Observation.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 87,
   "id": "8988a289",
   "metadata": {
    "ExecuteTime": {
     "start_time": "2023-08-16T22:51:35.412Z"
    }
   },
   "outputs": [],
   "source": [
    "# %cd ~/src/Sunrise-Demo/\n",
    "from __future__ import annotations\n",
    "try:\n",
    "    from mediocreatbest import auto, run\n",
    "except ImportError:\n",
    "    %pip install --quiet --upgrade pip\n",
    "    %pip install --upgrade --force-reinstall \\\n",
    "        mediocreatbest@git+https://gist.github.com/player1537/3457b026ed6ef6696d758517f55a58df.git\n",
    "from mediocreatbest import auto, run\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "id": "38633a1f",
   "metadata": {
    "tags": [
     "parameters"
    ]
   },
   "outputs": [],
   "source": [
    "# SPECIES = \"0000172\"\n",
    "SPECIES = \"0029846\"\n",
    "DO_SAVE = True\n",
    "TERRAIN_QUALITY = (\n",
    "    0\n",
    "    # 1\n",
    "    # 2\n",
    ")\n",
    "VIDEO_QUALITY = (\n",
    "#     0\n",
    "#     1\n",
    "    2\n",
    ")\n",
    "\n",
    "Z = 13\n",
    "TixelZ = 21\n",
    "\n",
    "SHOULD_SAVE = True\n",
    "\n",
    "# RLO=3300096\n",
    "# RHI=3310591\n",
    "# CLO=2236928\n",
    "# CHI=2259455\n",
    "\n",
    "# RLO=824832\n",
    "# RHI=827647\n",
    "RLO=823296\n",
    "RHI=829438\n",
    "# CLO=559104\n",
    "CLO=558080\n",
    "# CHI=564479\n",
    "CHI=566270\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eaf55110",
   "metadata": {},
   "source": [
    "## Setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "id": "22ac97e3",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-08-16T17:03:13.608025Z",
     "start_time": "2023-08-16T17:03:13.433756Z"
    }
   },
   "outputs": [],
   "source": [
    "%%scope\n",
    "def string_function(arr):\n",
    "    name = arr.__class__.__name__\n",
    "    if arr.size < 1024:\n",
    "        values = auto.numpy.array_repr(auto.numpy.ravel(arr))\n",
    "    else:\n",
    "        values = '...'\n",
    "        \n",
    "    shape = auto.numpy.shape(arr)\n",
    "    dtype = arr.dtype\n",
    "    return f'{name}({values}, {shape=!r}, {dtype=!r})'\n",
    "auto.numpy.set_string_function(string_function, repr=False)\n",
    "auto.numpy.set_string_function(string_function, repr=True)\n",
    "\n",
    "auto.numpy.set_printoptions(\n",
    "    threshold=4,\n",
    "    edgeitems=0,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "545d8e35",
   "metadata": {},
   "source": [
    "### Typing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "id": "8b501e17",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-08-16T17:03:13.613481Z",
     "start_time": "2023-08-16T17:03:13.610415Z"
    }
   },
   "outputs": [],
   "source": [
    "Degree = auto.typing.NewType('Degree', float)\n",
    "Radian = auto.typing.NewType('Radian', float)\n",
    "Meter = auto.typing.NewType('Meter', float)\n",
    "Kilometer = auto.typing.NewType('Kilometer', float)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "404d2bc7",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-08-15T21:06:47.748725Z",
     "start_time": "2023-08-15T21:06:47.744400Z"
    }
   },
   "source": [
    "### Location (lat, lng, alt) to spatial (x, y, z)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "id": "a0dc7442",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-08-16T17:03:13.623809Z",
     "start_time": "2023-08-16T17:03:13.615368Z"
    }
   },
   "outputs": [],
   "source": [
    "def convert_location_to_spatial(\n",
    "    *,\n",
    "    lat: Degree,\n",
    "    lng: Degree,\n",
    "    alt: Meter,\n",
    "    math=auto.math,\n",
    ") -> Tuple[Meter, Meter, Meter]:\n",
    "    # Thanks https://gis.stackexchange.com/a/4148\n",
    "    \n",
    "    #> Note that \"Lat/Lon/Alt\" is just another name for spherical coordinates, and \n",
    "    #> phi/theta/rho are just another name for latitude, longitude, and altitude.\n",
    "    #> :) (A minor difference: altitude is usually measured from the surface of the \n",
    "    #> sphere; rho is measured from the center -- to convert, just add/subtract the \n",
    "    #> radius of the sphere.)\n",
    "    phi: Radian = math.radians(lat)\n",
    "    theta: Radian = math.radians(lng)\n",
    "    \n",
    "    # Thanks https://en.wikipedia.org/wiki/Earth_radius\n",
    "    #> A globally-average value is usually considered to be 6,371 kilometres (3,959 mi)\n",
    "    rho: Meter = 6_371_000 + alt\n",
    "    \n",
    "    #> x = math.cos(phi) * math.cos(theta) * rho\n",
    "    x: Meter = math.cos(phi) * math.cos(theta) * rho\n",
    "    \n",
    "    #> y = math.cos(phi) * math.sin(theta) * rho\n",
    "    y: Meter = math.cos(phi) * math.sin(theta) * rho\n",
    "\n",
    "    #> z = math.sin(phi) * rho # z is 'up'\n",
    "    z: Meter = math.sin(phi) * rho\n",
    "    \n",
    "    #> (Note there's some slightly arbitrary choices here in what each axis means...\n",
    "    #> you might want 'y' to point at the north pole instead of 'z', for example.)\n",
    "    \n",
    "    # I do :)\n",
    "    y, z = z, y\n",
    "    \n",
    "    return x, y, z"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9b2b2f26",
   "metadata": {},
   "source": [
    "### Tile (zoom, x, y) to location (lat, lng)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "id": "fd229e66",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-08-16T17:03:13.642501Z",
     "start_time": "2023-08-16T17:03:13.626842Z"
    }
   },
   "outputs": [],
   "source": [
    "@auto.mediocreatbest.doctest\n",
    "def convert_tile_coordinates_to_latlng(\n",
    "    *,\n",
    "    z: int,\n",
    "    x: int,\n",
    "    y: int,\n",
    "    math=auto.numpy,\n",
    "    return_google_maps_url: bool=False,\n",
    ") -> Tuple[Degree, Degree]:\n",
    "    # r\"\"\"\n",
    "\n",
    "    # >>> convert_tile_coordinates_to_latlng(z=15, x=8739, y=12925, return_google_maps_url=True)\n",
    "    # 'https://www.google.com/maps/@35.48751102385376,-83.990478515625,15.79z?entry=ttu'\n",
    "\n",
    "    # \"\"\"\n",
    "    \n",
    "    # Thanks https://gis.stackexchange.com/a/133535\n",
    "    \n",
    "    #> n = 2 ^ zoom\n",
    "    n = 2 ** z\n",
    "    \n",
    "    #> lon_deg = xtile / n * 360.0 - 180.0\n",
    "    lon_deg = x / n * 360.0 - 180.0\n",
    "\n",
    "    #> lat_rad = arctan(sinh(π * (1 - 2 * ytile / n)))\n",
    "    lat_rad = math.arctan(math.sinh(math.pi * (1.0 - 2.0 * y / n)))\n",
    "    \n",
    "    #> lat_deg = lat_rad * 180.0 / π\n",
    "    lat_deg = lat_rad * 180.0 / math.pi\n",
    "    \n",
    "    if return_google_maps_url:\n",
    "        return f\"\"\"https://www.google.com/maps/@{lat_deg},{lon_deg},15.79z?entry=ttu\"\"\"\n",
    "    \n",
    "    return lat_deg, lon_deg"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9e5aca25",
   "metadata": {},
   "source": [
    "### Dataclasses"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "id": "4fc4294e",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-08-16T17:03:13.650011Z",
     "start_time": "2023-08-16T17:03:13.644468Z"
    }
   },
   "outputs": [],
   "source": [
    "@auto.dataclasses.dataclass(eq=True, order=True, frozen=True)\n",
    "class Coord:\n",
    "    \"\"\"Tile image coordinates for mapbox/etc services\"\"\"\n",
    "    z: int\n",
    "    x: int\n",
    "    y: int\n",
    "\n",
    "    @property\n",
    "    def nw(self) -> Location:\n",
    "        \"\"\"North-West lat/lng of current tile\"\"\"\n",
    "        lat, lng = tile_coordinates_to_latlng(\n",
    "            z=self.z,\n",
    "            x=self.y,\n",
    "            y=self.x,\n",
    "            # z=self.z,\n",
    "            # x=self.x,\n",
    "            # y=self.y,\n",
    "        )\n",
    "        return Location(lat=lat, lng=lng)\n",
    "\n",
    "    @property\n",
    "    def se(self) -> Location:\n",
    "        \"\"\"South-East lat/lng of current tile\"\"\"\n",
    "        lat, lng = tile_coordinates_to_latlng(\n",
    "            z=self.z,\n",
    "            x=1+self.y,\n",
    "            y=1+self.x,\n",
    "            # z=self.z,\n",
    "            # x=1+self.x,\n",
    "            # y=1+self.y,\n",
    "        )\n",
    "        return Location(lat=lat, lng=lng)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "5fdb5aa8",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-08-16T17:03:13.658280Z",
     "start_time": "2023-08-16T17:03:13.651767Z"
    }
   },
   "outputs": [],
   "source": [
    "@auto.dataclasses.dataclass(eq=True, frozen=True)\n",
    "class Domain:\n",
    "    \"\"\"Lower (inclusive) and upper (inclusive) bounds of latitude/longitude\"\"\"\n",
    "    lo: Coord\n",
    "    hi: Coord\n",
    "        \n",
    "    @property\n",
    "    def coords(self) -> List[Coord]:\n",
    "        \"\"\"All coordinates within lower/upper bounds\"\"\"\n",
    "        coords = []\n",
    "        for z, x, y in auto.itertools.product(\n",
    "            range(self.lo.z, 1+self.hi.z),\n",
    "            range(self.lo.x, 1+self.hi.x),\n",
    "            range(self.lo.y, 1+self.hi.y),\n",
    "        ):\n",
    "            coords.append(Coord(\n",
    "                z=z,\n",
    "                x=x,\n",
    "                y=y,\n",
    "            ))\n",
    "        \n",
    "        return coords"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "id": "a0bdce30",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-08-16T17:03:13.665765Z",
     "start_time": "2023-08-16T17:03:13.660337Z"
    }
   },
   "outputs": [],
   "source": [
    "@auto.dataclasses.dataclass(eq=True, order=True, frozen=True)\n",
    "class Location:\n",
    "    \"\"\"Geographical latitude/longitude\"\"\"\n",
    "    lat: Degree\n",
    "    lng: Degree\n",
    "    alt: Optional[Meter] = auto.dataclasses.field(default=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "id": "241550e4",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-08-16T17:03:13.675287Z",
     "start_time": "2023-08-16T17:03:13.667775Z"
    }
   },
   "outputs": [],
   "source": [
    "@auto.dataclasses.dataclass(eq=True, order=True, frozen=True)\n",
    "class Point:\n",
    "    x: Kilometer\n",
    "    y: Kilometer\n",
    "    z: Kilometer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "id": "7ddeb72b",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-08-16T17:03:13.683984Z",
     "start_time": "2023-08-16T17:03:13.677039Z"
    }
   },
   "outputs": [],
   "source": [
    "# @dispatch\n",
    "@auto.dataclasses.dataclass(eq=True, order=True, frozen=True)\n",
    "class Tixel:\n",
    "    y: int\n",
    "    x: int\n",
    "        \n",
    "    # z: ClassVar[int] = 23\n",
    "    z: ClassVar[int] = TixelZ\n",
    "        \n",
    "    @property\n",
    "    def location(self) -> Location:\n",
    "        \"\"\"Center lat/lng of current tixel\"\"\"\n",
    "        lat, lng = tile_coordinates_to_latlng(\n",
    "            z=1+self.z,\n",
    "            x=1+self.x,\n",
    "            y=1+self.y,\n",
    "        )\n",
    "        return Location(lat=lat, lng=lng)\n",
    "\n",
    "# @Tixel.register\n",
    "# def __tixel_from_coord(coord: Coord, /, *, res: int):\n",
    "#     dz = int(auto.math.log2(Tixel.z - coord.z))\n",
    "    \n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bcec0562",
   "metadata": {},
   "source": [
    "## Observations\n",
    "\n",
    "We want to get the observation category, i.e. the percentage. The goal of this section is to get the tile data for a particular species for the \"pinks\" colormap and assign a category (integer, 0 to 3, inclusive) according to the nearest \"pinks\" color. The categories are: `0` for 0-25%; `1` for 25-50%; `2` for 50-75%; and `3` for 75-100%."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "id": "a0e2cde4",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-08-16T17:03:13.730036Z",
     "start_time": "2023-08-16T17:03:13.719760Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fetching: https://species.atlasofthesmokies.org/atbirecords/lexical_index.json\n",
      "b'{\"items\": [{\"common_name\": \"Red Maple\", \"irma_id\": \"0000337\", \"latin_name_ref\": \"Acer rubrum v rubrum\", \"latin_name\": \"Acer_rubrum_v_rubrum\"}, {\"common_name\": \"Sugar Maple\", \"irma_id\": \"0000341\", \"latin_name_ref\": \"Acer saccharum\", \"latin_name\": \"Acer_saccharum\"}, {\"common_name\": \"Tuliptree  \", \"irma_id\": \"0023010\", \"latin_name_ref\": \"Liriodendron tulipifera\", \"latin_name\": \"Liriodendron_tulipifera\"}, {\"common_name\": \"Eastern Hemlock\", \"irma_id\": \"0041423\", \"latin_name_ref\": \"Tsuga canadensis\", \"latin_name\": \"Tsuga_canadensis\"}, {\"common_name\": \"American Beech\", \"irma_id\": \"0016280\", \"latin_name_ref\": \"Fagus grandifolia\", \"latin_name\": \"Fagus_grandifolia\"}, {\"common_name\": \"Virginia Pine\", \"irma_id\": \"0031480\", \"latin_name_ref\": \"Pinus virginiana\", \"latin_name\": \"Pinus_virginiana\"}, {\"common_name\": \"Eastern White Pine\", \"irma_id\": \"0031478\", \"latin_name_ref\": \"Pinus strobus\", \"latin_name\": \"Pinus_strobus\"}, {\"common_name\": \"American Hornbeam\", \"irma_id\": \"0007165\", \"latin_name_ref\": \"Carpinus caroliniana\", \"latin_name\": \"Carpinus_caroliniana\"}, {\"common_name\": \"Flowering Dogwood\", \"irma_id\": \"0010101\", \"latin_name_ref\": \"Cornus florida\", \"latin_name\": \"Cornus_florida\"}, {\"common_name\": \"Sourwood\", \"irma_id\": \"0028205\", \"latin_name_ref\": \"Oxydendrum arboreum\", \"latin_name\": \"Oxydendrum_arboreum\"}, {\"common_name\": \"Sweet-Gum\", \"irma_id\": \"0023006\", \"latin_name_ref\": \"Liquidambar styraciflua\", \"latin_name\": \"Liquidambar_styraciflua\"}, {\"common_name\": \"Yellow Buckeye\", \"irma_id\": \"0000129\", \"latin_name_ref\": \"Aesculus flava\", \"latin_name\": \"Aesculus_flava\"}, {\"common_name\": \"Chestnut Oak\", \"irma_id\": \"0034382\", \"latin_name_ref\": \"Quercus prinus\", \"latin_name\": \"Quercus_prinus\"}, {\"common_name\": \"Black Gum \", \"irma_id\": \"0026948\", \"latin_name_ref\": \"Nyssa sylvatica\", \"latin_name\": \"Nyssa_sylvatica\"}, {\"common_name\": \"Northern White Oak\", \"irma_id\": \"0034369\", \"latin_name_ref\": \"Quercus alba\", \"latin_name\": \"Quercus_alba\"}, {\"common_name\": \"Christmas Fern\", \"irma_id\": \"0032349\", \"latin_name_ref\": \"Polystichum acrostichoides\", \"latin_name\": \"Polystichum_acrostichoides\"}, {\"common_name\": \"Early Lowbush Blueberry\", \"irma_id\": \"0042020\", \"latin_name_ref\": \"Vaccinium pallidum\", \"latin_name\": \"Vaccinium_pallidum\"}, {\"common_name\": \"Common Alder\", \"irma_id\": \"0001493\", \"latin_name_ref\": \"Alnus serrulata\", \"latin_name\": \"Alnus_serrulata\"}, {\"common_name\": \"Sawbrier\", \"irma_id\": \"0037281\", \"latin_name_ref\": \"Smilax glauca\", \"latin_name\": \"Smilax_glauca\"}, {\"common_name\": \"Redbud\", \"irma_id\": \"0007828\", \"latin_name_ref\": \"Cercis canadensis v canadensis\", \"latin_name\": \"Cercis_canadensis_v_canadensis\"}, {\"common_name\": \"Winged Sumac Variety\", \"irma_id\": \"0035111\", \"latin_name_ref\": \"Rhus copallinum variety\", \"latin_name\": \"Rhus_copallinum_variety\"}, {\"common_name\": \"American Sycamore\", \"irma_id\": \"0031735\", \"latin_name_ref\": \"Platanus occidentalis\", \"latin_name\": \"Platanus_occidentalis\"}, {\"common_name\": \"Horsebrier\", \"irma_id\": \"0037286\", \"latin_name_ref\": \"Smilax rotundifolia\", \"latin_name\": \"Smilax_rotundifolia\"}, {\"common_name\": \"Deerberry\", \"irma_id\": \"0042024\", \"latin_name_ref\": \"Vaccinium stamineum variety\", \"latin_name\": \"Vaccinium_stamineum_variety\"}, {\"common_name\": \"American Strawberry-Bush\", \"irma_id\": \"0015642\", \"latin_name_ref\": \"Euonymus americanus\", \"latin_name\": \"Euonymus_americanus\"}, {\"common_name\": \"Northern Red Oak\", \"irma_id\": \"0034383\", \"latin_name_ref\": \"Quercus rubra\", \"latin_name\": \"Quercus_rubra\"}, {\"common_name\": \"Pignut Hickory\", \"irma_id\": \"0007192\", \"latin_name_ref\": \"Carya glabra\", \"latin_name\": \"Carya_glabra\"}, {\"common_name\": \"Sassafras\", \"irma_id\": \"0035604\", \"latin_name_ref\": \"Sassafras albidum\", \"latin_name\": \"Sassafras_albidum\"}, {\"common_name\": \"Scarlet Oak\", \"irma_id\": \"0034370\", \"latin_name_ref\": \"Quercus coccinea\", \"latin_name\": \"Quercus_coccinea\"}, {\"common_name\": \"Four-Flower Yellow-Loosestrife\", \"irma_id\": \"0023582\", \"latin_name_ref\": \"Lysimachia quadrifolia\", \"latin_name\": \"Lysimachia_quadrifolia\"}, {\"common_name\": \"Greater Tickseed\", \"irma_id\": \"0010072\", \"latin_name_ref\": \"Coreopsis major variety\", \"latin_name\": \"Coreopsis_major_variety\"}, {\"common_name\": \"Black Locust\", \"irma_id\": \"0035341\", \"latin_name_ref\": \"Robinia pseudoacacia\", \"latin_name\": \"Robinia_pseudoacacia\"}, {\"common_name\": \"Muscadine\", \"irma_id\": \"0042385\", \"latin_name_ref\": \"Vitis rotundifolia\", \"latin_name\": \"Vitis_rotundifolia\"}, {\"common_name\": \"Yellow Indian Grass\", \"irma_id\": \"0037464\", \"latin_name_ref\": \"Sorghastrum nutans\", \"latin_name\": \"Sorghastrum_nutans\"}, {\"common_name\": \"Goat\\\\u2019S-Rue\", \"irma_id\": \"0039757\", \"latin_name_ref\": \"Tephrosia virginiana\", \"latin_name\": \"Tephrosia_virginiana\"}, {\"common_name\": \"Pitch Pine\", \"irma_id\": \"0031476\", \"latin_name_ref\": \"Pinus rigida\", \"latin_name\": \"Pinus_rigida\"}, {\"common_name\": \"Black Oak\", \"irma_id\": \"0034387\", \"latin_name_ref\": \"Quercus velutina\", \"latin_name\": \"Quercus_velutina\"}, {\"common_name\": \"Redline Darter\", \"irma_id\": \"0014976\", \"latin_name_ref\": \"Etheostoma rufilineatum\", \"latin_name\": \"Etheostoma_rufilineatum\"}, {\"common_name\": \"White Ash\", \"irma_id\": \"0016833\", \"latin_name_ref\": \"Fraxinus americana variety\", \"latin_name\": \"Fraxinus_americana_variety\"}, {\"common_name\": \"Striped Pipsissewa\", \"irma_id\": \"0008078\", \"latin_name_ref\": \"Chimaphila maculata\", \"latin_name\": \"Chimaphila_maculata\"}, {\"common_name\": \"Mountain-Laurel\", \"irma_id\": \"0021198\", \"latin_name_ref\": \"Kalmia latifolia\", \"latin_name\": \"Kalmia_latifolia\"}, {\"common_name\": \"Eastern Poison-Ivy\", \"irma_id\": \"0040609\", \"latin_name_ref\": \"Toxicodendron radicans radicans\", \"latin_name\": \"Toxicodendron_radicans_radicans\"}, {\"common_name\": \"Mockernut Hickory\", \"irma_id\": \"0007189\", \"latin_name_ref\": \"Carya alba\", \"latin_name\": \"Carya_alba\"}, {\"common_name\": \"American Holly\", \"irma_id\": \"0020695\", \"latin_name_ref\": \"Ilex opaca v opaca\", \"latin_name\": \"Ilex_opaca_v_opaca\"}, {\"common_name\": \"Feathery False Solomon\\'S-Seal\", \"irma_id\": \"0023807\", \"latin_name_ref\": \"Maianthemum racemosum racemosum\", \"latin_name\": \"Maianthemum_racemosum_racemosum\"}, {\"common_name\": \"Blackjack Oak\", \"irma_id\": \"0034374\", \"latin_name_ref\": \"Quercus marilandica\", \"latin_name\": \"Quercus_marilandica\"}, {\"common_name\": \"Sweet Birch\", \"irma_id\": \"0004767\", \"latin_name_ref\": \"Betula lenta\", \"latin_name\": \"Betula_lenta\"}, {\"common_name\": \"Whitetail Shiner\", \"irma_id\": \"0011081\", \"latin_name_ref\": \"Cyprinella galactura\", \"latin_name\": \"Cyprinella_galactura\"}, {\"common_name\": \"Flowering Spurge\", \"irma_id\": \"0015714\", \"latin_name_ref\": \"Euphorbia corollata\", \"latin_name\": \"Euphorbia_corollata\"}, {\"common_name\": \"Common Persimmon\", \"irma_id\": \"0011365\", \"latin_name_ref\": \"Diospyros virginiana\", \"latin_name\": \"Diospyros_virginiana\"}, {\"common_name\": \"Fraser\\\\u2019S Magnolia\", \"irma_id\": \"0023797\", \"latin_name_ref\": \"Magnolia fraseri\", \"latin_name\": \"Magnolia_fraseri\"}, {\"common_name\": \"Northern Hog Sucker\", \"irma_id\": \"0020292\", \"latin_name_ref\": \"Hypentelium nigricans\", \"latin_name\": \"Hypentelium_nigricans\"}, {\"common_name\": \"Red-Eyed Vireo\", \"irma_id\": \"0042365\", \"latin_name_ref\": \"Vireo olivaceus\", \"latin_name\": \"Vireo_olivaceus\"}, {\"common_name\": \"River Chub\", \"irma_id\": \"0026709\", \"latin_name_ref\": \"Nocomis micropogon\", \"latin_name\": \"Nocomis_micropogon\"}, {\"common_name\": \"Variable Panic Grass\", \"irma_id\": \"0012105\", \"latin_name_ref\": \"Dichanthelium commutatum\", \"latin_name\": \"Dichanthelium_commutatum\"}, {\"common_name\": \"Black-Throated Green Warbler\", \"irma_id\": \"0036700\", \"latin_name_ref\": \"Setophaga virens\", \"latin_name\": \"Setophaga_virens\"}, {\"common_name\": \"Hairy Blueberry\", \"irma_id\": \"0042017\", \"latin_name_ref\": \"Vaccinium hirsutum\", \"latin_name\": \"Vaccinium_hirsutum\"}, {\"common_name\": \"Striped Maple \", \"irma_id\": \"0000333\", \"latin_name_ref\": \"Acer pensylvanicum\", \"latin_name\": \"Acer_pensylvanicum\"}, {\"common_name\": \"Buffalo-Nut  \", \"irma_id\": \"0034333\", \"latin_name_ref\": \"Pyrularia pubera\", \"latin_name\": \"Pyrularia_pubera\"}, {\"common_name\": \"Mountain Holly\", \"irma_id\": \"0020693\", \"latin_name_ref\": \"Ilex montana\", \"latin_name\": \"Ilex_montana\"}, {\"common_name\": \"Little False Bluestem\", \"irma_id\": \"0035757\", \"latin_name_ref\": \"Schizachyrium scoparium v scoparium\", \"latin_name\": \"Schizachyrium_scoparium_v_scoparium\"}, {\"common_name\": \"Indigo Bunting\", \"irma_id\": \"0028022\", \"latin_name_ref\": \"Passerina cyanea\", \"latin_name\": \"Passerina_cyanea\"}, {\"common_name\": \"Fungus\", \"irma_id\": \"0036247\", \"latin_name_ref\": \"Seiurus aurocapilla\", \"latin_name\": \"Seiurus_aurocapilla\"}, {\"common_name\": \"Common Silverbell\", \"irma_id\": \"0018255\", \"latin_name_ref\": \"Halesia tetraptera variety\", \"latin_name\": \"Halesia_tetraptera_variety\"}, {\"common_name\": \"Maple-Leaf Arrow-Wood\", \"irma_id\": \"0042267\", \"latin_name_ref\": \"Viburnum acerifolium\", \"latin_name\": \"Viburnum_acerifolium\"}, {\"common_name\": \"Virginia Creeper\", \"irma_id\": \"0027992\", \"latin_name_ref\": \"Parthenocissus quinquefolia\", \"latin_name\": \"Parthenocissus_quinquefolia\"}, {\"common_name\": \"Bear Huckleberry\", \"irma_id\": \"0017109\", \"latin_name_ref\": \"Gaylussacia ursina\", \"latin_name\": \"Gaylussacia_ursina\"}, {\"common_name\": \"Rattlesnake-Weed\", \"irma_id\": \"0017792\", \"latin_name_ref\": \"Hieracium venosum\", \"latin_name\": \"Hieracium_venosum\"}, {\"common_name\": \"Hooded Warbler\", \"irma_id\": \"0036687\", \"latin_name_ref\": \"Setophaga citrina\", \"latin_name\": \"Setophaga_citrina\"}, {\"common_name\": \"Short-Leaf Pine\", \"irma_id\": \"0031473\", \"latin_name_ref\": \"Pinus echinata\", \"latin_name\": \"Pinus_echinata\"}, {\"common_name\": \"Scarlet Tanager\", \"irma_id\": \"0031497\", \"latin_name_ref\": \"Piranga olivacea\", \"latin_name\": \"Piranga_olivacea\"}, {\"common_name\": \"Summer Grape\", \"irma_id\": \"0042378\", \"latin_name_ref\": \"Vitis aestivalis v aestivalis\", \"latin_name\": \"Vitis_aestivalis_v_aestivalis\"}, {\"common_name\": \"Naked-Flower Tick-Trefoil\", \"irma_id\": \"0011903\", \"latin_name_ref\": \"Desmodium nudiflorum\", \"latin_name\": \"Desmodium_nudiflorum\"}, {\"common_name\": \"American Crow\", \"irma_id\": \"0010244\", \"latin_name_ref\": \"Corvus brachyrhynchos\", \"latin_name\": \"Corvus_brachyrhynchos\"}, {\"common_name\": \"Black Chokecherry\", \"irma_id\": \"0033010\", \"latin_name_ref\": \"Prunus serotina v serotina\", \"latin_name\": \"Prunus_serotina_v_serotina\"}, {\"common_name\": \"Rue-Anemone\", \"irma_id\": \"0038579\", \"latin_name_ref\": \"Thalictrum thalictroides\", \"latin_name\": \"Thalictrum_thalictroides\"}, {\"common_name\": \"Ebony Spleenwort\", \"irma_id\": \"0004131\", \"latin_name_ref\": \"Asplenium platyneuron\", \"latin_name\": \"Asplenium_platyneuron\"}, {\"common_name\": \"Wavy-Leaf American-Aster\", \"irma_id\": \"0039094\", \"latin_name_ref\": \"Symphyotrichum undulatum\", \"latin_name\": \"Symphyotrichum_undulatum\"}, {\"common_name\": \"Mountain Bellwort\", \"irma_id\": \"0042003\", \"latin_name_ref\": \"Uvularia puberula\", \"latin_name\": \"Uvularia_puberula\"}, {\"common_name\": \"Black Huckleberry\", \"irma_id\": \"0017107\", \"latin_name_ref\": \"Gaylussacia baccata\", \"latin_name\": \"Gaylussacia_baccata\"}, {\"common_name\": \"Warpaint Shiner\", \"irma_id\": \"0023432\", \"latin_name_ref\": \"Luxilus coccogenis\", \"latin_name\": \"Luxilus_coccogenis\"}, {\"common_name\": \"Pileated Woodpecker\", \"irma_id\": \"0013009\", \"latin_name_ref\": \"Dryocopus pileatus\", \"latin_name\": \"Dryocopus_pileatus\"}, {\"common_name\": \"Carolina Chickadee\", \"irma_id\": \"0031946\", \"latin_name_ref\": \"Poecile carolinensis\", \"latin_name\": \"Poecile_carolinensis\"}, {\"common_name\": \"Eastern Hay-Scented Fern\", \"irma_id\": \"0011789\", \"latin_name_ref\": \"Dennstaedtia punctilobula\", \"latin_name\": \"Dennstaedtia_punctilobula\"}, {\"common_name\": \"Rosebay Rhododendron \", \"irma_id\": \"0035066\", \"latin_name_ref\": \"Rhododendron maximum\", \"latin_name\": \"Rhododendron_maximum\"}, {\"common_name\": \"Acadian Flycatcher\", \"irma_id\": \"0013547\", \"latin_name_ref\": \"Empidonax virescens\", \"latin_name\": \"Empidonax_virescens\"}, {\"common_name\": \"American Witch-Hazel\", \"irma_id\": \"0018294\", \"latin_name_ref\": \"Hamamelis virginiana\", \"latin_name\": \"Hamamelis_virginiana\"}, {\"common_name\": \"Tree Sparkle-Berry\", \"irma_id\": \"0042011\", \"latin_name_ref\": \"Vaccinium arboreum\", \"latin_name\": \"Vaccinium_arboreum\"}, {\"common_name\": \"White Snakeroot\", \"irma_id\": \"0000985\", \"latin_name_ref\": \"Ageratina altissima v altissima\", \"latin_name\": \"Ageratina_altissima_v_altissima\"}, {\"common_name\": \"Highland Doghobble\", \"irma_id\": \"0022461\", \"latin_name_ref\": \"Leucothoe fontanesiana\", \"latin_name\": \"Leucothoe_fontanesiana\"}, {\"common_name\": \"Worm-Eating Warbler\", \"irma_id\": \"0018649\", \"latin_name_ref\": \"Helmitheros vermivorus\", \"latin_name\": \"Helmitheros_vermivorus\"}, {\"common_name\": \"Tufted Titmouse\", \"irma_id\": \"0003263\", \"latin_name_ref\": \"Baeolophus bicolor\", \"latin_name\": \"Baeolophus_bicolor\"}, {\"common_name\": \"Black-And-White Warbler\", \"irma_id\": \"0025462\", \"latin_name_ref\": \"Mniotilta varia\", \"latin_name\": \"Mniotilta_varia\"}, {\"common_name\": \"Oldfield Cinquefoil\", \"irma_id\": \"0032520\", \"latin_name_ref\": \"Potentilla simplex\", \"latin_name\": \"Potentilla_simplex\"}, {\"common_name\": \"Trailing-Arbutus\", \"irma_id\": \"0014106\", \"latin_name_ref\": \"Epigaea repens\", \"latin_name\": \"Epigaea_repens\"}, {\"common_name\": \"Table Mountain Pine\", \"irma_id\": \"0031475\", \"latin_name_ref\": \"Pinus pungens\", \"latin_name\": \"Pinus_pungens\"}, {\"common_name\": \"Halberd-Leaf Yellow Violet\", \"irma_id\": \"0042317\", \"latin_name_ref\": \"Viola hastata\", \"latin_name\": \"Viola_hastata\"}, {\"common_name\": \"Blue-Headed Vireo\", \"irma_id\": \"0042367\", \"latin_name_ref\": \"Vireo solitarius\", \"latin_name\": \"Vireo_solitarius\"}, {\"common_name\": \"Smooth Shadbush \", \"irma_id\": \"0001757\", \"latin_name_ref\": \"Amelanchier laevis\", \"latin_name\": \"Amelanchier_laevis\"}, {\"common_name\": \"Pine Warbler\", \"irma_id\": \"0036696\", \"latin_name_ref\": \"Setophaga pinus\", \"latin_name\": \"Setophaga_pinus\"}, {\"common_name\": \"Anise-Scented Goldenrod\", \"irma_id\": \"0037384\", \"latin_name_ref\": \"Solidago odora\", \"latin_name\": \"Solidago_odora\"}, {\"common_name\": \"Wood Thrush\", \"irma_id\": \"0020188\", \"latin_name_ref\": \"Hylocichla mustelina\", \"latin_name\": \"Hylocichla_mustelina\"}, {\"common_name\": \"Red-Breasted Nuthatch\", \"irma_id\": \"0037229\", \"latin_name_ref\": \"Sitta canadensis\", \"latin_name\": \"Sitta_canadensis\"}, {\"common_name\": \"Dark-Eyed Junco\", \"irma_id\": \"0020999\", \"latin_name_ref\": \"Junco hyemalis\", \"latin_name\": \"Junco_hyemalis\"}, {\"common_name\": \"White-Breasted Nuthatch\", \"irma_id\": \"0037230\", \"latin_name_ref\": \"Sitta carolinensis\", \"latin_name\": \"Sitta_carolinensis\"}, {\"common_name\": \"Blue Ridge Two-Lined Salamander\", \"irma_id\": \"0014742\", \"latin_name_ref\": \"Eurycea wilderae\", \"latin_name\": \"Eurycea_wilderae\"}, {\"common_name\": \"Curtis\\' Goldenrod\", \"irma_id\": \"0037373\", \"latin_name_ref\": \"Solidago curtisii\", \"latin_name\": \"Solidago_curtisii\"}, {\"common_name\": \"Crossvine\", \"irma_id\": \"0004815\", \"latin_name_ref\": \"Bignonia capreolata\", \"latin_name\": \"Bignonia_capreolata\"}, {\"common_name\": \"Northern Parula\", \"irma_id\": \"0036683\", \"latin_name_ref\": \"Setophaga americana\", \"latin_name\": \"Setophaga_americana\"}, {\"common_name\": \"White Wood-Aster\", \"irma_id\": \"0014725\", \"latin_name_ref\": \"Eurybia divaricata\", \"latin_name\": \"Eurybia_divaricata\"}, {\"common_name\": \"Silver-Leaf Hydrangea\", \"irma_id\": \"0019782\", \"latin_name_ref\": \"Hydrangea radiata\", \"latin_name\": \"Hydrangea_radiata\"}, {\"common_name\": \"Yellow-Throated Warbler\", \"irma_id\": \"0036690\", \"latin_name_ref\": \"Setophaga dominica\", \"latin_name\": \"Setophaga_dominica\"}, {\"common_name\": \"Tennessee Shiner\", \"irma_id\": \"0026868\", \"latin_name_ref\": \"Notropis leuciodus\", \"latin_name\": \"Notropis_leuciodus\"}, {\"common_name\": \"American Hog-Peanut\", \"irma_id\": \"0001875\", \"latin_name_ref\": \"Amphicarpaea bracteata\", \"latin_name\": \"Amphicarpaea_bracteata\"}, {\"common_name\": \"Slippery Elm\", \"irma_id\": \"0041637\", \"latin_name_ref\": \"Ulmus rubra\", \"latin_name\": \"Ulmus_rubra\"}, {\"common_name\": \"Eastern Towhee\", \"irma_id\": \"0031483\", \"latin_name_ref\": \"Pipilo erythrophthalmus\", \"latin_name\": \"Pipilo_erythrophthalmus\"}, {\"common_name\": \"Blue Jay\", \"irma_id\": \"0010928\", \"latin_name_ref\": \"Cyanocitta cristata\", \"latin_name\": \"Cyanocitta_cristata\"}, {\"common_name\": \"Chimney Swift\", \"irma_id\": \"0006575\", \"latin_name_ref\": \"Chaetura pelagica\", \"latin_name\": \"Chaetura_pelagica\"}, {\"common_name\": \"Creeping Aster\", \"irma_id\": \"0014731\", \"latin_name_ref\": \"Eurybia surculosa\", \"latin_name\": \"Eurybia_surculosa\"}, {\"common_name\": \"New York Fern\", \"irma_id\": \"0038675\", \"latin_name_ref\": \"Thelypteris noveboracensis\", \"latin_name\": \"Thelypteris_noveboracensis\"}, {\"common_name\": \"Southern Harebell \", \"irma_id\": \"0005276\", \"latin_name_ref\": \"Campanula divaricata\", \"latin_name\": \"Campanula_divaricata\"}, {\"common_name\": \"Japanese Stilt Grass\", \"irma_id\": \"0025267\", \"latin_name_ref\": \"Microstegium vimineum\", \"latin_name\": \"Microstegium_vimineum\"}, {\"common_name\": \"Canadian Blacksnakeroot\", \"irma_id\": \"0033209\", \"latin_name_ref\": \"Sanicula canadensis v canadensis\", \"latin_name\": \"Sanicula_canadensis_v_canadensis\"}, {\"common_name\": \"Yellow Birch\", \"irma_id\": \"0004765\", \"latin_name_ref\": \"Betula alleghaniensis variety\", \"latin_name\": \"Betula_alleghaniensis_variety\"}, {\"common_name\": \"Perfoliate Bellwort\", \"irma_id\": \"0042002\", \"latin_name_ref\": \"Uvularia perfoliata\", \"latin_name\": \"Uvularia_perfoliata\"}, {\"common_name\": \"Yellow Ragwort \", \"irma_id\": \"0028378\", \"latin_name_ref\": \"Packera anonyma\", \"latin_name\": \"Packera_anonyma\"}, {\"common_name\": \"Heart-Leaf Aster\", \"irma_id\": \"0039072\", \"latin_name_ref\": \"Symphyotrichum cordifolium variety\", \"latin_name\": \"Symphyotrichum_cordifolium_variety\"}, {\"common_name\": \"Hairy-Leaved Shadbush \", \"irma_id\": \"0001756\", \"latin_name_ref\": \"Amelanchier arborea\", \"latin_name\": \"Amelanchier_arborea\"}, {\"common_name\": \"Great Chickweed\", \"irma_id\": \"0037984\", \"latin_name_ref\": \"Stellaria pubera\", \"latin_name\": \"Stellaria_pubera\"}, {\"common_name\": \"Sweet White Violet\", \"irma_id\": \"0042309\", \"latin_name_ref\": \"Viola blanda variety\", \"latin_name\": \"Viola_blanda_variety\"}, {\"common_name\": \"Dwarf Cinquefoil\", \"irma_id\": \"0032516\", \"latin_name_ref\": \"Potentilla canadensis\", \"latin_name\": \"Potentilla_canadensis\"}, {\"common_name\": \"Northern Maidenhair\", \"irma_id\": \"0000059\", \"latin_name_ref\": \"Adiantum pedatum\", \"latin_name\": \"Adiantum_pedatum\"}, {\"common_name\": \"Rattlesnake Fern\", \"irma_id\": \"0005470\", \"latin_name_ref\": \"Botrychium virginianum\", \"latin_name\": \"Botrychium_virginianum\"}, {\"common_name\": \"Broad Beech Fern\", \"irma_id\": \"0030236\", \"latin_name_ref\": \"Phegopteris hexagonoptera\", \"latin_name\": \"Phegopteris_hexagonoptera\"}, {\"common_name\": \"Jack-In-The-Pulpit\", \"irma_id\": \"0003857\", \"latin_name_ref\": \"Arisaema triphyllum triphyllum\", \"latin_name\": \"Arisaema_triphyllum_triphyllum\"}, {\"common_name\": \"He-Huckleberry\", \"irma_id\": \"0023566\", \"latin_name_ref\": \"Lyonia ligustrina v ligustrina\", \"latin_name\": \"Lyonia_ligustrina_v_ligustrina\"}, {\"common_name\": \"Sessile-Leaf Bellwort\", \"irma_id\": \"0042005\", \"latin_name_ref\": \"Uvularia sessilifolia\", \"latin_name\": \"Uvularia_sessilifolia\"}, {\"common_name\": \"Marginal Wood Fern\", \"irma_id\": \"0013031\", \"latin_name_ref\": \"Dryopteris marginalis\", \"latin_name\": \"Dryopteris_marginalis\"}, {\"common_name\": \"Small Woodland Sunflower\", \"irma_id\": \"0018504\", \"latin_name_ref\": \"Helianthus microcephalus\", \"latin_name\": \"Helianthus_microcephalus\"}, {\"common_name\": \"Showy Goldenrod\", \"irma_id\": \"0037397\", \"latin_name_ref\": \"Solidago speciosa v rigidiuscula\", \"latin_name\": \"Solidago_speciosa_v_rigidiuscula\"}, {\"common_name\": \"Smallmouth Bass\", \"irma_id\": \"0025233\", \"latin_name_ref\": \"Micropterus dolomieu\", \"latin_name\": \"Micropterus_dolomieu\"}, {\"common_name\": \"Telescope Shiner\", \"irma_id\": \"0026874\", \"latin_name_ref\": \"Notropis telescopus\", \"latin_name\": \"Notropis_telescopus\"}, {\"common_name\": \"Indian Cucumber-Root\", \"irma_id\": \"0022774\", \"latin_name_ref\": \"Medeola virginiana\", \"latin_name\": \"Medeola_virginiana\"}, {\"common_name\": \"Large-Leaf Wood-Aster\", \"irma_id\": \"0014728\", \"latin_name_ref\": \"Eurybia macrophylla\", \"latin_name\": \"Eurybia_macrophylla\"}, {\"common_name\": \"Eastern Yellow Star-Grass\", \"irma_id\": \"0020518\", \"latin_name_ref\": \"Hypoxis hirsuta\", \"latin_name\": \"Hypoxis_hirsuta\"}, {\"common_name\": \"Carolina Vetch\", \"irma_id\": \"0042287\", \"latin_name_ref\": \"Vicia caroliniana\", \"latin_name\": \"Vicia_caroliniana\"}, {\"common_name\": \"Evergreen Woodfern\", \"irma_id\": \"0013030\", \"latin_name_ref\": \"Dryopteris intermedia\", \"latin_name\": \"Dryopteris_intermedia\"}, {\"common_name\": \"Smooth Blackberry\", \"irma_id\": \"0035421\", \"latin_name_ref\": \"Rubus canadensis\", \"latin_name\": \"Rubus_canadensis\"}, {\"common_name\": \"Stoneroot  \", \"irma_id\": \"0008357\", \"latin_name_ref\": \"Collinsonia canadensis\", \"latin_name\": \"Collinsonia_canadensis\"}, {\"common_name\": \"Spotted St. John\\\\u2019S-Wort\", \"irma_id\": \"0020324\", \"latin_name_ref\": \"Hypericum punctatum\", \"latin_name\": \"Hypericum_punctatum\"}, {\"common_name\": \"Cucumber-Tree\", \"irma_id\": \"0023796\", \"latin_name_ref\": \"Magnolia acuminata\", \"latin_name\": \"Magnolia_acuminata\"}, {\"common_name\": \"Louisiana Waterthrush\", \"irma_id\": \"0029173\", \"latin_name_ref\": \"Parkesia motacilla\", \"latin_name\": \"Parkesia_motacilla\"}, {\"common_name\": \"Central Stoneroller\", \"irma_id\": \"0005305\", \"latin_name_ref\": \"Campostoma anomalum\", \"latin_name\": \"Campostoma_anomalum\"}, {\"common_name\": \"Carolina Wren\", \"irma_id\": \"0039998\", \"latin_name_ref\": \"Thryothorus ludovicianus\", \"latin_name\": \"Thryothorus_ludovicianus\"}, {\"common_name\": \"Bosc\\\\u2019S Rosette Grass\", \"irma_id\": \"0012102\", \"latin_name_ref\": \"Dichanthelium boscii\", \"latin_name\": \"Dichanthelium_boscii\"}, {\"common_name\": \"Canadian Wood-Nettle\", \"irma_id\": \"0021704\", \"latin_name_ref\": \"Laportea canadensis\", \"latin_name\": \"Laportea_canadensis\"}, {\"common_name\": \"Yellow Fairybells\", \"irma_id\": \"0032838\", \"latin_name_ref\": \"Prosartes lanuginosa\", \"latin_name\": \"Prosartes_lanuginosa\"}, {\"common_name\": \"Three-Leaved Rattlesnake-Root\", \"irma_id\": \"0032555\", \"latin_name_ref\": \"Prenanthes trifoliolata\", \"latin_name\": \"Prenanthes_trifoliolata\"}, {\"common_name\": \"Northern Black Racer\", \"irma_id\": \"0009603\", \"latin_name_ref\": \"Coluber constrictor constrictor\", \"latin_name\": \"Coluber_constrictor_constrictor\"}, {\"common_name\": \"Cinnamon Fern\", \"irma_id\": \"0028130\", \"latin_name_ref\": \"Osmundastrum cinnamomeum\", \"latin_name\": \"Osmundastrum_cinnamomeum\"}, {\"common_name\": \"Veery\", \"irma_id\": \"0007284\", \"latin_name_ref\": \"Catharus fuscescens\", \"latin_name\": \"Catharus_fuscescens\"}, {\"common_name\": \"Black-Throated Blue Warbler\", \"irma_id\": \"0036684\", \"latin_name_ref\": \"Setophaga caerulescens\", \"latin_name\": \"Setophaga_caerulescens\"}, {\"common_name\": \"Maryland Golden-Aster\", \"irma_id\": \"0008562\", \"latin_name_ref\": \"Chrysopsis mariana\", \"latin_name\": \"Chrysopsis_mariana\"}, {\"common_name\": \"Spotted Dusky Salamander\", \"irma_id\": \"0011915\", \"latin_name_ref\": \"Desmognathus conanti\", \"latin_name\": \"Desmognathus_conanti\"}, {\"common_name\": \"Northern Copperhead\", \"irma_id\": \"0000993\", \"latin_name_ref\": \"Agkistrodon contortrix mokasen\", \"latin_name\": \"Agkistrodon_contortrix_mokasen\"}, {\"common_name\": \"Spicebush\", \"irma_id\": \"0022675\", \"latin_name_ref\": \"Lindera benzoin\", \"latin_name\": \"Lindera_benzoin\"}, {\"common_name\": \"Common Stone\", \"irma_id\": \"0000685\", \"latin_name_ref\": \"Acroneuria abnormis\", \"latin_name\": \"Acroneuria_abnormis\"}, {\"common_name\": \"Entire-Leaf Yellow False Foxglove\", \"irma_id\": \"0004492\", \"latin_name_ref\": \"Aureolaria laevigata\", \"latin_name\": \"Aureolaria_laevigata\"}, {\"common_name\": \"Wild Hydrangea\", \"irma_id\": \"0019778\", \"latin_name_ref\": \"Hydrangea arborescens\", \"latin_name\": \"Hydrangea_arborescens\"}, {\"common_name\": \"Black-Bellied Salamander\", \"irma_id\": \"0011926\", \"latin_name_ref\": \"Desmognathus quadramaculatus\", \"latin_name\": \"Desmognathus_quadramaculatus\"}, {\"common_name\": \"Northern Flicker\", \"irma_id\": \"0009425\", \"latin_name_ref\": \"Colaptes auratus\", \"latin_name\": \"Colaptes_auratus\"}, {\"common_name\": \"Canadian Violet\", \"irma_id\": \"0042310\", \"latin_name_ref\": \"Viola canadensis v canadensis\", \"latin_name\": \"Viola_canadensis_v_canadensis\"}, {\"common_name\": \"Fragrant Bedstraw\", \"irma_id\": \"0017030\", \"latin_name_ref\": \"Galium triflorum variety\", \"latin_name\": \"Galium_triflorum_variety\"}, {\"common_name\": \"Sweet Joe-Pye-Weed\", \"irma_id\": \"0015691\", \"latin_name_ref\": \"Eupatorium purpureum v purpureum\", \"latin_name\": \"Eupatorium_purpureum_v_purpureum\"}, {\"common_name\": \"Toothwort  \", \"irma_id\": \"0006523\", \"latin_name_ref\": \"Cardamine diphylla\", \"latin_name\": \"Cardamine_diphylla\"}, {\"common_name\": \"Spurious Retreat-Maker\", \"irma_id\": \"0019953\", \"latin_name_ref\": \"Hydropsyche sparna\", \"latin_name\": \"Hydropsyche_sparna\"}, {\"common_name\": \"One-Flower Indian-Pipe\", \"irma_id\": \"0025654\", \"latin_name_ref\": \"Monotropa uniflora\", \"latin_name\": \"Monotropa_uniflora\"}, {\"common_name\": \"Hairy Woodpecker\", \"irma_id\": \"0031337\", \"latin_name_ref\": \"Picoides villosus\", \"latin_name\": \"Picoides_villosus\"}, {\"common_name\": \"Chinaroot\", \"irma_id\": \"0037289\", \"latin_name_ref\": \"Smilax tamnoides variety\", \"latin_name\": \"Smilax_tamnoides_variety\"}, {\"common_name\": \"Mountain Sweet Pepper-Bush\", \"irma_id\": \"0009059\", \"latin_name_ref\": \"Clethra acuminata\", \"latin_name\": \"Clethra_acuminata\"}, {\"common_name\": \"Black Walnut\", \"irma_id\": \"0020996\", \"latin_name_ref\": \"Juglans nigra\", \"latin_name\": \"Juglans_nigra\"}, {\"common_name\": \"Spoon-Leaf Purple Everlasting\", \"irma_id\": \"0017042\", \"latin_name_ref\": \"Gamochaeta purpurea\", \"latin_name\": \"Gamochaeta_purpurea\"}, {\"common_name\": \"Bitter-Nut Hickory\", \"irma_id\": \"0007191\", \"latin_name_ref\": \"Carya cordiformis\", \"latin_name\": \"Carya_cordiformis\"}, {\"common_name\": \"Great Crested Flycatcher\", \"irma_id\": \"0024379\", \"latin_name_ref\": \"Myiarchus crinitus\", \"latin_name\": \"Myiarchus_crinitus\"}, {\"common_name\": \"Eastern Wood Pewee\", \"irma_id\": \"0009755\", \"latin_name_ref\": \"Contopus virens\", \"latin_name\": \"Contopus_virens\"}, {\"common_name\": \"Green Ash\", \"irma_id\": \"0016834\", \"latin_name_ref\": \"Fraxinus pennsylvanica\", \"latin_name\": \"Fraxinus_pennsylvanica\"}, {\"common_name\": \"Woman\\\\u2019S-Tobacco\", \"irma_id\": \"0002528\", \"latin_name_ref\": \"Antennaria plantaginifolia\", \"latin_name\": \"Antennaria_plantaginifolia\"}, {\"common_name\": \"Seal Salamander\", \"irma_id\": \"0011922\", \"latin_name_ref\": \"Desmognathus monticola\", \"latin_name\": \"Desmognathus_monticola\"}, {\"common_name\": \"Shingle Oak\", \"irma_id\": \"0034373\", \"latin_name_ref\": \"Quercus imbricaria\", \"latin_name\": \"Quercus_imbricaria\"}, {\"common_name\": \"Round-Leaf Violet\", \"irma_id\": \"0042340\", \"latin_name_ref\": \"Viola rotundifolia\", \"latin_name\": \"Viola_rotundifolia\"}, {\"common_name\": \"Yellow-Billed Cuckoo\", \"irma_id\": \"0009346\", \"latin_name_ref\": \"Coccyzus americanus\", \"latin_name\": \"Coccyzus_americanus\"}, {\"common_name\": \"Rose-Breasted Grosbeak\", \"irma_id\": \"0030335\", \"latin_name_ref\": \"Pheucticus ludovicianus\", \"latin_name\": \"Pheucticus_ludovicianus\"}, {\"common_name\": \"Large Eastern Free Living Caddis\", \"irma_id\": \"0035165\", \"latin_name_ref\": \"Rhyacophila fuscula\", \"latin_name\": \"Rhyacophila_fuscula\"}, {\"common_name\": \"Chestnut-Sided Warbler\", \"irma_id\": \"0036694\", \"latin_name_ref\": \"Setophaga pensylvanica\", \"latin_name\": \"Setophaga_pensylvanica\"}, {\"common_name\": \"Alternate-Leaf Dogwood\", \"irma_id\": \"0010099\", \"latin_name_ref\": \"Cornus alternifolia\", \"latin_name\": \"Cornus_alternifolia\"}, {\"common_name\": \"Highbush Blueberry\", \"irma_id\": \"0042014\", \"latin_name_ref\": \"Vaccinium corymbosum\", \"latin_name\": \"Vaccinium_corymbosum\"}, {\"common_name\": \"American Goldfinch\", \"irma_id\": \"0037889\", \"latin_name_ref\": \"Spinus tristis\", \"latin_name\": \"Spinus_tristis\"}, {\"common_name\": \"Silvery-Spleenwort F \", \"irma_id\": \"0011795\", \"latin_name_ref\": \"Deparia acrostichoides\", \"latin_name\": \"Deparia_acrostichoides\"}, {\"common_name\": \"Annual Ragweed\", \"irma_id\": \"0001743\", \"latin_name_ref\": \"Ambrosia artemisiifolia\", \"latin_name\": \"Ambrosia_artemisiifolia\"}, {\"common_name\": \"Lowland Bladder Fern\", \"irma_id\": \"0011518\", \"latin_name_ref\": \"Cystopteris protrusa\", \"latin_name\": \"Cystopteris_protrusa\"}, {\"common_name\": \"Eastern Worm Snake\", \"irma_id\": \"0007162\", \"latin_name_ref\": \"Carphophis amoenus amoenus\", \"latin_name\": \"Carphophis_amoenus_amoenus\"}, {\"common_name\": \"Licorice Bedstraw\", \"irma_id\": \"0017015\", \"latin_name_ref\": \"Galium circaezans v circaezans\", \"latin_name\": \"Galium_circaezans_v_circaezans\"}, {\"common_name\": \"Showy Gentian\", \"irma_id\": \"0014829\", \"latin_name_ref\": \"Gentiana decora\", \"latin_name\": \"Gentiana_decora\"}, {\"common_name\": \"Widow\\\\u2019S-Frill\", \"irma_id\": \"0036999\", \"latin_name_ref\": \"Silene stellata\", \"latin_name\": \"Silene_stellata\"}, {\"common_name\": \"Southern Red Oak\", \"irma_id\": \"0034371\", \"latin_name_ref\": \"Quercus falcata\", \"latin_name\": \"Quercus_falcata\"}, {\"common_name\": \"Winter Caddisfly\", \"irma_id\": \"0012688\", \"latin_name_ref\": \"Dolophilodes distinctus\", \"latin_name\": \"Dolophilodes_distinctus\"}, {\"common_name\": \"Bearded Shorthusk\", \"irma_id\": \"0005544\", \"latin_name_ref\": \"Brachyelytrum erectum\", \"latin_name\": \"Brachyelytrum_erectum\"}, {\"common_name\": \"American Toad\", \"irma_id\": \"0002088\", \"latin_name_ref\": \"Anaxyrus americanus\", \"latin_name\": \"Anaxyrus_americanus\"}, {\"common_name\": \"Red-Bellied Woodpecker\", \"irma_id\": \"0024072\", \"latin_name_ref\": \"Melanerpes carolinus\", \"latin_name\": \"Melanerpes_carolinus\"}, {\"common_name\": \"Virginia Virgin-Bower\", \"irma_id\": \"0009032\", \"latin_name_ref\": \"Clematis virginiana\", \"latin_name\": \"Clematis_virginiana\"}, {\"common_name\": \"Blue-Gray Gnatcatcher\", \"irma_id\": \"0032013\", \"latin_name_ref\": \"Polioptila caerulea\", \"latin_name\": \"Polioptila_caerulea\"}, {\"common_name\": \"Hairy Sweet-Cicely\", \"irma_id\": \"0028123\", \"latin_name_ref\": \"Osmorhiza claytonii\", \"latin_name\": \"Osmorhiza_claytonii\"}, {\"common_name\": \"Wintergreen  \", \"irma_id\": \"0017099\", \"latin_name_ref\": \"Gaultheria procumbens\", \"latin_name\": \"Gaultheria_procumbens\"}, {\"common_name\": \"Downy Woodpecker\", \"irma_id\": \"0031336\", \"latin_name_ref\": \"Picoides pubescens\", \"latin_name\": \"Picoides_pubescens\"}, {\"common_name\": \"Green Frog\", \"irma_id\": \"0023064\", \"latin_name_ref\": \"Lithobates clamitans\", \"latin_name\": \"Lithobates_clamitans\"}, {\"common_name\": \"Northern Ringneck Snake\", \"irma_id\": \"0011981\", \"latin_name_ref\": \"Diadophis punctatus edwardsii\", \"latin_name\": \"Diadophis_punctatus_edwardsii\"}, {\"common_name\": \"Cope\\'S Gray Treefrog\", \"irma_id\": \"0020152\", \"latin_name_ref\": \"Hyla chrysoscelis\", \"latin_name\": \"Hyla_chrysoscelis\"}, {\"common_name\": \"Crested Dwarf Iris\", \"irma_id\": \"0019577\", \"latin_name_ref\": \"Iris cristata\", \"latin_name\": \"Iris_cristata\"}, {\"common_name\": \"Northern/Midland Brown Snake\", \"irma_id\": \"0037533\", \"latin_name_ref\": \"Storeria dekayi dekayiwrightorum\", \"latin_name\": \"Storeria_dekayi_dekayiwrightorum\"}, {\"common_name\": \"Blackburnian Warbler\", \"irma_id\": \"0036691\", \"latin_name_ref\": \"Setophaga fusca\", \"latin_name\": \"Setophaga_fusca\"}, {\"common_name\": \"Woodland Stonecrop\", \"irma_id\": \"0036236\", \"latin_name_ref\": \"Sedum ternatum\", \"latin_name\": \"Sedum_ternatum\"}, {\"common_name\": \"Chipping Sparrow\", \"irma_id\": \"0037969\", \"latin_name_ref\": \"Spizella passerina\", \"latin_name\": \"Spizella_passerina\"}, {\"common_name\": \"Confusing Retreat-Maker\", \"irma_id\": \"0011392\", \"latin_name_ref\": \"Diplectrona modesta\", \"latin_name\": \"Diplectrona_modesta\"}, {\"common_name\": \"Common Saddle-Case Maker\", \"irma_id\": \"0017342\", \"latin_name_ref\": \"Glossosoma nigrior\", \"latin_name\": \"Glossosoma_nigrior\"}, {\"common_name\": \"White Baneberry\", \"irma_id\": \"0000789\", \"latin_name_ref\": \"Actaea pachypoda\", \"latin_name\": \"Actaea_pachypoda\"}, {\"common_name\": \"Steelhead\", \"irma_id\": \"0027465\", \"latin_name_ref\": \"Oncorhynchus mykiss\", \"latin_name\": \"Oncorhynchus_mykiss\"}, {\"common_name\": \"Greenfin Darter\", \"irma_id\": \"0014970\", \"latin_name_ref\": \"Etheostoma chlorobranchium\", \"latin_name\": \"Etheostoma_chlorobranchium\"}, {\"common_name\": \"Pale Touch-Me-Not\", \"irma_id\": \"0020720\", \"latin_name_ref\": \"Impatiens pallida\", \"latin_name\": \"Impatiens_pallida\"}, {\"common_name\": \"Appalachian White Snakeroot\", \"irma_id\": \"0000986\", \"latin_name_ref\": \"Ageratina altissima v roanensis\", \"latin_name\": \"Ageratina_altissima_v_roanensis\"}, {\"common_name\": \"Hooked Buttercup \", \"irma_id\": \"0034506\", \"latin_name_ref\": \"Ranunculus recurvatus\", \"latin_name\": \"Ranunculus_recurvatus\"}, {\"common_name\": \"Chaste Flat-Headed Mayfly\", \"irma_id\": \"0023633\", \"latin_name_ref\": \"Maccaffertium pudicum\", \"latin_name\": \"Maccaffertium_pudicum\"}, {\"common_name\": \"Thyme-Leaf Bluet\", \"irma_id\": \"0019363\", \"latin_name_ref\": \"Houstonia serpyllifolia\", \"latin_name\": \"Houstonia_serpyllifolia\"}, {\"common_name\": \"Narrowleaf Cowwheat\", \"irma_id\": \"0024049\", \"latin_name_ref\": \"Melampyrum lineare v latifolium\", \"latin_name\": \"Melampyrum_lineare_v_latifolium\"}, {\"common_name\": \"Smooth Carrion-Flower\", \"irma_id\": \"0037282\", \"latin_name_ref\": \"Smilax herbacea\", \"latin_name\": \"Smilax_herbacea\"}, {\"common_name\": \"Poverty Wild Oat\", \"irma_id\": \"0011583\", \"latin_name_ref\": \"Danthonia spicata\", \"latin_name\": \"Danthonia_spicata\"}, {\"common_name\": \"St. Johnswort\", \"irma_id\": \"0020318\", \"latin_name_ref\": \"Hypericum hypericoides\", \"latin_name\": \"Hypericum_hypericoides\"}, {\"common_name\": \"Diverse Little Caddis\", \"irma_id\": \"0023573\", \"latin_name_ref\": \"Lype diversa\", \"latin_name\": \"Lype_diversa\"}, {\"common_name\": \"Brown Creeper\", \"irma_id\": \"0007906\", \"latin_name_ref\": \"Certhia americana\", \"latin_name\": \"Certhia_americana\"}, {\"common_name\": \"Pipevine\", \"irma_id\": \"0003863\", \"latin_name_ref\": \"Aristolochia macrophylla\", \"latin_name\": \"Aristolochia_macrophylla\"}, {\"common_name\": \"Allegheny Hawkweed\", \"irma_id\": \"0017786\", \"latin_name_ref\": \"Hieracium paniculatum\", \"latin_name\": \"Hieracium_paniculatum\"}, {\"common_name\": \"Umbrella Magnolia\", \"irma_id\": \"0023802\", \"latin_name_ref\": \"Magnolia tripetala\", \"latin_name\": \"Magnolia_tripetala\"}, {\"common_name\": \"Eastern Hop-Hornbeam\", \"irma_id\": \"0028149\", \"latin_name_ref\": \"Ostrya virginiana\", \"latin_name\": \"Ostrya_virginiana\"}, {\"common_name\": \"Wood Betony \", \"irma_id\": \"0029480\", \"latin_name_ref\": \"Pedicularis canadensis\", \"latin_name\": \"Pedicularis_canadensis\"}, {\"common_name\": \"Allegheny Blackberry\", \"irma_id\": \"0035418\", \"latin_name_ref\": \"Rubus allegheniensis\", \"latin_name\": \"Rubus_allegheniensis\"}, {\"common_name\": \"Golden-Crowned Kinglet\", \"irma_id\": \"0034547\", \"latin_name_ref\": \"Regulus satrapa\", \"latin_name\": \"Regulus_satrapa\"}, {\"common_name\": \"Purple Bedstraw\", \"irma_id\": \"0017020\", \"latin_name_ref\": \"Galium latifolium\", \"latin_name\": \"Galium_latifolium\"}, {\"common_name\": \"Common Blue Violet\", \"irma_id\": \"0042347\", \"latin_name_ref\": \"Viola sororia variety\", \"latin_name\": \"Viola_sororia_variety\"}, {\"common_name\": \"Black-Capped Chickadee\", \"irma_id\": \"0031945\", \"latin_name_ref\": \"Poecile atricapillus\", \"latin_name\": \"Poecile_atricapillus\"}, {\"common_name\": \"Purple-Node Joe-Pye-Weed\", \"irma_id\": \"0015973\", \"latin_name_ref\": \"Eutrochium purpureum v pupureum\", \"latin_name\": \"Eutrochium_purpureum_v_pupureum\"}, {\"common_name\": \"Pennsylvania Sedge\", \"irma_id\": \"0007061\", \"latin_name_ref\": \"Carex pensylvanica\", \"latin_name\": \"Carex_pensylvanica\"}, {\"common_name\": \"Flattened Wild Oat\", \"irma_id\": \"0011580\", \"latin_name_ref\": \"Danthonia compressa\", \"latin_name\": \"Danthonia_compressa\"}, {\"common_name\": \"White Bergamot\", \"irma_id\": \"0025563\", \"latin_name_ref\": \"Monarda clinopodia\", \"latin_name\": \"Monarda_clinopodia\"}, {\"common_name\": \"Eastern Red-Cedar\", \"irma_id\": \"0021182\", \"latin_name_ref\": \"Juniperus virginiana v virginiana\", \"latin_name\": \"Juniperus_virginiana_v_virginiana\"}, {\"common_name\": \"Pale Indian-Plantain\", \"irma_id\": \"0003931\", \"latin_name_ref\": \"Arnoglossum atriplicifolium\", \"latin_name\": \"Arnoglossum_atriplicifolium\"}, {\"common_name\": \"Frost Grape\", \"irma_id\": \"0042387\", \"latin_name_ref\": \"Vitis vulpina\", \"latin_name\": \"Vitis_vulpina\"}, {\"common_name\": \"Virginia Knotweed \", \"irma_id\": \"0032113\", \"latin_name_ref\": \"Polygonum virginianum\", \"latin_name\": \"Polygonum_virginianum\"}, {\"common_name\": \"Lanceleaf Wild Licorice\", \"irma_id\": \"0017019\", \"latin_name_ref\": \"Galium lanceolatum\", \"latin_name\": \"Galium_lanceolatum\"}, {\"common_name\": \"Mourning Dove\", \"irma_id\": \"0041807\", \"latin_name_ref\": \"Zenaida macroura\", \"latin_name\": \"Zenaida_macroura\"}, {\"common_name\": \"Northern Water Snake\", \"irma_id\": \"0026549\", \"latin_name_ref\": \"Nerodia sipedon sipedon\", \"latin_name\": \"Nerodia_sipedon_sipedon\"}, {\"common_name\": \"Appalachian Brook Crayfish\", \"irma_id\": \"0005196\", \"latin_name_ref\": \"Cambarus Cambarus bartonii\", \"latin_name\": \"Cambarus_Cambarus_bartonii\"}, {\"common_name\": \"Pale Stripetail\", \"irma_id\": \"0019654\", \"latin_name_ref\": \"Isoperla holochlora\", \"latin_name\": \"Isoperla_holochlora\"}, {\"common_name\": \"Yellowlined Caterpillar\", \"irma_id\": \"0024699\", \"latin_name_ref\": \"Nadata gibbosa\", \"latin_name\": \"Nadata_gibbosa\"}, {\"common_name\": \"Canada Warbler\", \"irma_id\": \"0006536\", \"latin_name_ref\": \"Cardellina canadensis\", \"latin_name\": \"Cardellina_canadensis\"}, {\"common_name\": \"Winter Wren\", \"irma_id\": \"0041339\", \"latin_name_ref\": \"Troglodytes hiemalis\", \"latin_name\": \"Troglodytes_hiemalis\"}, {\"common_name\": \"Button-Hemp  \", \"irma_id\": \"0004950\", \"latin_name_ref\": \"Boehmeria cylindrica\", \"latin_name\": \"Boehmeria_cylindrica\"}, {\"common_name\": \"White Edge Sedge\", \"irma_id\": \"0006757\", \"latin_name_ref\": \"Carex debilis variety\", \"latin_name\": \"Carex_debilis_variety\"}, {\"common_name\": \"Rock Bass\", \"irma_id\": \"0001703\", \"latin_name_ref\": \"Ambloplites rupestris\", \"latin_name\": \"Ambloplites_rupestris\"}, {\"common_name\": \"Pin Cherry \", \"irma_id\": \"0033007\", \"latin_name_ref\": \"Prunus pensylvanica\", \"latin_name\": \"Prunus_pensylvanica\"}, {\"common_name\": \"Scarlet Beebalm\", \"irma_id\": \"0025564\", \"latin_name_ref\": \"Monarda didyma\", \"latin_name\": \"Monarda_didyma\"}, {\"common_name\": \"Ruby-Throated Hummingbird\", \"irma_id\": \"0003585\", \"latin_name_ref\": \"Archilochus colubris\", \"latin_name\": \"Archilochus_colubris\"}, {\"common_name\": \"Yellow-Throated Vireo\", \"irma_id\": \"0042362\", \"latin_name_ref\": \"Vireo flavifrons\", \"latin_name\": \"Vireo_flavifrons\"}, {\"common_name\": \"Pearl Crescent\", \"irma_id\": \"0030784\", \"latin_name_ref\": \"Phyciodes tharos\", \"latin_name\": \"Phyciodes_tharos\"}, {\"common_name\": \"Early Blue Violet\", \"irma_id\": \"0042327\", \"latin_name_ref\": \"Viola palmata\", \"latin_name\": \"Viola_palmata\"}, {\"common_name\": \"Northern Cardinal\", \"irma_id\": \"0006538\", \"latin_name_ref\": \"Cardinalis cardinalis\", \"latin_name\": \"Cardinalis_cardinalis\"}, {\"common_name\": \"Water Penny Beetle\", \"irma_id\": \"0033384\", \"latin_name_ref\": \"Psephenus herricki\", \"latin_name\": \"Psephenus_herricki\"}, {\"common_name\": \"Early Meadow-Rue\", \"irma_id\": \"0039929\", \"latin_name_ref\": \"Thalictrum dioicum\", \"latin_name\": \"Thalictrum_dioicum\"}, {\"common_name\": \"Ebony Jewelwing\", \"irma_id\": \"0006285\", \"latin_name_ref\": \"Calopteryx maculata\", \"latin_name\": \"Calopteryx_maculata\"}, {\"common_name\": \"Mountain Maple\", \"irma_id\": \"0000343\", \"latin_name_ref\": \"Acer spicatum\", \"latin_name\": \"Acer_spicatum\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0030039\", \"latin_name_ref\": \"Phagocata morgani morgani\", \"latin_name\": \"Phagocata_morgani_morgani\"}, {\"common_name\": \"Lopseed\", \"irma_id\": \"0029446\", \"latin_name_ref\": \"Phryma leptostachya\", \"latin_name\": \"Phryma_leptostachya\"}, {\"common_name\": \"Zigzag Goldenrod\", \"irma_id\": \"0037376\", \"latin_name_ref\": \"Solidago flexicaulis\", \"latin_name\": \"Solidago_flexicaulis\"}, {\"common_name\": \"Wood Frog\", \"irma_id\": \"0023068\", \"latin_name_ref\": \"Lithobates sylvaticus\", \"latin_name\": \"Lithobates_sylvaticus\"}, {\"common_name\": \"Broad-Winged Hawk\", \"irma_id\": \"0005926\", \"latin_name_ref\": \"Buteo platypterus\", \"latin_name\": \"Buteo_platypterus\"}, {\"common_name\": \"Rat Snake\", \"irma_id\": \"0013337\", \"latin_name_ref\": \"Elaphe obsoleta obsoleta\", \"latin_name\": \"Elaphe_obsoleta_obsoleta\"}, {\"common_name\": \"Yellow-Striped Small Minnow Mayfly\", \"irma_id\": \"0003437\", \"latin_name_ref\": \"Baetis flavistriga\", \"latin_name\": \"Baetis_flavistriga\"}, {\"common_name\": \"Cedar Waxwing\", \"irma_id\": \"0005137\", \"latin_name_ref\": \"Bombycilla cedrorum\", \"latin_name\": \"Bombycilla_cedrorum\"}, {\"common_name\": \"Largescale Stoneroller\", \"irma_id\": \"0005306\", \"latin_name_ref\": \"Campostoma oligolepis\", \"latin_name\": \"Campostoma_oligolepis\"}, {\"common_name\": \"Carolina Free Living Caddis\", \"irma_id\": \"0035159\", \"latin_name_ref\": \"Rhyacophila carolina\", \"latin_name\": \"Rhyacophila_carolina\"}, {\"common_name\": \"Banded Tussock Moth\", \"irma_id\": \"0018283\", \"latin_name_ref\": \"Halysidota tessellaris\", \"latin_name\": \"Halysidota_tessellaris\"}, {\"common_name\": \"Eastern Tiger Swallowtail\", \"irma_id\": \"0028683\", \"latin_name_ref\": \"Papilio glaucus\", \"latin_name\": \"Papilio_glaucus\"}, {\"common_name\": \"Mottled Sculpin\", \"irma_id\": \"0010370\", \"latin_name_ref\": \"Cottus bairdi\", \"latin_name\": \"Cottus_bairdi\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0032116\", \"latin_name_ref\": \"Polygrammate hebraeicum\", \"latin_name\": \"Polygrammate_hebraeicum\"}, {\"common_name\": \"Wild Turkey\", \"irma_id\": \"0024164\", \"latin_name_ref\": \"Meleagris gallopavo\", \"latin_name\": \"Meleagris_gallopavo\"}, {\"common_name\": \"Three-Tailed Small Minnow Mayfly\", \"irma_id\": \"0003462\", \"latin_name_ref\": \"Baetis tricaudatus\", \"latin_name\": \"Baetis_tricaudatus\"}, {\"common_name\": \"Mitchell`S Dogfaced Caddis\", \"irma_id\": \"0026371\", \"latin_name_ref\": \"Neophylax mitchelli\", \"latin_name\": \"Neophylax_mitchelli\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0014655\", \"latin_name_ref\": \"Euplexia benesimilis\", \"latin_name\": \"Euplexia_benesimilis\"}, {\"common_name\": \"Common Dogfaced Caddis\", \"irma_id\": \"0026368\", \"latin_name_ref\": \"Neophylax consimilis\", \"latin_name\": \"Neophylax_consimilis\"}, {\"common_name\": \"American Squawroot \", \"irma_id\": \"0009720\", \"latin_name_ref\": \"Conopholis americana\", \"latin_name\": \"Conopholis_americana\"}, {\"common_name\": \"Longnose Dace\", \"irma_id\": \"0034940\", \"latin_name_ref\": \"Rhinichthys cataractae\", \"latin_name\": \"Rhinichthys_cataractae\"}, {\"common_name\": \"Silver-Spotted Skipper\", \"irma_id\": \"0013910\", \"latin_name_ref\": \"Epargyreus clarus\", \"latin_name\": \"Epargyreus_clarus\"}, {\"common_name\": \"Red Mulberry\", \"irma_id\": \"0024403\", \"latin_name_ref\": \"Morus rubra\", \"latin_name\": \"Morus_rubra\"}, {\"common_name\": \"Unequal Flat-Headed Mayfly\", \"irma_id\": \"0013918\", \"latin_name_ref\": \"Epeorus dispar\", \"latin_name\": \"Epeorus_dispar\"}, {\"common_name\": \"Southern Pygmy Clubtail\", \"irma_id\": \"0021688\", \"latin_name_ref\": \"Lanthus vernalis\", \"latin_name\": \"Lanthus_vernalis\"}, {\"common_name\": \"American Elm\", \"irma_id\": \"0041635\", \"latin_name_ref\": \"Ulmus americana\", \"latin_name\": \"Ulmus_americana\"}, {\"common_name\": \"Tuberculate Spiny Crawler Mayfly\", \"irma_id\": \"0012992\", \"latin_name_ref\": \"Drunella tuberculata\", \"latin_name\": \"Drunella_tuberculata\"}, {\"common_name\": \"Cut-Leaf Grape-Fern\", \"irma_id\": \"0005462\", \"latin_name_ref\": \"Botrychium dissectum variety\", \"latin_name\": \"Botrychium_dissectum_variety\"}, {\"common_name\": \"White Bluebead-Lily\", \"irma_id\": \"0009086\", \"latin_name_ref\": \"Clintonia umbellulata\", \"latin_name\": \"Clintonia_umbellulata\"}, {\"common_name\": \"Tall Rattlesnake-Root\", \"irma_id\": \"0032551\", \"latin_name_ref\": \"Prenanthes altissima\", \"latin_name\": \"Prenanthes_altissima\"}, {\"common_name\": \"Eastern Blacknose Dace\", \"irma_id\": \"0034939\", \"latin_name_ref\": \"Rhinichthys atratulus\", \"latin_name\": \"Rhinichthys_atratulus\"}, {\"common_name\": \"Rhomboid Eunotia Diatom\", \"irma_id\": \"0015617\", \"latin_name_ref\": \"Eunotia rhomboidea\", \"latin_name\": \"Eunotia_rhomboidea\"}, {\"common_name\": \"Southern Mountain-Cranberry\", \"irma_id\": \"0042015\", \"latin_name_ref\": \"Vaccinium erythrocarpum\", \"latin_name\": \"Vaccinium_erythrocarpum\"}, {\"common_name\": \"Hobblebush\", \"irma_id\": \"0042274\", \"latin_name_ref\": \"Viburnum lantanoides\", \"latin_name\": \"Viburnum_lantanoides\"}, {\"common_name\": \"River Birch\", \"irma_id\": \"0004769\", \"latin_name_ref\": \"Betula nigra\", \"latin_name\": \"Betula_nigra\"}, {\"common_name\": \"Wood-Sorrel  \", \"irma_id\": \"0028172\", \"latin_name_ref\": \"Oxalis montana\", \"latin_name\": \"Oxalis_montana\"}, {\"common_name\": \"Honey-Locust\", \"irma_id\": \"0017253\", \"latin_name_ref\": \"Gleditsia triacanthos\", \"latin_name\": \"Gleditsia_triacanthos\"}, {\"common_name\": \"Green-Head Coneflower\", \"irma_id\": \"0035444\", \"latin_name_ref\": \"Rudbeckia laciniata v humilis\", \"latin_name\": \"Rudbeckia_laciniata_v_humilis\"}, {\"common_name\": \"Beechdrops\", \"irma_id\": \"0014105\", \"latin_name_ref\": \"Epifagus virginiana\", \"latin_name\": \"Epifagus_virginiana\"}, {\"common_name\": \"Shag-Bark Hickory\", \"irma_id\": \"0007197\", \"latin_name_ref\": \"Carya ovata\", \"latin_name\": \"Carya_ovata\"}, {\"common_name\": \"Black-Chinned Red Salamander\", \"irma_id\": \"0033740\", \"latin_name_ref\": \"Pseudotriton ruber\", \"latin_name\": \"Pseudotriton_ruber\"}, {\"common_name\": \"Spring Salamander\", \"irma_id\": \"0018028\", \"latin_name_ref\": \"Gyrinophilus porphyriticus\", \"latin_name\": \"Gyrinophilus_porphyriticus\"}, {\"common_name\": \"Crossed Tail Armored Caddis\", \"irma_id\": \"0017548\", \"latin_name_ref\": \"Goera calcarata\", \"latin_name\": \"Goera_calcarata\"}, {\"common_name\": \"Wood Anemone \", \"irma_id\": \"0002263\", \"latin_name_ref\": \"Anemone quinquefolia\", \"latin_name\": \"Anemone_quinquefolia\"}, {\"common_name\": \"American Alumroot\", \"irma_id\": \"0017713\", \"latin_name_ref\": \"Heuchera americana\", \"latin_name\": \"Heuchera_americana\"}, {\"common_name\": \"Mountain Retreat-Maker\", \"irma_id\": \"0028920\", \"latin_name_ref\": \"Parapsyche cardis\", \"latin_name\": \"Parapsyche_cardis\"}, {\"common_name\": \"Serrate Fishfly\", \"irma_id\": \"0026636\", \"latin_name_ref\": \"Nigronia serricornis\", \"latin_name\": \"Nigronia_serricornis\"}, {\"common_name\": \"Mournful Finger-Net Caddis\", \"irma_id\": \"0042563\", \"latin_name_ref\": \"Wormaldia moesta\", \"latin_name\": \"Wormaldia_moesta\"}, {\"common_name\": \"Yellow Crownbeard\", \"irma_id\": \"0042152\", \"latin_name_ref\": \"Verbesina occidentalis\", \"latin_name\": \"Verbesina_occidentalis\"}, {\"common_name\": \"Maple Prominent\", \"irma_id\": \"0017652\", \"latin_name_ref\": \"Heterocampa guttivitta\", \"latin_name\": \"Heterocampa_guttivitta\"}, {\"common_name\": \"Atlantic Goldenrod\", \"irma_id\": \"0037364\", \"latin_name_ref\": \"Solidago arguta variety\", \"latin_name\": \"Solidago_arguta_variety\"}, {\"common_name\": \"Thin-Leaf Mountain-Mint\", \"irma_id\": \"0034114\", \"latin_name_ref\": \"Pycnanthemum montanum\", \"latin_name\": \"Pycnanthemum_montanum\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0039041\", \"latin_name_ref\": \"Symmerista albifrons\", \"latin_name\": \"Symmerista_albifrons\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0028505\", \"latin_name_ref\": \"Pangrapta decoralis\", \"latin_name\": \"Pangrapta_decoralis\"}, {\"common_name\": \"Lesser Smooth Free Living Caddis\", \"irma_id\": \"0035166\", \"latin_name_ref\": \"Rhyacophila glaberrima\", \"latin_name\": \"Rhyacophila_glaberrima\"}, {\"common_name\": \"Flatworm\", \"irma_id\": \"0005460\", \"latin_name_ref\": \"Botrychium dissectum v dissectum\", \"latin_name\": \"Botrychium_dissectum_v_dissectum\"}, {\"common_name\": \"American Dagger Moth\", \"irma_id\": \"0000700\", \"latin_name_ref\": \"Acronicta americana\", \"latin_name\": \"Acronicta_americana\"}, {\"common_name\": \"Morning-Glory Prominent\", \"irma_id\": \"0035813\", \"latin_name_ref\": \"Schizura ipomoeae\", \"latin_name\": \"Schizura_ipomoeae\"}, {\"common_name\": \"Pipevine Swallowtail\", \"irma_id\": \"0004661\", \"latin_name_ref\": \"Battus philenor\", \"latin_name\": \"Battus_philenor\"}, {\"common_name\": \"Hairy Bush-Clover\", \"irma_id\": \"0022343\", \"latin_name_ref\": \"Lespedeza hirta\", \"latin_name\": \"Lespedeza_hirta\"}, {\"common_name\": \"Catawba Spiny Crawler Mayfly\", \"irma_id\": \"0013998\", \"latin_name_ref\": \"Ephemerella catawba\", \"latin_name\": \"Ephemerella_catawba\"}, {\"common_name\": \"Black Free Living Caddis\", \"irma_id\": \"0035178\", \"latin_name_ref\": \"Rhyacophila nigrita\", \"latin_name\": \"Rhyacophila_nigrita\"}, {\"common_name\": \"Wataga Small Mark Caddis\", \"irma_id\": \"0025120\", \"latin_name_ref\": \"Micrasema wataga\", \"latin_name\": \"Micrasema_wataga\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0015428\", \"latin_name_ref\": \"Eudryas grata\", \"latin_name\": \"Eudryas_grata\"}, {\"common_name\": \"Painted Lichen Moth \", \"irma_id\": \"0020484\", \"latin_name_ref\": \"Hypoprepia fucosa\", \"latin_name\": \"Hypoprepia_fucosa\"}, {\"common_name\": \"Agreeable Tiger Moth \", \"irma_id\": \"0037877\", \"latin_name_ref\": \"Spilosoma congrua\", \"latin_name\": \"Spilosoma_congrua\"}, {\"common_name\": \"Yellow Stone\", \"irma_id\": \"0013144\", \"latin_name_ref\": \"Eccoptura xanthenes\", \"latin_name\": \"Eccoptura_xanthenes\"}, {\"common_name\": \"Tormented Spiny Crawler  Mayfly\", \"irma_id\": \"0014006\", \"latin_name_ref\": \"Ephemerella excrucians\", \"latin_name\": \"Ephemerella_excrucians\"}, {\"common_name\": \"Lesser Small Minnow Mayfly\", \"irma_id\": \"0003441\", \"latin_name_ref\": \"Baetis intercalaris\", \"latin_name\": \"Baetis_intercalaris\"}, {\"common_name\": \"Broad Shoulder Water Bug\", \"irma_id\": \"0034856\", \"latin_name_ref\": \"Rhagovelia obesa\", \"latin_name\": \"Rhagovelia_obesa\"}, {\"common_name\": \"Lash Springfly\", \"irma_id\": \"0034752\", \"latin_name_ref\": \"Remenus bilobatus\", \"latin_name\": \"Remenus_bilobatus\"}, {\"common_name\": \"Giant Cane\", \"irma_id\": \"0004041\", \"latin_name_ref\": \"Arundinaria gigantea gigantea\", \"latin_name\": \"Arundinaria_gigantea_gigantea\"}, {\"common_name\": \"American Redstart\", \"irma_id\": \"0036697\", \"latin_name_ref\": \"Setophaga ruticilla\", \"latin_name\": \"Setophaga_ruticilla\"}, {\"common_name\": \"Spiked Forestfly\", \"irma_id\": \"0001890\", \"latin_name_ref\": \"Amphinemura wui\", \"latin_name\": \"Amphinemura_wui\"}, {\"common_name\": \"Brook Springfly\", \"irma_id\": \"0023823\", \"latin_name_ref\": \"Malirekus hastatus\", \"latin_name\": \"Malirekus_hastatus\"}, {\"common_name\": \"River Fly\", \"irma_id\": \"0004298\", \"latin_name_ref\": \"Atherix lantha\", \"latin_name\": \"Atherix_lantha\"}, {\"common_name\": \"Southern Sturdy Burrower\", \"irma_id\": \"0033782\", \"latin_name_ref\": \"Psilotreta frontalis\", \"latin_name\": \"Psilotreta_frontalis\"}, {\"common_name\": \"Slosson`S Retreat-Maker\", \"irma_id\": \"0019952\", \"latin_name_ref\": \"Hydropsyche slossonae\", \"latin_name\": \"Hydropsyche_slossonae\"}, {\"common_name\": \"Common Little Caddis\", \"irma_id\": \"0033819\", \"latin_name_ref\": \"Psychomyia flavida\", \"latin_name\": \"Psychomyia_flavida\"}, {\"common_name\": \"Pale Flat-Headed Mayfly\", \"irma_id\": \"0038017\", \"latin_name_ref\": \"Stenacron pallidum\", \"latin_name\": \"Stenacron_pallidum\"}, {\"common_name\": \"Non-Biting Midge\", \"irma_id\": \"0041484\", \"latin_name_ref\": \"Tvetenia bavarica group\", \"latin_name\": \"Tvetenia_bavarica_group\"}, {\"common_name\": \"Silky Dogwood\", \"irma_id\": \"0010100\", \"latin_name_ref\": \"Cornus amomum\", \"latin_name\": \"Cornus_amomum\"}, {\"common_name\": \"Gray Catbird\", \"irma_id\": \"0013051\", \"latin_name_ref\": \"Dumetella carolinensis\", \"latin_name\": \"Dumetella_carolinensis\"}, {\"common_name\": \"Brown Trout\", \"irma_id\": \"0033173\", \"latin_name_ref\": \"Salmo trutta\", \"latin_name\": \"Salmo_trutta\"}, {\"common_name\": \"Western Black-Nosed Dace\", \"irma_id\": \"0034941\", \"latin_name_ref\": \"Rhinichthys obtusus\", \"latin_name\": \"Rhinichthys_obtusus\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0020646\", \"latin_name_ref\": \"Idia americalis\", \"latin_name\": \"Idia_americalis\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0020658\", \"latin_name_ref\": \"Idia rotundalis\", \"latin_name\": \"Idia_rotundalis\"}, {\"common_name\": \"Japanese Honeysuckle\", \"irma_id\": \"0023223\", \"latin_name_ref\": \"Lonicera japonica\", \"latin_name\": \"Lonicera_japonica\"}, {\"common_name\": \"Subequal Flat-Headed Mayfly\", \"irma_id\": \"0008760\", \"latin_name_ref\": \"Cinygmula subaequalis\", \"latin_name\": \"Cinygmula_subaequalis\"}, {\"common_name\": \"Tiger Spiketail\", \"irma_id\": \"0010049\", \"latin_name_ref\": \"Cordulegaster erronea\", \"latin_name\": \"Cordulegaster_erronea\"}, {\"common_name\": \"Mountain Delicate Burrower\", \"irma_id\": \"0016540\", \"latin_name_ref\": \"Fattigia pele\", \"latin_name\": \"Fattigia_pele\"}, {\"common_name\": \"Red Spruce\", \"irma_id\": \"0031330\", \"latin_name_ref\": \"Picea rubens\", \"latin_name\": \"Picea_rubens\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0035947\", \"latin_name_ref\": \"Scolecocampa liburna\", \"latin_name\": \"Scolecocampa_liburna\"}, {\"common_name\": \"Modest Flat-Headed Mayfly\", \"irma_id\": \"0023632\", \"latin_name_ref\": \"Maccaffertium modestum\", \"latin_name\": \"Maccaffertium_modestum\"}, {\"common_name\": \"Lundbeck`S Non-Biting Midge\", \"irma_id\": \"0028842\", \"latin_name_ref\": \"Parametriocnemus lundbeckii\", \"latin_name\": \"Parametriocnemus_lundbeckii\"}, {\"common_name\": \"Blueridge Stone\", \"irma_id\": \"0029846\", \"latin_name_ref\": \"Perlesta frisoni\", \"latin_name\": \"Perlesta_frisoni\"}, {\"common_name\": \"Pitiless Free Living Caddis\", \"irma_id\": \"0035186\", \"latin_name_ref\": \"Rhyacophila torva\", \"latin_name\": \"Rhyacophila_torva\"}, {\"common_name\": \"Ruffed Grouse\", \"irma_id\": \"0005167\", \"latin_name_ref\": \"Bonasa umbellus\", \"latin_name\": \"Bonasa_umbellus\"}, {\"common_name\": \"Post Oak\", \"irma_id\": \"0034386\", \"latin_name_ref\": \"Quercus stellata\", \"latin_name\": \"Quercus_stellata\"}, {\"common_name\": \"Slender Woodland Sedge\", \"irma_id\": \"0006758\", \"latin_name_ref\": \"Carex digitalis v digitalis\", \"latin_name\": \"Carex_digitalis_v_digitalis\"}, {\"common_name\": \"Creek Chub\", \"irma_id\": \"0036399\", \"latin_name_ref\": \"Semotilus atromaculatus\", \"latin_name\": \"Semotilus_atromaculatus\"}, {\"common_name\": \"Little Pronggill Mayfly\", \"irma_id\": \"0018158\", \"latin_name_ref\": \"Habrophlebia vibrans\", \"latin_name\": \"Habrophlebia_vibrans\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0028822\", \"latin_name_ref\": \"Parallelia bistriaris\", \"latin_name\": \"Parallelia_bistriaris\"}, {\"common_name\": \"Eastern Phoebe\", \"irma_id\": \"0035651\", \"latin_name_ref\": \"Sayornis phoebe\", \"latin_name\": \"Sayornis_phoebe\"}, {\"common_name\": \"Canada Goldenrod\", \"irma_id\": \"0037360\", \"latin_name_ref\": \"Solidago altissima v altissima\", \"latin_name\": \"Solidago_altissima_v_altissima\"}, {\"common_name\": \"Saffron Shiner\", \"irma_id\": \"0026872\", \"latin_name_ref\": \"Notropis rubricroceus\", \"latin_name\": \"Notropis_rubricroceus\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0015658\", \"latin_name_ref\": \"Euparthenos nubilis\", \"latin_name\": \"Euparthenos_nubilis\"}, {\"common_name\": \"Common Waterstrider\", \"irma_id\": \"0003130\", \"latin_name_ref\": \"Aquarius remigis\", \"latin_name\": \"Aquarius_remigis\"}, {\"common_name\": \"Carolina Flat-Headed Mayfly\", \"irma_id\": \"0038012\", \"latin_name_ref\": \"Stenacron carolina\", \"latin_name\": \"Stenacron_carolina\"}, {\"common_name\": \"Fraser Fir\", \"irma_id\": \"0000214\", \"latin_name_ref\": \"Abies fraseri\", \"latin_name\": \"Abies_fraseri\"}, {\"common_name\": \"Panicled-Leaf Tick-Trefoil\", \"irma_id\": \"0011906\", \"latin_name_ref\": \"Desmodium paniculatum v paniculatum\", \"latin_name\": \"Desmodium_paniculatum_v_paniculatum\"}, {\"common_name\": \"Fire-Pink\", \"irma_id\": \"0037000\", \"latin_name_ref\": \"Silene virginica\", \"latin_name\": \"Silene_virginica\"}, {\"common_name\": \"Irrorate Retreat-Maker\", \"irma_id\": \"0003632\", \"latin_name_ref\": \"Arctopsyche irrorata\", \"latin_name\": \"Arctopsyche_irrorata\"}, {\"common_name\": \"Box-Elder  \", \"irma_id\": \"0000330\", \"latin_name_ref\": \"Acer negundo\", \"latin_name\": \"Acer_negundo\"}, {\"common_name\": \"Yellow Birch\", \"irma_id\": \"0004764\", \"latin_name_ref\": \"Betula alleghaniensis v alleghaniensis\", \"latin_name\": \"Betula_alleghaniensis_v_alleghaniensis\"}, {\"common_name\": \"Fawn Darner\", \"irma_id\": \"0005496\", \"latin_name_ref\": \"Boyeria vinosa\", \"latin_name\": \"Boyeria_vinosa\"}, {\"common_name\": \"Eastern Least Clubtail\", \"irma_id\": \"0038904\", \"latin_name_ref\": \"Stylogomphus albistylus\", \"latin_name\": \"Stylogomphus_albistylus\"}, {\"common_name\": \"American Robin\", \"irma_id\": \"0041473\", \"latin_name_ref\": \"Turdus migratorius\", \"latin_name\": \"Turdus_migratorius\"}, {\"common_name\": \"American Mountain-Ash\", \"irma_id\": \"0037447\", \"latin_name_ref\": \"Sorbus americana\", \"latin_name\": \"Sorbus_americana\"}, {\"common_name\": \"Longtail Salamander\", \"irma_id\": \"0014739\", \"latin_name_ref\": \"Eurycea longicauda\", \"latin_name\": \"Eurycea_longicauda\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0031998\", \"latin_name_ref\": \"Polia detracta\", \"latin_name\": \"Polia_detracta\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0042743\", \"latin_name_ref\": \"Xestia dolosa\", \"latin_name\": \"Xestia_dolosa\"}, {\"common_name\": \"Black Willow\", \"irma_id\": \"0033170\", \"latin_name_ref\": \"Salix nigra\", \"latin_name\": \"Salix_nigra\"}, {\"common_name\": \"Meadow-Parsnip\", \"irma_id\": \"0038612\", \"latin_name_ref\": \"Thaspium trifoliatum variety\", \"latin_name\": \"Thaspium_trifoliatum_variety\"}, {\"common_name\": \"Little White Lichen Moth \", \"irma_id\": \"0009033\", \"latin_name_ref\": \"Clemensia albata\", \"latin_name\": \"Clemensia_albata\"}, {\"common_name\": \"Wavy-Lined Heterocampa \", \"irma_id\": \"0017649\", \"latin_name_ref\": \"Heterocampa biundata\", \"latin_name\": \"Heterocampa_biundata\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0023782\", \"latin_name_ref\": \"Macrurocampa marthesia\", \"latin_name\": \"Macrurocampa_marthesia\"}, {\"common_name\": \"Mountain Millstone\", \"irma_id\": \"0025486\", \"latin_name_ref\": \"Molanna blenda\", \"latin_name\": \"Molanna_blenda\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0027737\", \"latin_name_ref\": \"Orgyia definita\", \"latin_name\": \"Orgyia_definita\"}, {\"common_name\": \"Rearhumped Caterpillar\", \"irma_id\": \"0001905\", \"latin_name_ref\": \"Amphipyra pyramidoides\", \"latin_name\": \"Amphipyra_pyramidoides\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0031754\", \"latin_name_ref\": \"Plathypena scabra\", \"latin_name\": \"Plathypena_scabra\"}, {\"common_name\": \"Wingstem\", \"irma_id\": \"0042151\", \"latin_name_ref\": \"Verbesina alternifolia\", \"latin_name\": \"Verbesina_alternifolia\"}, {\"common_name\": \"Swan\\\\u2019S Sedge\", \"irma_id\": \"0007083\", \"latin_name_ref\": \"Carex swanii\", \"latin_name\": \"Carex_swanii\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0018166\", \"latin_name_ref\": \"Habrosyne scripta\", \"latin_name\": \"Habrosyne_scripta\"}, {\"common_name\": \"Dragonhunter\", \"irma_id\": \"0018211\", \"latin_name_ref\": \"Hagenius brevistylus\", \"latin_name\": \"Hagenius_brevistylus\"}, {\"common_name\": \"Ashy Fingernet Caddis\", \"irma_id\": \"0032047\", \"latin_name_ref\": \"Polycentropus cinereus\", \"latin_name\": \"Polycentropus_cinereus\"}, {\"common_name\": \"False Underwing Moth\", \"irma_id\": \"0001488\", \"latin_name_ref\": \"Allotria elonympha\", \"latin_name\": \"Allotria_elonympha\"}, {\"common_name\": \"Eastern Tailed Blue\", \"irma_id\": \"0016195\", \"latin_name_ref\": \"Everes comyntas\", \"latin_name\": \"Everes_comyntas\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0028557\", \"latin_name_ref\": \"Panopoda rufimargo\", \"latin_name\": \"Panopoda_rufimargo\"}, {\"common_name\": \"Black-Bordered Lemon Moth\", \"irma_id\": \"0039945\", \"latin_name_ref\": \"Thioptera nigrofimbria\", \"latin_name\": \"Thioptera_nigrofimbria\"}, {\"common_name\": \"Five-Lined Skink\", \"irma_id\": \"0015537\", \"latin_name_ref\": \"Eumeces fasciatus\", \"latin_name\": \"Eumeces_fasciatus\"}, {\"common_name\": \"Filmy Angelica\", \"irma_id\": \"0002283\", \"latin_name_ref\": \"Angelica triquinata\", \"latin_name\": \"Angelica_triquinata\"}, {\"common_name\": \"Pagan Stickbait Caddis\", \"irma_id\": \"0034137\", \"latin_name_ref\": \"Pycnopsyche gentilis\", \"latin_name\": \"Pycnopsyche_gentilis\"}, {\"common_name\": \"Brainy Slime Mold\", \"irma_id\": \"0003658\", \"latin_name_ref\": \"Arcyria cinerea\", \"latin_name\": \"Arcyria_cinerea\"}, {\"common_name\": \"Orange Sulphur\", \"irma_id\": \"0008295\", \"latin_name_ref\": \"Colias eurytheme\", \"latin_name\": \"Colias_eurytheme\"}, {\"common_name\": \"Macleod`S Retreat-Maker\", \"irma_id\": \"0019941\", \"latin_name_ref\": \"Hydropsyche macleodi\", \"latin_name\": \"Hydropsyche_macleodi\"}, {\"common_name\": \"Ant\", \"irma_id\": \"0002845\", \"latin_name_ref\": \"Aphaenogaster rudis\", \"latin_name\": \"Aphaenogaster_rudis\"}, {\"common_name\": \"Deer Mouse\", \"irma_id\": \"0029882\", \"latin_name_ref\": \"Peromyscus maniculatus\", \"latin_name\": \"Peromyscus_maniculatus\"}, {\"common_name\": \"Intermediate Water Bear\", \"irma_id\": \"0025351\", \"latin_name_ref\": \"Minibiotus intermedius\", \"latin_name\": \"Minibiotus_intermedius\"}, {\"common_name\": \"Pallar`S Water Bear\", \"irma_id\": \"0023679\", \"latin_name_ref\": \"Macrobiotus pallarii\", \"latin_name\": \"Macrobiotus_pallarii\"}, {\"common_name\": \"Waterbear\", \"irma_id\": \"0033488\", \"latin_name_ref\": \"Pseudechiniscus suillus group\", \"latin_name\": \"Pseudechiniscus_suillus_group\"}, {\"common_name\": \"Ovate Dagger Moth\", \"irma_id\": \"0000749\", \"latin_name_ref\": \"Acronicta ovata\", \"latin_name\": \"Acronicta_ovata\"}, {\"common_name\": \"Spotted Apatelodes\", \"irma_id\": \"0002822\", \"latin_name_ref\": \"Apatelodes torrefacta\", \"latin_name\": \"Apatelodes_torrefacta\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0034754\", \"latin_name_ref\": \"Renia discoloralis\", \"latin_name\": \"Renia_discoloralis\"}, {\"common_name\": \"Unmarked Dagger Moth\", \"irma_id\": \"0000732\", \"latin_name_ref\": \"Acronicta innotata\", \"latin_name\": \"Acronicta_innotata\"}, {\"common_name\": \"Summer Azure\", \"irma_id\": \"0007506\", \"latin_name_ref\": \"Celastrina neglecta\", \"latin_name\": \"Celastrina_neglecta\"}, {\"common_name\": \"Fringed Looper\", \"irma_id\": \"0005273\", \"latin_name_ref\": \"Campaea perlata\", \"latin_name\": \"Campaea_perlata\"}, {\"common_name\": \"Rosy Maple Moth \", \"irma_id\": \"0013006\", \"latin_name_ref\": \"Dryocampa rubicunda\", \"latin_name\": \"Dryocampa_rubicunda\"}, {\"common_name\": \"Leconte`S Haploa\", \"irma_id\": \"0018325\", \"latin_name_ref\": \"Haploa lecontei\", \"latin_name\": \"Haploa_lecontei\"}, {\"common_name\": \"Masked Birch Caterpillar\", \"irma_id\": \"0012878\", \"latin_name_ref\": \"Drepana arcuata\", \"latin_name\": \"Drepana_arcuata\"}, {\"common_name\": \"Blunt-Leaf Waterleaf\", \"irma_id\": \"0019900\", \"latin_name_ref\": \"Hydrophyllum canadense\", \"latin_name\": \"Hydrophyllum_canadense\"}, {\"common_name\": \"Canadian Melanolophia\", \"irma_id\": \"0024094\", \"latin_name_ref\": \"Melanolophia canadaria\", \"latin_name\": \"Melanolophia_canadaria\"}, {\"common_name\": \"Scarlet-Winged Lichen Moth \", \"irma_id\": \"0020486\", \"latin_name_ref\": \"Hypoprepia miniata\", \"latin_name\": \"Hypoprepia_miniata\"}, {\"common_name\": \"Fir Harlequin\", \"irma_id\": \"0013358\", \"latin_name_ref\": \"Elaphria versicolor\", \"latin_name\": \"Elaphria_versicolor\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0033729\", \"latin_name_ref\": \"Pseudothyatira cymatophoroides\", \"latin_name\": \"Pseudothyatira_cymatophoroides\"}, {\"common_name\": \"Bowed Eunotia Diatom\", \"irma_id\": \"0015628\", \"latin_name_ref\": \"Eunotia subarcuatoides\", \"latin_name\": \"Eunotia_subarcuatoides\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0029753\", \"latin_name_ref\": \"Peridea angulosa\", \"latin_name\": \"Peridea_angulosa\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0028617\", \"latin_name_ref\": \"Paonias excaecatus\", \"latin_name\": \"Paonias_excaecatus\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0014125\", \"latin_name_ref\": \"Epimecis hortaria\", \"latin_name\": \"Epimecis_hortaria\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0020253\", \"latin_name_ref\": \"Hypagyrtis unipunctata\", \"latin_name\": \"Hypagyrtis_unipunctata\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0027849\", \"latin_name_ref\": \"Orthodes cynica\", \"latin_name\": \"Orthodes_cynica\"}, {\"common_name\": \"Pluto`S Small Minnow Mayfly\", \"irma_id\": \"0003451\", \"latin_name_ref\": \"Baetis pluto\", \"latin_name\": \"Baetis_pluto\"}, {\"common_name\": \"Greater Bladder Sedge\", \"irma_id\": \"0007034\", \"latin_name_ref\": \"Carex intumescens\", \"latin_name\": \"Carex_intumescens\"}, {\"common_name\": \"Mountain Wood Fern\", \"irma_id\": \"0013025\", \"latin_name_ref\": \"Dryopteris campyloptera\", \"latin_name\": \"Dryopteris_campyloptera\"}, {\"common_name\": \"Recurved Brotherella Moss\", \"irma_id\": \"0005702\", \"latin_name_ref\": \"Brotherella recurvans\", \"latin_name\": \"Brotherella_recurvans\"}, {\"common_name\": \"Harmsworth`S Water Bear\", \"irma_id\": \"0023669\", \"latin_name_ref\": \"Macrobiotus harmsworthi\", \"latin_name\": \"Macrobiotus_harmsworthi\"}, {\"common_name\": \"Narrow Riffle Beetle\", \"irma_id\": \"0032780\", \"latin_name_ref\": \"Promoresia tardella\", \"latin_name\": \"Promoresia_tardella\"}, {\"common_name\": \"Barred Owl\", \"irma_id\": \"0038526\", \"latin_name_ref\": \"Strix varia\", \"latin_name\": \"Strix_varia\"}, {\"common_name\": \"Incised Eunotia Diatom\", \"irma_id\": \"0015588\", \"latin_name_ref\": \"Eunotia incisa\", \"latin_name\": \"Eunotia_incisa\"}, {\"common_name\": \"Pepper And Salt Geometer\", \"irma_id\": \"0004848\", \"latin_name_ref\": \"Biston betularia\", \"latin_name\": \"Biston_betularia\"}, {\"common_name\": \"Bent-Lined Gray\", \"irma_id\": \"0019575\", \"latin_name_ref\": \"Iridopsis larvaria\", \"latin_name\": \"Iridopsis_larvaria\"}, {\"common_name\": \"Catawba Rhododendron\", \"irma_id\": \"0035062\", \"latin_name_ref\": \"Rhododendron catawbiense\", \"latin_name\": \"Rhododendron_catawbiense\"}, {\"common_name\": \"Appalachian Bunchflower\", \"irma_id\": \"0024157\", \"latin_name_ref\": \"Melanthium parviflorum\", \"latin_name\": \"Melanthium_parviflorum\"}, {\"common_name\": \"American Umbrella-Leaf\", \"irma_id\": \"0011386\", \"latin_name_ref\": \"Diphylleia cymosa\", \"latin_name\": \"Diphylleia_cymosa\"}, {\"common_name\": \"Grove Blue Grass\", \"irma_id\": \"0031856\", \"latin_name_ref\": \"Poa alsodes\", \"latin_name\": \"Poa_alsodes\"}, {\"common_name\": \"Upland Bent\", \"irma_id\": \"0001184\", \"latin_name_ref\": \"Agrostis perennans\", \"latin_name\": \"Agrostis_perennans\"}, {\"common_name\": \"Waterbear\", \"irma_id\": \"0023676\", \"latin_name_ref\": \"Macrobiotus martini\", \"latin_name\": \"Macrobiotus_martini\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0032663\", \"latin_name_ref\": \"Probole amicaria\", \"latin_name\": \"Probole_amicaria\"}, {\"common_name\": \"Running Strawberry-Bush\", \"irma_id\": \"0015648\", \"latin_name_ref\": \"Euonymus obovatus\", \"latin_name\": \"Euonymus_obovatus\"}, {\"common_name\": \"Appalachian Joe-Pye-Weed\", \"irma_id\": \"0015700\", \"latin_name_ref\": \"Eupatorium steelei\", \"latin_name\": \"Eupatorium_steelei\"}, {\"common_name\": \"Two-Tailed Flat-Headed Mayfly\", \"irma_id\": \"0013930\", \"latin_name_ref\": \"Epeorus pleuralis\", \"latin_name\": \"Epeorus_pleuralis\"}, {\"common_name\": \"Fragile Dagger\", \"irma_id\": \"0000718\", \"latin_name_ref\": \"Acronicta fragilis\", \"latin_name\": \"Acronicta_fragilis\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0025712\", \"latin_name_ref\": \"Morrisonia latex\", \"latin_name\": \"Morrisonia_latex\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0030728\", \"latin_name_ref\": \"Phlogophora periculosa\", \"latin_name\": \"Phlogophora_periculosa\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0033681\", \"latin_name_ref\": \"Pseudorthodes vecors\", \"latin_name\": \"Pseudorthodes_vecors\"}, {\"common_name\": \"Michaux\\\\u2019S Saxifrage\", \"irma_id\": \"0035645\", \"latin_name_ref\": \"Saxifraga michauxii\", \"latin_name\": \"Saxifraga_michauxii\"}, {\"common_name\": \"Small Enchanter\\\\u2019S-Nightshade\", \"irma_id\": \"0008764\", \"latin_name_ref\": \"Circaea alpina alpina\", \"latin_name\": \"Circaea_alpina_alpina\"}, {\"common_name\": \"Black Elder\", \"irma_id\": \"0033189\", \"latin_name_ref\": \"Sambucus nigra canadensis\", \"latin_name\": \"Sambucus_nigra_canadensis\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0020553\", \"latin_name_ref\": \"Hypsibius convergens\", \"latin_name\": \"Hypsibius_convergens\"}, {\"common_name\": \"Possomhaw\", \"irma_id\": \"0042276\", \"latin_name_ref\": \"Viburnum nudum v cassinoides\", \"latin_name\": \"Viburnum_nudum_v_cassinoides\"}, {\"common_name\": \"Waterbear\", \"irma_id\": \"0028830\", \"latin_name_ref\": \"Paramacrobiotus tonollii\", \"latin_name\": \"Paramacrobiotus_tonollii\"}, {\"common_name\": \"Mountain Meadow-Rue\", \"irma_id\": \"0039927\", \"latin_name_ref\": \"Thalictrum clavatum\", \"latin_name\": \"Thalictrum_clavatum\"}, {\"common_name\": \"Skunk Goldenrod \", \"irma_id\": \"0037379\", \"latin_name_ref\": \"Solidago glomerata\", \"latin_name\": \"Solidago_glomerata\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0020645\", \"latin_name_ref\": \"Idia aemula\", \"latin_name\": \"Idia_aemula\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0036014\", \"latin_name_ref\": \"Scopula limboundata\", \"latin_name\": \"Scopula_limboundata\"}, {\"common_name\": \"Whorled Nodding-Aster\", \"irma_id\": \"0027041\", \"latin_name_ref\": \"Oclemena acuminata\", \"latin_name\": \"Oclemena_acuminata\"}, {\"common_name\": \"Swainson\\'S Thrush\", \"irma_id\": \"0007287\", \"latin_name_ref\": \"Catharus ustulatus\", \"latin_name\": \"Catharus_ustulatus\"}, {\"common_name\": \"Mountain Wood-Aster\", \"irma_id\": \"0014724\", \"latin_name_ref\": \"Eurybia chlorolepis\", \"latin_name\": \"Eurybia_chlorolepis\"}, {\"common_name\": \"Red Elderberry\", \"irma_id\": \"0033192\", \"latin_name_ref\": \"Sambucus racemosa v racemosa\", \"latin_name\": \"Sambucus_racemosa_v_racemosa\"}, {\"common_name\": \"Pine Siskin\", \"irma_id\": \"0037888\", \"latin_name_ref\": \"Spinus pinus\", \"latin_name\": \"Spinus_pinus\"}, {\"common_name\": \"Minor Eunotia Diatom\", \"irma_id\": \"0015599\", \"latin_name_ref\": \"Eunotia minor\", \"latin_name\": \"Eunotia_minor\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0004143\", \"latin_name_ref\": \"Astatumen trinacriae\", \"latin_name\": \"Astatumen_trinacriae\"}, {\"common_name\": \"Beautiful Stone\", \"irma_id\": \"0028753\", \"latin_name_ref\": \"Paragnetina immarginata\", \"latin_name\": \"Paragnetina_immarginata\"}, {\"common_name\": \"Saddleback Looper\", \"irma_id\": \"0013229\", \"latin_name_ref\": \"Ectropis crepuscularia\", \"latin_name\": \"Ectropis_crepuscularia\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0011887\", \"latin_name_ref\": \"Desmia funeralis\", \"latin_name\": \"Desmia_funeralis\"}, {\"common_name\": \"Great Spangled Fritillary\", \"irma_id\": \"0037712\", \"latin_name_ref\": \"Speyeria cybele\", \"latin_name\": \"Speyeria_cybele\"}, {\"common_name\": \"Red Admiral\", \"irma_id\": \"0042065\", \"latin_name_ref\": \"Vanessa atalanta\", \"latin_name\": \"Vanessa_atalanta\"}, {\"common_name\": \"Baltimore Bomolocha Moth\", \"irma_id\": \"0005151\", \"latin_name_ref\": \"Bomolocha baltimoralis\", \"latin_name\": \"Bomolocha_baltimoralis\"}, {\"common_name\": \"Yellow Poplar Weevil\", \"irma_id\": \"0027121\", \"latin_name_ref\": \"Odontopus calceatus\", \"latin_name\": \"Odontopus_calceatus\"}, {\"common_name\": \"Spotted Touch-Me-Not\", \"irma_id\": \"0020719\", \"latin_name_ref\": \"Impatiens capensis\", \"latin_name\": \"Impatiens_capensis\"}, {\"common_name\": \"Ornate Dogfaced Caddis\", \"irma_id\": \"0026374\", \"latin_name_ref\": \"Neophylax ornatus\", \"latin_name\": \"Neophylax_ornatus\"}, {\"common_name\": \"Red-Winged Blackbird\", \"irma_id\": \"0000957\", \"latin_name_ref\": \"Agelaius phoeniceus\", \"latin_name\": \"Agelaius_phoeniceus\"}, {\"common_name\": \"Oval Riffle Beetle\", \"irma_id\": \"0027649\", \"latin_name_ref\": \"Optioservus ovalis\", \"latin_name\": \"Optioservus_ovalis\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0033418\", \"latin_name_ref\": \"Pseudaletia unipuncta\", \"latin_name\": \"Pseudaletia_unipuncta\"}, {\"common_name\": \"Red-Twig Doghobble\", \"irma_id\": \"0022462\", \"latin_name_ref\": \"Leucothoe recurva\", \"latin_name\": \"Leucothoe_recurva\"}, {\"common_name\": \"Winter Ant\", \"irma_id\": \"0032556\", \"latin_name_ref\": \"Prenolepis imparis\", \"latin_name\": \"Prenolepis_imparis\"}, {\"common_name\": \"Girlfriend Underwing Moth\", \"irma_id\": \"0007317\", \"latin_name_ref\": \"Catocala amica\", \"latin_name\": \"Catocala_amica\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0015959\", \"latin_name_ref\": \"Eutrapela clemataria\", \"latin_name\": \"Eutrapela_clemataria\"}, {\"common_name\": \"Hesitant Dagger Moth\", \"irma_id\": \"0000722\", \"latin_name_ref\": \"Acronicta haesitata\", \"latin_name\": \"Acronicta_haesitata\"}, {\"common_name\": \"Io Moth \", \"irma_id\": \"0003178\", \"latin_name_ref\": \"Automeris io\", \"latin_name\": \"Automeris_io\"}, {\"common_name\": \"Lesser Grapevine Looper Moth\", \"irma_id\": \"0015510\", \"latin_name_ref\": \"Eulithis diversilineata\", \"latin_name\": \"Eulithis_diversilineata\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0040585\", \"latin_name_ref\": \"Zanclognatha laevigata\", \"latin_name\": \"Zanclognatha_laevigata\"}, {\"common_name\": \"Crayfish\", \"irma_id\": \"0005201\", \"latin_name_ref\": \"Cambarus Hiaticambarus longirostris\", \"latin_name\": \"Cambarus_Hiaticambarus_longirostris\"}, {\"common_name\": \"Appalachian False Goat\\\\u2019S-Beard\", \"irma_id\": \"0004198\", \"latin_name_ref\": \"Astilbe biternata\", \"latin_name\": \"Astilbe_biternata\"}, {\"common_name\": \"Tiny Riffle Beetle\", \"irma_id\": \"0028166\", \"latin_name_ref\": \"Oulimnius latiusculus\", \"latin_name\": \"Oulimnius_latiusculus\"}, {\"common_name\": \"American-Bellflower\", \"irma_id\": \"0005277\", \"latin_name_ref\": \"Campanulastrum americanum\", \"latin_name\": \"Campanulastrum_americanum\"}, {\"common_name\": \"Broad Loose-Flower Sedge\", \"irma_id\": \"0007042\", \"latin_name_ref\": \"Carex laxiflora v laxiflora\", \"latin_name\": \"Carex_laxiflora_v_laxiflora\"}, {\"common_name\": \"Yellow-Faced Non-Biting Midge\", \"irma_id\": \"0005666\", \"latin_name_ref\": \"Brillia flavifrons\", \"latin_name\": \"Brillia_flavifrons\"}, {\"common_name\": \"American Mite Eating Ant\", \"irma_id\": \"0024621\", \"latin_name_ref\": \"Myrmecina americana\", \"latin_name\": \"Myrmecina_americana\"}, {\"common_name\": \"Diatom\", \"irma_id\": \"0015602\", \"latin_name_ref\": \"Eunotia muscicola v tridentula\", \"latin_name\": \"Eunotia_muscicola_v_tridentula\"}, {\"common_name\": \"Meager Enotia Diatom\", \"irma_id\": \"0015580\", \"latin_name_ref\": \"Eunotia exigua\", \"latin_name\": \"Eunotia_exigua\"}, {\"common_name\": \"Maculate Fingernet Caddis\", \"irma_id\": \"0032055\", \"latin_name_ref\": \"Polycentropus maculatus\", \"latin_name\": \"Polycentropus_maculatus\"}, {\"common_name\": \"Silly Stickbait Caddis\", \"irma_id\": \"0034149\", \"latin_name_ref\": \"Pycnopsyche sonso\", \"latin_name\": \"Pycnopsyche_sonso\"}, {\"common_name\": \"Carolina Armored Mayfly\", \"irma_id\": \"0003467\", \"latin_name_ref\": \"Baetisca carolina\", \"latin_name\": \"Baetisca_carolina\"}, {\"common_name\": \"Twin-Spotted Spiketail\", \"irma_id\": \"0010050\", \"latin_name_ref\": \"Cordulegaster maculata\", \"latin_name\": \"Cordulegaster_maculata\"}, {\"common_name\": \"Flat-Headed Mayfly\", \"irma_id\": \"0013933\", \"latin_name_ref\": \"Epeorus rubidussubpallidus\", \"latin_name\": \"Epeorus_rubidussubpallidus\"}, {\"common_name\": \"Lamp Rush\", \"irma_id\": \"0021009\", \"latin_name_ref\": \"Juncus effusus v solutus\", \"latin_name\": \"Juncus_effusus_v_solutus\"}, {\"common_name\": \"Red Crossbill\", \"irma_id\": \"0023302\", \"latin_name_ref\": \"Loxia curvirostra\", \"latin_name\": \"Loxia_curvirostra\"}, {\"common_name\": \"Princess-Pine\", \"irma_id\": \"0023496\", \"latin_name_ref\": \"Lycopodium obscurum\", \"latin_name\": \"Lycopodium_obscurum\"}, {\"common_name\": \"Slender Wood-Reed\", \"irma_id\": \"0008748\", \"latin_name_ref\": \"Cinna latifolia\", \"latin_name\": \"Cinna_latifolia\"}, {\"common_name\": \"Unclear Dagger Moth\", \"irma_id\": \"0000730\", \"latin_name_ref\": \"Acronicta inclara\", \"latin_name\": \"Acronicta_inclara\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0011610\", \"latin_name_ref\": \"Dasychira obliquata\", \"latin_name\": \"Dasychira_obliquata\"}, {\"common_name\": \"Flat-Headed Mayfly A5\", \"irma_id\": \"0022474\", \"latin_name_ref\": \"Leucrocuta thetis\", \"latin_name\": \"Leucrocuta_thetis\"}, {\"common_name\": \"Bent-Winged Owlet\", \"irma_id\": \"0004940\", \"latin_name_ref\": \"Bleptina caradrinalis\", \"latin_name\": \"Bleptina_caradrinalis\"}, {\"common_name\": \"Closebanded Yellowhorn\", \"irma_id\": \"0009565\", \"latin_name_ref\": \"Colocasia propinquilinea\", \"latin_name\": \"Colocasia_propinquilinea\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0020285\", \"latin_name_ref\": \"Hypena scabra\", \"latin_name\": \"Hypena_scabra\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0023056\", \"latin_name_ref\": \"Lithacodia muscosula\", \"latin_name\": \"Lithacodia_muscosula\"}, {\"common_name\": \"Stenolophus Ground Beetle\", \"irma_id\": \"0038071\", \"latin_name_ref\": \"Stenolophus Stenolophus ochropezus\", \"latin_name\": \"Stenolophus_Stenolophus_ochropezus\"}, {\"common_name\": \"Plantain-Leaf Sedge\", \"irma_id\": \"0007063\", \"latin_name_ref\": \"Carex plantaginea\", \"latin_name\": \"Carex_plantaginea\"}, {\"common_name\": \"Pink-Shaded Fern Moth\", \"irma_id\": \"0006223\", \"latin_name_ref\": \"Callopistria mollissima\", \"latin_name\": \"Callopistria_mollissima\"}, {\"common_name\": \"Dusky Groundling Moth\", \"irma_id\": \"0009671\", \"latin_name_ref\": \"Condica vecors\", \"latin_name\": \"Condica_vecors\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0018939\", \"latin_name_ref\": \"Herpetogramma thestealis\", \"latin_name\": \"Herpetogramma_thestealis\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0017656\", \"latin_name_ref\": \"Heterocampa obliqua\", \"latin_name\": \"Heterocampa_obliqua\"}, {\"common_name\": \"Spotted Stickbait Caddisfly\", \"irma_id\": \"0034131\", \"latin_name_ref\": \"Pycnopsyche antica\", \"latin_name\": \"Pycnopsyche_antica\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0035979\", \"latin_name_ref\": \"Scoparia biplagialis\", \"latin_name\": \"Scoparia_biplagialis\"}, {\"common_name\": \"Smooth Sumac\", \"irma_id\": \"0035112\", \"latin_name_ref\": \"Rhus glabra\", \"latin_name\": \"Rhus_glabra\"}, {\"common_name\": \"Winged Elm\", \"irma_id\": \"0041634\", \"latin_name_ref\": \"Ulmus alata\", \"latin_name\": \"Ulmus_alata\"}, {\"common_name\": \"Ant B\", \"irma_id\": \"0032394\", \"latin_name_ref\": \"Ponera pennsylvanica\", \"latin_name\": \"Ponera_pennsylvanica\"}, {\"common_name\": \"Small Minnow Mayfly\", \"irma_id\": \"0000314\", \"latin_name_ref\": \"Acentrella ampla\", \"latin_name\": \"Acentrella_ampla\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0023607\", \"latin_name_ref\": \"Macaria fissinotata\", \"latin_name\": \"Macaria_fissinotata\"}, {\"common_name\": \"White-Footed Mouse\", \"irma_id\": \"0029881\", \"latin_name_ref\": \"Peromyscus leucopus\", \"latin_name\": \"Peromyscus_leucopus\"}, {\"common_name\": \"Carinate Antloving Rove Beetle\", \"irma_id\": \"0023647\", \"latin_name_ref\": \"Machaerodes carinatus\", \"latin_name\": \"Machaerodes_carinatus\"}, {\"common_name\": \"Oval-Based Prominent \", \"irma_id\": \"0029754\", \"latin_name_ref\": \"Peridea basitriens\", \"latin_name\": \"Peridea_basitriens\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0039821\", \"latin_name_ref\": \"Tetracis crocallata\", \"latin_name\": \"Tetracis_crocallata\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0040556\", \"latin_name_ref\": \"Zale minerea\", \"latin_name\": \"Zale_minerea\"}, {\"common_name\": \"Leconte`S Rove Beetle\", \"irma_id\": \"0019702\", \"latin_name_ref\": \"Ischnosoma lecontei\", \"latin_name\": \"Ischnosoma_lecontei\"}, {\"common_name\": \"Greenbrier Springfly\", \"irma_id\": \"0040519\", \"latin_name_ref\": \"Yugus bulbosus\", \"latin_name\": \"Yugus_bulbosus\"}, {\"common_name\": \"False Non-Biting Midge\", \"irma_id\": \"0032175\", \"latin_name_ref\": \"Polypedilum Polypedilum fallax\", \"latin_name\": \"Polypedilum_Polypedilum_fallax\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0013163\", \"latin_name_ref\": \"Echiniscus virginicus\", \"latin_name\": \"Echiniscus_virginicus\"}, {\"common_name\": \"Brownish Small Minnow Mayfly\", \"irma_id\": \"0003279\", \"latin_name_ref\": \"Baetis brunneicolor\", \"latin_name\": \"Baetis_brunneicolor\"}, {\"common_name\": \"American Plum\", \"irma_id\": \"0033000\", \"latin_name_ref\": \"Prunus americana\", \"latin_name\": \"Prunus_americana\"}, {\"common_name\": \"Luna Moth \", \"irma_id\": \"0000794\", \"latin_name_ref\": \"Actias luna\", \"latin_name\": \"Actias_luna\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0011649\", \"latin_name_ref\": \"Datana angusii\", \"latin_name\": \"Datana_angusii\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0032004\", \"latin_name_ref\": \"Polia nimbosa\", \"latin_name\": \"Polia_nimbosa\"}, {\"common_name\": \"Song Sparrow\", \"irma_id\": \"0024246\", \"latin_name_ref\": \"Melospiza melodia\", \"latin_name\": \"Melospiza_melodia\"}, {\"common_name\": \"Similar Antloving Rove Beetle\", \"irma_id\": \"0015987\", \"latin_name_ref\": \"Eutyphlus similis\", \"latin_name\": \"Eutyphlus_similis\"}, {\"common_name\": \"Dark Red Underwing\", \"irma_id\": \"0007418\", \"latin_name_ref\": \"Catocala ultronia\", \"latin_name\": \"Catocala_ultronia\"}, {\"common_name\": \"Imperial Moth \", \"irma_id\": \"0013109\", \"latin_name_ref\": \"Eacles imperialis\", \"latin_name\": \"Eacles_imperialis\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0015135\", \"latin_name_ref\": \"Euchlaena amoenaria\", \"latin_name\": \"Euchlaena_amoenaria\"}, {\"common_name\": \"Buckeye\", \"irma_id\": \"0021184\", \"latin_name_ref\": \"Junonia coenia\", \"latin_name\": \"Junonia_coenia\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0034327\", \"latin_name_ref\": \"Pyrrhia exprimens\", \"latin_name\": \"Pyrrhia_exprimens\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0028554\", \"latin_name_ref\": \"Panopoda carneicosta\", \"latin_name\": \"Panopoda_carneicosta\"}, {\"common_name\": \"Locust Leaf Miner\", \"irma_id\": \"0027127\", \"latin_name_ref\": \"Odontota dorsalis\", \"latin_name\": \"Odontota_dorsalis\"}, {\"common_name\": \"Undulated Eunotia Diatom\", \"irma_id\": \"0015636\", \"latin_name_ref\": \"Eunotia varioundulata\", \"latin_name\": \"Eunotia_varioundulata\"}, {\"common_name\": \"Creeping Cedar\", \"irma_id\": \"0011381\", \"latin_name_ref\": \"Diphasiastrum digitatum\", \"latin_name\": \"Diphasiastrum_digitatum\"}, {\"common_name\": \"Spiny Oakworm Moth\", \"irma_id\": \"0002364\", \"latin_name_ref\": \"Anisota stigma\", \"latin_name\": \"Anisota_stigma\"}, {\"common_name\": \"Carolina Satyr\", \"irma_id\": \"0018926\", \"latin_name_ref\": \"Hermeuptychia sosybius\", \"latin_name\": \"Hermeuptychia_sosybius\"}, {\"common_name\": \"Andromeda Underwing\", \"irma_id\": \"0007319\", \"latin_name_ref\": \"Catocala andromedae\", \"latin_name\": \"Catocala_andromedae\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0015873\", \"latin_name_ref\": \"Eupithecia miserulata\", \"latin_name\": \"Eupithecia_miserulata\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0023193\", \"latin_name_ref\": \"Lochmaeus manteo\", \"latin_name\": \"Lochmaeus_manteo\"}, {\"common_name\": \"Morrison\\'S Pero\", \"irma_id\": \"0029870\", \"latin_name_ref\": \"Pero morrisonaria\", \"latin_name\": \"Pero_morrisonaria\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0035814\", \"latin_name_ref\": \"Schizura leptinoides\", \"latin_name\": \"Schizura_leptinoides\"}, {\"common_name\": \"Tallulah Falls Antloving Rove Beetle\", \"irma_id\": \"0037441\", \"latin_name_ref\": \"Sonoma tolulae\", \"latin_name\": \"Sonoma_tolulae\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0023047\", \"latin_name_ref\": \"Lithacodes fasciola\", \"latin_name\": \"Lithacodes_fasciola\"}, {\"common_name\": \"Satchem\", \"irma_id\": \"0004288\", \"latin_name_ref\": \"Atalopedes campestris\", \"latin_name\": \"Atalopedes_campestris\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0015074\", \"latin_name_ref\": \"Eubaphe mendica\", \"latin_name\": \"Eubaphe_mendica\"}, {\"common_name\": \"Morbid Owlet Moth\", \"irma_id\": \"0008582\", \"latin_name_ref\": \"Chytolita morbidalis\", \"latin_name\": \"Chytolita_morbidalis\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0018935\", \"latin_name_ref\": \"Herpetogramma pertextalis\", \"latin_name\": \"Herpetogramma_pertextalis\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0023596\", \"latin_name_ref\": \"Lytrosis unitaria\", \"latin_name\": \"Lytrosis_unitaria\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0034225\", \"latin_name_ref\": \"Pyrausta acrionalis\", \"latin_name\": \"Pyrausta_acrionalis\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0041904\", \"latin_name_ref\": \"Urola nivalis\", \"latin_name\": \"Urola_nivalis\"}, {\"common_name\": \"Trumpetweed\", \"irma_id\": \"0015686\", \"latin_name_ref\": \"Eupatorium fistulosum\", \"latin_name\": \"Eupatorium_fistulosum\"}, {\"common_name\": \"Silky Willow\", \"irma_id\": \"0033171\", \"latin_name_ref\": \"Salix sericea\", \"latin_name\": \"Salix_sericea\"}, {\"common_name\": \"Lead-Colored Lichen Moth \", \"irma_id\": \"0008810\", \"latin_name_ref\": \"Cisthene plumbea\", \"latin_name\": \"Cisthene_plumbea\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0011653\", \"latin_name_ref\": \"Datana drexelii\", \"latin_name\": \"Datana_drexelii\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0011225\", \"latin_name_ref\": \"Digrammia ocellinata\", \"latin_name\": \"Digrammia_ocellinata\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0028604\", \"latin_name_ref\": \"Pantographa limata\", \"latin_name\": \"Pantographa_limata\"}, {\"common_name\": \"Spring Peeper\", \"irma_id\": \"0033408\", \"latin_name_ref\": \"Pseudacris crucifer\", \"latin_name\": \"Pseudacris_crucifer\"}, {\"common_name\": \"White Avens\", \"irma_id\": \"0017163\", \"latin_name_ref\": \"Geum canadense\", \"latin_name\": \"Geum_canadense\"}, {\"common_name\": \"Rosyside Dace\", \"irma_id\": \"0009080\", \"latin_name_ref\": \"Clinostomus funduloides\", \"latin_name\": \"Clinostomus_funduloides\"}, {\"common_name\": \"Yellow Non-Biting Midge\", \"irma_id\": \"0010722\", \"latin_name_ref\": \"Cryptochironomus fulvus\", \"latin_name\": \"Cryptochironomus_fulvus\"}, {\"common_name\": \"Black Cutworm\", \"irma_id\": \"0001200\", \"latin_name_ref\": \"Agrotis ipsilon\", \"latin_name\": \"Agrotis_ipsilon\"}, {\"common_name\": \"Spruce Harlequin\", \"irma_id\": \"0028461\", \"latin_name_ref\": \"Palthis angulalis\", \"latin_name\": \"Palthis_angulalis\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0028462\", \"latin_name_ref\": \"Palthis asopialis\", \"latin_name\": \"Palthis_asopialis\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0032679\", \"latin_name_ref\": \"Prochoerodes lineola\", \"latin_name\": \"Prochoerodes_lineola\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0041610\", \"latin_name_ref\": \"Udea rubigalis\", \"latin_name\": \"Udea_rubigalis\"}, {\"common_name\": \"Welsh Wave\", \"irma_id\": \"0042133\", \"latin_name_ref\": \"Venusia cambrica\", \"latin_name\": \"Venusia_cambrica\"}, {\"common_name\": \"Pale Lichen Moth \", \"irma_id\": \"0010383\", \"latin_name_ref\": \"Crambidia pallida\", \"latin_name\": \"Crambidia_pallida\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0010390\", \"latin_name_ref\": \"Crambus agitatellus\", \"latin_name\": \"Crambus_agitatellus\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0028456\", \"latin_name_ref\": \"Palpita magniferalis\", \"latin_name\": \"Palpita_magniferalis\"}, {\"common_name\": \"Small-Eyed Sphinx \", \"irma_id\": \"0028618\", \"latin_name_ref\": \"Paonias myops\", \"latin_name\": \"Paonias_myops\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0030051\", \"latin_name_ref\": \"Phalaenostola larentioides\", \"latin_name\": \"Phalaenostola_larentioides\"}, {\"common_name\": \"Gilt Darter\", \"irma_id\": \"0029719\", \"latin_name_ref\": \"Percina evides\", \"latin_name\": \"Percina_evides\"}, {\"common_name\": \"Cypress Rosette Grass\", \"irma_id\": \"0012108\", \"latin_name_ref\": \"Dichanthelium dichotomum v dichotomum\", \"latin_name\": \"Dichanthelium_dichotomum_v_dichotomum\"}, {\"common_name\": \"Nondescript Dagger Moth\", \"irma_id\": \"0000762\", \"latin_name_ref\": \"Acronicta spinigera\", \"latin_name\": \"Acronicta_spinigera\"}, {\"common_name\": \"White-Blotched Balsa\", \"irma_id\": \"0003527\", \"latin_name_ref\": \"Balsa labecula\", \"latin_name\": \"Balsa_labecula\"}, {\"common_name\": \"Gray Spruce Looper\", \"irma_id\": \"0007101\", \"latin_name_ref\": \"Caripeta divisata\", \"latin_name\": \"Caripeta_divisata\"}, {\"common_name\": \"Cloaked Marvel Moth\", \"irma_id\": \"0008585\", \"latin_name_ref\": \"Chytonix palliatricula\", \"latin_name\": \"Chytonix_palliatricula\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0015876\", \"latin_name_ref\": \"Eusarca confusaria\", \"latin_name\": \"Eusarca_confusaria\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0031681\", \"latin_name_ref\": \"Plagodis fervidaria\", \"latin_name\": \"Plagodis_fervidaria\"}, {\"common_name\": \"Arrow-Leaf Tearthumb\", \"irma_id\": \"0032107\", \"latin_name_ref\": \"Polygonum sagittatum\", \"latin_name\": \"Polygonum_sagittatum\"}, {\"common_name\": \"The Slowpoke\", \"irma_id\": \"0002491\", \"latin_name_ref\": \"Anorthodes tarda\", \"latin_name\": \"Anorthodes_tarda\"}, {\"common_name\": \"Polyphemus Moth\", \"irma_id\": \"0002550\", \"latin_name_ref\": \"Antheraea polyphemus\", \"latin_name\": \"Antheraea_polyphemus\"}, {\"common_name\": \"Eyed Baileya\", \"irma_id\": \"0003511\", \"latin_name_ref\": \"Baileya ophthalmica\", \"latin_name\": \"Baileya_ophthalmica\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0013417\", \"latin_name_ref\": \"Ellida caniplaga\", \"latin_name\": \"Ellida_caniplaga\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0026120\", \"latin_name_ref\": \"Nemoria bistriaria\", \"latin_name\": \"Nemoria_bistriaria\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0031680\", \"latin_name_ref\": \"Plagodis alcoolaria\", \"latin_name\": \"Plagodis_alcoolaria\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0032939\", \"latin_name_ref\": \"Protoboarmia porcelaria\", \"latin_name\": \"Protoboarmia_porcelaria\"}, {\"common_name\": \"Banded Woollybear\", \"irma_id\": \"0034325\", \"latin_name_ref\": \"Pyrrharctia isabella\", \"latin_name\": \"Pyrrharctia_isabella\"}, {\"common_name\": \"Yellow Woolly Bear\", \"irma_id\": \"0037883\", \"latin_name_ref\": \"Spilosoma virginica\", \"latin_name\": \"Spilosoma_virginica\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0039820\", \"latin_name_ref\": \"Tetracis cachexiata\", \"latin_name\": \"Tetracis_cachexiata\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0015773\", \"latin_name_ref\": \"Euphyia intermediata\", \"latin_name\": \"Euphyia_intermediata\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0018930\", \"latin_name_ref\": \"Herpetogramma abdominalis\", \"latin_name\": \"Herpetogramma_abdominalis\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0019789\", \"latin_name_ref\": \"Hydrelia inornata\", \"latin_name\": \"Hydrelia_inornata\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0020339\", \"latin_name_ref\": \"Hyperstrotia villificans\", \"latin_name\": \"Hyperstrotia_villificans\"}, {\"common_name\": \"Yellowstriped Armyworm\", \"irma_id\": \"0037978\", \"latin_name_ref\": \"Spodoptera ornithogalli\", \"latin_name\": \"Spodoptera_ornithogalli\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0039809\", \"latin_name_ref\": \"Tetanolita mynesalis\", \"latin_name\": \"Tetanolita_mynesalis\"}, {\"common_name\": \"Polytrichum Moss\", \"irma_id\": \"0032359\", \"latin_name_ref\": \"Polytrichum pallidisetum\", \"latin_name\": \"Polytrichum_pallidisetum\"}, {\"common_name\": \"Toed-Winged Beetle\", \"irma_id\": \"0002091\", \"latin_name_ref\": \"Anchytarsus bicolor\", \"latin_name\": \"Anchytarsus_bicolor\"}, {\"common_name\": \"Splendid Stickbait Caddis\", \"irma_id\": \"0034143\", \"latin_name_ref\": \"Pycnopsyche luculenta\", \"latin_name\": \"Pycnopsyche_luculenta\"}, {\"common_name\": \"Denuded Dicranodontium Moss\", \"irma_id\": \"0012267\", \"latin_name_ref\": \"Dicranodontium denudatum\", \"latin_name\": \"Dicranodontium_denudatum\"}, {\"common_name\": \"Ant\", \"irma_id\": \"0016780\", \"latin_name_ref\": \"Formica subsericea\", \"latin_name\": \"Formica_subsericea\"}, {\"common_name\": \"Cryptic Painted Minnow Mayfly\", \"irma_id\": \"0001768\", \"latin_name_ref\": \"Ameletus cryptostimulus\", \"latin_name\": \"Ameletus_cryptostimulus\"}, {\"common_name\": \"Eastern Needlefly\", \"irma_id\": \"0022483\", \"latin_name_ref\": \"Leuctra ferruginea\", \"latin_name\": \"Leuctra_ferruginea\"}, {\"common_name\": \"Black Carpenter Ant\", \"irma_id\": \"0005293\", \"latin_name_ref\": \"Camponotus pennsylvannicus\", \"latin_name\": \"Camponotus_pennsylvannicus\"}, {\"common_name\": \"Waterbear\", \"irma_id\": \"0025312\", \"latin_name_ref\": \"Milnesium bohleberi\", \"latin_name\": \"Milnesium_bohleberi\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0018394\", \"latin_name_ref\": \"Harpalus Opadius spadiceus\", \"latin_name\": \"Harpalus_Opadius_spadiceus\"}, {\"common_name\": \"Canadian Honewort\", \"irma_id\": \"0010755\", \"latin_name_ref\": \"Cryptotaenia canadensis\", \"latin_name\": \"Cryptotaenia_canadensis\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0020274\", \"latin_name_ref\": \"Hypena baltimoralis\", \"latin_name\": \"Hypena_baltimoralis\"}, {\"common_name\": \"Mountain Spleenwort\", \"irma_id\": \"0004129\", \"latin_name_ref\": \"Asplenium montanum\", \"latin_name\": \"Asplenium_montanum\"}, {\"common_name\": \"Marsh Blue Violet\", \"irma_id\": \"0042313\", \"latin_name_ref\": \"Viola cucullata\", \"latin_name\": \"Viola_cucullata\"}, {\"common_name\": \"Poverty Rush\", \"irma_id\": \"0021164\", \"latin_name_ref\": \"Juncus tenuis variety\", \"latin_name\": \"Juncus_tenuis_variety\"}, {\"common_name\": \"Malloch`S Non-Biting Midge\", \"irma_id\": \"0000223\", \"latin_name_ref\": \"Ablabesmyia mallochi\", \"latin_name\": \"Ablabesmyia_mallochi\"}, {\"common_name\": \"Shovel-Nosed Salamander\", \"irma_id\": \"0011921\", \"latin_name_ref\": \"Desmognathus marmoratus\", \"latin_name\": \"Desmognathus_marmoratus\"}, {\"common_name\": \"Drab Condylolomia\", \"irma_id\": \"0009675\", \"latin_name_ref\": \"Condylolomia participalis\", \"latin_name\": \"Condylolomia_participalis\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0036913\", \"latin_name_ref\": \"Steerecleus serrulatum\", \"latin_name\": \"Steerecleus_serrulatum\"}, {\"common_name\": \"Southern Bush-Honeysuckle\", \"irma_id\": \"0011213\", \"latin_name_ref\": \"Diervilla sessilifolia\", \"latin_name\": \"Diervilla_sessilifolia\"}, {\"common_name\": \"Spiny Crawler Mayfly 5\", \"irma_id\": \"0014751\", \"latin_name_ref\": \"Eurylophella funeralis\", \"latin_name\": \"Eurylophella_funeralis\"}, {\"common_name\": \"Flatheaded Mayfly\", \"irma_id\": \"0023622\", \"latin_name_ref\": \"Maccaffertium ithaca\", \"latin_name\": \"Maccaffertium_ithaca\"}, {\"common_name\": \"Flat-Headed Mayfly A4\", \"irma_id\": \"0022468\", \"latin_name_ref\": \"Leucrocuta juno\", \"latin_name\": \"Leucrocuta_juno\"}, {\"common_name\": \"Elegant Riffle Beetle\", \"irma_id\": \"0032777\", \"latin_name_ref\": \"Promoresia elegans\", \"latin_name\": \"Promoresia_elegans\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0034755\", \"latin_name_ref\": \"Renia factiosalis\", \"latin_name\": \"Renia_factiosalis\"}, {\"common_name\": \"Variable Antepione\", \"irma_id\": \"0002539\", \"latin_name_ref\": \"Antepione thisoaria\", \"latin_name\": \"Antepione_thisoaria\"}, {\"common_name\": \"Lichen\", \"irma_id\": \"0021936\", \"latin_name_ref\": \"Lecanora  cinereofusca\", \"latin_name\": \"Lecanora__cinereofusca\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0017005\", \"latin_name_ref\": \"Galgula partita\", \"latin_name\": \"Galgula_partita\"}, {\"common_name\": \"Zabulon Skipper\", \"irma_id\": \"0031877\", \"latin_name_ref\": \"Poanes zabulon\", \"latin_name\": \"Poanes_zabulon\"}, {\"common_name\": \"Comma\", \"irma_id\": \"0032084\", \"latin_name_ref\": \"Polygonia comma\", \"latin_name\": \"Polygonia_comma\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0040580\", \"latin_name_ref\": \"Zanclognatha cruralis\", \"latin_name\": \"Zanclognatha_cruralis\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0013188\", \"latin_name_ref\": \"Ecliptopera atricolorata\", \"latin_name\": \"Ecliptopera_atricolorata\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0021637\", \"latin_name_ref\": \"Lambdina fervidaria\", \"latin_name\": \"Lambdina_fervidaria\"}, {\"common_name\": \"Dicranum Moss\", \"irma_id\": \"0012340\", \"latin_name_ref\": \"Dicranum scoparium\", \"latin_name\": \"Dicranum_scoparium\"}, {\"common_name\": \"Medium Dagger Moth\", \"irma_id\": \"0000744\", \"latin_name_ref\": \"Acronicta modica\", \"latin_name\": \"Acronicta_modica\"}, {\"common_name\": \"Oak Besma\", \"irma_id\": \"0004759\", \"latin_name_ref\": \"Besma quercivoraria\", \"latin_name\": \"Besma_quercivoraria\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0011967\", \"latin_name_ref\": \"Diacme adipaloides\", \"latin_name\": \"Diacme_adipaloides\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0015513\", \"latin_name_ref\": \"Eulithis gracilineata\", \"latin_name\": \"Eulithis_gracilineata\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0023210\", \"latin_name_ref\": \"Lomographa vestaliata\", \"latin_name\": \"Lomographa_vestaliata\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0023613\", \"latin_name_ref\": \"Macaria pustularia\", \"latin_name\": \"Macaria_pustularia\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0029858\", \"latin_name_ref\": \"Pero ancetaria\", \"latin_name\": \"Pero_ancetaria\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0031885\", \"latin_name_ref\": \"Pococera asperatella\", \"latin_name\": \"Pococera_asperatella\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0040968\", \"latin_name_ref\": \"Tricholita signata\", \"latin_name\": \"Tricholita_signata\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0040552\", \"latin_name_ref\": \"Zale lunata\", \"latin_name\": \"Zale_lunata\"}, {\"common_name\": \"Hairy Wood-Rush\", \"irma_id\": \"0023437\", \"latin_name_ref\": \"Luzula acuminata variety\", \"latin_name\": \"Luzula_acuminata_variety\"}, {\"common_name\": \"Cornfield Ant\", \"irma_id\": \"0021872\", \"latin_name_ref\": \"Lasius Lasius alienus\", \"latin_name\": \"Lasius_Lasius_alienus\"}, {\"common_name\": \"Old Wife Underwing\", \"irma_id\": \"0007396\", \"latin_name_ref\": \"Catocala palaeogama\", \"latin_name\": \"Catocala_palaeogama\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0020250\", \"latin_name_ref\": \"Hypagyrtis esther\", \"latin_name\": \"Hypagyrtis_esther\"}, {\"common_name\": \"Little Nymph Underwing\", \"irma_id\": \"0007381\", \"latin_name_ref\": \"Catocala micronympha\", \"latin_name\": \"Catocala_micronympha\"}, {\"common_name\": \"Least-Marked Euchlaena Moth\", \"irma_id\": \"0015138\", \"latin_name_ref\": \"Euchlaena irraria\", \"latin_name\": \"Euchlaena_irraria\"}, {\"common_name\": \"White-Blotched Heterocampa Moth\", \"irma_id\": \"0017663\", \"latin_name_ref\": \"Heterocampa umbrata\", \"latin_name\": \"Heterocampa_umbrata\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0042394\", \"latin_name_ref\": \"Vitula edmandsii\", \"latin_name\": \"Vitula_edmandsii\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0042770\", \"latin_name_ref\": \"Xestia smithii\", \"latin_name\": \"Xestia_smithii\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0033497\", \"latin_name_ref\": \"Pseudeustrotia carneola\", \"latin_name\": \"Pseudeustrotia_carneola\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0034908\", \"latin_name_ref\": \"Rheumaptera prunivorata\", \"latin_name\": \"Rheumaptera_prunivorata\"}, {\"common_name\": \"York Sallfly\", \"irma_id\": \"0039008\", \"latin_name_ref\": \"Suwallia marginata\", \"latin_name\": \"Suwallia_marginata\"}, {\"common_name\": \"Greater Red Dart\", \"irma_id\": \"0000172\", \"latin_name_ref\": \"Abagrotis alternata\", \"latin_name\": \"Abagrotis_alternata\"}, {\"common_name\": \"Sordid Underwing\", \"irma_id\": \"0007410\", \"latin_name_ref\": \"Catocala sordida\", \"latin_name\": \"Catocala_sordida\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0031259\", \"latin_name_ref\": \"Physarum viride\", \"latin_name\": \"Physarum_viride\"}, {\"common_name\": \"Ant\", \"irma_id\": \"0021866\", \"latin_name_ref\": \"Lasius alienus\", \"latin_name\": \"Lasius_alienus\"}, {\"common_name\": \"Ant\", \"irma_id\": \"0038532\", \"latin_name_ref\": \"Temnothorax longispinosus\", \"latin_name\": \"Temnothorax_longispinosus\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0024338\", \"latin_name_ref\": \"Mychocerus striatus\", \"latin_name\": \"Mychocerus_striatus\"}, {\"common_name\": \"Yellow-Haired Dagger Moth\", \"irma_id\": \"0000728\", \"latin_name_ref\": \"Acronicta impleta\", \"latin_name\": \"Acronicta_impleta\"}, {\"common_name\": \"Tulip-Tree Silkmoth\", \"irma_id\": \"0006226\", \"latin_name_ref\": \"Callosamia angulifera\", \"latin_name\": \"Callosamia_angulifera\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0010358\", \"latin_name_ref\": \"Costaconvexa centrostrigaria\", \"latin_name\": \"Costaconvexa_centrostrigaria\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0017906\", \"latin_name_ref\": \"Gueneria similaria\", \"latin_name\": \"Gueneria_similaria\"}, {\"common_name\": \"Brown Bark Carpet\", \"irma_id\": \"0019335\", \"latin_name_ref\": \"Horisme intestinata\", \"latin_name\": \"Horisme_intestinata\"}, {\"common_name\": \"Hemlock Looper Moth\", \"irma_id\": \"0021638\", \"latin_name_ref\": \"Lambdina fiscellaria\", \"latin_name\": \"Lambdina_fiscellaria\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0035982\", \"latin_name_ref\": \"Scoparia cinereomedia\", \"latin_name\": \"Scoparia_cinereomedia\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0016171\", \"latin_name_ref\": \"Euzophera ostricolorella\", \"latin_name\": \"Euzophera_ostricolorella\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0042360\", \"latin_name_ref\": \"Virbia opella\", \"latin_name\": \"Virbia_opella\"}, {\"common_name\": \"Illinoian Non-Biting Midge\", \"irma_id\": \"0032176\", \"latin_name_ref\": \"Polypedilum Polypedilum illinoense\", \"latin_name\": \"Polypedilum_Polypedilum_illinoense\"}, {\"common_name\": \"Xenate Non-Biting Midge\", \"irma_id\": \"0039934\", \"latin_name_ref\": \"Thienemanniella xena\", \"latin_name\": \"Thienemanniella_xena\"}, {\"common_name\": \"American Holly\", \"irma_id\": \"0020696\", \"latin_name_ref\": \"Ilex opaca variety\", \"latin_name\": \"Ilex_opaca_variety\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0020552\", \"latin_name_ref\": \"Hypsibius cf dujardini\", \"latin_name\": \"Hypsibius_cf_dujardini\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0013356\", \"latin_name_ref\": \"Elaphria grata\", \"latin_name\": \"Elaphria_grata\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0025162\", \"latin_name_ref\": \"Microcrambus elegans\", \"latin_name\": \"Microcrambus_elegans\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0027292\", \"latin_name_ref\": \"Oligocentria lignicolor\", \"latin_name\": \"Oligocentria_lignicolor\"}, {\"common_name\": \"Gray-Foot Lancetooth\", \"irma_id\": \"0018361\", \"latin_name_ref\": \"Haplotrema concavum\", \"latin_name\": \"Haplotrema_concavum\"}, {\"common_name\": \"Core\\'S Starwort\", \"irma_id\": \"0036936\", \"latin_name_ref\": \"Stellaria corei\", \"latin_name\": \"Stellaria_corei\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0012030\", \"latin_name_ref\": \"Diarsia jucunda\", \"latin_name\": \"Diarsia_jucunda\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0011656\", \"latin_name_ref\": \"Datana ministra\", \"latin_name\": \"Datana_ministra\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0020655\", \"latin_name_ref\": \"Idia lubricalis\", \"latin_name\": \"Idia_lubricalis\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0041706\", \"latin_name_ref\": \"Zanclognatha ochreipennis\", \"latin_name\": \"Zanclognatha_ochreipennis\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0027297\", \"latin_name_ref\": \"Oligocentria semirufescens\", \"latin_name\": \"Oligocentria_semirufescens\"}, {\"common_name\": \"Little-Neck Ground Beetle\", \"irma_id\": \"0030573\", \"latin_name_ref\": \"Platynus Platynus tenuicollis\", \"latin_name\": \"Platynus_Platynus_tenuicollis\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0024098\", \"latin_name_ref\": \"Melanolophia signataria\", \"latin_name\": \"Melanolophia_signataria\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0028496\", \"latin_name_ref\": \"Pandemis limitata\", \"latin_name\": \"Pandemis_limitata\"}, {\"common_name\": \"Honest Ground Beetle\", \"irma_id\": \"0017061\", \"latin_name_ref\": \"Gastrellarius honestus\", \"latin_name\": \"Gastrellarius_honestus\"}, {\"common_name\": \"Splendid Dagger Moth\", \"irma_id\": \"0000765\", \"latin_name_ref\": \"Acronicta superans\", \"latin_name\": \"Acronicta_superans\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0030047\", \"latin_name_ref\": \"Phalaenophana pyramusalis\", \"latin_name\": \"Phalaenophana_pyramusalis\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0018931\", \"latin_name_ref\": \"Herpetogramma aeglealis\", \"latin_name\": \"Herpetogramma_aeglealis\"}, {\"common_name\": \"Worm\", \"irma_id\": \"0024518\", \"latin_name_ref\": \"Nais communis\", \"latin_name\": \"Nais_communis\"}, {\"common_name\": \"Broad Looseflower Sedge\", \"irma_id\": \"0007043\", \"latin_name_ref\": \"Carex laxiflora variety\", \"latin_name\": \"Carex_laxiflora_variety\"}, {\"common_name\": \"Pink Turtlehead\", \"irma_id\": \"0008003\", \"latin_name_ref\": \"Chelone lyonii\", \"latin_name\": \"Chelone_lyonii\"}, {\"common_name\": \"Green Arches\", \"irma_id\": \"0002037\", \"latin_name_ref\": \"Anaplectoides prasina\", \"latin_name\": \"Anaplectoides_prasina\"}, {\"common_name\": \"Spring Salamander\", \"irma_id\": \"0018027\", \"latin_name_ref\": \"Gyrinophilus porphyriticus danielsi\", \"latin_name\": \"Gyrinophilus_porphyriticus_danielsi\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0023458\", \"latin_name_ref\": \"Lycogala epidendrum\", \"latin_name\": \"Lycogala_epidendrum\"}, {\"common_name\": \"Small Brook Flat-Headed Mayfly\", \"irma_id\": \"0023628\", \"latin_name_ref\": \"Maccaffertium meririvulanum\", \"latin_name\": \"Maccaffertium_meririvulanum\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0032664\", \"latin_name_ref\": \"Probole nepiasaria\", \"latin_name\": \"Probole_nepiasaria\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0023192\", \"latin_name_ref\": \"Lochmaeus bilineata\", \"latin_name\": \"Lochmaeus_bilineata\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0025158\", \"latin_name_ref\": \"Microcrambus biguttellus\", \"latin_name\": \"Microcrambus_biguttellus\"}, {\"common_name\": \"Beaked Dodder\", \"irma_id\": \"0010914\", \"latin_name_ref\": \"Cuscuta rostrata\", \"latin_name\": \"Cuscuta_rostrata\"}, {\"common_name\": \"Flat-Headed Mayfly A8\", \"irma_id\": \"0038015\", \"latin_name_ref\": \"Stenacron interpunctatum\", \"latin_name\": \"Stenacron_interpunctatum\"}, {\"common_name\": \"Symbiotic Non-Biting Midge\", \"irma_id\": \"0039288\", \"latin_name_ref\": \"Synorthocladius semivirens\", \"latin_name\": \"Synorthocladius_semivirens\"}, {\"common_name\": \"Least Sallfly\", \"irma_id\": \"0018348\", \"latin_name_ref\": \"Haploperla brevis\", \"latin_name\": \"Haploperla_brevis\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0025636\", \"latin_name_ref\": \"Monopis marginistrigella\", \"latin_name\": \"Monopis_marginistrigella\"}, {\"common_name\": \"Digressing Non-Biting Midge\", \"irma_id\": \"0023724\", \"latin_name_ref\": \"Macropelopia decedens\", \"latin_name\": \"Macropelopia_decedens\"}, {\"common_name\": \"Brownish Sedge\", \"irma_id\": \"0003387\", \"latin_name_ref\": \"Carex brunnescens sphaerostachya\", \"latin_name\": \"Carex_brunnescens_sphaerostachya\"}, {\"common_name\": \"Bristly Buttercup\", \"irma_id\": \"0034502\", \"latin_name_ref\": \"Ranunculus hispidus variety\", \"latin_name\": \"Ranunculus_hispidus_variety\"}, {\"common_name\": \"Brown Thrasher\", \"irma_id\": \"0040625\", \"latin_name_ref\": \"Toxostoma rufum\", \"latin_name\": \"Toxostoma_rufum\"}, {\"common_name\": \"Nicolay`S Antloving Rove Beetle\", \"irma_id\": \"0025389\", \"latin_name_ref\": \"Mipseltyrus nicolayi\", \"latin_name\": \"Mipseltyrus_nicolayi\"}, {\"common_name\": \"Charming Underwing Moth\", \"irma_id\": \"0007325\", \"latin_name_ref\": \"Catocala blandula\", \"latin_name\": \"Catocala_blandula\"}, {\"common_name\": \"Two-Leaf Bishop\\\\u2019S-Cap\", \"irma_id\": \"0025445\", \"latin_name_ref\": \"Mitella diphylla\", \"latin_name\": \"Mitella_diphylla\"}, {\"common_name\": \"Yellow Wakerobin\", \"irma_id\": \"0041205\", \"latin_name_ref\": \"Trillium luteum\", \"latin_name\": \"Trillium_luteum\"}, {\"common_name\": \"Bristly Cutworm\", \"irma_id\": \"0021414\", \"latin_name_ref\": \"Lacinipolia renigera\", \"latin_name\": \"Lacinipolia_renigera\"}, {\"common_name\": \"Southern Pine Sphinx Moth\", \"irma_id\": \"0021691\", \"latin_name_ref\": \"Lapara coniferarum\", \"latin_name\": \"Lapara_coniferarum\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0040534\", \"latin_name_ref\": \"Zale aeruginosa\", \"latin_name\": \"Zale_aeruginosa\"}, {\"common_name\": \"Sap-Feeding Beetle 04\", \"irma_id\": \"0036932\", \"latin_name_ref\": \"Stelidota octomaculata\", \"latin_name\": \"Stelidota_octomaculata\"}, {\"common_name\": \"Green Non-Biting Midge\", \"irma_id\": \"0032749\", \"latin_name_ref\": \"Prodiamesa olivacea\", \"latin_name\": \"Prodiamesa_olivacea\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0008973\", \"latin_name_ref\": \"Clavicorona pyxidata\", \"latin_name\": \"Clavicorona_pyxidata\"}, {\"common_name\": \"Brown-Lined Dart Moth\", \"irma_id\": \"0002036\", \"latin_name_ref\": \"Anaplectoides brunneomedia\", \"latin_name\": \"Anaplectoides_brunneomedia\"}, {\"common_name\": \"Richweed  \", \"irma_id\": \"0031385\", \"latin_name_ref\": \"Pilea pumila\", \"latin_name\": \"Pilea_pumila\"}, {\"common_name\": \"Cinnabar-Red Chanterelle\", \"irma_id\": \"0005388\", \"latin_name_ref\": \"Cantharellus cinnabarinus\", \"latin_name\": \"Cantharellus_cinnabarinus\"}, {\"common_name\": \"Carolina Stone\", \"irma_id\": \"0000688\", \"latin_name_ref\": \"Acroneuria carolinensis\", \"latin_name\": \"Acroneuria_carolinensis\"}, {\"common_name\": \"A Spiny Crawler Mayfly\", \"irma_id\": \"0012988\", \"latin_name_ref\": \"Drunella longicornis\", \"latin_name\": \"Drunella_longicornis\"}, {\"common_name\": \"Ephemerellid Mayfly\", \"irma_id\": \"0014024\", \"latin_name_ref\": \"Ephemerella invaria group\", \"latin_name\": \"Ephemerella_invaria_group\"}, {\"common_name\": \"Morose Caddisfly\", \"irma_id\": \"0019943\", \"latin_name_ref\": \"Hydropsyche morosa\", \"latin_name\": \"Hydropsyche_morosa\"}, {\"common_name\": \"Light Brown Apple Moth\", \"irma_id\": \"0009057\", \"latin_name_ref\": \"Clepsis virescana\", \"latin_name\": \"Clepsis_virescana\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0014053\", \"latin_name_ref\": \"Ephestiodes infimella\", \"latin_name\": \"Ephestiodes_infimella\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0015413\", \"latin_name_ref\": \"Eudonia heterosalis\", \"latin_name\": \"Eudonia_heterosalis\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0033612\", \"latin_name_ref\": \"Pseudohermonassa bicarnea\", \"latin_name\": \"Pseudohermonassa_bicarnea\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0042762\", \"latin_name_ref\": \"Xestia normaniana\", \"latin_name\": \"Xestia_normaniana\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0029629\", \"latin_name_ref\": \"Penicillium oxalicum\", \"latin_name\": \"Penicillium_oxalicum\"}, {\"common_name\": \"Nodding Fescue\", \"irma_id\": \"0016589\", \"latin_name_ref\": \"Festuca subverticillata\", \"latin_name\": \"Festuca_subverticillata\"}, {\"common_name\": \"Scarab Beetle\", \"irma_id\": \"0036554\", \"latin_name_ref\": \"Serica georgiana georgiana\", \"latin_name\": \"Serica_georgiana_georgiana\"}, {\"common_name\": \"Northern White Violet\", \"irma_id\": \"0042324\", \"latin_name_ref\": \"Viola macloskeyi variety\", \"latin_name\": \"Viola_macloskeyi_variety\"}, {\"common_name\": \"Roundneck Sexton Beetle\", \"irma_id\": \"0026620\", \"latin_name_ref\": \"Nicrophorus orbicollis\", \"latin_name\": \"Nicrophorus_orbicollis\"}, {\"common_name\": \"Hypnum Moss\", \"irma_id\": \"0020376\", \"latin_name_ref\": \"Hypnum imponens\", \"latin_name\": \"Hypnum_imponens\"}, {\"common_name\": \"False Lily-Of-The-Valley\", \"irma_id\": \"0023806\", \"latin_name_ref\": \"Maianthemum canadense\", \"latin_name\": \"Maianthemum_canadense\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0042709\", \"latin_name_ref\": \"Xeromphalina campanella\", \"latin_name\": \"Xeromphalina_campanella\"}, {\"common_name\": \"Golden Grounsel\", \"irma_id\": \"0028379\", \"latin_name_ref\": \"Packera aurea\", \"latin_name\": \"Packera_aurea\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0040088\", \"latin_name_ref\": \"Thysanopyga intractata\", \"latin_name\": \"Thysanopyga_intractata\"}, {\"common_name\": \"Common Looper Moth\", \"irma_id\": \"0003171\", \"latin_name_ref\": \"Autographa precationis\", \"latin_name\": \"Autographa_precationis\"}, {\"common_name\": \"Ochre Dagger Moth\", \"irma_id\": \"0000745\", \"latin_name_ref\": \"Acronicta morula\", \"latin_name\": \"Acronicta_morula\"}, {\"common_name\": \"Ilia Underwing\", \"irma_id\": \"0007360\", \"latin_name_ref\": \"Catocala ilia\", \"latin_name\": \"Catocala_ilia\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0011706\", \"latin_name_ref\": \"Deidamia inscripta\", \"latin_name\": \"Deidamia_inscripta\"}, {\"common_name\": \"Eastern Pinelooper\", \"irma_id\": \"0021641\", \"latin_name_ref\": \"Lambdina pellucidaria\", \"latin_name\": \"Lambdina_pellucidaria\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0024934\", \"latin_name_ref\": \"Metarranthis hypocharia\", \"latin_name\": \"Metarranthis_hypocharia\"}, {\"common_name\": \"Variegated Cutworm\", \"irma_id\": \"0029768\", \"latin_name_ref\": \"Peridroma saucia\", \"latin_name\": \"Peridroma_saucia\"}, {\"common_name\": \"Yellow Stickbait Caddis\", \"irma_id\": \"0034135\", \"latin_name_ref\": \"Pycnopsyche flavata\", \"latin_name\": \"Pycnopsyche_flavata\"}, {\"common_name\": \"Dracula Ant\", \"irma_id\": \"0001713\", \"latin_name_ref\": \"Amblyopone pallipes\", \"latin_name\": \"Amblyopone_pallipes\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0032472\", \"latin_name_ref\": \"Porpidia albocaerulescens\", \"latin_name\": \"Porpidia_albocaerulescens\"}, {\"common_name\": \"Lichen\", \"irma_id\": \"0034085\", \"latin_name_ref\": \"Punctelia rudecta\", \"latin_name\": \"Punctelia_rudecta\"}, {\"common_name\": \"Carlson\\'S Flatheaded Mayfly\", \"irma_id\": \"0023619\", \"latin_name_ref\": \"Maccaffertium carlsoni\", \"latin_name\": \"Maccaffertium_carlsoni\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0026790\", \"latin_name_ref\": \"Nomophila nearctica\", \"latin_name\": \"Nomophila_nearctica\"}, {\"common_name\": \"Twelve-Spotted Ladybug\", \"irma_id\": \"0018381\", \"latin_name_ref\": \"Harmonia axyridis\", \"latin_name\": \"Harmonia_axyridis\"}, {\"common_name\": \"Mountain Button\", \"irma_id\": \"0024839\", \"latin_name_ref\": \"Mesomphix andrewsae\", \"latin_name\": \"Mesomphix_andrewsae\"}, {\"common_name\": \"Aurora Trout\", \"irma_id\": \"0033186\", \"latin_name_ref\": \"Salvelinus fontinalis\", \"latin_name\": \"Salvelinus_fontinalis\"}, {\"common_name\": \"Higgin\\'S Waterbear\", \"irma_id\": \"0011373\", \"latin_name_ref\": \"Diphascon Diphascon higginsi\", \"latin_name\": \"Diphascon_Diphascon_higginsi\"}, {\"common_name\": \"Tonolli`S Water Bear\", \"irma_id\": \"0023684\", \"latin_name_ref\": \"Macrobiotus tonollii\", \"latin_name\": \"Macrobiotus_tonollii\"}, {\"common_name\": \"Lemon Plagodis Moth\", \"irma_id\": \"0031685\", \"latin_name_ref\": \"Plagodis serinaria\", \"latin_name\": \"Plagodis_serinaria\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0032231\", \"latin_name_ref\": \"Polypogon laevigata\", \"latin_name\": \"Polypogon_laevigata\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0035903\", \"latin_name_ref\": \"Sciota virgatella\", \"latin_name\": \"Sciota_virgatella\"}, {\"common_name\": \"Light-Blothced False Darkling Beetle\", \"irma_id\": \"0012500\", \"latin_name_ref\": \"Dircaea liturata\", \"latin_name\": \"Dircaea_liturata\"}, {\"common_name\": \"Virginia Creeper Sphinx Moth\", \"irma_id\": \"0011584\", \"latin_name_ref\": \"Darapsa myron\", \"latin_name\": \"Darapsa_myron\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0017256\", \"latin_name_ref\": \"Glena cribrataria\", \"latin_name\": \"Glena_cribrataria\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0027025\", \"latin_name_ref\": \"Ochropleura implecta\", \"latin_name\": \"Ochropleura_implecta\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0028696\", \"latin_name_ref\": \"Papilio troilus\", \"latin_name\": \"Papilio_troilus\"}, {\"common_name\": \"Question Mark\", \"irma_id\": \"0032087\", \"latin_name_ref\": \"Polygonia interrogationis\", \"latin_name\": \"Polygonia_interrogationis\"}, {\"common_name\": \"Golden Waxy Cap\", \"irma_id\": \"0020044\", \"latin_name_ref\": \"Hygrocybe flavescens\", \"latin_name\": \"Hygrocybe_flavescens\"}, {\"common_name\": \"Weeping Milk Cap Mushroom\", \"irma_id\": \"0021581\", \"latin_name_ref\": \"Lactarius volemus\", \"latin_name\": \"Lactarius_volemus\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0020279\", \"latin_name_ref\": \"Hypena edictalis\", \"latin_name\": \"Hypena_edictalis\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0029755\", \"latin_name_ref\": \"Peridea ferruginea\", \"latin_name\": \"Peridea_ferruginea\"}, {\"common_name\": \"Yellow-Spotted Webworm\", \"irma_id\": \"0002019\", \"latin_name_ref\": \"Anageshna primordialis\", \"latin_name\": \"Anageshna_primordialis\"}, {\"common_name\": \"Eastern Tent Caterpillar\", \"irma_id\": \"0023812\", \"latin_name_ref\": \"Malacosoma americanum\", \"latin_name\": \"Malacosoma_americanum\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0024660\", \"latin_name_ref\": \"Mythimna unipuncta\", \"latin_name\": \"Mythimna_unipuncta\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0031684\", \"latin_name_ref\": \"Plagodis pulveraria\", \"latin_name\": \"Plagodis_pulveraria\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0031780\", \"latin_name_ref\": \"Pleuroprucha insulsaria\", \"latin_name\": \"Pleuroprucha_insulsaria\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0040035\", \"latin_name_ref\": \"Trigrammia quadrinotaria\", \"latin_name\": \"Trigrammia_quadrinotaria\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0011621\", \"latin_name_ref\": \"Dasylophia thyatiroides\", \"latin_name\": \"Dasylophia_thyatiroides\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0021689\", \"latin_name_ref\": \"Laothoe juglandis\", \"latin_name\": \"Laothoe_juglandis\"}, {\"common_name\": \"Four-Barred Gray Moth\", \"irma_id\": \"0000139\", \"latin_name_ref\": \"Aethalura intertexta\", \"latin_name\": \"Aethalura_intertexta\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0013242\", \"latin_name_ref\": \"Egira alternans\", \"latin_name\": \"Egira_alternans\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0035900\", \"latin_name_ref\": \"Sciota subcaesiella\", \"latin_name\": \"Sciota_subcaesiella\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0040587\", \"latin_name_ref\": \"Zanclognatha martha\", \"latin_name\": \"Zanclognatha_martha\"}, {\"common_name\": \"Common Gray\", \"irma_id\": \"0002083\", \"latin_name_ref\": \"Anavitrinella pampinaria\", \"latin_name\": \"Anavitrinella_pampinaria\"}, {\"common_name\": \"Hollow-Spotted Blepharomastix Moth\", \"irma_id\": \"0004935\", \"latin_name_ref\": \"Blepharomastix ranalis\", \"latin_name\": \"Blepharomastix_ranalis\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0023603\", \"latin_name_ref\": \"Macaria aemulataria\", \"latin_name\": \"Macaria_aemulataria\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0023608\", \"latin_name_ref\": \"Macaria granitata\", \"latin_name\": \"Macaria_granitata\"}, {\"common_name\": \"Scribbler Moth\", \"irma_id\": \"0008829\", \"latin_name_ref\": \"Cladara atroliturata\", \"latin_name\": \"Cladara_atroliturata\"}, {\"common_name\": \"American Ear Moth\", \"irma_id\": \"0001894\", \"latin_name_ref\": \"Amphipoea americana\", \"latin_name\": \"Amphipoea_americana\"}, {\"common_name\": \"Straw Besma\", \"irma_id\": \"0004758\", \"latin_name_ref\": \"Besma endropiaria\", \"latin_name\": \"Besma_endropiaria\"}, {\"common_name\": \"Sweet Fern Geometer\", \"irma_id\": \"0009766\", \"latin_name_ref\": \"Cyclophora pendulinaria\", \"latin_name\": \"Cyclophora_pendulinaria\"}, {\"common_name\": \"Tawny Holomelina \", \"irma_id\": \"0019134\", \"latin_name_ref\": \"Holomelina opella\", \"latin_name\": \"Holomelina_opella\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0020546\", \"latin_name_ref\": \"Hyppa contrasta\", \"latin_name\": \"Hyppa_contrasta\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0027848\", \"latin_name_ref\": \"Orthodes crenulata\", \"latin_name\": \"Orthodes_crenulata\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0032954\", \"latin_name_ref\": \"Protolampra brunneicollis\", \"latin_name\": \"Protolampra_brunneicollis\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0040601\", \"latin_name_ref\": \"Tolype notialis\", \"latin_name\": \"Tolype_notialis\"}, {\"common_name\": \"Jelly Babies\", \"irma_id\": \"0022082\", \"latin_name_ref\": \"Leotia lubrica\", \"latin_name\": \"Leotia_lubrica\"}, {\"common_name\": \"White-Lined Leafroller\", \"irma_id\": \"0001843\", \"latin_name_ref\": \"Amorbia humerosana\", \"latin_name\": \"Amorbia_humerosana\"}, {\"common_name\": \"Dogwood Probole\", \"irma_id\": \"0032662\", \"latin_name_ref\": \"Probole alienaria\", \"latin_name\": \"Probole_alienaria\"}, {\"common_name\": \"Yellow-Collared Scape Moth \", \"irma_id\": \"0008787\", \"latin_name_ref\": \"Cisseps fulvicollis\", \"latin_name\": \"Cisseps_fulvicollis\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0018574\", \"latin_name_ref\": \"Heliomata cycladata\", \"latin_name\": \"Heliomata_cycladata\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0020277\", \"latin_name_ref\": \"Hypena deceptalis\", \"latin_name\": \"Hypena_deceptalis\"}, {\"common_name\": \"Hermit Thrush\", \"irma_id\": \"0007285\", \"latin_name_ref\": \"Catharus guttatus\", \"latin_name\": \"Catharus_guttatus\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0018554\", \"latin_name_ref\": \"Helicoverpa zea\", \"latin_name\": \"Helicoverpa_zea\"}, {\"common_name\": \"Short-Tailed Shrew\", \"irma_id\": \"0004884\", \"latin_name_ref\": \"Blarina brevicauda\", \"latin_name\": \"Blarina_brevicauda\"}, {\"common_name\": \"Cherry Dagger Moth\", \"irma_id\": \"0000724\", \"latin_name_ref\": \"Acronicta hasta\", \"latin_name\": \"Acronicta_hasta\"}, {\"common_name\": \"Garden Tortrix\", \"irma_id\": \"0009054\", \"latin_name_ref\": \"Clepsis peritana\", \"latin_name\": \"Clepsis_peritana\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0017701\", \"latin_name_ref\": \"Heterophleps refusaria\", \"latin_name\": \"Heterophleps_refusaria\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0022371\", \"latin_name_ref\": \"Leucania adjuta\", \"latin_name\": \"Leucania_adjuta\"}, {\"common_name\": \"White Striped Black\", \"irma_id\": \"0040938\", \"latin_name_ref\": \"Trichodezia albovittata\", \"latin_name\": \"Trichodezia_albovittata\"}, {\"common_name\": \"Common Eastern Bumble Bee\", \"irma_id\": \"0005130\", \"latin_name_ref\": \"Bombus Pyrobombus impatiens\", \"latin_name\": \"Bombus_Pyrobombus_impatiens\"}, {\"common_name\": \"Bronta Retreat-Maker\", \"irma_id\": \"0019923\", \"latin_name_ref\": \"Hydropsyche bronta\", \"latin_name\": \"Hydropsyche_bronta\"}, {\"common_name\": \"Scallop Moth\", \"irma_id\": \"0007609\", \"latin_name_ref\": \"Cepphis armataria\", \"latin_name\": \"Cepphis_armataria\"}, {\"common_name\": \"Juvenal`S Duskywing\", \"irma_id\": \"0014521\", \"latin_name_ref\": \"Erynnis juvenalis\", \"latin_name\": \"Erynnis_juvenalis\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0020653\", \"latin_name_ref\": \"Idia laurenti\", \"latin_name\": \"Idia_laurenti\"}, {\"common_name\": \"American Painted Lady\", \"irma_id\": \"0042067\", \"latin_name_ref\": \"Vanessa virginiensis\", \"latin_name\": \"Vanessa_virginiensis\"}, {\"common_name\": \"Toothed Brown Carpet\", \"irma_id\": \"0042645\", \"latin_name_ref\": \"Xanthorhoe lacustrata\", \"latin_name\": \"Xanthorhoe_lacustrata\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0016553\", \"latin_name_ref\": \"Feltia herilis\", \"latin_name\": \"Feltia_herilis\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0032001\", \"latin_name_ref\": \"Polia imbrifera\", \"latin_name\": \"Polia_imbrifera\"}, {\"common_name\": \"Pale-Banded Dart Moth\", \"irma_id\": \"0001024\", \"latin_name_ref\": \"Agnorisma badinodis\", \"latin_name\": \"Agnorisma_badinodis\"}, {\"common_name\": \"Widow Underwing Moth\", \"irma_id\": \"0007421\", \"latin_name_ref\": \"Catocala vidua\", \"latin_name\": \"Catocala_vidua\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0023606\", \"latin_name_ref\": \"Macaria bisignata\", \"latin_name\": \"Macaria_bisignata\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0029223\", \"latin_name_ref\": \"Phlyctaenia coronata\", \"latin_name\": \"Phlyctaenia_coronata\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0015461\", \"latin_name_ref\": \"Eugonobapta nivosaria\", \"latin_name\": \"Eugonobapta_nivosaria\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0028388\", \"latin_name_ref\": \"Paectes abrostoloides\", \"latin_name\": \"Paectes_abrostoloides\"}, {\"common_name\": \"Grand Globe\", \"irma_id\": \"0024821\", \"latin_name_ref\": \"Mesodon normalis\", \"latin_name\": \"Mesodon_normalis\"}, {\"common_name\": \"Weevil 9\", \"irma_id\": \"0014703\", \"latin_name_ref\": \"Eurhoptus pyriformis\", \"latin_name\": \"Eurhoptus_pyriformis\"}, {\"common_name\": \"Hufeland`S Waterbear\", \"irma_id\": \"0023670\", \"latin_name_ref\": \"Macrobiotus hufelandi\", \"latin_name\": \"Macrobiotus_hufelandi\"}, {\"common_name\": \"Southern Red-Backed Vole\", \"irma_id\": \"0009061\", \"latin_name_ref\": \"Clethrionomys gapperi carolinensis\", \"latin_name\": \"Clethrionomys_gapperi_carolinensis\"}, {\"common_name\": \"Apical Retreat-Maker\", \"irma_id\": \"0028919\", \"latin_name_ref\": \"Parapsyche apicalis\", \"latin_name\": \"Parapsyche_apicalis\"}, {\"common_name\": \"Raspberry Dager Moth\", \"irma_id\": \"0000731\", \"latin_name_ref\": \"Acronicta increta\", \"latin_name\": \"Acronicta_increta\"}, {\"common_name\": \"Retarded Dagger Moth\", \"irma_id\": \"0000757\", \"latin_name_ref\": \"Acronicta retardata\", \"latin_name\": \"Acronicta_retardata\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0011614\", \"latin_name_ref\": \"Dasychira tephra\", \"latin_name\": \"Dasychira_tephra\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0034543\", \"latin_name_ref\": \"Redectis vitrea\", \"latin_name\": \"Redectis_vitrea\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0041705\", \"latin_name_ref\": \"Zanclognatha obscuripennis\", \"latin_name\": \"Zanclognatha_obscuripennis\"}, {\"common_name\": \"Wild Strawberry\", \"irma_id\": \"0016818\", \"latin_name_ref\": \"Fragaria virginiana\", \"latin_name\": \"Fragaria_virginiana\"}, {\"common_name\": \"Red-Banded Hairstreak\", \"irma_id\": \"0006394\", \"latin_name_ref\": \"Calycopis cecrops\", \"latin_name\": \"Calycopis_cecrops\"}, {\"common_name\": \"Spring Azure\", \"irma_id\": \"0007505\", \"latin_name_ref\": \"Celastrina ladon\", \"latin_name\": \"Celastrina_ladon\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0011619\", \"latin_name_ref\": \"Dasylophia anguina\", \"latin_name\": \"Dasylophia_anguina\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0029346\", \"latin_name_ref\": \"Phosphila turbulenta\", \"latin_name\": \"Phosphila_turbulenta\"}, {\"common_name\": \"Foxglove Aphid\", \"irma_id\": \"0004454\", \"latin_name_ref\": \"Aulacorthum solani\", \"latin_name\": \"Aulacorthum_solani\"}, {\"common_name\": \"Small Baileya Moth\", \"irma_id\": \"0003507\", \"latin_name_ref\": \"Baileya australis\", \"latin_name\": \"Baileya_australis\"}, {\"common_name\": \"Unspecified\", \"irma_id\": \"0016564\", \"latin_name_ref\": \"Feralia comstocki\", \"latin_name\": \"Feralia_comstocki\"}, {\"common_name\": \"Dreamy Duskywing\", \"irma_id\": \"0014520\", \"latin_name_ref\": \"Erynnis icelus\", \"latin_name\": \"Erynnis_icelus\"}, {\"common_name\": \"Variegated Fritillary Butterfly\", \"irma_id\": \"0014683\", \"latin_name_ref\": \"Euptoieta claudia\", \"latin_name\": \"Euptoieta_claudia\"}, {\"common_name\": \"Devils Snuff-Box\", \"irma_id\": \"0023479\", \"latin_name_ref\": \"Lycoperdon perlatum\", \"latin_name\": \"Lycoperdon_perlatum\"}]}\\n'\n",
      "done\n"
     ]
    }
   ],
   "source": [
    "@auto.dataclasses.dataclass(eq=True, frozen=True)\n",
    "class Observation:\n",
    "    common_name: str\n",
    "    irma_id: str\n",
    "    latin_name_ref: str\n",
    "    latin_name: str\n",
    "\n",
    "def fetch(url):\n",
    "    print(f'Fetching: {url}')\n",
    "    data = auto.requests.get(url).content\n",
    "    print(data)\n",
    "    print('done')\n",
    "    return data\n",
    "\n",
    "@run\n",
    "def observations():\n",
    "    observations = []\n",
    "    for observation in (\n",
    "        Observation(**kwargs)\n",
    "        for kwargs in (\n",
    "            auto.json.loads(fetch('https://species.atlasofthesmokies.org/atbirecords/lexical_index.json'))\n",
    "        )['items']\n",
    "    ):\n",
    "        observations.append(observation)\n",
    "    \n",
    "    return observations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "id": "26d3e8c6",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-08-16T17:03:13.737911Z",
     "start_time": "2023-08-16T17:03:13.732181Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Observation(common_name='Blueridge Stone', irma_id='0029846', latin_name_ref='Perlesta frisoni', latin_name='Perlesta_frisoni')\n"
     ]
    }
   ],
   "source": [
    "@run(after=print)\n",
    "def observation(observations, /):\n",
    "    for observation in observations:\n",
    "        if observation.irma_id not in [\n",
    "            SPECIES,\n",
    "        ]:\n",
    "            continue\n",
    "        \n",
    "        return observation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "id": "2989ed92",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-08-16T17:03:13.895641Z",
     "start_time": "2023-08-16T17:03:13.740045Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "13\n",
      "len(tiles)=164\n",
      "[2184, 2185, 2186, 2187, 2188, 2189, 2190, 2191, 2192, 2193, 2194, 2195, 2196, 2197, 2198, 2199, 2200, 2201, 2202, 2203, 2204, 2205, 2206]\n",
      "[3222, 3223, 3224, 3225, 3226, 3227, 3228, 3229, 3230, 3231, 3232]\n"
     ]
    }
   ],
   "source": [
    "@run(scope='observation')\n",
    "def db(observation, /):\n",
    "    @auto.mediocreatbest.contextgenerator(call=lambda generator: lambda sql, /, **parameters: generator.send((sql, parameters)))\n",
    "    def db(observation: Observation=observation, /):\n",
    "        # root = auto.pathlib.Path('/mnt/seenas2/data/johns_nps_run/maxent/mbtiles/out')\n",
    "        # path = root / f'atlas-user.{observation.irma_id}_pink.mbtiles'\n",
    "\n",
    "        root = auto.pathlib.Path('/mnt/seenas2/data/atlas_run/outputs/mbtiles')\n",
    "        path = root / f'seelab.{observation.latin_name.lower()}_pink.mbtiles'\n",
    "        \n",
    "        with auto.sqlite3.connect(path) as db:\n",
    "            db.row_factory = auto.sqlite3.Row\n",
    "            \n",
    "            cursor = None\n",
    "            while True:\n",
    "                sql, parameters = yield cursor\n",
    "                cursor = db.execute(sql, parameters)\n",
    "    \n",
    "    return db\n",
    "\n",
    "@run(scope='observation', after=print)\n",
    "def z():\n",
    "    z = 15\n",
    "\n",
    "    z = Z\n",
    "    return z\n",
    "\n",
    "@auto.dataclasses.dataclass(eq=True, frozen=True)\n",
    "class ObservationTile:\n",
    "    coord: Coord\n",
    "    image: bytes = auto.dataclasses.field(repr=False)\n",
    "\n",
    "@run(scope='observation', after=lambda tiles: print(f'{len(tiles)=!r}'))\n",
    "def tiles(db, z, /):\n",
    "    with db() as db:\n",
    "        tiles = []\n",
    "        for tile in db(r'''\n",
    "            SELECT\n",
    "                tile_row AS y_tms,\n",
    "                tile_column AS x,\n",
    "                zoom_level AS z,\n",
    "                tile_data AS image\n",
    "            FROM tiles\n",
    "            WHERE zoom_level = :z\n",
    "        ''', z=z):\n",
    "            tiles.append(ObservationTile(\n",
    "                coord=Coord(\n",
    "                    z=tile['z'],\n",
    "                    y=2 ** tile['z'] - 1 - tile['y_tms'],\n",
    "                    x=tile['x'],\n",
    "                ),\n",
    "                image=tile['image'],\n",
    "            ))\n",
    "    \n",
    "    return tiles\n",
    "\n",
    "@run(scope='observation', after=print)\n",
    "def xs(tiles, /):\n",
    "    return sorted(set(tile.coord.x for tile in tiles))\n",
    "\n",
    "@run(scope='observation', after=print)\n",
    "def ys(tiles, /):\n",
    "    return sorted(set(tile.coord.y for tile in tiles))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "id": "1b2c3662",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-08-16T17:03:13.903594Z",
     "start_time": "2023-08-16T17:03:13.897856Z"
    }
   },
   "outputs": [],
   "source": [
    "def __stitch_tiles(tiles, /, size: int=128, flip=False):\n",
    "    auto.PIL; from PIL import Image\n",
    "    \n",
    "    xs = set(tile.coord.x for tile in tiles)\n",
    "    ys = set(tile.coord.y for tile in tiles)\n",
    "    \n",
    "    xs = sorted(xs)\n",
    "    ys = sorted(ys)\n",
    "    \n",
    "    nx = len(xs)\n",
    "    ny = len(ys)\n",
    "    \n",
    "    sz = size\n",
    "    \n",
    "    composite = Image.new('RGB', (nx*sz, ny*sz))\n",
    "    \n",
    "    for tile in tiles:\n",
    "        xi = xs.index(tile.coord.x)\n",
    "        yi = ys.index(tile.coord.y)\n",
    "        \n",
    "        with auto.io.BytesIO(tile.image) as f:\n",
    "            try:\n",
    "                image = Image.open(f)\n",
    "            except auto.PIL.UnidentifiedImageError:\n",
    "                continue\n",
    "\n",
    "            image.thumbnail((sz, sz))\n",
    "\n",
    "        # composite.paste(image, (yi*sz, xi*sz))\n",
    "        if flip==True:\n",
    "            composite.paste(image, (yi*sz, xi*sz))\n",
    "        else:\n",
    "            composite.paste(image, (xi*sz, yi*sz))\n",
    "            \n",
    "    \n",
    "    return composite"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "id": "a275135f",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-08-16T17:03:19.009430Z",
     "start_time": "2023-08-16T17:03:13.905578Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/jpeg": "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",
      "image/png": "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",
      "text/plain": [
       "<PIL.Image.Image image mode=RGB size=736x352>"
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "__stitch_tiles(auto.mediocreatbest.g['observation__tiles'], size=32)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "id": "fed9a65a",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-08-16T17:03:19.018444Z",
     "start_time": "2023-08-16T17:03:19.012292Z"
    }
   },
   "outputs": [],
   "source": [
    "@run(scope='observation', cond=False)\n",
    "def _(tiles, /):\n",
    "    \"\"\"Remove redundant pixels from tile data\"\"\"\n",
    "    \n",
    "    def Image(tile: Tile, /) -> auto.PIL.Image.Image:\n",
    "        image: bytes = tile.image\n",
    "        with auto.io.BytesIO(image) as f:\n",
    "            image = auto.PIL.Image.open(f)\n",
    "            image.load()\n",
    "        \n",
    "        return image\n",
    "    \n",
    "    tile = tiles[9]\n",
    "    image = Image(tile)\n",
    "    \n",
    "    image = auto.numpy.array(image)\n",
    "    assert len(image.shape) == 3 and image.shape[-1] == 4, \\\n",
    "        f\"\"\"Wrong shape: {image.shape=!r}\"\"\"\n",
    "    NR, NC, _ = image.shape\n",
    "\n",
    "    image = image[:NR, :NC, 0]\n",
    "    \n",
    "    auto.IPython.display.display(image)\n",
    "    \n",
    "    raise NotImplementedError"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "id": "e289a888",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-08-16T17:03:51.344698Z",
     "start_time": "2023-08-16T17:03:19.020671Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "points[0][[0, -1]]=ndarray(array([824832, 827647]), shape=(2,), dtype=dtype('int64'))\n",
      "points[1][[0, -1]]=ndarray(array([559104, 564991]), shape=(2,), dtype=dtype('int64'))\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "None"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "  0%|          | 0/253 [00:00<?, ?it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 253/253 [00:02<00:00, 106.46it/s]\n"
     ]
    }
   ],
   "source": [
    "@run(scope='observation')\n",
    "def interpolator(tiles, z, xs, ys, /):\n",
    "    res = 256\n",
    "    \n",
    "    # Thanks https://species.atlasofthesmokies.org/style.css\n",
    "    pinks = auto.numpy.array([\n",
    "        # Black, obviously.\n",
    "        # Represents 0-25%\n",
    "        [0, 0, 0],\n",
    "\n",
    "        #> #legend-pink-50 { background-color: #f069a3; }\n",
    "        # Represents 25-50%\n",
    "        [247, 105, 164],\n",
    "\n",
    "        #> #legend-pink-75 { background-color: #c31d8e; }\n",
    "        # Represents 50-75%\n",
    "        [196, 28, 142],\n",
    "\n",
    "        #> #legend-pink-100 { background-color: #752879; }\n",
    "        # Represents 75-100%\n",
    "        [121, 0, 124],\n",
    "    ], dtype=auto.numpy.uint8)\n",
    "    \n",
    "    @auto.mediocreatbest.coroutine\n",
    "    def display():\n",
    "        handle = auto.IPython.display.display(None, display_id=True)\n",
    "        \n",
    "        while True:\n",
    "            obj = yield\n",
    "            handle.update(obj)\n",
    "        \n",
    "    @auto.mediocreatbest.coroutine  # (call=lambda gen: lambda *, z, x, y: gen.send((z, x, y)))\n",
    "    def category() -> Generator[Optional[auto.numpy.ndarray], tuple[float, float, float], None]:\n",
    "        category = None\n",
    "        while True:\n",
    "            coord = yield category\n",
    "            \n",
    "            for tile in tiles:\n",
    "                if tile.coord == coord:\n",
    "                    break\n",
    "            \n",
    "            else:\n",
    "#                 print(f'No tile found: {coord=!r}')\n",
    "                category = None\n",
    "                continue\n",
    "\n",
    "#             (exists,) ,= db(r'''\n",
    "#                 SELECT EXISTS(SELECT 1 FROM tiles WHERE zoom_level = :z AND tile_column = :x AND tile_row = :y)\n",
    "#             ''', z=z, x=x, y=y)\n",
    "\n",
    "#             if not exists:\n",
    "#                 category = None\n",
    "#                 continue\n",
    "\n",
    "#             (image,) ,= db(r'''\n",
    "#                 SELECT tile_data FROM tiles WHERE zoom_level = :z AND tile_column = :x AND tile_row = :y\n",
    "#             ''', z=z, x=x, y=y)\n",
    "\n",
    "            with auto.io.BytesIO(tile.image) as f:\n",
    "                image = auto.PIL.Image.open(f)\n",
    "                image.load()\n",
    "            \n",
    "            image = image.convert('RGB')\n",
    "            image = yield image\n",
    "\n",
    "            rgb = auto.numpy.array(image)\n",
    "\n",
    "            assert rgb.shape == (res, res, 3), \\\n",
    "                f\"\"\"Wrong shape for observation tile image: {rgb.shape=!r}\"\"\"\n",
    "\n",
    "            rgb = rgb.reshape((res*res, 3))\n",
    "\n",
    "            diffs = auto.numpy.subtract(rgb[:, None, :], pinks[None, :, :], dtype=auto.numpy.float32)\n",
    "            assert diffs.shape == (res*res, len(pinks), 3)\n",
    "\n",
    "            dists = auto.numpy.linalg.norm(diffs, axis=-1)\n",
    "            assert dists.shape == (res*res, len(pinks))\n",
    "\n",
    "            category = auto.numpy.argmin(dists, axis=-1)\n",
    "            assert category.shape == (res*res,), \\\n",
    "                f\"\"\"Wrong shape: {category.shape=!r}\"\"\"\n",
    "\n",
    "            category = category.astype(auto.numpy.uint8)\n",
    "            category = category.reshape((res, res))\n",
    "\n",
    "    @auto.mediocreatbest.coroutine\n",
    "    def debounce(coroutine, /, *, rate: 'item/seconds'):\n",
    "        def now() -> 'seconds':\n",
    "            return auto.time.clock_gettime(auto.time.CLOCK_MONOTONIC)\n",
    "        \n",
    "        prev = float('-inf')\n",
    "        while True:\n",
    "            value = yield\n",
    "            if (curr := now()) - prev > 1.0 / rate:\n",
    "                prev = curr\n",
    "                coroutine.send(value)\n",
    "    \n",
    "    dz = int(auto.math.log2(res))\n",
    "    # assert z + dz == Tixel.z\n",
    "    points = (\n",
    "        auto.numpy.arange(\n",
    "            (min(ys) + 0) * 2 ** dz,\n",
    "            (max(ys) + 1) * 2 ** dz,\n",
    "        ),\n",
    "        auto.numpy.arange(\n",
    "            (min(xs) + 0) * 2 ** dz,\n",
    "            (max(xs) + 1) * 2 ** dz,\n",
    "        ),\n",
    "    )\n",
    "    print(f'{points[0][[0, -1]]=!r}')\n",
    "    print(f'{points[1][[0, -1]]=!r}')\n",
    "\n",
    "    og = z\n",
    "    z += dz\n",
    "    if z < Tixel.z:\n",
    "        dz = Tixel.z - z\n",
    "        print(f'{dz=!r}')\n",
    "        points = (\n",
    "            points[0] * 2 ** dz,\n",
    "            points[1] * 2 ** dz,\n",
    "        )\n",
    "        z += dz\n",
    "        print(f'{z=!r}')\n",
    "        \n",
    "        print(f'{points[0][0]=!r}')\n",
    "        print(f'{points[0][-1]=!r}')\n",
    "    \n",
    "    assert z == Tixel.z\n",
    "    \n",
    "    \n",
    "    values = auto.numpy.zeros(\n",
    "        shape=(\n",
    "            len(ys)*res,\n",
    "            len(xs)*res,\n",
    "        ),\n",
    "        dtype=auto.numpy.uint8,\n",
    "    )\n",
    "\n",
    "    \n",
    "    \n",
    "    with auto.contextlib.ExitStack() as stack:\n",
    "        category = stack.enter_context( auto.contextlib.closing(category()) )\n",
    "        display = stack.enter_context( auto.contextlib.closing(display()) )\n",
    "        display = stack.enter_context(auto.contextlib.closing( debounce(display, rate=1) ))\n",
    "        \n",
    "        for (yi, y), (xi, x) in auto.tqdm.tqdm(auto.itertools.product(\n",
    "            enumerate(ys),\n",
    "            enumerate(xs),\n",
    "        ), total=len(ys)*len(xs)):\n",
    "            image = category.send(Coord(\n",
    "                z=og,\n",
    "                # z=z,\n",
    "                x=x,\n",
    "                y=y,\n",
    "            ))\n",
    "\n",
    "            if image is None:\n",
    "                continue\n",
    "            \n",
    "            display.send(image)\n",
    "            \n",
    "            src = category.send(image)\n",
    "                \n",
    "            values[\n",
    "                slice(\n",
    "                    (yi + 0) * res,\n",
    "                    (yi + 1) * res,\n",
    "                ),\n",
    "                slice(\n",
    "                    (xi + 0) * res,\n",
    "                    (xi + 1) * res,\n",
    "                ),\n",
    "            ] = src\n",
    "    \n",
    "    return auto.scipy.interpolate.RegularGridInterpolator(\n",
    "        points=points,\n",
    "        values=values,\n",
    "        method='nearest',\n",
    "        bounds_error=False,\n",
    "        fill_value=0,\n",
    "    )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "id": "1b7666df",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-08-16T17:03:51.353542Z",
     "start_time": "2023-08-16T17:03:51.347943Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "ndarray(array([824832., 827647.]), shape=(2,), dtype=dtype('float64'))"
      ]
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "auto.mediocreatbest.g['observation__interpolator'].grid[0][[0, -1]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "id": "a56d5578",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-08-16T17:03:51.375469Z",
     "start_time": "2023-08-16T17:03:51.355668Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "len(arr)=2816\n",
      "len(arr)=256\n",
      "ndarray(array([..., 827637.]), shape=(256,), dtype=dtype('float64'))\n",
      "len(arr)=5888\n",
      "len(arr)=256\n",
      "ndarray(array([..., 564969.]), shape=(256,), dtype=dtype('float64'))\n"
     ]
    },
    {
     "data": {
      "image/jpeg": "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",
      "image/png": "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",
      "text/plain": [
       "<PIL.Image.Image image mode=L size=256x256>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "@run(scope='observation')\n",
    "def __view(interpolator, /):\n",
    "    rs, cs = interpolator.grid\n",
    "    \n",
    "    def decimate(\n",
    "        arr: auto.numpy.ndarray,\n",
    "        /,\n",
    "        *,\n",
    "        length: int,\n",
    "    ) -> auto.numpy.ndarray:\n",
    "        print(f'{len(arr)=!r}')\n",
    "        stride = int(auto.math.floor( len(arr) / length ))\n",
    "        arr = arr[::stride]\n",
    "        arr = arr[:length]\n",
    "        print(f'{len(arr)=!r}')\n",
    "        print(f'{arr}')\n",
    "        return arr\n",
    "    \n",
    "    rs = decimate(rs, length=256)\n",
    "    cs = decimate(cs, length=256)\n",
    "    \n",
    "    grid = auto.numpy.hstack(tuple(\n",
    "        v.reshape((-1, 1))\n",
    "        for v in auto.numpy.meshgrid(\n",
    "            rs,\n",
    "            cs,\n",
    "            indexing='ij',\n",
    "        )\n",
    "    ))\n",
    "    assert grid.shape == (len(rs) * len(cs), 2)\n",
    "    \n",
    "    confidence = (interpolator(grid, method='linear') * 255.0 / 4.0).astype(auto.numpy.uint8)\n",
    "    confidence = confidence.reshape((len(rs), len(cs)))\n",
    "    \n",
    "    image = auto.PIL.Image.fromarray(confidence, mode='L')\n",
    "    \n",
    "    auto.IPython.display.display(image)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "id": "4f0d0c93",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-08-16T17:03:51.396720Z",
     "start_time": "2023-08-16T17:03:51.377473Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "r=826250 c=562518\n"
     ]
    },
    {
     "data": {
      "image/jpeg": "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",
      "image/png": "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",
      "text/plain": [
       "<PIL.Image.Image image mode=L size=257x257>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "## @Tile.from_.register(Location)\n",
    "@auto.mediocreatbest.doctest\n",
    "def convert_location_to_tile(*, lat: Degree, lng: Degree, zoom: int, math=auto.math) -> tuple[int, int]:\n",
    "    r\"\"\"\n",
    "    \n",
    "    >>> convert_location_to_tile(lat=35.6, lng=-83.52, zoom=11)\n",
    "    (807, 548)\n",
    "    >>> convert_location_to_tile(lat=35.0, lng=-84.5, zoom=15)\n",
    "    (12979, 8692)\n",
    "    >>> convert_location_to_tile(lat=36.25, lng=-82.5, zoom=15)\n",
    "    (12839, 8874)\n",
    "    \n",
    "    \"\"\"\n",
    "    # Thanks https://stackoverflow.com/a/72476578\n",
    "    \n",
    "    #> lat_rad = math.radians(lat_deg)\n",
    "    lat_rad = math.radians(lat)\n",
    "    \n",
    "    #> n = 2.0 ** zoom\n",
    "    n = 2.0 ** zoom\n",
    "    \n",
    "    #> xtile = int((lon_deg + 180.0) / 360.0 * n)\n",
    "    col = int((lng + 180.0) / 360.0 * n)\n",
    "    \n",
    "    #> ytile = int((1.0 - math.asinh(math.tan(lat_rad)) / math.pi) / 2.0 * n)\n",
    "    row = int((1.0 - math.asinh(math.tan(lat_rad)) / math.pi) / 2.0 * n)\n",
    "    \n",
    "    #> return (xtile, ytile)\n",
    "    return row, col\n",
    "\n",
    "\n",
    "@run(scope='observation')\n",
    "def __view(interpolator, /):\n",
    "    lat, lng = (\n",
    "        (35.6201452, -83.4372325)  # Clingman's Dome\n",
    "    )\n",
    "    \n",
    "    r, c = convert_location_to_tile(\n",
    "        lat=lat,\n",
    "        lng=lng,\n",
    "        zoom=Tixel.z,\n",
    "    )\n",
    "    print(f'{r=!r} {c=!r}')\n",
    "    \n",
    "    k = 2\n",
    "    rs = auto.numpy.arange(r-k*128, r+k*128+1, k)\n",
    "    cs = auto.numpy.arange(c-k*128, c+k*128+1, k)\n",
    "    \n",
    "#     rs, cs = interpolator.grid\n",
    "    \n",
    "#     def decimate(\n",
    "#         arr: auto.numpy.ndarray,\n",
    "#         /,\n",
    "#         *,\n",
    "#         length: int,\n",
    "#     ) -> auto.numpy.ndarray:\n",
    "#         print(f'{len(arr)=!r}')\n",
    "#         stride = int(auto.math.floor( len(arr) / length ))\n",
    "#         arr = arr[::stride]\n",
    "#         arr = arr[:length]\n",
    "#         return arr\n",
    "    \n",
    "#     rs = decimate(rs, length=256)\n",
    "#     cs = decimate(cs, length=256)\n",
    "    \n",
    "    grid = auto.numpy.hstack(tuple(\n",
    "        v.reshape((-1, 1))\n",
    "        for v in auto.numpy.meshgrid(\n",
    "            rs,\n",
    "            cs,\n",
    "            indexing='ij',\n",
    "        )\n",
    "    ))\n",
    "    assert grid.shape == (len(rs) * len(cs), 2)\n",
    "    \n",
    "    confidence = (interpolator(grid, method='linear').astype(auto.numpy.float32) * 255.0 / 4.0).astype(auto.numpy.uint8)\n",
    "    confidence = confidence.reshape((len(rs), len(cs)))\n",
    "    \n",
    "    image = auto.PIL.Image.fromarray(confidence, mode='L')\n",
    "    \n",
    "    auto.IPython.display.display(image)\n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8e24c44f",
   "metadata": {},
   "source": [
    "## Visualize"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "id": "01449241",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-08-16T17:28:08.202738Z",
     "start_time": "2023-08-16T17:28:06.107846Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAgwAAAHWCAYAAAAby9HbAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8g+/7EAAAACXBIWXMAAA9hAAAPYQGoP6dpAACrQklEQVR4nOzdd1QU198G8Gd3YYsgiEoTELCBIgpBRbDGRgzWaGyJNRp7jUnEYP8pKor6irFF0djFHjQo1kQxUUSMvYslgIUqStu97x+4E8ZdYHepC9/POXOOO3tn5s6Au5eZe+8jYIwxEEIIIYQUQFjWFSCEEEJI+UcNBkIIIYQUihoMhBBCCCkUNRgIIYQQUihqMBBCCCGkUNRgIIQQQkihqMFACCGEkEJRg4EQQgghhaIGAyGEEEIKRQ2GCkAgEGDu3LllcuzAwEDUqVMHIpEIbm5uRd7fsGHDYGxsXPSK6aFhw4bBwcGhrKtRYcydOxcCgaBY9/nkyRMIBAJs2bKlRI9DSHlEDYYPrl+/jr59+8Le3h5SqRQ2Njbo3LkzVq9eXdZVK7dOnDiBH374Aa1atUJISAgWLVpU1lUq9/7991/MnTsXMTExZV0V8pGzZ8/iiy++gJWVFcRiMSwsLNC9e3ccOHCgrKtWbn3ceNLVli1bIBAIuEUqlaJWrVrw8fHB//3f/yEtLa3olSVFZlDWFSgPIiMj8emnn6J27doYNWoUrKys8OzZM/z1119YtWoVJk6cWNZVLJdOnz4NoVCITZs2QSwWl3V19MK///6LefPmwcHBQeWOzMaNG6FQKMqmYpXcnDlzMH/+fNSvXx+jR4+Gvb093rx5g2PHjqFPnz7YsWMHBg0apHZbf39/zJgxo5RrXDHNnz8fjo6OyM7ORnx8PM6ePYspU6YgKCgIR44cQZMmTcq6ipUaNRgALFy4EKamprh8+TKqVavGe+/ly5dlUyk98PLlS8hksgrZWMjJyYFCoSjVczM0NCy1YxWXsrhOxW3fvn2YP38++vbti507d/J+Dt9//z2OHz+O7OzsfLc3MDCAgQF9lBaHrl27olmzZtxrPz8/nD59Gt26dUOPHj1w+/ZtyGSyMqxh5UaPJAA8fPgQLi4uKo0FALCwsOC9DgkJQYcOHWBhYQGJRIJGjRph7dq1Kts5ODigW7duOHv2LJo1awaZTAZXV1ecPXsWAHDgwAG4urpCKpXCw8MDV69e5W2vfJb/6NEj+Pj4wMjICLVq1cL8+fOhScDoixcvMGLECFhaWkIikcDFxQWbN2/W6Hrk5ORgwYIFqFu3LiQSCRwcHDBz5kxkZmZyZQQCAUJCQpCens7dRizs1mRoaCg8PDwgk8lQs2ZNfP3113jx4oXaspqc9+7du+Hh4YGqVavCxMQErq6uWLVqFa9McnIypkyZAjs7O0gkEtSrVw9Llizh/SWvfC69bNkyrFy5kjvvq1evwsDAAPPmzVOp3927dyEQCBAcHAwASExMxPTp0+Hq6gpjY2OYmJiga9euuHbtGrfN2bNn0bx5cwDA8OHDVa6buj4M6enp+O6777j6Ozk5YdmyZSrXQiAQYMKECTh06BAaN27M/czDw8ML+InkysrKwuzZs+Hh4QFTU1MYGRmhTZs2OHPmDK9cftfp1q1bAHLvOLVp0wZGRkaoVq0aevbsidu3b/P2kV8/DXX9ALQ5p/Pnz6N58+aQSqWoW7cu1q9fX+h5K82aNQvVq1fH5s2b1TbafHx80K1bt3y3L2rdlZ8Reete0D5DQ0PRqFEjyGQyeHl54fr16wCA9evXo169epBKpWjfvj2ePHnC2/7PP//El19+idq1a0MikcDOzg5Tp07F+/fveeWUnz0vXrxAr169YGxsDHNzc0yfPh1yubzAa5mWloYpU6bAwcEBEokEFhYW6Ny5M6KjowvcriAdOnTArFmzEBsbi+3bt/Pe0+R3Tnkt7927h6+//hqmpqYwNzfHrFmzwBjDs2fP0LNnT5iYmMDKygrLly9XqUNmZibmzJmDevXqcdfuhx9+4H0mVgqMsC5durCqVauy69evF1q2efPmbNiwYWzFihVs9erVrEuXLgwACw4O5pWzt7dnTk5OzNrams2dO5etWLGC2djYMGNjY7Z9+3ZWu3ZttnjxYrZ48WJmamrK6tWrx+RyObf90KFDmVQqZfXr12eDBw9mwcHBrFu3bgwAmzVrFu9YANicOXO41/Hx8czW1pbZ2dmx+fPns7Vr17IePXowAGzFihWFnuPQoUMZANa3b1+2Zs0aNmTIEAaA9erViyuzbds21qZNGyaRSNi2bdvYtm3b2MOHD/PdZ0hICAPAmjdvzlasWMFmzJjBZDIZc3BwYElJSVqf94kTJxgA1rFjR7ZmzRq2Zs0aNmHCBPbll19yZdLT01mTJk1YjRo12MyZM9m6devYkCFDmEAgYJMnT+bKPX78mAFgjRo1YnXq1GGLFy9mK1asYLGxsaxDhw6sUaNGKuczb948JhKJWHx8PGOMscuXL7O6deuyGTNmsPXr17P58+czGxsbZmpqyl68eMH9XObPn88AsG+//Vblug0dOpTZ29tzx1AoFKxDhw5MIBCwkSNHsuDgYNa9e3cGgE2ZMoVXHwCsadOmzNrami1YsICtXLmS1alTh1WpUoW9fv26gJ82Y69evWLW1tZs2rRpbO3atWzp0qXMycmJGRoasqtXr2p0nSIiIpiBgQFr0KABW7p0KZs3bx6rWbMmMzMzY48fP+b9fPOeo9KcOXPYxx9Hmp7TP//8w2QyGatduzYLCAhgCxYsYJaWlqxJkyYq+/zYvXv3GAA2YsSIAst9fA1CQkKKpe7R0dFMIpEwBwcHtnjxYrZw4UJWq1Yt1rRpU7X7bNKkCbOzs+N9dtSuXZsFBwezRo0aseXLlzN/f38mFovZp59+ytt+4sSJ7PPPP2eLFi1i69evZ9988w0TiUSsb9++vHLK/4MuLi5sxIgRbO3ataxPnz4MAPv5559V6pT3WgwaNIiJxWI2bdo09ssvv7AlS5aw7t27s+3btxd4XZWfD5cvX1b7/rNnz7jPJCVNf+eUPx83Nzc2cOBA9vPPPzNfX18GgAUFBTEnJyc2duxY9vPPP7NWrVoxAOzcuXPc9nK5nHXp0oVVqVKFTZkyha1fv55NmDCBGRgYsJ49exZ4XhUNNRhY7pePSCRiIpGIeXl5sR9++IEdP36cZWVlqZR99+6dyjofHx9Wp04d3jp7e3sGgEVGRnLrjh8/zgAwmUzGYmNjufXr169nANiZM2e4dcov7YkTJ3LrFAoF8/X1ZWKxmL169Ypb/3GD4ZtvvmHW1tYqXxQDBgxgpqamas9BKSYmhgFgI0eO5K2fPn06A8BOnz7Nq6ORkVG++1LKyspiFhYWrHHjxuz9+/fc+rCwMAaAzZ49W+vznjx5MjMxMWE5OTn5HnfBggXMyMiI3bt3j7d+xowZTCQSsadPnzLG/vsSMDExYS9fvuSVVf5sPm5MNmrUiHXo0IF7nZGRwWvwKfcrkUjY/PnzuXWXL19W+ZDNe+55v0wPHTrEALD//e9/vHJ9+/ZlAoGAPXjwgFsHgInFYt66a9euMQBs9erV6i4PJycnh2VmZvLWJSUlMUtLS94XaUHXyc3NjVlYWLA3b97wji8UCtmQIUPyPUel/L50NTmnXr16MalUyvs/devWLSYSiQptMBw+fFjjhjRj2jUYNKl79+7dWZUqVbhGJWOM3b9/nxkYGKjdp0Qi4X0ZKn8/raysWGpqKrfez8+PAeCVVff/PiAggAkEAt61U/4fzPt7yxhj7u7uzMPDI58rk8vU1JSNHz++wDLqFNZgUO7b3d2de63p75zy5/Ptt99y63JycpitrS0TCARs8eLF3PqkpCQmk8nY0KFDuXXbtm1jQqGQ/fnnn7z6rFu3jgFgFy5c0Pp89RU9kgDQuXNnXLx4ET169MC1a9ewdOlS+Pj4wMbGBkeOHOGVzfv8LCUlBa9fv0a7du3w6NEjpKSk8Mo2atQIXl5e3GtPT08AubfYateurbL+0aNHKnWbMGEC92/lLcmsrCycPHlS7bkwxrB//350794djDG8fv2aW3x8fJCSklLg7cFjx44BAKZNm8Zb/9133wEAjh49mu+2+YmKisLLly8xbtw4SKVSbr2vry+cnZ3V7rOw865WrRrS09MRERGR73FDQ0PRpk0bmJmZ8a5Dp06dIJfL8ccff/DK9+nTB+bm5rx1X3zxBQwMDLBnzx5u3Y0bN3Dr1i3079+fWyeRSCAU5v53ksvlePPmDYyNjeHk5KTz7dhjx45BJBJh0qRJvPXfffcdGGP4/fffees7deqEunXrcq+bNGkCExMTtb9XeYlEIq4PgkKhQGJiInJyctCsWTO1df/4OsXFxSEmJgbDhg1D9erVecfv3Lkz9zuli8LOSS6X4/jx4+jVqxfv/1TDhg3h4+NT6P5TU1MBAFWrVtW5jvnRpO4nT55Er169UKtWLa5cvXr10LVrV7X77NixI++RjvKzo0+fPrxzUPeZkvezKz09Ha9fv4a3tzcYYyqPRAFgzJgxvNdt2rQp9HepWrVq+Pvvv/Hvv/8WWE4XxsbG3GgJXX7nRo4cyf1bJBKhWbNmYIzhm2++4dXfycmJd56hoaFo2LAhnJ2deZ8jHTp0AACVR3cVGTUYPmjevDkOHDiApKQkXLp0CX5+fkhLS0Pfvn25Z7QAcOHCBXTq1Il7ZmZubo6ZM2cCgEqDIe8HGACYmpoCAOzs7NSuT0pK4q0XCoWoU6cOb12DBg0AQOX5pNKrV6+QnJyMDRs2wNzcnLcMHz4cQMEdOWNjYyEUClGvXj3eeisrK1SrVg2xsbH5blvQPgHAyclJ5T1nZ2eVfWpy3uPGjUODBg3QtWtX2NraYsSIESrPh+/fv4/w8HCV69CpUycAqtfB0dFRpX41a9ZEx44dsXfvXm7dnj17YGBggC+++IJbp1AosGLFCtSvXx8SiQQ1a9aEubk5/vnnH5XfC03FxsaiVq1aKl9mDRs25N7P6+PfNwAwMzNT+b1SZ+vWrWjSpAmkUilq1KgBc3NzHD16VG3dP75OBf18GzZsiNevXyM9Pb3QOqhT2Dm9evUK79+/R/369VXKqavPx0xMTACgRIbtFVb3ly9f4v379yr/1wCoXadun9p8pjx9+pT7glX2S2jXrh0A1c8uqVSq0njW5Hdp6dKluHHjBuzs7NCiRQvMnTu30EaGpt6+fcv9X9Dld07dtZNKpahZs6bK+rznef/+fdy8eVPlc0T5mVSZOsZT196PiMViNG/eHM2bN0eDBg0wfPhwhIaGYs6cOXj48CE6duwIZ2dnBAUFwc7ODmKxGMeOHcOKFStUhsSJRCK1x8hvPdOgM2NhlHX4+uuvMXToULVlNBmaVN4norGwsEBMTAyOHz+O33//Hb///jtCQkIwZMgQbN26FUDutejcuTN++OEHtftQ/odXyq/39YABAzB8+HDExMTAzc0Ne/fuRceOHXkfNIsWLcKsWbMwYsQILFiwANWrV4dQKMSUKVNKbaikrr9X27dvx7Bhw9CrVy98//33sLCwgEgkQkBAAB4+fKhSvii91PP7vcqvM11J/l8BchusALiOg8WpJOqu62eKXC5H586dkZiYiB9//BHOzs4wMjLCixcvMGzYMI0/uwrTr18/tGnTBgcPHsSJEycQGBiIJUuW4MCBA/neNdHE8+fPkZKSkm9DShPqzkmTn5FCoYCrqyuCgoLUlv24sVaRUYOhAMrhPXFxcQCA3377DZmZmThy5AivtVpSt6QUCgUePXrE+2K7d+8eAOQ7I6C5uTmqVq0KuVzO/SWtDXt7eygUCty/f5/7SxYAEhISkJycDHt7e532CeSOLFDexlO6e/euyj41PW+xWIzu3buje/fuUCgUGDduHNavX49Zs2ahXr16qFu3Lt6+favTdcirV69eGD16NPdY4t69e/Dz8+OV2bdvHz799FNs2rSJtz45OZnXsNCmIWZvb4+TJ08iLS2Nd5fhzp073PvFYd++fahTpw4OHDjAq9+cOXM0rieQ+7P82J07d1CzZk0YGRkByP0rNTk5WaWcLneugNzfd5lMhvv376u8p64+H2vQoAGcnJxw+PBhrFq1qlRnGbWwsIBUKsWDBw9U3lO3riiuX7+Oe/fuYevWrRgyZAi3vqBHerqytrbGuHHjMG7cOLx8+RKffPIJFi5cWKQGw7Zt2wCAe8ykze9cUdWtWxfXrl1Dx44dy/0fUiWNHkkg9wtfXatf+RxMedtL2RrNWzYlJQUhISElVjflsD3lcYODg2FoaIiOHTuqLS8SidCnTx/s378fN27cUHn/1atXBR7v888/BwCsXLmSt17Zuvb19dWm+gByG14WFhZYt24dbxjS77//jtu3b6vdZ2Hn/ebNG155oVDI3TlRHqNfv364ePEijh8/rrL/5ORk5OTkaFT/atWqwcfHB3v37sXu3bshFovRq1cvXhmRSKTyOxQaGqoybFT5IabuS/Njn3/+OeRyOe9aAMCKFSsgEAiK9AGcl7rf67///hsXL17UaHtra2u4ublh69atvPO6ceMGTpw4wf1OAbkfvikpKfjnn3+4dXFxcTh48KDOdffx8cGhQ4fw9OlTbv3t27fV/tzVmTdvHt68eYORI0eq/Z04ceIEwsLCdKpfQUQiETp16oRDhw7xnvk/ePBApX9KcRwL4P+MGWMqw5CLQi6XqzzasLCwQK1atYo0/PD06dNYsGABHB0d8dVXXwHQ7neuqPr164cXL15g48aNKu+9f/9e58dt+ojuMACYOHEi3r17h969e8PZ2RlZWVmIjIzEnj174ODgwD3779KlC/dX7ejRo/H27Vts3LgRFhYW3F2I4iSVShEeHo6hQ4fC09MTv//+O44ePYqZM2eqPF/Ma/HixThz5gw8PT0xatQoNGrUCImJiYiOjsbJkyeRmJiY77ZNmzbF0KFDsWHDBiQnJ6Ndu3a4dOkStm7dil69euHTTz/V+jwMDQ2xZMkSDB8+HO3atcPAgQORkJCAVatWwcHBAVOnTtX6vEeOHInExER06NABtra2iI2NxerVq+Hm5sbdGfn+++9x5MgRdOvWDcOGDYOHhwfS09Nx/fp17Nu3D0+ePFF5fpmf/v374+uvv8bPP/8MHx8flTk7unXrhvnz52P48OHw9vbG9evXsWPHDpW+GHXr1kW1atWwbt06VK1aFUZGRvD09FTbf6J79+749NNP8dNPP+HJkydo2rQpTpw4gcOHD2PKlCm8DnVF0a1bNxw4cAC9e/eGr68vHj9+jHXr1qFRo0Z4+/atRvsIDAxE165d4eXlhW+++Qbv37/H6tWrYWpqyss5GTBgAH788Uf07t0bkyZNwrt377B27Vo0aNBA586h8+bNQ3h4ONq0aYNx48YhJycHq1evhouLC69hkp/+/fvj+vXrWLhwIa5evYqBAwdyMz2Gh4fj1KlT2Llzp051K8zcuXNx4sQJtGrVCmPHjuUaiI0bNy7W6cOdnZ1Rt25dTJ8+HS9evICJiQn279+vUf8WTaWlpcHW1hZ9+/ZF06ZNYWxsjJMnT+Ly5ctq5zZQ5/fff8edO3eQk5ODhIQEnD59GhEREbC3t8eRI0d4naY1/Z0rqsGDB2Pv3r0YM2YMzpw5g1atWkEul+POnTvYu3cvjh8/zptsqkIr5VEZ5dLvv//ORowYwZydnZmxsTETi8WsXr16bOLEiSwhIYFX9siRI6xJkyZMKpUyBwcHtmTJErZ582aVIUz29vbM19dX5VgAVIYdKYdqBQYGcuuUQxYfPnzIjQG2tLRkc+bMURm+h4+GVTLGWEJCAhs/fjyzs7NjhoaGzMrKinXs2JFt2LCh0OuRnZ3N5s2bxxwdHZmhoSGzs7Njfn5+LCMjg1dO02GVSnv27GHu7u5MIpGw6tWrs6+++oo9f/5c7T4LO+99+/axLl26MAsLCyYWi1nt2rXZ6NGjWVxcHG9/aWlpzM/Pj9WrV4+JxWJWs2ZN5u3tzZYtW8YNm1V3/T+WmprKZDIZA6B2THlGRgb77rvvmLW1NZPJZKxVq1bs4sWLrF27dqxdu3a8socPH2aNGjXihs4ph+ipG3KYlpbGpk6dymrVqsUMDQ1Z/fr1WWBgIFMoFLxy6n6vGMv9Pcw7REwdhULBFi1axOzt7ZlEImHu7u4sLCxMpT6FXaeTJ0+yVq1aMZlMxkxMTFj37t3ZrVu3VMqdOHGCNW7cmInFYubk5MS2b9+e79BETc/p3LlzzMPDg4nFYlanTh22bt06tfssyKlTp1jPnj2ZhYUFMzAwYObm5qx79+7s8OHDKtdAk2GVmtb91KlTzN3dnYnFYla3bl32yy+/sO+++45JpdJC95nfz+TMmTMMAAsNDeXW3bp1i3Xq1IkZGxuzmjVrslGjRnFDPfOeT37/rwu7npmZmez7779nTZs2ZVWrVmVGRkasadOmKnM3qKMcVqlcxGIxs7KyYp07d2arVq3iDRnNS5PfOWW98w5FL+g827Vrx1xcXHjrsrKy2JIlS5iLiwuTSCTMzMyMeXh4sHnz5rGUlJRCz6+iEDBWTL2HSLEaNmwY9u3bp/FfeISQiqNXr164efOm2r4ZhJQV6sNACCFl6OOpme/fv49jx46hffv2ZVMhQvJBfRgIIaQM1alTB8OGDUOdOnUQGxuLtWvXQiwW5zscmJCyQg0GQggpQ5999hl27dqF+Ph4SCQSeHl5YdGiRWonoyKkLNEjiXJqy5Yt1H+BkEogJCQET548QUZGBlJSUhAeHo5PPvmkrKtFyrG1a9dyU42bmJjAy8ur0KG4oaGhcHZ2hlQqhaurq05Ttpdpg0Eul2PWrFlwdHSETCZD3bp1sWDBAm6scHZ2Nn788Ue4urpyMcdDhgxRO0/50aNH4enpCZlMBjMzM5Vx8soo4bzL7t27eWV27NiBpk2bokqVKrC2tsaIESN44/2zs7Mxf/581K1bF1KpFE2bNtUoPpgQQggpLra2tli8eDGuXLmCqKgodOjQAT179sTNmzfVlo+MjMTAgQPxzTff4OrVq+jVqxd69eqldq6eApXlEI2FCxeyGjVqsLCwMPb48WMWGhrKjI2N2apVqxhjjCUnJ7NOnTqxPXv2sDt37rCLFy+yFi1aqCSm7du3j5mZmbG1a9eyu3fvsps3b7I9e/bwyuDD0KG4uDhuyZuceP78eSYUCtmqVavYo0eP2J9//slcXFxY7969uTI//PADq1WrFjt69Ch7+PAh+/nnn5lUKmXR0dEleJUIIYSQgpmZmbFffvlF7Xv9+vVTGebv6enJRo8erdUxyrQPQ2RkJHr27MnN9Ofg4IBdu3bh0qVLAHJDQD6eujQ4OBgtWrTA06dPUbt2beTk5GDy5MkIDAzkpY41atRI5XjVqlWDlZWV2rpcvHgRDg4OXDKgo6MjRo8ejSVLlnBltm3bhp9++ombRWzs2LE4efIkli9fju3btxd6vgqFAv/++y+qVq1a6acYJYSQksAYQ1paGmrVqsUlyJa0jIwMZGVlFWkfjDGV7wWJRAKJRFLgdnK5HKGhoUhPT+elI+d18eJFlQRi5Qyp2layzCxcuJDZ29uzu3fvMsYYi4mJYRYWFmonxlGKiIhgAoGAmyzj77//ZgDY5s2bmZubG7OysmKfffYZu379Om87AKxWrVqsRo0arHnz5mzTpk28yW/Onz/PDA0N2dGjR5lCoWDx8fGsbdu2bNSoUVyZ6tWrq7TgvvrqK5XJdvLz7Nkz3uQktNBCCy20lMzy7NkzjT6Xi+r9+/fMykJU5PoaGxurrPt4Qr68/vnnH2ZkZMREIhEzNTVlR48ezbesoaEh27lzJ2/dmjVrmIWFhVbnWqZ3GGbMmIHU1FQ4OztDJBJBLpdj4cKF3HzhH8vIyMCPP/6IgQMHcrG0yujUuXPnIigoCA4ODli+fDnat2+Pe/fucVnp8+fPR4cOHVClShWcOHEC48aNw9u3b7k7Cq1atcKOHTvQv39/ZGRkICcnB927d8eaNWu44/v4+CAoKAht27ZF3bp1cerUKRw4cCDfpL3MzEzeHOrsQ9+M1vgcBjAs4tUjhBDysRxk4zyOqcTCl5SsrCzEv5Qj9ooDTKrqdkcjNU0Be48nePbsGffdBqDAuwtOTk6IiYlBSkoK9u3bh6FDh+LcuXNq764XlzJtMOzduxc7duzAzp074eLigpiYGEyZMgW1atVSiWbOzs5Gv379wBjD2rVrufXKWNaffvoJffr0AZDb69jW1hahoaEYPXo0AGDWrFncNu7u7khPT0dgYCDXYLh16xYmT56M2bNnw8fHB3Fxcfj+++8xZswYLoFw1apVGDVqFJydnSEQCFC3bl0MHz4cmzdvVnt+AQEBmDdvnsp6AxjCQEANBkIIKXa5f5eV+mNf46oCGFfV7ZgK5G6nHPWgCbFYzMV9e3h44PLly1i1ahXWr1+vUtbKygoJCQm8dQkJCfk+os9PmY6S+P777zFjxgwMGDAArq6uGDx4MKZOnYqAgABeOWVjITY2FhEREbwLam1tDYDfZ0EikaBOnTq89LqPeXp64vnz59wdgICAALRq1Qrff/89mjRpAh8fH/z888/YvHkzFyxlbm6OQ4cOIT09HbGxsbhz5w6MjY1VAoaU/Pz8kJKSwi3Pnj3T7UIRQggp1+RMUaSlqBQKRb6poF5eXjh16hRvXURERL59HvJTpncY3r17p9IpRSQScXcNgP8aC/fv38eZM2dQo0YNXnkPDw9IJBLcvXsXrVu35rZ58uQJl5muTkxMDMzMzLhbPu/evYOBAf9yqIuEBXLTFG1sbJCdnY39+/ejX79+ao+hSYeVfAkEEIjFucfPzgEU6h97EEIIKXsKMCjACi+Yz7ba8PPzQ9euXVG7dm2kpaVh586dOHv2LBfpPmTIENjY2HB/fE+ePBnt2rXD8uXL4evri927dyMqKgobNmzQ6rhl2mDo3r07Fi5ciNq1a8PFxQVXr15FUFAQRowYASD3i79v376Ijo5GWFgY5HI54uPjAQDVq1eHWCyGiYkJxowZgzlz5sDOzg729vYIDAwEAHz55ZcAgN9++w0JCQlo2bIlpFIpIiIisGjRIkyfPp1Xl1GjRmHt2rXcI4kpU6agRYsWqFWrFgDg77//xosXL+Dm5oYXL15g7ty5UCgUJTKFq6hmTcgdrcAMRTD8Nwk5sc+p0UAIIQQvX77EkCFDEBcXB1NTUzRp0gTHjx9H586dAQBPnz7l/THu7e2NnTt3wt/fHzNnzkT9+vVx6NAhNG7cWKvjlmlaZVpaGmbNmoWDBw/i5cuXqFWrFgYOHIjZs2dDLBbjyZMncHR0VLvtmTNnuHCW7Oxs+Pn5Ydu2bXj//j08PT2xcuVKuLi4AADCw8Ph5+eHBw8egDGGevXqYezYsRg1ahTvoq5evRrr1q3D48ePUa1aNXTo0AFLliyBjY0NAODcuXMYO3YsHj16BGNjY3z++edYvHgx16AoTGpqKkxNTdEePQvtwyCqXwdJzSyQIxWg+u10CKJugeXkaHQcQgiprHJYNs7iMFJSUjTuD1AUys/1f+/aFqnTYy2n56VWZ11RvHUp0rrB0Dy3wWB2+x2El29Sg4EQQgpRVg2GZ3dsitRgsHN+Ue4bDBQ+RQghhBRRafZhKCsUPkUIIYSQQtEdhrImEEBUsyZQjT/JiMJYBtnLbDCRAAaJ6ZAr9KMFqg2RmRlQoxqQZ7y0ICML8pevwPIZHiSQSCAyrwkmyzP6hDEgKQXyxKTcfxNCSClTgEFOdxhKTnlLq1yzZg0aNmwImUwGJycn/Prrr/nWfffu3RAIBCrH0ZZALIbc0QrJHhZIav7fklVDCtmdeMj+vg/Fk2cVb4SEUARmY4mUTyx55/3OxRrCAp7hCY2N8N7ZirdNsoclmJ0VIKAbZoSQsqF8JKHrog/K9A7DkiVLsHbtWmzduhUuLi6IiorC8OHDYWpqikmTJuHdu3eIjo7GrFmz0LRpUyQlJWHy5Mno0aMHoqKiuP3s378fo0aNwqJFi9ChQwfk5OSoje0MCQnBZ599xr2uVq0a9++1a9fCz88PGzduRPPmzXHp0iWMGjUKZmZm6N69O28/T548wfTp09GmTZtiuQ7MUIRsmQDIM0kYEwnA3r6FPDmlWI5RHjFDEXKkAijy/BbKJQIIRAV88QtFUEiEyJHmuSshz92XQChAMcx/UnQCAQQf5vBQYgpW8Rp9hBCOnDHIdbzDqet2pY3SKj/Ytm0bRo8ejf79+wMA6tSpg8uXL2PJkiW8BoNcLsdXX32FefPm4c8//0RycnKRrgHLzoHhi0RUzzYFhP99CYoS06F4n1GkfZdrTAHRyySY3RaCifKcd1omFOnv8t/s3TtUeZwCyRspt04gZxDFJyEnn0yP0mZgZQm5TU0wg/8aPsK3WRA8/Rfy1NQyrBkhhOiuTBsM3t7e2LBhA+7du4cGDRrg2rVrOH/+PIKCgvLdJiUlBQKBgLs7EB0djRcvXkAoFMLd3R3x8fFwc3NDYGCgyqQU48ePx8iRI1GnTh2MGTMGw4cP5+Ybz8zMhFQq5ZWXyWS4dOkSsrOzYWiYOwxy/vz5sLCwwDfffIM///yzwPP7OHwqVd2XhUKOnKcvIHjOf8wir+h/kTKGnH/jIEh4mffGSqHnrUhPB+48hEDIn7M9Ry4vH/0XBAIozKsh2dkYcvF/dZQmyWCSlApQg4GQCknxYdF1W31AaZUfwqd8fHzwyy+/oFevXvjkk09w5coV/PLLL8jOzsbr169hbW2N8+fPY9OmTYiJidHo/PILn1KhkJePW+mljTHd5pYo79dLKIRCxH/UwkTgde4khFQs8iJ0etR1u9JGaZUfGgyzZs1CfHw8WrZsCcYYLC0tMXToUCxduhRCoRBpaWkYPHgwNm7ciJo1a2p0fn5+fpg2bRr3OjU1FXZ2djpcKUIIIaRslWmDIW9aJQC4uroiNjYWAQEBvAZD3rTK06dPF1ta5YIFC5CZmQmJRAKZTIbNmzdj/fr1SEhIgLW1NTZs2ICqVavC3Nwc//zzD548ecLrz6BsrBgYGODu3buoW7cu7xhFCp8ihBCiN+Qsd9F1W31AaZUffaEbGhrC1tYWQO7QyW7dukEoFMLZ2RnXr1/nlfX390daWhpWrVpFdw4IR/D2Paq8NIIiTx8GcUoOWGZWGdaKEFKSqA9DCStPaZX37t3DpUuX4OnpiaSkJAQFBeHGjRvYunUrgNxI6487USo7Xmqb+EUqMMbAnsehSnIqf16InBwo0tLKrl6EkBKlgABy6NZPSaHjdqWtTBsMq1evxqxZszBu3DgurXL06NGYPXs2AODFixc4cuQIAMDNzY23bd60ysDAQBgYGGDw4MFcWuXp06dhZmYGIPeuwZo1azB16lQurTIoKAijRo3i9ieXy7F8+XLcvXsXhoaG+PTTTxEZGQkHB4cSvw6kYlFkZAAZFXhILCGkUqK0ylKkTVolIYQQ7ZVVWmXUTUsY65hW+TZNgWYuCZRWSQghhFR08iI8ktB1u9JGDQY9IKxSBQIjo9wXmZlg+c1oyBhYVpZucxsQQgjRWWVoMFSa8CkA2LJlC5o0aQKpVAoLCwuMHz+e9/4///yDNm3aQCqVws7ODkuXLlXZR2hoKJydnSGVSuHq6opjx44Vz8XIh8BQjGxPZzwfUh8vvq6PFJ+GyPJ0VrvkfNIAIivLEq0PIYSQyqnShE8FBQVh+fLlCAwMhKenJ9LT0/HkyRPu/dTUVHTp0gWdOnXCunXrcP36dYwYMQLVqlXDt99+CyA3+2LgwIEICAhAt27dsHPnTvTq1QvR0dElNlJCIBIiua4EilYpyMkRIvN2VRg/V9/OE2UA1ZOrAs9LpCqEEELyoWACKJiOoyR03K60lWmnx27dusHS0hKbNm3i1vXp0wcymQzbt29Xu83ly5fRokULxMbGcuFTDg4OmDdvHi98Kq+kpCTY2Njgt99+Q8eOHdWWWbt2LX766SfEx8dDLBYDyJ26+tChQ7hz5w4AoH///khPT0dYWBi3XcuWLeHm5oZ169YVer66dHoUSqV4NdgdWb7JyMkRQXGrKozyaRAYZADVo5OguHFHo30TQkhFU1adHs/dsClSp8d2jV+U+06PZfpIwtvbG6dOncK9e/cAgAuf6tq1a77bFBY+ZW1tja5du/LuMEREREChUODFixdo2LAhbG1t0a9fPzx79owrc/HiRbRt25ZrLAC5+RJ3795FUlISV6ZTp068+vj4+ODixYtFvhaEEEL0lxzCIi36oExrqZwW2tnZGYaGhnB3d8eUKVN0Dp/y9/dHWFgYzMzM0L59eyQmJnJlFAoFFi1ahJUrV2Lfvn1ITExE586dkZWVO/tefHw8LC35z/+Vr5WTReVXRvn+xzIzM5GamspbtCbUj18kQgghFVulCJ9SKBTIzs7G//3f/6FLly4AgF27dsHKygpnzpyBj49PiZyfxmmVHwgkEoisLcGq/BezrZAYIrOaQE/an4QQUjmxIvRhYHrSh6FShE+pK2Nubo6aNWtyZaysrJCQkMCrn/K1lZVVgWWU739M27RKobER3jlZ4J3Ff/0bFAZARk2GqkIFsiHKd1tCCCFlh4ZVljBtw6dOnjxZYPhU3m3yhk+1atUKAHhlEhMT8fr1a66Ml5cX/vjjD2RnZ3NlIiIi4OTkxE0x7eXlhVOnTvGOHxERAS8vL7XnJ5FIYGJiwlsKJBRBIRYiRwZukUsBhSGDQEATchJCSHklZ8IiLfqgTGupDJ86evQonjx5goMHDyIoKAi9e/cG8F/4VFRUFHbs2MGFT8XHx3N9D/KGT504cQJ3797F2LFjAfwXPtWgQQP07NkTkydPRmRkJG7cuIGhQ4fC2dkZn376KQBg0KBBEIvF+Oabb3Dz5k3s2bMHq1at4t0hmDx5MsLDw7F8+XLcuXMHc+fORVRUFCZMmFCal40QQggpdZUifAoAfv31V0ydOhW+vr4QCoVo164dwsPDYWiYe/vf1NQUJ06cwPjx4+Hh4YGaNWti9uzZ3BwMQO6ojp07d8Lf3x8zZ85E/fr1cejQIUqrJISQSk4BARQ6/g2ugH7cQabwqVJU2DwMInNzpLd0xFvr//oqMBHw1h5gtd9Dni2E9IEUsgT1PzKah4EQUtmV1TwMR/6pC6OquvUzS0+To0eTh+V+HgbKkijnBApA+lKAnPQqEMsBw7dlXSNCCCEfK0pfBLme/N1ODYbyjgGGbxk1FAghhJQpajDoOQEDDNMZxKkKiDLkEL59B0XhmxFCCClGuX0YdMySoGGVhdO3tMotW7ZAIBDwFqlUirIme5kN4ytPIY16AHlcQuEbEEIIKVaKIkwLrWtnydJGaZUfaJJWCeQO48w7n4NAUAwtQ4EAEAghEAlR0CMwAQOgXJTrFIAoQw55YhJYZmbR66KvPlxDAIBCXrZ1IYRUOtSHoYRFRkaiZ8+e8PX1BQA4ODhg165duHTpEoDcoY4RERG8bYKDg9GiRQs8ffqUS6ucPHkyAgMDeWmVeWd1TEpKgr+/v0paZZMmTbh/79ixA1lZWdi8eTPEYjE3VXVQUBCvwSAQCPKd2VEnQhEMattAbm6KrCoGyDbK/xdOmA1UeZkDcXLWfysZYJiQArm8En9JCgQwsKkFuZUZBNlyCJ4nQP4msaxrRQghFQqlVX6gSVolALx9+xb29vaws7NDz549cfPmzXzrqkn4lMDQANk21ZHoYozkulJkG+V/x0KYzVDlSQqEl2//t0TdRs6TZ2A5OfluV9EJRCLk1KqOpEZVkepkCpiZlnWVCCGVjOLDowVdF31AaZVapFU6OTlh8+bNOHz4MLZv3w6FQgFvb288f/5cbX0DAgJgamrKLfnlSDChAAqD3NyIgjJIBAxAjhwsO4u30C14gImEkBvmXkMUx2MiQgjRgpwJirTogzJtMORNq4yOjsbWrVuxbNkybN26VaWspmmVHh4eCAkJgUAgQGhoKFdGmVbp4+ODli1bYteuXbh//z7OnDmjcX29vLwwZMgQuLm5oV27djhw4ADMzc2xfv16teX9/PyQkpLCLXnvaBBCCCH6hNIqtUir/JjyrsiDBw/Uvi+RSCCRSDS4EoQQQvSZcsSDbtvqR6dHSqvUIq3yY3K5HNevX+caJDpRMBikZqDKKzlkiQqIsgrfhPCxD9fQ6KUcstc5ELyvxKNFCCFlQsGERVr0QZneYVCmVdauXRsuLi64evUqgoKCMGLECAD/pVVGR0cjLCyMS6sEgOrVq0MsFvPSKu3s7GBvb4/AwEAA6tMqN2zYABMTE/j5+amkVc6bNw/ffPMNfvzxR9y4cQOrVq3CihUruPrOnz8fLVu2RL169ZCcnIzAwEDExsZi5MiROl8DlpMNwaPnMI6XAdVMkNq4Bt7X0I9fnnJDIQd78hxGr5MAuRzyNJoWkxBSuirDHQZKq9QirTIpKQmjRo1CfHw8zMzM4OHhgcjISN6jDq0xBkVaGpCWBpGCQZRVXfd9VWKK9HQgPb2sq0EIIRUWpVWWIl3SKvMSv2Uwi3oF+b2HJV1VQgjRS2WVVrk+2gMyY93+Bn//NgejP7lCaZWEEEJIRVeU+RT0ZR4GajDoAWEOIJADoiwGKDSMlhIIIBCLIRCJwLJzcudrIIQQUiKKNjW0fjQYKHzqg4yMDAwbNgyurq4wMDBQu31cXBwGDRqEBg0aQCgUYsqUKcV1KfIlUABVXspR/Z9UmNxMBF5rNuWxqGpVoHE9ZLdwhrC+AwQ0vJMQQkgRUPjUB3K5HDKZDJMmTcL+/fvV1jczMxPm5ubw9/fnjZ4oSQIFIHmTCdy4D3lONqBhlxOBURWk1zbG+xpCmIoEED8TV+5wKkIIKUGVId6awqc+MDIy4maQvHDhApKTk1Xq6+DggFWrVgEANm/eXMSz1xJTaNxY4AhyFz2ZdZQQQvRWaT6SCAgIwIEDB3Dnzh3IZDJ4e3tjyZIlcHJyynebLVu2YPjw4bx1EokEGRkZGh+XwqcIIYSQIlLOw6Droo1z585h/Pjx+OuvvxAREYHs7Gx06dIF6YUMLTcxMUFcXBy3xMbGanXcMr3DMGPGDKSmpsLZ2RkikQhyuRwLFy7UOXwqKCgIDg4OWL58Odq3b4979+6hevXqvPCpVatWwdTUFP7+/ujcuTP++ecfXkJlccrMzERmnscA6tIqCSGEEG2Eh4fzXm/ZsgUWFha4cuUK2rZtm+92AoEg36gDTVD4lBbhU9rSNK1SiWVkQBb3Diax2XmWLBi8TgNT0HQZhBBSXimYoEhLUaSkpADInQG5IG/fvoW9vT3s7OzQs2dP3Lx5U6vjUPjUhzIlwc/PD9OmTeNep6amFthoULx9C+GtR5AZ/PdjYYxBkUUR1oQQUp4pijA1tHIeho/vQmsSYKhQKDBlyhS0atUKjRs3zreck5MTNm/ejCZNmiAlJQXLli2Dt7c3bt68CVtbW43qSeFTH8qUBIlEAhMTE95SIMagePcO8tRUblGkpdHoBkIIKeeKI3zKzs6Od1c6ICCg0OOOHz8eN27cwO7duwss5+XlhSFDhsDNzQ3t2rXDgQMHYG5ujvXr12t8jhQ+9SF8CgBu3bqFrKwsJCYmIi0tDTExMQD4ORbKdW/fvsWrV68QExMDsVhctDwJQgghld6zZ894f1gWdndhwoQJCAsLwx9//KHxXQIlQ0NDuLu748GDBxpvQ+FThv9lOnz++ee8XqPu7u4AgLxxG8p1AHDlyhXs3LkT9vb2vDkdCCGEVC5yCCDXcT4F5XYa3YlG7nfSxIkTcfDgQZw9exaOjo7aH1Mux/Xr1/H5559rvA2FT5WiwsKnIBRBaFQFAgMDsKwsKN69037uhQ9E5uZ4/4k9MqoboOrTDIiu3svdHyGEVGBlFT417+9OkOoYPpXxNgdzPE9qXOdx48Zh586dOHz4MG/uBVNTU8hkMgDAkCFDYGNjwz3WmD9/Plq2bIl69eohOTkZgYGBOHToEK5cuaLxHXLKkihHRMZGkDdyQGZ1CaQv30N4+3FubLMOFKmpqHIzDjKpGEhLhzyD+kEQQkhJkQNFuMOgHeVIQeVddqWQkBAMGzYMAPD06VNeH8GkpCSMGjUK8fHxMDMzg4eHByIjI7V6nE4NhvJEIkGGuTQ33prJUOWB7j8elpmJnOcvirFyhBBCygNNHgycPXuW93rFihVFjjSgBkN5kpkJyetMgEkgfZ0Blp1T1jUihBCigbyjHXTZVh9QWuUHmqRVArmzN/7000+wt7eHRCKBg4NDseVKyN+mw+DmYxj99RCCO0+ozwEhhOgJZZaEros+oLTKDzRJqwSAfv36ISEhAZs2bUK9evUQFxfHmzeiSBRyyGn6aEII0TusCGmVTE/SKst0lES3bt1gaWmJTZs2cev69OkDmUyG7du3q93m8uXLaNGiBWJjY7m0SgcHB8ybN4+XVplXUlISbGxsVNIq8zNs2DAkJyfj0KFDvPXh4eEYMGAAHj16VOgUnOoUOkqCEEJIkZTVKIkZF7tCYqzb53rm22ws9vq91OqsK0qr1MKRI0fQrFkzLF26FDY2NmjQoAGmT5+O9+/fqy2fmZmJ1NRU3kIIIaTioUcSJUzf0iofPXqE8+fPQyqV4uDBg3j9+jXGjRuHN2/eICQkRKV8QEAA5s2bp+PVIYQQoi+KEiJV1PCp0kJplVqkVSoUCggEAuzYsQMtWrTA559/jqCgIGzdulXtXQY/Pz+kpKRwi7Z3NAghhOgH+YfwKV0XfUBplVqkVVpbW8PGxgampqbcuoYNG4IxhufPn6N+/fq88pokjRFCCCH6gNIqtUirbNWqFf7991+8ffuWW3fv3j0IhUKtgz8IIYRUHMpHErou+qBMGwzKtMqjR4/iyZMnOHjwIIKCgtC7d28A/6VVRkVFYceOHVxaZXx8PLKysgCAl1Z54sQJ3L17F2PHjgWgPq0yMjISN27cwNChQ9WmVcbExCAxMREpKSmIiYnh0ikBYNCgQahRowaGDx+OW7du4Y8//sD333+PESNGcPN3E0IIqXwUEBZp0QeUVqlFWqWxsTEiIiIwceJENGvWDDVq1EC/fv3wv//9r9ivDSGEEFKeUFplKaJ5GAghpGSV1TwMY//8okjzMKxtc6Dcz8NAWRKEEEJIEVWGYZXUYCCEEEKKiBUhfIrpycRNFD71wdmzZ9GzZ09YW1vDyMgIbm5u2LFjB2/7jRs3ok2bNjAzM4OZmRk6deqES5cuFe9FIYQQQsohCp/6IDIyEk2aNMGPP/4IS0tLhIWFYciQITA1NUW3bt0A5DYqBg4cCG9vb0ilUixZsgRdunTBzZs3YWNjUyrXjBBCSPkjhwByHUOkdN2utFH4VAF8fX1haWmZb3y1XC6HmZkZgoODMWTIkEL3R50eCSGkZJVVp8fhZ/tBbKxZzMDHst5mIaT93nLf6ZHCpwqQkpJSYCrlu3fvkJ2drVNyJSGEkIpD8aEPg66LPijTWiqnhXZ2doahoSHc3d0xZcoUncOn/P39ERYWBjMzM7Rv3x6JiYlcGWX41MqVK7Fv3z4kJiaic+fO3ARQH9u7dy8uX76M4cOH51v/H3/8EbVq1UKnTp3Uvk9plYQQQioKCp9SEz515swZDB8+HBs3boSLi4vaui9evBi7d+/GwYMHIZVK1ZYJCAiAqakpt9jZ2Wl9jQghhJR/CgiKtOgDCp/6KHzq3Llz6N69O1asWJFvv4Rly5Zh8eLFOHnyJJo0aZLv+fn5+WHatGnc69TUVGo0EEJIBSRnAsh1nE9B1+1KG4VP5QmfOnv2LHx9fbFkyRJ8++23auu8dOlSLFiwAOHh4WjWrFmB5yeRSGBiYsJbCCGEVDyVoQ9Dmd5hUIZP1a5dGy4uLrh69SqCgoIwYsQIAP+FT0VHRyMsLIwLnwKA6tWrQywW88Kn7OzsYG9vj8DAQADqw6c2bNgAExMT+Pn58cKnzpw5g27dumHy5Mno06cPdxyxWMx1alyyZAlmz56NnTt3wsHBgStjbGwMY2Pj0rtwhBBCSCkr02GVaWlpmDVrFg4ePMiFTw0cOBCzZ8+GWCzGkydP4OjoqHbbvOFT2dnZ8PPzw7Zt27jwqZUrV/L6H6SmpmLq1Kk4cOAAFz61atUq7hHBsGHD1PadaNeuHc6ePQsAcHBw4IVTKc2ZMwdz584t9HxpWCUhhJSsshpW2e/UYIiNdBxWmZ6FvR23lfthlRQ+VYqowUAIISWrrBoMX54aAkMdGwzZ6VkI7fhruW8wUJYEIYQQUkSVIXxKP3paEEIIIaRM0R0GQgghpIiKMtpBX0ZJUFrlB5qkVbZv3x4CgUBl8fX1Ld4LQwghRK8oH0nouugDSqv8QJO0ygMHDvCmkn7z5g2aNm3KDd8khBBSORVlxkZ9memR0ioLUFha5cqVKzF79mzExcXByMio0P3RKAlCCClZZTVKovuJb4o0SuK3LpvK/SgJSqssQGFplZs2bcKAAQPybSxQ+BQhhFQOleGRBKVV6phWeenSJdy4cQMjR47M9/wofIoQUhoEhmIIjYwglEoBoaisq1MpUYOhhOlzWuWmTZvg6uqKFi1a5Ht+fn5+SElJ4ZbC7mgQQoi2BAYGEDraIcvTGXJ3J4hq5H9XlJScytBgoLRKHdIq09PTsXv3bsyfP7/A85NIJJBIJIVeB0II0ZlIhGyLqkhxFEOSZohq8VWAV2VdKVIRUVqllmmVABAaGorMzEx8/fXXOpw1IYSUAAGgJ3+oVkh0h6GE6VtapdKmTZvQq1cvlcYLIYSQyolB9+GR+hLoVKYNhtWrV2PWrFkYN24cl1Y5evRozJ49GwDw4sULHDlyBADg5ubG2zZvWmVgYCAMDAwwePBgLq3y9OnTMDMz48r/+uuvmDp1Knx9fbm0yvDwcBga5g5v3Lp1K969e4eAgAAEBARw2+VNqwRy71KcP38eJ06cKIErQgghhJRPlFZZimgeBkJIcRNIJJA3b4gkZxnEaQxml+KQ8zi2rKtVZspqHoYOR8fAwEi3Pms56Zk47buu3M/DQFkShBBCSBFVhrRKajAQQoieE8gZRFmAKJsBeTqNk9JTGRoMFD71wd27d/Hpp5/C0tISUqkUderUgb+/P7Kzs7kyBw4cQLNmzVCtWjUuoGrbtm3Ff2EIIURDLDsHhs/fwOx6KqreSQJLoRllScmg8KkPDA0NMWTIEHzyySeoVq0arl27hlGjRnEzRAK5IzN++uknODs7QywWIywsDMOHD4eFhQV8fHxK5ZoRQgiPQo6c5y+A5y8gBwDqllYmKsMdBgqfKsC0adNw+fJl/Pnnn/mW+eSTT+Dr64sFCxYUuj/q9EgIISWrrDo9tjo8oUidHi/0DC73nR4pfCofDx48QHh4ONq1a6f2fcYYTp06hbt376Jt27Y6nD0hhJCKQhlvreuiDyh86qPwKW9vb0ilUtSvXx9t2rRRmf45JSUFxsbGEIvF8PX1xerVq9G5c2e19aW0SkIIIRUFhU99FD61Z88eREdHY+fOnTh69CiWLVvGe79q1aqIiYnB5cuXsXDhQkybNo03sVNelFZJCCGVQ2WYGlqrBkN2djZGjBiBx48fF8vB84ZPubq6YvDgwZg6dSpvpkXlcZXhUxERESUaPmVnZ4dGjRph4MCBWLx4MebOnQu5XM69LxQKUa9ePbi5ueG7775D3759VeqrRGmVhBBSOTAmKNKijYCAADRv3hxVq1aFhYUFevXqxctKyk9oaCicnZ0hlUrh6uqKY8eOaXVcrRoMhoaG2L9/v1YHKEh5C5/6mPLOhKKAcc0KhQKZmZlq35NIJDAxMeEthBBCKp7SvMNw7tw5jB8/Hn/99RciIiKQnZ2NLl26ID09Pd9tIiMjMXDgQHzzzTe4evUqevXqhV69eqmMKCyI1sMqe/XqhUOHDmHq1KnabqqiPIVP7dixA4aGhnB1dYVEIkFUVBT8/PzQv39/Lm8iICAAzZo1Q926dZGZmYljx45h27ZtvEckhBBCSEkKDw/nvd6yZQssLCxw5cqVfDvhr1q1Cp999hm+//57AMCCBQsQERGB4OBgrFu3TqPjat1gqF+/PubPn48LFy7Aw8MDRkZGvPcnTZqk8b7KU/iUgYEBlixZgnv37oExBnt7e0yYMIHXMEpPT8e4cePw/PlzyGQyODs7Y/v27ejfv7/G50wIIaTi0eXRQt5tAah0jJdIJJBICh+qmZKSAgAqycp5Xbx4EdOmTeOt8/HxwaFDhzSup9bzMDg6Oua/M4GAG7VAVNE8DIQQUrLKah6GT/ZNg0jHeRjk6ZmI7huksn7OnDmYO3dugdsqFAr06NEDycnJOH/+fL7lxGIxtm7dioEDB3Lrfv75Z8ybNw8JCQka1VPrOwzF1eGREEIIqSgYdJ9kU7nZs2fPeI0cTe4ujB8/Hjdu3CiwsVBcdJ4aOisrC48fP0bdunVhYEAZVoQQQkhRaNs5fsKECQgLC8Mff/wBW1vbAstaWVmp3ElISEiAlZWVxsfTeh6Gd+/e4ZtvvkGVKlXg4uLCDUucOHEiFi9erO3uCCGEEL1XmjM9MsYwYcIEHDx4EKdPny6wq4CSl5cXTp06xVsXEREBLy8vjY+rdYPBz88P165dw9mzZyGVSrn1nTp1wp49e7Tal76lVQLAypUr4eTkBJlMBjs7O0ydOhUZGRlanTchhJCKpTTnYRg/fjy2b9+OnTt3omrVqoiPj0d8fDzev3/PlRkyZAj8/Py415MnT0Z4eDiWL1+OO3fuYO7cuYiKisKECRM0Pq7WzxIOHTqEPXv2oGXLlhAI/jtJFxcXPHz4UKt96Vta5c6dOzFjxgxs3rwZ3t7euHfvHoYNGwaBQICgINUOK4QQQioHBRNAUEpplcqh/MqRgkohISEYNmwYAODp06e8eY68vb2xc+dO+Pv7Y+bMmahfvz4OHTqExo0ba3xcrRsMr169goWFhcr69PR0XgNCE5GRkejZsyd8fX0BAA4ODti1axcuXboEADA1NUVERARvm+DgYLRo0QJPnz7l0ionT56MwMBAXlpl3lkdk5KS4O/vr5JW2aRJE+7fderUQZ06dbjX9vb2OHv2LC+pMjIyEq1atcKgQYO4+g4cOBB///23VudNCCGE6EqTwY3qIgu+/PJLbn4iXWj9SKJZs2Y4evQo91rZSPjll1+0ehYC6F9apbe3N65cucI1aB49eoRjx47h888/V7sPCp8ihJDKgbGiLfpA6zsMixYtQteuXXHr1i3k5ORg1apVuHXrFiIjI3Hu3Dmt9jVjxgykpqbC2dkZIpEIcrkcCxcu1DmtMigoCA4ODli+fDnat2+Pe/fuoXr16ry0ylWrVsHU1BT+/v7o3Lkz/vnnH4jFYu4Y3t7eiI6ORmZmJr799lteWuWgQYPw+vVrtG7dGowx5OTkYMyYMZg5c6ba+gYEBGDevHlaXRNCCCH6pzgmbirvtL7D0Lp1a8TExCAnJweurq44ceIELCwscPHiRXh4eGi1L31Lqzx79iwWLVqEn3/+GdHR0Thw4ACOHj2KBQsWqD0/Cp8ihJDKoTQ7PZYVnSZQqFu3LjZu3Fjkg+dNqwQAV1dXxMbGIiAgAEOHDuXK5U2rPH36dImnVSrLyuVyfPvtt/juu+8gEokwa9YsDB48GCNHjuTqm56ejm+//RY//fSTSpCWptN6EkIIIeWdTg0GuVyOgwcP4vbt2wByv1x79uyp9QRO2qZVnjlzpsC0ytatW3Pb5JdWqZzcQtu0SpFIlG99Ac06oRBCCKmYSnOURFnRusFw8+ZN9OjRA/Hx8XBycgKQOzzS3Nwcv/32m1ZDNPQtrbJ79+4ICgqCu7s7PD098eDBA8yaNQvdu3fnGg6EEEIqn6J0XtSXvze1bjCMHDmSmzNBmQaZlJSEYcOG4dtvv0VkZKTG+9K3tEp/f38IBAL4+/vjxYsXMDc35xo9hBBCSEWmdVqlTCZDVFQUXFxceOtv3LiB5s2b82aaInyUVkkIISWrrNIq62+fAVEVaeEbqCF/l4H7Xy8utTrrSutREg0aNFAbhfny5UvUq1evWCpFCCGE6BMaJfFB3gmHAgICMGnSJMydOxctW7YEAPz111+YP38+lixZUjK1JIQQQsoxhv9iqnXZVh9odIehWrVqMDMzg5mZGbp3745bt26hX79+sLe3h729Pfr164cbN26ge/fuWh28PIVP5fXgwQNUrVqVm01Snd27d0MgEKg9DiGEEFLRaHSH4ePJjYpLeQqfUsrOzsbAgQPRpk2bfDtwPnnyBNOnT0ebNm2K9XoQQgjRT5VhpkeNGgx58xSKU3kKn1Ly9/eHs7MzOnbsqLbBIJfL8dVXX2HevHn4888/kZycXKRrQAghpAKoBM8ktO70CORmOly6dAlhYWE4cuQIb9FGeQufOn36NEJDQ7FmzZp8jz9//nxYWFjwGieEEEIquaJ0eKxIdxjyCg8Px5AhQ/D69WuV9wQCAeRyucb7Kk/hU2/evMGwYcOwffv2fIe1nD9/Hps2bUJMTIxG55eZmYnMzEzuNaVVEkII0Vda32GYOHEivvzyS8TFxUGhUPAWbRoLQPkKnxo1ahQGDRqEtm3bqq1rWloaBg8ejI0bN6JmzZoanV9AQABMTU25RZlTQQghpGKheGs1EhISMG3aNFhaWhb54OUpfOr06dM4cuQIl07JGINCoYCBgQE2bNiATz75BE+ePOGNBFE2VgwMDHD37l3UrVuXd35+fn6YNm0a9zo1NZUaDYQQUgFRp0c1+vbti7Nnz6p8OeqiPIVPXbx4kXeH5PDhw1iyZAkiIyNhY2MDmUyG69ev847t7++PtLQ0rFq1Sm1DgNIqCSGkkihKX4SK2mAIDg7Gl19+iT///BOurq5cFoPSpEmTNN5XeQqfatiwIa9uUVFREAqFvDCtj4O1lB0vtQncIoQQQvSR1g2GXbt24cSJE5BKpTh79iwEgv9aRgKBQKsGQ3kKnyKEEEJ0VRnSKrUOn7KyssKkSZMwY8YMlccJpGAUPkUIISWrrMKn7DfOglDH8CnFuwzEjlpQ7sOntL7DkJWVhf79+1NjgRBCCPmgMnR61Ppbf+jQodizZ09J1IUQQggh5ZTWdxjkcjmWLl2K48ePo0mTJip9AIKCgoqtcoQQQoje0JO+CLrS+g7D9evX4e7uDqFQiBs3buDq1avcoukMiErlKa3yyZMnEAgEKstff/3F20doaCicnZ0hlUrh6uqKY8eOaXXOhBBCKh5dp4UuyqOM0qb1HYbiTK4sj2mVJ0+ehIuLC/c677wPkZGRGDhwIAICAtCtWzfs3LkTvXr1QnR0NA2tJISQyqwShE9pPUqiOHXr1g2WlpbYtGkTt65Pnz6QyWTYvn272m0uX76MFi1aIDY2lkurdHBwwLx58/INhEpKSoKNjY1KWmVeT548gaOjI65evaoyhFOpf//+SE9PR1hYGLeuZcuWcHNzw7p16wo9XxolQQghJausRknYrZsDoUzHURLvM/BszLyKN0ri008/5c298LHTp09rvC9vb29s2LAB9+7dQ4MGDbi0yoL6QRSWVhkfHw83NzcEBgZyf/V/nFaZlpYGb29vLF++XGWGxh49eiAjIwMNGjTADz/8gB49enDvXbx4kTfVMwD4+Pjg0KFDautK4VOEEFJZCD4sum5b/mndh8HNzQ1NmzbllkaNGiErKwvR0dFwdXXVal/KHAlnZ2cYGhrC3d0dU6ZM0Tmt0t/fH2FhYTAzM0P79u2RmJjIlVGmVa5cuRL79u1DYmIiOnfujKysLACAsbExli9fjtDQUBw9ehStW7dGr169eJHd8fHxKhkalpaW3OyTH6PwKUIIqSRYERc9oPUdhhUrVqhdP3fuXLx9+1arfeVNq3RxcUFMTAymTJmCWrVq8cKnAM3TKgEgJCQEtra2CA0NxejRo3lplV26dAGQO2OllZUVzpw5Ax8fH9SsWZN396B58+b4999/ERgYyLvLoA0KnyKEkEqiEvRh0LrBkJ+vv/4aLVq04NIeNVGe0irV8fT0REREBPfaysoKCQkJvDIJCQmwsrJSuz2FTxFCCKkoim26xosXL0Iq1a7Dh7ZplSdPniwwrTLvNvmlVSp9nFapTkxMDNfYAAAvLy+cOnWKVyYiIgJeXl6anjIhhJCKSJlWqeuiB7S+w/DFF1/wXjPGEBcXh6ioKMyaNUurfZWntMqtW7dCLBbD3d0dAHDgwAFs3rwZv/zyC1ffyZMno127dli+fDl8fX2xe/duREVFYcOGDdpeRkIIIRVIZQif0rrBYGpqynstFArh5OSE+fPnc/0DNFXe0ioXLFiA2NhYGBgYwNnZGXv27EHfvn259729vbFz5074+/tj5syZqF+/Pg4dOkRzMBBCSGVXCfowlOk8DJUNzcNACCElq6zmYbBdPa9I8zA8nzin4s3DQAghhJCPFKUvQkXrw+Do6FjghE0AIBAI8PDhwyJXihBCCNEnApa76LqtPtB4lMSUKVMwefJktUvPnj0RHx+vNpuhIPoWPrVlyxaV97UdGUIIIYToI43vMEyePFllXWJiIhYsWIC1a9fC09MTS5Ys0erg+hY+BQAmJia84ZmF3XUhhBBSCVSCTo869WF4//49goKCsGzZMtjb2+PAgQP4/PPPtd5PZGQkevbsCV9fXwCAg4MDdu3ahUuXLgHIHZGRd+IkAAgODkaLFi3w9OlTLnxq8uTJCAwM5IVP5Z2kKSkpCf7+/irhU02aNFGpU40aNfKdiAnIbSAU9D4pmLBKFQirmwGGBkBWNlhGBqBQ/79FIBED0tyJr1hiMuSUxUEIKa+oDwOfXC7Hxo0bMW/ePEilUvzf//0fvv76a53/yta38CkAePv2Lezt7aFQKPDJJ59g0aJFvDsSpBD1auNZp+rINGOoEi+AydMcCORqGgwCIN3SAG/tBBDIgVoXakJ07hqgkJd+nQkhpDB0h+E/e/fuhb+/P5KTk/HTTz9h7NixEIvFRTr4jBkzkJqaCmdnZ4hEIsjlcixcuFDn8KmgoCA4ODhg+fLlaN++Pe7du4fq1avzwqdWrVoFU1NT+Pv7o3Pnzvjnn38gFou58KlWrVpBKBRi//796NWrFw4dOsQ1GpycnLB582Y0adIEKSkpWLZsGby9vXHz5k3Y2tqq1JfSKlVlV6+CtEZZqGmVijePzAAYQJitvsGQ5gBInJORnS1C+iMjmAoFYArVooQQQkqexg2GAQMGQCaTYeDAgYiNjcWMGTPUlivo7sDH9C18ysvLizcNtLe3Nxo2bIj169djwYIFKucXEBCAefPmaXw9CCGE6Cm6w/Cftm3bFjpsUttHE/oWPvUxZST3gwcP1L5PaZWEEFJJUIPhP2fPni32g2sbPnXmzJkCw6dat27NbZNf+JTy0YEu4VMfk8vluH79er4dPimtkhBCKgnq9Fiy9C18av78+WjZsiXq1auH5ORkBAYGIjY2FiNHjiy1a0YIIYSUhTJtMOhb+FRSUhJGjRqF+Ph4mJmZwcPDA5GRkbxHHYQQQiqfyjDTI4VPlSIKnwKYd1M87CsDLDJhECuFyQNAmKOmoAB4ayvAu/qZQI4QNuFCGB2MKpZhlQKJBAIDA0D5OEyhAMvJAcszooUQop/KKnyq9pL/FSl86umP/hrX+Y8//kBgYCCuXLmCuLg4HDx4UO3sxkpnz57l7qbnFRcXp9W8QhQ+RUqV4eME2B+zQY6xIcTJmTBMfKd+HgYApg9lyLwuhkDBUOXeK8iLYUylQCKBsJ4DMq2MuceGAgZI4t9C8eAJNRoIIeVeeno6mjZtihEjRuCLL77QeLu7d+/yGiQWFhZaHZcaDKRU5cTFwzAuHoYCAcAYCmoCCABIP5QrrumaBAYGyLQyRkod/hwipjCG+IkBNRgIIeVe165d0bVrV623s7Cw4CY91IXG4VNKbdu2xezZs3Hq1ClkZGTofGBSyWn6JKwEn5jl7dSsJ52UCSHllAD/9WPQevmwj9TUVN6SWcx/wLi5ucHa2hqdO3fGhQsXtN5e6wZDly5d8Ndff6Fnz56oVq0aWrduDX9/f0RERODdu3da7as8pVUCAGMMy5YtQ4MGDSCRSGBjY4OFCxdy78fFxWHQoEFo0KABhEIhpkyZotX5EkIIqaCUf4HougCws7ODqakptwQEBBRL1aytrbFu3Trs378f+/fvh52dHdq3b4/o6Git9qP1Iwl/f38AQE5ODi5fvoxz587h7NmzWLp0KYRCoVZ3HcpbWuXkyZNx4sQJLFu2DK6urkhMTERiYiL3fmZmJszNzeHv748VK1Zoe+lIeZKnVQ/oSS9lgQAQCMGbH5v6LBNSPhTDxE3Pnj3j9TEornl8nJyc4OTkxL329vbGw4cPsWLFCmzbtk3j/ejch+HRo0e4fv06rl27hn/++QdVq1ZF27ZttdpHeUqrvH37NtauXYsbN25wF9bR0ZF3bAcHB6xatQoAsHnzZq3OlZQPLCcHkvi3MGXG/7UYGCBJeAtFjrrhGuWDqJop3rZ3QlI9AxhkANJEBQwyGIyepgPX71PfC0IqABMTk1IZ2QEALVq0wPnz57XaRutHEoMGDYKNjQ28vb0RHh6Oli1b4vfff8fr169x8OBBrfbl7e2NU6dO4d69ewDApVUW1JmjsLRKa2trdO3alXeH4eO0SltbW/Tr1w/Pnj3jyvz222+oU6cOwsLC4OjoCAcHB4wcOZJ3h0FbmZmZKs+kSNlimZlQPHgC8d93IP7rw/L3nfI/QqJmdTzvnYOVY9dj6NhjkH/1BnF9M5HQ0gRCY6Oyrh0hhBVxKWWFzWSsjtZ3GHbv3o2aNWti5MiR6NChA1q3bo0qVapouxsA5Sut8tGjR4iNjUVoaCh+/fVXyOVyTJ06FX379sXp06d1Oj8KnyqfWGZm+W4cqCMSwdj0PTrK5KgmvIe/qtUBYwJkyKrkPqoghJSp0py46e3bt7wMo8ePHyMmJgbVq1dH7dq14efnhxcvXuDXX38FAKxcuRKOjo5wcXFBRkYGfvnlF5w+fRonTpzQ6rha32F48+YNfvnlF2RlZcHPzw81a9aEt7c3Zs6cqfXB86ZVRkdHY+vWrVi2bBm2bt2qUlbTtEoPDw+EhIRAIBAgNDSUK6NMq/Tx8UHLli2xa9cuLp9CWSYzMxO//vor2rRpg/bt22PTpk04c+YM7t69q+1lApAbPpWSksItee9oEEIIqUBK8Q5DVFQU3N3duSiDadOmwd3dnZslOS4ujhesmJWVhe+++w6urq5o164drl27hpMnT/Ie0WtC6zsMZmZm6NGjBxf5/ODBA/zvf/9DYGAglixZArlc8xHz5Smt0traGgYGBmjQoAFXpmHDhgCAp0+f8jqMaIrCpwghhBS39u3bo6BJmrds2cJ7/cMPP+CHH34o8nG1bjC8efOGGxlx9uxZ3Lp1C9WqVUP37t3Rrl07rfZVntIqW7VqhZycHDx8+BB169YFAK5vRUGJloSUBkFmFt6+qIElb+rjXrolop/aITtFghqJDJDzp78SSCQQWVmAVclnmlq5AoJ3GWCZWf+tYwqw9xlQpKeX4FkQUoFRvLUqCwsL1KxZE23atMGoUaPQvn17uLq66nTw8pRW2alTJ3zyyScYMWIEVq5cCYVCgfHjx6Nz5868uw4xMTEAcp8hvXr1CjExMRCLxRRARUqU4uVr1NtZHYf/6AhRFoNdSg6EWVkwTEiF4i3/S15kbYl/u9nibW31n0KiDKDqE6DKqzx3AxlQ5UkqBHcegJXj0SKElFeVIXxK6wbDP//8AxcXl2I5eHlKqxQKhfjtt98wceJEtG3bFkZGRujatSuWL1/OO67ymREAXLlyBTt37oS9vb3KnA6EFCfFu3cQXIhB1Y/Wq3sAyIxkSHNUoGbD12r3lZIuw1tFVSgMRNw6gQIQJ0shEokAajAQor28U8fqsq0e0Dmt8tWrV1xnQCcnJ5ibmxdrxSoiSqskpUHk4oR7I8wKbDDgZlVU+fe///oCBWB25z1El2/r3wgSQvIoq7RKx3mLIJTqmFaZkYHHc2aWWp11pfUoifT0dIwYMQLW1tZo27Yt2rZti1q1auGbb77RempoQgghpELQs3kYdKF1g2HatGk4d+4cfvvtNyQnJyM5ORmHDx/GuXPn8N1335VEHQkh2mAMgmwB3mUZql2yswwgyAGEHy0ChZ58ahFSDukcPFWEvg+lTesGw/79+7Fp0yZ07dqVm8by888/x8aNG7Fv3z6t9qVv4VNA7uyNP/30E+zt7SGRSODg4EDTRJPy5U0yrP+Sw/BYNbVL9QgpLKOyUf1WOreY3XoLw3+TwLKp/wIhRD2tOz2+e/cOlpaWKustLCy0fiShb+FTANCvXz8kJCRg06ZNqFevHuLi4njDQAkpa/KXr1Dl9xQYiUTqCygUYHIFP8QKQI6CAQrN51EhhORRCYZVat3psWPHjqhRowZ+/fVXSD908Hj//j2GDh2KxMREnDx5UuN9devWDZaWlti0aRO3rk+fPpDJZNi+fbvabS5fvowWLVogNjaWC59ycHDAvHnzeOFTeSUlJcHGxkYlfCqv27dvo0mTJrzwqY+Fh4djwIABePToEapXr67xeSpRp0dCCClZZdXpsc6sRRDp2OlRnpGBRwsqYKfHVatW4cKFC7C1tUXHjh3RsWNH2NnZ4cKFC1ySo6b0LXzqyJEjaNasGZYuXQobGxs0aNAA06dPx/v377U6b0IIIRVMJej0qPUjicaNG+P+/fvYsWMH7ty5AwAYOHAgvvrqK8hkMq32pW/hU48ePcL58+chlUpx8OBBvH79GuPGjcObN28QEhKiUt/MzExk5hmiRmmVhBBC9JXWDQYAqFKlCkaNGsVbFxcXh++//x7BwcEa7ydv+JSLiwtiYmIwZcoU1KpVi5clAWgePgUAISEhsLW1RWhoKEaPHs0Ln+rSpQsAYNeuXbCyssKZM2fg4+PDC59Szuy4adMmeHh44O7du3BycoJCoYBAIMCOHTtgamoKILdvRN++ffHzzz+rNJgorZIQQiqJStCHQatHEjdv3kRwcDA2bNiA5ORkAMDr168xdepU1KlTh0t+1FTe8ClXV1cMHjwYU6dORUBAAK9c3vCpiIiIMgmfUpaxsbHhGgvKMowxPH/+XOX8KK2SEEIqBxpWmceRI0fg7u6OSZMmYcyYMWjWrBnOnDmDhg0b4vbt2zh48CBu3ryp1cG1DZ86efJkgeFTebfJL3xKqaDwKaWPw6datWqFf//9F2/fvuWVEQqFXKhVXhKJhBt6qlwIIYQQfaRxg+F///sfxo8fj9TUVAQFBeHRo0eYNGkSjh07hvDwcHz22WdaH1wZPnX06FE8efIEBw8eRFBQEHr37g3gv/CpqKgo7Nixgwufio+PR1ZWbtJe3vCpEydO4O7duxg7diwA9eFTkZGRuHHjBoYOHZpv+NTVq1dx5coVjB49mhc+NWjQINSoUQPDhw/HrVu38Mcff+D777/HiBEjtO6/QQghhOgTjRsMd+/exfjx42FsbIyJEydCKBRixYoVaN68uc4HX716Nfr27Ytx48ahYcOGmD59OkaPHo0FCxYA+C986vnz53Bzc4O1tTW3REZGcvsJDAzEgAEDMHjwYDRv3hyxsbFqw6c8PT3h6+uLdu3awdDQUG34VM2aNdG2bVv4+vqiYcOG2L17N7cPY2NjREREIDk5Gc2aNcNXX32F7t274//+7/90vgaEEEIqgEowSkLjeRiEQiHi4+NhYWEBAKhatSquXbuGOnXqlGgFKxKah4EQQkpWWc3DUG9G0eZheLC4/M/DoNUoiePHj3Md/hQKBU6dOqUyo2KPHj2Kr3aEEEKIvtCTOwW60qrB8PFQx9GjR/NeCwQCyOU0tSwhhBBS0WjcYKC8BEIIISQfNA9DySpPaZVz586FQCBQWYyMjLgyGzduRJs2bWBmZgYzMzN06tQJly5dKv4LQwghRK9UhnkYdJrpsbiUp7TK6dOnY8yYMbxtOnbsyBsFcvbsWQwcOBDe3t6QSqVYsmQJunTpgps3b8LGxqZkLhIhhJDyrxLcYdA6rbI4lae0yo9du3YNbm5u+OOPP9CmTRu1ZeRyOczMzBAcHIwhQ4YUuk8aJUEIISWrrEZJ1P9+EUQSHUdJZGbgfmD5HyVRpo8kylNa5cd++eUXNGjQIN/GApA7U2V2dna+UdeZmZlITU3lLYQQQiqeyvBIokwbDMocCWdnZxgaGsLd3R1TpkzROa3S398fYWFhMDMzQ/v27blo6rxplStXrsS+ffuQmJiIzp07czNGfnycHTt25HvHQunHH39ErVq10KlTJ7XvBwQEwNTUlFvs7Ow0vjaEEEL0SCWYuKlMGwx50yqjo6OxdetWLFu2DFu3blUpq2lapYeHB0JCQiAQCBAaGsqVUaZV+vj4oGXLlti1axfu37+vNjDr4MGDSEtLUxlGmtfixYuxe/duHDx4ENJ8Juug8ClCCKkkKkGDQaNOj2ZmZhAIBBrtUPlXvSbyplUCgKurK2JjYxEQEMD7ss6bVnn69OkSSavM65dffuH6V6izbNkyLF68GCdPnkSTJk3yPT+JRAKJRFLodSCEEELKO40aDCtXriyRg2ubVnnmzJkC0ypbt27NbZNfWqUyVfLjtEqlx48f48yZMzhy5IjaOi9duhQLFy7E8ePH0axZsyKcPSGEkIqiKH0R9KUPg0YNhoJuzReFMq2ydu3acHFxwdWrVxEUFIQRI0YA+C+tMjo6GmFhYVxaJQBUr14dYrGYl1ZpZ2cHe3t7BAYGAlCfVrlhwwaYmJjAz8+Pl1aptHnzZq7j5MeWLFmC2bNnY+fOnXBwcODqYmxsDGNj4xK5RoQQQvRAJRhWqdM8DA8fPkRISAgePnyIVatWwcLCAr///jv3xa+p1atXY9asWRg3bhxevnyJWrVqYfTo0Zg9ezaA/9IqAcDNzY237ZkzZ9C+fXsAuWmVBgYGGDx4MN6/fw9PT0+1aZVTp06Fr68vhEIh2rVrx0urBHL7OmzZsgXDhg2DSCRSqe/atWuRlZWFvn378tbPmTMHc+fO1fi8CSGEVDCVoMGg9TwM586dQ9euXdGqVSv88ccfuH37NurUqYPFixcjKioK+/btK6m66j2ah4EQQkpWWc3D4DS5aPMw3F1VAedhmDFjBv73v/8hIiICYrGYW9+hQwf89ddfxVo5QgghRB/QPAxqXL9+Hb1791ZZb2FhgdevXxdLpQghhBC9UgmGVWrdYKhWrRri4uJU1l+9elXrPAV9C59q37692jK+vr5anTchhBCib7Tu9DhgwAD8+OOPCA0NhUAggEKhwIULFzB9+nSN8hTy0rfwqQMHDvBmhnzz5g2aNm3KjcYghBBSOVWGYZVad3rMysrC+PHjsWXLFsjlchgYGEAul2PQoEHYsmWL2tEF+dH38KmVK1di9uzZiIuL492JyA91eiSEkJJVVp0eG44vWqfH22sqYKdHsViMjRs34tGjRwgLC8P27dtx584dbNu2TavGAqD/4VObNm3CgAEDNGosEEIIqcCoD4MqZfaCnZ0dPv/8c/Tr1w/169cHAKxfv16rfelz+NSlS5dw48YNjBw5Mt8ylFZJCCGkotC6wfDZZ5/h+++/R3Z2Nrfu9evX6N69O2bMmKHVvvQ5fGrTpk1wdXVFixYt8i1DaZWEEFI5CIq46AOd7jAcPHgQzZs3x61bt3D06FE0btwYqampiImJ0WpfecOnXF1dMXjwYEydOhUBAQG8cnnDpyIiIso8fCo9PR27d+8uNP6a0ioJIaSSoEcSqry9vRETE4PGjRvjk08+Qe/evTF16lScPXtWJcipMNqGT508ebLA8Km82+QXPqVUWPhUQY2B0NBQZGZm4uuvvy7w/CQSCUxMTHgLIYSQiqcyTNykU5bEvXv3EBUVBVtbW/z777+4e/cu3r17p3XnP30Ln1LatGkTevXqpdJ4IYQQQioqre8wLF68GF5eXujcuTNu3LiBS5cu4erVq2jSpAkuXryo1b5Wr16Nvn37Yty4cWjYsCGmT5+O0aNHY8GCBQD+C596/vw53NzcYG1tzS2RkZHcfgIDAzFgwAAMHjwYzZs3R2xsrNrwKU9PT/j6+qJdu3YwNDTUOnwKyL1Lcf78+UIfRxBCCKlEKsEjCa3nYbC2tsbmzZt5f4FnZ2dj5syZ+L//+z9kZmYWeyUrCpqHgRBCSlZZzcPgMnoRRGId52HIysDN9eV/HgatH0lcv34dNWvW5K0zNDREYGAgunXrVmwVI4QQQvRFZZjpUetHEh83FvJq165dkSpDCCGEkPJJozsMX3zxBbZs2QITExN88cUXBZY9cOBAsVSMEEII0RtF6Yug5XZ//PEHAgMDceXKFcTFxeHgwYNqAxfzOnv2LKZNm4abN2/Czs4O/v7+GDZsmFbH1egOg6mpKQQCAffvghZtlKe0SgA4fvw4WrZsiapVq8Lc3Bx9+vThBVSdP38erVq1Qo0aNSCTyeDs7IwVK1Zodc6EEEIqntIcVpmeno6mTZtizZo1GpV//PgxfH198emnnyImJgZTpkzByJEjcfz4ca2Oq9EdhpCQEMyfPx/Tp09HSEiIVgcoSHlKq3z8+DF69uyJadOmYceOHUhJScHUqVPxxRdfIDo6GgBgZGSECRMmoEmTJjAyMsL58+cxevRoGBkZ4dtvvy2260IIIUTPlOIdhq5duxY49P9j69atg6OjI5YvXw4AaNiwIc6fP48VK1bAx8dH4/1oPEpCJBIhLi4OFhYWGu+8MOUprXLfvn0YOHAgMjMzucmkfvvtN/Ts2ROZmZm84Zd5ffHFFzAyMsK2bdsKPV8aJUEIISWrrEZJuH5TtFES1zfpNkpCIBAU+kiibdu2+OSTT7By5UpuXUhICKZMmYKUlBSNj6Vxp0ctR19qpDylVXp4eEAoFCIkJARyuRwpKSnYtm0bOnXqlG9j4erVq4iMjMy3syeFTxFCSOVQHI8kPv6+KK5pCuLj41WiDiwtLZGamor3799rvB+tRkko+zEUl/KUVuno6IgTJ05g5syZkEgkqFatGp4/f469e/eq1MPW1hYSiQTNmjXD+PHj802spPApQgipJIph4iY7Ozved8bHuUplTat5GBo0aFBoo0H5Ja2JvGmVLi4uXGeMWrVqqSRFappWCeTearG1tUVoaChGjx7NS6vs0qULAGDXrl2wsrLCmTNn4OPjg/j4eIwaNQpDhw7FwIEDkZaWhtmzZ6Nv376IiIjgnfeff/6Jt2/f4q+//sKMGTNQr149DBw4UOX8/Pz8MG3aNO51amoqNRoIIaQiKoY+DM+ePeM9kpBIJEWuFgBYWVkhISGBty4hIQEmJiaQyWQa70erBsO8efO0HglRkLxplQDg6uqK2NhYBAQE8BoMedMqT58+XSJplWvWrIGpqSmWLl3Kldm+fTvs7Ozw999/o2XLltx6R0dHrr4JCQmYO3eu2gaDRCIpth84IYSQiq2kQgq9vLxw7Ngx3rqIiAh4eXlptR+tGgwDBgwo1k6P2qZVnjlzpsC0ytatW3Pb5JdWaWtrC0A1rTK/ugDg1edjCoWCpsMmhJBKrjRnenz79i0ePHjAvX78+DFiYmJQvXp11K5dG35+fnjx4gV+/fVXAMCYMWMQHByMH374ASNGjMDp06exd+9eHD16VKvjatxgKO7+C0D5Sqv09fXFihUrMH/+fO6RxMyZM2Fvbw93d3cAuXchateuDWdnZwC5k2csW7YMkyZNKvZrQwghRI+U4rDKqKgoXtKy8tH30KFDsWXLFsTFxXF3z4Hcu+JHjx7F1KlTsWrVKtja2uKXX37RakgloEWDoSRGSaxevRqzZs3CuHHj8PLlS9SqVQujR4/G7NmzAfyXVgkAbm5uvG3PnDmD9u3bA8hNqzQwMMDgwYPx/v17eHp6qk2rnDp1Knx9fSEUCtGuXTteWmWHDh2wc+dOLF26FEuXLkWVKlXg5eWF8PBw7hmPQqGAn58fHj9+DAMDA9StWxdLlizB6NGji/3aEEII0R8CxiDQ8XtS2+3at29f4Hfyli1b1G5z9epVbavGo3VaJdEdzcNACCElq6zmYXAbvLBI8zDEbPup4qVVEkIIIeQjpfhIoqxQg4EQQggpIoq3LmH6Fj4FADt27EDTpk1RpUoVWFtbY8SIEXjz5k2xXRNCCCF6qBgmbirvyrTBoAyfCg4Oxu3bt7FkyRIsXboUq1evBgBe+FR0dDQOHDiAu3fvokePHrz97N+/H4MHD8bw4cNx7do1XLhwAYMGDeKVCQoKwk8//YQZM2bg5s2bOHnyJK+HqDJ8qkOHDoiJicHx48fx+vVrXpz3hQsXMGTIEHzzzTe4efMmQkNDcenSJYwaNaoErxIhhBBS9sr0kURkZCR69uwJX19fAICDgwN27dqFS5cuAciN0o6IiOBtExwcjBYtWuDp06dc+NTkyZMRGBjIC5/KO0lTUlIS/P39VcKnmjRpwv37ypUrkMvl+N///sfNxzB9+nT07NkT2dnZMDQ0xMWLF+Hg4MANo3R0dMTo0aOxZMmSYr4yhBBC9Ak9kihh+hY+5eXlhWfPnuHYsWNgjCEhIQH79u3D559/XgJXhxBCiN6gRxIlS9/Cp1q1aoUdO3agf//+EIvFsLKygqmpKdasWaO2vpRWSQghpKIo0wZD3vCp6OhobN26FcuWLcPWrVtVymoaPuXh4YGQkBAIBAKEhoZyZZThUz4+PmjZsiV27drFTTcNgBc+dfnyZZw7dw5isRh9+/blOmHeunULkydPxuzZs3HlyhWEh4fjyZMnGDNmjNrzo7RKQgipHIoj3rq8K9M+DPoWPhUQEIBWrVrh+++/B5DbB8LIyAht2rTB//73P+44SpRWSQghlUQlmIehTO8waBs+dfLkyQLDp/Juk1/4lJIu4VMFlVE3YaZEIuHSx0oqhYwQQkj5UJHvLgBl3GBQhk8dPXoUT548wcGDBxEUFITevXsD+C98KioqCjt27ODCp+Lj47m+B3nDp06cOIG7d+9i7NixANSHT0VGRuLGjRsYOnSoSvjU5cuXMX/+fNy/fx/R0dEYPnw4L3yqe/fuOHDgANauXYtHjx7hwoULmDRpElq0aIFatWqV9uUjhBBCSk2ZPpLQt/CpYcOGIS0tDcHBwfjuu+9QrVo1dOjQgYZVEkJIZcdY7qLrtnqAwqdKEYVPEUJIySqr8Klmff8HA0PdwqdysjMQtc+fwqcIIYSQCo86PRJCCCGE0B0GQgghpMgEitxF1231AaVV5rF37164ubmhSpUqsLe3R2BgYL51v3DhAgwMDFQ6YxJCCKmEKsHU0GV6h0GZVrl161a4uLggKioKw4cPh6mpKSZNmsRLq2zatCmSkpIwefJk9OjRA1FRUdx+9u/fj1GjRmHRokXo0KEDcnJyeFkSQG5a5fLlyxEYGAhPT0+kp6fzoqt///13fPXVV1i9ejW6dOmC27dvY9SoUZDJZJgwYQJvX8nJyRgyZAg6duyIhISEEr1GhBBCyr/KED5VpqMkunXrBktLS2zatIlb16dPH8hkMmzfvl3tNpcvX0aLFi0QGxvLpVU6ODhg3rx5vLTKvJKSkmBjY6OSVpnXoEGDkJ2dzU0nDeQO+1y6dCmePn0KgUDArR8wYADq168PkUiEQ4cOISYmRqPzpVEShBBSsspqlESLnkUbJXHpcPkfJUFplR9kZmZCKuX/sGUyGZ4/f47Y2FhuXUhICB49eoQ5c+YUen4UPkUIIZWEch4GXRc9QGmVH2aM9PHxwYEDB3Dq1CkoFArcu3cPy5cvBwDExcUBAO7fv48ZM2Zg+/btMDAo/GkOhU8RQkjlUBnCpyit8kNa5ahRozBhwgR069YNYrEYLVu25EKxhEIh5HI5Bg0ahHnz5qFBgwYanZ+fnx9SUlK4Je8dDUIIIRUIdXosWeUprVIgEGDJkiVYtGgR4uPjYW5ujlOnTgEA6tSpg7S0NERFReHq1atcJ0iFQgHGGAwMDHDixAl06NCBd34SiQQSiaR4LhYhhBBShsq0waBtWuWZM2cKTKts3bo1t01+aZW2trYAVNMq8x7fxsYGALBr1y54eXnB3NwcCoUC169f55X9+eefcfr0aezbtw+Ojo5FvRyEEEL0VGUYJVGmDQZlWmXt2rXh4uKCq1evIigoCCNGjADwX1pldHQ0wsLCuLRKAKhevTrEYjEvrdLOzo43f4K6tMoNGzbAxMQEfn5+vLTK169fY9++fWjfvj0yMjIQEhKC0NBQnDt3DkDuY4nGjRvz6m9hYQGpVKqynhBCSCVTCcKnKK3S8L/hjVu3bsX06dPBGIOXlxfOnj2LFi1alOxFIIQQovcqwx0GSqssRTQPAyGElKyymofBq+v8Is3DcPH32eV+HgbKkiCEEEKKqhKkVVKDgRBCCCmiyvBIolKET23ZsgUCgUDt8vLlS67c2bNn8cknn0AikaBevXrYsmWLynHWrFkDBwcHSKVSeHp64tKlS8V+XQghhOgZBSvaogfKtMGgDJ8KDg7G7du3sWTJEixduhSrV68GAF74VHR0NA4cOIC7d++iR48evP3s378fgwcPxvDhw3Ht2jVcuHABgwYN4t7v378/4uLieIuPjw/atWsHCwsLAMDjx4/h6+uLTz/9FDExMZgyZQpGjhyJ48ePc/vZs2cPpk2bhjlz5iA6OhpNmzaFj48Pr9FBCCGEVESVInzqY69evYKNjQ02bdqEwYMHAwB+/PFHHD16lJdBMWDAACQnJyM8PBwA4OnpiebNmyM4OBhA7sRNdnZ2mDhxImbMmFHocanTIyGElKyy6vTo3WlekTo9Rp6cU+47PVaK8KmP/frrr6hSpQr69u3Lrbt48SI6derEK+fj44OLFy8CALKysnDlyhVeGaFQiE6dOnFlCCGEVE4CFCFLoqwrr6Ey7fQ4Y8YMpKamwtnZGSKRCHK5HAsXLtQ5fCooKAgODg5Yvnw52rdvj3v37qF69eoq+9m0aRMGDRoEmUzGrYuPj4elpSWvnKWlJVJTU/H+/XskJSVBLperLXPnzh219c3MzERmZib3mtIqCSGE6KtKET6V18WLF3H79m2NH18UBaVVEkJIJVEJ4q0rRfhUXr/88gvc3Nzg4eHBW29lZYWEhATeuoSEBJiYmEAmk0EkEkEkEqktY2Vlpfb8/Pz8MG3aNO51amoqNRoIIaQComGVJUzb8KmTJ08WGD6Vd5u84VNKb9++xd69e9XeXfDy8uLSKZUiIiLg5eUFABCLxfDw8OCVUSgUOHXqFFfmYxKJBCYmJryFEEJIBUTx1iWrtMKnlPbs2YOcnBx8/fXXKnUZM2YMgoOD8cMPP2DEiBE4ffo09u7di6NHj3Jlpk2bhqFDh6JZs2Zo0aIFVq5cifT0dAwfPrykLhEhhBBSLlSa8Ckgt7PjF198wY2wyMvR0RFHjx7F1KlTsWrVKtja2uKXX36Bj48PV6Z///549eoVZs+ejfj4eLi5uSE8PFylIyQhhJDKRcAYBDr2RdB1u9JG4VOliOZhIISQklVW8zC0aTsHBgY6zsOQk4E//5hX7udhoCwJQgghpIgqwx2GMu30SAghhBD9QHcYCCGEkKKqBPHWlFapRVrl3LlzVbZ3dnYukWtDCCFEj9DETSVLmVa5detWuLi4ICoqCsOHD4epqSkmTZrES6ts2rQpkpKSMHnyZPTo0QNRUVHcfvbv349Ro0Zh0aJF6NChA3JycnhZEv3798dnn33GO/awYcOQkZGhklY5ZswY7NixA6dOncLIkSNhbW3NGynh4uKCkydPcq8NDOgmDSGEVHaVYeKmMv22i4yMRM+ePeHr6wsAcHBwwK5du3Dp0iUAgKmpKSIiInjbBAcHo0WLFnj69CmXVjl58mQEBgbyJmTKO/OjTCbj5Ua8evUKp0+f5qVkrlu3Do6Ojli+fDkAoGHDhjh//jxWrFjBazAYGBjkO7MjIYQQUlFRWuUHhaVVKt2/fx+1atVCnTp18NVXX6mdflopMzMTqampvIUQQkgFVMqPJNasWQMHBwdIpVJ4enpyf2iro+6xvFSq/RDQMm0wKHMknJ2dYWhoCHd3d0yZMkXntEp/f3+EhYXBzMwM7du3R2Jiotr96JJWCQCenp7YsmULwsPDsXbtWjx+/Bht2rRBWlqa2uNQ+BQhhFQOAkXRFm3s2bMH06ZNw5w5cxAdHY2mTZvCx8eH1yfvYyYmJoiLi+OW2NhYrc+R0iq10LVrV3z55Zdo0qQJfHx8cOzYMSQnJ2Pv3r1qy/v5+SElJYVbnj17pvUxCSGE6IFSvMMQFBSEUaNGYfjw4WjUqBHWrVuHKlWqYPPmzfluIxAIYGVlxS26zFBMaZUfFJZWqU61atXQoEEDPHjwQO37EokEEomkoEtACCGEAIDKY2t13yFZWVm4cuUK/Pz8uHVCoRCdOnVSeYSe19u3b2Fvbw+FQoFPPvkEixYtgouLi1b1o7TKDwpLq1Tn7du3ePjwIddoIYQQUkkVQ1qlnZ0d7zF2QECAymFev34NuVyu9hG6MpzxY05OTti8eTMOHz6M7du3Q6FQwNvbG8+fP9fqFCmt8gNN0iqnT5+O7t27w97eHv/++y/mzJkDkUiEgQMHltQlIoQQogeKY2roZ8+e8e6gF9cdai8vL94fv97e3mjYsCHWr1+PBQsWaLwfSqv8QJO0yufPn2PgwIF48+YNzM3N0bp1a/z1118wNzcvvotCCCFE/xRlAqYP25mYmBQaPlWzZk2IRCK1j9A1HfKvHGSQ3+P0/FBaZSmitEpCCClZZZVW+amHX5HSKs9cCdC4zp6enmjRogVWr14NILfzf+3atTFhwgTMmDGj0O3lcjlcXFzw+eefIygoSON60jSFhBBCSFExAFoOj+Rtq4Vp06Zh6NChaNasGVq0aIGVK1ciPT0dw4cPBwAMGTIENjY2XB+I+fPno2XLlqhXrx6Sk5MRGBiI2NhYjBw5UqvjUoOBEEIIKaLSjLfu378/Xr16hdmzZyM+Ph5ubm4IDw/nOkI+ffqUN6AgKSkJo0aNQnx8PMzMzODh4YHIyEje6EJNUPjUh4ku4uLiMGjQIDRo0ABCoRBTpkxROcbNmzfRp08fODg4QCAQYOXKlSVxWQghhOgbhiLMw6D94SZMmIDY2FhkZmbi77//hqenJ/fe2bNneeGJK1as4MrGx8fj6NGjcHd31/qYFD71IXwqMzMT5ubm8Pf3x4oVK9TW9927d6hTpw6+/PJLTJ06tQSuCCGEEFI+UfjUBw4ODli1ahUA5DtbVvPmzdG8eXMA0KhjCSGEkEqiGEZJlHcUPkUIIYQUlaKIix4o0zsMM2bMQGpqKpydnSESiSCXy7Fw4UKdw6eCgoLg4OCA5cuXo3379rh37x6qV6+ush914VMlITMzE5mZmdxrSqskhBCiryh8qgRRWiUhhFQOylESui76gMKnSpCfnx+mTZvGvU5NTaVGAyGEVETUh6FklafwqZIgkUi4qT41mfKTEEKInirFeOuyQuFTecTExADIbVi8evUKMTExEIvF3N2LrKws3Lp1i/v3ixcvEBMTA2NjY9SrV6/Yrw8hhBBSXpRplkRaWhpmzZqFgwcPcuFTAwcOxOzZsyEWi/HkyRM4Ojqq3TZv+FR2djb8/Pywbds2Lnxq5cqVKlnf3t7ecHR0xI4dO9TuUyAQqKyzt7fHkydPACDf+rRr1w5nz54t9HwpS4IQQkpWWWVJdGz4HQxEuqVL5sgzcer28lKrs64ofKoUUYOBEEJKVpk1GJyK2GC4W/4bDJQlQQghhBRRaWZJlJUy7fRICCGEEP1A4VNahE8BQHJyMsaPHw9ra2tIJBI0aNAAx44dK/ZrQwghRI/QKImSpW/hU1lZWejcuTMsLCywb98+2NjYIDY2lpummhBCSCWlYIBAxy9+BTUYCqVv4VObN29GYmIiIiMjYWhoyG1HCCGkkqOJm0qWvoVPHTlyBF5eXhg/fjwsLS3RuHFjLFq0CHK5XKv9EEIIIfqGwqe08OjRI5w+fRpfffUVjh07hgcPHmDcuHHIzs7GnDlzVMpT+BQhhFQWRemLQHcYCqVv4VMKhQIWFhbYsGEDPDw80L9/f/z0009Yt26d2vIUPkUIIZUEdXosWfoWPmVtbQ1DQ0OIRCJuXcOGDREfH4+srCyIxWJeeQqfIoSQSkLBoPOdAj3p9EjhU1po1aoVHjx4wKvfvXv3YG1trdJYACh8ihBCSMVB4VN5FBY+NXbsWAQHB2Py5MmYOHEi7t+/j0WLFmHSpEklcXkIIYToC6bIXXTdVg9Q+FQehYVPAbl9IKZOnYqYmBjY2Njgm2++wY8//sh7TJEfypIghJCSVVZZEp3sxsJAqGOWhCITJ5+tLfdZEhQ+VYqowUAIISWrzBoMNmOK1mB4sa7cNxgoS4IQQgghhaK0SkIIIaSoKsFMj9RgIIQQQoqKoQgNhmKtSYmhtMoPaZUHDhxA586dYW5uDhMTE3h5eeH48eO8YwQEBKB58+aoWrUqLCws0KtXL95wTkIIIZVUJZi4qUwbDMq0yuDgYNy+fRtLlizB0qVLsXr1agDgpVVGR0fjwIEDuHv3Lnr06MHbz/79+zF48GAMHz4c165dw4ULFzBo0CDu/f79+yMuLo63+Pj4oF27dlxa5R9//IHOnTvj2LFjuHLlCj799FN0794dV69e5fZz7tw5jB8/Hn/99RciIiKQnZ2NLl26ID09vRSuFiGEEFJ2ynSURLdu3WBpaclLjezTpw9kMhm2b9+udpvLly+jRYsWiI2N5dIqHRwcMG/ePI0nZHr16hVsbGywadMmDB48ON9yLi4u6N+/P2bPnp3vfiwsLHDu3Dm0bdu20OPSKAlCCClZZTZKwmIkDISqE/hpIkeRhZMvf6FREgUpz2mVCoUCaWlpasOr8tYFQL5lMjMzkZqaylsIIYRUQPRIomQpcyScnZ1haGgId3d3TJkyRee0Sn9/f4SFhcHMzAzt27dHYmKi2v1okla5bNkyvH37Fv369VP7vkKhwJQpU9CqVSs0btxYbRkKnyKEkEqCGgwlq7ymVe7cuRPz5s3D3r17uT4OHxs/fjxu3LiB3bt357sfPz8/pKSkcMuzZ8/yLUsIIYSUZ5RW+ZHdu3dj5MiRCA0NRadOndSWmTBhAsLCwvDHH3/A1tY23/OTSCSQSHSb+YsQQogeobTKklXe0ip37dqF4cOHY9euXfD19VV5nzGGCRMm4ODBgzh9+nS+OReEEEIqF8YURVr0AaVVfrBz504MHToUq1atgqenJ3ccmUwGU1NTALmPIXbu3InDhw+jatWqXBlTU9MC+0MQQggh+o7SKj9o3749zp07p7J+6NCh2LJlCwD1aZYAEBISgmHDhhV6vjSskhBCSlZZDavsWG0IDAQ6DqtkWTiV/Gu5H1ZJaZWliBoMhBBSssqswWA6uGgNhpRt5b7BQFkShBBCSFEpFIBAx74IetKHgeKtCSGEEFIoCp/SInzKwcFB7T7Gjx9fcheJEEJI+VcJJm4q00cSyvCprVu3wsXFBVFRURg+fDhMTU0xadIkXvhU06ZNkZSUhMmTJ6NHjx6Iiori9rN//36MGjUKixYtQocOHZCTk8ObGrp///747LPPeMceNmwYMjIyVMKnFi1ahGrVqiEkJATdu3fH33//DXd3dwC5ORZyuZzbx40bN9C5c2eV0RiEEEIqF6ZQgOn4SEJfhlVS+FQRwqemTJmCsLAw3L9/P98RFHlRp0dCCClZZdXpsYOsf5E6PZ5+v6fcd3qk8Kl8FBY+lZWVhe3bt2PEiBEaNRYIIYQQfVamjyRmzJiB1NRUODs7QyQSQS6XY+HChTqHTwUFBcHBwQHLly9H+/btce/ePbVf+MURPnXo0CEkJycXOP9CZmYmMjMzudeUVkkIIRWUggECHW/Y60kfBgqfUkOT8KlNmzaha9euqFWrVr77obRKQgipJBjLHR6p06IfDQYKn/qIJuFTsbGxOHnyJA4cOFDg+fn5+WHatGnc69TUVGo0EEJIBcQUDEzHOwz6Mn8ihU/lUVj4lFJISAgsLCwKLAPkNlxMTEx4CyGEEFJUa9asgYODA6RSKTw9PXHp0qUCy4eGhsLZ2RlSqRSurq44duyY1scs0waDMnzq6NGjePLkCQ4ePIigoCD07t0bwH/hU1FRUdixYwcXPhUfH4+srCwA4IVPnThxAnfv3sXYsWMBaB8+NWTIECxfvpwLn4qPj0dKSgqvnEKhQEhICIYOHQoDA5ookxBCCIrwOEKh9UyPe/bswbRp0zBnzhxER0ejadOm8PHx4eYV+lhkZCQGDhyIb775BlevXkWvXr3Qq1evAgcHqEPhUx9oEj4FACdOnICPjw/u3r2LBg0aaHW+NKySEEJKVlkNq2wv6K3z53oOy8ZZdlDjOnt6eqJ58+YIDg4GkPuHrJ2dHSZOnIgZM2aolO/fvz/S09MRFhbGrWvZsiXc3Nywbt06jetJ4VOliBoMhBBSssqswVCEz3Vt6pyVlYUqVapg3759vBmNhw4diuTkZBw+fFhlm9q1a2PatGmYMmUKt27OnDk4dOgQrl27pnE96Z56KVK2zXKQDVAzjRBCil0OsgGUfkfConyuK+v88dB7iUQCiUTCW/f69WvI5XJYWlry1ltaWuLOnTtq9x8fH6+2fHx8vFb1pAZDKUpLSwMAnIf2nU0IIYRoLi0tDaampiV+HLFYDCsrK5yPL9rnurGxscooujlz5mDu3LlF2m9xogZDKapVqxaePXsGxhhq166NZ8+eaXzLTDkkU5ttdN2OjkXHomPRsfT1WIwxpKWlFThHTnGSSqV4/Pgx1xFfV4wxlVmDP767AAA1a9aESCRCQkICb31CQgKsrKzU7tvKykqr8vmhBkMpEgqFsLW15W476TLUUtfhmXQsOhYdi45VWY5VGncW8pJKpZBKpaVyLLFYDA8PD5w6dYrrw6BQKHDq1ClMmDBB7TZeXl44deoUrw9DREQEvLy8tDo2NRgIIYQQPTJt2jQMHToUzZo1Q4sWLbBy5Uqkp6dj+PDhAIAhQ4bAxsYGAQEBAIDJkyejXbt2WL58OXx9fbF7925ERUVhw4YNWh2XGgyEEEKIHunfvz9evXqF2bNnIz4+Hm5ubggPD+c6Nj59+pQ3KaK3tzd27twJf39/zJw5E/Xr18ehQ4fQuHFjrY5LDYYyIJFIMGfOHLXPp4pzGzoWHYuORceiY1VMEyZMyPcRxNmzZ1XWffnllyqTGWqL5mEghBBCSKHKdGpoQgghhOgHajAQQgghpFDUYCCEEEJIoajBQAghhJBCUYOBEEIIIYWiBgMhFQANdio75f3a5+TklHUVSAVBDYYS9vz5c7x+/Zp7/eeff+Krr75CmzZt8PXXX+PixYtqt3vz5g3OnDmDxMREALkJZUuWLMH8+fNx+/btfI/3+vVrLF26FL1794aXlxe8vLzQu3dvBAYG4tWrVyrlJ06ciD///LOIZ/mfOnXq4P79+zpt++zZM4wYMULte8HBwRgyZAh2794NANi2bRsaNWoEZ2dnzJw5U+VDMTo6Go8fP+Zeb9u2Da1atYKdnR1at27N7Ued27dvIyQkhEt+u3PnDsaOHYsRI0bg9OnTare5desWxo0bB3d3d1hbW8Pa2hru7u4YN24cbt26pXab7t27Y9u2bXj//n3+F0VDEomkwN+LwuR37ePi4jB79mx06NABDRs2hIuLC7p3745NmzZBLper3Zeu116X6w5of+2L87oDhV/7uLg4bN++HceOHVPJG0hPT8f8+fPVbnft2jUMGTIEderUgUwmg5GREVxdXTFr1iyVVEMACA8Px/Xr1wHkThW8YMEC2NjYQCKRwNbWFosXL863caPL5422nzVA8XzeMMZw5swZbNy4EWFhYcjOzi7S/ogWGClRLVq0YL/99htjjLFDhw4xoVDIevTowX788UfWu3dvZmhoyL2v9PfffzNTU1MmEAiYmZkZi4qKYo6Ojqx+/fqsbt26TCaTsStXrqgc69KlS8zMzIzZ2NiwoUOHsh9++IH98MMPbOjQoczW1pZVr16dXb58mbeNQCBgQqGQ1a9fny1evJjFxcVpdF6rVq1Su4hEIubn58e91kZMTAwTCoUq6xcsWMCqVq3K+vTpw6ysrNjixYtZjRo12P/+9z+2aNEiZm5uzmbPns3bpkmTJiwiIoIxxtjGjRuZTCZjkyZNYmvXrmVTpkxhxsbGbNOmTSrH+v3335lYLGbVq1dnUqmU/f7778zc3Jx16tSJdejQgYlEInbq1CneNseOHWNisZi1bNmSzZkzh/3888/s559/ZnPmzGHe3t5MIpGw8PBwlWMJBAJmYGDATE1N2ZgxY1hUVFSh12jq1KlqF6FQyIYMGcK91pa6a3/58mVmamrKPDw8WOvWrZlIJGKDBw9m/fv3Z9WqVWPe3t4sNTVVZV+6XHtdrjtjul17Xa47Y7pd+0uXLrFq1aoxExMTJpPJWL169diNGze49+Pj49X+zoeHhzOZTMb69OnDvv76a1alShU2YcIE9uOPP7J69eqxunXrqvxfdXJyYn/88QdjjLFFixaxGjVqsKCgIPb777+zlStXMktLS7Z48WKVY+nyeaPLZ43y2mv7edO1a1eWnJzMGGPszZs3zNPTkwkEAmZubs6EQiFzdnZmL1++LHQ/pOiowVDCjIyM2KNHjxhjjHl6eqr8h129ejVzd3fnrevUqRMbOXIkS01NZYGBgczW1paNHDmSe3/48OGsV69eKsfy9PRk3377LVMoFCrvKRQK9u2337KWLVvy1gsEAnby5Ek2efJkVrNmTWZoaMh69OjBfvvtNyaXy/M9L4FAwGxtbZmDgwNvEQgEzMbGhjk4ODBHR0feNocPHy5wWbFihdoPz7p167L9+/czxnK/2EQiEdu+fTv3/oEDB1i9evV428hkMvbkyRPGGGPu7u5sw4YNvPd37NjBGjVqpHIsLy8v9tNPPzHGGNu1axczMzNjM2fO5N6fMWMG69y5M2+bJk2asFmzZuV7rebMmcNcXV1V1gsEAnbz5k22YsUK5urqyoRCIWvatClbvXo1S0xMVLsvgUDA3NzcWPv27XmLQCBgzZs3Z+3bt2effvqpyna6XPtWrVqxuXPncq+3bdvGPD09GWOMJSYmMjc3NzZp0iSVY+ly7XW57ozpdu11ue7K7bS99p06dWLDhw9ncrmcpaamsrFjx7IaNWqw6Ohoxlj+DQY3Nze2du1a7vWJEyeYs7MzY4yxrKws1rFjRzZs2DDeNhKJhMXGxjLGGGvcuDHbu3cv7/2wsDCV/yfKOmr7eaPLZ43yGmr7eSMQCFhCQgJjjLGxY8eyRo0acZ+pz549Yx4eHmzMmDFqtyXFixoMJczU1JRdu3aNMcaYhYUF92+lBw8esCpVqvDWmZmZsVu3bjHGcj8chEIh+/vvv7n3r1y5wmxsbFSOJZVK2e3bt/Oty+3bt5lUKuWty/ufMSsri+3Zs4f5+PgwkUjEatWqxWbOnMnu37+vsq/Ro0czNzc3rp5KBgYG7ObNm2qPr/zrQiAQ5Luo+/CUyWTcByFjjBkaGvL+Snvy5InKNaxRowb3l6OFhQWLiYnhvf/gwQMmk8lUjmViYsKdr1wuZwYGBtyHO2OMXb9+nVlaWvK2kUql7M6dO2rPmTHG7ty5o3LdlddDee0Zy/1L79tvv2WmpqZMJpOxgQMHqvxVHRAQwBwdHVXWF3TdlcfS9trLZDL28OFD7rVcLmeGhoYsPj6eMZb7JVarVi2VY+ly7XW57ozpdu11ue6M6XbtzczM2N27d1X2Y2Zmxi5dupRvg0EqlbLHjx9zrxUKBTM0NGT//vsvY4yxP/74g5mbm/O2sba2ZhcvXmSMMWZpacm7fowxdu/ePbW/87p83ujyWcOYbp83ebdxcnJihw8f5r1/8uRJlT9OSMmgPgwlrF27dti1axcAwN3dXWWO7zNnzsDGxoa3LisrCzKZDABgaGiIKlWqoGbNmtz7NWvWxJs3b1SOZWVlhUuXLuVbl0uXLnHhJOoYGhqiX79+CA8Px6NHjzBq1Cjs2LEDTk5OKmXXrVuH2bNnw8fHB8HBwfnuMy9ra2scOHAACoVC7RIdHa12OysrK+5Z9P379yGXy3nPpm/evAkLCwveNl27dsXatWsB5P4M9u3bx3t/7969qFevntrjKTPphUIhpFIpLyq3atWqSElJ4ZV3cHDA0aNH8z3vo0ePwt7ePt/3lVq0aIH169fj33//xc8//4xnz56hc+fOvDIzZszAnj17MHbsWEyfPl3j57e6XHsLCwvExcVxrxMSEpCTk8PFCdevX5975p2Xrtde2+sOFM+11+S6A7pf+4yMDJX9zJw5E126dEFkZKTabWxsbHD37l3u9cOHD6FQKFCjRg0AgK2tLd6+fcvbpnfv3li4cCHkcjl69uyJn3/+mddnYfXq1XBzc1M5li6fN0X9rFEeS9PPG+XvRlJSEurWrct7r169evj3338LPBYpJmXdYqnobt26xWrUqMGGDBnCFixYwIyNjdnXX3/NFi5cyIYMGcIkEgkLCQnhbePs7Mz7KyYsLIy9e/eOe/3XX38xW1tblWMFBwcziUTCJk2axA4fPsz++usv9tdff7HDhw+zSZMmMZlMxtasWcPb5uO/tj6mUCjYiRMn8n3/+fPnrEOHDuyzzz5jcXFxBf611b179wJvH8fExDCBQKCy3t/fn5mbm7ORI0cyR0dHNmPGDFa7dm22du1atm7dOmZnZ6fy7PjFixfMwcGBtW3blk2bNo3JZDLWunVrNmrUKNa2bVsmFovZ0aP/396ZR0VxpW387WYRupFFRBqUTbGhDZBRYxAXcEOMcdcgoqIjTqIcY+KAuCWCins84pIwThSJC6C4zSFuuIALjJq4jaMeQcQNjZqJIppPRHi+PzjUseluwOpuiPH9nVPnWPf2c5/bRVn19r233tqr4eXn54f9+/cL+5cuXUJ5ebmwf/z4cY1fM9u3b4epqSkGDhyIVatWIT09Henp6Vi1ahUGDRoEc3Nz7NixQ8OrrmMPQOPXaTWlpaWIiIiAn58fLl26BDMzs1pHGMQc+y+++AI+Pj7Yv38/jh49ip49e6JHjx5C/YEDB9CmTRuNtsQcezHHHRB37PU57sCbHfvu3burTS28ztKlS9GkSROtIwzz5s1Dq1atkJSUhOTkZPj4+GDo0KFC/a5duzSmdZ48eYIPPvgAnp6eGDt2LCwsLODm5obg4GB4eHjAxsYGp06d0vASc70Rc60BxF1vJBIJ+vfvj6FDh8LOzk5jzdepU6e0jj4xhocDhgbg+vXrCAsLQ9OmTYXhXzMzM3Tp0gW7d+/W+Hx8fDzS0tJ0tjd79mwMGzZMa116ejr8/f1hamoqeJmamsLf3x/btm3T+Ly7uzt+/fVX0d8NqPpPvmjRIigUCpiYmOi8eB4/flztplCTZ8+eIScnR6O8oqICCxcuxIABA7Bo0SJUVlYiLS0NLi4usLe3x/jx4/Hs2TMN3ePHjzFjxgy0a9cOFhYWMDc3h5ubG8LDw7UuyAKApKQk/Pjjjzr7OGvWLERGRmqU5+bmYuTIkXB1dYW5uTnMzc3h6uqKkSNHIi8vT2tbPXr0wOPHj3V61Ye0tDQ4OjpCKpXWGjCIOfalpaUIDQ0VzqUuXboIc8cAcPDgQY158mre9NiLPe7Amx97Qxx3oH7H/vvvv8eYMWN0trFkyRK4u7trlJeXlyM2NhbOzs6wt7dHeHg4Hj16JNSfPn0ax44d09C9fPkSSUlJ6N+/P7y9vaFUKhEUFITZs2fjzp07Wvsg9nrzptcaQNz1Zvz48WpbzbanT5+OkJCQN2qTEQe/rbIBAUAPHz6kyspKat68OZmZmYlq5/fffycTE5NaX+1aXl4uPM6pj9ebcPbsWTp58iRFRESQnZ2d0f2YKu7evUtnz56lPn36kFwuN3j7L168oFevXpGVlZXB237bMfax/yNQ1/WmMa41r/P8+XMyMTEhCwuLBvV9F+GAoZEoKioiFxcXMjU1NbrXq1ev3thHjEYfAAjzlA2hqy9lZWVERLUGZ0z9yMnJIX9/f2G+3FiUlZXR3bt3qVWrVvX+u4nR6MODBw8IACkUCqPoKioq6NdffyWpVEoODg76dJVhBHjRYyPh5eVV7wRH9+7do7i4OBo9ejTFxMQIiW1qIiZxi9hkL2KS35SVlVFMTAwFBgbS0qVLiYgoISGBrKysqGnTphQeHq41IY0unVwur1X3polvqjl06BD179+f7OzsSCaTkUwmIzs7O+rfvz8dPny43t+3mqtXr1Lr1q0Nprt48SIlJCTQd999p5YUjIjo6dOnOpNfrV+/nsaNG0cbN24kIqJt27aRSqWi1q1bU1xcnME0uujbty/dvHlTa93Dhw/V9i9cuEDjxo2jrl270ogRIzQWC1eTkpIiJD978eIFRUZGklwuJ6VSSVZWVjRp0iQh6NNHQ0Tk6+tLCxYsoDt37tT7O//22280YsQIcnV1pcmTJ1NFRQVNnDiRnJycqGXLltSlSxe1haX66vbu3UuBgYEkl8vJ2dmZFAoF2dra0tixY+n27ds6+ykm8VhtFBYWUq9evQymE5v8ijEwjTQV8s4wdOhQrZtUKkWfPn2E/dextLQUEpFcvnwZNjY28PT0xCeffAJvb2/IZDKNxzMBcYlbxCZ7EZt0yNnZGdHR0VCpVIiKioKrqyu2bNmC1NRUeHp64vPPPzeITkziGwBISUmBqakpwsLCsHHjRuzbtw/79u3Dxo0bMWrUKJiZmWHTpk11ftfX0ZWQSozu4MGDMDc3x3vvvQdXV1fY29vj6NGjQr2ux/RWrlwJuVyOYcOGwcnJCQkJCULyq3nz5sHa2hrr1q3TWwNU5V7QtkkkEqhUKmH/daRSqbAYLjc3F2ZmZggKCsL06dMRHBwMU1NTrXP2Hh4ewkK+mJgYuLu7Y9euXbh69Sr27NkDpVKJ6dOn660Bqs55e3t7mJiYICQkBDt27FBbmKmNCRMmwMfHB2vWrEFQUBAGDx4MPz8/nDx5Enl5eejUqRMiIiIMotu0aROaNm2K6OhozJkzBwqFAjNnzkRSUhKCgoLQvHlz5Ofna3iJTTxWG4Y858Umv2IMDwcMRkYikSAoKEhj4Y5UKsWQIUOE/Zqa6ovn4MGDMXDgQOHCVFFRgbCwMAwYMEDDS0ziFrHJXsQkv3FxcREyABYWFkIqlWLPnj1CfVZWFtzc3AyiE5P4BgDatm2LtWvXau0/AHz77bcax0NXBsDqbcyYMVovaGJ0AQEBQkKjyspKLF26FFZWVsKCRl0XT29vb2zduhUAcO7cOZiammL9+vVC/fr169GxY0e9NUBVXoJ+/fohPj5e2OLi4iCVShEVFSWUvc7r53xwcDAmTJigVv/FF1+gV69eGl6vn79KpVJjYeexY8fg6uqqt6a6j8XFxdi9ezcGDhwIU1NTODg4IDo6WiMfSTVOTk7Izc0FUPW3kUgkak8BnDx5UmtOFTE6b29vpKenC/s//fQTWrVqJSRXGjlypMaPE0Bc8itdmV6rt9jYWK3noRid2ORXjOHhgMHIpKWloVWrVkhOTlYrryvBUfXF08XFRRgBqObcuXNwcnLS0IlJ3CI22YuY5Dd1JWAqKirSSMAkVicm8Q1QdTN500RAUqkUHTp00MgAWL198MEHWi9oYnTW1ta4fv26WtnWrVshl8uRmZmp8+JZ8xg2adJE7RgWFBTA1tZWbw1QdTNr06YN5s6dq5a9r77n/OvnZDX//e9/0bx5cw2dm5ubMMLSsmVLjScwrly5ArlcrremZh8B4N69e1i0aBHatm0LqVSKgIAAjZTXMplMyHoJVJ27ly5dEvZv3Lih1UuMztLSUu2cB6qOeXFxMYCq/6Pa/l5ik185OztrZHqt3pydnbWeh2J0YpNfMYaHA4YGoKioCF27dsWwYcOEX9+1XTylUqkwJeHm5qYx/XDjxg2tWdSioqIwYMAAvHr1Cp9++ikmTpyolrr1888/R0BAgN4aQPfz1M+fP8fGjRvRrVs3jf/EXl5ewi+gM2fOwNzcXC2QSk9PR9u2bTXaFKNr06aN2jBqQUEBTExMUFZWBqDqGGoLhDp06KB1OLqa2NhYdOjQQa1MqVRi8+bNOjXnz5/XekETo3NwcNA6/ZOWlgaZTIakpCStXvb29mq/glu1aqV2QyooKICVlZXemmqePHmCsLAw+Pv7CwFOXQHD9evXUVJSAg8PD43AVVtGVKDqkb+AgAA8fvwYM2fOxMCBA1FaWgqg6lwMDQ1F37599dYA6tMmNcnOzsaYMWM0buLvv/++MGK1b98+NG3aFCtWrBDqk5KS4OPjo9GeGJ1KpUJGRoawf/bsWZibm+PVq1cAqv5e2oITb29vtbZrsmLFCnh5eamVubu763x0EtB9zovR2dnZaZ2CXb58OWxtbbFr1y4OGBoIDhgaiIqKCsydOxcuLi44cOBArcleJBIJbG1tYWdnBzMzM42bSlZWltZnt8UkbhGb7EVM8puVK1fCwsICffr0gZ2dHVavXg2FQoHY2FjMnDkTNjY2mD9/vkY7YnRiEt8AVRd+uVwOX19fTJs2DUuWLMGSJUswbdo0+Pn5wcrKSmMuPTw8HF9++aXO46ArIZUYXXBwMJYvX67186mpqTAzM9N68ezatavacHVNMjMzNW5AYjQ1SU5OhkKhwLp16+o856VSqZC+uub7J/71r39pnRorKyvDoEGDYGdnh+DgYFhYWEAmk6Ft27aQy+VwdXXVOA/FaKr7WNc5X1JSora/ZcsWmJiYwNPTE02aNEFGRgacnZ0RGhqKsLAwmJuba50CE6Nbu3YtbGxsEBsbi7lz58LZ2Vktd8WWLVs01o4A4pJfDR8+HLGxsTqPg65zXoxObPIrxvBwwNDAnDhxAh4eHrUme0lJSVHbag7Pzp8/X+cbCcUkbhGjEZv8ZuvWrZgyZQpSU1MBVN2gu3fvjo4dOyI+Pl7nC2jeVCc28Q1QNSIUGxuLwMBAKJVKKJVKBAYGYsaMGRpDvgBw//59tV/e9UWMbteuXbUGGVu3blXLxljNyZMncf78eZ26b7/9FmvWrNFbo438/Hx06tRJWPeijZycHLWt5g07MTERy5Yt0+mxf/9+REVFoV+/fujbty/GjRuHf/7zn1oTeonVjB8/XuvbOevi5MmT+Oabb4Q1CZcvX8bYsWMxfPhwpKSkGFT33XffoUuXLujYsSNmz56N//u//xPq8vPzdb7/4U2TX12+fFln8jOg6pqi7dwWoxOb/IoxPJyHoRF49uwZFRYWkre3Nz/fz7wTVFZWUmlpKVlbWxs1bwbDMMaDA4YGpKSkhH755Rciqnp5y+sv1zGkhr0M48UwDMO8RuMOcLwbfP/991CpVGpztFKpFCqVSu0xtdo01VttGkN51Ucjto+G+l7G9KoNMc+XG/KZdPZiL2N47d27F5GRkZg+fbrGI6K//fYbevbsWaum5lSHLo1YnVgvxrBwwGBkli1bBplMhpkzZyI7OxtXrlzBlStXkJ2djVmzZkEul2ssYhOjYS/DeNWFrsVchtawF3s1lNfWrVthYmKCjz/+GN26dYOFhQW2bNki1Gt7bFGMpqG9GMPDUxJGxs3NjZYvX06hoaFa67dt20bTp09XS9sqRsNehvEaNmyY1s9XU1JSQjk5OVRRUaGXhr3Y64/i1b59e/rrX/9KU6dOJSKi7du304QJE2jVqlUUGRlJDx48IGdnZzWdGE1DezGGp+HeLvSO8vDhQ/L19dVZ7+vrq/E+ADEa9jKMV2ZmJgUHB5Ojo6NWnbaLkhgNe7HXH8WroKCABg4cKOyHhoaSg4MDDRo0iMrLy2no0KEG0TS0F2MEGnuI489O9+7dERERoTXn/KtXrxAREYHAwEC9NexlGC9fX99a1zdoSywjRsNe7PVH8dKWWROoetTVysoKc+bM0dCJ0TS0F2N4eITByKxdu5ZCQkJIoVBQYGCgEP0/ePCAjh8/Tubm5pSVlaW3hr0M49WxY0c6d+4cRUZGatQRVb3m2tXVVW8Ne7HXH8Xrww8/pP3791Pnzp3VyoOCgigzM5MGDBhgEE1DezGGh9cwNAClpaW0ZcsWOnXqlNrjfQEBARQeHk7W1tYG0bCX/pqysjKqqKggmUymtR/aEKNhL/b6o3gdO3aM8vLyaNasWVrrs7OzadOmTcIrzsVqGtqLMTwcMDAMwzAMUyfSxu4AwzAMwzB/fDhgMDLl5eUUGxtLnp6e9OGHH1JycrJa/YMHD8jExERvDXuxF3uxF3sxRqVx11z++YmLi4OjoyOWL1+OOXPmwMbGBp9++qlQ/8svv2gkUxGjYS/2Yi/2Yi/GmHDAYGQ8PT2RmZkp7BcUFMDT0xPjx49HZWWl1ixlYjTsxV7sxV7sxRgTDhiMjKWlpcYrke/evQulUonRo0ejuLhY42QXo2Ev9mIv9mIvxphwwGBkPDw8cPjwYY3y4uJiKJVKBAcHa5zsYjTsxV7sxV7sxRgTXvRoZHr16kWpqaka5c7OznT06FEqKioyiIa92Iu92Iu9GKPS2BHLn52bN2/iwIEDOuuLi4uRkpKit4a92Iu92Iu9GGPCiZsYhmEYhqkTfpeEkSkrKyOpVEpmZmZERFRYWEjJycl0+/ZtcnNzo8jISPLw8NBbw17sxV7sxV6MUWnsIY4/O0FBQcjIyAAAnDx5Ek2aNIGfnx9GjhyJ9u3bQyaTIS8vT28Ne7EXe7EXezHGhAMGI2NtbY38/HwAVSf+tGnT1Oq/+uordO3aVW8Ne7EXe7EXezHGhAMGIyOXy3H16lUAgKOjIy5cuKBWf/36dVhZWemtYS/2Yi/2Yi/GmPBjlUbG39+fMjMziYioTZs2dPHiRbX6CxcuULNmzfTWsBd7sRd7sRdjTHjRo5FJSEigjz76iJ4/f06jRo2i6OhoKigoIJVKRdeuXaPVq1drvOddjIa92Iu92Iu9GKPS2EMc7wJ5eXno3LkzJBKJ2tayZUskJiYaTMNe7MVe7MVejLHgPAwNyKNHj+jGjRtUWVlJTk5O5O7ubhQNe7EXe7EXezGGhgOGBub58+e0fft2un79Ojk7O1NYWBjZ29sbXMNe7MVe7MVejEFp3AGOPz8qlQr/+9//AAC3b9+Gu7s7bGxs0KlTJzRr1gwtWrTAjRs39NawF3uxF3uxF2NMOGAwMhKJBA8ePAAAjB49Gl26dMGTJ08AAKWlpejTpw9GjRqlt4a92Iu92Iu9GGPCAYORef1kb926NbKystTqc3Nz4eLioreGvdiLvdiLvRhjwnkYGgCJREJERC9evCAnJye1upYtW9KjR48MomEv9mIv9mIvxlhwHoYGoHfv3mRqakpPnz6la9eukY+Pj1B369YtrQt2xGjYi73Yi73YizEWHDAYmbi4OLV9Kysrtf3MzEzq3r273hr2Yi/2Yi/2YowJP1bJMAzDMEyd8BoGhmEYhmHqhAMGhmEYhmHqhAMGhmEYhmHqhAMGhmEYhmHqhAMGhtHB+PHjaciQIQZrLyUlhWxtbQ3WXm24u7tTYmJig3i9jUgkEtqzZ09jd4Nh3io4YGDeSSQSSa1bfHw8rVq1ilJSUhq8b9nZ2dS/f3+yt7cnmUxG7dq1o+joaCouLm7wvhiD+Ph4kkgkNGnSJLXyCxcukEQioZs3bzZOxxiGqRUOGJh3kvv37wtbYmIiWVtbq5XFxMSQjY1Ng40IVLNu3Trq06cPKRQK2rlzJ125coX+8Y9/UElJCa1YsaJB+2JMLCwsaMOGDVRQUNDYXTEYL1++bOwuMIxR4YCBeSdRKBTCZmNjQxKJRK3MyspKbUri0aNHpFAoaNGiRUIbeXl5ZG5uTkeOHCEiorKyMoqJiaGWLVuSXC4nf39/ysnJqXef7t69S1OnTqWpU6dScnIy9ejRg9zd3SkwMJDWr19Pc+fOFT67c+dOeu+996hJkybk7u5eazBx8+ZNkkgkdOHCBaHsyZMnJJFIhP7l5OSQRCKhgwcPUvv27cnS0pJ69epFDx8+pP3795NKpSJra2sKDw+n33//XWinR48eNHXqVIqNjaVmzZqRQqGg+Pj4Or+rl5cX9ezZk+bMmaPzM9qmcPbs2SOkCSaqGq34y1/+QsnJyeTq6kpWVlYUFRVFFRUVtGzZMlIoFNSiRQtauHChRvv379+njz76iCwtLal169a0Y8cOtfo7d+5QaGgo2draUrNmzWjw4MFqox/V58fChQvJ2dmZvLy86vzeDPM2wwEDw9QDBwcHSk5Opvj4ePr555+ptLSUxo4dS1OmTKHevXsTEdGUKVPo3//+N6Wnp9N//vMf+uSTT6hfv371/hWdkZFBL1++pNjYWK311TfPs2fPUmhoKIWFhdGlS5coPj6evv76a4NMn8THx9PatWspLy9PuGEmJiZSamoq7d27l7KysmjNmjVqmh9++IHkcjmdPn2ali1bRvPnz6dDhw7V6bVkyRLauXMn/fzzz3r1ubCwkPbv308HDhygtLQ02rBhA3388cd09+5dOnbsGC1dupS++uorOn36tJru66+/puHDh9PFixdp9OjRFBYWRlevXiUiovLycgoJCaGmTZvSiRMnKDc3l6ysrKhfv35qIwlHjhyha9eu0aFDh+jHH3/U63swzB+exn77FcM0Nhs3boSNjY1G+bhx4zB48GC1sqioKCiVSoSHh8PX1xcvXrwAANy6dQsmJiYoLi5W+3zv3r0xa9asWn2qmTx5Mqytrevsb3h4OIKDg9XKpk+fjnbt2gn7bm5uWLlyJQCgqKgIRITz588L9Y8fPwYRITs7GwCQnZ0NIsLhw4eFzyxevBhEhMLCQqHss88+Q0hIiLAfFBSEbt26qfWlU6dOmDFjhs7+x8XF4f333wcAhIWFoVevXgCA8+fPg4hQVFQEQPvx2r17N16/bMXFxUEmk+Hp06dCWUhICNzd3VFRUSGUeXl5YfHixcI+EWHSpElqbfv7+2Py5MkAgM2bN8PLywuVlZVCfVlZGSwtLXHw4EEAVeeHo6MjysrKdH5Xhvkzwe+SYJg34JtvviEfHx/KyMigs2fPUpMmTYiI6NKlS1RRUUFKpVLt82VlZfV+MQ4AteF2XVy9epUGDx6sVta1a1dKTEykiooKMjExqee30cTPz0/4t6OjI8lkMmrdurVa2ZkzZ3RqiIicnJzo4cOH9fJLSEgglUpFWVlZ1KJFC1F9dnd3p6ZNm6r10cTEhKRSqVpZzT4FBARo7FdP21y8eJGuX7+u1i5R1dsSCwsLhX1fX18yNzcX1W+GedvggIFh3oDCwkK6d+8eVVZW0s2bN8nX15eIiJ49e0YmJiZ09uxZjRt2zZfl6EKpVFJJSQndv39f4xW++lB948Rrr40pLy/X+lkzMzPh3xKJRG2/uqyyslKnRtdndNGmTRv629/+RjNnzqQNGzZo9Bs1XnWjrd/a/PXpE1HV37Njx460detWjToHBwfh33K5vN5tMszbDq9hYJh68vLlSxozZgyNHDmSFixYQBMnThR+tbZv354qKiro4cOH5OnpqbYpFIp6tT9ixAgyNzenZcuWaa1/8uQJERGpVCrKzc1Vq8vNzSWlUql1dKH6Bnf//n2h7PUFkI3N3LlzKT8/n9LT09XKHRwcqLS0lJ4/fy6UGbLfp06d0thXqVRERNShQwcqKCigFi1aaPw9bWxsDNYHhnmb4ICBYerJnDlzqKSkhFavXk0zZswgpVJJEyZMIKKq0YHRo0dTREQE7dq1i4qKiujMmTO0ePFi2rt3b73ad3FxoZUrV9KqVasoMjKSjh07Rrdu3aLc3Fz67LPPaMGCBUREFB0dTUeOHKEFCxZQfn4+/fDDD7R27VqKiYnR2q6lpSV17tyZlixZQlevXqVjx47RV199ZZiDYgAcHR3p73//O61evVqt3N/fn2QyGc2ePZsKCwspNTXVoHkxMjIyKDk5mfLz8ykuLo7OnDlDU6ZMISKi0aNHU/PmzWnw4MF04sQJKioqopycHJo6dSrdvXvXYH1gmLcJDhgYph7k5ORQYmIibd68maytrUkqldLmzZvpxIkTlJSUREREGzdupIiICIqOjiYvLy8aMmQI/fTTT+Tq6lpvn6ioKMrKyqLi4mIaOnQoeXt708SJE8na2loICDp06EDbt2+n9PR08vHxoblz59L8+fNp/PjxOttNTk6mV69eUceOHenLL7+khIQEvY6HoYmJidGYumnWrBlt2bKF9u3bR76+vpSWllavRzbry7x58yg9PZ38/Pxo06ZNlJaWRu3atSMiIplMRsePHydXV1caNmwYqVQqioyMpBcvXpC1tbXB+sAwbxMS1JwkZBiGYRiGqQGPMDAMwzAMUyccMDAMwzAMUyccMDAMwzAMUyccMDAMwzAMUyccMDAMwzAMUyccMDAMwzAMUyccMDAMwzAMUyccMDAMwzAMUyccMDAMwzAMUyccMDAMwzAMUyccMDAMwzAMUyccMDAMwzAMUyf/DzmNGRxDRS+yAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "@run\n",
    "def __visualize(observation__interpolator, /):\n",
    "    def visualize(\n",
    "        *,\n",
    "        name: str,\n",
    "        interpolator: auto.scipy.interpolate.RegularGridInterpolator,\n",
    "        num: int,\n",
    "    ):\n",
    "        lat0, lng0 = 35.572785, -83.518351\n",
    "        lat1, lng1 = 35.553081, -83.487097\n",
    "        \n",
    "        r0, c0 = convert_location_to_tile(\n",
    "            lat=lat0,\n",
    "            lng=lng0,\n",
    "            zoom=Tixel.z,\n",
    "        )\n",
    "        \n",
    "        r1, c1 = convert_location_to_tile(\n",
    "            lat=lat1,\n",
    "            lng=lng1,\n",
    "            zoom=Tixel.z,\n",
    "        )\n",
    "        \n",
    "        rlo, rhi = min(r0, r1), max(r0, r1)\n",
    "        clo, chi = min(c0, c1), max(c0, c1)\n",
    "\n",
    "        # real_rlo = interpolator.grid[0].min()\n",
    "        # real_rhi = interpolator.grid[0].max()\n",
    "        # real_clo = interpolator.grid[1].min()\n",
    "        # real_chi = interpolator.grid[1].max()\n",
    "        # assert rlo >= real_rlo, \\\n",
    "        #     f'{rlo=!r} < {real_rlo=!r}'\n",
    "        # assert rhi <= real_rhi, \\\n",
    "        #     f'{rhi=!r} > {real_rhi=!r}'\n",
    "        # assert clo >= real_clo, \\\n",
    "        #     f'{clo=!r} < {real_clo=!r}'\n",
    "        # assert chi <= real_chi, \\\n",
    "        #     f'{chi=!r} > {real_chi=!r}'\n",
    "\n",
    "    # rs = auto.numpy.arange(rlo, rhi)\n",
    "    # cs = auto.numpy.arange(clo, chi)\n",
    "\n",
    "        \n",
    "        rs = auto.numpy.linspace(rlo, rhi, num=num)\n",
    "        cs = auto.numpy.linspace(clo, chi, num=num)\n",
    "        \n",
    "        grid = auto.numpy.hstack(tuple(\n",
    "            v.reshape((-1, 1))\n",
    "            for v in auto.numpy.meshgrid(\n",
    "                rs,\n",
    "                cs,\n",
    "                indexing='ij',\n",
    "            )\n",
    "        ))\n",
    "        assert grid.shape == (len(cs)*len(rs), 2), \\\n",
    "            f\"\"\"Wrong shape: {grid.shape=!r}\"\"\"\n",
    "        \n",
    "        values = interpolator(grid)\n",
    "        values = values.reshape((len(rs), len(cs), -1))\n",
    "        \n",
    "        %matplotlib inline\n",
    "        plt = auto.matplotlib.pyplot\n",
    "        \n",
    "        fig = plt.figure()\n",
    "        ax = fig.add_subplot(111)\n",
    "        im = ax.imshow(values)\n",
    "        ax.set_yticks(auto.numpy.arange(0, len(rs), 5))\n",
    "        ax.set_yticklabels([f'{int(r)}' for r in rs[::5]], rotation=0)\n",
    "        ax.set_xticks(auto.numpy.arange(0, len(cs), 5))\n",
    "        ax.set_xticklabels([f'{int(c)}' for c in cs[::5]], rotation=90)\n",
    "        \n",
    "        ax.set_title(f\"Sample of {name} around Clingman's Dome\")\n",
    "        ax.set_xlabel('Tixel Column Number')\n",
    "        ax.set_ylabel('Tixel Row Number', rotation=90)\n",
    "        \n",
    "        fig.colorbar(im)\n",
    "        fig.tight_layout()\n",
    "        plt.show()\n",
    "    \n",
    "    visualize(\n",
    "        name='observation',\n",
    "        interpolator=observation__interpolator,\n",
    "        num=128,\n",
    "    )\n",
    " \n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ae88466e",
   "metadata": {},
   "source": [
    "### Save"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "id": "b22e54fd",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-08-16T17:04:15.273285Z",
     "start_time": "2023-08-16T17:03:53.848170Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wrote 656,719 bytes to /home/raustin9/src/Sunrise-Demo-Dev/temp/park-observation_0029846.npz\n"
     ]
    }
   ],
   "source": [
    "@run\n",
    "def __save(observation__interpolator, /):\n",
    "    def save(\n",
    "        *,\n",
    "        name: str,\n",
    "        interpolator: auto.scipy.interpolate.RegularGridInterpolator,\n",
    "    ):\n",
    "        path = auto.pathlib.Path.cwd() / 'temp' / f'park-{name}.npz'\n",
    "        auto.numpy.savez_compressed(\n",
    "            path,\n",
    "            points0=interpolator.grid[0],\n",
    "            points1=interpolator.grid[1],\n",
    "            values=interpolator.values,\n",
    "        )\n",
    "        \n",
    "        print(f'Wrote {path.stat().st_size :,d} bytes to {path}')\n",
    "    \n",
    "   \n",
    "    save(\n",
    "        name=f'observation_{SPECIES}',\n",
    "        interpolator=observation__interpolator,\n",
    "    )\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2e9e08f7",
   "metadata": {},
   "source": [
    "## Observation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "id": "2f85a376",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Decimate by factor of 3**2=9 from 50,302,980 to 5,591,040 vertices\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "5cb7ebb04791470caba44c362c34a0cf",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/2048 [00:00<?, ?row/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Counter({0: 5509124, 1: 57850, 2: 19583, 3: 4483})\n",
      "Wrote 5,591,048 bytes to /home/raustin9/src/Sunrise-Demo-Dev/data/observation_0029846/OSPGeometricModel.index.vec1uc.bin\n",
      "None\n"
     ]
    }
   ],
   "source": [
    "@run(scope='render', after=print)\n",
    "def observation(observation__interpolator, /) -> 'uint8[]':\n",
    "    \"\"\"OSPGeometricModel::index:uint8[]\"\"\"\n",
    "    \n",
    "    def Data(array: auto.numpy.ndarray, /, *, type: lib.OSPDataType) -> lib.OSPData:\n",
    "        if len(array.shape) == 0:\n",
    "            array = array[None, None, None]\n",
    "\n",
    "        elif len(array.shape) == 1:\n",
    "            array = array[:, None, None]\n",
    "\n",
    "        elif len(array.shape) == 2:\n",
    "            array = array[:, :, None]\n",
    "            \n",
    "        elif len(array.shape) == 3:\n",
    "            array = array[:, :, :]\n",
    "\n",
    "        else:\n",
    "            raise NotImplementedError()\n",
    "\n",
    "        src = lib.ospNewSharedData(\n",
    "            array.ctypes.data, type,\n",
    "            array.shape[0], array.strides[0],\n",
    "            array.shape[1], array.strides[1],\n",
    "            array.shape[2], array.strides[2],\n",
    "        )\n",
    "        lib.ospCommit(src)\n",
    "\n",
    "        dst = lib.ospNewData(type, *array.shape)\n",
    "        lib.ospCopyData(src, dst, 0, 0, 0)\n",
    "        lib.ospCommit(dst)\n",
    "\n",
    "        lib.ospRelease(src)\n",
    "        return dst\n",
    "    \n",
    "  \n",
    "    \n",
    "\n",
    "    rs = auto.numpy.arange(RLO, RHI)\n",
    "    cs = auto.numpy.arange(CLO, CHI)\n",
    "    # rs = auto.numpy.aran\n",
    "\n",
    "    def decimate(\n",
    "        rs: auto.np.ndarray,\n",
    "        cs: auto.np.ndarray,\n",
    "        /,\n",
    "        *,\n",
    "        duration: 'seconds',\n",
    "        rate: 'item/s',\n",
    "    ) -> tuple[auto.np.ndarray, auto.np.ndarray]:\n",
    "        total_items = len(rs) * len(cs)\n",
    "\n",
    "        actual_items = duration * rate\n",
    "    #             print(f'{items = } = {duration} * {rate}')\n",
    "\n",
    "        factor_items = total_items / actual_items\n",
    "\n",
    "        stride = int(auto.math.ceil(auto.math.sqrt( factor_items )))\n",
    "\n",
    "    #             stride = int(auto.math.ceil())\n",
    "    #             print(f'{stride = } = int(auto.math.ceil( {len(rs)} / {items} == {len(rs)/items} ))')\n",
    "\n",
    "        rs = rs[::stride]\n",
    "        cs = cs[::stride]\n",
    "\n",
    "        print(f'Decimate by factor of {stride}**2={stride**2 :,d} from {total_items :,d} to {len(rs)*len(cs) :,d} vertices')\n",
    "        return rs, cs\n",
    "\n",
    "    rs, cs = decimate(\n",
    "        rs, cs,\n",
    "        duration=[\n",
    "            1,  # lo resolution\n",
    "            10,  # medium resolution\n",
    "            1000,  # high resolution\n",
    "        ][TERRAIN_QUALITY],\n",
    "        rate=6260094,\n",
    "    )\n",
    "    \n",
    "    index = auto.numpy.zeros(\n",
    "        shape=(len(rs), len(cs)),\n",
    "        dtype='u1',\n",
    "    )\n",
    "    \n",
    "    for (ri, r) in enumerate(auto.tqdm.autonotebook.tqdm(rs, unit='row')):\n",
    "        grid = auto.numpy.hstack(tuple(\n",
    "            v.reshape((-1, 1))\n",
    "            for v in auto.numpy.meshgrid(\n",
    "                [r],\n",
    "                cs,\n",
    "                indexing='ij',\n",
    "            )\n",
    "        ))\n",
    "        assert grid.shape == (len(cs), 2), \\\n",
    "            f\"\"\"Wrong shape: {grid.shape=!r}\"\"\"\n",
    "#             print(f\"\"\"{grid[:, 0].min()=!r} ;; {grid[:, 0].max()=!r}\n",
    "# {grid[:, 1].min()=!r} ;; {grid[:, 1].max()=!r}\"\"\")\n",
    "        \n",
    "        try:\n",
    "            observation__interpolator.fill_value = 0\n",
    "            category = observation__interpolator(\n",
    "                grid,\n",
    "                method='nearest',\n",
    "            )\n",
    "            # interpolate.observation.fill_value = 0\n",
    "            # category = interpolate.observation(\n",
    "            #     grid,\n",
    "            #     method='nearest',\n",
    "            # )\n",
    "        except ValueError:\n",
    "            print(f'{grid.shape=!r}')\n",
    "            print(f'{auto.np.min(grid, axis=0)=!r}')\n",
    "            print(f'{auto.np.max(grid, axis=0)=!r}')\n",
    "            raise\n",
    "\n",
    "        assert category.shape == (len(cs),), \\\n",
    "            f\"\"\"Wrong shape: {category.shape=!r}\"\"\"\n",
    "        assert auto.numpy.all((0 <= category) & (category < 4))\n",
    "        \n",
    "        index[ri, :] = category\n",
    "    \n",
    "    index = index.reshape((-1,))\n",
    "    print(auto.collections.Counter(index.flat))\n",
    "    \n",
    "    \n",
    "    #--- Save to Disk\n",
    "\n",
    "    def Save(data: auto.numpy.NDArray, /, *, path: auto.pathlib.Path):\n",
    "        if not DO_SAVE:\n",
    "            return\n",
    "        \n",
    "        path.parent.mkdir(parents=True, exist_ok=True)\n",
    "        with open(path, 'wb') as f:\n",
    "            f.write(auto.struct.pack('I', len(data.shape)))\n",
    "            f.write(auto.struct.pack(f'{len(data.shape)}I', *data.shape))\n",
    "            data.tofile(f)\n",
    "        print(f\"Wrote {path.stat().st_size :,d} bytes to {path}\")\n",
    "\n",
    "    if SHOULD_SAVE:\n",
    "        Save(\n",
    "            index,\n",
    "            path=auto.pathlib.Path.cwd().joinpath(\n",
    "                f\"data\",\n",
    "                f\"observations\",\n",
    "                f\"observation_{SPECIES}\",\n",
    "                f\"OSPGeometricModel.index.vec1uc.bin\",\n",
    "            ),\n",
    "        )\n",
    "    "
   ]
  }
 ],
 "metadata": {
  "gist": {
   "data": {
    "description": "share/notebooks/Sunrise.ipynb",
    "public": false
   },
   "id": ""
  },
  "hide_input": false,
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.10.12"
  },
  "nbTranslate": {
   "displayLangs": [
    "*"
   ],
   "hotkey": "alt-t",
   "langInMainMenu": true,
   "sourceLang": "en",
   "targetLang": "fr",
   "useGoogleTranslate": true
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {
    "height": "539px",
    "width": "751px"
   },
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {
    "height": "calc(100% - 180px)",
    "left": "10px",
    "top": "150px",
    "width": "265.4px"
   },
   "toc_section_display": true,
   "toc_window_display": false
  },
  "varInspector": {
   "cols": {
    "lenName": 16,
    "lenType": 16,
    "lenVar": 40
   },
   "kernels_config": {
    "python": {
     "delete_cmd_postfix": "",
     "delete_cmd_prefix": "del ",
     "library": "var_list.py",
     "varRefreshCmd": "print(var_dic_list())"
    },
    "r": {
     "delete_cmd_postfix": ") ",
     "delete_cmd_prefix": "rm(",
     "library": "var_list.r",
     "varRefreshCmd": "cat(var_dic_list()) "
    }
   },
   "types_to_exclude": [
    "module",
    "function",
    "builtin_function_or_method",
    "instance",
    "_Feature"
   ],
   "window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}