{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
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   "source": [
    "# Natural language processing with DAAO\n",
    "\n",
    "<style>\n",
    "  a {\n",
    "    color: #1ea5a6 !important;\n",
    "  }\n",
    "</style>\n",
    "\n",
    "This is an exploratory data analysis of collected data from [DAAO](https://www.daao.org.au/). We focus on venues and organisations adopting natural language processing to reveal patterns in the data.\n",
    "\n",
    "The visualisations consist of...\n",
    "- word clouds\n",
    "- dendrograms\n",
    "- time series and temporal bar charts"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Import packages and pre-process data\n",
    "\n",
    "We have provided the code used to generate the data used in this notebook. Collapse `Tip` for more details on how to manage the data efficiently."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "```{admonition} Tip\n",
    ":class: tip, dropdown\n",
    "To ensure faster runtimes, change the `save_locally` parameter to `True` at **line 127** (second last line) in the following code block. This will save the data to your local machine and load it into the notebook. The location of the data is specified in the `folder_name` variable at **line 21**, so change this accordingly.\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "tags": [
     "hide-input"
    ]
   },
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   "source": [
    "# for data mgmt\n",
    "import numpy as np\n",
    "from collections import Counter\n",
    "import requests, gzip, io, os, json, pandas as pd\n",
    "import ast\n",
    "\n",
    "# for plotting\n",
    "import matplotlib.pyplot as plt\n",
    "import plotly.express as px\n",
    "import plotly.graph_objects as go\n",
    "\n",
    "from itables import show\n",
    "\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "\n",
    "# provide folder_name which contains uncompressed data i.e., csv and jsonl files\n",
    "# only need to change this if you have already donwloaded data\n",
    "# otherwise data will be fetched from google drive\n",
    "global folder_name\n",
    "folder_name = 'data/local'\n",
    "\n",
    "def fetch_small_data_from_github(fname):\n",
    "    url = f\"https://raw.githubusercontent.com/acd-engine/jupyterbook/master/data/analysis/{fname}\"\n",
    "    response = requests.get(url)\n",
    "    rawdata = response.content.decode('utf-8')\n",
    "    return pd.read_csv(io.StringIO(rawdata))\n",
    "\n",
    "def fetch_date_suffix():\n",
    "    url = f\"https://raw.githubusercontent.com/acd-engine/jupyterbook/master/data/analysis/date_suffix\"\n",
    "    response = requests.get(url)\n",
    "    rawdata = response.content.decode('utf-8')\n",
    "    try: return rawdata[:12]\n",
    "    except: return None\n",
    "\n",
    "def check_if_csv_exists_in_folder(filename):\n",
    "    try: return pd.read_csv(os.path.join(folder_name, filename), low_memory=False)\n",
    "    except: return None\n",
    "\n",
    "def fetch_data(filetype='csv', acdedata='organization'):\n",
    "    filename = f'acde_{acdedata}_{fetch_date_suffix()}.{filetype}'\n",
    "\n",
    "    # first check if the data exists in current directory\n",
    "    data_from_path = check_if_csv_exists_in_folder(filename)\n",
    "    if data_from_path is not None: return data_from_path\n",
    "\n",
    "    urls = fetch_small_data_from_github('acde_data_gdrive_urls.csv')\n",
    "    sharelink = urls[urls.data == acdedata][filetype].values[0]\n",
    "    url = f'https://drive.google.com/u/0/uc?id={sharelink}&export=download&confirm=yes'\n",
    "\n",
    "    response = requests.get(url)\n",
    "    decompressed_data = gzip.decompress(response.content)\n",
    "    decompressed_buffer = io.StringIO(decompressed_data.decode('utf-8'))\n",
    "\n",
    "    try:\n",
    "        if filetype == 'csv': df = pd.read_csv(decompressed_buffer, low_memory=False)\n",
    "        else: df = [json.loads(jl) for jl in pd.read_json(decompressed_buffer, lines=True, orient='records')[0]]\n",
    "        return pd.DataFrame(df)\n",
    "    except: return None \n",
    "\n",
    "def expand_DAAO_events(fname = 'DAAO_event_expanded_data.csv', save_locally=False):\n",
    "    # first check if the data exists in current directory\n",
    "    data_from_path = check_if_csv_exists_in_folder(fname)\n",
    "    if data_from_path is not None: return data_from_path\n",
    "\n",
    "    dfs = fetch_data(acdedata='event') # 40s\n",
    "\n",
    "    dfs_expanded = []\n",
    "\n",
    "    # get start and end years - 20 secs\n",
    "    for idx,row in dfs[dfs.data_source.str.contains('DAAO')].iterrows():\n",
    "\n",
    "        try: \n",
    "            this_locations = pd.json_normalize(ast.literal_eval(row['coverage_ranges']))\n",
    "\n",
    "            for idx2, row2 in this_locations.iterrows():\n",
    "                try: start_yr = row2['date_range.date_start.year']\n",
    "                except: start_yr = None\n",
    "\n",
    "                try: end_yr = row2['date_range.date_end.year']\n",
    "                except: end_yr = None\n",
    "\n",
    "                try: place_address = row2['place.ori_address']\n",
    "                except: place_address = None\n",
    "\n",
    "                try: \n",
    "                    latitude = row2['place.geo_coord.latitude']\n",
    "                    longitude = row2['place.geo_coord.longitude']\n",
    "                except:\n",
    "                    latitude = None; longitude = None\n",
    "\n",
    "                row['start_year'] = int(start_yr); row['end_year'] = int(end_yr)\n",
    "                row['latitude'] = latitude; row['longitude'] = longitude\n",
    "                row['place_address'] = place_address\n",
    "                dfs_expanded.append(row)\n",
    "\n",
    "        except:\n",
    "            start_yr = None; end_yr = None; latitude = None; longitude = None; place_address = None\n",
    "            dfs_expanded.append(row)\n",
    "\n",
    "    # remove last column of the dataframe and return df\n",
    "    if save_locally: pd.DataFrame(dfs_expanded).to_csv(f'{folder_name}/{fname}', index=False)\n",
    "    return pd.DataFrame(dfs_expanded)\n",
    "\n",
    "# read in expanded data\n",
    "dfs_expanded = expand_DAAO_events(fname = 'DAAO_event_expanded_data.csv', save_locally=False)\n",
    "dfs_expanded = dfs_expanded.drop_duplicates()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Summary statistics\n",
    "\n",
    "Firstly, we review at a high level the data we have collected in terms of richness across fields."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "In DAAO,\n",
      "- there are 21838 events.\n",
      "- there are 20544 events with dates.\n",
      "- there are 17214 events with geocodes and dates.\n",
      "- there are 7418 events with geocodes, dates and biographical information.\n",
      "- there are 7248 events with geocodes, dates and biographical information after filtering for events between 1900 and 2020.\n"
     ]
    }
   ],
   "source": [
    "locations_cond = dfs_expanded.latitude.notnull()\n",
    "year_cond = dfs_expanded.start_year.notnull()\n",
    "desc_cond = dfs_expanded.description.notnull()\n",
    "period_cond = (dfs_expanded.start_year >= 1900) & (dfs_expanded.start_year <= 2020)\n",
    "\n",
    "print('In DAAO,') \n",
    "print(f'- there are {dfs_expanded.shape[0]} events.')\n",
    "print(f'- there are {dfs_expanded[year_cond].shape[0]} events with dates.')\n",
    "print(f'- there are {dfs_expanded[locations_cond & year_cond].shape[0]} events with geocodes and dates.')\n",
    "print(f'- there are {dfs_expanded[locations_cond & year_cond & desc_cond].shape[0]} events with geocodes, dates and biographical information.')\n",
    "print(f'- there are {dfs_expanded[locations_cond & year_cond & desc_cond & period_cond].shape[0]} events with geocodes, dates and biographical information after filtering for events between 1900 and 2020.')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "We use the 7,248 events for the remainder of the analysis. In this subset,\n",
      "- there are 6629 exhibitions (91.46%).\n",
      "- there are 85 other-events (1.17%).\n",
      "- there are 31 festivals (0.43%).\n",
      "- there are 20 performance-event (0.28%).\n",
      "- there are 488 events with missing type data (6.73%).\n",
      "\n",
      "In terms of time,\n",
      "- there are 33 events between 1900-1910 (0.46%).\n",
      "- there are 31 events between 1910-1920 (0.43%).\n",
      "- there are 39 events between 1920-1930 (0.54%).\n",
      "- there are 40 events between 1930-1940 (0.55%).\n",
      "- there are 41 events between 1940-1950 (0.57%).\n",
      "- there are 90 events between 1950-1960 (1.24%).\n",
      "- there are 159 events between 1960-1970 (2.19%).\n",
      "- there are 629 events between 1970-1980 (8.68%).\n",
      "- there are 1333 events between 1980-1990 (18.39%).\n",
      "- there are 2141 events between 1990-2000 (29.54%).\n",
      "- there are 2216 events between 2000-2010 (30.57%).\n",
      "- there are 493 events between 2010-2020 (6.8%).\n",
      "- there are 3 events in 2020 (0.04%).\n"
     ]
    }
   ],
   "source": [
    "dfs_rich = dfs_expanded[locations_cond & year_cond & desc_cond & period_cond].copy()\n",
    "\n",
    "type_count = dfs_rich['types'].value_counts().reset_index().rename(columns={'index':'type','types':'count'})\n",
    "type_count['prop'] = round((type_count['count']/dfs_rich.shape[0])*100,2)\n",
    "exh_prop = type_count['type'].str.contains('exhibition')\n",
    "other_prop = type_count['type'].str.contains('other event')\n",
    "fest_prop = type_count['type'].str.contains('festival')\n",
    "perf_prop = type_count['type'].str.contains('performance')\n",
    "\n",
    "# # create a decade column\n",
    "dfs_rich['decade_start'] = [str(int(x))[:3]+'0' for x in dfs_rich['start_year']]\n",
    "dfs_rich['decade_start'] = dfs_rich['decade_start'].astype(int)\n",
    "\n",
    "print('\\nWe use the 7,248 events for the remainder of the analysis. In this subset,') \n",
    "print(f'- there are {type_count[exh_prop][\"count\"].sum()} exhibitions ({round(type_count[exh_prop][\"prop\"].sum(),2)}%).')\n",
    "print(f'- there are {type_count[other_prop][\"count\"].sum()} other-events ({round(type_count[other_prop][\"prop\"].sum(),2)}%).')\n",
    "print(f'- there are {type_count[fest_prop][\"count\"].sum()} festivals ({round(type_count[fest_prop][\"prop\"].sum(),2)}%).')\n",
    "print(f'- there are {type_count[perf_prop][\"count\"].sum()} performance-event ({round(type_count[perf_prop][\"prop\"].sum(),2)}%).')\n",
    "print(f'- there are {dfs_rich[\"types\"].isnull().sum()} events with missing type data ({round((dfs_rich[\"types\"].isnull().sum()/dfs_rich.shape[0])*100,2)}%).')\n",
    "\n",
    "print('\\nIn terms of time,')\n",
    "for t in range(1900,2021,10):\n",
    "    if t != 2020: print(f'- there are {dfs_rich[dfs_rich.decade_start == t].shape[0]} events between {t}-{t+10} ({round((dfs_rich[dfs_rich.decade_start == t].shape[0]/dfs_rich.shape[0])*100,2)}%).')\n",
    "    else: print(f'- there are {dfs_rich[dfs_rich.start_year == t].shape[0]} events in {t} ({round((dfs_rich[dfs_rich.start_year == t].shape[0]/dfs_rich.shape[0])*100,2)}%).')"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Most frequent geocodes\n",
    "\n",
    "Before jumping into the visuals, we inspect the nuances of the geocodes attached to exhibtion data. We find that the geocodes are not always accurate, and that there are many distinct venues representing the same geocode. Further pre-processing will need to be conducted to ensure downstream trends can be accurately identified. \n",
    "\n",
    "Below is a list of the top 100 geocodes, and the number of events they represent. Through further inspection we can see which geocodes accurate represent the place names."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
    {
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       "      \n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>Frequency</th>\n",
       "      <th>most_frequent_address</th>\n",
       "      <th>2ndmost_frequent_address</th>\n",
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       "  </thead><tbody><tr><td>Loading... (need <a href=https://mwouts.github.io/itables/troubleshooting.html>help</a>?)</td></tr></tbody><tfoot><th>latitude</th><th>longitude</th><th>Frequency</th><th>most_frequent_address</th><th>2ndmost_frequent_address</th><th>3rdmost_frequent_address</th><th>4thmost_frequent_address</th><th>5thmost_frequent_address</th></tfoot></table>\n",
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       "    const data = [[-34.928621, 138.599959, 923, \"Experimental Art Foundation, Adelaide, SA\", \"Contemporary Art Centre of South Australia, Adelaide, SA\", \"Adelaide Central Gallery, Adelaide, SA\", \"Greenaway Art Gallery, Adelaide, SA\", \"Flinders University Art Museum, Adelaide, SA\"], [-33.868901, 151.207091, 887, \"Artspace, Sydney, NSW\", \"Sydney, NSW\", \"Sherman Galleries, Sydney, NSW\", \"Ivan Dougherty Gallery, Sydney, NSW\", \"Australian Centre for Photography, Sydney, NSW\"], [-27.470933, 153.023502, 488, \"Institute of Modern Art, Brisbane, QLD\", \"Brisbane City Art Gallery, Brisbane, Qld\", \"Brisbane, Qld\", \"University of Queensland Art Museum, Brisbane, QLD\", \"Brisbane, QLD\"], [-37.813187, 144.96298, 486, \"Monash University Museum of Art, Melbourne, VIC\", \"RMIT Gallery, Melbourne, VIC\", \"Australian Centre for Contemporary Art, Melbourne, VIC\", \"Karen Woodbury Gallery, Melbourne, Vic.\", \"Melbourne, Vic.\"], [-33.868627, 151.217062, 292, \"Art Gallery of New South Wales, Sydney, NSW\", \"Art Gallery of NSW, Sydney, NSW\", \"Art Gallery Of New South Wales, Sydney, NSW\", \"[National] Art Gallery of New South Wales, Sydney, New South Wales\", \"Art Gallery of New South Wales, Sydney, 14 October - 29 November 1987;\"], [-34.416667, 150.883333, 183, \"Wollongong City Gallery, Wollongong, NSW\", \"Wollongong City Art Gallery, Wollongong, NSW\", \"Project Contemporary Artspace, Wollongong, NSW\", \"Wollongong City Gallery, NSW\", \"Project Centre for Contemporary Art, Wollongong, NSW\"], [-12.437368, 130.833821, 128, \"Museums and Art Galleries of the Northern Territory, Darwin, NT\", \"Museum and Art Gallery of the Northern Territory, Darwin, NT\", \"Museum & Art Gallery of the Northern Territory, Darwin, NT\", \"Museum and Art Gallery of the Northern Territory , Darwin, NT\", \"Museums and Art Galleries of the Northern Territory, Darwin NT.\"], [-37.822536, 144.969113, 124, \"National Gallery of Victoria, Melbourne, VIC\", \"National Gallery of Victoria, Melbourne, Vic.\", \"Ian Potter Centre, National Gallery of Victoria, Melbourne, VIC\", \"Access Gallery, National Gallery of Victoria, Melbourne, Vic.\", \"National GAllery of Victoria, Melbourne, Vic.\"], [-31.952222, 115.858889, 116, \"John Curtin Gallery, Curtin University, Perth, WA\", \"Perth, WA\", \"Perth Institute of Contemporary Art, Perth, WA\", \"Greenhill Galleries, Perth, WA\", \"Katanning Arts Centre, Katanning & Western Australian Museum, Perth, WA\"], [-27.472096, 153.018173, 113, \"Queensland Art Gallery, Brisbane, QLD\", \"Queensland Art Gallery, Brisbane, Qld\", \"Queensland Art Gallery, Brisbane, Qld.\", \"Queensland Art Gallery, Brisbane. QLD\", \"Queensland Art Gallery, Brsbane, QLD\"], [-32.929205, 151.772973, 106, \"Newcastle Region Art Gallery, Newcastle, NSW\", \"Newcastle Regional Art Gallery, Newcastle, NSW\", \"Newcastle Regional Art Gallery, NSW\", \"None\", \"None\"], [-33.281886, 149.102659, 102, \"Orange Regional Gallery, Orange, NSW\", \"Orange Regional Art Gallery, Orange, NSW\", \"Orange Regional Gallery, NSW\", \"Orange Regional Gallery\", \"None\"], [-38.38553, 142.482454, 99, \"Warrnambool Art Gallery, Warrnambool, VIC\", \"Warrnambool Art Gallery, VIC\", \"None\", \"None\", \"None\"], [-33.872355, 151.224854, 96, \"8 Llankelly Place, Kings Cross, Sydney, 2011\", \"None\", \"None\", \"None\", \"None\"], [-33.884611, 151.226586, 94, \"Ivan Dougherty Gallery, COFA, UNSW, Paddington, NSW\", \"Roslyn Oxley9 Gallery, Paddington, Sydney, NSW\", \"Mary Place Gallery, Paddington, NSW\", \"Kaliman Gallery, Paddington, Sydney, NSW\", \"Global Gallery, Paddington, NSW\"], [-31.950414, 115.860604, 90, \"Art Gallery of Western Australia, Perth, WA\", \"Art Gallery of Western Australia, Perth, WA (and touring)\", \"None\", \"None\", \"None\"], [-33.888493, 151.1871, 87, \"Tin Sheds Gallery, University of Sydney, Sydney, NSW\", \"Sydney College of the Arts, University of Sydney, Sydney, NSW\", \"Tin Sheds, University of Sydney, New South Wales\", \"Tinsheds Gallery, University of Sydney, Sydney, NSW\", \"SCA Galleries, Sydney College of the Arts, University of Sydney, Sydney, NSW\"], [-37.79997, 144.957338, 82, \"Ian Potter Museum of Art, University of Melbourne, Melbourne, Vic.\", \"The Ian Potter Museum of Art, University of Melbourne, Vic.\", \"Ian Potter Museum of Art, University of Melbourne, Vic.\", \"Ian Potter Gallery, The University of Melbourne, Vic.\", \"Ian Potter Museum of Art, Melbourne, VIC\"], [-37.562107, 143.856149, 82, \"Ballarat Fine Art Gallery, Ballarat, VIC\", \"Ballarat, VIC\", \"Ballarat Fine Art Gallery, Ballarat, Vic.\", \"None\", \"None\"], [-41.437456, 147.134155, 81, \"Queen Victoria Museum and Art Gallery, Launceston, TAS\", \"Queen Victoria Museum and Art Gallery, Launceston, Tas.\", \"Queen Victoria Museum and Art Gallery, Launceston, Tasmania\", \"None\", \"None\"], [-37.7589, 145.084301, 72, \"Heide Museum of Modern Art, Melbourne, VIC\", \"Heide Museum of Modern Art, Bulleen, Vic.\", \"Heide Museum of Modern Art, VIC\", \"Heide Museum of Modern Art, Bulleen, VIC\", \"None\"], [-34.920638, 138.603939, 65, \"Art Gallery of South Australia, Adelaide, SA\", \"Art Gallery of SA, Adelaide, SA\", \"Art Gallery of South Australia, SA\", \"Art Gallery of South Australia, Adelaide\", \"None\"], [-41.426181, 147.112468, 64, \"Launceston, TAS\", \"None\", \"None\", \"None\", \"None\"], [-35.30053, 149.136282, 58, \"National Gallery of Australia, Canberra, ACT\", \"Australian National Gallery, Canberra, ACT\", \"Marsh Pond, Sculpture Garden, National Gallery of Australia, Canberra, ACT\", \"The Drill Hall Gallery, ANU & National Gallery of Australia, Canberra, ACT\", \"National Gallery Australia, Canberra, ACT\"], [-33.860064, 151.208954, 58, \"Museum of Contemporary Art, Sydney, NSW\", \"Mosman Art Gallery, Sydney, NSW\", \"Musuem of Contemporary Art, Sydney, NSW\", \"St George Museum, Sydney, NSW\", \"Paddington Contemporary Arts Gallery, Sydney, NSW\"], [-35.308056, 149.124444, 52, \"Canberra Contemporary Art Space, Canberra, ACT\", \"Beaver Galleries, Canberra, ACT\", \"Canberra School of Art Gallery, Canberra, ACT\", \"Canberra, ACT\", \"Canberra Museum and Art Gallery, Canberra, ACT\"], [-42.881903, 147.323815, 50, \"Bett Gallery, Hobart, Tas.\", \"Hobart, TAS\", \"University of Tasmania Fine Arts Gallery, Hobart, Tasmania\", \"Entrepot Gallery, Hobart, TAS\", \"Plimsoll Gallery, Hobart, TAS\"], [-42.90389, 147.32476, 50, \"Plimsoll Gallery, University of Tasmania, Hobart, TAS\", \"Fine Arts Gallery in University of Tasmania, Hobart, TAS\", \"Tasmanian School of Art, Hobart, University of Tasmania, Hobart, TAS\", \"Plimsoll Gallery, University of Tasmania, Hobart, Tas.\", \"University of Tasmania, TAS\"], [-35.283593, 149.118669, 48, \"School of Art, Australian National University, Canberra, ACT\", \"Drill Hall Gallery, Australian National University, Canberra, ACT\", \"Old Canberra House, Australian National University, Canberra, ACT\", \"Drill Hall Gallery, ANU, Canberra, ACT\", \"Australian National University, Canberra, ACT\"], [-42.881935, 147.332296, 44, \"Tasmanian Museum and Art Gallery, Hobart, TAS\", \"Tasmanian Museum and Art Gallery, Hobart, Tasmania\", \"Tasmanian Museum and Art Gallery, Hobart, Tas.\", \"None\", \"None\"], [-41.434529, 147.142523, 43, \"Corner Brisbane and Tamar Streets, Launceston, TAS\", \"None\", \"None\", \"None\", \"None\"], [51.500152, -0.126236, 42, \"Burlington House, Piccadilly, London, England, UK\", \"Galerie Besson, London, UK\", \"Primavera, London, UK\", \"Cosa Gallery, London, UK\", \"London, England, UK\"], [-34.811152, 138.6226, 41, \"University of South Australia\", \"Adelaide Festival, University of South Australia, Adelaide, SA\", \"University of South Australia, Adelaide, SA; Victorian College of the Arts, Melbourne, Vic.\", \"University of South Australia, Adelaide, SA\", \"Adelaide Festival of Arts, South Australian School of Art, University of South Australia, Adelaide, SA\"], [-31.979612, 115.818556, 31, \"Lawrence Wilson Art Gallery, University of Western Australia, Perth, WA\", \"Lawrence Wilson Gallery, University of Western Australia, Perth, WA\", \"University of Western Australia, Perth, WA\", \"Berndt Museum of Anthropology, University of Western Australia, Perth, WA\", \"None\"], [40.714353, -74.005973, 30, \"Garth Clark Gallery, New York, USA\", \"Robert Steele Gallery, New York, USA\", \"New York, USA\", \"Ubu Gallery, New York, USA\", \"Claire Oliver Gallery, New York, USA\"], [-33.890647, 151.212925, 27, \"Chalk Horse Gallery, Surry Hills, NSW\", \"Ray Hughes Gallery, Surry Hills, Sydney, NSW\", \"Labor Club, Surry Hills, NSW\", \"Flinders Street Gallery, Surry Hills, Sydney, NSW\", \"Art Space, Surry Hills, NSW\"], [-33.861302, 151.204458, 26, \"S.H. Ervin Gallery, Sydney, NSW\", \"SH Ervin Gallery, The Rocks, Sydney, NSW\", \"SH Ervin Gallery, Sydney, NSW\", \"S. H. Ervin Gallery, Sydney, NSW\", \"S.H. Erwin Gallery, Sydney, NSW\"], [-37.797577, 144.964595, 26, \"University of Melbourne, Melbourne, Vic\", \"Baillieu Library, Melbourne University, Melbourne, Vic.\", \"Baillieu Library, University of Melbourne, Melbourne, Vic.\", \"George Paton Gallery, Melbourne University, Melbourne, Vic.\", \"None\"], [-33.888408, 151.237218, 22, \"Eva Breuer Art Dealer, Woollahra, NSW\", \"Rex Irwin Art Dealer, Woollahra, NSW\", \"Dickerson Gallery, Woollahra, Sydney, NSW\", \"Rex Irwin Art Dealer, Woollahra, Sydney, NSW\", \"Rudy Komon Art Gallery, Woollahra, Sydney, NSW\"], [-27.229741, 153.108256, 22, \"Ace of Clubs Hall, Redcliffe, QLD\", \"Redcliffe Art Contest, Ace of Clubs Hall, Redcliffe, QLD\", \"Redcliffe, QLD\", \"Redcliffe, Qld\", \"A of Clubs Hall, Redcliffe, QLD\"], [-33.867383, 151.212885, 21, \"NSW Parliament House, Sydney, NSW\", \"Parliament House, Sydney, NSW\", \"NSW Parliament House, NSW\", \"None\", \"None\"], [-32.05604, 115.74718, 20, \"Fremantle, WA\", \"The Moores Building Contemporary Art Gallery, Fremantle, WA\", \"Indigenart, Mossenson Galleries, Fremantle, WA\", \"The Moores Building, City of Fremantle, Perth, WA\", \"Town Hall, City of Fremantle, Perth, WA\"], [-34.067774, 150.813192, 20, \"Campbelltown City Art Gallery, Campbelltown, NSW\", \"Campbelltown City Bicentennial Art Gallery, Campbelltown, NSW\", \"Campbelltown Arts Centre, Campbelltown, NSW\", \"Campbelltown City Bicentennial Gallery, Campbelltown, NSW\", \"Campbelltown & Tamworth City Galleries, Australia\"], [47.751074, -120.740139, 18, \"West Australian Society of Arts, WA\", \"PICA (Perth Institute of Contemporary Arts), WA\", \"WA\", \"The Church Gallery, Perth International Arts Festival, WA\", \"Porongurup National Park, Stirling Ranges, WA\"], [-34.928726, 138.599945, 17, \"Adelaide, SA\", \"None\", \"None\", \"None\", \"None\"], [-38.234574, 146.394711, 16, \"Latrobe Regional Gallery, Morwell, VIC\", \"None\", \"None\", \"None\", \"None\"], [-19.257622, 146.817879, 16, \"Perc Tucker Regional Art Gallery, Townsville, Qld\", \"Perc Tucker Regional Art Gallery, Townsville, QLD\", \"Umbrella Studio Contemporary Arts, Townsville, Qld\", \"Perc Tucker Regional Gallery, Townsville, Qld\", \"Perc Tucker Regional Gallery, Townsville, QLD\"], [-33.917224, 151.230227, 16, \"College of Fine Arts, University of New South Wales, Sydney, NSW\", \"College of Fine Arts Gallery, University of New South Wales, Sydney, NSW\", \"Ivan Dougherty Gallery, University of New South Wales, Sydney, NSW\", \"Ivan Dougherty Gallery, College of Fine Arts, University of New South Wales, Sydney, NSW\", \"Ivan Dougherty Gallery, College of Fine Arts,University of New South Wales, Sydney, NSW\"], [-33.896549, 151.179963, 15, \"King Street Gallery, Newtown, Sydney, NSW\", \"Defiance Gallery, Newtown, Sydney, NSW\", \"Level Gallery, Newtown, Sydney, NSW\", \"Seymour Centre, Presented by Defiance Gallery, Newtown, Sydney, NSW\", \"Level 2 Gallery, Newtown, Sydney, NSW\"], [-36.84846, 174.763331, 15, \"Auckland, NZ\", \"Auckland, New Zealand\", \"Artspace, Auckland, NZ\", \"Roger Williams Contemporary, Auckland, New Zealand\", \"Snowwhite, Unitec, Auckland, NZ\"], [-41.437087, 147.139377, 15, \"University Gallery, Launceston, Tas.\", \"University Gallery, Launceston, TAS\", \"Queen Victoria Museum and Art Gallery, Inveresk, Launceston, TAS\", \"Academy Gallery, University of Tasmania, Launceston, Tas.\", \"Queen Victoria Museum & Art Gallery, Launceston, TAS\"], [-41.440074, 147.138801, 15, \"Bender's Lane, 144 Charles Street, Launceston, Tasmania\", \"None\", \"None\", \"None\", \"None\"], [-28.001171, 153.428317, 14, \"Chevron Hotel, Surfers Paradise, QLD\", \"Corroboree Room, Chevron Paradise Hotel, Surfers Paradise, QLD\", \"Gold Coast City Art Gallery, Surfers Paradise, Queensland\", \"Jedda Gallery, Surfers Paradise, Gold Coast, QLD\", \"Moomba Room, Chevron Hotel, Surfers Paradise, Qld\"], [52.523405, 13.4114, 14, \"Berlin, Germany\", \"Querhause Gallery, Berlin\", \"Artspace, Sydney and Kunstlerhaus Bethanien, Berlin\", \"Dock 11, Berlin, Germany\", \"Ruine der Kuenste, Berlin, Germany\"], [-32.916667, 151.75, 13, \"Newcastle, NSW\", \"von Bertouch Galleries, Newcastle, NSW\", \"Lindsay Street Gallery, Newcastle, NSW\", \"Von Bertouch Galleries, Newcastle, NSW\", \"Field Gallery, Newcastle, NSW\"], [-30.525371, 151.664879, 13, \"New England Regional Art Museum, Armidale, NSW\", \"New England Regional Art Museum,  Armidale, NSW\", \"New England Regional Art Museum, Armidale, SW\", \"New England Regional Art, NSW\", \"None\"], [-27.471758, 153.017726, 13, \"Queensland Museum, Brisbane, QLD\", \"Queensland Museum\", \"Queensland Museum, South Brisbane, QLD\", \"Queensland Art Gallery/Gallery of Modern Art, Brisbane\", \"Queensland Art Gallery, Gallery of Modern Art, Brisbane, QLD\"], [-33.873651, 151.20689, 13, \"Sydney, NSW\", \"Contemporary Art Society of Australia, New South Wales Branch, Sydney, NSW\", \"Craft Expo Exhibition, Centre Point, Sydney, NSW\", \"Contemporary Art Society of Australia, New South Wales Branch, Sydney ,NSW\", \"None\"], [-33.88068, 151.21862, 13, \"TAP Gallery, Darlinghurst, Sydney, NSW\", \"Coo-ee Gallery, Darlinghurst, Sydney, NSW\", \"L'otel, Darlinghurst, Sydney, NSW\", \"The Tap Gallery, Darlinghurst, NSW\", \"United Galleries, Darlinghurst, NSW\"], [-35.282, 149.128684, 12, \"Canberra, ACT\", \"None\", \"None\", \"None\", \"None\"], [31.230393, 121.473704, 12, \"Shanghai Art Gallery, Shanghai, China\", \"Shanghai Art Museum, Shanghai, China\", \"Shanghai Art Gallery\", \"Lu Yanshao Art Academy Gallery, Shanghai, China\", \"Shanghai Author Gallery, Shanghai, China\"], [-34.851047, 150.744804, 11, \"Shoalhaven City Arts Centre, NSW\", \"None\", \"None\", \"None\", \"None\"], [35.689487, 139.691706, 11, \"Tokyo, Japan\", \"Tokyo Gallery, Tokyo, Japan\", \"Art Front and Hillside Galleries, Tokyo, Japan\", \"Tokyo Metropolitan Museum of Photography, Tokyo, Japan\", \"Hinode Gallery, Tokyo, Japan\"], [-38.147172, 144.356821, 11, \"Geelong Art Gallery, Geelong, VIC\", \"Geelong Art Gallery, Geelong, Vic.\", \"Geelong Gallery, Geelong, VIC\", \"None\", \"None\"], [-33.422294, 149.57988, 11, \"Bathurst Regional Art Gallery, Bathurst, NSW\", \"Bathurst Art Gallery, Bathurst, NSW\", \"Bathurst Regional Art Gallery,  Bathurst, NSW\", \"None\", \"None\"], [-37.880197, 145.0229, 10, \"Glen Eira City Gallery, Melbourne, Vic.\", \"City Gallery, Melbourne, Vic.\", \"None\", \"None\", \"None\"], [-12.46282, 130.841769, 10, \"Karen Brown Gallery, Darwin, NT\", \"Framed Gallery, Darwin, NT\", \"Raft Art Space, Darwin, NT\", \"24 Hour Art Gallery, Darwin, NT\", \"Darwin Entertainment Centre, Darwin, NT\"], [-35.023823, 117.884729, 10, \"Albany Town Hall, Albany, WA\", \"Residency Museum, Albany, WA\", \"Vancouver Arts Centre, Albany, WA\", \"Albany Town Hall Theatre, Albany, WA\", \"Albany Museum, Albany, WA\"], [-36.758711, 144.283746, 10, \"Bendigo Art Gallery, Bendigo, VIC\", \"Bendigo Art Gallery, Bendigo, Vic.\", \"Bendigo, VIC\", \"None\", \"None\"], [-33.752178, 150.691047, 10, \"Penrith Regional Gallery, Penrith, NSW\", \"Penrith Regional Art Gallery, NSW\", \"Penrith Regional Gallery/Lewers Bequest, NSW\", \"Joan Sutherland Performing Arts Centre, Penrith, NSW\", \"Penrith, NSW\"], [48.856667, 2.350987, 10, \"Paris, France\", \"Australian Embassy, Paris, France\", \"Au Printemps Department Store, Paris, France\", \"Galerie Schleicher+Lange, Paris, France\", \"Cite Internationale des arts, Paris, France\"], [-33.946822, 150.900776, 9, \"Casula Powerhouse Arts Centre, Casula, NSW\", \"Casula Powerhouse, Casula, NSW\", \"The lounge, Casula Powerhouse, Casula, NSW\", \"None\", \"None\"], [-33.883779, 151.157053, 9, \"Birrung Gallery, Leichhardt, NSW\", \"Walkabout Gallery, Leichhardt, Sydney, NSW\", \"Walkabout Gallery, Leichhardt, NSW\", \"Boomalli Aboriginal Artists Co-operative, Leichhardt, Sydney, NSW\", \"Boomalli Aboriginal Artists Cooperative, Leichhardt, Sydney, NSW\"], [-27.575, 151.947, 9, \"Toowoomba, QLD\", \"Toowoomba, Qld\", \"Toowoomba University Gallery, Toowoomba, QLD\", \"Toowoomba Art Gallery, Toowoomba, QLD\", \"Demoaly House, Toowoomba, QLD\"], [-33.892507, 151.201718, 9, \"Legge Gallery Redfern, NSW\", \"Damien Minton Gallery, Redfern, Sydney, NSW\", \"Byron McMahon Gallery, Redfern, NSW\", \"Redfern, Sydney, NSW\", \"MOP Projects, Redfern, NSW\"], [-34.923886, 138.610463, 9, \"Tandanya National Aboriginal Cultural Institute, Adelaide, SA\", \"Tandanya, Adelaide, SA\", \"None\", \"None\", \"None\"], [-33.829225, 151.24406, 9, \"Mosman Art Gallery, Mosman, NSW\", \"Mosman Art Gallery, Mosman, Sydney, NSW\", \"Sculptors Society, Mosman, NSW\", \"Mosman Art Prize, Mosman, NSW\", \"Mosman, Sydney, NSW\"], [-33.916071, 151.225626, 8, \"National Art School, Sydney, NSW\", \"Australia Council for the Arts\", \"None\", \"None\", \"None\"], [-35.302346, 149.129621, 8, \"Old Parliament House, Canberra, ACT\", \"New Parliament House, Canberra, ACT\", \"National Museum of Australia / Old Parliament House, Canberra, ACT\", \"National Museum of Australia/Old Parliament House, Canberra, ACT\", \"National Museum of Australia, Old Parliament House, Canberra, ACT\"], [-33.867487, 151.20699, 8, \"Sydney\", \"Sydney, NSW\", \"Cleland Store 24-33 Playfair St The Rock Sydney\", \"None\", \"None\"], [39.904214, 116.407413, 8, \"Beijing, China\", \"Redgate Gallery, Beijing, China\", \"Pickled Art Centre, Beijing, China\", \"Red Gate Gallery, 798 Village, Beijing, China\", \"Linda Gallery, 798 Art District, Dashanzi, Beijing China\"], [-33.893812, 151.263074, 8, \"Bondi, Sydney, NSW\", \"Bondi, NSW\", \"Bondi Road Art School, Bondi, Sydney, NSW\", \"None\", \"None\"], [-31.091085, 150.930374, 8, \"Tamworth Regional Gallery, Tamworth, NSW\", \"Tamworth Regional Art Gallery, Tamworth, NSW\", \"Tamworth Art Gallery, Tamworth, NSW\", \"Tamworth City Art Gallery, Tamworth, NSW\", \"Tamworth City Gallery, Tamworth, NSW\"], [-31.953513, 115.857047, 7, \"Perth, WA\", \"Perth\", \"None\", \"None\", \"None\"], [-33.798521, 151.28612, 7, \"Manly Art Gallery & Museum, Manly, New South Wales\", \"Manly Regional Art Gallery, Manly, NSW\", \"Manly Regional Art Gallery and Museum, Manly, NSW\", \"Manly Art Gallery and Museum, Manly, Sydney, NSW\", \"Artroom Gallery, Manly, NSW\"], [-36.080779, 146.916469, 7, \"Albury Regional Art Centre, Albury, NSW\", \"Albury Regional Art Gallery, Albury, NSW\", \"Albury Regional Gallery, Albury, NSW\", \"None\", \"None\"], [-33.85755, 151.181043, 7, \"GroundFloor Gallery, Balmain, Sydney, NSW\", \"Balmain Community Centre, Balmain, NSW\", \"Groundfloor Gallery, Balmain, Sydney, NSW\", \"Balmain Art and Craft Show, Balmain, NSW\", \"None\"], [-31.865287, 116.027398, 7, \"Gomboc Gallery, Perth, WA\", \"Gomboc Gallery, Middle Swan, WA\", \"None\", \"None\", \"None\"], [-33.879225, 151.200167, 7, \"Powerhouse Museum, Sydney, NSW\", \"None\", \"None\", \"None\", \"None\"], [-23.70021, 133.880611, 7, \"Alice Springs, NT\", \"Alice Springs\", \"Curated by Artback NT Arts Development, Darwin and Alice Springs, NT\", \"Watch This Space, Alice Springs, NT\", \"Gondwana 11, Alice Springs, NT\"], [-28.001744, 153.42844, 7, \"Gold Coast City Gallery, Gold Coast, Qld\", \"Gold Coast City Art Gallery, Gold Coast, Qld\", \"Gold Coast, Qld\", \"Gold Coast Art Gallery Acquisitions Society, Gold Coast, QLD\", \"Art Galleries Schubert, Gold Coast, QLD\"], [-37.803211, 144.973834, 7, \"Royal Exhibition Building, Melbourne, VIC\", \"Royal Exhibition Building, Melbourne, Vic\", \"Exhibition Building, Melbourne, Vic\", \"Exhibition Building, Melbourne, Vic.\", \"Royal Exhibition Building, Carlton, VIC\"], [-33.88394, 151.22032, 7, \"Sydney College of the Arts, Sydney, NSW\", \"College of Fine Arts, Sydney, NSW\", \"College of Fine Arts, NSW\", \"B.M.G. Fine Art, Sydney, NSW\", \"None\"], [-33.324146, 115.635336, 6, \"Bunbury Regional Art Galleries, Bunbury, WA\", \"None\", \"None\", \"None\", \"None\"], [-37.867512, 144.978981, 6, \"Linden Centre for Contemporary Art, St Kilda, VIC\", \"Linden Centre for Contemporary Arts, St Kilda, Melbourne, Vic.\", \"St Kilda, Melbourne, VIC\", \"St Kilda, Vic\", \"None\"], [-28.01726, 153.425699, 6, \"Gold Coast, QLD\", \"None\", \"None\", \"None\", \"None\"], [-33.866754, 151.212784, 6, \"State Library of NSW, Sydney, NSW\", \"State Library of New South Wales, Sydney, NSW\", \"None\", \"None\", \"None\"], [-37.818635, 145.00147, 6, \"Dickerson Gallery, Richmond, Melbourne, VIC\", \"Pollock Gallery, Richmond, VIC\", \"Pinacotheca Gallery, Richmond, VIC\", \"Christine Abrahams Gallery, Richmond, Vic.\", \"Charles Nodrum Gallery,  Richmond, Vic\"], [-16.923399, 145.773851, 6, \"Cairns Regional Art Gallery, Cairns, QLD\", \"Cairns Regional Art Gallery, Cairns, Qld.\", \"Cairns Regional Art Gallery\", \"Tank Arts Centre, Cairns, QLD\", \"None\"], [-35.293253, 149.1211, 6, \"National Museum of Australia, Canberra, ACT\", \"Old Parliament House / National Museum of Australia, Canberra, ACT\", \"Australian National Museum, Canberra, ACT\", \"None\", \"None\"]];\n",
       "\n",
       "    // Define the dt_args\n",
       "    let dt_args = {\"scrollY\": \"400px\", \"scrollCollapse\": true, \"scrollX\": true, \"paging\": false, \"dom\": \"tpr\", \"order\": [], \"initComplete\": function () {\n",
       "    // Apply the search\n",
       "    this.api()\n",
       "        .columns()\n",
       "        .every(function () {\n",
       "            const that = this;\n",
       "\n",
       "            $('input', this.footer()).on('keyup change clear', function () {\n",
       "                if (that.search() !== this.value) {\n",
       "                    that.search(this.value).draw();\n",
       "                }\n",
       "            });\n",
       "        });\n",
       "}\n",
       "};\n",
       "    dt_args[\"data\"] = data;\n",
       "\n",
       "    $(document).ready(function () {\n",
       "        // Setup - add a text input to each header or footer cell\n",
       "$('#587ef9d6-b038-493c-a9d0-13e2a4f9f2c8 tfoot th').each(function () {\n",
       "    let title = $(this).text();\n",
       "    $(this).html('<input type=\"text\" placeholder=\"Search ' +\n",
       "        // We use encodeURI to avoid this LGTM error:\n",
       "        // https://lgtm.com/rules/1511866576920/\n",
       "        encodeURI(title).replaceAll(\"%20\", \" \") +\n",
       "        '\" />');\n",
       "});\n",
       "\n",
       "        $('#587ef9d6-b038-493c-a9d0-13e2a4f9f2c8').DataTable(dt_args);\n",
       "    });\n",
       "</script>\n",
       "</div>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "most_freq_geocodes = dfs_rich[['latitude','longitude']].value_counts().reset_index().rename(columns={0:'Frequency'})\n",
    "most_freq_geocodes = most_freq_geocodes.head(100)\n",
    "\n",
    "# get the most frequent place_address for each geocode\n",
    "for idx,row in most_freq_geocodes.iterrows():\n",
    "    place_address = dfs_rich[(dfs_rich.latitude == row['latitude']) & (dfs_rich.longitude == row['longitude'])]['place_address'].value_counts().index[0]\n",
    "\n",
    "    try: place_address2 = dfs_rich[(dfs_rich.latitude == row['latitude']) & (dfs_rich.longitude == row['longitude'])]['place_address'].value_counts().index[1]\n",
    "    except: place_address2 = None\n",
    "    \n",
    "    try: place_address3 = dfs_rich[(dfs_rich.latitude == row['latitude']) & (dfs_rich.longitude == row['longitude'])]['place_address'].value_counts().index[2]\n",
    "    except: place_address3 = None\n",
    "\n",
    "    try: place_address4 = dfs_rich[(dfs_rich.latitude == row['latitude']) & (dfs_rich.longitude == row['longitude'])]['place_address'].value_counts().index[3]\n",
    "    except: place_address4 = None\n",
    "\n",
    "    try: place_address5 = dfs_rich[(dfs_rich.latitude == row['latitude']) & (dfs_rich.longitude == row['longitude'])]['place_address'].value_counts().index[4]\n",
    "    except: place_address5 = None\n",
    "    \n",
    "    most_freq_geocodes.loc[idx,'most_frequent_address'] = place_address\n",
    "    most_freq_geocodes.loc[idx,'2ndmost_frequent_address'] = place_address2\n",
    "    most_freq_geocodes.loc[idx,'3rdmost_frequent_address'] = place_address3\n",
    "    most_freq_geocodes.loc[idx,'4thmost_frequent_address'] = place_address4\n",
    "    most_freq_geocodes.loc[idx,'5thmost_frequent_address'] = place_address5\n",
    "\n",
    "# display data\n",
    "show(most_freq_geocodes, scrollY=\"400px\", scrollCollapse=True, scrollX=True,\n",
    "     paging=False, showIndex=False, column_filters=\"footer\", dom=\"tpr\")"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Top 10 geocoded places with most events\n",
    "\n",
    "After omitting geocodes with random or erroneous place names, we can see that the \"true\" top 10 geocoded places with the most events. As expected these are all art galleries - all with over 100 events."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "| Venue | City | Frequency |\n",
    "| :- | -: | -: |\n",
    "| Art Gallery of New South Wales | Sydney, NSW | 292 |\n",
    "| Wollongong City Gallery | Wollongong, NSW | 183 |\n",
    "| Museums and Art Galleries of the Northern Territory | Darwin, NT | 128 |\n",
    "| National Gallery of Victoria | Melbourne, VIC | 124 |\n",
    "| Queensland Art Gallery | Brisbane, QLD\t| 113 |\n",
    "| Newcastle Region Art Gallery | Newcastle, NSW | 106 |\n",
    "| Orange Regional Gallery | Orange, NSW | 102 |\n",
    "| Warrnambool Art Gallery | Warrnambool, VIC | 99 |\n",
    "| 8 Llankelly Place, Kings Cross | Sydney, NSW | 96 |\n",
    "| Art Gallery of Western Australia | Perth, WA | 90 |"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data pre-processing\n",
    "\n",
    "We split the cleaning process into various parts. We discuss each part in detail below."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1. Aggregate place names with no geocode/address conflicts\n",
    "\n",
    "First, we aggregate place names with the same geocodes, however we only do this for geocodes with no conflicting places i.e., erroneous geocodes. We manually checked this for the top 100 geocodes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [],
   "source": [
    "qag_dict = dfs_rich[dfs_rich.place_address == 'Queensland Art Gallery, Brisbane, QLD'][['latitude','longitude']]\\\n",
    "            .head(1).T.iloc[:,0].to_list()\n",
    "\n",
    "qvmag_dict = dfs_rich[dfs_rich.place_address == 'Queen Victoria Museum and Art Gallery, Launceston, TAS'][['latitude','longitude']]\\\n",
    "            .head(1).T.iloc[:,0].to_list()\n",
    "\n",
    "fix_these_placenames = ['Art Gallery of New South Wales, Sydney, NSW',\n",
    " 'National Gallery of Victoria, Melbourne, VIC',\n",
    " 'Museums and Art Galleries of the Northern Territory, Darwin, NT',\n",
    " 'Queensland Art Gallery, Brisbane, QLD', \n",
    " 'Queensland Museum, Brisbane, QLD',\n",
    " 'Newcastle Region Art Gallery, Newcastle, NSW',\n",
    " 'Orange Regional Gallery, Orange, NSW',\n",
    " 'Warrnambool Art Gallery, Warrnambool, VIC',\n",
    " 'Art Gallery of Western Australia, Perth, WA',\n",
    " 'Queen Victoria Museum and Art Gallery, Launceston, TAS',\n",
    " 'University Gallery, Launceston, Tas.',\n",
    " 'Ballarat Fine Art Gallery, Ballarat, VIC',\n",
    " 'Ian Potter Museum of Art, University of Melbourne, Melbourne, Vic.',\n",
    " 'Heide Museum of Modern Art, Melbourne, VIC',\n",
    " 'Art Gallery of South Australia, Adelaide, SA',\n",
    " 'National Gallery of Australia, Canberra, ACT',\n",
    " 'Tasmanian Museum and Art Gallery, Hobart, TAS',\n",
    " 'Plimsoll Gallery, University of Tasmania, Hobart, TAS',\n",
    " 'University of South Australia, Adelaide, SA',\n",
    " 'Lawrence Wilson Art Gallery, University of Western Australia, Perth, WA',\n",
    " 'University of Melbourne, Melbourne, Vic',\n",
    " 'S.H. Ervin Gallery, Sydney, NSW',\n",
    " 'Ace of Clubs Hall, Redcliffe, QLD',\n",
    " 'NSW Parliament House, Sydney, NSW',\n",
    " 'Campbelltown City Art Gallery, Campbelltown, NSW',\n",
    " 'Ivan Dougherty Gallery, University of New South Wales, Sydney, NSW',\n",
    " 'New England Regional Art Museum, Armidale, NSW',\n",
    " 'Geelong Art Gallery, Geelong, VIC',\n",
    " 'Bathurst Regional Art Gallery, Bathurst, NSW',\n",
    " 'Bendigo Art Gallery, Bendigo, VIC',\n",
    " 'Shanghai Art Gallery, Shanghai, China',\n",
    " 'Glen Eira City Gallery, Melbourne, Vic.',\n",
    " 'Penrith Regional Gallery, Penrith, NSW',\n",
    " 'John Curtin Gallery, Curtin University of Technology, Perth, WA',\n",
    " 'Tandanya National Aboriginal Cultural Institute, Adelaide, SA',\n",
    " 'Mosman Art Gallery, Mosman, NSW',\n",
    " 'Casula Powerhouse Arts Centre, Casula, NSW',\n",
    " 'Tamworth Regional Gallery, Tamworth, NSW',\n",
    " 'Royal Exhibition Building, Melbourne, VIC',\n",
    " 'Gomboc Gallery, Perth, WA',\n",
    " 'Albury Regional Art Centre, Albury, NSW',\n",
    " 'Manly Art Gallery & Museum, Manly, Sydney, NSW',\n",
    " 'Devonport Regional Gallery, Devonport, Tas.',\n",
    " 'State Library of NSW, Sydney, NSW']\n",
    "\n",
    "# iterate over fix_these_placenames and update place names of rows with matching geocodes\n",
    "for place in fix_these_placenames:\n",
    "    this_place = dfs_rich[dfs_rich.place_address == place].head(1)\n",
    "    matching_geocodes = dfs_rich[(dfs_rich.latitude == this_place['latitude'].values[0]) &\\\n",
    "                                 (dfs_rich.longitude == this_place['longitude'].values[0])]\n",
    "    \n",
    "    # use index of matching_geocodes to replace place_address with place\n",
    "    dfs_rich.loc[matching_geocodes.index,'place_address'] = place\n",
    "\n",
    "dfs_rich.loc[dfs_rich.place_address == 'Queensland Museum, Brisbane, QLD',['latitude','longitude']] = qag_dict\n",
    "dfs_rich.loc[dfs_rich.place_address == 'University Gallery, Launceston, Tas.',['latitude','longitude']] = qvmag_dict\n",
    "\n",
    "# iterate over fix_these_placenames and update place names of rows with matching geocodes\n",
    "for place in ['Queensland Art Gallery, Brisbane, QLD','Queen Victoria Museum and Art Gallery, Launceston, TAS']:\n",
    "    this_place = dfs_rich[dfs_rich.place_address == place].head(1)\n",
    "    matching_geocodes = dfs_rich[(dfs_rich.latitude == this_place['latitude'].values[0]) &\\\n",
    "                                 (dfs_rich.longitude == this_place['longitude'].values[0])]\n",
    "    \n",
    "    # use index of matching_geocodes to replace place_address with place\n",
    "    dfs_rich.loc[matching_geocodes.index,'place_address'] = place"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2. Cleaning by aggregating by geocode\n",
    "\n",
    "Next, we use the `geopy` library to convert the place names into geocodes. This helps us identify erroneous place names, and also helps us identify duplicate venues. There are only 33% of venues that have a geocode attached to them - these are handled accordingly keeping only venues with more than 4 exhibitions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "33.0% of the addresses could be geocoded.\n"
     ]
    }
   ],
   "source": [
    "# import geopandas # !pip install geopandas\n",
    "# import geopy # !pip install geopy\n",
    "# from geopy.geocoders import Nominatim\n",
    "# from geopy.extra.rate_limiter import RateLimiter\n",
    "\n",
    "# venue_addresses = pd.DataFrame(dfs_rich['place_address'].unique()).rename(columns={0:'address_prompt'})\n",
    "\n",
    "# # 40 min process\n",
    "# locator = Nominatim(user_agent=\"myGeocoder\")\n",
    "\n",
    "# # 1 - conveneint function to delay between geocoding calls\n",
    "# geocode = RateLimiter(locator.geocode, min_delay_seconds=1)\n",
    "\n",
    "# # 2- - create location column\n",
    "# venue_addresses['location'] = venue_addresses['address_prompt'].apply(geocode)\n",
    "\n",
    "# # 3 - create longitude, laatitude and altitude from location column (returns tuple)\n",
    "# venue_addresses['point'] = venue_addresses['location'].apply(lambda loc: tuple(loc.point) if loc else None)\n",
    "\n",
    "# # 4 - split point column into latitude, longitude and altitude columns\n",
    "# venue_addresses[['latitude2', 'longitude2', 'altitude2']] = pd.DataFrame(venue_addresses['point'].tolist(), index=venue_addresses.index)\n",
    "\n",
    "# # save csv\n",
    "# venue_addresses.to_csv('data/DAAO_venue_addresses_geocoded.csv',index=False)\n",
    "\n",
    "# read csv\n",
    "# venue_addresses = pd.read_csv('data/local/DAAO_venue_addresses_geocoded.csv')\n",
    "venue_addresses = fetch_small_data_from_github('DAAO_venue_addresses_geocoded.csv')\n",
    "\n",
    "print(f'{round(venue_addresses[\"point\"].notnull().sum()/venue_addresses.shape[0],2)*100}% of the addresses could be geocoded.')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [],
   "source": [
    "# join the geocoded addresses to the dfs_rich\n",
    "dfs_rich2 = dfs_rich.merge(venue_addresses,how='left',left_on='place_address',right_on='address_prompt')\n",
    "dfs_rich2.loc[dfs_rich2['place_address'].str.contains('University of South Australia',na=False),'location':] = np.nan # fix one address\n",
    "# print(f'{round(dfs_rich2[dfs_rich2[\"latitude2\"].notnull()].shape[0]/dfs_rich2.shape[0],2)*100}% of the events could be geocoded.')\n",
    "\n",
    "dfs_rich_uncoded = dfs_rich2[(dfs_rich2[\"latitude2\"].isnull()) | (dfs_rich2[\"address_prompt\"].isnull())].copy()\n",
    "dfs_rich_coded = dfs_rich2[(dfs_rich2[\"latitude2\"].notnull()) & (dfs_rich2[\"address_prompt\"].notnull())].copy()\n",
    "# dfs_rich_coded = dfs_rich2[(dfs_rich2[\"latitude2\"].notnull()) & (dfs_rich2[\"address_prompt\"].notnull())].copy()[['place_address',\n",
    "#                                                                      'decade_start',\n",
    "#                                                                      'latitude','longitude',\n",
    "#                                                                      'address_prompt',\n",
    "#                                                                      'location','point',\n",
    "#                                                                      'latitude2','longitude2']]\n",
    "\n",
    "# keep rows with Frequency over 4\n",
    "dfs_rich_coded_counts = dfs_rich_coded[['point']].value_counts().reset_index().rename(columns={0:'Frequency'})\n",
    "unique_points = dfs_rich_coded_counts[dfs_rich_coded_counts['Frequency'] > 4]['point'].values\n",
    "dfs_rich_coded_top = dfs_rich_coded[dfs_rich_coded['point'].isin(unique_points)].copy()\n",
    "\n",
    "# keep rows with Frequency over 4\n",
    "dfs_rich_uncoded_counts = dfs_rich_uncoded[['latitude','longitude']].value_counts().reset_index().rename(columns={0:'Frequency'})\n",
    "unique_longlats = dfs_rich_uncoded_counts[dfs_rich_uncoded_counts['Frequency'] > 4][['latitude','longitude']].values\n",
    "dfs_rich_uncoded_top = dfs_rich_uncoded[dfs_rich_uncoded['latitude'].isin(unique_longlats[:,0]) & dfs_rich_uncoded['longitude'].isin(unique_longlats[:,1])].copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Below are the top 10 most common place names for the verified addresses (after cleaning part 1): \n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Art Gallery of New South Wales, Sydney, NSW     292\n",
       "Institute of Modern Art, Brisbane, QLD          218\n",
       "Queensland Art Gallery, Brisbane, QLD           126\n",
       "National Gallery of Victoria, Melbourne, VIC    124\n",
       "Orange Regional Gallery, Orange, NSW            102\n",
       "Warrnambool Art Gallery, Warrnambool, VIC        99\n",
       "Art Gallery of Western Australia, Perth, WA      91\n",
       "Ballarat Fine Art Gallery, Ballarat, VIC         83\n",
       "Artspace, Sydney, NSW                            79\n",
       "Heide Museum of Modern Art, Melbourne, VIC       72\n",
       "Name: address_prompt, dtype: int64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "verified_df = pd.DataFrame()\n",
    "\n",
    "ignore_these = ['Melbourne, Vic.','Brisbane, Qld','Sydney, NSW','Fremantle, WA','Hobart, TAS','Adelaide, SA',\n",
    "                'Berlin, Germany','Paris, France','London, England, UK','New York, USA','Gold Coast, QLD','Perth, WA',\n",
    "                'Newcastle, NSW','Auckland, NZ','Bondi, Sydney, NSW','Canberra, ACT','Launceston, TAS']\n",
    "\n",
    "for idx, row in enumerate(dfs_rich_coded_top.point.unique()):\n",
    "    thisrow = dfs_rich_coded_top[dfs_rich_coded_top.point == row].copy()\n",
    "    topcount = thisrow['address_prompt'].value_counts().reset_index().iloc[0][0]\n",
    "    if topcount not in ignore_these: verified_df = pd.concat([verified_df,thisrow],axis=0)\n",
    "\n",
    "# create a new dataframe for each unique address with matches\n",
    "verified_df1 = pd.DataFrame()\n",
    "\n",
    "for thispoint in dfs_rich_coded_top[dfs_rich_coded_top.index.isin(verified_df.index)]['point'].unique():\n",
    "    # get all rows with address in all_addresses\n",
    "    thisrow = dfs_rich_coded_top[dfs_rich_coded_top['point'] == thispoint].copy()\n",
    "\n",
    "    # get the most common response\n",
    "    thisrow['address_prompt'] = thisrow['address_prompt'].value_counts().index[0]\n",
    "\n",
    "    # concat to verified2\n",
    "    verified_df1 = pd.concat([verified_df1,thisrow],axis=0)\n",
    "\n",
    "verified_df1 = verified_df1.drop_duplicates()\n",
    "print('Below are the top 10 most common place names for the verified addresses (after cleaning part 1): \\n')\n",
    "verified_df1['address_prompt'].value_counts().head(10)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3. Cleaning by edit distance\n",
    "\n",
    "The remaning venues are cleaned using edit distancing. If two place names share more than 75% common characters, then they are considered the same place. This is a very conservative threshold, but it is necessary to ensure that we do not merge two distinct places. Again we only keep venues with more than 4 exhibitions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Below are the top 10 most common place names for the verified addresses (after cleaning part 2):: \n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Experimental Art Foundation, Adelaide, SA                             424\n",
       "Contemporary Art Centre of South Australia, Adelaide, SA              341\n",
       "Wollongong City Gallery, Wollongong, NSW                              165\n",
       "Museums and Art Galleries of the Northern Territory, Darwin, NT       128\n",
       "Newcastle Region Art Gallery, Newcastle, NSW                          106\n",
       "8 Llankelly Place, Kings Cross, Sydney, 2011                           96\n",
       "Queen Victoria Museum and Art Gallery, Launceston, TAS                 96\n",
       "Ian Potter Museum of Art, University of Melbourne, Melbourne, Vic.     82\n",
       "Tin Sheds Gallery, University of Sydney, Sydney, NSW                   80\n",
       "Brisbane City Art Gallery, Brisbane, Qld                               68\n",
       "Name: address_prompt, dtype: int64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# use pairwise distancing to find similar addresses using only address_prompt\n",
    "from sklearn.metrics.pairwise import pairwise_distances\n",
    "from sklearn.feature_extraction.text import TfidfVectorizer\n",
    "\n",
    "unique_addresses = dfs_rich_uncoded_top[dfs_rich_uncoded_top['address_prompt'].notnull()]['address_prompt'].unique()\n",
    "\n",
    "# conver to lower case\n",
    "unique_addresses2 = [x.lower() for x in unique_addresses]\n",
    "\n",
    "# remove commas and periods\n",
    "unique_addresses2 = [x.replace(',','') for x in unique_addresses2]\n",
    "unique_addresses2 = [x.replace('.','') for x in unique_addresses2]\n",
    "\n",
    "# remove_these_terms = ['nsw', 'sydney', 'melbourne', 'vic', 'qld', 'brisbane', \n",
    "#                       'adelaide', 'new south wales', 'perth', 'canberra', 'australia', 'paddington',\n",
    "#                       'tas','act','queensland','hobart']\n",
    "\n",
    "# remove strings in this list, remove_these_terms\n",
    "# unique_addresses2 = [' '.join([word for word in x.split() if word not in remove_these_terms]) for x in unique_addresses2]\n",
    "\n",
    "unique_addresses = pd.DataFrame([unique_addresses, unique_addresses2]).T\n",
    "\n",
    "tfidf = TfidfVectorizer()\n",
    "tfidf_matrix = tfidf.fit_transform(unique_addresses2)\n",
    "distances = pairwise_distances(tfidf_matrix, metric='cosine')\n",
    "\n",
    "# get pairs with threshold less than 0.5\n",
    "pairs = np.argwhere(distances < 0.25)\n",
    "pairs = [(unique_addresses2[x[0]], unique_addresses2[x[1]]) for x in pairs]\n",
    "\n",
    "# get unique pairs\n",
    "unique_pairs = []\n",
    "for pair in pairs:\n",
    "    if pair[0] != pair[1] and pair not in unique_pairs and (pair[1], pair[0]) not in unique_pairs:\n",
    "        unique_pairs.append(pair)\n",
    "\n",
    "# print(len(unique_pairs))\n",
    "\n",
    "unique_pairs_df = pd.DataFrame(unique_pairs)\n",
    "unique_pairs_df.columns = ['address1','address2']\n",
    "\n",
    "# create a new dataframe for each unique address1\n",
    "# each unique address1 should have a corresponding list of address2s\n",
    "\n",
    "# create a dictionary of address1 and address2s\n",
    "address_dict = dict()\n",
    "for idx, row in unique_pairs_df.iterrows():\n",
    "    if row['address1'] not in address_dict: address_dict[row['address1']] = [row['address2']]\n",
    "    else: address_dict[row['address1']].append(row['address2'])\n",
    "\n",
    "# create a dataframe of address1 and address2s\n",
    "address_df = pd.DataFrame.from_dict(address_dict, orient='index').reset_index()\n",
    "\n",
    "# rename columns\n",
    "address_df.columns = ['address1','address2','address3','address4','address5']\n",
    "\n",
    "# merge with unique_addresses\n",
    "address_df = unique_addresses.merge(address_df, left_on=1, right_on='address1', how='left')\n",
    "address_df['all_addresses'] = address_df.apply(lambda x: [x['address1'], x['address2'], x['address3'], x['address4'], x['address5']], axis=1)\n",
    "address_df['all_addresses'] = address_df['all_addresses'].apply(lambda x: [y for y in x if str(y) != 'nan'])\n",
    "address_df['all_addresses'] = address_df['all_addresses'].apply(lambda x: list(set(x)))\n",
    "\n",
    "address_dict = dict()\n",
    "for idx, row in address_df.iterrows(): address_dict[row[1]] = row[0]\n",
    "\n",
    "# replace all data from address1 to address5 according to address_dict\n",
    "for idx, row in address_df.iterrows():\n",
    "    for col in ['address1','address2','address3','address4','address5']:\n",
    "        if row[col] is not None:\n",
    "            if str(row[col]) != 'nan': address_df.loc[idx,col] = address_dict[row[col]]\n",
    "\n",
    "# create a list column in address_df which stores all data from address1 to address5 without nulls\n",
    "address_df['all_addresses'] = address_df.apply(lambda x: [x['address1'], x['address2'], x['address3'], x['address4'], x['address5']], axis=1)\n",
    "address_df['all_addresses'] = address_df['all_addresses'].apply(lambda x: [y for y in x if y is not None])\n",
    "address_df['all_addresses'] = address_df['all_addresses'].apply(lambda x: [y for y in x if str(y) != 'nan'])\n",
    "address_df = address_df[[0,'all_addresses']]\n",
    "\n",
    "# create a new dataframe for each unique address with matches\n",
    "verified_df2 = pd.DataFrame()\n",
    "\n",
    "for idx,row in address_df.iterrows():\n",
    "    if len(row['all_addresses']) > 0:\n",
    "        # get all rows with address in all_addresses\n",
    "        thisrow = dfs_rich_uncoded_top[dfs_rich_uncoded_top['address_prompt'].isin(row['all_addresses'])].copy()\n",
    "\n",
    "        if thisrow.shape[0] > 4:\n",
    "            # get the most common response\n",
    "            thisrow['address_prompt'] = thisrow['address_prompt'].value_counts().index[0]\n",
    "\n",
    "            # concat to verified2\n",
    "            verified_df2 = pd.concat([verified_df2,thisrow],axis=0)\n",
    "\n",
    "# verified_df2 = verified_df2.drop_duplicates()\n",
    "\n",
    "# merge back with original dataframe\n",
    "v_df2_cols = dfs_rich_uncoded_top.columns.tolist()\n",
    "v_df2_cols.remove('address_prompt')\n",
    "verified_df2 = pd.concat([dfs_rich_uncoded_top, verified_df2],axis=0).drop_duplicates(subset=v_df2_cols)\n",
    "\n",
    "# get the most common response\n",
    "print('Below are the top 10 most common place names for the verified addresses (after cleaning part 2):: \\n')\n",
    "verified_df2['address_prompt'].value_counts().head(10)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4. Final cleaning phase and removing duplicates\n",
    "\n",
    "The final phase consists of merging the two cleaned datasets, and removing any duplicate venues. We also remove any venues with less than 5 exhibitions. The final data consists of 43% of data modified by geocode aggregation and 57% of data modified by edit distance."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "At this point, we have 131 unique venues.\n"
     ]
    }
   ],
   "source": [
    "verified_df1['coded'] = True\n",
    "verified_df2['coded'] = False\n",
    "\n",
    "clean_data_v1 = pd.concat([verified_df1,verified_df2],axis=0)\n",
    "clean_data_v1 = clean_data_v1.drop_duplicates(subset=v_df2_cols)\n",
    "\n",
    "# use pairwise distancing to find similar addresses using only address_prompt\n",
    "unique_addresses = clean_data_v1[clean_data_v1['address_prompt'].notnull()]['address_prompt'].unique()\n",
    "\n",
    "# conver to lower case\n",
    "unique_addresses2 = [x.lower() for x in unique_addresses]\n",
    "\n",
    "# remove commas and periods\n",
    "unique_addresses2 = [x.replace(',','') for x in unique_addresses2]\n",
    "unique_addresses2 = [x.replace('.','') for x in unique_addresses2]\n",
    "unique_addresses = pd.DataFrame([unique_addresses, unique_addresses2]).T\n",
    "\n",
    "tfidf = TfidfVectorizer()\n",
    "tfidf_matrix = tfidf.fit_transform(unique_addresses2)\n",
    "distances = pairwise_distances(tfidf_matrix, metric='cosine')\n",
    "\n",
    "# get pairs with threshold less than 0.5\n",
    "pairs = np.argwhere(distances < 0.15)\n",
    "pairs = [(unique_addresses2[x[0]], unique_addresses2[x[1]]) for x in pairs]\n",
    "\n",
    "# get unique pairs\n",
    "unique_pairs = []\n",
    "for pair in pairs:\n",
    "    if pair[0] != pair[1] and pair not in unique_pairs and (pair[1], pair[0]) not in unique_pairs:\n",
    "        unique_pairs.append(pair)\n",
    "\n",
    "# print(len(unique_pairs))\n",
    "\n",
    "unique_pairs_df = pd.DataFrame(unique_pairs)\n",
    "unique_pairs_df.columns = ['address1','address2']\n",
    "\n",
    "# create a new dataframe for each unique address1\n",
    "# each unique address1 should have a corresponding list of address2s\n",
    "\n",
    "# create a dictionary of address1 and address2s\n",
    "address_dict = dict()\n",
    "for idx, row in unique_pairs_df.iterrows():\n",
    "    if row['address1'] not in address_dict: address_dict[row['address1']] = [row['address2']]\n",
    "    else: address_dict[row['address1']].append(row['address2'])\n",
    "\n",
    "# create a dataframe of address1 and address2s\n",
    "address_df = pd.DataFrame.from_dict(address_dict, orient='index').reset_index()\n",
    "\n",
    "# rename columns\n",
    "address_df.columns = ['address1','address2','address3','address4']\n",
    "\n",
    "# merge with unique_addresses\n",
    "address_df = unique_addresses.merge(address_df, left_on=1, right_on='address1', how='left')\n",
    "address_df['all_addresses'] = address_df.apply(lambda x: [x['address1'], x['address2'], x['address3'], x['address4']], axis=1)\n",
    "address_df['all_addresses'] = address_df['all_addresses'].apply(lambda x: [y for y in x if str(y) != 'nan'])\n",
    "address_df['all_addresses'] = address_df['all_addresses'].apply(lambda x: list(set(x)))\n",
    "\n",
    "address_dict = dict()\n",
    "for idx, row in address_df.iterrows(): address_dict[row[1]] = row[0]\n",
    "\n",
    "# replace all data from address1 to address5 according to address_dict\n",
    "for idx, row in address_df.iterrows():\n",
    "    for col in ['address1','address2','address3','address4']:\n",
    "        if row[col] is not None:\n",
    "            if str(row[col]) != 'nan': address_df.loc[idx,col] = address_dict[row[col]]\n",
    "\n",
    "# create a list column in address_df which stores all data from address1 to address5 without nulls\n",
    "address_df['all_addresses'] = address_df.apply(lambda x: [x['address1'], x['address2'], x['address3'], x['address4']], axis=1)\n",
    "address_df['all_addresses'] = address_df['all_addresses'].apply(lambda x: [y for y in x if y is not None])\n",
    "address_df['all_addresses'] = address_df['all_addresses'].apply(lambda x: [y for y in x if str(y) != 'nan'])\n",
    "address_df = address_df[[0,'all_addresses']]\n",
    "\n",
    "# update dataframe with new address_prompt\n",
    "clean_data_v2 = clean_data_v1.copy()\n",
    "\n",
    "for idx,row in address_df.iterrows():\n",
    "    if len(row['all_addresses']) > 0:\n",
    "        # get all rows with address in all_addresses\n",
    "        thisrow = clean_data_v2[clean_data_v2['address_prompt'].isin(row['all_addresses'])].copy()\n",
    "\n",
    "        if thisrow.shape[0] > 4:\n",
    "            # get the most common response\n",
    "            clean_data_v2.loc[clean_data_v2['address_prompt'].isin(row['all_addresses']),'address_prompt'] = thisrow['address_prompt'].value_counts().index[0]\n",
    "\n",
    "# merge back with original dataframe\n",
    "clean_data_v2 = pd.concat([clean_data_v1, clean_data_v2],axis=0).drop_duplicates(subset=v_df2_cols)\n",
    "clean_data_v2 = clean_data_v2[clean_data_v2['address_prompt'].isin(clean_data_v2['address_prompt'].value_counts()[clean_data_v2['address_prompt'].value_counts() > 4].index)]\n",
    "clean_data_v2 = clean_data_v2.drop_duplicates()\n",
    "\n",
    "print (f'At this point, we have {clean_data_v2.sort_values(\"address_prompt\")[\"address_prompt\"].nunique()} unique venues.')"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Through manual inspection, we identified some duplicate venues that were not picked up by our pre-processing. We fix these manually."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "After removing duplicates, we now have 119 unique venues.\n",
      "Below are the top 20 most common place names for the verified addresses (after final cleaning): \n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Experimental Art Foundation, Adelaide, SA                             424\n",
       "Contemporary Art Centre of South Australia, Adelaide, SA              341\n",
       "Art Gallery of New South Wales, Sydney, NSW                           292\n",
       "Institute of Modern Art, Brisbane, QLD                                218\n",
       "Wollongong City Art Gallery, Wollongong, NSW                          171\n",
       "Museums and Art Galleries of the Northern Territory, Darwin, NT       128\n",
       "Queensland Art Gallery, Brisbane, QLD                                 126\n",
       "National Gallery of Victoria, Melbourne, VIC                          124\n",
       "Newcastle Region Art Gallery, Newcastle, NSW                          106\n",
       "Orange Regional Gallery, Orange, NSW                                  102\n",
       "Warrnambool Art Gallery, Warrnambool, VIC                              99\n",
       "Queen Victoria Museum and Art Gallery, Launceston, TAS                 96\n",
       "8 Llankelly Place, Kings Cross, Sydney, 2011                           96\n",
       "Art Gallery of Western Australia, Perth, WA                            91\n",
       "Tin Sheds Gallery, University of Sydney, Sydney, NSW                   88\n",
       "Ballarat Fine Art Gallery, Ballarat, VIC                               83\n",
       "Ian Potter Museum of Art, University of Melbourne, Melbourne, Vic.     82\n",
       "Artspace, Sydney, NSW                                                  79\n",
       "Heide Museum of Modern Art, Melbourne, VIC                             72\n",
       "Brisbane City Art Gallery, Brisbane, Qld                               68\n",
       "Name: address_prompt, dtype: int64"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ngv_dict = clean_data_v2[clean_data_v2.address_prompt == 'National Gallery of Victoria, Melbourne, VIC'][['location','point','latitude2','longitude2','altitude2','coded']]\\\n",
    "            .head(1).T.iloc[:,0].to_list()\n",
    "\n",
    "monash_dict = clean_data_v2[clean_data_v2.address_prompt == 'Monash University Museum of Art, Melbourne, VIC'][['location','point','latitude2','longitude2','altitude2','coded']]\\\n",
    "            .head(1).T.iloc[:,0].to_list()\n",
    "\n",
    "ervin_dict = clean_data_v2[clean_data_v2.address_prompt == 'S.H. Ervin Gallery, Sydney, NSW'][['location','point','latitude2','longitude2','altitude2','coded']]\\\n",
    "            .head(1).T.iloc[:,0].to_list()\n",
    "\n",
    "tmag_dict = clean_data_v2[clean_data_v2.address_prompt == 'Tasmanian Museum and Art Gallery, Hobart, TAS'][['location','point','latitude2','longitude2','altitude2','coded']]\\\n",
    "            .head(1).T.iloc[:,0].to_list()\n",
    "\n",
    "nas_dict = clean_data_v2[clean_data_v2.address_prompt == 'National Art School, Sydney, NSW'][['location','point','latitude2','longitude2','altitude2','coded']]\\\n",
    "            .head(1).T.iloc[:,0].to_list()\n",
    "\n",
    "camcag_dict = clean_data_v2[clean_data_v2.address_prompt == 'Campbelltown City Art Gallery, Campbelltown, NSW'][['location','point','latitude2','longitude2','altitude2','coded']]\\\n",
    "            .head(1).T.iloc[:,0].to_list()\n",
    "\n",
    "\n",
    "duplicate_dict = dict({'Ivan Dougherty Gallery, COFA, UNSW, Paddington, NSW': 'Ivan Dougherty Gallery, Sydney, NSW',\n",
    "                       'Ivan Dougherty Gallery, University of New South Wales, Sydney, NSW': 'Ivan Dougherty Gallery, Sydney, NSW',\n",
    "                       'Christine Abrahams Gallery, Melbourne, Vic.': 'Christine Abrahams Gallery, Melbourne, VIC',\n",
    "                       'Gallery Gabrielle Pizzi, Melbourne, Vic.':'Gallery Gabrielle Pizzi, Melbourne, VIC',\n",
    "                       'Tin Sheds Gallery, Sydney, NSW':'Tin Sheds Gallery, University of Sydney, Sydney, NSW',\n",
    "                       'David Jones Gallery, Sydney, NSW':'David Jones Art Gallery, Sydney, NSW',\n",
    "                       'Monash University Gallery, Melbourne, VIC':'Monash University Museum of Art, Melbourne, VIC',\n",
    "                       'Flinders University City Gallery, Adelaide, SA':'Flinders University Art Museum, Adelaide, SA',\n",
    "                       'Hogarth Galleries, Sydney, NSW':'Hogarth Gallery, Sydney, NSW',\n",
    "                       'Wollongong City Gallery, Wollongong, NSW':'Wollongong City Art Gallery, Wollongong, NSW',\n",
    "                       'National Art School Gallery, Sydney, NSW':'National Art School, Sydney, NSW',\n",
    "                       'Mary Place Gallery, Sydney, NSW':'Mary Place Gallery, Paddington, NSW'\n",
    "                       })\n",
    "\n",
    "# replace address_prompt using duplicate_dict\n",
    "clean_data_v2['address_prompt'] = clean_data_v2['address_prompt'].replace(duplicate_dict)\n",
    "\n",
    "# replace all rows with address_prompt == 'National Gallery of Victoria, Melbourne, VIC' with ngv_dict\n",
    "clean_data_v2.loc[clean_data_v2.address_prompt == 'National Gallery of Victoria, Melbourne, VIC',['location','point','latitude2','longitude2','altitude2','coded']] = ngv_dict\n",
    "clean_data_v2.loc[clean_data_v2.address_prompt == 'Monash University Museum of Art, Melbourne, VIC',['location','point','latitude2','longitude2','altitude2','coded']] = monash_dict\n",
    "clean_data_v2.loc[clean_data_v2.address_prompt == 'S.H. Ervin Gallery, Sydney, NSW',['location','point','latitude2','longitude2','altitude2','coded']] = ervin_dict\n",
    "clean_data_v2.loc[clean_data_v2.address_prompt == 'Tasmanian Museum and Art Gallery, Hobart, TAS',['location','point','latitude2','longitude2','altitude2','coded']] = tmag_dict\n",
    "clean_data_v2.loc[clean_data_v2.address_prompt == 'National Art School, Sydney, NSW',['location','point','latitude2','longitude2','altitude2','coded']] = nas_dict\n",
    "clean_data_v2.loc[clean_data_v2.address_prompt == 'Campbelltown City Art Gallery, Campbelltown, NSW',['location','point','latitude2','longitude2','altitude2','coded']] = camcag_dict\n",
    "\n",
    "clean_data_v2 = clean_data_v2.drop_duplicates()\n",
    "print (f'After removing duplicates, we now have {clean_data_v2.sort_values(\"address_prompt\")[\"address_prompt\"].nunique()} unique venues.')\n",
    "print('Below are the top 20 most common place names for the verified addresses (after final cleaning): \\n')\n",
    "clean_data_v2.address_prompt.value_counts().head(20)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Compare this with original table:\n",
    "\n",
    "| Venue | City | Frequency |\n",
    "| :- | -: | -: |\n",
    "| Art Gallery of New South Wales | Sydney, NSW | 292 |\n",
    "| Wollongong City Gallery | Wollongong, NSW | 183 |\n",
    "| Museums and Art Galleries of the Northern Territory | Darwin, NT | 128 |\n",
    "| National Gallery of Victoria | Melbourne, VIC | 124 |\n",
    "| Queensland Art Gallery | Brisbane, QLD\t| 113 |\n",
    "| Newcastle Region Art Gallery | Newcastle, NSW | 106 |\n",
    "| Orange Regional Gallery | Orange, NSW | 102 |\n",
    "| Warrnambool Art Gallery | Warrnambool, VIC | 99 |\n",
    "| 8 Llankelly Place, Kings Cross | Sydney, NSW | 96 |\n",
    "| Art Gallery of Western Australia | Perth, WA | 90 |"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Extra categories\n",
    "\n",
    "Before we continue with our NLP analysis, we also add some extra categories to the data. These are manually added based on the venue names."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# read curated list \n",
    "venues_checked = fetch_small_data_from_github(\"DAAO_venues_list_with_categories.csv\")\n",
    "\n",
    "# manually create a State column\n",
    "venues_checked['State'] = np.where(venues_checked['venue_name'].str.contains('QLD') | venues_checked['venue_name'].str.contains('Qld'), 'QLD', np.nan)\n",
    "venues_checked['State'] = np.where(venues_checked['venue_name'].str.contains('NT'), 'NT', venues_checked['State'])\n",
    "venues_checked['State'] = np.where(venues_checked['venue_name'].str.contains('ACT'), 'ACT', venues_checked['State'])\n",
    "venues_checked['State'] = np.where(venues_checked['venue_name'].str.contains('Sydney') | venues_checked['venue_name'].str.contains('NSW'), 'NSW', venues_checked['State'])\n",
    "venues_checked['State'] = np.where(venues_checked['venue_name'].str.contains(' SA') | venues_checked['venue_name'].str.contains('South Australia'), 'SA', venues_checked['State'])\n",
    "venues_checked['State'] = np.where(venues_checked['venue_name'].str.contains('WA'), 'WA', venues_checked['State'])\n",
    "venues_checked['State'] = np.where(venues_checked['venue_name'].str.contains('VIC') | venues_checked['venue_name'].str.contains('Vic'),'VIC', venues_checked['State'])\n",
    "venues_checked['State'] = np.where(venues_checked['venue_name'].str.contains('Tas') | venues_checked['venue_name'].str.contains('TAS'),'TAS', venues_checked['State'])\n",
    "venues_checked['State'] = np.where(venues_checked['venue_name'].str.contains('USA'), 'USA', venues_checked['State'])\n",
    "venues_checked['State'] = np.where(venues_checked['venue_name'].str.contains('China'), 'China', venues_checked['State'])\n",
    "venues_checked['State'] = np.where(venues_checked['venue_name'].str.contains('Griffith'), 'QLD', venues_checked['State'])\n",
    "\n",
    "# change address_prompt two match curated venue list\n",
    "clean_data_v2.loc[clean_data_v2.address_prompt.str.contains('321 Blaxland Rd Wentworth Falls'), 'address_prompt'] = '321 Blaxland Rd Wentworth Falls, Sydney'\n",
    "clean_data_v2.loc[clean_data_v2.address_prompt.str.contains('282 Petrie Terrace'), 'address_prompt'] = '282 Petrie Terrace, Brisbane QLD'\n",
    "\n",
    "# merge venues_checked with clean_data_v2\n",
    "clean_data_v2 = clean_data_v2.merge(venues_checked, how='left', left_on='address_prompt', right_on='venue_name')\n",
    "\n",
    "########### Unique venue frequency by major category ###########\n",
    "venues_checked_count=pd.DataFrame(dict(Counter(venues_checked[\"venue_category_major\"])).items(),\n",
    "                              columns=[\"Venue Category\",\"Frequency\"])\n",
    "\n",
    "# explosion\n",
    "explode = (0.05, 0.05, 0.05, 0.05)\n",
    "\n",
    "# Pie Chart\n",
    "plt.pie(venues_checked_count['Frequency'], \n",
    "        labels = venues_checked_count['Venue Category'],\n",
    "        autopct='%1.1f%%', pctdistance=0.85,\n",
    "        explode=explode, colors=['#1f77b4','#ff7f0e','#2ca02c','#d62728'])\n",
    "  \n",
    "# draw circle\n",
    "centre_circle = plt.Circle((0, 0), 0.70, fc='white')\n",
    "fig = plt.gcf()\n",
    "  \n",
    "# Adding Circle in Pie chart\n",
    "fig.gca().add_artist(centre_circle)\n",
    "  \n",
    "# Adding Title of chart\n",
    "plt.title('Unique count of DAAO venues (n=119), Major categories')\n",
    "\n",
    "# Displaying Chart\n",
    "plt.show()\n",
    "\n",
    "########### Exhibition frequency by major category ###########\n",
    "venues_checked_count2=pd.DataFrame(dict(Counter(clean_data_v2[\"venue_category_major\"])).items(),\n",
    "                              columns=[\"Venue Category\",\"Frequency\"])\n",
    "\n",
    "# explosion\n",
    "explode = (0.05, 0.05, 0.05, 0.05)\n",
    "  \n",
    "# Pie Chart\n",
    "plt.pie(venues_checked_count2['Frequency'], \n",
    "        labels = venues_checked_count2['Venue Category'],\n",
    "        autopct='%1.1f%%', pctdistance=0.85,\n",
    "        explode=explode, colors=['#d62728','#1f77b4','#2ca02c','#ff7f0e'])\n",
    "\n",
    "# draw circle\n",
    "centre_circle = plt.Circle((0, 0), 0.70, fc='white')\n",
    "fig = plt.gcf()\n",
    "\n",
    "# # make figure larger\n",
    "# fig.set_size_inches(6,5.75)\n",
    "  \n",
    "# Adding Circle in Pie chart\n",
    "fig.gca().add_artist(centre_circle)\n",
    "\n",
    "# Adding Title of chart\n",
    "plt.title('Count of DAAO venue activity (n=4,522), Major categories')\n",
    "  \n",
    "# Displaying Chart\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "########### Unique venue frequency by State ###########\n",
    "ax = venues_checked['State'].value_counts().plot(kind='bar', figsize=(10, 6), rot=0) # rotate x-labels\n",
    "for p in ax.patches: ax.annotate(str(round(p.get_height()/len(venues_checked), 2)), (p.get_x() + 0.065, p.get_height() + 1.015))\n",
    "\n",
    "# make y-axis higher \n",
    "plt.ylim(0, 65)\n",
    "\n",
    "plt.title('Count (and proportion) of DAAO venues by State/Country (n=119)')\n",
    "plt.show()\n",
    "\n",
    "########### Exhibition frequency by State ###########\n",
    "ax = clean_data_v2['State'].value_counts().plot(kind='bar', figsize=(10, 6), rot=0) # rotate x-labels\n",
    "\n",
    "for p in ax.patches: ax.annotate(str(round(p.get_height()/len(clean_data_v2), 2)), (p.get_x() + 0.075, p.get_height() + 20))\n",
    "\n",
    "# make y-axis higher \n",
    "plt.ylim(0, 1750)\n",
    "\n",
    "plt.title('Count (and proportion) of DAAO venue activity by State/Country (n=4,522)')\n",
    "plt.show()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Most frequent terms used for place names\n",
    "\n",
    "From here, we explore the most frequent terms used for place names. We find that the most frequent terms are \"Gallery\", \"Art\", \"Centre\", \"Museum\", and \"University\"."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# find the most frequent words across the strings for place names\n",
    "from collections import Counter\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "import nltk\n",
    "# nltk.download('punkt')\n",
    "\n",
    "from nltk.tokenize import word_tokenize\n",
    "\n",
    "# create a list of all the place names\n",
    "all_place_names = clean_data_v2['address_prompt'].astype(str).tolist()\n",
    "\n",
    "# create a list of all the words in the place names\n",
    "all_words = []\n",
    "for place_name in all_place_names:\n",
    "    all_words.extend(word_tokenize(place_name))\n",
    "\n",
    "# find top 100 most frequent words\n",
    "most_freq_words = Counter(all_words).most_common(1000)\n",
    "\n",
    "# remove a list of all words that are not relevant\n",
    "words_to_remove = [',','NSW','Sydney','Melbourne','Adelaide','South','SA','Brisbane','VIC',\n",
    "                   '.', 'New', 'Australia', 'QLD', 'Vic', 'Wales', 'WA', 'Canberra', 'and',\n",
    "                   'Perth', 'ACT', 'of', 'Qld', 'Victoria','Wollongong','TAS','Queensland','Newcastle',\n",
    "                   'Street','Hobart','the','The','Launceston','Orange','UK','NT','London','USA',\n",
    "                   'Paddington','Darwin','for','Western','Warrnambool','Ballarat','Northern','Territory',\n",
    "                   'England','Watters','Macquarie','Artspace','St',\"'s\",'&','Potter','Kings','Ian','Cross',\n",
    "                   '8','Llankelly','2011','Fremantle','Queen','Ivan','Dougherty','Tasmania','Central','Tamar',\n",
    "                   'Curtin','France','Tin','Sheds','York','Monash','Paris','Heide','Tasmanian','Sherman','Campbelltown']\n",
    "\n",
    "# remove the words from the list of most frequent words\n",
    "most_freq_words = [word for word in most_freq_words if word[0] not in words_to_remove]\n",
    "\n",
    "most_freq_words_dict = dict(most_freq_words)\n",
    "# keep words in most_freq_words_dict with at least 50 occurrences\n",
    "most_freq_words_dict = {k: v for k, v in most_freq_words_dict.items() if v > 50}\n",
    "\n",
    "# add value of two keys\n",
    "most_freq_words_dict['Gallery'] = most_freq_words_dict['Gallery'] + most_freq_words_dict['Galleries']\n",
    "# most_freq_words_dict['Museum'] = most_freq_words_dict['Museum'] + most_freq_words_dict['Museums']\n",
    "\n",
    "# remove key 'Gallery'\n",
    "most_freq_words_dict.pop('Galleries')\n",
    "# most_freq_words_dict.pop('Museums')\n",
    "most_freq_words_dict2 = most_freq_words_dict.copy()\n",
    "\n",
    "# create a wordcloud with the most frequent words\n",
    "from wordcloud import WordCloud\n",
    "\n",
    "# control random state so that the same words appear each time\n",
    "wordcloud = WordCloud(width = 800, height = 800,\n",
    "                background_color ='white',\n",
    "                min_font_size = 10, random_state=100).generate_from_frequencies(most_freq_words_dict2)\n",
    "\n",
    "# plot the WordCloud image\n",
    "plt.figure(figsize = (8, 8), facecolor = None)\n",
    "plt.imshow(wordcloud)\n",
    "plt.axis(\"off\")\n",
    "plt.tight_layout(pad = 0)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Hierarchical clustering using event description data \n",
    "\n",
    "Next we explore exhibition descriptions using hierarchical clustering; a method used to group similar objects into clusters that follow a hierarchical structure. This can help conceptualise what a taxonomy of venue categories might look like. We use Google's BERT to embed the data."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Hierarchical clustering (BERT)\n",
    "\n",
    "The first dendrogram shows the hierarchical clustering of the exhibition descriptions using a BERT encoder. We cluster the data into five groups. The x-axis provides a count (in brackets) of the exhibitition within each respective cluster. \n",
    "\n",
    "We provide three sets of annotations. The annotations above the x-axis (in red) represent the most frequently occurring terms within the event description for each cluster. There is also a second set of frequently occurring terms that follow in black, however these are filteered to only contain distinctive terms to get a better sense of the differences between clusters. Lastly, the annotations below the x-axis represent the most frequently occuring venues for each cluster."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [],
   "source": [
    "import seaborn as sns\n",
    "import re\n",
    "from sklearn.feature_extraction.text import TfidfVectorizer\n",
    "from sklearn.cluster import AgglomerativeClustering\n",
    "from scipy.cluster.hierarchy import dendrogram, fcluster\n",
    "\n",
    "# import nltk\n",
    "# nltk.download('stopwords')\n",
    "from nltk.corpus import stopwords\n",
    "\n",
    "### collect all relevant textual data from the dataframe\n",
    "# if description is not \\n then append to slug2 in one line\n",
    "clean_data_v2['slug2'] = clean_data_v2['title'].fillna('') + clean_data_v2['description'].apply(lambda x: '' if x == '\\n' else x)\n",
    "\n",
    "### pre-process for NLP\n",
    "# Load the documents and their corresponding categorical variables into a Pandas dataframe\n",
    "df = pd.DataFrame({'text': clean_data_v2['slug2'], 'category': clean_data_v2['address_prompt']})\n",
    "\n",
    "# summarise text for each unique place name\n",
    "df['text'] = df.groupby('category')['text'].transform(lambda x: ' '.join(x))\n",
    "\n",
    "#add new column with count for each category\n",
    "df['cat_count'] = df.groupby('category')['category'].transform('count')\n",
    "df.drop_duplicates(inplace=True)\n",
    "\n",
    "# Clean the text\n",
    "stop_words = set(stopwords.words('english'))\n",
    "\n",
    "def clean_text(text):\n",
    "    text = re.sub('[^a-zA-Z]', ' ', text)\n",
    "    text = text.replace(',', '')\n",
    "    text = text.lower().split()\n",
    "    text = [word for word in text if word not in stop_words]\n",
    "    text = ' '.join(text)\n",
    "    return text\n",
    "\n",
    "df = df[df['text'].notnull()]\n",
    "df['clean_text'] = df['text'].apply(clean_text)\n",
    "\n",
    "### Generate clusters\n",
    "\n",
    "def get_most_common_word(df, more_words = [], no_of_words=25):\n",
    "    # remove a list of all words that are not relevant\n",
    "    # words_to_remove = [',','NSW','Sydney','Melbourne','Adelaide','South','SA','Brisbane','VIC',\n",
    "    #                 '.', 'New', 'Australia', 'QLD', 'Vic', 'Wales', 'WA', 'Canberra', 'and',\n",
    "    #                 'Perth', 'ACT', 'of', 'Qld', 'Victoria','Wollongong','TAS','Queensland','Newcastle',\n",
    "    #                 'Street','Hobart','the','The','Launceston','Orange','UK','NT','London','USA',\n",
    "    #                 'Paddington','Darwin','for','Western','Warrnambool','Ballarat','Northern','Territory',\n",
    "    #                 'England','Watters','Macquarie','Artspace','St',\"'s\",'&','Potter','Kings','Ian','Cross',\n",
    "    #                 '8','Llankelly','2011','Fremantle','Queen','Ivan','Dougherty','Tasmania','Central',\n",
    "    #                 'Curtin','France','Tin','Sheds','York','Monash','Paris','Heide','Place','Vic.',]\n",
    "    \n",
    "    words_to_remove = []\n",
    "    \n",
    "    # add more words to the list of words to remove\n",
    "    words_to_remove = words_to_remove + more_words\n",
    "\n",
    "    all_words = []\n",
    "    for i in df:\n",
    "        for j in i.split(' '):\n",
    "            all_words.append(j.replace(',',''))\n",
    "\n",
    "    # find the most common words\n",
    "    most_common_words = Counter(all_words).most_common(no_of_words)\n",
    "\n",
    "    # remove the words from the list of most frequent words\n",
    "    most_common_words = [word for word in most_common_words if word[0] not in words_to_remove]\n",
    "    return most_common_words\n",
    "\n",
    "def get_linkage_matrix(model, **kwargs):\n",
    "    # Create linkage matrix and then plot the dendrogram\n",
    "\n",
    "    # create the counts of samples under each node\n",
    "    counts = np.zeros(model.children_.shape[0])\n",
    "    n_samples = len(model.labels_)\n",
    "    for i, merge in enumerate(model.children_):\n",
    "        current_count = 0\n",
    "        for child_idx in merge:\n",
    "            if child_idx < n_samples:\n",
    "                current_count += 1  # leaf node\n",
    "            else:\n",
    "                current_count += counts[child_idx - n_samples]\n",
    "        counts[i] = current_count\n",
    "\n",
    "    linkage_matrix = np.column_stack(\n",
    "        [model.children_, model.distances_, counts]\n",
    "    ).astype(float)\n",
    "\n",
    "    return linkage_matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [],
   "source": [
    "# ### load bert model\n",
    "\n",
    "# # !pip install transformers\n",
    "# from transformers import BertTokenizer, BertModel\n",
    "# from transformers import pipeline\n",
    "# tokenizer = BertTokenizer.from_pretrained('bert-base-uncased')\n",
    "# model = BertModel.from_pretrained(\"bert-base-uncased\")\n",
    "\n",
    "# ### encode text using bert (takes 15 seconds to run)\n",
    "# import random\n",
    "# import pickle\n",
    "\n",
    "# # encode the text using bert\n",
    "# def bert_encode(x):\n",
    "#   encoded_input = tokenizer(x, return_tensors='pt')\n",
    "#   output = model(**encoded_input)\n",
    "#   return pd.DataFrame(output['pooler_output'].detach().numpy()).T\n",
    "\n",
    "# # randomly sample 512 tokens from each row in df['clean_text']\n",
    "# # some strings are smalle than 512\n",
    "# df['clean_text_sampled'] = df['clean_text'].apply(lambda x: ' '.join(random.sample(x.split(' '), 300)) if len(x.split(' ')) >= 300 else x)\n",
    "# X_bert = df['clean_text_sampled'].apply(lambda x: pd.Series(bert_encode([str(x)])[0]))\n",
    "\n",
    "# # setting distance_threshold=0 ensures we compute the full tree.\n",
    "# model_bert = AgglomerativeClustering(distance_threshold=0, n_clusters=None)\n",
    "# model_bert = model_bert.fit(np.array(X_bert))\n",
    "\n",
    "# # save model as pickle\n",
    "# pickle.dump(model_bert, open('models/model_bert.pkl', 'wb'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
    {
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m3R07duiFF16wqt3MjqFevHhRbdu21YkTJ1Kskxt9WwCPD5KiAAD51v49u9QnBzre1nS6c9L9+/f1wgsvaM2aNVbVDwkJ0XfffadJkyapQIGs6xqYTCa99dZb+umnn6yqf/XqVc2YMUP/+c9/SIoCAAA5KiEhQf369TMSop555hl16NBBJUuW1NWrV7V27VpjJayEhAQNGzZMbm5u6tu3b5pte3h4qEWLFqpfv75KlCihggULKiwsTDt27ND69esVFxcnSVq9erWGDh1qJN8nZ+PGjRYJUfb29urYsaOaNGmi0qVLy8bGRjdv3tSpU6e0Z88e7d+/P9l2ypYtq8qVKys2NlaXL182znt6emZpfxAAACA/cHFxUYsWLdSoUSN5eHjIxcVFkZGROnTokFavXq2bN29Kepjs3rlzZ+3bt09OTk65GzQAAACy1YgRIywSouzs7NS+fXv5+vqqePHiunz5statW6ddu3YpMDAw1QWWJOmpp55S6dKljWSngICAFJOizBOcEm3evDnFtqOjo7V3716jbJ4UJUlvvvmmMXF03759OnjwoOrXr59qvJL04MEDLViwwCi/8MILKlq0aKr3hIWFqUuXLgoNDZWLi4u6deumJk2aqHDhwrp48aKWLl2q48ePS5Ju376tl156SUeOHKF/DQAAoIdz63r37q3IyEjZ29urW7duat68uZydnXX27FktW7ZM58+flyTdunVLHTp00M6dOy12P0qNv7+/vv/+e5lMJrm7u6tnz5566qmnZG9vr5CQEO3atSvFe7NzDDVxLuSJEydkY2MjPz8/+fn5yd3dXZGRkdq1a5fs7e0l5WzfFsDjhZkuAIAnQnZ1vK3tdLu6uhqJVmfPnjXuL1WqlAoXLpxs246Ojhl6108//dQiIcrNzU1dunRRnTp15OrqqgcPHig8PFxHjx7V1q1bFRISkmw7ifFGREQYq0sUKFBAnp6eydYvW7asRXnGjBkWCVHOzs7q0qWLGjZsKDc3N5lMJkVGRur48ePasWOHMcANAACQ07Zt26aEhAQ5Ojpq0aJF6tGjh8X10aNHa9GiRRo0aJAePHhgJH8/++yzKlmyZJL2bG1t1a1bN7377rt65plnZGtrm+xzQ0JC9NJLL2nHjh2SpAULFmjgwIFJJiYk+vLLL43jypUra+PGjakm81+6dEnTpk1LknC+aNEiSVJgYKDFswIDA+Xl5ZViewAAAE+SBg0aaOTIkerWrVuK43TR0dEaPny4sYroiRMnNHHiRKt3DQUAAEDes3XnHk2ZMsUoe3h4yN/fX97e3hb1PvnkEy1evFiDBg3S/PnzUxwjTOTr66ulS5dKepj49P777ydbzzwBys7OTvHx8Tpx4oSuXLkiDw+PJPX/+usvY2EmGxsb+fr6Wlzv2bOnSpQooRs3bkh6uKL+Dz/8kGqskrR27VqLHatef/31NO+ZMWOGEhIS1KZNG/38889yd3e3uD569Gi9+eabmjNnjiTp/PnzmjdvnoYOHZpm2wAAAPndzJkzlZCQoMqVK8vf31+1a9e2uD5+/Hj95z//MfqqN2/e1ODBgxUYGCgbG5s020+8780339TkyZOtmjuZE2Ooid/S3d3dtXLlSjVv3jzFujnZtwXweCEpCgCQr2V3xzs9ne533nlHkix+ZEycOFEDBw609nXSFBMTYzEI36VLFy1evFguLi4p3rN//35NmTIlyY+fM2fOSJLGjh1r/C3Kli1rnE/LV199ZRx7e3vrt99+U6lSpVKsf/LkSU2dOlWFChWyqn0AAICskpCQIEmaO3dukoSoRP369VNsbKzeeOMNSQ8Tx7/88ktNnjw5Sd2RI0fKwcEhzed6eXlpw4YNatiwoZE4/8MPPySbFHX//n1t3brVKH/77bdp7m5arlw5TZgwIc04AAAAYMmncYMUd9005+LiopkzZyoqKkrLli2TJE2fPl0ff/yxChYsmN1hAgAAIBeMnjBJJpNJklSwYEH9/vvvKa4+/9JLLyk2Nlavv/66MQaZEj8/PyMpKigoSHFxcUl2dTeZTNqyZYukh4tZvvDCC/rll18kPUyk6tevX5J2zXeWqlOnjkqUKGFx3d7eXgMHDtQ333wj6eGCSpMmTUpzfDPx27ok1ahRQ08//XSq9aWH47ANGzbUunXrjNX8zRUoUED//e9/FRAQYCzsuXjxYpKiAAAA9LAv5eLiog0bNqhKlSpJrhcsWFDfffedwsPDtXDhQkkPE+R/++03de3a1apn9OnTR9OmTbOqro+PT46NoRYsWFAbN25U3bp1U62Xk31bAI+X1JchAQAgD2vQ2Fv79+9X3759U911KbHj3bt3b+Pc9OnT9eDBA6uek9jpTi0hKqfs3LlTsbGxkh4OGs+ZMyfVhChJatiwoebPny87O7ssi+PcuXMWO1DNmDEj1YQoSapevbq+//57lS9fPsviAAAAsJafn5/69OmTap3XX3/dYsXXBQsW6N69e0nqWZMQlahIkSIaPXq0Ud60aZPi4+OT1Ltx44bF+WrVqln9DAAAAKRPevpzkuXiQGFhYVZNBgAAAEDecyo8Xn9t322UBw8enGJCVKLXXntNTZo0SbNt84WSoqOjtXv37iR1Dh06pPDwcElSkyZN1K1bN+Oa+Q5S5szPp7RD/eDBg43jyMhI/frrr6nGGhoaqo0bNxrl9Kyk/+OPPyabEJWoUKFCFouK7tu3z9jpCgAA4Ek3cuTIZBOizH377bdydnY2yjNnzrSqbXt7e4vF2NOSk2Oo//rXv9JMiEqUk31bAI8PkqIAAPlWTnW809Ppzm5Xr141jl1dXZOs9JUbcUhM2gUAAI+/N99806p6iTtFSVJ4eLi2b9+e6We3adPGOL5z546OHz+epI6Tk5NFOSueCwAAgKxRsWJFVapUySjv2bMnF6MBAABAdtlwxjI557XXXrPqPmvqVa1aVeXKlTPK5js8JXo0wck8ySm5+pGRkTp48KBR9vPzS/HZ5m2Zr5SfnDlz5hgLONnb26t///6p1k9UrVo1NWvWLM16Pj4+xvHdu3ctFuMEAAB4Utna2lqVsFOqVCl1797dKG/cuDHZhT4f1aFDB5UuXTozIaYqM2OogwYNsrpuTvVtATxeSIoCAOD/y2jHOz2d7uxmPln22rVrOnv2bK7HITFpFwAAPP7atm1rVb327dtblLNiwquHh4dFOTQ0NEmdYsWKqWLFikb5vffe0/Lly5WQkJDp5wMAACDzzPt0yfXnAAAAkPftufzPWFzRokXVoEEDq+7z9fW1ql5aSU7m5/z8/FSqVCnVqlVLknT+/PkkyUOBgYHG+KGtra2eeeaZFJ9tvqJ+YGCgzp07l2w9k8mkuXPnGuVu3bqpZMmSqbzVP6xJiJKksmXLWpRv3rxp1X0AAAD5Wd26dZN8V06J+TftBw8e6NChQ2ne07x58wzHZq2MjKG6uLike8H6nOjbAni8kBQFAICZ9Ha8M9Lpzk6PDrx369YtV1amrVmzphwdHY3ygAED9Mcff+R4HAAAANYoX768ihUrZlXdcuXKWdQ9ceJEinXv37+v3377TW+++aaaNWsmd3d3OTs7y8bGxuJfwYIFLe5L6SP/kCFDjOOoqCj17t1b5cuX15AhQ7R06VJdunTJqncAAACA9Xbt2qWRI0eqTZs2qlChgooUKSJbW9skfbpt27YZ9zBpEwAAIH86H/lPUlTNmjWtvq9q1apJxgCTY54UtWPHDt29e9cox8fHKygoSJJUqFAhtWjRQpLl7k/mO0k9Wm7QoEGqY6A9e/ZUiRIlJD2cHDp79uxk6/355586f/68UX7jjTfSei2Du7u7VfVcXFwsynfu3LH6GQAAAPlVnTp1Mlw3tW/aiapUqZLumBJl5xhqxYoVZWubvnSHnOjbAni8kBQFAHgiZFfHOyOd7uzk6empDh06GOWjR4/K29tbdevW1ahRo7RhwwbdunUr2+MoVKiQBg4caJRDQ0PVtm1bValSRcOHD5e/v7+uX7+e7XEAAABYo1SpUumqb746VGRkZLJ1Vq1apSpVqqhr166aMWOGdu7cqbCwMMXExKTZvvlkB3MjRoxQly5dLM5dvnxZ06dPV9++fVW+fHlVrVpVb7/9tnbu3JmONwIAAMCjgoOD1aJFC/n4+GjSpEn6888/dfHiRd2+fVsmkynVe1PqzwEAACBvu3n3n35g8eLFrb7P1tZWRYsWTbOeeYLT3bt3tWPHDqO8b98+4ztvs2bN5ODgkOSeR3eXenRnqdTY29tbfN+dN2+e4uPjk9SbNWuWcezl5aU2bdqk2q65xJjTK63+NwAAwJMgPd+0H93tKKVv2uaKFCmS7phyYgw1I3HlRN8WwOPl8ZnFDQBANsjujndGOt3ZbebMmUlWbggODtZXX32lDh06yNXVVd7e3ho3blyKW8Nmha+//lre3t4W586ePavvvvtOPXr0UOnSpVW3bl198MEHOnLkSLbFAQAAkBbzHS6t4ezsbBxHR0cnuT516lT17NlTFy9eTHKtcOHCKlOmjCpVqqTKlSsb/8yl1E+1s7OTv7+/pk6dqgoVKiRb58yZM5o6daqaNWsmX19fnTx5Mj2vBgAAAEk7du9TixYttH379iTXHBwc5O7uLi8vL4v+nPkETyZtAgAA5E/3zOZRFipUKF33WlPf09NTFStWNMrmSU3muz6Z7yjVqlUrYxFP8zrXrl3T0aNHk70nJYMHD5aNjY2kh4sxrV+/3uJ6RESE/P39jfJrr71m1AcAAED2Ss83bfPv2VLy37QfVaBAgXTFs2PHjhwZQ01vXIno2wJPFpKiAAD51r49u7K9453RTnd2Klu2rPbu3asRI0aocOHCSa4nJCRoz549Gjt2rKpVq6bXX39dUVFRWR6Hi4uLtmzZogkTJhjb0ZozmUwKDg7W119/rTp16qhHjx66cuVKlscBAACQltjY2HTVv3PnjnHs4uJice3YsWMaPny4xfWRI0fqr7/+UlRUlKKiohQaGqqzZ8/qzJkzOnPmjE6fPm31s21tbTV06FCdP39egYGB+vjjj+Xr65vsIPiWLVvk7e2tw4cPp+v9AAAAnmR340x65V/v6fbt28a5F198UWvXrlVYWJhiY2N15coVnT9/3ujPnTlzJsniQAAAAMh/ipjlNZn3F61h7fdY8+SllJKizHd9Kl68uOrXry9JCg0N1alTp5LUL1CggFq2bJnms6tWrSpfX1+jPHv2bIvrP//8s+7duyfp4QJOgwYNsuKNAAAAkBXS803b/Hu2lPSbdmbdvXtXr7zyymM9hkrfFniykBQFAMiXTHH39e6/Xn+sO97ZqWjRovrmm2905coV/frrr3r77bfVoEEDY5WwRPHx8Zo9e7aefvrpbEmMcnBw0OjRo43VFt5//335+PioYMGCSer6+/urSZMmunTpUpbHAQAAkJpr166lq/7169eN4+LFi1tc++GHH/TgwQNJD1fr2rp1qyZOnKiWLVsmm7AuSTdv3kxfwHqYHNWqVSuNHz9emzdv1s2bNxUQEKC33nrLYjfTqKgovfbaa+luHwAA4Em1+kSczp6/YJRnzJihxYsXq1OnTipVqlSK91nTp8vISqMxMTHpvgcAAADZo6TTP/255HaJT8mtW7esTqIyT4ras2ePoqOj9eDBA23dulXSw1X/mzZtanGPeZJUYiKVeUJVkyZNrJ4IO3jwYOM48dt6IvOJpB06dFDZsmWtahMAAACZl55v2ubfs6Wk37Qza/Xq1Tp79qxRzsox1KxE3xZ4cpAUBQDIl2JO79SF8+eM8uPa8c5uzs7O6tGjh3744Qft379f4eHhWr58uZ5//nnZ2dkZ9YKDgzV+/Phsi6NgwYJq3769Jk2apB07digyMlLr1q3TgAEDLHbnCg0NtdhZAQAAICdcvHjR6n5gaGioRd3q1atbXP/zzz+N4/79+6tevXpptnnu3Lk066TF3t5erVu31o8//qjTp09bxLV3716dPHky088AAAB4Evx5Ps44rl69ut54440070lISFBISEia9ZycnIxja5OdzD/UAwAAIHfVK/3P99UzZ85Yneh04MABq59hnuD04MEDBQUFaffu3cZq/08//XSSBSjTSooyT7RKS8+ePVWyZElJUlxcnObPny9J2rVrl4KDg416r7/+utVtAgAAIPPM+2JpOXLkiEX50W/amWX+TTyrx1CzEn1b4MlBUhQAIF+6e+GQcfw4d7xzWrFixdSrVy+tWLFC27Ztk6Ojo3Ft4cKFORaHs7OzOnbsqHnz5ik4ONj48SE93DEqOjo6x2IBAACQpE2bNllVb8OGDRblJk2aWJRDQ0ONY2sSoiTLQeOsUKpUKX311VcW544dO5ak3qOTJxISErI0DgAAgLwo9LbJOLa2P7d3716rdmEvVqzYP88x6zemZufOnVbVAwAAQPZrVv6fpKiEhAStXr3aqvtWrlxp9TPKlCmjatWqGeWAgIA0E5xatmypAgUKSJICAwN18eJFnTlzJtV7UmJvb68BAwYY5cQV9M1X0vfw8FCnTp2sbhMAAACZd/jwYV29etWquubftAsWLKj69etnaSwZ+SZu7RhqVqJvCzw5SIoCAORL8bfDjePHreOdOCAt5e7E06ZNm1psEXv16lVFRkYmqWc+WTY74q1SpYo++ugjoxwXF6fTp09n+XMAAABSM3PmTKvqzZo1yzh2c3NTixYtLK6bTP9Mor17926a7d2/f18//fSTlVFa79HVvh48eJCkjouLi0X51q1bWR4HAABAXmPWnbOqPydJ3333nVX1atSoYRzv2rXLilhMxuqlAAAAyH0dqhSQa/FiRnnixImKj49P9Z7Lly9r7ty56XqOeRJTQECANm/ebJTNd4VK5OLiYizedP36dX3//ffGNXt7+yRjmGkZPHiwbGxsJEmnTp3Shg0btGTJEuP6wIEDLb55AwAAIPslJCRYJPOk5Pr16/L39zfK7dq1U6FChbI0lvR+E5esH0PNavRtgScDSVEAgHzJpMe3420++TS3J56md7JsdsVrTRwAAADZ6X//+59WrFiRap25c+darNTfv3//JAPIFSpUMI7Xrl2b5nNHjhxp1W6lERERun37dpr1Eh06dMii7OXllaTOo+eOHDlidfsAAAD5VYWiNsbxX3/9leYiSv7+/vrll1+sartp06bG8dmzZxUYGJhq/W+//VYnT560qm0AAABkv0IFbDR4wItG+ciRI3r//fdTrH/v3j3169dPd+7cSddzzBOfDh48qO3bt0uSihYtqoYNG6Z5z9SpU41jHx8fOTo6puv5VatWla+vr1EeOHCgMTZpY2Oj1157LV3tAQAAIGtMnDhR586dS7XO+++/r+joaKP8xhtvZHkc5t/Es3oMNavRtwWeDCRFAQDypQJFShrHj1vH23zyaVZPPL148WKaq5GZM58s6+zsrJIlSyapYx5vVFSULl68mGa7V69e1b179zIUhyR5enpafS8AAEBm2do+HB4ZMGCAVq9enWydX375RUOGDDHKrq6uGjVqVJJ67dq1M44DAgL0xRdfJNvenTt3NGzYME2ZMsV4fmoOHz6sChUq6MMPP9TRo0dTrRscHGwxGaNs2bJq3LhxknpFixa12K3g66+/TnMQHQAAIL9rV/mfVUFv3ryp/v37KyYmJkk9k8mk2bNnq0+fPpJkVZ+uV69esre3N8qvv/56smNt8fHxmjx5sj744ANjFVMAAAA8Hj4eMcziW+Z3332nbt26af/+/ca5+Ph4bdq0SU2bNlVgYKBKly4tV1dXq5/h6+tr9AMTEhKM766tWrWSnZ1dsveYJ0XFxsYax+a7TqXH4MGDjeOwsDCL9ipXrpyhNgEAAJBxtra2un37ttq3b69jx44luf7gwQONGDFCCxYsMM61bNlSXbp0yfJYzL+JZ/UYanagbwvkf+z3BgDIlxwrNlT0wQ2S/ul4L168WE5OThb1TCaT5syZo6FDh0p62PFOSEjI1th8fHx08OBBSdLSpUvVr18/i0HqzJg9e7YWLlyoYcOGqU+fPnJ3d0+x7rJlyyy21O3atWuykyy8vb0t/i4jR47UtGnTVLRo0RTb3rBhg0aNGqW3335b/fr1S3ZngkSBgYEWk4WbNWum0qVLp/aaAAAAWapFixYqUKCANm/erO7du6tVq1bq0KGDSpYsqbCwMK1du9ZYjVV6uGLU1KlTk00oHz58uGbMmGHsVjp69GgtX75cPXr0UPny5RUTE6MjR47o119/1bVr1yRJEyZM0EcffZRmnDdv3tTEiRM1ceJEVatWTT4+PqpVq5ZcXV1la2urq1evavv27dqwYYNFovzkyZNTHGB+9dVXNXLkSEkPE/YrV66s8uXLq3jx4hZ9w8T+KwAAQH7XtXoBPVW9qo6dPC1JWr16tapWraq+ffuqZs2aSkhI0Pnz57V69WodP35cktS+fXvduXNHQUFBqbbt6uqqYcOG6dtvv5X0cLeoWrVqqV+/fqpfv75sbGx09uxZ+fv769SpU5Kk8ePH65NPPsnGNwYAAEB6ODs7aeXKlXr22Wd169YtSdKaNWu0Zs0aubi4qHjx4rp+/boxPmhra6tFixbptddeU0REhCSlmNiUqFSpUnrqqaeSLI6UWoJT8+bNVahQoSQLV2b0O3TPnj1VsmRJXb9+3eJ8duw0AAAAgLS98cYb8vf31+nTp9WwYUN1795dzZs3l5OTk86ePatly5ZZLIBZrFgxzZw5M1sWXerataueeuopIzkrK8dQswN9WyD/IykKAJAvOVZpqqrVa+r0yYed6sep4z1o0CBNnz5dJpNJd+7c0bPPPis3Nzd5eHhYDIDPmjUr2RX903L27Fm9++67eu+999S4cWN5e3urUqVKKl68uB48eKCQkBBt2rRJe/fuNe5xdnbWhAkTkm3Pw8ND7du31++//y5JWrJkiVasWCEvLy85Ozsb9Ro3bqxZs2YZ5atXr+rjjz/Wxx9/rLp166pp06aqVq2aXF1dZTKZdOnSJQUGBiowMNC4x87OzpgUAgAAkFNsbW21ePFitWnTRkePHtWWLVu0ZcuWFOtOmTJFffv2Tfa6l5eX5s2bp5dffllxcXGSHiYUpZRUNGTIEI0aNcqqpChzp06dMibKpsTOzk7/93//p969e6dYZ/jw4dq8ebPWr19vnLt48aJVu4MCAADkR3a2Nlo5/yc90+VF4yP55cuXNXny5GTrN2vWTIsXL1aPHj2sav+zzz7Trl27tHXrVknS7du3NW3atCT1bG1tNWHCBL344oskRQEAADxmGjVqpD///FMvv/yyTpw4YZyPjo5WdHS0UXZzc9OiRYv07LPPWiQrFSlSJM1n+Pn5JUmKSi3BycHBQc2aNbP49uro6KimTZta80pJ2Nvba8CAAfrmm2+Mc25ublb3ewEAAJC13N3dtWzZMnXr1k03b97U0qVLtXTp0mTrFilSRL///ruqV6+eLbHY2dlp5cqVeuaZZ7JlDDWr0bcF8j+SogAA+ZKNrZ2mz1ukPl3bPXYdb29vb3322WcaM2aMTCaTJCk8PFzh4eEW9cwHzDMiISFBu3fv1u7du1Ot5+rqqtWrV6tSpUop1vnpp5/UunVrYzWJuLg4nTlzxqJOsWLFUrz/8OHDOnz4cKpxODo66ueff1azZs1SrQcAAJAd3N3dtWvXLn3wwQeaP39+sn2xBg0a6IcfflCLFi1SbatPnz4qW7as3n33Xe3bty/ZOrVr19ann36qXr16WRVfgwYNNGXKFP3+++/atm1bqn1Fe3t7derUSWPHjlXdunVTbbdAgQJat26dfv31Vy1btkwHDhzQ1atXFR0dbfRVAQAAnjQ1qlXR/v379c4778jf3z/ZfpGHh4eGDh2qDz/8UAUKWP+5zcnJSRs3btTHH3+sqVOn6v79+0nq1KtXT998843atGmjkJCQzLwKAAAAskmjRo108OBBLViwQMuWLdPRo0cVHh4uNzc3VaxYUT179lT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kMmnSpPj+++/z1B955JFx0003lf2CAAAAAAAyzPLly2PcuHF56rOysuL++++PfffdtxxWRUUjKQoAAAAAAACgALVq1Yo999wzzj777LjkkkuicmWXWAEAAAAACiM7Ozt22GGHOOSQQ+L3v/99dO3atbyXRAWRlUgkEuW9CAAAAAAAAAAAAAAAAIB0ZZf3AgAAAAAAAAAAAAAAAAAKQ1IUAAAAAAAAAAAAAAAAkFEkRQEAAAAAAAAAAAAAAAAZRVIUAAAAAAAAAAAAAAAAkFEkRQEAAAAAAAAAAEAG6t69e2RlZUVWVlacd955BbY777zzku26d+9eZusDAAAoTZXLewEAAAAAAABUXIsWLYoxY8bE1KlTY/HixbFu3bqoVatW7LDDDtG6devYc889o1GjRuW9zG3WTTfdFIMGDYqIiFatWsX06dPLd0HbgenTp8cuu+ySLI8aNcpNowBQAoYNGxbnn39+sjx06NAtJnDkNnfu3DjmmGNi7NixyboDDzwwRo4cKZYsZ5v/Xh977LE466yz0ur74IMPxsUXX5wsV69ePRYtWhTVq1dPq3/nzp3jk08+iYiImjVrxuLFi6NKlSqFWD0AkCnWrl0bn376acycOTPmz58fixcvjtq1a0eDBg1i9913j/bt26cdQ8CWLFq0KB5++OEYOXJkTJo0KRYvXhxr1qxJvv/FF19Ehw4dSmSudevWxYQJE+LLL7+MhQsXxvLly6N69epRt27d2HnnnaNdu3bRtm3byMrKKpH5Khr7uGwiKQoAAAAAAIAS9/zzz8f9998fOTk5kUgktti2TZs2cfjhh0fv3r3jF7/4RVSuXPEuYd10003J13379i2xC+dlYfXq1dGgQYNYvXp1REQcddRR8b///S+tvsuXL48GDRrE+vXrk3XDhg2Lfv36pdV/8xtlH3/88TjzzDMLsXoAINP98MMPcdRRR8W3336brOvRo0e8+OKLUbt27XJcGRERRxxxREp51KhRaSdF5eTkpJRXr14dH330UVo3Mi5fvjw+//zzZLlr164SogCggkkkEvHMM8/EsGHD4t13342VK1cW2LZy5crRtWvXOOecc+K0006rkHFiTk5OMn6qX79+/Pa3vy3X9VREX3zxRRx77LExe/bsUp3nm2++ibvuuiueeOKJWLZs2Rbb1qtXLzp37hzHHHNMnHbaabHTTjuV6trKw4gRI5IPwGjdunXaD8+ATSreFSUAAAAAAADKzaJFi+Kss86KkSNHpt1n6tSpMXXq1Bg2bFjMmjUrmjVrVoorLB+bTnuK+PnCbiYlRVWvXj26dOmSvOni/fffj7Vr10bVqlW32nf06NEpCVERP98om25S1OY3ynrSJwBsX77++us4+uijY+bMmcm6vn37xlNPPRXVqlUrx5WxSatWrWKXXXaJadOmRUTe+G1L3nnnnTx1OTk5acV8m8eZmydnAQCZ7a233orf/e538eWXX6bVfv369cmkoauvvjpuuOGGuOiiiyrUw5dycnJSTpSXFFWy1q1bFyeffHJKQlSVKlWiefPmKcn3xf3/kH/84x9xzTXXJB9AtTVLliyJN954I954441Yu3ZtXH311cWaf1s0YsSIGD58eEREdOvWTVIUhVZx/qUHAAAAAACgXC1fvjyOPvroGDNmTLIuKysrunTpEl27do3WrVtHzZo1Y+nSpfHTTz/FmDFj4qOPPorly5eX46pJxxFHHJG8wXXVqlXxySefRNeuXbfaL7+bYot6o+zuu+8eO+64Y9p9AYDM9tlnn0Xv3r1j/vz5ybrzzjsvHn744ahUqVI5rozNHXHEEcmkqO+++y5mzJgRLVu23GKfr776KubMmRMREbVr107+P8GoUaNSTlktyOYxpaQoAKg47rnnnrjiiitiw4YNybqsrKzYb7/94ogjjogdd9wxGjVqFEuXLo05c+bEF198ETk5ObFmzZqIiJg3b1785je/ia5du2bUg4koX6+++moypo2IuO666+Laa6+NGjVqlNgct912W1x77bUpdTvuuGP07t079tprr2jQoEGsXbs2FixYEOPHj4+PP/44pk+fXmLzQ0UlKQoAAAAAAIASceONN6YkRLVv3z6GDRu2xZsP1qxZE//73//ikUceif/85z9lsEqK4ogjjogbb7wxWR41alShk6I23ez6/fffx7Rp02KXXXbZYt/cN8puWgMAsH3IycmJE044IZYtW5as+93vfhd/+9vfIisrqxxXRn6OOOKIGDJkSLKck5MT55xzzhb7jBo1Kvn67LPPjieeeCKWLl0aH3/8caxatWqrN5/mjjPr1KkT+++/f9EWDwBsU2655Za44YYbkuWsrKw444wz4pZbbok2bdoU2G/FihXx9NNPx6BBg+KHH34oi6VSwXz00UfJ182aNYubb765RP/fY9y4cXH99dcny9WrV4+77747Bg4cGNnZ2QX2Gz9+fDz77LPx73//u8TWAhWNpCgAAAAAAACKbfny5fHAAw8kyzvttFPk5ORE/fr1t9ivWrVqcfzxx8fxxx8fP/74YzRo0KCUV0pRdO7cOWrWrBkrV66MiJ9vQs19ET8/y5YtSybJ1a1bN84444x46KGHkv23lhTl6f8AsH166aWX4vTTT4/Vq1cn62655Za47rrr0h4jkUjE5MmTY9KkSTFz5sxYtmxZ1KhRIxo1ahTt27eP/fbbb4s3HhbG2rVrY/To0fH999/HnDlzombNmnHiiSdG69atC+yzZs2aeP/992P69Okxd+7cqFGjRjRv3jwOP/zwaNasWYmsa+HChfHOO+/EjBkzYvXq1dGkSZPo2rVrtGvXrkTGz23zOG3UqFFbTYrKHesdeeSR8f3338fIkSNjzZo18eGHH0aPHj0K7Lt8+fL4/PPPk+XDDjssKlfe8m1wq1atSv6e5s+fH3Xq1IlmzZrFYYcdFk2bNt1i360pzbEnTpwYn332WcyaNSvq168fLVu2jO7du0etWrWKNe7mVqxYETk5OTFjxoxYsmRJNGvWLA444IDYe++9S3Se0jJx4sT48ssvY9asWbFmzZro1KlT9OzZs7yXBUAhvfHGGyknRlatWjUee+yxOPXUU7fat1atWtG/f/84++yz49Zbb41bbrmlFFdKRZT7hNo2bdqU+MMY/vrXv6acfvbYY4/FySefvNV+++23X+y3335x/fXXpzxACvj/SYoCAAAAAACg2N56662UG1cvvfTSrSZEba5FixaFnnfevHkxevTomDVrVixdujQaNWoULVu2jMMPP7zEbxTc1mzcuDHee++9+Pbbb2Pu3LlRv3792HPPPaNr165bvSm0sKpWrRqHHHJIvPnmmxER8cEHH8SaNWuiWrVqBfYZPXp08kL/YYcdFj169EgmRY0aNSrOP//8Lc6Z+0bZrKz/j737ju/p+v8A/sqWSCJTJEZCjBgl9ghJjNoj1FYSSpW2Wqv9qtZoaUtVlarRkqDUrNijSMQeQRCbICJIJITscX5/eOT+Pjf5jPvJpF7Px+PzeNxzP+ece+79fMj53Hve5xjA19dXY964uDhcvHgRt2/fRmJiIoQQsLOzg6urK1q1agUrKyuFZ1p4WVlZOHXqFG7duoXHjx/D2NgYFSpUQMuWLXUGgmkSHx+Ps2fP4vbt23j+/DkMDAxQtmxZVKxYETVq1EDdunVhZGRUxGdCRERU8tasWYMRI0YgKysLAGBoaIjffvsNY8aM0Vk2PT0dO3bswKZNm3Do0CHZoMa87O3t8emnn2L8+PGwtrbWWXdAQABWrVoFAPDx8UFoaChSUlLwzTffIDAwEImJibL85cqVQ0BAQL56oqKi8M0332Dr1q1SsLkqAwMDeHt746effkLTpk11tsvNzQ337t0D8GrV1hkzZiA+Ph7jx4/Hpk2bkJ6enq9M69atsXjxYtSvX19n/Url9klu3rwJIH9wuzqHDx+Wtr29vXH79m3s2bNHKq8tKOrIkSPSdwSA1rwPHjzA1KlTsWnTJqSmpuZ738DAAF5eXvj+++/Rpk0bne0uqbqPHTuGTz/9FOfPn8/3nqWlJfz9/TF37lxYWFjoVW9eKSkp+OKLL7Bq1Sq8fPky3/uNGjXCokWL0KpVK6313L17V9bXDQkJ0dp/zxUUFCT7XSCEUJsvNDRUFnwXFRUFNzc3bNmyBTNnzsSlS5dk+X18fNCxY0d4eXnh+PHjAIBmzZrh1KlTOtukqlWrVjhx4kSByxMRkXIpKSkYOnQocnJypH1r165F37599arH1NQUM2bMQIsWLfS6HxQbG4vjx4/j0aNH0j3GatWqoU2bNlrvf+nj0qVLiIiIQExMDMqUKQM3Nze0bdtWUX+0OMXGxuLEiROIjY2VgqNHjBihs0xxXy8lMjMzcfz4cdy+fVuabMDJyQktWrTQOkmBprpymZiYFHFLgd27d0vbHh4eigKiVJmamqJy5cp6lSnK6/MmunXrFs6ePYsHDx7AyMgIlSpVQtu2beHg4FDaTaOiJoiIiIiIiIiIiIiIiIgKacGCBQKA9NqzZ0+xHu/kyZOibdu2wtDQUHbc3JeZmZkYOHCgiIqKUlSfatnAwEBFZUJCQmTl8h5r+vTpatum7RUSEqKxDldXV2n/okWLRKVKldTW4ejoKJYtW6boHPQxe/Zs2XEOHz6sNf/kyZOlvHPnzhWPHj2S0pUrV9Z5PCcnJyl/vXr18r0fHh4uJk+eLOrUqaP1mhoZGYnevXuLCxcuKDrPqKgorZ+JJo8fPxZjx44VNjY2GtvSsGFDsW/fPkX1CSHE+fPnRdeuXYWRkZHWcyxbtqzw8/MTFy9eVFw3ERFRSQsMDNTa5/r111+FgYGB9L6JiYlYt26d4vrz9s2UvDw8PMStW7d01u3v7y+V8fHxEffv3xceHh4a61XXn1y6dKkwNTVV1C4DAwMxf/58ne1ydXWVykyfPl1cuHBBVKxYUWf9VlZW4sSJE4qvrRIffvih7Bh3797VmPfy5ctSvjp16gghhDhx4oS0r3Xr1lqP9cUXX8iOFR4erjbfjh07hIWFheLvw8SJE0VOTo6i8y3OuhctWqTxd47qq169eiI2Nlb4+PhI+/z9/TXWm/d7HBsbK+rWravzOIaGhuK3337T2uaC9qHz/r+gibrfXp988onGNvv4+AghhAgKCpLtv3TpkqJ2CSFEZGSkrOzy5csVlyUiIv3lvbc4dOjQEjlucHCwaNKkiawfqvqytLQUn332mUhMTNRZl6Z7hQcOHBCNGjVSW7+pqamYMGGCSE5O1livvn3c3L+DmurI7atGRESIDh06qO13lMT1KoynT5+KcePGCWtra43XoUGDBiI4OFhrPar9aSUvpX2cvJ49eyarZ8CAAQWqR6miuj658vYjlcr7e0VV3v6jklfevq6mPui5c+dkfeS8fduAgAARFxen+Dzo9ceVooiIiIiIiIiIiIiIiKjQ8s50r7pqVFGbNm0aZs2apXEWceDVSgHr169HcHAw1qxZo/essq+rzMxMDBgwAFu3btWYJy4uDqNHj8bNmzfx008/FdmxVWdmB17N/u7t7a0xf0hIiLTt6+sLJycn1KpVC9evX0d0dDRu374Nd3d3tWWvXr2Kx48fazw2APTp00daGUGb7OxsbN26Fbt27cLSpUt1rlBVEDt27MCQIUPw4sULrfnOnz+PTp06Yfz48Zg/f77WvGvXroW/v7+02pY2ycnJCA4ORrdu3fDOO+/o1XYiIqLXwcyZMzFjxgwpbW5ujs2bN6Nr164Fqs/S0hJeXl5o3LgxnJ2dYWlpicTERERERGDbtm149uwZAODatWvo3r07wsPDFa+4k5GRgX79+uHatWswMDBAu3bt0K5dO1SoUAGJiYk4deoUTE1NZWXmzJmD//3vf7J9bdq0Qfv27VGxYkWkpaXh3Llz2LRpE16+fAkhBCZMmAAzMzOMHTtWUbseP36MHj16ICYmBpaWlujVqxeaNm0KKysrREdHY8OGDbh69SoA4MWLFxg8eDAuX75c6JWGcvn6+mL58uVSOjQ0FP7+/mrzqq4k5ePjAwBo0qQJypYti+TkZJw+fRopKSka26baz7SxsYGnp2e+PHv27EHv3r1lK0o1aNAAfn5+qFy5MhITExESEoJ9+/ZJ/a2ff/4ZWVlZWLBggdZzLc66169fj3Hjxsl+67Rq1QrdunWDk5MTnjx5gj179uDIkSO4fPkyhgwZIltRQ6mcnBwMGTIEkZGRAF6t1tWlSxc4Ojri0aNH2LlzJ06ePCnl/fTTT2Fvb4+BAwfqfazisGDBAvz2228AgGrVqsHPzw/Vq1eHgYEBbt26hYcPHwIA+vfvj/Hjx0uruf355586P4Ncf/75p7RtaWn52pw7EdF/kRBCdp/EwMBA1jcsDi9fvsTAgQOxa9cunfl+/fVXbNq0Cf/++y/q1Kmj13Hmzp2LKVOmaPx7nZGRgfnz5+Ps2bPYu3cvzM3N9aq/oP766y+MHDlS7cqi6pTU9VLi9OnT6Natm9aVYQEgIiICfn5+GDhwIFavXl0sqz8pVZL3zt/E61OUdH23c3JyEBQUhNOnTyM0NBSOjo4l3EIqDgyKIiIiIiIiIiIiIiIiokLL+/Bw37598PPzK/LjTJ06Fd9//72UNjQ0xLvvvov27dvDzs4OMTEx2L59O8LDwwG8esA8YMAAbNy4Ee+9916Rt0cbOzs7Kejn9u3b0v7y5cvDyspKbRldAx8++eQTKSCqdevW6NixI1xcXPDy5UuEhoZi27Zt0gDKefPmoV27dujSpUtRnA6aNm0qDVQFXg1mnT59utq8SUlJOH/+PADAysoKjRo1AvBq0Ov169el8pqColQHugLqg6JyGRgYwNPTE82bN0eNGjVga2uLtLQ0REVFYe/evbh06RKAV4NMPvjgA1SpUgXt27fX48y1W7duHYYNGyYLXmrUqBE6d+4MV1dXZGdn4/Lly9i4caM0GOGXX36BsbEx5s6dq7bOyMhIBAQESHUaGhqiffv2aN26NVxcXGBsbIznz5/j9u3bCA8Px6lTpxQFTxEREb1uhBD4/PPPsXDhQmlfuXLlsHPnTrRu3Vrv+ho2bIgvvvgCvXr10tivevnyJcaPHy8FPFy7dg1z5szBzJkzFR3jxIkTAIAKFSpgy5YtaNWqldb8ISEh+Oqrr6R0lSpVsH79erRs2TJf3lmzZqFv377SMSZNmoQOHTqgZs2aOtu1fPly5OTkoEOHDlizZg0qVKgge3/q1KkYPXo0Vq5cCQCIiopCUFCQ4qArXdQF0CsJivL19QUAGBsbo1WrVvj333+RkZGB48ePo0OHDvnKvnjxAufOnZPSPj4+MDQ0lOWJj4/H8OHDpaAlQ0ND/PbbbxgzZows36RJk3Dy5En06dMHsbGxAIBff/0VnTp10tiHLs66nzx5go8//ljqz5uZmWHVqlUYMGCALN+UKVPwzz//YMiQITh06FC+81fi2LFjyMnJgbm5OdauXYvevXvL3p86dSrWrl2L4cOHIzMzE0IIfPzxx2jfvv1rMXD0119/BfAqoPKrr76CsbH6YZDm5uZ4//33sWjRIgCvBsnOmTMHZmZmWuvPyMjAmjVrpPSAAQM0/oYjIqLCu3jxIu7fvy+l3333XVSrVq3YjpecnIy2bdvi7Nmz0j4rKyv06NEDTZo0Qbly5fDkyRPs3bsXhw8fBgA8fPgQPj4+CA8PR5UqVRQdZ926dZg6dSoAoEaNGvDz84O7uzuEELhw4QL++usv6T5bWFgYZsyYgTlz5uSrJ/f+WUJCghToa2xsDFdXV7XHrVixotZ2nT59GitWrEBGRgZsbW3h5+cHT09PWFhYICYmJt9kTCV1vZQ4f/482rdvj5cvX0r7qlevjr59+6JatWp4+fIlTp06heDgYCkoZv369UhLS1M7yZSbm5vUj3jy5Ik04VGZMmXUXseCBq3Z2dnB0NBQCo47evSo1kkACqqor09xMjExkb7bSq49ADg5OWmt8/Dhw5g9ezYyMzNRqVIl9O7dGx4eHjAxMcGVK1fw119/Sfdnr1y5gk8++QQbNmwowrOiUlNqa1QRERERERERERERERHRf8alS5cEAOllbGwsVq9eXaTHCA0NFQYGBtIxHB0dRVhYmNq8f/75pzA2Npby2traipiYGI11q7Y9MDBQUXtCQkJk5aKiooq0fiGEmD59ulTO0NBQOpf9+/erzb9nzx5hamoqlWnatKniYynRqVMnqW4zMzORmpqqNt/OnTulfF26dJH2r127Vto/ZMgQjcfp16+flM/AwEA8ffo0Xx5PT08xbdo0cffuXa1t3rhxo7CyspLqq1q1qsjOztaYPyoqSvZ5hYSEaMx75coVYWFhIeW1s7MT27dvV5s3MTFR9OrVS3ZeoaGhavP6+/tL+RwcHMSZM2e0nmNcXJyYO3euxmMTERG9DgIDA2V/Y//44w8xdOhQ2b7y5cuL8+fPF6h+Tf0STfr37y8d18nJSWRkZGjMq/q3GYAwMTEREREROo+RnZ0t3N3dZecXHR2ttUxSUpKoWrWqVOb999/XmNfV1VXWrkaNGon09HSN+dPS0oSbm5uU38vLS+c56MPDw0Oq29XVVW2enJwc4ejoKOV79OiR9N6sWbOk/VOnTlVbfteuXbJzXrBgQb48kyZNkuX55ZdftLb7/Pnzsj507dq1NeYtzro///xzWd1BQUFa6/77779l+QEIf39/jfnzfo8BiPXr12s9xh9//CHLP378eLX59OlDq8r7/4ImeX97ARBffvmlomNcvnxZr3MW4tVvCNUyJ0+eVHQsIiIqmF9//VX2/+6cOXOK9XgBAQGy4w0cOFDEx8erzbt9+3ZRtmxZKW/79u011pv375WhoaEwNDQU8+bNE1lZWfnyR0VFyfpzZmZmIiEhQWP9qvcJNfW1NMn7dxSA8PPzU3vPLa/iul76SktLE3Xq1JG15euvvxaZmZn58l69elXWNwUglixZorV+1b6Sj49PkbU7V+PGjWXt6du3r0hKSiqy+ovz+hT02qh+v6dPn17k9eftg+beP584caJIS0vLlz8+Pl40bNhQViYyMlLx8ej1pf80EURERERERERERERERER51KtXDy1atJDSWVlZGDZsGBo1aoSff/4ZFy5cKPRKNpMmTZJmTTc2NsauXbvQpk0btXk/+OADafZwAEhMTMSsWbMKdfzSlpOTA2NjY+zevRvvvvuu2jydO3fGxIkTpfSZM2dw8+bNImuD6goA6enpOHnypNp8qis9+fj4qN1WXSEgr7CwMGm7QYMGsLOzy5fnxIkTmDlzpsZZcXP169cP69evl9JRUVHYuXOn1jJKffzxx0hJSQEAWFhY4NChQ+jRo4favDY2Nti8eTOaN28OABBC4Ouvv1ab99ChQ9L2119/jSZNmmhth4ODAyZPnqzx2ERERK+jqVOnylZicXV1xdGjR+Hp6Vmg+sqUKaNX/h9//FHafvz4sWz1IV3GjBmD+vXr68wXHBwsWzF0wYIFqFSpktYyVlZWshUCNm3ahKdPnypq12+//QZTU1ON75uZmSEgIEBKh4eHSyseFQXVvuK9e/cQFRWVL09kZCTi4uIAAB4eHrLZ3lX7inlXDs2Vtw/Zrl07WTotLU1aDQsAPD09MW7cOK3tzpvn6tWrao9fnHWnp6dj9erVUrply5YaV9rKNXDgQK0rqurSrl27fKtQ5TVy5Eg0a9ZMSq9evVpaVaA0OTk5YcaMGYry1q1bV7ai24oVK3SWyV1JDnj1Wze3D09ERMXj9OnTsrTq356iFhYWhqCgICk9ZMgQ/P3337C3t1ebv0ePHvj777+l9MGDB3Hw4EFFx8rJycHcuXMxceJEGBkZ5Xvfzc0Ny5cvl9Lp6enYsmWLwjMpnNatW2PTpk1q77mpKsnrpcuff/6JK1euSOnPPvsM3333ndoVIz08PLB//35ZO6dOnYrU1NQiaUtBjBw5UpbevHkz3NzcMG7cOOzbtw/Pnz8vVP1v+vUpCjk5Ofjkk08wb948tSuD2tvbY926dbKVVtetW1eSTaRiwqAoIiIiIiIiIiIiIiIiKhJLlixB2bJlZfvOnz+PSZMmoWHDhrC2toaXlxc+//xzbNq0CY8fP1Zc95kzZ3D27FkpPXbsWDRt2lRrmTFjxsjyrFmzBi9evFB8zNfRiBEjZMFn6owePVqWzjuwpDDyDrpUMljV19dX2q5YsSLc3d0BADExMWoDtq5cuSL7buQd6JpLn4HPXbt2hbe3t5Tes2eP4rKanD9/Xnb+X3/9NRo0aKC1jLGxMRYtWiSljx49isuXL+fL9+jRI2m7Zs2ahW4rERHR6+jJkyfStqmpKQ4ePIgaNWqU2PGrVq2KatWqSekzZ84oLjt8+HBF+VQH2Lm4uOgMQMnVu3dvWFlZAXg1OFY1YFyTmjVromXLljrzqfYl09LScPfuXUVtUiJvX1FdELzqPtUgKODVAGhzc3MArz6P5ORkreUdHBxQr1492fvHjx9HQkKClP7oo49kgx41GTt2LAwMDKS0uiD64qz72LFjsrpHjRqls14A+PDDDxXlUyfv7wZNVNvy9OlTHD9+vMDHLCoDBw7U6/eA6rkeOHBA6/f+/v37OHDggJRW+lkQEVHB5b1HWLVq1WI71rx586Rte3t7LFmyRGeZHj16oGvXrlJaSRngVeDJhAkTtObp2LEj3NzcpPSpU6cU1V1YCxcuVBssk1dJXi9dfv/9d2nb2dkZs2fP1pq/cuXKmDlzppROSEiQTZxU0j744APZfVLgVZsWLVqEzp07w9bWFrVq1cKQIUPw22+/ISIiQpogTIk3/foUBVtbW9nkF+p4eHjI7hOX1L85Kl4MiiIiIiIiIiIiIiIiIqIi4enpiYMHD2pcuSclJQXHjx/Hr7/+iv79+8PZ2Rnt27dXNAPqjh07ZOkxY8boLGNgYICxY8dK6ZcvX2pdnehNoGQArqurKypUqCClr169WmTHb9y4MaytraW0uuv5/PlzXLhwAQBgaWmJxo0by97XtVpU3n2Fmf1eVYcOHaRtfQY9a7J27Vpp29TUFB9//LGick2bNkXt2rWl9L///psvj4WFhbT9Ogw6JSIiKm4ZGRn4+OOPkZaWVqLHdXZ2lrZjYmIUlbG0tFS0ShTwKgA6V+fOnRUF0ACvAqkbNWokpZUM1FMSEAW8ClJX9ezZM0XllPD19ZUF/6gLoNcUPA+86lPlBm1lZmbi2LFjsvdfvHghW9Er7/GA/NeqS5cuitpetWpV1KlTR2M9xV133okMOnXqpKjuzp07K8qnTseOHQt0jKLoSxeW6spPSvTr1w+2trYAXq3YGhgYqDHvypUrkZOTA+DV6mrvv/9+wRtKRESK5F0V08bGpliO8/z5c+zatUtKjxw5UgpE10V1BceDBw8qClbx9/fP11dRRzVovSjv42nSoEEDNGzYUGe+kr5e2ty5c0e2CpK/v3++ybnUCQgIkOUrqtXjC8LExATbtm1Dv3791L4vhMCNGzewbt06fPrpp/D09ES1atUwc+ZMnX32/8L1KQr9+/dXdN4l/W+Oih+DooiIiIiIiIiIiIiIiKjING/eHFevXsX8+fN1rnAjhMChQ4fQt29ftGnTRutAVNWBg1WrVoWHh4ei9nTv3l1jPW8aExOTfAFGmqgOdi3Kga5GRkZo06aNlD558iRSU1NleY4cOYLs7GwAgJeXV75ZZ1WDonQNlM17vMIoyKBnbY4cOSJtt27dWhYspkuzZs2kbXXfSdVB0HPmzMGyZcuQkZFRwJYSERG9nsaNGwc7OzspvW/fPvTs2TNf36IgTp06hS+++AIdOnRAlSpVYG1tDUNDQxgYGMheqkE3SvtMVatWVRTc9OjRI9mqB3Xr1tXrHJycnKTtBw8e6MyvGhSvjaWlpSytbjWmgnJ0dJSdZ95gdyEEDh8+LKXzrhSVd1/e8qr9TEB98PyNGzekbRsbG1SpUkVx+1WD3VTrKYm6r127Jm3b2trCxcVFUb02NjaoVKmS4nbkqly5suIB55UqVZLlVW1raalevbpe+c3NzWXBTYGBgVLgk6qcnBxZwNR7770n+3+KiIiKR96V3fP2V4rK8ePHZf//d+vWTXFZ1Xs5z549w/Xr13WW0bXae67iuo+nidLg4pK+XtoUNDi9bNmyskD80r43bG1tjY0bN+LgwYPo0qWLztW67t69ixkzZsDd3R3//POPxnz/letTWK/rvzkqfgyKIiIiIiIiIiIiIiIioiJlbm6O8ePH4/r167hw4QLmz5+Pvn37olq1ahpnRz169CiaN2+Ohw8fqn1fdeBggwYNFLfFwcFBFgyjbgDim8LOzg4mJiaK8qoOHinKga6AfPBpRkYGTpw4IXtfNdBJ34GuAGQDZRs1aoRy5cppbU9sbCx+/fVX9OvXD7Vr14a9vT1MTU3zDXoeNWqUVKYoHnZHRERI20U9yPmjjz6StjMzM/HRRx/B2dkZ/v7+WLVqFW7fvl2AFhMREb1eGjZsiIMHD8Le3l7a9++//6JHjx4FDoy6dOkSvLy80KJFC/z00084ePAgoqOj8eLFC52z0ytdpUppIHTeFQ8mTpyYr3+i7bVx40apbGJios7jlSlTRlG78irsrP15qfYVo6OjZf2Wy5cvIz4+HgBQs2ZNWT89l7YAeiUriqpeq/Lly+vVdtU+mrr+4utat6Ojo175C3sMJd/H4qbPhAS5Ro8eLW1HR0dj//79+fLs378f9+/fl9IjR44sWAOJiEgveVcfevnyZbEcR/VeDqDf/RzVv+VA8QWtF/V9PHWUBheX9PXSJu89XX3uD6sGp8fExCAlJaVQbSkK7dq1w+7du/Hw4UOsW7cOH330EZo0aaKxT5+QkIC+ffsiKChI7fv/tetTUK/rvzkqfgyKIiIiIiIiIiIiIiIiomLToEEDjB8/Hps2bcLt27eRmJiIXbt2YdSoUfkGPMTExMDf319tPUU1APF1GMBXUK/jQFdA+2BV1ZlGc7m6usLV1RXAq4Am1Zlir1y5gidPnmg8lqqUlBRMmDABVapUweeff47Nmzfj2rVrSEhIQGZmptZzUDroWZPk5GSkp6dL6UWLFuk1yHnu3LlSWXXfyf79+2Ps2LGyfQkJCVi9ejUCAgJQvXp1VK5cGSNGjMC///5b5J8xERFRSfH09MShQ4fg4OAg7Tt48CC6d++u92C8EydOwMvLC8ePH8/3XpkyZVChQgW4ubnB3d1deqn2r5T+PdU1m3uuopxx/E0amJi3/6baN1TdVhc8D7ya3d3MzAwAcPbsWdmgaNV+Z4UKFVC7du185VXzW1hY6NX2smXLStuZmZmy/l5x1606GNPc3LzAdStVmGMU10B1fSj9d6iqbt26spUx/vzzz3x5VPdVr15d7e8ZIiIqeqpB8kDxrdySN2jd3t5e8b2cvH/7iytovSTu8RQ0yL+4r5c2quVNTU11TqKkKm+A1ut0f9jR0RGDBg3CkiVLcObMGbx8+RJnz57F999/Dw8PD1leIQQ++ugjtZMl/Vevj74Kev+c3nwMiiIiIiIiIiIiIiIiIqISU65cOXTt2hXLly9HVFQU+vTpI3v/wIEDOHnyZL5yRTUA8XUYwPem8/T0hI2NjZRWHdz67NkzXLhwAcCr696kSRO1dWhaLSpvgJWmoKjU1FR06dIFv/zyC7KysmTvGRoawsHBAZUqVZINetY3mE6bkhjkvHjxYqxfv17tYF/g1Qy7gYGB6NixIxo1aqT23w0REdGboH79+jh06JBsJZpDhw6hW7duimftTktLw9ChQ/HixQtp36BBg7Bz5048fvwYqampiI2NRVRUFG7duiW9mjVrVuTnkytvn9XFxUXWN9Hn5eLiUmztLGo+Pj6y1WFV+3eq25qCTcqUKSN9LllZWTh69CgAICkpCefPn5fyaeonqs76rm8wmer3zcTERArOKom6VX+z6LtSWkFmty/MMVSvw5tGdbWo7du3Iy4uTkrHxcVh+/btUvqDDz7QuNIxEREVrbxBGXfv3i2W47ytQet5vYlB/kV1bzhvXa8bIyMjNG7cGFOmTEFkZCSWLVsm6zemp6fjp59+ylfubbk+RJroP2UCERERERERERERERERURGwt7fHxo0b4e3tLZvRf9euXWjRooUsr6WlJZ4/fw6gcAMQ3+QBfK8LQ0NDeHt7SwMGT58+jZSUFFhYWCAsLAw5OTkAgFatWsHExERtHT4+Pli9ejWAV4NjcwcnqgZImZiYoE2bNmrLz5o1C2FhYVK6bt26+PTTT+Hr64tq1aqpPW5gYCBGjBih/wmrkXdwgaOjo+JZdvOqVKmSxvcGDBiAAQMG4MyZM9i/fz/CwsJw8uRJJCUlyfJduHAB3t7e2LlzJzp27FigdhAREZWmd955ByEhIWjXrp20amRoaCi6du2K3bt361wJZ9u2bbIZ05cvX45Ro0bpPG5xrUIAQLb6FQDMmzcPgwYNKrbjvS7s7OxQv359REREAPj//p0QQtZ/07RSVO57R44ckcp37twZR44cQXZ2tpRHU1CUra2ttK26AqkSqvlVJwF43etWDewpSHv0PYZqW3MVNHiopAeU9+/fH59//jkSExORmZmJ1atXY+LEiQCA1atXSyvOGhsbIyAgoETbRkT0NmvWrBnWrl0rpU+fPq21r1BQqvdzjIyM4ObmVuC6rKysiqBFr7fX6XoVVXB63rpeZ4aGhvjwww+Rk5ODMWPGSPt37dqVL+/beH2IVDEoioiIiIiIiIiIiIiIiEqNkZERJkyYIAuKunbtWr58tra2UlBUYQYgqhvAV1Bv8oywhdW2bVspKCojIwPHjx9Hhw4dZEFNuga65jp8+LC0rTpQtmnTpmoHQGdmZuK3336T0u3atcPu3bvzzbafV1EOeraxsYGRkZE0MHf8+PGYMmVKkdWfV9OmTdG0aVNMnToV2dnZOHPmDIKDgxEYGCh9vzMzMzFixAjcvn1b57UgIiJ6HdWtW1cKjHr8+DGAV32DLl26YPfu3VoH5x08eFDarlWrlqKAqJycnGJbhQB4tTKUtbW1FMwcGRlZbMd63bRt21YKioqJicHNmzeRmpqKp0+fAgCqV6+OihUraizv4+ODWbNmAfj/1aVU+5m5x1CnZs2a0vazZ89w//59VKlSRVG7L168qLaekqi7Vq1a0nZiYiIePnyoaIWwZ8+e4cGDB4raoCo6OhrPnj1TG6CVV0xMjKwvrdrWXHknDVD6Wyn333pJKVOmDIYOHYqFCxcCAFasWCEFRa1YsULK1717d1SoUKFE20ZE9DbLew/p4MGDmDx5cpEfRzVo3cTEBDdv3uSqgFq8TtdL9Z5uRkYGnj9/jnLlyikqm/declHeHy4JI0eOxJQpU6T+2IMHD5CcnCy7b1rc1+dNCYCnt5dhaTeAiIiIiIiIiIiIiIiI3m5169aVpXODn1SpDhzMHWCpxNOnT/Hw4UO19ahSHcT3ug7ge53kHYSqbrCqr6+vxvLu7u7SQNhHjx7h6tWriIyMlD2E1zTQ9cyZM7KVkmbPnq0oCOjOnTs68yhlYGAgGwxakoOcjYyM0KJFC/z444+4ffs2vL29pfdiYmLyDRgmIiJ6k9SpUwchISGyYIQjR46gS5cuePnypcZyMTEx0naDBg0UHevs2bP5Vl8sSkZGRrJVL3fs2FFsx3rd5O3HhYaGSv1FQHvwPCBfcTQ8PBwvXryQ9XEqVaqE6tWrqy2bd8XZPXv2KGrz3bt3ZX26vPUUd93NmzeXpffv36+o7n379inKp47SY+zdu1eWbtq0ab485cqVkw2WVf03qc3JkycV5StKH374obR99epVHD9+HMePH8fVq1el/UoCK4mIqOi88847skDjf//9F1FRUUV+HA8PD2k7LS1NttIo5fc6Xa+893T1uT+sGpxesWLFfMHcrztjY+N8Qel5758X9/UpyL3zjIwMJCYmKm4HUWEwKIqIiIiIiIiIiIiIiIhKVVpamixtZ2eXL4/qwMGoqChcv35dUd07d+7UWI8q1RnSi2MAn7GxsbSdk5OjuNzrqn79+rC3t5fSoaGhePbsmfTA3dzcXO1gSVWqg2FDQ0MVz/6f9/NROvBZdQWJoqDavr179yIrK6tI61fC0tISv/76q2zflStXSrwdRERERal27doIDQ2Fs7OztO/o0aPo1KkTXrx4obaMEELaztu31GTBggWFaqcSAwcOlLYvXryoOIjmTeft7Q1Dw/8flhYSEqI4eB54NeiySZMmAIDs7Gzs2rUL58+fl97X1E8EgJYtW8r6qcuWLZN9PzRZsmSJLF/37t1LtG4vLy/Z76A//vhDZ7365CtM2T///FPatre3h5eXV748pqamqFq1qpQ+deqUznqjo6Nx6NAhRW0oSnXr1pWdw4oVK2TnWKlSJXTq1KnE20VE9DYzNDTEhAkTpHROTg6+/fbbIj+Or6+vLIj3TQtazw0aB0rm/uLrdL0KGpyekpIi64dqujf8utN1/7y4r09B7p2Hh4crvl9a0t9t+u9hUBQRERERERERERERERGVqmPHjsnS6mZ979Gjhyy9dOlSnfUKIbBkyRIpbWVlpXFWetWZT5UM4EtOTsamTZt05stlaWkpbatbCetNY2BgILuWZ86cwe7du6WH1q1atYKpqanWOlTL5x0oa2ZmhlatWqktl3fgqZKBz/v375fN/F4UVAc5P336tFADUgsj70yxmZmZpdIOIiKiolSrVi2EhobCxcVF2nf8+HF06tRJ7epOqisLhIWF6VwBKjg4GH///XfRNViDgQMHolq1alJ61KhRiI6O1qsOpUFerxMbGxs0bNhQSoeGhiIsLExK61opKm+e2bNnIzs7W0q3a9dOY7kyZcpgxIgRUvr8+fNYvHix1mNdvHhRFmhep04dtYFbxVm3mZkZhg0bJqWPHz+Ov/76S2vdmzZtKlTg/4EDB7B582ateQIDA2WTQQwbNkzjKq2qq11t2bJF68oAQgiMHTu2VCYWAOSrRW3YsAEbN26U0iNGjICRkVFpNIuI6K02atQolC9fXkoHBQUhODi4wPXt3bs338pGjo6Osn7EggULkJ6eXuBjlLSSvr/4Ol2vqlWrom7dulJ69erVilYsWrVqlWzFWXXB6a+7xMRE2SRIFStWRJkyZWR5ivv6qN47f/jwIR48eKCz7sDAQJ15cv3X7p1TyWNQFBERERERERERERERERXatm3bMH/+fKSmpupV7unTp/jxxx9l+9Q9fG3SpIls5aHFixfLZotXZ/ny5bIAp/fffx9WVlZq86oO4AsNDcWtW7e01v3ll19qHeSXl5ubm7R9+fJlxeVeZ6oz9GdmZuKHH36Q0voOdD18+DAOHz4spVu0aAFzc3O15VQHPQP5VwPLKzExER999JHO9uirdevWaNOmjZT+8ssvpZWylMrKypIN8AVezdD65MkTxXXkPabqd42IiOhNVrNmTRw+fBgVK1aU9p04cQIdO3bMN1BOdVWXZ8+eYdiwYWoHAQohsGLFCgwYMAAAZKsZFQdjY2P88ccfUoBFTEwMmjdvjh07duhcYSgyMhJTpkyBu7t7sbaxuKj2FWNjY5GQkAAAqFatGipXrqyzvGpfMW//WdtKUQDwxRdfwMnJSUp//vnnWL58udq8p06dQpcuXWQDfH/++edSqXvKlCmwtbWV0iNHjtQ4EUNwcDD8/f0BFOx7nFvG398f27ZtU5vn77//lvWj7ezsMGXKFI11Dh48WNp+9uwZAgIC1Ab1JSUlYejQodi5c6ds9YmS1L9/f+laJycnIzk5GcCr66Ia+EZERCXHwsICa9askf1dGzhwILZs2aJXPRkZGZgxYwa6deumdpXRr776Stq+f/8+Ro8erWjlR1WlFbSues8nKSlJ72D7gnidrtfYsWOl7YcPH2LatGla8z948ECWx87OTjbJUUnKzs7GsGHDcPPmTb3LfvXVV7JJkDQFLhXn9VG9dw7IVxJV5+TJk3oFRal+t2/evPlGBSvS64FBUURERERERERERERERFRocXFxmDhxItzc3PDll18qCvw5ceIEWrduLZtZsm3btmjRooXa/PPmzZMGRmRmZqJr1644fvy42rxBQUH45JNPpLSdnR2++eYbjW1RHcCXnZ2NIUOGqA16Sk9Px+TJk7F48WK9BvCpntOGDRtw6NAhxWVfV3kHo6p+5upmv8+rVq1a0oDSJ0+eIC4uTmPdqpo0aQI7OzspPXHiRFy4cEFt3sjISHh7eyMqKqpYBj0vWbJEmsn0xYsX8Pb2RlBQUL5Ap7yioqLwww8/wM3NTXbewKtr4ebmhrFjx+L06dNa67l//z5GjRolpc3NzWWDwomIiN501atXx+HDh2VBNKdOncoXGNWzZ0/UqVNHSm/btg01atTAxIkT8eeff2L58uWYMmUK6tati5EjRyIjIwOdO3eGl5dXsZ9Du3btsGDBAqnvGBsbi549e8LDwwMff/wxFi5ciKCgICxZsgSzZs3CoEGDUK1aNdSrVw8//vgjnj59WuxtLA6a+nNKgucBwMvLS+1qPVWrVoWrq6vWsg4ODggMDISxsTGAV/370aNHo1GjRvj222+xYsUK/Pzzz+jRowe8vLzw8OFDqexnn32Gzp07l0rd5cuXx++//y59V9LT09G/f3+0bt0aP/zwA1auXIkff/wRvr6+6N27N1JTU9GuXbsCfY+9vLzQtm1bpKSkwM/PD76+vpgzZw5WrlyJH374AV5eXhg8eDAyMjIAvFopdvHixXB0dNRYZ9euXdGsWTMpvX37dnh4eGDq1KlYuXIlFi9ejNGjR6NatWpYu3YtrKysMGnSJL3bXhTKlCmDoUOH5tv/7rvv6vx+ERFR8enYsSNmzJghpXP/Fg4bNgxRUVFayyYnJ2PlypWoWbMmZs6cKa1mnle7du0wfPhwKb1q1Sr06NEDd+/e1Vp/eno6du/eDT8/P0ycOFHxORWlZs2aye5vffHFF8W+qs7rdL0++OAD2WpIP//8M2bOnKn2Ptz169fRqVMnxMfHS/u+//77fCsslRQhBNasWYPatWvjvffew7Zt23Su9v706VN88MEHWLp0qbTP1NQUEyZMUJu/OK9PzZo10bhxYyk9Z84cjSuW/vvvv+jatSuysrIU3z9XvXeempqKr776Su/J1+jtZlzaDSAiIiIiIiIiIiIiIqL/jidPnmDu3LmYO3cuXF1d0bx5c9StWxcODg4oW7YsXrx4gVu3buHw4cP5AlkqVKigcZZ1APD29saUKVMwe/ZsAMCjR4/Qpk0bdOrUCe3bt4etrS1iYmKwfft2nD17VipnaGiI5cuXw9nZWWPd9erVw3vvvSfNPnv69GnUqlULQ4cORe3atZGZmYnr169jy5YtePDgAYyNjfHVV1/h22+/VXRdhg8fjmXLlkEIgeTkZLRv3x729vZwdnaWDfb8888/0aRJE0V1lra6deuifPny+VY1KlOmjGwwpDY+Pj7YuHFjvv3agqKMjY0xefJkaZb6uLg4NGvWDH5+fmjdujWsrKwQFxeHsLAw7N27F9nZ2bC2tsaYMWMwZ84cPc5Qt7p162LNmjUYMGAAMjIykJSUhOHDh+Obb75Bp06dUK9ePdjY2CA9PR0JCQm4du0azp49iytXrmitNzU1FUuWLMGSJUtQpUoVtGrVCu+88w4cHBxgamqKuLg4nDlzBjt27JDNtjtjxgyUK1euSM+RiIiotLm7uyM0NBRt27bF/fv3Abzqq3Xo0AH//vsvbGxsYGRkhC1btsDb21sKOH748CHmz5+vts6WLVti3bp16N27d4mcwyeffIJKlSrB398fSUlJAIAbN27gxo0bOsuqCwx6E7Rp0wbGxsbIysqS7VcSPA8AVlZWaNSoEc6cOSPbr2uVqFxdunTB1q1bMWDAAGnVsPPnz2tdbXbChAmYN29eqdY9cOBAxMXF4fPPP5cGcx87dgzHjh3Ll7du3bpYu3ZtgVY8MDQ0xLp169ChQwdERkbmW7k1b95ff/1V53EMDQ2xevVq+Pr64tGjRwCAe/fu4fvvv8+X19raGps2bZIFjZW0Dz/8EAsXLpTtGzlyZCm1hoiIcn3zzTewtrbGxIkTkZ2djZycHKxZswZ//fUXPD094evrCxcXF9jb2yMpKQmPHz/GuXPnEBoaqnh1md9//x23bt3CkSNHAAC7du3C3r170bZtW7Rq1QouLi4wMzPD8+fPERMTg4iICJw4cUJaeWr06NHFdv7aODs7o3Pnzti9ezcAYP369di8eTPc3NxQtmxZKV+TJk10ruSjj9flepmZmWHNmjXw9vbGy5cvAby6F7Z27Vr069cPVatWRXJyMk6ePIng4GDZPTM/P79S+9xUZWdn459//sE///wDKysrNG3aFI0bN4azszNsbW2RkZGB2NhYnD17FgcOHMi3ytbPP/+MmjVrqq27uK/PjBkz0KNHDwCvVv/q2LGjFFxftmxZxMbGYt++fdL35IMPPsCBAwdw7949ndcl9xlCZGQkAGD+/PlYvHgx3NzcZIFaPXv2VHw/nt4ygoiIiIiIiIiIiIiIiKiQ1q5dKwAU+NWwYUNx/fp1Rcf6+uuvFddrZmYmNm7cqKjeR48eCQ8PD511mpqailWrVomQkBDZ/qioKK31f/fdd8LAwEBr3SEhIbIy06dPl95zdXVVdB5CCOHj4yOV8/f3V1xOX/379893Dm3btlVcfvHixfnKm5ubi7S0NK3lsrKyRK9evRR9B8qVKyf27t0rAgMDZfs1iYqK0vqZqHP06FFRoUKFAn33Hz9+rPX4Sl+TJ09WdM2JiIhKS96/xYGBgXqVv3PnjnB1dZXV0bhxY5GQkCDliY6OFr1799bY53J2dhbfffedyMzMFEIo7zP5+/tL+Xx8fApw9q/Ex8eLKVOm6Ow3mJiYCC8vLzFnzhzx4MEDjfWpXo/p06crakNB+joF1bx583zndvfuXcXlJ02alK/8mjVr9GrD/fv3xbBhw4S5ubnaa21gYCC8vLzE4cOH9T29Yq37yJEjwtPTU229lpaW4uOPPxbJyclCiMJ9j1++fCk+/vhjYWlpqfZYDRs2FEePHtWr7VFRUaJnz55q6zM0NBRdu3YVt2/fFkLk/39BE31/eynVpEkTqU5HR0eRkZFRJPUSEVHh/fvvv6JevXoFukfi7Owsli9fLrKysjTWn56eLj744IMC1T927Fi1dRb075U+9//u3bsnqlWrprV96vqrhemHC1E816ugTp06JRwcHBQff+DAgYr+xhdVn1+drKwsjX1GJS9ra2uxYsUKRccqrusjhBDjx49XVGfPnj1Fenq6Xr9Xzp07J8qXL6+13rx93YL+tlHaB6U3h4EQQoCIiIiIiIiIiIiIiIiokO7evYvg4GDs378fJ06cwLNnz7TmNzQ0hLe3NwICAjB06FAYGhoqPtaJEyfw1VdfISwsTJpBXZWZmRl69+6N77//HlWrVlVcb3x8PCZNmoQ1a9aorbd169b49ddf0ahRI2nFglxRUVFwc3PTWv/p06excuVKnDx5Evfu3cPLly9ls+eHhITIZs+fMWMGZs6cCQBwdXXF3bt3FZ2Hr6+vNNO7v78/goKCFJXT19KlSzFmzBjZvhkzZmD69OmKykdGRqJevXqyfe3bt8eBAwd0ls3JycHcuXPx008/ISEhId/7pqam6N69O+bPnw9XV1cEBQVh+PDh0vuaHpPevXtX9p3J+5lokpycjN9++w3Lli1DVFSUxnyGhoZo2LAhunXrhqFDh6J69eqy99PT07FmzRrs3LkTYWFhSExM1FpXu3bt8M0338Db21tnG4mIiN4WMTExOHLkCB48eICcnBw4OTnB3d0drVq10qvPWZwuX76MixcvIi4uDi9evEDZsmXh4OCAmjVrol69erLZ/qnwUlNTERYWhrt37+Lp06ewtLSEs7Mz2rRpgwoVKry2dV++fBlnzpzB48ePUa5cOVSuXBlt27Yt8u/Hy5cvERoaiujoaDx//hwVKlRA06ZNUbdu3QLXGRMTg9DQUDx8+BCGhoaoVKkSvLy8UKlSpSJsecGlpaXB2dlZ+t06adIk/PTTT6XbKCIikhFCYMOGDQgKCsKRI0ekFRrVMTExgbe3N4YNG4Z+/frB3Nxc0TFOnTqF2bNnY//+/VpXmrK3t0e7du0wYMAA9OjRA6ampvnyFOReIaD//b+XL18iKCgIu3btwqVLl5CQkIDU1FTpfR8fH4SGhsrKGBgYSNuBgYEICAjQ2S51ivJ6FUZCQgJmzpyJoKAgaSXWvOrXr48ZM2YoXh02ICAAq1atAqD+GhZWSkoK9u7di127diEsLAy3bt3SWcbNzQ2DBg3CuHHj9OpXFsf1ybVs2TJMmzYNT548yfeei4sLvvjiC4wbNw4GBgZwc3OTVoqaPn06ZsyYobXuuLg4rFixAvv378fVq1fx7Nkz2YpWee9zF/Q+rtL7xPTmYFAUERERERERERERERERFbmcnBzcvn0bN2/exP3795GUlISMjAxYWlqiXLlyqFmzJurXrw8rK6tCHScuLg5hYWGIjY1FUlIS7OzsUKVKFfj4+BRqoGB8fDxCQkIQHR2NrKwsVKpUCU2bNkWNGjUK1V4qeqmpqTh27BiuXr2KpKQk2Nvbw8XFBd7e3rCxsSmVNt26dQvh4eGIi4vD8+fPUaZMGdjZ2aFGjRqoV6+e4nYJIXDjxg1cv35d+ndkYGAAa2truLu7o0mTJnBwcCjekyEiIiIi+g9au3Yt3n//fSl97do11KpVqxRbRERE2mRkZOD06dN48OAB4uPj8fz5c1haWsLW1ha1atWCp6cnzMzMClx/amoqjh8/jnv37iE+Ph7Z2dmwsrJCpUqVULt2bdSsWVMWWPS2e12uV2ZmJo4dO4Zbt24hPj4eZcqUgZOTE1q2bKkoIK00xcfH49q1a7h9+zYSEhKQnJwMMzMz6TrWr18fVapUKdQxiuv6ZGVl4dixY4iMjMSzZ8/g6OiI6tWrw9vbG0ZGRoVqM1FBMCiKiIiIiIiIiIiIiIiIiIiIiIiIiN4aXl5eOH78OIBXK+2GhISUcouIiIiIiKggXo/1oImIiIiIiIiIiIiIiIiIiIiIiIiIitnBgwelgCgAGDt2bCm2hoiIiIiICoMrRRERERERERERERERERERERERERHRf97Zs2fRt29f3Lt3DwBQu3ZtXL58GYaGnF+eiIiIiOhNZFzaDSAiIiIiIiIiIiIiIiIiIiIiIiIiKmoPHz5E165dAQBxcXF4+PCh7P358+czIIqIiIiI6A3GoCgiIiIiIiIiIiIiIiIiIiIiIiIi+s/JyMhARESE2vemTp2Kzp07l3CLiIiIiIioKDEoioiIiIiIiIiIiIiIiIiIiIiIiIj+0wwMDGBra4smTZrgk08+QY8ePUq7SUREREREVEgGQghR2o0gIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIlLKsLQbQERERERERERERERERERERERERERERERERESkDwZFEREREREREREREREREREREREREREREREREdEbhUFRRERERERERERERERERERERERERERERERERPRGYVAUEREREREREREREREREREREREREREREREREb1RGBRFRERERERERERERERERERERERERERERERERG8UBkURERH9B4SGhsLAwEB63b17t7SbRKXk7t27su9CaGhoaTeJiIiIiIiIiIiIiIiISKecnBycO3cOW7ZswfLly/HDDz9g3rx5+OOPP7Bt27bX6hloUFCQ7JmcNqr5goKCSqaBRERERESvmYCAAKlf7OvrqzEfx0ISkb6MS7sBRET0egoKCsLw4cMLVUe5cuXw7NmzomkQ0WsoKChI+tHl6ekJPz+/Um1Paapbty6uXLkipdu3b48DBw6UeDv4mRAREREREREREREREb1Zdu7ciT///BOHDx/W+XzZxsYGnTp1Qt++fdGtWzeYm5uXTCOJiIiIqNTMnTsXX375pZQ2NDTEnTt34OrqWoqtKl4cA0VEpByDooiIiIgKKCgoCIcPHwYA+Pv7v7U/Pk+ePCkLiAKAQ4cOISoqClWrVi3RtvAzISIiIiIiIiIiIiIiejMcOXIE48ePR3h4uOIyz549w4YNG7BhwwY4OTnhiy++wJgxYxgcRURERPQfFhgYKEvn5OQgKCgI06dPL6UWFT+OgSIiUo5BUUREpEj58uVhZWWlVxlra+tiag0RvU5WrFiRb58QAoGBgfj2229LoUVERERERERERERERET0Olu8eDE+//xzZGVlyfbXrFkTbdu2RZUqVWBvbw8DAwM8evQIMTExOHToEG7duiXlffz4MSZOnIiaNWuie/fuJX0KRERERFQCjh07hmvXruXbHxgYiG+++QaGhoal0CoiInqdMCiKiIgUmTNnDgICAkq7GaSBr68vhBCl3Qx6CyUnJ2PDhg1SumrVqoiKigLwasaSGTNm8OYDERERERERERERERERSb777jtMmzZNShsYGKB///6YPn06ateurbXszZs3sXTpUixduhQpKSnF3VQiIiIiKmWqkzWrjku6d+8eDh48iHfffbe0mkbFhGMhiUhfHKFKRERERAW2ceNGvHjxAgBgZmaGdevWSe9FR0dj//79pdU0IiIiIiIiIiIiIiIies3s2bMHM2bMkNLm5ubYtGkT1q9frzMgCgBq1KiBn3/+GXfv3sUHH3xQjC0lIiIiotL24sULbNy4UUp/8cUXaN68uZRWDZgiIqK3F1eKIiKit0ZCQgLCwsLw4MEDpKSkwMXFBa1bt4abm1uh6k1PT8exY8dw9+5dPHnyBObm5nB2doa3tzcqVKhQJG1PTEzEkSNH8PDhQyQkJMDe3h5Dhw6FhYVFkdSfKyoqCqdPn8aDBw+QnZ0Nd3d3dOjQAeXKldNYJi4uDmFhYYiKikJ2djZcXFzQrl07VKxYsVBtiYyMREREBJ48eYL09HQ4OTmhXr16aNy4MQwMDApVNwDk5OTg6NGjuHnzJp48eQIbGxvUrl0brVu3hrFxyXaR4uLicPHiRdy+fRuJiYkQQsDOzg6urq5o1aoVrKysSrQ9+lC9udCzZ0+0aNECzZo1w+nTp6X3O3fuXGTHO3v2LK5fv47Y2FgIIdC6dWu0bNmyyOonIiIiIiIiIiIiIiKi4vHy5UsMGzYMOTk50r5NmzahW7duetfl6OiIP//8E506dYKNjY2iMnfu3EFkZCTu3buHpKQkmJqaws7ODnXq1EHjxo1hYmKidzuKmxAC586dw5UrV/DkyRMIIeDk5IRGjRqhbt26RXKMjIwMHDlyBPfu3cPjx49hYWGBXr16Ffo5OhEREVFhbdiwAcnJyQBeTdY8YMAACCFw6tQpAEBwcDASEhJgZ2dXms3MJyMjAxcuXMDly5eRkJCAtLQ0mJubw8HBAVWrVoWnpyesra1LpW2RkZG4dOkSYmNjkZ6ejkaNGqFjx45q82ZnZyMyMhJXr15FbGwskpOTYWlpCQcHBzRu3BgeHh4l3HrtkpOTcfHiRdy4cQPx8fFIS0uDjY0NnJ2d0bJlSzg7O5d2E4mouAgiIiI1AgMDBQDpFRgYWCT1Hjp0SBgaGkr1du7cWeTk5OgsFxkZKczNzaVynp6eIi0tLV8+Hx8fKY+/v78QQoi4uDgxePBgYWZmJjun3Jevr6+IjIzU+1zu3LkjhgwZIiwsLNTWa2BgIHx8fMTp06cV1efq6iqVnT59uhBCiLt374o+ffoIU1PTfPVHRUVJZUNCQjS+l5e6zzUyMlK0a9dOGBgY5DuOubm5mD59usjOzpbVExsbKwYPHiyMjY3VnvvQoUNFQkKCPpdUpKWliXnz5okqVaqovaYARMWKFcVvv/0msrKydNY3ffp0qZyrq6u0f9GiRaJSpUpq63d0dBTLli3TWGfea63klft5qgoPDxeTJ08WderU0VrWyMhI9O7dW1y4cEHRNYyKipKVDwkJUVSuIK5duyY71s6dO4UQQixevFjaZ2pqKuLi4hTXmff/nlxLliwR1apVy3d9/P39i+wzISIiIiIiIiIiIiIiouLz888/y57XfPTRR8V6vKysLLF7924REBAgXFxctD47srS0FJ9//rl49OiRoro1PdNSpyDP3ZOSksTUqVOFk5OTxjbXqFFDrFu3TlF9/v7+UjkfHx8hhBDJycliwoQJwtbWNl/dgYGB4vr167J9v//+u6Jj5SpseSIiIqIWLVpIfYm+ffsKIYRISEiQjQNcuHChorr0GV+nStP4M3WSkpLEF198Iezt7bX2PQ0NDUWjRo3E8uXLtbaxIGOgNJ3n5s2bxTvvvJOvfG7fUPUcgoKCRI8ePYS1tbXWY1euXFn88ssvIj09XdG1VNcnVUefz+r+/fti7ty5wsvLS5iYmGhtb9OmTUVwcLCithLRm8UQREREJaht27b43//+J6X37t2LX375RWuZtLQ0DBw4EKmpqQAACwsL/P333zAzM9N5vKtXr6JRo0ZYt24d0tPT1eYJDQ1Fo0aNEBwcrPg8li1bBg8PD6xduxYpKSlq8wghcPjwYTRv3lznOapz4MABNGjQAP/88w8yMjL0Lq/U9u3b0bRpUxw6dAhCiHzvp6amYubMmRgyZIj0/sWLF+Hp6Yl169YhKysrXxkhBNasWYOOHTvixYsXitpx8+ZNvPPOO5g0aRLu37+vMV9MTAw++eQTtGvXDklJSQrP8pXMzEz06dMHn376KR48eKA2T1xcHEaPHo3JkyfrVbe++vTpg59++glXrlzRmi87Oxtbt25Fs2bNEBgYWKxt0pfqKlHly5dHp06dAAADBw6EqakpgFczn/z1118FPkZWVhZ69+6NMWPG4M6dO4VrMBEREREREREREREREZWKnJwczJ8/X0obGRnhq6++KtZjRkdHo2vXrggKCsLDhw+15n358iUWLFiAhg0b4uzZs8XaLl1OnjyJGjVqYPbs2Xj8+LHGfDdv3sTgwYPRv39/ZGZm6nWM6OhoNG7cGPPnz0diYqLaPDVr1oSvr6+UVn02qMSff/4pbVtYWGDw4MF6lSciIqK325UrV3Dy5EkpPWzYMACAra0tevToIe3Xt49SXB48eIBGjRph7ty5ePr0qda8OTk5OHfuHFatWlUibfv000/Rt29fXLp0SWfeLVu2ICAgADt27NA5Ni86Ohrjx49H27ZtERcXV1TN1cs333yDL774AseOHdPZJz5z5gz8/PwwZswYZGdnl1ALiagkGJd2A4iI6O0zc+ZMhISE4MSJEwCAKVOmwNfXF40aNVKbf+LEibIO+cKFCxUtvZqSkoK+ffsiOjoahoaG6NSpE9q3bw8bGxvcv38f//zzDy5fvgwASE9Px4ABA3DgwAG0adNGa71z5syRBXYBQJs2bdC+fXtUrFgRaWlpOHfuHDZt2oSXL19CCIEJEybAzMwMY8eO1dluAIiKisLChQvx/PlzWFhYoEePHmjevDnKlSuHx48fY9euXTAwMFBUlzaRkZFYsmQJUlJSULFiRfTr1w8eHh4QQuDs2bP466+/pGCy9evXo3379ujevTs6d+6Mx48fo2zZsujduzeaNm2KsmXL4ubNm1i9ejViY2MBAGfPnsW0adN0BoVFRkbC19cX8fHx0r7KlSujV69e8PDwQJkyZRAVFYXNmzfj+vXrAICwsDB06dIFhw8fhrGxsi7NJ598gq1btwIAWrdujY4dO8LFxQUvX75EaGgotm3bJgV+zZs3D+3atUOXLl1kdZibm8Pd3R3AqwCttLQ0AICVlRXKly+v9rjalmg2MDCAp6cnmjdvjho1asDW1hZpaWmIiorC3r17pe9+RkYGPvjgA1SpUgXt27dXdL7FKSsrC6tXr5bSQ4YMkT4HOzs79OjRA1u2bAHw6ubD559/XqDjTJo0SQpYrFevHnr06AE3NzdkZGTg6tWrMDMzK/LPhIiIiIiIiIiIiIiIiIpWREQEYmJipHTnzp1RuXLlEju+mZkZWrVqhSZNmqBSpUqwtrbGixcvcPnyZezYsUN6vhkbG4tu3bohIiICFSpUKLH25QoJCUH37t1lE3PWqlUL3bt3h7u7O4yNjXH9+nVs3LgR0dHRAIBNmzbBwMAAGzZsUHSMjIwM9OvXD9euXYOBgQHatWuHdu3aoUKFCkhMTMSpU6ekCRBHjx6N0NBQAEB4eDguXLgAT09PncfIzMyUPUvs168fypUrp/AqEBEREeWfrFl1DJe/vz82b94M4FU/Mzw8HI0bNy7xNuYSQqB///64deuWtK969ero1q0batSoAUtLS6SkpODRo0e4ePEiQkND8ezZs3z1FMcYqAULFuC3334DAFSrVg1+fn6oXr06DAwMcOvWLa2TB9jZ2aF169Zo2LAhypcvD3Nzczx9+hRnz57F9u3bpUnujx8/jv79++PgwYMwNCy99VqqVq2KVq1aoV69erC3t4eBgQEePnyIsLAw2YTxS5cuRfny5TFz5sxSaysRFbFSW6OKiIhea4GBgbKlQwMDA4u0/qioKFGuXDmp/ho1aogXL17kyxccHCxrR79+/bTW6+PjI1tmFoBwcHAQYWFh+fLm5OSIuXPnyuqvUaOGSE1N1Vj/oUOHpHoBiCpVqojjx4+rzRsTEyNatmwp5TU3NxfXr1/XWLerq2u+JVtbtWol7t+/r/WchdBvyVjVfAYGBgKAGD16tEhJScmXNyIiQtjY2Ej53dzchJ+fnwAgvLy8xIMHD/KVSUxMFJ6enlIZExMTER8fr7E9KSkpom7durLP7YcffhAZGRn58mZlZYmZM2fKzuHbb7/VWLfq8sW5n5utra3Yv3+/2vx79uwRpqamsiVztVH9vvn7+2vNm5enp6eYNm2auHv3rtZ8GzduFFZWVtJxqlatKrKzszXmj4qKkl2fkJAQvdql1NatW2XHOX/+vOz97du3y94/deqUonrz/t8DQBgbG4tly5aJnJwcneUL85kQERERERERERERERFR8fjll19kz3/mzZtX7MeMiooS1atXF8uXLxfPnj3TmC89PV188803svYNGzZMa915n2lpo/S5++PHj4WTk5OUt0yZMmLFihVqn5GlpKSI0aNHy+pevXq1xrr9/f3zPYOrUKGCOHbsmNa2p6enCwcHB6nMJ598ojV/rn/++Ud2rCNHjigqR0RERCSEEBkZGcLR0VHqS3z22Wey9zMzM2X9pjFjxuisU5/xdapUx5+5uroqqvvbb7/VOr4rMzNT7Ny5U0yZMkVjnoKOgcrbltzXzJkzRWZmps7ygYGBwsfHR+zcuVPt+L1cT548ET169JAdY+XKlVrrVu2T+vj4KD4HbZ/VyJEjRUBAgDh9+rTWY1+4cEHUqlVLqtPIyEjcvHlTaxkienOUXjgmERG91dzc3LB8+XIpffPmTXzyySeyPDExMfjggw+ktKurq6yMLjk5OTA0NMS2bdvUrv5kYGCAyZMnY+rUqbJ2aDpGTk4ORo0ahZycHACvZqA4duwYWrZsqTa/i4sL9u3bh6pVqwIAUlNT8d133yluf/Xq1bFv375inSFNCIG+ffti6dKlMDc3z/d+/fr1MW3aNCl99+5dBAcHw93dHXv37kXFihXzlbGxscGff/4ppTMzM/HPP/9obMNPP/2EyMhIKb106VL873//g4mJSb68RkZGmDZtGiZOnCjtmzNnDp4/f67zXHNycmBsbIzdu3fj3XffVZunc+fOsrrPnDmDmzdv6qy7IE6cOIGZM2fC1dVVa75+/fph/fr1UjoqKgo7d+4sljbpQ3U2lvr16+ebEa5Lly6yGUoKs1T1okWL8OGHHxbJ6mhERERERERERERERERU8k6fPi1LN2vWrNiPWbFiRVy7dg2jRo3SukqRqakpvv32W0yePFnat2HDBsTFxRV7G1X973//w+PHjwEAhoaG2Lp1K0aMGKH2GZm5uTmWLl2K9957T9r3zTffSM+ydTExMcG+ffvQqlUrrflMTU0REBAgpdeuXSutWKCN6vNiDw8PtG7dWlG7iIiIiABg+/btsr6Yv7+/7H1jY2MMHjxYSq9bt05atag0HDp0SNr29PTEN998o3XFJGNjY3Tr1g3ff/99STQPX375JaZNmwZjY2OdeQcOHIjQ0FB069ZN7fi9XI6OjtiyZYusP7lo0aIiaa8+Fi1ahMDAQDRt2lRrvgYNGuDAgQOwtbUFAGRnZ+P3338viSYSUQlgUBQRESkyfPhwGBgY6PUKCgrSWmf//v0xYsQIKb1q1SqsW7cOwKsAlvfffx9Pnz4F8CoYZu3atbCxsdGr3QEBATpv5H799deywKM//vhDbb7g4GDcvn1bSi9YsACVKlXSWreVlRXmzJkjpTdt2iSdky5z586FpaWlorwFZWxsjF9//VVrniFDhuS70T5nzhytbWvcuDHq1KkjpU+dOqU2X3p6OhYvXiylO3bsiFGjRuls93fffQd7e3sAQHJyMtasWaOzDACMGDECLVq00Jpn9OjRsnTeBzRFpUyZMorzdu3aFd7e3lJ6z549xdEkxR4+fChrw7Bhw/LlyXvzYf369UhJSdH7WJ6envk+EyIiIiIiIiIiIiIiInqzPHnyRJbWNXFgUTAxMYGRkZHi/NOmTYOFhQWAV88xVQe3FrdHjx5h7dq1UnrkyJHo3LmzznILFy6UBqveu3cPu3fvVnS8MWPGoH79+oryfvjhh9J2YmKi1gkxgVeTn+7bt09Kjxw5UtFxiIiIiHKpTr5cr149NGzYMF8e1UCp58+f6+yjFKdHjx5J2zVr1iy1dqjj5OSEGTNmKM6vz5g2ExMTzJo1S0qfP39eCvIvKfq0t1KlSvj000+ldGmPwSOiosOgKCIiKlULFy6Eh4eHlB4zZgzu3LmD2bNnIzQ0VNo/ffp0eHl56V2/kmCKMmXKyII6Ll++jKioqHz5cgO2gFerQA0YMEBRG3r37g0rKysAr26eh4WF6Sxjb2+PHj16KKq/MDp06AAXFxetecqXLy8L/rK2tkavXr101t2oUSNp+9q1a2rz/Pvvv7IHIOPHj9dZL/Bq5rP+/fvL6lFi+PDhOvO4urqiQoUKUvrq1auK6i5uHTp0kLbPnDlTii15FcCYnZ0N4FXA4pAhQ9TmU735kJSUhM2bN+t9LH9/f64QRURERERERERERERE9IZLSEiQpbWt3FRaLC0tZRMsluQzuc2bNyMjI0NKK31u6uLiInuOWJTPTXPVqFEDbdu2ldKqq0Cps3LlSulZoqmpqdoJFomIiIg0efDggSzAOu8qUbkaNGiABg0aSGnVQKqSlhtYDwBnz55FZmZmqbUlr4EDB+oVOKSvNm3awMzMTEqX9rg2XVT7ztevX0dSUlIptoaIigqDooiISJHy5cvD3d1dr5e1tbXOesuWLYu///5b6hgnJSWhW7dumDlzppTH29sbU6dO1bvNtra2aNasmaK8eWfZUtc5P3r0qCy/tiVuVRkbG8sChDStmqSqWbNmiparLazmzZsryufk5CRtN2rUSFHbVAOLnj17pjbPkSNHpO0yZcqgXbt2itoDQPbZKrmmJiYmaNy4saK6K1asKG1rantJc3Z2lrZjYmJKsSWvHmTk6tixo+yzVuXp6SmbYa4gNx90rfRGREREREREREREREREr78XL17I0paWlorK+fn5wcDAQOerqJTWMznV56bVqlWTTSyqi77PTS0tLRWvEpVLdbWo0NBQ3LlzR20+IQQCAwOldK9eveDo6KjXsYiIiOjtFhQUhJycHADaJ2sG5AFToaGhuH37drG3Tx3VsYF37tzBwIED8eDBg1JpS17FPfbK2NgYDg4OUrq0x7XpotrfF0IgNja2FFtDREWFQVFERKTInDlzcOvWLb1effr0UVS3p6cn5syZI6WvXbsmzRxla2uLtWvXKg5AUlWvXj3Fed955x1ZOu/KRo8ePZIt7Vq3bl292qIaVKTkB0/16tX1qr+gNAWz5FW2bFlpW/VclJZJTk5WmyciIkLarlGjBkxNTRXVnbcdjx8/1jnDhp2dHUxMTBTVrfoQRlPbi0psbCx+/fVX9OvXD7Vr14a9vT1MTU3zPcgZNWqUVKY0A7UOHz6MW7duSWlNs7Goez8sLAw3b97U63gl9W+BiIiIiIiIiIiIiIiIio+VlZUsXdzP4PK6fPkypk2bhq5du6Jq1aqwsbGBkZFRvmdya9eulcqU5DM51eemxf0sumrVqno/f+/Tp4802FUIoXEyxIMHDyIqKkpKqz7jJCIiItIlb4D1u+++KwtiyWvIkCHS5N55y5akPn36yALB//nnH7i5uaF9+/aYM2cOTpw4IVsVtCQVdOxVTk4ODh06hHHjxsHb2xsVK1aElZUVDA0N8/WhVQOhSmtcW3JyMtavX4+AgAA0btwYTk5OMDc3z9fWGjVqyMq9LhOmE1HhFP8SFERERAp89tlnOHDgAHbu3Cnbv2LFClSqVKlAdZYvX15x3nLlysHU1FT68ZGYmCh7/+nTp7L0xIkTMXHixAK1K2/d6ihZZasoFGRp3IKUEUKo3a96XS9dulSoWdyePXumdZaxgi4DrKnthZWSkoKvv/4aixYtQlZWll5l09LSiqVNSqg+4ChXrhx69eqlNf+QIUPw5ZdfSue4cuVK/PDDD4qPV1L/FoiIiIiIiIiIiIiIiKj42NnZydLPnj1T9BzI2dkZ7u7u+fY/efIk3+pT6ty7dw+ffPJJvufQSpTkMznV56Y7duwo8HPT4noWbWpqioCAAMybNw/AqxUcvv32WxgZGcny/fnnn9K2m5sbOnTooPexiIiI6O0VEhIiW5Fy2LBhWvOXL18enTt3lvp6QUFBmDlzZr4+SnGztLTE+vXr0atXL7x8+RIAkJ2djUOHDuHQoUMAAAsLC7Ru3Rq9e/fGwIEDYWNjUyJtK0jfLywsDGPGjMGVK1f0Llsa49qWL1+OKVOmICEhQe+ypTkOj4iKDleKIiKi10beVYKsra0LtXyrubm5XvktLCyk7dwfJ7mKckaAlJQUnXlyZ7D4ryvp6/q6SE1NRZcuXfDLL7/kC4gyNDSEg4MDKlWqBHd3d+mlT5BfcXn+/Dk2b94spfv166cz2MzJyQmdOnWS0qtWrZJWglPibfm3QERERERERERERERE9F+W91nXvXv3FJVbsmQJbt26le/Vp08fnWVv3ryJVq1aqQ2IMjExgZOTE6pUqSJ7Jqe6olVxTZ6oTlE9Ny3OZ9EffvihFKz18OFD7NmzR/Z+QkICgoODpfQHH3xQqEkxiYiI6O2jOlmztbU1/Pz8dJbx9/eXtmNiYrBv377iaJpO7dq1Q3h4ON577z21QVkpKSnYv38/xowZA1dXV/z0008l0t/Ut+8XHByMDh06qA2IsrCwgLOzM6pWrSrrQ6seoyT70AAwefJkjB49Wm1AlI2NDSpWrIhq1apJbXV1dZXlKen2ElHx4ChTIiJ6LSxduhT//POPbF9SUhICAgKwe/fuAt0sTU1N1Su/6g1iS0tL2XuqAVMA4OLionfQlWpZekX1ulpaWsLJyanAdb1JwTOzZs1CWFiYlK5bty4+/fRT+Pr6olq1ajAxMclXJjAwECNGjCjJZubz999/y/5d/fnnn7LZ3pSIjY3Fnj170L1796JuHhEREREREREREREREb2mmjVrhr///ltKnz59Gm3atCm24wkhMHz4cDx8+FDa16VLF4wYMQItW7aEi4uL2mfQ/v7+WL16dbG1SxMLCwskJSUBAGxtbfOtrPU6qFGjBnx9fRESEgLg1aBl1Wd+a9asQXp6OgDAyMgIw4cPL5V2EhER0Zvp2bNnsvGDSUlJ+cbsKbFy5Up07dq1KJumWM2aNbF582Y8evQIu3fvRmhoKI4dOyZb/Qp4dW5ffPEFIiMjERQUVCptVScuLg7Dhw9HZmYmgFfj8UaOHIm+ffuiUaNGsLW1VVvO1dUV9+/fL8mmAgD+/fdfaSVTAHBwcMC4cePQuXNn1KtXT+34zqioKFSrVq0km0lEJeDNGT1MRET/WZGRkZgwYYKULlu2LJKTkwEAe/fuxYIFCzB+/Hi9633y5InivM+fP0dGRoaUztuBd3BwkKXnzZuHQYMG6d0mklO9rq1atSq1mTpKUmZmJn777Tcp3a5dO+zevRtmZmZayxXlqloFpTobS2HrYVAUERERERERERERERHR28PHx0eWDg0NxcSJE4vteKdPn8axY8ek9FdffYXZs2frLFdaz+QcHBykoKh+/fph2bJlpdIOXT788EMpKGrnzp14/PixNPGl6rPELl26oGLFiqXSRiIiInozrV27FmlpaYWuZ/v27YiLi4Ojo6Nsf0FXsFSyEmdeFSpUwIgRI6QJsKOjo7Fr1y6sWrUKJ0+elPKtWrUK/fr1Q7du3QrUtqK2cuVKqT9saGiInTt3olOnTjrLlVYfev78+dK2k5MTzp49i0qVKmkt8zqMwSOiomdY2g0gIqK3W1paGgYNGiStPmNhYYGTJ0+iefPmUp7//e9/OH/+vN51X758ucB5a9WqJUu7uLjA2tpaSkdGRurdHsrPw8ND2la35O5/0ZkzZ6QHGgAwe/ZsnQFRAPLNGFLSLl68iLNnz0ppZ2dn2TLIul6qq4DlPiAhIiIiIiIiIiIiIiKit0ODBg1kQTJ79uzBgwcPiu14Bw8elLatra0xbdo0ReVK65mc6nPT1/lZdJ8+faQBxllZWVi1ahUA4NSpU7h06ZKUb+TIkaXSPiIiInpzqQZYW1pa6jUuyd3dXSqbmZmJNWvW5Ks/76pTSoOdimKMU+XKlfHRRx/hxIkT+PXXX2Xv/fXXX4Wuv6io9qHfffddRQFR8fHxsrFwJSUnJ0cK1geAzz//XGdAFFD6Y/CIqHgwKIqIiErVxIkTZTdHFy5ciHr16mHdunVSEFJGRgYGDhworR6lVGJiIk6fPq0o7969e2Xppk2bytJGRkZo06aNlN6xY4debSH12rZtK20/ePCgQMFvpcnExETazsnJUVQmJiZGlm7QoIGicqo/OkuD6o0HQ0NDhIeH49atW4pfhw8flspnZWVh9erVxdLOgnwmREREREREREREREREVLwMDQ0xfvx4KZ2dna1o5aaCUn0m5+HhoWiSwkePHpVaQJLqc9OTJ08iPj6+VNqhi6mpKfz9/aV07jNE1WeJzs7Or81qB0RERPRmOH/+vGzc2DfffKPXuKRbt26hRYsWUnnVvkkuGxsbWTrvGC5NVFd2Kgrjxo2TjRfTNJF4aYyBUr0mSse0HTp0qLiao9XTp0+Rnp4upd+UMXhEVDwYFEVERKVm27Zt+P3336V0v3798MEHHwAAqlWrJnvvxo0bGDdunN7H+OOPP3TmSU9PlwVo1KtXD9WqVcuXb+DAgdL2xYsXsWfPHr3bQ3KdOnWS/eD88ccfS68xBWBpaSltP3/+XFEZIYQsrWTZ5/379+Pq1av6Na4IpaenY+3atVK6bdu2cHZ21quOWrVqoVGjRlJ65cqVRdY+VQX5TIiIiIiIiIiIiIiIiKj4jR49Gvb29lJ66dKl2LVrV7EcS/WZnJLnccCrCTzzPssrKX379oWxsTGAVwFjP/30U6m0Q4kPP/wQBgYGAF49x9+7dy/Wr18vvR8QECCdCxEREZESqkFMBgYGsnF6Sg0ePFjavnLlSr5gpqpVq8oC5U+dOqWzzuPHj+PGjRt6t0WXWrVqSduZmZlq85TGGKiC9KHzrnxVUgoyBu/p06dqVxEjojcfg6KIiKhUxMTESAFQAODq6orly5fL8gwZMgRDhw6V0itXrsTGjRv1Ok5gYKDO2Rq+//573L9/X0qPGjVKbb6BAwfKgqVGjRqF6Ohovdqj9MfC28LKygqffvqplN64cWOBgmVK67q6ublJ25cvX1ZUpkqVKrL0zp07teZPTEzERx99pHfbilJwcDCePn0qpQcNGlSgelTLXbt2DcePHy902/IqyGdCRERERERERERERERExc/S0hKrVq2SAmqAVxNnbtmypciPpfpM7vLly7h7967W/KdPn8a8efOKvB1Kubm5yZ6lzZ8/H/v379erDiEEMjIyirpp+dSoUQO+vr5SOiAgAC9evADwahCz6jgAIiIiIl3S0tKwbt06Ke3l5ZVvfJUS/fv3h5GRkZTOOwbN2NhYNqHzqlWrNAYkAUBGRoZsXJs2uvqaqoQQuHTpkpRWHeukqjTGQKle9z179iA7O1tr/gULFhTL+C8l7O3tYWFhIaV1jcHLycnBqFGj8PLly+JuGhGVAgZFERFRicvJycH7778vBVkYGRlh7dq1+ZaoBYDff/8d1atXl9Iffvgh7t27p+g4hoaGyM7ORs+ePXHs2LF87wshMH/+fHz33XfSvurVq+PDDz9UW5+xsTH++OMP6cdTTEwMmjdvjh07duicMSwyMhJTpkyBu7u7ora/Tb788kvUq1dPSo8cORL/+9//kJSUpLVcQkICAgMD0aRJEwQHBxdzK9VTXXb5zp07+OWXX5CVlaW1TJMmTWBnZyelJ06ciAsXLqjNGxkZCW9vb0RFRcHQsPS6baqzsZiZmeG9994rUD0DBw6UnYe6paoLqyCfCREREREREREREREREZWMbt26Ydq0aVI6NTUV/fr1w6BBg3DlyhWd5TMzM7FhwwaEhoZqzdepUydpOycnB4MGDUJ8fLzavNu3b0fHjh2RmZlZqs/k5s6dC2dnZwBAVlYWevTogZ9//lnnBJGxsbFYtGgRPDw8cO7cuZJoquyZ+uPHj6Xttm3b8pk4ERER6eWff/5BYmKilFZd8UkfTk5OaNeunZRev349kpOTZXlU67516xbGjRunNvDn8ePH6NatG86dOycL6Ndk+PDh8Pb2xoYNG5CSkqIxX1ZWFiZNmoSrV69K+/z8/NTmLY0xUKp96Js3b+LTTz9Ve8zMzEzMnj0bEyZMAIBS6UMbGRmhQ4cOUjooKAirV69Wm/fp06cYMGAAtm7dWqr9fSIqPlyrmIiIFPnyyy8xa9YsvcutXbsWzZs3l+37/vvvZTepp02bBi8vL7XlLS0tsW7dOnh5eSEzMxPPnz/H4MGDERYWJpvZQZ333nsPly9fxtWrV+Ht7Y0uXbqgXbt2KFeuHB48eIAtW7bIZl0wNTXFihUrUKZMGY11tmvXDgsWLMC4ceMghEBsbCx69uyJmjVrokOHDqhVqxasra2RmpqKp0+fIjIyEqdOnUJUVBQAyJbgpVfKli2LrVu3wtvbG7GxsRBCYM6cOfj999/RqVMnNGnSBA4ODgCAZ8+e4fbt27hw4QLOnDlT6sEuPXv2hIODg/QAZcKECfj666/h6uoKU1NTKd9HH30krfZkbGyMyZMnY8qUKQCAuLg4NGvWDH5+fmjdujWsrKwQFxeHsLAw7N27F9nZ2bC2tsaYMWMwZ86cEj/He/fu4eDBg1K6S5cuagMYlahUqRLatGmDw4cPA3i1Mtivv/4qW+65sArymRAREREREREREREREVHJmTFjBmxsbDBp0iRkZ2dDCIH169dj/fr1qFmzJtq2bQtXV1fY29vD1NQUycnJePjwIa5cuYKQkBA8f/5cVl+1atXyHaNhw4bo1KkT9u3bBwA4efIkatasiYEDB6JBgwYwNjZGdHQ0du3ahbNnzwIAPD09UaNGDWzatKn4L4IaFSpUwJYtW9C5c2ckJSUhIyMDkyZNwo8//ohOnTrB09MTdnZ2yM7OxrNnz3Djxg2cO3cO58+f1zmJZ1Hr06cPHB0dERcXJ9s/atSoEm0HERERvflUJ1U2NjZGv379ClzX4MGD8e+//wIAXrx4gU2bNiEgIEB6f/jw4Zg3b540KfvSpUtx5MgR9O/fH5UrV8aLFy9w9uxZbN26FS9fvkSlSpXQrVs3LFu2TOtxhRA4cuQIjhw5grJly6Jly5Zo0qQJXFxcYG1tjeTkZFy7dg3bt2+XTQhfv359DB8+XG2dpTEGauTIkfjhhx+kPt6SJUtw4MAB9OvXD+7u7khPT8eNGzewdetW6Tw+/PBD7Nu3T/FE90Xpf//7nzShfU5ODvz9/bFixQp06dIFFSpUQFJSEsLDw7Ft2zbpN8R3332HqVOnlnhbiah4MSiKiIgUefLkCZ48eaJ3udTUVFn6xIkTmDlzppRu06aNzk5m06ZNMWvWLHz55ZcAgOPHj+Pbb7+V1aOOhYUFNm/ejE6dOuHBgwfYtWsXdu3apTavqakpNmzYAG9vb53n9Mknn6BSpUrw9/eXVjO6ceMGbty4obOsrkCut1X16tVx9uxZ9OnTB6dOnQLw6ofp5s2bsXnzZp3lS+u6mpubY82aNejXr5+0tG5KSopsNg8AePTokSw9efJknDx5Etu2bQPwavaMTZs2qX3AUq5cOWzYsAGxsbHFdBbaBQYGIicnR0oPGjSoUPUNGjRICop6+fIlNmzYgA8++KBQdaoq6GdCREREREREREREREREJefzzz+Hp6cnxo8fjwsXLkj7lT53BQAHBwdMmTIFn3zyidr3V61aBS8vL9y+fRsAkJiYiCVLlqjN6+Hhga1bt2LGjBl6nUdRa9myJU6ePAk/Pz/pOsTHx2Pt2rVYu3atzvIl9dzU1NQU/v7+mDdvnrTP3t4evXv3LpHjExER0X9DVFQUQkJCpPS7774rTZ5dEH369MGYMWOklTZXrFghC4oqW7Ys1q5di86dO0vjiiIjIzF9+vR8dTk7O2P79u3S+C6lkpOTceDAARw4cEBrvgYNGmDPnj0wMTFR+35pjIGysrLC5s2b0aVLF2nFq5s3b+L7779Xm79nz55YtGgRatasWWRt0EfLli3x008/YdKkSdK+sLAwhIWF5ctraGiI7777DoMHD2ZQFNF/ENeAIyKiEpO7ylPu6j62trZYu3atohuzkydPxrvvviulZ8+erbbzmledOnVw/vx5DB48WDZDgipfX1+cO3dO41K06vj5+eHOnTuYMmUKKlSooDWviYkJvLy8MGfOHMU38N9GLi4uOH78ONavX4+mTZvqXHq4WrVqGDNmDI4cOVKoGUIKq3PnzoiMjMTXX38NLy8vODo6avyu5TIyMsI///yDH374AXZ2dmrzmJqaok+fPoiIiJAtTVyShBAICgqS0paWlujRo0eh6uzXr5/sx7zqbC9FpSCfCREREREREREREREREZUsX19fnD9/Htu2bUPPnj1Rrlw5nWVyA2+2bNmCmJgYTJgwQeNzICcnJ5w5cwYjRozQONjU1tYW48ePR3h4ONzc3ApzOkWmdu3auHz5MpYuXYo6derozF+nTh1MnDgR58+fR9OmTUugha+oDjAGgKFDh8LMzKzEjk9ERERvvpUrV8pWvBw8eHCh6rO2tkbXrl2l9NGjR3H9+nVZHi8vLxw9ehRt2rRRW4epqSkGDRqEiIgINGzYUNFxZ82ahY8//lhRcFC1atXw008/4cyZM3B2dtaatzTGQHl7e+P06dNo27atxjzu7u5YsmQJtm3bVupjsiZOnIjg4GCt175FixY4ePAgvvrqqxJsGRGVJANR0usnExERFSNfX19pFRp/f39ZQEdCQgLCwsIQHR2NlJQUuLi4oHXr1qhatWqhj3v58mVcvHgRcXFxePHiBcqWLQsHBwfUrFkT9erVQ9myZQt9jLdNfHw8jh07hkePHiEhIQFGRkYoV64cqlatirp166JixYql3cQikZqaimPHjuHq1atISkqCvb09XFxc4O3tDRsbm9JuHhEREREREREREREREVGJyM7Oxvnz53H37l3Ex8cjISEBpqamsLGxgYODA+rXr49q1aoVqO74+HiEhYXh7t27yMjIQPny5eHq6gpvb2+NAVOvi5iYGJw8eRKPHz9GYmIiTE1NYWtrC3d3d9SrVw+Ojo6l0q7169dj0KBBUvry5cuoW7duqbSFiIiIqCBu3bqFo0eP4vHjxzAzM0PlypXh4+NTqNWq4uPjcenSJdy5cwcJCQlIT09H2bJlUaFCBTRs2BAeHh5FeAbF6/bt2zh27BhiY2NhZGQEZ2dneHh4oHHjxqXdtHxycnJw7tw5hIeH4+nTp7C0tISzszOaNGlSJONDiej1xqAoIiL6T9EWFEVERERERERERERERERERESF9+677+LAgQMAgJYtW+L48eOl3CIiIiIiIiJ6GxmWdgOIiIiIiIiIiIiIiIiIiIiIiIjozXDjxg0cPHhQSo8ePboUW0NERERERERvMwZFERERERERERERERERERERERERkSLfffcdhBAAAHt7ewwYMKCUW0RERERERERvK+PSbgARERERERERERERERERERERERG93rKysrBw4UL89ddf0r6JEyeiTJkypdgqIiIiIiIiepsxKIqIiIiIiIiIiIiIiIiIiIiIiIjyWbp0KZYuXYqsrCzcv38fL168kN6rVq0aPvvss1JsHREREREREb3tGBRFRERERERERERERERERERERERE+Tx69AgRERH59pcrVw4bN26EhYVFKbSKiIiIiIiI6BXD0m4AERERERERERERERERERERERERvd5MTEzg5uaGDz/8EBEREWjcuHFpN4mIiIiIiIjecgZCCFHajSAiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiUoorRRERERERERERERERERERERERERERERERERHRG4VBUURERERERERERERERERERERERERERERERET0RmFQFBERERERERERERERERERERERERERERERERG9URgURURERERERERERERERERERERERERERERERERvFAZFEREREREREREREREREREREREREREREREREdEbhUFRREREb5gZM2bAwMAABgYGcHNzK+3m6C0gIEBqv6+vb2k3h4iIiOitFB0djeDgYPz+++/44Ycf8OOPP2LRokXYvHkzwsPDkZqaWmptCw0NlfqLBgYGuHv3bqm1hYiIiIiI8gsKCpL12YmIiIiIiIiIiIiISotxaTeAiIheT0FBQRg+fHiBy2/duhV+fn5F1yB6rdy9exdBQUFS+vPPP4eNjU2ptYeIiIheH3PnzsWXX34ppQ0NDXHnzh24urqWYqsIANLT0/H7779j+fLluHbtmta8xsbGqFu3Ltq3b49evXrB29u7hFpJpeHChQsIDg6W0jNmzCi1thAR0ZtP033FHTt2oHv37nrVlZiYCGdnZ6Snp8v2+/v7y+5NEdF/3+nTp9G8eXPZvjVr1uD9998v0XY8e/YMCxYskNIBAQFv5ORlRERERERERERERP8VDIoiIiIivd29exczZ86U0gEBAQyKIiIiIgBAYGCgLJ2Tk4OgoCBMnz69lFpEABAREYEBAwbg+vXrivJnZWUhIiICERER2LVrl84gKnqzXbhwQda/Z1AUEREVh5UrV+odFLV27dp8AVFE9HZauXJlvn0rVqwolaAo1b6zr68vg6KIiIiIiIiIiIiIShGDooiISJHy5cvDyspKcX5LS8tibA0RERERvY6OHTumNngmMDAQ33zzDQwNDUuhVRQZGYl27dohISFB2mdmZoYOHTqgadOmqFChAkxNTZGQkICoqCicOXMG4eHhyM7OLsVWExER0X/Nzp07ERcXB0dHR8Vl1AVBENHbJyUlBX///Xe+/YcPH8bt27fh7u5eCq0iIiIiIiIiIiIiotcBg6KIiEiROXPmICAgoLSbQf8BQUFBCAoKKu1mEBERUTFYsWKFtF21alVERUUBAO7du4eDBw/i3XffLa2mvbVycnIwfPhwWUBU//79sXDhQjg5OWks9/TpU+zYsQN//PGHrCwRERGRvpycnPD48WNkZmbir7/+wvjx4xWVi4iIwPnz5wG8moBJCIHk5OTibCoRvaY2b96MpKQkAECZMmVgY2ODR48eQQiBlStXYvbs2aXcQiIiIiIiIiIiIiIqLZyimYiIiIiIiIgK7cWLF9i4caOU/uKLL9C8eXMprRowRSXn0KFDOHPmjJTu0aMH1q9frzUgCgDs7e0REBCAY8eOYefOncXdTCIiIvoPGzZsmLQdGBiouJxq/7Ffv34oU6ZMkbaLiN4cqv8f9OrVC/7+/lI6KCiIq9wSERERERERERERvcW4UhQREZWK1NRUHDlyBPfu3UN8fDysrKxQoUIFtGnTRucAzddFQkICDh8+jOjoaKSlpaF8+fJo3bo1qlevXuA6Hz16hNDQUDx48AAmJiaoWLEiWrVqBRcXl0K3NyYmBpcuXUJUVBSeP38OQ0ND2NnZoXr16mjRosUbMbAkMzMTx48fx+3bt/HkyROYm5vDyckJLVq0gJubW5Ed5/Tp07h69SpiY2NhaWmJ6tWrw9fX9424RkRERKVlw4YN0sz9ZmZmGDBgAIQQOHXqFAAgODgYCQkJsLOzK5LjxcTE4MSJE4iOjkZ2djacnZ3h4+ODSpUqFUn9RdkfyM7ORmRkpFRfcnIyLC0t4eDggMaNG8PDw6NI2qzOrl27ZOmpU6fCwMBArzrc3d31Pm5WVhZOnTqFW7duIT4+HhkZGShXrhyqV6+Oxo0bw97eXu86c126dAkRERGIiYlBmTJl4ObmhrZt28La2rrAdZaG5ORkXLx4ETdu3EB8fDzS0tJgY2MDZ2dntGzZEs7OzkV2rNjYWJw4cQKxsbF4/vw5KlSogBEjRhRZ/URERNr07dsXy5YtQ1JSEi5duoSzZ8+iSZMmWsukp6dj3bp1UnrEiBHYvn17cTdVb/Hx8Th79ixu376N58+fw8DAAGXLlkXFihVRo0YN1K1bF0ZGRnrXm5CQgKNHj+Lhw4dITEyEjY0NqlSpAl9fX5QtW7YYzqRoZWZm4vDhw4iKikJcXBxsbW3RvHlzNGrUSGMZIQROnz6N8+fPIyEhAdbW1qhbty68vb0LdA2vXr2K8+fP4/Hjx0hOToaZmRnKlSsHV1dXvPPOO0Vyv1WTkuz/JycnIyQkBPfv30dSUhIcHR3RrFkzvPPOOwWu89mzZzh48CDu378PIQQqVqyIJk2aFOh3QVG4efMmwsLCpPSwYcNQtWpVzJkzBwDw8OFD7N27F926dSuS4yUnJyMsLAwPHjxAXFwcypUrh/79+8PR0bFI6iciIiIiIiIiIiKiIiaIiIjUCAwMFACkV2BgYJHUGx0dLYYNGybMzc1l9ee+DAwMROvWrUVYWJii+nx8fKSy/v7+ituh9NxcXV2lfNOnTxdCCBEXFyfef/99YWZmpvYcWrduLSIiIhS3RQgh7t+/L/z8/ISRkVG++oyMjES3bt3EnTt3hBBCTJ8+XXrP1dVVa72hoaFi7Nixolq1amrbmvsyMzMTw4cPF7dv39Zan+r1VvrKy9/fX3rPx8dH0fV5+vSpGDdunLC2ttZ4nAYNGojg4GBF9eX9fuf6+++/Rc2aNdXWb2lpKWbPni2ysrIUHYOIiOht06JFC+nvZt++fYUQQiQkJMj6TAsXLtSrTnV9tjt37oju3bur7TcBED179hRRUVE66y7u/kBSUpIICgoSPXr00NqHASAqV64sfvnlF5Genq7X9VHCz89PdqzU1NQiP4aqqKgoMWLECK3nbGhoKJo2bSoWL16sto6QkBBZ/tzP88CBA6JRo0Zq6zQ1NRUTJkwQycnJGtu2Y8cOWRuePn2q9VyaNWsmO8ZPP/2kNf/y5culvFZWViIzMzNfnvv374u5c+cKLy8vYWJiovV70bRpU8X9WyHU/3uJiIgQHTp0EIaGhmr76aq/d5S8VH9/REVF6f3bQFNdRET035K3n3Xp0iUxatQoKT127Fiddaxfv17KX7NmTSGEEPb29tI+bfcBC3LvSQj19wE1OX/+vOjatavGPmnuq2zZssLPz09cvHhRURsOHz4sfH19NdZbpkwZMWzYMBETE6OzLk39XV2UXj919yizs7PF7NmzRfny5TX2b9TdN127dq2oWrWq2jKVKlUS27ZtU9T2nJwcsWzZMlGjRg2dfRE3Nzfx+eefi5ycHMXXRpvi7P+ruwf+8uVL8emnnwpLS0u1x3jnnXfE4cOH9TqHp0+fiuHDhwtTU1O1dbZp00acO3dOCFHw71dB/O9//5OOU6FCBen3WNOmTaX9ffr00atOddc0Pj5eDB8+XJQtWzbfuYeEhMj+bSh9KfltSkRERERERERERESFYwgiIqISsnPnTtSqVQurV69Gamqq2jxCCBw9ehTe3t6YNGkShBAl3ErtIiIi4Onpib/++gvp6elq8xw9ehStW7fGyZMnFdV54sQJ1KtXD8HBwcjOzs73fnZ2Nnbt2oXGjRvjyJEjerXX19cXv//+O+7cuaM1X3p6OgIDA9GwYUPs2bNHr2MUt9OnT6NWrVpYuHAhkpKSNOaLiIiAn58fBg0ahMzMTL2P8+mnn2LQoEG4ceOG2vdfvnyJqVOnYvDgwa/d95KIiKi0XblyRdb3GTZsGADA1tYWPXr0kPavWLGiUMc5cOAAGjVqhJ07d6rtNwHA9u3b4eXlhZs3b+pdf1H2B7Zs2YKAgADs2LFDax8GAKKjozF+/Hi0bdsWcXFxerdbm5SUFFk6LS2tSOtX9fvvv6NWrVpYuXKl1nPOycnBmTNn8PHHHyuue+7cuejYsSPOnTun9v2MjAzMnz8fXbp00fhbQ3WVgZycHISGhmo8XlJSEsLDw2X7Dh06pLWNqu+3adMGxsb5F2j/5ptv8MUXX+DYsWM6+6xnzpyBn58fxowZo/H7rs1ff/2FZs2a4cCBA8jJydG7PBERUVFSXaHw77//1tknWblypbQ9fPjwYmtXQaxduxZNmjTB7t27df6NTk5ORnBwsLR6qiZZWVkYOXIkfHx8EBoaqrHetLQ0rF69GrVr15atnPM6SEtLQ6dOnTB16lQ8efJEbZ4zZ87Ay8sLZ86cAfDqXvDHH3+MIUOGICoqSm2ZBw8eoHfv3li7dq3W42dkZMDPzw+jR49W9Fvg7t27WLBgQYH6WeqUZP///v37aNq0KRYtWoSXL1+qzXPp0iV06NABwcHBiuq8efMm6tevj8DAQGRkZKjNc+TIEbRq1QqbNm3Su80FlZ2djVWrVknpwYMHS316f39/af+OHTs0fu+UiIiIkM4/dwVkIiIiIiIiIiIiInoz5B+dQUREVAz27NmD3r17IysrS9rXoEED+Pn5oXLlykhMTERISAj27dsnPYj++eefkZWVhQULFpRSq+UeP36MHj16ICYmBpaWlujVqxeaNm0KKysrREdHY8OGDbh69SoA4MWLFxg8eDAuX74MCwsLjXVev34dXbt2lT0od3d3R79+/VCtWjW8fPkSJ06cwLZt25CYmIh+/fqhd+/eerfdyMgIzZo1Q7NmzeDm5oZy5cohJSUFN27cwM6dO6WgqaSkJLz33ns4c+YM6tatm6+eihUrwt3dHampqXj48KG039XVVe2gz8I6f/482rdvL3u4X716dfTt21e6PqdOnUJwcLAUpLZ+/XqkpaVh69atio/z/fff47fffgMAeHp6onv37nB1dUV6ejpOnjyJDRs2SINWN27cCF9fX4wZM6YIz5SIiOjNphrsVL58eXTp0kVK+/v7Y/PmzQBeDTQLDw9H48aN9T7GtWvX8NlnnyEpKQn29vbo3bs36tevDwsLC9y6dQvr1q3D/fv3AQAPHz7EsGHDcOzYMRgaKpsPpjj7A3Z2dmjdujUaNmyI8uXLw9zcHE+fPsXZs2exfft2KYjn+PHj6N+/Pw4ePKi43bo4OjrK0vv27cOAAQOKpG5V06dPx7fffivbV6tWLXTt2hXVqlWDhYUFEhISEBERgZCQEMTExCiue926dZg6dSoAoEaNGvDz84O7uzuEELhw4QL++usvaeBiWFgYZsyYgTlz5uSrx9raGo0bN8bp06cBvApi6tOnj9pjhoWF5Rsge+TIEWRlZWns96oGWbVt21bneVWtWhWtWrVCvXr1YG9vDwMDAzx8+BBhYWE4dOiQFHi3dOlSlC9fHjNnztRZZ67Tp09jxYoVyMjIgK2tLfz8/ODp6QkLCwvExMRIfWU3NzcYGxvjxYsXskGk7u7uauutVKmStG1iYqIxnyZ37tzhBANERG+pFi1aoE6dOrhy5QoSExMRHByMgQMHqs0bHR2NAwcOAHh1Tys34P51EBkZiYCAAKmfYGhoiPbt26N169ZwcXGBsbExnj9/jtu3byM8PBynTp3SGXSTnZ0NPz8/7Nq1S9pnZmaGbt26oUWLFnBwcEBCQgJCQkKwZ88e5OTkICkpCZ07d8aRI0cK1LcuDmPGjMGBAwdgYGCAzp07o23btrC3t0dsbCw2bdqEiIgIAK8mGhg0aBAiIyMxZ84c/P777wBe9cF79uyJypUrIyUlBfv375euSU5ODj766CP4+vqiYsWKao8/ffp0bN++XUrb29ujR48eeOedd2BnZ4fMzEw8ffoUkZGROHr0KO7evVts16I4+/8pKSno1asXrl69ClNTU3Tv3h2tWrWCnZ0dHj16hK1bt0pBZ5mZmQgICMDVq1fh7Oyssc64uDh06NBB1kd3dnbGgAED4OHhgYyMDISHh2PLli14+fIlAgIC9JrgoDB2796N2NhYKa36/8GgQYMwYcIEZGRkIDMzE2vWrMHEiRP1PkZiYiJ69+6Nhw8fwtjYGF27dkXr1q1hb2+P+Ph4hIaGwsjICE5OTnB3d0dWVhbu3bsnlXdxcYG5ubnauk1MTPRuDxERERERERERERHpqfQWqSIiotdZYGCgACC9AgMDC1xXXFyccHJykuoyNDQUv//+u9q8J06cEM7OzrJj7969W2PdPj4+Uj5/f3/FbVJ6bq6urrJ2AxAdOnQQsbGx+fJmZmaKESNGyOpevHixxrpzcnJEmzZtZPknTZokMjIy8uW9ePGiqFatmqwdAISrq6vW83R2dhY///yzePTokcY82dnZYvHixcLExESq19vbW2u9ISEhsnZHRUVpza/K399fKufj46MxX1pamqhTp47sOF9//bXIzMzMl/fq1avCw8NDlnfJkiUa6877/TY0NBRlypQRa9asUZs/PDxc2NraSvmdnZ1FVlaW4nMmIiL6L8vIyBCOjo7S38nPPvtM9n5mZqasLzhmzBjFdef9ew1ADBkyRDx79ixf3uTkZNG5c2dZmV27dmmsu7j7A4GBgcLHx0fs3LlTbf8u15MnT0SPHj1kbVm5cqWWq6KfRYsWyep2dnYW4eHhRVa/EELs2LFDGBgYSMewtrYW69at05g/Oztb/Pvvv6Jdu3Zq38/b1zQ0NBSGhoZi3rx5aq95VFSUrN9uZmYmEhIS1Nb95ZdfSvlq166tsY0TJkyQ8hkZGUnbx48fV5s/MjJS1mZN13jkyJEiICBAnD59WuOxhRDiwoULolatWrI23Lx5U2sZ1ePnvvz8/MTTp0+1lhMi/7+H4vDTTz/JjjF06NBiOQ4REZW+vH9XLl26JISQ/y149913NZb/9ttvpXzdunWT9tvb2yu6D6j03lNeqv2J6dOn66zbwcFBnDlzRmudcXFxYu7cuWL79u0a88yYMUN2vdq1ayfu37+vNu+JEydE+fLlpbx16tQRaWlpavMW9O+70us3ffp0KV9uX7B8+fJq+0vZ2dli5MiRsvZ8+umnwsjISBgbG4s//vhD0TlMmDBBbb7k5GRhbm4u5evRo4d48eKF1vMMDw8Xw4YNK7J7fMXZ/1e9B577u8jT01Nj/1D1swEgJk+erLX+IUOGyPIPHjxYvHz5Ml++e/fuiSZNmuS7R11c/UchhOjVq5d0jAYNGuR7v0+fPor693mpXtPcV61atURkZKTOslFRUbJyISEhepwRERERERERERERERU1BkUREZFaRRkUNWnSJFldv/zyi9b858+fF6ampooeZpZkUBQA0ahRI5Genq4xf1pamnBzc5Pye3l5acwbHBwsqzsgIEBrm2/evCksLS1lZXQFRaWmpmp9X9XixYtldUdERGjMWxJBUb/99pvsGHkHWOd1//592eAYOzs7kZKSojZv3u83ALFp0yat9S9btkyW/99//9V1qkRERG+FzZs3y/5Gnjt3Ll+e8ePHS++XK1dO49/ovPL+ve7Ro4fIycnRmD8uLk5YW1tL+YcMGaIxb3H3B/Tph2VkZIhWrVpJ9TZs2FBxWV3i4uLy9SENDQ1Ft27dxMqVK8Xt27cLVX9GRoaoVKmSVLe5uXmhg67y9jUBiHnz5mkts2/fPll+TQNr8+ZTN9mBEEJ4enpKeYYNGyZtz5o1S21+1eAzGxsbkZ2drTafPt+L6OhoWSDe+PHjtebPe81at26tdkIBdYo7KOqff/6RDZxt0aKFXteCiIjeLJqCoh4/fiyMjY2l/oi6wJ+cnBxpYiAAYvPmzdJ7r0NQVOXKlaU8CxYsUFy3Jrdv35YFYPv4+GgNqBHiVTCP6uRGf/75p9p8JRkUBUCYmJio/S2QKyUlRVSoUCFfn0XT5Fm5unfvLuV1cXFRm+fgwYNSHmNjYxEXF6foXItScfb/8wbwVK5cWeMkALlU669YsaLGfOfPn5fV3b59e62BYnFxcbL+f3H1H4UQ4tGjR9L/GQDE/Pnz8+XZtm2brB2aJjHIK+81tbW1FTExMYrKMiiKiIiIiIiIiIiI6PViCCIiIgWGDx8OAwMDRa8LFy5I5dLS0rBy5Uop7enpiXHjxmk9Vt48V69eRUhISJGfU0H89ttvMDU11fi+mZkZAgICpHR4eDiysrLU5l2+fLm0bWVlhZ9++knrsatXr47Jkyfr1d4yZcoozvvRRx+hatWqUnrPnj16Hauo/f7779K2s7MzZs+erTV/5cqVMXPmTCmdkJCA9evXKzpWx44d0bdvX6153n//fVhYWEjpU6dOKaqbiIjov27FihXSdr169dCwYcN8efz9/aXt58+f459//tH7OMbGxli8eDEMDAw05nFwcECfPn2ktD5/r4u6P6BPP8zExASzZs2S0ufPn8fjx48Vl9fGwcEBv/zyi2xfTk4Odu3ahREjRsDd3R2Ojo7o3Lkzpk2bhv379yM5OVlx/X///TcePHggpWfNmoVGjRoVSdtzeXh4YMKECVrzdOzYEW5ublJa02fTunVrmJiYSOlDhw7ly5OQkICLFy8CeNUPHTt2rPSept8lqvt9fHxgaKj+lps+34tKlSrh008/ldL69s8XLlwIY2NjvcoUh/DwcLz//vvIyckBALi5uWHbtm16XQsiIvpvKF++PLp16wbgVX8kKCgoX57Q0FDcuXMHwKt+TM+ePUuyiTo9evRI2q5Zs2ah61uwYAGys7MBAKampli1apWsr6JOo0aNMGrUKCm9ZMmSQrejKIwaNUrtb4Fc5ubmeO+992T76tWrhzFjxmitd9iwYdL2w4cPZX3PXKqfi52dHRwcHJQ2u8iUZP9/zpw5sLW11Zrnww8/lLZjYmIQExOjNt8ff/whbRsaGuK3336DkZGRxnodHBx03qctKqtWrZLurRsbG2Pw4MH58nTt2hWOjo5SWvVZhD6++eYbuLi4FKyhRERERERERERERFSqGBRFRETF6vjx40hISJDSH330kcYBgqrGjh0rG/C6c+fOYmmfPmrWrImWLVvqzNeiRQtpOy0tDXfv3s2XJy0tDf/++6+U7t27t6KH9SNHjlR0/QrC0NAQbdu2ldJnzpwpluMocefOHVy5ckVK+/v7o2zZsjrLBQQEyPIp/d4MHz5cZx4LCwvUr19fSl+9elVR3URERP9lDx48wL59+6S0avCTqgYNGqBBgwZSWjWQSqn27dujcuXKOvOp9sVu376NzMxMRfWXdn+gTZs2MDMzk9JF2RcbOXIkVqxYIQvoUhUfH499+/bhu+++Q6dOneDo6IghQ4YgPDxcZ90bN26UtsuVK4ePPvqoyNqdy9/fX2swXC7Vz17TZ2NhYYFmzZpJaXVBUYcPH5YCeNq2bYsmTZrA2toawKvfN+np6bL8QggcPnxYSrdr105nW5Xq0KGDtH39+nUkJSUpKtegQQOtg5JLSnR0NHr06IGUlBQAr74ju3btQvny5Uu5ZUREVFpGjBghbQcFBUEIIXtftZ/4/vvv6wwQKmmq/anjx48Xur6///5b2u7duzdcXV0VlVPtd587d052/7W0qAYvaZI3eH7o0KF6l7l27Vq+PKqfy5MnT3D79m2d9Za2gvb/LS0tdU7mAMj7xoDm/vGOHTuk7datW8PDw0Nn3QMGDEC5cuV05iss1QCnTp06wcnJKV+evMFSGzZs0GuSB+DVfXEl318iIiIiIiIiIiIiej0xKIqIiBQpX7483N3dFb1UH+bmnaG9S5cuio5XtWpV1KlTR2M9pUFJQBQAVKxYUZZ+9uxZvjwXLlyQDdDt1KmTorpdXFzwzjvvKMpbEM7OztK2ptlDS0JBvzdly5aFr6+vxno0yTtIQBPVz1bd50pERPS2CQoKkoJHjIyMMGTIEI15VQduhoaG6j1QsSB/r4UQeP78ebHVX5T9AWNjY1mQfFH3xUaMGIFbt27h888/1xmMn5qainXr1qFp06YYPXp0viCgXDk5OTh27JiU7ty5s8bAq8Io6s9GNWhJXVCU6r527drByMgIbdq0AfDq2pw4cUKW/8KFC3j69KmUVp1ooLBU++dCCMTGxioq16pVqyJrQ0G9ePEC3bt3l9psbGyMjRs3yn7nERHR26dr166oUKECgFeT4qgGFuddUVQ1gOp1oRqgM2fOHCxbtgwZGRkFquvq1auIj4+X0rmraCnRsGFDKWBMCIHTp08XqA1FxcTERNFqoXmDWpo3b66zTO73JZe6fl7eYPBevXqV6oRPShS0/9+4cWNFwYJK7lE/evQI0dHRUlrpPWozMzPZPdjicPToUVy/fl1KawtaUv2t+eLFC9nEDUrUqlUL9vb2+jeSiIiIiIiIiIiIiF4LDIoiIiJF5syZg1u3bil61a5dWyp348YNadvGxgZVqlRRfEzVWfhV6ykteR/Aa2JpaSlLq5uZMu+MpvXq1VPcjoIERd25cwc//PADevXqhRo1asDOzg4mJiYwMDCQvWbPni2VKc2gn7yft+rKErqofm9iYmKkWem1Kchnq++Mo0RERP81QggEBgZK6XfffVcWwJHXkCFDYGxsrLasEkXZFyuq+pXUnZOTg0OHDmHcuHHw9vZGxYoVYWVlBUNDw3x9MdWBkMXRF3N2dsYvv/yC2NhYHDp0CNOnT9c44zrw6nNavnw5unfvjuzs7Hzvx8bGytrZpEmTIm8zUPSfjWrQUlRUFO7duyd7PyQkRNrODaBSDaRSfT9v2tHRUVHfPjk5GevXr0dAQAAaN24MJycnmJub5/tO1KhRQ1ZO6feievXqivIVl+zsbAwYMAAXL16U9i1atAgdO3YsxVYREdHrwNjYWLY6kGqf8O+//0ZqaiqAV/2K4pwYqKBUV8XMzMzERx99BGdnZ/j7+2PVqlV6Bf5HRETI0nXr1lVc1sTEBLa2tlL6wYMHissWh9x7jbrkXQleUz9UWxl1/TxXV1fZpEqRkZFo1qwZ6tevjylTpmDv3r2KJ0sorOLu/7/J96j1obpqnI2NDXr27Kkxb8OGDWXt0Xdl4tLuOxMRERERERERERFR4TAoioiIilViYqK0Xb58eb3Kqj4Ufx1W5SlTpkyBygkh8u1TvS6AftfG0dFRcd6nT58iICAA1atXx1dffYX/Y+++45q6/v+Bv8IGQRkiggMUwVn3FhVHRXBbd+u2Wv3U1tVlW0dtq7XaOmrdilqriAP3qopbVFQUcYsLFFBBEJV5f3/4435zIeMmJAx9PR+PPB45yTnnvm8SyMm5Z+zYsQO3b99GYmIiMjMzNZZ98+aN7OMYmvLrY2FhgVKlSskum3swRe7XWhV93ltV7ysREdH75MiRI7h7966Y1rRyN/C2vdOxY0cxHRgYqHKijTqGbIsZqn5tdR87dgwffPAB2rVrh4ULF+L48eOIjY3Fy5cvtZY1ZlvMzMwMbdq0wbRp07Bv3z48efIEjx49wrp169C1a1eYmEi7i/777z/MmjUrTz3KuyMB0DgpLj8M/d40a9ZMUqfyzlDx8fG4evUqgLeDaytVqgRA8+5SymlfX18oFAqNsS1btgwVK1ZE//79sWbNGly4cAHx8fGy3nO5n4uSJUvKymcs48aNw969e8X0+PHjJYPIiYjo/aa8A9TmzZuRkpICAFi1apXKPEVJnz59MGbMGMljz58/x9q1a8U+uAoVKmDYsGE4ePCgxjZJ7rZUgwYN8kya0XSLj48Xy8rp/zImfdvqhmznLV++PM/klitXrmDWrFnw9/eHo6MjGjdujOnTp0t+xxhSQbT/i2Mfta5SUlIQHBwspvv06aP1vJV3izpT6dfhAAEAAElEQVR58qRklyltCrvtTERERERERERERET5w0lRRERkVC9fvhTv29jY6FRWeRXQjIwMpKWlGSyuwpZ7ZU5ra2vZZXOvjqpOQkICWrVqhTVr1uS56G1qaooyZcqgQoUK8PT0FG/KK8wW5qQfQ31uctdFREREhqO8+nbJkiXRvXt3rWWUB6rFxMRg//79xgitSAgJCUH79u0RFRWV5zkbGxu4urqiUqVKkrZYzk5aQMG3xcqVK4dPPvkE27dvR0RERJ6dCubMmZNnoGbOAOYcuVejL6qsrKzQrFkzMa08qUnVLlHA251LnZycAABhYWHibqRZWVk4fvy4mE95FypVvvrqK4waNQrPnz/P85y9vT3KlSuHypUri58Jd3d3SR65nwvlz1JBmz9/Pv766y8x3bVrV8yZM6fQ4iEioqKnWrVq4nfxq1evEBQUhMjISJw7dw7A2+/q/v37F2aIGi1atAgbN25E9erVVT7/6NEjrF69Gh06dED9+vVx5swZlfkMuQiUnJ3S33XlypXD+fPnMXHiRNjZ2eV5Pjs7G+fOncO0adPg7e2NESNGIDk52WDHL27tf6Bg+qj1sXHjRkls2hbgAKQ7EwO67RZVmG1nIiIiIiIiIiIiIso/9vISEZFRKQ+M1PXivPKFT3Nzc1haWhosrsKW+6Lx69evZe+GlPtitTrjxo2TXIRv1qwZRo8eDR8fH1SsWBGmpqZ5ykydOhU//fSTrPqNyVCfm9x1ERERkWEkJSVh69atYjo5OVnniczA290AAgICDBlakZCQkIChQ4ciIyMDwNtBdiNGjECvXr1Qv359yUR0Ze7u7njw4EFBhqpSrVq18N9//6FatWp48eIFgLfv+cmTJ9GuXTsxX+52VnGajN6mTRtxApScSVEKhQKtW7fG1q1bkZGRgRMnTqBDhw44f/68ZDCtpklRBw8elEwOKl26NL744gt07NgRtWrVUjkINTo6GpUrV9bvJAvBrl27MGHCBDFdr149/Pvvv3l2HyMiIho+fDhOnz4N4G2bMGenRgDo2bMn7O3tCykyefr27Yu+ffvi3LlzOHDgAI4dO4YzZ87kmWRz6dIltGrVCrt27UKHDh0kz+VuP3t6euodj7r25fumVKlSmDNnDqZPn44DBw7g8OHDOHnyJCIiIpCdnS3my8rKwsqVK3H27FmcOHEi3zsFFdf2v6o+arnk9lHrI/eEJh8fH53rWLt2LX799VdOeCIiIiIiIiIiIiJ6D7AnmIiIjEr5gm98fLxOZZXzqxsIoVAodI6pKKycmvtCeHx8PMqWLSurbEJCgtY8T548wYYNG8T0J598gjVr1mgdjGjIFWrzQ/n1SU9Px4sXL2RPGsv9OeOgECIiIsNbv359nl2D9LFjxw4kJCTA2dnZAFEVHatWrRLbVSYmJti1axf8/Py0lisqbTEAKFu2LAYOHCjZ8ef69euSSVE5OyflePz4cYHFl1/Kk5diY2Nx48YNVK1aVTJBSnlSVE46ZzLg4cOH0aFDB0l+V1dXVKtWTe0x//jjD/G+i4sLzp8/j/Lly2uMsyh9JrS5dOkS+vfvLw44LleuHHbu3GnUXQSIiKj46tu3L7788kukpqbi9OnTiIyMFJ8bOnRovurWp78Q0K/PsFGjRmjUqBG+//57ZGVl4dy5cwgJCcHq1avFPqqMjAwMGzYMd+7ckSz6VLp0aUldx48fh6urq16xq1KQr0NRU6JECfTo0QM9evQA8LZN9d9//2Hjxo0ICQlBVlYWAODKlSuYMWMGfv/993wdr7i2/1X1Ucslp49aH1evXkVYWFi+64mLi8Pu3bvRrVs3A0RFREREREREREREREUZl2klIiKj8vb2Fu8nJSXptPLl5cuXVdajTHlFVbkX7OPi4mTHYCxVq1aVpJUHfmgjJ+/hw4chCAKAtwMgfvvtN1mrs9+9e1d2HMaU+/2OiIiQXVb5c1OuXDm9dq0gIiIizZRX7ra1tYWnp6dOtxwZGRlYt25dYZyCUR06dEi8/+GHH8oaEPn06dM8OwsUtpo1a0rSObtG5ShXrpxkIOX58+cLJC5DaNKkiWSyzuHDhxETE4Nbt24BeNted3Nzk5RRniSVMxlKeVKUpl2isrOzJbtQjRs3TuuEKKDotM+1iY2NRefOncXdwkqUKIGdO3eiXLlyhRwZEREVVba2tujdu7eYTklJAfB25xzlSdj60Ke/MD09HYmJifk6rqmpKZo2bYpZs2bhzp07aNWqlfhcTEwMQkNDJflzT6ZW3i3LEHL3iRWnvlNDs7e3R69evbB582acPHlSskPnP//8k+/6i2v7P/dn0NB91PpQ/q1pamqq829N5fc2945TRERERERERERERPRu4qQoIiIyqqZNm0rSe/fulVXu3r17koEAuevJobyDVExMjKy6z5w5IyufMdWrVw/m5uZi+sCBA7LKPX78WDLpRx3l18LZ2TnPgE5V0tLScOLECVlxKMcOQFwN3lD0/dy8evVKMsBE3eeGiIiI9Hfx4kVcvHhRTP/444+4ffu2Tjfl7+h3caCaclusTp06ssooT64pKnLvBubo6ChJKxQK+Pj4iOl9+/YVm50FzM3N0aJFCzF9+PBhrROcqlevLu7ueuHCBSQkJODUqVMay+R49uwZ0tLSxLTcz4XyAFtjyk/7PjU1FZ07dxY/9yYmJli/fj3q1atn0BiJiOjdM2zYsDyPDRkyRO8djnLo018YHh6OzMzMfB1Xma2tLebPny95LCoqSpKuX7++ZGf0nTt3Guz4gPR1AOS9FhkZGbhw4YJB4yhqmjRpgpEjR4rpJ0+e5HtCXHFt/5ctWxYVKlQQ03L7qNPT0/NM8jOE9PR0yaIZHTp00Pm35pdffimW37Nnj1F2szV23zgRERERERERERER6YaTooiIyKiaNWsGJycnMb106VJxByNNFi9eLMnXuXNnlfmUV7OMiIjIM3BTldWrV2vNY2xWVlb48MMPxfTWrVvx7NkzreVWrFgh6yKr8munPPhSkzVr1iApKUlWXltbW0k6964B+VWpUiXJzgRr166VNcB2zZo14ur0gPrPDREREelPeRKTQqFAv379dK5jwIAB4v2oqKgiMWndkJTbYnLapwDyDJotCk6ePClJV6lSJU8e5ff/xYsXWLJkidHjMhTlSUyhoaGSCUjKu0KpKpOVlYXZs2dL2qjqygDI8xtIzufi2bNnBbaTmr7t++zsbAwYMEAyUXL27Nno1q2bQeMjIqJ3U8uWLeHn54c6deqItyFDhuS7XuX+wtjYWDx69EhrGWP0F+beKT4jI0OSNjU1Ra9evSQxxMfHG+z4uXcBCgsL01omODhY0rf2rtL23uiqOLf/u3TpIt4/fvw4bty4obVMUFCQ7H5kXezYsQNPnz4V08q/G+VSLpOVlYU1a9YYJDZlxu4bJyIiIiIiIiIiIiLdcFIUEREZlZWVlWTV14sXL2LRokUay1y+fFlyUbhGjRrw9fVVmbdJkybi/dTUVGzcuFFj3Zs3b8bBgwdlRG58yiuSpqSk4Ouvv9aY/+7du/j9999l1V2xYkXx/osXL3D8+HGN+aOjo/HNN9/IqhsAPDw8JOnIyEjZZeUaM2aMeD82NhZTpkzRmP/Ro0eSPI6OjnoN0iYiIiL13rx5g3///VdMt2jRQtLukKtPnz4wNTUV06tWrTJIfEWF8muyd+9eZGVlacw/b948yY5DhvTbb79h69atshYmUHbq1Cls27ZNTNvZ2aFVq1Z58vXp00dyvj/++GOx2V1AeRLT06dPsWnTJgBvJ/up2/VJuYzy75qKFSuicuXKao/l5OQEGxsbMb1r1y6NsWVnZ+PTTz8tsEHJ+rbvJ06ciB07dojpkSNHYuLEiYYMjYiI3nH79u3DpUuXxFvu7yR9KPcXAm8XGdLkzJkzsiZFvXr1SqdJSxEREZK0qnP75ptvxHZxSkoKBgwYoPMEHXWTcCpUqCDZPV7b65CYmIhvv/1Wp2MXFQ8fPtTa5lam/N6UKFECzs7O+Tp+UWr/6+rTTz8V72dnZ2Ps2LEaF+V69uwZvv/+e6PEorwAh7W1Nbp3765zHR988AFq1aolpo3xW7NUqVJwcHAQ08boGyciIiIiIiIiIiIi+TgpioiIjO7rr7+Gi4uLmB43bhyWLVumMm9YWBj8/f0luxvNnTtXbd1t27aV1P3VV1/h8uXLKvP++++/GDhwIBQKha6nYBRdu3aFj4+PmF61ahW+/fZbZGZm5sl79epV+Pn5ISUlBSYm2r++27ZtCzMzMzE9bNgw3Lt3T2XekydPolWrVkhKSpJVN/D2wq/yarOzZ8/G3bt3ZZWVa/jw4ZLdoubOnYvp06erHFRw48YN+Pn5SVYS/fXXX2FlZWXQmIiIiN53W7duRWJiopjWZ+VuAHBxcZFMLtm4cSNSU1PzHV9R4efnJ96/desWxo4dq7KNl5GRgV9++QUTJkwAANltMV1cuXIFH330ET744AP88ccfePLkicb8giDgn3/+gb+/v6TdNXHiRFhYWOTJb2ZmhqVLl4pt7FevXqFt27YaFysQBAGhoaGSnVMLQ4MGDVCyZEkx/fr1awBvB1KWLl1aZRnlz21OfgBqJ1HlMDU1Rfv27cV0YGAg1q5dqzLvs2fP0LdvX2zbts0onwlVatSoATs7OzE9depUxMXFaSyzatUqzJs3T0y3b99e6wIYREREBcHb2xsNGjQQ07/99ptkR0hlBw8eREBAADIzM7X2GcbHx8PDwwNjxozB2bNnNeZ98OCBZLKJtbW1pI2Yw8vLCz/++KOYPnToEFq2bIkrV65orD8rKwuhoaEYNGgQ+vTpozZf//79xftHjx7FzJkzVea7c+cO2rZti4cPHxaZvlNdrFy5ElWrVsX8+fO1tnc3bdokmXzTtWvXfJ9zUWr/66pu3br4+OOPxfTBgwcxZMgQlb/PHj58iICAADx8+NDgsT969AgHDhwQ0126dMmzI5Ncyp/7W7duaV0wTB/Kky+XLFmCS5cuGfwYRERERERERERERCSPmfYsRERE+VO6dGmsXr0aXbt2RWZmJrKysjBq1CgsWbIE3bt3R7ly5ZCUlITQ0NA8K2l++eWX6Nixo9q6zczM8MMPP2Ds2LEA3q7w3qhRI/Tr1w9NmjSBpaUl7t+/j127duHixYsAgBkzZkgGGxQWhUKBFStWoEmTJnjx4gWAt4M0tmzZgt69e6Ny5cpITU3FqVOnEBISgvT0dLi4uKBHjx5YsmSJxrrLlCmD4cOHY+nSpQCA27dvo2bNmujTpw8aNWoEKysrPH78GP/99x9CQ0MBAOXLl0eXLl2wePFiWfEPGzZM3N0qMjISnp6eqFChAhwcHCQDCfS9IGxpaYl169ahVatW4gr506ZNw/r169G7d29UqlQJqampOHPmDEJCQiSr4nbv3h2jRo3S67hERESknvLgQTMzM/Tu3VvvugYMGCDu4JmSkoLg4GAMGTIkvyEWCSNGjMDMmTORkJAAAFi8eDH+++8/9O7dG56enkhLS8PNmzexbds23L9/H8DbHXb2798vpg3t6tWrmDhxIr766ivUrFkTTZo0gaenJ5ycnGBmZobExERERUVh//79ePTokaSsj4+Pxl0DOnbsiGnTpmHq1KkA3u5U2r9/f0ybNg2dOnVC5cqVYWNjg+fPnyMyMhKHDx/GgwcPjHKeujA1NUXLli2xe/duyeOaJjhVrlwZ7u7ued4n5clS6nz77bfYuXMnBEFAdnY2Bg8ejJUrV8Lf3x9ly5ZFcnIywsPDsX37dvH3wYwZM4y2Er8yc3NzDBw4EH///TcA4MiRI3Bzc4O7uzvs7OzE9r2bmxv27NkDADh27JikjqioKMnCCdqUL19e/C1CRERkaNOmTUOXLl0AvN1JqUOHDujevTt8fX1RokQJPH78GPv37xcnSwwfPhz//fef1rbY69evsXjxYixevBgVK1ZE8+bNxQnVFhYWSEhIwLlz57Bz505JX9W0adNQqlQplXVOmTIF165dQ1BQEIC3i0bVrl0bzZs3R6tWrVCxYkXY2NggOTkZT548weXLl3H69Gk8e/YMAFROtsoxYcIELF++HMnJyQCAyZMnY/v27ejRowfKlCmDxMREnDp1Cjt37kR6ejrq1KkDLy8vbN68WeYrXXTcuXMH48aNw4QJE9CwYUM0btwYlStXhoODAzIyMnDv3j0cOHAA58+fF8uUKFECP//8c76PXRTb/7r4888/cezYMTx8+BAAsG7dOhw6dAj9+vVD1apVkZGRgfDwcAQHB+Ply5ewsbHB//73P/z+++8Gi2H16tWSHar0XYADeDspSrkNvXLlSrRs2TJf8eU2bNgw7Nu3DwAQGxuLevXqoWzZsnB2dpZMGNuzZ49kxzYiIiIiIiIiIiIiMjxOiiIiogLh7++Pbdu2oW/fvnj16hUA4OLFi+JEJVUmTJiAOXPmaK17zJgxOHr0qHixPj09HWvXrlW58vro0aPxww8/FIlJUQBQtWpV7NmzB/7+/uLghNu3b6tctdXBwQHBwcFqV7bN7Y8//sClS5cQFhYG4O2q/YGBgQgMDMyT183NDdu3b8eOHTtkxz5+/HgcOXIEe/fuFR97+PChePHcEOrVq4dDhw6hU6dO4i5Qt27dwq+//qq2TL9+/dSuuk9ERET6i46OxpEjR8T0hx9+qHY3HTl69uyJ0aNHi4NFV65c+c5MirKzs8PmzZvh7+8vtn01tWG6du2KhQsXwtvb2+Cx2NjYSNLZ2dm4cuWK1t0HcvTp0werVq2CpaWlxnxTpkyBo6MjJkyYgIyMDABvd/O8ceOGfoEXkLZt2+aZFKVtglObNm3ytKm17RQFAM2aNcPvv/+OSZMmiY8dO3Ysz+Qi4O2uATNmzMCAAQMKZFIU8Han1bCwMISHhwN4+1mJjo6W5ElKSlJbPjY2Vqfjqdo9gYiIyFA6d+6M8ePH488//wTw9ntt69at2Lp1a568Xbt2xd9//61zW+zBgwd48OCBxh0ygbc72+csLKSKQqHAhg0b4OXlhV9//VWcGHLq1CmcOnVKaxympqZqn3Nzc8OqVavQr18/8bs3LCxM7C9UVrVqVWzfvl2c6F5cZWdn4+zZs1p383J0dMT27dtRuXLlfB+zKLX/9eHs7IxDhw7B19dXbNPFxsbijz/+yJPXysoKgYGBBt3pVxAErF69Wkzb29vD399f7/oqVaqEpk2b4syZMwCA4OBgLFiwQLJLbH717t0bI0aMwIoVK8THnjx5kmensvT0dIMdk4iIiIiIiIiIiIhUM9GehYiIyDA6d+6M69evY9CgQbC2tlaZR6FQoEWLFjh69Cjmzp0r2XFIHRMTE2zcuBE///wz7OzsVOapUqUK/v33X3Hl86KkefPmiIyMRLdu3SSrSOYwNTVFQEAAwsPDdVrR0sbGBqGhoZg0aVKewbA5SpQogaFDh+Ly5cuoX7++TnGbmZlh9+7d2Lx5M/r06QMvLy/JKvKG0rhxY9y4cQNffPGFxgvXtWvXxtatW7FhwwaYm5sbNAYiIiICVq1aBUEQxHR+Vu4GgJIlSyIgIEBMnzhxoshPoNFFq1atcPbsWY2TZTw9PbF48WJs374dFhYWRolj2bJlOHfuHH744Qc0b95c6+QmALC2tkafPn1w5MgRBAUFoUSJErKO9fnnn+PatWv4+OOP1bY/gbft2xYtWmD58uWyz8NYcr8/pqamaN26tcYyuSdN5eyYKsfEiRMREhKicQBs06ZNcejQIUyePFlWnYZSqlQpnDp1Stzl18PDAyVKlDB4+56IiKig/PHHH1iyZAnKlCmj8nk3NzfMmzcPISEhstpirq6uWL58Obp16wYHBweNeU1MTNC+fXscPXoUs2fP1lq3QqHAjBkzEBkZiY8//hi2trYa89vZ2aFLly4IDAwUd5hS56OPPsJ///2H2rVrq3y+RIkSGDNmDMLDw+Hu7q411qJo4MCBmDJlCho1agQzM83rQTo4OODzzz/H9evX4ePjY7AYikr7X19eXl64cuUKhgwZoja2li1b4tSpU/naMViVw4cPSybjf/TRR/l+fZR/r7569Urr5EV9LF++HAcOHMCgQYNQo0YNlCxZUmX/PhEREREREREREREZl0JQHtFERERUQF6/fo1jx47h3r17ePbsGWxtbeHq6oqWLVuibNmyetf75s0bhIaG4tatW3j58iXKli2L6tWro2nTpgaM3ngeP36M0NBQPHr0CObm5ihXrhxatGgBNze3fNWbnJyM48eP49atW3j16hWcnZ1Rvnx5tG7dWuOA1aImIyMDJ0+exO3bt/H06VNYWVnBxcUFzZo1g4eHR2GHR0RERKTSnTt3cPLkSTx+/BimpqZwdXVFtWrV0KBBgwKPJS0tDdevX8ft27fx+PFjpKSkQBAE2NnZwcnJCTVr1kT16tXzPQgxLS0NJ0+eRHR0NBISEgC8XfG9SpUqaNCggdaBxO+67OxsXLhwAeHh4ZLfQw0bNkSlSpUKOzwiIqJ3SmZmJk6ePImrV68iKSkJzs7OqFKlClq1aqVxlyVNBEHAzZs3cePGDTx48ADJyclQKBQoWbIkPD090bBhw3ztqpqRkYGwsDCxDywtLQ12dnZiO7J69epaJ/+ocvnyZZw9exYJCQmws7NDxYoV0aZNG7ULTRVHr1+/RkREBO7cuYO4uDi8evUKVlZWcHJyQq1atVCnTh2jT0gqSu1/fSQmJuLQoUN48OABBEFAuXLl0KhRI3h6ehZ2aEREREREREREREREeXBSFBEREREREREREREREREREREREREREREREREVKyaFHQARERERERERERERERERERERERERERERERERkS44KYqIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIihVOiiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiKiYoWTooiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIioWOGkKCIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIqVjgpioiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiKFU6KIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIqJihZOiiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiKhY4aQoIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIipWOCmKiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIoVTooiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiomKFk6KIiIiIiIiIyKCys7Nx4cIFbNmyBcuWLcPMmTMxZ84cLF++HNu3b8e9e/cKO0RRYGAgFAqFeNNEOV9gYGDBBEhERET0jilObUXg/WsvvgvnUBy8fv0aixcvhr+/P8qXLw9ra2vJax8SElLgMU2bNk08voeHR4Efn4iICADS09Nx8uRJBAUFYdGiRfjll18wf/58rF27FmFhYXjz5o2senRpwxW0e/fuSWILDQ0t7JC0GjJkiBivr69vYYfz3iiOnxVD8fDwEM972rRphR0OERFRofH19RW/E4cMGVLY4ZCR3bp1C1999RUaN24MR0dHmJubi++/vb19YYdHVKSZFXYARERERERERPRu2LVrF1asWIGjR48iKSlJY157e3v4+fmhV69e6NSpE6ytrQsmSCIiIiIqFGwrEr314MEDtG/fHrdu3TJK/cqDRrt37466desa5ThERESGIggCNm3ahMDAQBw7dgyvXr1Sm9fMzAw+Pj4YOHAg+vTpA1tb2wKMtHi7d++eZNL7uHHjOLDSSMaMGYPFixeLaTs7Ozx58gQ2NjaFGBUREVHRFxgYiKFDh4rp1atXvxMTgS5duiRZAMcYE34L4hj6SEpKwrx588T0kCFDuBiPGmvWrMHIkSORnp5e2KEQFUucFEVERERERERE+XL8+HGMHz8e4eHhssskJSUhKCgIQUFBcHFxwddff43Ro0dzwCsRERHRO4ZtRSKpAQMGSCZEmZiYwNXVFVZWVuJj+RngPX36dPG+h4cHJ0UREVGRdujQIYwfPx5XrlyRlT8zMxOhoaEIDQ3Ft99+iylTpuCzzz6DmRmHP2lz7949STthyJAhnBRlBG/evMGGDRskj6WkpCA4OBiDBw8upKiIiIioMF26dEnSDjPWpChjH0MfSUlJkrh8fX05KUqF69evY/jw4cjKyhIfK1GiBJydnWFqagoAKFmyZGGFR1QssFeAiIiIiIiIiPS2aNEijBs3DpmZmZLHvb290aZNG1SsWBFOTk5QKBR48uQJYmJicPjwYdy+fVvMGxcXh4kTJ8Lb2xudO3cu6FMgIiIiIiNhW5FIKiIiAidPnhTTQ4cOxbx58ziogYiI3ksLFizAhAkTJAP/FAoFateujTZt2sDNzQ1OTk5ITk5GXFwcLl68iNDQUKSlpQEAEhISMHbsWPj4+HASMBUZW7ZsUbkz7sqVKzkpioiIiIhUWrp0qfi7yMzMDJs3b0bXrl2hUCgKOTKi4oOTooiIiIiIiIhILzNmzMCUKVPEtEKhQJ8+fTB16lRUr15dY9lbt25hyZIlWLJkCV69emXsUImIiIiogLGtWDwJglDYIbzTzpw5I943MTHBwoULUaJEiUKMiIiIqHCoaiv2798fM2bMQOXKldWWS01NRVBQEKZPn44HDx4URKgG5+HhUezaXIGBgQgMDCzsMIqFlStXivcrVaqE6OhoAG930L158ya8vb0LKzQiIiIqhkJDQws7BCoAyn2GPXv2RLdu3QoxGqLiyaSwAyAiIiIiIiKi4mfv3r2YNm2amLa2tkZwcDA2btyodZArAHh5eWHu3Lm4d+8ehg8fbsRIiYiIiKigsa1IpNrTp0/F+2XLluWEKCIiei8dOHBA0la0sLBAUFAQ1q9fr3FCFACUKFECw4YNw61btzB16lSYmHDYExUdd+/elQxcXrhwIdzc3MT0qlWrCiEqIiIiIirqlPsMq1SpUoiREBVf3CmKiIiIiIiIiHTy8uVLDBo0CNnZ2eJjwcHB6NSpk851OTs7Y8WKFfDz84O9vb2sMnfv3sXVq1dx//59JCcnw8LCAo6OjqhRowYaNGgAc3NzneMwNkEQcOHCBURFRSE+Ph6CIMDFxQX169dHzZo1DXKM9PR0HD9+HPfv30dcXBxsbGzQrVs3eHh4GKR+IiIiIjkKu60IsL2ojrHbi8Y4hxcvXiA8PBw3btzAixcvkJ2dDRsbG7i6uqJKlSr44IMPYGFhYZD41cnOzsa5c+dw7do1xMfHw8zMTDwvOZP8lGVkZIj3i+LnUJ3s7GycOHECt27dQnx8POzt7VG9enX4+PjAzEz/y82ZmZkICwvD7du3ERcXBzMzM5QtWxbNmjVDpUqVDHgGRERUVLx69QoDBw6UtBXXr1+PXr166VSPhYUFpk2bhqZNm8LOzk7nOM6ePYtr167h8ePHsLW1RZUqVeDr6wsrKyud68otNTUVx44dw6NHj5CQkIBSpUqhT58+cHZ2zle9MTExOH/+PB48eIDk5GSYmprCzs4O5cuXR7Vq1eDt7Q2FQpHv+I3JGK97QbSj5Vq1apW4C5irqys6duyITz75BLNnzwYArFmzBj///HO+2k/Krly5gsuXLyMmJgbW1taoVKkS2rZtCxsbG4PUf/78edy4cQOPHz+GIAjw8fFBs2bNVOZNT0/HlStXcP36dcTFxeH169coWbIkypQpg8aNGxu0bff8+XMcPXoUDx8+xJs3b1CmTBn4+PjoPYA4ISEBly9fxp07d5CYmAhBEODo6Ah3d3c0b95cr/8x6oSHh+Pq1auIjY2FlZUVatWqBV9fX42fiVu3buH06dOIjY2FhYUFKlWqhA8//BC2trY6H/9d+D9CRCRHeno6QkNDce/ePTx79gyOjo6oW7cuGjVqpNek+rt37+LChQuIiYlBSkoKzM3NUbJkSVSsWBE1atRgH0YBu3r1KiIiIhAfH4+0tDS4uLigVq1aaNCgQYF+jyUnJ4vt/ufPn8PBwQFubm5o1aoVHBwcdKqruPYZEhUpAhERERERERGRDubOnSsAEG+fffaZUY+XmZkp7NmzRxgyZIjg5uYmOXbum62trTBu3DjhyZMnsupevXq1pLwmyvlWr14tq/7k5GTh+++/F1xcXNTG7OXlJfz777+y6hs8eLBYrnXr1oIgCEJqaqowYcIEwcHBIU/dq1evFm7cuCF57O+//5Z1rBz5LU9ERETvl4JuKwoC24vK9GkvFrVzEARBuHPnjtCvXz/B0tJS4/tpaWkpdOjQQTh69KjsuuVKTU0Vpk2bJjg7O6s9vqenp7By5UohKytLbT2tW7fWeA7a3hM5pk6dqtMxAAhHjhxRW4e7u7v4+MKFC4Xy5currMPZ2VlYunSpzvHGxcUJY8aMEezt7dXGV69ePWH//v06101EREXbvHnzJP/vBw4caJTjqGvDbdiwQfD29lbbTvzll1+EzMxMrfUrf78PHjxYEARBePr0qTB06FChRIkSGr93o6OjNX4n53bkyBGhZcuWWr/bHRwchI8//lh48OCB2ljl3nJT1cYsjNddmTHaoPmRmZkplCtXTjz2pEmTBEEQhKtXr0pi2rFjh+w61X1WDh48KNSrV0/t6zlp0iTh1atXWutX934tXrxYqFy5cp66cz7rORISEoRFixYJ7du3F6ytrTV+pqpVqyasXr1ayM7OlnXu7u7uYtmpU6eKx/vkk0/U/kbw8fERIiIiZNUfHh4ufPXVV0KNGjU0xm1qair06NFDuHTpkqx6jxw5IikfHR0tCIIgbNu2TahevbrKY7i5uQnBwcF56jp79qzQokULlWWsra2FX3/9VePvkNxx5ef/CBFRQcn93aSpj0RV+yQjI0OYOnWq4OTkpPL/nIeHh7B161bZ8WzevFntd67yrWzZssLIkSOFFy9eSMorf5/JuSn3x+RQ1e405DF0bZvm0NZnqvz+yL3lfG+q8ubNG2HOnDlCxYoV1ZYvV66c8Ndff+ncrtRVVFSU0K1bN8Hc3FxlHGZmZoK/v7/Gdknu113OjYg0418JEREREREREcmWlZUlubhrampq9Atk+nQKurq6CufOndNatzEHuZ4+fVrjRfnct969ewvp6eka68zdwf/gwQOhWrVqauvMidPX11d8rEGDBlpjV/bVV1+JZW1sbISkpCSdyhMREdH7ozDaioLA9qIyfduLRekcDh06JNjY2Oj0fn7//fdaY9XFrVu3VA4EVXdr06ZNnoEvOYrrpKj09HShR48esurKGfQrx44dOwQ7OzvZcY4fP17n14OIiIqm7OxsySBGhUIh3LlzxyjHUtWG+/zzz2V99/Tp00frxI3cg1MvXbqkcXK+vpOiZs6cqfN3/MGDB9XGKveWW34mRRnydc9hjDZofu3evVtyzMuXL4vPNWzYUHy8W7dusutU9VmZN2+eYGJiovWca9WqJcTHx2usP/f7lZGRIXTv3l1tnbkHYuvTBu3WrZvw8uVLreeee1LUpUuXJL811d3s7OyE06dP61S/nJuFhYWwatUqrfWqmhT1/fffyzqG8mJk69atUzvQWvk2cuRIrTEZ4v8IEVFByc+kqKSkJKF58+ay/s/99ddfGuPIzs4WRo8erfP/z1u3bknq4aQo3V4/dZOibt68KXh5ecmup1WrVmr76fJr6dKlgpmZmaw4TE1NhXnz5qmsh5OiiAzPMPvxEhEREREREdF7ISIiAjExMWK6Y8eOqFChQoEd39LSEs2bN0fDhg1Rvnx5lCxZEikpKYiMjMTOnTvx+PFjAMDjx4/RqVMnREREoGzZsgUWX44jR46gc+fOePXqlfhY1apV0blzZ3h6esLMzAw3btzApk2b8PDhQwBAcHAwFAoFgoKCZB0jPT0dvXv3xvXr16FQKNC2bVu0bdsWZcuWRWJiIsLCwmBhYQEAGDVqFEJDQwEA4eHhuHTpEurWrav1GBkZGVi7dq2Y7t27N0qVKiXzVSAiIqL3TWG3FQG2F5Xp0l4sKucQHx+Pnj17Sups3rw52rRpg4oVK8LCwgIpKSm4f/8+Ll68iBMnTiA9PV3vc1Dl4cOHaNmyJZ48eSI+5ubmhr59+6Jq1apIT0/HxYsXsXnzZqSkpIivxYcffojjx4/neU3LlSsHT09PAMDz58+RmJgIADAzM4O7u3ue45csWVLnmB0dHcVj3LlzR3y8TJkysLOzU1nG2tpaY52ff/45tm3bBgDw8fFBhw4d4ObmhpcvXyI0NBTbt2+HIAgAgDlz5qBt27bw9/fXWOe///6LQYMGISsrS3ysfv366NixI9zd3ZGVlYXIyEhs2rQJT58+BQD8+eefMDMzw+zZs7W8CkREVNRdvnwZDx48ENMffvghKleuXCDH/vXXX/HXX38BAOrWrYvOnTvD3d0daWlpOHPmDIKCgpCRkQEA2LRpE3x9fTF69GhZdScmJqJHjx6IjY2FmZkZAgIC4OPjAycnJzx9+hShoaEwNTXVOeb9+/fju+++E9MWFhYICAhAo0aN4OLiAoVCgaSkJNy8eRPnzp3DhQsXVNaT0xZ5/fo1YmNjxcfd3d1hZmbcYWPGeN0Loh2tj5UrV4r369Wrhw8++EBMDx48GOfPnwcA7N69G0+ePNHrN8jhw4fxyy+/IDs7G05OTujbty9q1aqF7OxsREREIDg4GElJSQCAyMhI+Pn54dSpU7CyspJV/6RJkxASEgIAqFWrFrp06QIPDw+kp6fj2rVrsLS0VFvW1dUVLVq0QN26dVG6dGmYm5sjLi4Op0+fxt69e5GZmQkA2L59O8aMGYM1a9bIPu+4uDh06dIFMTExsLW1Rbdu3dCoUSPY2dnh4cOHCAoKwrVr1wAAKSkpGDBgACIjI2FjY6O1boVCgbp166JJkybw8vKCg4MD3rx5g+joaOzbtw9XrlwB8Pa31fDhw1GxYkW0a9dOduxr1qzBL7/8AuDt30C3bt1QoUIFpKSk4ODBg9izZ4+Y98svv4Svry+ePHmCIUOGICsrC+XKlUOvXr1QtWpVmJiY4Pz581i3bh3S0tIAAMuWLUNAQAC6deum8viG+j9CRFTUZWdno3///jh16hQUCgU6dOiANm3awNnZGYmJidi7dy8OHTok5h83bhxatmyJ2rVrq6xv2bJlWLx4sZguUaIEunTpgvr168PJyQmCICAxMRHXrl3D6dOnxe+h3Dw8PGBmZoaUlBTEx8eLj+f04eRWvnx5nc+9II6hDxcXF3h6eiIzMxP3798XH3dzc1PbJ2Vubp7nsatXr8LX11fsJwKAChUqoFu3bqhWrRqsrKwQHR2NzZs348aNGwCAY8eOwd/fH0ePHjVoe3f58uUYNWqU5LEWLVogICAALi4uSEhIwP79+8Vr8llZWRg3bhwEQcC4cePynKvye3T//n2xveTg4ABHR0eDxU303ijkSVlEREREREREVIz8+eefkhWJ5syZY/RjRkdHC1WqVBGWLVumcZeitLQ04ccff5TEN2jQII11G2Pl/7i4OMlKpVZWVsLKlStVrnT66tUrYdSoUZK6165dq7ZuVatqlS1bVjh58qTG2NPS0oTSpUuLZT7//HON+XNs3bpVcqzjx4/LKkdERETvp8JoKwoC24vK9G0vFpVzUF5t3srKSti7d6/GeF+8eCEsXbpUWLlypazz0yY7O1to166dJNZhw4YJqampefLGxMQILVq0kOT95ptvNNafezcmY5D7HmqKLWf3AQcHB+HAgQMq8+/du1ewsLAQyzRq1Ehj/VFRUZIdwBwdHYUdO3aozJuYmCh069ZNzKtQKITQ0FDZ50JEREXT/PnzJd9Tv/32m9GOlbsNZ2JiIlhZWQnr1q1TmT88PFxwcHAQ87u6ugqZmZlq61e1+1LVqlWFq1evao1N7mr8ysfw9PQUbt++rbHehw8fCt9//70QFham8nlVO9jIpe9OUYZ+3Y3Zjs6P+Ph4ya4+f/75p+T5p0+fStpNcj/7uT8rOW00f39/4dmzZ3nyx8XFCb6+vpIyP/zwg9r6c79fAAQzMzNh6dKlsnbtmj59utCtWzfhyJEjQlZWlsbzaNasmeQ4hw8f1li38q4XOefdvn174fHjx3nyZmRkCMOGDZPUv2jRIo31161bV5gyZYpw7949jfk2bdok2eW0UqVKGs8199+ZQqEQX1NV1qxZI8n/0UcfiTvqjR49Wnj16lWeMpcuXRJKlSollqlfv77aeAz9f4SIyNj03Skq57vC3d1dOH/+vMr8K1eulNTdu3dvtXV7eHiI+Ro3bizExcVpjPv69evC2LFjhQcPHsg6L11o2ykqv8cw1k5R+a1fEN6252rWrCl5n2fOnKlyB9DMzExh+vTpkmP99NNPso+lzY0bNwRra2uxbhsbG2Hr1q0q8+7atUuwtbUV81pYWAgREREa68+9SyYR6Y6TooiIiIiIiIhItv79+0s6E48dO2b0Y6anp2u8GJ7bV199JcZnaWkpxMfHq81rjEGuQ4cOlXTOahvIKQiC8NFHH4ll3N3d1V5YzT3I1dzcXGsnao5JkyaJ5RwcHITXr19rLRMQECCWqVatmqzjEBER0furMNqKgsD2orL8tBeLwjm0bNlSzDNu3DjZcRvKrl27JK9Bjx49NA4ITUpKEry8vCSDSB89eqQ2f3GZFJVzLqdPn9ZY5rvvvpOUuXnzptq8bdq0kQwcuXTpksa6MzIyhCZNmohlfHx8ZJ8LEREVTR9//LHeAyJ1pWqyR3BwsMYyS5culeQ/ePCg2ry5J0U5ODgIMTExsmKTMzA0LS1NMDU1FfOEhITIqluTwpgUZejX3Zjt6PyYM2eOpA2lauB0jx49xDxVq1aVVW/uzwoAoV69ehr7dZOTk4Vq1apJBuGq+72j6v1avHixvJMWBFn9yzlevHgheHp6StrZmigPDAbeTvxJS0tTm//NmzeSAewtWrQwWOy7d++WxLJ9+3a1eXP/nQEQFi5cqLH+rl275inTt29fjWWUP3Pq2uHG+D9CRGRs+k6KAiCULFlSuHv3rsb6lfsuLS0thZSUlDx57ty5I6lXW/+FHJwUpd9vgNyTnJYtW6a1zMSJE8X8JUqU0LiAli569eoliWXbtm0a8+duP/j7+2vMz0lRRPlnAiIiIiIiIiIimeLj4yVpd3d3ox/T3NwcpqamsvNPmTIFNjY2AIC0tDQcPnzYWKHl8eTJE6xfv15MjxgxAh07dtRabsGCBTA3NwcA3L9/H3v27JF1vNGjR6N27dqy8o4cOVK8n5iYiK1bt2rMHxMTg/3794vpESNGyDoOERERvb8Ko60IsL2oiS7tRbmMeQ5PnjwR73t7exsgWt38/fff4n1ra2ssXLgQCoVCbf5SpUrhzz//FNOZmZlYtmyZUWMsKMOGDUPTpk015hk1apQkffbsWZX5Ll68iCNHjojpH374AXXq1NFYt5mZGRYuXCimT5w4gcjISG1hExFRERYXFydJV6pUqcCO3aFDB/Tq1Utjnk8++URsIwJAWFiY7Pp//PFHuLm56R1fbk+fPkVWVpaYLox2kSEY8nUv6Ha0LlatWiXe79ixI8qUKZMnz+DBg8X7N27cwMmTJ/U61vz582FlZaX2eTs7O8ydO1dMp6enY+3atbLqrlu3bp72nSaa4sitZMmS+P7778X0gQMHJJ9xbf766y9YWFiofd7S0hJDhgwR0+Hh4cjMzFSbX5fYAwIC0KpVKzG9d+9e2WVr1qyJ//3vfxrzDBw4UJI2NzeX/MaQU0bV38278n+EiEiub7/9Vmv7Uvl7Li0tDREREXnyKPdNAfz/WVjS0tKwaNEiMd2hQwd8+umnWsvNmDEDTk5OAIDU1FSsW7cu37HExsYiJCRETHft2hXdu3fXWCYgIEDSDt63bx/u3LmT71iISD1OiiIiIiIiIiIi2Z4/fy5JlypVqpAiUc/W1lYyeO/cuXMFduzNmzcjPT1dTI8fP15WOTc3N7Rv315MHzx4UFa5oUOHyo7Ny8sLbdq0EdMrVqzQmH/VqlXiRVMLCwsMGjRI9rGIiIjo/VQc2ooA24v5ZcxzUB4Qe+rUqXxEqbu0tDT8999/Yrpbt24oV66c1nIBAQGSQTe7du0ySnwFTc5nx93dHWXLlhXT165dU5lPeQCzhYWF1oGhORo1aoTq1auLabmfeyIiKpqePXsmSdvb2xfYseV8r9nY2Egmk6v7XsvNxMTE4P1mym0ioODbRYZiyNe9oNvRcp0+fRpRUVFiWnnyk7KAgAA4OzuL6ZUrV+p8rOrVq6Nly5Za8/n7+6NChQpieseOHbLqHzx4sMYFAfJL+X1ITU2V/Tfm7e2NZs2aac2n/BvvzZs3uHfvns4xqqMcuy6/HwcOHKj1Na1fv36eY7m6umosU6ZMGZQvX15MX79+PU+ed+X/CBGRXMqTY9Vp3LgxTEz+b9i8qu8i/v8sGg4ePChZgEtu28/a2hp9+vSR1JNf+/btk0y2HjNmjKxyyv1fgiAYZXI+Ef0fTooiIiIiIiIiItlSUlIkaVtbW1nlunfvDoVCofVmKMoXDWNiYgxWrzbHjx8X71euXBnVqlWTXbZx48bifTkr0dra2uq86r/yblGhoaG4e/euynyCIGD16tViulu3bpKL9kRERESqFJe2IsD2Yn4Y8xyUBwT+888/mDFjBlJTU/WMVDcXLlyQDLT19/eXVU6hUCAgIEBMX758Ga9fvzZ4fAXJ3NwcDRo0kJVXeeJYUlKSyjzKnxkfHx+ULFlSdiy6fu6JiKjo0retaAjadj/MIed7LbeqVauKq9Ebir29vWTS9YQJExAcHIzs7GyDHsfYDPm6F2Q7WhfKk5scHBzQpUsXlfnMzc3Rv39/Mb1p06Y8fxPa+Pn5ycqnUCjQoUMHMR0eHi7rs9O8eXOd4tFV7ok+cn+HyZkQBSDPggZy/4bl0Pf3Y5MmTbTmcXFx0bkMAMniBKrO9V35P0JEJIe7u7vWCaXA2wkzDg4OYlrV/8/q1avD2tpaTA8ePJiLtBQC5baflZUV2rZtK7usodt+ynVYWFjIjqV169aws7MzaCxEpB4nRRERERERERGRbModdwAKbIBijsjISEyZMkVcjd3e3h6mpqZ5Bswqr0RuyIuf2kRERIj3a9asqVNZ5Yufjx490pq/UqVKktXM5OjZsydKly4N4O3EJ3Urkh46dAjR0dFi+tNPP9XpOERERPR+Kuy2IsD2ojJ92otyGPMcRo4cKZkAN2XKFJQtWxZ9+vTB0qVLERUVBUEQ9Ihau5s3b0rSderUkV1WefJZZmampC1dHDk6OsLc3FxWXuUB7er+5gvyc09EREVX7rbiy5cvC+zYypMHNJHzvZZblSpV9IpJm88++0y8n5ycjD59+qBChQr47LPPEBQUVCy+Fw35uhfF9kRqaiqCgoLEdN++fWFpaak2v/IuUrnLyvHBBx/olTc1NVXWeev7WU5PT8fOnTsxatQoNGvWDGXLlkWJEiXy/AbL3b6U+ztMn88RIO9v+PHjx5g/fz569+6N6tWrw8nJCRYWFnliV+4f1+X3o5zYS5QoIUnnniQlp5y6c30X/o8QEckh97sC0N7usLS0lOw6FRMTgw4dOqBKlSoYP348QkJCkJCQkK94STvltp+XlxcsLCxkl1X+Lo2Li0NGRka+YlHuM6xRo4bsPjOFQoFatWqprIeIDM+ssAMgIiIiIiIiouLD0dFRkk5KSpK1yrerqys8PT3zPB4fHy9rRcz79+/j888/x65du+QH+/+9efNG5zL6evbsmXh/586deu9okJiYqDWPLqur57CwsMCQIUMwZ84cAEBgYCB++uknmJqaSvKtWLFCvO/h4YH27dvrfCwiIiJ6/xRWWxFge1EVfdqLchjzHJo2bYqZM2fi22+/FR97+fIlgoODERwcDABwdnZG27Zt0a9fP3Tq1En2QARd4ylTpozssrkHLsp5f4oyKysrvcqpmrCWmpqKtLQ0Mb1w4UIsXLhQr/qL++tKRPS+y72bUlJSEkqVKlUgx9bnu03uRGxjtbkmTpyIEydOYOfOneJjsbGxWLp0KZYuXQrg7SQWPz8/fPLJJ7J3ZSpIhnzdC7IdLVdQUJBkct+gQYM05q9fvz5q1aqFyMhIAG93mRoxYoTs4+nSPnV2dpakExMTUbFiRY1l9Pksb9u2DV9++SUePnyoc1m5v8MM2TbN8erVK/zwww9YuHAhMjMzdapXl9+P+sRuyL+bd+H/CBGRHIb+rpg9ezbCw8Nx9uxZ8bE7d+5g3rx5mDdvnjjZxd/fHwMHDpRMfCHDUG77XblyRe+2H/D2d0futpEulNuPurTHAGmfIfu1iIyLO0URERERERERkWy5O/ru378vq9zixYtx+/btPLeePXtqLXvr1i00b95c5QBXc3NzuLi4oGLFivD09BRvyivPGmsleVUMtcvAq1evtOYxM9NvrRvl1fdjY2Oxd+9eyfPPnz9HSEiImB4+fHi+OpqJiIjo/VEYbUWA7UV19G0vamPsc/jmm29w4MABNG7cWOXzCQkJCAoKQo8ePVCtWjXs2bPHIPHk3q3CxsZGdtncq7sX5M4XRZ0hd2KT87knIqKiK/ck4nv37hVOIAZmrDaXqakpQkJCsGjRIrWTWW7fvo1FixahWbNm8PX1xY0bN4wSS1FQkO1ouVauXCne9/LyQrNmzbSWUd4t6syZM4iKipJ9PGtra9l59Wmf6vpZXrRoEXr27KlyQpSdnR3c3NxQuXJlye8wZQX5O0zZ69ev4e/vjz///DPPhCgTExOULl0a5cuXl8St6wDoooL/R4iI9GNra4ujR4/i559/RunSpfM8LwgCrly5gtmzZ+ODDz5Ajx498Pjx40KI9N1VlPqTlNtRuvQXAtI2GfsLiYyLO0URERERERERkWyNGzfGhg0bxPTZs2fRsmVLox1PEAQMHToUsbGx4mP+/v4YNmwYmjVrBjc3N5UTdgYPHoy1a9caLS51bGxskJycDABwcHDIs1tCUeDl5QVfX18cOXIEwNuL9507dxafX7dunbiSu6mpKYYOHVoocRIREVHxU9BtRYDtxcJQEOfw4Ycf4sMPP8TVq1exb98+HDt2DKdOncLTp08l+e7evYvOnTtjxYoVGDZsWL6OaWtrK0m/evVK9u4VqampGut6n+UeLOLs7Kz3jhrly5c3REhERFRIGjdujPXr14vps2fPonXr1oUYUdFnYmKCMWPG4LPPPsPx48fx33//4cSJEwgLC8Pr168leY8ePYrGjRvj+PHjqF27diFFbDxFrR19/fp1nDp1SkzfunVLr4WlVq1ahTlz5sjKm/s918TY7dOoqCiMHz9eUv+YMWPQuXNn1K1bV7IIRQ5BEGBiUvjrt//88884duyYmK5ZsybGjh0LX19fVK5cWeVOtKtXr873743Cwv8jRET6sbKywvfff4+vv/4ahw4dwqFDh3DixAmEh4cjIyNDkjckJATnzp3DmTNn2HdhIMr9Sba2tnkWWNBFfhcxUG5H6TrBSrlNxv5CIuPipCgiIiIiIiIiki33QIXQ0FBMnDjRaMc7e/YsTp48KaYnT56MX375RWs5Q64epYvSpUuLF+d79+6NpUuXFkoc2owcOVKcFLVr1y7ExcWJncnKK5z6+/ujXLlyhRIjERERFT8F3VYE2F4sDAV5DjVr1kTNmjUxceJEcRXe7du3Y9WqVeLuEoIgYOzYsejcuXO+VnB3cHCQpOPj4+Hq6iqrbHx8vMa63mf29vYwNTVFVlYWAGD8+PH47rvvCjkqIiIqDLnbiocOHcJXX31VSNEULyYmJmjdurX4Gqanp+PkyZPYsmUL1q1bJ7bNkpOTMXz4cJw7d64wwzWKotaOVu5DzY+1a9di5syZKifi5Ja7zalJQkKCJG3o9unChQvFAeHW1tY4ceIE6tSpo7FMYf0GU5aRkYG//vpLTLdt2xZ79uyBpaWlxnJFIfb84v8RIiL9mJubo2PHjujYsSOAt5Ncjh49ik2bNiEoKAhv3rwBAMTExGD8+PEIDg4uzHB1ps+kbsD4u3kr79DVvHlz7N+/36jH00S5HaVLeyx3fvYXEhlX4S+/QERERERERETFRp06dSSTZPbu3YtHjx4Z7XiHDh0S75csWRJTpkyRVe7u3bvGCkmjatWqifevXr1aKDHI0bNnTzg7OwMAMjMzsWbNGgBAWFgYrly5IuYbMWJEocRHRERExVNBtxUBthcLQ2Gdg0KhQO3atfHjjz/ixo0b6Nu3r/jcq1evsG3btnzV7+3tLUlHRETILnv58mXxvrm5OSpVqpSvWN4lCoUCVatWFdPF9XNPRET598EHH6BixYpi+uDBg4iOji7EiIovCwsLtGnTBn/99Rdu3bol+a49f/48bty4UYjRGUdRakdnZGRg3bp1Ytre3h6enp6ybx4eHmLZhIQE7Ny5U9ZxlftttYmMjBTvlyhRwuALXyn/Dhs0aJDWCVFA4f0GU3bu3Dlx8g8A/PLLL1onRAFFI3ZDex//jxARGUKJEiUQEBCAwMBAXLlyRbzeCrzdMerly5eFGJ3ucu/wLXeyU1xcnDHCESm3/aKioox6LG2U+wyvXbuWZ6cwdXIWeFJVDxEZHidFEREREREREZFsJiYmGD9+vJjOysqStRK/vmJiYsT71apVk3WB8smTJ4V2YbxNmzbi/TNnzuDp06eFEoc2FhYWGDx4sJjOWdlUeYVTV1dXdOrUqcBjIyIiouKroNuKANuLhaEonIOFhQUWL14sWc02vwMk6tevDwsLCzG9d+9e2WX37Nkj3q9duzasra3zFUt+mJmZifezs7MLLQ5lyp+Zffv2ITMzsxCjISKiwmJiYoIJEyaI6ezsbPz000+FGNG7oUyZMpg1a5bkMVXtotw7ERWVdoJcRaENmmPXrl2SgcBLly7F7du3Zd/u3LkjmaQkd9epAwcOyMonCIIkb/369WFqairz7ORR/h0mZ0IUIJ1IVViU4waKV+zGJPf/CBERSVWpUgWTJ08W05mZmbh161aefAXRDtP3GKVKlZL0r+X+rlTnzJkzRo1Lue336NEjXLx4UVY5Y2jatKl4Py0tDYcPH5ZV7tixY0hJSVFZDxEZHidFEREREREREZFORo0aBScnJzG9ZMkS7N692yjHEgRBvP/mzRtZZRYsWCApV5B69eolDkLMysrC77//XihxyDFy5Eixk/vmzZvYt28fNm7cKD4/ZMgQyYBKIiIiIjkKsq0IsL1YGIrKOTg4OEhW45W7Sqs6lpaW+PDDD8X09u3b8fjxY63l9u7dK1k5vnPnzvmKI79sbW3F+y9evCjESP5Pv379xPvPnj3D8uXLCzEaIiIqTJ9++inKlCkjpgMDAxESEqJ3ffv27cOdO3cMEFnxprzDC6C6XaTcRgCKTjtBrqLSBgWkk5hsbW3RpUsXncqbmJhIdj3dv3+/rAHIUVFROHnypNZ8+/btw4MHD8R0t27ddIpPDl1/h6Wnp2Px4sUGj0NXuX8Hyon9wIEDuHbtmrFCKjLk/B8hIqK8iko7TN9jWFhYSHY8DwsL01rm4cOHsicG6RuXn58f7O3txXTuybsFqWPHjpJr5kuWLJFV7u+//xbvm5iYICAgwOCxEdH/4aQoIiIiIiIiItKJra0t1qxZI1k1qnfv3tiyZYvBj1WxYkXxfmRkJO7du6cx/9mzZzFnzhyDxyGXh4cH+vfvL6b/+OMP2St45hAEAenp6YYOLQ8vLy/4+vqK6SFDhoirVSkUCgwfPtzoMRAREdG7pyDbigDbi4XBmOeg7f1TFhMTI9khwMPDQ6cYVBkzZox4//Xr1/jiiy80TqBLTk6W7I5mZmaGkSNH5juO/FB+HSIjIwsvECU+Pj5o2bKlmP7mm28QERGhUx2ZmZnIysoydGhERFTAbGxssG7dOpiY/N9wpX79+uncVkxPT8e0adPQqVMnyerr74rnz5/rdF65v1dVtYtyP1ZU2glyFZV2dGxsLPbt2yemu3fvrtcuocrnkpWVhTVr1sgq9+WXXyItLU3t86mpqZg0aZKYtrCwwKBBg3SOTxvl32G7du3Smv/rr7/Wqa1vLMpxA9pjT0xMxGeffWbMkIzGGP9HiIjeB0+ePNH4XZtb7v+f7u7uefIURDssP8do0qSJeH/Lli1ITExUm1cQBIwZM0b2LuClSpWCg4ODznHZ2dlh7NixYnrTpk1YtWqVrLLK5C6ipYmrqyt69OghpkNCQrS2Ifbt24dNmzaJaT8/P1SuXDnfsRCRepwURUREREREREQ669SpE6ZMmSKmX79+jd69e6N///6IiorSWj4jIwNBQUEIDQ3VmM/Pz0+8n52djf79+0sGPirbsWMHOnTogIyMDMnAioI2e/ZsuLq6Ang7cK9Lly6YO3eu1k7Xx48fY+HChahWrRouXLhQEKFKBmzGxcWJ99u0aQNPT88CiYGIiIjePQXVVgTYXiwsxjoHLy8vfPLJJzhy5Aiys7PV1vP8+XN88sknYh6FQmGQFfD9/f3Rvn17Mb1582Z89tlneP36tcpz6dy5M27cuCE+NmnSJLi5ueU7jvxo2rSpeD8oKEj2yr3GtnjxYnF14JSUFLRq1QqBgYFaJzpFR0dj5syZ8PDwQEJCQkGESkRERtahQwdMmzZNTKelpaFPnz4YNGgQoqOjNZZNTU3FqlWr4O3tjenTp2tsLxRnly9fRsWKFfHtt9/i6tWrGvNeuXJFMgmmXLlyaNiwYZ58pUqVQrVq1cT07NmzJbtdFgdFoR2du/0yYMAAvepp2LAhvL29xfSqVau07mZrYmKC8PBw9OrVS+Vg5YSEBHTr1k3ym+vrr7+W7K5qKMq/ww4fPoxff/1VZb7U1FSMHTsW8+fPL9TfYDkaNmwIR0dHMT1x4kRcunRJZd6rV6+iVatWiI6OLhKx68oY/0eIiN4H+/btg4eHB3755RetE3pDQ0Ml34HNmjWDi4tLnnw1atSAnZ2dmJ46darkuqwh5OcYyu2ZpKQkDBkyRGX7Kjk5GQMHDsSuXbskC2JpozzpasmSJWq/e3P75ptvUKtWLTE9YsQIfPvtt0hOTtZY7vnz51i9ejUaNmyYr11plf3888+SifD9+vXDjh07VObds2cP+vTpI6YtLCwKdacroveFmfYsRERERERERER5TZs2Dfb29pg0aRKysrIgCAI2btyIjRs3wtvbG23atIG7uzucnJxgYWGB1NRUxMbGIioqCkeOHMGLFy8k9alaHalevXrw8/PD/v37AQBnzpyBt7c3+vXrhzp16sDMzAwPHz7E7t27cf78eQBA3bp14eXlheDgYOO/CCqULVsWW7ZsQceOHZGcnIz09HRMmjQJs2bNgp+fH+rWrQtHR0dkZWUhKSkJN2/exIULF3Dx4kWtF74NrWfPnnB2ds4zuPDTTz8t0DiIiIjo3VMQbUWA7cXCYqxzyMzMxPr167F+/Xq4uLigefPmqFu3LsqUKQNra2s8f/4cly5dQkhIiGQAxGeffYaqVavm+7wUCgVWrVqFxo0b48mTJwCAZcuWYffu3ejbty+qVq2KjIwMXLhwAZs3b5bE0LhxY0yfPj3fMeTX0KFDsXTpUgiCgNTUVLRr1w5OTk5wdXWFqampmG/FihUFOtCxZs2aWLduHfr27Yv09HQkJydj6NCh+PHHH+Hn54datWrB3t4eaWlpeP78Oa5fv47z58/LmkhJRETFz48//oiSJUti4sSJyMrKQnZ2NtatW4d//vkHdevWha+vL9zc3ODk5ITk5GTExcXhwoULCA0N1Wnl/uIsKSkJv/32G3777Td4e3ujadOmqFmzJhwdHWFiYoInT57g1KlT2Ldvn2SSzh9//KF2AsewYcPw9ddfA3i7Sr+npycqVKgABwcHycBWuQNVC1pht6MFQcDq1avFdOnSpfHhhx/qXV///v3F9uOdO3dw9OhR+Pr6qs0/efJk/Prrr9i1axe8vb3Rt29f1KpVC4IgICIiAkFBQUhKShLz16tXD99//73e8Wkyfvx4LFu2TBww/f333yM4OBg9evRAhQoV8OrVK0RGRmLr1q2Ij48H8HYw8eTJk40Sj1xmZmb46quv8N133wF4O5GscePG6N69O3x8fGBnZ4eEhAQcO3ZM/NsqWbIkRo8ejd9++61QY9eHMf6PEBG9D548eYIffvgBP/zwA2rXro0mTZrA29sbjo6OEAQBjx49QmhoqGRBJ1NTU8ydO1dlfebm5hg4cCD+/vtvAMCRI0fg5uYGd3d32NnZie0wNzc37NmzR6+Y83OMgIAANG7cGGfPngXwdmGpatWq4eOPP4anpydev36Ny5cvY8uWLXj27Bns7Ozw2Wef4ffff5cV27Bhw8SdNmNjY1GvXj2ULVsWzs7Oku+bPXv2SBYbKlGiBLZt24ZWrVrh8ePHEAQBv/32G/7++2/4+fmhYcOGKF26NIC333l37tzBpUuXcO7cOdk7Wcnl7e2N+fPniwuOpqamolu3bmjZsiX8/f3h4uKChIQE7N+/H0eOHJGU/e2331C7dm2DxkNEeXFSFBERERERERHpbdy4cahbty7Gjx8vuVh+8+ZN3Lx5U1YdpUuXxnfffYfPP/9c5fNr1qxBixYtcOfOHQBAYmIiFi9erDJvtWrVsG3bNslqs4WhWbNmOHPmDLp37y6+Dk+fPhUHeGqjPFjRmCwsLDB48GDMmTNHfMzJyQk9evQokOMTERHRu60g2ooA24uFxdjnEBcXh23btmHbtm0a83388ceYP3++/MC1qFChAo4fP44OHTqIu1XExMTgjz/+UFvG19cX27dvh4WFhcHi0Ffjxo3x008/YcqUKeLg32fPnuHZs2eSfC9fvizw2Lp3747Dhw+jV69e4qSzR48eYeXKlbLKc2AmEdG75csvv0TNmjUxfvx4REZGAng76eTixYu4ePGi1vKurq6YPn06PvjgA2OHWujktJ9NTU3x559/Slalz238+PE4cuQI9u7dKz728OFDPHz40GCxGlthtqOPHj2K27dvi+nevXvDzEz/oXfKk6IAYOXKlRonRbVr1w6lS5fGhAkT8PTpUyxatEht3po1a2L//v2wsrLSOz5NPDw8EBgYiE8++UQcdHzp0iW1E+o+++wzfPfdd4U+KQoAvvrqK5w5cwbbt28H8Han4uDgYJWLZpQqVQpBQUF4/PhxQYdpcIb6P0JE9L65fPkyLl++rDGPtbU11q1bh2bNmqnN8+uvvyIsLAzh4eEA3u54n3uXVOXJzfrQ9xgmJiZYu3YtfH19xf6a+/fvq9wJsmTJkggODkZsbKzsuHr37o0RI0ZgxYoV4mNPnjwRj5UjPT09T9kqVarg/Pnz6NmzJ8LCwgC83YF88+bN2Lx5s9ZjG7IP9dNPP4UgCPjf//4ntn+OHz+O48ePq8xvYmKCuXPnYty4cQaLgYjUY88xEREREREREeWLr68vLl68iO3bt6Nr164oVaqU1jI5E2+2bNmCmJgYTJgwQe0AQhcXF5w7dw7Dhg2Dubm5yjwODg4YP348wsPD4eHhkZ/TMZjq1asjMjISS5YsQY0aNbTmr1GjBiZOnIiLFy+iUaNGBRDhW0OGDJGkBw4cCEtLywI7PhEREb3bjN1WBNheLEyGPof169ejf//+cHFx0VpX06ZNsXXrVvzzzz9q33d9ValSBZGRkZg6dSqcnZ3V5vP09MSKFStw6NAhlCxZ0qAx5McPP/yAM2fOYNSoUahTpw7s7e3zNWDXkFq0aIHbt29j1qxZqFSpksa8JiYmaNCgAaZMmYJbt26hTJkyBRQlEREVlPbt2+Py5cvYsGED/Pz8YGNjozG/ubk52rVrhzVr1uDOnTv49NNPi8RkcUOrV68e5s+fDz8/P9ja2mrMa2FhgR49euDChQsYO3asxrxmZmbYvXs3Nm/ejD59+sDLy0uyc0BxUVjt6NwTuQcMGKB3XQBQtWpV1K9fX0xv2bIlz465uX355ZfYv38/6tatq/L5EiVKYOLEiTh37pzGdqwh9O3bF0eOHEGDBg3U5qlVqxaCg4PVLlpRGExNTbF161bMnDkTjo6OKvNYWFigZ8+eiIiIgJ+fXwFHaBjG+j9CRPSu69ixI2bNmoVWrVppnVxsY2ODQYMGISoqCh999JHGvKVKlcKpU6ewevVqdO3aFR4eHihRooRB22H5OUbVqlVx+vRpdO3aVeXzJiYmCAgIwMWLF9GhQwedY1u+fDkOHDiAQYMGoUaNGihZsqTsxW/c3Nxw6tQpbNy4EY0aNdJ6PpUrV8bo0aNx/Phx9O7dW+dYNRk5ciQuX76Mrl27qu2PNDU1hb+/Py5evMgJUUQFSCEYYn9gIiIiIiIiIqL/LysrCxcvXsS9e/fw9OlTPH/+HBYWFrC3t0fp0qVRu3ZtVK5cWa+6nz59imPHjuHevXtIT09HmTJl4O7ujlatWhl8IKShxcTE4MyZM4iLi0NiYiIsLCzg4OAAT09P1KpVy+gXqdXZuHEj+vfvL6YjIyNRs2bNQomFiIiI3n3GbCsCbC8WNkOeQ3R0NK5du4b79+/jxYsXyMrKQsmSJeHu7o6GDRvCzc3NiGfyf7Kzs3H27Flcu3YN8fHxMDMzg4uLC+rVq8d2swHcvn0b4eHhSEhIwIsXL2BlZQVHR0d4eXmhVq1asLe3L+wQiYioAKWnp+Ps2bN49OgRnj59ihcvXsDW1hYODg6oWrUq6tat+94t5pOVlYWoqCjcvHkTMTExePnyJUxMTGBvbw9vb280aNBA1sID77J3oR2tjytXriAiIgKxsbGwsrKCh4cH2rdvr3VyoTFcvXoVYWFhiI+Ph6WlJVxdXVG7dm1Zk9YK0+vXr3Hy5Elcu3YNycnJcHJygpubG1q1avVOtUP5f4SISD/p6emIjIzErVu38PjxY7x8+VJsZ1SvXh3169cvlO9dY4uJiUFoaChiY2NhYmKC8uXLo0WLFihfvnxhhwbgbf/vyZMn8eTJEzx//hympqYoVaoUKlWqhJo1a6JcuXIFEseLFy9w9OhRPHr0CElJSShVqhTKlSuH1q1bw8HBoUBiIKL/w0lRRERERERERETvsQ8//BD//fcfAKBZs2Y4depUIUdERERERERERERERERERERERKSdvL3niIiIiIiIiIjonXPz5k0cOnRITI8aNaoQoyEiIiIiIiIiIiIiIiIiIiIiko+TooiIiIiIiIiI3lMzZsxAzibiTk5O6Nu3byFHREREREREREREREREREREREQkj1lhB0BERERERERERAUrMzMTCxYswD///CM+NnHiRFhZWRViVERERERERERERERERERERERE8imEnOWAiYiIiIiIiIjonbVkyRIsWbIEmZmZePDgAVJSUsTnKleujCtXrsDGxqYQIyQiIiIiIiIiIiIiIiIiIiIiko87RRERERERERERvQeePHmCiIiIPI+XKlUKmzZt4oQoIiIiIiIiIiIiIiIiIiIiIipWTAo7ACIiIiIiIiIiKljm5ubw8PDAyJEjERERgQYNGhR2SEREREREREREREREREREREREOlEIgiAUdhBERERERERERERERERERERERERERERERERERHJxpygiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiKlY4KYqIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIihVOiiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiKiYoWTooiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIioWOGkKCIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIqVjgpioiI9BITE4OdO3di5cqVmDVrFubPn4+NGzfi5MmTyMjIKOzwiIqlIUOGQKFQQKFQwNfXt7DDKXb4+hERERERERHRu2DatGliH4eHh0dhh0MkCg0NFT+bCoUC9+7dK+yQiIjoHZOdnY0LFy5gy5YtWLZsGWbOnIk5c+Zg+fLl2L59e5H67gkMDJR8L2qinC8wMLBgAiQiIiKiYo9joYiI5DEr7ACIiKj4SE1NxYIFC7Bp0yZcunRJbb6SJUuiQ4cOGD9+PJo3b15wAVKx4OHhgfv376t93sTEBLa2trC3t0eNGjXQpEkT9O/fH1WrVi3AKImIiIiIiIiISB+BgYEYOnSo5LEaNWrg8uXLMDU1lVVHaGgo2rRpI6Z37tyJzp07GzTOgjBt2jTxfvfu3VG3bt1Ci4W009ZvmR9Hjhx57wauzJs3D0lJSQAAX1/f9+78iYhIN7t27cKKFStw9OhR8ftDHXt7e/j5+aFXr17o1KkTrK2tCyZIIiIiIjIqVf2KgH59g4mJiXB1dUVaWprk8cGDB3OSOqlUs2ZNREVFiel27drhv//+K/A4AgMDxcUg6tati+7duxd4DETFESdFERGRLP/88w++/vprPH78WGve5ORkbN68GZs3b8ZHH32EhQsXwtXVtQCipHdBdnY2kpOTkZycjAcPHmDfvn2YPn06PvroIyxatAguLi6FHSIREREREREREekgKioKa9aswbBhwwo7lAI1ffp08b6HhwcnRdF7Zd68eZJJZpwURUREqhw/fhzjx49HeHi47DJJSUkICgpCUFAQXFxc8PXXX2P06NGcHEVERET0jlq1apXOk6LWr1+fZ0IUkTpnzpyRTIgCgMOHDyM6OhqVKlUq0FgCAwNx9OhRAG8n8XFSFJE8nBRFRERaTZ48GTNnzpQ8VqJECQQEBKB27dooW7YsUlNT8ejRI+zfvx9XrlwR823ZsgXh4eHYt28fd/qhPMzMzODu7i55LGdS1LNnzySPb9myBZcuXcKJEydQtmzZggyTiIiIiIiIiIjyaerUqRgwYACsrKwKOxQilTw8PGBmpvnS6evXrxEbGyumHRwc4OjoqLVuDtImIiLKa9GiRRg3bhwyMzMlj3t7e6NNmzaoWLEinJycoFAo8OTJE8TExODw4cO4ffu2mDcuLg4TJ06Et7d3sdxZlIiIiIi027VrFxISEuDs7Cy7zKpVq4wYEb1rVq5cmecxQRCwevVq/PTTT4UQERHpipOiiIhIowkTJuDPP/8U0xYWFvjqq68wefJk2NjY5Mn/+++/49y5cxg1ahQuXrwIALh37x5atGiBc+fOFfjMeSraypUrJ7lwoSw+Ph5BQUGYNm0anj9/DgC4c+cOPv30U+zcubMgwywwgYGB3KKZiIiIiIiIiN5Jjx49woIFC/D1118XdihEKoWGhsrK06ZNGzH9xRdfYNq0acYLqojx9fWFIAiFHQYREb0DZsyYgSlTpohphUKBPn36YOrUqahevbrGsrdu3cKSJUuwZMkSvHr1ytihEhEREVEhcXFxQVxcHDIyMvDPP/9g/PjxsspFRESI4xZtbW0hCAJSU1ONGSoVY6mpqQgKChLTlSpVQnR0NIC3Y/mmTZsGExOTwgqPiGTiXykREam1Y8cOyYQoGxsbHDhwAD///LPKCVE5GjVqhLNnz6Jnz57iY8+ePUP//v3zrPRFpE6ZMmUwduxYnDlzBg4ODuLju3btwqVLlwovMCIiIiIiIiIikk15x+9Zs2YhMTGxEKMhIiIiosK2d+9eyaRia2trBAcHY+PGjVonRAGAl5cX5s6di3v37mH48OFGjJSIiIiICtOgQYPE+6tXr5ZdTnnXn969e3PnetJo06ZNSElJAQBYWlri33//FZ97+PAhDhw4UFihEZEOuFMUERGplJycjGHDhkke27RpE1q3bi2rvJmZGTZu3AhfX1+cOnUKABAWFobZs2dj8uTJesV09+5dhIeH4/Hjx3j58iW8vb3Rq1cvlXkFQcCNGzcQFRWFR48eISUlBdbW1nByckKdOnVQu3Ztg83gT09PR2hoKO7du4dnz57B0dERdevWRaNGjfQ+RkpKCg4fPoz79+8jLS0N5cqVQ506dVCzZk2DxAwAL1++xPHjx/Ho0SM8ffoUdnZ2KFeuHHx9fSWTkAqbl5cXxo8fL1ktbvfu3ahbt67sOgRBwIULFxAVFYX4+HgIggAXFxfUr18/X6+pIAg4c+YMrl69iqdPn6J06dLw8PBA69atYW5urne9+sjIyMCpU6dw584dxMfHw9raGi4uLmjatCk8PDwMdpyzZ8/i2rVrePz4MWxtbVGlShX4+vrq1YGQlZWFq1evivWlpqbC1tYWpUuXRoMGDVCtWjWDxU1EREREREREhWPKlCkYM2YMACAxMREzZ87E7NmzjXrM5ORkHDt2DI8ePcLz58/h4OAANzc3tGrVymD9Xunp6Th+/Dju37+PuLg42NjYoFu3bgbth1ElOzsbJ06cwK1btxAfHw97e3tUr14dPj4+MDPT/7JfZmYmwsLCcPv2bcTFxcHMzAxly5ZFs2bNUKlSJYPEnpqaKr4vCQkJKFWqFPr06QNnZ2etZZ8/f46jR4/i4cOHePPmDcqUKQMfHx9UqVLFILEVlKL+OicmJuL48eOIjY3F8+fP4eTkhIEDB2pcJK0gFFTf5/nz53Hjxg08fvwYgiDAx8cHzZo1M1j9RET09vrkoEGDkJ2dLT4WHByMTp066VyXs7MzVqxYAT8/P9jb28sqc/fuXVy9ehX3799HcnIyLCws4OjoiBo1aqBBgwYFfn1PDmNd51RWWG1bIiIiIk169eqFpUuXIjk5GVeuXMH58+fRsGFDjWXS0tIkk1qGDRuGHTt26B2DMfskoqOjcfLkScTGxsLGxgbly5dHq1at4OjomK96cx/j3LlziIuLQ2pqKpydnVG1alU0a9YMpqamBjmGvv0pxurn1JXyJLquXbuiadOmaNy4Mc6ePSs+37FjR4Mdj/1PREYiEBERqTBnzhwBgHgbOHCgXvVcvXpVsLCwEOtxdnYWXr9+rTJvdHS05JhHjhwRBEEQQkNDhaZNm0qeAyC4u7tLyr9580YIDg4W+vTpI5QuXTpPfuWbk5OTMG3aNOHFixeyzmPw4MFi2datWwuCIAgZGRnC1KlTBScnJ5XH8PDwELZu3arT65WUlCSMGjVKsLKyUllnw4YNhcOHDwuCIAhHjhyRPBcdHS3rGJcuXRK6dOkieV+Ub2ZmZkLXrl2FGzdu6BS7XO7u7mrfQ3VOnz4tiXHAgAGyyiUnJwvff/+94OLiovaz4OXlJfz77786n8e6deuEChUqqKzT2dlZmD59upCZmZnnnKdOnaq2TlWfM22ePXsmfPHFF0LJkiXVnmOdOnWEkJAQWfWtXr1aUjbHhg0bBG9vb5X129raCr/88ot4vpokJycLgYGBQpcuXTTGDECoUKGC8OeffwppaWmyYtfn9SMiIiIiIiIiw8rdt3DlyhWhc+fOYtrKykp4+PChxjpy93vt3LlT1rGjoqKEbt26Cebm5mr7vfz9/YWIiAhZ9anqa0hNTRUmTJggODg45Kl/9erVwtSpUzX2d6i65fSD5lCuQ7n/bOHChUL58uXV9kctXbpU1nkpi4uLE8aMGSPY29urja9evXrC/v37ZdXXunVrsdzgwYMFQRCEp0+fCkOHDhVKlCih8dxV9aElJCQIn3zyiWBpaakyNh8fH9nvpyHk/mxq6utTVtRf53v37gk9e/ZU2Wes3O+srU8699+/nNvq1avVnmdB9X0uXrxYqFy5cp66Bw8eLGRlZUn6gfv06SPrWDmysrIkf7e6licietfMnTtX8r/2s88+M+rxMjMzhT179ghDhgwR3NzcNH4n2draCuPGjROePHkiq2513yuqyP3uU2bo65z6tG1v3Lgheezvv/+Wdawc+S1PRERE7xdV/YqffvqpmB4zZozWOjZu3Cjm9/b2FgRBkIzty+lH0cbQfRLKrl69Kvj6+qqs09LSUhgwYICQkJAgCIJ+Y6GysrKEVatWCdWqVVMbu5OTkzB9+nS14ziV6dOfkqMg+zn1cf36dcmxd+3aJQiCICxatEh8zMLCQnw/5NDn9crd5ybnJrdfkuh9YZgtMoiI6J2SnZ2NBQsWiGmFQoHp06frVVeNGjXQr18/MZ2QkIB//vlHdvnZs2ejbdu2OHPmjNa8p0+fRu/evbFp0yY8ffpUY95nz55h2rRpaNKkCe7cuSM7nhwvXrxA69atMX36dDx79kxlnnv37qFnz55YtGiRrDqjo6NRu3ZtLF26FG/evFGZ5/z58/jwww8l748upkyZgvr162Pnzp1IT09XmSczMxM7duzABx98gE2bNul1HENzcnKSpLW9vwBw5swZeHl54ZdffkFcXJzafLdu3cKAAQPQp08fZGRkaK03OzsbQ4cOxcCBA/Hw4UOVeRISEjB16lS0b98eqampWuvU19mzZ1G1alUsWLAAycnJavNFRESge/fu6N+/v6xzzG3s2LHo378/bt68qfL5ly9f4vvvv8eAAQMgCILGurZs2YIhQ4Zg586dGmMG3m5BPH78eLRp0wYJCQk6x01ERERERERERcOsWbPEHdXfvHkj2RHcUJYtW4batWtj+/btavs/MjMzsXfvXtSvXx/z58/X+RgPHz5EgwYN8McffyAxMTG/IcuWkZGBnj17YuzYsXj06JHKPAkJCRg1ahS++uor2fXu3LkTVapUwd9//42kpCS1+S5evAg/Pz9MmDBB19ARERGB2rVrY/Xq1Tr3k0VERKBu3br4559/kJaWpjLPiRMn4OPjI6v/uLAU9df5v//+Q506dbB161a1fcaFoSD6PjMzM9GjRw+MHj0ad+/eVZnHxMQEw4cPF9MhISFqrwmosm/fPsnf7YgRI3SKkYjoXZKdnY0//vhDTJuammLy5MlGPebDhw8REBCAwMBAxMbGasz78uVLzJs3D/Xq1cP58+eNGpc2xrrOqUxO29bb2xu+vr5iWnkVfTlWrFgh3rexscGAAQN0Kk9EREQ0bNgw8f6GDRvUjqnLsWrVKvH+0KFD9TqmMfsktm3bhvr16yM0NFTl8zk7XdWvXx/Xrl3TOfa4uDg0a9YMw4YNw/Xr19Xme/bsGaZOnYoGDRpobSfnJqc/RR1j9XPqS7l9W6ZMGfj5+QEA+vXrBwsLCwBvd1XVZbxrbvl5vYhIvoLbX46IiIqNiIgIPHjwQEy3adMGlSpV0ru+4cOHY+3atWJ6165dsi78hYSEYMGCBRAEAWXLlkXPnj1Ro0YNWFhY4N69ewgLC1Nb1tbWFi1atECDBg3g6uoKW1tbJCYmIiIiAtu3bxcvPl+/fh2dO3dGeHg4bGxsZJ1PdnY2+vfvj1OnTkGhUKBDhw5o06YNnJ2dkZiYiL179+LQoUNi/nHjxqFly5aoXbu22jqTkpLQrl07yevu7OyM3r17o2bNmlAoFLh27RqCg4Px5MkTjB8/Ht9//72seHOMHj0aS5YsEdMmJibo0KEDWrVqBRcXF6SkpODUqVMICQlBeno60tPTMWDAAFhbW6NLly46HcvQck+CMjc315j/yJEj6Ny5M169eiU+VrVqVXTu3Bmenp4wMzPDjRs3sGnTJnFiU3BwMBQKBYKCgjTWPXHiRAQGBoppU1NTdOzYEb6+vnBwcEBsbCx2796NsLAwhIaG4n//+5+OZyvPxYsX0a5dO7x8+VJ8rEqVKujVqxcqV66Mly9fIiwsDCEhIeKgkY0bN+LNmzfYtm2b7OP8+uuv+OuvvwAAdevWRefOneHu7o60tDScOXMGQUFB4g/7TZs2wdfXF6NHj5ZVt6OjI3x8fFCvXj2UKVMG1tbWePbsGc6fP48dO3bg9evXAIBTp06hT58+OHTokDiAioiIiIiIiIiKj5o1a2LQoEFin8ratWsxceJE1KxZ0yD1L1++HKNGjZI81qJFCwQEBMDFxQUJCQnYv3+/ONggKysL48aNgyAIGDdunKxjpKeno3fv3rh+/ToUCgXatm2Ltm3bomzZskhMTERYWBgsLCzg6OgIT09PAJAsxlSmTBnY2dmprNva2lrjsT///HOxP8fHxwcdOnSAm5sbXr58idDQUGzfvl1cqGbOnDlo27Yt/P39Ndb577//YtCgQcjKyhIfq1+/Pjp27Ah3d3dkZWUhMjJSsgDVn3/+CTMzM8yePVvLq/VWYmIievTogdjYWJiZmSEgIAA+Pj5wcnLC06dPERoaClNTU5Vl4+Li0KVLF8TExMDW1hbdunVDo0aNYGdnh4cPHyIoKEgcGJKSkoIBAwYgMjJSdh9vQSnqr3N0dDQWLFiAFy9ewMbGBl26dEGTJk1QqlQpxMXFYffu3VAoFLLPt2TJkuLn//79+8jMzAQAODg4wNHRUW2Z3Aqq73PSpEkICQkBANSqVQtdunSBh4cH0tPTce3aNVhaWgJ4O5FpxowZyMrKQnp6OtatWyf7f4fyYPBKlSqhffv2suMjInrXREREICYmRkx37NgRFSpUKLDjW1paonnz5mjYsCHKly+PkiVLIiUlBZGRkdi5cyceP34MAHj8+DE6deqEiIgIlC1btsDiy2HM65w55LZtAWDUqFFiOzo8PByXLl1C3bp1tR4jIyNDMkagd+/eKFWqlMxXgYiIiOitpk2bokaNGoiKikJiYiJCQkIkC7Qre/jwIf777z8Ab8dzDRo0SOfjGbNP4tixY+jXr59kUZratWujR48eqFChAhITE3Ho0CEcOHAADx8+RK9evXTqP338+DF8fHwkE2+cnZ3RtWtX1K5dG7a2tnj06BF27NiB8PBwAEBUVBRat26N8PBwlX00qsjtT1HFGP2c+srMzJS0Vz/++GOYmb2dVuHo6IguXbpgy5YtAN5OnpLbF5SbnNfL2tpa7FOLiYkRJ//Z2dmhTJkyKutV19dG9N4q1H2qiIioSJo/f75kq83ffvstX/VlZWUJJUqUkGy/mp2dnSdfdHS0yq0+R40aJaSmpmo9zpEjR4R69eoJGzZsEF69eqU2X0pKijBixAjJMaZMmaKxbuWtaE1MTMQtXc+fP68y/8qVKyX19+7dW2P9uePp2bOnkJSUlCdfcnKy0K9fP0kcObfo6Gi19QcGBubZvjcqKkpl3uvXrwteXl5i3jJlyui0Baw27u7uKrfF1WTatGmS+MeOHas2b1xcnODi4iLmtbKyElauXKnyM/fq1Sth1KhRkrrXrl2rtu7jx48LCoVCzOvq6iqEhYWpzLt+/XrBwsIiz3ulaetauVsev3nzRqhRo4Yk7h9++EHIyMjIk/fatWt5tkNevHix2rpzb+FrYmIiWFlZCevWrVOZPzw8XHBwcJC8JpmZmRrrb926tbBr1y4hPT1dbb74+HihS5cuklhWrVqlNr8g6LdlNBEREREREREZVu6+hStXrgiCIAgPHjwQrKysxMe7dOmito4jR45I6ti5c6favDdu3BCsra3FvDY2NsLWrVtV5t21a5dga2sr5rWwsBAiIiLU1q3c15BzK1u2rHDy5ElZr4VyudWrV8sqIwiCMHXq1Dx9kQ4ODsKBAwdU5t+7d6/YDwVAaNSokcb6o6KiBBsbGzG/o6OjsGPHDpV5ExMThW7duol5FQqFEBoaqrbu1q1b53nNqlatKly9elXreSv3G+acd/v27YXHjx/nyZuRkSEMGzZMcpxFixZpPUZ+5f5saurrKw6vc86tefPmwoMHD3Q+f0190srH0fQ65VaQfZ8ABDMzM2Hp0qUq+4+VKfdV1qpVS9a5xMXFCebm5mK5GTNmyCpHRPSu+vPPPyX/g+fMmWP0Y0ZHRwtVqlQRli1bpvLaa460tDThxx9/lMQ3aNAgjXXn/l7RRG670JjXOfVt26alpQmlS5cWy3z++eca8+fYunWr5FjHjx+XVY6IiIjeX+r6FX///XfxsQ8//FBt+Z9++knM16lTJ/FxJycn8fHBgwerLW/MPonXr18LVapUkfT9/PHHHyrbeUePHhXbX8pjzjSNhcrKyhLatWsniefLL78UXr58qTL/smXLBFNTUzHvsGHD1Nadn/4UY/dz5se2bdsk53Tx4kXJ8zt27JA8r26MYG75eb0EQdrvp+nzSkRSnBRFRER5DBgwQNIoO3ToUL7rbNGihaTOW7du5cmjalJU3759ZR/j9evXOsXUp08f8TguLi4aJ2jk7iQuWbKkcPfuXY319+/fX8xvaWkppKSkqMx3584dyUSb5s2ba4wlMzNT8PX1zfNaqbsA/eLFC6FUqVJivmrVqgkvXrzQGPuDBw8Ee3t7yQ88Q9F1UtTNmzclsQAQtm/frjb/0KFDJT+m9u7dq/UYH330kSSmrKwslflatWol5jM3N8/zYyi3FStW5HmfDDEp6q+//srzI1aTBw8eSH7gOzo6qp04qOqHWXBwsMb6ly5dKsl/8OBBtXl1+TtNT08XmjdvLtZbr149jfk5KYqIiIiIiIio8KkbvCAIgjBp0iRZAyN1mRTVq1cvSd5t27ZpjG/37t2S/P7+/mrz5u4TNDc31ziJKjflsvpOisq5aH769GmNZb777jtJmZs3b6rN26ZNGzGfjY2NcOnSJY11Z2RkCE2aNBHL+Pj4qM2be7KOg4ODEBMTo/mE/7/ck3Xq168vpKWlqc3/5s0bwcPDQ8zfokULWcfJD10mRRWX17lKlSpq+65zK4hJUQXd96lpwJKyXbt2ScqdOXNGa5nZs2eL+U1NTYVHjx7JOhYR0btK+dopAOHYsWNGP2Z6errGxfxy++qrryTXd+Pj49XmNcakKGNe58xP21a5He/g4CDrel9AQIDk+jQRERGRNur6FePi4gQzMzOxjaRqYZfs7GyhcuXKYtnNmzeLz8mdFGXMPol58+ZJ6p42bZrGuk+ePJlnwXRNY6HWrFkjyTt58mSN9QuCICxcuFDMr1Ao1PYn5qc/xdj9nPnRuXNn8Ri1a9fO83xGRoZQpkwZMc/IkSNl1Zuf10sQOCmKSF8mICIiyiUuLk6SrlKlSr7r9PLy0ngMVSwsLDB//nzZx7CystIpplmzZkniuXDhguyy3377LSpVqqQxz6hRo8T7aWlpiIiIUJlv5cqV4ravADB//nyYm5urrdfU1BQLFy6UHeuKFSvw4sULyfG0bXdboUIFTJ48WUwvX74cWVlZso9pCPHx8fjrr7/QrFkzJCUliY/XqFEDAQEBKss8efIE69evF9MjRoxAx44dtR5rwYIF4mt+//597NmzJ0+emzdv4tixY2J65MiRqFu3rsZ6hw8fjkaNGmk9vq7+/vtv8b6rqyt++eUXjfkrVKiA6dOni+nnz59j48aNso7VoUMH9OrVS2OeTz75BDY2NmI6LCxMbV5d/k7Nzc3x888/i+mLFy/K+t9BREREREREREXT5MmTYW9vL6a/+eabfNUXGxuLkJAQMd21a1d0795dY5mAgABJX8e+fftw584dWccbPXo0ateurU+o+TJs2DA0bdpUYx7lvkgAOHv2rMp8Fy9exJEjR8T0Dz/8gDp16mis28zMTNIfeeLECURGRmoLGwDw448/ws3NTVbe3P766y9YWFiofd7S0hJDhgwR0+Hh4cjMzNTrWIZWnF7n2bNnw9bWVq+yxlCQfZ9169bN87ejjr+/PypUqCCmV65cqbWMch5/f3+UK1dO1rGIiN5V8fHxkrS7u7vRj2lubg5TU1PZ+adMmSJe80pLS8Phw4eNFVoexrzOqYoubduRI0eK9xMTE7F161aN+WNiYrB//34xPWLECFnHISIiIlKlTJky6NSpEwAgOzsbgYGBefKEhobi7t27AIDSpUuja9euOh/HmH0Sy5cvF++7u7vju+++01h38+bNMXjwYDlhAwDmzp0r3q9evTpmzJihtcz//vc/1KxZEwAgCAKWLl0q61i69KfkZsh+zvyIjY3F3r17xfSgQYPy5DEzM8OAAQPE9MaNG/Hq1Sudj5Wf14uI5OOkKCIiyuP58+eStPJABX2VKlVK4zFU8ff3h4uLS76PrU6lSpVQuXJlMX3u3DnZZZUvtqvTuHFjmJj831fttWvXVOZTbmDXrl0bDRs21Fp3rVq1tP5AyPHvv/+K95s0aYLmzZvLKqfc2I+Li8Ply5dlldNFTEwMqlSpIrl5enrC2dkZLi4uGDt2LJ49eybmL1WqFP7991+YmZmprG/z5s1IT08X0+PHj5cVh5ubG9q3by+mDx48mCfPvn37JOnhw4fLqltuPrnu3r2LqKgoMT148GCUKFFCa7khQ4ZI8u3atUvW8YYOHao1j42NjeSiibrPuj5atmwJS0tLMa3L3ykRERERERERFS0ODg749ttvxfSpU6ewfft2vevbt2+fZBLMmDFjZJX73//+J94XBEH2wFE5/STGIOe47u7uKFu2rJhW1z+jPNDWwsJC8lpo0qhRI1SvXl1Mq+o/y83ExETlgAI5vL290axZM635lPtI37x5g3v37ul1PEMrLq+zk5MTunTpoldZYyjovs/BgwdDoVDIymtiYiIZ0L1x40akpqaqzX/8+HHcuHFDTH/66aeyjkNE9C7LfX049/XjosDW1lbSvijI61LGvM6pii5tWy8vL7Rp00ZMr1ixQmP+VatWiQtuWlhY6N1WISIiIsoxbNgw8X5gYKBkAXJAujDJJ598onFBclWM2Sdx9+5dXL16VVK3poWAcihPTNckMjJSMq7viy++kIxZVEehUEjaaXLbkbr0p+RmyH7O/FizZo3YXjU1NcXHH3+sMp/yxLTk5GRs3rxZ52Pl5/UiIvk4KYqIiPJISUmRpOU08LXJvdJkcnKy1jJyJ+/kh6urq3g/JiZGVhl3d3dJOXWsra3h4OAgppV3O8rx5s0byWqfvr6+smKQm/fly5e4dOmSmM5ZNUMOFxcXyQptmnb/0VdmZibu3Lkjud29exdPnz7Nk7d169YICwvTuKLq8ePHxfuVK1dGtWrVZMfSuHFj8b6qc1W+6FGqVCnUq1dPVr26vKdy5I7N399fVrkSJUpIYpH7fsqdfKe8yqmqz7q+zMzMULp0aTEt9++UiIiIiIiIiIqmL7/8EuXLlxfT3333nd47lCv3b1hYWKBt27ayyrVu3Rp2dnYq61HH1ta2UHaJMjc3R4MGDWTlldM/o9x/5uPjo3VHeWXa+s9yq1q1KpycnGTXr0zOhCgAeXbeMWS/VH4Ul9e5cePGahegKgwF3fep6zWI4cOHi7uNpKSkYNOmTWrzKg/GcnV11alvnojoXZX7GrTcnQq7d+8OhUKh9WYo+lw/NgRjXufMTZ+2rfKgXOWdGHITBAGrV68W0926dYOzs7NOxyIiIiLKLSAgQJwoc/fuXRw9elR87sWLF5KdLJUnUMllzD6J3Dsd+fn5yaq7adOmshazV25HArqND1RuR169elXjAjA59B3Taeh+zvxYtWqVeL9Dhw6SSVjK6tatK2k3y9k5PLeCGANLRJwURUREKigPCAAgq7GrzcuXLyVpOReBq1SpovfxwsLC8PXXX6N9+/aoWLEiSpYsCRMTkzyd4ydPnhTLyG1Aq2sEq6Lcma/qdXz06BEyMjLEdI0aNWTXnbN9rSaRkZGSQSVyyihT3qnr0aNHOpU1pBEjRuDgwYOoWrWqxnwRERHifUOfa3R0tHhfebVWbby8vHRefUSTmzdvStKaJonlpvwjLSYmRtaWvnI/79o+67llZ2fj8OHD+OKLL9CqVSuUK1cOdnZ2Kv9OlS84FZWBLURERERERESkHysrK0ybNk1MX7t2DYGBgXrVpdxPUqNGDdl9MAqFArVq1VJZjzqVKlWStcKqoTk6Oso+Lzn9M8bsP8stP/27+vRJAYbpyzaE4vI656esMRR036eu51+uXDkEBASIaXW7ZCQnJyM4OFhMDx06VJxMRUT0PjPGNWhdREZGYsqUKQgICEClSpVgb28PU1PTPNellHd8LMjrUgXZftCnbduzZ09xIUNBENQOCD106JDkuip3SyQiIiJDMDMzw8CBA8W08iTsDRs24PXr1wCAhg0b4oMPPtC5fmP2SVy/fl2SVu6X1EZOXuV2pJ2dHSpUqCC7fuV2ZFZWFh4/fqy1jL79SYbu59TX0aNHcfv2bTGtvBuUKsrPHzt2DLdu3dLpeEWt/43oXcVJUURElIejo6MkbYjO3hcvXmg8hiq6rJ6Z48qVK2jRogWaNm2K33//HYcOHcLDhw+RkpKSZ9vc3N68eSPrGFZWVjrHBUDl8XO/tso7S2kjJ++zZ88k6Y8++kjWSmo5N+WVKhITE2XHJpe7uzsEQZDcnj59ivDwcHz11VfixZEVK1agQ4cOeSbXaTrfnTt36nSuY8aM0Xiuyu+VLu+TiYkJSpUqJTu/NsqxWVhY6FS38g/Z3HWpo8/nXdvf2rFjx/DBBx+gXbt2WLhwIY4fP47Y2Fi8fPnSYH+nRERERERERFR0DRkyRLI40LRp08SBC7pQ7tsoU6aMTmWV+0nk9JHo01dpCIbsi0xNTUVaWpqYXrhwoU79Z7NnzxbLGvs1M+R5F7Ti9DoX1udanYLu+9Tn/EeNGiXeP3XqVJ6BTQDw77//igOgFAoFhg8frvNxiIjeRfpeg3Z1dYWnp2eeW+5JVurcv38fXbp0wQcffIAZM2Zg7969uHfvHl68eIHs7GyNZQvyupQxr3Pmps93oIWFBYYMGSKmAwMDVe74qjxp2MPDA+3bt9f5WERERESqKO8AtXnzZnEnUuVdf/TZJQowbp+EctrS0lKntpicHTeV25EpKSk6tSNzL+BuzL6ootLfpzy5v1SpUujWrZvG/B9//LFkp3Xlz5scRa3/jehdxUlRRESUR+6GuvLMeH3lniGf+xiqKDcm5Th9+jRatGiBU6dO5XnOysoKZcuWhYeHh6SzXLmxXRgXzJUvjgNvf/jIJSevIVcvk7OypiE4OTmhfv36mD17Ns6ePSuuOBYaGor+/ftrLGuo81V1rsrvlS7vkz75NVGeGGZjY6NT2RIlSqitq6CEhISgffv2iIqKyvOcjY0NXF1dUalSJcnfqfL/gqIwsIWIiIiIiIiI8sfU1BQzZ84U048ePcKCBQt0rsdQ/SRy+kh07assigq6r/BdeM30UZxe56L2HhV036c+5+/v7y9ZcVnVblHKj7Vt2xaVK1fW+ThERO+i3JPY79+/L6vc4sWLcfv27Ty3nj17ai1769YtNG/eHLt27crznLm5OVxcXFCxYkW1k60K8rqUMa9z5qZvG2DkyJFQKBQAgNjYWOzdu1fy/PPnzxESEiKmhw8fLuYnIiIiyq9q1aqhWbNmAN62eYKCghAZGYlz584BeDs+UNvYMnWM2SehvNORtbV1vupWpTj1RRW2Fy9eYPPmzWK6d+/eWidrubi4wM/PT0yvWbNG5eIA6hTn14uoOOFfGhER5dG4cWP8+++/Yvr8+fNo27at3vVlZ2fj0qVLYtrJyQmenp75CTGPN2/eYODAgeIKEADQv39/fPzxx2jUqJHalWJbt26NY8eOGTQWXeReCUA5fm2Sk5O15sn9I61ixYqyt6HNTdfVdg2hWrVqWLt2LQICAgAAu3btwl9//YXPP/9cZX4bGxvxdXFwcJC1I5lcyu+VLu8TIO+9kkt5e2BdJ6rl3k5Yua6CkJCQgKFDhyIjIwPA2x99I0aMQK9evVC/fn21O3C5u7vjwYMHBRkqERERERERERlZ165d4ePjgxMnTgAAZs2ahZEjR+q0Q7eh+kkKuo+ksOTuK3R2dtZ7pdLy5csbIqR3El9n/RWHvk8TExOMGDECU6dOBQCsXbsWM2fOFPvdL1++jPDwcDH/iBEjjBIHEVFx1LhxY2zYsEFMnz17Fi1btjTa8QRBwNChQxEbGys+5u/vj2HDhqFZs2Zwc3NTOWFn8ODBWLt2rdHiUseY1zkNxcvLC76+vjhy5AiAt6vsd+7cWXx+3bp14kKTpqamGDp0aKHESURERO+u4cOH4/Tp0wDe7thz9epV8bmePXvC3t5er3qN2SehPLHp9evX+apbFeW+KCsrK5QrV06nYyjTdzen4mLDhg2S92DFihUqF7zR5PHjx9i7d6+kHUxEhY+TooiIKI/cnc/79u3D119/rXd9J06ckDTQfXx8DL4i1Pbt23Hnzh0xvWzZMnz66adayxlypQR95N7i9uHDh7LLPnr0SGuenF2WcmzcuFFcMaO48Pf3R8+ePbF161YAwI8//oj+/fvDyckpT97SpUuLFwt69+6NpUuXGiwO5fdKl/fpxYsXOk+i0kR5YFB6ejpevHghe8vm+Ph4tXUVhFWrVol/cyYmJti1a5dkJQ11CvvvlIiIiIiIiIiM47fffkOLFi0AvP39/+uvv+L333+XXV65byN3v4c2yvkLuo+ksNjb28PU1FRcyXT8+PH47rvvCjmqdw9fZ/0Vl77P4cOH46effkJWVhYSEhKwY8cOfPTRRwCA5cuXi/mcnJzQo0cPo8VBRFTctG7dWpIODQ3FxIkTjXa8s2fP4uTJk2J68uTJ+OWXX7SWK6zrUsa8zmlII0eOFCdF7dq1C3FxcXBxcQHwdpJUDn9//3wNyCUiIiJSpW/fvvjyyy+RmpqK06dPIzIyUnwuPxOyjdknoZxOS0tDcnKy7AV0EhIStOZRHh9YsWJF3LhxQ1bd7yPl9mp+6+GkKKKixaSwAyAioqKnTp06khUoQ0NDcffuXb3ryz2b3hgNwkOHDon3q1atKmtCVHZ2Nu7du2fwWHRRtmxZyQ5MFy5ckF1WTt6qVatK0sqrYxQnP//8M0xM3jZbkpKSMGPGDJX5qlWrJt439LnWqVNHvH/79m3ZE50uXrxo0Di8vb0l6YiICNllL1++LN4vV66czts955fy3+mHH34oa0LU06dPDbrTFhEREREREREVHc2bN0e3bt3E9F9//aXTYjTK/STXrl0Td6fWRhAEXLlyRWU97zKFQiHpLyyufYVFHV9n/RWXvs9y5cqhU6dOYjpnQM2bN2+wfv168fGBAwfC0tLSaHEQERU3derUkUyS2bt3r6xFIPWlfF2qZMmSmDJliqxy+bkunh/GvM5pSD179hQXk8zMzMSaNWsAAGFhYZI2NndLJCIiImOwtbVF7969xXTO+C13d3e0a9dO73qN2SeRe/ye8kQubeTkVW5HRkdH67zT1fvi8uXLOH/+vJh2dXWFp6en7FvOQgDA/y0OQERFBydFERFRHqampvjiiy/EtCAImDZtml51RUVFISgoSEw7Ozvjk08+yW+IecTExIj3lSevaHL+/PkiMdlCeeemffv2ydomNz09HTt37tSar0yZMqhZs6aYllOmKKpevTp69uwpppcsWaLyIkmbNm3E+2fOnMHTp08NFoPy+5SdnY3t27fLKrdlyxaDxQAATZs2laT37t0rq9yrV68QGhqqtp6CoM/f6eHDh40VDhEREREREREVATNnzoSpqSmAtxMK5A5WBaT9G2lpabL7EY4dOyZZ8MZY/SRmZmbi/ezsbKMcQ1fK/Wf79u1DZmZmIUbz7uLrDJibm4v35X7+i1Pf58iRI8X7+/fvx8OHD7F161YkJiaKj3MwOBGRlImJCcaPHy+ms7KyZO3cpC/l61LVqlWTNVH1yZMnhTYhyZjXOQ3JwsICgwcPFtM5k4OVV913dXWVTCAmIiIiMqRhw4bleWzIkCFQKBR612nMPokmTZpI0gcOHJBVd1hYmKxdTJXbkRkZGdi/f7+s+t83yu1VExMThIeH4/bt27JvR48eFctnZmZi7dq1RolTnz41IuKkKCIiUmPkyJFwdHQU0+vWrcPu3bt1qiMjIwOffvop0tPTxce+/PJLWFlZGSzOHIIgiPffvHkjq8y8efMMHoc+Pv74Y/H+y5cvsXDhQq1lFi9ejOfPn8uqv1+/fuL9Xbt2FemVxTT57rvvxPtpaWkqL5L06tVLHGySlZWF33//3WDH9/f3l/xN/Pbbb8jKytJYJjY2FqtXrzZYDABQqVIlyUS3tWvXylrhY82aNXj58qWYLowtfPX5O50/f76xwiEiIiIiIiKiIqB69eoYMmSImF67dq3s/quOHTtKJh4tWbJEVrm///5bvG9iYoKAgAB5werI1tZWvP/ixQujHENXyn2Fz549w/LlywsxmncXX2f9Pv/Fqe/T398fFStWBPB2gEpgYCBWrFghPt+sWTPJuRAR0VujRo2Ck5OTmF6yZInO16Dl0ue61IIFCyTlCpIxr3Ma2siRI8VBxzdv3sS+ffuwceNG8fkhQ4ZI2ulEREREhtSyZUv4+fmhTp064k25f1EfxuyTqFy5sqTuNWvWSMZTqrNs2TKteQCgfv368PLyEtO//fabrHLvk7S0NMnu3m3atIGrq6tOdVStWhX169cX06tWrTJYfMqKYp8yUXHASVFERKRSqVKlJBfwAKBPnz6SGe+aZGZmol+/fjh16pT4WKNGjfD1118bNM4cORcfgbcrvWrbASokJAQbNmwwSiy66tatmyT+6dOn4/Tp02rznz9/Hj/88IPs+j///HOULFkSwNuLs/3799e5wSz3QoEx1a9fH35+fmJ65cqVuH//viSPh4cH+vfvL6b/+OMP2atr5BAEQeUPT0tLS8nqn5GRkZg0aZLaetLS0vDxxx8jNTVVp+PLMWbMGPF+bGys1hWUHz16JMnj6OgoGZhRUJQ/53v37tU6qWzevHmS/yFERERERERE9G6aPn06rK2tAbztv/r5559llXN1dUWPHj3EdEhICHbt2qWxzL59+7Bp0yYx7efnh8qVK+sRtXYeHh7i/cjISKMcQ1c+Pj5o2bKlmP7mm28QERGhUx2ZmZla+3Xed3yd9f/8F5e+TxMTEwwfPlxM//XXX5KVoT/99FOjx0BEVBzZ2tpizZo1klX8e/fujS1bthj8WMrXpSIjI3Hv3j2N+c+ePYs5c+YYPA65jHmd09C8vLzg6+srpocMGSLuxKpQKCTfkURERETGsG/fPly6dEm8KfdD6MuYfRLK/QT37t3D7NmzNdZ95swZrFmzRk7YMDExwbfffiumw8LCMHXqVFlllRWF8YHGEhISgmfPnolp5Xa3LpTLXb9+3Sjj2opinzJRccBJUUREpFaPHj3wxRdfiOlXr16hQ4cO+PHHHzWuhHDu3Dk0adIEW7duFR9zdHTEhg0bJNt7GpLyZJmkpCQMGjRIZYyCIGDlypXo27cvgLc/CgqbhYWFZHXaV69eoV27dpg1axYSEhLEx589e4a5c+fC19cXL1++RI0aNWTVb29vL9l96sqVK2jSpAlOnDihsZwgCDh37hw+//xz+Pj46HhWxjF58mTxfkZGBmbMmJEnz+zZs8WVHDIzM9GlSxfMnTtX6w+3x48fY+HChahWrRouXLigMs8PP/wAd3d3MT1v3jx069ZNkj8rKwsHDhxAkyZNEBoaChcXF8kOU4YwfPhwyQoic+fOxfTp01UOkrhx4wb8/Pzw9OlT8bFff/3VKDu2aaP8d3rr1i2MHTsWmZmZefJlZGTgl19+wYQJEwAUjb9TIiIiIiIiIjKecuXKSfohnzx5Irvszz//LE6oAt7u0LNjxw6Veffs2YM+ffqIaQsLC8yaNUuPiOVp2rSpeD8oKAiHDx822rF0sXjxYnHF0ZSUFLRq1QqBgYFaJ+BER0dj5syZ8PDwkPRbkmrv++us/PkPDQ1FUFCQrJ03ilPf5/Dhw2FqagoAiI+PF8/Pzs5O8r+GiIikOnXqJBk8+vr1a/Tu3Rv9+/dHVFSU1vIZGRkICgqSTEZVRfm6VM7CkcrfGcp27NiBDh06ICMjo1CvSxnzOqehKS8mGRcXJ95v06YNPD09CyQGIiIiIkMyZp/EqFGjUKVKFTE9ZcoULFiwQGXeEydOoGvXrsjKypLdNh08eDDat28vpn/66ScMGzYM8fHxGsu9fPkSwcHBaNu2LebPny/rWMXRypUrxfuWlpb46KOP9KqnX79+kvdEuV5DUe5Tu3v3Lv7880+V4+uISIp7FRMRkUbz5s2DpaUlfv/9dwBAeno6fv75Z/z555/o1KkTateujbJlyyI1NRWPHj3C/v37cfnyZUkdFStWxL59+4za+dm1a1fUqFFD7Cjfvn07vLy80K9fP1SvXh3Z2dmIjo7G9u3bce3aNQBAx44dkZqaiuPHjxstLrk6deqEH374QVwF9/Xr1/juu+8wefJkODs7Q6FQICEhAdnZ2QCA6tWrY/bs2ZItd3MuvqoyaNAgREZGiu/jjRs30LJlS9StWxdt27ZF5cqVYWtri5cvXyIhIQFXrlzBmTNnEBsbC+Dt9q9FQatWrdCiRQucPHkSwNvthCdPnixZzbds2bLYsmULOnbsiOTkZKSnp2PSpEmYNWsW/Pz8ULduXTg6OiIrKwtJSUm4efMmLly4gIsXL2q9KF+iRAls2bIF7dq1E3fb2rFjB3bs2AFbW1s4ODggISFBvDBhYmKC9evXY/jw4Xj+/DkAze+TXJaWlli3bh1atWolbsE8bdo0rF+/Hr1790alSpWQmpqKM2fOICQkRHKhpHv37hg1alS+Y9DHiBEjMHPmTHEwx+LFi/Hff/+hd+/e8PT0RFpaGm7evIlt27aJu4CNHDkS+/fvz7MrGBERERERERG9W7799lssX75c7EORy9vbG/PnzxcHZaampqJbt25o2bIl/P394eLigoSEBOzfvx9HjhyRlP3tt99Qu3Ztg51DbkOHDsXSpUshCAJSU1PRrl07ODk5wdXVVdJHtGLFCjRs2NBoceRWs2ZNrFu3Dn379kV6ejqSk5MxdOhQ/Pjjj/Dz80OtWrVgb2+PtLQ0PH/+HNevX8f58+dlDVKm//O+v84ff/wxpk6dirS0NGRnZ6Nfv34YNWoUypcvDzOz/7tE/dNPP6Fr165iujj1fZYrVw6dOnXKMxFzwIABKFGiRIHFQURUHE2bNg329vaYNGkSsrKyIAgCNm7ciI0bN8Lb2xtt2rSBu7s7nJycYGFhgdTUVMTGxiIqKgpHjhwRr9PlULXzZ7169eDn54f9+/cDeLvavre3N/r164c6derAzMwMDx8+xO7du3H+/HkAQN26deHl5YXg4GDjvwgqGPM6p6H17NkTzs7OeSZx/z/27jssiut9G/hNB+lNRFTABvaKXUBjVOwae8OuMUWNpmiMJSbRGDUxibF8NWKLSEzsQY0Kig0VBRsqKiig0pUmdef9w5f57cA2kAWJ9+e6uK45s+eceXYZnbPDeeZwtUQiIiKqqrR5T8LY2BhbtmzBu+++i7y8PAiCgFmzZuH333/H4MGDUatWLTx//hynTp3C0aNHIZPJ0LhxYzRp0kSjsamenh78/f3RtWtXcW7k1q1b8ccff+Ddd99F+/bt4eDgAH19fbx48QIxMTEIDw9HaGio+D569uz5Oh/fG+vRo0c4efKkWPbx8YGVlVWZ+qpVqxa6du2K06dPAwACAgKwdu1a8cFI5WHAgAGws7MTE+4++eQT8UHuhoaGYr0ZM2ZgxowZ5XZcoqqOSVFERKSSjo4OVq5ciSZNmuDzzz8Xn/KUlZWFgIAABAQEqGw/aNAgrFu3DjVr1tRqnHp6evjrr7/g6ekp3nh98uQJ1qxZo7B+x44d8ccff2Dw4MFajas0li1bBisrKyxcuFD8siEIQoknNnTr1g3+/v64du2aZL+FhYXK/leuXAkXFxfMmTMHeXl5ACAuIaxOeSTylJf58+eLyWAFBQX4+uuv4efnJ6nTsWNHXLx4EYMGDcK9e/cAAMnJydi1axd27dql9hiq3m+bNm1w8uRJjB07Fnfu3BH3Z2Zmil+IAcDW1ha7du3CO++8g9zcXHG/ut+Tplq1aoWTJ0+ib9++4pegqKgofPfdd0rbjBw5Etu3by+X45eFubk59u7dCx8fH3ElN1UxDxgwAL/88gsaNmxYkWESERERERERUSWwsrLC/Pnz8emnn5a67dSpUyEIAj744APxqZkhISFKH4akq6uL1atXY/bs2a8Tslrt2rXD119/jUWLFomTVFNSUpCSkiKpJ39PqaIMGjQIp06dwtChQ8WVueLi4jR+uilX9tbM2/w516pVCxs2bMC0adOQn58PAHjx4kWJSeyKEiGr0r3PadOmlUiKmjJlSoXHQURUFc2ePRstW7bEnDlzJH+vvHfvnvj3PXXs7Owwf/58fPjhhwpf37ZtGzp37owHDx4AANLS0rB+/XqFdd3d3bFv3z4sWbKkVO+jvGnz75zlydDQEL6+vli1apW4z9bW9o36+zsRERFRaWnznoSnpyd2796NUaNGiXP3IiIiEBERUaJu7dq1sXfvXnz//fcax25ra4uLFy9izJgxOHz4MAAgNzcXhw8fFsuqvEnzA8vT1q1bxQfRA8CoUaNeq79Ro0aJSVGZmZnYs2cPJk+e/Fp9yjMxMcGOHTswbNgw8b5xdna2mOxWpOheIxG9UnXvpBMRUYXy9fXF/fv38c0336h9eqq5uTmGDBmCkJAQ7Nu3T+sJUUXc3d1x9epVDB48GDo6OgrrODo6YtmyZThz5gysra0rJK7SmDt3Lm7duoX58+ejRYsWsLKyQrVq1VC/fn0MGTIE+/fvx7///ovq1atL/liso6OjUbLNzJkzcf/+fcycOVPt+zcxMUGPHj2wbt26N2I1rSJ9+/ZFixYtxPLOnTsV/mGkUaNGuHnzJjZs2IDGjRur7bdx48aYO3curl27Bg8PD5V127Rpg/DwcGzatAk9evSAo6MjDA0N4ejoiE6dOmHVqlWIjIxEr169IAgC0tLSxLZlfdKEIu3atcPdu3fx8ccfq/z9N2/eHH///Td2794NAwODcjt+WXh6euLSpUvo1q2b0jr16tXD+vXrceDAAckTLoiIiIiIiIjov+2jjz5CnTp1ytR22rRpuH79OgYMGKD0/oeenh58fHxw7do1rSdEFVm4cCEuXryI6dOni/f75FfJqUydO3fG/fv3sWLFCri6uqqsq6urizZt2mDRokWIiopC9erVKyjKqu9t/pwnTJiAiIgIzJkzBx4eHrCxsdH4/mRVufdZtCJdkZYtW1boym9ERFWdt7c3rl27hgMHDmDAgAGwtLRU26Yo8eavv/5CfHw8PvnkE6V/T3JwcMDly5cxadIkpdcJa2trzJkzB2FhYXBxcXmdt1NutPl3zvI0YcIESXncuHEwMjKqsOMTERERaYM270kMGTIEV69ehZeXl8LXjYyMMHr0aFy9ehWNGjUqdewWFhY4dOgQjh49im7duqm9D1mzZk34+voiMDAQn3zySamP96YTBEHysHUzMzP079//tfocNmyY5Pet6cOPSqN37964desWFi5ciM6dO8Pe3p5z6IjU0BEqev1kIiL6T4iNjcW1a9eQkJCA5ORkmJiYoHr16qhTpw7at29f6YkX8fHxCAkJQVxcHGQyGRwcHFCvXj106tSpSj9dU96CBQuwfPlyAED9+vURFRVVqvYymQxXr15FZGQkkpOTkZWVBTMzMzg4OMDNzQ1NmjT5T920jo+Px8WLF5GQkIC0tDQYGhrC2toa9erVQ9OmTWFvb6+V4967dw9ubm5i+ezZs+jcuXO5Hyc/Px/nzp3D/fv3kZycDGNjYzg4OKBjx45vzB9winvw4AHOnTuHp0+fQk9PD46OjnB3d0ebNm0qOzQiIiIiIiIiqsJevHiB06dPIy4uDs+fP4elpSWcnJzg5eX1Rj4o6U1x//59hIWFISkpCS9evICxsTFsbGzQoEEDNG3atFwf9vM24+dcem/yvc/4+Hg4OzujsLAQAPDrr7/igw8+qNSYiIiqssLCQly7dg0xMTFITk5GamoqDA0NYWVlBTs7OzRv3hx169YtU9/Jyck4c+YMYmJikJeXh+rVq8PZ2Rmenp6V/rdtdSrr75zq+Pv7S560f/PmTTRp0qRSYiEiIiLSBm3ek3j48CHOnTuHJ0+eoFq1aqhduzY8PT1hY2NTPsEDSE9Px7lz5xAXFyeuXm9hYQFnZ2c0btxY7QN8iIiqCiZFERERVVGtWrVCeHg4AGDEiBHw9/ev3IBIoZ9++glz5swB8OpJr+np6TA1Na3kqIiIiIiIiIiIiIjodX377bdYuHAhAMDExARPnjxhYhsREb013n33XZw4cQIA0LFjR5w/f76SIyIiIiIiIqK30X9jqQwiIqK3zJEjR8SEKODVkqn05snKysLatWvFcteuXZkQRURERERERERERPQfUFBQgP/9739iecSIEUyIIiKit8a9e/dw8uRJsTx9+vRKjIaIiIiIiIjeZkyKIiIiekNcvnwZhYWFauvduHEDkyZNEstWVlYYMWKENkMjOdHR0UhISFBbLycnB+PGjUNMTIy4j38MICIiIiIiIiIiIvpv2LZtGx49eiSWZ86cWYnREBERVaxly5ZBEAQAgK2tLf9eTURERERERJWGSVFERERviK+++gpubm745ptvEB4ejoKCAvE1QRBw+/ZtLFiwAB07dkRiYqL42vLly2FiYlIZIb+VQkND4erqismTJ+Po0aN4/vy55PXk5GTs2LEDbdq0wb59+8T9nTp14h8DiIiIiIiIiIiIiP4Djh8/jnnz5onlnj17wsPDoxIjIiIiqhgFBQVYs2YNdu7cKe6bO3cujI2NKzEqIiIiIiIiepvpCEWP7SAiIqJK1bt3bxw7dkwsGxoawtbWFvr6+khJSUF2dnaJNuPGjcP27dsrMsy3nr+/P0aNGiXZZ2trCzMzM2RkZCAtLQ3Fh1d16tRBcHAwXF1dKzJUIiIiIiIiIiIiIioHV65cwZQpUyAIAp4+fYqkpCTxNQMDA4SFhaFZs2aVGCEREZH2bNiwARs2bEBBQQEeP36MjIwM8bW6devixo0bqFatWiVGSERERERERG8z/coOgIiIiF4xMDCQlPPy8vD06VOFdc3MzDB//nzMnz+/IkIjOcV/TwCQkpKClJQUhfV9fHywZcsWODo6ajs0IiIiIiIiIiIiItKCzMxMRERElNivo6ODdevWMSGKiIj+0549e6bwOmhpaYmAgAAmRBEREREREVGlYlIUERHRG+Kvv/7CiRMncOrUKVy5cgXR0dFITk5GTk4OTE1NYWtri2bNmqF79+4YN24cbG1tKzvkt9J7772Hmzdv4siRI7hw4QLu3buHJ0+eIDMzE3p6erCxsUGdOnXg5eWFoUOHwsPDo7JDJiIiIiIiIiIiIqJyoqurCzs7O3Tq1Alz585Fly5dKjskIiKiCmNgYAAnJyf07NkTCxYsgLOzc2WHRERERERERG85HUEQhMoOgoiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIhIU7qVHQARERERERERERERERERERERERERERERERERUWkwKYqIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIqhQmRRERERERERERERERERERERERERERERERERFRlcKkKCIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiKqUvQrOwAiIqqaZDIZwsPDER0djZSUFKSkpMDAwACWlpaoXr06WrRoARcXl8oOEwDg5+eHiRMnimVBEJTW1dHREbe3bt2KCRMmaDM0IiIiov+kvLw8XL58GXFxcUhOTsbz589hZmYGa2truLm5oUWLFjA2Nq7sMIlKLTk5GWFhYUhKSkJycjKys7NhYWEBS0tL1K9fH82bN4epqWllhylycXHBo0ePAACLFy/GkiVLFNZbsmQJli5dCgBwdnZGTExMBUVIREREREREREREREREREREVHZMiiIiolI5fPgwNm/ejNOnT+P58+cq61pZWaFXr14YOnQo+vbtCxMTk4oJkoiIiIgqnCAICAgIgJ+fH86cOYPs7GyldfX19dGlSxeMGzcOw4cPh5mZWQVGSsrExMTAz89PLM+ePRtWVlaVFs+bIjExEWvXrsXhw4dx48YNlQ9Z0NXVRbNmzTBkyBAMGzYMjRo1qsBIiYiIiIiIiIiIiIiIiIiIiN4uupUdABERVQ0hISFo27Yt+vfvjwMHDqhNiAKA58+fY8+ePRg2bBhcXV2xZs0avHz5UvvBEhEREVGFOnnyJFq0aIGRI0fi6NGjKhOiAKCgoADBwcGYPHky6tati19//RUFBQUVFC0pExMTg6VLl4o/moz5/8tycnLw6aefwtXVFd999x2uX7+uMiEKeLWibkREBBYvXozGjRtjwIABuHr1agVFTERERERERERERERERERERPR24UpRRESk1rp16zB79uwSE1UbNmyIbt26oU6dOrC1tYWOjg6ePXuG+Ph4nDp1Cvfv3xfrJiQkYO7cuWjYsCH69etX0W+BiIiIiLTk559/xieffILCwkJxn46ODpo3b45u3bqhZs2asLW1RXp6OhISEnDt2jUEBwcjNzcXAJCUlISPPvoIXbp0QcuWLSvpXRBJxcfHY9CgQbhy5Ypkv6mpKbp06YK2bdvCzs4OlpaWSEtLQ0JCAm7cuIGgoCDk5OSI9Q8dOoQnT56U6IeIiIiIiIiIiIiIiIiIiIiIXh+TooiISKVly5Zh0aJFYllHRwfDhw/H4sWL0ahRI5Vto6KisGHDBmzYsEHtagFEREREVPUoGiuOGjUKy5YtQ926dZW2y8rKwp49e7B06VI8fvy4IkIl0tizZ8/Qvn17xMfHi/tq166NL7/8EhMnToShoaHSti9fvkRgYCCWL1/ORCgiIiIiIiIiIiIiIiIiIiIiLdOt7ACIiOjNFRgYiCVLlohlExMT/Pnnn/D391ebEAUADRo0wOrVqxETE4PJkydrMVIiIiIiqmjHjx+XjBUNDQ2xZ88e7Nq1S2VCFPBqtZ1JkyYhKioKixcvhq4ub0/Qm6GgoADDhw+XJET16NEDN2/exPTp01UmRAGvvjMNGTIEly9fxqFDh1CzZk1th0xERERERERERERERERERET01uJKUUREpFBmZibGjx8PmUwm7vvzzz/Rt2/fUvdlb2+PzZs3o1evXrCystKozcOHD3Hr1i08evQI6enpMDQ0hI2NDRo3bow2bdrAwMCg1HFomyAIuHr1Km7fvo3ExEQIggAHBwe0bt0aTZo0KZdj5OXlISQkBI8ePUJCQgKqVauGgQMHwsXFpVz6JyIiItJEdnY2xo0bJxkr7tq1C0OHDi1VP4aGhliyZAk6dOgAc3Nzjdrk5+fj/PnzePDgARITE2FiYgIHBwd06NDhjR4TZWZmIiQkBHFxcUhOToa5uTmcnJzg7e0Na2vrcjlGfHw8Lly4gNjYWBQWFsLR0RFeXl6oVatWufRfVllZWThz5gzi4uKQlJQES0tLDB8+HPb29pUalyKrV69GSEiIWO7UqRP++eefMn3/6NevH65fv45169Zp3CYrKwvXr1/HvXv3kJycjJycHFhZWcHR0REdO3aEo6NjqeOoCKmpqTh79iyePHmCtLQ0WFlZoU6dOvD29oapqWm5HOPhw4cICwvD06dPkZmZiYYNG5b6/xwiIiIiIiIiIiIiIiIiIiL6b2FSFBERKbRp0yYkJyeL5RkzZpQpIUresGHDlL5WWFiI48ePIyAgAMePH8eTJ0+U1jUzM8OUKVPwxRdfwMHB4bViKg8ZGRn4/vvvsXnzZiQkJCis06BBAyxduhSjRo1S29+ECROwbds2AICXlxeCg4ORnZ2Nr776Clu3bkVaWpqkvqWlJTp16gQ3Nzdx32+//Yb3339f4/dw796912pPREREb5f//e9/SExMFMvjxo17reSE3r17q62TmpqKpUuXws/PD+np6QrrtGjRAkuXLsXAgQOV9rNmzRrMnTsXAKCjo4Po6Gg4OztrHOvatWsxe/ZssXzv3j00aNBAaf2IiAh89dVXOHbsGPLy8kq8rq+vjz59+uCHH35Aw4YN1R5fR0dH3N66dSsmTJiA6OhofPzxxwgMDERhYWGJNgMGDMDatWuVJo15e3vj9OnTJfa7uroqjUMQBKV9+Pr6ws/PDykpKfj0008REBCArKwsSf0mTZogPz8fPXv2FPf9888/8PHxUXrM4o4fP45evXqVuX1xOTk5WLNmjViuVq0aduzY8VoPZLC1tcWiRYtU1omNjYW/vz8OHDiAS5cuIT8/X2ldDw8PfPnllyrP8Yp05swZLF68GCEhIQrPPWNjYwwfPhzLly9Xu2pWTEyM5JwLCgoSz6svvvgCFy9elNR3dnbG0KFDMWbMGPzxxx8AgJo1a+Lx48fQ09PT+D2MHj0au3fvLnN7IiIiIiIiIiIiIiIiIiIiqjy6lR0AERG9eWQymWQyoJ6eHhYsWKDVY8bGxqJPnz7w8/NTmRAFvHrK/k8//YRWrVrhypUrWo1LnYsXL6JBgwb49ttvlSZEAUBUVBRGjx6N4cOHq5zkqEhsbCzatGmDNWvWlEiIKtKwYUN4e3uL5S1btpTqGJs3bxa3q1WrhtGjR5eqPREREb09BEGQjBV1dHSwZMkSrR7z0qVLcHNzw88//6w0IQp4lYA0aNAgjBo1SumYa8yYMWLCgyAI2LlzZ6li2bFjh7jdoUMHlQlRixYtQuvWrXHo0CGFCVEAUFBQgIMHD6JZs2YICAgoVSwAcOLECbRu3RqHDx9WmJQCAAcPHkTnzp0RFRVV6v7LKiIiAs2bN8fWrVtLJEQV6dGjB+rWrSuWX2cMW7t2bUmCVFls375dkuw3duxYSXza8tVXX+Gzzz7DuXPn1H5XuHz5MgYNGoT3339f6e+7IhQUFGDKlCniQxyUxZKTk4Pt27ejUaNGOHPmTKmPs3LlSnTv3r1EQpS8adOmidtPnjxBYGCgxv2npaVh3759YnnChAlMiCIiIiIiIiIiIiIiIiIiIqpCuFIUERGVEBERgfj4eLHcu3dv1K5du8KOb2RkhE6dOqFt27aoVasWLCwskJGRgZs3b+LQoUN4+vQpAODp06fo27cvIiIiUKNGjQqLr0hQUBD69euH7OxscZ+bmxv69euHevXqQV9fH3fv3kVAQABiY2MBAH/++Sd0dHSwZ88ejY6Rl5eHYcOG4c6dO9DR0UH37t3RvXt31KhRA2lpaQgNDYWhoSEAYPr06QgODgYAhIWFITw8HC1btlR7jPz8fGzfvl0sDxs2DJaWlhp+CkRERPS2uX79Oh4/fiyW3333Xa0mjly7dg3vvPMOMjMzxX3169fH0KFDUbduXWRmZiI0NBT79+9Hbm4uAMDf3x85OTmSZIciDg4O6Nmzp5g4sWPHDnz55ZcaxRIZGYmwsDCxPH78eKV133//fWzYsEEs6+rqomfPnvD09ISDgwMyMjJw/vx57N+/H3l5ecjLy8Po0aNhYmKC/v37axTPnTt3MGvWLKSnp8PW1haDBw9G8+bNUa1aNdy/fx9//PGH+Lt68uQJxo8fj3PnzkFXV/qMHCcnJ9SrVw8vX76UPKDA2dkZ+vqlv3WUlpaGwYMH48mTJ+JKWF26dIGtrS2Sk5MRHBwMPT096OjoYOrUqZg/fz6AV8lbiYmJqF69utpjJCcn48CBA2J50qRJJd5XaR05ckRSnjp16mv1Vxaurq7o1KkTmjZtCltbW+jo6ODJkyc4c+YMTp06Ja7QtWHDBlSvXh1Lly6t8BgLCwsxaNAgyedlZGSEvn37okOHDrCzs0NqaiqCgoIQGBgImUyG9PR09O7dGyEhIWjTpo1Gx9m/fz9+/vlnCIKAGjVqYMiQIWjcuDEMDQ0RExOD0NBQAK9W13V3d8edO3cAvEqW69evn0bH2LFjB3JycgC8SvCcPHlyaT4KIiIiIiIiIiIiIiIiIiIiqmwCERFRMT/++KMAQPxZtWqV1o8ZHR0t1K9fX9i0aZPw/PlzpfVyc3OFr776ShLf+PHjVfa9detWSX1V5Ott3bpVab2EhATBwcFBrGtsbCxs2bJFkMlkJepmZ2cL06dPl/S9fft2pX37+vpK6gIQatSoIZw7d05l7Lm5uYKdnZ3Y5sMPP1RZv8jff/8tOVZISIhG7YiIiOjttHbtWsnY4fvvv9fasXJycoTGjRtLjrdw4UIhPz+/RN3IyEjB3d1dUnf9+vUK+929e7ek3qVLlzSKZ/78+WIbQ0NDISUlRWE9Pz8/Sf8tWrQQbt++rbDunTt3hAYNGoh1q1evLiQlJSmNQb5fXV1dAYAwZswYhWPorKwsoXfv3pI2R44cUdp3UFCQpG50dLTqD0SOl5dXiTGsm5ubcOvWLZXtnj17JhgYGJT6u8eaNWskn8OjR480jlURmUwmWFtbi31aWFgoHNtrw5QpU4QJEyaoPQ/Dw8MFNzc3MUY9PT0hKipKZRtnZ2ex/uLFi5XWW7x4sVjP2dlZZZ9LliyR/J67d+8uPH78WGHdCxcuCNWrVxfrNm7cWMjJyVFYNzo6usQ5BECYPn26kJWVpTKm1atXi/X19fWFp0+fqqxfpHnz5mK7d955R6M2RERERERERERERERERERE9OZ4vUfoEhHRf9KlS5ck5Xbt2mn9mE5OTrhz5w6mTp2qcpUiQ0NDfP311/j000/FfXv27EFSUpLWY5T3xRdfICEhAcCrp/7v27cPkyZNgo6OTom6JiYm2LBhA9577z1x31dffQWZTKbRsQwMDHDs2DF06tRJZT1DQ0NMmDBBLO/atUt86rkqmzdvFrfd3d3RpUsXjeIiIiKit1NFjhU3b96M27dvi+VZs2Zh2bJlClcvcnd3x/Hjx2Frayvu+/LLL/Hy5csSdQcOHAgLCwuxvGPHDrWxCIKAXbt2ieW+ffvCxsamRL309HTMmjVLEteZM2fQqFEjhf26ubnh5MmTsLKyAgAkJiZi7dq1auMBAJlMhv79+2PHjh0Kx9DVqlXDjh07JO/1jz/+0Kjv12VtbY1Tp06hcePGKus5ODhg4MCBYnnLli0a9S9fr2fPnqhTp07ZAv3/oqKikJaWJpbbtm2rcGyvDb/88gu2bt0KDw8PlfVatGiBEydOwNraGsCrFZt+++23ighR9PDhQyxbtkwse3l54ejRo0pXFu7QoQMCAwNhYGAAALh9+zZ27typ8fFGjBiBDRs2oFq1airr+fr6wsjICABQUFCAbdu2qe378uXLuH79uliujJXBiIiIiIiIiIiIiIiIiIiI6PUwKYqIiEpITEyUlJ2dnbV+TAMDA+jp6Wlcf9GiReLEuNzcXJw6dUpboZXw7NkzyYTYKVOmoHfv3mrb/fzzz+JkwEePHuGff/7R6Hjvv/8+mjdvrlHdadOmidtpaWn4+++/VdaPj4/HsWPHxPKUKVM0Og4RERG9vYoSw4u4urpq7VjyCR+Ojo749ttvVdavXbs2li5dKpZTU1Ph7+9fop6JiQmGDh0qlv39/VFQUKCy79OnT+Px48diefz48Qrrbd68GS9evBDLW7ZskSQlKYt7wYIFYvl///sfCgsLVbYBAH19faxbt05l8o6dnR2GDBkilkNDQ9X2Wx6++uor1KxZU6O68mPYyMhInD9/XmX9Cxcu4NatW2K5PMawlfEdqIixsbHGdWvVqoWPPvpILAcGBmojJKV++ukn8dw0NDTEtm3bxO84yrRu3VqScLR+/XqNjmVoaKhxgqCtra3kIRSaJNfJPxzC1tYWgwcP1uhYRERERERERERERERERERE9OZgUhQREZWQmpoqKatauamymJmZoUOHDmL58uXLFXbsvXv3Ii8vTyzPmTNHo3Y1a9ZEjx49xPK///6rUbuJEydqHFuDBg3QrVs3sSw/0U+R33//XTKpUdnkXiIiIqIiKSkpknLRCkfl7eHDh5JVonx9fWFqaqq23YQJEyT1Dh8+rLCe/LgnKSkJR48eVdmv/GpStra26Nu3r8J68isxtW/fXu1qn4riSUhIkKxgo8w777yjdIUeefLj5gcPHiA/P1+jmMpKV1e3VOPKHj16oF69emJZ3RhW/vXq1atjwIABpQ+ymKrwHaiI/HeKu3fvIj09vcKOvXv3bnF78ODBGieP+fr6ittXr14t8Xkr4uPjAwcHB41jmz59urgdFRWFM2fOKK2bnZ0tSZgcP348DA0NNT4WERERERERERERERERERERvRmYFEVERCVkZGRIymZmZhq1GzRoEHR0dNT+lBdHR0dxOz4+vtz6VSckJETcrlu3Ltzd3TVu265dO3Fbk6f0m5mZabxKVBH5J+0HBwfj4cOHCusJgoCtW7eK5YEDB8Le3r5UxyIiIqK3T1nHiqVVfKzk4+OjUTtTU1N4e3sr7aeIp6enJKFDPumpuJycHOzdu1csjxw5UuHqOJmZmQgPDxfLyhKnFHFwcJDEo8lYUT7ZSRUnJydxWxAEyUpW2uDm5gZbW1uN6+vo6EhWewoICChxnhXJzMxEQECAWPb19VW7UpEmynpeh4eHa/QdaMmSJa8dYxH570GCIODp06fl1rcqkZGRSE5OFsulOb9btWol/p4EQcClS5fUttE0obCIp6en5LuZqtWiAgICJMlkXDGXiIiIiIiIiIiIiIiIiIioamJSFBERlWBubi4pZ2VlVejxb968iUWLFqFPnz5wdXWFlZUV9PT0Skws3LVrl9jm+fPnFRZfRESEuN2kSZNStZV/0nlcXJza+q6urtDVLd3lesiQIbCzswPwasKhssmAJ0+eRHR0tFieOnVqqY5DREREb6fiY8XMzEytHOfevXuScosWLTRuK59UHh8fj+zs7BJ1dHR0MHbsWLF88OBBpclCBw4ckCRQjBs3TmG9mzdviqtwAtofK9aoUUOjfosn+Gh7fF+/fv1St5k4caKYNJOVlSVZxUeev7+/5Jwrr2SWyv4OVHRMf39/TJgwAW3atIGDgwNMTExKfA9q0KCBpF1FfReS/x4ElO78NjAwgLW1tVjW5Pwuy3kk/51m7969Sv9Ny6821qlTJzRu3LjUxyIiIiIiIiIiIiIiIiIiIqLKx6QoIiIqwcbGRlLWdJKdo6Mj6tWrV+Kn+ARDZR49eoT+/fujWbNmWLZsGQIDAxETE4MXL15AJpOpbJuTk6PRMcpDSkqKuH3o0CGNngxf9DNz5kyxbVpamtpjWVhYlDo+Q0NDTJgwQSz7+flJJucWkZ8I6OLigh49epT6WERERPT2Kb4CkLYSMuTHSoaGhrC0tNS4rXxyUfG+5I0fP17cLr4alDz5VaQaNmyI9u3bK6wnP04EgPfee69UY0X51XM0GSsaGxurraOIIAhlaqepsoxhHRwcMHDgQLGsLLFffgzr6emJhg0blj5ABcr6HcjIyEjhdyD5Vb80sWnTJtSpUwejRo3Ctm3bcPXqVSQmJmr0PaeivgsVP7/btGlTqvM7MTFRbKut70K+vr4wMjICAGRnZ2P37t0l6ty5cwfnzp0Ty1wlioiIiIiIiIiIiIiIiIiIqOpiUhQREZVQvXp1SfnRo0catVu/fj3u379f4mfIkCFq20ZFRaFTp044fPhwidcMDAzg4OCAOnXqKE220vbETnnlNfFX0YoFxenr65ep72nTpkFHRwcA8OTJEwQGBkpeT01Nxf79+8Xy5MmTxfpEREREqhRPOIqJidHKceRXA6pWrVqp2pqamirtS17xBCf55KciSUlJOHbsmFiWT6QqrjwTxDQZK76pXmcMWyQ0NBQ3b96UvH7r1i2EhoaK5fJc6bSs34EaNWqk8DtQcHCwxsf+9NNPMX36dKSmppZ4zcrKCk5OTqhbt67ShKuK+i5U0ed3Wc4jW1tbvPfee2JZPolO0T4LCwsMHz681MchIiIiIiIiIiIiIiIiIiKiN0PZZqkQEdF/Wrt27SRP1L506RK6du2qteMJgoCJEyfiyZMn4j4fHx9MmjQJHTt2RM2aNRUm7Pj6+mL79u1ai0uZatWqIT09HQBgbW1d4qnyb4IGDRrA29sbQUFBAF49ab9fv37i6zt27EBubi4AQE9PDxMnTqyUOImIiKjqadeuHXbt2iWWL126BC8vr3I/jpmZmbhd2gShrKwspX0VN27cODHR5syZM3j06JEk6WT37t0oKCgAAOjo6GDs2LFK+yqevFWnTh0YGBiUKvYixZN03gY9evRAvXr18ODBAwCvxrA//vij+Lp8MouVlRWGDh1absdu0KABrK2txRWMrly5AkEQtP7ggH///RerVq0Sy3Z2dvj444/Ru3dvNG3aFCYmJiXaREdHo27dulqNS5Hi53e9evXK3Je1tfXrhqPU9OnT8ccffwAAwsLCEBERgRYtWgAA8vPzJcmPo0aNKpFESURERERERERERERERERERFUHk6KIiKiE4pNag4ODMXfuXK0d79KlSzh37pxYXrBgAb799lu17crzSeWlYWdnJyZFDRs2DBs3bqyUONSZNm2amBR1+PBhJCQkiCs7bNmyRazn4+MDJyenSomRiIiIqp7iY8WTJ0/i008/LffjyCdN5OXl4cWLF7C0tNSobWJiotK+ihs5ciQ++eQT5OXlQRAE7Nq1CwsWLBBfl0+g8PT0LLFKjzw7OztJ2d/fHx07dtQoZnqVdDZlyhTMnz8fwKvP/vvvv4ehoSHy8vKwc+dOse7YsWNhbGxcrsfu2rUrDh48CABIT0/H1atX0aZNm3I7hiJr1qwRtx0cHHDlyhXUqlVLZZvK/B4kLyQkBI6OjpUSiyqenp5wd3fHnTt3ALxKpvvll18AAAcPHpT8/1Ceq40RERERERERERERERERERFRxdOt7ACIiOjN06JFC0mSTGBgIOLi4rR2vJMnT4rbFhYWWLRokUbtHj58qK2QVHJ3dxe3b926VSkxaGLIkCGwt7cHABQUFGDbtm0AgNDQUNy4cUOsN2XKlEqJj4iIiKqmZs2aoU6dOmL533//RXR0dLkfp2HDhpJyRESExm2vX78ubjs5OZVY4Uaera0t+vTpI5blk6Du3LmDK1euiOXx48erPK6bm5uk/CaPFd9UEydOFFfXSklJwf79+wEA+/btQ3JyslhPG2PYvn37SsqbNm0q92PIk8lk4kMMAGD27NlqE6KAN+N7EPBmn9/Tpk0Tt3ft2oWcnBwA0tXGWrZsqfWkNyIiIiIiIiIiIiIiIiIiItIuJkUREVEJurq6mDNnjlguLCzUaOWmsoqPjxe33d3dYWRkpLbNs2fPKm0SXrdu3cTtixcvSiZnvkkMDQ3h6+srlotWh5JfJcrR0bHE5E8iIiIiVXR1dfHJJ5+IZZlMhq+//rrcj9OhQwdJOTAwUKN22dnZCA4OVtqPIuPGjRO35ROh5BOkTExMMHToUJX9VK9eHU2aNBHLhw4d0ijmN0VRMlIRmUxW4TE4ODhg4MCBYrkoiUV+DOvh4YEWLVqU+7HHjRuH6tWri+WdO3dqJeGvSEpKCnJzc8Wypu9J/qESFal169aS1dre5PPb19dX/F6ZlpaGv//+G3FxcTh+/LhYh6tEERERERERERERERERERERVX1MiiIiIoWmT58OW1tbsbxhwwYcOXJEK8cSBEHcLnqCtzo///yzpF1FGjp0KPT19QG8Shj74YcfKiUOTUybNg06OjoAgHv37uHo0aPw9/cXX58wYYL4XoiIiIg0NXXqVEnyiJ+fn7iiT1kcPXoUDx48kOxzdXWVJBht374d2dnZavvatm0bMjMzxXK/fv3UtunXrx9sbGzE8o4dOyAIAnbt2iXuGzhwICwsLNT2NXLkSHH78OHDb/RqOsWZmZlJyi9evKiUOKZPny5unzhxAqdPn5YkAmlrpVMTExPMnj1bLGdnZ2Ps2LHIz8/XyvGKf5/R5LtQSkqKJFmvIunp6UkSA7du3YrExMRKiUUdGxsbSaxbtmzB77//Lib6mZiYYMyYMZUVHhEREREREREREREREREREZUTJkUREZFCZmZm2LZtm5hQAwDDhg3DX3/9Ve7HqlOnjrh98+ZNxMTEqKx/6dIlrFq1qtzj0JSLiwtGjRolltesWSN54rgmBEFAXl5eeYdWQoMGDeDt7S2WJ0yYgIyMDACAjo4OJk+erPUYiIiI6L+nWrVq2LFjB3R1/++2wsiRI0s9VszLy8OSJUvQt29fcYwib+bMmeL2kydPsGjRIpX9xcXFSerY2NhIkpSUMTQ0xIgRI8Ty7t27cfLkSTx69EjcN378eLX9AMCHH34oJk/JZDKMGjWq1MlFmj4ooLy5uLhIyjdv3qyUON555x3Uq1cPwKtx84gRI8RkFlNTU8lYvLzNmzcPnTp1Esvnz59Hnz59tJIgZmtri2rVqonlw4cPq6wvk8kwdepUSdJfRfv888+hp6cHAMjIyMDo0aNLnTRWUef3tGnTxO2goCD8+uuvYnnYsGGSVa+IiIiIiIiIiIiIiIiIiIioamJSFBERKdW3b1/JpNKXL19i2LBhGDVqFG7fvq22fX5+Pvbs2YPg4GCV9Xr16iVuF00cTU5OVlj34MGD6NmzJ/Lz8yWTcCvaypUr4ejoCAAoKChA//79sXr1arUT/J4+fYpffvkF7u7uuHr1akWEKpkMmJCQIG5369ZNnGxKREREVFo9e/bEkiVLxHJubi6GDx+O8ePHIzo6WmXbrKws/P7772jYsCGWLl0qJrwUN3nyZMlqUatXr8bSpUtRWFhYou7du3fRq1cvyTjyu+++g7GxsUbvRz7pKSkpCe+//75YdnBwQM+ePTXqx8rKCr/88otYvnHjBtq3b4+zZ8+qbCcIAi5fvowPP/wQXbp00ehY5c3S0hLu7u5ieeXKlXj48GGFx6GjoyNZDUp+DDtixAiYm5tr7dgGBgb4888/xbE+8Gq1qmbNmmHjxo0aPdggOjoa3377rdp6enp66NGjh1j28/PD9u3bFdZNSUnBiBEjsG/fvkr9HtSgQQN89dVXYvnkyZPo2rUrbty4obJdYWEhgoODMX78eAwfPlzbYQIAPD09xfNZEAQkJSWJr2lrtTEiIiIiIiIiIiIiIiIiIiKqWPqVHQAREb3ZlixZAisrK8ybNw+FhYUQBAH+/v7w9/dHw4YN0a1bNzg7O8PW1haGhobIysrCkydPcPv2bQQFBZV4onrdunVLHKNVq1bo1asXjh07BgC4ePEiGjZsiJEjR6JFixbQ19dHbGwsjhw5gitXrgAAWrZsiQYNGuDPP//U/oegQI0aNfDXX3+hd+/eSE9PR15eHubNm4cVK1agV69eaNmyJWxsbFBYWIjnz5/j3r17uHr1Kq5duwZBECo01iFDhsDe3l4yCRAApk6dWqFxEBER0X/PV199BQsLC8ydOxeFhYWQyWTYsWMHdu7ciZYtW8Lb2xs1a9aEra0t0tPTkZCQgKtXryI4OBi5ublq+zcyMsKOHTvg6ekpro6zZMkS7Nq1C8OGDYOrqyuysrJw8eJF7N+/X5KgPmjQIEyfPl3j99KhQwc0aNAAUVFRAID79++Lr40ePVpcHUcT48ePx82bN/HDDz8AeJWw1bVrV7Rs2RLdu3dH3bp1YWZmhszMTCQlJeHGjRu4ePEinjx5AgBwc3PT+FjlbdKkSfjss88AvFopql69eqhduzasra0lq8iGh4drNY6JEydi0aJFJVYhqogxbM2aNREaGoqBAwfi2rVrAIDY2FjMmDEDc+fORZcuXdC2bVvY2dnBysoK+fn5eP78OR48eIDQ0NASn42urm6JVbiKfPHFFzh06BAEQYBMJoOvry+2bNkCHx8f1KhRA+np6QgLC8OBAwfE71bLli3Dl19+qc2PQKVFixYhMjISe/bsAQCEhoaiefPm6NSpEzw9PVGnTh1Uq1YN6enpePbsGa5fv44LFy4gJSUFgPShGNo2bdo0fPLJJ5J9bm5u6Nq1a4XFQERERERERERERERERERERNrDpCgiIlJr9uzZaNmyJebMmSOZ4Hfv3j3cu3dPoz7s7Owwf/58fPjhhwpf37ZtGzp37owHDx4AANLS0rB+/XqFdd3d3bFv3z7JygSVoWPHjrh48SIGDRokfg7JycnYtWsXdu3apbZ9aSbWvg5DQ0P4+vpi1apV4j5bW1sMHjy4Qo5PRERE/22zZs1CkyZNMGfOHNy8eRPAq1VZrl27JiaUqOLo6IilS5eiWbNmCl9v1aoVTp48ib59+4qrQEVFReG7775T2ufIkSOVrrijyrhx4yQrpRaRX0VKUytXroSLiwvmzJkjri4UHh6uUTJRRY0TFZkzZw6CgoIQGBgo7ouNjUVsbGyFxuHg4ICBAwdi79694r4mTZqgQ4cOFXL82rVr49y5c/jyyy+xYcMGvHz5EsCrVc6OHTsmPtBBnd69e2PlypVKz++OHTvihx9+wLx588R9Z86cwZkzZ0rU1dXVxbJlyzB69OhKTYrS0dHB7t270aBBA3z33XfiSm/nz5/H+fPn1bavyPPb19cX8+fPlyRhcpUoIiIiIiIiIiIiIiIiIiKi/w7dyg6AiIiqBm9vb1y7dg0HDhzAgAEDYGlpqbZNUeLNX3/9hfj4eHzyyScwNDRUWNfBwQGXL1/GpEmTYGBgoLCOtbU15syZg7CwMKVPWq9ojRo1ws2bN7FhwwY0btxYbf3GjRtj7ty5uHbtGjw8PCogwlcmTJggKY8bNw5GRkYVdnwiIiL6b+vRoweuX7+O3bt3o1evXqhWrZrK+gYGBnjnnXewbds2PHjwAFOnTlWZKNGuXTvcvXsXH3/8MSwsLJTWa968Of7++2/s3r1b6ZhSlXHjxklWQwKAZs2aoWXLlqXuCwBmzpyJ+/fvY+bMmbC2tlZZ18TEBD169MC6desQEhJSpuOVB319fRw5cgR79+7F8OHD0aBBA5ibm5f4XCpC8TFsRa90amJigjVr1uDhw4f44osv0LRpU7Wfg56eHpo1a4ZFixbh/v37CAwMVJoQVWTu3LnYv38/GjZsqLROhw4dcPLkSSxYsKBM76W86ejoYNmyZbh58ybGjBkDMzMzlfXNzc3Rv39/+Pn5iStMVQQbGxv0799fLBsYGMDX17fCjk9ERERERERERERERERERETapSMIglDZQRARUdVTWFiIa9euISYmBsnJyUhNTYWhoSGsrKxgZ2eH5s2bo27dumXqOzk5GWfOnEFMTAzy8vJQvXp1ODs7w9PTs0yTWytSfHw8Ll68iISEBKSlpcHQ0BDW1taoV68emjZtCnt7+0qJy9/fH6NGjRLLN2/eRJMmTSolFiIiIvrvy8vLw6VLlxAXF4fk5GS8ePECZmZmsLa2hpubG1q2bFnmBO38/HycO3cO9+/fR3JyMoyNjeHg4ICOHTu+MYnzishkMly9ehWRkZFITk5GVlYWzMzM4ODgADc3NzRp0oRJ68WsWLEC8+fPBwAYGRnhyZMnsLGxqdSYkpKSEBYWhsTERKSkpODly5ewsLCAtbU1nJ2d0apVK5iampap76JzJCwsDCkpKTAzM4OjoyPatm0LV1fXcn4n5Ss/Px+hoaHiv8vc3FyYm5vD0dER7u7uaNSoEfT1K2fB+kaNGuHOnTsAgKFDh+LPP/+slDiIiIiIiIiIiIiIiIiIiIio/DEpioiI6C3w7rvv4sSJEwCAjh074vz585UcERERERGRcoIgwM3NDVFRUQCAUaNG4Y8//qjkqKiqOXfuHLp06SKWjx07hp49e1ZiRERERERERERERERERERERFSedCs7ACIiItKue/fu4eTJk2J5+vTplRgNEREREZF6J06cEBOiAI5hqWx+++03cbtu3bp49913KzEaIiIiIiIiIiIiIiIiIiIiKm9MiiIiIvqPW7ZsGYoWhrS1tcWIESMqOSIiIiIiItWWLVsmbjdp0gReXl6VGA1VRXfv3kVAQIBYnjFjBnR0dCoxIiIiIiIiIiIiIiIiIiIiIipvTIoiIiL6jyooKMCaNWuwc+dOcd/cuXNhbGxciVERERERESn38uVLzJs3DyEhIeK+L7/8shIjoqro3r17GDlyJAoKCgC8ejjEjBkzKjkqIiIiIiIiIiIiIiIiIiIiKm86QtHSEURERFTlbdiwARs2bEBBQQEeP36MjIwM8bW6devixo0bqFatWiVGSEREREQktWjRIhw8eBC5ubl49OgRXr58Kb7WqVMnhISEQFeXz/Uh1Vq2bAkASEtLQ1xcHGQymfjahg0bMH369EqKjIiIiIiIiIiIiIiIiIiIiLRFv7IDICIiovLz7NkzRERElNhvaWmJgIAAJkQRERER0Rvn8ePHCsewtWrVwq5du5gQRRpRdA4BwLhx4zBt2rQKjoaIiIiIiIiIiIiIiIiIiIgqAmeVEBER/UcZGBjAxcUF06ZNQ0REBNq0aVPZIRERERERqWRkZISGDRti7ty5uHbtGlxcXCo7JKqCLCws0LVrV/j5+WHbtm3Q0dGp7JCIiIiIiIiIiIiIiIiIiIhIC3QEQRAqOwgiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIk1xpSgiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiqlKYFEVEREREREREREREREREREREREREREREREREVQqTooiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIioSmFSFBERERERERERERERERERERERERERERERERFVKUyKIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIqIqRb+yAyAiIiIiIiIiIiIiIiIiel0uLi549OgRAGDx4sVYsmRJ5QZEryUmJgaurq5iOSgoCN7e3pUXEBERUTmaMGECtm3bBgDw8vJCcHBw5Qb0houPj8fVq1eRmJiIpKQkmJiYwMHBAbVr10a7du1gYGBQ2SFKeHt74/Tp0wAAX19f+Pn5VW5AWiYIAq5du4br168jKSkJurq6qFmzJpo1a4amTZtWdnhERERvFE3HgcHBwejWrZtYjo6OhouLSwVESFR6jx8/RkREBJKTk5GcnAyZTAYrKyvUqFEDrVu3Ru3atTXq520bR1P5YVIUERERERERERERERERlQs/Pz9MnDhRsq9x48a4fv069PT0NOqj+B/8Dx06hH79+pVrnPTmCg4OFieDWFlZYfbs2ZUaj7Yp+jdTnJGRESwsLODk5IRWrVqhV69eGDRoEIyMjCooSiIiovLB6x6VRlZWFn7++WcEBAQgPDxcaT0LCwv07NkTc+bMQadOnSouQEJmZibWrl2LtWvXIikpSWGdRo0aYd68eZg0aVIFR0dERFWFfJIQAMTGxqJWrVoatR0xYgQCAgLEsre3N4KCgjRqm5mZCWtraxQUFAAA3n33XRw/frwUkRO93WJjY7FmzRr8888/uHfvnsq6jo6OGD58OMaPH4/WrVu/9rHDw8Oxf/9+scyHY5FuZQdARERERERERERERERE/123b9+WTGwgUiU4OBhLly7F0qVL8dNPP1V2OG+E3NxcJCUlITw8HFu3bsXIkSNRu3Zt+Pv7V3ZoRERE5Y7XPQKAnTt3okGDBliwYIHKhCgASE9Px969e9G5c2cMHToUT58+rZgg33J37txBmzZtsHDhQqUJUQAQGRmJyZMno2/fvsjKyqrACImIqKqQfzgSgFKtoFm0okyRCxcuICcnR6O2ISEhYkKUojiISLGsrCzMmjULDRo0wE8//aQ2IQoAnj59irVr16JNmzYYMGAAIiMjXyuG8PBw8R7y0qVLX6sv+m/gSlFERERERERERERERESkVYsXL8bo0aNhbGxc2aEQvdGqV68Oc3Nzyb6cnBwkJycjNzdX3JeUlIRRo0YhLi4O8+bNq+gwiYiIygWve6TIggULsHz5csk+U1NT9OnTB82bN0eNGjWQlZWFuLg4HDt2DDdu3BDr/fXXXwgLC8PRo0fh5uZW0aG/NWJjY+Hl5YXExERxX40aNTB8+HA0atQIwKuHY/z555949uwZAOCff/7B8OHDcfDgQY1XESYioreDoqSosWPHqm0XGRmJhIQEyb7c3FxcvHgR3t7eatsXT75iUhSRenFxcRgwYACuXbsm2W9lZYV33nkHzZo1g729PQwNDZGQkIDHjx/j33//RXR0tFj30KFD0NXVlaz0RPS6mBRFREREREREREREREREWhUXF4eff/4Zn332WWWHQvRG+/777zFhwoQS+wsKChAaGoqVK1fi4MGD4v7PPvsM3t7eaNu2bQVGWTFcXFwgCEJlh0FERFrE6x4V98knn+DHH38Uy4aGhvj000+xYMECVKtWrUT9H374AZcvX8b06dPFiZkxMTHo3LkzLl++DFdX1wqL/W0yatQoSULU6NGjsXHjRpiZmUnqfffdd5gyZQr27NkD4FVi1A8//IAvvviiQuMlIqI3W506dVC3bl08fPgQABAUFKRRO/mkJjMzM2RmZortS5sUZWZmxjEmkRrPnj1Dhw4dEB8fL+6rXbs2vv76a4wbN05l4vvNmzexfPly+Pv7QyaTKa1XmpXiiOTpVnYARERERERERERERERE9N9Uo0YNcXvFihVIS0urxGiIqi59fX107twZBw4cwIcffijuFwQB33zzTSVGRkREVP543Xs7HTx4UJIQVa1aNRw/fhzffPONwoSoIh4eHrh06RKGDBki7ktJScGoUaNQUFCg1ZjfRoGBgTh37pxY9vT0xI4dO0okRAGvJpj/8ccf6Ny5s7hv+fLlSE5OrpBYiYio6pBfpenhw4eIjY1V20Y+eWrmzJnitiZJFZmZmbh69apY7tq1K/T1uc4IkTKFhYUYOXKkJCHKy8sLN27cwIQJE9SuBNq0aVPs2rULV69eFVcWJSpP/B+ciIiIiIiIiIiIiIiItGLRokXipIS0tDQsX74cK1eu1Ppxb926hYiICCQmJiI3NxcODg5o2rQp2rRpAx0dHa0fXxsEQcDVq1cRGRmJpKQkZGdnw8LCAnXr1kWrVq1Qs2ZNjft6/vw5rl+/jqioKKSmpiI/Px/W1taoVasWOnfuDBsbmzLHGRkZiWvXriEhIQFZWVkwMjKCpaUlnJ2d0axZs1LFWdGqynmzYsUKbN++Henp6QCAEydOIC8vD4aGhhr3kZqairNnz+LJkydIS0uDlZUV6tSpA29vb5iampY5tuTkZAQFBSEuLg6CIMDJyQkeHh6oW7dumfssq7i4OJw/fx7Pnj1DdnY27OzsULduXXTp0qVUn5UqqampOH36NGJjY5GTk4Pq1aujS5cuqF+/frn0T0REr3/dk8lkuHz5MiIjI5GYmAh9fX04ODigdevWZZ6MJ5PJcP36dVy/fh1JSUl4+fIljI2NYWNjA2dnZ7Ro0QJ2dnZl6vtNcf/+fVy5cgVxcXHQ09NDrVq10K1bN629r/T0dEyaNEmyLyAgAF5eXhq119fXh7+/P7y9vXH+/HkAEFcbW7BgQbnHq23R0dG4fPmyOKa2t7eHm5sbOnbsqHbCqbZt375dUl65ciV0dZU/l11XVxcrV64UE6PS09OxadOmKvl7ISIi7enWrRu2bNkiloOCgjB+/HiVbU6fPi1uz549G+vXr0dGRgYuXryIly9fwsTERGnbkJAQSfK0fFKWMklJSQgJCcHTp0+Rnp4OW1tb1K5dG56enq91L0VboqKicPnyZfE+V/Xq1eHm5ob27duX23giPj4eFy5cQGxsLAoLC+Ho6AgvLy/UqlWrzH3eu3cPoaGhePLkCczMzFCrVi14enrC2tq6XGJ++fIlQkJC8OjRIyQnJ8Pc3Bw1atRA165d4eDgUC7HkMlkOHv2LKKiopCYmAgrKys0atQIXbp0KXPyXU5ODoKCghAdHY2MjAzUrFkT7u7u8PDwKJeY1fnxxx8l/+batGmDY8eOwcjIqFT9tGjRApcuXcJff/1V3iHS204gIiIiIiIiIiIiIiIiKgdbt24VAIg/N27cEPr16yeWjY2NhdjYWJV9BAUFSfo4dOiQRsfOyckRVq1aJdSpU0fSXv7HyclJ+PXXX4WCggKl/dy4cUPS5tq1ayqPO3z4cEn9Dz74QGX948ePS+o/e/ZMZf3ExERhzpw5gp2dndL3BUBo0qSJ8P333ws5OTkK+7lz546wZMkSoU2bNoKurq7SfnR0dIR33nlHOH36tMq45MlkMmHjxo1CgwYNVMYIQHBxcRFmz54tyGQySR/q2hX/8fLyKhGHs7Oz+PrixYs1ir28zpuyKv5vZuvWrRq169Wrl6TdvXv3NGp3+vRpwdvbW9DT01P4Xo2NjYXx48cL8fHxpXofT548EYYPHy7o6+srPKe6desmREREKHzPykRHR0vqBQUFaRRLYGCg0LZtW6W/TzMzM2HGjBlCYmKiRv0pOq+SkpKEsWPHCkZGRgqP0aVLF/H9EhHR/6nI615WVpawZMkSwd7eXuk1oV69esKWLVuEwsJCjeLIzc0Vli9fLjg5OakdqzRq1Ej49ttvlfbl6+urclyzadMmSX+3b9/WKMYiGzduVNle2XX26tWrgpeXl8L3pKurK0yYMEFISkoqVSyaWLVqleRY48aNK1M/t27dEgwNDcV+7O3thZcvX5ao5+fnJzne9OnTNer/5MmTkrG0j49PiXGtIAiSz9DX11ejvgsLC4Xff/9dcHd3V3pe2draCkuXLlX4nopo+9xxcHAQX6tVq5bG/cr/u2ndunWpYiIiov+++Ph4yfVn4sSJKuvfunVLrNu4cWNBEAShd+/e4r6TJ0+qbP/ZZ59JjnflyhWldS9evCh069ZN6f00IyMjYeTIkUJ0dLRG71XdOLBI8XukmvQvk8mEnTt3qhxP2NjYCPPnzxcyMjI0ilfR+P3hw4dCv379lN5fGjBggMafR5HQ0FChXbt2Ku9XpaSkCIKg+WcoLzY2Vhg/frxgYmKi8Bg6OjpCly5dhDNnzmjU3+LFi8W2zs7O4v5ffvlFqFWrlsJj2NvbCxs3bizV55KTkyMsWLBAsLCwUNinu7u7EBAQIAhC2e+laRJDjRo1JOd8aceYmlI3jpa/T6fJT9HvprCwUKhdu7a4f/jw4aWKq7CwUPJ7LW170j7lj2kgIiIiIiIiIiIiIiIiek0rVqwQnxyek5ODRYsWlfsxoqKi0KxZM8ybNw+PHz9WWi8+Ph4ffvghunfvLq42UFzTpk1RvXp1sXzq1CmVxw4ODpaU1dWXf71x48Yqn0C6b98+1K1bFz/++COSk5NV9nvr1i18/vnnePr0qcLXp0+fjiVLliAsLAwymUxpP4Ig4OTJk/D29sY333yj8pgAkJeXh0GDBmH69OmIiopSWz8mJgY//fQTCgsL1dbVtvI8byqara2tpKzu/CgoKMCUKVPg5eWF4OBgpZ9/Tk4Otm/fjkaNGuHMmTMaxRIWFoYmTZogICBA8pTlIoIgICgoCB06dMDevXs16rMsCgsLMXnyZPj4+ODKlStK62VmZmLDhg1o2LAhQkJCSn2ciIgItGzZEjt37kRubq7COmfPnkWXLl1w8eLFUvdPREQllfa6d//+fTRr1gxLlixBUlKS0noPHjzA5MmT0aNHD7XX+BcvXsDT0xPz589HfHy82pgjIyPx22+/qa2nzKhRo2Bubi6W5VdO0MTmzZvF7U6dOmm0KtbOnTvRsWNHyRPg5clkMvj5+cHLy0vl51paMpkMP//8s1jW0dHB0qVLy9RX48aNMXLkSLGclJSEnTt3lqjn6+uL0aNHi+WNGzfi77//Vtl3cnIyxo4dK46la9SogW3btpXLiqIJCQno2LEjJk2ahDt37iitl5KSgsWLF6NNmzZ48uSJwjraPHdycnKQkJAglps3b65xv/J1r169iri4uFLFRURE/201a9ZEw4YNxXJQUJDK+vKve3t7A4BkhUl17eXv51laWqJVq1YK6y1atAgdO3ZEUFCQ0vtpubm58Pf3R6NGjbR630Od7Oxs9O3bF2PHjlU5nkhNTcXy5cvRuHFjREZGlvo4J06cQOvWrXH48GGl95cOHjyIzp07a3SvEAD+97//oWPHjrh06ZLC14vuV7Vq1apMMR8+fBhubm7Yvn07Xr58qbCOIAg4e/YsPD09MW/ePAiCUKpj5OfnY8iQIfjoo4+UjnOSkpIwffp0fPrppxr1mZqaig4dOuC7775T+n3lzp07GD58uMZ9lsXOnTvx7NkzsTxy5Mgyr7pbWXR1dTF58mSxvH//fqSkpGjc/ujRo5Lf65QpU8o1Pnp9ZVuDjYiIiIiIiIiIiIiIiEgDTZo0wfjx4+Hn5wcA2L59O+bOnYsmTZqUS/+3bt2Ct7e3ZHJs7dq1MXDgQLi7u8PY2BjR0dHYu3cv7t69CwA4c+YMfHx8cPr0aejrl/xzmbe3NwICAgC8SmL65JNPFB775s2bSExMlOyLjIzEs2fPUKNGDYVt5CdldOvWTen72rJlC6ZNmyaZcFGnTh307dsXbm5usLCwwPPnz3Hr1i2cPn0a9+/fV9pXcY0aNULHjh3RqFEjWFtbo6CgALGxsTh58qSYxCEIAr766is4OTlh4sSJSvtavHgxDh48KJZtbW3Rv39/NGvWDDY2NsjPz0dKSgpu3bqFs2fPIiYmRmE/9erVA/Dqj/1paWkAAH19fTg7Oyus7+TkpPH7VUQb501FKj4Z3MDAQGndwsJCDBo0CEeOHBH3GRkZoW/fvujQoQPs7OyQmpqKoKAgBAYGQiaTIT09Hb1790ZISAjatGmjtO/o6Gj07NlT/J0Br87TYcOGoWHDhsjLy0NERAT27t2L58+fw9fXFx988MFrvHPlfH19sWvXLrFsaGiIfv36oUuXLjA3N0dMTIzk9/n8+XP06tULJ06cQKdOnTQ6RkJCAvr374/4+HiYmZlh4MCB8PDwgLm5OWJjY7Fnzx5xck5GRgZGjx6Nmzdvolq1auX/homI3iKlue7Fxsaia9eukkl7NWvWxIgRI+Dm5oa8vDxcu3YNe/fuRUZGBoBX47N3330XISEhMDQ0VNjvjBkzEBoaKpadnJzQv39/NGrUCJaWlsjJyUFSUhJu3ryJ4OBgSeJIWZiZmWH06NHYuHEjgFdj6OXLl6t870Vu3LiBy5cvi+WpU6eqbXP69Gl8++23yM/PR61atTB48GC4u7vDwMAAt2/fxs6dO8Xfw+3bt/Hhhx9iz549ZXx3UhEREZIE9W7dusHV1bXM/U2ePBnbt28Xy4cPH1Y4aXHDhg24ePEiHj58CODVxEYPDw/Url1bYb8TJ04UH0Cgo6OD7du3w97evsxxFnn69Cm6dOkixgEA9vb2GDBgAJo3bw4zMzPExcXh4MGDCAsLA/Dqd+Dl5YWwsDBYWFhI+tPmuZOamiopW1tba/w+i9eNiIhArVq1NG5PRET/fd7e3rh37x6AVw/VefTokdL7QvJJTUXJUPJJUcUfYiQvIyNDvKYWtSt6oJO8L7/8Et99951Y1tXVxbvvvot33nkHNjY2iI+Pl1yfc3JyMGLECAQEBOC9995T/4bLUUFBAfr06SNJbjc1NcV7772HNm3awNjYGPfu3UNAQABiY2MB/N+4+eLFi6hfv75Gx7lz5w5mzZqF9PR02NraYvDgwWjevDmqVauG+/fv448//hDHdU+ePMH48eNx7tw5hZ9vkX379mHGjBmSe6Bt27ZF//794eTkhOfPn+PMmTP4559/8PjxYwwdOrRU95UDAwMxePBgyYN8WrRogUGDBqF27dpIS0tDUFAQjh07JiZ5rV69GgUFBfjpp580Ps6HH36Iffv2AQC6dOmCnj17ombNmsjMzERwcDAOHDggJlqtWrUK3bt3h4+Pj9L+8vPz4ePjg/DwcHGfhYUF3nvvPbRq1QpGRka4f/8+9u7di+joaKxatQqmpqYax1sahw8flpSnT5+uleNowsXFBfr6+sjIyJDcly+6t1yc/HhzypQpWLZsGQoLC5GXl4cdO3Zg9uzZGh1X/sEBrq6u6NGjR9neAGlPZS5TRURERERERERERERERP8dW7duFQCIPzdu3BAEQRAeP34sGBsbi/v79++vtI+goCBJH4cOHVJaNzs7W2jSpIlYV1dXV1i+fLmQl5dXom5BQYGwdOlSSd9ff/21wn7Xr18v1jE3Nxfy8/MV1vv555/Fenp6euL2H3/8obB+enq6oK+vL9b766+/FNYLCwsTjIyMxHqGhobCzz//rDQOQRCE0NBQYciQIcKjR48Uvu7j4yPMmjVLuH37ttI+BEEQTp06JTg6Okre//PnzxXWzcrKEkxMTCS/14yMDJX9h4WFCePHjxcKCgoUvr548WKxP2dnZ5V9Fefs7Cy2Xbx4sdJ62jpvyqL4v5mtW7eqbZORkSGYm5tL2iUnJyutv2TJEknd7t27C48fP1ZY98KFC0L16tXFuo0bNxZycnKU9v3uu+9K+p45c6bC+gkJCUL37t3Fz1u+jTLR0dGSekFBQUrrbt++XVK3QYMG4v8/8goLC4Wvv/5aUrdevXpCZmam0r7lz6ui2Hv06CE8ffq0RN38/Hxh0qRJkv7XrVuntG8ioreNtq97MplMeOeddyR1J02aJGRlZZWoGx8fL3Tu3FlS9/PPP1fYb/Fr0rRp04Tc3FylMRcWFgrBwcHC+++/r7SOr6+v2J+Xl5fCOlevXpUcd+/evUr7k/fxxx+LbSwsLBS+/+LvqegaN3fuXIXX8uTkZKFVq1aSNrdu3dIoHnXWrl0r6ff7779/rf4KCwsFU1NTsT9bW1tBJpMprBsaGioYGBiIdbt27apwnPrTTz9JYvz0009VxuDl5SXW9fX1VRlr8XN21qxZSscmmzZtknzvmDRpksJ62jp3UlNTJf0OGTJEo34FQRAGDx4sabty5UqN2xIR0dth9+7dGo0VZTKZYG9vL9Z79uyZIAiCkJeXJ1SrVk28l6ZoDCQIgnDkyBHJcX788ccSdYKDgwUdHR2xjr29vXDmzBmF/W3evFlyv8/a2lqIj49X+j41GQcKQsl7pNHR0UrrFr/X0a5dO4X3CHNycoQZM2ZI6nbq1EkoLCxU2reiMeOYMWMU3i/MysoSevfuLWlz5MgRpX2npqYKDg4OYl19fX3h999/V1g3LCxMqF27dol7S6o+w6SkJEn/urq6wm+//aaw7oULFyT3RAEI//zzj9K+5e9hFsVjbW0tHD9+XGH9wMBAwdDQUGzj4eGhtG9BEIRvvvlGEkuXLl0Unle5ubnCnDlzFN5zU3UvTVMymUywtbUV+zQzM1N5vrwuTcfRxb9baqp///5im6ZNm2rUJiEhQfKdYdmyZRofjyoOk6KIiIiIiIiIiIiIiIioXChLihIEQZg3b57ktZCQEIV9lCYpqniyyqZNm9TGOHfuXLG+qampwj/g3717V9LvhQsXFPY1aNAgsc748ePF7SlTpiisf+jQIbGOjo6O0gm97dq1k/xRXdXkAU29fPlS47rh4eGSP/SuXbtWYb2TJ09KJi0kJSW9dpwVkRSlrfOmLMoyOfyDDz6QtGnVqpXSug8ePJBMnPXy8lKY/CUvLCxM8vvfvHmzwnqnTp2SxDFs2DCV/WZkZAju7u6SNqomLWiaFJWXlyeZtGJlZaVyopAgCMKnn34q6VvV5Gv58wqA0Lp1a5UT4XNycgQXFxexfufOnVXGQkT0NtH2de/w4cOSuoMHD1aaDCMIgvD8+XOhQYMGkvFMXFxciXpbtmwR69jb26u9lmpC08mwbdu2Fev17t1bbb85OTmCjY2N2GbGjBkK6xW/zgIQPvzwQ5V9R0ZGSiZafvnll2rj0cTo0aMlcZw8efK1+yye8BYVFaW07ooVKyR1i48jr127JnlgQdu2bdWeA5pO5ty2bZvk2AsWLFD73n755RfJd4p79+4prKeNc0cmk0nGiar+PRbXokULyXudPn26xm2JiOjt8OzZM8m1Qtk19MaNG2Idd3d3yWs9evQQX/v3338Vti9+TyA8PLxEHfnrqL6+vnDp0iWVsa9bt07S5+smxwuC5klRycnJkodRubq6CqmpqSrjHT58uKTvPXv2KK1bfMzYv39/lWPspKQkwcLCQqw/ZswYpXUXLVok6Vvdg2Vu3bolGZep+wyL349WlAAn79q1a5LEpUaNGimtK38Ps+g8UXYPucj8+fMlbZSN49LT0wUzMzOxXr169YQXL16o7HvcuHElflflkRQVFRWl8eddHrSdFFX8O+PFixfVtlm5cqVYX09PT+F3Rqp8ytejIyIiIiIiIiIiIiIiIionCxYsgJWVlVj+/PPPX6u/3NxcrFu3Tiz37NkTU6dOVdtu2bJlsLW1BQBkZWVhx44dJeo0bNgQTk5OYvnUqVMl6shkMpw+fRoAYGBggEWLFomvBQUFKTy2/P7mzZuLccg7c+YMLl26JJY/+OAD9OnTR93bUsvY2Fjjui1atMCoUaPEcmBgoMJ6z549E7dtbGxgZ2dX9gAriDbPG20qKCjA+fPnMWjQIEn8APDpp58qbffTTz+hsLAQAGBoaIht27bBwMBA5bFat24t+UzWr1+vsN7mzZvFbUNDQ/z0008q+zUzM8OqVatU1imL/fv34+nTp2J50aJFcHFxUdlm6dKlqF27tlhev349ZDKZRsf79ddfYWhoqPR1IyMjTJgwQSyHhYWhoKBAo76JiOiVsl73fvvtN3HbxMQEv/zyC3R0dJTWt7S0xI8//ig57qZNm0rUkx/zuLq6qr2Wlqdp06aJ28ePH0dsbKzK+n///TdSU1PF8pQpUzQ6jrW1NVasWKGyjru7Ozw9PcVyaGioRn2rk5CQICnXr1//tfts0KCBymPI++yzz9CjRw+x/M033yAkJAQAkJ2djVGjRiE3NxfAq/HM7t27y+0cWL16tbjdqFEjLFu2TG2bDz74AE2aNAEACIKAjRs3KqynjXNHR0cHbdq0Ecs3btxAYmKi2pgTEhJw8+ZNyb709HS17YiI6O3i4OCARo0aiWVl99eCg4PFbW9vb8lrXl5epWpva2uL5s2bS16/fPkyrly5IpZnzpwJDw8PlbG///77kjo7duxARkaGyjbl5ffff0dOTo5YXr16NaytrVW2+fnnn2FmZiaWi4+5ldHX18e6detUjrHt7OwwZMgQsaxszCiTyfD777+L5WbNmmHGjBkqj9+4cWN89NFHGsWak5Mj6b9ly5b4+OOPVbYpXicyMlLpeVTcpEmT0KFDB5V1pk+fLinL3wOW5+/vj8zMTLG8YsUKWFhYqOx71apVqFatmkaxlkbxcbSrq2u5H6Mi+fj4SO4JbtmyRW0b+To+Pj6SvxvQm4NJUURERERERERERERERKR11tbW+OKLL8Ty+fPnceDAgTL39++//0om4M2ZM0ejdiYmJhg+fLikH0XkJ1UoSoqKiIhAWloaAMDDwwP16tUTJ248ePAAjx8/LtFGvp/u3bsrPG5AQIC4rauri3nz5ql4N9ojPzH08uXLCuvI/6E9MTERDx480Hpcr0vb583r+vzzz1G/fn3JT+3atWFmZobOnTuX+DczceJESQJbcbt37xa3Bw8eDGdnZ43i8PX1FbevXr0qmSBb5NixY+J27969UbNmTbX9+vj4aFSvNA4dOiRuGxkZYdKkSWrbmJiYSOrFxMTg1q1bats1bNgQHTt2VFtPfhJMTk4OYmJi1LYhInobled1Lzc3FydOnBDLAwcO1GiyWp8+fSQT+w4fPlyijvyYJzIyEs+fP1fbb3kZNWoUzM3NAbyaOLp161aV9eWTllu1aiVJYFFl+PDhMDU1VVtP/hoXGRmpUd/qFB9nyD9IoawsLS1VHkOejo4OduzYAXt7ewBAYWEhxowZg7S0NHz00Ue4c+eOWPe3334rl6QtALh58yauX78ulj/++GPo6qqfyqejo4Px48eLZWXjUm2dO7179xa3CwoKJImFyqxevVpM1C9SURPFiYioaunWrZu4/fjxY0RHR5eoI5/UJJ8EVbwsX69IRkYGrl69Kpa9vb1LJPjI32cAXiU8qaOjo4OZM2eK5czMTIXH1wb5eGvWrImBAweqbePg4ID33ntPLIeEhODFixdq273zzjuShBJl5MeMDx48QH5+fok6N2/eRFxcnFieOHGiRmMhTZP+z58/LxkDzpgxQ6P+Z86cKTknFH0/UGTixIlq6zg7O6NGjRpiWdl4Wv4BVba2thr9TqtXr44BAwZoEGnppKSkSMrlMVavTLq6upJzyN/fH1lZWUrrh4SE4O7du2JZk4drUeVgUhQRERERERERERERERFViFmzZqFWrVpief78+SUmx2mq6OntwKtVkJQlGSnSrl07cVvZ00rl+zt//rz4dPgiihKc5NsUT6RKTU2VTHqUn+QhT/59eXh4oE6dOkrfhzY5OjqK2ykpKSXeP/BqsqS8gQMHKk2gelNo+7x5XUXJZfI/cXFxJT5/CwsLrFy5UuXTTCMjI5GcnCyW+/btq3EcrVq1EldAEAShxJNrHzx4IJkUUfzJzMro6upKVpgoD/K/i06dOpWYBK1Mv379lPajjCYJUQBKTMKvyMnzRERVSXle965evYq8vDyx7OPjo1EMOjo6klU5r1+/jpcvX0rqtG7dWtzOyMjAwIEDJRPjtMnMzAyjR48Wy1u3boUgCArrRkdHS55kr+mEUQBqn2pfRP4aV17Xt+LJMZokZ6kjv/IBoH5Voho1amDbtm3iBNjY2Fh07dpVsrrAmDFjMG7cuNeOrYj8uBQo3VhNflx669YthRM5tXXuvP/++zAxMRHLq1atUjlZ+MCBA1izZk2J/cX/nREREQEl75cVX6VHEAScOXNGLBdPimrXrp24Wvrly5dLXCNDQkIk9yIV3Z+Tvz/g6uoKd3d3jWIvy32G11VYWIiwsDCx3KtXL40SfwBpvIIgaHRPryxjRkEQFCZcFT+epveW3NzcJIlFyhT//DX9fuDq6orGjRsr7UcRAwMDjR9GoMl4Wv6z6dy5s8arlGr6GZZG8bF68XF2VTR58mTo6ekBePX+5B9SVpz8d1BHR8dSjdmpYjEpioiIiIiIiIiIiIiIiCqEsbExlixZIpYjIyPh5+dXpr4iIiLE7QYNGsDQ0FDjtg4ODuJ2QkKCwqeVyk+KePnyJS5cuCB5XX5ShqKkqOKTNoKDgyGTyQAAenp6ShND5J8Q2rZtW7XvpbTS0tKwefNmjB49Gs2bN4e9vT2MjY2ho6Mj+Xn33Xcl7RT9kd7Z2VkyoeDWrVto164dmjdvjvnz5+Po0aMaPWW2Imn7vKkI9vb2OH78OD799NMSTzOWJ/9eAaBJkyYaH8PAwADW1tZiWf7JvQBKPKlZfrKIOqWJQx1BEHD//n2x3KJFC43bNm3aVDJR6N69e2rbaDLpBig5QUTVE2eJiEg1Ta97xf8fL801oXnz5uJ2QUFBietcly5dJNevM2fOoFGjRujYsSOWLl2KoKAgZGdna3y80po+fbq4HRMTI1kRS96WLVvEpBcTExOMGTNG42OU5RpXXte3otWMyrPfzMxMSdnCwkJtGx8fH8yaNUssy68iWbduXaxfv/6145InP1YzNzfXaNWFIvLj0sLCQjx9+lRhPW2cO9WrV8e3334rlgsKCjBo0CB88MEHuHLlCrKyspCVlYUrV65g5syZeO+991BYWIhq1apJxl7Ff+9ERERAyZWbiq+2dPPmTSQlJQF4tZqz/EN9gFcrSBcl7uTn5+PcuXOS14v3pygpSn5cWZoxpZ2dnSQeTe4zvK64uDjJOLSsY2Cg4u+LaPvekvz7sbKyKtWDp+Q/G00+FxsbG40Tl9SNpwsKCiT34SrrnluR4mO24uPsqsjJyUnyYAz5FVPlpaen488//xTLEydOFJOp6M3DpCgiIiIiIiIiIiIiIiKqMBMmTJD8MXfJkiVlekq4/Co1N27cKJHUo+pH/o+egOKEH1dXV7i4uIhl+SSnwsJC8cnuxsbG4uox3t7e4kS/4itFyZdbt26tcDWb9PR0SaJN8Ykdr6OwsBDffvstatWqhalTp2L37t24ceMGkpOTFa4CVVxOTo7C/f/73/9Qv359yb4bN25gxYoV8PHxgY2NDdq1a4elS5fi4cOH5fJeXoe2z5vXVfQE/6KfvLw8PHjwAH/++ad4niUlJcHT0xN///23xu8VANq0aVOq95uYmCi2TUtLk/RV/L3LJ1CpU5q66rx48UJMNgReTdLVlLGxsWSCdPH3qKxNWShblYGI6G1Xnte94v+Pl+aaIJ9goqgvXV1d7N69W9KnIAi4ePEilixZgu7du8PKygqenp5YvXo1nj17pvGxNdGqVStJsryiFbMKCwslDxsYNmyYxqsnAmW/xpUHGxsbSbk8xljFE/OLH0OZ77//XrIyGPAqWXz37t3lnsQjP1bLyMgo1Tit+ORYZeMYbZ07c+bMwcyZMyV9/Pbbb/Dw8ICZmRnMzMzg4eGB9evXo7CwELq6uti8ebNk3FaeY0IiIvrvsLOzQ9OmTcWyoocOFVG2Ko786lGq2js4OChMOJG/rpZmTFnUp6J+tEWbY2BFyvO+iPyYz8TEBEZGRhr3p8k4orx+j5qMTbX1uQCVd8+tiK2traT8X1kNXf7hAefPn8edO3dK1Pnjjz/EpEMdHR1Mnjy5wuKj0mNSFBEREREREREREREREVUYPT09LF++XCzHxcXh559/LnU/5fkHWGVP9pd/Wqx8UtOVK1eQnp4OAOjYsaP4h28bGxvxSaJxcXGIiopS2F7RU2iBV5Mh5RV/qmpZCYKA0aNHY+HChQrfq42NDWrVqoV69eqJPzVr1izRhyJOTk64cuUK5s6dq3CiqEwmw+XLl7FkyRI0bNgQU6ZMET+7ylAR5015MjAwQN26dTF06FCcP38eH374IQAgLy8PI0aMKLGCmTxtvtfiiXSlmbhSmrrqFH86bbVq1UrV3tTUVGlfRERU8V7nuvc61wT564GivgCgWbNmCA8Px+TJkxVOeszPz0dISAjmzZsHV1dXfP7558jLy9M4BnWmTZsmbu/fv79E8nNgYCDi4+PF8tSpU8vt2NpWfEKu/CqQZSU/Dld0DGV0dXWhr68v2VerVi00a9bstWMqrqLGpdo6d9atW4dNmzapnWTs4uKCEydOoE2bNpL9dnZ2Gh2HiIjePvL3zeLi4vDgwQOxLJ/UJJ/8JE9+v3z99PR0XL16VSwrS6qSHwu+6fcZtD0G1ib5e0ulvVekSf3y+j3m5+dr9ECp8vKm3HMrUnwcHRMTU+7HqAw+Pj6SlVoVrRYlv6979+6oW7duhcRGZaOvvgoRERERERERERERERFR+RkwYAC6dOmCs2fPAgBWrFiBadOmlepplvJ/zDYzM9N4oqMixSc+FunWrRu2bt0KAAgNDUVWVhZMTU0lT5nt3r27pE337t0RHh4O4NXTaBs0aICEhARERkZK+lWkeBJUeU1G2Lx5MwICAsSys7MzPv74Y/To0QNubm4K/2AeFBRU4r0pY2lpiVWrVmHp0qU4fvw4Tp06hXPnziEiIkLyNPjCwkJs2bIFly5dwtmzZyWr9FSUijhvtOmnn35CWFgYLly4gIKCAowePRo3btxQmEBXfMJHvXr1ynzc4v82i//uiif0qVKeSXHF33dpE9WysrKU9kVERJWvNNc9RdcETVdKkr8eKOqriKOjIzZv3owffvgBR48eRVBQEM6ePSsZ5wGvVthcuXIlrl69isDAwHIZM4waNQpz585FRkYGcnNzsXPnTsyaNUt8XX4FIHd3d3Tp0uW1j1lR2rVrhz/++EMsX7lyReNxqCIymUwcjwOvnm6v6Tho4cKFuHTpkmRfdHQ05syZgw0bNpQ5JkXkx2rGxsZwcnIqc1+qVifQ5rkzdepUjBkzBvv27cOJEydw//59pKamwsLCAq6urhg0aBAGDBgAY2NjHDx4UNK2VatWpXiHRET0NvH29pY8QCkoKAj16tWDIAg4ffq0pJ4iHTp0gKGhIfLy8nDlyhVkZmbCzMwMISEhKCwsFOspG2+YmZmJq06+6fcZXue+iKZjYG2Rv7dU2nugmtxbkn8/r/N7NDAw0EqykTJvyj23IvXq1YOtra2YWB8WFgaZTAZd3aq9Lo+uri6mTJmCxYsXAwC2b9+O5cuXw8DAAABw/fp1hIWFifWnTJlSKXGS5pgURURERERERERERERERBXu+++/R+fOnQG8ekr6d999hx9++EHj9vJPFu/UqROOHTtW7jHKJy/l5+fj7Nmz6NWrl2TVJ0VJUWvWrAHwanWoadOmSeobGBiga9euCo9naWkJfX19FBQUAACePn1aLu+jKB4AaNy4Mc6fP692knBZnlxvamqKwYMHY/DgwWIfJ06cgL+/P/bv3y9OPLlx4waWLVtWqt93eamI80ab9PT0sH79erRq1QqCICAmJgYrV67E119/XaJu8afvh4SEwNHRsVzisLe3l5RjY2M1bhsXF1cuMQCv/s3o6uqKyXeJiYkat83JyZFMFilNUiYREVWM0lz3iv8/npiYqPF1r/j1Q901wdraGqNGjcKoUaPE9kePHsWuXbtw/Phxsd6JEyewceNGfPDBBxrFoYqZmRlGjx6NjRs3AniVyFKU2JKQkIDDhw+LdavahL3iY+OjR4/is88+K3N/Z8+elUxk7dKlC3R0dNS2O3nypGR8ampqKvazceNG9OrVSxznlgf5sVqdOnVw9+7dcutbnrbPnWrVqmHMmDEYM2aMynrFV3pr165dqY9FRERvBy8vL8l3/eDgYEyZMgU3btwQEzPq169fYpXzIiYmJmjXrh3Onj2LgoICnD17Fr1795asGgUof2iRtbW1mBRVmvsMxetXxH0GRWNgTZV2DFze5O8tFRQU4OnTpxqP3zW5tyT/fl7n92hlZVWqtq/L3NwcRkZG4opRlXXPrYiOjg66du2K/fv3A3iVpHXp0iV06NCh3I9V0SZPnoyvv/4ahYWFSEpKwsGDB/Hee+8BAP73v/+J9Wxtbcv1ewBpR9VO0yMiIiIiIiIiIiIiIqIqqVOnThg4cKBY/vXXX0v1R153d3dx+/bt2+UaW5FatWqhQYMGYvnUqVPIz8/HuXPnALyaYFh8Mp+np6e4GkDRilLySVEeHh4wNTVVeswmTZqI21euXHnt9/DkyRPcuXNHLH/11VcarZrw8OHD1z62lZUVhg4dir179+LcuXMwMTERX9u5c+dr918WFXHeaFuLFi0wYsQIsbx69WrEx8eXqCf/XgHg1q1b5RZD06ZNJU+EvXr1qsZtS1NXHR0dHdSvX18sR0REaNz21q1bkpXMGjZsWG5xERFR+dH0ulf8//HSXBOuX78ubhsYGMDV1bVUMVavXh3jx4/HsWPHsG/fPsk1sjzHPNOnTxe3b9y4Ia5o5OfnJybVGxoaYvz48eV2zIrQokUL1KpVSywHBwe/1lh08+bNknK/fv3UtklOTsa4cePEsUGNGjUQHh4uORemTJlSqu8r6siP1aKjo0u9gkFpvAnnzj///CNuu7q6vtYqpkRE9N9mY2OD5s2bi+Wi+2vySU3KVokq4uXlpbK9k5OT5J6fPPlxZWnGlCkpKXjy5InCfrSlVq1akvuMZR0DAxV/X6RFixaSsqb3i3JycjS6pyf/fp4/f47Hjx9rHJv8Z1MZ94vkP5vKuucmr/h4etOmTVo5TkVzcnJC3759xXLRCqo5OTnYtWuXuH/cuHEVuloYlQ2TooiIiIiIiIiIiIiIiKhSLF++HHp6egBe/bFx0aJFGreVf5prXFwcrl27Vu7xFT/OqVOncPHiRXHCYpcuXcQEqCLm5uZo06YNgFdPFb1165Y4+aJ4f4p4enqK25cvXy7VH+wVKT5puPiEA2VOnjz5Wsctrn379pg2bZpYfvbsGdLS0krUMzAwELflE1bKS0WdN9r25ZdfiiseZGdn47vvvitRp3Xr1pIEuEOHDpXb8c3MzNCsWTOxvG/fPo3aJSQk4OzZs+UWBwDJk2kvXLggPs1ZHflVEYr3Q0REbxZNr3uGhoZiOTAwUOP+5ZM1mjdvLknkLq1Bgwahf//+Yrk8k7BbtWqFtm3biuWi5J/ff/9d3Ddw4MASKzq+6fT09PDxxx+LZUEQsGTJkjL1dfv2bezZs0cs29vbY+zYsWrbTZw4UVylVUdHB9u3b0f9+vXxxx9/iOP91NRUjB07ttzGqMVXpdXmCqaVfe5cvnxZMrl46tSpWjkOERH9d8hfJ588eYKoqCjJ/TX5pCdF5F8PDg5Genq65B6Qqvtz8vcHoqOjNV7NsTLuM+jp6Yn3IQHg+PHjGo9V5OPV1dWt8FUc27VrJ3mYgKb3lo4cOSKuoqRK8c9f0+8HMTExkgcLVcb9oo4dO4rbYWFhGt8f/uuvv7QSz9ixY1GjRg2xvHv3bq2tcqop+XvIQNnvI8vfrz527BhiY2Px999/S+5bV7WVeN9WTIoiIiIiIiIiIiIiIiKiStGoUSNMmDBBLG/fvl3j1Wx69eoFKysrsbxixYpyju4V+UkS165dk/yBvnv37grbyO/ftm0bHjx4oLZNkZEjR4rbMpkMq1atKnXM8gRBkJRzcnLUtrlz545WJmW6ublJyvn5+SXqmJmZiduaJreURkWdN9rWtGlTyVNaN2/eXGKChJ6eHoYOHSqWt27disTExHKLYcyYMeL2gwcPEBAQoLbNihUrUFhYWG4xAJBMPM/JyYGfn5/aNjk5OZJJwK6urpJV2oiI6M2iyXXPyMgI7777rlg+cOCAmOSiSmBgoGRVIk1WFVJHfsyjaLzzOuRX/PH390dgYCDu3bsn7quqE/amTZsGGxsbsbxjxw4cOXKkVH3k5+dj6tSpyMvLE/fNmjULxsbGKtutXbtWMil43rx54rnUoUMHSYLWmTNn8O2335YqLmVat24tWaHi+++/L5d+lanMc+fTTz8Vt01MTDBp0iStHYuIiP4biictnTp1CmfOnBHL6laK6tSpk5jYHBYWhn/++UdyP0JVUpT8fQYA2LBhg9p4BUHA+vXrxbK5ubnaxK3yIh9vfHy8Rg/FSUxMlCTQdO3aFRYWFlqJTxlbW1v07t1bLO/atQuPHj1S2UYmk2H58uUa9d+xY0fY2tqK5Y0bN5a4T6rI+vXrJfXK4/tBacnfcxMEQaP7lwcOHMDNmze1Eo+RkRHmzp0rlnNycjB+/HjJuLs0MjMzsW3btteKSf4eMlD2+8g+Pj6oU6cOgFfnl5+fn2Tl2Y4dO/KeYRXBpCgiIiIiIiIiIiIiIiKqNEuXLhWfxi+TyfDNN99o1M7c3BwfffSRWA4ICJAkOWhKXZKQ/CSJwsJCyUQITZKifv31V3HbyMhI8qRPRTp16iSps27dOsnqBaVV9EfdIsWfWltcbm4uJkyYoNHTNWNjY0uV4BIRESFum5qaKnwSvYuLi7idnp6O2NhYjfvXREWdNxVhwYIF4nZeXp7Cfzuff/65uBpbRkYGRo8eXerJ2cre64QJE2Bubi6WP/roI0RFRSnt58iRI5J/D+Vl0KBBqFmzplj++uuv1T5Bd+nSpZI6M2bMEFcgISKiN5Mm172ZM2eK2y9fvsTHH3+scuJjeno65syZI5b19fUlTwovom5yZnHyYx75sU15GDVqlHj9zcjIwMSJEyXH6tGjR7ker6JYWlpKJh8CwPDhw3H69GmN2hcUFGDkyJE4f/68uM/DwwOfffaZynYRERH4/PPPxXLbtm1LJD3Nnz9fMvF66dKlkuOUla6uLr744guxHBoaisWLF5e6H03HpZV17ixZskTye/z666/h4OCglWMREdF/h6enp3g/A3h1fy01NRUAULduXdSqN8uR3gAAUlRJREFUVUtle1NTU3GVxMLCwhLXd1UPLWrbti08PDzE8rp169SuNL5p0yaEhoaK5bFjx0rumWjTxIkTJUngc+fOxfPnz1W2mT17NjIyMsSy/Di6IsmvFpqTk4PRo0cjOztbaf0vv/wSYWFhGvVtbGwsScS+du0a1q1bp7LN9evXsXbtWrHcuHFjtQl42uDh4SFZoWrjxo34+++/ldaPiYnB+++/r9WY5syZI0n0u3TpEvr06SM5jzRx/fp1tG/fXuOVwZQp/j2rrAlhurq6mDx5slj+9ddfERwcLJa5wmnVwaQoIiIiIiIiIiIiIiIiqjROTk6SP4A/e/ZM47aff/45mjZtKpanTJmCL774Aunp6SrbpaamYuvWrWjbti3279+vsq6DgwMaN24sll++fAkAsLKyQqtWrRS26dy5MwwNDSX1gVdPmi9KAFNl/fr1MDIyAvAqUWzw4MH49ddfVSYghYWFYdiwYSWSQWrUqIHmzZuL5eXLl+Pff/9V2Mfjx4/Rq1cvhIaGQldX/Z8Rt2zZAjc3N6xdu1bt7y0gIABbtmwRywMGDFCYhNKuXTvJsT/77LNyXzGqIs6bitChQwdJ0p6fnx+io6MldRo0aICvvvpKLJ88eRJdu3bFjRs3VPZdWFiI4OBgjB8/HsOHD1dYx97eHt99951YTkxMRIcOHbBx40bJZxkfH4+FCxdi8ODBKCgokPx7Kg/6+vqSlRVSU1PRs2dP3L59u0RdmUyG7777TvKE3Xr16uGDDz4o15iIiKj8aXLd8/HxkSR27N27FzNmzJCMx4o8ffoU/fr1w927d8V98+bNkyTaFlm8eDFatmyJ33//XeUEU0EQ8OOPP0pW3Bw0aJAmb09jpqamGD16tFhOSEgQtydNmqTRGO5NNXjwYMn3guzsbPTs2RNfffWVysmxly9fRvv27SUTRW1sbLB7924YGBgobZednY2RI0ciNzcXwKunzStqo6uri507d4orDRQWFmLMmDHlMkb19fWVnLNff/01Jk2apHZ1z8zMTPz555/o3r27ZOKuKuV57pw/fx5bt25FVlaW0jqpqamYNm0ali5dKu7r2LGjJBGRiIhIGUtLS8l9N/mEB02TVOQTOOTbu7i4qE1cX7VqlXhtzM/PR58+fZQmRfv5+eHDDz8UyzY2NpJ7Mdpma2uLL7/8Uiw/ePAAffr0QVxcXIm6ubm5+OCDD7B7925xX+fOnSUrjVekXr164b333hPL58+fR7t27fDPP/+goKBA3B8REYFhw4ZhxYoV0NXVhbu7u0b9f/bZZ5Jk7NmzZ2PTpk0K64aGhsLHx0ccGwLA6tWrS/uWys369evF1c5kMhlGjBiBzz//XPIAqczMTGzZsgXt2rXD06dPy/2emzw9PT34+/vDyclJ3Hfy5Ek0a9YMO3bsUPvgrJs3b2Ls2LFo1aqVwnt2pdW4cWNJ4uHixYsl49vSmDx5spiEmZiYKD5Yw9zcXOl9UXrz6Fd2AERERERERERERERERPR2++KLL/C///1PfOKrpkxNTbFv3z54enri6dOnEAQB33//PX777Tf06tULbdu2hZ2dHQDg+fPnePDgAcLDw3H58mXJH9bV6datW4k/1np5eSmdOGhiYoIOHTrgzJkzkv2qnkIrr0WLFli/fj2mTJkCmUyGvLw8fPTRR/jhhx/Qv39/NGzYEBYWFnj+/DkiIyNx+vRpcULvDz/8UKK/+fPnY9SoUQBeJWn16tULPj4+6N69O2xtbZGWloYLFy7g0KFDyMnJgb6+Pr766iuNnlT/4MEDzJ49G5988gnatm2Ldu3aoW7durC2tkZ+fj5iYmJw/PhxXLlyRWxjamqqdEUwR0dH9O7dW1wdy9/fH3v37oWLiwtMTU3Fem3bti2xmoCmKuq8qQjz589HUFAQgFeTdJYtW1Zi5atFixYhMjISe/bsAfBqkkfz5s3RqVMneHp6ok6dOqhWrRrS09Px7NkzXL9+HRcuXEBKSgqAVxNUlPnggw9w+fJlbN++HcCrya8zZszABx98gOrVqyM/Px/Jycli/W7dumHs2LHiE1jLa+L22LFjcfToUezatQsAcPfuXbRq1QoDBgxA586dYW5ujpiYGPz111+IjIwU25mYmGDHjh2Sc4uIiN5c6q57Ojo6+P3339GuXTsxYXvTpk04cuQIRowYATc3N+Tn5+Pq1avYu3evJIm3Xbt2kuSN4iIiIjB58mS8//77aN++PTw8PFCnTh1YWVkhJycH9+/fx5EjRyTXmZo1a6pdqagspk+fjo0bN0r26enpSVb+qap++uknGBkZiWPaolXBfvzxR/Tt2xfNmzdHjRo1kJWVhbi4OBw7dgzXr1+X9FGnTh0cPXoU9erVU3msjz/+GHfu3BHL69atQ/369RXWdXJywpYtW8Qkt5iYGEyfPh3+/v6v8W7/b3Jp165dxXNn69at+OOPP/Duu++iffv2cHBwgL6+Pl68eIGYmBiEh4cjNDRUXCGqZ8+eGh+vvM6dx48fY9KkSZg5cya8vLzQpk0b1K5dG4aGhkhKSsLly5dx7NgxZGZmim1atWqFI0eOSFb9ICIiUqVbt26S+0lF5JOdVPHy8pI8REW+X3U8PT0xf/58cYWpZ8+eoWvXrujVqxfeeecdWFtbIz4+HgcPHpTEqKuri02bNsHR0VGjGMvL/Pnz8e+//4r3Ii9cuIBGjRph6NChaN26NYyMjBAVFYWAgADJA5VsbW3h5+dXqYn1mzZtQlRUlDimu3XrFvr27QsjIyNUr14dz58/l6xGtHDhQjx69Egcx6kaW9jZ2WHr1q0YMGAACgoKUFhYiOnTp2PDhg0YNGgQnJyc8Pz5cwQHByMwMFCS2DNr1iz07t1bS+9avZYtW2L9+vWYNm0aBEFAQUEBVq5ciZUrV8LW1hZGRkZISEgQY3ZwcMCWLVvQsWNHsY/yHnfVqFEDFy9eRP/+/REeHg7g1aq648ePx6xZs9CjRw80bdoU9vb2MDAwQGJiIh4/fox///0XDx8+LNdYDAwMMG7cOPz2228AgKCgINSsWRPOzs4wNzcXH8ZVs2ZN8T6zMk5OTujbty8OHjwo2T969GjeM6xKBCIiIiIiIiIiIiIiIqJysHXrVgGA+HPjxg2N2/7www+StkU/hw4dUts2Pj5eaN++vcL26n4CAgLU9v/XX3+VaLd27VqVbZYsWVKizZkzZzT+PIqOa2pqWqr3Ex0drbCvDz/8UKP2RkZGgp+fnxAUFKS238WLF5f687axsRFCQkJUvu9Hjx4JdevWVdmPl5dXiXbOzs7i64sXL1b7+Wr7vNFE8X8zW7duLXUfHh4eYnt9fX0hKiqqRB2ZTCYsXLhQ0NXVLfV77dOnj8rjFxQUCPPmzRP09PRU9jNixAghIyND2LBhg7jPyspKab/R0dGS9kFBQWrjmDhxosbvy8rKSjh9+rTaz7e051VZYicieltU1HUvKipKcHV11fia4O3tLbx48ULpMX19fUt9/axTp45w+/ZtjfpUNK5Rp23btpLj9e3bt1Tty3qtKv471BY/Pz/BwcGh1J/7oEGDhPj4eLX9BwQESNqNHj1ao7jef/99Sbvff/9dYT0vLy+xjq+vr9p+X7x4IfTr169M49KVK1dqFHuR1z13BEEQdu/eXaoYBw8eLKSmppb6OERE9Hb7559/FF5XHj16pFH7Fy9eKLxXsX37do1jWLhwocbXOyMjI43uF2k6DtTk3py8rKwsoXfv3hrHW6tWLeHWrVtq4y3L+L20sScmJgp9+vRRGa+enp6wfPlyQSaTCSNHjpSM/9Q5dOiQUK1aNY0/m08++USQyWQq+5S/L+rs7KzR5yIIpR8n7ty5U7CyslIZb4sWLYSoqCjhzp07kv3h4eEax1UamZmZwkcffSQYGRmVafw6dOhQhd/jBKF0n8/z58+FNm3aqDyWpr+bw4cPl2h7+fLlUn4yVJmq7prJRERERERERERERERE9J/x0UcfoU6dOmVqW7NmTZw/fx7+/v7w8PAQnwSpTN26dfH+++8jJCQEw4YNU9u/t7d3iT7VrfpU/HUTExO0b99e7bHkDRkyBPfv38fMmTNhZWWltJ6Ojg5atmyJH3/8ETVr1lRY55dffsH//vc/ODk5KXxdT08PPXr0wKVLl+Dr66tRfOPGjcOiRYvg4eEBfX19lXWtra3x4Ycf4s6dO+jSpYvKunXq1EFERAR++eUX9O7dG05OTjAxMdEoptLQ9nlTUebPny9uFxQU4Ouvvy5RR0dHB8uWLcPNmzcxZswYmJmZqezT3Nwc/fv3h5+fn7jClDJ6enr44YcfcPXqVXz88cdo1KgRzMzMYGZmBjc3N4wdOxYnT56Ev78/zMzMJCvCqTqvS0tPTw+///47jhw5gjZt2iitZ2ZmhunTp+Pu3bvw9PQst+MTEVHF0OS6V79+fdy8eROLFy+Gvb290r7q1auHzZs34+TJk7CwsFBab86cOfj000/RrFkztU/Rd3R0xMKFC3Hr1i00atRIg3dUNhMmTJCUp06dqrVjVQZfX1/cv38f33zzDZo3b66yrrm5OYYMGYKQkBDs27dP6Xi4yKNHjzBt2jSx7OrqivXr12sU1+rVq9GkSROx/NFHH+HevXsatVXFwsIChw4dwtGjR9GtWze1Y+uaNWvC19cXgYGB+OSTT0p1rPI4dxo3boy+ffvC3NxcaR09PT1069YNR44cwd9//w1ra+tSH4eIiN5uXbt2LXFNdHFx0fj+oYWFBVq1alVivyYrRRVZtmwZzp8/D29vb6XjQCMjI4wcORKRkZGVer+oWrVq+Oeff7Bjxw64ubkprWdjY4MvvvgCt2/fRuPGjSswQuXs7e1x5MgRHDlyBCNHjoSLiwuMjY1hY2ODFi1aYO7cubh58ya++OIL6OjolPreUr9+/XDnzh2MHz9e6T1GHR0ddO7cGadPn8bq1avV3iesKGPGjEFkZCSWLVsGDw8PcZUoFxcX+Pj4YOfOnQgNDUX9+vUlnwtQvvfd5JmamuLnn39GVFQUZs+ejQYNGqht4+TkhE8++QQ3btzAn3/+qXSF1tKwtLTE+fPnxdXAXFxcYGpqWqbfnY+PDxwcHMRyy5Yt0bZt29eOkSqOjiAIQmUHQURERERERERERERERFRekpOTce7cOTx79gypqanQ09ODpaUlXF1d0aRJE6WJQW+ygoIChIaG4t69e0hKSkJBQQEsLS1Rt25dtG7dWvJHW1Xy8/MRGhqK69evIy0tDVZWVnB0dESnTp1Qo0aNMsf38uVLRERE4MGDB0hISEB2djaMjY1ha2uLpk2bokWLFjA0NCxz/xXhv3jeKFN0Hty/fx/JycnIzc2Fubk5HB0d4e7ujkaNGqmdjFtWo0ePxu7duwEAPXr0wL///quV48TGxuL8+fN49uwZsrOzYWdnh7p166JLly4wMjLSyjGJiOjNI5PJcOnSJURGRiIxMRH6+vpwcHBAq1atJMktmkpPT0dERAQePnyIpKQkvHz5EqamprC3t0fz5s3RtGlT6OnpaeGdSM2YMQMbN24EANSoUQOxsbFau3a/CWJjY3Ht2jUkJCQgOTkZJiYmqF69OurUqYP27dvDwMCgskMsV+np6Th37hzi4uKQkpIC4NXEbmdnZzRu3Biurq5l7rs8z52CggJcu3YNjx49QkJCAl68eAE7Ozs4OjqiY8eOsLOzK3OcREREb5qkpCScOXMGT58+RXp6OmxsbFCnTh14eXnB1NS0ssMr4e7du7hy5QoSEhKQl5cHe3t7uLm5oWPHjhUyXtWmmjVr4unTpwCAb775Bl9++aXGbV++fIkzZ84gJiYGKSkpMDMzg6OjI7p27fpa90bfBJs2bcL06dMBAMbGxsjIyKiw7wiPHj3C9evXkZSUhOTkZMhkMlhbW8PR0RGtWrVC7dq1KySOsoqPj4ezszMKCwsBAL/++is++OCDSo6KSoNJUUREREREREREREREREREpHV5eXmoXbs2EhMTAQCff/45VqxYUclRERERVS3Z2dlwdHREeno6gFerZ3333XeVHBVVBTx3iIiIqKoLDw+XrAAWGBiI3r17V2JEb45BgwbhwIEDAID27dvj4sWLlRxR1fHtt99i4cKFAAATExM8efJEayttkXaoXtOZiIiIiIiIiIiIiIiIiIioHPzvf/8TE6IAcNIKERFRGezatUtMatHV1cXUqVMrOSKqKnjuEBERUVUnn9BtZmaGLl26VGI0b47r16/j8OHDYpn33DRXUFCA//3vf2J5xIgRTIiqgpgURUREREREREREREREREREZaLpU2eDgoLw2WefiWU3Nzd4e3trKSoiIqL/ptzcXHz//fdiuXfv3nB1da3EiKiq4LlDREREb6Ls7Gxcv35do7orV67En3/+KZZHjx4NMzMzbYVW6cLDw5Gbm6u23uPHjzF8+HAUFhYCAPT09DB58mRth/efsW3bNjx69Egsz5w5sxKjobJiUhQREREREREREREREREREZXJhAkT0LJlS/z444+IjIyETCYTX5PJZAgLC8PMmTPRq1cvZGdni6/9+OOPlREuERFRlZWWlobJkyfjwYMH4r6FCxdWYkRUVfDcISIiojdVeno6WrZsiT59+mDXrl2Ii4uTvP7y5UscP34cPj4++Pzzz8X91tbWWLx4cUWHW6E2bNgAV1dXzJ8/H6GhoSUSpB4+fIjvv/8erVu3xt27d8X98+bNQ+3atSs63Crp+PHjmDdvnlju2bMnPDw8KjEiKisdQRCEyg6CiIiIiIiIiIiIiIiIiIiqHnd3d8nEC2NjY9ja2gIAUlJSkJOTU6LNV199ha+//rrCYiQiIqqqpkyZgitXruDly5eIiYlBXl6e+NrIkSOxe/fuSoyO3mQ8d4iIiKgqePbsGRwdHSX7zM3NYW1tjZycHKSkpIgrIBUxNjbG3r170bdv34oMtcLNmDEDGzduFMv6+vqwtbWFkZER0tLSkJGRUaLNO++8g3/++QeGhoYVGWqVceXKFUyZMgWCIODp06dISkoSXzMwMEBYWBiaNWtWiRFSWelXdgBERERERERERERERERERFQ1GRgYSMo5OTmIj49XWNfOzg4rVqzA5MmTKyI0IiKiKu/+/fuIiIgosb9Zs2b47bffKiEiqip47hAREVFVoKenB11dXcnK4xkZGQoTfgCgcePG2Lx5Mzp27FhRIVaa4vfcCgoKkJCQoLCuoaEh3n//ffzwww8l2tH/yczMVDhG1tHRwbp165gQVYUxKYqIiIiIiIiIiIiIiIiIiMrk4sWLCAwMRHBwMMLDwxETE4PU1FTk5ubCwsICdnZ2aNWqFXr06IHRo0fDzMysskMmIiKqkoyNjdGgQQO89957mDdvHkxNTSs7JKoieO4QERHRm8re3h7x8fE4dOgQzp49i5s3byI2Nhbp6ekoLCyElZUVatSogU6dOsHHxwcDBgyArq5uZYddIX766Se89957+Pfff3Hp0iU8fPgQiYmJePnyJYyNjWFjYwN3d3d069YNY8eORe3atSs75CpFV1cXdnZ26NSpE+bOnYsuXbpUdkj0GnQEQRAqOwgiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIk29HamSRERERERERERERERERERERERERERERERERPSfwaQoIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIqpSmBRFRERERERERERERERERERERERERERERERERFUKk6KIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIqErRr+wAiIio6khKSsLly5cRExODFy9eQE9PD9bW1nBzc0Pr1q1hZmZW2SGWiouLCx49egQAWLx4MZYsWVK5AWmBjo6OuL1161ZMmDCh8oJRY8mSJVi6dCkAwNnZGTExMQrrxcTEwNXVVSwHBQXB29u7AiJ88/CzICIievN4e3vj9OnTAABfX1/4+flVyHFlMhnCw8MRHR2NlJQUpKSkwMDAAJaWlqhevTpatGgBFxeXColFE35+fpg4caJYFgRBad2qNKYlIiIiKq309HRcvnwZCQkJSE5ORkZGBszNzWFpaQkXFxe0bNkSlpaWlR2mSNPxbmnGe0RERERFqtI9Lt7fIiIiIqLKxPuKRET/h0lRRESkVmBgIH744QcEBwcrHWQaGRlh8ODBWLhwIZo0aVLuMUyYMAHbtm0Ty9HR0W/MDW8ideQTvpSpVq0aLC0tUbduXbRp0wbvvfcePD09KyhCIiKi0il+I7LIoUOH0K9fv1L1lZaWBkdHR+Tm5kr2V2RCUVV2+PBhbN68GadPn8bz589V1rWyskKvXr0wdOhQ9O3bFyYmJhUTJBEREdH/t3LlSnz++ediWVdXFw8fPoSzs3OFxhEeHo79+/eL5Yp+WFJ6ejp+++037Nu3D2FhYSgsLFRZv2HDhhg0aBCGDRuGtm3bVlCURERERBWH97iIiIiISBXeV3yF9xWJiBTTrewAiIjozVVYWIjJkyejT58+CAoKUpl1n5ubC39/f7Rq1Qq//vprBUZJ9N+QnZ2Np0+f4ty5c/j555/h5eWFNm3aICIiorJDIyIi0tjvv/9e6ja7du0qkRBF6oWEhKBt27bo378/Dhw4oHayCAA8f/4ce/bswbBhw+Dq6oo1a9bg5cuX2g+WiIiI6P/bunWrpCyTySolET48PBxLly4VfyqKTCbDihUr4OLigvnz5+PSpUtqJy4AwL1797By5Up4eHjAy8sLQUFBFRAtERERkfbxHhcRERERaYL3FXlfkYhIFa4URURESs2cObPExFZvb2+88847qFmzJvLz8/HgwQMcOHAA9+7dAwDk5+fjo48+goWFBcaPH18ZYRO98WrWrFniqXWZmZlISkqCTCYT9129ehUdOnTA8ePH0bVr14oOk4iIqNQOHz6MpKQk2Nvba9ymLIlUb7t169Zh9uzZKCgokOxv2LAhunXrhjp16sDW1hY6Ojp49uwZ4uPjcerUKdy/f1+sm5CQgLlz/1979x0fVZX/f/ydkAak0kJgISFUUSFKkSjSBOl1BQRXQkfRXcVFd1dZQFn92nBdFwQLVYEoglQBBUFQIPQA0pYOAUIPIRDS7u8Pflxnkkwyk2RmEnk9H488HnPunHPuZ5ILc+Yz95zzV9WpU8fh3b0AAAAK4pdfftGBAwdyHJ8xY4b++c9/ytPz972OX1JSkp588kmtXLnS6rivr6+aNWumZs2aqWLFigoJCVFycrISExN14MABrV69WsnJyWb99evXq3fv3rp48aKrXwIAAECRIscFAAAAe5BXJK8IAPlhUhQAIFdxcXH69NNPzXJwcLAWLFigNm3a5Kj7zjvv6P3339crr7xiHhs1apR69uypgIAAl8QLlCRz5sxRq1atchxPTk7W0qVLNWbMGB07dkySlJqaqp49e+rw4cMKDg52baAAANgpNDRUiYmJSk9P15dffqlRo0bZ1S4+Pl47d+6UJPn7+8swDKWkpDgzVKdbt26dU/ufMGGCxo4da5Y9PDzUp08fjRs3Tvfcc0+ebf/3v/9p6tSpmjp1qm7cuOHUOAEAALKbNm2a+bhGjRpm7uPEiRNas2aN2rVr567QnC4lJUUtWrTQ7t27zWPly5fXyy+/rOeee07+/v4226anp2vdunV65513tGbNGleECwAA4HTkuAAAAGAv8orkFQEgP7/v6bEAgAKbPXu2VXnatGm5ToiSbiepX375ZY0cOdI8dvnyZS1btsypMQK/NwEBAerfv7+2b9+u+vXrm8cvXbqkDz/80H2BAQCQD8sdQmfMmGF3O8sEdu/eveXn51ekcf3erFixQuPHjzfLpUuX1vz58xUbG5vvzSKSVLt2bU2cOFHHjx/XkCFDnBgpAACAteTkZH399ddm+ZVXXtFDDz1kli3Hhb9HQ4cOtbpxISoqSrt379bf/va3PG9ckCRvb2+1a9dOq1ev1s8//6x69eo5O1wAAACnIscFAAAAe5FXJK8IAPZgpygAQK62bdtmPq5UqZJ69uyZb5tnn31WH3/8sVmOj49Xv379nBKfuxiGoYMHD2rfvn06ffq0kpOTVbp0aZUvX14NGzZUgwYNimxL3rS0NK1bt07Hjx/XpUuXVK5cOUVFRalJkybFattfwzC0Y8cO7du3T+fPn5dhGAoNDdWDDz6oe++9193hlUghISGaPHmyWrdubR5bvHix1RdEhZGWlqY9e/bowIEDSkxM1M2bNxUYGKhKlSqpadOmqlGjRqHPcee62L9/vy5cuKAbN24oMDBQkZGReuCBB1SlShWH+7x+/bo2bNig06dP6+LFiwoICFDVqlXVqlUrhYSEFDpmAEDBPfHEE/rkk0907do17dmzR9u2bVPjxo3zbHPr1i3NnTvXLA8ePFhLliwpcAzp6enauHGjjhw5ovPnz6t06dIKDQ1Vs2bNFBERUeB+s9u2bZsOHjyos2fPyjAMNW/eXNHR0UXWvy3Xr1/XgAEDlJWVZR6bP3++Onfu7HBfFStW1Oeff6727ds7tBPl0aNH9euvv+rEiRO6du2afHx8VK5cOdWvX1+NGjWSt7e3w7E4myvGqmlpadqwYYNOnDihxMRElSlTRt27dy/S6w4AgJLuq6++MncE9fX1Vd++fWUYhuLi4iRJixYt0uXLl1WuXLkiOd/Zs2e1adMmnT17VklJSapcubIGDx5cJH076quvvlJsbKxZrlmzpn766ScFBgY63Ncjjzyi7du3a8KECXa3cUUeyBlckQcqTtcJAAB3C3fnuMhv5Y78FgAAKK7IK5JXdBR5ReAuZQAAkItatWoZkgxJRnR0tF1tUlNTzTaSjGHDhhVZPDExMVZ9Hzt2rNB9hoeHm/2NGzfOZr3U1FRj/vz5Rp8+fYwKFSpYxZH9p3z58sb48eONpKQkh19Xy5YtDcMwjPT0dGPcuHFG+fLlcz1HRESEsXDhQrv6t2w3Y8aMfOvHxcVZvcbg4GDjp59+yrXutWvXjNdee80IDQ21+fuoXbu2MXfuXLtiHTdunNkuPDzcZr1jx45ZnWPt2rVWz2dmZhrVqlUzn+/Tp49d57ds/4c//KHA7XNj+dpyizk3WVlZRsWKFc02Hh4eRkZGhlWd/H4Xli5cuGBMnjzZaNu2rVG6dOk8r+N69eoZM2bMMLKyshx+refPnzdGjRqV77+Ve++913jnnXeM1NTUfPvctWuX0bVrV8PHxyfXvry8vIxu3boZBw8edDheAEDBzJgxw+r/4j179hjDhg0zyyNHjsy3j9jYWLN+nTp1DMMwrMY/MTExdsVy6dIl4y9/+YsRGBho832nYcOGxqJFiwr02u6YMmWKERkZmaPv7HG2bNnS4ddgj4kTJ1qd95lnnimyvm3JyMgwvvvuO2PgwIFGlSpV8nxv9/f3N1588UXj3LlzdvVt6/ecG0fHtIZR9GPV3MbtKSkpxksvvWSEhITk6HvGjBnGwYMHrY59/PHHdp3rjsK2BwCgOGnWrJn5nvbEE08YhmEYly9fNnx9fc3jH330kUN95jZGiI+PN9q2bWt4enrmeH82DOt8oD0/eeWo7NWgQQOr/M7GjRsL3Wd+nJkHsne868h4z1JR54EKcp28+uqrZtnPz8+4fPmy3fEbhmH84x//KFR7AAB+z1yd4yK/9RvyWwAAoCQir0he0V7kFYG7W/HZZgIAUKxYrp5wZ7WF/Fy/ft2qXKlSpSKNyV02bdqk3r176+uvv9bFixfzrHvp0iWNHz9eDz30kI4cOeLwuZKSktSyZUu9/vrrunTpUq51jh8/rl69emny5MkO95+XlStXqk2bNuZrrFKlitavX68WLVrkqLt582bVrl1bb775phITE232+b///U/9+/dXnz59lJ6eXqTx2uLp6akhQ4aY5UWLFtn8XeZm5cqVOn36tFkeOnRokcZnLw8PD0VGRpplwzAceh3ZTZo0Sc8995xWr16tmzdv5ln3wIEDGjRokHr27Gn3v39J+vbbbxUZGal///vf+f5b+fXXX/W3v/1NZ8+ezbPe2LFj9eCDD2rp0qVKS0vLtU5GRoaWLFmi+++/32rLbACAa1mufDRv3jylpqbmWX/69Onm40GDBhXonFu2bFHdunX10Ucf6dq1azbrxcfHq0ePHurXr5/DY5KMjAz17NlTzz77rI4ePVqgOAsrKytLH3zwgVkuVaqUXn31Vaef99SpU+rUqZNmzpypM2fO5Fn3+vXr+vDDD/XAAw9Y7TrrDq4Yq546dUqNGjXSBx98oCtXruRap06dOmrVqpVZnjZtmkPn+Pzzz83HZcqUUf/+/R1qDwBAcbFv3z5t3rzZLA8YMEDS7Z2yu3btah539L0yuy+//FJNmzbV6tWrrXYecKfvv/9eu3fvNsvt2rVzyS6jrsgDOYMr8kD2XCfDhg2Tp+ftr1BTU1M1Z84cu/vPzMzUrFmzzHKvXr3Y4RwAgP/PHTku8lu2kd8CAADFHXlF8or2Iq8IwMvdAQAAiqeHH35YW7ZskXR78sK5c+dUuXLlPNusWbPGqpzbZJqSzt/fX4888ogaNWqksLAw+fv768qVK4qPj9fixYt19epVSbcH/V26dNH27dtVpkwZu/rOyspSv379tHHjRnl4eOjxxx9X69atVbFiRV25ckUrVqyw+h2/+OKLevTRR9WgQYNCv67Zs2dryJAhysjIkCTVrVtXq1atUnh4eI66a9euVZcuXXTjxg3zWN26ddWlSxfVrFlTXl5eOnjwoL7++mudOnVKkjR//nx5eHjoq6++KnSs9hg6dKgmTJigzMxMpaWl6YsvvtCLL75oV1vL5HyNGjXUtm1bJ0WZvzt/jztKlSpVJP2GhYXpkUceUVRUlCpUqCBvb28lJiZq06ZNWrFihXnexYsXa+TIkVYfuGyZNm2ahg8fbvWhr3r16urcubPq1q2rwMBAXb16Vb/++qt++uknHT58ON8+n332WU2dOtUse3p66vHHH1eLFi0UGhqq5ORkbdy4UYsWLVJaWprS0tLUv39/lS5d2ir5AQBwjWbNmql+/frat2+frly5okWLFunJJ5/Mte6pU6e0evVqSbff3+4ksB2xc+dOPfbYY1YT82vVqqUnnnhCkZGRun79uuLi4rRo0SLdunVLkhQbG6vU1FR9++23dp9n9OjRWrRokSTpvvvuU9euXRUREaG0tDTt379fvr6+DsfuqPj4eCUkJJjlDh06qFq1ak4/ryVfX189/PDDaty4sf7whz8oMDBQycnJ2rt3r5YuXWpOdD579qw6d+6s+Pj4fD8/OIMrxqppaWnq3bu3Dhw4IA8PD7Vp00Zt2rRR5cqVdeXKFcXFxcnHx0eSNGLECK1bt06StH37du3atUtRUVH5niM9PV2zZ882y71791ZQUJCdvwUAAIoXy5sSKlWqpI4dO5rlmJgYffPNN5Juj3m2b9+uRo0aOXyOLVu2aNq0aUpLS1NISIh69OihqKgolSlTRgkJCeb4LyIiQl5eXkpOTtb58+fN9jVr1sy13z/84Q8Ox2Jp+fLlVuVhw4YVqr+CcEYeyBlckQdy5Dpp166dVq1aJel2vvD555+36xzLly+3uuHaHX9zAACKK3fnuMhv/Yb8FgAAKAnIK/6GvKJt5BUBSHJgXzkAwF3lwIEDhre3t7kdZ58+ffLc6vTixYtGrVq1zPoNGza0e2tUe8TExFhtN3rs2LFC92m5re24ceNs1lu7dq3xwAMPGPPmzTNu3Lhhs15ycrIxdOhQqzjHjh2bZwyWr+vOtqrh4eHGtm3bcq0/bdo0q/579+6dZ//KZRvX7N59913Dw8PDrPfQQw8ZFy9ezLVuYmKiERoaarVN67Rp03L9W9+4ccMYMWKEVQyzZ8+2Geu4cePs2kL42LFjVn2uXbs213pdu3Y169x33302+8v++iyv+wkTJtjVLj+Wry2vmC1lZGQYQUFBVlv4ZmZmWtWx93dhGIbx+uuvG927dzfWrl2bo5/sfUZHR1v1++OPP+YZ6/bt2622pfbx8TE++ugjIz093WabuLg4o1evXsaJEydyfX7mzJlWMTRs2NDYt29frnUPHDhg1K5d26xbqVIl48KFC3nGDAAonOxb1u/Zs8cwDMN47733zGPt2rWz2f6NN94w63Xu3Nk8Xr58efN4TEyMzfapqalG/fr1rWIYM2ZMru89+/fvN+rVq2dVd8qUKXa/tjvvw5988old49uWLVva9Roc8e9//9sqnvfff79I+s3PsWPHjFq1ahmffvqpcfXqVZv1bt26Zfzzn/+0inHAgAF59p3995wXe8a0huHcsWr2zyOSjMqVKxu//PJLnrHfunXLqFChgtnm+eefz7P+HQsXLrQ614YNG+xqBwBAcZOWlmZUrFjRfE974YUXrJ5PT0+3ev9+9tln7e47+3uzJKNHjx7GpUuX8m3ryFikMBo2bGh1HlflK5yZB7J3vOvI79iZeaCCXicLFiywamMrX5tdt27dzDa1atUq0hw5AAAlnTtyXOS3fkN+CwAAlCTkFckrklckrwg4gklRAACbJk6caDVAe+yxx4z169db3WyanJxszJ0716hRo4ZZr0KFCjYHlwXlzklRN2/edKjfPn36mP2GhoYaaWlpNutmf12BgYHG0aNH8+y/X79+Zn1fX18jOTnZZt28EuxZWVnGiy++aFWnY8eORkpKis3+Bg0aZNb19PQ0VqxYkWeshmEYf/zjH8024eHhNj8wFfWkqGXLllnV27x5c76xvvvuu2b9UqVKGadPn863jT0KMinq22+/tWoTHR2do44jk6IcuY6TkpKMmjVrmv327Nkzz/pNmza1ui6WL19u97lsnd9yQli9evWMpKSkPNucPHnSCA4ONtuMGTOmUDEAAPJma1JUYmKi4eXlZb4nnDx5MkfbrKwsIzIy0mz7zTffmM/ZOylq0qRJVufPngTP7uTJk1Z9lytXzuZk99wmReU1iSo7Z0yKshz/STLWr19fJP3mJy0tzcjIyLC7/ssvv2w1Tj1//rzNus64acSZY9Xs43Zvb28jPj4+3/4NwzBGjx5ttgsJCbFrXNapUyersRAAACXVN998Y/UeumPHjhx1Ro0aZT4fFBSU56JElrKP2Zo3b57nAi2WXHHzws2bN81FkCQZkZGRTjmPrXPby9E8UFHfvODsPFBBr5P09HQjLCzMbPfMM8/k2+bMmTPm5yFJxttvv51vGwAA7ibuyHGR3/oN+S0AAFCSkFckr0heEYAjPAUAgA0vvfSSpk2bpuDgYEnSmjVr1KJFCwUEBCg8PFxVq1ZVUFCQ+vfvr2PHjkmS2rZtq7i4ON1zzz1ujLxo+fn5OVT/7bffNh8nJiZqx44ddrf9+9//rho1auRZZ8SIEebjW7duKT4+3qH4JJnbwH744YfmsQEDBmjJkiUqU6ZMrm3OnTunOXPmmOWhQ4eqQ4cO+Z7ro48+kre3tyTpxIkT+u677xyOtyA6duyoatWqmWXLLZVtsazTsWNHVa1a1Smx5efYsWN67rnnrI498cQTherTkes4MDBQr732mln+/vvvlZmZmWvd9evXa8uWLWb5ueeeU6dOnQoeqG5vHZyUlGSWp02bpsDAwDzbVKtWTa+++qpZ/uyzz2zGDABwnkqVKqlz586SpKysLM2cOTNHnXXr1uno0aOSpAoVKqhbt24On+fjjz82H4eFhenNN9/Ms361atX0+uuvm+XLly8rNjbWrnNFRUVZjb/c4fz581bl8PBwl5zX29tbpUqVsrv+2LFjzbHkrVu39OOPPzortBxcPVZ99tln1aBBA7vqDh8+3Hx85coVLVy4MM/6CQkJWrVqlVkeOnSoXecBAKA4ssy13HfffXrggQdy1ImJiTEfJyUl5fteactHH30kLy+vArV1hosXLyorK8ssu2oMJzkvD+QMrs4D2XudeHl5adCgQWZ53rx5unnzZp5tZs6cqYyMDLP9wIED7YoJAIC7hTtyXOS3bCO/BQAAijPyiuQV80NeEYAlJkUBAPI0ePBgHT9+XCNGjJCHh4ckKTU1VSdPntSZM2fMAXjZsmX1/vvva9WqVYqMjHRnyG5Xo0YNq9/B1q1b7W5rz4C2adOm8vT87S18//79DsWXnJyszp07W90I/PLLL2vmzJl5Dty/+eYbpaWlmeVRo0bZdb4qVaqobdu2ZvmHH35wKN6C8vT0tEqwx8bGKiUlxWb9DRs26ODBg2Z52LBhTo0vuxs3bmjPnj1688039eCDD+rMmTPmc9WrV9ezzz7r0ngs/2YpKSk2r7Ovv/7afOzp6anRo0cX+txz5841Hz/00EN6+OGH7Wo3YMAA83FiYqJ2795d6FgAAI4bPHiw+XjmzJkyDMPqecsE9p/+9CfzC3t7HT16VPv27TPLMTExKlu2bL7tBg4caFVv2bJldp0vJibGHAe7y+XLl63KQUFBbookb/7+/mrWrJlZdmQcXFiuHqtaJrLzU7t2bbVu3dosf/7553nWnz59upl89/HxsRrjAABQkpw+fdrqRkjLmxQsNWzYUA0bNjTL9ixsk1sfud0Y4U4lZQwn2Z8HcgZX5oEcvU6GDRtm5mGTkpI0f/58m3UNw9D06dPNcteuXRUaGmr3uQAAuBuUhPER+a3ckd8CAACuRF6x+I+b7yCvmDvyioDrMSkKAJCn7777Ts2bN9cnn3yS44ZWSykpKRo9erTuuecerVmzxoURFk9hYWHm44SEBLvahIeHW7WzpXTp0goJCTHLV69etTuuxMREtWrVSqtXr5YkeXh46IMPPtC7776b782+GzZsMB9HRkaqXr16dp+3adOm5uO4uDi72xXWkCFDzNXfkpOTrSbwZGf5wTgsLMzc5cIZWrduLQ8PD6ufsmXLqkGDBhozZozV37RcuXJavny5Spcu7bR4cpP9WrR1HVteF02aNFH16tULdd7r169r165dZtmRv0NoaKjV6iiuvNYAAL/p1KmTKleuLOn2BKaffvrJfC77Cl2WE6jslf3/944dO9rVrmzZsmrVqpXNfmyxN3nqTMnJyVZlf39/u9r16NEjx5gjt5+iVJBxcFFw5VjV39/f7lV077BcTddyt7TsDMPQjBkzzHL37t1VsWJFh84FAEBxMXPmTHNBpVKlSumpp56yWdfyxoZ169bpyJEjDp2rOIzZsivoGO7q1at2jeGKcrVQe/NARc3VeSBHr5OIiAi1a9fOLOd1Y81PP/2kw4cPm2V2QwAAIKeSkuMiv5U78lsAAMBVyCuSV8wPeUUA2TEpCgBg0+uvv67OnTtr7969kqS6devq008/1ZEjR5Samqrk5GTt2rVLb7zxhjlJ59ChQ2rXrp3V7PXfk7i4OL3yyitq27atqlevrsDAQHl6eub48PDLL7+YbeydtHTn5mF7WH7YyWv3I0tHjhzRI488oh07dkiSvL299eWXX9q9ylh8fLz5+N5777U7VklWqxecPn3aobaFUbVqVXXq1Mks21q17Nq1a1YrMgwaNMicTOUuHh4e6t69u+Lj43XfffcVWb9paWlaunSpRowYoejoaFWuXFlly5bNcQ1n37XD1nVsucJH48aNCx3f3r17rbYlLinXGgDgN15eXnr66afNsuUX4JZbwzdu3Fj333+/w/0fOnTIqmy5+ld+LL/oT0hI0I0bN/JtU6tWLfuDc5KAgACrsr3jv6K0d+9ejR07Vp06dVKNGjUUHBysUqVK5RhDzJkzx2zjyOT9wnLlWLVGjRpWO7fao1evXqpQoYKk2zeG2Ep8r1mzRseOHTPLrt69FACAopL9Rsh27drluRjQU089Ze5gnr2tPYrDmC274jCGK+o8UFFzdR6oINeJ5c2/69evz/F55A7LvGO1atXUoUMHh88FAMDvnbvHR+S3fkN+CwAAFFfkFd0/bpbIK2ZHXhEo/rzcHQAAoHiaN2+exo8fb5a7d++uefPmWe1W4+vra25DGxMTozZt2ujIkSMyDEMjRozQAw88UOy2ly2oPXv26JlnntHGjRsdbpuammpXPT8/P4f7lpTnDl6W/vWvf5mPvby8tHz5cqsVCfJz6dIl8/HSpUsLvOLalStXCtSuoEaMGKGlS5dKkjZu3KgDBw7kWFlt7ty55k3RHh4eGjJkiFNjqlKlitW/JQ8PD/n5+SkoKEg1atRQ48aN1b17d0VERBTpeb/99lu98MILOnXqlMNtc7uOr127pvT0dLNsz05n+bG8ziTpj3/8Y4H7cvW1BgD4zeDBg/Xee+9Jkr755htNmjRJAQEBVhPnC7JLlGT9/7uPj4+CgoLsbpt9m/krV66oTJkyebYJDAx0LEAnKFeunFX56tWrdsUVFhammjVr5jh+/vz5HCuM2XLixAk9//zzWrZsmX3BWrB3HFwUXDlWLcg14ePjo4EDB+r999+XdHuFuzfeeCPHRHzLpHdERITatm3r8LkAACgO1q5da7Vy/IABA/KsX6lSJXXo0MEcc8ycOVOvv/663YvWFIcxW3a5jeHsUapUqVzHcJIcWum2qPNAzuDqPFBBrpNu3bopLCxMZ8+elSRNnz5db7/9tlWdq1evasGCBWZ50KBBDt9kDADA3cBdOS7yWzmR3wIAAMUVeUXyivYgrwggOyZFAQByyMjI0CuvvGKWw8LCNGfOHKtJHNlVr15dX331lZo0aSLDMJSRkaGxY8eak1FKsk2bNql9+/a5JtX9/PwUHBwsPz8/qw9TCQkJ5iDf3klLzubn52fGlJGRodWrVzs0KaqoVnKwZ0eGotSxY0dVq1bN/KD2+eefm8n6OyyT823atFFkZKRTY5ozZ45atWrl1HNkN3nyZD3//PO5PhcQEKCAgAD5+flZfcFi+YE4t+u4oNs156UoVwxx9bUGAPhNvXr1FB0drU2bNunGjRv66quv1KxZM23dulXS7XFJv379CtT39evXzcf5TWjKrmzZsjb7suXOymLuVKlSJavyiRMnVL169XzbTZkyJdfjAwcO1KxZs/Jt/7///U+tWrXSmTNncjzn7e2tcuXKydfX12oFMMubUVw5DnblWLWg18Tw4cM1ceJEGYahM2fOaMWKFerSpYv5/OXLl7Vo0SKzPGTIkALf/AIAgLtZrhofGBioHj165NsmJibGvHkhISFBq1atstoBPC/FYcyWXYUKFeTp6amsrCxJt8dw9ggICNDhw4dzfc7esYEz8kDO4Oo8UEGuEy8vLw0aNEhvvfWWJGnWrFn617/+ZdXXl19+aeZdPT09C7wABAAAv3fuyHGR38od+S0AAFBckVckr2gP8ooAsit+/5sDANxuw4YNVtuCDho0KMcNpLlp1KiRoqOjzd2UVq1apRs3bjh8s2pxkpqaqqefftpq8ke/fv301FNPqUmTJjmS93e0bNlS69evd1WYdnnrrbc0d+5cbdu2TZL07rvvKiMjQxMnTrSrfZkyZXTt2jVJUkhISI5VKYorT09PDR06VOPGjZMkzZ49W//3f/9nfrmxe/dubd++3aw/dOhQt8TpTPv27dOoUaPMsr+/v0aOHKkuXbooKioqx7bL0u0PqfmtPJF9EpQ9N5bnJ/v/F9WrV8+x1bK9bP37BAC4xpAhQ7Rp0yZJt1c9+vXXX83nevXqpeDg4AL1a/n+4+gE2JSUFJt9FWdNmzbVvHnzzPKWLVv06KOPOvWchmFo0KBBVjeMdOzYUYMHD1Z0dLSqVKmSa/I8JiZGs2fPdmpsuSkJY9XatWurVatWWrt2raTbX+pY3jTyxRdf6NatW5Jur+Q2aNAgt8QJAEBhXb16VQsXLjTL165dK1B+cPr06XbfvFAc+fn56f7771d8fLwk6ejRo7p06ZLKly/v1PM6Kw/kDCUlDzRs2DC9/fbbysrK0rlz57R8+XJ1797dfN7yZp127dopPDzcabEAAFCSuTrHRX6r6JHfAgAAzkRe8TbyivkjrwggOyZFAQBy2L17t1W5cePGdrdt3LixOSkqPT1dhw4dUlRUVFGG51KLFy+2Ws3g008/1bBhw/JtV5SrERSVkJAQrV69Wo8//ri2bNkiSfrggw+UmZmpDz/8MN/2FSpUMBPxvXv31ieffOLMcIvUkCFD9MYbbygzM1MXLlzQkiVLzG1zP/vsM7Ne+fLl1bNnT3eF6TT//e9/lZ6eLkkqXbq0fv75ZzVs2DDPNvZcw0FBQfLy8lJGRoYkmdv9FkaFChWsyrGxsYqOji50vwAA1+vbt69eeOEFpaSkaNOmTdq7d6/5XGG+DA8JCTEfp6WlKSkpSUFBQXa1PX/+vM2+irOWLVtaldetW6e//vWvTj3nli1b9Msvv5jlV199VW+++Wa+7dw1Di4pY9Xhw4ebN40sW7ZMiYmJCg0NlWSd9O7YsaOqVq3qlhgBACisOXPmmKtbFsaSJUt04cIFVaxYsQiico+WLVuaNy9It8dxd3JSzuKsPJAzlJQ8UEREhNq1a6dVq1ZJur3r/J2bF7Zv365du3aZde3JHQMAcLdydY6L/JZzkN8CAADOQl7xN+QV80ZeEUB2rp+eCQAo9gqzgn72HaVu3rxZJDG5y5o1a8zHdevWtWvwmZWVpePHjzsxqoILCgrSDz/8YPUh4D//+Y/+/Oc/59u2Xr165mPLnR5KgqpVq6pz585m+U5CPjU1VXPmzDGPP/300/L19XV5fM5meR0PGDAg3w+s0u1VRuxx7733mo/v7EJWGHXr1rUql7RrDQDwG39/f/Xu3dss39l5Mzw8XI899liB+61Tp45V2TIZnB/Lyf9Vq1YtMTuaNmzY0OoGghUrVljt7OoMluOHwMBAjR071q529o4hilpJGav26tXL/AImIyNDs2bNkiTFxcVpz549Zr3f4+6lAIC7h+WNkP7+/qpZs6ZDP3ekp6friy++cMdLKDKW+Sjp9oJLzubMPFBRK0l5oBEjRpiPV6xYYe448fnnn5vHK1WqpG7durk8NgAASgpX57jIbzkH+S0AAOAs5BV/Q14xb+QVAWTHpCgAQA7ZV8w/d+6c3W2z7xTj7G1bnS0hIcF8bM9AX7o9MeTOKl7FUWBgoFatWqXmzZubxyZNmqSRI0fKMAyb7Vq3bm0+3rx5sy5evOjUOIva8OHDzcerVq3SqVOntHDhQl25csU8/ntNzhfkOrb8oJuXFi1amI+3bt2qkydPOhZcNpUqVbKaaLV06dJC9QcAcK/BgwfnODZw4EB5eHgUuM9mzZpZlVesWGFXuxs3bmjdunU2+ynOPD09NWrUKLOcmZlp16q2hWE5fqhXr55dE8fPnTvntoRzSRmr+vj4KCYmxizf+XLH8kuesLCwHF90AABQUuzcuVM7d+40y//85z91+PBhh34sx2mW75FFydvb26qclZXllPM8/vjjuv/++83yDz/8oM2bNzvlXHc4Mw9U1EpSHqhr164KCwuTdHs8PnPmTN28eVPz5s0z68TExOS4tgAAwG9cneMiv+Uc5LcAAIAzkFe0Rl4xb+QVAWTHpCgAQA61atWyKv/www92tcvMzNSPP/5oln19fVWtWrUijc3VLCcJ2bs974cffuikaIpOQECAVq5cqZYtW5rHpkyZohEjRticGPXEE0/Iy8tL0u2/9XvvveeSWItKx44dVb16dUm3P5DOnDnTasWF6Ohoqw9LvyeOXsdpaWmaMmWKXX0/+eST5uOsrCy9//77jgeYR5/Lli0r1qt5AADy9uijj6p9+/Zq2LCh+TNw4MBC9VmjRg2r9+zZs2frxo0b+babNWuWrl+/bpa7dOlSqDhcbcSIEVYLDkydOlXLly932vkKMg7+6KOP8pxk70wlaaw6fPhwc2LgoUOHtHLlSsXGxprPDxw40HwtAACUNJY3G3h4eFh9xrdX//79zcf79u1zypf9/v7+VuWkpKQiP8cd//jHP8zHhmHoT3/6k1MXVHJmHsgZSkoeyMvLy2rRh+nTp+vrr7+2unaGDBnijtAAAChRXJnjIr/lPOS3AABAUSOvmBN5xbyRVwRgiUlRAIAcHn30UZUpU8Ysx8bGavfu3fm2mzRpktUuMS1btlTp0qWdEqOr3JlEI0nr16/P94PFokWLrGbxF2dly5bVd999pzZt2pjHPvvsMw0dOjTXVSwiIiLUr18/s/zBBx/o+++/d+ichmEoLS2t4EEXgqenp9UHiEmTJlntFjFs2DA3ROUaltfxsmXL8q3/yiuv6Pjx43b1/fDDDys6OtosT548Wd99953DMVp6/vnnFRgYKOn2RKt+/fo5nESw98stAIDzrVy5Urt27TJ/IiIiCt3nyJEjzcdnzpzR2LFj86x/+vRpqzrlypUrUCLdnfz9/TVr1iyrXbZ69+6tBQsWOOV8luOHvXv35js22LJlS5FMji6okjRWrV27tlq1amWWBw4cqOTkZEm3v+Qh6Q0AKKlSU1M1d+5cs/zII49YjSns1adPH5UqVcosT58+vUjis5R9TLp3794iP8cd/fr1U+/evc3ykSNH1LJlS6uVV4uSM/NAzlCS8kBDhw6Vp+ftr1aPHDmiv/3tb+ZzLVq0UN26dV0SBwAAJZkrc1zkt5yH/BYAAChK5BVzR14xb+QVAVhiUhQAIAc/Pz+rG03T09PVqVMnbdy4Mdf6hmHo448/1ujRo62OZy+XRO3btzcfX716VQMGDMh1JwLDMDRt2jT17dtXksxBbHFXpkwZLVu2TO3atTOPTZ8+XYMHD851YtS7775rbueakZGhrl27auLEifl+QDh79qz++9//ql69etqxY0fRvggHDBkyxPzwe/78eXOFi4CAAPXp08dtcTmb5XX8448/6q233sq1XkpKiv785z/rP//5j0PX8JQpU+Tr6yvp9ofMnj17atKkScrMzLTZZvv27erdu7fVRMo7goOD9d///tcs79mzRw899JB+/vnnPOMwDENbt27V888/r+bNm9sdPwCg5BkyZIjVblETJ07U66+/nut7z8GDB9W+fXtdvHjRPPbWW2/Jz8/PJbEWpc6dO1tN7rp586Z69+6tfv36ad++ffm2T09P11dffWU1MdwWy/HDnSSy5e/Q0pIlS/T4448rPT3drePgkjRWHT58uPk4MTHRfNy6dWvVrFnTJTEAAFDUFi5cqCtXrphly5VZHREaGmq1iE9sbKxSUlIKHZ+l+vXrKyAgwCyPGzfO6j25qE2fPt1q/Lpr1y41bNhQ77zzjtVuprYkJibqtddes+tczs4DFbWSlAeKiIiwyqNaXjNDhw51SQwAAPweuCrHRX7LuchvAQCAokJe0TbyiraRVwRgib2KAQC5GjNmjL777jsz8ZyQkKBHHnlErVq1Ups2bVS1alWlp6fryJEjWrJkiQ4ePGjVfuDAgVYDuaLWqlUreXk59jb27rvvqlevXg616datm+rXr2/+HhYvXqzatWvrySef1D333KOsrCwdO3ZMixcv1v79+yVJHTp0UEpKijZs2ODQudyldOnSWrJkiXr16qUVK1ZIkmbNmqXMzEzNnDnTagWNypUra8GCBerQoYOuXbumtLQ0jR49Wm+//bbat2+vqKgolStXTpmZmbp69aoOHTqkHTt2aOfOnVZb7LpL1apV1blzZy1ZssTqeP/+/VW2bFk3ReV8o0aN0qeffmp+YfLaa69p/vz56tmzp6pVq6YbN25o7969Wrhwoc6fPy9J+te//qVXX33Vrv4bNmyoKVOmmLuMpaWl6c9//rPee+89de3aVXXq1FFgYKCuXr2q/fv366effjL/z3jvvfdy7XPAgAHau3ev+fzBgwf16KOPKioqSm3atFFkZKT8/f11/fp1XbhwQXv27NHmzZt15swZSWIFDQD4nfP19dUXX3yhFi1amMne8ePHa86cOerdu7dq1KihlJQUbd68WYsWLbK6aaBHjx4aMWKEu0IvtPHjxys4OFijR49WZmamDMNQbGysYmNjVadOHbVu3Vrh4eEqX768fHx8lJKSojNnzmjfvn1au3ZtjtWxIiMjcz3PAw88oPbt22vVqlWSpM2bN6tOnTp68skn1bBhQ3l5eenUqVNavny5tm3bJkmKiopS7dq1NX/+fOf+EmwoSWPVXr16qWLFirpw4YLV8d/z7qUAgN+/adOmmY+9vLysVjF1VP/+/fXDDz9IkpKTkzV//nwNHDiwsCGavL299fTTT+vjjz+WJK1du1ZVqlRReHi4AgICzJ0LqlSpUugdsaXbOyJs2LBBffv2NV/XpUuX9Pe//13jxo1Ts2bN1KxZM1WqVEkhISHKzMzUtWvXdPToUe3YsUNxcXE5FjCydaOps/NAzlCS8kAjRowwx8h3BAcH64knnnBZDAAA/B64IsdFfsu5yG8BAICiQl7RNvKKeSOvCMBkAABgw+nTp42mTZsakhz6GTJkiJGenl6kscTExDgcR/afGTNmWPUZHh5uPjdu3Dib596/f79RsWJFu84RHR1tXL582WjZsqV5LCYmxq7X1bJlS7t/H/bGntfrzy41NdXo0qWLVZt+/foZGRkZOeru27fPqFOnToH+Dlu2bMn1/OPGjTPrhIeH24zz2LFjVv2tXbs2z9eV3bJly3LEtHXrVof6cJTlaytIzLY48ruIjY01vLy87PobPfPMM4ZhOHb9GIZhLFiwwChbtqxD18OxY8fy7HPy5MmGj4+Pw9dZ/fr1HfhNAgAcNWPGDKv/d/fs2VMk/ZYvX96uMdQdcXFxRoUKFex+f3jyySeNtLQ0h16bo+wdBxbW2rVrjaioqAKPjStUqGBMnDjRuHXrls1znDt3zqhZs6Zd/dWrV884duyY3eNbR37Pjo5JnDFWLei4PS+jR4+2Onf58uWN1NTUIukbAABXO3r0qOHh4WG+r3Xs2LFQ/SUlJRl+fn5mf82bN89Rx9ExQnZXr141GjVqlOfYIK8cVUFkZGQYEyZMMIKDgws8jmvWrJmxYcOGPM/jzDyQvePdgoyrnZEHKux1kl16eroRFhZm1e9zzz1X6H4BALhbOTvHRX7rN+S3AABAcURe0T7kFfNGXhGA+/atAwAUe1WrVtXGjRs1ZcoU3X///XnW9fT0NFfa+vzzzx3exak4q1evnnbs2KGePXuaqzlkFxYWpgkTJmj9+vUKCQlxcYRFw9fXVwsWLFD37t3NY/PmzVP//v2VkZFhVfeee+7R3r17NXXqVNWvXz/fvuvXr6+//vWv2rlzp5o0aVLksTuiY8eOCg0NNctRUVFq3LixGyNyjb59+2rt2rVq1KiRzTr33Xef5s+frylTphToHL169dLhw4c1cuRIBQcH26zn4eGhqKgo/fvf/1aVKlXy7HPkyJFmn/n92ypdurTatm2ryZMnl5id2gAAhdO0aVMdPHhQf/nLXxQYGGizXoMGDbRw4ULNmzdP3t7eLozQeVq1aqWdO3dq8eLF6tatm4KCgvJtU758efXs2VMLFixQQkKCXnrpJfn4+NisHxoaqq1bt2rw4ME2f28hISEaNWqUtm/froiIiIK+nCJVUsaq2Vele/rpp+Xr6+uy8wMAUJSmT59utTJ9//79C9VfYGCgOnXqZJZ//vnnHDvVF1ZQUJA2btyoGTNmqFu3boqIiFDZsmVt5v+KQqlSpTRmzBgdP35cb775pho3bmy1S3tuPDw8VKdOHb300kuKj4/Xpk2b1Lx58zzbuCIP5AwlIQ/k5eWlp556yurY0KFDXXZ+AAB+b5yd4yK/5VzktwAAQGGRV7QPecW8kVcE4GFYvpsAAJCH06dPa9u2bUpISFBSUpJKlSql4OBg1axZU02aNLErSV3SJSQkaMOGDTp9+rSysrIUGhqqmjVr6uGHH5an59071zghIUGbN29WYmKirly5Ih8fH4WEhKhmzZq67777VLFiRXeHaEpISFB4eLgyMzMlSZMmTdJzzz3n5qhc69dff1VcXJzOnz8vX19fhYWFqUGDBnZ9qWKvjIwMxcXF6dChQ7pw4YIyMjIUFBSkyMhIPfjgg1YT0+yVlZWlHTt2aP/+/bp48aJSUlLk7++v0NBQ1a1bV/feey9ftADAXSw9PV2//PKLDh8+rIsXL8rPz0+hoaGKjo4uNjczOFNmZqZ27typ48eP6+LFi7p8+bJ8fHwUHBysChUqqEGDBoqMjCxw/xcvXtT69et1/PhxpaWlqVKlSgoPD1eLFi2K/USz4jpWjY2NVb9+/czy3r17de+997olFgAA4D5JSUnasmWLzp8/r4sXL+r69esKCAhQSEiIqlatqkaNGhUq7+qKPJAzFOc8UIcOHbRq1SpJUuPGjbV161a3xAEAwO+RM3Nc5LeKHvktAAAA9yGvmDvyisDdiUlRAADgrvLmm29qzJgxkm6v/HDmzJk8dzUCAAAAnKFdu3ZavXq1JCk6OlobN250c0QAAADIz8mTJ1WjRg1lZWVJkj755BMNHz7czVEBAAC4B/ktAAAAwD7kFQHnunu3tAAAAHedjIwMffbZZ2a5b9++TIgCAACAyx06dEhr1qwxyyNGjHBjNAAAALDXJ598Yt64EBAQYLUzAgAAwN2E/BYAAABgP/KKgHMxKQoAANw1Zs2apRMnTpjlkSNHujEaAAAA3K0mTJigO5u3ly9fXn379nVzRAAAAMjPpUuX9PHHH5vlp59+WgEBAW6MCAAAwH3IbwEAAAD2Ia8IOB+TogAAwF3h+++/1+jRo83y448/riZNmrgxIgAAANxtMjIy9MEHH+jLL780j/31r3+Vn5+fG6MCAABAfs6cOaN+/frp6tWrkiQfHx+98sor7g0KAADADchvAQAAAPYjrwi4hpe7AwAAAHCGbdu2aejQoTIMQ2fPntWFCxfM57y9vfX++++7MToAAADcLaZOnaqpU6cqIyNDJ0+eVHJysvlcZGSkXnjhBTdGBwAAAFs6deqkM2fOKDk5WSdOnFBmZqb53EsvvaTw8HA3RgcAAOA65LcAAAAA+5FXBFyPSVEAAOB36fr164qPj89x3MPDQ5MnT9b999/vhqgAAABwtzl37lyu49KgoCB9/fXXKlOmjBuiAgAAQH727dunEydO5Dj+2GOPafz48a4PCAAAwE3IbwEAAAD2I68IuJ6nuwMAAABwNk9PT1WqVEk9evTQ+vXrNWzYMHeHBAAAgLuQt7e3IiIiNHz4cMXHx6tRo0buDgkAAAB2KFu2rBo3bqwPP/xQK1eulK+vr7tDAgAAcAvyWwAAAID9yCsCruFhGIbh7iAAAAAAAAAAAAAAAAAAAAAAAAAAwF7sFAUAAAAAAAAAAAAAAAAAAAAAAACgRGFSFAAAAAAAAAAAAAAAAAAAAAAAAIAShUlRAAAAAAAAAAAAAAAAAAAAAAAAAEoUJkUBAAAAAAAAAAAAAAAAAAAAAAAAKFGYFAUAAAAAAAAAAAAAAAAAAAAAAACgRGFSFAAAAAAAAAAAAAAAAAAAAAAAAIAShUlRAAAAAAAAAAAAAAAAAAAAAAAAAEoUJkUBAAAAAAAAAAAAAAAAAAAAAAAAKFGYFAUAAAAAAAAAAAAAAAAAAAAAAACgRGFSFAAAAAAAAAAAAAAAAAAAAAAAAIAShUlRAAAAAAAAAAAAAAAAAAAAAAAAAEoUJkUBAAAAAAAAAAAAAAAAAAAAAAAAKFGYFAUAAAAAAAAAAAAAAAAAAAAAAACgRGFSFAAAAAAAAAAAAAAAAAAAAAAAAIAShUlRAAAAAAAAAAAAAAAAAAAAAAAAAEoUJkUBAAAAAAAAAAAAAAAAAAAAAAAAKFGYFAUAAAAAAAAAAAAAAAAAAAAAAACgRGFSFAAAAAAAAAAAAAAAAAAAAAAAAIAShUlRAAAAAAAAAAAAAAAAAAAAAAAAAEoUJkUBAAAAAAAAAAAAAAAAAAAAAAAAKFGYFAUAAAAAAAAAAAAAAAAAAAAAAACgRGFSFAAAAAAAAAAAAAAAAAAAAAAAAIAShUlRAAAAAAAAAAAAAAAAAAAAAAAAAEoUJkUBAAAAAAAAAAAAAAAAAAAAAAAAKFGYFAUAAAAAAAAAAAAAAAAAAAAAAACgRGFSFAAAAAAAAAAAAAAAAAAAAAAAAIAShUlRAAAAAAAAAAAAAAAAAAAAAAAAAEoUJkUBAAAAAAAAAAAAAAAAAAAAAAAAKFGYFAUAAAAAAAAAAAAAAAAAAAAAAACgRPl/ro1zZNk7FZoAAAAASUVORK5CYII=",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from textwrap import wrap\n",
    "\n",
    "# read model from pickle\n",
    "import pickle\n",
    "\n",
    "# if a word is a duplicate then remove from all_words\n",
    "def find_duplicates(all_words, occurences=1):\n",
    "    duplicates = []\n",
    "    non_duplicates = []\n",
    "\n",
    "    for i in all_words:\n",
    "        if i in duplicates: continue\n",
    "        else:\n",
    "            if all_words.count(i) > occurences: duplicates.append(i)\n",
    "            else: non_duplicates.append(i)\n",
    "    return duplicates\n",
    "\n",
    "def fetch_bert_models_from_github(fname):\n",
    "    url = f\"https://raw.githubusercontent.com/acd-engine/jupyterbook/master/data/analysis/models/{fname}\"\n",
    "    response = requests.get(url)\n",
    "    rawdata = response.content\n",
    "    return pickle.loads(rawdata)\n",
    "\n",
    "model_bert = fetch_bert_models_from_github(\"model_bert.pkl\")\n",
    "\n",
    "# cut = 5\n",
    "# l_matrix = get_linkage_matrix(model_bert)\n",
    "# df['cluster'] = fcluster(l_matrix, cut, criterion='maxclust')\n",
    "# dendrogram(l_matrix, orientation='top', truncate_mode=\"lastp\", p=cut, show_leaf_counts=True)\n",
    "\n",
    "# all_words = []\n",
    "\n",
    "# for i in df['cluster'].unique():\n",
    "#     cluster_docs = df[df['cluster'] == i]\n",
    "#     # print(i, get_most_common_word(cluster_docs['clean_text']))\n",
    "\n",
    "#     annot = \"\\n\".join(i[0] for idx,i in enumerate(get_most_common_word(cluster_docs['clean_text'])) if (idx < 3))\n",
    "    \n",
    "#     plt.annotate(annot, xy=(i/df['cluster'].nunique()-0.1, 0.15), \n",
    "#                  xytext=(i/df['cluster'].nunique()-0.1, 0.15), \n",
    "#                  xycoords='axes fraction', fontsize=9, color='red')\n",
    "\n",
    "#     [all_words.append(i[0]) for idx,i in enumerate(get_most_common_word(cluster_docs['clean_text']))]\n",
    "    \n",
    "# all_words_to_remove = find_duplicates(all_words, occurences=2)\n",
    "# all_words_to_remove.extend(['j','n','r','th','nd','exhibitionexhibited','http','www','isbn'])\n",
    "\n",
    "# for i in df['cluster'].unique():\n",
    "#     cluster_docs = df[df['cluster'] == i]\n",
    "#     # print(i, get_most_common_word(cluster_docs['clean_text']))\n",
    "#     annot = \"\\n\".join(i[0] for idx,i in enumerate(get_most_common_word(cluster_docs['clean_text'],\n",
    "#                                                                        more_words=all_words_to_remove)) if (idx < 5))\n",
    "    \n",
    "#     plt.annotate(annot, xy=(i/df['cluster'].nunique()-0.1, 0.025), \n",
    "#                  xytext=(i/df['cluster'].nunique()-0.1, 0.025), \n",
    "#                  xycoords='axes fraction', fontsize=9)\n",
    "    \n",
    "#     annot2 = cluster_docs.sort_values('cat_count', ascending=False)['category'].values[0:3]\n",
    "#     annot2 = '\\n\\n'.join(['\\n'.join(wrap(line, 18)) for line in [i.split(',')[0] for i in annot2]])\n",
    "#     # annot2 = '\\n'.join(wrap(annot2, 18)) # breaks strings into new lines\n",
    "\n",
    "#     plt.annotate(annot2, xy=(i/df['cluster'].nunique()-0.115, -0.24), \n",
    "#                 xytext=(i/df['cluster'].nunique()-0.115, -0.24), \n",
    "#                 xycoords='axes fraction', fontsize=9)\n",
    "\n",
    "# plt.title(\"Hierarchical Clustering Dendrogram - BERT\")\n",
    "\n",
    "# # make figure bigger\n",
    "# fig = plt.gcf()\n",
    "# fig.set_size_inches(14, 10)\n",
    "\n",
    "# plt.show()\n",
    "\n",
    "# # save the figure\n",
    "# fig.savefig('images/images_analysis/DAAOVenues_BERT1.png', dpi=300, bbox_inches='tight')\n",
    "\n",
    "# # save the data\n",
    "# df_model_bert = df.merge(clean_data_v2[['venue_name','venue_category_major','venue_category_minor','still_exists','State']], \n",
    "#                          left_on='category', right_on='venue_name', how='left').drop_duplicates()\n",
    "\n",
    "# df_model_bert.to_csv('data/local/DAAOVenues_BERT1.csv', index=False)\n",
    "\n",
    "from IPython.display import Image\n",
    "Image(filename='images/images_analysis/DAAOVenues_BERT1.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>.itables table td {\n",
       "    text-overflow: ellipsis;\n",
       "    overflow: hidden;\n",
       "}\n",
       "\n",
       ".itables table th {\n",
       "    text-overflow: ellipsis;\n",
       "    overflow: hidden;\n",
       "}\n",
       "\n",
       ".itables thead input {\n",
       "    width: 100%;\n",
       "    padding: 3px;\n",
       "    box-sizing: border-box;\n",
       "}\n",
       "\n",
       ".itables tfoot input {\n",
       "    width: 100%;\n",
       "    padding: 3px;\n",
       "    box-sizing: border-box;\n",
       "}\n",
       "</style>\n",
       "<div class=\"itables\">\n",
       "<table id=\"1d8a0afb-52b2-495b-8981-f7b7f3f823d3\" class=\"display nowrap\"style=\"table-layout:auto;width:auto;margin:auto;caption-side:bottom\"><thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      \n",
       "      <th>category</th>\n",
       "      <th>cat_count</th>\n",
       "      <th>cluster</th>\n",
       "      <th>venue_category_major</th>\n",
       "      <th>venue_category_minor</th>\n",
       "      <th>still_exists</th>\n",
       "      <th>State</th>\n",
       "    </tr>\n",
       "  </thead><tbody><tr><td>Loading... (need <a href=https://mwouts.github.io/itables/troubleshooting.html>help</a>?)</td></tr></tbody><tfoot><th>category</th><th>cat_count</th><th>cluster</th><th>venue_category_major</th><th>venue_category_minor</th><th>still_exists</th><th>State</th></tfoot></table>\n",
       "<link rel=\"stylesheet\" type=\"text/css\" href=\"https://cdn.datatables.net/1.13.1/css/jquery.dataTables.min.css\">\n",
       "<script type=\"module\">\n",
       "    // Import jquery and DataTable\n",
       "    import 'https://code.jquery.com/jquery-3.6.0.min.js';\n",
       "    import dt from 'https://cdn.datatables.net/1.12.1/js/jquery.dataTables.mjs';\n",
       "    dt($);\n",
       "\n",
       "    // Define the table data\n",
       "    const data = [[\"NSW Parliament House, Sydney, NSW\", 23, 3, \"Government / Public Museum \", \"State Parliament\", \"Y\", \"NSW\"], [\"Art Gallery of New South Wales, Sydney, NSW\", 292, 3, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"NSW\"], [\"Artspace, Sydney, NSW\", 79, 5, \"ARI or Indpendent \", \"CAOA\", \"Y\", \"NSW\"], [\"Tandanya National Aboriginal Cultural Institute, Adelaide, SA\", 9, 1, \"Government / Public Museum \", \"National Institution\", \"Y\", \"SA\"], [\"Art Gallery of South Australia, Adelaide, SA\", 65, 5, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"SA\"], [\"National Gallery of Victoria, Melbourne, VIC\", 124, 5, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"VIC\"], [\"National Gallery of Australia, Canberra, ACT\", 58, 1, \"Government / Public Museum \", \"National Institution\", \"Y\", \"ACT\"], [\"Bendigo Art Gallery, Bendigo, VIC\", 10, 3, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"VIC\"], [\"University of Melbourne, Melbourne, Vic\", 26, 3, \"University Gallery\", \"University Gallery\", \"Y\", \"VIC\"], [\"Macquarie University Art Gallery, Sydney, NSW\", 6, 1, \"University Gallery\", \"University Gallery\", \"Y\", \"NSW\"], [\"Manly Art Gallery & Museum, Manly, Sydney, NSW\", 10, 1, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Casula Powerhouse Arts Centre, Casula, NSW\", 17, 1, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Museum of Contemporary Art, Sydney, NSW\", 49, 1, \"Government / Public Museum \", \"Public Independent\", \"Y\", \"NSW\"], [\"Queensland Art Gallery, Brisbane, QLD\", 126, 5, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"QLD\"], [\"Powerhouse Museum, Sydney, NSW\", 7, 1, \"Government / Public Museum \", \"State Design Institutite\", \"Y\", \"NSW\"], [\"New England Regional Art Museum, Armidale, NSW\", 13, 5, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Centre for Contemporary Photography, Melbourne, VIC\", 17, 1, \"ARI or Indpendent \", \"ARI or Independent\", \"Y\", \"VIC\"], [\"Roslyn Oxley9 Gallery, Paddington, Sydney, NSW\", 15, 4, \"Commercial\", \"Commercial\", \"Y\", \"NSW\"], [\"Royal Exhibition Building, Melbourne, VIC\", 7, 1, \"ARI or Indpendent \", \"ARI or Independent\", \"Y\", \"VIC\"], [\"Museum of Sydney, Sydney, NSW\", 5, 4, \"Government / Public Museum \", \"City Gallery / Museum\", \"Y\", \"NSW\"], [\"Australian Centre for Contemporary Art, Melbourne, VIC\", 36, 5, \"ARI or Indpendent \", \"CAOA\", \"Y\", \"VIC\"], [\"Orange Regional Gallery, Orange, NSW\", 102, 1, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Campbelltown City Art Gallery, Campbelltown, NSW\", 22, 5, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Mosman Art Gallery, Mosman, NSW\", 15, 4, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"S.H. Ervin Gallery, Sydney, NSW\", 26, 5, \"Government / Public Museum \", \"Public Independent\", \"Y\", \"NSW\"], [\"Beaver Galleries, Canberra, ACT\", 5, 4, \"Commercial\", \"Commercial\", \"Y\", \"ACT\"], [\"Penrith Regional Gallery, Penrith, NSW\", 12, 4, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Geelong Art Gallery, Geelong, VIC\", 11, 3, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"VIC\"], [\"Institute of Modern Art, Brisbane, QLD\", 218, 5, \"ARI or Indpendent \", \"CAOA\", \"Y\", \"QLD\"], [\"Griffith University\", 5, 2, \"University Gallery\", \"University Gallery\", \"Y\", \"QLD\"], [\"Monash Gallery of Art, Melbourne, VIC\", 8, 4, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"VIC\"], [\"Art Gallery of Western Australia, Perth, WA\", 91, 1, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"WA\"], [\"RMIT Gallery, Melbourne, VIC\", 34, 5, \"University Gallery\", \"University Gallery\", \"Y\", \"VIC\"], [\"TAP Gallery, Darlinghurst, Sydney, NSW\", 7, 4, \"ARI or Indpendent \", \"ARI or Independent\", \"Y\", \"NSW\"], [\"Monash University Museum of Art, Melbourne, VIC\", 47, 3, \"University Gallery\", \"University Gallery\", \"Y\", \"VIC\"], [\"Hazelhurst Regional Gallery, Sydney, NSW\", 9, 2, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Heide Museum of Modern Art, Melbourne, VIC\", 72, 3, \"Government / Public Museum \", \"Public Independent\", \"Y\", \"VIC\"], [\"Bathurst Regional Art Gallery, Bathurst, NSW\", 11, 1, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Tasmanian Museum and Art Gallery, Hobart, TAS\", 46, 5, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"TAS\"], [\"Ballarat Fine Art Gallery, Ballarat, VIC\", 83, 5, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"VIC\"], [\"Warrnambool Art Gallery, Warrnambool, VIC\", 99, 5, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"VIC\"], [\"State Library of NSW, Sydney, NSW\", 6, 5, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"NSW\"], [\"National Art School, Sydney, NSW\", 13, 1, \"University Gallery\", \"University Gallery\", \"Y\", \"NSW\"], [\"Shanghai Art Gallery, Shanghai, China\", 12, 3, \"ARI or Indpendent \", \"International\", \"NaN\", \"China\"], [\"Latrobe Regional Gallery, Morwell, VIC\", 16, 5, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"VIC\"], [\"321 Blaxland Rd Wentworth Falls, Sydney\", 5, 1, \"ARI or Indpendent \", \"ARI or Independent\", \"N\", \"NSW\"], [\"282 Petrie Terrace, Brisbane QLD\", 5, 1, \"ARI or Indpendent \", \"ARI or Independent\", \"Y\", \"QLD\"], [\"Museums and Art Galleries of the Northern Territory, Darwin, NT\", 128, 3, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"NT\"], [\"Gallery Gabrielle Pizzi, Melbourne, VIC\", 15, 4, \"Commercial\", \"Commercial\", \"Y\", \"VIC\"], [\"Performance Space, Sydney, NSW\", 6, 2, \"ARI or Indpendent \", \"CAOA\", \"Y\", \"NSW\"], [\"Tamworth Regional Gallery, Tamworth, NSW\", 8, 3, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Boomalli Aboriginal Artists Cooperative, Sydney, NSW\", 6, 2, \"Commercial\", \"Commercial\", \"Y\", \"NSW\"], [\"Macquarie Galleries, Sydney, NSW\", 17, 1, \"Commercial\", \"Commercial\", \"N\", \"NSW\"], [\"Ian Potter Museum of Art, University of Melbourne, Melbourne, Vic.\", 82, 1, \"University Gallery\", \"University Gallery\", \"Y\", \"VIC\"], [\"Karen Woodbury Gallery, Melbourne, Vic.\", 19, 4, \"Commercial\", \"Commercial\", \"N\", \"VIC\"], [\"Annandale Galleries, Sydney, NSW\", 5, 4, \"Commercial\", \"Commercial\", \"Y\", \"NSW\"], [\"Blaxland Gallery, Sydney, NSW\", 7, 5, \"Commercial\", \"Commercial\", \"N\", \"NSW\"], [\"Hogarth Gallery, Sydney, NSW\", 19, 1, \"Commercial\", \"Commercial\", \"N\", \"NSW\"], [\"Newcastle Region Art Gallery, Newcastle, NSW\", 106, 3, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Greenaway Art Gallery, Adelaide, SA\", 23, 1, \"Commercial\", \"Commercial\", \"Y\", \"SA\"], [\"Lawrence Wilson Art Gallery, University of Western Australia, Perth, WA\", 31, 1, \"University Gallery\", \"University Gallery\", \"Y\", \"WA\"], [\"Flinders University Art Museum, Adelaide, SA\", 23, 5, \"University Gallery\", \"University Gallery\", \"Y\", \"SA\"], [\"Canberra Contemporary Art Space, Canberra, ACT\", 11, 3, \"ARI or Indpendent \", \"CAOA\", \"Y\", \"ACT\"], [\"Ray Hughes Gallery, Sydney, NSW\", 8, 2, \"Commercial\", \"Commercial\", \"N\", \"NSW\"], [\"Kaliman Gallery, Paddington, Sydney, NSW\", 7, 2, \"Commercial\", \"Commercial\", \"N\", \"NSW\"], [\"Stella Downer Fine Art, Sydney, NSW\", 19, 1, \"Commercial\", \"Commercial\", \"Y\", \"NSW\"], [\"Australian Centre for Photography, Sydney, NSW\", 22, 5, \"ARI or Indpendent \", \"ARI or Independent\", \"N\", \"NSW\"], [\"Anna Schwartz Gallery, Melbourne, Vic.\", 11, 2, \"Commercial\", \"Commercial\", \"Y\", \"VIC\"], [\"Ivan Dougherty Gallery, Sydney, NSW\", 61, 5, \"University Gallery\", \"University Gallery\", \"N\", \"NSW\"], [\"Glen Eira City Gallery, Melbourne, Vic.\", 10, 5, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"VIC\"], [\"Sherman Galleries, Sydney, NSW\", 42, 1, \"Commercial\", \"Commercial\", \"N\", \"NSW\"], [\"Contemporary Art Centre of South Australia, Adelaide, SA\", 341, 5, \"ARI or Indpendent \", \"CAOA\", \"N\", \"SA\"], [\"Drill Hall Gallery, Australian National University, Canberra, ACT\", 21, 3, \"University Gallery\", \"University Gallery\", \"Y\", \"ACT\"], [\"Brisbane City Art Gallery, Brisbane, Qld\", 68, 3, \"Government / Public Museum \", \"City Gallery / Museum\", \"Y\", \"QLD\"], [\"Wollongong City Art Gallery, Wollongong, NSW\", 171, 5, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Bett Gallery, Hobart, Tas.\", 6, 2, \"Commercial\", \"Commercial\", \"Y\", \"TAS\"], [\"Queen Victoria Museum and Art Gallery, Launceston, TAS\", 96, 3, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"TAS\"], [\"Eva Breuer Art Dealer, Woollahra, NSW\", 10, 4, \"Commercial\", \"Commercial\", \"N\", \"NSW\"], [\"Perth Institute of Contemporary Art, Perth, WA\", 8, 4, \"ARI or Indpendent \", \"CAOA\", \"Y\", \"WA\"], [\"David Jones Art Gallery, Sydney, NSW\", 18, 5, \"Commercial\", \"Commercial\", \"Y\", \"NSW\"], [\"Object Gallery, Sydney, NSW\", 6, 2, \"Government / Public Museum \", \"State Design Institutite\", \"Y\", \"NSW\"], [\"Plimsoll Gallery, University of Tasmania, Hobart, TAS\", 50, 5, \"University Gallery\", \"University Gallery\", \"Y\", \"TAS\"], [\"University of South Australia, Adelaide, SA\", 41, 5, \"University Gallery\", \"University Gallery\", \"Y\", \"SA\"], [\"Experimental Art Foundation, Adelaide, SA\", 424, 1, \"ARI or Indpendent \", \"CAOA\", \"N\", \"SA\"], [\"Tin Sheds Gallery, University of Sydney, Sydney, NSW\", 88, 5, \"University Gallery\", \"University Gallery\", \"Y\", \"NSW\"], [\"Coventry Gallery, Sydney, NSW\", 11, 2, \"Commercial\", \"Commercial\", \"N\", \"NSW\"], [\"ARC One Gallery, Melbourne, Vic.\", 5, 2, \"Commercial\", \"Commercial\", \"Y\", \"VIC\"], [\"Mori Gallery, Sydney, NSW\", 9, 2, \"Commercial\", \"Commercial\", \"N\", \"NSW\"], [\"Albury Regional Art Centre, Albury, NSW\", 7, 4, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Watters Gallery, Sydney, NSW\", 14, 1, \"Commercial\", \"Commercial\", \"N\", \"NSW\"], [\"Stills Gallery, Sydney, NSW\", 18, 1, \"Commercial\", \"Commercial\", \"N\", \"NSW\"], [\"Mary Place Gallery, Paddington, NSW\", 12, 1, \"Commercial\", \"Commercial\", \"Y\", \"NSW\"], [\"Christine Abrahams Gallery, Melbourne, VIC\", 17, 4, \"Commercial\", \"Commercial\", \"N\", \"VIC\"], [\"Ace of Clubs Hall, Redcliffe, QLD\", 22, 1, \"ARI or Indpendent \", \"Art Society\", \"N\", \"QLD\"], [\"Queen Victoria Market, Sydney, NSW\", 5, 2, \"ARI or Indpendent \", \"Art Society\", \"N\", \"VIC\"], [\"Alcaston Gallery, Melbourne, VIC\", 5, 4, \"Commercial\", \"Commercial\", \"Y\", \"VIC\"], [\"Garth Clark Gallery, New York, USA\", 5, 4, \"ARI or Indpendent \", \"International\", \"N\", \"USA\"], [\"Greenhill Galleries, Perth, WA\", 7, 2, \"Commercial\", \"Commercial\", \"N\", \"WA\"], [\"Global Gallery, Paddington, NSW\", 7, 4, \"Commercial\", \"Commercial\", \"N\", \"NSW\"], [\"Katanning Arts Centre, Katanning & Western Australian Museum, Perth, WA\", 5, 3, \"ARI or Indpendent \", \"Arts Centre\", \"Y\", \"WA\"], [\"Gomboc Gallery, Perth, WA\", 7, 2, \"Commercial\", \"Commercial\", \"Y\", \"WA\"], [\"Adelaide Central Gallery, Adelaide, SA\", 35, 1, \"University Gallery\", \"University Gallery\", \"Y\", \"SA\"], [\"Chalk Horse Gallery, Surry Hills, NSW\", 12, 1, \"Commercial\", \"Commercial\", \"Y\", \"NSW\"], [\"Bunbury Regional Art Galleries, Bunbury, WA\", 6, 1, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"WA\"], [\"Rex Irwin Art Dealer, Sydney, NSW\", 5, 3, \"Commercial\", \"Commercial\", \"N\", \"NSW\"], [\"Access Contemporary Art Gallery, Sydney, NSW\", 10, 3, \"Commercial\", \"Commercial\", \"N\", \"NSW\"], [\"West Australian Society of Arts, WA\", 8, 3, \"ARI or Indpendent \", \"Art Society\", \"Y\", \"WA\"], [\"8 Llankelly Place, Kings Cross, Sydney, 2011\", 96, 1, \"ARI or Indpendent \", \"ARI or Independent\", \"Y\", \"NSW\"], [\"Utopia Art Gallery, Sydney, NSW\", 8, 2, \"Commercial\", \"Commercial\", \"Y\", \"NSW\"], [\"Shoalhaven City Arts Centre, NSW\", 11, 1, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Charles Nodrum Gallery, Melbourne, VIC\", 6, 2, \"Commercial\", \"Commercial\", \"Y\", \"VIC\"], [\"Sir Herman Black Gallery, Sydney, NSW\", 5, 4, \"University Gallery\", \"University Gallery\", \"N\", \"NSW\"], [\"University of Queensland Art Museum, Brisbane, QLD\", 18, 3, \"University Gallery\", \"University Gallery\", \"Y\", \"QLD\"], [\"Central Street Gallery, Sydney, NSW\", 11, 1, \"Commercial\", \"Commercial\", \"N\", \"NSW\"], [\"Level 1, 129 Margaret Street  Brisbane, Qld, 4000\", 5, 1, \"ARI or Indpendent \", \"ARI or Independent\", \"N\", \"QLD\"], [\"John Curtin Gallery, Curtin University, Perth, WA\", 40, 5, \"University Gallery\", \"University Gallery\", \"Y\", \"WA\"], [\"School of Art, Australian National University, Canberra, ACT\", 24, 3, \"University Gallery\", \"University Gallery\", \"Y\", \"ACT\"], [\"Bender's Lane, 144 Charles Street, Launceston, Tasmania\", 15, 1, \"Commercial\", \"Commercial\", \"N\", \"TAS\"], [\"Corner Brisbane and Tamar Streets, Launceston, TAS\", 43, 1, \"Government / Public Museum \", \"State Design Institutite\", \"Y\", \"TAS\"]];\n",
       "\n",
       "    // Define the dt_args\n",
       "    let dt_args = {\"scrollY\": \"400px\", \"scrollCollapse\": true, \"scrollX\": true, \"paging\": false, \"dom\": \"tpr\", \"order\": [], \"initComplete\": function () {\n",
       "    // Apply the search\n",
       "    this.api()\n",
       "        .columns()\n",
       "        .every(function () {\n",
       "            const that = this;\n",
       "\n",
       "            $('input', this.footer()).on('keyup change clear', function () {\n",
       "                if (that.search() !== this.value) {\n",
       "                    that.search(this.value).draw();\n",
       "                }\n",
       "            });\n",
       "        });\n",
       "}\n",
       "};\n",
       "    dt_args[\"data\"] = data;\n",
       "\n",
       "    $(document).ready(function () {\n",
       "        // Setup - add a text input to each header or footer cell\n",
       "$('#1d8a0afb-52b2-495b-8981-f7b7f3f823d3 tfoot th').each(function () {\n",
       "    let title = $(this).text();\n",
       "    $(this).html('<input type=\"text\" placeholder=\"Search ' +\n",
       "        // We use encodeURI to avoid this LGTM error:\n",
       "        // https://lgtm.com/rules/1511866576920/\n",
       "        encodeURI(title).replaceAll(\"%20\", \" \") +\n",
       "        '\" />');\n",
       "});\n",
       "\n",
       "        $('#1d8a0afb-52b2-495b-8981-f7b7f3f823d3').DataTable(dt_args);\n",
       "    });\n",
       "</script>\n",
       "</div>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
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     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# read from github\n",
    "df_model_bert = fetch_small_data_from_github(\"DAAOVenues_BERT1.csv\")\n",
    "\n",
    "# display data\n",
    "show(df_model_bert.drop(['venue_name','clean_text','clean_text_sampled','text'],axis=1), scrollY=\"400px\", scrollCollapse=True, scrollX=True,\n",
    "     paging=False, showIndex=False, column_filters=\"footer\", dom=\"tpr\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
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   "source": [
    "##### Venue Category #####\n",
    "# using plotly, create interactive plot bar chart to show the venue categories proportion for each cluster\n",
    "import plotly.express as px\n",
    "import plotly.graph_objects as go\n",
    "\n",
    "df_model_bert_count_prop = pd.merge(df_model_bert[['cluster','venue_category_major']]\\\n",
    "        .groupby(['cluster','venue_category_major'])\\\n",
    "        .size().reset_index(name='Count')\\\n",
    "        .rename(columns={'venue_category_major':'Category','cluster':'Cluster'}),\n",
    "        df_model_bert[['cluster','venue_category_major']]\\\n",
    "        .groupby(['cluster','venue_category_major'])\\\n",
    "        .size().unstack().apply(lambda x: x/x.sum(), axis=1)\\\n",
    "        .unstack().reset_index(name='Prop')\\\n",
    "        .rename(columns={'venue_category_major':'Category','cluster':'Cluster'}), on = ['Cluster','Category'], \n",
    "        how='left')\n",
    "\n",
    "fig = px.bar(\n",
    "    data_frame = df_model_bert_count_prop\n",
    "    ,y = 'Prop'\n",
    "    ,x = 'Cluster'\n",
    "    ,color = 'Category'\n",
    "    ,title='BERT Clusters by major venue category'\n",
    "    ,height=500\n",
    "    ,width=800, # add hover\n",
    "    hover_data = {'Cluster':True, 'Category':True, 'Prop':':.2f', 'Count':True},\n",
    ")\n",
    "\n",
    "#move legend to top with two rows\n",
    "fig.update_layout(legend=dict(\n",
    "    orientation=\"h\",\n",
    "    yanchor=\"bottom\",\n",
    "    y=1.02,\n",
    "    xanchor=\"center\",\n",
    "    x=0.5,\n",
    "    font=dict(size=11.5),\n",
    "    title=None\n",
    "))\n",
    "\n",
    "# make y-axis labels larger\n",
    "fig.update_yaxes(tickfont=dict(size=16),title_text='')\n",
    "fig.update_xaxes(tickfont=dict(size=14),title_text='Clusters')\n",
    "\n",
    "fig.show()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We provide the same visual however show the most frequent terms used within the place names as opposed to the event descriptions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# cut = 5\n",
    "# l_matrix = get_linkage_matrix(model_bert)\n",
    "# df['cluster'] = fcluster(l_matrix, cut, criterion='maxclust')\n",
    "# dendrogram(l_matrix, orientation='top', truncate_mode=\"lastp\", p=cut, show_leaf_counts=True)\n",
    "\n",
    "# all_words = []\n",
    "\n",
    "# for i in df['cluster'].unique():\n",
    "#     cluster_docs = df[df['cluster'] == i]\n",
    "#     # print(i, get_most_common_word(cluster_docs['clean_text']))\n",
    "\n",
    "#     annot = \"\\n\".join(i[0] for idx,i in enumerate(get_most_common_word(cluster_docs['category'])) if (idx < 3))\n",
    "    \n",
    "#     plt.annotate(annot, xy=(i/df['cluster'].nunique()-0.1, 0.15), \n",
    "#                  xytext=(i/df['cluster'].nunique()-0.1, 0.15), \n",
    "#                  xycoords='axes fraction', fontsize=9, color='red')\n",
    "    \n",
    "#     [all_words.append(i[0]) for idx,i in enumerate(get_most_common_word(cluster_docs['category'], no_of_words=25))]\n",
    "    \n",
    "# all_words_to_remove = find_duplicates(all_words, occurences=4)\n",
    "# all_words_to_remove.extend([',','NSW','Sydney','Melbourne','Adelaide','South','SA','Brisbane','VIC',\n",
    "#                    '.', 'New', 'Australia', 'QLD', 'Vic','and','WA','Victoria','ACT','Qld',\n",
    "#                    'of','Wollongong','TAS','Queensland','Newcastle',\n",
    "#                    'Street','Hobart','the','The','Launceston','Orange','NT',\n",
    "#                    'Paddington','Darwin','for','Western','Warrnambool','Ballarat','Northern','Territory',\n",
    "#                    'England','Watters','Macquarie','Artspace','St',\"'s\",'&','Potter','Kings','Ian','Cross',\n",
    "#                    '8','Llankelly','2011','Fremantle','Queen','Ivan','Dougherty','Tasmania','Central',\n",
    "#                    'Curtin','France','Tin','Sheds','York','Monash','Heide',''])\n",
    "\n",
    "# for i in df['cluster'].unique():\n",
    "#     cluster_docs = df[df['cluster'] == i]\n",
    "#     # print(i, get_most_common_word(cluster_docs['clean_text']))\n",
    "#     annot = \"\\n\".join(i[0] for idx,i in enumerate(get_most_common_word(cluster_docs['category'],\n",
    "#                                                                        more_words=all_words_to_remove)) if (idx < 5))\n",
    "    \n",
    "#     plt.annotate(annot, xy=(i/df['cluster'].nunique()-0.1, 0.05), \n",
    "#                  xytext=(i/df['cluster'].nunique()-0.1, 0.05), \n",
    "#                  xycoords='axes fraction', fontsize=9)\n",
    "\n",
    "# plt.title(\"Hierarchical Clustering Dendrogram - BERT\")\n",
    "\n",
    "# # make figure bigger\n",
    "# fig = plt.gcf()\n",
    "# fig.set_size_inches(14, 10)\n",
    "\n",
    "# plt.show()\n",
    "\n",
    "# # save the figure\n",
    "# fig.savefig('images/images_analysis/DAAOVenues_BERT1_placenames.png', dpi=300, bbox_inches='tight')\n",
    "\n",
    "from IPython.display import Image\n",
    "Image(filename='images/images_analysis/DAAOVenues_BERT1_placenames.png')"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Hierarchy Clustering - BERT by demi-decade\n",
    "\n",
    "Using the BERT model, we generate a series of dendrograms that show the hierarchical clustering of the exhibition descriptions by 5-year periods. We omit pre-1960s data as there is not enough data to generate a meaningful dendrogram for each demi-decade (see table output below)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "      <th>10</th>\n",
       "      <th>11</th>\n",
       "      <th>12</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>decade_start</th>\n",
       "      <td>1900</td>\n",
       "      <td>1910</td>\n",
       "      <td>1920</td>\n",
       "      <td>1930</td>\n",
       "      <td>1940</td>\n",
       "      <td>1950</td>\n",
       "      <td>1960</td>\n",
       "      <td>1970</td>\n",
       "      <td>1980</td>\n",
       "      <td>1990</td>\n",
       "      <td>2000</td>\n",
       "      <td>2010</td>\n",
       "      <td>2020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>7</td>\n",
       "      <td>6</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>13</td>\n",
       "      <td>39</td>\n",
       "      <td>77</td>\n",
       "      <td>515</td>\n",
       "      <td>1042</td>\n",
       "      <td>1488</td>\n",
       "      <td>1113</td>\n",
       "      <td>212</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                0     1     2     3     4     5     6     7     8     9   \\\n",
       "decade_start  1900  1910  1920  1930  1940  1950  1960  1970  1980  1990   \n",
       "count            7     6     4     5    13    39    77   515  1042  1488   \n",
       "\n",
       "                10    11    12  \n",
       "decade_start  2000  2010  2020  \n",
       "count         1113   212     1  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(clean_data_v2['decade_start'].value_counts().sort_index().reset_index().rename(columns={'index':'decade_start', 'decade_start':'count'}).T)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Top ten place names and year"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "start_year  address_prompt                                          \n",
       "1983.0      Experimental Art Foundation, Adelaide, SA                   45\n",
       "1982.0      Experimental Art Foundation, Adelaide, SA                   30\n",
       "1979.0      Contemporary Art Centre of South Australia, Adelaide, SA    25\n",
       "1986.0      Experimental Art Foundation, Adelaide, SA                   23\n",
       "1978.0      Contemporary Art Centre of South Australia, Adelaide, SA    23\n",
       "1976.0      Experimental Art Foundation, Adelaide, SA                   22\n",
       "1997.0      Experimental Art Foundation, Adelaide, SA                   22\n",
       "1985.0      Experimental Art Foundation, Adelaide, SA                   22\n",
       "1979.0      Experimental Art Foundation, Adelaide, SA                   22\n",
       "1977.0      Experimental Art Foundation, Adelaide, SA                   20\n",
       "dtype: int64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(clean_data_v2[['start_year','address_prompt']].value_counts().head(10))"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Top ten place names and decade"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "decade_start  address_prompt                                                 \n",
       "1980          Experimental Art Foundation, Adelaide, SA                          199\n",
       "1970          Contemporary Art Centre of South Australia, Adelaide, SA           110\n",
       "1990          Art Gallery of New South Wales, Sydney, NSW                        106\n",
       "1980          Contemporary Art Centre of South Australia, Adelaide, SA           105\n",
       "1990          Experimental Art Foundation, Adelaide, SA                          101\n",
       "              Institute of Modern Art, Brisbane, QLD                              99\n",
       "1970          Experimental Art Foundation, Adelaide, SA                           98\n",
       "1990          Contemporary Art Centre of South Australia, Adelaide, SA            96\n",
       "1980          Museums and Art Galleries of the Northern Territory, Darwin, NT     80\n",
       "1990          Wollongong City Art Gallery, Wollongong, NSW                        79\n",
       "dtype: int64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(clean_data_v2[['decade_start','address_prompt']].value_counts().head(10))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "tags": [
     "remove-cell"
    ]
   },
   "outputs": [],
   "source": [
    "# def temporal_dendos(startdt=1900, enddt=1920, cut_input=3):\n",
    "#     df_period = clean_data_v2[(clean_data_v2['start_year'] >= startdt) & (clean_data_v2['start_year'] <= enddt)]\n",
    "#     # df_period = clean_data_v2[(clean_data_v2['decade_start'] >= startdt) & (clean_data_v2['decade_start'] <= enddt)]\n",
    "#     ### pre-process for NLP\n",
    "#     # Load the documents and their corresponding categorical variables into a Pandas dataframe\n",
    "#     df_period = pd.DataFrame({'text': df_period['slug2'], 'category': df_period['address_prompt']})\n",
    "\n",
    "#     # summarise text for each unique place name\n",
    "#     df_period['text'] = df_period.groupby('category')['text'].transform(lambda x: ' '.join(x))\n",
    "\n",
    "#     #add new column with count for each category\n",
    "#     df_period['cat_count'] = df_period.groupby('category')['category'].transform('count')\n",
    "#     df_period.drop_duplicates(inplace=True)\n",
    "\n",
    "#     # Clean the text\n",
    "#     stop_words = set(stopwords.words('english'))\n",
    "#     df_period = df_period[df_period['text'].notnull()]\n",
    "#     df_period['clean_text'] = df_period['text'].apply(clean_text)\n",
    "\n",
    "#     # randomly sample 512 tokens from each row in df['clean_text']\n",
    "#     # some strings are smalle than 512\n",
    "#     df_period['clean_text_sampled'] = df_period['clean_text'].apply(lambda x: ' '.join(random.sample(x.split(' '), 275)) if len(x.split(' ')) >= 275 else x)\n",
    "#     X_bert_period = df_period['clean_text_sampled'].apply(lambda x: pd.Series(bert_encode([str(x)])[0]))\n",
    "\n",
    "#     # setting distance_threshold=0 ensures we compute the full tree.\n",
    "#     model_bert_period = AgglomerativeClustering(distance_threshold=0, n_clusters=None)\n",
    "#     model_bert_period = model_bert_period.fit(np.array(X_bert_period))\n",
    "\n",
    "#     ### generate dendrogram\n",
    "#     cut = cut_input\n",
    "#     l_matrix = get_linkage_matrix(model_bert_period)\n",
    "#     df_period['cluster'] = fcluster(l_matrix, cut, criterion='maxclust')\n",
    "#     dendrogram(l_matrix, orientation='top', truncate_mode=\"lastp\", p=cut, show_leaf_counts=True)\n",
    "\n",
    "#     all_words = []\n",
    "\n",
    "#     for i in df_period['cluster'].unique():\n",
    "#         cluster_docs = df_period[df_period['cluster'] == i]\n",
    "#         # print(i, get_most_common_word(cluster_docs['clean_text']))\n",
    "\n",
    "#         annot = \"\\n\".join(i[0] for idx,i in enumerate(get_most_common_word(cluster_docs['clean_text'])) if (idx < 3))\n",
    "        \n",
    "#         plt.annotate(annot, xy=(i/df_period['cluster'].nunique()-0.1, 0.15), \n",
    "#                     xytext=(i/df_period['cluster'].nunique()-0.1, 0.15), \n",
    "#                     xycoords='axes fraction', fontsize=9, color='red')\n",
    "\n",
    "#         [all_words.append(i[0]) for idx,i in enumerate(get_most_common_word(cluster_docs['clean_text']))]\n",
    "        \n",
    "#     all_words_to_remove = find_duplicates(all_words, occurences=2)\n",
    "#     all_words_to_remove.extend(['j','th','nd','exhibitionexhibited','http','www','isbn'])\n",
    "\n",
    "#     for i in df_period['cluster'].unique():\n",
    "#         cluster_docs = df_period[df_period['cluster'] == i]\n",
    "#         # print(i, get_most_common_word(cluster_docs['clean_text']))\n",
    "#         annot = \"\\n\".join(i[0] for idx,i in enumerate(get_most_common_word(cluster_docs['clean_text'],\n",
    "#                                                                         more_words=all_words_to_remove)) if (idx < 5))\n",
    "        \n",
    "#         plt.annotate(annot, xy=(i/df_period['cluster'].nunique()-0.1, 0.025), \n",
    "#                     xytext=(i/df_period['cluster'].nunique()-0.1, 0.025), \n",
    "#                     xycoords='axes fraction', fontsize=9)\n",
    "        \n",
    "#         annot2 = cluster_docs.sort_values('cat_count', ascending=False)['category'].values[0:3]\n",
    "#         annot2 = '\\n\\n'.join(['\\n'.join(wrap(line, 18)) for line in [i.split(',')[0] for i in annot2]])\n",
    "#         # annot2 = '\\n'.join(wrap(annot2, 18)) # breaks strings into new lines\n",
    "\n",
    "#         plt.annotate(annot2, xy=(i/df_period['cluster'].nunique()-0.115, -0.24), \n",
    "#                     xytext=(i/df_period['cluster'].nunique()-0.115, -0.24), \n",
    "#                     xycoords='axes fraction', fontsize=9)\n",
    "\n",
    "#     plt.title(f\"Hierarchical Clustering Dendrogram - BERT - {startdt}-{enddt}\")\n",
    "\n",
    "#     # make figure bigger\n",
    "#     fig = plt.gcf()\n",
    "#     fig.set_size_inches(14, 10)\n",
    "\n",
    "#     plt.show()\n",
    "#     # return df_period\n",
    "\n",
    "#     # # save the figure\n",
    "#     # fig.savefig(f'images/daao_tlc/outputnew_bert_{startdt}_{enddt}.png', dpi=300, bbox_inches='tight')\n",
    "\n",
    "# temporal_dendos(1900, 1960, cut_input=5)\n",
    "# temporal_dendos(1960, 1980, cut_input=5)\n",
    "# temporal_dendos(1980, 2000, cut_input=5)\n",
    "# temporal_dendos(2000, 2021, cut_input=5)\n",
    "\n",
    "# # from IPython.display import Image\n",
    "# # Image(filename='images/daao_tlc/outputnew_bert_1900_1920.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1400x1000 with 1 Axes>"
      ]
     },
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     "output_type": "display_data"
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     "data": {
      "text/html": [
       "<style>.itables table td {\n",
       "    text-overflow: ellipsis;\n",
       "    overflow: hidden;\n",
       "}\n",
       "\n",
       ".itables table th {\n",
       "    text-overflow: ellipsis;\n",
       "    overflow: hidden;\n",
       "}\n",
       "\n",
       ".itables thead input {\n",
       "    width: 100%;\n",
       "    padding: 3px;\n",
       "    box-sizing: border-box;\n",
       "}\n",
       "\n",
       ".itables tfoot input {\n",
       "    width: 100%;\n",
       "    padding: 3px;\n",
       "    box-sizing: border-box;\n",
       "}\n",
       "</style>\n",
       "<div class=\"itables\">\n",
       "<table id=\"b765d8f9-10ea-4272-b1d8-4b9b72f5825c\" class=\"display nowrap\"style=\"table-layout:auto;width:auto;margin:auto;caption-side:bottom\"><thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      \n",
       "      <th>category</th>\n",
       "      <th>cat_count</th>\n",
       "      <th>cluster</th>\n",
       "      <th>venue_category_major</th>\n",
       "      <th>venue_category_minor</th>\n",
       "      <th>still_exists</th>\n",
       "      <th>State</th>\n",
       "    </tr>\n",
       "  </thead><tbody><tr><td>Loading... (need <a href=https://mwouts.github.io/itables/troubleshooting.html>help</a>?)</td></tr></tbody><tfoot><th>category</th><th>cat_count</th><th>cluster</th><th>venue_category_major</th><th>venue_category_minor</th><th>still_exists</th><th>State</th></tfoot></table>\n",
       "<link rel=\"stylesheet\" type=\"text/css\" href=\"https://cdn.datatables.net/1.13.1/css/jquery.dataTables.min.css\">\n",
       "<script type=\"module\">\n",
       "    // Import jquery and DataTable\n",
       "    import 'https://code.jquery.com/jquery-3.6.0.min.js';\n",
       "    import dt from 'https://cdn.datatables.net/1.12.1/js/jquery.dataTables.mjs';\n",
       "    dt($);\n",
       "\n",
       "    // Define the table data\n",
       "    const data = [[\"Art Gallery of New South Wales, Sydney, NSW\", 12, 2, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"NSW\"], [\"National Gallery of Victoria, Melbourne, VIC\", 5, 4, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"VIC\"], [\"Macquarie University Art Gallery, Sydney, NSW\", 1, 3, \"University Gallery\", \"University Gallery\", \"Y\", \"NSW\"], [\"Queensland Art Gallery, Brisbane, QLD\", 14, 1, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"QLD\"], [\"Ballarat Fine Art Gallery, Ballarat, VIC\", 2, 3, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"VIC\"], [\"Ace of Clubs Hall, Redcliffe, QLD\", 6, 4, \"ARI or Indpendent \", \"Art Society\", \"N\", \"QLD\"], [\"Central Street Gallery, Sydney, NSW\", 9, 1, \"Commercial\", \"Commercial\", \"N\", \"NSW\"], [\"Newcastle Region Art Gallery, Newcastle, NSW\", 3, 3, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Queen Victoria Museum and Art Gallery, Launceston, TAS\", 1, 3, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"TAS\"], [\"Plimsoll Gallery, University of Tasmania, Hobart, TAS\", 1, 5, \"University Gallery\", \"University Gallery\", \"Y\", \"TAS\"], [\"Contemporary Art Centre of South Australia, Adelaide, SA\", 4, 3, \"ARI or Indpendent \", \"CAOA\", \"N\", \"SA\"], [\"Watters Gallery, Sydney, NSW\", 7, 2, \"Commercial\", \"Commercial\", \"N\", \"NSW\"]];\n",
       "\n",
       "    // Define the dt_args\n",
       "    let dt_args = {\"scrollY\": \"400px\", \"scrollCollapse\": true, \"scrollX\": true, \"paging\": false, \"dom\": \"tpr\", \"order\": [], \"initComplete\": function () {\n",
       "    // Apply the search\n",
       "    this.api()\n",
       "        .columns()\n",
       "        .every(function () {\n",
       "            const that = this;\n",
       "\n",
       "            $('input', this.footer()).on('keyup change clear', function () {\n",
       "                if (that.search() !== this.value) {\n",
       "                    that.search(this.value).draw();\n",
       "                }\n",
       "            });\n",
       "        });\n",
       "}\n",
       "};\n",
       "    dt_args[\"data\"] = data;\n",
       "\n",
       "    $(document).ready(function () {\n",
       "        // Setup - add a text input to each header or footer cell\n",
       "$('#b765d8f9-10ea-4272-b1d8-4b9b72f5825c tfoot th').each(function () {\n",
       "    let title = $(this).text();\n",
       "    $(this).html('<input type=\"text\" placeholder=\"Search ' +\n",
       "        // We use encodeURI to avoid this LGTM error:\n",
       "        // https://lgtm.com/rules/1511866576920/\n",
       "        encodeURI(title).replaceAll(\"%20\", \" \") +\n",
       "        '\" />');\n",
       "});\n",
       "\n",
       "        $('#b765d8f9-10ea-4272-b1d8-4b9b72f5825c').DataTable(dt_args);\n",
       "    });\n",
       "</script>\n",
       "</div>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n"
     ]
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1400x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<style>.itables table td {\n",
       "    text-overflow: ellipsis;\n",
       "    overflow: hidden;\n",
       "}\n",
       "\n",
       ".itables table th {\n",
       "    text-overflow: ellipsis;\n",
       "    overflow: hidden;\n",
       "}\n",
       "\n",
       ".itables thead input {\n",
       "    width: 100%;\n",
       "    padding: 3px;\n",
       "    box-sizing: border-box;\n",
       "}\n",
       "\n",
       ".itables tfoot input {\n",
       "    width: 100%;\n",
       "    padding: 3px;\n",
       "    box-sizing: border-box;\n",
       "}\n",
       "</style>\n",
       "<div class=\"itables\">\n",
       "<table id=\"52514257-08ca-4681-b480-c034e13be711\" class=\"display nowrap\"style=\"table-layout:auto;width:auto;margin:auto;caption-side:bottom\"><thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      \n",
       "      <th>category</th>\n",
       "      <th>cat_count</th>\n",
       "      <th>cluster</th>\n",
       "      <th>venue_category_major</th>\n",
       "      <th>venue_category_minor</th>\n",
       "      <th>still_exists</th>\n",
       "      <th>State</th>\n",
       "    </tr>\n",
       "  </thead><tbody><tr><td>Loading... (need <a href=https://mwouts.github.io/itables/troubleshooting.html>help</a>?)</td></tr></tbody><tfoot><th>category</th><th>cat_count</th><th>cluster</th><th>venue_category_major</th><th>venue_category_minor</th><th>still_exists</th><th>State</th></tfoot></table>\n",
       "<link rel=\"stylesheet\" type=\"text/css\" href=\"https://cdn.datatables.net/1.13.1/css/jquery.dataTables.min.css\">\n",
       "<script type=\"module\">\n",
       "    // Import jquery and DataTable\n",
       "    import 'https://code.jquery.com/jquery-3.6.0.min.js';\n",
       "    import dt from 'https://cdn.datatables.net/1.12.1/js/jquery.dataTables.mjs';\n",
       "    dt($);\n",
       "\n",
       "    // Define the table data\n",
       "    const data = [[\"Art Gallery of New South Wales, Sydney, NSW\", 10, 2, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"NSW\"], [\"Art Gallery of South Australia, Adelaide, SA\", 16, 2, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"SA\"], [\"National Gallery of Victoria, Melbourne, VIC\", 6, 4, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"VIC\"], [\"University of Melbourne, Melbourne, Vic\", 4, 5, \"University Gallery\", \"University Gallery\", \"Y\", \"VIC\"], [\"Queensland Art Gallery, Brisbane, QLD\", 12, 2, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"QLD\"], [\"Institute of Modern Art, Brisbane, QLD\", 4, 5, \"ARI or Indpendent \", \"CAOA\", \"Y\", \"QLD\"], [\"Art Gallery of Western Australia, Perth, WA\", 3, 4, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"WA\"], [\"Monash University Museum of Art, Melbourne, VIC\", 2, 3, \"University Gallery\", \"University Gallery\", \"Y\", \"VIC\"], [\"Tasmanian Museum and Art Gallery, Hobart, TAS\", 5, 4, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"TAS\"], [\"Ballarat Fine Art Gallery, Ballarat, VIC\", 4, 4, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"VIC\"], [\"Warrnambool Art Gallery, Warrnambool, VIC\", 18, 5, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"VIC\"], [\"National Art School, Sydney, NSW\", 1, 1, \"University Gallery\", \"University Gallery\", \"Y\", \"NSW\"], [\"Macquarie Galleries, Sydney, NSW\", 1, 1, \"Commercial\", \"Commercial\", \"N\", \"NSW\"], [\"Watters Gallery, Sydney, NSW\", 3, 2, \"Commercial\", \"Commercial\", \"N\", \"NSW\"], [\"Coventry Gallery, Sydney, NSW\", 2, 1, \"Commercial\", \"Commercial\", \"N\", \"NSW\"], [\"Ace of Clubs Hall, Redcliffe, QLD\", 1, 2, \"ARI or Indpendent \", \"Art Society\", \"N\", \"QLD\"], [\"Experimental Art Foundation, Adelaide, SA\", 14, 2, \"ARI or Indpendent \", \"CAOA\", \"N\", \"SA\"], [\"Hogarth Gallery, Sydney, NSW\", 2, 1, \"Commercial\", \"Commercial\", \"N\", \"NSW\"], [\"Central Street Gallery, Sydney, NSW\", 2, 2, \"Commercial\", \"Commercial\", \"N\", \"NSW\"], [\"Newcastle Region Art Gallery, Newcastle, NSW\", 11, 5, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"John Curtin Gallery, Curtin University, Perth, WA\", 1, 2, \"University Gallery\", \"University Gallery\", \"Y\", \"WA\"], [\"Queen Victoria Museum and Art Gallery, Launceston, TAS\", 5, 5, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"TAS\"], [\"Museums and Art Galleries of the Northern Territory, Darwin, NT\", 4, 4, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"NT\"], [\"Plimsoll Gallery, University of Tasmania, Hobart, TAS\", 1, 3, \"University Gallery\", \"University Gallery\", \"Y\", \"TAS\"], [\"Contemporary Art Centre of South Australia, Adelaide, SA\", 40, 5, \"ARI or Indpendent \", \"CAOA\", \"N\", \"SA\"]];\n",
       "\n",
       "    // Define the dt_args\n",
       "    let dt_args = {\"scrollY\": \"400px\", \"scrollCollapse\": true, \"scrollX\": true, \"paging\": false, \"dom\": \"tpr\", \"order\": [], \"initComplete\": function () {\n",
       "    // Apply the search\n",
       "    this.api()\n",
       "        .columns()\n",
       "        .every(function () {\n",
       "            const that = this;\n",
       "\n",
       "            $('input', this.footer()).on('keyup change clear', function () {\n",
       "                if (that.search() !== this.value) {\n",
       "                    that.search(this.value).draw();\n",
       "                }\n",
       "            });\n",
       "        });\n",
       "}\n",
       "};\n",
       "    dt_args[\"data\"] = data;\n",
       "\n",
       "    $(document).ready(function () {\n",
       "        // Setup - add a text input to each header or footer cell\n",
       "$('#52514257-08ca-4681-b480-c034e13be711 tfoot th').each(function () {\n",
       "    let title = $(this).text();\n",
       "    $(this).html('<input type=\"text\" placeholder=\"Search ' +\n",
       "        // We use encodeURI to avoid this LGTM error:\n",
       "        // https://lgtm.com/rules/1511866576920/\n",
       "        encodeURI(title).replaceAll(\"%20\", \" \") +\n",
       "        '\" />');\n",
       "});\n",
       "\n",
       "        $('#52514257-08ca-4681-b480-c034e13be711').DataTable(dt_args);\n",
       "    });\n",
       "</script>\n",
       "</div>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n"
     ]
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1400x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<style>.itables table td {\n",
       "    text-overflow: ellipsis;\n",
       "    overflow: hidden;\n",
       "}\n",
       "\n",
       ".itables table th {\n",
       "    text-overflow: ellipsis;\n",
       "    overflow: hidden;\n",
       "}\n",
       "\n",
       ".itables thead input {\n",
       "    width: 100%;\n",
       "    padding: 3px;\n",
       "    box-sizing: border-box;\n",
       "}\n",
       "\n",
       ".itables tfoot input {\n",
       "    width: 100%;\n",
       "    padding: 3px;\n",
       "    box-sizing: border-box;\n",
       "}\n",
       "</style>\n",
       "<div class=\"itables\">\n",
       "<table id=\"f17caaf9-3cf6-4bd4-a0e4-465b52ea71cf\" class=\"display nowrap\"style=\"table-layout:auto;width:auto;margin:auto;caption-side:bottom\"><thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      \n",
       "      <th>category</th>\n",
       "      <th>cat_count</th>\n",
       "      <th>cluster</th>\n",
       "      <th>venue_category_major</th>\n",
       "      <th>venue_category_minor</th>\n",
       "      <th>still_exists</th>\n",
       "      <th>State</th>\n",
       "    </tr>\n",
       "  </thead><tbody><tr><td>Loading... (need <a href=https://mwouts.github.io/itables/troubleshooting.html>help</a>?)</td></tr></tbody><tfoot><th>category</th><th>cat_count</th><th>cluster</th><th>venue_category_major</th><th>venue_category_minor</th><th>still_exists</th><th>State</th></tfoot></table>\n",
       "<link rel=\"stylesheet\" type=\"text/css\" href=\"https://cdn.datatables.net/1.13.1/css/jquery.dataTables.min.css\">\n",
       "<script type=\"module\">\n",
       "    // Import jquery and DataTable\n",
       "    import 'https://code.jquery.com/jquery-3.6.0.min.js';\n",
       "    import dt from 'https://cdn.datatables.net/1.12.1/js/jquery.dataTables.mjs';\n",
       "    dt($);\n",
       "\n",
       "    // Define the table data\n",
       "    const data = [[\"Art Gallery of New South Wales, Sydney, NSW\", 29, 4, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"NSW\"], [\"Art Gallery of South Australia, Adelaide, SA\", 20, 1, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"SA\"], [\"National Gallery of Victoria, Melbourne, VIC\", 23, 4, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"VIC\"], [\"Bendigo Art Gallery, Bendigo, VIC\", 1, 3, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"VIC\"], [\"University of Melbourne, Melbourne, Vic\", 12, 1, \"University Gallery\", \"University Gallery\", \"Y\", \"VIC\"], [\"Queensland Art Gallery, Brisbane, QLD\", 10, 3, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"QLD\"], [\"S.H. Ervin Gallery, Sydney, NSW\", 1, 5, \"Government / Public Museum \", \"Public Independent\", \"Y\", \"NSW\"], [\"Beaver Galleries, Canberra, ACT\", 1, 5, \"Commercial\", \"Commercial\", \"Y\", \"ACT\"], [\"Geelong Art Gallery, Geelong, VIC\", 1, 5, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"VIC\"], [\"Institute of Modern Art, Brisbane, QLD\", 53, 1, \"ARI or Indpendent \", \"CAOA\", \"Y\", \"QLD\"], [\"Art Gallery of Western Australia, Perth, WA\", 5, 1, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"WA\"], [\"RMIT Gallery, Melbourne, VIC\", 2, 5, \"University Gallery\", \"University Gallery\", \"Y\", \"VIC\"], [\"Monash University Museum of Art, Melbourne, VIC\", 10, 1, \"University Gallery\", \"University Gallery\", \"Y\", \"VIC\"], [\"Tasmanian Museum and Art Gallery, Hobart, TAS\", 5, 2, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"TAS\"], [\"Ballarat Fine Art Gallery, Ballarat, VIC\", 4, 1, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"VIC\"], [\"Warrnambool Art Gallery, Warrnambool, VIC\", 19, 4, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"VIC\"], [\"Shanghai Art Gallery, Shanghai, China\", 1, 5, \"ARI or Indpendent \", \"International\", \"NaN\", \"China\"], [\"Hogarth Gallery, Sydney, NSW\", 2, 5, \"Commercial\", \"Commercial\", \"N\", \"NSW\"], [\"Watters Gallery, Sydney, NSW\", 3, 5, \"Commercial\", \"Commercial\", \"N\", \"NSW\"], [\"Experimental Art Foundation, Adelaide, SA\", 116, 4, \"ARI or Indpendent \", \"CAOA\", \"N\", \"SA\"], [\"Ivan Dougherty Gallery, Sydney, NSW\", 3, 1, \"University Gallery\", \"University Gallery\", \"N\", \"NSW\"], [\"Australian Centre for Photography, Sydney, NSW\", 2, 5, \"ARI or Indpendent \", \"ARI or Independent\", \"N\", \"NSW\"], [\"Coventry Gallery, Sydney, NSW\", 3, 5, \"Commercial\", \"Commercial\", \"N\", \"NSW\"], [\"Stella Downer Fine Art, Sydney, NSW\", 1, 2, \"Commercial\", \"Commercial\", \"Y\", \"NSW\"], [\"Ace of Clubs Hall, Redcliffe, QLD\", 2, 5, \"ARI or Indpendent \", \"Art Society\", \"N\", \"QLD\"], [\"David Jones Art Gallery, Sydney, NSW\", 3, 5, \"Commercial\", \"Commercial\", \"Y\", \"NSW\"], [\"Lawrence Wilson Art Gallery, University of Western Australia, Perth, WA\", 1, 5, \"University Gallery\", \"University Gallery\", \"Y\", \"WA\"], [\"Plimsoll Gallery, University of Tasmania, Hobart, TAS\", 4, 2, \"University Gallery\", \"University Gallery\", \"Y\", \"TAS\"], [\"Queen Victoria Museum and Art Gallery, Launceston, TAS\", 14, 1, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"TAS\"], [\"Blaxland Gallery, Sydney, NSW\", 2, 5, \"Commercial\", \"Commercial\", \"N\", \"NSW\"], [\"Central Street Gallery, Sydney, NSW\", 1, 2, \"Commercial\", \"Commercial\", \"N\", \"NSW\"], [\"Wollongong City Art Gallery, Wollongong, NSW\", 5, 1, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Museums and Art Galleries of the Northern Territory, Darwin, NT\", 6, 1, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"NT\"], [\"John Curtin Gallery, Curtin University, Perth, WA\", 3, 1, \"University Gallery\", \"University Gallery\", \"Y\", \"WA\"], [\"Newcastle Region Art Gallery, Newcastle, NSW\", 9, 2, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"University of Queensland Art Museum, Brisbane, QLD\", 1, 5, \"University Gallery\", \"University Gallery\", \"Y\", \"QLD\"], [\"Contemporary Art Centre of South Australia, Adelaide, SA\", 88, 1, \"ARI or Indpendent \", \"CAOA\", \"N\", \"SA\"], [\"Corner Brisbane and Tamar Streets, Launceston, TAS\", 25, 3, \"Government / Public Museum \", \"State Design Institutite\", \"Y\", \"TAS\"]];\n",
       "\n",
       "    // Define the dt_args\n",
       "    let dt_args = {\"scrollY\": \"400px\", \"scrollCollapse\": true, \"scrollX\": true, \"paging\": false, \"dom\": \"tpr\", \"order\": [], \"initComplete\": function () {\n",
       "    // Apply the search\n",
       "    this.api()\n",
       "        .columns()\n",
       "        .every(function () {\n",
       "            const that = this;\n",
       "\n",
       "            $('input', this.footer()).on('keyup change clear', function () {\n",
       "                if (that.search() !== this.value) {\n",
       "                    that.search(this.value).draw();\n",
       "                }\n",
       "            });\n",
       "        });\n",
       "}\n",
       "};\n",
       "    dt_args[\"data\"] = data;\n",
       "\n",
       "    $(document).ready(function () {\n",
       "        // Setup - add a text input to each header or footer cell\n",
       "$('#f17caaf9-3cf6-4bd4-a0e4-465b52ea71cf tfoot th').each(function () {\n",
       "    let title = $(this).text();\n",
       "    $(this).html('<input type=\"text\" placeholder=\"Search ' +\n",
       "        // We use encodeURI to avoid this LGTM error:\n",
       "        // https://lgtm.com/rules/1511866576920/\n",
       "        encodeURI(title).replaceAll(\"%20\", \" \") +\n",
       "        '\" />');\n",
       "});\n",
       "\n",
       "        $('#f17caaf9-3cf6-4bd4-a0e4-465b52ea71cf').DataTable(dt_args);\n",
       "    });\n",
       "</script>\n",
       "</div>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n"
     ]
    },
    {
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       "    <tr style=\"text-align: right;\">\n",
       "      \n",
       "      <th>category</th>\n",
       "      <th>cat_count</th>\n",
       "      <th>cluster</th>\n",
       "      <th>venue_category_major</th>\n",
       "      <th>venue_category_minor</th>\n",
       "      <th>still_exists</th>\n",
       "      <th>State</th>\n",
       "    </tr>\n",
       "  </thead><tbody><tr><td>Loading... (need <a href=https://mwouts.github.io/itables/troubleshooting.html>help</a>?)</td></tr></tbody><tfoot><th>category</th><th>cat_count</th><th>cluster</th><th>venue_category_major</th><th>venue_category_minor</th><th>still_exists</th><th>State</th></tfoot></table>\n",
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Ervin Gallery, Sydney, NSW\", 1, 5, \"Government / Public Museum \", \"Public Independent\", \"Y\", \"NSW\"], [\"Penrith Regional Gallery, Penrith, NSW\", 1, 1, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Geelong Art Gallery, Geelong, VIC\", 1, 4, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"VIC\"], [\"Institute of Modern Art, Brisbane, QLD\", 49, 5, \"ARI or Indpendent \", \"CAOA\", \"Y\", \"QLD\"], [\"Art Gallery of Western Australia, Perth, WA\", 18, 4, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"WA\"], [\"Monash University Museum of Art, Melbourne, VIC\", 4, 3, \"University Gallery\", \"University Gallery\", \"Y\", \"VIC\"], [\"Heide Museum of Modern Art, Melbourne, VIC\", 9, 3, \"Government / Public Museum \", \"Public Independent\", \"Y\", \"VIC\"], [\"Bathurst Regional Art Gallery, Bathurst, NSW\", 1, 1, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Tasmanian Museum and Art Gallery, Hobart, TAS\", 8, 3, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"TAS\"], [\"Ballarat Fine Art Gallery, Ballarat, VIC\", 2, 5, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"VIC\"], [\"Warrnambool Art Gallery, Warrnambool, VIC\", 17, 4, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"VIC\"], [\"Shanghai Art Gallery, Shanghai, China\", 2, 3, \"ARI or Indpendent \", \"International\", \"NaN\", \"China\"], [\"Wollongong City Art Gallery, Wollongong, NSW\", 31, 5, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Experimental Art Foundation, Adelaide, SA\", 150, 2, \"ARI or Indpendent \", \"CAOA\", \"N\", \"SA\"], [\"Ivan Dougherty Gallery, Sydney, NSW\", 9, 4, \"University Gallery\", \"University Gallery\", \"N\", \"NSW\"], [\"Coventry Gallery, Sydney, NSW\", 2, 1, \"Commercial\", \"Commercial\", \"N\", \"NSW\"], [\"Queen Victoria Museum and Art Gallery, Launceston, TAS\", 23, 3, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"TAS\"], [\"Greenhill Galleries, Perth, WA\", 2, 4, \"Commercial\", \"Commercial\", \"N\", \"WA\"], [\"Museums and Art Galleries of the Northern Territory, Darwin, NT\", 51, 4, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"NT\"], [\"Albury Regional Art Centre, Albury, NSW\", 1, 1, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"David Jones Art Gallery, Sydney, NSW\", 1, 1, \"Commercial\", \"Commercial\", \"Y\", \"NSW\"], [\"Plimsoll Gallery, University of Tasmania, Hobart, TAS\", 18, 3, \"University Gallery\", \"University Gallery\", \"Y\", \"TAS\"], [\"Hogarth Gallery, Sydney, NSW\", 1, 1, \"Commercial\", \"Commercial\", \"N\", \"NSW\"], [\"Australian Centre for Photography, Sydney, NSW\", 5, 5, \"ARI or Indpendent \", \"ARI or Independent\", \"N\", \"NSW\"], [\"Newcastle Region Art Gallery, Newcastle, NSW\", 9, 4, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"John Curtin Gallery, Curtin University, Perth, WA\", 1, 4, \"University Gallery\", \"University Gallery\", \"Y\", \"WA\"], [\"Ian Potter Museum of Art, University of Melbourne, Melbourne, Vic.\", 8, 3, \"University Gallery\", \"University Gallery\", \"Y\", \"VIC\"], [\"Flinders University Art Museum, Adelaide, SA\", 3, 3, \"University Gallery\", \"University Gallery\", \"Y\", \"SA\"], [\"Brisbane City Art Gallery, Brisbane, Qld\", 1, 5, \"Government / Public Museum \", \"City Gallery / Museum\", \"Y\", \"QLD\"], [\"School of Art, Australian National University, Canberra, ACT\", 6, 3, \"University Gallery\", \"University Gallery\", \"Y\", \"ACT\"], [\"University of Queensland Art Museum, Brisbane, QLD\", 5, 3, \"University Gallery\", \"University Gallery\", \"Y\", \"QLD\"], [\"Contemporary Art Centre of South Australia, Adelaide, SA\", 71, 3, \"ARI or Indpendent \", \"CAOA\", \"N\", \"SA\"], [\"Corner Brisbane and Tamar Streets, Launceston, TAS\", 15, 2, \"Government / Public Museum \", \"State Design Institutite\", \"Y\", \"TAS\"], [\"Mori Gallery, Sydney, NSW\", 1, 3, \"Commercial\", \"Commercial\", \"N\", \"NSW\"], [\"Performance Space, Sydney, NSW\", 1, 2, \"ARI or Indpendent \", \"CAOA\", \"Y\", \"NSW\"]];\n",
       "\n",
       "    // Define the dt_args\n",
       "    let dt_args = {\"scrollY\": \"400px\", \"scrollCollapse\": true, \"scrollX\": true, \"paging\": false, \"dom\": \"tpr\", \"order\": [], \"initComplete\": function () {\n",
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",
      "text/plain": [
       "<Figure size 1400x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<style>.itables table td {\n",
       "    text-overflow: ellipsis;\n",
       "    overflow: hidden;\n",
       "}\n",
       "\n",
       ".itables table th {\n",
       "    text-overflow: ellipsis;\n",
       "    overflow: hidden;\n",
       "}\n",
       "\n",
       ".itables thead input {\n",
       "    width: 100%;\n",
       "    padding: 3px;\n",
       "    box-sizing: border-box;\n",
       "}\n",
       "\n",
       ".itables tfoot input {\n",
       "    width: 100%;\n",
       "    padding: 3px;\n",
       "    box-sizing: border-box;\n",
       "}\n",
       "</style>\n",
       "<div class=\"itables\">\n",
       "<table id=\"29e75257-8a72-40ab-bbe4-6cf9825995c1\" class=\"display nowrap\"style=\"table-layout:auto;width:auto;margin:auto;caption-side:bottom\"><thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      \n",
       "      <th>category</th>\n",
       "      <th>cat_count</th>\n",
       "      <th>cluster</th>\n",
       "      <th>venue_category_major</th>\n",
       "      <th>venue_category_minor</th>\n",
       "      <th>still_exists</th>\n",
       "      <th>State</th>\n",
       "    </tr>\n",
       "  </thead><tbody><tr><td>Loading... (need <a href=https://mwouts.github.io/itables/troubleshooting.html>help</a>?)</td></tr></tbody><tfoot><th>category</th><th>cat_count</th><th>cluster</th><th>venue_category_major</th><th>venue_category_minor</th><th>still_exists</th><th>State</th></tfoot></table>\n",
       "<link rel=\"stylesheet\" type=\"text/css\" href=\"https://cdn.datatables.net/1.13.1/css/jquery.dataTables.min.css\">\n",
       "<script type=\"module\">\n",
       "    // Import jquery and DataTable\n",
       "    import 'https://code.jquery.com/jquery-3.6.0.min.js';\n",
       "    import dt from 'https://cdn.datatables.net/1.12.1/js/jquery.dataTables.mjs';\n",
       "    dt($);\n",
       "\n",
       "    // Define the table data\n",
       "    const data = [[\"Art Gallery of New South Wales, Sydney, NSW\", 27, 2, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"NSW\"], [\"Artspace, Sydney, NSW\", 8, 5, \"ARI or Indpendent \", \"CAOA\", \"Y\", \"NSW\"], [\"Tandanya National Aboriginal Cultural Institute, Adelaide, SA\", 1, 5, \"Government / Public Museum \", \"National Institution\", \"Y\", \"SA\"], [\"Art Gallery of South Australia, Adelaide, SA\", 7, 2, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"SA\"], [\"National Gallery of Victoria, Melbourne, VIC\", 25, 2, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"VIC\"], [\"National Gallery of Australia, Canberra, ACT\", 10, 2, \"Government / Public Museum \", \"National Institution\", \"Y\", \"ACT\"], [\"Manly Art Gallery & Museum, Manly, Sydney, NSW\", 2, 1, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Queensland Art Gallery, Brisbane, QLD\", 19, 5, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"QLD\"], [\"New England Regional Art Museum, Armidale, NSW\", 1, 5, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Roslyn Oxley9 Gallery, Paddington, Sydney, NSW\", 6, 5, \"Commercial\", \"Commercial\", \"Y\", \"NSW\"], [\"Royal Exhibition Building, Melbourne, VIC\", 2, 5, \"ARI or Indpendent \", \"ARI or Independent\", \"Y\", \"VIC\"], [\"Australian Centre for Contemporary Art, Melbourne, VIC\", 11, 5, \"ARI or Indpendent \", \"CAOA\", \"Y\", \"VIC\"], [\"Orange Regional Gallery, Orange, NSW\", 4, 3, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"S.H. Ervin Gallery, Sydney, NSW\", 4, 5, \"Government / Public Museum \", \"Public Independent\", \"Y\", \"NSW\"], [\"Penrith Regional Gallery, Penrith, NSW\", 1, 4, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Institute of Modern Art, Brisbane, QLD\", 47, 5, \"ARI or Indpendent \", \"CAOA\", \"Y\", \"QLD\"], [\"Griffith University\", 1, 1, \"University Gallery\", \"University Gallery\", \"Y\", \"QLD\"], [\"Art Gallery of Western Australia, Perth, WA\", 24, 5, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"WA\"], [\"RMIT Gallery, Melbourne, VIC\", 1, 5, \"University Gallery\", \"University Gallery\", \"Y\", \"VIC\"], [\"Monash University Museum of Art, Melbourne, VIC\", 7, 3, \"University Gallery\", \"University Gallery\", \"Y\", \"VIC\"], [\"Heide Museum of Modern Art, Melbourne, VIC\", 16, 5, \"Government / Public Museum \", \"Public Independent\", \"Y\", \"VIC\"], [\"Bathurst Regional Art Gallery, Bathurst, NSW\", 1, 1, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Tasmanian Museum and Art Gallery, Hobart, TAS\", 11, 2, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"TAS\"], [\"Ballarat Fine Art Gallery, Ballarat, VIC\", 7, 5, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"VIC\"], [\"Warrnambool Art Gallery, Warrnambool, VIC\", 17, 2, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"VIC\"], [\"State Library of NSW, Sydney, NSW\", 2, 2, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"NSW\"], [\"Shanghai Art Gallery, Shanghai, China\", 8, 2, \"ARI or Indpendent \", \"International\", \"NaN\", \"China\"], [\"Gallery Gabrielle Pizzi, Melbourne, VIC\", 2, 1, \"Commercial\", \"Commercial\", \"Y\", \"VIC\"], [\"Performance Space, Sydney, NSW\", 3, 4, \"ARI or Indpendent \", \"CAOA\", \"Y\", \"NSW\"], [\"Hogarth Gallery, Sydney, NSW\", 4, 4, \"Commercial\", \"Commercial\", \"N\", \"NSW\"], [\"Canberra Contemporary Art Space, Canberra, ACT\", 2, 5, \"ARI or Indpendent \", \"CAOA\", \"Y\", \"ACT\"], [\"Australian Centre for Photography, Sydney, NSW\", 6, 5, \"ARI or Indpendent \", \"ARI or Independent\", \"N\", \"NSW\"], [\"Contemporary Art Centre of South Australia, Adelaide, SA\", 52, 2, \"ARI or Indpendent \", \"CAOA\", \"N\", \"SA\"], [\"Wollongong City Art Gallery, Wollongong, NSW\", 46, 5, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Tin Sheds Gallery, University of Sydney, Sydney, NSW\", 4, 2, \"University Gallery\", \"University Gallery\", \"Y\", \"NSW\"], [\"Coventry Gallery, Sydney, NSW\", 3, 4, \"Commercial\", \"Commercial\", \"N\", \"NSW\"], [\"Macquarie Galleries, Sydney, NSW\", 3, 4, \"Commercial\", \"Commercial\", \"N\", \"NSW\"], [\"Mori Gallery, Sydney, NSW\", 2, 4, \"Commercial\", \"Commercial\", \"N\", \"NSW\"], [\"Albury Regional Art Centre, Albury, NSW\", 1, 5, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Glen Eira City Gallery, Melbourne, Vic.\", 1, 4, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"VIC\"], [\"David Jones Art Gallery, Sydney, NSW\", 1, 4, \"Commercial\", \"Commercial\", \"Y\", \"NSW\"], [\"Museums and Art Galleries of the Northern Territory, Darwin, NT\", 39, 2, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"NT\"], [\"Queen Victoria Museum and Art Gallery, Launceston, TAS\", 26, 5, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"TAS\"], [\"Boomalli Aboriginal Artists Cooperative, Sydney, NSW\", 2, 3, \"Commercial\", \"Commercial\", \"Y\", \"NSW\"], [\"Greenhill Galleries, Perth, WA\", 1, 4, \"Commercial\", \"Commercial\", \"N\", \"WA\"], [\"Experimental Art Foundation, Adelaide, SA\", 75, 1, \"ARI or Indpendent \", \"CAOA\", \"N\", \"SA\"], [\"University of South Australia, Adelaide, SA\", 12, 3, \"University Gallery\", \"University Gallery\", \"Y\", \"SA\"], [\"Christine Abrahams Gallery, Melbourne, VIC\", 2, 4, \"Commercial\", \"Commercial\", \"N\", \"VIC\"], [\"Plimsoll Gallery, University of Tasmania, Hobart, TAS\", 13, 5, \"University Gallery\", \"University Gallery\", \"Y\", \"TAS\"], [\"Blaxland Gallery, Sydney, NSW\", 2, 4, \"Commercial\", \"Commercial\", \"N\", \"NSW\"], [\"Ivan Dougherty Gallery, Sydney, NSW\", 10, 2, \"University Gallery\", \"University Gallery\", \"N\", \"NSW\"], [\"Ian Potter Museum of Art, University of Melbourne, Melbourne, Vic.\", 17, 3, \"University Gallery\", \"University Gallery\", \"Y\", \"VIC\"], [\"John Curtin Gallery, Curtin University, Perth, WA\", 6, 5, \"University Gallery\", \"University Gallery\", \"Y\", \"WA\"], [\"Flinders University Art Museum, Adelaide, SA\", 8, 3, \"University Gallery\", \"University Gallery\", \"Y\", \"SA\"], [\"Newcastle Region Art Gallery, Newcastle, NSW\", 13, 2, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"School of Art, Australian National University, Canberra, ACT\", 9, 3, \"University Gallery\", \"University Gallery\", \"Y\", \"ACT\"], [\"University of Queensland Art Museum, Brisbane, QLD\", 2, 2, \"University Gallery\", \"University Gallery\", \"Y\", \"QLD\"], [\"Drill Hall Gallery, Australian National University, Canberra, ACT\", 1, 5, \"University Gallery\", \"University Gallery\", \"Y\", \"ACT\"], [\"Perth Institute of Contemporary Art, Perth, WA\", 1, 5, \"ARI or Indpendent \", \"CAOA\", \"Y\", \"WA\"], [\"Corner Brisbane and Tamar Streets, Launceston, TAS\", 5, 5, \"Government / Public Museum \", \"State Design Institutite\", \"Y\", \"TAS\"]];\n",
       "\n",
       "    // Define the dt_args\n",
       "    let dt_args = {\"scrollY\": \"400px\", \"scrollCollapse\": true, \"scrollX\": true, \"paging\": false, \"dom\": \"tpr\", \"order\": [], \"initComplete\": function () {\n",
       "    // Apply the search\n",
       "    this.api()\n",
       "        .columns()\n",
       "        .every(function () {\n",
       "            const that = this;\n",
       "\n",
       "            $('input', this.footer()).on('keyup change clear', function () {\n",
       "                if (that.search() !== this.value) {\n",
       "                    that.search(this.value).draw();\n",
       "                }\n",
       "            });\n",
       "        });\n",
       "}\n",
       "};\n",
       "    dt_args[\"data\"] = data;\n",
       "\n",
       "    $(document).ready(function () {\n",
       "        // Setup - add a text input to each header or footer cell\n",
       "$('#29e75257-8a72-40ab-bbe4-6cf9825995c1 tfoot th').each(function () {\n",
       "    let title = $(this).text();\n",
       "    $(this).html('<input type=\"text\" placeholder=\"Search ' +\n",
       "        // We use encodeURI to avoid this LGTM error:\n",
       "        // https://lgtm.com/rules/1511866576920/\n",
       "        encodeURI(title).replaceAll(\"%20\", \" \") +\n",
       "        '\" />');\n",
       "});\n",
       "\n",
       "        $('#29e75257-8a72-40ab-bbe4-6cf9825995c1').DataTable(dt_args);\n",
       "    });\n",
       "</script>\n",
       "</div>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n"
     ]
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1400x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<style>.itables table td {\n",
       "    text-overflow: ellipsis;\n",
       "    overflow: hidden;\n",
       "}\n",
       "\n",
       ".itables table th {\n",
       "    text-overflow: ellipsis;\n",
       "    overflow: hidden;\n",
       "}\n",
       "\n",
       ".itables thead input {\n",
       "    width: 100%;\n",
       "    padding: 3px;\n",
       "    box-sizing: border-box;\n",
       "}\n",
       "\n",
       ".itables tfoot input {\n",
       "    width: 100%;\n",
       "    padding: 3px;\n",
       "    box-sizing: border-box;\n",
       "}\n",
       "</style>\n",
       "<div class=\"itables\">\n",
       "<table id=\"09e61d53-d178-43b8-af77-397f9936fa5b\" class=\"display nowrap\"style=\"table-layout:auto;width:auto;margin:auto;caption-side:bottom\"><thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      \n",
       "      <th>category</th>\n",
       "      <th>cat_count</th>\n",
       "      <th>cluster</th>\n",
       "      <th>venue_category_major</th>\n",
       "      <th>venue_category_minor</th>\n",
       "      <th>still_exists</th>\n",
       "      <th>State</th>\n",
       "    </tr>\n",
       "  </thead><tbody><tr><td>Loading... (need <a href=https://mwouts.github.io/itables/troubleshooting.html>help</a>?)</td></tr></tbody><tfoot><th>category</th><th>cat_count</th><th>cluster</th><th>venue_category_major</th><th>venue_category_minor</th><th>still_exists</th><th>State</th></tfoot></table>\n",
       "<link rel=\"stylesheet\" type=\"text/css\" href=\"https://cdn.datatables.net/1.13.1/css/jquery.dataTables.min.css\">\n",
       "<script type=\"module\">\n",
       "    // Import jquery and DataTable\n",
       "    import 'https://code.jquery.com/jquery-3.6.0.min.js';\n",
       "    import dt from 'https://cdn.datatables.net/1.12.1/js/jquery.dataTables.mjs';\n",
       "    dt($);\n",
       "\n",
       "    // Define the table data\n",
       "    const data = [[\"Art Gallery of New South Wales, Sydney, NSW\", 61, 2, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"NSW\"], [\"Artspace, Sydney, NSW\", 6, 3, \"ARI or Indpendent \", \"CAOA\", \"Y\", \"NSW\"], [\"Art Gallery of South Australia, Adelaide, SA\", 9, 3, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"SA\"], [\"National Gallery of Victoria, Melbourne, VIC\", 28, 4, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"VIC\"], [\"National Gallery of Australia, Canberra, ACT\", 24, 2, \"Government / Public Museum \", \"National Institution\", \"Y\", \"ACT\"], [\"Bendigo Art Gallery, Bendigo, VIC\", 1, 1, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"VIC\"], [\"University of Melbourne, Melbourne, Vic\", 1, 5, \"University Gallery\", \"University Gallery\", \"Y\", \"VIC\"], [\"Manly Art Gallery & Museum, Manly, Sydney, NSW\", 2, 3, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Casula Powerhouse Arts Centre, Casula, NSW\", 2, 5, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Museum of Contemporary Art, Sydney, NSW\", 7, 4, \"Government / Public Museum \", \"Public Independent\", \"Y\", \"NSW\"], [\"Queensland Art Gallery, Brisbane, QLD\", 27, 4, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"QLD\"], [\"Powerhouse Museum, Sydney, NSW\", 1, 5, \"Government / Public Museum \", \"State Design Institutite\", \"Y\", \"NSW\"], [\"New England Regional Art Museum, Armidale, NSW\", 5, 2, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Centre for Contemporary Photography, Melbourne, VIC\", 2, 5, \"ARI or Indpendent \", \"ARI or Independent\", \"Y\", \"VIC\"], [\"Roslyn Oxley9 Gallery, Paddington, Sydney, NSW\", 1, 1, \"Commercial\", \"Commercial\", \"Y\", \"NSW\"], [\"Royal Exhibition Building, Melbourne, VIC\", 2, 5, \"ARI or Indpendent \", \"ARI or Independent\", \"Y\", \"VIC\"], [\"Australian Centre for Contemporary Art, Melbourne, VIC\", 17, 4, \"ARI or Indpendent \", \"CAOA\", \"Y\", \"VIC\"], [\"Orange Regional Gallery, Orange, NSW\", 46, 4, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Campbelltown City Art Gallery, Campbelltown, NSW\", 8, 2, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Mosman Art Gallery, Mosman, NSW\", 1, 3, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"S.H. Ervin Gallery, Sydney, NSW\", 5, 3, \"Government / Public Museum \", \"Public Independent\", \"Y\", \"NSW\"], [\"Penrith Regional Gallery, Penrith, NSW\", 1, 1, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Geelong Art Gallery, Geelong, VIC\", 5, 4, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"VIC\"], [\"Institute of Modern Art, Brisbane, QLD\", 80, 2, \"ARI or Indpendent \", \"CAOA\", \"Y\", \"QLD\"], [\"Griffith University\", 4, 3, \"University Gallery\", \"University Gallery\", \"Y\", \"QLD\"], [\"Art Gallery of Western Australia, Perth, WA\", 36, 2, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"WA\"], [\"Monash University Museum of Art, Melbourne, VIC\", 13, 4, \"University Gallery\", \"University Gallery\", \"Y\", \"VIC\"], [\"Heide Museum of Modern Art, Melbourne, VIC\", 21, 3, \"Government / Public Museum \", \"Public Independent\", \"Y\", \"VIC\"], [\"Bathurst Regional Art Gallery, Bathurst, NSW\", 2, 5, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Tasmanian Museum and Art Gallery, Hobart, TAS\", 5, 3, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"TAS\"], [\"Ballarat Fine Art Gallery, Ballarat, VIC\", 31, 2, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"VIC\"], [\"Warrnambool Art Gallery, Warrnambool, VIC\", 17, 3, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"VIC\"], [\"State Library of NSW, Sydney, NSW\", 4, 2, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"NSW\"], [\"National Art School, Sydney, NSW\", 1, 3, \"University Gallery\", \"University Gallery\", \"Y\", \"NSW\"], [\"Latrobe Regional Gallery, Morwell, VIC\", 1, 3, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"VIC\"], [\"Gallery Gabrielle Pizzi, Melbourne, VIC\", 6, 5, \"Commercial\", \"Commercial\", \"Y\", \"VIC\"], [\"Performance Space, Sydney, NSW\", 3, 5, \"ARI or Indpendent \", \"CAOA\", \"Y\", \"NSW\"], [\"Annandale Galleries, Sydney, NSW\", 3, 1, \"Commercial\", \"Commercial\", \"Y\", \"NSW\"], [\"Blaxland Gallery, Sydney, NSW\", 3, 4, \"Commercial\", \"Commercial\", \"N\", \"NSW\"], [\"Hogarth Gallery, Sydney, NSW\", 6, 1, \"Commercial\", \"Commercial\", \"N\", \"NSW\"], [\"Museums and Art Galleries of the Northern Territory, Darwin, NT\", 18, 2, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"NT\"], [\"Macquarie Galleries, Sydney, NSW\", 4, 5, \"Commercial\", \"Commercial\", \"N\", \"NSW\"], [\"Greenaway Art Gallery, Adelaide, SA\", 4, 5, \"Commercial\", \"Commercial\", \"Y\", \"SA\"], [\"Anna Schwartz Gallery, Melbourne, Vic.\", 3, 5, \"Commercial\", \"Commercial\", \"Y\", \"VIC\"], [\"Ivan Dougherty Gallery, Sydney, NSW\", 22, 2, \"University Gallery\", \"University Gallery\", \"N\", \"NSW\"], [\"Glen Eira City Gallery, Melbourne, Vic.\", 2, 5, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"VIC\"], [\"Wollongong City Art Gallery, Wollongong, NSW\", 53, 3, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Contemporary Art Centre of South Australia, Adelaide, SA\", 47, 2, \"ARI or Indpendent \", \"CAOA\", \"N\", \"SA\"], [\"Ian Potter Museum of Art, University of Melbourne, Melbourne, Vic.\", 21, 4, \"University Gallery\", \"University Gallery\", \"Y\", \"VIC\"], [\"Experimental Art Foundation, Adelaide, SA\", 55, 4, \"ARI or Indpendent \", \"CAOA\", \"N\", \"SA\"], [\"Tin Sheds Gallery, University of Sydney, Sydney, NSW\", 24, 2, \"University Gallery\", \"University Gallery\", \"Y\", \"NSW\"], [\"University of South Australia, Adelaide, SA\", 14, 3, \"University Gallery\", \"University Gallery\", \"Y\", \"SA\"], [\"Newcastle Region Art Gallery, Newcastle, NSW\", 31, 4, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Sherman Galleries, Sydney, NSW\", 2, 5, \"Commercial\", \"Commercial\", \"N\", \"NSW\"], [\"Queen Victoria Museum and Art Gallery, Launceston, TAS\", 15, 3, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"TAS\"], [\"Christine Abrahams Gallery, Melbourne, VIC\", 3, 1, \"Commercial\", \"Commercial\", \"N\", \"VIC\"], [\"Garth Clark Gallery, New York, USA\", 1, 1, \"ARI or Indpendent \", \"International\", \"N\", \"USA\"], [\"Boomalli Aboriginal Artists Cooperative, Sydney, NSW\", 1, 1, \"Commercial\", \"Commercial\", \"Y\", \"NSW\"], [\"Albury Regional Art Centre, Albury, NSW\", 1, 3, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Access Contemporary Art Gallery, Sydney, NSW\", 6, 4, \"Commercial\", \"Commercial\", \"N\", \"NSW\"], [\"Canberra Contemporary Art Space, Canberra, ACT\", 3, 4, \"ARI or Indpendent \", \"CAOA\", \"Y\", \"ACT\"], [\"Coventry Gallery, Sydney, NSW\", 3, 5, \"Commercial\", \"Commercial\", \"N\", \"NSW\"], [\"Stills Gallery, Sydney, NSW\", 3, 1, \"Commercial\", \"Commercial\", \"N\", \"NSW\"], [\"Adelaide Central Gallery, Adelaide, SA\", 1, 1, \"University Gallery\", \"University Gallery\", \"Y\", \"SA\"], [\"Tamworth Regional Gallery, Tamworth, NSW\", 1, 5, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Plimsoll Gallery, University of Tasmania, Hobart, TAS\", 18, 2, \"University Gallery\", \"University Gallery\", \"Y\", \"TAS\"], [\"John Curtin Gallery, Curtin University, Perth, WA\", 10, 3, \"University Gallery\", \"University Gallery\", \"Y\", \"WA\"], [\"Flinders University Art Museum, Adelaide, SA\", 4, 3, \"University Gallery\", \"University Gallery\", \"Y\", \"SA\"], [\"Brisbane City Art Gallery, Brisbane, Qld\", 2, 4, \"Government / Public Museum \", \"City Gallery / Museum\", \"Y\", \"QLD\"], [\"School of Art, Australian National University, Canberra, ACT\", 6, 3, \"University Gallery\", \"University Gallery\", \"Y\", \"ACT\"], [\"Lawrence Wilson Art Gallery, University of Western Australia, Perth, WA\", 6, 4, \"University Gallery\", \"University Gallery\", \"Y\", \"WA\"], [\"University of Queensland Art Museum, Brisbane, QLD\", 3, 3, \"University Gallery\", \"University Gallery\", \"Y\", \"QLD\"], [\"Drill Hall Gallery, Australian National University, Canberra, ACT\", 1, 4, \"University Gallery\", \"University Gallery\", \"Y\", \"ACT\"], [\"Perth Institute of Contemporary Art, Perth, WA\", 2, 4, \"ARI or Indpendent \", \"CAOA\", \"Y\", \"WA\"], [\"Bender's Lane, 144 Charles Street, Launceston, Tasmania\", 6, 2, \"Commercial\", \"Commercial\", \"N\", \"TAS\"], [\"Mary Place Gallery, Paddington, NSW\", 1, 3, \"Commercial\", \"Commercial\", \"Y\", \"NSW\"], [\"Bunbury Regional Art Galleries, Bunbury, WA\", 1, 3, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"WA\"], [\"Corner Brisbane and Tamar Streets, Launceston, TAS\", 4, 2, \"Government / Public Museum \", \"State Design Institutite\", \"Y\", \"TAS\"]];\n",
       "\n",
       "    // Define the dt_args\n",
       "    let dt_args = {\"scrollY\": \"400px\", \"scrollCollapse\": true, \"scrollX\": true, \"paging\": false, \"dom\": \"tpr\", \"order\": [], \"initComplete\": function () {\n",
       "    // Apply the search\n",
       "    this.api()\n",
       "        .columns()\n",
       "        .every(function () {\n",
       "            const that = this;\n",
       "\n",
       "            $('input', this.footer()).on('keyup change clear', function () {\n",
       "                if (that.search() !== this.value) {\n",
       "                    that.search(this.value).draw();\n",
       "                }\n",
       "            });\n",
       "        });\n",
       "}\n",
       "};\n",
       "    dt_args[\"data\"] = data;\n",
       "\n",
       "    $(document).ready(function () {\n",
       "        // Setup - add a text input to each header or footer cell\n",
       "$('#09e61d53-d178-43b8-af77-397f9936fa5b tfoot th').each(function () {\n",
       "    let title = $(this).text();\n",
       "    $(this).html('<input type=\"text\" placeholder=\"Search ' +\n",
       "        // We use encodeURI to avoid this LGTM error:\n",
       "        // https://lgtm.com/rules/1511866576920/\n",
       "        encodeURI(title).replaceAll(\"%20\", \" \") +\n",
       "        '\" />');\n",
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       "\n",
       "        $('#09e61d53-d178-43b8-af77-397f9936fa5b').DataTable(dt_args);\n",
       "    });\n",
       "</script>\n",
       "</div>\n"
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     "output_type": "display_data"
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n"
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Q2AAAAAAAABiGwAYAAAAAAMAwBDYAAAAAAACGIbABAAAAAAAwDIENAAAAAACAYQhsAAAAAAAADENgAwAAAAAAYBgCGwAAAAAAAMPke2ATExMjh8Ph8ggJCcnv1QAAAAAAABRZxQtiobVq1dKKFSucz4sVK1YQqwEAAAAAACiSCiSwKV68OL1qAAAAAAAArlCBXMNmz549CgsLU8WKFfXggw/qzz//zLZsSkqKkpKSXB4AAAAAAAA3snwPbG6//XbNnj1by5Yt0wcffKD4+Hg1btxYJ06cyLL8+PHj5e/v73yEh4fnd5UAAAAAAACuK/ke2LRp00ZdunRR7dq1dffdd2vJkiWSpFmzZmVZfujQoUpMTHQ+Dhw4kN9VAgAAAAAAuK4UyDVsLubt7a3atWtrz549Wc739PSUp6dnQVcDAAAAAADgulEg17C5WEpKin755ReFhoYW9KoAAAAAAACKhHwPbAYPHqw1a9Zo7969+uGHH9S1a1clJSWpT58++b0qAAAAAACAIinfh0QdPHhQ3bt3119//aWgoCA1bNhQGzZsUGRkZH6vCgAAAAAAoEjK98Bm/vz5+b1IAAAAAACAG0qBX8MGAAAAAAAAeUNgAwAAAAAAYBgCGxgtLi5ODodDCQkJWc5fu3atypcv73weHR2tKVOmZLu8WrVqafHixdnOHzdunLp3736l1QUAAEAOLrcvBqDwTZkyRdHR0YVdDagArmEDXEt33nmnDh48mOvyO3fudP49c+ZMTZkyRdu2bXNOGzZsWH5WDwAAABe5eF8MAJAzetgAAAAY4Ny5c7Isq7CrAQAADEFgg3xTo1oVTZw4UQ0bNpSvr6+aNWumAwcOSJKOHTumnj17KiwsTGFhYRo0aJBSUlIkSffff7969erlXM6kSZNUq1YtnTlzxjntyy+/VJUqVRQQEKC+ffsqLS1NkrR69WoFBAS41OPQoUOKjo6Wr6+vGjVqpF9++cU5r0KFClq0aJG2bt2qJ554Qtu3b5ePj498fHy0f/9+xcTEqFOnTs7yv//+u1q3bq3AwEBVrlzZZbjVzJkzdcstt2jMmDEqW7asgoODcxyOBVytCtVqavz48apfv768vb3Vpk0b/f333+rfv78CAgJUtWpVrVu3zi77/7/rGRYtWqQKFSo4n0+ePFkRERHy9fVVhQoV9OGHHzrnrVixQg0aNFBAQIBq1aqlL774wjnv0mGH27Ztk8PhcJk/ZMgQ3XXXXfL29lbDhg116NAhxcTEKCgoSOXLl9fChQvz/8MB8kGFajWz3I5ZlqUhQ4YoJCREfn5+qlatmnNIh2VZev3111W5cmUFBgbqnnvu0Z9//ulcpsPhcOnJeWk3c4fDoalTpyoqKkpeXl5KTk7Wnj171LFjRwUFBSkwMFCdO3d2lv/jjz/UoUMHBQUFKTIyUmPHjtX58+cL/LMB8svF26dPPvlENWrUUEBAgJo0aaKtW7c6y82dO1dRUVHy9fVVRESERowY4RJoOhwOvfvuu4qKipKfn586duyoxMTEa/12AONcuo/3wQcfKDg4WGvWrHEpd9NNN+k///mPJLvnW8a2r3nz5jp8+LBL2cu1t+y2TWlpaZddN3JGYIN8NXv2bMXGxur48ePy9vZ2blw7duyokJAQ/f7779q+fbt++uknjR07VpL0wQcfaO3atZo9e7Y2bdqksWPHav78+SpZsqRzuUuWLNGWLVu0a9curVixQnPnzs22Dh999JHGjx+vEydOqEWLFrr33nuVnp7uUubWW2/Vu+++q9q1ays5OVnJycmKiIhwKZOenq727dvr5ptv1uHDh7Vw4UJNnDhRsbGxzjI7d+5UiRIldOjQIS1YsECDBw/WH3/8kR8fJZClefPm6dNPP9WhQ4e0f/9+NWjQQC1atNCJEyf04IMP6oknnrjsMn777Te9/PLLWr58uU6ePKkffvhBDRo0kCT9/PPPuv/++zVhwgT9/fffeu+999S7d2/t3r0713WcO3eu3nzzTZ04cULe3t6688475e/vryNHjmjkyJF69NFHnaErYJqstmPffPONYmNjtWXLFiUlJWnFihWqVq2aJGnOnDmaPHmyFi1apMOHD6tWrVpq3759pu1OTmJjY7V8+XIlJSXJzc1Nd999t6KiohQXF6f4+HgNHDhQknTmzBndddddatGihQ4dOqS1a9dq/vz5mjFjRoF8FkBBWrt2rZ588km99957On78uLp27arWrVs7DwIDAwP12WefKSkpSV988YXef/99l30wSVqwYIG+/fZb7d+/XwcPHtQbb7xRGG8FMMZvv+3JtI93++23q3fv3i7bivXr1+vYsWPO46SOHTvqrrvu0okTJzRu3DiXE3kZsmtvOW2b3N3dc1w3Lo/ABvlqwIABqlSpkkqUKKGePXtq8+bN2rRpk/bs2aNJkybJy8tLpUuX1rBhw5wb3YCAAM2dO1fPPPOMHnjgAY0bN061a9d2WW5MTIz8/PwUFhamNm3aaPPmzdnW4cEHH1SjRo3k4eGhmJgYHT16VBs2bMjze/nhhx905MgRjR07ViVKlFCdOnU0YMAAzZw501mmdOnSeuGFF+Tu7q7o6GhVrFjR5UwqkN/69++viIgIBQQEqF27dipTpoy6du2qYsWKqXv37tqxY4dSU1NzXEaxYsVkWZZ27typM2fOKDg4WHXq1JEkvffee+rbt69atGghNzc3NWnSRO3bt8/TWZBevXopKipKJUqUUJcuXXTmzBk9++yzKl68uHr27KkTJ05o3759V/U5AAUlq+2Yu7u7zp49q507dyotLU0REREugc3TTz+t2rVrq0SJEho3bpwOHjyoH3/8MdfrfPHFFxUWFiZPT08tXrxY7u7uevXVV+Xt7S0PDw81b95ckrR48WKVKlVKzz77rDw8PBQREaFnnnkm00EscD2YPXu2evXqpaZNm8rd3V2DBg1SqVKltGTJEklSmzZtVK1aNTkcDt1yyy3q3r27Vq9e7bKMIUOGKDg4WAEBAerSpUuO+4fAjSC7fbx+/frp008/VXJysiR7pECPHj3k6emp9evX66+//lJMTIw8PDzUqFEjdevWLdOys2tvl9s25bRuXB6BDfJVSEiI829vb2+dPHlScXFxSkhIUGBgoAICAhQQEKCuXbvq6NGjzrJ33HGHKlWqpKSkJP3rX//K1XKzExkZ6fzb3d1doaGhOnToUJ7fy8GDBxUWFiYPDw/ntEqVKrlc5PjieuWmbsDVuvg75+Xllem5ZVk6ffp0jsuoXLmyZs2apalTpyo4OFitWrVyBo1xcXF69913nW01ICBAn3/+eaausXmpY3BwsMtzSc6NNmCarLY3zZs316hRozRixAiVKVNGXbp00d69eyXZ24qLhxt6enoqLCwsTxfEv7iH5759+1S5cmWXoYYZ4uLitGPHDpf2+fzzzys+Pv4K3ilQuC5tO5JUsWJFZ9tZtmyZGjdurDJlysjf31/vvvuu/vrrL5fyedk/BG4ElStXynIfr0aNGoqKitJ///tfnT17Vv/5z3/08MMPS5IOHz6ssLAwubu7O5dz8fFUhuza2+W2TTmtG5dHYIMCFx4errJlyyohIcH5SExMdDlge/3115WSkqIaNWpc9Z2aLj5zn5aWpiNHjqhcuXKZyrm55fz1L1++vA4fPuwydGPv3r0utxEHTOXj4+MS3Bw5csRl/gMPPKBVq1bp6NGjuvnmm9W7d29Jdnt95plnXNprcnKypk+fnqvlAkVV//79tWHDBu3fv1+enp56+umnJdnbiri4OGe51NRUHT582Lmt8Pb2vmybuXh7FBkZqT/++CPLiw+Hh4erXr16Lu0zKSmJu+7gunRp25HsA7/y5csrNTVVnTt31uOPP65Dhw4pMTFRTzzxBBflBnIhu328fv36aebMmVq4cKEiIiJUr149SVJYWFimY579+/fnen252TZlt25cHoENClz9+vUVERGhl19+WSdPnpRlWdq3b5+WLl0qSdq8ebPGjBmjefPmKTY2VrNmzdKyZcuueH0LFizQDz/8oNTUVI0ePVpBQUFq2LBhpnLBwcE6cuSIy8WNL9agQQMFBwfrlVdeUUpKinbs2KGpU6eqT58+V1w34FqpW7eu5s2bp7Nnz+rPP//UtGnTnPN2796tb775RmfOnJGHh4d8fHxUvHhxSdLjjz+uGTNmaNWqVTp37pxSUlK0fv1658W769atq88++0yJiYk6duyYJk6cWCjvD7iWNm7cqHXr1ik1NVUlS5aUt7e3s8306tVLU6dO1a5du5SSkqKXX35Z5cqVc14Xqm7dupozZ47S09O1bds2zZkzJ8d1tWvXTikpKXrllVd06tQppaamatWqVZKk9u3b6+jRo3rnnXd09uxZnTt3Trt37840TAS4HvTq1Utz587V999/r/T0dL399ts6ceKE2rZtq5SUFJ09e1alS5eWp6enfvjhB4b+Abmwe/dv2e7jdevWTVu2bNGECRNcerg0bNhQpUuX1pgxY5SamqoffvhBCxYsyPU6c7Ntym7duDwCGxS4YsWK6csvv9ShQ4dUo0YN+fv7q127dvr999+VnJys7t2769VXX1Xt2rUVHh6u999/X3369NGxY8euaH2PPPKIhgwZosDAQH3zzTdatGiR84fqYi1atFDDhg1Vrlw5BQQEZEqS3d3dtXjxYm3evFkhISHq2LGjnnvuOfXo0eOK6gVcS2PHjlVCQoKCgoLUo0cPPfTQQ855qampGjFihIKDg1W6dGmtXLnSeW2mW2+9VfPmzdPLL7+soKAglStXTiNGjHDe1e3ZZ59VaGiowsPD1aJFiyzHOANFTVJSkvr376/SpUsrJCREhw8f1ptvvilJeuihhzRw4EC1b99eISEh+umnn/Tll186tztvv/221q9fr4CAAA0ZMuSyob+Pj49WrFihzZs3KyIiQqGhoc7ANWPet99+qwoVKqh06dLq0aMHQ6JwXWrWrJnefvtt9evXT6VLl9b8+fO1dOlSBQQEyNfXV9OmTdNjjz0mPz8/vfrqq2xvgFxITct+H8/X11ddu3bVL7/8op49ezpf4+7urs8//1zLli1TYGCgXnrpJT3yyCO5Xmdutk3ZrRuX57AM61uYlJQkf39/JSYmys/Pr7Crg8s4nZqumq/YvWF2jW4tL4/MwQiAq5B6ShoXZv897LDk4V249QGKGtoYULAuaWPhlW/Se++9p7Zt2xZuvYCiIg/bsdGjR2vbtm367LPPrlHlzFi3afKSeXB0DQAAAKDAHT16VMeOHVOlSpUKuyrADef48eP64IMPXG6xfSOs+3rHkCgAAAAABWrFn+m6qU499e/fXzfddFNhVwe4obz66quqUKGC2rVrp7vvvvuGWXdRQA8bAAAAAAXq7krF9c/Rgww7BArB8OHDNXz48Btu3UUBPWwAAAAAAAAMQ2CDa8LHx0fbt2+/bDmHw6Ft27YVfIWAImTcuHHq3r37NVvf3Llz1bhx42u2PgBSdHS0pkyZUtjVAK5KhWo1tWjRosKuBgCDBAQEuNwCHK4YEoVrIjk5ubCrABRZw4YNy3VZh8OhrVu36pZbbrni9fXs2ZNbMgIAANzA4uLiVLFiRf3zzz8KCAgo7OoUWfSwAQDkWnp6emFXAQBwA8tqO8S2Cchf586dk2VZhV0NiMAG+ahGtSqaOHGiGjZsKF9fXzVr1kwHDhyQ5DrUacuWLWrYsKH8/PxUpkwZdejQwWU5a9asUfXq1RUQEKBu3bopMTFRkp3iOhwOzZkzR1WqVFFAQID69u2rtLS0a/o+gcIweX2KWrRu6zJtwYIFuummmxQTE6NOnTo5p8fHx6tXr14KCwtTQECAmjZtqjNnzqhBgwaSpMaNG8vHx0fjxo2TJG3atEl33HGHAgICVLNmTc2bN8+5rJiYGLVv315PPvmkAgMDNWTIEM2cOdOlh87kyZNVtWpV+fr6qnLlypo6dWrBfRBAAcvu+3y5bdDq1asVEBCgDz/8UOHh4SpdurRefPFF53IvbaeSazfwrVu3qkmTJgoMDFRQUJC6d++uEydOXJP3DBSGo0ePqm7dunrxxRf1xx9/qEOHDgoKClJkZKTGjh2r8+fPS5JzmzNy5EiFhISoW7duWW6bANiSkpI0YMAARUREyM/PT/Xr19eBAwcyXXpiypQpio6Odj53OByaOnWqoqKi5OXlpeTk5Bz38TL2K8uXLy8fHx/NnTtXkn2s17x5cwUGBqpKlSr64IMPnK85f/68RowYoeDgYIWFhWnatGkF+2EUAQQ2yFezZ89WbGysjh8/Lm9vb40YMSJTmQEDBqhDhw5KSEjQoUOH9MILL7jMnzNnjlatWqW4uDj9888/GjRokMv8JUuWaMuWLdq1a5dWrFjh/HEAirKetd313ffrnSGoZLeV3r17u5Q7f/68OnbsqOLFi2vnzp3666+/NG7cOLm5uenHH3+UJK1bt07JyckaNmyYEhISdM899+jBBx/U8ePHNX36dD366KP6/vvvncv8+uuvdfvtt+vYsWMaM2ZMprpFRkZq5cqVSkpK0ocffqgXXnjB5fXA9eRy3+ectkEnT57U9u3btWfPHn333XeaNm1arsflu7m5acKECTp69Kh27NihQ4cO6aWXXsrvtwcY4ffff1eTJk3Uu3dvjRo1SnfddZdatGihQ4cOae3atZo/f75mzJjhLL9jxw4VL15c+/fv15w5cyRdftsE3Kj69u2r33//XRs2bFBCQoLef/99lSxZMlevjY2N1fLly5WUlCRvb+8ct4kZ+5UHDx5UcnKyevbsqfj4eLVs2VJPPvmkjh8/rkWLFmnkyJH69ttvJdkB7MyZM7VmzRr9/vvv2rRpk06ePFkwH0QRQWCDfDVgwABVqlRJJUqUUM+ePbV58+ZMZdzd3bVv3z4dPnxYnp6eatq0qcv8F1980dkzYMyYMYqNjXWeZZHss5R+fn4KCwtTmzZtslwHUNQE+7jp7hbNnQeHx48f1zfffKNevXq5lNu4caN27dql6dOnq1SpUipevLiaNGkiT0/PLJe7ZMkSBQUFaeDAgXJ3d1ezZs3Uo0cPzZo1y1kmKipKffv2VfHixeXl5ZVpGV26dFF4eLgcDoeaN2+u1q1bc/E4XLcu933OaRtkWZbGjx+vEiVKqEaNGmrcuHGut1E333yzmjRpInd3dwUHB+u5556jHaFI2rx5s6KjozVq1Cg9++yzWrx4sUqVKqVnn31WHh4eioiI0DPPPKPY2Fjna/z9/TV8+HB5eHg4t0OX2zYBN6KjR49q4cKFev/99xUWFiY3NzfdeuutKlOmTK5en3Ec5unpKTc3tzzv482ZM0dNmzbVAw88oGLFiikqKkoPP/ywsz3PnTtXAwcO1E033SQvLy9NmDDB5TgPmRHYIF+FhIQ4//b29s4yMf3444919uxZ1atXTzfddFOm4RORkZEuf6empur48eN5WgdQFD3Uq7vzzGJsbKwaN27s0l4kad++fSpXrlyuz6QcPHhQFSpUcJlWqVIlHTx40Pk8IiIix2XMnTtXdevWValSpRQQEKCvvvpKf/31V67WD5jmct/nnLZBfn5+LgeOedlG/f7777r33nsVFhYmPz8/9erVi3aEIumDDz5Q5cqV9cADD0iyhxvu2LFDAQEBzsfzzz+v+Ph452vKlSsnNzfXw5bLbZuAG9G+/Qfk6el5xe3j0tfldR8vLi5OX331lUt7fuutt3TkyBFJ0uHDh132XYODg7M9qQgbgQ2uucqVK2v27NmKj4/Xhx9+qMGDB7ucgdy3b5/z7/3798vDw0NBQUGFUVXAKPd2aK+DBw9q8+bNWQ6HkuyQ89ChQzpz5kyWy3A4HC7Py5cvr7i4OJdpe/fuVfny5Z3PL91Jvtj+/fvVp08fTZw4UcePH1dCQoLatm3LhepwXdq//0CBfZ99fHx0+vRp5/PTp08rKSnJ+fyJJ55QuXLltGvXLiUlJemTTz6hHaFImjJlikqWLKn7779faWlpCg8PV7169ZSQkOB8JCUlaefOnc7XZLUdymnbBNyoIiPClZKS4jKEPoO3t7fLdigjRLnYxe3qcvt4WbXB8PBw3XfffS7t+eTJk/rqq68kSWFhYS7HeseOHVNKSsqVv+EbAL90uOZmz56to0ePyuFwqFSpUnJzc1Px4hfuMD9p0iQdPnxYCQkJeuWVV/Tggw+yUQYklSxZUl27dtXw4cO1a9cude3aNVOZ+vXrq3r16nrqqaeUkJCg9PR0fffdd86NYXBwsP744w9n+bZt2+rYsWN65513lJ6errVr1yo2NlYPPfRQruqUnJwsy7JUtmxZubm56auvvtLy5cvz5w0D11jyqYL7PtetW1fr16/Xr7/+qrNnz2ro0KEuAWpSUpJ8fX3l5+enAwcOaNKkSfmyXsA0JUqU0Oeff66UlBR16dJFbdu21dGjR/XOO+/o7NmzOnfunHbv3s2QQOAKBAcH695779UTTzyhI0eO6Pz589q6datOnDihunXras6cOUpPT9e2bducvbazc7l9vKCgILm5ubnsV/bu3VsrV67Up59+qrS0NKWlpWnbtm3auHGjJKl79+6aNm2adu/erTNnzmjo0KEc510Gnw6uuRUrVujmm2+Wj4+POnbsqEmTJunmm292zu/Vq5eaN2+uyMhI+fr66s033yzE2gJmeeihh7Rs2TJ16tRJfn5+mea7ubnpyy+/1OnTp1W9enWVKVNGL7/8snN88JgxY/T000+rVKlSmjBhgkqVKqWlS5fqk08+UenSpfXYY49p+vTpatKkSa7qU7NmTQ0fPlwtWrRQ6dKltWDBAnXs2DFf3zNwrdSsUaPAvs8tWrTQ448/rsaNG6tKlSqqXbu2fH19nfMnT56sxYsXy8/PT/fee6+6dOmSL+sFTOTp6alFixbJsix1795dX3/9tb799ltVqFBBpUuXVo8ePVyGRAHIvVmzZik8PFy33XabAgIC9MQTT+jMmTN6++23tX79egUEBGjIkCHq06dPjsu53D5eyZIlNXLkSLVp00YBAQGKjY1VuXLltGzZMr333nsKDQ1VcHCwnnrqKWeP0kceeUS9evXSnXfeqUqVKunWW2912RYiM4dlWH/bpKQk+fv7KzExMcuDEZjldGq6ar6yTJK0a3RreXkUv8wrAORJ6ilpXJj997DDkod34dYHKGpoY0DBoo0BBYs2dt3JS+ZBDxsAAAAAAADDENgAAAAAAAAYhsAGAAAAAADAMAQ2AAAAAAAAhiGwAQAAAGCcWrVqafHixYVdDQAoNAQ2AAAABujbt68GDRpU2NUAjLFz5061b9++sKsB3PBmzpypW265pbCrcUMisAEAALiEZVk6d+7cNVtfenr6NVsXYLpz587JsqzCrgaA69SVbFNN3Q4T2CBfTZ48WVWrVpWvr68qV66sqVOnSpJWr16tgIAAl7KdOnVSTEzMta8kcB07ePCgWrVqJT8/P9WrV0/jxo1ThQoVJEkOh0Pbtm1zlp0yZYqio6Odz48dO6aePXsqLCxMYWFhGjRokFJSUpzzt2zZoubNmyswMFBVqlTRBx984JwXExOjDh06aMCAAQoICFBERIQWLFhQ0G8XuKYqVKup8ePHq2HDhvLy8tJ3332XbZvJ2K69/fbbCg0NVUhIiEaOHOlykPnJJ5+oRo0aCggIUJMmTbR161bnvOjoaL344otq1aqVvL29NW3aNM2dO1fvvPOOfHx8VKtWrWv+/oGCVqFaTb366quqW7eu/Pz81Lp1ax0+fFiSvQ2bOnWqoqKi5OXlpeTkZFWoUEGLFi2SJNWrV08+Pj7OR7FixZz7kcnJyRowYIAiIiJUtmxZPfTQQ0pMTCykdwkUrqSkJGd78PPzU/369XXgwAEdPXpUDzzwgIKCghQREaHhw4c7Q4qMbdqHH36o8PBwlS5dWi+++KIkaevWrXriiSe0fft2Z/vbv3+/JGn+/PmqU6eOAgICVL9+fa1bt85Zj+joaA0ZMkR33XWXvP8fe/cdFdW1Pnz8O3RhgKEJ0mPvNfHaRaLX2DXGip0U9RpjiTG2aBJjy9XExFhijFjAkvjTG1us4LWkWWOLlSJgQRRhkM5+//D1XEdAMaKgPp+1WMs5Z5+99xnZ8xye2fscOzsaNGhAXFwcU6ZMwc3NDW9vb9avX6+VHzBgAIMGDaJLly7o9Xpq1qzJvn37tP0pKSm8/fbblClThjJlyjB48GBSU1MBiIqKQqfTsXTpUsqXL4+XlxcAH3zwAX5+ftjb21O1alV++OEHrb6757xgwQJ8fX1p2LAhXbp04eOPPzZ5P9955x2GDh1alP9Fj0QSNqJI+fn5sXv3bpKTk/nuu+8YM2YM+/fvL+5uCfHc6N27N2XKlOHKlSuEhoaaJFUeRClFx44d8fDw4Pz58xw/fpxjx44xdepUAK5cuUKrVq0YMmQICQkJbNiwgcmTJ7Nr1y6tjm3bttG4cWMSExOZOnUqb775JikpKU/kPIUoLiEhISxbtgyj0cjIkSMLHDNw5+Lx8OHDXLhwgYiICL7//nuWL18OwN69exkyZAiLFi0iISGBN954g9atW5v8ERkSEsLUqVMxGo28/fbbBAUFMXToUIxGIydPnnzq5y7E0/Ddd98RFhbGlStX8PDwICgoSNsXFhbG9u3bSU5Oxs7OzuS4Q4cOYTQaMRqNbNy4EUdHR7p06QLAoEGDuHHjBn/++SeRkZFkZWUxbNiwp3peQpQUAwYM4Pz58/z6668kJSXx7bffUqpUKXr37o2lpSWRkZHs3buXDRs2MGvWLO24lJQUjh8/zrlz59i3bx/ffPMNERER1KlTh4ULF1KjRg1tDPr6+rJlyxbef/99QkJCuHHjBuPGjaNDhw4kJiZqdYaGhjJ37lwSExOxs7OjadOmODo6cvnyZSZPnsxbb71FVlaWSflBgwaRlJTE0KFD6dixI0lJSQC89957nD9/nhMnTnD8+HH++usvRo4caXLuP/30EwcPHiQyMhKAWrVq8ccff5CUlMRHH31E3759tX13z/nYsWP89ddf7Nmzh+DgYJYtW6Z9+ZKens7atWsZOHBgkf8/FZoqYW7duqUAdevWreLuiiiE1Iws5Td2k/Ibu0mlZmTl2d+pUyc1depUFR4erhwdHfPsmzx58tPpqBDPqgyjUpMdlJrsoGLO/6UAdfXqVW33jBkzlJ+fn1JKKUAdOXJE2/fFF1+o5s2bK6WU+v3335Wzs7PKycnR9m/fvl2VLVtWKaXUrFmzVOfOnU2aHj9+vBo0aJBSSqnJkyerf/zjH9q+3NxcZWVlpQ4ePFiUZyvE03fPGPPz81VffPGFUurhYyY8PDzf8fjqq68qpZR688031eDBg02aqlixogoNDVVKKdW8eXP13nvvmezv379/nm1CPPPuG2MzZ87Udl25ckUB6tKlSwpQ69evNznUz88vz7a//vpLubq6qo0bNyqllLp27ZoyMzNTiYmJWpmzZ88qS0tLlZ2d/cROS4gS454xdiXmggJUdHS0SZHY2FgFqMuXL2vbQkNDVYUKFZRSd2KaTqdTqamp2v6WLVuqf//730oppZYuXapq1aplUmfbtm3Vl19+abKtUaNGavny5UqpO3Fu7Nix2r5vvvlGeXh4aK9TU1MVoM6dO6eUuhMD27RpY1Jf5cqV1YoVK1ROTo6ytrZWv/76q7Zv//79ytraWuXk5KjIyMg818H5qVWrllq5cqV2zoC6efOmtj87O1t5enqq8PBwpZRSYWFhqlq1ag+s8+94lJyHRfGkicTzKjQ0lNmzZxMZGYlSitu3b/PSSy8Vd7eEeC7EX76MjY0NpUuX1rb5+fkV6tioqCiSkpJwdnbWtql77tERFRXFli1bTJYu5uTk0LRpU+21h4eH9m+dTkepUqVkho147vj6+gIPHzNAvuMxLi4OuLN88d4liQAvvfQSsbGxedoS4kVyb9xyd3fH2tpaGzcPGxOJiYm0b9+eiRMnajcjjoqKIjc3l7Jly5qUNTMz48qVK9rSCCFeBNExl7C2ts4zlmJjY7GxsTG5litbtqxJTHJwcMDW1lZ7bWdn98DrvKioKMaPH8/kyZO1bVlZWdp4BtNrR1tbW9zd3U1ew50ljXfdf117N64mJCSQkZGh3Qbgbv8zMjK4fv26tu3+8/7iiy/47rvviI2NRafTYTQaTcrb29ubXPuam5vTr18/QkJCCAgIICQkpHhn1wCSsBFF5lJMDP379+fnn38mICAACwsLOnfujFIKvV5PWloaSil0Oh0Aly9flruNC/EIPMuUIT09nWvXrml/JN5dQwx3Auvt27e115cvX9b+7ePjQ+nSpU223cvHx4cuXbqwevXqJ9R7IZ4NZmZ3Vos/bMwA+Y7Hu38cent7ExUVZVI+KioKb2/vPG0V9FqI51F0dLT272vXrpGRkaGNmweNgczMTLp06cI///lP3nvvPW27j48PZmZmxMfHm/yxKcSLyM/Xh4yMDC5duoSPj4+23dvbm/T0dK5evaolTSIjI01i0oPkNzZ9fHx49913GTx4cNF0HtPPB/hfXHVzc8PKyoqoqCiT/ltbW+Pq6qpdD9/bz3379jFlyhR2795NnTp1MDMzo3bt2ib3msvvvAYNGkTdunUZN24ce/bsYcWKFUV2fn+HXBmIImNMNaKUonTp0piZmbFlyxa2b98OQMWKFbG0tCQsLIycnBxWr15tcvNFIcTD+fh407hxYz788EPS0tI4c+YMixYt0vbXrVuXFStWkJ2dzdGjR00CzCuvvIKvry8TJ04kJSUFpRTR0dFs3boVgL59+7J7927WrVtHVlYWWVlZHD16lD/++OOpn6cQJcHDxgzcudAbN26cNh6/+eYb7X4cffr0ITQ0lP3795Odnc3XX39NYmIibdu2LbBNd3d3Ll68+MTPTYjitGjRIs6cOUNaWhpjx46lWbNmhfqjMTg4GDs7O7766iuT7R4eHnTu3Jlhw4Zp35xfuXLF5GamQrwo3N3d6dSpE4MHD+by5cvk5uZy5MgRbGxsaNGiBe+//z6pqanExMQwbdo0+vfvX+h6L1++TFpamrZt2LBhfP755xw6dEhbWbFz506TWTuPavfu3WzevJns7GwWL17M5cuXadeuHWZmZvTu3ZsJEyZw48YNEhMTmTBhAn379i0w0ZucnIyFhQVubm7k5uby/fffc+LEiYf2oUKFCtStW5cePXrw2muvmcykLQ6SsBFFpkqVqkyYMIHAwEBcXFxYs2YNHTt2BO5MsVu8eDEffvghLi4u7Nu3j9atWxdzj4V49oSFhXHp0iVKly5N7969GTRokLbv66+/5pdffsFgMDB27FiTIGxubs7GjRuJi4ujSpUqODo60q5dO86fPw+Al5cX27ZtY9GiRZQpUwZ3d3f+9a9/kZyc/NTPUYiS4GFjBu5Mpa5duzZly5alWbNm9OvXTxt3zZs35+uvvyY4OBgXFxdWr17N1q1b8zwx8V5vvvkmcXFxODk5UbNmzSd9ikIUi0GDBtGrVy/c3d2Ji4sjNDS0UMetXLmSiIgIHB0dtSfVTJs2DbhzA++7T6lxcHCgadOmHDp06EmehhAl1rJly/Dx8eHll1/GYDAwePBg0tLSCAsLIy0tDT8/Pxo3bky7du20J0E9TGBgIA0aNMDLywuDwUBMTAzt27dnxowZvPXWWzg5OfHSSy8xd+5ccnNz/3bfe/fuzeLFizEYDHz11Vf85z//wcnJCYC5c+fi7+9P1apVqVatGuXLl2fOnDkF1vXaa6/RtWtXatSogaenJydPnqRx48aF6kdwcDDHjh0r9uVQADp175ygEiA5ORlHR0du3bqFg4NDcXdHPMTtzGyqfrQNgFOftMbWSlbZCVGkMlNhmuedf4+PByvTp2Zs2LCBESNG5Fl6IYQopIeMsYJERETQuXNn7ekVQogC3DPG/EMMfPnlXDp37ly8fRLiefI341hJM2DAAAwGA19++WVxd4X//ve/dOvWjdjYWCwtLYu8/kfJecgMGyGEEEIIIYQQQrzwMjMzmT17Nm+99dYTSdY8KknYCCGEEEIIIYQQ4oW2Z88enJycuH79OmPGjCnu7gDylCghhHimde7cWaaWC1EMAgICZDmUEI8o6uypZ3a5hhDiyQoJCSnuLtC8eXNSU1OLuxsmZIaNEEIIIYQQQgghRAkjCRshhHhG+FesyoYNG/Ldp9frOX78+NPtkBDioaKiotDpdAXOxtm7d6/JI40DAgIeeMPFatWqsWnTpgL3T5s2jV69ev3d7grx3AgNDaVRo0bF3Q0hSoyHxSNRMknCRgghngNGo5EaNWo8tJxOp+Po0aNPvkNCiEJp2rQpsbGxhS5/8uRJ2rdvD9yZPl67dm2T/ePHj2fVqlVF2UUhSryIiAgMBoPJtqCgIA4cOFA8HRJCiCIiCRvx3MjJyaGEPaVeiOdOdnZ2cXdBCCGEEEKIF4IkbESRqVKxPLNmzaJBgwbY29vTvHlzLl26hFKKsWPH4uHhgYODAxUrVtSmcyulmD17NuXKlcPZ2ZnXXnuNixcvanXePxvgyy+/JCAgwGT/vHnzqF69Ora2thiNRs6dO0fHjh1xc3PD2dmZ119/XSt/4cIFOnTogJubG35+fkydOpXc3Nwn/t4IUVTOnj2bZ4yB6Vg5fPgwDRo0wMHBAVdXVzp06ABA/fr1AWjUqBF6vZ5p06YBcPDgQRo3bozBYKBq1aom385PmTKF9u3bM2TIEJydnRk7dizu7u7s2bPHpF+VK1dm7dq1T/r0hXii/CtWzTeOAVy7do2goCA8PT3x9PRkxIgRZGRkANCtWzf69Omj1fP5559TrVo10tLStG0bN26kfPnyGAwGBgwYQFZWFpD/zIC4uDgCAgKwt7enYcOGnD59+n999Pdnw4YNHDlyhMGDB3P8+HH0ej16vZ6YmBimTJliciPy8+fP07p1a5ydnSlXrpzJcqu7M3Q+/fRTSpcujbu7+wOXYwlRFObMmUOFChWwt7enXLlyzJs3D8h/LHTu3JkpU6Zorw8dOkRgYCDOzs64ubnx7rvvkpiYSJs2bbh165Y2Fvbu3ZtnBtrVq1fp3r07bm5u+Pr6MmHCBO1LiLttf/fdd/j4+ODi4sIHH3zwpN8KIZ6IgsbY/Xbs2EHNmjWxt7fH3d2dIUOGaPsedG0oni5J2IgitXz5csLCwkhISMDOzo5JkyaxY8cOwsLCOHz4MMnJyezcuZOKFSsCsGLFCubMmcOGDRuIj4+nWrVqtG/f/pG+xQ8LC2P79u0kJydjZmZGy5YtqV69OlFRUVy5coV3330XgLS0NF599VUCAwOJi4tj7969rF69mqVLlz6R90KIJyG/MXa/YcOG0aFDB5KSkoiLi9MeS/j7778DcODAAYxGI+PHjycpKYnXXnuNnj17kpCQwIIFC3jrrbfYv3+/Vt/PP//MP/7xD65du8ann35K3759TcbNL7/8wrVr1+jUqdMTPnshnrz8xphSio4dO+Lh4cH58+c5fvw4x44dY+rUqQAsXryYvXv3snz5cg4ePMjUqVNZvXo1pUqV0urdvHkzhw8f5tSpU+zcuZPQ0NAC+7BkyRKmT59OYmIigYGBdOrUKU9crFOnDgsXLqRGjRoYjUaMRiO+vr4mZbKzs2nfvj21atUiPj6e9evXM2vWLMLCwrQyJ0+exMbGhri4ONasWcP777/PhQsXiuKtFCJffn5+7N69m+TkZL777jvGjBljEnMKEhcXR2BgIG+88Qbx8fFER0fTvXt3XFxc2Lp1K46OjtpYaNq0aZ7je/fujaWlJZGRkezdu5cNGzYwa9YsbX9KSgrHjx/n3Llz7Nu3j2+++YaIiIiiPHUhnorCjrH+/fszZswYUlJSuHjxIn379gUo1LWheHokYSOK1LBhwyhbtiw2NjYEBQVx6NAhLC0tSU9P5+TJk2RlZeHr62uSsBk+fDg1atTAxsaGadOmERsbq/1hWRgffPABnp6eWFtbs2nTJiwtLfnss8+ws7PDysqKFi1aALBp0yacnJwYOXIkVlZW+Pr68t5775lcuApR0uU3xu5naWlJdHQ08fHxWFtb06xZswLr27x5s/YtpaWlJc2bN6d3794sW7ZMK1O9enUGDBiAhYUFtra2BAcHs27dOoxGI3DnW/revXtjbW1d9CcsxFOW3xg7ePAg586d4/PPP8fW1hYXFxfGjx+vxQ+DwUBoaCjvvfce3bt3Z9q0aXnuKTVlyhQcHBzw9PSkTZs2+Y7du3r27EnDhg2xsrJiypQpXL16lV9//fWRz+W3337j8uXLTJ06FRsbG2rWrMmwYcNMHp3q4uLCmDFjsLS0JCAggJdeeknucyWeqK5du+Lj44NOp6NFixa0bt26UImRlStXUq9ePYYOHYqNjQ22trb5JmbyExcXx+7du5k9ezZ6vR4/Pz8mTJhgMhaUUkyfPh0bGxuqVKlCo0aNHjhOhSipCjvGLC0tOX/+vPYFxd2bdBfm2lA8PZKwEUXKw8ND+7ednR0pKSm0aNGCjz/+mEmTJuHq6krXrl2JjIwEIDY2Fn9/f+0Ya2trPD09H+kGjPd+oxgdHU25cuXQ6XR5ykVFRXHixAkMBoP2M3r0aK5cufI3zlSI4pHfGLvf999/T3p6OvXq1aNy5coFToWFvGMQoGzZsiZj8P5v7atUqUL16tX58ccfSU9PZ+3atQwcOPBvnpEQJUt+YywqKoqkpCScnZ21+PHGG29w9epVrWzjxo0pW7YsycnJvPnmm4WqtyB+fn7avy0tLSlTpgxxcXGPfC6xsbF4enpiZWWlbbt/fN/br8L0TYjHFRoaSt26dXFycsJgMLBlyxauX7/+0OOio6OpUKHC32ozNjYWGxsbk9/3+8eCg4MDtra22msZC+JZVdgxtn79ek6cOEGlSpWoU6eOtrS9MNeG4umRhI14KoYOHcqvv/5KTEwM1tbWDB8+HABvb2+ioqK0cpmZmcTHx2uPOLWzs+P27dva/suXL+ep28zsf7/Gfn5+XLhwId+bD/v4+FCvXj2SkpK0n+TkZE6ePFlUpylEiVCuXDmWL1/OlStX+O6773j//fe1bwnvT2bePwYBIiMjTR4zfO8Yuys4OJiQkBDWr1+Pr68v9erVK/oTEaKE8PHxoXTp0ibx49atW9osM4DZs2eTkZFBlSpVGD9+/GO1Fx0drf07KyuLy5cv4+XlladcfmPzXt7e3sTHx2v3y4G841uIpykm5hL9+/dn1qxZJCQkkJSURNu2bVFKodfrSUtLM7mGu/e6z8/Pj/Pnz+dbb2HGQnp6ukmSVcaCeB49aIzdr27duqxbt47r168zadIkevfuzdWrVwt1bSieHknYiCfujz/+4MCBA2RmZlKqVCns7OywsLAAoE+fPsybN49Tp06RkZHBxIkT8fLy0m6OWrduXVasWEF2djZHjx5lxYoVD2yrXbt2ZGRk8NFHH5GamkpmZibh4eEAtG/fnqtXrzJ//nzS09PJycnhzJkzsj5ZPHeWL1/O1atX0el0ODk5YWZmpo05d3d3k/tTtG3blmvXrjF//nyys7PZu3cvYWFh9OvX74Ft9OjRg8OHDzNjxgyZXSOee6+88gq+vr5MnDiRlJQUlFJER0ezdetW4M6NUD/99FNWrVpFWFgYy5YtY9u2bX+7vTVr1vDbb7+RmZnJJ598gpubGw0aNMhTzt3dncuXL5vc3Phe9evXx93dnY8++oiMjAxOnDjBvHnz6N+//9/umxCPw5hqRClF6dKlMTMzY8uWLWzfvh2AihUrYmlpSVhYGDk5OaxevZojR45oxwYFBfH777+zcOFCMjIyuH37Nnv37gXujIWUlBQSEhLybdfLy4sWLVrw/vvvk5qaSkxMDNOmTZOxIJ47Dxpj98rMzGTFihXcvHkTMzMz7YbfFhYWf/vaUDwZkrART1xycjJDhw7FxcUFDw8P4uPjmTt3LgD9+vXj3XffpX379nh4eHDs2DE2btyo/XH59ddf88svv2AwGBg7duxDA6ter2fnzp0cOnQIX19fypQpwzfffGOyb9euXfj7++Pi4kLv3r1lSZR47uzcuZNatWqh1+vp2LEjn3/+ObVq1QLg008/Zfjw4Tg5OTFjxgycnJzYunUrK1euxMXFhbfffpsFCxbQpEmTB7Zhb2/PG2+8wenTpwkKCnoapyVEsTE3N2fjxo3ExcVRpUoVHB0dadeuHefPn8doNNKrVy8+++wzatSogY+PD99++y39+/fn2rVrf6u9QYMGMXbsWJydndmxYwcbNmzQ4uK9AgMDadCgAV5eXhgMBmJiYkz2W1pasmnTJg4dOoSHhwcdO3Zk1KhR9O7d+2/1S4jHVbVKFSZMmEBgYCAuLi6sWbOGjh07AneWJC1evJgPP/wQFxcX9u3bR+vWrbVjvb292blzJ2FhYbi7u+Pv78+PP/4IQKVKlQgODqZKlSoYDAb27duXp+2wsDDS0tLw8/OjcePGtGvXTp4EJZ47Dxpj9wsLC6N8+fLY29vz7rvvEhYWhouLy9++NhRPhk7lNz+qGCUnJ+Po6MitW7dwcHAo7u6Ih7idmU3Vj+58i3jqk9bYWuW9oBRCPIbMVJjmeeff4+PByq54+3OPTz75hKNHj/J///d/xd0VIf6+EjzGhHguyBgT4smSMfbMeZSch/x1LYQQ4pElJCSwePFik8d7CyGEEEIIIYqOLIkSQgjxSD777DP8/f1p164dLVu2LO7uCCGEEEII8VyShI0QQohHMmHCBFJTU1m4cGFxd0UIIYQQQojnliRshBBCCCGEEEIIIUoYSdiIEiEmJga9Xs+tW7eeetvVqlVj06ZNT71dIYpDcY41IYQQoiBRUVHodDqSkpKKuytCCGDv3r14e3s/lbamTJlC586dn0pbzxpJ2IgSwdfXF6PRiKOj41Nv++TJk7Rv3x6AkJAQateu/dT7IMSTotPpOHr0qPa6sGNNLpyFEEIIIV5cTZs2JTY2tri78cKThI147mVnZxd3F4R46uT3XgghhBDixaWUIicnp7i7IR6TJGxEkbGztjT5Jv/LL78kICBAe63T6Vi4cCHVq1fHwcGBjh07assy7v02//Dhw9jb23P79m3t2MuXL2NlZUVcXBwAhw8fpkWLFjg7O1O+fHkWL16slZ0yZQrt27dnyJAhODs7M3bsWCIjI2nZsiWOjo44OzvTuHFjrX5/f382bNjAkSNHGDx4MMePH0ev16PX64mOjsbGxobIyEit/vT0dJycnPj999+fxNsoxAPNmTOHChUqYG9vT7ly5Zg3bx7wvzG0dOlSypcvj5eXF/Xr1wegUaNG6PV6pk2blmfmzI4dO6hZsyb29va4u7szZMgQAO1Yb29v9Ho9oaGh3Lhxgy5duuDs7IzBYKBevXpER0c//TdBiCeooDEWERGBwWAwKdu5c2emTJny9DspxDOsoDF2v4LiE8DBgwdp3LgxBoOBqlWrsmrVqqfVfSFKNP+KVZk+fToNGjTA1taWffv2ERQUhKenJ56enowYMYKMjAyt/I8//kj58uVxdHTkrbfeon379lpcuz/upaSk8Pbbb1OmTBnKlCnD4MGDSU1NBf53HbpixQrKly+PwWBgwIABZGVlAWA0GunUqROlS5fG0dGRZs2acezYsaf2vjzLJGEjnqo1a9awa9cuYmJiiI2N5YsvvshTpm7duvj7+7N+/XptW2hoKM2bN8fLy4srV67QqlUrhgwZQkJCAhs2bGDy5Mns2rVLK//zzz/zj3/8g2vXrvHpp58yYcIEypcvz/Xr17l69Sqff/45FhYWJu3WqVOHhQsXUqNGDYxGI0ajET8/P9q3b8+yZcu0cuvXr8fT01P7g1aIp8nPz4/du3eTnJzMd999x5gxY9i/f7+2/6effuLgwYNERkZqScUDBw5gNBoZP358nvr69+/PmDFjSElJ4eLFi/Tt2xdAOzY2Nhaj0UhQUBD//ve/yc7OJjY2lsTERJYsWYK9vf1TOGshnp6HjTEhxOMp7BgrKD4lJSXx2muv0bNnTxISEliwYAFvvfWWjFMh/r+QkBCWLVuG0Whk5MiReHh4cP78eY4fP86xY8eYOnUqAGfPnqVv377MmzePxMRE6tevz7Zt2wqs97333uP8+fOcOHGC48eP89dffzFy5EiTMps3b+bw4cOcOnWKnTt3EhoaCkBubi69e/cmMjKSq1evUqdOHbp3745S6sm9Ec8JSdiIp2rs2LG4u7tjMBjo2rUrhw4dyrdc3759WbFihfZ6xYoV9OvXT/t3s2bN6N69O+bm5lSvXp2BAwcSFhamla9evToDBgzAwsICW1tbLC0tuXz5MlFRUVhaWtKoUSOsrKwK1efg4GCWL1+ufaCEhIQwcODAv/sWCPFYunbtio+PDzqdjhYtWtC6dWsiIiK0/ZMnT8ZgMGBra1uo+iwtLTl//jwJCQnY2dnRqFGjB5ZNTEzk3LlzmJubU7t2bZydnR/3lIQoUR42xoQQj6ewY6yg+LR582bc3Nx49913sbS0pHnz5vTu3dvkyzUhXmRDhgyhUqVKHD58mOjoaD7//HNsbW1xcXFh/Pjx2t9Ma9as4dVXX+W1117DwsKCt956i4oVK+ZbZ25uLmFhYUyfPh0XFxdcXV2ZNm0ay5cvJzc3Vys3ZcoUHBwc8PT0pE2bNtrfeg4ODvTo0QM7OztsbGz4+OOPOXv2LPHx8U/+DXnGScJGPFUeHh7av+3s7EhJScm3XJ8+fdi9ezeXL1/mzz//5MKFC7z++uvAnSl3W7ZswWAwaD9fffUVly9f1o739fU1qe/zzz/Hy8uLli1b4u/vz5QpU0w+XB6kdevWZGVlsWfPHuLi4tizZ4/2LY8QT1toaCh169bFyckJg8HAli1buH79urb//t/9h1m/fj0nTpygUqVK1KlTh7Vr1xZYdsyYMTRt2pTu3bvj4eHBe++9R1pa2t8+FyFKooeNMSHE4ynsGCsoPsXGxuLv729StmzZsnJzVCH+v7vXglFRUSQlJWlL2Q0GA2+88QZXr14FID4+Hh8fn3yPvV9CQgIZGRkmY69s2bJkZGSYjN+C/tZLS0tj6NCh+Pv74+DgoNUj8fXhJGEjioydnV2e+878XZ6enjRv3pywsDCWL1/O66+/jp2dHQA+Pj506dKFpKQk7SclJYUtW7Zox5uZmf5qly5dmvnz5xMdHc2mTZtYuHChyZKrgo67u61///6EhISwfPlyWrdujbu7+98+NyH+rpiYS/Tv359Zs2aRkJBAUlISbdu2NZlOev/vsE6ne2CddevWZd26dVy/fp1JkybRu3dvrl69mu9Y0Ov1zJw5kzNnzvDLL7+wa9cu5s+fXzQnJ0QJ8KAxptfrSUtLMxlvjxPnhHgRFSaO3VVQfPL29iYqKsqkbGRk5FN7/LAQJd3dazgfHx9Kly5t8jfTrVu3MBqNwJ2/ty5dumRybExMTL51urm5YWVlZTL2IiMjsba2xtXV9aF9mj17NocOHWLfvn0kJydr9ciSqIeThI0oMrXr1GHFihVkZ2dz9OhRkyVNf0e/fv1YtmwZYWFh2nIouLNcavfu3axbt46srCyysrI4evQof/zxR4F1rV27lpiYGJRSODo6Ym5unuceNgDu7u5cvnw5z6yBQYMG8X//938sWbJElkOJYmNMNaKUonTp0piZmbFlyxa2b9/+wGPc3d25cOFCvvsyMzNZsWIFN2/exMzMTLuxnIWFBW5ubpiZmZkcu2nTJs6ePUtubi4ODg5YWlrmO46EeFY9aIxVrFgRS0tLwsLCyMnJYfXq1Rw5cqSYeyzEs6WwcexB8alt27Zcu3aN+fPnk52dzd69e/NcKwoh4JVXXsHX15eJEyeSkpKCUoro6Gi2bt0KQPfu3dm1axfbt28nOzub77//nrNnz+Zbl5mZGb1792bChAncuHGDxMREJkyYQN++ffP9ku9+ycnJ2NjY4OTkVOB9FUX+JGEjisy/v/iSX375BYPBwNixY+nfv/9j1ff6668TGRmJmZkZgYGB2nYvLy+2bdvGokWLKFOmDO7u7vzrX/8iOTm5wLoOHTqkPSmnYcOGBAcH07FjxzzlAgMDadCgAV5eXhgMBi3LXLZsWV5++WWSk5Np167dY52XEH9X1SpVmDBhAoGBgbi4uLBmzZp8f4/v9emnnzJ8+HCcnJyYMWNGnv1hYWGUL18ee3t73n33XcLCwnBxcaFUqVJMnjyZNm3aYDAYCAsL4/z587z22mvY29tTtWpVGjZsaPLUDiGedQ8aYw4ODixevJgPP/wQFxcX9u3bR+vWrYu5x0I8Wx4ljhUUn5ycnNi6dSsrV67ExcWFt99+mwULFtCkSZOnfDZClGzm5uZs3LiRuLg4qlSpgqOjI+3ateP8+fMAVKpUiZCQEIYMGYKLiwu//PILgYGBWFtb51vf3Llz8ff3p2rVqlSrVo3y5cszZ86cQvVl1KhRmJub4+7uTvXq1WnYsGGRnefzTqdK2Dyk5ORkHB0duXXrFg4ODsXdHfEQtzOzqfrRnbuJn/qkNbZWz++37YMGDcJgMBT6g0mIIpGZCtM87/x7fDxY2RVvf4R43sgYE+LJkjEmxJNVhGOsUqVKTJo0iT59+hRR50R+HiXn8fz+dS1EEbpw4QI//PBDgU+1EkIIIYQQQohnycaNGwkICMDKyop58+YRHx/Pa6+9VtzdEveQJVFCPMQ777xD7dq1GTt2bIGPuhNCCCGEEEKIZ8m2bdvw8/PD1dWVVatW8Z///KdQNxEWT4/MsBHiIRYtWsSiRYuKuxtCCCGEEEIIUWTmzZvHvHnzirsb4gFkho0QQgghhBBCCCFECSMJGyGEEEIIIYQQQogSRhI2QgghhBBCCCGEECWMJGyEEEIIIYQQQgghShhJ2AghhBBCCCGEEEKUMJKwEUIIIYQQQgghhChhJGEjhBBCCCGEEEIIUcJIwkYIIYQQQgghhBCihJGEjRBCCCGEEEIIIUQJIwkbIYQQQgghhBBCiBJGEjZCCCGEEEIIIYQQJcwTS9jMnz+fl156CRsbG+rVq8fevXufVFNCCCGEEEIIIYQQz5UnkrBZs2YNI0aMYMKECRw5coSmTZvSpk0bYmJinkRzQgghhBBCCCGEEM+VJ5KwmTNnDsHBwbz55ptUqVKFL7/8Eh8fHxYsWPAkmhNCCCGEEEIIIYR4rlgUdYWZmZkcOnSIDz/80GT7P//5Tw4cOJCnfEZGBhkZGdrrW7duAZCcnFzUXRNPwO3MbHIzbgN3/s+yrYr8V0qIF1tmKmSoO/9OTgarnOLtjxDPGxljQjxZMsaEeLJkjD1z7uY6lFIPLVvkf11fv36dnJwc3N3dTba7u7tz5cqVPOWnT5/Oxx9/nGe7j49PUXdNPGFlvizuHgjxnJvhWdw9EOL5JmNMiCdLxpgQT5aMsWdKSkoKjo6ODyzzxKZD6HQ6k9dKqTzbAMaNG8eoUaO017m5udy4cQMXF5d8ywshhBBCCCGEEEI8i5RSpKSk4On58ARbkSdsXF1dMTc3zzOb5tq1a3lm3QBYW1tjbW1tss1gMBR1t4QQQgghhBBCCCGK3cNm1txV5DcdtrKyol69euzYscNk+44dO2jUqFFRNyeEEEIIIYQQQgjx3HkiS6JGjRpF3759efnll2nYsCHffvstMTExDB48+Ek0J4QQQgghhBBCCPFceSIJmx49epCYmMgnn3zC5cuXqV69Olu2bMHPz+9JNCeEEEIIIYQQQgjxXNGpwjxLSgghhBBCCCGEEEI8NUV+DxshhBBCCCGEEEII8XgkYSOEEEIIIYQQQghRwkjCRgghhBBCCCGEEKKEkYSNEEIIIYQQQgghRAkjCRth4pNPPqFq1ark5uZy+fJlJk6cSMOGDXF1dcXBwYF69erx7bffkpOT88B6vvvuO3Q6HXq9Ps++Zs2aMWLEiCd0BkI8m+4dewApKSkMHz4cLy8vrK2tqVixIrNmzcoz9pYsWYKXlxepqanF0W0hSpzHjWP79u2jbdu2ODk5UapUKSpUqMCnn35qUkbimBB53R/HkpOTmTBhAhUrVsTW1hYvLy+6devGyZMnTY6TOCaEqceJY0ajkREjRuDp6YmNjQ21a9dm9erVecpJHHuGKCH+v7i4OGVnZ6d++OEHpZRSGzduVD4+PmrChAlq8+bNavv27WrkyJHKzMxMDRw4sMB6YmNjlaOjo/L09FR2dnZ59kdERChLS0v1119/PbFzEeJZcv/Yy8rKUv/4xz+Uk5OTmjdvntq+fbsaNWqU0ul06t133zU5NisrS1WoUEF99NFHxdF1IUqUx41joaGhyszMTPXs2VP99NNPavfu3Wrx4sXq448/NikncUwIU/ePPaWUatasmbK1tVWzZs1Su3fvVsuXL1fly5dX9vb2KioqSisncUyI/3ncONaqVStlMBjUwoUL1e7du9Wbb76pABUaGmpSTuLYs0MSNkLzwQcfKC8vL5WTk6OUUurGjRsqMzMzT7l//etfClAxMTH51tO+fXvVoUMH1b9//3wTNkopVb16dfXWW28VXeeFeIbdP/ZWrVqlALVu3TqTcm+//bYyMzPLE1z//e9/K0dHR5WamvrU+ixESfQ4cSw2NlbZ2dmpIUOGFKotiWNC/M/9Y+/cuXMKUBMnTjQpd+DAAQWoOXPmmGyXOCbEHY8TxzZv3qwAFRYWZlK2VatWytPTU2VnZ5tslzj2bJAlUQKAzMxMlixZQu/evTEzu/Nr4eTkhKWlZZ6y9evXByA2NjbPvpUrV7Jnzx7mz5//wPb69u1LWFgYKSkpRdB7IZ5d+Y29/fv3o9PpaNOmjUnZ9u3bk5uby/r16022BwUFkZycnO+UVyFeFI8bx7777jtSU1MZO3ZsodqTOCbEHfmNvbvjztHR0aSswWAAwMbGxmS7xDEhHj+OrV+/Hr1eT7du3UzKDhw4kPj4eH777TeT7RLHng2SsBEA/PbbbyQmJtKiRYuHlt29ezcWFhZUrFjRZPu1a9cYMWIEM2bMwNvb+4F1BAQEkJqaSkRExON0W4hnXn5jLzMzEzMzszwB2traGoA///zTZLuHhweVK1dm8+bNT77DQpRQjxvH/vvf/+Ls7Mxff/1F7dq1sbCwoHTp0gwePJjk5OQ8dUgcE+KO/Maen58fnTp14osvviA8PByj0chff/3F8OHD8fX1pWfPniZ1SBwT4vHj2IkTJ6hSpQoWFhYmZWvWrKntv5fEsWeDJGwEAL/88gsAdevWfWC57du3s2LFCt59911cXFxM9g0dOpRKlSoxZMiQh7ZXp04ddDod+/fv//udFuI5kN/Yq1q1Kjk5Ofz6668mZfft2wdAYmJinnrq1q0r40m80B43jsXFxXH79m26detGjx492LlzJ2PGjGH58uW0bdsWpZRJPRLHhLijoLH3ww8/0K5dOwIDA7G3t6dKlSpcu3aNPXv24OTklKceiWPiRfe4cSwxMRFnZ+c85e9uu//6UeLYs0ESNgKA+Ph4dDodrq6uBZY5fPgw3bt3p0GDBkyfPt1k37p169i4cSOLFy9Gp9M9tD1LS0sMBgNxcXGP3XchnmX5jb2goCCcnZ15++23+e2330hKSmLVqlV89dVXANo02XuVLl2aa9eukZ2d/dT6LkRJ8rhxLDc3l/T0dMaPH8+4ceMICAhgzJgxTJ8+nf3797Nr1y6T8hLHhLijoLE3ZMgQ1q1bxxdffMGePXtYs2YNVlZWBAYGEh0dnaceiWPiRfe4cQx44N9h9++TOPZskISNACAtLQ1LS0vMzc3z3X/kyBFatWpFhQoV2LJli7Y0A+48Pu5f//oX7777Lp6eniQlJZGUlERmZiYASUlJ+T6q0cbGhrS0tCdzQkI8I/Ibe66urvz8888ANGjQACcnJ959913mzJkDgJeXV556bGxsUEqRnp7+dDouRAnzOHEM0L6lbN26tcn2u/eSOnz4cJ46JY4Jkf/Y+/nnn1myZAmLFi1ixIgRNGvWjO7du7Njxw5u3LjBlClT8tQjcUy86IoijuU3C/vGjRsA+c6+kThW8knCRgB3/kDMzMzMN7Fy5MgRWrZsiZ+fH9u3b89zA7nr169z9epVZs+ejZOTk/azatUqUlNTcXJyIigoKE+9N2/efGAGWYgXQUFj75VXXuHUqVNERkZy4sQJ4uPjqVKlCgDNmjXLU8+NGzewtrZGr9c/lX4LUdI8ThyD/63xv9/dpVD5zWyTOCZE/mPv6NGjwJ1Ydi+DwUD58uXz3EsDJI4J8bhxrEaNGpw+fTrPLLXjx48DUL169TzHSBwr+SRhIwCoXLkyABcuXDDZfvToUVq2bIm3tzc7duzId82xh4cH4eHheX5at26NjY0N4eHhTJ061eSY+Ph40tPTqVq16pM7KSGeAQWNvbv8/f2pVq0alpaWzJ49G09Pzzx3/we4ePGijCfxQnucOAbQtWtXALZu3WqyfcuWLcCd2W73kjgmxB35jT1PT0+APPdiS0xM5OzZs/k+nELimHjRPW4c69KlC0ajkXXr1plsX7ZsGZ6envzjH/8w2S5x7Nlg8fAi4kUQEBAA3Amsd79lPHPmDC1btgTgs88+49y5c5w7d047ply5cri5uWFjY6Mdf6+QkBDMzc3z3Xc3gBfmLuhCPM/yG3sAEyZMoEaNGpQpU4aYmBi+//57fvvtNzZv3kypUqVM6sjNzeX3338nODj4aXZdiBLlceIYwD//+U86dOjAJ598Qm5uLg0aNODgwYN8/PHHtG/fniZNmpi0J3FMiDvyG3uvv/46H330EUOGDCE2Npa6dety+fJlPv/8c27fvs17771nUofEMSEeP461adOGVq1aMWTIEJKTkylfvjyrVq3i559/ZuXKlXmWWkkce0YoIf6/pk2bqrZt22qvly5dqoACf5YuXfrA+vr376/s7Ozy3de3b19Vo0aNouy+EM+s+8eeUkoNGTJE+fr6KisrK+Xq6qq6du2q/vzzz3yP37VrlwLUoUOHnkZ3hSixHjeO3b59W40dO1b5+PgoCwsL5evrq8aNG6fS09PztCVxTIj/yS+OXb58WQ0bNkyVL19e2djYKE9PT9WuXTv1yy+/5Dle4pgQdzxuHEtJSVHDhw9XHh4eysrKStWsWVOtWrUq37Ykjj0bdErd95xK8cJat24dPXr0IDo6Ot+bmhaV5ORkPD09+eKLL3jrrbeeWDtCPCsed+z17duXixcvymMZxQtP4pgQxUPimBBFQ+KYuJ8kbIRGKUWjRo2oV68e8+bNe2LtfPzxx6xZs4Y///wTCwtZlSfE44y9CxcuUKVKFXbv3p1nyYYQLxqJY0IUD4ljQhQNiWPifnLTYaHR6XQsXrwYT09PcnNzn1g7Dg4OhISEyIeDEP/f44y9mJgY5s2bJxe5QiBxTIjiInFMiKIhcUzcT2bYCCGEEEIIIYQQQpQwMsNGCCGEEEIIIYQQooSRhI0QQgghhBBCCCFECSMJGyGEEEIIIYQQQogSRhI2QgghhBBCCCGEECWMJGyEEEIIIYQQQgghShhJ2AghhBBCCCGEEEKUMJKwEUIIIYQQQgghhChhJGEjhBBCCCGEEEIIUcJIwkYIIYQQQgghhBCihJGEjRBCCCGEEEIIIUQJIwkbIYQQQgghhBBCiBJGEjZCCCGEEEIIIYQQJYwkbIQQQgghhBBCCCFKGEnYCCGEEEIIIYQQQpQwkrARQgghhBBCCCGEKGEkYSOEEEIIIYQQQghRwkjCRgghhBBCCCGEEKKEkYSNEEIIIYQQQgghRAkjCRshhBBCCCGEEEKIEkYSNkIIIYQQQgghhBAljCRshBBCCCGEEEIIIUoYSdgIIYQQQgghhBBClDCSsBFCCCGEEEIIIYQoYSRhI4QQQgghhBBCCFHCSMJGCCGEEEIIIYQQooSRhI0QQgghhBBCCCFECSMJGyGEEEIIIYQQQogSRhI2QgghhBBCCCGEECWMJGyEEEIIIZ4Cf39/NmzYAEBISAi1a9cu1v7c69y5c7zyyivY29szevTo4u6OEEIIIZCEjRBCCCGeM4MGDUKn03H69OmHlo2IiMBgMDy0XFpaGpMmTaJSpUrY2tpSpkwZAgICWLFiRRH0uPjNmjWLmjVrkpKSwuzZs/PsDwkJQafT8f7775ts79y5M1OmTHlKvRRCCCFeLJKwEUIIIcRzw2g0snbtWpydnVmyZMkDy2ZnZxeqzqysLFq1akVERAShoaEkJSURExPDJ598wubNm4ui24+ksP1+FJGRkdSoUeOBZZycnFiwYAGXLl0q8vaFEEIIkZckbIQQQgjx3Fi9ejV2dnbMnDmT5cuXk5WVpe27uwxp8uTJeHh40KpVK9q0acOtW7fQ6/Xo9Xr27t2bp87Q0FDOnj3Lpk2bePnll7GyssLS0pJmzZqxevVqrdz27dt5+eWXcXR0pEyZMgwdOpS0tLRC9dtoNDJs2DB8fX0pXbo0/fr149atWwBERUWh0+lYunQp5cuXx8vLi5EjRzJw4ECTOqZPn07btm3zrT8rK4tx48bh6+uLm5sbPXr0ICEhAYD69esTHh7O2LFj0ev17Ny5M986fH196dq1K5MnTy7wPC5cuECHDh1wc3PDz8+PqVOnkpubC0DlypX5+eefATh+/Dg6nY6FCxcCcOvWLSwtLbl+/Xqh3i8hhBDiRSAJGyGEEEI8N5YsWUJQUBA9e/bk9u3bbNy40WT/iRMnsLCwICYmhs2bN7N161YcHR0xGo0YjUaaNm2ap85t27bx2muv4ejo+MC2S5UqxeLFi7lx4wb79+8nPDycOXPmFKrfgwYN4saNG/z5559ERkaSlZXFsGHDTMr89NNPHDx4kMjISIKDg/nxxx8xGo3a/mXLluVJ4tw1ffp0Nm3axL59+4iMjESn0xEUFATA77//TtOmTZk5cyZGo5GWLVsW2M9PP/2UNWvWcOrUqTz70tLSePXVVwkMDCQuLo69e/eyevVqli5dCkBgYCDh4eEA7N69m3LlymmvIyIiqFq1Kq6uroV6v4QQQogXgSRshBBCCPFcOHXqFL/++iv9+/dHr9fTpUuXPMuiHB0dmTBhAlZWVtja2haq3uvXr+Pp6am9zsjIwGAwYDAYsLGx4c8//wSgadOm1KlTB3Nzc8qWLcs777xDRETEQ+tPSEhg3bp1zJs3D4PBgJ2dHZ988glr1qwhJydHKzd58mQMBgO2trZUr16dqlWr8uOPPwLwyy+/kJCQQMeOHfNtY8WKFUycOBFfX1/0ej1z5sxhx44dxMfHF+o9uMvPz4+3336b8ePH59m3adMmnJycGDlyJFZWVvj6+vLee+8RFhYGQIsWLUwSNh999BF79uzRXgcGBj5SX4QQQojnnSRshBBCCPFcWLJkCbVq1aJWrVoA9O/fn23bthEXF6eV8fLywszs0S5/XF1dTRIb1tbWJCUlkZSUREZGhrbk548//qBly5a4u7vj4ODA+PHjC7XEJyoqitzcXMqWLaslgl555RXMzMy4cuWKVs7X19fkuEGDBhESEgLcWe7Vu3dvrK2t820jNjYWf39/7bWnpyfW1tbExsYW9m3QTJgwgfDwcH755Zc853HixAntHAwGA6NHj9bOISAggCNHjnDz5k0OHDhAly5d8PDw4OTJk5KwEUIIIfIhCRshhBBCPPOysrJYsWIFZ8+excPDAw8PD4KCgsjJydGSGkCeZE1hkjetWrVi27ZtJCcnP7Bcr169aNGiBRcvXiQ5OZlp06ahlHpo/T4+PpiZmREfH68lgpKSkkhPT8fLy6vAvvbq1YuDBw9y6tQp1q5dy6BBgwpsw9vbm6ioKO31lStXyMjIwNvb+6H9u5+rqytjxoxh7Nixec6jXr16JueQnJzMyZMnAXBzc6Ny5cp8+eWXlC9fHnt7ewIDA1mzZg1//fUXzZo1e+S+CCGEEM8zSdgIIYQQ4pn3008/kZyczOHDhzl69ChHjx7l2LFjTJo0ie+//77AxIm7uzspKSnaDXjz06dPH8qVK0eHDh04dOgQmZmZZGdns2/fPpNyycnJ2pKm06dPs2DBgkL13cPDg86dOzNs2DBtRs6VK1dYv379A49zcHCga9eu9O7dGz8/P+rUqfPAc5g2bRqXLl3CaDQyatQoWrZsabLU61GMHDmSc+fOmbwH7du35+rVq8yfP5/09HRycnI4c+aMybKwFi1a8OWXX9KiRQvgzn1t5s6dS506dR56jyAhhBDiRSMJGyGEEEI885YsWUKvXr2oXLmyNsPGw8OD4cOHEx8fr9075X6VKlUiODiYKlWqYDAY8iRhAKysrNixYwdNmjShZ8+eODo64uPjw4QJEwgNDdUeh71o0SL+/e9/o9frGTx4MD179ix0/0NCQrSlUA4ODjRt2pRDhw499Ljg4GCOHTtW4M2G7xo3bhytW7emYcOG+Pv7k5WVxcqVKwvdv/vZ2dnx0UcfkZiYqG27+4SpXbt24e/vj4uLC7179zZZ1tWiRQuSk5O15U/Nmzfn9u3bshxKCCGEyIdOFWaurhBCCCGEKHFiYmKoUKECcXFx8oQlIYQQ4jkjCRshhBBCiGdQTk4Ow4cP59atW481W0YIIYQQJZNFcXdACCGEEEI8msjISKpXr85LL73Eli1birs7QgghhHgCZIaNEEIIIYQQQgghRAkjNx0WQgghhBBCCCGEKGEkYSOeayEhIdSuXbu4u5GvmJgY9Ho9t27dKu6uCCGE+BumTJlC586di6XtiIgIDAZDsbQtxKPS6/UcP35ce/3xxx9TunRp9Ho9iYmJnDt3jldeeQV7e3tGjx7NtGnT6NWrV4H1RUVFodPpSEpKegq9F0KI4iMJG6EJCAjA3NycP//8U9uWlJSETqcjKiqq+DpWSE/i4lWn02Fra4u9vT3u7u707NmTa9euFUndvr6+GI1GHB0di6Q+IYR40Z05c4YOHTrg6uqKg4MDlStXZubMmUVS9+N+AXDw4EEsLS0xGo3atsWLF6PT6dizZ4+27fjx45iZmXH9+vXH6a4QT8y+ffto27Ytzs7OODg4ULFiRd59990HXisajUZq1KgBQGxsLJ9++il//PEHRqMRFxcXZs2aRc2aNUlJSWH27NmMHz+eVatWacfrdDqOHj36hM9MCCFKHknYCBNOTk6MGzeuuLtRohw4cICUlBROnTpFQkIC77//fnF3SQghRD7atWtHrVq1iImJ4ebNm6xbt46yZcsWd7cAqFu3LnZ2duzbt0/bFhERQZUqVQgPDzfZVqNGDXlEtyiRNm7cSJs2bfjnP//J6dOnSU5OZs+ePZQtW9bk9/iu7OzsPNuioqLQ6/X4+flp2yIjI7WEjhBCiP+RhI0wMXToUA4cOMB///vfAsusXr2amjVrYjAYeOWVVzhw4AAAv/76K2XKlNHKjR492uTbxK+//pqOHTtq+1etWkWtWrVwcHDAz8+PkJAQAI4cOUKTJk1wdnbGzc2NXr16kZiYqB0XGhpKhQoVsLe3x8vLi08//ZTExETatGnDrVu30Ov16PV69u7dm6fvRqORYcOG4evrS+nSpenXr1+hlyS5uLjw+uuvc+jQoULX99///pcaNWpgb2/P66+/TnBwMAMGDADyTufNyspi3Lhx+Pr64ubmRo8ePUhISNDq0ul0LFy4kOrVq+Pg4EDHjh1lOZUQQvx/169f58KFC7zzzjvY2tpibm5OtWrV6Natm1bm6tWrdO/eHTc3N3x9fZkwYYL2B2V+M2hq165NSEgIR44cYfDgwRw/flyLMTExMcCdR2sPGzYMg8GAr68va9asybd/ZmZmNGvWzOSP2j179jBx4sQ8CZsWLVoA8MEHH+Dn54e9vT1Vq1blhx9+KPD8s7Ky+OijjyhXrhwuLi507NiR+Ph4AJRSjB07Fg8PD21GxKZNmx7h3RXizu/R8OHDGT9+PCNGjMDd3R2AMmXKMHLkSAYOHKhd2yxdupTy5cvj5eUF/G+GzIYNG2jVqpV2vRYYGEj9+vUJDw9n7Nix6PV6du7cabLcsH79+gA0atQIvV7PtGnTtD5t3LiR8uXLYzAYGDBgAFlZWU/3TRFCiCdMEjbChLOzMx988AEffvhhvvu3bNnC+++/T0hICDdu3GDcuHF06NCBxMREXn75ZVJTUzl9+jQAu3fvxs/PT0uc7N69W7sI3bhxI8OGDeOLL74gKSmJP/74g1q1agF3LmpnzJjB1atXOXHiBHFxcVp/UlNTGTBgAEuWLCElJYWTJ0/y2muv4eLiwtatW3F0dMRoNGI0GmnatGme/g8aNIgbN27w559/EhkZSVZWFsOGDSvUe3P16lV++OEHKlasWKj6bt68SceOHRk5ciQ3b97kzTffJDQ0tMD6p0+fzqZNm9i3bx+RkZHodDqCgoJMyqxZs4Zdu3YRExNDbGwsX3zxRaH6LoQQzzsXFxcqV67MwIEDWbt2LdHR0XnK9O7dG0tLSyIjI9m7dy8bNmxg1qxZD627Tp06LFy4kBo1amgxxtfXF4Bt27bRuHFjEhMTmTp1Km+++SYpKSn51tOiRQsiIiIAOHfuHDY2NnTt2pVjx46RlpaGUor//ve/BAYGAlCrVi3++OMPkpKS+Oijj+jbty+RkZH51j1hwgT279/Pvn37uHz5MhUrVqRnz54A7Nixg7CwMA4fPkxycjI7d+40iWVCFMbZs2eJioqiR48eDy37008/cfDgwTy/r507dza5Xtu9eze///47TZs2ZebMmRiNRlq2bGlyzO+//w7cmfFsNBoZP368tm/z5s0cPnyYU6dOsXPnzgdeZwkhxLNIEjYijxEjRhAdHc2GDRvy7Pvmm28YM2YMdevWxczMjNdff53KlSuzZcsWLCwsaNq0KeHh4dy4cYMrV64wePBgwsPDyc3NZc+ePdpF6Pz583nvvfcIDAzEzMyM0qVLU6dOHeDOBWqTJk2wtLTE3d2dUaNGaRe4AJaWlto03LuzfAojISGBdevWMW/ePAwGA3Z2dnzyySesWbOGnJycAo9r2rQp9vb2eHh4kJ6ezrx58wpV36ZNm/D29mbQoEFYWFjQtm1bXn311QLbWbFiBRMnTsTX1xe9Xs+cOXPYsWOH9g0pwNixY3F3d8dgMNC1a1eT2T5CCPEi0+l0hIeHU6tWLT7++GPKli1L1apV2bFjBwBxcXHs3r2b2bNna8sxJkyYoM3u/Lvq1q1Lr169MDc3p2/fvmRmZnL27Nl8y7Zo0YJDhw6RnJxMREQEzZs3x9ramjp16vDLL79w4sQJbty4QbNmzQAICgqidOnSmJub07NnTypXrqzNar2XUor58+czZ84cypQpg5WVFVOnTmX//v1cunQJS0tL0tPTOXnyJFlZWfj6+krCRjyyu/dV8vT01LZ9/PHHGAwG9Ho93bt317ZPnjwZg8GAra3tE+3TlClTcHBwwNPTkzZt2sh1kRDiuSMJG5FHqVKlmDx5MuPHj8+TyIiKimL8+PEYDAbt5+jRo8TFxQF3LkbDw8MJDw+nWbNmtGzZkvDwcI4cOYKZmRk1a9YEIDo6mgoVKuTb/vnz5+nUqROenp44ODjQp08f7SLBzs6OjRs38p///AcfHx+aNGmS75rp/ERFRZGbm0vZsmW1vr/yyiuYmZlx5cqVAo/bu3cvKSkp/PLLL1y6dElLoDysvvj4eHx8fEzquvuNbH5iY2Px9/fXXnt6emJtbU1sbKy2zcPDQ/u3nZ1dgd/iCiHEi8jDw4PZs2dz8uRJEhISaNOmDV26dOHGjRvExsZiY2Nj8jlatmxZk8/Yv9vmXTqdjlKlShX42VyrVi0cHR3Zu3cvERERBAQEANC8eXPCw8OJiIigTp062g30v/jiC6pVq4ajoyMGg4ETJ07kezPi69evk5qaSrNmzbR45OHhgZWVFZcuXaJFixZ8/PHHTJo0CVdXV7p27VrgTB0hCnL3vkr3fpE0efJkkpKSeP/998nMzNS2P+h6pyjJdZEQ4nknCRuRr+DgYHJzc1m2bJnJdh8fH2bPnk1SUpL2k5qaqi1Zujvde9euXQQGBmo3f1y/fj0BAQHodDoA/Pz8OH/+fL5tDx48GC8vL06dOkVycjIrV65EKaXtf/XVV9myZQvXr1+nW7dudOnShdzcXMzMHvzr7OPjg5mZGfHx8Sb9T09P19ZYP0iDBg14//33eeedd1BKPbQ+T09PLl26ZFLH3Xse5Mfb29vkCQtXrlwhIyMDb2/vh/ZNCCGEKWdnZ6ZMmUJqaiqRkZF4e3uTnp7O1atXtTJ3t8Odxw7fvn3bpI57k/kPizGFodPpaN68OREREezZs4fmzZsDaNsiIiK0maj79u1jypQpLF++nJs3b5KUlET16tVN4uFdLi4u2Nra8ttvv5nEo7S0NBo1agTcuUfdr7/+SkxMDNbW1gwfPvyxz0e8WCpWrIifnx9r1659aNmiGC/3unv9KIQQLxpJ2Ih8mZub89lnn5nc2A1g2LBhfP755xw6dAilFLdv32bnzp3aN5R16tQhOzub0NBQWrRogU6no2nTpnz99dfaRSjAO++8w9y5c9mzZw+5ublcu3aNI0eOAJCcnIy9vT0ODg5cunSJzz//XDvu6tWrrF+/npSUFCwsLHBwcMDc3BwAd3d3UlJSTG7Uey8PDw86d+7MsGHDtG8or1y5wvr16wv9vgwePJjY2FjWrVv30PratWvHpUuXCAkJITs7m59//pndu3cXWHefPn2YNm0aly5dwmg0MmrUKFq2bGky9VgIIUT+bt68ycSJE/nrr7/Iycnh9u3bzJkzB2dnZypXroyXlxctWrTg/fffJzU1lZiYGKZNm0b//v2BOzcYvnjxInv37iU7O5tZs2aZ3PDe3d2dy5cvk5aW9lj9bNGiBStXrsTKykqbhdCgQQOOHj1qcsPh5ORkLCwscHNzIzc3l++//54TJ07kW6eZmRmDBw9m9OjR2hcFiYmJ2g2Q//jjDw4cOEBmZialSpXCzs4OCwuLxzoP8eLR6XTMnTuXzz77jK+++opr164Bd5aInzx58om27e7uzoULF55oG0IIURJJwkYUqGvXrpQvX95kW/v27ZkxYwZvvfUWTk5OvPTSS8ydO5fc3Fzgf0/BsLe319bHv/rqqyQnJ5skbDp37sycOXP417/+haOjI6+88grHjx8HYM6cOWzatAkHBwc6depE165dteNyc3OZO3cuPj4+ODo68s033/Djjz9iZmZGpUqVCA4OpkqVKhgMBpNHp94VEhKiLV1ycHCgadOmj7TeuVSpUowcOZIpU6aQm5v7wPqcnZ3ZsGED//73vzEYDHz77bd069YNa2vrfOseN24crVu3pmHDhvj7+5OVlcXKlSsL3TchhHiRWVlZERcXR9u2bXF0dMTX15f9+/fz888/Y2dnB0BYWBhpaWn4+fnRuHFj2rVrxwcffABA+fLlmTVrFm+88QZlypQhIyODatWqafUHBgbSoEEDvLy8MBgMD5wx+SAtWrTgypUr2uwauBNbateuTXJysnbD/Ndee42uXbtSo0YNPD09OXnyJI0bNy6w3unTp9OwYUMCAwOxt7enXr16bN++HbiT/Bk6dCguLi54eHgQHx/P3Llz/1b/xYutU6dObN68mS1btlCxYkXt2qd06dJP9EEIn376KcOHD8fJyYkZM2Y8sXaEEKKk0an85tYKIZ6If/7znzRr1oyJEycWd1eEEEIIIYQQQpRgMsNGiCdo+/btXL9+nezsbFavXk14eDivv/56cXdLCCGEEEIIIUQJJwuYhXiCDh06RFBQELdv38bf35+VK1dStWrV4u6WEEIIIYQQQogSTpZECSGEEEIIIYQQQpQwsiRKCCGEEEIIIYQQooSRhI14Zvj7+7NhwwbgztOeateuXaz9EaKkqFatGps2bXri7URFRaHT6UhKSnpqbQwYMIARI0Y8sfaEEEI8PU8rXt1v8ODBjB079qm3K4QQj0sSNiKPQYMGodPpOH369EPLRkREYDAYHlouLS2NSZMmUalSJWxtbSlTpgwBAQGsWLGiCHosxLMhICAAc3Nz/vzzT21bUlISOp2OqKioQtfx5Zdfmmw7efIk7du3L8Ke/n0xMTEMGjQILy8v9Ho9fn5+vPHGG+zfv7+4uyaEEOIx3fvl2V2Pkswvrni1cOFCZs6cCTydLx+EEKKoSMJGmDAajaxduxZnZ2eWLFnywLLZ2dmFqjMrK4tWrVoRERFBaGgoSUlJxMTE8Mknn7B58+ai6PYjKWy/hXgSnJycGDduXHF344mIjo7m5ZdfxsLCgn379pGcnMyJEyfo0aMHP/3001Pvj4x1IYR4McjnvRDieSUJG2Fi9erV2NnZMXPmTJYvX05WVpa27+4ypMmTJ+Ph4UGrVq1o06YNt27dQq/Xo9fr2bt3b546Q0NDOXv2LJs2beLll1/GysoKS0tLmjVrxurVq7Vy27dv5+WXX8bR0ZEyZcowdOhQ0tLSCtVvo9HIsGHD8PX1pXTp0vTr149bt24B//smZenSpZQvXx4vLy9GjhzJwIEDTeqYPn06bdu2/TtvmxCFNnToUA4cOMB///vffPcfOXKEJk2a4OzsjJubG7169SIxMRGA0aNHs3fvXsaOHYter6dNmzZA3m88V65cSZUqVTAYDDRp0oQjR45o+wICAhg3bhytW7dGr9dTt25djh8/ru2fM2cOFSpUwN7ennLlyjFv3rxCn9vkyZOpXbs23377LS+99BJmZmbY29vTrVs37ZvNx23jwoULdOjQATc3N/z8/Jg6dSq5ublA3s+oHj16UKdOHZYtW2ZSR+vWrZk1a1ah2xRCCFE4D4sxd+NVVlYWbm5ueWJh1apVtWvDa9euERQUhKenJ56enowYMYKMjAzgfzO8FyxYgK+vLw0bNiQjI4NBgwbh6uqKo6Mj1atX548//gBMl9fWr18fAG9vb/R6PaGhoRIrhBAlliRshIklS5YQFBREz549uX37Nhs3bjTZf+LECSwsLIiJiWHz5s1s3boVR0dHjEYjRqORpk2b5qlz27ZtvPbaazg6Oj6w7VKlSrF48WJu3LjB/v37CQ8PZ86cOYXq96BBg7hx4wZ//vknkZGRZGVlMWzYMJMyP/30EwcPHiQyMpLg4GB+/PFHjEajtn/ZsmV5kjhCFDVnZ2c++OADPvzww3z3m5mZMWPGDK5evcqJEyeIi4vTys6ePZumTZsyc+ZMjEYjW7duzXP83r17GTJkCIsWLSIhIYE33niD1q1bawlMgOXLlzNjxgySkpJ4+eWXeffdd7V9fn5+7N69m+TkZL777jvGjBlT6OVM27Zto2fPng8t93fbSEtL49VXXyUwMJC4uDj27t3L6tWrWbp0qVbm3s+oFStWEBwcbLI/Li6OiIgI+vbtW6hzEkII8WgeFGPusrS0pEePHiZL4w8ePEhcXBydOnVCKUXHjh3x8PDg/PnzHD9+nGPHjjF16lStfEpKCseOHeOvv/5iz549LFu2jGPHjnH+/HmSkpL4v//7Pzw8PPK0/fvvvwMQGxuL0WgkKChIYoUQosSShI3QnDp1il9//ZX+/fuj1+vp0qVLnmVRjo6OTJgwASsrK2xtbQtV7/Xr1/H09NReZ2RkYDAYMBgM2NjYaPfzaNq0KXXq1MHc3JyyZcvyzjvvEBER8dD6ExISWLduHfPmzcNgMGBnZ8cnn3zCmjVryMnJ0cpNnjwZg8GAra0t1atXp2rVqvz4448A/PLLLyQkJNCxY8dCnZMQj2PEiBFER0fnuQ8AQK1atWjSpAmWlpa4u7szatSoQo2Du5YvX06fPn1o1qwZlpaWjBgxAicnJ5Plh3379qVOnTpYWFjQv39/Dh06pO3r2rUrPj4+6HQ6WrRoQevWrQvd/v1jfdeuXRgMBhwcHEwumv9uG5s2bcLJyYmRI0diZWWFr68v7733HmFhYVqZ+z+jgoKC+P3334mMjNTen1atWlGmTJlCnZMQQohH86AYc69+/frxww8/kJ6eDsCKFSt44403KFWqFAcPHuTcuXN8/vnn2Nra4uLiwvjx400+73Nzc5kxYwa2trbY2tpiaWlJSkoKp0+fRilFxYoV8fHxKVSfJVYIIUoqSdgIzZIlS6hVqxa1atUCoH///mzbto24uDitjJeXF2Zmj/Zr4+rqSnx8vPba2tqapKQkkpKSyMjI0JYz/PHHH7Rs2RJ3d3ccHBwYP348169ff2j9UVFR5ObmUrZsWS0R9Morr2BmZsaVK1e0cr6+vibHDRo0iJCQEODOUorevXtjbW39SOcmxN9RqlQpJk+ezPjx402SigDnz5+nU6dOeHp64uDgQJ8+fQo1Du6KjY3F39/fZNtLL71EbGys9vre5ImdnZ3JTLPQ0FDq1q2Lk5MTBoOBLVu2FLr9+8f6q6++SlJSEj/99JN2Qf44bURFRXHixAltnBsMBkaPHm0yzu//jHJycqJTp07aVHeZSSeEEH+fpaWlyXJ5QHttaWkJPDjG3Kt+/fp4eHjw008/kZ2dzerVq+nXrx9w5/M+KSkJZ2dn7fP+jTfe4OrVq9rx9vb2Jg++6Nu3LwMGDGDw4MG4uroyYMCAQscviRVCiJJKEjYCuBNsV6xYwdmzZ/Hw8MDDw4OgoCBycnK0pAaQJ1lTmORNq1at2LZtG8nJyQ8s16tXL1q0aMHFixdJTk5m2rRpKKUeWr+Pjw9mZmbEx8driaCkpCTS09Px8vIqsK+9evXi4MGDnDp1irVr1zJo0KCHtiVEUQkODiY3NzfPmvnBgwfj5eXFqVOnSE5OZuXKlSbj4GFjztvbO88Tp6KiovD29n5on2JiYujfvz+zZs0iISGBpKQk2rZtW6hxCHfG+tq1a59YGz4+PtSrV89knCcnJ3Py5EmtTH7vT3BwMMuXL+fAgQMkJibSoUOHQp2PEEIIU35+ftoslLsuXLiAq6srdnZ2j1xf3759WbFiBT///DOlSpWiWbNmwJ3P+9KlS5t83t+6dcsk+XP/572FhQXjx4/n2LFjnD59mpiYGD7++OM8bRYURyVWCCFKIknYCODO/V2Sk5M5fPgwR48e5ejRoxw7doxJkybx/fffF/jHlLu7OykpKSQkJBRYd58+fShXrhwdOnTg0KFDZGZmkp2dzb59+0zKJScna0uaTp8+zYIFCwrVdw8PDzp37sywYcO0b1KuXLnC+vXrH3icg4MDXbt2pXfv3vj5+VGnTp1CtSdEUTA3N+ezzz5j2rRpJtuTk5Oxt7fHwcGBS5cu8fnnn5vsd3d358KFCwXW26dPH0JDQ9m/fz/Z2dl8/fXXJCYmFuqG2kajEaUUpUuXxszMjC1btrB9+/ZCn9PHH3/MoUOHGDJkCJGRkSiluH37Nr/99luRtNG+fXuuXr3K/PnzSU9PJycnhzNnzjx0OdWrr76KUoqhQ4cSFBSElZVVoc9JCCHE//Tp04dvvvmGI0eOoJQiOjqaKVOmEBQU9Lfq69u3L9u3b+eLL76gT58+6HQ6AF555RV8fX2ZOHEiKSkpWlv53bvtrt27d3P06FGys7Oxs7PDxsYGCwuLPOXc3NwwMzPLE0slVgghSiJJ2AjgznKoXr16UblyZW2GjYeHB8OHDyc+Pp7w8PB8j6tUqRLBwcHaE2nuT8IAWFlZsWPHDpo0aULPnj1xdHTEx8eHCRMmEBoaSo0aNQBYtGgR//73v9Hr9QwePLhQNy+9KyQkRFsK5eDgQNOmTQtcM32v4OBgjh07JtNeRbHo2rUr5cuXN9k2Z84cNm3ahIODA506daJr164m+0eMGMHOnTsxGAy0b98+T53Nmzfn66+/Jjg4GBcXF1avXs3WrVtNpo0XpGrVqkyYMIHAwEBcXFxYs2bNI93X6aWXXuKPP/7g9u3bNGrUCL1eT9WqVfn999/ZtGnTY7eh1+vZuXMnu3btwt/fHxcXF3r37m2yJCo/Op2OgQMHylgXQojH1L9/f95//32CgoJwdHSkRYsWNGvWLM+XD4Xl6+tLo0aN2L17t8kNfs3Nzdm4cSNxcXFUqVIFR0dH2rVrx/nz5wus6+rVq/Tq1QuDwcBLL72Eo6MjkydPzlPu7rLkNm3aYDAYtPviSKwQQpREOlXYue5CPIdiYmKoUKECcXFxuLq6Fnd3hBBPyPLly/nyyy85fPhwcXdFCCFECSWxQghR0sgMG/HCysnJYebMmXTr1k2SNUI8x4xGI1999RVDhw4t7q4IIYQooSRWCCFKIknYiBdSZGQkDg4O7Nmz529P4xVClHwrVqzA3d0dLy8v+vfvX9zdEUIIUQJJrBBClFSyJEoIIYQQQgghhBCihJEZNkIIIYQQQgghhBAljCRshBCihNi4cSP+/v7o9Xo2bNhQ3N15ZFFRUeh0OpKSkgAYPHgwY8eOLd5OCSGEEEI8J/z9/Z/Ja8Qn6f7rzwEDBjBixIi/Xd/evXvx9vYums4VAUnYCCFECTFq1Cg++eQTjEYjnTt3LrDcJ598gk6nY+vWrUXW9pO4AFi4cCEzZ84s0jqFeJh9+/bRpk0bnJycMBgM1KpVi1mzZpGZmfnYdT/uReDzLjAwkFKlSnHz5s2Hlg0JCaF27dpPvlNCCPEMOXPmDB06dMDV1RUHBwcqV6783F9LxcTEMGjQILy8vNDr9fj5+fHGG2+wf//+YulP06ZNiY2NLZa28yMJGyGEKCEiIyOpWbPmA8sopVi6dCnOzs4sWbLkKfXszlPV5JZnoqTbtGkTbdq0oXXr1pw7d46kpCTWrFnDqVOnuHz5cnF376nLzs5+KscAXLx4kYiICGxtbQkNDX0ibQghxPOuXbt21KpVi5iYGG7evMm6desoW7bsE2mrJHwWR0dH8/LLL2NhYcG+fftITk7mxIkT9OjRg59++ump96ckvCf3k4SNEEI8JVevXqV79+64ubnh6+vLhAkTyM7OJjExEb1eT05ODo0aNUKv15ORkZFvHbt27SIuLo5Fixbx008/kZCQoO3L7xvr2rVrExISAtxJCLVs2RJHR0ecnZ1p3Lgxt2/fplu3bsTExNCrVy/0ej2DBw8GQKfTMW/ePKpXr46trS1Go5E5c+ZQoUIF7O3tKVeuHPPmzSvwfO+fjdCnTx88PT1xcHCgXr16hIeH/703Uoh8KKUYPnw4Y8eOZcSIEbi6ugJQuXJlQkJC8PPzA+DgwYM0btwYg8FA1apVWbVqlVbHlClT6NChA8OGDcNgMODr68uaNWsA+OqrrwgNDWX+/Pno9XqqVasGQFZWFh999BHlypXDxcWFjh07Eh8fr9Wp0+n45ptvqFq1KnZ2dvTt25cbN27Qo0cPHBwcqFOnDn/99ZdW3t/fn88++4y6devi4OBA69atTeo7f/48rVu3xtnZmXLlyvHll19q++5+BkyePBkPDw969OiB0WikU6dOlC5dGkdHR5o1a8axY8dMzrl9+/YMGTIEZ2dnxo4di7u7O3v27DF5fytXrszatWsLfP+///57ateuzbvvvpsnmXx/G61bt2bw4MEcP34cvV6PXq8nJibmwf/BQgjxnLt+/ToXLlzgnXfewdbWFnNzc6pVq0a3bt1Myp09e5YGDRpgb29P8+bNuXTpkrbv2rVrBAUF4enpiaenJyNGjNCuKSMiIjAYDCxYsABfX18aNmxoEjdcXV3x8PBgzZo17N+/n+rVq+Po6EhwcDC5ubkAhYopBcXR/EyePJnatWvz7bff8tJLL2FmZoa9vT3dunUzmVn0KNef97tw4QIdOnTAzc0NPz8/pk6dqp1PfnHz7vt014PivFKKsWPH4uHhgYODAxUrVmTTpk2F7luhKCGEEE9FYGCg6t27t0pJSVFRUVGqatWq6rPPPtP2A+rIkSMPrKNnz56qS5cuKjc3V/n7+6vZs2dr+5YuXapq1aplUr5WrVpq6dKlSimlevXqpd555x2VmZmpMjMz1f79+1VGRoZSSik/Pz+1fv16k2MB1bBhQxUXF6fS09NVTk6O+vHHH1VMTIzKzc1Vu3fvVjY2Nmrfvn1KKaUiIyMVoG7evKmUUqp///7qvffe0+r7/vvvVVJSksrMzFSzZs1Szs7OKjk5ufBvoBAPcObMGQWo8+fPF1jm5s2bysXFRX311VcqMzNTRUREKDs7O+13ePLkycrS0lKFhYWp7OxstWzZMqXX67Xf0/t/p5VSasyYMSowMFDFx8erjIwMNXr0aNW0aVNtP6ACAwPV9evXVWxsrCpdurSqVq2a+u9//6uysrJUv379VIcOHbTyfn5+yt/fX50+fVqlpqaqfv36qYCAAKWUUllZWapSpUpqzJgxKi0tTR07dkyVKVNGhYaGKqXufAaYm5urTz75RGVkZKjU1FR169YttXr1amU0GlVaWpoaPny4qlixosrNzdXO2dzcXC1dulRlZWWp1NRUNXr0aNW/f3+tTwcOHFBOTk4qPT093/c1OztbeXl5qblz56oLFy4onU6nDh06pO3Pr438Pq+EEOJFlpubqypXrqxeffVVtWbNGhUVFZWnjJ+fn6pWrZq6cOGCSktLU23atNE+r3Nzc9U//vEPNWrUKJWamqquX7+uAgIC1MSJE5VSSoWHhyszMzP1zjvvqNTUVO2z2MLCQs2ZM0dlZWWpb7/9Vjk4OKjXX3/dJG6tW7dOKaUKFVMeFEfv5+HhoZYsWfLQ9+bvXn/evn1b+fn5qTlz5qiMjAwVHR2tqlWrpr777julVP5xMzw8XDk6OmptPyjOb9u2TXl7e6u4uDillFLR0dHqzJkzDz2fRyEJGyGEeApiY2MVoC5fvqxtCw0NVRUqVNBePyxhc+PGDWVtba02bNiglFJq4sSJqmrVqtr+hyVs+vXrpzp27KjOnj2bp+6CEjb3b7tfp06d1NSpU5VSD0/Y3M9gMGjBVojHtW/fPgWotLS0AsusXLlSVa5c2WTbW2+9pd566y2l1J0LzX/84x/avtzcXGVlZaUOHjyolMr7O52bm6vs7OzU0aNHtW1paWnKzMxMxcTEKKXujKOtW7dq+7t166Z69Oihvd68ebPy8vLSXvv5+amZM2dqr69cuaIAdenSJbVv3z7l4OCgJVqVUuqzzz5TrVq1Ukrd+QxwdnZWOTk5Bb4HN2/eVICKjY3Vzvn+z41Tp04pvV6vUlJSlFJKvf322+pf//pXgXVu3rxZWVpaqmvXrimllGrSpIkaOnSotj+/NiRhI4QQeV2+fFmNGjVKVa1aVZmZmakqVaqo7du3a/v9/PzUggULtNcrV65U1atXV0op9fvvv+eJAdu3b1dly5ZVSt1J2Nx7nabUnc9iDw8P7XVqamq+cWvChAn59je/mPKgOHo/CwsLk7Z27typHB0dlb29vXJ3dy/wfSrs9efatWtV7dq1TY799ttvVWBgoHb+979n9yZsHhbnd+/erVxdXdX27dtVZmZmgf19HLIkSgghnoLY2FhsbGzw8PDQtpUtW/aRbmq2cuVKHBwcaNu2LQD9+vXj1KlT/Prrr4U6/vPPP8fLy4uWLVvi7+/PlClTtCmhBfH19TV5HRoaSt26dbUbum7ZsoXr168/tO3c3FwmTJhAhQoVcHBwwGAwcOvWrUIdK0Rh3F0CFRcXV2CZ2NhY/P39TbbdPw7vHaM6nY5SpUqRkpKSb33Xr18nNTWVZs2aYTAYMBgMeHh4YGVlZTJF/d46bW1t87w2Go0m9d5dvgXg7u6OtbU1cXFxxMbG4unpiZWVVYH99/Lywszsf5d3aWlpDB06FH9/fxwcHLTzv3fs3T/Oq1SpQvXq1fnxxx9JT09n7dq1DBw4MN/3AGDJkiW0bdsWNzc3APr3709YWBhpaWkFtiGEECIvDw8PZs+ezcmTJ0lISKBNmzZ06dKFGzdumJS5y87OTotRUVFRJCUl4ezsrMWkN954g6tXr2rl7e3tTZb7wJ04c5etrW2eNu6NU4WJKY8SR11dXU2W/b766qskJSXx008/kZ6erm3/u9efUVFRnDhxQns/DAYDo0eP5sqVK1qZ++PmvR4W51u0aMHHH3/MpEmTcHV1pWvXrkRGRj60X49CEjZCCPEUeHt7k56ebhI0IyMjH+mxgUuWLOHWrVv4+Pjg4eFB06ZN0el02v0i9Ho9t2/fNjnm3oBUunRp5s+fT3R0NJs2bWLhwoWsX78eoMBAde/2mJgY+vfvz6xZs0hISCApKYm2bdsW6mbEYWFhhIWFsXnzZm7dukVSUhKOjo5yI2NRZCpWrIi/vz+rV68usIy3tzdRUVEm2x5lHN4/TlxcXLC1teW3334jKSlJ+0lLS6NRo0aPfA53RUdHa/++du0aGRkZeHl54e3tTXx8PFlZWQX2//4+zp49m0OHDmk3c7x7/veOvfzGf3BwMCEhIaxfvx5fX1/q1auXb18TEhLYuHEju3btwsPDAw8PDz788EOSkpL4v//7vwLbKOgzRwghxB3Ozs5MmTKF1NTUQiUBfHx8KF26tEk8unXrlsmXAo/72VuYmPIoWrVq9cD7o8HjXX/6+PhQr149k/ckOTmZkydPamUe9J4UJs4PHTqUX3/9lZiYGKytrRk+fHghz75wJFoKIcRT4OXlRYsWLXj//fdJTU0lJiaGadOm0b9//0Idf+jQIY4dO8aOHTs4evSo9rNo0SJWr15NamoqtWvX5uLFi+zdu5fs7GxmzZpFYmKiVsfatWuJiYlBKYWjoyPm5uZYWFgAd75duXDhwgP7YDQaUUpRunRpzMzM2LJlC9u3by9U/5OTk7GyssLV1ZXMzEw++eQTkpOTC3WsEIWh0+n4+uuvmTFjBl9//bX2u3/27FmCg4OJjo6mbdu2XLt2jfnz55Odnc3evXsJCwujX79+hWrD3d2dixcvaq/NzMwYPHgwo0eP1mbUJCYmPvAGi4WxaNEizpw5Q1paGmPHjqVZs2Z4e3tTv3593N3d+eijj8jIyODEiRPMmzfvgZ8jycnJ2NjY4OTkhNFoZPz48YXqQ48ePTh8+DAzZsx44Oya5cuX4+zszF9//aV9Lp04cYIBAwY88El27u7uXL582WQWjhBCvMhu3rzJxIkT+euvv8jJyeH27dvMmTMHZ2dnKleu/NDjX3nlFXx9fZk4cSIpKSkopYiOjmbr1q1F1se/G1MK8vHHH3Po0CGGDBlCZGQkSilu377Nb7/9ppV5nOvP9u3bc/XqVebPn096ejo5OTmcOXOGiIiIQh3/sDj/xx9/cODAATIzMylVqhR2dnbatXVRkYSNEEI8JXeXCPj5+dG4cWPatWvHBx98UKhjlyxZQkBAAM2aNdO+xfbw8GDAgAHY29uzZs0aypcvz6xZs3jjjTcoU6YMGRkZ2pNs4E7S5+5TqBo2bEhwcDAdO3YEYPz48cybNw8nJyeGDh2abx+qVq3KhAkTCAwMxMXFhTVr1mjHP0z//v2pVq0afn5+lC1bllKlSuHj41OoY4UorPbt27N161Y2b95MuXLltOnglStXpkyZMjg5ObF161ZWrlyJi4sLb7/9NgsWLKBJkyaFqv/NN98kLi4OJycnatasCcD06dNp2LAhgYGB2NvbU69evUJfSBZk0KBB9OrVC3d3d+Li4rTHZFtaWrJp0yYOHTqEh4cHHTt2ZNSoUfTu3bvAukaNGoW5uTnu7u5Ur16dhg0bFqoP9vb2vPHGG5w+fZqgoKACyy1ZsoQhQ4bg5eVl8tk0evRoIiIiCkwEBwYG0qBBA7y8vDAYDPKUKCHEC8/Kyoq4uDjatm2Lo6Mjvr6+7N+/n59//hk7O7uHHm9ubs7GjRuJi4ujSpUqODo60q5dO86fP19kffy7MaUgL730En/88Qe3b9/WrlGrVq3K77//rj1t6XGuP/V6PTt37mTXrl34+/vj4uJC7969TWagP8yD4nxycjJDhw7FxcUFDw8P4uPjmTt37qO/EQ+gUzIfXQghhBCiRPD39+fLL7+kc+fOxd0VPvnkE44ePWqytEkIIYQQT0/RztcRQgghhBDPvISEBBYvXszSpUuLuytCCCHEC0uWRAkhhBBCCM1nn32Gv78/7dq1o2XLlsXdHSGEEOKFJUuihBBCCCGEEEIIIUoYmWEjhBBCCCGEEEIIUcJIwkYUqTZt2jB//vwC93fu3JkpU6Y8vQ49Z86dO8crr7yCvb09o0ePLu7uCCGEeAoWL15MmTJl0Ov1HDlypLi7w5QpU0rETZGFEEKI550kbIQmICCAL7/8Ms92nU7H0aNHC1XH1q1bC3wk8OMKCQlBp9PRp08fk+1XrlzBwsICg8HwRNotSWbNmkXNmjVJSUlh9uzZxd0dIYQocfbt20ebNm1wcnLCYDBQq1YtZs2aRWZm5mPXXRyJiqysLN577z3WrFmD0WikTp06ecqcOXOGDh064OrqioODA5UrV2bmzJlF0n5ISAi1a9cukrrEsy8gIABra2v0er324+rq+sTbsre3p1q1avzwww9PpK0nYdCgQeh0Ok6fPv3QshERES/EdawQ4tFJwkY8U/z8/NiyZQu3bt3Sti1fvpwKFSoUY6+ensjISGrUqFHc3RBCiBJp06ZNtGnThtatW3Pu3DmSkpJYs2YNp06d4vLly0+lD9nZ2UVa39WrV0lLS6NmzZoFlmnXrh21atUiJiaGmzdvsm7dOsqWLVuk/RDirpkzZ2I0GrWf69evP/G2kpOTmTVrFkFBQURHR+dbtqjH3sPk5ORQ0K1AjUYja9euxdnZmSVLljywnqfdbyHEs0USNuKRrV69mpo1a2IwGHjllVc4cOCAtu/+WTrr1q2jfPnyODo68tZbb+UJSocPH6ZFixY4OztTvnx5Fi9e/MC2DQYDrVu3Zs2aNdq2kJAQBg4caFLO39+fDRs2aK83bNiAv7+/9nrOnDn4+vpib2+Pv78/3333nbZv586d1K9fH4PBQLVq1fjpp58KPL+jR4+i0+lM9o8dO5ZXX30VOzs7GjRoQFxcHFOmTMHNzQ1vb2/Wr19f4PllZWUxbtw4fH19cXNzo0ePHiQkJABQv359wsPDGTt2LHq9np07dz7wvRJCiBeJUorhw4czduxYRowYoX3rX7lyZUJCQvDz8wPgwoULdOjQATc3N/z8/Jg6dSq5ubnA/2aTfPrpp5QuXRp3d3ftM3/Dhg1MmzaNTZs2aTMLAAYMGEBwcDDdu3fHwcGBBQsWkJWVxUcffUS5cuVwcXGhY8eOxMfHF9j38+fP07p1a5ydnSlXrpzW5pEjR6hUqRIA3t7elCtXLs+x169f58KFC7zzzjvY2tpibm5OtWrV6Natm1bm6tWrdO/eHTc3N3x9fZkwYYIWj/ObQVO7dm1CQkI4cuQIgwcP5vjx49o5x8TEAHf+WB02bBgGgwFfX1+TuCxeTMOHD2fQoEEm22bOnMlrr70GwPbt23n55ZdxdHSkTJkyDB06lLS0tELVrdPpaNeuHQaDgTNnzgD/m5WyYMECfH19adiwIfB413EPG7s6nY558+ZRvXp1bG1tMRqN+fZ39erV2NnZMXPmTJYvX05WVpa27+6Ymzx5Mh4eHrRq1Yo2bdpw69YtbZzt3bu3UO+LEOL5Jwkb8Ui2bNnC+++/T0hICDdu3GDcuHF06NCBxMTEPGXPnTtH7969+eKLL0hMTKRevXr8/PPP2v4rV67QqlUrhgwZQkJCAhs2bGDy5Mns2rXrgX0YOHAg33//PQC//PILOp2O+vXrF/oczp49y8SJE9m+fTspKSn89ttv2vF//vkn3bp1Y8aMGdy4cYNFixbRt29f7eKgMEJDQ5k7dy6JiYnY2dnRtGlTHB0duXz5MpMnT+att94yCdz3mj59Ops2bWLfvn1ERkai0+kICgoC4Pfff6dp06bat03yqFUhhPifc+fOERkZSa9evQosk5aWxquvvkpgYCBxcXHs3buX1atXs3TpUq3MyZMnsbGxIS4ujjVr1vD+++9z4cIFOnfuzPjx42nfvr02s+CuVatWERwcTFJSEsHBwUyYMIH9+/ezb98+Ll++TMWKFenZs2e+fcrOzqZ9+/bUqlWL+Ph41q9fz6xZswgLC6NOnTqcPHkSgNjYWC5cuJDneBcXFypXrszAgQNZu3ZtvrMPevfujaWlJZGRkezdu5cNGzYwa9ash76nderUYeHChdSoUUM7Z19fXwC2bdtG48aNSUxMZOrUqbz55pukpKQ8tE7x/OrXrx8//vijSRJmxYoV9O3bF4BSpUqxePFibty4wf79+wkPD2fOnDmFqjs3N5f//Oc/pKenmywLTElJ4dixY/z111/s2bPnsa/jCjN2w8LC2L59O8nJydjZ2eVbz5IlSwgKCqJnz57cvn2bjRs3muw/ceIEFhYWxMTEsHnzZrZu3Yqjo6M2zpo2bVqo/gohnn+SsBEmxo0bh8FgMPm51zfffMOYMWOoW7cuZmZmvP7661SuXJktW7bkqWv16tW8+uqrdOjQAQsLCwYPHmyydGnFihU0a9aM7t27Y25uTvXq1Rk4cCBhYWEP7GPLli2Jj4/n9OnTLF26NM/smocxNzdHKcXJkydJS0vD3d1dm2q+aNEiBgwYQGBgIGZmZjRp0oT27duzdu3aQtffp08fqlevjo2NDV27diUtLY2RI0diYWFBUFAQiYmJBU7nXbFiBRMnTsTX1xe9Xs+cOXPYsWPHA7+ZFUIIgTYb0cvLq8AymzZtwsnJiZEjR2JlZYWvry/vvfeeSdxxcXFhzJgxWFpaEhAQwEsvvfTQ+7j985//pHXr1piZmVGqVCnmz5/PnDlzKFOmDFZWVkydOpX9+/dz6dKlPMf+9ttvXL58malTp2JjY0PNmjUZNmwYISEhhTpvnU5HeHg4tWrV4uOPP6Zs2bJUrVqVHTt2ABAXF8fu3buZPXs2er0ePz8/JkyYUOj6C1K3bl169eqFubk5ffv2JTMzk7Nnzz5WneLZcP+1YqtWrQB4+eWX8fHx4T//+Q9wZ4ZYTEwMXbp0AaBp06bUqVMHc3NzypYtyzvvvENERESh2rKzs+P1119n4sSJuLm5aftzc3OZMWMGtra22NraPtZ1nFKqUGP3gw8+wNPTE2tra8zM8v4pderUKX799Vf69++PXq+nS5cueZZFOTo6MmHCBKysrLC1tX1o34QQLy5J2AgT06dPJykpyeTnXlFRUYwfP94kUB89epS4uLg8dcXHx2tT0O+693VUVBRbtmwxqeurr7566H0GzMzM6NevH9988w3r1q3TvrkprHLlyrFs2TLmzZuHu7s7//znP7WL8aioKBYuXGjSp//85z+PlDDx8PDQ/m1ra4u7u7vJa6DAKbSxsbEmS7fuXhDExsY+whkKIcSL5+4SqPzi0V1RUVGcOHHC5DN+9OjRXLlyRStz72c4gJ2d3UNnjtyddQJ3liilpqbSrFkzrQ0PDw+srKzyTdjExsbi6emJlZWVtq1s2bKP9Lnv4eHB7NmzOXnyJAkJCbRp04YuXbpw48YNYmNjsbGxMTmvR62/oDbv0ul0lCpVSmbYvCDuv1a8mxwE6Nu3L8uXLwfu3GOwa9eu2rXPH3/8QcuWLXF3d8fBwYHx48c/9P43d9tKS0vjzJkzLF26lEWLFmn77e3tTb5cfJzruMKO3XvHe36WLFlCrVq1qFWrFgD9+/dn27ZtJp9NXl5e+SZ7hBDifvJJIR6Jj48Ps2fPNgnUqampfPjhh3nKenp65plJcnft+926unTpYlJXSkpKvrN17jdw4EAWLFhA48aNTRIid+n1em7fvq29vj8J1L17d8LDw7l69Sq1atXSkj4+Pj689957Jn0yGo0sWLCgUPU+Lm9vb6KiorTXV65cISMjA29v7yJtRwghnjcVK1bE39+f1atXF1jGx8eHevXqmXzGJycna8uOHqagP7Du3e7i4oKtrS2//fabSTtpaWk0atQoz7He3t7Ex8ebLJWNjIz825/7zs7OTJkyhdTUVK2e9PR0rl69mm/998c1wCSBJX9UikfRp08fdu3aRVxcHKtWrTL5Uq1Xr160aNGCixcvkpyczLRp0wq8aW9+ypcvT7t27di0aZO27f7fz8e5jivs2H3QmMjKymLFihWcPXsWDw8PPDw8CAoKIicnx2RW2/11yDgTQhREPh3EIxk2bBiff/45hw4dQinF7du32blzZ77f1HXv3p1du3axefNmsrOzWbx4scl06b59+7J7927WrVtHVlYWWVlZHD16lD/++OOh/ShXrhx79uxh3rx5+e6vW7cuq1atIj09nYsXL/LNN99o+86cOcOOHTtIS0vDysoKvV6PhYUFAO+88w5Lly4lPDycnJwcMjIy+OWXX7RHMtatW5f/+7//49atW1y7dq1Q9wB4FH369GHatGlcunQJo9HIqFGjaNmyJZ6enkXajhBCPG90Oh1ff/01M2bM4Ouvv9burXb27FmCg4OJjo6mffv2XL16lfnz55Oenk5OTg5nzpx56LKMu9zd3YmOjiYnJ6fAMmZmZgwePJjRo0dr38onJiYWeFPe+vXr4+7uzkcffURGRgYnTpxg3rx59O/fv1B9unnzJhMnTuSvv/4iJyeH27dvM2fOHJydnalcuTJeXl60aNGC999/n9TUVGJiYpg2bZpWf+3atbl48SJ79+4lOzubWbNmmdyXzt3dncuXLxf65rDixebt7U2TJk0IDg7GysqKgIAAbV9ycrK2vOn06dNaEqWwoqOj2bJlywOflvk413GPOnbz89NPP5GcnMzhw4c5evQoR48e5dixY0yaNInvv/++wASVu7s7KSkp2tJOIYS4SxI24pG0b9+eGTNm8NZbb+Hk5MRLL73E3LlztSds3KtSpUqsWLGC4cOH4+Liwm+//aY9KQDuTAfdtm0bixYtokyZMri7u/Ovf/2L5OTkQvWlSZMmBU5LnTp1KklJSbi5udG7d2/69eun7cvMzGTSpEm4u7vj4uLC7t27tW896tSpw6pVq7Q10l5eXkyaNImMjAwARo4cSZkyZfDx8SEwMJAePXoU9q0rlHHjxtG6dWsaNmyIv78/WVlZrFy5skjbEEKI51X79u3ZunUrmzdvply5chgMBt544w0qV65MmTJltCfs7dq1C39/f1xcXOjdu7fJjJIH6datGw4ODri6uua5x9u9pk+fTsOGDQkMDMTe3p569eqxffv2fMtaWlqyadMmDh06hIeHBx07dmTUqFH07t27UH2ysrIiLi6Otm3b4ujoiK+vL/v37+fnn3/WbogaFhZGWloafn5+NG7cmHbt2vHBBx8Ad2YtzJo1izfeeIMyZcqQkZFBtWrVtPoDAwNp0KABXl5eGAwGk5my4sV092mV9/7cm+Tr168f27Zto0+fPiYzRxYtWsS///1v9Ho9gwcPLvBG3AW11bhxY1q2bMlHH31UYPnHvY57lLGbnyVLltCrVy8qV66szbDx8PBg+PDhxMfHEx4enu9xlSpVIjg4mCpVqmAwGNi3b1+h2xRCPN906lHmIgohhBBCCCGEEEKIJ05m2AghhBBCCCGEEEKUMJKwEUIIIYQQQgghhChhJGEjhBBCCCGEEEIIUcJIwkYIIYQQQgghhBCihJGEjXgqDAZDoR+bKoQoGklJSeh0OqKiooq7K0K88CIiIkyeLNWmTRvmz59ffB0SogQKCAjgyy+/LO5uCCEeIioqCp1OR1JS0lNt997PiPvj6vNKEjZCExAQgE6nY+fOnSbbP//8c3Q6HSNGjCiejj2GwMBASpUqxc2bNx9aNiQkhNq1az/5TokXVkBAANbW1uj1euzt7alWrRo//PBDcXfrgQYMGKA99v5Rj3sWPzPE82HQoEHodDpOnz5dJPXpdDqOHj1aJHXdtXXrVoYOHVqkdQrxpN2NY/b29jg6OlK9enVGjx5NQkJCcXdNiOdCQUnLJxGHHkVRtJ+Tk8OcOXOoWbMmdnZ2lC5dmgYNGjBv3jyys7OLpqPPIUnYCBOVKlVi6dKlJttCQkKoXLlyMfWIvz2AL168SEREBLa2toSGhj6RNoR4VDNnzsRoNJKcnMysWbMICgoiOjq6uLuVh1KKnJyc4u6GEI/MaDSydu1anJ2dWbJkyVNpU2KIeJHMnDmTlJQUkpKSWLt2LXFxcdSrV4+rV68Wa79kHApR9IpyXPXu3Zvvv/+er776iuvXr3PlyhXmzZvH77//zq1bt4qsncLIyclBKfVU2/y7JGEjTPTs2ZOtW7dqg+a3335DKcU//vEPk3IHDx6kcePGGAwGqlatyqpVq7R9ubm5TJo0CXd3dzw9Pfnmm2/ytLN69Wpq1qyJwWDglVde4cCBA9q+gIAAPvjgA/75z39iZ2fH1q1b8ff3Z9asWTRo0AB7e3uaN2/OpUuXHngu33//PbVr1+bdd9/Nc9E+ZcoU2rdvz5AhQ3B2dqZ169YMHjyY48ePo9fr0ev1xMTEPPL7J0Rh6XQ62rVrh8Fg4MyZM9r2w4cP06JFC5ydnSlfvjyLFy/W9k2ZMoUOHTowbNgwDAYDvr6+rFmzRtufkZGh/U6/9NJL/PjjjyZtKqX46quvqFy5MgaDgYCAAJMZCP7+/kyfPp0GDRpga2vLqVOnTI6/ceMGXbp0wdnZGYPBQL169f5Wsik0NJTq1atjb2+Pr68vkyZNMgmaOp2OhQsXUr16dRwcHOjYsaNJIL9w4QIdOnTAzc0NPz8/pk6dSm5u7iP3QzyfVq9ejZ2dHTNnzmT58uVkZWUBd8ZP586dTcreu1z38OHDNGjQAAcHB1xdXenQoQMA9evXB6BRo0bo9XqmTZumTQVfunQp5cuXx8vLC4APPvgAPz8/7O3tqVq16gNn0N37LarRaKRTp06ULl0aR0dHmjVrxrFjx4rwXRGi6Ol0OqpWrcrKlStxdHRkzpw5wIPj2JEjR2jSpAnOzs64ubnRq1cvEhMTC2zjYTHx3mu5sWPHPrmTFaIEUUoxe/ZsypUrh7OzM6+99hoXL17U9sfGxtKqVSscHByoV68e06ZNw9/fX9s/Z84cKlSogL29PeXKlWPevHnavvziW35x8K6NGzdSvnx5DAYDAwYM0GLu/SIiIvjPf/7Dxo0bCQgIoFSpUpiZmfHyyy+zfPlyXFxcgEf/jLhXVlYWH330EeXKlcPFxYWOHTsSHx+v7dfpdMybN4/q1atja2vLV199RYsWLUzqWLVqFVWrVi1Ue0+NEuL/a968ufriiy9Ur1691IIFC5RSSr399ttq1qxZqn///uq9995TSil18+ZN5eLior766iuVmZmpIiIilJ2dndq3b59SSqklS5Yob29vdfr0aZWamqoGDBigzMzMVHh4uFJKqc2bNysvLy916NAhlZOTo9atW6ecnZ3V9evXtX64ubmp3377TeXm5qrbt28rPz8/Va1aNXXhwgWVlpam2rRpo/r371/guWRnZysvLy81d+5cdeHCBaXT6dShQ4e0/ZMnT1bm5uZq6dKlKisrS6WmpqqlS5eqWrVqFfn7KsRdd8eYUkrl5OSoDRs2KHt7e3Xt2jWllFKXL19Wzs7Oas2aNSo7O1sdP35clSlTRu3cuVMpdef31tLSUoWFhans7Gy1bNkypdfrVXJyslJKqUmTJqlatWqpuLg4dfPmTdWmTRsFqMjISKWUUt98842qWbOmOnv2rMrKylJz585V5cqVUxkZGUoppfz8/FTFihXVX3/9pbKzs7Xtd40bN061b99epaamquzsbHXkyBGVmJiY77ne+5lxvy1btqgzZ86o3NxcdeTIEVW6dGm1cuVKbT+gAgIC1JUrV9TNmzdVnTp11OTJk5VSSvs8mDNnjsrIyFDR0dGqWrVq6rvvvnvk/w/xfGrQoIEaOXKkSklJUXZ2dmrdunVKqTvjp1OnTiZlHR0dtdjUsGFDNXXqVJWTk6PS09PVnj17tHKAOnLkiPY6MjJSAapz587q5s2bKjU1VSml1MqVK9XVq1dVdna2WrVqlbK2tlYXL15USikVHh6uHB0dtTru/Ty4deuWWr16tTIajSotLU0NHz5cVaxYUeXm5hbtmyPEY7r39/ZeEyZMUPXr139oHDt69Kjau3evyszMVFeuXFFNmzZVb775Zr71FyYm3n8tJ8SzrqAxdm8cWrZsmfL09FR//vmnSktLU6NGjVJVqlRRWVlZSimlmjZtqoKDg9Xt27fVmTNnVNmyZZWfn59W148//qhiYmJUbm6u2r17t7KxsdH+jisovhUUB3v06KFu3bql4uLilJeXl1q6dGm+5/Xhhx+qpk2bPvT8H+Uz4v64OmbMGBUYGKji4+NVRkaGGj16tEmbgGrYsKGKi4tT6enp6vr168rm/7V352FVVfv/wN/nKJMczjnMh0kQEE0tFMtCU5BwQgKrawqiIKSSmVrqzwKnrzkg3tTSTCsnFBy+zgJeDUUSM2+hWE6YBiIgCugBmafP7w+/7stmPJgFej+v5znPw9lr77XXPuw17LXXXltXV6iniYiGDh1KkZGRLabz78QdNkzwOAMcP36c+vXrR6WlpWRsbEx37twRXXzt2LGDunfvLtp20qRJNGnSJCIi8vDwoBUrVghhubm5BEBoFHt5edGaNWtE2/fv35+ioqKEdNS/0LO1tRU6kR6noVevXk0eS1xcHGlpaQkXwq+//jpNnTpVCF+4cGGDzhnusGF/NTc3N9LV1SWFQkG6uroklUpFeSUyMpJGjRol2iYsLIyCg4OJ6NF5++qrrwphtbW1pK2tTb/88gsREdnb29Pu3buF8J9++knUYdOjRw86ePCgKH5LS0v64YcfiOhRPmuskfDYggULyNXVlVJTU1s81uY6bOqbMWOGqDIGQEePHhW+L1myhLy9vYmIaM+ePdS7d2/R9t988w15eHhotC/2fLt8+TIBEM7RgIAA8vLyIqKWO2wGDRpEkyZNotu3bzeIt6mGat1ljXF2dhY6I5vrsKnvwYMHBICysrKajZ+xv1tT5+369evJ0dGxxXqsvgMHDpCjo2Oj8WtSJ3K7jT1v6rYV637q1jmenp4UEREhbFNeXk4GBgZ05swZyszMJACUl5cnhEdGRoo6bOrz9fWlJUuWEFHT9VtT9eDVq1eFZe+99x5Nmzat0X289957NGbMGNEyJycnoU18+PDhRrdrroyoW6/W1taSvr6+qI1aVlZGUqmUMjMzhWM4cOCAKP53331XuCmYlZVF2tradOfOnUbT0lb4kSjWwBtvvIHc3Fx89tlncHV1hUqlEoVnZWWJhtUBgL29PbKysgAAOTk5sLW1FcLMzc2ho6MjfM/IyEBYWBiUSqXwSU1NRXZ2trBO586dG6Srbjr09fXx8OHDJo9h06ZN8PLygqmpKQAgMDAQMTExKCsra3YfjP3Vli9fDrVajbKyMqSlpWHLli3YuHEjgEd5Iz4+XpQ3vvzyS9y5c0fYvm4+kEgk0NPTE/JC/bxX9+/H8QcEBIjif/DggZB3gebzxZw5czBw4EC8++67UKlUmDFjhihPaerYsWPo378/TExMoFAosGHDBuTn54vWaSq/Z2Rk4NKlS6JjmDVrFnJzc1udDvb82bRpE5ydneHs7AzgUdl/7NgxUf3SlM2bN6O8vBx9+/ZF9+7dRUPEm1I/v6xevRo9e/aEQqGAUqnEpUuXGpzbjSkrK8PUqVNhZ2cHuVwu1LGabMtYe5CdnQ0jI6MW67EbN27A19cXlpaWkMvlCAgIaPI816RO5LYcex49bivW/dRV/1pMR0cHlpaWyMrKQk5ODnR1dWFiYiKE188n0dHRcHFxgaGhIZRKJeLj4xvkQ03zlqbXZyYmJqLHkwAgLS0NarUa5ubmwryJrSkj6srPz0dJSQkGDRoklBcqlQra2tqiaTTqH1dwcDCioqJARIiKisLQoUMbXPu2Ne6wYQ1IpVJMmDABERERmDhxYoNwa2vrBq8JTk9Ph7W1NQDA0tJSNK/FvXv3UFFRIXy3sbHB559/LiqESkpK8Mknn4jS8KTy8vJw5MgRnDhxAiqVCiqVCp988gnUajX279/f5D7+zD4ZexKOjo4YOXIkYmNjATzKG2+99ZYobzx8+BDx8fEaxVc/79Wfh8nGxgb/+7//K4q/tLQUfn5+wjrN5QOZTIYVK1YgLS0NZ8+exYkTJ1r9WuLKykq8/fbbmDJlCrKzs1FYWIjQ0FCNJ36zsbFB3759RcdQVFSEy5cvtyod7PlTVVWF7du34/r160LZP27cONTU1GDr1q2QyWQoLS0V1i8tLUVRUZHw3cHBAVFRUcjNzcV3332H2bNnIyUlBcCjztHG1M0vycnJWLRoEaKiovDgwQOo1Wr06tVLo3P7888/R0pKCpKTk1FUVCTUsZrmC8baUnV1NQ4dOgR3d/cW67HQ0FBYWVnhypUrKCoqwo4dO5o8zzWpE7ntxv4b1b8Wq6ysRE5ODqytrWFpaYny8nJRJ0fd9mBmZiYCAwMRGRmJvLw8qNVqeHl5NciH9fNWU/WgpoYMGYKff/65wTVkfa0pI+oyNjZGp06dcO7cOVGZUVZWhv79+wvr1T+uIUOGoKamBklJSdi2bRuCg4Of6Pj+SlzKsUZ99NFHOH78uDDpYl1eXl64d+8e1q9fj+rqapw+fRoxMTGYMGECAMDPzw9fffUV0tLSUFZWhk8//VSUOaZNm4aVK1ciJSUFRITS0lIkJCSI7vL/GVFRUTAyMsK1a9eQmpqK1NRUXLp0CUFBQc2+McTc3Bx37tx5ohEDjD2JW7duIT4+Hi+++CIAYPz48Th58iT27duHqqoqVFVVITU1FT///LNG8fn5+SEiIgI5OTlQq9VYvHixKPyDDz7AggULhEmOi4qKcOjQoWZHq9UVGxuL69evo7a2FnK5HFpaWujYsWOT69fU1KC8vFz0qaioQHl5OYyNjaGjo4Nz584hJiZGo/0DgLe3N+7evYv169ejvLwcNTU1SEtLEyaOZf+9Dh8+jKKiIpw/f14o+y9evIj58+dj8+bN6NOnD86ePYtr166hvLwcn376qagBGhUVhbt370IikcDQ0BBSqVQ4v83NzXHz5s1m919UVISOHTvC1NQUtbW12Lx5My5duqRR2ouKiqCrqwtDQ0MUFxcjLCzsyX8Ixv5G165dQ2BgIAoLC/Hxxx+3WI8VFRXBwMAAcrkct2/fxsqVK5uM+8/WiYw9rwICArBu3TpcuXIFFRUVmDdvnjA5sI2NDQYMGICwsDCUlZXh999/xzfffCNsW1xcDCKCmZkZpFIp4uPjcfz48Rb3qUk92BwPDw+MHDkSPj4+SEpKQllZGWpra3HhwgVRO7Q1ZURdUqkUoaGhmDVrljCipqCgQPRyjqa2CwoKwsyZM1FQUABvb+8nPsa/CnfYsEYZGRnB09MTWlpaDcIMDQ1x9OhR7NixA8bGxpg8eTK+/vprvP766wAeDS0LCAjAwIEDYW9vjz59+sDAwEDY3tvbGxEREZg0aRIMDQ3RpUsXfPHFF0/tLS+bNm3C+++/DysrK+Euq0qlwqxZs3Dq1KkmCxsPDw+89tprsLKyglKp5LdEsb/E3LlzhTeRDRgwAJ6enliwYAEAwMrKCseOHcPGjRthYWEBc3NzfPDBB6JRAM2ZN28eXn75ZfTq1Qu9e/du8EacadOm8+fqZgAALwBJREFUISgoCG+//TbkcjleeOGFVnWW3LhxA8OHDxfegOPq6or333+/yfXXrVsHPT090cfAwABfffUVJk+eDLlcjqVLl2LMmDEap0EmkyEhIQEnTpyAnZ0djI2N4e/vz49EMWzatAl+fn7o3r27qOyfPn06cnJyIJFIMGXKFPTv3x+Ojo548cUXRXVTQkICnJ2dIZPJ4OPjg5UrVwqPVn322WeYPn06DA0NERER0ej+hw8fjnfeeQcvvvgiLC0tcfnyZQwYMECjtH/88cfo0KEDzM3N0atXL7i6uv75H4Sxv8jcuXNhYGAAhUKBt99+GyqVCr/88gvMzc1brMdWrVqF2NhYyOVy+Pr64p133mlyP3+2TmTseTVhwgR8+OGH8Pb2hkqlwsWLF3HkyBHhJkNMTAz++OMPmJubY+zYsQgICBCmp+jRowfCw8Ph4eEBY2Nj7N69Gz4+Pi3uU5N6sCW7du3C+PHj8cEHH8DY2BgWFhYIDQ3FkiVLMHz4cACtKyPqW758OVxdXeHh4QEDAwP07dtXo86oiRMn4tdff0VAQECj175tTUI83pYxxhhjjDHGGHvuLFu2DCdPnkRCQkJbJ6VdKi0thZmZGX788Ue89NJLbZ2cBniEDWOMMcYYY4wx9hw4f/48rl27BiJCSkoK1q1bh9GjR7d1stolIsLatWvRu3fvdtlZAwBNTz7AGGOMMcYYY4yxZ0ZeXh5CQ0Nx9+5dmJqaIiQkBCEhIW2drHanpqYGSqUSJiYm2LdvX1snp0n8SBRjjDHGGGOMMcZYO8OPRDHGGGOMMcYYY4y1M9xhwxhjjDHGGGOMMdbOcIcNY4wxxhhjjDHGWDvDHTaMMcYYY4wxxhhj7Qx32DDGGGOMMcYYY4y1M9xhwxhjjDHGGGOMMdbOcIcNY4wxxhhjjDHGWDvDHTaMMcYYY4wxxhhj7Qx32DDGGGOMMcYYY4y1M9xhwxhjjDHGGGOMMdbOcIcNY4wxxhhjjDHGWDvDHTaMMcYYY4wxxhhj7Qx32DDGGGOMMcYYY4y1M9xhwxhjjDHGGGOMMdbOcIcNY4wxxhhjjDHGWDvDHTaMMcYYY4wxxhhj7Qx32DD2hJYtWwY/Pz/hu0QiQWpqatsliLFmPG/n56lTp6BUKts6GYw1q2fPnoiNjW3rZGjseSsnWPvUVvkiNDQUc+fO/dv2d+TIEdjZ2UEmk+HgwYN/234ZY88X7rBhAnd3d6xZs6atk9EmfvnlF2hpaaG4uFhY9u2330IikSApKUlY9ttvv0EqlSI/Px9hYWHYuXNnWySXPcOSk5MxYsQIGBoaQqlUwtnZGZGRkaisrGzrpDUpKCgI2trakMlkUCqVePnll/Gvf/2rrZPFWAPu7u7Q0dGBTCYTPiYmJm2WnsuXL8Pb27tN9h0UFISZM2c+9Xh/+OEHSCQSjS987ezs+GL1OdLY/zMjIwMSiQRqtVqjONoqX2zYsAErVqwA0Po0P4mPP/4YixcvRnFxMUaNGvWX7Yc9f5KTk+Hl5QUjIyPI5XI4OTnhww8/REZGRlsnrV1avHgxJBIJjh492uK6f0fef9q4w4a1GSJCTU1NWycDAODi4gJ9fX0kJycLy06dOoUXXngBiYmJomUvvvhim14AsGdXbGwsRowYgWHDhuH333+HWq3G7t27ceXKFdy5c6etk9esqVOnori4GPn5+fDz88M777zTZpVddXV1m+yXPRtWrFiB4uJi4ZOfn/+3p6GmpgZE9Lfv9++wadMmGBkZYdu2bc3mxef5N2DtU3urG9LT0/HSSy+1dTLYM+bIkSMYMWIEhg4diqtXr6KoqAhJSUmwt7cXXZPU1d7O/b8TEWHLli0wMjLCpk2bml33Wf2duMOGaWTVqlXo2rUrDAwM4ODggHXr1glhoaGh+OSTTwA8yjSmpqYYO3asEN63b1/s378fwKM7M8uXL8drr72GTp064cqVK7h37x7GjRsHS0tLWFpaYubMmaioqADwn8cevvvuO9jY2MDY2Bj/7//9P1Havv/+e7z66qtQKpWwsLDA8uXLhbCEhAT069cPSqUSPXv2xOHDhxs9PqlUikGDBokKwqSkJMybN69Bh83gwYMBAIsWLWryjsn58+fx2muvQS6Xw8TEBG+++aYQduPGDQwbNgxGRkZwcHAQjWraunUrevfujc8++wxmZmYwNzf/rx319LwhIkyfPh1z587FzJkzhU6/7t27Y+vWrbC1tQUABAQEwNLSEnK5HH379hWdf+np6fD09IRCoYCRkREGDBiA0tJSAA0fZVizZg3c3d0bTcuFCxfw+uuvw8jICKampvDz80NBQYFGx9GxY0dMmTIFpaWluHnzJh4+fIjJkyfDwsICFhYWCA0NRUlJCYDWlQ3FxcWYNm0aOnfuDDMzM0yYMAGFhYUA/nM3ZMuWLXB0dISVlZUQR3Nlw44dO/DCCy9AqVTi9ddfx4ULF4Sw+neJDx48CDs7O+H7qlWr0LlzZxgYGMDOzg7fffedEKZpucLal/Pnz0OpVOLSpUsAgAcPHsDGxgZRUVEAHo1ICQ4OxltvvQWZTIaXXnpJ1IlfVVWFBQsWwMHBAcbGxvDx8UFOTo4QLpFIsG7dOvTq1QudOnVCcXGx6Dx7XL4vXLgQJiYmUKlU2L17N86cOYNevXpBoVAgJCQEtbW1ojQPHjwYRkZGcHR0xLfffiuELVq0CG+++SamTZsGpVKJzp07Y/fu3QCAL7/8EtHR0Vi/fj1kMhl69uwJAIiOjkavXr1gYGCAzp07Y/78+a3qVCkqKsLevXuxbt06FBcXIy4uThRe/zd4++23kZmZCT8/P8hkMoSGhmq8L/bscnd3x6effophw4ZBJpPBxcUFv/32mxD+OF9UVVXB1NQUP/zwg2j7Hj16YNeuXQCgURvx66+/RufOneHq6oqKigoEBwfDxMQECoUCvXr1ws8//wxAPOqsX79+AABra2vIZDJER0ejT58+2LZtmygtw4YNQ2RkZKPHeffuXbz77rswNTVF586dER4ejurqahQUFEAmk6Gmpgb9+/eHTCYT0sxYcx63FcPCwjBz5kyYm5sDACwsLPDRRx9h4sSJAJpuFzVXZwDArl278NJLL0GpVOKVV17Bjz/+KIS1lG+f1rVgc/G89dZb+J//+R9RmqdMmYKpU6c2+ZudOHEC2dnZ2LhxIw4fPoy8vDwhrLEyorG83+4RY//Hzc2NVq9e3WjY3r17KTMzk2pra+nkyZOkq6tLycnJRES0e/du6tevHxERpaamkr29PalUKiIiun//PnXs2JHy8/OJiMjW1pacnJzo2rVrVF1dTeXl5fTqq6/Sxx9/TCUlJZSfn0/u7u40b948IiJKTEwkqVRK06dPp7KyMrpy5Qp16tSJEhMTiYjo/PnzpKenR3v37qXKykpSq9V09uxZIiK6ePEiKZVKOnHiBNXU1NDp06dJLpfTtWvXGj3GVatWCcdx/fp1cnBwoPLyclIoFFRaWkq1tbVkYmJChw4dIiKihQsXkq+vr7A9ALpw4QIREbm6utKSJUuopqaGysvLKSkpiYiIqqqqqFu3bjRnzhwqKyujixcvkoWFBUVHRxMR0ZYtW6hjx44UGRlJlZWVlJiYSB06dKAbN2606n/J2p+0tDQC0OL/cvPmzaRWq6myspIiIyPJyMiIioqKiIjIz8+PpkyZQpWVlVRZWUlnzpyhiooKIhKff0REq1evJjc3N+F73fDU1FQ6ffo0VVZWUm5uLg0cOJDee++9JtMUGBhIM2bMICIS0mVgYECFhYU0ceJEGjx4MOXn51NeXh65ubnRpEmTiKh1ZcPo0aPJz8+PHjx4QMXFxTR27FgKCAggIqL09HQCQKNGjaIHDx5QSUlJi2XDDz/8QDKZjJKSkqiyspJWr15NpqampFariehRWXTgwAHhGA8cOEC2trbC/0pPT4+uXr1KRES5ubl08eJFImp9ucL+Xs3VY0REn3/+OfXs2ZNKS0vprbfeIn9/fyEsMDCQtLW16fDhw1RVVUVff/01GRoa0oMHD4iIaM6cOeTh4UE5OTlUUVFBs2bNooEDBwrbAyBXV1fKzs6m8vJyqqmpEZ1nj8v3VatWUVVVFX3zzTckl8vp7bffpvz8fMrKyiIzMzPat28fERHduXOHjIyMaPfu3VRdXU2//fYbWVhYUEJCAhE9qoO0tLQoJiaGqquradu2bSSTyYTyom6+fSw+Pp7S0tKotraWLly4QGZmZrRjxw7RMdQtR+rbsGEDmZqaUlVVFU2YMIHefPNNUXhLvwF79jX2/3xcRj/OK25ubmRpaUnnz5+nqqoqmjRpkqg+qhvHBx98IKp/fv75Z5LL5UK7S5M24pQpU6ikpIRKSkpo48aN5OLiQg8ePKDa2lpKS0ujzMxMIhLnifppJiJau3atKJ1ZWVmkra1NOTk5jf4WHh4e5O/vTw8fPqSMjAzq0aMHLV26VAhvKT8xVt+1a9cIAN28ebPZ9RprF7VUZ8TFxZGVlRWlpKRQTU0N7du3j4yMjIR2WEv59mldCzYXz5EjR6hLly5UW1tLRERlZWWkVCrp3//+d5O/xdixY+mtt96i2tpasrOzo88//1wIa6yMaCzvt3fcYcMELTV06/L19aUlS5YQEdHdu3epY8eOVFhYSKtWraI5c+ZQr1696PLly7R//37q3bu3sJ2tra1oH//+97/JyMiIampqhGXHjx8ne3t7InqU0SQSCZWUlAjhnp6e9M9//pOIiEJDQ2nixImNpnHq1Kk0c+ZM0TJ/f39avHhxo+tfuHCBOnToQIWFhfTNN99QcHAwERG5u7vTiRMn6NdffyWpVCpk8OY6bAYNGkSTJk2i27dvi/aRnJxMcrlcuMgmIlq6dCkNGTKEiB416M3NzUXbODo60t69extNM3t2JCcnEwAqKytr1XZKpVKoyCZMmEA+Pj50/fr1Buu1psOmvgMHDpCjo2OTaXh8IatQKMjU1JQGDhxIp06dopqaGtLR0aGffvpJWPfMmTOko6NDNTU1GpcN9+7dI6lUSgUFBUI8169fJy0tLaqurhYq17rpb6lseO+99yg0NFR0HE5OTkLnaHMdNjdu3CBdXV3au3cvlZaWiuJobbnC/l5ubm6kq6tLCoVC+Hh6egrhtbW1NHz4cHrppZfI3t6eCgsLhbDAwEAaMWKEKL7u3bvT9u3bqba2lvT19Sk1NVUIKysrI6lUKlwMAmhwIVu/w+ZxA5aIqKSkhADQ0aNHhWWjR4+m8PBwIiKKjIykUaNGieILCwsT6qaFCxfSq6++Kjo2bW1t+uWXX4Tjqd9hU9+MGTNEF8stXWC+8sorwvmfkJBAHTp0EF3MtvQbsGefph02c+fOFcKTk5NJJpM1Gse5c+dIoVAIdeP06dOFc1yTNmL9C6/NmzdT165d6ccffxRtR9Ryh839+/dJT0+P/vjjDyIiWrZsGY0cObLR3yErK4sA0J07d4Rl0dHR1LVrV+E7d9iw1mqsrbho0SJSKBSkr69Po0ePJiJqtF3UUp3h5eVFa9asEYX379+foqKiiKjlfFvfk14LNhdPdXU1WVpaCjffYmJiqGfPnk1ue//+fdLR0aGDBw8SEdG8efOoR48eQnhjZcSz2GHDj0QxjURHR8PFxUWYKDU+Pl6YF8DMzAzdunXD6dOncfLkSQwePBhvvPEGEhMTcfLkSXh4eIji6ty5s/B3RkYG1Go1jIyMoFQqoVQq8Y9//AN3794V1pHL5ejUqZPwXV9fHw8fPgQA3Lp1C127dm00zRkZGdiwYYMQr1KpxKFDh0RD2OtydnaGQqHA6dOncerUKeFxEjc3NyQmJuLUqVPo06ePRm+m2bx5M8rLy9G3b190795dGO6XlZUFS0tLaGtrC+va29sjKytL+K5SqURx1T1e9ux6/AhUdnZ2k+vU1tYiPDwcXbt2hVwuh1KpRGFhoZDXVq5cCSsrK3h6esLOzg6LFi0SPT6hqRs3bsDX11d49CogIKDFeT7ef/99qNVq3Lt3Dz/88APc3NyQl5eHiooK0aNE9vb2qKioQH5+vsZlQ0ZGBmpra2Fvby/k1VdeeQVSqRS5ublC3HXLDqD5siErK0uULgDo0qWLKK81xcHBAdu2bcO6detgbm6OoUOHCo+btbZcYX+/5cuXQ61WC5/vv/9eCJNIJAgNDcWvv/6KqVOnQi6Xi7Z9/Ghi3e/Z2dnIz89HSUkJBg0aJPzfVSoVtLW1cfv2bWH9+udofY+HtwMQzt26Zf7jR6mAR+dafHy86Fz78ssvRfNd1d1WIpFAT0+v2fri2LFj6N+/v/C4yIYNGzSe4+e3337Dzz//jMDAQADA4MGDYWlp2eARkpZ+A/Zs09LSQlVVlWjZ4+9aWlrCsrrnpr6+vuilDnX169cPKpUKhw8fRnV1NXbt2oUJEyYA0KyNaGBgIGqXjR8/HkFBQQgNDYWJiQmCgoI0PscNDQ3h6+srnNPbtm0THkGpLysrC7q6uqLjrN+eY6y1HrcV67YpFi5cCLVajdmzZzd4QUX9a6rm6oyMjAyEhYWJwlNTU0Xt0uby7dO6Fmwung4dOmDChAnYunUrgEePEjeVB4FHj77L5XJ4eXkBACZMmIArV67gp59+EtapX0Y8i7jDhrUoMzMTgYGBiIyMRF5eHtRqNby8vETPvQ8ePBjff/89zp49i4EDB8LDw0PIpI/nfHlMKv3PaWdjYwMzMzNR47qwsLDJir0+W1tb3Lhxo9EwGxsbzJgxQxR3cXExvv7660bXl0gkcHNzw6lTp5CUlAQ3NzcAEJadOnWqQedTUxwcHBAVFYXc3Fx89913mD17NlJSUmBtbY2cnBxRYyc9PR3W1tYaxcueXU5OTrCzsxOey29MTEwMYmJiEBcXh8LCQqjVaigUCiGvmZmZYf369bh16xZiY2OxYcMGHDhwAMCjivXxfDYAmp3EODQ0FFZWVrhy5QqKioqwY8eOJ5oc1NTUFNra2qK3FqSnp0NHR0dodGhSNtjY2EAqlSInJ0eUX8vLy0Xz1dQtO1pibW3d4G0KGRkZQl6TyWTN/l7vvvsuEhMTcffuXTg7O2P8+PFCWltTrrD25cGDB/jwww8xefJkLFu2DJmZmaLwW7duib5nZmbCysoKxsbG6NSpE86dOyf635eVlaF///7C+q05R1tiY2ODt956S7S/hw8fIj4+XqPt66elsrISb7/9NqZMmYLs7GwUFhYiNDRU47z/eDLH4cOHQ6VSwdLSEvfu3cPmzZub3e/T/E1Y27O1tUV6erpo2c2bN2FiYgJ9ff0ninP8+PHYvn07/vWvf0FPTw+DBg0CoFkbsf751bFjR4SFheHixYu4evUqMjMzG8yJ0dh2j4WEhCAqKgo//vgjCgoKRHMQ1mVtbY3y8nJR5xG359if5eTkBFtbW+zZs0ej9etfUzVXZ9jY2ODzzz8XhZeUlAhzzzTnaV0LahJPcHAw9u3bh7S0NCQlJQntr8Zs2rQJhYWFsLGxgUqlwsCBAyGRSESTDz8PddKzl2L2l6qurkZ5ebnwqaioQHFxMYgIZmZmkEqliI+Px/Hjx0XbDR48GFu2bIGTkxNkMhnc3Nxw8uRJXL9+Xah4G/PKK6+gc+fOmDdvHh4+fAgiwq1btzR6LRsATJo0CTt37sSBAwdQXV2NwsJCoVd1ypQp2LJlCxITE1FTU4OKigqcPXsWV69ebTK+wYMHY8eOHdDW1hZ6rV977TWkpqaKJhxuSVRUFO7evQuJRAJDQ0NIpVJ07NgR/fr1g7m5ORYsWICKigpcunQJ69atE+5YsueXRCLB2rVrERERgbVr1wqT/F6/fh0hISG4desWioqKoK2tDRMTE1RWVmLx4sUoKioS4tizZw8yMzNBRFAoFOjQoQM6duwI4NGbzrZv347q6mqkpqZi+/btTaalqKgIBgYGkMvluH37NlauXPlExySVSuHv74/w8HDcv38fBQUFCA8Px/jx44UKUZOyQaVSYdSoUZg2bZpwlyU3N1fojHoSAQEBiI6OxpkzZ1BdXS385o/vwri4uGDnzp0oLy/HH3/8ga+++krYNi0tDd9//z3KysqE15k//p2fpFxh7cekSZMwcOBAbNy4ERMnTsS4ceNEbys8efIk4uLiUF1djW+//RZ37tzByJEjIZVKERoailmzZgkjagoKCoRJfv8K48ePx8mTJ7Fv3z5UVVWhqqoKqampwgSqLTE3N8cff/whfK+oqEB5eTmMjY2ho6ODc+fOISYmRqO4KisrsWPHDkRERCA1NVX4nDt3Dn/88UeDSWPrp+PmzZsa7Ye1fwEBAfjqq69w4cIFoc22aNEijBs37onjHD9+PI4fP47Vq1cjICAAEokEwJO1EU+ePInU1FRUV1dDX18furq6Qvldl6mpKaRSaYNz84033gARYerUqRg3bpxoRHRdVlZWGDx4MGbPno2SkhJkZmZi2bJl3J5jf4pEIsEXX3yBpUuX4ssvv8S9e/cAAHl5ebh8+XKz27ZUZ0ybNg0rV65ESkoKiAilpaVISEjQaFTY07oW1CSerl27wsXFBWPGjMHw4cNhZmbWaJpSUlJw8eJFfP/996J6aePGjdi1a5fwAoz6msr77Rl32DCROXPmQE9PT/h069YNPXr0QHh4ODw8PGBsbIzdu3fDx8dHtJ27uzsePnwojEBRKBTo2rUr+vbt22DIeV0dOnTAkSNHkJ2djRdeeAEKhQIjR45sctRMfS4uLti3bx+WLl0KIyMjvPDCC0hKSgIA9OnTBzt37sS8efNgamoKKysrzJ8/v9mZ+gcPHozc3FxhdA0A6OnpoXfv3igqKsLAgQM1SldCQgKcnZ0hk8ng4+ODlStXwtnZGVpaWoiNjUVKSgpUKhV8fHzw8ccfw9/fX6N42bPN29sbR48eRVxcHBwcHITh3d27d4eFhQUCAwPRs2dP2Nrawt7eHnp6erCxsRG2T0lJEd444erqipCQECEvrl27FmfPnoVSqcTcuXObbTSuWrUKsbGxkMvl8PX1xTvvvPPEx/TFF1/Azs4OPXr0QM+ePeHo6IhVq1YJ4ZqWDVu3bhUehZLL5Rg4cCBSUlKeOF1ubm5Yu3YtQkJCYGxsjF27duHo0aPCsNglS5ZArVbD1NQU/v7+whB84NHF6fz582Fubg5jY2OcPHlSGJ77JOUK+3vNnTsXMplM9CkoKMDGjRtx/vx5YTTU8uXLUV5ejiVLlgjb+vv749tvvxWGkh86dAiGhobC+q6urvDw8ICBgQH69u3boKH5NFlZWeHYsWPYuHEjLCwsYG5ujg8++EDUiduc9957D9nZ2TA0NMRLL70EAwMDfPXVV5g8eTLkcjmWLl2KMWPGaBTXwYMHUVlZialTp0KlUgkfZ2dnjBo1SvQWtfrCwsKwbt06GBoaNvumD/ZsCAwMxOzZszFu3DgoFAoMHjwYgwYNwrJly544zs6dO6N///44efKk6G76k7QR7969Cz8/PyiVSnTp0gUKhQILFy5ssJ6enh4WLlyIESNGQKlUCp2XEokEEydOxMWLF5t9FAN4NCq2rKwMtra2GDBgAEaOHNngbYWMtZavry/i4uIQHx8PJycnoU1kZmaG1atXN7ldS3WGt7c3IiIiMGnSJBgaGqJLly744osvNHq0/mldC2oSD/BopFtLeXDTpk1wd3fHoEGDRPVSUFAQDAwMmryh0lTeb88k9CTj4BljjDHGniNBQUFQKpVYs2ZNWyeFMdaGoqKisGbNGpw/f76tk8LYf6UffvgBo0ePRlZWlmhurP9WPMKGMcYYY4wx9l+vuLgYX375JY8GY6yNVFZW4vPPP8ekSZO4s+b/cIcNY4wxxhhj7L/a9u3bYW5uDisrK56LhrE2kJSUBENDQ+Tn52POnDltnZx2gx+JYowxxhhjjDHGGGtneIQNY4wxxhhjjDHGWDvDHTbsmWFnZ4eDBw8CePRGmd69e7dpehhjjLH6Dh48CDs7uyfe/vTp07C2tn56CWKsnanfhqvbvmOM/Tmcv54/3GHDGggODoZEIsHVq1dbXPfUqVPCa3KbU1ZWhvnz56Nbt27o1KkTLCws4O7uju3btz+FFDP2bPkr8lhzkpOTMWLECBgaGkKpVMLZ2RmRkZGorKz8U/ECwKJFizBq1Kg/HQ9jT4O7uzt0dHREr/Rev359WyerSRkZGZBIJFCr1cKygQMHIisrq+0SxVgz3N3dIZFIkJCQIFq+cuVKSCQSzJw5s20SxthzJDk5GV5eXjAyMoJcLoeTkxM+/PBDZGRktHXSWBvgDhsmUlxcjD179sDIyAibNm1qdt3q6mqN4qyqqsKQIUNw6tQpREdHQ61WIzMzE4sXL0ZcXNzTSHaraJpuxv4Kf0Uea05sbCxGjBiBYcOG4ffff4darcbu3btx5coV3Llz50/HrwnOc+zvtGLFChQXFwsfftsLY09Xt27dsGXLFtGyrVu3onv37m2UIs1xfcTauyNHjmDEiBEYOnQorl69iqKiIiQlJcHe3h6JiYl/a1o4v7QP3GHDRHbt2gV9fX2sWLECUVFRqKqqEsIeD7FbuHAhVCoVhgwZghEjRqCwsFC4k3n69OkGcUZHR+P69euIjY3Fyy+/DG1tbWhpaWHQoEHYtWuXsN7x48fx8ssvQ6FQwMLCAlOnTkVZWZlG6S4uLsa0adPQuXNnmJmZYcKECSgsLATwnzuYW7ZsgaOjI6ysrPDRRx9h4sSJojiWL18OLy+vJ/nZGNPY08hj6enp8PT0hEKhgJGREQYMGIDS0tIG+yIiTJ8+HXPnzsXMmTNhYmICAOjevTu2bt0KW1tbAMDNmzfx5ptvwtTUFLa2tliyZAlqa2tFafrss89gZmYGc3NzrFmzBsCjRz+WLVuG2NhYIX0AEBQUhJCQELz77ruQy+X4+uuvUVVVhQULFsDBwQHGxsbw8fFBTk7OX/lTMyY4fvw4+vTpA4VCARcXF9HoAHd3d+GcBoDU1FRIJBJR+Keffophw4ZBJpPBxcUFv/32mxCelZWFoUOHQi6Xo2/fvrhy5Ypo36tWrULXrl1hYGAABwcHrFu3Tgjr168fAMDa2hoymQzR0dENRtU9fPgQkydPhoWFBSwsLBAaGoqSkhIA/6nftm/fDkdHRyiVSgQFBYnKFcaetrFjx+Lo0aNCO+vcuXMgIrz66qvCOs3VK425fPkyXFxcIJfLMWzYMFH9cOPGDQwbNgxGRkZwcHAQ5dfGRnkqlUqcOnVKCPf29sb7778PIyMjzJ07F0FBQZg0aRLGjh0LAwMDdOvWTVgfANdXrM08breFhYVh5syZMDc3BwBYWFiIrl0CAgJgaWkp1Dut6chJSEhAv379oFQq0bNnTxw+fFgIq99+W758OXR1dZGeni6sU15eDkNDQ/z73/9+SkfNWsIdNkxk06ZNGDduHMaOHYvS0lIcOXJEFH7p0iV07NgRmZmZiIuLw9GjR6FQKIQ7mQMHDmwQ57FjxzB8+HAoFIpm962np4dvv/0W9+/fx5kzZ5CYmIhVq1ZplO7g4GDcv38fv/76K9LT01FVVYVp06aJ1jl8+DB++eUXpKenIyQkBHv37kVxcbEQvm3btgadOIw9bU8jj4WHh8PR0RH5+fm4e/cuVq5ciY4dOzbY1++//4709HT4+fk1mZ6ysjK88cYb8PDwQHZ2Nk6fPo1du3aJ7p5evnwZurq6yM7Oxu7duzF79mzcvHkTo0aNQlhYGLy9vYX0PbZz506EhIRArVYjJCQE4eHhOHPmDJKTk3Hnzh04OTlh7NixT+EXZax5N2/ehK+vL+bPn4+CggKEhYXBx8dH1ABtSVRUFCIiIqBWq/Hyyy/jww8/FML8/f1hYWGB3NxcREdH49tvvxVta2tri5MnT6KoqAjfffcd5syZgzNnzgCA0ODNyspCcXExxo0b12DfM2bMwI0bN3Dp0iX89ttvuHbtGj766CPROnFxcTh//jyuXLmChIQEREdHa3xsjLWWUqnE8OHDsXPnTgDA5s2bRe0nTeqV+r777jvExMQgNzcXKpVKyAvV1dXw9vaGs7MzcnJycODAAURGRiImJkbj9P7rX//Cq6++inv37uGzzz4D8OjmyeTJk6FWqzF+/HgEBQUJ63N9xdrK9evXkZGRgTFjxjS73htvvIGrV6+ioKAAY8eOxT/+8Q88fPiwxfh//fVXjB49GhEREbh//z42btyI8ePHIy0tTVinbvtt1qxZ8Pb2xrZt24TwAwcOwNLSUrjhwP4GxNj/uXz5MgGg1NRUIiIKCAggLy8vIXzLli1kZGRENTU1wrLExERSKBTNxuvp6Ulz584VvpeXl5NCoSCFQkE6Ojp08eLFRrdbvXo1eXp6Ct9tbW3pwIEDQlqcnZ2JiOjevXsklUqpoKBAWPf69eukpaVF1dXVlJ6eTgDowoULovj79etHW7ZsISKiH3/8kYyMjKi8vLzZY2Hsz3haeWzChAnk4+ND169fb3Z/ycnJBIDKysqaXGfPnj3Uu3dv0bJvvvmGPDw8hDSZm5uLwh0dHWnv3r1ERLRw4ULy9fUVhQcGBoqW1dbWkr6+vnDcRERlZWUklUopMzOz2WNgrDXc3NxIV1dXqGMUCgUtWbKEhg8fLlpvyJAhtHTpUmGb1atXC2EXLlygus0jNzc3UR2WnJxMMpmMiIgyMzMJAN29e1cIj4iIIFtb2ybT6OvrS0uWLCEiEuqnBw8eCOF183xNTQ3p6OjQTz/9JISfOXOGdHR0qKamRtj+6tWrQvh7771H06ZNa+GXYuzJPM4vx48fp379+lFpaSkZGxvTnTt3KDAwkGbMmKFRvfK4DUf0qH23YsUK4Xtubi4BoNu3b1NycjLJ5XKqqKgQwpcuXUpDhgwhosbrIIVCQYmJiUJ43X0RPaqjxowZI3zPysoiAJSfn8/1FWtTjbXbFi1aRAqFgvT19Wn06NGNbqdUKik5OZmIGs9fj6+fpk6dSjNnzhRt6+/vT4sXLyaihu03IqL4+Hjq0qUL1dbWEhHR0KFDaeXKlX/mMFkr8QgbJti0aROcnZ3h7OwMAAgMDMSxY8eQnZ0trGNlZQWptHWnjYmJiWgoqY6ODtRqNdRqNSoqKoQhsj///DM8PT1hbm4OuVyOsLAw5Ofntxh/RkYGamtrYW9vD6VSCaVSiVdeeQVSqRS5ubnCep07dxZtFxwcjK1btwJ49NiHv78/dHR0WnVsjLXG08pjK1euhJWVFTw9PWFnZ4dFixY1OtT88SNQdeOvLyMjA5cuXRLyjlKpxKxZs0R5R6VSibbR19dv8U5O3fyWn5+PkpISDBo0SNiHSqWCtrY2bt++3Ww8jLXW8uXLhTpGrVYjKyurwVub7O3tWzWxb908oK+vL4wmy8nJga6uLszMzITwx48aPhYdHQ0XFxdh0u/4+HiN6jYAyMvLQ0VFhSj99vb2qKioEMVRP32a3Gll7M944403kJubi88++wyurq6ic1CTeqW+uvnG3NwcOjo6yM7ORlZWFiwtLaGtrS2Etzb/1m//AQ3zDPDo8UOur1hbetxuq3vdtHDhQqjVasyePRuVlZWora1FeHg4unbtCrlcDqVSicLCQo2vmTZs2CDKm4cOHRLtr35+GTZsGKqqqpCUlITs7GwkJSVh/PjxT+mImSa4w4YBePS87vbt23H9+nWoVCphOGpNTY3QqQGgwYWkJp03Q4YMwbFjx1BUVNTsen5+fhg8eDD++OMPFBUVYdmyZSCiFuO3sbGBVCpFTk6OqJFeXl4OKyurJtPq5+eHX375BVeuXMGePXsQHBzc4r4Ye1JPM4+ZmZlh/fr1uHXrFmJjY7FhwwYcOHCgwXpOTk6ws7MTzRVVn42NDfr27SvKO0VFRbh8+bJGx9VUGVB3ubGxMTp16oRz586J9lNWVob+/ftrtB/GnpS1tXWDN2ukp6cLr86WyWSiOaBaMxm3paUlysvLce/ePWFZZmam6O/AwEBERkYiLy8ParUaXl5eQt3WUh1qamoKbW1tUfrT09Oho6MjNOwZawtSqRQTJkxAREREg8fJn6ReuXXrlvD3vXv3UFFRASsrK1hbWyMnJ0c0L1Nz+be0tLRBe7M1Nxq5vmJtycnJCba2ttizZ0+T68TExCAmJgZxcXEoLCyEWq2GQqHQ+JppxowZonO7uLgYX3/9tbBOY+3QwMBAbN26FVFRURg2bJgwtw77e3CHDQPwaH6XoqIinD9/HqmpqUhNTcXFixcxf/58bN68uclCwNzcHA8fPkReXl6TcQcEBMDBwQFvvvkmUlJSUFlZierqaiQnJ4vWKyoqglKphL6+Pq5evSoqPJqjUqkwatQoTJs2Tehdzs3NbfQCti65XI533nkH/v7+sLW1RZ8+fTTaH2NP4mnmsT179iAzMxNEBIVCgQ4dOjQ6h41EIsHatWsRERGBtWvXoqCgAMCjZ6RDQkJw69YteHt74+7du1i/fj3Ky8tRU1ODtLQ00QSMzTE3N8etW7dQU1PT5DpSqRShoaGYNWuWcIeyoKAAu3fv1mgfjP0ZY8aMwalTp3Do0CHU1NRg//79OH36tDAnhYuLC/bv34/CwkLcu3cPkZGRGsdtY2ODAQMG4JNPPkFZWRnS0tKwceNGIby4uBhEBDMzM0ilUsTHx+P48eNCuKmpKaRSKW7evNlo/FKpFP7+/ggPD8f9+/dRUFCA8PBwjB8/vtWjXRl72j766CMcP34cb775pmj5k9QrGzduRFpaGsrKyjB37lwMGjQI1tbW6NevH8zNzbFgwQJUVFTg0qVLWLduHQIDAwE8yr9nz57FtWvXUF5ejk8//VQ0aXhrcX3F2pJEIsEXX3yBpUuX4ssvvxRuBuTl5QkdnkVFRdDW1oaJiQkqKyuxePHiFm+KPzZlyhRs2bIFiYmJqKmpQUVFBc6ePYurV682u11wcDD279+PTZs28XyfbYBrewbg0aMafn5+6N69u3D3X6VSYfr06cjJyWly9vFu3bohJCQEL7zwApRKZYNOGADQ1tbG999/j9dffx1jx46FQqGAjY0NwsPDER0djRdffBHAo8r6n//8J2QyGUJDQ1s1wdvWrVuFR6HkcjkGDhyIlJSUFrcLCQnBxYsXufBhf7mnmcdSUlLQv39/yGQyuLq6IiQkBD4+Po1u7+3tjaNHjyIuLg4ODg5QKpX4xz/+ge7du8PCwgIymQwJCQk4ceIE7OzsYGxsDH9//2aHrtc1evRoyOVymJiYiN5sU9/y5cvh6uoKDw8PGBgYoG/fvqILV8b+Ko6Ojti/fz8WLlwIQ0NDLF68GAcOHIC9vT2ARxedFhYWsLGxgYeHR4uTPdYXExOD27dvw8zMDP7+/qLRmj169EB4eDg8PDxgbGyM3bt3i/Kqnp4eFi5ciBEjRkCpVDY6keoXX3wBOzs79OjRAz179oSjo6PGE/Iz9lcyMjKCp6cntLS0RMufpF4JDg6Gn58fzM3NkZ2dLUycraWlhdjYWKSkpEClUsHHxwcff/wx/P39AQAeHh6YMmUK+vfvD0dHR7z44oswMDD4U8fF9RVrS76+voiLi0N8fDycnJyE6xozMzOsXr0agYGB6NmzJ2xtbWFvbw89PT3Y2NhoFHefPn2wc+dOzJs3D6amprCyssL8+fNRUVHR7Hb29vZ4+eWXUVRUhJEjRz6Nw2StICFNxk8x9pzKzMxE165dkZ2dzcPLGWOMMcYYY6ye4OBgKJVKvmHQBrjDhv3XqqmpwfTp01FYWIgdO3a0dXIYY4wxxhhjrF25efMmevfujZSUFDg5ObV1cv7rNJz0gLH/Aunp6ejVqxe6dOmC+Pj4tk4OY4wxxhhjjLUrU6ZMQUxMDObOncudNW2ER9gwxhhjjDHGGGOMtTM86TBjjDHGGGOMMcZYO8MdNowxxhhjjDHGGGPtDHfYMMYYY4wxxhhjjLUz3GHDGGOMMcYYY4wx1s5whw1jjDHGGGOMMcZYO8MdNowxxhhjjDHGGGPtDHfYMMYYY4wxxhhjjLUz3GHDGGOMMcYYY4wx1s5whw1jjDHGGGOMMcZYO/P/Acd1+1Z8jc50AAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 1400x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<style>.itables table td {\n",
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       "\n",
       ".itables table th {\n",
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       "\n",
       ".itables thead input {\n",
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       "<div class=\"itables\">\n",
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       "    <tr style=\"text-align: right;\">\n",
       "      \n",
       "      <th>category</th>\n",
       "      <th>cat_count</th>\n",
       "      <th>cluster</th>\n",
       "      <th>venue_category_major</th>\n",
       "      <th>venue_category_minor</th>\n",
       "      <th>still_exists</th>\n",
       "      <th>State</th>\n",
       "    </tr>\n",
       "  </thead><tbody><tr><td>Loading... (need <a href=https://mwouts.github.io/itables/troubleshooting.html>help</a>?)</td></tr></tbody><tfoot><th>category</th><th>cat_count</th><th>cluster</th><th>venue_category_major</th><th>venue_category_minor</th><th>still_exists</th><th>State</th></tfoot></table>\n",
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       "    dt($);\n",
       "\n",
       "    // Define the table data\n",
       "    const data = [[\"NSW Parliament House, Sydney, NSW\", 1, 5, \"Government / Public Museum \", \"State Parliament\", \"Y\", \"NSW\"], [\"Art Gallery of New South Wales, Sydney, NSW\", 67, 3, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"NSW\"], [\"Artspace, Sydney, NSW\", 7, 1, \"ARI or Indpendent \", \"CAOA\", \"Y\", \"NSW\"], [\"Tandanya National Aboriginal Cultural Institute, Adelaide, SA\", 4, 2, \"Government / Public Museum \", \"National Institution\", \"Y\", \"SA\"], [\"Art Gallery of South Australia, Adelaide, SA\", 7, 1, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"SA\"], [\"National Gallery of Victoria, Melbourne, VIC\", 19, 3, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"VIC\"], [\"National Gallery of Australia, Canberra, ACT\", 12, 2, \"Government / Public Museum \", \"National Institution\", \"Y\", \"ACT\"], [\"Bendigo Art Gallery, Bendigo, VIC\", 3, 2, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"VIC\"], [\"University of Melbourne, Melbourne, Vic\", 1, 4, \"University Gallery\", \"University Gallery\", \"Y\", \"VIC\"], [\"Manly Art Gallery & Museum, Manly, Sydney, NSW\", 4, 3, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Casula Powerhouse Arts Centre, Casula, NSW\", 7, 2, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Museum of Contemporary Art, Sydney, NSW\", 16, 3, \"Government / Public Museum \", \"Public Independent\", \"Y\", \"NSW\"], [\"Queensland Art Gallery, Brisbane, QLD\", 16, 3, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"QLD\"], [\"Powerhouse Museum, Sydney, NSW\", 1, 4, \"Government / Public Museum \", \"State Design Institutite\", \"Y\", \"NSW\"], [\"New England Regional Art Museum, Armidale, NSW\", 3, 2, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Centre for Contemporary Photography, Melbourne, VIC\", 7, 5, \"ARI or Indpendent \", \"ARI or Independent\", \"Y\", \"VIC\"], [\"Royal Exhibition Building, Melbourne, VIC\", 1, 1, \"ARI or Indpendent \", \"ARI or Independent\", \"Y\", \"VIC\"], [\"Museum of Sydney, Sydney, NSW\", 5, 5, \"Government / Public Museum \", \"City Gallery / Museum\", \"Y\", \"NSW\"], [\"Australian Centre for Contemporary Art, Melbourne, VIC\", 8, 1, \"ARI or Indpendent \", \"CAOA\", \"Y\", \"VIC\"], [\"Orange Regional Gallery, Orange, NSW\", 35, 3, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Campbelltown City Art Gallery, Campbelltown, NSW\", 7, 2, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Mosman Art Gallery, Mosman, NSW\", 1, 4, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"S.H. Ervin Gallery, Sydney, NSW\", 5, 3, \"Government / Public Museum \", \"Public Independent\", \"Y\", \"NSW\"], [\"Penrith Regional Gallery, Penrith, NSW\", 1, 5, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Geelong Art Gallery, Geelong, VIC\", 2, 5, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"VIC\"], [\"Institute of Modern Art, Brisbane, QLD\", 32, 3, \"ARI or Indpendent \", \"CAOA\", \"Y\", \"QLD\"], [\"Griffith University\", 2, 4, \"University Gallery\", \"University Gallery\", \"Y\", \"QLD\"], [\"Monash Gallery of Art, Melbourne, VIC\", 1, 1, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"VIC\"], [\"Art Gallery of Western Australia, Perth, WA\", 13, 3, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"WA\"], [\"RMIT Gallery, Melbourne, VIC\", 24, 3, \"University Gallery\", \"University Gallery\", \"Y\", \"VIC\"], [\"TAP Gallery, Darlinghurst, Sydney, NSW\", 5, 1, \"ARI or Indpendent \", \"ARI or Independent\", \"Y\", \"NSW\"], [\"Monash University Museum of Art, Melbourne, VIC\", 10, 1, \"University Gallery\", \"University Gallery\", \"Y\", \"VIC\"], [\"Hazelhurst Regional Gallery, Sydney, NSW\", 1, 4, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Heide Museum of Modern Art, Melbourne, VIC\", 20, 1, \"Government / Public Museum \", \"Public Independent\", \"Y\", \"VIC\"], [\"Bathurst Regional Art Gallery, Bathurst, NSW\", 1, 4, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Tasmanian Museum and Art Gallery, Hobart, TAS\", 14, 3, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"TAS\"], [\"Ballarat Fine Art Gallery, Ballarat, VIC\", 28, 3, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"VIC\"], [\"Warrnambool Art Gallery, Warrnambool, VIC\", 21, 3, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"VIC\"], [\"State Library of NSW, Sydney, NSW\", 3, 5, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"NSW\"], [\"Latrobe Regional Gallery, Morwell, VIC\", 1, 1, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"VIC\"], [\"Annandale Galleries, Sydney, NSW\", 1, 5, \"Commercial\", \"Commercial\", \"Y\", \"NSW\"], [\"Museums and Art Galleries of the Northern Territory, Darwin, NT\", 17, 3, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"NT\"], [\"Newcastle Region Art Gallery, Newcastle, NSW\", 24, 1, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Lawrence Wilson Art Gallery, University of Western Australia, Perth, WA\", 12, 1, \"University Gallery\", \"University Gallery\", \"Y\", \"WA\"], [\"Australian Centre for Photography, Sydney, NSW\", 6, 5, \"ARI or Indpendent \", \"ARI or Independent\", \"N\", \"NSW\"], [\"Brisbane City Art Gallery, Brisbane, Qld\", 41, 3, \"Government / Public Museum \", \"City Gallery / Museum\", \"Y\", \"QLD\"], [\"Sherman Galleries, Sydney, NSW\", 18, 5, \"Commercial\", \"Commercial\", \"N\", \"NSW\"], [\"Greenaway Art Gallery, Adelaide, SA\", 7, 5, \"Commercial\", \"Commercial\", \"Y\", \"SA\"], [\"Wollongong City Art Gallery, Wollongong, NSW\", 40, 3, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Ian Potter Museum of Art, University of Melbourne, Melbourne, Vic.\", 14, 3, \"University Gallery\", \"University Gallery\", \"Y\", \"VIC\"], [\"Eva Breuer Art Dealer, Woollahra, NSW\", 2, 4, \"Commercial\", \"Commercial\", \"N\", \"NSW\"], [\"Queen Victoria Museum and Art Gallery, Launceston, TAS\", 15, 3, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"TAS\"], [\"Gallery Gabrielle Pizzi, Melbourne, VIC\", 5, 5, \"Commercial\", \"Commercial\", \"Y\", \"VIC\"], [\"Canberra Contemporary Art Space, Canberra, ACT\", 4, 1, \"ARI or Indpendent \", \"CAOA\", \"Y\", \"ACT\"], [\"University of South Australia, Adelaide, SA\", 11, 3, \"University Gallery\", \"University Gallery\", \"Y\", \"SA\"], [\"Experimental Art Foundation, Adelaide, SA\", 61, 3, \"ARI or Indpendent \", \"CAOA\", \"N\", \"SA\"], [\"Anna Schwartz Gallery, Melbourne, Vic.\", 5, 1, \"Commercial\", \"Commercial\", \"Y\", \"VIC\"], [\"Mary Place Gallery, Paddington, NSW\", 2, 1, \"Commercial\", \"Commercial\", \"Y\", \"NSW\"], [\"Tin Sheds Gallery, University of Sydney, Sydney, NSW\", 41, 3, \"University Gallery\", \"University Gallery\", \"Y\", \"NSW\"], [\"Flinders University Art Museum, Adelaide, SA\", 6, 3, \"University Gallery\", \"University Gallery\", \"Y\", \"SA\"], [\"Hogarth Gallery, Sydney, NSW\", 9, 5, \"Commercial\", \"Commercial\", \"N\", \"NSW\"], [\"Christine Abrahams Gallery, Melbourne, VIC\", 6, 5, \"Commercial\", \"Commercial\", \"N\", \"VIC\"], [\"Bett Gallery, Hobart, Tas.\", 1, 4, \"Commercial\", \"Commercial\", \"Y\", \"TAS\"], [\"Garth Clark Gallery, New York, USA\", 1, 2, \"ARI or Indpendent \", \"International\", \"N\", \"USA\"], [\"Alcaston Gallery, Melbourne, VIC\", 1, 5, \"Commercial\", \"Commercial\", \"Y\", \"VIC\"], [\"Albury Regional Art Centre, Albury, NSW\", 2, 1, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Contemporary Art Centre of South Australia, Adelaide, SA\", 63, 3, \"ARI or Indpendent \", \"CAOA\", \"N\", \"SA\"], [\"Access Contemporary Art Gallery, Sydney, NSW\", 5, 3, \"Commercial\", \"Commercial\", \"N\", \"NSW\"], [\"Mori Gallery, Sydney, NSW\", 3, 5, \"Commercial\", \"Commercial\", \"N\", \"NSW\"], [\"Ivan Dougherty Gallery, Sydney, NSW\", 12, 3, \"University Gallery\", \"University Gallery\", \"N\", \"NSW\"], [\"Plimsoll Gallery, University of Tasmania, Hobart, TAS\", 4, 1, \"University Gallery\", \"University Gallery\", \"Y\", \"TAS\"], [\"Stills Gallery, Sydney, NSW\", 2, 5, \"Commercial\", \"Commercial\", \"N\", \"NSW\"], [\"Coventry Gallery, Sydney, NSW\", 1, 5, \"Commercial\", \"Commercial\", \"N\", \"NSW\"], [\"Ray Hughes Gallery, Sydney, NSW\", 2, 1, \"Commercial\", \"Commercial\", \"N\", \"NSW\"], [\"Drill Hall Gallery, Australian National University, Canberra, ACT\", 5, 1, \"University Gallery\", \"University Gallery\", \"Y\", \"ACT\"], [\"Sir Herman Black Gallery, Sydney, NSW\", 3, 5, \"University Gallery\", \"University Gallery\", \"N\", \"NSW\"], [\"Rex Irwin Art Dealer, Sydney, NSW\", 1, 1, \"Commercial\", \"Commercial\", \"N\", \"NSW\"], [\"Perth Institute of Contemporary Art, Perth, WA\", 2, 5, \"ARI or Indpendent \", \"CAOA\", \"Y\", \"WA\"], [\"Tamworth Regional Gallery, Tamworth, NSW\", 1, 3, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Greenhill Galleries, Perth, WA\", 1, 5, \"Commercial\", \"Commercial\", \"N\", \"WA\"], [\"Glen Eira City Gallery, Melbourne, Vic.\", 3, 1, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"VIC\"], [\"John Curtin Gallery, Curtin University, Perth, WA\", 9, 1, \"University Gallery\", \"University Gallery\", \"Y\", \"WA\"], [\"University of Queensland Art Museum, Brisbane, QLD\", 4, 1, \"University Gallery\", \"University Gallery\", \"Y\", \"QLD\"], [\"School of Art, Australian National University, Canberra, ACT\", 6, 1, \"University Gallery\", \"University Gallery\", \"Y\", \"ACT\"], [\"Bender's Lane, 144 Charles Street, Launceston, Tasmania\", 12, 2, \"Commercial\", \"Commercial\", \"N\", \"TAS\"], [\"Bunbury Regional Art Galleries, Bunbury, WA\", 1, 1, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"WA\"], [\"Corner Brisbane and Tamar Streets, Launceston, TAS\", 4, 2, \"Government / Public Museum \", \"State Design Institutite\", \"Y\", \"TAS\"]];\n",
       "\n",
       "    // Define the dt_args\n",
       "    let dt_args = {\"scrollY\": \"400px\", \"scrollCollapse\": true, \"scrollX\": true, \"paging\": false, \"dom\": \"tpr\", \"order\": [], \"initComplete\": function () {\n",
       "    // Apply the search\n",
       "    this.api()\n",
       "        .columns()\n",
       "        .every(function () {\n",
       "            const that = this;\n",
       "\n",
       "            $('input', this.footer()).on('keyup change clear', function () {\n",
       "                if (that.search() !== this.value) {\n",
       "                    that.search(this.value).draw();\n",
       "                }\n",
       "            });\n",
       "        });\n",
       "}\n",
       "};\n",
       "    dt_args[\"data\"] = data;\n",
       "\n",
       "    $(document).ready(function () {\n",
       "        // Setup - add a text input to each header or footer cell\n",
       "$('#32bd7c3f-cd49-4edb-a0e5-079d858aa624 tfoot th').each(function () {\n",
       "    let title = $(this).text();\n",
       "    $(this).html('<input type=\"text\" placeholder=\"Search ' +\n",
       "        // We use encodeURI to avoid this LGTM error:\n",
       "        // https://lgtm.com/rules/1511866576920/\n",
       "        encodeURI(title).replaceAll(\"%20\", \" \") +\n",
       "        '\" />');\n",
       "});\n",
       "\n",
       "        $('#32bd7c3f-cd49-4edb-a0e5-079d858aa624').DataTable(dt_args);\n",
       "    });\n",
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      "\n",
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",
      "text/plain": [
       "<Figure size 1400x1000 with 1 Axes>"
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     "output_type": "display_data"
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     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      \n",
       "      <th>category</th>\n",
       "      <th>cat_count</th>\n",
       "      <th>cluster</th>\n",
       "      <th>venue_category_major</th>\n",
       "      <th>venue_category_minor</th>\n",
       "      <th>still_exists</th>\n",
       "      <th>State</th>\n",
       "    </tr>\n",
       "  </thead><tbody><tr><td>Loading... (need <a href=https://mwouts.github.io/itables/troubleshooting.html>help</a>?)</td></tr></tbody><tfoot><th>category</th><th>cat_count</th><th>cluster</th><th>venue_category_major</th><th>venue_category_minor</th><th>still_exists</th><th>State</th></tfoot></table>\n",
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       "\n",
       "    // Define the table data\n",
       "    const data = [[\"NSW Parliament House, Sydney, NSW\", 14, 2, \"Government / Public Museum \", \"State Parliament\", \"Y\", \"NSW\"], [\"Art Gallery of New South Wales, Sydney, NSW\", 44, 1, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"NSW\"], [\"Artspace, Sydney, NSW\", 56, 3, \"ARI or Indpendent \", \"CAOA\", \"Y\", \"NSW\"], [\"Tandanya National Aboriginal Cultural Institute, Adelaide, SA\", 3, 5, \"Government / Public Museum \", \"National Institution\", \"Y\", \"SA\"], [\"Art Gallery of South Australia, Adelaide, SA\", 9, 3, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"SA\"], [\"National Gallery of Victoria, Melbourne, VIC\", 16, 1, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"VIC\"], [\"National Gallery of Australia, Canberra, ACT\", 7, 3, \"Government / Public Museum \", \"National Institution\", \"Y\", \"ACT\"], [\"Bendigo Art Gallery, Bendigo, VIC\", 5, 2, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"VIC\"], [\"Macquarie University Art Gallery, Sydney, NSW\", 3, 3, \"University Gallery\", \"University Gallery\", \"Y\", \"NSW\"], [\"Manly Art Gallery & Museum, Manly, Sydney, NSW\", 1, 4, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Casula Powerhouse Arts Centre, Casula, NSW\", 8, 5, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Museum of Contemporary Art, Sydney, NSW\", 26, 1, \"Government / Public Museum \", \"Public Independent\", \"Y\", \"NSW\"], [\"Queensland Art Gallery, Brisbane, QLD\", 13, 3, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"QLD\"], [\"Powerhouse Museum, Sydney, NSW\", 3, 5, \"Government / Public Museum \", \"State Design Institutite\", \"Y\", \"NSW\"], [\"New England Regional Art Museum, Armidale, NSW\", 2, 5, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Centre for Contemporary Photography, Melbourne, VIC\", 7, 4, \"ARI or Indpendent \", \"ARI or Independent\", \"Y\", \"VIC\"], [\"Royal Exhibition Building, Melbourne, VIC\", 2, 2, \"ARI or Indpendent \", \"ARI or Independent\", \"Y\", \"VIC\"], [\"Museum of Sydney, Sydney, NSW\", 2, 1, \"Government / Public Museum \", \"City Gallery / Museum\", \"Y\", \"NSW\"], [\"Australian Centre for Contemporary Art, Melbourne, VIC\", 2, 3, \"ARI or Indpendent \", \"CAOA\", \"Y\", \"VIC\"], [\"Orange Regional Gallery, Orange, NSW\", 29, 3, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Campbelltown City Art Gallery, Campbelltown, NSW\", 6, 5, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Mosman Art Gallery, Mosman, NSW\", 8, 5, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"S.H. Ervin Gallery, Sydney, NSW\", 6, 5, \"Government / Public Museum \", \"Public Independent\", \"Y\", \"NSW\"], [\"Beaver Galleries, Canberra, ACT\", 1, 1, \"Commercial\", \"Commercial\", \"Y\", \"ACT\"], [\"Penrith Regional Gallery, Penrith, NSW\", 4, 5, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Geelong Art Gallery, Geelong, VIC\", 3, 2, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"VIC\"], [\"Institute of Modern Art, Brisbane, QLD\", 3, 2, \"ARI or Indpendent \", \"CAOA\", \"Y\", \"QLD\"], [\"Monash Gallery of Art, Melbourne, VIC\", 6, 5, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"VIC\"], [\"Art Gallery of Western Australia, Perth, WA\", 4, 3, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"WA\"], [\"RMIT Gallery, Melbourne, VIC\", 10, 3, \"University Gallery\", \"University Gallery\", \"Y\", \"VIC\"], [\"TAP Gallery, Darlinghurst, Sydney, NSW\", 2, 5, \"ARI or Indpendent \", \"ARI or Independent\", \"Y\", \"NSW\"], [\"Monash University Museum of Art, Melbourne, VIC\", 11, 3, \"University Gallery\", \"University Gallery\", \"Y\", \"VIC\"], [\"Hazelhurst Regional Gallery, Sydney, NSW\", 6, 3, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Heide Museum of Modern Art, Melbourne, VIC\", 16, 3, \"Government / Public Museum \", \"Public Independent\", \"Y\", \"VIC\"], [\"Bathurst Regional Art Gallery, Bathurst, NSW\", 3, 1, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Tasmanian Museum and Art Gallery, Hobart, TAS\", 5, 3, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"TAS\"], [\"Ballarat Fine Art Gallery, Ballarat, VIC\", 27, 3, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"VIC\"], [\"Warrnambool Art Gallery, Warrnambool, VIC\", 9, 1, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"VIC\"], [\"Latrobe Regional Gallery, Morwell, VIC\", 14, 3, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"VIC\"], [\"Museums and Art Galleries of the Northern Territory, Darwin, NT\", 6, 3, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"NT\"], [\"Tamworth Regional Gallery, Tamworth, NSW\", 3, 2, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Boomalli Aboriginal Artists Cooperative, Sydney, NSW\", 1, 1, \"Commercial\", \"Commercial\", \"Y\", \"NSW\"], [\"Ian Potter Museum of Art, University of Melbourne, Melbourne, Vic.\", 21, 1, \"University Gallery\", \"University Gallery\", \"Y\", \"VIC\"], [\"Greenaway Art Gallery, Adelaide, SA\", 8, 5, \"Commercial\", \"Commercial\", \"Y\", \"SA\"], [\"Lawrence Wilson Art Gallery, University of Western Australia, Perth, WA\", 9, 2, \"University Gallery\", \"University Gallery\", \"Y\", \"WA\"], [\"Flinders University Art Museum, Adelaide, SA\", 7, 3, \"University Gallery\", \"University Gallery\", \"Y\", \"SA\"], [\"Ray Hughes Gallery, Sydney, NSW\", 7, 4, \"Commercial\", \"Commercial\", \"N\", \"NSW\"], [\"Karen Woodbury Gallery, Melbourne, Vic.\", 7, 1, \"Commercial\", \"Commercial\", \"N\", \"VIC\"], [\"Stella Downer Fine Art, Sydney, NSW\", 4, 4, \"Commercial\", \"Commercial\", \"Y\", \"NSW\"], [\"Canberra Contemporary Art Space, Canberra, ACT\", 4, 3, \"ARI or Indpendent \", \"CAOA\", \"Y\", \"ACT\"], [\"Drill Hall Gallery, Australian National University, Canberra, ACT\", 17, 3, \"University Gallery\", \"University Gallery\", \"Y\", \"ACT\"], [\"Sherman Galleries, Sydney, NSW\", 19, 5, \"Commercial\", \"Commercial\", \"N\", \"NSW\"], [\"Bett Gallery, Hobart, Tas.\", 3, 4, \"Commercial\", \"Commercial\", \"Y\", \"TAS\"], [\"Queen Victoria Museum and Art Gallery, Launceston, TAS\", 16, 1, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"TAS\"], [\"Eva Breuer Art Dealer, Woollahra, NSW\", 6, 4, \"Commercial\", \"Commercial\", \"N\", \"NSW\"], [\"Kaliman Gallery, Paddington, Sydney, NSW\", 5, 4, \"Commercial\", \"Commercial\", \"N\", \"NSW\"], [\"Perth Institute of Contemporary Art, Perth, WA\", 4, 5, \"ARI or Indpendent \", \"CAOA\", \"Y\", \"WA\"], [\"Object Gallery, Sydney, NSW\", 4, 5, \"Government / Public Museum \", \"State Design Institutite\", \"Y\", \"NSW\"], [\"Gallery Gabrielle Pizzi, Melbourne, VIC\", 2, 4, \"Commercial\", \"Commercial\", \"Y\", \"VIC\"], [\"Plimsoll Gallery, University of Tasmania, Hobart, TAS\", 4, 3, \"University Gallery\", \"University Gallery\", \"Y\", \"TAS\"], [\"Newcastle Region Art Gallery, Newcastle, NSW\", 22, 3, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Contemporary Art Centre of South Australia, Adelaide, SA\", 27, 1, \"ARI or Indpendent \", \"CAOA\", \"N\", \"SA\"], [\"ARC One Gallery, Melbourne, Vic.\", 2, 4, \"Commercial\", \"Commercial\", \"Y\", \"VIC\"], [\"Stills Gallery, Sydney, NSW\", 9, 5, \"Commercial\", \"Commercial\", \"N\", \"NSW\"], [\"Australian Centre for Photography, Sydney, NSW\", 4, 5, \"ARI or Indpendent \", \"ARI or Independent\", \"N\", \"NSW\"], [\"Anna Schwartz Gallery, Melbourne, Vic.\", 3, 4, \"Commercial\", \"Commercial\", \"Y\", \"VIC\"], [\"Mary Place Gallery, Paddington, NSW\", 5, 5, \"Commercial\", \"Commercial\", \"Y\", \"NSW\"], [\"Tin Sheds Gallery, University of Sydney, Sydney, NSW\", 30, 3, \"University Gallery\", \"University Gallery\", \"Y\", \"NSW\"], [\"Christine Abrahams Gallery, Melbourne, VIC\", 7, 5, \"Commercial\", \"Commercial\", \"N\", \"VIC\"], [\"Ivan Dougherty Gallery, Sydney, NSW\", 11, 1, \"University Gallery\", \"University Gallery\", \"N\", \"NSW\"], [\"University of South Australia, Adelaide, SA\", 9, 1, \"University Gallery\", \"University Gallery\", \"Y\", \"SA\"], [\"Alcaston Gallery, Melbourne, VIC\", 3, 5, \"Commercial\", \"Commercial\", \"Y\", \"VIC\"], [\"Garth Clark Gallery, New York, USA\", 2, 5, \"ARI or Indpendent \", \"International\", \"N\", \"USA\"], [\"Wollongong City Art Gallery, Wollongong, NSW\", 27, 3, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Global Gallery, Paddington, NSW\", 5, 5, \"Commercial\", \"Commercial\", \"N\", \"NSW\"], [\"Annandale Galleries, Sydney, NSW\", 1, 5, \"Commercial\", \"Commercial\", \"Y\", \"NSW\"], [\"Gomboc Gallery, Perth, WA\", 5, 4, \"Commercial\", \"Commercial\", \"Y\", \"WA\"], [\"Albury Regional Art Centre, Albury, NSW\", 1, 2, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Mori Gallery, Sydney, NSW\", 4, 5, \"Commercial\", \"Commercial\", \"N\", \"NSW\"], [\"Adelaide Central Gallery, Adelaide, SA\", 1, 4, \"University Gallery\", \"University Gallery\", \"Y\", \"SA\"], [\"Rex Irwin Art Dealer, Sydney, NSW\", 4, 2, \"Commercial\", \"Commercial\", \"N\", \"NSW\"], [\"Access Contemporary Art Gallery, Sydney, NSW\", 1, 1, \"Commercial\", \"Commercial\", \"N\", \"NSW\"], [\"Utopia Art Gallery, Sydney, NSW\", 3, 4, \"Commercial\", \"Commercial\", \"Y\", \"NSW\"], [\"Charles Nodrum Gallery, Melbourne, VIC\", 2, 4, \"Commercial\", \"Commercial\", \"Y\", \"VIC\"], [\"Sir Herman Black Gallery, Sydney, NSW\", 2, 4, \"University Gallery\", \"University Gallery\", \"N\", \"NSW\"], [\"Glen Eira City Gallery, Melbourne, Vic.\", 6, 3, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"VIC\"], [\"John Curtin Gallery, Curtin University, Perth, WA\", 16, 3, \"University Gallery\", \"University Gallery\", \"Y\", \"WA\"], [\"Experimental Art Foundation, Adelaide, SA\", 24, 3, \"ARI or Indpendent \", \"CAOA\", \"N\", \"SA\"], [\"Brisbane City Art Gallery, Brisbane, Qld\", 36, 3, \"Government / Public Museum \", \"City Gallery / Museum\", \"Y\", \"QLD\"], [\"University of Queensland Art Museum, Brisbane, QLD\", 6, 2, \"University Gallery\", \"University Gallery\", \"Y\", \"QLD\"], [\"School of Art, Australian National University, Canberra, ACT\", 2, 4, \"University Gallery\", \"University Gallery\", \"Y\", \"ACT\"], [\"8 Llankelly Place, Kings Cross, Sydney, 2011\", 19, 1, \"ARI or Indpendent \", \"ARI or Independent\", \"Y\", \"NSW\"]];\n",
       "\n",
       "    // Define the dt_args\n",
       "    let dt_args = {\"scrollY\": \"400px\", \"scrollCollapse\": true, \"scrollX\": true, \"paging\": false, \"dom\": \"tpr\", \"order\": [], \"initComplete\": function () {\n",
       "    // Apply the search\n",
       "    this.api()\n",
       "        .columns()\n",
       "        .every(function () {\n",
       "            const that = this;\n",
       "\n",
       "            $('input', this.footer()).on('keyup change clear', function () {\n",
       "                if (that.search() !== this.value) {\n",
       "                    that.search(this.value).draw();\n",
       "                }\n",
       "            });\n",
       "        });\n",
       "}\n",
       "};\n",
       "    dt_args[\"data\"] = data;\n",
       "\n",
       "    $(document).ready(function () {\n",
       "        // Setup - add a text input to each header or footer cell\n",
       "$('#74894599-c175-4666-b4de-ce6cb3d0ad92 tfoot th').each(function () {\n",
       "    let title = $(this).text();\n",
       "    $(this).html('<input type=\"text\" placeholder=\"Search ' +\n",
       "        // We use encodeURI to avoid this LGTM error:\n",
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       "        '\" />');\n",
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",
      "text/plain": [
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       "    <tr style=\"text-align: right;\">\n",
       "      \n",
       "      <th>category</th>\n",
       "      <th>cat_count</th>\n",
       "      <th>cluster</th>\n",
       "      <th>venue_category_major</th>\n",
       "      <th>venue_category_minor</th>\n",
       "      <th>still_exists</th>\n",
       "      <th>State</th>\n",
       "    </tr>\n",
       "  </thead><tbody><tr><td>Loading... (need <a href=https://mwouts.github.io/itables/troubleshooting.html>help</a>?)</td></tr></tbody><tfoot><th>category</th><th>cat_count</th><th>cluster</th><th>venue_category_major</th><th>venue_category_minor</th><th>still_exists</th><th>State</th></tfoot></table>\n",
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       "    // Define the table data\n",
       "    const data = [[\"NSW Parliament House, Sydney, NSW\", 22, 5, \"Government / Public Museum \", \"State Parliament\", \"Y\", \"NSW\"], [\"Art Gallery of New South Wales, Sydney, NSW\", 15, 1, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"NSW\"], [\"Artspace, Sydney, NSW\", 17, 1, \"ARI or Indpendent \", \"CAOA\", \"Y\", \"NSW\"], [\"Tandanya National Aboriginal Cultural Institute, Adelaide, SA\", 3, 3, \"Government / Public Museum \", \"National Institution\", \"Y\", \"SA\"], [\"Art Gallery of South Australia, Adelaide, SA\", 2, 4, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"SA\"], [\"National Gallery of Victoria, Melbourne, VIC\", 2, 3, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"VIC\"], [\"National Gallery of Australia, Canberra, ACT\", 6, 4, \"Government / Public Museum \", \"National Institution\", \"Y\", \"ACT\"], [\"University of Melbourne, Melbourne, Vic\", 1, 4, \"University Gallery\", \"University Gallery\", \"Y\", \"VIC\"], [\"Macquarie University Art Gallery, Sydney, NSW\", 4, 2, \"University Gallery\", \"University Gallery\", \"Y\", \"NSW\"], [\"Manly Art Gallery & Museum, Manly, Sydney, NSW\", 2, 3, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Casula Powerhouse Arts Centre, Casula, NSW\", 3, 2, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Museum of Contemporary Art, Sydney, NSW\", 7, 4, \"Government / Public Museum \", \"Public Independent\", \"Y\", \"NSW\"], [\"Queensland Art Gallery, Brisbane, QLD\", 3, 4, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"QLD\"], [\"Powerhouse Museum, Sydney, NSW\", 1, 3, \"Government / Public Museum \", \"State Design Institutite\", \"Y\", \"NSW\"], [\"New England Regional Art Museum, Armidale, NSW\", 5, 2, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Centre for Contemporary Photography, Melbourne, VIC\", 5, 5, \"ARI or Indpendent \", \"ARI or Independent\", \"Y\", \"VIC\"], [\"Roslyn Oxley9 Gallery, Paddington, Sydney, NSW\", 3, 5, \"Commercial\", \"Commercial\", \"Y\", \"NSW\"], [\"Australian Centre for Contemporary Art, Melbourne, VIC\", 2, 4, \"ARI or Indpendent \", \"CAOA\", \"Y\", \"VIC\"], [\"Orange Regional Gallery, Orange, NSW\", 6, 5, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Campbelltown City Art Gallery, Campbelltown, NSW\", 4, 4, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Mosman Art Gallery, Mosman, NSW\", 7, 4, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"S.H. Ervin Gallery, Sydney, NSW\", 8, 2, \"Government / Public Museum \", \"Public Independent\", \"Y\", \"NSW\"], [\"Beaver Galleries, Canberra, ACT\", 4, 4, \"Commercial\", \"Commercial\", \"Y\", \"ACT\"], [\"Penrith Regional Gallery, Penrith, NSW\", 5, 5, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Geelong Art Gallery, Geelong, VIC\", 1, 4, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"VIC\"], [\"Institute of Modern Art, Brisbane, QLD\", 2, 3, \"ARI or Indpendent \", \"CAOA\", \"Y\", \"QLD\"], [\"Monash Gallery of Art, Melbourne, VIC\", 3, 5, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"VIC\"], [\"Art Gallery of Western Australia, Perth, WA\", 1, 4, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"WA\"], [\"RMIT Gallery, Melbourne, VIC\", 1, 5, \"University Gallery\", \"University Gallery\", \"Y\", \"VIC\"], [\"TAP Gallery, Darlinghurst, Sydney, NSW\", 1, 4, \"ARI or Indpendent \", \"ARI or Independent\", \"Y\", \"NSW\"], [\"Hazelhurst Regional Gallery, Sydney, NSW\", 5, 5, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Heide Museum of Modern Art, Melbourne, VIC\", 3, 4, \"Government / Public Museum \", \"Public Independent\", \"Y\", \"VIC\"], [\"Bathurst Regional Art Gallery, Bathurst, NSW\", 2, 4, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Tasmanian Museum and Art Gallery, Hobart, TAS\", 2, 2, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"TAS\"], [\"Warrnambool Art Gallery, Warrnambool, VIC\", 2, 1, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"VIC\"], [\"National Art School, Sydney, NSW\", 7, 1, \"University Gallery\", \"University Gallery\", \"Y\", \"NSW\"], [\"Shanghai Art Gallery, Shanghai, China\", 2, 5, \"ARI or Indpendent \", \"International\", \"NaN\", \"China\"], [\"Karen Woodbury Gallery, Melbourne, Vic.\", 16, 4, \"Commercial\", \"Commercial\", \"N\", \"VIC\"], [\"Greenaway Art Gallery, Adelaide, SA\", 9, 2, \"Commercial\", \"Commercial\", \"Y\", \"SA\"], [\"Kaliman Gallery, Paddington, Sydney, NSW\", 2, 4, \"Commercial\", \"Commercial\", \"N\", \"NSW\"], [\"Stella Downer Fine Art, Sydney, NSW\", 12, 2, \"Commercial\", \"Commercial\", \"Y\", \"NSW\"], [\"Sherman Galleries, Sydney, NSW\", 15, 4, \"Commercial\", \"Commercial\", \"N\", \"NSW\"], [\"Contemporary Art Centre of South Australia, Adelaide, SA\", 3, 4, \"ARI or Indpendent \", \"CAOA\", \"N\", \"SA\"], [\"Museums and Art Galleries of the Northern Territory, Darwin, NT\", 2, 5, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"NT\"], [\"Newcastle Region Art Gallery, Newcastle, NSW\", 5, 2, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Annandale Galleries, Sydney, NSW\", 1, 3, \"Commercial\", \"Commercial\", \"Y\", \"NSW\"], [\"Queen Victoria Museum and Art Gallery, Launceston, TAS\", 2, 4, \"Government / Public Museum \", \"State Gallery / Library\", \"Y\", \"TAS\"], [\"Eva Breuer Art Dealer, Woollahra, NSW\", 5, 4, \"Commercial\", \"Commercial\", \"N\", \"NSW\"], [\"Boomalli Aboriginal Artists Cooperative, Sydney, NSW\", 2, 3, \"Commercial\", \"Commercial\", \"Y\", \"NSW\"], [\"Object Gallery, Sydney, NSW\", 6, 4, \"Government / Public Museum \", \"State Design Institutite\", \"Y\", \"NSW\"], [\"Gallery Gabrielle Pizzi, Melbourne, VIC\", 3, 5, \"Commercial\", \"Commercial\", \"Y\", \"VIC\"], [\"Bett Gallery, Hobart, Tas.\", 3, 5, \"Commercial\", \"Commercial\", \"Y\", \"TAS\"], [\"ARC One Gallery, Melbourne, Vic.\", 3, 4, \"Commercial\", \"Commercial\", \"Y\", \"VIC\"], [\"Anna Schwartz Gallery, Melbourne, Vic.\", 2, 3, \"Commercial\", \"Commercial\", \"Y\", \"VIC\"], [\"Tin Sheds Gallery, University of Sydney, Sydney, NSW\", 2, 3, \"University Gallery\", \"University Gallery\", \"Y\", \"NSW\"], [\"Mary Place Gallery, Paddington, NSW\", 7, 1, \"Commercial\", \"Commercial\", \"Y\", \"NSW\"], [\"Christine Abrahams Gallery, Melbourne, VIC\", 4, 5, \"Commercial\", \"Commercial\", \"N\", \"VIC\"], [\"Ivan Dougherty Gallery, Sydney, NSW\", 5, 5, \"University Gallery\", \"University Gallery\", \"N\", \"NSW\"], [\"Garth Clark Gallery, New York, USA\", 1, 2, \"ARI or Indpendent \", \"International\", \"N\", \"USA\"], [\"Stills Gallery, Sydney, NSW\", 5, 2, \"Commercial\", \"Commercial\", \"N\", \"NSW\"], [\"University of South Australia, Adelaide, SA\", 1, 5, \"University Gallery\", \"University Gallery\", \"Y\", \"SA\"], [\"Global Gallery, Paddington, NSW\", 3, 4, \"Commercial\", \"Commercial\", \"N\", \"NSW\"], [\"Katanning Arts Centre, Katanning & Western Australian Museum, Perth, WA\", 5, 5, \"ARI or Indpendent \", \"Arts Centre\", \"Y\", \"WA\"], [\"Gomboc Gallery, Perth, WA\", 2, 3, \"Commercial\", \"Commercial\", \"Y\", \"WA\"], [\"Chalk Horse Gallery, Surry Hills, NSW\", 11, 2, \"Commercial\", \"Commercial\", \"Y\", \"NSW\"], [\"Bunbury Regional Art Galleries, Bunbury, WA\", 2, 4, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"WA\"], [\"Ian Potter Museum of Art, University of Melbourne, Melbourne, Vic.\", 15, 1, \"University Gallery\", \"University Gallery\", \"Y\", \"VIC\"], [\"Mori Gallery, Sydney, NSW\", 2, 2, \"Commercial\", \"Commercial\", \"N\", \"NSW\"], [\"Australian Centre for Photography, Sydney, NSW\", 1, 4, \"ARI or Indpendent \", \"ARI or Independent\", \"N\", \"NSW\"], [\"8 Llankelly Place, Kings Cross, Sydney, 2011\", 28, 1, \"ARI or Indpendent \", \"ARI or Independent\", \"Y\", \"NSW\"], [\"Wollongong City Art Gallery, Wollongong, NSW\", 7, 1, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Albury Regional Art Centre, Albury, NSW\", 1, 5, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Utopia Art Gallery, Sydney, NSW\", 8, 5, \"Commercial\", \"Commercial\", \"Y\", \"NSW\"], [\"Tamworth Regional Gallery, Tamworth, NSW\", 3, 1, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Performance Space, Sydney, NSW\", 1, 4, \"ARI or Indpendent \", \"CAOA\", \"Y\", \"NSW\"], [\"Shoalhaven City Arts Centre, NSW\", 5, 4, \"Government / Public Museum \", \"Local Government and/or Regional Gallery\", \"Y\", \"NSW\"], [\"Charles Nodrum Gallery, Melbourne, VIC\", 4, 4, \"Commercial\", \"Commercial\", \"Y\", \"VIC\"], [\"University of Queensland Art Museum, Brisbane, QLD\", 1, 5, \"University Gallery\", \"University Gallery\", \"Y\", \"QLD\"], [\"Greenhill Galleries, Perth, WA\", 3, 4, \"Commercial\", \"Commercial\", \"N\", \"WA\"], [\"John Curtin Gallery, Curtin University, Perth, WA\", 2, 4, \"University Gallery\", \"University Gallery\", \"Y\", \"WA\"], [\"Lawrence Wilson Art Gallery, University of Western Australia, Perth, WA\", 2, 4, \"University Gallery\", \"University Gallery\", \"Y\", \"WA\"]];\n",
       "\n",
       "    // Define the dt_args\n",
       "    let dt_args = {\"scrollY\": \"400px\", \"scrollCollapse\": true, \"scrollX\": true, \"paging\": false, \"dom\": \"tpr\", \"order\": [], \"initComplete\": function () {\n",
       "    // Apply the search\n",
       "    this.api()\n",
       "        .columns()\n",
       "        .every(function () {\n",
       "            const that = this;\n",
       "\n",
       "            $('input', this.footer()).on('keyup change clear', function () {\n",
       "                if (that.search() !== this.value) {\n",
       "                    that.search(this.value).draw();\n",
       "                }\n",
       "            });\n",
       "        });\n",
       "}\n",
       "};\n",
       "    dt_args[\"data\"] = data;\n",
       "\n",
       "    $(document).ready(function () {\n",
       "        // Setup - add a text input to each header or footer cell\n",
       "$('#2408b945-88b9-4dfa-8773-de538b480714 tfoot th').each(function () {\n",
       "    let title = $(this).text();\n",
       "    $(this).html('<input type=\"text\" placeholder=\"Search ' +\n",
       "        // We use encodeURI to avoid this LGTM error:\n",
       "        // https://lgtm.com/rules/1511866576920/\n",
       "        encodeURI(title).replaceAll(\"%20\", \" \") +\n",
       "        '\" />');\n",
       "});\n",
       "\n",
       "        $('#2408b945-88b9-4dfa-8773-de538b480714').DataTable(dt_args);\n",
       "    });\n",
       "</script>\n",
       "</div>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "def temporal_dendos(startdt=1900, enddt=1920, cut_input=3, model=None):\n",
    "    df_period = clean_data_v2[(clean_data_v2['start_year'] >= startdt) & (clean_data_v2['start_year'] <= enddt)]\n",
    "    # df_period = clean_data_v2[(clean_data_v2['decade_start'] >= startdt) & (clean_data_v2['decade_start'] <= enddt)]\n",
    "    ### pre-process for NLP\n",
    "    # Load the documents and their corresponding categorical variables into a Pandas dataframe\n",
    "    df_period = pd.DataFrame({'text': df_period['slug2'], 'category': df_period['address_prompt']})\n",
    "\n",
    "    # summarise text for each unique place name\n",
    "    df_period['text'] = df_period.groupby('category')['text'].transform(lambda x: ' '.join(x))\n",
    "\n",
    "    #add new column with count for each category\n",
    "    df_period['cat_count'] = df_period.groupby('category')['category'].transform('count')\n",
    "    df_period.drop_duplicates(inplace=True)\n",
    "\n",
    "    # Clean the text\n",
    "    stop_words = set(stopwords.words('english'))\n",
    "    df_period = df_period[df_period['text'].notnull()]\n",
    "    df_period['clean_text'] = df_period['text'].apply(clean_text)\n",
    "\n",
    "    if model is None:\n",
    "        # randomly sample 512 tokens from each row in df['clean_text']\n",
    "        # some strings are smalle than 512\n",
    "        df_period['clean_text_sampled'] = df_period['clean_text'].apply(lambda x: ' '.join(random.sample(x.split(' '), 275)) if len(x.split(' ')) >= 275 else x)\n",
    "        X_bert_period = df_period['clean_text_sampled'].apply(lambda x: pd.Series(bert_encode([str(x)])[0]))\n",
    "\n",
    "        # setting distance_threshold=0 ensures we compute the full tree.\n",
    "        model_bert_period = AgglomerativeClustering(distance_threshold=0, n_clusters=None)\n",
    "        model_bert_period = model_bert_period.fit(np.array(X_bert_period))\n",
    "\n",
    "        # save model as pickle\n",
    "        pickle.dump(model_bert_period, open(f'models/model_bert_{startdt}_{enddt}.pkl', 'wb'))\n",
    "    else:\n",
    "        model_bert_period = fetch_bert_models_from_github(f'model_bert_{startdt}_{enddt}.pkl')\n",
    "\n",
    "    ### generate dendrogram\n",
    "    cut = cut_input\n",
    "    l_matrix = get_linkage_matrix(model_bert_period)\n",
    "    df_period['cluster'] = fcluster(l_matrix, cut, criterion='maxclust')\n",
    "    dendrogram(l_matrix, orientation='top', truncate_mode=\"lastp\", p=cut, show_leaf_counts=True)\n",
    "\n",
    "    all_words = []\n",
    "\n",
    "    for i in df_period['cluster'].unique():\n",
    "        cluster_docs = df_period[df_period['cluster'] == i]\n",
    "        # print(i, get_most_common_word(cluster_docs['clean_text']))\n",
    "\n",
    "        annot = \"\\n\".join(i[0] for idx,i in enumerate(get_most_common_word(cluster_docs['clean_text'])) if (idx < 3))\n",
    "        \n",
    "        plt.annotate(annot, xy=(i/df_period['cluster'].nunique()-0.1, 0.15), \n",
    "                    xytext=(i/df_period['cluster'].nunique()-0.1, 0.15), \n",
    "                    xycoords='axes fraction', fontsize=9, color='red')\n",
    "\n",
    "        [all_words.append(i[0]) for idx,i in enumerate(get_most_common_word(cluster_docs['clean_text']))]\n",
    "        \n",
    "    all_words_to_remove = find_duplicates(all_words, occurences=2)\n",
    "    all_words_to_remove.extend(['j','th','nd','exhibitionexhibited','http','www','isbn'])\n",
    "\n",
    "    for i in df_period['cluster'].unique():\n",
    "        cluster_docs = df_period[df_period['cluster'] == i]\n",
    "        # print(i, get_most_common_word(cluster_docs['clean_text']))\n",
    "        annot = \"\\n\".join(i[0] for idx,i in enumerate(get_most_common_word(cluster_docs['clean_text'],\n",
    "                                                                        more_words=all_words_to_remove)) if (idx < 5))\n",
    "        \n",
    "        plt.annotate(annot, xy=(i/df_period['cluster'].nunique()-0.1, 0.025), \n",
    "                    xytext=(i/df_period['cluster'].nunique()-0.1, 0.025), \n",
    "                    xycoords='axes fraction', fontsize=9)\n",
    "        \n",
    "        annot2 = cluster_docs.sort_values('cat_count', ascending=False)['category'].values[0:3]\n",
    "        annot2 = '\\n\\n'.join(['\\n'.join(wrap(line, 18)) for line in [i.split(',')[0] for i in annot2]])\n",
    "        # annot2 = '\\n'.join(wrap(annot2, 18)) # breaks strings into new lines\n",
    "\n",
    "        plt.annotate(annot2, xy=(i/df_period['cluster'].nunique()-0.115, -0.24), \n",
    "                    xytext=(i/df_period['cluster'].nunique()-0.115, -0.24), \n",
    "                    xycoords='axes fraction', fontsize=9)\n",
    "\n",
    "    plt.title(f\"Hierarchical Clustering Dendrogram - BERT - {startdt}-{enddt}\")\n",
    "\n",
    "    # make figure bigger\n",
    "    fig = plt.gcf()\n",
    "    fig.set_size_inches(14, 10)\n",
    "    plt.show()\n",
    "\n",
    "    df_period_model_bert = df_period.merge(clean_data_v2[['venue_name','venue_category_major','venue_category_minor','still_exists','State']], \n",
    "                            left_on='category', right_on='venue_name', how='left').drop_duplicates()\n",
    "    # display data\n",
    "    show(df_period_model_bert.drop(['venue_name','clean_text','text'],axis=1), scrollY=\"400px\", scrollCollapse=True, scrollX=True,\n",
    "        paging=False, showIndex=False, column_filters=\"footer\", dom=\"tpr\")\n",
    "\n",
    "    print('\\n')\n",
    "    return df_period\n",
    "\n",
    "# # use this configuration for first time runnning in a local env\n",
    "# # this will also create a pickle locally for each time period\n",
    "# df_65_70 = temporal_dendos(1965, 1970, cut_input=5, model=None)\n",
    "# df_70_75 = temporal_dendos(1970, 1975, cut_input=5, model=None)\n",
    "# df_75_80 = temporal_dendos(1975, 1980, cut_input=5, model=None)\n",
    "# df_80_85 = temporal_dendos(1980, 1985, cut_input=5, model=None)\n",
    "# df_85_90 = temporal_dendos(1985, 1990, cut_input=5, model=None)\n",
    "# df_90_95 = temporal_dendos(1990, 1995, cut_input=5, model=None)\n",
    "# df_95_00 = temporal_dendos(1995, 2000, cut_input=5, model=None)\n",
    "# df_00_05 = temporal_dendos(2000, 2005, cut_input=5, model=None)\n",
    "# df_05_10 = temporal_dendos(2005, 2010, cut_input=5, model=None)\n",
    "\n",
    "# use this configuration for pre-loaded pickles from github for each time period\n",
    "df_65_70 = temporal_dendos(1965, 1970, cut_input=5, model=0)\n",
    "df_70_75 = temporal_dendos(1970, 1975, cut_input=5, model=0)\n",
    "df_75_80 = temporal_dendos(1975, 1980, cut_input=5, model=0)\n",
    "df_80_85 = temporal_dendos(1980, 1985, cut_input=5, model=0)\n",
    "df_85_90 = temporal_dendos(1985, 1990, cut_input=5, model=0)\n",
    "df_90_95 = temporal_dendos(1990, 1995, cut_input=5, model=0)\n",
    "df_95_00 = temporal_dendos(1995, 2000, cut_input=5, model=0)\n",
    "df_00_05 = temporal_dendos(2000, 2005, cut_input=5, model=0)\n",
    "df_05_10 = temporal_dendos(2005, 2010, cut_input=5, model=0)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### National Gallery of Victoria, Melbourne, VIC\n",
    "\n",
    "We assess five venues and their associated clusters to see if they are any consistent venue pairings. For example over the dendrograms above, NGV is clustered with Warrnambool Art Gallery four times out of a potential nine temporal iterations. We see a similar pattern for AGNSW."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Art Gallery of New South Wales, Sydney, NSW    4\n",
      "Warrnambool Art Gallery, Warrnambool, VIC      4\n",
      "Queensland Art Gallery, Brisbane, QLD          3\n",
      "Museum of Contemporary Art, Sydney, NSW        3\n",
      "Ivan Dougherty Gallery, Sydney, NSW            3\n",
      "Name: category, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "def try_merge(df1, df2, venue):\n",
    "    try: return pd.concat([df1, df2[df2['cluster'] == df2[df2['category'] == venue]['cluster'].values[0]]])\n",
    "    except: return df1\n",
    "\n",
    "\n",
    "df_test = pd.DataFrame()\n",
    "venue = 'National Gallery of Victoria, Melbourne, VIC'\n",
    "df_test = try_merge(df_test, df_65_70, venue)\n",
    "df_test = try_merge(df_test, df_70_75, venue)\n",
    "df_test = try_merge(df_test, df_75_80, venue)\n",
    "df_test = try_merge(df_test, df_80_85, venue)\n",
    "df_test = try_merge(df_test, df_85_90, venue)\n",
    "df_test = try_merge(df_test, df_90_95, venue)\n",
    "df_test = try_merge(df_test, df_95_00, venue)\n",
    "df_test = try_merge(df_test, df_00_05, venue)\n",
    "df_test = try_merge(df_test, df_05_10, venue)\n",
    "print(df_test['category'].value_counts().head(6).tail(-1))\n"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Experimental Art Foundation, Adelaide, SA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Queensland Art Gallery, Brisbane, QLD                     4\n",
      "Art Gallery of New South Wales, Sydney, NSW               3\n",
      "National Gallery of Victoria, Melbourne, VIC              3\n",
      "Orange Regional Gallery, Orange, NSW                      3\n",
      "Australian Centre for Contemporary Art, Melbourne, VIC    3\n",
      "Name: category, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "df_test = pd.DataFrame()\n",
    "venue = 'Experimental Art Foundation, Adelaide, SA'\n",
    "df_test = try_merge(df_test, df_65_70, venue)\n",
    "df_test = try_merge(df_test, df_70_75, venue)\n",
    "df_test = try_merge(df_test, df_75_80, venue)\n",
    "df_test = try_merge(df_test, df_80_85, venue)\n",
    "df_test = try_merge(df_test, df_85_90, venue)\n",
    "df_test = try_merge(df_test, df_90_95, venue)\n",
    "df_test = try_merge(df_test, df_95_00, venue)\n",
    "df_test = try_merge(df_test, df_00_05, venue)\n",
    "df_test = try_merge(df_test, df_05_10, venue)\n",
    "print(df_test['category'].value_counts().head(6).tail(-1))"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Contemporary Art Centre of South Australia, Adelaide, SA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Queen Victoria Museum and Art Gallery, Launceston, TAS    7\n",
      "Ivan Dougherty Gallery, Sydney, NSW                       5\n",
      "Art Gallery of New South Wales, Sydney, NSW               4\n",
      "National Gallery of Australia, Canberra, ACT              4\n",
      "University of Melbourne, Melbourne, Vic                   4\n",
      "Name: category, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "df_test = pd.DataFrame()\n",
    "venue = 'Contemporary Art Centre of South Australia, Adelaide, SA'\n",
    "df_test = try_merge(df_test, df_65_70, venue)\n",
    "df_test = try_merge(df_test, df_70_75, venue)\n",
    "df_test = try_merge(df_test, df_75_80, venue)\n",
    "df_test = try_merge(df_test, df_80_85, venue)\n",
    "df_test = try_merge(df_test, df_85_90, venue)\n",
    "df_test = try_merge(df_test, df_90_95, venue)\n",
    "df_test = try_merge(df_test, df_95_00, venue)\n",
    "df_test = try_merge(df_test, df_00_05, venue)\n",
    "df_test = try_merge(df_test, df_05_10, venue)\n",
    "print(df_test['category'].value_counts().head(6).tail(-1))"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Art Gallery of New South Wales, Sydney, NSW"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Warrnambool Art Gallery, Warrnambool, VIC                          6\n",
      "Ivan Dougherty Gallery, Sydney, NSW                                5\n",
      "National Gallery of Victoria, Melbourne, VIC                       4\n",
      "Museums and Art Galleries of the Northern Territory, Darwin, NT    4\n",
      "Contemporary Art Centre of South Australia, Adelaide, SA           4\n",
      "Name: category, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "df_test = pd.DataFrame()\n",
    "venue = 'Art Gallery of New South Wales, Sydney, NSW'\n",
    "df_test = try_merge(df_test, df_65_70, venue)\n",
    "df_test = try_merge(df_test, df_70_75, venue)\n",
    "df_test = try_merge(df_test, df_75_80, venue)\n",
    "df_test = try_merge(df_test, df_80_85, venue)\n",
    "df_test = try_merge(df_test, df_85_90, venue)\n",
    "df_test = try_merge(df_test, df_90_95, venue)\n",
    "df_test = try_merge(df_test, df_95_00, venue)\n",
    "df_test = try_merge(df_test, df_00_05, venue)\n",
    "df_test = try_merge(df_test, df_05_10, venue)\n",
    "print(df_test['category'].value_counts().head(6).tail(-1))\n"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Wollongong City Gallery, Wollongong, NSW"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ballarat Fine Art Gallery, Ballarat, VIC        5\n",
      "Artspace, Sydney, NSW                           5\n",
      "Art Gallery of South Australia, Adelaide, SA    4\n",
      "Institute of Modern Art, Brisbane, QLD          4\n",
      "Art Gallery of Western Australia, Perth, WA     4\n",
      "Name: category, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "df_test = pd.DataFrame()\n",
    "venue = 'Wollongong City Art Gallery, Wollongong, NSW'\n",
    "df_test = try_merge(df_test, df_65_70, venue)\n",
    "df_test = try_merge(df_test, df_70_75, venue)\n",
    "df_test = try_merge(df_test, df_75_80, venue)\n",
    "df_test = try_merge(df_test, df_80_85, venue)\n",
    "df_test = try_merge(df_test, df_85_90, venue)\n",
    "df_test = try_merge(df_test, df_90_95, venue)\n",
    "df_test = try_merge(df_test, df_95_00, venue)\n",
    "df_test = try_merge(df_test, df_00_05, venue)\n",
    "df_test = try_merge(df_test, df_05_10, venue)\n",
    "print(df_test['category'].value_counts().head(6).tail(-1))"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Organisations\n",
    "Similar to venues, we first produce a word cloud for common terms used in organisation names. We find that the most frequent terms are \"Ltd\", \"Pty\", \"Australia\", \"Art\", and \"Design\"."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# fetch organisation data from github\n",
    "org_data = fetch_data(acdedata='organization')\n",
    "daoo_org_data = org_data[(org_data.data_source.str.contains('DAAO')) & (org_data.primary_name.notnull())]\n",
    "all_place_names = daoo_org_data.primary_name.apply(lambda x: ast.literal_eval(x)).astype(str).tolist()\n",
    "\n",
    "# create a list of all the words in the place names\n",
    "all_words = []\n",
    "for place_name in all_place_names:\n",
    "    all_words.extend(word_tokenize(place_name))\n",
    "\n",
    "# find top 100 most frequent words\n",
    "most_freq_words = Counter(all_words).most_common(30)\n",
    "\n",
    "# remove a list of all words that are not relevant\n",
    "words_to_remove = [',','.','and','of','the','The','for',\"'s\",'&','(',')','J.','Melbourne',\n",
    "                   'UK','VIC','London','A',\n",
    "                   'Jane','Lapham','*','Adelaide',\"'\",'Sydney','NSW','New','South','Wales']\n",
    "\n",
    "# remove the words from the list of most frequent words\n",
    "most_freq_words = [word for word in most_freq_words if word[0] not in words_to_remove]\n",
    "\n",
    "most_freq_words_dict = dict(most_freq_words)\n",
    "\n",
    "# # add value of two keys\n",
    "# most_freq_words_dict['Gallery'] = most_freq_words_dict['Gallery'] + most_freq_words_dict['Galleries']\n",
    "# most_freq_words_dict['Museum'] = most_freq_words_dict['Museum'] + most_freq_words_dict['Museums']\n",
    "\n",
    "# # remove key 'Gallery'\n",
    "# most_freq_words_dict.pop('Galleries')\n",
    "# most_freq_words_dict.pop('Museums')\n",
    "\n",
    "# create a wordcloud with the most frequent words\n",
    "from wordcloud import WordCloud\n",
    "\n",
    "wordcloud = WordCloud(width = 800, height = 800,\n",
    "                background_color ='white',\n",
    "                min_font_size = 10, random_state=300).generate_from_frequencies(most_freq_words_dict)\n",
    "\n",
    "# plot the WordCloud image\n",
    "plt.figure(figsize = (8, 8), facecolor = None)\n",
    "plt.imshow(wordcloud)\n",
    "plt.axis(\"off\")\n",
    "plt.tight_layout(pad = 0)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As shown above, the use of dendrograms can be an interesting exercise to explore the data. The initial idea was to repeat the same approach with organisations to assess any latent patterns through this taxonomic approrach. However, we find that the data is not as rich as the venue data and that there are many organisations with no biographies, no summaries, and no relations to people records, exhibition records, etc.  Nevertheless we provide one dendrogram using organisation biographies.\n",
    "\n",
    "Below is a list of the proportion of missing data for each field across DAAO organisations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "_id                      0.000000\n",
       "data_source              0.000000\n",
       "_class                   0.000000\n",
       "_class_ori               0.000000\n",
       "ori_id                   1.000000\n",
       "ori_dbid                 0.000000\n",
       "ori_url                  0.000000\n",
       "date_created             0.105490\n",
       "date_modified            0.320775\n",
       "record_status            0.000000\n",
       "version                  0.000000\n",
       "contributors             1.000000\n",
       "note                     1.000000\n",
       "summary                  0.609257\n",
       "primary_name             0.000000\n",
       "alternative_names        0.846071\n",
       "types                    0.864370\n",
       "longterm_roles           0.000000\n",
       "operation                0.000000\n",
       "locations                0.819160\n",
       "nla                      0.996771\n",
       "biography                0.534984\n",
       "contact                  1.000000\n",
       "copyright_agents         0.997847\n",
       "editing_complete         0.789020\n",
       "email                    1.000000\n",
       "fax                      1.000000\n",
       "is_australian            1.000000\n",
       "is_deleted               0.000000\n",
       "is_featured              0.000000\n",
       "is_locked                0.000000\n",
       "is_primary               0.000000\n",
       "is_shadow                0.000000\n",
       "locked_biographies       0.997847\n",
       "ori_dbid_unf             1.000000\n",
       "ori_url_data             1.000000\n",
       "other_occupations        0.987083\n",
       "periods_active           0.814855\n",
       "phones                   1.000000\n",
       "place_of_demise          1.000000\n",
       "place_of_origin          1.000000\n",
       "pubts                    1.000000\n",
       "references               0.503767\n",
       "see_alsos                0.913886\n",
       "source_database_ids      0.928956\n",
       "sources                  0.603875\n",
       "tags                     0.820237\n",
       "urls                     0.853606\n",
       "web_links                1.000000\n",
       "related_events           1.000000\n",
       "related_organizations    1.000000\n",
       "related_people           1.000000\n",
       "related_recognitions     1.000000\n",
       "related_resources        1.000000\n",
       "related_works            1.000000\n",
       "dtype: float64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# find the proportion of null values in each column\n",
    "display((daoo_org_data.isnull().sum()/daoo_org_data.shape[0]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "tags": [
     "hide-cell"
    ]
   },
   "outputs": [],
   "source": [
    "from bs4 import BeautifulSoup\n",
    "\n",
    "orgs = pd.DataFrame(columns=['name','summary','bio'])\n",
    "\n",
    "for i,row in daoo_org_data.iterrows():\n",
    "    try:\n",
    "        try: pd.json_normalize(json.loads(row['biography']))['text']\n",
    "        except: continue\n",
    "\n",
    "        try: this_summary = ast.literal_eval(row['summary'])\n",
    "        except: this_summary = None\n",
    "\n",
    "        # try: period_end = row['periods_active'][0]['end']['_date']\n",
    "        # except: period_end = None\n",
    "\n",
    "        # use pandas.concat to append new row to dataframe\n",
    "        orgs = pd.concat([orgs, pd.DataFrame({'name': [ast.literal_eval(row['primary_name'])],\n",
    "                                                'summary': [this_summary],\n",
    "                                                'bio': [pd.json_normalize(json.loads(row['biography']))['text'].values[0]]\n",
    "                                                })], ignore_index=True)\n",
    "        \n",
    "    except:\n",
    "        print(i)\n",
    "        break\n",
    "\n",
    "# remove empty summary\n",
    "orgs['summary'].fillna('', inplace=True)\n",
    "\n",
    "# remove rows with stub text\n",
    "orgs = orgs[~orgs['bio'].isin(orgs['bio'].value_counts().head(5).index.to_list())]\n",
    "\n",
    "# combine summary and bio\n",
    "orgs['bio'] = orgs['summary'] + orgs['bio'].apply(lambda x: BeautifulSoup(x, 'lxml').get_text())\n",
    "\n",
    "orgs = orgs[['name','bio']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "tags": [
     "hide-cell"
    ]
   },
   "outputs": [],
   "source": [
    "### load bert model\n",
    "# # !pip install transformers\n",
    "# from transformers import BertTokenizer, BertModel\n",
    "# from transformers import pipeline\n",
    "# tokenizer = BertTokenizer.from_pretrained('bert-base-uncased')\n",
    "# model = BertModel.from_pretrained(\"bert-base-uncased\")\n",
    "\n",
    "# ### encode text using bert (takes 8secs to run)\n",
    "# import random\n",
    "# import pickle\n",
    "\n",
    "# # encode the text using bert\n",
    "# def bert_encode(x):\n",
    "#   encoded_input = tokenizer(x, return_tensors='pt')\n",
    "#   output = model(**encoded_input)\n",
    "#   return pd.DataFrame(output['pooler_output'].detach().numpy()).T\n",
    "\n",
    "# ### pre-process for NLP\n",
    "# # Load the documents and their corresponding categorical variables into a Pandas dataframe\n",
    "# df_org = pd.DataFrame({'text': orgs['bio'], 'category': orgs['name']})\n",
    "\n",
    "# #add new column with count for each category\n",
    "# df_org['cat_count'] = df_org.groupby('category')['category'].transform('count')\n",
    "# df_org.drop_duplicates(inplace=True)\n",
    "\n",
    "# # Clean the text\n",
    "# stop_words = set(stopwords.words('english'))\n",
    "\n",
    "# def clean_text(text):\n",
    "#     text = re.sub('[^a-zA-Z]', ' ', text)\n",
    "#     text = text.replace(',', '')\n",
    "#     text = text.lower().split()\n",
    "#     text = [word for word in text if word not in stop_words]\n",
    "#     text = ' '.join(text)\n",
    "#     return text\n",
    "\n",
    "# df_org['clean_text'] = df_org['text'].apply(clean_text)\n",
    "\n",
    "# # randomly sample 512 tokens from each row in df['clean_text']\n",
    "# # some strings are smalle than 512\n",
    "# df_org['clean_text_sampled'] = df_org['clean_text'].apply(lambda x: ' '.join(random.sample(x.split(' '), 350)) if len(x.split(' ')) >= 350 else x)\n",
    "# X_bert_org = df_org['clean_text_sampled'].apply(lambda x: pd.Series(bert_encode([str(x)])[0]))\n",
    "\n",
    "# # setting distance_threshold=0 ensures we compute the full tree.\n",
    "# model_bert_org = AgglomerativeClustering(distance_threshold=0, n_clusters=None)\n",
    "# model_bert_org = model_bert_org.fit(np.array(X_bert_org))\n",
    "\n",
    "# # save model as pickle\n",
    "# pickle.dump(model_bert_org, open('models/model_bert_orgs.pkl', 'wb'))"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Biographical data for each organisation (~120 organisations) is used to create the clusters. From here we show the most common terms used in the organisation name for each cluster."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# # fetch bert model from github\n",
    "# model_bert_org = fetch_bert_models_from_github(\"model_bert_orgs.pkl\")\n",
    "\n",
    "# cut = 5\n",
    "# l_matrix = get_linkage_matrix(model_bert_org)\n",
    "# df_org['cluster'] = fcluster(l_matrix, cut, criterion='maxclust')\n",
    "# dendrogram(l_matrix, orientation='top', truncate_mode=\"lastp\", p=cut, show_leaf_counts=True)\n",
    "\n",
    "# all_words = []\n",
    "\n",
    "# for i in df_org['cluster'].unique():\n",
    "#     cluster_docs = df_org[df_org['cluster'] == i]\n",
    "#     # print(i, get_most_common_word(cluster_docs['clean_text']))\n",
    "#     [all_words.append(i[0]) for idx,i in enumerate(get_most_common_word(cluster_docs['category'], no_of_words=5))]\n",
    "    \n",
    "# all_words_to_remove = find_duplicates(all_words, occurences=4)\n",
    "# all_words_to_remove.extend(['h','co','e','test','Lapham','J.','Jane','','and','of','&','The','SymbioticA','Nevin','Smith'])\n",
    "\n",
    "# for i in df_org['cluster'].unique():\n",
    "#     cluster_docs = df_org[df_org['cluster'] == i]\n",
    "#     # print(i, get_most_common_word(cluster_docs['clean_text']))\n",
    "#     annot = \"\\n\".join(i[0] for idx,i in enumerate(get_most_common_word(cluster_docs['category'], no_of_words=6,\n",
    "#                                                                        more_words=all_words_to_remove)) if (idx < 3))\n",
    "    \n",
    "#     plt.annotate(annot, xy=(i/df_org['cluster'].nunique()-0.1, 0.05), \n",
    "#                  xytext=(i/df_org['cluster'].nunique()-0.1, 0.05), \n",
    "#                  xycoords='axes fraction', fontsize=12)\n",
    "    \n",
    "#     # annot2 = cluster_docs.sort_values('cat_count', ascending=False)['category'].values[0:3]\n",
    "#     # annot2 = '\\n\\n'.join(['\\n'.join(wrap(line, 18)) for line in [i.split(',')[0] for i in annot2]])\n",
    "#     # # annot2 = '\\n'.join(wrap(annot2, 18)) # breaks strings into new lines\n",
    "\n",
    "#     # plt.annotate(annot2, xy=(i/df_org['cluster'].nunique()-0.115, -0.24), \n",
    "#     #             xytext=(i/df_org['cluster'].nunique()-0.115, -0.24), \n",
    "#     #             xycoords='axes fraction', fontsize=9)\n",
    "\n",
    "# plt.title(\"Hierarchical Clustering Dendrogram - BERT, Organisations\")\n",
    "\n",
    "# # make figure bigger\n",
    "# fig = plt.gcf()\n",
    "# fig.set_size_inches(14, 10)\n",
    "\n",
    "# plt.show()\n",
    "\n",
    "# # save the figure\n",
    "# fig.savefig('images/images_analysis/DAAOVenues_BERT_orgs.png', dpi=300, bbox_inches='tight')\n",
    "# df_org.to_csv('data/local/DAAOVenues_BERT_orgs.csv', index=False)\n",
    "\n",
    "from IPython.display import Image\n",
    "Image(filename='images/images_analysis/DAAOVenues_BERT_orgs.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
    {
     "data": {
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       ".itables table th {\n",
       "    text-overflow: ellipsis;\n",
       "    overflow: hidden;\n",
       "}\n",
       "\n",
       ".itables thead input {\n",
       "    width: 100%;\n",
       "    padding: 3px;\n",
       "    box-sizing: border-box;\n",
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       "<div class=\"itables\">\n",
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       "    <tr style=\"text-align: right;\">\n",
       "      \n",
       "      <th>category</th>\n",
       "      <th>cluster</th>\n",
       "    </tr>\n",
       "  </thead><tbody><tr><td>Loading... (need <a href=https://mwouts.github.io/itables/troubleshooting.html>help</a>?)</td></tr></tbody><tfoot><th>category</th><th>cluster</th></tfoot></table>\n",
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       "    import dt from 'https://cdn.datatables.net/1.12.1/js/jquery.dataTables.mjs';\n",
       "    dt($);\n",
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       "\n",
       "    // Define the dt_args\n",
       "    let dt_args = {\"scrollY\": \"400px\", \"scrollCollapse\": true, \"paging\": false, \"dom\": \"tpr\", \"order\": [], \"initComplete\": function () {\n",
       "    // Apply the search\n",
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       "                if (that.search() !== this.value) {\n",
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       "                }\n",
       "            });\n",
       "        });\n",
       "}\n",
       "};\n",
       "    dt_args[\"data\"] = data;\n",
       "\n",
       "    $(document).ready(function () {\n",
       "        // Setup - add a text input to each header or footer cell\n",
       "$('#367fa071-525f-49a5-b662-c576f4458f05 tfoot th').each(function () {\n",
       "    let title = $(this).text();\n",
       "    $(this).html('<input type=\"text\" placeholder=\"Search ' +\n",
       "        // We use encodeURI to avoid this LGTM error:\n",
       "        // https://lgtm.com/rules/1511866576920/\n",
       "        encodeURI(title).replaceAll(\"%20\", \" \") +\n",
       "        '\" />');\n",
       "});\n",
       "\n",
       "        $('#367fa071-525f-49a5-b662-c576f4458f05').DataTable(dt_args);\n",
       "    });\n",
       "</script>\n",
       "</div>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# read from github\n",
    "df_model_bert_org = fetch_small_data_from_github(\"DAAOVenues_BERT_orgs.csv\")\n",
    "\n",
    "# display data\n",
    "show(df_model_bert_org.drop(['clean_text','clean_text_sampled','text','cat_count'],axis=1), scrollY=\"400px\", scrollCollapse=True,\n",
    "     paging=False, showIndex=False, column_filters=\"footer\", dom=\"tpr\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "tags": [
     "remove-cell"
    ]
   },
   "outputs": [],
   "source": [
    "# with open(\"data/daao_relation.json\") as json_file: daao_relation_data=json.load(json_file)\n",
    "# relation_df = pd.json_normalize(daao_relation_data)\n",
    "# print(relation_df[((relation_df['obj._cls'] == 'PersonGroup') & (relation_df['subj._cls'] == 'Person'))]['obj._ref.$id.$oid'].shape)\n",
    "\n",
    "# with open(\"data/daao_xparty.json\") as json_file: daao_xparty_data=json.load(json_file)\n",
    "# xparty_df = pd.json_normalize(daao_xparty_data)\n",
    "# xparty_df.head()\n",
    "\n",
    "# xparty_df[xparty_df['_cls']=='VersionedDocument.XParty.PersonGroup']['primary_name'].value_counts()\n",
    "\n",
    "# org_df = pd.json_normalize(daoo_org_data)\n",
    "# org_df[org_df['_id.$oid'].isin(relation_df[(relation_df['obj._cls'] == 'PersonGroup') & (relation_df['subj._cls'] == 'Person')]['obj._ref.$id.$oid'])]\n",
    "\n",
    "# orgs_ppl = pd.DataFrame()\n",
    "\n",
    "# for i,row in pd.json_normalize(daoo_org_data).iterrows():\n",
    "#     try: \n",
    "#         related_people = []\n",
    "#         for j,row2 in pd.json_normalize(row['related_stub_people']).iterrows():\n",
    "#             related_people.extend([pd.json_normalize(row2['predicate'])['_id.$oid'].values[0], \n",
    "#                                 pd.json_normalize(row2['target'])['_id.$oid'].values[0]])\n",
    "\n",
    "#         ppl = pd.DataFrame({'related_people':list(dict.fromkeys(related_people))})\n",
    "#         ppl['organisation'] = row['primary_name']\n",
    "#         orgs_ppl = pd.concat([orgs_ppl, ppl], ignore_index=True)\n",
    "#     except: continue"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Temporal analysis of venues\n",
    "\n",
    "To further explore frequently used terms in place names, we produce an interactive time series of the number of events per decade by associated terms.\n",
    "\n",
    "Before the visuals, we provide an ordered list of the decades with the most event activity, and also a list of the most frequent terms used in place names."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1990    1488\n",
       "2000    1114\n",
       "1980    1042\n",
       "1970     515\n",
       "2010     212\n",
       "1960      77\n",
       "1950      39\n",
       "1940      13\n",
       "1900       7\n",
       "1910       6\n",
       "1930       5\n",
       "1920       4\n",
       "Name: decade, dtype: int64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "events_df = clean_data_v2.copy()\n",
    "\n",
    "# create a new column with the decade of start year\n",
    "events_df['decade'] = events_df['start_year'].apply(lambda x: str(x)[:3] + '0')\n",
    "events_df['decade'] = events_df['decade'].apply(lambda x: '2000' if x == '2020' else x)\n",
    "events_df['decade'] = events_df['decade'].astype(int)\n",
    "display(events_df['decade'].value_counts())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Art': 2992,\n",
       " 'Gallery': 2606,\n",
       " 'University': 502,\n",
       " 'Museum': 473,\n",
       " 'Contemporary': 472,\n",
       " 'Centre': 456,\n",
       " 'Experimental': 424,\n",
       " 'Foundation': 424,\n",
       " 'Modern': 290,\n",
       " 'City': 282,\n",
       " 'National': 249,\n",
       " 'Institute': 235,\n",
       " 'Regional': 184,\n",
       " 'Museums': 128,\n",
       " 'Australian': 116,\n",
       " 'Place': 108,\n",
       " 'Region': 106,\n",
       " 'Fine': 102}"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "most_freq_words_dict2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [],
   "source": [
    "words_by_decade = pd.DataFrame()\n",
    "\n",
    "for key in most_freq_words_dict2:\n",
    "    words_this_decade = events_df[events_df['address_prompt'].str.contains(key, na=False)]\\\n",
    "                        .groupby('decade')['address_prompt']\\\n",
    "                        .count()\\\n",
    "                        .reset_index(name='count')\\\n",
    "                        .sort_values(['decade'], ascending=True)\n",
    "    words_this_decade['term'] = key\n",
    "    words_by_decade = pd.concat([words_by_decade, words_this_decade], ignore_index=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
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    "import plotly.express as px\n",
    "fig = px.line(words_by_decade, x=\"decade\", y=\"count\", color='term',\n",
    "                title='Count of each term by decade')\n",
    "\n",
    "\n",
    "# # make figure size bigger\n",
    "# # fig.update_layout(\n",
    "# #     autosize=False,\n",
    "# #     width=700,\n",
    "# #     height=500,\n",
    "# # )\n",
    "\n",
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    "# events_df['diff'] = events_df['end_year'] - events_df['start_year']\n",
    "# # events_df[(events_df['place_name'].str.contains('Contemporary')) & (events_df['diff'] > 1)]\n",
    "\n",
    "# using start_date, end_date, place_name, calculate the difference between start_date of the first event in an venue and end_date of the last event in that venue\n",
    "places_with_start_end = []\n",
    "[places_with_start_end.extend([p, events_df.loc[events_df['address_prompt'] == p, 'start_year'].min(), \n",
    "                              events_df.loc[events_df['address_prompt'] == p, 'end_year'].max()] for p in events_df['place_address'].unique())]\n",
    "\n",
    "places_with_start_end = pd.DataFrame(places_with_start_end)\n",
    "places_with_start_end.columns = ['address_prompt', 'start_year', 'end_year']\n",
    "places_with_start_end['diff'] = places_with_start_end['end_year'] - places_with_start_end['start_year']\n",
    "places_with_start_end = places_with_start_end[places_with_start_end['diff'] >= 0]\n",
    "# places_with_start_end.sort_values('diff', ascending=False)"
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   "source": [
    "Beyond the above time series, we also provide a series of bar charts, however instead of illustrating event activity within a certain decade, we plot the number of venues active across time. We calculate the start and end of a venue's \"lifespan\" by using the earliest and latest event date associated with a venue. We do this by filtering on venues with associated terms in the place name."
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    "decade_placeholder = pd.DataFrame([0] * 13, index=range(1900, 2020+1, 10)).reset_index().rename(columns={'index':'decade', 0:'count'})\n",
    "decade_placeholder['decade'] = decade_placeholder['decade'].astype(str)\n",
    "\n",
    "for term in most_freq_words_dict2:\n",
    "    # create a wide form of contemporary with each decade as a column and a binary value for whether the venue existed in that decade\n",
    "    # use start_year as the start and end_year as the end of the venue\n",
    "    contemporary = places_with_start_end[(places_with_start_end['address_prompt'].str.contains(term))].sort_values('start_year', ascending=True)\n",
    "    contemporary_wide = pd.DataFrame()\n",
    "\n",
    "    for i,row in contemporary.iterrows():\n",
    "        for year in range(int(row['start_year']), int(row['end_year'])+1): \n",
    "            contemporary_wide.loc[row['address_prompt'], str(year)[:3] + '0'] = 1\n",
    "\n",
    "    contemporary_wide = contemporary_wide.\\\n",
    "        fillna(0).\\\n",
    "        reset_index().\\\n",
    "        rename(columns={'index':'address_prompt'}).\\\n",
    "        sum().tail(-1).\\\n",
    "        reset_index().\\\n",
    "        rename(columns={'index':'decade', 0:'count'})\n",
    "    \n",
    "    contemporary_wide = pd.merge(contemporary_wide, decade_placeholder, on='decade', how='outer')\n",
    "    contemporary_wide['count'] = contemporary_wide['count_x'] + contemporary_wide['count_y']\n",
    "    contemporary_wide = contemporary_wide[['decade', 'count']].sort_values('decade', ascending=True)\n",
    "\n",
    "    fig = px.bar(contemporary_wide, x=\"decade\", y='count',\n",
    "                    title=f'Number of venues that existed in each decade, {term}')\n",
    "\n",
    "    # remove y-axis label\n",
    "    fig.update_yaxes(title_text='')\n",
    "    fig.update_xaxes(title_text='')\n",
    "\n",
    "    # # make figure size bigger\n",
    "    # fig.update_layout(\n",
    "    #     autosize=False,\n",
    "    #     width=700,\n",
    "    #     height=400,\n",
    "    # )\n",
    "\n",
    "    fig.show()"
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   "source": [
    "### Proportions\n",
    "We repeat the same temporal visuals as above, however this time we plot the proportions to effectively normalise the data with respect to the number of events across decades, and the number of venues that existed across time, repsectively.\n",
    "\n",
    "Note that the y-axis limits in the bar charts changes for each term."
   ]
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    "words_by_decade_prop = []\n",
    "\n",
    "# find the proportions of each word in each decade\n",
    "for i in most_freq_words_dict2.keys():\n",
    "    for j in events_df['decade'].unique():\n",
    "        prop = events_df[(events_df['address_prompt'].str.contains(i)) & (events_df['decade'] == j)].shape[0] /events_df[events_df['decade'] == j].shape[0]\n",
    "        words_by_decade_prop.append([i,j,prop])\n",
    "    \n",
    "words_by_decade_prop = pd.DataFrame(words_by_decade_prop)\n",
    "words_by_decade_prop.columns = ['word','decade','proportion']"
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    "# plot proportion of each term by decade\n",
    "# make it interactive\n",
    "\n",
    "import plotly.express as px\n",
    "\n",
    "fig = px.line(words_by_decade_prop.sort_values('decade'), x=\"decade\", y=\"proportion\", color='word',\n",
    "                title='Proportion of each term by decade')\n",
    "\n",
    "# make figure size bigger\n",
    "# fig.update_layout(\n",
    "#     autosize=False,\n",
    "#     width=700,\n",
    "#     height=500,\n",
    "# )\n",
    "\n",
    "fig.show()"
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   "cell_type": "code",
   "execution_count": 48,
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   "source": [
    "allplaces_wide = pd.DataFrame()\n",
    "\n",
    "for i,row in places_with_start_end.iterrows():\n",
    "    for year in range(int(row['start_year']), int(row['end_year'])+1): \n",
    "        allplaces_wide.loc[row['address_prompt'], str(year)[:3] + '0'] = 1\n",
    "\n",
    "decade_placeholder_forprop = allplaces_wide.\\\n",
    "                            fillna(0).\\\n",
    "                            reset_index().\\\n",
    "                            rename(columns={'index':'address_prompt'}).\\\n",
    "                            sum().tail(-1).\\\n",
    "                            reset_index().\\\n",
    "                            rename(columns={'index':'decade', 0:'count'}).\\\n",
    "                            sort_values('decade', ascending=True)"
   ]
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   "cell_type": "code",
   "execution_count": 49,
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    "for term in most_freq_words_dict2:\n",
    "    # create a wide form of contemporary with each decade as a column and a binary value for whether the venue existed in that decade\n",
    "    # use start_year as the start and end_year as the end of the venue\n",
    "    contemporary = places_with_start_end[(places_with_start_end['address_prompt'].str.contains(term))].sort_values('start_year', ascending=True)\n",
    "    contemporary_wide = pd.DataFrame()\n",
    "\n",
    "    for i,row in contemporary.iterrows():\n",
    "        for year in range(int(row['start_year']), int(row['end_year'])+1): \n",
    "            contemporary_wide.loc[row['address_prompt'], str(year)[:3] + '0'] = 1\n",
    "\n",
    "    contemporary_wide = contemporary_wide.\\\n",
    "        fillna(0).\\\n",
    "        reset_index().\\\n",
    "        rename(columns={'index':'address_prompt'}).\\\n",
    "        sum().tail(-1).\\\n",
    "        reset_index().\\\n",
    "        rename(columns={'index':'decade', 0:'count'})\n",
    "    \n",
    "    contemporary_wide = pd.merge(contemporary_wide, decade_placeholder_forprop, on='decade', how='outer')\n",
    "    contemporary_wide['prop'] = np.where(contemporary_wide['count_x'] > 0, \n",
    "                                     contemporary_wide['count_x']/contemporary_wide['count_y'], 0)\n",
    "    contemporary_wide = contemporary_wide[['decade', 'prop']].sort_values('decade', ascending=True)\n",
    "\n",
    "    fig = px.bar(contemporary_wide, x=\"decade\", y='prop',\n",
    "                    title=f'Number of venues that existed in each decade, {term}')\n",
    "\n",
    "    # remove y-axis label\n",
    "    fig.update_yaxes(title_text='')\n",
    "    fig.update_xaxes(title_text='')\n",
    "\n",
    "    # make figure size bigger\n",
    "    # fig.update_layout(\n",
    "    #     autosize=False,\n",
    "    #     width=700,\n",
    "    #     height=400,\n",
    "    # )\n",
    "\n",
    "    fig.show()"
   ]
  }
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