Gaia_BH3_fit_astrometric_orbit.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "d12f490b-fc1b-4da5-9fdf-cd33ba895e28",
   "metadata": {},
   "source": [
    "Copyright (c) European Space Agency, 2024.  \n",
    "This file is subject to the terms and conditions defined in file 'LICENCE.txt',   \n",
    "which is part of this source code package. No part of the package, including  \n",
    "this file, may be copied, modified, propagated, or distributed except according to   \n",
    "the terms contained in the file ‘LICENCE.txt’."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "46ec3ea5-6a44-4c7e-949b-9daa17f90cc3",
   "metadata": {},
   "source": [
    "# Analysis of Gaia measurement timeseries that led to the discovery of the black hole `Gaia BH3`\n",
    "## This notebook was prepared by the Gaia collaboration. If you find it useful for your research or otherwise, please reference the discovery paper (Gaia Collaboration, Panuzzo, et. al. 2024 \"Discovery of a dormant 33 solar-mass black hole in pre-release Gaia astrometry\") and the DOI associated with this notebook repository."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2aed9c24-a649-4985-b888-9847f9c1f3e4",
   "metadata": {},
   "source": [
    "## Content of this notebook  \n",
    "This notebook demonstrates the following steps:\n",
    "- Load the timeseries data of the Gaia astrometric instrument. The data are identical to the ones published with the paper and available at the CDS.\n",
    "- Fit an orbit to the astrometric data and determine the black hole's mass.\n",
    "- Load the timeseries data of the Gaia radial-velocity instrument. The data are identical to the ones published with the paper and available at the CDS.\n",
    "- Fit an orbit to the combination of astrometric and radial-velocity data and determine the black hole's mass.\n",
    "\n",
    "## Environment installation\n",
    "- This notebook is most easily executed within the associated `Binder` environment in a web browser, where no software installation is needed.\n",
    "- For local execution, one can use the environment.yml file included in this repository to create a python environment using conda with the necessary dependencies for code execution:  \n",
    "`conda env create --file gaia-bhthree/environment.yml`"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "92f7ca12-1bb9-4853-a7bb-6c73e6b6c659",
   "metadata": {},
   "source": [
    "### Imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "61537d3c-5aec-48d8-b6dd-a27e681d0d68",
   "metadata": {},
   "outputs": [],
   "source": [
    "from collections import OrderedDict\n",
    "import copy\n",
    "import os\n",
    "\n",
    "from astropy.time import Time\n",
    "import astropy.units as u\n",
    "from IPython.display import display, Markdown\n",
    "import matplotlib.pyplot as pl\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "from kepmodel.astro import AstroModel as AstrometricModel\n",
    "from kepmodel.rv import RvModel\n",
    "from kepmodel.astrorv import AstroRvModel\n",
    "from pystrometry.pystrometry import convert_from_angular_to_linear, pjGet_m2, OrbitSystem, MS_kg, MJ_kg, convert_from_linear_to_angular\n",
    "from pystrometry import gaia_astrometry as gaia_astrometry_plotter\n",
    "import spleaf"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7e0cd8bf-354d-44f3-b188-220a7926ca6a",
   "metadata": {},
   "source": [
    "### Folder and constants definition"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "f9d48ab9-6cc5-4fe7-9b2a-e82748d59c63",
   "metadata": {},
   "outputs": [],
   "source": [
    "base_dir = os.getcwd()\n",
    "data_dir = os.path.join(base_dir)\n",
    "plot_dir = os.path.join(base_dir)\n",
    "\n",
    "DR4_REFERENCE_EPOCH = Time('2017.5', format='jyear', scale='tcb')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d47a7cf3-5c5c-42ef-a804-2b65a793590f",
   "metadata": {},
   "source": [
    "### Source parameters from paper"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "fb4372f7-f71e-4ab6-bdf2-f4901ba543c9",
   "metadata": {},
   "outputs": [],
   "source": [
    "source_id = 4318465066420528000\n",
    "m1_MS = 0.76  # Primary star mass from paper Table 3\n",
    "bh3_ra_deg = 294.8278502411 # Right Ascension from paper Table 2\n",
    "bh3_dec_deg = 14.9309190720 # Declination from paper Table 2"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "587a09d8-f9b8-4f82-886f-701bf188bc05",
   "metadata": {},
   "source": [
    "## Load astrometric-timeseries data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "aef5ccab-1345-44a5-9972-8d4e315b1b5c",
   "metadata": {},
   "outputs": [],
   "source": [
    "columns = 'transit_id ccd_id obs_time_tcb centroid_pos_al centroid_pos_error_al parallax_factor_al scan_pos_angle outlier_flag'.split()\n",
    "gaia_astrometry = pd.read_csv('epochast.dat', names=columns, delim_whitespace=True, comment='#')\n",
    "\n",
    "# filter our unused data\n",
    "gaia_astrometry = gaia_astrometry[gaia_astrometry['outlier_flag']!=1]\n",
    "\n",
    "# set auxiliary fields\n",
    "gaia_astrometry['source_id']  = source_id\n",
    "gaia_astrometry['transitid'] = gaia_astrometry['transit_id']\n",
    "gaia_astrometry['relative_time_year'] = Time(gaia_astrometry['obs_time_tcb'], format='jd', scale='tcb').jyear - DR4_REFERENCE_EPOCH.jyear\n",
    "gaia_astrometry['mjd'] = Time(gaia_astrometry['obs_time_tcb'], format='jd', scale='tcb').mjd\n",
    "gaia_astrometry['relative_time_day'] = gaia_astrometry['relative_time_year'] * u.year.to(u.day)\n",
    "gaia_astrometry['cpsi_obs'] = np.cos(np.deg2rad(gaia_astrometry['scan_pos_angle']))\n",
    "gaia_astrometry['spsi_obs'] = np.sin(np.deg2rad(gaia_astrometry['scan_pos_angle']))\n",
    "gaia_astrometry['ppfact_obs'] = gaia_astrometry['parallax_factor_al']\n",
    "gaia_astrometry['da_mas'] = gaia_astrometry['centroid_pos_al']\n",
    "gaia_astrometry['sigma_da_mas'] = gaia_astrometry['centroid_pos_error_al']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7654eebd-9062-49dd-9b16-40954ce60ac0",
   "metadata": {},
   "source": [
    "### Display a few data records"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "1985b70e-780c-4c5d-a92e-e260f5d027b0",
   "metadata": {},
   "outputs": [
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       "      <th>relative_time_year</th>\n",
       "      <th>centroid_pos_al</th>\n",
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      "text/plain": [
       "               source_id          transit_id  ccd_id  relative_time_year  \\\n",
       "17   4318465066420528000   22150086612000799       1           -2.578958   \n",
       "236  4318465066420528000   52687653750370648       1           -1.066927   \n",
       "281  4318465066420528000   60072325242450363       1           -0.701310   \n",
       "317  4318465066420528000   69681710950008689       1           -0.225529   \n",
       "325  4318465066420528000   69685803249345627       1           -0.225327   \n",
       "423  4318465066420528000   91999756014371726       1            0.879512   \n",
       "440  4318465066420528000   97549895534830543       1            1.154323   \n",
       "502  4318465066420528000  100312802889225719       1            1.291104   \n",
       "569  4318465066420528000  112761770976220367       1            1.907498   \n",
       "587  4318465066420528000  120150603084362450       1            2.273328   \n",
       "\n",
       "     centroid_pos_al  centroid_pos_error_al  parallax_factor_al  \\\n",
       "17           379.996                  0.446           -0.466571   \n",
       "236           -7.920                  0.268            0.394007   \n",
       "281           93.716                  0.207           -0.714470   \n",
       "317            0.132                  0.141            0.701433   \n",
       "325            0.116                  0.156            0.702254   \n",
       "423          128.743                  0.174           -0.602385   \n",
       "440         -170.556                  0.189            0.232098   \n",
       "502          -77.868                  0.205            0.703518   \n",
       "569          278.254                  0.153           -0.504061   \n",
       "587         -311.529                  0.213           -0.695162   \n",
       "\n",
       "     scan_pos_angle  \n",
       "17        -5.114377  \n",
       "236      107.029731  \n",
       "281       35.396723  \n",
       "317      128.854659  \n",
       "325      128.754022  \n",
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   "source": [
    "columns_to_show = 'source_id transit_id ccd_id relative_time_year centroid_pos_al centroid_pos_error_al parallax_factor_al scan_pos_angle'.split()\n",
    "display(gaia_astrometry.query('ccd_id == 1')[columns_to_show].sample(10, random_state=1).sort_values('relative_time_year'))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a1140fda-08e6-453e-b5f8-f0f1ef2cad3a",
   "metadata": {},
   "source": [
    "## Fit the standard astrometric model \n",
    "The standard astrometric model for the motion $w_\\mathrm{ss}$ of a single star can be written as\n",
    "\\begin{equation}\n",
    "w_\\mathrm{ss} = ( \\Delta\\alpha^{\\star} + \\mu_{\\alpha^\\star} \\, t ) \\, \\sin \\psi + ( \\Delta\\delta + \\mu_\\delta \\, t ) \\, \\cos \\psi + \\varpi \\, f_\\varpi, \n",
    "\\end{equation}\n",
    "where $\\Delta\\alpha^{\\star} = \\Delta\\alpha \\cos{\\delta}$ and $\\Delta \\delta$ are small offsets in equatorial coordinates from a fixed reference point ($\\alpha_0$, $\\delta_0$), $\\mu_{\\alpha^\\star}$ and $\\mu_\\delta$ are proper motions in these coordinates, $t$ is time since the Gaia DR4 reference time J2017.5, $\\varpi$ is the parallax, $f_\\varpi$ is the parallax factor, and $\\psi$ is the instantaneous Gaia scan angle. For more details see Section 3 of https://www.aanda.org/articles/aa/full_html/2023/06/aa44161-22/aa44161-22.html and https://www.aanda.org/articles/aa/full_html/2023/06/aa43969-22/aa43969-22.html\n",
    "\n",
    "We use the open-source python package [kepmodel](https://obswww.unige.ch/~delisle/kepmodel/doc/) (Delisle & Ségransan, 2022, A&A, 667, A172), which allows us to model radial velocity and/or astrometric time series including Keplerian orbits."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "9ad10b6e-573f-4d84-aeaf-f99f9fa9f30d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Best-fit single-star model parameters: (the units are mas and mas/year)\n",
      "Parameter                        Value     Error       \n",
      "lin.ra                         1.50624  ±  0.00708     \n",
      "lin.dec                       -0.03341  ±  0.00674     \n",
      "lin.parallax                   0.71520  ±  0.00871     \n",
      "lin.mura                     -30.29679  ±  0.00477     \n",
      "lin.mudec                   -148.62246  ±  0.00427     \n",
      "\n"
     ]
    }
   ],
   "source": [
    "include_jitter_term = False\n",
    "\n",
    "if include_jitter_term:\n",
    "    astrometric_jitter_value = 0.05\n",
    "else:\n",
    "    astrometric_jitter_value = 0.0\n",
    "    \n",
    "# set up the single-star model with an additional jitter term of 0.05 mas\n",
    "single_star_model = AstrometricModel(gaia_astrometry['relative_time_day'].values, \n",
    "                                     gaia_astrometry['centroid_pos_al'].values, \n",
    "                                     gaia_astrometry['cpsi_obs'].values, \n",
    "                                     gaia_astrometry['spsi_obs'].values, \n",
    "                                     err=spleaf.term.Error(gaia_astrometry['centroid_pos_error_al'].values),\n",
    "                                     jit=spleaf.term.Jitter(astrometric_jitter_value))\n",
    "    \n",
    "# define the linear parameters\n",
    "single_star_model.add_lin(gaia_astrometry['spsi_obs'].values, 'ra')\n",
    "single_star_model.add_lin(gaia_astrometry['cpsi_obs'].values, 'dec')\n",
    "single_star_model.add_lin(gaia_astrometry['parallax_factor_al'].values, 'parallax')\n",
    "single_star_model.add_lin(gaia_astrometry['relative_time_year'].values * gaia_astrometry['spsi_obs'].values, 'mura')\n",
    "single_star_model.add_lin(gaia_astrometry['relative_time_year'].values * gaia_astrometry['cpsi_obs'].values, 'mudec')\n",
    "\n",
    "# add jitter term\n",
    "if include_jitter_term:\n",
    "    single_star_model.fit_param += ['cov.jit.sig']\n",
    "\n",
    "# perform the fit\n",
    "single_star_model.fit()\n",
    "\n",
    "print(\"Best-fit single-star model parameters: (the units are mas and mas/year)\")\n",
    "single_star_model.show_param()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e4e33cc3-995d-4c82-8092-4a22d61be016",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Fit the Keplerian astrometric model \n",
    "\n",
    "Using [kepmodel](https://obswww.unige.ch/~delisle/kepmodel/doc/), we first compute the periodogram of the residuals of the standard-model fit. With the estimated period we initialise a Keplerian model and fit it to the data.\n",
    "\n",
    "The astrometric motion corresponding to a Keplerian orbit of a binary system has generally seven independent parameters. These\n",
    "are the period $P$, the epoch of periastron passage $T_0$, the eccentricity $e$, the inclination $i$, the ascending node $\\Omega$, the argument of periastron $\\omega$, and the semi-major axis of the photocentre $a_0$. The Thiele-Innes coefficients $A, B, F, G$, which linearise part of the equations, are defined as\n",
    "\\begin{eqnarray}\n",
    "%\\begin{split}\n",
    "% \\begin{array}{ll}\n",
    "A &=&  \\ \\ \\, a_0 \\; (\\cos \\omega \\cos \\Omega - \\sin \\omega \\sin \\Omega \\cos i)   \\\\\n",
    "B &=&  \\ \\ \\, a_0 \\; (\\cos \\omega \\sin \\Omega + \\sin \\omega \\cos \\Omega \\cos i)  \\\\\n",
    "F &=& -a_0 \\; (\\sin \\omega \\cos \\Omega + \\cos \\omega \\sin \\Omega \\cos i)  \\\\\n",
    "G &=&  -a_0 \\; (\\sin \\omega \\sin \\Omega - \\cos \\omega \\cos \\Omega \\cos i) \n",
    "% \\end{array}\n",
    "%\\end{split}\n",
    "\\end{eqnarray}\n",
    "\n",
    "The elliptical rectangular coordinates $X$ and $Y$ are functions of eccentric anomaly $E$ and eccentricity: \n",
    "\\begin{eqnarray}\n",
    "E - e \\sin E &=& \\frac{2\\pi}{P} (t-T_0)\\\\\n",
    "X &=& \\cos E - e\\\\\n",
    "Y &=& \\sqrt{1-e^2} \\sin E\n",
    "\\end{eqnarray}\n",
    "\n",
    "The single Keplerian model $w_\\mathrm{k1}$ can then be written as \n",
    "\\begin{equation}\n",
    "w_\\mathrm{k1} = (B \\, X + G \\, Y) \\sin \\psi + (A \\, X + F \\, Y) \\cos \\psi.\n",
    "\\end{equation}\n",
    "\n",
    "The combined model $w^\\mathrm{(model)}$ for the Gaia along-scan abscissa is\n",
    "\\begin{equation}\n",
    "\\begin{split}\n",
    "w^\\mathrm{(model)} =&\\, w_\\mathrm{ss} + w_\\mathrm{k1} \\\\\n",
    " =&\\, ( \\Delta\\alpha^{\\star} + \\mu_{\\alpha^\\star} \\, t ) \\, \\sin \\psi + ( \\Delta\\delta + \\mu_\\delta \\, t ) \\, \\cos \\psi + \\varpi \\, f_\\varpi \\\\\n",
    " &+\\, (B \\, X + G \\, Y) \\sin \\psi + (A \\, X + F \\, Y) \\cos \\psi.\n",
    "\\end{split}\\end{equation}\n",
    "\n",
    "\n",
    "More details are given in Section 3 of https://www.aanda.org/articles/aa/full_html/2023/06/aa44161-22/aa44161-22.html and in https://www.aanda.org/articles/aa/full_html/2023/06/aa43969-22/aa43969-22.html"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "56d185dc-8e1d-4e30-8809-7c8b62c854c5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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piI6Oxu3btxEVFYUbN27gwoULCAsLw71796Tje3l5oVGjRmjRogXatGmDli1bohBnMyQncnQ2YNgiIiIiIsTGxmLgwIH4559/oNFo8M4772Ds2LFo2LAhNBrN8yeqnPr98ePHCA0NxfHjx3Hs2DGcOHECCQkJAAB3d3c0bdoUbdu2Rbt27dC0aVN4eno66hKJDDBs2RnDFhEREZGuw4cP47333sO9e/fQs2dPTJo0CdWqVVN+so3rbGVlZeH8+fPYv38/9u3bh4MHDyIpKQkA4O3tjZYtW0qVtJCQELi6utpyaUQmMWzZGcMWERER0XOzZs3C559/Dk9PT8ydOxf9+vUzvYOdFzXOyMjA6dOnsW/fPuzbtw9Hjx5Feno6AMDPzw8vv/wy2rVrh3bt2qFmzZq6VTYiGzFs2RnDFhEREVG2uXPn4qOPPkKtWrWwfv161KxZ0/xOdg5b+tLS0nDs2DHs3bsXe/fuxalTp6DVagEApUqVkroctmvXDuXLl7fruangYdiyM4YtIiIiImDNmjXo3bs3qlWrhsOHD6NEiRKW7ejgsKUvPj4eBw8elMLXpUuXpMeqVq2Kdu3aoX379mjTpg0CAwMd2hbKfxi27Ixhi4iIiAq6f//9F926dUPJkiVx5MgRVKhQwfKdczhs6Xv48CH27dsnha/IyEgAgEajQb169dC2bVu0aNECLVq0QFBQUI62jfIehi07Y9giIiKiguzu3buoXbs23N3dcfjwYcu6Dso5OWzpu3nzphS89u3bh0ePHkmPVa1aFS1btpTCV40aNTjmi3QwbNkZwxYREREVVIIgoHPnzti5cye2bduGLl26qD9ILgtbclqtFlevXsWRI0dw9OhRHDlyBDdu3JAeDwwMRPPmzdGiRQu0bNkSDRs2hLe3txNbTM7GsGVnDFtERERUUC1ZsgQffPAB+vfvj2XLlll3kFwctpQ8ePAAR48elb7OnDmDzMxMAICrqytq1aqFhg0bIiQkBA0bNkS9evVQWLw+yvcYtuyMYYuIiIgKoqioKNSpUwe+vr64ePEi/P39rTtQHgtb+lJSUvDff//hyJEjCA0NxZkzZxAVFSU9rtFoUL16dSl8NWzYEA0aNICfn58TW02OwrBlZwxbREREVBC99tpr2LZtG7Zv347OnTtbf6A8HraUPHr0CGfPnsWZM2ekL3n3QyB7/FfdunVRu3Zt6Ss4OBgeHh5OajXZA8OWnTFsERERUUFz7NgxtGjRAj179sSaNWtsO1g+DFtKnjx5grCwMCl8hYaG4tq1a9KaXwDg5uaGatWqoXbt2qhevTqCg4MRHByM6tWro2jRok5sPVmKYcvOGLaIiIiooOnQoQP27duHy5cvo3r16rYdrICELSVpaWm4evUqLl26pPN148YN6N9SFytWDMHBwahWrRqqVKmCSpUqoVKlSqhcuTJKlizJWRFzCUdnAze7H5GIiIiIco0jR45gz549eP/9920PWgWcl5cX6tWrh3r16ulsT0tLw40bNxAREYGIiAhcvXpV+v7YsWOKxxHDV8WKFVG2bFmUK1dO+ipTpgw8PT1z6rLIgVjZIiIiIsrH2rVrhwMHDiA8PBzBwcG2H7AAV7as8fTpU9y6dQu3bt3CzZs3df4bGRmJ9PR0xf2CgoJQtmxZlC1bFqVKlUKpUqVQsmRJnf8GBQXB3d09h68of2Fli4iIiIiscujQIezbtw99+/a1T9Ai1fz9/dGgQQM0aNDA4DGtVouYmBjcuXPH4Ovu3bu4c+cOwsLCkJWVZfT4xYoVQ1BQEIoXL47ixYujWLFiOv+Vfx8QEAAvLy9HXi7pYWWLiIiIKJ/q0qULdu3ahStXrqBq1ar2OSgrWzlKq9UiNjYW0dHRePDgAaKjow2+j4mJQWxsLOLi4swez8vLC0WLFjX48vf31/nZ19dX+ipSpIj030KFCsHFxSUHrjxnsLJFRERERKrduXMHO3bswOuvv26/oEU5zsXFBSVKlECJEiUMxorpy8zMxOPHjxEbG4tHjx4Z/DcuLg5PnjyRvm7cuIEnT54Y7cqoRKPRoHDhwjpBTAxh4pePj4/Of5W2+fj4wMfHB15eXjpfnp6e+WryEIYtIiIionxo6dKlEAQBH3zwgbObQjnEzc0NQUFBCAoKUrVfamqqTgh78uQJEhMTkZCQIP3X2Pf3799HYmIikpOTkZmZaZfr8PT0NAhhSl8eHh7w8PCAu7u71d/bq83GsBshERERUT6TlZWFypUrIysrC5GRkXBzs+Pn6+xGSEZkZGQgOTkZycnJSElJUfyv/rb09HSkpaUpfpl6LDU11a5Bid0IiYiIiMgie/bsQVRUFL766iv7Bi0iE9zd3eHv7w9/f/8cOZ9Wq0VmZiaePXsmfWVkZCh+b+yx+Ph4fPzxxw5rI999RERERPnM4sWLAQADBw50ckuIHMfFxUXqDmithIQEh4at/DOVCBEREREhJiYGmzdvRvv27VGpUiVnN4eoQGPYIiIiIspHVq9ejYyMDAwaNMjZTSEq8Bi2iIiIiPKRDRs2wMfHB6+//rqzm0JU4DFsEREREeUTMTExOHr0KF555RV4e3s7uzlEBR7DFhEREVE+sXXrVmi1WrzxxhvObgoRIReErblz56JSpUrw8vJCSEgIDh8+bPL5f/zxB+rVqwcfHx+UKlUKAwYMwOPHj3OotURERES516ZNm+Dq6opXX33V2U0hIjg5bK1btw4jR47EhAkTcPbsWbRq1QqdO3dGVFSU4vOPHDmCvn37YtCgQbh06RL++usvnDp1iiujExERUYGXlJSEXbt24aWXXkJAQICzm0NEcHLYmjlzJgYNGoQPPvgANWvWxOzZs1GuXDnMmzdP8fknTpxAxYoVMWLECFSqVAktW7bEkCFDcPr06RxuOREREVHusmvXLqSnp6N79+7ObgoR/T9VYSszMxMrVqzAgwcPbD7xs2fPEBoaio4dO+ps79ixI44dO6a4T/PmzXH37l1s374dgiDg4cOHWL9+vclSeXp6OhISEnS+iIiIiPKbTZs2AQBnISTKRVSFLTc3NwwbNgzp6ek2nzg2NhZZWVkICgrS2R4UFGQ0zDVv3hx//PEHevToAQ8PD5QsWRL+/v6YM2eO0fNMmTIFfn5+0le5cuVsbjsRERFRbpKRkYGtW7ciJCSE9zpEuYjqboRNmzZFWFiY3Rqg0Wh0fhYEwWCb6PLlyxgxYgS+/vprhIaGYseOHbh16xaGDh1q9Pjjx49HfHy89HXnzh27tZ2IiIgoNzh+/DiePHmCbt26ObspRCTjpnaH4cOHY/To0bhz5w5CQkJQqFAhncfr1q1r0XGKFSsGV1dXgypWTEyMQbVLNGXKFLRo0QKff/65dK5ChQqhVatWmDx5MkqVKmWwj6enJzw9PS1qExEREVFetG/fPgBAhw4dnNwSIpJTHbZ69OgBABgxYoS0TaPRSBWprKwsi47j4eGBkJAQ7N69W2cg5+7du432NU5JSYGbm26TXV1dAWRXxIiIiIgKov3796Nw4cJo1KiRs5tCRDKqw9atW7fsdvLRo0ejT58+aNSoEZo1a4aFCxciKipK6hY4fvx43Lt3DytXrgQAdO3aFYMHD8a8efPQqVMnREdHY+TIkWjSpAlKly5tt3YRERER5RUpKSk4fvw42rdvD3d3d2c3h4hkVIetChUq2O3kPXr0wOPHjzFp0iRER0ejTp062L59u3SO6OhonTW3+vfvj8TERPz666/47LPP4O/vj7Zt22Lq1Kl2axMRERFRXnL06FFkZGSgbdu2zm4KEenRCFb0v/v9998xf/583Lp1C8ePH0eFChUwe/ZsVKpUKddPN5qQkAA/Pz/Ex8fD19fX2c0hIiIissmXX36JKVOm4PTp0wgJCXH8CZOTgcKFs79PSgL0xu8T5SWOzgaqZyOcN28eRo8ejS5duuDp06fSGC1/f3/Mnj3b3u0jIiIiIhP27dsHf39/1K9f39lNISI9qsPWnDlzsGjRIkyYMEGanAIAGjVqhAsXLti1cURERERkXEJCAk6fPo2XX35Z576MiHIH1WHr1q1baNCggcF2T09PJCcn26VRRERERGTe4cOHkZWVhTZt2ji7KUSkQHXYqlSpkuKixv/++y9q1apljzYRERERkQXE9bU4OQZR7qR6NsLPP/8cH330EdLS0iAIAv777z+sWbMGU6ZMweLFix3RRiIiIiJSsH//fhQvXhy1a9d2dlOISIHqsDVgwABkZmZi7NixSElJQa9evVCmTBn8/PPP6NmzpyPaSERERER6kpOTce7cOXTr1g0ajcbZzSEiBarDFgAMHjwYgwcPRmxsLLRaLUqUKGHvdhERERGRCaGhodBqtWjatKmzm0JERqges7Vo0SJcu3YNAFCsWDEGLSIiIiInOHnyJADgxRdfdHJLiMgY1WFrxowZqF69OkqXLo333nsPCxYswJUrVxzRNiIiIiIy4sSJE3BxcUGjRo2c3RQiMkJ12Lpy5Qru37+PGTNmwM/PD7NmzULt2rVRsmRJjtkiIiIiyiEnT55EnTp1ULhwYWc3hYiMsGrMVsmSJfHee++hW7duOHLkCNauXYtVq1Zh/fr19m4fEREREem5e/cu7t27hy5duji7KURkguqw9e+//+LgwYM4cOAAzp07h9q1a6N169b4+++/0apVK0e0kYiIiIhkxPFanByDKHdTHbZeffVVFC9eHJ999hl27twJPz8/R7SLiIiIiIzg5BhEeYPqMVszZ85EixYt8NNPP6F69ero0aMH5s2bh/DwcEe0j4iIiIj0nDx5EkWKFEGNGjWc3RQiMkEjCIJg7c4XLlzAwYMHsX//fvzzzz8IDAxEdHS0PdtndwkJCfDz80N8fDx8fX2d3RwiIiIiVTIzM+Hn54cXX3wRe/fuzfkGJCcD4qQcSUlAoUI53wYiO3F0NrBqggwAOHv2LA4cOID9+/fj8OHD0Gq1KFu2rD3bRkRERER6Ll68iJSUFHYhJMoDVHcj7NatGwICAtC4cWP88ccfCA4Oxu+//464uDicOnXKEW0kIiIiov/333//AeDkGER5gerKVnBwMD788EO0bt2a3fCIiIiIctjZs2cBACEhIU5uCRGZozpsTZ8+3RHtICIiIiILhIWFoVixYihdurSzm0JEZqjuRggABw8eRNeuXVG1alVUq1YN3bp1w+HDh+3dNiIiIiKSycrKwvnz51G/fn1oNBpnN4eIzFAdtlatWoX27dvDx8cHI0aMwMcffwxvb2+0a9cOq1evdkQbiYiIiAjA9evXkZKSgvr16zu7KURkAdXdCL///ntMmzYNo0aNkrZ9+umnmDlzJr777jv06tXLrg0kIiIiomxhYWEAwLBFlEeormzdvHkTXbt2NdjerVs33Lp1yy6NIiIiIiJD586dAwDUq1fPyS0hIkuoDlvlypVTXEBv7969KFeunF0aRURERESGwsLC4OnpierVqzu7KURkAdXdCD/77DOMGDECYWFhaN68OTQaDY4cOYLly5fj559/dkQbiYiIiAjZYatOnTpwd3d3dlOIyAKqw9awYcNQsmRJzJgxA3/++ScAoGbNmli3bh1ef/11uzeQiIiIiICHDx8iOjoaXbp0cXZTiMhCqsMWAHTv3h3du3e3d1uIiIiIyAhxvBYnxyDKO6wKWwBw+vRphIeHQ6PRoGbNmlzF3M7u3LmDsmXL2ryGRnR0NLZv346BAwdyPQ4iIqI8jDMREuU9qifIuHv3Llq1aoUmTZrg008/xYgRI9C4cWO0bNkSd+7ccUQbC5zdu3ejfPnymDx5ss3H6tixIz744AMcOnTIDi0jIiIiZxHDVt26dZ3bECKymOqwNXDgQGRkZCA8PBxxcXGIi4tDeHg4BEHAoEGDHNHGAufgwYMAgPXr19t8rIsXLwIAnj59avOxiIiIyHnCwsJQpUoV+Pr6OrspRGQh1d0IDx8+jGPHjulMOVq9enXMmTMHLVq0sGvjCqqsrCwAgKurq92O6eKiOlcTERFRLpGWloarV69yMjKiPEb1HXj58uWRkZFhsD0zMxNlypSxS6MKOkEQAMCuY6w4XouIiCjvioiIgFarRe3atZ3dFCJSQXXYmjZtGj755BOcPn1aCgWnT5/Gp59+iunTp9u9gQWRI4IRwxYREVHedenSJQBg2CLKY1SHrf79+yMsLAxNmzaFl5cXPD090bRpU5w5cwYDBw5EQECA9GWJuXPnolKlSvDy8kJISAgOHz5s8vnp6emYMGECKlSoAE9PT1SpUgVLly5VexlEREREeQbDFlHepHrM1uzZs+128nXr1mHkyJGYO3cuWrRogQULFqBz5864fPkyypcvr7jPu+++i4cPH2LJkiWoWrUqYmJikJmZabc25SZi5ZCIiIgKtkuXLsHV1RXBwcHObgoRqaA6bPXr189uJ585cyYGDRqEDz74AEB2kNu5cyfmzZuHKVOmGDx/x44dOHjwIG7evClVzipWrGi39hARERHlRpcuXULVqlXh6enp7KYQkQpOm6Lu2bNnCA0NRceOHXW2d+zYEceOHVPcZ8uWLWjUqBGmTZuGMmXKIDg4GGPGjEFqampONJmIiIgox6WlpeHGjRvsQkiUB6mubNlLbGwssrKyEBQUpLM9KCgIDx48UNzn5s2bOHLkCLy8vLBx40bExsZi+PDhiIuLMzpuKz09Henp6dLPCQkJ9rsIstnevXvRvn17XLhwAXXq1HF2c4iIiHKdq1evciZCojzK6Ysv6c+SJwiC0ZnztFotNBoN/vjjDzRp0gRdunTBzJkzsXz5cqPVrSlTpsDPz0/6KleunN2vIS/IrbMR/u9//wMALF682MktISIiyp04OQZR3uW0sFWsWDG4uroaVLFiYmIMql2iUqVKoUyZMvDz85O21axZE4Ig4O7du4r7jB8/HvHx8dLXnTt37HcRDpJbg5EjaLVaAFx0mYiIyBgxbNWqVcvJLSEitZx2h+vh4YGQkBDs3r1bZ/vu3bvRvHlzxX1atGiB+/fvIykpSdoWEREBFxcXlC1bVnEfT09P+Pr66nzlFQVhNkKGLSIiItM4EyFR3mXRmK0333zT4gNu2LDB4ueOHj0affr0QaNGjdCsWTMsXLgQUVFRGDp0KIDsqtS9e/ewcuVKAECvXr3w3XffYcCAAfj2228RGxuLzz//HAMHDoS3t7fF56XcIysrCwDDFhERkTGXLl1CtWrVOBMhUR5kUdiSd9sTBAEbN26En58fGjVqBAAIDQ3F06dPVYUyAOjRowceP36MSZMmITo6GnXq1MH27dtRoUIFAEB0dDSioqKk5xcuXBi7d+/GJ598gkaNGiEwMBDvvvsuJk+erOq8uV1B6kYoVu8K0jUTERFZKjU1FTdu3FB9j0VEuYNFYWvZsmXS9+PGjcO7776L+fPnw9XVFUB2dWL48OFWddEbPnw4hg8frvjY8uXLDbbVqFHDoOthfiMGkILQjZAhi4iIyLirV69CEAROjkGUR6nuu7V06VKMGTNGCloA4OrqitGjRxudfp2cL7eHmoIQLImIiNTi5BhEeZvqsJWZmYnw8HCD7eHh4dJkB/Tc9evXMWnSJFWvjRiMcntAsoeCcI1ERETWunr1KoDs2ZeJKO9RvajxgAEDMHDgQFy/fh0vvvgiAODEiRP48ccfMWDAALs3MKdNmjQJoaGh2Lx5s12O16ZNG9y9exdNmzZFp06dVO3Lag8REVHBJoatqlWrOrklRGQN1WFr+vTpKFmyJGbNmoXo6GgA2etfjR07Fp999pndG5jTvvnmG7seT1z/y9iiy/by7NkzXLp0CQ0aNHDoeRyFwZIALgVARKTv6tWrKF++PHx8fJzdFCKyguo7GhcXF4wdOxb37t3D06dP8fTpU9y7dw9jx47VGcdFutTcPIpd69QEkOHDh6Nhw4Y4ePCg6rY5kzXXSvlX06ZN8c477zi7GUREuYJWq8W1a9dQvXp1ZzeFiKxk1cfHmZmZ2LNnD9asWSPdLOsvNky61IQta4LHxo0bAQCXL19Wva8zccwWidLS0nD69GlVa/UREeVn9+7dQ0pKChczJsrDVHcjvH37Nl555RVERUUhPT0dHTp0QJEiRTBt2jSkpaVh/vz5jmhnnufoblHm1qvK7aGGlS1KSEhwdhOIiHKViIgIAGBliygPU50APv30UzRq1AhPnjyBt7e3tL179+7Yu3evXRuXn6gJO7YEo9weqvTltfaS48jDFmc2JSJ6PjkGK1tEeZfqytaRI0dw9OhReHh46GyvUKEC7t27Z7eGkTqsDFFel5iYKH2flJRk1SLpRET5CStbRHmf6sqWVqtFVlaWwfa7d++iSJEidmkUqWeuG2FuxQkySJScnCx9//TpU+c1hIgol7h69So8PT1Rvnx5ZzeFiKykOmx16NABs2fPln7WaDRISkrCN998gy5dutizbQWWLQGEYYvyqvT0dMXviYgKqoiICFSrVo3LYRDlYarfvbNmzcLBgwdRq1YtpKWloVevXqhYsSLu3buHqVOnOqKN+YKaEGRN8MjrE2QQPXv2TPo+MzPTiS0hInK+9PR0REZGsgshUR6nesxW6dKlERYWhjVr1uDMmTPQarUYNGgQevfurTNhBuUsVoYor5NXsxi2iKigu379OrRaLSfHIMrjVIctAPD29sbAgQMxcOBAe7eHrJRXx2yJGBaJlS0iouc4OQZR/qC6G6GrqyvatGmDuLg4ne0PHz6Eq6ur3RpWkFkTmMyFldwaZvJqOCT7k1e2MjIynNgSIiLn47TvRPmD6rAlCALS09PRqFEjXLx40eAxUuaIAKXmPLn1d8OwRSJ2IyQieo6VLaL8QXXY0mg0+Pvvv9G1a1c0b94cmzdv1nmMnMtYqMqtYUuU29tHjsduhEREz129ehXFihVDQECAs5tCRDawqrLl6uqKn3/+GdOnT0ePHj0wefLkPHuzfPnyZdStW1f6BMlRciqIys9z7do16fvc+vvh1O/WSUxM1FmXKj9gZYuI6LmIiAh2ISTKB2xauOHDDz/Ejh07MHv2bPTp08debcpR48ePx4ULF/Dtt986uykGbA0gjRo1stuxKHcpWrQoOnbs6Oxm2BUrW0RE2eLi4hAbG8suhET5gOqwVaFCBZ2JMF5++WWcOHECd+/etWvDCjJbqmDyUJWQkKC4PTfK7e3LbbKysnDs2DFnN8OuWNkiIsrGyTGI8g/VU7/funXLYFvVqlVx9uxZPHz40C6Nyo8c3Y3Q3PFza5hx1ji/hw8fokiRIvDx8XHK+ckQK1tERNk4OQZR/mFTN0I5Ly8vVKhQwV6HyzG5MYQ4IoDkxusEnBe2SpYsiapVqzrl3KZs2rQJMTExJp+TW3+XtmLYIiLKxsoWUf5hUdgKCAhAbGwsgOyxIgEBAUa/yH7seVOt5lhxcXH4888/c/Sm3hkBIjo6OsfPaUpYWBi6d++ONm3amHyePJTkJ/K1tRi2iKggi4iIgIuLS678UJCI1LGoG+GsWbNQpEgRAMDs2bMd2Z4cl1+mqxevY9y4cXjzzTdRtGhRncfVhJk33ngDhw8fRpUqVRASEmLXdupzxmyEufFG/r///sPWrVsBZM+QaUpWVlZONCnHMWwREWW7evUqKlasCE9PT2c3hYhsZFHY6tevn+L3+UFO3eTn1KLGjx8/xtdff405c+ZYfazDhw8DACIjIx0etpxBflOfWzRt2tTi5zJsERHlX1qtFteuXTPby4GI8gaLwpZ8VjtzfH19rW6MM+WmCpetwezp06cmH7eUi4vdhvQZ5YzKllarzbFzOYI8bGm12hz5PeUEeffI3BiIiYhyQlRUFNLT0zk5BlE+YVHY8vf3t2i2O41Gk2c/dc9Pkw7Ip+YX5fawlZPyetiStz8jIyPfdDNhZYuIiJNjEOU3FoWt/fv3O7odZCN5aFEKMNaELaXQlh/k9WAt/0AjMzOTYYuIKB/htO9E+YtFYeull15ydDucLjd2IwwPD0dCQoJdumZaW9maM2cOHj9+jIkTJ9rcBlPYjdBy+mErv2DYIiJ6Xtli2CLKH1QvaixKSUlBVFSUwTTUdevWtblR+ZG1YW7EiBH44IMP0KhRI3h5eVl9LmvCjEajwYgRIwDAYWGLY7bUX7s8bOWnsU0MW0RE2ZUtHx8flC5d2tlNISI7UB22Hj16hAEDBuDff/9VfDyvjtnKrVasWIEVK1agb9++WLFihUX72DNs5VUpKSnw8fFRfCy3hS217xlWtoiI8q+rV68iODg430x+RFTQqX4njxw5Ek+ePMGJEyfg7e2NHTt2YMWKFahWrRq2bNniiDY6RW4b17Nnzx6Tj1sygYlaeXU2whs3bqBQoUKYOXOm4uO5LWypXaRY3v78FErkr0N+uK7z588jLi7O2c0gojwkNTUVUVFRnByDKB9RfTe9b98+zJo1C40bN4aLiwsqVKiA999/H9OmTcOUKVMc0cYCRyk4qQk+eamy5YhzbN68GQAwY8YMxcdzW5BWG7ZY2cr9nj59inr16qFJkybObgoR5SHXr18HwJkIifIT1WErOTkZJUqUAAAEBATg0aNHAIAXXngBZ86cUd2AuXPnolKlSvDy8kJISIi0oK45R48ehZubG+rXr6/6nHLGbrztfUNua6iwdf/cFrYOHDiA8ePHO+TY4o26u7s7BEHAjRs3dB7P65UtjtmyTnh4ON577z3Exsba/dhK5wJg8LdHRGQKZyIkyn9Uh63q1atLM+XUr18fCxYswL179zB//nyUKlVK1bHWrVuHkSNHYsKECTh79ixatWqFzp07IyoqyuR+8fHx6Nu3L9q1a6e2+U6jJuxYE3IcMfX7gQMHVO9jqTZt2uDHH3+Uulk5otqk0Wgwf/58VK1aFX/++ae0PT+FrbxeAZJzdNj68MMPsXbtWqxbt87ux9b34MED6fv8FIiJyLHEsMXKFlH+YdWYrejoaADAN998gx07dqB8+fL45Zdf8MMPP6g61syZMzFo0CB88MEHqFmzJmbPno1y5cph3rx5JvcbMmQIevXqhWbNmqltvgFjwcbeN//y4125ckXnZswSzqhsff/99zad0xJi90h7vt7yY23dulXnv0DuC1tqg0V+DlseHh7S9/Ym/n/r6dOndj+2Pvn7OyfOR0T5gxi2qlWr5uSWEJG9qA5bvXv3Rv/+/QEADRo0QGRkJE6dOoU7d+6gR48eFh/n2bNnCA0NRceOHXW2d+zYEceOHTO637Jly3Djxg188803apuuKKe6EcqPV7NmTdVVQFsrY7llnJL+zHtiWx88eIALFy7Y5RzitcrHuclfk9zyWojUBiZ5WMxPVZOMjAxpBklHhEjx954Tv/+HDx9K3z958sTh5yOi/CEiIgLFixdH0aJFnd0UIrITq9fZEvn4+KBhw4aq94uNjUVWVhaCgoJ0tgcFBRmt+ly7dg1ffPEFDh8+DDc3y5qenp6O9PR06eeEhATVbc1rcmvY0mq1cHNzw/vvvy9tE9u1detWbN261S7tFI9hrBqY2ypbnPo927Nnz+Dt7Y2nT5865LrEv4fk5GS7H1tffHy89D3DFhFZKiIiguO1iPIZ1WFLEASsX78e+/fvR0xMjMGN64YNG1QdT/+GWBAExZvkrKws9OrVC99++62qvsxTpkzBt99+a9H55Td4jqxsWcNcN0JHjNmyNzH0rlq1Stqmpl1paWkWLewsP6b8+xEjRqBXr17SBC+5BbsRZsvIyIC3tzcAdde1fft2fPTRRzh48CDKly9v9HlipTMnwlZiYqL0PcMWEVkiLi4OsbGx6Nq1q7ObQkR2pLob4aeffoo+ffrg1q1bKFy4MPz8/HS+LFWsWDG4uroaVLFiYmIMql1A9s3L6dOn8fHHH8PNzQ1ubm6YNGkSzp07Bzc3N+zbt0/xPOPHj0d8fLz0defOHcXn/fHHH3B3dzfb7oyMDBw7dsyh1RFzwUqr1Rqc31xoyQ1hS+k1s7RdmzZtgre3NzZt2mT2ufJuhOL3oaGhmDNnDpo1a5bnK1v5dZ0ta8PW4MGDERkZqTMuT4n4vkpKSrK+kRaSh62cOB8R5X3Xrl0DwMkxiPIb1ZWtVatWYcOGDejSpYtNJ/bw8EBISAh2796N7t27S9t3796N119/3eD5vr6+BmN65s6di3379mH9+vWoVKmS4nk8PT3h6empun3GQsCXX36J6dOnY9WqVejdu7fNx7NG5cqVAQCRkZGKj+fWypYlYctYZVOshq1ZswZvvPGGyfMoXau8K2l+Clv5bcyWNWFLnIDC0tcip8NWamqqw89HRHkfZyIkyp9Uhy0/Pz/pZt9Wo0ePRp8+fdCoUSM0a9YMCxcuRFRUFIYOHQoguyp17949rFy5Ei4uLqhTp47O/iVKlICXl5fBdkcSp0MPCwtTFbbs6fbt26r3ySthS6vVwtXV1ejzLFncWQxrgiAoXndueC3kCmI3wvT0dJw/fx6NGzeWtlkbtsTnmuuuJwbunO5GmJKS4vDzEVHex7BFlD+p7kY4ceJEfPvtt3b5tLZHjx6YPXs2Jk2ahPr16+PQoUPYvn07KlSoACB7qmZza27ZyhlTvztCXhizZWnYUmJu0gs5edhSOl5+qmzl1bDVs2dPNGnSRFr8F7B9NkJzYUtcz8wela01a9botF0fK1tEpFZERAQ0Gg2qVKni7KYQkR2pDlvvvPMOnjx5ghIlSuCFF15Aw4YNdb7UGj58OCIjI5Geno7Q0FC0bt1aemz58uUmF9adOHEiwsLCVJ/THs6fP696MVpjHj16hBEjRiA2NhaAcqBQs85Wfg5bas4jP5b8NcltYcuWqd9zKmz9+uuv+Pnnn+12PHHsnbhAOpAdtsQJUNRcl/g+TEtLs+h5tla2Ll68iF69eqFNmzZGn8OwRURqRUREoHz58lKFn4jyB9XdCPv374/Q0FC8//77CAoKsnmxXWeaO3cutmzZoviYuZv7Xbt2YciQIVi2bJlF5zJ1vLFjx2L58uVIT0/HggULrGqPnNLvZO3atahYsSI6dOhg8XHszZJrsEdlSx62lM6Z28KWLVO/59SYrU8++QRA9gQ59iQuxSAIAjIzM+Hu7g53d3eLw5b8tZCPy1Nir8rW6dOnAWSvpfXs2TNpIWa5xMREFC9eHI8ePWI3QiIySxAEREREoEWLFs5uChHZmeqwtW3bNuzcuRMtW7Z0RHty1EcffWT0MUsWO960aZPFYcuUx48fA3h+E+iIALtv3z7s27fPqRWunOpGKN6AGwtbuaHKJ5cXKluOIlZ9xNDo7u4ONzc3i69Lvp6VucqWeA5bw9b169el72/duqW4Jk5iYiKqVKmCR48esbJFRGbdv38fKSkpHK9FlA+p7kZYrlw5+Pr6OqIteY6aUHTo0CEAyjf64jaliSEsPZe5MVu5gSXjp+wZtoy9Jnm9sqUUtr766iud9cvyCmNhy9KKnXyclqWVLVu7EcqXq7h3757B41lZWUhLS0Px4sUBsBuhKceOHUONGjWwfv16ZzeFyKk4OQZR/qU6bM2YMQNjx441Ou14fmGs+iG/abdkZjzRjz/+iLS0tFxXVbGXHTt24P79+yafY0nIMff6qAlbxo6X18OWfjfCtLQ0fP/99+jTp4+9mwbAsZVAsYudtZUtedgyVdnKysqSfu+2VrYePnwofS9WpeXEcBUYGAiAsxGaMmnSJFy9ehVjx451dlOInIphiyj/Ut2N8P3330dKSgqqVKkCHx8fg4WA4+Li7Na43Eh+46m2giSOSXE0jUaTo93LoqOj0blzZxQvXhwxMTFGn5fTE2TI98vNlS1buxE6+j0nnwhm+PDhaNq0Kfr162eXY+tXtjw8PKwOW6YqW/JKWWZmptGxVpZ49OiR9L2psBUQEKDzM+nKysqSKv63bt1CVFQUypcv7+RWETkHwxZR/qU6bM2ePdsBzch9LLm5Vxu2LH2+Nd0A9fcRb2JygriorPwmVIktYUvcbkk10VylSH6OHTt24JVXXjF7TEeytRuhoysn8orRvHnzMG/ePLuFLVsrW+LfHmA6bOnPHJqUlCSFIbXEST0A5bAlXlORIkXg7u7OsGXE1atXkZqaiqJFi+LJkyc4d+4cwxYVWBEREXB3d5eWviGi/ENV2MrIyMCBAwfwv//9z24LG+cn5sYV5dQiuxqNRvUNvC0sPZcl126u6qSmG+GdO3ekddrk55F/37lzZ2RlZSE1NRVhYWFo0qQJ+vTpg+HDh+ssQ+BIti5qbG6skq3MTTxhCzGIiGHIUd0I7R22Spcujfv375usbPn4+MDHx4fdCI0QJxp5++23sWjRIly6dAldu3Z1cquInCMiIgJVq1Y1OXabiPImVWO23N3dsXHjRke1JVexNABt3LgRN27cAAC0adPG5KdSxmbHszeNRpOjY8Ms7ZaX07MRGnsN9M+RnJyM77//Hi1btsTYsWOxbt06vPTSS2bPYy+2VLYyMjIcHrYccXzx92jP2Qgt7UYI2DZJRmJiIipWrAjAdGXL29sb3t7erGwZIY77bdu2rc7PRAVNRkYGbt68yS6ERPmU6gkyunfvLi1IWtAlJibizTffRNWqVQEABw8exJ07d4w+31zYEm9AbZ1N0Jlh68GDBzqztRl7nsgRYctc+NN/PCEhAfPnzwcAKTg7mlarxfz583H37l2bx2zJqzaOGKvniMqW2B3U1m6E4mQX7u7uqitb1hAEAUlJSQgKCoKnp6fZypa3tzcrW0aI4apJkybw8vKSqtBEBU1kZCQyMzMZtojyKdVjtqpWrYrvvvsOx44dQ0hICAoVKqTz+IgRI+zWOGeyJKyo/cRfq9Xm2OtjSfszMzPRo0cPDBkyBB07djR7PFPdI0WlSpUyev6cmiBDzZgtIDtsiTf3OdWFY/v27Rg2bBjWr1+Pvn37Gjxu6vU21Y0wKSkJ/v7+dm2rvcOWIAjSNdha2RIrVAEBARaN2SpSpAgSExOtrmylpKRAq9XC19cXgYGBZitbPj4+rGwZERkZCRcXF5QrVw7ly5fH7du3nd0kIqfg5BhE+ZvqsLV48WL4+/sjNDQUoaGhOo9pNJoCFbbU0mq1WLBggcPPaWllKzQ0FBs2bMCGDRvMPt/UzX9u7UZoaTsSExOlbTkVtsSJHQ4dOoTevXsbPJ6VlQU3N+W3p6luhImJibk+bMmrTPqVLXE2QmPBKS0tDV5eXtLPYoUqICAAsbGxRs8pHr9o0aJITEy0urIlTo5RpEgRaWIHfWK4ErsRmps4pqCKjIxE2bJl4e7ujvLly+P48eMm/z9DlF8xbBHlb6q7Ed66dcvo182bNx3RxlxLbTgy9nxx+++//47Vq1dj3rx5NrfNEmq6nJkKVMauKzk5WWdMjSVha//+/SbPYW3Ykp9HqbIlUrN2mi3E6xAEQfH3YCowmqpsnTx50o6tzKYUtmz5YEDeXjEEWVLZOnjwILy9vXXGjYoVqsDAQIu6EYqTYlhb2UpMTASQHbYKFSqkeBwxQLIboWn37t1D2bJlAQAVKlRAcnJyvl86hEgJwxZR/mbTnaWx2fXyA0dVtszp3bu3ybELlk5Jb8nz1EzMYOp4xh4rW7asTpVF6fr1t/Xt21eapUzpHNaO2cptYUsk71InZ+p3Y2rM1jvvvGPfBkI5bOlPOKGGvL3i95bMRrh27VoAkMbXAdmhSaPRwN/f36JuhEWLFgXwPDSpJe7n6+uLwoULK1bI5JUtdiNUlpWVhdjYWAQFBQEAypUrBwC4e/euM5tF5BQREREoUqSI9H4govzFqjvLlStX4oUXXpC6ydStWxe///67vdvmdJcuXcKQIUN0buJsCWG2jEeSV0JMPW7uXHKODlvyNZDMHUNO6UbY1sqW/PVQClvicXMqbInnycrKsjlsOWPqd1sChDxsKVW23N3dFcOc2B2vSJEi0rbk5GQUKlQIXl5eePbsmdG/e/F4gYGBAKwPW2Ily8fHB4ULF1asbOlPkJGamppvP5SyVlxcHLRarXRzWaJECQDm1+ojyo8iIiIQHBzMLrRE+ZTqO8uZM2di2LBh6NKlC/7880+sW7cOr7zyCoYOHYpZs2Y5oo1OIQgCOnbsiIULF2L9+vUAsm+ALR3EPWbMGCxdulRnm6Vjm5SI/xO25BiW/g9bTXuGDx8OAFizZg1++uknHD9+XNrfnmO2ACiOVbI1bMm3maps5RT5NdrSjTAjI0MnmBQuXNhOLXxOKczZK2yJ31vSjVAMNvJrFMOWp6enwbGVzlmsWDEAulPGqyEGT29vbxQuXBgZGRkG59SfICMrK8umSmB+9PDhQwDPQ5b435iYGKe1icgZkpOTcffuXXYhJMrHVE+QMWfOHMybN09nBrXXX38dtWvXxsSJEzFq1Ci7NtCZxMqMeDM1bNgwxdnHlMyYMcNg286dO21ukyXVKI1GY1EoUfNp+5IlS7Bo0SL06tVL2jZ37lwMGzbM4mNYGraUJqnIqcqWLYHYWubaa+qxzMxMnWBSq1Yt+zYOypUtW8YhWRu2xHPKq49paWnw9vaWJs1IT0/XmUBDJB7fXmHLy8tLmolVf4Fk/cqWuM3Dw8Oqc+ZHYqhi2KKCTuw2z7BFlH+prmxFR0ejefPmBtubN2+O6OhouzQqN1AKAStWrLDpmIcOHbL4XMYYuwmXhxBLx2zZOsHHwYMHVR3H0rBlKlA5asyWeFxHrFOlRB6wbO1GKH+u2i6F9+/fN7tQeU52IxRnIzQVtvTDmru7u1TZMjZJhrhP8eLFAdgnbIkVNv2uhPqLGsu3UTaGLaJsnByDKP9THbaqVq2KP//802D7unXrUK1aNbs0KrcRb9SNdVHSZ+xGzpbxQI6ovKgNW/rnFm8kbelGaOk2W9fZsnSCDDXj2GyhH5j0qZmNUL6/2rDVrl07vPnmmyYX47Z3ZUvepc6aboT6YcvDw0MKW8auXz4boUajsTpsySe/EMOW/iQZ+hNkyLdRNoYtomwMW0T5n+puhN9++y169OiBQ4cOoUWLFtBoNDhy5Aj27t2rGMLyKq1Wa/VgVWNdKe0x+YKlY7asrQCpeb7YLcrelS1TzzN3XZcuXcLmzZsNtpsbsyUeN6fClr0qWxkZGTrBxNIPBERXrlwBYDoM5JZuhGJA0p863sfHR+o6aKyyJR7fy8sLvr6+du9GKKc/9TvAsKVPP2z5+/vD3d2dYYsKHDFs5dcPq4nIisrWW2+9hZMnT6JYsWLYtGkTNmzYgGLFiuG///5D9+7dHdFGp7DlpvvGjRuK222ZacheYeDs2bPSWja2VrbEsVX2DluLFi0y+jxzr2GdOnXMjoHS7w4aHx+f42FL3h5ndiMUmfogQCnAWLsoMKDcjdCSqd/FMZTya1Rb2XJ3d0fRokWxf/9+q67Bkm6E+osaA+xGqE8MVeJshBqNBiVKlGDYogInPDwcpUqVgp+fn7ObQkQOorqyBQAhISFYtWqVvduSq9hy021sbFalSpWsPqa5boT6Y7aMadiwIUqXLo179+7ZHLbEG3RLK2RK51PaNmfOHMyePVsnAKiZIMPcufXHKKWnp+epypaxboReXl5Why1T53Nk2DJW2RIEAVqtVmeKfFNjtuQTZJg6p4eHB+Lj46HVajF69GgsXLhQVduVwpaxypaXlxe7ERoRExMDNzc3nXX4GLaooBEEAeHh4WjSpImzm0JEDpSzK7jmIUrr59iqfv36itvtMUGGnLlAcv/+fdXnVTq3eCNs7jhxcXH4+++/VY3F0u8OZ2vYMvW6yasojpggY/369Zg8ebLR9qgds2WsG2GhQoWsDlumrlspbPXs2VPq/qKWJRNk6LdJXhkyVdkyN0GGh4eHNIPmnj17VLfdkm6Eqamp8Pb2hkajYWXLiJiYGBQvXlznAxWGLSpo7t69i6SkJIfMIktEuYfFYcvFxQWurq4mv5TWR8qtduzYYfLxe/fu2f2c9pjcwtKp3y2RU2GrU6dOePvttxUrfsb21b9pdnTYcmRl65133sH//vc/nW32nI1QHrbUjtmy5HzGAty0adOsOpd+ZUoQBIPKFmA8bOmHNUu6EcrD3OTJk1G4cGFpgWM1xAqVudkIxZDFMVvKxLAlV6JECSQnJ9vlg65Hjx7h+PHjOVapJrLG5cuXAThmyQ4iyj0sTkempoc+duwY5syZo/rm3Zl69Ohh8nFxPR5AfSgxxpbjiOOjLK1sOWLqd2Nhy9wNzenTpwE8X8jU1DFF4g31s2fPpBtpwPqw9eTJE6OPyW/qla7lyZMn8Pf3t2nMHZB9w+/u7g7AtjFb+t0IxZ99fHyQnp4OQRBUt1VtN0LA+r9n8Xcr/p1mZmaaDVvyG3Clypa5CTLklS2NRoNSpUoZfa4p+osaA8YrW+LzxG30XGxsLCpWrKizTZws49GjR1LV0BoXLlxA69at8fTpU/Ts2RNr1qyxpalEDiOGrZo1azq5JUTkSBZXtl5//XWDr+rVq2P58uWYMWMG3nnnHVy9etWRbc1RtsxGaOqY1lITtgDLboRtnY1Q7ZgtNd0IxZt//ZBk798JoHtTL5+WHAAuXryIgIAALFiwwObzyG+49QOTvs2bNxvtpmessiWOD9K/BktYE7YePXqk+jzA8/aJYSUjI0MxbMmvQ6myJVbE1EyQIc6g6e7ubtXrZGk3QvF3wbBl6NmzZ4iPjzeobIk/29KVUBAEfPjhh0hKSkK9evWwdu1aHD582Kb2EjlKeHg4AFa2iPI7q8Zs3b9/H4MHD0bdunWRmZmJsLAwrFixAuXLl7d3+5wmMjLSpkkAlNhS2VIKNoIgYO7cuahfv77OjaNGo7EoANla2TI1aYel24wRb/71g4gjwlZGRoZ0XP0b8G3btgEAfvzxR2mbIAg4ffq06tdPXp2RvxZKYebLL79E9erVFY9jaswWoH76d0Bd2Prkk08AKFcqLSG2T95e+WyBYvXPXGVLHtDUTJAh7mPN+DxLFzVm2DLu8ePHAHR7DwDPw1ZsbKzVxz516hROnDiBAQMGYPXq1QCAlStXWn08Ike6fPkyAgMDDT54IKL8RVXYio+Px7hx41C1alVcunQJe/fuxT///IM6deo4qn1O061bN7sf01jYOH/+vNl9xcqW/KZYEAR89NFHOHfunDQttvwxc2wNW+L+SjfqSjeyls5GKD+mfnBwVGVLPK78fJcuXdKZxls0ffp0NG7cGGvXrlV1Hnl1Rv6aJSYmqjqOsW6EYnixZpIMNWHrrbfeQnBwsMUB4vr162jRogVCQ0MBPH+NxbDy7Nkzq8ZsyQOUmgkyxPPYUtny9PRU1Y3Qmi6L+ZUYpvTDlvizLWFLnF3yo48+Qq1atVC9enXs2rUrT3VxJ9uFhYXh+++/x5QpU3D06FFnN0eRIAi4fPkyatWq5ZB/14go97A4bE2bNg2VK1fG1q1bsWbNGhw7dgytWrVyZNtyFXNVGUuqNkoB5L///kN0dLTZfZUqW6amgbe2siUucqtE/5jizarSuZSuVU03wtu3bwOwrkqjljxsyW/A69SpI30KL1ZbgOez2Kmdzc5YZUtt2DLXjdDRYcvNzQ2enp4Wn+eXX37BsWPHpOqgfmVL3o3Q2GyEpipbOd2NUJwMyNSixqxsGeeosKXVaqUP/+rVqwcAePnllxEVFYWoqCgbWkx5RUpKCt5++200aNAAX331Fb788ku0bNkSbdu2lWbhzS0ePnyIJ0+ecLwWUQFg8QQZX3zxBby9vVG1alWsWLHCYGFY0YYNG+zWuNzEXJejNm3amD2G0kDtS5cuWXR+Y90IldgStkz9j1//mOJrYkvYMuadd97Bw4cPDW6Ic3rMllLYs3RiEH3GKlumuquuXr0arVu3RtmyZRX3lXcjzMmw5eHhYXFIjI+PB/A8VCp1I1RT2RKvTx6gLJ0gQwzN1oat9PR0KdiJ7Vda1JgTZBgnjvUzNmbL2rGAYWFhiImJQb9+/aRtDRs2BJA9aUaFChWsOi7lDUlJSXj11Vdx6NAhdOvWDaNHj4abmxsWLVqEFStWoFmzZti5cydq1Kjh7KYC4HgtooLE4rDVt2/fAlvqFgTB7I21sYWM5ZSmk7e0e4vSBBmmKls5MUGGeLNqSzdCY20QB8nrH8ce0+frM1bZApTbLP4u1I75kQcGSytbvXv3Rr9+/bB8+XLFffWnfgfsP2ZLP7yJYcvS84hBSAwc+t0IjU2QoVTZcnFxMehG6O7urmrqd3Efaytb4rlcXV3h7e2tE5azsrKQnp7OypYJjqps7dq1CwDwyiuvSNtq164NIPtDrddee82q41LeMHLkSBw6dAgjRozA7Nmzpf+nt2jRAi+//DIGDx6MV155BadPnzb423MGTvtOVHBYHLbkN3sFkT36/OsHhcOHD1t8XBcXF1y/fh1Dhw4126acmiBj0aJFWLhwoeK5lG5krZk0w5LwYytTE2QoBSrxhl3tzbq8AqJmzNa6desUw5aHh4dTxmy5urqq6kYo7q//GlszZisgIACxsbEGa3PlVDdCeWULyH7N5WFLPjW8/L8MW88ZC1t+fn5wdXW1urJ1/PhxuLm5oVmzZtI2edii/Gvz5s1YsmQJOnbsqBO0RP3794dWq8WgQYPw7rvvYteuXU5fF5Rhi6jgsGo2woJm+PDhiIuLs/k4+kGhdevW2Lp1q8X7vv3229i/f7+0zVRQsSZsmQsymzdvtvhclnYjNFcxzOnKln61Ruk6zN3Yy8mv7+2335baL78Oc5/kyyfnkB9TDFvO6kZoaWUrISEBwPPul+ZmIzRV2SpatCgAw2qY2rDl5uZm1WyE6enpUqUOyA6M8hAthkJWtowzFrZcXFxQrFgxqypbgiDg5MmTqFu3rs77xd/fH2XKlMHFixdtazTlWmlpafj444/h7++PpUuXGu2BM3DgQAwfPhz79+/HrFmzcriVhi5fvowiRYqgdOnSzm4KETkYw5YFMjIydKb+tpZSmBH7bZuTmpoqTdZg6njidjWzEZqawl1uxIgROj+LE6TYErZyQ2XLVDdC8Trk5xVv2C0JG/LjPXv2TPrUXh5uxN/rxo0b0atXL4NjyG/ugeevmaenp01jtuTX5MiwJVbu9MdametGeO/ePfTt2xe3b9+WQoy/v790LKWp33NyzJZ4DfLKlv7slfpdKOl52AoMDDR4zNqwFRUVhYcPH6Jp06YGj9WuXRvh4eEO+aCGnO+3337D3bt38b///Q9lypQx+dzp06cjODgYX3/9tdF1DHOCIAi4dOkSZyIkKiAYtiykPwjeGrYEhaCgIIP/KRu7eRAEwaIbC/E54nHVTvggPt/SMVtKk6qorWw5KmyJ1HQjtCRs6D9HrJAq/X7eeOMNvPzyywbb5Tf38n09PT1tGrMlvzZTvwf9oCCfjdCS34cYRsQgZOkEGdOnT8fvv/+O7777TtpXDFv6+1hS2XJ1dZXG27m7u1s0FlOfuW6E+pUtFxcXeHp6MmzJPHr0CL6+vgZ/10B22LKmG+Hp06cBAE2aNDF4rHLlykhLS7NpsWTKnRISEvDDDz+gXLlyGD58uNnne3t7Y8mSJUhLS8PQoUOdtiRAdHQ0Hj16hPr16zvl/ESUs5wetubOnYtKlSrBy8sLISEhOHz4sNHnbtiwAR06dEDx4sXh6+srzS6UV4jdqawRGBhoELZMVbbUhq1Zs2ZhxowZqtok3qhaWtkydQxj9MOPo7sR6rdbKbiIYWvv3r1mj63ffrGKZey6xTAgp39Tqt+NUPxZbWVLfm2mfg/yiT2A55UtwLLfsxiU9Ctb+mHLzc0NGo1GClviOJu4uDhp3yJFikjHUhu2xDaL+wDqx90pVbbkH8SIoUr8XQDZN3gMW8/FxsYanaCgePHiePLkieounmI3wbp16xo8Js5CKC4nQfnH0qVLERcXh//9738GPQCMadmyJT744APs378fW7ZscXALlZ07dw4ApCUKiCh/c2rYWrduHUaOHIkJEybg7NmzaNWqFTp37mx0TZRDhw6hQ4cO2L59O0JDQ9GmTRt07doVZ8+edXhb7dHl4ObNm1bvKwiCNOZFZCp4mPvEbv/+/dINtouLC0aPHo0vv/xSVZtMhS1Lb2LNhaecqGzJ26rfbvEmWX5epU/kjdEPa1OnTgVg/LqVwpY8JMj3lVe2NBqNdLNhadiSP89Y2NJqtUhNTdW5ZnnYsqSKJoYt/cqWfjdCeRc/4PmU8fLJOHx9faVj5JawlZSUJP19iMFUPm6IYUuXqbBVrFgxCIKAJ0+eqDrmxYsXodFoFJeuYNjKnzIzM/Hzzz+jePHi6NOnj6p9v/vuOxQuXBhjxozJkbUc9YWFhQEAK1tEBYRTw9bMmTMxaNAgfPDBB6hZsyZmz56NcuXKYd68eYrPnz17NsaOHYvGjRujWrVq+OGHH1CtWjX8888/Dm/rsWPHHHJcS/trK4UtWypbbdu2Rf/+/VW1QZ/aboTWyOnKlj6lm2SlQGSMfvvFCVHUVLb0Z82Sz0YojtkSu/YBlncjtCRsidcvVpTENqqZJER8jrluhGIAEkORfD9bK1sZGRkOCVuFChVCZmamdE2sbJkmCILZyhagfq2tixcvomrVqgaTyQDPwxYXNs5fNm3ahMjISHz00UcWV7VEJUuWxPjx43H9+nUsXLjQQS007ty5c9BoNHjhhRdy/NxElPOcFraePXuG0NBQdOzYUWd7x44dLQ42Wq0WiYmJCAgIMPqc9PR0JCQk6HzlJpZWatRUtiztRiiyNWxZM8ugJQ4fPozQ0FCdbaZeL1vOaez1UrpJVvPaijfh+mOx1FS29MOWeJ1iZSsrK0snbNmzG6HYRU4ettRWtvTDltLU78+ePTOobMn3N1fZcnV1hZubm8nKlvy44vdqPxRQqmwBz1+n/F7Z2rFjBz755BOTC3GbkpKSgrS0NJOVLUDdWlvp6em4du0a6tSpo/h4+fLlAbCyld8sXLgQbm5uGDZsmFX7jxw5EiVLlsT3339v0FXa0cLCwlClShXp/x9ElL85LWzFxsYiKysLQUFBOtuDgoLw4MEDi44xY8YMJCcn49133zX6nClTpsDPz0/6KleunE3ttjdLw5bSTaSpsKWmu50jwpY1M73pa926NSZPnqyzTelcjx49wj///IOvvvrK6nMZCxtiQJC/nvptCA0NNfqPtRhG5LNkmZqYQT9QA4bhQ6kboZubm3SDn5CQgJCQEPz000+K5xBZUtkSr8uWsGVszJZY/THWjVDeTnFf8eZEv7IFZL8epmYjtLWyJQgC0tLSDKZ+B55PApKfK1vPnj1Dt27d8Ouvv2LatGlWHUOsWIkVLH1i2FJT2bpx4waysrJQo0YNxcdLlSoFNzc3s2HLWZMlkHpRUVHYs2cPunXrhhIlSlh1DB8fH3z55Zd48OCB0d40jpCSkoJr166xCyFRAeL0CTKUJn2w5OZ/zZo1mDhxItatW2fyf7bjx49HfHy89HXnzh2b22xPlv4Dv2XLFly/ft2ifR1d2apfvz5q166dI90I9Sldc7NmzdCtWzfMnDlT1bG2bt2Kfv36ATDeXqWwJb/eEydOoFGjRvj8888V9xdv5oODg6VtmZmZqipb+tuUuhG6urpK3fIiIiJw5swZjB07VvEcIkvCllixEStKAFRX0ZS6EXp4eOgENnnFSH+MmtiN0MPDQ2dcmlLYsnTMllgtVBO2xOfqdyMEnoet/FzZCgsLk16DjRs3WnUMY2tsicQQpqayJf5/sVq1aoqPu7q6oly5cibD1qhRo1CkSBH88MMPFp+XnGfFihUQBAEDBgyw6TiDBw9G2bJlMXXq1Byrbl28eBFarZaTYxAVIE4LW8WKFYOrq6tBFSsmJsag2qVv3bp1GDRoEP7880+0b9/e5HM9PT3h6+ur85WbXLt2zep97RW2lKop5ri6utplNkK1lK75xo0bACwfqyQqU6aMdKNuLGyIN+/ya5R/f+vWLQAw+smo2CYvLy8MHDgQQHZ4UDNmS279+vVYunQpAMPKlnjjb+kHCpZ0I7SksnX//n0cOnTI6HnEkCV2eRS79InHyMjIwJMnT6QFi41Vtjw9PXXOa0vYsqayJR5bqRuhuJZYfq5siTP++fr64uLFi1ZNpW4ubFnTjVAMW1WrVjX6nAoVKhgNW8eOHcPs2bORnJyMr776SpopjnInrVaL5cuXo2TJknjllVdsOpaXlxfGjRuHR48eYdmyZXZqoWni5BgMW0QFh9PCloeHB0JCQrB7926d7bt370bz5s2N7rdmzRr0798fq1evxquvvuroZuZqti5qLFJb2RIEwWlhy1SIVDtI2sXFRapwGGuv0myE8mAiVn6M9b0XA428KpOWlqaqsiUPBPKukvIJMeRhS3/xa2PUVLZMha0mTZrgpZdeUrxB1q/ipaenS8FHDDzPnj3TCVv6lS152JJX1HJD2BI/vBHDVn6ubEVGRgIABg0aBAA4cOCA6mNYGrbUBDlLw5bYu0Hf8uXLAQDLli2DIAj4+eefLT435bxDhw7h5s2b6Nu3r8F4VmsMHDgQxYoVw/Tp0x3275acGObZjZCo4HBqN8LRo0dj8eLFWLp0KcLDwzFq1ChERUVh6NChALK7APbt21d6/po1a9C3b1/MmDEDL774Ih48eIAHDx4o/gNaEJgKVGoqW9YMds9NlS2RqZstJfKwZe2YLXmYUiIPBPKwpaayJX8t5WFCPGdaWhpcXV1RokQJuLi44Pz584rH1icPAGoqW/qzEd67dw/A8wqjnH74SUtLM+hGmJ6ejqdPn0oLFutXtsRuhGoqW1qtVud1c1TYEl8Xc5Ut+eLTeZUYtsRZTPfv36/6GObCltirwdJxu0B22PLx8UHJkiWNPkecJENpRsJdu3YhODgY/fv3R+PGjbF+/XqjY//I+cQKlK1dCEU+Pj745JNPEBkZiT///NMuxzQlLCwMRYsWRdmyZR1+LiLKHZwatnr06IHZs2dj0qRJqF+/Pg4dOoTt27dLU/VGR0fr/OO4YMECZGZm4qOPPkKpUqWkr08//dRZl+BU9pogQy39ypbSjbo9JshQYipEyheXtYSLi4vZboTiTZexboTi48a6/1la2ercubPR48hfS6X1vlJTU+Hu7g5fX1/UqVMHT58+VWyLPvmHFGrGbLm4uChOkKH0+uvftKalpUnTsIvHiI2NhSAIFnUjNFXZ8vLykgJRr169UKtWLel1tsfU75aELWOVLUB5Zsu8JDIyEoGBgahbty4qVKiAffv2qT6GuQkyPDw8UKxYMdy/f9/iY16/fh1Vq1Y1WaE3ttbW7du3cfv2bbz00ksAsv9NSkxMxL///mvx+SnnJCQk4K+//kKzZs2MTohijY8++giFChXC1KlTHfpvp1arxfnz51G/fn2rJ6YiorzH6RNkDB8+HJGRkUhPT0doaChat24tPbZ8+XKdrioHDhyQgoT8S+wGUtDYa8yWNcxVtvSnbLcXU/8Qqq3QWdKNUNwuDyPy782FLfFmXj9s6YebFStWGD3OzZs3cfz4cQC6XT7lYUu8DjVjEuXLIKipbInXA5gPW/qVLaVuhA8fPgQAi7oRmqtsib+PdevW4dq1a9KxjVW21FSbbKlsyR/Lq27fvi2FlrZt2yIiIgJ3795VdQxzlS0AKF26NKKjoy063rNnz3D79m2zVW1jYevgwYMAIIUtcWbbnKhwkHobNmxAamqqVF21l8DAQAwePBjnz5/Hjh077HpsufDwcCQlJSEkJMRh5yCi3MfpYYusl5vD1rfffmt0X/3KhRqmwpal60uJ5GHL3KeZ8gqI/hgkwHxlS78bof5NvhgElI6TmJiI5s2bG8zUKe6TkpIiXYeacWtqKlv6YUse9ERKYdeSboRitcOSboSWjNmSV9Pi4uIAGF9ny5rKlvw1Nha28ltlSxAEREdHS0sYdOjQAQAMxtyaExsbCxcXF+l3raRUqVKIjo62qMIQGRkJrVZrcdjS70Z4+PBhAM/DVrly5dC8eXP8888/Ob72Epn3+++/w8PDA++8847djz169Gi4ublh6tSpdj+2SFxD1NS4dCLKfxi28jB7TZBhDXPdCE1RO5GFnDzoPHjwQOcTcFvCljnym3L59Yo30MbClhhA9CtbasKW/rlEYmAQuxECtoWty5cvY926dTrPMRa2xPbKJ+Mw1Y1QnPFSDFvy2QjFsOXn56dzbAAICAhQ7EZoasyWvE3ysGVJN0JTH1KI12JJN8L8Vtl6/PgxMjIyUKpUKQCQZoHdtWuXquPExsYiICDA5N95qVKlkJKSYtEC9JZMjgFAWl9Rv7J16tQplClTRmf8TM+ePZGcnJwj1S1BELB69Wp8+OGHWLNmDdf6MuHu3bvYv38/XnvtNakKbk/lypVD7969cfDgQakngb2Jx23WrJlDjk9EuRPDVh42ZMgQxe2OrmxZMhuhKfKbVWvOLSpVqhRKly4t/WxN2LK0ymassiWGKWM3j+IEL1qtVrpucdySnCVhKykpSaeyJQ9bYmhU89rqdyPs378/evbsKXW9A56HB/3uifLxViJT3QjFICWvbIntF29AxOfIfydBQUGK3QjllS35taenp+uEyLi4OGmyDHPrbF27dg1+fn6YMWOG4utlqhuh+FqmpqZCo9HoPEcMwObCVkpKiuIEDrmB+KGGGLaKFy+Ohg0bYteuXaqWXIiNjTXZhRCA9J62pCuhpWHLy8sLpUuXxs2bN6VtKSkpuHjxIho3bqzz3D59+sDHxwdz5sxxePiZOHEievfujUWLFqFXr14YNGiQw3sl5FViGH3//fcddg5xbUJHVbeOHz+OihUrmpzMhYjyH4atPMxY3/Lc0I3QFGMz91nCntdlqrKlPw7QWGVLDBj6a5WdOXNGZ7HtSpUqGVS25PuIIUtN2JLPpGhrZSszMxOnTp0C8HzWOfn1GetGaC5sidUgMazJx2zp/x0oVbbEm5LExESLJ8jQD1vycXMipcrW3r17kZSUZLQLrKVTv3t7e+v8niytbL322msIDg6W1m7LTfTDFpA9vikuLg6bN2+2+DiPHj0yOjmGSDyHOMulKZaGLfE58oXhw8LCkJWVZRC2/P390bdvX5w5c8ZhFQ4ge1zrd999h5CQEFy6dAmdO3fGsmXLVC/OXlCsWrUKRYsWRZcuXRx2jlq1aqFbt27YvHkzwsPD7XrsuLg4XLlyhV0IiQoghq18KDfMRmiKo8ZsqeXu7m40bOlXiIxVtsSAoX+c77//XuoeBwCNGzc2CFvu7u4Gi3JbU9mSn98eY7bk026bmyDDXDdC/cqW0gQZIjG4iOuFAc/DVlpamkUTZADQed3VhC0x5IjBydi1yP82ChUqBDc3Nzx58gTA87AlZ0nYevr0Kfbv34/09HSsXbvW6POcRSls9evXDz4+Phg3bpxFM4FqtVo8fvzYbGWrYsWKAHRDvzERERHw8vKSxpKZUrVqVTx58kTqWnr69GkAQKNGjQye+/HHHwMA5syZY/a41po0aRIEQcCyZctQq1Yt/PXXX6hRowbGjx8vffBB2c6fP4/z58/j3XfftalnhCW++OILAMC0adPsetyTJ08CYBdCooKIYSsfys+VLTFs2WPNIlNhS7+N5ipb+iFJ3qWxWrVqAGAQttzc3LBr1y6d189c2NJvv8hU2Lp48SJee+01g25ZxsKW/MZZ/F5/jIT4+sinmTc1QYa8sqU/9btIvGGWd1kUQxoAiybIAKDTDfLx48eKa6EpzUZ4584d6XulddWUwpZGo0GxYsWkgJeQkGDQ5dKSsHX27Fnpe3HRU2fIyMjAlClTDMYrKYWtkiVL4vvvv8etW7d0Fts25unTp9BqtWbDVuXKlQHAogrflStXEBwcbFBZViJWv8TqlhholMJW7dq10bZtW6xfv17VNPSWunv3Lv755x9069YNL7zwAoDs4L5u3TpoNBoMGjTIYctn5EWrVq0CAId2IRQ1a9YMrVq1wh9//KHz/wRbiZNjMGwRFTwMW/lQbh+zZUtlSzyX0gK6aqkJW1qtVjq30pgt/Zs9+Y2SGIDkYSsjIwNubm7QaDQ61Sp52Priiy+kxVjFcxmrbBnrRqjVajFixAhs27YNK1eu1HlMPmZLHjrkYUusbOmHLTFwyMOW2sqW/DUeNGgQgoODAehOLiG/Hvk+pipbMTEx0j5Pnz41Gbbkvyd5l0ix3Rs2bEBAQACOHDmiGLaA7PFLYth6+vSpTkAELAtb8r/nCxcuAMj+3f3zzz9WLTpuraVLl+LLL79Ejx49dLpRiWFLf6zJJ598ghdffBFz5sxBRESEyWOLvxdz3QjFypZ8fJUScYybpest6Yet06dPo0qVKggICFB8/ieffILMzEwsWLDAouOrsWrVKgiCgIEDB+psr1u3LsaPH48LFy5g1qxZdj9vXpSVlYXVq1ejYsWKOdYF74svvkBGRoZdfwfHjx+Ht7c36tata7djElHewLCVD+X0bIQ5GbbE67LHuBZ3d3ejbVGqvok35kpVIFOzGoo320qVLX3ysNWnTx/UqVNH+jkpKUkn1FlS2Xr27Jn06az+RAZxcXFSsJEHL/3Klqenp0HXOKXKlqmwpTRmS97+pk2bSt8rrSUmfi+vbIkB0VTYio+PV5xF0FzYEl+PX375BfHx8Vi3bp3JsBUTEwNBEBAfH29V2BJ/R1WqVMHVq1eRnp6OlStXolu3bhg2bJjR/ezt77//lr7fuHGj9L0YtoKCgnSe7+rqip9++glZWVn49ddfTR5brDjqH0Ofj48PSpYsaTZsXbt2DYIgWBW2EhIScPXqVcWqlqhr166oUKECFixYoGoSEHMEQcDKlSsRGBgoLWYuN378eAQHB2PixIm5cvxeTjt48CDu3buH3r17W1TBtIfOnTvjhRdewMKFC6Vup7bIysrCyZMn0aRJE5v+/SOivIlhKx/KqcqWeB5xrRpLKQWZ7777zqJ9xeuSjxWylpoxW8DzG3NLZiOU3xQoVbbEMVv65MeRB1r5ueTtFxmbjTA9PV1qr/6NyuPHj6UbX3lokq8vlJKSAh8fH4PfmbVhKzk5GYIgwN3dXedaCxcurLPf5cuXcfnyZYOwZaqyJb6++mFLbJd8LJhS2JL/TYlhSwwIN2/eVFxnC8ju9paQkICYmBibw9arr76KrKwshIeHY+vWrQCAf//91+h+akVHR6NOnToYNGiQwWMZGRk4ePAgXnrpJRQuXFhnDa3o6GgUK1ZM8b3bokULVKpUCZs3bzb5IY+lYQvIfk3Nha0rV64AgMVhq1q1atBoNLh48SJCQ0MhCILB5Bhyrq6uGD58OB4+fIi//vrLonNY4ty5cwgPD8d7772n+Hp6eXlh/vz5SE1Nxbhx4+x23rxK7ELYu3fvHDunRqPB2LFjkZycjLlz59p8vDNnziApKQktWrSwQ+uIKK9h2MqHcmrMFgD8+OOPOHLkiKp99UNGqVKl0KRJE5P73L59Gx4eHtLNnHwSBGuZqmyZClumApDIkrBlrrLl6uqq070vMTFRJxxY0o0wPT1dcZybVqvFkydPpDE44gQPgGFlq1ChQgavh/izfNyXJWFLnHzCw8NDp4KlPwFHzZo1UbNmTZ3rsXTMlrVhS6myJVZ0njx5olghA7JnMAOA/fv3Iysry6qwFR0dDW9vb7Rs2RJA9g35/v37pWuwxxhFAFiwYAEuXbqEpUuX4uLFizqPXblyBc+ePUPz5s3xwgsv4NKlSzrtk4/XktNoNHj99dcRFRVlcryZGLbks3QaU716dTx69Ejnd6Lv6tWr0nMtUbhwYdSoUQOnT5/G0aNHAcDs/3cGDRoET09PLF682KJzWGLDhg0AYHJh3jZt2qBbt27466+/HDJZRkZGBk6ePIljx47pLAKe26SmpmL9+vUICQlBzZo1c/TcPXr0QIUKFfDzzz/bvMD1tm3bAACvvPKKPZpGRHkMw1Y+lFOzEQLAgQMHVO+vH3A0Go3Z9pYsWRIajUYKkfYIW6bW2TLVjVCpsqV/MywPEraELXmwi4qK0pl4w5JuhPLKljwYipMViGNwjFWoxMqW/uskvj7ykGbJBBnyRZ7l9CtbImPdCC0Zs1WuXDmdsCUfC6a/zlZaWprODVVCQgJSUlKkMBkXF2e0G+Hrr78OV1dXTJ48GQCsClviLH3iZAnLly+Xui9lZmbabaD+vn37pO/FG0CRGJTq1auHGjVq4NGjR3j8+DEEQTAZtoDs1wAANm3aZPQ5aipb9erV02mTErGyJY71s8SLL76IW7du4bfffkORIkV0uq8qCQwMxGuvvYaDBw/i7t27Fp/HlI0bN6J48eJmqxw//PADXFxcMG7cOLv+/3z9+vUoX748XnzxRbRo0QIlS5bEjBkzcuX6Xlu2bEFiYiL69OmT4+d2d3fHZ599htjYWCxbtsymY23fvh3+/v6cHIOogGLYyodysrJlzVgGpbBljjiZhHjTYeoTb1vaIlI7Zks/bMkrW+LNuRiExKqM2srWtGnTdAKBpWO2xL8F+ZTmYpc5MWyZq2y5uLhg1KhR+O233wA8f32MTayRmZmJkydPmqxsyelXtkT6iwOL12xuNkJ3d3cEBQVZXNkSg42/vz+A7GqSfPbGJ0+eGA1blStXRpMmTaRKkDVhKzY2FoGBgahatSo8PT2lDzHeffddANBZH8pa4u+kdevWcHV1laaiFontf+GFF6QqQnh4OBITE5GSkmIybLVs2RIBAQEm19wSQ7CasBUWFmb0OZcvX0bZsmWNBnUlb7zxBoDs5Q26d+9u0cyo77//PgRBwJo1ayw+jzHXrl3DxYsXpYBuSu3atdG/f3/s378fu3btsvncADB79my88847yMzMxNdff43vv/8egYGBGDNmDHr16mW3Cqq9rFq1Cq6urujZs6dTzj9o0CAUK1YM06dPt/q1efjwIU6dOoVOnTqZHNtLRPkXw1Y+FBcXhxMnTjjs+PLKljXTE+vf4FgStlxcXODi4mLXboSA8bBlqhuh0ppb8n+I27dvj3/++cfgWNZUtvRfX3koUtuNUB62xNevdOnSBseVB7onT55I4WHmzJkYPny4zjWJfHx8dMLWF198gRdffFG6SbQ2bMmvx8vLS6pGmgpbjx49gp+fH/z8/MyGLfH3Jl5/hQoVAGRXtuRTfpsKWwCkihRgW2XLzc1NmnHNy8tLmuraHhMl3Lx5E8+ePUOTJk0QHBxsUDW6cuUKXF1dUbVqVSlsXblyRXHad31ubm547bXXEBYWhtu3bys+5+HDh3BzczOY2VKJGLbOnDmj+Hh8fDwuXLhgtjKlr0uXLujcuTOqVKmCr7/+2qJ9OnfujMKFC+u8p60lTjrSvXt3i54/ceJEeHp6Yty4cTZ/gLZt2zaMHj0atWrVwvnz5/Htt9/iyy+/xIULF/Dmm29i3bp1GDp0qMMnV7LUo0ePsGPHDnTo0MGigO4IPj4++OSTTxAZGWl12N65cycAOHQxZiLK3Ri28qE///xTZ3C7I+R0ZUt8nnjDYY8ZopTaIlL6xLtPnz4YP368YsAUb9pTUlKwd+9encdsmSBD6VxVq1bF+fPnLZ4gQwwJ8rAl3ryLa4ApdSNMSEjA06dPdaafF+m/PsWLF9cJW+vWrQMA6bUwF7Ys6UYovn6enp46YUt8zeTBzNfXF35+fkhISJC6LpqqbCmFLbES4+bmhoyMDOlvTilsyadz1g8l5sLWs2fPkJCQgMDAQADABx98AI1Gg1GjRklrTtmjG6E4lXvNmjVRr1493Lx5U+dv4sqVK6hSpQo8PDykSSfCw8MtClvA8zFIS5cuVXz84cOHKFGihEUzyhUtWhQ1atTAgQMHFG/+jx07Bq1Wi9atW5s9lpybmxu2bduG69evo0qVKhbt4+npiZdeegknTpyweRr+DRs2oEiRImjXrp1Fzy9XrhxGjBiBc+fOmbzZz8rKMhnGrl+/jt69e6No0aLYunWrzu/Sx8cHa9euRadOnbBkyRKjv7+c9scffyAzMzNH1tYy5ZNPPoGvry8mTZpkVXVr+/btADhei6ggY9giq4g399aELf2bVUvGbAHZ1a0dO3Zg+vTpdhvUbSxs6U91DgBHjhzBjz/+iAcPHhg8JnYtVHrMlsqW0j/uTZo0wQsvvKCzv6nKlnhDrRS2qlSpAldXV52xYGJoEisUYgCR0w9LJUqU0Dm+GGLEvw/9sKX/ultS2ZK/juJaZe7u7lJYl4/JEitbgiBIoUn+uLGwJQbLhIQEqfonTsAg/m7Nha2yZcvqPCae11jYEkOcuNhvr169EB0djcmTJ6NcuXIA7BO25LP3ie0VJ8nIyMjA9evXpZBVqVIleHp6qgpbnTt3RsWKFY1Olf7w4UNVFYoOHTrg/v37UruB55VaceyZ2rAFWP7hjly7du2QkZGheuZVuXv37uHkyZPo0qWL4t+QMV988QX8/f3x1Vdf6bxP5dzc3NC+fXvFx549e4aePXsiISEBa9euRaVKlQye4+7ujtWrV6Ns2bL47LPPFP8/lpO0Wi3mzp2LwMBAvPXWW05tS9GiRTF69Ghcv34dv//+u6p9MzMzsXPnTjRu3NiiiWGIKH9i2CLVBEGwa9jS/6S7bdu2ivuJN0mff/65xec1t4CqmrAlkocKkRiKlLo3itcrBgP5osb6TE2QIRJv3i0Zs5WUlCQFU/mn8uK02pUrVzZ4DcSwFRkZCcCysFWyZEnpugAY3BSamyBDXnWSU6ps6YctkVLYArJvcvXPYUllS/xdihMwiDeg+q8xoNuNUAxI+u1Smq0ReD5+TqxsAdnjmlxcXODr6wtfX1+7hy39CShu3ryJzMxMKWy5uroiODjY4m6E4j7iVOnr16/XeUwQBNVhq1OnTgCyq0GCIGDcuHHw9vZGgwYNsHDhQlSsWFHndXckMcjoV63VEMezvfnmm6r2CwgIwPjx4xEZGam4wLL4XhNnr9Q3YcIEhIaG4ssvv0SHDh1MnmfOnDmIj4/HqFGjVLXR3vbs2YNr165h0KBBiu+3nDZy5EgULVoUkyZNUvVv3q5du/D06VO89tprDmwdEeV2DFukmjxsGfuk1RT9fzw1Go1O8DC29o38E2lL/8EzNz7E2CB1U//Ay6c7F5kKW+KxNBqNFBQsqWy5u7tLXYPkQUEMgpaELfnaUfKQePPmTfj7+6No0aIGwUccs3Xjxg0AzxeDlXNxcdFpv3gTLb42xsKWfjdCcXySsa5l+mO2gOzrVwpb8tfIz89PCi9RUVEGj6sJW2JlSwwdSlUJf39/tG/fHk2aNJG6/onc3Nzg4eEhha2MjAydMXLiZC9iZUtfuXLlFMNWcnIypk2bpjNFuykREREoVqwYAgICpMrW+fPnASivWVWzZk1ERkZKwdxc2AKAgQMHwsvLC3PmzNHZnpSUhNTUVFVhq2PHjihdujTmz5+PqVOnYtq0aShfvjwuX76MpKQkTJ061ewkE/ZSp04dlChRAnv27LH6GBs2bICnp6fiQsbmfPLJJyhTpgy+++47nQXIAeVqumjXrl2YPn06XnzxRXzzzTdmz/PGG2+gW7duWLt2rTTWyBl+++03aDQaDB061GltkPPz88O4ceMQGRmJX375xeL9fvvtN7i4uKB///6OaxwR5XoMW6SavStbGo0Gbdq0wZAhQ3Dy5EnFag6ge0Nu7rzu7u4YMGCAydnRgOcTROgTZz9UYmrMlqnKFvC8KpOWlqZ40y6/eXRzc5O6V8rHNImVEvn+xroRytsjD1u3b99GxYoVDY4DPK/AiGHL2NgWMTB5enpKoXblypUALK9sHTx40GSXUP2p38VrTE1NNVvZEmdaFK/D2rAljmszFbYAYPfu3Thx4oTi303hwoWl13XgwIEoU6aMVFVSqmzJiWFLv6vtd999h3HjxkkLIZtz/fp16VrKlCmDgIAAabY/pbD1wgsvQBAEafynJWErMDAQvXv3xokTJxAaGiptVzPtu8jd3R0jR47E3bt3MX78eNSoUQPnzp3DvXv3cPv2bWmmxpyg0WjQrl07nDt3zqrJeeLi4nDgwAG0b9/eaJdZU7y9vfHtt98iNjYW06dP13nMWNi6e/cu+vTpgyJFimD16tVGq/j65syZg0KFCmH48OEmJ3VxlMjISPzzzz949dVXFbs8Osunn36KSpUqYdKkSRZ1s7x58yb+/fdfdOvWTXHcKxEVHAxbpJqtlS2lsOXq6or58+ejSZMmRm8c5Texxs4rLgr766+/YunSpTo3j0qqVq2qWFHQaDSqxlWIbbYkbKWmpiIhIcFg1jrAsLIldqls06aNtF2sbCmtG6UftuRT5OtP/S52sZSHEPlEF9evX4enp6fRQCpel4+Pj3Qtn332GWJiYgwG64s3mPqVLTc3N5Ovs1Jly1g3Qv3KlnhjbypsiaFdDFulS5eGm5ubNEGG/Dhi109TEzwYC+iFChVCcnIynj17hlWrViE1NVWaRET8HZkKW2lpaTpVSkEQsHz5cgDZwdnYrH0i8XrEKqVGo0GDBg1w7tw5ZGVlSWFLvkBwgwYNAGRXxHx9fXX+3kz58MMPAQCrV6+WtlkTtgBg1KhR+N///ofevXvj33//hZ+fH4oXL24wLi4niO/FgwcPqt73n3/+QVZWlsWzECrp168fatasiZkzZ+rc7MuXKBDfd+np6XjnnXcQExODZcuWqQot5cuXx6RJk3Dz5k1p7bicNH/+fAiCgI8++ijHz22Kl5cXZsyYgcTERIwfP97s88XrEGdwJaKCi2GLVNNqtdLNvTXrXSmFLf3jKz0urygZG/9SsWJFCIIg3fBZwljlxtS4Lf1zWtKNEMi+9sePHyMrK8ts2HJ1dcXPP/+Mffv2SYvGAs9Dlrx9xmYjlLcnKSkJgiAgMzMTiYmJ0ppS8qpZiRIlpNf27t27KF++vNFwIQYmb29vncHfSjNh+vj4wM3NTepmaMn6RvrXox+20tLSdF5bY5Wt9PR0aDQa6XrlxxJDuxi2ihYtCl9fX6myVbx4cQQEBCi2R41ChQohKSkJly9flrYdO3YMwPPKlrHxhUqTZISHh+Phw4dSIDIXAMR1uuRdQhs2bIiUlBRERETgypUrKFGihM61NmzYUPq+du3a5i/y/zVu3Bjly5eXpjkHrA9bbm5umDRpElatWiVVYp3l5ZdfBmDdQu7r16+Hi4sLunXrZvX53dzcMGXKFCQnJ+tMWy8PW+L7a/To0Thx4gTGjh1r1QQTI0aMQP369fHTTz9Z3E3VHhITE7Fo0SJUrVoVHTt2zLHzWuqNN95Ahw4dsHz5cmzZssXo81JSUrBkyRIEBwdbPPMkEeVfDFukmnydLWuYW2fLWNiSd2nRH7cgsmbRSP3FXUXGKg36ihQpoqoboTg7nrmwJY5la9OmjU6QUKpsGetGKA/DgiAgJSVFeu1MhS1xFj9TM2iJv0cfHx/07t1buqkQZ7iTX5OrqysKFSokjQeztEuT0myE3t7eSE1NlRZcFhmrbAHZv0v534Z4LHnYcnd3h4+Pj0HYko/7syVsJScnS+OfAODq1asALBuzBeiGLTFcffzxxwBg9oZYDFtiN0LgeZg6deoUwsPDDarApUqVkiagECersIRGo0GnTp1w69YtaXISa8NWblKlShWUKVNGddiKiorC9u3b8corr5idsMecbt264eWXX8aiRYtw5MgRALphKy4uDitXrsTcuXPRpk0bfP/991adx83NDQsWLEBmZiaGDh1q8xpflpo/fz7i4uIwduxYi5YIyGkajQZLlixB0aJFMWDAANy9e1fxeePGjUNcXBw+/fTTXHkdRJSz+H8BUk0QBFy4cMHq/fWDmqVhSz4NurHFlK0JW+Jsc/r0b36NHVsetpQqffphS6yimAtbckphS6mypT+rn3izK3YFTExMlNbUUgpbxYsXR1ZWFtLS0hAbG2sybMnDj4+PD6ZNmwbg+SyG+s+Tn8cela2UlBSd10WpsiXe6Ojf5Irnl4etokWLQqPRwNfXF/Hx8YiNjbV72BJfm4oVK+LBgwdISEiwKmydPn0aAPDaa68hKCjI4rAlr2w1adIEQPYg/vj4eLz44osG+61duxaTJ0/G2LFjLblMg2OfOnUKQP4IWxqNBi+//DIuXbokfWBiiYULF0Kr1dqlW5xGo8GCBQvg6emJDz/8EImJiTpha+/evRgyZAjKli2LtWvXWvX/Q1GTJk0wfPhwHDlyBLNnz7a57eYkJydjxowZKFOmDPr27evw81mrXLlyWLZsGeLi4vDGG28YfMC2bds2/Prrr3jppZcwZMgQJ7WSiHIThq0cNmDAAGc3wWYlS5a06R9xeXcuwDBsDRw40OTjIqWFcC2tmMiFhoYqTm8u3vy2aNECr776qsHAdFFAQACysrKQmpqKbdu2GTyuFBiA55NGyBn7FFQerMRAJQ8XYnjQD1ti9USsUCQmJkpdjfTDloeHhxQA7969C61Wa1FlSzyn2AVNXMNL5IiwlZGRgcTERJ3rlb+evr6+8PDwkMaq6F+HRqOBh4eHQdgS9719+zYyMzNRokQJnbBl7TTU4gQZ4msjVoquXbuG2NhYKbAqUQpbFy5cQFBQEEqUKIHatWvj8uXLJteqUwpblStXRnBwMP777z8AuuMCRbVq1cKECRMs7lIratq0KQBIxxbDVl5fa0jsSnjo0CGLnp+QkIAFCxagUqVKqqqDpgQHB2PSpEkIDw9H06ZNdcbGDRkyBFqtFn///bddXuupU6ciODgY48ePlyZTcZSff/4ZDx8+xBdffGH1hxo55fXXX8fEiRMRGhqK5s2b4/Dhw0hPT8fq1avRv39/+Pv74/fff8+x2TKJKHdj2Mph+WFWohUrVmDWrFlW7btu3TqzY7bkY0UAKC7sCyhXhsyFQKWxXIULFzaoxgDPw4i/vz+2bt2qs3CtnLe3N7KysvDDDz8oPm4sbCm131iwlN+IiyFQfgMsTkBhrBuhPGyJlS3x/GIIcnFxkcKLGApM3bCJ5xL3EUOJscqW0vT15sj3Ec8nvhbx8fE6j8tvbMqUKQPg+Qx64vgt/XYphS1/f3/pb6548eLw8PCQzmNLZSs1NRW3bt2Cm5ubdNN+9epVxMbGGq1qAc8XSRbDllarxaVLl1CnTh0A2eOpkpOTpSnulVy7dg0BAQEGSyGIFYRq1arZdWxJ9erV4eLiIoX9hw8fwsXFxeR15gXi783Ymlb6pkyZgtjYWEyYMMGuN96ff/45JkyYgIiICGRlZelMLf7zzz9LlUVbFSpUCKtXr4ZWq0XPnj11liywp0ePHmHq1KmoUqWKqvG2zvTNN99g3rx5uHnzJlq3bo1ChQqhd+/eSE9Px8qVKw3W2yOigothK4ep7Y6T23Tq1AnBwcFGZ6izhLluhJZSqgyZC1tqPl0Ww5YYToxVHsRzGuu/L69WycOQpWPC9M8tdomT3/iLgUmj0eDw4cP4448/pMf8/Pykf/iTkpIMuhGK/83IyJDOc/v2bZ1zKdEPUb6+vnB1dZWqGPrPk1e2zK1/pn9d8uPIf+/GfifiZAoffPABAChOTGAqbInE6xcfsyVsAdkz+5UpUwY1a9aUfn706JHJEOLj44PAwEApbEVGRiIlJUUK0LVq1QJgetyWfNp3uXHjxmHdunXYvXu3VVVhYzw8PFChQgVcu3YNQHbYKlasWJ7/pL9KlSqoVKkStmzZYnYc05kzZzBr1izUrVvX7ussaTQaTJ48GTExMXj48CF69uwpPWbvsBISEoLp06fj6tWr6Nq1q+I6g7b64osvkJCQgB9++MHiqnduMHToUJw+fRpff/012rZti6+++gqRkZHo2rWrs5tGRLkIw5YZX331lc7Ptv5DYOn0yc7i6MG8giCgffv2BttMefXVVxW3WxO21NxQijfd4qe58irKTz/9ZHBOcSpuffKbMnnYUhNY5ecWq03ykCoPJS1btkT9+vWlnytWrChVvhISEgzClhgksrKypPOIVRJTgVC8cRb30Z/xT/xbUqps6XclNUb+9yi2RV4R1O82+ffff2PChAlSZatv3764c+cOevXqZXBsT09PaVbDtLQ06XWQB0ExbIldJG0NW9euXUOZMmWk7nwRERFmK1uA7sLG4nhJsbIlBjdx+nZ9SUlJePDggeLi1G5ubnj33XcVu9Haqlq1arh+/ToEQcDDhw/z9HgtkUajwTvvvIO7d+8anVgHyK4Mi9O8L1682GEhMyAgAH5+flLgnjBhgkP+Hz5ixAiMGTMGR48eRatWraSKpT0cOnQIS5cuRfv27fHOO+/Y7bg5pUGDBvj222+xa9cufPfddzozehIRAQxbJm3bts1g0Lj8Jju/8fPzw+jRo00+R36DP3fuXIuPLd4AaLValC9fXlr7CDB+kygy1iZruhGqGWsm3nSL4UR+Y//pp58CAJo1a2ZwTP1xefI1wawNW/IwpXRjrj9+TR4KKlWqJL1WSmFLHnzUhC1xbTH56yK/0RC78NlS2ZKTV9BE+h9evPnmm5g8ebL0d6rRaIyuySRWtuTTvgOOqWzJ21ymTBkUKlQIZcuWxfnz55GYmGhR2Lp37x60Wq00fbw4HbsYtsLDwxX3Fd9rSmHLkapVq4bU1FTcv38fMTEx+SJsAZAWUxbXSdO3bds2NG3aFHfu3MGiRYvQuHFjh7epXLlySExMdNi6WBqNBtOmTcOUKVNw6dIl1KtXD+PHj7docV9T4uPj0bdvX3h7e2Pu3LlW93IgIsrNGLZM6NKli8E28QYyP8rKyjL4BLZixYqYP3++4vONLRh86tQpgzVS5GFL/rM569evlxYT1acUtsxVriwJW3/++ScAw8qWPCy4u7vjxo0b2LZtm8E569WrJ31fo0YNvPLKK9LP8rClNI7IGKUFeeVMha2KFStK19K7d2+pi6F+ZUt+HkvClvi7NBa2xOsT/6bE6pr+Oc356quvMGjQIOlnU5UtNXx8fJCSkmIQtuRtE6uI4utg7cQw8tdFDH81atSQuv6Z61JatmxZZGRk4NGjR1KoEkOWuBaYsbAlduXL6bAlnk8MlPklbDVs2BDVq1fH8uXLpQ8ugOxxR71798Zrr72G9PR0bNy4EX369MmxdilNGGRPGo0GX3zxBQ4cOICqVavixx9/RIUKFTBgwACcP39e9fG0Wi0GDBiA27dvY9asWYrdXImI8gOGLT3ymZ0Aw/FEeX3MgSmZmZk6N5Nubm64desWhgwZIg2kl78epqYp1w8E4n7iDbqln2CaqiSY636oxJLfnzi4XLzpFtf3En8Wu1xVrlxZMTSIN+gtWrRAeHi4zo220rpR+tq2bWswwN1YiBSvR7/rivw8JUqU0KnWhIaGAngeWuSPiRUYcT0oSypb8rbJXw+xcif+zuXjv9TMbvfdd99h8eLFBm0EbOuWW7RoUTx58sSiypb4O01MTLTqXPLfj9jFsXr16tI2cxPniAHt7t27CA8PR6lSpaTfn0ajQc2aNREeHq74nlBaYysniOc7evQogLw97bucRqPBl19+ifj4eAwbNgz37t3Db7/9hpo1a2L16tXo1q0bLl++rLMQeX7SqlUrnDt3Dhs3bkTTpk2xfPly1KtXD506dbJ4lkZBEDBmzBhs3LgRPXv2zDOTYhARWYNhS2bevHl477330K9fP6kaoR8KxL7xlvrpp58QERFhU7vEmyVT7DHLYVZWls6Ns/zaxZtM+eBoY4HJ1dXVoHIl/izeDNpjXIF8kWORvHuivhUrVpg8rzgbm3izLU5fLVZV3NzccP36dZw5c0ZnP/0Flt988018/vnnWLlypcE5xBBkKvTt3bsXJ06cMNi+c+dOHD58WGfbsWPH8OOPPxrcSMvDjJ+fn2IVULxO8Ua+du3aUnc2Nd0I5deiVNkSnycPW7Z0F5Ifx5ZP8wMCAhAXF4e4uDgAz8OWfAZG8VzihxDWtlspbMkrw1WqVDG5v3xGwitXrkhVLVGtWrUQFxeHBw8e4JdffsHMmTOlx5Smfc8J4t+k+DebX8IWAPTp0wfdunXD2rVrUbZsWXz88cfw8PDA2rVrsWnTJul3nF+5urrijTfewKFDh/Dff/+hR48e2LNnD1566SW0atUK27dvN/phWHp6OoYNG4ZZs2ahRYsWWLZsGbsPElG+VqDD1sSJExW3L1++HP/++y+A5zfcoho1auD27dtYunSpRecYPHiwwQ1rv379LG5jRESE2RsxILtKIu++pu+nn34yOXtW3bp1sXfvXqPdpDZu3Agg++ZeZCwwaDQag8f0uxHaY+YzpZtH/eAj17dvX5MhZ+vWrYiOjpaCSenSpXHnzh0sXLhQek6VKlUMqkjyrkRA9u9i2rRpqFy5ssE5xLBlrrKjdPPRsWNHtGzZUmdbkyZNMG7cOIPn608xr99l0dXVVeqC17BhQ4waNQqLFi3SGTvk5uam0/XPWBvFMAXoVrbEMCf+zu11sy2fUtmWbr1FixZFVlaWNM29+HuVv9/0Z0CUV6PUUOpGKB8Pamxhbf19Tpw4gaSkJIOwJY4Lmjx5Mj799FN89tln2LlzJ4DsMZFFixbN8YH7lSpVgqura74MWxqNBn/99RdmzZqFAQMGYOHChYiIiECPHj0KXHBo3Lgx1q5diytXrmDQoEE4efIkXn31VdSpUwfz58+XFl1OTU3Fpk2b0KRJEyxYsADt2rXDjh07rF67jogoryjQYeubb77R+Vnpkzjx02+58uXL60yCsGHDBqPnUKqkLFu2DAkJCUYH7suJN6pffvmlzvYFCxYYnCcsLAwhISGKxxkzZozJm4Ddu3ejVatWRitbSpo0aYLevXsrtlke2tq2bSu9Dkpdz6w1YsQIg21KAUdOvFkePHiwwWNeXl4GoaRs2bJmq3BqpkKWLyDsSPJQ6efnh0KFCmHYsGHSNn9/f+n36+rqipkzZ6JZs2Y6s9IFBgaa/BtQCq7yG3oxUIp/w+JU5WKXVGvJqwa2VBDEarA42YkY3itXrozAwECdYDt+/HiMGjUKU6dOtepc8naK09I3aNAADRo0QOPGjc1WzMX/V+zevRsADMJWq1atAOhOWrN48WI8e/YMoaGhaNSoUY6HAHd3d1SuXFn6/2p+WGNQzsPDAyNHjsTSpUsxePBgh4+Zyu2qVauGxYsX48aNG/jss89w9+5dDBs2DKVLl0ahQoVQpEgRdO/eHVevXsXXX3+Nf//9t8C/ZkRUMFg32jsfql27tjTLlD5zg/nlwWHw4MFYtGiR9LNGozG4ydFoNCYrBvKxU+LiqpMnT8a7774rTendtm1bpKeno127djhy5IjBmCi1xE8X1YQgNzc3rFq1CrVr14a7uzs+//xzg/aXKVMGmzZtMhi/Y2nYkFdN5Jo0aYJKlSoZbP/uu+8Mtm3dulWawa1EiRKIjY1V7FZnLVPVNH3i62ztrHbWECtMc+fOxZ07d7B161aj1+/n54cWLVrg6NGjZiefmD9/Pj755BOMGTNG2iZ/r4hhTLzZrlevHvbs2WOyAmsJ+TgtSz6wMKZv376YMWMGkpOTATzv9ubh4YFLly7pfOJeuHBhna55aokhVj47oqurK06fPg1BEMwGejGsiV1Y9cNW9erVERISgtDQUPTs2RMxMTHYsmUL9u/fj7S0NDRr1szqttuievXqTpugg5yjXLlymD59Or7++mts2bIFBw4cwJ07d1C4cGE0bdoU77//vk3rNBIR5TVOr2zNnTsXlSpVgpeXF0JCQgzGpOg7ePAgQkJC4OXlhcqVKxudKc+c06dPA8ieee6ff/7BxYsXTY5PadiwodHH5BUxpYqTn58fGjRogFmzZhk8BhjOeujq6opdu3ahd+/e0k2VRqNBvXr1pMqVr68vPDw8pMVa5WsdybVt21ZnimL9KaaPHj2KqVOnSt2k5BUp+XWJExQodTMcP368zg23vLLVsGFDFClSRLrxFsOWpWFDDJtyd+7cwf79+6HRaNCsWTOdmeqUQuyrr74qBUEgu2Jj7axySuRjfMx1MxOvJycX7pQHK3EMkqkqh/g39ejRI5PHbdiwIY4eParTPUxe2VKqFLdr187sNOeW2Lx5M77++muzlUxTqlSpguvXryMoKAjvvPOOzu8kKCjIroHczc0NV65cMRh/6eLiYtGkLYUKFdIZq6YftjQaDdasWYMpU6Zgzpw5GDBgAJ49e4aBAwcCgMESFjlFXAsMsK0KSXmPr68v3n//fSxevBg7d+7E33//jbFjxzJoEVHBIzjR2rVrBXd3d2HRokXC5cuXhU8//VQoVKiQcPv2bcXn37x5U/Dx8RE+/fRT4fLly8KiRYsEd3d3Yf369RafMz4+XgAgxMfHq2prVlaWkJ6errMNgABA+Oeff4SpU6cKXbt21dkOQEhKSjJ6zMmTJwsAhCNHjujsZ0pCQoJw+fJl6efExEShf//+wtWrVwVBEIRGjRoJAITRo0cLWVlZBvtfv35dmDVrltFzzZs3T3ps586d0vbHjx8L5cqVEzZs2GC0bf/995/w6aefClqtVujfv78AQOjcubMgCIIQGBgoABB+/fVX6fkTJ0402g5x+59//iltO3r0qDBz5kyD56alpVn02jnK/fv3hc8//1zYtm2bcOfOHZPPnTp1qgBAqFSpksPbJb4m8vfT2LFjBQBCuXLljO53//59oXLlysLixYtVn3PLli3SeTdu3CgAEPr06WNV+3NKamqqoNVqnd0Ms9q3by8AEIoUKWK2vcnJyUJAQIAAQAgMDBTS0tJyqJW6/vvvPwGA0LdvX6ecn4gcJClJEIDsLxP3OUR5gbXZwFJODVtNmjQRhg4dqrOtRo0awhdffKH4/LFjxwo1atTQ2TZkyBDhxRdftPic9nxBDx8+LLz55psGIezbb78VAAhDhw41eVOk1WqFR48eST9fvXpVOH36tE1tWr16tQBAOH78uMnnGQsn27dvFwCoek2VjBs3TgAg9O7dWxAEQVixYoUAQLhx44b0HK1WKwwYMED4+++/DfZfuXKlULx4cSEuLs7subKyspwattS4fv26ULhwYWHt2rUOP5f4mjx9+lTaNn78eLv8fo0Rb64BCBkZGcLvv/8uJCQkOORcBY34nurevbtFz9+0aZNQs2ZNYdWqVQ5umWkxMTFCZmamU9tARHbGsEX5iKPDlkYQrFisyA6ePXsGHx8f/PXXX+jevbu0/dNPP0VYWBgOHjxosE/r1q3RoEED/Pzzz9K2jRs34t1330VKSorieKP09HSkp6dLP8fHx6N8+fK4c+eOzno9+UliYqLJMWHA865l+pM7CIKAtWvXon379jrdltRKSEjAzJkz8fHHH0vdxgRBcNggfT8/P5QvXx4XLlxwyPHtSWnxaEd4+eWXce7cOTx+/Fjqsnr58mW8+uqrWLx4sTTVvT0lJSWhdevWGDJkCIYMGWL34xdkjx8/xi+//IK+fftaNEMpEZHDJCcDYpfQ+/cBGxaYJ3K2hIQElCtXDk+fPrXrEAKJQyKcBe7duycAEI4ePaqz/fvvvxeCg4MV96lWrZrw/fff62w7evSoAEC4f/++4j7ffPONTrc+fvGLX/ziF7/4xS9+8Ytf/JJ/yXtf2ZPTZyPUr3QIZqofSs9X2i4aP348Ro8eLf2s1WoREhKCM2fO2KXK0rhxY5w6dSpH91e7j6XPF5N9fq762cLW33VOcEYbHXlOex7blmNZuy/fq87B92rOn5PvVWV8rxqXF96nAN+rjjpObnqvir3eHLUepdPCVrFixeDq6ooHDx7obI+JiTG6+GXJkiUVn+/m5mZ0JkFPT0+Dme88PT3tViZ0dXW16X+g1uyvdh+1z/f19eU/Cgps/V3nBGe00ZHntOexbTmWtfvyveocfK/m/Dn5XjWN71VDeeF9CvC96qjj5Mb3qrllWKzltKnfPTw8EBISIi3SKdq9ezeaN2+uuE+zZs0Mnr9r1y40atRI1fpQH330kfoGO+hY1uyvdh97Xm9BlhdeR2e00ZHnzC3vVWv35XvVOfLC68j3qmOOxfdq3pFXXkO+Vx1znIL0XnXaBBkAsG7dOvTp0wfz589Hs2bNsHDhQixatAiXLl1ChQoVMH78eNy7dw8rV64EANy6dQt16tTBkCFDMHjwYBw/fhxDhw7FmjVr8NZbbznrMvKNhIQE+Pn5IT4+Pk982kRUUPG9SpQ38L1KlPs5+n3q1DFbPXr0wOPHjzFp0iRER0ejTp062L59OypUqAAAiI6ORlRUlPT8SpUqYfv27Rg1ahR+++03lC5dGr/88guDlp14enrim2++sXjBYSJyDr5XifIGvleJcj9Hv0+dWtkiIiIiIiLKr5w2ZouIiIiIiCg/Y9giIiIiIiJyAIYtIiIiIiIiB2DYIiIiIiIicgCGLSIiIiIiIgdg2CKLde/eHUWLFsXbb7/t7KYQkYI7d+7g5ZdfRq1atVC3bl389ddfzm4SESlITExE48aNUb9+fbzwwgtYtGiRs5tERCakpKSgQoUKGDNmjOp9OfU7WWz//v1ISkrCihUrsH79emc3h4j0REdH4+HDh6hfvz5iYmLQsGFDXL16FYUKFXJ204hIJisrC+np6fDx8UFKSgrq1KmDU6dOITAw0NlNIyIFEyZMwLVr11C+fHlMnz5d1b6sbJHF2rRpgyJFiji7GURkRKlSpVC/fn0AQIkSJRAQEIC4uDjnNoqIDLi6usLHxwcAkJaWhqysLPCzb6Lc6dq1a7hy5Qq6dOli1f4MWwXEoUOH0LVrV5QuXRoajQabNm0yeM7cuXNRqVIleHl5ISQkBIcPH875hhIVYPZ8n54+fRparRblypVzcKuJCh57vFefPn2KevXqoWzZshg7diyKFSuWQ60nKjjs8V4dM2YMpkyZYnUbGLYKiOTkZNSrVw+//vqr4uPr1q3DyJEjMWHCBJw9exatWrVC586dERUVlcMtJSq47PU+ffz4Mfr27YuFCxfmRLOJChx7vFf9/f1x7tw53Lp1C6tXr8bDhw9zqvlEBYat79XNmzcjODgYwcHB1jdCoAIHgLBx40adbU2aNBGGDh2qs61GjRrCF198obNt//79wltvveXoJhIVeNa+T9PS0oRWrVoJK1euzIlmEhV4tvybKho6dKjw559/OqqJRCRY91794osvhLJlywoVKlQQAgMDBV9fX+Hbb79VdV5WtgjPnj1DaGgoOnbsqLO9Y8eOOHbsmJNaRURylrxPBUFA//790bZtW/Tp08cZzSQq8Cx5rz58+BAJCQkAgISEBBw6dAjVq1fP8bYSFWSWvFenTJmCO3fuIDIyEtOnT8fgwYPx9ddfqzqPm91aTHlWbGwssrKyEBQUpLM9KCgIDx48kH7u1KkTzpw5g+TkZJQtWxYbN25E48aNc7q5RAWSJe/To0ePYt26dahbt67UL/3333/HCy+8kNPNJSqwLHmv3r17F4MGDYIgCBAEAR9//DHq1q3rjOYSFViW3v/aimGLJBqNRudnQRB0tu3cuTOnm0REeky9T1u2bAmtVuuMZhGRHlPv1ZCQEISFhTmhVUSkz9z9r6h///5WHZ/dCAnFihWDq6urQYqPiYkxSPtE5Bx8nxLlDXyvEuUNOfVeZdgieHh4ICQkBLt379bZvnv3bjRv3txJrSIiOb5PifIGvleJ8oaceq+yG2EBkZSUhOvXr0s/37p1C2FhYQgICED58uUxevRo9OnTB40aNUKzZs2wcOFCREVFYejQoU5sNVHBwvcpUd7A9ypR3pAr3qvWTZ5Iec3+/fsFAAZf/fr1k57z22+/CRUqVBA8PDyEhg0bCgcPHnReg4kKIL5PifIGvleJ8obc8F7VCIIg2C+6EREREREREcAxW0RERERERA7BsEVEREREROQADFtEREREREQOwLBFRERERETkAAxbREREREREDsCwRURERERE5AAMW0RERERERA7AsEVEREREROQADFtERJSrTZw4EfXr17fpGJGRkdBoNAgLCzP5vKtXr6JkyZJITEw0+pzly5fD39/fpvao8euvv6Jbt245dj4iIrIfhi0iIrKL/v37Q6PRQKPRwN3dHZUrV8aYMWOQnJxs03HHjBmDvXv32qmVpk2YMAEfffQRihQpkiPns8TgwYNx6tQpHDlyxNlNISIilRi2iIjIbl555RVER0fj5s2bmDx5MubOnYsxY8ZYdSxBEJCZmYnChQsjMDDQzi01dPfuXWzZsgUDBgxw+LnU8PT0RK9evTBnzhxnN4WIiFRi2CIiIrvx9PREyZIlUa5cOfTq1Qu9e/fGpk2bAGSHp2nTpqFy5crw9vZGvXr1sH79emnfAwcOQKPRYOfOnWjUqBE8PT1x+PBhg26EWq0WkyZNQtmyZeHp6Yn69etjx44dOu3477//0KBBA3h5eaFRo0Y4e/as2bb/+eefqFevHsqWLauzffny5Shfvjx8fHzQvXt3PH78WOfxGzdu4PXXX0dQUBAKFy6Mxo0bY8+ePdLjkyZNwgsvvGBwvpCQEHz99dfStTdp0gSFChWCv78/WrRogdu3b0vP7datGzZt2oTU1FSz10FERLkHwxYRETmMt7c3MjIyAABfffUVli1bhnnz5uHSpUsYNWoU3n//fRw8eFBnn7Fjx2LKlCkIDw9H3bp1DY75888/Y8aMGZg+fTrOnz+PTp06oVu3brh27RoAIDk5Ga+99hqqV6+O0NBQTJw40aLq2qFDh9CoUSOdbSdPnsTAgQMxfPhwhIWFoU2bNpg8ebLOc5KSktClSxfs2bMHZ8+eRadOndC1a1dERUUBAAYOHIjLly/j1KlT0j7nz5/H2bNn0b9/f2RmZuKNN97ASy+9hPPnz+P48eP48MMPodFopOc3atQIGRkZ+O+//8xeBxER5SICERGRHfTr1094/fXXpZ9PnjwpBAYGCu+++66QlJQkeHl5CceOHdPZZ9CgQcJ7770nCIIg7N+/XwAgbNq0Sec533zzjVCvXj3p59KlSwvff/+9znMaN24sDB8+XBAEQViwYIEQEBAgJCcnS4/PmzdPACCcPXvWaPvr1asnTJo0SWfbe++9J7zyyis623r06CH4+fkZPY4gCEKtWrWEOXPmSD937txZGDZsmPTzyJEjhZdfflkQBEF4/PixAEA4cOCAyWMWLVpUWL58ucnnEBFR7sLKFhER2c3WrVtRuHBheHl5oVmzZmjdujXmzJmDy5cvIy0tDR06dEDhwoWlr5UrV+LGjRs6x9CvLsklJCTg/v37aNGihc72Fi1aIDw8HAAQHh6OevXqwcfHR3q8WbNmZtuempoKLy8vnW3h4eEG++r/nJycjLFjx6JWrVrw9/dH4cKFceXKFamyBWRPcrFmzRqkpaUhIyMDf/zxBwYOHAgACAgIQP/+/aWK2M8//4zo6GiD9nl7eyMlJcXsdRARUe7h5uwGEBFR/tGmTRvMmzcP7u7uKF26NNzd3QEAt27dAgBs27YNZcqU0dnH09NT5+dChQqZPY+8ix2QPR5M3CYIglVtL1asGJ48eWJwXHM+//xz7Ny5E9OnT0fVqlXh7e2Nt99+G8+ePZOe07VrV3h6emLjxo3w9PREeno63nrrLenxZcuWYcSIEdixYwfWrVuHr776Crt378aLL74oPScuLg7Fixe36tqIiMg5GLaIiMhuChUqhKpVqxpsr1WrFjw9PREVFYWXXnrJ6uP7+vqidOnSOHLkCFq3bi1tP3bsGJo0aSKd6/fff0dqaiq8vb0BACdOnDB77AYNGuDy5csG7dbfV//nw4cPo3///ujevTuA7DFckZGROs9xc3NDv379sGzZMnh6eqJnz546lTfx/A0aNMD48ePRrFkzrF69WgpbN27cQFpaGho0aGD2OoiIKPdg2CIiIocrUqQIxowZg1GjRkGr1aJly5ZISEjAsWPHULhwYfTr18/iY33++ef45ptvUKVKFdSvXx/Lli1DWFgY/vjjDwBAr169MGHCBAwaNAhfffUVIiMjMX36dLPH7dSpEz744ANkZWXB1dUVADBixAg0b94c06ZNwxtvvIFdu3YZzHxYtWpVbNiwAV27doVGo8H//vc/aLVag+N/8MEHqFmzJgDg6NGj0vZbt25h4cKF6NatG0qXLo2rV68iIiICffv2lZ5z+PBhVK5cGVWqVLH4dSIiIufjmC0iIsoR3333Hb7++mtMmTIFNWvWRKdOnfDPP/+gUqVKqo4zYsQIfPbZZ/jss8/wwgsvYMeOHdiyZQuqVasGAChcuDD++ecfXL58GQ0aNMCECRMwdepUs8ft0qUL3N3ddaZtf/HFF7F48WLMmTMH9evXx65du/DVV1/p7Ddr1iwULVoUzZs3R9euXdGpUyc0bNjQ4PjVqlVD8+bNUb16dTRt2lTa7uPjgytXruCtt95CcHAwPvzwQ3z88ccYMmSI9Jw1a9Zg8ODBql4nIiJyPo1gbed2IiKifGbu3LnYvHkzdu7cafdjC4KAGjVqYMiQIRg9erTF+128eBHt2rVDREQE/Pz87N4uIiJyHHYjJCIi+n8ffvghnjx5gsTERBQpUsRux42JicHvv/+Oe/fuYcCAAar2vX//PlauXMmgRUSUB7GyRURE5GAajQbFihXDzz//jF69ejm7OURElENY2SIiInIwfq5JRFQwcYIMIiIiIiIiB2DYIiIiIiIicgCGLSIiIiIiIgdg2CIiIiIiInIAhi0iIiIiIiIHYNgiIiIiIiJyAIYtIiIiIiIiB2DYIiIiIiIicgCGLSIiIiIiIgf4P36q0VxA28lpAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 1000x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "model = copy.deepcopy(single_star_model)\n",
    "\n",
    "# Periodogram settings \n",
    "Pmin = 5\n",
    "Pmax = 10000\n",
    "nfreq = 10000\n",
    "nu0 = 2 * np.pi / Pmax\n",
    "dnu = (2 * np.pi / Pmin - nu0) / (nfreq - 1)\n",
    "\n",
    "# plot the single-star residuals\n",
    "resisuals = model.residuals()\n",
    "res_err = np.sqrt(model.cov.A)\n",
    "pl.figure(figsize=(10, 3))\n",
    "pl.errorbar(model.t, resisuals, yerr=res_err, fmt='o', ecolor='0.7', ms=4, color='k')\n",
    "pl.xlabel(f'Relative time (days)')\n",
    "pl.ylabel('Single-star residuals (mas)')\n",
    "pl.axhline(ls='--')\n",
    "pl.show()    \n",
    "\n",
    "# compute periodogram\n",
    "nu, power = model.periodogram(nu0, dnu, nfreq)\n",
    "\n",
    "# convert from angular frequency to period\n",
    "P = 2 * np.pi / nu\n",
    "\n",
    "# identify highest peak and compute false-alarm probability (FAP)\n",
    "kmax = np.argmax(power)\n",
    "faplvl = model.fap(power[kmax], nu.max())\n",
    "\n",
    "# plot periodogram as a function of frequency\n",
    "pl.figure(figsize=(10, 3))\n",
    "pl.plot(nu, power, 'k', lw=1.2)\n",
    "pl.ylim(0, 1.1 * power.max())\n",
    "pl.xlabel('Angular frequency (rad/day)')\n",
    "pl.ylabel('Normalized power')\n",
    "pl.title(f'nu={nu[kmax]:.4f} rad/d' + 20*' ' + f'FAP={faplvl:.2g}')\n",
    "pl.show()\n",
    "\n",
    "# plot periodogram as a function of period\n",
    "pl.figure(figsize=(10, 3))\n",
    "pl.plot(2 * [P[kmax]], [0, 1.1 * power.max()], 'r')\n",
    "pl.plot(P, power, 'k', lw=1.2, rasterized=True)\n",
    "pl.xlim(Pmin, Pmax)\n",
    "pl.ylim(0, 1.1 * power.max())\n",
    "pl.xscale('log')\n",
    "pl.xlabel('Period (days)')\n",
    "pl.ylabel('Normalized power')\n",
    "pl.title(f'P={P[kmax]:.1f} d' + 20*' ' + f'FAP={faplvl:.2g}')\n",
    "pl.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d713f579-6f76-4b5a-b16b-ee6c4f236a1e",
   "metadata": {},
   "source": [
    "## Fit the Keplerian model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "2a575d4c-360e-4025-b17c-f6b220713ff9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Adding a Keplerian with period 1724.7 days to model.\n",
      "\n",
      "Best-fit parameter (Thiele-Innes coefficients)\n",
      "Parameter                        Value     Error       \n",
      "lin.ra                          4.2638  ±  0.0578      \n",
      "lin.dec                         2.4251  ±  0.0821      \n",
      "lin.parallax                   1.68081  ±  0.00894     \n",
      "lin.mura                      -28.3284  ±  0.0736      \n",
      "lin.mudec                     -155.201  ±  0.123       \n",
      "kep.0.P                           4236  ±  109         \n",
      "kep.0.M0 [deg]                 339.554  ±  0.547       \n",
      "kep.0.e                        0.72823  ±  0.00527     \n",
      "kep.0.TIA                       2.3471  ±  0.0540      \n",
      "kep.0.TIB                       10.752  ±  0.197       \n",
      "kep.0.TIF                       20.669  ±  0.442       \n",
      "kep.0.TIG                      -17.011  ±  0.311       \n",
      "\n",
      "Best-fit parameter (Campbell elements)\n",
      "kep.0.P is the period in days, kep.0.as is the semimajor axis in milli-arcseconds\n",
      "\n",
      "Parameter                        Value     Error       \n",
      "lin.ra                          4.2638  ±  0.0578      \n",
      "lin.dec                         2.4251  ±  0.0822      \n",
      "lin.parallax                   1.68081  ±  0.00894     \n",
      "lin.mura                      -28.3284  ±  0.0737      \n",
      "lin.mudec                     -155.201  ±  0.124       \n",
      "kep.0.P                           4236  ±  109         \n",
      "kep.0.Tp                         -3995  ±  109         \n",
      "kep.0.as                        27.303  ±  0.544       \n",
      "kep.0.e                        0.72823  ±  0.00528     \n",
      "kep.0.w [deg]                   77.853  ±  0.162       \n",
      "kep.0.i [deg]                  110.589  ±  0.101       \n",
      "kep.0.bigw [deg]               136.216  ±  0.140       \n",
      "\n"
     ]
    }
   ],
   "source": [
    "keplerian_model = copy.deepcopy(model)\n",
    "\n",
    "print(f'Adding a Keplerian with period {P[kmax]:.1f} days to model.\\n')\n",
    "\n",
    "keplerian_model.add_keplerian_from_period(P[kmax])\n",
    "\n",
    "# fit the new model\n",
    "keplerian_model.fit()\n",
    "\n",
    "print(f\"Best-fit parameter (Thiele-Innes coefficients)\")\n",
    "keplerian_model.show_param()\n",
    "\n",
    "# print('Change orbital parameter set:')\n",
    "param = ['P', 'Tp', 'as', 'e', 'w', 'i', 'bigw']\n",
    "keplerian_model.set_keplerian_param(f'0', param=param)\n",
    "\n",
    "print(f\"Best-fit parameter (Campbell elements)\\nkep.0.P is the period in days, kep.0.as is the semimajor axis in milli-arcseconds\\n\")\n",
    "keplerian_model.show_param()    "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b19341ce-42d3-4017-b285-2a17d9cc8d2e",
   "metadata": {},
   "source": [
    "## Compute the mass of the black hole"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "b99076b2-d7a5-450b-852c-442bdbc56dd7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/markdown": [
       "## <strong>Results from astrometry only:</strong>"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "## <strong>The mass function value is 31.87 solar masses</strong>"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "## <strong>With a primary mass of 0.76 solar masses, the companion has a mass of 33.34 solar masses</strong><br/>"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "keplerian_parameters = {}\n",
    "for i, key in enumerate(keplerian_model.keplerian['0']._param):\n",
    "    keplerian_parameters[key] = keplerian_model.keplerian['0']._par[i]\n",
    "\n",
    "linear_parameters = {}\n",
    "for i, key in enumerate(keplerian_model._lin_name):\n",
    "    linear_parameters[key] = keplerian_model._lin_par[i]\n",
    "\n",
    "a_m = convert_from_angular_to_linear(keplerian_parameters['as'], linear_parameters['parallax'])\n",
    "m2_kg = pjGet_m2(m1_MS * MS_kg, a_m, keplerian_parameters['P'])\n",
    "m2_MS = m2_kg / MS_kg\n",
    "mass_function = keplerian_parameters['as']**3 * (u.year.to(u.day))**2 / (keplerian_parameters['P']**2 * linear_parameters['parallax']**3)\n",
    "\n",
    "display(Markdown(f'## <strong>Results from astrometry only:</strong>'))\n",
    "display(Markdown(f'## <strong>The mass function value is {mass_function:.2f} solar masses</strong>'))\n",
    "display(Markdown(f'## <strong>With a primary mass of {m1_MS} solar masses, the companion has a mass of {m2_MS:.2f} solar masses</strong><br/>'))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2e6a6cbb-082b-4f66-8603-d0f37cb3475f",
   "metadata": {},
   "source": [
    "## Create orbit model and display it together with the Gaia measurements\n",
    "\n",
    "We use plotting tools provided by the open-source python package [pystrometry](https://github.com/Johannes-Sahlmann/pystrometry) (https://zenodo.org/records/10839734), which supports the analysis of high-precision astrometry timeseries. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "299ffbb7-0420-4064-a172-065ce9aa9bf3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/markdown": [
       "## <strong>The five figure panels below show the following (for a detailed description see https://www.aanda.org/articles/aa/full_html/2023/06/aa44161-22/F12.html):\n",
       "Top left: Parallax and proper motion of the source projected on the sky  \n",
       "Bottom left: On-sky orbital signature relative to the system's barycentre   \n",
       "Top right: Orbital signature relative to the system barycentre as a function of time  \n",
       "Middle right: Aggregated residuals as a function of time  \n",
       "Bottom right: Individual residuals as a function of time </strong>"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "++++++++++++++++++++++++++++++\n",
      "System parameters:\n",
      "Distance is 595.0 pc \t Parallax = 1.7 mas\n",
      "Primary   mass = 0.760 Msol \t = 796.150 Mjup\n",
      "Secondary mass = 33.343 Msol \t = 34928.909 Mjup \t = 11101399.607 MEarth\n",
      "Mass ratio q=m2/m1 = 43.872284\n",
      "a1_mas    = 27.303, a_rel_mas = 27.926, a_rel_au = 16.614\n",
      "Inclination  110.6 deg\n",
      "Period is   4235.8 day \t Eccentricity = 0.728\n",
      "omega = 77.9 deg, OMEGA = 136.2 deg, T_periastron = 53941.2 day\n",
      "RV semi-amplitude of primary = 56989.295 m/s\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x700 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# A helper function for plotting\n",
    "def plot_astrometry(astrometry_timeseries, parameter_df, plot_dir, reference_time, model_name):\n",
    "    \"\"\"Make a figure showing the model and the data.\"\"\"\n",
    "    \n",
    "    source_id = parameter_df.loc[0, 'source_id']\n",
    "\n",
    "    iad = gaia_astrometry_plotter.GaiaValIad.from_dataframe(astrometry_timeseries, source_id, 'source_id')\n",
    "\n",
    "    iad._mjd_field = 'mjd'\n",
    "    iad.time_column = 'relative_time_year'\n",
    "    iad.set_reference_time(reference_time)\n",
    "\n",
    "    parameter_dict = parameter_df[parameter_df['source_id'] == source_id].iloc[0].to_dict()\n",
    "    parameter_dict['source_id'] = np.int64(source_id)\n",
    "    parameter_dict['name_seed'] = f\"{source_id}_{model_name}\"\n",
    "    if model_name == 'multiple_star':\n",
    "        axp = gaia_astrometry_plotter.plot_individual_orbit(parameter_dict, iad, plot_dir=plot_dir, m1_MS=parameter_dict['m1_MS'])\n",
    "    return axp\n",
    "    \n",
    "reference_time = DR4_REFERENCE_EPOCH\n",
    "model_name = 'multiple_star'\n",
    "\n",
    "attribute_dict = OrderedDict([  \n",
    "                                ('ra', bh3_ra_deg), \n",
    "                                ('dec', bh3_dec_deg),    \n",
    "                                ('absolute_plx_mas', linear_parameters['parallax']), \n",
    "                                ('muRA_mas', linear_parameters['mura']),\n",
    "                                ('muDE_mas', linear_parameters['mudec']),\n",
    "                                ('muAlphaStar_masPyr', linear_parameters['mura']),\n",
    "                                ('muDelta_masPyr', linear_parameters['mudec']),\n",
    "                                ('Tref_MJD', reference_time.mjd),\n",
    "                                ('scan_angle_definition', 'gaia'),\n",
    "                             ])  \n",
    "\n",
    "attribute_dict['m2_MJ'] = m2_kg / MJ_kg\n",
    "attribute_dict['m1_MS'] = m1_MS\n",
    "attribute_dict['P_day'] = keplerian_parameters['P']\n",
    "attribute_dict['p1_omega_deg'] = np.rad2deg(keplerian_parameters['w'])\n",
    "attribute_dict['ecc'] = keplerian_parameters['e']\n",
    "attribute_dict['p1_OMEGA_deg'] = np.rad2deg(keplerian_parameters['bigw'])\n",
    "attribute_dict['p1_incl_deg'] = np.rad2deg(keplerian_parameters['i'])\n",
    "attribute_dict['p1_Tp_day'] = attribute_dict['Tref_MJD'] + keplerian_parameters['Tp']  # this is in MJD\n",
    "attribute_dict['p1_a1_mas'] = keplerian_parameters['as']\n",
    "attribute_dict['p1_ecc'] = keplerian_parameters['e']\n",
    "attribute_dict['p1_period_day'] = keplerian_parameters['P']\n",
    "attribute_dict['p1_Tp_day-T0'] = keplerian_parameters['Tp']\n",
    "attribute_dict['offset_alphastar_mas'] = linear_parameters['ra']\n",
    "attribute_dict['offset_delta_mas'] = linear_parameters['dec']\n",
    "\n",
    "attribute_dict['source_id'] = source_id\n",
    "\n",
    "attribute_dict['epoch_omc_description'] = ''\n",
    "attribute_dict['orbit_signal_description'] = ''\n",
    "attribute_dict['orbit_description'] = [['']]\n",
    "attribute_dict['ppm_description'] = ''\n",
    "attribute_dict['title'] = 'Gaia BH3 astrometric orbit'\n",
    "attribute_dict['frame_omc_description'] = ''\n",
    "\n",
    "\n",
    "display(Markdown(f'## <strong>The five figure panels below show the following (for a detailed description see https://www.aanda.org/articles/aa/full_html/2023/06/aa44161-22/F12.html):\\nTop left: Parallax and proper motion of the source projected on the sky  \\nBottom left: On-sky orbital signature relative to the system\\'s barycentre   \\nTop right: Orbital signature relative to the system barycentre as a function of time  \\nMiddle right: Aggregated residuals as a function of time  \\nBottom right: Individual residuals as a function of time </strong>'))\n",
    "axp = plot_astrometry(gaia_astrometry, pd.DataFrame(attribute_dict, index=[0]), plot_dir, reference_time, model_name)    "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "586c8ec2-ef1b-4fd1-bcbb-60a8b562b0a6",
   "metadata": {},
   "source": [
    "# Combined analysis of astrometric and radial-velocity timeseries"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0c64f06e-bacd-4209-8508-81c85e04d987",
   "metadata": {},
   "source": [
    "## Load radial-velocity timeseries data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "d8acbc43-b5ae-401f-81f0-21bd1130fe9c",
   "metadata": {},
   "outputs": [],
   "source": [
    "columns = 'transit_id obs_time_tcb radial_velocity radial_velocity_err'.split()\n",
    "gaia_rv = pd.read_csv('epochrv.dat', names=columns, delim_whitespace=True, comment='#')\n",
    "gaia_rv['relative_time_year'] = Time(gaia_rv['obs_time_tcb'], format='jd', scale='tcb').jyear - DR4_REFERENCE_EPOCH.jyear\n",
    "gaia_rv['relative_time_day'] = gaia_rv['relative_time_year'] * u.year.to(u.day)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "75f7ecfe-ab66-4f86-8bf2-0ddec0517c8e",
   "metadata": {},
   "source": [
    "## Set up a the combined astrometry + radial-velocity model and fit it to the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "46af8baf-66ae-4cb2-80a7-f56bd3979975",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Parameter                        Value     Error       \n",
      "astro.lin.ra                    4.2796  ±  0.0500      \n",
      "astro.lin.dec                   2.4021  ±  0.0649      \n",
      "astro.lin.plx                  1.68364  ±  0.00774     \n",
      "astro.lin.mura                -28.3484  ±  0.0573      \n",
      "astro.lin.mudec              -155.1721  ±  0.0979      \n",
      "rv.lin.rv_offset               -357212  ±  402         \n",
      "kep.0.P                         4211.6  ±  86.1        \n",
      "kep.0.assini                    15.108  ±  0.238       \n",
      "kep.0.M0 [deg]                 339.445  ±  0.450       \n",
      "kep.0.e                        0.72706  ±  0.00426     \n",
      "kep.0.omega [deg]               77.814  ±  0.152       \n",
      "kep.0.i [deg]                 110.6136  ±  0.0892      \n",
      "kep.0.bigomega [deg]           136.192  ±  0.121       \n",
      "\n"
     ]
    }
   ],
   "source": [
    "# fit the simplest radial-velocity model (constant offset)\n",
    "rv_default_jitter = 0.0\n",
    "rv_model = RvModel(\n",
    "  gaia_rv['relative_time_day'].values,\n",
    "  gaia_rv['radial_velocity'].values*1e3,\n",
    "  err=spleaf.term.Error(gaia_rv['radial_velocity_err'].values*1e3),\n",
    "  jit=spleaf.term.Jitter(rv_default_jitter*1e3),\n",
    ")\n",
    "rv_model.add_lin(np.ones(len(gaia_rv)), 'rv_offset')\n",
    "rv_model.fit()\n",
    "# rv_model.show_param()\n",
    "\n",
    "# set up a fresh single-star model \n",
    "single_star_model = AstrometricModel(gaia_astrometry['relative_time_day'].values, \n",
    "                                     gaia_astrometry['centroid_pos_al'].values, \n",
    "                                     gaia_astrometry['cpsi_obs'].values, \n",
    "                                     gaia_astrometry['spsi_obs'].values, \n",
    "                                     err=spleaf.term.Error(gaia_astrometry['centroid_pos_error_al'].values),\n",
    "                                     jit=spleaf.term.Jitter(astrometric_jitter_value),\n",
    "                                     angular_keplerian_param=False)\n",
    "\n",
    "# define the linear parameters\n",
    "single_star_model.add_lin(gaia_astrometry['spsi_obs'].values, 'ra')\n",
    "single_star_model.add_lin(gaia_astrometry['cpsi_obs'].values, 'dec')\n",
    "single_star_model.add_lin(gaia_astrometry['parallax_factor_al'].values, 'plx')\n",
    "single_star_model.add_lin(gaia_astrometry['relative_time_year'].values * gaia_astrometry['spsi_obs'].values, 'mura')\n",
    "single_star_model.add_lin(gaia_astrometry['relative_time_year'].values * gaia_astrometry['cpsi_obs'].values, 'mudec')\n",
    "\n",
    "# add jitter term\n",
    "if include_jitter_term:\n",
    "    single_star_model.fit_param += ['cov.jit.sig']\n",
    "\n",
    "# perform the single-star fit\n",
    "single_star_model.fit()\n",
    "\n",
    "# set up and fit the combined model (astrometry + radial velocity)\n",
    "full_model = AstroRvModel(single_star_model, rv_model)\n",
    "full_model.add_keplerian_from_period(P[kmax])\n",
    "full_model.fit()\n",
    "full_model.show_param()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "97005bf2-9922-4790-aae1-1e934e8f3a4e",
   "metadata": {},
   "source": [
    "## Recompute the mass of the black hole"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "260ad6a1-2cb5-44e8-91f3-45987f711d19",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/markdown": [
       "## <strong>Results from combined astrometry + radial-velocity analysis: </strong>"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "## <strong>The mass function value is 31.63 solar masses</strong>"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "## <strong>With a primary mass of 0.76 solar masses, the companion has a mass of 33.10 solar masses</strong><br/>"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "## <strong>Assuming uncorrelated Gaussian errors we obtain the uncertainties. These are larger than in the discovery paper, because here we do not account for the strong correlation between semimajor axis and period (see Section 2.2. of the paper): </strong>"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "## <strong>Mass function =  31.7 +/- 2.0 solar masses</strong>"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "## <strong>Black hole mass = 33.2 +/- 2.0 solar masses</strong><br/>"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "keplerian_parameters = {}\n",
    "for i, key in enumerate(full_model.keplerian['0']._param):\n",
    "    keplerian_parameters[key] = full_model.keplerian['0']._par[full_model.keplerian['0']._index[i]]\n",
    "\n",
    "linear_parameters = {}\n",
    "for i, key in enumerate(single_star_model._lin_name):\n",
    "    linear_parameters[key] = single_star_model._lin_par[i]\n",
    "\n",
    "rv_parameters = {}\n",
    "for i, key in enumerate(rv_model._lin_name):\n",
    "    rv_parameters[key] = rv_model._lin_par[i]\n",
    "\n",
    "keplerian_parameters['as_au'] = keplerian_parameters['assini']/np.sin(keplerian_parameters['i'])\n",
    "keplerian_parameters['as_m'] = keplerian_parameters['as_au'] * u.astronomical_unit.to(u.m)\n",
    "keplerian_parameters['as_mas'] = convert_from_linear_to_angular(keplerian_parameters['as_m'], linear_parameters['plx'])\n",
    "m2_kg = pjGet_m2(m1_MS * MS_kg, keplerian_parameters['as_m'], keplerian_parameters['P'])\n",
    "m2_MS = m2_kg / MS_kg\n",
    "mass_function = keplerian_parameters['as_mas']**3 * (u.year.to(u.day))**2 / (keplerian_parameters['P']**2 * linear_parameters['plx']**3)\n",
    "display(Markdown(f'## <strong>Results from combined astrometry + radial-velocity analysis: </strong>'))\n",
    "display(Markdown(f'## <strong>The mass function value is {mass_function:.2f} solar masses</strong>'))\n",
    "display(Markdown(f'## <strong>With a primary mass of {m1_MS} solar masses, the companion has a mass of {m2_MS:.2f} solar masses</strong><br/>'))\n",
    "\n",
    "# assume uncorrelated Gaussian errors and compute companion mass uncertainty\n",
    "value, std = full_model.get_param_error(full_model.fit_param, 1e-6)\n",
    "np.random.seed(1)\n",
    "resampled = np.random.multivariate_normal(value, np.diag(np.nan_to_num(std)**2), size=10000)\n",
    "\n",
    "def compute_companion_mass(assini_au, i_rad, plx_mas, period_day, m1_MS):\n",
    "    as_au = assini_au/np.sin(i_rad)\n",
    "    as_m = as_au * u.astronomical_unit.to(u.m)\n",
    "    as_mas = convert_from_linear_to_angular(as_m, plx_mas)\n",
    "    m2_kg = pjGet_m2(m1_MS * MS_kg, as_m, period_day)\n",
    "    m2_MS = m2_kg / MS_kg\n",
    "\n",
    "    mass_function_msun = as_mas**3 * (u.year.to(u.day))**2 / (period_day**2 * plx_mas**3)\n",
    "    return m2_MS, mass_function_msun \n",
    "\n",
    "m2_MS_mc, mass_function_msun_mc = compute_companion_mass(resampled[:, full_model.fit_param.index('kep.0.assini')], \n",
    "                       resampled[:, full_model.fit_param.index('kep.0.i')], \n",
    "                       resampled[:, full_model.fit_param.index('astro.lin.plx')], \n",
    "                       resampled[:, full_model.fit_param.index('kep.0.P')], m1_MS)\n",
    "\n",
    "display(Markdown(f'## <strong>Assuming uncorrelated Gaussian errors we obtain the uncertainties. These are larger than in the discovery paper, because here we do not account for the strong correlation between semimajor axis and period (see Section 2.2. of the paper): </strong>'))\n",
    "display(Markdown(f'## <strong>Mass function =  {np.mean(mass_function_msun_mc):.1f} +/- {np.std(mass_function_msun_mc):.1f} solar masses</strong>'))\n",
    "display(Markdown(f'## <strong>Black hole mass = {np.mean(m2_MS_mc):.1f} +/- {np.std(m2_MS_mc):.1f} solar masses</strong><br/>'))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9757679c-5fb7-4519-b829-20e5dcb70841",
   "metadata": {},
   "source": [
    "## Plot radial velocity curve, the Gaia measurements, and the residuals"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "ea4f0dee-d130-46b3-88ad-12a9971cb845",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# create dictionary that defines the OrbitSystem\n",
    "attribute_dict = {\n",
    "    'gamma_ms': rv_parameters['rv_offset'],\n",
    "    'P_day': keplerian_parameters['P'],\n",
    "    'ecc': keplerian_parameters['e'],\n",
    "    'omega_deg': np.rad2deg(keplerian_parameters['omega']),\n",
    "    'OMEGA_deg': np.rad2deg(keplerian_parameters['bigomega']),\n",
    "    'i_deg': np.rad2deg(keplerian_parameters['i']),\n",
    "    'a_mas': keplerian_parameters['as_mas'],\n",
    "    'Tp_day': DR4_REFERENCE_EPOCH.mjd + keplerian_parameters['P'] * (1-keplerian_parameters['M0']/(2*np.pi)), # Eq (1) in Sahlmann\n",
    "    'm1_MS': m1_MS,\n",
    "    'm2_MJ': m2_kg / MJ_kg,\n",
    "    'Tref_MJD': DR4_REFERENCE_EPOCH.mjd,\n",
    "}\n",
    "\n",
    "\n",
    "n_figure_rows = 2; n_figure_columns=1;\n",
    "fig, axes = pl.subplots(n_figure_rows, n_figure_columns, figsize=(n_figure_columns*8, n_figure_rows*3), facecolor='w', edgecolor='k', sharex=True,  sharey=False, squeeze=True)\n",
    "\n",
    "# orbit panel\n",
    "ax = axes[0]\n",
    "pl.sca(ax)\n",
    "orbit = OrbitSystem(attribute_dict=attribute_dict)\n",
    "orbit.plot_rv_orbit()\n",
    "gaia_rv['time_jyear'] = Time(gaia_rv['obs_time_tcb'], format='jd', scale='tcb').jyear\n",
    "gaia_rv.plot('time_jyear', 'radial_velocity', yerr='radial_velocity_err', kind='scatter', ax=ax, color='k')\n",
    "ax.axhline(rv_parameters['rv_offset']/1e3, ls='--', label='systemic velocity')\n",
    "ax.legend()\n",
    "ax.set_ylabel('Gaia radial velocity (km/s)')\n",
    "ax.set_title('Gaia BH3 radial-velocity orbit (from combined fit)')\n",
    "\n",
    "# residual panel\n",
    "ax = axes[1]\n",
    "gaia_rv['radial_velocity_model'] = orbit.compute_radial_velocity(gaia_rv['relative_time_day']+DR4_REFERENCE_EPOCH.mjd)/1e3\n",
    "gaia_rv['radial_velocity_residual'] = gaia_rv['radial_velocity'] - gaia_rv['radial_velocity_model']\n",
    "gaia_rv.plot('time_jyear', 'radial_velocity_residual', yerr='radial_velocity_err', ax=ax, kind='scatter', color='k')\n",
    "ax.axhline(0, ls='--')\n",
    "ax.set_xlabel('Year')\n",
    "ax.set_ylabel('Residual (km/s)')\n",
    "pl.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "002602c8-fca0-49a5-9c90-42770b3c6e9b",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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