{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "b900438d-7a82-46bc-82e5-f187e8e20d54",
   "metadata": {
    "tags": []
   },
   "source": [
    "# HETDEX Source Catalog 2: Catalog description and access"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "d6f7de4a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Required python moduldes for opening FITS files and plotting\n",
    "import numpy as np\n",
    "import os.path as op\n",
    "import os\n",
    "import glob\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib import gridspec\n",
    "\n",
    "from astropy.io import fits\n",
    "from astropy.table import Table, hstack\n",
    "import astropy.units as u\n",
    "from astropy.coordinates import SkyCoord\n",
    "from astropy.wcs import WCS\n",
    "\n",
    "from astropy.visualization import make_lupton_rgb, ZScaleInterval"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "51ed1c40",
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "cad9200a-654c-4be7-9f25-e321fb9ee316",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Download the catalog to your local directory if you are not on the HETDEX JupyterHub"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "5b10541a-9b9a-4a35-abe9-2b2ec47cb559",
   "metadata": {},
   "outputs": [],
   "source": [
    "# fill in the path to the HETDEX Source Catalog 2 files \n",
    "path_to_cat = '/home/jovyan/Hobby-Eberly-Public/HETDEX/pdr/pdr1/hetdex_source_catalog_2/'\n",
    "version = 'v1.5' # Change to latest version \n",
    "\n",
    "# switch to True if you are not on the HETDEX JupyterHub to download catalog\n",
    "remote = False\n",
    "\n",
    "if remote:\n",
    "    # Put catalog in desired working directory in directory hetdex_source_catalog_2\n",
    "    path_to_cat = \"/home/jovyan/work/pdr1/hetdex_source_catalog_2\"\n",
    "\n",
    "    os.makedirs(path_to_cat, exist_ok=True)\n",
    "    url = \"http://web.corral.tacc.utexas.edu/hetdex/HETDEX/pdr/pdr1/hetdex_source_catalog_2/\"\n",
    "\n",
    "    !wget -r -np -nd -A \"*.fits\" -P \"$path_to_cat\" \"$url\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6ee0ab2c-0ea6-492d-abcf-3b3963f37fff",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true,
    "tags": []
   },
   "source": [
    "## Catalog Organization\n",
    "\n",
    "Two catalogs make up HETDEX Source Catalog 2:\n",
    "    \n",
    "    1. The Source Observation Table: hetdex_sc2_vX.dat/.fits\n",
    "       With SPECTRA arrays included: hetdex_sc2_spec_vX.fits\n",
    "       \n",
    "        One row per source observation. The table provides basic coordinates/redshift/source information for each observation of a unique astornomical source. The larger file hetdex_sc2_spec_vX.fits contains the same info from the first table plus addition data units of spectral array data.\n",
    "        \n",
    "    2. The Detection Information Table: hetdex_sc2_detinfo_vX.fits\n",
    "        One row per line or continuum detection. Bright sources can be comprised of multiple line or continuum emission. This catalog provides specific detection information such as line parameter info (S/N, line flux, line width), observational data and instrument details."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "546db53f-8f43-43ef-96b2-e2021994b47f",
   "metadata": {},
   "source": [
    "## How to Open the Source Observation Table without Spectra"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b608f9ab-0aec-4e61-8ae5-1f893843de79",
   "metadata": {},
   "source": [
    "Multiple formats are provided for the source table."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "79b94845-32d3-4762-80c2-7017460ffe3b",
   "metadata": {},
   "outputs": [],
   "source": [
    "source_table = Table.read(op.join( path_to_cat, 'hetdex_sc2_{}.fits'.format(version) ) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "7cba7760-6499-433c-9db1-1955317eb4b6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1,107,763 rows\n",
      "\n",
      "source_name               |S26     None                 HETDEX IAU designation\n",
      "source_id                 >i8      None                 HETDEX Source Identifier\n",
      "shotid                    >i8      None                 integer represent observation ID: int( date+obsid)\n",
      "ifuslot                   |S3      None                 string identifier of IFU location in focal plane\n",
      "RA                        >f4      deg                  source_id right ascension (ICRS deg)\n",
      "DEC                       >f4      deg                  source_id declination (ICRS deg)\n",
      "RA_det                    >f4      deg                  detectid right ascension (ICRS deg)\n",
      "DEC_det                   >f4      deg                  detectid declination (ICRS deg)\n",
      "gmag                      >f4      mag                  sdss-g magnitude measured in HETDEX spectrum\n",
      "Av                        >f4      mag                  applied extinction correction in V band\n",
      "z_hetdex                  >f4      None                 HETDEX spectroscopic redshift\n",
      "z_hetdex_src              |S8      None                 HETDEX spectroscopic redshift source\n",
      "z_hetdex_conf             >f4      None                 0 to 1 confidence HETDEX spectroscopic redshift source\n",
      "source_type               |S10     None                 options are 'star', 'lae', 'agn', 'lzg', 'oii', 'none'\n",
      "detectid                  >i8      None                 emission line or detection ID\n",
      "field                     |S12     None                 field ID: cosmos, goods-n, dex-fall, dex-spring, nep, ssa22\n",
      "flux                      >f4      1e-17 erg / (s cm2)  extinction corrected line flux at \"wave\"\n",
      "flux_err                  >f4      1e-17 erg / (s cm2)  mcmc error in extinction corrected line flux\n",
      "flux_aper                 >f4      1e-17 erg / (s cm2)  extinction corrected, OII line flux measured in elliptical galaxy aperture \n",
      "flux_aper_err             >f4      1e-17 erg / (s cm2)  error in flux_aper\n",
      "flag_aper                 >i8      None                 1 = OII aperture line flux used, 0 = PSF-line flux used from \"flux\" column\n",
      "major                     >f4      arcsec               Major axis of aperture ellipse of resolved OII galaxy defined by imaging\n",
      "minor                     >f4      arcsec               Minor axis of aperture ellipse of resolved OII galaxy defined by imaging\n",
      "theta                     >f4      deg                  angle in aperture ellipse\n",
      "logL_lya                  >f4      erg / s              log10 of Lya luminosity in erg/s\n",
      "logL_lya_err              >f4      erg / s              error in logL_lya\n",
      "logL_oii                  >f4      erg / s              log10 of [OII] line luminosity (erg/s) from flux if flag_aper=0 or from flux_aper if flag_aper=1\n",
      "logL_oii_err              >f4      erg / s              error in logL_oii\n",
      "flux_lya                  >f4      1e-17 erg / (s cm2)  extinction corrected Lya line flux in $10^{-17}$ erg/s/cm$^2$\n",
      "flux_lya_err              >f4      1e-17 erg / (s cm2)  error in flux_lya\n",
      "flux_oii                  >f4      1e-17 erg / (s cm2)  OII line flux from flux if flag_aper=0 or flux_aper if flag_aper=1 in 10^-17 erg/s/cm^2\n",
      "flux_oii_err              >f4      1e-17 erg / (s cm2)  error in flux_oii\n",
      "sn                        >f4      None                 signal-to-noise for line emission\n",
      "det_type                  |S4      None                 detection type: 'line' or 'cont'\n",
      "apcor                     >f4      None                 aperture correction applied to spectrum at 4500\\AA\n",
      "p_conf                    >f4      None                 LAE/Faint OII emitter confidence score from RF Classifier. 1=high confidence, 0=low confidence\n",
      "p_cnn                     >f4      None                 LAE/Faint OII emitter confidence score based on CNN Classifier. 1=high confidence, 0=low confidence\n"
     ]
    }
   ],
   "source": [
    "print(f\"{len(source_table):,} rows\\n\")\n",
    "\n",
    "for c in source_table.colnames:\n",
    "    col = source_table[c]\n",
    "    desc = col.description if col.description else \"\"\n",
    "    print(f\"{c:25} {str(col.dtype):8} {str(col.unit):20} {desc}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cf9332b2-da2e-4ef7-bcac-04a469d4adc9",
   "metadata": {},
   "source": [
    "## How to Open the Source Observation Table with Spectra"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "871d8588-780b-4286-99f9-4a9679359969",
   "metadata": {},
   "source": [
    "If spectral data is desired, a fits file contains spectral array data matching each row of the Source Observation Table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "f8e39ac4-ebf9-44db-ae79-2253df10aadb",
   "metadata": {},
   "outputs": [],
   "source": [
    "hdu = fits.open( op.join( path_to_cat, 'hetdex_sc2_spec_{}.fits'.format(version)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "3be6d789-1b2f-495d-83c4-0571d663d898",
   "metadata": {},
   "outputs": [],
   "source": [
    "# The source table can also be accessed by astropy Table class or through HDU1\n",
    "#source_table = Table.read( op.join( path_to_cat, 'hetdex_sc2_spec_{}.fits'.format(version)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "a02df88c-5f28-4d1c-bc69-f8855704f741",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Filename: /home/jovyan/Hobby-Eberly-Public/HETDEX/pdr/pdr1/hetdex_source_catalog_2/hetdex_sc2_spec_v1.5.fits\n",
      "No.    Name      Ver    Type      Cards   Dimensions   Format\n",
      "  0  PRIMARY       1 PrimaryHDU       4   ()      \n",
      "  1  INFO          1 BinTableHDU    104   1107763R x 37C   [26A, K, K, 3A, E, E, E, E, E, E, E, 8A, E, 10A, K, 12A, E, E, E, E, K, E, E, E, E, E, E, E, E, E, E, E, E, 4A, E, E, E]   \n",
      "  2  SPEC          1 ImageHDU        10   (1107763, 1036)   float32   \n",
      "  3  SPEC_ERR      1 ImageHDU         9   (1107763, 1036)   float32   \n",
      "  4  WAVELENGTH    1 ImageHDU         8   (1036,)   float32   \n"
     ]
    }
   ],
   "source": [
    "hdu.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "f73704be-a2e4-4992-bedb-44c9ac4d3a55",
   "metadata": {},
   "outputs": [],
   "source": [
    "spec = hdu['SPEC'].data\n",
    "spec_err = hdu['SPEC_ERR'].data\n",
    "wave_rect = hdu['WAVELENGTH'].data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "dfa71915-8430-40b3-bc66-3fe083f04018",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$\\mathrm{1 \\times 10^{-17}\\,\\frac{erg}{\\mathring{A}\\,s\\,cm^{2}}}$"
      ],
      "text/plain": [
       "Unit(\"1e-17 erg / (Angstrom s cm2)\")"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#spec unit is:\n",
    "u.Unit( hdu['SPEC'].header['BUNIT'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "a82b4906-1a5e-4768-a973-3cd0443cd405",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$\\mathrm{\\mathring{A}}$"
      ],
      "text/plain": [
       "Unit(\"Angstrom\")"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# wavelength unit is:\n",
    "u.Unit( hdu['WAVELENGTH'].header['BUNIT'])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "225cfbf5-9ee7-4b8e-a32a-a801d4df7df7",
   "metadata": {},
   "source": [
    "### Query by source type example"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "7152fffa-dcf8-4511-aa0b-b3323ba2f961",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 426654 LAES in the catalog\n"
     ]
    }
   ],
   "source": [
    "sel_lae = source_table['source_type'] == 'lae'\n",
    "print('There are {} LAES in the catalog'.format(np.sum(sel_lae)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "941f3e61-28aa-44c5-a241-10821e499ef3",
   "metadata": {},
   "outputs": [],
   "source": [
    "source_ids_lae = source_table['source_id'][sel_lae]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "4b6f53e3-b2c8-4b14-9952-e4a914e91b87",
   "metadata": {},
   "outputs": [],
   "source": [
    "# let's plot up all LAEs observed after June 2024. We can use the shotid colun\n",
    "# as it is organized based on date"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "e579ef1a-c0d9-4af4-995d-0f1c4a7fc2d9",
   "metadata": {},
   "outputs": [],
   "source": [
    "sel_date = source_table['shotid'] > 20240600000\n",
    "sel_flux = source_table['flux_lya'] > 15"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "ba6000cc-b021-4a7b-a12f-78329b42c14d",
   "metadata": {},
   "outputs": [],
   "source": [
    "sel =  sel_lae & sel_date & sel_flux"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "7d336ef3-bfd0-437c-bb37-b9b016a34b63",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1036, 3248)"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.shape( spec[:, sel])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "fa36f912-3fe7-466a-aa16-d2e10403c657",
   "metadata": {},
   "outputs": [],
   "source": [
    "lae_spec_table = hstack([\n",
    "    source_table[sel],\n",
    "    spec[:, sel].T,\n",
    "    spec_err[:, sel].T\n",
    "])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "ac0bde6c-4a8f-4cfc-b1a6-a57e7609400d",
   "metadata": {},
   "outputs": [],
   "source": [
    "lae_spec_table.rename_column('col0_2', 'spec')\n",
    "lae_spec_table.rename_column('col0_3', 'spec_err')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "9ce2a381-67d9-4513-a773-0579958f5f64",
   "metadata": {},
   "outputs": [],
   "source": [
    "lae_spec_table.sort('z_hetdex')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "a85a5fc9-6b39-47cd-b4fe-7066f8a8bd5c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'HETDEX 1D LAE spectra')"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 400x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(4, 10))\n",
    "plt.imshow( lae_spec_table['spec'], aspect=0.1, vmin=-0.01, vmax=2)\n",
    "plt.title('HETDEX LAE spectra in increasing redshift order')\n",
    "plt.xlabel('wavelength/z_hetdex')\n",
    "plt.ylabel('HETDEX 1D LAE spectra')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "21964aa1-b5d5-48d1-ad49-425ab4071bbc",
   "metadata": {},
   "source": [
    "### Query by Sky Coordinate Example"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "8af1ed4e-2fde-4928-be69-75e76eeeffaf",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create array of coordinates for all HETDEX source members\n",
    "source_coords = SkyCoord(ra = source_table['RA'], dec= source_table['DEC'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "8edbae8d-e59d-4de5-b3f2-99cb359e395d",
   "metadata": {},
   "outputs": [],
   "source": [
    "coord = SkyCoord(ra=220.21432*u.deg, dec=52.095898*u.deg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "aad74ae4-9a9f-48ad-9a72-8d099ed5f022",
   "metadata": {},
   "outputs": [],
   "source": [
    "sel_match = np.where(  source_coords.separation(coord) < 1.*u.arcsec)[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4ca5d632-b632-40ad-bb96-c2cd858a936d",
   "metadata": {},
   "source": [
    "### Access and Plot Spectra"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "ef7e111c-2197-4516-8788-73e0f87933a0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'HETDEX J144051.45+520545.0  source_id=5020000662553')"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "redshift = source_table['z_hetdex'][sel_match][0]\n",
    "\n",
    "lya_wave = 1216* (redshift + 1)\n",
    "source_id = source_table['source_id'][sel_match][0]\n",
    "name = source_table['source_name'][sel_match][0]\n",
    "plt.plot( wave_rect, spec[:, sel_match[0]])\n",
    "\n",
    "plt.xlim(lya_wave-50, lya_wave+50)\n",
    "plt.ylabel(r'spec (10$^-17$ ergs/s/cm$^2$/$\\AA$)')\n",
    "plt.xlabel(r'wavelength ($\\AA$)')\n",
    "plt.title('{}  source_id={}'.format(name, source_id))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "47364783-d8c4-4664-b0e2-f9133c5cd878",
   "metadata": {},
   "source": [
    "## How to Open the Detection Info Table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "5f3aeb91-9f57-4f57-81a6-402aa74b2b70",
   "metadata": {},
   "outputs": [],
   "source": [
    "det_table = Table.read(op.join(path_to_cat, 'hetdex_sc2_detinfo_{}.fits'.format(version)))\n",
    "det_table.convert_bytestring_to_unicode()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "b5241b59-9c7d-47c5-9302-4dbd245002e9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><i>Table length=3296101</i>\n",
       "<table id=\"table139726119037520\" class=\"table-striped table-bordered table-condensed\">\n",
       "<thead><tr><th>source_id</th><th>source_name</th><th>RA</th><th>DEC</th><th>z_hetdex</th><th>z_hetdex_src</th><th>z_hetdex_conf</th><th>source_type</th><th>detectid</th><th>selected_det</th><th>det_type</th><th>shotid</th><th>ifuslot</th><th>line_id</th><th>p_conf</th><th>p_cnn</th><th>RA_det</th><th>DEC_det</th><th>src_separation</th><th>n_members</th><th>gmag</th><th>Av</th><th>ebv</th><th>wave</th><th>wave_err</th><th>flux</th><th>flux_err</th><th>flux_obs</th><th>flux_obs_err</th><th>flux_aper</th><th>flux_aper_err</th><th>flux_aper_obs</th><th>flux_aper_obs_err</th><th>flag_aper</th><th>flux_lya</th><th>flux_lya_err</th><th>flux_oii</th><th>flux_oii_err</th><th>logL_lya</th><th>logL_lya_err</th><th>logL_oii</th><th>logL_oii_err</th><th>sigma</th><th>sigma_err</th><th>continuum</th><th>continuum_err</th><th>continuum_obs</th><th>continuum_obs_err</th><th>sn</th><th>sn_err</th><th>chi2</th><th>chi2_err</th><th>flux_noise_1sigma_obs</th><th>flux_noise_1sigma</th><th>apcor</th><th>counterpart_mag</th><th>counterpart_mag_err</th><th>counterpart_dist</th><th>counterpart_catalog_name</th><th>counterpart_filter_name</th><th>plya_classification</th><th>z_elixer</th><th>best_pz</th><th>z_diagnose</th><th>cls_diagnose</th><th>stellartype</th><th>agn_flag</th><th>wave_group_id</th><th>wave_group_a</th><th>wave_group_b</th><th>wave_group_pa</th><th>wave_group_ra</th><th>wave_group_dec</th><th>wave_group_wave</th><th>fwhm</th><th>throughput</th><th>field</th><th>date</th><th>obsid</th><th>multiframe</th><th>fiber_id</th><th>weight</th><th>x_raw</th><th>y_raw</th><th>x_ifu</th><th>y_ifu</th><th>ra_aper</th><th>dec_aper</th><th>catalog_name_aper</th><th>filter_name_aper</th><th>dist_aper</th><th>mag_aper</th><th>mag_aper_err</th><th>major</th><th>minor</th><th>theta</th></tr></thead>\n",
       "<thead><tr><th></th><th></th><th>deg</th><th>deg</th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th>deg</th><th>deg</th><th>arcsec</th><th></th><th>mag</th><th>mag</th><th></th><th>Angstrom</th><th>Angstrom</th><th>1e-17 erg / (s cm2)</th><th>1e-17 erg / (s cm2)</th><th>1e-17 erg / (s cm2)</th><th>1e-17 erg / (s cm2)</th><th>1e-17 erg / (s cm2)</th><th>1e-17 erg / (s cm2)</th><th>1e-17 erg / (s cm2)</th><th>1e-17 erg / (s cm2)</th><th></th><th>1e-17 erg / (s cm2)</th><th>1e-17 erg / (s cm2)</th><th>1e-17 erg / (s cm2)</th><th>1e-17 erg / (s cm2)</th><th>erg / s</th><th>erg / s</th><th>erg / s</th><th>erg / s</th><th>Angstrom</th><th>Angstrom</th><th>1e-17 erg / (Angstrom s cm2)</th><th>1e-17 erg / (Angstrom s cm2)</th><th>1e-17 erg / (Angstrom s cm2)</th><th>1e-17 erg / (Angstrom s cm2)</th><th></th><th></th><th></th><th></th><th>1e-17 erg / (s cm2)</th><th>1e-17 erg / (s cm2)</th><th></th><th>mag</th><th>mag</th><th>arcsec</th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th>arcsec</th><th>arcsec</th><th>deg</th><th>deg</th><th>deg</th><th>Angstrom</th><th>arcsec</th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th>deg</th><th>deg</th><th></th><th></th><th>arcsec</th><th>mag</th><th>mag</th><th>arcsec</th><th>arcsec</th><th>deg</th></tr></thead>\n",
       "<thead><tr><th>int64</th><th>str26</th><th>float32</th><th>float32</th><th>float32</th><th>str8</th><th>float32</th><th>str10</th><th>int64</th><th>bool</th><th>str4</th><th>int64</th><th>str3</th><th>str20</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>int64</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>int64</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>str16</th><th>str16</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>str7</th><th>str1</th><th>float32</th><th>int64</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>str12</th><th>int32</th><th>int32</th><th>str20</th><th>str38</th><th>float32</th><th>int32</th><th>int32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>str16</th><th>str16</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th></tr></thead>\n",
       "<tr><td>5020000000080</td><td>HETDEX J095913.96+015850.1</td><td>149.80818</td><td>1.980593</td><td>2.2118</td><td>elixer</td><td>0.036</td><td>lae</td><td>3000000068</td><td>True</td><td>line</td><td>20170103002</td><td>106</td><td>Lya</td><td>0.06</td><td>0.233</td><td>149.80818</td><td>1.980593</td><td>-999.0</td><td>1</td><td>23.619</td><td>0.053</td><td>0.0192</td><td>3902.98</td><td>1.08</td><td>32.2497</td><td>8.1</td><td>30.06</td><td>7.55</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-1</td><td>32.249695</td><td>8.099974</td><td>-999.0</td><td>-999.0</td><td>43.097</td><td>0.109</td><td>-999.0</td><td>-999.0</td><td>3.7</td><td>0.96</td><td>-0.4077</td><td>0.3326</td><td>-0.38</td><td>0.31</td><td>5.14</td><td>0.49</td><td>1.18</td><td>0.22</td><td>5.232</td><td>5.6131</td><td>0.868</td><td>28.267</td><td>0.676</td><td>0.0</td><td>HSC-SSP</td><td>r</td><td>0.999</td><td>2.2118</td><td>0.036</td><td>-999.0</td><td>n/a</td><td>-</td><td>-1.0</td><td>-1</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>2.322</td><td>0.09</td><td>cosmos</td><td>20170103</td><td>2</td><td>multi_004_106_033_LU</td><td>20170103002_2_multi_004_106_033_LU_075</td><td>0.1816</td><td>209</td><td>665</td><td>21.61</td><td>-22.03</td><td>-999.0</td><td>-999.0</td><td>0.0</td><td>0.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td></tr>\n",
       "<tr><td>5020000000061</td><td>HETDEX J095906.12+015613.5</td><td>149.7755</td><td>1.937077</td><td>2.047</td><td>elixer</td><td>0.212</td><td>lae</td><td>3000000625</td><td>True</td><td>line</td><td>20170103002</td><td>104</td><td>Lya</td><td>0.31</td><td>0.836</td><td>149.7755</td><td>1.937077</td><td>-999.0</td><td>1</td><td>25.228</td><td>0.054</td><td>0.0198</td><td>3702.76</td><td>0.57</td><td>28.249</td><td>5.2529</td><td>26.19</td><td>4.87</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-1</td><td>28.249014</td><td>5.252871</td><td>-999.0</td><td>-999.0</td><td>42.958</td><td>0.081</td><td>-999.0</td><td>-999.0</td><td>2.31</td><td>0.51</td><td>0.2912</td><td>0.302</td><td>0.27</td><td>0.28</td><td>4.8</td><td>0.43</td><td>1.03</td><td>0.22</td><td>6.438</td><td>6.9441</td><td>0.875</td><td>27.188</td><td>0.399</td><td>0.0</td><td>HSC-SSP</td><td>r</td><td>0.999</td><td>2.047</td><td>0.212</td><td>-999.0</td><td>n/a</td><td>-</td><td>-1.0</td><td>-1</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>2.322</td><td>0.09</td><td>cosmos</td><td>20170103</td><td>2</td><td>multi_016_104_026_LL</td><td>20170103002_1_multi_016_104_026_LL_091</td><td>0.204</td><td>109</td><td>837</td><td>17.8</td><td>-11.02</td><td>-999.0</td><td>-999.0</td><td>0.0</td><td>0.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td></tr>\n",
       "<tr><td>5020000000079</td><td>HETDEX J095914.09+015905.9</td><td>149.8087</td><td>1.984976</td><td>1.9434</td><td>elixer</td><td>0.612</td><td>lae</td><td>3000000090</td><td>True</td><td>line</td><td>20170103002</td><td>106</td><td>Lya</td><td>0.1</td><td>0.028</td><td>149.8087</td><td>1.984976</td><td>-999.0</td><td>1</td><td>29.586</td><td>0.052</td><td>0.0191</td><td>3576.85</td><td>0.74</td><td>70.1841</td><td>9.6848</td><td>65.1078</td><td>8.9843</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-1</td><td>70.184074</td><td>9.6847725</td><td>-999.0</td><td>-999.0</td><td>43.298</td><td>0.06</td><td>-999.0</td><td>-999.0</td><td>5.09</td><td>0.89</td><td>0.1119</td><td>0.3968</td><td>0.1038</td><td>0.3681</td><td>5.45</td><td>0.5</td><td>1.78</td><td>0.23</td><td>9.7015</td><td>10.4579</td><td>0.875</td><td>28.533</td><td>0.844</td><td>0.0</td><td>HSC-SSP</td><td>r</td><td>0.999</td><td>1.9434</td><td>0.612</td><td>-999.0</td><td>n/a</td><td>-</td><td>-1.0</td><td>-1</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>2.322</td><td>0.09</td><td>cosmos</td><td>20170103</td><td>2</td><td>multi_004_106_033_LU</td><td>20170103002_1_multi_004_106_033_LU_022</td><td>0.1845</td><td>44</td><td>196</td><td>7.63</td><td>-15.42</td><td>-999.0</td><td>-999.0</td><td>0.0</td><td>0.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td></tr>\n",
       "<tr><td>5020000000003</td><td>HETDEX J095906.43+015621.8</td><td>149.77678</td><td>1.939388</td><td>-0.0</td><td>diagnose</td><td>0.9</td><td>star</td><td>3000000600</td><td>False</td><td>line</td><td>20170103002</td><td>104</td><td>n/a</td><td>1.0</td><td>1.0</td><td>149.7762</td><td>1.939448</td><td>2.0976</td><td>4</td><td>19.895</td><td>0.054</td><td>0.0198</td><td>3992.35</td><td>1.28</td><td>22.5161</td><td>7.1833</td><td>20.97</td><td>6.69</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-1</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>3.49</td><td>1.17</td><td>10.4903</td><td>0.3543</td><td>9.77</td><td>0.33</td><td>4.89</td><td>0.51</td><td>2.1</td><td>0.22</td><td>4.105</td><td>4.4077</td><td>0.884</td><td>17.846</td><td>0.0</td><td>2.742</td><td>HSC-SSP</td><td>r</td><td>0.001</td><td>0.071</td><td>0.005</td><td>-0.0</td><td>STAR</td><td>G</td><td>-1.0</td><td>-1</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>2.322</td><td>0.09</td><td>cosmos</td><td>20170103</td><td>2</td><td>multi_016_104_026_LL</td><td>20170103002_3_multi_016_104_026_LL_075</td><td>0.169</td><td>254</td><td>689</td><td>8.9</td><td>-8.81</td><td>-999.0</td><td>-999.0</td><td>0.0</td><td>0.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td></tr>\n",
       "<tr><td>5020000000072</td><td>HETDEX J095907.77+015356.3</td><td>149.7824</td><td>1.89897</td><td>2.5348</td><td>elixer</td><td>0.053</td><td>lae</td><td>3000000266</td><td>True</td><td>line</td><td>20170103002</td><td>093</td><td>Lya</td><td>0.08</td><td>0.033</td><td>149.7824</td><td>1.89897</td><td>-999.0</td><td>1</td><td>24.344</td><td>0.056</td><td>0.0204</td><td>4295.59</td><td>0.99</td><td>17.6144</td><td>4.7357</td><td>16.44</td><td>4.42</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-1</td><td>17.614368</td><td>4.735737</td><td>-999.0</td><td>-999.0</td><td>42.978</td><td>0.117</td><td>-999.0</td><td>-999.0</td><td>2.97</td><td>0.86</td><td>-0.2143</td><td>0.2571</td><td>-0.2</td><td>0.24</td><td>5.1</td><td>0.46</td><td>1.27</td><td>0.23</td><td>3.299</td><td>3.5347</td><td>0.883</td><td>29.355</td><td>0.259</td><td>0.0</td><td>HSC-SSP</td><td>r</td><td>0.999</td><td>2.5348</td><td>0.053</td><td>-999.0</td><td>n/a</td><td>-</td><td>-1.0</td><td>-1</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>2.322</td><td>0.09</td><td>cosmos</td><td>20170103</td><td>2</td><td>multi_008_093_054_LL</td><td>20170103002_1_multi_008_093_054_LL_051</td><td>0.1835</td><td>406</td><td>475</td><td>20.34</td><td>-6.61</td><td>-999.0</td><td>-999.0</td><td>0.0</td><td>0.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td></tr>\n",
       "<tr><td>5020000000077</td><td>HETDEX J095913.04+015857.4</td><td>149.80432</td><td>1.982622</td><td>1.9796</td><td>elixer</td><td>0.016</td><td>lae</td><td>3000000133</td><td>True</td><td>line</td><td>20170103002</td><td>106</td><td>Lya</td><td>0.2</td><td>0.632</td><td>149.80432</td><td>1.982622</td><td>-999.0</td><td>1</td><td>23.929</td><td>0.052</td><td>0.0191</td><td>3620.88</td><td>0.69</td><td>46.2184</td><td>9.811</td><td>42.9097</td><td>9.1087</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-1</td><td>46.218388</td><td>9.811009</td><td>-999.0</td><td>-999.0</td><td>43.136</td><td>0.092</td><td>-999.0</td><td>-999.0</td><td>2.53</td><td>0.62</td><td>0.2239</td><td>0.5545</td><td>0.2079</td><td>0.5148</td><td>4.83</td><td>0.47</td><td>1.09</td><td>0.22</td><td>9.8888</td><td>10.6513</td><td>0.763</td><td>25.501</td><td>0.17</td><td>1.447</td><td>HSC-SSP</td><td>r</td><td>0.999</td><td>1.9796</td><td>0.016</td><td>-999.0</td><td>n/a</td><td>-</td><td>-1.0</td><td>-1</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>2.322</td><td>0.09</td><td>cosmos</td><td>20170103</td><td>2</td><td>multi_004_106_033_LL</td><td>20170103002_2_multi_004_106_033_LL_050</td><td>0.174</td><td>70</td><td>461</td><td>22.88</td><td>-6.61</td><td>-999.0</td><td>-999.0</td><td>0.0</td><td>0.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td></tr>\n",
       "<tr><td>5020000000076</td><td>HETDEX J095914.38+015901.8</td><td>149.8099</td><td>1.983846</td><td>2.036</td><td>elixer</td><td>0.062</td><td>lae</td><td>3000000134</td><td>True</td><td>line</td><td>20170103002</td><td>106</td><td>Lya</td><td>0.32</td><td>0.028</td><td>149.8099</td><td>1.983846</td><td>-999.0</td><td>1</td><td>23.778</td><td>0.053</td><td>0.0192</td><td>3689.4</td><td>0.59</td><td>30.434</td><td>6.2418</td><td>28.28</td><td>5.8</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-1</td><td>30.434044</td><td>6.241777</td><td>-999.0</td><td>-999.0</td><td>42.984</td><td>0.089</td><td>-999.0</td><td>-999.0</td><td>2.2</td><td>0.64</td><td>-0.4735</td><td>0.3982</td><td>-0.44</td><td>0.37</td><td>5.23</td><td>0.79</td><td>1.03</td><td>0.24</td><td>8.207</td><td>8.8321</td><td>0.886</td><td>28.662</td><td>3.371</td><td>0.0</td><td>HSC-SSP</td><td>r</td><td>0.999</td><td>2.036</td><td>0.062</td><td>-999.0</td><td>n/a</td><td>-</td><td>-1.0</td><td>-1</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>2.322</td><td>0.09</td><td>cosmos</td><td>20170103</td><td>2</td><td>multi_004_106_033_LU</td><td>20170103002_2_multi_004_106_033_LU_061</td><td>0.1761</td><td>102</td><td>544</td><td>7.63</td><td>-19.83</td><td>-999.0</td><td>-999.0</td><td>0.0</td><td>0.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td></tr>\n",
       "<tr><td>5020000000075</td><td>HETDEX J095914.03+015923.7</td><td>149.80846</td><td>1.989912</td><td>2.417</td><td>elixer</td><td>0.028</td><td>lae</td><td>3000000154</td><td>True</td><td>line</td><td>20170103002</td><td>106</td><td>Lya</td><td>0.35</td><td>0.106</td><td>149.80846</td><td>1.989912</td><td>0.0008</td><td>1</td><td>23.771</td><td>0.052</td><td>0.0191</td><td>4152.38</td><td>1.05</td><td>23.4928</td><td>5.3976</td><td>21.98</td><td>5.05</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-1</td><td>23.49284</td><td>5.3975816</td><td>-999.0</td><td>-999.0</td><td>43.053</td><td>0.1</td><td>-999.0</td><td>-999.0</td><td>4.03</td><td>1.14</td><td>-0.2351</td><td>0.2458</td><td>-0.22</td><td>0.23</td><td>4.86</td><td>0.5</td><td>1.01</td><td>0.22</td><td>4.009</td><td>4.2849</td><td>0.887</td><td>99.9</td><td>0.0</td><td>0.0</td><td>HSC-SSP</td><td>r</td><td>0.999</td><td>2.417</td><td>0.028</td><td>-999.0</td><td>n/a</td><td>-</td><td>-1.0</td><td>-1</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>2.322</td><td>0.09</td><td>cosmos</td><td>20170103</td><td>2</td><td>multi_004_106_033_LL</td><td>20170103002_1_multi_004_106_033_LL_042</td><td>0.1802</td><td>336</td><td>395</td><td>-6.36</td><td>-4.41</td><td>-999.0</td><td>-999.0</td><td>0.0</td><td>0.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td></tr>\n",
       "<tr><td>5020000000047</td><td>HETDEX J095930.95+015619.8</td><td>149.87897</td><td>1.938839</td><td>1.9394</td><td>elixer</td><td>0.049</td><td>lae</td><td>3000001269</td><td>True</td><td>line</td><td>20170103002</td><td>076</td><td>Lya</td><td>0.25</td><td>0.343</td><td>149.87897</td><td>1.938839</td><td>-999.0</td><td>1</td><td>23.839</td><td>0.055</td><td>0.0199</td><td>3572.0</td><td>0.54</td><td>46.3851</td><td>6.7495</td><td>42.902</td><td>6.2427</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-1</td><td>46.385136</td><td>6.7495084</td><td>-999.0</td><td>-999.0</td><td>43.116</td><td>0.063</td><td>-999.0</td><td>-999.0</td><td>2.96</td><td>0.54</td><td>-0.6587</td><td>0.3344</td><td>-0.6093</td><td>0.3093</td><td>5.43</td><td>0.51</td><td>1.17</td><td>0.22</td><td>8.5363</td><td>9.2294</td><td>0.867</td><td>24.958</td><td>0.125</td><td>0.302</td><td>HSC-SSP</td><td>r</td><td>0.999</td><td>1.9394</td><td>0.049</td><td>-999.0</td><td>n/a</td><td>-</td><td>-1.0</td><td>-1</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>2.322</td><td>0.09</td><td>cosmos</td><td>20170103</td><td>2</td><td>multi_025_076_032_LU</td><td>20170103002_1_multi_025_076_032_LU_042</td><td>0.1979</td><td>51</td><td>392</td><td>6.36</td><td>-17.63</td><td>-999.0</td><td>-999.0</td><td>0.0</td><td>0.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td></tr>\n",
       "<tr><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td></tr>\n",
       "<tr><td>5020003030232</td><td>HETDEX J154758.51+491141.0</td><td>236.99379</td><td>49.194725</td><td>1.9296</td><td>elixer</td><td>0.483</td><td>lae</td><td>5003938512</td><td>True</td><td>line</td><td>20240731009</td><td>105</td><td>Lya</td><td>0.31</td><td>0.857</td><td>236.99379</td><td>49.194725</td><td>-999.0</td><td>1</td><td>23.647</td><td>0.049</td><td>0.0178</td><td>3560.49</td><td>0.57</td><td>19.639</td><td>4.9124</td><td>18.31</td><td>4.58</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-1</td><td>19.63903</td><td>4.912439</td><td>-999.0</td><td>-999.0</td><td>42.737</td><td>0.109</td><td>-999.0</td><td>-999.0</td><td>1.9</td><td>0.63</td><td>0.5041</td><td>0.2467</td><td>0.47</td><td>0.23</td><td>5.4</td><td>0.38</td><td>1.2</td><td>0.24</td><td>4.468</td><td>4.7923</td><td>0.918</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>nan</td><td>nan</td><td>0.999</td><td>1.9296</td><td>0.483</td><td>-999.0</td><td>UNKNOWN</td><td>-</td><td>-1.0</td><td>-1</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>1.534</td><td>0.1203</td><td>dex-spring</td><td>20240731</td><td>9</td><td>multi_513_105_051_RU</td><td>20240731009_2_multi_513_105_051_RU_055</td><td>0.2734</td><td>39</td><td>505</td><td>-15.25</td><td>19.83</td><td>-999.0</td><td>-999.0</td><td>0.0</td><td>0.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td></tr>\n",
       "<tr><td>5020003030231</td><td>HETDEX J154753.79+491124.4</td><td>236.9741</td><td>49.1901</td><td>2.2852</td><td>elixer</td><td>0.239</td><td>lae</td><td>5003938515</td><td>True</td><td>line</td><td>20240731009</td><td>105</td><td>Lya</td><td>0.26</td><td>0.646</td><td>236.97409</td><td>49.1901</td><td>0.0359</td><td>1</td><td>27.201</td><td>0.049</td><td>0.0179</td><td>3992.69</td><td>0.57</td><td>10.6005</td><td>2.4102</td><td>9.94</td><td>2.26</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-1</td><td>10.60046</td><td>2.410165</td><td>-999.0</td><td>-999.0</td><td>42.648</td><td>0.099</td><td>-999.0</td><td>-999.0</td><td>2.01</td><td>0.61</td><td>-0.1706</td><td>0.1493</td><td>-0.16</td><td>0.14</td><td>5.14</td><td>0.35</td><td>1.0</td><td>0.23</td><td>2.453</td><td>2.616</td><td>0.721</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>nan</td><td>nan</td><td>0.999</td><td>2.2852</td><td>0.239</td><td>-999.0</td><td>UNKNOWN</td><td>-</td><td>-1.0</td><td>-1</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>1.534</td><td>0.1203</td><td>dex-spring</td><td>20240731</td><td>9</td><td>multi_513_105_051_LL</td><td>20240731009_3_multi_513_105_051_LL_108</td><td>0.3608</td><td>251</td><td>980</td><td>24.15</td><td>-13.22</td><td>-999.0</td><td>-999.0</td><td>0.0</td><td>0.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td></tr>\n",
       "<tr><td>5020003030230</td><td>HETDEX J154754.12+491115.8</td><td>236.9755</td><td>49.187733</td><td>2.5324</td><td>elixer</td><td>0.395</td><td>lae</td><td>5003938520</td><td>True</td><td>line</td><td>20240731009</td><td>105</td><td>Lya</td><td>0.22</td><td>0.251</td><td>236.9755</td><td>49.18773</td><td>0.0307</td><td>1</td><td>27.401</td><td>0.049</td><td>0.0179</td><td>4293.1</td><td>0.76</td><td>11.4111</td><td>2.295</td><td>10.74</td><td>2.16</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-1</td><td>11.41108</td><td>2.294966</td><td>-999.0</td><td>-999.0</td><td>42.788</td><td>0.087</td><td>-999.0</td><td>-999.0</td><td>2.98</td><td>0.64</td><td>-0.255</td><td>0.1275</td><td>-0.24</td><td>0.12</td><td>5.2</td><td>0.43</td><td>0.99</td><td>0.22</td><td>2.125</td><td>2.2578</td><td>0.935</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>nan</td><td>nan</td><td>0.999</td><td>2.5324</td><td>0.395</td><td>-999.0</td><td>UNKNOWN</td><td>-</td><td>-1.0</td><td>-1</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>1.534</td><td>0.1203</td><td>dex-spring</td><td>20240731</td><td>9</td><td>multi_513_105_051_LU</td><td>20240731009_3_multi_513_105_051_LU_057</td><td>0.3643</td><td>404</td><td>515</td><td>17.8</td><td>-19.83</td><td>-999.0</td><td>-999.0</td><td>0.0</td><td>0.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td></tr>\n",
       "<tr><td>5020003030215</td><td>HETDEX J154736.16+491224.1</td><td>236.90065</td><td>49.2067</td><td>2.042</td><td>elixer</td><td>0.518</td><td>lae</td><td>5003938573</td><td>True</td><td>line</td><td>20240731009</td><td>103</td><td>Lya</td><td>0.09</td><td>0.098</td><td>236.90063</td><td>49.206703</td><td>0.0403</td><td>1</td><td>24.196</td><td>0.049</td><td>0.0178</td><td>3697.09</td><td>1.64</td><td>28.1743</td><td>7.1399</td><td>26.32</td><td>6.67</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-1</td><td>28.17432</td><td>7.139921</td><td>-999.0</td><td>-999.0</td><td>42.954</td><td>0.11</td><td>-999.0</td><td>-999.0</td><td>8.03</td><td>2.11</td><td>-0.1499</td><td>0.2248</td><td>-0.14</td><td>0.21</td><td>5.47</td><td>0.75</td><td>0.97</td><td>0.22</td><td>3.198</td><td>3.4233</td><td>0.929</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>nan</td><td>nan</td><td>0.999</td><td>2.042</td><td>0.518</td><td>-999.0</td><td>UNKNOWN</td><td>-</td><td>-1.0</td><td>-1</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>1.534</td><td>0.1203</td><td>dex-spring</td><td>20240731</td><td>9</td><td>multi_514_103_019_LU</td><td>20240731009_3_multi_514_103_019_LU_003</td><td>0.3617</td><td>103</td><td>35</td><td>6.36</td><td>-13.22</td><td>-999.0</td><td>-999.0</td><td>0.0</td><td>0.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td></tr>\n",
       "<tr><td>5020003030216</td><td>HETDEX J154738.60+491206.6</td><td>236.91084</td><td>49.201828</td><td>2.0509</td><td>elixer</td><td>0.343</td><td>lae</td><td>5003938572</td><td>True</td><td>line</td><td>20240731009</td><td>103</td><td>Lya</td><td>0.05</td><td>0.013</td><td>236.91084</td><td>49.201828</td><td>-999.0</td><td>1</td><td>24.221</td><td>0.049</td><td>0.0179</td><td>3707.95</td><td>1.44</td><td>22.1182</td><td>5.6313</td><td>20.66</td><td>5.26</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-1</td><td>22.118244</td><td>5.6312666</td><td>-999.0</td><td>-999.0</td><td>42.853</td><td>0.111</td><td>-999.0</td><td>-999.0</td><td>5.78</td><td>1.68</td><td>-0.3212</td><td>0.1927</td><td>-0.3</td><td>0.18</td><td>5.06</td><td>0.56</td><td>1.01</td><td>0.23</td><td>3.092</td><td>3.3102</td><td>0.921</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>nan</td><td>nan</td><td>0.999</td><td>2.0509</td><td>0.343</td><td>-999.0</td><td>UNKNOWN</td><td>-</td><td>-1.0</td><td>-1</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>1.534</td><td>0.1203</td><td>dex-spring</td><td>20240731</td><td>9</td><td>multi_514_103_019_LU</td><td>20240731009_3_multi_514_103_019_LU_092</td><td>0.2897</td><td>113</td><td>834</td><td>-21.61</td><td>-22.03</td><td>-999.0</td><td>-999.0</td><td>0.0</td><td>0.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td></tr>\n",
       "<tr><td>5023000273167</td><td>HETDEX J154736.99+491219.9</td><td>236.90414</td><td>49.205532</td><td>0.4564</td><td>elixer</td><td>0.092</td><td>oii</td><td>5003938571</td><td>True</td><td>line</td><td>20240731009</td><td>103</td><td>OII</td><td>0.14</td><td>0.148</td><td>236.90427</td><td>49.20517</td><td>1.3465</td><td>2</td><td>24.638</td><td>0.049</td><td>0.0178</td><td>5429.29</td><td>1.08</td><td>11.4313</td><td>2.4055</td><td>10.93</td><td>2.3</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>0</td><td>-999.0</td><td>-999.0</td><td>11.431281</td><td>2.4054844</td><td>-999.0</td><td>-999.0</td><td>40.972</td><td>0.091</td><td>4.86</td><td>1.18</td><td>-0.1673</td><td>0.0941</td><td>-0.16</td><td>0.09</td><td>4.87</td><td>0.54</td><td>1.01</td><td>0.23</td><td>1.807</td><td>1.8899</td><td>0.937</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>nan</td><td>nan</td><td>0.356</td><td>0.4564</td><td>0.092</td><td>-999.0</td><td>UNKNOWN</td><td>-</td><td>-1.0</td><td>-1</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>1.534</td><td>0.1203</td><td>dex-spring</td><td>20240731</td><td>9</td><td>multi_514_103_019_LU</td><td>20240731009_3_multi_514_103_019_LU_026</td><td>0.385</td><td>979</td><td>237</td><td>-2.54</td><td>-15.42</td><td>-999.0</td><td>-999.0</td><td>0.0</td><td>0.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td></tr>\n",
       "<tr><td>5020003030217</td><td>HETDEX J154735.44+491235.8</td><td>236.89767</td><td>49.20994</td><td>2.0806</td><td>elixer</td><td>0.38</td><td>lae</td><td>5003938569</td><td>True</td><td>line</td><td>20240731009</td><td>103</td><td>Lya</td><td>0.03</td><td>0.283</td><td>236.89767</td><td>49.20994</td><td>-999.0</td><td>1</td><td>25.133</td><td>0.049</td><td>0.0178</td><td>3744.01</td><td>0.84</td><td>18.8795</td><td>3.6689</td><td>17.65</td><td>3.43</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-1</td><td>18.879549</td><td>3.6689436</td><td>-999.0</td><td>-999.0</td><td>42.8</td><td>0.084</td><td>-999.0</td><td>-999.0</td><td>3.84</td><td>0.91</td><td>-0.2781</td><td>0.1711</td><td>-0.26</td><td>0.16</td><td>5.16</td><td>0.48</td><td>1.22</td><td>0.23</td><td>3.2</td><td>3.4229</td><td>0.922</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>nan</td><td>nan</td><td>0.999</td><td>2.0806</td><td>0.38</td><td>-999.0</td><td>UNKNOWN</td><td>-</td><td>-1.0</td><td>-1</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>1.534</td><td>0.1203</td><td>dex-spring</td><td>20240731</td><td>9</td><td>multi_514_103_019_LL</td><td>20240731009_3_multi_514_103_019_LL_033</td><td>0.3377</td><td>129</td><td>304</td><td>16.53</td><td>-4.41</td><td>-999.0</td><td>-999.0</td><td>0.0</td><td>0.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td></tr>\n",
       "<tr><td>5020003030311</td><td>HETDEX J154658.43+490938.9</td><td>236.74345</td><td>49.160793</td><td>2.3025</td><td>elixer</td><td>0.278</td><td>lae</td><td>5003938110</td><td>True</td><td>line</td><td>20240731009</td><td>070</td><td>Lya</td><td>0.23</td><td>0.545</td><td>236.74345</td><td>49.160793</td><td>-999.0</td><td>1</td><td>27.13</td><td>0.05</td><td>0.0183</td><td>4013.7</td><td>0.71</td><td>10.6024</td><td>2.3597</td><td>9.93</td><td>2.21</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-1</td><td>10.602423</td><td>2.359653</td><td>-999.0</td><td>-999.0</td><td>42.656</td><td>0.097</td><td>-999.0</td><td>-999.0</td><td>2.17</td><td>0.67</td><td>-0.299</td><td>0.1281</td><td>-0.28</td><td>0.12</td><td>4.85</td><td>0.41</td><td>1.0</td><td>0.23</td><td>2.345</td><td>2.5038</td><td>0.931</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>nan</td><td>nan</td><td>0.999</td><td>2.3025</td><td>0.278</td><td>-999.0</td><td>UNKNOWN</td><td>-</td><td>-1.0</td><td>-1</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>1.534</td><td>0.1203</td><td>dex-spring</td><td>20240731</td><td>9</td><td>multi_502_070_047_RL</td><td>20240731009_3_multi_502_070_047_RL_034</td><td>0.3609</td><td>264</td><td>310</td><td>1.27</td><td>8.81</td><td>-999.0</td><td>-999.0</td><td>0.0</td><td>0.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td></tr>\n",
       "<tr><td>5020003030634</td><td>HETDEX J154703.00+490159.0</td><td>236.7625</td><td>49.03306</td><td>1.9381</td><td>elixer</td><td>0.278</td><td>lae</td><td>5003935354</td><td>True</td><td>line</td><td>20240731009</td><td>032</td><td>Lya</td><td>0.05</td><td>0.644</td><td>236.76251</td><td>49.033066</td><td>0.0381</td><td>1</td><td>27.208</td><td>0.045</td><td>0.0166</td><td>3570.86</td><td>0.9</td><td>17.3314</td><td>4.7704</td><td>16.24</td><td>4.47</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-1</td><td>17.331434</td><td>4.770413</td><td>-999.0</td><td>-999.0</td><td>42.688</td><td>0.12</td><td>-999.0</td><td>-999.0</td><td>2.5</td><td>0.79</td><td>0.0427</td><td>0.2668</td><td>0.04</td><td>0.25</td><td>4.85</td><td>0.43</td><td>1.38</td><td>0.22</td><td>3.779</td><td>4.033</td><td>0.924</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>nan</td><td>nan</td><td>0.999</td><td>1.9381</td><td>0.278</td><td>-999.0</td><td>UNKNOWN</td><td>-</td><td>-1.0</td><td>-1</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>1.534</td><td>0.1203</td><td>dex-spring</td><td>20240731</td><td>9</td><td>multi_320_032_020_LL</td><td>20240731009_3_multi_320_032_020_LL_095</td><td>0.3043</td><td>40</td><td>866</td><td>7.63</td><td>-11.02</td><td>-999.0</td><td>-999.0</td><td>0.0</td><td>0.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td></tr>\n",
       "</table></div>"
      ],
      "text/plain": [
       "<Table length=3296101>\n",
       "  source_id          source_name             RA    ...  major   minor   theta \n",
       "                                            deg    ...  arcsec  arcsec   deg  \n",
       "    int64               str26             float32  ... float32 float32 float32\n",
       "------------- -------------------------- --------- ... ------- ------- -------\n",
       "5020000000080 HETDEX J095913.96+015850.1 149.80818 ...  -999.0  -999.0  -999.0\n",
       "5020000000061 HETDEX J095906.12+015613.5  149.7755 ...  -999.0  -999.0  -999.0\n",
       "5020000000079 HETDEX J095914.09+015905.9  149.8087 ...  -999.0  -999.0  -999.0\n",
       "5020000000003 HETDEX J095906.43+015621.8 149.77678 ...  -999.0  -999.0  -999.0\n",
       "5020000000072 HETDEX J095907.77+015356.3  149.7824 ...  -999.0  -999.0  -999.0\n",
       "5020000000077 HETDEX J095913.04+015857.4 149.80432 ...  -999.0  -999.0  -999.0\n",
       "5020000000076 HETDEX J095914.38+015901.8  149.8099 ...  -999.0  -999.0  -999.0\n",
       "5020000000075 HETDEX J095914.03+015923.7 149.80846 ...  -999.0  -999.0  -999.0\n",
       "5020000000047 HETDEX J095930.95+015619.8 149.87897 ...  -999.0  -999.0  -999.0\n",
       "          ...                        ...       ... ...     ...     ...     ...\n",
       "5020003030232 HETDEX J154758.51+491141.0 236.99379 ...  -999.0  -999.0  -999.0\n",
       "5020003030231 HETDEX J154753.79+491124.4  236.9741 ...  -999.0  -999.0  -999.0\n",
       "5020003030230 HETDEX J154754.12+491115.8  236.9755 ...  -999.0  -999.0  -999.0\n",
       "5020003030215 HETDEX J154736.16+491224.1 236.90065 ...  -999.0  -999.0  -999.0\n",
       "5020003030216 HETDEX J154738.60+491206.6 236.91084 ...  -999.0  -999.0  -999.0\n",
       "5023000273167 HETDEX J154736.99+491219.9 236.90414 ...  -999.0  -999.0  -999.0\n",
       "5020003030217 HETDEX J154735.44+491235.8 236.89767 ...  -999.0  -999.0  -999.0\n",
       "5020003030311 HETDEX J154658.43+490938.9 236.74345 ...  -999.0  -999.0  -999.0\n",
       "5020003030634 HETDEX J154703.00+490159.0  236.7625 ...  -999.0  -999.0  -999.0"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "det_table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "e306407c-f09a-4a19-a9f9-d1d0cca5dcbd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3,296,101 rows\n",
      "\n",
      "Column                    dtype    unit                 Description\n",
      "------------------------------------------------------------------------------------------\n",
      "source_id                 >i8      None                 HETDEX Source Identifier\n",
      "source_name               <U26     None                 HETDEX IAU designation\n",
      "RA                        >f4      deg                  source_id right ascension (ICRS deg)\n",
      "DEC                       >f4      deg                  source_id declination (ICRS deg)\n",
      "z_hetdex                  >f4      None                 HETDEX spectroscopic redshift\n",
      "z_hetdex_src              <U8      None                 HETDEX spectroscopic redshift source\n",
      "z_hetdex_conf             >f4      None                 0 to 1 confidence HETDEX spectroscopic redshift source\n",
      "source_type               <U10     None                 options are 'star', 'lae', 'agn', 'lzg', 'oii', 'none'\n",
      "detectid                  >i8      None                 emission line or detection ID\n",
      "selected_det              bool     None                 best detectid for Lya flux or OII line flux\n",
      "det_type                  <U4      None                 detection type: 'line' or 'cont'\n",
      "shotid                    >i8      None                 integer represent observation ID: int( date+obsid)\n",
      "ifuslot                   <U3      None                 string identifier of IFU location in focal plane\n",
      "line_id                   <U20     None                 line identification at observed wavelength (wave) assuming redshift of z_hetdex\n",
      "p_conf                    >f4      None                 LAE/Faint OII emitter confidence score from RF Classifier. 1=high confidence, 0=low confidence\n",
      "p_cnn                     >f4      None                 LAE/Faint OII emitter confidence score based on CNN Classifier. 1=high confidence, 0=low confidence\n",
      "RA_det                    >f4      deg                  detectid right ascension (ICRS deg)\n",
      "DEC_det                   >f4      deg                  detectid declination (ICRS deg)\n",
      "src_separation            >f4      arcsec               distance between detectid (RA_det, DEC_det) and the source center (RA, DEC) in arcsec\n",
      "n_members                 >i8      None                 number of detections in the source group\n",
      "gmag                      >f4      mag                  sdss-g magnitude measured in HETDEX spectrum\n",
      "Av                        >f4      mag                  applied extinction correction in V band\n",
      "ebv                       >f4      None                 applied selective extinction\n",
      "wave                      >f4      Angstrom             central wavelength of line emission\n",
      "wave_err                  >f4      Angstrom             mcmc error in wave\n",
      "flux                      >f4      1e-17 erg / (s cm2)  extinction corrected line flux at \"wave\"\n",
      "flux_err                  >f4      1e-17 erg / (s cm2)  mcmc error in extinction corrected line flux\n",
      "flux_obs                  >f4      1e-17 erg / (s cm2)  observed line flux\n",
      "flux_obs_err              >f4      1e-17 erg / (s cm2)  mcmc error in observed line flux\n",
      "flux_aper                 >f4      1e-17 erg / (s cm2)  extinction corrected, OII line flux measured in elliptical galaxy aperture \n",
      "flux_aper_err             >f4      1e-17 erg / (s cm2)  error in flux_aper\n",
      "flux_aper_obs             >f4      1e-17 erg / (s cm2)  OII line flux measured in elliptical aperture\n",
      "flux_aper_obs_err         >f4      1e-17 erg / (s cm2)  error in flag_aper_obs\n",
      "flag_aper                 >i8      None                 1 = OII aperture line flux used, 0 = PSF-line flux used from \"flux\" column\n",
      "flux_lya                  >f4      1e-17 erg / (s cm2)  extinction corrected Lya line flux in $10^{-17}$ erg/s/cm$^2$\n",
      "flux_lya_err              >f4      1e-17 erg / (s cm2)  error in flux_lya\n",
      "flux_oii                  >f4      1e-17 erg / (s cm2)  OII line flux from flux if flag_aper=0 or flux_aper if flag_aper=1 in 10^-17 erg/s/cm^2\n",
      "flux_oii_err              >f4      1e-17 erg / (s cm2)  error in flux_oii\n",
      "logL_lya                  >f4      erg / s              log10 of Lya luminosity in erg/s\n",
      "logL_lya_err              >f4      erg / s              error in logL_lya\n",
      "logL_oii                  >f4      erg / s              log10 of [OII] line luminosity (erg/s) from flux if flag_aper=0 or from flux_aper if flag_aper=1\n",
      "logL_oii_err              >f4      erg / s              error in logL_oii\n",
      "sigma                     >f4      Angstrom             sigma linewidth in gaussian line fit (\\AA)\n",
      "sigma_err                 >f4      Angstrom             mcmc error in sigma linewidth (\\AA)\n",
      "continuum                 >f4      1e-17 erg / (Angstrom s cm2) local fitted observed continuum\n",
      "continuum_err             >f4      1e-17 erg / (Angstrom s cm2) mcmc error in continuum\n",
      "continuum_obs             >f4      1e-17 erg / (Angstrom s cm2) local fitted observed continuum\n",
      "continuum_obs_err         >f4      1e-17 erg / (Angstrom s cm2) mcmc error in continuum\n",
      "sn                        >f4      None                 signal-to-noise for line emission\n",
      "sn_err                    >f4      None                 mcmc error in signal-to-noise\n",
      "chi2                      >f4      None                 reduced $\\chi^2$ quality of line fit\n",
      "chi2_err                  >f4      None                 mcmc uncertainty in reduced $\\chi^2$\n",
      "flux_noise_1sigma_obs     >f4      1e-17 erg / (s cm2)  observed 1 sigma flux sensitivity\n",
      "flux_noise_1sigma         >f4      1e-17 erg / (s cm2)  extinction corrected 1 sigma flux sensitivity\n",
      "apcor                     >f4      None                 aperture correction applied to spectrum at 4500\\AA\n",
      "counterpart_mag           >f4      mag                  selected closest counterpart mag from imaging data\n",
      "counterpart_mag_err       >f4      mag                  uncertainty in counterpart_mag\n",
      "counterpart_dist          >f4      arcsec               distance to closest counterpart\n",
      "counterpart_catalog_name  <U16     None                 image catalog source of counterpart\n",
      "counterpart_filter_name   <U16     None                 image filter of counterpart\n",
      "plya_classification       >f4      None                 0 to 1 on likelihood line is Lya\n",
      "z_elixer                  >f4      None                 None\n",
      "best_pz                   >f4      None                 confidence in best_z\n",
      "z_diagnose                >f4      None                 Best fit redshift from Diagnose\n",
      "cls_diagnose              <U7      None                 Diagnose classfication.\"STAR\", \"GALAXY\", \"QSO\", \"UNKNOWN\"\n",
      "stellartype               <U1      None                 diagnose spectral type classification for stars\n",
      "agn_flag                  >f4      None                 -1 not an AGN, 0 broad line source, 1 confident AGN\n",
      "wave_group_id             >i8      None                 id for 3D clustering at common ra, dec, wave\n",
      "wave_group_a              >f4      arcsec               semi-major axis from 3D FOF clustering\n",
      "wave_group_b              >f4      arcsec               semi-minor axis from 3D FOF clustering\n",
      "wave_group_pa             >f4      deg                  positional angle from 3D FOF clustering\n",
      "wave_group_ra             >f4      deg                  mean ra from 3D FOF clustering\n",
      "wave_group_dec            >f4      deg                  mean dec from 3D FOF clustering\n",
      "wave_group_wave           >f4      Angstrom             mean wavelength from 3D FOF clustering\n",
      "fwhm                      >f4      arcsec               measured seeing of the observation in arcsec\n",
      "throughput                >f4      None                 relative spectral response at 4540 assuming a 360 s nominal exposure\n",
      "field                     <U12     None                 field ID: cosmos, goods-n, dex-fall, dex-spring, nep, ssa22\n",
      "date                      >i4      None                 date\n",
      "obsid                     >i4      None                 observation number\n",
      "multiframe                <U20     None                 string identifier for the ifuslot/specid/ifuid/amp combination\n",
      "fiber_id                  <U38     None                 string identifier for the highest weight fiber\n",
      "weight                    >f4      None                 flux weight of the highest weight fiber\n",
      "x_raw                     >i4      None                 x value on the CCD of the detection (ds9 x value)\n",
      "y_raw                     >i4      None                 y value on the CCD of the detection (ds9 y value)\n",
      "x_ifu                     >f4      None                 x position in the ifu in arcsec\n",
      "y_ifu                     >f4      None                 y position in the ifu in arcsec\n",
      "ra_aper                   >f4      deg                  Right Ascension of aperture center of imaging counterpart in degrees\n",
      "dec_aper                  >f4      deg                  Declination of aperture center of imaging counterpart in degrees\n",
      "catalog_name_aper         <U16     None                 Imaging source for measuring OII resolved apertures\n",
      "filter_name_aper          <U16     None                 Filter of Imaging used for measuring OII resolved apertures\n",
      "dist_aper                 >f4      arcsec               distance between aperture center and detectid position in arcsec\n",
      "mag_aper                  >f4      mag                  photometric magnitude in aperture in imaging source\n",
      "mag_aper_err              >f4      mag                  photometric magnitude error in aperture in imaging source\n",
      "major                     >f4      arcsec               Major axis of aperture ellipse of resolved OII galaxy defined by imaging\n",
      "minor                     >f4      arcsec               Minor axis of aperture ellipse of resolved OII galaxy defined by imaging\n",
      "theta                     >f4      deg                  angle in aperture ellipse\n"
     ]
    }
   ],
   "source": [
    "# Column Info\n",
    "\n",
    "print(f\"{len(det_table):,} rows\\n\")\n",
    "\n",
    "print(f\"{'Column':25} {'dtype':8} {'unit':20} Description\")\n",
    "print(\"-\"*90)\n",
    "\n",
    "for c in det_table.colnames:\n",
    "    col = det_table[c]\n",
    "    desc = getattr(col, \"description\", \"\")\n",
    "    print(f\"{c:25} {str(col.dtype):8} {str(col.unit):20} {desc}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6344578a-19d2-494b-aaa0-f6c8b9fc1446",
   "metadata": {},
   "source": [
    "## Plot up all detections for a single source_id"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a7527bb1-ab17-4500-8390-aca362327bf0",
   "metadata": {},
   "source": [
    "Let's query the detection info table for a relatively nearby, bright galaxy that is composed of serveral line detections to demonstrate the content of the Detection Info Table. Nearby galaxies and bright sources such as AGN can be composed of many detections. This is because line emission at different spatial regions and wavelengths will result in multiple detections in the detection search. The source will also likely have a complementary continuum detetion if it is bright (g < 21)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "c7e90766-f22d-46a2-9729-78809347f1a5",
   "metadata": {},
   "outputs": [],
   "source": [
    "sel_big_oii = (det_table['source_type'] == 'oii') & (det_table['major'] > 6) \n",
    "sel_center_ifu = (np.abs( det_table['x_ifu']) < 5) & (np.abs(det_table['y_ifu']) < 5)\n",
    "selected_det = (det_table['selected_det'] == True) & (det_table['n_members'] > 6)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "00d01c99-4dac-4be5-854e-606b89a16ed9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " There are 174 matches \n"
     ]
    }
   ],
   "source": [
    "sel = sel_big_oii & sel_center_ifu & selected_det\n",
    "\n",
    "print(' There are {} matches '.format(np.sum(sel)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "c8bc12e8-d9d2-4544-9b2a-5e6130f5300a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Pick random object in list and plot up the source_id\n",
    "\n",
    "index = np.where(sel)[0][10]\n",
    "\n",
    "sid = det_table['source_id'][index]\n",
    " \n",
    "coords = SkyCoord(ra=det_table['RA'][index]*u.deg, dec=det_table['DEC'][index]*u.deg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "5ed8a935-57cf-4195-acfb-4afb41de4de8",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING: FITSFixedWarning: 'cdfix' made the change 'Success'. [astropy.wcs.wcs]\n"
     ]
    }
   ],
   "source": [
    "# Get Imaging data from Legacy Survey API\n",
    "fits_file = 'https://www.legacysurvey.org/viewer/fits-cutout?ra={}&dec={}&layer=ls-dr9&width=80&height=80&pixscale=0.25&bands=grz'.format(coords.ra.deg, coords.dec.deg)\n",
    "hdu_ls = fits.open(fits_file)\n",
    "wcs_ls = WCS( hdu_ls[0].header).dropaxis(2)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "31f8fa32-33e9-4847-b7c2-eb95c7681b89",
   "metadata": {},
   "outputs": [],
   "source": [
    "redshift = det_table['z_hetdex'][index]\n",
    "source_type = det_table['source_type'][index]\n",
    "\n",
    "grp = det_table[ det_table['source_id'] == sid]\n",
    "grp.sort('gmag')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "0471b616-8118-42e0-b693-d72b0acf108e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Get Spectrum from source_table\n",
    "hdu = fits.open(op.join(path_to_cat, 'hetdex_sc2_spec_{}.fits'.format(version)))\n",
    "source_table = hdu['INFO'].data\n",
    "spec = hdu['SPEC'].data\n",
    "sel_source = np.where( source_table['source_id'] == sid)[0][0]\n",
    "spectra = spec[:, sel_source]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "cae91f57-bb33-414e-a8c6-faa560fd55a6",
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "d73b6992-7a30-4447-88a3-52fa00411e05",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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i6+fr6tWrIptXRzfTnZfh4eEi6w683bt3i6w7FfUsZd3xmZiYKLJe2bx169Yip+w+BayPnzVr1ojcuXNnkfUs5fXr14usOwAfeeQRkfX2m993zSpVqiSyrjzQ26c7IBs1aiSyfv50x6mukDA/H+b3sQoVKqTZC1uQvPPOO7h16xbq1q0LW1tbGI1GTJkyxer1ZBYXFyfeq3UXKxERERERUX7KtZmE165dw/Dhw1GnTh0MGTIEDg4O2LNnj2UBipUrV6JJkyaWAbthw4ahSZMmmDVr1gPd/jfffINBgwZh6NChaNeuHZydnbFq1SrLYIunpyfWrVuH6OhodO3aFc2bN8fOnTuxYsUKqw+0mVGtWjWsWbMG27ZtQ+PGjfHpp59i+vTpVoMERERUtC1evBj/93//hz/++AOHDh3C/Pnz8b///S/NSoupU6fC3d3d8j89OEtERERERJSfcm0m4aJFi9K9fOTIkVazvTKjRIkS+P777/H999+neZ3mzZtbzbjJjLS2sVOnTjh06FCWb5eIiAq/t99+G++++y6GDRsGIHmRrsuXL2Pq1KmWWfMpvffee2LhrqioKA4UEhERERFRgZFrg4RERERF2Z07d6x6b21tbdPsvXV0dISjo2NebBoREREREVGmcZCwAIuLi7N8AA0MDBSX6Q4y3UloNBpF1p1koaGhIsfExIi8evVqkZs2bSqy7lSLjo4W+cSJE+ne/ujRo0XWnXG6s1B3+jk4OIisO9AuXLggcvXq1UV++umnRV6wYIHIf/zxh8i6E7B06dIi6/1RqlQpkXXHoO4i0x2FKXswgeTT51OaMGGCyHpQQj8fhw8fFrlOnToi645D3cmnOwhPnz4tcnx8vMh6hW79fOiOSt05WLVqVZE7duwo8ooVK9LdHt2B6OLiIrLuCNQdhu7u7iLr/evs7Cyy3t/Hjx8XWXcYPvPMMyLrVd/16+/JJ58UWR8P+vnT7w/68elOSE2/X+jjRXd49u/fX+R58+aJrGdev/jiiyKbOxBjY2PT3a6Cpn///pgyZQoqV66MevXq4fDhw/j666+tOkqJiIiIiIgKAw4SEhERZcH333+PDz/8EGPGjEFYWBjKly+PF198ERMnTszvTSMiIiIiIso0DhISERFlgZubG7799lt8++23+b0pRERERERE2ZZrqxsTERERERERERFR4cCZhAWYk5MTnJycAFh3+J0/f15k3cln/j0zNzc3kW/cuJHu5bdu3RJZd8bVrl1b5P/++09kLy8vkXUHn+7wCwsLE1l3sjVs2FDkLl26iHzq1CmRdQedfjy6I69ixYoi6063WrVqiaw7HX///XeRdYeb7qwzGAwi605C3YF37do1kXv16iWyXuVb7/9WrVqJvGTJEpH18VKmTBmRdcdi+/btRdbPv7493bG4Zs0akT08PETWnY/6+KxcubLIejEI3ZmnOz0zOn51p6d+Ppo1ayay7kTUx+uBAwdE1h2VuiNR5x07doisnx99fC1dulTkGjVqpLt9wcHBIuvFOLp16ybyX3/9JbLuyKxSpYrIHTp0EFk/H+bOxLt374KIqCiLMwJf/GfAoRDg134mlHLK+HeIiIiI8gpnEhIRERER5YGDwcAvRwzwDzXgTETG1yciIiLKSxwkJCIiIiLKAwkpJqonmdK+HhEREVF+4CAhEREREVEeSFleYUxK82pERERE+YKdhAXY9evXUaJECQDA5s2bxWW6s0x3iOmOu8jISJF1557uhNMdcseOHRNZd9TpDjrdERcQEJBu1tv/9NNPi/zTTz+JfP36dZF1x2Hjxo1F1o+vXLlyIpv3s9mdO3dE1p2J+v51R55+fnSnm+6Qu3jxoshVq1YVWXciXr58WWT9ePTzfejQIZH1/vD39xd5wIABIv/7778i6w5I3SGoj5e4uDiRq1evLrJ+fPr3Nd0JqJ8Pd3d3kZs3by6yfn51J2WLFi1EXrlypcj6eM+o87Ju3boi6+Nfb78+fvTt6U7CatWqiayPL90JeuTIEZG7d+8usp+fn8jmzkAzZ2dnkTt16iTylStXRNbH5+LFi0Xu2LEjAOvnhYioqEn59p7ImYRERERUwHAmIRERERFRHkh5inESZxISERFRAcNBQiIiIiKiPJBy8qCRMwmJiIiogOEgIRERERFRHhAzCTlISERERAUMOwkLsMqVK1t1f5npDjTdyac74HRHmb7d+Ph4kXVHoO5MCwkJEVl3xOnLGzRoIHJGnXD6ct2hpzv7atasifTY2tqK7OrqKrLuXGvSpInIurPwxIkTIuvOwf3796d7/7oTTj9fHTp0EFl3vOn9m6TOWdL3HxoaKnL79u1F1h13+v62bt0qsj5+9POjOxx1R6be3hs3boisOw7Pnj0r8rVr10TWHYT693Wn365du0TWz/fs2bNF1sfb+vXrRY6JiRFZvz7168fFxUVkLy8vkevVqyey7ijUz7/m4+Mjst5/urPSzc1NZN05efLkSZHt7OQ/HXv27BFZdzDq/VWyZEmRzceDfpxEhcm8efPwzDPP4Ndff8XIkSMf6HfM7y26p5SKLtFJyNONiYiIqIDhTEIiIiKiIiIgIAAGgyHN/y1atCjV3zt37hyGDh0KLy8vODk5oWHDhpgxY4bVlzomkwlr167FSy+9hIYNG8Ld3R3Ozs5o1KgRPvvsM9y9ezfNbVu/fj06d+6MkiVLws3NDZ07d7b6EiGlkJAQPPfcc/Dx8UGJEiVQu3ZtTJo0yeqLTbOkpCTMmDEDDRs2hJOTE7y8vDB06FCcO3cuzfvYv38/+vbti1KlSsHFxQUtW7bEH3/8keb1o6Ki8MYbb6BKlSpwdHRElSpV8MYbb1gtEAUAI0eOhKHSAPG/Pp0H4PIX/XD5i37o33UAPv029efD7K+//srwuUspMjISFSpUgMFgQO/evTO8PgCMGTPGch+pfQn177//4q233kKXLl3g7u4Og8HwwAPhREREVLhwJiERERFRNg0ePBitW7e2msmbXxo1aoRBgwZZ/bx+/fpWPzt58iTatm2LO3fuYOjQoahQoQLWrl2LV155BUePHsVPP/1kuW5cXBz69u0LR0dHdO7cGb169cLdu3exfv16vP/++1i+fDm2b99utQr877//jieffBKenp4YMWIEDAYD/vzzT/Tu3Rv/93//hyeeeEJcPyQkBK1atcLVq1cxaNAg1K5dGzt37sRHH32E3bt3Y/Xq1VZnPYwePRpz5syBn58fXnnlFYSGhmLx4sXYsGED/vvvP6uV27dt24ZevXrBwcEBw4YNg7u7O5YtW4YnnngCAQEBmDBhgrh+TEwMOnXqBH9/f/To0QPDhw/HkSNH8M0332Dr1q3YuXOnmCk+aNAgVC0tzxQ4ewNYc8GAqH1/w5RwF706NU3l2UsWFhaGMWPGwMXFxWrGelpeffVVq9ns6dm8eTNmzZqV7n388ssvmD9/PpydnVG5cuVUB0SJiIioaOAgIREREVE2ubu7W1Uf5KfGjRvj448/fqDrvvTSS7h16xZWr16Nvn37AgAmT56MPn36YM6cORg+fDi6dOkCILk+Y8qUKRgzZoyomkhISMDDDz+MVatWYcaMGXj77bctl928eRMvv/wyPD09cejQIVSqVAkA8N5776Fp06Z4+eWXLbP5zN555x1cuXIFP/74I1566SUAybMYn3nmGcyfPx/z58/HM888Y7n+1q1bMWfOHHTo0AEbN26Eo6MjAODpp59Gjx498NJLL2H79u2W6ycmJuK5556DwWDAv//+a6md+Oijj9CmTRt89NFHePTRR1GrVi3L70ybNg3+/v4YP348vvjiC8vPP/roI0yaNAnTpk3DJ598Yvn5oEGDMKi5rBtZeRbY+ttF3Nq1EJWrVUHLJrXTfV5cXFwwYsQIfPXVV2lez2zVqlVYsGABpk+fjldffTXD69++fRvPPvssBg8ejBs3boj9k9LLL7+Mt99+G3Xr1sX+/fvRpk2bDG+biIiICicOEhZgnTp1snR36Q689E6dAaw77xo2bCiy7tjTHYC6k0x3kCUkJIisO8t0R6DudNu2bVu626Nvr3PnziLrTrzjx4+LrDvP9KlJx44dE7lKlSoi6xkQ//33n8gODg4i6/2tO/B052GdOnVE1p10BoNBZH36lu6409fXz1fPnj1F1h2Cvr6+Ip8+fVpkPTNm8ODBIuvHp/efvv1Lly6JrI83/UE7MTFRZN2Z2KpVK5F1x+O///4rsu7o9Pb2Fnnjxo0iN27cWGT9fJk/8JrpfrGUHzJTU65cOZH182k0GkXWnYZ79+4VWXdC6u3TM4muXr0q8pYtW0QuW7asyPp41M+X7kitXr26yHq2yuHDhwFYP29UcCxduhTTp0/HqVOnEBUVBS8vL9SrVw+jR48Ws9X++ecffPXVVzh06BDi4+NRp04djBw5Eq+88oroZt22bRu6dOmCjz76yGogKyAgANWqVcOIESMwb948y8/N/474+/tj4sSJ+PvvvxEcHIy5c+daTn08evQopk2bhm3btuH69esoXbo0GjVqhLFjx6J///7iflasWIHp06fj0KFDiI2NRc2aNTFy5EiMGzfOqkf2QaTXSbhixQpMnjwZx48fR8mSJTFgwABMmzYt0/eRG86ePYt///0XXbp0sQwQAoC9vT2mTJmCzZs3Y86cOZZBQnt7e6sZduafv/fee1i1ahW2b98uBgn/+usvREZG4pNPPhHvRz4+Pnj99dfx7rvv4q+//sILL7wAIHnwavHixahevTpGjx5tub7BYMDUqVOxYMECzJkzRwwSzpkzB0Dy4KZ5gBBI7gzu1asX1q1bh7Nnz6J27eRBuS1btuDChQt45plnRC+tm5sbPvzwQwwbNgy//vorPvvsMwDJA5Rz586Fq6srJk6cKB77e++9h++//x4///wzPv74Y6v38JRMJiD6SPIp1p179Ujzen/88QeWLVuG9evXW/0NkpqIiAi88MILePzxx9G/f/8HGiR88803cfv2bfz444947LHH0rxe8+bNM7wtIiIiKhrYSUhERERpmjlzJh555BGcO3cOgwcPxhtvvIHu3bvj6tWrWL58ueV63333Hfr374+jR4/i8ccfx9ixYxEbG4tx48Zh6NChObIwTVxcHLp27Yq1a9eif//+ePnlly2D2H///TdatmyJP//8E61atcKbb76Jhx56CIGBgfj555/F7UyYMAGDBg3C2bNn8fDDD2PMmDEoUaIE3n77bQwbNizb25nSb7/9Zrmvp556CiNGjMCuXbvQvXv3NLv1ckJQUBBmzpyJqVOnYv78+VYLPpmZv7TTXyYBQMuWLeHh4ZHmDDPN3t4egPUXVendR69evQBA3Mfu3bsRFxeHHj16WA24+fj4oEGDBti7d6/4wmLbtm1wcXFBu3btHug+0tsm889SXv/cuXMICgpCu3btrL6oKVGiBDp27IjAwECcP3/e6vZSio2LQ8ypfwFbe7Tr2iXV64SEhOCVV17BqFGjUt2+1Lz88sswGo2YPn36A11/w4YNmDNnDr799lurL4KIiIio+OJMQiIiIkrT3Llz4eDggCNHjljNojWvTH7x4kW89dZb8Pb2xoEDByyzxT777DP07NkTy5Yts3TSZUdISAgaNmyIXbt2iRnLYWFhePrpp2FnZ4cdO3ZYrViecoBs48aNmDp1Kvr06YMlS5ZYZqabTCaMGTMGs2bNwtKlS/Hwww9na1uB5EUuXnnlFbi4uGD//v2WWWxTpkxB9+7dERwcbDWT3d/fXwy+ZqRq1aqpLiKxceNGMSvazs4Or776Kr788kvR5Wc+MyG1Gc8GgwE1a9bEgQMHcOfOHatZ/Novv/wCwHrgLb37MP8s5RkS6V3f/PMjR47g4sWL8PPzQ0xMDIKDg1G/fv1UZ4Fm9j5KlSoFT0/PTG+T+XrpzR7/b/t/MMXFwNm3I5xc3VK9zosvvogSJUo80CnGQPIA+cKFC7F48WKUKVMGt2/fTvf6UVFReO6559C3b1889dRTD3QfREREVDxwkJCIiIjSZW9vb5klllKZMmUAJC9KkZiYiDfffFOcTurg4IDPP/8cbdq0wbx587I9SAgAX375pVWlwfz58xEdHY2JEydaDRACQMWKFS3/PWPGDADA7NmzxaCXwWDA559/jtmzZ2PhwoU5Mki4fPlyy0CheYAQuH8qb4cOHax+x9/fX/TaZaRTp05ikNDZ2RkfffQRBg8ejOrVq+Pu3bvYs2cP3nnnHXz99ddwcHDA1KlTLdc3L3KRVp+iub7j1q1b6Q4Srlu3DrNnz4avry+effZZcVl69+Hi4gJbW1ux2EZmtikr13/Q30k5uJyV+0jN5nXJA7euDXvCmGR9+W+//YaVK1dixYoVVtUgqQkPD7ec9j906NAMrw8Ar7/+Om7duoXZs2c/0PWJiIio+OAgYQG2du1aywch3XmnOwk7deoksu7M0x1wkZGR6V5ffwDTXWE7d+4UWXeMJSXJv3z1qTmlS5cWWX/zrzvi9IdTvf26I01fX99ehQoVRNadd6GhoSLrP9T17ekPTvrx6Ptr3bq1yPo0vKNHj4qsO+VSlrsD1p2S+vbq1q0rsn5+dSdgvXr1RNazQvTxkPIDOADExsaKrDsjdUddo0aNRNYfsnTHnu5kTNk/BVg/3oxmVbi5ydkcL7/8ssj6+dCvJ13iXr58eZH1/tKdiJ6eniLrzk99+lqDBg3SvT/d2agHZvT7x4IFC0TWK6Lq23N1dRVZd5CuWrVKZL0CqX69VqtWDYD1cUMFw9ChQ/Huu++ifv36GDZsGDp37oz27duL90Vzr6TujwWS3++cnJzg7++f7W0pUaKE1fEPAPv27QOQ+qmj2p49e+Di4mJ1CrKZk5OTVS9rVpn/7U5tMLBNmzZWp+UCwMiRI1OdGfigvL29Rc+jm5sb+vfvjxYtWqB+/fr4+uuvMX78eKt/R7LjwIEDeOyxx+Du7o6//vrL6j2Zkp2/FIRTx07Azr0sSlRpBKP6tzoo5AZef/0NDBs2DAMGDHig2xwzZgwSEhIwc+bMB7r+2rVr8euvv2LWrFlW/3YTERERcZCQiIiI0jR+/HiUKVMGs2bNwtdff42vvvoKdnZ26Nu3L7799ltUq1YNUVFRAKwXuTHz9vZGYGBgtrfF29s71UUhzF8c6S9kUhMREYHExMR0Z+vpL76yyvyFh/5iCUj+Msk8EzMvlCtXDn379sWCBQuwf/9+y4CqeWZcWjPgzM+tXhDM7PDhw+jZsycMBgPWr19v9SWTvg/9mGNiYmA0GsUMvQfdJvP1Mnv9B/2d7GxTan5evBEmkwkuDZO7FpPUIOGY92fB1tYW33//fZq3kdKKFSvw119/Yd68eVYLYKXmzp07eP7559GlSxfLIjFEREREKXGQkIiIiNJkMBjw3HPP4bnnnsONGzewY8cOLFy4EH/++SfOnTuHY8eOWQaQQkNDrTr2gOTZwCkHmcyzS/UsbiD90zXTWjXWPKsxMDDQsgpyWkqWLAmDwWC1KntuMA8Y6dnQQPKq5Tdu3LAa2MypTsLUmGctp5x9nlpfn5nJZML58+dRvnx5qzMCAODQoUPo0aMHjEYjNmzYgBYtWqR6v7Vq1cKBAwdw7tw5q0HC1Lr+0tsm889tbGwss9JdXFzg4+ODS5cuwWg0Ws3mz+g+mjVrJq5/8+ZNhIeHo23btpnaJn0fKRmNRsz/aytsbGzg2qB78s/UWj7+Jy8hPDzcqvvTbPjw4Rg+fDi++eYbvP7665YZvGnNPl2/fj0MBgMaNWoEf39/hIWFITAwEIGBgVYzvM18fHwAJA/+Nm7cONXrEBERUdHFQUIiIiJ6IGXKlMGgQYMwaNAghIeHY8uWLTh//jyaNGmCv//+G9u2bUPLli3F7+zbtw+xsbHitHzzqa6pzS40D3xkRsuWLbFkyRJs2LAh1dVtU2rVqhXWrl2b4QITOcFcpbBjxw48+uij4rLdu3enOkia3U7C9JhPy045kGo+RXzDhg149913ra4fGRmJPn36WN3WoUOH0L17dyQmJmL9+vVo1apVutu4cOFCbNiwwapuY/369ZbrmLVu3RqOjo7YuDF55l3KweHg4GAcO3YMrVq1QokSJcR9LFq0CLt27ULHjh0zvI9OnTph6tSp2LBhg9WK1hs2bLC6fq1atVC+fHns2rULMTExYtD07t27+Pfff1G+fHmr+gWzNVsOIjgsAo1bNsdNt+TBWt1JOGxAB4THeVj97qFDh3D48GF06dIF1atXR/369QEATZs2tep/BJIrLRYvXoyKFSuiV69eqFy5MoDkU89Tuz4ArF69GiEhIXj88cfh5OSUp7NciYiIqODgIGEBtnr1aku3nu5MGzx4sMj6D2LdCbhu3TqRdfeX7iTUHWf6j0XdCRgcHCzyoUOHRNanH928eVPk9u3bi2z+A9hs+/bt6W6P+ZtvM915pjvqdA+P3h79IVPPAjl58qTIugNQdxRGRESIrDvu9P7UHXS6s053wuleKz3bRvdr6cev7093Bur9af7AZaZnPejf19urZwqdOXNGZH26lrmzzizlB0MA2Lt3r8iXL18WWZ+GpR/Pli1b0t0+3eGYssweuP/B20x3LOqOy4CAAJH1602/nvWpj8eOHRNZP//69aE7Bc2nxZnpTkU9s0l3KOr7O3v2rMj6+dKdkLoz1Ly9uluTCob169ejW7du4nlPSEiwvK85OTnh8ccfx6RJk/D111/jySeftBzTCQkJloGnlANZderUgaurK1auXImIiAhLT21oaCgmT56c6W0cMWIEJk2ahK+++gqDBw+2mgEVGBhoOa5fffVVrF27FqNGjcLy5cutXi8hISG4efMmfH19M70d2sCBA1GyZEn88ssvePnlly2LlyQkJOCDDz5I9Xey20m4b98+NGnSxOp19vXXX2PXrl3w8/MT71G1a9dGx44dsXXrVqxZswZ9+/a12sbnn39e3JZ5gDAhIQHr1q2zeg/Rhg4dinfeeQfff/89nnnmGUvPbnBwML799lt4eHiIQdSSJUvisccew2+//YZZs2bhpZdeApD8b+17772HpKQkq2164YUXsGjRInzwwQfYtGmT5e+azZs3Y/369ejYsaNYPKZbt26oXr06/vjjD7z66quWY+b27dv49NNPYWdnJ54H84zaSZMmYdKkSfjiiy8sl02dOhU3b97EK6+8kuZs158XJS9Y0rFnD6y4VzurZxJ+/t4IoGJ/q9/9+OOPcfjwYbzwwgtiQHPAgAGpdhcGBARg8eLFqFevHubOnWv5eZkyZUROqXPnzggJCcFXX331QKcuExERUdHEQUIiIiJK02OPPQZnZ2e0b98eVapUQUJCAjZu3IiTJ0/iscces8xS+uKLL/Dmm2+iYcOGGDp0KFxcXPDPP//g9OnTGDhwoFhAx8HBAS+//DI+//xzNG3aFAMHDsTt27exatUqdOrUCRcuXMjUNnp7e+O3337DsGHD0LJlSwwYMAB16tRBeHg49u7di6pVq1pO4e3duzc+/PBDfPrpp6hZsyZ69+6NKlWq4MaNGzh//jx27NiByZMn58ggobu7O6ZPn46RI0eiRYsWGDZsGNzd3fHPP//AycnJ6guunDB+/HicPn0anTp1QqVKlRAbG4vdu3fj8OHDKFWqFBYsWGA1kDVz5ky0bdsWgwcPxtChQ1G+fHmsW7cOR48exXPPPYcuXbpYrhsREYHu3bvj5s2b6N27NzZu3IiNGzeK2/Pw8MDrr79uyaVKlcKMGTPw1FNPoWnTphg2bBhsbGywePFihIaGYsGCBVYLqXz++efYunUrxo4di02bNqF27drYsWMHdu3ahV69emHEiBHi+l26dMFzzz2HuXPnokmTJnjooYcQGhqKxYsXo2TJklYLe9jZ2WHu3Lno1asXOnTogOHDh6NkyZJYtmwZLl26hMmTJ4tBRfO+XblyJaZNm4bDhw+jWbNmOHLkCNauXYvGjRtj/PjxqT4noddvYvWWAyjr5YHGLVtixa7knxuTDABMqf5OQbJz507L4KJ54bCdO3daBlHr1q1rNQuViIiICicOEhIREVGapk6dinXr1mHfvn1YtWoVXFxcULNmTcyePRujRo2yXO+NN95AzZo18fXXX+P//u//EB8fj9q1a+Orr77Cq6++ajUwNXnyZDg4OFhWWq1atSo+/PBD9O/fH0uXLs30dg4ePBh79+7F1KlTsX37dqxcuRKenp5o3Lix1ayzSZMmoWPHjpg+fTo2b96MyMhIlClTBtWqVcPHH3+MJ554Ims7KxUjRoyAu7s7Jk+ejPnz58Pd3R0DBgzAtGnT0KRJkxy7H7Mnn3wSS5cuxX///WfpXaxSpQpee+01vPXWW6muaOvn54d9+/bh/fffx9q1axEdHY2aNWti+vTpGDt2rLhuVFSUZfb9unXrrM5UMN9fykFC83Z5enpi6tSpmDdvHoDk02Xnz5+PXr16Wd2Gj48P9u7diw8++ACrV6/GP//8g8qVK+OTTz7BO++8k2qn3uzZs9GwYUPMnj0b06dPh6urK/r3748pU6ZYDfgByQOLO3fuxEcffYQ///wT8fHxqFevHj799NNUjwEXFxds27YNn3zyCZYsWYJt27ahXLlyGDduHD766KNUexsBYP6SLUhMNGLEI11hsLnfl6hnEhZU58+fx/z588XPLly4YBnM79SpEwcJiYiIigiDSZ8nSfnOvKJev3790jzdOGVPDpD50411YXtGpxvr0zMzOt1Yn16Z2dON9QqZGZ1urE+f1NvbrVs3kfXpk9k93Vh/MDh16pTI+nRjfTpuRqcb6w9Q+vTd+Pj4dO9fn56rPyTu2bNHZPOql2b68WX2dGN9Gqk+nVef/q5PN9anW+vjzTyzwUyfKpXR6cb6+czodOMTJ06IrBdqyOzpxinL8QHr1/PWrVtF1o9fn/6rT082nz5opveXPr719uvTwfX96deTPh7182s0GkU2nwZ6584dPPfcc7h161aaK6kWJeb3+uLyeImKpWurRPzlCDBpR/IA50tNTXinrfozPJXTjYnynDpuM8Tjlogo52T2PRh4oPfhB/3swZmEBVjlypXh6OgIwLrjq0GDBiLrTjU9yNe1a1eRdWdgSEiIyPqg0UXcelBOD4Lo04bM/UNmetBAd/jpQUK9UqHu9NOdZ3Xq1BFZj4XrQVI9SKj3hx5k04MgR44cEVnPcNAddnrQS+/PjH5fd+7pzkV9CpvO+vkyH2dma9asEVkPOutBtuPHj4uckJAgco0aNUTWg5h60Mjb21vkjDr39CCWHgTT26vduHFDZL1//Pz8RNaDtrrzb+3atSIPGTJEZF3wr59f3fGnOwL18awHYfWgre5M1ItF6PeXzZs3i6zfT/TrMSgoSGT9+tGDzHpG2cWLFwFYv66IiIqaJFPq/01ERERUEFifq0FERERERDku5Xc8heV0YyIiIio+OJOQiIiISAkICLB056VHL9JBlJ6UswcTk9K+HhEREVF+4CAhERERkRIQEIBPPvkkw+ultkgHUVp4ujEREREVZBwkLCT0wh47d+4UeebMmSIPGzZMZL0wie7k0x1lmu4U0x16tWrVEvn06dMi64UXhg8fLrJe4VF37ulONL3QhO7cMy/4YqZXytQdeHrhEN0R16FDB5H1Qg26E1F32OlOQ/18tGjRQmTd2RcXFyey7szT+0d3FOoOO/18Z7TQiO7s8/DwEFk/H3phDr3wju4Y1B2ULVu2FFl3Curt09fXC43ozjzdWaj3n369HTt2TGT9fOuOSf38JSYmily6dGmR/f39RT58+LDI+vjRC53oDkv9/qA7RvXCJjt27BBZL1yi949+/ejnR3dY6o5KfTyaf5+dhFSQdO7c2epYJcquJJ5uTERERAUYOwmJiIiIiPJAynHBJJ5uTERERAUMBwmJiIiIiPJAysmpiZxJSERERAUMBwmJiIiIiPKAON2YMwmJiIiogGEnYQGWkJAAg8EAwLrjTXfUjR8/XmTdybZ3716RdceYs7OzyCEhISLrrrBOnTqJrDvndOfhuXPnRNYdZroTUHemubq6ity8eXORM+okvHLlisixsbEi6w423cGoO+Z27dqF9AwYMEDkChUqiKz375kzZ0TW26/3b6tWrUT28vISuVKlSiKvW7dOZN1xp/d369atRdadfrpjTu8v3TmoOx3149m0aVO629e5c2eRdQeiPt5q1Kghsn696Odfvx4uXbokcrly5UTWnX8dO3YUeeTIkene/3///Seyfv316tVL5EOHDomsH3+pUqVE1se7Pv7060d3Fur9qenL9fGqOxP17W/cuFHkMmXKALDeT0RERU2SyZDiv/NxQ4iIiIhSwZmERERERER5IOW4IE83JiIiooKGg4RERERERHkg5exBLlxCREREBQ0HCYmIiIiI8oDoJORMQiIiIipg2ElYgJUvX97SzbZq1SpxWZ06dUR2dHQU+ciRIyInJiaKfPbsWZF1x5yfn5/IupPu2rVrIutOuqFDh4qsOw11p9qJEydEjo6OTnd7dEdhVFSUyLoD7/r16yKvWbNGZN3JV69ePZFtbW1F1vtb71+9PbVq1UJ6Lly4kO793759O937052GuqNOd/TpDrm5c+eKHBoamu7v605BDw8PkXUH5aJFi0SuVq2ayLrD7vTp0yLr40N31+mOPN3JqB+P7uhLUtM59P0/9thjIutOSXd3d5H186WPd72/dCei3r/6eNadhnp7dcemjY38Pkhf39wJaFaxYkWRdQdn3bp1Ra5cubLI+vHrjkq9v4xGo/h/IqKiioOEREREVJBxJiERERERUR4wcXVjIiIiKsA4SEhERERElAc4k5CIiIgKMg4SEhERERHlAbFwCQcJiYiIqIBhJ2EBVqVKFTg7OwOw7szTHWY3btwQWXfW6Y463eHWpk0bkXUHXLly5UTWHW9VqlQRWXcWHjp0SGTd2Tds2DCR9eO9cuWKyLoT0GSSf2nv27dP5Dt37oisO9/0/nFwcBB59+7dImfUybZy5UqRDxw4IHLjxo1F7t+/f7rXN3dTmnl6eoqsO+P08/v000+LHBsbK7Lu6NOdl7pDTj+/Tk5OIt+8eVNk/Xybj2sz3VlZu3ZtkSMjI0XW3XXNmzcXWXfu6cenr6+fL739Ws2aNUU+fPiwyLqDr3r16iLrjk/dMbhu3bp0f1/v78DAQJH19usOz+PHj4usX09jx44VWXdSli1bVuRbt26JrJ9ffTzq/W/usLx79y6IiIqylGcY83RjIiIiKmg4k5CIiIiIKA+YeLoxERERFWAcJCQiIiIiygNcuISIiIgKMg4SEhERERHlAfO4oL2NiTMJiYiIqMBhJ2EB5u3tDRcXFwDWnXC6U0x3Bpp/zyyjTj/dQRcQECCy7ijUnWzff/+9yJ07d073+rrDT3fk+fj4iOzh4SGy7jw7duyYyFevXhVZd/7pTrv9+/eLXK1aNZFbtWolsu6A1B2Ienujo6NF1h1u+vnRz2/btm1F1o9Hd9LVqlVLZN3ZePnyZZFbtmwpsu68K1mypMgGg0Fkvf/1/evf18eXra2tyLoT0tfXV2T9eHXnoe7M8/LyEnnbtm0i6w7DoUOHiqz3V0REhMj6+NbPp36827dvF1kfH1WrVhVZd4zq/a2P51GjRqV7/7rjUT//169fF1kfD/rxZdThqC/X7yfm9wP9OImIihrzYiX2tpxJSERERAUPZxISEREREeUB8yChnQ07CYmIiKjg4SAhEREREVEeME/st7e5P2BIREREVFBwkJCIiIiIKA8kpRgk5ExCIiIiKmjYSViAhYaGWrr3SpQoIS7TnWgXL14UOaMOQDc3N5EPHjwosu6Q052Fd+7cEfnu3bsi647E8PBwkVu0aCGy7oQLDg4WuVmzZiL7+/uLHBYWJnKpUqVEPnfunMi68/DChQsir127VmQ/Pz+R9f45efKkyLpDT+8/vT369vXjrVevnshbtmwRWXcc2tjI8f9Vq1aJrDvqmjZtKrLuQDx8+LDIupNRdzjq7dO6dOki8oEDB0Q+deqUyPr4ad26tchr1qwRWXcWdu3aVWTdydm9e3eRdUel7gB8+umnRdadinp7Q0NDRd65c6fIzZs3F/nhhx8W2dPTU+QqVaogPfr1oO9fd5bqTkd9PB49elTkhIQEkStVqiRyw4YNRd69e7fI+vVev359ANbvK0RERY043ZidhERERFTAcCYhEREREVEe4ExCIiIiKsg4SEhERERElAfM44J2XN2YiIiICiCebkxERESFXuLNm7i54P9we/NmJAQGAiYT7CtWhFu3bij11JOwUzUUmWVKSkL8xYuIPXoMsceO4u6x44g7cwame6ffV54/Hy6tWmZ4O0kxMbh78uS92zmGu8eOJW8vAPvy5VFzy+aMt8VkQuyhQ4jZtQt3Dh1G3IXzMEbego2DA+x8ysG5RQuUeuwxlKhb94Ee290zZ3Dz/37HnX37kBAWBoONDex8ysG1UyeUfuIJ2Jcv/0C3QxlLOZMwhjMJiYiIqIDhIGEBZjQakZiYCMC6A093+umOscjISJF1x1tcXJzIulNNd/rprrDGjRuL7OrqKrLueNMdeN9//73I5k4yM925pjvxzp8/L7K9vb3IuoNtwYIFIuvOPd3BpjvTdIej7oi0s5MvJd1ppx+P7oy8evWqyPrx7NixQ2TdgaifD/38ly1bVmSDwSCy7vD777//RD5z5ozIpUuXFtnJyUnkxx9/XOTY2FiRr1+/LrLuKAwKChJZP5+6I0/v/27duoms92/Pnj1Fvnbtmsj//vuvyMePHxdZH3/69aPp7WnZUg4k6A5Offzp19+JEydE1q9/3TGpn193d3eR+/TpI/KhQ4dE1h2o+vWjj7fffvtN5Js3b4qsOyHNx5t+XyJ6ULHHjuHamLFIVO8tcWfOIO7MGUQuWYKKP/wApwb107iFjN1asRLB772X3U3F1ZfG4M6+fdm6jfPduiExKNjq50kJCYg/fwHx5y8gctFilHl2FLzefNPqPT+l69O/R/jMmfeX3UXybLf48xcQcf4CIhf/CZ+pn6Fkjx7Z2mZKlnKQMJEzCYmIiKiA4SAhERERFVoJoaG4+tIYGMPDATs7lBk5Aq6dOwMAordtw41585EYFoarL72EakuXwF59afLAUgyiwd4ejrVqAolGxJ09m+XbsXF3h1O9eoj190dSJhbuSQxNXpzIvkpllOzZE05NmsLO2xumuLuI2bsXEfN/Q9KtW7gx92fAxhbeb4xL9XbCf5qD8B9/BADYeXmh9LOj4NykCQDgzuHDuPHzzzBeD0fQm2/Bbt48ODdtkrnHSlZSLlySxJmEREREVMBwkJCIiIgKrevffJs8QAigwv++RMnevS2XOTdvjhL16yPw9XEwhofj+nfTUf6zKVm6H8eaNVB2wgQ4NWwAR19f2Dg64vr3MzI9SFiyXz94DB0Kp4YN4HBvlvn5rt0yNUjo1KABPMeOhUv7dlazBJ2bNYN7v34IGDYcxogI3PjlF3g8+ggc1CrkCaGhCJ8xAwBg5+2Nqn/9Bfuy3vfvo1EjlOzTBwGPDkViWBhCJk1CtWVLYbBhnXVOsOXCJURERFQA8S89IiKiLAoMDMSTTz6JMmXKwNnZGY0bN8bBgwfze7OKjcTwcNxatQoA4NK+vRggNCvZuzdc2rcHANxasQKJ9wYUM8upYUOUfvopODVuDBt1ynxmlHpsKNz797MMEGZF1UUL4dqhfZqnETtUrgzPMWOSQ2Iibm+27jmMWr0Gpvh4AIDnKy+LAUIz+7Jl4fnKywCAuNOnEa2qGCjzeLoxERERFWScSViA3bhxw9J9d+HCBXFZdHS0yLoTrkOHDiJ36tRJ5N27d4scf++DgpnuJPT09Ez3/nRn3Ny5c0XWnW3lypUTWXfMDR48WGTdqaY75m7duiWyt7f8sKM72rp27Sqy7nzcp/qifHx8RA4LCxNZd67pjkPdIWk0GkVeunSpyJXUjA9nZ2eR29/7wGtWvXp1kfXxobdHf7D83//+J7LuwNPHj97/en9Vq1ZNZL39uqNQ7z/dAVmvXr10b0/ff/PmzUVu0kSeIufv7y+yPj51h+PYsWNF1seTvr1WrVqle/s6Dx8+XGTd2Xjs2DGRR48eLbLuSFy4cKHIev/pDssDBw6ke396//31118i26iZRbVq1RJZd4qaTHL6zKeffgoAiImJwTfffIPC4ubNm2jXrh26dOmCtWvXwtvbGxcuXICHh0d+b1qOi1z2N4InTHjg63uOHQuve4NLuen2li3AvfdTjyGD07ye++BBiNm5EzAacXvLFpQaOjTXty2/pVxEJeHKVavL7x6//zp37dgxzdtxTfH3xO31G+B271RuypokE2BjMMHGwNONiYiIqODhICEREVEWfPHFF6hUqRJ+/fVXy8+qVq2afxtUDMWmmLXprL6MSSnlZbEHDxWLQcKklF/+pXKKsDHy/pdrdmXKpHk7KS+7oxblosxLHiTk6cZERERUMHGQkIiIirSEhASEhITgzp078PLyslqdO6tWrlyJXr164dFHH8X27dtRoUIFjBkzBs8//3yO3H5B4ta9G0rUX5HudcK+/B9i7q3Ebl++fF5sFuIuXAQA2Li5wc7LK83r2Xt7w8bVFUnR0Yi7eDFPti2/pRzQc6hezepyg/P9MwKMt2/DTp1BYLksxcz0hMBAJMXGwkadTUAPzmRK7vqxMwBJPN2YiIiIChgOEhIRUZETHR2N33//HQsXLsS+ffsQFxdnuaxixYro2bMnXnjhBasqgMy4ePEiZs6ciTfeeAMTJkzAvn378Oqrr8LR0RFPP/201fXj4uLEdkRFRWX5vvOabcmSsFW1DClF/P67ZYCwZP/+8Hh4iOWymL37cGXEiGxvQ41Nm+BQsYL4WUJICADAvlzGKxbb+5RD3LnzSAgJzva2FHRJsbGI+O03AIDB3h5u3bpZXcexeg1EI7mr8M7+/SjZs2eqtyVmD5pMSAgJgWM160FHejBJJsBgSJ7cmciZhERERFTAcJCwALO3t4eDgwMAwEvNkLh27ZrIemaM7hTTHXo1a9ZM9/fDVbG77ihcsULOKNGdeC1bthR548aNIl+6dElk3ZmnO73+VWXpkZGRIleoID846t9v2LChyPrx6o49/fuJiYki79q1S2TdIVexYkWRdedjQECAyLoj7vLly+n+vn68uhOuvJrFo7dvsyqx1x18+vlzVCX9Li4uIuvjRWd9fOj707evO/tu374t8po1a0S+e/euyD3Vh92goCCRdQefPh7089euXTuRdaemPn6nT5+e7vaNHz9eZH086Nd3TEyMyLoDUb+e27Rpk+7tz5w5U2T9+qhRowbSozs/Q+4N1Jjp/as7QPXxbH596/2UVd988w2mTJmCqlWrYsCAAXj33XdRoUIFODk5ISIiAsePH8eOHTvQo0cPtG7dGt9//71Vj+KDSEpKQvPmzfHZZ58BSO5uPHHiBGbOnJnqIOHUqVPxySefZPvxFTQxu3cjdOrnAIASDRvCZ/KneXbfSfdeGwbVU5oag1PydUwxD76KcGEV9r+vkBiUPBha6vHHYV/WehDVrVtX3PjpJwBA+I8z4dqpk9WCLElxcQj/Ub5fJBWD/ZebknDvdGMDkGQywGQyIY31Z4iIiIjyHAcJiYioSPnvv/+wdetWNGjQINXLW7ZsiVGjRmHWrFn4+eefsX379iwNEvr4+FgNEPv6+lotRGT23nvv4Y033rDkqKgoq0WKCpv4gABce30ckJgIu7JlUXHG91YDTU4N6qPayvRPVX4Qqa2+a7o3M9Ngb5/h7xsckq+TlGI2Z1F0a9Uq3Pz9dwCAQ40a8Br3eqrXc2rUCK5duyJ6yxbEnT6Ny089De9xr8Pp3pdWsf7+CPvmW8SdPg2DvT1MCQkAAFNczgzmF1fmTkIbw/1sy0FCIiIiKiA4SEhEREWKXn05LY6OjhgzZkyW76ddu3Y4c+aM+NnZs2dRpUqVNO9Pz5otzIxRUbj60hgk3boFQ4kSqPjDD7D3th7Is3F2RonatXNlGwyOjjDFxloGsNJjik++jh7ELEpi9u5D8PsfAABs3N1R8btvYVOiRJrXL//5VFx9/gXEHjmCu0eP4sozo6yuU6JBAzjWqoVby5Yl366aSU6ZY7o3SGh37wQAowmwTf9XiIiIiPKM9XJ3RERElKFx48Zhz549+Oyzz3D+/Hn88ccf+OmnnzB27Nj83rRcZzIaETjuDcTfq44oP/UzONWvl+fbYR6wMt3J+BRYU2zydQwuGZ+aXBjFHjuOa2PGwBQfD4OzMyrPngVHVUWg2ZYsiSoLfkPZ996FQ01ZM2Dr5QnPMS+hyu//h6QUi5ek101JGTN3EppnDxq5eAkREREVIJxJmIqZM2di5syZlh6vevXqYeLEiejTpw8AYOTIkZg/f774nVatWmHPnj2WXLVqVcybN89yfd0J9iCcnZ3hdG8FwZs3b4rLypQpY3XdlIKDZTG7u7u7yLpzzF6dqqW3Vxfs6464aqrEfNOmTSLrjr26deuKrGfe/P333yLrDkJ9f3Hq9LGLavVKff+6c0/Tj1d35Ont6dGjh8jnz58XWXca2tnJl15CBrNgSqiZILqjUT+/oaGhIjdq1EjkqlWriuzp6Smy7mTUnZanT58WWT8fTZo0EVl36unj5476gK+PR91xl6SWhOzbt6/I48aNE7lDhw4i6w5I/frRnXm6Y1F3BuqOSt1xqTskdSegPr50R2Dv3r1F1sfzkiVLRNbHk96f3dQiBq1atRJZPx49M093PurX086dO0XWXYP69W5+fcTGxiIv3LhxA0eOHIG/v784/TezWrRogb///hvvvfceJk2ahGrVquHbb7/FE088kYNbWzCFTv0cMfeOE88xY1Dy3r+PqUm6cwfx6jWTFY7VqlmdVmxftiyM4eFICAlN47fuSwg2L3Lik+1tKWjizp3D1eefR1JMDAwODqg043vLacMZMTg4oPSIESg9YgSMt2/DeOMGDM7OsPPyguFeWV7cvRmzNi4usFOdrJQ5SfdWNzafbmzk4iVERERUgHCQMBUVK1bE559/blkMYP78+Rg4cCAOHz6MevWSZ0r07t0bv/76q+V3zAuMEBFR/jh//jw+/PBDeHh44LPPPkOpUqVw7tw5+Pv7WwYFjxw5gqCgIJhMJri4uGRrkBAA+vXrh379+uXQIygcbi7+Ezf/7/8AAG49e8LzlZfTvX7sseO5trqxY80auHviBJJu30bi9euwU4t8mSWEhVlmwzmqhZQKu/grV3Bl1LMwRkYCdnao8M3XcGnbNku3ZevmBls3N/GzxPBwxF+5AiD51GODDU9CyQ7LTMIUpxsTERERFRT8Sy8V/fv3R9++fVG7dm3Url0bU6ZMgaurq5gp6OjoiHLlyln+p1dHJSKivPXEE0+gbdu2eOihh1CvXj24ubmhTp06eOGFF7B161ZUqFABQUFB+Pnnn3H58mWrGa2UsZi9+xAyeTIAwNHPF+W/+Nwy2yw/ODVtZvnvO/v3p3m9lJc5NW2aq9uUlxJCQnBl5DNIvH4dsLFB+alT4aZmCmdX1OrVyUV6AEqqWc2UeSbcX90Y4OnGREREVLBwJmEGjEYj/vrrL8TExKBNmzaWn2/btg3e3t7w8PBAp06dMGXKFHinUthORER5Izw8HPXr10f16tURFhaGd955B2PGjBGne//yyy9o2bJloV9VOD/EX7mCwNdeAxISYOvpiUo//ACbe5UY6XFp1RK+p0/lyja5de2CkE8+AZKSELnsb5RU1QNmt/5envwfNjZw69olV7YlryXeuIErz4xCQlAQAKDcxx/BvX/Ozmo1RkcjfO5cAIBNyZIoWcxmzeYG072ZhObTjTmRkIiIiAoSDhKm4dixY2jTpg3u3r0LV1dX/P333/Dz8wMA9OnTB48++iiqVKmCS5cu4cMPP0TXrl1x8OBBy8qVKTv9stJHCCT3tpm7xWzU6T3169cXWXcW6g6w6ur0qugUJeSAdWec7pS7cu9UI7NSpUqJrDvbMnrMulPR1dVV5JSzNgHrzsHWrVuLfOPGDZHd1OlSOuvb0/tXd87pmTK607GkKnLXnYP68V2/fl1kPRNVdxjqFVH1/tedhXr7dGfisWPHRN67d6/IumNOd+rpjsJz586JrI+Hjh07iqwfn+6w1MdfRvu7nOrIevLJJ0U+fvy4yOXLlxd59erVIutuvD6qb61OnTrp5q5du4q8bds2kcuWLSuy7pT09/cXWb++ndTAjO6Y1MeD7nzUnYD69a/3j6+vr8gnTpxId3uGDRsmsj6+9fFnfv51F2Rmfffddxg9ejS8vLwwa9YsfPfddzhx4gSmTZuG2rm0um5xYYyOxtWXxsAYGWnpvLP3yf9uPzsvL7j374dbK1YiZudORK1bj5K9e4nrRK1bh5h7PZnuAwakekpyzN59llOi3QcNQvnPp+b+xmeDMSoKV5573rJwTNn33kWpoUMzfTsJYWGwK1XKqusRAIzRMQh89VUYrye/n5cd/zZsXbmycXbpTsIkjhISERFRAcJBwjTUqVMH/v7+iIyMxNKlSzFixAhs374dfn5+eOyxxyzXq1+/Ppo3b44qVapg9erVGDJkSKbvKzo6WiyEwVPgiKg4CwwMFIsHeXh4WA20p0b3Az7zzDOYOXMmOnbsiIcffhgfffRRrmxvcRD66aeIv3ABAFB6xNMwODvj7tmzaV7frkwZ2Kkvg3KL1+uvI3rHThgjIhD41lu4e+I4XDt3BgBEb9uGG7/OAwDYli4Nr9dfy9Z9RS6Ti2rdTbGIU8zOHUgIDLRkhyqV4dysGbT4y5dx5+Ah8bOkewP5SXfuWN2Ha4f2YmAzKT4eV18cjbhTybMzS/bvD+c2bdJ9PmycneFQsaLVz6NW/YMbv/4Kj0ED4dyiBey8vGCMjkbskSO4uXAhEoOSF0FzHzIEHo88kubt04NLMiUPEJq/ejRxkJCIiIgKEA4SpsHBwcGycEnz5s2xf/9+fPfdd5g9e7bVdX18fFClShWr2VQP6u2338asWbOytb1EREWFeda22ejRo61WhH4Qtra2ePnll/HEE0/go48+Qt26dZGUlASj0ZhTm1psJNwbLAKAG3Pm4sacuele33PsWHhlsKBJTrH38UGlmT/i6ssvw3g9PNXts/XyRKUZM2CfzZV5gydMSPMyfZ/ugwalOkh45+ChNG/HGBlpdVnl+fPFIGFi2HXEHj5syVGrViFq1ap0t9u5RQtUWfBb6vcZHo4bc3/Gjbk/W19oZ4cyz4yEl1oxnrIuCfcGCc2nG3OQkIiIiAoQDhI+IJPJZHWKqtmNGzdw9epV+GTx1Ksvv/wS77//viXfvn3b6kMyEVFxcfLkSVER4OHhka3bK1WqFKZPn47Ro0dj3Lhx6NatG8aPH4+xY8danSpNhZNTo0aovnIlIn77DdGbNltm9NlXrAjXbl1R+umnYadqGghw69kDpvg4xOzZi/irV2C8EQGDgwPsy5WFS9t28HjkYTjWqpXfm1mk6E5CrltCREREBYnBZOJ3mNqECRPQp08fVKpUCbdv38aiRYvw+eefY926dWjTpg0+/vhjPPzww/Dx8UFAQAAmTJiAK1eu4NSpU1bdd1kRFRUFd3d3fPTRR5ZuMd3pdfXqVZEv3DsNzEx3lOlOOj2gqTvbdMefra2tyLrTUHfM6c44ff2z6rQoZ2dnkZOS5J/NuqtMd7rpDjndMaj7yPT+S3lqIwC0aNFC5IwGgNeuXSuy7nDsq8r0M+rk04PEulNOv2z1zCj9/OtBljNnzois92/lypVF1p1/+v7149Xbqxf1CQkJEVkPwOv9rTsqdeef7gTUt687JfXxp+9fzwpOuWgRABw5ckTk9u3bi6w7JPXrS+8P3fkXmOKURcC6M1K/XnQHaUREhMid7516aaZfj/v27RNZd2rqDsNbt26J3LBhQ5H18dWgQQOR69WrJ/KcOXMAJB+Hc+bMwa1bt6zeQ3LSP//8g7feegu3bt1CcHBwxr+QS8zv9bn9eIkoH12Tszz7LTbgVhzQqzow19+AXSOSUCHln44V++ft9hGl5lr6s5Ot8LglIso5mX0PBh7offhBP3vYpHlJMRYaGoqnnnoKderUQbdu3bB3716sW7cOPXr0gK2tLY4dO4aBAweidu3aGDFiBGrXro3du3fnyAAhERFl34QJE6wGP8369euH48ePY/z48Xm8VURU3Jk7CblwCRERERVEPN04FT//nEovzz1OTk5Yv359Hm4NERFlVnBwMPr16wdbW1v0798fAwcORPfu3S2zPO3s7DCOPWtElMfMqxuzk5CIiIgKIs4kJCKiIufXX39FaGgo/vzzT3h4eODNN9+Ep6cnhgwZgnnz5iE8PDy/N5GIiiFLJ+G9zJmEREREVJBwJmEBduDAAdjb2wOw7vBq27atyLpjTHfK6VOh9Qdk3WmmO8dKqcL31q1bi7x8+XKRdSea+XGY6c68pk2bpnv/ujNO377uwNOdf/rx6v2lO+t0T1lGHY0nTpxId3s2bNggsu6I052J+vnQj0c/H7rDT3fi6cUZGjduLLJ+/NeuXRN5zZo1IusOQH17en/px6/3zxNPPCGy7sTT26c7EXUHnu601M+/vn93d3eR9fHYrl07kXVHn368evvLly8vsoODg8i6Y3D48OEi607S06dPi1yxYkWRD6dY+RRIfi9JSR8fXbp0EVl3VCYkJKT7+7oDMiYmRmTdAXn79m2RmzdvDsC6WzS7DAYDOnTogA4dOmDatGk4deoUVq1ahTlz5uDFF19Eq1atMGDAAAwfPhwVKlTI0fsmIkqNeXVjnm5MREREBRFnEhIRUbHg6+uL8ePHY9euXbh27RpGjBiBHTt2YOHChfm9aURUTCRxdWMiIiIqwDiTkIiIiozY2FhERERYzQw8ceKEmJHt5eWFZ599Fs8++2xebyIRFWOmewuXsJOQiIiICiLOJCQioiJhyZIlqF27Nvr27YuGDRti7969lsueeuqpfNwyIqJk5k5CQ4pMREREVFBwJmEBVq9ePUv3l+70W7duncguLi4i646zy5cvi3zlyhWRa9WqJbLuJAsKChL54sWLIh89elRk3ZGnt79ly5YiN2nSROQjR46IrDvVNN3hV7JkSZF155+5A81Md9bpTr6bN2+KrDvvdCdfRh2KusNNd9T5+vqKrDsQS5QoIbLuKNT74+DBgyLrjkr9+7ozUh9fuiNw3759IpcpU0bk1157TWT9+AMDA0XW+6N69eoi79y5U2R9vOnHp5+vhg0biqz3j5eXl8i6c1Lfn+4ADA0NFVk/n7rj7/z58yLr15vuIPT09BRZH2/69a47OPUsO90hqPef7jj95ZdfRK5fv77I1apVE1m/H+nXg/n51+87mTV58mQcOnQIXl5eOHDgAEaMGIH3338fjz/+uFWPJRFRfrjfSWgCYGAnIRERERUoHCQkIqIiISEhwTLA27x5c/z7778YMmQIzp8/bzWwTUSUH5JMauGS/N0cIiIiIoGnGxMRUZHg7e0tZjWXKVMGGzduxKlTp6xmOxMR5QerQULOJCQiIqIChIOERERUJCxYsADe3t7iZw4ODli4cCG2b9+eT1tFRHSfpZOQC5cQERFRAcTTjQuwWrVqWbq8dKfXmjVrRK5SpYrIuvNr8+bNIpcuXVpkd3d3kcuVKyfyjh07RHZychK5Tp06ItvYyPFn3fmmO++mT5+e7vbofOfOHZH1qYS6Y1F3tm3ZskXkpk2bivzQQw+JvGfPHpF1J6O+P90JqDvidAdfs2bNRC5fvrzIukNSd94dP35cZN0hl5iYKHLdunVFTrnAA2DdUag7HHWHnn48ugNSd+idOnVKZP386dvTnYd6/2zcuFHkGjVqiBwWFiay7nTUHZbXr18XuVKlSiKnXCUXsD6e9u/fn+7v6/175swZkXUHpB740h2F+nhr3769yPp41R2bV69eFVkfz/r6+vGbu1PN9OPNqGuwd+/eAJK7E+fMmZPuddNTsWLFNC9r165dlm+XiCinJJmSv6HnTELKjqioqEz/jv5bh4iIKDUcJCQioiLt7t27OHr0KMLCwqwWsRkwYEA+bRURFUeW041TZKLM8vDwyFTXrsFgwNmzZ60WgiMiItI4SEhEREXWunXr8PTTT1utYA4kf2gyGo35sFVEVFzdX934XuYgIWXRkiVLrM4MSo3JZELfvn3zYIuIiKgo4CAhEREVWS+//DIeffRRTJw4EWXLls3vzSGiYs6qkzB/N4cKqSpVqqBjx44oU6bMA12/evXqsLe3z+WtIiKiooCDhAWYvb295R903WGmOwN1Z5j+Q+DGjRsid+jQQWTdAac753Rnnz7FQd+/7hx0cHAQWXfk6Q67Y8eOiezh4SHy7du3RdYdfLqz7uTJkyLHxMSkuz26w+3SpUsi605Gvb91x1xCQoLIerAiODhYZN25uGrVKpH18aC72HSnnX4+dIeh7qnRHZC6806fsqn3x4EDB0TWnYq6o1J77LHH0r1/Hx8fkXUHnj4eQkJCRNavH935qY9/PdtMd3Tq46dt27Yi6+NNdxbqjkT9jb+/v7/I+vWmOyb161l3huqZB/r51PenOx7160sfL+fOnRNZPz+6S8m8v/VxnxPCwsLwxhtvcICQiAoE8+nGXLiEskP/XZoR/XcfERFl3dGjRzP9O35+frCzKxzDb4VjK4mIiLLgkUcewbZt26wGOomI8kOSCTCAnYRERESFVePGjWEwGGB6wG/6bGxsClUvLAcJiYioyJoxYwYeffRR7NixAw0aNLCa9fvqq6/m05YRUXFkAjsJKefFxMRg+/btuHLlCuLj48Vl/HeOiCjn7d27F15eXhlez2QyoX79+nmwRTmHg4RERFRk/fHHH1i/fj2cnJywbds2UZVgMBj44YmI8pRJn26cv5tDRcDhw4fRt29f3LlzBzExMShdujTCw8Ph7OwMb29v/jtHRJTDOnXqhJo1a1pVoqWlY8eOVvVcBRkHCQuwa9euWbrKdKferVu3RNadYG5ubiLrTsFr166JrDsLfX19083693UH2t69e0XWfWD6fHxbW1uRq1WrJrLuOKtQoYLIumPtl19+EVl37vn5+YmsOwj19uns6ekpckadg5GRkenenu6k0515PXv2FFl3+ulOPL1/dCekfr50x5/unAsKChI5OjpaZD3VWncs6v2jOxMbNmwocpMmTUS2sbERecOGDSLrzj09ldvb21tk3cHn6Ogost4f+vjT39Lr/a3vX9+f7uS7fv26yLoTUHdw6v2tj6datWqJfPny5XRvTx9/oaGhIuv9r7Pev/r9R79/6fvft28fAOvjJCd88MEHmDRpEt59912r7SYiymtJ9xYu4UxCyinjxo1D//79MXPmTHh4eGDPnj2wt7fHk08+iddeey2/N4+IqMjZunVrpq6/Zs2aXNqS3MFPTEREVGTFx8fjscce4wAhERUI5oVLOEhIOcXf3x9vvvkmbG1tYWtri7i4OFSqVAnTpk3DhAkT8nvziIiokOFMQiIiKrJGjBiBxYsX84MSERUISabkb+g5SEg5xd7e3lKlUbZsWVy5cgW+vr5wd3fHlStX8nnriIiKvmvXrmHlypWp9sJ+/fXX+bRVWcdBQiIiKrKMRiOmTZuG9evXo2HDhlYLlxTGf7iJqPCydBKmyETZ0aRJExw4cAC1a9dGly5dMHHiRISHh2PBggVo0KBBfm8eEVGRtnnzZgwYMADVqlXDmTNnUL9+fQQEBMBkMllVvhUWHCQswC5dumTpktMdcbpTT3cK6hV0jEajyPPnzxe5Y8eOIpcpU0bkEydOiFylShWR69WrJ3JYWJjImzZtErlz584ib9++XeS7d++KrDv6atSoIXJISIjIuqNPd9zpklHdoag71lxdXUXWnXL6VEb9fOlORN35pjvt9DcQuuNOdxzq+z979qzILVq0EFl32umOS91BqJ8P3bEXHh4usu6c089Xq1atRNYddsuXLxdZdyDqjkV9+7qzUXd2Ojs7ixwQECCy7sbT+1t3KuqVrfT26aJafTzo40nffrdu3US+cOGCyLozUT+/+vVx584dkfXzqzsK9fOtH58+3vQ/iPr29fNpfv+Ii4vDihUrkJOOHTtmef0fP348R2+biCizkiA7CTlGSNn12WefWf7u+vTTTzFixAi89NJLqFmzplVHNxER5az33nsPb775JiZNmgQ3NzcsXboU3t7eeOKJJ9C7d+/83rws4SAhEREVWZktFiYiyk1JanVjnm5M2dW8eXPLf3t5eRW6gnwiosLs1KlTWLhwIYDkxSRjY2Ph6uqKSZMmYeDAgXjppZfyeQszj03uRERUZE2dOjXVmRS//PILvvjii3zYIiIqzpJMBi5cQjmqa9euVmc8AMlnKXTt2jXvN4iIqBhxcXFBXFwcgOSzCVOe8aXPtissOEhIRERF1uzZs1G3bl2rn9erVw+zZs3Khy0iouLK3ARhY7j/BzgHCSm7tm3bZlVTAyRXfezYsSMftoiIqPho3bo1du3aBQB46KGH8Oabb2LKlCkYNWoUWrdunc9blzU83bgA8/Pzs3SZ6U66ZcuWiaw7wx5++GGRr1+/LnLbtm1FbtiwocgbNmwQ2dbWVmTdWRgRESFyhw4dRNYddRUrVhT50qVLIm/btk1k/Xh0p5nudKtWrZrIujNOd+DprDsNdUeh7qy7efOmyMHBwSLrzj+9/3VHnL+/v8j68erOudq1a4usO+vOnz8v8s6dO0Xu1auXyPp40Z2X+nioWbOmyHZ28q1Fd0Dq/fvvv/+KrLdfP7+6A1PvH90xqDsBS5cuLfKhQ4dE1h2GukNQdwbqDj/9x/rRo0dF1t14lSpVEjnlqUOAdeeieRXDtOgOUt2RqY93ffz5+vqKrN9f9POhOwf1/evf1x2a5o5I/fOcEBISAh8fH6ufe3l5Wb1OiYhyk3lA0JDidGMuXEJZlfJvi5MnT4r+YaPRiHXr1ll1XhMRUc76+uuvLZ9FP/74Y0RHR2Px4sWoWbMmvvnmm3zeuqzhICERERVZlSpVwq5du6y+ONi1a5fV4CkRUW6yDBIixenG+bY1VNg1btwYBoMBBoMh1dOKnZyc8P333+fDlhERFR8pJ3M5Ozvjxx9/zMetyRkcJCQioiLrueeew+uvv46EhATLh6jNmzdj/PjxePPNN/N564ioODEPCLKTkHLCpUuXYDKZUL16dezbt0+cNePg4ABvb2+rMz+IiChnVa9eHfv377c60zIyMhJNmzbFxYsX82nLso6DhEREVGSNHz8eERERGDNmjOU08BIlSuCdd97Be++9l89bR0TFiegk5CAhZVOVKlUAWFd6EBFR3gkICLCqWgKAuLg4BAYG5sMWZR8HCQuwY8eOwcHBAYB1J5yjo6PI5j8UzHTHWmhoqMiVK1cWWXeo6U42/QeI7nxzdXUVef/+/SLrTjrdWadP+3vkkUfSvf2TJ0+KbO40M4uNjU33+rpj8OrVq+lub6lSpURO2fuSWtbPj+6Q028k+vnSt6cXXtCddnv27BFZ76+DBw+me7nu9NPdcDrrzsImTZqI3KhRI5F1x6XuHPT09BTZfNybpfbNTErmslizdu3aiaw78/Qbtu7808e7PlW1QYMGIuuOSL0/dWenPr50Z6J2+fJlkY8cOSKyn5+fyLrTUO+fU6dOiaw7NnVHqO4o1Ct1XblyRWT9fqM7O/Xza359ZNS1mBUGgwFffPEFPvzwQ5w6dQpOTk6oVauW1WuUiCi3mVKcbsxOQsqOlStXPvB1BwwYkItbQkRUPKV8H16/fr0YPzEajdi8eTOqVq2aD1uWfRwkJCKiImfChAkYNGgQWrZsCSB5YLxFixb5vFVEVJwlpTKTkGOElBWDBg16oOsZDIZUZ7gQEVH2mN+HDQYDRowYIS6zt7dH1apV8dVXX+XDlmUfBwmJiKjICQ4ORr9+/WBra4v+/ftj4MCB6N69O2cQElG+EZ2E5p9xlJCygKcYExHlL/P7cLVq1bB//36rM+MKM5uMr0JERFS4/PrrrwgNDcWff/4JDw8PvPnmm/D09MSQIUMwb948q1OmiYhyW8qZhAZ2ElIu0PUqRESUuy5dumQZICwq78GcSViARUVFwd7eHoB1h1z37t1FDgoKEll33OlON90ppw/opk2biqw7CBMTE0XWfSczZswQOS4uTmTdeaY731q3bp3u/R0+fFhk3WWmO9l0B52/v7/IuhNRdxxu2rRJZN3hpjv79GpyderUEfnWrVsi6+dP59q1a4usOx2Dg4PT3Z6zZ8+KXKtWLZF1B6XePyVLlhS5dOnS6V5fd/DduXNHZH086udPd0r26tVLZN3JGBYWJrLe/xll/fzUrFlT5GvXrons5uYmsv7maN68eSLr469x48bp3v7evXtF1q9HfXzq/RETEyOynnGgOxF1R6HenoYNG4psfl8y0x2TuhNSP/+6A9W8P/VxnV0GgwEdOnRAhw4dMG3aNJw6dQqrVq3CnDlz8MILL6B169YYMGAAhg8fjgoVKuTofRMRaZZOQgM7CSnnGI1GfPbZZ5g1axZCQ0Nx9uxZVK9eHR9++CGqVq2KZ599Nr83kYioyEpKSsKUKVOK1HswZxISEVGx4Ovri/Hjx2PXrl0IDAzEiBEjsGPHDixcuDC/N42IigHRSah+RpRVU6ZMwbx58zBt2jSxMFiDBg0wd+7cfNwyIqKib/LkyUXuPZiDhEREVGTFxsaKmYyXL1/Gt99+i8OHD+PZZ5/FihUr8NZbb+XjFhJRcZHawiUcJKTs+u233/DTTz/hiSeeEGdKNGzYEKdPn87HLSMiKvqK4nswTzcmIqIia+DAgRgyZAhGjx6NyMhItGzZEg4ODggPD8fXX3+Nl156Kb83kYjy0dGjRzP9O35+flmqR7AMEiLFIGGmb4VICgwMtKpJAZJPgdP1OERElLOK4nswBwkLsEcffdTSPaY719atWyey7vzTnXxVq1YVWXeK6U453UGoO+x0R+L+/ftF1p11urNNn96nt6devXoiV6xYUWTdUag7/nRnnO5cM6kSoLp164ocEhIi8o0bN0TWbwS6s08/H/r5K1eunMi6c1B3wOlFFvSHk4w643Qnoe68q1y5ssj79u0TWe/fcePGiaw77H799VeRR44cKXKpUqVEXrFihcgpp2oDwPnz50XWnXz6+Tt27Fi6v6+PH3286U5H3fGpO/h014Tu3NPPn349GI1GkU+ePCmyPt50f56+vn78+nhr0qSJyC4uLiLr4//EiRMi68ev3190h2KJEiVETmtVRr3fc8KhQ4fwzTffAACWLFmCcuXK4fDhw1i6dCkmTpzIQUKiYq5x48YwGAxWfxekxcbGxtI3lFnsJKTcUK9ePezYsQNVqlQRP//rr7+s/r0nIqKcVRTfgzlISERERdadO3csXxps2LABQ4YMgY2NDVq3bo3Lly/n89YRUUGwd+9eeHl5ZXg9k8mE+vXrZ/l+zF+P8HRjykkfffQRnnrqKQQGBiIpKQnLli3DmTNn8Ntvv+Gff/7J780jIirSiuJ7MAcJiYioyKpZsyaWL1+OwYMHY/369ZZZsGFhYVYzgImo+OnUqRNq1qxptep7Wjp27AgnJ6cs3Zfx3ihhykFCziSk7Orfvz8WL16Mzz77DAaDARMnTkTTpk2xatUq9OjRI783j4ioSCuK78EcJCQioiJr4sSJePzxxzFu3Dh069YNbdq0AZA8q7CwngJARDln69atmbr+mjVrsnxf5lmDtgZ2ElLO6tWrF3r16pXfm0FEVCwVtfdgDhIWYAEBAZYur6ioKHFZUFCQyK1atRJZd7alXGkHAKKjo0WOiIgQ+dy5cyLrjjLdoXfw4EGRGzRoILL+hr5t27Yi6w5Bvb26E09vv+480x1t1apVE9nb21tk3dmXUYfbpUuXRL548WK6v687Hg8cOCCy7tRr3Lhxutunn/+rV6+KHBsbK3KdOnVE1h2UX3/9tch6f+vOwpUrV4qsS1n18687FK9fvy6yfvx6+//991+RdQdjixYtRNavF33/BnMZ1D26E/C7774TuWfPniLr7d+9e7fIujNQ319kZKTIelaKfv4dHR1F1seb7ljU++fmzZsi6+ff3d1d5CtXrogcHBwsst6/zzzzjMh6IQD9+tfvV+bOzpiYGOS0Rx55BO3bt0dwcDAaNWpk+Xm3bt0wePDgHL8/IqK0pFzd2KB+RkRERIXXgQMHcOrUKRgMBvj6+qJZs2b5vUlZxkFCokKqrNNNhMaWSvPy8q5RCIrm6ZRUPE2YMAGDBg1Cy5YtUa5cOauB+5YtW+bTlhFRQfPGG2880PX0F2qZZUw5SMjTjSkbSpUqZfUFZFr0RAAiIso5165dw/Dhw7Fr1y7LxIjIyEi0bdsWCxcuRKVKlfJ3A7OAg4REhVAzr/MYVXcLVlxqiQ3XGltd3r/GKTxW9yhmHG6DPUGVrW+AqIgLDg5Gv379YGtri/79+2PgwIHo3r271axMIqLDhw9neJ0HHZBJj3lA0NaGC5dQ9nz77beW/75x4wYmT56MXr16WSo1du/ejfXr1+PDDz/Mpy0kIioeRo0ahYSEBJw6dcpy9t6ZM2cwatQoPPvss9iwYUM+b2HmcZCQqJDxsAnBo3W3wNZgwpDqe+FmfwcLzzS3XN6nylE8WusIAODlJrtxN9EOl+Lc07o5oiLp119/hclkws6dO7Fq1Sq8+eabCAwMRI8ePTBgwAD069cPnp6e+b2ZRFQAZLaXMKvMMwkNAGzu/YyDhJQVI0aMsPz3ww8/jEmTJuHll1+2/OzVV1/FjBkzsGnTJsuCXURElPN27NiB//77T9R71alTB99//z3atWuXj1uWdRwkLMCOHj0KBwcHAICvr6+4THdp2djYiBwYGChylSpVRNadc6VLlxZZn4qnO+90d5juhNOddFu2bBFZdxrqx6c773SH4LVr10QuU6aMyLrjUD8e3WGoO9t8fHxE1h10uhPx9u3bIuvBB70/Lly4ILLuONSdcS4uLiI71GmJIdX3AgB6VDoG16RrGL+mHsa0uYhHa93vK/z3XAm82fxf/OifiD3BVVDeJQpBMSWtZlPpx6/p42Pt2rUi6069t956S+Tz58+LrJ+fjDoiu3fvLrKe0bF+/XqRdYeg7sTTnYdxcXEip+yuA2D5Zt5MP38nTpwQWXcc1qtXT2Td8aePJ93RqPevvv3Tp0+LrI8XLy8vkWfPni2yPhVXd4Lq12dGrx/dmai3R3eEVqxYEYD16yi7DAYDOnTogA4dOmDatGk4deoUVq1ahTlz5uCFF15A69atMWDAAAwfPtyqR7K4WH8iBG6OdmhbkwOmRLnNaJlJaOJMQsox69evxxdffGH18169euHdd9/Nhy0iIio+KleubNXPDyR3xhfWzxccJCQqhDZcaww3+zvoUekYAKBNlZvY/MIuONje/7Sx9YwTutRJHgwb22Q3qnvcQJ9qZ/HD4TZYGsiXPhU/vr6+8PX1xfjx43H9+nWsXLnS8oWEHtguLl5ckLzoVMDnD+XzlhDln7zqJEy5urGlkzBbt0iU/EX533//jbffflv8fPny5VZfohMRUc6aNm0aXnnlFfzwww9o1qwZDAYDDhw4gNdeew3/+9//cux+zkcA2y4Dzza+/zdEbuFIAVEhtfRSW/g4R6J+meRZnikHCC9ct7MMEALAsfBy6FfjDIDkAcP955vhSmTyCth3nO+kf0ecYESFWGxsLEwmk2XF98uXL+Pvv/+Gn58fnn32WTz77LM5cj9Tp07FhAkT8Nprr4muKCIq+PKqkzApyXxb9zsJuXAJZdcnn3yCZ599Ftu2bbOc+bBnzx6sW7cOc+fOzeetIyIqevTiUTExMWjVqhXs7JKH1xITE2FnZ4dRo0Zh0KBBOXKffRcZEJ9kQOsKSajvnfH1s4ODhESF2IwTffFdu5/haJsofl7D635OnlF4//TWP880tAwQhnmH4bTfaeA2gF2p3EE7AN2AiEMRKB1UOpUrEBVsAwcOxJAhQzB69GhERkaiZcuWcHBwQHh4OL7++mu89NJL2b6P/fv346effkLDhg1zYIuJKK/ldSehrYELl1DOGTlyJHx9fTF9+nQsW7YMJpMJfn5+2LVrF1q1apXfm0dEVOTkx4SA+KTkPxyi4nP/vjhIWIBVq1bN0v1VubJcoVafPqA71nTHW1RUlMiPPvqoyDNnzhRZd6TpTjjdKbd8+XKRe/fuLXJQUJDIumNNdyTqDsQ7d+RstyTz1/Fp/L6548zs0KFDItvb24usO9b++usvkXXn2tChQ0XW+0t3NuqOuY4dO4qsO+VCQkJE1kunm/d/jwqHrQYIU4pNsBEzCr/fUQG/HbDHqVMHkVQ6CbGdY5Pb03sA5SuUR7nz5Szbf8P3BsIbhwMAApoGIGBPAJAcLd+SmDVv3lzko0ePiqxnYOj9r6+vOzT18VS1alWR33//fZH18Z5RB6d+PekOQd2Vp1+PuqNQH5/6+DKpqSP69XDy5EmRExPlc6w7BvX268dbqlQpkVu3bi2y7vh0dXUVWR9/5ll5Zhs3bhRZd4DqjkI9a8fc0ahf5znh0KFD+OabbwAAS5YsQbly5XD48GEsXboUEydOzPYgYXR0NJ544gnMmTMHkydPzolNLnQuhcfg1YWH8c1jjVHT2zXjXyAq4MLDw2EwGHL8VM2kVAcJDeBJx5RdrVq1wu+//57fm0FEVCykXDwqr91N+6N/jrHJ+CpEVJCUd00eAOtR4TAGV9tj+XlqsxGc7O8PViUPEN5fkMUmwgb2O+4P1gX5BSGkZvLgZMoBQgDAZlgGCIkKkzt37lgG1Tds2IAhQ4bAxsYGrVu3xuXLl7N9+2PHjsVDDz1k9UVKcXIyKArHAm/hRNCtjK9MVEBFRkZi7Nix8PT0RNmyZeHt7Q1PT0+8/PLLiIyMzJH7MP87bTAkr3AMcHiQsi4qKuqB/kdERDkvv96D82KQkDMJiQqRNuWv4JVme3EqsiLql74/23L35VJoUyXtFYojY23FAKGZw77k1bMTOiWvyBTkF4TQmqEwOtxfPdfT3xPhuzhCSIVTzZo1sXz5cgwePBjr16/HuHHjAABhYWEoWbJktm570aJFOHToEPbv3/9A14+LixMraReVD29GlqpRIRcREYE2bdogMDAQTzzxBHx9fWEymXDq1CnMmzcPmzdvxn///Wc1KzuzjKksXMLTjSmrPDw80u3KNJlMMBgMMBqNaV6HiIiyJq/fgx1sTYg3GgruIOEjjzyC5s2b49133xU///LLL7Fv3z6rUzWJKPvKu0bhlWZ7YWtjEgOExyMqoU2Vq+n8JuDhZMTTzYPTHCj08vJCkF/yKeF6gLDMqTII5zRCKqQmTpyIxx9/HOPGjUO3bt0spe4bNmxAkyZNsny7V69exWuvvYYNGzZYnU6elqlTp+KTTz7J8n0WVMZ7p9cncbCQCqlJkybBwcEBFy5cQNmyZa0u69mzJyZNmmSpLsgqy+nGNuwkpOxL2aVpMpnQt29fzJ07FxUqVMjHrSIiKh7y+j24hB0QbwRiC+og4fbt2/HRRx9Z/bx37945usxzcVerVi1L95fuvIuIiBBZFxPrTrQvv/xSZN2xpzvhdCeb7szTHXT68g0bNog8ZMgQkatXry7y5s2bRdYdfnXq1BFZd5cdPHhQZN0JqDvUMhrRd3d3F7lWrVoimzvUzPTzobPurNOdkXp7O3ToIHK7du0AAGfiveEX/5vl50HRbmLAMD2vdAhEYmIiftnjhdq1a4vLqsRXwerE1UiwS7D8zDbONrmj0B4oV66cuL7en/pUrEaNGomsO/z+/vtvkfXzod9cd+7cKfKVK1dE1p15586dS/f2HR0dRb506ZLIuoOwfv36Iuv9l5CQIHJoaKjI/v7+IusZZPr41q/fgIAAke/evYv06E5Lff2HHnpIZP3+ost49YfmLl26iDxgwIB0b8/FxSXdvHv3bgAQs+xyyiOPPIL27dsjODhYHJfdunXD4MGDs3y7Bw8eRFhYGJo1a2b5mdFoxL///osZM2YgLi4Otra24nfee+89vPHGG5YcFRVldewWRsZ7h6s6bIkKjeXLl2P27NlW73VA8r9/06ZNw+jRo3NskNDAhUsoB3Tq1ElkW1tbtG7d2upvbCIiynl5/R5cwhaIQgE+3Tg6OhoODg5WP7e3ty8yp08RFUTnHR4GAMtAYXnX22le99BVZzStJAdTx3VJHrxacLC8+PlZ77NigBAAjI5GXK9zHV5n5CIZRIVNuXLlrAa69eIqmdWtWzccO3ZM/OyZZ55B3bp18c4771gNEALJg9N6gLooSLo3ysGZhFRYBQcHW305mlL9+vWtvnzJCvOAesqFS/iyISIioow43VtKoMAOEtavXx+LFy/GxIkTxc8XLVoEPz+/HNkwIkrdeYeHcezYMTxW53Ca15n+b3nM318OI1qEYEz7IKw/5Y6H6iUvKvBKp1DsuFQaARHJp0iG1gxFUPn7q0/bJ9pbBgxDGyQPKhrC0+5bICrIUs7cS8lgMKBEiRKoWbMmBg4caLXidUbc3NysZpi6uLigTJkyVj8v6hLvDRJyrIMKK09PTwQEBKBixYqpXn7p0qUcWenYPNnWJsXCJZxJSERERBkpcW/+QXS8Abn9V3eWBgk//PBDPPzww7hw4QK6du0KIPl00YULF7KPkCgPrL5UHw9VOwFXh3jLz2ITbOFgm4T5/rUwf78rAGD+/nLYfsEDZ0NscDasBF7pFIp3V1aSA4T17g8Q+gX5oXZYbey23W0ZIAxtEArXGFe4+rvm4SMkyhmHDx/GoUOHYDQaUadOHZhMJpw7dw62traoW7cufvzxR7z55pvYuXMnv+TKIvPCJSZOiaJCqnfv3nj//fexceNGqzNl4uLi8OGHH6J3797Zvh/zKfk2KWcSZvtWie5Lr0SfiIhyV26+B5e4N3IXk5D+9XJClgYJBwwYgOXLl+Ozzz7DkiVL4OTkhIYNG2LTpk1W52ZT1sXFxcHGxgaAdceY7njTHXm6I65atWoiz58/X+SqVauKrDvnzNthdvLkSZFHjRolsl41VHf86dvTs3h0p1lYWJjITZs2FVkvHKBPe796Vfb26evb2cmXgu4SqFmzpsi6U69bt24i61MNf/vtN5F1R57uJNTbpzvuHmsQIAYIAcDJ3oj9tzvgRtn+8PTcZPl5NIAaNZyw/XoNnF9/G4Hxbhg5sitCjaH4POpzy/XMA4QAUOpEKSQZk3C98fXk7WsVgyZOTeB6N3mgUHfw7dq1S2TdOWdvby+y7n3Sp37q/aM7/XQHpt7/+njS+y8oKEhkDw8PkfVsEn286s5CfbzeuHFDZN0JqDsuGzRoILLu5svoeMmoc1NffurUKZF9fX3T3R69/fr1pF/f58+fF1mfYqvfn1xdk48r/TrMCeZZgr/++qvlfSkqKgrPPvss2rdvj+eff96ysMn69euzdV/btm3LgS0ufIxG88Il+bwhRFn0ySefoHnz5qhVqxbGjh1r6UU+efIkfvzxR8TFxWHBggXZvh/zTEJbdhJSDtB933fv3sXo0aOt/gZbtmxZXm4WEVGxkNfvwY73PiZFx6d/vZyQ5U9kDz30kFX5PRHlvkb269Cywg5LjkksARe75EGcFm47cCfJFZvS+N3A226W/y5rWxZPuTyFBTELUDeormWA0KzM6eRTq643vI5GFxpZBgiJCpMvv/wSGzduFF9clCxZEh9//DF69uyJ1157DRMnTkTPnj3zcSvzR07N/DPeuxl2ElJhVbFiRezevRtjxozBe++9Z3ltGAwG9OjRAzNmzMiRRYaMqcwk5CAhZZX+gu7JJ5/Mpy0hIip+8vo92OHeHKQ7BXUmIZA8E2TJkiW4ePEi3nrrLZQuXRqHDh1C2bJlc23ZZ6LirpH9OrR0uP9txOrADtgW1gr9qp9AJ/e1AIBO7mtxvn4t/Hm8Wlo3Y9HUoSkq2FbASf+TqV5e5nQZuAa6wsfTJ2ceAFEeu3XrFsLCwqxOJb5+/bplxrGHhwfi4/Pga7kCJqcGJ4xJnElIhV+1atWwdu1a3Lx5E+fOnQOQfBZBZvtK02N+jdgYklc4BrhwCWXdr7/+mt+bQERUbOX1e7D5b4gCe7rx0aNH0b17d7i7uyMgIADPPfccSpcujb///huXL1+2OrWSiLLP3RCM5vbLLdk8QAgA+6K7AIBloHBkk/PYfcUbV6NcrG5HK2tbFieR+iAhADjedgQ8s7HhRPlo4MCBGDVqFL766iu0aNECBoMB+/btw1tvvYVBgwYBAPbt24fatWunf0NFUE7N/DPPjuJoBxUFpUqVyvbq52kx/4Fva5Ni4ZJcuSciIiIqShLv/cFQYE83fuONNzBy5EhMmzYNbm73T1/s06cPHn/88RzbuOLOw8PD0iWmv8m+cOGCyBnNgvH29ha5devWIutOQ91ppjvSdClnQECAyD169BB59uzZIuvT3Dp27ChyuXLlRNYdaGvWrBE55XEIJK9UmJI+TUhvr+6U06uT3rx5U2S9fy5evCiy7jTUXZ2xsbEiHz16VGTdwXjp0iUAwPVy7TC64U5sDu+Cvbfbwckp+fIaNWrgBmrgeGIZ+CX+gQOOr6Pv8HaW37927Zq4Pd1xqfdfRs+H7hjUHYxnz54VWXfoNWnSRGR9/CUmJqabdSen7sy7fPmy5b/L2F+HjX0VcbmPz/2ZkaVsQuHsIzsndUehPl6PHz8usn7+WrVqJfKZM2dE1vtfn+qqOwP189OiRQuRdQdnUpL82KmfH328Ll26VGTdKdqwYUORdXef7tCMiIgQuXPnziIfO3ZMZPPzqbsfc8Ls2bMxbtw4DBs2zHIc2dnZYcSIEfjmm28AAHXr1sXcuXNz/L4LOmMOTf3jTEIqzIYMGYJ58+ZZve+l5YknnsA333xj9XfVgzCfmm8Dnm5M2ZOXxy0REUn58R5s/lK+wM4k3L9/v9WgDwBUqFDB6sMvEeWcvSFVceV2KTh6NUr18rN2gxFk0wLRNhVTvby48XM5hkHeS7Arug/2x3S1urxpiY1o47wa+42vI9C2XSq3QIWdq6sr5syZg2+++QYXL16EyWRCjRo1LIulAEDjxo3zbwPzUU5N/DP/0cJOQiqMVqxYgevXrz/QdU0mE1atWoVPP/00S3/oW043tuEgIWVPXh63REQk5cd7sLGgn25cokQJq5krQPJsGS8vr2xvFBGlLTjGHVXTeZlxgDBZGfvrGOS9BDaGJHRwWw0AYqCwaYmNaOeyCgDQIuFb3DJU4b4rYhISEtCzZ0/Mnj0btWvXtpoRWdwZc2zhkuTb4WAHFUYmkynP6gYspxuzk5CyKS+PWyIikvLjPdhY0E83HjhwICZNmoQ///wTQPKpp1euXMG7776Lhx9+OEc3kIgoK24keGFrRDd0K7MRAMRAYcoBQgA4afc4BwiLIHt7exw/ftyqHoGS5VwnYfJfLTm1WjJRXtq6dWumfyerC/RxdWPKKXl53BIRkZQf78GJ9/5eiDemf72ckKVBwv/973/o27cvvL29ERsbi06dOiEkJARt2rTBlClTcnobi62AgABL15fuwLOzs7O6bkq6Q7BRI3l66rhx40T+7LPPRD548KDINWvKzjYHBweR9+7dK7LuAOzQoYPIhw4dSvf29eX69rR9+/aJfOvWLZGbNWsmst6fukNNd+DduXNH5O7du4usPxzv2rVLZN1RqDv+9HTllJ15gHXHnO4Y1J13ZcqUSXf79O3pDsLw8HCRdeefvv3mzZuLrJeET0iQ86J195w+PnXHpt5fgYGBIu/Zs0fkunXrAgA2xTRDfHwC+vhsA5A8UNjceSucbO8/n/vih+DfoEYA7vf0OTo6pvt4goKCRNb79/Tp0yK7uMgFZPTxvGTJEpF1h2Pfvn1FLlWqlMgnTpwQWT9fuuNSH/9ly5YVWXdE6tytWzeRq1WTK2nrzkK9P/WMc3Ofh+66zAlPP/00fv75Z3z++ec5ftuFXVKOdRIm/z/HCKkw0p3BuSnl6sbmfwX5sqGsyMvjloiIpPx4DzZ/fDfmwYpnWRokLFmyJHbu3ImtW7fi4MGDSEpKQtOmTa0GToiI8tu/4a3h5FQCnT3WAYDVAOHRxD4AIvNn4yjXxcfHY+7cudi4cSOaN29uNWD79ddf59OW5b+cmsF0f+ESDncQpSfl6cacSUhEREQPyjyTMKEgDhImJSVh3rx5WLZsGQICAmAwGFCtWjWUK1cOJpOJp3URUYGz93ZntHL7VwwQ3jW53BsgpKLs+PHjaNq0KQDrVbeL+79XOXe6sfn2cuTmiIosY4qZhOwkJCIiogdlOXMHBhiTTLC1Sf/62ZGpQUKTyYQBAwZgzZo1aNSoERo0aACTyYRTp05h5MiRWLZsGZYvX55Lm0pElDWt3LaJAUIAKGGIQUO7tRwoLOKy0hlSXOTc6cb3Ogl54iRRusTpxpxJSERERA8oMcUMwoQkFJxBwnnz5uHff//F5s2b0aVLF3HZli1bMGjQIPz22294+umnc3Qj89rMmTMxc+ZMS89fvXr1MHHiRPTpkzyYYDKZ8Mknn+Cnn37CzZs30apVK/zwww+oV6+e5TaqVq2KefPmAQBGjhxp1Rn4ICIjIy2dhK6uruIy3SGmb18vr+3p6SnysWPHRNbP2cKFC0W+ePGiyLrjT9/f+fPnRdadfJUrVxZZz/DZuXOnyG3atBG5RYsWIi9btkxk3anXs2dPkXVxqO70052G0dHRIusOuh49eoisO/d0R92lS5dE1h1/Ouvb0x2Cev+dO3dOZN1x5+fnJ7Kbm5vI+vHrTkZ9edu2bUWuVauWyN9++63I5uParH379iL/9NNPIutVaZ2dndPdnpSvRT/8g6Y26yz5rskFJQzJ+6OlwzKcO3cOJ2NlVULXrl1F1p2bFSvKRU704/H39xdZHx+6k/D48eMi605M3Smoj299POnV50uXLi2yfv2ltlp9SpcvXxZZH5/69ZFRrl+/vsjm41V3KeaUHTt2YPbs2bh48SL++usvVKhQAQsWLEC1atWsjr3iJMdON773fsgZUUTpSzlIaFA/IyIiIkpLyr8XcruXMFPjjwsXLsSECROsBgiB5A/V7777Ln7//fcc27j8UrFiRXz++ec4cOAADhw4gK5du2LgwIGWxQGmTZuGr7/+GjNmzMD+/ftRrlw59OjRA7dv387nLSeilJIHCBdb8v6Eh/FH3HT8fqKB5WdP1DuGruX258fmUR5YunQpevXqBScnJxw6dMiyqNPt27etFmwqbow5fboxRzuI0mU+3djWJsVMwvzbHCIiIiokUs4kTCxIg4RHjx5F796907y8T58+OHLkSLY3Kr/1798fffv2Re3atVG7dm1MmTIFrq6u2LNnD0wmE7799lu8//77GDJkCOrXr4/58+fjzp07+OOPP/J704nonpIIQmPDX5a8P+FhHDMmrxK88ryvGCjsU2EXvEtEWN0GFX6TJ0/GrFmzMGfOHLF6ctu2ba1WUS9ucvp0Y44REqXPlMrpxpyBS0RERBkxpvh7IbcXL8nUIGFERITVaa4plS1bFjdv3sz2RhUkRqMRixYtQkxMDNq0aYNLly4hJCREnL7q6OiITp064b///svHLSWilKJQHrtMLyHJZCMGCM3MA4XGJAN+v9gHYXdLp3FLVJidOXPG6vR8AChZsiQiIyPzfoMKkJxfuISjHUTpSW3hEg6uExERUUaMeTiTMFOdhEajEXZ2af+Kra2tVZdWYXXs2DG0adMGd+/ehaurK/7++2/4+flZBgL1YGnZsmVFb1fKjsCs9BECyStJG41GANYdaLpjzsfHR2TdMaYXlNGdYvrxODk5pbttesao7ii8cOGCyC4uLiJfv35d5JIlS4r82GOPiezg4JDu9ugOOT1DaNGiRSLrDjl9/7Vr1073+ilnJAHWj0d3OOoOSN3Jdvjw4XQvDwkJEXnjxo0i6+dPv051R6DuYNSdd/rUed1ZqHPNmjVF7t5ddvzpDr3Y2FiR9ftG1apVRdbbr18P8fHxIjs6OgIAQtAJG0w1EW7yhIPt/cvNX2bM318OW866wcWnBoD726A7NP/++2+Rdeem7kx8+eWXRdaPV3+ZkpQk3+n1/j9w4IDI+vnSnYS6g3DAgAEie3l5pXt7uqdvx44dIq9evVpk3UnaunVrkfXxoe/PfDyl9+9LVvn4+OD8+fNWx9TOnTutnufiJsc6CS0LlxBResx/4NveGyC0MZg4k5CIiIgylHImYYEaJDSZTBg5cqTlA7hm7noqCurUqQN/f39ERkZi6dKlGDFiBLZv32653GD+Cvgek8lk9bMHFR0dLWa0sNuQKOfcNlQAkPZ709VbLqjrk+bFlA8CAwPFFx0eHh5Wizc9qBdffBGvvfYafvnlFxgMBgQFBWH37t146623MHHixJza5EIpx2YS3rsZvaATEUnmV4iN4f7/s5OQiIiIMpKXnYSZGiQcMWJEhtcp7Csbmzk4OFhmvzRv3hz79+/Hd999h3feeQdA8syulLP3wsLC0j0VOz1vv/02Zs2alf2NJiIqAvTq26NHj8bMmTOzdFvjx4/HrVu30KVLF9y9excdO3aEo6Mj3nrrLasZn8VNzncScpCQCrdr166l+qVEQkICdu/enWp1QWaYZxJaBgnB040p665du4YSJUrA09MTQPKs/1mzZuHKlSuoUqUKxo4dizZt2uTzVhIRFV03btzA0aNH0ahRI5QuXRrh4eH4+eefERcXh0cffRS+vr45dl8Fdibhr7/+mlvbUeCZTCbExcWhWrVqKFeuHDZu3IgmTZoASD7Vcfv27fjiiy+ydNtffvkl3n//fUu+ffu21YdkIqLi4uTJk+KUdg8Pj2zd3pQpU/D+++/j5MmTSEpKgp+fX5ZnJhYlaQ1O/H34Gpzs7dC7frkHuh3jvRviYAcVVsHBwRg4cCAOHjwIg8GAJ554Aj/88IPlfSIiIgJdunSxVMBkldGUPDpoPt3YYODCJZR1Q4cOxYcffog+ffpgxYoVGDJkCPr164d27drh7Nmz6NSpE5YtW4Z+/frl96YSERU5+/btQ8+ePREVFQUPDw9s3LgRjz76KOzs7GAymfD5559j586daNq0aY7cX8pOwtxeuCTnC6CKgAkTJqBPnz6oVKkSbt++jUWLFmHbtm1Yt24dDAYDXn/9dXz22WeoVasWatWqhc8++wzOzs54/PHHs3R/rq6u4gOr+TQ7g8FgOYVZd/rpTjH9h6vuyCtXTn7Y69Wrl8i7d+8WWXfotWzZUmTdeXjq1CmRx40bJ/KcOXNE1h17wcHBIutZmQkJCSLrzjvdN3b8+HGR69WrJ7Kzs3O626M7G3UH340bN0T+4YcfRNadgXoAedOmTSLrbrTo6GiRdSdjqVKlRNYdb/r51vuvU6dOIuuORZ31/tTPvz7+dPWAnn2hb+/u3bsit23bVmT9Tbju2EyrAsFML1BRo0YNkXWnnu7c1B2Rume0Q4cOIuvnS3dA6o7L4cOHi6z3r74/vb26o9HGRq5JpY+ngwcPimyehWCmTxvVX1ro14/uSK1UqZLI+vVy9uxZkc3Hm/l+K1SoYNUTml3Ozs5o3rx5jt5mYWdMMaqXsjLj641n4eHkkIlBQvNt5PgmEuWJd999F7a2tti7dy8iIyPx3nvvoXPnzti4caPl39ucOJ3esrrxvbdoGwMH1ynrjh8/bpmlMnXqVHz22WeWM54AYMaMGZg4cSIHCYmIcsH777+PRx99FF9//TVmz56NQYMGoXfv3pZxj+eeew6ffvqpVbd9VphM979oBOSAYW7I1OrGxUVoaCieeuop1KlTB926dcPevXuxbt069OjRA0Dy6Wuvv/46xowZg+bNmyMwMBAbNmywGkgiIiIqqFKeHpxyoCIh0SQGEDNiWbiEo4RUSG3atAnfffcdmjdvju7du2Pnzp2oWLEiunbtioiICADWXdRZYVnd+F42cJCQssHGxsbypeKlS5fQp08fcXmfPn2svqQkIqKccfDgQbzxxhtwc3PDa6+9hqCgIDz//POWy8eOHYv9+/fnyH0Z1d8KuT2TkIOEqfj5558REBCAuLg4hIWFYdOmTZYBQiD5D8WPP/4YwcHBuHv3LrZv324104iIiKggk4OE9/87McmUqX5B8x8u7CSkwurWrVtihr6joyOWLFmCqlWrokuXLlaz9bPK/FqxNc8kBAcJKes6deqEhQsXAgCaNGmCbdu2icu3bt2KChUq5MOWEREVffHx8XBycgKQfFaUs7OzODurTJkyVmdTZZUeJCxQnYRERERUNKQcnEg5wGeeGfig7i9ckiObRZTnqlevjqNHj6JWrVqWn9nZ2eGvv/7Co48+mmOna1pON07ZSZgjt0zF0eeff44OHTogKCgI7du3x/vvv4/9+/fD19cXZ86cweLFi7kwIhFRLqlUqRIuXrxoqT1btGiRWNg2ODjYqtIpq/TpxewkLMYqVapkGZ3WHXO6AzAoKEjkrl27iuzu7i6y7sz777//RK5du7bIuiNQdyTqDrnff/9dZN0J16JFC6RHdwTqTjW90qnuTNR/0IeGhop84cIFkc372ezq1asi6xe47mjTnY6dO3cWWXfE6edDX64XVdDX1/mll14S+amnnhJZL/ygO+50h1yDBg1E1h10W7ZsEfnkyZMi604//S1KnTp1RNb7Xz//iYmJIuvTvnQnod6fVapUEVkfT3oquO7M04WzugNT70+9P/TxqTsidQeo7mi0s5Nv1fr1p59f/XzduXNHZN0h+c8//4isu/v0+4/uXGzcuLHIt27dEvn06dMi79ixQ2Tz8R4fHw/KOykHBlNOAsz0TMJ7o4OcSEiFVZ8+ffDTTz/h4YcfFj83DxQ+/PDDuHbtWrbvx2p1Y55uTNng6+uLvXv34oMPPsC0adMQExOD33//HXZ2dmjRogUWLVqEQYMG5fdmEhEVScOGDRNnGjz00EPi8pUrV1p9BswqPXMwtzsJOUhIRERFwsqVK9GjRw+rQWdKXVJS6qcbG5NMmRq4uL+6MUc7qHCaMmWK1ZcpZnZ2dli2bFnODBKaTzdOMUjIlw1lR40aNbBw4UKYTCaEhYUhKSkJnp6eVgvQERFRzvroo4/Svfz999+Hra1tjtyX+e9yBxsT4pMMuX66MTsJiYioSBg2bBiqVKmC4cOHY/ny5UViZuLfh68hNOpuxlfMgpQDgXomYWYWIbk/k5CjHVQ42dnZpbuiuq2trdWM9KzQpxtzJiHlFIPBgLJly8LHx4cDhEREBYCzs7PV2W5ZZR4UdLw3xY8LlxARET2AOnXq4NKlSxgwYADmz5+PSpUq4emnn8bq1autTlkvDI5cjcS4xUcw7Kc9uXL7xnRmEppMwNWIOxjz+0GE3U5/kPL+wiW5splE+e7q1asYNWpUtm/HqAYJ2UlIuSmnjlsiIsq8nHwPNqpBQi5cUoy5urpausWOHj0qLrt48aLIpUuXFvn69esiX7lyReS4uDiRdUfcxx9/LHJgYGC6WXf2Xbp0SWTdmaY7AXXnmZubm8hNmjQRefXq1SIfP35c5PLly4usO+b0SoUDBgwQ+ebNmyJv3bpVZL2add++fUW+ffu2yLNnzxZ5xIgRIusZCrqTLiIiQmTdOffmm2+KfOjQIZF1h6LusJwzZ47IunPvxRdfFHno0KEi6+NR37/uANRTr/W3LLojUXcM6k4/fTyXKFFCZN1hWK1aNZF1Z2LFihVFTlILOejTzvT26dvXHYC6s1EPYLVp00bkvXv3iqw7Pnv37i2yfv3rTk69vfr0XH1/+njx9fUVWe8vvX36+NWrLZpvLzY2FosWLUJWGQwGuLi4YPjw4Rg+fDhu376NFStWYPbs2XjuuecQHByc5dvOD5Gxycf5pfCYXLl9k1jd+P7PjPc6CT9ZdRKbToXC3ckBU4c0SONWUi5cwuEOKpoiIiIwf/58/PLLL9m6nSR9ujE4uP7H3iv4eNUJ7H+/O9ydOAMuJ+XUcUtERJmXk+/Biff+VnC89xGag4REREQPQJ/u6ubmhieffBJPPvkkoqKi8mmrCi6jWLgk+b/v9wsCCfe+tozP4C8R87ebxXysgwqxlStXpnu5/iIsq5J4urGVCX8nL9x1PPAW2tXMmVUgi4u8Om6JiMhaXr4Hm/9WKMGZhERERA9u8eLFaV6WXt9YcZVycML83+aBQxNMsL03kpFR16B5JiE7CamwGjRoEAwGQ7rHsJ6RnhWW043vTeYuroOEicYk9P5uBx5uen8WuoMdG5AyK6+OWyIispaX78GWTsI8mknIf5GJiKhIqF27dn5vQqGS2urGlpmESfdnO2V0GnHK3yEqjHx8fLB06VIkJSWl+j9doZFV+nRjQzFd3fhWbALOh0Vjf8D9KgoHW34kyay8Om6JiMhaXr4Hm8/aKZFHC5dwJmEhoTv7tAMHDoisO9B0x1+HDh1E1p2BulNw7ty5IuvOMwcHB5GHDx8usu44051xuitMd+LpTsXmzZuLrDvdLl++LHKzZs1E1tN/t2/fLrLuLDx16pTIuhNPd+iVKVNG5FatWqX7+7du3RJ5x44dIuuOOt0Rp2dQPfTQQ0hP+/btRdb7T3cE6vvTz6eXl5fITZs2FVk/X/rUz4CAAJFdXFxE1sen7mzcvXu3yHqwSG+fPv50p6R+vehvgfTxktHy9gcPHhR5//79Ivfs2VNk3VG5efNmkfXx2KhRI5Ht7ORbe3h4uMi6M1E/P/r1qN8v9Ovx6tWrIh8+fFhkvf/17Zkfj35ec9LBgwet3gcKo6QkEz5dfRJDmlREg4ru2bstcbpx8v8nipWKDfeul/7t3D9FuRiOdlCR0KxZMxw6dAiDBg1K9fKMZgo8KH26sQHFcybh7bvJf3OER9/vEzbPXKYHl1fHLRERWcvL92DzmQjmmYRGDhISERFlz+DBg60GNwu61D4yH756E7/uCsCvuwIQ8Hn6XwZkJOXghKWT0Gg+3TgTMwlN93+HqDB6++23EROT9gJBNWvWtFrALCvMf9Sn7CQsjq8byyDh7fuDhPySIfPy6rglIiJrefkenMiZhERERJmnV902M5lMVissFyRrjwXDwTkKg5tUzPC6sfE591eBUZxunPz/iSlmBd7vJEz/dsynGfNDPhVWenaz5uLigk6dOmX7fsyvXtsCunDJ7O0XEHU3AW/3qpur93P7bvLZFOHR8ZafGQvSjigk8uq4JSIia3n5HmzM405CDhISEVGRsGnTJixYsACurq7i5yaTCf/++28+bVXG3l5yFDaOzuhU2xulXRzSvW5iDhb/pTwFwqqT0JTcl5bysoy2iWOEROlLSmUmYUEaG5u69jQA5PogYdS9mYTxKc6X4iAhERFR6iynG3N1YypVqpSlm23fvn3iMt0xpjvkfH19Rf7nn39E1h1wWmhoqMh168o/GHXnWcuWLUXu0qWLyGfOnBE5MjJSZD8/P5H19m/ZskXkUqVKiaw7/nQnob68Zs2aIuuOOj11uHPnziKXLl1a5NOnT4usO90mTpyY7u3Pnj1bZN1xp7dX35+NjSz8vnHjhsht27YVWXe/1atXT+SbN2+KfOzYMZH18aGvr/en7tR0dnYWWXc6HjlyRGT9eHRnn34+9PboTsV27dqJXKtWLZH1gJJeGVfffp06dUTWz//gwYNF1tuvX4+6U/SZZ54Ref369SIfP35cZHt7e5ErV64ssu6kjI2NTff2vL29RW7YsKHI+jRefXv6+dfH8+rVqwEA8fHxyI7OnTvD1dU11W/tmjRpkq3bzguL91/FS51rpHudnPwgbUxlkDAxxUrF5i7OjAb/jJxJSEXchQsX8Pzzz1v9LZJZRhNggMkyAF9cFy6Juptg9TMOEua8nDpuiYgo83LyPdg8SFiCg4REREQPbtmyZWletm7dujzckqw5fEUOPhtSKSVMzMEP0rKTMPn/jZaFSwDbextgzHB1Y84kpKItOjraasGqrEgy3Z9FCNybSZjtWy18zJ2EKWX0PkOZl1PHLRERZV5OvgcnWp1ubEButhpzkJCIiIqkkJCQDFeGL0gSHmCpspycbZOUlNpMwvudhObBjIxWZuPqxlTYTZ8+Pd3LAwMDc+R+kkz3+wgBwAZAYjF82dzmTMIckVfHLRERWcvL92DdSciFS4ioQPAuEYGwu6WzfDlRXuvZsyeOHj2a35vxwOIfYJDQPJBok9rSx5mUclBPzyRM7iQ0WP47PSlnHxIVRq+//jp8fHzg4JB6J2h2qxDMjCYgZTuIwQCYiuFUwlRnEnKQMNPy6rglIiJrefkezNONyeL06dNwcnICYN3h5+npKbLu6NMdb4MGDRL59u3bIn/33Xci6w62119/XWR/f3+Rr169KvLBgwdFNqjz5vTMFN2hduLECZHN+8FMdyxWrVpVZN25pjveQkJCkJ7evXuLrDsCdcedfnPQnXMHDhwQWS+soJ/PGjVkL9nOnTtF1h2UuvNu165dIuv9e+fOHZFPnjwpsu6Ue3VgWbQz/AF/06M4iX5WnZRe139Bl9KbsTzsEZyMaWDVaaenWutVaJs2bSqy7vzT+0tvX4MGDUTWx6/uNDR3fZpl1EGY0ePRx7e7u7vImzZtEtnDw0PkJLUYhe4o1B1++njUx4++XHcGXrhwQWQ92+7cuXMi69ejfr708aaPD90BqTs5zfcfFxeHnJTRDLiCxMYAJDzAlCLzB2nbHBglTPmZ3DKT0Gge8Lvfm5bhTEITZxJS4ValShV88cUXaa6Q7u/vj2bNmmX7fvTpxoYCtnCJWcpO0tyQlzMJj1yNxMAfdmH68CYY0Kh8rtxHfsmr45aIiKzl5XuweR5BCTsTAEOuDxLaZHwVIirOyrtGoZ1hJmwMSWhqsxh+kAO0dU0r0a3MRtgYkjDIewnK2F/Ppy0lknLzQ25O83YrgTg1kzC1MbccHSQUpxvL25edhBndjvk2CuBoB9EDaNasmdWXmykZDIYc+dLB6nTjAjpImJPdp6nJy5mEa44nLyT2078XMrhm4ZNXxy0REVnLy/dg8zyC+52EOXKzaeJMQiJKV1B0SfibHkVTw2IAQFObxbAx2eC0YQDqmlaisWmh5bpbI7rhRoIXgPA0bo2INFsbAxzsbJCg/sVPbdDN/OHd3ib73/HJ043l6sZJmZhJmMiFS6iQmzRpktUM+5T8/Pxw6dKlbN+P1cIlyM3a8axLMCbB3jb35hFE3U2Aq6Md4hOTLDULuTVIaHdvhydm9G1HIZRXxy0REVnLy/dgSychTzcmooLiJPoBSckDhADQ2LQQvqZVcES05Tqbb/TA7lsd82sTiQotG8O9QcIHmEloHiS0tc3+TMKUq4nqmYTJgxnmTsK0P1ybTCbL7xbEGVFED8LPzy/dy+3t7a1qRLLCmJTK6sYF8HWTkGgCUq9YyhG37yai5L1ipaBbdwHk3urGdve+UCmKnYd5ddwSEZG1vHwPNqqZhFy4pBgzGo1ITEw+JaNs2bLiMt2Bd/bsWZF1516vXr1E1h1v3bt3F7lhw4YinzlzRuS9e/eKrEfRdWeZ7mDTHWbXrl0TuUmTJiJXr15d5C5duoh869YtkXXHmu5g1B1/ev/qXKJECZHLl5e9NrpDTm9vRh2NusNNdyhu3rxZZN25qDsr9ePVHXB6tSXdcajz2bNncRa1EV66K3p6b0m+TooBwvOuz8FQbjja3sv6+Dx9+rTI+vlasmSJyPoNtVGjRiLrjkf9fEdHR4usOwWDg4NFdnNzE/nu3bsi68fTr18/kXfv3p3u7+vOwNKl5QIv+v51h6J+PjV9vOnjR3cw6uNbHz++vr4i6+Jd3clYq1YtkY8dOybyhg0bRHZ2dhbZvD/0fsuutIqECxpbG8De1gZ34uUpeKkNzhnvDSTaZeF047hEI+xsbCynKqfaSWg+3Rj3O8nS++ye8oN3bp7WZjKZ4H81En7lS8LRzjbjXyAqgPTpxgZDwZyB+yCLKGXH7buJcCthD0d7m/uDhLk8k7AoDhISEVHxkKhmEubyP9PsJCSiB7czoh3uGOUiMrFJzrjiOjyftogobXowuaBK63Tj1D7UJmajk7DOB+vQ9attlpwkBvjkfSaZkgcv09oOyzaK2Yi59yF825nrGPzjf5i06mTGVybKgiNHjmDy5Mn48ccfER4uKzOioqIwatSobN+H1enGBXUmYQ5++jAmmTDsp91YuO/+AlpxCUaUsLeBp6ujuF5uMM+6TkgqmstI58VxS0REqcur9+CkPJ5JyEFCInpg7UvvgrOtXFnYyeYOKkcvTOM3iCgjtgYDHGwNVrN3UvvMbP4gbZfFTsLLN+7P+k5KZYDPMpPQZIIBmZxJmKUtejBnQ5Nn0249HZaL90LF1YYNG9CyZUssWrQIX3zxBXx9fbF161bL5bGxsZg/f36278dYgAcJU84EzslBwoiYeOy5GIH3lt2fYW40mWBjY4Cn6/3Z3rk1SGjubzUWwU7CvDpuiYjIWl6+B1tmEtoCBpi4ujERFQztS++ynGoMJM8gNKsZPZcDhVTgXLt2De+//z66dOkCX19f+Pn5oUuXLnj//fdx9erV/N48C1sbA+xtbRCfqDsJrT/Umj+858jqxilu/v5MwvuLkJjvwpTO8F/KD/a5Odhhd29aY0JBGVGhIuXjjz/GW2+9hePHjyMgIADjx4/HgAEDsG7duhy9n5QzdIGCNUiY8rWck4OEqb1/GJOSvxzJk5mE5oVLCsqOzkF5ddwSEZG1vHwPNv+zbGMA7G24cEmxFhwcbOmG051guoNNd9zp6+uOs7i4OJF1B5w+TU93DOrOsqCgIJF1B5yXl5fIuiNPd9S1bNlS5ISEBJF1x6F+vPrxJanTTMqUKSOyk5M8hVZ3JOqOR93pqDvZ9u3bJ7LuWtO/r/dPgwYNRL58+bLIevsjIiJEfvHFF0Xev3+/yFFRUSLrzj+9v+sYV6Cn9x5L3h07CP7xPdHYYQPaOC0HkDxQGB4eDv/4Xlb7Xz9fugNPHz96f+sOxkOHDomsOyO7du0qsj5eb968KbI+PipXriyy7ji0t7cXWb8+dCdg8+bNRTZ3jZrFxsrZmXq6ur4/ffycOnVK5FatWomsOwt1h6YeMKtbty7So49nfX/68et/LOvUqSNyx47JC97o/ZAdO3fuRJ8+fVCpUiX07NkTPXv2hMlkQlhYGJYvX47vv/8ea9euRbt27XLsPrPq/sIl8kNsakX+8UbzTMIcGCQUA3z3ZhIaTZZsMFh3F1rfxv3/zs1OQntb9opR7jlx4gQWLFgAIPnvqbfffhsVK1bEI488goULF1r9TZJVSSYg5SvX1nC/jDy/pRxEi0/MuY3SX34Aye8vNjYGeLmlGCTMpfcP81tlURwkzKvjlgq3uwlGdP5yG17qXAMj2lbN780hKjLy8j3Y/M+ynU3yl40cJCSifFXaLgwDKt1fqObvS60RUronAMA/Pvn/zQOFLR1XIiCxEUJRKs+3kyilcePG4bnnnsM333yT5uWvv/661QB6frDMJHyA041zdiah9SBhaqsbpzcwl5hilDA3OwnNp1fn5AwnejDPzd+PvZcicOzjXhlfuZBydHS0+vJq+PDhsLGxwbBhw/DVV1/lyP0Y1UxCOxsgwZj29fNSYi7NJNRffgDJ7ym2BgOaVSklfpYbzHefWATfO/LquKXC7eadeIRE3cXxwFsZX5mIHlhevgcn3vtbwc4m+X883ZiI8lVEojfmnekOo8mAvy+1xsZAufK0f3xP7Lk7CEkmG2yOfQaRSeXSuCWivHP8+HGMHj06zctffPFFqxnP+cXWxgAHWxsYk0zy9N1UPjSbZ+XY2Wb/n2+56Ejy/yeKjsH7/YQPchupXW3fpQhM33wum1sK2N2bSZhYUKZdFSObToXh9t3EIj2Ls3HjxqJHyOyxxx7D3Llz8eqrr+bI/SQlydWN7W1yv3z8QaUcREvMwUU+Up1JmGSCrY0BDSt64M8X2wDIvUFC8+MqijMJ8+q4pcLN/BqMiU/M4JpElBl5+R5s/qfUziZv/nbgTEIiytDB8Jq4FlMGobGpzxD0j++FgMRGHCCkAsPHxwf//fef1anNZrt374aPj08eb1XqbGwAB7v7M+Vs/5+9646Tm7i/T9vb9e5zOfdu497ANqYZiMFgeifBhOYkP1qABEJICBAgBQKEFggQSgKmg23A4N57t88+21d8ve9tX/3+kEY7M5J295ptQO/zMdzsalVGo9HMm/d9X5OUukxLmRdTEsY+C0eiuOPtLbhyUm/MGJSj+k00KqLJF1J9Tu9e5JSE9N/xptYRjZBlGpe9uAYAcP3UIqQ5rarvk4VF8RU7SRiVHyGafCFkum2JN/we4tZbb8Xy5cs1v7vyyisBAC+99FKnjxMFQLvDWM0nEUnYTeHGtCoxGI7CZjEpiUuAmCq620jCKJuU6YeE49VuDXy/QUjCFr9BEhow0JU4nn0wGStYj5OS0CAJT2LMmDEDbrcbgNpzjPew4z3keM+xZcuWMeX+/fszZd4Djfd8mzx5MlPmPcl4Dz3+e/785s6dy5QzMzOZsonL3Ml7DprN5ri/X7VqFVMuLCxkymPGsGo43qPv2LFjTJmvf97Dj98/r7zhPfZyc3PjHo+vv759+zJl3vONr/9Ennvz5s1jyrzHHe9xyRMt/Pnt2bMHkqug9F/+/rS1tTHl/fv3M2XeMzAjgyUj+fbL32+Lhe3K+PMbNGhQ3PNZsWIFU967dy9T5j0r+fs7bNgwpsx7gPKehgMGDIh7PN6jk69P3tMzkUfp7t27mTIvjec9I4uLi5nyhAkTmDLf3lpaWpjy1KlTmTLv8VhVVcWUSfvn71tncPfdd+OWW27Bpk2bcNZZZyEvLw+CIKCyshJfffUVXnnlFfztb3/rsuN1BhaTSfHcC0aicFgJSajelgz2zVQfuauiGYt2VWLRrkocfvx81W8WvLMFn+84pvpcKzMxPZEOK6HHnU9coqWKbA+UxCWGkvCEod4b/MGShBdddBEuuugi3e+vvPJKZcDfGUSi0uCewGICoqIghd+e4NgeWqXbleHGtI1Cky+EnBS7HG4sfdbtJGGE+K2eJGxsF+J4tVsD328EiJIwYJCEBgx0JY5nH6woCc3S2KG7X2lGuLEBAwYMGPjB4bbbbsMbb7yBjRs34pJLLsHUqVMxZcoUXHLJJdi4cSPeeOONuOHIxxMmgVISUkuDmuHG8qjASnkSJvIC1CII+d+RY0WoBYUISWISZyDCEI1xzqOzfoVdkailoxBFESsO1Hyv/RD/u6EUr6w41O7f0fe0oS0YZ8sfJl5//XXVok1nQGcNBwCbvP5zMqgJaZVul5KEVJ/WKLehqCgq5CB5trsrcQm5rh+gkFAXXd1uDXy/QcYN3sBJYoBqwMAPHN3RB4ei0rvSKicu6e41c4MkNGDAgAEDP0hcfvnlWLt2Ldra2lBeXo7y8nK0tbVh7dq1uOyyy0706SkgiUsAVnWjHW4sKr/pLOhJs5YnYVcqCbuLAOgK/OGz3Rj20CJdteN3+2tw7avr8dVuVgFb3ujDw5/s0vRcO9lw7wfb8cfP9yTekIOPyqpR1/rjIwlvvvlmVFRUdNn+IhxJSFSF8ZpQMBxFdUvXqaz10F1KQnpfjbLtQSQqKomRlARJ3TTj+TGqj7u63Rr4foO8o1oNJaEBA8cF3dEH056EFsEINzZgwIABAwY6BavVqvIfLC0txe9+9zv861//OkFnFYPZZIKNhNOG45NuQTm9GR1R3tEpcFRDBch6Ekbl7/T3kaySsLOhhN2ZNOPVlSUAJELMbVcPi3aUSavBvK/jLW9uwo7yJhRluXDDtL6q3/0QQF/zD1lJyFtYEITDYUyZMkWxQKmvr+/UcSKiOnEJEH+w/6v3tuCLHZVY98AZyEt1dOr48cB4EnYhsUaT6A3eIERRRFSMLXSQpETdpiT8HiuAE+F4tVsD328YiUsMGOgeHM8+OEKRhMdDSWiQhCcxzGaz4kV25MgR5rusrCymfNZZZzHld999lynznne8px3vkcdPqPnf9+rViynznoa8hxrvNdavXz+mzHsObtmyhSn36dMnbpn3PFy5ciVTDgQCTJm/3nCYfXHyHms2G+vDxHvQ+Xw+ppydnR33e/5+lpWVMWVeosx7QvL1y9c/7/nGXy//+5KSEqbMe/bxv+evh/d4zMvLY8q8Jx7vAckfLyUlhSnz9cGfD++5uHXrVqbMtzfeI5D36OPbD+8nwd//xYsXM2XeU9NutzNlnkzp2bMnU+brg/cYPf3005nyqaeeypQ//fRTprxt2zamzNcH/5KrqalhyrzHJ3/+/GoZf7/4440aNYopr1u3DkDXehImQn19Pf7973+fFCQhHW4cpPpmrUkzUcV0BWcW1cpuTI06tJSEm4824NJ/rsHnvzgVQ/JTNTMka6GzWYk7Gq4siiIue3ENzhtZgBsTEHltQW2ScF+V9D7gyYZGn/Teagt9f0K4RFFUeZbGQ7Mv9m6s9/5wScJQKIQZM2bg0ksvVT4TRRE33XQT7r33XpXvcEchilKiIgJCEgbjNKEvdkiexmUNvm4mCalw4y6UKPBKQkL4E5JQURJ2c+KSHyKOV7slaA4Aq8uA2f0Tb2vg5EHQ8CQ0YKBbcDz74BCtJDTFHzd0BQyS0IABAwYM/ODwySefxP3+0KH2+7PxeOyxx7Bw4ULs3bsXTqcTU6dOxRNPPKGbUVkPZoEKN6aUhFrKPDLYZ1WA7Db/21iKY01+/OKMgXGPyxJ8+tmNaYLuT5/vQSQq4q21R/DHuSOTVhJ2dqLeUZIwEI5iw+EG5KY6kiAJwwDsqs/3V0okIR+2KEAiN07iSGoVgpEo7BZz4g1l0ErCHzJJuGXLFlx11VVYunQpnnvuOSWZ1/z58zF37lzVwlBHERFZnx85R1GSYUPd29C6K9w4wHkSkn7HfNyyG8eO316S/GRHd7VbURRxtAnok8Z+fsuXAlaXCXhnbhRTemr/1sDJB2JjEoqICIQj7XoHGDBgQB/Ha+wAsOHGZhMQDsXfvrMwPAkNGDBgwMAPDnPnzsVFF12EuXPnav678847O32MZcuW4fbbb8fatWvx1VdfIRwO4+yzz1Zln04Es0mIJS6hJudak2Yy2I+KIqJRUSa2WNzz/nb85av9qs950OTW9a+tx87yJk1PQnq7ikZJRdwj3ak6x/hKws6RDh39OSEokjm+lql7IBxBSa10P8OcYpl4y8UjR082+Nq59NxMhxv/gEnCAQMGYPXq1cjPz8cpp5yiUk93FSIimCzGxJMwmcQl7W1m/lAEr68qQSCc3D2nn/2u9SSM7bfFH1YSIZmF45S4hCE/vz/PajLornb74ZZyzHjThHd3sZ+vLpPuVePxE/0b6ALQIf9G8hIDBroOx2vsAMTGCVbZk9BIXGLAgAEDBgy0EwUFBfjggw8QjUY1/23evLnTx1i0aBFuuOEGDB8+HKNHj8Zrr72Go0ePYtOmTe3aj37iEvW2IYUkBB76ZCeGPbQYTb6OkTcRTo148Qur2ezGGkrCiiZpdpjjsav3EUfp1GklYQd/T+orGZWSFuFaUutVzl2lJBS+f0rCtnaShLSSsO4HTBICgMViwRNPPIGXXnoJV111FR544IEuV511Jrtxe5V2j32xBw9/uhsvfHcwqe3pZ594EoYj0XYTyzxogqLFH1bIQBMJNyYk4XFIXOJPkjD9PqE72u2q4joAwJcHY/uppVxQmgL8LwyczGBJQiPk2ICBrsTxGDsArJLQZCQu+XFj//79cDoltUZqairzHe8pyCtXBg5kw8x4TzS3282UR4wYwZT5cDneI5AH72HGh/LxnmS8h9yePWzWRd5DjT9/3tOM97zjPRt5z0Peg46XA/MegbxnW3p6OlPmPfaqq6uZssPB+gjxncf06dOZMn+9a9euZcq8R6LVamXKFgv7aBcVFTHlRJ53vOcg7+GXn5/PlPnr4b3leM89Iscm4D0heU9F3kORB3+9/P5Wr17NlPnz58+Pv16+Pvj2ynsk8p6U/P749sF7ZlZWVjLlDRs2MOUhQ4bE/X15eTlT5j0ie/fuzZRzcnLiHo9/Xvjj8x6hn332GVP+6quvmDKvvJo1axYAtZdjZzBu3Dhs3rwZc+fO1fxeEIQuV4ARL0Y9I+NAIMDcK9JvmE0CbLJ5P+0FFi/cWBRFvLX2KABg5YG6Dp0vH8IbDEd1shvr74NREsYZsHTGk7DJF+pwVkZSX8mQlF4NMmRfZcyflr8G0uud7JZn9D1qL0nY7I+RhI2+bo5tOUkwa9YsbN68GfPnz4fb7U74/mkPIlE+u7EIQEAytpaBds4ItpdL/VGyClCaTGtqCyISFXH725uxeFcV9v5hNhzWjtUDrUps9lOehMdJSUiTn/5QBKkOa5ytv7/oynbrtku/9cqP/MEG4Iz/xN7PNW1avzJwsiIQYYl6AwYMdD26c+wAcNmNjcQlBgwYMGDAQPtxzz33xA37HTBgAL799tsuO54oirjzzjtx6qmnqhZdCB577DH8/ve/V31OhxsHEoQbK8o4UcSgPA/2V7ViXYk2Sajnv0U+11LnaWU3JmQiTVqS7dhw43hKwo4veY7+/ZIO/5bUVzIkZZsGEcmQhNw1kKrVU1De+/425KY4cPc57fOo7GrQKhJ/O5Os0EpC348oM2ZWVhYWLlzY5fvtSHZjgo7euzRncqQY/Sw/s7QYzf4wFu+SFuxaA+EOk4R0+2v2hZV+x6STuCQQjuCDTeW4dHxPRWHdGYSo6wokI9n8HqOr2i1J4NQq88v/3c2+R2raBHS3R6aBrgOjJPwR9eMGDBxvdNfYAWATl5hNHbfhSRZGuLEBAwYMGPjB4bTTTsPs2bN1v3e73ZgxY0aXHe+OO+7A9u3b8c477+huc//996OpqUn5V1paCkBSNZLJMK0k1FKoxRKXAANzpSzguyqa1RtCPzwxEkchSKuJCLEmihJB2NAWI4yI6ocPWdYDreRr8Yfw2Bd78MoKdfKYTUfqUVwdI+Y6m8wgpiRMwpNQQ2W3vyp2Lnrhxnr+bf/dWIZ/fFuc9Ll2F2hyKZ6ScMmuSvz09Q2s8kvObpzltrVbhfh9QyQSQUlJiRLpEAgE8N///hfvvvuuSt3eEYgi4AsDDmp5PpnsxgTtVRI2tbVP+cm349dXH1b+bi9BSSPIqJhCVOISyP9nScLHv9yLBz7cgWeXds2zQ/uRduY6TlZ0R7v1yCQhaUIfcxa33a0k3F7WiD9+trvbktn82ECThB1V5RswYEAb3T12UI6j+PlKRKERbmzAgAEDBgycxFiwYAE++eQTLF++XBW6TsNut6usBADpZR9LXBJfmUe+TybbbygiQiuJYTgqfa61j8qmWGg9maCFo1Gc/tR3OFrfpvqODhGM60lIXdc/vi3Gi8slgvCm01grinkvrAEAHH78fABAQ1vnfPCC7VESaigs9lW1IMVhQYs/rEp+QrQ1vqB6pMarLs2mrvenSRY0uaR1jQQ3vyl5ae6vasHwHlJaU6JGy09zoLLph5utYNu2bZg9ezaqq6sxYsQIfP755zj33HNRUlIikfhWKxYvXowJEyZ0+BjeEBCOCkh3xNqGpRuVhCQ8vCUBKVDXGsCvP9iOGYNZ2wyrWVD6G38nFHi8J2GUCzfmScLiasmeg+6LOgOaaOrMdZyM6K5267LFwo2jIlDpFXBefxHXjBRx+yKh20nCq19ZhxZ/GNMH5WD6oJzEPzAQF4YnoQED3YPjMXYgCEUBq0mEIEhEoRFu/CPG7NmzkZIiKUX272eX8XbtYlOOvffee0yZDzE7//zzmfLEiROZMu8FxnsS8h59y5YtY8pTp05lyok8+3iPPt6jbtq0aUx53bp1TJl4NRLwnnv8RJ33lOPLvEcc7wHZo0cPpsx7HNbW1jJl/np79erFlF0uF1MeO3YsU+aTKvCedqRdEPAecyUlJUx57969TJmv7+HDhzNl/vpaWlqYMt8e+e356+E9CnlPRF7RVVBQwJT5lRje45L3VOS359sD7/XG348xY8YwZb7++esZOXIkUz569ChT5tsP71nIewDy94d/vvjsWfz94J+vvn37MmXe07ShoYEpZ2RkMOVLLrmEKfOejIk8E3mPSL4+iacmf14dxdGjR1XPRDyUl5ejsLCw3ccRRRELFizAhx9+iO+++05Vz8mCTVwSqwOtcGA6u3EidVwwEoUTapZQKyEJwcGaWIh2mAopPlzHPrPa4cb650KfK002BcNRhSDVQk1L5xzy2+VJKGd9fHPNYTz48S4su2cmKpv8GJKfih1c5mcgFibpk8mbikYfzntmBV64ehxG9UxTtqts9qMwnX1nHU/Q5FIySShoxWCTLwSLSUCWx45DNYmzdouiiN98tBPTB2Zj9oiChNufLLj33ntx6qmn4ne/+x1eeeUVnHPOORg+fDg2b94MQRBw44034oEHHlD5q7YHJCNsBtU9W9uRuMTfDtlAOBJVns1EHmRPLdmHr/dU4+s97DjIZbMoJHFnFHhEoei2mSVPQi5xCU8Skme2K0KNpePHnlvyrLYFw/jthzvxf2cNQq9Ml95PuxUHa1pxoKqlU89Jd7VbMoNoDcZUrnYLMLUnkOc+fp6EJbVegyTsAtDjCoMkNGCg63A8xg4E4WhsYfF4KAmNcGMDBgwYMPCDwoQJEzB//nysX79ed5umpia8/PLLGDFiRIf9Q26//Xa89dZbePvtt5GSkoLKykpUVlaqFiESwSQIsCnhxvFJNyXcWEzsRxLUGUEoCUk0vqaVezElob53YfKehLHv6POij6eVqKW2VU0SticEjRyrPdmNn1oike7f7atBKCIiRY4P5cMxyVocIVD+t7EMjW0h/OajHcxE7Ghd986or3hpTdwMtnRGV18SZA8djtbsDyHVaYXLaoYvFEmY7KclEMbb647ilrc6nz38eGLDhg145JFHMGLECDz22GPYt28f7r77blitVlgsFtx3330JE7hpQRRFfF0ChCIxkpBWEpJw42RIwkA7iLpjFBHfmoAk1Hs26Oc0mXajB7KfLI9dym6cIHEJWQiJt3jQHtALFMSP7dUVJVi4pRy3/SdxO/WHIvjvhlJVPe0oa8JvP9rR4ZDYc/+2Are8tRl1Gn1csuiOdlta36ZYSwQigtI2SVvNcXUNSbjpSINuUp3eMnFbWm9kSOkKsOHGP7yQewMGThS6a+ygBZokNDwJDRgwYMCAgXZiz549SEtLw+zZs5GXl4fzzz8f8+fPx4IFC3DNNddg7NixyM3Nxeuvv44nn3wSCxYs6NBxXnjhBTQ1NWHmzJkoKChQ/vHK7kSw6CQu0Q43jikJIwmUhHpeeVGNUGECejJBiD2tUF0tklAUJRWeltcgvQ/6GDQJGNQ4Xy0loR75SZ/bsv01EEVRURHp1QUA2OW6J0pComBqkTP7En8uvh5I9RF1nl2eRQdCUYZoO1rPKvCiURGvrDjUKXKAIBSJYu2hejyxaK/uNnSyhmR8BZupZCXNvhDSnFYl/DBRuGaou5e2uwmiKMJike4z/38AMJvNit9Qe/DuhlLc9LkJf1otoFG+3ekaSsJkqq09noR1FPnSEuhYVmpfOxWoWrj5jY14ZaUU2ZDlsaE1QJGEOolLyPNts5jw9rqj+M+6I7r7f2f9URTd9znKGvTJJFpJSMh70re1BSVS+/Ev9Z+fP3y2G/d+sB3/WslGaFz43Eq8tfYo1h7qWHZ50t8dqk2s0NVDV7fbYDiK0/78Lf7+zQHlM9IMSFvNdgFtIQGdSXZe3ezHvBdW46LnV2l+n5cqPSSdqRsDMRjhxgYMdA7vrj+K9zeVqT7vrrGDFkKR2GKNFG4sxPUC7ywMktCAAQMGDPygkJmZiaeeegoVFRV44YUXMGjQINTW1uLAAWnic/XVV2PTpk1YtWoVzj333A4fRxRFzX833HBDu/Zj0k1con77E6JAFBP7kegRY4qSUIskZLIr6yf90EpcEhVFPPjxLvzx8z2q7T/dVoFtpY2qY9S1xsgMmoAi/n9aSsJAOD5h8fdvDuD6f63HG2uOKGFW5Dzv+d82FN33OaOIIyQhURKSMgnT9BAlIVcPRKFHyBSH/Dt/KKIQjgBwhFMSfrC5DH/8fA8WvNP51eVkSL9kw43JddPqnmZfCKkOC5wySRjP0xBoX0jsyYRx48bhiSeeQHl5OR577DH07dsX//jHP5Tvn332Wd2s5fFwqEayVthSSSkJKVtSogpIRqjXHiUhTfQmUhImg46GGy/ZHbP+yHLbEYmKynNFwo0tOuHGdrMJD3y4A7/5cKfu/h+V+5pVxbW629B9FCFICDEZFYEHPtyBfy7TV+KS5/dgDWuTQXYbbwEiGRAPxo4g2XYriiIe/Xw3lu+vibu/qma17yjpMsjk1GOT/t/aCZKQhLHzNhYEpE7p7PK+YAQHqlo0tzcQH/Q793iRhHWtAeyt1E6qZsBAe9HUFjqhz/99C3fg7v9tU33eXWMHLfBKQiC+zU9nYXgSnsRwOp2K9x7vCciXJ0+ezJSXLFnClA8eZAdAvGcY72lGJtMEvKdbXl4eU+Y91niPwB07djBl3sOMN/PnPfd4jzavl11dzMzMZMq851ljYyNT5sMB+bBE3hOPr18evAccv2rAe+bx9VVczGbx48/3wgsvZMr89fNl3mOyvLw87vnm5rKG5fn5+UyZ95gMhUJxy4EAO7HnPfyIBx1BRUUFU+Y9HXmPSN7jjvf8+/LLL5nyVVddxZT59rd48WKmPGXKFKbMtwdeOs57+vXp04cp19fXM2W+/nNyWM8dehUKANLS0pgy3775+h40aBBT5uuHv37ec5Jvn/z++eeZv3+nnXYaU+ZfkLxfIPGQbG+YbiI4HA5cfPHFuPjii7t0v10NE6UkDMVREtI+Y5Fox5WEiiehxuiCVp2FNdSCyj4iGolL4gxWPtlWgU+2VeDw4+cziqg6b6xt0eRfayCMdJdNU0nY4g/jjTVH0DfbjTmje6i+3yqTkbsqmhRFCrmG/8krwYFwFA5ZGmOzmAGElezGVrNEIDQTklBHSUjqSiEJrURtF2GUhDQRCgDV8jWVNXS+vSej8KKJu3ikottuQSAcZLJYN/lC6J/rUZSEbcEIsuId6zhmjxVFEV/vqcb0Qdmwa2XoaQcee+wxzJ49G6+99hqys7Px7bff4qc//SkKCgpgMpnQ0NCATz/9tN37Ncvv4kgUaFDCjWPftyfcuD0ELO1DmMiTUEDipDq+UATHmnzIdNs6XNfZMrvUKLcvEm5s4knCiNqTMBoVle1o8OHvH28tx6S+WchPi1UynXCIhFqSXdF9rN4xCHmup+TsaDKUbI8dta0BHKjqOEmYbLttaAvh5RUleHlFiZIUSgvljeo+SfEklG+7Wx6+eYNS6HFHkGhiS/q1qmY/RFGEIAj416oS/PWr/Vhz/xnISVEnADOgjwATbnx8SMLTn/oOzf4wDjx6bpf5ixr48WLu86tQUuvFrt+fA7f95KGvumvsoAXGk1B+VYVFaDiPdw1Onlo2YMCAAQMGfoSQEpdIb3w6LIjn+AKcyjCRF1YwrP39jCe/xRs/najtecgoCeN4EuooCZMBfY00gUYTlE2+ENJdNtS2qj2rfvvRTizbX4OcFLsmSUim+VExdj28CrDFH1ZIPYI2efJEJjTNcrgxGZDyikqiJCTEmBJuHI4yao1AOAJ/KKIcL5aYofMZj70JlH0Aq0BrC+lv77KZUe+N+USGI1F4gxGkOq1w2qQ6SORNdzxJwv9tLMO9H2zH1ZN649GLRib+QRxMmDABR44cwb59+zB48GB4PB589913+M9//gOfz4ezzjpLldAtGRCVXFgEmrTCjduhJGxP3ZK2CyTObpwMjtS14ZfvbsW5I/LxwjXjOrSPLEIS+qT2RWf8NpsElZKQzr/X0BZElkefGBIgYGd5E3757lYUpjux6r5Zynd0uDF5xnliEpDattbkkzzXevXf2MEM7FluG2pbAyiu6ThJmGy71SL/tFChsR1pt6S79NhEAEKnlISJ+hHyfTgqKgs6lU1+hKMi6rwBgyRsJ05EuDFZZAuGowZJaKDTKJGtB1r84ZOKJOyusYMWwqJaSRiJottYwpOnlg0YMGDAgIEfIcxU4hKapONVMjRJKIqJk3HoKQkD4SgWvLMFE/tmqr6j90mUc1rcn54nYTKgJyw1rdpKwmafNMHQCjcmSkEN0Q/zuShSiUs4FWBrIIycFDv2V7Uo5B8h3Gxc2K3TaobZJCAUEXHne1tR2tCG/90yVSENiOqFXH84KjLk3Td7qzHkwUUY3iMVl43vRSVm6PzIri0JE3pageaPoyQkakGiJCSTPNqTMFF4c0dVVR3BPjn0aGdFx0PaDtW0YvGuKtwyox88Hg/GjYsRYA6HAz/72c/i/r7eG0R1i5QBWwuxzL1Ao1/6mw43pj0JRRFoDgC0bpzuAwLtqFvip5nmtCp/60FIgqsmobZf7qxM+hx4ZLgkkpC0Lz2SkPRbQeqZrWoOxCUJIcQUkzwhFo5GYTEJCEdFtAbZcGO6z/IGtSefDvk51VMSNnbQnI/0d0fqOue7l0y7bUuSGCrXUDfXyhHBVpNUWR5ZSaixfpM0EimgaUK22R+Cw2pW+lSvkXij3QiGozAJUrs/XkpC+thug9M10EVoDYQAOBJudzzRkbFDRxCOsNmNge7NcGyQhAYMGDBgwMAJhNkkqFRmgFqZR5NoUrhxAiVhHK+stmAkofIv3v7bm92YP6+CNAeONfl1PQmJEkprMkn8rPTCKGMEgKgQDrwastUfxptrj+DBj2J+Z21KuLE0+iKhzg6rSSIZIlEs3FKu7JuQBrTqhUAr3HNXRTP+8NluXDVJCre3dYGSMJFHIMApCXXq02O3KMpSoowivnYsSRj/eO3xzessyL3tTD1e/MJqNLaFMLFvJsb1ycCBAwewevVqVFZWQhAE5OXlYerUqRg4cKDm78/8yzLUe4NMSF29N4i1h+owokdaTElIhRtnUPMbCxVu/MYO4HfLTXj/lnqML5IIfPoZ9ifw4qRBSPYe6U7sOdaMUCR5NU+a06o8YwT1Ollo2wOSJbypTUNJKAiKOpk8V/QiR1WLH8OgJmLpp1qvvwtHRaS7rKhtDSoqqpifE+1XGAFS1L+PKYS167+hg0pC8iy2BSMIhCN4ZUUJrpvSBykOa4JfqqHXbmtMGXhvQymundwn8U4AVDSpScJjstCRENpu2ZPQG5Ta9Tu7gEuHtm/a7oujaAbYd0GrP4zclNi7oKNJdH6oCIQjsJlNEOKw/cFIFHaLGTaL6biThO1JuGTAQCI0+U7OxDvtHTt0BKEom7gE6N4MxwZJeBLjo48+UjwJ9+5lM69lZGQw5Ztuuokp855+/O+XL1/OlHlPtZEj2dAd3iuM96jjz2ffvn1MmffM4xUybrebKdtsNqbMe5wVFhYy5aamJqbMe6zx3/OefbxnW1sba6bMewryHmu8lJj33Dt69ChTplccAGD79u1Mefjw4UyZ94TbuHEjU+bvB399/fv3Z8r89ZF2pre/mhrW7PqCCy6Ie368xyPvucd7ZPK/z8piXa/WrVvHlHnPxptvvpkpT506lSmvWLGCKY8fP54p8/dr165dTJn34Ny2jTWvnTFjRtwy72G4Zw+b2IGvn0iEHQTzzyvv4XnOOefE/f2xY8eYstnMKpj46+PvT20tawrPe0Ty11taWsqUeU9Gvr7J88y3yx8LzCZB0/dKFW4cYgnEhErCOIPz1kAYiRKuaYUZx86tc0rCTLcNda1BJsMvPQknJEW8pABkcs17pJG5kogY6cpfS0sghP9tZNspIRAIsVOtkIRmWM0mZh913qByvUT1EtbIokpj2oAsrCquw7Yy6X1EFIudQVKJS2hPQo7Eaw2EMfr3S3DuiHylrgghRO5BqsMKp8wQJFQAtYPI6izoLLjtwdK9VXDZLJjcL0vxx6utb8CFv7gBn376KdLS0pCbmwtRFFFTU4Pm5mbMmTMHb7zxhqrvI3UVoELqnly8F++sL8XAXA8uGiv1baEo0OSX1FguqvuTuVeEosA7u6R2t3x/jUIS0v1BR5SEhekO7DnWjFZ/GBluW4JfSfj3Tyfi7v9tYxJqaCnM2guXHLLewiUPAaRnjg83pvuvai6hhiiK+Pfqw0z7b9ZR9IUjItKchCQknoQkcUn8ZxaIkZk0cUWPYRu9ncse7Q9G8Py3B/H3bw7gSJ0Xf75kdNL7aGpqwnXXXadqt9U1NWhuaoZjwERkn38nhvfQVrryKG9UJy450iRdP2mripIwBLy4GXhyrQm7a0Q8VpT0aSfst+hwZLLIEiNVkycJBv7mC8weUYBnrxzDfL63shm9M11KmzzR8AbCcFrNmp6Y8dDUFsLoR5bguil98MiF+skRguEobBYTPHbLcVdiJko0ZsBAe5BIGX+8odcHJxo7dAThKOCU+19FSWhkNzZgwIABAwZ+mJBIwljSCwK1kpAmCdmkIVqIpyQEEv8+XmIUhSSkjf/b4Ulos5jgsJp0SRAy4Q8mSOHc1KY1YNRQEnJ10eoPo7SeJaUJCUjOiZBkdosJFrPAEJZ0xuLa1iCa2kKMZ6EW4TCyMB0AlCzPyZKq8ZAMSRiIk92YqAa/3FmpkDOEOGtilIQW5nhf767CKysOAZBCwu9fuAMt/lCXhhv/a2UJzv37Cl0ynE5wse5QHRbtlBZDDtW04qZ/b9T1ivvp6xtxxUtrmc/++sj9KCkpwZo1a9DQ0IB9+/Zh//79aGhowOrVq1FSUoJpF16Dwb/9UrXICbB1fFiOz2xoC8FKJS5pDABpdja8N1F2Y1pZ3C4loT+mJATiJyvgL8diitkfECTraRcPRI1Ksi3ThzBphBvThHZlE7uQWFLrxcOf7lbKkajI+DDSCEei8NgtMJvUoZZ0t6BHEobCpF+InY+Xeo6Ix6IW1h2qw7bSRs02oyjjQhGUNkhtprJZba8QDwsWLFDabV1dPTZs24n9+/fjiY82Iu+aJxFurET91/9kkhHFQ1m9eqGuRF5jt/HZjYNARavUmA82tuu0dRcbDlS1YNTDixnlKrlnhBxMps8DpPseioj4dBubWG1XRRNm/20F7l+4Q+eXxxcltV4M/91i/O3r/Yk35lDTKpG6b6w5Enc7liQ8/uHGBgx0FRIl4uoOMBEz3HiE7oP1xg4LFizokvPQym7cnUpCgyQ0YMCAAQM/OoTDYezevRvvv/8+HnnkEVxxxRUn7FxMJkEJaattDWDJLsn3i55YSuGtLIHIZ9sF2AFMKAHBtqOsKe738ZSEh+u8WF1cy4Ubx92dcn7BSBQ2s0mlzqNJEDLhj6ckBKA5+Y1lLo0RfjzR1BoIq35LSE7eVN9hNcNiMjH1zROMM576lqlvkkWVJoRGFnJZyrtgspZU4hKaaOKujb6mSlmtRQhacg9SnRaF4CGT+5ve2Ig/fr4Hoiji4U924Z31R/H0kv1dmrjkkc92Y8+xZjS0BeEPRfDIp7sZ5Sk5d6vZhMtfWotb3toMAPjdJ7vw9Z4q/P2bA0kfa9U3i/Dyyy9j0qRJqu8mTZqEF198EbvWLEUgHNUMn6PVmqQeA+GIcv/DUYlU8XBiPk1fIarRxLt38dDiD8FqFpAt+/gt3VuNDYfrNbflFxMsZkGlzmT9UDvGbitKQn98JSF5VGkyo6qFVbjxz85rq0rw5GI2goUgHBVhMZvgtpkVoon0O/S16D1LpN+lFzFoAlqPgDtS58XlL63Fhc+twooDrBo/GI4q5xCOispz1d7Q+U8++QQvv/wy+gwZjb98tR8T/vg11h2qw7EmP+w9BiPrnDvQdmAdKpti9afXp3oDYZRo+COWNEr/1wo3pv1f2wO9xCVPLNqnENwERDlEyMFfvbcVt761KeEx9LKBrzskPQdL91Ynfb7dia2lUiTXc98dTLClGsz7M07/QN65bru5Q++d/20sxZ5jHfN+7Ui4cW1rQLe/MvDjBnl/rDxQi8l/+kaxhelO0H0m/74kfXC8scPHH3/cNecRjWU1VsKNDSWhAQMGDBgw0Dl88MEHmDdvHoYNG4b09HTMnz8fS5YsQXp6On7+85+fsPMyC7Fw46/3VOPmNzdh9cFaRqUnirySUNRU7tG/SUSwVTarQ8uYfcVh/b7eU40bXt+gqARMgprU1IIvFFFUDXSyAoBXEsYyI8aDlh8YHW5M6iDEXYtWaCIRAvKTLbvFDKtZYBQstJIQkNR3EQ0lYRYV4jmsRypDGiZD8CVCMgkJ6Oshf1c3+7GquFZTbeoNhiGKInbJCUEy3TY4dTwJadKstjXQLYlLolERz31bjH+tKsGvP4hZcyjhxpzqzSMnn9DK1BoP8Ty96O9IO2WTikSUz47Jvm6BUJRS3AK+MJhQYyCmzgpGtI9Nt//2TLabfWGkOqyKD+DvPtmFS/+5RnNbPhzQYjLFDeG+4bUNHQr5UpSEii9g7JqJklDUCf+t5SaCvJpsf1WrooAFJBXZR1vK8e/VhxGOijCbBLjtFoW8J8pimmTRC8Mk9U4fk/Zs1FOs0sQc3xZ5kowQ8h3JAlta34bJj32Df3xbjEA4ijve2YLNR2ULIbnd0sdv1VHi7K1s1iT7FJKQKAmVcGNBmagms0BEg65Lcs9FUcSq4hiZmi4/LIQUoNWHX+6sbJc/Kv2eOSwToUVZbtVv2oNl+2uw4J0tnVbK0R66yeJwrReLd1Uy78ztcRb9guEo7BYT3B1QErYFw7jn/e34x9Lidv2OQKvfCkeiuOu/23SJwDnPrsSl/1yjmbjMwPcHwXA04Ti0vSB95f/9dysqm/34hFMKdyWqW/x4+JNdjLJZqz0nO3boLI63kvDkMGMwoIlwOIxQSHoYeI8x3pPss88+Y8q8t9eZZ57JlHmPsj59WFNj3mOP91TjjThbW1uZ8u7du5ly3759mTLvkcdfD+9Z9u233zJl/vx5D0X+97xHH+/Z2K9fP6a8YcMGpvz1118z5fz8fKbMe7bxHojkPhLwnnq8J9+BA6wCgvd85Dud8vJypjxs2DCmzHve8Z56V199ddzz5T0eec863uOO94wsKSlhysXF7GCjd+/eTJn3ZJwyZUrc3/Megnz74q/X4/Ew5SuvvJIp8x6HvKfnT37yE6ZcUFDAlNesYSdj/PMxYMAApszff94jdOzYsUw5kQcn7+nJe4Ty7Zd//iwW9tXA12fPnj2ZMv888ueXnZ3NlPnBMD1J6E7cddddeP7555GdnY0HH3wQBQUF+NOf/qQ6v+MNs0mAIEjqnaBCuASZidefF+/DP5fFnrtoVNRU+tGToc5OXuIpCcn+yWTPYjYxhFNUjK100vAGw8qEhSQDIWiPkrBHmgMVTX7NCbpAhRsr2Y25aymuaVX9jpCuPEnosErhxvSxjtSrFTc0QUbIy3SXDbVycpYMlxUDcjw4IHu9dYU3FO8xqAVyPYIQO8eZT32HtmAE78yfrNo+KgKH69rw6ooSDMrzYEJRpqIi4Y/X4g8zKsOuVBISBMJRzWQ1ISXcmFbeRZCXKqVQ0Ard1Otjps06B/Pnz8err76q8qzduHEjbrnlFrgGTAQgtdM0WBmigw5RJ3UcjEQpT0zAGwJyXOxxaSWhcmo0+RimCd52kIT+EFIclqSSYPBeh3S4Md0nESzbX4Mvd1Tisgm9kj4fQCvcWJ24hElYQZEZvPopkTdmky+EX723FYCUMMVqFhiChKh+6faqR56Qe0sTo7TNQaOOkpDOesyHyPHnTxI4JVJ/85gzZw5+/as7EJg8H/YCaVxe0xJATUsAgWMHULf4ObgGTMQxirBs0fGn3FmuVoql2ES0BDlPQircWOigmoW+fpJUo7Y1yJCnuSl2NLaFlLrjF1XWl9Rj5uBc3WPQSsKalgDy06R+4VCN1HfnpSZOudvsD8FlNcOiQd7e9tYmeIMRnDM8Dz8Z1UPj1/qobPJj+f4aXDo+NpZqD9E686nvAABv/myi8tmuiiZM7JupuT0TbhyMIBoVk/Y/JP1cWTsWXeiIBi1Pwr2VLfhgcxk+2FyGw4+fr/qetNdmX0hRQyeLQzWt+GZPNW46rW/SBI0/FIHFJGje55MFkaiIv3+9H5eO74Vema7EPzhOIEncSPI9GsMeWoQsjw3rHjhT45cdA+mHyWuy6yg4Na57dT32VrYgk+ov+ffhnDlzEo4deB//jiIcjSm6iaKwO6P5T96nwYABAwYMGOhCvPvuuzjvvPMwceJELF68GHPmzMFZZ52FF1988YSel1keyNop9Y7NLDADbZogBKQBEu+NArDEXjAS7RTxmigxChCbvFtNArPCGtbxM/QGIlLok8UEs1lgzpcmK8jfeiRh7yxpkKw1QSdrQqIIhiQURREOWQ5TppGIgVwvT8bYLWZYTSZm0k/CjX8+vR9G90oHwKoaq1oCcFrNcNvMzH4uGRebFHZFuHFbEkQjuS/pTqsyYSMTPz6LLcGGknoEI1H8dFpfWM0mhgikFTwt/lDsu1CkXb55oUgUv3qXUj3pnn9EaSdmk4Db396MOc+uVEhpXg1GzqeqSa2U1SNhfvXQY+jRowcmTpyIzMxMDBkyBEOHDkVmZiYmTZqEgoICZJ4pqY0JsaSlLjjGHZN414WjgC+kVhJaqcQlBDS5wSgJkyRgWwNhHGvyI9VpVVSV8cArI+hwY4/doiTy6QjoObpLPheyAECHGxNVMU0E0SQ6/6wk8qWjQ4CD4SgsJhNHEkrXTF+73vNInpmWQFjpc+m+oFHnGaKJRN4vkVcSHpX7E3ohQhRFbDxcH7cffvbZZ5GRk4fKN+5E6d+vgPi/X6H85VtQ+vcrUPnmXTB7MpB55s8VdavWuRDsLJcW93JTYqRMH8ohwcaHG4dik0it18yuiia8tqpE249Rwye1zsuS+jnyecQ8CbmEbvvZxXke9PNCZ20mCx6JSPcWfwjTHluKV1eWaH5fmCH5fa49VBd3P1q44bX1uPeD7VhzqE7TNiRZ0ORzab0+iReQSUK3/Awms7hEQO4PUaM2eIM4XKteJGN+E1IvoNBIVjGbaKFSC7P/vgKPfrEHe461JN4Y0jhqyIOLcOPrGxJv3M2IRvUT0m0tbcAzS4vx0ZZyze9PFBa8swVj//CVpro8HBVR1U6f1UQgbZ70K514PcVFMBzF3kqpDVm4hUgazz77bMKxwzPPPNMl56SpJEzwiIiiiBteW48318b3LdWCQRIaMGDAgIEfFLZv346oBkk1eTKrmpo3bx5Wr16No0ePqjKoH08QRQ29EmsxmeImAomIiZWEoUg07gRzYt9MvHezWkmmtS89kAmcxcwqjvQmPmQSbDObYDGZmGP4mYmF9LeeGrK3vJKu5QemKAkhMiRjOCoqWXppgoeAnIqeklAr3DgnxY5JsnqDJiyrmvxw2y1M5mW7xYTLxvdSiJOuCMVJKruxfD1pTiv8oSij3tQLGyXeZAVy4gsnlbiktoVNKkCaaVswopsBVgvbyxrx0dYKXPz86gTnH0UkEiMJP99+DDvKm5S6o4lObyCsTEq1wun1Mm06Pan48ssvsWvXLjz99NO4/vrrcd111+Hpp5/Grl278MUXX8Dk8CjnA7CkMCEkSIgpmbgopFQUaAsBLo6zIyGcoagUHk//Rjrf9ocbX/PKOjT5QhAApDrUJGGDN4hPt1Uo90cz3FiegTgsJuWZoVGTRBigRMzHyi6rfrgxIQlp0puuB6I+bPAGsb+qJWGoKXNvwlFYTAI8lB+bVt+p9yzFwstjmZnJc+OymREMay/G0AlNeCUhOX9CwJJj0+e9aGclLvnnGvx5ERvJAMTCpdPT03Hv3/6NHj97Hnc9+EfcctNPMeaMC3DmDXdj186deOf9j2FyeBhyXI8k3Hy0AYXpTkVxBwA9qKAb0lbdJNw4GJuoar0qzn9mJX7/6W6UaBBK9P0j107UlAQ5soKM1DWvvvxy5zHNhTICui86JmdtDkeiqJP7/kR2D9UtAbQEwgpRwKMgTeobVx6IT1Zq4ZBcJ2UNvnbbTtDPKx06flQj6QwB8SQkiwZ6qtloVMT8Nzbiwy1lymeE8KtpCcAfimD6n7/FzKe+i9u/08+S1js82YzHySrT/7uhFIt2VjLHSzaRWqtc/7xv6InAdf9aj/4PfKH5XUUj8brtHunYxc+vwuQ/fdOu36w9VIfPth9DWzCi8gbsysgg+jknVjHkk64M56Wxvyr23NPPGd+e09PTE44d0tPTu+ScaJLQYhKVz+LBG4zgu301ePCjne0+nhFubMCAAQMGflAYM2YMjh07htzcXPTr1w8bNmxAVlaW5rZOpxOPPvqoKoT9eMKkoSS0Wkxxw4+ioqg5QWJIQsocXwsZLmvSIUd6IIMnKxdbrHdcorqxkXBjJixJTYjoKb8ISajpB0Z8sqKsyXQkKsJls6ChLaSakAJSnYYi6jojiUtoVMsDYofVjBR54kUTj1UtfvTJdCmKLJvZBJNJQIbbhuJHz8NvP9qBd9aXwhsII92lDv1LFvRkOyJ7r/Go9wZhMQnI8thxpM6reHIB+pkCiVKEqIoIwdMWjDAEUYs/zGQfpdU7oYgIm0W/fdEEajwEqHZMq9p8MglQTSkVjjX5mQmwPxRhyHe9BByEdBk6dCiGDh2qOgd6W38ogtrWAK5+ZV3sM05JWJTlxqFar3IuxHPQZWXbFjk1eqBPnz+T3TjJCfNWOXt2IByFhyMJRVHEL9/biuX7a+CymXHG0Ly4SkKL2QS71ayQYwTxzOJFUcT/NpVh1pBYKOgfLhyu+FoqJKFG4pKWABWiSx2T/P2TZ1eivNGH356vvkc0GrhFAItZgNtkQVswwtgQ0CD13uwPobi6FWN7SzYvdP3UtQaQ5rQqKscMlw1tQZ8SMkuDJq9VSkKZRMl025S+BGAXGgiR9Nn2Y7j/vNj1frHjGG77z2YsvG0qxvbOQFsgDGt2L8y7YjIm9cvC/dRxcjXIXK1nvq41gIM1Xsw9pQeOUGRTKtU1KWFuJsBpEeEN6Ycb04sfm440oF8Oa/HiC8a+J4QS7z9HKwmDGu+yY01+rC2pw9T+2nYhNBH16bYKvLT8IHMe3kAYH24pw1e7q/CPK8eq3oWkPdRpLCjR35c2+CCKYrvIinSnFdUtATS1hRDiFjQbKasKLZBwaYB9RvhkWjSC4SiscuISQKrTPI3tGtqC+Gp3FWpbA7hojKR6pwm/yia/ckw6xPRwrRfljT5MGyDdC5+GFQMN+rMWf0jXFiHZTNb3yl61dOhysv3liciWq4eVsidnIBxR9SdkAaq9C4tNvhCiUVHTYoDG5qON7dovACaZDX+v9JITdQRse5HuV7SblYT0e5juv7V8nAH9sUNXQRSBUFSAVSYHlcQlCZpDogW1eDBIwpMYo0aNgtstGevyHoCHDx9myocOHWLKfj+7gs57FKampjJl3hNt3bp1THnUqFFMmfe4q6tj5fb88SdMmMCUN21iM5ONHj2aKa9YsYIp855uvEcfP8HnPd8SeaI5nU6mzHsa8p5wDoeDKfOecPz9aG5mvV6qqqqY8sSJE5ky7xHHeyjy9c97RvLb8/eb96BctWoVU87LY4cPwSA7SOI9+vj7zZ8fX1+DBg2Ke378/ZwxY0bc7fnz2bmTXTE5/fTTmfJXX33FlP/zn/8w5WnTpjFl3lMzN5f1weE9+HhPS/555T0Rec9G3vPx3HPPjXv8mpoapsx7EqalpTFlvv3zHpkjRoyIe76bN29myvz58/XFe6ryHolerzTo5dtRR5Geno6SkhLk5ubi8OHDmqpCHnyfcTxBiB07lyxATyVhNQuIitpEHB3mG4poqw0J0p22Tg+wyECKJ9HCOiMXRUkoJy7RU0qRv/UGZL0y9cONySVFRRHBMEUERUUlFFnLED0SFTUnFnaLSUWCEhSmO5VrZUMFISsJpQOS7NWAdL/dsjKvtZMkoTdIk3JRmE1q4q2y2Y+8VAecVjP8oSj2Vcbep3ohliUcSUgIHn+IVQzQJGG9N8TUHwkr1wNP2OlNsgOhiJIUxky1M5LpmA6lvOxF1g+2sS2EZ5buxtnD8jBzcC5zfmFGdSuFo3/99ddYvXo1KisrIQgC8vLyMG3aNEw5LfYO8oci+GLHMWZyqSgJZfVinywXDtV6VfXLhxuT6glFpH8Ae09ZT0KiuArg9dWH8dNpfTUnftkeyQfzTxePVE2+A+EoDsgKif1VrRJJqOVJKJ+YSYg9K5eN74ksjx0vfHcQ1XK24TUH6zAoz4Msyjfsk20VuPf97Zg2QFqYuXx8L1w7pQiiKMIkUNmNNRKX0M+zlpKwXA55PJQg3JEPo7eYJXVkJCrKpLN2wh4AuPj51SiubsX635yB3BQHcw9Kar3ol+NRJsBpTivKG32yz6r0jKw8UItdFU3MtbT4w9hW2ggRwCm90pXfq0hCX0h5FogPFq96fmf9UQDAKysO4fmrx6E1EIavZAveeG4lXm9rZNrtqTNmqq5TK2nTpiNSyP/4okxFsQQAVOQxKOcEuG2SkpAMJfjXzPayRuXvzUcbcOl41r/SF4rdW5+eklA+eLM/rJroXjSmEB9uKceGkgZM7Z+NbaWNMJsEjKAyyNP9y6JdkspsG5XcwxuI4P/ek/yqm+aGlGdp89EGrDpQi3FF0jyDJ5wJyLMdiYpo9oWRxj/ccZAmk4T1bUGGLAeAUx6RxqdaXn2AvsLpaH2bbj8airDhxnrJawjRs72sCd5AGG67hSH86AQ4Lf6wQhISj8S9f5gNh9WMNur+aioJqT7nSF0bc9/Y80lMcPDREwTJ2nloPQ+JUFLrRVGWq9tUbA3eEPLT2Hc5CZlvr5LwoudW4VCtFwf/dJ7mIiKgTjqX7HXR70CeJNSzMukI6Pe2QhLK97277gFNcpJEeoDawxdA3LHDGWec0SXnSBZiYkpC6f9h/SE+gOQsafRghBsbMGDAgIEfFObNm4cZM2agb1/JuHr8+PHo16+f5r+TAYT3oFeOw5GobriM02pGNKqT3ZgaMNd5g7jhX+t1j3vd1D6dHrwQVYGVU4zphSo3eGUlodkMi1lgBvV8uHEkjj9Pboq08KBFIpLfREWR+T4ciSoZjLUG2lFRVAaGLmpG7OCM69OpyeDAPA88MhFTz6ka3XaLQg7yBLBbCfvSHsCtL6nHlgRefQDgoyZReoRqZZMf+WkOOKwmBMIRlNTGSEI+3Jh4KB6q9cJiEpAhE5jk/P0hXkkYUiacdd4AQ3AlSpxDfx/Pt4hWEtJzHEJWNsdRglQ2+/H2uqO44bUNyr7o/SrHP1aOMWPG4txzz8WHH36IQ4cOobi4GB9++CFmz56NqZMmIdwiqTz84ShSNcg3AKiUJ3JF2dICLx9KqJfdOCQnNgG4cGNqQuILSSq4L3ZW4tmlxTjjL8s0Q7qC4SimDcjC2N4ZKk9CXzCCLDnzBCFZVeHG5lh2Y7p/OGd4Pn49ewiy3DbUtARwrMmHK19ei7nPs4uMhGRae6geQKxvEASJHCfPJ21LZjFJiUvocFt60ukLRZiFh4PV6sRDNPxc27OaBPSRfUxXFdcipDGz8gak+i2W903C6ul2UqwkHZLuUYYce0u35WteXYfHvtyrkH8pdgsO13px4XOrMPe5Vcy1ZXIkbyQqKu2Z1DyvyBmQKy3a7a5oRnl5OR6bfyGq//c7fLv4c1W7nTZ5Esy+eub3vHJKFEWFeJzcL1MhEsyCqIQWS3UY+9tjlUhC0lT5bnoLpUoiBCQNmngiRBBPhppNUqh7qz+sIiBIHZCQ7gufW4WfPLuS2SaRkoy2I2gNhFHV7Mftb2/Gxc+vxtNf7cc+Ocy43htEaX0bFm4uYxbuaBKK+CmuPFCLO97enFDtleaUKvZYo6/d3rSHa2Oij1ZZeVuY7oQvFMG+Ku3Q6HBEhDVOuPHCzWWY8+xK5R5EoiI2yveNrkfay1frvImSuk1noUPrs+LqVizdW6XptUf2s7W0EWc8/R2zIERAk3z7qNDwZFWI7SUJNx6ux+lPfYfFMvHcHSDt6cMtZZj55LdoC4Y7rCQkCyrLD9TobkM/e3rjCC3Q4wee0KWJtc6GHjOEHUlcIpdNSY5hH/tiD659dV3iDWWwxKS+krC8vBxjx+qPHcaPH69KLtoRkFeM4kmYpJKwvXYGNAyS0IABAwYM/KDw0ksv4aOPPsJdd90FURQxf/58/PKXv9T8dzIg5kkYeyWHIqJuuLHTZkZUx5OQ9gJ8cflBZaDPY+39Z2B4j7SkB1h6IJMNK68k1As3ZpSErCchQ+CE4vv1pchhlFpEFJ2UIMQkUxF1E6oA0so0IWV6pMfU5VK4cayeRlKqh8J0p3IuhAAl8FCehHw9k8ma1kTLH4rgshfX4KIEXn0ASzKGNOoiGI6itjWI/DQH7FYzQhFRUWMBasKAqGmC4ShyUuyK2ksQBNgtJvg4JWFrIKYkFEWgnJpEJiIJ6Ynifp3JLdmOtJP2evS1cfVLD/zpv//xx/uxrzGKS576FFu3bsXixYuxZMkSbN26FaWlpXCnpqL+q38qv+MnCnTiEpfNrGTk5BU7fLgxrSQkQiom3Fg+jstmRlSUyqQl1XuDqNBIzkL8x4DYc6JccziCLLdd+T197gRWcyy7Md1sSVhnTood1S0B5dr4hAmEuCb3jE5S4KTId1oVahIkJaGWx2jM3zF2vw7WaCsJT5GTCPFJXswmEy6f0AsWk4DXVx9WhXgCUlum/ecIYRkIRdFXJn0PylnRCQFBVMBaE+tDNa1IsVuQ7rYqGc0J/CE1SUgIepLwRC9cj/Txh+vaMPvS62D3pKLwttfx3er1qnabnp6utFsCniBafbAO3+6rwUVjCjEgN0Ux6TcLUlgxAa8kbAsB5Jbw3T1REeWm2BVygwZN4JAkGoQYIT6a/lAEKQ4LWvwhFeFDCN+mthBDQOi9T7QQ4Qi/W9/ahM+3H1M+I4RTnTeAfywtxp3/3YZfyhmzAbYeSVu55tV1+Gz7MWyTQ/5pvL+pDF/ukPZPFvi+21+DXRUxdWMyIbJVLSy5CQBDC6TomvP+vgJH6thnQ5QXy2wWAQ75fcQnmLrzv9uwo7wJO8pj57LmoBQhRtf9TupcT3/qOzz8yS5mP2UNEoHJhBtrKK8YlefOSvz09Y1KNnIa5Nj3L9yBgzVevLbqsGobenGO9hXU811s8AYx7fGl+Gq3FNFFLzK9tfYI/rJkX1yvS9JHrC9JvIhH8NqqEjz25Z6ktyd98/+9tw2H69qwq6JZ6evJezUUiWLkw4vx16/2K787VNOq9FEA+479OE7CEzrhVjLKszfWHMZn2yviKgnpEN3O+ijSz0Vls5/xu03We/LF5Yew4kBt0oQlfT3Nfu2FOwC47bbbkJmZidLSUs2xQ3p6Om6//fakjhkPIZ4kTDJxCX0d7SVrDZLQgAEDBgz84DB79mzccccduP7663UJwpOFJLQo4caxWVgkKiIST0koaqv16M/ijQfocMLOQMluzGUr1EtcQkgAm8UEK+dJSAaCbptZIvg0Jt4XjykEIJFzFi5cmSAoHzsYjqo8CeMlY4mKsYl5AWXe77CamOujQ6MEQVCIGJ7wc9stCtnCwx2HJFy+X3/Fnwe9eq/l31glq2UKUh3KBJFOJKAiCanQZzrLKSARPP5QhFFe0OHGABvGnUjxQJOI1XE87mglYXv9dWhlY2NbUJdk3LFhFTJm3YS1lepzLigowC/ufwT+w1sBSO2UXNttM/vL+4olLslPdShheKpwY87khwz4/REgIPsWejUm2ER55AtGmHrlyTDit0eeb17B6gtGlO8I2UDXQ5rTCrvFTPUPAt746UQ8c+UYheDLSbGjujkAvSeprJElDemQc1qha9bIbtyoEdpJQplpv0Itu4BfzBqAP84dobomQCI+C9KcOKVXOnZVNGs+K95AGK9TJESMRI0gL9WOTLdNISdJO0x3qpWEBAdrvEhzWTVUpxFNJSHxy6uVyTKaJKT3T6tadm1cjbyz5sPiyVSyRxMUFBTgqaeeQstB1h6EJx8JsTNX7lvJ+8hsYpWvtJLQYQb8YSCoQxKSfqUww8lkhdY6B0JK1LZK3ql5qVLf6w9FkOq0oskXUj33+akO2MxSxnlasdT/gS/w3LfFyu+TRUWjT+XJtqsilgWZhHp+uq0CflnRyygJuVBp3oMyEI7g7v9tw63/ke4FIbwb20LYcDhGNtFKPT1UUwpIUs83TivCPecMRlQE/vDZbmb7MEXWOxTbCO2+mQ4RXXuoDn9Zsg+3vx1rP1s58vP11YdRXB0j1sn5M4lLuPfA66tK8BeK2Ppmb8x+iX8/E7KREMdaqj/a5mNlcezdqUcSHqptRXmjT1Hq0/v87Uc78czSYt1kNUDM3mL3sSbdbWgEw1H8/tPdeHHZocQby+BVtVazSVGpk/5/y9FGtPjD+Ps3B5TtZj29DGc8vUwp0369tRo+zAQ0SZiMsvWhj3fhjre3xCcJqXrlkw61F3R/0dgWwrayRoUcbK+y0pvkubDhxrSSkP39N998g7/85S9oMXnw6Oe7GcU76YO//vrrdp2jFiIcSaiEGydSEjIeze2rK8OT8CRGU1MTQiGpYR49epT5jngVEvAeasuWLWPKvCchzybz259/PuuFwXvM8efDe8yNHz+eKfMeg7xH2FtvvcWUec88PiywoKCAKfOegJWVrAy8qKiIKRMPNALeo662ls1ylZmZyZR5D8cLLriAKe/ezb6keU86/nx5D0HeA5Cv74qKCqbMe8Dx58t7yiXypOM99XhPOT4TLF/fvCdjOBz/pTN48GCmzHti/vWvf2XKvMck71nJm8fy9bN06VKmzNfP8OHDmbLFwnaV/PXxnpUmTlU1ffp0psy3D94Tc9asWUyZv99mszluubS0lCn7fOzAk29fZ555JlPmn5cdO3Yw5YYGdgWV9zDkPUN5z0beY5F8z/dTXYHXXnuty/fZ1VASl1CzsHBUO2MmEMs0q0XEJTtgUsIJ0TVKQosqcYn2+RPFhV32JCSTgg2H6/GfdVI/l+q0ypl/1b//40Uj8OhFI+G0SUSG1vWSQVowEoWVGkFpJSWhERFjnoSFlJLQbjEz1zckX+qviWcWTwIQeOwWxcuQF2wSErKiUT0pXLg5+dAU2lRfqy4ISZif5lAUOzRJyE9maY+7nBTWS9ZhkTwN6UlfayDMDELpSWYi9QC9n3gTen8opiRMNoSMgD63RTsr0ScrNnaiCTaLzY6oTz+EtaqmDoLFJv8uqpA2JDEIIfMqm/wY2TNNUQXz58vbTwoCYDWJoGzg2HDjSIwkPNbkhy/EkoShiIgrXlqDGYNycevM/ghHJQUyWXDg7QR8oYhCuBAFIF0P2XIoslVRkwmYPogd/+WmOOCTk7dooZwjOmii3GWLvUtp/txsEhCllIQ2SyxbOglvTjR5ddosSr3z5Cl5fp1yNmItz9Q9x5qx+mAdBEFaYCHkQ0D2G+yf41YUgV5FSSg9+3r9brrLqgr5rvcGmcQlBCMKU7GjvAnlDT6M7Z0BP9V2jjX5lLbbGgjDahbw2YLTMOwZG0rKq+Hok6+ZhbqhoQEmq9RPZbltqPMGmTbZ1BYj2YiSkVgrWExgwo1pJaHdIqkI9ZSEZFJdmO7ElqON8AbDjD8mTRp8tr0CH24pQ0mtF5luG6b0z8KB6lb0znQh3WnF4bo21XOU5rQizSURiLSyDgCeXLwPt83sH7f/cdvMDFmglYF5N5WUoYoi5vZVtmBwfgpCEREZLisa2kJMmDwAxtcRALaVsmMgvRDAQzX6fRBBNafkBqR30O2nD8DSvdUqspO0TavZBAdlG6EFcp0Wk4Ad5U0qUnB7mZoY+2JHbPxf3uBDcXUL5r+xUfls6d5qnD0sTyHBH/40Nv6dMSgHy6hFsca2IONvSuopVSbjtTJz11MK/lXFMX98PTKIqMLoREU8eBsOGiRT9u6K5qT8+9Yeip1TJCr5smr9hlb9qUhnX0i578FIFDvKmnDDa5KVjNZzr5wrRf7FSyRSSYVxk+ROetdFL1g0xwk3pscCbaEI2FlB+0DIrXNH5OPLnZVYuqdaWQRvL0nY4A2q+mQt+BglIUUScv2K0+lEVU0tbn5Hygj+k1E9MLpXOpr9IaTYLWhoaFDN8ToCwu+RaUKicOPVB2vx6ooSXHBKD+WzRl8QTlvy52IoCQ0YMGDAgIETCCXcmFIShiIi9CJjiRpHa3CUbFiHVjhhR0BWki0mniTUDpcmZv42s4nxJLz0n7GEE6kOKwLhiKY6x2IyKYomm0VSkvx79WFm0k/22V4loSiKymCUDjc2mwQmMcvY3hn48yWjsPDWqQDUIZ0EHrtZUXLxZGxvOVzuSB1LjO851qyY7OdwSj4ebcEwozzRuvdkkpCfFlMS0v5/aiVhbCKfl8oe32E1wR+KMOE2Lf4QQ940+vQH0zySzdxLKwm1JnTxQJ/bfQt3YMPhmD8bvao+cvq5qP38r/DuXcksajQ1NeH999/Ho/ctgHuYlLzEH44RdSSztT8cQYs/hJZAWArttiSnJAQkMkaPJCQh5KySMNaGm3whrD1UjycW7UVpfZtSp3oJY/yhiKJiKm/0KYk8CEiYNGmvWv2DR86QyofXE/BqKCtDEsb6OBOnJAxHRYWYo1WsxEOx1R+OmwjHaTUp9R4IRxmVNHl+7RYzAuGIZt9JCMqrJ/UGECMfJJLQhII0JxrbpOQ8bYEw7BaTMkEndcgvjEjJodhKrGsNKhN++hkf1TMdgJSAAmAn9XTIbrNfItwG56egYOwZqP38rwgVr0ZrS4zUIu32xhtvxJBp0qLcTadJi+3kWfvvhlKMfmQJHv1CCoMkBC7py00C4KSVhBQXQZSEpKkSslAURfxj6QFsPtoAi0lQvGObqWQDbUHWY/DLnZX4ek81DtZ4keWx47fnD8PL143HJeN6Is1pRbOGkjDNaUW604rGtiBD4BFsLW1UEcU0iFqRQGsf9LviKJU5eFdFs/KM9pYTaPEZkPnFHxK6CwA3vLYeZQ0+DCtIxaS+7II+HUavt0hInysJ+SfPRYbLhmYfG4JN/DetZpOicKbbFn2dpJ2NL8qI+66kQRNqZQ1t+O/GMub79SX1mEWp22j0SGfvA1+PhKghSlRidfHO+qMorm7BV7urGEKShp7qnLzzWuVGSytRCeItSBC7jmZ/GOWNPizbX8Nk+eWxZHeMRO3/wBd44MMdmtvR1hS8kvBwnVchxYLhKP7w2W7lGeqb7UZpfRv+sTSmKCT1RXs4xlPz0bYVj3+5B6MeXoJVxbWa29LnRivsulNJSPqsyf2y4LCasK2sESKIkrB9IbQ8oa8H+pyZJGXcuOaKK67ANddeB+/elYgGvGjyhVDR6MPY336MOXc+hRtvvBFXXXVVu85RC7wnYaLEJVe9vA7f7K3G0r3Vymdaif7iwVASGjBgwIABAycQSnZjWkkYiTLhxhYqNJdMTMNRUVG9ECRLEhKlUGc9CcnxtMKNtbxiiPpIy5OQwGU3o9kf0pzI09n5rGYTtpU2YltpI5p8IfzijIEAYoPGYDgKq5n1JIw38YlEY4lLsj0sQUZnN3bbLbiMytbJZ5CltyNqT76ae2Y4YRKg8o96V04g4JYVT/FAkiiQthFPSZiX6mA8L0kGXF4xQYcbkwkwgcNqVvnx1bUGmUE6fc6JDNDpbflJBOMtFooq2Y15hUUi8CFnOynPLVq5MfPau7CztAG1nz2FzMw/Kxnig8EgLBYLZsy5HPv6XgyAhBtL50fufSAUjYV2pzkUcjhRdmNAIl8YkpBScgQjLEnYFmTJ81YqBPfzHcdwudwu9UnCqDJ5lrKyhhh1bbZMWpFnV6t/IEQDSRpBIxyJMgkhpOvT8yRkScKonLjEbjHJ9SpNcImHYkNbKO4z4bLFsolLJKGgXMdEmYyxW00IRcS4/SRZIPjr1/sVP0y7NeYzWecNwhuMSHYC8vHIefHhXBlum5JNOtVhQbM/jDpvEEt2VyLbY8domRgEgFE9JRuDUpmQ8jNkPPH9FNHqDytKmMlX/gqLvX4c++hJZH74uKrd/uxnP8PvH3sS/ogUxvvEor1oC0YQjYr44+dsRIPbzioJBbCkto1qUpKSUEBAfg4IH7CrohlPLZFCSTNcVqQ6Y2GiVrOAi55bjbZgGN5gBIXpTsYftUeaAxeM7gGbxYSzhuUBkNp9MBJVPfepTivSXVaU1Ho1kx7trGiOe49zU+1Mhux4iZMA6V5IiyRR7KxoUjJ398p0YVtZE/68aB/e3xQjxwhJuLuiGb/+YDvTbr/bJynn8tMcGFGYhnUlsYUL2k8uHBWZ9w4gPbN02CjpX0i7T3VYEI5Ki13kWQsqSkJBeXbptkUrgkkf1j/HoyQeIshPdaiebYAl2coafBjeQztTsRZ4sra2NYBBebHIKkI8Ed/BI3VtOFrXhvsX7mAiEQBgdK90xguSTwpW3exHfVvsnRdfSahPEtLqvF0Vzfj5m5sA6GejXr6fJdveWV+Kxy4epdqOPt86b5BZOKMTNQUjIg5Rycd8oQiuf209DlEEc2swjFSHlVlc4H0oadDjkG/l9rnnWDOmDchWbUu8QwHgCEWe8/6/tI9fe0L/taBY0dgtSHfa0OwPK4vQicZJAJhFZC3fWy0wlghMIh72eE8//TR2lNZj2WdPAdEoznrBBlEUEQqFcNBkwpxLrsaTTz6Z1DHjgRxWURIST8IEl0/XT3vHTwZJaMCAAQMGDJxAKOHG1MQ+HBUZNYDDalYmBPRE224xMQP+ZAZMQCzcxaQvzGkXtMKNtQg5MsngPQkL0hzK4NtuMSHAqQAJaHUQHcZIZ3VUlISRKGxMdmPtZC8EUTEWpkgTatL1xcq8clAvdMVjtyiDS55qsVvM6JHuxGFOSbj+cANyUuwYVpCK9SX1iIf9VdJEYXiPVGwra9IkCclAPd1pVSaIAFCU5UZta1BFYqVS0iEtkrCxLYRAKAKTIF0DuWdWs6Ba0SfnE42K6PfAF7h4bCH+ctkpyvf0/eVDoeh2HAhHFDVMR8ONLxpTiA+3lKNUR3npj5qQdc7tyJh5I16fk4WqKsknqyrkwJnTJ2N9mR+PyF5f/lBM2UjufSAcVbKO0p6EPE+uSRJySkKi7vtuX7USfkhIQj8XbkxPZr2BsFKnel6YN7y2nrlP9IQPALLl8FfymGj1D6Sf0lIl7KxoRiQqok+WS1HJMgQ7FW5soklCQeoLGtpCyHDZYKN+Q0JytQgKGk6bGXaFBIkgHBUxumcaXrpuvEJG6JG3NHqkxVTEz393UPlddop0HrUtAfiCEbhsZqWeSXtt4jzTBuV6lHDDQXkp2HikAesO1eFQjRfXTO7NKCv7ZruRYrdoKglbAiGc9uelKMpyoyUQUiwOemSmIOuc2zF4zi3480yP0m7z8/Mxbtw4pKamMudjMQnwhSI4VOtVZQUnSkKrfF9EcJ6EtJJQvo1yAmj4wsD8NzZiBZVBNdUZ82Ns8YexbH8NQwqe0itdCr0ORTC5XybevXkKeKTJJ1Baz/aTDqsZabJfoZYKsKyhTVH5ZrptqPcG4bSalTrlrRS09sGjX7YHNa0BbD7SoLQfuo+kSRoSbjz/jY3MNdNw2y3okcaeB5t0IsoQ7OP/+BVO6ZWOSFREusuKxraQ8vwTspr03/uqWnDP/7bhr5efojw/VnNM+UqTNvT5kWcsnyPvAKB/rlvzGaTDvQ9Ut2JyP30Shh+f8CQhr6Aj/X2D/Hl1SwBljVJb4McXpw3IxrbSRozqmYbtZU2qBaKJf/oGAHDfuUMAxEKZtXwOW3T6h2hURGWTHzkpdtS0BLCBekc3+6Xn8tWVJSipbcUjF4xAaUMbo0KNB9pztd4bYNpkMdUu6loDqG0N4uIxhThSL+2fJ+Ga2qRzIe/nvFS7Yl+waGclluyuxJ/njcJ/1h3FjEE5iv8mDZ5kjR0/do8a20LIS7WjqjmgejfTfaEvFEFxdSs+3FKGu84azPT9ycBHjctIMiOxHZ6ETLRDskpCHWKTb8M2mw2zfvYbHOo7F4HKA5g31IPtpU0obrXAlj8A8y6doCzedAbkdBQloVyFiYb89H255tV1+OSOaShKTW7gb5CEJzEWLlwIq1Xq8K+99lrmO94zjPdw4z3I+HJhYSFTnjNnDlN2udjJwZo1a5gy73nHexfwnnD8A8KXE3n29ezZkynz179rF5thi/eEa25mO0DeY/Gss85iyitXrmTKvIfhd999x5S3bt3KlPn6Wb2azVL50EMPMWXeo3H58uVM+dixY0x59OjRTJn3BMzPz2fKvOchf794D76yMjZcwOFgX+R5eXlMma/P3Nxcpsx7KvLt68iRI0yZ97AbM2ZM3PLzzz/PlBN5KvKeknx75e8nf/389X3++edMma9PfvsDBw4wZd5zk/dc5M+Xfx54D8C9e/cy5ZoaNhEC7+GYlsau/PKeg3z7HDlyJFPmw2KKi4uZMu8xSiYyBOR5JR6sPzYQRQ2t/glHWJLNbjGBLPjTHjSSuit59RaPzioJCXgl4QX/WIWbp/dTbUeHG5tNUrjxfzeWMgN6m8WMem8QN2uEEdF9F11f9ECfCTdmlITaxCWNmOqCvR4ycbaZTarvbBaTQmzazCZlH267JS4pWZTlxuajDYpqrNkfwt7KZpw7Ih+hiKh5L19efggjCtMk3y6ZGB3WI02XJCT16rZbGOKzT5YbG480qBQTNFFNQqIJyCQ7GJE82jwOi6KYyfbYGYUFEBtMExXIws3lLEkY1icJaZWfPxSN66cEaJOUQCykrGeGRPzQZAM9sSKTCJPdpXjC+kMRDHlwEf62ezPuPCvmu7zxSINCphHC+J/LJDLJbBJw6sAcFalB4NYhCYNR9jksqfXilrdiCQNoJSF9n+nJDx0KbrdqTwL4OuLN7IlaLp6SkBBxPCEGAF/LGUMvHN0DzyyV3gPJJC6xmAU0toWwta0RQ/JTGFKe+CRWaWTJpeGyxcL7iR9Zr0wXQ0SQcGS9pAZAjJiiYbeYlLqpbQ3AGwzDbbPAZmHVWnydDC1IxYAcD2paApjULxMbjzRguUyknTogm1nwcVrN6JXp0iQJm31hlNb7UFrvQ5rTqhCZJCw7YLKrvIy14LSa8dXuKiWzKw2iJKQVnnRVMJ6E8t9EgBeICKp9pjgsMS85X0hJkEJQkOZAhssKX1NEyR7Ng7T73cekvu5/t0xBnkzwpTltCEVEHNbwEyyr96FfjrTPbI9EEuanORTvQV6hR8K/J/XNxLqSeoVoouFxWDAoz4OPtlYo++GTOxFUNPkgiqIuQQhIanHa1gJgicZAKKIsQpAs9V/vkUIHe2ZIoe/k+SfPGOmPnl6yDweqW/HQxzvxt8vHyNds0vTspEOjiaKSJ++A2L3gQavVmnwhJQPyyMI0JlsyoFbt8ZYWvNKJqJ5p8pBXOBLcOK0ITpsZ88b2xOTHvtFdUCJjEPLu01IS0qG/Lf6Qohiv8wYRjEQxY1AOPtxSjpVUSO7Gw/WYNSRPSRwzMDdF6Y/0VJh6x6xsDjD1erA61i6IV+aAPA9qvUF4A5JqkH6XN/lC6IWYSrRXhkshoG95S1I+pjqseH31YQwrSMWRuja4bGamzvR8M/mFpfxUB6qaAyoPSD7c+Gevr0KzP4xJfbMYn9toVEQoGmUS9/EgY1yn1YwUhwWlDT5dJaE3EEZVs1/xwJTOhcpErpEcS/uY0vXQ/riAnq2LDya7C84+ozFk2iB8vbQYPftYUNsa1CShOwJyWPJqJP9P5ArA3681B+tQNCZHZ2sWhiehAQMGDBgwcAJBJss018p7+tETN3rS7eAGVskqCQk6m92YgPckBICXlrMJfvhrsJgFiCJw7/vb0ewPI8NlxSvXjVcG1rQ/kxZotRQ9OQ/rZDcOR+KHGwMxgtFiEvDZglOx8DbJd5AoJfX9By3MdoBEzJGSlgl47ywX2oIRhajZcrQRoghMKMqEzWJSeSgGwhE8+sUeXPnyWgCST5FJAAbmeuTr1SDJ/DGSkB6EEwUMP5GiJ890kg+A9SS0WUzom+1WPKToBAwEpC3qqXQYJR8XphnglIR6JCFpK2lO7ZV6QgaRRDQ0qUYfwxsIIxr0o2XrItx4440499xzcd5556H287+hZdtitLTGFi6X76/Bwi1Schk+1PzKib3QN9utyipMoDXPpjdNsUn3kFfUELLFF2I9CemJpUTgSvVkp56Nf90wHiML2YUg+lpokLBc4mml1W6JSrKJUxKKoojFuyqR5bbhNGoSaEsi3Jgm7XyhCNMOM+VwYzLJpolGGk6aJNTJuq4oCTlynCbQtRIB2C1m5FAkYVsgAqfNrJynnpJwSEEK/nHVGPzt8lMwb6y0uEdUOwVpTuZYgiCgd6YLFY0+BMIRJnEJTTA0+WKkRV6qA9GgH8fWfca02xtvvBGvvPKKaoHbydUdSbwiCLF3CSFo4ykJFZIwznw71WFVRdDw+QAAinRJREFU+suWQEiV0CY/zaEci4SU8yDEFPF8G94jVVm8IOe+v7pV9bvShpi6itQVrZIm7ZsQv6SPunVmf+x5ZDZOH8wu7AJSH3/aQKldf7lTWph32y04c2guLhjdg3mXljf6sIVL+sHDZbOoSEK9xE+88rVnulQHJHTWzpGE5HqcNjOlLhY0PQl5X1wAyEtTk4QTiqS+4VdnDmQ+J8ci75SVByTi7D/zJzHb+UMRFWGSyyk667xBJhN2WzCCT7ZVoNkfViw79LzyMt023H76AOSnOeC0mhWSi1/EJsSZEm6s4Un4xKK9+MNnu7FkVyVGPrwES+UMzMTjr2+2GwNyPEwW5CW7qpiFp6eW7FO+H1LACjWK7vscuzn1Hn2Pt5U24olFscX+SiqhDLmcATkepMjRCvxzTYjQtmAENrOkvuPfoa+vPgwgRjqS+0ufz9vrjioLYAQ8kZsrE8o+jlSkyVdfKKIol3nV44J3t2DwbxfFHZvFlIRmpDiscZWEf/lqP2Y9vYx5t9Hn8ugXe7C9rFH3WARKBnou25jWGPtodQNati5C7ed/w9N33YDSdx9E8+Jn0LJtMWoaksuCnQhkeGc1SX+QV2SiIb+WVUOyMEhCAwYMGDBg4ASCTJbpMVKI8/SjFWm0AocPiw3E8Z3RRvcoCbVAhzART0Ias0fk48xheSqCxazDZNJkKT25ClJKwhA1gkpGZUkGgGaTgBGFaRjbO0Mus5MwHmSQTp9rSoIMelkysdYke7uRDINF2W6F5KEHpLzqr8EbQrrLphxbS0nYKg/cPZySsDBDO8MdPZ/iw6gdVjMC4Sj84QjsFhPG9YkpmEdR3moEpL6rdfy+4iUu4Vfuec/CIfkp+Om0vsrE1GnTbn/k+l12i1Lf9H4JKg8fQMXLN6Pxu9fQ0NCA3r17Iy07H9FAKxq//Rf+/LPzEKxlFfEA2x5mDMrB7+ZIKnK7BtEEaCsJ6fkdEdbw10snLqHbsZdREkaVa6KfjVlD8vDAeaxanoCE0946sz8W/2o6JvWTvNaUcGONR08JN6Y8CUORKFYV1+FAdSvmjO7BqI6SSVxCZ2R1Ws3Mb4iSkChrhhWwIbSxfVsgCAJsFpMy4eYXL4jCkidd6PPVJAmtMSVhTUsAbcEw3HYz40kYjYoqkrAw3Yksjx1zxxQqRBh5xvLTHIwFACBlOI6KUhZZ2kOMTwaTSrJq1xxBxcs3o+HbWLvt2bMnGhoacM8992Dw4MHYvTvmPUiTCZP7ZSr+by6rWQkBtOgoCelXDWn28az8UhwWJdy42RdWqery0xzoIxN+xLuQByECyxt9yHBZmezY6fI9K+EyAuek2FHW4FOeBdLvpVLP6kyZBLx+ihTlQAgBj90Cp82s2T967BZMlb0ICQGR4rDglesn4Jkrx6BAVnemOCwQReDVlSXM7/m26LGbVYk7aDAkIdf356YSxa9UjikJpTohykin1cxmN9bwJDxAWXUQ8Ao/ALhmch98tuBU3DZzgPJZptumeLxN7S/VTTgqSmGh3Pvjkc92q9oAr8Ssaw0w/dv2skb84p0tAICJMom16Qgb6dI/x42LxxYyCxpuuwXeQBh/+3o/hjy4CJ9sq1C+o0nCUCSqu4j16soSPCMnAyEqWRJGXpDmwFCO+Ht/U5niN1mU5UKLP6wQcTwZDADvbpDeJ6Io4rt91QqZc9vM/gCkPpF+ZwkCUEC1l77ZbkX9y4P0zW3BMFx2M5w2KeJEFEXVe5BgIpdE59NtFXjgwx14/Es2MolPLpPtscFsElRKQrqPpd9nPBX4+XYpUk5PfQ9AWTBxWM1IdVrhD0VjSkJOHU+SBD38SSzCkB47hSIirv/Xet1j0edsNgmqMR8/xt69eze+evgKNC9/HdFAKyLOLFhSsmGL+ND47b/w15+fj927dyMSFXH/wu34+Zv6FgTxQA5LXu2KJ2ECJSFp7+R5bI9li0ESGjBgwIABAycQhFiiV7wj0ShDEtIEEO3nwodonCglYVIkYRpLEvKTJjIJ56/JoaPKotVGTRrhxoEIqyQMhJIgCeURF++xaFWUhNqrsIRYoOvBbbcoA2KtqG4y4SUhsWQg7bKaVQkRAPVEsb4tiEy3TTmm1r33BsJwWs0wmwSGkOAnp+T64oVHk2tskbPMjqdIwrOGqZU3iZSEjCchN3Blw40jKhLx7fmT8dCcYYoSyW4x45JxrA0DECPR7BaTKls0vc8t7/0F9l4j0HPBW/jwww/x4osvYv4DjyP34t+i54K30Gf4ONR/9YJq/zSROrV/lnIvaEKWqAMBQIsLoZu3R25etD8VQJGEoQhDfLdw4cZ62Y35xQSeAP7ptL4YnB+b9JLMkeZ4iUsoJWFbMIK31x+BSQB+dmpfZv9WWvlMtUGaUL9igpRw5fGLR+KZK8cwzxHpN0rlcNXhPfRIQmnfDotJue8WlZJQDjfm2ls6pUR12sxM2wYkgod4Ej61ZD+a/WEmUcrBmlb0e+ALPLlYmlAPK0jFL2YNYIiLVGcs0YnZJCDbY1ctiEyWSdo1B+vgC8YUlXyorkeeuP7ryQeVdvvRRx/hxRdfxEsvvYSPPvoIVVVVmD59Om6//fbYtcn1bzOb8M78yQpx5qLuF+n7RJFNXEJ312TzYET/BWKRFUyAFHpYLmf0JchPdeCpS0fjxmlFuHZykeY+aPKWJ+5IWDjvrTgkPwX13qBCZpB7Ttf1haf0wLd3z8Ttpw9g+mbSJ/ekjkXaqdtuQV6KAxaToJAObqrenrx0FNJdVvxx7ggAMfKDYGAeSyrZrWa4bBa8dsME/OMq1kIHkJJJPPDhDtS2BlT9AZ9Yi6h1CSlLnk0HTRJaYuHGdN+3v6pV5UGo5UloNZswojCN6VtyuezcMWW3VaVCfnvdUYXwI+AVcHWtQeY9TSeU6Z/r0VwwfGLeKMbGApBC50tq2/C3rw8gEI7inXWxBR6SIbk1EMaTi/cxCWx47CyXVHbEw5IoCQvSnEw465UTeyMcFfGvVRIxTJKoAdJzo1WfZMyy4XADbnhtA+79YDsAYGr/bDx/9Vg8e+UYfLLgVGX7HI+d8XRNcViV9serJf/29QHsLG+SvFOtZqXf9QYjSnbfC0b3UJIlAZJHKA1+UbKq2Q9RFFHPKdNSHFa4bGbVO5xXudP71co8fbBGrQgmWFFcC7NJQK8Mp4q04xdHycJCaUObUi98gjZ+gVoLvlAETqruCBrbQnh6yT7lGm677XbYeg7Hjc9/hYJLHoRlxs+RNXsBHn3+3+j9i7eQN2gMbr/9dhytb8M760uxeFeVSsGfDMhjQV7lSnbjBMNaEnnw5k2SsldrPKUHw5NQA4899hgWLlyIvXv3wul0YurUqXjiiScwePBgZZsbbrgB//73v5nfTZo0CWvXrlXKRUVFeP3115Xted+9RMjLy4PdLnXAvEfa5s2bmXJWVhZTnjdvHlNua2MHGLyn3vjx45kyf64HD7Jy4169ejFl3iNtyZIlTPmKK65gyrznIO/5xnsI8p57vKcZv7+BA1k5PO9xV1FRwZT5kIzy8nKmfMoppyAeeM+2ffv2MWXeU/KLL75gyvz1l5SwK5AzZ85kyrxnHX/8ZcuWMeWpU6cyZb7+Pv30U6bM1z/vIfnTn/6UKfMeiO+88w5T5ttHIo8+3nORx86dO5nyww8/zJSDQfYlxtf3l19+yZT79u3LlPfv38+UiTcoQV1dHVPmX9C8R2B1dTVTJs81Ae/xyLcHvv02NjYy5SlTWMNvvj34/ewkfdy4cUyZ96Dkz4/3TNy4kfWK4/ubRNt//PHHTJl4gvLn+WNBjCSMfRaKiKBvIx2KQY+T1UrCE+NJyJNqWqAHynazmiQkK9y8n5rTZlZN6gF9T0I63DgQR61GwyRIqoyYkpCrV3mEpqd4IZMd+prcdrMqcQUNj6wCIFkB/YryJUYSSmRZzPyfRoM3iP45HoVI0FQS+sPKRIImX0m4GsHv5gzHbz/aiXNH5GNyvyxGdUNAe9GlOiyKknBArocJ9yXeRqQuiaoFkOpXiwDlQ6FopUsgrPYkJAoKcu12iwlPXToaTqsZb66Nedx6Kc+uvFQHEx5Gt43mo3uQd91fIZitCEVE2CwCqmVyUzBbMeXim7Dz7itVdUJPIHIp9Q1d124rMDpPxMpSARpRfEwYJ5lz8yFwhCzZVtrIZCOlJ2K0kpAn2vnJeG6qHa010m9vmdFfRaDGyE6t0FvpO5qY9wbCqG4OINNtR69MFzMpo5OQsCRhbJ9/umgkfjdnuHKe9AJAbooDghBTmgzVURISAsxuNVPhxpySUD53PrSNJqMcFjPenj8Z4WgUC97egm/2VuNAVasqJNZliz2nq2X1Ckkm9PAFw1XKHEEQMDgvBTvKm5CbYlf6/dMH5yiK5VE90+GwmiSSMBRFbooD5Y0+lZKQkLB7tm1GxtVPQzCrFy9sNhseeOABTJw4MVZHcv2mOiXVJVn0oPst+m+9yDS7WUQiFXowHFXqtazBB28wghGFqUp4Y16qA3mpDkV9qwW6Xynk1FjpLm1F1JD8FKw4UIsS2a6CvCPpvlgQBMUH0WOzKGQ76Vfo/jHDZUNtawApDgtMMrlLwj/p52Zq/2xsfehsBMIRxceMZLQGgH45biVsGogtjJw+JFdTRXXDa5K39uC8FAzJZwlG+rg2i0kh5HgCxSL7/gKskpD0p5GoiIM1rZjcLwutgTBaA2FYzYKu/yAPmiRNc1rRJ8uF/VWtDOlOg88sy/dTNa0BBCLa7+kUhwVFWS6VDYmWSs9lszBh1GsOxcbsipIwGMHGw/XIdNtwzzmDcf/CHZrHBYAmmVgjvrs90h0oonw0ycLFVlkRPaxHKrI9dtS2BpDptmlaJJD+c1cFO7532804daA0x6OJt4I0BxNt4rSZlX6A95otrm7FT56VvPX757iV+15a34aoCNwwtQgPXzAcd7y9GdvLmuCwmhRVL6D2+F17qA5XvLQWD5w3BHXeAAQh9jxFo6L8zpfaeVlDG/7+9QFUUJ6K9HXc/b9teGDhDux/9FzVOZ8xNDYXikZFXP/aeqQ6rVi+vwbnjcxHbqojIUlICPJQRESLhl8jIN0fPTz+5V7sPtYMfygCh9WsUpYTdWhbMIIHfzIM69avQ8ZVT6NXdirSSlsUq5Ae6U6kul3ocfa1WPbkfJY0TULNt/pgLea/LmDRlSJ6pQKEmyXqbvJq0wqQ4eekNktswaYtGEZ1S3JzLUNJqIFly5bh9ttvx9q1a/HVV18hHA7j7LPPVhFJs2fPxrFjx5R/PBFhwIABAwYMJAIZ4LPhxaySkBBfGS4rQ+x1XknYNSShXkgwjTwu3JgnFm0aig9Am6igtwckgo9M/GmFGh1aEY9AJZN92pOQBlFypLZDSWi3mBVFllY9kwkWCcshA0cnlTWVPmeaeIlGRTS0BZHhtsYyrGqRhIGwQkbS5CtPCl1wSg8cfvx89MvxYFyfDJXqBYhNtpt8IdgsZqS7bPjiF6fh/VumMGQ1mWCS86GVhHSIarxwY57cpUlCi0lQrtmqKAljCi32+mMefXxoG23eb3J4EG6QFg9JmGeVTG7aLCbUVhyByaFOrsCTWQR0G7aYgNd+ImLbTVFoRYexnoTS//mwVeIj9O6GUny7L6ZC4BOX6CkJ+YkO7bOUqREDfcesAbhgdA88dal6wU5bSRiWE9pIx6UVL+wzEfubfiZMJoEhMunfOG1SJlsyQc722PGHC4fj1evH48qJvZjtyDHIfefbA318EsYMsD5NDpsJNosJLpsFf7xoBEb3SsdNp/XVrFObWTpmOKJPOtIgIYr09b1240QskJVHNosJwwpScaC6Bf5QBCkOSa1Y08LG9RKyIiMzA462avz2fO1w8uLiYmbRkpAVpB8jJAP9rlE8CUVotlcgpiSMh0A4qkxM91ZK5FghRb5pJcfgQddjzwx2YSPHow6Jpfdb3SKRGYlU7h6KdCBKQlr1ThavSJum+86CNDVBZbeYceO0IgDAaQNzcJpM+Azm+lQ6MUQ8n7BAOKIiOWglId2meQLFG4woXrVWswCrvDhHFmFKalsRCEcxMNej/JaE7ScDmiT0OCyKj61eGCwPdQIZv0rxP6lvJh6/eCRuP30Ak/CCQCt5jIc6/kVj2ESdxANYIki96JXp0rURISDkJknykp/mQF/Ks7dI/pu883pluFAgt6Est13TfqLJF8JHW8pVYen0uTisJkXpWpDmVCWBIvXPe9jScNstSv9PkvyQZ4Sco8duZdTfvFckCbd+Z30pGttCyHLb8dbPJsFtM2NK/yy4bBZlrDX3udX436Yy1LQElPc0v8inNVbhlYRbShux4kCtosj92amS+IAfg9EkoT8UYd6dJEkJGTsRsj0UZyz4z2UHsXx/DZp8ISkZlk4SMPL+S0lNR7ihArkpdqa/KkhzINVpQXXZEWRkZDDv6rIGH7YcbVDtk8Yjn+6GNyTgvd1SA6iWOe9cudkpSkKNhWjVoqrNrPT9vmBU1wKGh6Ek1MCiRYuY8muvvYbc3Fxs2rQJ06dPVz632+0qBZUBAwYMGDDQHhBCil4lDnOehKFoFD0znFj561mM1wo/gNEjCRfMGoBemS7c+/525nN6LmA2CQkTe2jBbBKSIhtJuB4gZR3lJ/BEpacKN9YjCbkJRr03iJwUOzNo5BN/kPPlr9NmNsEfijKehDSIsisZT8Ih+SnYW9mCVKdFWW3Xqh4ywCeTRUJOOSyxgSk9mKZDS5v9IURFMOHGWtl9vcGwMnClk9zwClRbEuHiZKJBqwHJijydJTfNacWxJr9yH+iQsca2kDIBIXWdYrfE9SRs8YcZFZDTZlYmseTZIW2Ev2+0krBXJksy0Kv57lFno/bzvyJtyuXYtCkHa6sieP7bg4h4GxA5thNfrHgXnjFzmN8LAns8erJKt1mrSVILpunMm2k7RY8OSZimo2DVJQnN8UlC2rIgQ0ORleqw4pkr1SGQgJ6SUDo2mfTT+2cSLemEG/PgicVMt02ZlLntFlw7pQgAcMbQPLyzvpTZt8NqVvy9VIlLqOMXZriUdksrZ+m6Kkhz4uPbpynl+af1xcsrpEl9nTcYW1zg1Pt6JCHxAIyXYTPLY8e2siaYTQLSnE6kOKwIyOqnuaf0wEdbKxTl0s3z5+Nvf/srGse6sS31LOTl5UEQBFRWVuKrr77Cn/70J/zqV79SXVuKfH6kP6Pn7OSZEqHdbwExT0IAcFpE+MLqDensvHvk7MSFcrggsSxIBLoe6dBIgCfrHApxSn5T2xqA02rGaQNz8PHWCswckouhBamqvoYmRwi5ZbOYcN2UPhiY68EXOyqZ78hxXTazpuIaAO6bPQQTizIxtCAVqU4rDtW0qhIIFFBEZDz/2gYqizEBTXDTJCFPNrb6w4ySECDeshFEoiJ+9d5WAMDUAVlYfqAGx5okQiERNj94FkwC8MCHMfWdx25BH52EWHqgych+OW6UN/hUBNKjF43AgFzpufnVGYPw2qrDzPe8pQDAtpuLxxbiwy2x6DD63d/kC6FnulOVAI5gzuge+Hp3FRbvqsRz3xbjWJMf2R4b7BYzirJj7xNeheeymVGQ5sCO8iaku6yaiay2HG3ElqNbAUh1fv6oAny+/RhDnguCAJdViqTIT3MofS4hfMkYQi+xFyA98+S5L6mTSML8NLvyHSC1bdrvkyd5yXtUgPQ+TnVYcOrAbOx4+ByYTAL+8tV+VDUHcKTOyyjdsz02VDT5daM46Pd8MZeA6IsdsXD9YQWpSuQCPwYj+1hfUo+rX1nLjIPqvEFEoiIe/lTyZX36stG46d8bdeuL9gosb/ChZ4ZL06MWiBHcs+ddhbde/StW9hQB1wBEWi0QTEBlyT7Urn4fxUvewoP33c34B/9rVQn+taoEG35zpmrBlsCiRIhIZZLgOkduaoonocaQn19UcNliRLEvFGGiO+LBIAmTAAn1y8xkQwe+++475ObmIj09HTNmzMCjjz6qCqM0YMCAAQMG4kHLk5DPbiyKMeUNPXHjCTQywO6Z4WRC1Ppmu1WTLICdzJsFARGITChJsuefjLchvQKcl+qAhQrpvXhMIc4fWQBAS0moPZnkJ5mtgTByUuwqVQ8BUad57BYVCSOpEsPKgFOlJJRXohN5ElpMAt77+RSU1rchN8WhqF36ZqtVaB5FSSiNAhVzbptJUSjpJS4hA/EMl02lggSAD7eUYX9VK0rrfejRV1K70PUoCALsFpNSJ8l4StJtLd49Ip5AWp6E5Y0+vPDdQVQ2+ZXw3FSnVRm0R6MiTCaB8STkQ9S0VGp6SkKaJBzMhezRE+/0U6+GYLGjZeNHOOO01yCSUEpRhDUlExMvuAFlvc9mfm81m5hJrp6SMFHVJlISWkwCM4GjQbcJfziW1ETlSchN/Olq0iIJ40ErQ6o3ICkJtYgfum3RbSjewgKtMLKZTch02XAI0iyJ91P85q4Z2F/Zonxut5iUc1MlLqHOz2YWcMPUIvx7zWEmZFFvUQIAfnP+MJgEAS8uP4SjdW3K9bYFOI9Dl3Y/Qbzu+PtBI8ttQyQqorolgH7ZHqQ6LMrzft3UIsyf3k9RpT388MNwOp34y1/+gnvvvVdpj6IoIj8/H/fddx/uvfdeZd9OuR25CFko92f0u8eShF8XzSFM6wl8fVi9zeUTesFiNsFjtyjPWo90B1b+elbSivcstw2nDczGuD4ZuGB0D+Y7Ory/MN2pkIQ0UWa3mjBvbCFG9UzDwFyPpkIuQ1YK0hmeAeCRCyVvwbWH6gHEyAnSp8dT3AmCwIROjuqZjg2H65XyU5eOxtxTYtdDv4fpEGVAIpRbOJKQfmbpBQG1kjCMcJQnCU3wBSOoaPRhZ3kz5o3tiVlD8vDct5KtlDkJ6xCSzd7FeORZkC0THsT3jkb/HLcqVJhG3yw3DtV4FdXs/NP6Yv70fky/muayYtvvzsabaw7jqSX79XaFa6cU4es9ks0P77XHozDDqUqmAQAvXTsOZw3Lw6lPfIvyRh+eXLwPZpOg+GrSYwGa6CF+jFmeWKIivWz3BL5QBH++ZDT+OHekqg912S3wBiMoSHMo/olkvOFJQrHpspmVRUxeSUgI1p4ZrErRzfWxJHRYEKSxELle0m5rWgKobQ1gxpPfMb/LTrGjosmPtmBEsXQh+O/GUmZMepjLsv3t3moUpjtx37lDFK9WQIMklMd7f/t6v2qhtMEbxJJdMXutVIcVTg3/RIKN1DPqDUbgsKk9CQnIWOMnN/4Sn+6qw5fvvIK62moQG4aJ/xDhSM1C9rTL8NBDD+EjiqiOXbNXkyQMRaJKP0yEtTVt0n55JeHGYwKeXAN8dJmIpSWAu/wIJnFWF257rA34gmHUtCTX/xokYQKIoog777wTp556KkaMGKF8fu655+LSSy9Fnz59UFJSggcffBCzZs3Cpk2bFD8v2tevvX6EgKRU1NoXoPakS09PZ8rbtm1T7YsGfS2A2nPO4/Ew5UQeZrzHXXFxMVOeNWsWU164cGHc451//vlMOSWFHdx/9dVXTNntZidgvLcZ79HWp08fpsx7FNbUsKai/PXx4D3jCgoKmLLLxSoYQiF20nPkyBGmHOE8OTZt2sSUeY/JoqIipkw83gj49sPXN4+5c+cyZd4j75lnnmHKfH3z58d7EvL1eejQIabMk+05OWyIwYQJE5jy8uXLmTLvx1BYyIYb3HjjjUyZvz7eE3HAgAFMmX++6uvrmTKdTRAAhg0bxpTHjh3LlPn2w7d33lOSPz7fXs1m9qV27BhroM23L75/4D0XR40axZT5523p0qVMuUcPdjC/Zs0apnzqqacy5ZEjRwJQt5sfC8hAa0zvdCyUBxLhSFSldiODEnpyzQ9gSAjlwFwPQxJGRW2zZnoObTIBiEiTifaELZuF5JSEZDJzxhDp+aYn8FdP7qNMuHh1pN4qP09s+UMRRKOiKvkG8dchdaNJEsoTI0Ky8GQTIWN0lYTyfYiIItKcVqQVSoPfS8b1hC8UwdxTClW/IeEfiidhSO1JGNQJNy6tl+4tqySMyt+14f/ei/URhDzh2wohCc0mIalwcZoI5Cc9tPqTqDgC4SgO1rRiJ+W59Ow3B5RMtiT0J81pRUsghBteW48DVa1Ydd8sJty4kZtw0v5OFsWTUPqMb4etFEk4NJ/1IeIn3mmTL0Ha5EvwysW9cONzXyMcjcLkzkB+YW+M7p+FMi4RgZ1rf7RfJR9uHA9anoR0+7SaTZqeVvT1AcSTMKI6PqB+hui2kKGT7VIPWqS9V/agdGmQYyxJSNVLHDKC/MZlk7Lu0ueYl8a+r/rneNCfSiLA1L0qcQl9X0z43Zxh+N2cYUzIXyLC/JwR+Xhx+SH8ZFSB0qfRpIjNYtKdWM4akoerJ/XGFRN66+6fXKsoSqpZus9Jc1qZawWAX//61/j1r3+NkpISxb87Pz9f5bUMxPpgUvdEMRRhwo1jSkI90N2gywr0SxdxqDF2P7c+dJbiGdgzw6l4gfZMdyXtdwdI78Y3fzZJ8ztafdcj3QnIWW/pxSi77Nc3SMM+gaBXhgvrS+qlhTiNfpAQYoQ4IZN6noBOBHpxQyvJEkFOip0lCduCqsQLNKFDq2P5UMzWQJgJNwakvtIfjqmJBuVJ7WlkYRo2HWmAlRsnXDmxtypkl4Am7HtluJDhYhOnEHxw61QMLUjBsIcWq/bx359PwcriWoiiiG/2Viv+jNkeuyrsFZCeAfKM6Km8ZgzKwT3nDEa2x6a7sEfQM8OJSFQ93slLdUAQBGS4rYrCLBIV0ZtSpA/JT0FtawB2ORFbOCoqJDXpa4KRqG5/8NfLR+Pz7ZW4UCaMtRZZ3DYzagAUpDuV55eQs26NxaNFvzoN4YioeBK6bBbl+IRIJ/6qN04rQml9G+48exAAqe2N7pmuUv4dlFV+wUgULf4wk7QFACb1y8Kn29h5NBALi/eFIjAJAhMdc+/72xnVar1XaucpDiua2kI4VOvFhaf0wBxucSDFzoUbh6PYfLRB8YUFpEWD8kYf6rxBHK2XiNHhPVKRl+qA02pGM/c8EewoY+diUtIX7fcBGZvVe4NIm3wJPnrzr3jp8zX4cNUuzD+tH248awz+vKoei3ZVIhoVVWpgACip9WJCEUvoVTb5Mfmxb5Ty69ulMXZNGyBARLa8nkVen58ekP54eQvk0OSd+OBWds6Y7rLBZjbBJEj3oqpZ+/p5GCRhAtxxxx3Yvn07Vq5cyXx++eWXK3+PGDEC48ePR58+ffD555/j4osvbtcxWltbmUQEfBIOAwYMGPgxoby8nEmek56enpDY/j7DIhMb10zug9xUB37+5iaEoqKK7Cb8B03o8GRAQCaK+EyQwXBUc1IjUObz0splFFaTgKDymRA34y3ZJhkLo4vGFsIbDOOy8ZKPGK1YoK8jUdIFAj6k0heKqML+AGkiEYqElZATLaKPnEtMScjue1BeCg7VejEwV3uySc6RVzGaTAKun1qk+RsywSJqN6J+ctIkYURbSXhUnkhJSkL23N9Zf5Q9jhJSyJ6bw2pGsz+s8oXSgzOOkpAmdsmkOhCO4vVVhyGKwC9mDcAzS4uxtbRR2W5vZQssJgFuuxnVLQF8J3vtVTT6GJKQ92NzaagnyPFJkyBq2AAVftuTeya8GoN2AEjJLoS5YDCcZhOCESkZSCgcVSkhrFwd0Koiizk2adSZY8T2Q32fapMSQjRRk+x4pBMxQ7dbTCiublXIYX6yaTULyE91YEzvdPhCEfzhwhE47c/fAojdr2TBP5+A7EkYjmoSbPRzSv9WK3MyAWmrhNzJos5Rz4tO6xjxlIRWKuFDPPUgj7G9M7DugTOQ7bGjRFbm0KRIPBLMZjHh0YtGxt0/7RfpsJoYkiPevvv27atJDNIgZAi5J+RdQvcNfJ3dPk5UEYb0I2i3AJ9cJuKLutFKhlY6qUj/HI9CEuZrZe7pIOjnjVaC0mR9Mve1N2dDwIM8H6S/pq0l2gNeAauHnBQ7o7hr8IZUme3p54x9vtjnzxuIhRuT7Zw2M/yhKGrk5AVEkfnb84eif65H1U+eOyJflYSHgA5LddrMmDlYWgB8+AIpGc03d81ANCoqHrdnDMnFN3vZRH4T+2ZiYt9MJeFUqby4GS8cnSyoxfM+vP30Abrf0ShMdyrth4T8AjG1HX/fxvROV/7+/BenAYCcBMiChraQQtTSCn8tJeGfLxmFuacU4qIx+oQxECMEC9IcyruetEH63Ibkp+Cd+ZOR4bYxpLLLFgs3Ju9SMiZIcVjxJOU7u+E3ZwIArno5loQViIXhVjUFEIpGVWOoxy4eiZtP64d5L6zGmcNylRB9EhbvD0bkBTy2JyEJ6dKcVjT5QjhS14YRhWnYVtYIQFsFqpW45Plv2eSq/XLcKG/0ocEbxN7KFvTNdiv3ymUzo6o5gE1H6vHJ1go8+JNhymISnyDKaWMTlxDyEYgt5BE/yCy3DU//9Gzcf9kMxdokdVMLRFFakNQabxzSUNa+ufYwU46KAl7eCkwoEJHpjC0q8sM2et2bX1TI8dghCAKcVjP2VbZgZX18P0QCgySMgwULFuCTTz7B8uXLVUooHgUFBejTp48qS2syuOeee/DPf/6zo6dpwIABAz8o8MrLW265BS+88MIJOpvuRyyMWMDU/lJYRTgSBc/NaYcba3sSjuqZDuAo9XlEUyXBKAnlv60WEyAP3izmxCShySQkZXRuNZtw47TYJJaejOolNwDiJS5RKwm1Qo1dNjZ8K95kjZByvMrpz5eOwpzRPXDeSG0fYsWvT8sgRgduPtw4FIHZJHkNaSkJ6ZVooraglYTk2MsP1CDbY0MgLK36k+OQCfq8sdJ4hhBryfgRStvH7oMqnJUiZkgoXCAUQUmtFx67BWcOy8MzS4tVbZoQYHQSkWX7a5j2wLc/lzV2/wi5oZAecjs0CwLCFMlus5hU7Z+feIdqSxGo2IsVG+QJY+8oFr33Go7WNaPnOXNhsfXF2vvPwM1vbMTGIw0Kufr1ndM1nxGn1YyWQDihkjBRuLHVbNINVyNtIsNlUzKukuulIQgC1j5whuY+Mtsdbqw+l1aZjNBqS1YLrXyOfa/VHxGQyRMJqyXKoWyPLWFfE0+tSBOIVhN9XsmThECMQLBrkPntUcppgSZtHVY2Q7rWvvfs2YO1a9diypQpGDJkCPbu3Yu///3vCAQCuOaaa5hIHhKOR+qFvFPoY9CJSwDgninqtk3P021myUtzpIadBSBN2JVtk/Ah7AjoRTG6jhIlpACAXpnq5CM0hvdIhcUUy4Yc0nlHJEKyyTxyOPVcQ1tQpUJilYSsjcRVk3ojL8WBjUfqseVoo4YnoQmNbSHFKzYvJRZ6eu1kNsoKiB8qSwgsQuLnpTpw+PFYJBiven3x2nHYW9miqNxoEE/XMvndFq+t9Jfb1LkjCnS3oZGf6mD6Rykbr/TOKcp2o3+OB4t/NR19slw4VOPFnmPNyJIJLr7uiTcewBLFHpkkJO3vgtE98NLyQ7hlRn/Vwkqa06osliYCaTf5qY6YElg+rodTGWdwSXbItTpl41tiW5CIsOYzBhOQfo7/vcduwcieadjwmzNhMQsKSZjpjikJ42F0r3Qs31+Do/USSUgWE0drkoRsH+gPR7B8fw2mDcjCqmJJTdg/x4MVB2pxrMmPw7VenDUsFvrvtFngC4Yx7wUpwun8UT0UEpz2JASkdzj9bhicn6IiCetagwjVluLz99/GzOmnMn3w+oNV8GWNR7PvdE2SkE/WIooiPtFQZALAsdaYHyGgtjFpotZS+UgZQtY6bRYcrmtDNBD/fhB0T2/9PYcoirjjjjuwcOFCLF26NOHKHCCF55WWlqrCTJPBk08+idLSUuUfH6powIABAz8m7N69m+kTn3zyyRN9St0KWrRGFGzhqKgONxbU4cZ62Y2zPTbs/+O5ijl6KCJCa0rDq58AlrDjQ4+0YEngSXj2sDx8csc01ed0+DOtZuM5AL0JPK9aCoSimoNbPlTTE2fiqOdJmOqw4vxRBboEBVnZ1xtca8GtoSQkZCMJZdULN1aUhHS4sRxW5g1EkO2xK4orEtKT7bFj+8Nn44l5kpKJEHvJTtxZT0K2Tun7R0gOkmkwzWlFPmXGnp/qUCZShCT0hSLKfV99sI7xJORBKwnJM2LhEmbwBBQ534W3TcXfrzgFAJiQI9+hTah4fQEavv0X7r/uPPgObcKr912P1poyhJqqseQvv0DwyDZkum0okFUn5DkckJuCIVwoMxDzRkvEP9Hfk3wE9LnZLSbddkcmsLwHXiIPLBrJECnsvtUXFJCT/mi1JYsOGRdPSVgsT54GySHp5D5nJ1AR8ufH91+MkpDOoNxOkpBA63q7kiR0Ws0KWQGo+7xFixbhlFNOwd13340xY8Zg0aJFmD59OoqLi3H06FGcc845jB0ITxiRexBPSagFRkko/61HPPBEUXeggOpfaE9CrezDPBIpCc8aloftD5+tZO4lxNSdZw1q1zmS/p6E9+qBVs1mum1yuDFLMLDemmyb+NNFI/HLMwfCbZO8IBXfWfk3DosZ/lAE1ZySUA/xlgiJFUQymaoBaYyhp1wm+yhtkN5tWv0MwczBufjg1il4aM4w3W1ofHj7VJw7IrbAd+bQPIztnY4/zB2htM/B+SlwWM14/5YpWHv/Gcoz0uBlCZfhPbTJcPI+Jc//iMI0lDx2HuaM7qFaWGlPqLrbboEgSPVD+hsyVqMJM8bvldq/02ZRzo0kakpEEhKfP73EPHoh3GkuK+NnmOKQEmZ4g5G4C6ij5QWGI7Iv4c7yJsb/kUaGmz02SXYzMDdFqR8y7t1wuB5RERhMvZ+dVhPaKNJyZ3ksxLi80cd4BGZ7bEpyNgAYSD27hIjbvvY7HHt9AX5z/69VfbC3rgrV/30I5933ArNQTXCIIwkP1XoVKxkeZS2C4kcIqG1MSPZjAFh5oJb5jrw3nbb20X6GklADt99+O95++218/PHHSElJUTw+0tLS4HQ60draiocffhjz5s1DQUEBDh8+jAceeADZ2dm46KKL2n08j8fDhNKRMDuPx6N4pQWD+pnQAKB///5MmfdY4z3TeE8z3vON9yibNIn1BOGzOq9YsYIp06GCALB161am3NrKPhi9e7P+LIEAG1508CArJeY9/c4+mzUU58PDv/zyS6Z85plnMuULL7yQKV9zzTVM+dNPP2XKO3fuZMp5eXlM+ZRTTmHKvCch7/Fo4gaypM3p7Y8/Hu85yGfo5j3w+PszZcoUprxx40amzCu7+OPv2rWLKfOel3zYpNPJDtx69WJX1Pj2OnToUKb80ksvMWXeM4/31OM9+AYNYgd3vCcnXz/8+fOelvPmzWPKfP3x7Yf3DOQ9/PjrDYe1w+IIeI/OjIwMpjx+/HimvG7dOqbM31++3NDAStP59srXD3/9vMco7xFKPE59PunlWFhYiNRU9eDghwp6NZqQHXx2Y4AKN2Y8CTmiTMnOK6nR6LBVrczFrJJQKtAKG6vFBCRIhGZKkN14aEGqrGxkoackDHF+iA4dwoMnQvwh7YEoTzLyptw0QjqehIlAjqGXNEULhLwj2Y0DoahyP8l9o8Nu6UHmnkqpjypIcyhEUVDu53zBCNJdVoUcpffB+HVZ1aRwPNBECj8xpUksoiT0ySRhqtOKnBS74oGYl2qHySRgy9FG2MwmOK1mhKMiTII0IW32hRCQw8mcMoEIxDwUadKXtGnS/q6fUoSVB2px68z++Nm/Y/0Qqc+xvTMwtncG7n1/uxImBABNq95B6sR5yJh+LXo1bMHqN57Aldf/DHmzbsQHm8tg2/Iejq3+H4D7lPbIP5880pySl1VCT0JaSajpSZi4LapJwuRJr3iKPi1oKQmDkSiCOmF1tJk8rTiN94w9fdloPP7FXlwse6ERsrxnRnxCB2CVVSoloc53er5TiaClnOwsSUj7L3ocFlwzqQ9WF9dpkiuPPPII7rnnHvzxj3/Eu+++i6uuugq33norHn30UQDAb37zGzz++OOKmpAPPSVKneumxMY0yXgS0l0oie7l/fAI6FDg7oLZJOCf14zDgFw3PJSKqiCJ8GY+6zkPQWATBw3OT2HUcsnCYTVjxb2nJ/QApdto70wXdpQ3qcIHGeW9Ttsl7zklI64pFqrqD0VRLSsJeeUiwaXjeuJ/m8qYzL08yLuFVosmgp6/KiFnypIINwaAcX20Q6C1UJDmxPVTi/DlTmluNaxHqm72drfdwowReme6UN7ow8S+mTh9cK7ueZH3AR3urvgsc/1xe/rcn0/vj7OG5cFmMSn3nYyd0ukkPTrn5bKZmURJLps54fgmLPcTqU6rMu7IS7Ur6tNkF5Y8dgtcNnPcbO4AMFoeH5LFz/1VLeiX7dZcIM5P5ZW2UvvumeFEit2CunAQJkGA1SxgV4U0ThpMeZK6bBZGOU1Ui75gBPXeIM4cmqskvZnQNxNnDInNd2mrC/JcbfroFfQ47TKUffsfVR9c2xrAyPNvRPFX/8GRKVK4M/HIBiRSUhRFpZ2s2M/6y/OIpySspGiVT7dXMPeLJBQiURhFWS6Uxj2SBENJqIEXXngBTU1NmDlzJgoKCpR/7733HgBpgr9jxw5ceOGFGDRoEK6//noMGjQIa9asUSUcMGDAgAEDBuKBIQnlv8PRqCrDcCxxSewzPSUh2Q9RSXjsFmX1mB700+QeGXTQXmvJrHibBUFTpcifNw+LjichT/TpeRKqEpeEY+HGtCE2H+aVokESkivQ8yRMBFcHlIQWOYyUVhKSQXGMJIwtcNDhsaX1PqTYLchNsSuhRV45hIQoEgmpwGcHJiC/S5YkZBKXxCFVYkrCKJp8IaTL2R7JZDwnxaGElllMgkI+Eg47FIkqA/AiKis0US/QRBN5Rkg7znDb8P6tU1VhSvwEKsVhYXzkgrVH4RkpheOGek9CNOjDJfPmKdeZOep0+KtLmGtPEIWvkEWJOD66Kj3ynK+Nyr5I2sIdcTy20p0s8ZCMOnRS30wM79H+xRg9JWEoIjJtaZacoIhWwiUbbnz64Fws/r/pCqFyx6wB+MmoAvzpohG6v1GOQXsSqhKXUCrDLlAS8r6UQOdJQlpJNqZXBnpluvDNXTPw7s2TVdvu2rULN9xwAwDgsssuQ0tLC7NoeeWVV2L79u1KOcwpbwfnp2DDb87EvbOHKNuQPj9e+3ZQ1ZXvkTbUU2iP6pmGU3qlKwrersQ/rxmLQXkeTOibidkj8jEgN4VpV8l4IMayFXesDbQHvTJduiou0ifS7adPlguRqIiKRjY5oJlS7+sl9iJEDunnSFu1W8xoDYTxv01lsFlMumqxxy4eiS0PnhVXjfnLMwZi3tieSiboZKCXqZ2cR52sdkvWBiNZ0IRTe9TTf7/yFPzhwuF47+bJuHVmf93tyLtI6/nn35fxVNQ8pvTPwtWTJBJfIQnl55dWzepFXLg4X71kvDHJOIgm/odSqr5k689tl5Km1LXGX2kemOeB22bGgaoWPPdtMQ7XtSkqch6CIDCkH0HPDJfi9zp7RD6zODE4PybE4seTm440oKrZj6EPSeIaOsnRxKJMOG1m3HRqX0ztn8V8R8YozRUlGHjaTwCo++Bsjx0/vf4aBGtKlMzUJGkMII2Rmn2xcd2KA7WwmATdd0gW9ShauCbU4I994A9FceqAmPiLKAkJWZysN6yhJNQAr4rh4XQ6sXixOkOTAQMGDBgw0F7QRJwgCFLCg4jIZJwEWO9C5bccA0FIJbLts1eOwVtrj+DqSb1hMZvw0e3TUESRhPRYlRBjTLhxEgN1cwJPQl2SUEdJyGdW1pvAqz0JY+HGHodFMcV2cpMSepBMElwQKErCdvpNkXNsD0lIzsVLeRKSgT4htf7+9QF8srUCj80bqVKT9M/1QBAEZXJOFIW+oEQSDspLwdd7qnUngX2z3VhXUq/ab6JrBOJP4FKdVgiCRFY2+2MeTWRike2JhUi3+MOqQXsoEsXO8iZYTJJH555jzcrva1sDTJsnzwjfxvgwU/58PXaLolrgUdkShGCxYWCvPGw/IKs8YUfELw3yyaQ8moAlVEjCBI8Q40moEflHnuW7zxmMraWNWFlcyyQUMpsE1aQtmQn2ez+fknAbLfChjsFIFG3BWBZpguevHot6b5DJUJpsuDGPbI8d/7hqbOINwakF4yUuoRcpOhpu3M1Kwsn9JLWUIAgJPfBMJhMcDgfS09OVz1JSUtDUFAunmzO6B1YcqMU5w2PRQDlcozMnsUBC8ww9POR30vnxikeH1YyPblfbTXQFZo8owOw4vnTJKAlNJgFf3zmDUYCdCLz38ylYuLkMZw/Lx58X7QMQU02REFwAGC974pHuJ1cn1JcsjpGQYNLn0o9EMBzVfXdbzKaEqscsjx1PXzY67jY89BYwyKIVWSSMtxDVEdALFIkyHtPITXHg2ilFCbcjSkIt0pZfpGqneFsB4SdIv2Y2Ccq7QE8N7bJZWJIwCYJv+qAcHKhuxaR+mdgtv3+HFqQqycWSVxKa4bSZUdag/a4lyEt1oHeWGxuPNGCjnKVciwgkuOvsQbj5zU3MZz0znBhRmKaofMf2zlDCl4uyYouNdF1M7Z+F1QfrcP/CHcpnWZRakDxbv/1JLLrqn9eMw3/WHcGKA7UIRaIQISJNXqTT6oMLczIgBtpwpK4NLptZlXjtWLMPaS4rolERGw7XY2TPNLT6wypfQQBIs8fGHIle8eP6ZOCDzVKUFvEkJO0mI0kfYkNJaMCAAQMGDJxA8KG6ZnnQx4czkoElvT0/CVaUcPKEMt1lwx2zBiqKmlN6pTOZJ+kQZDI3ZEnCJJSECcKN9b5jPAmpQTTv+aMXRqOVuISQdPQkwMkNnulB8ulyNkZiXh/Q8SRMBEJ0JVKX8XDbLTFyj/IkJNd2qNaLb/ZWY83BOpWnzYBcaXbuspohCJLSMCyHfTptZvzyzIG455zBuO/cIdAC8WLSUxryoCf/8SZwLpsZDosZta0BiGKMNCGTp0hURJ7sg9USCKv2FQxHsa2sCUMKUphMm2TSS7dPPtyYgE6WYTEJKtWax2Fh7pUlLRfhhmNKecj8v2HwgH7KuTXVHoMtVUoqRIgunsTnQa5bw4qIAc2RpiYYu5OJID3RcWhkP+6uBBGARKqQ/RNihbRhmjRzWM2qUFM7oyTsnvOzx1FC23VUhh1WEmr0j6mdJAlpFXR6gslcUVERiouLlfKaNWsY+x7eK/3ScT2x4Tdn4oyhrGUMDeWK4ikJaZKQmsuve+AMfHv3zLjnfDyRn5pcqPOAXA9DZp8I9M12466zBzOLJmmyjUCLP4yhBal4Z/5kvHrDBOZ3PXSIUBIyS2wVSFslJAzQvjDhrsSf543Ce5wy1mQSmAU8e1crCalnv70+rMmAvA+0FNJ8/9xeiweCEFECm9h+VusYBFLiEurak1AS3nfuECy8bSp+MipmhcQqCZPr49x2iaAk2ai1kOGywmE1ow8X9h+vbZ49PB/bHjobE4pi1kq8bcB46ju6r6cVw7+/YDjSXVYspTJun9IrHZ8tOBWLfzVd89izR+Qr0Tjf7KmGOTUXpuaYRRjfB0dbamF2S+fitltUUTfHmiSV8IHqVjT7wxjfJwMunXuUTj3qiV7x/an6I0pCn7xwrucLysNQEp7E6NWrl+Ldxvtz8Z59Xq86jTaNzEzWu4H34HvuueeYMq+m5D3K/vrXvzJl3jNt5MiRTPmCCy6Iu3/es2/w4MFMedMmdsUgNzeXKTc2Nsb9/tZbb2XKvCfe5s2bmTLvied2s53VtGnsqihf/7wnHu+pePToUaY8Y8YMpuz3s6EFaWnspJn3rOPPf8wY1mtjwAA2TGnNmjVMubSUdSfgPROzs7OZMu9Zydf/sWPHmDLvYWi1si8Y3jOQ95zkz7elpYUp8+1pyBB2Ulxby5q4Hjp0iCnz7e/IkSNM+bzzzmPKRUVFTJm/v/z58WV6ZR+AKuER75HIewjy7Yv3rOTrg7dB4J9P/vnet28fU+Y9Cfls79Onsy/TLVu2MGXeg5DPAk/qO5H36g8VKhWU2SStUPLZjZXVY+ozjhwJttNTjyY6YkpCbYUfD+IRlyhxid4uWCVh7O/Th+TiswWnKhkQ9Yg3/tx8oYji9UJPAviQQ6JYGN4jFf+4agx2VTRjxYFarCquU0jWjnoSthduu0VRYflpT0LunBvbQihv8KFnhlPxbCIkn8kkwCOb1PvDMS8/u8WM2+OEqBKSMVlkU4ojm1n/esmkhHhekYkumaj4w1FmQs4TNEfr29DQFsI5w/MYQ3xC8ND3PaooCdlzoLfRIszcnLo0Zcx5EMVYPzVwyDBYLBaFcKrftx6ZA6T3KrlHiZSEhEBLxMHSp+fRGLvT/QBRvNmtJrTIw0Cnzawi0tuTuKQjsFtMCIajSHVYUdsay76qFX5Lo6NKwvaAPgbfR9gZNZFF8/P2QBAkwpRWP3dWSSgIAv55zVjkJ5F049Zbb2XGT7wf9JdffslkNxYEQaUcVB8/8TnSYpgeVDeSbAKL44Ue6SfX+SQD+tmlyZgUuwVT+mepti/Q8XwkFgTVckdB3ilT+mXh8x3H8NK14zSzxx4PXDZBO7Ov225W+pKOqnv1QD/jeur6zoAMc7WeH74/7mgoNfEKZP1UpTrT6/PNJoHxWExGSWg1mzC2d4ai4gckVWum24Z6bzBpktUqew7HA1kIoW1wUhwWJeOwHtJcVuXdnuKwqPrdMb0kYo7/nCZMi7LdGNMrHd/KCsn3b5nCZK/WA8nafMtbm5Ay5jykUP4LfB+8c90yOPpIaluPPeaH2DvThaP1baiUScKNRyTeYXxRJnaWN0MLGVR3lmj9vj81viN9Phlr8vYkejBIQgMGDBgwYOAEgieYLGY53DjKKwk1wo1NAv51w3gs31+L11cf1s3Oq4cstx0jClNx+fheeH31YdVveYKNRqrTipqWgJS4JM7x9JSE9ECXHzSPKEzDHacPwD++LWbUZDR48ueVFSVKZjja0LuVk3KZTQK2PnQWHFYzHFYzJhRlYlWxtJBASNb2Kgk7Ssq4bWbUyJM4v4YnIUFxdSt8oQhmDs5BmtOKN9ccwWkDY4s3HocFLYGwMgjU83Gk0d6so7QCIR6p4rSZ4bCYUNUsDX7JIP3OswZhfUk9bp3RH1UtsYUwXpVAlI3De6QpPl1AzE+NJpQVJSF3v+j7p0US8pOclDHnIc1pRSAcgT8UVRJkEGIyffp1SlZS8lkCIWEse3UCkpCuSpdVap/0sy9Ski6ihqH7ALvFrApz704lIRDzTOyX48GhWq/yjCWa/CabuKQzYJSEfOIS6js6BK0zZ2I3dy1JCCBuCC2NW265Je73JIFJRxCvedOPT4LkuCcUJxtpmQwYkpDLFKsFPSUh6TvLG6V3IiHMH583Er84YyAG63i+nUh47BZUyZnS+GRMnQWrJOzafQOxd6JWH0grmE8fnIP7zxuq2iYZKJ6iTPZi6XgqtaIgLbBGRRG5KXbFWiUZT0Jl39Q+M1xW5Kc6ZJIwufqLRkVmLDKiMBUZLhtWUNl3yTF6UyTh9t+dHdfChoC0aa2xzNCCFPz+guGYyhHrTm4RaVB+ikISjumdmCAEgKsn9cYz30hih5Qx52H6GfpZth/705+w6A9SckmP3aLYu/TPcTMk4Y6yJvkc0vG/jdrjN3rNIxHPnOW24Y9zR2DtoTqlbZD3tsue3PjACDc2YMCAAQMGTiD4lVaLyYSIRrgxUd6wyUYEzBqSh9G9JLUxIViSnYCbTQI+W3Aarp1SpPwm2XBjMmmxmOInLtElCTkvRh53nzMYhx8/X3flm1ci1XuDeGe9pNLuTYWeTB+Uw4SYWMwC0l02TVVTR7MbJ5v8g0eKw4JmfwiiKMYlCbeXSwPIoiw37jlnCLY/fA5GFMYU5h67Ba3+EPxBWUmYBElYqEO+6oG+R/HIIKdMvpIJDQm/HFGYhp2/PwfDeqQy5F+6DqmS4rAwisOQEkqvDjfm24IgCMo5ap2r1kTJYTUppuLEy4wNXTUp2wGJw42VhDIJBNL0428xqbN504chx6avlmQrpdHdJCGpd5L4RFH/JDgu3Z90NOQuEejnOl64Ma1cIeFXxAOwPSB1bTULyPbYMbpnWoJfnNxor5KwmwShncI3d83AazdM6LDC+0TCxigJEyvA9JSEhCAli1BWRXVlPSkJQgDwUOST3nuho+ho4pJk8eI143DeyHxcObG36ju633vtxolMAoz2gCRmS8YqgbyvIlEpoRRZvPDYk69XPvSdKHMTEY3PXDkG/XLcGN0rnTm/G6b2xSvXj9c8RjblBZgMQQgAzbJvn5Z/oSAIuH5qEQZy3/EJioZQz0Ky4768VAceonwKc+Oos9NdVmUM4rablciYfjKxueFwPc76yzJ8seMYXDYzcjx23eQ+adRh6MQl/TPUYxFBEHDN5D6Mly8JN3YkMT4EDJLQgAEDBgwYOKHgjYwtJgGhaFQVzkjGTTTnQXz9CBFXXN0q76P9r3ezRuKSeIo6onIwCR1LXJKMQT6gH5bIk6g0+mTRfiw2bH7wrLjnQwgLoghqL+nXUZKwR7oTwXAUx5r8CEdFZUDNky17KqTwE/q6aHgcUrixLyQna0licmw2CfjPTZPw5S9Pa/d5xyOhXDYLEyqmpayiyb8Mt/akxWYxITeVVhKq701UJ3GJtJ30mZbqUWvCbbfEMkITb0r6t0p2UCUbcwKSMGklIWVGLqgVIfRRyHc08e6wmuAPs5YdXZ0ZVA+EqFbCjRMcl+4nuivcmLEa4BPY6CgJ0102rL5vFl6/cWK7j0f2ObZ3Bjb+9kzVpPT7init+zg1rw6jf44Hpw/JTbzhSQjy7GZ77IxiS4+Y0UvOksdJPK3dRMp3JWjlZFcocmnQ79T2qOmSxcC8FDx/9TgmtJcgWdIrESJaSkL5nUAIIIK7zh4EABjfR1r4SOcSiCUD+l2U7rShf45HXgyJH656wegeWHrXTMmTkCKkXDbJBuWFq8cqiymEtBsrq/ho8i0RSuSMwQPzko+K4BPZDcztWH9N++3GIwkFQVAiVPpme5RxQ5bHBrfNjNUH6xQ/wh7pTgiCoJtpnVYS0mLO0VxXN6Wf2pYAANrk8aHbmlwbMMKNT2Ls2bNH8X7jvbp4jzPec23gwIFM+Y033mDKvCfaZZddxpR5D7Nt27Yx5Z/85CdMubKykinTRsoAsGLFCqZ88cUXM+X333+fKS9YsIApz5kzhymbuIHfxo0bmXJNTQ1T9njYDoT37OvTpw9T5j3XysrK4u6f96TjPeGqqqqY8syZM5lya2srU+Y93XjPv9WrVzNl3vNx69atTPnNN99kyrzHJe8px3vIrVq1iinn5OQwZb5+e/Vi/UYGDRrElPn7xXs+8p6C33zzDVPmPQx5D0feY/GDDz5gyjfddBNT5j0d+fvF31/eQ5B/XngPx/z8fKbMt7/Zs2czZd4Tk39eaVNcAMjKYl8I5eXlTHns2LFMme9PmptZ/wveA9PhYAehvGehmfMn48v8/f/888+Z8mmnSSSFz+fDe++9hx8b+Gx4JNyYtzwjRAirJJR/w/WJHZnEkd8k60lIBn8Ws6AQmCTbKQ09xVCyIb16JCOpHhJWQ6NvdqxPsZlNDGmidVyToiTUJ53iIZkEL1ogZtsHZHI35knItglSp3RmahqSkpAKN05SQTNtQHbijSiQUFgtEqpHmgMVTX6YTQKTaVFrspclk3GF6U7d5Ax2OSGH02rGzME52FspjXvoya5e4hKAqC0iOkpC9TnZLSbcMWsAfv7mJswZ3UP+jApNko9L2k+iJDUk0UoikpDmWwUtkpAaT5Dnkb5cyRg+9k6c1DezyyaliTC0QHr3eUniknYoGLsr3JgmVvhwY/qY+VwoKp9kJVmkOqw41uRn7sH3GUQXniic/q0Lo8hvn2OBgSQgCAKW33M60pxWJVQY0A+R1VNLZnnszLuxowtZxxOEvEuxW+JanXQEJOFSKBJVedJ+X0AWyui6Ifffx/U/N0/vh/mn9VPGX2kuG1AXP8swD3ocYbOYcPusAZgzukfChEo06PaZKrfhc0cWYNXBWmwra1IUrzkpdiUzcbIgkTPtScBDfB3JmG1ArgdOqxk/O7Vvu45dSL0vEtkaXDSmELsqmnD/eUOw/G8Sf2ASBJw6MBuLd8Xmm+QdROpsSJaIR2aIuGyhdL/TKS7Sbgb6pYs41Cgw2eY3/vZMXSJ4/mn98M9lBzGqV3Jq9+/nU2LAgAEDBgz8QMCTaCRxiTq7sdqTkHzGT7iTVelp/YYNN9bfDxlomwRBWcXOT3PgaD07ENXjAvgJvP556ZCEcv24bLEMwQR0KKHNYmLqWKtuyNdK4pJ2kix2S3KkHI9esvfdgSqJAOOzGwOSFxAZDPMZ/AhSHBZ4g5GY50yS4STtRarDgoa2kGpCAgBL7pyhkJQ08a0VNmYyCVhx7+lIdVhR5w2ovgdidbDnD9IiyqlPLAXAJscgE2AtkpC0XZvGvdEaRLvsFpwzPB97/zCbyhip9rcjx0qUuIQ8H1FRQDxdFi90dHAf0L8kjyOrJDQrqri7zhqEBWewi8TdicJ0J2wWE1oDUns4GUhCWiUUr//qqnDn207vj1++u/W4EbPdDXIZiRK1n6qde8JAF4D4szX7YysMfJ/1/NVjFXJeC2aTlKSmqpkNNz6ZQRTeHU0klAgOiwl2bjxwvPD7C4bHVZwlA7KwQRNUeiShIAjMYhJ5Dzf5EqxaUeD781SHlbE5SQaMryEVNXDP2UMgQMDdZw/W+llS6JftxqFaLwbnpybeWEaL7J9L3hMOq1kZY7QHdFKk3ATGrH+5bDREUXrnkHG9SQDOG1nAkISF8j7JQqTdDAyiHDB4m84ZfYBDjUC1F5jZR8TacjZsm8e95wzGbaf3B4I+3W1oGCShAQMGDBgwcBKBqLV4klAJN6YGfoS44Cfc7U28Qe+XCTeOQ+QRJaHZJCi+RwUaJKEe4ZbsOeoN6En12C0mtHI8UypFTPFEgdZxSf0FI1GYhPYTCEMLUvCzU/vivJH5iTem0CtTGuwfqCJKQjVJmOqUSMKCNIeuaoQMeGvliuguLy5yLs0aEw2P3UINvOMrCYEY4Um3czppBx9yfdWk3vjzon2MEfkjFw7Hz9/chEvGs+p/ALDJbVeLuNIKNyP+enTdMUpCuR2ZFCVhfBqFTBwKPPG342+V6t5RP9d6lhxWM+46ezAG5aVg7pjCuMfqKiy8bSqafCHF+7E1ILWH9oQ5H59wY/Ux5ozu0aVZby88pRDhiNjuyfPJjkRKQgPdj9Q44cbnjUyc3CYv1REjCTuodj+eINfYEbuUZGC3mo+bFQOP66cWdXof9583FD0zXLhuaiz6bVyfDCzbX5MwbJYkgmlsS2CS28WgFyyJnQcgeRz+Ye4IrZ8kjXdvnoyDNV6GNE2EWUNy8btPduH3F3bu2PS16HkIEtCEbYwkFHDO8HycNSwPX+2WiMIeckb72BgDoN1Y+Ffm/00U0eADbhsnYmASdromk4BUhxXNBklowIABAwYMfP9gMQkIhKP64cbUxJcoisJciG9HVDqxxCXxw41JCJNLhyRUbd9NnoRESail4HFwYTKJzofsIxiOdmiCIggCHmyHlw4BURLur5aUhOS8aYKMkGx9dEKNgVj47C/f3Qog8aC1oxian4ojdW0JE6PQ9Z+VwL+IJnTTnFbUy5k+eHXmrTP64+qJfZBGLaefNjAHux/RVgGY5XaspWTUIgnH9EpXfcYmLiFKQqmcKNx4VM90PHnJKEx1b427Hc9hxvMkNCl9ALu9zWLCvHFqorS7MJbKAmmzmNDqlT0J26FW6i41T7xwYwB49soxqs86i+NZ992NH4oi8ocAN+VX3BEfPcn7VbKrsXYT8daVIAR/d6mMUx2WpJJ6naxwWM2YP70f89kdpw/A0IJUzErgwXnXWYOx51hzuzMrnzUsD310IhiSAV3fGe0IU04GuakO5LYzg3mvTFe7w5q10NF+kiy+CIIAh9WMl68bj3F/+Ap13qDy7id7jkK9iEgj1Q787ezuW80xSMKTGBkZGYoXGO95NnXqVKbMe4otXryYKV9xxRVMmffgs1rZQTTv+bZs2TKmzHvO7dq1iyn36NEj7v4//PDDuOdz3333MeWnn36aKfOea/PmzWPK5557LlMePJiVM/Mee6+++ipTHjlyJFMOh8Nxy7znHO+Rd/nllzPlzz77jCnznne85+LZZ5/NlD/++GOmXFRUxJQXLlzIlInnGwF/P/j65PfHexDy7YO/3y4X+0Lhr4/vXPn2xJ8P3z7OP5/t4Hfu3MmUeY++K6+8Mu7x9uzZw5R5z8C5c+cy5ddee40p8+3r6NGjTDk9PZ0p8/Xz5ZdfMmW+vjMyMphybi47GODPl/cMfOedd5gy70nJeyDynpperzfu+cyYMYMp856p/PPVty/r/TFxomQWz3tz/lhhNZvQGggnFW5MCK3SBla91yElYZLZjQVBAERRIaLMgoCqFqnPy09Tr+h2Vkmot52ZyhhXyzUdOkMsTxJqKgnlj0KRaLdNULSQ7rLCY7dgy9FGALFJEiGnTumVrnxWpJO0BFAn4nDaumdC+NRlozFmbXpCVQRNdCWa3NL1TZOE/H0TBIEhCBOhrlXaD+1PqZyTRrjxmN7pqs9okpA8F+1RwF06vhdQtjXuNnxkHT+Rovtjcmw6n7izm0LzkgWtzLGfBL5n8RKXGEgeIuKHyRvoftDecx3JyEsrZk9EiG17QfrY7lI9/vmS0d8LRWV7YDIJOGtYXsLteme5sOT/ZiTcjsfL141PvFEc0GOB72O28Xj4+s7p7VZc3332YNz7wXacPjg2zzt7eB7eWV+qjFXIGJ9b+z/uMN6eBgwYMGDAwEkEkrgkEtUmCemxPplDXDC6kM1m2IFxsEISahAjNMiuicrBYhaUD3trrDjrZzfuXLjxpeN64tJxPfHaDROYzx+9aAQzueLDixJlN+4IwdpRCILAkFMkkYjFbMKWB8/CuzdPVpR2veMoCVM4Iq67BuMeuwU/n9E/oQk+7enXnhX3VGoi3NmwMOLPqJXshSb/zh0hLfL1y1ZnYaCzNMeShnRt++Bv1YQidhFGS0koUp+e6ImXLQ4hfyLAkIQ/MELgeID4nk3sYRCEJxO0FjYSgVb8fh9AIiK6a6FuXJ8MjOqZ3i37NqCNZJOofR8xIDel3dnsL5vQC4cfPx/9cmLjjYcvGI63fjYJZ8pkL2n+hIBccV0U6288/ozhiX+bGzBgwIABAwYUWEwCwlERosiuqJOBA61kIiG7+WkOrHvgTFwqh72laGRvTQQlcQk1QOeVOIIQIy1cVOKSl64djxunFeESjbA7PU6ls4lLHFYznrx0NDPY+uDWqbh6Eqs8TkZJqIRtR0UlTPV4Yd7YWJ0NyY8NODPcNjisZiXcOJ6SkFdHdFe4cbIgnoTtzSJJhx53lXl9kYaSkKzYzz+tL56/eiwOPHquJhmtlbhk5uAcnDk0D//9+ZQuOT/+Mif3Y5XwtFKBPAvRaOyen+hJWLLZ0I8XnBrEroHkMaEoAy9eOw4vnWeQhCcTOvJOn9g3CaOykwgheWHUeG5/OOiuqIYfEuwWM04dmK2UyXiU9MC9UoHc5BM4dxmMcGMDBgwYMGDgJILFZEI4GkUkKsqZjiVFVExJSJOE7G+fmDcKj88b1TFPQo3EJTaLwG0jIKJkFZaVhCYBA3I9+N2c4dr71TmXZEMB23MtWkky+AmHppKQCeE+viThOcPzMSjPg7ljCjVVaiRbXb8c/VFibStrRn6iiSOibnO300crnQq17SqDeS1ytU+WGxt/eyay3DYIgqAbgkaTnKS9OqxmvHJ950KwaPDiO5JAhYBWDZqVMCQRZpOAUERk1I4nAnT26GSUhOt/cwaaffpZWTsLgekfDSVheyHIhvooO9FnYoBGx8KNk0/ocDKA9Pl6ya4MfP9wosci30fMHpGPf3xbjJvHnNiFGoMkPImxZMkSWCzSLeI9x3jPsrVr1zJl3hOP92DbunUrUybHIeAnKryH2pYtW5hyIMCmluQ92fjveRw6dCju+fKeerxHHe8p99FHHzFlpzP+i3LKFFYRwHtA8p6LZWXs6Im/P4WFbIbBbdu2MeXevXszZb7+q6urmXIoxGaSvOqqq5jy/v37mTLvmcifz4gRbFanb775hilXVFTE/T3fHkpLS5lyXV0dU87LY/0y+Pu1evVqppzIE5H3yOQ9Dx9++GGmzLf34uJipsyfP3+8l156iSnznof8+fL1x3tW9uvHGg+vW7eOKfPtNzs7myknev4vvPBCppyWxmZdfOONN5hyZmb81WbeQ5D3oKyqqopbPnz4MFMeNGgQUyb3x+dLLuPWDx0k3DgqinBYzAAkkpBMeOnumU/+0RnfIa1wY57IMwmSyhGIESj8Mcf0TsepA7Lx7FLpOdPzcEt2At8eD7h0Dc86tZJQTWTQfNTx9jFz2sxxvYKum9IH/XPcGJKfqrvNtVP6YEtpA1YVS33vyTIwdyVpEj+lXxbWHKpDmjP2Luwq8qtnhvb7n5Cv8UBPzLvLy4qvIovZhE/vOBX/XnMY728qY5SEViqbudROoyf8Xrc33Dg3xYEEiTi7DN+HZA0GDCSDjoQbA8BL145DY5s6G/3JiPnT+6G80Ye7zh6UeGMD3wskm6DOQAwjCtNQ8th5EMo/S7xxN8IgCQ0YMGDAgIGTCJJ6MIqoKDIqOMKV0eRaewi0RFBIQjrcmCNGTCYQzhJOmxlWs6DyRPvwtmkAoJCEesRlsoq9zioJeUWa1pjVdBKrj7I9dlx4SmHcbfJSHfjPTZNRdN/nAHDCMzi2BaSFqmSVhP/+6UT4wxH8Y2lsAaezSsJ/XjMOZQ1tjD9le0Gff3eFwGnxaiN7puE35w3FgaoW/P7C2KLe5RN6Y8PhBvzijIG4/KU1ANiQ6BMBe4JERycShiehgR8KOpLdGADOHp6feKOTBB67BU9dOvpEn4aBLoQ/FEm8kQEVToYs8wZJaMCAAQMGDJxEMMuehJGoyPi5EPKquwgtrezGKoKNO/aL145D78z4Zim62Y2TnMCbkhgsDS1IxZ5jzZpEjipxicb+mHDjHwCxcKKJI6+cNCRZJaHNYoLNYuL87Tp3H2aP6PzkmG5P3dUu9G5VhtuGj+84lfnMaTPjuavHSudjOjk8CWn1oP0kSFxC44fwLBv4cePLX56G/VUtJzxBkQEDHQFRwI7umZZgSwMnGwyS0IABAwYMGDiJYDULSmZjlzX2miZEFhtu3JUkoZy4xKJPjPx/e/ceVlWV9wH8ew5XQUARFBBEDa+AV0zRytIiyWtXGy9DNVOvpZaZ03SZxpops2mmp97Kmi7OONak8zraRQ11ylsqpiCCd1RQU7yDoHIT1vuHc05n/Q7ngsI5B/h+nqcnf2evs1l7r733OSzW+i0vgwG/G9kDr67Yi/6xrdHuvyth2mOrj8/g5BLMzvyi/+XUwaiqrj1/izNTILXRmR42krAu3ryvF9btP3PNo07qyyXTSMI6Llyij5z1rHZoqJGE1/q7v2WORHey7Mz19fKsjgxON6bGrkdkMHpE2k41QeTJbu0ajjfuTcQdPRvPiFa6ip2EHmz06NHw97/6C1hNjb70dU5OjhbLHF8yR57MkSZzoPn46FO0oqP1FSq9xBc/mUPulltu0eKTJ09q8bZt27Q4NTVVi4cMGVKn+skcfjJHm9xuFF8UZQ42Pz89N1FhYaEWBwbqI2Xk++XxJiYmavGZM2e0WOZ0DA7WvwDI8x8XF6fFMqefzJGXkpKixfL6kTkDZQ7DLl26aLFsD3k9TJkyRYu3b9+uxefPn9fiESNGaHF6eroWyxySSum//A8ePFiLe/ToocWrVq3SYln/YcOGabHMMSlzVMr6yByH8vrq3VufLiFzJsr6yfa/4447tDg/P99ufeX9vmTJErvlH3jgAbv1kzkHZU7FrKwsLZbHL49n3LhxWpyZmanFpuuvslJffKG5ssyJ528xEqvW6cb1+DtwbQuX1La68a9v7oxHhnRyOv9hjY3cyzXKuaTMzvwYP28v2OoXk52EV2qpkGV/lKsXLqlP9yfF4P6kGMcFG9iY3lH4dtfJWle7tseTV7VsqOviWgffmZ4D7u4ktLy/fLwb771DRET1y2AwYPyADo4LksdhJyEREZEHsfylO8CiA8A0TdZyamzbIMcj+ZxlNE83tj3l0zzluQ4dJtU2egmd7SS8XnJkYG2dhHrHq+d2VDUWqYmRyH05BUH+dVulsr5WNK5Pft5GVFypua7chvZc68xw073p7qnl2urGHtJ+X04dgq2Hz6F1oK/jwkRERKRhJyEREZEHsewktFyAwmjuJPy5bFQr+yu314V3LTkJ5cguZ/IDSrY6A22NMLR2baOTPpzUH3tOXLB6/Up1jdVrWk7CRjyS0JPUtYMQ8LyFL4CfOwl9G6hu1zuS0O05CS1zmHpITsI+Ma3QJ6aVu6tBRETUKLGTkIiIyINY/tKtdRK6YeESuUpuXUYQmtQ2cg8AIkOujoK8tVt4rdtNrjU13YiECG3xivAgP5wprYCft3Wniievbtyc+HhIJ5Mlfx8vlJRfabCRhNd6tZnuU/dPN7bISeiB7UdERER1w05CDxYfH2/OhXfgwAFtW9u2bbW4Y8eOWixz4BUUFGixzOF35513avGRI0fsbh86dKgWf/LJJ1oscwL26tVLi2XOsuLiYi2WOfS++eYbLY6MjNTikBB91aT27dvb3X7x4kUtljn0ZA48mUNP5gCUx7N8+XK7P+/CBX10y3333afFy5Yt02J5Pr///nstDggI0OKbbtJXRDx16hTs+fHHH7VY5pgcMGCAFv/lL3/R4upqfYn7u+++W4tlzsDDhw/bfb/M+SdzEO7Zs0eLZQ4/eb3n5eVpsWxfmaNv+PDhWixz6PXs2dPu/nbv3q3FMgekzLHZqlUr2CNzeMocmjt37tTipKQkLb755pu1uLy8XIvLysq0+P/+7/+0eNCgQVos20vmRC0pKdFimdNT3k+m8mVlZVi0aBEam3nz5uHNN99EYWEh4uPj8fbbb1ud87qwXCHUcpSQqe/K1vTd6+VVy3Rjf9GhVpf+M6Ph6mjBGhv1bRfsj43P3ubU4if1Yenjg7EitxBD4tpYbbM8Lo4kdB9PzElo6oRrqPvuWplHEjq5gnRDsfyjRmgAp/cSERE1dp73bYyIiKiRWLx4MWbMmIEXX3wRO3bswM0334zU1FQcPXr0mvfpa7OT8GqnwPHiq526YS31zuLrZcp5aNlR4yfynXnVYVifqRPDXu7BmNAAh6OP6qvLLiY0AFOG3lDrqrlNZXXjxs7PA0eimXL+lVdVOyjpWqaRjbIj39VM96/BgAYbbUlERESuw5GERERE1+itt97Cr371K/z6178GALz99ttYtWoVPvjgA7z++utO7aOyslJb2dkHNfBGNRQMCLAYJeSlqlFZWYnY1r7wRjUmJEWZ32cwGLQRqvZWirZV1qCq4Y1qGP/7fwDwMeijur1QY3ffvr4/jyTyMSgoVKNKHF9tZauqqqxG5JpUX6nSYntl67Jf4OqoXoPBAKPBACNqYISCr6H2YzSVBa6uyC1HvFvy9vY2r/rtCWWrq6utRgBb8vLyMq9a786ypg5qA5Td68xoNJpH2NfU1JhXSG+IsgHegDeqUVZeodXJsqxSClVVVbXuE1XVMBoN5g40pRSqrvzcbm38AG8o3NtdobJKwVBV5dS97GOohhdq4O9rdFgWqJ9nRO31uHosbYP8HJYF6nZ/ekLZutz3TeoZITrFvbyM5j+gVNcoVMvcrhbt7ornSUPf9/Vd1u4zoo5lG+pebqiygH7P8RnRRJ4Rgqd8j2gyzwjxDLb3PcLMid8JHN1/JuwkJCIiugaVlZXIzMzEc889p72ekpKCzZs3W5WvqKhARUWFOTZNs/7LX/5iNYV8kj9wrDoE/j7dfn4x92vM2bnMvL0kIwtzMq5uio2NxcMPP2wu+vbbb+Py5cu11jsqKgqPPfaYOX7//ffNKRAm+QMZS7Mw6b8zgHd/nw8gzlx2YOUOzJmzqdb9hoSE4OmnnzbHt3vtQaj3JexNz8LedL1sQEAAnn32WXP82WefWaW5MPHx8cE9/UZiTO8oAMC//vUvqxQCll5++WXzv5ctW2aVnsDSCy+8AF9fXxiNBgz2KUCc1zngBDBnzhqrsr/5zW/MU+dXrVqFbdu22dzvU089hdatWwO4mh6ituvB5IknnjCnENm4cSPWr19vs+yjjz5qTqexdetWrFljXU+TtLQ0dOrUCcDVlAkrV660WXbChAnmtAE5OTn46quvbJa9//77ER8fDwDYt2+fVXoCS2PHjkXfvn0BAIcOHcI///lPm2Xvuusu+LSMBQC0M5Zizpw5NsvecccdGDJkCACgsLAQH3/8sc2yQ4cOxW233QYAOHv2LObNm2ez7ODBg5GSkgLgalqQd955B30A9PEHrmRlYU7Wz2UHDBiAkSNHAgAuX76MN9980+Z+e3dpg7uHdgQAVF2pwZwF2dr2Sf4ACoA5BUDPnpVaCgxb5yEBQIhPCPx9fk7f8Oabb9rsXKivZ4QV/2AA3cwrrX/88cdWKW9M5DPib3/7G06cOFFr2bo+I1588UVz3BDPCOBq6huZ3sNSk35GpMSha4erqXtyDp7DVxtkW2Sb/9WQz4gbb7wRwNW0SAsWLLBZ1pXPCFvq9Izo3ducqqeqqsru869nz55OPSMAoEuXLpg4caI5dsczIjw8HFOnTjXHfEY00WeEh3yPaLLPCAffI666+pq9Z4Tl7yH2sJPQg61evdr8i6OcHhUVFaXFphvYpGXLllosLwjZCy8fEKYbzGThwoVanJGRocUyZ5nMKTds2DAtPnv2rBbn5uZqscxh1r17dy2OiYnR4qKiIi3u1q2bFsvz8d1332mxPH8yZ5zM+ZeQkKDFmzbpvzSPGTNGi+VfaeSHrvwLlcyxJ3MQyvO9d+9eLY6IiNBieTwyB6TMESc/XDp06KDFMuegzHEnj+fQoUNaXFhYqMXyfMoOE9neK1as0GKZo1LWR+Zo/Omnn7TY9EFlYu+DGIDVF6zQ0FAtln81kscjc3TK41u7dq0Wr1q1yu7Pl8+H2NhYLZb3V3R0tN36yuvr0qVLWmz6K53J/PnztTgxMVGLc3JytFjmUPX396+1Hp7u7NmzqK6uRrt27bTX27Vrh5MnT1qVf/311/HKK6/U6We4O9+YQUz2rctE3E5hgbhw7pLjgk5464E+9bIfWzjD2DN44urGns7dqxubFiZqF1y/6Q+IiIjIPQzK3vhZcouSkhKEhITgySefdLqTUHbqyV+2Zafe6dOntVh2Isn9yYVT6tpJKDvNZCeh7NSRnYTyrz2OOgll/R11EsqFR+T5kJ1InTt31mLZSRgXF6fFjjoJJdkpIzsJ5cIsspNw7NixWuyok1BeL3KhDdlJKDtAZPvJTk65P9lJKM+PbG/ZiSg7CeXCHrI+sv0ddRLK+klyIRrZSXj+/Hktlue7rp2Ecn917SQ8duyYFstOQnm8slPcUSdhaWmpFl9rJ2FZWRmefvppXLhwweqe9EQnTpxA+/btsXnzZiQnJ5tff+2117Bw4ULs27dPK1/bSMKYmBicOXNGO97F247ilW/2QMGA349JxOyvry6E8+iQDvjNnfofQEzqc5rQ0fOXMOLtjQCAf01Jxj0f/rywUVyYP1Y+aXtRFk+Y+nMt04Q2HzyLSZ9sgREKw7u3xbsT+tksC3jG1J+mOE0oI78IEz/ZCgMU9v8hxWZZV04TenbJTizPKcQDSTF4eUx8rWXtTg88vtK5aUL/ZYge6dS9/Ng/tmPT4fPImzPKYVmg4aYSTp7/I7YWXMAvbuyA1+9J5FTCpvKMOK6PGHI43bj9XRZlOZVQluV0Y043rmtZj39GCJ7yPaLJPCPEM9ip7xH/fQ7buz9LSkoQHh7u8HctjiQkIiK6BmFhYfDy8rLqND99+rTV6ELg6ohSOaoUuPpl1PILqb+fH67g6pccy5GERm9vrZw9zparrayf7xXzzw9qIVYeNjpfB/nHCU8uazAYUAMjagB4+fg4PEa54rynl7X84uzJZU1/71AwOH2dGY3GBi37yrg+CGjhj9+O6A5f39qvJ4PBTn3FSD+DwQBfe6P/xDVra78j+8SgY9sQp8rWpr7Kjuwdja0FFzC6V2Sd9+vu+76uZT3hXnbZM8LONeplNMDLKLbbaPeGep409H1f32XtPiOuoyzgnvveVWU94b7nM+KqxvI9wsQT7vvrekbYeQbb/B5h42dZ7tfZ+rCTkIiI6Br4+vqif//+WLNmjTYFf82aNVajeeu0X4sVXv0tvgTUZWXh+uIvvoS4ow6uoK9uzBVa3cYD57aEBPhgzt2Jjgu62P1JMbjf3ZUAMHlQLEYmRqJNPa+2TkRERO7BTkIPVlxcbO7tveWWW7RtMsfgwYMHtVhO1zUl/DSR0w/ldMJdu3ZpsZzeakqyaTJ58mQt/uSTT7T4xx9/1GI5vLVnz55aLKdnJiUlafHhw4e1WNb/hx9+0GI5ekf+fHk+5F+N5HTbjRs3arFMqiunk8rprbJ9srKytNgofkmVvf6mBQ9MwsLCtFhOv27VqpUWt2nTRotlAmF5/PKvNvJ45XRSuT85fVWOspLtIa9vOV3YlBDWRCb+tUzWClifPznyS+ZglNMK5PmT78/MzNRieXxyf+np+ioOt956qxbLHIsyltfPli1btFhO15bpCVq0aKHFx48f12J5vPJ+l8mpZaLoDRs2aLFpOrGJren98rpvDGbOnInJkycjKSkJycnJ+Oijj3D06FFMmTLlmvfpZ9FJ6Ov187+NLuqgM1p0mPn56G3SRPsItZyE3kxQ6DYe2EdIDhgMBnYQEhERNSHsJCQiIrpG48ePx7lz5/CHP/wBhYWFSEhIwMqVK63yQtaF5UhCX++fO6yMLuq8svwxclEErybagWbURhI2zWNsDGqYJpuIiIjIrdhJSEREdB2eeOIJPPHEE/W2P1+Lkbs+2kjCevsRdlmuaCynG7tqNKOrWU6j5khC9wkNvDrqu1u7IDfXhIiIiKh5YichERGRB/G1Md3YVfkALfvILDspAdeNZnQ1y85Pb6+meYyNQXxUCD5NS0LfDq3dXRUiIiKiZomdhB4sMjLSnEvPUU41mYNOkjnG5PLzMkfYxYsXtbhfv35afOjQIS1++eWXtXjatGla/Oc//1mLZY47mROwrKxMi2UONLkaU5cuXbRY5ojr1KmTFsvj0ZYch3VOvh07dmixzIH4i1/8QotljkGZk0+ef/nzZW62hIQELd63b58Wy/bq2rWrFsvj2bRpkxYfOHBAi4cNG6bFcuqkzEkoc/DJ5d7Pnz+vxTKnntwuc+R99913Wjxr1iwtljkWZU48mdNPXu8y56XMqShz/vXo0UOLly9fbnf/Mgdg586dtTgiIkKLz549q8W7d+/WYpmzU14vMoemvF9kztGYmBgtjouL0+IBAwZoscwxKnMuhoaGarHMmSrv93Xr1gGwvm6aK8tOQh+Lf7uqg85gpzOyifYRwvIW8m6EuTGbkuE9rFcGJyIiIiLX4DdhIiIiD2I5etDy366a6WuvI7CpTje2PC7mJCQiIiKi5oqdhERERB7EckVhy1GFrppubG8koavq4GqWHYPMSUhEREREzRU7CYmIiDyIrZGErhrFZ6+PrIn2EWrHzJGERERERNRcMSehBzt58qQ5F6HMSdetWzct3rlzpxb37dvXal+WZI4zmROvZcuWWixziKWnp2uxzJEmc/LJ+rRv316Ljxw5osUlJSVaLHMCypyC8vzInHb5+flaLHPiyZ9XXV2txa1b60nUT506pcVbt27V4sOHD2vx6NGj7b5f5pCT7fnll19q8YgRI7RYtp/M7bZx40Ytrqmp0eIpU6ZosWzfn376SYtljkyZQ1Lm7JM59mRsyr1pct9992lxx44dtXjJkiVa3KtXLy2W51fmTJTXg9wu209ef71799bixx57TIv/8Y9/aLG8n+6//34tljk3Zc5HeT3K+1/mVPzhhx+0WOaclDkrZc7GoCB9ZdGvv/5ai/fs2WO3vLyeZQ5OeXym+1Fex82VnwfnJGyqHWiWHbABvl52ShIRERERNV0cSUhERORBbK1u7Kr+OXujBZtDTsIAX/79lIiIiIiaJ3YSEhEReRDbnYSumm5sZ3XjJjqS0HKEZKAfRxISERERUfPETkIiIiIPouUkdMN0Y/urG7ukCi5n2S8a6MeRhERERETUPPGbsAcbMmQIWrRoAcA6J1x5ebkWt2rVSotlzkGZ02zQoEFaXFFRocUyJ5XMKebtrV86v/zlL7V47969WixzIsocdP7+/lrs4+OjxTLH3qFDh7Q4PDxci2XOvLCwMC2WxytjeX7l/mVOt5UrV2pxbGysFi9cuFCL77jjDi2Wudji4uK0eMOGDVp88OBBLY6OjtbiTZs2abE8PtmeMgeizNkYEBCgxTInXl5enhbn5uZqsVJKiy9fvqzF3bt312J5PPL63759uxbL892lSxe7P0/myDQa9b+XyJx7bdq00WKZU1HmZBw1apQWy+v5888/hz3Dhg3TYtNzwFZ9ZY4/mZNT1l/mSIyJibFb39OnT2txaGioFjvKkSpzLvbs2VOLTc8TeV02V94WnYQ+Xj8/i13VQVejbG9rDqsbB3K6MRERERE1U/wmTERE5KEsO69c1UEX6OuFSYM64JYu4Vbb7C1q0phx4RIiIiIiInYSEhEReSzLTjlX5SQ0GAx4dVxirdu8mmiSEstzy+nGRERERNRcNdGv+0RERE2LuwbxWY5mbLqrG//8b44kJCIiIqLmin8ubyRkTj+ZY6xjx45aLHOAyZxlcsqYzGkYFBSkxcXFxVpcUlKixRcvXtTiS5cuaXHr1q21WObYCw4O1mJ5fDKnXNu2bbX4zJkzWizrL3MwZmZmarHMediuXTst3rJlixYnJydrsTz/UVFRWixzxMkckTJnoKzPY489psUy51tkZKQWr1u3TovHjh1r9+dlZGRocUJCghbL60Mej8yhKHMmFhYWarHMYXnu3Dkt/s9//qPFsr28vPRf4nNycrT4yJEjWizbU15fcn+pqalaXFBQoMWy/Q4cOKDFSUlJWizvN3l/yOtZ5nCUZI5AeX5kjkTZnrK+ISEhWixzeMr7T+4/KytLi+X1NGTIEC2WOT1N15fcL+m83LRqSMbzw3GiuAxj39/UTFY35lcjIiIiImqe+E2YiIioEXDXKL7wID+0CfRFoK8XQlr4OH5DI2TZ+cmRhERERETUXLGTkIiIqBFw5yg+o9GAr6ffhPAgP8eFGyF94RJ+NSIiIiKi5onfhImIiDzMOw/2QeWVGu01d8/0vSG8pXsr0IAsV45217RuIiIiIiJ3YyehB1u5ciV8fK5O7ZI5y+Lj47XY21tvytDQUC2WOd9kjj2Zc+7UqVNa3KlTJy0eMGCAFsscaZWVlVosc6zJ+siccTfddJMWt2yp/3JaU6P/8hwdHa3FMmffvn37tFjmVJQ5DHv37q3F8vjk8XTr1k2LY2JitHjcuHFavHXrVi02GvU1hBzVV56f0tJSLT5//rwWl5eXa/Htt9+uxX5++uggmdPSUX1kzkuZs0+2n8xpKHPRyVieX/nz5PUpc+zt379fi3fv3q3FMkfgww8/rMUyJ9+xY8e0WOaglOdH5jTs0aOH3VjWb8eOHVocHh6uxabnhInMsSjPh6zf+vXrtbhPnz5aLJ8HRUVFWiyvH3m9yZyhcntERAQA6/PcnI3t097qtaa6aIgn4KklIiIiIuLqxkRERNTMcfQgERERERE7CYmIiBqFGgerXtO14yhNIiIiIiJ2EhIRETUK7CNsOBxISERERETEnIQerX///vD39wdgnSPuwIEDWhwcHKzFMoeYzOFmEKMmZE42+f7Y2FirullaunSpFgcGBmqxzPk3YsQIuz9P5jDr3LmzFufl5WmxzJEmcwbKHHcyZ2D37t21WB5vRkaGFsscbC1atNBieX5ljj5ZH1nf1q1b290uc8rJ83HXXXdpca9evbQ4JydHi7dv367FMuekr6+vFsvrUeaAlPXv0qWLFmdlZWmxzKEnc+zJnJMyJ5/MqSlz8JnuI5P27fV8bwcPHtTiXbt22X2/zEEo6y+vH5mDT+aM3LNnj93tMidjhw4dtFjWX/68rl27arE8P+np6XZ/vmw/mWNR5oS88cYbtXjjxo1aLHN8HjlyBABQUVEBsmYwXO0g5EjChiOf2UREREREzRFHEhIREXkw01RY9hE2vCFxbdxdBSIiIiIit+FIQiIiIg9mNADVABTYS9iQDs+5y3EhIiIiIqImjJ2EREREHswAAwCFmhp316RpMzIxIRERERE1c+wk9GApKSlo2bIlAOucfl999ZUWyxyFt956qxbLnINnz57V4ri4OC2WOcVkDrqtW7dqcVVVlRYbjfpM9vHjx2vxyZMntfjYsWNa/O6772qxzEkocwrKfFIyZ+DRo0e1WOa0kzkWZQ7H4uJiLZY5FNu1a6fFMuegqR1NasRv+7J9Zf3k/mV79+jRQ4tlDkJZXp4PmdNStndpaakWy5yGMmehPD7ZPoMHD9bizZs3a7HMcTlkyBAtltfnt99+C3tkTj7ZfjLn4L59+7S4Y8eOWhwWFqbFsv3Wr1+vxaaceyYyZ+fly5e1WOb4GzRokBbL60vmCJT7z8/P1+KLFy9qcXx8vBbL60XmEJRkDkS5P3k9yPtd3q+kM90+HEdIREREREQNiTkJiYiIPJipk5ALlxARERERUUNiJyEREZEHM3IoIRERERERuQCnG3sg9d/RInJKoCU53VBO95PvldsrKirs7s/b29vudrm/yspKu/uX01Ud1e/KlSt29y/L17V+js6XnD4t3+/oeOX+5XRvuV2ebyVGDMn3y+OV9XFUvq7Xg6P2kdOJHZ0fOb1WbpfTU+X+HB2/5Oh8y/Z2dD5k/eX0ekfXn/z5Xl5edn+evD4dtY+8fmR5R+fPUftJjuorz5et68/0f1n/5s7USciRhERERERE1JDYSeiBTB1qw4cPd3NN6s8bb7zh7irYNXfuXHdXoVn54IMP6lRe5txbvHhxPdaGPE1paSlCQkLcXQ2PYeqCr2EfIRERERERNSB2EnqgqKgoHDt2DEFBQVYjtFzt+PHj6NmzJ/bs2YP27du7tS6NAc+X83iunNdczpVSCqWlpYiKinJ3VVzCNGKypKTEbrmYIAN2lVyGT3W5w7JE5GFKLzsuY4n3OHkCXrdERO5T12cw4NRz2PR7hKNZW+wk9EBGoxHR0dHurgaAny+koKAgqxVwyRrPl/N4rpzXnM5VcxpBaBo1Lldrt+WBtxuwMkRERERE1OQ5mrXFTkIiIiI38KRR401RSUkJYmJicOzYsSbfud5YsY08G9vH87GNPBvbx/OxjTwb26d+OTtri52EREREbuBJo8absuDgYH6x9HBsI8/G9vF8bCPPxvbxfGwjz8b2qT/OzNoyOixBzVqrVq0wZcoUtGrVyt1VaRSCg4MxdOhQPsScwHPlPN6HRERERERE1NA4kpDsatmyZZ1Xom3OgoODsW7dOndXo1HguXIe70MiIiIiIiJqaBxJ2IgVFBQgKSnJ3dUgIiLyOH5+fpg9ezb8/PzcXRWygW3k2dg+no9t5NnYPp6PbeTZ2D7uYVCO1j8mj1VQUID77rsP27dvd3dViIiIiIiIiIioEeNIwkauqqoKaWlp6NGjB8aPH4/67vMtKChA79698dBDD6Fnz554/PHH8eWXX2LgwIGIj49HXl5evf68a3Hx4kWMGDECiYmJSExMxKpVq9xdpTprCsfgKjxXzuO5IiIiIiIiImexk9CNNmzYgNGjRyMqKgoGgwFffvmlzbKvv/46DAYDZsyYob2+d+9ePP/889izZw9OnTqFH374QXvPgAEDEBQUhLZt22LcuHHYv3+/1X4dlTH9jNzcXKxbtw6bNm3C1q1bMX36dLz33ntO1/eDDz5Ar169zKsTJScn49tvv3XqXM2bNw+dOnWCv78/+vfvj40bN5q3rVq1Cm3atEFubi5ycnKQnJzs1D4dqe0YnDlftXn55ZdhMBi0/yIiIhr8GFylPs8V4J72dpXazlVdngWWmvp1RURERERERK7DTkI3unTpEnr37m2zo81k27Zt+Oijj9CrVy+rbd26dUP37t1hMBjQt29fFBQUmLetX78eU6dORUZGBtasWYMrV64gJSUFly5dqlOZbt26oVu3bvDy8kKPHj1w++23AwB69eql/TxH9Y2OjsbcuXOxfft2bN++HcOGDcPYsWOxe/duu8e/ePFizJgxAy+++CJ27NiBm2++GampqTh69CgAIDExERs3bsSzzz6LjIyMelkt19YxOHO+bImPj0dhYaH5v9zcXPO2hjgGV6nvc+WO9nYVW+fK2WdBbZrqdUVEREREREQupsgjAFDLli2zer20tFR16dJFrVmzRg0dOlQ99dRT5m35+fmqf//+5viZZ55Rf/vb32z+jNOnTysAav369U6XkT/j3nvvVWvXrlVKKbVlyxY1cuRIp+tbm9atW6tPPvnEbpkbb7xRTZkyRXute/fu6rnnnjPHZ8+eVQsWLFADBgxQ7777rt39OVKXY3DmnCql1OzZs1Xv3r3tlqnPY3CVhjhXrm5vV3H2XNl6FtSmqV5XREopNW/ePJWYmKiCgoJUUFCQGjRokFq5cqV5O4Ba//vTn/5kLjN06FCr7ePHj9d+zvnz59WkSZNUcHCwCg4OVpMmTVJFRUWuOswmZc6cOQqA9nyrqalRs2fPVpGRkcrf318NHTpU7dq1S3tfeXm5mjZtmmrTpo0KCAhQo0ePVseOHdPKsJ2un2yfyspK9eyzz6qEhAQVEBCgIiMj1eTJk9Xx48e19/E+cp3a7qG0tDSr8z9w4EDtfbyHXKO29uFnkXvNnj3b6ty2a9fOvJ2fQe5nr434OeSZOJLQw02dOhUjR440j967HhcuXAAAhIaGXlcZe5ytb3V1NRYtWoRLly7ZnQJZWVmJzMxMpKSkaK+npKRg8+bNAIATJ04gMDAQv/zlL/HUU08hOzv7mupe12MA6na+8vLyEBUVhU6dOuHBBx/E4cOHzdvq+xhcpb7PlTva21Xq81621BSvKyLA8ehzyxG0hYWFmD9/PgwGA+69915tP48++qhW7q9//au2fcKECcjOzkZ6ejrS09ORnZ2NyZMnu+w4mwpbI6X/9Kc/4a233sJ7772Hbdu2ISIiAnfccQdKS0vNZWbMmIFly5Zh0aJF+OGHH3Dx4kWMGjUK1dXV5jJsp+tTW/tcvnwZWVlZeOmll5CVlYWlS5fiwIEDGDNmjNX7eR81PHszh0aMGKGd/5UrV2rbeQ81PFvtw88i97M3q4afQZ7BVhvxc8hDubuXkq5CLaOHvvjiC5WQkKDKysqUUuq6RhLW1NSo0aNHq5tuuslmHWorU5eRhI7qq5RSOTk5KjAwUHl5eamQkBC1YsUKm/VRSqnjx48rAGrTpk3a66+99prq2rWrUkqp9PR0lZCQoHr37q0GDRqkdu/ebXef9jhzDCbOnFOTlStXqiVLlqicnBzzSLJ27dqps2fP1vsxuEpDnCtXt7er1OVc1fYssKUpXldE9tgbfT527Fg1bNgw7TVHI5z37NmjAKiMjAzza1u2bFEA1L59++qlzs2BrZHSNTU1KiIiQs2dO9dctry8XIWEhKgPP/xQKaVUcXGx8vHxUYsWLTKXOX78uDIajSo9PV0pxXa6XnUZ9f/jjz8qAOrIkSPm13gfNTx7bZSWlqbGjh1r8728hxpeXe4hfha5lr1ZNfwM8gzOzHyyxM8h9+NIQg917NgxPPXUU/jss8/g7+9fa5mOHTti+/bt5vjPf/4zHnrooVrLTps2DTk5Ofjiiy9s/szaysifsWTJEtx6660AgEGDBmH58uVO1xe4mt8wOzsbGRkZePzxx5GWloY9e/bYLG9iMBi0WCllfu3OO+9Ebm4usrOzsWXLFvTs2dPh/mrj7DGYOHNOTVJTU3HvvfciMTERt99+O1asWAEAWLBgQb0eg6s05LkCXNPerlLXc1UXTe26IrLF0ejzU6dOYcWKFfjVr35lte3zzz9HWFgY4uPjMWvWLG30wJYtWxASEoKBAweaXxs0aBBCQkLMo5fJMVsjpfPz83Hy5EltdLifnx+GDh1qPr+ZmZmoqqrSykRFRSEhIcFchu10feo66t9gMKBVq1ba67yPGpajNlq3bh3atm2Lrl274tFHH8Xp06fN23gPNTxn7yF+FrmHrVk1/AzyHPZmPkn8HHI/b3dXgGqXmZmJ06dPo3///ubXqqursWHDBrz33nuoqKiAl5eXU/uaPn06vv76a2zYsAHR0dHXXKY+6uvr64u4uDgAQFJSErZt24Z33nnHariwSVhYGLy8vHDy5Ent9dOnT6Ndu3Z1rmd9HANw/ecrMDAQiYmJyMvLq7f6u1JDnStXtrer1Oe97Ehjv66IpNzcXCQnJ6O8vBwtW7bEsmXLau3sXrBgAYKCgnDPPfdor0+cOBGdOnVCREQEdu3aheeffx47d+7EmjVrAAAnT55E27ZtrfbXtm1bq+cQ1W7RokXIysrCtm3brLaZzqF8frdr1w5Hjhwxl/H19UXr1q2typjez3a6dvbaRyovL8dzzz2HCRMmaAtd8T5qWI7aKDU1Fffffz9iY2ORn5+Pl156CcOGDUNmZib8/Px4DzWwutxD/CxyvYEDB+If//gHunbtilOnTuHVV1/F4MGDsXv3bn4GeQh7bdSmTRutLD+HPAM7CT3U8OHDtXwKAPDwww+je/fu+O1vf+tUp4JSCtOnT8eyZcuwbt06dOrU6ZrKNGR9lVKoqKiwuV9fX1/0798fa9aswd13321+fc2aNRg7duw11dUWZ46hvs5XRUUF9u7di5tvvrk+qu5yDXWuXNnerlIf97KzGvt1RSSZRp8XFxfj3//+N9LS0rB+/XqrjsL58+dj4sSJVqN1H330UfO/ExIS0KVLFyQlJSErKwv9+vUDYD1yGdBHL5NtppHSq1evtjtS2t7ocFtkGbZT3TnbPgBQVVWFBx98EDU1NZg3b562jfdRw3GmjcaPH2/+d0JCApKSkhAbG4sVK1ZYdUZZ4j10/epyDwH8LHKH1NRU878TExORnJyMG264AQsWLMCgQYMA8DPI3ey10cyZM83b+DnkOdhJ6EYXL17EwYMHzXF+fj6ys7MRGhqKDh06ICEhQSsfGBiINm3aWL1uy9SpU/HPf/4TX331FYKCgsy96CEhIWjRooXTZZwRFBTksL4vvPACUlNTERMTg9LSUixatAjr1q1Denq6+T3vvfceli1bhu+++8782syZMzF58mQkJSUhOTkZH330EY4ePYopU6Y4Xb/6OgZnzldtxzBr1iyMHj0aHTp0wOnTp/Hqq6+ipKQEaWlp9XoMrtKQ58pV7e0qzpwrR88CoHlcV0SSM6PPN27ciP3792Px4sUO99evXz/4+PggLy8P/fr1Q0REBE6dOmVV7syZM4129LIrORopvX//fgBX/8IfGRlpLmM5OjwiIgKVlZUoKirSRnKcPn0agwcPNpdhO9WdsyPZq6qq8MADDyA/Px/ff/+9NnqjNryP6s+1zDaIjIxEbGysedYA76GGU5f24WeRZ7CcVTNu3DgA/AzyNLXNfOLnkIdxcQ5EsrB27VqrpbwBqLS0tFrLO0rYKdW2bwDa4ibOlLlWsr6PPPKIio2NVb6+vio8PFwNHz5crV69WnvP7NmzVWxsrNW+3n//ffN7+/Xrp9avX3/d9XOGPAZnzldtxzB+/HgVGRmpfHx8VFRUlLrnnnua3CIS9XWulHJfe7uKPFfOPAua63VFZGnYsGFWn5FpaWnaAlv25ObmKgDmZ4op0fXWrVvNZTIyMpjo2kklJSUqNzdX+y8pKUlNmjRJ5ebmmpPGv/HGG+b3VFRU1Jo0fvHixeYyJ06cqDVpPNupbhy1j1JKVVZWqnHjxqn4+Hh1+vRpp/bL+6j+ONNG0tmzZ5Wfn59asGCBUor3UEOqS/vws8gzlJeXq/bt26tXXnmFn0EeyrKNlOLnkCdiJyERERF5nOeff15t2LBB5efnq5ycHPXCCy8oo9Go/XHpwoULKiAgQH3wwQdW7z948KB65ZVX1LZt21R+fr5asWKF6t69u+rbt6+6cuWKudyIESNUr1691JYtW9SWLVtUYmKiGjVqlEuOsSmSfwSZO3euCgkJUUuXLlW5ubnqF7/4hYqMjFQlJSXmMlOmTFHR0dHqP//5j8rKylLDhg1TvXv3Zjs1AMv2qaqqUmPGjFHR0dEqOztbFRYWmv+rqKhQSvE+cgfLNiotLVXPPPOM2rx5s8rPz1dr165VycnJqn379ryH3KS2QRv8LHKfZ555Rq1bt04dPnxYZWRkqFGjRqmgoCBVUFCglOJnkCew10b8HPJM7CQkIiIij+PM6PO//vWvqkWLFqq4uNjq/UePHlW33HKLCg0NVb6+vuqGG25QTz75pDp37pxW7ty5c2rixIkqKChIBQUFqYkTJ6qioqKGPLQmTf4CXVNTo2bPnq0iIiKUn5+fuuWWW6xG4JSVlalp06ap0NBQ1aJFCzVq1Ch19OhRrQzbqX5Ytk9+fr7NUf9r165VSvE+cgfLNrp8+bJKSUlR4eHhysfHR3Xo0EGlpaVZ3R+8h1yntk5Cfha5j6NZNfwMcj97bcTPIc9kUEqp65+0TERERERERERERI2V0d0VICIiIiIiIiIiIvdiJyEREREREREREVEzx05CombmoYcegsFggMFggLe3Nzp06IDHH38cRUVFWrmysjK0bt0aoaGhKCsrc1NtiYiIiIiIiMgV2ElI1AyNGDEChYWFKCgowCeffIJvvvkGTzzxhFbm3//+NxISEtCzZ08sXbrUTTUlIiIiIiIiIlfwdncFiMj1/Pz8EBERAQCIjo7G+PHj8fe//10r8+mnn2LSpElQSuHTTz/FxIkT3VBTIiIiIiIiInIFdhISNXOHDx9Geno6fHx8zK8dOnQIW7ZswdKlS6GUwowZM3D48GF07tzZjTUlIiIiIiIioobC6cZEzdDy5cvRsmVLtGjRAjfccAP27NmD3/72t+bt8+fPR2pqqjkn4YgRIzB//nw31piIiIiIiIiIGhI7CYmaodtuuw3Z2dnYunUrpk+fjjvvvBPTp08HAFRXV2PBggWYNGmSufykSZOwYMECVFdXu6vKRERERERERNSA2ElI1AwFBgYiLi4OvXr1wv/+7/+ioqICr7zyCgBg1apVOH78OMaPHw9vb294e3vjwQcfxE8//YTVq1e7ueZERERERERE1BAMSinl7koQkes89NBDKC4uxpdffml+bd26dUhNTcWhQ4cwffp0+Pr64sUXX9TeN3fuXJSXl2PJkiUurjERERERERERNTSOJCQi3HrrrYiPj8drr72Gb775BmlpaUhISND+S0tLw9dff40zZ864u7pEREREJCxfvhydO3fGgAEDcODAAXdXh4iIGiF2EhIRAGDmzJn46KOPUFVVheHDh1ttv+222xAUFISFCxe6oXZEREREZI/pu9ykSZPw+9//3t3VISKiRoidhETNzN///ndtqrHJhAkTUFVVBaUUfHx8rLZ7e3vj3LlzmDlzpgtqSURERNS0/e53v4Ofnx8mTJjg9HvOnTuHtm3boqCgwGpbWFgY4uLi0LlzZ4SEhGjb7rvvPrz11lvXW2UiImrimJOQiIiIiIjIxUpKSrBw4UJMmzYNeXl5iIuLc/ieWbNmoaioCJ9++qnVto8//hhTpkxBeHg4du/ejTZt2pi35eTk4LbbbkN+fj6Cg4Pr9TiIiKjp4EhCIiIiIiIiFwsODsYjjzwCo9GI3Nxch+XLysrw6aef4te//rXVtitXruCdd97Bs88+i9LSUrRu3Vrb3qtXL3Ts2BGff/55vdWfiIiaHnYSEhERERERucGVK1cQEBCAXbt2OSz77bffwtvbG8nJyVbbPvzwQ3Tu3BlTp07F5cuXkZeXZ1VmzJgx+OKLL+ql3kRE1DSxk5CIiIiIiMgNfve73+HixYtOdRJu2LABSUlJVq8XFRXhj3/8I9544w1ER0cjJCQE2dnZVuVuvPFG/Pjjj6ioqKiPqhMRURPETkIiIiIiIiIXy8zMxIcffoiRI0c61UlYUFCAqKgoq9d///vf4+6770aPHj0AAD179sTOnTutyrVv3x4VFRU4efLk9VeeiIiaJG93V4CIiIiIiKg5qampwf/8z/9g2rRpGDhwICZOnIjKykr4+vrafE9ZWRn8/f211/bs2YPPPvsMe/fuNb+WkJBQ60jCFi1aAAAuX75cPwdBRERNDjsJiYiIiIiIXOjdd9/FmTNn8Ic//AFHjx7FlStXsH//fiQmJtp8T1hYGIqKirTXnn76aRQXFyM6Otr8Wk1NDSIjI63ef/78eQBAeHh4PR0FERE1NewkJCIiIiIicpHjx4/jpZdewhdffIHAwEB06dIFfn5+2LVrl91Owr59++Kzzz4zx8uXL0dmZiZ27NgBb++ff63btm0bHnnkEZw5c0brENy1axeio6MRFhbWMAdGRESNHjsJiYiIiIiIXOTJJ59EamoqRo4cCQDw9vZGjx49HOYlvPPOO/H888+jqKgILVu2xDPPPIPf/OY36NOnj1YuODgYALBz507cfvvt5tc3btyIlJSU+j0YIiJqUthJSERERERE5ALLly/H999/r+UQBIDExESHnYSJiYlISkrCv/71L1y6dAnFxcWYNm2aVbmYmBgEBAQgOzvb3ElYXl6OZcuWYdWqVfV3MERE1OQYlFLK3ZUgIiIiIiIi+1auXIlZs2Zh165dMBqNTr/v/fffx1dffYXVq1c3YO2IiKix40hCIiIiIiKiRuCuu+5CXl4ejh8/jpiYGKff5+Pjg3fffbcBa0ZERE0BRxISERERERERERE1c86PUSciIiIiIiIiIqImiZ2EREREREREREREzRw7CYmIiIiIiIiIiJo5dhISERERERERERE1c+wkJCIiIiIiIiIiaubYSUhERERERERERNTMsZOQiIiIiIiIiIiomWMnIRERERERERERUTPHTkIiIiIiIiIiIqJmjp2EREREREREREREzdz/A1gTiDpTNFUmAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 1300x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(13,4))\n",
    "gs = gridspec.GridSpec(1, 2, width_ratios=[1.2,3])\n",
    "\n",
    "ax1 = plt.subplot(gs[0], projection=wcs_ls)\n",
    "ax1.set_aspect('auto')\n",
    "im_zscale = ZScaleInterval(contrast=0.5, krej=1.1)\n",
    "im_vmin, im_vmax = im_zscale.get_limits(values=hdu_ls[0].data[2])\n",
    "plt.imshow(hdu_ls[0].data[2], origin='lower', cmap=plt.get_cmap('gray_r'), vmin=im_vmin, vmax=im_vmax  )\n",
    "\n",
    "sel_line = (grp[\"det_type\"] == \"line\")\n",
    "if np.sum(sel_line) >= 1:\n",
    "    plt.scatter(\n",
    "        grp[\"RA_det\"][sel_line],\n",
    "        grp[\"DEC_det\"][sel_line],\n",
    "        transform=ax1.get_transform(\"world\"),\n",
    "        marker=\"x\",\n",
    "        color=\"orange\",\n",
    "        linewidth=2,\n",
    "        s=50,\n",
    "#        zorder=100,\n",
    "        label=\"line emission\",\n",
    "    )\n",
    "\n",
    "sel_cont = grp[\"det_type\"] == \"cont\"\n",
    "if np.sum(sel_cont) >= 1:\n",
    "    plt.scatter(\n",
    "        grp[\"RA_det\"][sel_cont],\n",
    "        grp[\"DEC_det\"][sel_cont],\n",
    "        transform=ax1.get_transform(\"world\"),\n",
    "        marker=\"x\",\n",
    "        color=\"green\",\n",
    "        linewidth=2,\n",
    "        s=50,\n",
    "        label=\"continuum\",\n",
    "    )\n",
    "lon = ax1.coords[0]\n",
    "lat = ax1.coords[1]\n",
    "lon.set_axislabel('RA', minpad=0.5)\n",
    "#lat.set_axislabel('Dec', minpad=-0.6)\n",
    "lat.set_axislabel('Dec', minpad=0.3)\n",
    "lon.set_ticklabel(exclude_overlapping=True)\n",
    "    \n",
    "ax2 = plt.subplot(gs[1])\n",
    "\n",
    "plt.plot(wave_rect, spectra, linewidth=1.2, color='tab:blue')#, yerr=spec_table['spec1d_err'])\n",
    "plt.xlabel(r'$\\lambda$ ($\\AA$)')\n",
    "plt.ylabel(r'f$_\\lambda$ (10$^{-17}$ ergs/s/cm$^2$/$\\AA$)')\n",
    "plt.xlim(3540, 5450)\n",
    "\n",
    "selw = (wave_rect > 3540) & (wave_rect < 5450)\n",
    "y2 = np.max(spectra[selw])\n",
    "y1 = np.min(spectra[selw])\n",
    "\n",
    "if y1 > 0:\n",
    "    y1 = 0\n",
    "\n",
    "# plot all emission lines detected in det_table related to the source_id\n",
    "\n",
    "for line in np.array( np.unique(grp['line_id'])):\n",
    "    \n",
    "    if line == 'n/a':\n",
    "        continue\n",
    "    \n",
    "    sel_line = grp['line_id'] == line   \n",
    "\n",
    "    plt.bar(grp['wave'][sel_line][0], height=2*y2, width=30, bottom=y1, color='orange', alpha=0.3)\n",
    "    \n",
    "    label = '{}  [{}]'.format( grp['detectid'][sel_line][0], line)\n",
    "    if np.isfinite( grp['wave'][sel_line][0]):\n",
    "        plt.text(grp['wave'][sel_line][0]-70, 0.1*y2, label, rotation=90, fontsize=10)\n",
    "\n",
    "plt.axhline(0, color='tab:grey', linestyle='dashed')\n",
    "plt.text(0.05, 0.7, 'z={:6.4f}'.format(redshift), transform=ax2.transAxes, color='tab:red', fontsize=20)\n",
    "plt.text(0.05, 0.85, 'source_id={}'.format(sid), transform=ax2.transAxes, fontsize=14, color='black')\n",
    "plt.ylim(y1,1.1*y2)\n",
    "plt.subplots_adjust(wspace=0.3, hspace=0)\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "355b2966-97e5-4e62-8682-54688776a078",
   "metadata": {},
   "source": [
    "## ELiXer Reports"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "01083023-8251-421d-9aee-137ae1d985b8",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true
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   "source": [
    "An important diagnostic for HETDEX detections is provided by the **ELiXer reports**, which are generated for every curated detection in the HETDEX catalog. A full description of these reports is given in the Appendix of Davis et al. (2023).\n",
    "\n",
    "ELiXer reports summarize ancillary imaging and spectroscopic information at the location of each detection. They include:\n",
    "- Imaging cutouts from available surveys\n",
    "- Cutouts of the amplifier array showing the highest-weight fibers used in the PSF extraction\n",
    "- The full HETDEX PSF-extracted spectrum with associated error\n",
    "- A zoomed view of the spectral region around the detected line\n",
    "\n",
    "These reports are used for visual validation of HETDEX detections.\n",
    "\n",
    "This release includes **ELiXer reports for all detections** in the full supplemental HETDEX detection catalog (Appendix: Detection Info Table), including every detection in the main HPSC2 catalog."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "8c64180a-0b18-4d76-baee-13c27d12ebc6",
   "metadata": {},
   "outputs": [],
   "source": [
    "from IPython.display import Image, display"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "860c1bcf-6705-4037-b882-7f628700b1c9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<img src=\"https://web.corral.tacc.utexas.edu/hetdex/HETDEX/pdr/pdr1/detect/elixer/30900/3090018437.jpg\" width=\"900\"/>"
      ],
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
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    {
     "data": {
      "text/html": [
       "<img src=\"https://web.corral.tacc.utexas.edu/hetdex/HETDEX/pdr/pdr1/detect/elixer/30008/3000842112.jpg\" width=\"900\"/>"
      ],
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img src=\"https://web.corral.tacc.utexas.edu/hetdex/HETDEX/pdr/pdr1/detect/elixer/30008/3000842114.jpg\" width=\"900\"/>"
      ],
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img src=\"https://web.corral.tacc.utexas.edu/hetdex/HETDEX/pdr/pdr1/detect/elixer/30008/3000842116.jpg\" width=\"900\"/>"
      ],
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img src=\"https://web.corral.tacc.utexas.edu/hetdex/HETDEX/pdr/pdr1/detect/elixer/30008/3000842113.jpg\" width=\"900\"/>"
      ],
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img src=\"https://web.corral.tacc.utexas.edu/hetdex/HETDEX/pdr/pdr1/detect/elixer/30008/3000842117.jpg\" width=\"900\"/>"
      ],
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img src=\"https://web.corral.tacc.utexas.edu/hetdex/HETDEX/pdr/pdr1/detect/elixer/30008/3000842118.jpg\" width=\"900\"/>"
      ],
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot up all detectids from previous example\n",
    "\n",
    "detectids = grp['detectid'] \n",
    "\n",
    "for det in detectids:\n",
    "    prefix = str(det)[:5]\n",
    "\n",
    "    url = f\"https://web.corral.tacc.utexas.edu/hetdex/HETDEX/pdr/pdr1/detect/elixer/{prefix}/{det}.jpg\"\n",
    "\n",
    "    display(Image(url=url, width=900))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bb186659-44a8-4700-8aa1-afaddad4bbe0",
   "metadata": {},
   "source": [
    "## References"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8e81da36-0f07-474a-b941-de30c9a27c50",
   "metadata": {},
   "source": [
    "* Davis, D., Gebhardt, K., Mentuch Cooper, E., et al. 2023, ApJ, 946, 86, doi: 10.3847/1538-4357/acb0ca\n",
    "* Dey, A., Schlegel, D.J., Lang, D., et al. 2019, ApJ, 157, 168. doi:10.3847/1538-3881/ab089d LEGACY SURVEY: we use the LS API to obtain a sky cutout at the HETDEX source\n",
    "https://www.legacysurvey.org. \n",
    "* Gebhardt, K., Mentuch Cooper, E., Ciardullo, R., et al. 2021, ApJ, 923, 217. doi:10.3847/1538-4357/ac2e03\n",
    "* Mentuch Cooper, E., Gebhardt, K., Davis, D. et al. 2023, ApJ,  943, 177 doi: 10.3847/1538-4357/aca962 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7cee9020-1977-4f27-9f68-9cc6f00bbac3",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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