{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Adding your own terms"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This notebook shows how to add custom terms to the transport equation that AM³ solves (eq. 6 in Klinger et al. 2024):\n",
    "\n",
    "$$ \\partial_{t}n(E,t)=-\\partial_{E} \\left[ \\dot{{E}}({E,t})n(E,t) \\right] -\\alpha(E,t) n(E,t)+Q(E,t)$$\n",
    "\n",
    "where\n",
    "\n",
    "$$n(E,t)\\equiv\\frac{d^2 N}{d E d V} $$\n",
    "\n",
    "and the extra cooling term:\n",
    "$t_{extra\\;cooling}^{-1}(E)=\\dfrac{\\dot{E}(E)}{E}$ \n",
    "can be inserted via `am3.set_t_<species>_extra_cooling(array)`\n",
    "\n",
    "and the escape term:\n",
    "$t_{escape}^{-1}(E) = \\alpha(E)$ \n",
    "can be inserted via `am3.set_t_<species>_escape(array)`\n",
    "\n",
    "and the injection term:\n",
    "$Q(E)$ \n",
    "can be inserted via `am3.set_injection_rate_<species>(array)`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# %matplotlib widget\n",
    "\n",
    "from tqdm import trange\n",
    "import am3 as am3lib"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Some useful definitions\n",
    "c_light=3.e10              # speed of light--always useful       \n",
    "m_electron=9.10938356e-28  # electron mass\n",
    "sigma_t=6.65e-25           # Thomson cross section\n",
    "mec2 = m_electron*c_light**2\n",
    "eV2erg = 1.60218e-12\n",
    "erg2eV = 1/eV2erg"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "set up two AM³ instances, one for testing the escape term and one for the extra cooling term"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_AM3(escape=0):\n",
    "    am3 = am3lib.AM3()\n",
    "    am3.update_energy_grid(1e-6, 1e3, 1e22)\n",
    "    # set switches\n",
    "    am3.set_estimate_max_energies(0)\n",
    "\n",
    "    am3.set_process_parse_sed(1)\n",
    "    am3.set_process_hadronic(1)\n",
    "    am3.set_process_merge_positrons_into_electrons(0)\n",
    "    am3.set_process_escape(escape)\n",
    "    # expansion related\n",
    "    am3.set_process_adiabatic_cooling(0)\n",
    "    am3.set_process_expansion(0)\n",
    "\n",
    "    # synchrotron related\n",
    "    am3.set_process_electron_syn(0)\n",
    "    am3.set_process_electron_syn_emission(0)\n",
    "    am3.set_process_electron_syn_cooling(0)\n",
    "    am3.set_process_quantum_syn(0)\n",
    "    am3.set_process_ssa(0)\n",
    "    am3.set_process_proton_syn(0)\n",
    "    am3.set_process_proton_syn_emission(0)\n",
    "    am3.set_process_proton_syn_cooling(0)\n",
    "    am3.set_process_pion_syn(0)\n",
    "    am3.set_process_pion_syn_emission(0)\n",
    "    am3.set_process_pion_syn_cooling(0)\n",
    "    am3.set_process_muon_syn(0)\n",
    "    am3.set_process_muon_syn_emission(0)\n",
    "    am3.set_process_muon_syn_cooling(0)\n",
    "\n",
    "    # inverse Compton related\n",
    "    am3.set_process_electron_compton(0)\n",
    "    am3.set_process_electron_compton_emission(0)\n",
    "    am3.set_process_electron_compton_cooling(0)\n",
    "    am3.set_process_compton_photon_energy_loss(0)\n",
    "    am3.set_process_proton_compton(0)\n",
    "    am3.set_process_proton_compton_emission(0)\n",
    "    am3.set_process_proton_compton_cooling(0)\n",
    "    am3.set_process_pion_compton(0)\n",
    "    am3.set_process_pion_compton_emission(0)\n",
    "    am3.set_process_pion_compton_cooling(0)\n",
    "    am3.set_process_muon_compton(0)\n",
    "    am3.set_process_muon_compton_emission(0)\n",
    "    am3.set_process_muon_compton_cooling(0)\n",
    "\n",
    "    # secondary decay\n",
    "    am3.set_process_pion_decay(0)\n",
    "    am3.set_process_muon_decay(0)\n",
    "\n",
    "    # pair production (gamma+gamma -> e- + e+)\n",
    "    am3.set_process_annihilation(0)\n",
    "    am3.set_process_annihilation_cooling(0)\n",
    "    am3.set_process_annihilation_pair_emission(0)\n",
    "\n",
    "    # Bethe-Heitler\n",
    "    am3.set_process_bethe_heitler(0)\n",
    "    am3.set_process_bethe_heitler_emission(0)\n",
    "    am3.set_process_bethe_heitler_cooling(0)\n",
    "\n",
    "    # p-gamma\n",
    "    am3.set_process_photopion(0)\n",
    "    am3.set_process_photopion_emission(0)\n",
    "    am3.set_process_photopion_cooling(0)\n",
    "    am3.set_process_photopion_photon_loss(0)\n",
    "\n",
    "    # proton proton\n",
    "    am3.set_process_pp(0)\n",
    "    am3.set_process_pp_emission(0)\n",
    "    am3.set_process_pp_emission_pi0_into_cascade(0)\n",
    "    am3.set_process_pp_cooling(0)\n",
    "    return am3\n",
    "\n",
    "am3_esc = get_AM3(escape=1)\n",
    "am3_cool = get_AM3(escape=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "init. AM3 kernels:\n",
      "AM3 has the following switches (at step: 0)\n",
      "estimate maximum energies: 0\n",
      "parse sed components: 1\n",
      "escape: 1\n",
      "expansion: 0\n",
      "adiabatic: 0\n",
      "synchrotron:\n",
      "  e+/-: 0  (em..: 0, cool.: 0)\n",
      "  protons:0  (em..: 0, cool.: 0)\n",
      "  pions:0  (em..: 0, cool.: 0)\n",
      "  muons:0  (em..: 0, cool.: 0)\n",
      "  syn-self-abs.:0\n",
      "  e+/- quantum-syn.:0\n",
      "inv. Compton:\n",
      "  e+/-: 0  (em.. : 0, cool.: 0 (continuous))\n",
      "  photon loss due to upscattering: 0\n",
      "  protons:0  (em.. (step approx.): 0, no cooling)\n",
      "  pions:0  (em.. (step approx.): 0, cont. cool.: 0)\n",
      "  muons:0  (em.. (step approx.): 0, cont. cool.: 0)\n",
      "pair prod. (gamma+gamma->e+e)0  (photon loss.: 0, e+/- source (feedback): 0(opt. 14-bin kernel))\n",
      "'hadronic' processes (below): 1\n",
      " Pion decay: 0 Muon decay:0)\n",
      "proton Bethe-Heitler: 0  (em..: 0, cool.: 0)\n",
      "proton photo-pion: 0  (em..: 0, cool.: 0, photon loss: 0)\n",
      "proton p-p: 0  (em..: 0 , cool.: 0)\n",
      "\n",
      "AM3 params (comoving):\n",
      "escape_timescale: 1e+06 s\n",
      "  with fractions: (protons: 1, neutrons: 1, pions: 1, muons: 1, neutrinos: 1, pairs: 1)\n",
      "expansion_timescale: 1e+06 s\n",
      "t_adi: 3e+06 s\n",
      "B: 0.01 G\n",
      "pp target density = 0 cm^-3\n",
      "dt = 1000 s\n",
      "eta_Bohm: electrons:1, protons: 1\n",
      "inj. el:\n",
      "  power density = 0 erg/s/cm^3, \n",
      "   Emin = 1e+07 eV,\n",
      "   Ebreak = 1e+07 eV,\n",
      "   Emax = 1e+13 eV,\n",
      "   index = 2,\n",
      "   index above break = 2,\n",
      "   cut_off steepness = 1\n",
      "inj. protons: power density = 0 erg/s/cm^3, \n",
      "   Emin = 1e+10 eV,\n",
      "   Ebreak = 1e+10 eV,\n",
      "   Emax = 1e+15 eV,\n",
      "   index = 2,\n",
      "   index above break = 2,\n",
      "   cut_off steepness = 1\n",
      "\n",
      "init. AM3 kernels:\n",
      "AM3 has the following switches (at step: 0)\n",
      "estimate maximum energies: 0\n",
      "parse sed components: 1\n",
      "escape: 0\n",
      "expansion: 0\n",
      "adiabatic: 0\n",
      "synchrotron:\n",
      "  e+/-: 0  (em..: 0, cool.: 0)\n",
      "  protons:0  (em..: 0, cool.: 0)\n",
      "  pions:0  (em..: 0, cool.: 0)\n",
      "  muons:0  (em..: 0, cool.: 0)\n",
      "  syn-self-abs.:0\n",
      "  e+/- quantum-syn.:0\n",
      "inv. Compton:\n",
      "  e+/-: 0  (em.. : 0, cool.: 0 (continuous))\n",
      "  photon loss due to upscattering: 0\n",
      "  protons:0  (em.. (step approx.): 0, no cooling)\n",
      "  pions:0  (em.. (step approx.): 0, cont. cool.: 0)\n",
      "  muons:0  (em.. (step approx.): 0, cont. cool.: 0)\n",
      "pair prod. (gamma+gamma->e+e)0  (photon loss.: 0, e+/- source (feedback): 0(opt. 14-bin kernel))\n",
      "'hadronic' processes (below): 1\n",
      " Pion decay: 0 Muon decay:0)\n",
      "proton Bethe-Heitler: 0  (em..: 0, cool.: 0)\n",
      "proton photo-pion: 0  (em..: 0, cool.: 0, photon loss: 0)\n",
      "proton p-p: 0  (em..: 0 , cool.: 0)\n",
      "\n",
      "AM3 params (comoving):\n",
      "escape_timescale: 1e+06 s\n",
      "  with fractions: (protons: 1, neutrons: 1, pions: 1, muons: 1, neutrinos: 1, pairs: 1)\n",
      "expansion_timescale: 1e+06 s\n",
      "t_adi: 3e+06 s\n",
      "B: 0.01 G\n",
      "pp target density = 0 cm^-3\n",
      "dt = 1000 s\n",
      "eta_Bohm: electrons:1, protons: 1\n",
      "inj. el:\n",
      "  power density = 0 erg/s/cm^3, \n",
      "   Emin = 1e+07 eV,\n",
      "   Ebreak = 1e+07 eV,\n",
      "   Emax = 1e+13 eV,\n",
      "   index = 2,\n",
      "   index above break = 2,\n",
      "   cut_off steepness = 1\n",
      "inj. protons: power density = 0 erg/s/cm^3, \n",
      "   Emin = 1e+10 eV,\n",
      "   Ebreak = 1e+10 eV,\n",
      "   Emax = 1e+15 eV,\n",
      "   index = 2,\n",
      "   index above break = 2,\n",
      "   cut_off steepness = 1\n",
      "\n"
     ]
    }
   ],
   "source": [
    "am3_esc.init_kernels()\n",
    "am3_cool.init_kernels()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# short cuts for energy grids\n",
    "Ep_eV = am3_esc.get_egrid_had()\n",
    "Ep_erg = Ep_eV * eV2erg"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def powerlaw_array_number(Es, Emin, Emax, p, norm):\n",
    "    powerlaw = (Es/Emin)**(-p) * np.less_equal(Es, Emax) * np.greater_equal(Es, Emin) #np.exp(-(Es/Emax)) \n",
    "    integral = np.log(Es[1]/Es[0]) * np.sum(Es * powerlaw)\n",
    "    return norm/integral * powerlaw"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "set a continuous injection term with a constant rate as a power law with a broad energy range"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "Emin = 1e10 \n",
    "Emax = 1e20\n",
    "s_inj = 2\n",
    "N0 = 1\n",
    "\n",
    "am3_esc.clear_particle_densities()\n",
    "am3_esc.set_injection_rate_protons(Ep_eV * powerlaw_array_number(Ep_eV, Emin, Emax, s_inj, N0))\n",
    "\n",
    "am3_cool.clear_particle_densities()\n",
    "am3_cool.set_injection_rate_protons(Ep_eV * powerlaw_array_number(Ep_eV, Emin, Emax, s_inj, N0))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "\n",
    "ax.loglog(Ep_eV,  Ep_erg*am3_cool.get_injection_rate_protons())\n",
    "ax.set_aspect(\"equal\")\n",
    "ax.grid(alpha=0.3)\n",
    "ax.set_ylim(1e-5, 1e5)\n",
    "ax.set_xlabel(r\"$E$ [eV]\")\n",
    "ax.set_ylabel(r\"$E dN/dEdVdt$ [erg/cm³s]\")\n",
    "ax.set_title(\"proton injection term\")\n",
    "ax.set_aspect(\"equal\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "define an (unphysical) time scale array for the escape/extra coooling term to test the implementation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "t_escape = 10**(np.sin(np.log10(Ep_erg)) + 2) # in seconds\n",
    "t_advect = 10**(np.sin(np.log10(Ep_erg)+3) + 2)  # in seconds\n",
    "t_step = 10 # in seconds\n",
    "Ntotal = int(1e4/t_step)\n",
    "\n",
    "am3_esc.set_t_proton_escape(t_escape)\n",
    "am3_cool.set_t_proton_extra_cooling(t_advect)\n",
    "am3_esc.set_solver_time_step(t_step)\n",
    "am3_cool.set_solver_time_step(t_step)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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wd3cnMDCQWbNmMW7cOLp160bv3r354osviIuLY+rUqTd03GtvmQmCIAiC0PDUm4Ro//79DBo0yPK4qMPzhAkTWLp0Kffddx+pqanMmzePhIQEOnbsyNq1awkKCrqh486YMYMZM2aQlZWFi4vLDe1LEARBEIS6qd4kRAMHDqSiKZOmT5/O9OnTa6lEgiAIgiA0FA2iD1FNCg8Pp3379nTv3t3aRREEQRAEoYaIhKgColO1IAiCIDR8IiGqgGghEgRBEISGTyREFRAtRIIgCILQ8ImESBAEQRCERk8kRIIgCIIgNHoiIaqA6EMkCIIgCA2fSIgqIPoQCYIgCELDJxIiQRAEQRAaPZEQCYIgCILQ6ImEqAKiD5EgCIIgNHwiIaqA6EMkCIIgCA2fSIgEQRAEQWj0REIkCIIgCEKjJxIiQRAEQRAaPZEQCYIgCILQ6ImEqAJilJkgCIIgNHwiIaqAGGUmCIIgCA2fSIgEQRAEQWj0REIkCIIgCEKjJxIiQRAEQRAavUaXEOXl5REUFMQzzzxj7aIIgiAIglBHNLqE6M0336Rnz57WLoYgCIIgCHVIo0qITp8+zYkTJ7j99tutXRRBEARBEOqQepMQbd26lREjRuDn54ckSaxZs6ZEzKJFi2jevDm2traEhYWxbdu2Ys8/88wzzJ8/v5ZKLAiCIAhCfaGxdgEqKzc3l5CQECZNmsRdd91V4vmVK1cyc+ZMFi1axE033cTnn3/OsGHDOHbsGIGBgfz222+0adOGNm3asHPnzhsqh1qtLrFdrVZja2tbLK4sKpUKOzu764rNy8tDUZRSYyVJwt7e/rpi8/PzMRqNFOTnoZK0SFLxeDt7B8v/CwvykWW5zDJfHasvLMBkMlVLrK2dPdLlgun1hZiMxmqJ1dnaoVKZfxsY9HqMRkOx5xUF5Mv1YmtXfuzVtDpby2elKrFGgwGDQV92rFaHWqOpcqzJaESvLywz1sZGi8bGplKxGo0NRR8Rk8mEvrCg3FgbrbbKsbIsU1iQXy2xao0GrVYHgKIoFOTnVU+sWo1Wd+W8z8/Ls3xWrj2HSsaWf97rbO2uK7Ygv/zz3tbO/rpiq3LeXx179flTVCcN7RpR1VhFgTw78/lQFKvX6zEYyt6vre1V1xODAb2+7PNep9OhuXzeVyXWaDRSWFj2ea/VarG5fI2oSqzJZKKgoOzz3sbGBu1V14jc3FxLvZQXK8sy+flln/dXx1aKUg8ByurVq4tt69GjhzJ16tRi29q2bavMnj1bURRFmT17thIQEKAEBQUpHh4eirOzszJ37twyj1FQUKBkZmZa/p0/f14Byvw3bNgwxWQyWf7Z29uXGTtgwIBisZ6enmXGduvWrVhsUFBQmbHt27cvFtu+ffsyY4OCgorFduvWrcxYFzd35d8jCZZ/nbv1LjNWZ2dXLLZHv8Hl1tvVsf2G3lFu7G97YyyxQ0beW27sT1sPW2JH3D+x3Njl6/ZaYu+eOK3c2C/WbLbEjp32dLmxn/zwtyX2kVmvlBv77te/WmIff+mtcmNfD19hiX3mjYXlxr78/heW2Jff/6Lc2GfeWGiJfT18RbmxM158U1m7+5iy7nC88u7Xv5Yb+8isVyz7/eSHv8uNHTvtaUvsF2s2lxt798Rpltjl6/aWGzvi/omW2J+2Hi43dsjIey2xv+2NKTe239A7in2Gy4vt0W9wsVidnV2ZsZ279S4W6+LmXmZsmw4hxWJ9/ALKjA1q2aZYbFDLNmXG+vgFFItt0yGkzFhxjbjyryrXiJ07d1quwe+88065sf/9958l9pNPPik39vfff7fEfvXVV+XG/vjjj5bYH3/8sdzYr776yhL7+++/lxv7ySefWGL/+++/cmPfeecdxWQyKQaDQVm7dm25sXPmzLHs99ChQ+XGPv3004rJZFLS09MVQMnMzCw3t6g3LUTl0ev1REREMHv27GLbhw4damkNmj9/vuV22dKlSzly5Ahz5swpc5/z589n7ty5VSpDcnKy5bFSxq+u0mLL+9VlMBiKxZb368hoNBaLNZbzi8dkMhWLLe+XiaIomHIzrjyWy94vCsVjTWXvF66JLedXF4Ccl4FJ0V+OLfsXD4ApLwuTzvzxVgxl/4ox7zfLUo4KY/Ovji37Fw+AqSD7Sqy+7F8xAHJBjiVWLiy7RaLKsYW5V8WW3cpQtC9LbEFO+bH6fPP+pIpjFX2+Zb+mguzyYw0FV8qQn1VBbOGV2LzKx5oqijXqrypD+fWrGA3FPsPlxpquiS37EoEiG4ufG+VcTxTZdE1s2deTErFy2dcTRZGrECuuEZbYKlwj0tPTLdfhnJzyz6OMjAxLbHZ2+edRZmZmpWOzsrIssVlZ5Z8b2dnZltjMzMxKx2ZkZJQbm5OTQ3JyMrIsV1je3Nxcy37T0tLKjc3LyyM5ObnCfRaRlPLOtDpKkiRWr17NqFGjAIiPj8ff358dO3bQp08fS9xbb73FsmXLOHnyZLHXFyVE7733XpnHKCwspLCwkCVLlrBkyRJMJhPR0dFcuHABZ2fnEvEN5ZbZxsho1PauXNveb2d/bdN52R+bq2PNTdzlNbNXPtbWzu6aJu7yms4rH6uztb3SxG3QYzRcczFXFEx5GajtXdFdfcustNiraHW6q5q4Kx9rvg1Wzu01rfaaW2aVizXfBiv7S8LGxuaaW2Zlx2o0GiR9LmoHV2RZRl9O07nGRoONzdW3zCoXa74NVs7ttSrEqjXqa26DlXd7rQqxalXx22C5uZbPyrXnUInYvLKTLZVKuuaWWeVjzbfBSo+VJEq5ZVa52Kqc98Virzp/iuqkwV0jqhqrKHTwgICAAMttJXHLTIssyyQmJuLk5FStt8yysrJwc3MjMzOz1O/vIg0qIdq5cye9e/e2xL355pusWLGCEydO3PAxs7KycHFxqbBC6zNZlvl3/ynUDq6WC4Vw5devqJcrRJ2UTtRLSaJOSlIUhU4e4O3tXeYXf2MkyzLJycnVXi+V/f5uEH8JT09P1Go1iYmJxbYnJyfj4+NzQ/sWq90LgiAIQsPXIBIirVZLWFgY69evL7Z9/fr1xW6hXQ+x2r0gCIIgNHz1plN1Tk4O0dHRlsdnzpwhKioKd3d3AgMDmTVrFuPGjaNbt2707t2bL774gri4OKZOnXpDxw0PDyc8PLzczsyCIAiCINRv9SYh2r9/P4MGDbI8njVrFgATJkxg6dKl3HfffaSmpjJv3jwSEhLo2LEja9euJSgo6IaOO2PGDGbMmGG5BykIgiAIQsNTbxKigQMHljv0FGD69OlMnz69Wo8rWogEQRAEoeFrEH2IapLoQyQIgiAIDZ9IiARBEARBaPREQlQBMexeEARBEBo+kRBVQNwyEwRBEISGTyREgiAIgiA0eiIhEgRBEASh0RMJUQVEHyJBEARBaPhEQlQB0YdIEARBEBo+kRAJgiAIgtDoiYRIEARBEIRGTyREFRB9iARBEASh4RMJUQVEHyJBEARBaPhEQiQIgiAIQqMnEiJBEARBEBo9kRAJgiAIgtDoiYRIEARBEIRGTyREFRCjzARBEASh4RMJUQXEKDNBEARBaPhEQiQIgiAIQqMnEiJBEARBEBo9kRAJgiAIgtDoNZqEKDs7m+7duxMaGkqnTp1YsmSJtYskCIIgCEIdobF2AWqLvb09W7Zswd7enry8PDp27MiYMWPw8PCwdtEEQRAEQbCyRtNCpFarsbe3B6CgoACTyYSiKFYulSAIgiAIdUG9SYi2bt3KiBEj8PPzQ5Ik1qxZUyJm0aJFNG/eHFtbW8LCwti2bVux5zMyMggJCSEgIIDnnnsOT0/PWiq9IAiCIAh1Wb25ZZabm0tISAiTJk3irrvuKvH8ypUrmTlzJosWLeKmm27i888/Z9iwYRw7dozAwEAAXF1dOXjwIElJSYwZM4a7774bHx+fUo9XWFhIYWGh5XFWVhYAsiwjy3INvEPrk2UZRVFKbzlTZHT5SThkn0WXn4CNPguNIRuVqQBFZYOsssGksafQzocCO1/yHQLQ23qBJNX+G6lmRXVSl1sUFUUhu8BIYlYBabl6cgtN5OqN6E0yaklCrZLQaVS42Nng5qDF4/I/6Tr/PvWhTqzhhutFUdAWXsIuJw773PNo9JloDLmojXkgqTCpdchqO/S27uTbB5Dv4E+hnQ9Idfe3bUP7rOQWGknOLiQlu5CcQiP5BhOFBhkFBRu1Cq1GhaNOYznH3B11aFTFzzNzfdBgv0uuV9F3UHXXS2X3Jyn18FMqSRKrV69m1KhRlm09e/aka9euLF682LKtXbt2jBo1ivnz55fYx7Rp07j55pu55557Sj3Ga6+9xty5c0tsP3XqFE5OTjf+JuogWZaJjI5HZeuAjSEHt7RI3NIP4pZ2EKfs02hMBVXaX6HWnSyXYDJd2nPJsyeZrh1QVPUmB7dQUJALclHZOiBRNxI8vUkmJrWA6EsFRKfmcz5DT56hahcROxsVAS5agtx0tPOyp7WXLVp15b5Y62Kd1AVVrRfJpMf98nnmmnEEl4yj2BhzqnRMo8aeTOe2ZLp2IN0tlFTPbshq2+t9C9WuPn9WZEXhTFoh0ZfyiU0rIDatkOxCU5X2oVFJNL18nrXytKOdtx32WhXNnMDFxQWVqu4ms7VNlmUyMzOrvV6ys7Np06YNmZmZODs7lxnXIBIivV6Pvb09P//8M6NHj7bEPfnkk0RFRbFlyxaSkpKws7PD2dmZrKwsevfuzQ8//EDnzp1LPUZpLURNmzYlPT293Aqtz+TsJE78+zW+l3bgnrwHlWIs/rykId+xKfn2/hi1Lhi0zshqWyTZgEo2oDFko8tPwjYvEdu8BCSKf0EbbJxI9bmJxMA7uOQ7AEWtrc23d90URcGUm4HawfW6W1SqQ4HBxMELmUTGpXP4YhZ6U/H6lQB3By1eTjocdBoctGq0GhWyrGBSFAoMMhl5etLzDKTl6jHKxU99jUoi2NeJ7s3c6NrUDTutusyy1JU6qWsqUy8qYx7eFzfgHb8Bj8RtaIx5xfeBigL7JpdbWT0wahwwaewBBbWpELUxD23BJexyL2Kbl4BKMRR7vUmlI827Fyn+Q0hqehtGG+v+gKtvnxWTrHAkPpPIuAwOXcgku9BYIsbFzgYvJx0udjbYalTY2qiRMP9QMZhksgqMpOboScstRG8qfp5JErT0dGBYW1ce6NMaXxe7WnpndZ8sy6SkpODl5VWtCVFWVhZubm4VJkT17+d6KS5duoTJZCpx+8vHx4fExEQALly4wOTJky1Nt48//niZyRCATqdDp9MRHh5OeHg4JpP5V4FKpWpYGb0sw5nNELEU6cRfdJSvnPy5Ts1J9+pOpmcYme4h5Ds2RVHZVGq3KmM+jpkncU47guulCNyTdqDVZ+B74R98L/yDQetCYtPhXGg1llyXVjX05qqPJEmWf7XtbGouW0+lsOdMGoXGK0mQm70NbXycaO3tSEsvR3xdbLGpZAuP0SSTkFlAXFoep5NzOBafRVqenqPxWRyNz+I7dRxdmroxKNiLVt6Opb5va9ZJXVZWvTinHcIv9md84/5EY8y1bC+09SbNpzcZHl3I8gglx7lVpX8sSLIR+6wYXNIO4Zx2EI/E7djlxeOVuAWvxC0ER71Bsv8Q4lvcS7pXD6vdwq4Pn5WkrAK2R19iZ0wqmflXkkx7rZq2vk609HKklbcjAa526GzK/rFwNUVRSM4u5GxqLmcu5XIsIYv4jAKiU3L5JCWX8O0X6d/Gi/u6NWVoB1/UqrpbP7VFkqRq/56t7L4aRAtRfHw8/v7+7Ny5k969e1vi3nzzTVasWMGJEydu+JhZWVm4uLhUmGHWGyYDHPoJtn8IqactmzOd25IcNJyUgKHkOTWvvuPJJpzTj+B9YR2+cb9jm59seeqSbz/i2kwizeemOtnnyBq/cBVF4dDFTNYeTiAm5cqXp4+TjrBmbnQNdCPI3b7ayqMoCgmZBUSez2BXbCqJmVdujzbzsOeWdj50b+ZuuWDXt1/9taVEvSgKHgmbaXZiCW6X9lvi8hyakhR4Byn+g8ly61h9fYAUBYes03jFb8T33G84ZsVYnspy68C54MkkB9xWq7eu6/pnJfZSDn8fSSQqLoOiL0MnWw3dm7nTpakrrX0c0VTjl3NqTiEHL2Rw+HwahxOunNuB7vY8fFMz7unWFAddg2irqDJZlklOTsbb27vaW4gq8/3dIBKiytwyu15XtxCdOnWq/idEJgMcWG5OhDLPm7fpnKHzfchdxvHvBV3NX7hkE+4puwmI/gGv+A1IirnVI8OjCzEdZ5Lu07uCHdSu2rygK4rCgbgM/jwUz/n0fMB8K6troBsD2njRxqf01prqLsO5tDy2nkphV2wqhstN/j7OOu4M8aN7M3ckqNNfctZi+azYu+CVuJmWhz/EKfMkALLKhqSAYcS3uPtya00NtzQrCs7ph/GL/YUm59agvtwHMM+hKbEdnyQx8I5a6YxdVxOi2JQcVkVe5ERitmVbR39n+rXyIiTABU0lW1uvh6IodPKAHJUDqw5c5Ie9caTnmVul3OxtmDGoFWN7BWFbyZaohkIkRNehrE7VYWFhLFq0yLKtffv2jBw5stRO1VVV71uIFAVO/AUbXoXUaPM2Rx/o/Th0mwQ6J2RZ5t/9p2r1wmWXE0fT0yvwj11puWCneffiVOgL5Li2q5UyVKS2LugxKTn8tP+8pUVIp1ExKNibIe19cLGr3K3K6pZdYGDLqRQ2HE8m53JfCn9XO+4NCyDYRa5zX3LWpigKThe2Enz6M9wuRQBg1DhwoeX9nG89gUJ7X6uUy6YwjYDoH2gavQJtYRoA2S7BRHd+htQmA2r02HUtIUrMKmD1gYtExKUDoJYkerZw57YOvvi51k5/nqKEqOiLP19v4pcDF/hyWyznUs19ypq42PLULW24OywAVSO5lSYSokrKyckhOtr8Rd6lSxc++OADBg0ahLu7O4GBgaxcuZJx48bx2Wef0bt3b7744guWLFnC0aNHCQoKuu7jNogWopST8NfTcPbyvEz2njDgeeg6HmyujEaxRkJURJufQrPjnxEQ+yMq2YAiqbjQ4n5iOs7EqHOt1bJcq6Yv6Bl5en7af4G9Z81fVFq1iqHtfbilvQ+OdaTpvMBgYsPxJNYdTSLfYO5PF9LEgft6Nsfbue6MaLImbcElWh18B79zvwFgUtsS13o859o+ilHrYuXSmamMeQSeWkbQyS+xMZhbRlL8BnMy9EUKHJvWyDHrSkJUaDDxx6EE1h9LwqQoSBL0aeHBnSF+eDjqarUs1yZERYwmmV8PXGDhhtMkXL5tHdLUlddHdqBzgGutltEaREJUSZs3b2bQoEEltk+YMIGlS5cC5okZFyxYQEJCAh07duTDDz+kf//+1XL8etlCZMiHbe/D9oUgG0Bja24RuulJsC35HqyZEBWxzb1Iq0Pv4nt+LQB6rSunurxEYuCdVutfVFMXdFlR2HoqhV8PXCTfYEICbmrlychQP9zs6+YIvNxCI38cimfjiWRkxXw7784QP25tzB1CFRn/mB9pdfgDbAxZKEjEN7+L2A5PWK1FqCKawgyaH/+MpqeXo1KMmNQ6zrSbzrm2j1R64ERl1YWEKOp8Bj/sjSM1Vw9AJ38X7u4agL+bdUZ4lZUQFSkwmFix6xwf/XeanEIjkgQP9ghk9rC2ONlap7W4NoiEqI6rty1E5/fB6imQdrlTZZvbYNgCcCu7tawuJERF3JJ3Exz5Bo6ZpwBIaTKIE2FzrfIFUxMX9OTsAr7efpboFPOcM0Ee9ozrFUQzD4dq2X9Nu5iexw+7z3AixdzPKcjDnol9mtHUzd7KJatddjlxtN/3Im4pewHIcu3A0fZPk+N/k9XPocpwyIwmOHIe7sm7Achybc/RHu+Q6xpcbcewZkKUW2jk+71x7Dljbn31cNDyQI9AQpu61mo5rlVRQlQkOauA+X+fYHXkRQD8XGx5+67O9G/jVVtFrVUiIaon6k0LkVEPW96B7R+AIoNTE3Mi1G5EhS0sdSkhApBkA0EnvqTFsU9RyQYMNk6cCJtHUuDwWi1HdV7QFUVh6+lL/LT/PIVGGZ1Gxegu/twc7F2v+gkoioIxJ529STIr958nT29CLUmM6mJuLVLVgc9PjVIU/GNX0vrg22iMeRg19sR0nEVcqwcx5WXXmXOoUhQF37jfCY58Axt9JrLKhtj2j3O27WOguvFOvdZKiA5fzGTZzrNk5BuQJLi1vS8jOjep9JD5mlTZhKjIrphUnv/1EHFp5v5FD/QI5JU72mGvrRu31KuLSIjqiXqREKXFws8TIeGg+XHn+2DYO2DnVqmX17WEqIhD5mna73sBl7RDAFxocS+nQl9C1tReB8jquKDnFBr5ZscZDl7IBCDYx4mHb2pW6/0XqsPVdZJVYOTbPeeIjMsAoH0TZyb3bW61juA1TaPPov2+F/C+uB6AdK/uHOs+n3zHwDpxe+h6afNTaBsxB+/4/wDz4IYjPd9Hb3djrRG1XSfmfjgXWX88CQBfZ1sevqkZLbwca/zYlVXVhAggT29kwT8nWbrzLACtvR0Jf6grbXwazsoJIiGq4+rNLbPjf8CaGVCYCXbucMeH0GFUlXZRVxMiME9A1/zopzQ/vhgJhRznVhzuvZBclzY1fuzquKCfuZTLZ1tiSM3Vo1FJjOnqzy3tfOptS8q1daIoCtujL/HD3vPoTTLOthom921OB7+60Zm4ujinHaLjrpnY515AVtkQ3ekZ4tpMsAxfr88JEQCKQpNzq2kbMRe1KZ9CW0+O9nzXPEfYde+y9uokNaeQz7fGEnvJPFJzcFtv7uoagFZTtybTvZ6EqMjO6EvMXBlFcnYhtjYq5t3ZkXu6BdTPz9s1REJUT9TZFiKTATa8Brs+NT9u2hPu/gZc/Ku8q7qcEBVxS9pJxz3PoitIwaTWcbLLHOJblL4eXXW5kQu6oihsOpnCyv3nMckKXk46pg1oSaB7/e5rU1adxGfk8/nWWC5mmPsW3d7Rl1Gh/vXqdmCpFIWm0StoffAdVLKBPIcADvf+iGz3TteE1fOE6DL7rBg67ZqJU+ZJFCTOtJvGmQ6PX9eEjrVVJwcvZPDV9jPk6U3Ya9VM6tOMLoGVax2vbTeSEAFcyilk1k8H2XoqBYCRoX68ObpTnRmVer1EQlRP1MmEKCvefIvs/B7z496Pwy2vgfr6blXUh4QIwKYglQ57n8Mz0TyNwPlWD3Eq9MVqHx1T5Hov6AUGE8t3nbMMp+8S6MqkPs0axH3/8upEb5T5af95Nl++WHf0d+axfi3q7ftWGfNpv282vuf/BiDZfwjHus/HqC15HWgoCRGAylhAm6g3CIj9CYBUn5s43HthlacQqOk6kRWFNZEXWXvEvExTMw97pvRviZdT3b0VfaMJEYAsK3y+NZb3/j2JSVZo4+PIl+O7E+hRT39sySbk6I0kO3eyWkJUt9oR66Dw8HDat29P9+7drV2U4uIjYcnN5mRI5wL3fQe3vnndyVB9YrD1IKrfEqI7PoWCRNPo7+iydTI2lyecqwvScvW8888J9p5NQy1J3NstgOkDWtbbpKAqtBoVY3sF8Vi/FmjVKo5czOKttSeKLQdSX+jyEum26UF8z/+NrLLhZOhLHOrzaanJUEMja2w50e0NDvf6AJPaDo+kHXT/717ss2KtXTSLAoOJRZtjLMnQ4LbezL6tbZ1OhqqLSiUxbWBLfprSC28nHaeSchgZvp1dManWLlrVFWTBD/ej+v5ubKP/sloxRAtRJdWpFqKja2D1VDDmg1dbeOAHcG9xw7utLy1EV/OM30jH3U+jMeaS7xBA1E2Lq3XIMFT9F27spRzCN8WQmW/AyVbD9IEtae3dcDo+QuXr5FxqLp9uiiY9z4CdjZrH+regk3/96FfknHqQkB0z0BUko9e5cajPp2R4lf/DqCG1EF3NMf0YITumY5cXj8HGicO9F5Lm269Sr62pOknNKeSTTdFcSM9Ho5KY2KcZvVp4VNv+a1J1tBBdLSmrgMeW7+fghUw0KolX7+zAuF7XPyFxrUo/C9/fDynHUTS2ZA6cj3OfiaKFSKiAosDWd+HnCeZkqNUtMPnfakmG6qtLfjezb/BP5DkGYpd7ge4b78MjfpPVyrPvbBrvrjtJZr4Bf1c7Xr69XYNLhqoiyMOBl4e3p5WXI/kGEx//d5oNl0f/1GU+cX8StnksuoJkclzasHfwLxUmQw1Zjlt79t7yKxmeXbExZNNl26M0PbXUfE2ygpiUHN5Ye5wL6fk422p49tbgepMM1QQfZ1tWTunNyFA/jLLCK2uO8PKawxhNsrWLVr64PeY7HSnHwdEXZcJfFLS63WrFEQlRfWHUmyda3PiG+XHPafDASrCtH7+2a1KuS2v2Dv6FVO/eaIx5hO6Yhn/Mj7VaBkVR+PNQPJ9vjcVgUugc4MILw9rWyyH11c3Fzoanh7ahXytPFODHfef5af955LrYOK0oNDu2mE67Z6E2FZLidzP7bv6xxpa1qE8Mth5EDFhOfLO7kBSZ4Ki3aBP1lnm+s1pU9KMju8BIUzc7Xrq9HS3r0JB6a7G1UbPwvlCev60tkgTf7o5jyooI8vRGaxetdMf/gOV3Ql4qNAmBxzaBf1erFkkkRPVBYTZ8fw8cWgmS2jykftjboG74/VEqy6hzJar/l5aLdbuIObQ4vLBWfsHKssKK3edYExUPwND2Pjw+sFWjW6m6PDZqFeN7BzGmi3n047/HkvhiayyGuvQLVjYRfGAurY58CMDZ4Mkc7BOOyUZ82RZR1FqOdX+LU52fByDw9DI67XoKlamwVo7/33Hz58YoK3Rp6srzt4kfHVeTJHO/os/GhqHTqPjvRDIPLNlDak7t/H0qbe8SWDkOjAUQfDtM+huc/axdKpEQVcTqnapzkmHpHRC7GWwc4KGfoNvD1ilLHaeobDjW/S1i2z8OQIvji2i/bzaSbKixYxpMMou3xrD19CUk4KGegdzbrWn9H2ZeAyRJ4vZOTZjctzlqlcT+c+l8uOEUuYXW/wWrMhbQedeTNI35HgWJE11eITrk+WqZqbnBkSTi2k7mcK8PkFU2+Fz4my5bJ6PRZ9XYIRVF4ZeIC/yw7zwKMCjYi2kDWoofHWW4tYMv3z/aC1d7Gw6ez+CuxTs5l5pr7WKZf6BueA3WPgMoEDYJ7l0B2rqxZJHoVF1JVulUnRYLK8ZA+hnzCvUP/QT+YTV2uPrYqbosfrE/0TbiVVSKiUu+/TjU5xNkzfUNRy2rU2ie3sgnG6M5nZyDRiXxaL8WhAXVzXlPqtuNdpQ9npDFos0x5BtM+LnaMuuWNrhaaUFbjT6TkO1TcbsUgayy4UjP90luett17auhdqoui1vSLkJ2zkBjyCHHuTWR/b8qsd7gjdaJUZZZtvMcu2LNo6dGd/Hn9o6+9bp+q7tTdVliUnKY8PVeLqTn4+mo5ZuJPegUYKVuFiYD/PY4HLrcneHml6HfM8WWlLL2PESihaiuSjgEXw01J0OuQebO0zWYDDU08S3u5WDfxZjUdngmbqPr1odR67Orbf8ZeXre+eckp5NzsLNR89QtbRpNMlQd2jVx5rnbgnG1syE+o4B3/jlJSnbtN+vbFKQStmksbpciMNg4Edn/6+tOhhqjdJ/e7B/0HYW23jhmnabbxgewy4mrtv0bTDLhm2LYFZuKSoJJfZoxvFOTep0M1aaWXo6smtaH9k2cuZSj54Elu9l7xgrTkxj18MskczIkqWHkIuj/bIXra9Y2kRDVRef3mm+T5aaAbyeYvB48Wlq7VPVOapOBHBjwDQYbJ1wvHSBsy3hsCm78YpCWq2fBupNczMjHxc6G524NJti38Y4ku15N3ex5/ra2eDnqSMkpZMG6E8RfnuG6NmjzkwnbPBanzJMU2nqzf9D3pHv3rLXjNxQ5ru3YN3gluY7NsMu7SLeND+KQefqG91toNPHJxmgOX8xEq1bx+KBW3NTKsxpK3Lh4O9uyckoverVwJ6fQyPiv97Dl8qSptcJYaB4ZffwPUOvM08R0eaj2jl8FIiGqa85sg+WjzGuSBfaGiX+Bk4+1S1VvZXp2JWLgCvQ6d5zTjxK2+SF0eYnXvb/UnELeXXeS5OxCPB21zL6tLU3r+TIc1uTlpOP524Lxc7ElPc/AgnUna6Wvgy4vkbDN43DMiqHAzpf9g76t9vmrGpMCB38iBn1HjksbdAXJhG16CKe0I9e9v0KDORk6lpCFTqPiycGt6RzgWn0FbmScbG1YOqkHg4K9KDDIPLJsH/8cSaj5AxsKYOVYOLkWNLbmZKjNrTV/3OskEqK65PQG+O5uMORCi4Ew9lcxrL4a5Li1Z/+g7yiw88UxK4awTQ9eV7N+SnYhC9adJCWnEC9HHc8ODW4UM+LWNFd7Lc/eGkyQhz05hUbe+/cUp5Oq7/bmtXR5CYRtHotD9hny7f2IGPQt+U7Naux4jYXezov9A78l070TWn0GYVvG43Iposr7KTCY+GjjaU4kZqPTqJg5uLVoga0GtjZqPh/XjeGdmmAwKcz4PpLVkRdq7oD6PPjhfjj9L2js4MGV0GpwzR2vGoiEqAK1Nsrs+B/mD4+xANoMM88xVEd63jcEec4t2X/zD+Q5BmKfe4GwTQ/ikBld6den5Bh479+TpObq8XHS8eytwWK4bzVysrXhmSHBtPExT+D44YbTHI3PrPbj2OZeIGzTQ9jnxJHnEGBOhhwDq/04jZVR58qBActI9+qOxpBD1y0P4560o9Kvz9eb+HDDKU4lmfvmzRrShtY+IhmqLlqNio8f6MI9YQGYZIVZPx3k293nqv9A+lz4/l6I3WQeHT32F/OP/DpOJEQVmDFjBseOHWPfvn01d5BDP8NPE0A2QIfRcN8KsLGtueM1UgUO/uwf9D05Lm2wzU8mbPNDOGacqPB1iVkFvL/1Iml5BnxdbHn21mDcHawzIqohs9OqeXJwazr6OaM3yXyyMZpDFzKqb/85cYRtGot97gXyHAOJGPQdBQ4B1bZ/wcxk40hkvy+55NsPtSmfLtun4JW0tcLX5emNfLjhFDEpudhrzcmQmHCx+qlVEu/c1ZmJfZqhKPDymiMs2VqN69MVZsN398DZbaB1gnGroFnf6tt/DRIJkbVFLINVj4JigtCH4K6vGsUCrdait/MmYuAKMt06oi1Mp+vm8ThmHC8zPiEzn/f+PUVGgYkmLrY8OzTYasPDGwOdRs3jg1oRFuiGUVYI3xxD1PmMG96vXfZZwjaNxS4vnlyn5kQM/JZC+yY3XmChVLLGjoM3LSbZfygq2UCXAy/gdXFDmfG5hUY+WH+K2Eu5OGjVPD2kDc09RQt5TVGpJF4d0Z4Zg8yDdd5ce5zPtsTc+I4LsuDbu+DcDtA5w7jVENjrxvdbS0RCZE2KAjEbAQW6PwJ3fiomgqsFBp0bkQOWWvo6dN08Acf0YyXiLmbkX1mXzFnLM0Pa4GInktWaplGreLR/c7oFuWGSFRZviSEyLv2692efFUu3TWOxzU8kx7klEQNXlJgrR6h+ilrL4d4LSWw6HJVipPOuJ/G68G+JuJwCI++vP8XZ1DwcdRqeGRpMkIdIhmqaJEk8e2tbnrqlDQBv/32CRZsr342ghPwMWDEKzu8x930d/xs0rV/r/zWahOj8+fMMHDiQ9u3b07lzZ37++WdrF8k8B8OYJTAyHG5/D2pwgi6hOKPWmQP9l5LpHnK5A+gEnNKPWp6/kJ7He/+eJKvASICbHU/188NZJEO1RqNS8Wi/FnRvZk6KPtsSy4HrSIocMqOLLdJ6YOAK9HbeNVBioTSKSsORHguI97sVlWKk066ZeF9YZ3k+u8DAe+tPEpeWh5OthmeHBotRm7XsyVta8/QQc1K04J+ThG+6jqQoLw2Wj4SLEWDnDhP+sPq6ZNej0XwDazQaFi5cyLFjx9iwYQNPPfUUubl1YCpzjRa6jK1zE1Q1BiatEwf6f02GRyg2+ky6bp6AU9oR4tLyeO/fU2QXGAl0t+eZIW1w1ImWu9qmVkk80rcFPZq5Y1IUPt8SS8S5yidFDhknLydDl8h2CSZiwHL0tmIem9qmqDQcCnmV+MA7USlGOu6aiff5v8nMN/Duvye5kG6ez+vZocH4u9lZu7iN0v8Gt+bZW83TTry77iSf/FeFeaRyU2HZnZAQZV5RYcIf5sVa66FGkxA1adKE0NBQwDxduru7O2lpVpixU6hTTFrz7MQZHl2xMWQRunkC//z7FzmFRpp52PP0kDY46MQiutaiVklM7tucns0vJ0VbY9h/tuLz1jH9GGGbx6EtTCPLtT0HBi7HYOteCyUWSiWpOdrjbRKCRqJSTHTcPYsDf39NfEYBrpeTIT9XkQxZ04xBrXjuNnNS9P76U3y0oRJJUU4KLLsDkg6Dg7d53jzfjjVc0ppTbxKirVu3MmLECPz8/JAkiTVr1pSIWbRoEc2bN8fW1pawsDC2bdtW6r7279+PLMs0bdq0hkst1AcmG0ci+39JoksoOmM2X0pvcrvbBWaJZKhOUKskJt/UnN4tPJAV+GJbbLnLDzilHyVsywS0+gwy3TtxYOAyDDqxrIrVSWqOdn+bswHmpGiu4UPut9vLs7cG4+siRtXWBdMHtmL2sLYAfLjhFB+uP1V2cHYiLB0OycfA0decDHm3raWS1ox6kxDl5uYSEhLCp59+WurzK1euZObMmbz00ktERkbSr18/hg0bRlxc8Qn4UlNTGT9+PF988UVtFFuoJ05lwPC0meyR2+Is5fGRYR6+2dc/065QvVQqiUl9mtGnpTkpWrI9lj1nUkvEOacdouvmCdjoM8nwCOVA/6UYtWJy07oiNc/IfYkP8ZNxABpJ5i3lYzqnr7d2sYSrTB3QkhdvNyc2H/13mg/+PUmJNeCz4s3J0KWT4OwPk9aCVxsrlLZ61cvV7iVJYvXq1YwaNcqyrWfPnnTt2pXFixdbtrVr145Ro0Yxf/58AAoLCxkyZAiPPvoo48aNK/cYhYWFFBZeWWwyKyuLpk2bkp6eXnur3dcyWZZZH3G60azUXSQ6OYePNp6mwCDT2UvN19r38Ezdh1HjwIH+X5HhHtqoVjCvDGut6i4rCst3nWNHTCqSBA/3aUavFh4AuKRG0mXrI9gYc0j36EpkvyWYbGp3HpvGttp9ZRTVSbpix/vrT5Oaq8fLQcOPTX6g5YXVKKg40uMdEoPutHZRa03RavdeXl41utr9jfhy+xneWmuep23GwJbMGtLa/JnOPI+0fCRS+hkUlwCU8X+AW7NqOaYsy6SkpFR7vWRlZeHm5lbhavcN4n6AXq8nIiKC2bNnF9s+dOhQdu7cCZg/gBMnTuTmm2+uMBkCmD9/PnPnzi2xPSUlhYKCguopeB0jyzJyYS5IINE4LuanUvIJ35lAoUkh2MuOyb19ieRduu6fhUfaAbpueZj93T8g1b51o6qXiigoVvusPNTZBUx6dpzN5usdZzEV5nGbYwxd9z2FxpRHmntXIsLex6Q3gj6jVstmzXqpqxQUktMz+WhPHGn5RrwcbHiqnx+n7Z5DK8k0Pf8bHfc+j1KYQ7z/7dYubq1QUMhQm7+X6mpCdGcbB/JyAli49QLhm2PIzsnl8c4y7n9MQJN9EaNTAGl3LEc22ENycrUcU5ZlMjMzq71esrMrtxRQg0iILl26hMlkwsen+CKoPj4+JCaaF/LcsWMHK1eupHPnzpb+RytWrKBTp06l7vOFF15g1qxZlsdFLUReXl4NuoVIdT4TtX3j+HV7PCGLT3cmoDcptG/ixPSBrdBpzCdh1ICvCd0xFY/k3XTbN4v93d4ny31Qo6iXylAUBRSs8llRA+P7uqK2iWPr6UuciNjCi3bvoZHzSfXuRdRNi0FjjzXGBVqzXuqqxMx8Fu45R3q+CR9nHU8PaYPb5clNT/R8G8nGloDYlXQ6OA+V1paEZmOsXOKapygKrq51u4UI4InbvHF2dmLen8fZHHGQp0+9g0afiOLeAtW43/B0qd6Z3mVZRpKkaq8XW9vK9VFrEAlRkWsvQIqiWLb17dsXWZYrvS+dTodOpyM8PJzw8HBMJhMAKpWqTn+Ab5QkSZZ/DdnR+Ew+3RSNwaTQ0c+ZGYNaYaO+8ndVbOw52PdzQnZMxyNpB932P0WU7Rdk+NSfWVdrmjU/K2pJYmyvIDoURvJE0jtoZT3RTj2I6/sFisbWqm0zjeUcqozEzALeW3+azHzzTO/PDA0uPrmppOZE2FwUSU3TmO/psO9FVIqJ+Bb3Wq/QtUSS6sf3ycN9W+BWEEevba/jok/jkm0gHhP/QuXsVyPHkySp2uulsvuq23+JSvL09EStVltag4okJyeXaDWqqlpZy0yoVUcuZvLJRnMy1NnfpUQyVKRo+YFLPn3RmArosv0x3JJ2WqHEQmk8k7bzzKU52El6NppCGZ4ynU2xlWsaF2pefEY+C9adIDPfgF95M71LKk52fZW41uORUGi//2X8o3+o/QILpUs5xeioKTSR0jgl+zMsYzZzN6eX7GjdADSIhEir1RIWFsb69cVHK6xfv54+ffrc0L5rbbV7oVYcvJDBp5uiMcoKoU1dmT6wZanJUBFZY8vBmxaR7NUHtamA0O1TcE/cXoslFkrjkbCZ0O1TUcuFJPvdzE8t36IQLSt2n2PTierpzyBcvwvpebx71Uzvsyqa6V2SOBX6EufaTASg3YFXCTi9onYKK5Qt6RgsvR1yEsG7A0eHfMclyZWlO8/yym9HkOWGlRTVm4QoJyeHqKgooqKiADhz5gxRUVGWYfWzZs3iyy+/5Ouvv+b48eM89dRTxMXFMXXq1Bs6rmghajgi49JZtDkGo6wQFujG1AEt0JSTDBWR1Toiu75DSpNBqE2FhGyfikdCxat3CzXD6+IGQnbMQCUbSPYfyuHeH3NX95YMbW9uDf5ubxz/HU+ycikbr+ue6V2SOB3yAmeDHwGgbeTrND21tGYLK5Qt8bB50sXcFPDtBBP+YHS/LrxzV2ckCb7dHcdLaxpWUlRvEqL9+/fTpUsXunTpApgToC5dujBnzhwA7rvvPhYuXMi8efMIDQ1l69atrF27lqCgoBs6rmghahj2nU3jsy2xmGSF7s3ceLR/czRVuEetqLUc7PMxyX6DUct6QnZMwyNhc80VWCiV9/m1dNr5BCrZQFLAMA73/hBFrUWSJO4JC+C2DuZFW3/Yd571x0RSVNtiL+Xw3r8nr3+md0kiuvOznGk7BYDgqLcIPPlVDZVWKFN8JCwbAXmp4NcFxv8ODubpLe7t1pT37wlBJcEPe+OYvepQg0mK6uU8RNaQlZWFi4tLhfMY1GeyLPPv/lMNbg6VnTGX+GbnWRQFejZ35+GbmqNWVf79XT23jEo20Gn3LLwv/oussuFQn0+45HdzDZa+brLGfDtNzq6m/b4XkBSZhKA7Odb9bRRV8S9bRVFYHXmRtUfM/QnvCQvg1g61t7J9Y56H6HRStmU+r5ZeDjw5uDX2Ws311Ymi0OLox7Q4Fm7ed6dnONfusRosfe0qmofI29u77nWqjtsD390NhVng3w3G/gp2riXCfou6yFMro5AVuKtrAAvu7lyl62ppZFkmOTm52uulst/fdewvUfeIFqL6bcupFL7eYU6G+rXyZHIVk6FrKWoth3t/SFLAMFSygc47/4fXRTHTbk3zj/mR9ntnIykyF5vfw9EeC0okQ2AeoTK6iz93dG4CwM8RF/j7SEJtF7fROZ6QxYf/mZOhtr5OPHVLG+y1NzCIWZKI7fgkMR2eAKD14fdodmxxBS8SbljsFlgx2pwMBd0E41aXmgwBjAz156P7u6BWSfx64AJP/xSF0VT5kdx1kUiIKiD6ENVf648lsWL3OQBubuvNuN5BqG7wFwyAorLhSK/3SWw63NxitPNJfM79ccP7FUrX9PRy2kXMQULhfKuxHO/2OkhlX7okSWJUqD93hpiHBf964CJrIi82yFExdcGhCxl89N9p9EaZjn7OPHFza2xtqmcWqDMdHie641MAtDryIS2OfATi71gzTv0L390DhlxoeTM89AvYln83ZESIH5880AWNSmJNVDxProxCb6y/SZFIiKxMURQOxKVbuxgNzl+HE1i5/zwAt3Xw5YHuTVFV4y0MRaXhaM93L6/ebaTjnmcIiP6u2vYvmAWdWEJw5BsAnA1+hJNdXik3GbranSF+jOniD8CfhxP4Ye95ZPFlWq0OxKUTfnmgQmhTV2YMaoVWU71fK2fbT+N052cBaHEsnDaRb4BSf79066Rjv8GPD4KpEIKHwwM/gta+Ui+9vVMTPn2wKzZqib8OJfDo8v3k6001XOCaIRKiCtT0LbP3/z3FmEU7+Xr7mRrZf2NT1IdkdeRFAEaG+nFXV/8a6c+hqDQc7fEO51uNRUKh7YG55mZ98aV74xSFFkc+ovWhdwGIbT+D6M7Pmmezq4LbOzXhoR6BAGw8mczXO85grMIErULZdsem8tmWGEyyQrcg86jN8qawuBHn2j7KiS7mATSB0SvosPc5JNlQI8dqdA79BD9PAtkAHe+Ce5eBRlelXdzW0Zcl47tha6Niy6kUxn21h8z8+vf3EQlRBWrylpmiKOTqjQDM+/MY7647IZr1b4AsK3y7J46/Dpv7jNwTFsCIzn4127lVUnGyyyvEtp8BmJv1Wx1aIJKiGyGbaBvx6lUdap8mtuOTVU6Gigxq680jfZujkmB3bBqfbY7FUM/7OljbhuNJfLn9DLICvVt48Gi/FlUatXk9LrQey+Ge7yNLGpqc+53OOx5HZWyY60rWmr1LYNVjoJggdCyMWQLqcuaLKsfAYG++ndwTZ1sN+8+lc/8Xu0nJLqz4hXWISIisSJIk5tzRnmdvDQYgfFMML64+gqmBDGGsTQaTzOdbY9lyKgUJGNszsPZGF13uAHoq5AUAmp38inb7XwK5fjYbW5Nk0tNp91MExP6IgsTxsHmcazflhvfbq4UH0we2QqOSiLrc56XAIP4+VaUoCqsiL/DjPvPt6FvaeTPppmY3PLqospKCRnDwpnBMah1eCZvosm0yar2YnbzKFAU2vgFrnwEU6PEY3PkJqG6s71e3Zu6snNIbT0cdxxOyuOeznZxPy6ueMtcCkRBVoKZvmUmSxIxBrZg/ppNlXocZ3x0QF+sqyNMbWbjhNBFx6WhUElMGtGBgsHetlyMueBJHu89HkVT4n/mFTrufQmWqX7+QrEltyKHLtkfwufAPssqGw70/4mLL+6tt/6FNXZl5S2t0GhUnErN579+TZNXDZn1rMckKy3edY+1h85QGo7v4c1+36u2bVxmpfoOI7P81RhtH3FL2EbZ5HDYFqbVahnrNZIQ/noCt5tvRDHoJhi2Aamrha9fEmV+m9ibAzY6zqXnc89kuTifVj6RVJEQVqK1RZg/0CGTRQ13RqlX8czSRid/sJTNPXKwrkplv4N11JzmZlI2tjYqZt7SmW5C71cqT0PwuDvX+CFllg8+Ff+iyZSI2haLTfEW0+cmEbR6Pe/JujBoHIvstIbnpbdV+nLa+zjw7NBhHnYazqXnM//sEiVnitktFCo0mPtsaw7boS0gSjO8VxPBOTaw211KGV3ciBn6LXueOc8Yxum+8D/ts0Q+zQoZ8+GkcHFhuHpxwx0IY8Nx1344uSzNPB36Z2ofW3o4kZhVw92e72B1b95NWkRDVIbd1bMLSh7vjqNOwOzaNMYt3EJdaf5oba9uF9DzeXHuc8+n5ONtqeG5oW9r6Wn/SzJSAW4ns/xUGGyfcLkXQ7b/7sMuJs3ax6iyHjJP0+O8enNOPoNe5ETFwOek+N7YGYXmaeTow+7a2eDpqSckpZP7a4/XmF6w1FP3oiIzLQKOSmNq/Jf3beFm7WGS7tWf/zT+Q7xCAfU4c3f67D9cUMT1KmXJSYPlIOLkW1Dq4dwV0m1Rjh/N1seWnKb3pGuhKZr6BcV/tYdWBCzV2vOogEqI6pk9LT36e2hs/F1tiUnIZtWgHEefSrF2sOufwxUze/ucEabl6fJx0zB7WlkCPyg0TrQ3p3r3Yf/NK8u39ccg5S/f/7sE5NcraxapzPBK20n3j/djmJZDr1Jx9N/9EtnunGj+ur4stLw5rR3NPB3L1Jt5ff4q9Z8R5dq2L6fm8ufY4Z1PzcNRpmDWkDWFBbtYulkWeU3P2Df6JTPfOaPUZdN0yEd9zv1u7WHVP0jH48mY4vwdsXcwTLra7o8YP6+ag5ftHezG8UxMMJoVZPx3kw/Wn6uzgIZEQVcAaM1W3a+LMmhk30cnfhbRcPQ8s2cNvURdr7fh13X/Hk/j48hIBwT5OvHB7O7ydbK1drBJyXVqxb/BPZLl1RFuYTtjmcXifX2vtYtUZ/tHfE7J9ChpjLmlePdl380rynW5s7cGqcLaz4ZmhbejS1BWjrPDFtlj+PBRfZy/Wte3IxUzm/3Pc/KPDWccLw9rSxsfJ2sUqQW/rScTAFSQF3IpKNtBxzzM0PxouRnoWOfUvfDUUMuLArTlM3gDNbqq1w9vaqPnkgS5MHdASgI/+O83TPx2k0Fj3+smKtcwqyRprmeXpjcz8MYp/Ly9S+b+bWzHzljY1NqKjrq9lZpRlVu47z6aTKQD0beXJ2J6BlVqx/kbc6PpUKmMenXbPwit+IwBn2z5KdMdZNzyiw5pupE4kk542B9+mafS3AMQ3G83xsNdR1NqaKGqFZFnhp4jzbDieDEBYoBuTbmp2XbMtN4S1zBRF4b8Tyfy0/zyyAsE+Tkwb2BLHqizSes3+aqVOFJlWh96j2ckvAUgKGMax7m9hsnGouWNep1pZy0xRYM9nsO5F80SWQX3hvhVgb70+lj/sjePlNeaR1CFNXflsbFeauNhZnhdrmQllstdqWDw2jEf7NQfgk43RTFq6j/RcvZVLVvvS8/S8t+4Um06ah9Xf1dWfCb2DajwZqg6yxp6DfcI5G/woAM1OLKHLtkfRFGZYt2BWoM1PImzzeEsyFN3xKfMirVZKhgBUKon7uwcyvlcQapVERFw6b/19nKRG2Nm6wGBiybYz/LjPnAz1aenBU7e0vu5kqFZJKqJDnuN42LzLgxr+pvt/9zTOztb6XFgzDf6ZbU6Guowz3yazYjIE5sFDSyd1x8XOhoPnMxjxyfY61dlatBBVkrVXu18deYEXVh2mwCAT4GbHZ2PD6OjvUq3HqKstRCcSs/h8ayzZBUbsbNQ8fFMzugTWXj+G6vyF631+LR32voDalE+eQwCHbgonx7VdNZW09lxPnbgm76XT7pnoCi5hsHHiaM/3uOQ3qIZLWjUxKTks2hxDZr4BOxs1j/ZrTucA10q/vj63ECVmFrBoczTxmQWoJYl7ugUwuK33Db8Pa9SJy6VIOu36H7b5yRhtHDnS410u+Q+ulWNXRo22EF06DSvHQcpx80iyIfOg9+PVPpLsRsSl5jHl2wiOJ2ShVkm8dHs7Jt3UDEVRrNpCJBKiSrJ2QgTmFaWnfhvBudQ8tBoVb4zsyD3dAqrtIlPXEiJZUfjnSCKroy6iKBDgZse0AS3xca7d/kLVfUF3zDhB5x0zsM89j0lty6mQF8zz7dSBOq+sKtWJIhN46htaHXoPlWIi2yWYQ30+rdX+QlWRkadn8ZYYYlJykYChHXwYHepfqdbI+poQRZxL55udZygwyLjY2TB1QAtae1dPfyFr1Yk2P4VOu57E7dJ+AM60nUJsxydQVNc3E3N1qrGE6Miv8PsToM8BB2+4+2to3q/69l+N8vUmZq86xG9R8YB5odg3RrYnPyu97idEv/9e9Z77Q4YMwc7OruLAeqAuJERgHgI7a2UU/50w93cY3rkJb43qhIv9jZ/kdSkhysw38M3OMxy5mAWYm+4f6hmITlP7/W5q4oKuKcyg456n8UzcBkCK32COdXsTg611m7Qrq7J1os1Pof2+2Zb3mRB4J8e7vY6sqdvXBYNJ5sd959lyytxfLcjDnkf7tsDXpfxkvL4lRIUGEz9FXLC8zzY+jkzp3xIXu+pLGqxZJ5JsoPXBdwg8vRyATPcQjvR6n3zHwFotx7WqPSHS58H6V2Cfuf8UQX3h7q/AqZZm679OiqLwzY6zvLn2OCZZIcjDnrlDA+nfqXndToiqWjhJkjh9+jQtWrSo0uvqmvDwcMLDwzGZTJw6dcrqCRGYO4Eu3hLDh+tPYZQVmrjY8v69IfRp6XmD+60bCdGBuHSW7zpHTqERjUriwR6B9GvtabUy1dgFXZFpeno5rQ+9i0o2UGjrxdEe75Dm27f6jlFDKlMnnvEbab/vBbSF6ZjUOk6HzOZCywfrVUvYgbh0lu08S67ehFaj4v7uTenXquzPYn1KiM6m5rJkWyxJWebZ1G/t4MPoLv7VviZZXagT7/Nrabf/FWwM2Rg1Dpzs+goJQaOt9lms1oToQgSsngKpp82P+84yzz6trgf9vi6LOJfGEz9EcTEjn2l9/Hj2jpC6nxAlJibi7V25JRGcnJw4ePBgvU+IitSVFqKrHTyfwcyVUZy5lAvA2F6BPH9bW5xsr+/XnbUTouwCAz/tv8Cuy53smrrZ8Ui/Fvi7Wrc1oaYv6I4Zx+m4+2kcs6IBON/yQaI7P4PJxrHaj1VdyqsTm8I02kS+RZM4c6tytkswR3p9QK5La2sU9Yal5+n5avsZTiSaJ28MCXDhoZ5BuDuU7AheF778K6I3yvxxKJ51RxORFXCzt+Hhm5rTrknNXNfqSp3Y5l6kw55ncLsUAcAl3/4c7/Y6hfZNar0s1ZIQGQpg23uw7QPz4qxOTWDkp9DqluotbC3JzDOwbOcZ7u7ghK+PT91OiCZNmsTHH3+Mk1Pl7itPmzaN119/HU/PG2u1qCvqYkIEkFto5I2/jvPDXvNMyE1cbHljVEcGt/Op8r6slRApisLu2DRW7j9PTqERCbi1gy+jQv3qxCiy2rigq4wFtD70Dk2jvwOgwM6Hk13nkOI/pEaOd6NKrRNFwef8XwRHvo62MB1FUhHXeiLRnWZZdRRZdZAVhXVHE1kTFY9JVrC1UTGmSwADg72KreVVV778y3IyMZvlu86SdHkV8m5BboztFVSjo8jqUp1IspHAk1/R8ujHqGQDRo0D0Z2e5kLLB2p1GowbTojObIU/n4JU848oOt4Ft79n9VFkN8raw+5Fp+pKqqsJUZGd0ZeYveowcZdXFh4U7MXLd7SnpVflWxmskRDFpeaxcv95Tl5eOsHf1Y4JvYNoUYVy17TavKC7Je2kXcSr2OecA+BSkwGcCnmePOdWNXrcqrq2TpzSj9Em8g1LB9YclzYc6/YmWR4hVi5p9bqYns/y3WeJSTG3yjbzsOe+bk1pfXnCwrr05X+11JxCfjlwgX1nzevqudjZMLZnYK2M1qyLdWKfFU37fS/ienn2+GzXtpzs8goZXrUzAe91J0SZF+C/eXBopfmxoy8Mewc6jKqRcta2epkQ5efnoygK9vbmpRLOnTvH6tWrad++PUOHDr3+UtdhdT0hAnOv/YX/neLr7WcwmBQ0KolxvYOYPrAVXk66Cl9fmwlRWq6eNVEX2RWTigLYqCVGdPZjaAefau/DcKNq+4KuMhbQ/Pgigk58iUoxIktqLrZ8gNj2j9eZTtdFdWIv5dPyWDh+Z35BQsGktuVs2ymcbftovW8VKousKGw5mcKqyIvkG8yz7YYFuTGmiz/eTro69eWfpzfy79Ek1h1LxGBSkID+bby4q6s/9tra6WNSFxMiAGQTATHf0/LIR9gYzIM3kgKGEdPxCfKcW9booaucEBVkwfYPYfciMBYAEnR/BAa/Yl6Ko4GolwnR0KFDGTNmDFOnTiUjI4O2bdtiY2PDpUuX+OCDD5g2bdoNFb6mjB49ms2bNzN48GB++eWXKr22PiRERWJTcnjzr+OWkWh2NmrG9w7isf4t8HAsOzGqjYQoNaeQv48ksj36EkbZ/NHr2dydMV38yy2bNVnrgm6fFUvrQ+/iFf8fACa1HRdaPsC54Mno7ay7uKY2L5Ggwx/T9PxvqGQDAIlNh3O687MUOvhZtWy1JSvfwG8H49l6OgVFAZVk/izf2tIBf98bn7/nRuTpjWw4nsz6Y0mWpK2NjyP3dw8k0L121/yrswnRZTYFabQ8shD/2JVIKCiSioTAOznTfkaNTQ1R6YQoPx32fAF7Fpv/DxB0Ewx9A/y71kjZrKleJkSenp5s2bKFDh068OWXX/LJJ58QGRnJr7/+ypw5czh+/PgNFb6mbNq0iZycHJYtW9agE6Ii206n8N6/pzh4PgMAWxsVo0L9mdCnWakdKGsqIVIUhdhLuWw+mcLeM2mYLn/kWns7cndYQJVu61mDtS/obkm7aH3oXZzTjwBgUutICBrNhVYP1Pqkjs5ph2h6ejk+cX+jUsyJUJpXT2I6PkmmV7daLUtdcSE9j18PXOTwxUwAJKBLoCuDgr1p6+tUq5+ZpKwCNp5IZmdMqiUR8nO1ZWSIP10DrfP5tfb5U1mOGSdocfRjvC9uAEBBIsXvZs63mUi6V49qHZFWYUKUGgMR38D+paA3dyfAo7V5ksXgYfVqpGZV1MuEyN7enhMnThAYGMi9995Lhw4dePXVVzl//jzBwcHk5eXdUOFr0ubNm/n0008bRUIE5hNv88kUFm44xcELmZbt3Zu5MTLUn9s7NbGMlqnuhCgjT8+BuAy2R1+y9G0CaOvrxIjOfgT71r2FIktTJy7oioJH4haaH1tk6fcAkOHRlfhmo0kJGIJBVzO307T5Kfic/xvfuN9wSTts2Z7m3oXYTjPJ8OldI8etb85eyuWPQ/HFzjNfF1v6tvSkezO3GmsBzdebiDyfzp7YNI4mZFm2+7nYMiLEj7Agt2Idv2tbnTh/qsA57RDNj36KV8Jmy7Yc51YkBI0kMXBEtbSAlpoQFWTBqXUQudzcabqIT0foNwvaj6rX6x9WRr1MiDp37swjjzzC6NGj6dixI//88w+9e/cmIiKC4cOHk5iYeEOFL83WrVt59913iYiIICEhgdWrVzNq1KhiMYsWLeLdd98lISGBDh06sHDhQvr1Kz5LZ2NLiIooisL+c+ks3XmWf44kYrp8u0qjkujd0oP+rb3o09KdcxcSsHF0u64Ll0lWOJeWy6nEHA5dzOB0Ug5FHy6NSqJHc3cGBnvRwrNutwhdq05d0BUF15R9BMR8h/eF9agUIwCypCbduyeXmgwkw6sH2S7B13/xlE04ZRzDPWknHkk7cEvZi6TI5qdUNiQG3kFcq7FkaAPqRp3UIYqiEBefxLbzheyKTaXQKFuea+7pQEiAC8E+TjT3dLjuEZSKopCQWcCJxGyOxWdxJD7TcvtZAjr5u3BzW2/a+zlbNREqUqfOnyqwz4qh6ekV+J1dhdp0ZV27TPcQUn37kurbjyz3ziiqqvfFUhSFTu4K3qp0VHG7zIlQ7CYwFa1TKUHrIeZ+Qq2HNtgWoWvVy4Tol19+4cEHH8RkMjF48GD+/fdfAObPn8/WrVv5+++/r7/kZfj777/ZsWMHXbt25a677iqREK1cuZJx48axaNEibrrpJj7//HO+/PJLjh07RmDglVlJbzQhSk9IKL1C1WpUuiu/AOXyWslUKlS2ttcXm59vXsW4NJKE6qqZwcuKTcwq4K/DCaw5nsbRePMvSq3JgKTI2NuoCHCzx9/VHh8XHS62Njjb2WDr7IhKAgkJuaCAnAI9eYUm0vP0xGcUkJiVT1xaHoVGmULNlXpo46qlW6AzPZt54Ghb8sKh2F41x5C+EEmWS8RYYnW2Vy4MBj2SyVQ9sVodFJ18BgOSyVj8eUXBlJeJ2t4FdLblxhZ7nY0W1OqqxxqNSEZDObE2oNagzU/BN+YXvM/9g3PmiWIxBo0TOW5tyXVrRZ5rawrsm2BQO6NXO6FIaiQUJMWETWEG2oJLaAtScMg9g1POaZwyT6IuzEGRr1yEM9w7kxxwG0kBt2G0dUdWazAV5pi/5GQZyVD2gsOKWgM2l+fGMpkqHyvLSPrCaopVg83lTt6KglRY9sKtVYpVqUB7VctPfp7ls1JgkNl3Lo3IuAxOJWVjklQY1ObyatUqWjqpaOJsRxNXW9wdtDjqNDjZ2qBWSSiShMlGS57eRGa+gZzMbJKyCojPyOdiRj7ZBVc+S4qkwt3diZ7N3OnZwh0fLeVeIxTdleuJVFhQ6VgKCy2Jcal1cfW5fFXs1edPUUJUpfPeytcItT4H7+TN+F74A7fkPWBSUBTz60xqLTnObchxaUuuczP0tt4UOgdgsHVBkWxQZFDp89AYsrHRZ2Gbn4B91hnsc87ilnEEtSED6fLlRDGB4tYK2t0JoQ+AS0Cxckg6HdLla4RiMKAYyr5GSFotkkZT9VijEUVf9vkp2dggXT7nqhRrMqEUln1+ShoNklaLLMskJSTg5eJSZkJUFAugyDJKQdnnZ1FsjQ+7T0xMJCEhgZCQKzNK7t27F2dnZ9q2bXs9u6w0SZJKJEQ9e/aka9euLF682LKtXbt2jBo1ivnz51u2VTYhKiwspPCqP2BWVhZNmzZlb6vWOKpL/vJ26N+fgM+uHPtUWDeU/PxS923XvTuBy5ZaHkff1BdTenqpsbYdOxD000+WxzG3DMEYH19qrLZlS5r/cWWJlTMj7kQfE1NqrMbPj5Yb1hObksOmkym0nPM/miSWvip0ptaB+2+fa3n8zrZFdE6NLTW2QK1l7rRw2vo6ExroSpuFc7A7sKfUWIALv26y/N/9vdew37WlzNiL3621XBzdPnkbh83ryoyN/3o1sosrAK5LFuL4z29lxiYs/gGTt3mKe5dln+H0+8oyYxM//BpjYHMAnFcuxfmnZWXGJr2zGEMr87nguOZHXFd8XmZsytwPKewYCoDD36tx+/LjMmMvvfgWBWHm21T2G//BPfydMmP9+6ThHGi+YGTF2XJxZ9m31Zr0SMe1hfkzm5HoSsLmsjvfpk9+gsz+A1E7uGJ79CBerz5VZmzGuCnkjLofAJvoE/g8X/agi6x7J5B130QANHFn8H3q4TJjs++8j8wJUwFQJyfSZNoDZcbm3DaSjEdnAqDKzMDv4dFlxuYOvJX0/80GQCrIx/+h28uMzes9gLRnXrM8Drir7MVqLwZ3YfGtMziZlENOoZHVf7yAran0L6pDHi14vt90y+Mf176Kiz631NicoNakv/+5JdnwnXo/mpSkUmMNAUEkfbTU8tjnyYnYXDhXaqzRy4fEz360PPZ+biramJOlxpqcXUj4Zo3lsdecmeiOHiw1VtbZEv/9lR/NHm/OrjfXCF1+Ep5L3kbaElVmbIthyehczAlrymEnLh0tu2tA0G1Z2IV2QWnWn7QoIymfrSgztunSb7Dv0QOA9O+/J/mNN8uM9V+8CMcBAwDIXL2axJdeLjPW74MPcLrtVgCy/1lH/KxZZcb6vvkGLqPN507Oli1cnDa9zFjvl1/C7cEHAcjbu5fzEyeVGev19NO4T34YWZZJ2LaNnHL26zF9Op6PzwCg8HQ0Z0eOLDPWbdIkvJ99hqysLNzc3CpMiK573KWvry++vsXXSelx+Y9V2/R6PREREcyePbvY9qFDh7Jz587r2uf8+fOZO3duxYGXFeoLSU5OtjwuL8806PXFYuVyfvEYDMbiseX84jGaiscay2mRkE0mkpOTcQRGtHEgy0WLqYw7nZIEthoVCsrl0TTlrF2llpjao2gyzjyUcsoAYMrNsPxfMZb9awPAlJeJYiqsdKx8+dOtGMr+ZWKOzcKUa/4lLBvK/rUBIOdnW8os6ysfq+hLT44tZSjIuWq/5cfKBblXxZbfXy/Jpz8F3vloC1MxaDPKjU3x7sO5kP5kO7XCFJ2K9+a3yy6DIR+5MBckc9nLo+jzLeVV52eXGyvrCyyxqopiDVdiycsqN1YxFF75W+Rllh9r1Ftiy2sduja2Im62Kh7t5oGsuJOYbUDzlwRlnM4qSUKnkbC3UeGs06BWlX3O2agU5KvfU3mtOIpc/JwrJ5ZrY+Wyrz1cvi1meVjeeV+VWOrWNSIPHVn2QbgQVWZsgc4LySbXMmVGeS7d8TXajua5ugqifiw3Nj09g5zL1/eC7PLPjcyMDPIuxxZmVRCblUn+5Vh9VvnnRlZWNoWXYw0ZGeXGZmdnYyiKTS8/Nic3B2NyMrIsk1PBe8vNzUW+vF9TWmq5sXl5eSQnJ5NdwT6LVLqF6NChQ3Ts2LHS9/WOHj1KcHAwGk31z3VxbQtRfHw8/v7+7Nixgz59+lji3nrrLZYtW8bJk+ZfNbfeeisHDhwgNzcXd3d3Vq9eTffupU/EVVYLUerFi/X+llmpsQUFyEYjG6NiijVtFymrObw0xZu49UjlXEirFCtumd1YbEW3qzQ2UHS+VhArbpldflqlBu1V8y1ddcusxDl0TaxUUHbiq0gquOp6UqXYKtwGqxu3zOr/NaKqsYqi0MEdvPz9URfdVtLrUYxl77ex3DJLTkzE09m52m+ZVWsLUZcuXUhMTMTLq3Lzn/Tu3ZuoqKhaXcusxAVIUYptW7eu7ObTa+l0OnQ6XbHFXQE0jo5oHCvuFKyqRMx1xTo41Eysvb25pcrWDuzsS3TiK/boqgStNMVideWPrLnuWG1NxWqBayYUVBSQ9WBnX/wzVlpsVfZbVqyNzZUv+uqM1WiuJDw3GqsoSHoJSZLMF9Pq2u/VD9Rq82exumMlqWZiAcXO3vJZKfccgirtt0qxVycQFcVXKbYK5/3VsVedP0V10uCuEVWNVRRU9qC2sbnyxV9B/Raj01VYF9cVq9UWT/CrK1alKvc6VSxUo0Hj6Fi5xheVCirzfVzJhpxKJ0SKovDKK69YZqeuiL6czLG6eXp6olarS4xuS05Oxsen6mt6CYIgCILQuFQ6Ierfv7/l1lNl9O7dGzu78n99VBetVktYWBjr169n9OgrnSXXr1/PyHI6XFXGjBkzmDFjhqWXuiAIgiAIDU+lE6LNmzfXYDEqlpOTQ3R0tOXxmTNniIqKwt3dncDAQGbNmsW4cePo1q0bvXv35osvviAuLo6pU6fe0HGvvWUmCIIgCELDUzur+1WD/fv3M2jQlSGtsy4PDZwwYQJLly7lvvvuIzU1lXnz5pGQkEDHjh1Zu3YtQUE3thaNaCESBEEQhIav3iREAwcOLHcoO8D06dOZPr3s+QsEQRAEQRBKU31zYzdQ4eHhtG/fvszh+YIgCIIg1H/XlRD17t2brKzyJ0JrKGbMmMGxY8fYt2+ftYsiCIIgCEINua6EaM+ePRSUMhlSVlYWzz777A0Xqi4RLUSCIAiC0PBVKSEaM2YMb7/9NpIkFVsiokhubi4ffPBBtRWuLhAtRIIgCILQ8FWpU3VQUBB//vkniqIQEhKCh4cHISEhhISE0LlzZw4dOkSTJk1qqqyCIAiCIAg1okoJ0YcffgiYl7XYvn078fHxREZGEhUVxerVq5FlmQULFtRIQQVBEARBEGrKdQ27z83NtSzaeqMzQdd1YmJGQRAEQWj4rqtTdU2sYF9XiT5EgiAIgtDwiXmIBEEQBEFo9ERCJAiCIAhCoycSogqIeYgEQRAEoeETCVEFRB8iQRAEQWj4REIkCIIgCEKjJxIiQRAEQRAavcYzfr6WmEwmDAaDtYtxXWRZRo2MSjYgSZK1i1NnKIoCol6KqY46kSU1SOI3mSAIdYNIiKqJoigkJiaSkZFh7aJcN0VR8NAaQclEUqxdmrpDAdDKol6ucqN1omD+vOVjS4HGCUSiKQiClYmEqAKVnam6KBny9vbG3t6+XrYkKIpCTn4hkkpt7aLUOYpsEvVyjRupE0VRKCwo4FJKChizKbBxrubSCYIgVI1IiCowY8YMZsyYQVZWFi4uLqXGmEwmSzLk4eFRyyWsPoqioJdBUomPxbUU2Sjq5Ro3Wic6WzsATMlJFCiO4vaZIAhWJa5A1aCoz5C9vb2VSyII9YvO1hZJklApYq1AQRCsSyRE1ag+3iYTBGuSJAlx1giCUBeIhEgQBEEQhEavUSVEf/75J8HBwbRu3Zovv/zS2sWxuoEDBzJz5swqvcbFXsufv/9WMwW6bP4b8+jbs1uNHkMQBEEQrtZoeokajUZmzZrFpk2bcHZ2pmvXrowZMwZ3d/caO+aGY0k1tu/S3NLep0rxq1atwsbGpkqvORUbh6ubW5VeUx4Xey3f/fgzd9w50rLtfzNnMWXajGo7hiAIgiBUpNG0EO3du5cOHTrg7++Pk5MTt99+O+vWrbN2sazK3d0dJyenKr3Gx9cXnU5XQyUyc3R0xL0ej9Yrj6IoGI3GBncsQRCE+q7eJERbt25lxIgR+Pn5IUkSa9asKRGzaNEimjdvjq2tLWFhYWzbts3yXHx8PP7+/pbHAQEBXLx4sTaKXmdde8usefPmvP/uAmZMeRR/b3c6tGnJN18Vv7V47S2z+IsXmTjuQQL9vGkW4MsD94zh3LmzxV6zYtlSeoaF4OXqSJvmgTzz1JMAdGrbGoCH7r8HF3ut5fG1t8xkWeadt96gXavmeLk60rdnNzb8eyWZPXfuLC72Wn5fs5o7bhuCr4cLN/UMY++e3eW+/8zMTJ6YMY2WQf4E+Hhwx7ChHD500PJ8UTl+/P5bOrVvS1NfTyaNf4js7GxLjKIoLPzgPTq3D8bH3ZmbeoaxZvWvlue3bd2Ci72WDev/ZcBNvfBydWTnju1kZ2fzyKTxNPF0pU3zQMI/+Yjht97C7GefBuCdt96gd/cuJcrcv09P3pz3Wqnvp6xjxcbG8MA9Y2jVLAA/LzcG9u3Npo3/FXttp7ateW/B2+X+7ffs3kXfnt3wdnNiwE29+POP33Gx13LoYJQl5sTxY9w96k78vNxo1SyAxyZPJPXSpXL/DoIgCHVBvUmIcnNzCQkJ4dNPPy31+ZUrVzJz5kxeeuklIiMj6devH8OGDSMuLg4oWmqgODEqrKRPP/mY0K5hbN21l8mPTWHWk49z6uSJUmPz8vK4Y9gQHBwc+fvf/1i3YRMOjo7cNfIO9Ho9AF9+8TnPPPUEEx9+hF37DvDDz6to0bIlAJu27QRg0edfcio2zvL4WovDP+HTjxfy+vy32bk3gpuHDOH+e8YQE326WNzrc+fwvyefYvvufbRs1ZrJE8aV2UKiKAr3jhlJclIiP6/6nS07dhMS2oU7h99GWlqaJe7MmVj+/ON3Vv78Kyt/XcOObdv48L0FV4752hy+W7GMDz76hN0RUUx//Ekee3gi27dtLXa8V19+gVfnvcHeyEN07NiJF59/lj27dvHDz6tY8+dadu7YzsGoSEv82PETOXH8OBH791u2HTl8iEMHo3hw3PhS31NZx8rNyWHIrcP47c+/2bZrL4NvGcL9d4/m/Pm4Yq/79OOFZf7ts7Ozue/u0bTv2JGtO/fw8pzXeG3OK8Ven5iQwO233kKnzp3ZvH0Xv675g+TkZCaMe7Dc8gqCINQF9aYP0bBhwxg2bFiZz3/wwQdMnjyZRx55BICFCxeybt06Fi9ezPz58/H39y/WInThwgV69uxZ5v4KCwspLCy0PM7KygLMrRWyLBeLlWUZRVEs/4oo1O46D6UlfZV5zdWvGzL0Vh6ZMgUJiaeefpZFn37Mtq1baRPctsRrf/35J1QqFZ8u/tySXC76/EsCm3ixbesWBt8yhPfemc/jT8xk2oz/WV4X1s3c+uPp5QWAi4sLPr6+ZZbxk4Uf8uSsZ7j7nvsAmPfGfLZt2cKiTz/h/YUfW+L+9+Qsbh12OwAvvjyHnmGhxMZEl1r2rVs2c+zoEaLPXbTcAnxz/jv89cfv/LZ6FZMmmz9Hsiyz6IsvcbK3B7Wa+x58kC2bNwHmJD38k4/44+9/6dGzFwDNm7dg184dfPPVEvr262853osvv8rNg28BzMnFD9+t4Mulyxk46GZLvbVtGWSJ9w8IYPAtQ/luxTJLfX23Yjl9+/WnefMWZdbVtccCcPfwoFPnEMvjV16bx59//Mbff/7JY9OmW7YPvfU2Hp0yFaDE3/6nH39AkiQ+Dv8MW1tbgtu144kL53nif1f6en215HNCQrvw6rw3LNvCF39B+zYtiD59ilat25Ra3qJlPK7n81vXlHYdaOxEnZRkrg9KfJc0dkXfpdVdL5XdX71JiMqj1+uJiIhg9uzZxbYPHTqUnTvNrQ49evTgyJEjXLx4EWdnZ9auXcucOXPK3Of8+fOZO3duie0pKSkUFBQU22YwGJBlGaPRWKxFoqLlPqpbVfuLFF2krn5dhw4dQDZZUjlvbx9SkhNRZONVrzOhyEaiDuwnNiYGf+/iHdMLCgo4E3Oa5I4dSEiIp/+AAcVeX7Icpmv2L6OgoMhGsrKySEiIp2fPnsVievbqxZHDh1FkI4psulz2dpYYH29zspWclEjr1q1KHDPqwH5ycnJoHlA8EcvPz+dMbLR5v4pMYGAQTg72KLKMJIOPjw8pKckospETxw5TUFDAqDuKJ+p6vZ7OISHFyhbaJcRStjOxpzEYDHTt2tWyzdnJgVatW5vf++Vt4ydO4PHp03hz/nzUajU//fgDb8yfX2ZdlnYsMCdu78x/i3V//01CYgImo5H8/HzOnz9niVNQ6NChQ7HXXf23P33qBB06dESn1VhiuoSFFfv7RUVGsG3LZvy8Sna6j405TcuWJRM5RTaBLCPrszHVnwbrMikoyIW5IIGYYclM1ElJCgoZavM1WKWq/5/76iLLMpmZmdVeL1d3cyhPg0iILl26hMlkwsen+CgrHx8fEhMTAdBoNLz//vsMGjQIWZZ57rnnyl1m44UXXmDWrFksWbKEJUuWYDKZiI6OxsvLC2fn4usuFRQUkJ2djUajQaO5UqVqde2ufXX1sStDkiQkSSr2OhsbLajUlguXSpJQlOLLeUiSGkmlQVYgtEtXlnyzrMS+PT29LB9oSaUud4mHov1deaxCQkJSaSzbVWrNNfuQkFSqyzHmerbR2lpiJLV59JxyeT/XkhXw9W3Cn+vWl3jO1cXVvF9JZR6Fp1KbFzBVqVGp1CiygqTSoCjm9/fTqt9o4udXbB86na5Y2RwcXa4qh6rU96Qol9/75W233zES3cyZ/PXnn2i1OvT6QkaOvrvMuiz9WDDn5Zf5b8N63njrbVq0bImtnR0THrwfg+HK0hsSEjZaXbHXFf/bX6lvc71e+bVv+TzIcNvtw5n7xlslyubr26TUcksqI6hUqOycQFW1EY91kaIooIDa3lXckr9M1ElJiqLg6gpeXl4iIbqKLMtIklTt9WJra1upuAaREBW59mRTFKXYtjvvvJM777yzUvvS6XTodDqefvppnn76actaZiqVqsQfSqVSWZKLq49X27+Grudic22Zq/IrLiS0C6t+/RkvL+8SSWKRwKBmbNm0kf4DBpb6vI2NDSa57JY0Z2dnmjTxY9fOHdzUt59l+57duwjr1r1S5Syr7ElJiWg0GoKCmpUbKyGhlFIvwe3aodPpuHA+rtjtsYo0b9ESGxsbIvbvIyCgKWC+JRsbE11sPxqNhgfGjuXbFcvRabWMufve61oeZtfO7Tw0dhwjRo4CICcnh7i4c1XaR+s2wfy08gcKCwvNyR4SkZEHisWEhIby+2+rCQpqVqXkXKKUz2E9Vtq1oLETdVKSJFHq90ljJ0lStddLZffVIP4Snp6eqNVqS2tQkeTk5BKtRlUVHh5O+/bt6d79+r98G6p7738ADw8PHrz3Lnbu2M7Zs2fYvm0rzz8zi4sXLgDwwksv8+nHC/ls0afERJ8mKjKSzxeHW/YRGBTElk2bSEpMJD09vdTjPPHULD764D1+/eUnTp86yauvvMjhQweZNuPx6y77oJsH06NnLx669242rP+Xc+fOsmf3Ll5/bQ4HIiIqtQ8nJyf+9+RTvPD8s3z/7XJiY2M4GBXJks8W8/23y8t93QMPjeOVF19g65bNHD92lBlTH7Uk1lebMPFhtm7exPp/1zFu/MTreq8tWrTk99/WcOhgFIcPHeSRieOqfI/+nvvuR5Zlnnx8GidPHGfD+n/59KOPgCuJ+KNTppGens7DE8YSsW8fZ87E8t+G9cyY8mit3z4WBEGoqgaREGm1WsLCwli/vvjtj/Xr19OnT58b2veMGTM4duwY+/btu6H9NET29vb8/e9GApo2ZewD99KjS2dmTH2M/Px8nC63GD04djzzF7zPl198Rs+wUO67axQx0dGWfbw5fwGbNv5H+zYt6N+7R6nHmTr9cR5/YiYvz36e3t278t+///Ljz6to2ar1dZddkiR+Xv07ffr24/GpjxHWuQMPjx9LXNw5vH28K72fl1+dy/MvvMQH7y2gR5fOjBl5B3+v/YugZs3Lfd1b77xLj549ue+uUYwcPoxevfvQJrgtOtviczy1bNWanr1607pNG7r1KL1+KvLWgvdwdXNj6M0DuP/uMQy+ZSghoSWH9JfH2dmZlb+s5vChg/Tt1Z3XX5vDc7NfAK40Rzfx8+Pf/zZjMpkYPXI4vbt1Yfazs3C+3LIqCIJQl0lKPen6n5OTQ/TlL9IuXbrwwQcfMGjQINzd3QkMDGTlypWMGzeOzz77jN69e/PFF1+wZMkSjh49SlBQUAV7L1t4eDjh4eGYTCZOnTpFZmZmqX2Izpw5Y5kDqb5SFIWsvIIy+6gUFhbi7ebEmj//ZtDNg2u5dNalyMZy+0HdqNzcXNq1asYb8xcwfuKkK8dVFLqFdmTS5Ed5/ImZNXb867Hyh2+ZMXUK5xMvYWdnd1370BcWcD7uHOkqV+QG0ofIlJuB2kH0lyki6qQkRVHo5AHe3t7ix8JVZFkmOTm52uulqMtLad/fV6s3fYj279/PoEGDLI9nzZoFwIQJE1i6dCn33XcfqampzJs3j4SEBDp27MjatWtvKBkCcwvRjBkzLBXaWGVlZfHHb2tQqVS0aRNs7eLUewejIjl96iRdu3UnKzOLBfPNQ9WH3zHCEpOSnMyPP3xHQnw8D42bYK2iWvzw3QqaNW9BEz8/jhw6xGuvvMzou+6+7mRIEAShLqk3CdHAgQMrnMdi+vTpTJ8+vdyYqrq6hagxm//GPH7+6UfmvvEW/gEB1i5Og/Dxwg+JPn0KG62W0C5d+Xv9Rjw8PS3Pt2oWgIenJx99ugi3alw/7nolJSXx1uvzSEpKxMe3CSNHj2HO3DcqfqEgCEI9UG9umVlbeU1ujeWWWWNW07fM6qPqqBNxy6zhE3VSkrhlVjpr3zITfwlBEARBEBo9kRBVQAy7FwRBEISGTyREFRDD7gVBEASh4RMJkSAIgiAIjZ5IiCogbpkJgiAIQsMnEqIKiFtmgiAIgtDwiYRIEARBEIRGTyREgiAIgiA0eiIhEho9g8FQpe2CIAhCwyMSogo05E7ViqKwYMECWrRogZ2dHaGhofy2erXl+fT0dB6ZNJ4WgX74uDvTpVN7vl2+zPL8xQsXmDT+IYL8fWji6cqAm3qxf+9eAGJjY3jgnjG0ahaAn5cbA/v2ZtPG/4odv1Pb1iyY/yaTJ47Dz8uN4BZBfL44vFhMZmYmT8yYRssgfwJ8PLhj2FAOHzpY7vua8/ILdO3cHl8PFzq3D+aNua8WS27mvzGPvj27sWLZUjq3D8bL1RFFUXCx1/LVki944J4xNPF05d2338JkMjFj6mN07tAOH3dnwkI6sDj8E8u+dmzfhoezPUmJicXK8NLs5xg25OZK/iUEQRAEaxNrEVTgehZ3VRSFfIN11j6zs1FXenr8l19+mVWrVrF48WJat27Nli1beOyRh/H09qFvv/68Oe81Thw/zi+r/8DD04PYmBgK8vMByMnJ4fZbb8HPz48ff16Ft48PB6MikRUZgNycHIbcOoyXX52Lra0t33+7gvvvHs3+g0do2jTQUoaPF37ArGef54WXXuG/Det54blnaN0mmJsH34KiKNw7ZiRubm78vOp3XFyc+fqrL7lz+G1EHDyKu7t7qe/LydGJxV98hW+TJhw7coQnZkzD0cmJmbOescTExsaw+tdfWPH9j6jVasv2+W/O49W5b/DWgvdQq9XIsoy/vz9Ll6/Aw8uHvbt38eTj0/Hx9WXMXfdwU99+NGvenB9/+I4nn3oaAKPRyMofv+e1eW9W6W8nCIIgWI9Yy6ySqrKWWZ7eSPs566xSzmPzbsVeW3Gem5ubi6enJxs3bqR3796AOZGbMGkS+fkFfLXUnMB4eHgS/vmSEq//5qsveeXF5zl0/HSZicm1eoaFMPmRKTw2zbwAb6e2rWkT3JZff/vDEjNp/ENkZ2Xzy5rf2bJ5E2Pvv4focxfR6XSWmNCO7XjyqaeZNPmRSh33ow/fZ9UvP7Nlx27A3EL0/rvvcCL6LJ5eXpY4F3st0x9/gvkL3iuxj6vX7Xp65hMkJyex4vuVACz84D2+/3Y5ew8cAuCvP37nsckTOXXmPA4ODpUqY30k1jIrSazbVZKok5LEWmals/ZaZqKFqJE6duwYBQUFDBkypNh2vV5P55BQACY/OoVxD97HwahIBt1yC3eMGEnPXubk6fChg3QOCS0zGcrNzeXtt15n3d9rSUxIwGg0kp+fz/kLccXievTsec3jXiz61HxLKiryADk5OTQP8C0Wk5+fz5kzMWW+tzWrf2Xxp58QGxNDbm4ORqMRp2tOgqaBQcWSoSJdunYtse2rJV+wfOlXnD9/noL8fPR6PZ06h1ief2jseN6Y+yr79u6he4+efLt8KaPG3N2gkyFBEISGRiRENcDORs2xebda7diVIcvmW1t//fUX/v7+gPlXS05+ITo7ewCG3HobR05Es+6fv9m86T/uvP1WHpkyjTfnv4OdnV25+3/lxdn8t2E9b7z1Ni1atsTWzo4JD96PQV9xR+WiX5GyLOPr24Q/160vEePq4lrqa/ft3cPD48fywstzGHzLUFxcnPn155/49OOFxeIc7O1Lfb29ffEkZtWvP/Pi88/wxlvz6dGrD45OTnz84QdE7NtrifHy9ua224fz7fJlNGvWnH/X/cNf6zZU+D4FQRCEukMkRDVAkqRK3baypvbt26PT6YiLi2PAgAGAOSHKyisodhvE08uLh8aN56Fx4+ndpy9zXprNm/PfoUPHjixf+jVpaWmlthLt2rmdh8aOY8TIUYC5z1Fc3LkScfv27r3m8R7atAkGICS0C0lJiWg0GoKCmlXqfe3etZOmgUE8+/wLlm1xcXHlvKJ8u3bsoEev3jzy2BRLvZw5E1sibsLEh3l4wlj8/f1p3qIFvXr3ue5jCoIgCLVP3LysQEMdZebk5MQzzzzDU089xbJly4iJiSEyMpIln3/G998uB+DNea/x1x+/ExMTzfFjR1n391+0CW4LwN333o+3jw8P3Xc3u3ft5MyZWH5bs4q9e8z9dFq0aMnvv63h0MEoDh86yCMTx1lapa62Z/dOFn7wHtGnT7Hks8WsWfUrU2c8DsCgmwfTo2cvHrr3bjas/5dz586yZ/cuXn9tDgciIkp9Xy1atOTC+Th++XklsbExfLboU/7847frrqcWLVsSdSCC/zasJ/r0Kd6Y+yqREftLxA0eMhRnZxfefWc+D42bcN3HEwRBEKxDJEQVaMhLd7z++uvMmTOH+fPn065dO2677Tb++XstQc2aA6DVapn76svc1COMYUMHo1ar+Xr5t5bnVv+xFk8vL+4ZfSd9unflw/feRa0y37J7a8F7uLq5MfTmAdx/9xgG3zKUkNAuJcrw+BMziYo8QL/ePVjw9lu8+fYCbhkyFDC3tP28+nf69O3H41MfI6xzBx4eP5a4uHN4+3iX+p6Gj7iT6f97gmdnzaRfr+7s2b2L52a/eN119PAjjzHizlFMmjCemwf0JS0tjcmPTSkRp1KpeHDsOEwmEw88OPa6jycIgiBYhxhlVklVGWVWX5V2y6wmdWrbmmmP/4/pjz9RK8e7EZUZUfW/6VNJSU7ix19WlxvXUIhRZiWJEVUliTopSYwyK50YZSYI9VxmZiYHIvbz88of+P6nX61dHEEQBOE6NKrUdPTo0bi5uXH33XdbuyhCA/LgvXfxwD1jmDT5UW4efIu1iyMIgiBch0bVQvTEE0/w8MMPs2zZsoqDhRp3+MRpaxehWogh9oIgCPVfo2ohGjRoEE5OTtYuhiAIgiAIdUydSYi2bt3KiBEj8PPzQ5Ik1qxZUyJm0aJFlo7LYWFhbNu2rfYLKgiCIAhCg1NnEqLc3FxCQkL49NNPS31+5cqVzJw5k5deeonIyEj69evHsGHDik26FxYWRseOHUv8i4+Pr623IQiCIAhCPVRn+hANGzaMYcOGlfn8Bx98wOTJk3nkEfOCngsXLmTdunUsXryY+fPnAxBRxmR916OwsJDCwkLL46ysLMA8LPDaCQZlWUZRFMu/ek0BBQUJMTy2iGKuFFEvV6nOOlGgYZw70HCuA9VI1ElJ5vqg1MlqG7Oi79LqrpfK7q/OJETl0ev1REREMHv27GLbhw4dys6dO2vkmPPnz2fu3LkltqekpFBQUFBsm8FgQJZljEYjRqOxRspTG8wnqYwkm7+khCtEvZRUHXWiyCaQZWR9Nqa602B93RQU5MJckBDJ82WiTkpSUMhQm6+5Yh6iK2RZJjMzs9rrJTs7u1Jx9SIhunTpEiaTCR8fn2LbfXx8SExMrPR+br31Vg4cOEBubi4BAQGsXr26zCU5XnjhBWbNmmV5nJWVRdOmTfHy8ip1Ysbs7Gw0Gg0aTb2o0jJJehOo1OLCdRUFBUlB1MtVqqtOJJURVCpUdk7QQCZmRAG1vZiEsIiok5IURcHVFby8vERCdBVZlpEkqdrrpbITJterb+9rTyZFUap0gq1bt67SsTqdDp1OR3h4OOHh4ZhMJsC8RMO1fyiVSoUkSZZ/9ZWiKI3uV9x3K5bzwnNPE5eQAsD8N+bx1x+/s33PlfXKJCSURlYvFanOOpGg3p87V2sI14LqJuqkJEkq/fuksZMkqdrrpbL7qhd/CU9PT9RqdYnWoOTk5BKtRtWtIa9ldqO2bd2Ci72WjIwMaxel2vxv5ix+X1v5xFkQBEFoGOpFQqTVagkLC2P9+vXFtq9fv54+ffrU6LEb6mr3tUmv11u7CJXm6OiIu4eHtYshCIIg1LI6kxDl5OQQFRVFVFQUAGfOnCEqKsoyrH7WrFl8+eWXfP311xw/fpynnnqKuLg4pk6dWqPlasgtRIqisGDBAlq0aIGdnR2hoaH8tnq15bk7h9/GmDvvsIwOycjIoEOblsx79RXOnTvLHbcNASDIzxsXey3THpsMwPBbb+GZp57kxeefpXnTJoy6wzx68NOPF9K7exeaeLrSvnULZj35P3JycsotY0ZGBk/MmEarZgF4uznRq1so/6z9y/L8b2tW0TMsBC9XRzq1bc0nH31Y7PXp6elMeWQSgX7e+Hq4cNfIEcRElz1D9vw35tG3ZzfL42mPTebBe+/ik48W0qZ5IM0CfHl65hMYDAZLTGJCAveMHomPuzOd2rXh55U/0KltaxZ9+nGFfwNBEAShbqgzfYj279/PoEGDLI+LOjRPmDCBpUuXct9995Gamsq8efNISEigY8eOrF27lqCgoBot17V9iCpFUcCQV3OFKo+NvfnmdCW8/PLLrFq1isWLF9O6dWu2bNnCY488jKe3D3379eezL76id4+ufLboU6bN+B9PPTEDL29vXnh5DiqVihXfr2Tcg/cRcfAITk7O2NrZWfb9w3crePjRx/j3v82WhEqlUvHOex8SGBTEubNneXrm/5jz0gt88NEnpZZPlmXuHjWCnJxsvvhqKc1btODk8eOo1WoAIg8cYOLYB3nhpVcYc/c97Nm9m6dn/g93dw8eGjcegOmPTSYmJpoff16Fk5MTr778EnePHsneAwexsalcJ95tW7fg4+PDn//8S2xMDJPGP0SnziFMfNicAE559GFSL13ir382oLGx4aXZz5KSklypfQuCIAh1Q51JiAYOHFjhPBXTp09n+vTptVQisxkzZjBjxgyysrJwcXGp3IsMefCWX80WrCwvxoPWocKw3NxcPvjgAzZu3Ejv3r0BaN68OZu2bOGbr5bQt19//Pz9WfhJOFMmTyI5KYl/1v7Ftl17LYmEm7s7AJ5e3ri6uhbbf/MWLXn9zbeLbZv++BOW/zdr1pyX5rzGrCf/V2ZCtGnjf0Ts38e+yEO0at3mchlbWJ4P/2QhAwbdzHMvvARAq9ZtOHHiGB8vfJ+Hxo0nJvo0a//6k383bqFnL/N7/PKbZbRv04I///iN0WMqt8ivq6sb737wIRobHW2C2zL0tmFs2byRiQ9P5tTJE2ze+B+btu2ia1gYAB8v+oyundpXat+CIAhC3VBnEqK66rpaiOqBY8eOUVBQwJAhQ4pt1+v1dA4JtTwePeZu/vz9Nz54bwEffPSpJTGpSJeuYSW2bd2ymffffYeTx4+TnZ2F0WikoKCA3NxcHBxKJnGHDx3E3z+gzGOePHGC4XeMKLatV68+LP70E0wmEydPnECj0dCtew/L8+4eHrRq3YZTJ05U6n0AtG3X3tIqBeDr24SjR48AcPrUKTQaDaFdulieb9myFa5ubpXevyAIgmB9IiGqwHW1ENnYm1tqrMHGvlJhRTN3/vXXX/j7+wPmfkM5+YXo7K7sIy8vj6jIA6jVamJjoitdjGsTnLi4c9wz+k4efuQxXp7zGm5ubuzauZPHpz1WrD/O1eyuugVXmtKmXbi6lbHMFscqTtdgY1P8NJEkCeVy/ZV1DDErryAIQv0iEqKaIEmVum1lTe3bt0en0xEXF8eAAQMA85d4Vl4BkurKx+Kl2c+hUqn4Zc0f3DP6TobeNowBA819vbRaLQByJVrPIg9EYDQaefPtBZY5IVb/+ku5r+nQsRMXL14g+vSpUluJ2rZrx65dxWcq37NnF61at0atVtO2XTuMRiP79+213DJLS00lOvo0bdq2rbDMldEmOBij0cjBqCi6dO0KQExMNJkNaCoCQRCExqDOjDKrqxrqsHsnJyeeeeYZnnrqKZYtW0ZMTAyRkZEs+fwzvv92OQDr/l7Lt8uXsuTr5dw8+BaeevpZpj06mfT0dACaNg1EkiT++fsvLqWklDtirHnzFhiNRj5fHM6ZM/9v787joir3P4B/hhFQBFH2HVdUZFFwTw1R8WpqpKm3EqUIc0sR0euSmpZxL9dMSzSt1NzuNeuilVZSKZC4JEK/VpcEwRUxFURZ5Dy/P4jJcQYYYIZhZj7v14uXr3PmOec854Mcvjxnu4D/7t6JLe+/V2MfBwwchMcGDETEsxPx7TdfIycnG8lffYmvD1U+J2jW7LlIOfwtEuJX4fy5s9i9czvee3cjXp5TeUF+h46d8MSo0Zg9cxqOpR/Fj//3A6JfiISrmzueGDVGGzHCp3MXhIQOwZxZ05Hx/ff4ISsTc2bNQIsWLfgQOiIiA8KCqBbGfNv9a6+9hmXLliE+Ph5du3bF3/72N3z5xUF4t22Hghs3MGv6S1i4ZKni+piFS5bCxdUVc2fPBAC4ubtj8SvL8OrSV9CxrQfmx86pdlsBgd3xxr/+jbVvrka/nj3w0X//i+UrX6u1j9t370FQUE9ERUagT1Aglr2ySHE9V/cePbBt52588vFH6NuzB954bSUWL12uuMMMABI3vY/uPYIwcVw4hg0eBCEEPk7ar/EdZprY9N4WODk5Y0RYKCb9fQIin38B1jY2sLTU7HHxRESkfzLBix00UnUN0Z07d9S+yyw7Oxvt2rXT+J0pTZG6U2ZUSUgPNM7l8qVL8PVpj/0HvkTI4FAd90x/6pJJdcpKS5CXexG3zFpDMpJ3mVUU34a8Jd/bVYWZqBJCwN8ecHJy4qs7HiJJEvLz87WeS02/vx/G33y1MNa7zEh7Uo4cRvHdu/D188P1a9ewbMkieHm3xWMDBuq7a0REpCGWprUw5lNmpB3l5eVY+epS9A3ujuf+Ph4ODg448FWyVk/LERGRbnGEiKiBhg4Lw9BhYfruBhERNQBHiIiIiMjksSAiIiIik8eCqBbG+hwiIiIi+gsLolrwomoiIiLjx4KIiIiITB4LIiIiIjJ5LIhISVpqKmytLHCbLyclIiITwoLIhIWEhCAmJkZpXp++fXH2Qi5sbW3106lq+HfphA3r39Z3N4iIyEixIKqFqd1lZmFhAWcXF75ziIiITAoLoloY611mkZGRSElJwbp16yCTySCTyZCTk6NyymzXju3wcnXElwcPIDiwG1zsbRHx7EQUFxdj987t8O/SCV5uTpgfG6P0vreysjIsXbIQXTq0hatDa4QOegxpqSk19in+9ZXo5tMBjq2t0bm9NxbMmwsAeGL4UOTmXsSiBXGwtbKArZWFYpkTx49hxLBQONu1gm+n9lgwby6Ki4sVn/t36YSE+FWIioyAm2MbdG7vjU0bE7WYJBERGQMWRDok3btX/VdpqeZtS0o0alsX69atQ79+/RAdHY2rV6/i6tWr8PT0VNv23r17eHdjIrZ8uBOf7P8c36WlYtIzE3Doqy+xN2k/Nr+/Fdu2vI99SZ8olpnx0os4cewYtmzfiaMnMxA+dhzGPTkKv58/p3Yb+5I+wYb1b2PtO4k4/eMv2L3nY/h28wMA7PjPR3B398CSpctx9kIuzl7IBQD8/NOPGDvmCYx+MhzpJzOwdccuHEs/ivlz5yit++21a9DNzx+p6ScQO38BFi2Iw7fffF2nvIiIyLjxXWY6dCYouNrPWj4+CF6bNimmzz42AOL+fbVtrXr1gveO7Yrp80OGouLWLZV2XX/7VeO+2drawsLCAlZWVnBxcQEACCHUti0vL8eade+gffsOAIAnw8diz3924VzOJVhbW6NLV18MHBSCtJQUjHt6Ai5c+B0ff7QHv57LhqubGwBgdkwsvk4+hJ3bP8Tyla+rbONSXh6cnJ0REjoE5ubm8PT0QvCfpynt7Owgl8thbWMD5z/7ClQWOk9P+DtmzJoNAOjQsRMS3nwLI8OGYM3b69G8eXMAQJ++/REbtwAA0LGTD44fS8eGd95G6JChGudFRETGzWRGiPLy8hASEgJfX18EBARg7969+u6SwbCyslIUQwDg5OQEL29vWFtb/zXP2Qk3buQDAH7IyoQQAsGB3eDm2EbxdTQtFdnZF9RuI3zsOJTcL0Ggb2e8PGMaPtu/Dw8ePKixX1mZp7F753albYwd8wQkScLFnGxFu959+igt17tPX5w581udcyAiIuNlMiNEzZo1w9q1a9G9e3fk5+cjKCgII0eORMuWLXW2zc6nM6r/UC5XmvQ5+l31bc2U69aOjXy6x9zcXGlaJpPBvJnqPCFJAABJkiCXy5Fy9DjMHtlP65bWUMfDwxOnfvgJh7/5GkcOf4t5MbPx9to1OHjoG5XtV5EkCc9HReOlGTNVPvP09Kpxn3jROBERPcxkCiJXV1e4uroCqBzhsLOzwx9//KHTgsjMykrvbWtiYWGhdCG0tgQGdkdFRQVu3LiB/o8N0Hi5Fi1aYOSo0Rg5ajSiX5qGnt398fNPP6F7jx4wtzBX6Wtg9x749ddf0KFDxxrX+/3Jk49Mn4CPT2fNd4iIiIxekzlllpqaitGjR8PNzQ0ymQz79u1TabNhwwa0a9cOzZs3R3BwMNLS0uq1rVOnTkGSpGovIjYVbdu2xYkTJ5CTk4OCggJIf47wNFTHTj6Y8Pdn8NKLL+DTfUnIyclGxqlTeOvNf+PQl1+oXWbXju3Yvm0rfvn5J2RnX8B/d+9CixYt4OVVOdLj5d0W6d+l4crly7hZUAAAiImNw/cnjmNezGz83w9Z+P38ORz8/DPMj41RWveJ4+lYu2Y1zp87i/fe3Yh9//sE02bO0sq+EhGRcWgyBVFxcTECAwOxfv16tZ/v2bMHMTExWLJkCTIzMzFw4ECMGDECubm5ijbBwcHw8/NT+bpy5Yqizc2bNzF58mRs3rxZ5/vU1MXFxUEul8PX1xeOjo5KWTbUhk3v45lnn8OSRf9Az0A/PDN+LE59fxLuHh5q29va2uLDrR9g+JAQPNY7GClHDuO/HyfBzt4eALBk6XLk5l5Ed78uaO9VeaG2n38ADnz1DX7//TxGDAvFwH69seq1V5UuvAaAWbNjkJV5GgP79UbCP9/Aqn8mYOiwMK3tKxERGT6ZqO7WIj2SyWRISkpCeHi4Yl6fPn0QFBSEjRs3KuZ17doV4eHhiI+P12i9paWlGDZsGKKjoxEREVFr29KHbo0vLCyEp6cnbt26hVatWim1LSkpQU5OjmL0ypAVFpcAcjlkMI5rbPy7dML0WS8r7kSrDwEBVFQYVS4Npa1MykpLkJt7EbdktpDM1F8rZkiEEKgovg15y9a8Tu1PzESVEAL+9oCjoyPMzJrMuITeSZKEGzduaD2XwsJCtGnTBnfu3FH5/f0wg7iGqKysDBkZGVi4cKHS/LCwMKSnp2u0DiEEIiMjERoaWmsxBADx8fFYsWKFyvwbN26g5JHnApWXl0OSJDx48KDWO6OaMiEEhJAgk4AmVyXXk0DlPgmpYd8XY8tFG7SRiZAqAEmCVFaEiqYzYF1vAgJSaTEgA4vnPzETVQICt+WVx1wWRH+RJAl37tzRei5FRUUatTOIgqigoAAVFRVwdnZWmu/s7Ixr165ptI6jR49iz549CAgIUFyftGPHDvj7+6ttv2jRIsTGxiqmq0aIHB0d1Y4QFRUVoVmzZmjWzCAirZasrAIwM56REBlkkMnMIDOr//dFQEAmYFS5NJS2MpGZPQDMzGDWwgYwkhEiCEBuxdGQKsxElRACrVtzhOhRkiRBJpNpPRdNz9wY1G/vR3+YhBAa/4ANGDCgThcNW1pawtLSEomJiUhMTFTc4WRmZqbyjTIzM1O8/sKQf+CFEEb3V9yPv6l/MnZdyCCDMLJcGkqbmcgAg//ZeZgxHAu0jZmoksnU/z4xdTKZTOu5aLoug/hOODg4QC6Xq4wG5efnq4waEREREdWVQRREFhYWCA4ORnJystL85ORk9O/fX6fbNtaXuxIREdFfmswps7t37+L8+fOK6ezsbGRlZcHOzg5eXl6IjY1FREQEevbsiX79+mHz5s3Izc3FtGnTdNqvR0+ZERERkfFpMgXRqVOnMHjwYMV01QXNU6ZMwbZt2zBx4kTcvHkTK1euxNWrV+Hn54eDBw/C29tbp/2aOXMmZs6cicLCQtja2up0W0RERKQfTaYgCgkJqfZt61VmzJiBGTNmNFKPiIiIyFQYxDVE+pSYmAhfX1/06tVL310hIiIiHWFBVAteVK0906dG4dkJ4+q1bFpqCmytLHD79m3tduoRFy/mwNbKAv/3Q1aTWI+hbZuIyFCxIDJhISEhiImJqfNyTwwfioXz52m/QzXo07cfzl7IbZLXcakr9Dw8PHH2Qi58u/kZ7baJiIwJC6Ja8JRZ02BhYQFnFxeDebCbXC6Hs4uLXp5crs9tExEZKhZEtWjIKbPi4uJqvx59H1pNbe/fv69R27qIjIxESkoK1q1bp3iCbE5ODgDgu7RUDB7YH46treHTzgvLly5WvKNt+tQofJeWio2J78DWygK2Vha4eDEHFRUVmDltKvy7+sDZrhWCA7thY+I7depTbu5FTBwXDi83J7g6tEaf4EAc+vILAKqnzHbt2A4vV0d8efAAggO7wcXeFhHPTkRxcTF279wO/y6d4OXmhPmxMUqPTLC1ssDnn+5X2q6XqyN27diutk9V+xXQrava/Yp/fSV279yBA59/psgjLTVF7WmrmnIFKkfeFsybi6VLFsLb3Rmd2noi/vWV1eal6barsvs6+RAG9O0FZ7tWGDUiDDfy85H81Zfo1cMfHs72eGHKJNy7d0+xfiEE1q5ZjQDfznC2a4XH+gRjX9InNX8TiYgMFP+E1CFra+tqPxs5ciQOHDigmHZyclL6ZfSwxx9/HEeOHFFMt23bFgUFBSrtartL72Hr1q3D2bNn4efnh5UrK3/pOjg44Fx2DsY/NQbPTpqMTe9vwdkzZzB71nQ0t2yORa8swz//vQbnz51DV99uWLJ0eeVyjo6QJAnu7u7YtmM37B3scfL4McyZNQPOLi4YO268Rn2Ki5mDsvIyfHHoG1i1bIkzv/6KljVkeO/ePby7MRFbPtyJu3fvYtIzEzDpmQmwtbXF3qT9yMnORsSzE9G3f3+Me3qCxtk8TLFf23fA3tFZZb9ejonFmTO/oaiwCBs2vQcAaGNnh6tXryit58rlyzXmWuU/u3Zg5stz8G3Kdzh54jimT30Rffr1R+iQoSp903TbVf656jWsfmsdWrRogciI5xAZ8SwsLC3x/tbtKC4uxnN/H49NGxMxd958AMBrry7DZ5/uw5p176BDx45I/+47TH0hEg4OjhgwcFC98iQiaqpYENXCWB/MaGtrCwsLC1hZWcHFxQVAZUH1webNcPfwwOq3KkeOfDp3wdWrV/Hq0sX4x+JXlJZz/nM5oPI0zeI/CyQAaNu2HU4cP46kTz7WuCC6dCkXY558Ct38Kl+4265d+xrbl5eXY826d9C+fQcAwJPhY7HnP7twLucSrK2t0aWrLwYOCkFaSkq9CyJzc3MsXrocQnoAmVkzlf2ytrZGixYtUFZaqpTHo97f/G6NuVa9a6ebnz8WLlkKAOjQsRM2v7sRKUe+VVsQabrtKq8sX4G+/Sqf7B4xJRIrlr2CrJ9/U+T8ZPhYpKWkYO68+SguLkbiO+vw2ReH0LtPXwCV349j6Uex9YP3WBARkdFhQVSLhjyY8e7du9V+JpfLlabz8/Orbfvoi+mqTm3pwpkzZ9C7d1+la3X69uuHu3fv4vLlS/D09Kp22Q/e24zt27YgLy8XJffvo6ysDP4BgRpv+6XpsxA7Zxa+/eZrhAwOxZjwp+DnH1BteysrK0UxBFSOsnl5eyuNzDk5O+HGjeqz1UTlfn2AvLy8eu0XAJw585tGuVYVg1VcXFxQkH+jQf2v4vfQup2cnGFlZaVUdDo5OSHjVOWp4d9+/RUlJSUIHzVCaR1lZWUICOyulf4QETUlLIh0qGXLlnpvW1dCCJULl6tOxdV0QfP/PtmLxf+Iw+vxCejdpw+sbWzw9ltrkPH9SY23PeX5FzBk2DB89cUX+PabZKxZnYBV/0zAS9Nnqm1vbm6uNC2TyWDeTHWekCTl6UdOLZaXl9e+X2/Eo3ff/vXaLwCAhrmq2ydJSNCGZg+tWyaTqd1WVVZV/370v/1wdXNTamdpaamV/hARNSUsiEyYhYWFyqnALl264NNP9ysVRieOH4eNjQ3c3NwBAOZqljt29Ch69+2H6Jf+erdcdvaFOvfJw8MTUdFTERU9Fa8uW4IPt35QbUFUHw6Ojrh27Zpi+vfz56q9dgv4a79enPoSZGaVPy6P7pe5uWoej+rcpSs+3Z9UY671ocm266Nz166wtLTEpbxcnh4jIpPAu8xqYcy33bdt2xYnTpxATk4OCgoKIEkSoqZOxeVLlzA/NgZnz/yGA599ivhVKzHz5TmKU3deXt449f1JXLyYg5t/Lte+Qwdknc7A18mHcP7cWby+YjkyM07VqT8L58/D18mHkJOTjazMTKQeOQKfzl20us+DHg/Be5s2ICszE6czMhAze5bKSMnDqvbrm6+Tq90vL29v/PzTTzh39gxuFhSoHXF6ceq0WnOtD022XR82NjZ4ec5cLPrHfOzeuR0XLvyOH7Iy8d67G7F7p/o78oiIDBkLoloY85Oq4+LiIJfL4evrC0dHR+Tm5sLNzR17kz5Fxqnv8Vifnpg7exYipkRi/sLFiuVmx8yFXC5Hn6BAtPdyQ15eLl54cSpGjwnHC5OfQ+jjA/DHH38gaupLdepPRUUF4ubOQe8eARgXPgqdfHywZm3dbt2vzar4BLh7eGJkWChefD4Cs+fMhZWVVbXtq/br+SmTq92vyOej0NHHByED+qG9lxuOH0tXWY+be+251ocm266vV5avwD8WLcGa1Qno3SMAY58chS8OHoB323Za2wYRUVMhE3W5V9uEVV1UfefOHbRq1Urps5KSEmRnZ6Ndu3Zo3ry5nnrYcEIIFN4rUZwaor9U3WVGf9FGJmWlJcjLvYhbZq0hmVU/UmcohBCoKL4NecvWBvMQUV1jJqqEEPC3r7yRoSEjxMZGkiTk5+drPZeafn8/jN8JIiIiMnksiIiIiMjksSAiIiIik8eCqBbGfJcZERERVWJBVIu63GXG69OJ6kYIAf7UEFFTwIJIC6qeY1PTA/6ISFVpSQmEEJBk8tobExHpEO8j1gK5XI7WrVsr3kdmZWVlkLeXCiFQVloKmdkDfXelyRFSBXN5REMyEUKgtKQEBTdu4D6aAzL+bUZE+sWCSEuq3hhf00tamzohBErKHgBmZjC8ck53BABIEnN5SEMzEaj8/3YfzVHSzEa7nSMiqgeTKYiKiooQGhqK8vJyVFRUYPbs2YiOjtba+mUyGVxdXeHk5KS11yc0NkmScPSnHJi1sDHIES5dEUJAKitiLg/RRiaSTM6RISJqMkymILKyskJKSgqsrKxw7949+Pn5YezYsbC3t9fqduRyOeRyw7weQpIkVMAMMDPnL/6HCCGYyyOYCREZG5P580wulyveWVVSUoKKigreFUZEREQAmlBBlJqaitGjR8PNzQ0ymQz79u1TabNhwwbF+8KCg4ORlpZWp23cvn0bgYGB8PDwwIIFC+Dg4KCl3hMREZEhazIFUXFxMQIDA7F+/Xq1n+/ZswcxMTFYsmQJMjMzMXDgQIwYMQK5ubmKNsHBwfDz81P5unLlCgCgdevW+OGHH5CdnY3du3fj+vXrjbJvRERE1LQ1ybfdy2QyJCUlITw8XDGvT58+CAoKwsaNGxXzunbtivDwcMTHx9d5G9OnT0doaCjGjx+v9vPS0lKUlpYqpu/cuQMvLy9cvHixxrflGjJJknA463eYWdnyupCHCCEg3bvDXB7CTNRjLqqYiSohBLrZAQ4ODnzb/UMkSUJBQYHWcyksLIS3tzdu374NW1vbatsZxEXVZWVlyMjIwMKFC5Xmh4WFIT09XaN1XL9+HS1atECrVq1QWFiI1NRUTJ8+vdr28fHxWLFihcp8b2/vunWeiIiI9K6oqMjwC6KCggJUVFTA2dlZab6zszOuXbum0TouXbqEqKioylcFCIFZs2YhICCg2vaLFi1CbGysYlqSJPzxxx+wt7c32r9yCgsL4enpiby8PKMdBasP5qKKmajHXFQxE1XMRD1d5SKEQFFREdzc3GpsZxAFUZVHCxEhhMbFSXBwMLKysjTelqWlJSwtLZXmtW7dWuPlDVmrVq34Q6oGc1HFTNRjLqqYiSpmop4ucqlpZKiKQZy8dHBwgFwuVxkNys/PVxk1IiIiIqorgyiILCwsEBwcjOTkZKX5ycnJ6N+/v556RURERMaiyZwyu3v3Ls6fP6+Yzs7ORlZWFuzs7ODl5YXY2FhERESgZ8+e6NevHzZv3ozc3FxMmzZNj702LpaWlli+fLnKqUJTx1xUMRP1mIsqZqKKmain71yazG33R44cweDBg1XmT5kyBdu2bQNQ+WDGhIQEXL16FX5+fnjrrbcwaNCgRu4pERERGZsmUxARERER6YtBXENEREREpEssiIiIiMjksSAiIiIik8eCiKr11FNPoU2bNnj66aeV5n/++efo3LkzOnXqhPfff19PvdMfdbnk5eUhJCQEvr6+CAgIwN69e/XYw8ZX3f8VALh37x68vb0RFxenh57pV3W5ZGdnY/DgwfD19YW/vz+Ki4v11MPGV10mb731Frp16wZfX1/Mnj0bpnR5a03HD1M93laXiU6PtYKoGt9++6349NNPxbhx4xTzysvLRadOncSlS5dEYWGh6Nixo7h586Yee9n41OVy5coVkZmZKYQQ4vr168Ld3V3cvXtXTz1sfOoyqbJ48WIxfvx4MW/ePD30TL+qy2XQoEEiNTVVCCHEzZs3RXl5uT66pxfqMsnPzxft27cX9+/fFw8ePBD9+/cX6enpeuxl46ru+GHKx9vqMtHlsZYjRFStwYMHw8bGRmneyZMn0a1bN7i7u8PGxgYjR47EV199pace6oe6XFxdXdG9e3cAgJOTE+zs7PDHH3/ooXf6oS4TADh37hx+++03jBw5Ug+90j91ufz8888wNzfHwIEDAQB2dnZo1qzJPBJO56r7v/LgwQOUlJSgvLwc5eXlcHJy0kPv9KO644cpH2+ry0SXx1oWREYqNTUVo0ePhpubG2QyGfbt26fSZsOGDWjXrh2aN2+O4OBgpKWl1breK1euwN3dXTHt4eGBy5cva7PrOqWrXB526tQpSJIET09PLfVat3SZSVxcHOLj47Xc48ahq1zOnTsHa2trjBkzBkFBQXjjjTd00Hvd0FUmjo6OiIuLg5eXF9zc3DB06FB06NBBB3ugG9rM5eHjhyEfb3WViSbz64sFkZEqLi5GYGAg1q9fr/bzPXv2ICYmBkuWLEFmZiYGDhyIESNGIDc3t8b1CjXn9TV9wW5ToKtcqty8eROTJ0/G5s2btdltndJVJvv374ePjw98fHx00W2d01Uu5eXlSEtLQ2JiIo4dO4bk5GSV1xI1VbrK5NatW/j888+Rk5ODy5cvIz09HampqbrYBZ3QVi6PHj8M+Xirq0xqm98gWjnxRk0aAJGUlKQ0r3fv3mLatGlK87p06SIWLlyoNO/w4cNK5/qPHj0qwsPDFdOzZ88Wu3bt0n6nG4E2cxFCiJKSEjFw4ECxfft2nfS3MWgzk4ULFwoPDw/h7e0t7O3tRatWrcSKFSt01ndd0mYu6enpYvjw4YrphIQEkZCQoP1O65g2M/noo4/EjBkzFNMJCQniX//6l/Y73Qjqm4u644exHG+1mUlN8xuKI0QmqKysDBkZGQgLC1OaHxYWhvT09BqX7d27N3766SdcvnwZRUVFOHjwIIYPH67L7jaahuQihEBkZCRCQ0MRERGhy242qoZkEh8fj7y8POTk5GD16tWIjo7GsmXLdNndRtOQXHr16oXr16/j1q1bkCQJqamp6Nq1qy672ygakomnpyfS09NRUlKCiooKHDlyBJ07d9ZldxuNJrlUd/ww1uNtQzLR5bHWdK7kI4WCggJUVFTA2dlZab6zszOuXbummB4+fDhOnz6N4uJieHh4ICkpCb169cKbb76JwYMHQ5IkLFiwAPb29o29CzrRkFxKS0uxZ88eBAQEKM6V79ixA/7+/o25C1rX0P8rxqqhubzxxhsYNGgQhBAICwvDqFGjGnsXtK4hmfTt2xcjR45Ejx49YGZmhiFDhmDMmDGNvQs6oUkuR48erfb4YYzH24ZkcufOHZ0da1kQmbBHz0ULIZTmVXc3w5gxY4zmYKVOfXORJEmn/dKn+mZSJTIyUhfd0rv65jJixAiMGDFCp33Tl/pmsmrVKqxatUqnfdOnmnIZMGBAtccPYz7e1jcTXR1recrMBDk4OEAulyv91QYA+fn5KhW7KWEuqpiJesxFFTNRj7moaqqZsCAyQRYWFggODla5syU5ORn9+/fXU6/0j7moYibqMRdVzEQ95qKqqWbCU2ZG6u7duzh//rxiOjs7G1lZWbCzs4OXlxdiY2MRERGBnj17ol+/fti8eTNyc3Mxbdo0PfZa95iLKmaiHnNRxUzUYy6qDDITrd6zRk3G4cOHBQCVrylTpijaJCYmCm9vb2FhYSGCgoJESkqK/jrcSJiLKmaiHnNRxUzUYy6qDDETmRAm9AY9IiIiIjV4DRERERGZPBZEREREZPJYEBEREZHJY0FEREREJo8FEREREZk8FkRERERk8lgQERERkcljQUREREQmjwURERERmTwWRERERGTyWBARkckICQmBTCaDTCZDVlaWVtcdGRmpWPe+ffu0um4i0j0WRERksAYNGqQoQh7+eu6556pdJjo6GlevXoWfn59G2xg9ejSGDh2q9rNjx45BJpPh9OnTWLduHa5evVqv/SAi/Wum7w4QEdWHEAJZWVlYvXq1SgFkbW1d7XJWVlZwcXHReDtRUVEYO3YsLl68CG9vb6XPtmzZgu7duyMoKAgAYGtrW4c9IKKmhCNERGSQzp07h6KiIgwaNAguLi5KXzUVRI8SQiAhIQHt27dHixYtEBgYiI8//ljx+ahRo+Dk5IRt27YpLXfv3j3s2bMHUVFR2tolItIjFkREZJAyMjLQrFkzBAQENGg9r7zyCrZu3YqNGzfi559/xty5czFp0iSkpKQAAJo1a4bJkydj27ZtEEIoltu7dy/KyspqPD1HRIaDBRERGaTTp0+joqIC9vb2sLa2VnxFR0drvI7i4mKsWbMGW7ZswfDhw9G+fXtERkZi0qRJ2LRpk6LdCy+8gJycHBw5ckQxb8uWLRg7dizatGmjzd0iIj3hNUREZJAyMjIwfvx4rFq1Sml+XQqUX375BSUlJRg2bJjS/LKyMvTo0UMx3aVLF/Tv3x9btmzB4MGD8fvvvyMtLQ2HDh1q2E4QUZPBgoiIDFJmZiZWrlyJjh071nsdkiQBAA4cOAB3d3elzywtLZWmo6KiMGvWLCQmJmLr1q3w9vbGkCFD6r1tImpaeMqMiAzOhQsXcPv2baVRnPrw9fWFpaUlcnNz0bFjR6UvT09PpbYTJkyAXC7H7t278eGHH+L555+HTCZr0PaJqOngCBERGZyMjAwAgLOzM65du6b0mZOTE8zMNPtbz8bGBnFxcZg7dy4kScKAAQNQWFiI9PR0WFtbY8qUKYq21tbWmDhxIhYvXow7d+4gMjJSa/tDRPrHgoiIDM7p06cBAD4+Pkrzzc3NUVRUpHK6qyavvfYanJycEB8fjwsXLqB169YICgrC4sWLVdpGRUXhgw8+QFhYGLy8vBq2E0TUpMjEw/eREhEZsZCQEHTv3h1r167V2TZkMhmSkpIQHh6us20QkfbxGiIiMikbNmyAtbU1fvzxR62ud9q0aXV6ICQRNS0cISIik3H58mXcv38fAODl5QULCwutrTs/Px+FhYUAAFdXV7Rs2VJr6yYi3WNBRERERCaPp8yIiIjI5LEgIiIiIpPHgoiIiIhMHgsiIiIiMnksiIiIiMjksSAiIiIik8eCiIiIiEweCyIiIiIyeSyIiIiIyOSxICIiIiKT9/+lqKGZ/VzkNgAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "ax.axvspan(Emin, Emax, alpha=0.3, label=\"injection energy range\")\n",
    "ax.loglog(Ep_eV, am3_esc.get_t_proton_escape(), label=\"escape array\")\n",
    "ax.loglog(Ep_eV, am3_cool.get_t_proton_extra_cooling(), label=\"extra cooling\")\n",
    "ax.axhline(t_step, ls=\"--\", label=\"time step\", c=\"tab:red\")\n",
    "ax.axhline(Ntotal*t_step, ls=\"--\", label=\"total simulation time\", c=\"k\")\n",
    "ax.legend()\n",
    "ax.set_aspect(\"equal\")\n",
    "ax.grid(alpha=0.3)\n",
    "ax.set_ylim(1e-3, 1e5)\n",
    "ax.set_xlabel(r\"$E$ [eV]\")\n",
    "ax.set_ylabel(r\"$t$ [s]\")\n",
    "ax.set_title(\"proton timescales\")\n",
    "ax.set_aspect(\"equal\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "run both simulations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 1000/1000 [00:00<00:00, 2621.65it/s]\n"
     ]
    }
   ],
   "source": [
    "am3_esc.clear_particle_densities()\n",
    "am3_esc.clear_particle_densities()\n",
    "for i in trange(Ntotal):\n",
    "    am3_esc.evolve_step()\n",
    "    am3_cool.evolve_step()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "plot the final proton distribution and compare it to the steady-state expectation $n_{steady\\; state} \\to Q(E) t_{escape/extra\\;cooling}$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "\n",
    "ax.loglog(Ep_eV, Ep_erg*am3_esc.get_protons(), label=\"escape array\")\n",
    "ax.loglog(Ep_eV, Ep_erg*am3_cool.get_protons(), label=\"extra cooling\")\n",
    "ax.loglog(Ep_eV, Ep_erg*am3_esc.get_injection_rate_protons()*am3_esc.get_t_proton_escape(), ls=\"--\", c=\"darkblue\")\n",
    "ax.loglog(Ep_eV, Ep_erg*am3_cool.get_injection_rate_protons()*am3_cool.get_t_proton_extra_cooling(), ls=\"--\", c=\"tab:brown\")\n",
    "ax.legend()\n",
    "ax.set_aspect(\"equal\")\n",
    "ax.grid(alpha=0.3)\n",
    "ax.set_ylim(1e-5, 1e5)\n",
    "ax.set_xlabel(r\"$E$ [eV]\")\n",
    "ax.set_ylabel(r\"$E dN/dEdV$ [erg/cm³]\")\n",
    "ax.set_title(\"proton population in steady state\")\n",
    "ax.set_aspect(\"equal\")"
   ]
  }
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