From bd547fb745b2ede35aadcc81228e2b23edd5ca21 Mon Sep 17 00:00:00 2001 From: "filipe@flexcompute.com" Date: Wed, 16 Jul 2025 17:15:47 -0300 Subject: [PATCH 1/4] adding directional coupler example --- DirectionalCoupler.ipynb | 1358 +++++++++++++++++++++++++++++ docs/case_studies/pic.rst | 1 + docs/features/parameter_sweep.rst | 3 +- misc/import_file_mapping.json | 142 ++- 4 files changed, 1473 insertions(+), 31 deletions(-) create mode 100644 DirectionalCoupler.ipynb diff --git a/DirectionalCoupler.ipynb b/DirectionalCoupler.ipynb new file mode 100644 index 00000000..0049d25a --- /dev/null +++ b/DirectionalCoupler.ipynb @@ -0,0 +1,1358 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "-" + } + }, + "source": [ + "# Directional Coupler\n", + "\n", + "Directional couplers are fundamental components in photonic integrated circuits, enabling efficient splitting and combining of optical signals. By placing two parallel waveguides in close proximity, these passive devices exploit evanescent field coupling to control how light is distributed between channels. It is also possible to control the output by adjusting the relative phase between the inputs, enabling flexible power splitting ratios and switching behavior. Their design and compatibility with silicon-on-insulator technology have made them a popular choice for applications ranging from wavelength-division multiplexing to optical switching and signal processing.\n", + "\n", + "An important consideration is how fabrication variations might affect device performance. Hence, one common approach is to sweep over different parameters and see how the quantities of interest behave.\n", + "\n", + "In this notebook, we will demonstrate how to set up a simple directional coupler simulation, illustrating the common steps of the workflow:\n", + "\n", + "[1](#1). Importing the geometry using [gdstk](https://heitzmann.github.io/gdstk/). For the process of this geometry, please follow the steps presented in [this](https://www.flexcompute.com/tidy3d/examples/notebooks/GDSCreation) example.\n", + "\n", + "[2](#2). Placing the [ModeSource](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.ModeSource.html) and [ModeMonitors](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.ModeMonitor.html) to excite the first TE mode and analyze the transmittance and losses on both arms\n", + "\n", + "[3](#3). Carry out the post-process analysis to find the 50/50 splitting frequency and efficiency.\n", + "\n", + "[4](#4). Create a parametric sweep over different values of the sidewall angle and its effect on the splitting frequency and efficiency, and create a [Batch](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.web.api.container.Batch.html) object to run in parallel.\n", + "\n", + "[5](#5). Use the `Simulation.updated_copy` method to easily create a simulation with two sources at the input ports with a $\\pi$/2 phase difference.\n", + "\n", + "\"Schematic\n", + "\n", + "For instructions on how to calculate the full S-matrix, please refer to our [SMatrix](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.plugins.smatrix.Port.html) tutorial. Additionally, if you are new to the finite-difference time-domain (FDTD) method, we highly recommend going through our [FDTD101](https://www.flexcompute.com/fdtd101/) tutorials." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "First, we import the relevant structures. We will use gdstk for importing the geometry. To install it, uncomment the `!pip install gdstk` line." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "# install gdstk\n", + "#!pip install gdstk\n", + "\n", + "# Standard python imports\n", + "import gdstk\n", + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "\n", + "# Tidy3d import\n", + "import tidy3d as td\n", + "from tidy3d import web\n", + "from tidy3d.plugins.mode import ModeSolver" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "tags": [] + }, + "source": [ + "## Importing the Geometry \n", + "\n", + "We will use gdstk to import the geometry into a [Polyslab](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.PolySlab.html) geometry, and extrude it along the z-direction (`axis=2`) with a given sidewall angle. For detailed instructions, please refer to [this](https://www.flexcompute.com/tidy3d/examples/notebooks/GDSImport) tutorial." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "gds_path = \"misc/coupler.gds\"\n", + "\n", + "# Load a GDSII library from the file previously created\n", + "lib_loaded = gdstk.read_gds(gds_path)\n", + "all_cells = {c.name: c for c in lib_loaded.cells}\n", + "\n", + "# Define waveguide height\n", + "wg_height = 0.22\n", + "dilation = 0.02\n", + "\n", + "# Define reference plane and sidewall angle\n", + "reference_plane = \"bottom\"\n", + "sidewall_angle = np.pi / 6\n", + "\n", + "substrate_geo = td.Geometry.from_gds(\n", + " all_cells[\"COUPLER\"],\n", + " gds_layer=0,\n", + " gds_dtype=0,\n", + " axis=2,\n", + " slab_bounds=(-4, 0),\n", + " reference_plane=reference_plane,\n", + ")\n", + "\n", + "arms_geo = td.Geometry.from_gds(\n", + " all_cells[\"COUPLER\"],\n", + " gds_layer=1,\n", + " gds_dtype=0,\n", + " axis=2,\n", + " slab_bounds=(0, wg_height),\n", + " sidewall_angle=sidewall_angle,\n", + " dilation=dilation,\n", + " reference_plane=reference_plane,\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Set up Structures\n", + "\n", + "Next, we assign material properties to the imported geometries and create the [`td.Structures`](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/structures.html) with those material properties." + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "# Permittivity of waveguide and substrate\n", + "wg_n = 3.48\n", + "sub_n = 1.45\n", + "medium_wg = td.Medium(permittivity=wg_n**2)\n", + "medium_sub = td.Medium(permittivity=sub_n**2)\n", + "\n", + "# Substrate\n", + "substrate = td.Structure(geometry=substrate_geo, medium=medium_sub)\n", + "\n", + "# Waveguides\n", + "arms = td.Structure(geometry=arms_geo, medium=medium_wg)\n", + "\n", + "structures = [substrate, arms]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Set up Simulation \n", + "\n", + "Now we set up the simulation. First, we define the wavelength of interest and set the runtime." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "# Wavelength range\n", + "wl1 = 1.4\n", + "wl2 = 1.7\n", + "\n", + "# Transforming in frequency\n", + "f1 = td.C_0 / wl2\n", + "f2 = td.C_0 / wl1\n", + "\n", + "fwidth = (f2 - f1) / 2\n", + "freq0 = f1 + fwidth\n", + "wl0 = td.C_0 / freq0\n", + "\n", + "# Frequencies to analyze\n", + "num_freqs = 21\n", + "freqs = [freq0] if num_freqs == 1 else np.linspace(freq0 - fwidth, freq0 + fwidth, num_freqs)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Now, we add the [ModeSource](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.ModeSource.html), which excites the first order TE mode (`mode_index = 0`). To analyze the transmittance, we will place [ModeMonitors](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.ModeMonitor.html) at the end of both output arms. These monitors will carry out mode decomposition and analyze the fraction of power transmitted in each mode. Since we are only interested in the first order TE mode, the number of modes analyzed can be just 1." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "# Source\n", + "source_time = td.GaussianPulse(freq0=freq0, fwidth=fwidth)\n", + "source = td.ModeSource(\n", + " center=(-8, -2, 0), size=(0, 2, 1), source_time=source_time, mode_index=0, direction=\"+\"\n", + ")\n", + "\n", + "# Field monitor\n", + "field_mon = td.FieldMonitor(\n", + " name=\"field_mon\",\n", + " size=(td.inf, td.inf, 0),\n", + " center=(0, 0, wg_height / 2),\n", + " freqs=freqs,\n", + ")\n", + "\n", + "# Mode monitor\n", + "mode_spec = td.ModeSpec(num_modes=1)\n", + "mode_mon_up = td.ModeMonitor(\n", + " center=(8, 2, 0), size=(0, 2, 1), freqs=freqs, name=\"mode_mon_up\", mode_spec=mode_spec\n", + ")\n", + "\n", + "mode_mon_down = td.ModeMonitor(\n", + " center=(8, -2, 0), size=mode_mon_up.size, freqs=freqs, name=\"mode_mon_down\", mode_spec=mode_spec\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Finally, we define the grid with our [AutoGrid](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.AutoGrid.html) object, which automatically creates a non-uniform mesh, and place everything together in the [Simulation](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.Simulation.html) object." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "# GridSpec\n", + "min_steps_per_wvl = 15\n", + "grid_spec = td.GridSpec.auto(min_steps_per_wvl=min_steps_per_wvl)\n", + "\n", + "# Simulation size\n", + "sim_size = (17, 8, wg_height + 2)\n", + "sim_center = list(arms_geo.bounding_box.center)\n", + "sim_center[2] = 0\n", + "\n", + "### Initialize and visualize simulation ###\n", + "sim = td.Simulation(\n", + " size=sim_size,\n", + " center=sim_center,\n", + " grid_spec=grid_spec,\n", + " structures=structures,\n", + " run_time=5e-12,\n", + " boundary_spec=td.BoundarySpec.all_sides(boundary=td.PML()),\n", + " sources=[source],\n", + " monitors=[field_mon, mode_mon_up, mode_mon_down],\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Plot Simulation Geometry\n", + "\n", + "It is a good practice to check the simulation and see if everything is correctly set. That can be easily achieved with the `Simulation.plot` method:" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "editable": true, + "slideshow": { + "slide_type": "" + }, + "tags": [] + }, + "outputs": [ + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(17, 5))\n", + "\n", + "sim.plot(z=wg_height / 2, lw=1, edgecolor=\"k\", ax=ax1)\n", + "sim.plot(x=0.1, lw=1, edgecolor=\"k\", ax=ax2)\n", + "\n", + "ax2.set_xlim([-3, 3])\n", + "_ = ax2.set_ylim([-1, 1])\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We can also see the 3D model." + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "
\n", + " \n", + " " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "sim.plot_3d()\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Before running the simulation, we can check the **maximum** possible Flexcredit cost." + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
16:49:20 -03 Created task 'directional coupler' with task_id                    \n",
+       "             'fdve-78d87a06-5318-4056-a6c5-7979e3776c81' and task_type 'FDTD'.  \n",
+       "
\n" + ], + "text/plain": [ + "\u001b[2;36m16:49:20 -03\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'directional coupler'\u001b[0m with task_id \n", + "\u001b[2;36m \u001b[0m\u001b[32m'fdve-78d87a06-5318-4056-a6c5-7979e3776c81'\u001b[0m and task_type \u001b[32m'FDTD'\u001b[0m. \n" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
             View task using web UI at                                          \n",
+       "             'https://tidy3d.simulation.cloud/workbench?taskId=fdve-78d87a06-531\n",
+       "             8-4056-a6c5-7979e3776c81'.                                         \n",
+       "
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             Task folder: 'default'.                                            \n",
+       "
\n" + ], + "text/plain": [ + "\u001b[2;36m \u001b[0m\u001b[2;36m \u001b[0mTask folder: \u001b]8;id=418019;https://tidy3d.simulation.cloud/folders/folder-dc5128c7-562b-4bcf-a539-9356f1d308ca\u001b\\\u001b[32m'default'\u001b[0m\u001b]8;;\u001b\\. \n" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "f8c9304fb9b14de1b5cdcff25e203f46", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Output()" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
\n"
+      ],
+      "text/plain": []
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
\n",
+       "
\n"
+      ],
+      "text/plain": [
+       "\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
16:49:23 -03 Maximum FlexCredit cost: 0.258. Minimum cost depends on task       \n",
+       "             execution details. Use 'web.real_cost(task_id)' to get the billed  \n",
+       "             FlexCredit cost after a simulation run.                            \n",
+       "
\n"
+      ],
+      "text/plain": [
+       "\u001b[2;36m16:49:23 -03\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.258\u001b[0m. Minimum cost depends on task       \n",
+       "\u001b[2;36m             \u001b[0mexecution details. Use \u001b[32m'web.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed  \n",
+       "\u001b[2;36m             \u001b[0mFlexCredit cost after a simulation run.                            \n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
16:49:24 -03 Maximum FlexCredit cost: 0.258. Minimum cost depends on task       \n",
+       "             execution details. Use 'web.real_cost(task_id)' to get the billed  \n",
+       "             FlexCredit cost after a simulation run.                            \n",
+       "
\n"
+      ],
+      "text/plain": [
+       "\u001b[2;36m16:49:24 -03\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.258\u001b[0m. Minimum cost depends on task       \n",
+       "\u001b[2;36m             \u001b[0mexecution details. Use \u001b[32m'web.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed  \n",
+       "\u001b[2;36m             \u001b[0mFlexCredit cost after a simulation run.                            \n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Estimating the cost\n",
+    "task_id = web.upload(sim, \"directional coupler\")\n",
+    "cost = web.estimate_cost(task_id)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Finally, we can run the simulation and analyze the data."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "
             Created task 'directional coupler' with task_id                    \n",
+       "             'fdve-4f0ad930-d203-403a-97a5-56e65d98030a' and task_type 'FDTD'.  \n",
+       "
\n"
+      ],
+      "text/plain": [
+       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'directional coupler'\u001b[0m with task_id                    \n",
+       "\u001b[2;36m             \u001b[0m\u001b[32m'fdve-4f0ad930-d203-403a-97a5-56e65d98030a'\u001b[0m and task_type \u001b[32m'FDTD'\u001b[0m.  \n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
             View task using web UI at                                          \n",
+       "             'https://tidy3d.simulation.cloud/workbench?taskId=fdve-4f0ad930-d20\n",
+       "             3-403a-97a5-56e65d98030a'.                                         \n",
+       "
\n"
+      ],
+      "text/plain": [
+       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mView task using web UI at                                          \n",
+       "\u001b[2;36m             \u001b[0m\u001b]8;id=984010;https://tidy3d.simulation.cloud/workbench?taskId=fdve-4f0ad930-d203-403a-97a5-56e65d98030a\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=806941;https://tidy3d.simulation.cloud/workbench?taskId=fdve-4f0ad930-d203-403a-97a5-56e65d98030a\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=984010;https://tidy3d.simulation.cloud/workbench?taskId=fdve-4f0ad930-d203-403a-97a5-56e65d98030a\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=771636;https://tidy3d.simulation.cloud/workbench?taskId=fdve-4f0ad930-d203-403a-97a5-56e65d98030a\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=984010;https://tidy3d.simulation.cloud/workbench?taskId=fdve-4f0ad930-d203-403a-97a5-56e65d98030a\u001b\\\u001b[32m-4f0ad930-d20\u001b[0m\u001b]8;;\u001b\\\n",
+       "\u001b[2;36m             \u001b[0m\u001b]8;id=984010;https://tidy3d.simulation.cloud/workbench?taskId=fdve-4f0ad930-d203-403a-97a5-56e65d98030a\u001b\\\u001b[32m3-403a-97a5-56e65d98030a'\u001b[0m\u001b]8;;\u001b\\.                                         \n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
             Task folder: 'default'.                                            \n",
+       "
\n"
+      ],
+      "text/plain": [
+       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mTask folder: \u001b]8;id=403570;https://tidy3d.simulation.cloud/folders/folder-dc5128c7-562b-4bcf-a539-9356f1d308ca\u001b\\\u001b[32m'default'\u001b[0m\u001b]8;;\u001b\\.                                            \n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "2718332f908340db9d7d2a78cbf04835",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Output()"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
\n"
+      ],
+      "text/plain": []
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
\n",
+       "
\n"
+      ],
+      "text/plain": [
+       "\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
16:49:27 -03 Maximum FlexCredit cost: 0.258. Minimum cost depends on task       \n",
+       "             execution details. Use 'web.real_cost(task_id)' to get the billed  \n",
+       "             FlexCredit cost after a simulation run.                            \n",
+       "
\n"
+      ],
+      "text/plain": [
+       "\u001b[2;36m16:49:27 -03\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.258\u001b[0m. Minimum cost depends on task       \n",
+       "\u001b[2;36m             \u001b[0mexecution details. Use \u001b[32m'web.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed  \n",
+       "\u001b[2;36m             \u001b[0mFlexCredit cost after a simulation run.                            \n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
16:49:28 -03 status = success                                                   \n",
+       "
\n"
+      ],
+      "text/plain": [
+       "\u001b[2;36m16:49:28 -03\u001b[0m\u001b[2;36m \u001b[0mstatus = success                                                   \n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "0804c80003a9421cb6081832b340e0ef",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Output()"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
\n"
+      ],
+      "text/plain": []
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
\n",
+       "
\n"
+      ],
+      "text/plain": [
+       "\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
16:49:49 -03 loading simulation from simulation_data.hdf5                       \n",
+       "
\n"
+      ],
+      "text/plain": [
+       "\u001b[2;36m16:49:49 -03\u001b[0m\u001b[2;36m \u001b[0mloading simulation from simulation_data.hdf5                       \n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sim_data = web.run(sim, \"directional coupler\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "##  Postprocessing \n",
+    "\n",
+    "Now we would like to analyze the output of each arm as a function of wavelength, and find the frequency where the fields are equally distributed, and the losses.\n",
+    "\n",
+    "The monitor decomposes the fields into mode components, and since the source is [normalized](https://docs.flexcompute.com/projects/tidy3d/en/latest/faq/docs/faq/How-are-results-normalized.html), the transmittance of each component is simply $\\text{|amplitude|}^2$.\n",
+    "\n",
+    "For finding the point where the amplitudes of each arm are the same, we will just look at the signal change of the difference between both signals, which is the crossing point. For better resolution, we will interpolate the data."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "
"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Crossing wavelength :1.53\n",
+      "Total transmittance: 0.9911578134355559\n"
+     ]
+    }
+   ],
+   "source": [
+    "from scipy.interpolate import interp1d\n",
+    "\n",
+    "\n",
+    "def postprocess(sim_data, plot=True):\n",
+    "    transmission_up = sim_data[\"mode_mon_up\"].amps.sel(mode_index=0, direction=\"+\").abs ** 2\n",
+    "    transmission_down = sim_data[\"mode_mon_down\"].amps.sel(mode_index=0, direction=\"+\").abs ** 2\n",
+    "    freqs = transmission_up.f.values\n",
+    "\n",
+    "    diff = (transmission_up - transmission_down).values\n",
+    "\n",
+    "    # Interpolate difference to find zero crossing (sign change)\n",
+    "    sign_change = np.where(np.diff(np.sign(diff)))[0]\n",
+    "    if len(sign_change) == 0:\n",
+    "        crossing_freq = freqs[np.argmin(abs(diff))]\n",
+    "        print(\"No sign change found, showing closest point only.\")\n",
+    "    else:\n",
+    "        i = sign_change[0]\n",
+    "        f_interp = interp1d(diff[i : i + 2], freqs[i : i + 2])\n",
+    "        crossing_freq = f_interp(0)\n",
+    "    amp_crossing = np.interp(crossing_freq, freqs, transmission_up)\n",
+    "    if plot:\n",
+    "        fig, ax = plt.subplots()\n",
+    "        ax = transmission_up.plot(ax=ax)[0].axes\n",
+    "        transmission_down.plot(ax=ax)\n",
+    "\n",
+    "        ax.plot([crossing_freq], [amp_crossing], \"*\", color=\"black\")\n",
+    "\n",
+    "        ax.set_ylabel(\"Transmittance\")\n",
+    "\n",
+    "        plt.show()\n",
+    "    return float(crossing_freq), 2 * amp_crossing\n",
+    "\n",
+    "\n",
+    "cross_freq, total_transmittance = postprocess(sim_data)\n",
+    "\n",
+    "print(f\"Crossing wavelength :{td.C_0 / cross_freq:.2f}\")\n",
+    "print(f\"Total transmittance: {total_transmittance}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now, we can easily plot the E field with the `SimulationData.plot_field` method. As we can see, the input field is equally split over the two output arms."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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JM888w/Of/3wGBgY4++yzOfDAA1m/fj3/+Z//SblcxnXddO473/lO+vr6uOSSS1KL2kc+8hEuu+wyTjzxRM455xweeughrrrqKu655x7uvPNOHMehXq9z0kknUavVOO+881iyZAnr16/nxz/+MQMDA3R1dfHnP/+ZV77ylRx++OFcfvnlZDIZHn300UmDt6eyXxiGvPrVr+bXv/41Z599NgcddBB/+tOf+NznPsfDDz/MzTffnM697LLL+MhHPsKxxx7L5Zdfjuu63H333fzsZz/j5S9/OZ///Oc577zzKBaLfOhDHwJg8eLF467v2muv5a1vfStHH300V1xxBZs2beILX/gCd955J7///e/p7u5O5wZBwEknncQxxxzD//2//5f/+Z//4TOf+Qz77rsv55xzzoT34dprr6VYLHLBBRdQLBb52c9+xiWXXMLQ0BCf/vSngcjVODg4yLp16/jc5z4HMEZ8NPOOd7yj5cMW4JZbbuHb3/42ixYtSse2bt064doSOjo6yGQyAPz+97+nUChw0EEHtcx5/vOfn24//vjjp3TcucTzPO65555J7/9UuOKKK8jlcnzgAx/g0Ucf5Utf+hKO46C1pr+/n4985CP89re/5dprr2X16tVccsklLfsfeeSRGGP4zW9+wytf+codXo+wOzJzV+XEhzXU63WGhoZahjOZTPo728wxxxzDtddeywEHHMCGDRu47LLLeOELX8j999/Pxo0bcV235bMNos/JjRs3zv7ap4MRhN2QN7/5zUZrbe65554x28IwNMYYc8011xjAHH/88cb3/XT75s2bjeu65uUvf7kJgiAd//KXv2wA8+///u/GGGN+//vfG8DcdNNN467jc5/7nAHMli1bprX+qez3zW9+02itza9+9auW8auvvtoA5s477zTGGPPII48YrbX5+7//+5brMaZxL4wx5pBDDjEnnHDCmPP8/Oc/N4D5+c9/bowxpl6vm0WLFplDDz3UVCqVdN6Pf/xjA5hLLrkkHTvzzDMNYC6//PKWYz73uc81Rx555MQ3wRhTLpfHjL3jHe8w+XzeVKvVdOzkk082e+2116THa8cjjzxiurq6zMte9rKW9wHR3/mTPq655pqWdeyzzz5jzlEqlQxgPvCBD0x5XTfddFPLfZ+I6V7/o48+agDzpS99acy2vfbay5x55pljxk844YSW90fyvjj00ENNvV5Px0877TSjlDJ/+7d/27L/2rVr267xmWeeMYD55Cc/OeX1C88ebrjhBrP2gGUm/N77Z/1x4PIF5owzzhjzO3vppZdOaW39/f2ms7PTfP3rXzff/va3jeu6Y+YcffTR5sILL5zluzI9xPUp7HaEYcjNN9/Mq171Ko466qgx25VSLT+//e1vx7Ks9Of/+Z//oV6vc/7557fEZb397W+ns7OTn/zkJwB0dXUBcOutt1Iul9uuJfnr6wc/+AHhNEzxU9nvpptu4qCDDuLAAw9k69at6eMlL3kJAD//+c+ByMUVhiGXXHLJmDiz0fdiKtx7771s3ryZd77znWSz2XT85JNP5sADD0zvTzOjA9Zf+MIX8thjj016rlwulz4fHh5m69atvPCFL6RcLvOXv/xl2msfTalU4u///u/p6enhO9/5Tsv74LbbbpvS46STTkr3qVQqbf9ST+5TpVLZ4TXPBtu2bQOgp6dnh4/15je/ucUFe8wxx2CM4W1ve1vLvGOOOYann34a3/dbxpM1TNWCKTwLMcxZMsEb3vAGBgcHWx4XXXTRlJbV3d3N/vvvz6OPPsqSJUuo1+tjwl82bdrEkiVLZvmGTA9xfQq7HVu2bGFoaIhDDz10SvNXr17d8vOTTz4JwAEHHNAy7rou++yzT7p99erVXHDBBXz2s5/l29/+Ni984Qt59atfzRlnnJGKuDe84Q18/etf5//8n//DBz7wAV760pfy2te+ln/4h3+YMDh/Kvs98sgjPPjgg/T19bU9xubNmwH461//itaagw8+eEr3YzLGuz8QxWw0Z0lBJFJGr7Gnp4f+/v5Jz/XnP/+Ziy++mJ/97Gdj3BfNcYAz5e1vfzt//etf+c1vfkNvb2/LttHu0amQy+XaxmEl5Seahed8wJgddzetWrWq5efkvb9y5cox42EYMjg42HKvkzXM5I8G4VnEHPX6dF2Xzs7OGe07MjLCX//6V/7xH/+RI488EsdxuP322zn11FOBKEv7qaeeYu3atbO55GkjQk141rMjX56f+cxneMtb3sIPfvADfvrTn/Lud7+bK664gt/+9resWLGCXC7HL3/5S37+85/zk5/8hFtuuYUbb7yRl7zkJfz0pz9tseCMXtNk+4VhyGGHHcZnP/vZtscY/UW5qxjvGidjYGCAE044gc7OTi6//HL23Xdfstksv/vd73j/+98/LQtlO77whS/wne98h29961scccQRY7ZPNe6kq6srfQ8tXbqUn//85xhjWoTHhg0bAGZURmMuSITSVMRywuhrShjv9R1vfLQ4TNaQZNcJwq7ife97H6961avYa6+9eOaZZ7j00kuxLIvTTjuNrq4uzjrrLC644AIWLFhAZ2cn5513HmvXruUFL3jBLl23uD6F3Y6+vj46Ozu5//77Z7T/XnvtBUR/LTVTr9d5/PHH0+0Jhx12GBdffDG//OUv+dWvfsX69eu5+uqr0+1aa1760pfy2c9+lgceeICPf/zj/OxnP0tdk+Mx2X777rsv27dv56UvfSknnnjimEdi8dp3330Jw5AHHnhgwvNN1aIx3v1Jxkbfn5lyxx13sG3bNq699lre85738MpXvpITTzyxrbtuutaYX/3qV7zvfe/j/PPP5/TTT287Z+nSpVN63Hjjjek+RxxxBOVymQcffLDlWHfffXe6fT6watUqcrkcjz/+eNvtw8PDY8bmqrBnsobRCRjCnoSJuhPM+mN6q1i3bh2nnXYaBxxwAK9//evp7e3lt7/9beoR+NznPscrX/lKTj31VF70ohexZMkSvve9783B/ZgeItSE3Q6tNaeccgo/+tGPuPfee8dsn8zdc+KJJ+K6Ll/84hdb5n7jG99gcHCQk08+GYChoaEx8TaHHXYYWuvU/dWu5EDyZd3ORZYwlf1e//rXs379er72ta+NmVupVNIM1lNOOQWtNZdffvkYK1Tz9RUKhTHxF+046qijWLRoEVdffXXLNfz3f/83Dz74YHp/dpTEItO8xnq93rblUKFQmLIrdMOGDbz+9a/n+OOPTzNH2zGTGLXXvOY1OI7TskZjDFdffTXLly/n2GOPbVnHX/7yFzzPm9K6ZxPHcTjqqKPa/n4A3HXXXS3dAv785z/zyCOPzIqrdDT33XcfSqld7j4ShBtuuIFnnnmGWq3GunXruOGGG9h3333T7dlslq985Sts376dUqnE9773vV0enwbi+hR2Uz7xiU/w05/+lBNOOCEtXbFhwwZuuukmfv3rX49JsW6mr6+Piy66iMsuu4xXvOIVvPrVr+ahhx7iyiuv5Oijj+aMM84A4Gc/+xnvete7eN3rXsf++++P7/t885vfxLKsNIbh8ssv55e//CUnn3wye+21F5s3b+bKK69kxYoVE5ZpmMp+//iP/8h3v/td/umf/omf//znHHfccQRBwF/+8he++93vcuutt3LUUUex33778aEPfYiPfvSjvPCFL+S1r30tmUyGe+65h2XLlnHFFVcAUZmEq666io997GPst99+LFq0KE1MaMZxHD75yU/y1re+lRNOOIHTTjstLc+x99578973vnemL1sLxx57LD09PZx55pm8+93vRinFN7/5zbZi4cgjj+TGG2/kggsu4Oijj6ZYLI5byPXd7343W7Zs4cILLxzTLeDwww/n8MMPB2YWo7ZixQrOP/98Pv3pT+N5HkcffTQ333wzv/rVr/j2t7/d4g686KKLuO6663j88cdb6r597GMfAyJxBPDNb34zjfu7+OKL03n/3//3//HDH/4QgEcffZTBwcF03+c85zmTFrJ9zWtew4c+9CGGhobGxPAMDAzwkpe8hNNPP52hoSG+9KUv0dHRwf3338+//du/8Y53vGPa92Y8brvtNo477rgxMYLCHkSSTCDMjF2SayoIs8CTTz5p3vzmN5u+vj6TyWTMPvvsY84991xTq9WMMY3yHO1KeBgTleM48MADjeM4ZvHixeacc84x/f396fbHHnvMvO1tbzP77ruvyWazZsGCBeZv/uZvzP/8z/+kc26//Xbzmte8xixbtsy4rmuWLVtmTjvtNPPwww9PuPap7lev180nP/lJc8ghh5hMJmN6enrMkUceaS677DIzODjYMvff//3fzXOf+9x03gknnGBuu+22dPvGjRvNySefbDo6OgyQlmIYXZ4j4cYbb0yPt2DBAnP66aebdevWtcw588wzTaFQGHN9l156qZnKx8udd95pXvCCF5hcLmeWLVtmLrzwQnPrrbeOWc/IyIh505veZLq7uw0wYamKE044YdxSG1NN25+IIAjMJz7xCbPXXnsZ13XNIYccYr71rW+NmZeULnn88cdbxsdb2+j7lbx/2z3aldcYzaZNm4xt2+ab3/xmy/hee+1lTj/9dPNP//RPpqOjwyxYsMBcfPHF5oc//KHp6OgwL3/5y40xjffF6PI04/1eJa95c8mZgYEB47qu+frXvz7peoVnJzfccINZu2apCb/93ll/HLhsgbn11lt39SXOOcqYObB1C4IgCLucs846i4cffphf/epX6djee+/Ni1/84p3S1unzn/88n/rUp/jrX/867zJihZ3DjTfeyBc+/F7u/MgbZ/3YB//LdXzhmu/w8pe/fNaPPZ+QGDVBEIRnKZdeemnabWNn43ken/3sZ7n44otFpO3pGOaohdSeYWeSGDVBEIRnKatWrWpJGtiZOI6T9lEU9nTM3MSo7Rk6TSxqgiAIgiAI8xWxqAmCIOxBPPHEE7t6CcKehmR97hBiURMEQRAEQZiniEVNEARBEIS5RSxqM0aE2hQJw5BnnnmGjo4OaS4sCIIg7LYYYxgeHmbZsmVovXMca0aSCWaMCLUp8swzz8ybJtiCIAiCsKM8/fTTrFixYlcvQ5gEEWpTpKOjI36mAbGoCYIgCLsrBgibvtfm+nRxE/XZP/AcHHP+IUJtijTcnQoRaoIgCMLuzk4N45EYtRkjWZ+CIAiCIAjzFLGoCYIgCIIwd8xVHbU9xEgnFjVBEARBEIR5iljUBEEQBEGYWyRGbcaIUBMEQRAEYe6QFlI7hLg+BUEQBEEQ5iliURMEQRAEYc4wGOlMsAOIUBMEQRAEYW6ZE9fnnqHUxPUpCIIgCIIwTxGLmiAIgiAIc4ckE+wQYlETBEEQBEGYp4hFTRAEQRCEuUUsajNGhJogCIIgCHOHMdFj1o87+4ecj8xr1+e//uu/opTi/PPPn3DeTTfdxIEHHkg2m+Wwww7jv/7rv1q2G2O45JJLWLp0KblcjhNPPJFHHnlkDlcuCIIgCIKw48xboXbPPffwb//2bxx++OETzvvNb37DaaedxllnncXvf/97TjnlFE455RTuv//+dM6nPvUpvvjFL3L11Vdz9913UygUOOmkk6hWq3N9GYIgCIKwx2PC2X/sKcxLoTYyMsLpp5/O1772NXp6eiac+4UvfIFXvOIV/Mu//AsHHXQQH/3oR3ne857Hl7/8ZSCypn3+85/n4osv5jWveQ2HH344//Ef/8EzzzzDzTffvBOuRhAEQRD2cEIz+489hHkp1M4991xOPvlkTjzxxEnn3nXXXWPmnXTSSdx1110APP7442zcuLFlTldXF8ccc0w6px21Wo2hoaGWhyAIgiAIws5k3iUT3HDDDfzud7/jnnvumdL8jRs3snjx4paxxYsXs3HjxnR7MjbenHZcccUVXHbZZdNZuiAIgiAIo5mrOmp7iFFtXlnUnn76ad7znvfw7W9/m2w2u0vXctFFFzE4OJg+nn766V26HkEQBEEQ9jzmlUXtvvvuY/PmzTzvec9Lx4Ig4Je//CVf/vKXqdVqWJbVss+SJUvYtGlTy9imTZtYsmRJuj0ZW7p0acucI444Yty1ZDIZMpnMjl6SIAiCIOzxzEXw/x5iUJtfFrWXvvSl/OlPf+IPf/hD+jjqqKM4/fTT+cMf/jBGpAGsXbuW22+/vWXstttuY+3atQCsXr2aJUuWtMwZGhri7rvvTucIgiAIgjBHJK5PSSaYEfPKotbR0cGhhx7aMlYoFOjt7U3H3/zmN7N8+XKuuOIKAN7znvdwwgkn8JnPfIaTTz6ZG264gXvvvZevfvWrAGkdto997GOsWbOG1atX8+EPf5hly5Zxyimn7NTrEwRBEARBmA7zSqhNhaeeegqtG4bAY489luuvv56LL76YD37wg6xZs4abb765RfBdeOGFlEolzj77bAYGBjj++OO55ZZbdnkcnCAIgiDsEcxF3bM9xKg274XaHXfcMeHPAK973et43eteN+4xlFJcfvnlXH755bO8OkEQBEEQJsSAmRNX5Z6h1OZVjJogCIIgCILQYN5b1ARBEARB2M3Zg1o+zTZiURMEQRAEQZiniEVNEARBEIS5Zc8IJ5sTRKgJgiAIgjB3GDM3yQR7iPgT16cgCIIgCMI8RSxqgiAIgiDMLZJMMGNEqAmCIAiCMGcYMze9PvcUxPUpCIIgCIIwTxGLmiAIgiAIc4u0kJoxYlETBEEQBEGYp4hFTRAEQRCEuUNi1HYIEWqCIAiCIMwtItRmjLg+BUEQBEEQ5iliURMEQRAEYU4xe0jg/1wgQk0QBEEQJkCh0udmGqmGzfuNZjrH2e2Zoxi1PUX8ietTEARBEARhniIWNUEQBEFoYiJL2ETbZuscE7HbWuIkmWDGiFATBEEQ9hhmS2jtKsZb/3wWcNJCascQ16cgCIIgCMI8RYSaIAiC8KxEtfn3bGW+X6cxs//YESPiv/7rv6KU4vzzz0/HqtUq5557Lr29vRSLRU499VQ2bdq0w9e+o4hQEwRBEARhj+Gee+7h3/7t3zj88MNbxt/73vfyox/9iJtuuolf/OIXPPPMM7z2ta/dRatsIEJNEARBeFYwL6xKSu2cx2TLmFeWNQXhHDxmwMjICKeffjpf+9rX6OnpSccHBwf5xje+wWc/+1le8pKXcOSRR3LNNdfwm9/8ht/+9rezdSNmhAg1QRAEYbdkpwmzaQsoPYePKa4pmTYfxFqcTDDbj5lw7rnncvLJJ3PiiSe2jN933314ntcyfuCBB7Jq1SruuuuuHbn6HUayPgVBEARB2C2p1+sMDQ21jGUyGTKZzJi5N9xwA7/73e+45557xmzbuHEjruvS3d3dMr548WI2btw4q2ueLmJREwRBEHYr5tSCNiU34/gWL4XVNolhwn/Kav9o+88a82i7FmVN2U26MzBGzfoDFDfeeCNdXV0tjyuuuGLM+Z9++mne85738O1vf5tsNrvzb8AOIBY1QRAEQRDmDMMc1VEz8IY3vIGvfOUrLcPtrGn33Xcfmzdv5nnPe146FgQBv/zlL/nyl7/MrbfeSr1eZ2BgoMWqtmnTJpYsWTIHi586ItQEQRCEec8OWdBmZFVqdTiNe3412jHV3lGlxsybAhMs2zQpn/GnhRgT8GxuC+C6Lp2dnZPOe+lLX8qf/vSnlrG3vvWtHHjggbz//e9n5cqVOI7D7bffzqmnngrAQw89xFNPPcXatWvnZO1TRYSaIAiCIAhzx1w1ZZ/G3I6ODg499NCWsUKhQG9vbzp+1llnccEFF7BgwQI6Ozs577zzWLt2LS94wQtmcdXTR4SaIAiCMC+ZlhVt2lazcSxfzedssYKNsrC1bLNaxlSbY4+1qO1oiPjEyseYEENIGNbABPO6xdR84XOf+xxaa0499VRqtRonnXQSV1555a5elgg1QRAEYX4xJYE2qTCbghBLB8cKskhYtQqwaH/d9HNjbrNIS5+P2i8aG3tMPU3RFk7BlWlMSGg8PL+MF1andfy5IAr+n1/ccccdLT9ns1m+8pWvjIl529WIUBMEQRAEYe4wYGZYoFYQoSYIgiDMI8YP2h/vi76Nm3FCq1mTlSsda1i5VItFTafWMjXmuYVSGt0ybqFV9LVqKafpmFZ85ng/4v2S8zatSccWt8kITTDhdkOIZ8qUrC0M+NvB+FM6rjD/EKEmCIIgCMKcYuYiRG4PCbsToTYH7KqWHRIsKgjC7sr0LGkTlM4YJwGg2Xo2Np6sEVemlZ1ayLRyUEpjJWOxxUwpC0vZWDgoZWGTiaxkysIx0XMLJ7abaSxjN2xooR3b0ixi2xxKRf8D6KaP8Ym+Syb7vPcxlE2NTe7TDJYf3aUJBYb5GaO2uyBCbQeZF33UYsZbiwg4QRDmM+1dlaPHJnFxtgnwj2gN3k9ck6DR2h7j0tTaSYWZpTKREFMZLOWg0NhkUkFm4WBhkzFZLGMRSTcbS+lIpimFpRSWVtgqEmSOUlgaHB2tXiuwlEovV8eXrlXz1YzPeGkFQQhDXha7onlcZTDUJzmSMF8RobYDzCeRNhE78leZIAjCXDG5QJuK5aw1S7N99qWdzkksZlpFgkxrG62c6IHG0XksbDQOGfLYZMiYLE7oYGORVS62UeQsG1spbK3I2xpbK1wNeTsSXlnL4CiwNGS1wVLgaIOrDbaCnOVjK7CUwVIGrUws2gwKg62j/7UyM6rXW/UtNlYz3LO9i7urRWrhyBz5H6eAUZJMsAOIUJsL5qq32hz8kjV/8IloEwRhlzLBZ2f6WTWB5aw56L85ESB1Z46ymNk6P644s7HJhwUcbPLKwbE0jtLkbI2jFQVb4VrgaCjakLHA1dBhhzjKkLdDXJ0893F0iKNDMnaApUM6cjUcJ0BbBtsJUDq6NG0Z0JE4a5P/MGX8smbThg4GvD6sTW58kGdvh4JnM/NKqF1xxRV873vf4y9/+Qu5XI5jjz2WT37ykxxwwAET7nfTTTfx4Q9/mCeeeII1a9bwyU9+kr/7u79LtxtjuPTSS/na177GwMAAxx13HFdddRVr1qyZ9hr32WdfLCvJ1Ek+OGYuzIwxhGGYPkb/nDx838fzvPQxwQFnvBYRbYIg7CzGWNPGsaRNLNBaszXHE2iJ9UwpjaUz6c+Oii1mbcSZoyyKloNraTocjasjYVa0FRnL0GGDqw1Zy9DlBOStgKwV0u3WsK2Qglsnk/HJZH3coo92QNsKbAuURahslG2jHYVyIl+nsmK1plT0CWwUBE2N1adT/7cCeSfPgswC9lf7Uapm43ZSUY/Lxx57eOoHmwV2lTHv2cC8Emq/+MUvOPfcczn66KPxfZ8PfvCDvPzlL+eBBx6gUCi03ec3v/kNp512GldccQWvfOUruf766znllFP43e9+l7aF+NSnPsUXv/hFrrvuOlavXs2HP/xhTjrpJB544AGy2ey01tjR0dEk1Jg769kkRIItEm/1ej39v1arUalUCMNx/nKa4m9LO5eEiDdBEGaDVhfmWIHWTpy1SwaI4s1aRZmlM2nZDNvKoRKLmYriyXJ0YZPBNS7FWJR1WC6uFYmxTleTtSBrKXpcQ94yLMwEFKyAvB2wMFcha/ssXDSCnQ2xcqBjg5WybYK6DY6Dztugs6AssCxQNgaNCaNLtpousaUih07uURtCpmxdUxrsoktmxKVYLKCdjhahtrOZi2SCPeUbaV4JtVtuuaXl52uvvZZFixZx33338aIXvajtPl/4whd4xStewb/8y78A8NGPfpTbbruNL3/5y1x99dUYY/j85z/PxRdfzGte8xoA/uM//oPFixdz880388Y3vnFuL2qOcBwHx3GAXNvt9XqdSqVKpVKhXC5TqVSo1WpjheU0/sxRKBFrgiDsENMTaWPjz0bHniVjlnbR2sHWbpStGQs0W2VwVR7HZLDJUAw7yOCSUTYdtkPW0nRlxoqzgh2wOONRdHz68mW6Oipkiz6Z3khp6bwLWReDg7JcjHYJ0ZGYCgGXFlGVuDJVs3UszRxouQWzgq0MrhvganF37u7MK6E2msHBQQAWLFgw7py77rqLCy64oGXspJNO4uabbwbg8ccfZ+PGjZx44onp9q6uLo455hjuuuuuHRNq6YfMLP52TcrUfulc18V1Xbq6OtMxY0wq3kZGRhgeHqZeb5MJNIF4E0ubIAgzYXxXZ3uB1l6c6Tj4v8mNGY/ZsSjLqCK2yuCYDEXThRM6dKosrrbIWhY9GYu8BTlbsShrKFghy3NVCrZPh+OxbOEQue46dhZ0HpSlCGouxsmBm4GsC46NiXWkUtEclQgvS6Xj0eWpFkGqEnHWLFIn+grRo+5baNqPj8LYAW7OJ6MNJlWPuwYDhHORTLCHfPXMW6EWhiHnn38+xx133JiO981s3LiRxYsXt4wtXryYjRs3ptuTsfHmtKNWq0UWqJihoaFpX8PcMN5v9OS/hEop8vkc+XyO3t5I/Hqex/BwJNpS4db8ATIFi5tY2gRBmBbtRNoYN2erSNPajZMB7LS+maNzaGVjKYes7sRWWXKmk0yYJWMydKkcGcuiy7XJ24qcDX0ZKDqGDjtgRa5Gl1tnxcJB8l0edt5E4iybIVRZjJXBZHIo1ZCZOhNbxaym67Djp7EoS8XY6OvVpAJLjRM2Y4wZdxvQ8JlORiPcbddjJEZtR5i3Qu3cc8/l/vvv59e//vUuOf8VV1zBZZddtkvOPTPaCbjJxZvjOCxY0MOCBT3AOMINJv0tSz7GRLAJgjCa9u7OUZa01M3ZaL2UxKAlVjStbGydScWaq4tYysEmQ4EeHOPSFXaRUzZZy6YnY5OzFb0ZRcE2dNiGZTmPbsejy62zalk/mY4AqyuDKnaCzkSWM6vV/qdd1XBVNlvMEtFlqYaVbPRHcZPlSzUXSBtNbCmbUKQJeyTzUqi9613v4sc//jG//OUvWbFixYRzlyxZwqZNm1rGNm3axJIlS9LtydjSpUtb5hxxxBHjHveiiy5qcakODQ2xcuXK1knGxL+tO8ukPF0X6/RLJY4WbpVKhf7+AQYGBqhWq42J4wg3yRwVBCFhoni0hhWtIdCaxVnk2nQjgaYdHJ3D0hkyuhhlaKoMRdNNNsyRwWWBnSVvWSzMaYq2osMxrMgFdDo+e3eM0JGr0bOwTGaRQWlFqDKEqhtdzINlYRSNzMzEIhZbypSjJxRiqbhqdnMG0eerafqsNMZAMOpzMTRjP4pHf742H2OKXzemGuJVNV7YLIR3fhJBup456UywZ4jaeSXUjDGcd955fP/73+eOO+5g9erVk+6zdu1abr/9ds4///x07LbbbmPt2rUArF69miVLlnD77benwmxoaIi7776bc845Z9zjZjIZMpnMDl3P7DPRb+hM4uRG7zP2+Llcjlwux7JlS6lWqwwMDNLf30+lUokmTCGeTQSbIAgNWkVa4uZstG5qxKDZVi4qSqscMlYntsqQU124JkcmzNJDJzltk7MtFmYtCjYsz0OXHdDt+uzbOUxXvsrC1WWsvIJMjjDMEeYKKFtHekzHFjOLyJKWZGA2uzFt3RBkWjXixFouKxYN8WeiMaYhwsYRXqnoat4emtHTGh/N07AJmFqI77l4oWpp+i7sfswroXbuuedy/fXX84Mf/ICOjo40hqyrq4tcLspufPOb38zy5cu54oorAHjPe97DCSecwGc+8xlOPvlkbrjhBu69916++tWvApEZ+fzzz+djH/sYa9asSctzLFu2jFNOOWWXXOfcMJXf4Ml+WSeOf8tmsyxZkmXJksXU6/XU0lYqlRpT2wg3sbIJwp7FeK7ORsJAIsqclhg0rWwsnUkzN12rkNY666KPbJijVxfJWxY5W7M4p+lwoNOB1fk6vZka+y7eTseSOnanwh8GY+dQ3X2EuRzK0mgHlI4tY46KEgFsPaHbUllNG2IhZYKw8bFrGkFYJogEmgmIrGchUYxWYFo/HsNYqJkm5wxxqY5R2aJjBNsUCCpQq9nU5kVHACW9PneAeSXUrrrqKgBe/OIXt4xfc801vOUtbwHgqaeeQuvGu/jYY4/l+uuv5+KLL+aDH/wga9as4eabb25JQLjwwgsplUqcffbZDAwMcPzxx3PLLbdMu4YawEMPPZSauaO/Cmf+5lNx7zetdfr/6IdSCsuycBwH13VxHBvHcWYYx9D8Wz6dv7Ca50bHcF2XxYsXsXjxImq1Glu2bGXbtm2N+jyTuEZFsAnCs4+JMjubszrTZAF0WmLDahJnSSxaTvWQIU+WAj1hN3ntsCjrUnQUHY5iVT6kxw1Y4Hrs19vPgiUlsks1YeDg04FaWkRZGuXGLk0FOI0Ys9Sl6ei2n6lpYH/YZCXzI2VlglhhhbEASxIrfYMxsVALwSTeRkU8P0CFPsoJUCaAwGC8MDpHYmIzYSr+TGgAE22ajkWtAv76AoPrQ/7y6COUqk9jjN+4jp2IAUKpozZj5pVQm8qb54477hgz9rrXvY7Xve514+6jlOLyyy/n8ssv35HlAVCtVkj84rPRmWDKJPcmPpdt22kttUjAObGbMjtFl+3sibZMJsOKFctZvnwZ/f0DbNmyJbKyTeIWFbEmCM8eJiu/0dpZwIpjz9w0Ls3RObS2ca0CtsrikEutaDkyLHZzFBzNioKm0zEscALWdJTozVXp7iyz4GAfch14tQK6mI3cmhYoJxZk7TIztQZbtVrMIBZfsQijyX1pIlFlDOCZ2CrWJMpCg/I9COoQehAE4PmYegC+j1KG0It0mG6ynJmAVIiFARAqwkBFei1sje+arGem0tHnqlez6O+36B8JKJVHqNRKmIavdSovqTBPmFdCbbdlZ/51Ep/L9zx8z6PSZopSKo0tSx/5HLY93svd7s+0qYi3VtGmlEoTESqVClu2bGX79u2NLgmj7pO4RAVh92dSK1pLY3Qrtp5lo/IaVgErdnfmrG4claeTPnImR97kWOzmKDqaDkexumhY4IYc0t1Pb0eZBSsrOAs1YVUTWh0EhQ6UrXGKjdIZKhO5NtG6pTRG63JVizDDD2OXpMEkYqwWNqxmGowPBD6mWgcveoRVD+oeQU3h1zX92/OU6xnqQY6yb1MPLbxQUQ4sAqOoBIrAKEIDgVGx1SnxlipiD2o6Pl28EPrr8MhgHc/fhQ3ZIXLvSh21GSNCbQcwmLYFYHc1xhjK5TLlcrll3LZtCsUiHR0ddHQU07i/9iTibarWtmRetF8ul2PVqpWsWLGc7dv72bx5c5Q1Ki5RQXhW0Pazr61IS3pvOqmrM4pFc3GsLJbK4Og8Od1D1hTpDReQ1w4Fx2Zp3qLLhQWu4aDOKotyFdYcvg2rxyIMcnimE92bQ+vYcqZVw7WZxJ5ZscUsEWmJKEueE6uj2J1pvPjnAMJ67HLEYCo1qFXRqorya/gD0bagrikNuoyU85TrDgP1DNVAM+jZVAONZ6AcaLwQ/BBqYSTM6qFJhVgS7hYm3lQa/8PMXJVeCCNewEYzQGhqk+8wx0gdtZkjQm0XMFMxsqOi0Pd9BgcGGBwYAMCybYqTCrcdE2xaaxYu7GXhwl4GB4fYsGFDJCAnEGwi1gRh/jLu59AEIq2R1dnI5rS1i6uLODpPRhXpChdSMDn63BwdjqYztqL1ugGLsh6HLN1C9941dHcRX3WC7UaJAXYcf+Y2CbSkrlkSe5a4Nk2T5SwEwsh6ZvwQfCAwhDWD8Q3Ua5hqFVOtooIayjKYOtTLilrJYsOWLsq+TcW32V53qAaaSqAY8jX1AEZ8hW8MXgjVKBQNPzR4oSEIITCGIPGQpJmiEDL2eTgDlWMwjJga/dbmJpensDsiQm0H2ZmiYrrnmkzYBeMIt66uLrq7u0a5SqfrHh0by9bV1UlXVydDQ8Ns2LChkS06jktUBJsgzA8mF2fQTqBplUlLbthWFq2iXpxZO3JzdrGEgilQDPMszebodjX7dkBfJqAvU+fw5Zvp2quO3WvjDWaheyEm62DbkXtTuZEIS+PNxqn8b/wg9SuaepBmZEaiDDAQ1jxUrYymghmpEdYNpS0uA0M51g33UvJthn2LLTWLcgADdaiHUA+g5Id4ocEPQ8qBR2BCKsYnICDEUFM1DCGhCvHxMYQEeACEKiRsqm9mks9aBWGSiTCFv9F1S2d3CIyHR5mytw1jvF36eTpXyQR7CiLUnsU0/2JOxRoX+D6Dg4MMDg7y1FNQLBbp6emhu7srbgA/mqla21qtbJ2dHXR2djA8PMKGDRsYGWkfPyGCTRB2PRO7OGFsGyidFq9Vyk67CiQFa604mzNLkQVhDx06S4djs6Jg0ZsxHNhRZUm+zOKeEXqPCAhNB57pQi+yQYPOxokBTa7NlqKzTbTEnSVuzbpJXZqmVscMlVBhGW08CGF4g83AQAeD1QzPlPMM+xabahZlHyqBor9mqIeGYS+kHoR4JqQa+nj4+ITUVI1A+XiqToBHqEI8U8UQYggISDIvA0LCKH5rVCHa2bKAeWGFul9iV/b5FHYcEWp7COOJnTEfwk2CaWR4mJHhYZ5+WlEoFFLR5rruqKNMNYO01crW0VGko2MNpVKZDRs2NPqpioVNEOYFE3UWaNkei7IkWUArF61tHKuArV0snSFv9eKqPDnTSV+4kA7LZVWnS29WsTAT8tzuIZZ1jrD8yDL+kCHQRQK3Dxwb21GQUY2SGrH1TDlW67qMwXhB6tYMq2FqOSOE0IewVEeHJVS1RHVjyMhQlke2LmLQsxnybDZWNSO+ohIY+muGahAy4tWpmYCa8SmrCp6qU6WErzwCPDxdSYVXaDyC0CNMSmEQEIZ+JMqIRJgxbSxoc0AY+gTh+LHBO5O5qKO2669q5yBCbQ8nET8TWtyMoVQqUSqVWLduHfl8ngULFtDbuwDLskZNno6VLZpbKOTZb799KZXKPP300+PGsEn8miDsHMbP5ITRNdHGJgtENdGSZAFb53FVjiK95MMOCnE2Z1fGYq8iLM74LMvVOGz/TWSXK6pDeay+HmzXQudUZDGzQdk6ij1rtqA1rysIMUGIqYfxcwjLUZR+UPKhMoxlRjAjAbUhzWB/jke39dBft1lfcRj2oeTD1qqh6odUg5DhwGsRZ56qU1Uj+KZK3UTiLDA+ofEiAdYkyhJBZuLnEIu0JsE2a6+XGvt5G50/JAjrs3aeGWPUHLk+9wx3qgg1AZiCYGuq45ZklK5fv54FCxbQ19dHPj86EWEqgq3VJVoo5DnwwAPYtm0769evx/e8MXuIdU0QdjLtmqg31USbKFkgY3WSUUUyqoOeYCFFlaXDdlhWsOjNwEEdNZYXSizrGyKz3CVwF+Asy6CsqK2TysYxaIlAg1Y3Z3P2Zj2I3JvVMKp15kEwWCboH8LNVjE+1AYUjz7RR38tQ3/d5umKw7AHm6tQ8gy1IGQgsZ7hUdalFnEW4OMFZQLjEZhaQwwZv0WUjRZkDVHWEGezJdSU0m0NZo017Lr+nsLsIEJNaKGdAGoRb6MaDG/bto1t27aRy+Xo6+tjwYKels4RU3OLts7v7V1AT083GzZsZNOmTWPOO3pNItoEYccZr+1Ty/ZRmZyWdgGN1ja2zqJ1nCxg9ZBRRRaYpRTDAh06y4qODL0ZRW/G8NzuMis6htnrBSMEw4rA7YGFRSylULkmceboRjHapJdSc82zWiP2LCzH4qwUomqDqPoI1U2wdWuRh/oXs71uM+Bp1leg5EHZN2yv1akYn0FG8FSdGhUqaohAefimhh/WYldmLRVkifUsNH6TCGuymrW1mDW5OucgA3M8i1r0xN/ln5GGuXF97imIUBMmZcJ6cXGTukqlwlNPPcW6devo7e2lr29hmxZdcbXIKaC1ZvnyZSxc2MvTT68bN34NxCUqCDvCxG7O5jg0O94cuTkTC5qOEwYcK0oWcHSOgu4lbzpZSA8dtkN3xmLvAizKBizN1jl8740UV4XUKx3ohd3YrkbZUQ20lhg0q6kHZ1o3O27jlMSg1SPhFgxUCAeGsXUZb0hRGnD584Y+ttYcHivZDHkw7MHWakDFD1KBVlNVymooEmbUqIUjqRgLwlqra7NFoCUxaM0Ws/EE2ShxNhWx1kZ8jce44s+E8+azUdIZZo4INWFKjP5lH8/KFgYBW7ZsYcuWLXR2drJ06VIKhXzTnpO5RFvdoZlMhv3225ehoWGefvpparXamHOOXs98+WAShF3BjOottnNvwhhxlhSstbSbtnuydAZbZcjrXrIUyZkCS00vHbbNPp02fRnDoozP8xdvZclew7iLNNXtWcJiD26nG7VwckC5cWKAHbs2dVMMWhAnCfhN4iwweMOg6iV0fYDqupCNmzv5c/9ittctttcV60pR6Ywt1Spl41FVVYbUAHVVwadKzYwQhD5+WI4C742fWs8MIWGYZGiOFmXBWHfmKLE0/ufQVCSLbmoSuqOIRNrdEaEmzIipWNmGhoYYGhqio6ODpUuXUiwWmiZNT7B1dnZw8MEHsXnzFjZs2DBuWyoQC5uwZ7FDhbAnLbMRN0+PMzmTvpzNMWi2ysQ10foohkWKKsOSnEtPRrGmGLAkW2dlxwgrnztC6Dl4pgd333zUh3OUmzNaUqODAJjUgmZqPsaL2jmFnsHfUsZWA4Qlj+EtDn94ailbai6PjlgM1mHYM2yuepQCj341SE1XqakyVTOEH1YJTEOgRS5Ov8Vilrgzm8UZ0CrQUnfnjoiy2dyvDfMg4xPmyPU5Py5tzhGhJsyYCRMQmpIPhoeHGR4eplgssnTpUjo6ik0TJ3OHNnweSikWL15Eb+8C1q9/hm3btjXiVkYhSQfCs5kds5qNZmySQGupDRvQqRVNKwfXKuDoXNT2iSJZCiwyvRRsm07HZq+ioi9jOLR7iBULB+la5RHobljQibYVOqsjK1rGbrg427V4il2cJohj0HyDtzGyoNmWz+CTLhu2LWRjJceDw1m21xTrSiFlP2DE99nOMBVdYZhteFTwwypeWEmtZolAa443M8ZvijPz4v/bW88any9TFFYzEU3jvm7CnoIINWGHmbCwbnNdtpERHnnkEQqFAkuXLqWzsyPeMlnCQat1zbZt9tprFX19fTz99NPjdjgYvR4RbcLuyLRE2YRf6qMSA9If2lnP7IaLU9loHYkzW0Vuzg61iCwFFpoFFLVD0bHYq2ixMHZzHtm3naUrhrDzhsAuwuIl2AUrqoVma5QbJwlYurGsuAu58cJUnJlyiAmjlk5maATtD1J6TLNhWzcbKznuH4rE2WDdsL5cpxR4bNP9VClRU2Uqph8/qOEFpTQzMwjrY6xmSc2zMS7NJnfm2M+Pps+tGbZ4asdEn6G7K3PVmWD3vzNTQ4SaMKtMamVTilKpxKOPPkqhUGDlypVtSnuMR1NEMZDP5zjggP3p7x9g3bp1eEk5D+kjKuxJTGIpS6eNEWfRnGaB1hyD1lxmQyuHrO7EUXmyFOkOF1JUOZZksnS6mh5XcUCHz9JcnaWFEns/b4jAd6GzFyfvRm7ObCNRILWgNf8NFpqoDpoXldnAMwRlg99fwg62Y2oBA8+4/H7dYjZVXbbWNY8Pw1A9YNj32RQOUtEVhtiCZ8r4pkY9HMEP6wRhjTD047izeirGJhNo7T8vJhZoO/oZM92OMtM53i7DKMn63AFEqAlzwrgxbE0u0VKpxF/+8hd6e3tZvnxZ3Ft0KrFrrW6Gnp5uuro62bRpMxs3bow+liYQa8n6hLmh3ev+bL3f432Rzsb1TvglPUVx1nKclizCRKDRkiSgtY0iEmiWSjoLZLBVliK9ZCmQDwsssooUHYtVxajtU6/r85wFgyztG6S4yhC4CwlzRey8QWfirgKulRarbbg5aZTc8EKMH2JqJopDK9cJt27DcWooS/HwnxewoZTnz0NZ+utRK6fEijaiymzTm/BMmXI4EAkz41EPSmnR18SC1rCmjZ8QMKH1LGHUZ8xcvMcnLZck7BGIUBPmjKm6RLdt20Z/fz/Lli2jr29hHEw8kTu01RUKUTmPpUuX0Ne3kE2bNrNly5ZGwsGo87Vbz7NVSEyXufoSmIvjzuQ121lfcjMVcJP31UyYirUsmteosWWlz5O4s8TNqXXUizOJQUusZ0V6yZk8uTBDn12g4Gg6Hc3qDuhzAw7r2cayviGKizxwLEK3G7WoiOVqcBQ6a4EdWc+UpeMEATBB2GiSHpiok0AlzuQcDLG8fiy3zMaHcjwz1MMzlSx/HnLZXjM8PeIxEnqMmArbrc3U9DB1U6Hq9eOHdfyg0kgMCOtxMkBzrNnYLM3W12V0KY3J32c78/Njd/ysilyfu3oVuy8i1ISdwmQu0TAMWbduHVu2bGHlypVN8WswfsLBWMFm2zbLly9j8eJFbN68hc2bN0eCbZykg4S5tIzMV3b3v8x3x/XvWLzZ1FyZ0a4NcZb8rJWdzkkapUftnjKx9ayYxqAV6CFLgZ6wm7x2KDg2S/MWnY5igWs4uLPCknyF/Q7ehi7YhO5CVEcBJxOV1lB5HceiWY0yG/HvX1oHzSTdBADP4JdCgu3DuJkBTC1k+19c7t+6gI1Vhy01zVMjIUP1gM3BCGVdoqyHGQ43x4Vpy9T9EqHx8YMqrbFnQVuBNqE4ixY6pZfp2fwZMZuI63PmiFATdirjCrb4Q7FWq/Hoo4/S1dXFihXLyWQy8YSJXKJjOyHYts2yZUtbBFsQjKpLNIUP4l2djLA7ipF5zW6TQTdR4P+o7U0xZtH8xIoWW89id2YUd2ZhKRtLZ9DKxoqtZ7bK0mEWkDEZsmGWRU6OvG2xNK/pdg3djuGgzhEW5SssWjREfmmIX3NQC/qgq4BlgS5aUZkNWzeapbeJQSOIBVpaagOCwQqZ4iCmXOXeu5bwTCXLxqrNw0OKgXrIkFdnQzhAWY0wqDfihWW8sELNH0qzNsM0ScBrCLOpijKYd5YzQUgQoSbsEiaLYRscHGRwcJDFixezdOmSprZUUynnkcwDy7JYunRJKtg2bdrUEGyj+wVOws5KRthtxdluI4LGY+qV4KfOdOphTU2ctbOWNYuzqDhtYyzJ2kySArRycFUutp5lKZhuMmGWLorktU3BtliSs+h0FasLPgtdn95sjYP22UxmkUG5LnW/C7uvgM6CcuJSG47VKFab1kKjJQYtzeasRpmcXr+PVd+Om6my+W6XjQN9PDBUYEtNs60GG8o+w4HHkCnTb22mZkaoBP0EYS1yc4bVtKRG1Hw8SIvTtlblF4vZriack/CH3f0zZ2qIUBN2GVPJEN20aRPbtm1j+fLl9PYuiDdOpRVV63atYcmSxSxa1Ed//wBbtmyhXC5HGydxizYzmVjbkdi3XSrQdnuRNR6zK76m8hq1vuZTO//YNk5TE2fR8+hjPLGcNcprNKxnSmkcncNWWSxscnThkiMTZuk0BfLaYUHGoeAoOh3FXoWQbsfn4O4hFvUMU1hQx1mSx9idmGwWN2rxic7rRian01QLrblZelKw1o+SBaJszpBw+wCOHgIFw49o/rxxIRuqLo+NWPTXDYO1gC1+iREVuTlL4Ta8sEw9KKVZnEkGZ2JJS6xobQXaLJbQEISdiQg1YZczmTvU9zyefPLJNH4takk1WXboaBI3kKa3dwG9vQsolyts3bqV7du3tyYejFng2ESEqWZjTZZlOmvibFaF1lxYlhrsMkE6jd6JETO7DzO5utam2u3cmNF6EmuZbmrtpJXTIsi0crBVBks52GRwVR7HZCiaDjKhi6scemyXnK3J2ZpFWUWnY1iV9+l16/Rmq+yz7zbcbvCrFirfgdW7GJW10I4GG7Q7SpyNbpjuhVEMmhdGvz6ewdRN5ObcPkKmZwS/VuWPv1vEM5Ucm6oODw/HmZyVMiOmSlmX6NfPUDcVvKBMLRiOLGlBFZMWqW24OU3acmn8riWTIcJs7ngWlIPbZUxbqD3++OP86le/4sknn6RcLtPX18dzn/tc1q5d26YJtyBMncnaUpXLZR566CF6enpYsWI5juMwnUbvDaISH/l8jlWrVrJixXK2bdvOli1bqFarY6dPwUU6mfgYLe6mLVZmRYjNXIDNqriatmCaKVO0Zs1oPdY441Ptz9i6f7Mwa/w81o2ZPNfaQcdjUbxZe3Hm4JIPCmRw6LBcspZFztL05RQFW1G0DStyHt2Oz349AyxcXMLtCiGbw7c7sBbl0Q4oS41p96SUahSsTWLQmqxnhJE4M77BeOAP1NDV7bgFj/77LDZtW8ADgx1sqUduzmdKUT20bQxS1sNUGaEaDqWdBJJszkYmZ9ji5owId0rZDGF6zFXB2z3lpZ2yUPv2t7/NF77wBe69914WL17MsmXLyOVybN++nb/+9a9ks1lOP/103v/+97PXXnvN5ZqFZzFTaUvVv307AwMDLFkSxZ6l4WvTEiKNWDatNX19C+nrW0ipVGbr1q0MDAyNSj4IWwTbTITLzOpijbfuHTwfTEMwTeOcUzrmeCJnekzlXGqCtU++/+wJynbnaifOGqIs7hCATi1lCo2tM1hEokxhRckApoiFTTHswDE2GWVT0DZZW+NqzYKMImMpFmcNRTuky/FZXSzRla2xoLdEfkmAsiH0bFRnB7qjAxwb21aobJS9iRWX14CGezOxogXEoiyI3JuBgaohrBtCH8JKgK5tRw2X2PxkgQ2D3fxxoIOtNcVjw4ahehSHtllto0qJYTZTj8XZZMkCLVa0JoEm4kx4NjElofbc5z4X13V5y1vewv/7f/+PlStXtmyv1Wrcdddd3HDDDRx11FFceeWVvO51r5uTBQt7BhNa1wAThmzYsIEtW7awePFi+voWxoJtZta1hEIhT6GwN6tWGYaHhxkYGGRgYADfrzd2GS+mrZ3YmszeP8WWP+PuPmMxtiMCBiYSW5PtP5F4mtlammk/fyKh1DI2ydpmZn0bu29DnDXVNovLZgBp0L9GR6JMWVjYOCqPbRxcctjGxjI2eZPDURYdtkPWisRZd0aRsxR529CXMRSsgBX5Gt1uja5clUV7j2DlQLkOgSqiCwWsDje2koFyY+tZ0upJj3qfNTdMD02kk+JMToJIpBnPR5UHcSnhj4Q8eH8fGyo5ttQcnihFbs7N1TrDYZWSqjDIFjwqVMOhNFmg0e5prKuT0cVqY0SkzU/mJplgz2BKQu1f//VfOemkk8bdnslkePGLX8yLX/xiPv7xj/PEE0/M1vqEPZgJrWsAxuB7HuvXr2fjxo0sWrSIRYv6sCxnmmca2+1AKUVnZyednZ2sWrWSkZER+vsjS17aqmoqtBN1Uyhg2jJ9Qkvc9IRYe6HRXnSNJ0rGEzPt509n7g7MG11jbLy1txFLrdundy/GQ7c9dmtJDRXf9yTwX6NTcaaVg0XUMSBDHgsnSgIIc5E4UxlsFK62KNhWKs6yFuQsInFmBxTtkGW5Cp2ZOitXDWAXDbrgEuoeTDYProMdJwaojEZZRALN1lEGp6VbXf9hqzjDxAVrTezmrBtMzSfYPoDFCGEZtqzLsnmgyJ8HO9hSs+ivK9aXAoY8n61miJIuUVWJmzNKFghDjzDN5AzbirTo82E6WbXCrsIYiVHbEaYk1CYSaaPp7e2lt7d3xgsShNFMRbAFvs+GDRvYtGkTixYtYvHiRVjWeFafyYrnjo17KxaLFIt5Vq5cQalUZqC/n+HhYcqVyiTHBdToL5NxyjBAG+E1NUtQs9gaT4yM3a/9ttHzJhJB45+rfQxWdNbpi6rGOSYWUhOtQbe53ubjjV3XqGtg/GuYaJ0KjY6PpSJnJtro9LmDizY6spgZBxuNi4ONwlFWaiWztaLDUbgWdDiKrDZkLehxA4q2z7JchYLj05mvsnB5KbKY2YClMCqLKnSjcgWMjtya2Coqq+HGNc+S0hoQxZ5FF9oQZF6QdhKIYtCAuiH0DcYH6h46HMSyqvQ/arFloJc/9XextR6Js6dGQkY8n2HfYwuDlNUww2oLvqniBZU0mzMI64ShD4RNJTdGCzTYkaQBQdidmHHW5+bNmxtV35s4/PDDd3hRgtCOydyhSYeDjRs3snnzZvr6+li8eFHcQ7SZiRIQJvoCjr61IvdoPjpSGDIyUmJ4eJjh4VJa8qM1eWC08Bm/3U/LvFGZgO3HxxNjE4uw1qD1NvPaCJ7xxFajZ+RY8TOeu6/dcca/vsnmN0TQmLWNEkxAi2iK5jcd34xdr25zjPHW0jyeHEuh0UajUSgTxZ3ZJEJNkVEWCoWtNFlbYylFxtI4GhytKDjgakXWMnQ6kNWGBa5H3grJ2wGL8mU6cjUWLCtH4sxRkMkRqiwql0XlXBQqSgJQcWJAJv45ydyMbkzjIuLyOASm0Sy9HkatngxQi5IEwjqYeh2GBnC66/jbfbY/leFPz/SxpebyyIjNQN0wVA/ZWKlRNh5lVWFQb8UzZarBIIGJSm20JAuYEENzP86piTRxe85X1NwkE+whTFuo3XfffZx55pk8+OCDkQmcyE1kjEEpNbb6uyDMIlOxrkEkoDZt2sTmzZvp7e2lr28huVyuaeJMskVhtJtUa01nZ0fc8krHwm2EkeFIvFUqlfT3JGXcGlkJY4XO+JaxUSJpHCE2drxVfOlx548VaUmwe9v9aIw3C7LRIio97qjXQLfZJ9ovPm4bIdW8PRI/YwXbaNEUbY/eQ4l4ah5r2T5qW/McNcqN3ZiTrDESYKmhSik0CkcrlCIWZQpbKywFeRtsFcWWuRoyGop2SN4KyVohCzN18rbPos4SuXwdNxfgLlToQhZj9WB0FrIu6GjVKhZmifUs6rkZdw9IYs9GuTYbxJ0EQqJCtfWoqwABkRVtpEzQP4ztVLA6LTbf47BlsIvNlRwPDuforyvWlUKGvZCS77OVISq6TF1VqIT91E0FP6zgh3VC46WN08c2TZ+gNpog7AFMW6i97W1vY//99+cb3/gGixcvHvNBJQg7g0nrmMUWAWMMW7duZevWreTzefr6+ujp6Y47HUy3FltCs5u0dUxrTVdnF12dXemWWt2jUqnEjzrVao1arQZYLfWw2omu0QKttdBpayB6o+G207J/Ev/UGGv8nMyNbDuR2LGS/WPXHIBl4iB3rFQMNVuOGmMNq5E2DWGTWI/Sn2PB0ixokm2pQFKMfa6akw6b9lfJcWPtgUrnRT8nmqSxj9XGy6dG7dN4rsaMpetoei82n8uK5zixFrKUwVGglcHVBkcZHB1StAMcbbBVSHemRs7x6SxWcdwAOxNi56P3mXYVaAfjuCg3g8p0oFwXLAss0FaUCICloiQADWjdeLvqUa7N5rdxEDZEWXPcmRc3Tq8bTBAnDIwMY2dLhEMem/9SZGtpEVuqWR4ZyTDgKYbqhvXlIBJnZoiKqlBVJUpmK35Ywze1NA6tkSwQEprYkma8xsKm4eoUa9r8Zk/pIjAXTFuoPfbYY/y///f/2G+//eZiPYIwY8a4RhP3TUy5XObJJ59k3bp1LFiwgL6+hbNe+6+dpS/jOmQyLt3dXUS1sRRhaKhWPWpVj3rdw/MCPC/A9wN8LyQMTdtSDYlYi87VWhg1EVhJQHrzc5UILJUIrdY4qWbxpcNxhFcsohLRZaUiMT56LL6Ujsfie69jyxEkgiV63rx9jDBSDYtQ+r9qslSN2sdSqkUkRc9N6xgNUaYAWyXHN+l5GvNNy35KRSLAVg1h1nyedN3xOS1l4uMZslaIpUIcHZK1AixtyNg+jhVg2yGZjI+2wsj65WisrMYuWOisC46Ndm2McjG2E72dDcTJoag0Q1M1EgE04FoNUaZVq6UsUZipKItqnpGU1ggjUZYKNANUqpjyEJoKylEM3G+xtb+bhwe62F632V7XrCvDiBdZ0LbUK5RVhX69lbop45sa1XCI0HiEoZ92FkiSBSKBFlnRmpunT9WKJiJtfhPVUZub4+4JTFuovfSlL+WPf/yjCDVh3jFRK6r0ORD4Pls2b2bL5s0UOzro6+uju7trnIy/yZrBN75AWmPPRmV7jhKNWtsUCg6FQmJXUrEIi4SQMUSizYfADwm8AKUsTKjAaIyJxJ6FG5eQUihjobFHiTEbjYUVW9GSoPVEgEXjDfGlAUvpZEXYSoNquOwi0ZLMa7jvLN1sSVJjBFZiXYKGqGodGyWMaAghnWwfJaaax6xYSFnKpPtZTcJJx8Ip2t4614rngMHSBk00JxFxljYolYxF61TKYOm4n6w2KB0fU4fRuaz44pOHjl5fbYGyNJZroywHbduEWGDZaEejHUAZtB2LMAuUAzq5EU50b1NBlryn4hvR4s5M3rKBid+CsWsz0UImsZqFkTCrx4kChrRhuuWMoOslgv4a6x7sZGt5EVtrGR4rZRiow4YKlLyQku+x3a9SVVUqqsKw3haV2vAbMWheWCEMfQxhS+unpEjwpD0621jSRKAJewLTFmpf//rXOfPMM7n//vs59NBD4+rwDV796lfP2uIEYVaYICtsZHiYkZERLMuhq6uLnp5uOjs7Y2tE81/xM4hpm0IP0XFLXWiNm7HIZuzYsqbSXo7EPyusJlGmUSoJUY/KPUTyy0IZhYUN8TzLWKk00ya1m5EcVcXWMgVYsZvSUvGWJiFlqdgViULr2D1Ik6VJqVjUNARW4o1LxhWN46VWs1SINQQbNAu3SERZ6X5NIi8WZCoRaSRWvOhnSzWsY1bsjLG0Sc9vxRm60fnD5EVCKYNRoGmMEQu4WAahlSFUpmVbKvB0dAytTSTELBMLLbDtMBZ2BmUTzXXi+DdF5DvVpBa39IJGM6bWGa0Ws1iwYUxUgixJDKhGmZtpLFqphDJldL1KfZuhf2Oe7SO9PDLUwYBnMeBp1pdhxDNsqXpUw4CyqTGgB6irCnVTpmoG8cMaXlAiMH4ag5Zkc44XhxbdSRFpz0YkmWDmTFuo3XXXXdx5553893//95htkkwg7Apmo71REHhs376d7du3R3FmXR309PTQ2dkRx7ONR8Oq1jYrta1Ya3JLzYBUpI06l47HR4u0WD41XJlNIs1KYtCaxVossKxEsClit2aTQCMaSwxGdryPjudCQ0ukAqtJeCXCrXl7si0Raamrcxxxlgi5xvNmkTbaCtewlLWe08TWvHhb8/x4XMVCLRGCjbnxWCzKALSOynpqq7GfSkVbZCGLRFos1KzYjZkIMTs1ESYvapytqRoxZ81lNGiylCXPgyixK01iSfpuJm5NA/hErk0/7ihQLmPKJSy7htLgbTWU+x0eeaaX7XWXgbrNk2WLIQ9KPmyp+JSDgG3hCHVVo6arlOjHNzV8U6UWDI1rRYvaP3nxeltbQI2pjSYC7VmDxKjNnGkLtfPOO48zzjiDD3/4wyxevHgu1iQIU2byyvxN26dYbykMQ/r7B+nvH0QpQ1dXF93d3XR1dTbVZhst3iKLW6tYawqISpfTvN6xAjDKnm6eH0urUYkF6XY0loq+6aNIsUSItVrSbCyUSaRctK0Rd6ZTC1okUmJB1yTQkv8TN2gkmlRDFOk21rM24iz22rW4NhNhRtM8FNiJdYxEOI1vMbNjIZS6UGMx1ZpQ0CrK0uM1CbLEzdlsUYuEWGIRCxsWPMuk21FNwqxJkJG6QaObmyTPKjt+a+pYnKWuy2SxE7yvQ9MQK00uTGgU6zepMCMVZGmXpRBMzQevjDZlKFUJhmHdY930V7sYrLs8XXEZ9nXs2oSyb9heq1MOPSrUGdKD1FWFsu4nMF6UJBCWo7gzE8egGT8SacZPe3NO2YIGUnpDEGKmLdS2bdvGe9/7XhFpwi5nWiKt+edpFMg0RjEwMMTAwBBaafKFPB0dHRSLBYrF4ijhNdY9mmxPyteMdyUt85ti1cZO1S3PW2uGtTt+LMdMUySaSSLSVLpPItIaVrWGKzPZlro5mwL9m61go0VabAga495M/m92bTYnCugmS1iLxazJcgat+yciLXFnJnNJzxU2xFciAlPrWuKibLWYNQu0Cd2Y2qTnUVZiRaPFaqZUdDFJcm8q0sZ7T7SzJIUKRdhqcAobc03QJN4Sa1kamx9CpUpYqUKtilZ1wjrUyrDuyW4GqxmeLOUZ9CyGfcXmKlR82FoNqAYh1dCnnxFqukaNCmX68cMatXAk7sXp4QWV2HLmt2RyRpczNpsTpu7mFHZvxlR+EabFtIXaa1/7Wn7+85+z7777zsV6BGFK7FCD8ym4Hdsd36AolWqUSjWUGkQpRaGQpVjM09FRIJ/PRp7ONi7Q6AvZanrenNEZS6ImgRZti7M0UzNMYhGz4+eNuLTxXJ6J1cxKrG1Gpe7Ohhs0TWdAKZW6LhNRFd+QhpWNJqHVNDcVWjTEk2r6mVHjzSRCsPm8ieBqLz9bjzGeczqxvEXHa7g2G5fVEGmtO44VaYkAG/c8o7Yl1iulwMRWxMSYhAZM/F4xALG7UkXP05vccrA4yy2M900FWjzFj9YQibcQ5VdRYZVwqEIw4jHwTJbBUo7heg/PlLMM+xbDvmZzVVPyDduqhloQUg1CBoMaNTxG9DB1Kni6RjUcbLKeVVLLWZIUkMSfNdyb0xBnTdc4GrGkCXs60xZq+++/PxdddBG//vWvOeyww8YkE7z73e+etcUJwrSZUezXJFapcQrUGmMolWqUSx6bNyXCLU+xI08u55DNZshkMk0HCpi4mXmrSEtcntG6GgkEiUhrxJw1XJ7AGJGWWNMSS1p0JdO8TwZCZbAim056FeNZCkPTGts+JvlWRaIjmRICOhlv2o5RkATsm7jbg1KETREvSSKjhSJUkdsTozDKxCdRBPF6tDGEKjluHGEYxj+qxO2sCMMo9lCrKFEiva4wPq9W0TXR8DyqxG2dbItVaurObjZPGqJFKxrVKBKBRuwCHS1QwkiUmVSoxXO1gbpHWPYgrGFZVcLhOkEN/KrmmWc6Gam5bKzkGPYtRnzNlpqiEigqvmFbLaAaGIa8OhXjU6NOWZeoU6HKCD41gtCjHo6k5TX8xLUZW86ixzguThiVyQlTtaCJSHu2oGj/J9eOH3dPYEZZn8VikV/84hf84he/aNmmlJoVofaVr3yFT3/602zcuJHnPOc5fOlLX+L5z3/+uPNvuukmPvzhD/PEE0+wZs0aPvnJT/J3f/d36XZjDJdeeilf+9rXGBgY4LjjjuOqq65izZo1O7xWYR4xrkhrF082dttkrZ0a1fktWgvPRv4spTTViqFWraBUDRjB4JPNumSzLpmsRTabIZ/PE4W6jXKTNh2veS2NTM/mUhrN9dQUjU4BjSzQ8e1MY2kRX00WwWYxBbEoUSYqD0IkfoyJ9ggT4UMkusJEyKj42HHioRULlTBafPo9nTqOVaLi4lgwo2iEIqvINRkdOdU8iUM0icNX8QFVLNYs1fiiUAbCeN8oY9WgTWLZagoRCzUoE4vO2JoYl+RQceak0iraV8V3TZvGeWMLpIp9w0oZlNUk2pJ7Op7JsA0q8MGrYzwPgjrU6ijHw9TBVCD0FNWqZuPmHkp1h2HPYWM1QzlQbKlpqoGiEhgGaoZqEFILQgZ9j5rxGVbD1HUdnxoVBgnw8cIygYkapHthJbaeNboImESo0VwHjTFxaK2ISNsTmZM6avPoLfLLX/5yRvvtvfferFq1asI50xZqjz/++IwWM1VuvPFGLrjgAq6++mqOOeYYPv/5z3PSSSfx0EMPsWjRojHzf/Ob33DaaadxxRVX8MpXvpLrr7+eU045hd/97ncceuihAHzqU5/ii1/8Itdddx2rV6/mwx/+MCeddBIPPPDArBc8FeaWcV2eY0TaxJmaY7Mz21vNGu7KhqUr+jmu1K/i8hlKo5VDUpjW0hm0srGUgzIaKhammqOGg68cMo6Lk7XQtsF2LWwbQtvHdjXaiso1mFHBSEYFhFhowlhYxZY9TGRqURYhAXEkUyyaNFqFBCaILUhRtqdpuj+GyDcXGa9MLLBay3IEGLSJ5JBlFL4yaVJBVM6j8fdyklhgNQmf5kr+OmwYlhTNbtTo50bsmWraX8UJAo1Xb3RZDogTHeKrs3Xi2kw8iZFFkPi8SVmORkJBa0kOO80CHZtsEL1TWrM/W4ScasxL7ksS25a4VKMxg+U0HVP5gI8yAYoA8DG1AOqRMAvqhrCmGNiSY6TqUvNybKtlKfsW2+s21VBRDhTba4paaKj6MOSF1APDsF+jZgI8E1BWFTxVx6NOWQ0SKo+aGSEIk1IataisRug1xZv5qQAbLc5MKsgaFrT0vZkiAk3YtVx11VVcddVVPPHEEwAccsghXHLJJfzt3/4tANVqlX/+53/mhhtuoFarcdJJJ3HllVdOKSb/zDPPnPZ6lFKcf/75kxq4lBnTiHBmbNiwgW9+85tceOGFO3ScY445hqOPPpovf/nLQJSBt3LlSs477zw+8IEPjJn/hje8gVKpxI9//ON07AUveAFHHHEEV199NcYYli1bxj//8z/zvve9D4DBwUEWL17Mtddeyxvf+MYprWtoaIiuri4aBQKEnc1MRdrE8WzjC7TxrGaRKGsWatFcW7uR1UvZ2DqDwsJWGSwcFBpHZbGMTc4UcHBwjENeZWIrUGPNngkji4+jMI6J/pyyDFrryDqjQcftgCJrjUHryNWnVGsMGmkTcJVep41O3ZWJcEkEWfpcJdamRkJBUkctLZ2RCC/VVLIjfjnGZn02RFeaN5sIHBpCrTkxwSJ2Y9KaoNA4Z0OoJeKsccxGAkIy3hCBpun8cSZoU4HbdA1x/FqzOEvmRpa/OOnAShITmuZpg1IhWgVoK6ARCxdbmVQS6B9i53wUPoSN0kZKQ1iH0IPaoIVXsxgpZRisZqn4NttrLtVQUwkUA55FNYAhT1ENDPWgIc5qYUgp8BviDI+6qlNVI1G8GTU8UyYwPn5YxpiwRaA1xBltrGe0xqDB5AIt2omJEKG2M4h874ODg3R2ds7pmW688UYu+z//zOcOefOsH/vtf/wqX//B9bz85S+f0vwf/ehHWJbFmjVrMMZw3XXX8elPf5rf//73HHLIIZxzzjn85Cc/4dprr6Wrq4t3vetdaK258847Z33t02FGvT7b8eSTT/K///u/OyTU6vU69913HxdddFE6prXmxBNP5K677mq7z1133cUFF1zQMnbSSSdx8803A5EFcOPGjZx44onp9q6uLo455hjuuuuuKQs1YdcytVppkwi0tpHgzUKsnfWsIc5Ui1BzWsSZUhpbZdDKwVIONhks5eCYhlDLhFkc45Ajg6MsHK3JagtLRw25HR2JpaytcBQ4GjKWwtFxRmN8OSaJb6LhTjCxSxAaAiqMg9STycm4anre7u41C6ZUjNHQw+O1XBp9bCu1PDXEVLKO1hZPiaWsdb+ki0Bra6YwPUaSnRmV5whTodWwTtEknMLUqtbI8mxkayZYVtjYX5uWGmnJ3KQLgY47EqTFa2mcTzsmzfDUsflQKVBu7AoFTFL7LBZkQQ1K2zN4nkWtblMPLOq+xbDnUA8tKoFmILaaDXqaegjVQDHiGWph1CGgHob4oWHE96mbAA+fkqrg6TpVVSLAIzBe5NLEayql4eGHdYwJMIRNrs1WCxowcytatDMTISLt2ct8eGVf9apXtfz88Y9/nKuuuorf/va3rFixgm984xtcf/31vOQlLwHgmmuu4aCDDuK3v/0tL3jBC3bFkoEZCLX+/v6Wn4Mg4LHHHuPBBx/kyiuv3KHFbN26lSAIxpgZFy9ezF/+8pe2+2zcuLHt/I0bN6bbk7Hx5rSjVksaZ0cMDQ1N/UKEWWO6VrT2cWZNcWjjuDSj53a6PXFpWjrT4s5MRJqtMi2CzMIhawo4xsU2FlmTxVEWOWVjKYWjFTlb42hF0YnEl6sVBdvEQgyyOhJjeStq0u1oQ8EKyFhRn0hbhyQtjaKrMthWiKVDLGVw7SAVEQkmVI2g8za3Mo0PawqU0qOEyXjfrTPK2xh9DD3+x3dDSLWKpXbnt6xwzFjzupNxNUp4GZOIpsaOSjfO225eMjckjncL1Jh7EZYVYaAIAk0Q6PT+Jq9HEEZjgVFUPAcv1NQDTcm38UJNOdB4ocIzkSuzHiq8EIY9RT00jHjghYZ6GFLxQ7zQUA4jy1lAkIqzAD+1nnlhmZAoxsw3SbZmQ6CNTg4YT6A1nsd3oa1AS+7Q9Ij+3JgPX+nCs50gCLjpppsolUqsXbuW++67D8/zWow6Bx54IKtWreKuu+6aklD77ne/yymnnILrugCsW7eOZcuWpUXTy+UyX/7yl6dt0Jq2UPv+97/fdvzjH/84N998M+94xzume8h5yRVXXMFll122q5exRzObIq3ZYpb8PNpqlroztd1iMdMqdl3qfBRzhsZVeRyTwSWHE7o4xqFAFkfpSKA5Fo5SFByFrRUZDXlbkbEMnQ5ktCGrQzqcAEcZXB2St30sZSg4Hq4d4FoBhXwd2wmw7BA7Ewej241L1Bmi4qmWQuc1Y0xloRkTz53cmui7uCmSfxLMZNHAo4/RZvq4x5j+d3or7YylrYaesbo90Rij5o23PmMmmdM0N/QioRb64HtWQ6AFUR/XMIwEXBAq/KDxvqyHBghxEuEcRl0fjDKESmFrCEwUExhqhRUnSoQqyXrVhMZgY2GMTahCGpnEFtqAUVFdPUOYWoijG+BHf7SoZiE2GovUnJuQ1gQRhPYY5qaFlCHyxI02pGQyozPuG/zpT39i7dq1VKtVisUi3//+9zn44IP5wx/+gOu6dHd3t8yfzKjTzGmnncaGDRvSePrkuPvssw8Aw8PDXHTRRXMv1CZa4Mc+9rEdOsbChQuxLItNmza1jG/atIklS5a03WfJkiUTzk/+37RpE0uXLm2Zc8QRR4y7losuuqjFpTo0NMTKlSundT3CzGnbiqmFNtmaia+J9rFmqumbOumbmQg0payGKFMaR+ewcHBVMXVh5k0HTujgYlNQGRyt6bBtXEuRtRSdLmQtRVYbul1DzgrpcXyyVkDeDliQq5BzfLp6yjj5ELsDnMUOKuegCi505cF1YNlyTHcX5HKYjg7IZMCe+a/qeB+PKoy/XEf/n9Bskmre1m5+m+fKjD6+GfXzqMqt481rPmYyFqmd1vW22795/phjmsac1Icctlln07mCoGm7aXNOE82px62Rxms/5gfghxgvwIyMQBASlgNqz4T4VU29YlOvW3iexUgtQ9W3KPs2Q55DNdQMelEGZzVUDHs29dBE/weGemgoeTnqYUjNBJTDbjzlUVEVPFUjUD41NUyAH1naVJnQ+ATKJjB+ZF1ToxMIwODH/ye5vUF8W0NQuvF6k1jXmhRxwhSKTjf/7ot1TZiMG2+8cYxL89JLL+UjH/lI2/kHHHAAf/jDHxgcHOQ///M/OfPMM8dUsJgpo0P+ZykFYPaE2h//+Eee+9zn7tAxXNflyCOP5Pbbb+eUU04BomSC22+/nXe9611t91m7di233347559/fjp22223sXbtWgBWr17NkiVLuP3221NhNjQ0xN13380555wz7lomUuTC3DJVkdYq0KLx0QINSC1liWtTNQk1rZ00zszRuTTGLKOKWDixOHPJGJeiyuBaFhmtKToWWUvR5SqyliFvQ68bkrdCCnbAwkyNguOzoKNENufjFn2yyzW6w0Gv7IOOHCzqxaxcjsnlMW3FWBzcVPfAV03bVfv/Pa9xPxKBkAqVZlGUPGmq6dYsntpZR8Kxoi39YjbNxT2SOaOOmQ42L7uN4DFRSqhKantA9KWeFDxTYdP3/uhrM62CKT5WqxAzraItNKO2xaazsHne6GMm22nMTzGRq9BJ3rYmPadJRWEInsbUfQhAFfPge2jLI3cAqVXU1HxMtUYwOII3AtUhh5HhDBXPYVslS9m3qYaNuLWBuqIWKqqBZsjT1AJDLbAZ8WxqYUA5zFKjTqACyioTizaPmnIIjEddjWCNcocqo1P3Z/QSRRa6ED+tFZdevmq8Fq0uzHEE2xS+xMQV+uxhrmyub3jDG/jKV77SMjbRd7fruuy3334AHHnkkdxzzz184Qtf4A1veAP1ep2BgYEWq9pEhqKdxbSF2ujAfYgu5Ac/+AEnn3xyy/bPfvaz017QBRdcwJlnnslRRx3F85//fD7/+c9TKpV461vfCsCb3/xmli9fzhVXXAHAe97zHk444QQ+85nPcPLJJ3PDDTdw77338tWvfhVopL9+7GMfY82aNWl5jmXLlqViUNidaCfSxro3G+JMpwJNNwk1W2disdYQaJlm61nYgYNDBwUyysK1NJ2OTdZWZC3ocSFvQ58bULADinbAklyFYqZOPlena2kVp0th711EdXVCRw5z6P6YYgdhT08sEADbJckxbCpYEW0zIQQh1IPoy117sQhLovpHW2uSiHbd+FRMvuOaPyXbuR+bv23DVutIOp7OTdaXjI0WaYmAalpfaNrMa4qFS8vrt3GjqWSubhVGSsfn0k3Har5gHYukxALUvDkWl8qQFn2jybepm9anwmibRePcOl6H1XodUdFaA74haZZuvEicpe2eksboGojd1jhADpSK59bqkAnRHQHkauiaTxaP7rCMqRmWrVeUh13qdZttpRzVwGZz1aUaRPFt2+pJzTTFUF1TTQVbhnoYkAldPOXh4TGiHQLlodFpgoFSUQZoc4JBVCAliluL6teFUSmXZiNZKq7DNiKr6XWAaYm19N4KuyemEec527iuu0OZq2EYUqvVOPLII3Ech9tvv51TTz0VgIceeoinnnoqNfzsKqYt1H7/+9+3HT/66KPZvHkzmzdvBmD8voYT84Y3vIEtW7ZwySWXsHHjRo444ghuueWWNBngqaeeSgPzAI499liuv/56Lr74Yj74wQ+yZs0abr755rSGGsCFF15IqVTi7LPPZmBggOOPP55bbrlFaqjNQ1rjzJLnk7k5o+4YOk0GaHVtJkkAiWtTK4eMLmJhY6ssOdNJxmQphgUyyiarLbozNllLsSCjKdiGog1Lsj4ddkCH47GsY4SOYo2uvevYfQ56YQGesy9m8aLIXVkogI6KS5i40ET0HWWBl3zZt8bNtaDjuZYVuUN3MrP+lRg2iaDRLkvi7+vE/dnshmzen9iKZ2KrWuA37dx8sDB1QarEMpaeu2lusp8fEFnjYmGcnnOU29TEbs3EWtg8Hh9bBUF089JjEo0lFrjQxHF6piHWgxATRNdkPMAojJWLY+gMJleEXBJPF4BXJ1eskw89qNdZ7lQw9RDjGYwPQQW2PFmkXHco1R2eqeQo+RZbajblIMoU7a/lqASGqm8Y8HqpmYBhStRUDU/VKetBQuLaamZsbbUgrEfiraltVBi7RiFIExDUmGSDUda18bI/2iCCTdhRLrroIv72b/+WVatWMTw8zPXXX88dd9zBrbfeSldXF2eddRYXXHABCxYsoLOzk/POO4+1a9dOK+MzORY0PIL3338/AAMDAzNa96zVUXu2I3XUdg4NIdZ8jzXjuzmbY9AaxWct7aYB1I6VRWHhWgUsIqGWU124JodrXDpMBzll0+m4ZK0oO3NhRlG0DUuyIZ2OT6cTsLJjmM5ilXxnncJBdiTOjtgPs2IZprMLXBewwDegHUi6AySCwrLb18UQGiSCLgzbq8VmMRcEo9yvzcchuu+JSPPbOF5MGAm5MBFSJhZYYyY2zuk3icPRgjIkEnJRWmfjGlLXbizMkji2VLiFqWgzfryWIHGXEgu5+Pi+IfTjufFSlW3A96AWtZBS1KBWx3iGoAKbHy8yUnPZUMoz4luUfItNNYtKACUftlUN1cDQX/eomYC68RjSw1ExXCLB5psadVOJWkgZDy+ojupQMLaFVHSbQka7qHekfMfY/YWZYdiZddQuPeuf+eTBb5n1Y7/rT1fzjWnUUTvrrLO4/fbb2bBhA11dXRx++OG8//3v52UvexnQKHj7ne98p6Xg7VRdn3q8mNQmlFIEQbvPmfGZtRg1QdhR2md5jhZprVa0RramjrM1G2U1LBVlbza7Nm2VwTEZOsNuMsYlq1y6XZecpenNKgp2VDJjWdanywlYVRyhK1ejo7NK1yEG3ZdHLVqIWfs8wq4uyOSJxLvVSIZTRJ+DVmwt0zvfIrbbohWpJXG0izaxpGkd3V+tIuvU6Bi5MIppU4mnzYSggrHHQmNCg/KIXKAmHBsPmSYtqMilmYxBq4s3avbZOt7iE7Rii118PK1SUaqCpsJ3tmoItTAWfIFKW1YZP0SHKrLKmihY2QQKLBeTdVG6EMmYYgh+FYcay3qrhCMjLF43zNBQlpGay8JynmHfZsjTFG1Nyddkraj3ZzVwcQOHuvFwtItHHU/X0GYQ30Q116LLtOPLi8RZEEYWNBM36DImbBvDNjZ+bXruUIlb2z2ZkxZS05z/jW98Y8Lt2WyWr3zlK2Ni3qZK2MZbMBtMSai94hWv4CMf+cik5r/h4WGuvPJKisUi55577qwsUHj2M5G7U6FSgdZsQUvEWWo9izM1k9Iari6mXQEK9JAxWTrCyHKW1Ta9OZu8rehwFEtzIV12yOpiha5MjZ5imb6DatjLcqjn74/Zd+/IYmbbmHqAwY7El7Yhqb/VXHJfmB3auUrNqG0Jza7RdKzNvGYXaLM7tu35E0takxVvIhGRWgIT1/aoZA+lgAC0FVvmYlHaXLcuOU4i1MIwstACqsmKZ4KwYXULmuLeEgOWrwh1nsDPQwEohHR0VSnWqihvmIOs7YR1Q1CC9Y93MVjN8GQpz6BnMeLbbKo6lHzD9moH1SCkHPgMmgpVVaGmq5R0Pz41qsFgXH/NwwsqcdJBcz02H6OaWk2NconO1B0qblBhT2JKQu11r3sdp556Kl1dXbzqVa/iqKOOYtmyZWSzWfr7+3nggQf49a9/zX/9139x8skn8+lPf3qu1y08S5io40A7kdbordlIEEisZ7aVS7sD5HVPWuesM+wkq1x6HJe8bZG3FUvz0OlAlx2wT7FMT7bGqpX9ZJeCvTSHOu5IwtV7Y7q6ABt8oGLAzkQWHUtU2Q7RLg4t3Ra7DNuV7GjaRyXug8TS1jwfWmPTEtdn4u4E0pZNo+PSmhMTkri1RICNFg6J2PPDhsuzXemQhMSilrhAJ0VFn9KhiZ7H7SmUVmBFCQvKj9cVNCx+xgbtKwiimDgTaIzKo3J5MBD4PqpWxukos1fXIP4wdP01EmwDdZeinWHE1+RtTcnTlHwLp6aphlnKYQ2lNXVVQVka39TwTQ2lNGHoE6ik24EfJerGVrbWxIOwpaTHuOU8Jr07Yl3bPVCYCT7rnw2sXr16RrH5U+n1OSWhdtZZZ3HGGWdw0003ceONN/LVr36VwcFBIPK3HnzwwZx00kncc889HHTQQdNeqLDn0d6KBqmrs6V9k9OoeRbHntlWLnJtaju1nuVicZYzBXqCLrLaJm9ZLCzYFB1YnoduJ2CB67N/9yALekoUFvtkj18Ca/YjPPwwINYI9RCUA2EszGyePYECk4mkZkYLpnbHSY7VzqrVvD3db9Qx2yUDJMdP3IPNJTTazWu2frW7jmROEkMG0fOWOcn/bUSXaToOTfOa486Se2Ba55kW4WfG1yHN4S1hm/vS3Lcrdp0qAMs0nidnMo1zmVhERpa3+NiBgwk7MV4nJhNgZcqsLJTY2x4CBd52Q7nf4a8bFrC9lmHAs3my7DLkwbCXY0ulSDkI6A/LY6xsvqlSC4YIQx8vrKT12FTop3FsSeFcEy8osSSOEWxiXRN2E6699toZ7bf33ntPOmfKXz2ZTIYzzjiDM844A4gam1cqFXp7e3EcicERps74VrSmeLRmV2dTokCSJOBY2bSVU1Z34qg8neECsiZHDpc+N0vB0eRtFQs0w37FCr3ZKgs7Syx6noe9qhP2Xkz4ouMABbUgdmm6YLep8r8raQlkH2UBSrYn20LTXiwltAu8H2/OZGKq+dxtBKBqZzUyTaKmeaxlTaMsW0mQf7t5zfMT61rztub9piS+knOOEl8t522TvdmcYACNYpfN25MEAZryYqBNrcA22zQoSydNTNvPjd+zCtVaOqQ5hs7E6wkUygFjQWh3oIodUYxNpYzdV6Kzo8KhXZvo35hnoJQja3WwvW4x6GkcbVPyLKyqGmNlq1OOcmpU1IIvMD4qLtVijMYYf9w6bCoVa/EFz1n1LWFnMupvl2clJ5xwwpwde8Y2gq6urjQFVRCmykSWtGistSZa5Oq000SBxM2ZWNFslaHIQjJhlgV0k7dsCrbFkpxFp6vodgz7FOr0Zavst2wbxeU+7t551MuOJdxnn8iVWQ1QNR+Tz+/azMxEaARhlLEYBuDaYEVVqzBekyUq/paz4uK2WjXKffh+XD2+3TmiIPqUdlaKJHgeGjF4LWLGNG1vijlq2R7933L00daudjFoo0VTaKJuBJZpf4xkvu/HhWjjexNtbL3O0BBVmCWqjdbWRdkkztq6RhtiJxWhSaZmsl2ryBUaGghii1YaRxZbi1VkFTPKwtRVlJBgWY33XvIyKZV+SisFOPG+1qj3aCLQQlqFnBX9xhnT1OM0ceEmdeG0xnINpm4IPQ3FIqFfJLRD3AUjLFlRYuG2beQe8thazrG1lsHRGYY8haVdSl5IybexfIuqqlJRFZTSeFYlWpqppYkHYehj4jp/E7lD21rHJkk0EDfo/ObZ7vqcS54tzhxhN2C8pIGGqxOUsgELS7skmZy2zqYFajNWZD0r0kvOFMiGORZaBQqOxfKCRZcDC1zDAR1lFuUr9HWPsPA4jd5nIeHJ/xjXNlOYkSqYHAQ2ZC3Mziip53mRhrDiQq1WkkkYP2plqFdRXo1UbGwto+r1aN9SJepSUKqA50dtikrVqBVREDbisJqr7c8QM0aYtXneNGYg/RId15g32vLWbm46Z9Q6mgxd6Xiz3mv33LTfnn7XxyK0pWmDaYxFcxtN2NtphNHbk/3DeExrg2WHaG3QVojlmKhmsWPSzFSdIW2XaUIL5VionI1y7Ei8WQ4GB6McYoVDnPSMUqBclQo6ZamogG6TRVgphVIKY7fWt0xr03qxa9QPUYl7NDAQWIT1TozbidJVVhSGWMVmlK3of9Bm22Cehwe62F632V53WFd2GKoXKfkhm+o9VFWVfnsrdVPGM2Wq4VDa9cAPKnGmaB2IXKMNd6jf5Aod5Q8WsSbsgYhQE3YKY0Xa2KzOiCYrWmxJc6wclo6sZznVQ4Y8PeFCcrgULIclOYdOV7G6YFiYCViUqXHIys10rPRx9uuAv/8bwoV90TmqISgb8gt2juUsiAtgBV50iX4tqrdmkrpXIapShlIZtXUbDJfgic2YioepB4T9dcJaSFiNCpmaQBEkDb8DReDrlkbfYSo0xlrUlG79AksExug5o8fHxs+P3a+56vhEzZdTITPBtuZjpPPN2HkhDYEUjhprXnd6LFSTVmyMtV5b03ni+eNdT8Nz2rim0dXXlTLYKjqLViZ9y1nKYKkQSxmydhA914Zipk4265HJVbEcg5UxqMSiZivQDsZxUa6DclxMxgXPQtkm+rWyFMYC5YZg6UgAJrWddGS4U7E1LxE9ytGRxQ1QVlPtNhMlqBJAqLOYTJbAC6A0TM+hJbpGBsj+2WdrKc+WahZbZRhwNQN1BeQp+S5haKioHHWdB8A3NXTsEg1Dr6XTQeIOTd8dY1yh6U2dUKwJ84+5cn3uKW8DEWrCrDNRJmci0sZLGNDaRScZnNrF0hnyVi+uypM1RRaGfRS1y9KCS3dG0eXAAR0ei7M1Dt17E4W9Dc7+PYRvSqxnwFAF/AzYDsy25WxMgVYDoQdZB/BhaBtqaAg1OAT/36OYwSreU2X8YagNWwwN5Kh5NhXPZthzqIcWQ14XvtF4oaIcKAKj8A3UQ9VcCzU1fEQhVKqdwaqFmerSyT5g24RvTcpEVo9WsTTBtmZD3wTnTgVbm/3GnLtlPzPuMcecY5zza9VaHrsh1FSaG+DoyMhqKXC1isSbFf3saChYITnLkLVCuh2PvO3TVyhTyJdxsz6ZHoPOu+DmCHUWnXHBVlE7qkjbRSIvE53TWBpl65aYt+j3UaWCDay4GDDRHxOBwdQMBApT7Cb0ujGUWbT/MMsym9EFiyN+77BlsMDmSo4Hh3P0122eGnEZ8QJGfJ+t9FLWI9RUmZLeFhXR9YfSzgd+UI3i1+L+ouNb15qSDNq8mGJVm58822PU5hIRasKsMq5IG90OapRIS+qiWbFQc60Cls7gqhwFesiHHeRNnkVOjk7XYlVR0eMaFmUCDu/tp69vmO5X9MABqwiPfF50jpoBHCgunBvrWRBEsVHGjyxlxSz4dfBq6L88DU9tIHzwGYL+On5/yOAzGapVh22lPkY8h2pgMeDZVAONZ6DkR/+XffBCRWCgHprICxXGNU6NSaswpEmRmElLfCXMpLPbVI4bTvGLcWrHGr1P+51aPLLx+cc7frvtU1lz2LRD8uU/+j3eLAraWQoTedG8n1Yq+nNFRaLNjt2TjlJYOhZsWmEpyFoaVysyFnQ6Dq429IwUyFkBeSukL1el6NZZtHgQO9tP6ChULkOoc6hCFvIueKA8g7KIOhnEFjcsE7vgVeoijReYJiOYIIlMCKLnoUIpQ9iZR2fzBLU6wfAAi46us2DLNvqeyAIL2VR1CY3NQF0xVLcw1Q5yYYaSymN0SN2UMVaANjX8UMfZoVH82sTWNUkyEPYspi3UzjzzTM466yxe9KIXzcV6hN2YqYi00VmdiUhLXJ1J2Q3XKuCoPBlVpCtcQNHk6bBcluRtFmQUa4oei7N1lhZK7H30EM6BCwjfdEp8bBfqgG3NUb2zEPDBL0PGjsVagH7gfnjyGcyGAWoPDlLbptm6qcBIrUDJc9hSy1ANNNvrFvVQUQ1g2Fd4ocEPoRqAF5pInIUQGEMtDGPrmSEwhtCYSJgRjTWLmER4NAsQPYUA3onmTFWATXVegpnCF+1Exxy9LRx1PKPaHz9sEVVT+7KfyloBwnHOCaBNqys6yYLURmMZC41Go3Cwo/9V9LtiK42rNY5W2FpRcCLR1uHYuNoia8GCikveMiwZLlJwfLozNRYvGcLOVlFlMLbC2BlUPofKF8Cy0XWDsg3GUSg3dpE2x7XREGxKx10ijIlco4HB6KhOm7JCjOticovw6x56wRCL+ipwz1YWDRaALrbVLbbXNZBlyLPJBi4mDCmrYULt4RsHRRSzpmJrWtr0HYCApOH7GLHWxg0q1rT5ydwkE+wZCQrTFmqDg4OceOKJ7LXXXrz1rW/lzDPPZPny5XOxNmE3YYxAa5PN2WgDlRSqzaSFax0rj9YOtnbJWj24KkcPy8iHBYoqy8p8li5X0ZuB53TVWJYvc9BRW3EP6oZD9iY8+sgoNqkOWJkoc9OdpYsLAqjXI3dmIQP4UCmj7/kdPLWZ+p+2U92iKQ26rN/eyZDnMuR1s7HaRzlQ9NcV1cBQDaDkGephSMX38UyIZ0Kqpo5PSEiIpzwC5ePjExDF7/jKS4VCgAcKDI36X83ioJ2gUONlf45CjzNvqmJmojXsKMZM3hdvsnU237PomO3nK6XbbkuOP+F9mqY+SI4V9aqNxJpSUTmaSLZFzy3jYPsOFg6ZWhYHh4xxcbBxlKZgObiWotPNk7UgZyl61/VRtA0ddsiyXI1Ot87q5dtwi/3ooovv5MEtoDIOygmjpIZclE2qLMC14udJRrFCuVYjls1PzLphI6at6mL8XoKaT/f+A/Syjf3L29j+dJZNgx38sb+TbXWHbTUndokuZCM9lPUIVWuEEb0Z39SoqeGop2joE4TVqMOBCjEm+l1Qxo9f0/HFmiA8m5i2ULv55pvZsmUL3/zmN7nuuuu49NJLOfHEEznrrLN4zWteIzXV9nRGuzhpTRhQykkFWlJyI0kWcHSOvO4hZzrpCbvpsFw6HZsVBc3CTMjSrM/hS7bQu6qC+6qDCI8+EjLZyFfo5MGdxfdeEERZmJaBnBV9H/z1L6hHn8Cs207pniFK213Wbe1jsO4y7NtsrDqM+IqSD/11qPiGYS+gHkQCrRx6+IRUVTWSYqqOp2oEyickIIi/iBKRZkw0BpGwSMTCaOEyFXE0VcE2U+ZCoKXHnqgmXHr+qTU5nsqxprKPaiqCNpNjjj5WcjwVt0hTqYizsJSNhYNSVtQWTTm4JoeFg41N1s/h+jZDXhZXazJa01+3yFqKnGWzpWZRsLNsqWTpztTpyVZZumoAOzuAyjoE5FEdBcBFxa5QY4Ioe9QhjneLxVpyqU4j2UOFUewaBOAplO2AvRBT60ZlBlm0oEzPti0Ef1JsrOTY5NgExqK/pvHKHWRClxHtEmgPz5QxVkgQ1vCppS2pFCFB0juUKEU2ikUbK9YkRm3+MarEoDBNZhSj1tfXxwUXXMAFF1zA7373O6655hr+8R//kWKxyBlnnME73/lO1qxZM9trFeYhE5bcSMfteLNuapruRvFo2sGxirgqh6uKdIeLKJgci90cXRmLHlexpuizLFdjRccwS48P0M/Zl/D4YyG0UYNVTEfXLMagheBXAB/yFvQPoJ/aCg8/gXfX01Q3wHB/hse2LmXQc1hfcRnxFZUAttUi92XFDxmqB9TCgJKp4cfWsoouE+BRVxVCExDixU2uQwwBgfExJkgz4YC0AXb68ziCaCIL0VSYLYva6LW0O/+OCpv255yiUNvFgrIdDZHWEGfJmE5DBCILm6UzaHTaKk2jcaw8jskwYgq4fgYXm2E/Em1ZSzNYt8jZmgEvS4edodPOs7qSpStbY2FPieKiQZQ/SLDdRhUKqI4OlG+jHQVZgwp1lDlqj4phI/kjzGB07NjSISaIqs6E2ISql3q1B92xnYMP2Uzfk0V6h4rUwiIFW+OFGbJ1m0zg4Gufqs4Q4OHF12wIUWhC46NVGH/ZR0kSjboqY2PW2om1iZKcRNjNPXPxm7envGo7lEywYcMGbrvtNm677TYsy+Lv/u7v+NOf/sTBBx/Mpz71Kd773vfO1jqFecT4rs4mgRYLsmhzI1nAtrJoZZOxO7F0howu0sUS8qZIMcyzPJunJ6PZv9OwNOuxPF/h8CM2kTmsC/WcfQmPfB5h3UDVhmwW0zULaZwjIyi/jOkuRnXMNmyA/7oLf12ZDffn6R/Jsb2W4cnyPgx5mmEfNlegEhi213zqYUjNBIyYCp7y8FSdshoiUB6eqhAYL64fVYsDpr3UQpaUKIDoi96YsEVMJF/+UxMBo+dMTaRNRczNhbiaHWbHQpYwm5aylnNOsM5ma+fY16LJ2hb/oQPEf/BEgs7WbiriEuubSxHHZLE8m2K9i4xx6RjIkrdsspZmYa6Tgq3osA3Lc1FbtX27hujrGybbMwjZHJ7Tid2TQ1khygGVi7JFVZyOqpKCy3FR3aQQrwrB2CFWEKLrBlPQGG8hod3B4sJ2lhc2s9+ft7NhWwf3butmcy1yhz45nGE48Nisuinbw9TMMCW9jcDU8MM6nl8iNA13KCqIEnmSjNDE3NdkWZsq7eaKeBPmC9MWap7n8cMf/pBrrrmGn/70pxx++OGcf/75vOlNb6KzsxOA73//+7ztbW8TofYsYaqZnO2aqEdfLm76JZOU3chYnbgqR44uesNeCipDl+uwomDRlzUc2llmRecwi1YMk33VGsK1R2NyhciClu+Iy1/sIF4NSgOQdzD5LPruu+Ghp/EfG2TjH7JsH1nAX4c76K9bDPmajRUo+VGsWX/dox4GDJkqNVXDU3WquoRnqoR41MMKofGiXocEGBPih/UWi1kiysaKsbHibLYsQe1coDsa3jOXVqrZYsqia9a/mye39EWntMacPxVtJnrdlNKERPFZWtvpaxnoGgqNrTPx75mDr2to5WAph7qu4JgMFdNFxs+Q8R3KQYa8ZZGzFcO+TYdtMej1sGCog75clf323orTWeH/b+/O4+Sq6oT/f86599bWXd2d7iTdWQhhGUQW2cHIPG7wTJ4ZRlwYZfwhouOAzkPc4gvBcXseZxzcRlAm4OO8FHx8UBgcFREHX04E3EAkCOoAAQIkmKTTSXqv7S7n/P64VdVVvaTXSlfI951XvdJ161bVPdVVt7/1Ped8TzjooFqzOJ1ZtAES8QQEbS1Wl6eh6LEsm0KXs2u6vC5pXE9GeeA5SUywAr9/lM4zRsju3k/hty5LCml2ey6BcRkoaaLiEpIqSU6liZyQwORRFDA6qE42sMSrb8QBWznBVnntxgVscyVdqAtrfI1BMXOzDtRWrFiBMYa3vvWtPPTQQ5x66qkT9nnNa15DR0fHAhyeaKTZfOMcu1P9RIHaVQVqx6BNFpw5OknaWYJHmk67glbTQptOcmRbgq6UYnnScGbnIKs6h1nxxgycfhLmhBMwJT+eKOB72PbM/Brt+2B8SGnU0B7UczsI7nqM/A7F1u3L2FvM0u8v4fmcw2gIewuWQmQohD5DpkBJ+ZRUiVE1SKhKlBjF2IDIBEQ2zphFNqxmyuLK65VsWTj2c10wNpOB7vMJhho7Pm2i6TJ7ZortC/V8TWa2mTlVWRezdmPt0moQGad6XUVxEOfXdJPq8ixqpRxcnUArD0+nq+vjpm07XpAk6adoz7WRUi5dyQQtXoqsl2LN3nY6E4YT2odZ3jFKdukg3rIMNpmFVBqdMCgHdCYuAqdcjfLKx+joctwZ12KrLBBvfYOODE5rG+FICzY9yOl/upfTrWX4OYeHnlvJ7qLH1pEWBkoZBktL2BlmyesceWeYUaePwBQohSNEpoSxIUa5GBuWPzMB8coN5QBLwaTvjVkEcLLg+8KwNP2ntKnNOlC77rrrePOb30wqNXWXU0dHB88999y8Dkw0zqwDtMnW5GTyDFql1EY8/sxFK4+km61Zl7OLjM2ynA6yCY+OhOaoLPQkA1Znipzw0j7SJ2Ywb7kgruDvA6oVsvOcxhkEYEqQjNui7/4x5pk+Ss8X2fZfnfTl0zw9mmbQVwwFit15QyEy9AclfBtQUCVG9RCBKsUz08wooS2V/2AE5YxZqZohq/zxsNU/ItRkz+LArD4gm+wPykKd2moeZ4Zj1mZsTl2y021/cZn1H/ma8XZjn9XKe0jXXQeNxYmzbkqjbHlslzIYFZbHdwVo5VX/D5RLqEvVz2RJFUnaFH6xnYzvkXYdSpFDm+dSMu0szbWwbH+RlwZ7SS3Lg+8RhEtwOjNA3C2KZwA3HsdmKK9Py1i3aCU4ihRog2M1OrWEYH8WXeqn/bgiJ+f30TWUxTdZWl1FxnUJRrOMREmSKkWkAhztxZMNlEtoSnF+0Wgs4VgpjwMtQQWTFxOcJniTgE0splkHapdeemkjjkMcBDMO0Catijq+zMbYsk/VmZxTrCyQ0vH6nCla6TTLaVUpetJJliTjkhsnZIsckR1lRfcQmdcdiT3nNHBTMOxDS3betdDUvl3YtAvJBPrp5+CxrYz+uI/+vgx9w8t5fCjLYKDZkYORwJILI/b7PkXrM1gOzgJVomiHiUw8ASA0eYwJpwjOylXO6ro2a4OzmgBlkkCnkX8M1AKPNZM/XLMxh/F047KO1d9ftTB/7ftpLGjTylSzb8a6KOVjbFD+jHpEtlTNrlWCNl/5pG2GtJ8kMBlaXIfQanq9BJ1Fj+LTLst35ulZPkymp49op4fq7EC1t6AC0DpCGYV1NaqyRFU1roxLfVht47FtJp5d6i1xMcFy/KEiPS8fZMnzeyj+l8OuQpKs5+KbBJmSQypwiWxIXmUwjiFQebR2IYQIv1oot/J6VRd4x5QDtkrttSl+D7XnvGnWEh373ch7fzYasoTUwj9kU5KVCRZZI7+pTRuYHSAgm/AYdd2btdmzODhT5QXUE04LWnmknY5qcNZhltJKmlbtsbrNY0lScVJ7wMp0kVVtI6z5S1AvW4s560JMEKGKBnQG2ubezan692NTDmRcVO8LqEe2sv+eEXr3tbEnn+GJ4WPo9xXDAezOR+RCn31RjqIqUFJFcmog7to0cdemsQFBVKyOMYuMPyFjZspdm5THpMUq42UqGZHa3/PBzygdLie2pjPn8VI13eJKjf3+6h4visdTWaqf00pZl9qxolFULF/X1TFuWrvVmaQjTguuTuLqFL12CSm/hReKS8goj1bX5fGhDB2JFjp2LeWktgI9mQLHvHQvTnGAyGvHlFrRyfIKBy1RvExVZdJBpRZbeZYo2o0nHXgRKrI46TThaBI6Rlj3ql5MwbD/uRQP7eymt+ixt5Ti2ZEehv1l7Lad5JwcRTXKqNNHaEpEtoRfnmwQRkWo+fIUTzqoCWjtgYItI0GbaDoSqDWJAy1LM9/Hqr9xqtvGdWlWr9RmzsZO+pXsWTzrLIXWHo5ySTptuCpJi15KxmZJmTQ9ThutnkNHQnNMFpYnA07p6qdn5TAtL3Wxf/16bHs7+ArcFuyS+UwUsKiBPdjOVigU0L97Av/bDzH8vMcj21ewp+Sx33d4biTOnuXDiL6gQFEVGdL9lMgTUqJohsvrDxaqZTMi49dMBAgnTAaYU4B2MAt1zmX9qJlaiHbM9/he7EVPK+1TivogX48tb1X7/qsW7zVUsm3VySQm3mZsiDEhWrsYDKEp4OgkVkeU1AiRDknZDCNBijDXwpDvMOBpIM3uYgLzOKxcNkzr8v3YkUGCVAfu8lZ0Hqxnq5MO6kp7wFh2DSde3cCxuICTaiMYaEUzwPKX5XhZqZ/O4Sy7CkkC4zHgaaLRdkZNmlGVAQ0lNUpg8wCE5TGhlex2ZfJBPAmjnNVmLGhTEz6f47JuB1hTVMyOvIJzJ4Fak5rtt7VJg7PZZMygLiiL7x4HTLq2DlpN9szTcaHaynJPLknaWUbGtLCcVloTDm3l4GxZIqI7VeD0tb1kj4nw/r9XYI4/Pn6i4QL4iXhM2lyUSqhCHtvRAvio3TsIv/AgQ8+69O5r45H9x7DX1zw3AsO+YST06YtGKOoCRXLk9ACBzZe/kQdENiSMCnXdmWCqGbPqgtFTBGVQ+zsblzWb4oRf+zue0ySPmWj2PzbNfnwLYL6ZF8VkVfij6me9dvGwylg3halm2+K7aqwKyvs5NRMSKquGuBT1IK5OMursxVVJPJ1hn+kiVWohVUjzx1z85evpkS4693SyLBFxatcgPUuHyDJImOzEuC24GYNOKkgqdNKJj9ONu0EV8c8AylqsF8ULwCcNttRFlM+y4qX7We3sAuCELV3szmf43VCKAT/BoN/KrlwHo8ZnVOUZ8PoIbJ68GayOHQ2iQrmkhz/551jFn+P4KGo/x07972qy5cHsxM/swcqszfQc0SyZPgsYmfU5ZxKoHQIONE18LgHaxOBs7PZK1gyodm3WdpVUitQ6ysVzWsvZsy6SNkPKZuiinRbXZUXGY0lC0Zm0nNRWYEVLnp6lw3T+eRucelw5SHNQAznskmWzfk3qBAVsRwK1/WnUw38g/H0fT/1mCTtHW+gtJtg64jDgW3blfEaNT14VGHD24ds8gc1Xs2dBVKwuXVM3GeBA48wmDc5gLgHagbbNV8OCvxoNywI3yMF8nRfquaZaGL4+2wa177/KuK3abFu8rVIotpJtK2egVJwpNjZe3CwqT6CxOqKoMiScDETQatJolWLI1/QnXLTqoC+fZkV/jmPO2IcqDmPoAhKo0GIV8czQUJe7P8eNYfN0eaUDwAUnkQR3BcFADjfo57gT99O9a5TQdrOn6LHf10CCYd9hNEigjaKgCijtEOoSoY27eo0JCZSufvHC6PJrUHkdKp/tsXIfta9X/fi2mtd2kmxbI0p6zOezISVGXhwkUFtsM5yBNKMP64THmk1wBrXdmpVlnsZP9fecFI5K4uokKdVOQmVoN11kbJqM8lieStKWUBzdCl2JkO6Uz2lH9tJ2dIR3/JLybM405AJoacUuSU/frqmEPmq4D9vZAQP9mNvvZ/TxiD29bTy6v4M9JYf9JcX20ZDRIKLXDlLQeYpqlJzZX5216Uc5rI0IK+sKziJAm3SMS61ZBGiNdKDnm+0fgkYc+0wfs9GB0HwdrOOYecAGY8FYzX0q7+VJu0cNmLi70FpDpF208bGOwdeF8kB+TZEWKHYyEngMB/GY1X2+w95SAu+3hu4jhnGLuwicVtzuTpSr4uyVY+NTj1Uo5VCNGdEoayFhUY7COgbHGJx0KybIwOAoS7KDnG762D2QZXchDSQZ8B0GfQeVbycXZdBaU6KArwso4qBNRbpaNidi3BCGcsBmrUEpB1se3xefJ03dBJxJJyWMW2t0Jp+nhfw8TqdZgrXFP4JDlwRqiyj+QE5SY2q64G2mGbO6UgwTM2a1QVllkoAur8FZKaCptYurM9U1BjNqCQmbJmlTdNl2WrRLT6tHqwcdCTi2NWR5ssTJa/fQepTBO74Tc9FfQzKJKfigMkAKWuYYoAVBXAutxQU3QPXuwr/23+l/NsWv/7iS3qJHX0mzbThiOPDJRQF79N544LHtI4zqBx7HY3T8sW/bwFi35nRZM5gQmMEBu/Ca4YQ5XjMe01QOpWM9GKbsMh//HlS17+GKse5RiOJB9uXuUVse7mCsX+0WDaMCWrsUlEfBGcTTaQb1ElKmlUwxS19xCVnXoy3h8Gyum2W7l3Fm5xCrlg/R5r5AONoBmTZ0QqEzcRFcEgac8kSDynqi5TpsKuFgkyYumBsajJvFhq20/UmO9uIAJzp7OeuFBLv3t9FbSPPESIr+UpJd+Qy50JALQ/bbUYq6wIjTT2iL1dI68Wc/IDT+hCw6JOrHn6qxYQ71XaQ1AdBUNdum+H3MORibyzjOJhhS0Ki1Phe/ZQeHBGqLbOJYtElS7NDw4KxSKLMyA6w2QEuquIszaTNko3bSJMloj+WpBK2eYk0LdCYMSxMhJy3dT+fyPG1/sQxedhxm7VoILGq0gM12gDfPFQVKo9Dqofp2on79W8LHdvPMY538cbSFJ0cS7C/BQMnQWyoyagvkdY4R+iiZUUrRMKHx4wWfo2LdmJX423Vl3M50WbOafWpNc0KUIEM00gHHOU6ZaauIM25j3X0h8fkjqMmyUV5zM/5CU1mHNtQlSioPFvJBC6NhEkclGQ40Kd1GfynJqoEcR798iGhwlCi1BOVksEH5DOXocgZNlbNsamwtUe1AeaF4bSw2AG9FKzZoJdyfo/2oQbI9+1i118N7oZs9xQRJx2E4cBj2NV6hjbzJ4NkEBZUnVCW045XX2A3QKl5BJCyXLxlfZqeyAsLYaxXVrIBwoO7Rca/vTGu3NXLCjzhkSaC22GoCq/E1rsbXUJpw1xmONZssOKsN0HS5Dpqj4qn6lQWfKwFaq+0gaZKkbIpON0XGcWjxFKtbFB2e5SXZIsvTBZa25eg516CPXYF5/f8AXCga8DxsyzwDtKCAGurDLu2CQgH77Z+Qf6LInhey/K4/7ubcPmoZ9A0jQcA+1U9el9cLjOL1AkvhSPWbs6mbwVkToM20S7NiBt9WJUATB5vFTp61mTIzX19QV1VqAdaMYzNQHcMGNYGaLcXdoY5DyRYp2FbcfAe5wCWhXQYDTb/vkdwSsvyoUbyW/RSfHcFb0YlSCXANeOXxa1pj3XICsFKLzVFxXTZAeSY+xfkWvaKFYLgVlRol2zLIae5uevvaSOh2+n2XwUCR0B4jgYtX0hRNCwV8XJ2Mu3BtEV/FhasrAVtkQ6Lymrxx0FYZt1YJ3MaCNmuDse5RmFATcerz9wEK705pHoWqlWmKrNrhUd66MSRQW0xKoVSyfCWqDmKtT7NPddexcWW11yszNGsDssoszUqxy0rGzCl3Z3o6g4OLxiNDO0mbImGTdJCJl5ZJu6QdRaunWJUxLPEMXQmfE5bvp6M7T+trytmzVasgm8XkAyADaJjvmul+Ke4e8SIoFTD/62aGntLV5Wb6Sppnhi3DfsjOcChebkYPM2r6CKICYVTAj8qLOUfFccFZbTHMipl3X0xHAjSxmMa//6bMstWJZ5DW1murzBq1Ks6yKaWrXaKR8avnF98dxSnPEB2hh1TQQv++pbR7Hu1Jj+35FXTviliR9jnzuF3otl0Ew1l0ewfK0+i0Bc+gEzou6aFBec5YsKZc8Cw6YSC08QzRtAG/FWtbSKUKrFk6wtHu84QjkB9I8PiuZewreTyfTzLkpxgNLX2FNoqRoWBCBm0eX5UY9Yaq6/SW7Gg8ns0GRKZUtySctbXLwo0r0aPKr1/1tas9l9SW5Jln1mw2q4uMCy7FoUkCtUWlq4FVbUVtpQ5cib8SlKm67Fk5UKtZrLnys1IOTnnsmaOS1etJ1YrGI0UrHkk8m6DNtpJUDinHpSsVB2jdaWj3LG1exLGteZZmCnQuydH535Koo9di/vtrQLvgWwg9yGQ5cJg5A8ZAfgBak3E9tAd+g3lsB9sfauWPI1meGEmyv6QY8C29hRI5W2JQ76PI6IRuznhqflgeg1Yeb2LDmj9kc8+WTUWCNNFsppyAMGHH+nptdVm26rj5cpeo8Ym7TQ1+mMPV8edsxNGUVCseCYp+hnyUwFMJRkOXoVCT3raclXtHWb0uR7g/R+R1oHqyqAgM8YQD5ShsZeyaLWfXVHkMm7JYG5/prGchsDgdaXRrmigX4aRGaOsY4bSW3fT3ZWjtX0K/7zEQaNKOSy605EOXdMmlGEWkojQlVaKkirg6RWiLRIQEKk9kAyJdirPxxCs+1GbbajNu4GKr55Ox7lJqzu9jgdZMgqd5LvmmNMqGTXE2akhSrxkadhBIoLaIlHJwnfrq+7bmw1vNrNV2j1a7MGu7NOPZmpp4jFllu6uTOHjxbE3SOMojZVtJ2AQeHq0mQ0I5tHseCUeRdjVdSUXWtbR6ljXpgM6kzzHL+2ntKpFc7eC+5njsnxyNXb4cG4bY0RKYFOgEzHM5TqIIiqX4cTyL2vNH1D1PsO/f+9m1t42duW4eG0qyvwTbR0JGooBRW2Sf01vXxRkan6A8WcCWayjFAVpYk0Fb+O4ACc7EoWDGdRmrn4+aLJu11E48CKMgXvXAOBjtE5RniAduAVcn8J1RPJ0hbdsYHF5OdjRF1nX5Yz5L1/4sp/QXWNWao3vpEFlvlCjRCYVkvOB7QqHSBuvoconHcpbNqVn8Pa3L4/gtOh1hI4vTqrFBBzbqIJHJs6xtmFUtf8SGFn8Qnn+2i/5iksHA44W8x0jo0VdMkQssxcgy5IcUbIhvA3KqQKB98mqYyAaElAhsfqyLlAhjwmpR7LGMvamey8eWlYPKign1v4+ZZ7vULAM3i8EYysHa4p2f4rysjL+bKwnUFpXGc1vqPri2ZkHmWpUsWyUgg0rGLN5emQRQGV+m0XERWuvh4JGyGTzj0UKKhHJIaoe2hEPKUSxJKtJOPJFyZSqg3YvoSPgcvXyA7LISmbM74NijsUeuxhyxBtAQKlAp6OiY/8tgLIQhBEVocQCD/vFmzO93MvpEyO9fWElvMcmeksOOHAyVIvaGOXKqQF6PkLcDBCZPEOUITammwGWlxMb4bs76IG2+xWYlQBMvNhOyb9ZWM2x1Ew/U2E3GhihrsMqgojjbVFTDRDqoLqhesi0U/QxuLk0u0CR0mn7fY38hxWnZ3SRX91Ham0Iv68QaB0cBjonHrblxMiqu2TvJ4u8JIDLxPkE8oVWpDLo9Q5QPoTBCsjvHsZn9hKOK4f1JOvctYdBPsMPzGA0Uo6FmX0lTDD1KUZKhIIlvIkZVmoAAX/kU9Wh1XF5EgNUmrjNnTTVwM9WArT54i19bM+6cP7duSTWDLlBb/n1YinN6DtEcJFBbJAqFUpqE0wJM/LDamrEOqlzfDKgGYbU/K+XgUh5vZuMsmkeCpEniWQ8Pl4z28LSmLeGQ0Iq0q+hMKlpcy/JkRNaNaPdCjmwfpq2tSMuygPSZS+CYYzGnnwLp1rhQZNFAIlWtKL4gwhIqtx/bkoZCEf2bRyjc/Tz7d2TYOdjJEyNp9pU0/SXLnnzASOTTrwcoqlFKdpRiNERkSwSmUDPNfqyrc0KQVn2Npy42O13AJsGZOOxMFazVdI9WZohGplKXTJdnVZbQjsbXWUo2i1PSFEIPT7uMBC5DQQuprctZsWeE7jOKRPv/SKRbUcvbwXPRrsKm4sBQQTzpQNtxi7/Hi8HHizBolDEYDSqwKOViM0sw4RJswsdbkmPp8jxtfb2M9McB24DvMRy47C465EJFIXIYKGmKkWXYT1AyUTloayEgoKByBKpUzbQZG2AwGB0Q2SA+D5WHWsTLWI0Fb/FrNf9grWKqoM2YEDCYyb//H1SN6Po8XM7CEqgdJJP94XedLMud4+q2jU+DV1LdDnFQ5lq3PPBf4VkPBwfXahLKwVOajOvgakWyPPg/oSHlKDoSloxjWZYMybohWS9g9ZJhWrIlsido9LIMauUSzMv/OyxZAoAZyoGTBDcDxotnYc13ckBFEEBQgowDuoR65hnUE9vZ9x+j9O5r47f9R7O3rmBtwLApsU/vpeiMkjP7CKJCtWCtMROzaJXyG2NZypl3d0ogJsQk2ebJukMr9dhspYBuHKRp5WJsGHeHare6juiwTjOql5MyrQwOLqPF8WjzXF7Id7B0Xzsn7S3QncmzfMkonZ29mFKayGlH+S5o0CnANShHQWSnrMMGGp0oF/AKDTaycddoOokNE9hoCV7WZ0lPni6zD0WINZb8Ts3QQIahQpLd+Qwjocueoksu9MhHioFSC8XIMhoYSsYQWkveBIQYIiIKqkikQwJ8IgJCFQduFhNn4MrnJIOpfiGvDdTMHAf+63HdogZDZEqUwmGCcBCqdSIXh0xnmDsJ1A6CqbIzjk6wzCyv22bqylGWp6SjcdE4SuMpjaMUjlJ4WuMo8HQ8vsxT0Oopkg6ktKUjYUlpS8Y1LEv6tLgBKzpGaMmWSHUZkidkUT1d2DNOxra3Y5MpcJPgG7AaMp3guNWaRgsmLIEXT8nHBOjb7iJ4coCR5xx+/0I3vcUk20ZdBkqW4SBir1+q1kQbZR++KVCKhjEmJCxPFjCmPotmKyel8etxCiHmZELJj7oMWzwhqtIdChHGxuU8ovJ4rYDKIPwgXjFAlXC1SyFqoWhSeDrFaKhwVIp9JY++fJqT2Ev72hHcriJBXxLV0Y7BizNsTryKQV0dtoixoA2qQZvVCmUsKrJYp1JEF6yTwKYTYDowxQCCPC3HFkmP5ugORlndN8TgYJpdI62MBB65yGFP0YkDNt/BjxxKBnKBh28MobEUowyBjSjYkIiIkIhABUSqvCQXIZEKMCq+Fr92BlMz7GX8F/ZKQFcZ6jKZ8ePXLIZA5bFE5Ob2KxdNQgK1eZrPch9tyVWc09levV4bDylUXEaovD2hLa6CtAuesng6zpB52pLQER1eQMqN6EoXSKd80i0BLasjnHYX3Z5EnbwGupdhVq8Gx4FEAjsyinWT4CTKA0BcwJn/pIDxSiUIo7hwZUqBDtH/706CpwYYfU7z++e76Sutpa/k8OyIYjiw7MoXyNsgXpdT91Gy8biQYjSAMWG15MbEAK28okBd2Y1KAVvJkgkxHxNKftReVWZswkE5uxaZCHAwNl5zM9RFFJrQ9SnqAUrOKAmdxlMZhgrdZPJp+gppsp5DWyLD1pE1dD4bsSzpc+LKvbQfuRPV3kKo20En0EkL2qA9BZ5COcTj1pzyDFFPx4GbOxbgqMhgK6XyIwvWYgODbU2CSWKKBpW1UCyRaSuSKRVZZXpRymJDCEYhyDvs2tNOIXApRg77SgmKkaZoNMOBS8nASKDwjSU0UIwgspbAgB/Fi1aFxmJs/OU8srY63s9gMdbWvdZTfc2crMOz8jcpwpK3JXq9PzKongEbLVpPgaUxKxMcLiRQW0QZ3cXxbfFHUANKjZVI1AocZcvBmiXlGDxlafVCEjoi4US0Jn0SXkQiEdLS6eNmwVudQmWTqGVL4SVHYVtbsS0t2HQaEkkohcSFaDWkuuKZVM6By4HMmSmfsKNSPFMBi37gQXh6JwM/GWbv3nZ6cxn+MJxhwFcM+rA7HzEShvQzQkEXKKocBTOAb+NuzsrC6VF52aepsmjTlt4QQszb5IV1TTW7FmeGKmPaNMaY6nJU1hoUwxgdj2EbUh4l1YIuKXKhx0jgAA77/XgNUbtrOd2DeY49uR+vq0hUShCVsujWDMZYtC2XKEuasXIeAK6qzhQFaiYiKKwuj0nV8TqjNrJoFwiBdBrrp+Lvd9ZiCyXwiyTbSiTDEkcv6ceGYAJFbjDBaC7JaCnBkJ+gEDkMBS7FSFMyikKkCKwiMFCMNJEFvxyoRRYiU3nl4usAkak5i00S5EzW0VG7KbIwGniUwuUo5cmEgkOYBGrzMN/12jrtCs7sGowDNGVRypaDs/LP2uI4BqUsqXSAmzAk2gxOGnRao7uSqJSLSqfgT1bDknbs0i6s0nGmrCULYXySRDkQOWO/cVcvfJdmLb8IYQEyHmQ0DA2gH/sD/n88yegOl9/v6GFvKUFfyeG5UcWwH4/52OMXKFBiSPdTpJxFM8PVdfmi8qzO2mKTY5k0DlBkUr7OCdEI1WCt2hVas92GVNYPNYRxOaHK7MfyZANLRKQClONQIo9WmkKUJhclgBTDnmbQV1iboq/oET2m6Mrm6TyigLe0hBnQGJXFtmVRbjxSyzqAWw7CrMIaW9clWlG97o3NblWBgoSNTyWeiYM632J1CptJVTNfTnuILfnoIKB9uU9bsYAtDRMVFFGg6N/fQt5P4Eea0cAjtJpSpMlHmsAoiiYO2IxVBLaSTVPlbRBZVd524GzU+NN4JSQNLAyUXIrDHfF4wTn8bheSnIHnTgK1RppmiZAzW3s48Zaj4znnuvzxSnjYynXXLdcO0vFC5ADpdHlfBcZiXa8846q8wLsfxY9XGVu20N2YU6lkzxwLBGDz6Cf+C7btJH9fH4O9KfYNt/D44FHs9x2ez40FZ3v9IjmKFHWBIb2XkBKFaKBcZmNsNmdcE6h2AfWpujphuiBNJgsIsXDqgjWgsgi8LU80UFQq+Md1IK0xmHKh3KC8skFoCmjlUXSGcXWShMqwP+gkVUrTQopduRStnsNTo120eZ10bDccl83TmS7Q2Zaj84QhSGUIRlrR5YBKuQbtKkjE3aJWq3gSQrl4Lm45eKvUZoOxn42Nu0iBch9lnFkLTXzuDRLQ6sVl5SIbN91Y3CiAMCBjfAhK2CDE+lFcgsja2nkX1T8RZmxyOiZQWKswIVirsEZVX1Y7yaoGStlx1+P/A99hV38b9/d18J+FVsJoeNEmFDSq6/NwOYtLoDZLqVR6bKAqatpgbGqaE7o97Kojy9drH0fFlfm1M3Y9WQ7EjI23GwuRH5fMcGq6LxMH8VcaRfFxhj4QxgPosKjeXrjrZwTPj5Lfqdi6vZu9xST9vstzOZdh37I7H5ELI/ImYL8eoESBIqMU7ACRDQlNgdD4k3ZzxsFZfZA2RrJoQiyGum7QaequgSmf5vy4dIapBGwhSmlCVSJUJdBQ0mmKpMFfQi70iKxHq6fIeg6+aaEjn6JzpJU/KQzS1ZMjtSqPGXKIyKJaW7GORkc2LinkgHVtNVhTNp6EEJf8GJ+aUpV4Mx7z5tT8bEB5Jj712Lj/UlV6eUONtQkwLdiIsdUBVbyvMhFEIdqL4gjNWJRfnpFevYy7DthgqvNZZQH7+q1RwdJlQ5bkHVpb2kEPVIeHWGspFkdn/TsWi6NpArUgCPjYxz7Gj370I5599lna29s5//zz+cxnPsPKlSsPeN9Nmzbx+c9/nt7eXk455RRuuOEGzj777OrtxWKRD33oQ9x2222USiXWr1/PjTfeSHd396yP8yUveQlOOSiKP3xzD9RWHdMFpOs3B0Ec/BiAKM6M1QZitYPYkkkWhbHxN7OgCKUctLcCDhTy6B/9FPN8P/t+DfuHOtibT/P0aJrBQDPkK3blDbnQsL8mizai+vFtntCWS23YgCAqxJMFyhMGKhW9JwvSJh2PdoAgTbJpQjTGgYK1eFslWAuoLPSuAWs1EX45Uw6OcjE6XvTdV3l8lQENOZMmLLSQ8V1aPI1vNG2eS9Z1yUcOS4ezHDu0n2yPj9s2QLhrAOOmUUsy2HQGXI32ymPTnHgCApGK/xJqJu0eBcYWiIe4dpuJM2Pxqgig3GrKK26itdigHLxZG2fdrAWjsJELnosxxMGfLnfVUk70jR8yXF6qU8H4dd+rJiujpgrgqgztiU5e4h5NvpSqliqKoojHHtsyxW+xAax8b56PpgnU8vk8jzzyCB//+Mc55ZRTGBgY4P3vfz8XXnghDz/88JT3u/3229m4cSNf+cpXOOecc7j++utZv349W7duZfnyuPTFBz/4Qe6++27uuOMO2tvb2bBhA29605v45S9/Ob+Drn6gD1QhuvaTVb/fruIkJwTPm98xNZJfhIQGHQdOau8e1FPbiB7cRmlHwGhfgqd6u+j3V/BsLsFwEHdv9hUMuTCgaEIGGKWgCozo/YSUCG1c58fYIM6klQcZx8s+mbpuTmBC2Y3ZBGkSoAnReBOCNRibEVrXFRqfDyMbAA7WhuUCueHYQu86F69TrDzyzgCuTtKv2kmYNMliip2FLCntknEcnkwlyHoJVvS30vGMocMLOTo7SkdLkeVH78PJKEiliKIMZFrKM0LLwVFCleuxMZZti2d41XeRVrJuWqH0JJOwlEJVMmDVGQJ27PRUe26q7GeYeM4q9xPa8ae36Qaa1fyJUY4hNRyQcprjvLfYY+QOZU0TqLW3t/OTn/ykbtu//Mu/cPbZZ7Njxw7WrFkz6f2++MUvcvnll/POd74TgK985SvcfffdfP3rX+eaa65haGiIr33ta3zrW9/ita99LQA333wzL33pS3nwwQd5+ctf3tiGHSCI251rgnLRUzEWojD+GmdKcYCWMBCGqH37UE9twzy0jdLOgF1PZenPL6G/lOTZXJLhQLEzD7kwzp71ByWK1qegiozoAQJbrHZxjo1BC2qWfjI1hWvHZdBg6vFokkUToikcuObaWHbNEgK6vARVuRaYgcpC70A8ik3HX9BCncRqg0+eok4S2ZCkTZIMEpRMmiHHoRQ5tLgOWU8zErbTPtrK2lyK9nSJJcvypFcUYbgfq5MY1YJqzUDgoFwbZ7M8Ddpia4M2q7CVFRDGdZHWBXDxhvg/pzxUpbbbtPY1Kp+v4qxcZSxc/T5qksBupowB14twlZ1Ql00cWpomUJvM0NAQSik6plhP0vd9tmzZwkc+8pHqNq01559/Pg888AAAW7ZsIQgCzj///Oo+xx9/PGvWrOGBBx6YMlArlUqUSqXq9eHh4QVoUf1M0fvy/wGcuSCPOy9RbcBoy+n4CEwx7s584GHoHSDaNcLg72BkOMVAIc3zo6sYChx2FTSjIeQC2FeMyEcRg1GBgipRUkVyehDf5jE2oBSOVhdOHx+cgZlkDBrUjkObsuyGZNGEaCoHCtYq2bT6JajiIC6qLD0V+dUxbMpoQlVAKxdfD6N1nGUb1X04eLg6SZ9tJxGmaRtqI6USpJXLkqRL2k3QleyixbVkt1tWpkM6vICOpM/alf0ks/txliRRrSmsSmK9VDwrvob2VKWGErjlZpS7Qy3lgA7GlrOaZEZ9tUtV14xxrqgEcgeqwzHL0fiaEDcZ4enFL1UkddTmp2kDtWKxyNVXX81b3/pW2traJt1n3759RFE0YaxZd3c3Tz75JAC9vb0kEokJwV53dze9vb1TPv+1117L//7f/3t+jZiGXaQZOERRzaAGAzYor90ZAhZKJdTQEOqXW7D7Rsj/doT8gMfwcJrnh9oZ8F1GwjhAy4WKfUVDIbRxgBaWKFBiRA8RqBK+zVMycZkNYwPCqFDNpFW6NWtLbcwqg1YhQZoQTWm6zNrYbNHK2DWDUpTHUjnlc4Ifr2WpqZ4ntPVQKp5spJWHVh6RDnFJEukwXuvYJikVW0kqh1zgknHjNY6HAo+s55F1U+wvJmlLBBy5dJBM2zBeq8VpVZBKYFUqXkIvmY7Hk5VbpBMqrtfmAJUgyKEauFVPrao+y2ax5QF55UBtkrFwtuZcVr1dIpzD3qIFarfeeivvfve7q9f/4z/+g//23/4bEE8seMtb3oK1lptuumlRju8jH/kIGzdurF4fHh7miCOOmPfj1gYPR6QOUjatkjGLoriUeBTEkwHSHlROHmGIGh5CPfAI7B/B9I0y+kTI6GCSF/q7GfY9hgKXnQWPkRByIewvWgqhYTCIx5+VCBjWwwSUyDMQL+9EUJ0gUBugTZ5FqwwyhsmzaOXtFdLVKUTTm0mwBuXsmtLVc0G1O1RpsPEM0UqXqCEez2atwVEhSpWwNsJRHpEOcEni6RSBCfCsR6HUQtJ3SGmHXOCQdhUZVzMYpMm6SfYWk/EayImA1UuHSHeUcDOleFxbDqIggXVTqGQSm0qA48ZdpeXJ+GgVB21KYTXVsW/VbFhNUFYJ5Gxl/NtUr5uewzmsJpNnzdjk0WbQiMNokqY13KIFahdeeCHnnHNO9fqqVauAsSBt+/bt/PSnP50ymwawdOlSHMdhz549ddv37NlDT08PAD09Pfi+z+DgYF1WrXafySSTSZJznlU5sxTzudnVc3z8SQRBXKcnWV41XUM8AN+AY8b+HxmJA7K+ffDYNsz+PPmnfIrDHrnRJLuGWxkJWhkJ29lTcilEir1FKIRQiCz9pQDfGIomZFjlCJRPXo0Q6CIhJQKbJzQlQlOeFDDj7Fn5dZtHcDbxfkKIZjBpsAaM1b+or7lWvY4px3VjUyOtjf9sKaWJTJxtiycf5FBoPGcYpTRaeQzrNA4eCdWKozw8k6Q1307SJkjikXUSpBxNezJJykmScqBrTwdpx9LqWLpTPi1uSHdLnrbWIunsCMmueEF4lU5AMoHFAy+BVQlQGlPuKNGVmaRltXPPlFLV0pfVG8cPZ67p9JjSgeaxFS1+waVkVHkdUE1lUtZiaEhi8DA53S9aoJbNZslms3XbKkHa008/zb333ktXV9cBHyORSHDGGWewefNm3vCGNwBgjGHz5s1s2LABgDPOOAPP89i8eTMXXXQRAFu3bmXHjh2sW7dugVozt77/JbMtRlsZ4K/LtdPinv/4f8/GxWZ1of54whByOfSTT8G+QeyO/ZiBIuFAxPCOBPl8gl3DnTULDrvkI0UhgoFSvEbdoB9RjAzFKGLEFikpn0CXAzRbxDejRJRnbZp8dbH0uEBtbe0zU51+X8mcje/ihNmPQ6vefLh8aoU4BE2+3NQB9qsu8F6ThGMsy2atQZXHs1Uybar8v1b1XaOhKqGVh6uSBLqEZ5N4JClEWbzIJRcmSWhNwlEM+g4pR5F2NHv9FGnHsrSQomUwotWN6HqhSNINWd49gpcpoZOgE8QBmOeC76ISHirjYpVGaRerHKx2sVbHzVK22rb48G19cq02AJvFTM9aUQF83yEwB4rmxKGgacaoBUHAX/3VX/HII4/wwx/+kCiKqmPIOjs7SSTiqOa8887jjW98YzUQ27hxI5dddhlnnnkmZ599Ntdffz25XK46C7S9vZ13vetdbNy4kc7OTtra2njve9/LunXr5jTjc2RkpKaO2nwK3oKfKxF/w6kEGLWBRmUWUBRny6jU/XHibbkCamQEcjnU8Ajs6IVSgNkzgs0FREMhhd2aUt6lUEjQn09TCF36S0vJl5cx6fc1hQgG/TggK0WWkcDgR4aSicjZEj4heZ0joESgS5TsaLkbs1LrLF7aKZ6pGcVdmuUArVr7bJrsWdzaAwx4lS5OIV4Uqt2c48t3wMTsGlSXm6qdgFDJskF9ps3YOLOmTBy4KaUJlFvOrrko5eAoF0cnq9eTuhUHl6TK4hgXzyRJ+2k865HEo8XxSGpNq+eQcFwSGrJeCwltyf5xOSltSTmWdi8i40SkHENHooTrGFqTPqlUQCIVkmiJUC7oRLxAvFUOxrpoT8elPxLl1RGUir+Iq/JqBFaNXcb9qamtnTZZfTVbgHBUU8z5jI7myBVH6uqoHUwWsHNdclE0T6C2c+dOfvCDHwBw6qmn1t1277338upXvxqAbdu2sW/fvuptF198MXv37uUTn/gEvb29nHrqqdxzzz11Ewyuu+46tNZcdNFFdQVv5+LZZ7dRrQTNxPEHk5v8G80j+X7ekdsXjw8L/PirYhjGWTNjUb4fjysrlmDfAOSK8cWPsIUAM1DE5A2mZPH7FaGvyY0kKZRaKAQuA6UU+dChaDQDvkPRKIYDhW8UxcgyEkwMzvI2ICAkUAF5HWfKisT/GxPg2zg4qw3QKl2bYwEa1fIa8c8zyZ7BbDJoEqAJ8WJWP34NaoK2CT2o5TVDLdWsWqWrrzqDVMW12SKlccr12hzlVjNuvirgKA8Hl6LO4lgXjyS5qIVE5DISJvCUg6sVGcch4cQTE5JakXAUra4m6XhxIOem8JSlxY1nXCa1IeNGuNrgaUPKDXGUJdtSxHUDHNfgeAbt2HhZqXLdM1X+6zy+mK2aJMatvh41p9CooMjvaqN/t+apZ54hX/xjzQS2g3/+lDkRc9c0gdratWvrZrxM5fnnn5+wbcOGDdUM22RSqRSbNm1i06ZN8znEqY1bjHiimtpBNXbmfdT/vQsbGmwpxIYW68erEtjQYiNb/hnCHES+xi84RKEmCBzyxSx+FKe2R/x40d/hwME3mmKkGQo1vomzZSNBvD57LrSUIktoLLkwmhCcFXQ+LkSrAgKbJyIkMHkMprycU4mo3JVZP/asPM2+LoMGk83ghGkCtMprOtXLLUGaEIe0SbtBx9Jk5Q315826LtGKuqBl8oCtOsatnGWrLAZfCdo0mqgmy1bpJnXwKDo5HOuSti141sMJXdJhAk9pUtrF0yoO3lyNqxUJTfyzUqQcB0/HHSEpx+IpcJQl7VgcZckMGhwV/+xqi8KiFTjKoBW4Ol4NFUCrA5/zzLg1QA0KP9L0FlNsG1WEUREpOXvoappA7ZA3WWBRF7yN/5BoHucp7rzlOCyKwCiMhaD8gbM2HlJrbPzdJzCKyELRKCIDoQXfKAIDkbX4BiIDxchWtxXCkMAaImspmpCAkJLyCYmIVEiJApEOKdmRaiDmmwLWRuXlmwKsNdXxZrVB2YwDM5h39qy6iwRoQrxoTDlmrS5gM+PuU/+Ft7ZrdOz2Sla/3H1anjVaKVam1dhkhFAVq9uUigO5gvJwytcdnUShcXUSBw+lHVyS8cQEm8SJPJzIJemncKyDi0MSD6UUSeWgUTiqfNFxni/hxIP7k46DUvE2p2YUjVtbkm0GvYW1mara02hgYDgwPF8YIozyizv908qi7PMhgdo8TDs4tm78xfj9DIPhCzyw/6R4jkD5jVy5S+2KIwaIjC0HbIaoHIhF1hJai7WUAzJDYA0hhoiIkvKJCAlVSKBLRCoksEUMQTzB3ZYwJiC0la7LqG68mRk3Q3Py4Kx23FnNkU86/qy2ZZO8RlO9jIfNx1GIw8uEMWt1N07WU1F7/tATzg1q/LmoptxH5b6GuEYbFlS5S9SqygoJGqV8wvLPWhWqY9sqgVylbpujXBRO3GVaXuZKKwfPxsGdRxKNRhuNg4uOFMpqXOIAzsOt1kpza4bT6PI2Pc2YLlPTdjPJeTTCMmqL7HFewNrShNvFoUMCtXma6UymyYK2nN/Hb/pHAIjK06bNuBOPqXxTVIZyKIVRBoMhKn9zNOUMmVERkQ3iIIooDsQoD/KvyZDZcnBV6cKsbre1szLrg7KxbVHd7fGVqYIymDTdLsGZEKLGtNk1mCZoqzzOuCEm5cHz8WNPk3UrZ9wq5T7in+M/kVqXs3DVYC4O2Cr7VwM5nGoXqi7vG98vvo4iDujiXFv1ebQa+7lCT7LulJmkvIZlbHYsgCm32WIIyJPz92JttKjnVMvhk/1qBAnUhBBCCNFQMplg7iRQWwAT0u/TZdjK3xL9cJhnUo+OZc0OUIywkr43GKwZ+8ZUrehfk+my1pQzaab8TWpsv9qM2dhqAOGEx6vPnMXPPHYwM5wQMK69ByIZNCEObwfsBoUDn0fqJiBM9thTPU6EQo1tKk9GgNpMG0TGqcmO1d9GTZatcnvt9dr7xPcby9zpCY81M/XDTWJmXNsrvSVBmK9mFsWhSQI1IYQQQjSUfBmfOwnUGmCqN+T4b4rGFBgs7aiOAYP6b0rjv2XV3jb+G1X9OLLafeq3T9xv+szZ1G2a/cSA+mOWD64Qol5d7bSZFkmdzblHjT93TvY4U2XaYHy2LebUbRs/3mzi/mOPM/ltk5sskxabZLxetbbl4k8ksMisz/mQQO0gmhCY2IhSMDhun5pAbYpCufYA3YwTP8jjA7GKmQZk09TekeBMCNEgcwrapn3QA52Domo36theelzX4bggDqpVaWu7TacyeVA2ceLAhOM6gAMFcIs9kUDMnywCJoQQQoiGsg24zMa1117LWWedRTabZfny5bzhDW9g69atdfsUi0WuvPJKurq6aG1t5aKLLmLPnj1za/ACkozaojJEplB3vd5s4ujpMl+TTWWfQXdmdeeZfyzk25sQYqFNdl6Zb5Zt0ozdhHNdxPjSIPV71Gfc1DTn4klPpdN1fU6ZMRu322zO6YeZ+++/nyuvvJKzzjqLMAz5+7//e/7sz/6Mxx9/nJaWFgA++MEPcvfdd3PHHXfQ3t7Ohg0beNOb3sQvf/nLRT12CdSEEEII0TCNGqM2G/fcc0/d9VtuuYXly5ezZcsWXvnKVzI0NMTXvvY1vvWtb/Ha174WgJtvvpmXvvSlPPjgg7z85S9fjMMGJFBbXNZiCQ6wQyOnVM+vnMakd5NMmhDiIFrIc84ByywdsDTIASYnHFBNFm1W5TNmmCFbzCWjJtGQw5nHYw4NDQHQ2dkJwJYtWwiCgPPPP7+6z/HHH8+aNWt44IEHJFATQgghhJgt3/cZHh6u25ZMJkkmk1PexxjDBz7wAc4991xOOukkAHp7e0kkEnR0dNTt293dTW9v74If92zIZIJFFH+DM4t0qT0QW3+ZQzskmyaEeDGxNf8OvKOd/DKtOZ67p3q+KZ6/Wc7NjfgrZoHbb7+d9vb2usu11157wGO58sor+cMf/sBtt9224O1sBMmoLbYmS09Pp1k+9EIIcbBMd96bdp3Sg6gZz9HWNm6M2sUXX8ymTZvqth0om7ZhwwZ++MMf8rOf/YzVq1dXt/f09OD7PoODg3VZtT179tDT07Pgxz0bklETQgghxCEpkUjQ1tZWd5ksULPWsmHDBr73ve/x05/+lKOOOqru9jPOOAPP89i8eXN129atW9mxYwfr1q1reDsORDJqi2ym334WrNjjDDTjNzIhhGhWjSgdMpfnbGaL3Xl05ZVX8q1vfYs777yTbDZbHXfW3t5OOp2mvb2dd73rXWzcuJHOzk7a2tp473vfy7p16xZ1IgFIoCaEEEKIF7mbbroJgFe/+tV122+++Wbe8Y53AHDdddehteaiiy6iVCqxfv16brzxxoN8pBNJoHaImM23p9l8kzvUvpUJIcShQM6t9Ra77K6dQUovlUqxadOmCWPeFpsEai9CcoIQQgjRLCyN6fo8XP7SyWQCIYQQQogmJRk1IYQQQjTUYnd9HsokUBNCCCFEA9kZjRETk5OuTyGEEEKIJiUZNSGEEEI0TCNXJjgcSKAmhBBCiIZqRJx2uMR+0vUphBBCCNGkJKMmhBBCiIZqSNfnYZJSk4yaEEIIIUSTkoyaEEIIIRrGIpMJ5kMCNSGEEEI0lCxtOHfS9SmEEEII0aQkoyaEEEKIhmpE1+fhkqOTQE0IIYQQDWNtfBFzI12fQgghhBBNSjJqQgghhGgoc9h0VC48yagJIYQQQjQpyagJIYQQoqFkjNrcNW1G7T3veQ9KKa6//vpp9920aRNr164llUpxzjnn8NBDD9XdXiwWufLKK+nq6qK1tZWLLrqIPXv2NOjIhRBCCFFhAdOAy+ES+zVloPa9732PBx98kJUrV0677+23387GjRv55Cc/ySOPPMIpp5zC+vXr6evrq+7zwQ9+kLvuuos77riD+++/n127dvGmN72pkU0QQgghhJi3pgvUdu7cyXvf+15uvfVWPM+bdv8vfvGLXH755bzzne/khBNO4Ctf+QqZTIavf/3rAAwNDfG1r32NL37xi7z2ta/ljDPO4Oabb+ZXv/oVDz74YKObI4QQQhz2rLULfjlccmpNFagZY7j00ku56qqrOPHEE6fd3/d9tmzZwvnnn1/dprXm/PPP54EHHgBgy5YtBEFQt8/xxx/PmjVrqvsIIYQQojEqa30u9OVw0VSTCT772c/iui7ve9/7ZrT/vn37iKKI7u7uuu3d3d08+eSTAPT29pJIJOjo6JiwT29v75SPXSqVKJVK1evDw8MzbIUQQgghxMJYtIzarbfeSmtra/Vy//3386UvfYlbbrkFpdRiHVbVtddeS3t7e/VyxBFHLPYhCSGEEIckg13wy+Fi0QK1Cy+8kEcffbR6+dWvfkVfXx9r1qzBdV1c12X79u186EMfYu3atZM+xtKlS3EcZ8IMzj179tDT0wNAT08Pvu8zODg45T6T+chHPsLQ0FD18sILL8yrvUIIIYQQs7VoXZ/ZbJZsNlu9fsUVV/C6172ubp/169dz6aWX8s53vnPSx0gkEpxxxhls3ryZN7zhDUA8zm3z5s1s2LABgDPOOAPP89i8eTMXXXQRAFu3bmXHjh2sW7duyuNLJpMkk8n5NFEIIYQQNKaO2uFSm61pxqh1dXXR1dVVt83zPHp6enjJS15S3Xbeeefxxje+sRqIbdy4kcsuu4wzzzyTs88+m+uvv55cLlcN7trb23nXu97Fxo0b6ezspK2tjfe+972sW7eOl7/85QevgUIIIcRhyB5mXZULrWkCtZnatm0b+/btq16/+OKL2bt3L5/4xCfo7e3l1FNP5Z577qmbYHDdddehteaiiy6iVCqxfv16brzxxsU4fCGEEEKIGWvqQO3555+f0bYNGzZUM2yTSaVSbNq0iU2bNi3g0QkhhBBiWvbw6aZshKYO1IQQQghx6JOuz7lrqoK3QgghhBBijGTUhBBCCNEw8coEC59RO1xydJJRE0IIIYRoUpJRE0IIIURD2cMm/7XwJFATQgghREOZxT6AQ5h0fQohhBBCNCnJqAkhhBCiYRq3MsHh0Z0qgZoQQgghGsrKrM85k65PIYQQQogmJRk1IYQQQjSMRVYmmA/JqAkhhBBCNCnJqAkhhBCioSSjNncSqM3Q2EBIebMJIYQ4lMV/xxoxwH+q57NSSW3OJFCboZGRkfJP8mYTQghx6BsZGaG9vX2xD0NMQwK1GVq5ciUvvPAC2WwWpdSCPObw8DBHHHEEL7zwAm1tbQvymAebtKF5vBjaIW1oDi+GNsCLox2NaIO1lpGREVauXLkgjzft89GYrs/DpX9LArUZ0lqzevXqhjx2W1vbIXsSqZA2NI8XQzukDc3hxdAGeHG0Y6HbcLAzaVLwdu5k1qcQQgghRJOSjJoQQgghGiaeSiDju+dKMmqLKJlM8slPfpJkMrnYhzJn0obm8WJoh7ShObwY2gAvjna8GNog5kfZgzc/VwghhBCHkdtvv52/veQDnJT9qwV/7EeHb+XO/7iNP/uzP1vwx24m0vUphBBCiIaSgrdzJ12fQgghhBBNSjJqQgghhGiYxk0mODyydBKoCSGEEKKhZAmpuZOuzwU2OjrKhg0bWL16Nel0mhNOOIGvfOUr097vjjvu4PjjjyeVSnHyySfzox/9qO52ay2f+MQnWLFiBel0mvPPP5+nn366Uc3giSee4MILL6S9vZ2WlhbOOussduzYcUi1oeI973kPSimuv/76affdtGkTa9euJZVKcc455/DQQw/V3V4sFrnyyivp6uqitbWViy66iD179iz4MQdBwNVXX83JJ59MS0sLK1eu5O1vfzu7du06ZNowk2MZr9neQ9deey1nnXUW2WyW5cuX84Y3vIGtW7dOe79ma0etz3zmMyil+MAHPnDA/ZqtDTt37uRtb3sbXV1dpNNpTj75ZB5++OED3ue+++7j9NNPJ5lMcuyxx3LLLbdM2Ge279H5iKKIj3/84xx11FGk02mOOeYY/uEf/mHaNTebrR3iILNiQV1++eX2mGOOsffee6997rnn7P/5P//HOo5j77zzzinv88tf/tI6jmM/97nP2ccff9x+7GMfs57n2d///vfVfT7zmc/Y9vZ2+/3vf98+9thj9sILL7RHHXWULRQKC96GZ555xnZ2dtqrrrrKPvLII/aZZ56xd955p92zZ88h04aK7373u/aUU06xK1eutNddd90B973ttttsIpGwX//61+1//dd/2csvv9x2dHTUtfs973mPPeKII+zmzZvtww8/bF/+8pfbV7ziFQt+3IODg/b888+3t99+u33yySftAw88YM8++2x7xhlnHDJtmMmx1GrG99D69evtzTffbP/whz/YRx991P7FX/yFXbNmjR0dHZ3yPs3YjoqHHnrIrl271r7sZS+z73//+w+ZNvT399sjjzzSvuMd77C//vWv7bPPPmt//OMf22eeeWbK+zz77LM2k8nYjRs32scff9zecMMN1nEce88991T3me17dL4+/elP266uLvvDH/7QPvfcc/aOO+6wra2t9ktf+tIh1Y7ZuO2222yLs9yetuTyBb8kdYf98Y9/vNhNbDgJ1BbYiSeeaD/1qU/VbTv99NPtRz/60Snv85a3vMVecMEFddvOOecc++53v9taa60xxvb09NjPf/7z1dsHBwdtMpm03/72txfw6GMXX3yxfdvb3jar+zRbG6y19o9//KNdtWqV/cMf/mCPPPLIaQO1s88+21555ZXV61EU2ZUrV9prr722erye59k77rijus8TTzxhAfvAAw80pA21HnroIQvY7du3T7lPM7VhumMZrxnfQ+P19fVZwN5///1T7tOs7RgZGbF/8id/Yn/yk5/YV73qVQcM1JqtDVdffbX90z/901nd58Mf/rA98cQT67ZdfPHFdv369dXrs32PztcFF1xg/+Zv/qZu25ve9CZ7ySWXTHmfZmzHbDRToHb//ffbv/zLv7QrVqywgP3e975Xd7sxxn784x+3PT09NpVK2fPOO88+9dRTC/yKzJ50fS6wV7ziFfzgBz9g586dWGu59957eeqppw5Y5+WBBx7g/PPPr9u2fv16HnjgAQCee+45ent76/Zpb2/nnHPOqe6zUIwx3H333Rx33HGsX7+e5cuXc8455/D973//gPdrpjZU2nHppZdy1VVXceKJJ067v+/7bNmype74tNacf/751ePbsmULQRDU7XP88cezZs2ahrRhvKGhIZRSdHR0THp7M7VhJscyXrO9hyYzNDQEQGdn55T7NGs7rrzySi644IIJxzaZZmvDD37wA84880ze/OY3s3z5ck477TT+9V//dV5tmMt7dL5e8YpXsHnzZp566ikAHnvsMX7xi1/w53/+51PepxnbMVvxouwL/2+2kwlyuRynnHIKmzZtmvT2z33uc3z5y1/mK1/5Cr/+9a9paWlh/fr1FIvF+b8I8yCTCRbYDTfcwBVXXMHq1atxXRetNf/6r//KK1/5yinv09vbS3d3d9227u5uent7q7dXtk21z0Lp6+tjdHSUz3zmM/zjP/4jn/3sZ7nnnnt405vexL333surXvWqpm8DwGc/+1lc1+V973vfjPbft28fURRNenxPPvkkELchkUhMCJQa1YZaxWKRq6++mre+9a1TLszcTG2YybGM12zvofGMMXzgAx/g3HPP5aSTTppyv2Zsx2233cYjjzzCb37zmxnt32xtePbZZ7npppvYuHEjf//3f89vfvMb3ve+95FIJLjssstm1Ybh4WEKhQIDAwOzfo/O1zXXXMPw8DDHH388juMQRRGf/vSnueSSS6a8TzO2Y/aaYwmpP//zP58yKLbWcv311/Oxj32M17/+9QD83//7f+nu7ub73/8+f/3Xf30wD7WOZNTm4dZbb6W1tbV6+fnPf84NN9zAgw8+yA9+8AO2bNnCP//zP3PllVfyn//5n4t9uJMa34bKQOnXv/71fPCDH+TUU0/lmmuu4S//8i9nNCliMYxvw/3338+XvvQlbrnlFpRSi314MzLZe6kiCALe8pa3YK3lpptuWsSjPLxdeeWV/OEPf+C2225b7EOZlRdeeIH3v//93HrrraRSqcU+nDkxxnD66afzT//0T5x22mlcccUVXH755U17TprKv/3bv3HrrbfyrW99i0ceeYRvfOMbfOELX+Ab3/jGYh/aYa8ZMvZTkYzaPFx44YWcc8451eurVq3ivPPO43vf+x4XXHABAC972ct49NFH+cIXvjBll0NPT8+EWXd79uyhp6enentl24oVK+r2OfXUUxe0DcuWLcN1XU444YS6/V760pfyi1/8YsrHaaY23HHHHfT19bFmzZrqtiiK+NCHPsT111/P888/P+Exli5diuM407bB930GBwfrMlK1+yxUG1atWgWMBWnbt2/npz/96ZTZtGZow2yPZbzFfA9NZ8OGDfzwhz/kZz/7GatXrz7gvs3Wji1bttDX18fpp59e3RZFET/72c/4l3/5F0qlEo7jNHUbVqxYMek56d///d+nvM9UbWhrayOdTuM4zqzfo/N11VVXcc0111SzMyeffDLbt2/n2muvnTIz2IztmC1L48pz+L7P8PBw3bZkMjnrtVEXO2N/IJJRm4dsNsuxxx5bvQRBQBAEaF3/sjqOgzFTv0nXrVvH5s2b67b95Cc/Yd26dQAcddRR9PT01O0zPDzMr3/96+o+C9WG9vZ2zjrrrAklCJ566imOPPLIQ6INV1xxBb/73e949NFHq5eVK1dy1VVX8eMf/3jSx0gkEpxxxhl1x2eMYfPmzdXjO+OMM/A8r26frVu3smPHjgVvQzqdrgZpTz/9NP/5n/9JV1fXAR9jsdsw22MZbzHfQ1Ox1rJhwwa+973v8dOf/pSjjjpq2vs0WzvOO+88fv/739d9Hs4880wuueQSHn300QlBWjO24dxzz13wc9Jc3qPzlc/nF/zvw2K0Y/YshmjBLxbL7bffTnt7e93l2muvXewGL6zFncvw4vOqV73Knnjiifbee++1zz77rL355pttKpWyN954Y3WfSy+91F5zzTXV67/85S+t67r2C1/4gn3iiSfsJz/5yUmnwnd0dNg777zT/u53v7Ovf/3rGzYV/rvf/a71PM9+9atftU8//XR1OvjPf/7zQ6YN40026/O1r32tveGGG6rXb7vtNptMJu0tt9xiH3/8cXvFFVfYjo4O29vbW93nPe95j12zZo396U9/ah9++GG7bt06u27dugU/Xt/37YUXXmhXr15tH330Ubt79+7qpVQqHRJtmO5YDoX30N/93d/Z9vZ2e99999X9DvL5fHWfQ6Ed442f9dnsbXjooYes67r205/+tH366aftrbfeajOZjP1//+//Vfe55ppr7KWXXlq9XilrcdVVV9knnnjCbtq0adKyFtN9XhbSZZddZletWlUtz/Hd737XLl261H74wx8+pNoxG7fddptNO0vtCUvetuCXhG6zd911lx0aGqq7FIvFaY+LcbM+t23bZgH729/+tm6/V77ylfZ973vfAr8qsyOB2gLbvXu3fcc73mFXrlxpU6mUfclLXmL/+Z//2Rpjqvu86lWvspdddlnd/f7t3/7NHnfccTaRSNgTTzzR3n333XW3V6YNd3d322Qyac877zy7devWhrXja1/7mj322GNtKpWyp5xyiv3+979fd/uh0IZakwVqRx55pP3kJz9Zt+2GG26wa9assYlEwp599tn2wQcfrLu9UCjY//k//6ddsmSJzWQy9o1vfKPdvXv3gh/vc889F/cWTHK59957D4k2THcsh8J7aKrfwc0333xItWO88YHaodCGu+66y5500kk2mUza448/3n71q1+tu/2yyy6zr3rVq+q23XvvvfbUU0+1iUTCHn300XW/t4rpPi8LaXh42L7//e+3a9assalUyh599NH2ox/9aN2Xr0OhHbNRCdReuuT/W/BLQrfNuY7a+ECtUnLmC1/4QnXb0NDQQS3/MxVl7TQlkYUQQggh5uD222/nnZdsYG3b1CWq5mrb0A+56z/uOGD5q1qjo6M888wzAJx22ml88Ytf5DWveQ2dnZ2sWbOGz372s3zmM5/hG9/4BkcddRQf//jH+d3vfsfjjz++qBNxZDKBEEIIIRrGKotRi1+e4+GHH+Y1r3lN9frGjRsBuOyyy7jlllv48Ic/TC6X44orrmBwcJA//dM/5Z577ln02dISqAkhhBCioQzRgj+mnWXB21e/+tUHXFdVKcWnPvUpPvWpT8330BaUzPoUQgghhGhSklETQgghRAPZhtVROxxIoCaEEEKIhrEWjF34rs/ZrvV5qJKuTyGEEEKIJiUZNSGEEEI0kHR9zodk1IQQB9XXvva1Gdc9mo977rmHU0899YDL8wghRLOTQE0IcdAUi0U+/vGP88lPfrLhz/U//sf/wPM8br311oY/lxDiQCyWaMEvMkZNCCEW2He+8x3a2to499xzD8rzveMd7+DLX/7yQXkuIcTkLGAa8O/wCNMkUBNCzMHevXvp6enhn/7pn6rbfvWrX5FIJNi8efOU97vtttt43eteV7ft1a9+NR/4wAfqtr3hDW/gHe94R/X62rVr+cd//Efe/va309raypFHHskPfvAD9u7dy+tf/3paW1t52ctexsMPP1z3OK973et4+OGH2bZt29wbK4QQi0gCNSHErC1btoyvf/3r/K//9b94+OGHGRkZ4dJLL2XDhg2cd955U97vF7/4BWeeeeacnvO6667j3HPP5be//S0XXHABl156KW9/+9t529vexiOPPMIxxxzD29/+9rrK42vWrKG7u5uf//znc3pOIcTCsJgFvxwuZNanEGJO/uIv/oLLL7+cSy65hDPPPJOWlhauvfbaKfcfHBxkaGiIlStXzvn53v3udwPwiU98gptuuomzzjqLN7/5zQBcffXVrFu3jj179tDT01O938qVK9m+ffucnlMIsRAsVuqozZlk1IQQc/aFL3yBMAy54447uPXWW0kmk1PuWygUAOa8wPHLXvay6s/d3d0AnHzyyRO29fX11d0vnU6Tz+fn9JxCCLHYJFATQszZtm3b2LVrF8YYnn/++QPu29XVhVKKgYGBaR83iiZ++/Y8r/qzUmrKbePLcfT397Ns2bJpn1MI0RhxFbWF/3e4kEBNCDEnvu/ztre9jYsvvph/+Id/4G//9m8nZLNqJRIJTjjhBB5//PEJt+3Zs6fu+rPPPrsgx1gsFtm2bRunnXbagjyeEEIcbBKoCSHm5KMf/ShDQ0N8+ctf5uqrr+a4447jb/7mbw54n/Xr1/OLX/xiwvY777yT7373u2zbto1Pf/rTPP7442zfvp2dO3fO6xgffPBBkskk69atm9fjCCHmpxF11A6PEWoSqAkh5uC+++7j+uuv55vf/CZtbW1orfnmN7/Jz3/+c2666aYp7/eud72LH/3oRwwNDdVtv+CCC/jc5z7HCSecwM9+9jNuvPFGHnroIb75zW/O6zi//e1vc8kll5DJZOb1OEKI+bBYaxb8crhMJpBZn0KIWXv1q19NEAR129auXTshABvvhBNO4IILLuDGG2/kIx/5SHX7qlWruOOOO+r2/bu/+7vqz5ONf6stw1F5/tpt+/bt4zvf+c6E2mpCCHEokYyaEOKg+vznP09ra2vDn+f555/nxhtv5Kijjmr4cwkhptaolQkOF5JRE0IcVGvXruW9731vw5/nzDPPnHNxXSHEQpI6avMhgZoQYlHdd999i30IQgjRtCRQE0IIIURDHU5LPi00GaMmhBBCCNGkJKMmhBBCiMaxtlxOQ8yFBGpCCCGEaCjLwk8msIfJZALp+hRCCCGEaFKSURNCCCFEw1ga1PV5eCTUJFATQgghRGPJGLW5k65PIYQQQogmJRk1IYQQQjSQbdCST4dH36dk1IQQQgghmpRk1IQQQgjRMBYZozYfEqgJIYQQooEasyj74dHxKV2fQgghhBBNSzJqQgghhGioxizKfnjk1CRQE0IIIUTjyFqf8yJdn0IIIYQQTUoyakIIIYRoKMmozZ1k1IQQQgghmpRk1IQQQgjRMBYrkwnmQQI1IYQQQjRUQ7o+D484Tbo+hRBCCCGalWTUhBBCCNFAjSnPcZgk1CRQE0IIIUSjyRi1uZKuTyGEEEKIJiUZNSGEEEI0jqxMMC+SURNCCCGEaFKSURNCCCFEw1gatSj74UECNSGEEEI0VGO6PmUygRBCCCGEWESSURNCCCFEA1kgWuyDOGRJoCaEEEKIBpJZn/MhXZ9CCCGEEE1KMmpCCCGEaDCZTDBXklETQgghhGhSklETQgghRGPJGLU5k0BNCCGEEA1ksYdJN2UjSNenEEIIIUSTkoyaEEIIIRpMJhPMlQRqQgghhGgse3gEVY0gXZ9CCCGEEE1KMmpCCCGEaCCZTDAfklETQgghREMkEonyTwsdqMWPl0wmF/hxm4+yVjqOhRBCCLHwSqUSqVSKOC+0kLkhAxjCMMRxnAV83OYjGTUhhBBCNEQymeRb3/oWcWC1UHkhCxjuueeeF32QBpJRE0IIIUQDGWPKAdVCZdUiAOxhstqBZNSEEEII0TBaa+677z4WJqtmAcujj/523sd1qJCMmhBCCCEaTqlKbmg+3ZWHVzYNJKMmhBBCiIPg8cf/i0pGbG7i++7YsX3hDuoQIBk1IYQQQhwUc8+qxRMI4PDKpoFk1IQQQghxkOzevYu5ZdXi+wwODiz8QTU5CdSEEEIIcVD09PQQhx4RMw/W4mzal7/8Zdrb2xt2bM1Kuj6FEEIIcdCMjo6SzWaZebmOuLhtqVSqWeng8CEZNSGEEEIcNK2trXz1q19lZuU64mzad77zncMySAPJqAkhhBDiIAvDEM/zmD6rFmfTjDEopQ7OwTUZyagJIYQQ4qByXZe77rqLA2fV4mzaL3/5y8M2SAPJqAkhhBBiEVhr0bpSpmOych2HX3HbyUhGTQghhBAHnVKKhx/+DZOX64i3PfXU1oN/YE1GMmpCCCGEWDSTF8GVbFqFZNSEEEIIsWiee+5Z6rNq8bi1vr49i3dQTUQyakIIIYRYVGNZtUoxXI210SIeUfOQjJoQQgghFlV//35q1/PM5UYW9XiaiQRqQgghhFhUS5YsIQ5JLDfffDOZTGaxD6lpuIt9AEIIIYQQxWKen/3sZ7z2ta9d7ENpKjJGTQghhBCiSUnXpxBCCCFEk5JATQghhBCiSUmgJoQQQgjRpCRQE0IIIYRoUhKoCSGEEEI0KQnUhBBCCCGalARqQgghhBBNSgI1IYQQQogm9f8DSKpP2qQAUiwAAAAASUVORK5CYII=",
+      "text/plain": [
+       "
"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plot field\n",
+    "sim_data.plot_field(\"field_mon\", \"E\", \"abs\", f=cross_freq)\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Parametric Sweep \n",
+    "\n",
+    "Now, we will investigate how the sidewall angle changes the component performance. To do so, we will create a dictionary where each value is a simulation object with a different coupler sidewall."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "sims = {}\n",
+    "sidewall_angles = [0, 5, 10, 15, 20, 25, 30]\n",
+    "for s_angle in sidewall_angles:\n",
+    "    arms_geo_sweep = td.Geometry.from_gds(\n",
+    "        all_cells[\"COUPLER\"],\n",
+    "        gds_layer=1,\n",
+    "        gds_dtype=0,\n",
+    "        axis=2,\n",
+    "        slab_bounds=(0, wg_height),\n",
+    "        sidewall_angle=np.deg2rad(s_angle),\n",
+    "        dilation=dilation,\n",
+    "        reference_plane=reference_plane,\n",
+    "    )\n",
+    "\n",
+    "    arms_sweep = td.Structure(geometry=arms_geo_sweep, medium=medium_wg)\n",
+    "    sims[s_angle] = sim.updated_copy(structures=[substrate, arms_sweep])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Next, we create a [Batch](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.web.api.container.Batch.html) object to run all simulations in parallel."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "a6c3124ddaa44eb3a859a69809486982",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Output()"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
\n"
+      ],
+      "text/plain": []
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
\n",
+       "
\n"
+      ],
+      "text/plain": [
+       "\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
16:49:54 -03 Started working on Batch containing 7 tasks.                       \n",
+       "
\n"
+      ],
+      "text/plain": [
+       "\u001b[2;36m16:49:54 -03\u001b[0m\u001b[2;36m \u001b[0mStarted working on Batch containing \u001b[1;36m7\u001b[0m tasks.                       \n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
16:50:03 -03 Maximum FlexCredit cost: 1.809 for the whole batch.                \n",
+       "
\n"
+      ],
+      "text/plain": [
+       "\u001b[2;36m16:50:03 -03\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m1.809\u001b[0m for the whole batch.                \n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
             Use 'Batch.real_cost()' to get the billed FlexCredit cost after the\n",
+       "             Batch has completed.                                               \n",
+       "
\n"
+      ],
+      "text/plain": [
+       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mUse \u001b[32m'Batch.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed FlexCredit cost after the\n",
+       "\u001b[2;36m             \u001b[0mBatch has completed.                                               \n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "36485fc5c7c34b9ab50868f9e800a3d1",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Output()"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
16:50:09 -03 Batch complete.                                                    \n",
+       "
\n"
+      ],
+      "text/plain": [
+       "\u001b[2;36m16:50:09 -03\u001b[0m\u001b[2;36m \u001b[0mBatch complete.                                                    \n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
\n"
+      ],
+      "text/plain": []
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
\n",
+       "
\n"
+      ],
+      "text/plain": [
+       "\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "c921578ef80a469999236e427d86fe9b",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Output()"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
\n"
+      ],
+      "text/plain": []
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
\n",
+       "
\n"
+      ],
+      "text/plain": [
+       "\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "batch = web.Batch(simulations=sims, folder_name=\"directional_coupler\")\n",
+    "batch_data = batch.run()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now we can easily track the crossing frequency and transmittance using our defined post-processing function."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "freqs = []\n",
+    "transmittance = []\n",
+    "for data in batch_data.values():\n",
+    "    f, t = postprocess(data, plot=False)\n",
+    "    freqs.append(f)\n",
+    "    transmittance.append(t)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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9+/cXW1iKSKVS8XeBXC7H48ePUVhYiBYtWpT4Pr/q2r/Oz2yjRo3Qpk0b8XVRK17Xrl0VrlHR+qJjlKcXf76Kehg6deqEW7duIT09vVi8RecLPG+tatCggUJcO3fuhJubG/r27VvsWEWfs+3bt6Nhw4ZwcXFR+Hx37doVAIp1jRa93y/3ftCbr8p0z7Vq1arMgeAv31kXHx8P4HkyVZr09HTk5eXh2bNnqFevXrHtDRo0wL59+1471gcPHuDp06f48ccf8eOPP5ZY5uWBzy9/aRT9UBb9krt58yaAV98x+N5778Ha2hpRUVHo1q0b5HI5fvrpJ/Tp0wcmJiZl7ls09mvbtm3o1q0bgOddc82aNUP9+vUBAPr6+pg/fz4mTJgAS0tLtG7dGr1790ZAQACsrKzKrB8AvL294e3tjZycHJw5cwbbtm3DihUr0Lt3b1y9erXY2Cbg+fup7DWKj4+HIAgllgUgdlcAz79cZsyYgWfPnuHo0aOwtrZG8+bN4ebmhqNHj4rjFl4evPzbb79hzpw5iIuLUxjvUF5z1MhkMmzduhVdunRBQkKCuN7T0xOLFi1CTEwMunfvrrDPqz4/d+7cAYAS77579913y0x6VPk8l0QQBIXXRV9sZX2mHzx4gJycHDRo0KDYtoYNG0Iul+Pu3btiV8yLis65pH1dXFxw7NgxhXXVqlUrsdu4pIHd5eXl31tFNmzYgEWLFuHq1asoKCgos/yrrv3r/My+XJeZmRkAwM7OrsT1r/uHkzKOHz+O6dOn4+TJk8W6RdPT08VjlxQv8Pz8X4zr5s2br/yDMT4+HleuXCmWwBZ5+fNd9Fl+2+elehtVmaTpVV786wR4/hcaAHz77bfFxgAUMTY2LnGQX2lK+wF5+S//omN/9NFHpSZtTZs2VXhd2m3YL3/RvIpUKsXgwYOxatUq/PDDDzh+/Dju379f5l07RfT19eHn54fdu3fjhx9+QGpqKo4fP4558+YplBs3bhx8fX2xZ88e7N+/H2FhYQgPD8fff/9dbCxVaapXr44OHTqgQ4cOqFWrFmbOnIk//vijzCRXGXK5HBKJBH/88UeJ7+mLrSzt27dHQUEBTp48iaNHj4p/sXbo0AFHjx7F1atX8eDBA4W/ZI8ePYr3338fHTt2xA8//ABra2vo6upi3bp15TbX1N9//43k5GRs3boVW7duLbY9KiqqWNJUXp+fkqjyeX6Rubk5JBJJhXzBlid9ff0Sx+dkZWUhKyvrlftLpdJSv3RL8/LvLeD5TQxDhw6Fn58fJk2aBAsLC0ilUoSHh4t/PL183JK8eO2V/Zktra6K/Hy96ObNm+jWrRtcXFwQEREBOzs76OnpYd++ffjuu+/Ez2J5xyWXy9GkSRNERESUuP3lpLHos/ziuFrSDkyaSlF0l46pqSm8vLxKLVd0x05Ry9SLrl27pvC66C+4lydkK/qL9sU6TUxMIJPJyjz26yg6n4sXL76yzoCAACxatAi//vor/vjjD9SuXVvprkZ/f39s2LABMTExuHLlCgRBELvmXo5nwoQJmDBhAuLj49GsWTMsWrQImzdvfu1zK2pBTE5OLnH761wjZ2dnCIIAR0dHsXWsNK1atYKenh6OHj2Ko0ePinf0dOzYEatWrUJMTIz4usjOnTthYGCA/fv3Q19fX1y/bt06Jc5UOVFRUbCwsMDy5cuLbdu1axd2796NFStWlPiFWxp7e3sAKPGOzJLWvUjdz3O1atXg7Oys0GoGQGy9Kbors7RjV69evdh1Bp7fdaejo1PsC61I0Tlfu3ZN7GYpcu3aNXH7qyxcuBAzZ858ZTl7e/tX3kGqjB07dsDJyQm7du1S+ENN3ekmyvNnVlml/aFZ2vpff/0VeXl52Lt3r0Ir0svdY6/D2dm5zM9YUZlz586hW7duSrUeFX2WGzZsqHJcpBlVZkzT6/Lw8ICzszMWLlxY4l+JDx48APD8LxVvb2/s2bMHiYmJ4vYrV65g//79CvuYmpqiVq1a4jiYIi9PqS+VStG/f3/s3LmzxB/WomO/jubNm8PR0RGLFy8ulrS9/FdV06ZN0bRpU6xevRo7d+7EwIEDlZ4/xcvLC+bm5ti2bRu2bduGVq1aKXQJ5OTkFJsJ19nZGSYmJq9stStKQl5W1L1WUjcK8HrXqF+/fpBKpZg5c2ax90UQBDx69Eh8bWBggJYtW+Knn35CYmKiQkvTs2fP8P3338PZ2RnW1tYKsUgkEoXWxdu3b5c467Eqnj17hl27dqF379744IMPii1jxoxBZmYm9u7d+1r12tjYwNXVFRs3blT4eTh8+DAuXLhQ5r7l8Xlu06YNTp8+rbCudu3a6NixI9auXatwXYH//0xLpVJ0794dv/zyi0JCkpqaii1btqB9+/YwNTUt8ZgtWrSAhYUFVqxYofDZ/OOPP3DlyhWl73SsyDFNJSlqPXnx83vq1ClxnN3rUudnVl1GRkYlzvpdNP/Vy9tKOvf09HS1/ijp378/zp07h927dxfbVnScAQMGICkpCatWrSpW5tmzZ8jOzlZYd+bMGUgkEoXxX6Qd2NJUCh0dHaxevRo+Pj5o3LgxgoKCYGtri6SkJBw8eBCmpqb49ddfAQAzZ85EdHQ0OnTogFGjRqGwsBBLly5F48aNcf78eYV6P/nkE3zzzTf45JNP0KJFCxw5cgTXr18vdvxvvvkGBw8ehKenJ4KDg9GoUSM8fvwY//33H/7666/Xnt9DR0cHkZGR8PX1RbNmzRAUFARra2tcvXoVly5dKpY8BAQEYOLEiQCgVNdcEV1dXfTr1w9bt25FdnY2Fi5cqLD9+vXr6NatGwYMGIBGjRqhWrVq2L17N1JTU1/5eIw+ffrA0dERvr6+cHZ2RnZ2Nv766y/8+uuvaNmyJXx9fUvdV9lr5OzsjDlz5iA0NBS3b9+Gn58fTExMkJCQgN27d+PTTz8V3xfgeYL0zTffwMzMTBwQbWFhgQYNGuDatWsKz44Dng8ijoiIQI8ePTB48GCkpaVh+fLlePfdd4t9VlSxd+9eZGZm4v333y9xe+vWrVG7dm1ERUWV2AJYlnnz5qFPnz5o164dgoKC8OTJEyxbtgyurq6v7H5S9/Pcp08fbNq0CdevX1doAfz+++/Rvn17NG/eHJ9++ikcHR1x+/Zt/P7774iLiwMAzJkzBwcOHED79u0xatQoVKtWDStXrkReXh4WLFhQ6jF1dXUxf/58BAUFoVOnThg0aJA45YCDgwPGjx+v1PtWkWOaStK7d2/s2rULffv2Ra9evZCQkIAVK1agUaNGSnUTvkydn1l1eXh44K+//kJERARsbGzg6OgIT09PeHh4AACmTJmCgQMHQldXF76+vujevTv09PTg6+uLESNGICsrC6tWrYKFhUWpLdGvMmnSJOzYsQMffvghhg0bBg8PDzx+/Bh79+7FihUr4Obmho8//hg///wzRo4ciYMHD6Jdu3aQyWS4evUqfv75Z+zfv19hTO2BAwfQrl07vPPOO+XyPlElqsQ79TSiaMqBf//9t8TtRbcZb9++vcTtZ8+eFfr16ye88847gr6+vmBvby8MGDBAiImJUSh3+PBhwcPDQ9DT0xOcnJyEFStWlHgLbU5OjjB8+HDBzMxMMDExEQYMGCCkpaUVu0VbEAQhNTVVGD16tGBnZyfo6uoKVlZWQrdu3YQff/zxlfGXNr3BsWPHhPfee08wMTERjIyMhKZNmwpLly4tdt7JycmCVCoV6tevX+L7UpYDBw4IAASJRCLcvXtXYdvDhw+F0aNHCy4uLoKRkZFgZmYmeHp6Cj///PMr6/3pp5+EgQMHCs7OzoKhoaFgYGAgNGrUSJgyZYqQkZGhULak91PZayQIgrBz506hffv2gpGRkWBkZCS4uLgIo0ePFq5du6ZQ7vfffxcACD4+PgrrP/nkEwGAsGbNmmJ1r1mzRqhXr56gr68vuLi4COvWrSsxDlWmHPD19RUMDAyE7OzsUssMHTpU0NXVFR4+fCh+Tkq6nbyk93Dr1q2Ci4uLoK+vL7i6ugp79+4V+vfvL7i4uLxyX2U+z6XJy8sTatWqJcyePbvYtosXLwp9+/YVatSoIRgYGAgNGjQQwsLCFMr8999/gre3t2BsbCxUr15d6NKli8Kt8YJQ+vu7bds2wd3dXdDX1xfMzc2FIUOGCPfu3VMoExgYKBgZGb3yPFRV2pQDJV03uVwuzJs3T7C3txf09fUFd3d34bfffhMCAwMVpjVQ9tor+zNrb28v9OrVq8S6Ro8erbCupGOX9DNw9epVoWPHjoKhoaEAQOE9mD17tmBrayvo6OgoTD+wd+9eoWnTpoKBgYHg4OAgzJ8/X1i7dm2xKQpKi7dTp05Cp06dFNY9evRIGDNmjGBrayvo6ekJderUEQIDAxWm0MjPzxfmz58vNG7cWNDX1xdq1qwpeHh4CDNnzhTS09PFck+fPhX09PSE1atXFzs2vfkkglDOI/FINGPGjBK7ebTBw4cPYW1tjWnTpiEsLEzT4dAbrFmzZqhdu3axaTzK2+zZs7Fu3TrEx8e/9c+fo7fX4sWLsWDBAty8efO1xhXSm4FjmqhE69evh0wmw8cff6zpUOgNUVBQgMLCQoV1hw4dwrlz59C5c+cKP/748eORlZVV4h2BRNqgoKAAERERmDp1KhMmLcUxTaTg77//xuXLlzF37lz4+fkp9UwxqhqSkpLg5eWFjz76CDY2Nrh69SpWrFgBKysrjBw5ssKPb2xsrNR8TkRvKl1d3WI3LZB2YdJECmbNmoUTJ06gXbt2WLp0qabDoTdIzZo14eHhgdWrV+PBgwcwMjJCr1698M0333BAKxFVCRzTRERERKQEjmkiIiIiUgKTJiIiIiIlMGkiIiIiUgKTJiIiIiIlMGl6hSNHjsDX1xc2NjaQSCSv/Yyw3NxcDB06FE2aNEG1atXg5+dXZvnjx4+jWrVqaNasmcoxExERUflj0vQK2dnZcHNzK/GJ8cqQyWQwNDTEF1988convD99+hQBAQHo1q2bSsciIiKiisOk6RV8fHwwZ84c9O3bt8TteXl5mDhxImxtbWFkZARPT08cOnRI3G5kZITIyEgEBwfDysqqzGONHDkSgwcP5pOviYiI3kBMmtQ0ZswYnDx5Elu3bsX58+fx4YcfokePHoiPj3+tetatW4dbt25h+vTpFRQpERERqYMzgqshMTER69atQ2JiImxsbAAAEydORHR0NNatW4d58+YpVU98fDwmT56Mo0ePolo1XhIiIqI3Eb+h1XDhwgXIZDLUr19fYX1eXp7Sj5WQyWQYPHgwZs6cWaweIiIienMwaVJDVlYWpFIpzpw5A6lUqrDN2NhYqToyMzNx+vRpnD17FmPGjAEAyOVyCIKAatWq4c8//0TXrl3LPXYiIiJ6PUya1ODu7g6ZTIa0tDR06NBBpTpMTU1x4cIFhXU//PAD/v77b+zYsQOOjo7lESoRERGpiUnTK2RlZeHGjRvi64SEBMTFxcHc3Bz169fHkCFDEBAQgEWLFsHd3R0PHjxATEwMmjZtil69egEALl++jPz8fDx+/BiZmZmIi4sDADRr1gw6OjpwdXVVOKaFhQUMDAyKrSciIiLNYdL0CqdPn0aXLl3E1yEhIQCAwMBArF+/HuvWrcOcOXMwYcIEJCUloVatWmjdujV69+4t7tOzZ0/cuXNHfO3u7g4AEAShks6CiIiI1CUR+M1NRERE9Eqcp4mIiIhICUyaiIiIiJTAMU0lkMvluH//PkxMTCCRSDQdDhERvcEEQUBmZiZsbGygo1NxbRG5ubnIz89Xux49PT0YGBiUQ0RVD5OmEty/fx92dnaaDoOIiLTI3bt3UadOnQqpOzc3F472xkhJk6ldl5WVFRISEpg4qYBJUwlMTEwAPP8BMDU11XA0RET0JsvIyICdnZ343VER8vPzkZImw50zDjA1Ub01KyNTDnuP28jPz2fSpAImTSUo6pIzNTVl0kREREqpjOEcxiYSGJuofhw5OOREHUyaiIiItIRMkEOmxkRBMkFefsFUQUyaiIiItIQcAuRQPWtSZ1/ilANERERESmFLExERkZaQQw51OtjU25vY0kRERKQlZIKg9qKK5cuXw8HBAQYGBvD09ERsbGypZQsKCjBr1iw4OzvDwMAAbm5uiI6OViiTmZmJcePGwd7eHoaGhmjbti3+/fdfhTK7du1C9+7d8c4770AikYgPu9ckJk1ERERUqm3btiEkJATTp0/Hf//9Bzc3N3h7eyMtLa3E8lOnTsXKlSuxdOlSXL58GSNHjkTfvn1x9uxZscwnn3yCAwcOYNOmTbhw4QK6d+8OLy8vJCUliWWys7PRvn17zJ8/v8LPUVl8YG8JMjIyYGZmhvT0dE45QEREZaqM74yiY9y5aqP+PE0u918rVk9PT7Rs2RLLli0D8PypGXZ2dvj8888xefLkYuVtbGwwZcoUjB49WlzXv39/GBoaYvPmzXj27BlMTEzwyy+/oFevXmIZDw8P+Pj4YM6cOQr13b59G46Ojjh79iyaNWumwlmXH45pIiIi0hJyCJCVw91zGRkZCuv19fWhr69frHx+fj7OnDmD0NBQcZ2Ojg68vLxw8uTJEo+Rl5dXbOJMQ0NDHDt2DABQWFgImUxWZpk3FbvniIiIqhg7OzuYmZmJS3h4eInlHj58CJlMBktLS4X1lpaWSElJKXEfb29vREREID4+HnK5HAcOHMCuXbuQnJwM4PlTN9q0aYPZs2fj/v37kMlk2Lx5M06ePCmWeVOxpYmIiKoUIf8chJwNQN4xAAKg1xKS6oGQ6HtqOrRXKq95ml5+TFhJrUyqWrJkCYKDg+Hi4gKJRAJnZ2cEBQVh7dq1YplNmzZh2LBhsLW1hVQqRfPmzTFo0CCcOXOm3OKoCGxpIiKiKkPI2Qbh8QAg9w9AeAoI6UDeQQhPPoaQtVLT4b1Sed09V/SYsKKltKSpVq1akEqlSE1NVVifmpoKKyurEvepXbs29uzZg+zsbNy5cwdXr16FsbExnJycxDLOzs44fPgwsrKycPfuXcTGxqKgoEChzJuISRMREVUJQuENCBnTAAgAZC9sef5/IWsRhPw3u6Wjsunp6cHDwwMxMTHiOrlcjpiYGLRp06bMfQ0MDGBra4vCwkLs3LkTffr0KVbGyMgI1tbWePLkCfbv319imTcJu+eIiKhKEHK24HlbgayUElII2Zsg0fOoxKhej/x/izr7v66QkBAEBgaiRYsWaNWqFRYvXozs7GwEBQUBAAICAmBrayuOizp16hSSkpLQrFkzJCUlYcaMGZDL5fjyyy/FOvfv3w9BENCgQQPcuHEDkyZNgouLi1gnADx+/BiJiYm4f/8+AODatWsAACsrq1JbuSoakyYiIqoa8k+j9IQJz7cV/FvGds2TqXn3nCr7+vv748GDB5g2bRpSUlLQrFkzREdHi4PDExMToaPz/x1Xubm5mDp1Km7dugVjY2P07NkTmzZtQo0aNcQy6enpCA0Nxb1792Bubo7+/ftj7ty50NXVFcvs3btXIYkaOHAgAGD69OmYMWPGa59HedDoPE1HjhzBt99+izNnziA5ORm7d++Gn59fmfssX74cy5Ytw+3bt1G3bl1MmTIFAQEBCmWePn2KKVOmYNeuXXj8+DHs7e2xePFi9OzZU6m4OE8TEdHbR/6wL1B4qexCOlbQsTjyWvVW5jxN5y9bwESNeZoyM+Vo2iiN328q0mhLU3Z2Ntzc3DBs2DD069fvleUjIyMRGhqKVatWoWXLloiNjUVwcDBq1qwJX19fAM/nlHjvvfdgYWGBHTt2wNbWFnfu3FHIcImIqArS7wQUXkHpnVRSQL9zJQZE2kajSZOPjw98fHyULr9p0yaMGDEC/v7+AAAnJyf8+++/mD9/vpg0rV27Fo8fP8aJEyfEZj4HB4dyj52IiLSLpPpACNlrAOQDxbqpJP8r83Flh/VaNDGmif6fVt09V9oso0W3KgLP+0DbtGmD0aNHw9LSEq6urpg3bx5ksrL6sYmI6G0nkVpBUnMFAD0ofv3pAJBCUiMCEt16mglOSXJIIFNjkf8vOSTVaNVAcG9vb6xevRp+fn5o3rw5zpw5g9WrV6OgoAAPHz6EtbU1bt26hb///htDhgzBvn37cOPGDYwaNQoFBQWYPn16ifXm5eUhLy9PfP3y9PJERPR2kOi3A2rHAM+2Q8g7DkAO6LWCpLo/JFJbTYdHbzitSprCwsKQkpKC1q1bQxAEWFpaIjAwEAsWLBBH7svlclhYWODHH3+EVCqFh4cHkpKS8O2335aaNIWHh2PmzJmVeSpERKQhEqkFYDwaEuPRry78hpELzxd19ifVaVX3nKGhIdauXYucnBzcvn0biYmJcHBwgImJCWrXrg0AsLa2Rv369SGVSsX9GjZsiJSUFOTn55dYb2hoKNLT08Xl7t27lXI+REREr0OdrrmihVSnVUlTEV1dXdSpUwdSqRRbt25F7969xZamdu3a4caNG5DL/3+42/Xr12FtbQ09Pb0S69PX1y82pTwRERHRizSaNGVlZSEuLg5xcXEAgISEBMTFxSExMRHA8xagF+dgun79OjZv3oz4+HjExsZi4MCBuHjxIubNmyeW+eyzz/D48WOMHTsW169fx++//4558+Zh9Gjta4YlIiJ6EVuaNEujY5pOnz6NLl26iK9DQkIAAIGBgVi/fj2Sk5PFBAoAZDIZFi1ahGvXrkFXVxddunTBiRMnFKYUsLOzw/79+zF+/Hg0bdoUtra2GDt2LL766qtKOy8iIqKKIBckkAuqJz7q7EsanhH8TcUZwYmISFmVOSP4sYs2MFZjRvCsTDnau97n95uKtOruOSIioqpM3S42ds+ph0kTERGRlpBBBzI1hiNzmmf1MGkiIiLSEoKaY5oEjmlSi1ZOOUBERERU2djSREREpCU4pkmzmDQRERFpCZmgA5mgxpgm3i+vFnbPERERESmBLU1ERERaQg4J5Gq0d8jBpiZ1MGkiIiLSEhzTpFnsniMiIiJSAluaiIiItIT6A8HZPacOJk1ERERa4vmYJjUe2MvuObWwe46IiIhICWxpIiIi0hJyNZ89x7vn1MOkiYiISEtwTJNmMWkiIiLSEnLocJ4mDeKYJiIiIiIlsKWJiIhIS8gECWSCGpNbqrEvMWkiIiLSGjI1B4LL2D2nFnbPERERESmBLU1ERERaQi7oQK7G3XNy3j2nFiZNREREWoLdc5rF7jkiIiIiJbCliYiISEvIod4dcPLyC6VKYtJERESkJdSf3JIdTOrgu0dERESkBLY0ERERaQn1nz3HthJ1MGkiIiLSEnJIIIc6Y5o4I7g6mDQRERFpCbY0aRbfPSIiIiIlsKWJiIhIS6g/uSXbStSh0XfvyJEj8PX1hY2NDSQSCfbs2fPKfZYvX46GDRvC0NAQDRo0wMaNG0stu3XrVkgkEvj5+ZVf0ERERBoiFyRqL6Q6jbY0ZWdnw83NDcOGDUO/fv1eWT4yMhKhoaFYtWoVWrZsidjYWAQHB6NmzZrw9fVVKHv79m1MnDgRHTp0qKjwiYiIqArRaNLk4+MDHx8fpctv2rQJI0aMgL+/PwDAyckJ//77L+bPn6+QNMlkMgwZMgQzZ87E0aNH8fTp0/IOnYiIqNLJ1eye4+SW6tGqdy8vLw8GBgYK6wwNDREbG4uCggJx3axZs2BhYYHhw4crXW9GRobCQkRE9KaRCzpqL6Q6rXr3vL29sXr1apw5cwaCIOD06dNYvXo1CgoK8PDhQwDAsWPHsGbNGqxatUrpesPDw2FmZiYudnZ2FXUKREREpKW0KmkKCwuDj48PWrduDV1dXfTp0weBgYEAAB0dHWRmZuLjjz/GqlWrUKtWLaXrDQ0NRXp6urjcvXu3ok6BiIhIZTJI1F5IdVo15YChoSHWrl2LlStXIjU1FdbW1vjxxx9hYmKC2rVr4/z587h9+7bC+Ca5/PkznatVq4Zr167B2dm5WL36+vrQ19evtPMgIiJShbpdbOyeU49WJU1FdHV1UadOHQDPpxXo3bs3dHR04OLiggsXLiiUnTp1KjIzM7FkyRJ2uxEREZHKNJo0ZWVl4caNG+LrhIQExMXFwdzcHHXr1kVoaCiSkpLEuZiuX7+O2NhYeHp64smTJ4iIiMDFixexYcMGAICBgQFcXV0VjlGjRg0AKLaeiIhI28gAtbrYZOUXSpWk0aTp9OnT6NKli/g6JCQEABAYGIj169cjOTkZiYmJ4naZTIZFixbh2rVr0NXVRZcuXXDixAk4ODhUduhERESVjt1zmqXRpKlz584QBKHU7evXr1d43bBhQ5w9e/a1jvFyHURERNqKD+zVLL57RERERErQyoHgREREVZEACeRqjGkSOOWAWpg0ERERaQl2z2kW3z0iIiIiJbCliYiISEvIBQnkgupdbOrsS0yaiIiItIYMOpCp0Umkzr7E7jkiIiJ6heXLl8PBwQEGBgbw9PREbGxsqWULCgowa9YsODs7w8DAAG5uboiOjlYok5mZiXHjxsHe3h6GhoZo27Yt/v33X4UygiBg2rRpsLa2hqGhIby8vBAfH18h56csJk1ERERaoqh7Tp3ldW3btg0hISGYPn06/vvvP7i5ucHb2xtpaWkllp86dSpWrlyJpUuX4vLlyxg5ciT69u2rMM/iJ598ggMHDmDTpk24cOECunfvDi8vLyQlJYllFixYgO+//x4rVqzAqVOnYGRkBG9vb+Tm5r7+G1dOJEJZs0tWURkZGTAzM0N6ejpMTU01HQ4REb3BKuM7o+gYY471hb6xrsr15GUVYFn73a8Vq6enJ1q2bIlly5YBAORyOezs7PD5559j8uTJxcrb2NhgypQpGD16tLiuf//+MDQ0xObNm/Hs2TOYmJjgl19+Qa9evcQyHh4e8PHxwZw5cyAIAmxsbDBhwgRMnDgRAJCeng5LS0usX78eAwcOVPk9UAdbmoiIiKqYjIwMhSUvL6/Ecvn5+Thz5gy8vLzEdTo6OvDy8sLJkydL3CcvLw8GBgYK6wwNDXHs2DEAQGFhIWQyWZllEhISkJKSonBcMzMzeHp6lnrcysCkiYiISEvIBInaCwDY2dnBzMxMXMLDw0s83sOHDyGTyWBpaamw3tLSEikpKSXu4+3tjYiICMTHx0Mul+PAgQPYtWsXkpOTAQAmJiZo06YNZs+ejfv370Mmk2Hz5s04efKkWKao7tc5bmVg0kRERKQlymtM0927d5Geni4uoaGh5RbjkiVLUK9ePbi4uEBPTw9jxoxBUFAQdHT+P+XYtGkTBEGAra0t9PX18f3332PQoEEKZd5Eb3Z0REREJBIEHcjVWIT/zQhuamqqsOjr65d4vFq1akEqlSI1NVVhfWpqKqysrErcp3bt2tizZw+ys7Nx584dXL16FcbGxnBychLLODs74/Dhw8jKysLdu3cRGxuLgoICsUxR3a9z3MrApImIiIhKpKenBw8PD8TExIjr5HI5YmJi0KZNmzL3NTAwgK2tLQoLC7Fz50706dOnWBkjIyNYW1vjyZMn2L9/v1jG0dERVlZWCsfNyMjAqVOnXnncisTJLYmIiLSEDBLI1Hjorir7hoSEIDAwEC1atECrVq2wePFiZGdnIygoCAAQEBAAW1tbcVzUqVOnkJSUhGbNmiEpKQkzZsyAXC7Hl19+Kda5f/9+CIKABg0a4MaNG5g0aRJcXFzEOiUSCcaNG4c5c+agXr16cHR0RFhYGGxsbODn56fy+auLSRMREZGWkAvqPQpFrsIkQ/7+/njw4AGmTZuGlJQUNGvWDNHR0eIg7cTERIWxSLm5uZg6dSpu3boFY2Nj9OzZE5s2bUKNGjXEMkXjqO7duwdzc3P0798fc+fOha7u/0+n8OWXXyI7Oxuffvopnj59ivbt2yM6OrrYXXeVifM0lYDzNBERkbIqc56moEMDoGesp3I9+Vn5WNf5Z36/qYgtTURERFqiaEC3OvuT6pg0ERERaQk5JJCrMaZJnX2Jd88RERERKYUtTURERFrixVm9Vd2fVMekiYiISEtwTJNm8d0jIiIiUgJbmoiIiLSEHBL15mniQHC1MGkiIiLSEoKad88JTJrUwqSJiIhIS8gFNVuaOBBcLRzTRERERKQEtjQRERFpCd49p1lMmoiIiLQEu+c0iyknERERkRLY0kRERKQl+Ow5zdJoS9ORI0fg6+sLGxsbSCQS7Nmz55X7LF++HA0bNoShoSEaNGiAjRs3KmxftWoVOnTogJo1a6JmzZrw8vJCbGxsBZ0BERFR5SnqnlNnIdVpNGnKzs6Gm5sbli9frlT5yMhIhIaGYsaMGbh06RJmzpyJ0aNH49dffxXLHDp0CIMGDcLBgwdx8uRJ2NnZoXv37khKSqqo0yAiIqIqQKPdcz4+PvDx8VG6/KZNmzBixAj4+/sDAJycnPDvv/9i/vz58PX1BQBERUUp7LN69Wrs3LkTMTExCAgIKL/giYiIKhkHgmuWVo1pysvLg4GBgcI6Q0NDxMbGoqCgALq6usX2ycnJQUFBAczNzcusNy8vT3ydkZFRfkETERGVEyZNmqVVd895e3tj9erVOHPmDARBwOnTp7F69WoUFBTg4cOHJe7z1VdfwcbGBl5eXqXWGx4eDjMzM3Gxs7OrqFMgIiIiLaVVSVNYWBh8fHzQunVr6Orqok+fPggMDAQA6OgUP5VvvvkGW7duxe7du4u1UL0oNDQU6enp4nL37t0KOwciIiJVcSC4ZmlV0mRoaIi1a9ciJycHt2/fRmJiIhwcHGBiYoLatWsrlF24cCG++eYb/Pnnn2jatGmZ9err68PU1FRhISIietMI+P9pB1RZBE2fgJbTqjFNRXR1dVGnTh0AwNatW9G7d2+FlqYFCxZg7ty52L9/P1q0aKGpMImIiMoVxzRplkaTpqysLNy4cUN8nZCQgLi4OJibm6Nu3boIDQ1FUlKSOBfT9evXERsbC09PTzx58gQRERG4ePEiNmzYINYxf/58TJs2DVu2bIGDgwNSUlIAAMbGxjA2Nq7cEyQiIqK3hka7506fPg13d3e4u7sDAEJCQuDu7o5p06YBAJKTk5GYmCiWl8lkWLRoEdzc3PDee+8hNzcXJ06cgIODg1gmMjIS+fn5+OCDD2BtbS0uCxcurNRzIyIiKm8c06RZGm1p6ty5MwSh9B7W9evXK7xu2LAhzp49W2adt2/fLofIiIiI3jzsntMsrRoITkRERKQpWjkQnIiIqCpiS5NmMWkiIiLSEoIggaBG4qPOvsTuOSIiIiKlsKWJiIhISxRNUqnO/qQ6Jk1ERERagmOaNIvdc0RERERKYEsTERGRluBAcM1i0kRERKQl2D2nWUyaiIiItARbmjSLY5qIiIiIlMCWJiIiIi0hqNk9x5Ym9TBpIiIi0hICgDKec6/U/qQ6Jk1ERIQ72Ym4kXULOhIdNDZtCAuD2poOieiNw6SJiKgKe5D3ED/c+BE3sm4prPeo6Y5gpyAYVauuocioJHJIIOGM4BrDgeBERFVUZkEmZl/6BreybhfbdvbJOSy4GoFCeWHlB0alKrp7Tp2FVMekiYioiopJO4SnBemQQ15smxxy3Mq+jbNPz2kgMqI3E5MmIqIq6uiDExDKGBqsAwmOPjhRiRHRqxRNbqnOQqrjmCYioioqszCzzO1yCEgvyKikaEgZgqDm3XO8fU4tbGkiIqqi3tEzL3NQsQ50YKHPu+iIijBpIiKqojpbdCxzuxxydLJoX0nRkDI4EFyzmDQREVVRnWt3QN3qdaBTwleBBBK0qOmOxqYNNRAZlYZJk2YxaSIiqqL0pfoIbTgJ7Wq1hlQi/f/1OvroZe2N0e+OgETCL9k3CQeCaxYHghMRVWFG1arjU+dhGFT3Q9zJuQupRAeORo4wkOprOjSiNw6TJiIigomuCVzNGmk6DHoF3j2nWUyaiIiItMTzpEn1LjYmTerhmCYiIiJ662zatAnt2rWDjY0N7ty5AwBYvHgxfvnlF5XrZNJERESkJXj3nHIiIyMREhKCnj174unTp5DJZACAGjVqYPHixSrXy6SJiIhISwjlsFQFS5cuxapVqzBlyhRIpf9/Z2iLFi1w4cIFletl0kRERERvlYSEBLi7uxdbr6+vj+zsbJXr1WjSdOTIEfj6+sLGxgYSiQR79ux55T7Lly9Hw4YNYWhoiAYNGmDjxo3Fymzfvh0uLi4wMDBAkyZNsG/fvgqInoiIqHKxe045jo6OiIuLK7Y+OjoaDRuqPmGrRu+ey87OhpubG4YNG4Z+/fq9snxkZCRCQ0OxatUqtGzZErGxsQgODkbNmjXh6+sLADhx4gQGDRqE8PBw9O7dG1u2bIGfnx/+++8/uLq6VvQpERERVRx1+9iqSP9cSEgIRo8ejdzcXAiCgNjYWPz0008IDw/H6tWrVa5XIghvxg2IEokEu3fvhp+fX6ll2rZti3bt2uHbb78V102YMAGnTp3CsWPHAAD+/v7Izs7Gb7/9JpZp3bo1mjVrhhUrVigVS0ZGBszMzJCeng5TU1PVToiIiKqEyvjOKDqG0/op0KluoHI98pxc3Bo6t0p8v0VFRWHGjBm4efMmAMDGxgYzZ87E8OHDVa5Tq8Y05eXlwcBA8cNiaGiI2NhYFBQUAABOnjwJLy8vhTLe3t44efJkmfVmZGQoLERERPTc8uXL4eDgAAMDA3h6eiI2NrbUsgUFBZg1axacnZ1hYGAANzc3REdHK5SRyWQICwuDo6MjDA0N4ezsjNmzZ+PFdpzU1FQMHToUNjY2qF69Onr06IH4+HilYx4yZAji4+ORlZWFlJQU3Lt3T62ECdCypMnb2xurV6/GmTNnIAgCTp8+jdWrV6OgoAAPHz4EAKSkpMDS0lJhP0tLS6SkpJRab3h4OMzMzMTFzs6uQs+DiIhIFUUzgquzvK5t27YhJCQE06dPx3///Qc3Nzd4e3sjLS2txPJTp07FypUrsXTpUly+fBkjR45E3759cfbsWbHM/PnzERkZiWXLluHKlSuYP38+FixYgKVLl/7vPAX4+fnh1q1b+OWXX3D27FnY29vDy8tLqYHcCQkJYoJVvXp1WFhYAADi4+Nx+/bt138T/kerkqawsDD4+PigdevW0NXVRZ8+fRAYGAgA0NFR/VRCQ0ORnp4uLnfv3i2vkImIiMqNJgaCR0REIDg4GEFBQWjUqBFWrFiB6tWrY+3atSWW37RpE77++mv07NkTTk5O+Oyzz9CzZ08sWrRILHPixAn06dMHvXr1goODAz744AN0795dbMGKj4/HP//8g8jISLRs2RINGjRAZGQknj17hp9++umVMQ8dOhQnTpwotv7UqVMYOnToa78HRbQqaTI0NMTatWuRk5OD27dvIzExEQ4ODjAxMUHt2rUBAFZWVkhNTVXYLzU1FVZWVqXWq6+vD1NTU4WFiIjobfXykJS8vLwSy+Xn5+PMmTMKw150dHTg5eVV6rCX0obSFI09Bp6PUY6JicH169cBAOfOncOxY8fg4+Mj1gFAoR4dHR3o6+sr1FOas2fPol27dsXWt27dusS76pSlVUlTEV1dXdSpUwdSqRRbt25F7969xZamNm3aICYmRqH8gQMH0KZNG02ESkREVH4EifoLADs7O4VhKeHh4SUe7uHDh5DJZK817MXb2xsRERGIj4+HXC7HgQMHsGvXLiQnJ4tlJk+ejIEDB8LFxQW6urpwd3fHuHHjMGTIEACAi4sL6tati9DQUDx58gT5+fmYP38+7t27p1BPaSQSCTIzM4utT09PF2cHV4VGpxzIysrCjRs3xNcJCQmIi4uDubm5+GYlJSWJczFdv34dsbGx8PT0xJMnTxAREYGLFy9iw4YNYh1jx45Fp06dsGjRIvTq1Qtbt27F6dOn8eOPP1b6+REREZUnVcclvbg/ANy9e1ehV0VfX1/NyP7fkiVLEBwcDBcXF0gkEjg7OyMoKEihO+/nn39GVFQUtmzZgsaNGyMuLg7jxo2DjY0NAgMDoauri127dmH48OEwNzeHVCqFl5cXfHx8oMxN/x07dkR4eDh++ukncUZwmUyG8PBwtG/fXuVz02jSdPr0aXTp0kV8HRISAgAIDAzE+vXrkZycjMTERHG7TCbDokWLcO3aNejq6qJLly44ceIEHBwcxDJt27bFli1bMHXqVHz99deoV68e9uzZwzmaiIiI/kfZoSi1atWCVCp9rWEvtWvXxp49e5Cbm4tHjx7BxsYGkydPhpOTk1hm0qRJYmsTADRp0gR37txBeHi4OFbZw8MDcXFxSE9PR35+PmrXrg1PT0+0aNHilXHPnz8fHTt2RIMGDdChQwcAwNGjR5GRkYG///77lfuXRqWk6datWwonr6rOnTuXmTGuX79e4XXDhg0VRt+X5sMPP8SHH36obnhERERvlkqe3FJPTw8eHh6IiYkR51GUy+WIiYnBmDFjytzXwMAAtra2KCgowM6dOzFgwABxW05OTrEbuKRSKeRyebF6zMzMADwfHH769GnMnj37lXE3atQI58+fx7Jly3Du3DkYGhoiICAAY8aMgbm5+Sv3L41KSdO7776LTp06Yfjw4fjggw+KDfgiIiKi8qfuo1BU2TckJASBgYFo0aIFWrVqhcWLFyM7OxtBQUEAgICAANja2orjok6dOoWkpCQ0a9YMSUlJmDFjBuRyOb788kuxTl9fX8ydOxd169ZF48aNcfbsWURERGDYsGFime3bt6N27dqoW7cuLly4gLFjx8LPzw/du3dXKm4bGxvMmzfvtc+3LColTf/99x/WrVuHkJAQjBkzBv7+/hg+fDhatWpVrsERERGRZvn7++PBgweYNm0aUlJS0KxZM0RHR4uDwxMTExVajXJzczF16lTcunULxsbG6NmzJzZt2oQaNWqIZZYuXYqwsDCMGjUKaWlpsLGxwYgRIzBt2jSxTHJyMkJCQpCamgpra2sEBAQgLCxM6bifPn2K2NhYpKWlFWvBCggIUOm9UOsxKoWFhdi7dy/Wr1+P6Oho1K9fH8OGDcPHH38sTgGgjfgYFSIiUlZlPkal7o/ToGOoxmNUnuUi8dNZb/3326+//oohQ4YgKysLpqamkEj+v4VNIpHg8ePHKtWr1pQD1apVQ79+/bB9+3bMnz8fN27cwMSJE2FnZ4eAgAClbgskIiIi5WhickttNGHCBAwbNgxZWVl4+vQpnjx5Ii6qJkyAmknT6dOnMWrUKFhbWyMiIgITJ07EzZs3ceDAAdy/fx99+vRRp3oiIiJ6kVAOSxWQlJSEL774AtWrVy/XelUa0xQREYF169bh2rVr6NmzJzZu3IiePXuKfZqOjo5Yv369wlQARERERJXB29sbp0+fLpc7/V+kUtIUGRmJYcOGYejQobC2ti6xjIWFBdasWaNWcERERPQiyf8WdfZ/+/Xq1QuTJk3C5cuX0aRJE+jq6ipsf//991WqV62B4G8rDgQnIiJlVeZAcLvIGWoPBL/72Yy3/vvt5TmgXiSRSFR+lIpKY5rWrVuH7du3F1u/fft2hUeaEBEREVU2uVxe6qLOs+dUSprCw8NRq1atYustLCzKfSIpIiIi+h8OBNcolcY0JSYmwtHRsdh6e3t7hWfFERERUTkSJM8XdfavIrKzs3H48GEkJiYiPz9fYdsXX3yhUp0qJU0WFhY4f/58sbvjzp07h3feeUelQIiIiIjKw9mzZ9GzZ0/k5OQgOzsb5ubmePjwIapXrw4LCwuVkyaVuucGDRqEL774AgcPHoRMJoNMJsPff/+NsWPHik8sJiIiovIlCOovVcH48ePh6+uLJ0+ewNDQEP/88w/u3LkDDw8PLFy4UOV6VWppmj17Nm7fvo1u3bqhWrXnVcjlcgQEBHBMExERUUVRd1xSFUma4uLisHLlSujo6EAqlSIvLw9OTk5YsGABAgMD0a9fP5XqVSlp0tPTw7Zt2zB79mycO3cOhoaGaNKkCezt7VUKgoiIiKi86OrqitMOWFhYIDExEQ0bNoSZmRnu3r2rcr0qJU1F6tevj/r166tTBRERESmLA8GV4u7ujn///Rf16tVDp06dMG3aNDx8+BCbNm2Cq6uryvWqlDTJZDKsX78eMTExSEtLg1wuV9j+999/qxwQERERlUwiPF/U2b8qmDdvHjIzMwEAc+fORUBAAD777DPUq1dPraeVqJQ0jR07FuvXr0evXr3g6uoKiaRqZK5EREQaxTFNSmnRooX4fwsLC0RHR5dLvSolTVu3bsXPP/+Mnj17lksQREREROWla9eu2LVrF2rUqKGwPiMjA35+fir3iKk8EPzdd99V6YBERESkIo5pUsqhQ4eKTWgJALm5uTh69KjK9aqUNE2YMAFLlizBsmXL2DVHRERUWdg9V6bz58+L/798+TJSUlLE1zKZDNHR0bC1tVW5fpWSpmPHjuHgwYP4448/0LhxY+jq6ips37Vrl8oBEREREamiWbNmkEgkkEgk6Nq1a7HthoaGWLp0qcr1q5Q01ahRA3379lX5oERERKQCtjSVKSEhAYIgwMnJCbGxsahdu7a4TU9PDxYWFpBKpSrXr1LStG7dOpUPSERERCpi0lSmokm2Dx48iGbNmolPLSkik8lw5MgRdOzYUaX6VXr2HAAUFhbir7/+wsqVK8W5EO7fv4+srCxVqyQiIiJSW9euXfH48eNi658+fYouXbqoXK9KLU137txBjx49kJiYiLy8PLz33nswMTHB/PnzkZeXhxUrVqgcEBEREZWCd88pRRCEEm9Ue/ToEYyMjFSuV+XJLVu0aIFz587hnXfeEdf37dsXwcHBKgdDREREpeOM4GUrehCvRCLB0KFDoa+vL26TyWQ4f/482rZtq3L9KiVNR48exYkTJ6Cnp6ew3sHBAUlJSSoHQ0RERKQqMzMzAM9bmkxMTGBoaChu09PTQ+vWrdVq3FEpaZLL5ZDJZMXW37t3DyYmJioHQ0RERGXgQPAyFd2o5uDggIkTJ6rVFVcSlQaCd+/eHYsXLxZfSyQSZGVlYfr06Xy0ChEREWnU9OnTyz1hAlRsaVq0aBG8vb3RqFEj5ObmYvDgwYiPj0etWrXw008/lXeMREREBEACNcc0lVskb57mzZsjJiYGNWvWhLu7e5lPLPnvv/9UOoZKSVOdOnVw7tw5bN26FefPn0dWVhaGDx+OIUOGKPQfvsqRI0fw7bff4syZM0hOTsbu3bvh5+dX5j5RUVFYsGAB4uPjYWZmBh8fH3z77bcKA9IXL16MyMhIJCYmolatWvjggw8QHh4OAwMDVU6XiIiI3nB9+vQRB36/KpdQlUpJEwBUq1YNH330kVoHz87OhpubG4YNGyaOeC/L8ePHERAQgO+++w6+vr5ISkrCyJEjERwcLD66ZcuWLZg8eTLWrl2Ltm3b4vr16xg6dCgkEgkiIiLUipeIiEijOOVAqaZPn17i/8uTSknTxo0by9weEBCgVD0+Pj7w8fFR+rgnT56Eg4MDvvjiCwCAo6MjRowYgfnz54tlTpw4gXbt2mHw4MEAng8GGzRoEE6dOqX0cYiIiN5IHAj+2rKysiCXyxXWmZqaqlSXyvM0vaigoAA5OTnQ09ND9erVlU6aXlebNm3w9ddfY9++ffDx8UFaWhp27NihMPi8bdu22Lx5M2JjY9GqVSvcunUL+/btw8cff1xqvXl5ecjLyxNfZ2RkVEj8REREVPESEhIwZswYHDp0CLm5ueL6okkvS5oBQBkqJU1Pnjwpti4+Ph6fffYZJk2apFIgymjXrh2ioqLg7++P3NxcFBYWwtfXF8uXLxfLDB48GA8fPkT79u0hCAIKCwsxcuRIfP3116XWGx4ejpkzZ1ZY3EREROWCLU1K+eijjyAIAtauXQtLS8syB4W/DokgCOX2Fp4+fRofffQRrl69+vqBSCSvHAh++fJleHl5Yfz48fD29kZycjImTZqEli1bYs2aNQCAQ4cOYeDAgZgzZw48PT1x48YNjB07FsHBwQgLCyux3pJamuzs7JCenq5yEx4REVUNGRkZMDMzq9DvjKJjOMydCx01bmqS5+bi9pQpb/33m7GxMc6cOYMGDRqUa70qDwQvsbJq1XD//v3yrFJBeHg42rVrJ7ZmNW3aFEZGRujQoQPmzJkDa2trhIWF4eOPP8Ynn3wCAGjSpAmys7Px6aefYsqUKdDRKT41lb6+vsJU60RERKS9WrZsibt3774ZSdPevXsVXguCgOTkZCxbtgzt2rUrl8BKkpOTg2rVFEOWSqViDEVlXk6MXi5DRESkldg9p5TVq1dj5MiRSEpKgqurK3R1dRW2N23aVKV6VUqaXu5Ck0gkqF27Nrp27YpFixYpXU9WVhZu3Lghvk5ISEBcXBzMzc1Rt25dhIaGIikpSbxbz9fXF8HBwYiMjBS758aNG4dWrVrBxsZGLBMREQF3d3exey4sLAy+vr5i8kRERKSVmDQp5cGDB7h58yaCgoLEdRKJRDMDwV++dU9Vp0+fRpcuXcTXISEhAIDAwECsX78eycnJSExMFLcPHToUmZmZWLZsGSZMmIAaNWqga9euClMOTJ06FRKJBFOnTkVSUhJq164NX19fzJ07t1xiJiIiojfbsGHD4O7ujp9++unNHQj+tqiMQX1ERPR2qMyB4I6z1B8InjDt7R8IbmRkhHPnzuHdd98t13pVamkqahFSBmfhJiIiKiecEVwpXbt2fXOSprNnz+Ls2bMoKCgQR6Zfv34dUqkUzZs3F8uVV3MYERERgWOalOTr64vx48fjwoULaNKkSbGB4O+//75K9aqUNPn6+sLExAQbNmxAzZo1ATyf8DIoKAgdOnTAhAkTVAqGiIiISF0jR44EAMyaNavYtkofCL5o0SL8+eefYsIEADVr1sScOXPQvXt3Jk1EREQVQCI8X9TZvyoorxvWXlZ8pkclZGRk4MGDB8XWP3jwAJmZmWoHRURERCUQymGpop4+fap2HSolTX379kVQUBB27dqFe/fu4d69e9i5cyeGDx+Ofv36qR0UERERkarmz5+Pbdu2ia8//PBDmJubw9bWFufOnVO5XpWSphUrVsDHxweDBw+Gvb097O3tMXjwYPTo0QM//PCDysEQERFRGYT/76JTZakqLU0rVqyAnZ0dAODAgQP466+/EB0dDR8fH/FRbKpQaUxT9erV8cMPP+Dbb7/FzZs3AQDOzs4wMjJSORAiIiJ6Bd49p5SUlBQxafrtt98wYMAAdO/eHQ4ODvD09FS5XpVamookJycjOTkZ9erVg5GREZ/tRkRvhfyCQuw/fQ1LfzmGH/f9g2v3io/hJKI3V82aNXH37l0AQHR0NLy8vAA8fwatqnfOASq2ND169AgDBgzAwYMHIZFIEB8fDycnJwwfPhw1a9Z8refPERG9SU5dTcTkNb/jaXYuqkl1IAgCIn87iTaN7DF/WE+YVFd9NmYitbGlSSn9+vXD4MGDUa9ePTx69Ag+Pj4Ans8zqc6Elyq1NI0fPx66urpITExE9erVxfX+/v6Ijo5WORgiIk26djcNny/fjfScXABAoUwOmfz5t0zs1USMjdzLFnXSKHXGM6k7XYE2+e677zBmzBg0atQIBw4cgLGxMYDnPWSjRo1SuV6VWpr+/PNP7N+/H3Xq1FFYX69ePdy5c0flYIiINGntn/9CLggoKS+SyQWcvZmEM/FJaFG/TvECRPTG0NXVxcSJE4utHz9+vFr1qpQ0ZWdnK7QwFXn8+DH09fXVCoiISBMKZXLEnI0XW5ZKItXRwZ9nrjFpItIC8fHxOHjwINLS0opNdjlt2jSV6lQpaerQoQM2btyI2bNnA3g+JblcLseCBQvQpUsXlQIhItKk/ILCMhMm4Pkg0qzc/EqKiKgEHNOklFWrVuGzzz5DrVq1YGVlpfAsXIlEUrlJ04IFC9CtWzecPn0a+fn5+PLLL3Hp0iU8fvwYx48fVykQIiJNMtTXRU1jQzzJelZmOXuLGpUTEFEJ+BgV5cyZMwdz587FV199Va71qjQQ3NXVFdevX0f79u3Rp08fZGdno1+/fjh79iycnZ3LNUAiosogkUjwYcem0HnhL9KXCRDQp41rJUZFRKp48uQJPvzww3Kv97VbmgoKCtCjRw+sWLECU6ZMKfeAiIg05eNuHvg77iZupTyC/IWuOokEEARgrF8HWJmbaDBCIlSZLjZ1fPjhh/jzzz8xcuTIcq33tZMmXV1dnD9/vlyDICJ6Exgb6mPthAGI/PUE9py4hGf5BQAAB0tzBPt4wqeli4YjpCqPY5qU8u677yIsLAz//PMPmjRpAl1dXYXtX3zxhUr1SgQVJh0ZP3489PX18c0336h00DddRkYGzMzMkJ6eDlNTU02HQ0Qa8Cy/AMmPMqCvWw0275gqDCQlelFlfGcUHePdr+ZBqq/6BKuyvFzcmP/1W//95ujoWOo2iUSCW7duqVSvSmOaCgsLERkZiRYtWmDEiBEICQlRWIiItJ2hni6crN+BbS0zJkz0xtDU5JbLly+Hg4MDDAwM4OnpidjY2FLLFhQUYNasWXB2doaBgQHc3NyKTXwtk8kQFhYGR0dHGBoawtnZGbNnz1aYPDYrKwtjxoxBnTp1YGhoiEaNGmHFihVKxZuQkFDqomrCBLxm99ytW7fg4OCAixcvonnz5gCA69evK5ThLxciIqIKooHuuW3btiEkJAQrVqyAp6cnFi9eDG9vb1y7dg0WFhbFyk+dOhWbN2/GqlWr4OLigv3796Nv3744ceIE3N3dAQDz589HZGQkNmzYgMaNG+P06dMICgqCmZmZ2HUWEhKCv//+G5s3b4aDgwP+/PNPjBo1CjY2Nnj//ffVeBNU91rdc1KpFMnJyeKb5O/vj++//x6WlpYVFqAmsHuOiIiUVZndc/Umqd89F//t63XPeXp6omXLlli2bBkAQC6Xw87ODp9//jkmT55crLyNjQ2mTJmC0aNHi+v69+8PQ0NDbN68GQDQu3dvWFpaYs2aNaWWcXV1hb+/P8LCwsQyHh4e8PHxwZw5c14Z971797B3714kJiYiP19xfrWIiAilzv1lr9XS9HJ+9ccffyA7O1ulAxMREdHrKa95mjIyMhTW6+vrl/hEj/z8fJw5cwahoaHiOh0dHXh5eeHkyZMlHiMvLw8GBoqJnaGhIY4dOya+btu2LX788Udcv34d9evXx7lz53Ds2DGFZKZt27bYu3cvhg0bBhsbGxw6dAjXr1/Hd99998rzjImJwfvvvw8nJydcvXoVrq6uuH37NgRBEHvKVKHSmKYifHAlERFRJRLKYQFgZ2cHMzMzcQkPDy/xcA8fPoRMJivWo2RpaYmUlJQS9/H29kZERATi4+Mhl8tx4MAB7Nq1C8nJyWKZyZMnY+DAgXBxcYGuri7c3d0xbtw4DBkyRCyzdOlSNGrUCHXq1IGenh569OiB5cuXo2PHjq98m0JDQzFx4kRcuHABBgYG2LlzJ+7evYtOnTqpNX/Ta7U0SSSSYmOWOIaJiIhIu9y9e1ehe648nxu7ZMkSBAcHw8XFBRKJBM7OzggKCsLatWvFMj///DOioqKwZcsWNG7cGHFxcRg3bhxsbGwQGBgI4HnS9M8//2Dv3r2wt7fHkSNHMHr0aNjY2MDLy6vMGK5cuYKffvoJAFCtWjU8e/YMxsbGmDVrFvr06YPPPvtMpXN77e65oUOHim9ubm4uRo4cCSMjI4Vyu3btUikYIiIiKkM5DQQ3NTVVakxTrVq1IJVKkZqaqrA+NTUVVlZWJe5Tu3Zt7NmzB7m5uXj06BFsbGwwefJkODk5iWUmTZoktjYBQJMmTXDnzh2Eh4cjMDAQz549w9dff43du3ejV69eAICmTZsiLi4OCxcufGXSZGRkJI5jsra2xs2bN9G4cWMAz1vPVPVaSVNR9lfko48+UvnARERE9Hoq+9lzenp68PDwQExMDPz8/AA8HwgeExODMWPGlLmvgYEBbG1tUVBQgJ07d2LAgAHitpycHOjoKI4QkkqlkMvlAJ5PW1BQUFBmmbK0bt0ax44dQ8OGDdGzZ09MmDABFy5cwK5du9C6dWtlTr1Er5U0rVu3TuUDERERkZo0MOVASEgIAgMD0aJFC7Rq1QqLFy9GdnY2goKCAAABAQGwtbUVx0WdOnUKSUlJaNasGZKSkjBjxgzI5XJ8+eWXYp2+vr6YO3cu6tati8aNG+Ps2bOIiIjAsGHDADxvCevUqRMmTZoEQ0ND2Nvb4/Dhw9i4caNSd75FREQgKysLADBz5kxkZWVh27ZtqFevnsp3zgEqPEaFiIiIqg5/f388ePAA06ZNQ0pKCpo1a4bo6GhxcHhiYqJCi1Bubi6mTp2KW7duwdjYGD179sSmTZtQo0YNsczSpUsRFhaGUaNGIS0tDTY2NhgxYgSmTZsmltm6dStCQ0MxZMgQPH78GPb29pg7d+4rnycnk8lw7949NG3aFMDzrjplJ8V8FZUeo/K24zxNRESkrMqcp6nBWPXnabq25O1/jIqBgQGuXLlS5uNUVKHWlAPqOnLkCHx9fWFjYwOJRII9e/a8cp+oqCi4ubmhevXqsLa2xrBhw/Do0SOFMk+fPsXo0aNhbW0NfX191K9fH/v27augsyAiIqocmnqMirZxdXVV63EppdFo0pSdnQ03NzcsX75cqfLHjx9HQEAAhg8fjkuXLmH79u2IjY1FcHCwWCY/Px/vvfcebt++jR07duDatWtYtWoVbG1tK+o0iIiI6A0yZ84cTJw4Eb/99huSk5ORkZGhsKhKo2OafHx84OPjo3T5kydPwsHBQXwujaOjI0aMGIH58+eLZdauXYvHjx/jxIkT0NXVBQA4ODiUa9xEREQaoYGB4Npk1qxZmDBhAnr27AkAeP/99xXmkxQEARKJBDKZTKX6tWogeJs2bfD1119j37598PHxQVpaGnbs2CG+OQCwd+9etGnTBqNHj8Yvv/yC2rVrY/Dgwfjqq68glUpLrDcvLw95eXnia3WyUCIioopS2VMOaJuZM2di5MiROHjwYIXUr1VJU7t27RAVFQV/f3/k5uaisLAQvr6+Ct17t27dwt9//40hQ4Zg3759uHHjBkaNGoWCggJMnz69xHrDw8Mxc+bMyjoNIiIiqgBF97Z16tSpQurX6Jim13X58mWMHTsW06ZNw5kzZxAdHY3bt28r3H4ol8thYWGBH3/8ER4eHvD398eUKVPKvN0wNDQU6enp4nL37t3KOB0iIqLXU07PnnubVeTj3bSqpSk8PBzt2rXDpEmTADyfUt3IyAgdOnTAnDlzYG1tDWtra+jq6ip0xTVs2BApKSnIz8+Hnp5esXpLe7ozERHRG4Vjml6pfv36r0ycHj9+rFLdWpU05eTkoFo1xZCLkqOiJrl27dphy5YtkMvl4mRb169fh7W1dYkJExEREb09Zs6cCTMzswqpW6NJU1ZWFm7cuCG+TkhIQFxcHMzNzVG3bl2EhoYiKSkJGzduBPB82vXg4GBERkbC29sbycnJGDduHFq1agUbGxsAwGeffYZly5Zh7Nix+PzzzxEfH4958+aJd9wRERFpK8n/FnX2f9sNHDgQFhYWFVK3RpOm06dPo0uXLuLrkJAQAM8fDLx+/XokJycjMTFR3D506FBkZmZi2bJlmDBhAmrUqIGuXbsqTDlgZ2eH/fv3Y/z48WjatClsbW0xduxYfPXVV5V3YkRERBWB3XNlqsjxTAAfo1IiPkaFiIiUVZmPUWk8Uv3HqFxa8fY+RkVHRwcpKSlvZ0sTERERUXmRy+UVWj+TJiIiIm3B7jmNYtJERESkTZj4aIxWTW5JREREpClsaSIiItISfPacZjFpIiIi0hYc06RR7J4jIiIiUgJbmoiIiLQEu+c0i0kTERGRtmD3nEaxe46IiIhICWxpIiIi0hLsntMsJk1ERETagt1zGsWkiYiISFswadIojmkiIiIiUgJbmoiIiLQExzRpFpMmIiIibcHuOY1i9xwRERGREtjSREREpCUkggCJoHpzkTr7EpMmIiIi7cHuOY1i9xwRERGREtjSREREpCV495xmMWkiIiLSFuye0yh2zxEREREpgS1NREREWoLdc5rFpImIiEhbsHtOo5g0ERERaQm2NGkWxzQRERERKYEtTURERNqC3XMaxaSJiF7pxtkE/P7jAdy9dh/GNY3QeUBbtOvbCrp6upoOjajKYReb5jBpIqJSCYKAHydtwo6IXyGtpgNZoRw6OhIc3x0L+8Z2WHAgDOZWNTUdJhFRpeCYJiIq1W8rD2BHxK8AAFmhHAAglz//M/futSTM6LcQAh8ASlR5BEH9hVSm0aTpyJEj8PX1hY2NDSQSCfbs2fPKfaKiouDm5obq1avD2toaw4YNw6NHj0osu3XrVkgkEvj5+ZVv4ERVgFwux7YFe0rfXijHlX+u49q/NyovKKIqrujuOXUWUp1Gk6bs7Gy4ublh+fLlSpU/fvw4AgICMHz4cFy6dAnbt29HbGwsgoODi5W9ffs2Jk6ciA4dOpR32ERVQvKtVKTeflBmGWk1Hfz7R1zlBEREpGEaHdPk4+MDHx8fpcufPHkSDg4O+OKLLwAAjo6OGDFiBObPn69QTiaTYciQIZg5cyaOHj2Kp0+flmfYRFVCYYHs1YUkEhQWFFZ8MET0HO+e0yitGtPUpk0b3L17F/v27YMgCEhNTcWOHTvQs2dPhXKzZs2ChYUFhg8frlS9eXl5yMjIUFiIqjprJ0sYmVUvs4ysQIYGrd6tpIiISCJXfyHVaVXS1K5dO0RFRcHf3x96enqwsrKCmZmZQvfesWPHsGbNGqxatUrpesPDw2FmZiYudnZ2FRE+kVbR09dF7xHvQUdHUuJ2HakOatV5B569mldyZEREmqFVSdPly5cxduxYTJs2DWfOnEF0dDRu376NkSNHAgAyMzPx8ccfY9WqVahVq5bS9YaGhiI9PV1c7t69W1GnQKRVPp7+IRq3c4FEAkheyJ10qulAv7oeZuyaBKlUqrkAiaoaoRwWUplWzdMUHh6Odu3aYdKkSQCApk2bwsjICB06dMCcOXOQmpqK27dvw9fXV9xHLn/eFlmtWjVcu3YNzs7OxerV19eHvr5+5ZwEkRbRN9THN3+GIXrN39gbGY37N1NhaGyAboM7oN+4XrBysNB0iERVCp89p1lalTTl5OSgWjXFkIv+yhUEAS4uLrhw4YLC9qlTpyIzMxNLlixhtxuRCvT0dfH+KG+8P8pb06EQkbpzLXGeJrVoNGnKysrCjRv/P8dLQkIC4uLiYG5ujrp16yI0NBRJSUnYuHEjAMDX1xfBwcGIjIyEt7c3kpOTMW7cOLRq1Qo2NjYAAFdXV4Vj1KhRo8T1RERERK9Do0nT6dOn0aVLF/F1SEgIACAwMBDr169HcnIyEhMTxe1Dhw5FZmYmli1bhgkTJqBGjRro2rVrsSkHiIiI3kbsntMsicBnIBSTkZEBMzMzpKenw9TUVNPhEBHRG6wyvjOKjuHZezaq6RqoXE9hQS5O/RbG7zcVadXdc0RERESaolUDwYmIiKoyds9pFpMmIiIibcG75zSK3XNERERESmBLExERkZZg95xmsaWJiIhIW2joMSrLly+Hg4MDDAwM4OnpidjY2FLLFhQUYNasWXB2doaBgQHc3NwQHR2tUEYmkyEsLAyOjo4wNDSEs7MzZs+ejRdv6JdIJCUu3377rWonUQ6YNBEREVGptm3bhpCQEEyfPh3//fcf3Nzc4O3tjbS0tBLLT506FStXrsTSpUtx+fJljBw5En379sXZs2fFMvPnz0dkZCSWLVuGK1euYP78+ViwYAGWLl0qlklOTlZY1q5dC4lEgv79+1f4OZeG8zSVgPM0ERGRsipznqa23rPUnqfpxP5prxWrp6cnWrZsiWXLlgF4/kxXOzs7fP7555g8eXKx8jY2NpgyZQpGjx4truvfvz8MDQ2xefNmAEDv3r1haWmJNWvWlFrmZX5+fsjMzERMTIzS51ve2NJERESkLeSC+gueJ2EvLnl5eSUeLj8/H2fOnIGXl5e4TkdHB15eXjh58mSJ++Tl5cHAQDGxMzQ0xLFjx8TXbdu2RUxMDK5fvw4AOHfuHI4dOwYfH58S60xNTcXvv/+O4cOHK/9eVQAmTURERNqinMY02dnZwczMTFzCw8NLPNzDhw8hk8lgaWmpsN7S0hIpKSkl7uPt7Y2IiAjEx8dDLpfjwIED2LVrF5KTk8UykydPxsCBA+Hi4gJdXV24u7tj3LhxGDJkSIl1btiwASYmJujXr58Sb1LF4d1zREREVczdu3cVuuf09fXLre4lS5YgODgYLi4ukEgkcHZ2RlBQENauXSuW+fnnnxEVFYUtW7agcePGiIuLw7hx42BjY4PAwMBida5duxZDhgwp1oJV2Zg0ERERaQkJ1Jxy4H//mpqaKjWmqVatWpBKpUhNTVVYn5qaCisrqxL3qV27Nvbs2YPc3Fw8evQINjY2mDx5MpycnMQykyZNElubAKBJkya4c+cOwsPDiyVNR48exbVr17Bt27bXONOKwe45IiIibVE0I7g6y2vQ09ODh4eHwuBruVyOmJgYtGnTpsx9DQwMYGtri8LCQuzcuRN9+vQRt+Xk5EBHRzEFkUqlkMvlxepZs2YNPDw84Obm9lqxVwS2NBEREVGpQkJCEBgYiBYtWqBVq1ZYvHgxsrOzERQUBAAICAiAra2tOC7q1KlTSEpKQrNmzZCUlIQZM2ZALpfjyy+/FOv09fXF3LlzUbduXTRu3Bhnz55FREQEhg0bpnDsjIwMbN++HYsWLaq8Ey4DkyYiIiItoYkZwf39/fHgwQNMmzYNKSkpaNasGaKjo8XB4YmJiQqtRrm5uZg6dSpu3boFY2Nj9OzZE5s2bUKNGjXEMkuXLkVYWBhGjRqFtLQ02NjYYMSIEZg2bZrCsbdu3QpBEDBo0CCVzre8cZ6mEnCeJiIiUlZlztPUvssMVKumxjxNhbk4dnAGv99UxDFNREREREpg9xwREZGWkAgCJGp0EKmzLzFpIiIi0h7y/y3q7E8qY/ccERERkRLY0kRERKQl2D2nWUyaiIiItMULz49TeX9SGZMmIiIibaHCrN7F9ieVcUwTERERkRLY0kRERKQlNDEjOP0/Jk1ERETagt1zGsXuOSIiIiIlsKWJiIhIS0jkzxd19ifVMWkiIiLSFuye0yh2zxEREREpgS1NRERE2oKTW2qURluajhw5Al9fX9jY2EAikWDPnj2v3CcqKgpubm6oXr06rK2tMWzYMDx69EjcvmrVKnTo0AE1a9ZEzZo14eXlhdjY2Ao8CyIiospR9BgVdRZSnUaTpuzsbLi5uWH58uVKlT9+/DgCAgIwfPhwXLp0Cdu3b0dsbCyCg4PFMocOHcKgQYNw8OBBnDx5EnZ2dujevTuSkpIq6jSIiIioCtBo95yPjw98fHyULn/y5Ek4ODjgiy++AAA4OjpixIgRmD9/vlgmKipKYZ/Vq1dj586diImJQUBAQPkETkREpAkcCK5RWjUQvE2bNrh79y727dsHQRCQmpqKHTt2oGfPnqXuk5OTg4KCApibm5daJi8vDxkZGQoLUVmePsjAnh/+xI+hP+HniN+Rdu/Rq3ciIlKXAECuxsKcSS1aNRC8Xbt2iIqKgr+/P3Jzc1FYWAhfX98yu/e++uor2NjYwMvLq9Qy4eHhmDlzZkWETG8ZQRDwc8Tv2DBrJ+RyOaRSHchlcqyd9jP8RnfHp+GDoKOjVX+LEJEWUXdcEsc0qUerfrtfvnwZY8eOxbRp03DmzBlER0fj9u3bGDlyZInlv/nmG2zduhW7d++GgYFBqfWGhoYiPT1dXO7evVtRp0Babt/ag1g77WfICmUQ5AIKC2SQywUIgoDdy/dj4+xdmg6RiIgqiFa1NIWHh6Ndu3aYNGkSAKBp06YwMjJChw4dMGfOHFhbW4tlFy5ciG+++QZ//fUXmjZtWma9+vr60NfXr9DYSfvJCmXYOKeMpEgAdiz5Ax+O6wkjs+qVFxgRVR0C1BzTVG6RVEla1dKUk5NTrOtDKpUCeN5tUmTBggWYPXs2oqOj0aJFi0qNkd5eV2Jv4Gla2ePdCvIKELv/XCVFRERVTtFAcHUWUplGW5qysrJw48YN8XVCQgLi4uJgbm6OunXrIjQ0FElJSdi4cSMAwNfXF8HBwYiMjIS3tzeSk5Mxbtw4tGrVCjY2NgCA+fPnY9q0adiyZQscHByQkpICADA2NoaxsXHlnyS9NXIycpUrl/msgiMhIiJN0GhL0+nTp+Hu7g53d3cAQEhICNzd3TFt2jQAQHJyMhITE8XyQ4cORUREBJYtWwZXV1d8+OGHaNCgAXbt+v8uk8jISOTn5+ODDz6AtbW1uCxcuLByT47eOrb1rJQqV6ee9asLERGpQp0754oWUplEENhW97KMjAyYmZkhPT0dpqammg6H3iCTeszDxRPXIZcV/80j0ZHA0r4W1l9YCIlEooHoiEgTKuM7o+gY3Vy/RDWp6mNwC2V5iLm4gN9vKtKqMU1Emjbmu0AYGulDR6r4o6Mj1UE1XSkmrvyUCRMR0VuKSRPRa7BvaIvvj8xAB7+WkBYlThLAw6sJvosJQ5N2DTQaHxG95TgQXKO0asoBojdBnXrW+HrjaGQ9zcaTtAyYvWMM03dMNB0WEVUFfIyKRjFpIlKRcQ0jGNcw0nQYRERUSZg0ERERaQu2NGkUkyYiIiJtIQegzr0mnHJALUyaiIiItAQf2KtZvHuOiIiISAlsaSIiItIWHNOkUUyaiIiItIVcACRqJD5yJk3qYPccERERkRLY0kRERKQt2D2nUUyaiIiItIa6j0Jh0qQOds8RERERKYEtTURERNqC3XMaxaSJiIhIW8gFqNXFxrvn1MLuOSIiIiIlsKWJiIhIWwjy54s6+5PKmDQRERFpC45p0igmTURERNqCY5o0imOaiIiIiJTAliYiIiJtwe45jWLSVMEEQYBEItF0GERE9DYQoGbSVG6RVElMmirA3Zw0bE/8G4cenEWuLB9WBu/A17Yd3rdpB32pnqbDIyIiIhUwaSpnF5/ewuTzK1AoyCD7362dybmPsOrmrziSFocFzUbBUKqv4SiJiEgrsXtOozgQvBwVymWYeWkd8uWFYsJURICA65l3sfn2fg1FR0REWk8uV38hlTFpKkcnHl7A04IsCKV0Gssh4Lf7J5EvK6jkyIiIiEhdTJrKUXzWPUgl0jLL5MhykZr3pJIiIiKit0pR95w6C6mMY5rKUTWJFMrcmqArebve9ie5z7D54jlsv3IRj3OfwdrIBIMbN8XARk1gqKur6fCIiN4eHNOkUWxpKket32lcbCzTy+oY1oalQc1Kiqji3cvIQM+tG/Fd7AkkZqQjKz8fN548wqxjB9F/109Iz8vVdIhERETlQqNJ05EjR+Dr6wsbGxtIJBLs2bPnlftERUXBzc0N1atXh7W1NYYNG4ZHjx4plNm+fTtcXFxgYGCAJk2aYN++fRV0BooamNaFq5kTdMp4WwfW9Xqr5m0ae+B3pOVkQ/7CXy9Fk/xfe/QQs44e1FhsRERvHbmg/kIq02jSlJ2dDTc3Nyxfvlyp8sePH0dAQACGDx+OS5cuYfv27YiNjUVwcLBY5sSJExg0aBCGDx+Os2fPws/PD35+frh48WJFnYaC6Y2D4GRsDQCQ/u/tLUqiPrLvju5WLSsljspw5eEDnEm5D1kpzb0yQcAv8Vfx+FlOJUdGRPR2EgS52gupTqNJk4+PD+bMmYO+ffsqVf7kyZNwcHDAF198AUdHR7Rv3x4jRoxAbGysWGbJkiXo0aMHJk2ahIYNG2L27Nlo3rw5li1bVlGnoaCGnjGWeYRglutwdLZwR+t3GqNfnY5Y2yoUgY4+b1Ur038p919ZplAux6WHaZUQDRFRFSCo2cqk4pim5cuXw8HBAQYGBvD09FT43n1ZQUEBZs2aBWdnZxgYGMDNzQ3R0dEKZWQyGcLCwuDo6AhDQ0M4Oztj9uzZEF6K78qVK3j//fdhZmYGIyMjtGzZEomJiSqdQ3nQqhHJbdq0wddff419+/bBx8cHaWlp2LFjB3r27CmWOXnyJEJCQhT28/b2LrPrLy8vD3l5eeLrjIwMteKUSnTQppYr2tRyVaueN51UR7kEUCrh0DkiIm21bds2hISEYMWKFfD09MTixYvh7e2Na9euwcLColj5qVOnYvPmzVi1ahVcXFywf/9+9O3bFydOnIC7uzsAYP78+YiMjMSGDRvQuHFjnD59GkFBQTAzM8MXX3wBALh58ybat2+P4cOHY+bMmTA1NcWlS5dgYGBQqef/Iq36NmvXrh2ioqLg7+8PPT09WFlZwczMTKF7LyUlBZaWlgr7WVpaIiUlpdR6w8PDYWZmJi52dnYVdg5vk3Z17PGqtMmwmi7cLKwqJR4ioreeBqYciIiIQHBwMIKCgtCoUSOsWLEC1atXx9q1a0ssv2nTJnz99dfo2bMnnJyc8Nlnn6Fnz55YtGiRWObEiRPo06cPevXqBQcHB3zwwQfo3r27QgvWlClT0LNnTyxYsADu7u5wdnbG+++/X2KiVlm0Kmm6fPkyxo4di2nTpuHMmTOIjo7G7du3MXLkSLXqDQ0NRXp6urjcvXu3nCJ+u9mZmqG707uQltLlKAEQ0MQNRnp83h4RUbkopxnBMzIyFJYXe1telJ+fjzNnzsDLy0tcp6OjAy8vL5w8ebLEffLy8oq1BhkaGuLYsWPi67Zt2yImJgbXr18HAJw7dw7Hjh2Dj4/P/05Tjt9//x3169eHt7c3LCws4OnpqdQNYxVJq5Km8PBwtGvXDpMmTULTpk3h7e2NH374AWvXrkVycjIAwMrKCqmpqQr7paamwsqq9NYOfX19mJqaKiyknG+79kATi+ctezr/S56Kkqj3HN/FBM/2GouNiIhKZmdnp9DDEh4eXmK5hw8fQiaTvVYPjre3NyIiIhAfHw+5XI4DBw5g165d4vc0AEyePBkDBw6Ei4sLdHV14e7ujnHjxmHIkCEAgLS0NGRlZeGbb75Bjx498Oeff6Jv377o168fDh8+XE7vwuvTqjFNOTk5qFZNMWSp9PkM3EWDx9q0aYOYmBiMGzdOLHPgwAG0adOm0uKsSkz19bG970D8dfsmdl69hAc5ObAzNYN/I1e0q2MvJlJERFQOhKJJXdTZH7h7965CA4G+fvk9SH7JkiUIDg6Gi4sLJBIJnJ2dERQUpNCd9/PPPyMqKgpbtmxB48aNERcXh3HjxsHGxgaBgYGQ/69FrE+fPhg/fjwAoFmzZjhx4gRWrFiBTp06lVu8r0OjSVNWVhZu3Lghvk5ISEBcXBzMzc1Rt25dhIaGIikpCRs3bgQA+Pr6Ijg4GJGRkfD29kZycjLGjRuHVq1awcbGBgAwduxYdOrUCYsWLUKvXr2wdetWnD59Gj/++KNGzrEq0JVK4eNcHz7O9TUdChHRW02QyyFIVJ82oGjKAWV7VWrVqgWpVPpaPTi1a9fGnj17kJubi0ePHsHGxgaTJ0+Gk5OTWGbSpEliaxMANGnSBHfu3EF4eDgCAwNRq1YtVKtWDY0aNVKou2HDhgrdfJVNo91zp0+fhru7uziaPiQkBO7u7pg2bRoAIDk5WeHWwqFDhyIiIgLLli2Dq6srPvzwQzRo0AC7du0Sy7Rt2xZbtmzBjz/+CDc3N+zYsQN79uyBq+vbfScbERFRedPT04OHhwdiYmLEdXK5HDExMa/swTEwMICtrS0KCwuxc+dO9OnTR9yWk5MDHR3FFEQqlYotTHp6emjZsiWuXbumUOb69euwt7dX97RUptGWps6dOxebk+FF69evL7bu888/x+eff15mvR9++CE+/PBDdcMjIiJ6s5RT99zrCAkJQWBgIFq0aIFWrVph8eLFyM7ORlBQEAAgICAAtra24rioU6dOISkpCc2aNUNSUhJmzJgBuVyOL7/8UqzT19cXc+fORd26ddG4cWOcPXsWERERGDZsmFhm0qRJ8Pf3R8eOHdGlSxdER0fj119/xaFDh1Q/fzVp1ZgmIiKiKk0uAJLKTZr8/f3x4MEDTJs2DSkpKWjWrBmio6PFweGJiYkKrUa5ubmYOnUqbt26BWNjY/Ts2RObNm1CjRo1xDJLly5FWFgYRo0ahbS0NNjY2GDEiBFiTxMA9O3bFytWrEB4eDi++OILNGjQADt37kT79pq7wUgilNXUU0VlZGTAzMwM6enpvJOOiIjKVBnfGUXH6Ko/ANUkqk/jUijk4++8n/n9piK2NBEREWkLQQCgxvPj2E6iFiZNREREWkKQCxDU6J5j55J6mDQRERFpC0EO9Vqa1NiXtGtGcCIiIiJNYUsTERGRlmD3nGYxaSIiItIW7J7TKCZNJSjKxDMyMjQcCRERvemKvisqoxWnEAVqzW1ZiILyC6YKYtJUgszMTADPnwJNRESkjMzMTJiZmVVI3Xp6erCyssKxlH1q12VlZQU9PdXneqrKOLllCeRyOe7fvw8TExNIJBKV68nIyICdnV2xp0m/rara+QJV75x5vm83nq9qBEFAZmYmbGxsij1PrTzl5uYiPz9f7Xr09PRgYGBQDhFVPWxpKoGOjg7q1KlTbvUp+zTpt0VVO1+g6p0zz/ftxvN9fRXVwvQiAwMDJjsaxikHiIiIiJTApImIiIhICUyaKpC+vj6mT58OfX19TYdSKara+QJV75x5vm83ni9R2TgQnIiIiEgJbGkiIiIiUgKTJiIiIiIlMGkiIiIiUgKTJiIiIiIlMGmqQMuXL4eDgwMMDAzg6emJ2NhYTYdUIWbMmAGJRKKwuLi4aDqscnPkyBH4+vrCxsYGEokEe/bsUdguCAKmTZsGa2trGBoawsvLC/Hx8ZoJthy86nyHDh1a7Hr36NFDM8GWg/DwcLRs2RImJiawsLCAn58frl27plAmNzcXo0ePxjvvvANjY2P0798fqampGopYPcqcb+fOnYtd45EjR2ooYvVERkaiadOm4gSWbdq0wR9//CFuf5uuLVU8Jk0VZNu2bQgJCcH06dPx33//wc3NDd7e3khLS9N0aBWicePGSE5OFpdjx45pOqRyk52dDTc3NyxfvrzE7QsWLMD333+PFStW4NSpUzAyMoK3tzdyc3MrOdLy8arzBYAePXooXO+ffvqpEiMsX4cPH8bo0aPxzz//4MCBAygoKED37t2RnZ0tlhk/fjx+/fVXbN++HYcPH8b9+/fRr18/DUatOmXOFwCCg4MVrvGCBQs0FLF66tSpg2+++QZnzpzB6dOn0bVrV/Tp0weXLl0C8HZdW6oEAlWIVq1aCaNHjxZfy2QywcbGRggPD9dgVBVj+vTpgpubm6bDqBQAhN27d4uv5XK5YGVlJXz77bfiuqdPnwr6+vrCTz/9pIEIy9fL5ysIghAYGCj06dNHI/FUhrS0NAGAcPjwYUEQnl9PXV1dYfv27WKZK1euCACEkydPairMcvPy+QqCIHTq1EkYO3as5oKqYDVr1hRWr1791l9bKn9saaoA+fn5OHPmDLy8vMR1Ojo68PLywsmTJzUYWcWJj4+HjY0NnJycMGTIECQmJmo6pEqRkJCAlJQUhWttZmYGT0/Pt/ZaA8ChQ4dgYWGBBg0a4LPPPsOjR480HVK5SU9PBwCYm5sDAM6cOYOCggKFa+zi4oK6deu+Fdf45fMtEhUVhVq1asHV1RWhoaHIycnRRHjlSiaTYevWrcjOzkabNm3e+mtL5Y8P7K0ADx8+hEwmg6WlpcJ6S0tLXL16VUNRVRxPT0+sX78eDRo0QHJyMmbOnIkOHTrg4sWLMDEx0XR4FSolJQUASrzWRdveNj169EC/fv3g6OiImzdv4uuvv4aPjw9OnjwJqVSq6fDUIpfLMW7cOLRr1w6urq4Anl9jPT091KhRQ6Hs23CNSzpfABg8eDDs7e1hY2OD8+fP46uvvsK1a9ewa9cuDUarugsXLqBNmzbIzc2FsbExdu/ejUaNGiEuLu6tvbZUMZg0kdp8fHzE/zdt2hSenp6wt7fHzz//jOHDh2swMqoIAwcOFP/fpEkTNG3aFM7Ozjh06BC6deumwcjUN3r0aFy8ePGtGpNXltLO99NPPxX/36RJE1hbW6Nbt264efMmnJ2dKztMtTVo0ABxcXFIT0/Hjh07EBgYiMOHD2s6LNJC7J6rALVq1YJUKi12B0ZqaiqsrKw0FFXlqVGjBurXr48bN25oOpQKV3Q9q+q1BgAnJyfUqlVL66/3mDFj8Ntvv+HgwYOoU6eOuN7Kygr5+fl4+vSpQnltv8alnW9JPD09AUBrr7Genh7effddeHh4IDw8HG5ubliyZMlbe22p4jBpqgB6enrw8PBATEyMuE4ulyMmJgZt2rTRYGSVIysrCzdv3oS1tbWmQ6lwjo6OsLKyUrjWGRkZOHXqVJW41gBw7949PHr0SGuvtyAIGDNmDHbv3o2///4bjo6OCts9PDygq6urcI2vXbuGxMRErbzGrzrfksTFxQGA1l7jl8nlcuTl5b1115YqHrvnKkhISAgCAwPRokULtGrVCosXL0Z2djaCgoI0HVq5mzhxInx9fWFvb4/79+9j+vTpkEqlGDRokKZDKxdZWVkKf2EnJCQgLi4O5ubmqFu3LsaNG4c5c+agXr16cHR0RFhYGGxsbODn56e5oNVQ1vmam5tj5syZ6N+/P6ysrHDz5k18+eWXePfdd+Ht7a3BqFU3evRobNmyBb/88gtMTEzEsSxmZmYwNDSEmZkZhg8fjpCQEJibm8PU1BSff/452rRpg9atW2s4+tf3qvO9efMmtmzZgp49e+Kdd97B+fPnMX78eHTs2BFNmzbVcPSvLzQ0FD4+Pqhbty4yMzOxZcsWHDp0CPv373/rri1VAk3fvvc2W7p0qVC3bl1BT09PaNWqlfDPP/9oOqQK4e/vL1hbWwt6enqCra2t4O/vL9y4cUPTYZWbgwcPCgCKLYGBgYIgPJ92ICwsTLC0tBT09fWFbt26CdeuXdNs0Goo63xzcnKE7t27C7Vr1xZ0dXUFe3t7ITg4WEhJSdF02Cor6VwBCOvWrRPLPHv2TBg1apRQs2ZNoXr16kLfvn2F5ORkzQWthledb2JiotCxY0fB3Nxc0NfXF959911h0qRJQnp6umYDV9GwYcMEe3t7QU9PT6hdu7bQrVs34c8//xS3v03XliqeRBAEoTKTNCIiIiJtxDFNREREREpg0kRERESkBCZNREREREpg0kRERESkBCZNREREREpg0kRERESkBCZNREREREpg0kT0BpFIJNizZ0+p22/fvg2JRCI+1kITOnfujHHjxomvHRwcsHjxYo3F86IZM2agWbNmmg6DiN5STJqIKsmDBw/w2WefoW7dutDX14eVlRW8vb1x/PhxsUxycjJ8fHw0GGXFuXfvHvT09ODq6qrpUIiIVMJnzxFVkv79+yM/Px8bNmyAk5MTUlNTERMTg0ePHoll3uYnq69fvx4DBgzAkSNHcOrUKXh6emo6JCKi18KWJqJK8PTpUxw9ehTz589Hly5dYG9vj1atWiE0NBTvv/++WO7l7rnY2Fi4u7vDwMAALVq0wNmzZ4vVffHiRfj4+MDY2BiWlpb4+OOP8fDhQwDAb7/9hho1akAmkwF4/rR6iUSCyZMni/t/8skn+OijjwAAjx49wqBBg2Bra4vq1aujSZMm+Omnn9Q+f0EQsG7dOnz88ccYPHgw1qxZo7C9qNtx165d6NKlC6pXrw43NzecPHlSodyqVatgZ2eH6tWro2/fvoiIiECNGjXKPPbq1avRsGFDGBgYwMXFBT/88IPa50NEVROTJqJKYGxsDGNjY+zZswd5eXlK7ZOVlYXevXujUaNGOHPmDGbMmIGJEycqlHn69Cm6du0Kd3d3nD59GtHR0UhNTcWAAQMAAB06dEBmZqaYbB0+fBi1atXCoUOHxDoOHz6Mzp07AwByc3Ph4eGB33//HRcvXsSnn36Kjz/+GLGxsWqd/8GDB5GTkwMvLy989NFH2Lp1K7Kzs4uVmzJlCiZOnIi4uDjUr18fgwYNQmFhIQDg+PHjGDlyJMaOHYu4uDi89957mDt3bpnHjYqKwrRp0zB37lxcuXIF8+bNQ1hYGDZs2KDW+RBRFaXhBwYTVRk7duwQatasKRgYGAht27YVQkNDhXPnzimUASDs3r1bEARBWLlypfDOO+8Iz549E7dHRkYKAISzZ88KgiAIs2fPFrp3765Qx927dwUAwrVr1wRBEITmzZsL3377rSAIguDn5yfMnTtX0NPTEzIzM4V79+4JAITr16+XGnevXr2ECRMmiK87deokjB07Vnxtb28vfPfdd2We++DBg4Vx48aJr93c3IR169aJrxMSEgQAwurVq8V1ly5dEgAIV65cEQRBEPz9/YVevXop1DtkyBDBzMxMfD19+nTBzc1NfO3s7Cxs2bJFYZ/Zs2cLbdq0KTNeIqKSsKWJqJL0798f9+/fx969e9GjRw8cOnQIzZs3x/r160ssf+XKFTRt2hQGBgbiujZt2iiUOXfuHA4ePCi2ZBkbG8PFxQUAcPPmTQBAp06dcOjQIQiCgKNHj6Jfv35o2LAhjh07hsOHD8PGxgb16tUDAMhkMsyePRtNmjSBubk5jI2NsX//fiQmJqp83k+fPsWuXbvELkAA+Oijj4p10QFA06ZNxf9bW1sDANLS0gAA165dQ6tWrRTKv/z6RdnZ2bh58yaGDx+u8P7MmTNHfG+IiF4HB4ITVSIDAwO89957eO+99xAWFoZPPvkE06dPx9ChQ1WqLysrC76+vpg/f36xbUVJR+fOnbF27VqcO3cOurq6cHFxQefOnXHo0CE8efIEnTp1Evf59ttvsWTJEixevBhNmjSBkZERxo0bh/z8fJXiA4AtW7YgNzdXYeC3IAiQy+W4fv066tevL67X1dUV/y+RSAAAcrlcpeNmZWUBeD4O6uVB51KpVKU6iahqY0sTkQY1atSoxLE9ANCwYUOcP38eubm54rp//vlHoUzz5s1x6dIlODg44N1331VYjIyMAPz/uKbvvvtOTJCKkqZDhw6J45mA5+OG+vTpg48++ghubm5wcnLC9evX1TrHNWvWYMKECYiLixOXc+fOoUOHDli7dq3S9TRo0AD//vuvwrqXX7/I0tISNjY2uHXrVrH3xtHRUeXzIaKqi0kTUSV49OgRunbtis2bN+P8+fNISEjA9u3bsWDBAvTp06fEfQYPHgyJRILg4GBcvnwZ+/btw8KFCxXKjB49Go8fP8agQYPw77//4ubNm9i/fz+CgoLEO+Zq1qyJpk2bIioqSkyQOnbsiP/++w/Xr19XaGmqV68eDhw4gBMnTuDKlSsYMWIEUlNTVT7vuLg4/Pfff/jkk0/g6uqqsAwaNAgbNmwQB3q/yueff459+/YhIiIC8fHxWLlyJf744w+xRaokM2fORHh4OL7//ntcv34dFy5cwLp16xAREaHyORFR1cWkiagSGBsbw9PTE9999x06duwIV1dXhIWFITg4GMuWLSt1n19//RUXLlyAu7s7pkyZUqwbzsbGBsePH4dMJkP37t3RpEkTjBs3DjVq1ICOzv//eHfq1AkymUxMmszNzdGoUSNYWVmhQYMGYrmpU6eiefPm8Pb2RufOnWFlZQU/Pz+Vz3vNmjVo1KiROM7qRX379kVaWhr27dunVF3t2rXDihUrEBERATc3N0RHR2P8+PEKY75e9sknn2D16tVYt24dmjRpgk6dOmH9+vVsaSIilUgEQRA0HQQRkSqCg4Nx9epVHD16VNOhEFEVwIHgRKQ1Fi5ciPfeew9GRkb4448/sGHDBk5WSUSVhi1NRKQ1BgwYgEOHDiEzMxNOTk74/PPPMXLkSE2HRURVBJMmIiIiIiVwIDgRERGREpg0ERERESmBSRMRERGREpg0ERERESmBSRMRERGREpg0ERERESmBSRMRERGREpg0ERERESmBSRMRERGREv4P44QG/zoRD8AAAAAASUVORK5CYII=",
+      "text/plain": [
+       "
"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = plt.subplots()\n",
+    "\n",
+    "# Use scatter for color mapping\n",
+    "sc = ax.scatter(sidewall_angles, freqs, c=transmittance, cmap=\"viridis\")\n",
+    "plt.colorbar(sc, ax=ax, label=\"Transmittance\")\n",
+    "\n",
+    "ax.set_xlabel(\"Sidewall Angle\")\n",
+    "ax.set_ylabel(\"Frequency\")\n",
+    "ax.set_title(\"Frequency vs Sidewall Angle (color=Transmittance)\")\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Creating a Simulation With Two Ports \n",
+    "\n",
+    "We can use the `updated_copy` method to easily create another simulation with a second source with a $\\pi$/2 phase difference."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "
16:51:35 -03 Created task 'sources at 1 and 2' with task_id                     \n",
+       "             'fdve-8680ee1c-a9ba-403a-8139-dce6422d6b5f' and task_type 'FDTD'.  \n",
+       "
\n"
+      ],
+      "text/plain": [
+       "\u001b[2;36m16:51:35 -03\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'sources at 1 and 2'\u001b[0m with task_id                     \n",
+       "\u001b[2;36m             \u001b[0m\u001b[32m'fdve-8680ee1c-a9ba-403a-8139-dce6422d6b5f'\u001b[0m and task_type \u001b[32m'FDTD'\u001b[0m.  \n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
             View task using web UI at                                          \n",
+       "             'https://tidy3d.simulation.cloud/workbench?taskId=fdve-8680ee1c-a9b\n",
+       "             a-403a-8139-dce6422d6b5f'.                                         \n",
+       "
\n"
+      ],
+      "text/plain": [
+       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mView task using web UI at                                          \n",
+       "\u001b[2;36m             \u001b[0m\u001b]8;id=218451;https://tidy3d.simulation.cloud/workbench?taskId=fdve-8680ee1c-a9ba-403a-8139-dce6422d6b5f\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=638127;https://tidy3d.simulation.cloud/workbench?taskId=fdve-8680ee1c-a9ba-403a-8139-dce6422d6b5f\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=218451;https://tidy3d.simulation.cloud/workbench?taskId=fdve-8680ee1c-a9ba-403a-8139-dce6422d6b5f\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=617073;https://tidy3d.simulation.cloud/workbench?taskId=fdve-8680ee1c-a9ba-403a-8139-dce6422d6b5f\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=218451;https://tidy3d.simulation.cloud/workbench?taskId=fdve-8680ee1c-a9ba-403a-8139-dce6422d6b5f\u001b\\\u001b[32m-8680ee1c-a9b\u001b[0m\u001b]8;;\u001b\\\n",
+       "\u001b[2;36m             \u001b[0m\u001b]8;id=218451;https://tidy3d.simulation.cloud/workbench?taskId=fdve-8680ee1c-a9ba-403a-8139-dce6422d6b5f\u001b\\\u001b[32ma-403a-8139-dce6422d6b5f'\u001b[0m\u001b]8;;\u001b\\.                                         \n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
             Task folder: 'default'.                                            \n",
+       "
\n"
+      ],
+      "text/plain": [
+       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mTask folder: \u001b]8;id=888957;https://tidy3d.simulation.cloud/folders/folder-dc5128c7-562b-4bcf-a539-9356f1d308ca\u001b\\\u001b[32m'default'\u001b[0m\u001b]8;;\u001b\\.                                            \n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "6e4d7f211d614a76ae7b6e5dff7e4006",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Output()"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
\n"
+      ],
+      "text/plain": []
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
\n",
+       "
\n"
+      ],
+      "text/plain": [
+       "\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
16:51:37 -03 Maximum FlexCredit cost: 0.262. Minimum cost depends on task       \n",
+       "             execution details. Use 'web.real_cost(task_id)' to get the billed  \n",
+       "             FlexCredit cost after a simulation run.                            \n",
+       "
\n"
+      ],
+      "text/plain": [
+       "\u001b[2;36m16:51:37 -03\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.262\u001b[0m. Minimum cost depends on task       \n",
+       "\u001b[2;36m             \u001b[0mexecution details. Use \u001b[32m'web.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed  \n",
+       "\u001b[2;36m             \u001b[0mFlexCredit cost after a simulation run.                            \n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
16:51:39 -03 status = success                                                   \n",
+       "
\n"
+      ],
+      "text/plain": [
+       "\u001b[2;36m16:51:39 -03\u001b[0m\u001b[2;36m \u001b[0mstatus = success                                                   \n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "a0a11d7c41b94fdda852e983c566d7e5",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Output()"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
\n"
+      ],
+      "text/plain": []
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
\n",
+       "
\n"
+      ],
+      "text/plain": [
+       "\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
16:51:57 -03 loading simulation from simulation_data.hdf5                       \n",
+       "
\n"
+      ],
+      "text/plain": [
+       "\u001b[2;36m16:51:57 -03\u001b[0m\u001b[2;36m \u001b[0mloading simulation from simulation_data.hdf5                       \n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "source_time2 = source_time.updated_copy(phase=np.pi / 2)\n",
+    "source2 = source.updated_copy(\n",
+    "    center=(source.center[0], -source.center[1], source.center[2]), source_time=source_time2\n",
+    ")\n",
+    "\n",
+    "sim2 = sim.updated_copy(sources=[source, source2])\n",
+    "\n",
+    "sim_data2 = web.run(sim2, \"sources at 1 and 2\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "As we can see, in this configuration, all power is directed to the upper output at the crossing frequency."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "
"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plot field\n",
+    "sim_data2.plot_field(\"field_mon\", \"E\", \"abs\", f=cross_freq)\n",
+    "\n",
+    "plt.show()"
+   ]
+  }
+ ],
+ "metadata": {
+  "description": "This notebook demonstrates how to import geometries from a gds file to Tidy3D for FDTD simulations.",
+  "feature_imag": "",
+  "feature_image": "N/A",
+  "kernelspec": {
+   "display_name": "base",
+   "language": "python",
+   "name": "python3"
+  },
+  "keywords": "gds, import, Tidy3D, FDTD",
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.7"
+  },
+  "title": "GDS File Import in Tidy3D | Flexcompute"
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/docs/case_studies/pic.rst b/docs/case_studies/pic.rst
index 237bcd9d..fc2a987a 100644
--- a/docs/case_studies/pic.rst
+++ b/docs/case_studies/pic.rst
@@ -45,3 +45,4 @@ Passive photonic integrated circuit (PIC) components form the backbone of many o
     ../../AnisotropicMetamaterialBroadbandPBS
     ../../SWGWaveguideCrossing
     ../../SiWaveguideTPA    
+    ../../DirectionalCoupler
diff --git a/docs/features/parameter_sweep.rst b/docs/features/parameter_sweep.rst
index c897dc3a..77cd0d9d 100644
--- a/docs/features/parameter_sweep.rst
+++ b/docs/features/parameter_sweep.rst
@@ -8,4 +8,5 @@ Tidy3D excels at exploring a high-dimensional design space because it is able to
     :maxdepth: 1
 
     ../../ParameterScan
-    ../../Design   
\ No newline at end of file
+    ../../Design   
+    ../../DirectionalCoupler
\ No newline at end of file
diff --git a/misc/import_file_mapping.json b/misc/import_file_mapping.json
index bd8abfd5..11cb37e9 100644
--- a/misc/import_file_mapping.json
+++ b/misc/import_file_mapping.json
@@ -1,31 +1,113 @@
 {
-    "8ChannelDemultiplexer.ipynb": ["8ChannelDemultiplexer.gds"],
-    "90OpticalHybrid.ipynb": ["mmi_stl.stl", "optical_hybrid_stl.stl"],    
-    "AdjointPlugin3InverseDesign.ipynb": ["inv_des_mode_conv.gds"],  
-    "AdjointPlugin6GratingCoupler.ipynb": ["invdes_gc.json", "inverse_designed_gc.gds"],
-    "AdjointPlugin8WaveguideBend.ipynb": ["inverse_des_wg_bend.gds"],   
-    "AdjointPlugin9WDM.ipynb": ["inv_des_wdm.gds"],    
-    "AdjointPlugin10YBranchLevelSet.ipynb": ["y_branch_fab.pkl", "inv_des_ybranch.gds"],
-    "AdjointPlugin12LightExtractor.ipynb": ["qe_light_coupler.pkl", "inv_des_light_extractor.gds"],
-    "Autograd6GratingCoupler.ipynb": ["grating_coupler_history_autograd.pkl"],
-    "CMOSRGBSensor": ["red_eps.csv", "green_eps.csv", "blue_eps.csv"],
-    "DifferentialStripline.ipynb": ["stripline_fem_mode.csv", "stripline_fit_mode.txt", "stripline_fem_sparam_long.csv", "stripline_fit_sparams_long.txt"],
-    "Fitting.ipynb": ["nk_data.csv"],
-    "FocusedApodGC.ipynb": ["Focusing_GC.gds"],
-    "GDSImport.ipynb": ["coupler.gds"],
-    "GDSExport.ipynb": ["dc_export_gds.gds"],    
-    "Near2FarSphereRCS.ipynb": ["mie_bRCS_phi0_2lambda_epsr4.txt", "mie_bRCS_phi90_2lambda_epsr4.txt"],
-    "NonHermitianMetagratings.ipynb": ["Cr_Sytchkova.csv"],
-    "OptimizedL3.ipynb": ["optimized_L3_holes.txt"],
-    "PlasmonicNanoparticle.ipynb": ["mie_plasmonic_flux_abs.txt", "mie_plasmonic_flux_scat.txt", "mie_plasmonic_RCS.txt"],
-    "PlasmonicYagiUdaNanoantenna.ipynb": ["McPeak.csv"],
-    "STLImport.ipynb": ["box.stl", "box_with_hole.stl", "box_with_indent.stl", "icecream_nonunionized.stl", "icecream_unionized.stl", "two_boxes.stl"],
-    "RadiativeCoolingGlass.ipynb": ["mat_SiO2.csv", "mat_Al2O3.csv"],
-    "XarrayTutorial.ipynb": ["gaussian_beam_data.h5", "mmi_simulation_data.h5", "waveguide_mode_data.h5"],
-    "TunableChiralMetasurface.ipynb": ["GST_A_nk.csv", "GST_C_nk.csv"],
-    "MoS2Waveguide.ipynb": ["MoS2_nk.csv"],
-    "FreeFormCoupler.ipynb": ["chip_to_chip_coupler.stl"],
-    "UnstructuredData.ipynb": ["unstructured_grid.vtu"],
-    "MMIMeepBenchmark.ipynb": ["MeepMMI.txt"],
-    "Autograd13Metasurface.ipynb": ["logo.png"],
-}
+    "8ChannelDemultiplexer.ipynb": [
+        "8ChannelDemultiplexer.gds"
+    ],
+    "90OpticalHybrid.ipynb": [
+        "mmi_stl.stl",
+        "optical_hybrid_stl.stl"
+    ],
+    "AdjointPlugin3InverseDesign.ipynb": [
+        "inv_des_mode_conv.gds"
+    ],
+    "AdjointPlugin6GratingCoupler.ipynb": [
+        "invdes_gc.json",
+        "inverse_designed_gc.gds"
+    ],
+    "AdjointPlugin8WaveguideBend.ipynb": [
+        "inverse_des_wg_bend.gds"
+    ],
+    "AdjointPlugin9WDM.ipynb": [
+        "inv_des_wdm.gds"
+    ],
+    "AdjointPlugin10YBranchLevelSet.ipynb": [
+        "y_branch_fab.pkl",
+        "inv_des_ybranch.gds"
+    ],
+    "AdjointPlugin12LightExtractor.ipynb": [
+        "qe_light_coupler.pkl",
+        "inv_des_light_extractor.gds"
+    ],
+    "Autograd6GratingCoupler.ipynb": [
+        "grating_coupler_history_autograd.pkl"
+    ],
+    "CMOSRGBSensor": [
+        "red_eps.csv",
+        "green_eps.csv",
+        "blue_eps.csv"
+    ],
+    "DifferentialStripline.ipynb": [
+        "stripline_fem_mode.csv",
+        "stripline_fit_mode.txt",
+        "stripline_fem_sparam_long.csv",
+        "stripline_fit_sparams_long.txt"
+    ],
+    "Fitting.ipynb": [
+        "nk_data.csv"
+    ],
+    "FocusedApodGC.ipynb": [
+        "Focusing_GC.gds"
+    ],
+    "GDSImport.ipynb": [
+        "coupler.gds"
+    ],
+    "GDSExport.ipynb": [
+        "dc_export_gds.gds"
+    ],
+    "Near2FarSphereRCS.ipynb": [
+        "mie_bRCS_phi0_2lambda_epsr4.txt",
+        "mie_bRCS_phi90_2lambda_epsr4.txt"
+    ],
+    "NonHermitianMetagratings.ipynb": [
+        "Cr_Sytchkova.csv"
+    ],
+    "OptimizedL3.ipynb": [
+        "optimized_L3_holes.txt"
+    ],
+    "PlasmonicNanoparticle.ipynb": [
+        "mie_plasmonic_flux_abs.txt",
+        "mie_plasmonic_flux_scat.txt",
+        "mie_plasmonic_RCS.txt"
+    ],
+    "PlasmonicYagiUdaNanoantenna.ipynb": [
+        "McPeak.csv"
+    ],
+    "STLImport.ipynb": [
+        "box.stl",
+        "box_with_hole.stl",
+        "box_with_indent.stl",
+        "icecream_nonunionized.stl",
+        "icecream_unionized.stl",
+        "two_boxes.stl"
+    ],
+    "RadiativeCoolingGlass.ipynb": [
+        "mat_SiO2.csv",
+        "mat_Al2O3.csv"
+    ],
+    "XarrayTutorial.ipynb": [
+        "gaussian_beam_data.h5",
+        "mmi_simulation_data.h5",
+        "waveguide_mode_data.h5"
+    ],
+    "TunableChiralMetasurface.ipynb": [
+        "GST_A_nk.csv",
+        "GST_C_nk.csv"
+    ],
+    "MoS2Waveguide.ipynb": [
+        "MoS2_nk.csv"
+    ],
+    "FreeFormCoupler.ipynb": [
+        "chip_to_chip_coupler.stl"
+    ],
+    "UnstructuredData.ipynb": [
+        "unstructured_grid.vtu"
+    ],
+    "MMIMeepBenchmark.ipynb": [
+        "MeepMMI.txt"
+    ],
+    "Autograd13Metasurface.ipynb": [
+        "logo.png"
+    ],
+    "DirectionalCoupler.ipynb": [
+        "misc/coupler.gds"
+    ]
+}
\ No newline at end of file

From fcf77ba65860799abf713c1c7bf38a82a8e46f0b Mon Sep 17 00:00:00 2001
From: "filipe@flexcompute.com" 
Date: Mon, 21 Jul 2025 19:34:32 -0300
Subject: [PATCH 2/4] review

---
 DirectionalCoupler.ipynb          | 166 ++++++++++++++++--------------
 docs/features/parameter_sweep.rst |   3 +-
 2 files changed, 87 insertions(+), 82 deletions(-)

diff --git a/DirectionalCoupler.ipynb b/DirectionalCoupler.ipynb
index 0049d25a..fcc6640f 100644
--- a/DirectionalCoupler.ipynb
+++ b/DirectionalCoupler.ipynb
@@ -56,8 +56,7 @@
     "\n",
     "# Tidy3d import\n",
     "import tidy3d as td\n",
-    "from tidy3d import web\n",
-    "from tidy3d.plugins.mode import ModeSolver"
+    "from tidy3d import web"
    ]
   },
   {
@@ -120,7 +119,7 @@
    "source": [
     "### Set up Structures\n",
     "\n",
-    "Next, we assign material properties to the imported geometries and create the [`td.Structures`](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/structures.html) with those material properties."
+    "Next, we assign material properties to the imported geometries and create the [`td.Structures`](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/structures.html) with each of those material properties."
    ]
   },
   {
@@ -182,7 +181,9 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Now, we add the [ModeSource](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.ModeSource.html), which excites the first order TE mode (`mode_index = 0`). To analyze the transmittance, we will place [ModeMonitors](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.ModeMonitor.html) at the end of both output arms. These monitors will carry out mode decomposition and analyze the fraction of power transmitted in each mode. Since we are only interested in the first order TE mode, the number of modes analyzed can be just 1."
+    "Now, we add the [ModeSource](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.ModeSource.html), which excites the first order TE mode (`mode_index = 0`). To analyze the transmittance, we will place [ModeMonitors](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.ModeMonitor.html) at the end of both output arms. These monitors will carry out mode decomposition and analyze the fraction of power transmitted in each mode. Since we are only interested in the first order TE mode, the number of modes analyzed can be just 1.\n",
+    "\n",
+    "We will also add a [FieldMonitor](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.FieldMonitor.html) to visualize the field profile in the xy-plane."
    ]
   },
   {
@@ -236,7 +237,7 @@
     "grid_spec = td.GridSpec.auto(min_steps_per_wvl=min_steps_per_wvl)\n",
     "\n",
     "# Simulation size\n",
-    "sim_size = (17, 8, wg_height + 2)\n",
+    "sim_size = (17, 7, wg_height + 2)\n",
     "sim_center = list(arms_geo.bounding_box.center)\n",
     "sim_center[2] = 0\n",
     "\n",
@@ -275,7 +276,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "
"
       ]
@@ -287,8 +288,8 @@
    "source": [
     "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(17, 5))\n",
     "\n",
-    "sim.plot(z=wg_height / 2, lw=1, edgecolor=\"k\", ax=ax1)\n",
-    "sim.plot(x=0.1, lw=1, edgecolor=\"k\", ax=ax2)\n",
+    "sim.plot(z=wg_height / 2, lw=1, ax=ax1)\n",
+    "sim.plot(x=0.1, lw=1, ax=ax2)\n",
     "\n",
     "ax2.set_xlim([-3, 3])\n",
     "_ = ax2.set_ylim([-1, 1])\n",
@@ -312,7 +313,7 @@
      "data": {
       "text/html": [
        "\n",
-       "    
\n",
+       "    
\n",
        "