUCSfvoZakjh07qmPHjqcdFxcdqcWLF3v2oU53OpWTna35I1Nks9nU5cHZWrt2rWd8cINwjb7/OUX0GK71y37Q7lVL5QqN17FQx4l7qKMSpMBQsz8eAJyTlS/N0qHEOM2fN8/qKECtVW82xVy6dKlGjhypxMRE2Ww2ffTRRxXOz58/X0OHDlVMTIxsNpvWr19/ymsMGDBANputws+VV15ZYczRo0c1duxYhYeHKzw8XGPHjlVubm6FMWlpaRo5cqRCQkIUExOjyZMne/Y0PWnjxo3q37+/goKClJSUpJkzZ8owjOooBQDUa4GBgRowYIDGjh2ru++6Sy/8+9/6cP582X65x/nHH3/U7t279d1332nu3Lm69+5pumNIFz3dK0pXhWTJ+O6/cr12p/T0OGnGUA1YMF1vD4zV3c1K1PDl69Ro3t1K+OYZNVj+nrRxyYk9qAHAi/zLirR9/Wpd2K+f1VGAWq3ezCy73W516NBB1157rS699NLTnu/Tp48uv/xyTZgw4YyvM2HCBM2cOdPzOCio4v1uY8aMkdPp1FdffSVJmjhxosaOHatPP/1UklRWVqYRI0YoNjZWP/zwgw4fPqxx48bJMAw9++yzkqT8/HxddNFFGjhwoFatWqUdO3Zo/PjxCgkJ0dSpU6tcCwDAmQUGBqpp06Zq2rTpKecmTZqkSZMmqbi4WFlZWXI6nQoODlb7piHa52vXloZRynDulnPjd3JlZSkoMFDbcvKU7i7TdSMH6eihQ7LHJMj2y6Jkxd1H6WhEigx3niRDCg5nYTIAVdYib4c2FxayvzJQRfWmWR4+fLiGDx9+xvNjx46VJO3bt++srxMcHCyHw3Hac1u3btVXX32l5cuXq0ePHpKkl19+Wb169dL27dvVsmVLLViwQFu2bFF6eroSExMlSU888YTGjx+vWbNmKSwsTHPnzlVhYaHmzJkju92udu3aaceOHZo9e7amTJnimf0AAFgjICBAjRs3VuPGjT3HUps0rnC5Y0lJiQ4ePKjEBv5q1MBft1x3jbZv367MzAxlONOVvvUnvXPzn9W7X4ruuOsePfPoQwoIDFLYL4uSRfW6WAF/uEb7D+Xq0IZlJy75jnRIoVE01ADOKtq5TiEhIWe8HQXA71NvmuXqMnfuXL399tuKj4/X8OHDNX36dDVo0ECStGzZMoWHh3saZUnq2bOnwsPD9dNPP6lly5ZatmyZ2rVr52mUJWno0KEqKirSmjVrNHDgQC1btkz9+/eX3W6vMGbatGnat2+fmjRpctpsRUVFKioqqnDMbrdXeB0AgHf4+/tX+Lv+phvPvBf13ydcqwu7d9b+9HSlp6UrMzND/Vo10P/7c5JWrHCq58T/u+LJP8Cu6MbNdNmcpUp3lWrdey+q3OYj/+gEBUQnyD8mUX5h0bL5WH+n1bDkX66+umG49Mee1oYB6rrkGEnSS/2itTIrSs2vvFJ+fvyqD1QF/w86B1dddZWaNGkih8OhTZs2adq0adqwYYMWLlwoScrOzlZcXNwpz4uLi1N2drZnTHx8fIXzkZGRCggIqDAmJSWlwpiTz8nOzj5js/zwww/r/vsrbhEwffp0zZgx45w/KwDAe1JTU5Wamnrac926dVNmZqZnH+r96ek6XnBcd/aKko/Npm53f6oNGzaopKTE85xvv/1WAwcO1GuvvaZvvvlGycnJSk5OVsOGDdW+ffszvpcZissMbUhIkhKSvPaeQH0UF2hTY0lDkoM1ZMrfrY4D1Ak0y+fg1/cyt2vXTs2bN1fXrl21du1ade58Yln+010ibRhGhePnM+bk4l5nuwR72rRpmjJlSoVjzCoDQO3m4+OjhIQEJSQkqFu3bqecX7VqlcrLy3Xw4EE5nU6lpaerbfsOKi03VFpaqszMTK1cuVJOp1NFRUW68ZbbNPGeh7Vk+Uo9MPEqhcQlKCA6Uf7RCQpNaqLmI8dJkgqPHlRAWKR8fM//V4WJrRooNcxf3T/KPO/XAPD7/K1VqF7oF6vLP96hbg1KNGVAG/n5cMsGUBU0y1XQuXNn+fv7a+fOnercubMcDodycnJOGXfw4EHPzLDD4dCKFSsqnD969KhKSkoqjDk5y3zSgQMHJOmUWelf45JrAKiffHx8FB8fr/j4eHXp0sVzfOLEiZo4caKkE//oevjwYZUbhiIiAxTcKlEHrx3rmbFOX79Z7m3BGnPbzdp7rET/GH2hio7lyS8yTuURDpWFO6TRd0hxKVLGdqnQdWIf6vA46QwN9R8Sg5Qa5u+NEgD4xYovP9SHr9ytSUePKuyXWwUBnB+a5SrYvHmzSkpKlJCQIEnq1auX8vLytHLlSnXv3l2StGLFCuXl5al3796eMbNmzVJWVpbneQsWLJDdbvf8gtOrVy/dddddKi4uVkBAgGdMYmLiKZdnAwDwe9hsNsXExHget0htplmzZp0yrtwwVFoepMZvvaGszAw5nU45nU7tT0/X3SOTdDwiXg9MvlsrP37nxBN8fGQLi5UxdKL0h2ulQ+nS2q+kCId2BrdSu/Km8isvU6lPgLc+KlCvFe9YrY4dO9IoA9XAZtSTzXtdLpd27dolSerUqZNmz56tgQMHKioqSo0aNdKRI0eUlpamzMxMjRgxQu+++65atmwph8Mhh8Oh3bt3a+7cubr44osVExOjLVu2aOrUqQoKCtKqVavk6+sr6cSq25mZmXrxxRclnfhX/caNG1fYOqpjx46Kj4/XY489piNHjmj8+PEaNWqUZ+uovLw8tWzZUoMGDdJdd92lnTt3avz48brvvvvYOgoAYKlyw9CR3Hw509OU/UsznZ6erq69eqt5z4F675Mv9MjN41Toyvc8p1WrVvp+3SY53aW65fpxUkiYbJEJKg6Ll6uBQ/mJ7ZRV6q9itqQGztvJy7CjklN0zWWj9NRTT1kdCaj16k2zvGTJEg0cOPCU4+PGjdOcOXM0Z84cXXvttaecP7lAVnp6uq6++mpt2rRJLpdLDRs21IgRIzR9+nRFRUV5xh85ckSTJ0/WJ598Ikm65JJL9NxzzykiIsIzJi0tTTfddJO+/fZbBQUFacyYMXr88ccrXEK9ceNG3XzzzVq5cqUiIyM1adIk3XfffWwbBQCo0U7MTEuuY/nKycpUenq6ysrKNHz4cJWWluqPI0eemK1OT1deXp4kadeuXWrWrJn+9v8m6/vvf1CDX7bP8ol0KLjDABUktVF6rlsZrlIV+XK7EXA6f2sVqvualSgpKUnvvPc/XXnF5VZHAmq9etMsAwCAmuXYsWPKyMhQamqq/Pz89Pbbb+uHH35QWnq6nE6nMpxOTZ8+XZMnT9b777+vK664QlHR0YpNSFJYfJLiW3fWBddMkdNdpo3LlupIULQOBMbpuG+Q1R8N8Lq/tQrV1bbtGjVqlDZu3Oi53Q/A+aNZBgAANdbJ3SLS0tL03XffKf2XRjrd6VRiUpKee/7fKik8rpCQEM9zIiIjFZeQpOlvfaJjQdFa9MWnyjx4WAUN4pQb4lCOPVYFfsEWfiqg+p28DLvyDisAzh8LfAEAgBrr5C/9jRo10tixY087xjcwULt27fI00id/RrdJkI+/XV/eNU8/fvRhhec88cxzGjF2oj79ZrE+fneufKIcKo9MUEGDeOWHJ+tAg4bKL2E+AbVLYWGhAux20SoD1YNmGQAA1Go+Pj5q1qyZmjVrdtrzH304X0VFRcrMzPQ00l26dFGLCH9t8z+uwv1blfHTQmVnZ8swDF100UXauWCBDuQeU68e3RThSFZQTIL8ohwqC09QUN8/K6vUX+lH3coz/CVm8VADFLuPKTw8WW/P/a8uv+xSq+MAdQKXYQMAAEgqKSlRVlaWiouLlZqaqtzcXM2YMcNz2bczPV05OTlyu92y2+0aOHCgVq1apfjEJEXEJykoNkFtLhknn9TO2rnfqfTsgzoYFKtcvzAaapjuT67V+njKFdq2bZtatmxpdRygTmBmGQAAQJK/v78aNWrkeRwREXHK9julpaXy8zvx69M///lPbd261bN9Vrpzry6JK9fFfaI1e/kc3XHHHZKkwMBAORKT1WvYJRp26wztPeTSog/eUmEDh/JC43QoKFZH/CNpqFElhdtXKSYmRi1atLA6ClBnMLMMAABQzY4ePaqdO3d6Gmmn06nU1FRdN2Gidu7cpQ7t2qi0tNQzPjAwUJsyjyiryKan/vWQDuXmqzzSoaIwh/JD43UoorEOG0HilzacSac3rlWj2Eh99OGHvz0YwO/CzDIAAEA1i4yMVPfu3dW9e/dTzrVp2VxFRUXKycnx3EN98OBBNYsMUjNJz+fs1v7ly5SZkaHi4mJJ0ocffqgRl/xJT7/wst568w2FxCTKP9ohRSVKjdvpeEpnpR8rUc7xUhk2Xy9/WljN1yjTnk3rddW991odBahTmFkGAACogcrLy3Xo0CE5nU41adJEkZGR+uyzz/Tee++duIf6l72or776ar388svatm2b2rVrp/iEREUnJCkkNlH22CR1mHifMgrKtGPbVh00gnTAHq1yGuo6pXusXYuHRKi0tFRhYWFWxwHqDJplAACAWsowDBUVFSkwMFCHDh3S+++/75mtTnc6VXi8UN//8IN8fWxq1qyZ9uzZI19fX8U7EhTlSNKYex5VYLMOWr1qpfbs2StXg3gdDorTgYBolfn6W/3x8DtNaR+mR7tHydeH+96B6kSzDAAAUA9s2rRJaWlpFfaivv2Ofyi1RUv9846peurJJz1jbTabJv6/yZpw37+0evs+/fc/T0qRCSoJj9exkHgdDYnXgZAElZRb+IHgMWjhdHVPTdbDDz1kdRSgTqFZBgAAqOcMw1B+fv7/zUqnpys1NVUDBgzQylWrNX78OGU4ncrPz5ckJSQkKDMzU4cLy3TZ6D+roMxQYEyCbJEJKg6Ll9peqGzfcDldJSoxmO00lWEo+u4euunGGzVz5kyr0wB1Cgt8AQAA1HM2m03h4eEKDw9X27ZtK5zr3q2rtmzeLEmehjovL0+SFB3oq7ZNG2n3nj1K/3mZMpxO5ebmas2aNercuaFuueUW/feddxSTkKQGcYkKjE6Qo+cQ2TsM1L5DeUrLyFSOPVZFfoFe/8x1RUpBuvYdOqS+fftaHQWoc2iWAQAA8LuEhYWpTZs2FY4999xzFR67XC4FBp5ofkeNGqW4uLhf9qF2yrlttUZ2a607Bsbq66/XatgVwyRJkVFRiktMVnKr9rps5r+V7irVD59/qHz/BsoNiVdOYKyO+wZ550PWMslZ65Tm46OePXtaHQWoc7gMGwAAAF6Xm5urdevWefahdjqdCgwM1COPPSHJUIPgIM/WWZIUERmpt75cLN/E5pr/v3e1c8dOlUY4VBAWr9zgeB0Ijpfbp/411H2+vFfufVu0bu1aq6MAdQ4zywAAAPC6iIgIDRw48AxnbcrLy1NGRkaFBcn6tUpRWFiQFmRs1raP5yonJ8fzjAceeEC3/vMufbroez3+8AMKjk2Sb5RDZREOFcY0VkHT7nK6SpVfUrfmiZ54+EH5u49YHQOok5hZBgAAQK1UXFyszMxMOZ1OJSYmqmnTplq2bJkee+wxpac7lZHhVHZ2trp3767ly5ervLxccXFxioiJVXh8koJiEuQX5VCjURN10KeB9jozlFXir3y/UMlW8xcmcwT5KuvqRlbHAOosmmUAAADUWSUlJcrLy1NMTIyKi4v17LPPVtiL2pmernXr1ik2NlajRo3Sxx9/rODgYMUnJikiPkl9x/xNcb2GaeuefdqxeaPyguN1MChWuf7hljfUfY+sUsudC/Sf//xH/v7siw1UN5plAAAAQNLGjRu1fft2z/ZZTqdTV429RsOGX6w5r72iv02c6BkbGBiogcMu1j///bb25hVpzqMzVR7pUGEDh/JD43QwKE5H/CNMbagv/O5RpS9boD27d5v2HkB9RrMMAAAA/IaysjLl5ORUaKQjIyM1duxYHTh8RD26dVVmRoZKSko8z8nMOaiS4Ajdc/fd2r13n/yiHTIiHCoKT9Dx5HY6EBinA8fLdL6/jLd+/jJ169BOb7zxRvV8SAAVsMAXAAAA8Bt8fX2VmJioxMREde/evcK5+Jho7du7V+Xl5Tpw4IDnMm9HbLRsNpsahwVoX1620jevVobTqeLiYs2ZM0fjru6qV159TffPnKkoR6JCYpPkH+1QcPNOCuoxQunHipWWkaWD9igZNt8K7xlS6tb2jet1282TvFkGoF5hZhkAAADwEsMwdOjQIQUGBqpBgwZasWKFPvroo/+7h9rpVK9evfTWm28qKytLiYmJ8vX1VXxCoqIdiQqJS9KfZvxbGRtX6I1br9aKFSvUunVrqz8WUCfRLAMAAAA1UEFBgb799tsK22dlZ+fo488+V3lpicZdc43ee+9d2WrByt1AbUSzDAAAANRChmHQKAMm8rE6AAAAAIBzR6MMmItmGQAAAACASmiWAQAAAACohGYZAAAAAIBKaJYBAAAAAKiEZhkAAAAAgEpolgEAAAAAqIRmGQAAAACASmiWAQAAAACohGYZAAAAAIBKaJYBAAAAAKiEZhkAAAAAgEpolgEAAAAAqIRmGQAAAACASmiWAQAAAACohGYZAAAAAIBKaJYBAAAAAKiEZhkAAAAAgEpolgEAAAAAqIRmGQAAAACASmiWAQAAAACohGYZAAAAAIBKaJYBAAAAAKiEZhkAAAAAgEpolnHOioqKNGPGDBUVFVkdpU6ivuaivuaivuaivuaivuaivuaivuajxvWPzTAMw+oQqF3y8/MVHh6uvLw8hYWFWR2nzqG+5qK+5qK+5qK+5qK+5qK+5qK+5qPG9Q8zywAAAAAAVEKzDAAAAABAJTTLAAAAAABUQrOMc2a32zV9+nTZ7Xaro9RJ1Ndc1Ndc1Ndc1Ndc1Ndc1Ndc1Nd81Lj+YYEvAAAAAAAqYWYZAAAAAIBKaJYBAAAAAKiEZhkAAAAAgEpolgEAAAAAqIRmGQAAAACASvysDoDaYf/+/crOzpbNZlN8fLwaN25sdaQ6hxqbi/qai/qai/qai/qai/qai/qai/rWcwZwFrNnzzaSk5MNHx8fw2azGTabzfDx8TGSk5ONJ5980up4dQI1Nhf1NRf1NRf1NRf1NRf1NRf1NRf1hWEYBs0yzmjmzJlGWFiY8cgjjxjr1q0zMjMzjYyMDGPdunXGI488YoSHhxsPPPCA1TFrNWpsLuprLuprLuprLuprLuprLuprLuqLk2iWcUbJycnGhx9+eMbz8+fPNxITE70XqA6ixuaivuaivuaivuaivuaivuaivuaivjiJBb5wRocPH1bLli3PeL5FixY6evSoFxPVPdTYXNTXXNTXXNTXXNTXXNTXXNTXXNQXJ9Es44y6d++uWbNmqbS09JRzpaWleuihh9S9e3cLktUd1Nhc1Ndc1Ndc1Ndc1Ndc1Ndc1Ndc1Bcn2QzDMKwOgZpp48aNGjJkiIqKitS/f3/Fx8fLZrMpOztbS5culd1u18KFC9W2bVuro9Za1Nhc1Ndc1Ndc1Ndc1Ndc1Ndc1Ndc1Bcn0SzjrI4dO6a3335by5cvV3Z2tiTJ4XCoV69eGjNmjMLCwixOWPtRY3NRX3NRX3NRX3NRX3NRX3NRX3NRX0g0ywAAAAAAnMLP6gCo+Vwul9asWePZkN3hcKhz584KDQ21OlqdQY3NRX3NRX3NRX3NRX3NRX3NRX3NRX3B1lE4o5KSEmPy5MlGUFCQYbPZDLvdbgQEBBg2m80ICgoybrnlFqO4uNjqmLUaNTYX9TUX9TUX9TUX9TUX9TUX9TUX9cVJNMs4o8mTJxtJSUnGu+++axw9etRz/OjRo8a7775rNGzY0Ljlllssy1cXUGNzUV9zUV9zUV9zUV9zUV9zUV9zUV+cRLOMM4qJiTEWLVp0xvPffPONERMT48VEdQ81Nhf1NRf1NRf1NRf1NRf1NRf1NRf1xUnss4wzOn78uGJiYs54Pjo6WsePH/diorqHGpuL+pqL+pqL+pqL+pqL+pqL+pqL+uIkVsPGGY0cOVLHjx/X3LlzFR8fX+FcTk6Oxo4dq8DAQH3yyScWJaz9qLG5qK+5qK+5qK+5qK+5qK+5qK+5qC9OolnGGaWnp+viiy/Wtm3b1K5duwobsm/atElt2rTR559/ruTkZKuj1lrU2FzU11zU11zU11zU11zU11zU11zUFyfRLOOsysvL9fXXX592Q/YhQ4bIx4cr+auKGpuL+pqL+pqL+pqL+pqL+pqL+pqL+kKiWQYAAAAA4BR+VgdA7ZGbm6v3339faWlpaty4sS6//HKFh4dbHavWO3DggDZv3qwuXbooLCxMOTk5euONN1ReXq4RI0aoffv2Vkes9Xbu3KmffvpJ2dnZstlsio+PV+/evdW8eXOrowHn7Nprr9WsWbOUmJhodZQ6he+46sf3m/n4fgPMxcwyzuiyyy7TmDFjNHr0aG3ZskX9+/eXzWZT06ZNtW/fPtlsNn377bdq3bq11VFrrSVLluiPf/yjCgoK5HA49NVXX2nEiBEKCgqSj4+P9u3bp08++URDhgyxOmqtlJeXp2uuuUaffvqpwsPDFRcXJ8MwdPDgQeXn52vkyJF68803FRYWZnXUWqmkpER333235s+fr6ioKN1444269tprPedzcnKUmJiosrIyC1PWXj///PNpj3ft2lX/+9//1LRpU0nSBRdc4M1YdQbfcebi+81cfL+Zi+83eFizYxVqg5iYGGPHjh2GYRjG8OHDjTFjxhhFRUWGYRhGcXGxcf311xtDhgyxMmKt16dPH+Pmm282jh07Zjz22GNGcnKycfPNN3vO33777Ubv3r0tTFi7jR071mjfvr2xfPnyU84tX77cuOCCC4xrrrnGgmR1w/Tp0434+HjjscceM+6++24jPDzcmDhxoud8dna2YbPZLExYu9lsNsPHx8ew2Wyn/Jw87uPjY3XMWovvOHPx/WYuvt/MxfcbTqJZxhkFBQUZu3btMgzDMBISEoy1a9dWOL99+3YjPDzcgmR1R1hYmKfGJSUlhp+fn7Fu3TrP+R07dlDjKggPDz/tLxInLVu2jPpWQWpqqvHpp596Hu/atcto3ry5MX78eKO8vNzIzs6mmauCDh06GCNGjDC2bt1q7Nu3z9i3b5+xd+9ew8/Pz1i4cKHnGM4P33Hm4vvNXHy/mYvvN5zEMm44owsuuEDffvutpBOr/+3fv7/C+f379ysoKMiKaHVGQECACgsLJUnFxcUqLy/3PJak48ePy9/f36p4dYLNZjuvc/htGRkZateunedxs2bNtGTJEi1btkxjx47l8rQqWrlypVJTU3XppZfqyJEjaty4sVJSUiRJiYmJaty4sRo3bmxtyFqM7zhz8f1mPr7fzMP3G06iWcYZ3Xvvvbrzzjs1Z84cTZ48WbfddpteffVV/fTTT3r99dd1/fXXa+zYsVbHrNX69OmjO++8Uz/++KNuu+02de7cWQ8++KDcbrcKCgr0wAMPqGvXrlbHrLVGjhypCRMmaPXq1aecW716tSZNmqRLLrnEgmR1g8Ph0O7duyscS0xM1LfffqtVq1Zp3LhxFiWrGwICAvTUU0/p8ccf1yWXXKKHH35Y5eXlVseqM/iOMxffb+bi+81cfL/Bw+qpbdRsH3zwgZGcnHzKfXOBgYHGrbfeapSWllodsVbbsWOHkZqaathsNqNt27ZGRkaGcckllxh+fn6Gn5+fERsba6xZs8bqmLXW0aNHjWHDhhk2m82IjIw0WrZsabRq1cqIjIw0fHx8jOHDhxtHjx61Omatdf311xvXXXfdac85nU4jNTWVy9SqSXZ2tjF8+HCjb9++hp+fn7F582arI9UJfMeZh+83c/H9Zi6+33ASq2HjN5WVlWnt2rXas2ePysvLlZCQoC5duqhBgwZWR6szDh8+rOjoaM/jRYsW6fjx4+rVq1eF4zg/27Zt07Jly5SdnS3pxL8Y9+rVS61atbI4We22f/9+bdu2TUOHDj3t+aysLC1YsIB/ga9GzzzzjBYvXqxnn31WycnJVsepE/iOMxffb+baunWrli9fzvdbNeP7DSfRLAMAAAAAUAn3LOOMioqKVFJS4nm8e/du3X333Ro7dqzuuece7d2718J0dQM1Nte8efNUUFBgdYw6i/qai/qai/qai/qab8OGDXr99dc9vyts3rxZN910kyZNmqSvv/7a4nS1H/WFRLOMsxg+fLg+/fRTSdKPP/6otm3b6rPPPlNJSYm++OILtWvXTsuWLbM4Ze1Gjc11+eWXy+FwaOLEiVqxYoXVceoc6msu6msu6msu6muuefPmqUuXLrrjjjvUoUMHLVq0SH379tXOnTu1b98+jRgxQv/973+tjllrUV94WHvLNGqyiIgIzx6J/fv3N2677bYK5++55x6jT58+VkSrM6ixuWw2mzFz5kyjU6dOnkVmnnzySePQoUNWR6sTqK+5qK+5qK+5qK+5OnfubDz44IOGYRjGO++8Y0RERBgzZ870nH/88ceNjh07WhWv1qO+OIlmGWcUEhJibN261TAMw4iPjzfWr19f4fyuXbuM0NBQK6LVGdTYXDabzcjJyTEMwzBWr15t3HjjjUZERIRht9uNyy+/3FiwYIHFCWs36msu6msu6msu6muukJAQY+/evYZhGEZ5ebnh7+9v/Pzzz57zu3fv5veHKqC+OInLsHFGPXr08Fwi3KxZM23YsKHC+fXr1ysqKsqKaHUGNfaeLl266N///reysrL08ssv6+DBgxo2bJhSUlKsjlYnUF9zUV9zUV9zUd/q16BBAx0+fFiSlJubq9LSUs9j6cQq5KGhoVbFq/WoL05iNWyc0bJlyzR8+HDdeuutiomJ0f33369JkyapdevW2r59u5555hlNmzZN//jHP6yOWmtRY3P5+voqKytLcXFxpz2/a9cuvf7665o1a5aXk9UN1Ndc1Ndc1Ndc1NdcY8eO1c6dO/X3v/9d7733nkpKSpSbm6vXX39dNptNf/vb3xQbG6v333/f6qi1EvXFSTTLOKtly5ZpypQppyzOkZiYqDvuuEO33HKLRcnqDmpsHh8fH2VnZ5/xlzVUDfU1F/U1F/U1F/U1V05Ojq6++motX75c/fr107vvvqu7775bzz//vGw2m5o1a6Yvv/xSzZo1szpqrUR9cRLNMn6XgwcPas+ePSovL1dCQgKXTpmAGle//fv3q1GjRrLZbFZHqZOor7mor7mor7morzX27NmjgoICtWrVSn5+flbHqXOob/1DswwAAAAAQCX8kwjO6vDhw/r555/VoUMHRUVF6dChQ3r11VdVVFSkyy+/XK1bt7Y6Yq1Hjc1Ffc1Ffc1Ffc1Ffc1Ffc1Ffc1FfSGJfZZxZitWrDDCw8MNm81mREZGGqtXrzaaNGliNG/e3EhNTTWCgoKMNWvWWB2zVqPG5qK+5qK+5qK+5qK+5qK+5qK+5qK+OIlmGWc0ePBg44YbbjDy8/ONxx57zEhOTjZuuOEGz/nrr7/eGDVqlIUJaz9qbC7qay7qay7qay7qay7qay7qay7qi5NolnFGkZGRxpYtWwzDMIzi4mLDx8fHWLFihef82rVrjaSkJKvi1QnU2FzU11zU11zU11zU11zU11zU11zUFyf5WH0ZOGqu4uJiBQUFSZL8/f0VHBysmJgYz/no6OgKG7Tj3FFjc1Ffc1Ffc1Ffc1Ffc1Ffc1Ffc1FfnESzjDNq2LCh9uzZ43n87rvvKiEhwfM4Kyurwl8cOHfU2FzU11zU11zU11zU11zU11zU11zUFyexGjbO6Morr9SBAwc8j0eMGFHh/CeffKLu3bt7O1adQo3NRX3NRX3NRX3NRX3NRX3NRX3NRX1xEvss45wZhiGbzaaCggL5+vrKbrdbHanOocbmor7mor7mor7mor7mor7mor7mor71D5dh45zZ7XZt3bpVwcHB/CVhEmpsLuprLuprLuprLuprLuprLuprLupb/3AZNs5oypQppz1eVlamRx55RNHR0ZKk2bNnezNWnUKNzUV9zUV9zUV9zUV9zUV9zUV9zUV9cRLNMs7oqaeeUocOHRQREVHhuGEY2rp1q0JCQmSz2awJV0dQY3NRX3NRX3NRX3NRX3NRX3NRX3NRX3h4d6cq1CYPPfSQ0aRJE2PRokUVjvv5+RmbN2+2KFXdQo3NRX3NRX3NRX3NRX3NRX3NRX3NRX1xEs0yzmrlypVGixYtjKlTpxrFxcWGYfAXRXWjxuaivuaivuaivuaivuaivuaivuaivjAMw2CBL5xVt27dtGbNGh08eFBdu3bVxo0bueykmlFjc1Ffc1Ffc1Ffc1Ffc1Ffc1Ffc1FfSNyzjN8hNDRUb7zxht59911ddNFFKisrszpSnUONzUV9zUV9zUV9zUV9zUV9zUV9zUV9wT7LOCdOp1Nr1qzR4MGDFRISYnWcOokam4v6mov6mov6mov6mov6mov6mov61k80ywAAAAAAVMI9ywAAAAAAVEKzDAAAAABAJTTLAAAAAABUQrMMAAAAAEAlNMsAAAAAAFRCswwAAAAAQCU0ywAAAAAAVEKzDAAAAABAJTTLAAAAAABUQrMMAAAAAEAlNMsAAAAAAFRCswwAAAAAQCU0ywAAAAAAVEKzDAAAAABAJTTLAAAAAABUQrMMAAAAAEAlNMsAAAAAAFRCswwAAAAAQCU0ywAAAAAAVEKzDAAAAABAJTTLAAAAAABUQrMMAAAAAEAlNMsAAAAAAFRCswwAAAAAQCU0ywAAAAAAVEKzDAAAAABAJTTLAADUY0uWLJHNZtOMGTOsjgIAQI1CswwAgEn27dsnm8121p+OHTuansNms2nAgAGmvw8AAHWJn9UBAACo65o1a6arr776tOccDoeX01TUvXt3bd26VTExMZbmAACgpqFZBgDAZKmpqTX2Mufg4GC1atXK6hgAANQ4XIYNAEAN8eGHH+qvf/2rUlNTFRwcrPDwcPXr10/z5s077fjFixdr+PDhSkxMlN1uV2JiogYMGKBXXnlF0v/djyxJ3333XYXLv+fMmVNhTOVmPiUlRSkpKXK73ZoyZYqSkpJkt9t1wQUX6IMPPjhtnn379ukvf/mLoqKiFBoaqv79+2vp0qWaMWOGbDablixZUi11AgDAG5hZBgCghpg2bZoCAgLUt29fJSQk6ODBg/rkk0902WWX6ZlnntHf//53z9jPP/9cI0eOVEREhP70pz95xq9fv15z587VDTfcoJSUFE2fPl3333+/GjdurPHjx3ue/3vulS4pKdGQIUN05MgRjR49WgUFBXr33Xd1xRVX6KuvvtKQIUM8YzMyMtS7d29lZWXp4osvVocOHbR9+3YNGTJEAwcOrM4yAQDgFTTLAACYbNeuXWe8DLtnz54aNmyYJOmLL75Q06ZNK5x3uVzq3bu37r33Xl1//fUKDg6WJL322msyDENLlizRBRdcUOE5hw8flnRidnjGjBm6//77Pf99LjIzM9WtWzctXrxYAQEBkqQxY8Zo8ODBmj17doVm+c4771RWVpYee+wx3X777Z7jc+bM0bXXXntO7wsAQE1AswwAgMl2796t+++//7TnbrnlFk+zXLlRlqTQ0FCNHz9eU6dO1apVq9S/f/8K54OCgk55TnR0dDWkPuHJJ5/0NMqS9Ic//EGNGzfWqlWrPMeKior0/vvvKz4+XpMnT67w/HHjxulf//qXtm3bVm2ZAADwBu5ZBgDAZEOHDpVhGKf9eeqppzzjDhw4oClTpqh169YKDg723F88depUSSdmek+64oorJEk9evTQzTffrHnz5unAgQPVmjsiIkJNmjQ55XhycrJyc3M9j7dv366ioiJ17dq1QmMtndi2qlevXtWaCwAAb2BmGQCAGuDIkSPq1q2b0tLS1KdPHw0ePFgRERHy9fXV+vXr9fHHH6uoqMgz/i9/+Yv8/f311FNP6cUXX9S///1vz37Ks2fPrpb9m8PDw0973M/PT+Xl5Z7H+fn5kqTY2NjTjo+Pj69yFgAAvI1mGQCAGuDVV19VWlqaHnzwQd19990Vzj3yyCP6+OOPT3nO6NGjNXr0aOXn5+unn37S/Pnz9eqrr2ro0KHavn27IiIivJI9LCxMknTw4MHTns/JyfFKDgAAqhOXYQMAUAPs3r1bknTJJZeccu77778/63PDwsI0bNgwvfTSSxo/frwOHDigFStWeM77+PiorKysegP/SsuWLWW327VmzRoVFxdXOGcYhpYvX27aewMAYBaaZQAAaoDGjRtLkn744YcKx//73//qiy++OGX8okWLVFhYeMrxk/ct/3rhr6ioKDmdzuqMW4Hdbtdll12m7OxsPfPMMxXOvfnmm9q6datp7w0AgFm4DBsAAJOdbesoSZoxY4bGjh2rf/3rX/r73/+uxYsXq3Hjxvr555/1zTffaPTo0Zo/f36F50ydOlVpaWkaMGCAUlJSZLPZ9MMPP2jlypXq3bu3+vTp4xk7aNAg/e9//9Nll12mTp06ydfXVyNGjFD79u2r7TM+/PDD+uabb3THHXdo8eLF6tixo7Zv367PPvtMw4YN01dffSUfH/6NHgBQe9AsAwBgsrNtHSWdaJaTk5P13Xff6R//+Ie++eYblZaWqnPnzlqwYIHS09NPaZanTZum+fPna82aNfr666/l7++vJk2a6NFHH9VNN90kX19fz9inn35akvTtt9/qww8/VHl5uRwOR7U2yw0bNtSyZcv0z3/+UwsWLNCSJUvUpUsXLViwQO+//76k/7u3GQCA2sBmGIZhdQgAAFB39e3bV8uWLVNeXp5CQ0OtjgMAwO/C9VAAAKBaZGVlnXJs7ty5+vHHHzV48GAaZQBArcLMMgAAqBbR0dHq1KmT2rRp49kfesmSJWrQoIF+/PHHar3sGwAAs9EsAwCAanH33Xfr008/VVpamtxut2JjYzVw4EDde++9atWqldXxAAA4JzTLAAAAAABUwj3LAAAAAABUQrMMAAAAAEAlNMsAAAAAAFRCswwAAAAAQCU0ywAAAAAAVEKzDAAAAABAJTTLAAAAAABUQrMMAAAAAEAlNMsAAAAAAFTy/wGnhJLmdQ3hWgAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 1000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create matplotlib figure and axis\n",
    "f, ax = plt.subplots(figsize=(10, 10))\n",
    "\n",
    "# Return a list of the BNGIndexedGeometry objects for the geometry at a 500m resolution\n",
    "bng_idx_geoms = geom_to_bng_intersection(geom=geom, resolution=500)\n",
    "\n",
    "# Extract geom property from each BNGIndexedGeometry object\n",
    "# Seperate core and edge geometries based on is_core property\n",
    "core = [g.geom for g in bng_idx_geoms if g.is_core]\n",
    "edge = [g.geom for g in bng_idx_geoms if not g.is_core]\n",
    "\n",
    "# Plot core and edge geometries\n",
    "gpd.GeoSeries(core, crs=27700).plot(ax=ax, color=\"#ff1f5b\", edgecolor=\"#fff\")\n",
    "gpd.GeoSeries(edge, crs=27700).plot(ax=ax, color=\"#009ade\", edgecolor=\"#fff\")\n",
    "# Plot original Polygon geometry boundary for context\n",
    "gpd.GeoSeries([geom], crs=27700).boundary.plot(\n",
    "    ax=ax, color=\"#000\", linewidth=1, linestyle=\"--\"\n",
    ")\n",
    "\n",
    "# Set the title\n",
    "ax.set_title(\n",
    "    \"Decomposition of Polygon Geometry into BNG Grid Squares at a 500m Resolution\",\n",
    "    fontsize=16,\n",
    ")\n",
    "\n",
    "# Add a categorical legend for is_core property\n",
    "legend_elements = [\n",
    "    Line2D(\n",
    "        [0],\n",
    "        [0],\n",
    "        marker=\"s\",\n",
    "        color=\"w\",\n",
    "        label=\"True\",\n",
    "        markerfacecolor=\"#ff1f5b\",\n",
    "        markersize=14,\n",
    "    ),\n",
    "    Line2D(\n",
    "        [0],\n",
    "        [0],\n",
    "        marker=\"s\",\n",
    "        color=\"w\",\n",
    "        label=\"False\",\n",
    "        markerfacecolor=\"#009ade\",\n",
    "        markersize=14,\n",
    "    ),\n",
    "]\n",
    "# Add legend to the plot\n",
    "legend = ax.legend(handles=legend_elements, title=\"is_core\", loc=\"upper left\")\n",
    "# Remove legend frame\n",
    "legend.get_frame().set_linewidth(0)\n",
    "\n",
    "# Set the aesthetics for the matplotlib axes\n",
    "plot_aesthetics(ax)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6a40fe63",
   "metadata": {},
   "source": [
    "## Hierarchy\n",
    "\n",
    "* `osbng` provides functionality to navigate the hierarchical structure of the BNG index system.\n",
    " * This `osbng.hierarchy` module allows for the traversal of this hierarchy by providing methods to return the parent and children of `BNGReference` objects at specified resolutions.\n",
    "\n",
    "Parent and child definitions:\n",
    "\n",
    "* **Parent**: The parent of a `BNGReference` object is the grid square at the next higher (coarser) resolution level that contains the current reference. For example, the parent of a 1km grid square reference would be the 5km grid square that contains it.\n",
    "* **Children**: The children of a `BNGReference` object are the grid squares at the next lower (finer) resolution level that are contained within the current reference. For example, the children of a 10km grid square reference would be the 5km grid squares that it contains.\n",
    "\n",
    "* While parent and child derivation defaults to the next higher and lower resolution, **any supported resolution in the hierarchy can be specified**."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "e80d8ed7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'100m'"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Convert a BNG reference string into a BNGReference object\n",
    "bng_ref = BNGReference(bng_ref_string=\"SU 372 155\")\n",
    "\n",
    "# The resolution of the BNGReference object as a descriptive label\n",
    "bng_ref.resolution_label"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "7857d194",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "BNGReference(bng_ref_formatted=SU 37 15 NW, resolution_label=500m)"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Return the parent BNGReference object at the next higher resolution\n",
    "bng_ref.bng_to_parent()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "5dfbb817",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "BNGReference(bng_ref_formatted=SU SW, resolution_label=50km)"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Return the parent BNGReference object at a custom higher resolution\n",
    "bng_ref.bng_to_parent(resolution=\"50km\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "ae023ab5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create matplotlib figure and axis\n",
    "f, ax = plt.subplots(figsize=(10, 10))\n",
    "\n",
    "# Return the parent BNGReference object\n",
    "bng_ref_parent = bng_ref.bng_to_parent()\n",
    "\n",
    "# Plot the parent BNGReference grid square\n",
    "gpd.GeoSeries([bng_ref_parent.bng_to_grid_geom()], crs=27700).plot(\n",
    "    ax=ax, color=\"none\", edgecolor=\"#00000075\", linewidth=1, linestyle=\"--\"\n",
    ")\n",
    "# Plot the original BNGReference grid square\n",
    "gpd.GeoSeries([bng_ref.bng_to_grid_geom()], crs=27700).plot(\n",
    "    ax=ax, color=\"#AF58BA\", edgecolor=\"none\", linewidth=1, linestyle=\"--\"\n",
    ")\n",
    "\n",
    "# Set the title\n",
    "ax.set_title(\"500m Resolution Parent of a 100m Resolution BNG Grid Square\", fontsize=16)\n",
    "\n",
    "# Set the aesthetics for the matplotlib axes\n",
    "plot_aesthetics(ax)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "28002887",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[BNGReference(bng_ref_formatted=SU 372 155 SW, resolution_label=50m),\n",
       " BNGReference(bng_ref_formatted=SU 372 155 SE, resolution_label=50m),\n",
       " BNGReference(bng_ref_formatted=SU 372 155 NW, resolution_label=50m),\n",
       " BNGReference(bng_ref_formatted=SU 372 155 NE, resolution_label=50m)]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Return the children of the BNGReference object at the next lower resolution\n",
    "bng_ref.bng_to_children()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "8c914a34",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[BNGReference(bng_ref_formatted=SU 3720 1550, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3721 1550, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3722 1550, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3723 1550, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3724 1550, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3725 1550, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3726 1550, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3727 1550, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3728 1550, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3729 1550, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3720 1551, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3721 1551, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3722 1551, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3723 1551, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3724 1551, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3725 1551, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3726 1551, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3727 1551, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3728 1551, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3729 1551, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3720 1552, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3721 1552, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3722 1552, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3723 1552, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3724 1552, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3725 1552, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3726 1552, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3727 1552, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3728 1552, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3729 1552, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3720 1553, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3721 1553, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3722 1553, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3723 1553, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3724 1553, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3725 1553, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3726 1553, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3727 1553, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3728 1553, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3729 1553, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3720 1554, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3721 1554, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3722 1554, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3723 1554, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3724 1554, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3725 1554, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3726 1554, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3727 1554, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3728 1554, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3729 1554, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3720 1555, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3721 1555, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3722 1555, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3723 1555, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3724 1555, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3725 1555, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3726 1555, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3727 1555, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3728 1555, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3729 1555, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3720 1556, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3721 1556, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3722 1556, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3723 1556, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3724 1556, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3725 1556, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3726 1556, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3727 1556, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3728 1556, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3729 1556, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3720 1557, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3721 1557, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3722 1557, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3723 1557, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3724 1557, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3725 1557, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3726 1557, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3727 1557, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3728 1557, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3729 1557, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3720 1558, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3721 1558, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3722 1558, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3723 1558, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3724 1558, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3725 1558, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3726 1558, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3727 1558, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3728 1558, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3729 1558, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3720 1559, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3721 1559, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3722 1559, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3723 1559, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3724 1559, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3725 1559, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3726 1559, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3727 1559, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3728 1559, resolution_label=10m),\n",
       " BNGReference(bng_ref_formatted=SU 3729 1559, resolution_label=10m)]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Return the children of the BNGReference object at a custom lower resolution\n",
    "bng_ref.bng_to_children(resolution=\"10m\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "96a92909",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create matplotlib figure and axis\n",
    "f, ax = plt.subplots(figsize=(10, 10))\n",
    "\n",
    "# Return the BNGReference object for the children at a 10m resolution\n",
    "bng_refs_children = bng_ref.bng_to_children(resolution=\"10m\")\n",
    "\n",
    "# Plot the BNGReference grid squares for each child\n",
    "gpd.GeoSeries(\n",
    "    [bng_ref.bng_to_grid_geom() for bng_ref in bng_refs_children], crs=27700\n",
    ").plot(ax=ax, color=\"none\", edgecolor=\"#00000075\", linewidth=1, linestyle=\"--\")\n",
    "# Plot the original BNGReference grid square\n",
    "gpd.GeoSeries([bng_ref.bng_to_grid_geom()], crs=27700).plot(\n",
    "    ax=ax, color=\"none\", edgecolor=\"#AF58BA\", linewidth=3, linestyle=\"--\"\n",
    ")\n",
    "\n",
    "# Set the title\n",
    "ax.set_title(\n",
    "    \"10m Resolution Children of a 100m Resolution BNG Grid Square\", fontsize=16\n",
    ")\n",
    "\n",
    "# Set the aesthetics for the matplotlib axes\n",
    "plot_aesthetics(ax)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bc257c39",
   "metadata": {},
   "source": [
    "## Traversal\n",
    "\n",
    "* The `osbng.traversal` module provides functionality for traversing and calculating distances within the BNG index system. It supports spatial analyses such as distance-constrained nearest neighbour searches and 'distance within' queries by offering:\n",
    "\n",
    "    * Generation of k-discs and k-rings around a given grid square.\n",
    "    * Identification of neighbouring grid squares and checking adjacency.\n",
    "    * Calculating the distance between grid square centroids.\n",
    "    * Retrieving all grid squares within a specified absolute distance."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "332acbe1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[BNGReference(bng_ref_formatted=SU 370 157, resolution_label=100m),\n",
       " BNGReference(bng_ref_formatted=SU 371 157, resolution_label=100m),\n",
       " BNGReference(bng_ref_formatted=SU 372 157, resolution_label=100m),\n",
       " BNGReference(bng_ref_formatted=SU 373 157, resolution_label=100m),\n",
       " BNGReference(bng_ref_formatted=SU 374 157, resolution_label=100m),\n",
       " BNGReference(bng_ref_formatted=SU 370 156, resolution_label=100m),\n",
       " BNGReference(bng_ref_formatted=SU 371 156, resolution_label=100m),\n",
       " BNGReference(bng_ref_formatted=SU 372 156, resolution_label=100m),\n",
       " BNGReference(bng_ref_formatted=SU 373 156, resolution_label=100m),\n",
       " BNGReference(bng_ref_formatted=SU 374 156, resolution_label=100m),\n",
       " BNGReference(bng_ref_formatted=SU 370 155, resolution_label=100m),\n",
       " BNGReference(bng_ref_formatted=SU 371 155, resolution_label=100m),\n",
       " BNGReference(bng_ref_formatted=SU 372 155, resolution_label=100m),\n",
       " BNGReference(bng_ref_formatted=SU 373 155, resolution_label=100m),\n",
       " BNGReference(bng_ref_formatted=SU 374 155, resolution_label=100m),\n",
       " BNGReference(bng_ref_formatted=SU 370 154, resolution_label=100m),\n",
       " BNGReference(bng_ref_formatted=SU 371 154, resolution_label=100m),\n",
       " BNGReference(bng_ref_formatted=SU 372 154, resolution_label=100m),\n",
       " BNGReference(bng_ref_formatted=SU 373 154, resolution_label=100m),\n",
       " BNGReference(bng_ref_formatted=SU 374 154, resolution_label=100m),\n",
       " BNGReference(bng_ref_formatted=SU 370 153, resolution_label=100m),\n",
       " BNGReference(bng_ref_formatted=SU 371 153, resolution_label=100m),\n",
       " BNGReference(bng_ref_formatted=SU 372 153, resolution_label=100m),\n",
       " BNGReference(bng_ref_formatted=SU 373 153, resolution_label=100m),\n",
       " BNGReference(bng_ref_formatted=SU 374 153, resolution_label=100m)]"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Convert a BNG reference string into a BNGReference object\n",
    "bng_ref = BNGReference(bng_ref_string=\"SU 372 155\")\n",
    "\n",
    "# Return a list of BNG reference objects representing a filled disc around the\n",
    "# BNGReference object up to a grid distance k, including\n",
    "# the given central BNGReference object\n",
    "bng_ref.bng_kdisc(k=2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "e02fd4f8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create matplotlib figure and axis\n",
    "f, ax = plt.subplots(figsize=(10, 10))\n",
    "\n",
    "# Return a k-disc of the BNGReference object at a grid distance of k=2\n",
    "bng_ref_kdisc = bng_ref.bng_kdisc(k=2)\n",
    "\n",
    "# Plot the original BNGReference grid square\n",
    "gpd.GeoSeries([bng_ref.bng_to_grid_geom()], crs=27700).plot(\n",
    "    ax=ax, color=\"#009ade\", linewidth=2\n",
    ")\n",
    "# Plot the BNGReference grid squares in the k-disc\n",
    "gpd.GeoSeries(\n",
    "    [bng_ref.bng_to_grid_geom() for bng_ref in bng_ref_kdisc], crs=27700\n",
    ").plot(ax=ax, color=\"none\", edgecolor=\"#00000075\", linewidth=1, linestyle=\"--\")\n",
    "\n",
    "# Set the title\n",
    "ax.set_title(\"K-Disc Around a BNG Grid Square Where k=2\", fontsize=16)\n",
    "# Set the aesthetics for the matplotlib axes\n",
    "plot_aesthetics(ax)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "7655738d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[BNGReference(bng_ref_formatted=SU 371 156, resolution_label=100m),\n",
       " BNGReference(bng_ref_formatted=SU 372 156, resolution_label=100m),\n",
       " BNGReference(bng_ref_formatted=SU 373 156, resolution_label=100m),\n",
       " BNGReference(bng_ref_formatted=SU 371 155, resolution_label=100m),\n",
       " BNGReference(bng_ref_formatted=SU 373 155, resolution_label=100m),\n",
       " BNGReference(bng_ref_formatted=SU 371 154, resolution_label=100m),\n",
       " BNGReference(bng_ref_formatted=SU 372 154, resolution_label=100m),\n",
       " BNGReference(bng_ref_formatted=SU 373 154, resolution_label=100m)]"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Return a list of BNG reference objects representing a epresenting a hollow ring\n",
    "# around the BNGReference object at a grid distance k\n",
    "bng_ref.bng_kring(k=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "19b6360f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA4MAAAOeCAYAAAC538W/AAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjUsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvWftoOwAAAAlwSFlzAAAPYQAAD2EBqD+naQAAw2dJREFUeJzs3Xl4VPX5///XZN9DIJCQkBKUiLIIhCiyKAYRRETrQktRNi1q1Z9abavUBaV1aVW+pWqtFQWtVFyxKijIJiLIHgSiQIAQ1qyTZZJM1vP7g09OGbNAFjNnmOfjunJdMGeZe+aeTO57znveb5thGIYAAAAAAF7Fx90BAAAAAADaH80gAAAAAHghmkEAAAAA8EI0gwAAAADghWgGAQAAAMAL0QwCAAAAgBeiGQQAAAAAL0QzCAAAAABeiGYQAAAAALwQzSAAt1qzZo1sNpsuv/xyd4eCVsrMzJTNZlNiYqK7Q0EbeeKJJ2Sz2fTEE0806zh+r89+l19+uWw2m9asWePuUH4y06ZNk81m04IFC9wdCvCToRkEvFBiYmKTf+DsdrtSUlJks9l03nnn6ejRo02er65gPPXH19dX0dHRSk1N1Wuvvaba2tqf4JG4z/jx483HunfvXneHg1PUNaUNvSY7duyoSy+9VC+//LKqq6sbPL7u98Nms+njjz9u9H5GjRp12kKxtLRUL774osaOHav4+HgFBQUpLCxM5557rm666SbNnz9fxcXFrXq8X375pW699Vb16tVLkZGRCggIUExMjFJTUzVr1iz98MMPrTp/e0tPT9cdd9yh8847T8HBwQoNDVWPHj10+eWX67HHHtP69evdHaLHiI+Pl81m0+LFixvcnpWVZb7W77777kbPk5SURFPkBgsWLND06dPVv39/denSRf7+/urUqZNGjhypBQsWnHV/V+EeNIMAXBQUFGjUqFHaunWrevXqpa+++krx8fFndGxERISGDRumYcOGKSUlRT4+PlqzZo1uv/12jR8/vsHiOyQkRL169dLPfvaztn4oP5nc3Fx98cUX5v/ffvttN0aDpqSkpJivyUGDBsnf31/r1q3TPffcoyuvvFKVlZVNHv/EE0/IMIwW3ffy5ct1zjnn6N5779UXX3yhmpoa9enTRz179lRRUZE+/PBD3XrrrerRo4fL6+lM5eXl6corr9To0aM1f/58HT58WN26ddOAAQMUGhqqr776SrNnz1bv3r31m9/8pkWPITo6Wr169VJ0dHSLjm+uhQsXauDAgfrXv/6lzMxMxcfHq0+fPjIMQ1999ZX+/Oc/6957722XWM4Gl156qSTp66+/bnD7qbc3tk92drYyMjJczof28eijj2rBggXKyMhQhw4d1L9/f/n5+Wn16tWaPn26rrnmmtO+hwGnQzMIwJSfn68rrrhC27ZtU+/evbVmzRp17dr1jI8fOHCg1q1bp3Xr1mnjxo3KycnRm2++KR8fHy1dulTz58+vd8zFF1+sH374QW+99VZbPpSf1KJFi1RdXa0OHTpIOtkMtrRhwE/r/fffN1+TmzZt0okTJ/Sf//xHvr6+WrNmjebNm9fosb6+vtqxY4c+/PDDZt/vp59+qquvvlo5OTmaOHGidu3apRMnTmjr1q1KS0tTbm6utm3bpttvv10Oh0NpaWnNOn9RUZGGDRumFStW6LzzztOHH34ou92u3bt3a9OmTTpw4ICOHz+uF198UQkJCVq9enWzH4Mk3XPPPfrhhx90zz33tOj45sjMzNRtt92myspK3XrrrTpy5IgyMjK0adMmZWZm6vjx43rppZfUu3fvnzyWs8XpmsF169ZJknr06KFdu3bJbrc3uk9cXJzOPffcnyhSNGTmzJn69ttvVVJSor1792rLli3Kzs7WkiVLFB4ers8//1xz5851d5jwcDSDACSdvMowcuRIpaWlqW/fvlq9erViY2Nbfd4pU6Zo0qRJkqSPPvqo1eezgn//+9+SpKeeekpRUVE6ePCgvvnmGzdHhTNhs9n0q1/9SjfccIMkacWKFY3u+6tf/UqS9OSTTzar2c/JydHUqVNVU1OjRx99VO+884769OlTL46BAwfq1Vdf1ebNm9WrV69mPY677rpLe/fuVb9+/fTtt9/qhhtuUGBgoMs+MTExuueee/T999/rtttua9b53WHRokWqqKhQr1699Nprr6lLly4u22NjY3X33Xd71AdH7lbXDKalpcnhcNTb/vXXXys8PFwzZsyQYRgNDsGtayS5Ktj+7r77bg0ePFg+Pq7l+tVXX63HHntMkpocyg6cCZpBAMrNzdXIkSP13Xff6cILL9Tq1avrFWKtcdFFF0k6+cn/jzU20cSPJyN5++23lZKSopCQEHXs2FETJkzQgQMHGr3P7du3a/z48YqKilJYWJguueQSffDBB5JkfkemJfbs2aPNmzcrICBAkyZN0k033STpfw1iQ06dhODgwYOaNm2a4uPj5efn5zIxR2lpqf785z/rwgsvVGhoqCIiIjR48OBGv9+2YMEC2Ww2TZs2rcH7bey5PfX22tpazZ07V3379lVQUJBiYmJ02223KTc3t9HH89VXX2nUqFGKiIhQZGSkUlNT9eWXXzb+pJ3Grl27NGvWLA0ZMkRdu3ZVQECAunbtqhtuuOEn+35Y9+7dJanJIVa33nqrEhMTtWvXLr333ntnfO6///3vstvt6t+/v5588snT7n/hhRfq+uuvP+Pz7927V4sWLZIkvfHGG4qKimpy/5CQEP3+97+vd3vddyMzMzO1evVqjR07VtHR0S6TgpxuApnFixdr6NChCg0NVadOnXTNNddoy5YtZ/xYTlX3+9yvX796xe+ZOHTokG655RZ16dJFISEhuvDCC/Xyyy/LMAyXx3qq070XNHbcgQMH9Je//EWXX365EhISFBgYqM6dO+uqq67SkiVLGjzXqb931dXV+utf/6p+/fopJCSk3qRLP/zwg/n6CwwMVKdOnTRu3DitWrWqWc9J37591aFDB1VXV+vbb7912Wa325Wenq4hQ4bosssuk9TwFcS6K4NNNYM//PCDJkyYoOjoaAUHB2vQoEGn/Z1ZtmyZrr32WsXExCgwMFDdunXT9OnTtX///nr7/vjvwWuvvaaLLrpI4eHh9fJ35MgR3XvvveZ3Tjt06KDU1FTz/b+trFmzRuHh4fLz89Obb77Zpuc+E+eff74kqaysrN3vG2cXmkHAy+Xk5Cg1NVU7d+7UwIEDtWrVqjb/flDdH6uQkJAWHT9z5kxNnjxZeXl5Ou+881RWVqYPPvhAw4cPV15eXr39V6xYoSFDhuizzz5TbW2tLrjgAmVlZWnChAn6f//v/7XqsdRdlRg7dqw6dOigm2++WZL03nvvqaKioslj9+zZo+TkZC1atEixsbHmpAzSyYZ8yJAheuyxx7R792717NlT3bp106ZNm3TPPffo6quvltPpbFXsDZk8ebLuv/9+VVZWqmfPniooKNAbb7yh1NTUBh/PokWLNHLkSK1cuVIBAQE677zz9N133+mqq67Su+++26IY7r//fs2ePVs//PCDoqKi1K9fP1VXV2vx4sW67LLL9J///Ke1D7OeuoalrqBqiL+/vx555BFJJ68OnulkDXVF8O23396ipuZ0PvjgA9XW1uqiiy5SSkpKq8/3zjvvaNSoUdq4caPOOeccdevW7YyO++tf/6obbrhBGzZsUGRkpHr06KGvvvpKw4cPNxuI5oiIiJB08ipWVVVVs479/vvvNWjQIC1cuFAlJSXq3bu3ioqKdM899/wkQ1yffvppPfzww9q6davZePr7+2vZsmW65ppr9Je//KXRYw3D0M9//nM99NBDKi8vV+/evRUWFmZuf++999S/f3/Nnz9fBQUF6t27twICArR06VKNGjVKL7744hnH6ePjo2HDhkmq3+h98803MgxDw4cPV0pKigIDA+vt43A4tGPHDkkyG8Yf27p1qy666CItW7ZMiYmJCg8P17Zt2/TLX/6y0e9T33///brqqqv06aefSpL69OmjkpISLViwQMnJyU1+CPSb3/xGt99+u7Kzs3X++eebw/Wlkx9U9e3bVy+++KKOHDmipKQkRUREaM2aNZowYYJ+97vfNf2EnaHPPvtMY8eOVWVlpd577z1NnTq1Tc7bHBs2bJAkJScnt/t94yxjAPA63bt3NyQZzzzzjHHBBRcYkoxBgwYZBQUFLTrfrFmzDEnGiBEjGtw+YsQIQ5Jx66231tu2evXqBo89ePCgIcnw8/MzIiIijKVLl5rbjh8/blx44YWGJOOhhx5yOa64uNiIjY01JBnTp083ysrKDMMwjNraWuOll14yAgMDDUlGS97+amtrzefuvffeM29LSEgwJBkffPBBg8dNnTrVkGT4+voa1157rZGfn29uKy8vNwzDMG688UZDktGnTx8jIyPD3L5582YjJibGkGT84Q9/cDnv/PnzDUnG1KlTG7zfxp7butv9/f2NuLg4Y+PGjea2PXv2GN26dTMkGa+88orLcUeOHDHCwsIMScbDDz9sVFVVGYZhGJWVlcZvf/tbw9/f35BkdO/evfEnsQHvv/++8d1337ncVltba3z88cdGWFiYERERYRQXF5/x+epeO5KMgwcPmrdXVFQYe/fuNe69915DkhEZGWkcOHCg3vF1Of7666+Nqqoq45xzzjEkGQsXLnTZ74orrjAkGfPnzzdvy83NNe97x44dZxxzc4wbN86QZPz2t79t1XnqHqevr6/x5JNPmvmsra01nE6nYRj/+92eNWuWy7Hbtm0zfH19DZvNZrz00ktGbW2tYRiGUVJSYvzyl780XwuNvSc05MsvvzSfuyuuuMJYunSpUVpaetrjamtrjeTkZEOSMWbMGJffr3feecfw9/c3/Pz86r0eDMM47XtB3XP04+OWLl1qfPvtt+bjrrN27Vqja9euhq+vr8vvsWH87/fO19fX6NKli7F+/XpzW937wI4dO4zAwEAjKCjI+Ne//mXU1NSY+3zyySdGRESE4evra6SlpZ32eanzl7/8xZBkjBw50uX2P/zhD4YkY9WqVYZhGMawYcOMgIAAMxbDMIzly5cbkoyoqKh6j7Xufd3f39+45557zONqa2uNhx56yJBkxMXFGdXV1S7H/fOf/zQkGT169DBWr15t3l5dXW38+c9/NiQZ3bp1c4mj7nfa19fXCA0NNf773/+a2+re448ePWp07NjRsNlsxtNPP22+hg3DML755hsjPj7ekGR8+umnZ/zc1b13n/o7XveaCgkJMZYtW1bvmKVLlxrDhg1r9s/rr79+2ngqKyuNAwcOGE899ZTh5+dndOnSpd5rE2gumkHAC9UVOHUFUkpKimG321t8voaawcrKSuOHH34wbrvtNkOSERQUVK/gN4zTN4OSjBdeeKHecZ988okhybjwwgtdbq8rNM4//3yzuD1V3R/3ljSDa9asMSQZ4eHhZgFiGIbx+9//3pBkXHfddQ0eV3efsbGxhsPhqLd97969hs1mMyQZ27Ztq7f9vffeMyQZoaGhLk1Ra5tBScaHH35Y77i///3vhiTj2muvdbn90UcfNSQZF110UYP3V9egN7cZbErdff64EWvKqa+dxn5+8YtfGN9//32Dx5/aDBrG/57nXr16uRS2DTWDaWlp5n0UFRW17EGfxoABAwxJxty5c1t1nrrHOX78+Eb3aawZvOWWWwxJxoQJE+odU15ebnTp0qXZzaBhGMbtt9/ukic/Pz/jwgsvNO644w7j008/rddYGIZhrFixwpBkBAcHG7m5ufW21zX/bdkMNmXevHmGJOOpp55yuf10v3eGYRg33HBDk7l98cUXG/1grTHr1683JBkhISFGZWWlefvQoUMNf39/s+Gua+C++uorc5/HH3/ckGRcc8019c5b1wz279/fpWk1jJPv/3Ufyp36nlZRUWHExsYavr6+Db7XGcb/Phh76623zNtO9/fAMAzjgQceaPJDkk8//bTBprgpP24G//Wvfxk+Pj5GZGSk+f7wY3XvF839+fHv2Knuu+8+l31tNpsxffp0IzMz84wfC9AYhokCUEFBQZt87+Crr74yv4MTEBCg888/X6+//rp69+6tJUuWqF+/fi06b0OTX9R9D/HH3xus++7a5MmT5efnV++46dOntygG6X/fC7z++usVHBxs3l43VHTp0qXKz89v9Pgbb7xRoaGh9W7/8ssvzeFaAwcObPC4bt26qbS0tE0nqomKijInUjlVY8/tsmXLJKnRZQruuuuuFseSlZWlZ599Vr/4xS80cuRIDR8+XMOHDzeHntYNVWuuU5eWGDJkiLp37y4fHx8tWbJEb7755hkN/Zw8ebKSkpK0Z88eLVy4sMl9S0pKzH83lGvp5NDUH6+B+OPvjJ3JfTR2/meffbbBdRYbWxx8ypQpZ3zfdZYvXy6p4ddCUFCQbr311mafU5JeffVVffjhhxoxYoR8fX1VXV2t7777Tq+++qrGjx+v/v37a+fOnS7H1L0u676z9mOteV02JTc3V3PnztWkSZM0atQo8zX7t7/9TVLjr9nIyEhdd9119W6vrKzU0qVL5evr2+j3gK+99lpJJ99rz1RKSoqCg4NVVlambdu2SZKcTqe2bNmigQMHmsP3GxpOWvfvxoaISie/W/vj4dD+/v7q37+/JNf3kQ0bNujEiRNKTk5u8L3uTB5jY6/XugnKfv3rXze4/aqrrlJAQIDWr1/f6BqjTXnhhRd0++23q2PHjlq9erWGDx/e4H7Tpk2TcfJiS7N+GvteriSdc8455pJN0dHRMgxDS5cuZfIYtIn6lRIAr/HEE0/o9ddf14EDBzRq1CitXbu2Vd8XjIiIMBu+uqmwnU6n4uPjW/y9hujoaEVGRta7vW6Cmx/PkLdv3z5JJyflaEhjt5+O0+k0JyComx21Tv/+/dWnTx/t3r1b7777bqPF5wUXXNDg7XWL1jc2Zb6Pj4/OP/98HTlyRHv37tVVV13VosfwY41NE9/Yc1sXZ2OPo7HbT+fNN9/UnXfe2eR3IgsKClp07vfff79eo7V3717dfPPNevbZZ1VZWakXXnihyXP4+vrqscce05QpU/SnP/1JkyZNavCDBkkKDw83/11aWmp+D+5UgwYNMn/PiouL6zU3p1N3H6WlpQ1uT0hIMAt76eR3upp6bpubt8LCQuXk5DR5bEtfC5J0ww036IYbblBxcbE2bdqkb7/9Vp9++qk2bdqk3bt3a9SoUdq1a5c6d+4s6fSvy6SkJPn5+bWoAWjM8uXL9Ytf/EJFRUWN7tPYazYpKUm+vr71bq97vwwICNDVV1/d4LHG/81qe/To0TOO1d/fX4MHD9aaNWu0bt06DR48WJs2bVJlZaVLQzN06FDZbDbz+57V1dXauHGjpKYnj2nO+0jdaz0zM7PRZqqwsFBSw48xOjq6wb9RDofDnOTn9ttvbzRW6eR7eX5+vmJiYprc71Qvvviitm3bpvj4eH355Zeten23xL333uuyvuYXX3yh3/zmN7r//vvldDr10EMPtWs8OLtwZRDwYvHx8Vq5cqXi4+P1/fffa/To0fWKm6efftr8xPvUn+3bt9c736nrDO7YsUOHDx/WNddcoy+//FITJkxo0Vp8jV39aGxijroC+dSi/FSN3X46n3zyiYqKitSlSxeNGjWq3va6q4NNzSra2GOpK5aamsG1rnA59cpTa53uuf1xvurirCvCf6w5xVWd/fv3a8aMGXI6nXrwwQe1fft2FRcXq7a2VoZh6LXXXpOkZk8o0pTzzjvPXPPypZdeUnZ29mmPmTRpknr16qWMjIwmcxwfH2/+u6HZc6WTC6vX/Z784x//aF7wp9xHY+e/+eabzfOvW7fOJaaGNPY6aMypxX1bvhZ+LCIiQqNGjdKjjz6qjRs36v3335ePj49ycnL0r3/9q148jcXi4+PTppNiFRYWauLEiSoqKtKUKVP07bffym63q6amRoZhmKMTGnvNNvZ81733VlZW6ptvvmnwp25ileZOJvXj9QbrGr5TG7JOnTrp/PPP1/r161VTU6Nt27aprKxMISEhGjRoUKPnbs77SN1jzM3NbfQx7t69W5JUXl5+xvd16t+txs77zTffmLMHN3TupmRkZEiSunbtetrfp/Zw1VVXmR9O/vnPf2724wFORTMIeLkePXpoxYoV6ty5s7Zv366rr77a5YrD3r17G/yj2tQn4nWio6P1zjvvKD4+XitWrDjtELu2UFcsNLSmltTyZqpuFtGcnBz5+fnVG4L3xz/+UZL07bffmlcnz1TdTIJ1V1saUtewnNrM1s1E2liT3diVo5aqi7OxZSeair8x7733nqqqqjRx4kQ9//zzGjBggMt08YcPH255wE3o27evwsPDVVlZeUZDUH19ffX4449Lkv70pz81epUpOjpaPXv2lNT4Qt+tNWTIkJ/0/Kdz6syXbflaOJ2bbrpJN954oyRp06ZN9eJpLJba2tomh29Lzfsd+vzzz2W32zVkyBAtWLBAgwcPVocOHczmp6Wv2brHER8ff0bDCpujrhlct26dDMMwXzunXkGu+39xcbG+++47c59LLrlE/v7+LXpMP1b3GG+++ebTPr7GhjU3dV7pZDN9unM3Z1i29L8PRbds2VLvb+SPff755w1+gHq6nzfeeKNZMQ0aNEgxMTFyOBzN/psDnIpmEIDOP/98LV++XB06dND69et13XXXmZ88L1iwoME/pj9eu64xYWFh5uK4TzzxhGpqan6qhyHp5FUfSfruu+8a3N7cIXnSySKz7ntJXbp0UUxMTIM/dd8jbGw69dPFnJ6e3uD22tpa/fDDDy77Sv9rfBsrgus+zW4rdfddF8uPff/9980+Z93VraFDhza4vaXfFTwTdQX1mQ5BnThxonr37q2DBw9qwYIFje73i1/8QpL0r3/964yXo2iOCRMmyGazacuWLS1e0681OnToYF7FbsvXwpk455xzJLmuD3m612VGRsZpr9I19DtUVFTU4NI1da/ZIUOGNLhGYUtfs0lJSfL399fx48dbPCy6MUOHDpWfn5/y8/OVnp6uDRs26Lzzzqs3GqHuSmHdVWWpbRebrxsKv2vXrjY7p3Tye5hxcXGSZF5ZbEuhoaFaunSpLrnkEn3zzTe65pprGr0al52d3eTVycZ+srKymh1X3d/TthwCDe9DMwhAkjRgwAB9/vnnCgsL08qVKzVhwoQ2G5o3bdo0xcbGav/+/eZi2T+VK6+8UtLJhqyhxrOpIr4x77zzjqqrq5WYmKgTJ040+lM3cURzm8HRo0eb39VpaPjtRx99pCNHjig0NNTlk/y6wjgtLa1eMVBbW2sOhWwro0ePliT985//bHD7K6+80uxz1jXQDQ3V/OGHH8x1yNrad999Z149rnseT8fHx0ezZs2SdHJoVmO/H/fee686dOig7777zty/LZ133nn65S9/Kenk5B12u73N7+N06n7PGnotVFRUNPsqh3RmVxPrhkkmJSWZt9W9Lt9///0GrwA2NRS3LvebN2+ut23evHkNHtPUazY/P1+vv/56o/fXlJCQEI0ZM0a1tbX6+9//3qJzNCY0NNScsOXll19WUVFRg9/Zq3t/Wbt2rTlZVVOTxzTXpZdequjoaO3YsaNZV/7ORN1kWHXvw20tPDxcX3zxhQYNGqQ1a9bouuuua3At1p9iApmGrFu3Tnl5eQoKClKvXr3a6FHCG9EMAjBdcskl+uSTTxQUFKTPPvtMkydPbpMrG4GBgbrvvvskSc8880yLvjt4pn71q18pNjZW6enpLpOSGIahV155pUULmNd9R+yWW25p8EpAnV/84hcKDAzUgQMHmjXrZ8+ePc1CZsqUKS6z723bts2cOOCee+5xGSbav39/xcXF6fjx45o1a5b5vDqdTt1///2NXmlsqTvvvFOhoaHauHGjHnvsMbMBraqq0u9///sWfSJfV5D+4x//UFpamnn73r17NWHCBAUEBLRJ7Kfas2ePOavs+eef36yF2ydMmKB+/frp0KFDjeY4JiZGCxYskK+vr/785z9r4sSJDV6RPnDggDn8uLleeeUV9ezZUzt37tTgwYP14Ycf1itMy8vLNX/+/J9kyOZvf/tb+fj46L333tM///lP87VXWlqqW2+9tUVXtp5++mldeumleuedd+oN5z5+/LjuvPNOff3117LZbC6LfF9xxRUaOHCgysrKNHnyZJfm+L333tMrr7zS6IQ/Y8eOlSQ9+uijLs3dF198odmzZzd4XN2Vsvfee08rVqxwifHGG29s1VWaP/3pTwoMDNSf//xnPfvss/WuPh0/flxz585t9AOZptTFXfchUUPNYM+ePRUTE6PPPvtMubm58vf31yWXXNKCR9KwoKAgzZ49W9LJ36XFixfX+3uwa9cuPfTQQ82eOfmhhx5Sx44d9eabb+qBBx4wJ6KpU1BQoDfeeEN//vOfWxx/ZGSkli9frv79++vLL7/UjTfe6HKVui0tXbpUL7zwgo4fP+5ye21trd59911zBMKtt97a7O/9Ai5avCgFAI9Vt3bWqeujnWrJkiXmotG33nprvcWGf+x0i84bhmEUFhYa4eHhhiRj8eLF5u2nW2ewqTXr1MgaYV9++aUREBBgSCcXFr/ooouMuLg4c40qSYaPj0+Tj6nO999/b97PDz/8cNr9r7/+ekOScccdd5i3NbRw8Y/l5OQY/fr1MxdW7t+/v9G7d2/zvkeNGuWyCHOdf//73+Y+nTt3NlJSUoyIiAgjLCzMeP7555tcZ7CxfDX13L/99tvmmojR0dHGRRddZHTs2NHw8fExnn322WavM1hVVWVccskl5uO+4IILjL59+xo2m83o2rWruQh1Y2spNhW//m8NzbpFnYcOHWokJiYaPj4+Zvzbt2+vd/yP1xn8sQ8++MBlza+mfo+io6PN/bp06WIkJycbAwYMMGJiYsznsUOHDsY//vGPM358dbKzs43U1FTz/EFBQUafPn2Miy++2EhMTDQCAwPNbRMnTnRZjP3Ux9nUGnqNrTNoGIbx9NNPm+ePi4szUlJSjPDwcCMwMND405/+1Ox1Bu+//37zfD4+PkZSUpJx8cUXGz169DDXRPX19W1wDb5du3YZHTt2NNcbTElJMR/fXXfd1ehjzcnJMdfDCwwMNAYMGGAkJiYakoyHH3640eNuuukmM9aePXsaAwYMMPz8/Izw8HDjb3/7W4t+7+p89NFHRkhIiJnTAQMGGBdffLGRkJBg3udDDz10xs9rncWLF7u8bvfu3dvgfnVrHUoyLrnkkkbPV7fO4KkLx5+qqfe9hx9+2LyPjh07GhdddJGRnJxs5lCS8fnnn5v7n8nfA8MwjHXr1pm/c/7+/ka/fv2MwYMHG+ecc475+/bLX/6yyXOcyWPIyckx+vTpY0gyrr/++gbXtG2tU9crTEhIMC666CKjd+/eRlhYmHn71Vdf7bLmLdASXBkEUM/VV1+thQsXytfXV2+88Ybuv//+Vp8zMjJSd9xxh6STVwB+SqNGjdKGDRs0btw4SSe/ixcfH6933nnHjOFMZxWtuyp40UUXndFQnFtuuUXSyasGzfnEuHPnztqwYYNmz56tCy64QHv37tWhQ4d00UUX6cUXX9TSpUsVFBTU4P299957GjRokEpKSnTgwAFdccUV2rhxY5MzALbUzTffrFWrVik1NVVOp1M//PCD+vXrp88//9wcutgcfn5+WrZsmf6//+//U0xMjDIyMlRYWKjbbrtNW7dubfXMfVu2bHGZiTEvL099+/bVww8/rN27d2vAgAHNPucNN9xwRsddffXVOnjwoObOnavRo0fL19dXu3bt0t69exUSEqIbbrhB8+bNU1ZWVqNrNzalS5cuWrVqlb744gtNnTpV3bp106FDh7R9+3aVlZVp8ODBevTRR7Vnzx6988476tixY7PvoykzZ87UBx98oMGDB8tut2v//v269NJLtW7dukaXDWjK008/rSVLluiee+7RoEGDVFpaqu3btys3N1fnnXee7rzzTpcr5afq06ePtmzZokmTJikkJES7du1SRESEXnzxRb300kuN3mfnzp31zTffaMKECQoJCdGePXsUFRWl+fPn65lnnmn0uIULF+qxxx5TYmKiDh06pBMnTuimm27S5s2bzfX1Wur6669Xenq67rvvPiUmJmrPnj1KT09XSEiIrr/+er355pt6+OGHm33e4cOHmyMbunTp4jLU9lSnDkVvy+8LnuqZZ57RN998o0mTJik0NFQ7duxQZmamunXrpltvvVVLlizRFVdc0ezzDhs2TOnp6XrkkUfM7/d+99138vHx0VVXXaV//OMfmjt3bqvj79y5s1asWKFevXpp8eLFuuWWW9r8+/BXXnmlnn32WY0ZM8Z879i/f786duyoG264QR999JGWLFnisuYt0BI2w/gJx2sBgMVs3bpVKSkp6t+/v8uwRABnr7qm7eDBg82eSRIAzmZcGQTgVeq+L/PjKdUBAAC8Dc0ggLPO6tWrtWjRIpcJNaqqqjRnzhy98sor8vHx0YwZM9wYIQAAgPs1PL0WAHiwQ4cOafr06fL391ePHj0UERGhvXv3qri4WNLJ76u05LtiAAAAZxOuDAI461x66aW65557dN555yk3N1dpaWkKCgrS+PHjtWzZshZNvgAAAHC2YQIZAAAAAPBCXBkEAAAAAC9EMwgAAAAAXohmEAAAAAC8EM0gAAAAAHghmkEAAAAA8EI0gwAAAADghWgGAQAAAMAL0QwCAAAAgBeiGQQAAAAAL0QzCAAAAABeiGYQAAAAALwQzSAAAAAAeCGaQQAAAADwQjSDAAAAAOCFaAYBAAAAwAvRDAIAAACAF6IZBAAAAAAvRDMIAAAAAF6IZhAAAAAAvBDNIAAAAAB4IZpBAAAAAPBCNIMAAAAA4IVoBgEAAADAC9EMAgAAAIAXohkEAAAAAC9EMwgAAAAAXohmEAAAAAC8EM0gAAAAAHghmkEAAAAA8EI0gwAAAADghWgGAQAAAMAL0QwCAAAAgBeiGQQAAAAAL+Q1zeDatWs1fvx4xcXFyWaz6eOPP3bZ/tFHH2nMmDGKjo6WzWZTWlpavXNcfvnlstlsLj8TJ0502Wfbtm268sor1aFDB3Xq1Em33367HA6Hyz5ZWVkaP368QkNDFR0drXvvvVeVlZUu++zcuVMjRoxQcHCw4uPjNXv2bBmG0SbPBQAAAAB4TTNYWlqq/v3766WXXmp0+7Bhw/Tss882eZ4ZM2bo+PHj5s+rr75qbjt27JhGjRqlnj17auPGjfriiy+0e/duTZs2zdynpqZG48aNU2lpqdatW6dFixbpww8/1IMPPmjuU1xcrCuvvFJxcXHavHmzXnzxRT3//POaM2dO654EAAAAAPg/fu4OoL2MHTtWY8eObXT75MmTJUmZmZlNnickJESxsbENbvvss8/k7++vl19+WT4+J/vsl19+WQMHDlRGRoZ69uyp5cuXKz09XYcPH1ZcXJwk6YUXXtC0adP01FNPKSIiQgsXLpTT6dSCBQsUGBiovn37au/evZozZ44eeOAB2Wy2FjwDAAAAAPA/XtMMtpWFCxfq7bffVkxMjMaOHatZs2YpPDxcklRRUaGAgACzEZSk4OBgSdK6devUs2dPbdiwQX379jUbQUkaM2aMKioqtHXrVqWmpmrDhg0aMWKEAgMDXfaZOXOmMjMz1aNHjwZjq6ioUEVFhcttgYGBLudxJ7vdruDgYAUFBam0tLTe8NnAwEB16NBBtbW1ys3NrXd8ly5dZLPZZLfb6w2rDQ8PV0hIiJxOp4qKily2+fv7q2PHjpKk7Ozseuft1KmT/Pz8VFRUJKfT6bItLCxMoaGhqqyslN1ud9nm6+ur6OhoSVJubq5qa2tdtkdFRSkgIEAlJSUqKytz2RYcHKyIiAhVVVWpoKDAZZvNZlOXLl0kSfn5+aqurnbZ3qFDBwUGBjb5HNbU1CgvL6/eYz31OSwsLFTXrl3Jh8gH+TiJfJAP8kE+yAf5aG0+6mL0FDSDzXDzzTerR48eio2N1a5duzRz5kzt2LFDX375pSRp5MiReuCBB/Tcc8/pvvvuU2lpqf74xz9Kko4fPy5JOnHihGJiYlzOW/eiPnHihLlPYmKiyz51x5w4caLRZvCZZ57Rk08+6XLbrFmz9MQTT7TqcbcFu92uefPmadSoURo4cKC+//57rV692mWfc889VzfccIOcTqfeeuuteue47777FBAQoBUrVtS7glt33gMHDmjJkiUu2+Li4nTzzTdLUoPn/fWvf62oqCitW7dO6enpLtuGDh2qYcOG6ejRo/rggw9ctnXo0EEzZsyQJL377rsqLy932X7zzTcrLi5OW7Zs0ZYtW1y2DRw4UKNGjVJBQUG9mAICAnTfffdJkv773/8qPz/fZfv111+vnj17aufOnfr6669dtvXq1UvXXnutysrKGnysDzzwgHx9ffXhhx9q8eLF+sMf/qARI0aQD/IhiXyQD/JBPsgH+ch02UY+TjrTfCxbtkyHDx82H7snsBleOCuJzWbT4sWL9fOf/7zetrorb9u3b9eAAQOaPM/WrVuVkpKirVu3Kjk5WZL0n//8Rw888IDy8vLk6+ure++9V//+97/1wAMP6A9/+INuv/12HTp0SMuWLXM5V0BAgN566y1NnDhRo0ePVo8ePVy+j3j06FF169ZNGzZs0CWXXNJgPFa+Mpidna233npLv/jFL9S9e3c+uXLzJ1fffvut/vSnP+nJJ59USkoK+SAfksgH+SAf5IN8kA/y0Zp8ZGRkaPHixZoyZUq9iz9WxZXBVkhOTpa/v7/27dtnNoOTJk3SpEmTlJ2drdDQUNlsNs2ZM8e8mhcbG6uNGze6nMdut6uqqsp80cTGxppXCevk5ORIUpMvLKs0fk0JCgqSJIWGhio0NLTBfXx8fJp8nE190hIUFGTeR0OaOm9kZKQiIyMb3BYQENDksZ07d250W3h4uDmU+Mf8/f2bPG+nTp0a3dbUc+jr69vkecPCwiSRjx8jH+RDIh/ko2Hk4yTyQT4aQj7+F5On8ZrZRH8Ku3fvVlVVlbp27VpvW0xMjMLCwvTuu+8qKChIV155pSRpyJAh2rVrlzlsVJKWL1+uwMBADRo0yNxn7dq1Lp/OLF++XHFxcfWGjwIAAABAS3hNM+hwOJSWlmauH3jw4EGlpaUpKytLklRQUKC0tDRzTPOePXuUlpZmXqHbv3+/Zs+erS1btigzM1NLly7VhAkTNHDgQA0bNsy8n5deeknbtm3T3r179fLLL+uee+7RM888ow4dOkiSRo8erd69e2vy5Mnavn27Vq5cqd/97neaMWOGIiIiJJ28uhgYGKhp06Zp165dWrx4sZ5++mmPnknUz89PXbp0kZ8fF6OtoEOHDhoyZIj5uoR7kQ9rIR/WQj6shXxYC/mwloiICI0ZM8as6T2B13xncM2aNUpNTa13+9SpU7VgwQItWLBA06dPr7e9bgKWw4cP65ZbbtGuXbvkcDiUkJCgcePGadasWeZ4aUmaMmWKlixZIofDofPPP1+/+93vzGUr6mRlZemuu+7SqlWrFBwcrEmTJun55593GeK5c+dO3X333dq0aZOioqJ055136vHHH/fYZhAAAACAtXhNMwjgf8rLy7Vv3z4lJSWZy5/AfciHtZAPayEf1kI+rIV8WIsn5sNrhonCvXJycjRnzhxzIhy41/79+/XII49o//797g4FIh9WQz6shXxYC/mwFvJhLcXFxVq2bJmKi4vdHcoZoxlEuzAMQzU1NeJCtHX8eKpmuBf5sBbyYS3kw1rIh7WQD7QGzSAAAAAAeCGaQQAAAADwQjSDgBfy9/dXhw4d5O/v7+5QIPJhNeTDWsiHtZAPayEf1hIQEKCEhAQFBAS4O5QzxmyiaBfV1dUqLCxUhw4dWGvQAsiHtZAPayEf1kI+rIV8WAv5QGvRDAJeyDAM1dbWysfHh7UrLYB8WAv5sBbyYS3kw1rIh7V4Yj4YJop2UVxcrC+++MKjpto9m+3fv1933HEHU1FbBPmwFvJhLeTDWsiHtZAPa/HEpdRoBtEuysvLtXPnTpWXl7s7FEhyOp06fvy4nE6nu0OByIfVkA9rIR/WQj6shXygtWgGAQAAAMAL0QwCAAAAgBeiGQQAAAAAL8RsomgXDodD27ZtU3JyssLCwtwdjtcrKirShg0bNGTIEEVGRro7HK9HPqyFfFgL+bAW8mEt5MNaampqVFZWppCQEPn6+ro7nDNCMwgAAAAAXohhomgXlZWVOnz4sCorK90dCnRy6uPXX3/do6Y+PpuRD2shH9ZCPqyFfFgL+bCWwsJCffLJJyosLHR3KGeMZhDtwm63a9GiRbLb7e4OBTr5x+Ojjz7ij4dFkA9rIR/WQj6shXxYC/mwloqKCu3Zs0cVFRXuDuWM0QwCAAAAgBeiGQQAAAAAL0QzCAAAAABeiGYQ7cLHx0dhYWHy8eElZwVhYWHq06cPy3xYBPmwFvJhLeTDWsiHtZAPawkLC9Oll17qUflgaQkAAAAA8EJcpgG8UEVFhTIyMjxqtquzGfmwFvJhLeTDWsiHtZAPa/HEfNAMol3k5ubqlVdeUW5urrtDgaSMjAz94Q9/UEZGhrtDgciH1ZAPayEf1kI+rIV8WEthYaEWL17MOoPAj9XW1srhcKi2ttbdoUCSYRiqqKgQo8StgXxYC/mwFvJhLeTDWsgHWotmEAAAAAC8EM0gAAAAAHghmkHAC/n6+io0NFS+vr7uDgUiH1ZDPqyFfFgL+bAW8mEtfn5+6tSpk/z8/NwdyhljaQm0i8rKSmVnZysmJkYBAQHuDsfrkQ9rIR/WQj6shXxYC/mwFvKB1qIZBAAAAAAvxDBRtAuHw6G1a9fK4XC4OxRIOnjwoO69914dPHjQ3aFA5MNqyIe1kA9rIR/WQj6sJScnR3PnzlVOTo67QzljNINoF6Wlpdq4caNKS0vdHQp0Mh/79+8nHxZBPqyFfFgL+bAW8mEt5MNaDMNQZWWlRy31QTMIAAAAAF6IZhAAAAAAvBDNIAAAAAB4IZpBtIvg4GD169dPwcHB7g4Fkrp27apbbrlFXbt2dXcoEPmwGvJhLeTDWsiHtZAPa+nYsaOmTJmijh07ujuUM8bSEgAAAADghbgyiHZRXV2tvLw8VVdXuzsUSCooKNCHH36ogoICd4cCkQ+rIR/WQj6shXxYC/mwluLiYq1YsULFxcXuDuWM0QyiXeTn52v+/PnKz893dyiQdOzYMb3xxhs6duyYu0OByIfVkA9rIR/WQj6shXxYS3l5ubZv367y8nJ3h3LGaAYBAAAAwAvRDAIAAACAF6IZBAAAAAAvRDOIdmGz2eTr6yubzebuUCApJCRE3bt3V0hIiLtDgciH1ZAPayEf1kI+rIV8WEtISIhSUlI8Kh8sLQEAAAAAXogrg4AXqqys1LFjx1RZWenuUCDyYTXkw1rIh7WQD2shH9biifmgGUS7yM/P15tvvsnSEhaxf/9+/fa3v9X+/fvdHQpEPqyGfFgL+bAW8mEt5MNa7Ha7Fi5cKLvd7u5QzhjNINpFdXW1cnJyWHTeImpqauRwOFRTU+PuUCDyYTXkw1rIh7WQD2shH2gtmkEAAAAA8EI0gwAAAADghWgGAS9ks9nk7+/PUh8WQT6shXxYC/mwFvJhLeTDWnx8fBQcHCwfH89psVhaAu3C6XTq0KFD6t69u4KCgtwdjtcjH9ZCPqyFfFgL+bAW8mEt5AOtRTMIAAAAAF7Ic65hwqOVlpZqy5YtKi0tdXcokHTo0CE98sgjOnTokLtDgciH1ZAPayEf1kI+rIV8WEteXp5ee+015eXluTuUM0YziHbhcDi0evVqORwOd4cCSSUlJUpLS1NJSYm7Q4HIh9WQD2shH9ZCPqyFfFhLTU2NCgsLPWqpD5pBAAAAAPBCNIMAAAAA4IVoBgEAAADAC9EMol0EBgbq3HPPVWBgoLtDgaQuXbrommuuUZcuXdwdCkQ+rIZ8WAv5sBbyYS3kw1qioqJ00003KSoqyt2hnDGWlgAAAAAAL8SVQbSL2tpalZWVqba21t2hQCdnH1u5ciWzj1kE+bAW8mEt5MNayIe1kA9rKS0t1TfffONRS6nRDKJd5Obm6uWXX1Zubq67Q4FOrks0Z84c1iWyCPJhLeTDWsiHtZAPayEf1uJwOLR+/XqPWkqNZhAAAAAAvBDNIAAAAAB4IZpBAAAAAPBCNIOAFwoMDFRMTAxLfVgE+bAW8mEt5MNayIe1kA9rCQoKUu/evRUUFOTuUM4YS0ugXRiGoaqqKvn7+8tms7k7HK9HPqyFfFgL+bAW8mEt5MNayAdaiyuDaBc2m00BAQG8UVlETU2NSktLVVNT4+5QIPJhNeTDWsiHtZAPayEf1lJdXS273a7q6mp3h3LGaAbRLux2u95//33Z7XZ3hwJJ+/fv17333qv9+/e7OxSIfFgN+bAW8mEt5MNayIe15Ofna968ecrPz3d3KGeMZhDtorKyUpmZmaqsrHR3KJBUVVWlgoICVVVVuTsUiHxYDfmwFvJhLeTDWsgHWotmEAAAAAC8EM0gAAAAAHghmkEAAAAA8EIsLYF2UVZWpj179qhXr14KCQlxdzhej3xYC/mwFvJhLeTDWsiHtZAPtBbNIAAAAAB4IYaJol04nU6lp6fL6XS6OxRIOnbsmP7617/q2LFj7g4FIh9WQz6shXxYC/mwFvJhLQUFBVq4cKEKCgrcHcoZoxlEuygqKtKSJUtUVFTk7lCgk29WX331lUe9WZ3NyIe1kA9rIR/WQj6shXxYS1VVlY4dO+ZRS33QDAIAAACAF6IZBAAAAAAvRDMIAAAAAF6IZhDtwt/fX3FxcfL393d3KJDUsWNHjRgxQh07dnR3KBD5sBryYS3kw1rIh7WQD2uJjIzUuHHjFBkZ6e5QzhhLSwAAAACAF+LKIOCFysrKtH37dpWVlbk7FIh8WA35sBbyYS3kw1rIh7V4Yj5oBtEusrOz9dxzzyk7O9vdoUDSgQMH9Oijj+rAgQPuDgUiH1ZDPqyFfFgL+bAW8mEtJSUlWrFihUpKStwdyhmjGQQAAAAAL0QzCAAAAABeiGYQAAAAALwQzSDghfz9/dWxY0eW+rAI8mEt5MNayIe1kA9rIR/WEhAQoMTERAUEBLg7lDPG0hJoF9XV1SopKVF4eLj8/PzcHY7XIx/WQj6shXxYC/mwFvJhLeQDrUUzCHghwzBUVVUlf39/2Ww2d4fj9ciHtZAPayEf1kI+rIV8WIsn5oNhomgXRUVFWrJkiYqKitwdCiRlZGTozjvvVEZGhrtDgciH1ZAPayEf1kI+rIV8WEtOTo7mzp2rnJwcd4dyxrymGVy7dq3Gjx+vuLg42Ww2ffzxxy7bP/roI40ZM0bR0dGy2WxKS0urd47LL79cNpvN5WfixIku++zdu1fXXXedoqOjFRERoWHDhmn16tUu+2RlZWn8+PEKDQ1VdHS07r33XlVWVrrss3PnTo0YMULBwcGKj4/X7Nmz5ckXcZ1Op9LT0+V0Ot0dCiRVVFQoOztbFRUV7g4FIh9WQz6shXxYC/mwFvKB1vKaZrC0tFT9+/fXSy+91Oj2YcOG6dlnn23yPDNmzNDx48fNn1dffdVl+7hx41RdXa1Vq1Zp69atGjBggK655hqdOHFCklRTU6Nx48aptLRU69at06JFi/Thhx/qwQcfNM9RXFysK6+8UnFxcdq8ebNefPFFPf/885ozZ04rnwUAAAAAOMlrvmk6duxYjR07ttHtkydPliRlZmY2eZ6QkBDFxsY2uC0vL08ZGRl64403dOGFF0qSnn32Wf3jH//Q7t27FRsbq+XLlys9PV2HDx9WXFycJOmFF17QtGnT9NRTTykiIkILFy6U0+nUggULFBgYqL59+2rv3r2aM2eOHnjgAY8ZgwwAAADAurymGWwrCxcu1Ntvv62YmBiNHTtWs2bNUnh4uCSpU6dOuuCCC/TWW28pOTlZgYGBevXVVxUTE6NBgwZJkjZs2KC+ffuajaAkjRkzRhUVFdq6datSU1O1YcMGjRgxQoGBgS77zJw5U5mZmerRo0eDsVVUVNQbJhAYGOhyHncqKytTVlaWJCksLEwOh0N2u13V1dWSTk7HGxkZqfDwcJWUlKisrEylpaXm8dHR0eZjqaioUF5enrktNDRUISEh5rFFRUXm0Fs/Pz9FRUWZ9+l0OlVSUmIeGxUVpaCgIPn5+cnpdCo3N9fcFhISotDQUPO8JSUl5lBXHx8fderUSaGhoSovL5fT6XT5TmRkZKSCgoIUFBSksrIy5eXlmUN9g4KCFB4ebsZUWlqqsrIy89jOnTsrODhYVVVVcjqdstvt5raIiAgFBQUpNDRUDodDBQUFqqmpcXkOGztvdHS0goKCVFRUpKqqKuXm5io7O1sxMTGSpIKCAlVVVbnkre5xlJWVuTxvdfcXFRUlwzAaHB/fuXNn+fj4qLCwsN5rMywsTKGhofWet7qcderUSdLJ8fc/HiLdqVMn+fn5qbi4WOXl5S7bQkNDFRYWpsrKSpfnTTqZs86dO0uScnNzVVtb67I9KipKAQEB5nN3quDgYEVERKi6ulr5+fku22w2m7p06SJJys/PN1/Tdeqew9LSUjkcDpdtp/5+kg/yUYd8nEQ+yAf5OH0+qqqqdPToUXXu3Jn6ys31VWFhocvtnoBmsBluvvlm9ejRQ7Gxsdq1a5dmzpypHTt26Msvv5R08hf6yy+/1HXXXafw8HD5+PgoJiZGX3zxhTp06CBJOnHihPnGWafuDaRuKOmJEyeUmJjosk/dMSdOnGi0GXzmmWf05JNPutw2a9YsPfHEE6185K1XVVWlTZs2yW63Kz4+XqmpqVq9erW2bdum4uJiSSffoPv166eRI0dq1apVOnr0qPbt22eeY/jw4erZs6ekk1+YXrdunbktKSlJ8fHx5rE7d+4033AjIiKUnJxs3mdubq52795tHnvxxRcrMTFR0dHRSk9P19q1a803+cTERCUmJprn3bNnj44fPy7p5Jv74MGDNXjwYH333Xc6fvy4y3dNBw4cqPj4eJ1//vnasmWLNmzYYP5Bi4+PV1JSkq644gqtXLlSBw4cMBtlPz8/DR8+XP369dOxY8eUlZWlzZs3m+ft27evYmJiNHToUH399dfasmWL+Qeic+fO6tOnjxnvkSNHXL5UftlllykpKUlFRUXy8fHRV199pS1btuj3v/+9JOnzzz/XsWPHXHI3btw49e7dW3v27NGKFStctiUmJmrChAmqqqrSW2+9VS/vd999t0JCQrRq1Srt37/fZVtqaqpSUlJ06NAhffLJJy7bunTpoqlTp0qS3n77bfPNuM706dMVHR2t9evXa+fOnS7bBg8erMsuu0zZ2dlatGiRy7awsDD95je/kSR98MEH9f6wTpw4UQkJCdq2bZs2btzosq1fv3666qqrVFhYWO+x+vr66oEHHpAkffbZZ/UKm2uvvVa9evXS999/X+87xOeee66uvPJKDR06VJs3byYfpyAf5IN8kA/y0XQ+UlJS5OPjo6VLl+q7776jvnJzfeV0OuXn5+dRy3x45dISNptNixcv1s9//vN62+quvG3fvl0DBgxo8jxbt25VSkqKtm7dquTkZBmGoZ///OeqqqrSI488ouDgYM2bN0+ffPKJNm/erK5du+r222/XoUOHtGzZMpdzBQQE6K233tLEiRM1evRo9ejRw+X7iEePHlW3bt20YcMGXXLJJQ3GY+Urg9nZ2Zo3b57GjBmjhIQEPrly8ydXeXl5evfdd3Xdddepc+fOfLL7f9z1yW6HDh1ctpGPk8gH+SAf5IN8NJ2PiooK6iuL1VeLFy/WlClT6l38sSqawR9pTjNoGIYCAwP173//W7/85S+1cuVKjR49Wna7XREREeZ+SUlJuu222/Twww/r8ccf13//+1/t2LHD3G6329WxY0etWrVKqampmjJlioqKivTf//7X3Gf79u1KTk7WgQMHGr0yaGXZ2dl66623POqX42xGPgAA8Hz8PbcWT8yH18wm+lPYvXu3qqqq1LVrV0kyPyHw8XF9Wn18fMxPkIYMGaJdu3aZl8Ilafny5QoMDDS/VzhkyBCtXbvWZbmJ5cuXKy4urt7wUQAAAABoCa9pBh0Oh9LS0swxxwcPHlRaWpo5jrigoEBpaWlKT0+XJO3Zs0dpaWnm9/j279+v2bNna8uWLcrMzNTSpUs1YcIEDRw4UMOGDZN0somLiorS1KlTtWPHDu3du1e///3vdfDgQY0bN06SNHr0aPXu3VuTJ0/W9u3btXLlSv3ud7/TjBkzzKuJkyZNUmBgoKZNm6Zdu3Zp8eLFevrppz16JlE/Pz916dLFo8ZQn80iIiI0ZswYlyvYAADAs1BfWYsn1ldeM0x0zZo1Sk1NrXf71KlTtWDBAi1YsEDTp0+vt71uApbDhw/rlltu0a5du+RwOJSQkKBx48Zp1qxZ6tixo7n/li1b9Mgjj2jLli2qqqpSnz599Pjjj7ssa5GVlaW77rpLq1atUnBwsCZNmqTnn3/e5bt9O3fu1N13361NmzYpKipKd955px5//HGPbQYBAAAAWIvXNIMA/qe8vFz79u1TUlKSgoOD3R0OAACAx/PE+sprhonCvXJycjRnzpwGZwxD+ysuLtayZcvMaacBAIDnob6yFk+sr2gG0S4Mw1BNTU29KZ4BAADQMtRXaC2aQQAAAADwQjSDAAAAAOCFaAYBLxQQEKCEhAQFBAS4OxQAAICzgifWV8wminZRXV2twsJCdejQgbVwAAAA2gD1FVqLZhDwQoZhqLa2Vj4+PqxdCQAA0AY8sb5imCjaRXFxsb744guPmmr3bMZU1AAAeD7qK2vxxPqKZhDtory8XDt37lR5ebm7QwEAADgrUF+htWgGAQAAAMAL0QwCAAAAgBeiGQQAAAAAL8RsomgXDodD27ZtU3JyssLCwtwdjterqalRWVmZQkJC5Ovr6+5wAABAC1BfWYsn1lc0gwAAAADghRgminZRWVmpw4cPq7Ky0t2hQFJhYaE++eQTFRYWujsUAADQQtRX1uKJ9RXNINqF3W7XokWLZLfb3R0KJFVUVGjPnj2qqKhwdygAAKCFqK+sxRPrK5pBAAAAAPBCNIMAAAAA4IVoBgEAAADAC9EMol34+PgoLCxMPj685KwgLCxMl156KdNQAwDgwaivrMUT6yuWlgAAAAAAL8THCIAXqqioUEZGhkfNdgUAAGBlnlhf0QyiXeTm5uqVV15Rbm6uu0OBTq6Ds3jxYo9aBwcAALiivrIWT6yvaAbRLmpra+VwOFRbW+vuUAAAAM4K1FdoLZpBAAAAAPBCNIMAAAAA4IVoBgEv5Ofnp06dOsnPz8/doQAAAJwVPLG+YmkJtIvKykplZ2crJiZGAQEB7g4HAADA41FfobVoBgEAAADACzFMFO3C4XBo7dq1cjgc7g4FknJycjR37lzl5OS4OxQAANBC1FfW4on1Fc0g2kVpaak2btyo0tJSd4cCSYZhqLKyUgwMAADAc1FfWYsn1lc0gwAAAADghWgGAQAAAMAL0QwCAAAAgBdiNlG0i+LiYq1fv15Dhw5VRESEu8PxelVVVSooKFDHjh3l7+/v7nAAAEALUF9ZiyfWVzSDAAAAAOCFGCaKdlFdXa28vDxVV1e7OxTo5CeJK1asUHFxsbtDAQAALUR9ZS2eWF/RDKJd5Ofna/78+crPz3d3KJBUXl6u7du3q7y83N2hAACAFqK+shZPrK9oBgEAAADAC9EMAgAAAIAXohkEAAAAAC9EM4h2YbPZ5OvrK5vN5u5QICkkJEQpKSkKCQlxdygAAKCFqK+sxRPrK5aWAAAAAAAvxJVBwAtVVlbq2LFjqqysdHcoAAAAZwVPrK9oBtEu8vPz9eabbzL1sUXY7XYtXLhQdrvd3aEAAIAWor6yFk+sr2gG0S6qq6uVk5PDoqgAAABthPoKrUUzCAAAAABeiGYQAAAAALwQzSDghXx8fBQcHCwfH94CAAAA2oIn1lcsLYF24XQ6dejQIXXv3l1BQUHuDgcAAMDjUV+htWgGAQAAAMALec41THi00tJSbdmyRaWlpe4OBZLy8vL02muvKS8vz92hAACAFqK+shZPrK9oBtEuHA6HVq9eLYfD4e5QIKmmpkaFhYWqqalxdygAAKCFqK+sxRPrK5pBAAAAAPBCNIMAAAAA4IVoBgEAAADAC9EMol0EBgbq3HPPVWBgoLtDgaSoqCjddNNNioqKcncoAACghaivrMUT6yuWlgAAAAAAL8SVQbSL2tpalZWVqba21t2hQCenov7mm2+YihoAAA9GfWUtnlhf0QyiXeTm5urll19Wbm6uu0OBTk5FvX79eqaiBgDAg1FfWYsn1lc0gwAAAADghWgGAQAAAMAL0QwCAAAAgBeiGQS8UFBQkHr37q2goCB3hwIAAHBW8MT6iqUl0C4Mw1BVVZX8/f1ls9ncHQ4AAIDHo75Ca3FlEO3CZrMpICCANyqLqK6ult1uV3V1tbtDAQAALUR9ZS2eWF/RDKJd2O12vf/++7Lb7e4OBZLy8/M1b9485efnuzsUAADQQtRX1uKJ9RXNINpFZWWlMjMzVVlZ6e5QAAAAzgrUV2gtmkEAAAAA8EI0gwAAAADghWgGAQAAAMALsbQE2kVZWZn27NmjXr16KSQkxN3hAAAAeDzqK7QWzSAAAAAAeCGGiaJdOJ1Opaeny+l0ujsUSCooKNDChQtVUFDg7lAAAEALUV9ZiyfWVzSDaBdFRUVasmSJioqK3B0KJFVVVenYsWOqqqpydygAAKCFqK+sxRPrK5pBAAAAAPBCNIMAAAAA4IVoBgEAAADAC9EMol34+/srLi5O/v7+7g4FkiIjIzVu3DhFRka6OxQAANBC1FfW4on1FUtLAAAAAIAX4sog4IXKysq0fft2lZWVuTsUAACAs4In1lc0g2gX2dnZeu6555Sdne3uUCCppKREK1asUElJibtDAQAALUR9ZS2eWF/RDAIAAACAF6IZBAAAAAAvRDMIAAAAAF6IZhDwQgEBAUpMTFRAQIC7QwEAADgreGJ9xdISaBfV1dUqKSlReHi4/Pz83B0OAACAx6O+QmvRDAJeyDAMVVVVyd/fXzabzd3hAAAAeDxPrK8YJop2UVRUpCVLlqioqMjdoUBSTk6O5s6dq5ycHHeHAgAAWoj6ylo8sb7ymmZw7dq1Gj9+vOLi4mSz2fTxxx+7bP/oo480ZswYRUdHy2azKS0trd45Lr/8ctlsNpefiRMnmtvXrFlTb3vdz+bNm839srKyNH78eIWGhio6Olr33nuvKisrXe5r586dGjFihIKDgxUfH6/Zs2fLky/iOp1Opaeny+l0ujsUAACAswL1FVrLawYXl5aWqn///po+fbpuvPHGBrcPGzZMEyZM0IwZMxo9z4wZMzR79mzz/8HBwea/hw4dquPHj7vs/9hjj2nFihVKSUmRJNXU1GjcuHHq3Lmz1q1bp/z8fE2dOlWGYejFF1+UJBUXF+vKK69UamqqNm/erL1792ratGkKDQ3Vgw8+2KrnAQAAAAAkL2oGx44dq7Fjxza6ffLkyZKkzMzMJs8TEhKi2NjYBrcFBAS4bKuqqtInn3yie+65xxw3vHz5cqWnp+vw4cOKi4uTJL3wwguaNm2annrqKUVERGjhwoVyOp1asGCBAgMD1bdvX+3du1dz5szRAw884DFjkAEAAABYl9c0g21l4cKFevvttxUTE6OxY8dq1qxZCg8Pb3DfTz75RHl5eZo2bZp524YNG9S3b1+zEZSkMWPGqKKiQlu3blVqaqo2bNigESNGKDAw0GWfmTNnKjMzUz169Gjw/ioqKlRRUeFyW2BgoMt53KmsrExZWVmSpLCwMDkcDtntdlVXV0s62UxHRkYqPDxcJSUlKisrU2lpqXl8dHS0+VgqKiqUl5dnbgsNDVVISIh5bFFRkTn01s/PT1FRUeZ9Op1OlZSUmMdGRUUpKChIfn5+cjqdys3NNbeFhIQoNDTUPG9JSYk5FMPHx0edOnVSaGioysvL5XQ6XcbsR0ZGKigoSEFBQSorK1NeXp451DcoKEjh4eFmTKWlpSorKzOP7dy5s4KDg1VVVSWn0ym73W5ui4iIUFBQkEJDQ+VwOFRQUKCamhqX57Cx80ZHRysoKEiFhYUutwMAAM9EfUV91Ro0g81w8803q0ePHoqNjdWuXbs0c+ZM7dixQ19++WWD+7/++usaM2aMEhISzNtOnDihmJgYl/2ioqIUEBCgEydOmPskJia67FN3zIkTJxptBp955hk9+eSTLrfNmjVLTzzxRHMe5k+iqqpKmzZtkt1uV3x8vFJTU7V69Wpt27ZNxcXFkqROnTqpX79+GjlypFatWqWjR49q37595jmGDx+unj17SpIyMjK0bt06c1tSUpLi4+PNY3fu3Kn8/HxJJ3+5k5OTzfvMzc3V7t27zWMvvvhiJSYmKjo6Wunp6Vq7dq1qa2slSYmJiUpMTDTPu2fPHnMocHBwsAYPHqzBgwfru+++0/Hjx12+azpw4EDFx8fr/PPP15YtW7RhwwazWY+Pj1dSUpKuuOIKrVy5UgcOHDDfyP38/DR8+HD169dPx44dU1ZWlst3Tvv27auYmBgNHTpUX3/9tbZs2SKHwyHp5Jtcnz59zHiPHDmijIwM89jLLrtMSUlJcjqd8vPzYxpqAAA8GPUV9VVreeXSEjabTYsXL9bPf/7zetvqrrxt375dAwYMaPI8W7duVUpKirZu3ark5GSXbUeOHFH37t313nvvuXxH8fbbb9ehQ4e0bNkyl/0DAgL01ltvaeLEiRo9erR69OihV1991dx+9OhRdevWTRs2bNAll1zSYDxWvjKYnZ2tefPmmc0xn1y595OrvLw8LV68WFOmTKn34QQAAPAM1FfUV63lOW2rBSUnJ8vf31/79u2r1wzOnz9fnTp10rXXXutye2xsrDZu3Ohym91uV1VVlfmiiY2NNa8S1qmborapF5ZVGr/GBAQEKCEhwXwMoaGhjT6ekJCQ056vse9uhoSENHre0NDQJs8ZGRnZZEyNbQsLC5Mkl6vApwoPD29xTNLJT7oaO7Yl5/3xhwYAAMAzUV9RX7WG1ywt8VPYvXu3qqqq1LVrV5fbDcPQ/PnzNWXKFPn7+7tsGzJkiHbt2uUy6+jy5csVGBioQYMGmfusXbvWZbmJ5cuXKy4urt7wUQAAAABoCa9pBh0Oh9LS0swxxwcPHlRaWpo5jrigoEBpaWlKT0+XJO3Zs0dpaWnmFbr9+/dr9uzZ2rJlizIzM7V06VJNmDBBAwcO1LBhw1zua9WqVTp48KBuu+22enGMHj1avXv31uTJk7V9+3atXLlSv/vd7zRjxgxFRERIkiZNmqTAwEBNmzZNu3bt0uLFi/X000979Eyifn5+6tKli0eNoT6bRUREaMyYMeZrDgAAeB7qK2vxxPrKa74zuGbNGqWmpta7ferUqVqwYIEWLFig6dOn19teNwHL4cOHdcstt2jXrl1yOBxKSEjQuHHjNGvWLHXs2NHlmEmTJunQoUP65ptvGowlKytLd911l1atWqXg4GBNmjRJzz//vMsQz507d+ruu+/Wpk2bFBUVpTvvvFOPP/64xzaDAAAAAKzFa5pBAP9TXl6uffv2KSkpScHBwe4OBwAAwON5Yn3lNcNE4V45OTmaM2eOOREO3Ku4uFjLli0zp50GAACeh/rKWjyxvqIZRLswDEM1NTXiQjQAAEDboL5Ca9EMAgAAAIAXohkEAAAAAC9EMwh4oboFagMCAtwdCgAAwFnBE+srZhNFu6iurlZhYaE6dOjAWjgAAABtgPoKrUUzCHghwzBUW1srHx8f1q4EAABoA55YXzFMFO2iuLhYX3zxhUdNtXs2YypqAAA8H/WVtXhifUUziHZRXl6unTt3qry83N2hAAAAnBWor9BaNIMAAAAA4IVoBgEAAADAC9EMAgAAAIAXYjZRtAuHw6Ft27YpOTlZYWFh7g7H69XU1KisrEwhISHy9fV1dzgAAKAFqK+sxRPrK5pBAAAAAPBCDBNFu6isrNThw4dVWVnp7lAgqbCwUJ988okKCwvdHQoAAGgh6itr8cT6imYQ7cJut2vRokWy2+3uDgWSKioqtGfPHlVUVLg7FAAA0ELUV9biifUVzSAAAAAAeCGaQQAAAADwQjSDAAAAAOCFaAbRLnx8fBQWFiYfH15yVhAWFqZLL72UaagBAPBg1FfW4on1FUtLAAAAAIAX4mMEwAtVVFQoIyPDo2a7AgAAsDJPrK9oBtEucnNz9corryg3N9fdoUAn18FZvHixR62DAwAAXFFfWYsn1lc0g2gXtbW1cjgcqq2tdXcoAAAAZwXqK7QWzSAAAAAAeCGaQQAAAADwQjSDgBfy8/NTp06d5Ofn5+5QAAAAzgqeWF+xtATaRWVlpbKzsxUTE6OAgAB3hwMAAODxqK/QWjSDAAAAAOCFGCaKduFwOLR27Vo5HA53hwJJOTk5mjt3rnJyctwdCgAAaCHqK2vxxPqKZhDtorS0VBs3blRpaam7Q4EkwzBUWVkpBgYAAOC5qK+sxRPrK5pBAAAAAPBCNIMAAAAA4IVoBgEAAADACzGbKNpFcXGx1q9fr6FDhyoiIsLd4Xi9qqoqFRQUqGPHjvL393d3OAAAoAWor6zFE+srmkEAAAAA8EIME0W7qK6uVl5enqqrq90dCnTyk8QVK1aouLjY3aEAAIAWor6yFk+sr2gG0S7y8/M1f/585efnuzsUSCovL9f27dtVXl7u7lAAAEALUV9ZiyfWVzSDAAAAAOCFaAYBAAAAwAvRDAIAAACAF6IZRLuw2Wzy9fWVzWZzdyiQFBISopSUFIWEhLg7FAAA0ELUV9biifUVS0sAAAAAgBfiyiDghSorK3Xs2DFVVla6OxQAAICzgifWVzSDaBf5+fl68803mfrYIux2uxYuXCi73e7uUAAAQAtRX1mLJ9ZXNINoF9XV1crJyWFRVAAAgDZCfYXWohkEAAAAAC9EMwgAAAAAXohmEPBCPj4+Cg4Olo8PbwEAAABtwRPrK5aWQLtwOp06dOiQunfvrqCgIHeHAwAA4PGor9BaNIMAAAAA4IU85xomPFppaam2bNmi0tJSd4cCSXl5eXrttdeUl5fn7lAAAEALUV9ZiyfWVzSDaBcOh0OrV6+Ww+FwdyiQVFNTo8LCQtXU1Lg7FAAA0ELUV9biifUVzSAAAAAAeCGaQQAAAADwQjSDAAAAAOCFaAbRLgIDA3XuuecqMDDQ3aFAUlRUlG666SZFRUW5OxQAANBC1FfW4on1FUtLAAAAAIAX4sog2kVtba3KyspUW1vr7lCgk1NRf/PNN0xFDQCAB6O+shZPrK9oBtEucnNz9fLLLys3N9fdoUAnp6Jev349U1EDAODBqK+sxRPrK5pBAAAAAPBCNIMAAAAA4IVoBgEAAADAC9EMAl4oKChIvXv3VlBQkLtDAQAAOCt4Yn3F0hJoF4ZhqKqqSv7+/rLZbO4OBwAAwONRX6G1uDKIdmGz2RQQEMAblUVUV1fLbrerurra3aEAAIAWor6yFk+sr2gG0S7sdrvef/992e12d4cCSfn5+Zo3b57y8/PdHQoAAGgh6itr8cT6imYQ7aKyslKZmZmqrKx0dygAAABnBeortBbNIAAAAAB4IZpBAAAAAPBCNIMAAAAA4IVYWgLtoqysTHv27FGvXr0UEhLi7nAAAAA8HvUVWotmEAAAAAC8EMNE0S6cTqfS09PldDrdHQokFRQUaOHChSooKHB3KAAAoIWor6zFE+srmkG0i6KiIi1ZskRFRUXuDgWSqqqqdOzYMVVVVbk7FAAA0ELUV9biifUVzSAAAAAAeCGaQQAAAADwQjSDAAAAAOCFaAbRLvz9/RUXFyd/f393hwJJkZGRGjdunCIjI90dCgAAaCHqK2vxxPqKpSUAAAAAwAtxZRDwQmVlZdq+fbvKysrcHQoAAMBZwRPrK5pBtIvs7Gw999xzys7OdncokFRSUqIVK1aopKTE3aEAAIAWor6yFk+sr2gGAQAAAMAL0QwCAAAAgBeiGQQAAAAAL0QzCHihgIAAJSYmKiAgwN2hAAAAnBU8sb5iaQm0i+rqapWUlCg8PFx+fn7uDgcAAMDjUV+htWgGAS9kGIaqqqrk7+8vm83m7nAAAAA8nifWVwwTRbsoKirSkiVLVFRU5O5QICknJ0dz585VTk6Ou0MBAAAtRH1lLZ5YX3lNM7h27VqNHz9ecXFxstls+vjjj122f/TRRxozZoyio6Nls9mUlpZW7xyXX365bDaby8/EiRPr7bdkyRINHjxYwcHBio6O1g033OCyPSsrS+PHj1doaKiio6N17733qrKy0mWfnTt3asSIEQoODlZ8fLxmz54tT76I63Q6lZ6eLqfT6e5QAAAAzgrUV2gtrxlcXFpaqv79+2v69Om68cYbG9w+bNgwTZgwQTNmzGj0PDNmzNDs2bPN/wcHB7ts//DDDzVjxgw9/fTTGjlypAzD0M6dO83tNTU1GjdunDp37qx169YpPz9fU6dOlWEYevHFFyVJxcXFuvLKK5WamqrNmzdr7969mjZtmkJDQ/Xggw+29qkAAAAAAO9pBseOHauxY8c2un3y5MmSpMzMzCbPExISotjY2Aa3VVdX67777tNzzz2n2267zby9V69e5r+XL1+u9PR0HT58WHFxcZKkF154QdOmTdNTTz2liIgILVy4UE6nUwsWLFBgYKD69u2rvXv3as6cOXrggQc8ZgwyAAAAAOvymmawrSxcuFBvv/22YmJiNHbsWM2aNUvh4eGSpG3btuno0aPy8fHRwIEDdeLECQ0YMEDPP/+8+vTpI0nasGGD+vbtazaCkjRmzBhVVFRo69atSk1N1YYNGzRixAgFBga67DNz5kxlZmaqR48eDcZWUVGhiooKl9sCAwNdzuNOZWVlysrKkiSFhYXJ4XDIbrerurpa0snpeCMjIxUeHq6SkhKVlZWptLTUPD46Otp8LBUVFcrLyzO3hYaGKiQkxDy2qKjIHHrr5+enqKgo8z6dTqdKSkrMY6OiohQUFCQ/Pz85nU7l5uaa20JCQhQaGmqet6SkxByK4ePjo06dOik0NFTl5eVyOp0uY/YjIyMVFBSkoKAglZWVKS8vzxzqGxQUpPDwcDOm0tJSlZWVmcd27txZwcHBqqqqktPplN1uN7dFREQoKChIoaGhcjgcKigoUE1Njctz2Nh5o6OjFRQUpMLCQpfbAQCAZ6K+or5qDZrBZrj55pvVo0cPxcbGateuXZo5c6Z27NihL7/8UpJ04MABSdITTzyhOXPmKDExUS+88IJGjBihvXv3qmPHjjpx4oRiYmJczhsVFaWAgACdOHFCknTixAklJia67FN3zIkTJxptBp955hk9+eSTLrfNmjVLTzzxRGsfeqtVVVVp06ZNstvtio+PV2pqqlavXq1t27apuLhYktSpUyf169dPI0eO1KpVq3T06FHt27fPPMfw4cPVs2dPSVJGRobWrVtnbktKSlJ8fLx57M6dO5Wfny/p5C93cnKyeZ+5ubnavXu3eezFF1+sxMRERUdHKz09XWvXrlVtba0kKTExUYmJieZ59+zZo+PHj0s6OUR48ODBGjx4sL777jsdP37c5bumAwcOVHx8vM4//3xt2bJFGzZsMJv1+Ph4JSUl6YorrtDKlSt14MAB843cz89Pw4cPV79+/XTs2DFlZWVp8+bN5nn79u2rmJgYDR06VF9//bW2bNkih8Mh6eSbXJ8+fcx4jxw5ooyMDPPYyy67TElJSXI6nfLz82MaaqARttcOujsEnMKY0fDfPcDbUV9RX7WW50RqAad+l7Bv375KSkpSSkqKtm3bpuTkZPMF/sgjj5jfS5w/f766deum999/X3fccYckNTjM0zAMl9t/vE/dJx5NDRGdOXOmHnjgAZfbrHJV0N/fX0OHDtWYMWOUkJCgsLAwJSQkaPz48Q1+ctWtW7cmP7m69NJLNX78eHPbqZ9cdevWrdFPrhISEpr85ColJcVlOPGpn1x169at0U+uLrjggiY/uerdu7euvvrqBj+5io+PP+0nVzfddJO57dRPrnr06KFrrrmmwU+uunXr1ugnV3l5eTp69Kj53AMAAM9DfUV91Vo0g62QnJwsf39/7du3T8nJyerataskqXfv3uY+gYGBOuecc8xPJWJjY7Vx40aX89jtdlVVVZlX/2JjY82rhHXqpqj98VXFU1lpSGhDAgIClJCQYD6G0NDQRh9PSEjIac/X2Hc3Q0JCGj1vaGhok+eMjIxsMqbGtoWFhUmSEhISGtweHh7e4pikk590NXZsS8774+HEAADAM1FfUV+1htcsLfFT2L17t6qqqswmcNCgQQoMDNSePXvMfaqqqpSZmanu3btLkoYMGaJdu3aZl8Klk5PKBAYGatCgQeY+a9eudVluYvny5YqLi6s3fBQAAAAAWsJrmkGHw6G0tDRzzPHBgweVlpZmXrErKChQWlqa0tPTJUl79uxRWlqaeYVu//79mj17trZs2aLMzEwtXbpUEyZM0MCBAzVs2DBJJy8v33nnnZo1a5aWL1+uPXv26De/+Y0kacKECZKk0aNHq3fv3po8ebK2b9+ulStX6ne/+51mzJihiIgISdKkSZMUGBioadOmadeuXVq8eLGefvppj55J1M/PT126dPGoMdRns4iICI0ZM8Z8zQEAAM9DfWUtnlhf2QxPXsm8GdasWaPU1NR6t0+dOlULFizQggULNH369Hrb6yZgOXz4sG655Rbt2rVLDodDCQkJGjdunGbNmqWOHTua+1dVVWnmzJn697//rfLycg0ePFh/+9vfzNlEpZOLzt91111atWqVgoODNWnSJD3//PMuQzx37typu+++W5s2bVJUVJTuvPNOPf744x7bDAKAJ2ECGWthAhkA+Gl4TTMI4H/Ky8u1b98+JSUlKTg42N3hAJZDM2gtNIMAPIEn1ldeM0wU7pWTk6M5c+aYE+HAvYqLi7Vs2TJz2mkAAOB5qK+sxRPrK5pBtAvDMFRTUyMuRAMAALQN6iu0Fs0gAAAAAHghmkEAAAAA8EI0g4AXqlugNiAgwN2hAAAAnBU8sb5iNlG0i+rqahUWFqpDhw6shQPA8phN1FqYTRRoGPUVWqtVr5pzzjnntPv4+PgoIiJCvXr10vXXX69f/OIXrblLeCg/Pz9FR0e7Owz8H8MwVFtbKx8fH9auBADAQ1FfWYsn1letGiZaW1uryspKZWZmKjMzU0eOHJHT6dSRI0fM25xOpzIyMvTuu+/qV7/6lUaPHq3Kysq2ih8eori4WF988YVHTbV7NmMqagAAPB/1lbV4Yn3VqmYwLS1NXbt21ahRo7RhwwZVVFTo2LFjqqio0Pr163XFFVcoLi5OWVlZ2rt3r66++mqtXLlSL7zwQlvFDw9RXl6unTt3qry83N2hAAAAnBWor9BarWoGH3roIVVUVOiLL77Q4MGDzcuhNptNl1xyib744gs5nU49/PDD6tmzp95//311795dixYtapPgAQAAAAAt06pm8L///a+uvvpq+fg0fBpfX19dffXV+u9//ytJCgoK0siRI5WRkdGauwUAAAAAtFKrmsHi4uLTjlEuKipSUVGR+X++5AoAAAAA7teqZrB379569913dejQoQa3Z2Zm6t1331Xv3r3N27KystS5c+fW3C08UGhoqAYPHqzQ0FB3hwKd/FDmzjvv5MMZAAA8GPWVtXhifdWqdQY/+ugj3XTTTYqIiNCMGTM0ZMgQde7cWbm5uVq/fr3mzZunkpISvf/++7rhhhtUWVmpuLg4jR49Wv/5z3/a8nEAANBmWGfQWlhnEAB+Gq1edP6NN97Q/fffL4fD4bKehmEYCgsL05w5c/TrX/9aklRYWKivvvpKffr0Uc+ePVsXOTxKZWWlsrOzFRMTo4CAAHeH4/UKCwu1du1aXXbZZerQoYO7wwEsh2bQWmgGgYZRX1mLJ9ZXrVp0XpJuvfVW3Xjjjfrvf/+rHTt2qLi4WBEREerfv7+uu+46RUZGmvt26NBB1113XWvvEh7Ibrdr0aJFmjJlimJiYtwdjterqKjQnj17NHjwYHeHAgAAWoj6ylo8sb5qdTMoSZGRkZoyZUpbnAoAAAAA0A5aNYEMAAAAAMAztfrKYGVlpT7++GNt3rxZhYWFqqmpqbePzWbT66+/3tq7AgAAAAC0kVY1g4cOHdKVV16p/fv3q6l5aGgG4ePjo7CwMPn4cDHaCsLCwnTppZcqLCzM3aEAAIAWor6yFk+sr1o1m+gNN9ygjz/+WJMnT9att96qbt26yc+v4f6ye/fuLQ4SAID2xGyi1sJsogDw02jVlcFVq1bpiiuu0JtvvtlW8QBoBxUVFTp8+LASEhIUGBjo7nAAAAA8nifWV626plxbW6uBAwe2VSw4i+Xm5uqVV15Rbm6uu0OBTq6Ds3jxYhUWFro7FAAA0ELUV9biifVVq5rBIUOG6Pvvv2+rWHAWq62tlcPhUG1trbtDAQAAOCtQX6G1WtUMPvvss1q9erU++OCDtooHAAAAANAOWvWdwU8//VSpqan65S9/qREjRmjgwIGKjIyst5/NZtNjjz3WmrsCAAAAALShVjWDTzzxhPnvNWvWaM2aNQ3uRzMIWIufn586derU6Oy/AAAAaB5PrK9atbTEV199dcb7jhgxoqV3g7NAZWWlsrOzFRMTo4CAAHeHAwBNYmkJa2FpCaBh1FdorVY1gwAAnI1oBq2FZhAAfhqtmkAGOFMOh0Nr166Vw+FwdyiQlJOTo7lz5yonJ8fdoQAAgBaivrIWT6yvmjWgNSsrS5IUHx8vX19f8/9n4mc/+1nzIsNZpbS0VBs3blSvXr0UFhbm7nC8nmEYqqysFAMDAADwXNRX1uKJ9VWzmsHExETZbDZ9//33Ou+888z/n47NZlN1dXWLgwQAAAAAtK1mNYNTpkyRzWYzl4+o+z8AAAAAwLM0qxlcsGBBk/8HAAAAAHgGJpBBuwgODla/fv0UHBzs7lAgqWPHjpoyZYo6duzo7lAAAEALUV9ZiyfWVywtAQDAj7C0hLWwtAQA/DSaNUy0Ienp6XrppZe0efNmFRYWqqampt4+NptN+/fvb+1dwYNVV1ersLBQHTp0kJ9fq192aKXi4mJt2rRJF198sSIiItwdDgAAaAHqK2vxxPqqVcNEv/rqKw0aNEj//Oc/tWPHDjmdThmGUe+ntra2reKFh8rPz9f8+fOVn5/v7lAgqby8XNu3b1d5ebm7QwEAAC1EfWUtnlhfteojhIcffljV1dWaN2+epk6dKl9f37aKCwAAAADwE2pVM7hjxw5NnDhRt956a1vFAwAAAABoB60aJhoeHq4uXbq0VSwAAAAAgHbSqmZw3Lhx+vrrr9sqFpzFbDabfH19ZbPZ3B0KJIWEhCglJUUhISHuDgUAALQQ9ZW1eGJ91aqlJfLy8jRs2DCNGTNGzz77rEc9cAAAGsPSEtbC0hIA8NNoVjM4cuTIercVFhZqx44dCg0NVVJSkiIjI+vfic2mlStXti5SAG2msrJSeXl5io6OVkBAgLvDASyHZtBaaAYBeAJPrK+a1Qz6+LRsVKnNZmtw/UF4j/z8fH322We65ppr1KlTJ3eH4/Wys7P11ltvacqUKYqJiXF3OIDl0AxaC80g0DDqK2vxxPqqWbOJsl4gWqq6ulo5OTmqrq52dygAAABnBeortFarJpABAAAAAHimVjWDI0eO1FtvvdXkPu+8806D3zUEAAAAALhPq5rBNWvWKDMzs8l9srKy9NVXX7XmbgC0MR8fHwUHB7f4e8AAAABw5Yn1VbO+M9gSpaWl8vf3/6nvBhYXGRmpa6+9tsHZZtH+OnfurHvuucfdYQAAgFagvrIWT6yvmt0MZmVlufy/sLCw3m2SVFNToyNHjuj9999XYmJiiwPE2SEoKEi9evVydxgAAABnDeortFazF5338fGRzWY74/0Nw9Bzzz2nBx98sNnB4exRWlqq77//XhdccIFCQ0PdHY7Xy8vL0+LFi3X99dcrOjra3eEAlsPSEtbC0hJAw6ivrMUT66tmXxmcMmWKbDabDMPQW2+9pf79+2vAgAH19vP19VXHjh01cuRIXXXVVW0RKzyYw+HQ6tWrlZCQwJuVBdTU1KiwsJD1PwEA8GDUV9biifVVs5vBBQsWmP/+6quvNH36dN17771tGRMAAAAA4CfWqqlupk2bpo4dO7ZVLAAAAACAdtKqZvCpp57Szp072yoWAAAAAEA7aVUz2L17dxUUFLRVLDiLBQYG6txzz1VgYKC7Q4GkqKgo3XTTTYqKinJ3KAAAoIWor6zFE+urZs8meqrHH39cCxYs0M6dO1nfBABw1mA2UWthNlEA+Gm06srgo48+qgsvvFAjR47UkiVLlJOT01Zx4SxTW1ursrIy1dbWujsU6ORU1N98841KS0vdHQoAAGgh6itr8cT6qlXNYHBwsD7//HNt375d1157rbp27SpfX996P35+zZ60FGeZ3Nxcvfzyy8rNzXV3KNDJqajXr18vh8Ph7lAAAEALUV9ZiyfWV63q0i699NJmLUAPAAAAALCGVjWDa9asaaMwAAAAAADtqVXDRAEAAAAAnqnNvsx39OhR7dixQ0VFRYqIiNCAAQMUHx/fVqcH0IaCgoLUu3dvBQUFuTsUAACAs4In1letWlpCkg4cOKA777xTK1eurLftiiuu0D/+8Q/17NmzNXeBs4BhGKqqqpK/vz/fMwVgeSwtYS0sLQE0jPoKrdWqK4NHjhzRsGHDlJ2drQsuuECXXXaZYmNjlZ2dra+//lorVqzQpZdeqk2bNikhIaGtYoYHstlsCggIcHcY+D/V1dUqKSlReHg4s/0CAOChqK+sxRPrq1Z9Z/CJJ55Qdna2/vWvf2n37t165ZVXNGvWLP3jH//Qzp079dprryknJ0ezZ89uq3jhoex2u95//33Z7XZ3hwJJ+fn5mjdvnvLz890dCgAAaCHqK2vxxPqqVc3gsmXLdO211+rXv/51g9tvu+02jR8/Xp9//nlr7gZngcrKSmVmZqqystLdoQAAAJwVqK/QWq1qBnNyctSnT58m9+nTpw8LYQIAAACAxbSqGezcubN2797d5D7p6enq3Llza+4GAAAAANDGWtUMjhkzRp9++qlef/31Bre/8cYb+vTTT3XVVVe15m4AAAAAAG2sVUtLHD58WCkpKcrLy1Pv3r01YsQIxcTEKDs7W2vXrtXu3bsVHR2tLVu2MJuolysrK9OePXvUq1cvhYSEuDscAGgSS0tYC0tLAA2jvkJrtXqdwYyMDN1xxx1avXp1vW2pqal65ZVXdN5557XmLgAAaFc0g9ZCMwgAP41WN4N1jhw5ou3bt6u4uFgREREaMGAAVwNhcjqdOnDggM455xwFBQW5OxyvV1BQoM8//1xjx45Vx44d3R0OYDk0g9ZCMwg0jPrKWjyxvmqz1RC7deumbt26tdXpcJYpKirSkiVLNGXKFN6sLKCqqkrHjh1TVVWVu0MBAAAtRH1lLZ5YXzW7GbzrrruafSc2m00vv/xys48DAAAAAPw0mt0M/vOf/zzjfW02m/lvmkEAAAAAsI5mN4MNTRTTkKysLM2ePVv79+93aQoBAAAAAO7X7GZwxIgRTW632+16+umn9fLLL8vpdGrIkCH6y1/+0uIAcXbw9/dXXFyc/P393R0KJEVGRmrcuHGKjIx0dygAAKCFqK+sxRPrqzabTdTpdOpvf/ub/vrXv6qwsFDnn3++nn76af385z9vi9MDANBumE3UWphNFAB+Gj6tPYFhGJo3b56SkpL0xz/+USEhIfrXv/6lXbt20QgCFlVWVqbt27errKzM3aEAAACcFTyxvmpVM/jxxx+rT58+uuOOO+RwOPT0008rIyNDv/71r+Xj0+o+E2eR7OxsPffcc8rOznZ3KJBUUlKiFStWqKSkxN2hAACAFqK+shZPrK9atM7gunXr9NBDD+nbb79VQECAfvvb3+qRRx5RVFRUW8cHAAAAAPgJNLsZvPbaa7VkyRL5+Pho6tSpmj17NovNAwAAAICHaXYz+Nlnn8lms+lnP/uZTpw4odtvv/20x9hsNi1ZsqRFAQIAAAAA2l6LhokahqGDBw/q4MEzm22NdQYBawkICFBiYqICAgLcHQoAAMBZwRPrq2YvLXHo0KEW3VH37t1bdBzODtXV1SopKVF4eLj8/Fr0GQQAtBuWlrAWlpYAGkZ9hdZq9quGpg4t4efnxwRDFmIYhqqqquTv78+VewAAPBT1lbV4Yn3F+g9oF0VFRVqyZImKiorcHQok5eTkaO7cucrJyXF3KAAAoIWor6zFE+srr2kG165dq/HjxysuLk42m00ff/yxy/aPPvpIY8aMUXR0tGw2m9LS0uqd4/LLL5fNZnP5mThxoss+iYmJ9fZ5+OGHXfbJysrS+PHjFRoaqujoaN17772qrKx02Wfnzp0aMWKEgoODFR8fr9mzZ6uZI3otxel0Kj09XU6n092hAAAAnBWor9BaXjO4uLS0VP3799f06dN14403Nrh92LBhmjBhgmbMmNHoeWbMmKHZs2eb/w8ODq63z+zZs13OERYWZv67pqZG48aNU+fOnbVu3Trl5+dr6tSpMgxDL774oiSpuLhYV155pVJTU7V582bt3btX06ZNU2hoqB588MEWPX4AAAAAOJXXNINjx47V2LFjG90+efJkSVJmZmaT5wkJCVFsbGyT+4SHhze6z/Lly5Wenq7Dhw8rLi5OkvTCCy9o2rRpeuqppxQREaGFCxfK6XRqwYIFCgwMVN++fbV3717NmTNHDzzwgMeMQQYAAABgXV7TDLaVhQsX6u2331ZMTIzGjh2rWbNmKTw83GWfv/zlL/rTn/6khIQETZgwQb///e/NKWY3bNigvn37mo2gJI0ZM0YVFRXaunWrUlNTtWHDBo0YMUKBgYEu+8ycOVOZmZnq0aPhWdUqKipUUVHhcltgYKDLedyprKxMWVlZkk5eLXU4HLLb7aqurpZ0cjreyMhIhYeHq6SkRGVlZSotLTWPj46ONh9LRUWF8vLyzG2hoaEKCQkxjy0qKjKH3tZ9ubruPp1Op0pKSsxjo6KiFBQUJD8/PzmdTuXm5prbQkJCFBoaap63pKTEHIrh4+OjTp06KTQ0VOXl5XI6nS5j9iMjIxUUFKSgoCCVlZUpLy/PHOobFBSk8PBwM6bS0lKVlZWZx3bu3FnBwcGqqqqS0+mU3W43t0VERCgoKEihoaFyOBwqKChQTU2Ny3PY2Hmjo6MVFBSkwsJCl9sBAIBnor6ivmoNmsFmuPnmm9WjRw/FxsZq165dmjlzpnbs2KEvv/zS3Oe+++5TcnKyoqKitGnTJs2cOVMHDx7UvHnzJEknTpxQTEyMy3mjoqIUEBCgEydOmPskJia67FN3zIkTJxptBp955hk9+eSTLrfNmjVLTzzxRGsedpuoqqrSpk2bZLfbFR8fr9TUVK1evVrbtm1TcXGxJKlTp07q16+fRo4cqVWrVuno0aPat2+feY7hw4erZ8+ekqSMjAytW7fO3JaUlKT4+Hjz2J07dyo/P1/SyV/u5ORk8z5zc3O1e/du89iLL75YiYmJio6OVnp6utauXava2lpJJ78DmpiYaJ53z549On78uKSTQ4QHDx6swYMH67vvvtPx48ddvms6cOBAxcfH6/zzz9eWLVu0YcMGs1mPj49XUlKSrrjiCq1cuVIHDhww38j9/Pw0fPhw9evXT8eOHVNWVpY2b95snrdv376KiYnR0KFD9fXXX2vLli1yOBySTr7J9enTx4z3yJEjysjIMI+97LLLlJSUJKfTKT8/P6ahBhrBUgYAPAH1FfVVazV7ncGzgc1m0+LFi/Xzn/+83ra6K2/bt2/XgAEDmjzP1q1blZKSoq1btyo5ObnBfT788EPddNNNysvLU6dOnXT77bfr0KFDWrZsmct+AQEBeuuttzRx4kSNHj1aPXr00KuvvmpuP3r0qLp166YNGzbokksuafC+rHxlMDs7W/PmzdOYMWOUkJDAJ1du/uQqLy9Pixcv1pQpU+p9OAEAADwD9RX1VWt5TttqQcnJyfL399e+ffsabQbrGreMjAx16tRJsbGx2rhxo8s+drtdVVVV5osmNjbWvEpYp26K2qZeWFZp/BoTEBCghIQE8zGEhoY2+nhCQkJOe77GvpcZEhLS6HlDQ0ObPGdkZGSTMTW2rW6SoISEhAa3h4eHtzgm6eQnXY0d25Lz/vhDAwAA4Jmor6ivWsNrlpb4KezevVtVVVXq2rVro/ts375dksx9hgwZol27dpmXwqWTk8oEBgZq0KBB5j5r1651WW5i+fLliouLqzd8FAAAAABawmuuDDocDpexvQcPHlRaWpo6duyon/3sZyooKFBWVpaOHTsmSdqzZ4+kk5+OxMbGav/+/Vq4cKGuvvpqc+zzgw8+qIEDB2rYsGGSTk4O8+233yo1NVWRkZHavHmzfvvb3+raa6/Vz372M0nS6NGj1bt3b02ePFnPPfecCgoK9Lvf/U4zZsxQRESEJGnSpEl68sknNW3aNP3xj3/Uvn379PTTT+vxxx/32JlE/fz81KVLF48aQ302i4iI0JgxY8zXHAAA8DzUV9biifWV13xncM2aNUpNTa13+9SpU7VgwQItWLBA06dPr7e9bgKWw4cP65ZbbtGuXbvkcDiUkJCgcePGadasWerYsaMkadu2bbrrrrv0ww8/qKKiQt27d9fEiRP1hz/8weWyfFZWlu666y6tWrVKwcHBmjRpkp5//nmXIZ47d+7U3XffrU2bNikqKkp33nmnRzeDAAAAAKzFa5pBAP9TXl6uffv2KSkpScHBwe4OBwAAwON5Yn3FdwbRLnJycjRnzhxzIhy4V3FxsZYtW2ZOOw0AADwP9ZW1eGJ9RTOIdmEYhmpqasSFaAAAgLZBfYXWohkEAAAAAC9EMwgAAAAAXohmEPBCdQvUBgQEuDsUAACAs4In1lfMJop2UV1drcLCQnXo0IG1cAAAANoA9RVai2YQ8EKGYai2tlY+Pj6sXQkAANAGPLG+Ypgo2kVxcbG++OILj5pq92zGVNQAAHg+6itr8cT6imYQ7aK8vFw7d+5UeXm5u0MBAAA4K1BfobVoBgEAAADAC9EMAgAAAIAXohkEAAAAAC/EbKJoFw6HQ9u2bVNycrLCwsLcHY7Xq6mpUVlZmUJCQuTr6+vucAAAQAtQX1mLJ9ZXNIMAAAAA4IUYJop2UVlZqcOHD6uystLdoUBSYWGhPvnkExUWFro7FAAA0ELUV9biifUVzSDahd1u16JFi2S3290dCiRVVFRoz549qqiocHcoAACghaivrMUT6yuaQQAAAADwQjSDAAAAAOCFaAYBAAAAwAvRDKJd+Pj4KCwsTD4+vOSsICwsTJdeeinTUAMA4MGor6zFE+srlpYAAAAAAC/ExwiAF6qoqFBGRoZHzXYFAABgZZ5YX9EMol3k5ubqlVdeUW5urrtDgU6ug7N48WKPWgcHAAC4or6yFk+sr2gG0S5qa2vlcDhUW1vr7lAAAADOCtRXaC2aQQAAAADwQjSDAAAAAOCFaAYBL+Tn56dOnTrJz8/P3aEAAACcFTyxvmJpCbSLyspKZWdnKyYmRgEBAe4OBwAAwONRX6G1aAYBAAAAwAsxTBTtwuFwaO3atXI4HO4OBZJycnI0d+5c5eTkuDsUAADQQtRX1uKJ9RXNINpFaWmpNm7cqNLSUneHAkmGYaiyslIMDAAAwHNRX1mLJ9ZXNIMAAAAA4IVoBgEAAADAC9EMAgAAAIAXYjZRtIvi4mKtX79eQ4cOVUREhLvD8XpVVVUqKChQx44d5e/v7+5wAABAC1BfWYsn1lc0gwAAAADghRgminZRXV2tvLw8VVdXuzsU6OQniStWrFBxcbG7QwEAAC1EfWUtnlhf0QyiXeTn52v+/PnKz893dyiQVF5eru3bt6u8vNzdoQAAgBaivrIWT6yvaAYBAAAAwAvRDAIAAACAF6IZBAAAAAAvRDOIdmGz2eTr6yubzebuUCApJCREKSkpCgkJcXcoAACghaivrMUT6yuWlgAAAAAAL8SVQcALVVZW6tixY6qsrHR3KAAAAGcFT6yvaAbRLvLz8/Xmm28y9bFF2O12LVy4UHa73d2hAACAFqK+shZPrK9oBtEuqqurlZOTw6KoAAAAbYT6Cq1FMwgAAAAAXohmEAAAAAC8EM0g4IV8fHwUHBwsHx/eAgAAANqCJ9ZXLC2BduF0OnXo0CF1795dQUFB7g4HAADA41FfobVoBgEAAADAC3nONUx4tNLSUm3ZskWlpaXuDgWS8vLy9NprrykvL8/doQAAgBaivrIWT6yvaAbRLhwOh1avXi2Hw+HuUCCppqZGhYWFqqmpcXcoAACghaivrMUT6yuaQQAAAADwQjSDAAAAAOCFaAYBAAAAwAvRDKJdBAYG6txzz1VgYKC7Q4GkqKgo3XTTTYqKinJ3KAAAoIWor6zFE+srlpYAAAAAAC/ElUG0i9raWpWVlam2ttbdoUAnp6L+5ptvmIoaAAAPRn1lLZ5YX9EMol3k5ubq5ZdfVm5urrtDgU5ORb1+/XqmogYAwINRX1mLJ9ZXNIMAAAAA4IVoBgEAAADAC9EMAgAAAIAXohkEvFBQUJB69+6toKAgd4cCAABwVvDE+oqlJdAuDMNQVVWV/P39ZbPZ3B0OAACAx6O+QmtxZRDtwmazKSAggDcqi6iurpbdbld1dbW7QwEAAC1EfWUtnlhf0QyiXdjtdr3//vuy2+3uDgWS8vPzNW/ePOXn57s7FAAA0ELUV9biifUVzSDaRWVlpTIzM1VZWenuUAAAAM4K1FdoLZpBAAAAAPBCNIMAAAAA4IVoBgEAAADAC7G0BNpFWVmZ9uzZo169eikkJMTd4QAAAHg86iu0Fs0gAAAAAHghhomiXTidTqWnp8vpdLo7FEgqKCjQwoULVVBQ4O5QAABAC1FfWYsn1lc0g2gXRUVFWrJkiYqKitwdCiRVVVXp2LFjqqqqcncoAACghaivrMUT6yuaQQAAAADwQjSDAAAAAOCFaAYBAAAAwAvRDKJd+Pv7Ky4uTv7+/u4OBZIiIyM1btw4RUZGujsUAADQQtRX1uKJ9RVLSwAAAACAF+LKIOCFysrKtH37dpWVlbk7FAAAgLOCJ9ZXNINoF9nZ2XruueeUnZ3t7lAgqaSkRCtWrFBJSYm7QwEAAC1EfWUtnlhf0QwCAAAAgBeiGQQAAAAAL0QzCAAAAABeiGYQ8EIBAQFKTExUQECAu0MBAAA4K3hifcXSEmgX1dXVKikpUXh4uPz8/NwdDgAAgMejvkJr0QwCXsgwDFVVVcnf3182m83d4QAAAHg8T6yvGCaKdlFUVKQlS5aoqKjI3aFAUk5OjubOnaucnBx3hwIAAFqI+spaPLG+8ppmcO3atRo/frzi4uJks9n08ccfu2z/6KOPNGbMGEVHR8tmsyktLa3eOS6//HLZbDaXn4kTJzZ4fxUVFRowYECD58rKytL48eMVGhqq6Oho3XvvvaqsrHTZZ+fOnRoxYoSCg4MVHx+v2bNny5Mv4jqdTqWnp8vpdLo7FAAAgLMC9RVay2uawdLSUvXv318vvfRSo9uHDRumZ599tsnzzJgxQ8ePHzd/Xn311Qb3+8Mf/qC4uLh6t9fU1GjcuHEqLS3VunXrtGjRIn344Yd68MEHzX2Ki4t15ZVXKi4uTps3b9aLL76o559/XnPmzGnGIwYAAACAxnnNN03Hjh2rsWPHNrp98uTJkqTMzMwmzxMSEqLY2Ngm9/n888+1fPlyffjhh/r8889dti1fvlzp6ek6fPiw2Sy+8MILmjZtmp566ilFRERo4cKFcjqdWrBggQIDA9W3b1/t3btXc+bM0QMPPOAxY5ABAAAAWJfXNINtZeHChXr77bcVExOjsWPHatasWQoPDze3Z2dna8aMGfr4448VEhJS7/gNGzaob9++LlcNx4wZo4qKCm3dulWpqanasGGDRowYocDAQJd9Zs6cqczMTPXo0aPB2CoqKlRRUeFyW2BgoMt53KmsrExZWVmSpLCwMDkcDtntdlVXV0s6OR1vZGSkwsPDVVJSorKyMpWWlprHR0dHm4+loqJCeXl55rbQ0FCFhISYxxYVFZlDb/38/BQVFWXep9PpVElJiXlsVFSUgoKC5OfnJ6fTqdzcXHNbSEiIQkNDzfOWlJSYQzF8fHzUqVMnhYaGqry8XE6n02XMfmRkpIKCghQUFKSysjLl5eWZQ32DgoIUHh5uxlRaWqqysjLz2M6dOys4OFhVVVVyOp2y2+3mtoiICAUFBSk0NFQOh0MFBQWqqalxeQ4bO290dLSCgoJUWFjocjsAAPBM1FfUV61BM9gMN998s3r06KHY2Fjt2rVLM2fO1I4dO/Tll19KOjmD0LRp03TnnXcqJSWlwauMJ06cUExMjMttUVFRCggI0IkTJ8x9EhMTXfapO+bEiRONNoPPPPOMnnzySZfbZs2apSeeeKIFj7ZtVVVVadOmTbLb7YqPj1dqaqpWr16tbdu2qbi4WJLUqVMn9evXTyNHjtSqVat09OhR7du3zzzH8OHD1bNnT0lSRkaG1q1bZ25LSkpSfHy8eezOnTuVn58v6eQvd3Jysnmfubm52r17t3nsxRdfrMTEREVHRys9PV1r165VbW2tJCkxMVGJiYnmeffs2aPjx49LkoKDgzV48GANHjxY3333nY4fP+7y/dCBAwcqPj5e559/vrZs2aINGzaYzXp8fLySkpJ0xRVXaOXKlTpw4ID5Ru7n56fhw4erX79+OnbsmLKysrR582bzvH379lVMTIyGDh2qr7/+Wlu2bJHD4ZB08k2uT58+ZrxHjhxRRkaGeexll12mpKQkOZ1O+fn5MQ01AAAejPqK+qq1PCdSC5gxY4b57759+yopKUkpKSnatm2bkpOT9eKLL6q4uFgzZ85s8jwNDfM0DMPl9h/vU/eJR1NDRGfOnKkHHnjA5TarXBX09/fX0KFDNWbMGCUkJCgsLEwJCQkaP358g59cdevWrclPri699FKNHz/e3HbqJ1fdunVr9JOrhISEJj+5SklJcRlOfOonV926dWv0k6sLLrigyU+uevfurauvvrrBT67i4+NP+8nVTTfdZG479ZOrHj166Jprrmnwk6tu3bo1+slVXl6ejh49aj73AADA81BfUV+1Fs1gKyQnJ8vf31/79u1TcnKyVq1apW+//bZeA5aSkqKbb75Zb775pmJjY7Vx40aX7Xa7XVVVVebVv9jYWPMqYZ26KWp/fFXxVFYaEtqQgIAAJSQkmI8hNDS00cfT0BDbH2vsu5shISGNnjc0NLTJc0ZGRjYZU2PbwsLCJEkJCQkNbg8PD29xTNLJT7oaO7Yl5/3xcGIAAOCZqK+or1rDa2YT/Sns3r1bVVVV6tq1qyTp73//u3bs2KG0tDSlpaVp6dKlkqR33/3/27vz6Kjq+//jr8k22chGIBCIgEBRRFlEFNACFlmkWGuhtSjbqbQoP6GCS6lWwBalxVJR2x6rVOQrHloLiIpVZJMiYQkQBMEIAQKSkIRkkjDZl/v7gy/TjoBfCmHuZ3Kfj3M4h9zPnck7eYXwec/9zP38TXPnzpUk9e3bV/v27fNdCpfO3FTG7Xbrxhtv9J2zadMmv+0m1qxZo9TU1HOWjwIAAADApXDMlUGv1+u3tvfIkSPKzMxUUlKSrrrqKhUXF+vYsWPKzc2VJGVlZUk68+pIq1atlJ2draVLl+rOO+/0rX2eMWOGevbsqf79+0uSrrrqKr/PefbVjI4dO6pt27aSpCFDhqhr164aO3as5s+fr+LiYj366KOaNGmS4uLiJEljxozRnDlzNGHCBP3yl7/UwYMH9eyzz+rpp58O2juJhoWFqWXLlkG1hropi4uL09ChQ30/cwAAIPgwvzJLMM6vXFYw72T+X9i4caMGDRp0zvHx48dr8eLFWrx4sSZOnHjO+NkbsBw/flz333+/9u3bJ6/Xq7S0NI0YMUKzZs1SUlLSeT/n2Tt/7t69Wz169PAdP3bsmB566CGtX79eUVFRGjNmjJ5//nm/JZ579+7VlClTtH37diUmJmry5MlB3QwCAAAAMItjmkEA/1ZZWamDBw+qc+fOioqKsrscAACAoBeM8yveM4iAKCgo0IIFC3w3woG9ysrK9NFHH/luOw0AAIIP8yuzBOP8imYQAWFZlurr68WFaAAAgMbB/AqXi2YQAAAAAByIZhAAAAAAHIhmEHCgsxvURkRE2F0KAABAkxCM8yvuJoqAqKurU0lJiRISEtgLBwAAoBEwv8LlohkEHMiyLDU0NCgkJIS9KwEAABpBMM6vWCaKgCgrK9OHH34YVLfabcq4FTUAAMGP+ZVZgnF+RTOIgKisrNTevXtVWVlpdykAAABNAvMrXC6aQQAAAABwIJpBAAAAAHAgmkEAAAAAcCDuJoqA8Hq92rVrl3r16qXY2Fi7y3G8+vp6VVRUKDo6WqGhoXaXAwAALgHzK7ME4/yKZhAAAAAAHIhlogiImpoaHT9+XDU1NXaXAkklJSV69913VVJSYncpAADgEjG/Mkswzq9oBhEQHo9Hy5Ytk8fjsbsUSKqurlZWVpaqq6vtLgUAAFwi5ldmCcb5Fc0gAAAAADgQzSAAAAAAOBDNIAAAAAA4EM0gAiIkJESxsbEKCeFHzgSxsbG67bbbuA01AABBjPmVWYJxfsXWEgAAAADgQLyMADhQdXW1Dh06FFR3uwIAADBZMM6vaAYREIWFhfrzn/+swsJCu0uBzuyDs3LlyqDaBwcAAPhjfmWWYJxf0QwiIBoaGuT1etXQ0GB3KQAAAE0C8ytcLppBAAAAAHAgmkEAAAAAcCCaQcCBwsLC1Lx5c4WFhdldCgAAQJMQjPMrtpZAQNTU1Cg/P18pKSmKiIiwuxwAAICgx/wKl4tmEAAAAAAciGWiCAiv16tNmzbJ6/XaXQokFRQUaOHChSooKLC7FAAAcImYX5klGOdXNIMIiPLycm3btk3l5eV2lwJJlmWppqZGLAwAACB4Mb8ySzDOr2gGAQAAAMCBaAYBAAAAwIFoBgEAAADAgbibKAKirKxMW7ZsUb9+/RQXF2d3OY5XW1ur4uJiJSUlKTw83O5yAADAJWB+ZZZgnF/RDAIAAACAA7FMFAFRV1enU6dOqa6uzu5SoDOvJK5du1ZlZWV2lwIAAC4R8yuzBOP8imYQAVFUVKTXX39dRUVFdpcCSZWVldq9e7cqKyvtLgUAAFwi5ldmCcb5Fc0gAAAAADgQzSAAAAAAOBDNIAAAAAA4EM0gAsLlcik0NFQul8vuUiApOjpavXv3VnR0tN2lAACAS8T8yizBOL9iawkAAAAAcCCuDAIOVFNTo9zcXNXU1NhdCgAAQJMQjPMrmkEERFFRkd544w1ufWwIj8ejpUuXyuPx2F0KAAC4RMyvzBKM8yuaQQREXV2dCgoK2BQVAACgkTC/wuWiGQQAAAAAB6IZBAAAAAAHohkEHCgkJERRUVEKCeFXAAAAQGMIxvkVW0sgIKqqqpSTk6N27dopMjLS7nIAAACCHvMrXC6aQQAAAABwoOC5homgVl5eroyMDJWXl9tdCiSdOnVKr776qk6dOmV3KQAA4BIxvzJLMM6vaAYREF6vVxs2bJDX67W7FEiqr69XSUmJ6uvr7S4FAABcIuZXZgnG+RXNIAAAAAA4EM0gAAAAADgQzSAAAAAAOBDNIALC7XarY8eOcrvddpcCSYmJiRo1apQSExPtLgUAAFwi5ldmCcb5FVtLAAAAAIADcWUQAdHQ0KCKigo1NDTYXQp05lbUn376KbeiBgAgiDG/Mkswzq9oBhEQhYWF+uMf/6jCwkK7S4HO3Ip6y5Yt3IoaAIAgxvzKLME4v6IZBAAAAAAHohkEAAAAAAeiGQQAAAAAB6IZBBwoMjJSXbt2VWRkpN2lAAAANAnBOL9iawkEhGVZqq2tVXh4uFwul93lAAAABD3mV7hcXBlEQLhcLkVERPCLyhB1dXXyeDyqq6uzuxQAAHCJmF+ZJRjnVzSDCAiPx6O3335bHo/H7lIgqaioSK+99pqKiorsLgUAAFwi5ldmCcb5Fc0gAqKmpkZHjx5VTU2N3aUAAAA0CcyvcLloBgEAAADAgWgGAQAAAMCBaAYBAAAAwIHYWgIBUVFRoaysLHXp0kXR0dF2lwMAABD0mF/hctEMAgAAAIADsUwUAVFVVaX9+/erqqrK7lIgqbi4WEuXLlVxcbHdpQAAgEvE/MoswTi/ohlEQJSWlmr16tUqLS21uxRIqq2tVW5urmpra+0uBQAAXCLmV2YJxvkVzSAAAAAAOBDNIAAAAAA4EM0gAAAAADgQzSACIjw8XKmpqQoPD7e7FEiKj4/XiBEjFB8fb3cpAADgEjG/Mkswzq/YWgIAAAAAHIgrg4ADVVRUaPfu3aqoqLC7FAAAgCYhGOdXNIMIiPz8fM2fP1/5+fl2lwJJp0+f1tq1a3X69Gm7SwEAAJeI+ZVZgnF+RTMIAAAAAA5EMwgAAAAADkQzCAAAAAAORDMIOFBERITat2+viIgIu0sBAABoEoJxfsXWEgiIuro6nT59Ws2aNVNYWJjd5QAAAAQ95le4XDSDgANZlqXa2lqFh4fL5XLZXQ4AAEDQC8b5FctEERClpaVavXq1SktL7S4FkgoKCrRw4UIVFBTYXQoAALhEzK/MEozzK8c0g5s2bdLIkSOVmpoql8uld955x298xYoVGjp0qJKTk+VyuZSZmXnOcwwcOFAul8vvz7333ut3zl133aWrrrpKkZGRat26tcaOHavc3Fy/c44dO6aRI0cqJiZGycnJmjp1qmpqavzO2bt3rwYMGKCoqCi1adNGzzzzjIL5Im5VVZX279+vqqoqu0sBAABoEphf4XI5phksLy9X9+7d9fLLL19wvH///po3b943Ps+kSZOUl5fn+/PKK6/4jQ8aNEh///vflZWVpeXLlys7O1ujRo3yjdfX12vEiBEqLy/X5s2btWzZMi1fvlwzZszwnVNWVqY77rhDqamp2rFjh1566SU9//zzWrBgwWV8BwAAAADg3xzzTtPhw4dr+PDhFxwfO3asJOno0aPf+DzR0dFq1arVBccfeeQR39/btWunX/ziF7r77rt964fXrFmj/fv36/jx40pNTZUk/f73v9eECRM0d+5cxcXFaenSpaqqqtLixYvldrvVrVs3ffnll1qwYIGmT58eNGuQAQAAAJjLMc1gY1m6dKnefPNNpaSkaPjw4Zo1a5aaNWt23nOLi4u1dOlS9evXT+Hh4ZKk9PR0devWzdcIStLQoUNVXV2tnTt3atCgQUpPT9eAAQPkdrv9zpk5c6aOHj2qDh06nPfzVVdXq7q62u+Y2+32ex47VVRU6NixY5Kk2NhYeb1eeTwe1dXVSTpzO974+Hg1a9ZMp0+fVkVFhcrLy32PT05O9n0t1dXVOnXqlG8sJiZG0dHRvseWlpb6lt6GhYUpMTHR9zmrqqp0+vRp32MTExMVGRmpsLAwVVVVqbCw0DcWHR2tmJgY3/OePn3atxQjJCREzZs3V0xMjCorK1VVVeW3Zj8+Pl6RkZGKjIxURUWFTp065VvqGxkZqWbNmvlqKi8vV0VFhe+xLVq0UFRUlGpra1VVVSWPx+Mbi4uLU2RkpGJiYuT1elVcXKz6+nq/7+GFnjc5OVmRkZEqKSlRUVGR72spLy+X1+v1y8vtdishIUENDQ1+35OzWrZsKZfLJY/Hc84y52bNmik6Ovqc74kkhYeHKykpSZKUn59/zvM2b95cYWFhKi0tPWfZS2xsrGJiYlRTU+P3PZGk0NBQJScnS5IKCwvV0NDgN56YmKiIiAjfz9Z/ioqKUlxcnGpra1VcXOw35nK51LJlS0lSUVGR7+f1rISEBLnd7m/8HtbX1/v9vJ71n9/DkpIStW7dWpGRkeRBHpLIgzzIgzz+7zzO/n/O/Mqc+dXXf0ZMRzP4X7jvvvvUoUMHtWrVSvv27dPMmTO1Z88effzxx37nPfHEE3r55ZdVUVGhW265Re+//75v7OTJk0pJSfE7/+wvmZMnT/rOad++vd85Zx9z8uTJCzaDzz33nObMmeN3bNasWZo9e/alfLmNqra2Vtu3b5fH41GbNm00aNAgbdiwQbt27VJZWZmkM7/Er7/+et1+++1av369Tpw4oYMHD/qe49Zbb1WnTp0kSYcOHdLmzZt9Y507d1abNm18j927d6+KiooknfnH3atXL9/nLCws1Oeff+57bJ8+fdS+fXslJydr//792rRpk+8/gvbt26t9+/a+583KylJeXp6kM/8B3Hzzzbr55pv12WefKS8vz++9pj179lSbNm10zTXXKCMjQ+np6b5mvU2bNurcubO+853vaN26dTp8+LDvF3lYWJhuvfVWXX/99crNzdWxY8e0Y8cO3/N269ZNKSkp6tevn/71r38pIyPD959IixYtdN111/nq/eqrr3To0CHfY7/97W+rc+fOKioqUmZmpg4fPqx27drpwIED2rBhg19mHTt21D333KOqqiotWbLknEynTZumiIgIrV279pwr6oMHD1bPnj11+PBhrV692m8sNTVV9913nySd93kfeOABJSYmavPmzdq/f7/fWL9+/dS/f3+dOHFC//jHP/zGEhISNGnSJEnS3/72N1VWVvqN33fffUpNTVVGRoYyMjL8xnr27KnBgweruLj4nJoiIiI0bdo0SdKqVat8P1dnff/731enTp20d+9e/etf//Ib69Kli+666y5VVFSc92udPn26QkNDtXz5cq1cuVKPP/64BgwYQB7kIYk8yIM8yOP/zmPt2rVatWqVSkpK1LFjR+ZXNs+vqqqqFBYWFlTbfDhyawmXy6WVK1fq7rvvPmfs7JW33bt3q0ePHt/4PDt37lTv3r21c+dO9erVy3f81KlTKi4uVk5OjubMmaP4+Hi9//77crlc+ulPf6qcnBx99NFHfs8VERGhJUuW6N5779WQIUPUoUMHv/cjnjhxQm3btlV6erpuueWW89Zj8pXB/Px8vfbaaxo6dKjS0tJ45crmV66++OIL/frXv9acOXPUu3dvXtm1+ZXdrVu3ksd/IA/ykMiDPMjjYvOYPXu2pk+fru7duzO/snl+derUKa1cuVLjxo075+KPqYKnbTVQr169FB4eroMHD/o1g8nJyUpOTta3vvUtXXvttUpLS9PWrVvVt29ftWrVStu2bfN7Ho/Ho9raWt8PTatWrXxXCc86e4vab/rBMqXxu5CIiAilpaX5voaYmJgLfj3R0dH/5/Nd6L2b0dHRF3zemJiYb3zO+Pj4b6zpQmOxsbGSpLS0tPOON2vW7JJrks680nWhx17K856tNzIy0nfuhc4PCQn5xp+7xMTEC46d/WV9Id/0vPHx8YqPjz/vWERExDc+tkWLFhcca9as2QWXdoeHh3/j8zZv3vyCY9/0PQwNDf3G5yUP8jgf8jiDPMjjfMjjjNjYWIWGhio1NZX51X9Zk9T486uvX5QJBo65m+iV8Pnnn6u2tlatW7e+4DlnX6k4+8PRt29f7du3z3cpXJLWrFkjt9utG2+80XfOpk2b/F4tW7NmjVJTU89ZPgoAAAAAl8IxzaDX61VmZqZvzfGRI0eUmZnpW0dcXFyszMxM3xrzrKwsZWZm+q7QZWdn65lnnlFGRoaOHj2qDz74QKNHj1bPnj3Vv39/SdL27dv18ssvKzMzUzk5OdqwYYPGjBmjjh07qm/fvpKkIUOGqGvXrho7dqx2796tdevW6dFHH9WkSZMUFxcnSRozZozcbrcmTJigffv2aeXKlXr22WeD+k6iYWFhatmyZVCtoW7KEhIS1LdvXyUkJNhdCkQepiEPs5CHWcjDLORhlri4OA0dOtQ3pw8GjnnP4MaNGzVo0KBzjo8fP16LFy/W4sWLNXHixHPGz96A5fjx47r//vu1b98+eb1epaWlacSIEZo1a5Zv/frevXs1bdo07dmzR+Xl5WrdurWGDRump556yu8y9LFjx/TQQw9p/fr1ioqK0pgxY/T888/7LfHcu3evpkyZou3btysxMVGTJ0/W008/HbTNIAAAAACzOKYZBPBvlZWVOnjwoDp37qyoqCi7y3E88jALeZiFPMxCHmYhD7MEYx6OWSYKexUUFGjBggW+G+HAXtnZ2XryySeVnZ1tdykQeZiGPMxCHmYhD7OQh1nKysr00Ucf+bb1CAY0gwgIy7JUX18vLkSb4+u3zoa9yMMs5GEW8jALeZiFPHA5aAYBAAAAwIFoBgEAAADAgWgGAQcKDw9XQkKCwsPD7S4FIg/TkIdZyMMs5GEW8jBLRESE0tLSFBERYXcpF427iSIg6urqVFJSooSEBPYaNAB5mIU8zEIeZiEPs5CHWcgDl4tmEHAgy7LU0NCgkJAQ9q40AHmYhTzMQh5mIQ+zkIdZgjEPlokiIMrKyvThhx8G1a12m7Ls7Gz97Gc/41bUhiAPs5CHWcjDLORhFvIwSzBupUYziICorKzU3r17VVlZaXcpkFRVVaW8vDxVVVXZXQpEHqYhD7OQh1nIwyzkgctFMwgAAAAADkQzCAAAAAAORDMIAAAAAA7E3UQREF6vV7t27VKvXr0UGxtrdzmOV1paqvT0dPXt21fx8fF2l+N45GEW8jALeZiFPMxCHmapr69XRUWFoqOjFRoaanc5F4VmEAAAAAAciGWiCIiamhodP35cNTU1dpcCnbn18aJFi4Lq1sdNGXmYhTzMQh5mIQ+zkIdZSkpK9O6776qkpMTuUi4azSACwuPxaNmyZfJ4PHaXAp35z2PFihX852EI8jALeZiFPMxCHmYhD7NUV1crKytL1dXVdpdy0WgGAQAAAMCBaAYBAAAAwIFoBgEAAADAgWgGERAhISGKjY1VSAg/ciaIjY3VddddxzYfhiAPs5CHWcjDLORhFvIwS2xsrG677bagyoOtJQAAAADAgbhMAzhQdXW1Dh06FFR3u2rKyMMs5GEW8jALeZiFPMwSjHnQDCIgCgsL9ec//1mFhYV2lwJJhw4d0uOPP65Dhw7ZXQpEHqYhD7OQh1nIwyzkYZaSkhKtXLmSfQaBr2toaJDX61VDQ4PdpUCSZVmqrq4Wq8TNQB5mIQ+zkIdZyMMs5IHLRTMIAAAAAA5EMwgAAAAADkQzCDhQaGioYmJiFBoaancpEHmYhjzMQh5mIQ+zkIdZwsLC1Lx5c4WFhdldykVjawkERE1NjfLz85WSkqKIiAi7y3E88jALeZiFPMxCHmYhD7OQBy4XzSAAAAAAOBDLRBEQXq9XmzZtktfrtbsUSDpy5IimTp2qI0eO2F0KRB6mIQ+zkIdZyMMs5GGWgoICLVy4UAUFBXaXctFoBhEQ5eXl2rZtm8rLy+0uBTqTR3Z2NnkYgjzMQh5mIQ+zkIdZyMMslmWppqYmqLb6oBkEAAAAAAeiGQQAAAAAB6IZBAAAAAAHohlEQERFRen6669XVFSU3aVAUuvWrXX//ferdevWdpcCkYdpyMMs5GEW8jALeZglKSlJ48aNU1JSkt2lXDS2lgAAAAAAB+LKIAKirq5Op06dUl1dnd2lQFJxcbGWL1+u4uJiu0uByMM05GEW8jALeZiFPMxSVlamtWvXqqyszO5SLhrNIAKiqKhIr7/+uoqKiuwuBZJyc3P117/+Vbm5uXaXApGHacjDLORhFvIwC3mYpbKyUrt371ZlZaXdpVw0mkEAAAAAcCCaQQAAAABwIJpBAAAAAHAgmkEEhMvlUmhoqFwul92lQFJ0dLTatWun6Ohou0uByMM05GEW8jALeZiFPMwSHR2t3r17B1UebC0BAAAAAA7ElUHAgWpqapSbm6uamhq7S4HIwzTkYRbyMAt5mIU8zBKMedAMIiCKior0xhtvsLWEIbKzs/XII48oOzvb7lIg8jANeZiFPMxCHmYhD7N4PB4tXbpUHo/H7lIuGs0gAqKurk4FBQVsOm+I+vp6eb1e1dfX210KRB6mIQ+zkIdZyMMs5IHLRTMIAAAAAA5EMwgAAAAADkQzCDiQy+VSeHg4W30YgjzMQh5mIQ+zkIdZyMMsISEhioqKUkhI8LRYbC2BgKiqqlJOTo7atWunyMhIu8txPPIwC3mYhTzMQh5mIQ+zkAcuF80gAAAAADhQ8FzDRFArLy9XRkaGysvL7S4FknJycvTkk08qJyfH7lIg8jANeZiFPMxCHmYhD7OcOnVKr776qk6dOmV3KReNZhAB4fV6tWHDBnm9XrtLgaTTp08rMzNTp0+ftrsUiDxMQx5mIQ+zkIdZyMMs9fX1KikpCaqtPmgGAQAAAMCBaAYBAAAAwIFoBgEAAADAgWgGERBut1sdO3aU2+22uxRIatmypb773e+qZcuWdpcCkYdpyMMs5GEW8jALeZglMTFRo0aNUmJiot2lXDS2lgAAAAAAB+LKIAKioaFBFRUVamhosLsU6Mzdx9atW8fdxwxBHmYhD7OQh1nIwyzkYZby8nJ9+umnQbWVGs0gAqKwsFB//OMfVVhYaHcp0Jl9iRYsWMC+RIYgD7OQh1nIwyzkYRbyMIvX69WWLVuCais1mkEAAAAAcCCaQQAAAABwIJpBAAAAAHAgmkHAgdxut1JSUtjqwxDkYRbyMAt5mIU8zEIeZomMjFTXrl0VGRlpdykXja0lEBCWZam2tlbh4eFyuVx2l+N45GEW8jALeZiFPMxCHmYhD1wurgwiIFwulyIiIvhFZYj6+nqVl5ervr7e7lIg8jANeZiFPMxCHmYhD7PU1dXJ4/Gorq7O7lIuGs0gAsLj8ejtt9+Wx+OxuxRIys7O1tSpU5WdnW13KRB5mIY8zEIeZiEPs5CHWYqKivTaa6+pqKjI7lIuGs0gAqKmpkZHjx5VTU2N3aVAUm1trYqLi1VbW2t3KRB5mIY8zEIeZiEPs5AHLhfNIAAAAAA4EM0gAAAAADgQzSAAAAAAOBBbSyAgKioqlJWVpS5duig6OtruchyPPMxCHmYhD7OQh1nIwyzkgctFMwgAAAAADsQyUQREVVWV9u/fr6qqKrtLgaTc3Fz97ne/U25urt2lQORhGvIwC3mYhTzMQh5mKS4u1tKlS1VcXGx3KReNZhABUVpaqtWrV6u0tNTuUqAzv6w++eSToPpl1ZSRh1nIwyzkYRbyMAt5mKW2tla5ublBtdUHzSAAAAAAOBDNIAAAAAA4EM0gAAAAADgQzSACIjw8XKmpqQoPD7e7FEhKSkrSgAEDlJSUZHcpEHmYhjzMQh5mIQ+zkIdZ4uPjNWLECMXHx9tdykVjawkAAAAAcCCuDAIOVFFRod27d6uiosLuUiDyMA15mIU8zEIeZiEPswRjHjSDCIj8/HzNnz9f+fn5dpcCSYcPH9ZTTz2lw4cP210KRB6mIQ+zkIdZyMMs5GGW06dPa+3atTp9+rTdpVw0mkEAAAAAcCCaQQAAAABwIJpBAAAAAHAgmkHAgcLDw5WUlMRWH4YgD7OQh1nIwyzkYRbyMEtERITat2+viIgIu0u5aGwtgYCoq6vT6dOn1axZM4WFhdldjuORh1nIwyzkYRbyMAt5mIU8cLloBgEHsixLtbW1Cg8Pl8vlsrscxyMPs5CHWcjDLORhFvIwSzDmwTJRBERpaalWr16t0tJSu0uBpEOHDmny5Mk6dOiQ3aVA5GEa8jALeZiFPMxCHmYpKCjQwoULVVBQYHcpF80xzeCmTZs0cuRIpaamyuVy6Z133vEbX7FihYYOHark5GS5XC5lZmae8xwDBw6Uy+Xy+3Pvvff6xo8ePaqf/OQn6tChg6KiotSxY0fNmjVLNTU1fs9z7NgxjRw5UjExMUpOTtbUqVPPOWfv3r0aMGCAoqKi1KZNGz3zzDMK5ou4VVVV2r9/v6qqquwuBZKqq6uVn5+v6upqu0uByMM05GEW8jALeZiFPHC5HLO4uLy8XN27d9fEiRP1gx/84Lzj/fv31+jRozVp0qQLPs+kSZP0zDPP+D6Oiory/f2LL75QQ0ODXnnlFXXq1En79u3TpEmTVF5erueff16SVF9frxEjRqhFixbavHmzioqKNH78eFmWpZdeekmSVFZWpjvuuEODBg3Sjh079OWXX2rChAmKiYnRjBkzGutbAgAAAMDBHNMMDh8+XMOHD7/g+NixYyWdubr3TaKjo9WqVavzjg0bNkzDhg3zfXz11VcrKytLf/7zn33N4Jo1a7R//34dP35cqampkqTf//73mjBhgubOnau4uDgtXbpUVVVVWrx4sdxut7p166Yvv/xSCxYs0PTp04NmDTIAAAAAczmmGWwsS5cu1ZtvvqmUlBQNHz5cs2bNUrNmzS54fmlpqZKSknwfp6enq1u3br5GUJKGDh2q6upq7dy5U4MGDVJ6eroGDBggt9vtd87MmTN19OhRdejQ4byfq7q6+pxlAm632+957Jafny9JSklJkSQVFxertrbW75z4+HhFRkaqoqJCp0+f9huLiIhQYmKiLMs673rsFi1aKCQkRCUlJed8L2JjYxUTE6Oqqqpz3rsYFham5s2bSzqz3vvrS3KbN2+usLAwlZWVqbKy0m8sJiZGsbGxqqmpkcfj8RsLCQlRixYtJEmFhYVqaGjwG09MTFRERIS8Xq/Ky8v9xqKiohQXF6e6ujoVFRX5jblcLrVs2VKSVFRUpLq6Or/xs9/D8vJyeb1ev7H//HkoLCxUfn4+efwv8iAP8iAP8iAP8iAP6fLyCCY0g/+F++67Tx06dFCrVq20b98+zZw5U3v27NHHH3983vOzs7P10ksv6fe//73v2MmTJ33/UM86+wN78uRJ3znt27f3O+fsY06ePHnBZvC5557TnDlz/I7NmjVLs2fP/m++zCsiNjZWkvTRRx9Jkh577DFJ0j//+U/l5ub6nTtixAh17dpVWVlZWrt2rd9Y+/btNXr0aNXW1mrJkiXnfJ4pU6YoOjpa69evV3Z2tt/YoEGD1Lt3b+Xk5Ojdd9/1G2vZsqXGjx8vSXrzzTdVX1/vNz5x4kQlJydry5Yt2rt3r9/YzTffrG9/+9vKz8/XsmXLzvm6H3zwQUnSP/7xj3N+cdx7771KS0vTrl27tG3bNr+x66+/XsOGDVNJSck5X2toaKimT58uSXr//ffP+cV91113qUuXLjpw4IA2bNjgN9axY0fdcccd6tevn3bs2KGMjAzy+F/kQR7kQR7kQR7kQR7SpeVx9913a8qUKYqMjFSwcOTWEi6XSytXrtTdd999ztjZK2+7d+9Wjx49vvF5du7cqd69e2vnzp3q1auX31hubq4GDBigAQMG6LXXXvMd/+lPf6qcnBxfU3RWRESElixZonvvvVdDhgxRhw4d9Morr/jGT5w4obZt2yo9PV233HLLeesx/crgf76KwitXZ9j1ylVCQgJ5kIffGHmcQR7kQR7kQR7kIV16HsGGZvBr/ptm0LIsud1u/c///I9+9KMf+Y7n5uZq0KBBuvnmm7V48WKFhPz7pq1PP/20Vq1apT179viOeTweJSUlaf369Ro0aJDGjRun0tJSrVq1ynfO7t271atXLx0+fPiCVwYBAAAA4GI5ZmuJK+Hzzz9XbW2tWrdu7Tt24sQJDRw4UL169dLrr7/u1whKUt++fbVv3z7l5eX5jq1Zs0Zut1s33nij75xNmzb5bTexZs0apaamnrN8FAAAAAAuhWOaQa/Xq8zMTN/+gUeOHFFmZqaOHTsm6czl9MzMTO3fv1+SlJWVpczMTN/7+LKzs/XMM88oIyNDR48e1QcffKDRo0erZ8+e6t+/v6QzVwQHDhyotLQ0Pf/88yosLNTJkyd9zyFJQ4YMUdeuXTV27Fjt3r1b69at06OPPqpJkyYpLi5OkjRmzBi53W5NmDBB+/bt08qVK/Xss89yJ1EAAAAAjcYxy0Q3btyoQYMGnXN8/PjxWrx4sRYvXqyJEyeeM372BizHjx/X/fffr3379snr9SotLU0jRozQrFmzfHcLvdBzSPJbI33s2DE99NBDWr9+vaKiojRmzBg9//zzfu/t27t3r6ZMmaLt27crMTFRkydP1tNPP00zCAAAAKBROKYZBAAAAAD8m2OWiQIAAAAA/o1mEAAAAAAciGYQAAAAAByIZhAAAAAAHIhmEAAAAAAciGYQAAAAAByIZhAAAAAAHIhmEAAAAAAciGYQAAAAAByIZhAAAAAAHIhmEAAAAAAciGYQAAAAAByIZhAAAAAAHIhmEAAAAAAciGYQAAAAAByIZhAAAAAAHIhmEAAAAAAciGYQAAAAAByIZhAAAAAAHIhmEAAAAAAciGYQAAAAAByIZhAAAAAAHIhmEAAAAAAciGYQAAAAAByIZhAAAAAAHIhmEAAAAAAciGYQAAAAAByIZhAAAAAAHIhmEAFRXV2t2bNnq7q62u5SIPIwDXmYhTzMQh5mIQ+zkIdZgjEPl2VZlt1FoOkrKytTfHy8SktLFRcXZ3c5jkceZiEPs5CHWcjDLORhFvIwSzDmwZVBAAAAAHAgmkEAAAAAcCCaQQAAAABwIJpBBITb7dasWbPkdrvtLgUiD9OQh1nIwyzkYRbyMAt5mCUY8+AGMgAAAADgQFwZBAAAAAAHohkEAAAAAAeiGQQAAAAAB6IZBAAAAAAHohkEAAAAAAcKs7sANF05OTk6efKkXC6XUlJS1K5dO7tLcjTyMAt5mIU8zEIeZiEPs5CHWYI+DwtoZAsWLLDatm1rhYSEWC6Xy3K5XFZISIjVtm1b6w9/+IPd5TkOeZiFPMxCHmYhD7OQh1nIwyxNJQ+aQTSqZ555xoqLi7PmzZtn7d6928rNzbVOnDhh7d6925o3b54VHx9v/frXv7a7TMcgD7OQh1nIwyzkYRbyMAt5mKUp5UEziEbVtm1ba+XKlRccX7FihZWamhq4ghyOPMxCHmYhD7OQh1nIwyzkYZamlAc3kEGjKioqUpcuXS44/q1vfUsejyeAFTkbeZiFPMxCHmYhD7OQh1nIwyxNKQ+aQTSqPn36aO7cuaqrqztnrK6uTs8++6z69OljQ2XORB5mIQ+zkIdZyMMs5GEW8jBLU8rDZVmWZXcRaDr27t2rIUOGqLq6WgMGDFBKSopcLpdOnjypTZs2ye126+OPP9Z1111nd6mOQB5mIQ+zkIdZyMMs5GEW8jBLU8qDZhCN7vTp03rzzTe1detWnTx5UpLUqlUr9e3bV2PGjFFcXJzNFToLeZiFPMxCHmYhD7OQh1nIwyxNJQ+aQQAAAABwIDadxxXh9Xq1c+dO3yacrVq1Uq9evRQbG2t3aY5EHmYhD7OQh1nIwyzkYRbyMEuTyMPOW5mi6amtrbWmTp1qRUVFWS6Xy3K73VZERITlcrmsqKgoa9q0aVZNTY3dZToGeZiFPMxCHmYhD7OQh1nIwyxNKQ+aQTSqqVOnWm3atLGWLVtmeTwe33GPx2MtW7bMSktLs6ZNm2ZbfU5DHmYhD7OQh1nIwyzkYRbyMEtTyoNmEI0qOTnZWrdu3QXH165dayUnJwewImcjD7OQh1nIwyzkYRbyMAt5mKUp5cE+g2hUlZWVSk5OvuB48+bNVVlZGcCKnI08zEIeZiEPs5CHWcjDLORhlqaUB3cTRaMaOXKkKisrtXTpUqWkpPiN5efna+zYsYqMjNS7775rU4XOQh5mIQ+zkIdZyMMs5GEW8jBLU8qDZhCN6vjx47rzzjv1xRdfqFu3bn6bcO7bt09du3bV6tWr1bZtW7tLdQTyMAt5mIU8zEIeZiEPs5CHWZpSHjSDaHQNDQ366KOPzrsJ55AhQxQSwurkQCIPs5CHWcjDLORhFvIwC3mYpankQTMIAAAAAA7EpvO4Ig4fPqzNmzcrLy9PoaGhuvrqqzV48GDFxcXZXZojHTx4UFu2bPFtipqSkqJ+/fqpc+fOdpeG/1BeXq6dO3fq29/+tt2lALapr69XaGio7+Nt27apurpaffv2VXh4uI2VQZImTpyouXPnKjU11e5SHM/j8ejQoUNq3bp1UCxHbMpKSkr09ttv69ixY2rXrp1Gjx6t+Ph4u8u6KFwZRKMqLy/XhAkTtHz5ckmSy+VSy5YtVVhYqKioKM2bN09TpkyxuUrnKC0t1bhx4/Tee+8pPj5eLVu2lGVZKiwsVFlZmUaOHKklS5bQpBtiz5496tWrl+rr6+0uxRFqa2v15JNPasWKFUpKStKDDz6oiRMn+sbz8/OVmppKHgGSl5en0aNHa+vWrerfv7/eeecdjR07Vh988IEkqXPnztq4caNat25tc6XO8Nlnn533eO/evfX3v/9dV199tSTphhtuCGRZjvXLX/5STz31lKKjo1VbW6spU6Zo0aJFsixLLpdL3/ve9/TWW28pMjLS7lIdYdSoURozZozuuece7d+/XwMGDJDL5dLVV1+to0ePyuVyaf369br22mvtLvX/FByLWRE0pk+frry8PO3evVsHDhzQ97//fY0bN05lZWVauHChHn/8cb311lt2l+kYDz/8sI4cOaL09HR5PB5lZWXpyy+/lMfj0ZYtW3TkyBE9/PDDdpcJ2GLu3LlasmSJJk+erCFDhuiRRx7Rz372M79zeL00cJ544glZlqWVK1eqdevW+u53v6uysjIdP35cOTk5SklJ0dy5c+0u0zF69Oihnj17qkePHn5/6urq9IMf/MA3jsD47W9/K6/XK0maP3++3nnnHb399tv66quvtGrVKm3fvl3z58+3uUrn+OSTT3T99ddLkh599FENGTJEX331lbZu3arjx49rxIgR+vnPf25vkRfLjs0N0XQlJydbGRkZvo+Li4utyMhIq7y83LIsy3r55ZetHj162FWe48THx1tbt2694Hh6eroVHx8fuIIcLjEx8Rv/xMXFWSEhIXaX6RidOnWy3nvvPd/Hhw4dsjp37mxNmDDBamhosE6ePEkeAdS6dWsrPT3dsizLKioqslwul7V27Vrf+Pr1662rr77arvIcp3v37taIESOsAwcOWEePHrWOHj1qHTlyxAoLC7M+/vhj3zEEhsvlsvLz8y3LsqwePXpYixYt8hv/29/+Zl177bV2lOZIUVFR1qFDhyzLOvO7a9euXX7jWVlZQTO/4j2DaFR1dXV+Sw5jY2NVV1en8vJyRUdHa8iQIXr00UdtrNB5XC7XJY2h8VVXV+vBBx/0vZr4dTk5OZozZ06Aq3KuEydOqFu3br6PO3bsqI0bN+r222/X2LFj9bvf/c7G6pzH4/GoTZs2kqSkpCRFR0erXbt2vvGOHTsqLy/PrvIcZ/v27Xr88cf1gx/8QG+++abfVcDU1FS/bBAYZ//PPn78uPr06eM31qdPH+Xk5NhRliPdcMMNWr9+vTp27KhWrVopJyfH799ITk6OoqKibKzw4tEMolHddNNNWrhwoV5++WVJ0sKFC9WiRQu1aNFCkuT1ehUbG2tniY4ycuRITZo0SYsWLVLv3r39xjIyMjR58mTdddddNlXnPD169FBaWprGjx9/3vE9e/bQDAZQq1atlJ2drfbt2/uOpaamav369Ro0aNAFc8KV0bJlS+Xl5SktLU2S9P/+3/9TUlKSb9zj8SgmJsau8hwnIiJCL7zwgv75z3/qrrvu0kMPPaQnnnjC7rIc7dVXX1VsbKzcbrc8Ho/fWGlpqdxut02VOc+vfvUrjRs3TuHh4Zo6daoeeeQRFRUV6dprr1VWVpZmzZqlsWPH2l3mRaEZRKOaN2+e7rjjDi1fvlwRERE6efKk3njjDd/4li1bdOedd9pYobO89NJL+vGPf6w+ffooISFBLVu2lMvlUn5+vkpLSzV06FC9+OKLdpfpGCNGjFBJSckFx5OSkjRu3LjAFeRwt99+u9566y195zvf8Tt+tiEcOHCgPYU5VI8ePZSenu674jFv3jy/8c2bN3OzEhsMHz5cGRkZmjhxou9mPgi8q666Sq+++qqkM436rl27dNttt/nGN2zYoC5duthVnuOMGDFCf/nLX/Tzn/9cubm5sixLkyZNkiS53W5NnjxZzz33nM1VXhzuJopGl5eXp/fff1/V1dW6/fbb1bVrV7tLcrwvvvhC6enp52yKes0119hcGWCfnJwcffHFFxo6dOh5x/Py8rRmzRquEBpix44dioqK8lvai8B68cUXtWHDBr300ktsZWCYrVu3yu12c1OfAKuvr9euXbt0+PBhNTQ0qHXr1rrxxhvVrFkzu0u7aDSDAAAAAOBAbC2BRlVdXa3a2lrfx9nZ2XryySc1duxYPfXUUzpy5IiN1TnP8uXLVVFRYXcZ+F/kYRbyMAt5mIU8zEIeZmlKedAMolENHz5c7733niTp008/1XXXXaf3339ftbW1+uCDD9StWzelp6fbXKVzjB49Wq1atdJPf/pTbdu2ze5yHI88zEIeZiEPs5CHWcjDLE0pD5pBNKrdu3ere/fukqQnn3xSDz30kPbs2aNly5Zp165dmj59uh577DGbq3SWxx57TBkZGerbt6+6deumF154QUVFRXaX5VjkYRbyMAt5mIU8zEIeZmkyedi6yyGanJiYGOvAgQOWZVlWSkqKlZmZ6Td+6NAhKzY21o7SHOk/N6nNyMiwHnzwQSshIcFyu93W6NGjrTVr1thcobOQh1nIwyzkYRbyMAt5mKUp5cGVQTSqm2++2bdMtGPHjtqzZ4/feGZmpt++UQicG2+8UX/605+Ul5enV199VYWFhRo2bJjfHmsIHPIwC3mYhTzMQh5mIQ+zBHse7DOIRvWb3/xGw4cPV3l5uX784x9rxowZOnjwoG8TzhdffFEzZ860u0zHcLlc5xyLjIzU2LFjNXbsWB06dEivv/66DZU5E3mYhTzMQh5mIQ+zkIdZmlIebC2BRpeenq7p06ef84ba1NRUPfbYY5o2bZpNlTlPSEiITp48qZYtW9pdCkQepiEPs5CHWcjDLORhlqaUB80grpjCwkK/TTiD5XJ5U5KTk6OrrrrqvK9gIfDIwyzkYRbyMAt5mIU8zNKU8qAZBAAAAAAH4j2DaHRFRUX67LPP1L17dyUlJenUqVNatGiRqqurNXr0aF177bV2l+go5GEW8jALeZiFPMxCHmYhD7M0mTzsvJUpmp5t27ZZ8fHxlsvlshITE62MjAyrQ4cOVufOna1OnTpZUVFR1s6dO+0u0zHIwyzkYRbyMAt5mIU8zEIeZmlKedAMolENHjzYeuCBB6yysjJr/vz5Vtu2ba0HHnjAN/6Tn/zEuvvuu22s0FnIwyzkYRbyMAt5mIU8zEIeZmlKedAMolElJiZa+/fvtyzLsmpqaqyQkBBr27ZtvvFdu3ZZbdq0sas8xyEPs5CHWcjDLORhFvIwC3mYpSnlwabzaFQ1NTWKioqSJIWHhys6OlrJycm+8ebNm6uoqMiu8hyHPMxCHmYhD7OQh1nIwyzkYZamlAfNIBpVWlqaDh8+7Pt42bJlat26te/jvLw8v38suLLIwyzkYRbyMAt5mIU8zEIeZmlKeXA3UTSqe++9VwUFBb6PR4wY4Tf+7rvvqk+fPoEuy7HIwyzkYRbyMAt5mIU8zEIeZmlKebDPIALCsiy5XC5VVFQoNDRUbrfb7pIcjTzMQh5mIQ+zkIdZyMMs5GGWYMyDZaIICLfbrQMHDig6Ojoo/mE0deRhFvIwC3mYhTzMQh5mIQ+zBGMeLBNFo5o+ffp5j9fX12vevHlq3ry5JGnBggWBLMuxyMMs5GEW8jALeZiFPMxCHmZpSnnQDKJRvfDCC+revbsSEhL8jluWpQMHDigmJkYul8ue4hyIPMxCHmYhD7OQh1nIwyzkYZYmlUeg97JA0/bss89aHTp0sNatW+d3PCwszPr8889tqsq5yMMs5GEW8jALeZiFPMxCHmZpSnnQDKLRbd++3frWt75lzZgxw6qpqbEsKzj/cTQV5GEW8jALeZiFPMxCHmYhD7M0lTy4gQwa3U033aSdO3eqsLBQvXv31t69e4PnUnkTRB5mIQ+zkIdZyMMs5GEW8jBLU8mD9wziioiNjdUbb7yhZcuW6Y477lB9fb3dJTkaeZiFPMxCHmYhD7OQh1nIwyxNIQ/2GcQV99VXX2nnzp0aPHiwYmJi7C7H8cjDLORhFvIwC3mYhTzMQh5mCdY8aAYBAAAAwIF4zyAAAAAAOBDNIAAAAAA4EM0gAAAAADgQzSAAAAAAOBDNIAAAAAA4EM0gAAAAADgQzSAAAAAAOBDNIAAAAAA4EM0gAAAAADgQzSAAAAAAOBDNIAAAAAA4EM0gAAAAADgQzSAAAAAAOBDNIAAAAAA4EM0gAAAAADgQzSAAAAAAOBDNIAAAAAA4EM0gAAAAADgQzSAAAAAAOBDNIAAAAAA4EM0gAAAAADgQzSAAAAAAOBDNIAAAAAA4EM0gAAAAADgQzSAAAAAAOBDNIAAAAAA4EM0gAAAOtHHjRrlcLs2ePdvuUgAANqEZBACgkR09elQul+sb//To0eOK1+FyuTRw4MAr/nkAAMEpzO4CAABoqjp27Kj777//vGOtWrUKcDX++vTpowMHDig5OdnWOgAA9qEZBADgCunUqZOxyzCjo6N1zTXX2F0GAMBGLBMFAMBmK1eu1I9//GN16tRJ0dHRio+P12233ably5ef9/wNGzZo+PDhSk1NldvtVmpqqgYOHKjXXntN0r/fDyhJn3zyid/y1MWLF/ud8/VmtX379mrfvr3Ky8s1ffp0tWnTRm63WzfccIP+8Y9/nLeeo0eP6kc/+pGSkpIUGxurAQMGaNOmTZo9e7ZcLpc2btzYKN8nAEDj4sogAAA2mzlzpiIiInTrrbeqdevWKiws1LvvvqtRo0bpxRdf1MMPP+w7d/Xq1Ro5cqQSEhL0ve99z3d+Zmamli5dqgceeEDt27fXrFmzNGfOHLVr104TJkzwPf5i3qtYW1urIUOGqLi4WPfcc48qKiq0bNky/fCHP9SHH36oIUOG+M49ceKE+vXrp7y8PN15553q3r27srKyNGTIEA0aNKgxv00AgEZGMwgAwBVy6NChCy4TveWWWzRs2DBJ0gcffKCrr77ab9zr9apfv3761a9+pZ/85CeKjo6WJP31r3+VZVnauHGjbrjhBr/HFBUVSTpzdW/27NmaM2eO7+//jdzcXN10003asGGDIiIiJEljxozR4MGDtWDBAr9m8Be/+IXy8vI0f/58Pfroo77jixcv1sSJE/+rzwsACCyaQQAArpDs7GzNmTPnvGPTpk3zNYNfbwQlKTY2VhMmTNCMGTO0Y8cODRgwwG88KirqnMc0b968Eao+4w9/+IOvEZSk73znO2rXrp127NjhO1ZdXa23335bKSkpmjp1qt/jx48fr9/+9rf64osvGq0mAEDj4j2DAABcIUOHDpVlWef988ILL/jOKygo0PTp03XttdcqOjra9/6+GTNmSDpzpe6sH/7wh5Kkm2++WVOmTNHy5ctVUFDQqHUnJCSoQ4cO5xxv27atSkpKfB9nZWWpurpavXv39mscpTPbWvTt27dR6wIANC6uDAIAYKPi4mLddNNNOnbsmPr376/BgwcrISFBoaGhyszM1KpVq1RdXe07/0c/+pHCw8P1wgsv6JVXXtGf/vQn336CCxYsaJT9C+Pj4897PCwsTA0NDb6Py8rKJEktWrQ47/kpKSmXXQsA4MqhGQQAwEaLFi3SsWPH9Jvf/EZPPvmk39i8efO0atWqcx5zzz336J577lFZWZm2bNmiFStWaNGiRRo6dKiysrKUkJAQkNrj4uIkSYWFhecdz8/PD0gdAIBLwzJRAABslJ2dLUm66667zhn717/+9Y2PjYuL07Bhw/SXv/xFEyZMUEFBgbZt2+YbDwkJUX19feMW/B+6dOkit9utnTt3qqamxm/Msixt3br1in1uAMDloxkEAMBG7dq1kyRt3rzZ7/hbb72lDz744Jzz161bp6qqqnOOn33f4H/eWCYpKUlfffVVY5brx+12a9SoUTp58qRefPFFv7ElS5bowIEDV+xzAwAuH8tEAQC4Qr5pawlJmj17tsaOHavf/va3evjhh7Vhwwa1a9dOn332mdauXat77rlHK1as8HvMjBkzdOzYMQ0cOFDt27eXy+XS5s2btX37dvXr10/9+/f3nXv77bfr73//u0aNGqWePXsqNDRUI0aM0PXXX99oX+Nzzz2ntWvX6rHHHtOGDRvUo0cPZWVl6f3339ewYcP04YcfKiSE154BwEQ0gwAAXCHftLWEdKYZbNu2rT755BM9/vjjWrt2rerq6tSrVy+tWbNGx48fP6cZnDlzplasWKGdO3fqo48+Unh4uDp06KDf/e53euihhxQaGuo7d+HChZKk9evXa+XKlWpoaFCrVq0atRlMS0tTenq6nnjiCa1Zs0YbN27UjTfeqDVr1ujtt9+W9O/3FgIAzOKyLMuyuwgAAND03HrrrUpPT1dpaaliY2PtLgcA8DWs2wAAAJclLy/vnGNLly7Vp59+qsGDB9MIAoChuDIIAAAuS/PmzdWzZ0917drVtz/ixo0b1axZM3366aeNuiwVANB4aAYBAMBlefLJJ/Xee+/p2LFjKi8vV4sWLTRo0CD96le/0jXXXGN3eQCAC6AZBAAAAAAH4j2DAAAAAOBANIMAAAAA4EA0gwAAAADgQDSDAAAAAOBANIMAAAAA4EA0gwAAAADgQDSDAAAAAOBANIMAAAAA4EA0gwAAAADgQP8fu47KmQbahrQAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 1000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create matplotlib figure and axis\n",
    "f, ax = plt.subplots(figsize=(10, 10))\n",
    "\n",
    "# Return a k-ring of the BNGReference object at a grid distance of k=3\n",
    "bng_ref_kring = bng_ref.bng_kring(k=3)\n",
    "\n",
    "# Plot the original BNGReference grid square\n",
    "gpd.GeoSeries([bng_ref.bng_to_grid_geom()], crs=27700).plot(\n",
    "    ax=ax, color=\"#009ade\", linewidth=2\n",
    ")\n",
    "# Plot the BNGReference grid squares in the k-ring\n",
    "gpd.GeoSeries(\n",
    "    [bng_ref.bng_to_grid_geom() for bng_ref in bng_ref_kring], crs=27700\n",
    ").plot(ax=ax, color=\"none\", edgecolor=\"#00000075\", linewidth=1, linestyle=\"--\")\n",
    "\n",
    "# Set the title\n",
    "ax.set_title(\"K-Ring Around a BNG Grid Square Where k=3\", fontsize=16)\n",
    "# Set the aesthetics for the matplotlib axes\n",
    "plot_aesthetics(ax)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "596b5b08",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Convert BNG reference strings into BNGReference objects\n",
    "bng_ref1 = BNGReference(bng_ref_string=\"SU 372 155\")\n",
    "bng_ref2 = BNGReference(bng_ref_string=\"SU 371 155\")\n",
    "\n",
    "# Check if the two BNGReference objects are neighbours\n",
    "bng_ref1.bng_is_neighbour(bng_ref2=bng_ref2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "995f17af",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "181245.68960391858"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Convert BNG reference strings into BNGReference objects\n",
    "bng_ref1 = BNGReference(bng_ref_string=\"SX\")\n",
    "bng_ref2 = BNGReference(bng_ref_string=\"SU 1 2\")\n",
    "\n",
    "# Return the distance between two BNGReference objects in metres\n",
    "# The default distance is calculated as the Euclidean distance between\n",
    "# the centroids of the grid squares\n",
    "bng_ref1.bng_distance(bng_ref2=bng_ref2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "afd78c1d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "111803.39887498948"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Return the distance between two BNGReference objects in metres\n",
    "# edge_to_edge=True calculates the distance between the edges of the grid squares\n",
    "bng_ref1.bng_distance(bng_ref2=bng_ref2, edge_to_edge=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "8dc60fc7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[BNGReference(bng_ref_formatted=ST 2 9, resolution_label=10km),\n",
       " BNGReference(bng_ref_formatted=ST 3 9, resolution_label=10km),\n",
       " BNGReference(bng_ref_formatted=ST 4 9, resolution_label=10km),\n",
       " BNGReference(bng_ref_formatted=ST 2 8, resolution_label=10km),\n",
       " BNGReference(bng_ref_formatted=ST 3 8, resolution_label=10km),\n",
       " BNGReference(bng_ref_formatted=ST 4 8, resolution_label=10km),\n",
       " BNGReference(bng_ref_formatted=ST 2 7, resolution_label=10km),\n",
       " BNGReference(bng_ref_formatted=ST 3 7, resolution_label=10km),\n",
       " BNGReference(bng_ref_formatted=ST 4 7, resolution_label=10km)]"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Convert BNG reference stringsinto a BNGReference object\n",
    "bng_ref = BNGReference(bng_ref_string=\"ST 3 8\")\n",
    "\n",
    "# Return all BNGReference objects within a given distance d\n",
    "# of the input BNGReference object\n",
    "bng_ref.bng_dwithin(d=1000)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fafde96e",
   "metadata": {},
   "source": [
    "## Grids\n",
    "\n",
    "* The `osbng.grids` module provides functionality to generate BNG grid square data within specified bounds. This notebook provides examples of creating data at a range of resolutions and accross custom bounds.\n",
    "* Grid square data covering the BNG index system bounds is provided with the osbng package as iterators at 100km, 50km, 10km, 5km and 1km resolutions.\n",
    "* See `bng_grid_<resolution>` in `osbng.grids` module.\n",
    "* For BNG grid dataset covering the index system bounds at a range of resolutions in GeoPackage (GPKG) and GeoParquet formats see the [`osbng-grids`](https://github.com/OrdnanceSurvey/osbng-grids/) GitHub repo.\n",
    "* The `bbox_to_bng_iterfeatures` function returns an iterator of `BNGReference` objects represented using a GeoJSON-like mapping within specified bounds at a specified resolution. This function can be used to generate BNG grid data at different resolutions over custom bounds."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "ddd29374",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>geometry</th>\n",
       "      <th>bng_ref</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>POLYGON ((100000 0, 100000 100000, 0 100000, 0...</td>\n",
       "      <td>SV</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>POLYGON ((200000 0, 200000 100000, 100000 1000...</td>\n",
       "      <td>SW</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>POLYGON ((300000 0, 300000 100000, 200000 1000...</td>\n",
       "      <td>SX</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>POLYGON ((400000 0, 400000 100000, 300000 1000...</td>\n",
       "      <td>SY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>POLYGON ((500000 0, 500000 100000, 400000 1000...</td>\n",
       "      <td>SZ</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                            geometry bng_ref\n",
       "0  POLYGON ((100000 0, 100000 100000, 0 100000, 0...      SV\n",
       "1  POLYGON ((200000 0, 200000 100000, 100000 1000...      SW\n",
       "2  POLYGON ((300000 0, 300000 100000, 200000 1000...      SX\n",
       "3  POLYGON ((400000 0, 400000 100000, 300000 1000...      SY\n",
       "4  POLYGON ((500000 0, 500000 100000, 400000 1000...      SZ"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create a GeoPandas GeoDataFrame from the 100km resolution packaged iterator\n",
    "# of BNGReference object Features\n",
    "# Set the coordinate reference system to British National Grid (EPSG: 27700)\n",
    "# https://epsg.io/27700\n",
    "gdf = gpd.GeoDataFrame.from_features(bng_grid_100km, crs=27700)\n",
    "\n",
    "gdf.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "4ff21190",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>geometry</th>\n",
       "      <th>bng_ref</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>POLYGON ((529500 179600, 529500 179700, 529400...</td>\n",
       "      <td>TQ294796</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>POLYGON ((529600 179600, 529600 179700, 529500...</td>\n",
       "      <td>TQ295796</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>POLYGON ((529700 179600, 529700 179700, 529600...</td>\n",
       "      <td>TQ296796</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>POLYGON ((529800 179600, 529800 179700, 529700...</td>\n",
       "      <td>TQ297796</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>POLYGON ((529900 179600, 529900 179700, 529800...</td>\n",
       "      <td>TQ298796</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                            geometry   bng_ref\n",
       "0  POLYGON ((529500 179600, 529500 179700, 529400...  TQ294796\n",
       "1  POLYGON ((529600 179600, 529600 179700, 529500...  TQ295796\n",
       "2  POLYGON ((529700 179600, 529700 179700, 529600...  TQ296796\n",
       "3  POLYGON ((529800 179600, 529800 179700, 529700...  TQ297796\n",
       "4  POLYGON ((529900 179600, 529900 179700, 529800...  TQ298796"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Custom bounding box coordinates\n",
    "# (x_min, y_min, x_max, y_max)\n",
    "bbox = (529476, 179654, 532170, 181116)\n",
    "\n",
    "# Generate BNGReference object Features covering the custom bounds at 100m resolution\n",
    "# Create GeoPandas GeoDataFrame from the iterator of Features\n",
    "gdf = gpd.GeoDataFrame.from_features(\n",
    "    bbox_to_bng_iterfeatures(*bbox, resolution=\"100m\"), crs=27700\n",
    ")\n",
    "\n",
    "gdf.head()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "osbng",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.13.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}