{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# MRF rotor\n", "\n", "This notebook explains the implementation of the Multiple Reference Approximation (MRF) for rotor modelling. The geometry consists of an isolated XV15 rotorcraft.\n", "\n", "\n", "![XV 15 rotor](figures/poster_image.png)\n", "\n", "\n", "## 1. Create a project from geometry:\n", "\n", "* Load python libraries and Flow360 client.\n", "* Get geometry files from example database. The geometry used in the path `XV15_CSM.geometry` is \"XV15_Wing.csm\", if you want to use your own geometry, replace this file path with your local path to your CAD file.\n", "* Load the geometry according to the length unit used in the CAD software in which the model has been created\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": "501534a1" }, { "cell_type": "code", "metadata": {}, "source": [ "import flow360 as fl\n", "from flow360.examples.XV15_csm import XV15_CSM\n", "\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", "\n", "XV15_CSM.get_files()\n", "project = fl.Project.from_geometry(\n", " XV15_CSM.geometry, length_unit=\"inch\", name=\"MRF tutorial from Python\"\n", ")\n", "geometry = project.geometry" ], "execution_count": 1, "outputs": [ { "output_type": "display_data", "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "9da7d4f8148742868769c8a17f5346cf", "version_major": 2, "version_minor": 0 }, "text/plain": [ "Output()" ] }, "metadata": {} }, { "output_type": "display_data", "data": { "text/html": [ "
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[12:30:50] INFO: Geometry successfully submitted:                                                                  \n",
       "                   type        = Geometry                                                                          \n",
       "                   name        = MRF tutorial from Python                                                          \n",
       "                   id          = geo-6aa89928-0cc9-4f5c-91d9-3adbf052c317                                          \n",
       "                   status      = uploaded                                                                          \n",
       "                   project id  = prj-27ee099c-0348-44d6-a444-0e644487dfd9                                          \n",
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       "\u001b[2;36m[12:30:50]\u001b[0m\u001b[2;36m \u001b[0m\u001b[36mINFO\u001b[0m: Geometry successfully submitted:                                                                  \n",
       "\u001b[2;36m           \u001b[0m        type        = Geometry                                                                          \n",
       "\u001b[2;36m           \u001b[0m        name        = MRF tutorial from Python                                                          \n",
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   "id": "3f552b8c"
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. Geometry Primitives Definition:\n",
    "\n",
    "In order to apply the MRF approximation we have to define a cylinder corresponding to the rotating zone encapsulating the cylinder. We will also define a bigger cylinder which we will use to apply a volumetric refinement to the wake of the rotor.\n",
    "\n",
    "The farfield is defined automatically and determines the limits of the simulation domain. This is also included in this code snippet with the class `fl.AutomatedFarfield()`.\n"
   ],
   "id": "4f355c66"
  },
  {
   "cell_type": "code",
   "metadata": {},
   "source": [
    "with fl.SI_unit_system:\n",
    "\n",
    "    farfield = fl.AutomatedFarfield()\n",
    "    R = 3.81\n",
    "    MRF_cylinder = fl.Cylinder(\n",
    "        center=(0, 0, 0),\n",
    "        outer_radius=190 * fl.u.inch,\n",
    "        height=40 * fl.u.inch,\n",
    "        axis=(0, 0, -1),\n",
    "        name=\"RotatingCylinder\",\n",
    "    )\n",
    "\n",
    "    Wake_Cylinder = fl.Cylinder(\n",
    "        center=(0, 0, -200) * fl.u.inch,\n",
    "        outer_radius=210 * fl.u.inch,\n",
    "        height=500 * fl.u.inch,\n",
    "        axis=(0, 0, -1),\n",
    "        name=\"WakeCylinder\",\n",
    "    )"
   ],
   "execution_count": 2,
   "outputs": [
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[12:31:23] INFO: using: SI unit system for unit inference.                                                         \n",
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     "metadata": {}
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   ],
   "id": "dd94ca0f"
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. Rotating Zone Definition\n",
    "\n",
    "We use the RotatingCylinder Object to define the mesh volume zone in which the MRF approximation will be applied. We have to define the mesh properties at the interface between the volume zones, which will in turn, determine the overall mesh quality of the volume zone.\n",
    "\n",
    "For further mesh refinement, a uniform volumetric refinement using the MRF_cylinder could be applied to ensure a more uniform volume mesh in the rotating zone."
   ],
   "id": "1e30d43a"
  },
  {
   "cell_type": "code",
   "metadata": {},
   "source": [
    "RotatingZone = fl.RotationVolume(\n",
    "    name=\"RotatingZone\",\n",
    "    spacing_axial=1 * fl.u.inch,\n",
    "    spacing_circumferential=2 * fl.u.inch,\n",
    "    spacing_radial=2 * fl.u.inch,\n",
    "    entities=MRF_cylinder,\n",
    "    enclosed_entities=geometry[\"*\"],\n",
    ")"
   ],
   "execution_count": 3,
   "outputs": [],
   "id": "4976c480"
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4. Case Parameters Definition:\n",
    "\n",
    "### 4.1 Meshing:\n",
    "\n",
    "Having defined the basic information about the rotating zone we can define the different parameters which drive the simulation, starting from the meshing. The required inputs are:\n",
    "\n",
    "1. Meshing Defaults: in this section the basic parameters needed to create the surface and volume meshes are determined. In this case they have been chosen to ensure sufficient accuracy across the blades and ensure y+<1\n",
    "\n",
    "2. Volume Zones: for multizone meshes, all volume zones have to be specified. In this case we have a farfield and the rotating zone\n",
    "\n",
    "3. Refinements: a number of refinements can be included to increase the accuracy of the mesh. \n"
   ],
   "id": "808c2c32"
  },
  {
   "cell_type": "code",
   "metadata": {},
   "source": [
    "meshing = fl.MeshingParams(\n",
    "    defaults=fl.MeshingDefaults(\n",
    "        surface_max_edge_length=1 * fl.u.inch,\n",
    "        boundary_layer_first_layer_thickness=1.5e-6 * fl.u.m,\n",
    "        curvature_resolution_angle=8 * fl.u.deg,\n",
    "        boundary_layer_growth_rate=1.2,\n",
    "    ),\n",
    "    volume_zones=[farfield, RotatingZone],\n",
    "    refinements=[fl.UniformRefinement(entities=Wake_Cylinder, spacing=30 * fl.u.mm)],\n",
    ")"
   ],
   "execution_count": 4,
   "outputs": [],
   "id": "d27d9a40"
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4.2 Final MRF Definition:\n",
    "\n",
    "The MRF zone is established by defining a rotating region in the solver parameters. Using fl.Rotation() inside a fl.Steady configuration allows the solver to apply the MRF approximation."
   ],
   "id": "f168089f"
  },
  {
   "cell_type": "code",
   "metadata": {},
   "source": [
    "omega = 589 * fl.u.rpm\n",
    "\n",
    "MRF = fl.Rotation(name=\"MRF\", volumes=MRF_cylinder, spec=fl.AngularVelocity(omega))\n",
    "\n",
    "time_stepping = fl.Steady(max_steps=3500, CFL=fl.AdaptiveCFL(convergence_limiting_factor=0.75))"
   ],
   "execution_count": 5,
   "outputs": [],
   "id": "8dd73c2b"
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4.3 Dynamic parameters:\n",
    "\n",
    "Having defined the time-stepping scheme and the MRF rotating zone. We have to specify the turbulence model, and reference geometry. All the parameters are then groped under the following sections. The physical configuration is intended to demonstrate the numerical implementation of a forward-flight case, rather than to represent a realistic operating condition for the rotor."
   ],
   "id": "aa5ef552"
  },
  {
   "cell_type": "code",
   "metadata": {},
   "source": [
    "with fl.SI_unit_system:\n",
    "\n",
    "    params = fl.SimulationParams(\n",
    "        operating_condition=fl.AerospaceCondition.from_mach(\n",
    "            mach=0.12,\n",
    "            alpha=-90 * fl.u.deg,\n",
    "        ),\n",
    "        reference_geometry=fl.ReferenceGeometry(\n",
    "            moment_center=(0, 0, 0), moment_length=(R, R, R), area=np.pi * R**2\n",
    "        ),\n",
    "        time_stepping=time_stepping,\n",
    "        meshing=meshing,\n",
    "        models=[\n",
    "            fl.Fluid(\n",
    "                navier_stokes_solver=fl.NavierStokesSolver(\n",
    "                    low_mach_preconditioner=True, absolute_tolerance=1e-10\n",
    "                ),\n",
    "                turbulence_model_solver=fl.SpalartAllmaras(),\n",
    "            ),\n",
    "            fl.Wall(surfaces=geometry[\"*\"]),\n",
    "            fl.Freestream(surfaces=farfield.farfield),\n",
    "            MRF,\n",
    "        ],\n",
    "        outputs=[\n",
    "            fl.SurfaceOutput(\n",
    "                surfaces=geometry[\"*\"],\n",
    "                output_fields=[\n",
    "                    \"primitiveVars\",\n",
    "                    \"Cp\",\n",
    "                    \"Cf\",\n",
    "                    \"CfVec\",\n",
    "                ],\n",
    "            ),\n",
    "            fl.VolumeOutput(\n",
    "                output_fields=[\n",
    "                    \"Mach\",\n",
    "                    \"primitiveVars\",\n",
    "                    \"qcriterion\",\n",
    "                    \"Cp\",\n",
    "                ]\n",
    "            ),\n",
    "        ],\n",
    "    )"
   ],
   "execution_count": 6,
   "outputs": [
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   "id": "cf894a2e"
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  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5. Running the case\n",
    "Here we run the case using the beta mesher."
   ],
   "id": "bf7ce010"
  },
  {
   "cell_type": "code",
   "metadata": {},
   "source": [
    "case = project.run_case(params=params, name=\"MRF tutorial from Python\", use_beta_mesher=True)"
   ],
   "execution_count": 7,
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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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[12:31:26] INFO: Successfully submitted:                                                                           \n",
       "                   type        = Case                                                                              \n",
       "                   name        = MRF tutorial from Python                                                          \n",
       "                   id          = case-49fa6c8e-3387-48b6-8bff-e250066bd048                                         \n",
       "                   status      = pending                                                                           \n",
       "                   project id  = prj-27ee099c-0348-44d6-a444-0e644487dfd9                                          \n",
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       "\u001b[2;36m[12:31:26]\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        = MRF tutorial from Python                                                          \n",
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     "metadata": {}
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   ],
   "id": "441dc499"
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 6. Numerical and Force Convergence\n",
    "\n",
    "Having ran the case we can plot the thrust and non-linear residuals. Note that for the thrust we will need to use dimensional quantities from the case."
   ],
   "id": "8a9811d6"
  },
  {
   "cell_type": "code",
   "metadata": {},
   "source": [
    "case.wait()\n",
    "\n",
    "# Reference quantities\n",
    "density = case.params.operating_condition.thermal_state.density\n",
    "U_ref = (\n",
    "    case.params.operating_condition.reference_velocity_magnitude\n",
    "    or case.params.operating_condition.velocity_magnitude\n",
    ")\n",
    "A_ref = case.params.reference_geometry.area\n",
    "\n",
    "# Get results\n",
    "results = case.results\n",
    "\n",
    "# Plot thrust\n",
    "total_forces = case.results.total_forces.as_dataframe()\n",
    "total_forces[\"thrust\"] = total_forces[\"CFz\"] * 0.5 * density * U_ref**2 * A_ref\n",
    "total_forces.plot(\"pseudo_step\", [\"thrust\"])\n",
    "\n",
    "# Plot non-linear residuals\n",
    "non_linear = case.results.nonlinear_residuals.as_dataframe()\n",
    "non_linear.plot(\n",
    "    \"pseudo_step\",\n",
    "    [\"0_cont\", \"1_momx\", \"2_momy\", \"3_momz\", \"4_energ\", \"5_nuHat\"],\n",
    "    logy=True,\n",
    ")\n",
    "plt.show()"
   ],
   "execution_count": 8,
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ixVi8eHGzr9PSpO4zs40pqntKPqCflq+0t/oqDERERDaJd0grM3SfmbulyLHGlHyAM9CIiIgawlBkZYbuM52ZWooMwcfQbSaTyapmoDEUERER1YuhyMqqus/Mc77SyuBTvZtMxWn5REREjWIosjKp+8wMoUinEyjX6U+ksKsaUM0FHImIiBrHUGRl5pwLVqarCj11thQxFBEREdWLocjKzLmidWm10KOwqxaKFOw+IyIiagxDkZWZc++zsoqqsyirhyJ2nxERETWKocjKqlqKTD+XoaXIXi6DXF7VMcfZZ0RERI1jKLIRwgxtRWWV+5tV7zoDqo8pYvcZERFRfRiKrMycLUUldUzHB6ptCsuWIiIionoxFFmZ3IwrWtffUsQxRURERI1hKLIyS8w+U9VsKeLsMyIiokYxFFmZNPvMDE1FVS1FxqsfcZ0iIiKixjEUWZnUUmSGc9W1xQfA7jMiIqKmYCiysqq9z8zQfcbZZ0RERC3GUGRl5mwpMizeWKulSBpTVH9L0X8SL+CvH+5Ddn6xGa6EiIjozsNQZHXmG1Nk6D5r7uwzIQQ+/OUcjmTk4vvDV0y/ECIiojsQQ5GVmXP2mWGgtbKZ3WeXcoqQqdW3EO09fd3k6yAiIroTMRRZmTSmyAznqn+gdcOzz5LSb0p/P3ThFm6XlpvhaoiIiO4sDEVWJjPjoKLSxqbk1zOm6GB6jtE5Dpy/WWc5IiKitoyhyMoM+7bqzLh4o7JyDJFB1ZiiurvPDl7Qh6LADk4AgL2nb5h8LURERHcahiIrkxZvNMO56l28sXL2maElqbqbBSW4ePM2AGDysGAAwOGMW2a4GiIiojsLQ5GVmXND2Hq3+Wig++xMdgEAoJOHI4Z18wYAnLqqRTG3BCEionaGochGCDO0FbVkQ9izlaEoxMcFnTwc4e2qQrlO4PiVPJOvh4iI6E7CUGRlZm0pMize2Iwp+YZQ1M3HBTKZDP0D3AEAR9iFRkRE7QxDkZUZZp+Zc0q+or4VretoKTp3vaqlCAAGBHoAAA5fzDXDFREREd05GIqsTBoSbYZUVP/ijZXdZ3WMKarefQYA4ZWhaFdaNn49w4UciYio/WAosrKqZYrMOSW/ad1nBSXluJanX8k6xNsVABDe2QN/6uWL0nId/vHFIQYjIiJqN+ytfQHtncyMe5/VOyW/noHW5ypbibxdVXBzUgAA5HIZPnhiAJ5bl4yf/8jGP744hO+mDkbvjm6mXyC1Kdn5xdhxIhOHL95CamY+0m8UQgBQ2cnRwUWJod28MGV4V3TycLL2pRIRNQlDkZXJzbegNUrq6z6rZ0yRYTB1d18Xo9eV9nJ8OD4cT689iH1nb+L7w1cYiqzs1FUtXtp4FMHeznhmaBAGdPaQjgkhsOXYNfz8RxaeHdYVvfzVFr2WK7lFeH/XGWw8dBnlutq/uaXlOuSXlOPCzQz8kHIVKx8Lw6ievg2e82ZBCTK1xejk7iQF9JqytcW4mlcMlb0cPTSuVavBV9LpBK5pi1FRIRDg6VjrOBFRYxiKrM2MK1qX1TfQuvJ5hU6gvEIH+8rQ9NOxawCA+3rUvmEp7eV4uH8n7Dt7E8ev5Jp8bdRyhSXlmPb1YaTfKMSpa1psPX4NM0Z1xwujQgAAs/97DBuTLwMAdpzIxPSRIejq44Kk8zdx7EoeCkvK0bujG6YM74ruvq4tuobyCh2OXs7Df5Mv4bvkK9JCoGEB7hjVwwc9/NTo5uMChb0cpeU6pN8owHu7zuJIRi6mfJWMT54aiBGhPrXOW1BSjre2/oH/Jl9CWYWATAaMvkuD0b01cHdS4uLNQiRfvIXki7dw+VaR9L5gb2c8eU8g/q+PH3Jvl2HD75ew6chl3LpdBgBQO9ijbyd39OnkBi8XFbLzi3E6Mx+nswpwu7QcTkp7dPN1QTcfFzgq7aVFTK/kFkEIAbWjAj6uDvB0VqC8QqCorAJFZRW4XaL/U2Uvh5PKHs5KOzgo7FBarkNxWQWKyytQVi6gsJdBaSeHovJRoRPQCQGd0P+3XtcG0DKZvt1Yn+VkqC/T1f1PRd3/ftT3z0p9/9qYY2Nqc2GobZ96+6sRd3+o1T6focjKzNl9VlpPS1H1MUYl5fpQdCnnNpIv3oJMBvy5r1+d5+vbSd86dOKKFhU6ATs5/5GyhpU/n0b6jUJo1A6ICPbEDylX8c7Pp2FvJ4OPqwobky/DXi5DL381jl3Ow/L407XOcTqrAD+mXMWiv9yFv98T2OTPziksxfu7zmJj8iXkF1dtFBwZ3AGz7u+OgV0863xfkJcz7u3mjZkbUrDl2DVM+SoZX8ZG4O5q5TPzijFxzUGkZuYDADycFLh1uwzbT2Ri+4nMWueUywA/N0fcul2K89cL8fpPp/D6T6eMyijsZJBBBm1xOX47ewO/na17y5pbt8twJbcIu9MaGjPHtbqIWltdrc+tiaHIysz5P0PS7LMaLUXVQ1JJuQ7OKmBLZSvRPUEd4Kt2qPN8wd4ucFLa4XZpBc5dL2hxKwO1XHmFDt8fvgIAWPzQXbj/Lg3CAtzx+k+n8K+daVDI9d/trPtD8eywYPxw9Aq+TLyIojIdBnXxQHgXT7io7PDVgQzsSs3Gq5tP4MD5m3jjod7wcFY2+vlTv0pGUuWGwWoHe4zs4YPxEYEYFFR3GKpOYSfHir+FobCkHL+kXccza37H50/fjbu7eKK8Qofn1iUjNTMfXi4qvDsuDIO7euF0Vj6+OZiBlEu5KC7TwVetQv8AD4QHeqBfgBtcHRQoKCnHpiNX8HVSBtIytZDLZBjV0wePD+qMoSFeEAI4nZWPY5fzcPxKLvKLy+HprEQ3X1eE+rrC01mBnMIynMnOx7nsQpRV6KB2tEeXDs4I8HSCvVyGW7fLkJ1fjFuFpVDay+Gg0LcIuajs4aiwQ0l5BQpLKnC7tBxFZRVQ2unLOCrtYC+Xo6xCh9JyHUordKjQCchl+vF6cpkMcllVq1B1AvqWGiEMf6//34e6Xq6/bDNOUv/Lrcp22quotWnquR+1FoYiK6v+D5AQwqQmY2n2WY2WIns7OezlMpTrhFTm6KVcAMConrW7NAzs5DL09nfDwQs5OHY5D6XlOvw3+TKclHZ4MjIQn/2ajhNX8/DvJwfCzbHucSAAcCYrHx/vPY9pI0PQxcvZ6FhxWQXkMlmtIEd6iedv4mZhKTydlbivh/67enpIEM5kF+DrpAyUVugwJKQDJt0bBLlchr/274S/9u9U6zwjQ33w0Z5zWL7zNLYcu4a8ojJ8GRvR4GcnX7yFpPQcKO3k+PeT4RjW3bvZrYWG8WkT1hzEwfQcjP8kCVOGB+PyrSIczsiFq8oe/50SKf1edPd1xcIH72rwnC4qezx5TyCevCcQpeX60OGoNN4EuXdHt8pxcJ3rPU9Tgh0RtS8MRVZWPQQ19H+GTWFY0brmNh+AflxReWmFNC0/K18/Fb+xmUF9O+lD0fHLufjst3T8cU0LANiYfBnX80sAAJ/9lo64P3U3el/u7VK4OSogk8nw2g8ncOB8Dk5n5eP754bATi5DcVkF3tx6ChsPXUZHd0f8J3YQZynVYctRfYve6N4aaSwYALz5UG883L8jXBzs0d3HFfJGwopMJsNzI0IQGdwBj65OxK9nbiDlUi7CKlcwr8unv54HAMT098fIHvWH58Y4Ku2w9um7MXNDCv53Mgvv7jpbVY+/9q4VlJuDYZqIzIn/oliZUUuRiecqq2edIgBQKYyn5Wdr9YFG49ZwU2Xfypvm1uOZUiBS2sulQAQAa/alI6+oTHq+/fg1hC2Ox2s/nMCJK3k4cF7f/XL0ch6+TroIAPho9zl8dSADJeU6nL9RiAdW/oo/v/crfjp6tdn1bm3rD2bgs9/ScauwFB/uPotLObct8jlFpRXYfkIfimqO+5LLZRjYxRM9NOpGA1F1/Tt74C9h/gCA1bvP1Vsu73YZ/ndSP67nH/cGN/fSa3FS2uOj8eF4b1x/jAz1xui7NPjimUF4KKyjyecmIjIXhiIrq94yZOrMj9J6NoQFqi3gWKaDTieQpdW3FPmqVQ2ec1QPH7g62ONGgT4EDQ3xwucT7oZMpn9viI8L8ovLsf5gBgD9GJj/tyMVAPDVgQxM+/owAP1aSACwKuEMbpeW49tDlwAAL93fHV29nZFfUo4TV7R4/psjeHt7qkk/B0s6eTUPc78/jje2nMKoFXuwdEcaXv7vUYt81vdHLkNbXI4AT0dEBHUw23mnDO8KANh5KhNFpbX3wwOA3y/kQCeArt7OZhtLJpfL8GA/f6x5ehBWPxmO4d29zXJeIiJzYSiysuqDIE1uKZIGWtduOai+qnXO7VKU6/TTn71cGg5Fzip7PDYwQHo+urcGQ7t5YfuL9+KHaUMxcXAXAMCOylaFH1Ku4sLN29L6Sxdv3obSTo5PnhoIfzcH3CgoRdyGo7iWVwx3JwX+cW8wtr84DJunDcH0kfop5qv3nMPOk7VnH1nK/rM3sHRHKjIrV/duyOo956W/5xSWAgAOnM+RxmiZixACa/ddAABMHBxk1pl/3X1d4aqyh04AV3LrbuU6eEHfujfIjGGMiMjWcUyRtRm1FJl2qqqB1na1jlVf1drQStTBWVVnq1JNEwZ3wZr9FyADcH8v/ZpGPTT6BQLv7+WLVzefwJGMXJy7XoB/7UwDoJ8NJZfpxw490EeDHho1nhkahDe3/iEFqL/27wiHym69sAB3hAW4o6S8Ap/8mo4X16fgkfBOeHxQAOZ/fxz5xeUY1t0bU4Z3xbqki3BzVMDVwR4Xb97Gs8O61rvgX3VCCFToBDJybuNIRi6Gh3pj4Y8nsbVyJt53hy8jpn9H9A/wwOjemlrvz7h5G1uP6bv3YocG4Y9rWshkwL6zNzFjQwq6ejujXCcwO7qHyQsoJp6/iTPZBXBW2uHRgbUHTpuqo4cjUjPzcelWEUJ8arcEJZ2/CQCI4GBkImpHGIqsrHoDgKn7n0nbfNTVUqSoainK1urLNdZ1ZhDg6YQvnxkEAcCnxnRJH7UD+nd2x5GMXIxavgcA0NnTCbFDg6TAY/DY3QH4aPc53CwsRS8/tdSNU91L0aE4XjkO6csDF/HlgYvSsfM3CvHlgYuoqLGOxfnrhfjo7wManLlXXFaBR1bvx4krWuk1B4UcxWU6KOxk8HZR4WpeMf5d2RL02p97IXZokNE5ElKzoBP6NXpe+3MvAEBaZj7+791fkX6jEOk3CgEAf1zT4sfpQ+tc6uDA+Zv49tAlTB3eFd0a6JbaVDkN/y9h/lA7NB74mqtTZSi6Um1BRIOCknKcuKr/OXGGFhG1JwxFVlZz9pkpSuqZkg8YjykyDIqub32iugwO8ar32P29NDiSkSs9f+uvvWsFIgBwdVBgywtDoS0qR3dflzpDjMreDt9Mugf7z93E6z+dxOmsAnR0d8RL0d2xdEcaruUVw9tVhe6+LrhdWoHjl/Ow42QmNh25gocHVLWoXLhRiHKdQGAHJyjs5Pj+8BUpENnLZXBzVOBmZffXysf6Y2g3L3z+WzrOXi/A1mPX8MaWUwj1dcXQblX1Pli5Xk/110I1rvhh2hD8cU2Lcp3A57+l40x2Af7xxSF8+2ykNFU8p7AUXyZexLu7zqBCJ5CSkYstLwyFk7L2f4L6AdaG1jTztxIBVbMOL9cRipIv3kKFTqCThyP83R0t8vlERLaIocjKjNcpMu1cZQ0OtK7qPsts4iDrpnp0YCf8kpoNlUKOR8I74d5u9Q+g9XNzhF8j26jJZDIMCfHCj9OHIv5UFu4J7gBvVxXu7eaN7ScyEX2XL3xc9YHu3YQzWBF/GnO/P45OHk4YFOSJpPM38cSnSajQCdjLZQj2dsbpLP3mt3Mf6IGJg7ugpFyHdxPO4C5/NcZUzuya+afu+i0eHBT45mAG3thyCvf19EF3XxfEhHXE79I4G+PWk6o1cYAhXb0Q8+E+HL+Shwff/w2eTkqoHRXYe+a61L2psJPh/I1C/L/tqXj9od616r/l2FUUlJSjk4cjBgZ61DpuDp089GHn8q3aY4r2n9OvAn1PMMcTEVH7wlBkZTIzdp8ZbrqquqbkVxtonVU5Hb85LUUN8XJR4dspkWY5V3UOCjs82M/f6HOerLFFxbSRITh+JQ/xp7Lw90+T8GRkIBL+yJK2JSnXCSkQuTsp8OQ9gdLqxIYusOpkMhnmjA7FtuPXkJaVj7Qs/RYUqdfycaNAv7qxYfuTunTu4ITVfw/H+E8P4Gx2gdGx3h3ViB0ahA7OKjz1+UF8eeAinozsghCfqg15956+jlc2nwAAPBLeqVnT7ZujY2UL0JXc2i1F+yq3xhjaQOsgEVFbxFBkZUazz0zIRPoNJ/V/r6ulSCmFIh2ypZYi6y6nbg52chnefbw/pn19GLtSs/HZb+kA9EvF/2/mMBSUlGNP2nVsP3ENj90dAGdV47/y7k5KvBwdilc3n4C3qwrX80vw7736sUZhndylVrf6DAryxPdTh+B0Vj7s7WTIzCvGwC6eGNDZXeoyjOrpi5//yMK//peG1U+GA9DvAj/968MoLdfhT7188dyIEFN+NA2qr/vsVmEpTlaOJxocwpYiImpfGIqszLilqOUMXWdAPYs3VhtTZFjN2lzdZ9bmqLTDZxMGYldqNrYcu4YruUWY9afucHNUwM1RgSciOuOJiPq3e6jL3+8JxMgePvB1VeH/7UjFJ7/qw9Y9wU0beNynkxv6NNCiNHt0KHalZlWOh7qMmLCOeHXzCWiLy9G7oxofPDHAoqs1G7rPrueXoLisQhoDlnj+JoQAQn1dpS5KIqL2gqHIhpiyeKNhkDXQ2Jiiqu6ztnTTk8lkGNXTF6N6+prtnIYuplfG9MKD/fyx7+xNTBjc9B3mG9Ld1xXPjQjB+7+cxZzvjuNSThF2nsqCvVyGZY/0s/j2Fe5OCmmz36u5RQj21nfh7agc4M1WIiJqjyz2L+9bb72FwYMHw8nJCe7u7nWWycjIwJgxY+Dk5AQfHx+8/PLLKC8vNyqze/duDBgwACqVCiEhIVi7dm2t83zwwQfo0qULHBwcEBERgYMHDxodLy4uxrRp09ChQwe4uLhg7NixyMrKMldVTWKJliKFXf1T8ovLdNKig4ZVpqlxfTu5Y+qIrnXOFmupuD91x6gePigt12FF/GkAwDNDg9DTz7Q1jppCJpNJrUUZlduUnM0uwJbKdZgettCsNyIiW2axUFRaWopHH30UU6dOrfN4RUUFxowZg9LSUuzfvx9ffPEF1q5diwULFkhl0tPTMWbMGIwcORIpKSmYMWMG/vGPf+B///ufVGbDhg2Ii4vDwoULcfjwYfTr1w/R0dHIzs6WysycORM//fQTNm7ciD179uDq1at4+OGHLVX1ZjHXmKLSatPx657qrv+qs/OLpXV+PJyULf9AMplcLsPKx8OkgdZeLko8f5/lxhHVZAhfSZVLDbybcAY6Afypl2+DXX9ERG2VxULR66+/jpkzZ6JPnz51Ht+5cydOnTqFr776CmFhYXjggQfwxhtv4IMPPkBpqb4lY/Xq1QgKCsLy5cvRs2dPTJ8+HY888gjeeecd6TwrVqzApEmT8PTTT6NXr15YvXo1nJyc8PnnnwMA8vLy8Nlnn2HFihW47777EB4ejjVr1mD//v04cOCAparfZEb5xYRQVDUdv+7ZSobuM8NsI7WDPXcYtwGuDgp8PuFu/F8fDVb8LQyuFliosT4jQ30AAL+kZiNLW4ytx/Ure784qlurXQMRkS2x2l0xMTERffr0ga9v1RiQ6OhoaLVanDx5UioTFRVl9L7o6GgkJiYC0LdGJScnG5WRy+WIioqSyiQnJ6OsrMyoTI8ePdC5c2epjDXJqy/eaEIqklqK6gk67pXbYBimiXdoZM8zaj2dOzjhw/HhGNbKG6QO6+4NmQxIzczHqgT9opJ3d/GQ1lwiImpvrBaKMjMzjQIRAOl5ZmZmg2W0Wi2Kiopw48YNVFRU1Fmm+jmUSmWtcU3Vy9SlpKQEWq3W6GEJ1dt1dKZ0nzWwcCNQNf3eMMi6gzO7zto7T2cl+nVyBwB8nZQBAM2epUdE1JY0KxTNnTsXMpmswUdqaqqlrrVVLVmyBG5ubtIjICCg8Te1gNFAaxMGFTXWUqRxM55p5slQRNCPHzJwd1Lggd5+VrwaIiLratZUmlmzZmHixIkNlgkODm7SuTQaTa1ZYoYZYRqNRvqz5iyxrKwsqNVqODo6ws7ODnZ2dnWWqX6O0tJS5ObmGrUWVS9Tl3nz5iEuLk56rtVqLRKMjPY+M+E8ZRX6d9e17xmgX8ywOnafEYDKFbaVuFlYiiEhXnXuWUdE1F40KxR5e3vD29s84x4iIyPx1ltvITs7Gz4++gGf8fHxUKvV6NWrl1Rm27ZtRu+Lj49HZKR+SwmlUonw8HAkJCQgJiYGAKDT6ZCQkIDp06cDAMLDw6FQKJCQkICxY8cCANLS0pCRkSGdpy4qlQoqVesGB7PMPqunpcinxkKN7D4jQL+VyuOD2GVGRARYcPHGjIwM5OTkICMjAxUVFUhJSQEAhISEwMXFBffffz969eqFJ598EkuXLkVmZiZeffVVTJs2TQojU6ZMwfvvv4/Zs2fjmWeewa5du/Dtt99i69at0ufExcVhwoQJGDhwIAYNGoSVK1eisLAQTz/9NADAzc0NsbGxiIuLg6enJ9RqNZ5//nlERkbinnvusVT1m0Um0wciUwZaN7QZLKCffebprJTWKOrgwlBERERUncVC0YIFC/DFF19Iz/v37w8A+OWXXzBixAjY2dlhy5YtmDp1KiIjI+Hs7IwJEyZg8eLF0nuCgoKwdetWzJw5E6tWrUKnTp3w6aefIjo6Wirz2GOP4fr161iwYAEyMzMRFhaGHTt2GA2+fueddyCXyzF27FiUlJQgOjoaH374oaWq3mwyVHadmWGgdUPT7H1cVVIo4pgiIiIiYzJhyujedkSr1cLNzQ15eXlQq8274nDX+dtQoRNImj+qxZu0/nT0Kp7/5gjuCfbE+sl1dwtOXHMQu9OuAwDW/SMCQ7gLOhERtXHNuX9z9T4bYBhqbUo8baz7DDAebM2WIiIiImMMRTbAMAHNHIs3qhroPqveCsWB1kRERMYYimyAYVq+xVuKqq1V5MFQREREZIShyAYYus90JqSikkam5ANV3WdujooGwxMREVF7xDujDZC6z0xqKdK/uaGw08tfDaW9HH25AzoREVEtFpuST00nQ9072zdHY4s3AvoxRQfmjYKLil87ERFRTbw72gDztBRVhqJGusU464yIiKhu7D6zAdKUfDOsaN1QSxERERHVj3dQG2CO2WeGgdYKO9O74oiIiNojhiIbUNVS1HJV3Wfc5ZyIiKglGIpsgTSmyPTFGxX2bCkiIiJqCYYiG2DeliJ+pURERC3BO6gNkMtNH1NUyoHWREREJuEd1AZUbQhrSvdZ44s3EhERUf14B7UB0uwzE85Ryu4zIiIik/AOagOqWopafo4yaaA1v1IiIqKW4B3UBkgrWpvQVsSWIiIiItPwDmoTTB9oXbWiNafkExERtQRDkQ0wx95n0oawXLyRiIioRRiKbIA59j4zdJ9xmw8iIqKWYSiyAeZoKTJ0n3GgNRERUcvwDmoDZDC9daeq+4xfKRERUUvwDmoD5GZpKdK/mStaExERtQzvoDbAsHijzgwbwrKliIiIqGV4B7Uh5ljRmmOKiIiIWoZ3UBtQNdC6ZbFICMGWIiIiIhPxDmoDqla0bplyXdU7GYqIiIhahndQGyAzcUVrQysRwIHWRERELcU7qA2QSTPyW5aKDGsUAVy8kYiIqKUYimyAtKJ1S1uKKkORXAbYs/uMiIioRXgHtQGGKfktHVNk6D5TMBARERG1GO+iNsDUbT6khRsZioiIiFqMd1EbYOg+a+nijdJ0fA6yJiIiajHeRW2A1H3W4pYidp8RERGZindRGyANtG7hqKISthQRERGZjHdRGyCrSkUtUtVSxOn4RERELcVQZAOkxRtb+P6qMUV2ZroiIiKi9oehyAaYPvvMsO8ZW4qIiIhaiqHIhrR0TJEUijimiIiIqMV4F7UBps4+K+HijURERCbjXdQGmDjOWlq8kaGIiIio5XgXtQHyym9BcPFGIiIiq+Fd1AZIs89MHmjNr5OIiKileBe1AdLssxZ2oLGliIiIyHS8i9oAaUxRC1uKSrl4IxERkckYimyBibPP2FJERERkOt5FbYCps89KuSEsERGRySx2F33rrbcwePBgODk5wd3dvc4yMpms1mP9+vVGZXbv3o0BAwZApVIhJCQEa9eurXWeDz74AF26dIGDgwMiIiJw8OBBo+PFxcWYNm0aOnToABcXF4wdOxZZWVnmqqrJqla0blksKi6rAAA4KrjNBxERUUtZLBSVlpbi0UcfxdSpUxsst2bNGly7dk16xMTESMfS09MxZswYjBw5EikpKZgxYwb+8Y9/4H//+59UZsOGDYiLi8PChQtx+PBh9OvXD9HR0cjOzpbKzJw5Ez/99BM2btyIPXv24OrVq3j44YfNXueWMrWlqLhM31LkwFBERETUYvaWOvHrr78OAHW27FTn7u4OjUZT57HVq1cjKCgIy5cvBwD07NkTv/32G9555x1ER0cDAFasWIFJkybh6aeflt6zdetWfP7555g7dy7y8vLw2Wef4euvv8Z9990HQB/EevbsiQMHDuCee+4xR3VNYuqK1mwpIiIiMp3VB6FMmzYNXl5eGDRoED7//HOjLqTExERERUUZlY+OjkZiYiIAfWtUcnKyURm5XI6oqCipTHJyMsrKyozK9OjRA507d5bK1KWkpARardboYSlVc8ZaloqKSvWhyEFh9a+TiIjojmWxlqKmWLx4Me677z44OTlh586deO6551BQUIAXXngBAJCZmQlfX1+j9/j6+kKr1aKoqAi3bt1CRUVFnWVSU1OlcyiVylrjmnx9fZGZmVnvtS1ZskRq7bI0uaktReWGUMSWIiIiopZqVtPC3Llz6xwcXf1hCCNN8dprr2HIkCHo378/5syZg9mzZ2PZsmXNroQlzJs3D3l5edLj0qVLlvuwyqYiXQtDkaGlyFHJUERERNRSzWopmjVrFiZOnNhgmeDg4BZfTEREBN544w2UlJRApVJBo9HUmiWWlZUFtVoNR0dH2NnZwc7Ors4yhnFKGo0GpaWlyM3NNWotql6mLiqVCiqVqsV1aY6qgdYtnH1WuU6Rgz1DERERUUs1KxR5e3vD29vbUteClJQUeHh4SGEkMjIS27ZtMyoTHx+PyMhIAIBSqUR4eDgSEhKkWWs6nQ4JCQmYPn06ACA8PBwKhQIJCQkYO3YsACAtLQ0ZGRnSeaytakp+y95fzJYiIiIik1lsTFFGRgZycnKQkZGBiooKpKSkAABCQkLg4uKCn376CVlZWbjnnnvg4OCA+Ph4/POf/8RLL70knWPKlCl4//33MXv2bDzzzDPYtWsXvv32W2zdulUqExcXhwkTJmDgwIEYNGgQVq5cicLCQmk2mpubG2JjYxEXFwdPT0+o1Wo8//zziIyMtImZZ0C1DWFb+P6iMg60JiIiMpXFQtGCBQvwxRdfSM/79+8PAPjll18wYsQIKBQKfPDBB5g5cyaEEAgJCZGm1xsEBQVh69atmDlzJlatWoVOnTrh008/labjA8Bjjz2G69evY8GCBcjMzERYWBh27NhhNPj6nXfegVwux9ixY1FSUoLo6Gh8+OGHlqp6s5lr8UYOtCYiImo5mWjpnbid0Wq1cHNzQ15eHtRqtVnPPf7TA9h39iZWPR6Gh8I6Nvv9fRb9D/nF5dg1aziCvV3Mem1ERER3subcv9nfYgOk7rMWxtMSrmhNRERkMoYiGyB1n7VgVFF5hU7aEJYrWhMREbUcQ5ENaUlLkWE6PsCWIiIiIlMwFNkAU1a0NgyyBgCVPb9OIiKiluJd1AbIpBWtm5+Kqu97JpfLGilNRERE9WEosgFVK1o3Xwn3PSMiIjILhiIbIKsaad1sRaUcZE1ERGQODEU2wJS9z4q4cCMREZFZMBTZAFP2PuNq1kRERObBUGQTWr73Gfc9IyIiMg/eSW2AOVqKOKaIiIjINAxFNsCUMUUMRURERObBUGQDTGkpqlqniKGIiIjIFAxFNkBa0boF7zVs88FQREREZBqGIhtQ1VJk2orWRERE1HK8k9oAGUzY+6ycY4qIiIjMgaHIFpjQUlRc2VLkqGQoIiIiMgVDkQ0wZe+z4jKOKSIiIjIHhiIbYNj7rEWzz7iiNRERkVkwFNkAU1qKuKI1ERGRefBOagNMmX3GxRuJiIjMg6HIBsgaL1IvhiIiIiLzYCiyAaaMKeJAayIiIvNgKLIBUvdZC0YVFZSUAwCcVfbmvCQiIqJ2h6HIBhgWb9S1oKVIW1QGAFA7MhQRERGZgqHIBrR0Q1ghBLTFlaHIQWHmqyIiImpfGIpsQNWU/OalopJyHcoq9O9ROzIUERERmYKhyAa0tKXI0HUmlwHO3OaDiIjIJAxFNkDWwkn5hq4zVweFNIONiIiIWoahyAa0dPHGvCL9zDMOsiYiIjIdQ5ENaGn3WT4HWRMREZkNQ5FNqFy8sZnv0hZXthQxFBEREZmMocgGyE0caO3qwO4zIiIiUzEU2QBD95mumalIWqOI0/GJiIhMxlBkA2Qt7T4rYvcZERGRuTAU2QBpNn0zW4qkgdacfUZERGQyhiIbULWidfNwoDUREZH5MBTZAMPCixxoTUREZD0MRTakuXufcaA1ERGR+TAU2YCWL97I7jMiIiJzYSiyAS2ffcaB1kRERObCUGQDWtpSpOU2H0RERGbDUGQDpBWtm9FWVFJegeIyHQCGIiIiInNgKLIBLZl9Zli4EQBcOPuMiIjIZAxFNqBq7camp6KruUUAAF+1CnaGpiYiIiJqMYYiW9CCMUUXbhYCAAI9nS1wQURERO2PxULRhQsXEBsbi6CgIDg6OqJr165YuHAhSktLjcodO3YM9957LxwcHBAQEIClS5fWOtfGjRvRo0cPODg4oE+fPti2bZvRcSEEFixYAD8/Pzg6OiIqKgpnzpwxKpOTk4Px48dDrVbD3d0dsbGxKCgoMH/FW6Als88u3rwNAAjs4GSBKyIiImp/LBaKUlNTodPp8O9//xsnT57EO++8g9WrV2P+/PlSGa1Wi/vvvx+BgYFITk7GsmXLsGjRInz88cdSmf3792PcuHGIjY3FkSNHEBMTg5iYGJw4cUIqs3TpUrz77rtYvXo1kpKS4OzsjOjoaBQXF0tlxo8fj5MnTyI+Ph5btmzB3r17MXnyZEtVv1laMvuMoYiIiMjMRCtaunSpCAoKkp5/+OGHwsPDQ5SUlEivzZkzR4SGhkrP//a3v4kxY8YYnSciIkI8++yzQgghdDqd0Gg0YtmyZdLx3NxcoVKpxDfffCOEEOLUqVMCgPj999+lMtu3bxcymUxcuXKlSdeel5cnAIi8vLxm1Lhp/t/2P0TgnC1i0Y8nmvyesR/uE4FztogfU5p2/URERO1Rc+7frTqmKC8vD56entLzxMREDBs2DEqlUnotOjoaaWlpuHXrllQmKirK6DzR0dFITEwEAKSnpyMzM9OojJubGyIiIqQyiYmJcHd3x8CBA6UyUVFRkMvlSEpKqvNaS0pKoNVqjR6W0qKWohy2FBEREZlTq4Wis2fP4r333sOzzz4rvZaZmQlfX1+jcobnmZmZDZapfrz6++or4+PjY3Tc3t4enp6eUpmalixZAjc3N+kREBDQrPo2hwzNmz1WWFKO6/klADjQmoiIyFyaHYrmzp0LmUzW4CM1NdXoPVeuXMHo0aPx6KOPYtKkSWa7eEuaN28e8vLypMelS5cs9llVLUVNayrKqGwlcndSwM2JCzcSERGZQ7NX/Zs1axYmTpzYYJng4GDp71evXsXIkSMxePBgowHUAKDRaJCVlWX0muG5RqNpsEz144bX/Pz8jMqEhYVJZbKzs43OUV5ejpycHOn9NalUKqhUqgbraS7S4o1NLH/RMB2/A1uJiIiIzKXZLUXe3t7o0aNHgw/DGKErV65gxIgRCA8Px5o1ayCXG39cZGQk9u7di7KyMum1+Ph4hIaGwsPDQyqTkJBg9L74+HhERkYCAIKCgqDRaIzKaLVaJCUlSWUiIyORm5uL5ORkqcyuXbug0+kQERHR3B+B2Rk6z3RNbCn6/YJ+vFUPX1cLXREREVH7Y7ExRYZA1LlzZ/zrX//C9evXkZmZaTSG54knnoBSqURsbCxOnjyJDRs2YNWqVYiLi5PKvPjii9ixYweWL1+O1NRULFq0CIcOHcL06dMB6FtZZsyYgTfffBM//vgjjh8/jqeeegr+/v6IiYkBAPTs2ROjR4/GpEmTcPDgQezbtw/Tp0/H448/Dn9/f0v9CJqsuQOtd6fpW72Gdfe20BURERG1PxbbNCs+Ph5nz57F2bNn0alTJ6NjhrEzbm5u2LlzJ6ZNm4bw8HB4eXlhwYIFRusHDR48GF9//TVeffVVzJ8/H926dcPmzZvRu3dvqczs2bNRWFiIyZMnIzc3F0OHDsWOHTvg4OAglVm3bh2mT5+OUaNGQS6XY+zYsXj33XctVf1mac7ijZdybuPc9ULYyWUY2s3LshdGRETUjshEU0f3tnNarRZubm7Iy8uDWq0267nfTTiDFfGnMW5QZyx5uE+DZb88cBGvbT6Bu7t4YOOUwWa9DiIioramOfdv7n1mA6om5DeeT389fR0AMJxdZ0RERGbFUGQDmjqmSAiBQxf1g6wju7LrjIiIyJwYimyANCW/kVB0/kYhcgpLobKXo3dH83bhERERtXcMRTZENNJ99nt6DgCgX4A7VPZ2rXFJRERE7QZDkQ1oaveZYX2iu7t4WPiKiIiI2h+GIhsgb+KK1ocu6luK7u7i2UhJIiIiai6GIhvQlBWttcVluHhTv+dZ/wC2FBEREZkbQ5ENMHSfNdRUdCarAACgUTtwE1giIiILYCiyAU1Z0fp0Vj4AoJuvSytcERERUfvDUGQDqgZa1x+LDKGoOzeBJSIisgiGIhvSUEuRofsslKGIiIjIIhiKbEBTFm9MY/cZERGRRTEU2YDGxlnfKizF9fwSAEA3thQRERFZBEORDWhsTNHZ6/qus47ujnBR2bfWZREREbUrDEU2oLGWIsP6RF28nFrleoiIiNojhiIbIJcbmorqPn4pRx+KAjwYioiIiCyFocgGNLai9aVblaHIk6GIiIjIUhiKbEEjs88u5xQBADp5OLbWFREREbU7DEU2oGpMEVuKiIiIrIWhyAZUzT6rfaykvAKZ2mIAHFNERERkSQxFNqChvc+u5hZDCMBRYQcvF2XrXhgREVE7wlBkAxpqKTLMPOvk4SitfE1ERETmx1BkA6qiTu1UlJHD8UREREStgaHIBjTUUnT5ln7mWQBnnhEREVkUQ5ENaGhM0bU8fSjyd2coIiIisiSGIhvQ0N5n1/L0M8/8GIqIiIgsiqHIBhgGUOvqaCoytBT5uTm05iURERG1OwxFNqC+DWF1OoGsvBIADEVERESWxlBkA+rrPrtZWIrSCh1kMsBXzVBERERkSQxFNqC+5YcyK8cTebuooLDjV0VERGRJvNPaAGn2WY3+M44nIiIiaj0MRTZA6j6rMapImnnmxplnRERElsZQZENqtxTpQ5GGLUVEREQWx1BkAwxT8uvrPvN3ZygiIiKyNIYiGyBvpPtMw+4zIiIii2MosgGGgdY1F2/M0hrGFLGliIiIyNIYimyArI7VG4UQUijycVW1/kURERG1MwxFNqAqE1WlovySchSX6QAAPq5sKSIiIrI0hiIbULWiddVr2Vr99h6uKns4Ku2scFVERETtC0ORTaicfVbtlez8ytWs1ew6IyIiag0MRTagrr3PrufrW4p82XVGRETUKhiKbEAd46yl7jMfthQRERG1CoYiG1DX4o2G7jPOPCMiImodDEU2oM6WosruM848IyIiah0MRTZAbvgWqjUVsfuMiIiodTEU2YC6VrSWZp+x+4yIiKhVWCwUXbhwAbGxsQgKCoKjoyO6du2KhQsXorS01KiMTCar9Thw4IDRuTZu3IgePXrAwcEBffr0wbZt24yOCyGwYMEC+Pn5wdHREVFRUThz5oxRmZycHIwfPx5qtRru7u6IjY1FQUGBparfPHXsfSa1FLH7jIiIqFVYLBSlpqZCp9Ph3//+N06ePIl33nkHq1evxvz582uV/fnnn3Ht2jXpER4eLh3bv38/xo0bh9jYWBw5cgQxMTGIiYnBiRMnpDJLly7Fu+++i9WrVyMpKQnOzs6Ijo5GcXGxVGb8+PE4efIk4uPjsWXLFuzduxeTJ0+2VPWbRRpTVJmJikorkF9SDoDdZ0RERK1GtKKlS5eKoKAg6Xl6eroAII4cOVLve/72t7+JMWPGGL0WEREhnn32WSGEEDqdTmg0GrFs2TLpeG5urlCpVOKbb74RQghx6tQpAUD8/vvvUpnt27cLmUwmrly50qRrz8vLEwBEXl5ek8o3x+60bBE4Z4t4YOVeIYQQF28UisA5W0T3V7YJnU5n9s8jIiJqL5pz/27VMUV5eXnw9PSs9fpf/vIX+Pj4YOjQofjxxx+NjiUmJiIqKsrotejoaCQmJgIA0tPTkZmZaVTGzc0NERERUpnExES4u7tj4MCBUpmoqCjI5XIkJSXVea0lJSXQarVGD0upOfvsZqG+68zLRSVN1yciIiLLarVQdPbsWbz33nt49tlnpddcXFywfPlybNy4EVu3bsXQoUMRExNjFIwyMzPh6+trdC5fX19kZmZKxw2vNVTGx8fH6Li9vT08PT2lMjUtWbIEbm5u0iMgIKCFNW9czRWtcwr14648nZUW+0wiIiIy1uxQNHfu3DoHR1d/pKamGr3nypUrGD16NB599FFMmjRJet3LywtxcXGIiIjA3Xffjbfffht///vfsWzZMtNrZqJ58+YhLy9Pely6dMlinyWDcWvQTYYiIiKiVmff3DfMmjULEydObLBMcHCw9PerV69i5MiRGDx4MD7++ONGzx8REYH4+HjpuUajQVZWllGZrKwsaDQa6bjhNT8/P6MyYWFhUpns7Gyjc5SXlyMnJ0d6f00qlQoqVesMcq5qKdL/aWgp6uDCUERERNRamh2KvL294e3t3aSyV65cwciRIxEeHo41a9ZALm+8YSolJcUo3ERGRiIhIQEzZsyQXouPj0dkZCQAICgoCBqNBgkJCVII0mq1SEpKwtSpU6Vz5ObmIjk5WZrZtmvXLuh0OkRERDSpLpZUNaZIn4puFujHFHVgSxEREVGraXYoaqorV65gxIgRCAwMxL/+9S9cv35dOmZonfniiy+gVCrRv39/AMD333+Pzz//HJ9++qlU9sUXX8Tw4cOxfPlyjBkzBuvXr8ehQ4ekVieZTIYZM2bgzTffRLdu3RAUFITXXnsN/v7+iImJAQD07NkTo0ePxqRJk7B69WqUlZVh+vTpePzxx+Hv72+pH0GT1dz7rKr7jNPxiYiIWovFQlF8fDzOnj2Ls2fPolOnTkbHRLXtLN544w1cvHgR9vb26NGjBzZs2IBHHnlEOj548GB8/fXXePXVVzF//nx069YNmzdvRu/evaUys2fPRmFhISZPnozc3FwMHToUO3bsgIND1cKH69atw/Tp0zFq1CjI5XKMHTsW7777rqWq3yyG7jNdjYHWbCkiIiJqPTJRPaFQvbRaLdzc3JCXlwe1Wm3Wcyedv4nHPj6AYG9n7Jo1An95/zccu5yHT58aiKhevo2fgIiIiOrUnPs39z6zAdJaRIbus4LK7jMOtCYiImo1DEU2oEYmYvcZERGRFTAU2YCqvc8EikorUFRWAYDrFBEREbUmhiIbUL2lyLDFh9JODheVxcbBExERUQ0MRTahakq+NJ7IWcl9z4iIiFoRQ5ENqGopElzNmoiIyEoYimxA1Zgi7ntGRERkLQxFNkBebUXrnEJu8UFERGQNDEU2oGpDWMEtPoiIiKyEocgGyAwDrQHkFHBMERERkTUwFNmAqpaiqoUbOaaIiIiodTEU2RABwYHWREREVsJQZAPqainiQGsiIqLWxVBkA6qPKbpZoJ99xpYiIiKi1sVQZAMMLUXFZRUoLNXve9aBs8+IiIhaFUORDTCEovzicgCAvVwGtSP3PSMiImpNDEU2QAbjPc647xkREVHrYyiyAfIa+YfjiYiIiFofQ5ENqNkoxIUbiYiIWh9DkU2o2X3GQdZEREStjaHIBtRqKWL3GRERUatjKLIBNYdUc0wRERFR62MosgE1Z5p5MBQRERG1OoYiG1CzpchFZWeV6yAiImrPGIpsQM0xRQ72DEVEREStjaHIBtRcvNFBwVBERETU2hiKbECtliKGIiIiolbHUGQDaocifi1EREStjXdfG1Bz9hlbioiIiFofQ5ENqDn7jKGIiIio9TEU2QB2nxEREVkf7742oNbsM07JJyIianUMRTaAs8+IiIisj6HIBtQcU6Sy59dCRETU2nj3tQXVUpHKXg65vGZMIiIiIktjKLIB1ccUseuMiIjIOhiKbED1hiHOPCMiIrIO3oFtQPXFG1WceUZERGQVDEU2oPoIIg6yJiIisg7egW1A9Sn5KnafERERWQXvwDag+kBrdp8RERFZB0ORLeBAayIiIqvjHdgGGHWfsaWIiIjIKhiKbAAHWhMREVkf78A2wHhKPr8SIiIia+Ad2AYYtxSx+4yIiMgaLBqK/vKXv6Bz585wcHCAn58fnnzySVy9etWozLFjx3DvvffCwcEBAQEBWLp0aa3zbNy4ET169ICDgwP69OmDbdu2GR0XQmDBggXw8/ODo6MjoqKicObMGaMyOTk5GD9+PNRqNdzd3REbG4uCggLzV7oF5NVaipRsKSIiIrIKi96BR44ciW+//RZpaWn47rvvcO7cOTzyyCPSca1Wi/vvvx+BgYFITk7GsmXLsGjRInz88cdSmf3792PcuHGIjY3FkSNHEBMTg5iYGJw4cUIqs3TpUrz77rtYvXo1kpKS4OzsjOjoaBQXF0tlxo8fj5MnTyI+Ph5btmzB3r17MXnyZEtWv8lkNTaEJSIiIisQreiHH34QMplMlJaWCiGE+PDDD4WHh4coKSmRysyZM0eEhoZKz//2t7+JMWPGGJ0nIiJCPPvss0IIIXQ6ndBoNGLZsmXS8dzcXKFSqcQ333wjhBDi1KlTAoD4/fffpTLbt28XMplMXLlypUnXnpeXJwCIvLy8Zta6cUWl5SJwzhYROGeLWLYj1eznJyIiaq+ac/9utWaJnJwcrFu3DoMHD4ZCoQAAJCYmYtiwYVAqlVK56OhopKWl4datW1KZqKgoo3NFR0cjMTERAJCeno7MzEyjMm5uboiIiJDKJCYmwt3dHQMHDpTKREVFQS6XIykpqc7rLSkpgVarNXpYCluKiIiIrM/id+A5c+bA2dkZHTp0QEZGBn744QfpWGZmJnx9fY3KG55nZmY2WKb68ervq6+Mj4+P0XF7e3t4enpKZWpasmQJ3NzcpEdAQECz6t0cRitac/FGIiIiq2j2HXju3LmQyWQNPlJTU6XyL7/8Mo4cOYKdO3fCzs4OTz31FIQQZq2EJcybNw95eXnS49KlSxb7LC7eSEREZH32zX3DrFmzMHHixAbLBAcHS3/38vKCl5cXunfvjp49eyIgIAAHDhxAZGQkNBoNsrKyjN5reK7RaKQ/6ypT/bjhNT8/P6MyYWFhUpns7Gyjc5SXlyMnJ0d6f00qlQoqlarBepoLF28kIiKyvmbfgb29vdGjR48GH9XHCFWn0+kA6MfrAEBkZCT27t2LsrIyqUx8fDxCQ0Ph4eEhlUlISDA6T3x8PCIjIwEAQUFB0Gg0RmW0Wi2SkpKkMpGRkcjNzUVycrJUZteuXdDpdIiIiGjuj8DsjBZvZPcZERGRVVjsDpyUlIT3338fKSkpuHjxInbt2oVx48aha9euUlh54oknoFQqERsbi5MnT2LDhg1YtWoV4uLipPO8+OKL2LFjB5YvX47U1FQsWrQIhw4dwvTp0wHoA8WMGTPw5ptv4scff8Tx48fx1FNPwd/fHzExMQCAnj17YvTo0Zg0aRIOHjyIffv2Yfr06Xj88cfh7+9vqR9Bk3HxRiIiIhtgqSlwx44dEyNHjhSenp5CpVKJLl26iClTpojLly8blTt69KgYOnSoUKlUomPHjuLtt9+uda5vv/1WdO/eXSiVSnHXXXeJrVu3Gh3X6XTitddeE76+vkKlUolRo0aJtLQ0ozI3b94U48aNEy4uLkKtVounn35a5OfnN7k+lpySr9PppCn5CX9kmv38RERE7VVz7t8yIe6AUc82QKvVws3NDXl5eVCr1WY/f5e5WwEAX8VGYGg3L7Ofn4iIqD1qzv2bA1hsDMcUERERWQfvwDbG1aHZEwKJiIjIDHgHthEv3BeC6wWlCPV1tfalEBERtUsMRTYi7v5Qa18CERFRu8buMyIiIiIwFBEREREBYCgiIiIiAsBQRERERASAoYiIiIgIAEMREREREQCGIiIiIiIADEVEREREABiKiIiIiAAwFBEREREBYCgiIiIiAsBQRERERASAoYiIiIgIAEMREREREQDA3toXcKcQQgAAtFqtla+EiIiImspw3zbcxxvCUNRE+fn5AICAgAArXwkRERE1V35+Ptzc3BosIxNNiU4EnU6Hq1evwtXVFTKZzKzn1mq1CAgIwKVLl6BWq8167jtBe68/wJ9Be68/wJ8B69++6w9Y7mcghEB+fj78/f0hlzc8aogtRU0kl8vRqVMni36GWq1ut/8xAKw/wJ9Be68/wJ8B69++6w9Y5mfQWAuRAQdaExEREYGhiIiIiAgAQ5FNUKlUWLhwIVQqlbUvxSrae/0B/gzae/0B/gxY//Zdf8A2fgYcaE1EREQEthQRERERAWAoIiIiIgLAUEREREQEgKGIiIiICABDkdV98MEH6NKlCxwcHBAREYGDBw9a+5LMYtGiRZDJZEaPHj16SMeLi4sxbdo0dOjQAS4uLhg7diyysrKMzpGRkYExY8bAyckJPj4+ePnll1FeXt7aVWmyvXv34sEHH4S/vz9kMhk2b95sdFwIgQULFsDPzw+Ojo6IiorCmTNnjMrk5ORg/PjxUKvVcHd3R2xsLAoKCozKHDt2DPfeey8cHBwQEBCApUuXWrpqTdJY/SdOnFjrd2L06NFGZe7k+i9ZsgR33303XF1d4ePjg5iYGKSlpRmVMdfv/e7duzFgwACoVCqEhIRg7dq1lq5eo5pS/xEjRtT6HZgyZYpRmTu1/gDw0UcfoW/fvtLig5GRkdi+fbt0vC1//0Dj9b8jvn9BVrN+/XqhVCrF559/Lk6ePCkmTZok3N3dRVZWlrUvzWQLFy4Ud911l7h27Zr0uH79unR8ypQpIiAgQCQkJIhDhw6Je+65RwwePFg6Xl5eLnr37i2ioqLEkSNHxLZt24SXl5eYN2+eNarTJNu2bROvvPKK+P777wUAsWnTJqPjb7/9tnBzcxObN28WR48eFX/5y19EUFCQKCoqksqMHj1a9OvXTxw4cED8+uuvIiQkRIwbN046npeXJ3x9fcX48ePFiRMnxDfffCMcHR3Fv//979aqZr0aq/+ECRPE6NGjjX4ncnJyjMrcyfWPjo4Wa9asESdOnBApKSni//7v/0Tnzp1FQUGBVMYcv/fnz58XTk5OIi4uTpw6dUq89957ws7OTuzYsaNV61tTU+o/fPhwMWnSJKPfgby8POn4nVx/IYT48ccfxdatW8Xp06dFWlqamD9/vlAoFOLEiRNCiLb9/QvReP3vhO+fociKBg0aJKZNmyY9r6ioEP7+/mLJkiVWvCrzWLhwoejXr1+dx3Jzc4VCoRAbN26UXvvjjz8EAJGYmCiE0N9g5XK5yMzMlMp89NFHQq1Wi5KSEoteuznUDAU6nU5oNBqxbNky6bXc3FyhUqnEN998I4QQ4tSpUwKA+P3336Uy27dvFzKZTFy5ckUIIcSHH34oPDw8jH4Gc+bMEaGhoRauUfPUF4oeeuihet/TluovhBDZ2dkCgNizZ48Qwny/97NnzxZ33XWX0Wc99thjIjo62tJVapaa9RdCf1N88cUX631PW6q/gYeHh/j000/b3fdvYKi/EHfG98/uMyspLS1FcnIyoqKipNfkcjmioqKQmJhoxSsznzNnzsDf3x/BwcEYP348MjIyAADJyckoKyszqnuPHj3QuXNnqe6JiYno06cPfH19pTLR0dHQarU4efJk61bEDNLT05GZmWlUZzc3N0RERBjV2d3dHQMHDpTKREVFQS6XIykpSSozbNgwKJVKqUx0dDTS0tJw69atVqpNy+3evRs+Pj4IDQ3F1KlTcfPmTelYW6t/Xl4eAMDT0xOA+X7vExMTjc5hKGNr/27UrL/BunXr4OXlhd69e2PevHm4ffu2dKwt1b+iogLr169HYWEhIiMj2933X7P+Brb+/XNDWCu5ceMGKioqjL58APD19UVqaqqVrsp8IiIisHbtWoSGhuLatWt4/fXXce+99+LEiRPIzMyEUqmEu7u70Xt8fX2RmZkJAMjMzKzzZ2M4dqcxXHNddapeZx8fH6Pj9vb28PT0NCoTFBRU6xyGYx4eHha5fnMYPXo0Hn74YQQFBeHcuXOYP38+HnjgASQmJsLOzq5N1V+n02HGjBkYMmQIevfuDQBm+72vr4xWq0VRUREcHR0tUaVmqav+APDEE08gMDAQ/v7+OHbsGObMmYO0tDR8//33ANpG/Y8fP47IyEgUFxfDxcUFmzZtQq9evZCSktIuvv/66g/cGd8/QxFZxAMPPCD9vW/fvoiIiEBgYCC+/fZbq/9HS9bx+OOPS3/v06cP+vbti65du2L37t0YNWqUFa/M/KZNm4YTJ07gt99+s/alWEV99Z88ebL09z59+sDPzw+jRo3CuXPn0LVr19a+TIsIDQ1FSkoK8vLy8N///hcTJkzAnj17rH1Zraa++vfq1euO+P7ZfWYlXl5esLOzqzXzICsrCxqNxkpXZTnu7u7o3r07zp49C41Gg9LSUuTm5hqVqV53jUZT58/GcOxOY7jmhr5vjUaD7Oxso+Pl5eXIyclpkz+X4OBgeHl54ezZswDaTv2nT5+OLVu24JdffkGnTp2k1831e19fGbVabRP/w1Ff/esSEREBAEa/A3d6/ZVKJUJCQhAeHo4lS5agX79+WLVqVbv5/uurf11s8ftnKLISpVKJ8PBwJCQkSK/pdDokJCQY9b+2FQUFBTh37hz8/PwQHh4OhUJhVPe0tDRkZGRIdY+MjMTx48eNbpLx8fFQq9VSU+ydJCgoCBqNxqjOWq0WSUlJRnXOzc1FcnKyVGbXrl3Q6XTSPx6RkZHYu3cvysrKpDLx8fEIDQ21ma6jprp8+TJu3rwJPz8/AHd+/YUQmD59OjZt2oRdu3bV6uYz1+99ZGSk0TkMZaz970Zj9a9LSkoKABj9Dtyp9a+PTqdDSUlJm//+62Oof11s8vs3y3BtapH169cLlUol1q5dK06dOiUmT54s3N3djUbe36lmzZoldu/eLdLT08W+fftEVFSU8PLyEtnZ2UII/dTUzp07i127dolDhw6JyMhIERkZKb3fMDXz/vvvFykpKWLHjh3C29vbpqfk5+fniyNHjogjR44IAGLFihXiyJEj4uLFi0II/ZR8d3d38cMPP4hjx46Jhx56qM4p+f379xdJSUnit99+E926dTOakp6bmyt8fX3Fk08+KU6cOCHWr18vnJycbGJKekP1z8/PFy+99JJITEwU6enp4ueffxYDBgwQ3bp1E8XFxdI57uT6T506Vbi5uYndu3cbTTm+ffu2VMYcv/eGKckvv/yy+OOPP8QHH3xgE1OyG6v/2bNnxeLFi8WhQ4dEenq6+OGHH0RwcLAYNmyYdI47uf5CCDF37lyxZ88ekZ6eLo4dOybmzp0rZDKZ2LlzpxCibX//QjRc/zvl+2cosrL33ntPdO7cWSiVSjFo0CBx4MABa1+SWTz22GPCz89PKJVK0bFjR/HYY4+Js2fPSseLiorEc889Jzw8PISTk5P461//Kq5du2Z0jgsXLogHHnhAODo6Ci8vLzFr1ixRVlbW2lVpsl9++UUAqPWYMGGCEEI/Lf+1114Tvr6+QqVSiVGjRom0tDSjc9y8eVOMGzdOuLi4CLVaLZ5++mmRn59vVObo0aNi6NChQqVSiY4dO4q33367tarYoIbqf/v2bXH//fcLb29voVAoRGBgoJg0aVKt/wG4k+tfV90BiDVr1khlzPV7/8svv4iwsDChVCpFcHCw0WdYS2P1z8jIEMOGDROenp5CpVKJkJAQ8fLLLxutUyPEnVt/IYR45plnRGBgoFAqlcLb21uMGjVKCkRCtO3vX4iG63+nfP8yIYQwT5sTERER0Z2LY4qIiIiIwFBEREREBIChiIiIiAgAQxERERERAIYiIiIiIgAMRUREREQAGIqIiIiIADAUEVE7tGjRIoSFhVn7MojIxjAUERFZkEwmw+bNm619GUTUBAxFRERERGAoIiILGzFiBKZPn47p06fDzc0NXl5eeO2112DYYejDDz9Et27d4ODgAF9fXzzyyCPSe3U6HZYsWYKgoCA4OjqiX79++O9//ysdX7t2Ldzd3Y0+b/PmzZDJZEavvf322/D19YWrqytiY2NRXFxsdFyn02Hx4sXo1KkTVCoVwsLCsGPHjibVr7S0FNOnT4efnx8cHBwQGBiIJUuWAAC6dOkCAPjrX/8KmUwmPQeAH374AQMGDICDgwOCg4Px+uuvo7y8XDouk8nw0Ucf4YEHHoCjoyOCg4ON6k5EFmC2XdSIiOowfPhw4eLiIl588UWRmpoqvvrqK+Hk5CQ+/vhj8fvvvws7Ozvx9ddfiwsXLojDhw+LVatWSe998803RY8ePcSOHTvEuXPnxJo1a4RKpRK7d+8WQgixZs0a4ebmZvR5mzZtEtX/aduwYYNQqVTi008/FampqeKVV14Rrq6uol+/flKZFStWCLVaLb755huRmpoqZs+eLRQKhTh9+nSj9Vu2bJkICAgQe/fuFRcuXBC//vqr+Prrr4UQQmRnZ0ubol67dk1kZ2cLIYTYu3evUKvVYu3ateLcuXNi586dokuXLmLRokXSeQGIDh06iE8++USkpaWJV199VdjZ2YlTp041+zsgoqZhKCIiixo+fLjo2bOn0Ol00mtz5swRPXv2FN99951Qq9VCq9XWel9xcbFwcnIS+/fvN3o9NjZWjBs3TgjRtFAUGRkpnnvuOaMyERERRqHI399fvPXWW0Zl7r777lrvq8vzzz8v7rvvPqP6VQdAbNq0yei1UaNGiX/+859Gr3355ZfCz8/P6H1Tpkypdd1Tp05t9JqIqGXYfUZEFnfPPfcYdWlFRkbizJkzGDVqFAIDAxEcHIwnn3wS69atw+3btwEAZ8+exe3bt/GnP/0JLi4u0uM///kPzp071+TP/uOPPxAREWH0WmRkpPR3rVaLq1evYsiQIUZlhgwZgj/++KPR80+cOBEpKSkIDQ3FCy+8gJ07dzb6nqNHj2Lx4sVG9Zo0aRKuXbsm1b/mdRqeN+WaiKhl7K19AUTUfrm4uODw4cPYvXs3du7ciQULFmDRokX4/fffUVBQAADYunUrOnbsaPQ+lUoFAJDL5dLYJIOysrLWufhKAwYMQHp6OrZv346ff/4Zf/vb3xAVFdXg+J+CggK8/vrrePjhh2sdc3BwsOTlElED2FJERBaXlJRk9PzAgQPo1q0b7OzsYG9vj6ioKCxduhTHjh3DhQsXsGvXLvTq1QsqlQoZGRkICQkxegQEBAAAvL29kZ+fj8LCQuncKSkpRp/Vs2fPOj/fQK1Ww9/fH/v27TMqs2/fPvTq1atJ9VOr1XjsscfwySefYMOGDfjuu++Qk5MDAFAoFKioqDAqP2DAAKSlpdWqV0hICOTyqn+Wq1+n4XnPnj2bdE1E1HxsKSIii8vIyEBcXByeffZZHD58GO+99x6WL1+OLVu24Pz58xg2bBg8PDywbds26HQ6hIaGwtXVFS+99BJmzpwJnU6HoUOHIi8vD/v27YNarcaECRMQEREBJycnzJ8/Hy+88AKSkpKwdu1ao89+8cUXMXHiRAwcOBBDhgzBunXrcPLkSQQHB0tlXn75ZSxcuBBdu3ZFWFgY1qxZg5SUFKxbt67Ruq1YsQJ+fn7o378/5HI5Nm7cCI1GI82K69KlCxISEjBkyBCoVCp4eHhgwYIF+POf/4zOnTvjkUcegVwux9GjR3HixAm8+eab0rk3btyIgQMHYujQoVi3bh0OHjyIzz77zCzfCRHVwdqDmoiobRs+fLh47rnnxJQpU4RarRYeHh5i/vz5QqfTiV9//VUMHz5ceHh4CEdHR9G3b1+xYcMG6b06nU6sXLlShIaGCoVCIby9vUV0dLTYs2ePVGbTpk0iJCREODo6ij//+c/i448/FjX/aXvrrbeEl5eXcHFxERMmTBCzZ882GmhdUVEhFi1aJDp27CgUCoXo16+f2L59e5Pq9/HHH4uwsDDh7Ows1Gq1GDVqlDh8+LB0/McffxQhISHC3t5eBAYGSq/v2LFDDB48WDg6Ogq1Wi0GDRokPv74Y+k4APHBBx+IP/3pT0KlUokuXboY/WyIyPxkQtTokCciMqMRI0YgLCwMK1eutPal3FFkMhk2bdqEmJgYa18KUbvBMUVEREREYCgiImrQP//5T6Op89UfDzzwgLUvj4jMiN1nREQNyMnJkWaS1eTo6FhruQAiunMxFBERERGB3WdEREREABiKiIiIiAAwFBEREREBYCgiIiIiAsBQRERERASAoYiIiIgIAEMREREREQCGIiIiIiIAwP8H5/CBMZYVuIUAAAAASUVORK5CYII=",
      "text/plain": [
       "
"
      ]
     },
     "metadata": {}
    },
    {
     "output_type": "display_data",
     "data": {
      "image/png": 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",
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   "language": "python",
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