examples/tutorial-2-sars-cov-2.ipynb

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   "source": [
    "# Tutorial 2: Indexing assemblies (SARS-CoV-2 dataset)\n",
    "\n",
    "# 1. Background\n",
    "\n",
    "This tutorial shows you how to construct an index of assembled genomes for querying and visualization. The data consists of a set of 50 SARS-CoV-2 genomes downloaded from the NCBI Virus portal (https://www.ncbi.nlm.nih.gov/labs/virus/) on May 31, 2021.\n",
    "\n",
    "# 2. Getting data\n",
    "\n",
    "Let's first download the data for this tutorial. To do this please run the below commands:\n",
    "\n",
    "*Note: In a Jupyter Python notebook, prepending a command with `!` runs the command in a shell instead of the Python interpreter (e.g., `!unzip` runs the command `unzip`).*"
   ]
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--2022-12-15 15:37:25--  https://ndownloader.figshare.com/files/29095476?private_link=e54aded21bb036071aac\n",
      "Resolving ndownloader.figshare.com (ndownloader.figshare.com)... 52.16.102.173, 54.217.124.219, 2a05:d018:1f4:d003:1c8b:1823:acce:812, ...\n",
      "Connecting to ndownloader.figshare.com (ndownloader.figshare.com)|52.16.102.173|:443... connected.\n",
      "HTTP request sent, awaiting response... 302 Found\n",
      "Location: https://s3-eu-west-1.amazonaws.com/pfigshare-u-files/29095476/sarscov2genbank50.zip?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAIYCQYOYV5JSSROOA/20221215/eu-west-1/s3/aws4_request&X-Amz-Date=20221215T213726Z&X-Amz-Expires=10&X-Amz-SignedHeaders=host&X-Amz-Signature=05472f210b3541fca9dde05e9f73357d6f678b9563d997be7e7ca88bff6c07db [following]\n",
      "--2022-12-15 15:37:26--  https://s3-eu-west-1.amazonaws.com/pfigshare-u-files/29095476/sarscov2genbank50.zip?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAIYCQYOYV5JSSROOA/20221215/eu-west-1/s3/aws4_request&X-Amz-Date=20221215T213726Z&X-Amz-Expires=10&X-Amz-SignedHeaders=host&X-Amz-Signature=05472f210b3541fca9dde05e9f73357d6f678b9563d997be7e7ca88bff6c07db\n",
      "Resolving s3-eu-west-1.amazonaws.com (s3-eu-west-1.amazonaws.com)... 52.218.84.122, 52.218.109.19, 52.92.18.160, ...\n",
      "Connecting to s3-eu-west-1.amazonaws.com (s3-eu-west-1.amazonaws.com)|52.218.84.122|:443... connected.\n",
      "HTTP request sent, awaiting response... 200 OK\n",
      "Length: 491853 (480K) [application/zip]\n",
      "Saving to: ‘sars-cov-2-genbank-50.zip’\n",
      "\n",
      "sars-cov-2-genbank- 100%[===================>] 480.33K   672KB/s    in 0.7s    \n",
      "\n",
      "2022-12-15 15:37:27 (672 KB/s) - ‘sars-cov-2-genbank-50.zip’ saved [491853/491853]\n",
      "\n",
      "Archive:  sars-cov-2-genbank-50.zip\n",
      "   creating: sars-cov-2-genbank-50/\n",
      "   creating: sars-cov-2-genbank-50/fasta/\n"
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   "source": [
    "!wget -O sars-cov-2-genbank-50.zip https://ndownloader.figshare.com/files/29095476?private_link=e54aded21bb036071aac\n",
    "!unzip -n sars-cov-2-genbank-50.zip | head -n 3"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2da28c89-6435-42a4-968d-a082cd8f3aa6",
   "metadata": {},
   "source": [
    "## 2.1. Examine data\n",
    "\n",
    "Let's look at what files are available in this dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "7ca24edc-3bde-4793-a203-1dacc110ccdb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "fasta/\treference/  sars-cov-2.metadata.csv  tree.newick\n"
     ]
    }
   ],
   "source": [
    "!ls -F sars-cov-2-genbank-50"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1b271eb9-246e-44c2-9060-d5af002beb71",
   "metadata": {},
   "source": [
    "There is a file of metadata `sars-cov-2.metadata.csv` (from NCBI) which looks like:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "b40484c8-4d85-4d50-9cfd-84265f0f82b6",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Accession</th>\n",
       "      <th>Submitters</th>\n",
       "      <th>Release_Date</th>\n",
       "      <th>Pangolin</th>\n",
       "      <th>Species</th>\n",
       "      <th>Molecule_type</th>\n",
       "      <th>Length</th>\n",
       "      <th>Sequence_Type</th>\n",
       "      <th>Genotype</th>\n",
       "      <th>Geo_Location</th>\n",
       "      <th>USA</th>\n",
       "      <th>Host</th>\n",
       "      <th>Isolation_Source</th>\n",
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       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>MW023498.1</td>\n",
       "      <td>Schmedes,S., Blanton,J.</td>\n",
       "      <td>2020-09-21T00:00:00Z</td>\n",
       "      <td>A</td>\n",
       "      <td>Severe acute respiratory syndrome-related coro...</td>\n",
       "      <td>ssRNA(+)</td>\n",
       "      <td>29812</td>\n",
       "      <td>GenBank</td>\n",
       "      <td>NaN</td>\n",
       "      <td>USA: FL</td>\n",
       "      <td>FL</td>\n",
       "      <td>Homo sapiens</td>\n",
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       "      <td>2020-03-30</td>\n",
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       "      <th>1</th>\n",
       "      <td>MT704130.1</td>\n",
       "      <td>Keller,E.</td>\n",
       "      <td>2020-07-02T00:00:00Z</td>\n",
       "      <td>A</td>\n",
       "      <td>Severe acute respiratory syndrome-related coro...</td>\n",
       "      <td>ssRNA(+)</td>\n",
       "      <td>29873</td>\n",
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       "      <td>USA: MD</td>\n",
       "      <td>MD</td>\n",
       "      <td>Homo sapiens</td>\n",
       "      <td>oronasopharynx</td>\n",
       "      <td>2020-04-07</td>\n",
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       "    Accession               Submitters          Release_Date Pangolin  \\\n",
       "0  MW023498.1  Schmedes,S., Blanton,J.  2020-09-21T00:00:00Z        A   \n",
       "1  MT704130.1                Keller,E.  2020-07-02T00:00:00Z        A   \n",
       "\n",
       "                                             Species Molecule_type  Length  \\\n",
       "0  Severe acute respiratory syndrome-related coro...      ssRNA(+)   29812   \n",
       "1  Severe acute respiratory syndrome-related coro...      ssRNA(+)   29873   \n",
       "\n",
       "  Sequence_Type  Genotype Geo_Location USA          Host Isolation_Source  \\\n",
       "0       GenBank       NaN      USA: FL  FL  Homo sapiens              NaN   \n",
       "1       GenBank       NaN      USA: MD  MD  Homo sapiens   oronasopharynx   \n",
       "\n",
       "  Collection_Date BioSample  \n",
       "0      2020-03-30       NaN  \n",
       "1      2020-04-07       NaN  "
      ]
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     "execution_count": 3,
     "metadata": {},
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    }
   ],
   "source": [
    "import pandas as pd\n",
    "pd.read_csv('sars-cov-2-genbank-50/sars-cov-2.metadata.csv').head(2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d9725c3b-a447-447f-88c5-ffe7cba11749",
   "metadata": {},
   "source": [
    "There's a reference genome in the `reference/` directory:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "ab4e29b6-73d8-49ea-a54b-21a214a1816e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NC_045512.gbk.gz\n"
     ]
    }
   ],
   "source": [
    "!ls sars-cov-2-genbank-50/reference"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3d0ed1f3-e284-4c3c-8cc8-8312712b5fd6",
   "metadata": {},
   "source": [
    "And, there are the input SARS-CoV-2 genomes in the `fasta/` directory, one genome per file:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "47451196-db24-460a-b09d-4fb4fcc03daa",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "FR989650.1.fasta.gz\n",
      "FR990962.1.fasta.gz\n",
      "FR993910.1.fasta.gz\n",
      "FR995660.1.fasta.gz\n",
      "FR996003.1.fasta.gz\n",
      "FR996164.1.fasta.gz\n",
      "FR999475.1.fasta.gz\n",
      "HG997074.1.fasta.gz\n",
      "MT292574.1.fasta.gz\n",
      "MT375477.1.fasta.gz\n"
     ]
    }
   ],
   "source": [
    "!ls sars-cov-2-genbank-50/fasta | head"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a315eb4d-ad8f-465b-b4b5-9c9035fbf663",
   "metadata": {},
   "source": [
    "Now that we've seen the input data, let's go through generating an index.\n",
    "\n",
    "# 3. Create an index\n",
    "\n",
    "Before we create an index, let's first look at which version of `gdi` we are using."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "19df6d1d-2607-433a-b993-a67c9bf8f100",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "gdi, version 0.9.2\n"
     ]
    }
   ],
   "source": [
    "!gdi --version"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f274a7e2-7436-4370-8201-d7d8e92bc21e",
   "metadata": {},
   "source": [
    "## 3.1. Initialize an index\n",
    "\n",
    "To create an index, we use the command `gdi init [project]` to construct an project/index directory where we can then load up data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "211ab0f9-9eaa-4a59-8423-92f44eccb71f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Initializing empty project in [sars-cov-2-index]\n"
     ]
    }
   ],
   "source": [
    "!gdi init sars-cov-2-index"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "305e1109-ffb9-4f8d-9e86-ee2067b76e61",
   "metadata": {},
   "source": [
    "This will create a directory `sars-cov-2-index` which contains the empty index. If we look inside this directory we can see:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "d0df0bb5-2938-4910-bdfd-0b4277c15a3e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      ".  ..  gdi-config.yaml\t.gdi-data\n"
     ]
    }
   ],
   "source": [
    "!ls -a sars-cov-2-index"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "746220d5-6d7e-4d6e-aba1-6fa60460b57d",
   "metadata": {},
   "source": [
    "We see a config file `gdi-config.yaml` which defines some configuration settings:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "74c811f2-3448-4a7c-a7e8-3d419ba3c4e5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "database_dir: .gdi-data\n",
      "sqlite_database: .gdi-data/gdi-db.sqlite\n"
     ]
    }
   ],
   "source": [
    "!cat sars-cov-2-index/gdi-config.yaml"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "972bc2ab-1b1a-4443-8494-4cf89581ae2e",
   "metadata": {},
   "source": [
    "Specifically, this file defines the data directory which is used to store VCF/mash/other files. As well as a SQLite database connection path.\n",
    "\n",
    "The `.gdi-data` directory will initially be empty, but will be filled with data as we load data into the index.\n",
    "\n",
    "*Note: you can change from SQLite to another database by removing `sqlite_database=.gdi-data/gdi-db.sqlite` and adding `database_connection=dialect+driver://username:password@host:port/database`, where `dialect+driver...` refers to a [SQLAlchemy-compatible connection string](https://docs.sqlalchemy.org/en/14/core/engines.html#database-urls).*"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8d4b9b77-eb0e-4dc3-844f-ddddecbbe86e",
   "metadata": {},
   "source": [
    "## 3.2. Index mutations and kmers\n",
    "\n",
    "To index assembled genomes we can use the command `gdi --project-dir sars-cov-2-index analysis [...]`.\n",
    "\n",
    "The project directory must be specified with `--project-dir`. Or, alternatively, you can `cd sars-cov-2-index` and then run `gdi analysis [...]` and leave out the `--project-dir`.\n",
    "\n",
    "Indexing will align the assembled genomes to some reference genome using [minimap2](https://github.com/lh3/minimap2) (for identifying mutations in VCF format) and will also run [sourmash](https://sourmash.readthedocs.io/) for construcing kmer sketches. This is all scheduled using a [Snakemake](https://snakemake.readthedocs.io/) workflow."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "a0cf1ce7-5912-4c97-b89b-ad3125c850aa",
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     "text": [
      "\u001b[32m2022-12-15 15:37:38\u001b[0m \u001b[1;30mINFO:\u001b[0m Automatically structuring 50 input files into assemblies/reads\n",
      "\u001b[32m2022-12-15 15:37:38\u001b[0m \u001b[1;30mINFO:\u001b[0m Processing 50 genomes to identify mutations\n",
      "\u001b[32m2022-12-15 15:37:38\u001b[0m \u001b[1;30mINFO:\u001b[0m Including snpeff annotations in snakemake results\n",
      "\u001b[32m2022-12-15 15:37:38\u001b[0m \u001b[1;30mINFO:\u001b[0m Running Snakemake for rule all\n",
      "\u001b[32m2022-12-15 15:40:44\u001b[0m \u001b[1;30mINFO:\u001b[0m Finished running snakemake.\n",
      "\u001b[32m2022-12-15 15:40:44\u001b[0m \u001b[1;30mINFO:\u001b[0m Indexing processed VCF files defined in [/home/CSCScience.ca/apetkau/workspace/genomics-data-index-examples/examples/snakemake-assemblies.1671140258.212381/gdi-input.fofn]\n",
      "\u001b[32m2022-12-15 15:40:44\u001b[0m \u001b[1;30mWARNING:\u001b[0m \u001b[33mAttempting to set global database_path_translator=<genomics_data_index.storage.model.db.DatabasePathTranslator.DatabasePathTranslator object at 0x7f05f27e6e20> but it is already set\u001b[0m\n",
      "\u001b[32m2022-12-15 15:40:44\u001b[0m \u001b[1;30mINFO:\u001b[0m Attempting to load reference genome=[sars-cov-2-genbank-50/reference/NC_045512.gbk.gz]\n",
      "\u001b[32m2022-12-15 15:40:45\u001b[0m \u001b[1;30mINFO:\u001b[0m Sample batch 1/1: Stage 1/2 (Insert): Processed 0% (0/50) samples\n",
      "\u001b[32m2022-12-15 15:40:45\u001b[0m \u001b[1;30mINFO:\u001b[0m Sample batch 1/1: Stage 1/2 (Insert): Processed 10% (5/50) samples\n",
      "\u001b[32m2022-12-15 15:40:45\u001b[0m \u001b[1;30mINFO:\u001b[0m Sample batch 1/1: Stage 1/2 (Insert): Processed 20% (10/50) samples\n",
      "\u001b[32m2022-12-15 15:40:45\u001b[0m \u001b[1;30mINFO:\u001b[0m Sample batch 1/1: Stage 1/2 (Insert): Processed 30% (15/50) samples\n",
      "\u001b[32m2022-12-15 15:40:45\u001b[0m \u001b[1;30mINFO:\u001b[0m Sample batch 1/1: Stage 1/2 (Insert): Processed 40% (20/50) samples\n",
      "\u001b[32m2022-12-15 15:40:45\u001b[0m \u001b[1;30mINFO:\u001b[0m Sample batch 1/1: Stage 1/2 (Insert): Processed 50% (25/50) samples\n",
      "\u001b[32m2022-12-15 15:40:45\u001b[0m \u001b[1;30mINFO:\u001b[0m Sample batch 1/1: Stage 1/2 (Insert): Processed 60% (30/50) samples\n",
      "\u001b[32m2022-12-15 15:40:45\u001b[0m \u001b[1;30mINFO:\u001b[0m Sample batch 1/1: Stage 1/2 (Insert): Processed 70% (35/50) samples\n",
      "\u001b[32m2022-12-15 15:40:45\u001b[0m \u001b[1;30mINFO:\u001b[0m Sample batch 1/1: Stage 1/2 (Insert): Processed 80% (40/50) samples\n",
      "\u001b[32m2022-12-15 15:40:45\u001b[0m \u001b[1;30mINFO:\u001b[0m Sample batch 1/1: Stage 1/2 (Insert): Processed 90% (45/50) samples\n",
      "\u001b[32m2022-12-15 15:40:45\u001b[0m \u001b[1;30mINFO:\u001b[0m Sample batch 1/1: Stage 1/2 (Insert): Processed 100% (50/50) samples\n",
      "\u001b[32m2022-12-15 15:40:45\u001b[0m \u001b[1;30mINFO:\u001b[0m Finished processing 50 samples\n",
      "\u001b[32m2022-12-15 15:40:45\u001b[0m \u001b[1;30mINFO:\u001b[0m Reading features from 50 samples\n",
      "\u001b[32m2022-12-15 15:40:45\u001b[0m \u001b[1;30mINFO:\u001b[0m Sample batch 1/1: Stage 2/2 (Index): Processed 0% (0/50) samples\n",
      "\u001b[32m2022-12-15 15:40:46\u001b[0m \u001b[1;30mINFO:\u001b[0m Sample batch 1/1: Stage 2/2 (Index): Processed 0% (0/50) samples\n",
      "\u001b[32m2022-12-15 15:40:46\u001b[0m \u001b[1;30mINFO:\u001b[0m Sample batch 1/1: Stage 2/2 (Index): Processed 2% (1/50) samples\n",
      "\u001b[32m2022-12-15 15:40:46\u001b[0m \u001b[1;30mINFO:\u001b[0m Sample batch 1/1: Stage 2/2 (Index): Processed 4% (2/50) samples\n",
      "\u001b[32m2022-12-15 15:40:46\u001b[0m \u001b[1;30mINFO:\u001b[0m Sample batch 1/1: Stage 2/2 (Index): Processed 6% (3/50) samples\n",
      "\u001b[32m2022-12-15 15:40:46\u001b[0m \u001b[1;30mINFO:\u001b[0m Sample batch 1/1: Stage 2/2 (Index): Processed 8% (4/50) samples\n",
      "\u001b[32m2022-12-15 15:40:46\u001b[0m \u001b[1;30mINFO:\u001b[0m Sample batch 1/1: Stage 2/2 (Index): Processed 10% (5/50) samples\n",
      "\u001b[32m2022-12-15 15:40:46\u001b[0m \u001b[1;30mINFO:\u001b[0m Sample batch 1/1: Stage 2/2 (Index): Processed 12% (6/50) samples\n",
      "\u001b[32m2022-12-15 15:40:46\u001b[0m \u001b[1;30mINFO:\u001b[0m Sample batch 1/1: Stage 2/2 (Index): Processed 14% (7/50) samples\n",
      "\u001b[32m2022-12-15 15:40:46\u001b[0m \u001b[1;30mINFO:\u001b[0m Sample batch 1/1: Stage 2/2 (Index): Processed 16% (8/50) samples\n",
      "\u001b[32m2022-12-15 15:40:46\u001b[0m \u001b[1;30mINFO:\u001b[0m Sample batch 1/1: Stage 2/2 (Index): Processed 18% (9/50) samples\n",
      "\u001b[32m2022-12-15 15:40:46\u001b[0m \u001b[1;30mINFO:\u001b[0m Sample batch 1/1: Stage 2/2 (Index): Processed 20% (10/50) samples\n",
      "\u001b[32m2022-12-15 15:40:46\u001b[0m \u001b[1;30mINFO:\u001b[0m Sample batch 1/1: Stage 2/2 (Index): Processed 22% (11/50) samples\n",
      "\u001b[32m2022-12-15 15:40:46\u001b[0m \u001b[1;30mINFO:\u001b[0m Sample batch 1/1: Stage 2/2 (Index): Processed 24% (12/50) samples\n",
      "\u001b[32m2022-12-15 15:40:46\u001b[0m \u001b[1;30mINFO:\u001b[0m Sample batch 1/1: Stage 2/2 (Index): Processed 26% (13/50) samples\n",
      "\u001b[32m2022-12-15 15:40:46\u001b[0m \u001b[1;30mINFO:\u001b[0m Sample batch 1/1: Stage 2/2 (Index): Processed 28% (14/50) samples\n",
      "\u001b[32m2022-12-15 15:40:46\u001b[0m \u001b[1;30mINFO:\u001b[0m Sample batch 1/1: Stage 2/2 (Index): Processed 30% (15/50) samples\n",
      "\u001b[32m2022-12-15 15:40:46\u001b[0m \u001b[1;30mINFO:\u001b[0m Sample batch 1/1: Stage 2/2 (Index): Processed 32% (16/50) samples\n",
      "\u001b[32m2022-12-15 15:40:46\u001b[0m \u001b[1;30mINFO:\u001b[0m Sample batch 1/1: Stage 2/2 (Index): Processed 34% (17/50) samples\n",
      "\u001b[32m2022-12-15 15:40:46\u001b[0m \u001b[1;30mINFO:\u001b[0m Sample batch 1/1: Stage 2/2 (Index): Processed 36% (18/50) samples\n",
      "\u001b[32m2022-12-15 15:40:46\u001b[0m \u001b[1;30mINFO:\u001b[0m Sample batch 1/1: Stage 2/2 (Index): Processed 38% (19/50) samples\n",
      "\u001b[32m2022-12-15 15:40:46\u001b[0m \u001b[1;30mINFO:\u001b[0m Sample batch 1/1: Stage 2/2 (Index): Processed 40% (20/50) samples\n",
      "\u001b[32m2022-12-15 15:40:46\u001b[0m \u001b[1;30mINFO:\u001b[0m Sample batch 1/1: Stage 2/2 (Index): Processed 42% (21/50) samples\n",
      "\u001b[32m2022-12-15 15:40:46\u001b[0m \u001b[1;30mINFO:\u001b[0m Sample batch 1/1: Stage 2/2 (Index): Processed 44% (22/50) samples\n",
      "\u001b[32m2022-12-15 15:40:46\u001b[0m \u001b[1;30mINFO:\u001b[0m Sample batch 1/1: Stage 2/2 (Index): Processed 46% (23/50) samples\n",
      "\u001b[32m2022-12-15 15:40:46\u001b[0m \u001b[1;30mINFO:\u001b[0m Sample batch 1/1: Stage 2/2 (Index): Processed 48% (24/50) samples\n",
      "\u001b[32m2022-12-15 15:40:46\u001b[0m \u001b[1;30mINFO:\u001b[0m Sample batch 1/1: Stage 2/2 (Index): Processed 50% (25/50) samples\n",
      "\u001b[32m2022-12-15 15:40:46\u001b[0m \u001b[1;30mINFO:\u001b[0m Sample batch 1/1: Stage 2/2 (Index): Processed 52% (26/50) samples\n",
      "\u001b[32m2022-12-15 15:40:46\u001b[0m \u001b[1;30mINFO:\u001b[0m Sample batch 1/1: Stage 2/2 (Index): Processed 54% (27/50) samples\n",
      "\u001b[32m2022-12-15 15:40:46\u001b[0m \u001b[1;30mINFO:\u001b[0m Sample batch 1/1: Stage 2/2 (Index): Processed 56% (28/50) samples\n",
      "\u001b[32m2022-12-15 15:40:46\u001b[0m \u001b[1;30mINFO:\u001b[0m Sample batch 1/1: Stage 2/2 (Index): Processed 58% (29/50) samples\n",
      "\u001b[32m2022-12-15 15:40:46\u001b[0m \u001b[1;30mINFO:\u001b[0m Sample batch 1/1: Stage 2/2 (Index): Processed 60% (30/50) samples\n",
      "\u001b[32m2022-12-15 15:40:46\u001b[0m \u001b[1;30mINFO:\u001b[0m Sample batch 1/1: Stage 2/2 (Index): Processed 62% (31/50) samples\n",
      "\u001b[32m2022-12-15 15:40:46\u001b[0m \u001b[1;30mINFO:\u001b[0m Sample batch 1/1: Stage 2/2 (Index): Processed 64% (32/50) samples\n",
      "\u001b[32m2022-12-15 15:40:46\u001b[0m \u001b[1;30mINFO:\u001b[0m Sample batch 1/1: Stage 2/2 (Index): Processed 66% (33/50) samples\n",
      "\u001b[32m2022-12-15 15:40:46\u001b[0m \u001b[1;30mINFO:\u001b[0m Sample batch 1/1: Stage 2/2 (Index): Processed 68% (34/50) samples\n",
      "\u001b[32m2022-12-15 15:40:46\u001b[0m \u001b[1;30mINFO:\u001b[0m Sample batch 1/1: Stage 2/2 (Index): Processed 70% (35/50) samples\n",
      "\u001b[32m2022-12-15 15:40:46\u001b[0m \u001b[1;30mINFO:\u001b[0m Sample batch 1/1: Stage 2/2 (Index): Processed 72% (36/50) samples\n",
      "\u001b[32m2022-12-15 15:40:46\u001b[0m \u001b[1;30mINFO:\u001b[0m Sample batch 1/1: Stage 2/2 (Index): Processed 74% (37/50) samples\n",
      "\u001b[32m2022-12-15 15:40:46\u001b[0m \u001b[1;30mINFO:\u001b[0m Sample batch 1/1: Stage 2/2 (Index): Processed 76% (38/50) samples\n",
      "\u001b[32m2022-12-15 15:40:46\u001b[0m \u001b[1;30mINFO:\u001b[0m Sample batch 1/1: Stage 2/2 (Index): Processed 78% (39/50) samples\n",
      "\u001b[32m2022-12-15 15:40:46\u001b[0m \u001b[1;30mINFO:\u001b[0m Sample batch 1/1: Stage 2/2 (Index): Processed 80% (40/50) samples\n",
      "\u001b[32m2022-12-15 15:40:46\u001b[0m \u001b[1;30mINFO:\u001b[0m Sample batch 1/1: Stage 2/2 (Index): Processed 82% (41/50) samples\n",
      "\u001b[32m2022-12-15 15:40:46\u001b[0m \u001b[1;30mINFO:\u001b[0m Sample batch 1/1: Stage 2/2 (Index): Processed 84% (42/50) samples\n",
      "\u001b[32m2022-12-15 15:40:46\u001b[0m \u001b[1;30mINFO:\u001b[0m Sample batch 1/1: Stage 2/2 (Index): Processed 86% (43/50) samples\n",
      "\u001b[32m2022-12-15 15:40:46\u001b[0m \u001b[1;30mINFO:\u001b[0m Sample batch 1/1: Stage 2/2 (Index): Processed 88% (44/50) samples\n",
      "\u001b[32m2022-12-15 15:40:46\u001b[0m \u001b[1;30mINFO:\u001b[0m Sample batch 1/1: Stage 2/2 (Index): Processed 90% (45/50) samples\n",
      "\u001b[32m2022-12-15 15:40:46\u001b[0m \u001b[1;30mINFO:\u001b[0m Sample batch 1/1: Stage 2/2 (Index): Processed 92% (46/50) samples\n",
      "\u001b[32m2022-12-15 15:40:46\u001b[0m \u001b[1;30mINFO:\u001b[0m Sample batch 1/1: Stage 2/2 (Index): Processed 94% (47/50) samples\n",
      "\u001b[32m2022-12-15 15:40:46\u001b[0m \u001b[1;30mINFO:\u001b[0m Sample batch 1/1: Stage 2/2 (Index): Processed 96% (48/50) samples\n",
      "\u001b[32m2022-12-15 15:40:46\u001b[0m \u001b[1;30mINFO:\u001b[0m Sample batch 1/1: Stage 2/2 (Index): Processed 98% (49/50) samples\n",
      "\u001b[32m2022-12-15 15:40:46\u001b[0m \u001b[1;30mINFO:\u001b[0m Sample batch 1/1: Stage 2/2 (Index): Processed 100% (50/50) samples\n",
      "\u001b[32m2022-12-15 15:40:46\u001b[0m \u001b[1;30mINFO:\u001b[0m Aggregating 99908 features found in 50 samples\n",
      "\u001b[32m2022-12-15 15:40:52\u001b[0m \u001b[1;30mINFO:\u001b[0m A total of 24612 unique features across 50 samples will be updated. Searching for existing features in the database.\n",
      "\u001b[32m2022-12-15 15:40:52\u001b[0m \u001b[1;30mINFO:\u001b[0m Found 0/24612 features in database which already exist. These features will be updated to map to the new samples.\n",
      "\u001b[32m2022-12-15 15:40:52\u001b[0m \u001b[1;30mINFO:\u001b[0m Updating 0/24612 existing features in database\n",
      "\u001b[32m2022-12-15 15:40:52\u001b[0m \u001b[1;30mINFO:\u001b[0m Saving 24612/24612 new features in database\n",
      "\u001b[32m2022-12-15 15:40:53\u001b[0m \u001b[1;30mINFO:\u001b[0m Finished indexing features from 50 samples\n",
      "\u001b[32m2022-12-15 15:40:53\u001b[0m \u001b[1;30mINFO:\u001b[0m Loaded variants from [/home/CSCScience.ca/apetkau/workspace/genomics-data-index-examples/examples/snakemake-assemblies.1671140258.212381/gdi-input.fofn] into database\n",
      "\u001b[32m2022-12-15 15:40:53\u001b[0m \u001b[1;30mINFO:\u001b[0m Inserting kmer sketches for 50 samples into the database\n",
      "\u001b[32m2022-12-15 15:40:54\u001b[0m \u001b[1;30mINFO:\u001b[0m --clean is enabled so deleting [/home/CSCScience.ca/apetkau/workspace/genomics-data-index-examples/examples/snakemake-assemblies.1671140258.212381]\n"
     ]
    }
   ],
   "source": [
    "!gdi --project-dir sars-cov-2-index analysis \\\n",
    "    --reference-file sars-cov-2-genbank-50/reference/NC_045512.gbk.gz \\\n",
    "    --include-kmer \\\n",
    "    --kmer-size 31 --kmer-size 51 --kmer-size 71 \\\n",
    "    --kmer-scaled 100 \\\n",
    "    sars-cov-2-genbank-50/fasta/*.fasta.gz"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "25107694-837b-4cd9-980e-305d8a614879",
   "metadata": {},
   "source": [
    "The different parameters are interpreted as follows:\n",
    "    \n",
    "* `--reference-file`: Path to the reference file used for alignment. If you wish to use amino-acids for variant identifiers please specify a Genbank file with gene annotations to use with **snpeff**.\n",
    "* `--use-conda`: Install workflow dependencies using conda\n",
    "* `--include-kmer`: Include kmer (sourmash) sketches.\n",
    "* `--kmer-size`: Specify the kmer-sizes for sourmash.\n",
    "* `--kmer-scaled`: Specify the scaling factor for sourmash.\n",
    "* `sars-cov-2-genbank-50/fasta/*.fasta.gz`: The input genomes to index (assembled genomes).\n",
    "\n",
    "By default, this will use the maximum number of cores available on your machine for processing. This can be adjusted with `gdi --ncores [ncores]`.\n",
    "\n",
    "Note, the slower part of this will likely be installing the tools using conda/mamba.\n",
    "\n",
    "When everything is completed, the index directory `sars-cov-2-index/` should now have data within it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "7e2aa202-32ad-4070-b706-4a55f5fc685c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "gdi-db.sqlite  kmer  mlst  reference  variation\n"
     ]
    }
   ],
   "source": [
    "!ls sars-cov-2-index/.gdi-data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ef49e812-7ba4-4096-9797-098e7ebb4881",
   "metadata": {},
   "source": [
    "## 3.3. Build phylogenetic tree\n",
    "\n",
    "In addition to indexing mutations or kmer sketches, a phylogenetic tree can be built and saved using all genomes aligned to some specific reference genome. This can be accomplished with the `gdi rebuild tree` command.\n",
    "\n",
    "This command requires us to specify the reference genome name. This is derived from the file defined above, but to view all reference genome names you can use the `gdi list genomes` command."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "f7be9d9a-561f-4c26-8b40-2abca8874a70",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NC_045512\n"
     ]
    }
   ],
   "source": [
    "!gdi --project-dir sars-cov-2-index list genomes"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "024ad8f3-7078-48dd-a447-a95e93834a6a",
   "metadata": {},
   "source": [
    "Now that we have a reference genome, let's build a tree. This uses [iqtree](http://www.iqtree.org/) by default.\n",
    "\n",
    "*Note: if you wish you can skip this step and instead you can use the provided tree in `sars-cov-2-genbank-50/tree.newick` when querying. You will have to remember to join a tree to a query with [query.join_tree()](https://github.com/apetkau/genomics-data-index/blob/development/genomics_data_index/api/query/SamplesQuery.py#L177-L188).*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "264dc952-f52e-4b23-91f4-6d699cb97acb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32m2022-12-15 15:41:02\u001b[0m \u001b[1;30mINFO:\u001b[0m Started rebuilding tree for reference genome [NC_045512]\n",
      "\u001b[32m2022-12-15 15:41:02\u001b[0m \u001b[1;30mINFO:\u001b[0m Started building alignment for 50 samples with include_variants=['SNP', 'MNP', 'DELETION']\n",
      "\u001b[32m2022-12-15 15:41:05\u001b[0m \u001b[1;30mINFO:\u001b[0m Finished building alignment for 50 samples. Took 2.74 seconds\n",
      "\u001b[32m2022-12-15 15:41:07\u001b[0m \u001b[1;30mINFO:\u001b[0m Finished rebuilding tree\n"
     ]
    }
   ],
   "source": [
    "!gdi --project-dir sars-cov-2-index/ rebuild tree --align-type full --extra-params '--fast -m GTR+F+R4' NC_045512"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "928072e1-3471-488a-9e3f-e1ee186fba88",
   "metadata": {},
   "source": [
    "The parameters are interpreted as follows:\n",
    "\n",
    "* `--align-type full`: Use `full` to include all positions on the reference genome (29,903 bp in this case). Use `core` to include only core SNV-containing positions. Note that the tree is built using only SNVs (SNPs), indels or complex variants/mutations are excluded.\n",
    "* `--extra-params`: Extra parameters to pass to `iqtree`. I am specifying the model here to speed up building a tree. Specifying extra parameters is optional.\n",
    "* `NC_045512`: The name of the reference genome to use for building a tree.\n",
    "\n",
    "Once everything is complete you can export the tree in newick format as follows:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "1b0a1a30-a2f9-40e4-83ea-ad5401ea7228",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(FR989650.1:1e-06,((((((((((FR990962.1:0.000368037,((((((FR995660.1:1e-06,MT612123.1:6.68889e-05)1:1e-06,MT292574.1:3.3443e-05)1:0.000167245,(((MT704130.1:7.28805e-05,MW023498.1:3.3443e-05)1:7.25976e-05,MW190745.1:0.000100338)1:0.000255867,(MW667352.1:0.000100338,MZ000016.1:0.000312487)1:0.000606117)1:1e-06)1:1e-06,(MT375477.1:0.00013379,(MT627305.1:1e-06,MT633037.1:1e-06)1:1e-06)1:0.000100338)1:6.68889e-05,MW467468.1:0.000267627)1:1e-06,NC_045512:1e-06)1:0.00013379)1:1e-06,((FR993910.1:1e-06,MW637368.1:0.000285572)1:1e-06,(((FR999475.1:0.000167245,OB983396.1:0.000474555)1:1e-06,(OA980698.1:0.00013379,OA981378.1:6.68889e-05)1:3.3443e-05)1:1e-06,((MW436729.1:0.000108059,MW750847.1:0.000368419)1:2.0138e-06,OA979942.1:0.000321686)1:3.3443e-05)1:1e-06)1:1e-06)1:1e-06,((MW422101.1:0.000167245,MW539929.1:0.000236442)1:3.3443e-05,((MW493710.1:3.3443e-05,(((((MW639604.1:0.000148747,MW780358.1:0.000237657)1:2.0138e-06,MW780412.1:0.00047732)1:0.000386853,MW734415.1:0.000134309)1:4.82857e-05,(MW639621.1:0.000188721,MW834830.1:0.000616461)1:2.0138e-06)1:2.8216e-06,MW674816.1:0.000100338)1:1e-06)1:1e-06,OA970392.1:0.000200703)1:3.3443e-05)1:3.3443e-05)1:1e-06,MW672666.1:1e-06)1:1e-06,MW922928.1:1e-06)1:1e-06,((FR996003.1:5.08313e-05,HG997074.1:0.000256566)1:5.08684e-05,FR996164.1:6.68889e-05)1:1e-06)1:0.000116836,(MW780989.1:0.000263098,MZ039749.1:0.000846044)1:0.000167896)1:0.000352124,OA972232.1:0.000100338)1:1e-06,OA969796.1:1e-06)1:1e-06,(OA992224.1:0.00013379,(((OA992920.1:6.68889e-05,(OA996868.1:3.3443e-05,OD898064.1:0.000237052)1:1e-06)1:1e-06,OA997286.1:1e-06)1:1e-06,OA999333.1:3.3443e-05)1:1e-06)1:3.3443e-05)1:3.3443e-05,OA994670.1:1e-06);\n"
     ]
    }
   ],
   "source": [
    "!gdi --project-dir sars-cov-2-index export tree NC_045512"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "35131c2f-86c3-4f6c-ac12-dcab44c5e893",
   "metadata": {},
   "source": [
    "# 4. Basic querying/visualization\n",
    "\n",
    "Once you have the index setup you can do some basic querying as follows.\n",
    "\n",
    "I include this here to show a complete tutorial of both indexing and working with data. For an additional querying tutorial please see [Tutorial 1](https://github.com/apetkau/genomics-data-index/blob/development/docs/tutorial/tutorial-1-salmonella.ipynb).\n",
    "\n",
    "## 4.1. Command-line interface\n",
    "\n",
    "### 4.1.1. List samples"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "d6b26b76-0d21-452c-b88f-7fde8c790b6a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MW734415.1\n",
      "MW639604.1\n",
      "HG997074.1\n",
      "OA972232.1\n",
      "FR990962.1\n",
      "FR999475.1\n",
      "MW637368.1\n",
      "MT375477.1\n",
      "MW493710.1\n",
      "FR989650.1\n"
     ]
    }
   ],
   "source": [
    "!gdi --project-dir sars-cov-2-index list samples | head"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ed5adaac-54f2-4afa-bbd2-0c61aa0b5223",
   "metadata": {},
   "source": [
    "### 4.1.2. List reference genomes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "428f6f4f-c566-4f61-b5e0-7cc24ee7b80e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NC_045512\n"
     ]
    }
   ],
   "source": [
    "!gdi --project-dir sars-cov-2-index list genomes"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "854010cb-cfe5-495c-87a1-1deb8eefa1e3",
   "metadata": {},
   "source": [
    "## 4.2. Python API\n",
    "\n",
    "First lets connect to the index in the directory `sars-cov-2-index`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "054ad822-d8fc-4a3c-b8de-01a5ef04ce42",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<GenomicsDataIndex(samples=50)>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import genomics_data_index.api as gdi\n",
    "\n",
    "db = gdi.GenomicsDataIndex.connect('sars-cov-2-index')\n",
    "db"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5c1ce4e6-b98d-4d56-b57c-c2af5ff30845",
   "metadata": {},
   "source": [
    "Now let's load up the dataframe of provided metadata."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "69f68304-d278-4dc7-a7fc-64de44c07089",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Accession</th>\n",
       "      <th>Submitters</th>\n",
       "      <th>Release_Date</th>\n",
       "      <th>Pangolin</th>\n",
       "      <th>Species</th>\n",
       "      <th>Molecule_type</th>\n",
       "      <th>Length</th>\n",
       "      <th>Sequence_Type</th>\n",
       "      <th>Genotype</th>\n",
       "      <th>Geo_Location</th>\n",
       "      <th>USA</th>\n",
       "      <th>Host</th>\n",
       "      <th>Isolation_Source</th>\n",
       "      <th>Collection_Date</th>\n",
       "      <th>BioSample</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>MW023498.1</td>\n",
       "      <td>Schmedes,S., Blanton,J.</td>\n",
       "      <td>2020-09-21T00:00:00Z</td>\n",
       "      <td>A</td>\n",
       "      <td>Severe acute respiratory syndrome-related coro...</td>\n",
       "      <td>ssRNA(+)</td>\n",
       "      <td>29812</td>\n",
       "      <td>GenBank</td>\n",
       "      <td>NaN</td>\n",
       "      <td>USA: FL</td>\n",
       "      <td>FL</td>\n",
       "      <td>Homo sapiens</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2020-03-30</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>MT704130.1</td>\n",
       "      <td>Keller,E.</td>\n",
       "      <td>2020-07-02T00:00:00Z</td>\n",
       "      <td>A</td>\n",
       "      <td>Severe acute respiratory syndrome-related coro...</td>\n",
       "      <td>ssRNA(+)</td>\n",
       "      <td>29873</td>\n",
       "      <td>GenBank</td>\n",
       "      <td>NaN</td>\n",
       "      <td>USA: MD</td>\n",
       "      <td>MD</td>\n",
       "      <td>Homo sapiens</td>\n",
       "      <td>oronasopharynx</td>\n",
       "      <td>2020-04-07</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>MT627305.1</td>\n",
       "      <td>Nickerson,D.A., Frazar,C.D., Lee,J., Pelle,B.,...</td>\n",
       "      <td>2020-06-17T00:00:00Z</td>\n",
       "      <td>A.1</td>\n",
       "      <td>Severe acute respiratory syndrome-related coro...</td>\n",
       "      <td>ssRNA(+)</td>\n",
       "      <td>29862</td>\n",
       "      <td>GenBank</td>\n",
       "      <td>NaN</td>\n",
       "      <td>USA: Washington,King County</td>\n",
       "      <td>WA</td>\n",
       "      <td>Homo sapiens</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2020-03-02</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Accession                                         Submitters  \\\n",
       "0  MW023498.1                            Schmedes,S., Blanton,J.   \n",
       "1  MT704130.1                                          Keller,E.   \n",
       "2  MT627305.1  Nickerson,D.A., Frazar,C.D., Lee,J., Pelle,B.,...   \n",
       "\n",
       "           Release_Date Pangolin  \\\n",
       "0  2020-09-21T00:00:00Z        A   \n",
       "1  2020-07-02T00:00:00Z        A   \n",
       "2  2020-06-17T00:00:00Z      A.1   \n",
       "\n",
       "                                             Species Molecule_type  Length  \\\n",
       "0  Severe acute respiratory syndrome-related coro...      ssRNA(+)   29812   \n",
       "1  Severe acute respiratory syndrome-related coro...      ssRNA(+)   29873   \n",
       "2  Severe acute respiratory syndrome-related coro...      ssRNA(+)   29862   \n",
       "\n",
       "  Sequence_Type  Genotype                 Geo_Location USA          Host  \\\n",
       "0       GenBank       NaN                      USA: FL  FL  Homo sapiens   \n",
       "1       GenBank       NaN                      USA: MD  MD  Homo sapiens   \n",
       "2       GenBank       NaN  USA: Washington,King County  WA  Homo sapiens   \n",
       "\n",
       "  Isolation_Source Collection_Date BioSample  \n",
       "0              NaN      2020-03-30       NaN  \n",
       "1   oronasopharynx      2020-04-07       NaN  \n",
       "2              NaN      2020-03-02       NaN  "
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "metadata_df = pd.read_csv('sars-cov-2-genbank-50/sars-cov-2.metadata.csv')\n",
    "metadata_df.head(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "22b672a1-d843-473b-a264-9cf476065527",
   "metadata": {},
   "source": [
    "### 4.2.1. Create query which includes tree\n",
    "\n",
    "To create a query which includes a phylogenetic tree you will have to specify the reference genome."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "0913411e-dd4a-4b99-b38c-deb701825289",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<MutationTreeSamplesQuery[selected=100% (50/50) samples, unknown=0% (0/50) samples]>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q = db.samples_query(universe='mutations', reference_name='NC_045512')\n",
    "q"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6ae549d0-0947-4a1c-a0eb-7aa792beac91",
   "metadata": {},
   "source": [
    "### 4.2.2. Create query and join tree from file\n",
    "\n",
    "Alternatively, you can create a query and join to a tree stored in a separate file or some other external resource.\n",
    "\n",
    "First you have to load the tree using the **ETEToolkit**."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "b088c905-7690-4842-a1a6-e37fad1751f9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Tree node '' (0x7f5911af6c7)"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from ete3 import Tree\n",
    "\n",
    "tree = Tree('sars-cov-2-genbank-50/tree.newick')\n",
    "tree"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "249df10f-0182-41eb-b58e-954f83d3b7e6",
   "metadata": {},
   "source": [
    "Now we join this tree to a query. You have to specify the alignment length used to construct the tree (in this case the same as the length of the reference genome). This is so that I can do conversions between distance units (**substitutions/site** to **substitutions**).\n",
    "\n",
    "*Note: This may not quite be working 100% yet. This is still in-development software.*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "a2a2851d-32ee-4b49-8ce3-aef21ed30bca",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "1/51 leaves in the tree are not found in the query: [NC_045512]. Pruning tree to contain only those samples in the query (50/51).\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<MutationTreeSamplesQuery[selected=100% (50/50) samples, unknown=0% (0/50) samples]>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q = db.samples_query().join_tree(tree, alignment_length=29903)\n",
    "q"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a749481d-4df8-448c-97e4-275ef932a453",
   "metadata": {},
   "source": [
    "### 4.2.3. Create query with tree and dataframe of metadata\n",
    "\n",
    "To create a query with both the metadata and a tree attached we can do the following."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "6f3682ef-654c-4335-9724-a1f790f59fca",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<MutationTreeSamplesQuery[selected=100% (50/50) samples, unknown=0% (0/50) samples]>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q = db.samples_query(\n",
    "    universe='mutations', reference_name='NC_045512').join(metadata_df, sample_names_column='Accession')\n",
    "\n",
    "# Sets the outgroup of the tree\n",
    "q = q.set_outgroup('NC_045512')\n",
    "\n",
    "q"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "37b8147f-b0a2-488d-b9f2-652480c7ae23",
   "metadata": {},
   "source": [
    "### 4.2.4. Show summary of mutations\n",
    "\n",
    "This shows a summary of all mutations accross all genomes in the query. The **ID_HGVS...** columns show identifiers using [HGVS](https://varnomen.hgvs.org/) as derived from `snpeff`. You can use each of these identifiers (or the **Mutation** column) to search for particular mutations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "57e5f756-c786-4bfe-9cc7-c2bfd73b096b",
   "metadata": {},
   "outputs": [
    {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Mutation</th>\n",
       "      <th>Sequence</th>\n",
       "      <th>Position</th>\n",
       "      <th>Deletion</th>\n",
       "      <th>Insertion</th>\n",
       "      <th>Type</th>\n",
       "      <th>Count</th>\n",
       "      <th>Unknown Count</th>\n",
       "      <th>Present and Unknown Count</th>\n",
       "      <th>Total</th>\n",
       "      <th>...</th>\n",
       "      <th>Gene_Name</th>\n",
       "      <th>Gene_ID</th>\n",
       "      <th>Feature_Type</th>\n",
       "      <th>Transcript_BioType</th>\n",
       "      <th>HGVS.c</th>\n",
       "      <th>HGVS.p</th>\n",
       "      <th>ID_HGVS.c</th>\n",
       "      <th>ID_HGVS.p</th>\n",
       "      <th>ID_HGVS_GN.c</th>\n",
       "      <th>ID_HGVS_GN.p</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ID_HGVS_GN.p</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>&lt;NA&gt;</th>\n",
       "      <td>NC_045512.2:241:C:T</td>\n",
       "      <td>NC_045512.2</td>\n",
       "      <td>241</td>\n",
       "      <td>C</td>\n",
       "      <td>T</td>\n",
       "      <td>SNP</td>\n",
       "      <td>38</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>50</td>\n",
       "      <td>...</td>\n",
       "      <td>CHR_START-ORF1ab</td>\n",
       "      <td>CHR_START-GU280_gp01</td>\n",
       "      <td>intergenic_region</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>n.241C&gt;T</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>hgvs:NC_045512.2:n.241C&gt;T</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>hgvs_gn:NC_045512.2:n.241C&gt;T</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>hgvs_gn:NC_045512.2:ORF1ab:p.F924F</th>\n",
       "      <td>NC_045512.2:3037:C:T</td>\n",
       "      <td>NC_045512.2</td>\n",
       "      <td>3037</td>\n",
       "      <td>C</td>\n",
       "      <td>T</td>\n",
       "      <td>SNP</td>\n",
       "      <td>38</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>50</td>\n",
       "      <td>...</td>\n",
       "      <td>ORF1ab</td>\n",
       "      <td>GU280_gp01</td>\n",
       "      <td>transcript</td>\n",
       "      <td>protein_coding</td>\n",
       "      <td>c.2772C&gt;T</td>\n",
       "      <td>p.F924F</td>\n",
       "      <td>hgvs:NC_045512.2:GU280_gp01:c.2772C&gt;T</td>\n",
       "      <td>hgvs:NC_045512.2:GU280_gp01:p.F924F</td>\n",
       "      <td>hgvs_gn:NC_045512.2:ORF1ab:c.2772C&gt;T</td>\n",
       "      <td>hgvs_gn:NC_045512.2:ORF1ab:p.F924F</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>hgvs_gn:NC_045512.2:S:p.D614G</th>\n",
       "      <td>NC_045512.2:23403:A:G</td>\n",
       "      <td>NC_045512.2</td>\n",
       "      <td>23403</td>\n",
       "      <td>A</td>\n",
       "      <td>G</td>\n",
       "      <td>SNP</td>\n",
       "      <td>38</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>50</td>\n",
       "      <td>...</td>\n",
       "      <td>S</td>\n",
       "      <td>GU280_gp02</td>\n",
       "      <td>transcript</td>\n",
       "      <td>protein_coding</td>\n",
       "      <td>c.1841A&gt;G</td>\n",
       "      <td>p.D614G</td>\n",
       "      <td>hgvs:NC_045512.2:GU280_gp02:c.1841A&gt;G</td>\n",
       "      <td>hgvs:NC_045512.2:GU280_gp02:p.D614G</td>\n",
       "      <td>hgvs_gn:NC_045512.2:S:c.1841A&gt;G</td>\n",
       "      <td>hgvs_gn:NC_045512.2:S:p.D614G</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>hgvs_gn:NC_045512.2:ORF1ab:p.P4715L</th>\n",
       "      <td>NC_045512.2:14408:C:T</td>\n",
       "      <td>NC_045512.2</td>\n",
       "      <td>14408</td>\n",
       "      <td>C</td>\n",
       "      <td>T</td>\n",
       "      <td>SNP</td>\n",
       "      <td>34</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>50</td>\n",
       "      <td>...</td>\n",
       "      <td>ORF1ab</td>\n",
       "      <td>GU280_gp01</td>\n",
       "      <td>transcript</td>\n",
       "      <td>protein_coding</td>\n",
       "      <td>c.14144C&gt;T</td>\n",
       "      <td>p.P4715L</td>\n",
       "      <td>hgvs:NC_045512.2:GU280_gp01:c.14144C&gt;T</td>\n",
       "      <td>hgvs:NC_045512.2:GU280_gp01:p.P4715L</td>\n",
       "      <td>hgvs_gn:NC_045512.2:ORF1ab:c.14144C&gt;T</td>\n",
       "      <td>hgvs_gn:NC_045512.2:ORF1ab:p.P4715L</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>hgvs_gn:NC_045512.2:N:p.R203R</th>\n",
       "      <td>NC_045512.2:28882:G:A</td>\n",
       "      <td>NC_045512.2</td>\n",
       "      <td>28882</td>\n",
       "      <td>G</td>\n",
       "      <td>A</td>\n",
       "      <td>SNP</td>\n",
       "      <td>12</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>50</td>\n",
       "      <td>...</td>\n",
       "      <td>N</td>\n",
       "      <td>GU280_gp10</td>\n",
       "      <td>transcript</td>\n",
       "      <td>protein_coding</td>\n",
       "      <td>c.609G&gt;A</td>\n",
       "      <td>p.R203R</td>\n",
       "      <td>hgvs:NC_045512.2:GU280_gp10:c.609G&gt;A</td>\n",
       "      <td>hgvs:NC_045512.2:GU280_gp10:p.R203R</td>\n",
       "      <td>hgvs_gn:NC_045512.2:N:c.609G&gt;A</td>\n",
       "      <td>hgvs_gn:NC_045512.2:N:p.R203R</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>hgvs_gn:NC_045512.2:ORF1ab:p.Q5412H</th>\n",
       "      <td>NC_045512.2:16500:A:C</td>\n",
       "      <td>NC_045512.2</td>\n",
       "      <td>16500</td>\n",
       "      <td>A</td>\n",
       "      <td>C</td>\n",
       "      <td>SNP</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>50</td>\n",
       "      <td>...</td>\n",
       "      <td>ORF1ab</td>\n",
       "      <td>GU280_gp01</td>\n",
       "      <td>transcript</td>\n",
       "      <td>protein_coding</td>\n",
       "      <td>c.16236A&gt;C</td>\n",
       "      <td>p.Q5412H</td>\n",
       "      <td>hgvs:NC_045512.2:GU280_gp01:c.16236A&gt;C</td>\n",
       "      <td>hgvs:NC_045512.2:GU280_gp01:p.Q5412H</td>\n",
       "      <td>hgvs_gn:NC_045512.2:ORF1ab:c.16236A&gt;C</td>\n",
       "      <td>hgvs_gn:NC_045512.2:ORF1ab:p.Q5412H</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>hgvs_gn:NC_045512.2:N:p.V270L</th>\n",
       "      <td>NC_045512.2:29081:G:T</td>\n",
       "      <td>NC_045512.2</td>\n",
       "      <td>29081</td>\n",
       "      <td>G</td>\n",
       "      <td>T</td>\n",
       "      <td>SNP</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>50</td>\n",
       "      <td>...</td>\n",
       "      <td>N</td>\n",
       "      <td>GU280_gp10</td>\n",
       "      <td>transcript</td>\n",
       "      <td>protein_coding</td>\n",
       "      <td>c.808G&gt;T</td>\n",
       "      <td>p.V270L</td>\n",
       "      <td>hgvs:NC_045512.2:GU280_gp10:c.808G&gt;T</td>\n",
       "      <td>hgvs:NC_045512.2:GU280_gp10:p.V270L</td>\n",
       "      <td>hgvs_gn:NC_045512.2:N:c.808G&gt;T</td>\n",
       "      <td>hgvs_gn:NC_045512.2:N:p.V270L</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>hgvs_gn:NC_045512.2:ORF1ab:p.H110Y</th>\n",
       "      <td>NC_045512.2:593:C:T</td>\n",
       "      <td>NC_045512.2</td>\n",
       "      <td>593</td>\n",
       "      <td>C</td>\n",
       "      <td>T</td>\n",
       "      <td>SNP</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>50</td>\n",
       "      <td>...</td>\n",
       "      <td>ORF1ab</td>\n",
       "      <td>GU280_gp01</td>\n",
       "      <td>transcript</td>\n",
       "      <td>protein_coding</td>\n",
       "      <td>c.328C&gt;T</td>\n",
       "      <td>p.H110Y</td>\n",
       "      <td>hgvs:NC_045512.2:GU280_gp01:c.328C&gt;T</td>\n",
       "      <td>hgvs:NC_045512.2:GU280_gp01:p.H110Y</td>\n",
       "      <td>hgvs_gn:NC_045512.2:ORF1ab:c.328C&gt;T</td>\n",
       "      <td>hgvs_gn:NC_045512.2:ORF1ab:p.H110Y</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>hgvs_gn:NC_045512.2:N:p.G236S</th>\n",
       "      <td>NC_045512.2:28979:G:A</td>\n",
       "      <td>NC_045512.2</td>\n",
       "      <td>28979</td>\n",
       "      <td>G</td>\n",
       "      <td>A</td>\n",
       "      <td>SNP</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>50</td>\n",
       "      <td>...</td>\n",
       "      <td>N</td>\n",
       "      <td>GU280_gp10</td>\n",
       "      <td>transcript</td>\n",
       "      <td>protein_coding</td>\n",
       "      <td>c.706G&gt;A</td>\n",
       "      <td>p.G236S</td>\n",
       "      <td>hgvs:NC_045512.2:GU280_gp10:c.706G&gt;A</td>\n",
       "      <td>hgvs:NC_045512.2:GU280_gp10:p.G236S</td>\n",
       "      <td>hgvs_gn:NC_045512.2:N:c.706G&gt;A</td>\n",
       "      <td>hgvs_gn:NC_045512.2:N:p.G236S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>hgvs_gn:NC_045512.2:ORF1ab:p.F1925F</th>\n",
       "      <td>NC_045512.2:6040:C:T</td>\n",
       "      <td>NC_045512.2</td>\n",
       "      <td>6040</td>\n",
       "      <td>C</td>\n",
       "      <td>T</td>\n",
       "      <td>SNP</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>50</td>\n",
       "      <td>...</td>\n",
       "      <td>ORF1ab</td>\n",
       "      <td>GU280_gp01</td>\n",
       "      <td>transcript</td>\n",
       "      <td>protein_coding</td>\n",
       "      <td>c.5775C&gt;T</td>\n",
       "      <td>p.F1925F</td>\n",
       "      <td>hgvs:NC_045512.2:GU280_gp01:c.5775C&gt;T</td>\n",
       "      <td>hgvs:NC_045512.2:GU280_gp01:p.F1925F</td>\n",
       "      <td>hgvs_gn:NC_045512.2:ORF1ab:c.5775C&gt;T</td>\n",
       "      <td>hgvs_gn:NC_045512.2:ORF1ab:p.F1925F</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>288 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                  Mutation     Sequence  \\\n",
       "ID_HGVS_GN.p                                                              \n",
       "<NA>                                   NC_045512.2:241:C:T  NC_045512.2   \n",
       "hgvs_gn:NC_045512.2:ORF1ab:p.F924F    NC_045512.2:3037:C:T  NC_045512.2   \n",
       "hgvs_gn:NC_045512.2:S:p.D614G        NC_045512.2:23403:A:G  NC_045512.2   \n",
       "hgvs_gn:NC_045512.2:ORF1ab:p.P4715L  NC_045512.2:14408:C:T  NC_045512.2   \n",
       "hgvs_gn:NC_045512.2:N:p.R203R        NC_045512.2:28882:G:A  NC_045512.2   \n",
       "...                                                    ...          ...   \n",
       "hgvs_gn:NC_045512.2:ORF1ab:p.Q5412H  NC_045512.2:16500:A:C  NC_045512.2   \n",
       "hgvs_gn:NC_045512.2:N:p.V270L        NC_045512.2:29081:G:T  NC_045512.2   \n",
       "hgvs_gn:NC_045512.2:ORF1ab:p.H110Y     NC_045512.2:593:C:T  NC_045512.2   \n",
       "hgvs_gn:NC_045512.2:N:p.G236S        NC_045512.2:28979:G:A  NC_045512.2   \n",
       "hgvs_gn:NC_045512.2:ORF1ab:p.F1925F   NC_045512.2:6040:C:T  NC_045512.2   \n",
       "\n",
       "                                     Position Deletion Insertion Type  Count  \\\n",
       "ID_HGVS_GN.p                                                                   \n",
       "<NA>                                      241        C         T  SNP     38   \n",
       "hgvs_gn:NC_045512.2:ORF1ab:p.F924F       3037        C         T  SNP     38   \n",
       "hgvs_gn:NC_045512.2:S:p.D614G           23403        A         G  SNP     38   \n",
       "hgvs_gn:NC_045512.2:ORF1ab:p.P4715L     14408        C         T  SNP     34   \n",
       "hgvs_gn:NC_045512.2:N:p.R203R           28882        G         A  SNP     12   \n",
       "...                                       ...      ...       ...  ...    ...   \n",
       "hgvs_gn:NC_045512.2:ORF1ab:p.Q5412H     16500        A         C  SNP      1   \n",
       "hgvs_gn:NC_045512.2:N:p.V270L           29081        G         T  SNP      1   \n",
       "hgvs_gn:NC_045512.2:ORF1ab:p.H110Y        593        C         T  SNP      1   \n",
       "hgvs_gn:NC_045512.2:N:p.G236S           28979        G         A  SNP      1   \n",
       "hgvs_gn:NC_045512.2:ORF1ab:p.F1925F      6040        C         T  SNP      1   \n",
       "\n",
       "                                    Unknown Count Present and Unknown Count  \\\n",
       "ID_HGVS_GN.p                                                                  \n",
       "<NA>                                          NaN                       NaN   \n",
       "hgvs_gn:NC_045512.2:ORF1ab:p.F924F            NaN                       NaN   \n",
       "hgvs_gn:NC_045512.2:S:p.D614G                 NaN                       NaN   \n",
       "hgvs_gn:NC_045512.2:ORF1ab:p.P4715L           NaN                       NaN   \n",
       "hgvs_gn:NC_045512.2:N:p.R203R                 NaN                       NaN   \n",
       "...                                           ...                       ...   \n",
       "hgvs_gn:NC_045512.2:ORF1ab:p.Q5412H           NaN                       NaN   \n",
       "hgvs_gn:NC_045512.2:N:p.V270L                 NaN                       NaN   \n",
       "hgvs_gn:NC_045512.2:ORF1ab:p.H110Y            NaN                       NaN   \n",
       "hgvs_gn:NC_045512.2:N:p.G236S                 NaN                       NaN   \n",
       "hgvs_gn:NC_045512.2:ORF1ab:p.F1925F           NaN                       NaN   \n",
       "\n",
       "                                     Total  ...         Gene_Name  \\\n",
       "ID_HGVS_GN.p                                ...                     \n",
       "<NA>                                    50  ...  CHR_START-ORF1ab   \n",
       "hgvs_gn:NC_045512.2:ORF1ab:p.F924F      50  ...            ORF1ab   \n",
       "hgvs_gn:NC_045512.2:S:p.D614G           50  ...                 S   \n",
       "hgvs_gn:NC_045512.2:ORF1ab:p.P4715L     50  ...            ORF1ab   \n",
       "hgvs_gn:NC_045512.2:N:p.R203R           50  ...                 N   \n",
       "...                                    ...  ...               ...   \n",
       "hgvs_gn:NC_045512.2:ORF1ab:p.Q5412H     50  ...            ORF1ab   \n",
       "hgvs_gn:NC_045512.2:N:p.V270L           50  ...                 N   \n",
       "hgvs_gn:NC_045512.2:ORF1ab:p.H110Y      50  ...            ORF1ab   \n",
       "hgvs_gn:NC_045512.2:N:p.G236S           50  ...                 N   \n",
       "hgvs_gn:NC_045512.2:ORF1ab:p.F1925F     50  ...            ORF1ab   \n",
       "\n",
       "                                                  Gene_ID       Feature_Type  \\\n",
       "ID_HGVS_GN.p                                                                   \n",
       "<NA>                                 CHR_START-GU280_gp01  intergenic_region   \n",
       "hgvs_gn:NC_045512.2:ORF1ab:p.F924F             GU280_gp01         transcript   \n",
       "hgvs_gn:NC_045512.2:S:p.D614G                  GU280_gp02         transcript   \n",
       "hgvs_gn:NC_045512.2:ORF1ab:p.P4715L            GU280_gp01         transcript   \n",
       "hgvs_gn:NC_045512.2:N:p.R203R                  GU280_gp10         transcript   \n",
       "...                                                   ...                ...   \n",
       "hgvs_gn:NC_045512.2:ORF1ab:p.Q5412H            GU280_gp01         transcript   \n",
       "hgvs_gn:NC_045512.2:N:p.V270L                  GU280_gp10         transcript   \n",
       "hgvs_gn:NC_045512.2:ORF1ab:p.H110Y             GU280_gp01         transcript   \n",
       "hgvs_gn:NC_045512.2:N:p.G236S                  GU280_gp10         transcript   \n",
       "hgvs_gn:NC_045512.2:ORF1ab:p.F1925F            GU280_gp01         transcript   \n",
       "\n",
       "                                    Transcript_BioType      HGVS.c    HGVS.p  \\\n",
       "ID_HGVS_GN.p                                                                   \n",
       "<NA>                                              <NA>    n.241C>T      <NA>   \n",
       "hgvs_gn:NC_045512.2:ORF1ab:p.F924F      protein_coding   c.2772C>T   p.F924F   \n",
       "hgvs_gn:NC_045512.2:S:p.D614G           protein_coding   c.1841A>G   p.D614G   \n",
       "hgvs_gn:NC_045512.2:ORF1ab:p.P4715L     protein_coding  c.14144C>T  p.P4715L   \n",
       "hgvs_gn:NC_045512.2:N:p.R203R           protein_coding    c.609G>A   p.R203R   \n",
       "...                                                ...         ...       ...   \n",
       "hgvs_gn:NC_045512.2:ORF1ab:p.Q5412H     protein_coding  c.16236A>C  p.Q5412H   \n",
       "hgvs_gn:NC_045512.2:N:p.V270L           protein_coding    c.808G>T   p.V270L   \n",
       "hgvs_gn:NC_045512.2:ORF1ab:p.H110Y      protein_coding    c.328C>T   p.H110Y   \n",
       "hgvs_gn:NC_045512.2:N:p.G236S           protein_coding    c.706G>A   p.G236S   \n",
       "hgvs_gn:NC_045512.2:ORF1ab:p.F1925F     protein_coding   c.5775C>T  p.F1925F   \n",
       "\n",
       "                                                                  ID_HGVS.c  \\\n",
       "ID_HGVS_GN.p                                                                  \n",
       "<NA>                                              hgvs:NC_045512.2:n.241C>T   \n",
       "hgvs_gn:NC_045512.2:ORF1ab:p.F924F    hgvs:NC_045512.2:GU280_gp01:c.2772C>T   \n",
       "hgvs_gn:NC_045512.2:S:p.D614G         hgvs:NC_045512.2:GU280_gp02:c.1841A>G   \n",
       "hgvs_gn:NC_045512.2:ORF1ab:p.P4715L  hgvs:NC_045512.2:GU280_gp01:c.14144C>T   \n",
       "hgvs_gn:NC_045512.2:N:p.R203R          hgvs:NC_045512.2:GU280_gp10:c.609G>A   \n",
       "...                                                                     ...   \n",
       "hgvs_gn:NC_045512.2:ORF1ab:p.Q5412H  hgvs:NC_045512.2:GU280_gp01:c.16236A>C   \n",
       "hgvs_gn:NC_045512.2:N:p.V270L          hgvs:NC_045512.2:GU280_gp10:c.808G>T   \n",
       "hgvs_gn:NC_045512.2:ORF1ab:p.H110Y     hgvs:NC_045512.2:GU280_gp01:c.328C>T   \n",
       "hgvs_gn:NC_045512.2:N:p.G236S          hgvs:NC_045512.2:GU280_gp10:c.706G>A   \n",
       "hgvs_gn:NC_045512.2:ORF1ab:p.F1925F   hgvs:NC_045512.2:GU280_gp01:c.5775C>T   \n",
       "\n",
       "                                                                ID_HGVS.p  \\\n",
       "ID_HGVS_GN.p                                                                \n",
       "<NA>                                                                 <NA>   \n",
       "hgvs_gn:NC_045512.2:ORF1ab:p.F924F    hgvs:NC_045512.2:GU280_gp01:p.F924F   \n",
       "hgvs_gn:NC_045512.2:S:p.D614G         hgvs:NC_045512.2:GU280_gp02:p.D614G   \n",
       "hgvs_gn:NC_045512.2:ORF1ab:p.P4715L  hgvs:NC_045512.2:GU280_gp01:p.P4715L   \n",
       "hgvs_gn:NC_045512.2:N:p.R203R         hgvs:NC_045512.2:GU280_gp10:p.R203R   \n",
       "...                                                                   ...   \n",
       "hgvs_gn:NC_045512.2:ORF1ab:p.Q5412H  hgvs:NC_045512.2:GU280_gp01:p.Q5412H   \n",
       "hgvs_gn:NC_045512.2:N:p.V270L         hgvs:NC_045512.2:GU280_gp10:p.V270L   \n",
       "hgvs_gn:NC_045512.2:ORF1ab:p.H110Y    hgvs:NC_045512.2:GU280_gp01:p.H110Y   \n",
       "hgvs_gn:NC_045512.2:N:p.G236S         hgvs:NC_045512.2:GU280_gp10:p.G236S   \n",
       "hgvs_gn:NC_045512.2:ORF1ab:p.F1925F  hgvs:NC_045512.2:GU280_gp01:p.F1925F   \n",
       "\n",
       "                                                              ID_HGVS_GN.c  \\\n",
       "ID_HGVS_GN.p                                                                 \n",
       "<NA>                                          hgvs_gn:NC_045512.2:n.241C>T   \n",
       "hgvs_gn:NC_045512.2:ORF1ab:p.F924F    hgvs_gn:NC_045512.2:ORF1ab:c.2772C>T   \n",
       "hgvs_gn:NC_045512.2:S:p.D614G              hgvs_gn:NC_045512.2:S:c.1841A>G   \n",
       "hgvs_gn:NC_045512.2:ORF1ab:p.P4715L  hgvs_gn:NC_045512.2:ORF1ab:c.14144C>T   \n",
       "hgvs_gn:NC_045512.2:N:p.R203R               hgvs_gn:NC_045512.2:N:c.609G>A   \n",
       "...                                                                    ...   \n",
       "hgvs_gn:NC_045512.2:ORF1ab:p.Q5412H  hgvs_gn:NC_045512.2:ORF1ab:c.16236A>C   \n",
       "hgvs_gn:NC_045512.2:N:p.V270L               hgvs_gn:NC_045512.2:N:c.808G>T   \n",
       "hgvs_gn:NC_045512.2:ORF1ab:p.H110Y     hgvs_gn:NC_045512.2:ORF1ab:c.328C>T   \n",
       "hgvs_gn:NC_045512.2:N:p.G236S               hgvs_gn:NC_045512.2:N:c.706G>A   \n",
       "hgvs_gn:NC_045512.2:ORF1ab:p.F1925F   hgvs_gn:NC_045512.2:ORF1ab:c.5775C>T   \n",
       "\n",
       "                                                            ID_HGVS_GN.p  \n",
       "ID_HGVS_GN.p                                                              \n",
       "<NA>                                                                <NA>  \n",
       "hgvs_gn:NC_045512.2:ORF1ab:p.F924F    hgvs_gn:NC_045512.2:ORF1ab:p.F924F  \n",
       "hgvs_gn:NC_045512.2:S:p.D614G              hgvs_gn:NC_045512.2:S:p.D614G  \n",
       "hgvs_gn:NC_045512.2:ORF1ab:p.P4715L  hgvs_gn:NC_045512.2:ORF1ab:p.P4715L  \n",
       "hgvs_gn:NC_045512.2:N:p.R203R              hgvs_gn:NC_045512.2:N:p.R203R  \n",
       "...                                                                  ...  \n",
       "hgvs_gn:NC_045512.2:ORF1ab:p.Q5412H  hgvs_gn:NC_045512.2:ORF1ab:p.Q5412H  \n",
       "hgvs_gn:NC_045512.2:N:p.V270L              hgvs_gn:NC_045512.2:N:p.V270L  \n",
       "hgvs_gn:NC_045512.2:ORF1ab:p.H110Y    hgvs_gn:NC_045512.2:ORF1ab:p.H110Y  \n",
       "hgvs_gn:NC_045512.2:N:p.G236S              hgvs_gn:NC_045512.2:N:p.G236S  \n",
       "hgvs_gn:NC_045512.2:ORF1ab:p.F1925F  hgvs_gn:NC_045512.2:ORF1ab:p.F1925F  \n",
       "\n",
       "[288 rows x 25 columns]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = q.features_summary().sort_values(\n",
    "    'Count', ascending=False).reset_index().set_index('ID_HGVS_GN.p', drop=False)\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9f9791bc-a41c-438e-84cd-f32688e77594",
   "metadata": {},
   "source": [
    "### 4.2.5. Find genomes with a particular mutation\n",
    "\n",
    "This shows a summary of all genomes with a particular mutation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "6d2b1160-f0f6-47bc-8f7c-a80694863735",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "\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>Query</th>\n",
       "      <th>Present</th>\n",
       "      <th>Absent</th>\n",
       "      <th>Unknown</th>\n",
       "      <th>Total</th>\n",
       "      <th>% Present</th>\n",
       "      <th>% Absent</th>\n",
       "      <th>% Unknown</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>dataframe(names_col=[Accession]) AND hgvs_gn:N...</td>\n",
       "      <td>38</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>50</td>\n",
       "      <td>76.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                               Query  Present  Absent  \\\n",
       "0  dataframe(names_col=[Accession]) AND hgvs_gn:N...       38      12   \n",
       "\n",
       "   Unknown  Total  % Present  % Absent  % Unknown  \n",
       "0        0     50       76.0      24.0        0.0  "
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q.hasa('hgvs_gn:NC_045512.2:S:p.D614G').summary()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "157bab61-d90b-46a4-aeb1-57869679ff89",
   "metadata": {},
   "source": [
    "To view all individual genomes with this mutation, you can use `.toframe()` (I also use `.head(3)` to not clutter up the notebook with data from all 38 genomes with a `D614G` mutation)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "b86db40e-13f5-4af5-aa83-51a10894007e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "    }\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>Query</th>\n",
       "      <th>Sample Name</th>\n",
       "      <th>Sample ID</th>\n",
       "      <th>Status</th>\n",
       "      <th>Accession</th>\n",
       "      <th>Submitters</th>\n",
       "      <th>Release_Date</th>\n",
       "      <th>Pangolin</th>\n",
       "      <th>Species</th>\n",
       "      <th>Molecule_type</th>\n",
       "      <th>Length</th>\n",
       "      <th>Sequence_Type</th>\n",
       "      <th>Genotype</th>\n",
       "      <th>Geo_Location</th>\n",
       "      <th>USA</th>\n",
       "      <th>Host</th>\n",
       "      <th>Isolation_Source</th>\n",
       "      <th>Collection_Date</th>\n",
       "      <th>BioSample</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>dataframe(names_col=[Accession]) AND hgvs_gn:N...</td>\n",
       "      <td>OD898064.1</td>\n",
       "      <td>49</td>\n",
       "      <td>Present</td>\n",
       "      <td>OD898064.1</td>\n",
       "      <td>Howes,R., The Lighthouse Lab in,Cambridge., Al...</td>\n",
       "      <td>2021-04-23T00:00:00Z</td>\n",
       "      <td>AD.2</td>\n",
       "      <td>Severe acute respiratory syndrome-related coro...</td>\n",
       "      <td>ssRNA(+)</td>\n",
       "      <td>29903</td>\n",
       "      <td>GenBank</td>\n",
       "      <td>NaN</td>\n",
       "      <td>United Kingdom:England</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Homo sapiens</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2020-11-12</td>\n",
       "      <td>SAMEA7673077</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>dataframe(names_col=[Accession]) AND hgvs_gn:N...</td>\n",
       "      <td>OA992224.1</td>\n",
       "      <td>31</td>\n",
       "      <td>Present</td>\n",
       "      <td>OA992224.1</td>\n",
       "      <td>Wynn,J., Hyland,M., The Lighthouse Lab in Alde...</td>\n",
       "      <td>2021-04-20T00:00:00Z</td>\n",
       "      <td>AD.2</td>\n",
       "      <td>Severe acute respiratory syndrome-related coro...</td>\n",
       "      <td>ssRNA(+)</td>\n",
       "      <td>29903</td>\n",
       "      <td>GenBank</td>\n",
       "      <td>NaN</td>\n",
       "      <td>United Kingdom:England</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Homo sapiens</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2020-10-02</td>\n",
       "      <td>SAMEA7454619</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>dataframe(names_col=[Accession]) AND hgvs_gn:N...</td>\n",
       "      <td>OA992920.1</td>\n",
       "      <td>41</td>\n",
       "      <td>Present</td>\n",
       "      <td>OA992920.1</td>\n",
       "      <td>VanSteenhouse,H., Kasai,Y., Gray,D., Clugston,...</td>\n",
       "      <td>2021-04-20T00:00:00Z</td>\n",
       "      <td>AD.2</td>\n",
       "      <td>Severe acute respiratory syndrome-related coro...</td>\n",
       "      <td>ssRNA(+)</td>\n",
       "      <td>29903</td>\n",
       "      <td>GenBank</td>\n",
       "      <td>NaN</td>\n",
       "      <td>United Kingdom:England</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Homo sapiens</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2020-09-23</td>\n",
       "      <td>SAMEA7454128</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                               Query Sample Name  Sample ID  \\\n",
       "0  dataframe(names_col=[Accession]) AND hgvs_gn:N...  OD898064.1         49   \n",
       "1  dataframe(names_col=[Accession]) AND hgvs_gn:N...  OA992224.1         31   \n",
       "2  dataframe(names_col=[Accession]) AND hgvs_gn:N...  OA992920.1         41   \n",
       "\n",
       "    Status   Accession                                         Submitters  \\\n",
       "0  Present  OD898064.1  Howes,R., The Lighthouse Lab in,Cambridge., Al...   \n",
       "1  Present  OA992224.1  Wynn,J., Hyland,M., The Lighthouse Lab in Alde...   \n",
       "2  Present  OA992920.1  VanSteenhouse,H., Kasai,Y., Gray,D., Clugston,...   \n",
       "\n",
       "           Release_Date Pangolin  \\\n",
       "0  2021-04-23T00:00:00Z     AD.2   \n",
       "1  2021-04-20T00:00:00Z     AD.2   \n",
       "2  2021-04-20T00:00:00Z     AD.2   \n",
       "\n",
       "                                             Species Molecule_type  Length  \\\n",
       "0  Severe acute respiratory syndrome-related coro...      ssRNA(+)   29903   \n",
       "1  Severe acute respiratory syndrome-related coro...      ssRNA(+)   29903   \n",
       "2  Severe acute respiratory syndrome-related coro...      ssRNA(+)   29903   \n",
       "\n",
       "  Sequence_Type  Genotype            Geo_Location  USA          Host  \\\n",
       "0       GenBank       NaN  United Kingdom:England  NaN  Homo sapiens   \n",
       "1       GenBank       NaN  United Kingdom:England  NaN  Homo sapiens   \n",
       "2       GenBank       NaN  United Kingdom:England  NaN  Homo sapiens   \n",
       "\n",
       "  Isolation_Source Collection_Date     BioSample  \n",
       "0              NaN      2020-11-12  SAMEA7673077  \n",
       "1              NaN      2020-10-02  SAMEA7454619  \n",
       "2              NaN      2020-09-23  SAMEA7454128  "
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q.hasa('hgvs_gn:NC_045512.2:S:p.D614G').toframe().head(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fefc460d-cd2e-4c41-a74a-324d29032a69",
   "metadata": {},
   "source": [
    "### 4.2.6. Visualize queries on tree\n",
    "\n",
    "Here, we can visualize queries on a phylogenetic tree. In this case, we are looking for genomes with particular mutations `S:p.D614G` and `ORF8:p.L84S`.\n",
    "\n",
    "The boxes shown next to the tree include three categories: **[mutation]** (colored black) if the mutation is present, **U** (colored gray) if it is unknown if the mutaiton exists, and **[nothing]** (colored white) if the mutation does not exist. Those genomes for which it is unknown if the mutation exists is defined as those genomes where the mutation overlaps a region with gaps `-` or ambiguous bases `N` in the genome in question. \n",
    "\n",
    "*Note: those genomes where the mutation does not exist is **not** equivalent to saying they have the reference genome amino acid since it's possible there is a different mutation in this location*."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "e8e44ea3-6f6e-49ca-958e-5540274b1e8c",
   "metadata": {},
   "outputs": [
    {
     "data": {
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y4j47OTmhuLgY165d49J27dqF6upqzJs3T+rY+vp6NDY2Sl113K/9NlpHgoKCEBcXBzU1Nbn57cGjnUQiAZ/Ph1gs5tKam5vZPtv/1/YZ5knQZQD57rvvEBQUBADg8XgICwvD2rVrcf36dZmypaWlKC8vx+jRo3vUiPr6ety7dw8mJiZcmq6uLtTV1XHr1i0AwPXr17Fu3Trs3r1b5lZYRUUFAMDe3h6DBw+Gk5MTjh8/LpUfFxcHc3NzjBw5EkuWLEFlZSWXr6WlBQAgoi7bGhsbCyMjI9jZ2eHIkSNc+pYtW9g+2//X9hnmiWBvb0+dcXNzo6NHj5Kuri7l5OQQEZGnpyeNHz+eiIg2btxIM2fOJCKigoICAkC5ubmd1vmgqqoqAkBFRUVS6Xp6epSUlEQtLS1ka2tLBw4cICKi4uJiAkCNjY1c2T/++IMuX75Mly9fptDQUFJTU6Pk5GQiIiopKaG0tDS6evUqnTlzhsaOHUvjxo2TaceuXbvI2tq6w3ZmZGSQgYEBpaen9+j7MUxvWbt2LSUkJDzuZjxxkpOTydTU9HE345mRlJRE/v7+nZYZM2YMKfQyxdDQUAwbNgxRUVFSYyEmJiZQUlLCjRs3MGTIkG7Xp62tDVVVVVRXV+OFF14A0HY7rK6uDnp6eggODkZLSwvMzMyQmpqK8vJyAMCff/6JYcOGoW/fvrCzs+PqGzZsGDIyMhAfHw8HBwf069ePmzU1aNAgREdH45VXXsHdu3dhbGzcrTbm5ORg6tSp+OGHH2BjY9Pt78YwDPOsUug5ECMjI4SEhGD58uWoqanh0rW1tWFjY4Po6Oge1aeiooJXX30VWVlZXFpubi4AYOjQobh16xbq6+vh5+cHPz8/fPbZZwCAgIAAnDlzRm6dGhoaUFWVHx81NDQAoMP8B126dAnOzs4IDw+XmfrLMAzzvFL4QUJvb2/Y2Nhg69atUukbNmzAoUOHsH79em6qa2NjIwoKCjqtz8vLCyEhIaipqYFIJMK6deswZcoUaGpqYvv27bh48SK3nTp1CkDb9FxPT0/k5uYiPz+fqystLQ0JCQmYNm0aAOCXX37hBiDr6+uxevVqjBs3Dvr6+l1+z0uXLmHChAlYv349bG1tIRQKIRQK2TRehmGeew/1JPr3338vM/Ds4OCAo0eP4uDBg9DT04NAIIBAIMC3337baV1LlizB0KFDYWJigj59+uDWrVvcg4BdKS0txdixY6GjowMDAwPMnDkTISEhcHBwAADs3LkTAoEApqamMDY2Rm1tLfbt29eturdt24Y7d+5g7ty5MDIy4rZ33323W8czDMM8q7o9BlJdXS2T9uKLL+LevXsy6e+88w7eeecd1NfXo7q6Gn369JF6cE8eHo+H2NhY7oHAPn36dFi2f//+UoHLwcEBZWVlqKyshLKyssyxCQkJaG5uRmVlJYyMjDq8deXj4yPzpH1YWBjCwsI6bTvDMMzz6JGuSKilpcVNkQXafowffFAPaHs4sP3ZDh0dHYXOpaSk1OmzJ+rq6ujbt69CdTMMwzCy/tUlbX19feHp6SmTzufz/81mMAzDML3gXw0gfD6fBQuGYZhnBHudO8MwDKMQFkAYhmEYhfyrt7AYhnk4YrEYJ06cwNmzZx93U54otbW1aG1tZW+J6CW1tbWwsLDoshwLIAzzFGltbQXQNpWd+T9///03ysvLudcc/ZsefBbuUehsLaVHpb6+vssyLIAwzFNEXV0dLi4umD59+uNuyhMlNjYW+/bt4wLss+bfCFIPUldX77IMGwNhGIZhFMICCMMwDKMQFkAYhmEYhbAAwjAMwyiEBRCGYRhGISyAMAzDMAp5YqfxRkZGIjs7Wypt5MiRmDt3LpenpKQEXV1dDBkyBO7u7lLv2YqPj8eRI0egrKyM999/H++88w6X19zcjO+++w7nzp2DsbExFi5ciFdffZXL37hxI0pKSqTOff/aJESExMRE/PLLL6ioqMCMGTPg5eXF5dfV1SEmJgYZGRmor6/HmjVrMHLkSABATU0NtmzZguzsbAwYMAArVqzo8i3B8fHxKCoqwrJly3rQgwzDMI/WE3sFcvz4cVy8eBGmpqbcpqenx+VdvnwZZmZmkEgk2Lx5M6ysrLgHX4KDg7F8+XKMHz8eb7/9NubMmSP1Gvlp06bh2LFjmDFjBszMzPDWW2/hwoULXH77miSGhobc1o6I8N5772HTpk0YO3YsFi5ciKFDh3L5QqEQo0aNwh9//IGpU6di3rx5Uq+Znzx5MtLS0vDee++hqqoK9vb2aGxslNsHIpEIAQEBmDdvHuLj43unYxmGYXqLvb09dcbNzY2OHj3aaZlHYcqUKbR69epu5dXX15O+vj4lJiYSEZGRkRGdOHGCyz969CiZmJhQa2srXbp0idTV1amqqorLX7ZsGbm7u3OfNTQ0qLCwUO65f/jhBxo8eDA1NjbKzZ8zZw55eXnJzfvzzz9JS0uL6urqiIiotbWVhg8fTjt37pRbvr1dERERZG1tLbcM83xZu3YtJSQkPO5mPHH27t1LysrKBIBtvbSZm5t32udjxoyhJ/YKpCc0NTWhr6+PiooKNDU1oby8HMOGDePy//Of/0AoFOLq1asoKiqSupoBAGdnZ6SlpQFoe3y/sbFR6qrjfnv37sVHH30k97X0YrEYcXFx+Pjjj+Uem56eDltbW26RLSUlJUyYMAFnzpyRWz4oKAhxcXFQU1PrVj8wDMP8m564AHLhwgUcO3YMQNt4QWFhIbfJWz63vr4eYWFhqKyshLOzM/h8Pvr27YvMzEyuzNmzZyGRSFBVVYWBAweitLQUZWVlXH5aWhqqqqoAABUVFQAAe3t7DB48GE5OTjh+/DhX9sqVK9DQ0MCoUaOgr6+PN954AykpKQCA4uJiNDY2oqCgAObm5tDX14erqyuKi4sBtK3dbmJiItV+ExMT3Lp1S25ftAcaeuA1BomJidz+/WvNs/3nZ5/pPVpaWjAyMnokdfN4PIVXWe1JHTweDyoqKlJpysrKMDIyAo/He6jzd+pJu4W1efNm+uKLL2jKlCmkrq5Ourq63BYdHU1EbbewlJSUSEVFhQDQa6+9RhcuXODq2LVrF+nr65O/vz/5+fnRtGnTSFlZmQoKCoio7TaTubk5LV++nGbMmEHvvPMOmZmZccf/8ccfdPnyZbp8+TKFhoaSmpoaJScnExERn8+nsWPHUmlpKbW2tlJkZCQZGBhQTU0NnT17lpSVlWnhwoXU2NhIzc3N5OPjQxMmTCAiosWLF9OcOXOkvm9ISAjZ2dl12ie7du2SuoV1/+2ze/fusf3naJ/dwpJPkVtYDg4O9M8//5BIJKKqqioqLy+nwMBAUlJS4sokJSVRU1MTNTQ00M2bNyk2Npb69+8vk3//Zm9vT9ra2hQXF0fXrl2jvLw8On/+PA0ePFhuO5KSkmjWrFky6d2tw9zcnOrr68nPz49L8/X1pfLychIKhSQSiSgjI4PU1NSej1tYdXV1AIDly5ejurqa23x9fbkyn376Kaqrq3Hw4EHcvn1b6i97Hx8fpKWlwcrKCq6urvjf//4HAOjXrx8AICoqClFRURgyZAiWLVsGLy8vqbeb2tnZYdiwYRg2bBg+/vhjzJgxgxvEVlFRwVdffQVTU1MoKSnhww8/BI/HQ2ZmJlRUVKCiooLQ0FDw+Xyoqalh5cqV+P3339HS0oI+ffqgurpa6rvW1NRI3U7rjvtvnwkEArb/HO4zD8fCwgLHjh1DREQEBAIB+vTpAycnJ3z00UdYtWoVV05dXR1+fn7Q0tKCra0tlJWVsWvXLpn89tVW+Xw+/vjjDwQEBEBDQwPm5uYYMmQITpw4gU2bNslti7q6uszVA4Bu1aGqqooffvgB+fn5XJqJiQm+//57TJkyBYaGhtDS0sKiRYsgEoketttkPJEBpDt4PB4EAgGmTZsGGxsbLF++XCp/6NCh8PHxgZubGw4ePAgbGxtoampy+XZ2dvjwww9hY2ODuLg4ODo6dnguDQ0NqKq2zXgeMmSIzC0nsVgMdXV1DB48GK2trVK3x8RiMVRVVaGiooIRI0YgKytL6tiLFy926737DMP0nhUrViAxMRHh4eHcD2tWVhYWLVqElStXyryJlohQUlKC7du3w9rausv61dTUIBQKubcDFxcXc69kt7S0RE5ODl544QWF62i3du1apKSkSAUQAwMDEBHOnz8PoO036O+//+6yzYp4agPI/UJCQvDjjz/KHYw+fvw4vvzySwQFBcnkSSQSbNy4ERkZGdzAd25urtQ/RlpaGhISEjBt2jQAgK+vL4KCgrixkqioKKipqWHEiBHQ09PD1KlTsXTpUojFYrS0tOB///sfnJycoKSkhIkTJ6K2thZ79+4F0DY2c/z4ccycORNA29hGZGRkr/YNwzCy7Ozs8PPPP8uknzp1Cnw+H5aWlnKPGz16NPLy8rqsPyIiAm+99RY2bNiABQsWYMmSJVi7di0AoLq6GoWFhaipqVG4DgCwsbGBi4sLPv/8c6krmLy8POTl5SEhIQGDBw/usq0P44l9kLAnXnnlFXz88cdYuHAhsrKycODAAXz++ecQi8UQCASIjIzEhAkTuPLz5s1DcnIyKioqMHz4cJw6dYq7BVZaWoqZM2eiqakJPB4PGhoaCAkJgYODAwBg4cKFuHbtGgYNGgR1dXVoa2sjLi6Ou7r5/vvv4e3tDWNjYxAR3njjDezZswdA22yxH3/8Ed7e3vD390dLSwu++eYbjBgxAgAQExOD69ev46OPPvo3u49hnjt9+vTB3bt3ZdJbW1shFAqlnt1atGgRJk2ahH79+oHP53N/8LVbv349PvnkE+6zlZUVbt++jejoaHz66adQU1NDTEwMCgoKAACFhYWYNGlSl23srA6BQICdO3di5syZMremJBIJ3n77baxfvx6ZmZlITk7G6tWrcfHixe53UHc9iYPoy5Yte6g6WlpaqKSkROpZj/s1NjZScXEx1dfXy81vbW0loVBIlZWVHZ6jsbGRhEJhh/nV1dVSA6APtq+0tJTEYrFUen19PVVXV3dYJ8OwQXT5ejqIXlhYSJ6enjLpysrKJBaLydramgBQamoqbdmyhdzc3Cg5OZnWrVsnVT41NZXWrl1LlpaW3AaAli9fTklJSaSjo0O6urp04MABio+Pl9uW1NRU8vHxkUnvrI6dO3fSihUriM/nE5/Pp4MHD5K/vz/xeDypOnR0dOjrr7+m6upqMjEx6fVB9GfiCuRBKioq3IC5PHw+v9MlQZWUlKT+AumoDnnPgrTT1dXttH2mpqYy6feP0TAM8+ikpqZi4sSJ2L9/v1S6o6MjmpqapMYqs7OzcezYMVy9ehV//fUXYmNjuSsBACgqKpIZ2/Ty8kJgYCBqa2sBAH5+fqiqqoKmpiYaGhq61cbO6pg6dSr4fD7WrFkDoO33yMXFBePGjYO7uztXR21tLVatWgUPDw9YWVnhxIkTPeilrj0TYyAMwzA9sWnTJri7u2Pu3Lnc+MHw4cOxbds2bNy4Ec3NzTLH5ObmIjIyEjt27Oiy/pKSEtjZ2XGf7ezsUFxcjIaGBujr6yMgIEDqD1BlZWWoqqpym5KSUqd1GBoaQiAQcNvhw4fxySefwN3dHS+88ILUAP2oUaNgZGSEy5cvK9RXnWEBhGGY505OTg7c3Nzg7++Puro6CIVCJCcnIyoqCl9//XWHx61btw4WFhbw9PTstP6lS5fC2dkZBQUFyM7ORnBwMDw8PAC0jZFs3boVgwYN4spHRUVBLBZzm6ura6d1dMbc3BzZ2dmorKxESUkJDh8+jPnz56OwsLB7ndMDz+QtLIZhmK6cPn0aI0eOhEAggIaGBoRCocxbH8aOHSv1uba2Vur284P57fLz8/Hmm29CW1sbPB4PlZWVXN7JkydhbGyM8vLyTusA0GEdD5oxYwa3n5ycDAMDA+42vFAo7PC4h8UCCMMwz7W6ujru4eXeJu/1SwC44PEwdXSGiKssQDEAACAASURBVB5p4Gj3xAUQiUQi81cAwzBtWltbkZGRIXcK6vPs2rVr0NbW7vLZCqb75I0DPeiJCyBJSUkYPXr0424GwzyR1NTUkJOT0+2ZPM+LGzduoK6uTuZJ7X/Dv/EH7+P4Xt3xxAWQ+vp6/Pnnn4+7GQzzRGppacGsWbMwffr0x92UJ0psbCx++eWXZ/buxeP4Xg++zkUeNguLYRiGUQgLIAzDMIxCWABhGIZhFMICCMMwDKMQFkAYhmEYhbAAwjAMwyjkiZvG212BgYGQSCTYvHmzzBzpgoIChIaGwsbGBt7e3ggKCurwyc8PP/yQWzzm3Llz2LdvH4qLizFkyBCZd+JkZWUhKioKW7Zs4VYobE+Pjo5GaWkpzM3N4e/vL/M2YKFQiE2bNmHOnDkYNmwYly4SiRAZGYmUlBRoaGjAxcVF6m2aJ06cwOHDh1FZWYmXXnoJCxcuxMCBAzvtm/j4eBQVFWHZsmWdlmMYhnkYT+0VSEREBCIiIpCcnCyTFxYWht27d+PUqVMAACMjI5iamsLU1BT79+9HWVkZ97n9jZhbt27FtGnTMGDAAMyfP59bQKpddHQ0nJ2dsW3bNrS0tHDpGRkZcHV1hYmJCTw8PFBcXAwbGxvuFcztZaytrREWFoabN29K1fvuu+8iOTkZzs7OsLW1RUBAALZs2QIAOHToEFauXImhQ4fi/fffx71792Btbd3hU8gikQgBAQGYN28et4Y7wzDMI/OkLSg1ZswYGj9+fJfldHV1ydPTk7y8vKTSRSIRGRsbk4eHB82ePVvmuEGDBtGePXuk0q5fv07q6uqUm5sr91xHjx6l4cOHU0pKCgGgxsZGqfz7F46SSCRkZGREx44dIyKiO3fukJmZGf322280ePBg+vnnnzs8lojou+++o1GjRknVdz8zMzNKTEyU285ly5aRu7s7RUREkLW1tdwyzNONLSglX08XlGJb7ywo9dRegQCAp6cnDh06JPXX/tGjRzFs2LBOF5R60IEDBzB+/HgMGTJEbr6rqysyMjKk3rF/P4FAIPVZIpFwVzYmJibIzc2Fk5OT1JVLd44F2tYJaFdaWoqKigq8/PLLctsRFBSEuLg4qKmpyc1nGIbpTU9cANHW1saVK1fg4OAgd7t/bfOBAwfC0tIScXFxXFp0dDR8fX0hkUi6fc4rV67A3Nwc7777LoyMjPDSSy8hPDycy1dSUoKmpma3XicQGxsLIyMjqYVg2oNEV8c3NzcjIiJCak30iooKbN68GcuXL4ebmxs2bdqEkSNHyj1eS0tL7nmSkpK4/d27d7P9Z2Cf6T1aWlowMjJ6JHXzeDzo6Og88jp4PB63MFY7ZWVlGBkZgcfjPdT5O/Wk3cLy9/enTz75hE6fPi13O3PmDK1bt450dXUpJyeHIiIiyNbWloiIbt++TXp6elRXV0eLFy/u9i2sd955h8zMzCgjI4OIiM6fP0/a2tqUkpIiVe7GjRtyb2G1y8jIIAMDA0pPT5ebP2DAAJlbWO0kEgnNnDmTpk6dKpVeWlpKixcvpg8++IBGjBhBs2bN6nCt9Xa7du2SuoVVVlYm9R3Y/tO7z25hyafILSwHBwf6559/SCQSUVVVFZWXl1NgYCApKSlxZZKSkqipqYkaGhro5s2bFBsbS/3795fJv3+zt7cnbW1tiouLo2vXrlFeXh6dP3+eBg8eLLcdSUlJNGvWLJn07tZhbm5O9fX15Ofnx6X5+vpSeXk5CYVCEolElJGRQWpqar1+C+uJDCDfffddl+XaA0hNTQ1pampSXl4ebdy4kXx9fYmIehRAXF1dad26dVJpHh4eMmmdBZALFy5Q37596fjx4x22uaMA0traSvPnzydHR8cOgxMRUXNzM1lZWdEXX3zRYRki2QDCPDtYAJGvpwHEwsKC+9Ft/2G1tLSkgoICWr16NVcuNTWVfHx8SElJiczMzGj//v108uRJmfwH61+1ahUdPXqUa9OXX35JiYmJctvyMHWoqqpSeno6ZWZmcgHExMSERCIR2draEgDi8Xg0atQoNgYij46ODqZOnYqYmBjExMTA19e3x3UMGTIEt27dkkoTi8XdehslAFy6dAnOzs4IDw+Hi4tLj8/v7++PgoIC/PTTT1LjHw9SU1ODhYUFrl+/3uNzMAzzf1asWIHExESEh4dDJBIBaJuOv2jRIqxcuVLm/30iQklJCbZv3w5ra+su61dTU4NQKERraysAoLi4mHvcwNLSEjk5OR2OqXanjnZr165FSkoK8vPzuTQDAwMQEc6fPw+g7bfs77//7rLNinjqAwgA+Pj4IDQ0FBKJRGrsobs++OAD7N+/H+fOnQPQtl7yr7/+Cicnpy6PvXTpEiZMmID169fD1tYWQqEQQqFQamC/M/7+/sjIyMCuXbvQ0NDAHd/S0oKUlBTcuXOHK5uZmYmffvqJm2KcnZ2Nzz//HGKxuMffmWGeZ3Z2dvj5559l0k+dOgU+n889G/ag0aNHIy8vr8v6IyIi8NZbb2HDhg1YsGABlixZgrVr1wIAqqurUVhY2OXiV53VAQA2NjZwcXHB559/LjX+kZeXh7y8PCQkJGDw4MFdtvVhPLUPEt7P0dERBgYGmD17tkLHv/7669ixYwcmTZoEFRUVNDU14ZtvvoGVlVWXx27btg137tzB3LlzZdrU/hxKR8rKyrB9+3YAwIABA6TyUlJS8Ndff8HV1RXq6upQVlZGa2srFi9ezF1lnTp1Chs3boS/v7/UOs0Mw3SuT58+cp+nam1thVAo5NYTB4BFixZh0qRJ6NevH/h8PmbOnCl1zPr16/HJJ59wn62srHD79m1ER0fj008/hZqaGmJiYlBQUAAAKCwsxKRJk7psY2d1CAQC7Ny5EzNnzuSuoNpJJBK8/fbbWL9+PTIzM5GcnIzVq1fj4sWL3e+gbuqVALJlyxaZL6GoCxcudDid9n7V1dXcvrKyMoqKiqTyQ0JC5B539epVuekffPABvLy8IBQKYWxsLHcFsJdeeklmhlNYWBjCwsK6bC/Q9h/O/UxMTDqdmTV27FgsXrwYQqEQSkpKMDQ0lJrWu2TJEnh7e8PExETqOB8fH/j4+HSrTQzzPKqsrISxsbFMurKyMgwNDVFRUcGlpaamIikpCUuXLsWvv/4qdbsIAHbu3ImffvqJ+yyRSLB8+XJMnDgRgwYNgpKSEr7//nvs3btX6i0TXemsjpCQEOzZswfXrl0Dn8+HsrIyVFVVwePxIBaLUVlZCX9/f6xatQorV65EamoqhgwZgrKyMgV6q2MPHUBCQ0ORmJiIsWPH9kZ70NzcLPWP929SUVGR+TF+3Dprk7Ky8hPXXoZ5GqSmpmLixInYv3+/VLqjoyOampqQlZXFpWVnZ+PYsWO4evUq/vrrL8TGxnJXAgBQVFQkVR4AvLy8EBgYyN3K9vPzQ1VVFTQ1Nbu9HHFndUydOhV8Ph9r1qwBAPD5fLi4uGDcuHFSQaq2tharVq2Ch4cHrKyscOLEiR70UtceOoC0tLTAxsYG//3vf3ujPQgICJC6fGQYhultmzZtwtmzZ5GSkoKYmBhIJBIMHz4c27Ztw8aNG9Hc3CxzTG5uLiIjI7Fjx44ux0dLSkpgZ2eHkydPAmgbcykuLkZDQwP09fXh5eWFyMhINDU1AQB3BdFOIpF0WoehoaHU+RISEnDq1CmEh4dzg/PFxcUAgFGjRsHIyAiXL19WsLc69kwMojMMw/RETk4O3Nzc4O/vj7q6OgiFQiQnJyMqKkrmJar3W7duHSwsLODp6dlp/UuXLoWzszMKCgqQnZ2N4OBgeHh4AGgbI9m6dSsGDRrElY+KioJYLOY2V1fXTuvojLm5ObKzs1FZWYmSkhIcPnwY8+fPl7mF3hueiUF0hmGYnjp9+jRGjhwJgUAADQ0NCIVCmTHJB2/N19bWSk1Y6ejWfX5+Pt58801oa2uDx+OhsrKSyzt58iSMjY25N4R3dvu/ozoeNGPGDG4/OTkZBgYG3J0coVDY4XEPiwUQhmGea3V1dairq3skdd+7d09uekfLS/Skjs4Q0SMNHO1YAGGYp8zNmzeRkpLyuJvxRCkuLgafz+/2ADXTNXkvf30QCyAM8xTR0tJCQkICN7DKtKmqqkJzc7Pc6fePWmdT8XvLv/29iIh7Ar4zLIAwzFOkvr4ey5Ytw/Tp0x93U54osbGx+OCDD/6VH/PH4XF8r+4sC8FmYTEMwzAKYQGEYRiGUQgLIAzDMIxCWABhGIZhFMICCMMwDKMQFkAYhmEYhTw103gDAwMhkUiwefNmmTnRBQUFCA0NhY2NDby9vREUFNThk54ffvghLC0t8dNPP+HQoUNoamrC6NGjsWDBAm41wObmZnz33Xc4d+4cjI2NsXDhQrz66qtcHVlZWYiOjkZpaSnMzc3h7++Pfv36AQAaGhoQGBgodU5zc3MsXrwY6enpiI2NlduukJAQqZepAW2vihcKhdwbNzsSHx+PoqIiLFu2rNNyDMMwvempuQKJiIhAREQEkpOTZfLCwsKwe/dubgEnIyMjmJqawtTUFPv370dZWRn3mc/nY/PmzQgKCoKVlRWmTZuG/fv3Sy0SM23aNBw7dgwzZsyAmZkZ3nrrLVy4cAEAkJGRAVdXV5iYmMDDwwPFxcWwsbHhXrl8584dREVFwdDQkNt0dXUBAOrq6lLphoaGKC0tRVxcnNQ6H0Db66Y/++wzHD9+vMM+EYlECAgIwLx58xAfH/9wHcwwDNNDT80VCABMmjQJu3btgqOjI5cmFosRGxsLNzc3Lm3hwoXcfkxMDKZMmQJvb28ubcCAAViyZAm3DOSrr76KESNGoK6uDkVFRUhOTsadO3egp6cHAKioqMBXX32FuLg4WFtbIy8vDwKBAEBbsDE1NUVKSgpcXV1RXl4OU1NTrFu3Tqb9b7zxBt544w2Z77Rw4UKpAFJbWwtfX18sWLAAp0+f7rA/Vq1ahbKyMgQHByMqKqo7XcgwDNNrnporEADw9PTEoUOHpNYbP3r0KIYNG8bdQuoODQ0NqTWEJRIJVFVVoaKigqKiIpiamnLBAwCcnZ2RlpbGfW4PHvcf3377SygUyryrvyNXrlxBUlKSVMAD2tZE8fb2xvDhwzs9PigoCHFxcd16YpRhGKa3PXEBRENDA4mJiViwYAEWLFiAVatWcXkDBw6EpaUl4uLiuLTo6Gj4+vpCIpEofM6tW7fC29sbGhoaGDhwIEpLS6WWfkxLS0NVVZXcY2NjY2FkZAQ7OzsAbVcrV69exWuvvYahQ4fCw8Ojw4VcgoOD4eXlJbW0ZkJCAvLz8/H55593+foCLS0tALKvOUhNTeX2778FxvafjX2md2lpacHIyOiR1M3j8aCjo/PI6+DxeFJ/FANti1QZGRmBx+M91Pk788QFkPXr12PmzJl4/fXX8frrr+PVV19FUFAQgLYfSh8fH+zatQsAUFpairS0NKl34ffUjh07cPr0aXz77bcAgFdeeQXe3t6ws7PDp59+Cnd3d6Snp0NfX1/m2HPnzmHJkiWIiYnhrgLee+89HDx4EEeOHMH+/fuho6ODt99+W2ZQ//bt29i/fz+WLFkilbZs2TLs3btX5j+Gnrh/Rcf7l7xl+8/GPtM7HBwc8M8//6Cqqgr5+fkoLy9HYGCg1CSdpKQkNDU1oaGhATdv3kRsbCz69+8vk3//Zm9vD21tbcTFxSE3Nxd//fUXzp8/j8GDB8ttR1JSEmbNmiWT3t06zM3NUV1djY8++ohL8/X1RVlZGa5cuYL6+npkZGQ8mjsV9vb21Bk3Nzc6evRoh/mbN2+mZcuWdVpHb9DV1aWcnByqqakhTU1NysvLo40bN5Kvry8RES1evJhmz54tc9ygQYNoz549cuvcs2cPvfjii3T9+nWZvD/++IMiIyMpPT2d9uzZQ9bW1lL5Fy5coL59+9Lx48c7bXdrayv179+ffvzxR6n05cuXk4uLi1Taf/7zH5o/fz6lpKRQSkoKrVmzhl599VVKSUmh+vr6Ds+xa9cumfYxz6a1a9dSQkLC427GE2fv3r2krKxMALq1WVhYUH19Pfn5+ZGamhoBIEtLSyooKKDVq1dz5VJTU8nHx4eUlJTIzMyM9u/fTydPnpTJf7D+VatW0dGjR7k2ffnll5SYmCi3LQ9Th6qqKqWnp1NmZib5+fkRADIxMSGRSES2trYEgHg8Ho0aNarbfdO+mZubd9rnY8aMoSfuCqQrOjo6mDp1KmJiYhATEwNfX1+F6tm/fz8+//xzJCUl4eWXX5bJt7Ozw4cffggbGxvExcVJDdxfunQJzs7OCA8Ph4uLS6fnUVJSgrq6utQU3ZqaGkRERMhMu62qqkJqair8/Pzg5+eHXbt24caNG/Dz88Pt27cV+p4Mw8hasWIFEhMTER4eDpFIBKBtev6iRYuwcuVKqKurS5UnIpSUlGD79u2wtrbusn41NTUIhULulejFxcXclY2lpSVycnK4tcsVqaPd2rVrkZKSgvz8fC7NwMAARITz588DaJto9Pfff3fZZkU8VbOw2vn4+GDq1Kno168fN/bQEwcOHMAnn3yCI0eOQE9Pj1u5S0tLCxoaGlw5iUSC4OBgZGRkIDIyEkBb8JgwYQI2bNgAW1tb7lg1NTXo6OggLS0NQ4cOhYGBAVpbWxEWFoaamhrY29tz9YaHh2PgwIEYP368VLvOnTsn9Xnv3r3Ytm0bzp49CwDIzs5GfHw8vvjii0d6X5NhnnV2dnZYuXKlTPqpU6fA5/NhaWmJjIwMmfzRo0cjLy+vy/rbHznYsGEDbt26hY8//hju7u4AgOrqahQWFqKmpkbhOgDAxsYGLi4usLW1xb59+7j0vLw85OXlISEhAUuWLMHVq1e7bK+inrorEABwdHSEgYEBZs+erdDxQUFBuHv3Lt566y0YGRlxW/s4yLx58zB48GAYGhrixIkTOHXqFHcPetu2bbhz5w7mzp0rdey7774LADh79ixeeOEFGBkZQVdXF9HR0Th69Cg3M0skEiE0NBRLly7tcbtPnTqFjRs3oqKiQqHvzTBMmz59+uDu3bsy6a2trRAKhVLjiIsWLUJiYiLS09Mxa9YseHl5SR2zfv16ZGVlcZuKigpu376N6OhozJs3D//973/x22+/oaCgAABQWFiISZMmSc0mlaezOgQCAXbu3InZs2dzV1DtJBIJ3n77bdy8eROZmZk4cuRIlzM6Ffa0jIH8mxobG6m4uLjTcYfOtLS00J07d6ihoaFX2yWRSOjOnTu9WifzdGFjIPL1dAyksLCQPD09ZdKVlZVJLBaTtbU1Nz6xZcsWcnNzo+TkZFq3bp3M+MXatWvJ0tKS2wDQ8uXLKSkpiXR0dEhXV5cOHDhA8fHxPRoD6ayOnTt30ooVK4jP5xOfz6eDBw+Sv78/8Xg8qTp0dHTo66+/purqajIxMen1MZCn8hbWo8bn86VmWvSUiorKI5k1o6yszGbjMEwvSE1NxcSJE7F//36pdEdHRzQ1NSErK4tLy87OxrFjx3D16lX89ddfiI2N5a4EAKCoqEiqPAB4eXkhMDCQu8rw8/NDVVUVNDU1u71ue2d1TJ06FXw+n3vNEZ/Ph4uLC8aNGyd1m6u2tharVq2Ch4cHrKyscOLEiR70UteeyltYDMMwD2PTpk1wd3fH3LlzuSnzw4cPx7Zt27Bx40Y0NzfLHJObm4vIyEjs2LGjy/pLSkqkxmft7OxQXFyMhoYG6OvrIyAggHv4GGj741BVVZXblJSUOq3D0NAQAoGA2w4fPoxPPvkE7u7ueOGFF6QG6EeNGgUjI6MOn0d7GCyAMAzz3MnJyYGbmxv8/f1RV1cHoVCI5ORkREVF4euvv+7wuHXr1sHCwgKenp6d1r906VI4OzujoKAA2dnZCA4OhoeHBwDAysoKW7duxaBBg7jyUVFREIvF3Obq6tppHZ0xNzdHdnY2KisrUVJSgsOHD2P+/PkoLCzsXuf0ALuFxTDMc+n06dMYOXIkBAIBNDQ0IBQKZd7qMHbsWKnPtbW1MDU17TC/XX5+Pt58801oa2uDx+OhsrKSyzt58iSMjY25h4s7qgNAh3U86P6HqZOTk2FgYMBNBGifKfoosADCMMxzra6uDnV1dY+k7nv37slN72i5iZ7U0RkieqSBox0LIAzzlCEitLS0PO5mPFEevHJg/h0sgDDMU0QgEGDlypX44osvHndTniiNjY1QVlbmntpmHl5jY2OXZVgAYZinSF1dHTZt2oTp06c/7qY8UWJjY/HBBx887mY8U+5/K0dH2CwshmEYRiEsgDAMwzAKYQGEYRiGUQgLIAzDMIxCWABhGIZhFMICCMMwDKMQFkAYhmEYhbDnQP6/wMBASCQSbN68WWbZyIKCAoSGhsLGxgbe3t4ICgrq8FUEM2bMQEJCgty8RYsWYdiwYWhtbcXOnTtx6tQpaGlpYcGCBRg9erTcY8LCwiAUCrnXNrfLyspCVFQUtmzZIrVcbk5ODmJiYlBYWAgjIyO8//77Uqsh1tTUYMuWLcjOzsaAAQOwYsUK9O3bt9O+iY+PR1FRkcwSvAzDPN/YFcj/FxERwS0h+aCwsDDs3r0bp06dAgAYGRnB1NQUpqam2L9/P8rKyrjPGhoaMDQ0lNrU1dWxfft2iMViAG0rIgYHB8PFxQWDBw/G+PHjkZOTI3Pe1NRUfPbZZzh+/LhUenR0NJydnbFt2zapV1rcvn0bbm5u0NLSgqenJwYOHIiJEyciKSmJKzN58mSkpaXhvffeQ1VVFezt7Tt84lQkEiEgIADz5s1DfHx8zzuVYZhnGrsCuc+kSZOwa9cuODo6cmlisRixsbFwc3Pj0hYuXMjtx8TEYMqUKfD29ubSrK2tper99ttvMW7cOIwYMQLNzc3YsmULjh49inHjxgEASktLERwcjD179nDH1NbWwtfXFwsWLMDp06e59GPHjmHLli2Ij4+XWQ++X79+uHHjBpSV/+/vggsXLuDIkSNwdHREeno6zp8/j7KyMmhpacHDwwMjRozAvn37MHfuXJn+WLVqFcrKyhAcHIyoqKhu9yPDMM+HZ/4K5MCBAwgNDe1w2717N1fW09MThw4dklqr+OjRoxg2bBj69eun0PnFYjFCQkK4NdAvXboEsVgs9QpnJycnnDlzRuq4gIAAeHt7y6xl7OrqioyMDKkFY+53f/CQSCS4fPkyXn75ZQBAeno6bG1toaWlBQBQUlLChAkTZM7dLigoCHFxcVBTU5NKv/9qKSMjg+3/y/tM79LS0oKRkdEjqZvH40FHR+eR18Hj8biFsdopKyvDyMgIPB7voc7fmWc6gPz222/YtGkTbty40eF269YtBAUFAQAGDhwIS0tLxMXFcXVER0fD19cXEolEoTbs27cPmpqamDRpEoC2qw1DQ0Opf2wTExOUlJRwbxRNSEhAfn4+Pv/8c5m3jCopKUFTU7PTt4/u2LEDa9euhYODA0aPHs1dMZWWlsosiWtiYoJbt27Jrac90Dx4rvsDbFVVFdv/l/eZ3uHg4IB//vkHVVVVyM/PR3l5OQIDA6XGQJOSktDU1ISGhgbcvHkTsbGxUstdt+ffv9nb20NbWxtxcXHIzc3FX3/9hfPnz2Pw4MFy25GUlIRZs2bJpHe3DnNzc1RXV+Ojjz7i0nx9fVFWVoYrV66gvr4eGRkZMn8I9gp7e/tOF053c3Ojo0ePdpi/efNmWrZsWbcWvv+3HTt2jFxdXbtVVldXl3JycigiIoJsbW2JiOj27dukp6dHdXV1tHjxYpo9e7bMcYMGDaI9e/bIrbO1tZWGDx9OYWFhXNqhQ4do4MCBUuWysrIIALW0tFBJSQm9+OKLdPXqVSIi2rNnD1lbW8vUfePGDQJAjY2NMnmrV6+mDz/8kMaMGUMODg6Um5tLRESLFy+mOXPmSJUNCQkhOzu7TnqGaNeuXXLbwPz71q5dSwkJCY+7GU+cvXv3krKyMgHo1mZhYUH19fXk5+dHampqBIAsLS2poKCAVq9ezZVLTU0lHx8fUlJSIjMzM9q/fz+dPHlSJv/B+letWkVHjx7l2vTll19SYmKi3LY8TB2qqqqUnp5OmZmZ5OfnRwDIxMSERCIR2draEgDi8Xg0atSobvdN+2Zubt5pn48ZM4ae6SsQRcycORNZWVnIz8/H7t27MW3aNO4v8Z46ceIESktLMXv2bC6tT58+qK6ulipXU1MDbW1tqKiowNfXF87OzigtLUVqairy8/Nx7949pKamoqGhoVvn/eqrrxAZGYnU1FQMHz4c8+fP7/Tcenp6Cn0/hnlarVixAomJiQgPD4dIJALQNrNx0aJFWLlyJdTV1aXKExFKSkqwfft2mTFOedTU1CAUCrnXyxcXF3NXNpaWlsjJyenwNnR36mi3du1apKSkID8/n0szMDAAEeH8+fMA2m6j//333122WRFsEP0BOjo6mDp1KmJiYnDw4EFERkYqXFdwcDAWLlwo9Vrk4cOHo7q6GsXFxdx/QBcvXoSFhQWAtlsVJSUlSE1NBdD2A19RUQE/Pz8cPny4w8vgjlhZWeHw4cMAgBEjRuCHH36Qyr//3AzzvLCzs8PKlStl0k+dOgU+nw9LS0u5406jR49GXl5el/W3z+jcsGEDbt26hY8//hju7u4AgOrqahQWFqKmpkbhOgDAxsYGLi4usLW1xb59+7j0vLw85OXlISEhAUuWLMHVq1e7bK+i2BWIHD4+PggNDYVEIpGZ6dRd586dQ0ZGBhYtWiSVbmBggIkTJ2LDhg1oaWnB3bt3ERISAk9PT+64ixcvctvGjRsxYsQIXLx4scvgceXKFVy8eJH7XFZWhvDwcDg4OAAAJk6ciNraWuzduxcAcPbsWRw/fhwzZ84EACQmJj5UwGSYp0WfPn1w9+5dmfTW1lYIhUJuPXGg7fmtxMREpKenY9asWfDy8pI6Zv36MF21vgAAIABJREFU9cjKyuI2FRUV3L59G9HR0Zg3bx7++9//4rfffkNBQQEAoLCwEJMmTZIaS5SnszoEAgF27tyJ2bNnc1dQ7SQSCd5++23cvHkTmZmZOHLkiMxknN7CAogcjo6OMDAwkLr11FObNm2Cl5eXzKA1AHz//fc4f/489PT00L9/f9jZ2WHBggUP02QAbQFj4sSJ0NHRQf/+/TFo0CAMHDgQW7duBQBoamrixx9/RGBgIPT09DBhwgR88803GDFiBIC2KckhISEP3Q6GedJVVlbC2NhYJl1ZWRmGhoaoqKjg0lJTU7Fr1y40NjbiyJEjUreLAGDnzp3w8fHhNolEguXLl2PixIkYNGgQXnzxRZiYmHB/uHVXZ3WEhIRgz549uHbtGvh8PpSVlaGqqsrNuKqsrIS/vz/MzMxw6dIlpKamyv0temhsEP3xKSsro4aGhl6ts7W1lSoqKqikpIREIpHcMi0tLVRaWkpisVgqvb6+nqqrq3u1PUzvYoPo8vV0EH3v3r0UExMjk+7k5ET37t0jdXV1mQHuoUOH0r1798jc3LzLAfDMzExycnLiPuvp6RERkaamZrcH0TurQygUUl1dHbe1tLRQU1MTxcfHy/2+169fJxcXlydvEL2urg7Nzc0PW81zydjYuFvLRvaEkpIS9PX10a9fvw7nf6uoqMDU1FTqFShA2xWKrq5ur7aHYZ5EmzZtgru7O+bOnctNqR8+fDi2bduGjRs3yv1Ny83NRWRkJHbs2NFl/SUlJVK3v+3s7FBcXIyGhgbo6+sjICAAfD6fy2+/gmjflJSUOq3D0NAQAoGA2w4fPoxPPvkE7u7ueOGFF6QG6EeNGgUjIyNcvnxZob7qzEMHkF9//RV9+vTpjbYwDMP8K3JycuDm5gZ/f3/U1dVBKBQiOTkZUVFR+Prrrzs8bt26dbCwsODGLDuydOlSODs7o6CgANnZ2QgODoaHhweAtoktW7duxaBBg7jyUVFREIvF3Obq6tppHZ0xNzdHdnY2KisrUVJSgsOHD2P+/PkoLCzsXuf0wEPPwlJWVkZaWlpvtIVhGOZfc/r0aYwcORICgQAaGhoQCoUyD83e/8YIoO0hWlNT0w7z2+Xn5+PNN9+EtrY2eDweKisrubyTJ0/C2NiYeyFrR3UA6LCOB82YMYPbT05OhoHB/2PvzKOiOLq//2VgYFhlFXfjQlwCBgXF4IKoSEBUEsQlhAgxRoKQKBr0h4a4RBH0icRdAQEVfUR41KCYRAc1jCIxBIgroAmKiMiwDpsDM/X+waFf2xmGVRGpzzl1Tnctt2tK7NtVt+peA2YjgFAobLJde6HbeCkUSremsrISlZWVr0S2SCSSm9+UN+/WyFAEIeSVKo5G6C4sCoVCobSJLj0D+frrr5GYmChzOrORqqoqmJiYvOZeUSivjh49emD79u3M1mxKAzU1NVBVVUVtbW1nd+WtoSWbo7q0Ajl27BjOnz/fpBH/8uXLePjw4WvuFYXy6igrK4OHhwccHBw6uytvFKdOnWI8XlM6hpd3acqt8xr68cpQUlLCoEGDYGhoKLc8KyuLceNBobwNKCkpwdDQEAMGDOjsrrxRNPUOoLSdl93Dy4PaQCgUCoXSJqgCoVAoFEqboAqEQqFQKG2CKhAKhUKhtAmqQCgUCoXSJqgCoVAoFEqb6JYKJCwsDD4+PnKdi9XX12PFihX4/vvvATSEpX05RkZ2djZ8fHzw9OlTVn5oaCh+/fVXAA2RBNevX4+PPvoIy5cvR0FBAVNPLBZjz549WLBgATw9PXHy5EmWnJs3b2LlypVwcXGBl5cXfv/99yZ/y759+7Bp0yZW3smTJ/Hpp5/is88+wy+//MIqq6mpwfbt2xlPpAkJCU3KbiQjIwO+vr6or69vti6FQuk+dEsFcu7cOURHRyMiIkKmLDExEeHh4YiOjgbQ4FPm+++/h0QiYeqcOHECe/fuxc8//8zkSSQSBAYGMqfiZ8+ejatXr2LevHkoLS3F5MmTUVNTAwD4+OOPkZSUBAcHB1hbW8PX1xc7duwA0BCFzMnJCZqamli4cCEGDx4Me3t78Pl8mb4KBAL83//9H86dO8fkhYSEYNWqVZg6dSqmTJmCzz//nPU7Fy5ciN9++w2LFy/GlClT8OWXXyIqKqrJsTp06BAcHBywe/duqkAoFAqb9gaUmjBhApk6dWprYr90GIaGhqSoqKjJ8qYCSs2ZM4csXLiQ9O/fn0gkErllAwcOJIQQIhKJCJfLJampqUyd8ePHE3t7e+Lk5MTkpaSkEDU1NVJdXU2uXbtGNDU1SWVlJSGkIciTqakpCQ8PZ2S+yK5du4ilpSVz/3Kf3NzciK+vLyuvvLycDB06lKxZs4ZYWVkx+UZGRiQxMZG5T0hIIMbGxkQqlRJCCOFyuSQtLY0pDwwMJPPmzZMZo8a2pqamJDk5mQAgNTU1cutRXh80oJR8WhtQiqY3JKDUm05ZWRl+/fVXJjV63WwM1JKUlMTUffbsGa5cuYJZs2YxeVpaWrCyssKlS5cANLhGTktLw5YtW8Dn81FdXQ2gwTW0tbU11NXVkZKSAmtra2hqagJoOD08ffp0XL58mZH5IhKJRCa4zItld+7cwaBBg1htfH198emnn7JiHdfW1qKoqAgjRoxg8mbMmAGhUIj79+8DaAia0zhzqq2txeXLl2FtbS137GbOnInU1FRWcJpGHjx4QK878ZrScWhqasLIyOiVyOZyudDR0XnlMrhcrszJcQ6HAyMjoyYDy3UEb7UCmTBhAgYNGoQdO3Yw6bvvvgMASKVSuLu7s5ZvDh8+DGdnZ5kogdOnT2cUyPnz5zF27FiMGTMGgwYNYpaWLl26hOnTpwMACgoKZOIPGxsb4/HjxzJ9fP78OQ4ePIglS5aw8vfu3YvAwEDY2tpi3Lhx8Pb2Zsri4uKQnZ2NdevWseIX8Hg89O7dG+np6Uze9evXIZFIUFpaCqDBPhIfH48ZM2bAzMwMEyZMwNdffy13/JSUlKChoSETIwEAUlJS6HUnXlPaj62tLf766y+UlpYiOzsbRUVF8Pf3Zzln5fP5qK2tRXV1NR4+fIiYmBj069dPpvzFNHnyZGhrayM2Nhb37t3DjRs3kJaWhqFDh8rtB5/Ph7u7u0x+S2WYmJigrKyM9Q7x9PREYWEh7t69i6qqKqSmpkJVVbU9wyWft3kJqynmzJlDdu3aRbKzs4mGhgYpLy8nhBAycuRIcvnyZXLq1ClmCYsQQgQCAdHU1CRisZjMnz+f/PDDD4QQQvz9/cmSJUuIWCwmGhoazDLXN998Qz7//HPWM0NDQ8mkSZNYeRKJhMyfP584OzvL9HHt2rXkiy++IBMmTCC2trbk3r17hBBC8vPzyYABA8j9+/cJIYQcOXKEtYQVGRlJ9PX1iY+PD/Hy8iIfffQR4XA4JCcnhxBCyO+//06GDx9OPv/8c/Luu+8SJycnUlpaqnC8/v33X7qE9YZAl7Dk09olLDMzM1JVVUW8vLyIqqoqAUDMzc1JTk4OWbt2rUy8ciUlJdK3b19y/PhxcuHChWbjmQcEBJCEhASmT5s2bSLx8fFy+9IeGSoqKiQlJYWkp6cTLy8vAoAYGxsTsVhMrK2tCQDC5XKJpaUlXcLqaExMTGBubo4TJ07g+vXrzNfDy1hZWYHD4eCPP/7AhQsXGE+oM2fOxLlz5xjtbmFhAQDQ09NDWVkZS0Z5eTl0dXWZe0IIvL29IRQKcfz4cZln/vDDDwgLC4NAIICpqSmWLl0KoOHLwsHBAQUFBRAIBMjOzoZIJIJAIEB1dTU8PDxw9epVWFhYYObMmfjxxx8BAH369EFBQQFmz56NAwcOICIiArdv34aRkRFcXFw6ZkAplC7C6tWrER8fj/3790MsFgNo2G24bNkyrFmzBmpqaqz6hBDk5+djz549sLKyala+qqoqhEIhpFIpACAvL4+Z2Zibm+PmzZtyl4ZbKqORwMBAJCcnIzs7m8kzMDAAIQRpaWkAgLq6Ovz555/N9rktdGlvvB2Bh4cHIiMjYWZmBg8PD7mxRVRUVGBjY4OIiAioqqpi9OjRABqWyGpqahAZGQlbW1tmDXLUqFE4fPgwS8atW7dgZmbG3Pv4+CAnJwcJCQks+4c8LCwsGK/CpaWlyM/Ph0AgANCgmIqLi+Hl5YXTp09j6NChGD58OIYPHw4A+PHHHzF+/HhoaGjg0qVL0NXVZZSkiooKfH19MXbsWBBCmoyrQqG8bUyaNAlr1qyRyb948SJ4PB7Mzc2RmpoqUz5u3DhkZWU1K//gwYNISkrC5s2b8fjxY3z99ddwdXUF0GCXzc3NRXl5eZtlAMD48ePh6OgIa2trHDt2jMnPyspCVlYW4uLisGLFCsb++Sro1jMQAJg/fz4yMzMRExODRYsWNVlv+vTpiIuLg4ODA/OiVVZWxocffoiTJ08y9g8AsLe3R0VFBY4ePQqgwQ5x7tw5zJ8/H0CD8khNTUVkZCSqq6shFAohFApRX1+Pu3fv4tatW4yswsJC7N+/H7a2tgCAP/74A7du3WJSUFAQRo0ahVu3bsmsj547dw6bNm3Chg0bAADvvfcenj59yvzHIIQgNjYWFhYWUFJSQllZGVavXo1Hjx61d1gplDcaPT09PHv2TCZfKpVCKBQy8cQBYNmyZYiPj0dKSgrc3d3h5ubGarNx40ZkZGQwSVlZGU+ePMGhQ4fw5ZdfYuvWrfjtt9+Qk5MDAMjNzcWsWbNQUVGhsI+KZGhpaSE8PByLFi1iZlCNSCQSTJkyBQ8fPkR6ejrOnDnD2mzTkXR7BaKjo4OPPvoI48ePVxhjwc7ODiKRCI6Ojqx8JycniEQilgLR0NDAiRMn4O/vD11dXUyfPh3btm3DqFGjUFhYiD179iAtLQ0DBw6EkZERk65fv47CwkLY29tDR0cH/fr1w5AhQzB48OAWR6A7fPgwBgwYgN69e2P58uUICwtj+vbOO+/gwIED+PjjjzF8+HD0798fv//+O44cOQKgYZdPSEiI3C8vCuVtoqSkBD179pTJ53A4MDQ0RHFxMZMnEAgQGRmJmpoanDlzhrVcBADh4eHw8PBgkkQiwapVq2Bvb48hQ4ZgwIABMDY2Zj4oW4oiGaGhoThy5AgePHgAHo8HDocDFRUVZsdVSUkJfHx80LdvX9y+fRsCgUBmY0+H0F4j+ujRowmPxyMqKiqvPamrq7fJiP66qK+vJwUFBaSurq5V7aRSKSkuLib5+flELBa3+pn5+fnNGsaFQiFzTuVFnjx50qrnUV4v1Igun9Ya0Y8ePUqioqJk8u3s7IhIJCJqamoyBu7hw4cTkUhETExMmjWAp6enEzs7O+ZeV1eXEEKIhoZGi43oimQ0/v9tTPX19aS2tpacPHlS7u/9559/iKOj45tnRK+urkaPHj1QU1Pz2pOmpib27NnT3p/wylBWVkavXr1aFBryRZSUlKCvr48+ffq0eg+3srIy+vTpwzLYy8PAwIA5p/IivXv3btXzKJSuSHBwMOPOp9F2aWpqit27dyMoKEhuPPB79+4hLCwMe/fubVZ+fn4+c9YMaLC55OXlobq6Gvr6+vD19ZU5+6WiosIkJSUlhTIMDQ2hpaXFpNOnT2P58uVwdXVF//79WQZ6S0tLGBkZ4c6dO20aK0V0mBG9tS/JjmLZsmWd8lwKhdJ1uXnzJpycnPDjjz9i9+7dqKqqglQqxfbt2xESEtJku/Xr1yM7OxsLFy6Uu3uyET8/P8TExGDhwoWorq6GqqoqFixYAKBhU8zOnTuRlJSE27dvAwAiIiJYLodmzZqlUIYiTExMEBcXB6DB9x0hBEuXLpXr+6+9dPtdWBQKpXty6dIljB49GlpaWlBXV4dQKJQ5NDtx4kTWfUVFBXr16tVkeSPZ2dkYO3YstLW1weVyUVJSwpRduHABPXv2RFFRkUIZAJqU8TJz585lrpOSkmBgYMBsBBAKhU22ay9UgVAolG5NZWUl4+KooxGJRHLzG5VHe2QoghDyShVHI91+FxaFQqFQ2gadgVAoXQhNTU0cPnwYJ06c6OyuvFFUV1dDW1u72bMVr4KXl71eBZ1xyFfeRoKXoQqEQulClJeXw9LSUq7Lne7MhQsXcP78+dfyMu8MOuN3tURpUQVCoXQhVFRUMHLkSNjY2HR2V94o5Hm6prSPlnjvpTYQCoVCobQJqkAoFAqF0iaoAqFQKBRKm6AKhEKhUChtgioQCoVCobQJqkAoFAqF0ia63Tbe/Px8BAUFYeTIkfD29pYpT0xMRGJiItzd3aGvr49du3Zhx44djMdOiUQCPz8/zJ07l+Up89y5c/j333/h4+PD5J08eRKPHj3CypUrZfqwc+dOPHjwACNHjsQ333zDCmDD5/MRHR2NmpoauLi4MA7UUlJSEBMTI/d3hYaGyji03LdvH4RCIb777jsAQGZmJsLCwlh1HB0dZWKcvIhQKERwcDA+//xzjBgxosl6FAql+9HtZiBFRUWIjo7Gt99+K/fU6rp16xAdHY27d+/C2NgYe/fuxV9//cWUX7t2Dbt27cK+fftY7fbs2YMnT54AAMRiMXx9ffHll1/i5MmTrHolJSWwsrJCWVkZPvnkEzx69AgTJkxAdXU1gIaQmrNnz8b7778Pe3t7+Pn5MS99NTU1GBoaslJBQQFiY2PB4bD/KQUCAf7v//4P586dY/LS0tLA5/NZ7TU0NJocq9TUVFhZWWHfvn14+PBhS4aXQqF0I7rdDAQA9PX10a9fP8TGxuKLL75g8jMzM1FSUsLELtfR0cHYsWNx6dIljB07FkDDDGXGjBk4f/486uvroaKigvr6eiQnJ2PVqlUAgICAABQWFiIkJITlohkA/vvf/6Jv3744cOAAAMDZ2RkffPABoqKi4O3tjW3btsHf35+Ztejq6sLPzw9LlizBmDFjMGbMGJa8WbNmwdvbm6VAKioq4Onpia+++gqXLl1i8ouKijB+/HisX7++2TEqLCyEi4sLIiMj5c7UKBQKpUvPQAghyMvLw8OHD1uUGoPYi8VieHh4ICoqiiUvIiICHh4eLB8w06dPZ72Ez507h2XLlqFHjx4QCAQAgBs3bkAikWDChAkAgA0bNiA2NlbuSc5Hjx6xloI4HA5mzJiBq1evAmhYprKzs2PK7ezskJeXhwcPHsjIunv3Lvh8vswL3tfXF59++qlMHGShUAhDQ8OmB/QFjI2Nce/ePdjZ2aG+vp5V1jiO9LpzrimUN4UurUDmzZsHZ2dn2NjYtChFRkbiwIEDqK+vx/z585Gens4EqReLxTh+/DgWLVoEiUTCPGP69OkQCASor69HXl4esrOzYWtri5kzZyIhIQFAQ1yBiRMnQk1NDQCYSH/y/NcMHjwYGRkZTFl9fT3++OMPlJaWoqqqCiKRiBW7uEePHlBTU5PrqiEkJARubm6s2M5xcXHIzs7GunXrZJ5fXFyM2NhYmJiYYPTo0VixYoXCGANaWlpyf0dkZCS97sRrSseiqakJIyOjVyKby+VCR0fnlcvgcrmMnbYRDocDIyOjVkc1bRXtjYk+bNgwYmxs3JKwxW8E6enpxMDAgBBCyCeffEICAgIIIYScOHGCTJkyhRBCyPvvv08iIyMJIYQ8f/6caGpqkmvXrpF9+/aR6dOnE0IISUxMZGIGT58+nQQHB8s8KzIyklhZWbHyqqqqiKmpKbGxsSGrV68mtra2ZPLkycTNzY2UlpYSAOTRo0esNrq6uoTP57Py8vPziZqaGrl9+zYrb8CAAeT+/fuEEEKOHDnCen5+fj65evUquX//Prl8+TKZOHEisbGxaXbMBg4cSM6fP99sPcqrh8ZEl09rY6IDILa2tuSvv/4iYrGYlJaWkqKiIuLv70+UlJSYOnw+n9TW1pLq6mry8OFDEhMTQ/r16ydT/mKaPHky0dbWJrGxseTBgwckKyuLpKWlkaFDh8rtB5/PJ+7u7jL5LZVhYmJCqqqqiJeXF5Pn6elJioqKiFAoJGKxmKSmphJVVdU3LyZ6V8bDwwNHjhyBVCrFoUOH4OnpKVNHVVUVkyZNwuXLl/Hrr7/CwcEBAGBra4v8/Hzcvn0b165dw/Tp01v0TA0NDfz555/w8/PDu+++i/DwcJiYmKBfv37Q1taGiooKysrKmPpSqRSVlZUyMc537NiBadOmYeTIkUyep6cnHBwcUFBQAIFAgOzsbIhEIggEAlRXV6NPnz6wtrbGkCFDYGNjg0OHDuHKlSt49uxZW4aPQumymJmZ4ezZszh48CC0tLSgp6cHOzs7LFmyBAEBAUw9NTU1eHl5QVNTE9bW1uBwOKzZYGM5j8dj0u+//w5fX1+oq6vDxMQEw4YNQ2JiIoKDg+X2RU1NTWb2AKBFMlRUVHD48GFkZ2czecbGxjhw4ADmzJkDQ0NDaGpqYtmyZRCLxe0dNhm6tQKZNm0aACA6OhqpqalwcXGRW2/69Om4fv06fv/9d2bLK4/Hw7Rp0/Djjz9CXV0do0ePbvFz1dTUMHv2bHz++efo27cvfv75Z0ybNg3KysoYOXIkMjIymLr37t0DAAwfPpzJKy8vx8GDB2W2B5eWlkIgEMDLywteXl6IjIzEv//+Cy8vL2aH2Iuoq6sD6Lx49hRKZ7F69WrEx8dj//79zIs1IyMDy5Ytw5o1a5jl6EYIIcjPz8eePXtgZWXVrHxVVVUIhUJIpVIAQF5eHuMe3dzcHDdv3kT//v3bLKORwMBAJCcnsxSIgYEBCCFIS0sDANTV1eHPP/9sts9toVsrEA6HA3d3d/j4+MDFxYWxXbxMoyG9R48erBe5k5MTTp48ialTp7Yp4EtFRQU++eQTjBgxgjGcu7m5ITQ0FOXl5RCLxVi/fj3mzJnD2m67f/9+DB48GFOnTmXJ++OPP3Dr1i0mBQUFYdSoUbh16xaGDh2KX375hdkgUFVVhbVr18LGxgb6+voAgKCgIFy5cqXVv4NC6WpMmjQJ58+fl8m/ePEieDwezM3N5bYbN24csrKympV/8OBBfPDBB9i8eTO++uorrFixAoGBgQCAsrIy5ObmNrsxQpEMABg/fjwcHR2xbt061gwmKysLWVlZiIuLw9ChQ5vta3vo1goEaFjGqq6uhoeHR5N1Ro0aBXV1dZkDdzNnzoRIJGrx8lUjZmZmMDExwYABA6Curo5Tp04xZStWrMDw4cNhbGwMPT09PH78GLt372bKxWIxfvrpJ/j5+bXqmQAQHh4OLS0t9OrVCz179kRFRQWOHTvGlG/ZsgWxsbGtlkuhdDX09PTkLt1KpVIIhULWwd5ly5YhPj4eKSkpcHd3h5ubG6vNxo0bkZGRwSRlZWU8efIEhw4dwpdffomtW7fit99+Yzbs5ObmYtasWc1GT1QkQ0tLC+Hh4Vi0aJHM0pREIsGUKVPw8OFDpKen48yZMzI7MjuKbrd2YW5uzgo2b2JiIrPL6MUlJKAhMldhYaGMrL59+yqMFObh4SFXMV29ehWVlZVyd0hwuVzExMRg3759kEgk0NPTY5WrqqrKXY6Sx6effopPP/2UuY+Li8Pz589RUlICIyMjmaWrf//9Fz169JCRk5ub26LnUShdhZKSEtbuxUY4HA4MDQ1RXFzM5AkEAvD5fPj5+eHXX39lLRcBDR9mP//8M3MvkUiwatUq2NvbY8iQIVBSUsKBAwdw9OhRuLq6triPimSEhobiyJEjePDgAXg8HjgcDlRUVMDlclFXV4eSkhL4+PggICAAa9asgUAgwLBhw+S+x9pDt1MgbwI6OjrNbstr79a/plBTU0Pv3r3llrX0jAiF0tURCASwt7fH8ePHWfnTpk1DbW0t6yMyMzMTZ8+exf3793Hjxg3ExMQwMwGg4WzXyx+dbm5u8Pf3Z2YZXl5eKC0thYaGBuN1ojkUyXB2dgaPx2PcFPF4PDg6OsLGxoalpCoqKhAQEIAFCxbAwsICiYmJrRil5un2S1gUCqX7ERwcDFdXVyxevJixH5iammL37t0ICgpiHSZu5N69ewgLC8PevXublZ+fn8/ylTdp0iTk5eWhuroa+vr68PX1BY/HY8obZxCNSUlJSaEMQ0NDaGlpMen06dNYvnw5XF1d0b9/f5aB3tLSEkZGRrhz506bxkoR7VYgqqqqcregUSgUypvKzZs34eTkBB8fH1RWVkIoFCIpKQkRERHYsmVLk+3Wr18PMzMzLFy4UKF8Pz8/ODg4ICcnB5mZmQgJCWGcolpYWGDnzp0YMmQIUz8iIgJ1dXVMmjlzpkIZijAxMWHcMuXn5+P06dNYunTpK1mKbvcSVp8+fTBnzpyO6AuFQqG8Ni5duoTRo0dDS0sL6urqEAqFMjbNiRMnsu4rKirQq1evJssbyc7OxtixY6GtrQ0ul8vy+HDhwgX07NkTRUVFCmUAaFLGy8ydO5e5TkpKgoGBAbMR4EWbb0fTIUtYHb2uRqFQKK+LyspKFBUVKdwQ01ZEIpHcF3+j8miPDEUQQiAUCl+p8gCoEZ1C6XKcOXMGSUlJnd2NN4qKigro6uqitLT0tT/7VSieF2nLGbOOoLa2ttk6VIFQKF2I58+fQ0dHB5aWlp3dlTeKlJQUlJaWvvKXeWfQWb+pJc+lCoRC6UKoqalh7NixTbrd6a5wuVyEh4e/lQqks2h0daQIuo2XQqFQKG2CKhAKhUKhtAmqQCgUCoXSJqgCoVAoFEqboAqEQqFQKG2CKhAKhUKhtAm6jfcNJSwsDJmZmVi1ahXeeecdVll9fT2+/fZb6OjoYMOGDUhMTER2djaWL1/O1MnOzsbOnTuxbt06luuF0NBQjBgxAvb29gAaPIkeOnQId+/eBQBERUUx2/cIIYiPj8cvv/yC4uJizJ07F25ubkhJSUFMTIzcfoeGhkJFRQWJiYk4ffo0SkpK8M4778Db2xuDBw8G0ODdNCwsjNXO0dGRibdSWFiBKzQ4AAAgAElEQVSIPXv24M6dO+jZsyc+//zzZs89ZGRkICIiAjt27KARFimU1wSdgbyhnDt3DtHR0YiIiJApS0xMRHh4OKKjowE0vOi///57SCQSps6JEyewd+9emTgFgYGBzMnWa9euwcLCAlVVVVi0aBEWLlzIOMYkhGDevHkIDg7GxIkT4e3tzURjVFNTg6GhISsVFBQgNjYWHA4Hp06dwpo1azB8+HB88sknEIlEsLKyYgL4pKWlgc/ns9o3RlwUiUQYN24cysvLMW/ePPTu3RsTJ07EH3/80eRYHTp0CA4ODti9ezfq6+vbM+wUCqU1TJ48mSjCycmJJCQkNFlub29PxowZo1AGpfXMmTOHLFy4kPTv359IJBK5ZQMHDiSEECISiQiXyyWpqalMnfHjxxN7e3vi5OTE5KWkpBA1NTVSXV1NJBIJMTExIWFhYXKff/jwYTJ06FBSU1PTov46OTmR77//nrl/uc99+/Yl8fHxhBBCtm7dSjw8PJqUJRKJWPcuLi5k1apVcusmJCQQU1NTkpycTAC0uL9dlcDAQBIXF9fZ3XjjOHr0KOFwOAQATR2UTExMFI75hAkTCJ2BvME0xgJ40e/Rs2fPcOXKFcyaNYvJ09LSgpWVFS5dugSgwftmWloatmzZAj6fzwSwuXTpEqytraGuro7U1FQUFRXB3d1d7rOPHj2KJUuWsGIWNMXdu3fB5/Ph7e3N5HE4//9Pq6CgAMXFxRg0aBDTP0XBq7S0tFj3EomkyX7MnDkTqamprPgHFArl9dAiBfLo0SPcvn1bbqqqqnrVfezSPHjwACNGjIC6unqL06NHjwA0xGd2d3dHVFQUI+/w4cNwdnaWcTMwffp0RoGcP38eY8eOxZgxYzBo0CDw+XwADQqkMX773bt38d5772HTpk3o27cvjI2N4ePjwwTSuXv3LtTV1WFpaQl9fX2MGTMGycnJcn9jSEgI3NzcWCFCi4uLsX37dqxatQpOTk4IDg7G6NGjmbLY2FiYmJhg9OjRWLFiRZPeRnNycnDp0qUmFZ2SkhI0NDRkXFg0jgUAbN68+a25flExUzoGTU1NGBkZvRLZXC633dFFWyKDy+XKxGXicDhyw2Z3KM0tYZmbmxMA5L333pObdHV1iampaQdORt8uzp49SxwcHEhNTU2L0/fff0/mzJlDdu3aRbKzs4mGhgYpLy8nhBAycuRIcvnyZXLq1ClmCYsQQgQCAdHU1CRisZjMnz+f/PDDD4QQQvz9/cmSJUuIWCwmGhoazDLX1q1bCY/HIxEREUQqlZLCwkJibm7OtOPxeGTixImkoKCASKVSEhYWRgwMDJh+NJKfn0/U1NTI7du3WfkFBQXkm2++IZ999hkZNWoUcXd3Z5am8vPzydWrV8n9+/fJ5cuXycSJE4mNjY3M2AmFQjJixAgSGhra7Dj/+++/rCWsF5fQ6urq3prr77//ni5hyaEtS1i2trbkr7/+ImKxmJSWlpKioiLi7+9PlJSUmDp8Pp/U1taS6upq8vDhQxITE0P69esnU/5imjx5MtHW1iaxsbHkwYMHJCsri6SlpZGhQ4fK7Qefzyfu7u4y+S2VYWJiQqqqqoiXlxeT5+npSYqKiohQKCRisZikpqYSVVXVDl/CalaBDB06lCxatKjJcmoDUczZs2fJzJkzW92uUYEQQoi1tTU5ePAgSUlJIYMHDyZSqVRGgdTV1RFtbW0iEAiIvr4+SUtLI4QQcuXKFdKnTx+SnJxMdHV1SX19PSGEkG3btpEpU6awnrl//34mT1NTk1y+fJlV3qtXL5m8VatWEUdHR4W/5fnz58TCwoJlI3mR7OxsAoAUFhYyeeXl5WTs2LFk7dq1CmU38rICeVuhNhD5tFaBmJmZMS/dxherubk5ycnJIWvXrmXqCQQC4uHhQZSUlEjfvn3J8ePHyYULF2TKX5YfEBBAEhISmD5t2rSJxMfHy+1Le2SoqKiQlJQUkp6ezigQY2NjIhaLibW1NQFAuFwusbS0pDaQ7oqHhwciIyMRGRkJDw8PufEBVFRUYGNjg4iICKiqqjLLRRMmTEBNTQ0iIyNha2vLTHOHDRuGx48fs2TU1dVBTU2tReUAUF5ejoMHD2LlypUK+6+qqgozMzP8888/cssbl+Mat99WVFRgxowZmDZtGn744QeFsimUtrB69WrEx8dj//79EIvFABq2gi9btgxr1qxh/Z0DACEE+fn52LNnD6ysrJqVr6qqCqFQCKlUCgDIy8tj/t+am5vj5s2bzdrtFMloJDAwEMnJycjOzmbyDAwMQAhBWloagIb/t3/++WezfW4LVIF0AebPn4/MzEzExMRg0aJFTdabPn064uLi4ODgwPyhKSsr48MPP8TJkycZ+0dj3draWuzcuRMAUFJSgvDwcOZ8iKenJzZs2IDi4mIAYBTTqFGjGBn79+/H4MGDMXXqVFY/kpOT8fTpU+Y+PT0dP//8M2xtbQEAv/zyC2Nrqaqqwtq1a2FjYwN9fX2IRCJ8+OGHMDMzw8qVK5moao39KCsrw+rVqxk7EYXSFiZNmoTz58/L5F+8eBE8Hg/m5uZy240bNw5ZWVnNyj948CA++OADbN68GV999RVWrFiBwMBAAA1/w7m5uSgvL2+zDAAYP348HB0dsW7dOpb9IysrC1lZWYiLi8PQoUOb7Wt7oAqkC6Cjo4OPPvoI48ePx4ABA5qsZ2dnB5FIxBzIa8TJyQkikYilQNTV1XHmzBns27cPvXr1wsCBAzF+/Hj4+PgAALy9vTFz5kwMGTIExsbGCAoKQmxsLHNeQywW46effoKfn59MP27cuIF3330XRkZGMDY2xowZM/DNN9/A09MTABAeHg4tLS306tULPXv2REVFBY4dOwag4YxLSkoKwsPDYWRkxCRjY2MADZsSQkJCkJqa2o4RpXR39PT0mHNJLyKVSiEUCpl44gCwbNkyxMfHIyUlBe7u7nBzc2O12bhxIzIyMpikrKyMJ0+e4NChQ/jyyy+xdetW/Pbbb8jJyQEA5ObmYtasWaioqFDYR0UytLS0EB4ejkWLFjEzqEYkEgmmTJmChw8fIj09HWfOnIGpqWmbxqlZqA3k1dJWG8jr5NmzZ0QsFsstq6mpIUKhsNUy6+vrydOnT0lhYaHMmRBCCKmtrSVPnjxhGYhbypMnT1rd5m2B2kDk01obSG5uLlm4cKFMPofDIXV1dcTKyoqxT+zYsYM4OTmRpKQksn79ehn7RWBgIDE3N2cSALJq1SrC5/OJjo4O6dGjB/nvf/9LTp482SobiCIZ4eHhZPXq1YTH4xEej0f+97//ER8fH8LlclkydHR0yJYtW0hZWRkxNjbucBsI9flAUbiFkcfjtegsyMsoKyszswZ5qKmpoXfv3q2WC6DN7SiURgQCAezt7XH8+HFW/rRp01BbW4uMjAwmLzMzE2fPnsX9+/dx48YNxMTEMDMBoOGYw4v1AcDNzQ3+/v7MLMPLywulpaXQ0NBgzmU1hyIZzs7O4PF4+O677wA0/D91dHSEjY0NXF1dGRkVFRUICAjAggULYGFhgcTExFaMUvPQJSwKhdLtCA4OhqurKxYvXszYD0xNTbF7924EBQUxNroXuXfvHsLCwrB3795m5efn5zMHgYEGm0teXh6qq6uhr68PX19f1ocZh8OBiooKk5SUlBTKMDQ0hJaWFpNOnz6N5cuXw9XVFf3792cZ6C0tLWFkZIQ7d+60aawUQRUIhULpdty8eRNOTk7w8fFBZWUlhEIhkpKSEBERgS1btjTZbv369TAzM8PChQsVyvfz84ODgwNycnKQmZmJkJAQLFiwAABgYWGBnTt3YsiQIUz9iIgI1NXVMWnmzJkKZSjCxMQEmZmZKCkpQX5+Pk6fPo2lS5ciNze3ZYPTCugSFoVC6ZZcunQJo0ePhpaWFtTV1SEUCmU8GkycOJF1X1FRwfJu/XJ5I9nZ2Rg7diy0tbXB5XJZnhYuXLiAnj17oqioSKEMAE3KeJm5c+cy10lJSTAwMGA2AgiFwibbtReqQCgUSremsrISlZWVr0S2SCSSm9+oPNojQxGEkFeqOBrpEAVSVlYm1+04Bfj7779lttlRKG2lvr4eV65cYRlxKcDjx4+hra3d7NkKSsupra1ttk67FcigQYNQX1+PlJSU9op6K8nLy8N7773X2d2gvCWoqKjg2bNnMh6LuztPnz6FSCSS66XhVfPysteroDN+V0ue2W4FoqKiAmdnZ+YAGoXNuXPnsG/fvs7uBuUtwtXVFS4uLp3djTeKmJgYnDp16rW8zDuDzvhdL7tzkQfdhUWhUCiUNkEVCIVCoVDaBFUgFAqFQmkTVIFQKBQKpU1QBUKhUCiUNkEVCIVCoVDaBD2J3o25fPky4uLiMGfOHNjZ2cmU//TTT8jJycHGjRuhr6+PrVu3ykQpBIAZM2Zg9uzZkEqlCA8Px8WLF6GpqYmvvvoK48aNY+qVl5djx44dyMzMxMCBA7F69WqWZ10+n4/o6GjU1NTAxcWF5fenOdlAwyG7H3/8EcOHD8fs2bNZZYQQxMfH45dffkFxcTHmzp0rE9fhRYRCIYKDg/H5559jxIgRzQ8mhdINoTOQbkxGRgaio6OxceNGmTKhUIj169dj7969jDtpXV1dGBoaMonH42Hv3r1MtMANGzYgJCQEjo6OGDp0KKZOnYqbN28yMmfPno2rV69i3rx5KC0txeTJk1FTUwOgIRLc7Nmz8f7778Pe3h5+fn4ICwtj2jYn++nTp5g2bRqCgoJw7do11m8hhGDevHkIDg7GxIkT4e3tjeHDhzc5LqmpqbCyssK+ffvw8OHDNowshdI9oDOQbs60adNw4cIF3L9/nxX+8ujRo3BwcGDFS/Dy8mK1/eqrr2BjYwMPDw88f/4cO3bsQEJCAmxsbAAABQUFCAkJwZEjR5CSkoK0tDQUFhZCU1MTCxYswKhRo3Ds2DEsXrwY27Ztg7+/PxNfXVdXF35+fliyZEmzsgFgzpw5cHFxgYmJicxvPHr0KDIyMnDz5s1mY5sUFhbCxcUFkZGR8Pb2bsOIUijdBzoD6eaoq6vD2dkZUVFRrPzIyEiFLquTkpJw9OhRREREQElJCbdv30ZdXR3Ls6idnR0uX74MAEhJSYG1tTU0NTUBNLhJmD59Oqv8xWU0Ozs75OXl4cGDB83KBhqWv/z9/SGRSGT6evToUSxZsqRFgbGMjY1x79492NnZob6+vtn6FEp3hs5AXjG9evXC48ePMXr06M7uCoutW7cCaLAbfPnll1i8eDE2btwIDoeDP//8EyKRqEk305WVlVi8eDG2bNmCwYMHA2iYERgaGjLBeYCGl3F+fj4IISgoKJCJUGhsbIyMjAxUVVVBJBKxynv06AE1NTU8fvwYlZWVCmUrKSkxvqHkuXy4e/cunJycYGlpiX/++QfvvPMOfvrpJ1awnhdpStaBAwewdOnSTr3uDJ9IbzuamprQ0NBolYfclsLlcqGurt5s/PP2yuByuZBKpawPKA6HAwMDA5SVlaGurq7Nz1cEVSCvGAsLC8TGxrY4jOXr4sSJEzA2NgYhBNOmTQPQ8BVvZ2eHQ4cOYdGiRU2+rPz9/dG/f3+W/7O6ujqoqqqy6qmrq4MQAqlU2mS5RCJh/rgVlSuS/aJikUdRURFiY2Nx9uxZGBsbIyIiAh999BH++ecf6OjoKGz7InPmzOn067fV11NnYGtri//85z8wNTVFVVUV6uvrsW3bNmzbto0ZZz6fjwkTJkAqlaKoqAgCgQCrV69mNpM0lr/IjBkzkJ6ejoiICFhYWKC+vh6VlZWYP38+7t+/L9MPPp+PqKgoZjm2EW1t7RbJMDExQUZGBlauXIn9+/cDADw9PRESEgIlJSXo6OggPT0dkyZN6nDP4FSBvAbefffdzu6CDObm5ggNDQXQ8KXi7u6OqKgoTJo0CSdOnEBaWprcdpcuXcLhw4eRkZHBUjB6enooKytj1S0vL4e2tjaUlZWhp6eHvLw8mXJdXV1oa2tDRUUFZWVlTChOqVSKyspK6OrqQllZWaHs5lBWVsYPP/zABAL64osv8N133yE9PZ2xqbSEFwMJddY1pWMwMzPD2bNnsXLlShw6dAhisRjm5uY4efIkuFwuNm/eDKDBoaCXlxeio6PRp08fbN++HZGRkcxya2P5y0vAAQEBUFdXh4mJCaRSKTZt2oTg4GC5TjDV1NTk/h37+vo2K0NFRQWHDx9GdnY2k2dsbIwDBw5gypQpuHbtGrhcLt5///1XElaC2kAoAAAPDw+cOnUKUVFRMDc3xzvvvCNTp3Hp6ocffmAZ3IGGeNJlZWUsJXHr1i2YmZkBAEaNGoWMjAxWm8ZyZWVljBw5klV+7949AMDw4cObld0cw4YNk9l+XFdX1yJvo5S3k9WrVyM+Ph779+9nXqwZGRlYtmwZ1qxZI/O3QQhBfn4+9uzZAysrq2blq6qqQigUQiqVAmgI69D4wWVubo6bN2+y4pa3VkYjgYGBSE5OZikQAwMDEEKYj8C6ujr8+eefzfa5LVAFQgHQMA0ePXo0Vq5cCU9PT7l1/P390aNHD3zyyScQCoVMEolEMDAwgL29PTZv3oz6+no8e/YMoaGhjCHe3t4eFRUVOHr0KADg+vXrOHfuHObPnw8AcHNzQ2hoKMrLyyEWi7F+/XrMmTMHGhoazcpuDk9PT2zYsIHZbhwREQFVVVWMGjUKABAUFIQrV660a/woXYtJkybh/PnzMvkXL14Ej8eDubm53Hbjxo1DVlZWs/IPHjyIDz74AJs3b8ZXX32FFStWIDAwEEBDAL7c3Nxmg18pkgEA48ePh6OjI9atW8eawWRlZSErKwtxcXEyH3odDV3CojB4enrCz88PH3/8sdzyyMhI1NbWyhjDXVxcEBcXhwMHDuDjjz+Grq4uxGIx3N3d8dVXXwEANDQ0cOLECXz66afw8fFh1psbX+IrVqxAZmYmjI2NoaysjPfffx//+9//mGcokt0c3t7eePDgAYYMGQI1NTVoa2sjNjYWGhoaAIAtW7bgs88+a9VyFqVro6enh2fPnsnkS6VSCIVCJp44ACxbtgyzZs1Cnz59wOPxmI+eRjZu3Ijly5cz9xYWFnjy5AkOHTqEb7/9FqqqqoiKimKiSObm5mLWrFnN9lGRDC0tLYSHh2P+/PkyS1MSiQRTpkzBxo0bkZ6ejqSkJKxduxa3bt1q+QC1EKpAujHLly9n/eF/8cUX+OKLL5h7XV1dltG28dBfU/Tv3x83btzAs2fPoK2tDXV1dVb51KlTkZeXh6KiIhgaGkJF5f//+XG5XMTExGDfvn2QSCTQ09NrlexGXl6LBhpsPDt27EBQUBCqqqpYLwcA+Pfff9GjRw+Zdrm5uQp/L6XrUlJSgp49e8rkczgcGBoaMrNVABAIBODz+fDz88Ovv/7KWi4CgPDwcPz888/MvUQiwapVq2Bvb48hQ4ZASUkJBw4cwNGjR+Hq6triPiqSERoaiiNHjuDBgwfg8XjgcDhQUVEBl8tFXV0dSkpK4OPjg4CAAKxZswYCgQDDhg1DYWFhG0araagCoXQ48v5jNqKsrKzQKNzcrihFspuDx+PJPQtiaGjYZpmUrolAIIC9vT3roCzQcLC2traWZY/LzMzE2bNncf/+fdy4cQMxMTGsmPSPHj2Sse+5ubnB39+f2Xrr5eWF0tJSaGhotHhHpiIZzs7O4PF4+O677wA0/G07OjrCxsaGpaQqKioQEBCABQsWwMLCAomJia0YpeahNhAKhdLtCA4OhqurKxYvXszYD0xNTbF7924EBQXh+fPnMm3u3buHsLAw7N27t1n5+fn5rHNGkyZNQl5eHqqrq6Gvrw9fX1/Wx0zjDKIxKSkpKZRhaGgILS0tJp0+fRrLly+Hq6sr+vfvzzLQW1pawsjICHfu3GnTWCmCKhAKhdLtuHnzJpycnODj44PKykoIhUIkJSUhIiICW7ZsabLd+vXrYWZm1uwGDj8/Pzg4OCAnJweZmZkICQlhnINaWFhg586dGDJkCFM/IiICdXV1TJo5c6ZCGYowMTFBZmYmSkpKkJ+fj9OnT2Pp0qWvZEmWLmFRKJRuyaVLlzB69GhoaWlBXV0dQqFQ5qDmy94YKioqWEuwTXlryM7OxtixY6GtrQ0ul4uSkhKm7MKFC+jZsydz8r0pGQCalPEyc+fOZa6TkpJgYGDA2PqEQmGT7doLVSAUCqVbU1lZicrKylciWyQSyc1vjduUpmQoghDyShVHI1SBUChdCEII7ty5Aw6Hrj6/SHZ2NjQ0NF6ZIuiOtMSZKFUgFEoXQl1dHRcvXnwle/q7MoWFhaipqekUZ5Ovwz9ZZ/yuxhPwiqAKhELpQtTW1sLb21uuT6XuTExMDJKTk99aZ5Od8btedmAqDzoPplAoFEqboAqEQqFQKG2CKhAKhUKhtAmqQCgUCoXSJqgCoVAoFEqboAqEQqFQKG2iy27j9ff3h0Qiwfbt22X2SOfk5OCnn37C+PHj4eTkhHXr1jUpJzg4GNXV1Thw4AAyMzOhqakJW1tbuLu7g8PhICUlBTExMXLbhoaGQiwWw9/fn5VvYmKCb775RqZ+QUEBAgIC4OfnBzMzs2Zlb9iwAaWlpTJlM2bMwOzZs+W2q6+vx48//ojhw4c3WYdCoVA6gi47Azl48CAOHjyIpKQkmbJ9+/YhOjoaFy9eZNyH9+rVCxoaGtizZw80NDSYPCUlJTg5OeHx48dwdnbG5MmTERgYiPXr1wNoiFdsaGjISgUFBYiNjQWHw8HTp08RERHBKpcXW4IQAk9PT8TFxSE/P79FsvX09GTKjx8/jocPH8odk6dPn2LatGkICgrCtWvXOm6wKRQKRQ5ddgYCALNmzUJkZCSmTZvG5NXV1SEmJgZOTk4AAG1tbWYG8vjxY2zbtg1ff/01+vXrx7RJSUlhuYaQSqXYuXMnNm7ciDFjxmDMmDEyz/X29gaHw0FRURF69erFKJym2LVrFzQ1NVlulpuT7efnxyr766+/sGPHDixatEjuM+bMmQMXFxeYmJgo7AuFQqF0BF12BgIACxcuxKlTp5iAKwCQkJCAESNGoE+fPi2W87Jfob///huDBg2SW/fu3bvg8/nw9vYG0ODpsrmARHfu3MGPP/6Iffv2oa6ursl6L8t+meDgYCxevLjJoEt8Pp9Z2qNQKJRXzWtXIOnp6XB1dcXChQvblDZt2sTIGjx4MMzNzREbG8vkHTp0CJ6enq1+iSYkJOCHH37ARx99hOzsbOzatUtuvZCQELi5uTGR8YqLi3H//n289957GD58OBYsWMAK3CIWi/Hpp59i9+7d6Nmzp0KXBC/LfpF///0XZ86ckWtbaURLSwuArNuDF8NtxsfH0+u34JrScWhqasLIyOiVyOZyuc1G2ewIGVwulwmM1QiHw4GRkRG4XG67nq+I176EtWXLFvTu3RvW1tZtat+zZ09s2LABQMOL0sPDA5GRkfjiiy9QUFCAq1ev4sSJE0hPT2+V3OLiYjx58gS1tbUoLCzE33//jQEDBrDqPHnyBMePH8dff/3F5M2bN4+JACYSibBv3z5MmTIFt2/fhpGREb777jtYWVkxS2pNIU/2i2zfvh3Ozs4YOHBgq34XANaS1rBhw+h1F77++++/QekYbG1t8Z///AempqaoqqpCfX09tm3bhm3btjEfYXw+HxMmTIBUKkVRUREEAgFWr16Nx48fs8pfZMaMGUhPT0dERAQsLCxQX1+PyspKzJ8/H/fv35fpB5/PR1RUFI4cOcLK19bWbpEMExMTZGRkYOXKldi/fz8AwNPTEyEhIVBSUoKOjg7S09MxadIkiMXiDhs/AMDkyZOJIoYOHUoWLVrUZLmPjw/ZtWuXQhkvsmDBAnL8+PEW12+KHj16kJs3b5Ly8nKioaFBsrKySFBQEPH09CSEEPLNN9/I9DsvL48AIHl5eQplx8fHE01NTVJZWcnKX7VqFXF0dFTYViqVkn79+pETJ04QgUBA9PX1ya+//kqSk5NJcnIy6du3L9m+fTu5e/dui2UXFRURdXV18scffyh8diOLFi0iq1evblFdStciMDCQxMXFdXY33jiOHj1KOBwOAdCiZGZmRqqqqoiXlxdRVVUlAIi5uTnJyckha9euZeoJBALi4eFBlJSUSN++fcnx48fJhQsXZMpflh8QEEASEhKYPm3atInEx8fL7Ut7ZKioqJCUlBSSnp5OvLy8CABibGxMxGIxsba2JgAIl8sllpaWLR6bxmRiYqJwzCdMmEC6tA0EAHR0dODs7IyoqChERUXB09Oz3TItLCxQVVWFwsJCJq+8vBwHDx7EypUrFbZVUlKCmpoaVFRUkJOTg969e8PPzw9eXl7w8vJCUVERdu3ahYMHD7ZY9q5du2BpaYmxY8e2+7dRKBRg9erViI+Px/79+5mv8oyMDCxbtgxr1qyBmpoaqz4hBPn5+dizZw+srKyala+qqgqhUMi4RM/Ly2OOG5ibm+PmzZusDTWtldFIYGAgkpOTkZ2dzeQZGBiAEIK0tDQADRuL/vzzz2b73Ba69C6sRjw8PODs7Iw+ffqwgtC3hPLycty4cQNTp04Fh8PB8+fPERwcjEGDBrGWi/bv34/Bgwdj6tSprPZXr17F8OHDYWBgAKlUin379qG8vByTJ0+GoaEhPDw8WPWHDh2K3bt348MPP2xWNgBUV1djz549iIiIkCmLj49HSUkJlixZ0qrfTKF0dyZNmoQ1a9bI5F+8eBE8Hg/m5uZITU2VKR83bhyysrKald94xGDz5s14/Pgxvv76a7i6ugIAysrKkJubi/Ly8jbLAIDx48fD0dER1tbWOHbsGJOflZWFrKwsxMXFYcWKFXKXzTqKt0KBTJs2DQYGBk1ub1VEXV0d/Pz8kJ2dDSMjIxQXF8PCwgIJCQmMUUosFrtXZ8MAACAASURBVOOnn35CcHCwTPvr16/Dzs4OmpqaqK2txbvvvouEhIRmd2Y1okg2AEREREBPTw+zZs2SKYuKisI///xDFQiF0kr09PTw7NkzmXypVAqhUMjEEweAZcuWYdasWejTpw94PB7mz5/ParNx40YsX76cubewsMCTJ09w6NAhfPvtt1BVVUVUVBRycnIAALm5uXL/P7+MIhlaWloIDw/H/PnzZewaEokEU6ZMwcaNG5Geno6kpCSsXbv2lQQh67IKpKysjLnmcDh49OgRqzw0NFSmTb9+/WR2KBkaGuLvv/9GZWUlysvLoaenBw0NDVYdVVVVPHnyRG4/Vq5cieXLl0MoFEJHRwfq6uoK+/3y14Ai2QDg6+sLX19fuWUnTpyQuy04KipKYR8olO5OSUmJ3N2OHA4HhoaGKC4uZvIEAgH4fD78/Pzw66+/spaLACA8PJy101EikWDVqlWwt7fHkCFDoKSkhAMHDuDo0aOsGURzKJIRGhqKI0eO4MGDB+DxeOBwOFBRUQGXy0VdXR1KSkrg4+ODgIAArFmzBgKBAMOGDWMty3cEXVaBdDRaWlrMNtjWoqysDGNj4w7uUfO8rOgoFErLEAgEsLe3x/Hjx1n506ZNQ21tLTIyMpi8zMxMnD17Fvfv38eNGzcQExPDzAQA4NGjR6z6AODm5gZ/f3/mjJqXlxdKS0uhoaGB6urqFvVRkQxnZ2fweDx89913AAAejwdHR0fY2NiwlFRFRQUCAgKwYMECWFhYIDExsRWj1Dxd3ohOoVAorSU4OBiurq5YvHgxs1RtamqK3bt3IygoCM+fP5dpc+/ePYSFhWHv3r3Nys/Pz2fZYydNmoS8vDxUV1dDX18fvr6+4PF4THnjDKIxKSkpKZRhaGjIfPRqaWnh9OnTWL58OVxdXZljBY1YWlrCyMiIdT6to6AKhEKhdDtu3rwJJycn+Pj4oLKyEkKhEElJSYiIiMCWLVuabLd+/XqYmZlh4cKFCuX7+fnBwcEBOTk5yMzMREhICBYsWACgwUayc+dODBkyhKkfERGBuro6Js2cOVOhDEWYmJggMzMTJSUlyM/Px+nTp7F06VLk5ua2bHBaAV3ColAo3ZJLly5h9OjR0NLSgrq6OoRCoYyNdOLEiaz7iooK9OrVq8nyRrKzszF27Fhoa2uDy+WipKSEKbtw4QJ69uyJoqIihTIANCnjZebOnctcJyUlwcDAgNkIIBQKm2zXXqgCoVAo3ZrKykpUVla+EtkikUhufqPyaI8MRRBCXqniaIQqEAqlC6GkpITy8nLGlQalAZFIBC6XK9d2QWkbL8/G5NGsAhGLxR3vP4VCobQJTU1N7Nixg/F5RGmgsrKSeqHuYFry3m9WgZSWlrIculEolM6jsrIS69evh4uLS2d35Y0iJiYGn332WWd3463iZXcu8mjRLqyLFy+2uzMUCoVCebug23gpFAqF0iaoAqFQKBRKm6AKhEKhUChtot3beAcNGoTdu3cjJiamRfWfPHmCOXPmtPexFAqFQulk2q1Avv7661aFp92wYUOL/OlTKBQK5c2m3QpERUUF48ePb3F9XV1dDBs2DGFhYcjMzMSqVavwzjvvsOrU19fj22+/hY6ODjZs2IBjx47h2rVrcuW96H3yjz/+wLFjx5CXl4dhw4YxPm3EYjHCwsKQnJwMdXV1ODo6Mm1SUlKanD2FhoZCKpUiOjoaV65cQX19Pd5//334+PhAW1ubqcfn8xEdHY2amhq4uLiw/NXExcXh8uXLLLnffPMNK075y2RkZCAiIgI7duyAigo960mhUN5MOs0Gcu7cOURHR8uNtJeYmIjw8HBER0cDAHr06IFevXqhV69euH79Oq5fv87c6+joAAB27tyJjz76CAMHDsTSpUtha2vLyPv444+RlJQEBwcHWFtbw9fXFzt27ADQsNfZ0NCQlQoKChAbGwsOh4Nvv/0WZ86cwaRJkzB37lz88ssvmDlzJiP74sWLmD17Nt5//33Y29vDz88PYWFhTPnPP/+MBw8esORzudwmx+XQoUNwcHDA7t27UV9f375BplAolFfJ5MmTFQZO19bWJhMnTuyQwPeEELJgwQJy/PhxMmfOHLJw4ULSv39/IpFIWHUaywYOHCjTfvHixWTx4sWsvH/++YeoqamRe/fuyX2mSCRi3e/atYtYWlo22UcnJyfy/fffE0KITN9ycnIIAFJcXEwIIWTGjBlk/fr1TPnJkydJ//79mfsPP/yQREVFNfmsF0lISCCmpqYkOTmZACA1NTUtakfpPgQGBpK4uLjO7sYbx9GjRwmHwyEAaOqgZGJionDMJ0yYQDp1F1ajr/ukpCQm79mzZ7hy5UqLQj428t///hdTp05t8sT8y4GiJBIJyxf/i9y9exd8Ph/e3t4AGvz0v8jff/8NAwMDZuaTkpICOzs7ptzOzg55eXl48OABgAZPmC0Nbztz5kykpqayfPlTKBTKm8prVyCEEMbhmVQqhbu7OysE6+HDh+Hs7NxsaNgXuXv3LkxMTPDxxx/DyMgI77zzTpO+gp4/f46DBw82GUc8JCQEbm5urHCXGRkZCA4OxpIlS7B161acPHkSKioqqKqqgkgkYkUj7NGjB9TU1Bhnd8XFxfj2228xZMgQWFtbIzQ0tEmfPUpKStDQ0JBxYvZiCM0rV67Q625+TelYNDU1YWRk9Epkc7lc5mPzVcrgcrlMYKxGOBwOjIyMFC6Z/z/27jyuxvT/H/irc9pLaT2RtWSbIjK2IhRDC4WGrGEkydiy78sIMyMKg0qEQY1toj4zKlEkhkqIbC3adFpOe53q+v7Rr/vndk4rIa7n43E/Hve5rut+n+vcLde5r+u+r+tDffIGJC4ujvmHSAiBg4MDLl68yCzb6OvrCwcHhybFzM7Oxvnz57FmzRpkZ2fjwoULWLVqFSIjI1nlqqurMXv2bHTv3l3svDnp6ek4c+YMli1bxkovKipCWloaBAIBiouLmQH92vXIpaWlWeXl5OSYRuLy5cs4ffo0/vnnH6xYsQK//fYbtm/f3qTP926DQvfpPvVxjBw5Eg8ePEBeXh4SExORnZ2NVatWQUJCgikTGhqKsrIylJSUIDk5GadPn0aHDh1E8t/dhg8fjjZt2sDf3x9Pnz7FvXv3cP/+fXTr1k1sPUJDQzFz5kyR9MbG0NPTQ35+PutL8Zw5c5CVlYWEhAQUFxcjOjpa5P/UR/Gpx0B69epFpk6dSiZMmEA8PT0JIYQMHTqUHD16lERFRREdHR1SXV1NLl682OgxEEtLS9Y4BCE1Yy3vplVXV5MFCxYQMzOzOscWXF1diYWFRb31f/PmDZGTkyPXr18nlZWVRFJSkjx8+JDJr6qqIpKSkuT+/ftijz969Cjp1atXve/x+vVrAtAxEEoUHQMRr6ljIAYGBqS4uJg4OTkRaWlpAoAYGhqS58+fk/Xr1zPlIiMjiYODA5GQkCDa2trkzJkz5Nq1ayL578dft24dCQwMZOq0fft2cv78ebF1+ZAYkpKSJCoqisTExBAnJycCgPB4PFJRUUGGDh1KABApKSkyYMCAr28MpJaDgwN8fX2Zq493vwE0Ro8ePUTWRxAKhazZJF1cXPD8+XP8/fffYsc/BAIBjh49ihUrVtT7Xtra2uDxeHj16hW4XC569+6N2NhYJv/p06cAgJ49e4o9Xk5Ojt6aS1Gf2erVq3H+/HkcPnyYmbY8NjYWixYtwpo1a0RmoiWEIC0tDQcPHsSgQYMajC8tLQ0+n4/q6moAQGpqKvN/zdDQEPHx8Q2OddYXo9amTZsQERHB6uZWU1MDIQT3798HUPO/8L///muwzs3xRTQgU6ZMQVxcHE6fPo3Zs2c3+fhZs2bhzJkzuHv3LoCa9Y7/+ecfZnDbxcUF0dHR8PX1RUlJCfh8Pvh8Pus22cOHD0NHRwejRo1ixb569SpKSkqY135+fqzF7qdPn459+/ZBIBCgoqICW7ZswYQJEyAvLw+BQIAbN24w3Q+pqan4/fffMXHiRAA13XkbNmxgusIoivo0hg0bhuDgYJH0kJAQyMrKwtDQUOxxAwcObNSD0EePHsWQIUPwyy+/YOHChVi2bBk2bdoEAMjPz0dSUhIEAkGzYwDA4MGDYWFhgQ0bNrDGP549e4Znz57hr7/+qrPb7GP5Ir4KKykpwdbWFpmZmejUqVOTj+/bty8OHToEa2trcLlclJWV4ddff4WRkRGysrJw8OBBAEDnzp1Zx0VERMDExAQVFRXYv38/du/eLRLbz88PEydOhLq6OoqKiqCpqQl/f3/mQcBly5YhLi4OPB4PXC4Xffv2xYULFwDUtPwLFy7Eq1ev0LZtW5SUlGDBggVYv349gJpfVjc3N7i4uLDWWaYoqmWpqKjg7du3IunV1dXg8/nMeuIAsGjRIlhbW6N9+/aQlZXFlClTWMds27YNS5cuZV4bGRkhPT0dx44dw8qVKyEtLY3jx4/j+fPnAICkpKRG3WVaXwxFRUV4e3tjypQpIgs/VVVVYcSIEdi2bRtiYmIQFhaG9evX49GjR40/QY31ucZAWkJlZSXJzMwk1dXVHzVuWVkZSUtLI7m5uXWWEQgEdeYXFBSIrVdVVRXJzMz8qHWlvm50DES8po6BJCUlEXt7e5F0DodDhEIhGTRoEDM+4e7uTqysrEhYWBjZsmWLyPjFpk2biKGhIbMBIK6uriQ0NJQoKSkRZWVlcvbsWRIQENCkMZD6Ynh7e5PVq1cTWVlZIisrSy5cuEBcXFyIlJQUK4aSkhLZuXMnyc/PJzwe76OPgXwRVyAfC5fLZd1S+7HIyMigffv29Zap7za7Nm3asKY+qcXhcFqkvhRF1S8yMhI//PADzpw5w0o3MzNDWVkZa1wzLi4OV65cwYsXL3Dv3j2cPn2auRIAgJSUFFZ5oKZre9WqVczdpU5OTsjLy4O8vDyrS7w+9cWwsbGBrKwsNm7cCACQlZWFhYUFa2onACgoKMC6deswdepUGBkZISgoqAlnqWFfxBgIRVHUp7R7927Y2dlh3rx5zPiBvr4+Dhw4ADc3N+ZZtXc9ffoUXl5eOHToUIPx3x0nBWrGXFJTU1FSUgJVVVUsXryYdTMPh8OBpKQks0lISNQbQ11dHYqKisx26dIlLF26FHZ2dujYsSNrgH7AgAHQ0NDAkydPmnWu6kMbEIqivjnx8fGwsrKCi4sLioqKwOfzERYWBh8fH2YSVnG2bNkCAwMD2Nvb1xt/+fLlGDduHJ4/f464uDjs2bOHmWTVyMgIHh4e0NXVZcr7+PhAKBQym6WlZb0x6qOnp4e4uDjk5uYiLS0Nly5dwoIFC5CUlNS4k9MEX1UXFkVRVGNdv34d/fr1g6KiIuTk5MDn80Ue2DQxMWG9LigoYN3w8n5+rcTERHz//fdo06YNpKSkkJuby+Rdu3YNmpqayM7OrjcGgDpjvG/y5MnMflhYGNTU1JgbAfh8fp3HfSjagFAU9U0rKipCUVFRi8QuLCwUm17beHxIjPoQQlq04ahFu7AoiqKoZvnkVyDt2rVrsYnLKOprp6ysjG3btol9ZulbVlpaCklJSZFnIqjmE3cjwfs+eQPy/fffN2mmXYqi/j+BQIAVK1Zg/Pjxn7sqX5SAgAA4OTl97mp8VRoz+eInb0AkJCRE5pmhKKrxFBQU0LZt289djS+KvLz8567CV6cxcxLSMRCKoiiqWWgDQlEURTULbUAoiqKoZqENCEVRFNUstAGhKIqimoU2IBRFUVSzfLapTLy8vBAXFwdXV1d06dKFlVdZWYmVK1dCSUkJW7duxZ9//onbt2+LjfPu9MV3797Fn3/+idTUVPTo0YOZFC07OxtHjhxBXFwcFBQUMHLkSMycORMcTk37GR8fj+PHjyMpKQkaGhqYNm0ahg8fzrzH8+fPsX//fqSlpWHQoEFYtmwZcytyfbGjoqJw+vRpsfXet29fnUvbxsbGwsfHB+7u7nT5W4qivlif7Qrk6tWrOHHiBHx8fETygoKC4O3tjRMnTgCoefpWS0sLWlpauHPnDu7cucO8rl2Hw8PDA7a2tujcuTMWLFiAkSNHAqiZE8bKygpv3ryBjY0Nhg8fjk2bNmHLli0Aalb9srKygoKCAuzt7aGjo4MffvgBoaGhAICsrCwYGxuDEAI7Ozv8/fffmDt3bqNiy8jIQF1dnbVlZGTA39+fabzed+zYMYwbNw4HDhxgLblLURT1xfnUKxKuWbOGuLm5kQkTJhB7e3vSsWNHUlVVxSpTm9e5c2eR4+fNm0fmzZvHSnv16hWRkZEhT58+Ffue78f38vIiBgYGdeZPnz6dLF68mBBCyM6dO4mpqSmTl5mZSbhcLnn+/HmjYr/PysqKbN68WWxeYGAg0dfXJxEREQQAKS0trTMO9W2iKxKK19QVCen2cVYk/ORXIIQQ5pt17WIpYWFhTP7bt29x48aNRq0ZXOvs2bMYNWoUevToITb//W/7Dx8+RNeuXcXmV1VV4cmTJ0x+VFQUxowZw+TzeDwYGBjgxo0bjYr9roSEBISGhsLZ2VlsvqWlJaKjo1mLwQBARkYGKwbd/7b3qY9LQUGhxebnk5KSqne10o8VQ0pKilkYqxaHw4GGhgakpKQ+6P3r88kbEBcXFxQXFwOoWcB+5syZOH78OJPv5+cHGxubJs2XlZCQAD09PUycOBEaGhro0qULDh8+zCoTGBiIHTt2wNbWFomJifD09GTlHzp0CJs2bcLIkSMxcOBA5p98RkaGyLKzPB4Pb968aXTsWnv27MH06dOhqakpNl9CQgLy8vIiaxKkpaUx+/Hx8XT/G9+nPo6RI0fiwYMHyMvLQ2JiIrKzs7Fq1SrWFB6hoaEoKytDSUkJkpOTcfr0aXTo0EEk/91t+PDhaNOmDfz9/fH06VPcu3cP9+/fR7du3cTWIzQ0FDNnzhRJb2wMPT095OfnY/78+UzanDlzkJWVhYSEBBQXFyM6OrpRc1s12afuwqo1YcIE4unpSRITE4m8vDwRCASEEEJ69+5NwsPDycWLFxvdhTV27Fiira1NoqOjCSGE3L9/n7Rp04ZEREQwZXx9fcnChQvJ2LFjiaGhIQkMDGTFWL9+Pfnpp5+IsbExGTlyJNMd1rdvX+Ln58cqa2NjQzZu3Njo2IQQkpaWRmRkZMjjx48bPDevX7+mXViUWLQLS7ymdmEZGBiQ4uJi4uTkRKSlpQkAYmhoSJ4/f07Wr1/PlIuMjCQODg5EQkKCaGtrkzNnzpBr166J5L8ff926dSQwMJCp0/bt28n58+fF1uVDYkhKSpKoqCgSExNDnJycCADC4/FIRUUFGTp0KAFApKSkyIABA76OLqz36enpwdDQEOfOncOdO3eYFrwpuFwu5s+fj4EDBwIA+vfvD0tLS2YgHAAcHBxw6NAhBAcHY+PGjZg6dSpzJQQAO3bsgJeXFyIjI6Gvr48FCxYAAFRUVJCfn896P4FAwJrMrqHYAODu7g4zMzP07t27SZ+NoqiPb/Xq1Th//jwOHz7MTAEfGxuLRYsWYc2aNSITvhJCkJaWhoMHD2LQoEENxpeWlgafz0d1dTUAIDU1lbmyMTQ0RHx8vEhXdVNi1Nq0aRMiIiKQmJjIpKmpqYEQgvv37wMAhEIh/vvvvwbr3ByfvQEBav4B+/r6wtfXFw4ODo2aBfJdPXr0YHUpATUnra5Zf42MjFBcXIysrKw681+9egUA6NOnD2JjY5k8QggeP34MAwODRscWCAQ4evQoVqxY0aTPRVFUyxg2bBiCg4NF0kNCQiArKwtDQ0Oxxw0cOBDPnj1rMP7Ro0cxZMgQ/PLLL1i4cCGWLVuGTZs2AQDy8/ORlJQEgUDQ7BgAMHjwYFhYWGDDhg2s8Y9nz57h2bNn+Ouvv+rsNvtYvogGZMqUKYiLi8Pp06cxe/bsJh8/a9YsnDlzBnfv3gVQ01/8zz//YPTo0RAIBAgJCWFa8fLycuzevRtdu3ZF586dkZCQgEePHjGxsrKycPjwYeY24GnTpuHChQt49OgRCCHw8PAAl8uFqalpg7FrHT58GDo6Ohg1ahSr3nFxcdiwYQOEQmGTPzNFUc2noqKCt2/fiqRXV1eDz+cz64kDwKJFi3D+/HlERUVh5syZmD59OuuYbdu2ITY2ltm4XC7S09Nx7NgxODo6YteuXfj333/x/PlzAEBSUhKsra1RUFBQbx3ri6GoqAhvb2/Mnj1bZBGtqqoqjBgxAsnJyYiJicHly5ehr6/frPPUkC+iAVFSUoKtrS0GDx6MTp06Nfn4vn374tChQ7C2tkb79u1hamqKX3/9FUZGRhAKhVi+fDnk5eXRsWNHqKioID4+HoGBgeByucjKysIPP/wAJSUldOjQAbq6utDR0YGHhwcAYNCgQdi4cSMGDRqEtm3bYu/evfD394e0tHSDsQGgoqIC+/fvx/Lly0XqHRISAjc3N+Tk5HzYCaQoqklyc3PF3szC4XCgrq7O+puMjIyEr68vSktLcfnyZVZ3EQB4e3vDwcGB2aqqquDq6ooffvgBurq66NSpE3g8Hk6dOtWkOtYXY9++fTh58iRevnwJWVlZcDgcSEpKMndc5ebmwsXFBdra2nj8+DEiIyNFbgb6KD7XIHpLqKysJJmZmaS6ulokr7CwkLx584YUFxeL5FVXV5OcnBySlpZGKioqxMYuLS0lWVlZTY5dn6qqKpKZmdmkY6hvGx1EF6+pg+inTp0ix48fF0kfPXo0KSwsJDIyMiID3D179iSFhYVET0+vwQHwmJgYMnr0aOZ127ZtCSGEyMvLN3oQvb4YfD6fFBUVMVtlZSUpKysjAQEBYj/vq1eviIWFxdc3iP4xcblc8Hg8sWMoioqK0NbWFrtymYSEBFRVVdG+ffs675mWlZWFpqZmk2PXh8PhtMy3Aoqi6rV7927Y2dlh3rx5TG+Bvr4+Dhw4ADc3N7HrgT99+hReXl44dOhQg/HT0tKY59yAmjGX1NRUlJSUQFVVFYsXL4asrCyTX3sFUbtJSEjUG0NdXR2KiorMdunSJSxduhR2dnbo2LEja4B+wIAB0NDQwJMnT5p1rurzVTUgFEVRjREfHw8rKyu4uLigqKgIfD4fYWFh8PHxYebQE2fLli0wMDCAvb19vfGXL1+OcePG4fnz54iLi8OePXswdepUADU32nh4eEBXV5cp7+PjA6FQyGyWlpb1xqiPnp4e4uLikJubi7S0NFy6dAkLFixAUlJS405OE9CZ+iiK+iZdv34d/fr1g6KiIuTk5MDn80Ue4jUxMWG9LigogJaWVp35tRITE/H999+jTZs2kJKSQm5uLpN37do1aGpqIjs7u94YAOqM8b7Jkycz+2FhYVBTU2NuBODz+XUe96FoA0JR1DetqKgIRUVFLRK7sLBQbHpt4/EhMepDCGnRhqMW7cKiKIqimoVegVBUK6KkpARvb2+cPHnyc1fliyIUCmFsbNykOfQ+lve7vVpCUx+u/lBVVVVQUVFpsBxtQCiqFcnLy8OIESNEHkr91v3333/YuHGj2KfLqab777//EBMT02A52oBQVCvC5XLRrVs3fP/995+7Kl+UoqIiSElJ0fPykRQWFjbqtl86BkJRFEU1C21AKIqiqGahDQhFURTVLLQBoSiKopqFNiAURVFUs9AGhKIoimqWVtOArFq1CitWrBD70M7z58/h4uKCU6dOobq6GkuWLBGZs3/fvn04duwYKy0xMRHLli0TiZmRkYE5c+YgPj6elV5UVIQDBw5g5syZmDhxInOftJ+fH1xcXES233//XaSuTY0NAHfu3MGCBQtgZ2eHzZs3i10I530BAQFi35+iKOpjaTUNyNGjR3H06FGEhYWJ5P3xxx84ceIEQkJCwOFwcPv2bVy+fJnJLy8vx8aNG7Fx40ZWY3Hp0iVER0eznvIkhGDOnDn466+/kJaWxqTz+XwMGDAAN2/ehI2NDRwdHZnJyhQVFaGurs7aoqKicPv2bVY9mxP73r17GDNmDPr06QNHR0ekpKTAxMSkzlUMKyoqsHjxYjg6OiIgIKApp5iiKKpJWtWDhNbW1vD19YWZmRmTJhQKcfr0aVhZWTFp5ubmuH79OlauXAkACA8PR7du3ZCRkYEHDx7AyMgIQM2slebm5qz38PT0hIKCgsiC96tXr8aAAQPErio2ceJETJw4kXldVlaGP/74Q+QKoDmx//33X4wYMQKLFi0CAIwcORIyMjJ48eIFevXqJVJ+3bp1yMrKwp49e+Dj4yOST1EU9bE0qgEpKSnB48ePW7ouYsnLy6Nr164AAHt7e0ydOhUFBQVQUlICAAQGBqJXr15o3749swylubk5Dhw4gMrKSkhKSuLq1asYNWoU+Hw+AgMDmaVuIyMjsW7dOua9njx5gr179+Lu3bswNjZm0oVCIfz9/REaGtqoOvv6+kJbWxsjRoz44NgGBgY4cOAAMjMzoaWlhX///Rfq6uqstQTetXXrVigoKODEiROs9NzcXKiqqgKomQlUQ0OD7rfCfYr6kjTYhSUrK4tXr15hypQpn2XbsGEDtm7dCgDQ0dGBoaEh/P39mfodO3YMc+bMQVVVFZNmYmKCqqoq/PfffwCAoKAgjB07FlZWVggMDARQ0zUEAEOGDAFQ0/UzY8YMHDhwAJqamqyurtTUVJSWluL58+fQ09ODqqoqLC0tkZqaKnK+qqursXfvXqxYsYJJ+5DY48ePx88//4y+ffti0qRJWLVqFa5duwZpaWmxPy8FBQUAohO8BQUFMfvvdm3R/da1/6kn1aOoejW0Jrq2tjZZvnz5B6xW/HEoKyuT+Ph4cvToUTJ06FBCCCHp6emkbdu2pKioiCxZsoTMnj2bKW9ubk527txJEhISiIKCAikrKyMCgYBIS0uTN2/ekB07dpBx48Yx5VetWkWcnJyY17q6uiQ4OJgQQsidO3cIKpyKOgAAIABJREFUh8Mhzs7OpLS0lJSXlxMHBwdibm4uUk9/f3/SoUMH1trqHxK7oqKCLFiwgBgaGpLp06cTHo9Hzp071+D58vX1JYMGDWrMqaVaEbomunhhYWFES0vrc1fjqxEaGkpcXFzqLWNsbExa1RgIAEyZMgVLly5FYmIiLly4AFtbW+Zb97vMzc0RFhYGeXl5jBo1CjIyMpCRkYGxsTGCgoIQHh6OcePGAQBu3boFb29vnDlzBpGRkQBqxjEeP36MLl26gMvlgsvlYv/+/ZCUrDlla9asgYGBAdNNVuvXX3/Fzz//zKyt/qGx165di5SUFNy9exdSUlKIiYmBmZkZeDweTE1NW+5EUxRFNaDVNSBKSkqwsbHB8ePHceHCBXh5eYktZ25uDjc3NygoKMDCwoJJt7KyQmhoKKKiophB7ufPn6Ndu3ZYvnw5Uy47Oxuenp5IS0vDpk2bUF1djaysLGhrawOoGbuQlJQEl8tljrl+/ToSEhLg6OjIpH1o7Bs3bsDFxYVpkPr164dhw4bh5s2btAGhKOqzajW38b7LwcEB+/fvR1VVFYYNGya2TL9+/SApKYmQkBCRBiQoKAgKCgowMDBg4j169Ii1dezYEYcPH8bevXvRtm1b2NjYYPny5RAKhaisrMTevXsxevRoVp/0nj178NNPP0FZWZlV1w+J3adPH/z999+oqKgAAKSkpODOnTsYMGAAAOD8+fN1NqIURVEtqVU2IGZmZlBTU8Ps2bPrLMPhcDBq1Ch06tQJnTp1YtK7d+8OLS0tmJmZNWlA8siRIygoKICmpibU1dWRlJSEQ4cOMfnx8fEICQnBkiVLmvx56ou9e/dulJeXo0OHDvjuu+8wYMAALF26lOl+O378OPbt29fk96QoivpQraYLKz8/n9nncDhISUlh5Yv7J/ru3Vrvev8pdXFevHjBeq2mpobg4GAIBAJwuVwoKiqy8g0MDOp8uO9DYqurq+PKlSuoqKhAXl4eNDU1WQ3fuXPnxL6vg4MDHBwcGlUfiqKo5mg1DciX4t3uqU8ZW1paGjweTyRdXl6+xepDURRVn1bZhUVRFEV9frQBoSiKopqFNiAURVFUs9AGhKIoimoWOohOUa1ITk4OnJycWA+mfiyEEFRXV3/0uO+SkJAAh/Pxv7dWVFSgS5cumD9//keP/S0qLS1Fu3btGixHGxCKakWioqLA5/M/dzW+OCoqKkhISMCyZcs+d1W+Co8ePUJGRkaD5WgDQlGtSF2zMH/r5OTkUFlZiR9//PFzV+WroK6ujosXLzZYjo6BUBRFUc1CGxCKoiiqWWgDQlEURTULbUAoiqKoZqENCEVRFNUstAGhKIqimoXexitGWloa3NzcRNLXr1+PZ8+e4a+//gJQMxNup06dYGdnx5opNy0tDR4eHnj58iV69+6NJUuWQE1NjckPCAjA5cuXweFwMG3aNIwdO5bJq66uhre3N0JCQqCgoICFCxdi4MCBjY5NCMH58+fxv//9Dzk5OZg8eTKmT58OAMjKysLBgwfx5MkTaGpqYu7cuczCVHWJjY2Fj48P3N3dWUv3UhRF0SsQMbKzs3Hw4EFoampCS0uL2SQlJREbG4srV66gQ4cOkJOTQ3BwMHR1dfHo0SMAQG5uLgYNGoT8/HxMmzYNKSkpMDY2RklJCYCaVQtdXV0xatQojBgxAnPnzoWPjw/z3lu3bsWePXtgYWGBbt26YdSoUYiPj29UbEIIfvzxR+zevRsmJiZwdnZGz549AQCFhYUYOHAgBAIBfvzxR7Rr1w4mJia4e/dunefh2LFjGDduHA4cOIDKysoWOdcURbViw4cPJ/XR1tYmy5cvr7fM1yYmJoYAIEKhUCTP3d2dGBsbs9LGjh1LFi9eTAgh5ODBg2TgwIFMXlVVFRk4cCA5ePAgIYQQDQ0NEhQUxOQHBgYSHo9HqqurSVlZGWnTpg0JDw9n8hctWkRmzJjRqNh+fn6kW7dupLS0VOznKiwsZL2eNGkScXV1FVs2MDCQ6Ovrk4iICAKgzpjUpzV48GACgG7vbe3btyeampqf+8fz1QgNDSUuLi71ljE2Niaf5Aqkqqqq1WyEkCZ/vg4dOiAnJwdAzZrlvXr1YvI4HA7GjBmDW7duoaysDNnZ2az8MWPGgM/n48WLF3j8+DGEQiFMTEyY/NGjRyM8PLzB2ABw6tQpzJ8/H7KysmLr+f4qilVVVXWWtbS0RHR0NDp27CiS9+45ovuffp+ivhQt3oCsXr0aMjIyrWbbvn07jhw5AgBITk5GUlISkpKSkJqaKvLZhEIhwsPDceHCBdjb2wMAdHR0EBsby/zBV1ZW4u7du8jLy4OsrCzatWuHmJgYJsadO3dQVVWFvLw8ZGRkQF1dHVwul8nn8XhIS0sDIaTe2ACQkJAAOTk5DBgwAKqqqujfvz8iIiLE/lyeP3+O69evY+bMmWLzJSQkIC8vL/Yf1/bt2+n+Z9xvKmlpaWhoaHzUSQzbtGnDGntrCikpKdbv+Lvk5OSgqqrKWraZ+oK1dBfWiBEjyPXr15t9/OdQ24WlrKzMbN27dyeE1HRhASBcLpdISEgQRUVFcunSJebY4uJioq+vT0xNTcnq1avJyJEjyfDhw8n06dMJIYT4+voSVVVV4uLiQpycnIitrS3hcDjk+fPn5OLFi0RHR4dVl9jYWAKAVFZWNhhbVlaWmJiYkIyMDFJdXU28vLyImpoaEQgErJh8Pp/06tWL7Nu3r8Fz8fr1a9qF9QVpShcWh8MhHh4epLCwkPD5fFJWVkYOHjwotmxoaCgpLi4mRUVFJDs7m4SHh5MpU6aIlLO0tCQJCQnk5cuX5MmTJ6Rnz55MHpfLJbt27SKFhYV11klPT48UFxcTJycnVvq8efNIQkICqaioIPn5+aS4uJjs3r2bdmF9Jl9UF1ZrxefzkZ+fj/z8fDx79oxJHzJkCPLz8/Hy5Uvmm3oteXl5/Pfff1i+fDm6d+8Ob29v6OnpoUOHDgAABwcH3Lp1C0ZGRrC0tMTevXsBAO3bt4eKigry8/NZdRAIBGjTpg24XG6DsblcLnbs2AEtLS1ISEjgp59+gpSUFOuKp6CgAOPGjcPEiROxZMmSFjt31Odna2uLCRMmoFu3blBXVwePx8PBgwfFlpWRkcGiRYugqKiI3r174/Dhw9i7dy+2bt3KlBkwYACOHz8OZ2dn6Orqonfv3nj69CkAQENDA6GhoczNJeJISkrCz88PiYmJrPTNmzdj27ZtWLFiBRQUFNC2bVt0794dp0+f/khngmop9L7MZuBwOFBUVISioiLWr1+PRYsWIT4+HjIyMgBq/hjHjx8PACgvL8fff//N+mPo2bMnc3fU3r17MXjwYMjLy0NfXx/5+flITU1lxh4ePXoEAwMD5tj6Yvfo0QNv3rxh1VUoFDL1KigowJgxY2BmZoYdO3a0xKmhviA8Hg9JSUnIysoCUPNlRCAQAAAMDQ1x8uRJWFhYiHTPZmdn4+zZs0hPT0doaCgOHjyIt2/fYuXKlXB3d8f169dF3qu8vBw+Pj4IDQ3F1KlTxdZn06ZNiIiIQOfOnVl13LBhA8zMzHDz5k0mPS0tDWlpaR98DqiWRa9APlDt+gO7du0SySsoKMC0adPQq1cvjB49WiT/6tWr2L59O/MtT01NDT/88AN++eUXVFZW4u3bt9i3bx8zvtJQ7Dlz5mDr1q3MgL6Pjw+kpaXRp08fFBYWYuzYsTAwMMCKFSvA5/PB5/OZsvn5+Vi9ejVSUlI+zomhPrvg4GAYGRlh586dUFFRYeXl5+cjKSmJaVDEuXnzJvh8PoYNGwYAMDY2RnR0NLZs2QJPT0/miwxQ8/t48uTJOsdZBg8eDAsLC2zYsIE1/jF69GikpqayGg+q9aANyAeSlpaGu7s73Nzc8OLFCwCAgYEB9PT00KlTJ8jJybHm1ffz80OnTp3Qrl07LF26FF5eXjA3N2fyjxw5gvv376Nt27bo0KEDhg0bhoULFzL59cV2dnaGpaUldHV1wePx4ObmBn9/f8jLyyMoKAhRUVHw9vaGhoYGs9U+APny5Uvs2bMH0dHRLX3KqE/k9evXGDJkCPT19ZGSkgJPT0+oqqoCAJKSkmBtbY2CgoJ6Y6Snp0NNTQ0SEhLM1UJKSgoiIiKwd+9eODk5NVgPRUVFeHt7Y/bs2aioqGDlaWpqIjk5mXmtoaGB8PBwZqO+cHQQ/eMTCAQkLS2NVFRUiORVVlaStLQ0kpeXV2+MrKwsUlJS0qTYtUpLSwmfz29yvdPT05t8DPVpNfc5kK5du5LAwEBy584dsfmRkZHEwcFBJJ3P5xNbW1siJSVFCCFk4MCBTN7UqVNJVFQUq3yHDh1IZWUlK83b25usXr2ayMrKEllZWXLhwgXi4uJCpKSkiIODA4mPj2fKysjIEHNzczJr1ixCCKGD6J9JYwfR6RhIC1BSUoKSkpLYPC6Xi/bt2zcYQ1NTs8mxa8nKytb5fEd9GrMGMtU6vX79GosWLUJycjLk5eWZ2QvqM27cOCgoKCAiIgJCoRDp6ekQCoVMvkAgaNTvmY2NDWRlZbFx40YANb+fFhYWMDU1xZo1a3Ds2DF0794diYmJKC8vR0hICLp169b8D0t9MrQLi6K+Uvr6+qwvG9bW1nj58iVKSkqgqqqKxYsXi20AtLS0MHfuXPj5+WHz5s3MGuxnzpzB2rVrweFwwOFwMGPGjEaNXairqzM3nSgqKuLSpUtYunQp7Ozs8PLlS5w4cQIBAQGsm0Xqek6E+rLQBoSivlJWVlbIyspCZmYmcnJyMG/ePNjZ2QEAjIyM4OHhAV1dXaa8l5cXysvLkZiYiFmzZsHR0RF79uxh8jdv3gwul4ukpCSkpKRARUUFmzdv/uB6Ojo6IigoCDdu3EB2djZSUlJw//593Llz54NjUy2LdmFR1Fdq165d+P3336GmpoaioiIUFRUxedeuXYOmpiays7MBgDV9Tl2Ki4sxadIkKCsro6qqihWv1ps3bxqctXny5Mms10KhEGvXrsW6deugoaEBQgjy8vLoBJ6tAG1AKOorJhQKkZmZKTavtvFoqvpu/f0QhBC8ffu2RWJTLYM2IBTVipSVlX3uKnyR+Hw+evfujU2bNn3uqnwVGnsFSBsQimpFJCQkWnSiQdLCs/62VN3l5OSQnJzcrLsPKVHl5eWNmnyTNiAU1YrIyMi06qndW6ruCgoKqKysxLp161ok/rcmLCyM9ZByXehdWBRFUVSz0AaEoiiKahbagFAURVHNQhsQiqIoqlloA0JRFEU1C21AKIqiqGb5ZLfxenl5IS4ujpXWr18/zJs3j8mTkJCAsrIyevToATs7O9Y93ffu3YO3tzfy8/NhamqKBQsWMBOulZeXw9PTE3fv3oWmpiacnZ3Ru3dv5tigoCBcunQJubm56NKlC5ydnaGjo9Oo2LUCAgKQkpKCFStWsNIFAgHc3d0RFxeHzp07Y/Xq1Q3OaltXLIqiqNbkk12BXL16FY8ePYKWlhaztW3blsl78uQJtLW1UVVVhd9++w1GRkYoLi4GANy6dQtmZmbo0qULJk+eDD8/Pzg4ODCxbW1tceXKFUyePBna2toYMmQIHj58CAC4ePEi1qxZg549e2LatGkoLCzEoEGDmCkTGopdUVGBxYsXw9HREQEBASKfa/z48bh16xZ+/PFH5OXlYfjw4SgtLRV7DhqKRVEU1ap8qgWlJkyYQNavXy+2zPt5xcXFRFVVlZw/f54QQoidnR1ZtWoVk5+ZmUkUFBTI48ePyePHj4mMjAxrgaYVK1YQOzs75nVVVZXIZ2pM7HdjHT16lAwaNIgV5/bt20RBQYEUFRURQgiprq4m+vr6xNvbW+znrC8WRTVGcxeU+to3uqDUx9XYBaW+yDEQeXl5qKqqMut1p6SkoFevXkw+j8dDv379cOvWLaSkpLCuZoCahXBu3brFvH73kfyMjAzk5OSga9euDcYGgK1bt8Lf3x/S0tIi9YyKisLQoUOhoKAAoGaaBnNz8zqX4qwvFkVRVGvT4g1IaWkpbt++DaBmvCApKYnZCgsLRcoXFxfjjz/+QG5uLsaNGwcA0NHRQUxMDFPm7du3ePHiBfLy8qCjo4OMjAxkZWUx+bdu3UJeXh7zOicnB7/99htcXV1hZWWF3bt3o1+/fg3GBsA0DkTMFAwZGRnMmuK1eDwe3rx5I/Zc1BXrn3/+YfY9PT3pPt1vcL8ppKWloaGh0ai5jRqrTZs2UFNTa9axUlJSdS4YJScnB1VV1Rad74v6iBrqwjIxMSFbtmxp9qVQjx49yKZNm8iECROIjIwMUVZWZrZjx44RQmq6sCQkJAiXyyUAyHfffUcePnzIxIiLiyOqqqrE3t6euLq6ElNTU9K9e3fi5eVFCCFk7ty5RE9Pj7i6upLJkyeTsWPHEm1tbeb4jIwMsmTJEjJr1izSp08fMnPmTFJYWNio2LV8fX1Fup2WLFlC5s6dy0rbt28fGTZsWL3n5P1YtV1ghBCSk5ND9+l+nftN6cLicDjEw8ODFBYWEj6fT8rKysjBgwfFlg0NDSXFxcWkqKiIZGdnk/DwcDJlyhSRcpaWliQhIYG8fPmSPHnyhPTs2ZPJ43K5ZNeuXaSwsLDOOunp6ZHi4mLi5OTESp83bx5JSEggFRUVJD8/nxQXF5Pdu3fTLqzPpLFdWA02IDNmzCAnT55sdkV69OhBLCwsGhwDWbVqFSksLCQXLlwgKioqJCsri1UmKyuL/Pnnn+T06dMkLy+P6OrqkuDgYCb/5s2bxMvLi0RFRZGTJ0/WOcZQXl5OjIyMyObNmxsdmxDxDciWLVvIxIkTWWlbt24l1tbW9Z4TcbEoqjGa0oBMmjSJJCcnEx6PRwAQZWVl0rt3b7FlIyMjiYODAwFANDQ0yNSpU0laWhrZunUrU2bAgAEkOzubjBw5UuR4DQ0NEh4eTk6dOkUqKyvFvoekpCSJiooiMTExrAZk8+bNJC0tjVhYWBApKSkCgGhra5M+ffrQBuQzaXVjIFJSUlBUVIStrS0GDx4MV1dXVr6mpibs7e0xbdo0vH79Gunp6Rg6dCiTP2zYMPz0008YPHgw/P39YWZmJvZ9pKWlYWBggFevXjU6dl369OmD2NhYVtqjR49YaztT1OfC4/GQlJTEdO8KBAI8efIEAGBoaIj4+Hh07NhR5Ljs7GycPXsW9vb2WLduHTQ1NQEAK1euhLu7O65fvy5yTHl5OXx8fLBq1ao667Np0yZEREQgMTGRVccNGzbA3t4eQUFBEAqFAIC0tDTmTkrqy/XFNCDv2rdvH86dOyd2MDoxMRHTp0+Hq6srlJSUWHlVVVVwc3NDdHQ0fv75ZwBAREQEa0W2mJgY/P333xg5cmSTYovzww8/oKCgAKdOnQIA3LlzB1evXsWUKVMAAHFxcdiwYQPzR0FRn1JwcDCMjIywc+dOqKiosPLy8/ORlJRU7+qCN2/eBJ/Px7BhwwAAxsbGiI6OxpYtW+Dp6Ynx48czZQsKCnDy5Mk6x1kGDx4MCwsLbNiwgTX+MXr0aKSmpuLmzZsf8lGpz+SLbEC6d++On3/+Gc7OzqioqEBycjI0NDSgo6MDExMTTJkyBZs3b2bKOzo6olu3blBXV0dQUBBCQkKYwe179+6he/fu0NDQAI/Hw5gxY7BkyRLMmTMHABqMXR95eXmcO3cOq1atQtu2bWFubo5ff/0Vffr0AQCEhITAzc2NuZuMoj6l169fY8iQIdDX10dKSgo8PT2hqqoKAEhKSoK1tTUKCgrqjZGeng41NTVISEgwVwspKSmIiIjA3r174eTk1GA9FBUV4e3tjdmzZ6OiooKVp6mpieTkZOa1hoYGwsPDmY36wn2qMZAP9fbtW/L27VtSXV0tkldaWkpSU1NJcXGx2GMrKytJZmYmycrKEnkmpKHYjVFZWUkyMjKIUChkpVdVVZHMzMxmxaQocZr7HEjXrl1JYGAguXPnToNjIO9ufD6f2NraEikpKUIIIQMHDmTypk6dSqKioljlO3ToIDIG4u3tTVavXk1kZWWJrKwsuXDhAnFxcSFSUlLEwcGBxMfHM2VlZGSIubk5mTVrFiGE0DGQz6SxYyCtZkVCDQ2NOvNkZWXRoUOHOvO5XK7I7baNjd0YXC4XWlpaIukcDqfe96WoT+X169dYtGgRkpOTIS8vj5KSkgaPGTduHBQUFBAREQGhUIj09HRWd6xAIGjUErI2NjaQlZXFxo0bAdT8vVpYWMDU1BRr1qzBsWPH0L17dyQmJqK8vBwhISHo1q1b8z8s9cl8kV1YFEV9OH19fdZYnrW1NV6+fImSkhKoqqpi8eLFYhsALS0tzJ07F35+fti8eTP4fD4A4MyZM1i7di04HA44HA5mzJjRqLELdXV1KCoqMtulS5ewdOlS2NnZ4eXLlzhx4gQCAgJYN5/U9ZwI9WWhDQhFfaWsrKyQlZWFzMxM5OTkYN68ebCzswMAGBkZwcPDA7q6ukx5Ly8vlJeXIzExEbNmzYKjoyP27NnD5G/evBlcLhdJSUlISUmBiopKo8cL6+Po6IigoCDcuHED2dnZSElJwf3793Hnzp0Pjk21rFbThUVRVNPs2rULv//+O9TU1FBUVISioiIm79q1a9DU1ER2djYAwMTEpMF4xcXFmDRpEpSVlVFVVcWKV+vNmzeQlKz/38rkyZNZr4VCIdauXYt169ZBQ0MDhBDk5eWhsrKyMR+T+oxoA0JRXzGhUMi6jf1dtY1HU9V36++HIIQws2RTrcMnaUCqq6s/xdtQ1FePfisXr6CgAFpaWvDy8vrcVfkqJCcnN+p3rcUbEIFAwDwXQVHUhyH/byLOlphskIiZMLQltETdKysrkZeXh+Dg4I8euz4SEhIfdZJKcQghn/xLeH5+fqPuhGvxBqSyshIXL17E7t27W/qtKOqrJyUlBeDT/bNvCS1RdyUlJVRWVmLbtm0fPfa3KDo6GpGRkQ2Wo3dhURRFUc1CGxCKoiiqWWgDQlEURTULbUAoiqKoZqENCEVRFNUstAGhKIqimuWbexLdy8sLcXFxcHV1RZcuXVh5lZWVWLlyJZSUlLB161bs378f3bp1g6WlJVPm6tWriIyMhJubG5NWVVWFZcuWYenSpdDR0QEA3L17F3/++SdSU1PRo0cP7Ny5E0DN079HjhxBXFwcFBQUMHLkSMycORMcDgdRUVE4ffq02Hrv27cP1dXVOHHiBG7cuIHKykr07dsXLi4uaNOmDVOOEILz58/jf//7H3JycjB58mRMnz4dAFBaWoqDBw8iOjoaSkpKsLGxgbW1db3nKzY2Fj4+PnB3d29wigqKor4t39wVyNWrV3HixAn4+PiI5AUFBcHb2xsnTpwAUDOvz6FDh1hl9u7di927d7OW5bx//z4OHz7MTN3u4eEBW1tbdO7cGQsWLGBWPySEwMrKCm/evIGNjQ2GDx+OTZs2YcuWLQAAGRkZqKurs7aMjAz4+/uDw+Fg5cqVuHz5MoYNG4bJkyfjf//7H6txI4Tgxx9/xO7du2FiYgJnZ2f07NmTybe3t8e///6LefPmYcSIEXB0dMTx48frPFfHjh3DuHHjcODAAfoENEVRIr7Jr5TW1tY4ceIEtm7dynqK9NixY7C2tsbt27cBAObm5jhy5AgqKyshKSmJwsJC3L59G+bm5ggMDMSKFSsAAGFhYRg8eDAUFBTw+vVrrFq1CnFxcejRowfrfSUkJBAVFcV6z+rqanh4eGDbtm3o378/+vfvL1JXZ2dncDgcuLu7s441NDSEnp4ecnNzoaqqilOnTiE2Nhbx8fFip+kOCgrCnTt3mPd48eIFgoOD4eDgIFL2ypUrcHd3R0BAALOkKUVR1Lu+uSsQAMw/xLCwMCbt7du3uHHjBqtLZ/jw4aioqMD9+/cB1Mxg2rt3b9jb2yMwMJApd/36dZibmwMAzp49i1GjRok0HrXen/bg4cOH6Nq1q9iyCQkJCA0NhbOzc53HqqmpMWs+nDp1CvPnz69zkR99fX38/fffAICysjKEh4dj6NChYstaWloiOjoaHTt2FJtPURTV4g0Ih8NBTk4OrK2tP/tWVlYGoOZb/8yZM1ndN35+frCxsYGcnByTJicnhyFDhuD69esAarq/xo4dC0tLS9y+fRt5eXkQCoW4desW04AkJCRAT08PEydOhIaGBrp06YLDhw+zzklgYCB27NgBW1tbJCYmwtPTU+y527NnD6ZPnw5NTU0mLTY2Frt378b8+fOxa9cuBAQEMGMTCQkJkJOTw4ABA6Cqqor+/fsjIiKCOTYgIADnz5/HmDFjYGBgAGNjY/z8889i31tCQgLy8vIi007cvXuX2T9z5gzd/8T77y661FjS0tLQ0ND4qHM2tWnTBmpqas06VkpKqs4Fo+Tk5KCqqtoi82VRH1+Ld2HJy8uje/fuWLBgQUu/VYNqB74JIXBwcIChoSEKCgqgpKQEX19fHDp0CHl5eaxjzM3Ncf36daxevRrBwcEICAiApqYm+vXrh+DgYHTu3BlcLhcDBw4EUDNIHhYWhgsXLuDChQt48OABRowYAX19fWbNhZycHKSnp6OsrAxZWVl4+PAhOnXqxHrf9PR0nDlzBg8ePGClFxUVIS0tDQKBAMXFxbh9+zYzxpKdnQ1/f39cuXIFPB4PPj4+sLW1xatXr6CkpIT09HRUVlaiY8eOSE5ORnx8PAQCAdq2bdvoc9i5c2dm38jIiO5/4v309HQ0FofDwb59+zBnzhyUl5dDUVERPj4+WLRokUjZ0NBQDB48GIQQlJaW4vHjx/jjjz9w7tw5VjlLS0v89ttvkJaWRnl5OSZOnIinT58CqFlF8JdffsGiRYtYN3a8S09PD7GxsVixYgXri9W8efPg6uoKXV1dlJSUQEpKCgcOHMDq1asb/Xm/VDY2Nli9ejWGDBktGP7/AAAgAElEQVTCpJWWlsLExAQ3btyAoqLiZ6zdh/kkYyDt2rWDlZXVp3irellZWcHGxgZAzS+yoaEhzp07BwMDA5SVlWH48OG4fPky6xhzc3O4ubnhwYMHKCsrw+DBgwHU/CFdvXoVvXv3hqmpKXMVwOVyMX/+fKZB6d+/PywtLREaGso0IA4ODsy4w4ULFzB16lRkZWVBQUGBeV93d3eYmZmhd+/erPqYmJgwcdLS0qCnpwdjY2OMGDECXC4XO3bsYNZn/+mnn7Bx40bExMSge/fuGD9+PC5fvozhw4ejsrISjo6OmDRpEkJDQxt9Dt9d47179+50/xPv5+TkoLFsbW0xYcIEdOvWDVlZWVBWVoa2trbYsjIyMli0aBGOHz8ODQ0NmJmZYe/evejduzez6uCAAQNw/Phx/Pjjj8xVeS0NDQ0EBATgzZs3rKv4d0lKSsLPz491AwpQs9Kho6Mj5s+fj2vXrkEoFEJbW7vZVzhfmoqKClRVVbHSCCGoqKho1ZNiAt/oGEgtBwcH+Pr6wtfXFw4ODmIvmwcMGAApKSkcPHgQY8aMYS69rayscP36dURGRjLdVwDQo0cPvHnzhhVDKBRCRkZGbB2MjIxQXFyMrKwsJk0gEODo0aPMIH1dtLW1wePx8OrVqwbf+8GDB2jbti2GDx8OoOaPefHixbhx40ar/yWmxOPxeEhKSmJ+twQCAZ48eQKg5gaM+Ph4sWNc2dnZOHv2LOzt7bFu3TqmC3XlypVwd3cXaTwAoLy8HD4+Pli1alWd9dm0aRMiIiJYDQiPx8OGDRtgb2+PoKAgCIVCADVfjh4+fNj8D099Et90AzJlyhTExcXh9OnTmD17ttgyXC4XI0aMwF9//QULCwsmvX///pCQkGCNfwDArFmzcObMGWasID4+Hv/88w9Gjx4NgUCAkJAQZm7/8vJy7N69G127dmV1DR0+fBg6OjoYNWoUqy5Xr15FSUkJ89rPzw9paWnMTQFz5szB1q1bmW+pPj4+kJaWRp8+ffDdd98hMzMT0dHRAGq+Afn7+8PIyAgSEhKIi4vDhg0bmD9gqvULDg6GkZERdu7cCRUVFVZefn4+kpKS6l1d8ObNm+Dz+czvl7GxMaKjo7FlyxZ4enpi/PjxTNmCggKcPHmyznGWwYMHw8LCAhs2bGCNf4wePRqpqam4efPmh3xU6jP5phsQJSUl2NraYvDgwSJjEO8aPXo0ioqKMHbsWFa6paUl2rRpw+pm6tu3Lw4dOgRra2u0b98epqam+PXXX2FkZAShUIjly5dDXl4eHTt2hIqKCuLj4xEYGMj8UVVUVGD//v1Yvny5SD38/PygoqICbW1tKCsrY/v27fD394eenh4AwNnZGZaWltDV1QWPx4Obmxv8/f0hLy+PLl264MiRI5g4cSJ69uyJjh074ubNmzh58iQAICQkBG5ubk3qIqG+bK9fv8aQIUOgr6+PlJQUeHp6QlVVFQCQlJQEa2trFBQU1BsjPT0dampqkJCQYK4WUlJSEBERgb1798LJyanBeigqKsLb2xuzZ89GRUUFK09TUxPJycnMaw0NDYSHhzMb9WX75p4DuXTpEuv1qVOnWK9tbGyYcZJazs7OzK207zp69KjY95g1axamT58OPp8PTU1NpmtMXV0dDx8+RFFREQQCAVRUVCAvL886Vlpaus6B0nPnzqG8vBw5OTmQk5MT+VZZ+6yIm5sbiouLRfqQZ82ahVmzZiEnJweysrKsMZdly5ZhxowZrDEOAOjSpQvt4mrF4uPjMX78eHTt2hUeHh4ICgpixvEao3PnzsjOzoakpCQkJSWxevVq5uqaw+FgyZIlIncZvm/fvn04efIkXr58CVlZWXA4HEhKSkJKSgq5ublQV1dnyhYUFGDHjh1o374980Bva1ffHWWt/W6zb64B+VS4XK7IP+NaioqKzb7zQkZGBu3bt6+3jKysbJ3PggAQOzjJ4XDqrC/V+r1+/RqLFi1CcnIy5OXlWV2hdRk3bhwUFBQQEREBoVCI9PR0VhenQCCo9/eslo2NDWRlZbFx40YANb+fFhYWMDU1xZo1a3Ds2DF0794diYmJKC8vR0hISKOWU20teDwesrOzWWmZmZmQlpYW+QLZ2nzTXVgU9TXT19dnHjIFamY1ePnyJUpKSqCqqorFixeLbQC0tLQwd+5c+Pn5YfPmzeDz+QBqnkdZu3YtOBwOOBwOZsyY0aixC3V1deZLk6KiIi5duoSlS5fCzs4OL1++xIkTJxAQEMB6xqWu50Rao9GjR8PPz4+5maGsrAweHh4wNzdv8fXUW1rrrj1FUXWysrJCVlYWMjMzkZOTg3nz5sHOzg5Azd1/Hh4e0NXVZcp7eXmhvLwciYmJmDVrFhwdHbFnzx4mf/PmzeByuUhKSkJKSgpUVFSYW3w/hKOjI4KCgnDjxg1kZ2cjJSUF9+/fx507dz449pdgypQpGDFiBGxsbGBmZoZhw4ZBSkoKGzZs+NxV+2C0C4uivlK7du3C77//DjU1NRQVFaGoqIjJu3btGjQ1NZmuldpni+pTXFyMSZMmQVlZGVVVVax4td68edPgrM2TJ09mvRYKhVi7di3WrVsHDQ0NEEKQl5f31UzgWTtW9PPPPyM3NxeKiop13tbf2tAGhKK+YkKhEJmZmWLz3u+Xb6z6bv39EIQQvH37tkVifwkkJCS+mocja9EGhKJaEXpHnHgVFRVQVFRkHqqlPkxOTk6jftdoA0JRrcj7U2JQNUpKSqCgoIC9e/d+7qp8FUpKSmBqatpgOdqAUFQrQleFFE9dXR1CoZA+fPiRhIWF4eLFiw2Wo3dhURRFUc1CGxCKoiiqWWgDQlEURTULbUAoiqKoZqENCEVRFNUstAGhKIqimqXV3hPo5eWFuLg4Vlq/fv0wb948Jk9CQgLKysro0aMH7OzsWBPH3bt3D97e3sjPz4epqSkWLFjATOBWXl4OT09P3L17F5qamnB2dmat+ZGWlgYPDw+8fPkSvXv3xpIlS8Q+YVpdXQ1XV1cMGTIEdnZ2iIqKwunTp8V+nn379kFSUhJubm5IS0tj5R04cKDecxEQEICUlJQGVzCkKIr6mFrtFcjVq1fx6NEjaGlpMVvbtm2ZvCdPnkBbWxtVVVX47bffmKVjAeDWrVswMzNDly5dMHnyZPj5+TFrlAM1a0lfuXIFkydPhra2NoYMGcIsr5mbm4tBgwYhPz8f06ZNQ0pKCoyNjcVOj71r1y54eXnh/v37AGqmYldXV2dtGRkZ8Pf3Z2bl/OOPP1BVVcUqU5eKigosXrwYjo6OCAgI+CjnlaIoqrFa7RUIUDMBXF0zWg4dOhRr1qwBAGzcuBEdO3bEP//8g4kTJ2L//v1YuHAh1q5dCwAYPnw4dHV1mfWiw8LCkJmZyTRIOTk52LFjB/z9/XH27Floa2vjyJEjAGrWOhgyZAiOHz/OWnTq/v37OHbsGCZOnMik9e/fH/3792fV09raGs7OzkwDwufzsWbNGtYSt3VZt24dsrKysGfPHvj4+DTqnFEURX0srfYKpCnk5eWhqqrKLNeakpKCXr16Mfk8Hg/9+vXDrVu3kJKSwrqaAWoW1rl165bYYzkcDsaMGcPkA0BpaSlmzZoFLy8vSEtL11mvhIQEhIaGMg1PcXExSktL673qeNfWrVvh7+9f73tQFEW1lE/SgLx48QIrV678aFtSUhKAmllBk5KSmK2wsFDkvYuLi/HHH38gNzcX48aNAwDo6OggJiaGKfP27Vu8ePECeXl50NHRQUZGBrP4C1DT5ZWXl8ccGxsby0w0VllZibt37zL5AODq6goLCwuMHDmy3gnJ9uzZg+nTp0NTUxMAmAZu+PDh6NatG0aPHo2rV6/WeXztkrTvv0d8fDyzf+3aNbr/le03lbS0NDQ0ND7q4kVt2rRp9syyUlJSdS4YJScnB1VV1Va/1Ou3osW7sIRCIWJjY0XWGf8Qnp6eAGoG0k+ePMmku7u7Y86cOQCAnTt3YteuXaiqqsJ3332H8PBwdOjQAQCwZs0ajBw5Ev/H3puHRXVk//9vGpt9kaVpFVxAMZEAykCUuIZxiSDggkYRFwITRNHoKEp0UHSGGCGJGtCYCEgUHbckGpmgnygRaA2gIWiMYkgI0NoINPveNHB+f/Djfu10g4jiWq/nqee5t05tt6D79K1TdY5UKoW5uTmuXr0KAwMDGBsbY/jw4Vi0aBEmTJiAmTNnoqCgAHV1dTA2NgYALFq0CNHR0XBxcYGzszOuXLmC1tZWDBw4EABw9uxZ/Pjjj8jMzOzyGYqKinD06FH8/PPPXN6gQYOQlpbGvYGcP38ec+bMwblz5+Di4tLt+bk/1sD9cc/Z9Ytx3V14PB52796Nd955BzKZDHp6eoiLi0NQUJBS2eTkZDg7O4OI0NjYiJs3b2Lfvn04fvy4QrkZM2bg448/hoaGBmQyGebMmYPbt28DaI8i+MEHHyAoKAj6+voqx2RtbY1r165h3bp1CrHU/f39ERwcjKFDh6KhoQF8Ph979uxBSEjIQz834wkyceJE6opFixZRQkJCl2W6wtzcnAwNDXtcvzNmzpxJ//rXvzqVbdiwgWpra+mbb74hIyMjKikpUShTUlJC//3vf+nIkSNUWVlJQ4cOpbNnz3LytLQ0iomJofT0dEpISKAxY8ZwsqamJvr2228pLi6O8vLyyN/fn0JCQqiiooL69etHn3/+OYlEIhKJROTu7k4+Pj6UkZGh0H9wcDC5ubk98DkXLlxIy5cv77JMfHy8wvgYLy7Ozs4EoFvJy8uLCgsLSSgUEgAyNDQkGxsblWUvXbpEvr6+BIAEAgEtWLCAJBIJbdu2jSvj5OREUqmUXFxclOoLBAJKSUmhw4cPU0tLi8o++vTpQ+np6ZSdnU2BgYFcflhYGEkkEnJzcyM+n08AyNzcnOzt7bv9rAMGDCAzM7On/ed5YUhOTqaVK1d2WWbcuHH0XBvRu4LP50NPTw+zZ89GTEwMgoODcejQIU5uZmYGb29vAEB2djaKioowduxYTj5hwgRMmDABQPvbzOTJkzmZpqYmPD09AbRv+T1z5gyOHDmCoqIimJiYcG9IQPubhrq6OgoLCyESiQC0L73t37+/W94utbW1mQdWRo8QCoUoKCjglmOrq6u5YFCjRo1CQkIC3NzccOfOHYV6UqkUx44dQ1FREZKTk7F3716UlpZi/fr12LVrFy5evKjUl0wmQ1xcHJKTk7FgwQKV49myZQtEIpHCBhGhUIjQ0FBMnjxZIb66RCJR2s7OePZ4KYzou3fvxvHjx1W6es7NzYWPjw+Cg4NhYGCgIGttbcWHH36IzMxMvPfee0p1a2pqsHDhQowYMQJTp07Fa6+9hl9//VUhzZkzB/7+/pzyAIDPP/8cVlZW+Pvf/67Q3u3bt5Gbm8vdX758GV999RVmz54NALh+/TpCQ0Mhl8sfZToYLwlnz56Fo6Mjtm/fDiMjIwVZVVUVCgoKuowumJaWhrKyMu6H1Lhx45CZmYmtW7ciOjqa+xEFtH8WEhISOrWzODs7w83NDaGhoQr2j6lTp+LOnTsKyoPx/PBSKJDhw4fjvffew4oVK9Dc3IzCwkIIBAJYWVlh/PjxmD9/PsLCwrjyAQEBGDZsGExNTZGUlIQLFy5AKBRycjs7O1hbW2PQoEHQ1tbu1ptEB83Nzfj000+xdu1aJdm9e/cwfvx4GBgYwMTEBPPnz8fu3bs5+8eFCxfw4YcfcsZ2BqMr8vPz8cYbb8DW1hZisRjR0dGcLa+goAAeHh6oqanpso2Ot2o1NTXubUEsFkMkEmHnzp0IDAx84Dj09PQQGxuLpUuXorm5WUFmZmaGwsJC7l4gECAlJYVLjGec59UG8qiUlpZSaWkptbW1KckaGxvpzp07VF9fr7JudXU1SSQSam5ufuzjamtro7KyMqqoqFCStba2UnFx8WPvk/H88DA2kPuTpaUlJSYmUkZGxgNtIPensrIymj17NvH5fCIiGj16NCdbsGABpaenK5S3sLBQsoHExsZSSEgIaWlpkZaWFn3zzTe0cuVK4vP55OvrSzdu3ODKampq0pQpU2jJkiVERMwG8pR46W0gD0IgEHQq09LS4nZsqcLAwEBpuetxoaam1un2SB6Pp/AmxGB0l/z8fAQFBaGwsBA6OjoqPSf8FVdXV+jq6kIkEkEul6OoqEhh+bS6ulrBPVBnzJo1C1paWti8eTOA9s+Xm5sbJk2ahPfffx8HDhzA8OHDkZubC5lMhgsXLmDYsGE9f1jGE+OlWMJiMF5GbG1tFX7oeHh4IC8vDw0NDTA2NsaqVatUKoB+/frBz88Phw4dQlhYGMrKygAAR48excaNG8Hj8cDj8bBo0aJu2S5MTU2hp6fHpdOnT2PNmjWYN28e8vLycPDgQZw8eRJ2dnZcnc7OiTCeLZgCYTBeUNzd3VFSUoLi4mKUl5fD398f8+bNAwA4OjoiKioKQ4cO5crHxMRAJpMhNzcXS5YsQUBAACIjIzl5WFgY1NXVUVBQALFYDCMjIwXbYU8JCAhAUlISUlNTIZVKIRaLkZWVhYyMjEdum9G7vLRLWAzGi86OHTvwySefwMTEBHV1dairq+Nk58+fh5mZGaRSKYB2v3IPor6+Hl5eXjA0NERra6tCex3cvXv3gdvO586dq3Avl8uxceNGbNq0CQKBAESEyspKtLS0dOcxGU8RpkAYjBcYuVyO4uJilbIO5fGwdLX191EgIpSWlvZK24zegS1hMRgMBqNH9PobSGtrK2QyWW93w2C8FPz1HAWjnZKSEgwcOBD29vZPeygvBHK5XCEURWf0ugJpaWnh4nIwGIxHg7nuV42ZmRnq6+vx22+/Pe2hvBCkpKQgMTHxgeWeiA0kPDz8sezWYDAYDFWoqalBTU2NKdjHRHf97zEbCIPBYDB6BFMgDAaDwegRTIEwGAwGo0cwBcJgMBiMHsEUCIPBYDB6BFMgDAaDwegRzJXJY6a4uBgHDhzAL7/8AiKCvb09/P390a9fP65MTEwMrl+/DgDQ1dWFubk5Zs6cqRDqUyKRICoqCnl5ebCxscHq1asV3LxnZGQgPj4eFRUVsLGxQVBQEMzMzAC0u6j44osvcP36dejq6sLFxQWLFy/mosUlJSXh9OnTqKiowJAhQ7BixQpYWVlxbV+9ehWxsbGoqqrCpEmTsGzZMgXvqESEr7/+GufOnUN5eTnmzp0LHx+fTuekrKwMERER8PPzw4gRIx5xhhkMxrMCewN5jPz000+wtbXFtWvX8NZbb8HV1RW//PIL7O3tce3aNa7cd999h9u3b2PIkCHQ19eHSCTC8OHDuVjTFRUVGDNmDKqqqrBw4UKIxWKMGzeOi+Fw9epVTJs2Dfb29ggICIBYLMb48eMhl8tBRHB3d8fdu3cxa9YsTJw4EVu2bMHWrVsBAKdOncL777+PV199FQsXLkRtbS3GjBnD+SC6fPkyJk+ejCFDhmDu3Lk4dOgQfH19ubETEd5++21ERERg/PjxWLFiBV599dVO5yQzMxNjxozBvn37FCLPMRiMF4Dejkior69P6urqPa7/vNDW1kY2NjYqo3itXLmSRo4cyd3PnDmT/vWvfymU8fLyIj8/PyIi2rt3L40ePZqTtba20ujRo2nv3r1ERBQeHk4eHh6cXC6XE4/Ho1u3bnHl7ycmJobs7OwU2rsfc3Nz+vrrr4mIaN68ebRhwwZOVlxcTLq6unTz5k0iIjp06BANGzaMGhsbHzQlVFxcTObm5vT999/TsGHD6OzZsw+sw+iankYkfNETi0j4eHlmIhLK5XKoqakhLi6ut7t6avTv3x9mZma4desWzp07pyTfuHEj9uzZg2vXrmHUqFEq25DJZNwSlVgsVljq4fF4mDZtGi5fvowVK1bAzs4Oe/bsQXFxMfr164fvv/8epqamXGyHjqWqDn755RdYWloqtNfBvXv3UF5ezsnFYjHc3Nw4uVAohIODAy5fvgwbGxscPnwY7777brci0QmFQty+fRt6enpKrrk73swAIDs7Gw4ODuy6G9f9+/d/4Lz/FQ0NDRgaGqK8vBxtbW0PXV8V+vr60NDQQHl5+UPX5fP5aGtrQ2trq5JMW1sb2traqKysBBE9jqEyepFeVyBqamrg8/lIT0/v7a6eGq+88gpiY2NhaGiIgQMHKskHDBgAY2Nj3Lx5k1MgaWlp2Lp1K+RyOXJycsDn8xESEgIAsLKywrlz50BEUFNTQ0tLC65cucLZITw9PXHz5k2MHDkS48ePx2+//Ybz588ruHFITEzE9evXkZWVhcbGRuzfv5+TlZeXIz4+HsXFxbh48SIiIiK4LygrKytkZ2dzy1alpaX4448/UFlZCQDIycmBu7s7nJyc8Oeff2LIkCH49NNPMWHCBJVzo6enBwBKXwYSiYRTIHfu3OH6Z9ddXz9MKGUej4fdu3fjnXfegUwmg56eHuLi4hAUFKRUNjk5Gc7OziAiNDY24ubNm9i3bx+OHz+uUG7GjBn4+OOPoaGhAZlMhjlz5uD27dsA2qMIfvDBBwgKCoK+vr7KMVlbW+PatWtYt24dPv/8cy7f398fwcHBGDp0KBoaGsDn87Fnzx7uM8F4RuntJSxtbW3q27dvj+s/L8TExNCAAQM6lQ8cOJBiY2OJqH0Ja8KECRQWFkabNm2iuXPn0ujRo+nnn38mIqL6+nqytbWlSZMmUUhICLm4uNDEiRPJx8eHiIiam5tp2bJlNGrUKPLx8SGhUEjHjx9X6C8+Pp6WL19O06dPp1GjRlFiYiInu3fvHq1evZqWLFlC9vb2tHjxYqqtrSUiouvXr5OxsTF5e3tTcHAwTZo0iYYPH04xMTFERKSlpUXjx4+ne/fuUVtbG8XExJCJiQlVV1d3OT+DBw9mS1iPgYdZwvLy8qLCwkISCoUEgAwNDcnGxkZl2UuXLpGvry8BIIFAQAsWLCCJRELbtm3jyjg5OZFUKiUXFxel+gKBgFJSUujw4cPU0tKiso8+ffpQeno6ZWdnU2BgIJcfFhZGEomE3NzciM/nEwAyNzcne3t7toT1lOjuEhZTII+J7777jng8HslkMiVZc3Mzqaur07lz54hItQ0kPDycLC0tufumpib69ttvKS4ujvLy8sjf359CQkKIiGjdunXk6upKzc3NRET0888/k5GREaWkpKgc29dff026urpUV1enJJPJZOTo6EhhYWFcXklJCf33v/+lI0eOUGVlJQ0dOpT78tfV1VXqp1+/fp323QFTII+Hh1EgK1asoNTUVJWyUaNG0Y0bN2jgwIFKCqQjTZw4keRyOZmZmREAOn78OG3atEllewYGBrR48WIaMGBApwrk3//+N0VGRtLx48c5BSIUCkkul9PEiROZDeQZorsKhO3CekxMmDABGhoaOHnypJLsxIkT0NLS6nSZBwCGDh2KkpIS7l5TUxOenp7w8/ODubk5zpw5g8mTJwMAUlNTMX/+fPD5fACAg4MDJkyYgLS0NJVtOzo6or6+XqH9DjQ0NGBnZ4c///yTyzMzM4O3tzcWLlyI/Px8FBUVYezYsQDal+vu3r2r0IZcLoempmanz8Z4Opw9exaOjo7Yvn07jIyMFGRVVVUoKCjoMrpgWloaysrKuP/bcePGITMzE1u3bkV0dDQ8PT25sjU1NUhISFCyv3Xg7OwMNzc3hIaGKmwJnzp1Ku7cudPp/y7j2YYpkMeEvr4+Nm3ahPXr1+PixYsgIhARLl68iPXr12Pbtm3Q0dHhyhMRWlpa0NTUhF9++QWRkZGYPn26Urs1NTVYuHAhRowYgalTpwIA7O3tcebMGS64kFgsRkZGBpycnFBdXY0LFy5wxlKZTIaIiAhYWlpi8ODBEIlECiFOs7OzcebMGbi4uCj1nZubCx8fHwQHB3Nr7++88w62bdvGGU/j4uKgoaEBe3t7VFVVISQkBGKx+DHNKuNRyM/PxxtvvAFbW1uIxWJER0fD2NgYAFBQUAAPDw/U1NR02UZRURFMTEygpqYGoVCI0NBQiMViiEQi7Ny5E4GBgQ8ch56eHmJjY7F06VKlgFhmZmYK27sFAgFSUlK4xHi2YQcJHyObN2+Gvr4+Fi9ejIqKCgCAqakpNm/ejOXLlyuU3b59O7Zv3w41NTX0798fM2bMQEREBCe3s7NDU1MTpFIp3N3dcerUKU4WEREBX19fWFhYQCAQQCqV4p///CdcXV1RVlaGtWvXIjc3FwKBAOXl5XB0dERiYiLU1dVx9epVzJgxA5qamuDxeGhra8Pq1avxzjvvAAAKCwvh5OQEfX191NXVISgoCKGhoVzfK1asQF5eHoYOHQpNTU3o6+vjxIkT0NHRQU5ODiIjI+Hk5IRBgwb15lQzusmNGzfg6ekJS0tLREVFISkpCc7Ozt2uP3jwYEilUvTp0wd9+vRBSEgIrly5AqDdSL969WoFY7gqdu/ejYSEBOTl5UFLSws8Hg99+vQBn89HRUUFTE1NubI1NTUIDw/HgAEDcPDgwZ49NOPJwWwgvUN5eTlVVFT0uH51dTVJJBLOzqEKmUxGxcXF1NbWpiSrra2lu3fvUn19vZKspaWFiouLqaSkROlMCBFRaWkplZaWqmy3g8bGRiorK1PKLyoq6rQO49F5lHMggwYNIiIiHR2dLo3oHcnV1ZUaGxvJ1NSUAJBEIiEHBwcFeXZ2tkIdCwsLJRtIWVkZ1dXVcamlpYWampro5MmTNHToUGpra6Phw4cr1Bk2bBgREbOBPCWYDeQpY2xsrLTu/DAYGBhgwIABnJ1DFRoaGhAKhVBTU1OS6enpwdzcXGHZrAN1dXUIhUKYmZmpXLMWCAQQCAQq2+1AS0tLwbVKBz05p8DoHWxtbRW2/Xp4eCAvLw8NDQ0wNjbGqlWrVJ7n6devH/z8/HDo0CGEhYWhrKwMAHD06FFs3DBIriYAACAASURBVLgRPB4PPB4PixYt6pbtwtTUFHp6elw6ffo01qxZg3nz5iEvLw8HDx7EyZMnYWdnx9W5307CeHZhCoTBeEFxd3dHSUkJiouLUV5eDn9/f8ybNw9A+8aKqKgo7vAp0O6jTSaTITc3F0uWLEFAQAAiIyM5eVhYGNTV1VFQUACxWAwjI6PHEqo6ICAASUlJSE1NhVQqhVgsRlZWFjIyMh65bUbvwmwgDMYLyo4dO/DJJ5/AxMQEdXV1qKur42Tnz5+HmZkZpFIpAGD8+PEPbK++vh5eXl4wNDREa2urQnsd3L1794HxtOfOnatwL5fLsXHjRmzatAkCgQBEhMrKSiXvBYxnD6ZAGIwXGLlcrrDr7n46lMfD0tXW30eBiDinnoznA7aExWAwGIwe0etvIPT/n3dgMBiPTsdnqasNDj2FnpDzwt4Ye2lpKUaMGIFp06Y99rZfRuRyeZcHnzvodQXS2tqK9evX93Y3DMZLxZP6su8NemPsxsbGKCoqwokTJx572y8jGRkZyMzMfGC5J2IDiYiIwL///e8n0RWD8ULzIAP1y0rHvHQV3IzRfYqKipCVlfXAcswGwmAwGIwewRQIg8FgMHoEUyAMBoPB6BFMgTAYDAajRzAFwmAwGIwewRQIg8FgMHrEc70nsLGxEUeOHIFIJEJtbS0sLS2xdOlS2NvbK5WtrKzE2rVrsXnzZlhZWSnIJBIJoqKikJeXBxsbG6xevVrB02xGRgbi4+NRUVEBGxsbBAUFwczMDADQ1taG2NhYXLhwAbq6uli+fDlGjx6t0L5YLMaBAweQk5MDAPjyyy+hra0NALh69SpiY2NRVVWFSZMmYdmyZZwn0sbGRuzduxeZmZkwMDDArFmz4OHh0eWcXLt2DXFxcdi1axfb8slgMHqV5/YNpKKiAuPGjcP+/fsxevRoeHl5AWh3CqcqEM3hw4dx4sQJxMTEKLUzZswYVFVVYeHChRCLxRg3bhwaGhoAtH/BT5s2Dfb29ggICIBYLMb48eMhl8sBANu2bUNkZCTc3NwwbNgw/P3vf8eNGze49n/88UcupOzSpUvh7e3NKYjLly9j8uTJGDJkCObOnYtDhw7B19eXq+vt7Y3vv/8e/v7+ePPNNxEQEIAvv/yy0zk5cOAAXF1dsWfPHnb6n8Fg9D69HVCKz+eThoZGj+t3xvLly8nBwUEp4NJXX31FOjo6JJFIFPJHjhxJ27Zto/79+5NcLufy9+7dS6NHj+buW1tbafTo0bR3714iIgoPDycPDw9OLpfLicfj0a1bt6ipqYn09fUpJSWFkwcFBdGiRYu4tqytrSkmJkblM8ybN482bNjA3RcXF5Ouri7dvHmTiNrnLisri5Nv2bKF3n77bZVtJSYmkq2tLYlEIgJAjY2NKssxnm8eJaDUi5xYQKnHyzMdUOr69eu4fPlyj1NDQwOOHj2Kf/7zn0oBl7y8vGBhYaHg0uCnn36CWCzGhg0boK+vj6SkJE4mFosxYsQI7p7H42HatGm4fPkygPbQslevXuU8mn7//fcwNTXF0KFDcfPmTcjlcgVX2FOnTuViOWdmZkIqlWLx4sUq5+GvfQuFQjg4OHB929ra4syZMwCApqYmpKSkYOzYsSrbmjFjBjIzMzFw4EAl2Z07d9j1C3b9MGhoaEAgEKgMHtZT9PX1VQYU6w58Pr/TgFHa2towNjbuFX9ZjMfPE1cgmZmZ8PX1RUhISI/TunXrUFVVpRDB7H5sbW1x8+ZN7j42Nhbe3t7Q0tLC4sWLERcXx8msrKxw7do1zj9PS0sLrly5gsrKSgCAp6cn3nvvPYwcORJeXl7YsGEDzp8/Dw0NDdy7dw+mpqYKHwahUAiJRAIiQk5ODl577TX85z//gbm5OYRCIVauXAmZTMb1nZ2dzdUtLS3FH3/8wfV98uRJfP3115g2bRrs7Owwbtw4vPfeeyqfWU1NDTo6Oir9DJ0/f55dv2DX3YHH4yEqKgrl5eXIyclBQ0MD9u7dq7JscnIy6uvrUVdXB6lUipSUFMyfP1+p3IwZM5CTk4Nr165BJBIpuA5RV1fHjh07UFtb2+mYrK2tUVVVhXfffVch39/fHzk5Oaiursaff/6Juro6REREPNTzMp4CT3oJ63//+x/NmDGjx+0REf3+++8EgHJzc1XKFy9ezC0j1dfXk4GBAYlEImpsbKTffvuN+Hw+3bt3j5Pb2trSpEmTKCQkhFxcXGjixInk4+NDRETNzc20bNkyGjVqFPn4+JBQKKTjx48TEdGpU6fIyspKoe9r164RAGppaaEdO3aQlpYWxcXFUVtbG5WUlNCoUaMoPDyciIiuX79OxsbG5O3tTcHBwTRp0iQaPnw4t+SVlpZGr776Kvn5+dHw4cPJ3d2dKisru5yb/Px8toT1AvMwS1heXl5UWFhIQqGQAJChoSHZ2NioLHt/THSBQEALFiwgiURC27Zt48o4OTmRVColFxcXpfoCgYBSUlLo8OHDSjHRO1KfPn0oPT2dsrOzKTAwkMsPCwsjiURCbm5uxOfzCQCZm5uTvb09W8J6SjzTS1iPSr9+/cDj8SAWi1XKCwsLYWFhAaD9V3xNTQ0mTJgAbW1tvPLKK5DL5ZwxWkdHBz/99BPWrl2L4cOHIzY2FtbW1lz9jRs3QiwW48qVKzh8+DDOnj2LwMBApKamwsjICFVVVQp9V1dXQ19fH+rq6lBXV4ezszP8/PygpqYGMzMzBAYG4sKFCwAAe3t75OTkwMPDAw4ODjh9+jRaW1thYWGBe/fuwdPTE1988QXi4uJw8+ZNCAQCbrMAg/EghEIhCgoKUFJSAqD9f/PWrVsAgFGjRuHGjRsqlzylUimOHTsGb29vbNq0idtxuH79euzatQsXL15UqiOTyRAXF4cNGzZ0Op4tW7ZAJBIhNzdXYYyhoaHw9vZGUlIStzlFIpHgl19+6fnDM54Iz6UC0dPTg7OzM44dO6YkKywsxI8//ghXV1cA7ctXH330ERobG7m0b98+HDhwgKujqakJT09P+Pn5wdzcHGfOnMHkyZMBAKmpqZg/fz5na3FwcMCECROQlpYGW1tbVFVVKaxN//rrr9zS2iuvvIK7d+8qjE8ul0NTU5O7NzMzg7e3NxYuXIj8/HwUFRVh7Nix+Pnnn9G3b19MnDgRQLu30VWrViE1NfW5duXNeHKcPXsWjo6O2L59O4yMjBRkVVVVKCgo6DK6YFpaGsrKyri4EOPGjUNmZia2bt2K6OhoeHp6cmVramqQkJDQqZ3F2dkZbm5uCA0NVVjynTp1Ku7cuYO0tLRHeVTGU+K5VCAA8MEHHyAhIQH79+/nbAq5ubnw8fHB9OnTMXHiRPz222+4cuUKli5dCi0tLS75+PigqKhI6Z+2pqYGCxcuxIgRIzB16lQA7W8JZ86cQXNzM4B2w3dGRgacnJxgYmKCt956Cx988AFaWlpQWlqK3bt3w9vbGwAwZcoUNDU1ISoqCkD7luHY2Fi89dZbSs/TMfbg4GAYGBjgtddeQ3FxMeeTn4hw4sQJODo6Qk1NDVVVVQgJCen0LYzByM/PxxtvvAFbW1uIxWJER0fD2NgYAFBQUAAPDw/U1NR02UZRURFMTEygpqbGvS2IxWKIRCLs3LkTgYGBDxyHnp4eYmNjsXTpUu5z1IGZmRkKCwu5e4FAgJSUFC4xnm2eWwXy5ptv4ttvv8Xnn38OfX19GBgYwMnJCU5OTjh58iQAIC4uDu7u7hAIBAp19fX18fbbbyM2NhZA+04ra2trDBo0CNra2jh16hRXNiIiAjKZDBYWFnjttdfg5OSENWvWcG84X3zxBbKystC3b19YWFhgwoQJWL58OYD2HSXffvst9u3bh379+mHw4MFwdnbGypUrAbS/LQkEAlhZWWH8+PGYP38+wsLCAABDhgzBF198gTlz5uDVV1/FwIEDkZaWhoSEBABAXl4eIiMjuxX0hfHycuPGDXh6esLe3h5DhgxR2IHYHQYPHgypVIo+ffqgT58+CAkJwYEDB3DixAmEhoZi6dKlD2xj9+7dSEhIQF5eHrS0tMDj8dCnTx/w+XxUVFTA1NSUK1tTU4Pw8HAcOHAAkyZNeujnZTxhnkcj+l+pr6+n4uJiamtr61H96upqkkgkSmdK7kcmk3XZR0lJCTU0NHRav7S0VGX7paWlVFpa2uXYy8rKqK6uTim/qKio0zqMF5NHOQcyaNAgIiLS0dHp0ojekVxdXamxsZFMTU0JAEkkEnJwcFCQZ2dnK9SxsLBQMqJ3/P92pJaWFmpqaqKTJ0/S0KFDqa2tjYYPH65QZ9iwYUREzIj+lHihjeh/RUdHB0KhsMd7xw0MDDBgwAClMyX3o6Gh0WUfZmZmnHsSVQgEApXtCwQCCASCLsduYmICXV1dpfz+/ft3WofBsLW1hYGBAXfv4eGBvLw8NDQ0wNjYGKtWrYKWlpZSvX79+sHPzw+HDh1CWFgYysrKAABHjx7Fxo0bwePxwOPxsGjRom7ZLkxNTaGnp8el06dPY82aNZg3bx7y8vJw8OBBnDx5UmFbfmfnRBjPFi+EAmEwGMq4u7ujpKQExcXFKC8vh7+/P+bNmwcAcHR0RFRUFIYOHcqVj4mJgUwmQ25uLpYsWYKAgABERkZy8rCwMKirq6OgoABisRhGRkbckuujEBAQgKSkJKSmpkIqlUIsFiMrKwsZGRmP3Dajd2He9hiMF5QdO3bgk08+gYmJCerq6lBXV8fJzp8/DzMzM0ilUgBQ8KbQGfX19fDy8oKhoSFaW1sV2uvg7t27D3TiOXfuXIV7uVyOjRs3YtOmTRAIBCAiVFZWMn9uzwFMgTAYLzByuZxzw/NXOpTHw9LV1t9HgYhQWlraK20zege2hMVgMBiMHvFE3kCIiDsbUVRUxAxkDEYP6VjW6S1ng/QEDqn2xtilUin+9re/YdGiRY+97ZeR5uZmDBs27IHlHqhAmpubkZSUxLlD6Al6enqYOXMmACA7O5t52mQwekhbWxuAJ/NF31v0xtgNDAzw22+/PRajPqPdY/qff/75wHIPVCC7d+/GRx99hHv37vVoIEQEIsKCBQsAtB/i27dvX4/aYjBedjQ0NJ72EJ5JNDU10dLSwh3wZTwampqakEgkDyz3QAXSv39/7Ny5s8cD2bNnj4LvJwaDwWC8GDAjOoPBYDB6BFMgDAaDwegRTIEwGAwGo0cwBcJgMBiMHsEUCIPBYDB6xDPtyqSxsRFHjhyBSCRCbW0tLC0tsXTpUtjb2yuVraysxNq1a7F582ZYWVkpyCQSCaKiopCXlwcbGxusXr0aJiYmnDwjIwPx8fGoqKiAjY0NgoKCuDCeHVy7dg1xcXHYtWuXgq+fpKQknD59GhUVFRgyZAhWrFjB9b9582ZUVlYqjXXatGlcNLdjx47hf//7H4gI48aNg7+/f5e71srKyhAREQE/Pz+MGDGiG7PIYDAYvcMz+wZSUVGBcePGYf/+/Rg9ejQXC3z8+PE4ePCgUvnDhw/jxIkTiImJUWpnzJgxqKqqwsKFCyEWizFu3Dg0NDQAAK5evYpp06bB3t4eAQEBEIvFGD9+PBebGQAOHDgAV1dX7NmzR8HB26lTp/D+++/j1VdfxcKFC1FbW4sxY8Zw/nyMjIxgamqqkI4ePcpFYNu9ezf+9a9/wdPTE97e3khISMCyZcs6nZPMzEyMGTMG+/btU4jixmAwGE+FBwWUelQ0NTVJKBRy990NKLV8+XJycHBQCsL01VdfkY6ODkkkEoX8kSNH0rZt26h///4kl8u5/L1799Lo0aO5+9bWVho9ejTt3buXiIjCw8PJw8ODk8vlcuLxeHTr1i0iIkpMTCRbW1sSiUQEgBobGxX6bW1tVbg3Nzenr7/+WuUzZWVlkYGBAVVXVxMR0ZQpU+iTTz7h5D/88EOnQXGKi4vJ3Nycvv/+exo2bBidPXtWZTnGi82jBJR6kRMLKPV4eaYDSrW0tKC8vLzT1NzcjKNHj+Kf//ynUhAmLy8vWFhY4MSJE1zeTz/9BLFYjA0bNkBfX18hbKdYLFZY6uHxeJg2bRouX74MoD2c7dWrVzmPpd9//z1MTU25OAkzZsxAZmYmBg4cqPJZeLz/N4X37t1DeXk5LC0tVZaNiIiAv78/F+THzs4O586d4952zp07h7Fjx6qsKxQKcfv2bUydOlXJzXVjYyO7fkmuH+QqncF4kjxxBWJra4vi4mK88sornabAwEBUVVUpRCj7axs3b97k7mNjY+Ht7Q0tLS0sXrwYcXFxnMzKygrXrl3j/O+0tLTgypUrnG3C09MT7733HkaOHAkvLy9s2LAB58+f51xGqKmpQUdHp1P/PeXl5fj4448RHBwMd3d3REREwMHBQalcfn4+vv32W6xevZrL+89//gNDQ0OMHDkSkyZNwq1bt3DgwIFO505PTw+Asi+h6Ohodv2SXI8ZMwYPi4aGBgQCgcKPnUdFX19fwY74MPD5/E4dqmpra8PY2Jj5y3teeNJLWN3h999/JwCUm5urUr548WJatGgREbXHQzcwMCCRSESNjY3022+/EZ/Pp3v37nFyW1tbmjRpEoWEhJCLiwtNnDiRfHx8iIioubmZli1bRqNGjSIfHx8SCoV0/PhxpT7z8/NVLmHdu3ePVq9eTUuWLCF7e3tavHgx1dbWKtVfsWIFzZ8/XyHv7t27NGnSJPL09CQXFxeysbGh69evP3B+Bg8ezJawXlIeZgmLx+NRVFQU1dbWUllZGTU1NdHevXtVlk1OTqb6+nqqq6sjqVRKKSkpNH/+fKVyM2bMoJycHMrLy6Nbt27Rq6++ysnU1dVpx44dVFtb2+mYrK2tqb6+ngIDAxXy/f39KScnh5qbm6mqqorq6+spIiKCLWE9Jbq7hPVMKpDa2lri8Xh04cIFlfKJEyfS+++/T0REX375pcp/qA8//JAr39TURN9++y3FxcVRXl4e+fv7U0hICBERrVu3jlxdXTlby88//0xGRkaUkpKi0GdnCuR+ZDIZOTo6UlhYmEK+VColbW1tunLlikK+k5MThYeHc/exsbFkampKFRUVXc4PUyAvLw+jQLy8vKiwsJCEQiEBIENDQ7KxsVFZ9tKlS+Tr60sASCAQ0IIFC0gikdC2bdu4Mk5OTiSVSsnFxUWpvkAgoJSUFDp8+DC1tLSo7KNPnz6Unp5O2dnZCgokLCyMJBIJubm5EZ/PJwBkbm5O9vb2TIE8JZ5pG8iD0NPTg7OzM44dO6YkKywsxI8//sh53YyNjcVHH32ExsZGLu3bt09hKUhTUxOenp7w8/ODubk5zpw5g8mTJwMAUlNTMX/+fM7W4uDggAkTJiAtLe2hx62hoQE7OzslN8jR0dFwcnLC66+/zuXV19fjp59+Uohf4O/vj+bmZvz6668P3TeD8VeEQiEKCgq4UAzV1dW4desWAGDUqFG4ceOGStueVCrFsWPH4O3tjU2bNnFb2tevX49du3bh4sWLSnVkMhni4uKwYcOGTsezZcsWiEQi5ObmKowxNDQU3t7eSEpK4uyBEokEv/zyS88fnvFEeCYVCAB88MEHSEhIwP79+yGTyQAAubm58PHxwfTp0zFx4kT89ttvuHLlCpYuXQotLS0u+fj4oKioSEkJ1NTUYOHChRgxYgSmTp0KALC3t8eZM2fQ3NwMoN3onpGRAScnpweOUSQSKYQLzc7OxpkzZ+Di4sLlNTQ0YO/evVi3bp1CXV1dXVhZWeGrr77i8s6ePYuWlhbY2NigqqoKISEhEIvFDzlzDEY7Z8+ehaOjI7Zv3w4jIyMFWVVVFQoKCroMT5uWloaysjJMmDABADBu3DhkZmZi69atiI6O5s4yAe2frYSEhE7tLM7OznBzc0NoaKiC/WPq1Km4c+dOj36wMZ4+z6wCefPNN/Htt9/i888/h76+PgwMDODk5AQnJyecPHkSABAXFwd3d3cIBAKFuvr6+nj77bcRGxsLoH23k7W1NQYNGgRtbW2cOnWKKxsREQGZTAYLCwu89tprcHJywpo1a7oVV+Dq1asYPnw4BAIBhEIhpk2bhtWrV+Odd97hysTFxcHIyAgeHh5K9Y8dO4ZDhw5h8ODBeOWVVxAUFIQTJ07AxMQEeXl5iIyMRGZmZo/mj8HIz8/HG2+8AVtbW4jFYkRHR8PY2BgAUFBQAA8PD9TU1HTZRlFREUxMTKCmpsa9LYjFYohEIuzcuROBgYEPHIeenh5iY2OxdOlS7odaB2ZmZgpnmgQCAVJSUrjEeMZ5Fm0gf6W+vp6Ki4upra2tR/Wrq6tJIpEonSm5H5lM1qM+WlpaqLi4mEpKSpTOhHSX2tpaKi8vV8ovKirqUXuMF5eengOxtLSkxMREysjIeKAN5P5UVlZGs2fPJj6fT0REo0eP5mQLFiyg9PR0hfIWFhZKNpDY2FgKCQkhLS0t0tLSom+++YZWrlxJfD6ffH196caNG1xZTU1NmjJlCi1ZsoSIiNlAnhLdtYE8F5vKdXR0oKOj0+P6BgYG3NmLztDQ0IBQKHzottXV1XtU7346tuf+lf79+z9SuwxGB/n5+QgKCkJhYSF0dHQ4Twxd4erqCl1dXYhEIsjlchQVFSl4aKiuroaWltYD25k1axa0tLSwefNmAICWlhbc3NwwadIkvP/++zhw4ACGDx+O3NxcyGQyXLhwoVvxuBlPn2d2CYvBYDwatra2Cj+cPDw8kJeXh4aGBhgbG2PVqlUqFUC/fv3g5+eHQ4cOISwsDGVlZQCAo0ePYuPGjeDxeODxeFi0aFG3bBempqbQ09Pj0unTp7FmzRrMmzcPeXl5OHjwIE6ePKlw7quzcyKMZ4teVyA8Ho8dCmIwngLu7u4oKSlBcXExysvL4e/vj3nz5gEAHB0dERUVxXlcAICYmBjIZDLk5uZiyZIlCAgIQGRkJCcPCwuDuro6CgoKIBaLYWRkhLCwsEceZ0BAAJKSkpCamgqpVAqxWIysrCxkZGQ8ctuM3kVt4sSJlJqa2msd9O3bFytXrkR4eHiv9cFgvCy88cYbD/XFyufzYWJigrq6OtTV1SnIBAIBpFLpQ4/B0NAQra2tSu09KmpqahAIBCAiVFZWKrns6YoBAwagpaWF27LMeDR++OEHnDp1SsELwl8ZP378k1nCSkxMfBLdMBiMvyCXy1FcXKzyy74nygNot308buUBAESE0tJSSKXSh1IejKfHc2FEZzAY7TQ1NT3tITyTSKVS2NnZYe3atU97KC8ENTU1So5sVcEUCIPxHEFEvWpTpE6chj5OemP8urq6+OOPPxTOYDF6Tm5ubrfeMpkCYTCeI7S1tZ/Il3xv0hvj19HRQUtLC1auXPnY234Z6bCBPAi2jZfBYDAYPYIpEAaDwWD0CKZAGAwGg9EjmAJhMBgMRo9gCoTBYDAYPYIpEAaDwWD0iOdqG29MTAyuX7+O4OBgDBkyREHW0tKC9evXw8DAANu2bUNSUhJyc3OxZs0arkxubi6ioqIQGhqKfv36cfm7d+/GiBEj8NZbbym0uW/fPpSVlXFeRKVSKb744gtcv34durq6cHFxweLFixWC6NTV1eHLL79EZmYm6uvrsXnzZjg4OODQoUO4cuWK0jNZWlpi3bp1aG5uRkxMDEQiEbS1teHm5sb5LQLaI75FR0fjypUrMDMzw4oVK2BjY9PlfF27dg1xcXHYtWsX+vR5rv7UDAbjOeC5egP57rvvcPDgQcTFxSnJkpKSEBsbi4MHDwJo32seFhaG1tZWrszx48fx2Wef4cyZM1xea2srtmzZonS46dKlS9i4cSO+++47rj13d3fcvXsXs2bNwsSJE7FlyxZs3bqVq1NWVgYnJyekpaVh1qxZCAgIgImJCYB2l+2mpqYKKT09HT/++CMAYM6cOfjhhx/g6uqKsWPHYtWqVdi1axfX9uzZs/G///0Pc+fOhbm5Od54440uQ34eOHAArq6u2LNnD3MLwWAweofeDihlaGhI9vb2j6WtmTNnkre3Nw0cOFApeFOHbPDgwUTUHqSJz+dTZmYmV8bZ2Zneeustcnd35/LS09NJU1OTGhoauLzq6moaNmwYvf/++zRmzBgu/699xsTEkJ2dHXfv5+dHPj4+3XqWxsZGMjMzo4sXL3LjvZ/o6GhycnIiIqKbN2+SpqYmVVZWcvJ169bRvHnzVLadmJhItra2JBKJCAA1NjZ2a0yMZ5+eBpR60RMLKPV46W5AqefqDQQAF5/5hx9+4PJKS0uRmpqqEDZWT08PY8aMwcWLFwG0vx1kZWVh+/btSE5O5gLqXLx4EWPHjoW2tjZXd9WqVVi0aBFsbW0V+v5rvOdffvkFlpaWANqd1p04cQLvvfdet54jPj4e5ubmePPNN7nx3k9raysXq0EsFqNfv37o27cvJ3d1dcXly5dVtj1jxgxkZmZi4MCB3RoLg8Fg9IQnrkAqKirg4uICgUDwUOn27dsAgLa2NixevBhffvkl1+ahQ4cwa9YsBSUAAFOmTOEUyNmzZ/H666/jb3/7GywtLZGcnAygXYFMmTKFq/PVV18hNzcXoaGhKl0uJCYmIjw8HLNnz0Zubi7n7vjOnTtobGzE77//DmtraxgbG2PGjBm4c+eOUhttbW3YuXMn1q1bp3KOZDIZ9u/fj3fffRcAYGVlhXv37im4qr58+TIqKytV1ldTU4OOjo7K8X/00Ufs+gW4fhg0NDQgEAiUfgA9Cvr6+tzy7MPC5/M7DRilra0NY2NjFkPoeeFJL2H9+uuvNGLECJJKpQ+VtmzZQjNnzqTo6GjKzc0lHR0dqq6uJiIiGxsbSklJoVOnTnFLWEREly5dIl1dXWpubqb58+dTeHg4ERFt2LCB3n33XWpubiYdHR1umUsikdCgQYPojz/+ICKihIQEhSUsIqL4+Hhavnw5TZ8+nUaNGkWJiYlERJSRkUE8Ho9WrFhBL2pqQAAAIABJREFUjY2NJJPJyNfXl6ZMmaI0JydOnCALCwuVMdpbW1tp/vz5NGvWLIV8Pz8/sra2puDgYJo7dy5Nnz6dzM3Nu5z7/Px8pSWs+vp6dv0cXz/MEhaPx6OoqCiqra2lsrIyampqor1796osm5ycTPX19VRXV0dSqZRSUlJo/vz5SuVmzJhBOTk5lJeXR7du3aJXX32Vk6mrq9OOHTuotra20zFZW1tTfX09BQYGKuT7+/tTTk4ONTc3U1VVFdXX11NERARbwnpKdHcJ66kokNdee61HbXUoECKisWPH0v79+yk9PZ2srKyora1NSYHI5XLS19enS5cukbGxMWVlZRERUWpqKg0YMIBEIhH17duXWlpaiIho2rRptGzZMhKJRCQSiWjz5s1kY2NDIpFI4YPcwddff026urpUV1dHV69eJT6fT3K5nJPfvn1bKY+I6PXXX6fIyEil9tra2mjZsmU0efJklXaLtLQ0iomJofT0dJXK7a+oUiCM55uHUSBeXl5UWFhIQqGQAJChoSHZ2NioLHvp0iXy9fUlACQQCGjBggUkkUho27ZtXBknJyeSSqXk4uKiVF8gEFBKSgodPnyYWlpaVPbRp08fSk9Pp+zsbAUFEhYWRhKJhNzc3IjP5xMAMjc3J3t7e6ZAnhLdVSDP7d5OX19fxMfHw87ODr6+vipfefv06YNJkyYhLi4OGhoacHBwAACMGzcOjY2NiI+Ph4uLC/c6XVlZCYlEgkuXLgFoD5xTXl6OwMBAnD59GsOGDVNo39HREfX19SgpKcGwYcPQ1taGkpISmJubA2i3i/Tp00fhdf3ixYvIyclBQECA0nhXrlyJ33//HYmJiSpjVU+YMIGzAW3fvh2TJ0/uydQxXhKEQiEKCgq4pc/q6mpUV1cDAEaNGoWEhAS4ubkpLbNKpVIcO3YMRUVFSE5Oxt69e1FaWor169dj165d3LLw/chkMsTFxSE5ORkLFixQOZ4tW7ZAJBJh8ODBCmMMDQ3F5MmTFeKrSyQSSCSSR54DRu/y3BnRO5g/fz6uX7+OI0eOYOnSpZ2WmzJlCr766iu4urpySkZdXR3Tp0/HyZMnFewfV65cwa+//sqlDz/8EPb29vj1118hEAhw4cIFtLW1AWj/wERERMDS0hKDBw9G3759MWvWLKxduxZyuRwtLS3YuXMnpk6dqqDcIiMj8Y9//AOGhoYK41y5ciUyMzMRHx+PhoYGlJWVoaysTGkLbmtrKz788ENkZmZyBvuqqiqEhIRALBY/2qQyXijOnj0LR0dHbN++HUZGRgqyqqoqFBQUcApFFWlpaSgrK+N+tIwbNw6ZmZnYunUroqOj4enpyZWtqalBQkJCp3YWZ2dnuLm5ITQ0VOEH1dSpU3Hnzh0F5cF4fnhuFYiBgQFmz54NZ2dnDBo0qNNyU6dORW1tLdzc3BTy3d3dUVtbq6BAukIul2Pt2rXQ0dHBwIEDYWRkhBs3biAxMZH7QHzxxReoqamBmZkZTE1NUVBQgM8++4xr48aNG7hw4QJWr16t0HZJSQn27t2LrKwsDB48WGHzQEf864CAAAwbNgympqZISkrChQsXIBQKAQB5eXmIjIxEZmZmt56F8XKQn5+PN954A7a2thCLxYiOjoaxsTEAoKCgAB4eHqipqemyjaKiIpiYmEBNTY17WxCLxRCJRNi5cycCAwMfOA49PT3ExsZi6dKlaG5uVpCZmZmhsLCQuxcIBEhJSeES4xnnebKBPAvU1tbS3bt3VdpEOqiqqlI61/GoNDY20p07dzrtt6io6LH2x3g26ek5EEtLS0pMTKSMjIwH2kDuT2VlZTR79mzi8/lERDR69GhOtmDBAkpPT1cob2FhoWQDiY2NpZCQENLS0iItLS365ptvaOXKlcTn88nX15du3LjBldXU1KQpU6bQkiVLiIiYDeQp8cLbQJ4Wenp6Smc2/spfl6ceB1paWrCwsOhU3r9//8feJ+PFIT8/H0FBQSgsLISOjg53DqorXF1doaurC5FIBLlcjqKiIsjlck5eXV2t0lb3V2bNmgUtLS3OJZCWlhbc3NwwadIkvP/++zhw4ACGDx+O3NxcyGQyXLhwQcneyHg2eW6XsBgMRtfY2trCwMCAu/fw8EBeXh4aGhpgbGyMVatWqVQA/fr1g5+fHw4dOoSwsDCUlZUBAI4ePYqNGzeCx+OBx+Nh0aJF3bJdmJqacj+89PT0cPr0aaxZswbz5s1DXl4eDh48iJMnT8LOzo6r09k5EcazBVMgDMYLiru7O0pKSlBcXIzy8nL4+/tzDjodHR0RFRWFoUOHcuVjYmIgk8mQm5uLJUuWICAgAJGRkZw8LCwM6urqKCgogFgshpGREcLCwh55nAEBAUhKSkJqaiqkUinEYjGysrI4+x/j2YUtYTEYLyg7duzAJ598AhMTE9TV1aGuro6TnT9/HmZmZpBKpQCA8ePHP7C9+vp6eHl5wdDQEK2trQrtdXD37t0Hen6eO3euwr1cLsfGjRuxadMmCAQCEBEqKyuZE9DnAKZAGIwXGLlcjuLiYpWyDuXxsHS19fdRICKUlpb2StuM3uGpKJD7XawzGIzuc78Rm/H/qKqqwtChQznfdIxHo7i4uFtvgE9cgZw7d67bZy8YDIYyvelokFQ44Hzc9Mb41dTUUFxcjD/++OOxt/0yUlJSohB0rzOeuAKpqanBkSNH2C8FBqMH8Pn8J/Il35v0xvgNDQ3R0tKCTz/99LG3/TLyww8/4NSpUw8sx3ZhMRgMBqNHMAXCYDAYjB7BFAiDwWAwegRTIAwGg8HoEUyBMBgMBqNHMAXCYDAYjB7BTqJ3k5iYGFy/fh3BwcEYMmSIgqylpQXr16+HgYEBtm3bhqSkJOTm5mLNmjVcmdzcXERFRSE0NFRhf/Xu3bsxYsQIlJSU4MqVK0r9WlpaYt26dbh+/TpiYmIUZG5ublyck7a2NsTGxuLChQvQ1dXF8uXLMXr0aK5sRkYG4uPjUVFRARsbGwQFBcHMzEypv3v37mHTpk1Yu3Yt7OzskJ6ejiNHjqick927d3fqtuLatWuIi4vDrl27HujagsFgPJ+wN5Bu8t133+HgwYOIi4tTkiUlJSE2NhYHDx4E0L7PPSwsTOHE/fHjx/HZZ5/hzJkzXF5rayu2bNkCNTU16OnpwdTUVCGlp6fjxx9/BABkZWUhOTlZQa6jo8O1tW3bNkRGRsLNzQ3Dhg3D3//+d9y4cQMAcPXqVUybNg329vYICAiAWCzG+PHjlU41ExHeeecdfPXVV1w4UU1NTaVx3bt3DydOnOg0+tyBAwfg6uqKPXv2MH9GDMaLzJMOKLVlyxYyMjLq1T57g5kzZ5K3tzcNHDiQWltbVcoGDx5MRO1Bp/h8PmVmZnJlnJ2d6a233iJ3d3cuLz09nTQ1NamhoUGpv8bGRjIzM6OLFy8SEdGOHTvI19dX5diamppIX1+fUlJSuLygoCBatGgRERGFh4eTh4cHJ5PL5cTj8ejWrVsK7Xz66ac0Z84cGjFiBJ09e7bTuXB3d6ewsDCVssTERLK1tSWRSEQAqLGxsdN2GA9PTwNKveiJBZR6vHQ3oBR7A3kIOmJD//DDD1xeaWkpUlNT4eHhweXp6elhzJgxuHjxIgCgrKwMWVlZ2L59O5KTk7lgPhcvXsTYsWOhra2t1Fd8fDzMzc3x5ptvcm2YmpqqHNfNmzchl8sVPKpOnTqVCwlqZ2eHq1evck71vv/+e5iamiq48r516xZ27tyJffv2delvKScnB8nJyVixYoVK+YwZM5CZmYmBAwd22gaDwXgxeOIKREtLCzweDxMmTHhuUofX0ra2NixevBhffvkl9zyHDh3CrFmzlJTAlClTOAVy9uxZvP766/jb3/4GS0tLJCcnA2hXIKr8grW1tWHnzp1Yt24dl1deXo4TJ07A2toaDg4O+Oc//4mKigoA7XYLU1NThSA8QqEQEokERARPT0+89957GDlyJLy8vLBhwwacP38eGhoaAIDm5mYsWrQIe/bsgZmZWZeuJiIjI+Hj46PSfgK0+yTS0dFRauPq1avcdXx8PLt+xOuHQUNDAwKBoNMlx56gr68PExOTHtXl8/mdBozS1taGsbFxr/r7Yjw+nrh109jYGFOmTMHKlSufdNc9psNvFxHB19cXo0aNQk1NDQwMDBAfH4/PPvsMlZWVCnWmTJmCjz76CHK5HN999x1n7HZ3d0diYiKmT5+Oy5cvIzw8XKm/r7/+Gk1NTXj77be5vPDwcPzjH/+AUCjE3bt3ERoaijlz5iAlJQVyuZxTBh1oa2uDiNDW1oa2tjYUFhZiwIAB0NbWRllZGW7fvg17e3sAwObNmzFmzBi4u7t3OQ9FRUU4evQofv7554eeQ2tra+568uTJ7LqH1/v370d34fF42L17N9555x3IZDLo6ekhLi4OQUFBSmWTk5Ph7OwMIkJjYyNu3ryJffv24fjx4wrlZsyYgY8//hgaGhqQyWSYM2cObt++DaA9iuAHH3yAoKAg6OvrqxyTtbU1rl27hnXr1uHzzz/n8v39/REcHIyhQ4eioaEBfD4fe/bsQUhISLefl/EUeNI2kM8//5yWLVvWq332BjNnzqTo6GgiIho7dizt37+f0tPTycrKitra2ujUqVOcDYSo3c6gr69Ply5dImNjY8rKyiIiotTUVBowYACJRCLq27cvtbS0KPX1+uuvU2RkZJfjyc3NJQBUUlJCKSkpZGxsrCBPTU0lfX19IiJat24dubq6UnNzMxER/fzzz2RkZEQpKSnc+P7v//6PRCIRiUQiMjc3p48//phycnIU2gwODiY3N7duzVd+fj6zgfQCD2MD8fLyosLCQhIKhQSADA0NycbGRmXZS5cuka+vLwEggUBACxYsIIlEQtu2bePKODk5kVQqJRcXF6X6AoGAUlJS6PDhw9TS0qKyjz59+lB6ejplZ2dTYGAglx8WFkb/H3tnHhbFsf39L8MiO7IMgwE1KhqD6NVgFDWKC6hsCioiUQHFEKLgEjUGgyIJEeQXkYBbZBOMPxdyrxoC3rwCooCIuUQNKl4MAUdAYAbZl2EY6v2Dl35th00UBVKf56nn6a5z+nR1w/TprlNVp7i4mFhZWRF5eXkCgOjr65NJkybRGMhboqcxEDq+she4uroiOjoaEydOhKura4ef23JycjAzM0NkZCQUFBQwZcoUAMCsWbPQ2NiI6OhozJs3T+pT/urVq8jNzYW7u3uXbWjvMpOTk4OxsTGqqqrw5MkTJvZw7949Jsf0tWvX4OnpCXl5eQDAlClTMHv2bFy/fh3Dhw/HsGHD8PnnnzO2BQIBwsLCUFxcjODgYABtSYROnDjRoxU6Kf0DHo+HwsJClJWVAWj7G7Yng5o8eTJOnToFKysrPHnyhHWcQCDA2bNnUVJSguTkZBw5cgTl5eXYuXMnDh06xHTNPo9IJEJkZCSSk5OxatWqDtuzd+9epKWlYeTIkaw2+vj4YMGCBaz86sXFxcxIQEr/hQbRe4GjoyPu3r2L06dPw8XFpVM9c3Nz/PTTT7C0tGScjKysLBYvXoy4uLgO4x9BQUHYsGEDNDQ0WPX//ve/IRKJALSlFv3qq69gZmYGLS0taGtrY9GiRfj222/R0tKC8vJyhISEwMnJCQAwadIk/Pzzz2hubgYA8Pl83Lx5E1OnToWrqyvu3bvHKsOHD8fx48cZ5wEAx48fx+jRozF//nxWu+7evQsfHx+a6KgfcvnyZZiYmGD//v3Q1NRkyaqqqlBYWNhldsHr169DKBQyg0dmzZqFrKws7Nu3D2FhYViyZAmjW1NTg1OnTnUaZzE1NYWVlRV8fHxYL00WFhZ48uQJy3lQBg7UgfQCdXV12Nvbw9TUFCNGjOhUz8LCArW1tUz8ox0bGxvU1tZKOZCcnBwkJSVhy5YtUrYiIiKgqqoKPT096OrqoqamBv/7v//LyH/44QdkZ2dj6NChMDAwwOzZs/HZZ58BAA4cOACRSAQDAwNMmDABU6dOxdatW2Fpadmj621ubsb333/P+kppJykpCQEBAaioqOiRLcqbo6CgADNmzICxsTH4fD7CwsKgpaUFACgsLIStrS1qamq6tFFSUgJtbW3IyMgwXwt8Ph9paWkIDg6Gh4dHt+1QVVVFREQEXFxcmJeYdnR1dfH48WNmn8vlIjU1lSmUfs6biIHo6+uTwMBAEhgYSOzt7Ymbm1ufnnOw0tTUREpKSohYLO5Up6ysrMN5JYQQIhKJSGlpKWltbX1tbZJIJKS0tPS12aN0TW/ngYwaNYrEx8eTmzdvdhsDeb4IhUJib29P5OXlCSGETJs2jZGtWrWKZGZmsvQNDAykYiARERFk165dRFFRkSgqKpJ//etfxNPTk8jLyxNXV1eSk5PD6A4ZMoSYm5sTZ2dnQgihMZC3RL+JgSgpKWH06NHMKKWGhga8//77fX3aQcmQIUMwbNiwLnU6G14LtA3n5PF4r7VNHA7ntdukvH4KCgqwadMmPH78GMrKysxcpK6wtLSEiooK0tLSIBaLUVJSwuqqrK6uhqKiYrd27OzsoKioiD179gBoG8pvZWUFMzMzfPnll4iKisK4ceOQl5cHkUiEpKQkGBoa9v5iKW+MN9KFNXPmTAQGBiIwMBD29va0u4NCeQMYGxtDXV2d2be1tUV+fj4aGhqgpaUFLy+vDh2Anp4e1q9fj9jYWPj6+kIoFAIAzpw5A29vb3A4HHA4HKxZs6ZHsQsdHR2oqqoy5eLFi9i6dSscHByQn5+PmJgYxMXFMYM+AHQ6T4TSv6AxEAplkGJjY4OysjKUlpaioqICbm5ucHBwAACYmJggNDSUtRpBeHg4RCIR8vLy4OzsDHd3dwQFBTFyX19fyMrKorCwEHw+H5qamvD19X3ldrq7uyMxMRHXrl2DQCAAn89HdnY2bt68+cq2KX0LHcZLoQxSAgMDcfDgQWhra6Ourg51dXWM7MqVK9DV1WVWWXh+GZzOqK+vx/Lly6GhoQGJRMKy105RUVG3qy+vWLGCtS8Wi+Ht7Y3du3eDy+WCEILKykq6EOcAgDoQCmUQIxaLmTXQXqTdebwsXQ39fRUIISgvL+8T25S+gToQCmUAQd/KO6ahoQHa2trMOnOUV+Phw4dobW3tVo86EAplgNFXCw2SLhbRfJ30RfsbGhqgrKyMkJCQ127770htbS0rIV1nUAdCoQwg5OTk3tiDvq/oi/br6OigpaUF8fHxr93235GUlJQeLVtER2FRKBQKpVdQB0KhUCiUXkEdCIVCoVB6BXUgFAqFQukV1IFQKBQKpVdQB0KhUCiUXkGH8XbC5cuXcenSJZSWloLH42Hp0qVSeT3a2bVrF8zMzKTkIpEIYWFhuHXrFnR1dbFx40YYGRkBAGJjY3Hr1i0pW6NGjcL27dsBAHFxcbh06RI4HA4+/vhjLF68uEe2X+TYsWMQCoXMaqjNzc0IDw9HWloalJSUYGVlxayR1BlCoRAHDhzA+vXr6WrKFAoFAP0C6RBXV1ds2LABI0eOhKOjI0aNGgV3d/cO08zeu3cPhw8fxjfffCMls7e3xy+//IIVK1ZAX18fM2bMwB9//AGgLcmOjo4Oq2RmZuLGjRsA2jIT7tixA/Pnz8fcuXOxfv16REZG9sj286Snp8Pb2xsJCQlM3bJly5CSkgJLS0vMnDkTXl5eOHToUKf3IysrC9OnT8exY8dYyX8oFMrfnL5OKKWnp0d27drF7B8/fpx8+umnfXrOV+HcuXNESUmJ8Pl8Vj2fzydKSkrkwoULrPotW7aQrVu3kqFDh5L79+8z9ffv3ydDhgwhlZWVTN327duJg4NDh+dtbGwkurq65OrVq4QQQrhcLklMTGTk8fHxhMfjkdbW1h7brq6uJoaGhuTLL78k06dPZ+pra2tZemFhYWTq1Kkdtqu0tJTo6+uT//N//g8xNDQkly9f7lCP8mbobUKpwV5oQqnXS08TStEvkBeIjY2Fk5MThg8fzqofPnw41qxZg5MnTzJ1IpEIP/74Iz7++GM4ODggIiKCkfH5fOjp6WHo0KFMnaWlJTIyMjo8b3R0NPT19TF37lw0NTVBIBCwuooWLlwIoVCIP//8s8e2vby8sGbNGhgbG7PqVVVVWfsSiaTTxEA8Hg8PHz6EhYUFXYeJQqGweOMxEFVVVdy+fRuffPLJmz51t2zatAm5ublSucrbmThxIkJDQ5n9CxcugMfj4cMPP4RIJIK9vT0CAwOhoKCA0aNH4+nTpygrK2My9mVkZDCZGZ+ntbUVwcHB2LdvH4C2jG3Dhg3D7du38e677wIAbt68CYlEgsrKyh7Z/umnn5CXl4eoqCicOXOm02sWiUQ4ceIEdu3a1alOu8MhLyxBER8fD1tbW7r9Brffe++9l86ToaCgAA0NDVRUVPRogbyeoKamBgUFhV4lh5OXl0drayskEomUTElJCUpKSqisrBzwS7b8HXjjDmT16tWQkZHpUUrNN01MTAxEIhFUVFQ6lKuoqKCpqYnZj4iIwOrVq9HU1ISpU6dCTU0NP//8M1asWIFx48ZhzZo1mD17NpYuXYrCwkLU1dVBS0tLyu4///lPNDU1YeXKlUzd/v37sWHDBqSkpKClpQVlZWXgcDjQ0tKCoaFhl7ZLSkqwfft2pKSkdJnZrbW1FS4uLhg3bhycnZ1f+n7p6+vT7Te8XVNTg57C4XAQEhKCdevWQSQSQVVVFZGRkdi0aZOUbnJyMkxNTUEIQWNjI+7fv49jx47h3LlzLD1ra2t89913UFBQgEgkwrJly/Dw4UMAbVkEv/32W2zatAlqamodtmns2LG4c+cOtm/fjuPHjzP1bm5u2LFjB8aMGYOGhgbIy8vj8OHDXb7YUPoBbzoG0t/58MMPiY+PT4eyvXv3ElNTU0IIIQUFBURGRkaqL3bRokWsY65fv07Cw8NJZmYmOXXqFCsW8fw5g4KCpOpzc3NJdHQ0iY+PJwUFBYTD4ZD6+vpubS9cuJB8+umnJC0tjaSlpZE9e/YQIyMjkpaWxhzf2tpKPv30U7JgwQLS2NjYo3szcuRIGgN5y7xMDGT58uXk8ePHhMfjEQBEQ0ODGBkZdaibnp5OXF1dCQDC5XLJqlWrSHFxMfHz82N0pk6dSgQCAZk3b57U8Vwul6SmppIff/yRtLS0dHgOOTk5kpmZSW7fvk08PDyYel9fX1JcXEysrKyIvLw8AUD09fXJpEmTaAzkLdHTGAh1IC+we/duMm7cOCKRSFj1EomEvPfee8TPz48QQoiPjw+xtbUljY2NTLl37x6RlZWVCsC3Y2trS3bv3s2qS0lJIaqqqqSqqqrLdh08eJDMnDmzU/nztj/88EMyYcIEphgYGBAlJSUyYcIE8ujRI0IIIRs3biTz589nOaTuoA7k7fMyDmTjxo3k2rVrHcomT55McnJyyPDhw6UcSHuZM2cOEYvFRFdXlwAg586dI7t37+7Qnrq6Olm7di155513OnUgX3/9NQkKCiLnzp1jHAiPxyNisZjMmTOHBtH7ETSI3ku2bduGqqoqbNq0Cc+ePQMAPHv2DJs2bUJ9fT22bNkCiUSCkydPws3NDYqKikyZMGECZs6ciejoaJZNiUSCgIAAZGVlYfPmzSxZUFAQNmzYAA0NjU7blJCQgG+++QZ+fn5Sso5s37p1C/fu3WNKQEAAJk2ahHv37sHQ0BCenp7IyspCdHQ0GhoaIBQKIRQKmSB5QEAArl279kr3kfL2uXz5MkxMTLB//35oamqyZFVVVSgsLOwyu+D169chFAoxe/ZsAMCsWbOQlZWFffv2ISwsDEuWLGF0a2pqcOrUKXA4HT9STE1NYWVlBR8fH1a3qoWFBZ48eYLr16+/yqVS3hLUgbyAjo4OMjIywOfzwePxoKGhAT09PTx9+hQZGRnQ0NDAr7/+CrFYDGtra6njN2zYgOjoaBBC4O7uDkNDQ+jo6CAxMRFJSUlM0BsAcnJykJSUhC1btkjZiY2NxYgRIzBs2DBs3boV4eHhrOB+d7Y7o6ysDEeOHEF2djZGjhwJLpfLlPbg7P79+3H+/Pne3D5KP6KgoAAzZsyAsbEx+Hw+wsLCmDhZYWEhbG1tu42plJSUQFtbGzIyMuDxePDx8QGfz0daWhqCg4Ph4eHRbTtUVVUREREBFxcXNDc3s2S6urqsuUVcLhepqalMofRzaBdW5zQ3N5OSkhLS3Nzcq+MbGxvJkydPXqqbqJ2WlhZSXFzMmuvxumx3h0Ag6PU1U/qW3s4DGTVqFImPjyc3b97sNgbyfBEKhcTe3p7Iy8sTQgiZNm0aI1u1ahXJzMxk6RsYGEh1YUVERJBdu3YRRUVFoqioSP71r38RT09PIi8vT1xdXUlOTg6jO2TIEGJubk6cnZ0JIYR2Yb0letqFRZcy6QJ5eXkMGzas18crKirCwMCgV8fKysrinXfe6RPb3aGjo9Mndilvj4KCAmzatAmPHz+GsrJyj0ZBWlpaQkVFBWlpaRCLxSgpKYFYLGbk1dXVnc4feh47OzsoKioyS+koKirCysoKZmZm+PLLLxEVFYVx48YhLy8PIpEISUlJMDQ07P3FUt4YtAuLQhmkGBsbQ11dndm3tbVFfn4+GhoaoKWlBS8vrw4dgJ6eHtavX4/Y2Fj4+vpCKBQCAM6cOQNvb29wOBxwOBysWbOmR7ELHR0dqKqqMuXixYvYunUrHBwckJ+fj5iYGMTFxWHixInMMV0NP6f0H6gDoVAGKTY2NigrK0NpaSkqKirg5ubGLJppYmKC0NBQjBkzhtEPDw+HSCRCXl4enJ2d4e7ujqCgIEbu6+sLWVlZFBYWgs/nQ1NTE76+vq/cTnd3dyQmJuLatWsQCATg8/nIzs5+6QmTlDcP7cKiUAYpgYGBOHjwILS1tVFXV4e6ujpGduXKFejq6kIgEADdWHbVAAAgAElEQVQAPvroo27t1dfXY/ny5dDQ0IBEImHZa6eoqAhycl0/VlasWMHaF4vF8Pb2xu7du8HlckEIQWVlJV06ZwBAHQiFMogRi8UoLS3tUNbuPF6Wrob+vgqEEJSXl/eJbUrfQB0IhUIZ8BBCICsr2y+XSBqIiESiHulRB0KhDCCeHwVF+f8IBAIMGzYM06dPf9tNGRSIxWIsW7asWz3qQCiUAYS8vPzbbkK/RFdXFyKRCDk5OW+7KYOClJQUXLhwoVs9OgqLQqFQKL2COhAKhUKh9ArqQCgUCoXSK6gDoVAoFEqvoA6EQqFQKL2COhAKhUKh9ArqQCgUCoXSKwatA/niiy+wfft2EEKkZI8ePYKnpyd+/PFHtLa2YsuWLcjLy2PphISEICoqilWXl5eHbdu2Sdl8+vQp1q1bxxqDXlZWhr1792LFihXYuHEj/vOf/7COuXPnDjZv3gwHBwfs3r0bJSUlUu28c+cOvLy8pNYEam1txYkTJ7By5UqsW7cOt27dkjq2paUFQUFB+Pnnnzu5Q2zi4uJw8ODBHulSKBQKMIgdyIkTJ3DixAmkpKRIyY4dO4aYmBgkJSWBw+Hgxo0buHTpEiMXiUTYs2cP9uzZw3IWFy9eRFZWFmRkZJg6QgjWrVuHn376CcXFxQCA2tpaTJs2DdXV1Vi5ciWGDRuGjz76iHnQZ2VlwdraGjweD6tWrcKTJ09gamrKyg4XFRUFS0tLHD58WMqB+Pn5ISgoCFZWVjA0NMT8+fNZzqu0tBQLFixAQEAAbty40eV9am5uhpeXF9zd3REXF9eTW0uhUCgABvlMdFtbW0RHR2PBggVMnVgsxunTp2FjY8PUmZub4+rVq9i5cycAIDU1FYaGhnj69Cl+//13mJiYAGibnfl8WlkACAsLg4qKCoYPH87Uqamp4f79+1BVVWXq7t69i7i4OEybNg3Tp0/Hf//7X0Zub28PPT09pKWlwdraGr/88gsOHTqEuLg4Jh91OyKRCIcOHUJ8fDzMzMwAtH0BBQUF4dSpUwCApUuXYvny5Rg7dmy392j37t0oKytDUFAQIiMju7+pFAqF8v94618gIpEIBw8efG0lJiaGse3k5IQLFy6w3uzj4+Px/vvvs7L9mZubIy0tjXnTT0hIwPz587Fo0SLEx8cDaHM86enpLAfy4MEDBAcH49ixY1JrFD3vPABAIpGwkvd0Jbe2tkZWVhbLKbVz//59iMVi1vLbFhYWrPzRycnJ+OKLLyCRSDq56/8fPz8/nD9/HgoKCqz6O3fuMNuZmZl0u59sd/Q/0R0KCgrgcrngcF7fz11NTQ3a2tq9OlZeXr7ThFFKSkrQ0tJifeVT+i9v3YF89dVXuHz5Mp4+ffpailAohJ+fHwBg9OjRmDx5Ms6fP8+cLyoqCuvWrWM9XD/66CNIJBImTpGYmIjFixfDxsaGcSC//fYbAGDGjBkA2rp+1qxZg8OHD0NXV7fDWEs7jx49wtWrV7F27doO5adPnwaXy2W+NmRkZKCsrNyhzadPn0JHR4f1A+TxeCguLmb0251TV21qR0VFpUPd+vp6Zru2tpZu95PtFx19V3A4HISGhqKiogK5ubloaGjAkSNHOtRNTk5GfX096urqIBAIkJqaCkdHRyk9a2tr5Obm4s6dO0hLS8P48eMZmaysLAIDA1ntfZGxY8eiqqoKn3zyCavezc0Nubm5qK6uxl9//YW6ujocOHCgx9dKeUvMmTOnD1OzE6Knp0d27drVqXzr1q3k0KFDr/28GhoaJCcnh5w4cYLMnDmTEEJISUkJGTp0KKmrqyNbtmwhLi4ujL65uTnZv38/yc3NJSoqKqSpqYlUV1cTBQUFUlRURPz9/YmlpSWj/8UXXxAPDw9mf8yYMeTy5ctS7RAKheT9998nISEhHbYzKyuLaGtrk8zMTClZQUEBAUAaGxuZugsXLpDRo0ez9O7cuUMAkJaWFla9i4tLl/f+eaKjo8n06dN7pEt5e5iamhIAPSrLly8njx8/JjwejwAgGhoaxMjIqEPd9PR04urqSgAQLpdLVq1aRYqLi4mfnx+jM3XqVCIQCMi8efOkjudyuSQ1NZX8+OOPpKWlpcNzyMnJkczMTHL79m3i4eHB1Pv6+pLi4mJiZWVF5OXlCQCir69PJk2a1ONrfeedd4iuru7b/vMMGpKTk4mnp2eXOrNmzSJv/Qukr3F0dMSdO3eQl5eHmJgY2NvbM2/dz2Nubo7U1FT8+uuvmD9/PoYMGQJ1dXXMmjULiYmJSE1NZbqvMjIyEBERAXt7e6SnpyM9PR1NTU24f/8+Hj58yNisqamBpaUlli1bhi1btkidMycnB3Z2doiNjYWpqWmPrkdTUxNVVVWsuurqaqipqdE80hQWPB4PhYWFKCsrA9D2f/LgwQMAwOTJk5GTk9Nhl5hAIMDZs2fh5OSE3bt3Q1dXFwCwc+dOHDp0CFevXpU6RiQSITIyEl988UWn7dm7dy/S0tJYIx55PB58fHzg5OSExMREpiu4uLgYf/zxR+8vnvJGGPQORF1dHXZ2djh58iROnjyJdevWdahnbm6OrKwsXLt2DVZWVky9jY0NkpOTkZmZyTiQR48eYdiwYfj888/h4eEBDw8PCAQChIWF4cSJEwDanMfChQuxYMEC+Pv7S53v/v37sLS0xPHjx1nn6w5jY2NUVVXhyZMnTN29e/cwceLEHtug/D24fPkyTExMsH//fmhqarJkVVVVKCws7DK74PXr1yEUCpmu1VmzZiErKwv79u1DWFgYlixZwujW1NTg1KlTncZZTE1NYWVlBR8fH9aLjoWFBZ48eYLr16+/yqVS3hKD3oEAgKurK77//ntIJBKpUU3tTJkyBXJyckhKSpJyIImJiVBRUWEe0q6urrh37x6rDB8+HMePH0dwcDBqa2uxePFiTJw4Edu3b4dQKIRQKERFRQWANudhbm6Or7/+GjNnzmTkzwf7O0NbWxuLFi3Ct99+i5aWFpSXlyMkJAROTk49uhf//Oc/ER4e3iNdysCmoKAAM2bMgLGxMfh8PsLCwqClpQUAKCwshK2tbbf/cyUlJdDW1oaMjAzztcDn85GWlobg4GB4eHh02w5VVVVERETAxcUFzc3NLJmuri4eP37M7HO5XKSmpjKF0r8Z1MN421mwYAG0tbXh4uLSqQ6Hw8H8+fPx4MEDjBgxgqkfN24c9PT0MHXq1B6PDElMTERmZiYyMzMRERHB1MvKyqKlpQWHDx9GaWkp3NzcpNqZlJTUrf0ffvgBy5Ytw9ChQ9Hc3Iy1a9fis88+61HbTp48ib/++ksqiEkZnOTk5GDJkiUYNWoUQkNDkZiY2OPuUgAYOXIkBAIB5OTkICcnh127djHzmTgcDrZs2YLjx493aSMkJASnTp1Cfn4+FBUVweFwICcnB3l5eTx79gw6OjqMbk1NDfz9/fHOO++wRlRS+imDNYj+d6CsrIw0NDS81DH19fWkqqqqj1pE6WteJoj+YhkxYgQhhBBlZeUug+jtxdLSkjQ2NhIdHR0CgBQXF5MpU6aw5Ldv32YdY2BgIBVEFwqFpK6ujiktLS2kqamJxMXFkTFjxpDW1lYybtw41jGGhoaEEEKD6G8JGkT/G6CrqwslJaWXOkZZWRkaGhp91CJKf8LY2Bjq6urMvq2tLfLz89HQ0AAtLS14eXmx5ia1o6enh/Xr1yM2Nha+vr4QCoUAgDNnzsDb2xscDgccDgdr1qzpUexCR0cHqqqqTLl48SK2bt0KBwcH5OfnIyYmBnFxcaw4Hh0QMjCgDoRCGaTY2NigrKwMpaWlqKiogJubGxwcHAAAJiYmCA0NxZgxYxj98PBwiEQi5OXlwdnZGe7u7ggKCmLkvr6+kJWVRWFhIfh8PjQ1NeHr6/vK7XR3d0diYiKuXbsGgUAAPp+P7Oxs3Lx585VtU/qWv0UMhEL5OxIYGIiDBw9CW1sbdXV1qKurY2RXrlyBrq4uBAIBALBWNuiM+vp6LF++HBoaGpBIJCx77RQVFUFOruvHyooVK1j7YrEY3t7e2L17N7hcLgghqKyslFoDjtL/oA6EQhnEiMVilJaWdihrdx4vS1dDf18FQgjKy8v7xDalb6BdWBQKhULpFW/8CyQrKwvLli1j1vSpq6vDV1999aabQaEMSGi3TseUl5fD0NCw03lelJdDLBZj4cKF3eq9cQdy8eJFrFmzhpm34O/v32efxBTKYON1rqg7mNDW1oZQKERycvLbbsqgICMjo8Mla17krcRANDU18e677wJoWxaaDiulUHoGdSAdIysrC0IIK00Dpfdoa2v3aCg1/W+kUCgUSq+gDoRCoVAovYI6EAqFQqH0CupAKBQKhdIrqAOhUCgUSq+gDoRCoVAoveJvu5RJeHg47t69ix07djBDittpaWnBzp07oa6uDj8/P3z//fcwNDSEtbU1o5OQkID09HQEBAQwdRKJBNu2bcPWrVuhp6cnld5z7NixTGpbgUCAH374AXfv3oWKigrmzZuHtWvXMsM0RSIRwsLCcOvWLejq6mLjxo0wMjJibP3222+IiIhAVVUVzMzM8OmnnzLD7pqbmxEeHo60tDQoKSnBysqKWUSvJ7Y74s6dO4iMjMShQ4e6XeuIQqH8PfjbfoEkJCQgJiYGkZGRUrLExEREREQwCW2Kiopw9OhRlk5wcDAOHDjAyu+cnZ2N48ePg8fjobS0FJGRkdDR0WFK+3wXQghsbGxQVFQEOzs7zJkzB3v37sW+ffsYW/b29vjll1+wYsUK6OvrY8aMGUyO6IyMDCxYsADvvvsuVqxYgdjYWLi6ujLHLlu2DCkpKbC0tMTMmTPh5eWFQ4cO9ch2R0RFRcHS0hKHDx+mM6EpFArD3/pV0tbWFjExMfDz82NN0IqKioKtrS1u3LgBoC1f+g8//ICWlhbIycmhtrYWN27cgLm5OeLj47F9+3YAQEpKCkxNTaGiogKBQAA9PT2WU2hHRkYGmZmZrHO2trYiNDQUX3/9NR48eICUlBSUlpZi6NChAICKigr4+/vj/Pnz+P777/HZZ5/B29sbADBnzhyMGTMGDx48gJGREc6ePQtVVVXGtkgkQkxMDLZt29at7Rf55ZdfcOjQIcTFxdFlIigUCou37kBaW1vx4MEDJCQkvLFzLl68GAAwe/ZspKenIyUlBebm5gDa1tS5du0ajh49yjiQOXPmoLm5GdnZ2Zg+fTquXLkCIyMjODk5ISYmhnEgV69eZewIhUJWqs4XeXFG8R9//IFRo0YBAPh8PvT09JgHPABYWlrC2dmZkT+ft53H42HKlCnIyMiAkZERy3kAbV1r7YmDurP9ItbW1pg/f77Uyq3l5eXQ1dUFADx69Ahjx46l229guzcoKChAQ0MDFRUVaG1t7ZWNF1FTU4OCggIqKipe+lh5eXm0trZCIpFIyZSUlKCkpITKykoQQl5HUyl9yFt3IBs3boSXlxeOHTv2xs7ZnqimtbUVa9euxcmTJ5kHf2xsLOzs7FiZ/pSUlDBjxgxcvXoV06dPR0JCAhYvXgxra2t8+umnqKyshKqqKjIyMpgEOxUVFfjzzz8xYcIESCQSTJ48GXv37mXFGuLj43H37l1kZ2ejsbERJ06cAACMHj0aT58+RVlZGXg8HoC2bqvKykpGfvv2babbqry8HH/++Scjfx6RSIQTJ05g165dPbL9IjIyMlBWVpb6MRcWFjIO5LfffmMecnS7b7dfBg6Hg5CQEKxbtw4ikQiqqqqIjIzEpk2bpHSTk5NhamoKQggaGxtx//59HDt2DOfOnWPpWVtb47vvvoOCggJEIhGWLVuGhw8fAmhbTuTbb7/Fpk2boKam1mGbxo4dizt37mD79u2sXOpubm7YsWMHxowZg4aGBsjLy+Pw4cPM/y2ln/Kmc6J/+eWXJCAgoE/P2ROWLl1KwsLCSF5eHlFWVibV1dWEEEKMjIxIamoquXDhAhk5ciSj7+/vTxYuXEhaW1vJsGHDSHp6OiGEkGnTppHTp0+T9PR0oq6uTsRiMSGEkMbGRpKSkkIePXpEfv/9d/LJJ58QLpdLysvLGZvR0dHks88+I4sXLyaTJ08m8fHxjGz9+vVk7NixZMeOHWTFihVk8eLFRF9fnxBCyN27d4mWlhZxcnIiO3bsIGZmZmTcuHEkPDycdY0SiYQ4OjoSOzs7Vn1XtjujoKCAACCNjY0veacpr5OXyYm+fPly8vjxY8Lj8QgAoqGhQYyMjDrUfT4nOpfLJatWrSLFxcXEz8+P0Zk6dSoRCARk3rx5UsdzuVySmppKfvzxR6mc6O1FTk6OZGZmktu3bxMPDw+m3tfXlxQXFxMrKysiLy9PABB9fX0yadIkmhP9LdFvcqLr6uqyukv6G2PHjsXkyZNx7tw53Lx5E01NTZgzZ46Unrm5OTIyMvD777+jqakJpqamANreyBISEpCamgozMzNmhJKioiLmzZsHQ0NDTJkyBT/88AOGDBnCWuHS1dUVR48exeXLl7Fnzx6sWrUK9fX1AIDIyEhERkbivffew/bt27F69WoYGBgAACZNmoTc3FzY2tpiypQpuHjxIiQSCSMH2gL1GzduhFAoxJkzZ1jX0pVtyuCBx+OhsLAQZWVlANoSQT148AAAMHnyZOTk5GD48OFSxwkEApw9exZOTk7YvXs386W5c+dOHDp0qMNVWkUiESIjI6VGHj7P3r17kZaWxhp4wuPx4OPjAycnJyQmJkIsFgMAiouLuxzYQekf9LkDmTJlCkQiUV+f5pVwdXVFdHQ0oqOj4erqChkZGSmdqVOnQl5eHkeOHMHChQuZIbM2Nja4evUq0tPTmW6wjpCRkcGQIUM6HQJrYmKC+vp65scOtMVoNmzYAFNTU5w/fx4LFixgZLq6unBycsLHH3+MgoIClJSUYObMmYzc09MTjx49ws8//8zEP56nK9uUwcHly5dhYmKC/fv3Q1NTkyWrqqpCYWFhl6kUrl+/DqFQyAyemDVrFrKysrBv3z6EhYVhyZIljG5NTQ1OnTrV6WrBpqamsLKygo+PD2uVVwsLCzx58gTXr19/lUulvCX63IHIyMhg5MiRfX2aV8LR0RF3797F6dOn4eLi0qGOrKws5s6di59++okVwP7ggw8gIyODjIwMlgPJyMhgAoytra04cuQIqqurMWfOHFRXVyMpKYkJaIpEIhw4cACjRo2SulcSiQQBAQHIysrC5s2bpdqVl5eH1atXY8eOHVBXVwfQ5jyysrIQHR2NhoYGCIVCCIVCqSG4Hdm+e/cufHx8mDdBysCloKAAM2bMgLGxMfh8PsLCwqClpQWgLYZla2uLmpqaLm2UlJRAW1sbMjIyzNcCn89HWloagoOD4eHh0W07VFVVERERARcXFzQ3N7Nkurq6ePz4MbPP5XKRmprKFEr/5m87D+R51NXVYW9vD1NTU4wYMaJTPQsLC9TV1TGjuNqxtraGmpoaK0B+8+ZNDB8+HFwuFxoaGoiKikJ8fDx0dHQgFovx+eefQ1lZGcOHD4empiZycnIQHx/PvJ25u7vD0NAQOjo6SExMRFJSEhP0fvz4MbhcLkaPHo2PPvoIjo6OTPC+rKwMR44cQXZ2NkaOHAkul8uU9sEDXdlOSkpCQEBAr0bXUPofOTk5WLJkCSZNmoR3330XiYmJL3X8yJEjIRAIICcnBzk5OezatQtRUVE4f/48fHx8On3hep6QkBCcOnUK+fn5UFRUBIfDgZycHOTl5fHs2TPWaMWamhr4+/sjKioKZmZmL329lDdMXwfRXV1dSXR0NLPfX4Lob4KWlhZSWlpKGhoaOpTX1taSoqIiUl9fLyVrbGwkT5486VBGCCHl5eWkvLyctLa2vnS7urItkUhIaWnpS9ukvBleJoj+YhkxYgQhhBBlZeUug+jtxdLSkjQ2NhIdHR0CgBQXF5MpU6aw5Ldv32YdY2BgIBVEFwqFpK6ujiktLS2kqamJxMXFkTFjxpDW1lYybtw41jGGhoaEEEKD6G+JfhNE/zsjKysLHo/HGhL8PKqqqtDX14eysrKUTFFREQYGBh3KADBfFR3Fa7qjK9scDof5GqEMbIyNjZluTaBt4mx+fj4aGhqgpaUFLy+vDuNjenp6WL9+PWJjY+Hr6wuhUAgAOHPmDLy9vcHhcMDhcLBmzZoexS50dHSgqqrKlIsXL2Lr1q1wcHBAfn4+YmJiEBcXh4kTJzLH9CQbHuXtQx0IhTJIsbGxQVlZGUpLS1FRUQE3NzdmTTQTExOEhoZizJgxjH54eDhEIhHy8vLg7OwMd3d3BAUFMXJfX1/IysqisLAQfD4fmpqaTNfpq+Du7o7ExERcu3YNAoEAfD4f2dnZTJcrpf/y1icSUiiUviEwMBAHDx6EtrY26urqUFdXx8iuXLkCXV1dZoWBjz76qFt79fX1WL58OTQ0NCCRSFj22ikqKup2sc0VK1aw9sViMby9vbF7925wuVwQQlBZWUnXXRsAUAdCoQxixGIxSktLO5S9uDxNT+lq6O+rQAhBeXl5n9im9A20C4tCoVAovYJ+gVAoA4j2bp3eDJ7oCeQNLGDYF20vLy/H5MmTpbrHKL2jubkZ//jHP7rVow6EQhmAvIkHfV/RF20fOnQo8vPzWXlvKL3n999/x/3797vVow6EQhlA0GyQHaOgoICWlpYeDQagdE9zc3OP0gfQGAiFQqFQegV1IBQKhULpFdSBUCgUCqVXUAdCoVAolF5BHQiFQqFQegV1IBQKhULpFf3WgYSHh8PT0xOFhYVSspaWFmzbto1ZyO37779HQkICSychIQHe3t6sOolEgs2bN+Ovv/5i1be2tuLzzz9HXFwcqz4uLg5r1qyBs7Mz/v3vf7NkOTk52L59O5YvXw4PDw/WqqR79uyBp6enVPn5559ZNu7cuQMvLy+pNX9aW1tx4sQJrFy5EuvWrcOtW7e6uFNd26JQKJS+ot86kISEBMTExCAyMlJKlpiYiIiICMTExABoW8Dt6NGjLJ3g4GAcOHCAlX85Ozsbx48fl1quPDAwEOHh4cjOzmbqgoKCsGPHDsyfPx9z587F+vXrmbaUlJTAxsYGKioqcHJywujRo7Fo0SIkJycDADQ1NaGjo8MqZ86cYWVei4qKgqWlJQ4fPiz10Pfz80NQUBCsrKxgaGiI+fPnIycnp9N71ZUtCoVC6TP6a0KppUuXEicnJzJ8+HAikUg6lI0cOZIQQsi///1voqamRsRiMSGEkJqaGqKoqEgsLCzId999xxwXEBBAZs+ezbL1n//8h4wZM4Y4OzuTXbt2MfVcLpckJiYy+/Hx8YTH4zEJnF5s0+rVq4mXl1eH15KdnU3U1dVJdXU1Y8vY2JikpaURAKSxsZHRbWpqImpqaiQ1NZWp27RpE1mzZk2HtruyRRl8vEpCqcFcaEKp18uASihVWFiI/Px8ppD/t9TB7NmzAQApKSmMbnl5Oa5duwZbW1umbs6cOWhubma+IK5cuQIjIyM4OTkhPj6e0bt69Sorb3ljYyOcnZ0RHh4OBQUFpr6pqQkCgQDvv/8+U7dw4UIIhUL8+eefANoSL7UjkUjw4MEDjBo1qsPrO3DgANzc3JjkPtbW1sjKysLw4cOldO/fvw+xWMyaUWthYdFpfujObDU0NDDblZWVdHuQbVMo/YG37kB+/fVXzJ07F4sWLWJKe2yjtbUVa9euxcmTJxn92NhY2NnZsbL8KSkpYcaMGbh69SqAtu6vxYsXw9raGjdu3EBlZSXEYjEyMjJYDmTHjh2wsrLCvHnzWOvzKCoqYtiwYbh9+zZTd/PmTUgkEtaP+OjRo9i7dy/mzZuHadOmYePGjVLXV1BQgEuXLmHLli1MnYyMDJSVlTtcE+jp06fQ0dFhZWTj8XgoLi7uUL8zWzdu3GC2T506RbcH2fbLoKCgAC6Xy3rpeVXU1NSgra3dq2Pl5eU7zTiopKQELS2tPlsskvKaedtdWCEhIWTLli1Sxy1dupSEhYWRvLw8oqyszHT/GBkZkdTUVHLhwgWmC4sQQvz9/cnChQtJa2srGTZsGElPTyeEEDJt2jRy+vRpkp6eTtTV1ZlursTERDJ58mQiEokIIYS4ubmxurCio6OJlpYW8fT0JB4eHsTe3p5wOBzy6NEjRuerr74iGzZsILNmzSLz5s0jDx8+lLqOjRs3EkdHxw7vTUFBgVS304ULF8jo0aNZenfu3CEASEtLS4d2OrNFGXy8TBcWh8MhoaGhpLa2lgiFQtLU1ESOHDnSoW5ycjKpr68ndXV1RCAQkNTUVOLo6CilZ21tTXJzc0l+fj558OABGT9+PCOTlZUlgYGBpLa2ttM2jR07ltTX1xMPDw9WvZubG8nNzSXNzc2kqqqK1NfXkwMHDtAurLdET7uw+v3KbGPHjsXkyZNx7tw5TJw4EU1NTZgzZw4uXbrE0jM3N0dAQAB+//13NDU1wdTUFEBbF09CQgKMjIxgZmYGOTk5VFZWYv369di3bx8zwqmsrAxNTU3IysrC9OnT4erqClNTU9y8eRM6OjowNjbGpUuX8M477zDn9Pf3Z7Y3b96MTz/9lNXVJBQKER0djWvXrvX4ejU1NVFVVcWqq66uhpqaGs0TTXkp7O3tsXTpUhgaGqKsrAwaGhrQ19fvUHfIkCHYtGkTTp48CS6XiwULFiA4OBhGRkZMj8DUqVNx8uRJrFy5kvnab4fL5SIuLg5FRUWs3oHnkZOTQ2xsLGtgC9CWKtfd3R2ffPIJrly5ArFYDH19/V5/4VDeHP3egQCAq6sroqOjMXHiRLi6unb4eTt16lTIy8vjyJEjWLhwIfOwtbGxwfHjx/Hs2TNYWloCaBtFpa2tjbCwMOb4kpISyMrK4vHjx0hLSwMAjB8/HuPHjwfQNqrL1NQUysrKHbbRxMQEFy9eZNWFhYVh6tSp+PDDD3t8rUGkU58AACAASURBVMbGxqiqqsKTJ0+YuMa9e/cwceLEHtugUIC2rs/CwkKUlZUBaHsRac8mOHnyZJw6dQpWVlZ48uQJ6ziBQICzZ8+ipKQEycnJOHLkCMrLy7Fz504cOnRIynkAgEgkQmRkJJKTk7Fq1aoO27N3716kpaVh5MiRrDb6+PhgwYIFrKHwxcXFKC4ufuV7QOlb3noMpCc4Ojri7t27OH36NFxcXDrUkZWVxdy5c/HTTz/BysqKqf/ggw8gIyPDin9MmDAB9+7dY5Vly5bBzc2NcR7Pk5CQgG+++QZ+fn4AgNzcXNy7d4+Rl5WV4fjx45g3bx5T19DQgCNHjmD79u0vda3a2tpYtGgRvv32W7S0tKC8vBwhISFwcnICANy9exc+Pj4Qi8UvZZfy9+Py5cswMTHB/v37oampyZJVVVWhsLCwy/S0169fh1AoZAazzJo1C1lZWdi3bx/CwsKwZMkSRrempganTp3qNM5iamoKKysr+Pj4sL6kLSws8OTJE5bzoAwcBoQDUVdXh729PUxNTTFixIhO9SwsLFBXV4fFixez6q2traGmpgYjI6MenzM2NhYjRozAsGHDsHXrVoSHhzMOqKysDIsWLYK6ujoMDAwwZswYjB49GqGhoczxkZGR0NTUZI0W6yk//PADsrOzMXToUBgYGGD27Nn47LPPAABJSUkICAhARUXFS9ul/L0oKCjAjBkzYGxsDD6fj7CwMGhpaQFoG/loa2uLmpqaLm20f63LyMgwXwt8Ph9paWkIDg6Gh4dHt+1QVVVFREQEXFxc0NzczJLp6uqy5kdxuVykpqYyhdLP6a9B9LdNS0sLKS4uJpWVlR3KW1tbSUVFBSkuLibNzc190oaysjLS0NDAqpNIJKS0tLRPzkfp//R2HsioUaNIfHw8uXnzZofy9PR04urqKlUvFAqJvb09kZeXJ4S0DUppl61atYpkZmay9A0MDEhLSwurLiIiguzatYsoKioSRUVF8q9//Yt4enoSeXl54urqSnJychjdIUOGEHNzc+Ls7EwIITSI/pYYNEH0t4WsrCwrYP4iMjIyzNtcX6GrqytVx+FwpGbSUyjdUVBQgE2bNuHx48dQVlZmzRPqDEtLS6ioqCAtLQ1isRglJSWsrtPq6mooKip2a8fOzg6KiorYs2cPgLZh8lZWVjAzM8OXX36JqKgojBs3Dnl5eRCJREhKSoKhoWHvL5byxhgQXVgUCuXlMTY2ZiavAoCtrS3y8/PR0NAALS0teHl5degA9PT0sH79esTGxsLX1xdCoRAAcObMGXh7e4PD4YDD4WDNmjU9il3o6OhAVVWVKRcvXsTWrVvh4OCA/Px8xMTEIC4ujjVQhI44HBhQB0KhDFJsbGxQVlaG0tJSVFRUwM3NDQ4ODgDaRg2GhoZizJgxjH54eDhEIhHy8vLg7OwMd3d3BAUFMXJfX1/IysqisLAQfD4fmpqazBDfV8Hd3R2JiYm4du0aBAIB+Hw+srOzcfPmzVe2TelbaBcWhTJICQwMxMGDB6GtrY26ujrU1dUxsitXrkBXVxcCgQAAWEvndEZ9fT2WL18ODQ0NSCQSlr12ioqKICfX9WNlxYoVrH2xWAxvb2/s3r0bXC4XhBBUVlbShUEHANSBUCiDGLFYjNLS0g5l7c7jZelq6O+rQAhBeXl5n9im9A3UgVAoA4jm5uY+XSeKdLDe2uukr9ouEAgwfvx4rF27tk/sd8WbWLerr/8uL9LQ0AA9Pb1u9agDoVAGEBKJ5I0/TF4nfdV2JSUlFBQUMBNuKa9Gfn5+j+aaUQdCoQwgOltn6u+OoqIiWlpaejVxlyJNVlYW0tPTu9Wjo7AoFAqF0iuoA6FQKBRKr6AOhEKhUCi9gjoQCoVCofQK6kAoFAqF0iuoA6FQKBRKr6AOpJ8THh4OT09PFBYWSslaWlqwbds2Zj2ixMREhISEsHTy8vLg6ekpNRs5JCQEv/76K7PP5/Oxb98+ODo6wtHREY2NjQDaJmj5+/vDwcEBrq6uiImJQWtrK3OcSCTCd999h5UrV8LT0xMPHjyQamdntgEgOTkZzs7OcHBwwNmzZzu9D1evXoWrq2u3ibTu3LkDLy8vugwGhfIGoA6kn5OQkICYmBhERkZKyRITExEREYGYmBgAbZO0fH19IZFIGJ1z587h6NGj+Pnnn5k6iUSCvXv3MjNob9y4ARMTE9TX18PFxQVOTk6QlZUFIQQ2NjYoKiqCnZ0d5syZg71792Lfvn2MLXt7e/zyyy9YsWIF9PX1MWPGDPzxxx+MvDPbQFtyrCVLluAf//gHFi1ahM8//xzh4eFS11lRUQEPDw/ExMSwru1FoqKiYGlpicOHD1MHQqG8AehEwgGAra0tYmJi4Ofnx0oZGhUVBVtbW9y4cQMAYGZmhsbGRmRnZ2PatGkA2pzMwoULER8fD3d3dwDAb7/9hubmZsyePRutra1wdXVFQEAANmzYIHXuzMxM1jlbW1sRGhqKr7/+Gg8ePEBKSgpKS0sxdOhQAG0Pe39/f5w/f75b2//zP/+DL774gkn7O3ToUHz++ef45JNPWHru7u5YuXIl/P39O71Hv/zyCw4dOoS4uDgmBSuFQulb6BfIAKD9gZiSksLUlZeX49q1a6yZt6qqqpg+fTquXr0KABAKhcjOzsb+/fuRnJzMJBG6evUqZs6cCSUlJWRlZUEgEHS6htCLOa7/+OMPjBo1CkBb15Senh7jPIC2JEQZGRkA0K3tzMxMWFhYMPvt+bHz8/OZuujoaFRVVTHOrzOsra2RlZWF4cOHd6lHoVBeH9SBvGYkEgnmz58PeXn5Vy7//e9/AbS99a9duxYnT55kzhMbGws7OzuppS3Mzc0ZB3L58mV8+OGH+OCDDzBq1CgkJycDaHMg7fndc3NzMWHCBHzzzTfQ19cHj8eDp6cnRCIRYzM+Ph7+/v6wt7dHXl4ewsLCAACjR4/G06dPUVZWxuhmZGSgsrKyW9v19fWora1lZVfU0NDAkCFDUFRUBAD466+/sG/fPsTExHS7YJ2MjAyUlZWl1lp6Pq/2N998M2i2XwYFBQVwuVypl4FXQU1NDdra2r06Vl5evtOEUUpKStDS0nojCxRSXh3qQF4zLS0tuHHjBhobG1+5tAeVCSFwdXXFhQsXUFNTA6DtzdzV1VXq/Obm5khPT4dYLEZCQgKsrKwAtCUXio+Ph1gsRkZGBuNABAIBsrOzMXr0aBQVFSEnJwcZGRn47rvvGJsVFRUoKSlBU1MTysrKmBjHuHHjsGbNGsyePRs7d+6Eg4MDMjMzmVS/XdluD4YrKCiw2q+kpASJRAKJRIK1a9ciKCgIBgYGvf57mJmZMdtfffXVoNnuCRwOB6GhoaioqEBubi4aGhpw5MiRDnWTk5NRX1+Puro6CAQCpKamwtHRUUrP2toaubm5uHPnDtLS0jB+/HhGJisri8DAQNTW1nbaprFjx6Kqqkqqm9LNzQ25ubmorq7GX3/9hbq6Ohw4cOClrre/Ymdnh8zMTFZdY2MjTExMOsypMpCgDqSPkJOTe+XyfLa3sWPHYvLkyTh37hxu3ryJpqYmzJkzR+q806dPB4fDwa1bt3DlyhVYWloCaPvhJyQkICsrCwoKCjAxMQHQ9qM3NTXF+vXrISMjA11dXXh4eCApKYmx6erqiqNHj+Ly5cvYs2cPVq1ahfr6egBAZGQkIiMj8d5772H79u1YvXo188Dvyraamhrk5ORQVVXFnKe1tRV1dXUYOnQogoKC0NLSAn19faSnp+O3334D0BaUf/r0aY//Ds+/yT7/Bj7Qt3uCvb09li5dCkNDQ+jo6IDH43XqQIYMGYJNmzZBVVUVRkZGOH78OIKDg+Hn58foTJ06FSdPnsTGjRsxZswYGBkZ4eHDhwAALpeL5ORkGBgYdLrgo5ycHGJjY5GXl8eq9/X1xddff43t27dDRUUFQ4cOxbhx43D69OmXut7+SnNzs9TgD0IImpubB/TKygB1IAMKV1dXREdHM18fHX3my8nJwczMDJGRkVBQUMCUKVMAALNmzUJjYyOio6Mxb948pgvhvffeY7qM2hGLxRgyZEiHbWgfUfV8t9Xs2bOxYcMGmJqa4vz581iwYEG3tmVlZWFkZIQ7d+4wsvaH0fjx41FUVIT6+np4eHjAw8MD3t7eAAAvLy9WtxSlc3g8HgoLC5m/VXV1NTPMevLkycjJyekwZiQQCHD27Fk4OTlh9+7d0NXVBQDs3LkThw4dYrpIn0ckEiEyMhJffPFFp+3Zu3cv0tLSWA6Ex+PBx8cHTk5OSExMZL5Mi4uLWaP5KP0T6kAGEI6Ojrh79y5Onz4NFxeXTvXMzc3x008/wdLSknEysrKyWLx4MeLi4pjuq3bdpqYmhIaGAgCePXuGiIgILFq0CNXV1UhKSmLmfYhEIhw4cACjRo3CyJEjWeeUSCQICAhAVlYWNm/e3K1tAFi9ejVCQkJQXV2N5uZm7Nu3D0uXLoWysjKOHDmCe/fuMaX9iyg7OxtOTk6oqqrCrl27wOfzX8etHZRcvnwZJiYm2L9/PzQ1NVmyqqoqFBYWdpld8Pr16xAKhcwgjlmzZiErKwv79u1DWFgYlixZwujW1NTg1KlTnX4lmZqawsrKCj4+Pqz4R/vAievXr7/KpVLeEtSBDCDU1dVhb28PU1NTjBgxolM9CwsL1NbWMvGPdmxsbFBbW8tyIEpKSrh06RKOHTsGPT09jBw5EqampvD09IRYLMbnn38OZWVlDB8+HJqamsjJyUF8fDzzEHB3d2e6SBITE5GUlMQExruyDQDbtm3D+PHjwePxoKmpiaKiIhw+fLhH9yI/Px9BQUHIysp6qXv4d6KgoAAzZsyAsbEx+Hw+wsLCmPhUYWEhbG1tmZhaZ5SUlEBbWxsyMjLM1wKfz0daWhqCg4Ph4eHRbTtUVVUREREBFxcXNDc3s2S6urp4/Pgxs8/lcpGamsoUSv+GzgPp51y8eJG1/+OPP7L27ezsYGdnx6ozMjLqsG/1448/xscffyxV/8EHHyA3NxcCgQBDhw6FvLw8AEBHRwd//PEH6urqUF1dDU1NTSgrK7OODQ0NhVAohJaWlpSsK9tA22ic06dP49ixY5BIJFJvyc9jYGDAuiYTExOUlJRg2LBhLL133313wPcrv05ycnKwZMkSjBo1CqGhoUhMTISpqWmPjx85ciQEAgETl9u1axdu3boFoC0ms2XLFhw/frxLGyEhITh16hTy8/OhqKgIDocDOTk5yMvL49mzZ9DR0WF0a2pq4O/vj3feeYeZIDvQ6WpE2UAfbUYdCIWBy+V2WK+qqgpVVdUOZYqKij0aJdWZbaDty6o3vOg8KJ1TUFCATZs24fHjx1BWVmbmBHWFpaUlVFRUkJaWBrFYjJKSEtZSMtXV1VBUVOzWjp2dHRQVFbFnzx4Abf8zVlZWMDMzw5dffomoqCiMGzcOeXl5EIlESEpKgqGhYe8vtp/B4/EgEAhYdaWlpVBQUOjwpWsgQbuwKJRBirGxMcs529raIj8/Hw0NDdDS0oKXl1eHDkBPTw/r169HbGwsfH19IRQKAQBnzpyBt7c3OBwOOBwO1qxZ06PYhY6ODvMSoqqqiosXL2Lr1q1wcHBAfn4+YmJiEBcXh4kTJzLHdDZPZCBiYWGB2NhYZjBDe1zQ3Nz8tc7NeRsM7NZTKJROsbGxQVlZGUpLS1FRUQE3Nzc4ODgAaOsCDA0NxZgxYxj98PBwiEQi5OXlwdnZGe7u7ggKCmLkvr6+kJWVRWFhIfh8PjQ1NVlDzXuLu7s7EhMTce3aNQgEAvD5fGRnZ+PmzZuvbLs/4OjoiLlz58LOzg4LFizA7NmzIS8vDx8fn7fdtFeGdmFRKIOUwMBAHDx4ENra2qirq2NNWrty5Qp0dXWZrpWPPvqoW3v19fVYvnw5NDQ0IJFIOpwEV1RUBDm5rh8rK1asYO2LxWJ4e3tj9+7d4HK5IISgsrJy0CyI2R4r2rx5M549ewZVVdVOh8kPNKgDoVAGMWKxWGop/3Ze7JfvKV0N/X0VCCEoLy/vE9v9ARkZmV4v/9JfoQ6kD6CjgCh9RVNT09tuQr+kuroa7777Lk6cOPG2mzIoqKys7NFzjDqQ18yNGzd6NDaeQukNHA4HMjIyfTL8kxDS5y8/fdV2OTk5lJb+X/bOPC6rKn3gX/ZVEWUx0cgJrXCJxBIXxAJNUBQzt3IhKWpCUjNziUQnJ5dUCLcmZbXGBSuVwJkRRAQXbCgVy4YZEl8BQXZk8eUF7+8PPtyfby8oosTi+X4+9/O595znnnvu5eU+95znOc+Tp7HOpLXR0tJqdUO4JElqSdz+CCoqKujSpcs95YQCecgolUq2bdvG559/3tZdEXRC9PX1/5AXfWvRWn03MTGhtrZWXqQqeDBSU1NJSUm5p5zwwhIIBAJBixAKRCAQCAQtQigQgUAgELQIoUAEAoFA0CKEAhEIBAJBixAKRCAQCAQtQrjxdhJycnJYt24d9vb2vPvuuxr1cXFxxMXFMWfOHJ5//nkWL16Mn58f/fv3l2WCg4Pp2rUr8+fPl8syMjLYuXMnK1euVEtveid+fn4888wzVFdXs337dlJTU+natSteXl54enrKcv/973/5/PPPycnJYdiwYSxevFgO6VBQUMDf/vY3Lly4gImJCS+++CJz5syRfewPHjyokR9i4cKF9OvXD4CzZ88SHh5OcXEx9vb2+Pn5yZn0GqO2tpYtW7bw9NNPqyVGEggEzUeMQDoJBQUFREZGsnTp0kaTBAUEBBAZGcnly5fR1tbm9OnTHD58WK5XKpV8/PHHfPzxx2p++ocOHSI1NRUdHR0sLCzUNgMDA7Zv3y6H+J41axb/+te/8PHxYcyYMfj6+hIREQFAfn4+I0eORJIkpk2bxpEjR2RFJUkSEydOJDs7Gy8vL0aPHs2qVatYvXq13I8jR46QmZmpdv2G3CI//PAD48aNY/Dgwfj6+qJQKBg1apRa6PE7ycvLw9XVlXXr1nH69OkHeu4CwaOMGIF0Irp3707v3r05cOAAb775plx+4cIFiouL1cJlu7m5kZiYyNKlSwE4ceIEdnZ2XL9+nR9//BFHR0cAjh8/jpubG927d1d7oQNs3rwZFxcXBg8eDNSPcs6ePcuQIUMA+N///sfRo0fx9vYmLCwMe3t7tm/fDoCrqys2NjasWbMGOzs7zpw5o7ai9/bt24SEhPCXv/wFqFeQM2fObDSV77/+9S/GjBmDn58fAC+++CIGBgb873//45lnntGQnzx5MlOnTpVHLwKBoGW0+gikqKgIf39/HnvsMR577DF27tzZ2pd8ZKmpqcHb21v+6m8gNDQUb29vlEqlXObm5kZycrIc8TQ2NpaXXnqJl19+mZiYGKA+EF9KSopaCtwGVCoVwcHBvP/++3LZwIEDOXLkCFAfs+nEiROMGDECgDNnzjBu3DhZ1tramkGDBpGUlASgEQ7i4sWL9O3bVz4uLCxUy1x3J4MGDeKHH36Qgwb+61//wsLCQi1U+Z0kJCTw4YcfUldX12i9QCBoHq2uQK5du8aoUaP46aef+Omnn5g7d67ai6yzoa2tjYmJCc8999wftjWEb6itrWXGjBn89NNP/Pe//wXqlcrevXuZN2+e2gtz1KhR1NXV8e9//xuoHz2MHz+eiRMnygrkhx9+AGD48OEa9/n3v/8dY2NjNRtHdHQ033zzDePGjWPQoEGMHDmS9957D4Dr16/LudIbsLa2Jjs7Wz6OiYlh7dq1TJkyhYyMDLZu3SrXFRUVsXTpUp588klGjBhBcHCwfD+TJk3ivffe49lnn2Xq1Kl8+OGHHDt2DH19/Ub/Rg3ZFX8fUiM8PFze/9vf/tZu9+8XfX19LC0tH2rMpi5durQ4sqyenl6TCaOMjIzo3r17h0/1+qjwh0xhGRgY0LNnT6A+Zk1niYXfGDo6Ojz77LNqL7/WpmvXrnz22WdIkiQbryMiIvjrX//KoUOHGDhwoNrXPNT/TUaOHEliYiLdunUjLy+P0aNHo1QqmT17Njk5OSQmJjJ69Gi1POZQ/+LdtGkTixcvVvtHz83Npba2lj59+nD16lXS09MpKyujW7duqFQqjRe6kZGRmlIrKioiNzeXW7dukZ+fz8WLF3n88ccBOHz4MLW1tXTp0oULFy6wcOFCSktLWb16NSqViqtXr9KrVy+MjIwoLCzk119/lafWmsuECRPk/cmTJ7fb/eaira1NcHAwb7zxBkqlElNTU0JDQ+WpvjtJSEjAyckJSZKorq7m559/ZufOnezfv19NbsKECWzatAl9fX2USiWvvPIKv/76K1D/2//rX/+Kn59fk4H4+vXrx/nz51myZIlaLnUfHx8++OADnnzySaqqqtDT02Pbtm0sW7bsvu+7veHl5cWyZcvUPsSqq6sZNWoUSUlJTaaL7ggIG0grYGBggIODwx96zbfffpvo6GgAvL298fHx4ZNPPiEsLIw33nij0XPc3Nw4fvw4xsbGvPTSSxgYGMiKJS4ujhMnTuDu7q5xXlxcHNevX1ezR1y/fp1JkyZx+PBhRo8eTW1tLb6+vkydOpWEhATMzc0pLS1Va6dBuTTg7e2Nt7c3AN9++y0zZ84kPz8fExMTNfuNnZ0dxcXFBAUFsXr1alasWIFCoeDcuXPo6enx008/4erqirW1NS4uLs1+hnd6bTV88LTH/eYyZcoUJk+ejJ2dHfn5+ZiZmWFjY9OorIGBAX5+fkRERGBpaYmrqytbtmzB3t5ezjo4dOhQIiIimD59OomJiWrnW1paEh0dTXZ2NkZGRo1eQ1dXl6ioKDIyMtTKAwMD8fX15a233uLYsWOoVCpsbGw6Te6MmpoajelSSZKoqanpsEExGxBeWJ0QV1dXACIjI0lNTWXq1KmNyrm5uZGamkpSUhIeHh5y+cSJE0lISODMmTON2j82btzIu+++q/ai+PHHH+nWrRujR48G6l8W/v7+JCUlIUkSgwcP5vz587K8JEn8/PPPaorhThwdHamsrJTzSP8eIyMjOfNdUlISM2bMkEdKzz33HM7Ozs3K192Zsba2JisrS36GZWVl/PLLLwA4ODiQnp5Onz59NM4rKChg3759zJo1i5UrV8qKdenSpQQFBWkoD6j34gsNDeXDDz9ssj+rVq0iOTlZTYFYW1sTEBDArFmziIuLkz3ncnJyuHjxYstvXvCHIBRIJ0RbW5s5c+awYMECpk6diomJSaNyzz33HLq6usTHx2sokLi4OI0vf4Bz586RmpqqMQ0yYMAA8vLySE1NBeoVxIEDB3B0dERLS4vXXnuNb7/9lkuXLiFJEiEhIejo6ODi4kJZWRnx8fFyzgOlUsmGDRvo27cvtra2lJWVyYoI6u1qmzdv5pVXXgFg8ODBHDlyRM4FoVAoOHv2LEOHDgXgm2++YdeuXQ/6WDscR48exdHRkU8//RRzc3O1utLSUrKysu6aXfDkyZMUFhbi7OwMwMiRI0lNTWX16tVs3bpVbf1MeXk5e/bsadLO4uTkhIeHBwEBAWr2j7Fjx3Lt2rVHXtl3VIQC6aR4e3tTVVUlTwk1hra2Ni+99BKPP/64bGsA6N+/Pz179sTV1VXDmLlhwwZef/11DYP4E088wd/+9jdeeeUVnn76afr06cPJkyfZs2cPAMOGDePjjz9m2LBhdOvWjS1btnDgwAH09fVRqVS8//77GBsb06dPH8zNzUlPTycmJgYdHR1UKhV//vOfMTIyomfPngwYMAA3Nzc++ugjuU9KpZLevXszYMAAhg4dyqJFi+Tpt4iICIKDgx/GY+1QXLlyheHDhzNw4EAUCgVbt26le/fuAGRlZeHp6dnomqE7yc3NpUePHmhpacmjBYVCQXJyMlu2bGlW8jRTU1N2797NvHnzNBI+WVlZcfXqVfnY0tKSEydOyJugfdNubSCSJPHFF1+gUCjauiv3RVZWVpukHXVwcKCwsFA+7tevn8b86p1TSA0cOHCg0fZ+P0/dwDfffNNkH+bOncvcuXMpKirC0NBQY+Tz/vvv8+6771JeXo6lpaWsnCwsLLh48SIVFRWUlZVhbm6OsbGxfJ6FhQW//PILN2/epKqqCisrKzXFZmFhwffff09NTQ0lJSUa9fv37290UeHv3Z07I+np6UyaNIm+ffsSEhJCXFwcTk5OzT7f1taWgoICdHV10dXVZdmyZZw7dw6o/wBZuHChmjG8MYKDg9mzZw+ZmZkYGhqira2Nrq4uenp6FBcXq7lnl5eXs3btWnr16kVkZGTLbrqdcTePso7ubdZuFcjJkyfZunUrc+fObeuu3BempqYMGzasrbvRptzN+GloaIihoWGjdaampnf1SOnSpctd02zq6+trjIwANWX0qHLlyhX8/Py4evUqxsbGVFVV3fMcd3d3TExMSE5ORqVSkZubq6aIy8rKmvxb3omXlxeGhoZ8/PHHQP1vwMPDAxcXF5YvX05YWBj9+/cnIyMDpVJJfHw8dnZ2Lb/Zdoa1tTUFBQVqZXl5eejr63f432a7VSBQP7xdvnx5W3fjvkhISGDdunVt3Q2BQJ66apim8vT0JDMzk6qqKrp3787rr7/Orl27NEbMPXv2xMPDgw0bNhAYGCiPbPfu3cuKFSuYOXMmALNnz26W7eL3C0APHjxIfHy8PHKJjIwkOjqa2bNnk56eDtDkOpGOyNixY4mKimLEiBFYW1tz69YtQkJCcHNza/V86q1Nx+69QCBokokTJ5Kfn09eXh5FRUX4+Pgwbdo0oN7LLSQkRG21/q5du1AqlWRkZDB37lx8fX3ZuHGjXB8YGIiOjg5ZWVkoFArMzc1lF98HwdfXl7i4OJKSkigoKEChUJCWlsbZs2cfuO32wIwZMxgzZgxeXl64urri7OyMnp4eAQEBbd21B6Zdj0AEAkHLWb9+PZs3mAlMdAAAIABJREFUb6ZHjx5UVFRQUVEh1x07dgwrKyt5amXUqFH3bK+yspKpU6diZmZGXV2dWnsNZGdny+7VTfHqq6+qHatUKlasWMHKlSuxtLREkiRKSkrkMDsdnQZb0XvvvUdxcTGmpqadZjG1UCACQSdGpVLJMcJ+z+/n5ZvL3Vx/HwRJkrhx40artN0e0NLS6jSLIxsQCkQg6EB0lq/yh01lZSUWFhYkJCS0dVc6BdnZ2fK6rLshFIhA0MFoLdfPPyqsRmv0X6VSUVlZydGjRx9623dDW1u71Q3hkiT94ZGjKyoqGDBgwD3lhAIRCDoQurq6HT5+Umv0v1u3btTW1rJp06aH3vajSGpqKikpKfeUE15YAoFAIGgRQoEIBAKBoEUIBSIQCASCFiEUiEAgEAhahFAgAoFAIGgRQoEIBAKBoEW0uRtveno6JSUlbd0NQQv48MMPqaurY9OmTRq+/f/973/5/PPPcXJyYvbs2Xz++efY2dmp5R2PjY0lJSVFLfhkXV0dixcvZtGiRYSHhzf62xg3bpyczGjfvn18//33SJLEyJEj8fHxkcNElJWVERQUxIULF7C1tWXZsmU89thjGu3dvn2bDz74gOHDh8uxoho4f/48oaGhBAUFqYXoOH/+PGFhYVy/fp1+/fqxYMECevXqddfnFR0djUKhYMmSJXeVEwg6Cm0+Avnf//7H4MGD27obghbw5Zdf8uWXX3L8+HGNup07dxIZGUl8fDxQv7J1x44dajJbtmxhw4YNarlH0tLS+OKLL7C2tsbc3BwLCwu1be/evXICouDgYD766CMmTZrErFmz2LNnD2+//bbc1qRJkzh16hTTp0+npKSE0aNHU11drdHX9evXs2vXLtLS0tTKw8LCcHd3Z9u2bWorwFNTU5kwYQLW1tbMnDmTa9eu4eTk1GRyppqaGvz9/fH19ZXz1gsEnYE2H4EAHD9+/KFE9RT88Xh6ehIeHi7nYYf6VcFff/01EydOlMvc3Nz429/+Rm1tLbq6uty8eZPTp0/j5uZGTEyM/FV+/PhxnJycMDEx4f3331e71o8//khQUBDz5s0D6kcwfn5+TJ8+HQATExM51PiZM2dIS0sjPz9fLh88eDB///vf8fHxkdtMS0sjLCxMTo/bwPfff09QUBDR0dFyStcGhg0bxn/+8x85d8mUKVPo2bMnycnJaiOsBlauXEl+fj4bN24kNDT0/h6wQNCOafMRiKBjM2vWLL777ju1r++YmBieeeYZtSmd0aNHU1NTI3/lHzt2DHt7e2bNmkVMTIwsl5iYiJubW6PX2rBhAz4+PnTt2hWAQYMG8Y9//ENOcvSPf/yDESNGAPUKZMSIEXJWRC0tLdzc3NTSpFZXVzN37lx27dqFvr6+2rUmTJhAamoqffr0abQvv098VVdX12RypTVr1sjpewWCzkS7GIF0JkxMTCguLmbWrFlt3ZVWw9DQkPDwcAD+9Kc/4eDgwIEDB3jzzTeB+qmfN954g59++kk+x8jIiOHDh5OYmMiwYcOIjY1l/PjxTJgwgbfffpuSkhJMTU05depUo6PRK1eucPjwYf7zn//IZZ988gne3t48++yzWFpa0rVrV6KiogC4fv26RnZCa2trtbS+H3zwAR4eHrz44ot8/fXXarJaWloYGxs3K+zG119/jaWlpcZIpYEGJfb7tk6fPi0rvG+++YapU6fec78l6OvrY2ZmRlFRUbMC5DWHLl26oK+vT1FR0X2fq6enx+3btxuN72RkZISRkRElJSUdPmTLo4BQIA8ZJycnPvvssxaHyu4I6OnpsWbNGqD+pejt7U14eDhvvvkm169f59SpU+zfv19NgUD9NFZiYiLLli3j6NGjREdHY2VlxXPPPcfRo0extbVFR0eHF154QeOamzZtwsvLC1tbW7mstLSUgoIC+vXrx82bN/ntt9+4du0a5ubmqFQqjS9+IyMj+aV19OhRTp8+TWpq6gM9i3PnzrF48WK+//77+x5h9O7dW95/6qmn7mu/OWhraxMcHMwbb7yBUqnE1NSU0NBQ/Pz8NGQTEhJwcnJCkiSqq6v5+eef2blzJ/v371eTmzBhAps2bUJfXx+lUskrr7zCr7/+CtRnEfzrX/+Kn59fk6mH+/Xrx/nz51myZIlaLnUfHx8++OADnnzySaqqqtDT02Pbtm0sW7bsvu65PeLl5cWyZcsYPny4XFZdXc2oUaNISkq6axrn9o5QIK3AnfaAzsrUqVMJCgoC6jOuLVq0iIyMDL799lumTJkif3XfiZubG+vWrePHH3/k1q1bODk5AfUvpdjYWOzt7XFxcdFISFRYWEh4eDhJSUlq5V5eXnh5efHRRx8BEBoaiqurKxkZGZibm3Pt2jU1+bKyMrp160ZJSQnz589n9erVnDt3DoD8/Hxu3bpFampqs3Pap6en4+XlRVRUlHwv98Pjjz8u7w8cOPC+9pvDlClTmDx5MnZ2duTn52NmZoaNjU2jsgYGBvj5+REREYGlpSWurq5s2bIFe3t7eUQ4dOhQIiIimD59OomJiWrnW1paEh0dTXZ2NkZGRo1eQ1dXl6ioKDWnCajPdOjr68tbb73FsWPHUKlU2NjYdJrcGTU1NRqjLUmSqKmp6fCjrHahQEpLS/n444/Vyq5evaqRq1nQPunatSteXl5ERETw7bffsmvXrkblhg4dip6eHtu3b2fcuHFy3uuJEyfyxRdfUFxcjLu7u8Z5W7duZejQoTz//PNyWWVlJf/+9785ePCgXObj48P777/PpUuXGDx4sDyd1cClS5cYNGgQubm59OjRg61bt8p1ubm56OjocPXqVZKTk+95zz///DPu7u588cUXeHh43FO+LbC2tiYrK4v8/HygXoE2JINycHBgz549eHh4aCjagoIC9u3bR25uLgkJCWzfvp0bN26wdOlSgoKCNJQHgFKpJDQ0lISEBNmR4fesWrWK5ORktVGktbU1AQEBuLq6quVXz8nJIScn54GfgaB1aRdG9PT0dPT09DAwMJA3fX19tSGfoH3j7e3N559/Tl1dXZO2AB0dHcaMGcPBgwfVXrpDhgxBS0uLU6dOaRjQq6qq2L59u8baCRMTE/70pz+pKZCjR49SW1uLvb09L7/8MuXl5Xz11VcAnD17ltjYWGbMmMGAAQO4dOmS2vbKK6/g4+PTbOXh5ubGX/7yF0aMGEFhYSGFhYWyI8GFCxcICAiQjfttxdGjR3F0dOTTTz/F3Nxcra60tJSsrKy7Zhc8efIkhYWF8t9z5MiRpKamsnr1arZu3SqvxQEoLy9nz549TebGcHJywsPDg4CAAPnDAWDs2LFcu3ZNTXkIOg7tQoFAvatjQECAvM2ZM0djDl3QfnF1daVHjx6yi21TjB07loqKCsaPH69WPmHCBLp06YK9vb1aeWhoKObm5nh6emq0tW/fPqKiorC1teWpp57Cz8+PAwcO0KNHD4yNjdm/fz8ffvgh3bp1w83Njc8+++yhrDnatm0beXl5+Pj4YGlpKW8NrsDx8fGsW7euRQbmh8mVK1cYPnw4AwcORKFQsHXrVrp37w5AVlYWnp6eTa5daaBhtKalpSWPFhQKBcnJyWzZsoV33nnnnv0wNTVl9+7dzJs3j5qaGrU6KysreV0P1E+FnThxQt4E7Zt2MYUl6JiUlpbK+9ra2igUCrX64OBgjXPeffdd3n33XY3yL7/8stFr+Pv74+/v32jd888/z4ULF6ioqKCmpkZ+OTbw0ksvce3aNQoKCrCwsNCwrdzJ7t27Gy1/4oknNOapd+7cyc6dO5tsa/HixcyePVvDC8zb2xtvb+8mz2sN0tPTmTRpEn379iUkJIS4uLj7stfY2tpSUFCArq4uurq6LFu2TLYbaWtrs3DhQjVjeGMEBwezZ88eMjMzMTQ0RFtbG11dXfT09CguLsbCwkKWLS8vZ+3atfTq1YvIyMiW3XQ7424ZGFsru+QfhVAggg7P3bxYdHR06Nmz5x/Ym/oX6++VR1tz5coV/Pz8uHr1KsbGxlRVVd3zHHd3d0xMTEhOTkalUpGbm6s2LVdWVtbk2pc78fLywtDQULZzGhoa4uHhgYuLC8uXLycsLIz+/fuTkZGBUqkkPj4eOzu7lt9sO8Pa2lrDKzMvLw99fX2MjY3bqFcPh3YzhSUQCB4uAwcOlBddQn3UgMzMTKqqqujevTv+/v6NKoCePXsyf/58oqKiCAwMpLCwEIC9e/eyYsUKOQ/47Nmzm2W7sLCwwNTUVN4OHTrEokWLmDZtGpmZmURGRhIdHc2gQYPkc+60k3R0xo4dS1RUlOzMcOvWLUJCQnBzc2v1fOqtTcfuvUAgaJKJEyeSn59PXl4eRUVF+Pj4yMEiHR0dCQkJ4cknn5Tld+3ahVKpJCMjg7lz5+Lr68vGjRvl+sDAQHR0dMjKykKhUGBubv5QQhD5+voSFxdHUlISBQUFKBQK0tLSOHv27AO33R6YMWMGY8aMwcvLC1dXV5ydndHT0yMgIKCtu/bAiCksgaCTsn79ejZv3kyPHj2oqKigoqJCrjt27BhWVlby1MqoUaPu2V5lZSVTp07FzMyMuro6tfYayM7OvqutCeDVV19VO1apVKxYsYKVK1diaWmJJEmUlJSoBbDsyDTYit577z2Ki4sxNTWVI0Z3dIQCEQg6MSqViry8vEbrWhot4W6uvw+CJEncuHGjVdpuD2hpaXWaxZENCAUiEAg6PHV1dejp6TWpLAX3R1lZWbNWyQsFIhB0IDrLtM7DpqysjB49emikAPgjaG1DuCRJf3jIE6VS2ayQTEKBCAQdiHvZFx5Vunfvjkql4u9//3tbd6VTkJqaSkpKyj3lhBeWQCAQCFqEUCACgUAgaBFCgQgEAoGgRQgFIhAIBIIWIRSIQCAQCFqEUCACgUAgaBGd3idw165dXLhwgQ8++IAnnnhCra62tpalS5fStWtX1qxZQ1xcHBkZGSxatEiWycjIICQkhICAALWorsHBwTzzzDPk5+fL4a3vpG/fvixZsoSamhoiIyNJSkqitraWZ599lgULFjSaMzoxMZHIyEh27dqFnp6eRv3OnTspLCzUyN5YWFjIhg0bmD9/Ps8884xcfvDgQY2cCgsXLqRfv35NPq/z588TGhpKUFCQcBkVCAR3pdOPQGJjY4mMjCQ0NFSjLi4ujt27d8t5ByRJIjAwUC1/8f79+9mxYwdHjhyRy+rq6li1ahVaWlqYmppiYWGhtp05c4bTp08DsHTpUg4fPoyzszOvvvoq//jHP5gwYYJGX4qKinjnnXeIjIzUyJ8MkJKSwooVK4iNjVUrb8jhvXPnTrXEPABHjhwhMzNTrW+NKaYGwsLCcHd3Z9u2bWLBmkAguCePxCemp6cnkZGRrFmzRm3VaFhYGJ6envLL3sXFherqatLS0njhhReAeiUzbtw4YmJi8PX1BeCHH36gpqYGZ2dnjIyM5Ex0UB+qeefOnWzevBmAoKAgtWs6ODjQr18/iouL1RIg+fr6Mn36dNauXavR//Lyct544w3+/Oc/q+Wjzs/PZ+rUqYSHhzeapKmgoICZM2feM0sgwPfff09QUBDR0dFNpqQVCASCO+n0IxBAfiEeP35cLrtx4wZJSUlqqVJNTU0ZNmyY/JIuLCwkLS2NTz/9lISEBDkJT2JiIiNGjMDIyEjjWuHh4djY2DBmzBhAM8zBxYsX6dGjh1qehvDwcEpLS2UF9Xv8/f2ZPXs2AwcOVCu3trbm119/ZezYsY2OGAoLC9Wyvd2NCRMmkJqaSp8+fZolLxAIBO1ageTn57NmzZoWbzk5OQDcvn2bOXPmEBERIbcdFRWFl5eXhhJwc3OTFcjRo0d5/vnnGTJkCH379iUhIQGoVyBubm4a/b19+zZbtmxhyZIlauXnz59nw4YNvPXWW6xfv57o6GjZvvDbb7+xevVqIiMjG01vefDgQTIyMggICGg0Hk5DNr7G6oqKili6dClPPvkkI0aMIDg4uNHpMaiPFGpsbNxoO0lJSWK/nez/3o7XHPT19bG0tHyoMZu6dOnS4siyenp6TSaMMjIyonv37h0+1eujQrtVIC4uLixbtkwOJNaSbcuWLUD9y9Xb25vvvvuO8vJyoP6rv7H81G5ubqSkpKBSqYiNjcXDwwOoT84TExODSqXi1KlTjSqQb775hlu3bjF9+nS18oqKCnJycigrK6OyslKeMqurq2POnDls3LiR3r17a7SXm5vLkiVL+Oqrr1qUoe3w4cN8/fXX/POf/2TJkiVs2rSJTz755L7buVOpiP223b8ftLW1CQkJoaioiMuXL1NVVcX27dsblU1ISKCyspKKigoKCgo4ceIEM2bM0JCbMGECly9f5vz58yQnJ/P000/LdTo6Oqxfv56bN2822ad+/fpRWlrKW2+9pVbu4+PD5cuXKSsr47fffqOiooINGza06L7bG15eXpw5c0atrLq6GkdHx0ZzqnQk2rUNpLEX/P3i5eUF1P9wHRwc2L9/P4MGDeLWrVuMHj2aw4cPq8kPGzYMbW1tzp07x7Fjx/jwww+B+n+cWbNmMXfuXPT19XF0dNS41meffcZ7772nYageNWqUnLAnJyeHfv36MXLkSM6cOUNtbS02NjakpKTI+RlOnz7NM888wxtvvIG7uzvXr1/n+vXrZGRkcPPmTVJSUhgyZMg98ynfmSLUzs6O4uJigoKCWL169X09w4bpOLHf9vtZWVk0lylTpjB58mTs7OzIz8/HzMwMGxubRmUNDAzw8/MjIiICS0tLXF1d2bJlC/b29nLWwaFDhxIREcH06dPVbHEAlpaWREdHk52d3ejULtQHgoyKiiIjI0OtPDAwEF9fX9566y2OHTuGSqXCxsam0+TOqKmp0Rj5S5JETU3NHx5l92HTrhXIw8bb25vw8HAGDRqEt7d3o8NkXV1dXFxcCA0NRV9fn+eeew6AkSNHUl1dTXh4OC+++KLGiCAxMZHLly83acdowMbGBmtra3777Teys7OprKzknXfeAf4/VLe/vz8BAQGUlJSQk5MjR8UsKyuTvbUOHTqEnZ3dfd2/kZGRcM19hLC2tiYrK0vOxV1WViYng3JwcGDPnj14eHhw7do1tfMKCgrYt28fubm5JCQksH37dm7cuMHSpUsJCgrSUB5QH/47NDSUhIQEZs6c2Wh/Vq1aRXJyMra2tmp9DAgIwNXVVS2/ek5OjjwFLWi/tNsprNZgxowZXLhwga+//vqunklubm4cPHgQd3d3Wcno6Ogwfvx4oqOjG52+2rhxI2+++SZmZmZq5bGxsbLxHeptLzk5OTg7O7N9+3YuXbokb/Hx8QCkpaUxa9Yszp07p1a/bt06Bg8ezKVLl+6pPMrKykhKSpK/cK5du8bmzZtlj7HS0lKWLVuGQqFoxpMTdESOHj2Ko6Mjn376Kebm5mp1paWlZGVl3TW74MmTJyksLJSdUEaOHElqaiqrV69m69atTJo0SZYtLy9nz549TdpZnJyc8PDwICAgQO3ja+zYsVy7dk1NeQg6Do+UAunatStTpkzBycmJxx9/vEm5sWPHcvPmTdn+0cDEiRO5efOmhgJJT08nPj6ehQsXarQVFRWFubk5NjY2mJmZ8cknn3DgwIG7LuZ7GKhUKv785z9jZGREz549GTBgAG5ubnz00UcAZGZmsnHjRlJTU1u1H4K248qVKwwfPpyBAweiUCjYunWr7DqelZWFp6enbBNsitzcXHr06IGWlpY8WlAoFCQnJ7NlyxZ59Hw3TE1N2b17N/PmzaOmpkatzsrKSm39kqWlJSdOnJA3Qfum089nHDp0SO34q6++Ujv28vKS7SQN2NvbNzo3+dprr/Haa69plA8aNAiVStXo9ffv349SqaSoqAgjIyONL8E76d27913nRGfPns3s2bMbrfv93LiFhQW//PILN2/epKqqCisrK7UpO0dHR3Jzc3nsscfUznviiSc6/Lys4P9JT09n0qRJ9O3bl5CQEOLi4nBycmr2+ba2thQUFKCrq4uuri7Lli2TIy9oa2uzcOFCvvjii7u2ERwczJ49e8jMzMTQ0BBtbW10dXXR09OjuLhYzdW8vLyctWvX0qtXL3mBb0fnbh5lHd3brNMrkPaAgYEBvXr1apNrd+nSpdGwKYCG8hB0Xq5cuYKfnx9Xr17F2NhYbVq1Kdzd3TExMSE5ORmVSkVubq7ah1JZWRmGhob3bMfLywtDQ0M5BI+hoSEeHh64uLiwfPlywsLC6N+/PxkZGSiVSuLj4+/bvteesba2lh1kGsjLy0NfX/+ejjDtnTafwmpqXYJAIHgwBg4cqLZg1dPTk8zMTKqqqujevTv+/v6NKoCePXsyf/58oqKiCAwMpLCwEIC9e/eyYsUKtLW10dbWZvbs2c2yXVhYWGBqaipvhw4dYtGiRUybNo3MzEwiIyOJjo5W8xpsidt6e2Xs2LFERUXJzgy3bt0iJCQENze3Vs+n3tq0ee9LSkqQJIm//vWvbd0VgaBTMXHiRPLz88nLy6OoqAgfHx+mTZsG1E9hhoSE8OSTT8ryu3btQqlUkpGRwdy5c/H19WXjxo1yfWBgIDo6OmRlZaFQKDA3N5ddfB8EX19f4uLiSEpKoqCgAIVCQVpaGmfPnn3gttsDM2bMYMyYMXh5eeHq6oqzszN6enoEBAS0ddceGK3Ro0dLd650fdg899xz2NrayraIFStWYGZmxvLly4H6r6Sff/4ZlUolXEwFgnswfPjw+3qx6unp0aNHDyoqKjQWrVlaWmpMrTQHMzMz6urqHvoiOC0tLSwtLZEkiZKSkvsK6GllZUVtbS2t+S57UCRJori4GFNTUwwMDNq6O3clNTWVlJQUwsPDm5QZNWqUsIEIBJ0ZlUpFXl5eo3UtUR7AXV1/HwRJkrhx40artN0e0NLS6jSLIxto8yksgUAgEHRMxAhEIOhAiDwtjVNUVESvXr2YNWvWH37t1jaEN8T2+yNRqVSMHTv2nnJCgQgEHYjO5J30MDE3N6eiooL9+/e3dVc6BWlpafz73/++p5xQIAJBB6KjLzxrLbS1tbl9+3aTa54E94eRkVGzfmvCBiIQCASCFiEUiEAgEAhahFAgAoFAIGgRQoEIBAKBoEUIBSIQCASCFiEUiEAgEAhaxCOhQHbt2sWCBQsazSddW1vL4sWL5aBwcXFxBAcHq8lkZGSwYMECjZAQwcHB/POf/5SPFQoFq1evZsaMGcyYMYPq6mqgPmTE2rVrmTZtGt7e3kRGRnL79m35PKVSyaZNm5g+fToLFizgl19+0ehnU23X1NSwfft2Zs6cyRtvvEF0dHSjzyA6OprNmzc342nB+fPn8ff3F4vWBALBXXkkFEhsbCyRkZGEhoZq1MXFxbF79245eY0kSQQGBqqFmd+/fz87duzgyJEjclldXR2rVq2SfaVPnz6No6MjlZWVzJs3j1mzZqGjo4MkSUycOJHs7Gy8vLwYPXo0q1atYvXq1XJbU6ZM4fvvv+fVV1/FxsaG4cOHc/HiRbm+qbYBXnnlFY4fP467uzsjRozA39+foKAg+dyamhr8/f3x9fVtUrncSVhYGO7u7mzbtk0oEIFAcFcemYWEnp6eREZGsmbNGrXQA2FhYXh6enL69GkAXFxcqK6uJi0tjRdeeAGoVzLjxo0jJiYGX19fAH744Qdqampwdnbm9u3beHt7s27dOt58802Na585c0btmrdv3yYkJIS//OUv/PLLLxw/fpy8vDy6desG1IdlWLt2LQcOHLhn2/v27cPU1FQ+ViqVREZGsnjxYgBWrlxJfn4+GzdubFSB3sn3339PUFAQ0dHRch5sgUAgaIp2o0AOHDjQKmEaXn75ZQCcnZ1JSUnh+PHjck7zGzdukJSUxI4dO2QFYmpqyrBhw0hMTOSFF16gsLBQzk0watQoqqqqMDY2JjExkREjRmBkZMSZM2coKChgzpw5jfbh97FyLl68SN++fYH6qamePXvKygPqM8HNnTsXqA+rfLe271QeUD8yujNJ0Jo1azAxMWlWetAJEybw0ksvNRql9eeff2bAgAFivx3s3y/6+vqYmZlRVFSkNnX6IHTp0gV9fX2Kioru+1w9PT1u377daDI5IyMjjIyM5DxBgvZNu5nCCg8P57vvvnvo25o1a4D6r/45c+YQEREhXzMqKgovLy+MjIzU+uLm5kZiYiIAR48e5fnnn2fIkCH07duXhIQEABITE2VFdPnyZQYMGMAnn3yCjY0N1tbWLFiwAKVSKbcZExPD2rVrmTJlChkZGWzduhWAP/3pT1y/fl3OVgZw6tQpSkpKmt12A0qlki+//JK33npLLjMxMQFo1j+jlpYWxsbGjcpevnxZ7LeT/eaira1NSEgIRUVFXL58maqqKrZv396obEJCApWVlVRUVFBQUMCJEyeYMWOGhtyECRO4fPky58+fJzk5maefflqu09HRYf369dy8ebPJPvXr14/S0lK13yiAj48Ply9fpqysjN9++42Kigo2bNhw3/fcHvHy8uLMmTNqZdXV1Tg6Oj70nCp/NO1mBLJ8+XJcXV1bpW0vLy8kScLb2xsHBwfKy8vp2rUr4eHh7NixQ35ZN+Dm5sZnn32GSqUiNjYWDw8PoD7DW0xMDOPHj+fUqVOsXbsWqDeSp6WlMX/+fLKzsykoKODll19m06ZNfPTRR0D9tFRubi63bt0iPz+fixcv8vjjj9O/f39mz56Ns7MzkydPJisri4qKCrp3797stqFeQc6bN4/+/fvLo5eHyauvvir228l+c5kyZQqTJ0/Gzs6O/Px8zMzMsLGxaVTWwMAAPz8/IiIisLS0xNXVlS1btmBvby87mAwdOpSIiAimT58uf2A1YGlpSXR0NNnZ2RofZA3o6uoSFRVFRkaGWnlgYCC+vr689dZbHDt2DJVKhY2NTafJnVFTU6Mx2pIkiZp1HglnAAAgAElEQVSamg4/ymo3I5A/gn79+uHg4MD+/fs5e/Yst27dYvTo0Rpyw4YNQ1tbm3PnznHs2DHc3d2B+q+v2NhYUlNT0dfXx9HREaj/8nJycmL+/PloaWlhZWXFO++8Q3x8vNymt7c3O3bs4OjRo3z88cfMnDmTyspKAEJDQwkNDeWpp55iyZIlvP766/Tu3bvZbUuSxLvvvkthYSF79+5ttecn6FhYW1uTlZUlj27LyspkDz8HBwfS09Pp06ePxnkFBQXs27ePWbNmsXLlSqysrABYunQpQUFBGsoD6ke/oaGhfPjhh032Z9WqVSQnJ6spEGtrawICApg1axZxcXGoVCoAcnJy1BxJBO2TR0qBQP2LPDw8nPDwcLy9vRuNOKmrq4uLiwuhoaHo6+vz3HPPATBy5Eiqq6sJDw/nxRdflG02Tz31FNnZ2WptqFSqJtNWNnhU3Tlt5ezszJtvvomTkxMHDhyQR2PNaXvBggX897//5ciRI2r2D8GjzdGjR3F0dOTTTz/F3Nxcra60tJSsrKy7Zhc8efIkhYWFskPFyJEjSU1NZfXq1WzdupVJkybJsuXl5ezZs6fJ3BhOTk54eHgQEBCgZuscO3Ys165d4+TJkw9yq4I24pFTIDNmzODChQt8/fXXzJs3r0k5Nzc3Dh48iLu7u6xkdHR0GD9+PNHR0bL9o0H21q1bhISEAFBcXMzu3bt5+eWXKSsrIz4+XjZeKpVKNmzYQN++fbG1tVW7Zl1dHevWrSM1NZX33nvvnm1DvfJITU0lPDycqqoqCgsLKSwsbJYLbmlpKcuWLUOhUDT38Qk6EFeuXGH48OEMHDgQhULB1q1b5anRrKwsPD09KS8vv2sbubm59OjRAy0tLXm0oFAoSE5OZsuWLbzzzjv37IepqSm7d+9m3rx51NTUqNVZWVlx9epV+djS0pITJ07Im6B988gpkK5duzJlyhScnJx4/PHHm5QbO3YsN2/elO0fDUycOJGbN2+qKRAjIyMOHz7Mzp076dmzJ7a2tjg5ObFgwQJUKhXvv/8+xsbG9OnTB3Nzc9LT04mJiZG/xHx9fbGzs8PCwoK4uDji4+Oxtra+Z9v5+fls376dtLQ0bG1tsbS0lLezZ8/e81lkZmayceNGUlNTW/IoBR2A9PR0Jk2axODBg3niiSeIi4u7r/NtbW0pKChAV1cXXV1dli1bRlhYGAcOHCAgIOCuH2ENBAcHs2fPHjIzMzE0NERbWxtdXV309PQoLi7GwsJCli0vL2ft2rWEhYXh4uJy3/fbHrlbXo2Ont+l3RjRW5NDhw6pHX/11Vdqx15eXnh5eamV2dvbN2rgeu2113jttdc0yocMGcLly5cpKCigW7du6OnpAWBhYcHFixepqKigrKwMc3NzjI2N1c4NCQmhsLCQ7t27a9TdrW1ra+tmG+G8vb3x9vZWK3N0dCQ3N5fHHntMrfyJJ57o8MY9gTpXrlzBz8+Pq1evYmxsTFVV1T3PcXd3x8TEhOTkZFQqFbm5ubKNAuptKs2ZMvXy8sLQ0JCPP/4YAENDQzw8PHBxcWH58uWEhYXRv39/MjIyUCqVxMfHY2dn1/KbbWdYW1truMbn5eWhr6/f6P97R+KRG4G0NpaWlvIL/k5MTU2xsbFp9AdjaGhI79697/ljaqrtB+H3ykPQeRg4cCBdu3aVjz09PcnMzKSqqoru3bvj7+/fqALo2bMn8+fPJyoqisDAQAoLCwHYu3cvK1asQFtbG21tbWbPnt0s24WFhQWmpqbydujQIRYtWsS0adPIzMwkMjKS6OhoBg0aJJ/TmVL3jh07lqioKNnm2TAl7ebm1ur51Fubjt17gUDQJBMnTiQ/P5+8vDyKiorw8fFh2rRpQP3oMyQkhCeffFKW37VrF0qlkoyMDObOnYuvry8bN26U6wMDA9HR0SErKwuFQoG5ubns4vsg+Pr6EhcXR1JSEgUFBSgUCnnxbmdgxowZjBkzBi8vL1xdXXF2dkZPT4+AgIC27toD80hMYQkEjyLr169n8+bN9OjRg4qKCrVFa8eOHcPKykqeWhk1atQ926usrGTq1KmYmZlRV1fX6CK47OxsdHXv/lr5/ZoWlUrFihUrWLlyJZaWlkiSRElJSaeJxaatrc3ChQt57733KC4uxtTUtEkPzY7GH65Ahg0bxpw5c+RVps2ZixUIBC1DpVJpRJFuoLGQNc3hbq6/D4IkSdy4caNV2m4PaGlpdZrFkQ384QrEy8uLa9euyccjRoxoUZgGgUAgELQtbTKFdWfgQG1tbbS0tDq8O5tA8EfQEBKjNf5f/ijPu9boe3FxMYMGDWL58uUPve1HEZVKhYODwz3l2oUNRFdXl+TkZF566aW27opA0K5peMl3ZDfr1ui7ubk5V69eZffu3Q+97UeRH374gR9//PGecu1CgQCdZtGQQNCa3MtA/aiip6eHlpYWQ4YMaeuudApKS0u5dOnSPeWEG69AIBAIWkSbKxBTU1Nh/xAIBIIOSJsrECsrK7EaWiAQCDogba5AADlUgkAgEAg6Du1CgQgEAoGg4yEUiEAgEAhahFAgHYxdu3axYMECsrKyNOpqa2tZvHixHODu888/JzY2Vk0mNjaWFStWqJXV1dXx3nvv8dtvvwFw9uxZ3n77baZNm0ZgYKBaeImCggLWrl3LtGnT8Pb2JjIyUk6W9Xt27tzJJ598olb2IG2XlZWxevVqpkyZwqJFi7h+/fo9n1d0dDSbN2++p5xAILh/hALpYMTGxhIZGUloaKhGXVxcHLt37yYyMhKoD2y3Y8cONZktW7awYcMGtbzUaWlpfPHFF1hbW/PDDz8wbtw4Bg8ejK+vLwqFglGjRqFSqZAkiYkTJ5KdnY2XlxejR49m1apVrF69WqMvKSkprFixQk2BPWjbkyZN4tSpU0yfPp2SkhJGjx5NdXV1o8+ppqYGf39/fH19iY6Ovp9HLBAImsvo0aOl1sTBwUGaPHlyk/Wenp6SiYmJlJiY2Kr96CxMnjxZmjVrltSnTx+prq6u0TpbW1tJkiTpH//4h9SlSxdJpVJJkiRJ5eXlkqGhoTR27Fhp06ZN8nnr1q2TnJ2dJUmSpLVr10qenp5ynUqlkrS1taVffvlFkiRJ45q7du2SBg0apFZWVlYm2dnZScuXL5eGDRsmlz9I26dPn5ZMTEykiooKSZIk6fbt29LAgQOl3bt3N/qclixZIk2bNk368ssv1frQ0XFycpIAsf1u69Wrl2RlZdXWf55OQ0JCgrRgwYK7yowcOVJqN8taMzMzMTc3b+tutGueffZZAJydnUlJSeH48eNyat0bN26QlJTEjh07OH36NACjR4+mpqaGtLQ0hg0bxrFjx7C3t2fWrFlERkayZMkSABITE+V2Bg0axLZt28jLy6Nnz57861//wsLCQs4b8fsEOBcvXqRv375qZf7+/syePRs7OzsSExPl8gdp+8yZM4wYMQITExOgPp6Sm5sbJ06cwMfHR+NZrVmzBhMTE3k01kBZWRlmZmYA5Ofny6mDO8q+qampxr0KBG1Fu1Ag3bp1IygoSIRpuAeTJ08G4Pbt28yZM4eIiAj5xR8VFYWXlxdGRkayvJGREcOHDycxMZFhw4YRGxvL+PHjmTBhAm+//TYlJSWYmppy6tQp2W4yadIkfv75Z5599llGjRrFf/7zH44dO4a+vr7cbkxMDBcuXCAtLY3q6mq+/PJLue7gwYNkZGQQFhbG3r171fr/IG1fv35dfok2YG1tzfnz5xt9Vg2KRvpd3KW0tDQ55tp3333HO++806H2n376aeLj4xu956bQ19fHzMyMoqKiJu1V90uXLl3Q19enqKjovs/V09Pj9u3bcmDIOzEyMsLIyIiSkpIOHe/rkaE9TGENHDiwVfvQmZg8ebK0detWKSMjQzI2NpbKysokSZIke3t76cSJE9J3330nT2FJUv200bhx46Tbt29Ljz32mJSSkiJJkiS98MIL0tdffy2lpKRIXbt2lae5ampqpLfffltycHCQXn/9dcna2lrav3+/Wh/Cw8OlP//5z9L48eMlBwcHKSYmRpIkScrJyZEef/xx6X//+58kSZK0Z88etemjB2l74cKF0vz589Vkg4OD5am3pggPD39kp7C0tbWlkJAQ6ebNm1JhYaF069Ytafv27Y3KJiQkSJWVlVJFRYVUUFAgnThxQpoxY4aG3IQJE6TLly9LmZmZ0i+//CI9/fTTcp2Ojo60fv166ebNm032qV+/flJlZaX0zjvvqJX7+PhIly9flmpqaqTS0lKpsrJS2rBhg5jCaiM63BSW4P7o168fDg4O7N+/n0GDBnHr1i1Gjx7N4cOH1eTc3NxYt24dP/74I7du3cLJyQmACRMmEBsbi729PS4uLvLob8WKFSgUCs6dO4eenh4//fQTrq6uWFtbywEvvb298fb2BuDbb79l5syZ5Ofn88Ybb+Du7s7169e5fv06GRkZ3Lx5k5SUFIYMGcKqVata3La5ublaHhmon466MzWAQJ0pU6YwefJk7OzsyM/Px8zMDBsbm0ZlDQwM8PPzIyIiAktLS1xdXdmyZQv29vby6HTo0KFEREQwffp0talJAEtLS6Kjo8nOzlYbBd+Jrq4uUVFRag4cUJ8q19fXl7feeotjx46hUqmwsbHpdMmXOiNCgXRgvL29CQ8PZ9CgQXh7ezcaU2zo0KHo6emxfft2xo0bh46ODlCfL/uLL76guLgYd3d3WT4pKYkFCxagp6cHwHPPPYezszMnT55sNGKyo6MjlZWV5OfnU1JSQk5ODikpKUD9C76oqIh33nmHQ4cOPVDbgwcPJioqSq3+0qVLDBo0qIVPr/NjbW1NVlYW+fn5QP3foyGboIODA3v27MHDw0NDMRcUFLBv3z5yc3NJSEhg+/bt3Lhxg6VLlxIUFKShPACUSiWhoaEkJCQwc+bMRvuzatUqkpOTsbW1VetjQEAArq6unDx5Ui7PyckhJyfngZ+BoHURbrwdmBkzZnDhwgW+/vpr5s2b16iMjo4OY8aM4eDBg3h4eMjlQ4YMQUtLi1OnTsl2FIDBgwdz5MgRampqAFAoFJw9e5ahQ4dSVlZGfHy8PI+uVCrZsGEDffv2xdbWlnPnznHp0iV5W7duHYMHD+bSpUvY2dk9UNsvv/wy5eXlfPXVV0D9epLY2FhmzJgBwIULFwgICEClUj3kp9xxOXr0KI6Ojnz66acaDiqlpaVkZWXdNT3tyZMnKSwsxNnZGYCRI0eSmprK6tWr2bp1K5MmTZJly8vL2bNnj4YjRANOTk54eHgQEBAgf8QAjB07lmvXrqkpD0HHQSiQDkzXrl2ZMmUKTk5OPP74403KjR07loqKCsaPH69WPmHCBLp06YK9vb1ctmHDBpRKJb1792bAgAEMHTqURYsW4e7ujkql4v3338fY2Jg+ffpgbm5Oeno6MTExai+FpniQto2Njdm/fz8ffvgh3bp1w83Njc8++4zBgwcDEB8fz7p161pk1O2sXLlyheHDhzNw4EAUCgVbt26le/fuAGRlZeHp6Ul5efld28jNzaVHjx5oaWnJowWFQkFycjJbtmyRjft3w9TUlN27dzNv3jz546EBKysrrl69Kh9bWlpy4sQJeRO0c1rbiP7SSy9Jc+fObbJeGNHbJ0qlUsrLy5Nu376tUXfz5k0pOztbqqys/MPbrq2tla5fvy4b/Ruoq6uT8vLyWtSfjkRL14H07dtXiomJkc6ePdtofUpKiuTt7a1RXlhYKE2ZMkXS09OTJKne+aKhbubMmdKZM2fU5Hv37i3V1taqle3evVtatmyZZGhoKBkaGkrffvuttGDBAklPT0/y9vaW0tPTZVkDAwPJzc1Nfmc09/6EEf3h0m6M6CNHjmzW16mgfaGvr6/hNtuAqanpA61HeJC2dXR06Nmzp0a5trZ2k20K6kcjfn5+XL16FWNjY6qqqu55jru7OyYmJiQnJ6NSqcjNzVWbIiwrK8PQ0PCe7Xh5eWFoaMjHH38MgKGhIR4eHri4uLB8+XLCwsLo378/GRkZKJVK4uPjsbOza/nNCv4wWn0KS0dHR/hzCwRtwMCBA+natat87OnpSWZmJlVVVXTv3h1/f/9GFUDPnj2ZP38+UVFRBAYGyukW9u7dy4oVK9DW1kZbW5vZs2c3y3ZhYWEhfxiYmppy6NAhFi1axLRp08jMzCQyMpLo6Gg1hwjx0dkxEDYQgaCTMnHiRPLz88nLy6OoqAgfHx+mTZsG1Hu4hYSEyFEAoD5Qp1KpJCMjg7lz5+Lr68vGjRvl+sDAQHR0dMjKykKhUGBubi67+D4Ivr6+xMXFkZSUREFBAQqFgrS0NM6ePfvAbQtaF+HGKxB0UtavX8/mzZvp0aMHFRUVVFRUyHXHjh3DysqKgoICAEaNGnXP9iorK5k6dSpmZmbU1dWptddAdnb2PSNKvPrqq2rHKpWKFStWsHLlSiwtLZEkiZKSEmpra5tzm4I2RCgQgaATo1KpyMvLa7SuQXncL3dz/X0QJElSC+8vaP8IBSIQdCAajNiNLRp9GPwR9srW6HtBQQGOjo6NBtYU3D+3bt2iV69e95QTCkQg6EA0LLTsyI4prdH3Ll268Ouvv/LBBx889LYfRdLT05sVCUAoEIGgA2FgYNDWXWiXGBoaUltby9SpU9u6K50Cc3Nzvvvuu3vKCS8sgUAgELQIoUAEAoFA0CKEAhEIBAJBixAKRCAQCAQtQigQgUAgELQIoUAEAoFA0CI6rALZtWsXCxYsICsrS6OutraWxYsXy3F64uLiCA4OVpPJyMhgwYIFGqt0g4OD+ec//ykfnzt3jkWLFjF16lRWrlwJQGFhIQsWLGh0u3z5skZ/EhMT8fb2VotkevbsWd5++22mTZtGYGBgoytwz58/j7+/f6MhHSoqKti2bRtz5szhlVde4aeffrrL07p7WwKBQNASOqwCiY2NJTIyktDQUI26uLg4du/eTWRkJFC/cCkwMJC6ujpZZv/+/ezYsYMjR47IZXV1daxatUpeKRsSEsKUKVOwtbXl7bff5sUXXwTqQ4dbWFiobQYGBmzfvl0jI15DStfIyEj5+j/88APjxo1j8ODB+Pr6olAoGDVqlNq5YWFhuLu7s23bNo2XfmFhIUOHDuXkyZN4eXnh6+t71/zRd2tLIBAIWkxrJ5RavXq1FBgY2GR9SxNKTZ48WZo1a5bUp08fqa6urtE6W1tbSZLqkxTp6elJqampsoyTk5P08ssvSxMnTpTLzpw5IxkYGEhVVVXSb7/9JhkYGEi//vprs/qzadMmycXFRaP8lVdekQICAiRAqq6uliRJktauXSt5enrKMiqVStLW1pZ++eUXSZIkKSYmRho4cKCUnJysdl4D8+fPl15//fVm9etebQk6Fi1NKNXZN5FQ6uHS3IRS7WIEIkkSSqWy2VsDDbmajx8/LpfduHGDpKQkPD095TJTU1OGDRtGYmIiUP8Fn5aWxqeffkpCQoKcXCcxMZERI0ZgZGTEvn37eOmll3jqqafu2X+VSkVwcDDvv/++Wnl4eDilpaX/x965x0VVdf//wwx3kPswChaKYmmI+kiKohIKGiCIF1LElDCRl2L6zQteULR8vFCKQpgloELlheepzEeslECREItHzAs9GAKDIDCD3EWYgfX7gxfn52kGRBTxst+v1369ztlrnbX3OczM4uy1914IDAzk1Q8dOhS//fYbN3z2888/w8zMjNta28PDA5mZmXjllVdUtnX8+HF88MEHD+1XR7boge0kHnwzY8fP/jGD8azQ4w7E1NQU5eXlMDQ07HRZuXIlgNZ9gd59910cOnSIsxcfHw9vb2/o6Ojw2nFxceEcyOnTp/Hmm2/iH//4B/r374/k5GQArQ7ExcUFAJCTkwMbGxvMmDEDIpEI/fr1w/79+1XewzfffANdXV2e07p16xY2b96Mw4cPK20e5+XlhQ8++ADDhg3DzJkzsWbNGpw5cwaampoAWjeb09XVVblnUFFRERoaGnDz5k3Y2NjAxMQEHh4eKCoqUtm39mw96HS3b9/Ojp+j40dFU1MTIpEIAsGT+7r36tWrw2HTjtDQ0Gg3YZSOjg5MTEy6bbNIxhOmp4ewVqxYQREREY9sd9q0aRQVFUW5ubmkq6tL1dXVREQ0ZMgQSk1Npe+++44bwiIiunDhAunp6VFTUxPNnj2btm7dSkREa9asoUWLFlFTUxPp6upyw1xvv/02WVpacudZWVnUq1cvSktL4/WjpaWFbG1t6fPPP+fqFAoFjR07lo4ePUpEREVFRbzho6amJlq8eDENHz6c/Pz8SCwW07Fjx5TuMT8/X2nY6eLFiyQQCGjJkiXU0NBAjY2N5O/vTy4uLh0+L1W2GM8fjzKEJRAIKDIykmpra0kmk9H9+/cpOjpapW5ycjLV19dTXV0dSaVSSk1NpdmzZyvpeXh4UE5ODuXl5dGNGzfo9ddf52RCoZB27NhBtbW17fbJxsaG6uvrKSgoiFe/cOFCysnJoaamJqqqqqL6+nrauXMnG8LqIZ6ZnOjdjY2NDYYPH45jx45h6NChuH//PiZMmIATJ07w9EaPHg2BQIBLly7hzJkzWLNmDYDWIR5fX1/Mnz8fmpqaGDlyJIDWlJqLFi3CqFGjAAD/+Mc/4OHhgeTkZF7ynaSkJNy5cwcLFizg6sLDw6FQKGBpaYkLFy5weRd+/fVXDB48GLt27YJEIsGlS5egoaGBy5cvY9KkSRCLxXBycurwfoVCIYRCIfbu3csl7lm7di2GDh0KhULx0GQ+jJeH6dOnY9q0aRg4cCDKyspgaGgIS0tLlbpaWlpYunQpDh06BJFIhEmTJmH37t0YMmQIN5vR3t4ehw4dwjvvvMO9zbchEomQmJiI27dvK739t6Guro74+Hjk5uby6sPCwhAYGIhFixbhzJkzkMvlsLS07PIbDuPp8UL82vj7++PgwYMYOnQo/P39Vb7+qqurw8nJCbGxsdDU1MSIESMAAI6OjmhoaMDBgwfh7OzMvVq/9tpruH37Ns+GXC5X2g01PDwcS5Ys4X1pbt++jfr6egQFBQEAN/Np2bJlCA0Nxblz5xAcHAwNDQ0AwIgRIzB+/HicP3/+oQ5k4MCBaGlpQVlZGfdjIJfLoa6uzvJIM3iIxWIUFBSgrKwMQGsiqLZkUMOHD0dCQgLc3d2Vhj+lUimOHj2KkpISJCcnIzo6GuXl5Vi9ejUiIiKUnAcANDY2IjY2FsnJyZgzZ47K/mzatAlpaWmwsrLi9TE0NBSTJk3i5VcvLi7u1HbijJ6lx2MgT4LZs2fjypUr+Prrr3lvAn/HxcUF//rXv+Dm5sY5GaFQiLfffhuJiYlc/AMA5s+fjyNHjuDSpUsAWvfH/+mnn+Dq6srpXLp0CZmZmVi6dCmvnejoaFy7do0rZ8+eBQBkZWXB19cXdnZ2+OGHH9DU1AQAkEgkuHjxIuzt7R96r0ZGRvD29saHH34IuVwOhUKB3bt3w9XVFWpqarhy5QpCQ0OVphMzXj5Onz6NkSNHYtu2bTA2NubJqqqqUFBQ0GF2wfPnz0Mmk3GTVRwdHZGZmYnNmzcjKioKXl5enG5NTQ0SEhLajbM4ODjA3d0doaGhvH90XF1dUVRUxHMejOeHF8KBGBgYYPr06XBwcMCrr77arp6rqytqa2vh7u7Oq586dSpqa2t5DmTYsGHYt28fPD09YWFhAScnJ3zyySfcEBcA7Ny5E35+fhCLxY/U3507d6KxsRF9+/bFG2+8AXt7e6xYsQJubm6duv6LL75ATU0NzM3NYWZmhoKCAuzbtw8AcPbsWWzfvh0VFRWP1CfGi0d+fj7GjBkDW1tbSCQSREVFwcTEBABQUFAAT09P1NTUdGijpKQEpqamUFNT494WJBIJ0tLSsHv3bu4tuyP09fURExODBQsWcP80tWFubo7CwkLuXCQSITU1lSuMZ5znNYj+tFAoFFRaWkotLS1P3HZjY+Nj2a6qqqLa2lpeXXNzM5WWlj6J7jGeQbq6DqR///508uRJunjxokr5hQsXyN/fX6leJpPR9OnTSUNDg4iIRo0axcnmzJlDGRkZPP2+ffuSQqHg1cXExFBISAhpa2uTtrY2ffvttxQcHEwaGhrk7+9PV69e5XS1tLTIxcWF5s+fT0TEgug9xEsTRO9uhELhI79hdBZNTc3Hsm1oaKhUJxAIuq2/jOeX/Px8LF26FIWFhdDV1eXWPnWEm5sb9PT0kJaWBrlcjpKSEt7QaHV1NbS1tR9qx9vbG9ra2ti4cSOA1uyB7u7ucHJywtq1axEXF4dBgwYhNzcXjY2NOHv2LAYOHNj1m2U8NV6IISwGg6GMra0tDAwMuHNPT0/k5eXh3r17MDExwbJly1Q6gN69eyMgIADx8fEICwuDTCYDABw5cgTr1q2DQCCAQCDAvHnzOhW7MDMzg76+Ple+//57rFixAj4+PsjLy8Phw4eRmJiIoUOHctewCSHPB8yBMBgvKFOnTkVZWRlKS0tRUVGBhQsXwsfHBwAwcuRIREZGcrsfAK0blDY2NiI3Nxfz589HYGAgwsPDOXlYWBiEQiEKCgogkUhgbGzMTfF9HAIDA5GUlIRz585BKpVCIpEgKysLFy9efGzbjO6FDWExGC8oO3bswK5du2Bqaoq6ujrU1dVxsjNnzsDc3Jxbo/Tg2qb2qK+vx8yZM2FoaIjm5maevTZu37790LVIs2bN4p3L5XKsW7cO69evh0gkAhGhsrKSbfz5HMAcCIPxAiOXy5VSFrTR5jwelY6m/j4ORKQyrQHj2YU5EAbjOeL+/fs93YVnEplMhjfeeAMbNmzo6a68EFRVVaGlpeWhesyBMBjPEQKBoFs3GiQVG3g+Sbqr7zo6OsjPz+dNGmB0nbt373bqs8AcCIPxHKGpqdntP/LdSXf1XU9PD00iXfUAACAASURBVAqFAiEhId1i/2Xjl19+wXffffdQPTYLi8FgMBhdgjkQBoPBYHQJ5kAYDAaD0SWYA2EwGAxGl2AOhMFgMBhdgjkQBoPBYHSJl2oab2lpKeLi4vDHH3+AiGBnZ4eFCxeid+/eSroZGRmIj49HdHS0UpKc3377DTExMaiqqoKTkxMWL14MoVCIjIwMfP311yrb3rNnD9TV1VFdXY2IiAhcuXIFVlZWCAkJQZ8+fQAATU1NOHz4MM6dOweFQoFhw4YhODgYvXr1AtCa9S0qKgqXLl2Cubk5lixZgiFDhnBtZGdnIy4uDnfu3IGNjQ2Cg4NhYWHR4TNJTEyERCLBypUrH+lZMhgMxkvzBvL777/D1tYW2dnZmDJlCtzc3PDHH3/Azs4O2dnZSvqffvop4uPjcebMGV59eno6Jk2ahH79+mHWrFmIj4+Hv78/gNa80mZmZrxy584dHD9+nHNCXl5eSE9PxzvvvIPKykpMmDABDQ0NAIDVq1fjxIkTGD9+PGbNmoUff/wRHh4eXNvTp0/Hf/7zH8yaNQuWlpYYM2YM/vjjDwBAZmYmPDw8IBaLMWfOHBQVFcHBwaHdhEFNTU1YtmwZAgMDkZiY+NjPl8FgvIS8DAmlWlpaaMiQISoTpAQHB9OwYcN4deXl5aSrq0uhoaHk4+PDk/n4+NCaNWu489LSUtLT06Pr16+rbHvq1Knc/f/666+kp6dHdXV1XL9sbW0pJiaGiFqTQT3IzZs3CQBVVFTQ9evXSUtLiyorKzn5ypUref17MLlUc3MziUQi+s9//qOyX23XfvnllzR69GiVOoxnj64mlHrRC0so9WTpbEKpl+INJCsrCzdu3MCaNWuUZOvWrcOVK1d4byGHDx/GW2+9hcWLF+PkyZNcPgSgNX/54MGDuXOxWIwRI0YgPT1dyXZOTg6Sk5OxZMkSAK3DYmPHjoWenh6A1m0dXFxcuNSdfx8q++OPP2BqagoDAwNIJBL07t0bRkZGnNzNzY3Xrr6+Pu/65ubmdhP+bNmyBcePH4empqZKOYPBYDyMHncgdnZ22LFjB/r3798tZdq0acjJyYGhoSFeeeUVpfYtLCxgYmKC69evc3WxsbHw9/dH37594ejoiISEBE5mbW2Ny5cvc+fl5eX466+/UFlZqWQ7PDwcfn5+MDc3BwDcuXNHKVugWCzG7du3ufPs7Gzs3LkTixYtwo4dO5CYmAh1dXVYW1vjzp07KCsr43TT09NVtgsAX3/9NUQiEcaPH69S3ubE6G9bSzy4fcHevXvZ8TN4/KhoampCJBIp/YPyOPTq1QumpqZdulZDQ6PdhFE6OjowMTHp1v2+GE+Qnh7Cam5upvz8/G4rJSUl5OXlRRYWFu324ZVXXuGGkdLS0sjIyIiqqqqooaGBYmJi6I033uB0r1y5QiYmJuTr60urVq0iJycnGjRoEB04cIBns7i4mLS0tHhDW8uXL6eAgACe3p49e2j8+PHceVpaGi1btox8fHxoyJAhtHXrVk4WEBBANjY2tGrVKpo1axa9/fbbZGlpqXQ/mZmZZGpqShkZGe3ecxsHDx7kDWG1Da8REW+4jB0/G8ePMoQlEAgoMjKSamtrSSaT0f379yk6OlqlbnJyMtXX11NdXR1JpVJKTU2l2bNnK+l5eHhQTk4O5eXl0Y0bN+j111/nZEKhkHbs2EG1tbXt9snGxobq6+spKCiIV79w4ULKycmhpqYmqqqqovr6etq5cycbwuohOjuE1eMO5Glw6tQpEggE1NjYqCRramoioVBIP/74IxER+fv7q/yAPvhjXFZWRt988w19/fXXVFlZSQMGDKDTp0/z7K5atYrc3d15dZs3b6YZM2bw6rZs2UKenp4q+3379m3S0dGhlJQUru78+fN04MABysjIoISEBKX4xR9//EF9+vShU6dOPfzBkLIDYTzbPIoDmTlzJhUWFpJYLCYAZGhoSEOGDFGpe+HCBe6zLxKJaM6cOVRcXExbtmzhdOzt7UkqlZKzs7PS9SKRiFJTU+mrr74ihUKhsg11dXXKyMigy5cv8xxIWFgYFRcXk7u7O2loaBAAsrS0JDs7O+ZAeggWA3mA8ePHQ1NTU+Vso+PHj0NbWxvjx49HbW0tEhMTkZmZiYaGBq74+voiNjaWu8bc3By+vr6YO3cu8vPzUVJSgrFjx3Ly6upqfPnll0pTY1XN+Lp27RovF/SDWFpaQiwW49atW7x7ef/99+Hg4IDjx49j0qRJnOz69etwc3PD/v374e7u/mgPifHCIRaLUVBQwA17VldX48aNGwCA4cOH4+rVqyqHdaVSKY4ePQpfX1+sX7+eG4JdvXo1IiIikJKSonRNY2MjYmNjVcYZ29i0aRPS0tKQm5vL62NoaCh8fX2RlJQEuVwOACguLuZmGDKeXV4KB9KrVy+sX78eq1evRkpKCogIRISUlBSsXr0aW7Zsga6uLr755hvY2Nhg1KhR0NbW5sr777+PY8eOob6+nmc3NzcXfn5+WLVqFS8Pwf79+2FtbY2JEyfy9KdMmYKamhp89dVXAICLFy/i1KlTmD17NgDg1KlTuHfvHqcfHx+P4uJipThGc3Mztm/fjszMTHzwwQcAWp2Hi4sLPvroI4wdOxYymQwymYybxnvlyhWEhoZyX1DGi8/p06cxcuRIbNu2DcbGxjxZVVUVCgoKOswueP78echkMu7z5+joiMzMTGzevBlRUVHw8vLidGtqapCQkNBunMXBwQHu7u4IDQ3lxT9cXV1RVFSE8+fPP86tMnqIl8KBAMDGjRuxZs0avPvuu9DT04Oenh4WLFiAjRs3cm8KsbGxCAgIULrW2dkZ5ubmOHbsGAoLCyESiWBtbY1x48Zh9uzZCAsL43Sbmpqwd+9efPjhh0p2dHV1cezYMaxZswZGRkZwcXHBJ598Ajs7OwCtDsPY2BiWlpYwNDTExx9/jOPHj8PGxgYAEBgYiIEDB8LMzAxJSUk4e/YsF5T/7LPPUFpaioULF0IkEnFlxowZAICzZ89i+/btqKioeLIPlvHMkp+fjzFjxsDW1hYSiQRRUVEwMTEBABQUFMDT07PddUJtlJSUwNTUFGpqatzbgkQiQVpaGnbv3o2goKCH9kNfXx8xMTFYsGABmpqaeDJzc3MUFhZy5yKRCKmpqVxhPOO8DDGQv1NRUUF3797t8vXl5eVUXl5OLS0tXbpeoVDQnTt3SC6XK8nu379PxcXFKvvX0NBARUVFVF9f/8htNjc3U2lpaZf6y3h26Oo6kP79+9PJkyfp4sWLD42BPFhkMhlNnz6dNDQ0iIho1KhRnGzOnDmUkZHB0+/bt69SDCQmJoZCQkJIW1ubtLW16dtvv6Xg4GDS0NAgf39/unr1KqerpaVFLi4uNH/+fCIiFgPpITobA3mptjJpo+2/sK4iEoke63qhUKhy+xSgdTV7e9uPaGtro2/fvl1qUyAQKE0hZrw85OfnY+nSpSgsLISuri5vqLQ93NzcoKenh7S0NMjlcpSUlPCGQKurq9tdZ/Qg3t7e0NbWxsaNGwG0fo7d3d3h5OSEtWvXIi4uDoMGDUJubi4aGxtx9uxZDBw4sOs3y3hqvDRDWAzGy4atrS0vNufp6Ym8vDzcu3cPJiYmWLZsmUoH0Lt3bwQEBCA+Ph5hYWHcQtojR45g3bp1EAgEEAgEmDdvXqdiF2ZmZtDX1+fK999/jxUrVsDHxwd5eXk4fPgwEhMTeZNJ2lsnwni2YA6EwXhBmTp1KsrKylBaWoqKigosXLgQPj4+AICRI0ciMjISAwYM4PQPHDiAxsZG5ObmYv78+QgMDER4eDgnDwsLg1AoREFBASQSCYyNjXnxv64SGBiIpKQknDt3DlKpFBKJBFlZWbh48eJj22Z0Ly/lEBaD8TKwY8cO7Nq1C6ampqirq0NdXR0nO3PmDMzNzSGVSgEA48aNe6i9+vp6zJw5E4aGhmhububZa+P27dtQV+/4Z2XWrFm8c7lcjnXr1mH9+vUQiUQgIlRWVkKhUHTmNhk9CHMgDMYLjFwuR2lpqUpZm/N4VDqa+vs4EBHKy8u7xTaje2AOhMF4jmDreFRTXV0NKysrxMXF9XRXXghu376N5ubmh+oxB8JgPEe0LdTrrs0G6W+ba3YH3dX3iooKZGRkdIvtlw2ZTIb+/fs/VI85EAbjOaJtdtLT+KHvLrqj74aGhlAoFDhw4MATt/0y8ssvv/B25m4PNguLwWAwGF2CORAGg8FgdAnmQBgMBoPRJZgDYTAYDEaXYA6EwWAwGF2CORAGg8FgdImnNo33wIEDuHLlClatWoV+/frxZAqFAqtXr4aBgQG2bNmCpKQk5ObmYsWKFZxObm4uIiMjERoaytvJds+ePRg8eDCmTJkCAJBIJIiLi0NOTg4A4NChQ9DR0cHGjRtRWVmp1K/JkyfDy8sLZWVliI6Oxo0bN2Bubo6AgADY29vzdNuz3calS5fwzTffoKioCK+99hq2bdvGyerq6nDo0CFkZmaivr4eGzduxIgRI9p9XtnZ2YiNjUVERMRDt4ZgMBiMnuCpvYGcOnUKhw8f5qWGbSMpKQkxMTE4fPgwgNZ54mFhYbyVkMeOHcO+ffvwww8/cHXNzc3YtGkTtzDp119/xciRI1FfX48FCxbA19eXmzdvbGwMMzMzXjly5AgKCwtRW1uLUaNGobq6Gu+88w769OmDcePG4dKlS1xbHdkGgMjISEyfPh1WVlZYvHgxnJ2dOZlMJoO9vT3Onz8Pb29vBAYGwtTUtN1nFRcXBzc3N3z22WdsPyAGg/Hs8rQSSk2bNo18fX3plVdeoebmZp5Om8zKyoqIiGpra0lDQ4MyMzM5HQcHB5oyZQpNnTqVq8vIyCAtLS26d+8eNTc3k42NDR04cKBT/crKyiIDAwOqrq7m2nyQmTNn0qpVq4iIHmr71q1bpKWlRX/++adKeUBAAPn5+XWqXydPniRbW1tKS0sjANTQ0NCp6xgvB11NKPWiF5ZQ6snS2YRSTzUG0pZb+ZdffuHqysvLce7cOXh6enJ1+vr6GD16NFJSUgC0/geflZWFbdu2ITk5mUuGk5KSgrFjx0JHRweZmZmQSqV49913O9WXnTt3YuHChVy+BH19fZ68ubmZy5XwMNtHjx7FxIkT8dprrynJ5HI5jh8/zuUufxgeHh7IzMzEK6+80il9BoPB6Cm63YHU19ejpKQEANDS0oJ3330Xhw4d4uTx8fHw9vbmxRIAwMXFhXMgp0+fxptvvol//OMf6N+/P5KTkwG0OhAXFxcAQE5ODt544w18/PHHsLS0hFgsRnBwMBobG5X6lJ+fjxMnTmD58uUq+3zz5k2kpKRwDuNhtnNycmBjY4MZM2ZAJBKhX79+2L9/PwCgqKgIDQ0NuHnzJmxsbGBiYgIPDw8UFRWpbFtNTQ26uroqt3v4+uuv2fFLfvxg0qXOoqmpCZFIxO2j9STo1atXh8OwHaGhodFuwigdHR2YmJh0235ZjCdLtzuQ//3vfzA3NwfQGtvw9/fHd999h5qaGgDAwYMH4e/vr3Sdi4sLLly4ALlcjlOnTsHd3R1Aa5KckydPQi6XIz09nXMgUqkUWVlZsLa2xu3bt3H16lWkp6fj008/VbL96aefwtvbG1ZWVkqyiooKTJs2DVu2bMGgQYM6ZVsqleLf//431q5dC6lUim+//RZr1qzBhQsXIJVKQUT49ddfcfXqVZSWlnJB+kdl9OjR7PglPy4uLkZnEQgEiIyMREVFBXJycnDv3j1ER0er1E1OTkZ9fT3q6uoglUqRmpqK2bNnK+l5eHggJycH2dnZSEtLw+uvv87JhEIhduzYgdra2nb7ZGNjg6qqKixatIhXv3DhQuTk5KC6uhq3bt1CXV0ddu7c2el7ZfQQ3R0D8fLyohEjRtC0adMoKiqKiIjGjh1LX375JWVkZJC1tTW1tLTQd999x8VAiIjkcjn16tWLLly4QCYmJpSVlUVEROfOnSMLCwtKS0sjIyMjUigURET0ySef0FtvvcVre//+/Up1UqmUdHR06NKlS0p9ra6upjfffJM2bNjAq3+YbQ8PD9q8eTNPPmfOHNq8eTP99ttvpKGhQXK5nJP9+eefSnV/Jz8/n8VAGEo8Sgxk5syZVFhYSGKxmACQoaEhDRkyRKXuhQsXyN/fnwCQSCSiOXPmUHFxMW3ZsoXTsbe3J6lUSs7OzkrXi0QiSk1Npa+++ooUCoXKNtTV1SkjI4MuX75MQUFBXH1YWBgVFxeTu7s7aWhoEACytLQkOzs7FgPpIZ7JGEgb/v7+OHjwIPf2oep1VV1dHU5OToiNjYWmpiY35dXR0RENDQ04ePAgnJ2duVfh1157Dbdv3+bZkMvl0NLS4tVFRUXB3t4eb775Jq++pqYGkydPxqRJk7B161ae7GG2O5IPHDgQLS0tKCsr48nU1dVZ3mdGtyIWi1FQUMB99qqrq3Hjxg0AwPDhw3H16lWVsTapVIqjR4/C19cX69ev50YQVq9ejYiICG5o+UEaGxsRGxuLNWvWtNufTZs2IS0tDbm5ubw+hoaGwtfXF0lJSVy+k+LiYvzxxx9dv3nGU6FHHMjs2bNx5coVfP3111iwYEG7ei4uLvjXv/4FNzc3zskIhUK8/fbbSExM5Iav2nTv37+PyMhIAMDdu3cRExPDrQ8BwL3Cr1y5ktdObW0t3n77bQwdOhQrV66ETCaDTCZDRUVFp2zPnz8fR44c4ab9Xr16FT/99BNcXV1hZGQEb29vfPjhh5DL5VAoFNi9ezdcXV2hpqaGqqoqhISEQCKRPO5jZTB4nD59GiNHjsS2bdtgbGzMk1VVVaGgoKDD7ILnz5+HTCbjJr84OjoiMzMTmzdvRlRUFLy8vDjdmpoaJCQktBtncXBwgLu7O0JDQ3n/OLm6uqKoqAjnz59/nFtl9BA94kAMDAwwffp0ODg44NVXX21Xz9XVFbW1tVz8o42pU6eitraW50B0dHRw4sQJfP755+jduzesrKzg4OCA4OBgTic2NhbGxsa8GV9A6zqUjIwMxMTEQCQScUUsFnfK9rBhw7Bv3z54enrCwsICTk5O+OSTTzBy5EgAwBdffIGamhqYm5vDzMwMBQUF2LdvHwAgLy8P4eHhyMzMfIwnymAok5+fjzFjxsDW1hYSiQRRUVEwMTEBABQUFMDT05OLRbZHSUkJTE1Noaamxr0tSCQSpKWlYffu3QgKCnpoP/T19RETE4MFCxagqamJJzM3N0dhYSF3LhKJkJqayhXGM87TioE8TcrLy6mpqemp21YoFFRaWkotLS0q5VVVVUrrTYiISkpKnmgfGS8uXV0H0r9/fzp58iRdvHjxoTGQB4tMJqPp06eThoYGERGNGjWKk82ZM4cyMjJ4+n379lWKgcTExFBISAhpa2uTtrY2ffvttxQcHEwaGhrk7+9PV69e5XS1tLTIxcWF5s+fT0TEYiA9RGdjIC/kHhkikahHbAuFQu6tRRWGhoYq6/v06fPY/WIwOiI/Px9Lly5FYWEhdHV1ubVUHeHm5gY9PT2kpaVBLpejpKSEl5O9urqaWyvVEd7e3tDW1sbGjRsBANra2nB3d4eTkxPWrl2LuLg4DBo0CLm5uWhsbMTZs2cxcODArt8s46nBNlNkMF5QbG1tuYWyAODp6Ym8vDzcu3cPJiYmWLZsmUoH0Lt3bwQEBCA+Ph5hYWGQyWQAgCNHjmDdunUQCAQQCASYN29ep2IXZmZm0NfX58r333+PFStWwMfHB3l5eTh8+DASExN5a1zYBJPnA+ZAGIwXlKlTp6KsrAylpaWoqKjAwoUL4ePjAwAYOXIkIiMjMWDAAE7/wIEDaGxsRG5uLubPn4/AwECEh4dz8rCwMAiFQhQUFEAikcDY2BhhYWGP3c/AwEAkJSXh3LlzkEqlkEgkyMrKwsWLFx/bNqN7UZswYQKdO3eu2xqYNm0aioqK8N///rfb2mAwXhbGjBnzSD+sGhoaMDU1RV1dHerq6ngykUgEqVT6yH0wNDREc3Ozkr3HRU1NDSKRCESEysrKR9pI1MLCAgqFgjddntF1fvnlF3z33XeIiopqV2fcuHFPbzt3BoPx9JHL5SgtLVUp64rzANDh1N/HgYhQXl7eLbYZ3QNzIAzGcwSp2CONAdy/fx+Ghob4/fffe7orLwSFhYWd+qwxB8JgPEc8mCOH8f+pra2Fjo4O1q5d29NdeSGor6+Hk5PTQ/WYA2EwniNYdkrViEQiyOVynD17tqe78kLQFgN5GGwWFoPBYDC6BHMgDAaDwegSzIEwGAwGo0swB8JgMBiMLsEcCIPBYDC6BHMgDAaDwegST82BpKamIjg4GGfOnFEp37t3L4KDg3H37l3cvHkTH3zwAW/Oe3NzM5YvX460tDTedadOncJnn30GoDWLWUhICGbNmoVNmzZxCaHa+OGHH/Dee+/B19cXERERuH//PidrampCdHQ05syZg/feew+JiYm8ax/HNgAcPXoU8+bNg5+fH/bt24fGxsYOn5dMJsPq1auRk5PToR6DwWD0FE/NgWRnZ+Pw4cP46KOPlGQymQybN2/Gvn37UFNTA7FYjH379vH2z/r1118RFRWFzz//nHdtdHQ0SkpKcPfuXYwePRpVVVWYO3cuJBIJHB0duW2rP/30U2zZsgUjR47E9OnTceTIEcyePZuzM2PGDPzyyy9wc3PD2LFjsWzZMkRERADAY9ves2cPNmzYAC8vL/j6+iIhIQGLFy9u91llZmZi9OjR+Pzzz3nJdhgMBuOZ4mkllIqIiKBp06aRrq4u3bx5k6cTERFBvr6+BIDy8/OJqDVxzs6dOzmdtWvX0pQpU8jIyIjkcjkREcnlctLX16fk5GSKjo6mUaNGcfrNzc00atQoio6OJiKie/fukUKh4ORXr14lNTU1LsHT3xM9RUVFkb29PRHRY9t2cXGhXbt2cfJffvml3eQ3paWlZGlpST///DMNHDiQTp8+3e6zZbx8dDWh1IteWEKpJ0tnE0o91RiIjo4OvL29cejQIV79wYMH4evry6tzcXFBSkoKd37q1CksXboUhoaGuHDhAgDgt99+Q3NzMxwdHSGRSDB48GBOXyAQYPLkyUhPT+fafjDHQHNzM9TV1bk6fX19XvvNzc1croTHtT106FD8+OOPXDKeH3/8EWPHjlX5jMRiMf7880+4uro+0m6kDAaD8bTpdgdCRNwPp0KhgL+/P+Lj49HS0gIA+P3331FbW4tx48bxrnNxccGFCxegUChQVFSE3NxcODs7w8PDAydPngQApKSkYNy4cdDS0oK1tTWys7O5DcAUCgUuXbqEyspKlf2KjIzEvHnzoKOjoyRrbGzEl19+iUWLFgHAY9v++OOPYWhoiGHDhsHJyQk3btxAXFxcu8+szZnR3zYz++mnn9jxS37clUx9mpqaEIlEEAie3Ne9V69eMDU17dK1Ghoa7SaM0tHRgYmJCdTU1B6ne4ynRLc7kIqKCnh5eQFo/UGcNGkSACA5ORkAEBcXhwULFih9YMaMGQMiwm+//YZTp05h/Pjx0NfXx9SpU3kOxMXFBQAwb948NDc3w9nZGWvXrsXkyZNx//59mJiYKPVp3759SElJwa5du5RkLS0tWLBgAQYNGoT58+c/EdtVVVWQSqWwsbGBUCjErVu3UFRU9MjP8sGUuOz45Tz+++SMjhAIBIiMjERFRQVycnJw7949REdHq9RNTk5GfX096urqIJVKkZqayovjteHh4YGcnBxkZ2cjLS0Nr7/+OicTCoXYsWMHamtr2+2TjY0NqqqquH/O2li4cCFycnJQXV2NW7duoa6uDjt37uz0vTJ6iO6OgYwdO5Z69epFERERNHPmTCIiWr9+Pc2dO5caGhrIxMSE8vPzqbKykhcDISJ6++23adu2beTt7c3FEBoaGkhXV5euXbtGurq6lJWVxenfv3+fTpw4QbGxsZSXl0cLFy6kkJAQXn8SEhLo1VdfpVu3bin1taWlhRYvXkyTJk2ihoYGnuxxbNvb29PWrVu585iYGDIzM6O7d+92+OysrKxYDITB41FiIDNnzqTCwkISi8UEgAwNDWnIkCEqdS9cuED+/v4EgEQiEc2ZM4eKi4tpy5YtnI69vT1JpVJydnZWul4kElFqaip99dVXpFAoVLahrq5OGRkZdPnyZQoKCuLqw8LCqLi4mNzd3UlDQ4MAkKWlJdnZ2bEYSA/R2RhIjziQ3Nxc0tHRoc8//5wmTpxIRKTSgXz66afk5eVFJiYmlJOTw9V7enpSQEAAmZqaUktLi8p279+/TyKRiH7++Weu7ptvviErKyulIH4bS5YsoYkTJ1J9fX2H9/Qotuvq6ggAFRQU8OoNDAzo/PnzHbbDHAjj7zyKA1myZAmdO3dOpWz48OF09epVeuWVV5QcSFuZMGECyeVyMjc3JwB07NgxWr9+vUp7BgYG9O6775KFhUW7DuSjjz6i8PBwOnbsGOdAxGIxyeVymjBhAguiP0M8k0H0NmxsbDBixAisXLkS7733Xrt6bYF0Q0ND3qvy1KlTkZiYiIkTJ6ocK62pqcHcuXMxePBguLq6Amhdh7FixQocPXoURkZGkMlkkMlkaGhoAAAEBwcjMzMTBw8exL179zj53wPZj2pbT08P1tbW+Ne//sXZOH36NBQKBYYMGYKqqiqEhIRAIpF0/YEyGCo4ffo0Ro4ciW3btsHY2Jgnq6qqQkFBQYfZBc+fPw+ZTIbx48cDABwdHZGZmYnNmzcjKiqKG5oGWr8XCQkJ7cZZHBwc4O7ujtDQUF78w9XVFUVFRTh//vzj3Cqjh+ixlejvvfcehEIhZsyY0a6OnZ0ddHR04O7uzqv38PBAbW0tF/9oY+jQobCxscGrr74KHR0d3n72W7ZsQXl5OcaMGQORSMSVXbt2oaysDNHR0cjKyoKVgHKK8AAAIABJREFUlRVP3pZ/uqu2gVYHEx8fDysrK7z22mtYunQpjh8/DlNTU+Tl5SE8PByZmZmP/UwZjAfJz8/HmDFjYGtrC4lEgqioKC5uV1BQAE9PT9TU1HRoo6SkBKamplBTU4NYLEZoaCgkEgnS0tKwe/duBAUFPbQf+vr6iImJwYIFC9DU1MSTmZub89Y6iUQipKamcoXxbPPUstOsWLECK1as4M7ff/99vP/++9y5kZGR0qwjNTU1lJWVKdmytLRUmW4xPT0ddXV1EIlE0NDQ4MketqJblb0nZfvNN9/ElStXUFdXh6amJl7wfeTIkSgpKUGfPn2UrisoKOjQLoPxMK5evQovLy/0798fkZGRSEpKgoODQ6evt7KyglQqhbq6OtTV1RESEoJLly4BaA3SL1++HPv37+/Qxp49e5CQkIC8vDxoa2tDIBBAXV0dGhoauHv3LszMzDjdmpoabN26FRYWFjh8+HDXbprx1Hih0psZGBjAwMDgmbX997UmbahyHgzGkyQ/Px9Lly5FYWEhdHV1uV0UOsLNzQ16enpIS0uDXC5HSUkJNyUfAKqrq7m1Uh3h7e0NbW1tbNy4EQCgra0Nd3d3ODk5Ye3atYiLi8OgQYOQm5uLxsZGnD17tkvTlRlPH7aZIoPxgmJra8v7p8fT0xN5eXm4d+8eTExMsGzZMpUOoHfv3ggICEB8fDzCwsIgk8kAAEeOHMG6desgEAggEAgwb968TsUuzMzMoK+vz5Xvv/8eK1asgI+PD/Ly8nD48GEkJiZi6NCh3DXtrRNhPFswB8JgvKBMnToVZWVlKC0tRUVFBRYuXAgfHx8ArUOnkZGRGDBgAKd/4MABNDY2Ijc3F/Pnz0dgYCDCw8M5eVhYGIRCIQoKCiCRSGBsbIywsLDH7mdgYCCSkpJw7tw5SKVSSCQSZGVlcfFHxrOL2oQJE+jcuXPd1oCjoyOuXr360GAdg8F4OGPGjHmkH1YNDQ2Ympqirq4OdXV1PJlIJIJUKn3kPhgaGqK5uVnJ3uOipqYGkUgEIkJlZeUjbeVjYWEBhUKhMmbKeHR++eUXfPfdd4iKimpXZ9y4cS9WDITBYPCRy+UoLS1VKeuK8wDQ4dTfx4GIUF5e3i22Gd0DG8JiMBgMRpdgbyAMxnPEg7OgGP+fsrIyWFpa4o033ujprrwQKBQKzJw586F63e5A9PX12c6aDMYT4u9rkBitiMVi3L9/H7du3erprrwQpKSk4MSJEw/V63YHMnToUNy8ebO7m2EwGAw2/fcJ0dmt/59KDORh+b8ZDAaD8fzBgugMBoPB6BLMgTAYDAajSzAHwmAwGIwuwRwIg8FgMLoEcyAMBoPB6BLP7ELC4uJibN++Xal+w4YNaGlp4WQaGhro06cP3NzceLt5FhcXIzIyEnl5eRgyZAiWL18OU1NTTv7bb78hJiYGVVVVcHJywuLFi3lTAOvq6nDo0CFkZmaivr4eGzduxIgRIwC0buUQERGBK1euwMrKCiEhIbwt2W/evIm9e/eiuLgYo0ePxv/93/9BS0sLQGt+hkOHDqGgoAAikQhz587FhAkTOnwW2dnZiI2NRUREBNTVn9k/GYPBeMl4Zt9ApFIpoqOjYW5ujt69e3NFXV2dk1lYWMDU1BQ3btzAqFGjEBcXBwC4e/cuRo8ejaqqKsydOxcSiQSOjo5cDoT09HRMmjQJ/fr1w6xZsxAfHw9/f3+ubZlMBnt7e5w/fx7e3t4IDAzkOR8vLy+kp6fjnXfeQWVlJSZMmMClxi0rK4OjoyOICD4+Pvjhhx8QEBAAoDW729SpU6GnpwdfX19YW1tjypQpSE5Obvc5xMXFwc3NDZ999tkjbS7HYDAY3c6ECRO6NTn7ypUrycLC4pGvu3z5MgEguVzeKdmOHTto6NChREQUHR1No0aN4mTNzc00atQoio6OJiIiHx8fWrNmDScvLS0lPT09un79OhERBQQEkJ+fn8p+/frrr6Snp0d1dXVERNTS0kK2trYUExNDRETbtm0jJycnnm2hUEg3b97k+vIgfn5+tGzZMpVtnTx5kmxtbSktLY0AUENDg0o9xsuDg4MDAWDlb8XCwoLMzc17+s/zwpCcnEzBwcEd6jg6OlKPvoFcvnwZX3zxhVLJyMh4ZFt9+/ZFRUUFAEAikWDw4MGcTCAQYPLkyUhPT1cpF4vFGDFiBNLT0yGXy3H8+HF88MEHKtvJyMjA2LFjoaenB6B1C2oXFxcuf3NGRgYmT57Msz106FC0bZn/4ArP5uZm3LhxA/3791fZloeHBzIzM/HKK68oybKystjxS3hsYWGBR0VTUxMikajTq4s7Q69evXhv5Y+ChoZGuyvGdXR0YGJiwrY/ek7oUQcyefJk/Pe//8Xly5d55fbt2/jiiy8AAIWFhSgoKEBBQQGKioqUbLS0tOB///sf9uzZAz8/PwCAtbU1srOzuTznCoUCly5dQmVlJSe/fPkyZ6O8vBx//fUXKisrUVRUhIaGBty8eRM2NjYwMTGBh4cH1/adO3cgFot5fRCLxbh9+3an5ACwb98+bNq0Cc7Ozhg1ahSWLFmi8vmoqalBV1dXZb72O3fusOOX8Li9tMiqEAgEiIyMREVFBXJycnDv3j1ER0er1E1OTkZ9fT3q6uoglUqRmpqK2bNnK+l5eHggJycH2dnZSEtLw+uvv87JhEIhduzYgdra2nb7ZGNjg6qqKixatIhXv3DhQuTk5KC6uhq3bt1CXV0ddu7c2el7ZfQQPTmEpa6urnKIiuj/D1MZGhpyZdCgQTyZUCgkgUBAAGjLli2kUCiIiKi+vp5sbW3JycmJQkJCyNnZmSZMmMANS125coVMTEzI19eXVq1aRU5OTjRo0CA6cOAAXbx4kQQCAS1ZsoQaGhqosbGR/P39ycXFhYiIli9fTgEBAby+7tmzh8aPH09ERMOGDaP4+Hie3NvbmzZu3Midb9iwgd5//31ydHQkZ2dn+vPPPzt8hvn5+WwIi0FEjzaENXPmTCosLCSxWMx9l4YMGaJS98KFC+Tv708ASCQS0Zw5c6i4uJi2bNnC6djb25NUKiVnZ2el60UiEaWmptJXX31FCoVCZRvq6uqUkZFBly9fpqCgIK4+LCyMiouLyd3dnTQ0NAgAWVpakp2dHRvC6iE6O4T1zE/pkclk7c48qqiogFAoxMSJE9HY2Mi9Fuvq6uL333/HTz/9BJlMhsDAQGzbtg1mZmYAADs7O+Tk5CA5ORlEhA0bNsDe3h59+/aFUCiEUCjE3r17uXbXrl2LoUOHQqFQwNjYWOlNqLq6GkZGRgAAY2NjVFVVtSsHgK1bt3LHH3zwARYvXswNgTEYTwqxWIyCggIuS191dTWXDGr48OFISEiAu7u70udZKpXi6NGjKCkpQXJyMqKjo1FeXo7Vq1cjIiICKSkpSm01NjYiNjYWycnJmDNnjsr+bNq0CWlpabCysuL1MTQ0FJMmTeLlVy8uLkZxcfFjPwNG9/LMzsLqDHp6etDX10dkZCR27dqFP//8k5NpaWnBy8sLAQEBsLS0xA8//IBJkyZxcnNzc/j6+mLu3LnIz89HSUkJxo4di4EDB6KlpYWXGlMul0NdXR1CoRB2dnbIzs7m9ePatWvcFOK/y4kI169f500xfpCRI0eyLagZ3cLp06cxcuRIbNu2DcbGxjxZVVUVCgoKOswueP78echkMowfPx5Aa3rqzMxMbN68GVFRUfDy8uJ0a2pqkJCQ0G6cxcHBAe7u7ggNDeXFP1xdXVFUVMRzHoznh+fagbTh4OCA2bNnq4wl1NTUYO7cuRg8eDBcXV2V5Lm5ufDz88OqVatgYGAAIyMjeHt748MPP4RcLodCocDu3bvh6uoKNTU1TJkyBTU1Nfjqq68AABcvXsSpU6e48eK5c+fi22+/xbVr10BEiIyMhFAohJOTE3JycnDt2jWu7bKyMuzfvx/Ozs4AWr/UISEhkEgk3fGYGC8Z+fn5GDNmDGxtbSGRSBAVFQUTExMAQEFBATw9PVFTU9OhjZKSEpiamkJNTY17W5BIJEhLS8Pu3bsRFBT00H7o6+sjJiYGCxYsQFNTE09mbm6OwsJC7lwkEiE1NZUrjGebF8KBAMDOnTvx+++/IyEhAUBrHhIbGxu8+uqr0NHRwXfffcfpFhYWQiQSwdraGuPGjcPs2bMRFhbGyb/44gvU1NTA3NwcZmZmKCgowL59+wC0Do8dO3YMa9asgZGREVxcXPDJJ5/Azs4OADB69Ghs3LgRo0ePhpGREXbv3o3jx49DU1MTZWVlmDJlCgwMDNC3b18MGDAA1tbWiIyMBADk5eUhPDwcmZmZT+uxMV5wrl69Ci8vL9jZ2aFfv35ISkp6pOutrKwglUqhrq4OdXV1hISEIC4uDsePH0doaCgWLFjwUBt79uxBQkIC8vLyoK2tDYFAAHV1dWhoaODu3bvc0DLQ+g/f1q1bERcXBycnp0e+X8ZT5lkNoj8u1dXVVFxcTE1NTSrl5eXlVF5eTi0tLe3aqKqqotraWpUyhUJBd+7cabf/DQ0NVFZWpmS/paWFKioq2u1bSUlJu/1hMB5nHcirr75KRES6urodBtHbipubGzU0NJCZmRkBoOLiYhoxYgRP3jahpa307dtXKYguk8morq6OKwqFgu7fv0+JiYk0YMAAamlpoUGDBvGuGThwIBERC6L3EM/FOpDuxMDAABYWFu2mABWJRBCJRB3ONzc0NGx32qRQKORWxqtCW1sb5ubmSvbV1NRgYmLSbt8e3BKFwXgcbG1tYWBgwJ17enoiLy8P9+7dg4mJCZYtWwZtbW2l63r37o2AgADEx8cjLCwMMpkMAHDkyBGsW7cOAoEAAoEA8+bN61TswszMDPr6+lz5/vvvsWLFCvj4+CAvLw+HDx9GYmIiL07IMgs+H7ywDoTBeNmZOnUqysrKUFpaioqKCixcuBA+Pj4AWidvREZGYsCAAZz+gQMH0NjYiNzcXMyfPx+BgYEIDw/n5GFhYRAKhSgoKIBEIoGxsTFv6LerBAYGIikpCefOnYNUKoVEIkFWVhYuXrz42LYZ3cszP42XwWB0jR07dmDXrl0wNTVFXV0d6urqONmZM2dgbm4OqVQKABg3btxD7dXX12PmzJkwNDREc3Mzz14bt2/ffuiGn7NmzeKdy+VyrFu3DuvXr4dIJAIRobKyku399hzAHAiD8QIjl8tRWlqqUtbmPB6Vjqb+Pg5EhPLy8m6xzege2BAWg8FgMLpEt7+BEBGqqqpULqRraWnp7uYZjBeKtmGd7thskFTsudYddEffy8vL8frrr6tc68V4dORyeaemUXe7A2lpaUFDQwOOHDmiJBsxYgT++c9/PpFAHIPxMtD24/u0fuy7g+7ou4mJCe7cucNb78XoOhkZGZ3aFf2pxUBsbW1V1m/YsOFpdYHBeO5h01tV0xa4HzhwYA/35MVAIpF06rPGYiAMBoPB6BLMgTAYDAajSzAHwmAwGIwuwRwIg8FgMLoEcyAMBoPB6BLMgTAYDAajS7zUW5kcOHAAffr0wdSpU3n1//73v1FfX4/58+dzdXK5HCdOnEBycjLKy8thZGSEESNGYM6cOVw+g99++w0xMTGoqqqCk5MTFi9ezJsKl5iYiBMnTkAgEGDu3Ll4++23AbTOuf76669V9nHPnj1QV1fHzZs3sXfvXhQXF2P06NH4v//7P2hpaUEmk2Hz5s0qr126dCkGDx7Mq0tJScHhw4dx4MCBdncqBoDs7GzExsYiIiLioXsbMRiMl5OX+g3k1KlTKnf8TEtLw88//8ydl5aWYsyYMdi4cSP69u0Ld3d3vPrqq0hMTOT2BUpPT8ekSZPQr18/zJo1C/Hx8fD39+dshIeHY9WqVZg4cSLeeustBAQEIDY2FkBr+l0zMzNeuXPnDo4fPw6BQICysjI4OjqCiODj44MffvgBAQEBAACBQKB0rZaWFqKjoyGXy3n3VVFRgaCgIBw+fBjNzc3tPpe4uDi4ubnhs88+YxvaMRiM9unuhFIrVqwgNTU1lbLuTCjVGaZNm0YbNmxQql++fDn5+flx566urvTWW2/R/fv327Xl4+NDa9as4c5LS0tJT0+Prl+/TkREIpGIkpKSOPnJkydJLBa3m9Bq6tSpFBYWRkRE27ZtIycnJ55toVBIN2/eVHntp59+ytNvY8aMGRQaGkoAqKGhQeW1J0+eJFtbW0pLS+tQj9EzPE5CqRe5sIRST5bOJpTq8bGJ8+fP98jq2s6my/zzzz9x5swZ/PHHH9DS0mpXTyKRwN3dnTsXi8UYMWIE0tPTYW1tDalUyhtOmjx5MmQyGf766y/Y2NjwbOXk5CA5OZl7Q8nIyMDkyZN5tocOHYpz584prbyVy+XYs2cPoqOjefUHDx5EVVUVAgMDsXXr1nbvw8PDAxMnTlTaqVUqlUIkEgFoTQlsZWXFjnvo+FHR1NSEoaEhKioqntj+c7169YKmpiYqKioe+VoNDQ20tLSofAvW0dGBjo4OKisrn+vtWl4WetSBhISE4KOPPuqRttscSEpKCtauXcuTpaen47XXXgMAXL58Gb169eJtBllXV8cN7Whra0NbWxvW1ta4fPkyN2xVXl6Ov/76C5WVldDW1kafPn1w+fJl9OvXDwBw8eJFNDc3o7KyUqlv4eHh8PPzg7m5OQDgzp07EIvFPB2xWIzbt28rXfvNN99AV1cXnp6eXN2tW7ewefNmpKenP/S5qKmpQVdXV+nLe/XqVUycOJF7Zm33yY6f/nFnEQgE2LNnD9577z00NjZCX18fsbGxWLp0qZJucnIyHBwcQERoaGjA9evX8fnnn+PYsWM8PQ8PD3z66afQ1NREY2MjZsyYgT///BNA6zYr//znP7F06VL06tVLZZ9sbGyQnZ2NlStXYv/+/Vz9woULsWrVKgwYMAD37t2DhoYGPvvsM4SEhDzSPTOeMj05hNXTTJs2jcaOHUshISG8Ym9vzw1hxcTEUL9+/XjXOTo6cq/OK1euJCKiK1eukImJCfn6+tKqVavIycmJBg0aRAcOHCAiooMHD5KJiQkFBwdTUFAQTZ8+nQQCgdIwVHFxMWlpaXFDX0REw4YNo/j4eJ6et7c3bdy4kVfX0tJCtra29Pnnn3N1CoWCxo4dS0ePHiUioqKiok4NTeXn57MhrGeQRxnCmjlzJhUWFpJYLCYAZGhoSEOGDFGp+2BOdJFIRHPmzKHi4mLasmULp2Nvb09SqZScnZ2VrheJRJSamkpfffWVUk70tqKurk4ZGRl0+fJlCgoK4urDwsKouLiY3N3dSUNDgwCQpaUl2dnZsSGsHuKZGcJ6MCfzs4izs7PSkM6KFSu4PNCWlpa4c+cO7t+/z+WPPnfuHIgIfn5+3DV2dnbc0BMRYcOGDbC3t0ffvn0BAP7+/nBwcMDFixdhZmYGW1tbnDhxAhYWFry2IyIiMGnSJAwZMoSrMzY2RlVVFU+vuroaRkZGvLqkpCTcuXMHCxYs4OrCw8OhUChgaWmJCxcucENTv/76KwYPHsxysL/AiMViFBQUoKysDEDrZ6Zt0sfw4cORkJAAd3d3FBUV8a6TSqU4evQoSkpKkJycjOjoaJSXl2P16tWIiIhASkqKUluNjY2IjY1FcnIy5syZo7I/mzZtQlpaGm8oTiwWIzQ0FJMmTeLlVy8uLkZxcfFjPwNG99Lts7DGjBkDgeD5new1YcIEqKur4+jRo1ydUCiEurq6Ul4Dc3Nz+Pr6Yu7cucjPz0dJSQnGjh3LyV9//XX4+/tj6tSp+Pbbb+Hg4ABdXV1OXl1djS+//BIrV67k2bWzs0N2djZ3TkS4fv26Uo6V8PBwLFmyBDo6Olzd7du3UV9fj6CgIAQFBWHdunUAgGXLliE1NbXrD4bxzHP69GmMHDkS27Ztg7GxMU9WVVWFgoKCDrMLnj9/HjKZDOPHjwcAODo6IjMzE5s3b0ZUVBS8vLw43ZqaGiQkJLT7XXdwcIC7uztCQ0N5MU9XV1cUFRXxnAfj+eGp/LLTcxwM09XVxT//+U8EBwcjNjYWDQ0NAIDm5mbu+O/k5ubCz88Pq1atUvkGdurUKXz88cfYsmULr37//v2wtrbmYg1tzJ07F99++y2uXbsGIkJkZCSEQiFvIsClS5eQmZmpNL4dHR2Na9euceXs2bMAgKysLPj6+uLKlSsIDQ1VmvLLeP7Jz8/HmDFjYGtrC4lEgqioKJiYmAAACgoK4OnpiZqamg5tlJSUwNTUFGpqatzbgkQiQVpaGnbv3o2goKCH9kNfXx8xMTFYsGABmpqaeDJzc3MUFhZy5yKRCKmpqVxhPNv0+Cys54Hly5fDwMAA27dvx6JFi2BgYID6+nr07t0b06ZNA9A6S8be3h69evVCXV0dli5ditDQUM5GfHw890Otr6+PAwcOwMXFhZM3NTVh79692Llzp1L7o0ePxsaNGzF69Gioq6vDyMgIx48fh6amJqezc+dO+Pn5KQXbH8bZs2exfft2BAcHo3fv3o/6aBjPOFevXoWXlxf69++PyMhIJCUlwcHBodPXW1lZQSqVQl1dHerq6ggJCcGlS5f+H3v3HhZVtccN/MsAclXkMowK6lHA1NDyQICioYmmgKkhKYqKoGSi5TUvB0VPpcIxMZDsBCigHQ3KSxSek5IoKmD5SnnBMAJHBgdmEBCG2zD+3j943a+7Ga6Coq7P8+znmVlr7bXXjMhir7X2+gFomqT/4IMPeJPhmuzZswcHDx5Efn4+9PX1IRAIoKOjA11dXdy7d497EBdoupP5+OOP0a9fPyQkJHTsQzNPTldPoiclJXXbSfSOuH//PkkkEqqurlbLKy0tpdLSUo3PdjQ2NpJEIqHy8vIOX7u2tpZKSkqafXakI1QqFUml0k6rj+laj/McyIABA4iIyNDQsMVJ9IfH1KlTqba2liwsLAgASSQSGjVqFC//ypUrvHOsra3VJtHlcjlVV1dzR2NjI9XV1VFycjLZ2NjQgwcPaMiQIbxzbG1tiYjYJPpT0tZJ9C4fwqqsrMSWLVu6+jJPTM+ePdGvXz8YGRmp5QmFQgiFQo0xn7W1tdGvXz+1ie/20NfXh6WlZafGlBYIBO2+a2GeDfb29rwh1GnTpiE/Px81NTUwMzPDihUruIUhj+rTpw8CAgKQmJiI0NBQbkHJ4cOHsXHjRggEAggEAvj5+bVp7sLCwgLGxsbccfz4caxcuRI+Pj7Iz89HQkICkpOTeXN6LPLis+GJzIH8dayfYZiu5+XlhZKSEkilUpSVlSEwMBA+Pj4AAAcHB0RGRsLGxoYrHxMTg/r6euTl5WHBggUICgpCeHg4lx8aGgptbW0UFhZCLBbD1NQUoaGhj93OoKAgpKam4uzZs5DJZBCLxbh8+bLGbYaY7kXr9ddfp7Nnz3bZBWJjY7FkyZJneiKdYbqL0aNHt+sXq66uLszNzVFdXY3q6mpenlAoVNtxoC1MTEygUqnU6ntcWlpaEAqFICKUl5e3ax+2fv36obGxkVuyzDyen376CceOHUNUVFSzZcaOHcsm0RnmeaZUKiGVSjXmdaTzANDi0t/HQUQoLS3tkrqZrvHsPqDBMAzDPFXsDoRhniEPn9fpzIUUj3oSQ81d0XaZTIZRo0bxdodgOq6+vh5DhgxptRzrQBjmGfLwF/yzPKfYFW3v1asXbt26hY8++qjT634R5eTk4I8//mi1HOtAGOYZ8ujDo8z/p6enh8bGRl7YA6bjdHR01PZI04TNgTAMwzAdwjoQhmEYpkNYB8IwDMN0COtAGIZhmA5hHQjDMAzTIawDYRiGYTqk2yzjTU9PxzfffMNLMzY2xs6dO3l5hoaGGDBgAHx8fHi7yP7888+IjY1FRUUF3Nzc8O677/J29ExOTsaJEycgEAgwd+5cTJkyhXet6upqxMfHIzs7GwqFAps3b8aoUaO4fLlcjrCwMAQEBGDYsGG8c4kI3377Lf773/+irKwMs2bN0vhA05kzZ5CQkICYmBjo6uo2+13k5OQgLi4OERER0NHpNv9EDMMwPN3mDiQnJwcpKSno06cPd1haWnJ533//PaytrWFgYICTJ0/CxsYG165dAwBcuHABEydOxN/+9jfMmjULiYmJ8Pf35+oODw/H2rVr8cYbb2D8+PEICAhAXFwcly+Xy+Ho6Ihz585hxowZCAoKgrm5OZefnZ0NZ2dn7Nu3jxc9DWjqPN555x2EhYVh7NixWLZsGYYOHar2+crKyrB06VIkJCRApVI1+z3s378fU6dOxd69e9u1mRzDMMwT19UBpWJiYghAq+UiIiLI1dW1zXlTpkyhFStWEBGRj48Pffjhh1yeVColIyMjun79OhERCYVCSk1N5fJTUlJIJBJxgZkCAgJo3rx5Gq8tlUrJysqKfvzxR7K1taWTJ0/y8hMTE8nW1pZqa2tb/Hxvv/02hYSEEIBmy6akpJC9vT1lZGS0WI55cT1OQKnn+WABpTpXtwko9VBJSUmzR3OxxVtibW2NsrIyAIBYLOYNK4lEIowaNQoXLlxAXV0dZDIZL3/y5MmQy+X4448/oFQqkZSUhPfff1/jdUQiEW7evIlJkyZpvCM4dOgQlixZojEwz0MHDhxARUUFgoKCWvxMnp6eyM7ORv/+/dXyFAoFe81eg2G6ky7vQLS1taGtrY1XXnml2cPX1xdA0wZehYWF3KFpu2mlUon09HQcPXqUO2/w4MG4cuUKV6a0tBR//PEHysvLoa+vj759+/Lys7KyoFKpUF5ejjt37qC2tha3bt2CnZ0dzMzM4OnpyXuM39jYGIDmPXxyc3NhYGAAR0dHmJmZ4e9//zsyMjK4/D///BNbt25FQkJCq5vIaWlpwdDQUON19u3bx16z1+iIHj16QCgUQiDovP/uPXv25A3ztoeurm6zEQcNDAxgZmbWZZtFMp2sq4ewDhyYgpPIAAAgAElEQVQ4QIaGhq2Wi4iIIG1tbTIxMeGOgIAALg8AaWtrk5aWFhkbG9Px48e5c3/99VcyMzMjX19fWrt2Lbm5udGQIUMoJiaGa4OZmRktX76cli5dSjNnziSBQEC3bt2irKwsEggEtGzZMqqtraX6+nry9/cnd3d3tTYOHDhQbQhLX1+fxo4dS3fv3qUHDx5QTEwMmZubU2VlJTU2NtKYMWPoyJEjRER0586dNg1NFRQUsCEsRqP2DGEJBAKKjIykqqoqksvlVFdXR9HR0RrLpqWlkUKhoOrqapLJZJSenk6zZ89WK+fp6Um5ubmUn59PN27coKFDh3J52tratHPnTqqqqmq2TXZ2dqRQKGjp0qW89MDAQMrNzaWGhgaqqKgghUJBYWFhbAjrKWnrEFa3WuLj4uKC8+fPa8wbPXo0fvzxR8hkMrzyyiswNDTk8kaOHInc3FykpaWBiPCPf/wDjo6OsLa2BgD4+/vDxcUFWVlZsLCwgL29PU6cOIF+/fqhoqIC2tra+Oyzz7gVTxs2bMCIESPQ2NjY6ioobW1tfPzxx+jTpw8AYPHixdi8eTOuXLmCixcvorGxEVZWVjh//jx3R3Xx4kUMGzYMffv2fezvjGGaM3PmTEyfPh22trYoKSmBiYkJrKysNJbV09NDcHAw4uPjIRQKMXHiROzevRvDhw/nwtY6OjoiPj4e77zzDs6cOcM7XygUIjk5GUVFRTAwMNB4DR0dHSQmJiIvL4+XHhoaiqCgICxZsgSnTp2CUqmElZVVh+9wmCenW3UgLREIBDA2NoaxsTH+8Y9/IDg4GFevXoWenh4AwNLSkhvSunLlCoqLizFmzBju/KFDh3Kro3bv3g0XFxcYGhrC1tYWDx48QElJCfefS6lUQkdHp9nb7Ee99NJLKCoq4qUplUro6emhqKgICoUCS5cuBQBuDmXFihUICQnh2sswXUEkEqGwsJAL81pZWclFE3z11Vdx8OBBeHh4qO26KpPJcOTIERQXFyMtLQ3R0dEoLS3FunXrEBERodZ5AE3Dz3FxcUhLS8OcOXM0tmfLli3IyMjAwIEDeW0MCQnBxIkTce7cOS5dIpFAIpE89nfAdK1us4y3PVatWgUA2Llzp1peXl4e5s2bh7Vr16JXr15q+T/88AM++ugjbNu2DQDQu3dvzJgxA6tXr4ZSqURjYyN2796NSZMmtWkcdtGiRdi2bRs3oR8XF4cePXpg5MiRiI6OxrVr17jj9OnTAIDLly/D19cXv/76K0JCQrggQQzTmU6ePAkHBwds374dpqamvLyKigoUFha2GJ723LlzkMvlGDduHADA1dUV2dnZ2Lp1K6KiovDWW29xZe/fv4+DBw82O8/i4uICDw8PhISE8P4wmzRpEu7cucPrPJhnxzPZgfTo0QMRERHYsWMH/vjjD9y+fRtCoRCDBw/G2LFjMXv2bO62GwASExMxYMAA9O3bFytXrkRMTAzc3d25/H//+9+4f/8+LC0tYWFhgcLCQnz++edtasuyZcvg6ekJGxsbiEQi7NixA0lJSbwhtuacPn0aO3bs4DofhulMBQUFGD16NOzt7SEWixEVFQUzMzMAQGFhIaZNm4b79++3WEdxcTHMzc2hpaXF3S2IxWJkZGRg9+7d3N11S4yNjREbG4uFCxeioaGBl2dpacl7tkooFCI9PZ07mG6uu0yiP67S0lIqLS3lnu14VGNjI0kkEiovL2+xjoqKCqqqqurQ9Wtra0kul7frHJVKRVKptEPXY15MHX0OZNCgQZSSkkJZWVka88+fP0/+/v5q6XK5nGbOnEm6urpEROTk5MTlzZkzhzIzM3nlra2tqbGxkZcWGxtL69evJ319fdLX16ejR4/S8uXLSVdXl/z9/enq1atcWT09PXJ3d6cFCxYQEbFJ9KfkmZxEfxxCobDZPG1tbfTr16/VOkxMTDp8fX19/RafBdFEIBDwtmNhmK5SUFCA4OBg3L59G4aGhqipqWn1nKlTp8LIyAgZGRlQKpUoLi7mDbdWVla26Wd+xowZ0NfXx+bNmwE0/V/x8PCAm5sbNmzYgP3792PIkCHIy8tDfX09Tp8+DVtb245/WOaJeSaHsBiGaZ29vT1vHnDatGnIz89HTU0NzMzMsGLFCo0dQJ8+fRAQEIDExESEhoZCLpcDAA4fPoyNGzdCIBBAIBDAz8+vTXMXFhYW3AIYY2NjHD9+HCtXroSPjw/y8/ORkJCA5ORkjBgxgjunLQtYmKePdSAM85zy8vJCSUkJpFIpysrKEBgYCB8fHwCAg4MDIiMjYWNjw5WPiYlBfX098vLysGDBAgQFBSE8PJzLDw0Nhba2NgoLCyEWi2Fqasqba+yooKAgpKam4uzZs5DJZBCLxbh8+TKysrIeu26maz03Q1gMw/Dt3LkTn376KczNzVFdXY3q6mou79SpU7C0tOSeTRo7dmyr9SkUCnh7e8PExAQqlYpX30NFRUWtPjs1a9Ys3nulUomNGzdi06ZNEAqFICKUl5ezzUSfAawDYZjnmFKphFQq1Zinaaugtmhp6e/jICKUlpZ2Sd1M12AdCMM8Q+rr67t0nyjSsA9bZ+uK9stkMowcORIrV67s9LpfRFVVVW1aIME6EIZ5hjx48OCJ/JLvSl3RfiMjI9y6dQtLlizp9LpfRL///jsqKipaLcc6EIZ5hjS3z9SLztDQEI2NjXj33XefdlOeCz/99BOOHTvWajm2CothGIbpENaBMAzDMB3COhCGYRimQ1gHwjAMw3QI60AYhmGYDmEdCMMwDNMhbBnvE5Seno5vvvkG06dPx6RJk9TyP/vsM9y6dQv//Oc/UVZWhqioKERERHAby6lUKqxevRqzZs3igvwATUGyCgoK4ODggK+++krjtffs2QMdHR0UFRUhMjIS+fn5sLKywuLFizFy5EiuXFpaGhISElBbWwtvb29edLn6+npERUXh0qVLsLS0xLJlyzB8+HAuv7W6k5OTceLECQgEAsydOxdTpkxp8fuSy+UICwtDQEAAhg0b1sq3yzDMk8buQJ6gnJwcJCQk4J///Kdanlwux9atW/H555/j/v37EIlE+Pzzz/F//s//4cpcvHgRUVFR2LdvH+/c6OhoFBcXQ09PDxYWFrzj7t27SEpKgkAggEKhgIuLCxoaGvDee+/BysoKrq6uyM3NBdAU4Oqtt97CK6+8gjfffBOrV69GTEwMd52ZM2fi+++/x6xZs2BlZYXRo0fjt99+A4BW6w4PD8fatWvxxhtvYPz48QgICEBcXFyz31V2djacnZ2xb98+XsAhhmG6kecloNSzICIigqZPn06GhoZ069YttTxfX18CQAUFBUTUFDwoLCyMK7NhwwZ68803qXfv3qRUKomISKlUkrGxMaWlpWm8ppeXF4WGhhIR0fnz56lnz568/Ndff50+//xzIiKaPHkybd26lctLTk6m/v37ExHR9evXSU9PjxeUa82aNeTj49OmuoVCIaWmpnJ5KSkpJBKJNAYAk0qlZGVlRT/++CPZ2trSyZMnNX62F1FHA0o97wcLKNW52hpQit2BPGEGBgaYMWMG4uPjeekHDhyAr68vL83d3R1nzpzh3v/www8IDg6GiYkJzp8/DwD4+eefoVKp4Orqqnat3NxcpKWlYdmyZQAAOzs7KJVKLlTonTt3cPPmTTg5OQEAMjMzeUNrD+NV5+fnQywWo0+fPujduzeXP3XqVFy4cKHVuuvq6iCTyXjDUJMnT4ZcLscff/yh1m6RSISbN29i0qRJbEdWhunGXpgO5M8//4S9vT1MTU2fyrF3714AQGNjI/z9/ZGYmIgHDx4AAH755RdUVVWpbant7u6O8+fPo7GxEXfu3EFeXh4mTJgAT09PpKSkAADOnDmDsWPHQk9PT+0zh4eHY968ebC0tATQFH/62LFjmD17Nnx8fODq6oqoqCg4ODhAoVCgqqqKFyHRxMQEenp6KCoqwuDBg3H37l2UlJRw+RcuXEB5eXmrdevr66Nv3764cuUKd25WVhZUKhV3/l8ZGxsDUN83KSwsjL1upx49ekAoFEIg6Lz/7j179oS5uXmHztXV1W02YJSBgQHMzMy6dMNIphO9KENYx48fJ09PTyovL38qR0hICEVERJC3tzepVCrq378//fjjj0RE9N5779HWrVupvLycN4RVX19PRkZGdPHiRdq3bx+5u7sTEVFqairZ2dkREZG7uztvmOshiURCenp6dP36dV76vn37yMbGht59912ytLSkDRs20IMHD7hri8ViXvnevXtzw2MBAQFkZ2dHa9eupVmzZtGUKVPIysqq1bqJmn4OzMzMaPny5bR06VKaOXMmCQQCtaG8vxo4cCBvCKu2tvaFft2eISyBQECRkZFUVVVFcrmc6urqKDo6WmPZtLQ0UigUVF1dTTKZjNLT02n27Nlq5Tw9PSk3N5fy8/Ppxo0bNHToUC5PW1ubdu7cSVVVVc22yc7OjhQKBS1dupSXHhgYSLm5udTQ0EAVFRWkUCgoLCyMDWE9JW0dwnqhOpDp06c/1TY87ECIiDZt2kRz586l2tpaMjMzo4KCArUOhIhoypQptH37dpoxYwZ9+umnRNT0i8TQ0JCuXbtGhoaGdPnyZbVrrV27ljw8PHhpKSkpZG1tTVKplIiIZDIZjRo1iv75z39SY2Mj6ejo0G+//caVV6lUpKOjw6v/3LlzFBMTQ5mZmXTw4EFydnZute6HcnNz6cCBA5SSkkIFBQUkEAhIoVC0+J39tQN50bWnA/H29qbbt2+TSCQiAGRiYkLDhw/XWPb8+fPk7+9PAEgoFNKcOXNIIpHQtm3buDKOjo4kk8lowoQJaucLhUJKT0+nQ4cOUWNjo8Zr6OjoUGZmJl25coXXgYSGhpJEIiEPDw/S1dUlAGRlZUUjR45kHchTwuZAujl/f38cO3YM8fHxePXVV/G3v/1NYzl3d3dkZWXh3Llz8PDwAADo6+tj4sSJ2L17NwwMDDBq1CjeOZWVlfjyyy+xZs0aXvrZs2fh7u7ODVNZWFhg/vz5SE9Ph7a2NoYPH46cnByu/M2bNwEAQ4cO5dLGjRuHxYsXw8XFBUlJSZg4cWKrdT80dOhQ+Pv7w8vLC0ePHoWLiwsMDQ078O0xbSESiVBYWMgNO1ZWVuLGjRsAgFdffRVXr15F//791c6TyWQ4cuQIfH19sWnTJm4IdN26dYiIiODNyz1UX1+PuLg4fPjhh822Z8uWLcjIyEBeXh6vjSEhIfD19UVqaiqUSiUAQCKRcCv8mO6LdSBPiZ2dHUaNGoU1a9Zg0aJFzZZ7OJFuYmLC+0Xu5eWF5ORkvPHGG2rjxV988QUGDx6MN954g5c+cuRInDt3jotEV1NTg5SUFDg6OgIA5s2bhz179qCyshINDQ3YunUrpk+frvZLXqVSYceOHcjOzsb777/fprof9cMPP+Cjjz7Ctm3buLQdO3bg7NmzrX5vTNudPHkSDg4O2L59O0xNTXl5FRUVKCwsbDG64Llz5yCXy7lnjlxdXZGdnY2tW7ciKioKb731Flf2/v37OHjwYLPzLC4uLvDw8EBISAhv/uPhQo1z5849zkdlnpIu70CEQmGbIlu9iBYtWgRtbW28/fbbzZYZOXIkDAwMuLuPhzw9PVFVVQV3d3deekNDAz777DOsXr1arS4/Pz9Mnz4dQ4cOhb29PQYMGIB+/fohNDQUALBq1SoMHToUIpEIpqamKCoq4ib/ASAoKAi2trawsLBAamoqTp8+zd1xtFZ3YmIiBgwYgL59+2LlypWIiYnhtX379u1ISkpq5zfItKSgoACjR4+Gvb09xGIxoqKiYGZmBgAoLCzEtGnTcP/+/RbrKC4uhrm5ObS0tLi7BbFYjIyMDOzevRtLly5ttR3GxsaIjY3FwoUL0dDQwMuztLTkPecjFAqRnp7OHUw319VzIDdv3qQtW7Z06TXaojvMgXQXKpWKpFIpNTQ0aMyvrKyke/fuqaXX1tbSnTt3Wpy3aK7uxsZGkkgkvOdIHiWTyZptD/P/dfQ5kEGDBlFKSgplZWW1Ogfy6CGXy2nmzJmkq6tLREROTk5c3pw5cygzM5NX3traWm0OJDY2ltavX0/6+vqkr69PR48epeXLl5Ouri75+/vT1atXubJ6enrk7u5OCxYsICJicyBPSbeaA/n666+fxGWYNhIIBBCJRNDV1dWY36tXL7UhD6Bp7sXa2rrFeYvm6tbW1ka/fv14z5E8ysLCotn2MI+voKAAwcHBcHZ2bvO809SpU2FkZISMjAwolUoUFxdzcxRA05xKW0YXZsyYgc2bN0Mul0Mul+Ott97Crl278J///AcZGRl4+eWXMWTIEABNcymnT5/GxYsXO/ZBmSeKzYEwzHPK3t4evXr14t5PmzYN+fn5qKmpgZmZGVasWKGxA+jTpw8CAgKQmJiI0NBQyOVyAMDhw4exceNGCAQCCAQC+Pn5tWnuwsLCAsbGxtxx/PhxrFy5Ej4+PsjPz0dCQgKSk5MxYsQI7pzmnhNhuhfWgTDMc8rLywslJSWQSqUoKytDYGAgfHx8AAAODg6IjIyEjY0NVz4mJgb19fXIy8vDggULEBQUhPDwcC4/NDQU2traKCwshFgshqmpKTfH9TiCgoKQmpqKs2fPQiaTQSwW4/Lly8jKynrsupmuxXbjZZjn1M6dO/Hpp5/C3Nwc1dXVqK6u5vJOnToFS0tLbtXcX3dB0EShUMDb2xsmJiZQqVS8+h4qKiqCjk7Lv1ZmzZrFe69UKrFx40Zs2rQJQqEQRITy8nK2jc0zgHUgDPMcUyqVkEqlGvMedh7t1dLS38dBRCgtLe2Supmu0a07kFOnTnXaD9Tly5d5E4AM8yxiP8OalZeXw8bGBhEREU+7Kc+FkpKSNt0BdtsOJDMzEx9++CFefvnlTqmvqKgIf//73zulLoZ5mrpyo0H6y+aVXaEr2i8QCCCVSnHnzp1Or/tFJJVKYWFh0Wq5btuB1NTUwNzcHIcOHeqU+k6cOIEDBw50Sl0M87To6uo+kV/yXakr2m9iYoLGxkbs3r270+t+Ef300084duxYq+XYKiyGYRimQ1gHwjAMw3QI60AYhmGYDmEdCMMwDNMhrANhGIZhOoR1IAzDMEyHdNtlvMyLQSKRYMeOHRg+fDiWLVumlp+amorU1FTMnz8fzs7O+PbbbzVGxBs0aBAXgfHWrVv47LPPIJFI4OzsjFWrVkFPTw8AcPXqVcTHx6OwsBBCoRBz587F66+/zmtPZGQk8vPzMXz4cHzwwQcwNzcHAGzevBnl5eVq1548eTIvuBIAnDlzBgkJCYiJieF2GW6p7uYkJydDLBarRZdkmO6A3YEwT5VMJkNCQgLWrVunMbhRSEgIEhISkJubCwAwMjKChYUF7/j666+58KclJSVwdXUFEcHHxwffffcdAgICADQFR/Ly8oKRkRF8fX0xePBgvPnmm0hLSwMA3Lt3D87OzqioqMDcuXMhFovh6uqKmpoaAICpqanatQ8fPswLiAQAZWVlWLp0KRISEqBSqdpU9181NDRgxYoVCAoKQnJycid80wzTBZ5EQKmXXnqp3eedPn2aJk6c2GntYAGluqcrV67QgAEDaMyYMRQTE8PLy8nJoYEDB9Lo0aPpwIEDGs8/cuQIWVhYUGlpKRERbd++ndzc3Lh8qVRK2tradOvWLSJqCnj1qHnz5tGKFSuIiCg6OpqcnJy4PJVKRU5OThQdHa3x2pcvX6ZevXpRZWUlL/3tt9+mkJAQAkC1tbUdqnvNmjXk4+NDX375JTk7O3PpHQ0o9bwfLKBU5+pWAaUYpiUNDQ3w9/dHfHw8Lz0uLg7+/v6or6/XeJ5MJsPy5cuxd+9eCIVCAE1b4EyePJkrIxKJMGLECC7e+qMxu1UqFW7cuIFBgwYBAMRiMYYNG8blCwQCTJ48GRcuXNB4/bCwMAQGBvJibhw4cAAVFRUICgrilW1v3du2bUNSUhJ69OihMZ9huoMXZg5EJBLh9u3bGD169NNuCvP/vPbaawgICEBjYyNmz56NlStX4tatW7Czs0NDQwMOHz6MS5cu4fjx4xrPX7ZsGcaNG4fZs2dzaXfv3uXitD8kEolQVFTEvf/8888hlUqRnp4OJycnbu5l8ODB+O9//wsigpaWFhobG3Hp0iWNwY0KCgpw4sQJ/P7771zan3/+ia1bt2rsFNpTN9A0VAeob/vxyiuvtDtORo8ePWBiYoKysjI8ePCgXec2p2fPnujRowfKysrafa6uri4ePHjADe89ysDAAAYGBigvL3/mt2x5EbwwHYiLiwsSExOhUCiedlOY/8fExASRkZEgIvTq1QszZsxAfHw8PvnkExw/fhz29vbc3cFfJSUl4cyZM7h+/TovXalUqv3VbmBgwPtlVVxcjJKSEjx48AB5eXkoLCzESy+9BD8/P0RFRWHChAlwcXHBpUuXoFKp0L9/f7Xr79q1CzNmzMDAgQMBNN3NzJ8/H+Hh4bC2tuZ1WADaVXdLCgoK2lxWIBBgz549WLRoEerr62FsbIy4uDgEBwerlU1LS4OLiwuICLW1tbh+/Tr27dunFo7a09MTu3btQo8ePVBfX4+3334bN2/eBNAURfCTTz5BcHAwevbsqbFNdnZ2yMnJwZo1a/DFF19w6YGBgVi7di1sbGxQU1MDXV1d7N27F+vXr2/z52WevBemAwHAC5nJdA/vvvsuN0ns7++PwMBAfPTRR9i/fz8WLVqk8RyZTIbg4GBERkaq3W2YmpqioqKCl1ZZWcmLxf7xxx9zr99//328++67SE9Ph6GhIX755Rf873//g1wuR1BQELZv3662K6lcLseBAwe4YTEACA8PR2NjI6ysrHD+/Hku1sbFixcxbNgw9O3bt011t0bTQoPmzJw5E9OnT4etrS1KSkpgYmICKysrjWX19PQQHByM+Ph4CIVCTJw4Ebt378bw4cO5qIOOjo6Ij4/HO++8o7YSTigUIjk5GUVFRTAwMNB4DR0dHSQmJiIvL4+XHhoaiqCgICxZsgSnTp2CUqmElZVVqyvUmKfvhepAmO5t4sSJAICEhARkZ2fj22+/1Vhu2bJlGDNmDObOnauWN3LkSOTk5HDviQjXr1/Hxo0bNdbl4ODAGyLT09PjluTW19fju+++w1dffcU7JyoqCo6Ojnjttde4tKKiIigUCixduhQAuFgKK1asQEhICHx9fdtUd2cSiUQoLCxESUkJgKaO9GEwqFdffRUHDx6Eh4eH2hboMpkMR44cQXFxMdLS0hAdHY3S0lKsW7cOERERGpdR19fXIy4uDmlpaZgzZ47G9mzZsgUZGRncXdvDNoaEhGDixIm8+OoSiQQSieSxvwOma7FJdKbbEAgEmD9/PpYvXw5vb29uHuBRSUlJOHnyJD7++GPI5XLuuHfvHgBg7ty5OHr0KK5duwYiQmRkJLS1teHm5obc3Fxcu3aNq6ukpARffPEFJkyYoHad+/fvY+7cuRg2bBgmTZrEpdfU1CA6OlrtuYzo6Ghcu3aNO06fPg2gKZCZr69vq3X/+uuvCAkJ6dSAUSdPnoSDgwO2b98OU1NTXl5FRQUKCwtbjC547tw5yOVyjBs3DgDg6uqK7OxsbN26FVFRUbxnX+7fv4+DBw/yFik8ysXFBR4eHggJCeHN+0yaNAl37tzhdR7Ms4N1IEy34u/vj5qaGvj7+2vMP3DgABQKBUaOHAmhUMgdQ4YMAQA4Oztj8+bNcHZ2Ru/evbF7925uNVNJSQnefPNN9OrVC9bW1rCxscHgwYMRGRnJ1T9ixAjY2dlhwIABMDAwUIuJEBcXB1NTU0ybNq3dn62luk+fPo0dO3Z0aFK6OQUFBRg9ejTs7e0hFosRFRUFMzMzAEBhYSGmTZvW6pBYcXExzM3NoaWlxd0tiMViZGRkYPfu3dwdV0uMjY0RGxuLhQsXoqGhgZdnaWnJe45GKBQiPT2dO5hu7kV5DoR5sdTW1lJJSQk9ePCAl/7gwQMqKysjiURCDQ0NaudVVlY2m/e4WqpbpVKRVCpttY6OPgcyaNAgSklJoaysLI3558+fJ39/f7V0uVxOM2fOJF1dXSIicnJy4vLmzJlDmZmZvPLW1tbU2NjIS4uNjaX169eTvr4+6evr09GjR2n58uWkq6tL/v7+dPXqVa6snp4eubu704IFC4iI2HMgT0lbnwNhcyDMc0lfXx/6+vpq6VpaWtxf4Zr06tWL91xHZ2qpboFAoLYgoDMVFBQgODgYt2/fhqGhYbNPwD9q6tSpMDIyQkZGBpRKJYqLi3lDbJWVlRq/47+aMWMG9PX1sXnzZgBN/zYeHh5wc3PDhg0bsH//fgwZMgR5eXmor6/H6dOnYWtr2/EPyzwxbAiLYZ5T9vb2vA5r2rRpyM/PR01NDczMzLBixQqNHUCfPn0QEBCAxMREhIaGQi6XAwAOHz6MjRs3QiAQQCAQwM/Pr01zFxYWFjA2NuaO48ePY+XKlfDx8UF+fj4SEhKQnJzMWyXZ3PMxTPfCOhCGeU55eXmhpKQEUqkUZWVlCAwMhI+PD4Cm1WeRkZGwsbHhysfExKC+vh55eXlYsGABgoKCEB4ezuWHhoZCW1sbhYWFEIvFMDU15Zb4Po6goCCkpqbi7NmzkMlkEIvFuHz5crsfmGSePDaExTDPqZ07d+LTTz+Fubk5qqurUV1dzeWdOnUKlpaW3PMqY8eObbU+hUIBb29vmJiYQKVS8ep7qKioCDo6Lf9amTVrFu+9UqnExo0bsWnTJgiFQhARysvLuaXQTPfFOhCGeY4plUpIpVKNeQ87j/Zqaenv4yAilJaWdkndTNdgHQjDPEPYX+WaKRQKWFpa4n//+9/Tbspz4ffff2/TvmmsA2GYZ4yWllaX1EtPaPPCrmh/XV0dqqursW/fvk6v+0VUVVUFR0fHVmQqNCIAACAASURBVMuxDoRhniE6OjrP/C61XdF+c3NzNDY2NrtzM9M+P/30k9pDtJqwVVgMwzBMh7AOhGEYhukQ1oEwDMMwHcI6EIZhGKZDWAfCMAzDdAjrQBiGYZgOYct4n6La2lp89dVXyMjIQFVVFQYNGoSFCxdi5MiRamUzMzORmJiI6OhotaA9EokEkZGRyM/Px/Dhw/HBBx/A3NwccrkcW7du1Xjt4OBgDBs2DCUlJYiOjsaNGzdgaWmJgIAA3vrvnJwc7N+/H3fv3oWdnR2WL1+Ofv36AWh6kvnf//43fv31VxgZGWHChAmYP38+177W6tYkJycHcXFxiIiIaHVLDIZhni52B/KU3Lt3D66urvjyyy/h5OQEb29vAE17EiUkJKiV37VrFxITE3Hq1Cm1epydnVFRUYG5c+dCLBbD1dUVNTU1EAgEsLCw4B16enqIjo6GUqlEVVUVnJycUFlZiXfeeQd9+/bF2LFjcenSJQBAdnY2PD09IRKJMGfOHNy5cwcuLi64f/8+iAheXl4oKirCjBkz8Prrr2PLli1ch9Va3Zrs378fU6dOxd69e9kT1wzzLGABpZ6O9957j0aNGqUWXOibb74hQ0NDkkgkXFppaSkZGhpSSEgI+fj48MpHR0eTk5MT916lUpGTkxNFR0drvO6uXbvIzc2Ne19VVcXL9/b2prVr12rMV6lUJBQK6fvvv+fePyomJoZGjBjR5roflZKSQvb29pSRkUEAqLa2VmO5F11HA0o97wcLKNW52hpQit2BPAWNjY04fPgwVq1aBV1dXV6et7c3rK2tkZSUxKUlJCRg/PjxePfdd5GSksLFZwAAsViMYcOGce8FAgEmT56MCxcuqF1XqVRiz549WL16NZdmbGzMK6NSqXgxIlrK/+tQ2m+//YZBgwa1ue5HeXp6Ijs7G/3799eYzzBM98M6kMdUVVWFoKAgLFq0qM2HRCJBRUUFL4DOo+zt7XH9+nXufVxcHPz9/WFtbQ1XV1ccPHiQyxs8eDBycnK47SEaGxtx6dIllJeXq9X7n//8B4aGhs3G87516xbOnDmD+fPna8z/6quvIBQKMW7cOC4tJSUFH3/8MWbOnIm8vDxERUV1qG4tLS0YGhqqbXNx8+ZN7vWJEyfY6w7o0aMHhEKhWof/OHr27Alzc/MOnaurq9tswCgDAwOYmZl12X5fTOdiHchjSkxMxO3bt+Hm5tbm49NPPwUAGBkZaazTyMgIdXV1AIDz589DKpVi8uTJqKurg6+vL+Li4riyfn5+UKlUmDBhAjZs2MCV+2vYViLCrl27sGrVKo3/OcvKyjB9+nRs27YNQ4YMUcu/dOkSVq1ahfj4ePTo0YN3XnFxMerq6lBSUoLffvut3XW3pHfv3tzrgQMHstftIBAIEBkZibKyMuTm5qKmpgbR0dEay6alpUGhUKC6uhoymQzp6emYPXu2WjlPT0/k5uYiJycHGRkZGDp0KJenra2NnTt3oqqqqtk22dnZoaKiAkuWLOGlBwYGIjc3F5WVlfjzzz9RXV2NsLCwdn9m5gljcyCPZ+/evRQcHNyuc6qqqkggENDp06c15r/++uu0YcMGIiLy9/fXOOabmZnJla+rq6MTJ05QXFwc5efnU2BgIK1fv55X5/fff0/m5uZUU1Ojdr3Kykp67bXX6B//+IfG9vz222/Ut29f+uGHH1r8XN9++y0ZGRlRdXV1m+v+q4KCAjYH0oL2zIF4e3vT7du3SSQSEQAyMTGh4cOHayx7/vx57mdNKBTSnDlzSCKR0LZt27gyjo6OJJPJaMKECWrnC4VCSk9Pp0OHDlFjY6PGa+jo6FBmZiZduXKFli5dyqWHhoaSRCIhDw8P0tXVJQBkZWVFI0eOZHMgTwmbA+nGjI2N4eLigiNHjqjl3b59GxcvXsTUqVNRVVWF5ORkZGdno7a2ljv+eheip6eHt956CwEBAbCyssJ3332HiRMn8uoNDw/HsmXLYGBgwEu/f/8+Jk+ejIkTJ+Ljjz9Wa8/169cxdepUfPHFF/Dw8Gjxczk4OEChUKCkpKRNdTNdSyQSobCwkPv3qKysxI0bNwAAr776Kq5evapxzkkmk+HIkSPw9fXFpk2bYGlpCQBYt24dIiIicObMGbVz6uvrERcXhw8//LDZ9mzZsgUZGRnIy8vjtTEkJAS+vr5ITU2FUqkE0LQ0XdPdLNO9dPlCe0NDQ+jr62PSpEntOu/evXu8oZLnzSeffIIpU6bgtddew8KFC6Gnp4e8vDwEBARgypQpeP311/Hvf/8bdnZ2cHJy4p27ePFizJgxA3v27OENg92/fx+LFi3CsGHDeN/3pUuXkJ2dzZuYB5rmb6ZMmYIRI0ZgzZo13OS8lpYWzM3Ncf36dbi7u+OTTz7BmDFjuPwePXqAiPDzzz/jjTfegEAgQH19PcLCwjBo0CAMHDiw1borKiqwY8cOBAcHY8CAAV3yHb/oTp48ifDwcGzfvh3/+te/ePNiFRUVKCwsbDG64Llz5yCXyzFu3Dh8++233LLzrVu3wtzcHKdOncJ3330HoOln7+DBg7C2ttZYl4uLCzw8PDBmzBj85z//4dInTZqEO3fu4Ny5c530qZknqcs7kP79++PQoUPNhtVszpUrV3Dv3r0uatXTN378eJw4cQIbN27E8uXLudVJAQEB2LlzJ4CmyfOAgAC1cydMmABLS0t8/fXXCAgIwIgRI1BXVweZTAYvLy+1ffzDwsIwb948iEQiXnpqaioyMzORmZmJ2NhYLl1bWxuNjY3Yu3cvpFIpAgMDeedNnDgRR44cwerVq5GXlwehUIiysjI4ODggJSUF2trardadn5+P8PBwODo6sg6kixQUFGD06NH45JNPIBaLER8fj9DQUNy7dw+FhYXNLqZ4VHFxMczNzaGlpcXdLRw8eBA3btzA7t270a9fP3zxxRct1mFsbIzY2FjMnj0bDQ0NvDxLS0vcvn2bey8UCpGcnMy9Hz9+fPs+NPNkdfUcSEc9z3Mgf6VQKEgqldKDBw86dH5lZSVJJBK1Z0qehKqqKioqKiKFQtHuc4uLi7ugRc+3jj4HMmjQIEpJSaGsrKxW50AePeRyOc2cOZN0dXWJiMjJyYnLmzNnDmVmZvLKW1tbq82BxMbG0vr160lfX5/09fXp6NGjtHz5ctLV1SV/f3+6evUqV1ZPT4/c3d1pwYIFRERsDuQpaescCNsrohswNDSEoaFhh8/v1asXevXq1YktajtjY2O15z3aqm/fvp3cGqY5BQUFCA4Oxu3bt2FoaIiamppWz5k6dSqMjIyQkZEBpVKJ4uJibo4CaJpTae65nkfNmDED+vr62Lx5MwBAX18fHh4ecHNzw4YNG7B//34MGTIEeXl5qK+vx+nTp2Fra9vxD8s8MWwSnWGeU/b29rw/LKZNm4b8/HzU1NTAzMwMK1as0NgB9OnTBwEBAUhMTERoaCg3f3X48GFs3LgRAoEAAoEAfn5+bZq7sLCw4P7QMDY2xvHjx7Fy5Ur4+PggPz8fCQkJSE5O5j0X1dxzIkz3wjoQhnlOeXl5oaSkBFKpFGVlZQgMDISPjw+AphVzkZGRsLGx4crHxMSgvr4eeXl5WLBgAYKCghAeHs7lh4aGQltbG4WFhRCLxTA1NUVoaOhjtzMoKAipqak4e/YsZDIZxGIxLl++jKysrMeum+labAiLYZ5TO3fuxKeffgpzc3NUV1ejurqayzt16hQsLS0hk8kANG3i2RqFQgFvb2+YmJhApVLx6nuoqKio1V2UZ82axXuvVCqxceNGbNq0CUKhEESE8vJytqHmM4B1IAzzHFMqlc2ugHzYebRXS0t/HwcRobS0tEvqZroG60AYhnnmqVQqaGtrP9dL/58khULRpv3IWAfCMM8QNqyjWVlZGfr06aO2AwPTMQ0NDZg+fXqr5VgHwjDPEBalUTNLS0s0NDTgypUrT7spz4WffvpJ7YFkTdgqLIZhGKZDWAfCMAzDdAjrQBiGYZgOYR0IwzAM0yGsA2EYhmE6hHUgDMMwTIewNYGd7OTJkzhx4gSkUilEIhGmT5/ebCS/9evXw83NTS2/vr4eUVFRuHTpEiwtLbFs2TIMHz6cV0YsFmP//v3Izc0FAMTHx3PRBpOTk3HixAkIBALMnTsXU6ZMAQBkZmbiq6++0tiWPXv2QEdHBxKJBJGRkcjPz8fw4cPxwQcfwNzcnCtHRPj222/x3//+F2VlZZg1axbmzZvX7Pchl8sRFhaGgIAADBs2rJVvj2GYZwm7A+lE/v7+WLx4MQYOHIjZs2dj0KBBCAoKQlBQkFrZa9euYe/evfjoo4/U8mbOnInvv/8es2bNgpWVFUaPHs0L73nx4kUufOzChQvh6+vL7V4aHh6OtWvX4o033sD48eMREBDAhb/V09ODhYUF77h79y6SkpIgEAhw7949ODs7o6KiAnPnzoVYLIarqyu39TcR4Z133kFYWBjGjh2LZcuWYejQoc1+H9nZ2XB2dsa+fft4QYMYhnlOsIBSj+dhQKmvv/6aDAwMSCwW8/LFYjEZGBjQsWPHeOkffPABrVy5knr37k3Xr1/n0q9fv056enpUXl7Opa1Zs4Z8fHyIiEilUpGdnR3FxMRobI9QKKTU1FTufUpKColEomaDVXl5eVFoaCgREUVHR5OTkxOXp1KpyMnJiaKjo4mIKDExkWxtbam2tra1r4WkUilZWVnRjz/+SLa2tnTy5MlWz2Fa19GAUs/7wQJKda62BpRidyCdJDExEb6+vujfvz8vvX///vDz80N8fDyXVl9fj0OHDmHu3Lnw8fHhhXwVi8Xo06cPevfuzaVNnToVFy5cAND0V71MJsP8+fPV2vAwrO2jQ0WTJ0+GXC7HH3/8oVY+NzcXaWlpWLZsGXftR88VCASYPHkyd+1Dhw5hyZIlbQoiJBKJcPPmTUyaNIltv8EwzynWgXSChoYG5Obm8gLiPGrEiBG4fv069/7YsWMQiUR47bXXsGDBAhw8eJCLFT148GDcvXsXJSUlXPkLFy6gvLwcQNMv/ZdffhkfffQRrKysIBKJsHz5ctTX10NfXx99+/blbeeQlZUFlUrFnf+o8PBwzJs3D5aWlty1c3JyQEQAmvZdunTpEu/aBgYGcHR0hJmZGf7+978jIyOj2e/lYaTCh/U9+nnY68d73R49evSAUCiEQNB5/9179uzJmxtrD11d3WYDRhkYGMDMzKxNG/kxTx/rQB7TjRs3YGZmhvr6ehgZGWksY2RkhLq6Ou59bGws5s2bh7q6Ojg6OqJnz5747rvvAABDhgyBn58fxo0bh3Xr1sHHxweZmZkwMzMD0LQF9+XLlzF48GAUFRXh6tWruHDhAnbt2gUA2L59OxYvXowVK1bgvffew549eyAQCLjzHyouLsbhw4exatUqLs3Pzw8qlQoTJkzAhg0bMHnyZNTV1fGunZSUhO+//x5lZWVYtmwZZs6cifv377frO6utrWWvH/N1WwgEAkRGRqKsrAy5ubmoqalBdHS0xrJpaWlQKBSorq6GTCZDeno6Zs+erVbO09MTubm5yMnJQUZGBm8OTFtbGzt37kRVVVWzbbKzs0NFRQWWLFnCSw8MDERubi4qKyvx559/orq6GmFhYe36vMxTwOZAHs/SpUtp4MCB9Nprr1FISIjGMlu2bCEXFxciIiooKCAtLS21Mdw333yTd865c+coJiaGMjMz6eDBg+Ts7ExERP/6179o/PjxvLJffPEFLy03N5cOHDhAKSkpVFBQQAKBgBQKBe+ctWvXkoeHh1pb6+rq6MSJExQXF0f5+fkUGBhI69evJyIiIyMjSk9P55Xv06ePWtpfDRw4kM2BdJL2zIF4e3vT7du3SSQSEQAyMTGh4cOHayx7/vx58vf3JwAkFAppzpw5JJFIaNu2bVwZR0dHkslkNGHCBLXzhUIhpaen06FDh6ixsVHjNXR0dCgzM5OuXLlCS5cu5dJDQ0NJIpGQh4cH6erqEgCysrKikSNHsjmQp4TNgTxhkyZNQlJSEh48eMBLf/DgAb7++mtMnToVABAXFwcvLy/U1tZyx7Vr13D69GncuXOHO2/cuHFYvHgxXFxckJSUxG1T/dJLL6GoqIh3DaVSCT09Pe790KFD4e/vDy8vLxw9ehQuLi4wNDTk8isrK/Hll19izZo1ap9DT08Pb731FgICAmBlZYXvvvuuXddmug+RSITCwkJuOLSyshI3btwAALz66qu4evWq2pwd0HSneeTIEfj6+mLTpk3cEOe6desQERGBM2fOqJ1TX1+PuLg4fPjhh822Z8uWLcjIyEBeXh6vjSEhIfD19UVqaiqUSiUAQCKR8FYeMt0T60A6yapVq1BRUYHg4GAuqM29e/cQHBwMhUKBDz74ACqVCvHx8QgMDIS+vj53vPzyyxgzZgwOHDjAq1OlUmHHjh3Izs7G+++/DwBwd3dHXV0dIiMjuWvExsbizTffVGvTDz/8gI8++gjbtm3jpX/xxRcYPHgw3njjjWY/z/379zF37lwMGzYMkyZNAgAsWrQI27ZtQ1lZGYCmzrBHjx4YOXIkAGDHjh04e/ZsR74+pgucPHkSDg4O2L59O0xNTXl5FRUVKCwsbDG64Llz5yCXyzFu3DgAgKurK7Kzs7F161ZERUXhrbfe4srev38fBw8ebHaexcXFBR4eHggJCeHNf0yaNAl37tzBuXPnHuejMk8J60A6iYWFBS5cuACxWAyRSAQTExP06dMHd+/exYULF2BiYoL//e9/UCqV8PT0VDt/8eLFOHDgAIgIQUFBsLW1hYWFBVJTU3H69GmIRCIATZOMJ06cwL59+9CnTx8MHDgQLi4uWL58OYCm1WADBgxA3759sXLlSsTExMDd3Z27TkNDAz777DOsXr1a4+cYMWIE7OzsMGDAABgYGPBiAixbtgyenp6wsbGBSCTCjh07kJSUxN3dbN++HUlJSZ32nTKPp6CgAKNHj4a9vT3EYjGioqK4+azCwkJMmzat1fmr4uJimJubQ0tLi7tbEIvFyMjIwO7du7F06dJW22FsbIzY2FgsXLiQWyzykKWlJe8ZIaFQiPT0dO5gujk2B/J4Hs6BPKqhoYGKi4upoaGhQ3XW1tbSnTt31OYt/qq0tFTtGo2NjSSRSHjPkbRHZWUlSSSSFtteW1tLcrlcLV0mk3X4MzNt09HnQAYNGkQpKSmUlZXV6hzIo4dcLqeZM2eSrq4uERE5OTlxeXPmzKHMzExeeWtra7U5kNjYWFq/fj3p6+uTvr4+HT16lJYvX066urrk7+9PV69e5crq6emRu7s7LViwgIiIzYE8JW2dA2FbmXQBXV1d9O3bt8Pn6+vrw9rautVyQqFQLU1bWxv9+vXr8LV79eqFXr16tdo+Tc+CWFhYdPi6TNcqKChAcHAwbt++DUNDQ253gZZMnToVRkZGyMjIgFKpRHFxMTdHATTNqbTlmaAZM2ZAX18fmzdvBtD08+Ph4QE3Nzds2LAB+/fvx5AhQ5CXl4f6+nqcPn0atra2Hf+wzBPDhrAY5jllb2/P+2Ng2rRpyM/PR01NDczMzLBixQqNHUCfPn0QEBCAxMREhIaGQi6XAwAOHz6MjRs3QiAQQCAQwM/Pr01zFxYWFjA2NuaO48ePY+XKlfDx8UF+fj4SEhKQnJzMe46quedEmO6FdSAM85zy8vJCSUkJpFIpysrKEBgYCB8fHwCAg4MDIiMjYWNjw5WPiYlBfX098vLysGDBAgQFBSE8PJzLDw0Nhba2NgoLCyEWi2FqaorQ0NDHbmdQUBBSU1Nx9uxZyGQyiMViXL58GVlZWY9dN9O12BAWwzyndu7ciU8//RTm5uaorq5GdXU1l3fq1ClYWlpCJpMBAMaOHdtqfQqFAt7e3jAxMYFKpeLV91BRURF0dFr+tTJr1izee6VSiY0bN2LTpk0QCoUgIpSXl7MtcJ4BrANhmOeYUqmEVCrVmPew82ivlpb+Pg4iQmlpaZfUzXQNNoTFMAzDdAi7A2GYZwgb1tGstLQUNjY2cHV1fdpNeS40NDRwu2e0hHUgDPMM6cwddZ8nFhYWKCsrYzshdJLz58/jp59+arUc60AY5hnCOhDNHi4tfrhjA/N4TE1N2/Szxn4aGYZhmA5hHQjDMAzTIawDYRiGYTqEdSAMwzBMh3TrSfSGhgbeVs/dkaancRmGYV4E3bYDGT58OADAzc3tKbekZffu3eMitjEMw7xIum0H0rdv32ciStl7772HkydPdkndtbW1+Oqrr5CRkYGqqioMGjQICxcu5CIAPqq8vByrV6/G5s2bMXjwYF6eRCJBZGQk8vPzMXz4cHzwwQcwNzfn8n/++WfExsaioqICbm5uePfdd7ndUBsaGhATE4OMjAwYGBjAw8OD25APAHJycrB//37cvXsXdnZ2WL58OW87+e+++w7Hjh1DXV0dnJyc8N5772ncAfbu3bvYtGkTVq9ezduV9a/kcjnCwsIQEBCAYcOGtf3LZBim07E5kG7q3r17cHV1xZdffgknJyd4e3sDaNr0LiEhQa38oUOHkJSUhJiYGLV6nJ2dUVFRgblz50IsFsPV1ZWLB3HhwgVMnDgRf/vb3zBr1iwkJibC39+fO//tt9/GTz/9hKlTp2LMmDFYsWIFIiIiAADZ2dnw9PSESCTCnDlzcOfOHbi4uHBR7nbt2oVt27bBwcEBM2fOxOHDhzF79my1thMRFi1ahG+++QYSiaTZ7yQ7OxvOzs7Yt29ftx/aZJgXQneNSPis0BSRsDO89957NGrUKLUIf9988w0ZGhqSRCLhpb/yyiu0bds26tu3LymVSi49OjqanJycuPcqlYqcnJwoOjqaiIh8fHzoww8/5PKlUikZGRnR9evXiYioqqqKd52oqChydHTk3j+ar1KpSCgU0vfff09ERDU1NdTY2MjlX716lbS0tNTq/Oyzz+jtt9+mYcOG0cmTJzV+H1KplKysrOjHH38kW1vbZss97zoakfB5P1hEws7V1oiE7A6kC/zyyy/44YcfOnyUlZXh8OHDWLVqFXR1dXl1e3t7w9ramhd7/JdffoFYLMaHH36Inj17IjU1lcsTi8W8oR6BQIDJkyfjwoULGvNFIhFGjRrF5RsbG/Our1KpeENQLeUbGBjwAgOpVCro6Ojw0m7cuIHdu3dj3759vGh3fyUSiXDz5k1MmjRJbT+oW7duvVCv26tHjx4QCoWd+hR7z549ecOg7aGrq9tswCgDAwOYmZlBS0vrcZrHPCGsA+lkN2/exOLFi7Fv374OH+vWrUNFRUWzcwH29va4fv069z42Nha+vr7Q19fH/PnzERcXx+UNHjwYOTk5ICIATZvxXbp0CeXl5Vz+lStXuPKlpaX4448/uPxH1dfX48svv8SSJUs0tuurr76CUCjEuHHjNOZHRkbCz88PBgYGAJrmV/z8/LB3715YWlpybWzOw87qr+V+/vnnF+p1WwkEAkRGRqKsrAy5ubmoqalBdHS0xrJpaWlQKBSorq6GTCZDenq6xuFGT09P5ObmIicnBxkZGRg6dCiXp62tjZ07d6KqqqrZNtnZ2aGiokLtZygwMBC5ubmorKzEn3/+ierqaoSFhbX7MzNPGBvCejx/HcL65ZdfyMHB4bHqvHXrFgGgvLw8jfnz588nPz8/IiJSKBTUq1cvysjIoNraWvr9999JV1eX7t69y+Xb29uTm5sbrV+/niZMmECvv/46zZs3j4iIfv31VzIzMyNfX19au3Ytubm50ZAhQygmJoZ3zf/L3pmHNXVtf/9LIBBGAQmhorWKWEVAvaDiQNXiUHCoFFFBRC5YqoKt1wGHF6XW1qmt9gelEyAOHSzUWrXF+6siCCpgpVpRaakIREAgYZQAIQnr/YOX8xoDiiBO3Z/nOc9zzl5r77PPhmRl77XPWiqViubPn09z5sxpt09ZWVnUu3dvysjIaFceHR1NAwYMoKqqKq4sLCyMli5dyl3b2Nh0ammqf//+bAmrE4eXlxcVFRWRSCQiANSrVy+ys7NrV/fs2bMUEBBAAEgoFNKCBQuopKSEtmzZwuk4OzuTRCKhyZMna9QXCoWUmppKX3/9NSmVynbvoaOjQxkZGXTp0iVaunQpVx4REUElJSXk4eFBfD6fAJC1tTU5OjqyJawnBFvCeoaxsrICj8eDWCxuV15UVIS+ffsCABITE1FXVwdXV1fo6+vj5ZdfhkKhwL59+wAABgYGuHjxIlatWoXBgwcjNjYWtra2XH1HR0fk5uZi1qxZGDlyJH766SeoVCpODrT+4l++fDmkUim+++47jf7k5ORgzpw5OHDgAFxcXDTkX3/9NXbu3Ink5GSYmZkBaHXex8bGwtPTE2fPnsXZs2fR1NSEa9eu4c8//+zW+DFaEYlEKCwsRHl5OYDWRFDXr18HAIwYMQI5OTno16+fRj2JRIJDhw7Bx8cHGzdu5Lapr127Fnv27EFKSopGHblcjri4OISFhXXYn82bNyM9PR15eXlqfQwPD4ePjw+SkpK4ZcySkhJcuXKl6w/PeDywGUj36IkZCBHRuHHjaMmSJRrlhYWFpKOjQ2fOnCEiogkTJtCHH35IjY2N3PH555+Tra1tu+02NTWRUCikX3/9tV3577//Tvr6+lRbW8uVLV++nF599VWSyWQa+levXiVra2s6evRou+19++231L9/f/r777/VyuPj42nYsGFqh66uLvXv35/+85//tD8o/w82A+ncr/IBAwZQfX09bdu2jczMzNRkL730Eh0/fpxMTEw0ZiB3H7dv3yYvLy8CQMXFxeTm5kbvvvsuRUVF0ezZszX0+/bt2+4MxMXFhS5evEi6urr0ww8/cDMQPz8/unnzJnOiP2WwGcgzzgcffICDBw/iq6++glwuBwDk5eVh4cKFeO211/DKK6/gr7/+woULF7B48WII1x2k1QAAIABJREFUBALuWLhwIUpLSzXeo6mrq4Ovry+GDh2KqVOnatyzrf01a9bAxMQEABAaGoqsrCzEx8ejoaEBUqkUUqkUSqUS165dw5QpU/Dee+9h3LhxnKxtG++hQ4ewcuVKHDp0CKamppy8sbERAQEBuHr1qtrRr18/fPHFF9i9ezdqamqwbt26DmdhjAdTUFCAsWPHwt7eHmKxGFFRUTA3NwcAFBYWYtasWdzfqiNKS0vRu3dvaGlpcbMFsViM9PR07N69G0uXLn1gP4yMjBAbG4vFixejublZTWZpaam2JVsoFCI1NZU7GE83zIA8pUyaNAlHjx7FF198AWNjY5iYmMDZ2RnOzs5ITEwEAMTFxWHmzJkQCoVqdY2NjTFv3jzExsYCABwcHGBra4sXX3wR+vr6OHLkCKdbVFQEoVCIgQMHYsKECZg/fz4iIiIAAOXl5YiOjkZ2djb69+8PoVDIHZmZmfj0009RVlaGoKAgNdkbb7wBANiyZQsqKiowduxYNfnHH3/8wOfPz8/Hrl27kJWV9UjG859KTk4OZs+eDUdHR7z00ktqO/Q6Q//+/SGRSKCjowMdHR2sW7cOe/fuRUJCAsLDw7F48eIHtvHJJ5/g4MGDyM/Ph0AgAI/Hg46ODvh8PqqqqmBhYcHp1tXV4f3338fevXuf+igUDLAlrO7SU0tYdyOTyaisrIxaWlq6VL+2tpZKSko03ilpo6KigioqKrrcfk9RWlr6pLvw1NGd90BefPFFIiIyMDC4rxO97XB3d6fGxkaysLAgAFRSUkIjR45Uk1+6dOmBS1hSqZTq6+u5Q6lUUlNTEyUmJpKNjQ21tLTQ4MGD1eoMGjSIiIgtYT0h2BLWc4SBgQFEIlGX98abmJigT58+Gu+UtNE2M3ja9t6/8MILT7oLzzT29vbcUiQAzJo1C/n5+WhoaIC5uTlWrFjRblgZKysrBAYG4sCBA4iIiIBUKgUAfPfdd9iwYQOX/c/Pz69T4YYsLCxgZGTEHT/99BNWrlwJb29v5OfnY//+/UhMTFTbtt7ReyKMpwtmQBiM55SZM2eivLwcZWVlqKysRFBQEBfHzMnJCZGRkbCxseH0Y2JiIJfLkZeXB39/fwQHB2PXrl2cPCIiAtra2igsLIRYLIaZmRm33NkdgoODkZSUhDNnzkAikUAsFiM7OxuZmZndbpvRszy1wRQZDEb32LFjBz7++GP07t0b9fX1aqkHTp48CUtLS0gkEgCtMdYehEwmg5eXF3r16gWVStVuKoPi4mLo6Nz/a2Xu3Llq1wqFAhs2bMDGjRshFApBRKiurtaIOMB4+mAGhMF4jlEoFCgrK2tX1mY8Hpba2trudKlDiAgVFRU90jajZ2BLWAwGg8HoEmwGwmA8QyiVyh7d7EAPiEf2KOiJ/ldUVGDkyJFquWoYXUcul2P48OEP1GMGhMF4xngcX/I9SU/039TUFDdu3MDu3bsfedv/RH7//Xe1gK0dwQwIg/EM8SAH9T8VXV1dKJXKTm0GYDyY5ubmTqUQYD4QBoPBYHQJZkAYDAaD0SWYAWEwGAxGl2AGhMFgMBhdghkQBoPBYHQJZkAYDAaD0SXYnsAnTE5ODvbv34+bN2/CyMgIrq6uWLRoUbtRUuPj41FdXY1Vq1ZpyBITE3H06FHweDz4+vritdde42RyuRxRUVG4cOECLC0tsXz5ctjZ2XHyY8eO4ciRI2hqasLo0aOxbNkytfvfr+22nCHXr1+HpaUlAgMD4ezszMn//vtv/M///A9KSkowZswY/Oc//4Genl6H46FUKrF7924MGTIEs2fP7vxAMhiMxw6bgTxB4uLiMHbsWKhUKnh5ecHFxQWxsbFwdXXViDekVCoRHh6OrVu3oqamRk22a9curFmzBq+++iomTZqEwMBAxMXFcXJPT0/8/PPPmDt3LqytrTF27Fgu3/RHH32ELVu2wMnJCZ6envjuu+8wf/78TrV9584djB49GrW1tZg3bx5eeOEFTJgwARcuXADQalzGjx8PIoK3tzeOHTuGwMDADsejrKwMbm5u2L59O86fP9+9wWUwGD0PSyjVPbqaUKqoqIgEAgH98MMPauXNzc30r3/9i9555x218iNHjtCoUaNoxowZFB0drSYTCoWUlJTEXR8/fpxEIhG1tLTQtWvXSE9Pj6qrqzn56tWrydvbm4iIGhoaSKlUcrKcnBzS0tKiO3fuPLBtIuL02vDy8qI1a9YQEdG2bdto4sSJnKysrIy0tbU18qO3MXr0aNq5cycFBQXRunXr2tX5p9OdhFLP88ESSj1aWEKpJ0hLSwvy8/M7PCQSCRISEmBtbc2lf22Dz+dj9erVOHjwIFQqFVceGxsLb29v+Pr6cqlqAaCpqQkSiQRDhw7lyqZNmwapVIobN25ALBbDysoKpqamnNzd3R3nzp0DAOjr66sl71GpVNDR0YG2tvYD2wZa813fjUql4pa/MjIyMG3aNE4mEong4OCAM2fOtDtuycnJCAsLU3tuAGozrurqanbOYDwlMAPSAxQWFmLKlCmYPn16u8eePXvw7bffwt7evt3Acg4ODqiqquLCcJeUlODUqVPw8/ODp6cnbty4gUuXLgEABAIBXnjhBe4aADIzM6FSqVBdXY2BAwfi9u3bKC8v5+Tnzp3r8MsoMjISfn5+0NfXf2Db9/L3338jJSUFixYtAgDcvn0bIpFITUckEqG4uLjde7cZI7onVlJbDngAOHjwIDt/SHR1dSEUCsHjPbqPu7GxMXr37t2lunw+v8OMg/r6+jA3N3/qsmMyOoAtYXWP9pawBAIB5ebm3rfewoULydfXt11Zfn4+AaAbN24QEdHWrVtp+vTp1NjYSI2NjeTv708hISGcfnx8PJmbm1NoaCgtXbqUPD09icfjcUtFgYGBZGtrS2vWrKG5c+fSa6+9RtbW1hr3jY6OpgEDBlBVVVWn225DKpXS0KFD6ZNPPuHKhg8fTgcOHFDTmzNnDm3atOm+Y7N48WK2hNUBD7OExePxKDIyku7cuUNSqZSampooOjq6Xd3k5GSSyWRUX19PEomEUlNTaf78+Rp6M2bMoNzcXMrPz6fr16/TkCFDOJm2tjbt2LGD7ty502GfbG1tSSaT0dKlS9XKg4KCKDc3l5qbm6mmpoZkMhnt3LmTLWE9ITq7hMV2YT0h+vTpg4yMjHZlRUVF0NbWhpWVFYgI8fHxuHnzJvT19TkdU1NTfPTRRxAIBAgICICLiwsyMzNhYWEBe3t7HD16FH369AHQ6qxPT0/HX3/9BS8vL9y4cQOffvqp2j2//vpr7Ny5E6mpqTAzM+PKH9Q2ANTV1cHd3R1vvPEG3nnnHa7czMxMw+FfW1urtpzG6Dk8PT3x+uuvY9CgQSgvL0evXr1gbW3drq6enh5CQkKwb98+CIVCuLm5Yffu3bCzs+PS1jo7O2Pfvn2YN28eUlJS1OoLhUIkJiaiuLhY7f/0bnR0dHDgwAHk5eWplUdERCA4OBhvvvkmTp48CYVCAWtr6y7PcBiPD7aE9YSYOnUqMjMzUVRUpCH79ttv8corr8DQ0BCnT59GXV0d6urq0NjYiMbGRshkMhgbG+Pw4cNcnSFDhiAgIAAzZ87Ejz/+CBcXFxgYGHByV1dXLFmyBC4uLkhISICbmxsn++677xAeHo7k5GQMGDBAoz/3a7uurg7Tpk2Dm5sb3n//fbV6jo6OuHz5MndNRLh27RocHBy6PnCMTiMSiVBYWMgtX9bW1uL69esAgBEjRiAnJwf9+vXTqCeRSHDo0CH4+Phg48aNsLS0BACsXbsWe/bs0TAeQOtW8bi4OISFhXXYn82bNyM9PV3NgIhEIoSHh8PHxwdJSUlQKBQAWpdt23YKMp5emAF5QkydOhUTJ06En58fFzZZLpfjyy+/xDfffINt27YBaHWe+/n5wdjYGAKBAAKBAAYGBggICFDbqtvGL7/8gq1bt2LLli0aMpVKhe3btyMrKwtvv/02AODQoUNYuXIlDh06BFNTU0ilUkilUjQ2Nj6w7Tt37uC1116Dg4MDVq9ezdWtrKwEAPj6+uLHH3/E1atXQUSIjIyEtrY2Jk6cCAA4fPgwYmJiHsFoMtrjxIkTcHJywrZt29RmlUDrxoTCwsL7pqdNS0uDVCqFq6srAGD8+PHIysrCu+++i6ioKLX3dOrq6nDw4MEO/SwuLi7w8PBAeHi4mv9j6tSpuHXrFtLS0rrzqIwnBfOBdI+u+kCIiOrr62nZsmVkaGhIxsbGxOfzycnJiVJSUoiIqKqqivT09OjKlSsadQsKCkhbW5tu3LhB+/fvp379+pGVlRUNGjSIEhMT1XTffPNNsrGxIVNTU5owYYJae3evYd99bN26lYjovm0fOnSo3bra2tqczscff0wGBgZkYmJCL774IqWnp3OymTNnkp2dncazMR9IxzzsNl4HBwc6duwY3blzh6Kiosjc3LxdvbNnz1JAQIBGeXZ2NgUHB5OWlhYpFApKSUmhwMBAmjdvHt24cUPDl9G3b19SKpVqZUZGRnT16lUaNmwYAaAffviBq7dq1SpKSUnhdIVCIaWmpnJHZ5+T+UAeLZ31gTAD0k26Y0DaaGlpobKyMpLJZF3qg1KppJKSErV3Pe6msbGRbt261aX2H9R2Z2hsbKTy8nLu3ZE2ZDIZ1dTUdLndfyJdfQ9kwIABdPz4ccrMzHwoAyKVSsnT05P4fD4Rtb6r0yZbsGABZWRkPNCAxMbG0rp160ggEJBAIKAff/yRQkNDic/nU0BAAOXk5HC6enp6NGXKFPL39yciYgbkCcGc6M8QWlpaGttdHwZtbW01p/a9CAQC9O3bt0fa7gxtS2/3crePhtGzFBQUICQkBEVFRTAwMEBDQ8MD67i7u8PQ0BDp6elQKBQoLS3lfBRAq0+lvb/rvcyZMwcCgQCbNm0C0Pr/4OHhgYkTJ2L9+vXYu3cvBg8ejLy8PMjlcpw6dQqDBg3q+sMyHhvMB8JgPKfY29vDxMSEu541axby8/PR0NAAc3NzrFixol0DYGVlhcDAQBw4cAARERGQSqUAWjdbbNiwATweDzweD35+fp3yXVhYWMDIyIg7fvrpJ6xcuRLe3t7Iz8/H/v37kZiYqLa5oqP3RBhPF8yAMBjPKTNnzkR5eTnKyspQWVmJoKAgeHt7AwCcnJwQGRkJGxsbTj8mJgZyuRx5eXnw9/dHcHAwdu3axckjIiKgra2NwsJCiMVimJmZcVt8u0NwcDCSkpJw5swZSCQSiMViZGdnIzMzs9ttM3oWtoTFYDyn7NixAx9//DF69+6N+vp61NfXc7KTJ0/C0tISEokEADBhwoQHtieTyeDl5YVevXpBpVKptddGcXExdHTu/7Uyd+5ctWuFQoENGzZg48aNEAqFICJUV1dDqVR25jEZTxBmQBiM5xiFQsGFxLmXNuPxsNxv6293ICJUVFT0SNuMnoEZEAbjGaK5uRlaWlo9EiuK7olB1lP0RN8lEgn+9a9/YdmyZY+87X8ijY2NMDc3f6AeMyAMxjOESqUCET22L/ueoCf6bmJigj///BMhISGPvO1/ItevX+/UbJAZEAbjGaKjOFP/dAwMDKBUKrlI0Izucfr0aRw5cuSBemwXVjcxMDBgWw4ZDMY/EjYD6Savvvpqp16mYjAYjOcNNgN5BPzxxx9PugsMBoPx2GEGhMFgMBhdghmQHqC5uRnff//9k+4Gg8Fg9CjMgPQALS0tmDNnzpPuBoPBYPQozIn+mCkrK8PevXtx5coVEBEcHR0RFBQEKysrDd34+HhUV1dj1apVGrLffvsNsbGxqKmpwcSJE/HWW29xu8HkcjmioqJw4cIFWFpaYvny5bCzs1OrLxaLsXfvXuTm5gIA9u3bx20RzczMRHx8PKqqqmBnZ4eQkBAuKx0A1NfXY9++fcjKyoJMJsOmTZswcuRIAK2hLCIjI5Gfnw9ra2ssWbIEjo6O9x2TxMREiMVirF69+iFGksFgPGnYDOQxcvHiRdjb2+Py5cuYPn063N3dceXKFY3UrwCgVCoRHh6OrVu3auQVP3fuHNzc3PDSSy9h7ty5OHDgAAICAji5p6cnfv75Z8ydOxfW1tYYO3asWnrQ8+fPw8nJCTKZDIsXL4aPjw9nfH777TdMmzYNjo6OCA4OhlgsxoQJE7gw3lKpFM7OzkhLS8OcOXMQHBzM5a6WyWRwcXFBc3Mzli1bBmtra4wfP54zUvfS3NyMFStWIDg4GImJid0eXwaD8ZhhCaW6x88//0wzZszgri9evEgA6PLly2p6LS0tZGdn126SltDQUBo+fLha2ZEjR2jUqFE0Y8YMio6OVpN5e3tTWFgYd11WVkaGhoZ07do1unbtGunp6aklgFq9ejV5e3sTEZFKpSJbW1uKiYlp93nef/99mjVrFnetUCiIx+PR9evXiYgoMDCQFi5c2G7ds2fPkrGxsVrZK6+8Qp999lm7+m39+uqrr2jMmDHt6jDU6WpCqef9YAmlHi2dTSjFZiDdpKmpCX/88QfGjh2LsWPH4t///ne7etnZ2bh+/TrCwsI0ZBs2bMAff/yhNguJjY2Ft7c3fH19ERsbq6YvFosxdOhQ7lokEmHkyJE4d+4cxGIxrKysYGpqysnd3d1x7tw5AEBWVhYkEkmHb+w6ODjgt99+4wLw/frrr7CwsICNjQ0UCgUSEhK4fOr3YmtrC4VCgdTUVADArVu38Oeff2L06NHt6m/ZsgUJCQnQ1dVtV85gMJ5umAHpJhUVFaiursaePXuwZ88erFq1ClpaWnBycgKfzwefz8eUKVOQm5uLXr16oV+/fhpt9OnTB+bm5rh27RoAoKSkBKdOnYKfnx88PT1x48YNXLp0idMfOHCg2nVFRQVu3LiB6upqDBw4ELdv30Z5eTknP3fuHKqrqwEAubm5GDZsGLZu3Qpra2uIRCKEhoZCLpcDAGbPno23334bw4cPh5eXF8LCwnDy5Eno6uri1q1baGxsxN9//w1bW1uYm5tjxowZuHXrFgDA0tISR44cwfz58+Ht7Y3x48cjKioKTk5O7Y6doaEhAM3YSHv37uXOt27dys7vOX9YdHV1IRQKweM9uo+7sbExt3T5sPD5/A6jN+jr68Pc3LxHAi4yegC2hNU9PvvsM7Vlm7YlrKioKFIoFKRQKEipVNLs2bOpT58+HbbTr18/io2NJSKirVu30vTp06mxsZEaGxvJ39+fQkJCON0//viDzM3NycfHh9asWUMTJ06kwYMHc8tSgYGBZGtrS2vWrKG5c+fSa6+9RtbW1kREtGPHDhIIBBQXF0ctLS1UXl5OI0aMoPfff5+IiJqbm+mtt96iESNG0MKFC0kkEtH3339PRESZmZnE4/Fo+fLl1NjYSHK5nAICAmjKlClc3z7//HOysbGht956iywtLWn9+vUaudDvJT4+Xm0J6259lUrFzu86f5glLB6PR5GRkXTnzh2SSqXU1NRE0dHR7eomJyeTTCaj+vp6kkgklJqaSvPnz9fQmzFjBuXm5lJ+fj5dv36dhgwZwsm0tbVpx44ddOfOnQ77ZGtrSzKZjJYuXapWHhQURLm5udTc3Ew1NTUkk8lo586dbAnrCdHZJSxmQLpJRwbkXr/FL7/8Qjwej+RyuUYbzc3NpK2tTf/973+ppaWFBg4cqPEBMTU1pcbGRq5OeXk5ffvtt/TNN99QdXU12djY0IkTJzh5WloaxcTEUEZGBh08eJD7gv7www9p0qRJavf/4osvuLLVq1eTu7s7NTc3ExHR77//TmZmZpSamkq//fYb8fl8UigUXN0///yTKzt+/Dj17duXysrKiIhIIpHQyJEj6b333rvvGN5rQBgd8zAGxMvLi4qKikgkEhEA6tWrF9nZ2bWre/bsWQoICCAAJBQKacGCBVRSUkJbtmzhdJydnUkikdDkyZM16guFQkpNTaWvv/6alEplu/fQ0dGhjIwMunTpkpoBiYiIoJKSEvLw8CA+n08AyNramhwdHZkBeUIwH8hThqurK3R1ddvdbZSQkACBQABXV1ecPn0adXV1qKurQ2NjIxobGyGTyWBsbIzDhw9zdSwtLeHj4wNfX18UFBSgtLQU48aNU7vfkiVL4OLigoSEBLi5uQEAXn75ZRQXF6vdX6FQQE9PDwBw5swZzJ8/H3w+HwAwcuRIuLq6Ii0tDYMGDUJLS4va8phCoYCOjg60tbVx5swZTJkyBSKRCEBrLuxFixZxPhHG40UkEqGwsJD7e9XW1uL69esAgBEjRiAnJ6fdJVWJRIJDhw7Bx8cHGzdu5LZwr127Fnv27EFKSopGHblcjri4uHZ9fG1s3rwZ6enpyMvLU+tjeHg4fHx8kJSUxO32KykpUds5yHg6YQbkMWFsbIyNGzdi7dq1SElJ4XI6pKSkYO3atdiyZQsMDAwQGxsLPz8/GBsbQyAQQCAQwMDAAAEBAYiLi9NoNy8vDwsXLsSaNWtgYmKiJlOpVNi+fTuysrI4x/eUKVPQ1NSEyMhIAEBVVRViY2Mxffp0AICjoyOOHTuG5uZmAK0O+8zMTDg7O8PU1BRz5szBqlWroFAooFQqsXv3bkydOhVaWlpwdHREWloal+muoaEBx48fh7OzM4DWmGHh4eHclwSjZzlx4gScnJywbds2mJmZqclqampQWFh43+yCaWlpkEqlcHV1BQCMHz8eWVlZePfddxEVFYXZs2dzunV1dTh48GCHfhYXFxd4eHggPDxczf8xdepU3Lp1C2lpad15VMYTghmQx8imTZsQFhaGRYsWwdDQEIaGhli8eDE2bdqE1atXo7q6GkeOHEFgYKBG3cDAQKSlpSE/Px9FRUUQCoUYOHAgJkyYgPnz5yMiIoLTDQ4OxqBBg2BhYYGkpCScOnWKmxXo6+vj6NGj+Pzzz2FlZYX+/fvDxcUFoaGhAICdO3dCLpejb9++GDZsGJydnbFy5Uq4u7sDAL788kvU1dXB0tISFhYWKCwsxGeffQYA8PPzw+uvv44hQ4bA3t4eL774Ivr06cP17dSpU9i+fTsqKyt7dJwZrRQUFGDs2LGwt7eHWCxGVFQUl2WusLAQs2bNQl1d3X3bKC0tRe/evaGlpcXNFsRiMdLT07F7924sXbr0gf0wMjJCbGwsFi9ezP0wacPS0hJFRUXctVAoRGpqKncwnnKYD6R7dNYHci+VlZVUVVXV5ftWVFRQRUVFuw7qxsZGunXrFslksge20ebruBe5XE5lZWUdOsBramrozp077cpUKhWVlZVptN1Wzug6XX0PZMCAAXT8+HHKzMx8oA/k7kMqlZKnpyfx+XwiIho9ejQnW7BgAWVkZKjp9+3bV8MHEhsbS+vWrSOBQEACgYB+/PFHCg0NJT6fTwEBAZSTk8Pp6unp0ZQpU8jf35+IiPlAnhCd9YGwUCZPiM7kG74fQqGwQ5lAIEDfvn271Yauri43a2mPXr16dSjj8Xjt1u2onNHzFBQUICQkBEVFRTAwMEBDQ8MD67i7u8PQ0BDp6elQKBQoLS1VW36sra3tVC6cOXPmQCAQYNOmTQBa/z89PDwwceJErF+/Hnv37sXgwYORl5cHuVyOU6dOYdCgQV1/WMZjgy1hMRjPKfb29mp+sVmzZiE/Px8NDQ0wNzfHihUr2jUAVlZWCAwMxIEDBxAREQGpVAoA+O6777BhwwbweDzweDz4+fl1yndhYWEBIyMj7vjpp5+wcuVKeHt7Iz8/H/v370diYiIcHBy4OizL57MBMyAMxnPKzJkzUV5ejrKyMlRWViIoKAje3t4AACcnJ0RGRsLGxobTj4mJgVwuR15eHvz9/REcHIxdu3Zx8oiICGhra6OwsBBisRhmZmZqvreuEhwcjKSkJJw5cwYSiQRisRjZ2dnIzMzsdtuMnoUtYTEYzyk7duzAxx9/jN69e6O+vh719fWc7OTJk7C0tOR2zE2YMOGB7clkMnh5eaFXr15QqVRq7bVRXFwMHZ37f63MnTtX7VqhUGDDhg3YuHEjhEIhiAjV1dVQKpWdeUzGE4QZEAbjOUahUHBxze6lzXg8LPfb+tsdiAgVFRU90jajZ2AGhMF4hmhqanrSXXgqqaysxJAhQ/D+++8/6a48F1RWVnZqBsgMSA+gpaXV5V93DMb94PF40NLS6pFgg/T/Xm7tSXqq723BPu99z4TRNWpqamBgYPBAPWZAeoi2DH0MxqNEV1f3sXzR9xQ91XdjY2MolUq89957j7ztfyKnT5/GkSNHHqjHdmExGAwGo0swA8JgMBiMLsEMCIPBYDC6BDMgDAaDwegSzIAwGAwGo0swA8JgMBiMLsG28T5nlJWVYe/evbhy5QqICI6OjggKCoKVlRWnk5qaih9++AEAoKOjA5FIBDc3N4wePVqtrcbGRkRHRyMrKwsmJiaYM2cOZs2axclLSkoQGRmJ/Px82NnZ4Z133kHv3r05eWZmJuLj41FVVQU7OzuEhIRw2e1aWloQGxuLU6dOwdDQEMuWLdO4v1gsxt69e5GbmwsA2LdvH/T19dV0WlpasGbNGowdO5aL89QebcmvhgwZopYIicFgdB02A3nEyOXyJ7ZH/+LFi7C3t8fly5cxffp0uLu748qVK3B0dMTly5c5vcuXL+OXX37BSy+9BAsLC/z111+YMmUKXn/9dbUw3z4+Pvj1118RFBSESZMmITg4GPv27QPQmslwzJgxqKmpga+vL8RiMcaPH8/V/+233zBt2jQ4OjoiODgYYrEYEyZM4MKBb9myBbt27YKHhwcGDRqEV199FTk5Ody9z58/DycnJ8hkMixevBg+Pj7tRmjdsWMHYmJikJ2d3eG4lJWVwc3NDdu3b8f58+e7NcYMBuMuWEKp7nFvQqnk5GQCQH5+fo+1Hy0tLWRnZ9duEpjQ0FAaPnw4d71nzx4aP368ms7t27fJ0dGRQkJCuDL0EjubAAAgAElEQVQ+n0/Z2dnc9ebNm2nevHlERBQdHU2jR4/mZCqVikaPHs0l0nr//fdp1qxZnFyhUBCPx6Pr169TU1MTGRsbU2pqKicPCQnhxkylUpGtrS3FxMTc95kvXrxINjY25O/vT+vWretQb/To0bRz504KCgq6r96zQFcTSj3vB0so9WjpbEIpNgPpIe63nNITZGdn4/r16wgLC9OQbdiwAX/88YfaLORerKys8MEHHyA+Pp6bRdjb2+PYsWMAWmMwpaamYty4cQBal5eGDh3K1efxeJg2bRrOnTsHAHBwcMBvv/3GBfL79ddfYWFhARsbG1y7dg0KhUItAuzUqVO5FKZZWVmQSCRYtGhRh/1tbGyEv78/YmJioKure9+xSU5ORlhYGFQq1X31GAzGw8EMSA+xatUqODg4PJZjzJgxyM3NRa9evdCvXz+NvvTp0wfm5ua4du3affs8ZswYNDQ0oKCgAACQmJiIw4cPY9q0aXBwcMD48ePx9ttvAwAGDhyIy5cvc8t1SqUSFy5cQHV1NQBg9uzZePvttzF8+HB4eXkhLCwMJ0+ehK6uLm7fvg0LCwu1JSmRSISSkhIQEXJzczFs2DBs3boV1tbWEIlECA0NhVwu5/TXrFkDDw8PTJ48+YFLhkZGRgCgobd//37u/PPPP38mzkeNGoWHRVdXF0KhEDzeo/u4Gxsbq/m7HgY+n99hwih9fX2Ym5v3SLwsxqOHOdF7iO+//x56enqP5V7a2tpYv349DA0NO9QxNDTsdCTXNr3S0lIolUr069cPRUVFyMnJQW1tLUxNTeHn54eoqChMnjwZLi4uuHDhAlQqFWfAFAoFioqK0KdPH+jr60MqleLPP/+Eo6MjFAqFxqxBX18fRISWlhZIJBJkZ2cjMDAQxcXFkEgkmD59Oj766CP8n//zf3DixAmcP38eWVlZXRyxVmbOnMmde3l5PRPn169f7/B57oXH4+GTTz7Bv//9b8jlchgZGSEuLg4hISEausnJyXBxcQERobGxEdeuXcPnn3+O77//Xk1vxowZ+Oijj6Crqwu5XI433ngDf/75J4DW/8MPPvgAISEhMDY2brdPtra2uHz5MlavXo0vvviCKw8KCsKaNWtgY2ODhoYG8Pl8fPrpp1i3bl2nn5fx+GEGpIcYNmxYp/JFPyreeust/Pzzz2hubtb4cm7LZ/2gPOl//fUXAODFF1/E7du3MXv2bBw9ehSvvPIKlEolgoOD4eXlheTkZBgYGODixYv43//9X0ilUgQHB2Pbtm2wsLAA0LpsJhaLceHCBfD5fFy6dAlubm4QiUQwMzNDTU2N2r1ra2thbGwMbW1taGtrw8XFBYGBgQAAS0tLLF26FIcOHcLy5csRGBiId999FxcuXAAAlJeXo6mpCVlZWRgzZkynx+zuX9Btu8Oe9nOZTNbh89yLp6cnXn/9dQwaNAjl5eXo1asXrK2t29XV09NDSEgI9u3bB6FQCDc3N+zevRt2dnZc1kFnZ2fs27cP8+bNQ0pKilp9oVCIxMREFBcXa+yUa0NHRwcHDhxAXl6eWnlERASCg4Px5ptv4uTJk1AoFLC2tu7yDIfx+GAG5DnB1dUVurq6SExMxMKFC9VkCQkJEAgEcHV1vW8bH374IcaPHw+hUIhffvkFpqameOWVVwC0fvhXrFiBUaNGgYigpaUFPT09bkusXC7HsWPH8M033wAAzpw5g9DQUPD5fACt0YldXV2RlpaG5cuXo6amBrdu3eJmLFevXuVyYr/88sv48ssv1fqmUCigp6eH0tJS9O7dG1FRUZystLQU2traKCoqQnp6eleH8LlDJBKhsLAQ5eXlAFqNdFsyqBEjRuDgwYPw8PDArVu31OpJJBIcOnQIpaWlSE5ORnR0NCoqKrB27Vrs2bNHw3gArX//uLg4JCcnY8GCBe32Z/PmzUhPT0f//v3V+hgeHg43Nze1/OolJSUoKSnp9hgwehbmA3lOMDY2xsaNG7F27VqkpKRwYbNTUlKwdu1abNmyRS2+PxGhqakJ5eXlSE9Px+uvv47U1FRER0cDaJ1BlZWVcctERISEhAQ4OTlprE/X1dXB19cXQ4cOxdSpUwEAjo6OOHbsGJefQSwWIzMzE87OzujduzemT5+ODz74AEqlEhUVFfjkk0/g4+MDAJgyZQqampoQGRkJoHXLcGxsLKZPn45hw4bh6tWrascbb7yBoKAgznhs374dZ86c6cHRfjY4ceIEnJycsG3bNpiZmanJampqUFhYeN/sgmlpaZBKpdwPj/HjxyMrKwvvvvsuoqKi1N6nqaurw8GDBzv0s7i4uMDDwwPh4eFq/o+pU6fi1q1basaD8ezADMhzxKZNmxAWFoZFixbB0NAQhoaGWLx4MTZt2oTVq1er6Z4/fx76+vro27cv/Pz8YGlpiUuXLmH48OEAgJdeeglffvkl3njjDQwZMgT9+vVDWloaDh48yLXh4OAAW1tbvPjii9DX11fLH7Bz507I5XL07dsXw4YNg7OzM1auXAl3d3cAwJdffons7GyYmpqib9++cHV1xbJlywC0+kOOHj2Kzz//HFZWVujfvz9cXFwQGhraqXHYtm0bEhISujWWzwMFBQUYO3Ys7O3tIRaLERUVBXNzcwBAYWEhZs2ahbq6uvu20Tbj09LS4mYLYrEY6enp2L17N5YuXfrAfhgZGSE2NhaLFy/WSPhkaWmJoqIi7looFCI1NZU7GE857D2Q7tHReyCNjY1PsFdElZWVVFVV9UjakkqlVF9fr1FeW1tLJSUl1Nzc3GFduVxOZWVl1NLS0q68vLycGhoaOqxfUVFx3/bbQyKRPHSdZ4WuvgcyYMAAOn78OGVmZrYrP3v2LAUEBGiUS6VS8vT0JD6fT0St79S0yRYsWEAZGRlq+n379iWlUqlWFhsbS+vWrSOBQEACgYB+/PFHCg0NJT6fTwEBAZSTk8Pp6unp0ZQpU8jf35+IiL0H8oTo7HsgzAfynNL2S/NR0JEz08TEBCYmJvetq6urC5FI1KH8bgdxewiFwgd38B7aHPmM/09BQQFCQkJQVFQEAwMDtYgDHeHu7g5DQ0Okp6dzGzHaIgkArT6VzmwUmTNnDgQCATZt2gQAEAgE8PDwwMSJE7F+/Xrs3bsXgwcPRl5eHuRyOU6dOoVBgwZ1/WEZjw22hMVgPKfY29urGfhZs2YhPz8fDQ0NMDc3x4oVK9o1AFZWVggMDMSBAwcQEREBqVQKAPjuu++wYcMG8Hg88Hg8+Pn5dcp3YWFhASMjI+746aefsHLlSnh7eyM/Px/79+9HYmIit4kCQIfviTCeLpgBYTCeU2bOnIny8nKUlZWhsrISQUFBXIQEJycnREZGwsbGhtOPiYmBXC5HXl4e/P39ERwcjF27dnHyiIgIaGtro7CwEGKxGGZmZtwW3+4QHByMpKQknDlzBhKJBGKxGNnZ2cjMzOx224yehS1hMRjPKTt27MDHH3+M3r17o76+HvX19Zzs5MmTsLS0hEQiAQC1sDIdIZPJ4OXlhV69ekGlUqm110ZxcTF0dO7/tTJ37ly1a4VCgQ0bNmDjxo0QCoUgIlRXV0OpVHbmMRlPEGZAGIznGIVCwcUju5c24/Gw3G/rb3cgIlRUVPRI24yegRkQBuMZgv0qb5/6+npYW1sjMTHxSXflueDmzZudCj7KDAiD8YzRU4EG6THlsemJ/isUClRXV6u9i8ToOjU1NWrRtjuCGRAG4xlCR0fniSUse1T0RP/NzMygVCrx7bffPvK2/4mcPn26U8aY7cJiMBgMRpdgBoTBYDAYXYIZEAaDwWB0CWZAGAwGg9ElmAFhMBgMRpdgBoTBYDAYXYJt4+1hcnJysH//fty8eRNGRkZwdXXFokWL2g1iFx8fj+rqaqxatUpDlpiYiKNHj4LH48HX1xevvfYaJ5PL5YiKisKFCxdgaWmJ5cuXw87ODgBw4MABLvXr3QwYMACrV69Gc3MzYmJikJ6eDn19fXh4eHDxkgCgsbER0dHRyMrKgomJCebMmYNZs2aptSUWi7F3717k5uYCAPbt29dhWtO2ZxGLxRo5ShgMxrMFm4H0IHFxcRg7dixUKhW8vLzg4uKC2NhYuLq6aoSDUCqVCA8Px9atWzXyhe/atQtr1qzBq6++ikmTJiEwMBBxcXGc3NPTEz///DPmzp0La2trjB07FleuXAHQmszHwsJC7cjIyMD58+cBAG+88QZOnz4Nd3d3jBs3DitWrMCePXu4tn18fPDrr78iKCgIkyZNQnBwMPbt28fJz58/DycnJ8hkMixevBg+Pj4dRlJtbm7GihUrEBwczN4YZjCeB1hCqe7RUUKpvLw8EggE9MMPP6jpNzc307/+9S9655131MqPHDlCo0aNohkzZlB0dLSaTCgUUlJSEnd9/PhxEolE1NLSQteuXSM9PT2qrq7m5KtXryZvb+92+9vY2EiWlpaUkpJCRER37txRk0dFRZGzszN3zefzKTs7m7vevHkzzZs3j4iIVCoV2draUkxMTIfjczdt/frqq69ozJgxnarDUKerCaWe94MllHq0dDahFJuBPGIGDRoEHR0dHD58GNbW1njjjTfU5Hw+H6tXr8bBgwfVYs3ExsbC29sbvr6+iI2N5cqbmpogkUjUwgpMmzYNUqkUN27cgFgshpWVFUxNTTm5u7s7zp07127/4uPjYW1tjUmTJgFonaHcjUqlUltes7e3x7Fjx7i+pKamYty4cQCArKwsSCQSLFq0qFNjs2XLFiQkJEBXV7dT+gwG4+mGGZBHjKGhIQDgr7/+gr29fbtxfxwcHFBVVcVFSS0pKcGpU6fg5+cHT09P3LhxA5cuXQLQmr3thRde4K4BIDMzEyqVCtXV1Rg4cCBu376N8vJyTn7u3DlUV1dr3LelpQW7d+/u0Pcgl8vx1Vdf4c033+TKEhMTcfjwYUybNg0ODg4YP3483n77bQBAbm4uhg0bhq1bt8La2hoikQihoaGQy+X3HRu6J5RFUlKS2v3Yecfnw4YNw8Oiq6sLoVAIHu/RfdyNjY07zFT5IPh8fofLnPr6+jA3N++xeF+MRwszID2AiYkJfv/9d+4L817aypuamgC0zgomTZoEMzMzaGlpwdPTU83HsW3bNixZsgQrVqzAsmXL8Mknn4DH48Hc3ByDBw+Gn58fXF1dsXbtWnh7eyMjI6PdlLaHDx9GU1MT5s2bpyFraWnB4sWLMXjwYPj7+3PlpaWlUCqV6NevH3g8HnJycjj/jUQiQXZ2NgYOHIji4mLk5OTg3Llz+Oijjx5qvAYPHsyd3/0Fyc41zx8m3DmPx0NkZCQqKyuRm5uLhoYGREdHt6ubnJwMmUyG+vp6SCQSpKamYv78+Rp6M2bMQG5uLi5fvoz09HQMGTKEk2lra2PHjh24c+dOh32ytbVFTU2N2o8UAAgKCkJubi5qa2tx8+ZN1NfXY+fOnZ1+VsYTgvlAuse9PhCpVEq9e/emtWvX0oQJE9qtc/r0adLW1qb6+npqaWmhgQMHaqzpmpqaUmNjI1cnNzeX4uPj6fjx41RQUEA8Ho9kMhknT0tLo5iYGMrIyKCDBw+262MYNWoU7dq1S6O8paWF3nrrLXJzc1O7Z2lpKZmamtKZM2eIiEihUNC///1vevXVV4mI6MMPP6RJkyaptfXFF19olN1LfHw884F0kYfxgXh5eVFRURGJRCICQL169SI7O7t2dc+ePUsBAQEEgIRCIS1YsIBKSkpoy5YtnI6zszNJJBKaPHmyRn2hUEipqan09ddfk1KpbPceOjo6lJGRQZcuXaKlS5dy5REREVRSUkIeHh7E5/MJAFlbW5OjoyPzgTwhmA/kCTN16lRkZmaiqKhIQ/btt9/ilVdegaGhIU6fPo26ujrU1dWhsbERjY2NkMlkMDY2xuHDh7k6Q4YMQUBAAGbOnIkff/wRLi4uMDAw4OSurq5YsmQJXFxckJCQADc3N7V7pqSkIDc3F8HBwRr9CQ0Nxd9//41jx46p+T9+//13mJqa4pVXXgHQGgl2xYoVOHPmDIgIL7/8MoqLi9XaUigU0NPT69qgMR4pIpEIhYWF3PJmbW0trl+/DgAYMWIEcnJy0K9fP416EokEhw4dgo+PDzZu3AhLS0sAwNq1a7Fnzx6kpKRo1JHL5YiLi0NYWFiH/dm8eTPS09ORl5en1sfw8HD4+PggKSkJCoUCQOuybttOQsbTCzMgPcTUqVMxceJE+Pn54e+//wbQ+iH78ssv8c0332Dbtm0AWp3nfn5+MDY2hkAggEAggIGBAQICAtSWsdr45ZdfsHXrVmzZskVDplKpsH37dmRlZXF+ijZ27dqFJUuWoFevXmrloaGhyMrKQnx8PBoaGiCVSiGVSqFUKjFs2DCUlZUhKysLQKvvIiEhAU5OTtDS0sKUKVPQ1NSEyMhIAEBVVRViY2Mxffp0AK1LZjExMd0cSUZXOXHiBJycnLBt2zaYmZmpyWpqalBYWHjf7IJpaWmQSqVwdXUFAIwfPx5ZWVl49913ERUVhdmzZ3O6dXV1OHjwYId+FhcXF3h4eCA8PFzN/zF16lTcunULaWlp3XlUxpOCLWF1j46WsIiI6uvradmyZWRoaEjGxsbE5/PJycmJ20JbVVVFenp6dOXKFY12CwoKSFtbm27cuEH79++nfv36kZWVFQ0aNIgSExPVdN98802ysbEhU1NTmjBhgkZ7V65cIR0dHSooKFArLysr63BJID09nYiI9u/fT3369KGXX36ZrK2tady4cfTXX39xbWRnZ9OQIUNIJBKRkZERvfXWW9Tc3ExERDNnziQ7OzuNZ2NLWF3nYbfxOjg40LFjx+jOnTsUFRVF5ubmD1zCuvvIzs6m4OBg0tLSIoVCQSkpKRQYGEjz5s2jGzduqC1FAaC+fftqLGEZGRnR1atXadiwYQSAfvjhB67eqlWrKCUlRWMprO3o7HOyJaxHS2eXsJgB6SaHDh3iDAaRugFpo6WlhcrKytR8Fg+DUqmkkpIStXc97qaxsZFu3brV5fY7g1Qqpfr6+g7lFRUVnOFoQyaTUU1NTY/16Z9IV98DGTBgAB0/fpwyMzMfyoBIpVLy9PQkPp9PRESjR4/mZAsWLKCMjIwHGpDY2Fhat24dCQQCEggE9OOPP1JoaCjx+XwKCAignJwcTldPT4+mTJlC/v7+RETMgDwhOmtAWCiTbmJvb49ly5bdV0dLSwsikajL99DW1kafPn06lAsEAvTt27fL7XeGB23ZFAqFGmV3+2gYT5aCggKEhISgqKgIBgYGaGhoeGAdd3d3GBoaIj09HQqFAqWlpZyPAmj1qbQXkude5syZA4FAgE2bNgFo/X/18PDAxIkTsX79euzduxeDBw9GXl4e5HI5Tp06hUGDBnX9YRmPDeYDeQSwPMyMpxF7e3uYmJhw17NmzUJ+fj4aGhpgbm6OFStWtGsArKysEBgYiAMHDiAiIgJSqRQA8N1332HDhg3g8Xjg8Xjw8/PrlO/CwsICRkZG3PHTTz9h5cqV8Pb2Rn5+Pvbv34/ExEQ4ODhwdTp6T4TxdMEMCIPxnDJz5kyUl5ejrKwMlZWVCAoK4gJlOjk5ITIyEjY2Npx+TEwM5HI58vLy4O/vj+DgYOzatYuTR0REQFtbG4WFhRCLxTAzM0NERES3+xkcHIykpCScOXMGEokEYrEY2dnZyMzM7HbbjJ6FLWExGM8pO3bswMcff4zevXujvr4e9fX1nOzkyZOwtLSERCIBAEyYMOGB7clkMnh5eaFXr15QqVRq7bVRXFwMHZ37f63MnTtX7VqhUGDDhg3YuHEjhEIhiAjV1dVQKpWdeUzGE4QZEAbjOUahUHAhc+6lzXg8LPfb+tsdiOih3rRnPHmYAWEwGM88zc3NMDAwwI0bN550V54LOvvjghkQBuMZ4u4Izoz/T9uOsLvjuDG6TlNTk1rSuo5gBoTBeIZgu5PaRygUorm5mUuUxugep0+f7tTuUrYLi8FgMBhdghkQBoPBYHQJZkAYDAaD0SWYAWEwGAxGl2AGhMFgMBhdghkQBoPBYHQJto33MXPixAkcPXoUZWVlEIlEeP311+Hh4dGu7rp16zBx4kQNuVwuR1RUFC5cuABLS0ssX74cdnZ2nLykpASRkZHIz8+HnZ0d3nnnHbVour/99htiY2NRU1ODiRMn4q233uK2h+bk5GDfvn0oLCyEUCiEr68vl5EQAJKSkvDTTz+hqqoKL730EpYvX46BAwcCaH2Za//+/Thz5gyUSiWGDx+O0NBQGBsbdzgeSqUSu3fvxpAhQ9QSFDEYjKcfNgN5jAQEBGDJkiXo378/5s+fjwEDBiA4OLjdNLNXr17Fp59+iq1bt2rIPD098fPPP2Pu3LmwtrbG2LFjufSfVVVVGDNmDGpqauDr6wuxWIzx48dz4bvPnTsHNzc3vPTSS5g7dy4OHDiAgIAAAEBpaSlmzpwJQ0ND+Pj4YODAgZg+fTqSk5MBtEYdXr9+PYYMGQJfX1/cuXMHY8aM4cJPrF27FkePHoWrqyvmzp2L//73v5gxY0aH41FWVgY3Nzds376d7d9nMJ5FWEKp7tGWaa2N9hJKERF9//33pK+vT2KxWK1cLBaTvr4+HTlyRK38nXfeoZUrV5KpqSldu3aNK7927Rrp6empJZdavXo1eXt7ExFRdHQ0jR49mpOpVCoaPXo0RUdHExGRt7c3hYWFcfKysjIyNDTk7qFSqdT6sXDhQlqxYoVae3djbW1Nhw8fblf2999/EwCqrKzUGA+i1uREO3fupKCgIFq3bl27Ogx1uppQ6nk/WEKpR0tnE0qxGchj4sCBA/Dx8UG/fv3Uyvv16wc/Pz/s27ePK5PL5fj666/h6+sLb29vxMbGcjKxWAwrKyuYmppyZe7u7jh37hwnHzp0KCfj8XiYNm1ah3KRSISRI0dy8rtzWqtUKly/fh0DBgxQa6+N27dvo7KykpPfmw/7ypUr6N27t1pOirtJTk5GWFgYC8/BYDyjMAPyiNHS0oJKpcKmTZu4Izs7G7m5uWoJc+7GwcEB165d466PHDkCkUiEUaNGwd/fHwcPHkRzczMAYODAgbh9+zbKy8s5/XPnzqG6upqTX758GUQEoNXHcOHCBTX5pUuXuLoVFRW4ceMGJweAzz77DJs3b8bkyZMxevRoLF++nJNVVlbio48+wpo1azBz5kzs3LkTI0eO5OSXL1/Gzp078eabb2LHjh1ITEzsMLy3kZERAHB9bSMlJYWd3+f8YdHV1YVQKNQw8N3B2Nj4gVkqO4LP53cYkkVfXx/m5ubQ0tLqTvcYjwlmQB4x5ubmOHToEPT09LgjNjYWcrkchoaG7dYxNDREU1MTdx0bG4uFCxeiqakJzs7OMDY2xrFjxwAAgwcPhp+fH1xdXbF27Vp4e3sjIyMD5ubmAAA/Pz+oVCpMnjwZ69evx7Rp09DU1MTJ169fz81u1q5di3nz5sHExISTA62+kNu3b6OlpQV5eXkoLCzkZAqFAsXFxZBIJFAqlbh48aJaXoj6+nqUlJSgtrYWMpmsS76Nu79c2LnmeWfh8XiIjIxEZWUlcnNz0dDQgOjo6HZ1k5OTIZPJUF9fD4lEgtTUVMyfP19Db8aMGcjNzcXly5eRnp6OIUOGqPVxx44duHPnTod9srW1RU1NDd5880218qCgIOTm5qK2thY3b95EfX09du7c+dDPzHjMMB9I97jXB9IRo0aNovDw8HZlmzdvJhcXFyIiKigoIC0tLY013unTp6vVSUtLo5iYGMrIyKCDBw/SmDFjOFlTUxMdPXqU4uLiKD8/X8PHUF5eTt9++y198803VF1dTTY2NnTixIl2+7ZixQqaOHFiuzK5XE5OTk4UERHRrry4uJj09fUpJSWlg1FpZfHixcwH0kkexgfi5eVFRUVFJBKJCAD16tWL7Ozs2tU9e/YsBQQEEAASCoW0YMECKikpoS1btnA6zs7OJJFIaPLkyRr1hUIhpaam0tdff01KpbLde+jo6FBGRgZdunSJli5dypVHRERQSUkJeXh4EJ/PJwBkbW1Njo6OzAfyhGA+kKeMqVOnIiEhAS0tLWrlLS0t+P777+Hu7g4AiIuLw8yZM9HY2MgdV69exalTp3Dr1i2unqurK5YsWQIXFxckJCTAzc2Nk+np6WH27NkIDAyEtbU1jh07pia3tLSEj48PfH19UVBQgNLSUowbN67dfjs5OeHmzZvtynR1deHg4NCh3NraGiKRqEM5o2cRiUQoLCzkljtra2tx/fp1AMCIESOQk5Oj4ZMDWnNBHDp0CD4+Pti4cSMsLS0BtO6y27NnT7vLaXK5HHFxcQgLC+uwP5s3b0Z6ejry8vLU+hgeHg4fHx8kJSVBoVAAaN2K3razkPH0wgzIY+I///kPampqEBISgqqqKgCtW25DQkIgk8nwzjvvQKVSYd++fQgKCoJAIOCOYcOGYdy4cYiPj1drU6VSYfv27cjKysLbb7+tcc+6ujr4+vpi6NChmDp1qoY8Ly8PCxcuxJo1a2BiYoLc3FxcvXqVk5eXl+OLL77A5MmTAQDp6elq2e0uXbqEY8eOcfJffvmF2y4MtG4cKCkpgaurK/B/27vzuCir/Q/gn2EY2QZZBwjIBUEzQU1MJTYNsStuuCAuXDQwXMhcstSLhLcU00oNpCzRFLpl0A/raqgFiiIpJqm5oBgCg6wzrDLCzADn9wcvntvIIDhCKn7fr9e8nHnOOc+c52Gc7zznnOccAFu2bMGpU6c0PYXkIR09ehTOzs6IjIyEiYmJSlp1dTXy8/MfuLrg6dOnIZVKub+fq6srMjMzsXHjRkRHR6vct1NbW4v4+Ph2+1nGjBkDHx8fbNiwQaU5ztvbG4WFhTh9+vSjHCp5TCiA/E3Mzc2RkZEBsVgMS0tLGBkZwcrKCiUlJaERV6gAACAASURBVMjIyICRkRGOHz8OpVKp9t6JRYsW4auvvgJjDCEhIbC3t4e5uTmSk5ORkpICS0tLLq+TkxMcHBzQp08f6OnpqczrX1BQAJFIBDs7O7i5ucHf3x8REREAWgLGa6+9ht69e8PW1hYDBgyAnZ0doqKiALTcgDhw4ECIRCJYWlpiwoQJWLFiBV5//XUALQHDxMQENjY2MDIywgcffICEhAQ4ODgAACIjI5GQkNBt55ioysvLg4uLCxwdHSEWixEdHc31deXn52PKlCmora194D6Ki4thZmYGHo/HXS2IxWKkp6dj+/btWLJkSYf1EAqFiI2NxYIFC7jBIK0sLCxQUFDAvRaJREhLS+Me5AlHfSCPprN9IH+lUChYcXExUygUGr1nfX09KywsZDKZTG16TU0NKyoqanf/5eXlrLy8nDU3N7dJa25uZhUVFe2Wb2xsZKWlpaysrKzNfR+MtfS/FBUVscrKyjZpEolE42MmLTS9D6R///7s8OHD7Ny5cx32gfz1IZVK2fTp05lAIGCMtdy705o2Z84cdvbsWZX8tra2bfpAYmNj2dq1a5muri7T1dVlSUlJ7M0332QCgYAtXLiQXblyhcuro6PDxo8fzwIDAxljjPpAHpPO9oHQVCaPgUAgwHPPPadxeV1dXdja2rab3rt373bvvQBafuW1h8fjqYzIuh+fz1e52rmfjo4OrK2t1aaZm5u3W450r7y8PISGhqKgoAD6+voqTY3tmThxIgwMDJCeng6lUoni4mKujwL43zKyHfH19YWuri7Cw8MBtHx+fXx84OnpiXXr1mHfvn0YOHAgcnJyIJfLkZKSAnt7e80PlvxtqAmLkB7K0dFR5YfElClTkJubi3v37sHU1BTLly9XGwCsrKwQFBSEuLg4REREQCqVAgC+/fZbrF+/HlpaWtDS0kJAQECn+i7Mzc0hFAq5xw8//ICVK1fCz88Pubm5OHDgABITE1Xuk6Kle58OFEAI6aEmT56MsrIylJaWoqKiAsHBwfDz8wPQMrouKioKAwYM4PLv2bMHcrkcOTk5CAwMREhICLZt28alR0REgM/nIz8/H2KxGCYmJlz/2aMICQlBcnIyTp06BYlEArFYjKysLJw7d+6R9026F8/Dw4PRyBjNXbt2Df7+/iqjlwjpLi4uLg/1xSoQCGBmZoa6ujqVGz6BlqZMiUTy0HUwMjJCU1NTm/09Kh6PB5FIBMYYqqqq0NjY2Omy1tbWaGxsVJmhgWjuxIkTOHToEKKjo9vN4+bmRtO5E9KTKZVKlaHXf6VJ8ADwwKG/j4Ixxs3sTJ4O1IRFCCFEI3QFQshT5GGadZ4lZWVlsLa2xpAhQ/7W9+XxeH/LxI/3z2DR3dq7H+1+FEAIeYq0N7Pxs87U1BR1dXVITEx83FXpES5cuIDffvutw3z0aSSEPPVarwTam/GaPBxdXd1OXVlRHwghhBCNUAAhhBCiEQoghBBCNEIBhBBCiEYogBBCCNEIBRBCCCEaoWG83SQtLQ3ff/+9yjahUIgPP/xQJU1fXx99+vSBn5+fyjTpv/32G2JjY1FdXQ1PT08sXrxYZYbSgwcP4siRI2CMwdXVFcHBwdDR0QHQsrxodHQ0zp8/DwsLCyxbtgwvvviiSl3Onz+Pb775BoWFhRg0aBAiIyMBAJcvX8aePXtU8vr4+MDHxwdAyw1NsbGxSElJgYGBAZYuXYpRo0Y98FxcunQJe/fuxY4dO+g+BkJ6ELoC6SaXLl3C4cOHYWVlxT1a15a+dOkSjhw5AltbW+jp6eHo0aMYMGAANyFjRkYGvLy80K9fP8yaNQtxcXFYuHAht++dO3ciLCwMU6dOxdy5cxEfH4/Fixdz6dOnT8eRI0cwa9Ys2NjYwMXFRWV96aioKEyfPh19+/bF4sWLuSVpASArKwupqakwNzfnHvr6+lz6v//9b2zbtg0+Pj6wt7fHq6++iitXrrR7Hvbt24eJEydi165ddBc1IT0M/RzsRs8//zw2bNigNs3W1hbr1q3jXk+cOBFffvkloqKi8Omnn2Lp0qVYv349AMDDwwMDBgzA9evX8eKLL+Knn35CaGgoZs+eDQAwMDDAnDlzAADXr1/HiRMnUFpaCmNjYwBARUUFNm3ahISEBOTl5eHdd9/F5cuXMWjQoDb1kkgkGDNmDDZu3NgmTS6XY8eOHTh8+DA8PT0BACUlJdi2bRvi4+Pb5D9y5Ah27NiBxMREbl1tQkjPQVcg3UAmkz10GVtbW1RUVAAAxGIxBg8ezKVZWlripZdeQkZGBoCWNc+PHTvGrQ537NgxvPLKK1xZKysrLngALcGptezBgwfx6quvqg0eACCVSttdOfDatWtQKpVwc3Pjtnl7e7e7dvWkSZOQmZmJ559/vk3aX69a6Hnnnz9oNcj29OrVCyKRCFpaXfff3dDQEGZmZhqVFQgE7S4YpaenB1NT079lfiny6CiAdLFr167h/fffB9Dyiz0/P597qJs+W6lUIi0tDUlJSZg7dy4AwM7ODhcvXuTylJeX488//0RVVRUA4IMPPoCRkRGGDRsGT09PXL9+Hfv27ePKlpSUqKyLkJGRwZXNzs6Gg4MDZsyYAZFIhH79+mH37t1c3oqKCiQkJMDBwQEvvfQSVq1ahcrKSgAtVxvm5uYq//ktLS1RVFQExlibY+PxeNDX11ebduvWLXquwfMHLTd8Py0tLURFRaGiogLZ2dm4d+8eYmJi1OZNTU2FTCZDXV0dJBIJ0tLS4O/v3ybfpEmTkJ2djUuXLiE9PR0vvPACl8bn8/Hhhx/i7t277dbJwcEB1dXVeOONN1S2BwcHIzs7GzU1Nbh9+zbq6uqwdevWTh/rk8zX1xdnz55V2VZfXw9nZ+cuX1Pl70ZNWF2soaEBqampCAgIwMWLFzF8+HAubebMmdi7dy+Ali91bW1tNDc3w8DAAF9//TUmT54MAFi3bh3GjRsHiUQCGxsb/Pbbb+jduzf35VFdXQ2JRAIHBwfcvXsXt2/fRmFhIUxMTDBw4EAEBATA3d0d06ZNQ35+Purq6riyEokEJ06cQFJSEpKSkvD7779j7NixcHR0hJubGzZt2oRFixbB0tISd+7cwYYNGzBjxgykpaVBqVSiV69eKserp6cHxhiam5sfahnSGTNm0HMNnmdnZ6Ozpk+fjmnTpsHe3h5lZWUwMjKCjY2N2rw6OjoIDQ3F/v37IRKJ4OXlhe3bt+PFF1/kVh0cOXIk9u/fj9mzZ+PkyZMq5UUiERITE3Hnzh3o6empfQ9tbW3ExcUhJydHZXtERARCQkLwxhtv4JdffoFSqYSNjY3GVzhPGoVCgaamJpVtjDEoFAq1P66eJhRAutGYMWNw5swZtWkuLi74+eefIZFIMGzYMJWO6qFDhyI7OxupqalgjCEsLAwjR46Era0tgJZfNL6+vggLCwMA7N27F15eXsjJyYGJiQn27t2L9PR03Lx5EzNnzsSff/6JXbt2AWj5lfjGG29wI6dGjBiBSZMmITU1FW5ubrC2toa1tTUAYMCAAdi3bx8GDhyI8vJymJiYoLq6WuU4ampqYGhoSGtYP4EsLS2Rn5/PXY3W1NRwi0ENHz4c8fHx8PHxQWFhoUo5iUSCgwcPori4GKmpqYiJiUF5eTneeecd7Nixo03wAFqutvfu3YvU1FSuP+5+7733HtLT09G3b1+VOm7YsAFeXl4q66sXFRWhqKjokc8B6V7UhPWYaGlpQSgUon///ggLC0NoaCjkcjmXbmFhgblz52LevHnIy8tDcXExXnnlFchkMly4cAEBAQFc3uDgYCgUCpVldd3d3bFo0SKMGTMGCQkJ8PLyAgAMGjQId+7cUamLUqnkhgDfr/XXpLa2NhwdHVFdXa3yhXP16lU4OTk9+gkhXe7o0aNwdnZGZGQkTExMVNKqq6uRn5//wNUFT58+DalUyg2AcHV1RWZmJjZu3Ijo6GhMnTqVy1tbW4v4+Ph2+1nGjBkDHx8fbNiwQeXHhre3NwoLC1WCB3l6UAB5AqxatQoA8OGHH7ZJy8nJwfz587FmzRr07t0bBgYGsLOzU7nH5OjRo2hsbGxzr0dTUxO2bNmCzMxMvPXWWwCAwMBAfPvttzh//jyAlg7a48ePw9vbG0BLh3xrIJPJZAgLC4OnpydMTU1hZmaG1157DZs3b0ZjYyPKy8uxc+dOru/m8uXL2LBhA9e5Tx6vvLw8uLi4wNHREWKxGNHR0VxTZn5+PqZMmYLa2toH7qO4uBhmZmbg8Xjc1YJYLEZ6ejq2b9+OJUuWdFgPoVCI2NhYLFiwAAqFQiXNwsICBQUF3GuRSIS0tDTuQZ5sFECeAL169cKOHTuwZcsW/PnnnygoKIBIJIKdnR3c3Nzg7+/PtUMDLSOp4uLi0LdvXwwaNAihoaFISEjg2oxDQkJgb28Pc3NzJCcnIyUlhRu9M2zYMHz22WeYMmUKrK2t4enpiY8++gjOzs4AgNjYWAiFQu6+ldraWnzzzTfce3/xxRfIysqCsbExbG1t4e7ujqVLlwIAUlJSsGXLFm40GXn8rly5gqlTp2Lo0KHo168fkpOTH6p83759IZFIoK2tDW1tbaxduxb79u1DQkICNmzYgAULFnS4j507dyI+Ph65ubnQ1dWFlpYWtLW1IRAIUFlZqTLqr7a2Fps2bcK+ffu4oeJPuweNKHvaR5tRH0g3WblyJVauXNnptEmTJqGhoYF7ff36dQCAubl5mw/Zyy+/jMuXL6Ourg4KhaLNyJyoqChIpVKYmpqq9K20CgwMxPz58yGVSmFhYaGy/++//x5yuRyVlZUQiURt7hx//vnn8dtvv6G8vByGhoYqHaarVq1CQEBAm6Gm/fr1e+o7C592eXl5CA0NRUFBAfT19XHv3r0Oy0ycOBEGBgZIT0+HUqlEcXGxytVlTU0NdHV1O9yPr68vdHV1ER4eDqBlsSIfHx94enpi3bp1XD9bTk4O5HI5UlJSYG9vr/nBPmEsLS3bjMAsLS1Fr1691P7/fJrQFcgTSiQSQSQSPfAXilAoVDusU1dXF7a2tg/8cPL5fFhaWqrdv46ODp577rkHTjtiYWHRZrSNlpaWRvcpkO7h6OiI3r17c6+nTJmC3Nxc3Lt3D6ampli+fLnaAGBlZYWgoCDExcUhIiICUqkUAPDtt99i/fr10NLSgpaWFgICAjrVd2Fubg6hUMg9fvjhB6xcuRJ+fn7Izc3FgQMHkJiYqNKX1pMGZXh7eyMuLo4bzNDQ0ICoqCiMHz++S+/NeRye7toTQto1efJklJWVobS0FBUVFQgODoafnx8AwNnZGVFRURgwYACXf8+ePZDL5cjJyUFgYCBCQkKwbds2Lj0iIgJ8Ph/5+fkQi8UwMTFRaVrVVEhICJKTk3Hq1ClIJBKIxWJkZWXh3Llzj7zvJ4G/vz/Gjh0LX19feHl5wd3dHQKBoN1ZKp4mPA8PD3bq1KnHXY+n1rVr1+Dv78+NgMrKysLixYtx4cKFx1wz0hO5uLg81BerQCCAmZkZ6urq2ty0JhKJ1N7c2hEjIyM0NTV1+U1wPB4PIpEIjDFUVVU91NxpFhYWaGxsxJP8XcYYQ2VlJYRCYbujHp8UmZmZOHPmDL766qt287i5uVEfCCE9mVKpRGlpqdo0TYIHgAcO/X0UjDGUl5d3y76fBDwer8fcHNmKmrAIIYRohK5AHpGhoSF69eoFFxcXAC33Ttw/1p2QrtI6JUZ3DP/8u0bKdUfdq6qqMGTIELz77rtdvu9nkVKp5Ib2PwgFkEfUp08ffPfdd9y9Dzdu3MDNmzcfc61IT9X6Jf80D4vujrqbmJhALBbjwIEDXb7vZ9H58+c71Y9LAaQLODg4wMHBAUBLp+WuXbuwZcuWx1wr0hPRio7qtZ6XoUOHPuaa9AxSqRSXL1/uMB/1gRBCCNEIBRBCCCEaoQBCCCFEIxRACCGEaIQCCCGEEI1QACGEEKIRGhPYzY4ePYoff/wRpaWlsLS0xLRp0+Dj46M279q1a+Hp6dkmXS6XIzo6GufPn4eFhQWWLVumsnhUUVERoqKikJubixdffBErVqxQO2VCc3Mz1qxZAxcXF25SPQCoq6vD/v37kZmZCZlMhvDwcLz00kuIi4vjFp76q/79++Ptt98GANy6dQuffvopioqKMHr0aKxateqB8/w0NjZi+/bteOGFF1RWtCOEPH3oCqQbLVy4EIsWLULfvn3h7++P/v37IyQkBCEhIW3yXr16Fbt27cIHH3zQJm369Ok4cuQIZs2aBRsbG7i4uOCPP/4AAFRWVmL06NGorq7GvHnzIBaL4erqqna9hw8//BB79uxBVlYWt00qlWLkyJE4ffo0fH19ERISwgUfoVAIc3NzlcfZs2fx66+/AgDKysrg6uoKxhj8/Pzw3//+F0FBQe2ej9LSUnh5eWHLli3cPgghTzEPDw9Gus6FCxeYs7Mz++6775ienh4Ti8Uq6WKxmOnp6bFDhw6pbF+xYgVbuXIlMzY2ZteuXeO2X7t2jeno6LCqqipu29tvv838/PwYY4zFxMSwUaNGcWlNTU1s1KhRLCYmpk29BgwYwAIDA9natWu57UFBQWz+/PmdOrb6+npmYWHBTp48yRhjLDIyknl6enLppaWljM/ns1u3bqktP2rUKLZ161YWHBysUgfSeWPGjGEA6HHfw9ramllYWDzuP0+PkZqayt58880H5nF1dWV0BdINGGOIi4vD3Llz8fzzz6ukPf/88wgICMD+/fu5bXK5HF9//TXmzZsHPz8/xMbGcmlisRhWVlYwNjbmtk2cOBEZGRlc+uDBg7k0LS0tTJgwgUsHgPr6egQGBmLPnj3o1asXt12pVCIhIYFbL70jX331FWxsbDB27FgAwNmzZzFhwgQu3dLSEk5OTu1OqZ2amop3332Xm8+pVUlJCT3v5HNDQ0MQ8qSgANLF7O3tMW7cOGRnZ6ussPZXTk5OuHbtGvf60KFDsLS0xMsvv4zAwEDEx8dzEzLa2dmhpKSEW80MADIyMlBVVcWlX7p0iZtfqLGxEefPn+fSAWDNmjXw8fHBuHHjVOYhKiwsRH19PW7dugUHBweYmppi0qRJKCwsbFPn5uZmbN++nev7AFq+2O5fgdDS0hJ37txRe9xCoRBA27mQDh8+TM87+XzgwIF4WL169YJIJOrS1e8MDQ01nppcIBC0u+Kgnp4eTE1Nn/q1wp8Z1ITVPWxsbNiXX36pNm3v3r3M1taWe+3l5cU2b97M6uvrWX19Pevfvz9LTEzk0oOCgpiDgwNbs2YNmzVrFvvHP/7BbGxsGGOMyWQy5ujoyDw9PdnatWvZuHHjmIeHB9cslZyczIYPH87kcjljjKk0H507d45paWmxZcuWsfr6eiaXy9nChQvZ+PHj29Q5ISGB2draMoVCwW0bNmwYi4uLU8nn6+vLwsPDH3huFixYQE1YGnqYJiwtLS0WFRXF7t69y6RSKWtoaGAxMTFq86ampjKZTMbq6uqYRCJhaWlpzN/fv02+SZMmsezsbJabm8uuX7/OXnjhBS6Nz+ezDz/8kN29e7fdOjk4ODCZTMaWLFmisj04OJhlZ2czhULBqqurmUwmY1u3bqUmrMeks01YNAqrm1hbW0MsFqtNKygogK2tLQAgPz8fJ06cQGpqKsLCwrg8sbGxmDVrFgBg7969SE9Px82bNzFz5kz8+eef2LVrFwBAX18fFy5cwPHjxyGVShESEoLIyEiYm5ujqqoKQUFB2LhxIzeaqqysDA0NDcjMzASfzwefz8enn37KTUa3bt06ODk5obGxUWXivo8++ghvvfUWBAIBt83ExATV1dUqx1ZTU6PS3EYen+nTp2PatGmwt7dHWVkZjIyMYGNjozavjo4OQkNDsX//fohEInh5eWH79u148cUXuWVrR44cif3792P27Nk4efKkSnmRSITExETcuXMHenp6at9DW1sbcXFxyMnJUdkeERGBkJAQvPHGG/jll1+gVCphY2PT4xZf6okogHQTb29vJCQk4N///rdK00FzczO+++47zJs3D0BLcJg8eTISEhK4PLm5uRg2bBgKCwu5PhR3d3e4u7sDACIjI+Hl5cXl19HR4YbEyuVy/Pe//8V//vMfFBcXw8zMDNHR0Vze4uJi8Pl8FBQU4PDhw2hubkZZWRn3xaJUKqGtra3SxHDy5ElkZ2e3GT02dOhQXLp0iXvNGMO1a9ewfv36Rzt5pEtYWloiPz+fa/6sqanhVhMcPnw44uPj4ePj06bJUiKR4ODBgyguLkZqaipiYmJQXl6Od955Bzt27GgTPICWz93evXuRmpqKOXPmqK3Pe++9h/T0dPTt21eljhs2bICXlxdOnz7NbS8qKkJRUdEjnwPSvagPpJusWrUK1dXVCA0NRWVlJYCWIbehoaGQyWRYsWIFmpqasH//fgQHB0NXV5d7DBkyBK+88kqb9YibmpqwZcsWZGZmqu34rq2txbx58zB48GB4e3tjyJAhuHr1qspjxowZCA4ORnp6OoyNjeHr64vVq1dDqVRy92h4e3urtEFv27YNixYtgpGRkcr7zZs3D0lJSbh69SoYY4iKigKfz4enpycAYMuWLU/0GtU93dGjR+Hs7IzIyEiYmJiopFVXVyM/P/+By9OePn0aUqmU++Hi6uqKzMxMbNy4EdHR0Sr38dTW1iI+Pr7dfpYxY8bAx8cHGzZsUPlx4u3tjcLCQpXgQZ4eFEC6ibm5OTIyMiAWi2FpaQkjIyNYWVmhpKQEGRkZMDIywvHjx6FUKjFp0qQ25RctWoSvvvoKjDGEhITA3t4e5ubmSE5ORkpKikrntZOTExwcHNCnTx/o6enh0KFDna7nF198gdraWlhYWMDc3Bz5+fn47LPPuPQrV64gJSUFK1asaFN29OjRCA8Px+jRo2FsbIzt27cjISGBG+kVGRmpcmVF/l55eXlwcXGBo6MjxGIxoqOjYWpqCqCl6XTKlCmora194D5ar2J5PB53tSAWi5Geno7t27djyZIlHdZDKBQiNjYWCxYsaLNap4WFBQoKCrjXIpEIaWlp3IM84agTvfspFApWXFys0gH9MOrr61lhYSGTyWRq02tqalhRUZHG+2eMserqanb37l2N61dWVsaam5tVtkskkkeqE2lL0/tA+vfvzw4fPszOnTunNv3MmTNs4cKFbbZLpVI2ffp0JhAIGGMt9/K0ps2ZM4edPXtWJb+trS1rbGxU2RYbG8vWrl3LdHV1ma6uLktKSmJvvvkmEwgEbOHChezKlStcXh0dHTZ+/HgWGBjIGGPUif6YUCf6E0QgEOC5557TuLyuri7X6a5O79690bt3b433D6BN89TDaG16u5+5ufmjVIl0oby8PISGhqKgoAD6+vpqZyq438SJE2FgYID09HQolUoUFxdDqVRy6TU1NWr/7vfz9fWFrq4uwsPDAbR8Xnx8fODp6Yl169Zh3759GDhwIHJyciCXy5GSkgJ7e3vND5b8bagJi5AeytHRUeWHxZQpU5Cbm4t79+7B1NQUy5cvVxsArKysEBQUhLi4OEREREAqlQIAvv32W6xfvx5aWlrQ0tJCQEBAp/ouzM3NIRQKuccPP/yAlStXws/PD7m5uThw4AASExNV7ptq7z4R8mShAEJIDzV58mSUlZWhtLQUFRUVCA4O5ibRdHZ2RlRUFAYMGMDl37NnD+RyOXJychAYGIiQkBBs27aNS4+IiACfz0d+fj7EYjFMTEy4Ib6PIiQkBMnJyTh16hQkEgnEYjGysrJw7ty5R9436V48Dw8PRiNlCHk6uLi4PNQXq0AggJmZGerq6lBXV6eSJhKJIJFIHroORkZGaGpqarO/R8Xj8SASicAYQ1VVFRobGztd1traGo2NjSozNhDNnThxAocOHVK5BeB+bm5udB8IIT2ZUqlEaWmp2jRNggeABw79fRSMMZSXl3fLvkn3oABCyFNET0+vzY2eXaWpqanNRJddjcfjqcxm0FVkMhkEAgE2bNjQ5ft+FhUVFXVqJgAKIIQ8RZKSkrB169bHXY0n0vDhwx+4mBnpvJEjR2LcuHEd5qMAQshTxNjYGFu2bHnc1SAEAI3CIoQQoiEKIIQQQjRCAYQQQohGKIAQQgjRCAUQQgghGqEAQgghRCMUQAghhGiEAgghhBCNUAAhhBCiEQoghBBCNEIBhBBCiEZoLixCeqDm5mZ8++23OHbsGORyOfr06YOZM2fCxcWlTd49e/bg8uXLAAAdHR307dsXU6dORb9+/drkraurw/79+5GZmQmZTIbw8HC89NJLXLpUKsXWrVsRFBSEwYMHq61bSUkJ/vWvf2H16tUqqxACwJkzZ/DDDz9ALBZDR0cHAwcOxOzZszFo0KBHOBttXblyBQcOHMDt27chFArh7u6Of/7znyorNLaeFx6PByMjIwwaNAh+fn5cnqKiIrXzkoWFheG5557DwYMHceTIETDG4OrqiuDgYLWTPbbuJyoqClpabX/T37lzB1FRUcjNzYWNjQ0WLVqEoUOHtsmn7rzevXsXu3fvxvnz56Grq4uBAwciICAA/fv31/jc/RVdgRDSA61fvx5r167F8OHD8eqrr0KhULS7ENVPP/2EGzduoF+/ftDX18eJEycwcOBAvP/++yr5pFIpRo4cidOnT8PX1xchISEqU35nZmZi9OjR+Pzzz1FQUKD2vRhjeP311/H999+jqKiI297U1ITAwEBMmzYNPB4Pr732GpycnHDx4kVkZWV1wRn5n71798LFxQVNTU2YOXMmxowZg9jYWLi7u6usdfLTTz/h+vXrsLGxQVNTEz7++GM4OztDJpMBaFlPJSYmBhYWFrCysuIe2tra2LlzJ8LCwjB16lTMnTsX8fHxWLx4sdr6tO6nubm5TZpMJsOYMWOgUCiwdOlS2NjYwNXVFdnZ2Sr51J1XxhgmjOUuRAAAD6RJREFUTJiApKQkjB8/Hs7Ozrh582a7fxuNeHh4MEJIz2JjY8MOHDigNq2iooL98ssv3Otp06axsLAwlTznzp1jQqGQJSYmctuCgoLY/Pnz1e6ztLSU2djYsJ9//pnZ29uzo0ePqs336aefshkzZrDBgwer5Nm8eTMTiUSssLCw08eoiYKCAqarq8u+//57le0KhYKNGDGCrVixgtt2/3mRyWTM1NSU/d///R9jjLGLFy8yAEypVLZ5n/Hjx7NPPvmEe33ixAlmYWHBvU5PT2dFRUUd7ufMmTPM0NBQZZuHhwf77LPPVLapO6+3bt1iAFhBQcGDT4qGXF1dGV2BENIDWVpa4uLFi2rTdu/eDW9vb9y5c6fd8qNHj8bixYsRExMDoGVlw4SEBLz11lvtvt+NGzfg7e3d7lK0169fx/bt2/H5559DqVRy25ubm7Fr1y6Eh4fD1ta2s4eokYSEBNjY2GDGjBkq2wUCAd5++23Ex8e3u6iWvr4+TE1NUVFR0eH7ODk54dixY9xxHjt2DK+88gqX7uXlhffee6/D/Tg4OECpVCItLQ0AUFhYiBs3bmDUqFFcnvbOq7m5Ofh8frufg65AAYSQHmjbtm2IjY3F1KlT8fPPP4MxxqUFBQUhMTGxwy/r0aNH4+rVqwBavrjq6+tx69YtODg4wNTUFJMmTUJhYSGXXygUAoDKe7VSKBQICAjArl27YGFhoZKnrKwMJSUlcHV15bY1NDSguroa1dXVXbr2enZ2NhwdHcHj8dqkOTk5obKyUu0SwDKZDJ9//jkqKysxceJElbSCggLk5+cjPz+fOx8ffPABjIyMMGzYMHh6euL69evYt28fVyYpKQnr16/vsL4WFhY4dOgQ/P394efnB1dXV0RHR8PZ2RnAg8+rsbExNm/ejDlz5uDNN9/k/pZdiQIIIT2Ql5cXsrOz4eDgAH9/f4wYMQI3b94EAFhZWWHWrFmd2k9DQwOAlnZ6xhh+/fVXXLlyBaWlpbCwsEBQUFCn9hMeHo7Ro0dj8uTJbdLu3bsHACr9KZs2bYKJiQlMTEwwduzYTr1HZ8jlchgYGKhNa93eeswAEBkZCW1tbQiFQsTExCAtLa1N4HV2dsbw4cMxfPhwjB8/HgBQXV0NiUQCBwcH8Pl83L59WyXYTpo0CQMGDOhUnfPz82FoaAgzMzPI5XJcvHiRCxQPOq8AsHbtWpw+fRoSiQQjRoyAn59flwZkCiCE9FC2trb45JNPIBaLYWdnh3nz5j1U+Zs3b6Jv374AAD6fDz6fj08//RS6urro1asX1q1bh1OnTrXbZNUqIyMDsbGxmD59Os6cOYMzZ86goaEB165dw40bN2BlZQUtLS3k5eVxZd5//30olUquCa2rWFtbQywWq00rKCgAn8+HlZUVt+2dd95BdXU1kpKSUFxcDEtLyzblpFIpd7XUGqR9fX3h7e2NH3/8ESdOnMDq1avh5eWFqqqqh6rvkSNHsHnzZmRkZGD37t24du0ajh8/jk2bNnV4Xlu9/PLL+O6773Djxg1cuXIFERERD1WHB6EAQkgPZ2hoiKVLl3Jfbp1RV1eH3bt3w9fXFwBgb2+P5uZmlJWVcXmUSiW0tbXB5/MfuK9bt27hueeew+rVq7FkyRIsWbIEEokE0dHR+PLLL2FgYABPT0/s37+fK6OlpQVtbW21w1ofhbe3N86dO6d2JNI333wDDw8PlSsUgUAAoVCI6dOnY8yYMVizZk2H7yGTyXDhwgUEBARw24KDg6FQKB66GenUqVMYP348F7jMzc3xz3/+E2lpaR2e1/vZ2dlh1qxZD/U56BCNwiKkZ1EoFOzHH39kNTU1jDHGampq2Lx585i3tzdjjLFLly6xsLAwplAoGGMto43WrVvH6uvrWV5eHjt06BBzcnJiTk5O3D4YY2zmzJls9uzZTKFQMKVSyV5//XU2derUNu/ft2/fdkdhtRowYIBKnvPnzzMdHR32zjvvsNLSUm77Rx99xJydnTU/GWp4eXkxNzc3lpOTwxhjrKGhge3evZvp6emxs2fPcvnuH4V18+ZN1qtXL3by5EnG2INHT9nZ2bGPP/6Ye52cnMz09fWZVCpljDEWGRnJ0tLSVPZTWlrKJBIJ91AqlSwuLo7Z2dmx8vJyxljLSLBx48axd999V+2x/fW83r59m/3666+soaGBMcZYXl4ec3R0ZJs3b9bovN3P1dWVUQAhpIepr69nL7zwAgPAhEIh09bWZpMmTWJ37txhjDH28ccfMy0tLVZSUsIYa/miBMAAMF1dXTZkyBAWHh7O7t69q7JfqVTK/vGPfzBjY2NmZGTExo0bx+3zrzQJIIwxlpGRwdzc3BiPx2OGhoZMR0eHGRkZsaVLlz7K6Wijrq6OLV26lBkYGDBDQ0MmEAiYs7MzFxhaqRvevGbNGjZ48GAml8sfGEDOnz/Phg4dyvr06cMGDhzI+vfvz44cOcKlC4VCtmzZMsbY/wLI/Y+zZ8+y5uZmtmrVKmZqasqGDBnCzMzM2Pz585lMJlN7bH89r5mZmczS0pLxeDwmFAqZvr4+W758udr6asLV1ZXxPDw82KlTp7rukoYQ8kSoq6tDbW0tRCIRBAIBt725uRkSiURte35n1NTUgM/nc6OuuppcLodUKoVQKETv3r3VjpjqCowxlJeXw9DQEPr6+t3yHnV1dVAoFDA1NVXZLpVKYWRkpPJ3eZDWv5mpqWmnywAtx1hdXQ2FQgELC4suPZdubm6gAEIIIeShubm5USc6IYQQzVAAIYQQohEKIIQQQjRCAYQQQohGKIAQQgjRCAUQQgghGqEAQgghRCMUQAghhGiEAgghhBCNUAAhhBCiEQoghBBCNEIBhBBCiEYogBBCCNEIBRBCCCEaoQBCCCFEIxRACCGEaIQCCCGEEI1QACGEEKKRDgNIUVERZDLZ31GXRyIWi9HQ0PC4q0EIIc+MDgNIZGQkLly48HfU5ZGsW7cOOTk5j7sahBDyzKAmLEIIIRqhAEIIIUQjFEAIIYRoRLujDOnp6Th+/DgMDAz+jvpoTCwWY+bMmRg6dOjjrgohhDwTOgwg7u7umDVrFjw8PP6O+mgsICAADg4Oj7sahBDyzOgwgACAlpYW+Hx+d9flkfB4vMddBUIIeaZQHwghhBCNUAAhhBCikQ6bsNauXQtTU9O/oy6PZPPmzbCysnrc1SCEkGdGhwGkT58+f0c9Hln//v0fdxUIIeSZQk1YhBBCNNKpUVgAUFNTg4sXL2Lw4MGwtLRsk97U1ISzZ89CJBJh0KBBHZYrLCxEXl4eRowYAaFQCACQy+W4fv06FAoFnJ2doa3dUr2CggJUVVUBAPh8PpycnAAA9fX1+OOPP2BkZIQXXngBAHDr1q02kz8OGzYMPB4PeXl5KCwsxMsvvww9PT0uXalU4vfff0d9fT3Gjh3b2VNCCCHPtE5dgRQVFcHFxQXJycmYMmUKTp48qZLe3NwMLy8v/Oc//8Hq1auxZcuWB5Y7duwYpkyZgiNHjmDs2LEoKSnB3bt3MX78eMTHx+Obb76Bi4sL5HI5AGDJkiXYunUrdu7cic8//xwAcP36dbz66qtISkrC6tWrsX79egDAwYMHsXPnTuzcuRPbt2+Hu7s7mpqaEBMTg+DgYBw/fhxubm4oKSkBAGRnZ2P06NH45ptv8Ouvv3bBKSWEkGeEh4cH60hERAT7/PPPGWOM5eTkME9PT5X0kydPMn9/f8YYY42NjWzw4MGsrq6u3XKenp4sOzubMcbYl19+ySIiIhhjjDU3N3P7nDBhArt48SJjjLGRI0cyuVzepl6t2xQKBbO1tW2TnpiYyEJDQxljjNnZ2bF79+4xxhj7+uuv2TvvvMMYY2zixIksKyurw3NACCHkf1xdXVmnrkD++OMPvPzyywAABwcH5OXltZvO5/MxaNAg3Lx5s91yeXl5XJPTqFGj8PvvvwNoaQYrKirC4cOHIZPJuDx3795FQkICEhISuKYsAOjVqxcAICcnR6XZrNXHH3+MlStXAmi5SmrN369fP1y9ehV1dXUoLi6GXC7HJ598gnPnznXmdBBCCEEn+0AaGhpU5sJqampCU1MTd3d6Q0MDevfuzaUbGBigqqqqw3J/zQsAd+7cwapVq1BSUoIJEyZAIBAAAP71r38BaAk8o0ePxsmTJ2FjYwMAuHfvHpYtW4YdO3ao1PnkyZOwtraGvb09AGDWrFlYsGABRowYgfT0dAgEApSUlKC4uBgZGRkYMWIEli9fjp07d8LV1bWTp48QQp5dnQogIpFI5Zd/c3OzShAQiUQoLS3lXldVVcHExKTdcgKBAIwx8Hg8Li/QcmVw6NAhAMDrr7+OhIQEzJ07F4GBgdw+KisrkZycjDfeeAMNDQ2YNWsWVq9ejREjRqjUeevWrQgPD+def/TRR8jKykJTUxP69euHjIwMaGlpwc7ODmvWrAEALF++HL/88gsFEEII6YRONWF5eHjgl19+AQCcPXsWw4YNAwCUl5ejoaEB7u7uSElJAQDU1dXhxo0bGDJkSLvlRo0ahfT0dABASkoKXF1d0djYqPKezc3N3L+tzwHg9u3bsLW1hVwux5w5c7BkyRJMmzZNpewff/yBmpqaNoHA2dkZw4cPR0xMDObMmYP+/fujtrYWFRUVAFpGcFlbW3fmlBBCyDOvU1cg8+fPx+zZs/Haa6+huLgYBw4cAAAsW7YMEyZMQEhICFxcXODp6Ynq6mqEhYVBR0en3XIbN27EvHnzYGxsDJlMhp9++glZWVlYvnw5+vTpA4lEAhsbG8ycOROVlZV47bXXYGNjg/LycowaNQoTJ07E1q1bcfr0ady5cwfvv/8+AOCLL76As7Mztm7ditWrV6scw3fffYcffvgBt2/fxrx587i+mY8//hg+Pj6wsLCAQqFAWFhYl51cQgjpyXgeHh7s1KlTncpcW1sLAwMDrvlKJpNBV1eXe11fXw8ejwddXd0HlmtVXV0NY2Nj7nVjYyMqKythaGiocp8GYwyVlZUwMjLi7g15WEqlElVVVTAzM2tTD6VSiXv37sHIyEijfRNCyLPGzc2t8zcSAlDpKAfQZpGpv37pP6hcq78GDwDQ1taGhYVFm3w8Hg9mZmYPU9U2BAKB2n23plHwIISQh0NTmRBCCNEIBRBCCCEaoQBCCCFEIxRACCGEaIQCCCGEEI1QACGEEKIRCiCEEEI0QgGEEEKIRiiAEEII0QgFEEIIIRqhAEIIIUQjFEAIIYRohAIIIYQQjVAAIYQQohEKIIQQQjRCAYQQQohGKIAQQgjRCAUQQgghGqEAQgghRCPacrkcFy5ceNz1IIQQ8hSRy+X4f+u6mhM1wf6EAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q.tree_styler(show_legend_type_labels=False, annotate_show_box_label=True)\\\n",
    "    .annotate(q.hasa('hgvs_gn:NC_045512.2:S:p.D614G'), box_label='S:D614G')\\\n",
    "    .annotate(q.hasa('hgvs_gn:NC_045512.2:ORF8:p.L84S'), box_label='ORF8:L84S')\\\n",
    "    .render(w=400)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "50d2fe20-04e7-4f5c-b364-15460edc40b2",
   "metadata": {},
   "source": [
    "### 4.2.7. Highlight lineages\n",
    "\n",
    "To highlight lineages first we show which lineages are available."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "7a1f5933-4a4d-4c46-810e-3c374e1169aa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "B.1       28\n",
       "AD.2      10\n",
       "A.1        3\n",
       "A          2\n",
       "A.2        2\n",
       "A.23.1     2\n",
       "A.2.2      1\n",
       "A.3        1\n",
       "B          1\n",
       "Name: Pangolin, dtype: int64"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q.toframe()['Pangolin'].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "883d0ca0-e552-4785-9dfc-f52fb2dadffc",
   "metadata": {},
   "source": [
    "We can query for samples that are of a specific lineage with `isa()`.\n",
    "\n",
    "You can use `regex=True` to use regular expressions in the lineage query (to capture that `A.1` is also an `A` and `B.1` is also a `B`)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "e5492906-a289-4bc5-b3d6-6421f219c348",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<MutationTreeSamplesQuery[selected=42% (21/50) samples, unknown=0% (0/50) samples]>"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q.isa('^A', regex=True, kind='dataframe', isa_column='Pangolin')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "81755894-1e47-4527-bae8-fd464aea8db8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<MutationTreeSamplesQuery[selected=58% (29/50) samples, unknown=0% (0/50) samples]>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q.isa('^B', regex=True, kind='dataframe', isa_column='Pangolin')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "10a35a2b-0ac3-45b4-8460-c2811ce6532a",
   "metadata": {},
   "source": [
    "Now lets combine with previous visualization to show these lineages in relation to mutations on a tree."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "6370ddb0-318f-41f2-a510-82e2524434f6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q.tree_styler(show_legend_type_labels=False, annotate_show_box_label=True,\n",
    "             legend_title='Lineage')\\\n",
    "    .annotate(q.hasa('hgvs_gn:NC_045512.2:S:p.D614G'), box_label='S:D614G')\\\n",
    "    .annotate(q.hasa('hgvs_gn:NC_045512.2:ORF8:p.L84S'), box_label='ORF8:L84S')\\\n",
    "    .highlight(q.isa('^A', regex=True, kind='dataframe', isa_column='Pangolin'), legend_label='A')\\\n",
    "    .highlight(q.isa('^B', regex=True, kind='dataframe', isa_column='Pangolin'), legend_label='B')\\\n",
    "    .render(w=400)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cde349bf-f569-4bd1-9420-3b5744e36076",
   "metadata": {},
   "source": [
    "### 4.2.8. Show summary of mutations for a lineage\n",
    "\n",
    "Let's show a summary of mutations for lineage `AD.2`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "e924f140-83cd-4337-b580-4662330c5403",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Sequence</th>\n",
       "      <th>Position</th>\n",
       "      <th>Deletion</th>\n",
       "      <th>Insertion</th>\n",
       "      <th>Type</th>\n",
       "      <th>Count</th>\n",
       "      <th>Unknown Count</th>\n",
       "      <th>Present and Unknown Count</th>\n",
       "      <th>Total</th>\n",
       "      <th>Percent</th>\n",
       "      <th>...</th>\n",
       "      <th>Gene_Name</th>\n",
       "      <th>Gene_ID</th>\n",
       "      <th>Feature_Type</th>\n",
       "      <th>Transcript_BioType</th>\n",
       "      <th>HGVS.c</th>\n",
       "      <th>HGVS.p</th>\n",
       "      <th>ID_HGVS.c</th>\n",
       "      <th>ID_HGVS.p</th>\n",
       "      <th>ID_HGVS_GN.c</th>\n",
       "      <th>ID_HGVS_GN.p</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mutation</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>NC_045512.2:29227:G:T</th>\n",
       "      <td>NC_045512.2</td>\n",
       "      <td>29227</td>\n",
       "      <td>G</td>\n",
       "      <td>T</td>\n",
       "      <td>SNP</td>\n",
       "      <td>10</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>10</td>\n",
       "      <td>100.0</td>\n",
       "      <td>...</td>\n",
       "      <td>N</td>\n",
       "      <td>GU280_gp10</td>\n",
       "      <td>transcript</td>\n",
       "      <td>protein_coding</td>\n",
       "      <td>c.954G&gt;T</td>\n",
       "      <td>p.S318S</td>\n",
       "      <td>hgvs:NC_045512.2:GU280_gp10:c.954G&gt;T</td>\n",
       "      <td>hgvs:NC_045512.2:GU280_gp10:p.S318S</td>\n",
       "      <td>hgvs_gn:NC_045512.2:N:c.954G&gt;T</td>\n",
       "      <td>hgvs_gn:NC_045512.2:N:p.S318S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NC_045512.2:241:C:T</th>\n",
       "      <td>NC_045512.2</td>\n",
       "      <td>241</td>\n",
       "      <td>C</td>\n",
       "      <td>T</td>\n",
       "      <td>SNP</td>\n",
       "      <td>10</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>10</td>\n",
       "      <td>100.0</td>\n",
       "      <td>...</td>\n",
       "      <td>CHR_START-ORF1ab</td>\n",
       "      <td>CHR_START-GU280_gp01</td>\n",
       "      <td>intergenic_region</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>n.241C&gt;T</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>hgvs:NC_045512.2:n.241C&gt;T</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>hgvs_gn:NC_045512.2:n.241C&gt;T</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NC_045512.2:29771:A:G</th>\n",
       "      <td>NC_045512.2</td>\n",
       "      <td>29771</td>\n",
       "      <td>A</td>\n",
       "      <td>G</td>\n",
       "      <td>SNP</td>\n",
       "      <td>10</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>10</td>\n",
       "      <td>100.0</td>\n",
       "      <td>...</td>\n",
       "      <td>ORF10-CHR_END</td>\n",
       "      <td>GU280_gp11-CHR_END</td>\n",
       "      <td>intergenic_region</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>n.29771A&gt;G</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>hgvs:NC_045512.2:n.29771A&gt;G</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>hgvs_gn:NC_045512.2:n.29771A&gt;G</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NC_045512.2:3037:C:T</th>\n",
       "      <td>NC_045512.2</td>\n",
       "      <td>3037</td>\n",
       "      <td>C</td>\n",
       "      <td>T</td>\n",
       "      <td>SNP</td>\n",
       "      <td>10</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>10</td>\n",
       "      <td>100.0</td>\n",
       "      <td>...</td>\n",
       "      <td>ORF1ab</td>\n",
       "      <td>GU280_gp01</td>\n",
       "      <td>transcript</td>\n",
       "      <td>protein_coding</td>\n",
       "      <td>c.2772C&gt;T</td>\n",
       "      <td>p.F924F</td>\n",
       "      <td>hgvs:NC_045512.2:GU280_gp01:c.2772C&gt;T</td>\n",
       "      <td>hgvs:NC_045512.2:GU280_gp01:p.F924F</td>\n",
       "      <td>hgvs_gn:NC_045512.2:ORF1ab:c.2772C&gt;T</td>\n",
       "      <td>hgvs_gn:NC_045512.2:ORF1ab:p.F924F</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NC_045512.2:5622:C:T</th>\n",
       "      <td>NC_045512.2</td>\n",
       "      <td>5622</td>\n",
       "      <td>C</td>\n",
       "      <td>T</td>\n",
       "      <td>SNP</td>\n",
       "      <td>10</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>10</td>\n",
       "      <td>100.0</td>\n",
       "      <td>...</td>\n",
       "      <td>ORF1ab</td>\n",
       "      <td>GU280_gp01</td>\n",
       "      <td>transcript</td>\n",
       "      <td>protein_coding</td>\n",
       "      <td>c.5357C&gt;T</td>\n",
       "      <td>p.P1786L</td>\n",
       "      <td>hgvs:NC_045512.2:GU280_gp01:c.5357C&gt;T</td>\n",
       "      <td>hgvs:NC_045512.2:GU280_gp01:p.P1786L</td>\n",
       "      <td>hgvs_gn:NC_045512.2:ORF1ab:c.5357C&gt;T</td>\n",
       "      <td>hgvs_gn:NC_045512.2:ORF1ab:p.P1786L</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                          Sequence  Position Deletion Insertion Type  Count  \\\n",
       "Mutation                                                                      \n",
       "NC_045512.2:29227:G:T  NC_045512.2     29227        G         T  SNP     10   \n",
       "NC_045512.2:241:C:T    NC_045512.2       241        C         T  SNP     10   \n",
       "NC_045512.2:29771:A:G  NC_045512.2     29771        A         G  SNP     10   \n",
       "NC_045512.2:3037:C:T   NC_045512.2      3037        C         T  SNP     10   \n",
       "NC_045512.2:5622:C:T   NC_045512.2      5622        C         T  SNP     10   \n",
       "\n",
       "                      Unknown Count Present and Unknown Count  Total  Percent  \\\n",
       "Mutation                                                                        \n",
       "NC_045512.2:29227:G:T          <NA>                      <NA>     10    100.0   \n",
       "NC_045512.2:241:C:T            <NA>                      <NA>     10    100.0   \n",
       "NC_045512.2:29771:A:G          <NA>                      <NA>     10    100.0   \n",
       "NC_045512.2:3037:C:T           <NA>                      <NA>     10    100.0   \n",
       "NC_045512.2:5622:C:T           <NA>                      <NA>     10    100.0   \n",
       "\n",
       "                       ...         Gene_Name               Gene_ID  \\\n",
       "Mutation               ...                                           \n",
       "NC_045512.2:29227:G:T  ...                 N            GU280_gp10   \n",
       "NC_045512.2:241:C:T    ...  CHR_START-ORF1ab  CHR_START-GU280_gp01   \n",
       "NC_045512.2:29771:A:G  ...     ORF10-CHR_END    GU280_gp11-CHR_END   \n",
       "NC_045512.2:3037:C:T   ...            ORF1ab            GU280_gp01   \n",
       "NC_045512.2:5622:C:T   ...            ORF1ab            GU280_gp01   \n",
       "\n",
       "                            Feature_Type Transcript_BioType      HGVS.c  \\\n",
       "Mutation                                                                  \n",
       "NC_045512.2:29227:G:T         transcript     protein_coding    c.954G>T   \n",
       "NC_045512.2:241:C:T    intergenic_region               <NA>    n.241C>T   \n",
       "NC_045512.2:29771:A:G  intergenic_region               <NA>  n.29771A>G   \n",
       "NC_045512.2:3037:C:T          transcript     protein_coding   c.2772C>T   \n",
       "NC_045512.2:5622:C:T          transcript     protein_coding   c.5357C>T   \n",
       "\n",
       "                         HGVS.p                              ID_HGVS.c  \\\n",
       "Mutation                                                                 \n",
       "NC_045512.2:29227:G:T   p.S318S   hgvs:NC_045512.2:GU280_gp10:c.954G>T   \n",
       "NC_045512.2:241:C:T        <NA>              hgvs:NC_045512.2:n.241C>T   \n",
       "NC_045512.2:29771:A:G      <NA>            hgvs:NC_045512.2:n.29771A>G   \n",
       "NC_045512.2:3037:C:T    p.F924F  hgvs:NC_045512.2:GU280_gp01:c.2772C>T   \n",
       "NC_045512.2:5622:C:T   p.P1786L  hgvs:NC_045512.2:GU280_gp01:c.5357C>T   \n",
       "\n",
       "                                                  ID_HGVS.p  \\\n",
       "Mutation                                                      \n",
       "NC_045512.2:29227:G:T   hgvs:NC_045512.2:GU280_gp10:p.S318S   \n",
       "NC_045512.2:241:C:T                                    <NA>   \n",
       "NC_045512.2:29771:A:G                                  <NA>   \n",
       "NC_045512.2:3037:C:T    hgvs:NC_045512.2:GU280_gp01:p.F924F   \n",
       "NC_045512.2:5622:C:T   hgvs:NC_045512.2:GU280_gp01:p.P1786L   \n",
       "\n",
       "                                               ID_HGVS_GN.c  \\\n",
       "Mutation                                                      \n",
       "NC_045512.2:29227:G:T        hgvs_gn:NC_045512.2:N:c.954G>T   \n",
       "NC_045512.2:241:C:T            hgvs_gn:NC_045512.2:n.241C>T   \n",
       "NC_045512.2:29771:A:G        hgvs_gn:NC_045512.2:n.29771A>G   \n",
       "NC_045512.2:3037:C:T   hgvs_gn:NC_045512.2:ORF1ab:c.2772C>T   \n",
       "NC_045512.2:5622:C:T   hgvs_gn:NC_045512.2:ORF1ab:c.5357C>T   \n",
       "\n",
       "                                              ID_HGVS_GN.p  \n",
       "Mutation                                                    \n",
       "NC_045512.2:29227:G:T        hgvs_gn:NC_045512.2:N:p.S318S  \n",
       "NC_045512.2:241:C:T                                   <NA>  \n",
       "NC_045512.2:29771:A:G                                 <NA>  \n",
       "NC_045512.2:3037:C:T    hgvs_gn:NC_045512.2:ORF1ab:p.F924F  \n",
       "NC_045512.2:5622:C:T   hgvs_gn:NC_045512.2:ORF1ab:p.P1786L  \n",
       "\n",
       "[5 rows x 24 columns]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q.isa('AD.2', kind='dataframe', isa_column='Pangolin')\\\n",
    " .features_summary()\\\n",
    " .sort_values('Count', ascending=False).head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1be21794-be9b-4846-b1c8-7578b925273f",
   "metadata": {},
   "source": [
    "### 4.2.9. Unique features\n",
    "\n",
    "We can also produce a table of unique features found only in lineage `AD.2` (out of everything in our index)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "b08a318c-2c8a-4679-95c7-dd652004ab78",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Sequence</th>\n",
       "      <th>Position</th>\n",
       "      <th>Deletion</th>\n",
       "      <th>Insertion</th>\n",
       "      <th>Type</th>\n",
       "      <th>Count</th>\n",
       "      <th>Unknown Count</th>\n",
       "      <th>Present and Unknown Count</th>\n",
       "      <th>Total</th>\n",
       "      <th>Percent</th>\n",
       "      <th>...</th>\n",
       "      <th>Gene_Name</th>\n",
       "      <th>Gene_ID</th>\n",
       "      <th>Feature_Type</th>\n",
       "      <th>Transcript_BioType</th>\n",
       "      <th>HGVS.c</th>\n",
       "      <th>HGVS.p</th>\n",
       "      <th>ID_HGVS.c</th>\n",
       "      <th>ID_HGVS.p</th>\n",
       "      <th>ID_HGVS_GN.c</th>\n",
       "      <th>ID_HGVS_GN.p</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mutation</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>NC_045512.2:3256:T:C</th>\n",
       "      <td>NC_045512.2</td>\n",
       "      <td>3256</td>\n",
       "      <td>T</td>\n",
       "      <td>C</td>\n",
       "      <td>SNP</td>\n",
       "      <td>10</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>10</td>\n",
       "      <td>100.0</td>\n",
       "      <td>...</td>\n",
       "      <td>ORF1ab</td>\n",
       "      <td>GU280_gp01</td>\n",
       "      <td>transcript</td>\n",
       "      <td>protein_coding</td>\n",
       "      <td>c.2991T&gt;C</td>\n",
       "      <td>p.N997N</td>\n",
       "      <td>hgvs:NC_045512.2:GU280_gp01:c.2991T&gt;C</td>\n",
       "      <td>hgvs:NC_045512.2:GU280_gp01:p.N997N</td>\n",
       "      <td>hgvs_gn:NC_045512.2:ORF1ab:c.2991T&gt;C</td>\n",
       "      <td>hgvs_gn:NC_045512.2:ORF1ab:p.N997N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NC_045512.2:19718:C:T</th>\n",
       "      <td>NC_045512.2</td>\n",
       "      <td>19718</td>\n",
       "      <td>C</td>\n",
       "      <td>T</td>\n",
       "      <td>SNP</td>\n",
       "      <td>10</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>10</td>\n",
       "      <td>100.0</td>\n",
       "      <td>...</td>\n",
       "      <td>ORF1ab</td>\n",
       "      <td>GU280_gp01</td>\n",
       "      <td>transcript</td>\n",
       "      <td>protein_coding</td>\n",
       "      <td>c.19454C&gt;T</td>\n",
       "      <td>p.T6485I</td>\n",
       "      <td>hgvs:NC_045512.2:GU280_gp01:c.19454C&gt;T</td>\n",
       "      <td>hgvs:NC_045512.2:GU280_gp01:p.T6485I</td>\n",
       "      <td>hgvs_gn:NC_045512.2:ORF1ab:c.19454C&gt;T</td>\n",
       "      <td>hgvs_gn:NC_045512.2:ORF1ab:p.T6485I</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NC_045512.2:5622:C:T</th>\n",
       "      <td>NC_045512.2</td>\n",
       "      <td>5622</td>\n",
       "      <td>C</td>\n",
       "      <td>T</td>\n",
       "      <td>SNP</td>\n",
       "      <td>10</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>10</td>\n",
       "      <td>100.0</td>\n",
       "      <td>...</td>\n",
       "      <td>ORF1ab</td>\n",
       "      <td>GU280_gp01</td>\n",
       "      <td>transcript</td>\n",
       "      <td>protein_coding</td>\n",
       "      <td>c.5357C&gt;T</td>\n",
       "      <td>p.P1786L</td>\n",
       "      <td>hgvs:NC_045512.2:GU280_gp01:c.5357C&gt;T</td>\n",
       "      <td>hgvs:NC_045512.2:GU280_gp01:p.P1786L</td>\n",
       "      <td>hgvs_gn:NC_045512.2:ORF1ab:c.5357C&gt;T</td>\n",
       "      <td>hgvs_gn:NC_045512.2:ORF1ab:p.P1786L</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NC_045512.2:14202:G:T</th>\n",
       "      <td>NC_045512.2</td>\n",
       "      <td>14202</td>\n",
       "      <td>G</td>\n",
       "      <td>T</td>\n",
       "      <td>SNP</td>\n",
       "      <td>10</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>10</td>\n",
       "      <td>100.0</td>\n",
       "      <td>...</td>\n",
       "      <td>ORF1ab</td>\n",
       "      <td>GU280_gp01</td>\n",
       "      <td>transcript</td>\n",
       "      <td>protein_coding</td>\n",
       "      <td>c.13938G&gt;T</td>\n",
       "      <td>p.E4646D</td>\n",
       "      <td>hgvs:NC_045512.2:GU280_gp01:c.13938G&gt;T</td>\n",
       "      <td>hgvs:NC_045512.2:GU280_gp01:p.E4646D</td>\n",
       "      <td>hgvs_gn:NC_045512.2:ORF1ab:c.13938G&gt;T</td>\n",
       "      <td>hgvs_gn:NC_045512.2:ORF1ab:p.E4646D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NC_045512.2:1163:A:T</th>\n",
       "      <td>NC_045512.2</td>\n",
       "      <td>1163</td>\n",
       "      <td>A</td>\n",
       "      <td>T</td>\n",
       "      <td>SNP</td>\n",
       "      <td>10</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>10</td>\n",
       "      <td>100.0</td>\n",
       "      <td>...</td>\n",
       "      <td>ORF1ab</td>\n",
       "      <td>GU280_gp01</td>\n",
       "      <td>transcript</td>\n",
       "      <td>protein_coding</td>\n",
       "      <td>c.898A&gt;T</td>\n",
       "      <td>p.I300F</td>\n",
       "      <td>hgvs:NC_045512.2:GU280_gp01:c.898A&gt;T</td>\n",
       "      <td>hgvs:NC_045512.2:GU280_gp01:p.I300F</td>\n",
       "      <td>hgvs_gn:NC_045512.2:ORF1ab:c.898A&gt;T</td>\n",
       "      <td>hgvs_gn:NC_045512.2:ORF1ab:p.I300F</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                          Sequence  Position Deletion Insertion Type  Count  \\\n",
       "Mutation                                                                      \n",
       "NC_045512.2:3256:T:C   NC_045512.2      3256        T         C  SNP     10   \n",
       "NC_045512.2:19718:C:T  NC_045512.2     19718        C         T  SNP     10   \n",
       "NC_045512.2:5622:C:T   NC_045512.2      5622        C         T  SNP     10   \n",
       "NC_045512.2:14202:G:T  NC_045512.2     14202        G         T  SNP     10   \n",
       "NC_045512.2:1163:A:T   NC_045512.2      1163        A         T  SNP     10   \n",
       "\n",
       "                      Unknown Count Present and Unknown Count  Total  Percent  \\\n",
       "Mutation                                                                        \n",
       "NC_045512.2:3256:T:C           <NA>                      <NA>     10    100.0   \n",
       "NC_045512.2:19718:C:T          <NA>                      <NA>     10    100.0   \n",
       "NC_045512.2:5622:C:T           <NA>                      <NA>     10    100.0   \n",
       "NC_045512.2:14202:G:T          <NA>                      <NA>     10    100.0   \n",
       "NC_045512.2:1163:A:T           <NA>                      <NA>     10    100.0   \n",
       "\n",
       "                       ... Gene_Name     Gene_ID Feature_Type  \\\n",
       "Mutation               ...                                      \n",
       "NC_045512.2:3256:T:C   ...    ORF1ab  GU280_gp01   transcript   \n",
       "NC_045512.2:19718:C:T  ...    ORF1ab  GU280_gp01   transcript   \n",
       "NC_045512.2:5622:C:T   ...    ORF1ab  GU280_gp01   transcript   \n",
       "NC_045512.2:14202:G:T  ...    ORF1ab  GU280_gp01   transcript   \n",
       "NC_045512.2:1163:A:T   ...    ORF1ab  GU280_gp01   transcript   \n",
       "\n",
       "                      Transcript_BioType      HGVS.c    HGVS.p  \\\n",
       "Mutation                                                         \n",
       "NC_045512.2:3256:T:C      protein_coding   c.2991T>C   p.N997N   \n",
       "NC_045512.2:19718:C:T     protein_coding  c.19454C>T  p.T6485I   \n",
       "NC_045512.2:5622:C:T      protein_coding   c.5357C>T  p.P1786L   \n",
       "NC_045512.2:14202:G:T     protein_coding  c.13938G>T  p.E4646D   \n",
       "NC_045512.2:1163:A:T      protein_coding    c.898A>T   p.I300F   \n",
       "\n",
       "                                                    ID_HGVS.c  \\\n",
       "Mutation                                                        \n",
       "NC_045512.2:3256:T:C    hgvs:NC_045512.2:GU280_gp01:c.2991T>C   \n",
       "NC_045512.2:19718:C:T  hgvs:NC_045512.2:GU280_gp01:c.19454C>T   \n",
       "NC_045512.2:5622:C:T    hgvs:NC_045512.2:GU280_gp01:c.5357C>T   \n",
       "NC_045512.2:14202:G:T  hgvs:NC_045512.2:GU280_gp01:c.13938G>T   \n",
       "NC_045512.2:1163:A:T     hgvs:NC_045512.2:GU280_gp01:c.898A>T   \n",
       "\n",
       "                                                  ID_HGVS.p  \\\n",
       "Mutation                                                      \n",
       "NC_045512.2:3256:T:C    hgvs:NC_045512.2:GU280_gp01:p.N997N   \n",
       "NC_045512.2:19718:C:T  hgvs:NC_045512.2:GU280_gp01:p.T6485I   \n",
       "NC_045512.2:5622:C:T   hgvs:NC_045512.2:GU280_gp01:p.P1786L   \n",
       "NC_045512.2:14202:G:T  hgvs:NC_045512.2:GU280_gp01:p.E4646D   \n",
       "NC_045512.2:1163:A:T    hgvs:NC_045512.2:GU280_gp01:p.I300F   \n",
       "\n",
       "                                                ID_HGVS_GN.c  \\\n",
       "Mutation                                                       \n",
       "NC_045512.2:3256:T:C    hgvs_gn:NC_045512.2:ORF1ab:c.2991T>C   \n",
       "NC_045512.2:19718:C:T  hgvs_gn:NC_045512.2:ORF1ab:c.19454C>T   \n",
       "NC_045512.2:5622:C:T    hgvs_gn:NC_045512.2:ORF1ab:c.5357C>T   \n",
       "NC_045512.2:14202:G:T  hgvs_gn:NC_045512.2:ORF1ab:c.13938G>T   \n",
       "NC_045512.2:1163:A:T     hgvs_gn:NC_045512.2:ORF1ab:c.898A>T   \n",
       "\n",
       "                                              ID_HGVS_GN.p  \n",
       "Mutation                                                    \n",
       "NC_045512.2:3256:T:C    hgvs_gn:NC_045512.2:ORF1ab:p.N997N  \n",
       "NC_045512.2:19718:C:T  hgvs_gn:NC_045512.2:ORF1ab:p.T6485I  \n",
       "NC_045512.2:5622:C:T   hgvs_gn:NC_045512.2:ORF1ab:p.P1786L  \n",
       "NC_045512.2:14202:G:T  hgvs_gn:NC_045512.2:ORF1ab:p.E4646D  \n",
       "NC_045512.2:1163:A:T    hgvs_gn:NC_045512.2:ORF1ab:p.I300F  \n",
       "\n",
       "[5 rows x 24 columns]"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "u_df = q.isa('AD.2', kind='dataframe', isa_column='Pangolin').features_summary(selection='unique')\n",
    "u_df.sort_values('Count', ascending=False).head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4592e72a-f283-4e9b-9dd6-a44bf5868cdb",
   "metadata": {},
   "source": [
    "### 4.2.10. Compare feature proportions among lineages\n",
    "\n",
    "Sometimes just showing the unique features for a lineage will miss some important information when some (but very few) genomes from other lineages have a feature. For example, if 100% of genomes in lineage `AD.2` have a mutation, but 1% of genomes in other lineages have this same mutation, it will not show up from the unique features analysis above, but still may be useful to know.\n",
    "\n",
    "In these situations, you can use the `q.features_comparison()` method to generate a table of each lineage (or other division of samples) along with the percent/proportion of every feature found in this lineage."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "38320ebe-c427-4ed5-b84b-45d647294849",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Sequence</th>\n",
       "      <th>Position</th>\n",
       "      <th>Deletion</th>\n",
       "      <th>Insertion</th>\n",
       "      <th>Type</th>\n",
       "      <th>Total</th>\n",
       "      <th>A_percent</th>\n",
       "      <th>A.1_percent</th>\n",
       "      <th>A.2_percent</th>\n",
       "      <th>A.2.2_percent</th>\n",
       "      <th>...</th>\n",
       "      <th>Gene_Name</th>\n",
       "      <th>Gene_ID</th>\n",
       "      <th>Feature_Type</th>\n",
       "      <th>Transcript_BioType</th>\n",
       "      <th>HGVS.c</th>\n",
       "      <th>HGVS.p</th>\n",
       "      <th>ID_HGVS.c</th>\n",
       "      <th>ID_HGVS.p</th>\n",
       "      <th>ID_HGVS_GN.c</th>\n",
       "      <th>ID_HGVS_GN.p</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mutation</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>NC_045512.2:18877:C:T</th>\n",
       "      <td>NC_045512.2</td>\n",
       "      <td>18877</td>\n",
       "      <td>C</td>\n",
       "      <td>T</td>\n",
       "      <td>SNP</td>\n",
       "      <td>50</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>ORF1ab</td>\n",
       "      <td>GU280_gp01</td>\n",
       "      <td>transcript</td>\n",
       "      <td>protein_coding</td>\n",
       "      <td>c.18613C&gt;T</td>\n",
       "      <td>p.L6205L</td>\n",
       "      <td>hgvs:NC_045512.2:GU280_gp01:c.18613C&gt;T</td>\n",
       "      <td>hgvs:NC_045512.2:GU280_gp01:p.L6205L</td>\n",
       "      <td>hgvs_gn:NC_045512.2:ORF1ab:c.18613C&gt;T</td>\n",
       "      <td>hgvs_gn:NC_045512.2:ORF1ab:p.L6205L</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NC_045512.2:29867:T:G</th>\n",
       "      <td>NC_045512.2</td>\n",
       "      <td>29867</td>\n",
       "      <td>T</td>\n",
       "      <td>G</td>\n",
       "      <td>SNP</td>\n",
       "      <td>50</td>\n",
       "      <td>50.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>ORF10-CHR_END</td>\n",
       "      <td>GU280_gp11-CHR_END</td>\n",
       "      <td>intergenic_region</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>n.29867T&gt;G</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>hgvs:NC_045512.2:n.29867T&gt;G</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>hgvs_gn:NC_045512.2:n.29867T&gt;G</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NC_045512.2:29614:C:T</th>\n",
       "      <td>NC_045512.2</td>\n",
       "      <td>29614</td>\n",
       "      <td>C</td>\n",
       "      <td>T</td>\n",
       "      <td>SNP</td>\n",
       "      <td>50</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>ORF10</td>\n",
       "      <td>GU280_gp11</td>\n",
       "      <td>transcript</td>\n",
       "      <td>protein_coding</td>\n",
       "      <td>c.57C&gt;T</td>\n",
       "      <td>p.C19C</td>\n",
       "      <td>hgvs:NC_045512.2:GU280_gp11:c.57C&gt;T</td>\n",
       "      <td>hgvs:NC_045512.2:GU280_gp11:p.C19C</td>\n",
       "      <td>hgvs_gn:NC_045512.2:ORF10:c.57C&gt;T</td>\n",
       "      <td>hgvs_gn:NC_045512.2:ORF10:p.C19C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NC_045512.2:2659:G:T</th>\n",
       "      <td>NC_045512.2</td>\n",
       "      <td>2659</td>\n",
       "      <td>G</td>\n",
       "      <td>T</td>\n",
       "      <td>SNP</td>\n",
       "      <td>50</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>ORF1ab</td>\n",
       "      <td>GU280_gp01</td>\n",
       "      <td>transcript</td>\n",
       "      <td>protein_coding</td>\n",
       "      <td>c.2394G&gt;T</td>\n",
       "      <td>p.K798N</td>\n",
       "      <td>hgvs:NC_045512.2:GU280_gp01:c.2394G&gt;T</td>\n",
       "      <td>hgvs:NC_045512.2:GU280_gp01:p.K798N</td>\n",
       "      <td>hgvs_gn:NC_045512.2:ORF1ab:c.2394G&gt;T</td>\n",
       "      <td>hgvs_gn:NC_045512.2:ORF1ab:p.K798N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NC_045512.2:27603:C:T</th>\n",
       "      <td>NC_045512.2</td>\n",
       "      <td>27603</td>\n",
       "      <td>C</td>\n",
       "      <td>T</td>\n",
       "      <td>SNP</td>\n",
       "      <td>50</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>ORF7a</td>\n",
       "      <td>GU280_gp07</td>\n",
       "      <td>transcript</td>\n",
       "      <td>protein_coding</td>\n",
       "      <td>c.210C&gt;T</td>\n",
       "      <td>p.G70G</td>\n",
       "      <td>hgvs:NC_045512.2:GU280_gp07:c.210C&gt;T</td>\n",
       "      <td>hgvs:NC_045512.2:GU280_gp07:p.G70G</td>\n",
       "      <td>hgvs_gn:NC_045512.2:ORF7a:c.210C&gt;T</td>\n",
       "      <td>hgvs_gn:NC_045512.2:ORF7a:p.G70G</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NC_045512.2:1123:A:G</th>\n",
       "      <td>NC_045512.2</td>\n",
       "      <td>1123</td>\n",
       "      <td>A</td>\n",
       "      <td>G</td>\n",
       "      <td>SNP</td>\n",
       "      <td>50</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>ORF1ab</td>\n",
       "      <td>GU280_gp01</td>\n",
       "      <td>transcript</td>\n",
       "      <td>protein_coding</td>\n",
       "      <td>c.858A&gt;G</td>\n",
       "      <td>p.P286P</td>\n",
       "      <td>hgvs:NC_045512.2:GU280_gp01:c.858A&gt;G</td>\n",
       "      <td>hgvs:NC_045512.2:GU280_gp01:p.P286P</td>\n",
       "      <td>hgvs_gn:NC_045512.2:ORF1ab:c.858A&gt;G</td>\n",
       "      <td>hgvs_gn:NC_045512.2:ORF1ab:p.P286P</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NC_045512.2:14408:C:T</th>\n",
       "      <td>NC_045512.2</td>\n",
       "      <td>14408</td>\n",
       "      <td>C</td>\n",
       "      <td>T</td>\n",
       "      <td>SNP</td>\n",
       "      <td>50</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>ORF1ab</td>\n",
       "      <td>GU280_gp01</td>\n",
       "      <td>transcript</td>\n",
       "      <td>protein_coding</td>\n",
       "      <td>c.14144C&gt;T</td>\n",
       "      <td>p.P4715L</td>\n",
       "      <td>hgvs:NC_045512.2:GU280_gp01:c.14144C&gt;T</td>\n",
       "      <td>hgvs:NC_045512.2:GU280_gp01:p.P4715L</td>\n",
       "      <td>hgvs_gn:NC_045512.2:ORF1ab:c.14144C&gt;T</td>\n",
       "      <td>hgvs_gn:NC_045512.2:ORF1ab:p.P4715L</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NC_045512.2:2189:C:T</th>\n",
       "      <td>NC_045512.2</td>\n",
       "      <td>2189</td>\n",
       "      <td>C</td>\n",
       "      <td>T</td>\n",
       "      <td>SNP</td>\n",
       "      <td>50</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>ORF1ab</td>\n",
       "      <td>GU280_gp01</td>\n",
       "      <td>transcript</td>\n",
       "      <td>protein_coding</td>\n",
       "      <td>c.1924C&gt;T</td>\n",
       "      <td>p.L642F</td>\n",
       "      <td>hgvs:NC_045512.2:GU280_gp01:c.1924C&gt;T</td>\n",
       "      <td>hgvs:NC_045512.2:GU280_gp01:p.L642F</td>\n",
       "      <td>hgvs_gn:NC_045512.2:ORF1ab:c.1924C&gt;T</td>\n",
       "      <td>hgvs_gn:NC_045512.2:ORF1ab:p.L642F</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NC_045512.2:22992:G:A</th>\n",
       "      <td>NC_045512.2</td>\n",
       "      <td>22992</td>\n",
       "      <td>G</td>\n",
       "      <td>A</td>\n",
       "      <td>SNP</td>\n",
       "      <td>50</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>S</td>\n",
       "      <td>GU280_gp02</td>\n",
       "      <td>transcript</td>\n",
       "      <td>protein_coding</td>\n",
       "      <td>c.1430G&gt;A</td>\n",
       "      <td>p.S477N</td>\n",
       "      <td>hgvs:NC_045512.2:GU280_gp02:c.1430G&gt;A</td>\n",
       "      <td>hgvs:NC_045512.2:GU280_gp02:p.S477N</td>\n",
       "      <td>hgvs_gn:NC_045512.2:S:c.1430G&gt;A</td>\n",
       "      <td>hgvs_gn:NC_045512.2:S:p.S477N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NC_045512.2:6040:C:T</th>\n",
       "      <td>NC_045512.2</td>\n",
       "      <td>6040</td>\n",
       "      <td>C</td>\n",
       "      <td>T</td>\n",
       "      <td>SNP</td>\n",
       "      <td>50</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>ORF1ab</td>\n",
       "      <td>GU280_gp01</td>\n",
       "      <td>transcript</td>\n",
       "      <td>protein_coding</td>\n",
       "      <td>c.5775C&gt;T</td>\n",
       "      <td>p.F1925F</td>\n",
       "      <td>hgvs:NC_045512.2:GU280_gp01:c.5775C&gt;T</td>\n",
       "      <td>hgvs:NC_045512.2:GU280_gp01:p.F1925F</td>\n",
       "      <td>hgvs_gn:NC_045512.2:ORF1ab:c.5775C&gt;T</td>\n",
       "      <td>hgvs_gn:NC_045512.2:ORF1ab:p.F1925F</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>288 rows × 54 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                          Sequence  Position Deletion Insertion Type  Total  \\\n",
       "Mutation                                                                      \n",
       "NC_045512.2:18877:C:T  NC_045512.2     18877        C         T  SNP     50   \n",
       "NC_045512.2:29867:T:G  NC_045512.2     29867        T         G  SNP     50   \n",
       "NC_045512.2:29614:C:T  NC_045512.2     29614        C         T  SNP     50   \n",
       "NC_045512.2:2659:G:T   NC_045512.2      2659        G         T  SNP     50   \n",
       "NC_045512.2:27603:C:T  NC_045512.2     27603        C         T  SNP     50   \n",
       "...                            ...       ...      ...       ...  ...    ...   \n",
       "NC_045512.2:1123:A:G   NC_045512.2      1123        A         G  SNP     50   \n",
       "NC_045512.2:14408:C:T  NC_045512.2     14408        C         T  SNP     50   \n",
       "NC_045512.2:2189:C:T   NC_045512.2      2189        C         T  SNP     50   \n",
       "NC_045512.2:22992:G:A  NC_045512.2     22992        G         A  SNP     50   \n",
       "NC_045512.2:6040:C:T   NC_045512.2      6040        C         T  SNP     50   \n",
       "\n",
       "                       A_percent  A.1_percent  A.2_percent  A.2.2_percent  \\\n",
       "Mutation                                                                    \n",
       "NC_045512.2:18877:C:T        0.0          0.0          0.0            0.0   \n",
       "NC_045512.2:29867:T:G       50.0          0.0          0.0            0.0   \n",
       "NC_045512.2:29614:C:T        0.0          0.0          0.0            0.0   \n",
       "NC_045512.2:2659:G:T         0.0          0.0          0.0            0.0   \n",
       "NC_045512.2:27603:C:T        0.0          0.0          0.0            0.0   \n",
       "...                          ...          ...          ...            ...   \n",
       "NC_045512.2:1123:A:G         0.0          0.0          0.0            0.0   \n",
       "NC_045512.2:14408:C:T        0.0          0.0          0.0            0.0   \n",
       "NC_045512.2:2189:C:T         0.0          0.0          0.0            0.0   \n",
       "NC_045512.2:22992:G:A        0.0          0.0          0.0            0.0   \n",
       "NC_045512.2:6040:C:T         0.0          0.0          0.0            0.0   \n",
       "\n",
       "                       ...      Gene_Name             Gene_ID  \\\n",
       "Mutation               ...                                      \n",
       "NC_045512.2:18877:C:T  ...         ORF1ab          GU280_gp01   \n",
       "NC_045512.2:29867:T:G  ...  ORF10-CHR_END  GU280_gp11-CHR_END   \n",
       "NC_045512.2:29614:C:T  ...          ORF10          GU280_gp11   \n",
       "NC_045512.2:2659:G:T   ...         ORF1ab          GU280_gp01   \n",
       "NC_045512.2:27603:C:T  ...          ORF7a          GU280_gp07   \n",
       "...                    ...            ...                 ...   \n",
       "NC_045512.2:1123:A:G   ...         ORF1ab          GU280_gp01   \n",
       "NC_045512.2:14408:C:T  ...         ORF1ab          GU280_gp01   \n",
       "NC_045512.2:2189:C:T   ...         ORF1ab          GU280_gp01   \n",
       "NC_045512.2:22992:G:A  ...              S          GU280_gp02   \n",
       "NC_045512.2:6040:C:T   ...         ORF1ab          GU280_gp01   \n",
       "\n",
       "                            Feature_Type  Transcript_BioType      HGVS.c  \\\n",
       "Mutation                                                                   \n",
       "NC_045512.2:18877:C:T         transcript      protein_coding  c.18613C>T   \n",
       "NC_045512.2:29867:T:G  intergenic_region                <NA>  n.29867T>G   \n",
       "NC_045512.2:29614:C:T         transcript      protein_coding     c.57C>T   \n",
       "NC_045512.2:2659:G:T          transcript      protein_coding   c.2394G>T   \n",
       "NC_045512.2:27603:C:T         transcript      protein_coding    c.210C>T   \n",
       "...                                  ...                 ...         ...   \n",
       "NC_045512.2:1123:A:G          transcript      protein_coding    c.858A>G   \n",
       "NC_045512.2:14408:C:T         transcript      protein_coding  c.14144C>T   \n",
       "NC_045512.2:2189:C:T          transcript      protein_coding   c.1924C>T   \n",
       "NC_045512.2:22992:G:A         transcript      protein_coding   c.1430G>A   \n",
       "NC_045512.2:6040:C:T          transcript      protein_coding   c.5775C>T   \n",
       "\n",
       "                         HGVS.p                               ID_HGVS.c  \\\n",
       "Mutation                                                                  \n",
       "NC_045512.2:18877:C:T  p.L6205L  hgvs:NC_045512.2:GU280_gp01:c.18613C>T   \n",
       "NC_045512.2:29867:T:G      <NA>             hgvs:NC_045512.2:n.29867T>G   \n",
       "NC_045512.2:29614:C:T    p.C19C     hgvs:NC_045512.2:GU280_gp11:c.57C>T   \n",
       "NC_045512.2:2659:G:T    p.K798N   hgvs:NC_045512.2:GU280_gp01:c.2394G>T   \n",
       "NC_045512.2:27603:C:T    p.G70G    hgvs:NC_045512.2:GU280_gp07:c.210C>T   \n",
       "...                         ...                                     ...   \n",
       "NC_045512.2:1123:A:G    p.P286P    hgvs:NC_045512.2:GU280_gp01:c.858A>G   \n",
       "NC_045512.2:14408:C:T  p.P4715L  hgvs:NC_045512.2:GU280_gp01:c.14144C>T   \n",
       "NC_045512.2:2189:C:T    p.L642F   hgvs:NC_045512.2:GU280_gp01:c.1924C>T   \n",
       "NC_045512.2:22992:G:A   p.S477N   hgvs:NC_045512.2:GU280_gp02:c.1430G>A   \n",
       "NC_045512.2:6040:C:T   p.F1925F   hgvs:NC_045512.2:GU280_gp01:c.5775C>T   \n",
       "\n",
       "                                                  ID_HGVS.p  \\\n",
       "Mutation                                                      \n",
       "NC_045512.2:18877:C:T  hgvs:NC_045512.2:GU280_gp01:p.L6205L   \n",
       "NC_045512.2:29867:T:G                                  <NA>   \n",
       "NC_045512.2:29614:C:T    hgvs:NC_045512.2:GU280_gp11:p.C19C   \n",
       "NC_045512.2:2659:G:T    hgvs:NC_045512.2:GU280_gp01:p.K798N   \n",
       "NC_045512.2:27603:C:T    hgvs:NC_045512.2:GU280_gp07:p.G70G   \n",
       "...                                                     ...   \n",
       "NC_045512.2:1123:A:G    hgvs:NC_045512.2:GU280_gp01:p.P286P   \n",
       "NC_045512.2:14408:C:T  hgvs:NC_045512.2:GU280_gp01:p.P4715L   \n",
       "NC_045512.2:2189:C:T    hgvs:NC_045512.2:GU280_gp01:p.L642F   \n",
       "NC_045512.2:22992:G:A   hgvs:NC_045512.2:GU280_gp02:p.S477N   \n",
       "NC_045512.2:6040:C:T   hgvs:NC_045512.2:GU280_gp01:p.F1925F   \n",
       "\n",
       "                                                ID_HGVS_GN.c  \\\n",
       "Mutation                                                       \n",
       "NC_045512.2:18877:C:T  hgvs_gn:NC_045512.2:ORF1ab:c.18613C>T   \n",
       "NC_045512.2:29867:T:G         hgvs_gn:NC_045512.2:n.29867T>G   \n",
       "NC_045512.2:29614:C:T      hgvs_gn:NC_045512.2:ORF10:c.57C>T   \n",
       "NC_045512.2:2659:G:T    hgvs_gn:NC_045512.2:ORF1ab:c.2394G>T   \n",
       "NC_045512.2:27603:C:T     hgvs_gn:NC_045512.2:ORF7a:c.210C>T   \n",
       "...                                                      ...   \n",
       "NC_045512.2:1123:A:G     hgvs_gn:NC_045512.2:ORF1ab:c.858A>G   \n",
       "NC_045512.2:14408:C:T  hgvs_gn:NC_045512.2:ORF1ab:c.14144C>T   \n",
       "NC_045512.2:2189:C:T    hgvs_gn:NC_045512.2:ORF1ab:c.1924C>T   \n",
       "NC_045512.2:22992:G:A        hgvs_gn:NC_045512.2:S:c.1430G>A   \n",
       "NC_045512.2:6040:C:T    hgvs_gn:NC_045512.2:ORF1ab:c.5775C>T   \n",
       "\n",
       "                                              ID_HGVS_GN.p  \n",
       "Mutation                                                    \n",
       "NC_045512.2:18877:C:T  hgvs_gn:NC_045512.2:ORF1ab:p.L6205L  \n",
       "NC_045512.2:29867:T:G                                 <NA>  \n",
       "NC_045512.2:29614:C:T     hgvs_gn:NC_045512.2:ORF10:p.C19C  \n",
       "NC_045512.2:2659:G:T    hgvs_gn:NC_045512.2:ORF1ab:p.K798N  \n",
       "NC_045512.2:27603:C:T     hgvs_gn:NC_045512.2:ORF7a:p.G70G  \n",
       "...                                                    ...  \n",
       "NC_045512.2:1123:A:G    hgvs_gn:NC_045512.2:ORF1ab:p.P286P  \n",
       "NC_045512.2:14408:C:T  hgvs_gn:NC_045512.2:ORF1ab:p.P4715L  \n",
       "NC_045512.2:2189:C:T    hgvs_gn:NC_045512.2:ORF1ab:p.L642F  \n",
       "NC_045512.2:22992:G:A        hgvs_gn:NC_045512.2:S:p.S477N  \n",
       "NC_045512.2:6040:C:T   hgvs_gn:NC_045512.2:ORF1ab:p.F1925F  \n",
       "\n",
       "[288 rows x 54 columns]"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "comparison_df = q.features_comparison(sample_categories='Pangolin',\n",
    "                      categories_kind='dataframe',\n",
    "                      kind='mutations',\n",
    "                      unit='percent'\n",
    "                      )\n",
    "comparison_df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "925830b4-1474-4f65-ae37-27f453685fb6",
   "metadata": {},
   "source": [
    "#### Parameters\n",
    "\n",
    "The parameters for this command are:\n",
    "\n",
    "* **sample_categories='Pangolin'**: The column name (`Pangolin`) in the dataframe to define the sets of genomic samples to compare.\n",
    "* **categories_kind='dataframe'**: The kind of categories to compare (`dataframe` means that we are defining sets of samples based on a column name in the attached metadata dataframe. Alternative methods is to pass sample queries to define sets of samples).\n",
    "* **kind='mutations'**: The kind of features to compare (can be `mutations` or `mlst`).\n",
    "* **unit='percent'**: The kind of unit to use (can be `percent`, `proportion`, or `count`).\n",
    "* There are others and I would recommend referring to the Python API documentation for more details (e.g., run `?q.features_comparison` in Jupyter).\n",
    "\n",
    "#### Output\n",
    "\n",
    "The output of this command consists of a dataframe where rows are the features and columns (like `B.1_percent`, `AD.2_percent`, ..., `B.1_total`, `AD.2_total`) list the percent of each mutation for the given lineages (`B.1`, `AD.2`) as well as total samples in each lineage."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "6b2b1248-8e80-4a95-8e8b-6bbabee214a1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID_HGVS_GN.p</th>\n",
       "      <th>B.1_percent</th>\n",
       "      <th>AD.2_percent</th>\n",
       "      <th>B.1_total</th>\n",
       "      <th>AD.2_total</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mutation</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>NC_045512.2:22388:C:T</th>\n",
       "      <td>hgvs_gn:NC_045512.2:S:p.L276L</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>100.0</td>\n",
       "      <td>28</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NC_045512.2:23403:A:G</th>\n",
       "      <td>hgvs_gn:NC_045512.2:S:p.D614G</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>100.0</td>\n",
       "      <td>28</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NC_045512.2:26060:C:T</th>\n",
       "      <td>hgvs_gn:NC_045512.2:ORF3a:p.T223I</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>100.0</td>\n",
       "      <td>28</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NC_045512.2:19718:C:T</th>\n",
       "      <td>hgvs_gn:NC_045512.2:ORF1ab:p.T6485I</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>100.0</td>\n",
       "      <td>28</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NC_045512.2:14408:C:T</th>\n",
       "      <td>hgvs_gn:NC_045512.2:ORF1ab:p.P4715L</td>\n",
       "      <td>85.714286</td>\n",
       "      <td>100.0</td>\n",
       "      <td>28</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NC_045512.2:29742:G:A</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>28</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NC_045512.2:203:C:T</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3.571429</td>\n",
       "      <td>0.0</td>\n",
       "      <td>28</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NC_045512.2:29737:GCCACGCGGAGTACGATCGAGTGT:G</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3.571429</td>\n",
       "      <td>0.0</td>\n",
       "      <td>28</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NC_045512.2:29540:G:A</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3.571429</td>\n",
       "      <td>0.0</td>\n",
       "      <td>28</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NC_045512.2:29734:G:C</th>\n",
       "      <td>NaN</td>\n",
       "      <td>7.142857</td>\n",
       "      <td>0.0</td>\n",
       "      <td>28</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>288 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                                     ID_HGVS_GN.p  \\\n",
       "Mutation                                                                            \n",
       "NC_045512.2:22388:C:T                               hgvs_gn:NC_045512.2:S:p.L276L   \n",
       "NC_045512.2:23403:A:G                               hgvs_gn:NC_045512.2:S:p.D614G   \n",
       "NC_045512.2:26060:C:T                           hgvs_gn:NC_045512.2:ORF3a:p.T223I   \n",
       "NC_045512.2:19718:C:T                         hgvs_gn:NC_045512.2:ORF1ab:p.T6485I   \n",
       "NC_045512.2:14408:C:T                         hgvs_gn:NC_045512.2:ORF1ab:p.P4715L   \n",
       "...                                                                           ...   \n",
       "NC_045512.2:29742:G:A                                                         NaN   \n",
       "NC_045512.2:203:C:T                                                           NaN   \n",
       "NC_045512.2:29737:GCCACGCGGAGTACGATCGAGTGT:G                                  NaN   \n",
       "NC_045512.2:29540:G:A                                                         NaN   \n",
       "NC_045512.2:29734:G:C                                                         NaN   \n",
       "\n",
       "                                              B.1_percent  AD.2_percent  \\\n",
       "Mutation                                                                  \n",
       "NC_045512.2:22388:C:T                            0.000000         100.0   \n",
       "NC_045512.2:23403:A:G                          100.000000         100.0   \n",
       "NC_045512.2:26060:C:T                            0.000000         100.0   \n",
       "NC_045512.2:19718:C:T                            0.000000         100.0   \n",
       "NC_045512.2:14408:C:T                           85.714286         100.0   \n",
       "...                                                   ...           ...   \n",
       "NC_045512.2:29742:G:A                            0.000000           0.0   \n",
       "NC_045512.2:203:C:T                              3.571429           0.0   \n",
       "NC_045512.2:29737:GCCACGCGGAGTACGATCGAGTGT:G     3.571429           0.0   \n",
       "NC_045512.2:29540:G:A                            3.571429           0.0   \n",
       "NC_045512.2:29734:G:C                            7.142857           0.0   \n",
       "\n",
       "                                              B.1_total  AD.2_total  \n",
       "Mutation                                                             \n",
       "NC_045512.2:22388:C:T                                28          10  \n",
       "NC_045512.2:23403:A:G                                28          10  \n",
       "NC_045512.2:26060:C:T                                28          10  \n",
       "NC_045512.2:19718:C:T                                28          10  \n",
       "NC_045512.2:14408:C:T                                28          10  \n",
       "...                                                 ...         ...  \n",
       "NC_045512.2:29742:G:A                                28          10  \n",
       "NC_045512.2:203:C:T                                  28          10  \n",
       "NC_045512.2:29737:GCCACGCGGAGTACGATCGAGTGT:G         28          10  \n",
       "NC_045512.2:29540:G:A                                28          10  \n",
       "NC_045512.2:29734:G:C                                28          10  \n",
       "\n",
       "[288 rows x 5 columns]"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "comparison_df[['ID_HGVS_GN.p', 'B.1_percent', 'AD.2_percent', 'B.1_total', 'AD.2_total']]\\\n",
    " .sort_values(['AD.2_percent', 'ID_HGVS_GN.p'], ascending=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "09df04f1-71ae-4005-a879-0c5d352926a0",
   "metadata": {},
   "source": [
    "For example, here you can see that the feature `S:p.L276L` is found in **100%** (out of 10 samples) of lineage **AD.2** and **0%** (out of 28 samples) in lineage **B.1**.\n",
    "\n",
    "You can even use this information to plot out the major differences in mutations between lineages."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "fa99b392-4f4e-4b37-98f5-e00830b5e996",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Feature')"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "comparison_diff_df = comparison_df.copy()\n",
    "\n",
    "# Add in column which defines the differences between percent of features in\n",
    "# the selected lineages\n",
    "comparison_diff_df['B.1_minus_AD.2_percent'] = comparison_diff_df['B.1_percent'] \\\n",
    "                                               - comparison_diff_df['AD.2_percent']\n",
    "\n",
    "# Use this difference column (B.1_minus_AD.2_percent) to sort features to compare\n",
    "comparison_diff_df = comparison_diff_df.sort_values(['B.1_minus_AD.2_percent', 'ID_HGVS_GN.p'],\n",
    "                                                    ascending=True)\n",
    "\n",
    "# Limit data to only those features where the difference \n",
    "# between lineages is greater than 10%\n",
    "comparison_diff_df = comparison_diff_df[\n",
    "    abs(comparison_diff_df['B.1_minus_AD.2_percent']) > 15][\n",
    "    ['ID_HGVS_GN.p', 'B.1_percent', 'AD.2_percent']]\n",
    "\n",
    "# Plot percent difference\n",
    "comparison_diff_df.set_index('ID_HGVS_GN.p').plot(kind='barh')\n",
    "plt.xlabel(f'Percent of samples with a particular feature', fontdict={'size': 14})\n",
    "plt.ylabel('Feature', fontdict={'size': 14})"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f37ce604-dc41-4c07-b832-414586937f55",
   "metadata": {},
   "source": [
    "This shows a plot of the percent of samples with particular features in a lineage. For exmaple, the top entry shows that the feature `ORF3a:p.Q57H` is found in ~35% of lineage `B.1` and 0% of lineage `AD.2`.\n",
    "\n",
    "I am comparing only two different lineages here (`B.1` and `AD.2`). I have sorted the data so that I display those features with the greatest difference in percent."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b30b6ed2-717e-4368-ac1d-5f825c70d43f",
   "metadata": {},
   "source": [
    "### 4.2.11. Build and visualize kmer tree\n",
    "\n",
    "We can also build a kmer-based tree (using the sourmash sketches). We can then visualize this tree and display similar to the mutation-based phylogenetic tree.\n",
    "\n",
    "First we create a query and build a kmer-tree with it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "73420fc7-711e-4730-a3de-3b6541f0be81",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<KmerTreeSamplesQuery[selected=100% (50/50) samples, unknown=0% (0/50) samples]>"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "kq = db.samples_query().join(\n",
    "    metadata_df, sample_names_column='Accession').build_tree(\n",
    "    kind='kmer', kmer_size=31)\n",
    "kq"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0722c60d-4616-495d-94c4-e99bf015830e",
   "metadata": {},
   "source": [
    "Now let's visualize this tree, showing the same mutations and lineage information as in (**4.2.7**)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "9db975ba-5f49-4198-88de-545b4755ec8e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "kq.tree_styler(show_legend_type_labels=False, annotate_show_box_label=True,\n",
    "             legend_title='Lineage')\\\n",
    "    .annotate(kq.hasa('hgvs_gn:NC_045512.2:S:p.D614G'), box_label='S:D614G')\\\n",
    "    .annotate(kq.hasa('hgvs_gn:NC_045512.2:ORF8:p.L84S'), box_label='ORF8:L84S')\\\n",
    "    .highlight(kq.isa('^A', regex=True, kind='dataframe', isa_column='Pangolin'), legend_label='A')\\\n",
    "    .highlight(kq.isa('^B', regex=True, kind='dataframe', isa_column='Pangolin'), legend_label='B')\\\n",
    "    .render(w=400)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b9cc8de5-2900-4d37-ab91-ffc00e27c555",
   "metadata": {},
   "source": [
    "*Note: with SARS-CoV-2 being such a small genome where most samples are very closely-related the kmer-based trees will likely not cluster genomes similarly to mutation-based trees (mutation-based trees would be prefered here, but kmer trees may be prefered for more distantly-related genomes).*"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a4590370-17ef-45b2-b564-02ec5b92128c",
   "metadata": {},
   "source": [
    "# 5. Finished\n",
    "\n",
    "You are now finished with this tutorial. You are awesome 😁❤️. Please feel free to leave issues on GitHub if you encounter any problems."
   ]
  }
 ],
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