{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Transition Model 2D Airfoil\n", "\n", "This notebook sets up, runs, and post-processes a steady Flow360 simulation of a 2D airfoil with a transition model.\n", "\n", "![NLF AIRFOIL](figures/NLF_airfoil.png)\n", "\n", "**Note:** The settings in this example are by no means a validation setup; they are crafted to showcase the capabilities of Flow360 and we have intentionally reduced node count and example FC cost. For rigorous validation, modify the settings as needed." ], "id": "0e0f2c2d" }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 1. Create Project from Volume Mesh\n", "\n", "We initialize a Flow360 project by uploading an existing CGNS volume mesh, which becomes the `VolumeMesh` for this simulation." ], "id": "c1282a65" }, { "cell_type": "code", "metadata": {}, "source": [ "import flow360 as fl\n", "from flow360.examples import NLFAirfoil2D\n", "\n", "NLFAirfoil2D.get_files()\n", "\n", "project = fl.Project.from_volume_mesh(\n", " NLFAirfoil2D.mesh_filename, name=\"Transition Model 2D Airfoil\"\n", ")\n", "vm = project.volume_mesh" ], "execution_count": 1, "outputs": [ { "output_type": "display_data", "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "cb9ca740fba9432695f8f2feef1b24a3", "version_major": 2, "version_minor": 0 }, "text/plain": [ "Output()" ] }, "metadata": {} }, { "output_type": "display_data", "data": { "text/html": [ "
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[21:19:25] INFO: VolumeMesh successfully submitted:                                                                \n",
       "                   type        = Volume Mesh                                                                       \n",
       "                   name        = Transition Model 2D Airfoil from Python                                           \n",
       "                   id          = vm-b259b45a-653b-404b-afb4-8195ebbd026f                                           \n",
       "                   status      = uploaded                                                                          \n",
       "                   project id  = prj-df6618e1-487a-4f73-8ffd-da7a776b2953                                          \n",
       "                                                                                                                   \n",
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       "\u001b[2;36m[21:19:25]\u001b[0m\u001b[2;36m \u001b[0m\u001b[36mINFO\u001b[0m: VolumeMesh successfully submitted:                                                                \n",
       "\u001b[2;36m           \u001b[0m        type        = Volume Mesh                                                                       \n",
       "\u001b[2;36m           \u001b[0m        name        = Transition Model 2D Airfoil from Python                                           \n",
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   "id": "bfb8cc4e"
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. Operating Conditions and Time Settings\n",
    "\n",
    "We define the freestream Mach, Reynolds number, temperature, and angle of attack, then choose a steady time-stepping scheme with adaptive CFL for convergence. When using the transition model, more steps are needed to converge the flowfield due to the moving location of the transition location. This is the reason for such high number of steps and the higher `convergence_limiting_factor` of 0.4 which allows faster convergence while still using the adaptive CFL settings."
   ],
   "id": "50af2df2"
  },
  {
   "cell_type": "code",
   "metadata": {},
   "source": [
    "operating_condition = fl.AerospaceCondition.from_mach_reynolds(\n",
    "    mach=0.1,\n",
    "    reynolds_mesh_unit=4e6,\n",
    "    project_length_unit=project.length_unit,\n",
    "    temperature=540.0 * fl.u.R,\n",
    "    alpha=0.0 * fl.u.deg,\n",
    ")\n",
    "\n",
    "time_stepping = fl.Steady(max_steps=20000, CFL=fl.AdaptiveCFL(convergence_limiting_factor=0.4))"
   ],
   "execution_count": 2,
   "outputs": [
    {
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[21:19:47] INFO: Density and viscosity were calculated based on input data, ThermalState will be automatically     \n",
       "           created.                                                                                                \n",
       "
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       "\u001b[2;36m[21:19:47]\u001b[0m\u001b[2;36m \u001b[0m\u001b[36mINFO\u001b[0m: Density and viscosity were calculated based on input data, ThermalState will be automatically     \n",
       "\u001b[2;36m           \u001b[0mcreated.                                                                                                \n"
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   "id": "76881df9"
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. Transition Model\n",
    "\n",
    "We configure the transition model solver, choosing linear solver iterations, tight tolerances, and the critical amplification factor `N_crit` that controls transition onset.\n",
    "The Jacobian and equation evaluation frequencies control how often these operators are rebuilt, balancing robustness against computational cost."
   ],
   "id": "3dee4ca9"
  },
  {
   "cell_type": "code",
   "metadata": {},
   "source": [
    "transition_model_solver = fl.TransitionModelSolver(\n",
    "    linear_solver=fl.LinearSolver(max_iterations=30),\n",
    "    absolute_tolerance=1e-10,\n",
    "    N_crit=7.2,\n",
    "    update_jacobian_frequency=1,\n",
    "    equation_evaluation_frequency=1,\n",
    ")"
   ],
   "execution_count": 3,
   "outputs": [],
   "id": "bfd2d558"
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4. Outputs\n",
    "\n",
    "We request surface and slice outputs so that Flow360 saves pressure, skin-friction, y-plus, and related fields needed for later analysis around the airfoil."
   ],
   "id": "d12c58bf"
  },
  {
   "cell_type": "code",
   "metadata": {},
   "source": [
    "outputs = [\n",
    "    fl.SurfaceOutput(\n",
    "        surfaces=vm[\"Block/Aerofoil\"],\n",
    "        output_format=[\"paraview\", \"tecplot\"],\n",
    "        output_fields=[\"Cp\", \"Cf\", \"yPlus\", \"CfVec\"],\n",
    "    ),\n",
    "    fl.SurfaceSliceOutput(\n",
    "        name=\"surface_slices\",\n",
    "        entities=[fl.Slice(name=\"y\", normal=(0, 1, 0), origin=(0, -0.5, 0) * fl.u.m)],\n",
    "        target_surfaces=vm[\"Block/Aerofoil\"],\n",
    "        output_format=[\"paraview\"],\n",
    "        output_fields=[\"Cp\", \"Cf\", \"yPlus\", \"CfVec\"],\n",
    "    ),\n",
    "]"
   ],
   "execution_count": 4,
   "outputs": [],
   "id": "8bd8eb27"
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5. Define `SimulationParams`\n",
    "\n",
    "We assemble operating conditions, time stepping, boundary condition models, solvers, and outputs into a single `SimulationParams` object used to run the case."
   ],
   "id": "d790dc52"
  },
  {
   "cell_type": "code",
   "metadata": {},
   "source": [
    "with fl.SI_unit_system:\n",
    "\n",
    "    params = fl.SimulationParams(\n",
    "        operating_condition=operating_condition,\n",
    "        time_stepping=time_stepping,\n",
    "        models=[\n",
    "            fl.Wall(\n",
    "                surfaces=vm[\"Block/Aerofoil\"],\n",
    "            ),\n",
    "            fl.Freestream(\n",
    "                surfaces=vm[\"Block/Farfield\"],\n",
    "            ),\n",
    "            fl.SlipWall(entities=[vm[\"Block/Symmetry\"]]),\n",
    "            fl.Fluid(\n",
    "                turbulence_model_solver=fl.SpalartAllmaras(\n",
    "                    absolute_tolerance=1e-10,\n",
    "                    linear_solver=fl.LinearSolver(max_iterations=30),\n",
    "                    update_jacobian_frequency=1,\n",
    "                    equation_evaluation_frequency=1,\n",
    "                ),\n",
    "                navier_stokes_solver=fl.NavierStokesSolver(\n",
    "                    linear_solver=fl.LinearSolver(max_iterations=50),\n",
    "                    absolute_tolerance=1e-12,\n",
    "                    update_jacobian_frequency=4,\n",
    "                    equation_evaluation_frequency=1,\n",
    "                ),\n",
    "                transition_model_solver=transition_model_solver,\n",
    "            ),\n",
    "        ],\n",
    "        outputs=outputs,\n",
    "    )"
   ],
   "execution_count": 5,
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "text/html": [
       "
           INFO: using: SI unit system for unit inference.                                                         \n",
       "
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      ],
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       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0m\u001b[36mINFO\u001b[0m: using: SI unit system for unit inference.                                                         \n"
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     "metadata": {}
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   "id": "2988d248"
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 6. Run Case\n",
    "\n",
    "We submit the configured simulation to Flow360, creating a case on the server that runs using the project, parameters, and models defined above."
   ],
   "id": "7d6a220d"
  },
  {
   "cell_type": "code",
   "metadata": {},
   "source": [
    "case = project.run_case(params=params, name=\"Steady transition\")"
   ],
   "execution_count": 6,
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
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           INFO: Density and viscosity were calculated based on input data, ThermalState will be automatically     \n",
       "           created.                                                                                                \n",
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       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0m\u001b[36mINFO\u001b[0m: Density and viscosity were calculated based on input data, ThermalState will be automatically     \n",
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           INFO: using: SI unit system for unit inference.                                                         \n",
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       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0m\u001b[36mINFO\u001b[0m: using: SI unit system for unit inference.                                                         \n"
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[21:19:49] INFO: Successfully submitted:                                                                           \n",
       "                   type        = Case                                                                              \n",
       "                   name        = Transition Model 2D Airfoil from Python                                           \n",
       "                   id          = case-11767f48-bb81-412f-aec0-70494c03fd78                                         \n",
       "                   status      = pending                                                                           \n",
       "                   project id  = prj-df6618e1-487a-4f73-8ffd-da7a776b2953                                          \n",
       "                                                                                                                   \n",
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       "\u001b[2;36m[21:19:49]\u001b[0m\u001b[2;36m \u001b[0m\u001b[36mINFO\u001b[0m: Successfully submitted:                                                                           \n",
       "\u001b[2;36m           \u001b[0m        type        = Case                                                                              \n",
       "\u001b[2;36m           \u001b[0m        name        = Transition Model 2D Airfoil from Python                                           \n",
       "\u001b[2;36m           \u001b[0m        id          = case-\u001b[93m11767f48-bb81-412f-aec0-70494c03fd78\u001b[0m                                         \n",
       "\u001b[2;36m           \u001b[0m        status      = pending                                                                           \n",
       "\u001b[2;36m           \u001b[0m        project id  = prj-\u001b[93mdf6618e1-487a-4f73-8ffd-da7a776b2953\u001b[0m                                          \n",
       "\u001b[2;36m           \u001b[0m                                                                                                        \n"
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   "id": "87097dbe"
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 7. Post Processing\n",
    "\n",
    "After the case finishes, we download surface data, compute integrated forces, inspect residual histories, and visualize the friction coefficient distribution over the airfoil.\n",
    "\n",
    "Notice that the drag coefficient reaches a pseudo step where it increases again due to more length modelled as turbulent boundary layer. Maybe it wwould be good to run even longer for full convergence but for the sake of this example it is not needed. Finally, from the surface slices, we can plot the friction coefficient. We observe the transition locations both at the pressure and suction sides where the friction coefficient increases significnatly."
   ],
   "id": "601455c8"
  },
  {
   "cell_type": "code",
   "metadata": {},
   "source": [
    "import tempfile\n",
    "import os\n",
    "import tarfile\n",
    "import pyvista as pv\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "\n",
    "def extract_results(results):\n",
    "    with tempfile.TemporaryDirectory() as temp_dir:\n",
    "        destination = os.path.join(temp_dir, \"case_data\")\n",
    "        os.makedirs(destination, exist_ok=True)\n",
    "\n",
    "        results.download(\n",
    "            surface=True,\n",
    "            destination=destination,\n",
    "        )\n",
    "\n",
    "        surfaces_path = os.path.join(destination, \"surfaces.tar.gz\")\n",
    "        with tarfile.open(surfaces_path) as tar:\n",
    "            tar.extractall(path=temp_dir)  # extract directly into temp_dir\n",
    "\n",
    "        mesh_path = os.path.join(temp_dir, \"surface_slice_y.pvtu\")\n",
    "        mesh = pv.read(mesh_path)\n",
    "\n",
    "        x = mesh.points[:, 0]\n",
    "        y = mesh.points[:, 1]\n",
    "        z = mesh.points[:, 2]\n",
    "        cf = mesh.point_data[\"Cf\"]\n",
    "        cp = mesh.point_data[\"Cp\"]\n",
    "\n",
    "        # Sort based on x-direction\n",
    "        sorted_indices = x.argsort()\n",
    "        x = x[sorted_indices]\n",
    "        y = y[sorted_indices]\n",
    "        z = z[sorted_indices]\n",
    "        cf = cf[sorted_indices]\n",
    "        cp = cp[sorted_indices]\n",
    "\n",
    "        return x, y, z, cf, cp\n",
    "\n",
    "\n",
    "case.wait()\n",
    "results = case.results\n",
    "\n",
    "total_forces = results.total_forces.as_dataframe()\n",
    "total_forces_filtered = total_forces[total_forces[\"pseudo_step\"] >= 5000]\n",
    "total_forces_filtered.plot(\"pseudo_step\", [\"CD\"])\n",
    "plt.ylabel(\"Drag Coefficient\")\n",
    "\n",
    "non_linear = results.nonlinear_residuals.as_dataframe()\n",
    "non_linear_filtered = non_linear[non_linear[\"pseudo_step\"] >= 5000]\n",
    "non_linear_filtered.plot(\n",
    "    \"pseudo_step\",\n",
    "    [\"0_cont\", \"1_momx\", \"2_momy\", \"3_momz\", \"4_energ\", \"5_nuHat\"],\n",
    "    logy=True,\n",
    ")\n",
    "plt.ylabel(\"Non-Linear Residual\")\n",
    "\n",
    "# Plot friction coefficient\n",
    "x, y, z, cf, cp = extract_results(results)\n",
    "\n",
    "plt.figure(figsize=(10, 6))\n",
    "plt.scatter(x, cf, label=\"Friction Coefficient\")\n",
    "plt.xlabel(\"Chord Position\")\n",
    "plt.ylabel(\"Friction Coefficient\")"
   ],
   "execution_count": 7,
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[21:33:50] INFO: Saved to /tmp/tmpkjcvuse8/case_data/surfaces.tar.gz                                               \n",
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",
      "text/plain": [
       "
"
      ]
     },
     "metadata": {}
    },
    {
     "output_type": "display_data",
     "data": {
      "image/png": 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",
      "text/plain": [
       "
"
      ]
     },
     "metadata": {}
    },
    {
     "output_type": "display_data",
     "data": {
      "image/png": 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yXBUaHd77+TQ27D2D5Q+GIi7UzyrPS0RE8mXTla/OnTtDpVKhoKCg3uMFBQXw9fVt8hhfX98Wx+v/a8w5gZq9Z9XV1cjNzTX227AJjVaHxdsyhcez4AYROTqNVod/fJNu9ectrdDg2c1HMXPzEa6CERFRi2wafLm4uGDAgAFISkqqfUyr1SIpKQnR0dFNHhMdHV1vPADs3LmzdnxAQAB8fX3rjSkpKcGhQ4eaPScApKWlQalUNllh0R6l5BQir1hsNUvt6YaIAC8Lz4iIyLZWJ51GaYVlUg1FbEvPR+jiH5GQftFmcyAiIvtm87TDOXPm4PHHH8fAgQMRERGBFStWoLS0FE8++SQA4LHHHkOXLl2wbNkyAMCsWbMwbNgwvPPOOxg7diy2bNmCw4cPY8OGDQAAhUKB2bNnY8mSJQgKCqotNe/n54cJEyYAqCnacejQIQwfPhzt27dHcnIyXnjhBUyZMgUdO3a0yc/BWMakEcaPD2ZlLiJyaAnpF7EySSwN25L0q2DjM/KwYlI4X3uJiKgemwdfEydOxOXLl7Fo0SLk5+cjLCwMiYmJtQUzzp07B6Xy1gLd4MGDsXnzZixYsACvvvoqgoKC8N1339X2+AKAuXPnorS0FE899RSKioowdOhQJCYm1vb4cnV1xZYtW/Daa6+hoqICAQEBeOGFF+rtA7N3ommEL8T0QmyI2sKzISKyncSMPDy7+aitp1HPtvR87Dr5I/eCERFRPTbv8yVXorX8LUWj1WHoW7uQX1yO5v4Bfdq74MC8GN55JSKHJdLrsCFXJwWG3+GNnt7tER3YCYP8vXDk7DXkF9/ElRsVOHLuGn45cRnl1VpJ5jjtLn/MH9tHknMREZF9Eo0NbL7yRaZRKRWIHx+M6ZtSoQCaDMAqNDrszMznyhcROSyRdht1RfXwwud/j2p0Uyo6sFPt/09DTVB3MPsq/vXTCRw9X2zWHDfuzcXFonKsmsw0RCKi1s6mBTfIPLEhaqybEg7PNs5Nfr24rArTN6UiMUO6JqNERPZCo9Xh3/tzhcd7tnFqMvBqikqpwJCgzvi/54bi/YfD0c7VvHuV239nMQ4iImLwJXtarQ4l5U3f9dWvhi3elsnyx0TkcNbsOo3im+KrXm89GGrSylNcqBrH4u/F51Mj0b+bp9HH67EkPRERMfiSMf0m85bew3UA8orLkZJTaLV5ERFZmjFN5hUK4P2Hw81KwW64EtbWRWXyuViSnoio9WLwJVPGNlk2pjQ9EZE9M/b17/kRQYgLlW7va1yoGumvjcY4M87JVTAiotaJwZdMGdNkGRAvTU9EZO+Mef3r4O6M50cGST4HlVKBNQ+HcxWMiIiMwuBLpoxZyerg7oyIAC8LzoaIyHqMef1784G+Fq0wqF8FG9vX1+Rz6FfBlm4/LuHMiIjIHjH4kiljVrJY2JiIHEnulVKhcdZqMq9SKrD2kQGYdleAWefZuDcXz33ONEQiIkfG4EumIgK8oPYUC8CulVWx4AYROQSNVocvUs4ZHOfr4YoZI3paYUa3zB8bbHYaIkvSExE5NgZfMqVvsiyKBTeIyBGk5BQiv6TC4LjJEd1t0tCYxTiIiKglDL5kLDZEjRdixDaSs+AGETkC0RtJ/p3dLTyT5rEYBxERNYfBl8zNGBEEX4/mAysFALWnGwtuEJFDEN3vZQ83nKRcBWMxDiIix8DgS+ZUSgVeuy8YCjQurKH/PH58sE3Sb4iIpCS638uebjhJtQrGYhxERI6BwZcDiA1RY92UcPg2KMDh6+mGdVPCrVLti4jI0kT3e00adLvd3XCSoiQ9i3EQEcmfk60nQNKIDVFjRG8ffJaci7OFZeju5Y5Ho/3h4sT4mogcgxz2e7VEX5Leb3smNu7NMekc+jTE8Rl5WDEp3O6CTCIiahmDLweRmJGHxdsykVd86+Lkw305iB8fzJUvInIIctrv1ZL5Y4PRv1tH/OO/x1BaqTHpHNvS87E3ayfefKAvX+OJiGSEyyIOIDEjD9M3pdYLvAAgv7gc0zelIjEjz0YzIyKSRmJGHt77+XSLY+RUYEiKYhxFZVV4hq/xRESywuBL5jRaHRZvy0RTW7D1jy3elslN2kQkW/rXORFyKjAkVTGOl79J52s8EZFMMPiSuZScwkYrXnXpAOQVlyMlp9B6kyIikpCh1zm92TG9ZJmCZ24xjuKb1Xjkw4MMwIiIZIDBl8yJbkAXHUdEZG/kXmhDhL4Yx7S7Akw6/uCZQlZCJCKSAQZfMie6sdzeN6ATETWnNb3OzR8bbHIaor4S4szN7AdGRGSvGHzJ3IDuHeHV1qXFMXLZgE5E1JRrpYZ7eznS65y5xTi2pbMfGBGRvWLwJWOJGXkYtnw3CksrWxx3Xz+1bDagExHVpdHq8Pr2PwyOWzhWPoU2RNQtxuHmbPxbNVfBiIjsE4MvmWquvHxTth7L45svEcmSaLGNjgYyAOQqLlSN9PjRJgVgAFfBiIjsDYMvGWqpvHxTWO2QiOSKRYUAFycl3n2on8nH61fBlm4/LuGsiIjIFAy+ZEj0TnBd+7Muc/WLiGSnNRXbaElcqB+evtu0Soh6G/fm4rnPmYZIRGRLDL5kyJQ7vGt2Z2Pgkp1MPSEiWYkI8IKvR/OBlQKOVWyjJfPiTK+EqLf9d6YhEhHZEoMvGTL1Du+1sio8u/koliVkSjwjIiLL2JmZj/JqTZNf05fXiB/vWMU2WmJuJUSAaYhERLbE4EuGIgK8oPZ0g6mXGh/8moOE9DxJ50REJDV9YaGisqomv97B3RnrpoQjNsT0QESO6lZCNGcVjGmIRETWx+BLhlRKBeLHBwOAyQHYjC9S+YZLRHZLpLCQq5MSo4J9rTYneyPFKhjTEImIrIvBl0zFhqixbko4fD1NS0HU6oB3fzop8ayIiKQhUlgov6Si1VdylWIVjD3BiIish8GXjMWGqLHv5RGYMbynScev/SWbb7REZJdYYt44+lWwsX1NXwlkTzAiIstj8CVzKqUCQ3p2Nvl4rn4RkT1iiXnjqZQKrH1kAKbdZXpJehbjICKyLAZfDiAiwAsd3Z1MOparX0RkjwwVFmpNJeaNNX+s+SXpWYyDiMgyGHw5AJVSgciATiYfz9UvIrI3dQsLNdQaS8wbS4o0RBbjICKSHoMvB1FYWmHysWt/yUZiBkvPE5H98XR3bvRYay0xbywp0xBZjIOISBoMvhyARqvDsfPFZp3jta2ZfGMlIrvRUo+va830/aKmSZGGyGIcRETSYPDlAFJyClGhMS9wyi8pb/Ulm4nIPhjq8aUAsHgbbxgZQ4qeYCzGQURkPgZfDkCqUsss2UxE9sBQjy8dgLxi3jAylhQ9wQAW4yAiMgeDLwcgVanlxN+574uIbI89viyLxTiIiGyHwZcDCOvWQZLzJB4vQGW1VpJzERGZij2+LI89wYiIbIPBlwPYdPCsJOfRAfgsOVeScxERmYo9vqyHPcGIiKyLwZfMabQ6/HhcunTBs4Vlkp2LiMgUdXt8NQzA2ONLelIU42AaIhGRGAZfMpaYkYehb+3C4bNFkp3zRjlLOBOR7Y0K9sXsmF7wbFO/z5evpxt7fFmAFMU4mIZIRGSYQqfTMU/ABCUlJfD09ERxcTE8PDys/vz6HjhS/+O5qBT44/UxvKNMRDaTmJGHxdsy61U87NDGGU8O8ceMEUF8fbIwjVaH579Ixfbf800+x9i+vlg1OZz/VkTUaojGBlz5kiFDPXDMUanR4cDpKxY4MxGRYfobSw1LzRffrMKKn09jZ6bpAQGJkaIYx/bf89EnPhGLt2YgOfsq94MREf0Pgy8ZMtQDx1zfHP3TYucmImpOSzeW9I+xubL1mFuMo7xKi48PnMXkjQcxaOlO7gcjIgKDL1mydG+bskqNRc9PRNQUNle2P1L0BAOAwtIq7gcjIgKDL1kytbdNtw6uQuOKb7LoBhFZH5sr2ycp0hD1WJaeiFo7Bl8yZKgHTnMmDewuNC4lt5DNlonI6thc2b5J0RMMYFl6ImrdGHzJUEs9cFqSdrFIaJxOx2bLRGR9bK5s/6RKQ2RZeiJqrRh8yVRsiBrrpoTD11P8DvDNCvG9XNlXbpgyLSIik7G5sjxInYY4Ye0+7M+6wlREImoVGHzJWGyIGnv+MRyi1yF9u3rCRSU2OOPPYjNmRkRkmuZuLLG5sv2RKg0x7XwxHvnwEFMRiahVcLL1BMg8h85chejNwsE9OuP4xRL8KtDHKzPvOjRaHe8wE5HVjQr2RXtXZySfuQJAgejATojq0YmvR3YoLlSN0SG+mLXlKH5IzzPrXPpUxPEZeVgxiQ2aicgxceVL5r5NFe/JpVQpMKzXbUJjq7VstkxE1peYkYehb+3CIx8dwprd2VizOwsvfX2MzZXtmEqpwJqHw/H+w+Hwauti9vm2pbMgBxE5LgZfMldqRE+uKzcq8Gi0v/B4NlsmImtKzMjD9E2pjXp95ReXY/qmVCRmmLeyQpYVF6rGb/Nj8MW0KAy/Q+xGX3NYkIOIHBWDL5kb0L2j8NjcK2VwcVLC36uN0PicK6WmTouIyCgarQ6Lt2WiqSxq/WOLt2WyKIOdUylr0kQ/fjJCkv1gLMhBRI6GwZfM9bqtnfDYjw/kQKPV4ZEof6Hxpwqu882OiKwiJaew0YpXXToAecXlSMkptN6kyCxSlaVnQQ4iciQMvmQsMSMPM7YcFR5fVFaFNbuy8Phgf6HxN6u0OJh91cTZERGJu3S9+cDLlHFkH6QsS69PRZy5+QhvDBKRbDH4kin93ghj9nwBwJpdp6FSKtC/q4fQ+P8czDVhdkRExvFuL9azUHQc2Rd9Wfp2ruYXWd6Wno/gRTuwYudJBmFEJDsMvmSopb0RhlRpddh3+jJu79RWaPyvpy7zzY2ILC4iwAtqT7dGzZX1FADUnm6ICPCy5rRIQnGhahyLvxcvxPSCi5N5lx8V1TqsSMpCn0WJTEUkIllh8CVDhvZGGPLqt79DoRDrn3KzSss9FkRkcSqlAvHjgwGgUQCm/zx+fDB7P8mcSqnArJgg/PHPWMweGQRXlXn/nuXVWqYiEpGs2EXwtXbtWvj7+8PNzQ2RkZFISUlpcfzXX3+N3r17w83NDX379kVCQkK9r+t0OixatAhqtRpt2rRBTEwMTp8+3eS5KioqEBYWBoVCgbS0NKm+JYsyd8/DheJy+HqKp+6wvw4RWUNsiBrrpoQ3en3y9XTDuinhiA1R22hmJDWVUoHZo3oh8/UxZhfkAJiKSETyYfPg68svv8ScOXMQHx+P1NRU9OvXD6NHj8alS5eaHH/gwAFMnjwZU6dOxdGjRzFhwgRMmDABGRkZtWPefvttrFq1CuvXr8ehQ4fQtm1bjB49GuXljYOWuXPnws/Pz2LfnyVIseeh5GaV8Njv0i7yzYyIrCI2RI19L4/AF9OisHJSGL6YFoV9L49g4OWgpCzIoU9FDF64Ayt/PsX3LSKySwqdTmfTV6fIyEgMGjQIa9asAQBotVp069YNM2fOxCuvvNJo/MSJE1FaWooffvih9rGoqCiEhYVh/fr10Ol08PPzw4svvoiXXnoJAFBcXAwfHx988sknmDRpUu1xO3bswJw5c/DNN9+gT58+OHr0KMLCwoTmXVJSAk9PTxQXF8PDQ6x4hVQ0Wh2GvrXLrNTDkXd0RvKZqyirEvvn/2JaFKIDO5n8fERERC1JSM/D3G/ScaOiWpLztXVVYfmDoYgLldcNViKSJ9HYwKYrX5WVlThy5AhiYmJqH1MqlYiJiUFycnKTxyQnJ9cbDwCjR4+uHZ+Tk4P8/Px6Yzw9PREZGVnvnAUFBZg2bRo+++wzuLu7G5xrRUUFSkpK6n3YSt29EaYquF6Je+7wFh7P8s5EZA0arQ7J2VfxfdoFJGdf5epFKyJlQQ7gVmn6Jz8+xN8lIrIb5td8NcOVK1eg0Wjg4+NT73EfHx+cOHGiyWPy8/ObHJ+fn1/7df1jzY3R6XR44okn8Mwzz2DgwIHIzc01ONdly5Zh8eLFQt+XNcSGqPHk4O74+MBZk46/Xl6FHrd5AygQGp9dcMOk5yEiEpWYkYfF2zLrreqrPd0QPz6YaYethL4gx4wRPbE66TTW/ZKFCo15QdPuk1ew++QVeLV1xpL7Q7gSRkQ2ZfM9X7awevVqXL9+HfPmzRM+Zt68eSguLq79OH/+vAVnKKZrR8Mrds05V3gTg/w7Co/fuO8M7xoSkcXoexc2TKfOLy7H9E2pSMzIs9HMyBbqFuQYFypN4F1YWoVnNx/F0u3HJTkfEZEpbBp8de7cGSqVCgUF9VdfCgoK4OvbdPUjX1/fFsfr/9vSmF27diE5ORmurq5wcnJCz549AQADBw7E448/3uTzurq6wsPDo96HrXm2cTb5WB2AUwXX4SJY5vdmlRYHs6+a/HxERM1pqXeh/rHF2zJ5A6gVUikVWPNwON5/OBxuEqQiAsDGvbl4gqmIRGQjNg2+XFxcMGDAACQlJdU+ptVqkZSUhOjo6CaPiY6OrjceAHbu3Fk7PiAgAL6+vvXGlJSU4NChQ7VjVq1ahWPHjiEtLQ1paWm1peq//PJLLF26VNLv0ZKO/Vlk1vHnr93Eff3E0y8OZF8x6/mIiJpiqHehDkBecTl7DrZicaFqHJeoNxgA/HLyCiZvPIhBS3eySTMRWZXN0w7nzJmDjRs34tNPP8Uff/yB6dOno7S0FE8++SQA4LHHHquXHjhr1iwkJibinXfewYkTJ/Daa6/h8OHDmDFjBgBAoVBg9uzZWLJkCbZu3Yrff/8djz32GPz8/DBhwgQAwO23346QkJDaj169egEAAgMD0bVrV+v+AMxg7v26bh3b4I0HQoXH/3ic/b6ISHqiBX1Y+Kd1s2Qq4nOfH+YqGBFZhU0LbgA1peMvX76MRYsWIT8/H2FhYUhMTKwtmHHu3DkolbdixMGDB2Pz5s1YsGABXn31VQQFBeG7775DSEhI7Zi5c+eitLQUTz31FIqKijB06FAkJibCzc38/lj2JKBTW7OO7+3rARcnJfp1bY9jf143OD77cikqq7WSVKEiItIT7V0oRY9Dkj99KmJciHSl6bf/XoCfM3fg2eE9MWNEEFRK81fXiIiaYvM+X3Jlyz5fejcrNbhzUaLJx7/31374f+FdsfHXM1ia8IfQMQvH3ompd/Uw+TmJiBrS9y7MLy5vckVfAcDX0w37Xh7Bi2KqR6PV4WD2VSz/8Q+k/SlNCxhXJwWmDwvEzJG9+PtGRMJk0eeLzJN2vsis46/cqAAAdG7vKnzM2cIys56TiKihur0LG17q6j+PHx/MC2FqRKVUYEhQZ3w34y5MuytAknNWVOuwIikLfRYlcj8YEUmOwZeM5ZeYt//hyLlrAABfD/FUnlP5htMTiYiMFRuixrop4fD1rP965OvphnVTwtnniwyaPzYY7z8cDq+2LpKcr7xai2c3H8UDa/dhf9YV7gkjIknYfM8Xma7wfytXpvrlxGVotDpEBHihYxsnXLtpOG/+YE4h930RkUXEhqgxKtgXKTmFuHS9HN7t3RAR4MUVLxIWF6rG6JCa36EP9mThl1PmV+lNPV+MRz48hLauKix/MJRNmonILLyClrEO7ubd3SuvrundpVIq8EC4eJXHV79NN+t5iYiao1IqEB3YCfeHdUF0YCcGXmQ0/e/QJ3+LlCwVEQBKKzR4dvNRPMkeYURkBgZfMlZUVmn2OZLP1NwVjAluuql1UxIy8vmmQ0REdk/qVEQA2M0eYURkBgZfMibNm0nNXeWIAC+0cRb7dSir1LDZKRFJSqPVITn7Kr5Pu8BVBZJUXKgav82PwRfTojD8jtskOy97hBGRKbjnS8Z8PduYfY7owE4AatI0Jg7shk+Szwodl1980+znJiICgMSMPCzelom84ltFhNSebogfH8xCGyQJfSpidGAnJKRL1x8MqOkR9tPxBMQE+2JKVHdE9WC6LBE1jytfMnb1unnVDhUKYJC/V+3no424yPnqt/NmPTcREVATeE3flFov8AKA/OJyTN+UisSMPBvNjBxVXKgax+LvxedTI9G/m6ck56zSAjsy8vHIh4cQuvhHpiMSUbMYfMlUYkYeZmxJM+scOh1w5Oy12s8jArzg2UZsMVRf9ZCIyFQarQ6Lt2U22VhZ/9jibZlM6SLJ6fuD/d9zQ/H+w+Fwk7CCr74wB9MRiagpDL5kSH/BIoW66YMqpQJ/GyJWGUoH4LPkXEnmQEStU0pOYaMVr7p0APKKy7nHlCwqLlSN4/+MxeyRQZIGYdt/L0DvBQmYvukI+4QRUS0GXzJk6ILFGPuz6vdAmTEiCIJ1N/BN6p+SzIGIWqdLgqnTouOITKVSKjB7VC8c/2csXojpBWeVNHu2mI5IRA0x+JIhKS9Efv7jUr27cTWbkjsLHftH3nWmHhKRybzbu0k6jshcKqUCs2KCcOL1MRjXV9piL0xHJCKAwZcsSXkhUnSzqlFKz4SwLkLHMvWQiMwREeAFtacbmltjUKCm6mFEgFczI4gsQ6VUYM0j4ZL3CAOYjkjU2jH4kiH9BYtUGpaNV3cQL2F/trBMsnkQUeuiUioQPz4YABoFYPrP48cHs2w32YyleoTVTUcMXrQDK3aeZBBG1EoYHXyNGDECRUVFjR4vKSnBiBEjpJgTGVD3gkUKhaWV9T6PCPBCezeV0LGn869LNg8ian1iQ9RYNyUcvg1uKPl6umHdlHD2+SKb0/cI+/jJCLz/cDjauUrbIrWiWocVSVnovYBBGFFroNDpdEb9lSuVSuTn58Pb27ve45cuXUKXLl1QVVUl6QTtVUlJCTw9PVFcXAwPDw+bzGHqJylIOnHZ7PO881A/PDiga73Htqb+iee/OmbwWKUCOPH6GLhIWCGKiFofjVaHlJxCXLpeDu/2NamGXPEie6TR6nAw+yo2HcrFzuMFqJY4VnJVKfDs8J6YMSKIfwNEMiIaGwjfvklPT6/9/8zMTOTn59d+rtFokJiYiC5dxPYKkfk0Wh2Oni+S5FxFZZWNHrvNUyz1UKur2fc19a4eksyFiFon/eoCkb3T9wgbEtQZGq0Os744ih9+l64ZeIVGh/d+Po33f8nC9GGBmDmyF4MwIgciHHyFhYVBoVBAoVA0mV7Ypk0brF69WtLJUfNScgpRWCrNKqNXO9dGjxlTUZH7voiIqDXSF+aIS8/D3G/ScaOiWrJz69MR1+7OxnPDGYQROQrh4CsnJwc6nQ49evRASkoKbrvt1sZTFxcXeHt7Q6US2ydE5ssvka7cvHcTwZcxFRW574uIiFqzuFA1Rof4WiQdsUp7KwibEnU77u2jZloukYwJB1/du3cHAGi17OtkDwpvVEh2rt9yCzEkqH5vr4gAL3i3c8alG4ZX1w7lFqKyWst9X0RE1GpZOh2xSqvDxwfO4uMDZ9HWVYVpQwO4GkatVmW1Fp8l5+JsYRm6e7nj0Wh/2VyHGl1wAwBOnz6N3bt349KlS42CsUWLFkk2OXtm64Ib/5f6J14QKIghooO7M44sGNXoBXzlz6fw3s+nhc6xcOyd3PdFRERUR4IF0hHrclYqmJJIrc6yhExs3JuDuoVBlQpg2l0BmBcnXTVwY0lecENv48aNmD59Ojp37gxfX18oFLf+2BUKRasJvmzNV7AghoiisppGyw03u/t3bit8Du77IiJTsdIhOaqG6Yg/Z15ClYSl5OumJDIIo9ZgWUImPvg1p9HjWh1qH7dlACbC6OBryZIlWLp0KV5++WVLzIcE6Rst5xU3v/fL18MVN6u0KL5pOHWwqQIb3PdFRJaWmJGHxdsy672WqT3dED8+mD2+yCE0TEdcnXQaa3dnWSwI474wclSV1Vps3Ns48Kpr494cvHhvb7tOQTR6ZteuXcNDDz1kibmQEVRKBe7r1/KFyf1hfnhicHeh83Vu27joRkSAF3zauwgdfzCnZt8XEZGoxIw8TN+U2ugmUn5xOaZvSkVihnT7ZYjsgUqpwOxRvXBiyRjMHhkEN4kvEPX7wiZvPIjQxT+yaTM5lM+Sc2Ho11nfAsmeGf1X/9BDD+Gnn36yxFzICBqtDluPtXxhsvVYHgZ29xI7YRM3x1RKBRbfHyJ0uA7ApwdavhtBRKSn0eqweFsmmnof1T+2eFsmLxzJIemDsOP/jMXnUyPRv5un5M9RWqHBiqQs9F6wg0EYOYTcq2JbXETH2YrRaYc9e/bEwoULcfDgQfTt2xfOzs71vv78889LNjlqXkpOYYsphwCQV1yO5DNXhc53qZnS9bEhavTr6oFjf5YYPMcP6XmYdneg0PMRUetm6DVMh5rXsKb2oxI5ilspiUORkJ6HOV+loVziLBJ9SuLqXVkYFeyDR6P9EdWjE1MSSYZEbyDY940Go4OvDRs2oF27dtizZw/27NlT72sKhYLBl5WINkG+WHRTaFxhaWWzX+vRuZ1Q8HX8YjE0Wh1f0InIINHXMGMavhPJmb44hyX2hAGARgckHi9A4vECuDopMH0YC3SQvIR2EVshFh1nK0YHXzk5TC2zB6LFMNSeYuM6uDe/t+uB8K74v7SLBs9RrQVWJ53G7FG9hJ6TiFov0dcwYwr/EMmdPh1x5sggrE46jQ/3ncGNCo3kz1NRzQIdJD8l5WItG0TH2YrJOz0rKytx8uRJVFfb9zfoqAZ07whDr5FKBdCxhaCqrqKy5le+BvfsDGfB35QP951hXjkRGaSv2Nrcy5gCNTePIgIE960SORB9EHYsfjS+mBaFJwd3h7NK+sCIBTpITkSvaUXH2YrRwVdZWRmmTp0Kd3d39OnTB+fOnQMAzJw5E2+++abkE6SmHTl7Tajii0iZeQD4s4X0RJVSgZhgX6Hz3KjQICWnUGgsEbVeKqUC8eNrerE0vKTUfx4/Pph34qlVUykViA7shPj7QnDi9ZoKic4W+ptggQ6yd9daWCgwZZytGB18zZs3D8eOHcMvv/wCN7db6SAxMTH48ssvJZ0cNU90H4RC8DV6a9rFFl9op0SJlawHwPLQRCQkNkSNdVPC4dsgPdrX0w3rpoSzzxdRHQ3L1FsqCNMX6Og1PwHPfHYY+7OuMBAju+DVVmxFS3ScrRi95+u7777Dl19+iaioKCjqXNn36dMH2dnZkk6Omte5XeO+XE2JDOiEzSnnUFja8grY1dLKFquKRfXoBGeVAlUawy/AXx/5E4vG9+EdayIyKDZEjVHBvkjJKcSl6+Xwbu/GvSdELbDWvjAW6CB74+vZRtJxtmL0ytfly5fh7e3d6PHS0tJ6wRhZVkqOWAl5pUKB+/v5CY3NL2459XBwD7Fyz2WVTD0kInH61Kr7w7ogOpAlsIlEWGtfGHCrQAdTEsmWROsdDOje0ToTMpHRwdfAgQOxffv22s/1AdeHH36I6Oho6WZGzdJodfj0wFmhsVdKK9C1o7vQ2JbKzQPA3b1uEzoPAOzMzBceS0RERKax5r4wpiSSLYnWOzhy9pp1JmQio9MO33jjDYwZMwaZmZmorq7GypUrkZmZiQMHDjTq+0WWkZJTiCLBQhre7d0M/qLqeRlIZXw02h+vb/9D6FxfHf4T88dyszwREZG1NExJXL8nW/KmzQBTEsk2HKU/pNErX0OHDkVaWhqqq6vRt29f/PTTT/D29kZycjIGDBhgiTlSA6K/VB3cnRER4AVvwf1hhsa5OCkxtq+P0LluVFTjYLZYaiQRERFJRx+EHf9nLD6fGonRfXygMrm5UMuYkkjWIlrvQHScrRi98gUAgYGB2Lhxo9RzIUGiTUeH9uxccxdK9EaUwLh7+6ix/fcCodNtOpSLIUGdBZ+ciIiIpKRSKjAkqDOGBHWGRquzaIEOfUri6l1ZGBXsg0ej/RHVg3s4STpagaJvxoyzFaHgq6SkBB4eHrX/3xL9OLKciAAv+Hq4Ir+kosVxR85eg0arw6USwWVagXGigR8A7D5xGRqtji+8RERENlY3JTElpxA/Hc/DpkPnhKoYG4MpiWQph3LFMqoO5V7FXXeI1ymwNqFF6I4dO+LSpUsAgA4dOqBjx46NPvSPk+WplApMjrjd4Li84nKk5BQaLKShtz/risExEQFeaOeqEjpfebWWqYdERER2xJoFOvQpiSzQQVIQ/c2x998woZWvXbt2wcvLCwCwe/dui06IxPh3bis07tL1coOFNPR+/uOSwZUqlVKBhwZ0xceC1RaZekhEzdFodezvRWRDLNBBcnKxqPmWSHV5ujpbeCbmEQq+hg0b1uT/k+2Ipv8ZkyZYdLOqxUbLevf2UQsHXzsyCpCYkYfYELXwPIjI8SVm5GHxtkzkFd9Kd1Z7uiF+fDBfL4isrG4QdjD7Kv5zMBc//1EAjfRxWO1qGPeGkTE0Wh1+zBBrY1RULpbxZStG1775+OOP8fXXXzd6/Ouvv8ann34qyaTIMGMazUUEeMHTTay2SkuNlvUiArzQ0V38rsLibZlMMyCiWokZeZi+KbVe4AUA+cXlmL4pFYkZeTaaGVHrpi/Q8cGjA3FqSZxFUxL1q2GPfHgIoa8lIiH9okWehxxDSk4hyqrE7gYoFRYq7SkRo2e3bNkydO7cOI3M29sbb7zxhiSTIsOMaTSnUioQc6e30Hmv3Gi5iAdQ8+K8dEKI0PmAW3vPiIg0Wh0Wb8tsMidf/xhv2BDZnn417MSSmn1hbk6Wu6AtrdTi2c1HMWHtXu4LoyblCxaPA2Awg8vWjP5LOnfuHAICAho93r17d5w7d06SSZFhxjaa8+3QRmi8aPPmuFA/9PFrLzQWAHZmii0VE5FjS8kpbLTiVZcOvGFDZE+s2TMs7XwJHvnwEIIXsWcY1VcosDgAAG2cVYjq4WDBl7e3N9LT0xs9fuzYMXTqZN/frCMxds+XQrDZl+g4AHigf1fhsV8d/pMvokRk9I0jIrIP1kxJZJVEaqiDu4vQuL8O7Gr3+weNDr4mT56M559/Hrt374ZGo4FGo8GuXbswa9YsTJo0yRJzpCZEBHhB7dlyAKb2rKkeBgCR//uvIcb8vj4a7S889kZFNcvOE5FFigURkXVZKyWx7r4wroa1bkVlYkU0bvdyt/BMzGf0X8vrr7+OyMhIjBw5Em3atEGbNm1w7733YsSIEdzzZUUqpQL39Wu5Ith9/dS10b9SMKpa90u28Aubi5MSI3uLN7FLPmO4jxgROTb9jaPmXpEUqH/jiIjslzVTEvWrYXfMT2AQ1gqJrnyJjrMlo/9EXFxc8OWXX+LEiRP4/PPP8e233yI7Oxv//ve/4eJi/9+wo9Boddh6rOWKYFuP5dW+OIkU0gCAKq0OK3eeEp7H3+8KFB67P4srX0StnUqpQPz4YABoFIDpP48fH2z3aSNEdEtTKYmWWg2r1oEpia1QYanYypfoOFsy+S+jV69eeOihhzBu3Dh0795dyjmRAEOb1oH6m9aNSeHZuO+M8AtZRIAXOrQRK2Of9mcRKi3QvJGI5CU2RI11U8Lh2yB12tfTDeumhLPPF5GMWWs1rG5KYu+FO/DujycYhDmwa4Jph6LjbEnoqnnOnDl4/fXX0bZtW8yZM6fFse+++64kE6OWGbtpPSLAC65OClRUG35hulmlFWq2DNS8yD4x2B8rkrIMjtXpgM+SczH1rh6GJ05EDi02RI1Rwb5IySnEpevl8G5fk2rIFS8ix6BfDRsS1BkarQ6rk05j7e4sVFkgQKrS6LBqdzbW7M7GvX3YuNkRKQT/KUXH2ZJQ8HX06FFUVdWUIE9NTYWime+sucdJerlXSoXG6Ve8VEoFxoWq8U2qWBPDi9fKAIhVrwy4rZ3QOAD4JvUCgy8iAlDzumTv/ViIyHz61bCZI4OwOuk01uzOQrUFgjAtalbDEo8XwEkJ3B/mh2UP9IOLBXuUkXV4uDlLOs6WhIKvlStXwsPDAwDwyy+/WHI+JECj1eGLFMM91RpuWl/2QD/h4Gtr+kU8OLCb0FhjUhoz80qQkJ6HuFCmFREREbUmDYOw9XuyUW6h7QjVWuCb1Iv4JvUiwrp54B+j7+RqmIwVC/ahFR1nS0K3Avr3748rV2oq1fXo0QNXr7Jwgi2l5BQiv8RwAY0B3TvWe5FxcVLiTl+xVarkM4VG7fvyaS9ebGXh9xnMyyYiImqlrFklEbjVvLnXggQ8/Z/fWKRDhhwp7VDoV71Dhw7IyckBAOTm5kKrZdEEWxLd77WviReXgf5i5Zsrq7XCfblUSgUW3x8iNBYArpZW1hYCISIiotbJmlUSAUCjBX7MvIRHPjyEOxYk4MWvjrIQmEw4Utqh0G/4gw8+iGHDhiEgIAAKhQIDBw5Ejx49mvwgyxNN8ysqq2oU5PTv1lH4eYzpyxUbosZfwrsIjxcNIImIiMjxNVwNC+vmadHn06cl9lqwAxPW7uVqmJ0ruilWxVB0nC0J7fnasGEDHnjgAWRlZeH555/HtGnT0L59e0vPjZpRU97dGUUCea0Ngxx1hzbCz3P60g2j5jUk6Db8N/WC0Nicy2IFQ4iIiKj1uFUlcSgS0vMw95t03Kiotuhz6tMSVUogprc3HhscwP1hduZI7jWhcXlF9n9zXyj4Sk9Px7333ovY2FgcOXIEs2bNYvBlQyqlAk8O8cd7P582OLbhKllEgBfauapwo0Jj8NhfT12GRqsTfvHx9RAvvLF+TzZmjgziCxsRERE1KS5UjdEhvjiYfRX/OZiLXScuoUpjudUpfVrij5mX4KxSYPrdPTBr1B28VrExjVaHtPNFQmP9Oohfi9qK0QU39uzZg8pK+1/Sc3QzRgShrYuqxTEd3Z3rVTsEagK3hwZ0FXqOm1Xi+76AWytyIsqrtVidZDh4JCIiotar7r6wE6+PsUpKInCrd1jPV7k3zNYOnrmKSsGge0jgbRaejflYcEPGnA1sSm3u1/TePuJl3vdnXxYeq1+RE7V+Tzbzq4mIiEiIPhD77rmhOLVkDB4M7wInC69K6XBrb9iwt3dh469nGIhZ2YFssRoEzkoFomTQO5IFN2QqJacQRWUt7/lqquAGULNC5eok9mJ14dpNo+Y1Y0QQXAUrFZVXa7FmV5ZR5yciIiJycVLinb+G4eSSMbXl6i2dHXi28CaWJvyBXgt2YNIHBxiEWYnotWiVVoedmfkWno35WHBDpkSrBTY1TqVUILRrB/wmsHnx+MUSo+alUirwzLAeWJkkFlR98Gs2ZozoyXxqolZGo9UhJacQl66Xw7t9TUN4vg4QkbFuFejoDI1Wh5U7T2Hdr9kW3RsGAAdzrqHXgh1s4GwFOp34v+XibZkYFexr1/8WQsEXAMTGxgIAC27YCdFy882NiwjwEgq+si+XorJaCxcj+m48P7IX3t+djSqBlMKySg0OZl/FkKDOwucnInlLzMjD4m2ZyCu+dXNI7emG+PHBiA0RT4smIqpLpVRgzug7MGtULxzMvorlP51A2vliiz6nvlKiq0qB6fcEYubIXnZ94S9Hfh3FK3XnFZcjJacQ0Xacfmh0J7uPP/4Y7du3R1ZWFn788UfcvFmzFGhMVErmiwjwgtrTDc39eStQczHTsOCG3uBAsWBHB+Cz5Fyj5qZSKjAl6nbh8cb0EyMieUvMyMP0Tan1Ai8AyC8ux/RNqUjMyLPRzIjIUTTcGzY/rjdCu3g0e80khQqNDiuSsnDH/ASs2HmSe9ol1KGNi1Hj7b2XrNHBV2FhIUaOHIlevXohLi4OeXk1b5RTp07Fiy++aNIk1q5dC39/f7i5uSEyMhIpKSktjv/666/Ru3dvuLm5oW/fvkhISKj3dZ1Oh0WLFkGtVqNNmzaIiYnB6dP1K+vdd999uP322+Hm5ga1Wo1HH30UFy9eNGn+tqBSKhA/PrjZoho6APHjg5u9+xLVoxOcBf/195wWL7qhZ1RRjyzxiopEJF8arQ6Lt2U2+bqlf2zxtkxetBCRZFyclJh2dyC2zrwLWW/E4fnhPeGsslwYVq0DgzCJGds4WTQ7zFaMDr5mz54NZ2dnnDt3Du7u7rWPT5w4EYmJiUZP4Msvv8ScOXMQHx+P1NRU9OvXD6NHj8alS5eaHH/gwAFMnjwZU6dOxdGjRzFhwgRMmDABGRkZtWPefvttrFq1CuvXr8ehQ4fQtm1bjB49GuXltyLh4cOH46uvvsLJkyfxzTffIDs7G3/5y1+Mnr9cqZQKRAuufh08U2j0i0dEgBc6uouVnT96vggJ6bzbTeToUnIKG6141aXDrZQRIiKp6dMSrVGynkGYdIxpnNxS1pe9UOiMzBf09fXFjz/+iH79+qF9+/Y4duwYevTogTNnziA0NBQ3btwwagKRkZEYNGgQ1qxZAwDQarXo1q0bZs6ciVdeeaXR+IkTJ6K0tBQ//PBD7WNRUVEICwvD+vXrodPp4OfnhxdffBEvvfQSAKC4uBg+Pj745JNPMGnSpCbnsXXrVkyYMAEVFRVwdjYcNJSUlMDT0xPFxcXw8PAw6nuWgkarw9C3djV7IaMA4Ovphn0vj2h29evbI39iztfHhJ7v86mRRu/LSki/iGc3HxUa69XWBb/Nj2GeNJED+z7tAmZtSTM4buWkMNwf1sXyEyKiVq+yWotPD+Rg08GzOFtoXIVnYzgpgBkjenJPmAlmfZGK74+J3aRfPyXcZnuHRWMDo1e+SktL66146RUWFsLV1dWoc1VWVuLIkSOIiYm5NSGlEjExMUhOTm7ymOTk5HrjAWD06NG143NycpCfn19vjKenJyIjI5s9Z2FhIT7//HMMHjy42cCroqICJSUl9T5sSYo7yOoO4hsYTdmXFRfqh3DBu0qFpZW8203k4MwtFEREJDV9WuKeuSNqe4dZIjTiSpjpLhSJBcWDuneQRdEmo4Ovu+66C//5z39qP1coFNBqtXj77bcxfPhwo8515coVaDQa+Pj41Hvcx8cH+flN1+nPz89vcbz+vyLnfPnll9G2bVt06tQJ586dw/fff9/sXJctWwZPT8/aj27duol9kxZiTql5vYgAL7i7iP0KnL5k3Iqm3uCe4p3GN/yabdJzEJE8mFsoiIjIkvS9wyy5N0wfhPVekIAf0i5Ifn5Ho9HqkHauSGisnxGLCrZkdPD19ttvY8OGDRgzZgwqKysxd+5chISE4Ndff8Vbb71liTlazD/+8Q8cPXoUP/30E1QqFR577LFmqzbOmzcPxcXFtR/nz5+38mzrk+IOskqpwJgQX6HzJGdfNekujTGlPnefvMy9X0QOTF8oCECjAEz/eUuFgoiIrKHh3rB7g70lXw2r0gIztqQh6o2fsffUZa6ENePgmauoFvzRdDGiJL0tGR18hYSE4NSpUxg6dCjuv/9+lJaW4oEHHsDRo0cRGBho1Lk6d+4MlUqFgoKCeo8XFBTA17fpoMDX17fF8fr/ipyzc+fO6NWrF0aNGoUtW7YgISEBBw8ebPJ5XV1d4eHhUe/DliICvNChhYIWoneQhwZ5Cz1fSXm1SWmBUT06oY1oWUUAC77P4AsQkQOLDVFj3ZRw+HrWvzHk6+mGdTbM1Sciakhfsn7DY4NqV8NURl85tyy/pAKP/jsFveYn4N0fT/AaqIED2eLbXoYEimdb2ZJwk+W6PD09MX/+fLOf3MXFBQMGDEBSUhImTJgAoKbgRlJSEmbMmNHkMdHR0UhKSsLs2bNrH9u5cyeio6MBAAEBAfD19UVSUhLCwsIA1GyAO3ToEKZPn97sXLRaLYCavV1ysDMzH0VlVc1+3VCpeT1fD/G9FfnFxm9EVSkVeGZYIN77+bThwbi198uem+MRkXliQ9QYFeyLlJxCXLpeDu/2NTeKuOJFRPaqbgPn1UmnsWZ3FqolDJQ0OmDV7mys+SUbqyaGYRyLDgEALlwTu/Z0USkQJZNrR5OCr6KiInz00Uf4448/AAB9+vTB3/72N3h6Gl+yc86cOXj88ccxcOBAREREYMWKFSgtLcWTTz4JAHjsscfQpUsXLFu2DAAwa9YsDBs2DO+88w7Gjh2LLVu24PDhw9iwYQOAmj1os2fPxpIlSxAUFISAgAAsXLgQfn5+tQHeoUOH8Ntvv2Ho0KHo2LEjsrOzsXDhQgQGBtYGcfZM3yvHkP/Fky2KCPBCO1clblQYHrwv6wr+X3hXkSnWM2NEEN7/JRsV1QITArBxbzaDLyIHV9Pugn/nRCQvKqUCs0f1wsyRQRYJwrS6mnTEJQl/YPlf+mFwz86t+saUaFH2fl09ZfNzMnrx9PDhwwgMDMR7772HwsJCFBYW4t1330VgYCBSU1ONnsDEiRPxr3/9C4sWLUJYWBjS0tKQmJhYWzDj3LlztY2cAWDw4MHYvHkzNmzYgH79+uG///0vvvvuO4SEhNSOmTt3LmbOnImnnnoKgwYNwo0bN5CYmAg3t5pVHnd3d3z77bcYOXIk7rjjDkydOhWhoaHYs2eP0RUbbcFQpUO9hQIpfCqlAkMFi2L8eDzfpOXwmtWvHsLjd524jErBQI2IiIjI2vRB2MklYzB7ZBCcJL7w16cjsjqiGLkU2wBM6PN11113oWfPnti4cSOcnGoWzqqrq/H3v/8dZ86cwa+//mqRidobW/b5Eu2VAwBfTIsyeHf5Xz+exJrdWZKdrykarQ53LtyBSo3Yr1uUf0dseWaw0c9DREREZG0arc4iK2F6KgXw3D2BmDXqDtms8Ejh+c2p2CpQjO2+UDVWPRxuhRk1z2J9vg4fPoyXX365NvACACcnJ8ydOxeHDx82bbZkFGN64IiUpDcmmDJl3xdQc4fo0ajuwuMP5l7D0u2GUyuJiIiIbM3SK2H6PWE9X21dhTlO5hcLjbtyQx41GwATgi8PDw+cO3eu0ePnz59H+/btJZkUtSwiwAtebZuvdFiXSKAW1aMTXJ3EXiTM+eWOCRYra6+3cW8OS88TERGRbFg6CNPhVhD24ldHHXqbhkarw6lLZUJjResK2AOjg6+JEydi6tSp+PLLL3H+/HmcP38eW7Zswd///ndMnjzZEnOkBlRKBZbcH2JwnGizUpVSgeF3iJWcP3LumtC4pkQEeMGnvYtRx7D0PBEREclNwyBM6kxBHYBvUi+i14IdeHbTYYe8VjqQdQWi31VXmfT4AkwIvv71r3/hgQcewGOPPQZ/f3/4+/vjiSeewF/+8hfZNVmWs7hQP4wKbjlguq+fWjgvuKe32KrlLydMbwSoUiqwWCBorEtfep6IiIhIbvRB2OmllukTBgAJGQUIdMB0xG9S/xQe+5fwbhacibSM/hVwcXHBypUrce3aNaSlpSEtLQ2FhYV47733ZFEp0FFotDpkXChpcczWY3nCf4Si+77Kq7U4mH1VaGxTYkPUeP/h/kYdszMz3+TnIyIiIrI1fZ+wU0vi8NmTEfDxMC4TSMSq3dkImp+AH9IuSH5uWzh/TSzlUAEgUkatS4SDL41Gg/T0dNy8WVNwwd3dHX379kXfvn2hUCiQnp5e26iYLE+k3HxecbnwqlFUj05wUYmtku3Pviw0rjlxoX54fkRP4fGbD51zqDs5RERE1DqplArcdcdtOPTqKKye3F/ylTB9n7BR7+yW/X4wV8Efjg7AsOW7kZghjzoBwv/kn332Gf72t7/BxaVxpO7s7Iy//e1v2Lx5s6STo+aJVDE0ZpxKqUBYtw5CY386XiA0riWzYnoJB3vl1VqsTjpt9nMSERER2Yvx/fxwaklNOqLUe8JOXy6T/X6wK9fFK2znF5dj+qZUWQRgwsHXRx99hJdeegkqlarR1/Sl5jds2CDp5Kh5ouXmjSlLP0igOAcAZF8uNftuirGl59f9kiXbFw8iIiKipujTES21JywhowA9X5VfKqJGq8Ppy+LBl/4KcfG2TLu/XhT+Jz558iSioqKa/fqgQYPwxx9/SDIpMiwiwAtqTzc0d6NEAfFqh3qDAzsLjdMB+Cw5V/i8zTGm9HyFRodZW46a/ZxERERE9qbunjCpqyPqUJOKOPWTQ9Kd1MIOnrkqXOlQTwfjttzYinDwVVpaipKS5gs8XL9+HWVlYhvjyHwqpQLx44MBoFEApv88fnywUV3Qo3p0grPgb8Se0+bt+wJqAsiO7k6GB/7PD+l57PtFJHMarQ7J2VfxfdoFJGdftfs7lERE1tSwOqKUQVjSiSu45+0kWbzu7j99xeRjRbfc2Ipw8BUUFIQDBw40+/V9+/YhKChIkkmRmNgQNZ66OwCKBn+YCgXw1N0BiA1RG3U+lVKBaMHVr4NnCs3+41UpFVg6oa9Rxyxk3y8i2UrMyMPQt3Zh8saDmLUlDZM3HsTQt3bJIkefiMiaGqYjOgvukzckt7BcFmmIx/4sMvlYY7bc2IJw8PXwww9jwYIFSE9Pb/S1Y8eOYdGiRXj44YclnRy1LDEjDxt+zUHDWESrAzb8mmPSBc2EsC5C4yrNLDmvFxfqh+F3iAV8AHCVfb+IZCkxIw/TN6U2qtIqp03SRETWpg/CTrw+Bp9PjUT3TuY3E5ZDGuLNymqjjzFly40tCAdfL7zwAvr27YsBAwZgzJgxeOGFF/DCCy9gzJgxGDhwIEJCQvDCCy9Ycq5Uh0arw+JtmS3mw5qy6VDdQfyPOvmM6UvCdT11t3jZeQBYuj1TkuclIuto6fVKTpukiYhsRaVUYEhQZ+z5xwjJStTbcxpi7tVSo8abuuXGFoT/6ZydnfHTTz9h6dKlyMvLw4YNG/DBBx8gLy8PS5cuxU8//QRnZ2dLzpXqMNTny9RNhxEBXnB3Efu1OH3phlHnbuk5fT3EG3RnXCzBtmMXJXluIrI8S71eERG1RnVL1JsbZuQWliPo1QQkpNvPdVVltRaFZcatfPl6umHdlHCjt9zYglFxs7OzM+bOnYu0tDSUlpairKwMaWlpmDt3bpP9v8hypO7zpadSKjAmRKwKoVSb5VVKBV67r49Rx8z97zG7vFNDRI1Z6vWKiKi10qcjZr0RhzjB67bmaAE8u/koXv8hQ5rJmemT/TnCYwfc3gFfTIvCvpdHyCLwAowMvsh+WKLPl97QIG+hcSXl1ZLdqY4NUeOFGPGCLTertFizK0uS5yYiy7Lk6xURUWumUirw/pQBOLVkDHre5m7WuT7adxZ/+9j2+8B+yswXHjt7ZC9EB3ay+1TDuhh8yZQl+nzp+XqIXwD9dFy6TfIzRgShnWvjJt7NWcvGy0SyYMnXKyIiAlyclPj5xeGYOjTArPPsOnkF41bukWhWprlwTay5sgLA4CDxom32gsGXTNXt89WQuZsOIwK80M5V7Ffjm9QLkgVAKqUCb/4/8dLzldVaNl4mkgFL9CUkIqLGFo4LxvsPh5t1gZ+RdwNjbRSAabQ65JVUCI3t0sFNlu8bDL5kro1LEytFJvb50lMpFRja8zahsVKmHgLAuLAuiLlT7LkBYHt6HiqrtZI9PxFZRmyIGuumhMPXs/7Kupw2SRMRyUFcqBqn34hD/66eJp/jeN4NjFv1q4SzEnMgS7yStnd78WJt9oTBl0wlZuThmU2pKKvUNPqaTgd8YGKfL72e3u2Fx+40IjdXxIePRyDIu63QWB2Az5JzJX1+IrKM2BA19r08Al9Mi8LKSWGy2yRNRCQXKqUC/zdjqFlpiBkXr2PqJ79JOCvD/nvkT+Gx3bzM2+NmK0YHXxqNBh999BEefvhhxMTEYMSIEfU+yPI0Wh1e23rc4Dhz+uZEB3YSHvvV4T8l33v17HDx4hv/3ideFYeIbEulVCA6sBPuD+siu03SRERyo09DNPWVNunEJau299lz6rLw2L+Ed7PgTCzH6OBr1qxZmDVrFjQaDUJCQtCvX796H2R5KTmFyBfIhzWnb05Uj05oK9jv60ZFNQ5mXzXpeZpjTNGPC8Xl+Pun1r0zQ0RERCQHcaFqZL0RB3+vNiYdP/OLo1YpcFZZrUXRzSqhsXIttgEATsYesGXLFnz11VeIi4uzxHxIgDG9cEztm6NSKjBp0O34aH+u0Pj/HMzFEAn/CCICvODT3gUF1yuFxv/8R82dmfH9/CSbAxEREZEjUCkV+GXuCEz95Dcknbhk9PEj/7Ubv8y1bIbbpwdyhcf6d3KXbeaE0StfLi4u6NmzpyXmQoKM6YVjTt+cmGDxpn2/nros6V0RlVKBxfeHGHUMGy8TERERNe+jJwZh5cQwo4/LLbxp8f1f245dEB47KUKeKYeACcHXiy++iJUrV0Kn40WurUQEeMHXw3CFF3P75kQEeKFtU9UUm3CzSitp1UOAjZeJiIiIpHZ//y54/+Fwo4+z5P4vjVaH9AslwuOfHNLDIvOwBqODr3379uHzzz9HYGAgxo8fjwceeKDeB1meSqnA/WGG0+vM7ZujUiow7S7xKjnmVFdsjrGNlz/4NZurX0REREQtiAtV4/2H+xt93Owtltn/ZUyJ+Q5tnODiJN+C7UbPvEOHDvh//+//YdiwYejcuTM8PT3rfZDlabQ6bD3WcqDTwd0Zo4xIG2zOzJG9oBKM374+In3VQ2MbL5dVarj6RURERGRAXKgfVv01zKhjNDpg5uZUyediTIn5wNvaSf781mR0wY2PP/7YEvMgI6TkFCKvuOVCGkVlVUjJKTSqZHxTahoud8ae04bvSJRVaiR5zobGhXXBd8cu4Oc/xMqPrv0lCzNG9JTtRkwiIiIia7gvvAu+T/8TSSfEV54SMvKRkJ6HuFDpejQaU2L+3j4+kj2vLZi8Znf58mXs27cP+/btw+XL4j8wMp9oBUNTKx02dHev24TH/nRc+tRDwLjGy5XVWqxOOm2ReRARERE5ko+eiIS/l3EF2mZJmH5oTIl5QN77vQATgq/S0lL87W9/g1qtxt133427774bfn5+mDp1KsrKyiwxR2pAtIKhOZUO63o02l947Jbfzltsz5UxjZfX/ZLFvV9EREREApJeGmFUI+YqrQ4rd56S5Lk/2Z8jPNa7nYus93sBJgRfc+bMwZ49e7Bt2zYUFRWhqKgI33//Pfbs2YMXX3zREnOkBiICvKD2dGv2j0QB8ysd1uXipMTwO8R6eN2s0krecFnPmMbLFRodnv9C+pxkIiIiIkejUiqwelKYUceskehG99rd4tlKU40oBGevjA6+vvnmG3z00UcYM2YMPDw84OHhgbi4OGzcuBH//e9/LTFHakClVCB+fDAANArA9J+bW+mwoafuFu/t9p+DuZI9b10RAV7o6O4sPH777/lYuj3TInMhIiIiciTjwrog/Hbx4nlaHcxe/bpZqUFxuUZ4vNxTDgETgq+ysjL4+DTe6Obt7c20QyuKDVFj3ZRw+HrWXw3y9XTDuinhiA2RbhMkUBP4uDmL/bpI3XBZT6VUYOkE4xovb9ybg4R0y+xDIyIiInIkXz8zBMbcuzd39eupT8UbNztCyiFgQvAVHR2N+Ph4lJffKuZw8+ZNLF68GNHR0ZJOjloWG6LGnn8Mx8Kxd+Kx6O5YOPZO7PnHcMkDL6Am8LlHsPCGJRou68WF+mHaXf5GHbPgu9+5/4uIiIjIAJVSgVUTw4THm7P6pdHqsNeIrSqOkHIImBB8rVy5Evv370fXrl0xcuRIjBw5Et26dcOBAwewcuVKS8yRmpGYkYdhy3fj9e1/4D/JZ/H69j8wbPluizQ7BowrvLHh12yLzAEA5o/tg7Bu4svihWVV7P1FREREJGBcWBfhCtMA8P4e01a/jGmsDDhGyiFgQvAVEhKC06dPY9myZQgLC0NYWBjefPNNnD59Gn369LHEHKkJiRl5mL4ptVG/r/zickzflGqRACyqRyfh1MNfTl5GZbVW8jno/WN0b6PGv/fzKYsFpURERESOZPvzdwuPrdbCpBY/8VszhMcGdnZ3iJRDwIQmywDg7u6OadOmST0XEqTR6rB4WyaausegQ03RjcXbMjEq2FfSohsqpQKTB3XDxwfOGhyrA/BZci6m3mWZuxRRPTrBs40Tim9WCx/zyre/S/4zISIiInI0Lk5KRAV0xMGca0Lj1+/JxsyRQcLXWJXVWpy5Il4r4rXxxu35t2dCwdfWrVsxZswYODs7Y+vWrS2Ove+++ySZGDUvJaew0YpXXToAecXlSMkpRHRgJ0mf+94+aqHgCwB+PX3FYsGXSqnAWw+G4plN4uXki8qqcDD7KoYEiZXNJyJpabQ6pOQU4tL1cni3r2mHwZshRET26T9To9BrwQ6hseXVWqOusR75MFl4HgoAgx3o2k0o+JowYQLy8/Ph7e2NCRMmNDtOoVBAoxEvF0mmuXS9+cDLlHHGiAjwQjtXJW5UGE4pTMm5Co1WZ7GLq9gQNV6ICcJ7P4svdX92MIfBF5ENJGbkYfG2zHo3jtSebogfH2yRIkFERGQeFyclwrp5IO18idD45T+dwJCgoQbHVVZr8VtukfA8hvTs5FA36oSSJ7VaLby9vWv/v7kPBl7W0bmdq6TjjKFSKvC3wWLVZizZcFlvxoggo3p/JR6/xNLzRFZmiz2qRERkvn+MvlN4bNr5YqH9/q/895hRc9j42CCjxts7o3eu/ec//0FFRUWjxysrK/Gf//xHkkmRAaIFZSxUXT3Qp73w2E2Hci0zif8xpffXs5t5sUdkLYb2qAI1e1TZDoKIyP5E9egEV5X4qtOnB3Ja/LpGq8O3aReFz9elgxvauKiEx8uB0cHXk08+ieLi4kaPX79+HU8++aQkk6KWXSltHPyaM85Y3u3dDA/6n58zL1n8osqU3l9zvjrGiz0iKzBmjyoREdkXlVKB6fcECo/fdqzlwGrlzpNGPf/Pc+4xarwcGB186XQ6KBSNI+A///wTnp7ivZfIdKLBjzFBkjEiAryEU/2qtDqTyo8aa/7YPhjb11d4fFmlxirzImrtbLlHlYiIzDdzZC/hgOH3CyXN3tzWaHVYvVu8D6yHm5PDrXoBRgRf/fv3R3h4OBQKBUaOHInw8PDaj379+uGuu+5CTEyMJedK/xMR4IUOBoKfDu7OiAjwssjzG5vqt35PtlVWmVZNDoe7EX+k1poXUWtm65tFRERkHpVSgVHB3kJjdQBW7jzV5NdW7jxp1I6Y54aLr7jJiXCfL32Vw7S0NIwePRrt2rWr/ZqLiwv8/f3x4IMPSj5BMo2la8LEhfohfO8ZpJ5vnILakLHlR02lUirw9N09hKsflldrsSrpNF4Y1cui8yJqzSICvKD2dEN+cXmTb7oKAL6ebha7WUREROZ7bHAAfsy8JDR2/a/ZmDWqV70KhRqtDquMWPUCgCeHWKZdka0JB1/x8fEAAH9/f0yaNAmurtJX0iMxKTmFKCqranHMtbIqi/T5quvF0b3xyIeHhMbuz75slRLvM0YEYcOv2SitNFxtBwBWJp3GHT7tERfKUtdElqBSKhA/PhjTN6VCgfp1gPRvy/Hjgx2qjDARkaOJ6tEJTkpAoJghKjW6RjfdV/xk3F6vyICOcHEyeneULBj9XQUHByMtLa3R44cOHcLhw4elmBMZYC97KKJ6dIKz4G/QT8cLLDoXPZVSgeV/6WfUMax+SGRZsSFqrJsSDl/P+qmFvp5uWDclnH2+iIjsnEqpwP1hfsLj/3Mwt/b/NVodVv9i3KrXZ1OjjBovJ0YHX8899xzOnz/f6PELFy7gueeek2RS1DJ72UOhUiow8k4fobFZl0ut1l/LlOqHr3z7O/d/EVlQbIga+14egS+mRWHlpDB8MS0K+14ewcCLiEgmlj0gfnN794lb1a7/sm6fUc/jyKtegAnBV2ZmJsLDwxs93r9/f2RmZkoyKWqZfg9Fc0k6CgBqK+2heDTaX3jsgu8zrBbgzB/bB2HdxKtvFpVVWbwhNFFrp1IqEB3YCfeHdUF0YCemGhIRyYiLkxJh3TyExupTD29WanD0fIlRz+PIq16ACcGXq6srCgoap5Dl5eXByUl4CxmZQb+HAmhcWMPaeyiienSCq+DdicLSSqv28vnH6N5GjX87kTcPiIiIiJrzj9F3Co9d/tMJDHz9J6POP6aPj0OvegEmBF/33nsv5s2bV6/RclFREV599VWMGjVK0slR82JD1Hjq7gA0bLmmUABP3R1gtVQelVKBEb3Fyo8CwM7MfAvOpr6oHp3Q1lW89PyxC9cx9ZMUC86IiIgcmUarw/7TV/B24h+YveUolv94AvuzrjCtnRyGMfv9084Xo7RKrACa3ppHBpgwK3lR6HQ6o14RLly4gLvvvhtXr15F//79AdSUn/fx8cHOnTvRrVs3i0zU3pSUlMDT0xPFxcXw8BBbgpVSYkYepm9KbbZ0szU3se/PuiJc9bCdqxOOxd9rtXSjhPSLeHbzUaOOibnTGx8+PshCMyIiIkeg0dakVe3PvoyLReW4WaXBnlOXUd7ExaaLChgXqoaPZxtcvHYTCoUCXTq2weDAzojqwRRckpdnPjuMRAsUUls5KQz3h3WR/LzWIhobGB18AUBpaSk+//xzHDt2DG3atEFoaCgmT54MZ+eWG/86ElsGXxqtDkPf2oW84qarGer75ux7eYRVXtA1Wh1CX0sULu/++dRIq5Sd11u6/Tg27s016pjVk/tjfD/xqj5ERNQ6aLQ6rE46jfV7slEuUnfbAGclMKK3Nwb6d0Ln9q7w9ajZs82AjOyVMTfdRfl6uODgq/LOoBONDUzapNW2bVs89dRTJk+OzJOSU9hs4AXU9NHJKy63eJ8vPZVSgUmDbsdH+3OFxm86lGvV4Gv+2D64WFSO7b+Lpzy+9NVRxPVV882PiIhqV7k2HcrFz5mXUCVhGmGVFvgx81K9BrZtXVWYNjQAM0f24vsQ2Z2a1VpAY/69h1q/zh0p3cnsnFDwtXXrVowZMwbOzs7YunVri2Pvu+8+SSZGzbOXPl91xQT7CgdfP2fWlB+15hvKqsnh+OXUjyit0AiNr9AAsSv2IHH2ML7xERG1YgnpeZj7TTpuVFRb7TlLKzRYkZSF1buyMCrYB49G+zM9keyGSqlATG/vejcMzNEaimzUJRR8TZgwAfn5+fD29saECROaHadQKKDRiF3ckunspc9XXREBXujo7oxrZVUGx1ZpdThw+gruuuM2K8yshkqpwPIHQ43a/3X6UimCFyVi5aQw9iIiImqFlm7PxMa9OTZ7fo0OSDxegMTjBXBWAiPvZCBG9uGxwQGSBV+tochGXUJhplarhbe3d+3/N/fBwMs6IgK80MG95f11Hd2drdLnS0+lVGDphBDh8Yt/OG7B2TQtLtQPU4d2N+qYimotntmUisQM6zSIJiIi+/D6D8dtGng1VKWtCcQe+fAQghclYvqmI6ykSDZjTNXDlqycFNbqbiQY9WOrqqrCyJEjcfr0aUvNhyRii5fiuFA/+Hu1ERqbdbkUCenWD2gWjgvByN7Gr7jN/e8xvsEREbUCGq0Oz31+BB/ty7X1VJpVUa3Fjox8PPLhIfRekIBnPjvMQIysSqVUYOSdPmadI6CTu6yrG5rKqODL2dkZ6enplpoLCUrJKUSRgfS+orIqqzY01nskyl947Nxv0m3yRvHRExEIv72DUceUlGsQu2IP39iIiBxYYkYewl//yagCTbZWf0VsB1bsPMn3KrKKR6P9zTr+5xfvkWQecmP0guGUKVPw0UcfWWIuJMgeC27oPT7YX3jsjYpqrNmVZbnJtODrZwbDzcjNnacvlaL3gh1ISL9ooVkREZGtJGbk4ZlNqSi+ab3CGlKrqNZhRVIWes3nahhZXlSPTlCZeGxrTDfUM7rUfHV1Nf7973/j559/xoABA9C2bdt6X3/33Xclmxw1zR4Lbui5OCkR3s0TqeeLhcavSjqFGSN6Wv0PUKVU4F9/CcWMLWlGHVel1eHZzUfx9J9FmBcXbJnJERGRVWm0Orzy7e+2noZk6hbqcHVSYPqwQJatJ8mplAqYUm2+taYb6hndZHn48OHNn0yhwK5du8yelBzYusnygCU7W0w97ODujCMLRtnkhdbY5nsDbu+Ab54dYsEZNe/vn6bg5z8um3Ts+w+HIy6UVRCJiORu5uYj2JZueqphU42SB3TviN9yCpF85gq0OsCzjTOKblbicE4h0v4sRpXGuitSTgogvHtHDArwwuDAzqyYSGYbsmwnLhRXGn1c9htxDvm7J3mT5TNnziAgIAC7d++WZIJ1rV27FsuXL0d+fj769euH1atXIyIiotnxX3/9NRYuXIjc3FwEBQXhrbfeQlxcXO3XdTod4uPjsXHjRhQVFWHIkCFYt24dgoKCAAC5ubl4/fXXsWvXLuTn58PPzw9TpkzB/Pnz4eLiIvn3Zwu2/JWO6tEJbZyVuFkldj/kyLkibDt2EeP7+Vl4Zo19+HgE/v7pb/j5D+PLpS747neMDvF1yBcQIqLWIiH9okmBl7OypsfllKjuzQYyQ4I6Y0hQ50aP65s278++jItF5bhZpcGuE5csGpBV64CU3GtIyb2GtbuzuSJGZhm74heTAq/Vk/u3+t834U0vQUFBuHz51grBxIkTUVBQYPYEvvzyS8yZMwfx8fFITU1Fv379MHr0aFy61PTF8IEDBzB58mRMnToVR48exYQJEzBhwgRkZGTUjnn77bexatUqrF+/HocOHULbtm0xevRolJfX7IE6ceIEtFotPvjgAxw/fhzvvfce1q9fj1dffdXs78caRApuXLNRwQ2gZhn6mWGBRh1jy2qCHz4+CCsnhhl9XGFZFasgEhHJmEarwz++Mb6QWFyID04sicO6KQMwpGdnoy8mVUoFhgR1xtzYO7FiUn988OhAnHh9DGaPDDJ6P7KpuD+MTPW3jw/heH6p0cd5tnGyyY12eyOcdqhUKmsbLQNA+/btcezYMfTo0cOsCURGRmLQoEFYs2YNgJo+Yt26dcPMmTPxyiuvNBo/ceJElJaW4ocffqh9LCoqCmFhYVi/fj10Oh38/Pzw4osv4qWXXgIAFBcXw8fHB5988gkmTZrU5DyWL1+OdevW4cyZM0LztmXa4fdpFzBLYK/SyklhNsup1Wh1CH0tEaWV4tnAL8T0wqyYIAvOqmVbUy/g+a/SjD7OzUmJd//aD3GhfEEhIpKTlT+fwns/G9c+Z9pd/pg/to+FZnRrVew/B3MtvhrWEFfDyJDF2zLw8f6zJh3rolLgj9fHOOzvlmhsYJ3bK82orKzEkSNHEBMTU/uYUqlETEwMkpOTmzwmOTm53ngAGD16dO34nJwc5Ofn1xvj6emJyMjIZs8J1ARoXl7NNyWuqKhASUlJvQ9bseeCG3oqpQLL/9LPqGNWJZ2y6V23+8K7IOZO43uAlVdr8ezmo1iWkGmBWRERkSVotDp88KvYDVcAcHNW4v2H+1s08AJurYrpV8M+nxqJZ+/pgQj/jnCy8EUrV8OoJa//cNzkwAsAKjU1NxZaO+HgS6FQQKFQNHrMHFeuXIFGo4GPT/0mbT4+PsjPbzr/Oj8/v8Xx+v8ac86srCysXr0aTz/9dLNzXbZsGTw9PWs/unXr1vI3Z0ERAV5Qe7o1u69LAUDt6YaIgOaDSWuIC/XD1KHdhcdrdMBf1x+w4IwM+/DxCMTc6W3SsR/8mmOTxtFERGS81UmnUVapERrr5qxEevxoq2c41E1P/OqZwTi5xDqpifpqiewdRnqLtx2XpPH4/mzTipw5EuGCGzqdDk888QRcXV0BAOXl5XjmmWcalZr/9ttvpZ2hhV24cAGxsbF46KGHMG3atGbHzZs3D3PmzKn9vKSkxGYBmEqpQPz4YEzflAoFgLovh/qALH58sF0s6y4cF4KDZwpx/OJ1ofG2LL6h9+Hjg/DuTyexyoQeZCzCQdQ0jVaHlJxCXLpeDu/2NTeH+HdCtpKQfhErk8TTDd99KAwuVtqL1RKVUoHZo3ph5sig2tTEn/8ogMaUet+C9Kthq3dlYVSwDx6N9melxFbmbx+nYNdJaYKm32xUj8CeCAdfjz/+eL3Pp0yZYvaTd+7cGSqVqlHhjoKCAvj6+jZ5jK+vb4vj9f8tKCiAWq2uNyYsLKzecRcvXsTw4cMxePBgbNiwocW5urq61gae9iA2RI11U8KxeFsm8opvNVP29XRD/PhgxIbYTwn0BWP7YPLGg8LjX/jyKOL6qm36wj4rphc+O3gW1wwUNmlIX4Tj7b/04xsT0f8kZuQ1eq1S2+FrFbUOiRl5eHbzUeHx40LVdtdWRL8iNiSoMzRaHVYnncb6Pdkor7ZcFFa3d5izEhh5JwOx1mDcql+RIXgDXcSxP4uh0epa9e+M0X2+pBYZGYmIiAisXr0aQE3Bjdtvvx0zZsxotuBGWVkZtm3bVvvY4MGDERoaWq/gxksvvYQXX3wRQM0qlbe3d72CGxcuXMDw4cMxYMAAbNq0CSqVcT26bVlwo67Kai0+S87F2cIydPdyx6PR/nZxd64ujVaHgUt2GhXIjOurxppHwi04K8MS0i8a9QZdF4twENVIzMjD9E2paPhGo3/bXTclnAEYWY1In8y62jgrkbE4VhYXirYq1MEiHY4rbuUeZObdkPy8n0+NbLIFg9yJxgY2D76+/PJLPP744/jggw8QERGBFStW4KuvvsKJEyfg4+ODxx57DF26dMGyZcsA1JSaHzZsGN58802MHTsWW7ZswRtvvIHU1FSEhIQAAN566y28+eab+PTTTxEQEICFCxciPT0dmZmZcHNzw4ULF3DPPfege/fu+PTTT+sFXs2tuDVkD8GXnO4mmxLInFoyxuaB5LKETHzwa47Jxz99dwDmxQVLOCMi+dBodRj61q56r1F1KVCzWr/v5RG8aCOrMLa6oa2r8JpKH4htOpSL3ScuW3RFTE+lANMSHYRGq0Pkkp9wpazaIud/9p4emBt7p0XObUuSN1m2lIkTJ+Ly5ctYtGgR8vPzERYWhsTExNqCGefOnYNSeesCfPDgwdi8eTMWLFiAV199FUFBQfjuu+9qAy8AmDt3LkpLS/HUU0+hqKgIQ4cORWJiItzcaqr/7dy5E1lZWcjKykLXrl3rzcfGsaiw5u4m5xeXY/qmVLu7mxwX6oep5wrx0T7xKjnjVu3FT3OGWXBWhs2LC0a/rh0x56s0k968Pvg1B/26drS7lBUia0jJKWw28AJq9qvmFZcjJacQ0YGdrDcxapU0Wh0+3p8rPL6DuzNmjOhpuQlZUMO0RGvsD2NaomNISM/Ds5tTLfocrX3fl81XvuTKlitfcr6b/MDafUg9Xyw8fvXk/nbRkE+j1WHuf4/hm9QLRh/r5e6M3xaMsrt/CyJLk0NPQmo9krOvGrX/eL2d3cSUgrX2h9XFtET5eP2HTHy0z/RsnzbOStysMvx75aj9vmTR54tMY8zdZHvz9fQhUBnxt/bCl0ftorytSqnA23/ph47uzkYfW1hWhVVGVNUichRy6ElIrcfPmU23m2lIoQDef9jxAi/gVrXE4/+MxedTIzG6jw9UFr4SrNs77N0fT9jFezo19rePU8wKvPqo2+FvQwOExrb2fl8MvmTo0vXmAy9TxlmTSqnAyolhwuOrtcDzFl7+FqVSKrB0QojhgU1YmXQaz31+mG861KrIpSchOT6NVof/SxPLXHh+RJDDp4rXbeR8akmc1XqHrdqdjaBX2cDZnmi0Otzz9i6zSsmHqNth+6xhGBwoXkSjNff7YvAlQ3K/mzwurAt6+bQ1PPB/tmfkY9uxixackbi4UD88fbfYnZ2Gtv9egD6LEpGQbh/fC5Gl6XsSAmgUgNlbT0JybCk5hSgsNVzhsJ2rE54fKb8CG+aw9mqYFrcaOPdewEDMlrYdu4jAVxOQW3jT5HOMuKMzfphVsz8/qkcnOAm+nLfmfV8MvmQoIsALHQykv3V0d7bru8k/zLzbqPEzvziKxIw8C83GOPPigvH+w+Em3SUsr9bi2c1HsSwh0wIzI7I/+p6Evp71bwb5errZXWEgclyiKYd/Hdi11d4MsMVqWJWWgZgtVFZrMerdXzDzC9Pa6eg9OaQ7/v1kZO3nKqUC/bt3FDpW3++rNbJ5tUOyDHv/dXZxUmJsXx9s/73A8OD/efmbdIwK9rWLN8a4UDVGh/iaXISDVRCpNYkNUWNUsC9Scgpx6Xo5vNvXpBraw98yOT5jUg5HBYu1m3F0+tWwmSODrNY7TB+IJR4vgEoJxPT2xmODA1gtUUIarQ4zPj+CHcfFr72aM+0uf8wf26fR4xEBXvgt95rB4/X7vhyx35chXPmSoZScQoMNIovKquyy4EZdqyYPMKr4RvHNaszaYt5dGimZU4QDABZ893urvetDrY9KqUB0YCfcH9YF0YG8mCLrEU057NTWxa4zRmyh7mrYidfHWK1Ih0YL/Jh5iStiEtp27CJ6vpogSeD1/sP9mwy8ABi17yv5zBWz5yJHDL5kSM4FN+oytvgGAPyQnoeEdPtIPwTMK8LBKohERJYnmnJ4f5gfbwq0wBZpiUD91MRe8xNw35q92PjrGVRaqVS+3FVWaxHzzm7M/OKo2VlR3Tu6IfuNOMSFNt8CKKpHJ7ioxM7XWmNpBl8yJPeCG3UZW3wDAJ7/ItWu7n6ZU4SDVRCJiCwnMSMPHwk2VmbKobiminQ4G5PKYiKNDkj/swRLE/5ArwU7MPKd3Vj+4wmuijWg0eqw9+RljHxnN3ot2IGsy2VmnzNE3Q57Xh5p8AaFSqnAOMEtFfkttE1yZGyybCJbNlmurNai98IdLd4xUCqAE6+PgYsV7kqZq7Jai14Ldhh1zIDbO+CbZ4dYaEamSUjPwwtfHkWFCTnxbk5KvPvXfi3eTSIiInEarQ5D39rVYl9MPbWnG/a9PIIrX2bQaHW1+8N2ZhZYfVWD+8Rq/g1W/HQSa/dkS/rzH9m7Mz56ItLwwP9Z/uMJrN2dbXCcm5MSx/8Z6zD/Vmyy7MCOnL1m8I9Kq6sZJwcuTkqjV46OnCvC90eNL3RhSXGhamS+Pgbj+hpfRENfBXHp9uMWmBkRUeuTklMoFHgBbHkghbppiaeXxpn0XmiOuvvEWlt6YmW1FnO+PIrAVxOw+hdpA681k8KMCrwAQNFsd8f6yqu1rbLZMqsdypCj7Pmqa15cMP68VmZU9cNZX6bBWaW0q4qBKqUCax4JR8+dp7DChP1cG/fmQqsDFo5reiMrERGJEd3r9bch/mx5IDH9e+G71VrM+zYd36ddRLUVl8L06Yn6FEW1hwv8OrqjW0d3PBjeFYN7dpZ9sK3R6nDg9BW89kMGsiVIK2zI38sNSS+ZthocHdgJa3ZnCY3dn3251VU8ZPAlQ46056uuVZMH4JcTiSitEr9L9ezmVKxX2l+voJkjg/Bpci6uGahK2ZSP9uUCYABGRGQqlpe3Dy5OSrzz1zC8/Zd+VitZ35S8kkrklVTiyNkifJd2EQoA/p3awK+DO/p17YAhQZ1lkaqoD7hW7jqFI2eLLNZW6MkhtyN+fF+Tj9c3W64WmGBrbLbM4EuGIgK8oPZ0Q35xeZN/eArUNDCVW8lclVKB5Q/1w7ObjSsnb0/9v/T0VRCN/V70GIAREZmO5eXtiz4lcUhQ53p7w2wRiAE1vVBzrt5EztWb2J99Fe/vyYYCQJC3O9q5OaONs5NdBGWV1Vp8vP8MfszIR87VUhSVVVu0j6uLClgxsb/Z+8/1zZZF+n3pmy3b0zWcpTH4kiGVUoH48cGYvikVCtRvqKz/1ZVr/npcqB+mnivER/vOCh9TfLMaz3+RirWPDLDgzIwXF+qHp/8swge/5ph0/Ef7cqHV6RA/3rRS9kRErZVo2j3Ly1tfU4HY8p9OIO18sU3npQNw6tKt9L2GQVlbVydUaWqKs0QEdMLjg/0lLWpWN9AquF6O0nINisqrJTt/SzzaqLB28gBJ0zHZbLl5rHZoIltWO9RLzMjD4m2Z9TYUqz3dED8+2O7S8Iw1dtWvOH7xulHHTB3qb5crReZUQQSAkb1vw0dPREg8KyIix5WcfRWTNx40OO6LaVGIDuxkhRmRIZXVWnx6IAfbjl1EZt51q+4RM9VtbZ3g7dEGLioFKjW6Jv9bUa1FlUYLHXRwdXJq9JiLSoWLxeUoummdQKuhVX/th/vCu0p+3v1ZV/DIh4eExs4YHoiXRveWfA7WJhobMPgykT0EX0DNi9Vnybk4W1iG7l7ueDRa2jsxtiL6xtnQtLsCMH9ssAVmZB6NVodZXxzFD7+b1iA6vJsnvp4+hHdoiYgEJKRfNJj2zfLy9sseUhMdXXg3D3w9fajFfv81Wh3uXJiASo3hsc/eE4i5sa0n+GLaoYw1tfL14b4ch1j5igjwgq+HK/JLKow6buPeHPTr0gHjwuyrX5a+8lOciatgqeeLEfraj3jnr/1k/29LRGRJGq0Or2//w+C4hWPlmZ7fGjSVmvhpcg52nbgsixUxe3anTzt8+9xQtHFRWfR59M2Wvz1q+KZza2u2LP8lklYqMSMP0zelNuphkl9cjumbUpGYYdoKi71QKRV47T7TUghnbDmKhHT7/P71vcDGhhhfXau0UoNnHODflojIkkT7e3Vs62KF2ZC59IHYhscG4eSSMfh8aiSevacHAm9zt/XUZOWBMD+cWjIGO14YZvHAS0/dQezfKOH3PGhaUVDN4EuGNFodFm/LbLLijf6xxdsyZf+LHBuixvsP9zfp2Gc322+QolIqsHbKAEwd6m/S8S9+ldYqmkYSEZnCEXthUg19IDY39k4kvTgcp5aMwfy43gjt4gEnrmI2ogAw855AZL8Rh3cn9bf6thQ2W24agy8ZMnRXTwcgr7gcKQ7QOyEu1A9rJpkWgD23OdWug5SF4/qYFICVVmrRJz4RCekXpZ8UEZHM5V4pFRont16Y1JiLkxLT7g7E1pl31a6K3Rvs3eoDscDObfHZ3yKQ9UYcXoztbbP0WmOK2ezPvmzBmdgX7vmSodZ2V29cmB9+v2h8yXaNFghetANrHra/Jsx6C8f1gVanw8f7xUvrA0CVRodnNx/F2N8vYtXkAdy3QESEmsyQL1LOGRynlmEvTGpZU/vE9mdfxp+FZThZcANZl29AY7/3Y82mAPD/wvzw5l/62U3hNWOaLV+4dtPyE7ITDL5kSPRunSPd1ZsXF4y+fh0wY4txTYurtcAzm1Lx/sPmNw20lPjxITh3tQxJJ4y/67P99wIk/ZGId//az26/PyIia0nJKRQq1DRp0O28aeXA6gZievqAbG/WJaSfL0bW5Ru4dL3ShrM0X8c2zri71234y4CukvbokooxzZYVCvuauyUx+JKhiAAvdHB3RlFZVbNjOro7O9xdPX0FQ2MDMAB4dvNRvA8F4kLtcwXsoyciMPWTFJMCsPJqLVfBiIggnvHh35nFGlqbpgIyfW+xlJxClJZXAQqFXQdlbV1U6O3bHqP7+OKJIQF2s8LVkoH+YsHXzSqBmvQOgsGXg5J3qY3mjQvzw7EL17Bxb67Rxz67ORXvw35XwD56IgKv/5CJj/YZl16px1UwImrtuN+LjKHfMzbt7sB6jzcVlOUV38TZwpuwVi0zn3bOuM2jzf9SZDvh8cHy7OPq5e4qNO7XU5eh0epaxQ1kBl8ylJJT2OKqFwAUlVUhJafQqM2OcjF/bB9odcBH+3KNPtbeV8AWjgtG/67Gp1fq6VfBpp2/hvljTSvVT0QkR4kZeXjv59MtjlEA8OV+LzKguaCsYerizapqVFbr4KJSoFLT9H8rqrWo0mihgw6uTk6NHnNRqVCl0UKhVOBOX0+7TSE0Vef2YsHXzaqaiod1VyYdFYMvGWptBTeaYmqhCqBmBWy90n6LcJiTXqm3cW8uLly7idUPMw2RiByfvgWLiPjxbK5MpmkqdZFa5ushvsq8P/tyq/jZym/9klplwY2mxI8Pwcjet5l07Ew7L0M/LswPT98dYNY5EjIK0HvBDqzYeVL2Pd+IiFoi2lh5dkwvu73xRuSIIgK84OokdrOjtVQ8ZPAlQxEBXlB7thxYtZYyuh89EWFSAFalBfrEJ9ptI2agpsLj+w+Hw1Vl+h3aKq0OK5Ky0GcR+4KRbWi0OiRnX8X3aReQnH2VNwLIIlhog8g+qZQK9O3iaetp2BUGXzKkUipwX7+W79zd10/datIqPnoiAk8O8Tf6uCqNDs9sSrXroCQuVI3M18dgXF/z7tTq94I99/lhXvyS1SRm5GHoW7sweeNBzNqShskbD2LoW7vs+qYHyRMzQojsV9eOYjc9RFavHQGDLxnSaHXYeqzli5etx/Ja1UV2/Pg+mDrU36Rjn918FD+k2W8AplIqsOaRcLNXwYCaiohMRSRrSMzIw/RNqY3eTPOLyzF9UyoDMJKUvgVLcxRoPRkhRPamS8c2QuPS/yxuFdcmDL5kSCS3Pa+4HCk5hVaakX1YOM70AGzGlqNYliC2WdtWpFoFYyoiWZq++EFTb6H6xxZvy2wVb7JkHTsz81usAqwDC20Q2crgQLEiGuXVNRUPHR2DLxlitcPmmROAffBrDramXpB2QhKTchWMqYhkKYZuEOnQOm8QkWWIVDrs4O6MUcG+VpoREdUV1aMTXASvWfZnX7bwbGyPwZcMMbe9ZeYEYM9/lYbXfzgu7YQsQL8KNjbE/IuJ7b8XcBWMJMUbRGRNItkg+t6XRGR9KqUC/bqKFd1oDRUPGXzJkL7aYXP3EJjbXhOAPTmku0nHfrQvFw+8v8/uV4NUSgXWThmAaXeZV5IeuLUK9uTHh1iRjszGG0RkTQz2ieyfXwexfV8Xixh8kR1SKRWIHx8MAI0CMP3nzG2v6QMWc6e3ScemnitG8MIdslgNmj+2piS9m5P5f867T17B5I0HMWjpTll872SfeIOIrInBPpH9UyjErkmPtYKiGwy+ZCo2RI11U8Lh26Dfl6+nG9ZNCWcTyf/58PFBJq+AVWh0eHbzUSzdLo80xOP/jMXskUEQ7GXYosLSKu4HI5PxBhFZEysdEtk/0YqHlRqdwxfdUOh0Ol5ZmaCkpASenp4oLi6Gh4eHzeah0eqQklOIS9fL4d2+5s2FFzSNvf5DJj7al2Py8XEhPlj98ABZ/Gw1Wh1mfXEUP/wuTSlvZ6UCzw0PxMyRvWTx/ZP9SMzIw+JtmfX246g93RA/Ppg3iEgyiRl5eGZTaotj1vOmJJFN7c+6gkc+PCQ09tl7emBu7J0WnpH0RGMDBl8mspfgq7Jai8+Sc3G2sAzdvdzxaLQ/XCRIP3NES7cfx8a9uSYf7+akxLt/7Ye4UD/pJmVBCel5mPNVGsqrtZKcT27fP9kH3iAiS9JodRj61q4WC250cHfGkQWj+HtHZEMarQ53zE9AtUDUcX8/NVZODrf8pCTG4MvC7CH4WpaQiY17c1A3K0ypAKbdFYB5ccE2mZO9+/7oBcz6Ms2sc0y7yx/zx/aRZkIWptHqsDrpNNbsOi30gidibF8frJosj1VAInJsydlXMXnjQYPjvpgWhejATlaYERE15y/r9uPw2SKD4wZ174Cvpw+x/IQkJhobcIlEppYlZOKDX+sHXgCg1dX0q7L3hsG2cn//Lnj6bvOqA27cm4tnN8ljL5RKqcDsUb1wcmmc2c2Z9bb/XoDeC3Zgxc6TsvgZEJHjYqVDIvno2tFdaJyjF91g8CVDldVabNzb8v6ljXtzUClRupmjmRdXUx3QnMIUCRkFsqmGCEjbnBkAqrQ6rEjKQu8FO7B4awbL0xORTbDSIZF8sOhGDQZfMvRZcm6jFa+GtLqacdS0uFA1Ti6Nw5g+PiafQ18NUU4VAfXNmaVaBavS6vDxgbMsT09ENsG2BkTyMTiws/DY5DNXLDgT22LwJUNnC8skHddaqZQKrHt0oNlNirf/XoC+8YlIzJCmuqCl1V0F82rrItl5WZ6eiKxNpVTgvn5qtPSKw7YGRPYhqkcnuKjExjryZQSDLxnq7iWWMys6rrWbPzYYayb1N+scZVVaPLMpVVb7oOJC1fhtfgy+mBaF4XfcJtl5t/9egD6LErkKRkQWl5iRhw2/Np+G/9TdASwxT2QnVEoFxoWK/T16tmm+d5/cMfiSoUej/WHoJp5SUTOOxIwL88P7D5tf1nRFUhb6xCfih7QLEszK8lRKBaIDO+HjJyPw/sPhcJOoTUF5tZarYERkURqtDou3Zba46rX1WB5fg4jsiI+n2L6vHTLJJjIFgy8ZcnFSGkyVm3ZXAPt9GSkuVI31U8Lh6eZk1nnKq7SYsSUND7y/T1Zv+nGhahz/ZyxmjwwyqxhJXTWVERMwfdMR7M+6IqufBxHZt5Scwhb7ewFAXnE5UnIKrTQjIjIkr0is8mja+WKHLRzHq3OZmhcXjKfvDmi0AqZUAE/fzT5fpooNUSN10b2YPTLI7HOlnitGr/kJskpFtERp+iotsCMjH498eAihi39kOiIRSYJl5onkR7TiIQB8eqDlyt5yxSbLJrKHJstATdn5z5JzcbawDN293PFotD9XvCSSmJGHF75Mw80q8++8uKoUeG9iGOJC/SSYmfUkpOdhzldpKJf47hMbNRORudhgmUh+9mddwSMfHhIaO+pOb2x8fJCFZyQdNlluJVRKBYL9PDGge0cE+3nyYlZCsSFqZCyOlWQFSF+WfsLavbJKv6ubiugs4e8WGzUTkblYZp5IfqJ6dDJYt0DvvINW7ebKl4nsYeUrMSMPi7dl1st5V3u6IX58MKs7SSwhPQ8vfHkUFRpp/lzcnJX414OhGBfWRZLzWYNGq8PqpNP4cN8Z3KjQSHZeZyUQE+yLKVHdEdWjE28gEJGwhPQ8PLs5tdHj+leRdVPC+X5IZGceWrcfv50tMjjORaXAH6+Pkc11gWhswODLRLYOvhIz8jB9U2qjKk98w7EcjVaH5zenYntGvmTn9O/UBkv/X6isgg6NVoeUnEJs+DUbu09elvTcbV1VWP5gqOzSM4nI+pq6AanHG5FE9mv5jyewdne20NjPp0ZiSJB4c2ZbYtqhA2upvK7+scXbMpnOJTGVUoG1UwaY3ZS5rtyrN/HIh4cQvEg+KXgNy9O7qqQLGksrNCxRT0QG6W9ANlftcOHYOxl4EdmpwYHiwdT+bGlv8toDBl8yZKi8rg4sr2tJ88cG4/2Hw9HO1byS9HVVVOuwIikLQa8m4JnPDstmX1hcqBqZr4+RrDKiHkvUE1FzDPX3UgB4ffsffN0gslNRPToJt7S5cO2mZSdjAwy+ZIjldW0vLlSNY/H34vOpkfDv5C7ZebUAEo8XyGo1TKVUYM0j4ZIHpHVL1MvlZ0FElscbkETyplIqEHZ7B1tPw2YYfMmQd3s3SceRaVRKBYYEdcYv/xiO1ZP7Q+oK//rVsF7z5bEaVjcgHRPiI1mjZuDWz6L3gh1YvDUDydlX7fpnQUSWwxuQRPLXpYNYv6+LRY638iXdbWqyGn153Zbu/LG8rnWN7+eHuL5qzPriKH74PU/Sc2t0NathiccL4KpSYPo9gZg5spddFujQB6RDgjpDo9VJ/vOo0urw8YGz+PjAWbR1VWHa0AC7/VkQkWXwBiSR/CkUYu/bx/4shkarc6j3ea58yZBKqcB9/VreY3NfP7VD/aLKQd30OzcLNbqu0NxaAbL3NDxL/zxKKzSy+VkQkXTY34tI/rp0FFv5qtTocDD7qoVnY10MvmRIo9Vh67GWVxO2HsvjxaiN1G1MbKkgrEorn5RES/889D8LFuggah1USgXixwc3+TV9QBY/Ppg3IInsmDEVD/dmXbLgTKyPfb5MZMs+X8nZVzF540GD476YFoXowE5WmBE1R6OtuWMz/7vfkXvVsp3anZXAyDt98Gi0v932DdP/PDYdysXO4wWottCrj6uTAtOH2W96JhGZJzEjD698+zuKyqrqPd7R3RnLHujLMvNEdk6j1SHo1QRoBcYO7uGFzU9FW3xO5hKNDbjnS4a42Vg+6hbl2HbsIv7x32MorxJ5qTFelbbO3jA7DT4svSdMT1+gY+3uLMQE+2JKVHe7DUgdmb4h96Xr5fBuX5MGxn8DMpe+x1dT926uNQjGiMg+qZQKdO/UBjlXDRfUyCtxrOtZBl8yxM3G8qQvynEw+yqW/3QCaeeLLfZc+uBjVVIW7u1jn6th+j1hcel5mPtNOm5UVEv+HPpy9Tsy8u02IHVUiRl5WLwts15hILWnG+LHB3NVgkwm0uNr8bZMjAr25d85kZ3z6+AuFHydL7zpUEU3uOdLhvSbjVvCzcb2Sb/y891zQyXvi9UUOfQNa1ii3tlCL676gDR44Q6s/PmU3f0cHIl+ZaJhRdb84nJM35SKxAzpVzupdWCPLyLH0a9rB6Fx1VrHKrrB4EuGWO3QMdQNOp69pwcGde8AlQX/Iu25b5g+KF03ZSBOLBmD2SODLBeEaXR47+fTdhuMyl1LKxP6xxZvy+TPnUzCtHsixzEkqHUW3bB58LV27Vr4+/vDzc0NkZGRSElJaXH8119/jd69e8PNzQ19+/ZFQkJCva/rdDosWrQIarUabdq0QUxMDE6fPl1vzNKlSzF48GC4u7ujQ4cOUn9LFsdqh45DH3TMjb0TX08fglNL4iwaeAC3+oY98uEh3DE/AQ+tP4DlP56wm2BMpVRg9qhetUFYO1eVRZ6HjZstgysTZElMuydyHFE9OgkHIukW3KphbTYNvr788kvMmTMH8fHxSE1NRb9+/TB69GhcutR0dHvgwAFMnjwZU6dOxdGjRzFhwgRMmDABGRkZtWPefvttrFq1CuvXr8ehQ4fQtm1bjB49GuXlty4GKisr8dBDD2H69OkW/x4twdDFDcCLG7lqGHi4WqhUvV61Dvgt9xrW7s62u9RE/c/iWPxofDEtCk8O7g5nlfRBqb5x8+SNBxG6+Ee7+f7liisTZEns8UXkOPRFN0RkXb5h4dlYj01LzUdGRmLQoEFYs2YNAECr1aJbt26YOXMmXnnllUbjJ06ciNLSUvzwww+1j0VFRSEsLAzr16+HTqeDn58fXnzxRbz00ksAgOLiYvj4+OCTTz7BpEmT6p3vk08+wezZs1FUVGT03G1Zav77tAuYtSXN4LiVk8Jwf1gXy0+ILEZfmv0/B3Px8x8F0FimUGIjKgUwKtj+CnVotDqsTjqN9XuyUV5tuR+GsxKskmgitsIgS2uu2qH+r3TdlHAWdSGSiUc2HsR+wf1cp5aMgYuFb0qbQzQ2sNl3UFlZiSNHjiAmJubWZJRKxMTEIDk5ucljkpOT640HgNGjR9eOz8nJQX5+fr0xnp6eiIyMbPacoioqKlBSUlLvw1aYdtF66NMSP3h0YG1KoqUaN9dlr6mJ+tWw4/+MtWiBDn2VRHtbDZQDrkyQNXi6Ozd6rIO7MwMvIpkRLboBAJ8eyLHcRKzIZsHXlStXoNFo4OPjU+9xHx8f5OfnN3lMfn5+i+P1/zXmnKKWLVsGT0/P2o9u3bqZdT5z8OKmdWoYeIzu42ORNLyGGqYm9l5g+4IdTRXosFRQemtvWAKmbzpi8wDU3qmUCsSPDwaARq9R+s/jxwdzNZFMol/1athcGWCPLyI5MqbohqNsp2GfL0Hz5s3DnDlzaj8vKSmxWQCmv7iZvikVCqBe6gUvbhxfw0bF1ugbVlfdZs4uKgX6dfVEl47u6NKxDQYHdrZ6mp4+KJ05MggHs69i06Fc/Jx5CVUSB0h1e4a5OSsxeVA33NtHzcbBTYgNUWPdlPBGfb582eeLzMAeX0SOJ6pHJygVgMhbdpkF+oHags2Cr86dO0OlUqGgoKDe4wUFBfD19W3yGF9f3xbH6/9bUFAAtVpdb0xYWJhZ83V1dYWrq6tZ55ASL24IqBuIDUWCBZsVN6dSo8NvZ4vw29kiAMDa3dlwUgBht3dAVysHZA2DUkvuDSuv0uLjA2fx8YGz8GrrjCX3hyAu1E/y55Gz2BA1RgX7IiWnEJeul8O7vRsDVTKLMZU0uZ+QSB5USgX6d/XAkfOGt/NUWHCvtzXZLPhycXHBgAEDkJSUhAkTJgCoKbiRlJSEGTNmNHlMdHQ0kpKSMHv27NrHdu7ciejoaABAQEAAfH19kZSUVBtslZSU4NChQ7KtbNgSXtxQXXGhaowO8cXB7KvYn30Zv+UUIvV8kdWKdOhV64DDZ4twuEFA1r97R0QEeFklGGu4Gvavn07gqIVWBgtLq/Ds5qMY+/tFrJo8gH9/daiUCl4Ek2RYSZPIMbm5NN7D2ZSaaxqd7N9nbZp2OGfOHDz++OMYOHAgIiIisGLFCpSWluLJJ58EADz22GPo0qULli1bBgCYNWsWhg0bhnfeeQdjx47Fli1bcPjwYWzYsAEAoFAoMHv2bCxZsgRBQUEICAjAwoUL4efnVxvgAcC5c+dQWFiIc+fOQaPRIC0tDQDQs2dPtGvXzqo/AyIp1V39AaxXHdAQ/b4x/d4xfbqiX4c2UCgUFlsha7gyOOerNIv9HLb/XoCfM3fg2eE9MWNEkOzfHIjsDYtNETkmd8F+nlodcOD0Fdx1x20WnpFl2bTUPACsWbMGy5cvR35+PsLCwrBq1SpERkYCAO655x74+/vjk08+qR3/9ddfY8GCBcjNzUVQUBDefvttxMXF1X5dp9MhPj4eGzZsQFFREYYOHYr3338fvXr1qh3zxBNP4NNPP200l927d+Oee+4RmrctS83rJWbk4bWtx5FfUlH7mK+HK167rw/TDqmeuiXrd524hCqNfRaMcFYCI3p7I7y7F0rKq6BAzcqJVEGZPhj9cN8Z3KjQSDDjprk6KTB9WCBmjuzFIIxIIhqtDkPf2oX84vIm930pUJN6v+/lEfy7I5KRjb+ewdKEP4TG3t9PjZWTwy08I9OIxgY2D77kytbBV2JGHp7ZlNrs19ez3C41Qx+I2TI10VhS7yPTaHVIySnET8fz8MVv51FeZZkfgKtKwZUwIgnpqx0CTRebYql5IvmprNai14IdQmN7dHbHrpeGW3hGpmHwZWG2DL40Wh0GLNnZZKldvQ7uzjiyYBQv+Mgge0lNNJZUlRb1wailqiQCQFtXFZY/GMqiHEQSSEjPw4LvM1BYWln7mJrFpohkLfqNn5FXJ5OrOU5K4OSSOLu8vmXwZWG2DL72n76CRz46ZHDc51MjjeqfQK2bXFITW+KiAsaFquHj2QZ5ReVGB2WWDkSn3eWP+WP7SH5eotYiMSOvUZVfVhwlkr9ZXxzF98cuCo3VX9/qs1jspeicaGzAPl8ylHzmivA4Bl8kqqn+YfrUxLQ/i2URjFVqgG+P5tV7bO3ubOG9ZJbuGbZxby5+y72Gf4zubfV+aERyp085bPjXeK20Cs9tPop1SgVXvohkqqtXG+Gxe7Mu4XpFVaMbMXJZAefKl4lsufL1rx9PYs3uLIPjZgzviZdG32GFGZGjqxuMHc69hmN/FjtEvw2RoMxSRTqYikgkTl9so7k+Xyy2QSRv+7Ou4JEPDWd1AcAdPu1wquBGoxsxtt77ybRDC7Np2qHgL+jnf4/EkJ5c+SLpyXVlTFRT6YtRAZ2gVCrw4d4z2H3ysmTPNT7UFysmhfOCkagFydlXMXnjQYPjvpgWxd5yRDKk0eoQ+GqC0FiloqbsfFNseSOGaYcOLKpHJ3Rwd26x4EZHd2dE9eAbEFlGU/3E9MHYhWs3cbHopqwDsubSF12dFLin120Y2L0D0s4Xo1qCdMRt6fnYm7UTbz7Q1+5TJYhshQ2WiRybSqlAt45uOH/N8N9wS2+9OgB5xeVIySm02xsxDL5kSKVU4M0H+rZYan7ZA315J52spmEwBjQOyPKKy2WfrlhRrcOPmZckP29RWRWe2ZTKFhFEzWCDZSLH19vXQyj4EmHPN2IYfMlUbIga66eE47Wtmcgvkd9mQ3J8IgGZ3FfIpDbnyzSM6O0DFyelradCZFciAryg9nQz2GA5IsDL2lMjIolEBHTCzj+kucFpzzdiuOfLRLZusqxnb2U2iYxVNyC7WFQOdQc3FBRXYPvvebJeJTPHIP+OGOjfER3auKDoZiUuXrsJhUIBdQc3eLm7onN7V/h68O+dWhc2WCZybMY0W26J2s73fDH4MpG9BF9EjqrhKhkAh0hdlJK7ixKxfXxqC4OoO7jVBmxNfW5OM2oie9BUny9mfBA5jrDXElFUbl5l4fcfDkdcqP1WO2TaIRHZpabSFgHHr7RojLJKbaPCIIas3Z0NF5UCYd06YECd1bXmgjeutJG90Gh18Gzjgrmj70BhaSW82vH3ksjReHu6oai81KxzdGzrItFsLIPBl8wx7ZBam+YqLSafuQKtDvBs44zUc9ew68SlVhuUGVKp0SEl9xpScq8ZdVw7VyWGBHZGGxcnBmpkVS2tePH3jMhx3OnriVMF5gVf9lxsA2DwJWtMvyASWyHjXjJp3KjQCld71KdEqju4Q/e/oJjpj2QK/V6vhrdS8ovLMX1TKvd6ETmQvwzoiu+PXTTrHPZcbAPgni+T2XrPV3NvRtx4TNQyBmX2o2H6Y0l5FXQ6oKO7C1fQCEDN3+vQt3bVu8lYly0bqhKR9IxpttyQrV8PuOfLgWm0OizeltlkuV39Y4u3ZWJUsC/fjIgaaG6lbPlD/ZpMX9xz6jLKqxiUWYJI+mNzRUX0gZpnG2eUlFdBAQWiAzvJYjWtqRsATe29q/s9NvU1OX3PpkrJKWw28ALk0VCViMSplAqoPVyRV1Jh1HH6V0A5pCIz+JIhQ29GAN+MiIzVUvpiSk4h8otv4sqNChSW3Sr9frNKw+DMwowpKrJmdxZcnRQYfoc3etzWrtmgpaWAprmvSXWeo+ev4ZcTl1Eu0Spr3e+5p3d7hwvGRPdu2PseDyISFxHQyejUQ18Zbbth8CVDdZsqSzGOiJqnUipavInR0irGxWs3WR7fyiqqdUg8XgCgwNZTsZra7/l4wf+CMSVG9PbGlKjusg/ERPdu2PseDyISZ+y+r8//Himr1zoGXzJUeENsKVZ0HBGZrrkVs7oa9izTN0z2cHPG14fP4cyVm1acMTm6imotdmTkY0dGPtq6qrD8wVDEhfrZelomiQjwgtrTDfnF5U2m2uv3eEQEeFl7akRkIYN7Nv9+2hStRiebwAtg8CVLXoL9C0THEZFltRSgTb+nJ5Zuz8TGvTk2mBk5utIKDZ7dfBTjM/KwYlK4rC5QgJq/nfjxwZi+KRUKoF4AJqc9HkQkTqVUIKCTO3KulgmNf/+X0xgc1Fk2rwOsdmgiW1Y7TM6+iskbDxoc98W0KO75IpKJH9IuYsaWo0YfNyFUDbVXmxb3JxXdrMSR3GtMf2zl5LwKxtYqRK3Lhj3ZeGPHCeHx9vB6IBobMPgykS2DL0Old4GaX0KW3iWSF1MCMAWA1ZP6Y1yY4Qtq0Sp7+s9vVmlwIPsqrpdXm/gdkT2adpc/5o/tY+tpGKVuM3W0giqPRK1dZbUWvRbsEB5vD62WGHxZmL32+QJqfgHZ54tInpYlZOKDX41PQXz67gDMiwuWfD5NVXtsKlC7UHQTv7VQMp7sy9i+vlg1WR5piFz1ImqdghfuQJkR1YTl0ueLwZeJbB18AXxDInJUpqYgvv9wOOJCbfO3r9HqMOTNXS1WWXV3ViCkSwemP9oJOaQhNnej0R7uchORZc37Jh1f/Hbe6ONste2GwZeF2UPwBdy6K33pejm829dUfJLDnUwiapkpAZibsxLp8aPh4qS00Kxapr9QBpoujKC/UG4u/bGkvApZl26wd5qV2WsaoqEUe1vf5SYiy7pZqcGdixKNPm7lpDDcH9bFAjNqmWhswGqHRER2aFyYH45duIaNe3OFjymv0iJ08Y9496F+NlnNiA1RY92U8EYr8g2bXxoqz193f4/WQCPj/OJy/JiZj9IKjVW+Rym5qhTo160DBvh3NKqRc0FxhaTf88a9ubhYVG53aYgpOYUt7m3WAcgrLkdKTiGLSxE5oDYuKrg7K1BWZdw6kb33/WPwJWNMOyRybDWrEQqjytCXV2nx7OajePrPIovsATMkNkSNUcG+Zq3Ii/ROq6vhvrSim00HLS0FNIa+JtV5SsqroJCgYETD7/nIuWtIyryEKq1pySzbf8/H/uydePOBvnbz/nHpevOBlynjiEh+nh/ZC28mnhQe7+XuYvd9/5h2aCJbpx0yD56o9ZDjHjCyPo1Wh9VJp7HulyxUaEx/a19vJ+8fbKtCRMZWPQy6zR07XxxuwRk1TzQ2sM3GADKLRqvD4m2ZTVY61D+2eFsmNCbeASUi+zIuzA9rJvU3+rg5X6ehkoUtWg2VUoHZo3oh8/UxGNvX1+TzvPj1Mbv4vYkI8ILa0w3NrQ0qUJPtYe93uYnIdC5OSnTrKJ5GmHNFrDGzLTH4kiFj8uCJyDGMC/PD+FDjLqj1e8AS0i9aaFZkj1RKBdY+MgDT7gow6fjSCg3CX9+JxIw8iWdmHJVSgfjxNamzDQMw/efx44Ptap8aEUlvx6xhwmOrdbCLm0ctYfAlQ8yDJ2qdVkwKRwd3Z6OO0e8Bm7n5CFfDW5n5Y4Px/sPhaOuiMvrYGxXVeGZTqs0DMH0RF1/P+ne+fT3dmF5P1Eq0c3MyKmD5eP8Zi81FCgy+ZEi0iou9V3shIuOolAq8+UBfk47dlp6PAUtsv5pB1hUXqkb6a6NNTkN85dvfbR60jwr2xb/+0g8zhgdixvCe+Pzvkdj38ggGXkStyF8HdRMe+9PxAgvOxHwMvmRoQPeOMJRloVTUjCMixxIbosb6KeHwbGN8sdqisiq7WM0g6zInDbGorAprdmVZYFZiEjPyMPStXXjko0NYszsba3Zn4aWvj2FnZr7N5kRE1hc/XrwXYfHNCgvOxHwMvmToyNlrMHQjUqurGUdEjic2RI3UhfciqodphQZe/ibd5qsZZH36NEQ3Z+Pe+t//Jcsmeyj0VX0b7nHOLy7HdN5EIGpV2rio0FbwtcvVyb47aTH4kiHu+SIilVKBz/8eZfQeMAAovlmNRz48yACsFYoLVSM9fjTauYpfnFRUa61egINVfYmooTt82wuNc3Wy7/DGvmdHTeKeLyICzNsDdvBMISshtlIuTkr866FQo46xdgEOVvUlooYqBfsXio6zFQZfMsTeJ0SkZ84esNIKDSshtlL635u2rsZVQrRWAQ5meBBRQ76erpKOsxUGXzLE3idEVJd+D9i4UNOqv21Lz+cqWCsUG6LG0YX3GpWiY60CHMzwIKKGIgM6SzrOVhh8yZS+94mPR/3o3sfDlb1PiFohlVKBNQ+Hm1RQAbi1CrZ0+/Emv67R6pCcfRX/l/onPtp7Bv939AKSs682WgXRj/s+remvk31xcVLi2XsCjTrmg1+zLf7vygwPImro8cH+UBhYV1AoasbZM/suB0ICmlv7IqLWKC5UjZhgH4Qu/hHlVcZXqNu4NxcXi8qxanJ47ep5QnoeFnyfgcLSykbj1Z5uiB8fjNgQNRIz8rB4W2a9vTp1v072acaIIHx8IBdFZVVC48sqNViVdBovjOplsTnpMzymb0qFAqhXeIMZHkStk4uTEk/dFYAPfs1pdsxTdwXAxc4Lbih0Oh1vS5qgpKQEnp6eKC4uhoeHh9WfX1+Ct+E/nv5tiKtfRK3b/2/v3qOiuu49gH9neAwPeYhUZjCToAR8oRBRCBprJBgohoQ0vRpjreaqxAr2JsQHahRjUkWT9FoLSmNd0d4bojEPYwzFGJR6oyhZAgIVqEYwmgCWEgGx8pp9/7BMMrycGeGcGfx+1mIpZ/aZ8zusvc7M7+x9fjuz6DsszSgwe39nlQ22PD0OWedrcLjozkUWXvjpcLx9ooLXJCuVVVKFJf+bb9I+qc8+hCeCvPspotuY0BNRZ5szz2PX/1UYLLukVACLpw7H6ugxssVlbG7A5MtMciZf7TqBR7Yc67ESlAKA2s0BX64K511BonvY5szzvd4h7EsKBdDTpwmvSdYhq6QKLx84h6bmdqP3eeGn/ftlp10ncPrrfyL3Ui0ABcJ8h+DhEUPYj4jucS1tOvxPbiUu193EAx5OmBfmI/uIF5OvfiZn8pX79T8xZ9fpO7Z7b/HDCPMdIkFERGSpMouqsOKDc2hqMf4LdX/hNcnytbTpMG7DETSbsKjyjucmINrMYi+94agXEVkTY3MDy54USd1iCV4iMlb0eA2KNkSaXQmxL/GaZPnMKcCReKAQLSYka8bomFrfeYZHdf0t/FrC9caIiPoaky8rxBK8RGSKH1dCdLY3bV2nvsRrknVICPeDu5Od0e1vteow4bWjfZYQtesEXv30fJfnB4EfCm+8+ul5VtIkIqvE5MsKdZTg7Q1L8BJRZx2jYDPHqSU9LsuCWxcbpQIpPx9n0j43mtuwpI9GpPIq6np8phm4nYBV1d9CXkXdXR+LiEhqTL6skI1SgScDe59C9GSghg8kE1EXNkoF0uYGY/HU4ZIcj2XBrVNUgAY7nnvI5MVLkj4qvusRKU6tJ6KBjMmXFWrXCRw61/vdxUPnqjglg4h6tHbmmH6Zhth5uprazYFl5q1U9Hhv/OHZh0za5/rNVqQeu3hXx+XUeiIayLjIshW605QM4IcpGawsRkQ9iR6vQWSAGr95Lx+fFVf3yXs62Crx7qJQ1N5oxlCX21MNOeJlvZ4I8saR81X4tMj4/rEj5yJ+/aiv2WWfO6bWV9ff6va5r46lCziNlYisEUe+rBCnZBBRX+nraYjVDc1QKhR4KmgYwny5HtNAsO3ZCSYV4Ghuu7sCHDZKBZJjbq8d1rn3cBorEVk7Jl9WiFMyiKivdUxD9HC27/Z1D2c7PD/5AaPe6y8lVcj9+p+c+jxAyFGAY8YYNV6M8IebI6exEtHAwkWWzSTnIsvtOoFHthy745SML1eF884gEZmkXSeQV1GH6vp/oa6pBR6DVFC73p7ilVdRZ9QC7x24IO7AklVShZcPnENTs/ELdrs52iJ/3eMmfRZ1t7iyu6Mdnp/ig4RwP36uEZFFMjY3YPJlJjmTL+CHBSh7Sr54Z5CI+tqdbvx01vEVmdejgaOlTYdxG46g2YRFlYO0blgVNdqo5/96+mxjXyIiS2dsbsBph1YqKkCDuJ8OR+fPMaUCiPvpcH44EVGf63gWx9g7dlwQd+Cxt1Vi6aO+Ju1TeKUec3adxvhXj2Db0fIe+wIXVyaiewGTLyuVVVKFt09UoPNnkBDA2ycq+mShSyKizqICNHgpws/o9lwQd+BJCPczqQBHh6bmdmzLvogx6/6C33/x9y5JFBdXJqJ7AZMvK8S7g0QkJx9PZ5P3YfXVgcOcAhw/1twu8N9fXEDw64YVEVnJl4juBUy+rBDvDhKRnMyppMrqqwNLVIAG6b+cAGeV+Yt0X7/ZalARkZV8iehewOTLCvHuIBHJKWS4BzycjZ92puGCuANSVIAGBeseh4Pd3X2VSPqoGO06oV9cuaeSHAqwLxGR9WPyZYV4d5CI5GSjVODpoGFGt+eCuAOXva0Sv/uPwLt6j+s3W5F67KLB4sqdcXFlIhoomHxZoY67g73h3UEi6k8RY9RGtXspwp/VVwe46PHeWDzV567eI+34BbxxpAyfFH4HZ5Vtl9fdnexYZp6IBgQmX1bIRqnAk4G9fwA9Gajh3UEi6jd3miIGAGpXFRLCH5QsJpLP2pljsXjqcLP3b2kXSDv+Nf5SUo0bzW1dXv/+ZuvdhEdEZDGYfFmhdp3AoXO9l5I/dK6K1Q6JqN/8eIpY5wRM8e+fDU+O5U2ge8jamWOw47kJ8HC27/P3VoBVfIloYGDyZYXuVO0QYLVDIup/UQEa7PzlBKg7TYNWuzlwitg9Knq8Bl+tjcB7ix/G85MfuOtiHB1YxZeIBoquE6vJ4rHaIRFZiqgADWaMUSOvog7XGm9hqMvt50054nXvslEqEOY7BGG+Q/DKE2Nx6kIt/nPvV2jtg1Erfq4RkbWziJGvtLQ0+Pj4wMHBAaGhocjLy+u1/YEDBzBq1Cg4ODhg3LhxyMzMNHhdCIH169dDo9HA0dERERERuHDhgkGburo6zJ07F66urnB3d8fChQtx48aNPj+3/sBqh0RkSTq+bD8VNAxhvkOYeJGejVKBqSN/0mfP/vFzjYisnezJ1/79+5GYmIjk5GTk5+cjMDAQkZGRuHbtWrftT506hTlz5mDhwoUoKChAbGwsYmNjUVJSom+zdetWbN++Henp6Thz5gycnZ0RGRmJW7d+uGM2d+5c/O1vf8PRo0dx+PBhnDhxAnFxcf1+vn2Ba6EQEZE1SQj3g7uT8WvDdYefa0Q0ECiEELI+vRoaGopJkyYhNTUVAKDT6aDVarFs2TIkJSV1aT979mw0NTXh8OHD+m0PP/wwgoKCkJ6eDiEEvL298fLLL2P58uUAgPr6enh5eWHPnj149tlnUVpaijFjxuCrr77CxIkTAQBZWVmIjo7G1atX4e3t3eW4zc3NaG5u1v/e0NAArVaL+vp6uLq69unfxBhZJVX49f/mA7g9F75DR0LG5y2IiMiSZJVUYcm/P7fM8VKEP/4rwq8PIyIi6jsNDQ1wc3O7Y24g68hXS0sLzp49i4iICP02pVKJiIgI5ObmdrtPbm6uQXsAiIyM1LevqKhAdXW1QRs3NzeEhobq2+Tm5sLd3V2feAFAREQElEolzpw50+1xN2/eDDc3N/2PVqs176T7CB90JyIiaxIVoMFLd5E8+Xg69WE0RETykLXgRm1tLdrb2+Hl5WWw3cvLC2VlZd3uU11d3W376upq/esd23prM3ToUIPXbW1t4eHhoW/T2erVq5GYmKj/vWPkS0580J2IiKxJQrgfMs58g5rG5js37oTPexHRQMBqh0ZSqVRQqVRyh9FFx4PuREREls5GqcCrT401afqhArdndfB5LyIaCGSddujp6QkbGxvU1NQYbK+pqYFare52H7Va3Wv7jn/v1KZzQY+2tjbU1dX1eFwiIiK6e1EBGqT/coJRBTg65nEkx4zhrA4iGhBkTb7s7e0RHByM7Oxs/TadTofs7GyEhYV1u09YWJhBewA4evSovv3w4cOhVqsN2jQ0NODMmTP6NmFhYbh+/TrOnj2rb3Ps2DHodDqEhob22fkRERFRV1EBGpx9ZQbeXRiKhOm+SJj+IF58zA9qVz7HTEQDm+zVDvfv34/58+fjj3/8I0JCQrBt2za8//77KCsrg5eXF371q19h2LBh2Lx5M4DbpeanTZuGlJQUzJw5E/v27cOmTZuQn5+PgIAAAMCWLVuQkpKCvXv3Yvjw4Vi3bh2Kiopw/vx5ODjcvrD/7Gc/Q01NDdLT09Ha2ornn38eEydOREZGhlFxG1vRhIiIiIzTrhN8jpmIrJKxuYHsz3zNnj0b//jHP7B+/XpUV1cjKCgIWVlZ+oIZ33zzDZTKHwboJk+ejIyMDLzyyitYs2YN/Pz8cPDgQX3iBQArV65EU1MT4uLicP36dTzyyCPIysrSJ14A8O677yIhIQGPPfYYlEolnnnmGWzfvl26EyciIiIDfI6ZiAY62Ue+rBVHvoiIiIiICLCSdb6IiIiIiIjuFUy+iIiIiIiIJMDki4iIiIiISAJMvoiIiIiIiCTA5IuIiIiIiEgCTL6IiIiIiIgkwOSLiIiIiIhIAky+iIiIiIiIJMDki4iIiIiISAJMvoiIiIiIiCTA5IuIiIiIiEgCTL6IiIiIiIgkYCt3ANZKCAEAaGhokDkSIiIiIiKSU0dO0JEj9ITJl5kaGxsBAFqtVuZIiIiIiIjIEjQ2NsLNza3H1xXiTukZdUun0+G7776Di4sLFAqFrLE0NDRAq9XiypUrcHV1lTUWsg7sM2Qq9hkyFfsMmYp9hkxlSX1GCIHGxkZ4e3tDqez5yS6OfJlJqVTivvvukzsMA66urrJ3PLIu7DNkKvYZMhX7DJmKfYZMZSl9prcRrw4suEFERERERCQBJl9EREREREQSYPI1AKhUKiQnJ0OlUskdClkJ9hkyFfsMmYp9hkzFPkOmssY+w4IbREREREREEuDIFxERERERkQSYfBEREREREUmAyRcREREREZEEmHwRERERERFJgMmXlUhLS4OPjw8cHBwQGhqKvLy8XtsfOHAAo0aNgoODA8aNG4fMzEyJIiVLYUqf2bVrF6ZOnYrBgwdj8ODBiIiIuGMfo4HH1OtMh3379kGhUCA2NrZ/AySLY2qfuX79OuLj46HRaKBSqeDv78/Pp3uMqX1m27ZtGDlyJBwdHaHVavHSSy/h1q1bEkVLcjpx4gRiYmLg7e0NhUKBgwcP3nGfnJwcTJgwASqVCg8++CD27NnT73GaismXFdi/fz8SExORnJyM/Px8BAYGIjIyEteuXeu2/alTpzBnzhwsXLgQBQUFiI2NRWxsLEpKSiSOnORiap/JycnBnDlzcPz4ceTm5kKr1eLxxx/Ht99+K3HkJBdT+0yHyspKLF++HFOnTpUoUrIUpvaZlpYWzJgxA5WVlfjggw9QXl6OXbt2YdiwYRJHTnIxtc9kZGQgKSkJycnJKC0txe7du7F//36sWbNG4shJDk1NTQgMDERaWppR7SsqKjBz5kxMnz4dhYWFePHFF7Fo0SIcOXKknyM1kSCLFxISIuLj4/W/t7e3C29vb7F58+Zu28+aNUvMnDnTYFtoaKh44YUX+jVOshym9pnO2trahIuLi9i7d29/hUgWxpw+09bWJiZPniz+9Kc/ifnz54unnnpKgkjJUpjaZ3bu3ClGjBghWlpapAqRLIypfSY+Pl6Eh4cbbEtMTBRTpkzp1zjJ8gAQH3/8ca9tVq5cKcaOHWuwbfbs2SIyMrIfIzMdR74sXEtLC86ePYuIiAj9NqVSiYiICOTm5na7T25urkF7AIiMjOyxPQ0s5vSZzm7evInW1lZ4eHj0V5hkQcztMxs3bsTQoUOxcOFCKcIkC2JOnzl06BDCwsIQHx8PLy8vBAQEYNOmTWhvb5cqbJKROX1m8uTJOHv2rH5q4qVLl5CZmYno6GhJYibrYi3ff23lDoB6V1tbi/b2dnh5eRls9/LyQllZWbf7VFdXd9u+urq63+Iky2FOn+ls1apV8Pb27nIRo4HJnD7z5ZdfYvfu3SgsLJQgQrI05vSZS5cu4dixY5g7dy4yMzNx8eJFLF26FK2trUhOTpYibJKROX3mueeeQ21tLR555BEIIdDW1oYlS5Zw2iF1q6fvvw0NDfjXv/4FR0dHmSIzxJEvIjKQkpKCffv24eOPP4aDg4Pc4ZAFamxsxLx587Br1y54enrKHQ5ZCZ1Oh6FDh+Ltt99GcHAwZs+ejbVr1yI9PV3u0MhC5eTkYNOmTdixYwfy8/Px0Ucf4bPPPsNrr70md2hEZuPIl4Xz9PSEjY0NampqDLbX1NRArVZ3u49arTapPQ0s5vSZDm+++SZSUlLwxRdfYPz48f0ZJlkQU/vM119/jcrKSsTExOi36XQ6AICtrS3Ky8vh6+vbv0GTrMy5zmg0GtjZ2cHGxka/bfTo0aiurkZLSwvs7e37NWaSlzl9Zt26dZg3bx4WLVoEABg3bhyampoQFxeHtWvXQqnkGAL9oKfvv66urhYz6gVw5Mvi2dvbIzg4GNnZ2fptOp0O2dnZCAsL63afsLAwg/YAcPTo0R7b08BiTp8BgK1bt+K1115DVlYWJk6cKEWoZCFM7TOjRo1CcXExCgsL9T9PPvmkvsKUVquVMnySgTnXmSlTpuDixYv6RB0A/v73v0Oj0TDxugeY02du3rzZJcHqSN6FEP0XLFklq/n+K3fFD7qzffv2CZVKJfbs2SPOnz8v4uLihLu7u6iurhZCCDFv3jyRlJSkb3/y5Elha2sr3nzzTVFaWiqSk5OFnZ2dKC4ulusUSGKm9pmUlBRhb28vPvjgA1FVVaX/aWxslOsUSGKm9pnOWO3w3mNqn/nmm2+Ei4uLSEhIEOXl5eLw4cNi6NCh4vXXX5frFEhipvaZ5ORk4eLiIt577z1x6dIl8fnnnwtfX18xa9YsuU6BJNTY2CgKCgpEQUGBACB+97vfiYKCAnH58mUhhBBJSUli3rx5+vaXLl0STk5OYsWKFaK0tFSkpaUJGxsbkZWVJdcpdIvJl5X4wx/+IO6//35hb28vQkJCxOnTp/WvTZs2TcyfP9+g/fvvvy/8/f2Fvb29GDt2rPjss88kjpjkZkqfeeCBBwSALj/JycnSB06yMfU682NMvu5NpvaZU6dOidDQUKFSqcSIESPEb3/7W9HW1iZx1CQnU/pMa2ur2LBhg/D19RUODg5Cq9WKpUuXiu+//176wElyx48f7/a7SUcfmT9/vpg2bVqXfYKCgoS9vb0YMWKEeOeddySP+04UQnDcloiIiIiIqL/xmS8iIiIiIiIJMPkiIiIiIiKSAJMvIiIiIiIiCTD5IiIiIiIikgCTLyIiIiIiIgkw+SIiIiIiIpIAky8iIiIiIiIJMPkiIiIiIiKSAJMvIiKyeAqFAgcPHpTkWDk5OVAoFLh+/bokx+tsw4YNCAoK6rVNZWUlFAoFCgsLJYmJiIj6BpMvIiKSVXV1NZYtW4YRI0ZApVJBq9UiJiYG2dnZcofWIx8fHygUCigUCjg7O2PChAk4cOBAn7z38uXLDc59wYIFiI2NNWij1WpRVVWFgICAPjkmERFJg8kXERHJprKyEsHBwTh27BjeeOMNFBcXIysrC9OnT0d8fHy/HrulpeWu9t+4cSOqqqpQUFCASZMmYfbs2Th16tRdxzVo0CAMGTKk1zY2NjZQq9WwtbW96+MREZF0mHwREZFsli5dCoVCgby8PDzzzDPw9/fH2LFjkZiYiNOnTxu0ra2txdNPPw0nJyf4+fnh0KFDBq//9a9/RUhICFQqFTQaDZKSktDW1qZ//dFHH0VCQgJefPFFeHp6IjIyEgCQmZkJf39/ODo6Yvr06aisrDQqdhcXF6jVavj7+yMtLQ2Ojo749NNPAQDFxcUIDw+Ho6MjhgwZgri4ONy4cUO/b05ODkJCQuDs7Ax3d3dMmTIFly9fBmA47XDDhg3Yu3cvPvnkE/1IW05OTrfTDo05/9/85jdYuXIlPDw8oFarsWHDBqPOlYiI+gaTLyIikkVdXR2ysrIQHx8PZ2fnLq+7u7sb/P7qq69i1qxZKCoqQnR0NObOnYu6ujoAwLfffovo6GhMmjQJ586dw86dO7F79268/vrrBu+xd+9e2Nvb4+TJk0hPT8eVK1fw85//HDExMSgsLMSiRYuQlJRk8rnY2trCzs4OLS0taGpqQmRkJAYPHoyvvvoKBw4cwBdffIGEhAQAQFtbG2JjYzFt2jQUFRUhNzcXcXFxUCgUXd53+fLlmDVrFqKiolBVVYWqqipMnjy5SztTzt/Z2RlnzpzB1q1bsXHjRhw9etTk8yUiIvNwvgIREcni4sWLEEJg1KhRRrVfsGAB5syZAwDYtGkTtm/fjry8PERFRWHHjh3QarVITU2FQqHAqFGj8N1332HVqlVYv349lMrb9xr9/PywdetW/XuuWbMGvr6+eOuttwAAI0eORHFxMbZs2WL0ebS0tOCtt95CfX09wsPDkZGRgVu3buHPf/6zPqlMTU1FTEwMtmzZAjs7O9TX1+OJJ56Ar68vAGD06NHdvvegQYPg6OiI5uZmqNXqHmMw9vzHjx+P5ORk/d8iNTUV2dnZmDFjhtHnS0RE5uPIFxERyUIIYVL78ePH6//v7OwMV1dXXLt2DQBQWlqKsLAwg9GjKVOm4MaNG7h69ap+W3BwsMF7lpaWIjQ01GBbWFiYUfGsWrUKgwYNgpOTE7Zs2YKUlBTMnDkTpaWlCAwMNBjNmzJlCnQ6HcrLy+Hh4YEFCxYgMjISMTEx+P3vf4+qqirj/xDdMPb8f/w3BACNRqP/GxIRUf9j8kVERLLw8/ODQqFAWVmZUe3t7OwMflcoFNDpdCYds7vpjeZasWIFCgsLcfXqVXz//fdYtWqV0fu+8847yM3NxeTJk7F//374+/t3ecatP/TF35CIiMzH5IuIiGTh4eGByMhIpKWloampqcvrpqyzNXr0aOTm5hqMpp08eRIuLi647777et0vLy/PYJuxSZCnpycefPBBqNVqgxGn0aNH49y5cwbndPLkSSiVSowcOVK/7aGHHsLq1atx6tQpBAQEICMjo9vj2Nvbo729vddYzD1/IiKSFpMvIiKSTVpaGtrb2xESEoIPP/wQFy5cQGlpKbZv32709D/gdtXEK1euYNmyZSgrK8Mnn3yC5ORkJCYm6p936s6SJUtw4cIFrFixAuXl5cjIyMCePXvu6pzmzp0LBwcHzJ8/HyUlJTh+/DiWLVuGefPmwcvLCxUVFVi9ejVyc3Nx+fJlfP7557hw4UKPz335+PigqKgI5eXlqK2tRWtra5+dPxERSYtXZCIiks2IESOQn5+P6dOn4+WXX0ZAQABmzJiB7Oxs7Ny50+j3GTZsGDIzM5GXl4fAwEAsWbIECxcuxCuvvNLrfvfffz8+/PBDHDx4EIGBgUhPT8emTZvu6pycnJxw5MgR1NXVYdKkSfjFL36Bxx57DKmpqfrXy8rK9KX14+LiEB8fjxdeeKHb91u8eDFGjhyJiRMn4ic/+QlOnjzZZ+dPRETSUghTn3gmIiIiIiIik3Hki4iIiIiISAJMvoiIiIiIiCTA5IuIiIiIiEgCTL6IiIiIiIgkwOSLiIiIiIhIAky+iIiIiIiIJMDki4iIiIiISAJMvoiIiIiIiCTA5IuIiIiIiEgCTL6IiIiIiIgkwOSLiIiIiIhIAv8PQEEA57ZTUDUAAAAASUVORK5CYII=",
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   "language": "python",
   "name": "python3"
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