HajimeKawahara/exojax

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Ackerman and Marley Cloud Model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here, we try to compute a cloud opacity using Ackerman and Marley Model.\n",
    "Although `atmphys.AmpAmcloud` can easily compute the parameters of the AM model,\n",
    "we here try to run the methods one by one.\n",
    "We consider enstatite (MgSiO3).  \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-10-30T01:22:37.965127Z",
     "iopub.status.busy": "2022-10-30T01:22:37.963471Z",
     "iopub.status.idle": "2022-10-30T01:22:38.540897Z",
     "shell.execute_reply": "2022-10-30T01:22:38.540563Z"
    }
   },
   "outputs": [],
   "source": [
    "import jax.numpy as jnp\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Sets a simple atmopheric model. We need the density of atmosphere."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-10-30T01:22:38.544103Z",
     "iopub.status.busy": "2022-10-30T01:22:38.543724Z",
     "iopub.status.idle": "2022-10-30T01:22:40.211235Z",
     "shell.execute_reply": "2022-10-30T01:22:40.210931Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2024-10-02 10:27:38.117849: W external/xla/xla/service/gpu/nvptx_compiler.cc:765] The NVIDIA driver's CUDA version is 12.2 which is older than the ptxas CUDA version (12.6.20). Because the driver is older than the ptxas version, XLA is disabling parallel compilation, which may slow down compilation. You should update your NVIDIA driver or use the NVIDIA-provided CUDA forward compatibility packages.\n"
     ]
    }
   ],
   "source": [
    "from exojax.utils.constants import kB, m_u\n",
    "from exojax.atm.atmprof import pressure_layer_logspace\n",
    "from exojax.utils.astrofunc import gravity_jupiter\n",
    "\n",
    "Parr, dParr, k = pressure_layer_logspace(\n",
    "    log_pressure_top=-4.0, log_pressure_btm=6.0, nlayer=100\n",
    ")\n",
    "alpha = 0.097\n",
    "T0 = 1200.0\n",
    "Tarr = T0 * (Parr) ** alpha\n",
    "\n",
    "mu = 2.3  # mean molecular weight\n",
    "R = kB / (mu * m_u)\n",
    "rho = Parr / (R * Tarr)\n",
    "\n",
    "gravity = gravity_jupiter(1.0, 1.0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The solar abundance can be obtained using utils.zsol.nsol. Here, we assume a maximum mol Mixing Ratio for MgSiO3 and Fe from solar abundance. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-10-30T01:22:40.213693Z",
     "iopub.status.busy": "2022-10-30T01:22:40.212613Z",
     "iopub.status.idle": "2022-10-30T01:22:40.215940Z",
     "shell.execute_reply": "2022-10-30T01:22:40.215660Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Database for solar abundance =  AAG21\n",
      "Asplund, M., Amarsi, A. M., & Grevesse, N. 2021, arXiv:2105.01661\n"
     ]
    }
   ],
   "source": [
    "from exojax.utils.zsol import nsol\n",
    "\n",
    "n = nsol()  #solar abundance\n",
    "MolMR_enstatite = np.min([n[\"Mg\"], n[\"Si\"], n[\"O\"] / 3])\n",
    "MolMR_Fe = n[\"Fe\"]\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Vapor saturation pressures can be obtained using atm.psat"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-10-30T01:22:40.218059Z",
     "iopub.status.busy": "2022-10-30T01:22:40.217778Z",
     "iopub.status.idle": "2022-10-30T01:22:40.333037Z",
     "shell.execute_reply": "2022-10-30T01:22:40.333268Z"
    }
   },
   "outputs": [],
   "source": [
    "from exojax.atm.psat import psat_enstatite_AM01\n",
    "\n",
    "P_enstatite = psat_enstatite_AM01(Tarr)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Computes a cloud base pressure."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-10-30T01:22:40.346523Z",
     "iopub.status.busy": "2022-10-30T01:22:40.335398Z",
     "iopub.status.idle": "2022-10-30T01:22:40.503575Z",
     "shell.execute_reply": "2022-10-30T01:22:40.502377Z"
    }
   },
   "outputs": [],
   "source": [
    "from exojax.atm.amclouds import compute_cloud_base_pressure\n",
    "\n",
    "Pbase_enstatite = compute_cloud_base_pressure(Parr, P_enstatite, MolMR_enstatite)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The cloud base is located at the intersection of a TP profile and the vapor saturation puressure devided by VMR."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-10-30T01:22:40.518181Z",
     "iopub.status.busy": "2022-10-30T01:22:40.517589Z",
     "iopub.status.idle": "2022-10-30T01:22:41.483689Z",
     "shell.execute_reply": "2022-10-30T01:22:41.483391Z"
    }
   },
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(Tarr, Parr, color=\"black\", ls=\"dashed\", label=\"T - P profile\")\n",
    "plt.plot(Tarr,\n",
    "         P_enstatite / MolMR_enstatite,\n",
    "         label=\"$P_{sat}/\\\\xi$ (enstatite)\",\n",
    "         color=\"gray\")\n",
    "plt.axhline(Pbase_enstatite, color=\"gray\", alpha=0.7, ls=\"dotted\")\n",
    "plt.text(500, Pbase_enstatite * 0.8, \"cloud base (enstatite)\", color=\"gray\")\n",
    "\n",
    "plt.yscale(\"log\")\n",
    "plt.ylim(1.e-4, 1.e5)\n",
    "plt.xlim(0, 3000)\n",
    "plt.gca().invert_yaxis()\n",
    "plt.legend()\n",
    "plt.xlabel(\"Temperature (K)\")\n",
    "plt.ylabel(\"Pressure (bar)\")\n",
    "plt.savefig(\"pbase.pdf\", bbox_inches=\"tight\", pad_inches=0.0)\n",
    "plt.savefig(\"pbase.png\", bbox_inches=\"tight\", pad_inches=0.0)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Compute Mass Mixing Ratio (MMRs) of clouds. In this block, we first convert mol mixing ratio of condensates to MMR, then computes a cloud profile."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-10-30T01:22:41.495452Z",
     "iopub.status.busy": "2022-10-30T01:22:41.495135Z",
     "iopub.status.idle": "2022-10-30T01:22:41.603339Z",
     "shell.execute_reply": "2022-10-30T01:22:41.603078Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['H2O', 'CO2', 'O3', 'N2O', 'CO', 'CH4', 'O2', 'NO', 'SO2', 'NO2', 'NH3', 'HNO3', 'OH', 'HF', 'HCl', 'HBr', 'HI', 'ClO', 'OCS', 'H2CO', 'HOCl', 'N2', 'HCN', 'CH3Cl', 'H2O2', 'C2H2', 'C2H6', 'PH3', 'COF2', 'SF6', 'H2S', 'HCOOH', 'HO2', 'O', 'ClONO2', 'NO+', 'HOBr', 'C2H4', 'CH3OH', 'CH3Br', 'CH3CN', 'CF4', 'C4H2', 'HC3N', 'H2', 'CS', 'SO3', 'C2N2', 'COCl2', 'SO', 'CH3F', 'GeH4', 'CS2', 'CH3I', 'NF3']\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/kawahara/exojax/src/exojax/spec/molinfo.py:64: UserWarning: db_HIT is set as True, but the molecular name 'MgSiO3' does not exist in the HITRAN database. So set db_HIT as False. For reference, all the available molecules in the HITRAN database are as follows:\n",
      "  warnings.warn(warn_msg, UserWarning)\n"
     ]
    }
   ],
   "source": [
    "from exojax.atm.amclouds import mixing_ratio_cloud_profile\n",
    "from exojax.spec.molinfo import molmass_isotope\n",
    "from exojax.atm.atmconvert import vmr_to_mmr\n",
    "fsed = 3.\n",
    "muc_enstatite = molmass_isotope(\"MgSiO3\")\n",
    "MMRbase_enstatite = vmr_to_mmr(MolMR_enstatite, muc_enstatite,mu)\n",
    "MMRc_enstatite = mixing_ratio_cloud_profile(Parr, Pbase_enstatite, fsed, MMRbase_enstatite)\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The followings are the base pressures for enstatite and Fe."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "104.674515\n"
     ]
    }
   ],
   "source": [
    "print(Pbase_enstatite)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here is the MMR distribution."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-10-30T01:22:41.610770Z",
     "iopub.status.busy": "2022-10-30T01:22:41.609027Z",
     "iopub.status.idle": "2022-10-30T01:22:42.048810Z",
     "shell.execute_reply": "2022-10-30T01:22:42.048510Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.gca().get_xaxis().get_major_formatter().set_powerlimits([-3, 3])\n",
    "plt.plot(MMRc_enstatite, Parr, color=\"gray\", label=\"MMR (enstatite)\")\n",
    "\n",
    "\n",
    "\n",
    "plt.yscale(\"log\")\n",
    "#plt.ylim(1.e-7, 10000)\n",
    "plt.gca().invert_yaxis()\n",
    "plt.legend()\n",
    "plt.xlabel(\"Mass Mixing Ratio (clouds)\")\n",
    "plt.ylabel(\"Pressure (bar)\")\n",
    "plt.savefig(\"mmrcloud.pdf\", bbox_inches=\"tight\", pad_inches=0.0)\n",
    "plt.savefig(\"mmrcloud.png\", bbox_inches=\"tight\", pad_inches=0.0)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Computes dynamic viscosity in H2 atmosphere (cm/g/s)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-10-30T01:22:42.051735Z",
     "iopub.status.busy": "2022-10-30T01:22:42.051446Z",
     "iopub.status.idle": "2022-10-30T01:22:42.058732Z",
     "shell.execute_reply": "2022-10-30T01:22:42.058453Z"
    }
   },
   "outputs": [],
   "source": [
    "from exojax.atm.viscosity import eta_Rosner, calc_vfactor\n",
    "\n",
    "T = np.logspace(np.log10(1000), np.log10(2000))\n",
    "vfactor, Tr = calc_vfactor(\"H2\")\n",
    "eta = eta_Rosner(T, vfactor)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-10-30T01:22:42.069516Z",
     "iopub.status.busy": "2022-10-30T01:22:42.062894Z",
     "iopub.status.idle": "2022-10-30T01:22:42.257335Z",
     "shell.execute_reply": "2022-10-30T01:22:42.257637Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(T, eta)\n",
    "plt.xscale(\"log\")\n",
    "plt.yscale(\"log\")\n",
    "plt.xlabel(\"Temperature (K)\")\n",
    "plt.ylabel(\"Dynamic viscosity (cm/g/s)\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The pressure scale height can be computed using atm.atmprof.Hatm."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-10-30T01:22:42.260254Z",
     "iopub.status.busy": "2022-10-30T01:22:42.259923Z",
     "iopub.status.idle": "2022-10-30T01:22:42.262257Z",
     "shell.execute_reply": "2022-10-30T01:22:42.261965Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "scale height= 361498.2549385839 cm\n"
     ]
    }
   ],
   "source": [
    "from exojax.atm.atmprof import pressure_scale_height\n",
    "T = 1000  #K\n",
    "print(\"scale height=\", pressure_scale_height(1.e5, T, mu), \"cm\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We need the substance density of condensates. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-10-30T01:22:42.264615Z",
     "iopub.status.busy": "2022-10-30T01:22:42.264328Z",
     "iopub.status.idle": "2022-10-30T01:22:42.278867Z",
     "shell.execute_reply": "2022-10-30T01:22:42.278593Z"
    }
   },
   "outputs": [],
   "source": [
    "from exojax.atm.condensate import condensate_substance_density, name2formula\n",
    "\n",
    "deltac_enstatite = condensate_substance_density[name2formula[\"enstatite\"]]\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's compute the terminal velocity. \n",
    "We can compute the terminal velocity of cloud particle using atm.vterm.vf.\n",
    "vmap is again applied to vf."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-10-30T01:22:42.281818Z",
     "iopub.status.busy": "2022-10-30T01:22:42.281481Z",
     "iopub.status.idle": "2022-10-30T01:22:42.494043Z",
     "shell.execute_reply": "2022-10-30T01:22:42.494309Z"
    }
   },
   "outputs": [],
   "source": [
    "from exojax.atm.viscosity import calc_vfactor, eta_Rosner\n",
    "from exojax.atm.vterm import terminal_velocity\n",
    "from jax import vmap\n",
    "\n",
    "vfactor, trange = calc_vfactor(atm=\"H2\")\n",
    "rarr = jnp.logspace(-6, -4, 2000)  #cm\n",
    "drho = deltac_enstatite - rho\n",
    "eta_fid = eta_Rosner(Tarr, vfactor)\n",
    "\n",
    "g = 1.e5\n",
    "vf_vmap = vmap(terminal_velocity, (None, None, 0, 0, 0))\n",
    "vfs = vf_vmap(rarr, g, eta_fid, drho, rho)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Kzz/L will be used to calibrate $r_w$. following Ackerman and Marley 2001  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-10-30T01:22:42.496860Z",
     "iopub.status.busy": "2022-10-30T01:22:42.496539Z",
     "iopub.status.idle": "2022-10-30T01:22:42.497772Z",
     "shell.execute_reply": "2022-10-30T01:22:42.498042Z"
    }
   },
   "outputs": [],
   "source": [
    "#sigmag:sigmag parameter (geometric standard deviation) in the lognormal distribution of condensate size, defined by (9) in AM01, must be sigmag > 1\n",
    "\n",
    "Kzz = 1.e5  #cm2/s\n",
    "sigmag = 2.0 # > 1\n",
    "alphav = 1.3\n",
    "L = pressure_scale_height(g, 1500, mu)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-10-30T01:22:42.500440Z",
     "iopub.status.busy": "2022-10-30T01:22:42.500137Z",
     "iopub.status.idle": "2022-10-30T01:22:42.501683Z",
     "shell.execute_reply": "2022-10-30T01:22:42.501923Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.18441767216274083"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Kzz/L"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-10-30T01:22:42.507693Z",
     "iopub.status.busy": "2022-10-30T01:22:42.507407Z",
     "iopub.status.idle": "2022-10-30T01:22:43.714400Z",
     "shell.execute_reply": "2022-10-30T01:22:43.714105Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0, 'condensate size (cm)')"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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/xojA8HoDqZOTcEZjwim4DjSKpS601vq8pHtKjRELCwtRVFQU9caI4RrViVCwli5diqVLlwZ1bVJSUkwXdRERUeQMpzGi1lSVlHSMxuXv6jile8VqY8RwjepESHrxGxsbvY43NjaioKBgWPeuqqpCVVWV1xAgERGNTW63G83NzV6jQNLPfz1HYwL1BpKoR2W0lr8rn6PX8nd1DMqkS1p1lpKSArPZjIKCAlgsFqSkpAzjVY8No7pGKDExEbNmzcK2bdvkYx6PB9u2bcO8efOGde9Vq1ahpqYGu3fvHm6YREQUo0RRRFdXFw4fPoyamhqcOnUK7e3tcLlcEavjUTYU9FdTpKZe/j5UHc9wa4qkDtdSkiQtiZ84cSLOPvtsnHHGGWMiCQJGwYhQd3c3jh49Kr9/4sQJfPLJJ8jOzsaECRNQWVmJiooKzJ49G3PnzsX69evR09MjryIjIiLSMjg4iMbGRp/GiMranViaqopGTZHRaMS4ceOQnZ0t1wIlJibq9SWICTGfCO3ZswcLFiyQ35cKmSsqKrBhwwZcf/31aG5uxpo1a2C32zFz5ky8/vrrPgXUREREwOlf+h0dHaivr4fdbkd7ezsGBgZ86nYk/qaipHORmKoKp6ZIK9ZwkyNBOL09RkZGhrwkPiMjw2cKbSwQRK2vegAnTpzAe++9h5MnT6K3txe5ubk4//zzMW/ePCQnJ0cqzhGnrBE6fPgwOjo6kJ6eHu2wiIhoGJxOJxoaGmCz2eBwONDT0+OTUKiTB3WNj5SoAPBaWaVOSJQjO+qRH2XCMtR5f6NGUqzKKayhkqNgYjUajRg/fjzMZjMsFgsKCgpgMpl0ePVHVmdnJzIyMob8/R10IvTss8/id7/7Hfbs2YP8/Hy5SKq1tRXHjh1DcnIybrjhBvzkJz/BxIkTdftEoi3YF5KIiGKXx+NBW1ubV2NEp9MZdEKilRypp9BGKjkKlKhJ59UjSsEkRwaDAUlJScjKykJBQQGKiopGVWNEtWB/fwc1NXb++ecjMTERK1aswD/+8Q+fvjoDAwPYuXMnnnvuOcyePRv/8z//g2uvvXZ4nwEREZEO+vr65FGglpYW9PX1eSUAgaaqxuLyd60pPpPJhLS0NOTm5sJisSAvLw8JCTFfPaOLoEaE3njjjYDdmJVaWlrwxRdfYNasWcMOLhZwRIiIaHQKtjGiXlNV/up71IlIKM8K5bwk0LSZOlaj0ThmGiOq6ToiFGwSBAA5OTkBOzePFuwjREQ0evX09MjF0C0tLejv7x/xTs3K5EN53N/IUTixaCVXgQqulc0hExMT5VGgkpISZGdnj+rGiOEKuVh63759MJlMmD59OgDg5ZdfxtNPP42ysjL8/Oc/H3PL6jgiREQ0erjdbjQ2NqK+vh4Oh8OrMSIQudGYWK4pUidOgiAgNTUVOTk5KCwsRGFh4ZjpCaQU7O/vkBsq3nbbbTh8+DAA4Pjx41i+fDlSU1Pxwgsv4O677w4/YiIiojCJ4unGiIcOHcLBgwdRW1uLjo4OzcaIWs0IlfcJpxmh+ryyaaJ0rZJyg1Ot5Ee6l55NHKVRIGVjxNLS0jGZBIUi5Eqow4cPY+bMmQCAF154AZdccgmqq6vxwQcfYPny5Vi/fr3OIRIREfk3ODgIu92O+vp6uTGilECEUzisx1SV8nn+ttTQs+B6qFgNBgPGjRsnjwJZLJYxN4MTrpATIWWG+dZbb+HKK68EAJSUlMDhcOgbHRERkR+i+GVjRJvNho6ODvT39/uMvihrY4DRtfu78nmhJkfS3+OlMWK4Qk6EZs+ejV/+8pcoLy/Hu+++iyeeeALA6UaLY6mbM4uliYhil9PplIuhlY0R/U0dhTIao1xpFankSD06FSg5UsasvI+/USxpm5Cx0hgx0kIulv70009xww034NSpU6isrMR9990HALj99tvR0tKC6urqiAQaLSyWJiKKHcrGiE1NTejq6pK3xwD07dQs8bc8Xe+Ca/X9g1n+rlVwLTVGzM7OlkeBxo8fH3ejQLp3lj5+/DgmTZrk93x/fz+MRuOYyzaZCBERxQatxogAhr2qKtgtNYZKjpQjO8NNjrRi8RerMr6EhASkp6fLo0D5+flxuSQe0LmPEACcd955KC0txdKlS3HVVVdh7ty5XufH0j5jREQUO4JpjAhEfqpqpGqK/CVjylgkykQqNTVV3h6juLgYqampen0JxrSgEyGHw4E333wTL7/8MpYuXQpBEHDllVdi6dKluOyyy5gIERGR7np6elBXVwebzYa2tja/jREB34QkmITD3/lwaoqU9xqp5Egqhk5LS0NeXh6Ki4uRk5Pjs3yf/Au5Rgg4/cXZuXMnXnnlFbzyyis4deoUysvLsXTpUixZsgS5ubmRiDUqODVGRDTyXC4XmpqavBojSkXA/mpjojVVFWj392BjDSUW6Zi0PcZYb4wYLt1rhAI5cuQIXnnlFbz88sv4+OOP8fDDD2PVqlXDvW1UKVeNHT58mIkQEdEIEMXTjRHr6upgt9vR3t4Op9MJt9utmXBEq1Oz8p6hJkfKa8MpuAaAxMREZGRkyNtjZGZmchRIZUQTIaWWlha0trbirLPO0vO2UcMRISKikaFujNjV1QW32x3UCi9/hc3BrNDSIzkKtuB6uLEoGyNaLBYUFhayMaIfuhdLKzU0NOD9999HU1OTT6vy22+/fUxsukpERCNDFE83RpRGgZSNEbU6Qw9VOKx+X6ugWnquvzoeZWzB1vEoSQmNdDzYDtf+aooAsDFihIScCG3YsAG33XYbEhMTkZOT45PN3n777boGSEREY5eyMWJzczN6e3t9Eg8g/FVVEuXH+EuOpOQl1CJm5fmhErVwOlwbDAakpaXBbDajqKgI+fn5Y65VTTSFnAj97Gc/w5o1a7B69WrORxIRUVi0GiM6nU6va4azqspfp+ZwRmP0WOEVzn5jysaIBQUFKCoqisvGiJEWciLU29uL5cuXMwkiIqKwaDVGVI6k+JvKks4Fk5DoNRoTqf3GhhrFMplMcmPEoqIi5OXlxW1jxEgLOZv5zne+gxdeeCESsRAR0RjmdrvR1NSEmpoaHDlyBDabDT09PfB4PD71plLyAHjvGaaum/F3Xvq7dN5fcqQknVfGor6nKIpee1AGE0ug88r7SEnTuHHjUFBQgEmTJqGsrAyFhYVMgiIo5FVjbrcbV155Jfr6+jB9+nSfecqHH35Y1wCjhcvniYj0o9UYUWu1FzB6lr/rHYs0CsTGiPqI2KqxtWvX4o033sDUqVMB+Ga0Y8WqVauwatUq+YUkIqLQ+WuMCHgnOtHu1BzO7u96xcLGiNEVciK0bt06PPXUU1ixYkUEwiEiorFAFLUbIwZKOAIVDmvVDAVKSJRxBJuQKI1EwbUgCD6NEbOyssbUoMJoEHIilJSUhPnz50ciFiIiGgMGBwdhs9nQ0NAgN0aUlqX7W1UVqHBYug6AT0IhnVNOVYU6MqR1f61Y9Cy4NhqNSE1NZWPEGBDy5OMdd9yBxx57LBKxEBHRKCaKItra2nDw4EEcPnwYdXV1aG9v99oENZTCYXVC4q9OR7qXVhGz8ny4RcwA5AQrnIJr5fME4fQmqTk5OSgtLcW0adMwYcIEJkFRFPKI0K5du/D222/j1VdfxTnnnONTLP3iiy/qFhwREY0OUmNEm80Gh8OBvr4+n13ggeEvf5dEe/m7coQr2FEso9GI8ePHy0viCwoKkJAQ1gYPpKOQvwKZmZlYtmxZJGIhIqJRJlBjxHCLmCXSx4fTjHAkaoqCLbiWGiNmZWXJjRHT0tLCfs1JXyEnQk8//XQk4iAiolGmr69P3h5DqzFitJoRKq9TXh8oOQq3pkjrvDJWo9EoN0YsLi5Gbm4uewLFmJAToRMnTsDlcvnsLn/kyBGYTCaUlpbqFRsREcUgt9uNlpYWr1Egt9s9olNVwY7GKAVbcK1HcgQAqamp8ihQcXExUlNTw33JKYJCLpZesWIFPvzwQ5/jH3/88ZhaUl9VVYWysjLMmTMn2qEQEcWMnp4eHD16FDU1NTh16hTa29vhcrkAhF44DOjXqVn9bH8jR+pr9S64FkURJpMJOTk5mDBhAqZNm4bJkyczCYphIXeWTk9Px759+zB58mSv40ePHsXs2bPR3t6uZ3xRF2xnSiKisUxqjFhXVweHwyEviQd8p8C0prG0ukZL10hvlSM76pEfZTISzHk15eovra7R6uJrrWcp76UVq7oxosViQXJy8jBedRqOiHWWFgQBXV1dPsc7Ojq8MmkiIhr9RDFwY8RQp6qU1ykTjkhMm6mnwtSxqONRng+l4NpgMLAx4igWciJ0ySWXYO3atfjb3/4mF3y53W6sXbsWX/nKV3QPkIiIokPZGNHhcKC7u9unMSIwOpa/R6qmiI0RR7+QE6Ff//rXuOSSSzB16lRcfPHFAID33nsPnZ2dePvtt3UPkIiIRpYoimhvb0ddXR0aGxvR3t6OgYGBkAqHpWuUycxoXf6uvk6SlJSEjIwM5Ofno7i4GBkZGRwFGoVCToTKysrw6aef4vHHH8f+/fuRkpKCm2++GT/4wQ+QnZ0diRiJiGiEDAwMoKGhQd4eo7e316czdKijMXotf5eOayVHw1nhFWpyJC2Jl0aB2BhxdAu5WDresFiaiOKBx+NBa2urT2NEf0XKEr2KnMMtuFbHEsyzQjmvboyYnJyMzMxMNkYcBXQtlj516hQmTJgQ9MPr6+tRVFQU9PVERBQ9UmNEm82G1tZWr+0xRnKqSincmiKtWMOtKVLGkpCQgLS0NDZGHIOC6iM0Z84c3Hbbbdi9e7ffazo6OvDHP/4R5557Lv7xj3/oFiAREUWG2+1GY2MjampqcOTIEdhsNnkqTE2dAGn1BlKO2ISywanWdJe/3kBKI9EbSBAEpKamoqCgAGeeeSbKyspQUFDAJGgMCWpEqKamBg888AAuu+wyJCcnY9asWXJ/hLa2NtTU1ODzzz/HBRdcgIceeghXXHFFpOMmIqJh6OnpQV1dHWw2G9ra2jAwMOBVCxRK4XAkVnip7x9OwbWyX1CosQKAyWSSl8QXFxcjJydHTvZo7AipRqivrw9btmzB+++/j5MnT6Kvrw9msxnnn38+Fi1ahHPPPTeSsUYFa4SIaCwJ1BhxqNobrToeZcIRbB1PpGuKpPPqpCnYmiJpSXx2djYbI45iwf7+ZrH0EJgIEdFYIIqnGyPW1taisbERbW1tGBwcDCoh0VrhpZVwaNUUKa+NdJHzcAuuBUFAYmIiMjMzYTab2RhxlItYZ2kiIhpdhtMYUT0dJSUVQ01Vqd8OVXAd7rSZ1nllrMEWXEujQGazGYWFhWyMGEeYCPlRVVWFqqoquciud7AXaWKa/M036B7EoGcQCYYEJBq//GbpHewFACQnJMMgnP6Xx6BnEIPuQRgNRiQZk8K6ts/VB1EUkWRMgtFwukjP5XHB6XbCIBiQnJAc1rX9rn54RA8SjYlIMJz+38HtcWPAPRDStYIgICUhRb52wD0At8cNk9EEk8EU8rUe0YN+Vz8AINX05WaFTrcTLo8LJoMJJmPo14qiiD5XHwAgJSHF5+sZyrVBfe11+P9E6+upx/8n0tdzuP+fqL+ew/3/xN/Xc7j/nyi/nsP9/8Tf1zPs/08i9DNi0D2I5tZm2BpsaGtukxsjuuCCCBEJSIBBMEAQBLg9brhEFyACiYZE+fNwwQVRFGEUjTDg34kERLgF9+lrhUQ54RgUByFChEkwyUmGRzx9HCKQZEiSX99BzyDcohsJQgKMgvF0AgNRfp4JJjm5cf/7vwQkwIjTn5vH44FTPL28X7qvIAhwiS64RTcMHgOMghEGg+F0bBiEAAGJQqIcm0t0AQbAlGiCOcuMgoICWCwWmFJNcAkumEQTf0aM8p8RwWDVlx+rVq1CTU2NvFLu0hcuRdtAm3z+6c+fhrXaigc/ftDr477296/BWm2FrccmH3vu4HOwVlux5oM1Xtd+/R9fh7XaiuPtx+VjLx99GdZqK+569y6va6/afBWs1VYcaD0gH3v9i9dhrbbi9rdv97r2269+G9ZqK/Y17ZOPvVv3LqzVVqzcutLr2hWvr4C12ooPGz6Uj31s/xjWaitufO1Gr2v/863/hLXaim2ntsnHPnV8Cmu1Fde8co3XtT/a/iNYq63YcnyLfOxI+xFYq6248sUrva5d/d5qWKut2HR4k3ystqsW1moryl8o97r2/p33w1ptxV8P/FU+1tzbDGu1FfP/Nt/r2od2PwRrtRV//Ncf5WNdg12wVlthrbae/iH4b4/+81FYq6149J+Pysdcoku+tmvwy/31/vivP8JabcVDux/yet78v82HtdqK5t5m+dhfD/wV1mor7t95v9e15S+Uw1ptRW1XrXxs0+FNsFZbsfq91V7XXvnilbBWW3Gk/Yh8bMvxLbBWW/Gj7T/yuvaaV66BtdqKTx2fyse2ndoGa7UV//nWf3pde+NrN8JabcXH9o/lYx82fAhrtRUrXl/hde3KrSthrbbi3bp35WP7mvbBWm3Ft1/9tte1t799O6zVVrz+xevysQOtB2CttuKqzVd5XXvXu3fBWm3Fy0dflo8dbz8Oa7UVX//H172uXfPBGlirrXju4HPyMVuPDdZqK7729695Xfvgxw/CWm3F058/LR9rG2iTv55Kj+x9BNZqK57Y/4R8rM/VJ18r/aIDgCf2PwFrtRWP7H3E6x7StbH0M6K/vx/P7H4Gi15bhF989gs4HA65L9AG9wasc61DrVgrr6o6Kh7FOtc6POd5zmu05RnXM/jt4G9xXDwuj7icwin8dvC32Oja6DU69Hf337HOtQ6HxEPyyEy9px7rXOvwlPspr2tfdL+Ih90Po0askZ/XJDbhN87f4EnXkwC+HDl6xf0K1rnW4Z/uf8ojPO1COx52P4zHXY/LsYqiiNdcr2Gdax32Yq983x6hB+tc6/Dw4MNeo0Hbxe34jfM32J+8H1OmTMGUKVNgSDXgwr9dyJ8RGBs/I4LBESEiojHE4/HA4XCcrgWyNwI4vUxeNCjKQVWVoeoaGK+pJmhPRak/Vn1ertdRPEu9wut0KKJcZ6R1rbJGSTouCAIE8cvneXW+hu/nom4HIAgCUlJSkOJJAbog9wYCADhBcSbkYumenh6MGzcuUvHEHKnYyuawIT87P6aGvTk1xqmxeB/25tSY99e+t7cXjkYHmuxNaG1tRXdPNwbFQRgEAxL+/e9eQRDg9DhPf40MiTAI/+7F8+8pLINggEkwyde64ILbc3paSoAgT2Epr5V+jTg9TkAATIJJvlY5NSZNuYmiCJfogiiIMMIIQTxda+T2uOUptwQkyCM3ymsN/57I8Hg8cAmnR2yk6TlBEOB0O+GBBwbRgARDgjxtJ12bakpFeno6zGYz8ix5yMrOQlJCEn9GjMGfERFbNTZ+/Hhcd911uPXWW+Nit3muGiOiWOd2u+VRoObmZnR1dcHlcgW1qipay9+1Cqylv0uxhrv8Xeu8wWBASkoKsrOz5e0xUlO//CVKY0+wv79DrhH661//itbWVlx66aWYMmUKfvWrX6GhoWFYwRIRUXi6u7tx9OhRHDhwALW1tejo6JCTIInH4/ly+klBPSWm7NSsvEa9yms4nZrV55X3UU6FaS3VV95TfS/lOWUyJ4oiTCYTsrOzMXHiRJx99tk488wzmQSRLOw+Qs3NzXjmmWewYcMGHDhwAIsWLcKtt96KpUuXjqldeDkiRESxyOVyobGxEfX19WhubpaXxAPBjcb4W24ODK83ULgjQ/7uP5zeQAaDAePGjUN2djYsFgsKCwvZGDGOjGhDxcceewx33XUXnE4nzGYzvv/97+Oee+4ZExk3EyEiiiWiGH5jxEDng004hpqq0nPazN/IkL9ETXltUlKS3BhxwoQJyMzM9BkBo7Et4g0VGxsb8Ze//AUbNmzAyZMncc011+A73/kO6urq8Otf/xofffQRtm7dGu7tiYhIZajGiMDwdn9XJ0CxsN+Y8nnB7DeWkJCAcePGIScnRx4FMpmC7ylD8SfkROjFF1/E008/jTfeeANlZWX4r//6L9x4443IzMyUr7noooswbdo0PeMkIopboiiivb0dp06dQnNzs9wYUSv5CTfh0DqvlXAoE51AnZqV99ErOdJKxqT3jUYjEhMTkZWVhfz8fBQXFyMtLc3rXkRaQk6EbrnlFixfvhwffPAB5syZo3mNxWLBT3/602EHR0QU7/r7+9HQ0ACbzQaHw4G+vj6fYmN1QiGdG+nRGMA7OQqUqOk5cmQ0GpGWliZvj1FQUDCmalUpskKuEert7R0TtT/BYo0QEUWDx+NBa2sramtr0dTUhK6uLjidX3b706qNCVQ4rPw4Pep4Irn7+1DnpecZDAYkJycjKytLXhI/fvz4cF9yGmMiViOUlpYGm82GvLw8r+MtLS3Iy8vzWlZJRESh6+3tlUeBWlpa5FGgUEZjRmKqSo+aIn+jWFLtk79YTCaT3BixuLgYZrMZRqNRl9ef4kvIiZC/AaSBgQHu1EtENAxutxvNzc2oq6vzaYyoHn2J1FTVcGqK1PU4kSi4FgSBjRFJV0EnQo8+enqjOUEQ8Kc//clr+NHtdmPHjh04++yz9Y+QiCgOdHV1ob6+Hna7HW1tbRgYGPBKCIDAhcP+Eg4lZfIRiZoirdEefwXX6liHGsUSxdONETMyMpCXl4fi4mJkZ2f7NIkkClXQidAjj5zebVkURTz55JNeQ5CJiYkoLS3Fk08+qX+EOrj66qvxzjvvYOHChdi0adPQH0BENEJcLhfsdjsaGhq8GiOqE4GRmqqK9vJ3ZazKpE9aEl9YWMjGiKSroBOhEydOAAAWLFiAF198EVlZWRELSm933HEHbr31VvzlL3+JdihERAC0GyM6nU45IdBjqmo0LX/XGsUSBEFujCiNArExIukt5Bqh7du3RyKOiPra176Gd955J9phEBEBAJxOJ+x2O+rr69HS0hKwMaJeozH+Eo5gaoqUzxqpgmtlY8SioiIUFBSwMSJFRFCJUGVlJX7xi19g3LhxqKysDHjtww8/HFIAO3bswG9+8xvs3bsXNpsNL730Eq666iqva6qqqvCb3/wGdrsdM2bMwGOPPYa5c+eG9BwiomgTRd/GiE6nMyoJRzDJkfR2OL2B/MXiL1aDwYCkpCQ2RqQRE1Qi9M9//hODg4Py3/0J53/Unp4ezJgxA7feeiuWLVvmc/75559HZWUlnnzySVitVqxfvx6LFi3CoUOH5CX8M2fOhMvl8vnYrVu3wmKxhBwTEZHetBojqpOLWF3+rqRVxKwVy1DL37ViSUhIkBsjWiwW5OfnszEiRZwum67qRRAEnxEhq9WKOXPm4PHHHwdwet68pKQEt99+O+65556g7/3OO+/g8ccfH7JYemBgAAMDA/L7nZ2dKCkpYUNFIgqLv8aI/pIR6WPC3f19qPPK0Z5gPn44u78r76VMtNSxqBsjFhcXY9y4ccN52YmCbqgY8rrDjo4OtLa2+hxvbW1FZ2dnqLcLyOl0Yu/evSgvL5ePGQwGlJeXY+fOnbo+S7J27VpkZGTIf0pKSiLyHCIa+3p7e3Hs2DHU1NTg5MmTaG1tlf+hpVz2rR5lGWo0RrpWOYIjJRbKpES5FYfWVJXWea1Y1DFoTaupl/qr76Vstqt8lslkQlZWFkpKSnD22Wdj8uTJTIJoRIWcCC1fvhzPPfecz/G///3vWL58uS5BSRwOB9xuN/Lz872O5+fnw263B32f8vJyXHvttXjttddQXFwcMIlavXo1Ojo65D+1tbVhx09E8cntdsNut6OmpgZHjx6F3W5Hb28vAO3aGfXeYdLf/dXxhJNwaD0rlFik8/6SIyVlcuQvFkE43RixoKAAkyZNQllZGfLz89kdmkZcyJOvH3/8sWZB9Ne+9rWY3Wj1rbfeCvrapKQkJCUlRTAaIhrLpMaINpsN7e3t6O/v95kqGq3L30MpuFbGrLwXAK/GiCUlJcjKymJjRIqakBOhgYEBzcLkwcFB9PX16RKURNo7prGx0et4Y2MjCgoKdH0WEdFwSI0R6+vr4XA4vBojjpbl74FiGW7BtTRtp2yMaLFY+A9PirqQU/C5c+fiD3/4g8/xJ598ErNmzdIlKEliYiJmzZqFbdu2ycc8Hg+2bduGefPm6fostaqqKpSVlWHOnDkRfQ4RjW7SkvhDhw7h0KFDqKurQ2dnJ9xu94hOVamTI+XbYKaqwq0pUp9XT5NJ7ycmJiI3NxelpaWYNm0aSktLmQRRTAh5ROiXv/wlysvLsX//fixcuBAAsG3bNuzevRtbt24NOYDu7m4cPXpUfv/EiRP45JNPkJ2djQkTJqCyshIVFRWYPXs25s6di/Xr16Onpwe33HJLyM8KxapVq7Bq1Sq56pyISE3ZGNHhcKC3t1dOgEb78vdwR7HU9zcajRg/fjwbI1LMCmv5/CeffIKHHnoI+/fvR0pKCs477zysXr0aZ511VsgBvPPOO1iwYIHP8YqKCmzYsAEA8Pjjj8sNFWfOnIlHH30UVqs15GeFI9jld0QUP0RRRGtrq7xLfHt7u9xrDYi/5e9asUhL4jMzM9kYkaIi2N/fMdVHKJZUVVWhqqoKbrcbhw8fZiJERABON0aUiqFbWlq8GiNKAiUcQyVHoSYcwSQk6pEpf4mauvha61nBxGo0GuXGiEVFRcjLy2NjRBpxEU2E3G43Nm/ejAMHDgAAzjnnHCxdunRMLnvkiBARAV82RpS2x+js7JRHgfwlJNEajfF33t+UmhTrcEex2BiRYkmwv79DTtGPHj2Kb3zjG6irq8PUqVMBnG5CWFJSgi1btuDMM88MP2oiohjU29uLuro62O12tLa2oq+vL+jd4ZX81fGMVE1RqLu/K6/T+ryUz0xISEB6ejrMZjOKi4vlVb9EsS7kEaErrrgCoiji2WefRXZ2NgCgpaUFN954IwwGA7Zs2RKRQKOFI0JE8cvtdqO5uVmuBZJWg4U7VQX4jgwBQ4/GBDtyFEoseo1iGQwGpKSkIDs7Wx4FSklJ0ePlJxqWiI0Ivfvuu/joo4/kJAgAcnJy8Ktf/Qrz588PL1oiohgTqDGiHiu8Ao3GKJMTde2O1mhMOLGEEqu/1WhJSUlIT09Hbm4uGyPSqBVyIpSUlISuri6f493d3UhMTNQlqFigLJYmovghNUasq6tDS0uL3BhRoudUVbAJh5K/5EePWNTnpXjUsRiNRqSmprIxIo0JIU+N3Xzzzdi3bx/+/Oc/Y+7cuQBOb7uxcuVKzJo1S17yPlZwaowoPoiiiI6ODtTX18Nut6OtrQ1OpzPswuFoTVX5i0WPgmvgdGPEzMxM5OXlobi4GJmZmT61UESxIGJTY48++igqKiowb948uSmWy+XC0qVL8bvf/S78iImIosTpdMJms6GhocGrMaKa1miMdDySU1XqGKKx35jUGNFsNsNisbAxIo0ZISdCmZmZePnll3HkyBEcPHgQADBt2jRMnjxZ9+CIiCJJFE83RqytrUVzczM6OjrkJfGBpqqUIzPK0ZhITlVJyYw6FnU8yvND1RQFs98YGyPSWBd2h6uzzjorrE7SRESxYKjGiIFGYyTRXv7u8Xg0z6ljVn5OoYxiJSQksDEijXlB/R9dWVkZ9A0ffvjhsIOJJSyWJhqbPB4PHA6H15J4rcaIgO9ojFbCoedoTCQLrtWjWOrkSPkcaUl8ZmYmGyPSmBdUsbTWXmCaNxMEvP3228MOKpawWJpo7BiqMWIohcP+kiF1EbP0MaEUXIcbSygF18r4lAXXbIxIY4WuxdLbt2/XLTAiopHmrzEiEJvL3/09a6hY/J0PZhRLEASkpKTAbDajoKAAFouFjREpLoQ92Xv06FEcO3YMl1xyCVJSUjTn04mIokkURXR3d6Ourk5ujDgwMOAzmhJs4bBeydFQNUV6F1xL12hN8QmCgMTERGRkZMBsNrMxIsWdkBOhlpYWXHfdddi+fTsEQcCRI0cwadIkfOc730FWVhbWrVsXiTiJiEIyODiIxsbGgI0RtQqHlUXIeozGaBVc+6spGumCa3VjxKKiojHVGJcoGCGn/D/60Y9gMplw6tQppKamysevv/56vP7667oGF01VVVUoKyvDnDlzoh0KEYVAFEW0t7fj8OHDOHToEOrr69HR0eGT3EikaSHpY5ULJLRWVknJlPpcoPPKWh1/U1VK0nll4qYVS7ixCoKApKQkmM1mnHHGGSgrK0NpaSmTIIpLIXeWLigowBtvvIEZM2YgLS0N+/fvx6RJk3D8+HGcd9556O7ujlSsUcFiaaLRw+l0oqGhATabDQ6HAz09PV7JABBa4bC6CFmiHDlSntejiNlfXJLhFlyzMSLFi4h1lu7p6fEaCZK0trZyrxkiigqPx4O2tja/jRGVoyOhLH9X1tFEaqoq2IJr9XXK+wRTU8TGiETaQp4au/jii7Fx40b5fekb96GHHgp6mT0RkV76+vpw4sQJHDhwACdPnkRLSwsGBwe9EhbAewos1KkqdTIlHfM3VRXKtJn6vL8iZyk+5bSZ1iiVOhYAMJlMyMzMRElJCaZOnYopU6YgPT2dSRARwhgReuihh7Bw4ULs2bMHTqcTd999Nz7//HO0trbigw8+iESMREQ+wmmMKJ3TKhwONBqjFMxojNazhlNwHc4olnRcaowoFUOzMSKRt5AToXPPPReHDx/G448/jrS0NHR3d2PZsmVYtWoVCgsLIxEjEZEXZWPElpYW9Pf3x83yd/XIkPq89PfExESkpaUhNzcXxcXFyMnJYWNEIg0hF0vHGxZLE8UOt9uNxsZG1NfXw+FweDVGBCLXqVl9f4/Ho9k1OhoF1+pkSBAEryXxhYWFbIxIcSlixdKTJ0/GjTfeiBtuuGFMb7rKvcaIYoconm6MWFtbC7vdjvb2djidTrjd7hHf/V09pSZdE+2CawBsjEgUhpBHhB555BFUV1dj7969mDVrFm688UZcf/31KCgoiFSMUcURIaLoGhwchN1uR319vdwYUVmUHEujMeqpMuXIkcTfKNNQo1CBYjEYDBg3bpw8CmSxWNgTiOJesL+/w54aO3z4MJ599ln87W9/w4kTJ7BgwQLceOONuPnmm8MOOhYxESKKDlEU0dHRgfr6ethsNnR0dKC/v1+zNmeoqSrltZFOjoLtDaRHLACQlJSEjIwMeUl8RkYGV4MRYQQSIaWPPvoI//mf/4lPP/10zE0lMREiGnlOpxP19fWw2+1yY0T1tFegAmfAf3Kk92hMMOcjkRyxMSJRYBGrEVLatWsXqqur8fzzz6OzsxPXXnvtcG5HRHFO3Rixs7MTAwMDfmtjQln+rkxOlMmGv5oiPfcb04pFmRyFst+YwWBAUlISsrOz5VGg8ePHcxSIKEwhJ0LqKbFLL70Uv/71r7Fs2TKMHz8+EjESURzo6+uTt8doaWlBX1+ffC7UhCSY5EhrFClSRczK54VTcC3dx2QyIT09XR4Fys/P55J4omEKORE6++yzMWfOHKxatQrLly9Hfn5+JOIiojihR2PEoc4rDWc0Ro/kSCsZk97318RRaoyYlZWFgoICNkYk0lHIidChQ4fG9LJ5Iho5PT09cmPE1tZWv40RhzMao0xoYnn5u9YoliB82RgxLy9PbozIJfFE+gk5EWISRETD5XK50NTU5NUYUarJAWJjNEadHGkVXAebHGnFEkysbIxIFHnDKpYey9hQkUh/oiiiq6tLHgXSaow40lNVwdYUKalj0bPgWhoFysjIQG5uLkpKSpCZmclRIKII4RYbQ+DyeSJ9aDVGdLlcmskIEN3l7+qPH6neQMrGiBaLBYWFhWyMSBSmEVk+T0Q0FFE83RhRGgWSGiNqTVUFOxqjTDb0HI1RnleO9ui5/F0rVoCNEYmihYkQEUWMsjFic3Mzent7NZeWhzNVpTWKFIlpM4n08cNZ/q5VU2QwGJCWlgaz2YyioiLk5+ezMSLRCAoqEaqsrAz6hg8//HDYwRDR2KBsjNjU1ISuri44nU6va4JNSPyNxkhGw/J35fSX8l7JycnIzs6Wl8SzMSLRyAsqEfrnP/8Z1M34DUxE/hojatXpAKGNxgS7wktrNEb5rGgXXCsbIxYVFSEvL4+NEYmiJKhEaPv27ZGOg4hGObfbjZaWFnl7jK6uLp/GiIC+CUcwyZH0NtipKr2WvytJyZG0JF5qjFhcXIzU1NThvvRENAysESKiYZMaI9psNrS1tcmNEeNx+bvW/QEgMTER6enpbIxIFGPCSoT27NmDv//97zh16pTPvP+LL76oS2BEFPv8NUZUi4XRGHUs0rlIJ2pGoxEpKSlsjEgUo0L+58hzzz2Hiy66CAcOHMBLL72EwcFBfP7553j77beRkZERiRiJKMaIoojOzk4cPnwYBw8eRG1tLTo6OuB2u/0WOUvUCYMySZESC2VPHuV2E1rJkdZ5ZVKjTGiUz9GaVlNfq76XssGqv2dJ56Rd4nNycjBx4kRMmzYNpaWlTIKIYkzII0IPPvggHnnkEaxatQppaWn43e9+hzPOOAO33XYbCgsLIxEjEcWQwcFB2Gw2NDQ0oKWlBV1dXfIUUihTVSMxGqM1VaX38netWNkYkWj0CDkROnbsGL7xjW8AOD3n3dPTA0EQ8KMf/QiXXnop7r//ft2DJKLoE0UR7e3tqKurQ2Njo1djxEAJyVhd/q6OQ8LGiESjS8iJUFZWFrq6ugAARUVF+OyzzzB9+nS0t7ejt7dX9wCJKPqkxog2mw0OhwN9fX1yYjLUaAww9pa/S8eV9zEajRg/fry8JL6goAAJCVyPQhTrQv4uveSSS/Dmm29i+vTpuPbaa3HHHXfg7bffxptvvomFCxdGIsao4KarRIEbI+qRcIy25e8SZSxGoxFJSUnykng2RiQaXULedLW1tRX9/f2wWCzweDx46KGH8OGHH+Kss87Cvffei6ysrEjFGhXcdJXiVV9fn7w9htQYUZm4aI3WKBMGdfKjTFgCnR+pDU6DiSXQ/QHAaDTKjRGLi4uRm5vLxohEMSLY39/cfX4ITIQo3igbI0qjQMrVYP6mqqS3wZwPNeGIteRIEAQ2RiSKcRHdfd7j8eDo0aNoamry6RlyySWXhHNLIooBWo0RtRIKdeGwVp3OSOz+Lhmpgmvg9PYYGRkZyM3NZWNEojEg5EToo48+wn/8x3/g5MmTPgWEgiCwpoZoFJIaI9bV1cHhcMhL4gF4fZ8H26l5NO3+Hmys6saIFosFycnJw3jViSgWhJwIff/738fs2bOxZcsWFBYWsiCQaBQTRRFdXV2oq6uD3W5He3s7nE6nz/SRUrRGY6TzoSx/V49eBRrF0opV+pOYmCiPApWUlCArK4s/+4jGiJAToSNHjmDTpk2YPHlyJOIhohESTGNEIPipqqFGY7TupdcKL3XdkF77jRmNRqSmprIxItEYFnIiZLVacfToUSZCRKOUKHo3Rmxvb8fAwEDEpqqkt8FOVfk77y+W4SRH/kaxADZGJIoXISdCt99+O3784x/Dbrdj+vTpMJlMXufPO+883YIjIn0NDAygoaHBqzGi2+3WdaoqlnZ/V54PdhRLWhKfnZ3NxohEcSDk5fNaqyOU//Iba8XSXD5PY4HH40Fraytqa2vR3NyMzs5ODA4OyufVS8YlyoRFeV75PR/M+Vhb/q41amQwGJCcnIzMzEy5MWJaWtpwX3oiipKILZ8/ceLEsAIjopElNUa02WxobW312h5DWWisHIkBfEdrhjMa46/gWjoe7YLrhIQEpKWlsTEiURwKORGaOHFiJOIgIp0Faoyopt43y99U1XCTIymZkZ4ZasF1oBVe4cQqCAJSUlKQnZ0tjwKxMSJRfAkqEXrllVewePFimEwmvPLKKwGvXbp0qS6BEVH41I0RBwYGvJaEx9ry92ALrtX3UsYyVKzKWAA2RiSi04KqETIYDLDb7cjLywv4g4I1QkTRFUxjRH8Jj8fjkY8rExxlkjFSdTzB1hQpf3wFGwsbIxLFB11rhJT/elRvqUFE0SeKwTVGVCcKoYzGhDpVNdyaInUC5G81mvo6rVikj0lMTERmZibMZjMbIxIRgDD3GiOi2KFsjOhwONDd3R2wMSKgz/L3YKaq1OeHkxz5228smIJrqTGi2WxGYWEhGyMSkSysRGj37t3Yvn275qarDz/8sC6B6aW2thY33XQTmpqakJCQgJ/97Ge49tprox0W0bCJov/GiMDIdGoONBqjd8G18nnB7jdmNBrlUaD8/HwUFRWxMSIReQk5EXrwwQdx7733YurUqcjPz/f5IRVrEhISsH79esycORN2ux2zZs3CFVdcgXHjxkU7NKKwDQwMyEviW1pa0Nvb6zMlNdwVXurzSqGMxijvM5L7jSmXxBcWFrIxIhFpCvmnwu9+9zs89dRTWLFiRQTC0Z80DA4ABQUFMJvNaG1tZSJEo5KyMaK0JN7pdPpNKICxvfxdaxRLEE4viWdjRCIKRshrRQ0GA+bPn69bADt27MCSJUtgsVggCAI2b97sc01VVRVKS0uRnJwMq9WKXbt2hfWsvXv3wu12o6SkZJhRE4283t5eHD9+HAcOHMCpU6fQ2toqJ0HqhALwTTqUKzqVCYd0Xkpw1OfU5w0Gg1dSIp3zV8ejfKu+l79YpFiHikV93mQyISsrCyUlJTj77LNx1llnMQkiooBCToR+9KMfoaqqSrcAenp6MGPGDL/3fP7551FZWYn77rsP+/btw4wZM7Bo0SI0NTXJ18ycORPnnnuuz5+Ghgb5mtbWVtx88834wx/+oFvsRCPB7XajsbERNTU1OHLkCGw2G3p7ezUTDomUkPgbbQH0S46kqSrlfZSjOf42NQ01OQoUiyAISE1NRUFBASZNmoRp06ahoKCA3aGJaEgh7zXm8XjwjW98A4cPH0ZZWZnPpqsvvvhi+MEIAl566SVcddVV8jGr1Yo5c+bg8ccfl59fUlKC22+/Hffcc09Q9x0YGMBll12GlStX4qabbhry2oGBAfn9zs5OlJSUsI8QRUV3d7dcC6RujAgELnAGhu4NpLxWuQpMPdWkx/lI7DcGsDEiEWmL2F5jP/zhD7F9+3YsWLAAOTk5ES2Qdjqd2Lt3L1avXi0fMxgMKC8vx86dO4O6hyiKWLFiBS699NIhkyAAWLt2Le6///6wYybSg8vlQmNjI+rr69Hc3Iyenh6v0Zt4W/6uvI9yFGrcuHHIzs6GxWJBYWEhGyMSUchCToT+8pe/4B//+Ae+8Y1vRCIeLw6HA263G/n5+V7H8/PzcfDgwaDu8cEHH+D555/HeeedJ9cfPfPMM5g+fbrm9atXr0ZlZaX8vjQiRDQSRPF0Y8Ta2lo0Njaira0Ng4ODfhsjDlU4LF0TzpYakVz+rl7hpT6vFavyOUlJSXJjxAkTJiAzMzOi/ygjorEr5EQoOzsbZ555ZiRiiYivfOUrIXXDTkpKQlJSUgQjItI23MaIQ51XCpRwjMTyd39TY8pY1LEKwunGiOPGjfPaHkM9PU9EFIqQJ9J//vOf47777kNvb28k4vFiNpthNBrR2NjodbyxsREFBQURfXZVVRXKysowZ86ciD6HSBRFtLW14cCBAzh8+DDq6urQ0dHhtzg4lBVeyvPqpMbfCi+JVsG18p7SvfRajeZv5EgURRiNRiQlJSE3NxdnnHEGysrKMGHCBCZBRDRsIY8IPfroozh27Bjy8/NRWlrq84No3759ugWXmJiIWbNmYdu2bXIBtcfjwbZt2/CDH/xAt+doWbVqFVatWiUXWxFFQn9/PxoaGmCz2eBwONDX1+eTGMTCaIxkpPcbA8DGiEQUUSH/NFGu6NJDd3c3jh49Kr9/4sQJfPLJJ8jOzsaECRNQWVmJiooKzJ49G3PnzsX69evR09ODW265Rdc4iEZSoMaIgPZUVaCEA9A3OQq24Fp5H71rigwGA5KTk5GVlYWCggJYLBb2BCIi3YWUCLlcLgiCgFtvvRXFxcW6BLBnzx4sWLBAfl8qVK6oqMCGDRtw/fXXo7m5GWvWrIHdbsfMmTPx+uuv+xRQE40Wvb298ihQS0sL+vr65CQg0GiMMqkIZjRGfV55jZ7Jkfq6oWIJJjkymUxIT0+H2WxGcXGxPE1ORKS3kPsIpaWl4V//+hdKS0sjFFJsqKqqQlVVFdxuNw4fPsw+QjRsbrcbzc3NqKurQ3NzM7q6uuR/XCiTG3/JkHRe2RtIoi6IVt9LndyEc16riNpfnyL1iJbWs5SxSomWwWBASkoKsrOz5e0xUlNTh/nKE1E8CraPUMiJ0De/+U0sW7YMFRUVww5yNAj2hSQKpKurSx4F8tcYUXqrlZBEohnhcJMjrVikWAM1cdSKFfiyMWJeXh6Ki4uRnZ3NxohEFLaINVRcvHgx7rnnHvzrX//CrFmzfDYvXbp0aejREo1RLpcLdrsdDQ0NaG5ulpfES0ItHJZICU2gmiLlvWKh4Fp6qy64lhojSkvi2RiRiEZSyCNCgf6FJgiC11LasYAjQhQOUQy+MeJIjMaEO1U1nFiHGsUCIDdGzM3NRUlJCRsjEpFuIjYiFEpzwtFMWSNEFAqpMWJ9fT1aWlp8GiMCo2f5u/q8ViyBYlVSJlcJCQnyKFBRUREKCgrYE4iIoiLkESGl/v7+MT+EzREhCpYoimhvb8epU6fQ3NyM9vZ2eUl8LNXxRCsWUTzdGDExMRFZWVnIz89HcXEx0tLSOApERLoL9vd3yJWIbrcbv/jFL1BUVITx48fj+PHjAICf/exn+POf/xx+xESjWH9/P06cOIGamhp88cUXcDgcGBwc1ByNUY6qKkeGAP+dmiXKj1d/rNZ55X20Ro78JT+BYlGeDyUWqRi6pKQEU6ZMwZQpU5Cens4kiIiiKuRE6IEHHsCGDRvw0EMPITExUT5+7rnn4k9/+pOuwRHFOo/HA4fDgQMHDuDIkSOw2Wzo6emRp8L8bWOhrp3RSo6UIzbhbKmhPq+u7/M3bab3lhrSkvj8/HxMmjQJ06ZNQ1FREbtDE1FMCPkn0caNG/GHP/wBCxcuxPe//335+IwZM4LeEZ5oLOjt7UV9fT1sNhtaW1vl7TG06njC6dSs5wov5TOU9450TREbIxJRrAs5Eaqvr8fkyZN9jns8HgwODuoSVCxgsTT5E6gxYqDCYqVAyZHWajC9kyOt5/kruFbGrF6Npo5Deo4gCF6NEYuLi5GSkhLuS05EFDEhJ0JlZWV47733MHHiRK/jmzZtwvnnn69bYNHGTVdJS1dXlzwK1N7ejv7+fp9EJ1BCMtQKr1jqDRTMKJZy+k46r2yMWFJSgqysLDZGJKKYFXIitGbNGlRUVKC+vh4ejwcvvvgiDh06hI0bN+LVV1+NRIxEUeevMaIeCUcsL38PJjmSEjVBELwaI1osFiQlJQ33pSciiqiwls+/9957+O///m/s378f3d3duOCCC7BmzRpcfvnlkYgxqrh8Pr6JoojOzk7U1dXBbrfLS+IjveQ8FrfU0Lq/dFxqjChtj8HGiEQUbRHbayzeMBGKX06nE3a7HfX19XA4HOjt7YXb7Q6YEEhvgzk/2pMjURRhMpnYGJGIYlLE+ghNmjQJLS0tPsfb29sxadKkUG9HFHNEUURraysOHDiAw4cPo76+3mePMHVCMhLL37UKrrWm1fRe/u4vltTUVOTm5uKMM85AWVkZiouLmQQR0agTco3QF198obmSamBgAPX19boEFQu4aiw+9ff3y8XQLS0t6Ovr80kuorX8XZ2sqFd/SddEuqYoISEBaWlpMJvNKCoqQl5eHnsCEdGoFfRPr1deeUX++xtvvOG1ksrtdmPbtm0oLS3VNbho4qqx+OLxeNDa2ora2lo0NTWhq6sLTqcTAHxWbQFDFw5HeoWX1vJ3f8mRMmbp45UjSVqjQlqxGAwGJCcnIysrS14SP27cOB1efSKi6Ak6EbrqqqsAnP6hWVFR4XXOZDKhtLQU69at0zU4opHQ29srF0NrNUaU6LHCS7oOiHxyFM7yd62RI2kUiI0RiWgsCjoRkn6onnHGGdi9ezfMZnPEgiIaCeE2RvRXqAz4T46kt7G8/F1rFEsQ2BiRiMa2kCf2T5w4EYk4iEZUoMaI4dbxhDoa428qSjo31FRVuMmROgatUSwASEpKQlpaGhsjEtGYxgpHiitSY8S6ujq0tLT4rAbTczRGKVBypE6ilPfxN1UVyYJro9GI1NRUNkYkorjARIjigiiK6OjoQH19vdwYcWBgIGDhsJS8DDfhCDU5imbBdWJiIhsjElFcYSLkB5fPjx3+GiOqqQuHR/vy91BiNRqNGD9+PMxmMywWCxsjElHcYGfpIbCz9OgliqK8JL65uRkdHR0YHByUz2t1alYXNI/0NhbKWPzFpTymjiWUZ0n3TE5ORmZmJvLz81FcXIy0tDSOAhHRqBfs7++QR4T27dsHk8mE6dOnAwBefvllPP300ygrK8PPf/5zJCYmhh81kU78NUZUJwGhjsZI10n30HvkKBIF1/5iYWNEIqIwtti47bbbcPjwYQDA8ePHsXz5cqSmpuKFF17A3XffrXuARKHweDxoampCTU0Njh49CpvNhp6eHng8Hp+tI6S/Sx/nLzlSvlVuY6G8Rj1dpbWNhUT58eqPVZ5XH1fXM4W7pYbBYEBqairy8/MxadIklJWVwWKxMAkiorgU8k++w4cPY+bMmQCAF154AZdccgmqq6vxwQcfYPny5Vi/fr3OIRIFJ5jGiMEWDo/25e/+Cq7ZGJGIyFvIiZDyX7NvvfUWrrzySgBASUkJHA6HvtERBUHdGLGzs1MeBdEabdF7qkp9nfI+oUxVDRWL+v6hFFwLwunGiDk5OXItEBsjEhGFkQjNnj0bv/zlL1FeXo53330XTzzxBIDTjRbz8/N1D5DIH1EU0d3djbq6Orkx4sDAgE9hcCRHY2Jt+bt62kwQBCQmJiIjIwNms5mNEYmIVEJOhNavX48bbrgBmzdvxk9/+lNMnjwZALBp0yZcdNFFugdIpCWYxoiRHo0BQttvTJmcjETBtboxYlFRERczEBGp6LZ8vr+/H0ajccz1HuHy+dgiikM3RozW8nd/U2rA6WLscJe/D3VeHQtwenuMjIwMNkYkorgVseXzANDe3o5Nmzbh2LFjuOuuu5CdnY2amhrk5+ejqKgo7KBjCRsqxh6n04mGhgbYbDY4HA55NZgk0GiMv4QiklNVei5/D7bDNRsjEhGFJuQRoU8//RQLFy5EZmYmvvjiCxw6dAiTJk3Cvffei1OnTmHjxo2RijUqOCIUfR6PB21tbX4bI8bSaMxQ57WaOCr/Hu4oFhsjEhF5C/b3d8gVk5WVlbjllltw5MgRJCcny8evuOIK7NixI7xoifzo6+vDiRMncODAAZw8eRItLS0YHBz0Gs0B4FX8qx7NGao3EOBd9yOdU9fyBNP7Z6jz6iJlf6NYofQGMplMyMzMRElJCaZOnYopU6YgPT2dSRARURBCnhrbvXs3fv/73/scLyoqgt1u1yUoIo/HA4fD4bUkXhoFCqdwONBUldYo0lBTVeEWXCufN9z9xgwGA1JSUpCZmSkXQ48bN25YrzsRUbwJORFKSkpCZ2enz/HDhw8jNzdXl6AovikbI7a0tKC/vz/oxohDnVeSkiPpeCwuf1fGqvwcTCaTvD1GSUkJcnJy2BiRiCgMISdCS5cuxX//93/j73//O4DTP6BPnTqFn/zkJ/jWt76le4AUP9xuNxobG+Vd4rUaIw5nNEZrmiuWl79rjWIJgiAviS8oKIDFYmFjRCKiYQi5WLqjowPXXHMN9uzZg66uLlgsFtjtdsybNw+vvfbamBuaZ7F05Imib2NEp9MJt9sdk8vflXGPRMG19LFsjEhEFLyILZ/PyMjAm2++iQ8++AD79+9Hd3c3LrjgApSXl2suDyYKZHBwEI2NjT6NEZUjMLE2VaW12kt9L3UswS5/1zpvMBgwbtw4uTGixWJhY0QiIp2EnAj95je/wV133YX58+dj/vz58nG3240bb7wRf/vb33QNkMYmUfyyMaLNZkNHR4dXY0RJsIXD/pIj9TV6T1UFU3AdbqImCILcGFFaEp+RkeFT60REROELKxHKzs7Gd77zHfmY2+3G8uXL8dlnn+kaHI1NTqdT7gwtNUZUJz+BmhEqp5KGGo2R+EuOlOeDSY60YolEwTUbIxIRjYyQE6EtW7bg8ssvR0ZGBq655hq4XC5cd911OHjwILZv3x6JGGmMUDdG7OzslEeBJHqPxvibqgq34Fr5vOEsf9eKVapDSkpKQnZ2tjwKNH78eI4CERFFSMiJ0Jw5c/CPf/wDV111FRITE/HnP/8ZR48exfbt27n7PPnV19cnb4/R0tKCvr4+zdGcoRISJX+jMdK5WKkpUp6X3molRyaTCenp6fIoUF5eHhISwtoFh4iIghTWT9lLL70UGzduxLe+9S1MmzYN7777Lsxms96xRRX3GtOHXo0RleeVCctITVXpXVOkxMaIRETRE9Ty+WXLlmke/+ijjzB58mSvJOjFF1/UL7oYwOXz4evp6UFdXR0aGxt9GiNKlKuqgLGx+/tQH6+sVZIaI0q7xOfk5HBJPBGRDnRdPp+RkaF5fNGiReFFR2OaVmNEafl4oBVeQHR2fx+q4Fq6Vzg1RerPVTpmMBjkxoiFhYUoLCxkY0QioigIKhF6+umnIx0HjQGieLoxYm1tLex2u2ZjxGBGY6IxVTUSNUXScakxYm5uLoqLi9kYkYgoisKuxGxubsahQ4cAAFOnTuU+Y3FucHAQdrsd9fX1cmNEqb4qnMLhQCNHoY7GKM/7qymSRLKmiI0RiYhiT8iJUE9PD26//XZs3LhR/gViNBpx880347HHHkNqaqruQVLsEsXTjRGlTVI7OjrQ398fduGwVkG0nqMx0jXBrPBSxxrOKJb0dzZGJCKKTSGPx1dWVuLdd9/F//7v/6K9vR3t7e14+eWX8e677+LHP/5xJGKkGOV0OvHFF1/gwIEDOHHiBBwOB5xOp0/ioU4SJKEkHMqkQ7mST5kcKZ+ldU7rvPI+0nl/I0fKt9J5ZXInPUu5P5rBYEB6ejqKioowdepUTJ06FZmZmUyCiIhiRMibrprNZmzatAlf+9rXvI5v374d1113HZqbm/WML+q4asyXsjFiU1MTurq64HQ65fPBrqoCtGtz/K3wUk9baT1LeV/lKFS4q9HUozzqmiJ/sSgbIxYUFKCoqIiNEYmIRlDENl3t7e3VbJyYl5eH3t7eUG9Ho4xWY0RAO6EAgi9iHu5UVaCaIvV5rVgCxaoUTMG1sjFiUVER8vLyYDQaQ3yliYhoJIScCM2bNw/33XcfNm7ciOTkZACnfznef//9mDdvnu4BUmxwu91oaWmRt8fo6uryaYwI6LvCK1ByJAm2pkiv5e+BkiNpSXxWVhYKCgpQXFzMmjkiohgXciK0fv16fP3rX0dxcTFmzJgBANi/fz+Sk5Pxxhtv6B4gRZ/UGNFms6Gtrc1vY0RA/9GYYAuutabYhrPCK5hYpXtL02BsjEhENPqEXCMEnJ4ee/bZZ3Hw4EEAwLRp03DDDTeMyYZw8Vwj5HK50NTU5NMYEYhep2atJe1adTwjVVNkNBqRkpLCxohERDEmYjVCO3bswEUXXYSVK1d6HXe5XNixYwcuueSS0KOlmCKKIrq6uuQl8crGiOpVU2qRnqqSrhluTZFWrKGMYgmC4NUYsaSkBJmZmRwFIiIaZUJOhBYsWACbzYa8vDyv4x0dHViwYAE3KR3l1I0Ru7q6vLbHUIqFqapQC66lt8EWXGvFomyMaLFYUFhYyMaIRESjVMiJkNYvRABoaWnhjtmjmCiKaG9vR319vWZjREB736yxsPt7sKNYANgYkYhojAk6EZJ2oBcEAStWrEBSUpJ8zu1249NPP8VFF12kf4QUcU6nE/X19bDZbHA4HOjr6/PZzgIYvcvf9Si4NhgMSEtLk5fE5+fnw2Qyhf+iExFRTAg6EZJ2oBdFEWlpaV4FoYmJibjwwgt96oZiQXt7O8rLy+FyueByuXDHHXfEZJzREKgxYqSnqiSRrinyd14dQ6BRLDZGJCIau4JOhKQd6EtLS3HnnXeOmmmwtLQ07NixA6mpqejp6cG5556LZcuWIScnJ9qhRVVfX588DSY1RlQmLrE0GhPp5e9S3Y96FCshIUFujFhcXIzc3Fw2RiQiGmNCrhG6++67vX5hnDx5Ei+99BLKyspw+eWX6xqcHoxGo9zUbmBgwOuXfTxSNkaURoHcbnfUR2MkI11TpH6GdF82RiQiig8hr/X95je/iY0bNwI4Pe00d+5crFu3Dt/85jfxxBNPhBzAjh07sGTJElgsFgiCgM2bN/tcU1VVhdLSUiQnJ8NqtWLXrl0hPaO9vR0zZsxAcXEx7rrrLpjN5pDjHAt6enpw9OhR1NTU4NSpU2hvb4fL5fK6Rl2ro+cGp+prPB6P3I9IHYNSoA1Oh4p1qFiU50VRRGJiInJycjBhwgRMmzYNkydPZhJERDSGhZwI7du3DxdffDEAYNOmTSgoKMDJkyexceNGPProoyEH0NPTgxkzZqCqqkrz/PPPP4/Kykrcd9992LdvH2bMmIFFixahqalJvmbmzJk499xzff40NDQAADIzM7F//36cOHEC1dXVaGxsDDnO0czlcqGhoQGff/45jh07hsbGRvT39wPQXgGmHrmJVHJkMBh8Rmyk0aehaoqk0R/p+uHGYjQaMX78eFgsFkyePBnTpk1Dbm4u+wIREY1xYW26mpaWBgDYunUrli1bBoPBgAsvvBAnT54MOYDFixdj8eLFfs8//PDDWLlyJW655RYAwJNPPoktW7bgqaeewj333AMA+OSTT4J6Vn5+PmbMmIH33nsP11xzjeY1AwMDGBgYkN/v7OwM8jOJPaKo3RhRPbKiNFThcDSmqiT+kiPl8UCr0dTnpT/qxohZWVkshiYiihMh/3N38uTJ2Lx5M2pra/HGG2/IdUFNTU26b0HhdDqxd+9elJeXy8cMBgPKy8uxc+fOoO7R2NiIrq4uAKebPu7YsQNTp071e/3atWuRkZEh/ykpKRneJxElg4ODqK2tRU1NDU6cOIGmpib09/fLozlaiYJWwqO8VjJSU1VaS/iVyZUylqFGsbRiNRqNSEtLg8ViwVlnnYVp06YhOzubSRARURwJORFas2YN7rzzTpSWlsJqtco7zm/duhXnn3++rsE5HA643W7k5+d7Hc/Pz4fdbg/qHidPnsTFF1+MGTNm4OKLL8btt9+O6dOn+71+9erV6OjokP/U1tYO63MYaaIooq2tDQcPHsThw4dRV1eH9vZ2r6QiUEIiUY/mBJqqUiccekxVDZUcqWNQUiZqWsmRIAhISkpCTk4OSktLMW3aNEyYMIHdoYmI4lDIU2PXXHMNvvKVr8Bms8m7zwPAwoULcfXVV+sanB7mzp0b9NQZcLpzsLJZ5GgyMDCAhoYGr8aI0v5g4a7wkhIi6Zpglr8rNzgNtBot0svfle9L56VRoJycHBQVFaGgoAAJCSF/GxAR0RgR1m+AgoICFBQUeB2bO3euLgEpmc1mGI1Gn+LmxsZGn+fHM4/Hg9bWVtTW1qK5udmrMaLBYNB9+XswyVGs1RQJgoCUlBRkZmbKjRGlWjciIopfMb0kJjExEbNmzcK2bdvkYx6PB9u2bZOn5CKlqqoKZWVlmDNnTkSfM1x9fX04fvw4Dhw4gFOnTqG1tRVOp1NOFvSo0/F3fiSWv4c6raZVU5SQkIDMzEwUFxfj7LPPxllnncUkiIiIAIQ5IqSn7u5uHD16VH7/xIkT+OSTT5CdnY0JEyagsrISFRUVmD17NubOnYv169ejp6dHXkUWKatWrcKqVavQ2dkpby8SS4ZqjBhoNEavqSqtqTF/U1US6Tp10bNW4qOV3IQyiiWNAmVlZaGwsBBFRUXsCURERF6ingjt2bMHCxYskN+vrKwEAFRUVGDDhg24/vrr0dzcjDVr1sBut2PmzJl4/fXXfQqo40lPTw/q6upgs9nQ1taG/v5+zWkrIPCqKmD0LH8PJRYAMJlM8pL44uJi5OTksCcQERH5EESt30yEqqoqVFVVwe124/Dhw+jo6NC9PUCoXC4XmpqaUFdXB4fDga6uLjnRCFTDA0CewlKPxvhLjqS3wZxXjvIEc16ddKlHsaS/DxWLMtGSzhuNRqSkpCAnJweFhYWwWCxITk7W4dUnIqLRRJrRGer3NxOhIQT7QkaSKAZujBhKwqH8e7AJh9b5UJOfoe7vL1ELNjkShNONETMzM2E2m9kYkYgozgX7+zvqU2MU2ODgIGw2GxoaGuBwONDd3S2vAtNrhZd0LtI1RerzyhqhYJe/a9U/SRvrms1mFBYWorCwkD2BiIgoKEyEYpQoimhvb0ddXR0aGxvR3t6OgYGBsAuHQ02Ohiq41qumyN9IlTIWiTo5MhqN8vYY0pL4jIwMjgIREVHQmAj5oawRGmkDAwOor6+HzWZDS0sLent7fTpDD3c0BoDX5qehjsYEWuEl3UOv5EgrUUtISJAbI1osFjZGJCKisLBGaAgjWSOkbIwoLYl3Op1B1dloFQ6HU8cTqYLr4dYUSecNBgOSk5PZGJGIiAJijdAo09fXJ48Ctba2oq+vTx5hGSrh0HM0Jpzl78qkKZI1RSaTCenp6TCbzSgqKkJubi6MRuNwXnYiIopzTISizO12w+FwoK6uzqcxokQ5WqK1kioWpqoiWVMkCKcbI2ZnZ8ujQGyMSEREemAiFEXqxogDAwNetUCBRmPUdTyA/9EY5bnhdGrWGpnSikWv5AhgY0QiIoosJkJ+RLJYWhRF2Gw2uTFid3e313NCHY2RzvlLOCI1VRXKCq9QO1wbDAaMGzcO2dnZsFgsKCwsZGNEIiLSHYulhxCJYmmPx4Ndu3ahvr4eg4ODwy5yjmSn5nCLnJWxSH+XYg1UcC0I3o0RJ0yYgMzMTJ9RKCIiokBYLB3jnE4nBgYGwh6NAUb38nc1QWBjRCIiGnlMhKJAnbTotcJLPbUUKDnyNxoTTHKkFUuoNUXK5EhqjJiVlYX8/HwUFxcjLS2No0BERBRxTISiQGsaK1LL3wPV8SjjUU55+aspkrb2GG5NkXJkSmqMKI0CsTEiERGNJP7GiRIp+YmlqapABdd6xiKdT0lJkUeB2BiRiIiigYmQH5HeYkNrCfhITVVpTZsp7xvp3kDKxojFxcUwm81sjEhERFHBVWNDiNSqsffffx/19fWa01ijZYVXqLEaDAY2RiQiohHBVWMxTjlKojUaI50biamqYGuKlImUcrRoqFEsURTlxoh5eXkoLi5GdnY2GyMSEVHUMRGKoliZqlLeI5SaIiWt5Ecq3h43bhxycnLkJfFsjEhERLGCiVAUaC0rl5KPYJe/BzsaMxLL37VGsQRBQFJSEjIzM5Gbm4uSkhI2RiQiopjDRCgKAiUkw1n+rlXHoxwZ0mv5u/pjpPel5CghIUEeBZK2xzCZTMN/4YiIiHTGRChKlKM1IzFVpfe0mfL+UjxsjEhERKMNEyE/Ir18HtB/+btkpGuKDAYDjEaj3BjRYrEgPz+fjRGJiCjmcfn8ECK1fP6DDz5AbW0tgNGz/F0rFoPBgOTkZGRlZclL4sePH6/L60RERBQuLp+PceokJpaXv/sruGZjRCIiGu2YCEXRaFj+roxFOi8IAhsjEhHRmMBEKEoCrfACor/8XXkv5SgTGyMSEdFYwkQoCpSJBaC9/F06Honl76EkR9IUmiAIbIxIRERjDhOhKFAmIf6mqpRFzHpPmynPK5e/a9UUAUBiYiIyMzPlUSA2RiQiorGCiVAMiIXl7+qpMY/HA5PJJI8CFRUVoaCggI0RiYhoTGEiFCXqJfBaU1XK0RmtFV7q++hVUyTtEp+ZmcnGiERENKYxEfIj0g0V1SMwWoXJeu7+Huy0WUJCgtwYsaioCHl5eWyMSEREYxYbKg4hUg0V33//fdTX1wMYunGiepRHq29QMI0RAz1L3RixuLgY48aN0+XzJSIiGmlsqDgKjPTyd62RI2kUiI0RiYgoHjERigJ1oqLn8nfpeDAF1+rGiMXFxUhJSYngZ05ERBRbmAhFgXqaK5LL37UKrgEgKSkJaWlpyMvLQ0lJCbKystgYkYiI4g4ToSgRRRFutzsiy9+lxovqcwBgNBqRmpoqN0a0WCxISkoawc+ciIgodjARihJp9CVSvYG0iqrZGJGIiMgbE6EoCWX5u5Qcqa8JNjkyGo0YP348zGYzLBYLGyMSERH9GxOhGBHMCi+Jv+RIeV65JJ6NEYmIiLQxEYoircaJ4Sx/1xoZYmNEIiKiofE3YxTotfxdq6ZIuT0GGyMSEREFxkQoCtRbZUjJTLDL35XJkXJ6jI0RiYiIQsNEKEqUI0ChLH9XJ0fSsZSUFOTk5Mi1QGyMSERENDQmQn5EetNVYOjd4bX2FAPgNRqUmJiI9PR05ObmsjEiERFRiLjp6hAiuelqXV0dAP+brQbajNVgMHg1RiwqKkJiYqIu8REREY123HR1FBlqZEi6RnqblJSEjIwMNkYkIiIaJiZCUSQlOlJNEBsjEhERjSwmQlEU7JYabIxIREQUGUyEokBr1Zd0XJ0cmUwmpKWlITc3FxaLhY0RiYiIdMTfqFGgHMnxt9+YsjGiVAzNxohERET6YiIUQ9gYkYiIaGQxEYoSra7RgiDIS+ILCgpgsVjYGJGIiCiCmAhFiXqbjMTERGRkZMBsNrMxIhER0QhhIhRlRqMR48aNQ3Z2NhsjEhERjTAmQlGibIwoLYnPyMjgkngiIqIRxEQoCgRBQH5+PhITE9kYkYiIKIqYCEWBIAgoLS1FQUEBGyMSERFFEROhKElMTGQtEBERUZRxWRIRERHFrbhJhHp7ezFx4kTceeed0Q6FiIiIYkTcJEIPPPAALrzwwmiHQURERDEkLhKhI0eO4ODBg1i8eHG0QyEiIqIYEvVEaMeOHViyZAksFgsEQcDmzZt9rqmqqkJpaSmSk5NhtVqxa9eukJ5x5513Yu3atTpFTERERGNF1BOhnp4ezJgxA1VVVZrnn3/+eVRWVuK+++7Dvn37MGPGDCxatAhNTU3yNTNnzsS5557r86ehoQEvv/wypkyZgilTpozUp0RERESjhCAqd/6MMkEQ8NJLL+Gqq66Sj1mtVsyZMwePP/44AMDj8aCkpAS333477rnnniHvuXr1avz1r3+F0WhEd3c3BgcH8eMf/xhr1qzRvH5gYAADAwPy+52dnSgpKUFHRwfS09OH9wkSERHRiOjs7ERGRsaQv7+jPiIUiNPpxN69e1FeXi4fMxgMKC8vx86dO4O6x9q1a1FbW4svvvgCv/3tb7Fy5Uq/SZB0fUZGhvynpKRk2J8HERERxaaYToQcDgfcbjfy8/O9jufn58Nut0fkmatXr0ZHR4f8p7a2NiLPISIiouiLq87SK1asGPKapKQkJCUlRT4YIiIiirqYHhEym80wGo1obGz0Ot7Y2IiCgoKIPruqqgplZWWYM2dORJ9DRERE0RPTiVBiYiJmzZqFbdu2ycc8Hg+2bduGefPmRfTZq1atQk1NDXbv3h3R5xAREVH0RH1qrLu7G0ePHpXfP3HiBD755BNkZ2djwoQJqKysREVFBWbPno25c+di/fr16OnpwS233BLFqImIiGgsiHoitGfPHixYsEB+v7KyEgBQUVGBDRs24Prrr0dzczPWrFkDu92OmTNn4vXXX/cpoI4UqbtAZ2fniDyPiIiIhk/6vT1Ul6CY6iMUS6qqqlBVVQWn04ljx45FOxwiIiIKQ21tLYqLi/2eZyI0BI/HgylTpmDv3r0QBCGoj5kzZ86QtUVSo8ba2lo2avy3YF63aBrp+CL1PL3uO5z7hPOxoXxMsNfy+9BXLH8fRiO2SDwzHr4Hg70+kt+Doiiiq6sLFosFBoP/kuioT43FOoPBgMTERGRkZAT9MUajMegvaHp6On8A/1sor1s0jHR8kXqeXvcdzn3C+dhQPibU+/P78Eux/H0Yjdgi8cx4+B4M9fpIfQ8G87s7pleNxYpVq1ZF9Ho6LdZft5GOL1LP0+u+w7lPOB8bysfE+v9LsSyWX7toxBaJZ8bD92C4z4gGTo1FSbB7oBBR5PD7kCi6YuF7kCNCUZKUlIT77ruPXayJoojfh0TRFQvfgxwRIiIiorjFESEiIiKKW0yEiIiIKG4xESIiIqK4xUSIiIiI4hYTISIiIopbTIRGiRMnTmDBggUoKyvD9OnT0dPTE+2QiOJKaWkpzjvvPMycOdNro2giGjm9vb2YOHEi7rzzTt3uyS02RokVK1bgl7/8JS6++GK0tray7wlRFHz44YcYP358tMMgilsPPPAALrzwQl3vyRGhUeDzzz+HyWTCxRdfDADIzs5GQgJzWCIiih9HjhzBwYMHsXjxYl3vy0RIBzt27MCSJUtgsVggCAI2b97sc01VVRVKS0uRnJwMq9WKXbt2BX3/I0eOYPz48ViyZAkuuOACPPjggzpGTzT6Rfp7EAAEQcBXv/pVzJkzB88++6xOkRONDSPxPXjnnXdi7dq1OkX8JQ4r6KCnpwczZszArbfeimXLlvmcf/7551FZWYknn3wSVqsV69evx6JFi3Do0CHk5eUBAGbOnAmXy+XzsVu3boXL5cJ7772HTz75BHl5efj617+OOXPm4LLLLov450Y0GkT6e9BiseD9999HUVERbDYbysvLMX36dJx33nkR/9yIRoNIfw/u3r0bU6ZMwZQpU/Dhhx/qG7xIugIgvvTSS17H5s6dK65atUp+3+12ixaLRVy7dm1Q9/zwww/Fyy+/XH7/oYceEh966CFd4iUaayLxPah25513ik8//fQwoiQauyLxPXjPPfeIxcXF4sSJE8WcnBwxPT1dvP/++3WJl1NjEeZ0OrF3716Ul5fLxwwGA8rLy7Fz586g7jFnzhw0NTWhra0NHo8HO3bswLRp0yIVMtGYosf3YE9PD7q6ugAA3d3dePvtt3HOOedEJF6isUaP78G1a9eitrYWX3zxBX77299i5cqVWLNmjS7xcWoswhwOB9xuN/Lz872O5+fn4+DBg0HdIyEhAQ8++CAuueQSiKKIyy+/HFdeeWUkwiUac/T4HmxsbMTVV18NAHC73Vi5ciXmzJmje6xEY5Ee34ORxERolFi8eLHulfJEFJxJkyZh//790Q6DiHC6nYyeODUWYWazGUajEY2NjV7HGxsbUVBQEKWoiOIHvweJoivWvweZCEVYYmIiZs2ahW3btsnHPB4Ptm3bhnnz5kUxMqL4wO9BouiK9e9BTo3poLu7G0ePHpXfP3HiBD755BNkZ2djwoQJqKysREVFBWbPno25c+di/fr16OnpwS233BLFqInGDn4PEkXXqP4e1GXtWZzbvn27CMDnT0VFhXzNY489Jk6YMEFMTEwU586dK3700UfRC5hojOH3IFF0jebvQUEURTEK+RcRERFR1LFGiIiIiOIWEyEiIiKKW0yEiIiIKG4xESIiIqK4xUSIiIiI4hYTISIiIopbTISIiIgobjERIiIiorjFRIiIiIjiFhMhItJdaWkp1q9fH+0wRtzPf/5zzJw5M+LPuemmm/Dggw9G9BnLly/HunXrIvoMoljARIiI4oIgCNi8eXNEn3HnnXd67bAdCfv378drr72GH/7whxF9zr333osHHngAHR0dEX0OUbQxESIi0sn48eORk5MT0Wc89thjuPbaazF+/PiIPufcc8/FmWeeib/+9a8RfQ5RtDERIhrDPB4PHnroIUyePBlJSUmYMGECHnjgAfn8v/71L1x66aVISUlBTk4Ovve976G7u1s+v2LFClx11VX47W9/i8LCQuTk5GDVqlUYHByUr2lqasKSJUuQkpKCM844A88++6xPHO3t7fjud7+L3NxcpKen49JLL8X+/fvl89KU0jPPPIPS0lJkZGRg+fLl6Orqkq/ZtGkTpk+fLsdaXl6Onp4eAMDu3btx2WWXwWw2IyMjA1/96lexb98++WNLS0sBAFdffTUEQZDfB4CXX34ZF1xwAZKTkzFp0iTcf//9cLlcfl/Td955B3PnzsW4ceOQmZmJ+fPn4+TJk16fh0QQBJ8/ymd/9tlnWLx4McaPH4/8/HzcdNNNcDgcfp/tdruxadMmLFmyxOv4wMAAfvKTn6CkpARJSUmYPHky/vznP8vxCoKAN954A+effz5SUlJw6aWXoqmpCf/3f/+HadOmIT09Hf/xH/+B3t5er/suWbIEzz33nN94iMYCJkJEY9jq1avxq1/9Cj/72c9QU1OD6upq5OfnAwB6enqwaNEiZGVlYffu3XjhhRfw1ltv4Qc/+IHXPbZv345jx45h+/bt+Mtf/oINGzZgw4YN8vkVK1agtrYW27dvx6ZNm/A///M/aGpq8rrHtddeK//i3bt3Ly644AIsXLgQra2t8jXHjh3D5s2b8eqrr+LVV1/Fu+++i1/96lcAAJvNhm9/+9u49dZbceDAAbzzzjtYtmwZRFEEAHR1daGiogLvv/8+PvroI5x11lm44oor5ERq9+7dAICnn34aNptNfv+9997DzTffjDvuuAM1NTX4/e9/jw0bNngli0oulwtXXXUVvvrVr+LTTz/Fzp078b3vfQ+CIGheb7PZ5D9Hjx7F5MmTcckllwA4nRxeeumlOP/887Fnzx68/vrraGxsxHXXXef36/npp5+io6MDs2fP9jp+8803429/+xseffRRHDhwAL///e99Rox+/vOf4/HHH8eHH36I2tpaXHfddVi/fj2qq6uxZcsWbN26FY899pjXx8ydOxe7du3CwMCA35iIRj2RiMakzs5OMSkpSfzjH/+oef4Pf/iDmJWVJXZ3d8vHtmzZIhoMBtFut4uiKIoVFRXixIkTRZfLJV9z7bXXitdff70oiqJ46NAhEYC4a9cu+fyBAwdEAOIjjzwiiqIovvfee2J6errY39/v9fwzzzxT/P3vfy+Koijed999YmpqqtjZ2Smfv+uuu0Sr1SqKoiju3btXBCB+8cUXQX3ubrdbTEtLE//3f/9XPgZAfOmll7yuW7hwofjggw96HXvmmWfEwsJCzfu2tLSIAMR33nlH8/x9990nzpgxw+e4x+MRr776anHWrFlib2+vKIqi+Itf/EK8/PLLva6rra0VAYiHDh3SvP9LL70kGo1G0ePxyMekr8Gbb76p+THbt28XAYhvvfWWfGzt2rUiAPHYsWPysdtuu01ctGiR18fu378/pNedaDRKiFYCRkSRdeDAAQwMDGDhwoV+z8+YMQPjxo2Tj82fPx8ejweHDh2SR47OOeccGI1G+ZrCwkL861//ku+RkJCAWbNmyefPPvtsZGZmyu/v378f3d3dPrUzfX19OHbsmPx+aWkp0tLSvJ4jjSzNmDEDCxcuxPTp07Fo0SJcfvnluOaaa5CVlQUAaGxsxL333ot33nkHTU1NcLvd6O3txalTpwK+Rvv378cHH3zgNQLkdrvR39+P3t5epKamel2fnZ2NFStWYNGiRbjssstQXl6O6667DoWFhQGf8//9f/8fdu7ciT179iAlJUV+9vbt2zVrfY4dO4YpU6b4HO/r60NSUpLXCNQnn3wCo9GIr371qwFjOO+88+S/5+fnIzU1FZMmTfI6tmvXLq+PkWJVT5kRjSVMhIjGKOmX2HCZTCav9wVBgMfjCfrju7u7UVhYiHfeecfnnDJhCvQco9GIN998Ex9++KE8hfPTn/4UH3/8Mc444wxUVFSgpaUFv/vd7zBx4kQkJSVh3rx5cDqdQ8Z2//33Y9myZT7nkpOTNT/m6aefxg9/+EO8/vrreP7553HvvffizTffxIUXXqh5/V//+lc88sgjeOedd1BUVOT17CVLluDXv/61z8f4S6zMZjN6e3vhdDqRmJgIIPivs/L1FQQhqK+rNHWZm5sb1DOIRiPWCBGNUWeddRZSUlL8LueeNm0a9u/fLxccA8AHH3wAg8GAqVOnBvWMs88+Gy6XC3v37pWPHTp0CO3t7fL7F1xwAex2OxISEjB58mSvP2azOejPRxAEzJ8/H/fffz/++c9/IjExES+99JIc9w9/+ENcccUVOOecc5CUlORTdGwymeB2u72OXXDBBTh06JBPXJMnT4bB4P/H4/nnn4/Vq1fjww8/xLnnnovq6mrN63bu3Invfve7+P3vf++TKF1wwQX4/PPPUVpa6vNs5SidklSIXVNTIx+bPn06PB4P3n33Xb/xhuuzzz5DcXFxSF8notGGiRDRGJWcnIyf/OQnuPvuu7Fx40YcO3YMH330kbya6IYbbkBycjIqKirw2WefYfv27bj99ttx0003ydNiQ5k6dSq+/vWv47bbbsPHH3+MvXv34rvf/a7XKEV5eTnmzZuHq666Clu3bsUXX3yBDz/8ED/96U+xZ8+eoJ7z8ccf48EHH8SePXtw6tQpvPjii2hubsa0adMAnE76nnnmGRw4cAAff/wxbrjhBp+RktLSUmzbtg12ux1tbW0AgDVr1mDjxo24//778fnnn+PAgQN47rnncO+992rGceLECaxevRo7d+7EyZMnsXXrVhw5ckSOQ8lut+Pqq6/G8uXLsWjRItjtdtjtdjQ3NwMAVq1ahdbWVnz729/G7t27cezYMbzxxhu45ZZbfBI2SW5uLi644AK8//77Xp9XRUUFbr31VmzevBknTpzAO++8g7///e9BvbaBvPfee7j88suHfR+iWMZEiGgM+9nPfoYf//jHWLNmDaZNm4brr79errtJTU3FG2+8gdbWVsyZMwfXXHMNFi5ciMcffzykZzz99NOwWCz46le/imXLluF73/se8vLy5POCIOC1117DJZdcgltuuQVTpkzB8uXLcfLkyaATrvT0dOzYsQNXXHEFpkyZgnvvvRfr1q3D4sWLAQB//vOf0dbWhgsuuAA33XQTfvjDH3rFAADr1q3Dm2++iZKSEpx//vkAgEWLFuHVV1/F1q1bMWfOHFx44YV45JFHMHHiRM04UlNTcfDgQXzrW9/ClClT8L3vfQ+rVq3Cbbfd5nPtwYMH0djYiL/85S8oLCyU/8yZMwcAYLFY8MEHH8DtduPyyy/H9OnT8f/+3/9DZmZmwNGo7373uz4tCp544glcc801+K//+i+cffbZWLlypddIXzj6+/uxefNmrFy5clj3IYp1gij+e/0pERHFvL6+PkydOhXPP/885s2bF7HnPPHEE3jppZewdevWiD2DKBZwRIiIaBRJSUnBxo0bAzZe1IPJZPLpK0Q0FnFEiIiIiOIWR4SIiIgobjERIiIiorjFRIiIiIjiFhMhIiIiiltMhIiIiChuMREiIiKiuMVEiIiIiOIWEyEiIiKKW0yEiIiIKG79/4tlq1eFcvDwAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for i in range(0, len(Tarr)):\n",
    "    plt.plot(rarr, vfs[i, :], alpha=0.2, color=\"gray\")\n",
    "plt.xscale(\"log\")\n",
    "plt.yscale(\"log\")\n",
    "plt.axhline(Kzz / L, label=\"Kzz/H\", color=\"C2\", ls=\"dotted\")\n",
    "plt.ylabel(\"stokes terminal velocity (cm/s)\")\n",
    "plt.xlabel(\"condensate size (cm)\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Find the intersection."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-10-30T01:22:43.757265Z",
     "iopub.status.busy": "2022-10-30T01:22:43.720784Z",
     "iopub.status.idle": "2022-10-30T01:22:43.947705Z",
     "shell.execute_reply": "2022-10-30T01:22:43.947403Z"
    }
   },
   "outputs": [],
   "source": [
    "from exojax.atm.amclouds import find_rw\n",
    "\n",
    "vfind_rw = vmap(find_rw, (None, 0, None), 0)\n",
    "rw = vfind_rw(rarr, vfs, Kzz / L)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Then, $r_g$ can be computed from $r_w$ and other quantities."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-10-30T01:22:43.952944Z",
     "iopub.status.busy": "2022-10-30T01:22:43.952655Z",
     "iopub.status.idle": "2022-10-30T01:22:44.123144Z",
     "shell.execute_reply": "2022-10-30T01:22:44.122838Z"
    }
   },
   "outputs": [],
   "source": [
    "from exojax.atm.amclouds import get_rg\n",
    "\n",
    "rg = get_rg(rw, fsed, alphav, sigmag)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-10-30T01:22:44.136701Z",
     "iopub.status.busy": "2022-10-30T01:22:44.136043Z",
     "iopub.status.idle": "2022-10-30T01:22:44.328611Z",
     "shell.execute_reply": "2022-10-30T01:22:44.328316Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f0ef4558df0>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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UKhEeHo7WrVuXWw49Gm+uV8rjvmZmZmL9+vUAgKlTp2r95xERadqpU6cQGBiI7OxsdOrUCRcvXmQRVAo63yKUnZ2NO3fuqB7HxMQgMjISjo6OcHNzQ0hICIYOHQpvb2+0bNkSS5YsQU5ODt5//32tZyvagyo/P1/nFgY0BLm5uQBQbNaDpm3YsEH1F1SnTp209nOIiLTlzTffRK1ateDu7o6dO3fy86iUdL4QunTpEjp27Kh6HBISAgAYOnQoQkNDERwcjJSUFMyaNQuJiYlo0qQJwsLCnhtArQ1mZmawtrZGSkoKzM3NOdNIQyRJQm5uLpKTk2Fvb6+1TU8lSVINJBw7dixXWCUiveTk5IQTJ07Azs4OcrlcdBy9o1frCInwunUI8vPzERMTA6VSKSCdYbO3t0fVqlW1VqAcO3YMnTt3RsWKFfHw4cNXrjNBRKRLNmzYgKdPn2LEiBGio+iskq4jpPMtQrpOLpejbt26yM/PFx3FoJibm2utJahIUWvQ4MGDWQQRkd5YuXKlaouihg0bok2bNoIT6TcWQhpgYmLClaX1TFxcHPbt2wfgWbcYEZE++Omnn1RbAI0dOxatWrUSnEj/cVALGaWVK1dCoVCgffv2r1xpnIhIV3zzzTeqImjy5Mn46aefODZVA3gHyejk5+dj1apVANgaRET6Ye7cuZgyZQoAYObMmVi0aBEneGgIu8bI6OzduxeJiYmoWrUq+vTpIzoOEdErHTt2DDNnzgQAzJkzR/XfpBkshMjo/PzzzwCAESNGaHWNIiIiTejYsSM+/fRTVKpUSdUqRJrD6fOvUdLpd6QfoqOj0ahRI5iamiI2NhY1atQQHYmI6DmSJCE/P597X5ZBST+/OUaIjMry5csBAD179mQRREQ6SZIkfPzxx3jrrbfw5MkT0XEMHrvGyGg8evQIv/76KwDgo48+EpyGiOh5jx49wgcffIC9e/dCJpPh+PHj6N69u+hYBo2FEBmNefPmITMzE56entxXjIh0ztmzZ/Huu+/i/v37kMvlWLVqFYugcsCuMTIKsbGx+OmnnwAACxcu5NobRKQzlEolFixYgPbt2+P+/fuoU6cOIiIiMGTIENHRjAJbhMgozJo1C/n5+ejUqRMCAwNFxyEiUhkxYgTWrl0LAHj33XexfPlyTs4pR/yzmAxefHw8Nm/eDOBZaxAXISMiXTJ16lTUrl0bq1evxqZNm1gElTO2CJHBW7t2LRQKBdq1awdvb2/RcYiIIEmS6o8yDw8P3Lx5E2Zm/EgWgS1CZNAUCgVWrlwJAKrdmomIRMrOzka3bt1w5MgR1TEWQeLwzpNBO3ToEB48eIBKlSqhX79+ouMQkZHLzs5Gjx49cPLkSURFReHu3buwtrYWHcuosUWIDNqKFSsAAMOGDYOlpaXgNERkzP5dBNna2mLfvn0sgnQACyEyWA8ePMDBgwcBACNHjhSchoiM2X+LoCNHjqBly5aiYxFYCJEBW716NZRKJfz8/FCvXj3RcYjISOXk5LAI0mEshMggFRYWYvXq1QCAUaNGCU5DRMbshx9+YBGkwzhYmgzSwYMHER8fDycnJ/Tp00d0HCIyYlOnTkVsbCw++OADFkE6iIUQGaR/D5K2sLAQnIaIjE1GRgbMzMxQoUIFmJmZqZbxIN3DrjEyOFFRUapB0iNGjBCchoiMTWRkJJo3b46PPvoIkiSJjkOvwRYhMjifffYZACA4OJiDpImo3EiShNWrV2P8+PHIy8tDYWEhUlNTUblyZdHR6BXYIkQG5cyZMzhw4ABMTU0xZ84c0XGIyEjk5ORg2LBhGDlyJPLy8tCjRw9cuXKFRZAeYIsQGZQvvvgCADB8+HDUrVtXbBgiMgpZWVkIDAzE2bNnYWJigrlz52Lq1KkwMWFbgz5gIUQG486dOzh69ChkMhlmzJghOg4RGQFJktC/f3+cPXsW9vb22Lt3Lzp06CA6FpUCy1UyGGvWrAEABAQEwN3dXWwYIjIKMpkMU6dOhYuLC44cOcIiSA+xRYgMQkFBAdatWweAM8WIqHx16tQJd+/e5X6GeootQmQQDhw4gKSkJFSpUgVBQUGi4xCRAcvPz8eHH36I69evq46xCNJfLITIIBRtpzFs2DCYm5sLTkNEhqqwsBADBw7EmjVr0K1bN+Tl5YmORGXEQoj0XlxcHA4dOgQA+OCDDwSnISJDpVAoMHToUOzatQtyuRwrVqzgyvUGgIUQ6b3Q0FAolUq0b9+eCygSkVYolUqMGDECmzdvhpmZGXbs2IHAwEDRsUgDWAiRXlMqlarZYh9++KHgNERkiCRJwscff4x169bBxMQEmzdvRs+ePUXHIg1hIUR67fjx44iNjYWtrS369esnOg4RGaClS5di2bJlkMlkWL9+Pfr37y86EmkQCyHSa0U7Or/33nuwtrYWnIaIDNGQIUPQrl07rFixAoMGDRIdhzRMJnFr3FfKzMyEnZ0dMjIyYGtrKzoO/Ut0dDQ8PT0hSRIiIyPh5eUlOhIRGYjk5GQ4OTmptslQKBQwNTUVnIpKo6Sf32wRIr31xRdfQJIk9O3bl0UQEWnMyZMn0bhxY3z99deqYyyCDBcLIdJLUVFR2LlzJ2QyGb788kvRcYjIQCxfvhydO3dGUlISdu/ezXWCjAALIdJLS5YsAQAMGDAAjRo1EhuGiAzCihUrMGbMGNWiiWfOnOE6QUaAhRDpnaysLGzfvh0A8PHHHwtOQ0SGYNOmTRgzZgwA4NNPP8XGjRtRoUIFwamoPLAQIr2zfft25ObmwsPDA61btxYdh4j03N69ezF06FBIkoRx48Zh/vz5kMlkomNROWEhRHpn7dq1AIDhw4fzlxURlVlycjKUSiWGDh2KH374gb9XjAynz78Gp8/rlps3b6J+/fowNTXFgwcPUK1aNdGRiMgAnDhxAu3atYOZmZnoKKQhnD5PBik0NBQAEBgYyCKIiNQWHR2NtLQ01WM/Pz8WQUaKhRDpDYVCgV9//RUA8P777wtOQ0T66tatW+jUqRM6dOiAhIQE0XFIMBZCpDeOHDmC+Ph4VKpUCUFBQaLjEJEeun//Pvz9/ZGcnAy5XM6teYiFEOmPdevWAXi2r5hcLhechoj0TXJyMrp06YIHDx7Aw8MDYWFhsLOzEx2LBGMhRHohPT0de/fuBQAMGzZMaBYi0j/p6ekIDAzErVu34ObmhiNHjqBKlSqiY5EOYCFEemH16tXIz89H48aN0aRJE9FxiEiP3LlzBz4+Prh69SqqVKmCI0eOwNXVVXQs0hEshEjn5eTkYPHixQCATz75hGt8EFGp2Nvbo6CgAG5ubjh69Cjq1asnOhLpEM4VJJ33yy+/ICUlBbVr18agQYNExyEiPSBJkuqPJicnJxw8eBCVKlVidxg9hy1CpNPy8vJUrUEzZ87kOh9E9FqSJGHEiBFYvXq16tibb77JIoheyOALocePH8Pb2xtNmjRBo0aNsGrVKtGRqBR+//13JCcno3r16mwNIqIS+fTTT7FmzRp8/PHHxRZNJHoRg//z2sbGBidPnoS1tTVycnLQqFEj9O3bF5UqVRIdjUpg/fr1AIDBgwfD3NxccBoi0nWLFy9WtSIvXbqUv+vptQy+RcjU1FS1YFZeXh4kSQK3V9MPycnJOHToEABgyJAhgtMQka5bt24dpk6dCgBYuHAhhg8fLjgR6QOdL4ROnjyJoKAguLi4QCaTqdaS+bdly5bB3d0dlpaW8PHxwYULF4o9//jxY3h5eaFGjRqYMmUKnJycyik9lcWWLVtQWFiIFi1a4M033xQdh4h02P79+/Hhhx8CAKZMmaIqiIheR+cLoZycHHh5eWHZsmUvfH7btm0ICQnB7NmzceXKFXh5eSEgIADJycmqc+zt7REVFYWYmBhs3rwZSUlJ5RWfyqBoX7GhQ4cKTkJEuuzGjRsIDg6GUqnEsGHDsHDhQtGRSI/IJD3qJ5LJZNizZw969+6tOubj44MWLVpg6dKlAAClUglXV1eMHz8e06ZNe+4aH330ETp16oS33377hT8jLy8PeXl5qseZmZlwdXVFRkYGbG1tNfuC6KWuXbsGT09PmJubIyEhgf38RPRSkiRh6tSp+Pvvv7Fnzx7OLiUAzz6/7ezsXvv5rfMtQq+Sn5+Py5cvw9/fX3XMxMQE/v7+iIiIAAAkJSUhKysLAJCRkYGTJ0/Cw8PjpdecP38+7OzsVF9cfVSMotagt956i0UQEb2STCbD4sWLsXv3bhZBVGp6XQilpqZCoVDA2dm52HFnZ2ckJiYCAO7duwdfX194eXnB19cX48ePh6en50uvOX36dGRkZKi+Hjx4oNXXQM9TKBTYtGkTgGezxYiI/islJQWffPIJnj59qjrGmaWkDoMvnVu2bInIyMgSn29hYQELCwvtBaLXOnbsGOLj4+Ho6IgePXqIjkNEOiY7Oxvdu3fHpUuXkJaWpmpBJlKHXrcIOTk5wdTU9LnBz0lJSahataqgVFRWRb/U3nnnHcjlcsFpiEiX5Ofno1+/frh06RKcnJwwc+ZM0ZFIz+l1ISSXy9G8eXOEh4erjimVSoSHh6N169YCk5G6srOzsXv3bgDsFiOi4pRKJYYPH47Dhw/D2toaBw4c4AaqVGY63zWWnZ2NO3fuqB7HxMQgMjISjo6OcHNzQ0hICIYOHQpvb2+0bNkSS5YsQU5ODt5//32BqUlde/bsQW5uLurWrQsfHx/RcYhIh3z66afYtGkTzMzMsGvXLrRs2VJ0JDIAOl8IXbp0CR07dlQ9DgkJAfBsbZnQ0FAEBwcjJSUFs2bNQmJiIpo0aYKwsLDnBlCTftiwYQMAYNCgQaqdo4mIfvnlF3zzzTcAgLVr1yIwMFBwIjIUerWOkAglXYeAyu727dvw8PCAJEm4c+cO3njjDdGRiEhHREVFoW3btpg1axZXjaYSKennt863CJHxWLBgASRJQo8ePVgEEREkSVK1DHt5eeHKlSuoW7eu4FRkaPR6sDQZjvv376tmi3322WeC0xCRaPfu3YOPj49qcVwAqFevHrvMSeNYCJFO+P7771FYWIhOnTpxxh+RkYuJiUHr1q1x8eJFjB49GkqlUnQkMmAshEi4goICbNy4EQAwadIkwWmISKS0tDR069YNCQkJaNCgAX777TeYmPCjirSHY4RIuCNHjiA1NRVVqlRB165dRcchIkGePHmCoKAg3Lx5E66urjh8+DCqV68uOhYZOJbZJFxRa9A777zDDROJjJRCocB7772HiIgI2Nvb49ChQyyCqFywECKhsrOzsW/fPgDAe++9JzgNEYmybNky7NmzB3K5HPv27UPDhg1FRyIjwT+/Sai9e/ciNzcXderUQYsWLUTHISJBRo4ciTNnzqBfv35o37696DhkRFgIkVCbNm0C8Kw1iNNiiYyXpaUltm7dyt8DVO7YNUbCJCcn48iRIwCAgQMHCk5DROXt9OnTmDlzpmp6PIsgEoEtQiTMjh07oFAo0Lx5c+4gTWRkbt68iZ49eyI9PR1VqlTBxx9/LDoSGSm2CJEwmzdvBsBB0kTGJikpCd26dUN6ejp8fHzw4Ycfio5ERoyFEAnxzz//4OzZs5DJZHjnnXdExyGicpKcnIzu3bsjJiYGb7zxBn777TdYW1uLjkVGTK2usby8PJw/fx737t1Dbm4uKleujKZNm6JWrVqazkcG6ocffgAAdOnSBdWqVROchojKw99//60qgipVqoSDBw+icuXKomORkStVIXTmzBn88MMP+O2331BQUAA7OztYWVnh0aNHyMvLQ+3atTFy5EiMHj0aNjY22spMei4tLQ2rV68GAEyePFlwGiIqD0+ePEGnTp2QkJCA2rVr4+DBgxwbSDqhxF1jPXv2RHBwMNzd3XH48GFkZWUhLS0NcXFxyM3Nxe3btzFz5kyEh4ejXr16qtlARP+1dOlS5ObmomnTpvD39xcdh4jKgZWVFZYsWYI2bdrg3Llz8PDwEB2JCAAgkyRJKsmJK1aswPDhw2Fubv7ac69fv46EhAR07ty5zAFFy8zMhJ2dHTIyMmBrays6jt5TKBSoUaMGEhMTsXXrVgQHB4uORERaJElSsWnxSqWSm6hSuSjp53eJ342jRo2Cubk5FAoFTp48icePH7/03AYNGhhEEUSad+LECSQmJsLR0RF9+vQRHYeItCgqKgotW7bE3bt3VcdYBJGuKfU70tTUFF27dkV6ero28pCB27JlCwDg7bffhlwuF5yGiLQlPj4eb731Fi5duoTp06eLjkP0UmqV5o0aNcI///yj6Sxk4PLz87Fr1y4A4JR5IgOWk5ODoKAgxMXFoX79+lixYoXoSEQvpVYh9PXXX2Py5Mn4/fffkZCQgMzMzGJfRC9y+PBhPH78GNWqVeOmikQGSqFQYODAgbhy5QoqV66MAwcOwMHBQXQsopdSax2h7t27A3g2k+zfg+CKBsUpFArNpCODUtQtNmDAAJiamgpOQ0TaMGXKFOzfvx8WFhbYt28fateuLToS0SupVQgdP35c0znIwOXm5mLfvn0A2C1GZKhCQ0Px/fffAwDWr1+P1q1bC05E9HpqFUIdOnTQdA4ycAcOHEBOTg5q1qwJHx8f0XGISAu6desGHx8fBAUFcWkM0htl2n0+NzcX9+/fR35+frHjjRs3LlMoMjzbtm0D8Kw16N/dqURkOJydnfHnn39yRijpFbUKoZSUFLz//vs4dOjQC5/nGCH6t8zMTBw4cAAAu8WIDE1ycjJOnDiBAQMGAAAsLCwEJyIqHbVmjU2cOBGPHz/G+fPnYWVlhbCwMKxfvx5169bF/v37NZ2R9NyOHTvw9OlT1KtXD15eXqLjEJGG3L9/H35+fggODsaPP/4oOg6RWtRqETp27Bj27dsHb29vmJiYoGbNmujSpQtsbW0xf/589OjRQ9M5SU9JkqQaPPnhhx+yW4zIQPzvf/9Dt27dEB8fj+rVqyMwMFB0JCK1qNUilJOTgypVqgAAHBwckJKSAgDw9PTElStXNJeO9N4ff/yB6Oho2NjYYOTIkaLjEJEGHDt2DL6+voiPj0fDhg0RERHBneRJb6lVCHl4eODmzZsAAC8vL6xYsQIPHz7E8uXLUa1aNY0GJP327bffAgBGjBgBOzs7wWmIqKzCwsIQGBiIzMxMtG/fHqdOnYKrq6voWERqK/Hu8/+2ceNGFBYWYtiwYbh8+TICAwPx6NEjyOVyhIaGGtS0Se4+r76HDx/C1dUVkiQhJiYG7u7uoiMRURk8fPgQDRo0QGZmJvr164eNGzfC0tJSdCyiFyrp57daY4QGDRqk+u/mzZvj3r17+Pvvv+Hm5gYnJyd1LkkGaNeuXZAkCW3atGERRGQAXFxc8OWXX2L//v3YvHkzp8mTQVCra+zfJEmClZUVmjVrxiKIiilaO8iQWgiJjJlMJsPEiRNx5MgRFkFkMNQuhNasWYNGjRrB0tISlpaWaNSoEVavXq3JbKTH4uLicPbsWchkMvTr1090HCJSkyRJWLZsGTIyMlTHuFcgGRK1CqFZs2ZhwoQJCAoKwo4dO7Bjxw4EBQXhk08+waxZszSdkfTQzp07AQBt27ZF9erVBachInX9+OOPGDduHNq1a/fcLgJEhkCtMUK//PILVq1ahXfffVd1rGfPnmjcuDHGjx+Pr776SmMBST9t374dAFSrzRKR/vnjjz8QEhICABg+fDi7w8ggqdUiVFBQAG9v7+eON2/eHIWFhWUORfotLi4OERER7BYj0mM3b95EcHAwlEolhg8fjokTJ4qORKQVahVCgwcPxi+//PLc8ZUrV+K9994rcyjSb//uFnNxcRGchohKKz09HUFBQcjIyEC7du3w888/c1V4Mlgl7horah4Fns0cWL16NQ4fPoxWrVoBAM6fP4/79+9jyJAhmk9JemXHjh0AgP79+wtOQkSlVVhYiODgYNy+fRtubm7YtWsXN1Ilg1biQujq1avFHjdv3hwAcPfuXQCAk5MTnJycEB0drcF4pG8ePnyIs2fPAgC7xYj0UFxcHG7cuAFra2vs379ftZ0SkaEqcSF0/PhxbeYgA7Fr1y4AnC1GpK/c3d1x8eJFREdHw8vLS3QcIq1Ta9YY0cuwW4xIP+Xl5am6wKpWrYqqVasKTkRUPko8WHr06NGIi4sr0bnbtm3Dpk2b1A5F+ik+Ph5nzpwBAPTt21dwGiIqqbi4ONSvX5+/t8kolbhFqHLlymjYsCHatm2LoKAgeHt7w8XFBZaWlkhPT8f169dx+vRpbN26FS4uLli5cqU2c5MO2rJlCyRJgo+PD3ejJtITsbGx6NKlC2JjY7Fo0SIMGDAA5ubmomMRlZtS7T6flJSE1atXY+vWrbh+/Xqx52xsbODv748PP/wQgYGBGg8qCnefLxmFQoE6deogNjYWK1aswMiRI0VHIqLXuHbtGgICAhAfHw93d3ccP36cGySTwSjp53epCqF/S09Px/379/HkyRM4OTnhjTfeMMh1JlgIlcyePXvQt29fODo64sGDB7C2thYdiYhe4dy5c+jevTvS09PRsGFDHD58mOt+kUEp6ee32oOlHRwc4ODgoO63k4H58ccfAQAjR45kEUSk4y5evIjOnTsjNzcXrVq1woEDB+Do6Cg6FpEQau8+T1Tk4cOHOHHiBABgzJgxYsMQ0Wtt2bIFubm56Ny5M44cOcIiiIwap89Tme3ZswcA0KpVK7i5uQlOQ0Sv8+233+LNN99EcHAwKlasKDoOkVAshKjMihZR5ErSRLpNkiTIZDLIZDKMGDFCdBwincCuMSqTlJQUnDx5EgALISJdtnr1avTt2xdZWVmioxDpFLULocLCQhw9ehQrVqxQ/cOKj49Hdna2xsKR7tu/fz+USiWaNm2KWrVqiY5DRC9w7tw5jB07Fnv37sWGDRtExyHSKWp1jd27dw+BgYG4f/8+8vLy0KVLF9jY2GDhwoXIy8vD8uXLNZ2TdNTu3bsBsDWISFclJiaiX79+yM/PR9++fTmhgeg/1GoRmjBhAry9vZGeng4rKyvV8T59+iA8PFxj4Ui3ZWRk4OjRowBYCBHpovz8fPTv3x/x8fF48803ERoaapDrvRGVhVqF0KlTpzBz5kzI5fJix93d3fHw4UONBNOkPn36wMHBAW+//bboKAblwIEDyM/PR/369VG/fn3RcYjoPyZNmoTTp0/D1tYWe/fuhY2NjehIRDpHrUJIqVRCoVA8dzwuLk4n/6FNmDABv/76q+gYBofdYkS6a/369Vi6dCkAYNOmTahXr57gRES6Sa1CqGvXrliyZInqsUwmQ3Z2NmbPno3u3btrKpvG+Pn56WSBps9yc3Nx6NAhAM9a3IhIt3h4eMDFxQWzZ8/GW2+9JToOkc5SqxD65ptvcObMGTRo0ABPnz7FwIEDVd1iCxcu1GjAkydPIigoCC4uLpDJZNi7d+9z5yxbtgzu7u6wtLSEj48PLly4oNEM9Lzt27cjNzcX7u7uaNasmeg4RPQfrVq1QlRUFGbNmiU6CpFOU2vWmKurK6KiorBt2zZERUUhOzsbH3zwAd57771ig6c1IScnB15eXhg+fDj69u373PPbtm1DSEgIli9fDh8fHyxZsgQBAQG4efMmqlSpUuqfl5eXh7y8PNXjzMzMMuU3RJIk4aeffgIAjB49moMviXTEgQMHYGZmhoCAAACAk5OT4EREekAqpfz8fKl27drS9evXS/utZQZA2rNnT7FjLVu2lMaOHat6rFAoJBcXF2n+/PnFzjt+/LjUr1+/1/6M2bNnSwCe+8rIyNDIazAEEREREgDJwsJCSklJER2HiCRJ2rFjh2RmZiZZWVlJkZGRouMQCZeRkVGiz+9Sd42Zm5vj6dOnmqzF1Jafn4/Lly/D399fdczExAT+/v6IiIhQ65rTp09HRkaG6uvBgweaimswVq5cCQB49913+RcnkQ44e/Ys3n33XRQWFqJ3795o0KCB6EhEekOtMUJjx47FwoULUVhYqOk8pZKamgqFQgFnZ+dix52dnZGYmKh67O/vj/79++PgwYOoUaPGK4skCwsL2NraFvui/1NYWIj9+/cDAIYMGSI4DRElJSWhf//+KCwsRL9+/bBhwwaYm5uLjkWkN9QaI3Tx4kWEh4fj8OHD8PT0RIUKFYo9XzStWlcULfpHZXf69GmkpaWhUqVK8PX1FR2HyKgVFhbinXfeQXx8POrXr49169bB1NRUdCwivaJWIWRvb68Ta8c4OTnB1NQUSUlJxY4nJSWhatWqglIZtqJZe0FBQTAzU+vtQ0QaMmPGDJw4cQIVK1bE7t27uUwIkRrU+iRbt26dpnOoRS6Xo3nz5ggPD0fv3r0BPFvsMTw8HOPGjRMbzgBJkqQqhIruNxGJoVAoEBMTA+DZ7+Q333xTcCIi/aTzf9JnZ2fjzp07qscxMTGIjIyEo6Mj3NzcEBISgqFDh8Lb2xstW7bEkiVLkJOTg/fff19gasMUFRWFe/fuwcrKCl26dBEdh8iomZqaYvv27fjzzz/h5+cnOg6R3lKrEKpVq9Yr1475559/1A70X5cuXULHjh1Vj0NCQgAAQ4cORWhoKIKDg5GSkoJZs2YhMTERTZo0QVhY2HMDqKnsilqDAgICYG1tLTYMkZHKz8+Hubk5ZDIZZDIZiyCiMlKrEJo4cWKxxwUFBbh69SrCwsIwZcoUTeRS8fPzgyRJrzxn3Lhx7AorB0WFUK9evcQGITJSkiRh+PDhKCgowOrVqzkmiEgD1CqEJkyY8MLjy5Ytw6VLl8oUiHRTbGwsoqKiYGJigqCgINFxiIzSihUrsGnTJpiammLChAlo06aN6EhEek+tdYReplu3bti1a5cmL0k6Yt++fQAAX19fVKpUSXAaIuNz6dIl1R+h8+fPZxFEpCEaLYR27twJR0dHTV6SdMTOnTsBcLYYkQg3b95Er169kJ+fj969e2Py5MmiIxEZDLW6xpo2bVpssLQkSUhMTERKSgp+/vlnjYUj3XD9+nWcPn0apqamePvtt0XHITIqN27cQKdOnZCYmIiGDRti3bp13OiYSIPUKoT+2ypgYmKCypUrw8/PD/Xr19dELtIhy5cvB/BsEcUaNWoITkNkPBQKBXr37o3ExEQ0btwYR48ehb29vehYRAZFJr1uSpaRy8zMhJ2dHTIyMoxy37GcnBy4uLggMzMTf/zxB7p27So6EpFROX/+PKZNm4adO3dyfB5RKZT081utMUJXrlzBX3/9pXq8b98+9O7dGzNmzEB+fr46lyQd9ccffyAzMxO1atWCv7+/6DhERsfHxwfHjh1jEUSkJWoVQqNGjcKtW7cAPFs8MTg4GNbW1tixYwemTp2q0YAkVtFO83369IGJiUbH1hPRS3z++ee4fPmy6jHHBBFpj1qfbLdu3UKTJk0AADt27ECHDh2wefNmhIaGcvq8AVEoFPj9998BAD179hSchsg4hIaG4uuvv4avry8SExNFxyEyeGoVQpIkQalUAgCOHj2K7t27AwBcXV2RmpqquXQkVEREBNLS0uDg4IC2bduKjkNk8KKjo/HRRx8BeLazfNWqVQUnIjJ8ahVC3t7e+Prrr7Fhwwb8+eef6NGjB4BnG6Jyjy/DUdQt1r17d5iZ6fz+vER6LTs7G/3798eTJ0/QtWtXzJgxQ3QkIqOgViG0ZMkSXLlyBePGjcNnn32GOnXqAHi26B5XOzUcRYUQu8WItEuSJHz00Ue4ceMGXFxcsGHDBo7JIyonGp0+//TpU5iamsLc3FxTlxTOWKfP37p1Cx4eHjAzM0Nqairs7OxERyIyWOvWrcPw4cNhYmKC48ePo3379qIjEek9rU6ff/DgAeLi4lSPL1y4gIkTJ+LXX381qCLImP32228AgA4dOrAIItIiSZJw8OBBAMCcOXNYBBGVM7UKoYEDB+L48eMAgMTERHTp0gUXLlzAZ599hq+++kqjAUmMokKI3WJE2iWTybBt2zZs3rwZ06ZNEx2HyOioVQhdu3YNLVu2BABs374djRo1wtmzZ7Fp0yaEhoZqMh8JkJ6ejtOnTwN4tq0GEWmXiYkJ3n33XY4LIhJArX91BQUFsLCwAPBs+nxRq0H9+vWRkJCguXQkxKFDh6BQKNCwYUPUqlVLdBwig7RhwwYMHz4cOTk5oqMQGTW1CqGGDRti+fLlOHXqFI4cOYLAwEAAQHx8PJeBNwBFiyiyNYhIO/7++2+MGTMG69atw7p160THITJqahVCCxcuxIoVK+Dn54d3330XXl5eAJ5Nty7qMiP9VFBQgEOHDgFgIUSkDU+ePMGAAQOQk5ODTp06YcyYMaIjERk1tVbJ8/PzQ2pqKjIzM+Hg4KA6PnLkSFhbW2ssHJW/kydP4vHjx3BycoKPj4/oOEQGpaCgAIMGDcJff/2FKlWqYOPGjTA1NRUdi8ioqT0yT5IkXL58GStWrEBWVhYAQC6XsxDSc2vWrAEA9OvXj7+giTSosLAQgwYNwu7duyGXy7FlyxZUq1ZNdCwio6dWi9C9e/cQGBiI+/fvIy8vD126dIGNjQ0WLlyIvLw8LF++XNM5qRykpqaqNs0dOXKk4DREhmX8+PHYvn07zM3NsXv3bnTq1El0JCKCmi1CEyZMgLe3N9LT02FlZaU63qdPH4SHh2ssHJWvDRs2ID8/H82aNUOzZs1ExyEyKMOHD0eVKlWwY8cO1f6MRCSeWi1Cp06dwtmzZyGXy4sdd3d3x8OHDzUSjMrfzp07ATz7hU1EmtWiRQvcvXsXFStWFB2FiP5FrRYhpVIJhULx3PG4uDjY2NiUORSVv9TUVERERADgatJEmnLnzh3cuHFD9ZhFEJHuUasQ6tq1K5YsWaJ6LJPJkJ2djdmzZ6N79+6aykblKCwsDJIkoXHjxnB1dRUdh0jv5eXlITg4GN7e3qq9xIhI96jVNfbNN98gMDAQDRo0wNOnTzFw4EDcvn0bTk5O2LJli6YzUjk4cOAAAHDsApGGzJgxA1euXIGjo6NqrTUi0j0ySZIkdb6xsLAQ27ZtQ1RUFLKzs9GsWTO89957xQZPG4LMzEzY2dkhIyMDtra2ouNoRWFhISpXrozHjx/jzJkzaNOmjehIRHotLCwM3bp1AwDs27eP3c1EApT087vULUIFBQWoX78+fv/9d7z33nt47733yhSUxIuIiMDjx4/h6OjIRRSJyigxMRFDhw4FAIwbN45FEJGOK/UYIXNzczx9+lQbWUiQom6xwMBALqJIVAZKpRJDhw5FcnIyPD09sXjxYtGRiOg11BosPXbsWCxcuBCFhYWazkMCFA3k5PggorLZvHkzDh8+DEtLS2zZsgWWlpaiIxHRa6g1WPrixYsIDw/H4cOH4enpiQoVKhR7fvfu3RoJR9r34MED/PXXXzAxMUFAQIDoOER67Z133sHt27dRvXp1NGzYUHQcIioBtQohe3t79OvXT9NZSICineZbtWqFSpUqCU5DpN/MzMzw5Zdfio5BRKWgViG0bt06TecgQbZv3w6A3WJE6srNzcW8efMwc+ZMdoUR6aFSjRFSKpVYuHAh2rZtixYtWmDatGl48uSJtrKRlsXExCA8PBwymYyz/4jUkJeXhz59+mDu3Ln8N0Skp0pVCM2dOxczZsxAxYoVUb16dfzwww8YO3astrKRloWGhgIAOnfujJo1a4oNQ6RnCgoKEBwcjMOHD6NChQqYNGmS6EhEpIZSFUK//vorfv75Z/zxxx/Yu3cvfvvtN2zatAlKpVJb+UhLJEnCr7/+CoCbrBKpY/r06di3bx8sLCywb98+LkRKpKdKtbK0hYUF7ty5U2wvKktLS9y5cwc1atTQSkDRDHVl6ejoaDRq1AgWFhZ49OgRrK2tRUci0htHjx5Fly5dAAC7du1C3759BSciov8q6ed3qVqECgsLnxsMaG5ujoKCAvVSkjBFs8X8/PxYBBGVQlpammrl6NGjR7MIItJzpZo1JkkShg0bBgsLC9Wxp0+fYvTo0cXWEuI6QrqvqBAq2g+JiErm1q1byMvLg4eHB7799lvRcYiojEpVCBX9FfRvgwYN0lgYKh/Z2dk4deoUABZCRKXVunVr/PXXX0hPT2drKpEBKFUhxPWDDMOxY8dQUFCA2rVro27duqLjEOmdatWqoVq1aqJjEJEGqLXXGOm3om6xwMBAyGQywWmIdF9hYSF69uyJPXv2iI5CRBrGQsjISJKEsLAwAM8KISJ6vfnz5+O3337DsGHDkJaWJjoOEWkQCyEjc+vWLcTGxkIul6Njx46i4xDpvIsXL6r2D1u2bBn35CMyMCyEjExRa5Cvry8qVqwoOA2RbsvJycGgQYOgUCgwYMAAbqNBZIBYCBmZgwcPAmC3GNHrKJVKjBo1Crdu3UL16tXxyy+/cEwdkQFiIWREEhIScPToUQBAz549Bach0l2SJCEkJASbNm2Cqakp1q9fD0dHR9GxiEgLWAgZkaJ94Vq3bo169eqJjkOk04q6jkNDQ9G5c2fBaYhIW0q1jhDpL0mSsH79egDAsGHDxIYh0nEymQxff/01+vXrh6ZNm4qOQ0RaxBYhI3H79m1cu3YNcrkcAwYMEB2HSCclJiaisLBQ9ZhFEJHhYyFkJP744w8AQLt27WBvby82DJEOys/PR/fu3eHr64vY2FjRcYionLBrzEgUFUIBAQGCkxDppjlz5uDq1auoVKkSLC0tRcchonJiFC1Cffr0gYODA95++23RUYTIy8vDiRMnAABdu3YVG4ZIB50/fx7z5s0DACxfvhxVq1YVnIiIyotRFEITJkzAr7/+KjqGMGfPnkVOTg6cnZ3RuHFj0XGIdEpubi6GDBkCpVKJgQMHGu0fTETGyigKIT8/P9jY2IiOIUxRt1jXrl1hYmIU/8uJSmzGjBm4desWXFxcsHTpUtFxiKicCf9UPHnyJIKCguDi4gKZTIa9e/c+d86yZcvg7u4OS0tL+Pj44MKFC+UfVI/9uxAiov9z4sQJ/PDDDwCANWvWwMHBQXAiIipvwgdL5+TkwMvLC8OHD0ffvn2fe37btm0ICQnB8uXL4ePjgyVLliAgIAA3b95ElSpVAABNmjQpNuW1yOHDh+Hi4lKqPHl5ecjLy1M9zszMLOUr0i3JycmIjIwEAHTp0kVsGCIdU6VKFTRv3hzNmzfntjNERkp4IdStWzd069btpc9/9913GDFiBN5//30AzwYyHjhwAGvXrsW0adMAQPVBrwnz589X7TRtCIq21GjSpAmcnZ0FpyHSLQ0aNEBERAQKCgpERyEiQYR3jb1Kfn4+Ll++DH9/f9UxExMT+Pv7IyIiQis/c/r06cjIyFB9PXjwQCs/p7wcPnwYALvFiP4tNzdX9d/m5uawtrYWmIaIRNLpQig1NRUKheK5lgxnZ2ckJiaW+Dr+/v7o378/Dh48iBo1aryyiLKwsICtrW2xL30lSZKqEGK3GNEz6enpePPNN/HZZ58hPz9fdBwiEkynCyFNOXr0KFJSUpCbm4u4uDi0bt1adKRyER0djYSEBFhZWaFdu3ai4xDphAkTJuD+/fvYsWPHC8cWEpFx0elCyMnJCaampkhKSip2PCkpiQuelcCRI0cAAB06dOBKuUQA9u3bhw0bNsDExATr169nlxgR6XYhJJfL0bx5c4SHh6uOKZVKhIeHG02rTlmEhYUBYLcYEQDExMRgxIgRAIBJkybxdwgRAdCBWWPZ2dm4c+eO6nFMTAwiIyPh6OgINzc3hISEYOjQofD29kbLli2xZMkS5OTkqGaR0YslJyerCsi33npLcBoisVJTUxEYGIiUlBR4eXnhq6++Eh2JiHSE8ELo0qVL6Nixo+pxSEgIAGDo0KEIDQ1FcHAwUlJSMGvWLCQmJqJJkyYICwvjVPDX2LZtGxQKBVq0aIF69eqJjkMkjFKpRK9evXDr1i24ubnh4MGD7ComIhXhhZCfnx8kSXrlOePGjcO4cePKKZFh2LhxIwBg0KBBgpMQiWViYoLx48fjn3/+QVhYWKkXWSUiwyaTXleFGLnMzEzY2dkhIyNDb6bSx8fHo3r16pDJZEhISGDrGRGerR3EwdFExqOkn986PVia1FM0NqhZs2YsgshoJSQkID09XfWYRRARvQgLIQNUtK0GZ4uRsZIkCUOHDkXDhg3x559/io5DRDpM+Bgh0ixJklSF0L+3JiEyJmvXrsWRI0dgaWnJNceI6JXYImRgbty4gfj4eFhaWqJt27ai4xCVu4cPH6pmn86ZMwceHh6CExGRLmMhZGCKWoN8fX05RZiMjiRJGDVqFDIzM+Hj44NPPvlEdCQi0nEshAxMUSHUuXNnwUmIyt+mTZtw4MAByOVyrF27FqampqIjEZGOYyFkQAoLC3HixAkALITI+CQlJWHChAkAgFmzZqFBgwaCExGRPuBgaQNy8eJFZGVlwcHBAU2bNhUdh6hcyeVyvPXWW/jrr78wdepU0XGISE+wEDIgResHdezYkV0CZHQcHBywfv16ZGdnw9zcXHQcItIT7BozIAcOHADAafNkXO7fv4/CwkLV44oVKwpMQ0T6hoWQgYiJicG5c+dgYmKC3r17i45DVC7i4+PRrl079OrVC9nZ2aLjEJEeYteYgdi6dSuAZ5vYVqtWTXAaIu3Lzs5GUFAQHjx4AGtra+Tn54uORER6iC1CBmLbtm0AgIEDBwpOQlQ+Ro0ahStXrqBy5co4ePAgHB0dRUciIj3EQsgAJCUlISoqCgDQq1cvwWmItO/333/H5s2bYWJigj179qB27dqiIxGRnmIhZACOHz8OAGjSpAmcnJwEpyHSrszMTIwZMwYAEBISwq1kiKhMWAgZgKJp81xEkYzBjBkzEBcXhzfeeANffvml6DhEpOdYCBmAY8eOAXi2fhCRoRs8eDA8PT2xcuVKWFtbi45DRHpOJkmSJDqELsvMzISdnR0yMjJga2srOs5zYmNjUatWLZiamiI9PR02NjaiIxFpnUKh4KKhRPRKJf38ZouQnisaH9SyZUsWQWTQMjIyVP/NIoiINIWFkJ5jtxgZgxs3bsDNzQ1z586FUqkUHYeIDAgLIT0mSZKqRahTp06C0xBph1KpxIgRI5CZmYmIiAjIZDLRkYjIgLAQ0mO3b9/Gw4cPIZfL0aZNG9FxiLRi1apVOHPmDCpWrIiff/6ZhRARaRQLIT1W1C3WunVrWFlZCU5DpHl3797F1KlTAQBz586Fm5ub4EREZGhYCOmxPXv2AAC6du0qOAmR5mVkZCAoKAiZmZlo1aoVxo4dKzoSERkgFkJ6KjU1VbWQYv/+/QWnIdIspVKJd955Bzdu3ED16tWxa9cuzhQjIq1gIaSndu/eDYVCgaZNm6Ju3bqi4xBplImJCfr06QM7Ozvs378fLi4uoiMRkYFiIaSn9u3bBwAYMGCA4CRE2jFy5EjExMSgWbNmoqMQkQFjIaSHCgsLcerUKQBAQECA4DREmvP06VM8ffpU9djBwUFgGiIyBiyE9NDVq1eRlZUFe3t7NG7cWHQcIo2ZO3cuPD098eeff4qOQkRGwkx0ACq9EydOAAA6dOjAAaRkMG7cuIGFCxeioKAAaWlpouMQkZFgi5Ae+nchRGQIJEnCmDFjUFBQgLfeegt9+vQRHYmIjAQLIT3z7/FB3F+MDMX69evx559/wtraGkuXLuXq0URUblgI6Zmi8UEODg4cH0QGIS0tDZMnTwYAfPHFF6hZs6bgRERkTFgI6ZmibjFfX1+YmPB/H+m/Tz/9FGlpafD09MTEiRNFxyEiI8NPUj1TVAj5+fkJzUGkCYWFhUhKSgIALF++HObm5oITEZGx4awxPfLv8UEcKE2GwMzMDPv378fVq1e5cCIRCcEWIT0SGRmJrKws2NnZwcvLS3QcIo2QyWQsgohIGBZCeqRokTlfX1+uH0R67f79+xgzZgxSU1NFRyEiI8euMT3C9YPIUEycOBF79uxBfHy8at88IiIR2CKkJxQKBU6fPg2AhRDpt507d2LPnj0wMzPD3LlzRcchIiPHQkhPnDp1Co8fP4ajoyOaNm0qOg6RWq5du4Zhw4YBACZPnoxGjRqJDURERo+FkJ7YuXMnAKBXr14wM2OPJumfR48eoVevXsjJyUHHjh3x1VdfiY5ERMRCSB8olUrs3r0bAPD2228LTkNUegqFAu+++y7++ecfuLu7Y/v27VwziIh0AgshPRAZGYmEhATY2Nigc+fOouMQldq9e/cQHR0Na2tr7N27F05OTqIjEREB4KwxvXDy5EkAQPv27WFhYSE4DVHp1a5dG3///TciIyO5BhYR6RS2COmBfxdCRPqqYsWKaNeunegYRETFsBDScZIkqbbVYCFE+ubixYtYt24dlEql6ChERC/ErjEdd+PGDaSmpsLKyorbEJBeUSgUGDNmDC5fvoy4uDh8/vnnoiMRET2HLUI6rqhbrHXr1pDL5YLTEJXc6tWrcfnyZdjZ2WHkyJGi4xARvRALIR3H8UGkj9LS0jBjxgwAwFdffQVnZ2fBiYiIXoyFkA779/ggX19fwWmISm7mzJl49OgRPD098dFHH4mOQ0T0UiyEdNi9e/cQFxcHMzMztGrVSnQcohK5cuUKVqxYAQBYunQpV0InIp1m8IXQ48eP4e3tjSZNmqBRo0ZYtWqV6EglVtQt1rx5c1hbWwtOQ/R6kiRh/PjxkCQJAwcOZJcuEek8g/9TzcbGBidPnoS1tTVycnLQqFEj9O3bF5UqVRId7bWOHz8OgN1ipD9kMhkWL16M6dOnY9GiRaLjEBG9lsEXQqampqrWlLy8PEiSBEmSBKd6vcLCQvz2228AgO7duwtOQ1Rybdq0wZ9//ik6BhFRiQjvGjt58iSCgoLg4uICmUyGvXv3PnfOsmXL4O7uDktLS/j4+ODChQul+hmPHz+Gl5cXatSogSlTpujFPkenT59GWloaKlWqxBYh0nn379/H+fPnRccgIio14YVQTk4OvLy8sGzZshc+v23bNoSEhGD27Nm4cuUKvLy8EBAQgOTkZNU5ReN//vsVHx8PALC3t0dUVBRiYmKwefNmJCUlvTRPXl4eMjMzi32JUFQQ9uzZk4NNSacplUoEBwfD19cXu3btEh2HiKhUhH/CduvWDd26dXvp89999x1GjBiB999/HwCwfPlyHDhwAGvXrsW0adMAPNudvSScnZ3h5eWFU6dO4e23337hOfPnz8eXX35ZuhehBUXjg3r06CE4CdGrrVu3DufOnYOtrS28vb1FxyEiKhXhLUKvkp+fj8uXL8Pf3191zMTEBP7+/oiIiCjRNZKSkpCVlQUAyMjIwMmTJ+Hh4fHS86dPn46MjAzV14MHD8r2ItTw+PFj/PXXXwDATSpJpz1+/BjTp08HAMyePRs1a9YUnIiIqHSEtwi9SmpqKhQKxXOr0jo7O+Pvv/8u0TXu3buHkSNHqgZJjx8/Hp6eni8938LCAhYWFmXKXVZnz56FJEmoW7cuV+QlnfbVV18hJSUF9evXx7hx40THISIqNZ0uhDShZcuWJe460xWnT58GwNYg0m03btzATz/9BABYsmQJ98IjIr2k011jTk5OMDU1fW5wc1JSEqpWrSoolfaxECJdJ0kSPvnkExQWFiIoKAgBAQGiIxERqUWnCyG5XI7mzZsjPDxcdUypVCI8PBytW7cWmEx78vLyVMsDsBAiXSVJEjp37gwnJyd8++23ouMQEalNeNdYdnY27ty5o3ocExODyMhIODo6ws3NDSEhIRg6dCi8vb3RsmVLLFmyBDk5OapZZIbmypUryMvLQ+XKlVG3bl3RcYheyMTEBFOmTMG4ceNgZWUlOg4RkdqEF0KXLl1Cx44dVY9DQkIAAEOHDkVoaCiCg4ORkpKCWbNmITExEU2aNEFYWJjBDiIu6hZr27YtZDKZ4DREr8YiiIj0nfCuMT8/P9WMrn9/hYaGqs4ZN24c7t27h7y8PJw/fx4+Pj7iAmsZxweRLktOTkabNm1w5MgR0VGIiDRCeCFE/0eSJJw9exbAsxYhIl0zbdo0REREYPr06VAqlaLjEBGVGQshHXLlyhWkpqaiQoUKaNasmeg4RMVs3rwZ69atA/BsuryJCX99EJH+428yHbJv3z4AQGBgINdkIZ1y48YNjBw5EgDw2WefseuWiAwGCyEdUlQI9ezZU3ASov+Tk5OD/v37IycnBx07dtSJvfiIiDSFhZCOePjwIf73v//BxMSEG62STpkzZw6io6NRrVo1bN68GaampqIjERFpDAshHXHmzBkAgJeXFypVqiQ4DdEzkiTh1q1bAIDly5cb9IruRGSchK8jRM8UzRZr06aN4CRE/0cmk2H37t04d+6cQS9bQUTGi4WQjihqEeK0edJFrVq1Eh2BiEgr2DWmA3JycnD16lUAbBEi3aBUKjFv3rznNjwmIjI0LIR0wKVLl6BQKFC9enW4ubmJjkOELVu24LPPPkPz5s2Rn58vOg4RkdawENIB/x4fxP3FSLQnT55g2rRpAICxY8dyTSsiMmgshHRAUSHUunVrwUmIgO+++w5xcXFwc3PDxIkTRcchItIqFkKCSZKEiIgIABwfROIlJiZiwYIFAID58+dzd3kiMngshAS7ffs20tLSYGFhgaZNm4qOQ0Zu9uzZyM7ORosWLfDOO++IjkNEpHUshAQr6hbz9vbmWAwSKjo6GqtXrwbwrHuMm6oSkTHgOkKCsVuMdEXVqlUxfvx4JCUlcVNVIjIaLIQE40Bp0hWVKlXCkiVLIEmS6ChEROWGbd8CZWZmIjo6GgALIRKnoKAABQUFqsdcwoGIjAkLIYGOHTsGSZJQp04dbmZJwnz22Wdo3749YmNjRUchIip37BoT6PfffwcA9OjRQ3ASMlZhYWFYvHgxACAyMhLu7u5iAxERlTO2CAmiVCpx8OBBAMBbb70lOA0Zo4SEBAwZMgQAMG7cOPTu3VtsICIiAVgICXLt2jUkJCSgYsWKaN++veg4ZIQmT56MlJQUeHl5qVqFiIiMDQshQYqmzbdq1YrrB1G5u3z5MjZv3gwAWLt2LSwtLQUnIiISg4WQIEWFEGeLUXmTJAlTp04FAAwaNAjNmjUTnIiISBwWQoKcO3cOwLMWIaLylJ6ejpSUFMjlcsyZM0d0HCIioThrTICnT5+q/tvHx0dgEjJGjo6OuHr1Kq5evcpZYkRk9FgICWBpaYm///4b6enpcHBwEB2HjJCpqSm8vb1FxyAiEo5dYwKxCCIiIhKLhRAREREZLRZCREREZLRYCBEREZHRYiFERERERouFEBERERktFkJERERktFgIERERkdFiIURERERGi4UQERERGS0WQkRERGS0WAgRERGR0WIhREREREaLhRAREREZLTPRAXSdJEkAgMzMTMFJiIiIqKSKPreLPsdfhoXQa2RlZQEAXF1dBSchIiKi0srKyoKdnd1Ln5dJryuVjJxSqUR8fDxsbGwgk8lExxEiMzMTrq6uePDgAWxtbUXH0Xm8XyXHe1VyvFelw/tVcoZ6ryRJQlZWFlxcXGBi8vKRQGwReg0TExPUqFFDdAydYGtra1D/SLSN96vkeK9KjveqdHi/Ss4Q79WrWoKKcLA0ERERGS0WQkRERGS0WAjRa1lYWGD27NmwsLAQHUUv8H6VHO9VyfFelQ7vV8kZ+73iYGkiIiIyWmwRIiIiIqPFQoiIiIiMFgshIiIiMloshIiIiMhosRAyUsuWLYO7uzssLS3h4+ODCxcuvPTc6Oho9OvXD+7u7pDJZFiyZEmZr6lPNH2vvvjiC8hksmJf9evX1+IrKF+luV+rVq2Cr68vHBwc4ODgAH9//+fOlyQJs2bNQrVq1WBlZQV/f3/cvn1b2y+jXGj6Xg0bNuy591ZgYKC2X0a5KM292r17N7y9vWFvb48KFSqgSZMm2LBhQ7FzDPl9BWj+fhnyewsSGZ2tW7dKcrlcWrt2rRQdHS2NGDFCsre3l5KSkl54/oULF6TJkydLW7ZskapWrSp9//33Zb6mvtDGvZo9e7bUsGFDKSEhQfWVkpKi5VdSPkp7vwYOHCgtW7ZMunr1qnTjxg1p2LBhkp2dnRQXF6c6Z8GCBZKdnZ20d+9eKSoqSurZs6dUq1Yt6cmTJ+X1srRCG/dq6NChUmBgYLH31qNHj8rrJWlNae/V8ePHpd27d0vXr1+X7ty5Iy1ZskQyNTWVwsLCVOcY6vtKkrRzvwz1vSVJksRCyAi1bNlSGjt2rOqxQqGQXFxcpPnz57/2e2vWrPnCD/eyXFOXaeNezZ49W/Ly8tJgSt1R1vdBYWGhZGNjI61fv16SJElSKpVS1apVpcWLF6vOefz4sWRhYSFt2bJFs+HLmabvlSQ9+7Dq1auXpqMKp4nfL02bNpVmzpwpSZJhv68kSfP3S5IM970lSZLErjEjk5+fj8uXL8Pf3191zMTEBP7+/oiIiNCZa+oCbb6u27dvw8XFBbVr18Z7772H+/fvlzWucJq4X7m5uSgoKICjoyMAICYmBomJicWuaWdnBx8fH6N/b/33XhU5ceIEqlSpAg8PD4wZMwZpaWkazV7eynqvJElCeHg4bt68ifbt2wMw3PcVoJ37VcTQ3ltFuOmqkUlNTYVCoYCzs3Ox487Ozvj777915pq6QFuvy8fHB6GhofDw8EBCQgK+/PJL+Pr64tq1a7CxsSlrbGE0cb8+/fRTuLi4qH6JJyYmqq7x32sWPaePtHGvACAwMBB9+/ZFrVq1cPfuXcyYMQPdunVDREQETE1NNfoayou69yojIwPVq1dHXl4eTE1N8fPPP6NLly4ADPd9BWjnfgGG+d4qwkKIqJx169ZN9d+NGzeGj48Patasie3bt+ODDz4QmEysBQsWYOvWrThx4gQsLS1Fx9FpL7tX77zzjuq/PT090bhxY7zxxhs4ceIEOnfuLCKqMDY2NoiMjER2djbCw8MREhKC2rVrw8/PT3Q0nfS6+2XI7y12jRkZJycnmJqaIikpqdjxpKQkVK1aVWeuqQvK63XZ29ujXr16uHPnjsauKUJZ7tc333yDBQsW4PDhw2jcuLHqeNH38b31f152r16kdu3acHJy0uv3lrr3ysTEBHXq1EGTJk0wadIkvP3225g/fz4Aw31fAdq5Xy9iCO+tIiyEjIxcLkfz5s0RHh6uOqZUKhEeHo7WrVvrzDV1QXm9ruzsbNy9exfVqlXT2DVFUPd+LVq0CHPmzEFYWBi8vb2LPVerVi1UrVq12DUzMzNx/vx5o3xvvepevUhcXBzS0tL0+r2lqX+HSqUSeXl5AAz3fQVo5369iCG8t1REj9am8rd161bJwsJCCg0Nla5fvy6NHDlSsre3lxITEyVJkqTBgwdL06ZNU52fl5cnXb16Vbp69apUrVo1afLkydLVq1el27dvl/ia+kob92rSpEnSiRMnpJiYGOnMmTOSv7+/5OTkJCUnJ5f769O00t6vBQsWSHK5XNq5c2exablZWVnFzrG3t5f27dsn/e9//5N69eplENOcNX2vsrKypMmTJ0sRERFSTEyMdPToUalZs2ZS3bp1padPnwp5jZpS2ns1b9486fDhw9Ldu3el69evS998841kZmYmrVq1SnWOob6vJEnz98uQ31uSxOnzRuunn36S3NzcJLlcLrVs2VI6d+6c6rkOHTpIQ4cOVT2OiYmRADz31aFDhxJfU59p+l4FBwdL1apVk+RyuVS9enUpODhYunPnTjm+Iu0qzf2qWbPmC+/X7NmzVecolUrp888/l5ydnSULCwupc+fO0s2bN8vxFWmPJu9Vbm6u1LVrV6ly5cqSubm5VLNmTWnEiBF6/8dIkdLcq88++0yqU6eOZGlpKTk4OEitW7eWtm7dWux6hvy+kiTN3i9Df2/JJEmSyrcNioiIiEg3cIwQERERGS0WQkRERGS0WAgRERGR0WIhREREREaLhRAREREZLRZCREREZLRYCBEREZHRYiFERERERouFEBERERktFkJERERktFgIEZFeSEtLQ5UqVRAbG1um6/j5+WHixIkayVQW77zzDr799lvRMYiMHvcaIyK9EBISgqysLKxatapM13n06BHMzc1hY2OjoWTquXbtGtq3b4+YmBjY2dkJzUJkzNgiREQ6pbCw8Lljubm5WLNmDT744IMyX9/R0VHtIig/P7/MP79Io0aN8MYbb2Djxo0auyYRlR4LISISJjY2FjKZDNu3b4evry8sLCywf//+5847ePAgLCws0KpVK9UxPz8/jB8/HhMnToSDgwOcnZ2xatUq5OTk4P3334eNjQ3q1KmDQ4cOFbvWv7vGlEolFi1ahDp16sDCwgJubm6YO3dusXPHjRuHiRMnwsnJCQEBAQCAvLw8fPzxx6hSpQosLS3Rrl07XLx4sdj3ffzxx5g6dSocHR1RtWpVfPHFF8+9rqCgIGzdurUst5CIyoiFEBEJExUVBQBYvHgxZs2ahejoaHTu3Pm5806dOoXmzZs/d3z9+vVwcnLChQsXMH78eIwZMwb9+/dHmzZtcOXKFXTt2hWDBw9Gbm7uC3/+9OnTsWDBAnz++ee4fv06Nm/eDGdn5+d+hlwux5kzZ7B8+XIAwNSpU7Fr1y6sX78eV65cQZ06dRAQEIBHjx4V+74KFSrg/PnzWLRoEb766iscOXKk2LVbtmyJCxcuIC8vr3Q3jog0RyIiEuSLL76QKlSoIMXExLzyvF69eknDhw8vdqxDhw5Su3btVI8LCwulChUqSIMHD1YdS0hIkABIERERxb5vwoQJUmZmpmRhYSGtWrXqpT+3Q4cOUtOmTYsdy87OlszNzaVNmzapjuXn50suLi7SokWLXphNkiSpRYsW0qefflrsWFRUlARAio2NfeXrJyLtYYsQEQkTFRWFnj17wt3d/ZXnPXnyBJaWls8db9y4seq/TU1NUalSJXh6eqqOFbXuJCcnP/e9N27cQF5e3gtboP7tvy1Rd+/eRUFBAdq2bas6Zm5ujpYtW+LGjRsvzAYA1apVey6HlZUVALy0xYqItI+FEBEJExkZCT8/v9ee5+TkhPT09OeOm5ubF3ssk8mKHZPJZACejQX6r6Ii5HUqVKhQovNKku2/OYq60ipXrqzWzyCismMhRERCZGZmIjY2Fk2bNn3tuU2bNsX169c1+vPr1q0LKysrhIeHl+r73njjDdWYoSIFBQW4ePEiGjRoUKprXbt2DTVq1ICTk1Opvo+INMdMdAAiMk5RUVEwNTUt1pX1MgEBAZg+fTrS09Ph4OCgkZ9vaWmJTz/9FFOnToVcLkfbtm2RkpKC6OjoV07Tr1ChAsaMGYMpU6bA0dERbm5uWLRoEXJzc0s9vf/UqVPo2rVrWV8KEZUBCyEiEiIqKgoeHh4vHPvzX56enmjWrBm2b9+OUaNGaSzD559/DjMzM8yaNQvx8fGoVq0aRo8e/drvW7BgAZRKJQYPHoysrCx4e3vjjz/+KFWR9vTpU+zduxdhYWFleQlEVEZcWZqI9MKBAwcwZcoUXLt2DSYm+t+r/8svv2DPnj04fPiw6ChERo0tQkSkF3r06IHbt2/j4cOHcHV1FR2nzMzNzfHTTz+JjkFk9NgiREREREZL/9uXiYiIiNTEQoiIiIiMFgshIiIiMloshIiIiMhosRAiIiIio8VCiIiIiIwWCyEiIiIyWiyEiIiIyGixECIiIiKj9f8AvXcpSD0KSO0AAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(rg * 1.e4, Parr, label=\"$r=r_g$\", color=\"black\")\n",
    "plt.plot(rw * 1.e4, Parr, ls=\"dashed\", label=\"$r=r_w$\", color=\"black\")\n",
    "#plt.ylim(1.e-7, 10000)\n",
    "plt.xlabel(\"$r$ (micron)\")\n",
    "plt.ylabel(\"Pressure (bar)\")\n",
    "plt.yscale(\"log\")\n",
    "plt.savefig(\"rgrw.png\")\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "These processes can be reprodced using `AmpAmcloud`, which uses `PdbCloud` as one of the input arguments. Here, we show an example:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      ".database/particulates/virga/virga.zip  exists. Remove it if you wanna re-download and unzip.\n",
      "Refractive index file found:  .database/particulates/virga/MgSiO3.refrind\n",
      "Miegrid file does not exist at  .database/particulates/virga/miegrid_lognorm_MgSiO3.mg.npz\n",
      "Generate miegrid file using pdb.generate_miegrid if you use Mie scattering\n",
      ".database/particulates/virga/virga.zip  exists. Remove it if you wanna re-download and unzip.\n",
      "Refractive index file found:  .database/particulates/virga/Fe.refrind\n",
      "Miegrid file does not exist at  .database/particulates/virga/miegrid_lognorm_Fe.mg.npz\n",
      "Generate miegrid file using pdb.generate_miegrid if you use Mie scattering\n"
     ]
    }
   ],
   "source": [
    "from exojax.atm.atmphys import AmpAmcloud\n",
    "from exojax.spec.pardb import PdbCloud\n",
    "pdb_enstatite = PdbCloud(\"MgSiO3\")\n",
    "pdb_Fe = PdbCloud(\"Fe\")\n",
    "\n",
    "amp = AmpAmcloud(pdb_enstatite,bkgatm=\"H2\")\n",
    "rg, MMRc = amp.calc_ammodel(Parr,Tarr,mu,MMRc_enstatite,gravity,fsed,sigmag,Kzz,MMRbase_enstatite,alphav=alphav)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We found here the particle size is basically sub-micron.  \n",
    "Here, we try to use the geometric cross section instead though this is sometimes wrong, depending on the wavelength. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-10-30T01:22:44.331940Z",
     "iopub.status.busy": "2022-10-30T01:22:44.331117Z",
     "iopub.status.idle": "2022-10-30T01:22:44.366173Z",
     "shell.execute_reply": "2022-10-30T01:22:44.365907Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/kawahara/exojax/src/exojax/spec/dtau_mmwl.py:13: FutureWarning: dtau_mmwl might be removed in future.\n",
      "  warnings.warn(\"dtau_mmwl might be removed in future.\", FutureWarning)\n"
     ]
    }
   ],
   "source": [
    "from exojax.spec.layeropacity import layer_optical_depth_cloudgeo\n",
    "\n",
    "dtau_enstatite = layer_optical_depth_cloudgeo(Parr, deltac_enstatite, MMRc_enstatite, rg, sigmag, g)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The Mie scattering can be computed using `OpaMie`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/kawahara/exojax/src/exojax/utils/grids.py:144: UserWarning: Resolution may be too small. R=907.6757560767178\n",
      "  warnings.warn(\"Resolution may be too small. R=\" + str(resolution), UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "xsmode =  lpf\n",
      "xsmode assumes ESLOG in wavenumber space: xsmode=lpf\n",
      "======================================================================\n",
      "The wavenumber grid should be in ascending order.\n",
      "The users can specify the order of the wavelength grid by themselves.\n",
      "Your wavelength grid is in ***  descending  *** order\n",
      "======================================================================\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 63/63 [00:25<00:00,  2.45it/s]\n"
     ]
    }
   ],
   "source": [
    "from exojax.utils.grids import wavenumber_grid\n",
    "from exojax.spec.unitconvert import wav2nu\n",
    "\n",
    "N = 1000\n",
    "wavelength_start = 5000.0  # AA\n",
    "wavelength_end = 15000.0  # AA\n",
    "\n",
    "\n",
    "margin = 10  # cm-1\n",
    "nus_start = wav2nu(wavelength_end, unit=\"AA\") - margin\n",
    "nus_end = wav2nu(wavelength_start, unit=\"AA\") + margin\n",
    "nugrid, wav, res = wavenumber_grid(nus_start, nus_end, N, xsmode=\"lpf\", unit=\"cm-1\")\n",
    "\n",
    "\n",
    "from exojax.spec.opacont import OpaMie\n",
    "\n",
    "opa_enstatite = OpaMie(pdb_enstatite, nugrid)\n",
    "\n",
    "rg = 1.0e-4  # 0.1um\n",
    "# beta0, betasct, g = opa.mieparams_vector(rg,sigmag) # if you've already generated miegrid\n",
    "beta0, betasct, g = opa_enstatite.mieparams_vector_direct_from_pymiescatt(\n",
    "    rg, sigmag\n",
    ")  # uses direct computation of Mie params using PyMieScatt\n",
    "\n",
    "\n",
    "from exojax.spec.layeropacity import layer_optical_depth_clouds_lognormal\n",
    "\n",
    "dtau_enstatite_mie = layer_optical_depth_clouds_lognormal(\n",
    "    dParr, beta0, deltac_enstatite, MMRc_enstatite, rg, sigmag, gravity\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The difference of the geometric approximation and Mie scattering is a bit."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "ax=fig.add_subplot(111)\n",
    "plt.plot(dtau_enstatite, Parr, color=\"C1\", ls=\"dashed\", label=\"geometric approximation\")\n",
    "plt.plot(np.median(dtau_enstatite_mie,axis=1), Parr, color=\"C3\", label=\"Mie\",alpha=0.5,lw=2)\n",
    "plt.legend()\n",
    "plt.yscale(\"log\")\n",
    "plt.xlabel(\"$d\\\\tau$\")\n",
    "plt.ylabel(\"Pressure (bar)\")\n",
    "#plt.xscale(\"log\")\n",
    "plt.gca().invert_yaxis()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's compare with CIA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-10-30T01:22:44.576729Z",
     "iopub.status.busy": "2022-10-30T01:22:44.576296Z",
     "iopub.status.idle": "2022-10-30T01:22:48.426500Z",
     "shell.execute_reply": "2022-10-30T01:22:48.426186Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "H2-H2\n"
     ]
    }
   ],
   "source": [
    "#CIA\n",
    "\n",
    "from exojax.spec import contdb\n",
    "cdbH2H2 = contdb.CdbCIA('.database/H2-H2_2011.cia', nugrid)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-10-30T01:22:48.434436Z",
     "iopub.status.busy": "2022-10-30T01:22:48.433956Z",
     "iopub.status.idle": "2022-10-30T01:22:49.096682Z",
     "shell.execute_reply": "2022-10-30T01:22:49.095464Z"
    }
   },
   "outputs": [],
   "source": [
    "from exojax.spec.layeropacity import layer_optical_depth_CIA\n",
    "from exojax.atm.atmconvert import mmr_to_vmr\n",
    "\n",
    "mmrH2 = 0.74\n",
    "molmassH2 = molmass_isotope(\"H2\")\n",
    "vmrH2 = mmr_to_vmr(mmrH2, mu, molmassH2)\n",
    "dtaucH2H2 = layer_optical_depth_CIA(\n",
    "    nugrid,\n",
    "    Tarr,\n",
    "    Parr,\n",
    "    dParr,\n",
    "    vmrH2,\n",
    "    vmrH2,\n",
    "    mu,\n",
    "    gravity,\n",
    "    cdbH2H2.nucia,\n",
    "    cdbH2H2.tcia,\n",
    "    cdbH2H2.logac,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-10-30T01:22:49.105862Z",
     "iopub.status.busy": "2022-10-30T01:22:49.104211Z",
     "iopub.status.idle": "2022-10-30T01:22:49.111118Z",
     "shell.execute_reply": "2022-10-30T01:22:49.109930Z"
    }
   },
   "outputs": [],
   "source": [
    "dtau = dtaucH2H2 + dtau_enstatite_mie\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-10-30T01:22:49.121247Z",
     "iopub.status.busy": "2022-10-30T01:22:49.119405Z",
     "iopub.status.idle": "2022-10-30T01:22:49.833268Z",
     "shell.execute_reply": "2022-10-30T01:22:49.832974Z"
    }
   },
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<Figure size 2000x300 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from exojax.plot.atmplot import plotcf\n",
    "\n",
    "plotcf(nugrid, dtau, Tarr, Parr, dParr, unit=\"AA\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-10-30T01:22:49.836239Z",
     "iopub.status.busy": "2022-10-30T01:22:49.835783Z",
     "iopub.status.idle": "2022-10-30T01:22:50.073322Z",
     "shell.execute_reply": "2022-10-30T01:22:50.073030Z"
    }
   },
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 2000x300 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from exojax.plot.atmplot import plotcf\n",
    "\n",
    "plotcf(nugrid, dtaucH2H2, Tarr, Parr, dParr, unit=\"AA\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-10-30T01:22:50.079246Z",
     "iopub.status.busy": "2022-10-30T01:22:50.078958Z",
     "iopub.status.idle": "2022-10-30T01:22:50.397120Z",
     "shell.execute_reply": "2022-10-30T01:22:50.396828Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2000x300 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from exojax.plot.atmplot import plotcf\n",
    "\n",
    "plotcf(nugrid,\n",
    "       dtau_enstatite_mie,\n",
    "       Tarr,\n",
    "       Parr,\n",
    "       dParr,\n",
    "       unit=\"AA\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-10-30T01:22:50.402987Z",
     "iopub.status.busy": "2022-10-30T01:22:50.399894Z",
     "iopub.status.idle": "2022-10-30T01:22:50.732775Z",
     "shell.execute_reply": "2022-10-30T01:22:50.732473Z"
    }
   },
   "outputs": [],
   "source": [
    "from exojax.spec import planck\n",
    "from exojax.spec.rtransfer import rtrun_emis_pureabs_fbased2st as rtrun\n",
    "#from exojax.spec.rtransfer import rtrun_emis_pureabs_ibased as rtrun\n",
    "sourcef = planck.piBarr(Tarr, nugrid)\n",
    "F0 = rtrun(dtau, sourcef)\n",
    "F0CIA = rtrun(dtaucH2H2, sourcef)\n",
    "F0cl = rtrun(dtau_enstatite[:, None] + np.zeros_like(dtaucH2H2), sourcef)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this case, the effect of clouds and CIA are comparable with each other"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-10-30T01:22:50.743739Z",
     "iopub.status.busy": "2022-10-30T01:22:50.737339Z",
     "iopub.status.idle": "2022-10-30T01:22:50.878863Z",
     "shell.execute_reply": "2022-10-30T01:22:50.878533Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(wav, F0, label=\"Clouds+CIA\")\n",
    "plt.plot(wav, F0CIA, label=\"CIA only\", ls=\"dashed\")\n",
    "plt.plot(wav, F0cl, label=\"Clouds only\", ls=\"dotted\")\n",
    "plt.xlabel(\"wavelenght AA\")\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3.8.8 ('base')",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.19"
  },
  "vscode": {
   "interpreter": {
    "hash": "72bc7f8b1808a6f5ada3c6a20601509b8b1843160436d276d47f2ba819b3753b"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}