{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Editing a scene" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "## Overview\n", "\n", "In this tutorial, you will learn how to modify a Mitsuba scene after it has been loaded from a file. You might want to edit a scene before (re-)rendering it for many reasons. Maybe a corner is dim, or an object should be moved a bit to the left. Thankfully we can use the *traverse* mechanism to perform such modifications in Python with Mitsuba 3. As we will see in later tutorials, this mechanism is also essential for inverse rendering applications and more.\n", "\n", "
\n", "\n", "🚀 **You will learn how to:**\n", "\n", "\n", "\n", "
" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Loading a scene\n", "\n", "Following the same steps as in [Mitsuba quickstart tutorial][1], let's import `mitsuba`, set the desired variant and load a scene from an XML file on disk.\n", "\n", "[1]: https://mitsuba.readthedocs.io/en/latest/src/quickstart/mitsuba_quickstart.html" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import drjit as dr\n", "import mitsuba as mi\n", "mi.set_variant('llvm_ad_rgb')\n", "\n", "scene = mi.load_file(\"../scenes/simple.xml\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let's quickly render this scene." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "original_image = mi.render(scene, spp=128)\n", "\n", "import matplotlib.pyplot as plt\n", "plt.axis('off')\n", "plt.imshow(original_image ** (1.0 / 2.2));" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Accessing scene parameters\n", "\n", "Any Mitsuba object can be inspected using the [traverse()][1] function, which returns a instance of [SceneParameters][2]. It has a similar API to Python `dict` and holds all parameters that are exposed by the input object and its children. Therefore, when given a scene as input, this function will return the parameters of all the objects present in the scene.\n", "\n", "Let's print the paramters available in our teapot scene.\n", "\n", "[1]: https://mitsuba.readthedocs.io/en/latest/src/api_reference.html#mitsuba.traverse\n", "[2]: https://mitsuba.readthedocs.io/en/latest/src/api_reference.html#mitsuba.SceneParameters" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "SceneParameters[\n", " ----------------------------------------------------------------------------------------\n", " Name Flags Type Parent\n", " ----------------------------------------------------------------------------------------\n", " sensor.near_clip float PerspectiveCamera\n", " sensor.far_clip float PerspectiveCamera\n", " sensor.shutter_open float PerspectiveCamera\n", " sensor.shutter_open_time float PerspectiveCamera\n", " sensor.x_fov float PerspectiveCamera\n", " sensor.to_world Transform4f PerspectiveCamera\n", " teapot.bsdf.reflectance.value ∂ Color3f SRGBReflectanceSpectrum\n", " teapot.vertex_count int PLYMesh\n", " teapot.face_count int PLYMesh\n", " teapot.faces UInt PLYMesh\n", " teapot.vertex_positions ∂, D Float PLYMesh\n", " teapot.vertex_normals ∂, D Float PLYMesh\n", " teapot.vertex_texcoords ∂ Float PLYMesh\n", " light1.position Point3f PointLight\n", " light1.intensity.value ∂ Color3f SRGBEmitterSpectrum\n", " light2.position Point3f PointLight\n", " light2.intensity.value ∂ Color3f SRGBEmitterSpectrum\n", "]\n" ] } ], "source": [ "params = mi.traverse(scene)\n", "print(params)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "As you can see, the first level of our scene graph has 4 objects: \n", "\n", "- the camera (`sensor`)\n", "- the teapot mesh (`teapot`)\n", "- two light sources (`light1` and `light2`). \n", "\n", "Some of those objects have nested child objects, like `teapot.bsdf`.\n", "\n", "Names like *teapot* are defined in the `id` field in the XML file. Parameters such as `teapot.vertex_positions` or `sensor.far_clip` are documented in their respective parent's plugin documentation (see [PLYMesh][1] and [PerspectiveCamera][2]). The plugin documentation lists which parameters are exposed, as well as all input parameters it takes in the XML file.\n", "\n", "If you wish to modifiy a plugin's parameter that is not exposed with `traverse`, you still have the option to modify the XML file directly. `traverse` is merely a convenience function to edit scene objects in-place.\n", "\n", "Individual scene parameters can be accessed with the `__getitem__` operator, providing the `key` corresponding to the parameter. Let's print some scene parameter values.\n", "\n", "[1]: https://mitsuba.readthedocs.io/en/latest/src/generated/plugins_shapes.html#ply-stanford-triangle-format-mesh-loader-ply\n", "[2]: https://mitsuba.readthedocs.io/en/latest/src/generated/plugins_sensors.html#perspective-pinhole-camera-perspective" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "sensor.near_clip: 0.009999999776482582\n", "teapot.bsdf.reflectance.value: [[0.8999999761581421, 0.8999999761581421, 0.0]]\n", "light1.intensity.value: [[100.0, 100.0, 100.0]]\n" ] } ], "source": [ "print('sensor.near_clip: ', params['sensor.near_clip'])\n", "print('teapot.bsdf.reflectance.value:', params['teapot.bsdf.reflectance.value'])\n", "print('light1.intensity.value: ', params['light1.intensity.value'])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Edit the scene" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Similarly to a Python `dict`, parameters can be modified in-place using the `__setitem__` operator. However, it is necessary to call the `SceneParameters.update` method to properly apply the desired changes.\n", "\n", "Some objects need to be notified if the children have been updated. For instance, a change to the vertex position buffer of a mesh will trigger the recomputation of the Embree/Optix BHV.\n", "\n", "Internally, the `SceneParameters` object will record every update written to it.\n", "Using `SceneParameters.update` will propagate all updates through the dependency graph, and perform all necessary updates to the parent objects." ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "# Give a red tint to light1 and a green tint to light2\n", "params['light1.intensity.value'] *= [1.5, 0.2, 0.2]\n", "params['light2.intensity.value'] *= [0.2, 1.5, 0.2]\n", "\n", "# Apply updates\n", "params.update();" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Mesh editing is also possible but requires specifying the layout of the stored data. See [transformation toolbox][1] and [mesh manipulation][2] for more geometry and mesh operations.\n", "\n", "[1]: https://mitsuba.readthedocs.io/en/latest/src/how_to_guides/mesh_io_and_manipulation.html\n", "[2]: https://mitsuba.readthedocs.io/en/latest/src/how_to_guides/image_io_and_manipulation.html" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "# Translate the teapot a little bit\n", "V = dr.unravel(mi.Point3f, params['teapot.vertex_positions'])\n", "V.z += 0.5\n", "params['teapot.vertex_positions'] = dr.ravel(V)\n", "\n", "# Apply changes\n", "params.update();" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "After rendering the scene again, we can easily compare the rendered images using `matplotlib`. " ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "nbsphinx-thumbnail": {}, "tags": [] }, "outputs": [ { "data": { "image/png": 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qwnMWwlQueG6aEM4aQkjNQlH7EMrKCWpROL59nZn5uojGTiA4AyKETXTtXQitZRHDsXX2bP6e2Mvjo/d2XVZFOuG7QyI87wn6Hl68GF+fn8N0KnIznYrs5PlIbIwgbbfaZ7fTs/ciOObvaVt4+TKpOwkJ9wVGds6DqlOgybcJoZdD5D+BMQxl5ABuT9z23lQXO4eRIgsxWejHQkgloyE5DinZ+QpGguTQuIxQmFdo6uTniUNVLhAnazVRMqpVZrY2dakIfiLb38ZsZmgbc8EYWrNrt3HbfkM4f+YVLnOBOHZ+VJuM+FVOxuoDI6F8V2FhyIm7rY4t3Hiv+iNyZ2TVh783I9aeb2f4ToTnPcJmI2Ky3So0NZuNhKeuta4sx9few36v184p5OW9nk3hubiQfychIeF+wCYnj0jDKkzMZjYevCaukl/2qLiwvogmNsucyiMiYeErIz4W6ioZyYgnqMp+zLgqgnITh6AGP6a326Roxz1Eoag6HLtg9MvU6Npqp2OaqdmUohwY3GhatjFXYftD2NfITEyGjGCVBOUnHLN0MEEKlhtgz9gEFRubh2UOM9T7a/eOkZ4M3ZeToBKehNe5GxW9m8/ajeR5FdqEWMackewWhTmft/p7/KZIhOc9gpEV7xWCquvRzDydjqGrqtKzmZfNv9O2I9EZBpGmly9TbZ6EhPuELPyybtDEsxnGYnymiliY5yZlPFJ4BjcWFYTQ3JPR/+L9uK11NO/9WPzP0s+z8N65MSvLSJAd0zKwikDAWkTMhjA+U4CMsJjSApGS5DQRzxiNyI4xjGeKkqlVrR+7sA9hnQtEqwcm2W1zduVuK10xcSoyWAKvBk32sYo0c2Nq/7N+/AzeZjiCsT2XuX2awawIzVuDKlcAVRa8T06PLIOphzKDOty/PoNdob+X5we42GgO+jZIhOc9gxEWSzcvSy3Pc63rOj07N2ZzGbmBsfaOqTvf9g8wISHh7YEpIz2AH30k5o+xNHALV5lS48J6IylGEDwhJBSRoyHsY+nnpsjkdqBofwsT2bHCsG7IU+9HMpE7GY0tHGKkiLBtNx5eSlNQZqoopNJG11a4kfxY+MyUpLgAoqXE23XYfbE0dRftAyNxybxUCyNiDpEeU0WWWbgnmVSe9i1XeSoHJyWclfCghpOQEDPLYFuFWk2IyMzCBfc5TIFNof1/rYNVBd0Amx42O3i5gRc7uGq+/T1IhOc9xDBI6YEx/dyIS5aNhmXQcuek8phP53CAq6tUdDAh4b7BOSAbycEUTUTmsbGwVRa9tknEwlhGbsyPEhcgHAjfOdG21vPKsqiyKOxhBAJGEmEhLzM5W0aVY8x4stCVjd3GYwSnJVKXwjlrFD6JK0PX3K7Z0yNfkHlJsojU2Di7sM3UjYpNrOqYSmamb0v5P83gQaYsOLtvpkadZLDv396aPZWDBxN4NIWHM5iXMKmACpYOHjrY1XDqpdpU4f6WAwwZ7AvwHRwaeO7g1Q6+eAkXK1gfvrukmER43lP0/UhmqmokOXFFZSNBRTGqPm0rz44RpoSEhHuCDFwBLsg83kM+QOVhYiGayDhqBMMIzk0mkx/9L7Hp2EJE9tVh5mDPbUVoiH7FT9xYvM/UmdqN+xZBYTFPTx42MvJhIaeaUPyPkay1RlbC+Xw4n11L56WybPx4vWW0XRNCMjM3ZopZEcPcaZvOj6E7Iy9ZuMbajf2/5tmoSNn1Gik0Qjh1386/8n2hcHAyE9F5MoGHFbgaqEOUIFe4qs5D6CqDQxFqFnWwdSI7rwa47ODTa/jsFay/h9puifC8xzAfj9WKiCsvl6UIUNxiAuDyUkbmhISEewQXyE7FjcEmD+0YikA2ypDI4IcQtvKjodgxqjdGPuLl1j/LyE3rI2LBSCJ6LzPvgLKUMkQsFtlIKG5q7HC7JxeMBMmKFVr2mCkwHqk4JeGHHeO+Fp5yaBxGWswnZIZkz+jLMQ+QFUKsnDKwCsaqzKZU7f1oBq/CcU21mgTVye7ZJtQ0MoXL2mi8bYSncHA6hQdzWM6gnMBQQllAVUCVQ1/onpz0kA1wcLAL93TvoO1g3cCnPTz7Al5ewnbPt0vHet14v/tDJrwrMPOy+XWsCGH86HupO1ZvZ7UayU9CQsI9QQ6uDKSnCOEqJ7VnMLLig+9kUHZRNkAWvh/cENowDFItmmHMTrLQlpEDx23iMmFs4VBlownZ1B9rY7H1ox/o4Md+WDfqDmOV5psQlxsLDc7cmHUF8sXkyCTrA6HpnMZ9PYxp01MXzLXhdWPnYkw7J4xzQBfl3ZhVVruRCM4sthUfKyKIMNYgskrSOSJE80xK2/4t+f7NMlhO4WwJyzksK6grmOaQF9DWYzafMd9DHtS6FsoOLpBP57MN/OwlbK6/X19oIjwJN2EsUHjLihFaSwkYQ151fdvobGExy9SKvT6JGCUkfHdw0bOFd44L+N3a1o37wBiW8Rz1cArqThb+77OcIIHoYeQHB1WvX+yZl/8i8yI5RlgmXVBTepj1mrSHHvoBSj9mL1nYqh0iIhKWWe2bjtHLsg8hoIZAZpwIT4fUj90weoim0Y0oUNq3hczqSKVZhjpDZnLOnMgX4ZilUzgrCyTLCI/VzbFKyd4rI8nudYPGZunph3DjT4I3ZxVITBldcx0+GEujn2ZS0konoleHY87d20F4MidF59ECTucwmUvVOQGKSirPAmhzKYRlIIGXucJYWQNXPXzewouXCmGttt//nJEIzzuGPB8rJJsys9l8MwOxNRA1EmMhrNlMBMbS060mj7WnmEy0r/XV6nsti9PWrYDhfq9lVsunae42QickvK+wcItlSMWeGIOlecdZQOZ3sWJu5puxbc2LZ+vsXKBJ+WoIk2cOLg/nzfQdkGfhXHnw9OQKYVEEJSgcNPNaX6LX0/D/XGQwa6E3gtCF0JgPapCHIjwvQlzJDWMpjBaRoTKcZ7AQGDrGhLG+zm5QOrMLIaneySi7HTSOCVrehuMaWZqg68+CUvQgG8nQLCgqD93o4bE6PTUiUedBGcKJhFnIrvVSkUqkzODHLC88zMJ92w86R+tH8jp1o7naMZqejazNHKx4s60nnJOy83AJ51OYBpPyWZiPZkEpc5ke3sOOUBiy0XW3W/i4kapzcR3KpfwAY0+E5y1Elt0mNWUpQmFhJiMpRjhOT+EXvxid7M7dPt5drNk5HWM+H+vxmH+naUR2LORlhMc51evZbsfig9aSwtbH7SnMEB2HxqzZqKFpRvLTNGNavD0nJNwnWOjF0p4Lxno2jrEmjJEfGD0cpnjE3hPbv4+2NwXI/s9M2bEaNy6QgS2afFwhwuOy8XsgH4IPxRhUmM2HTCQid+BL/Vr3hciMz0VsMsL//KDjZA66DKbhh44LqtCig0MGXS5liECC9g7mgxSOOqhHlnVVD1KnZl7jzwN5GJA3xArYVWGbEtgEQ7AL2z0M31W7DCbDaC6eBkVs4mET7t3MwbkfvTaNg7WDc0R8Si8T9lk49lX4YOpwnLhlxW7QmPJw/QRyZwbolnH8YfWNmuTRGM5yEbBXb/C7sShEeE6ncDKBeQF1AUUestPC9a0Dia5a3c/9AIcernbw7BX87Aqut9D9gD96E+F5C2A9roritrpSB5d72+o9jIrOditSYKqKhaGMhMSkYhhG0uPcbdJUVWOIyraxNhI2NmslYQrQfj+Gu4yw7Ha3z2u/Lo0AxeeO+3IZOep7XY8VOjQCZOSnbZMalPDuwjKWJiFUEhfbKwOB6Jz8JKayDOEZF8JBgcmU6LVHv/pv/tejid1Ila26MfKG0ELfQ9GAO2jDzI1qThYUncGWEybpsBw3hoBcqCRXWFnhGqoOtlMRlqqFuodtLQOrc1J+mhL2mUJkXQlFC00G8wY2E02Ys04EpxjgVTVmNz1oRZROwqRfhfDada7rLweZYpeD1J7THraZVJjBw9kAV9nY5T0Dznq4yERU8LD0IU0+kJU6UsqeDlKHtoTPEBGnQ9jO+VDXxyscVXiRn2UIAbpBxGkWvuvMyDxFZMa6uhdBTWqDCmVFFS3N/019Hc5rqTrTGiYlzHIVW9xPoG5gXetzO2vgqlRIsxtgOKiA4B++gOeXsG1+eNtDIjxvAFkmojGfS7kxcmNKSUwwhkHkxto3WKNOa+AJv1wo8EbG9iMJsgahphgVxRjGspYSprTEnhwb7+EwHst6cBlxsrEYYbHxxB3X4TYhismZES77dQm3M8bihzUzNaKXkPC2wtQcy7Cpw/90XcA8kAv7AVCEjV0uEtGXoQBeiGFVvRSUPrudeeTD+8LLL9E7mLTap8/kpclDmMeyhzyhhP8G3CvAeuMR1CWncVj8zNSiIRibPSJN5OB6ja1AJtTMAcVI2nwmgyoTKTcnB9jMRIL6XMSlHkSQZp2u8THQVpCV0ORQt/KFLFspRbtZpJA4yINStBhGX1LhYB6+d8pBJGGbSTmygoAWRio85D38yMN1II2bsP/aheN6kc5JUGgalHV05TSOTQiZ+UBoNsCkDxWeB6k7LtO47bPIg7IzENp2BCWpRFlaVpXYuxCq86PxeeJ0zh8aRQX1TKRn6cDX+qwed/pMm1KfeetgHVj29QAXrWrq/OELeL6C5g0VFEqE5wdEVYkszGa3vTNmCLY+V+bHsbBRrGwcKzhxKCleZrAaOnmu1+bFOQ5jwajK5LlUHFNnTHGxooSW2VXXt6/P3PWxgTkei702xcnOZTV9jAR5P4bE7L5YIUQL95nqkzq1J7yNsMaX00BwJkX4f6+hqNVbqK8UBnCZiESRw1CENOdC610+pn/fNF4M/+tZWD4UehQOFnspIoda+xat1JculxLiEIlodvLIuEKkxciOM9IV/BfOKSxV9sGPwRhWM+UnRwStMqJVaLI3dairdO7MBzUn3J9JL1WrC4XoisDiSq9zHQpN9oWHMlTqPe3gotKyZRNIXSbyVHdBNXGafDcTkZ1q0ARcZXrdhXswGeCkg00uFaLoRdQmISRVBPJnmWmZ/cAMYSyf6f4/6eDzkLJ1MsCLDAghskk4zlV47cMxp04htRady7nRF9URTMyMfaYsFJl5+X5mw5shPJMaphW4CfhK97QMZLgKf49l+OG7cfrbOnSw2cLPL+HZNbRvUKlPhOd7hpGLxWIM35jpt+9FLA4HTdyHwy+TmxhGUI5VkthDcxxWMtJiihHcVoC6Tuv3exGxprlNckwNatsx3GTKEWidETYrXGjhqLoeQ15Glo7DbXddg6lC5iey7Y7vhSlUkMJeCW8PKgenodLsdCLpnylUE5iWkM00MTbzMUxUIC+ML2CogoHYSaHpqxCGclILnAOGUN+lF6HIOx2rnYNvpZQMpXw0vteE5DPtf+3guoLuF9o2C8UGb4zLQ5hgM02wFMG7E0JqOKkuudM5mrB/k481e8xp67zO3YfCNNNQbKYNSkoZlKlqgLYMad7h/HkmQnWoRGRcCFnNPGxKhcyGTKGwuoftBJ7s4GWt+zHkygpatPILNbkUokOm0NMimJ17B7tSxON00NA74FkFHzTwWa5w08TDOhOh9F4huXIQcekdzJGPaIY8PXs3kpcykJWNqexuvOdNP9b1MdNyxhiGtK8+U3lKVJfo2v+wndSLCuq51J1FBlS6L4shKDvh77jqYZWrMnQ+aG55tYEXV2+W7EAiPN8rqgpOTkbDcdzGoWnkezGfCtxWWo7JTazeHJOeWKWxdXauWEmJjx2HnoxYZNmomBhxMEJipmMYryHO7LJQmKktNq7Y/GxGa1tviJWn+Dri6s/x+Y9VI7sn1uA09fdKeFMonAyd8zMZOidTNU/sTqCYQF1CflNeF8qdSIN3gZB0et8ayfEiNJ5gPg4le/O9VJ1+Mv79+9D0KvOQNSIOzgHVeGzn4QsH13t5KsyLk0WhMZeLeFmhHAtpeUui6KXoZEFdKu17CxGboRSBKXqdN0MkoQokpCnl1SkHvS+HEA4JJMlUow6Fu5pcpOrkINVnCGGwphBxwikktSnVf2kbUupXwUxdIaLjAtFyHpY9rAt42EjpmSLilAOXmfYbnJadBnL5soRHLaycxnoSlLE2EKhNrmXOBz+Wk8/HOxGavdNYSjf6sR4UypazkFgZKTtB6KMhtMGIXs9DaOsHIzwO6iksKhH5zDxZ2TjOHv1NHIC8leK3b+Gwgc8v9PpNIxGe7wmm6tT1qOYMgwzHu93tzCdTX+I00njyt/cxQbH3x96bmDDYdqbCGMmw7eyL0shITChiQmIqDYjAWNr54aD3dm19P5IXa1dh5zLiY6EqC1NZqAzG0Ftc7NDGG6fH9/3Y9d3Ga/fISFi8PiHhh0AWyM6jE6gewGKpHztlBfkp5MHb4nLYl5Ad9NxkIjid0+Q4NKo+2w4wtDJ8tuEHCgP4Lfh9UIOCT4YM+g03M6LL5K8wpuS8CE83qG/R/gKGy6Ai5UHlMd9OCKPlIX7lw+TsXFiW6dd8G66FQcuLoMx0hYhP3us1hF//h6DMZLCewcleqs7DjY7dVCI/+yqYpBEpmbbwdANXk0BEgsrSZSH7q4dNBR/sRSSqQcRl2SsMVXm4rKQ85MCjBi5KmA7wrIYnBykSA3BZwlmrSfxxp+XVMHp2DpmO9zgYoxfI51N5Eb8mhKsuGP1JezfW9WnR52w+nr1T1tuZl59n78eu4i1BYWN8b53ZayfSs+KH6a+V1yLvdaXXZa5x1yjMuMsDyWulIHY99C2s9/CLPVxsudUy5E0hEZ7vAWZIrutxcraHkYqb9M/8Nrk49uPE/a1idQZGchHvYxlbx8UAY9PycVjJyE/srbGx2DEs9BWHwYwsGZGJVamuE/mwGj2xT8euy56NjNkjNlnH+5iSZPvu96NiZETIQoizmYjlu2psNhO6FYI0z1UR/cfGn1VRjH9fptiZkggp1Pd9wzmYzuH0HKpz1SdxDyGf6td/PpEa4hoRmm4vJaLdSwXYPYPtBtpXMGyDUtJLhRkahW9uCHyv95aCZYTkZjnchJ60wegP8V7kg0BWXEgOoOTGVEtQdxxSaVzo1OlcyKqahO8uP56mGOTPIfzqrzuRHR8mwTaTj8iKF+KhLfR6PRWpyMK4uxyWe5GTbSl/zsUsFDpEYyy8nie9SA8hJHSwH45BIcnC63qAdQknjY67K5RFNB3UqXtwsAxZYfNBoZhVrsyqjYOnLXxe6P5Ow72vvUJYlYdX+ViDyAiNG3TuXbhJByf+uQrqTxuUngGFw7oQoipQ3Rr7l+18KEkQFD/nQtq7++HaTVQ1zIK6M8tkwF+EH9TXU5HYOvihsoPSz9eDPKlfXCts9zYgEZ7vGHG2lPly9vsxzGIEJ07PjsNQpsoYKTmub2Pk5di3Y8TBjh9nScVEKVZhYnIRL3dO4zViAaO6tN/fHuuxnyhWbGD0/9iY4zEZGYmN1UaeDDH5ssww26YoxppAtq2NczrVedbrd0vpMZIzncLZmcY+n4vAxaHIth1rIpWlrnM+F8HxHq6v9R60/fPn7y75exdQzeDsEcxP9SgW6itUVCIN2zkMO+h3sCphu4PtH8HqCg7X0K4CwWnBqs55i2N9159bDq5WWOImOwsRoKEK3pkBCBlZwX6j75SSG4Un67mpQjwUwXeSifgsmpH4tCGlPANOd7CbiCCVwxjy8hlMO02etYXivNSeWRsUJC+T8q6UYXlAobA2U1XnbalMrk0IZV2XIkSHXOPsncjKF5PgHcq0zBQwW3ZViLwMTudbDPA8hPBqH7w7YTz7ECKbhn3rYazv4wl+oEBumgwe9EHpcdzUJ/I5NGF+MI46dVJ7eripAZSFP4V9IEATJ/Kx6b/7P5EYrpL/bFIE83gptfJQ6rq90+eQeaBXvZ2hhasDPNvA1f7t+Q5OhOc7hpGBYRgNyfbrOiY59jqe/OOQU6zkwEgujITE2Vq2rREFUzpiI7ERBlNnmmZMKbfjxyqPkR8LI8Wp4zZG299UH9CyY39Q3IA0DtVV1UiujPTEfiC7L7ZfbLyOix4aAYhhtY0s8+1tR56PquB8rvto4Uq7p1YaYBLq35tHqixFjnY7PTsHH36o+/LyJfzsZ4nsfJ9wGdQnsDyB6ol6MC37EJ4qZMod9nDYwnoHF5/Ci59BeyHp31uHyR9qvEV4EP43g0na1JmiC+tdqK8TPEfFAD6Qlz5kdxV9qIacy1ydIcNwH7w9TRWULadQGt1IdLYhREXw9+wqmLdadz0V0Zl0IkJtUIcW7fj8fCaVZleKmPigmOxKEaR5J0KzL0QczjttV/mRyC06kY8eeX5AIa0eEZcqhLEcOuY+17I2036nne7LpZOpuQFOvFScKpCaAZGeSSBdZfg+blzo3ZWpcrNHRGcTvosPnpteXCbo5U7eLKvNY81Nv892E5UpzTVklUhxkYsItqXuZ+91P3yvopYcoF/B8/WbNyrHSITnO8ZxyngcwjomOfH2MSkwGKGwif/YqGzm4di3A6O/J1aBDOaFgTEcZeuPidlxGCQ2EcfhMudGj07s97HriQ3bVrPHxhb7fGy/mEjFpCw2XsfZYicnUjS6TmTg5OS2ymbtLd5WzGaqlr1c6vV0OhJMIz6WlQajj2qxGO8njOHTzQaePYMvvlD9ptTd/ntGBsUMiqWMnf2pfvlnOVQbyfm7CrbX8PJjePYzaLb8oCTnBjnctIcwhZlgXA5hoKGSwlP02n4oNambFJR5qTtDIBLZwE0DTDKpQF0uD8/8EOrLoFT5IZcKNG1FruYtXM65SYF3QW05Cf6m3OveFWHGHyLPDk6+ni6XwtMD60C6pr3IzC7npmWBd/IQTQPJ2QfSt810TU8OOsbz4CHqw/fLwalGUOtEmhqCXyWoObug8rSM38Xz4N1pXChGGMhY7jSOKhAEa8EwCT/4ehQ2K/xNZPHmuNZV3ghQ70fz8vdGeDIoZzLbV7nM3VPEgX2477lXKvpuUGYWjUzxz1ewasb7/zYgEZ7vEDFxsZTuPNcv79ijEvt2TKGITctxaraZd4/9LRY+smNZZpWpAscp6KagxIZhIxRmKrYwlm1TliOBsWNa8b/pdFQcrC5OXDvnWKk5zha7S8GKCynGoTgjSpblZdcxmYzHzTIRBsuKg9FHVFVv76Q/mcD5OTx8OBIeEJmxvx+7fzHxsc/FlJ/9XkrWJ5/oYRmAb4uUfJ/hMshPFCYqylA9eUAhmeCt6i/l01n9Apr1Gxxsxk0rCauunGdB2WkVvsh7bePzkIUVTNCZ16TtkApUeNRewilsVQXviw8FCDOvIoNtDcudJu9yUHZVFsaymYT9vKoxdyWchv/VRQOEsFKGyNEhhNl2VQhn5Qpj9Vmo7BvIUe5Fis4O8KLWWKpeY25ymZZ/YwOfTnSckwZeVlJsfCBk5aC2FFblunWwzUdTtHOjh8kR0tsdN73MqmEkOLkPJAl5gg6ZTOmngfD0hYoN9kMgE4H0NFFYq/XcFCnsverx5F5emvXw/fTXMnVnUkCdA5UUqcIpbOccN+1Auh58C/0ePtvBZ1td49uERHi+I9hEbz4Tm9hj30lciC+e/G0/W26IyZGRIiMKMQGKSYaNxUJWptIYERoGTbJWGTkmV6YgxCpMWY7ZWM7p9XQajHP1WPHYFJlYjYqLKlrauxGgOPxm/qFYJYrDdHGW2zHBson/8eOxAnR8X7pOx30bs7aqSkTn/FxELVZ3rKij3Se7H0ZQjXi2rfw7l5fw8cfy6pinKeGHgQtVgV0I0Uw3kE0U8mk9lGvwO3AXsN+8yYFyk4mVEb5DAjHJh0CC0OubZWj7oVC4wmdKK8/aUD+nF0kpQ1iKQJLI5E/JHEwa7eeNVAVDc+61j1XnvSkSGPxBz5chFT2QnGkn8tDm8Gin51VQegqv2kKLLnhvnLw7oGXPpvBgr+0uSvjxQeN70KolxbaQ0lN7XfNVqf2mvRScGlVhng6jJ2cRvDMdmvAnwKNeZOR5YEFNFpqFOqVrX4XvpmkgUSdhrG2ma2zQ/talHhTi6sK4svCo3ZiSPnNjF/jvFJm8Owuk6szQ9WeheCSZQnx5H3qB9bBrYbODq2vYtm+XugOJ8HxnMFOx/Sq3ifrYhGzkIFZN4nYOMQE5TjOPzc02qRtiwmOqkJGcmGzNZqPfxlSdOAQXj8sUn+NsICMcMcmzGj4x6bLsKzMY2/t43HYMM+XatVi2mZ07DonZeG18p6d3t8awfaZTEaO3SeWpa5Gdhw9Fduo6pDAHshMrYbF5HERouk7PV1cKX33yiV6nbKwfGA7VJEGy/jDVRFoCWQPlXgXiWEO3fnMl9QGsxPFNo9CgLrgC1d1x3Hhx8n40E/siTL6Zaqu4XopDHr4vqhaa0Durq7mpwNzW+vXfFmp34ZxCWsUg9ahuQ9p6BngRnrLX+10tw/Ek1O4ZHKxD+OqnV/LpNDmcNnAZTNDOKwxWDOHh4dVUxzjkUtuKQeGkea/mluiSVSV4UJp61Y9q1pWROQ8/akP4y+kzvg7fT00gJAs/EshlCFnNh9Gr0yJi0gcyU3qllQ/RMlOKzPsTLEtMnFSV1iuDK/5Ie/f9mJfzSsb7bMpNKvoEEb061/0tW/3dFz28ALoGnm3hxZ6bRqhvExLh+Y4Q+3Nsgo+JTkwqYu+KmW3NuBurPkZWqup22Cv2/8QhDpvsbILve71er7mpUROnh8cZX9aw1BSZ2GezWIwFEi1TzMiEqTKxidlUpCwba/ZYBWdLsYbxOEaA4to9k8mY0m5ExaopTyYiSKY6mZpl9zImieZ3Kcu3h/BUlVSd83Pd2+lUz/YZGVk2b5QRVLu+ptFnenUFn38Ov/jF26lgvRdwUnbySobO3MH+BNwO2Cvzir0ytFyo7/JGPqag7rhi9OtkFt5yIYwVMpGKPqg9HvIQVjI/iS8CSfLy6hQd7OY63upE5KLogGIkRBkhTT0UWAQRG6shlHuloa/majwJ8GSldPX1FB5t4ONzqPYKc32+1H0sB7ieRAQrVwhrW0id6jI9Hwr46Vbk5ZDL8HxVyWc16VRMsCOQoUGenYNTSvrpAFe5FJjLXOOugYedyMWOkXSsci3fZDIhz3qdY9nBhRtDXYdAXpwTkRk8XBFeh8/GI5KUBZ/OxaDzDJ6b9h65U0YUSOX5Ts3Lmb5nJ2VIQR/C306uz30bsvVO9iJ++15hy08aeLVTWvrbiHtNeGJPjb2PXx8Th3g93FZijvezOidxeCkOacWhrdiPEvt0+n5URWwyOx7XcfgqDnFY13Lgpv6M+VZs0mwaZf0YodlsbofcjlWm+XysX2N1hCzcFFdcnk5vh7KsAWpsojbSYmEaU4JgHKdlWFnndiN2pjxdX4+kzo5h12okcTLRddlnYAQhJg1Wz+ZN992yMNaDB1KmTN0xf44VqrTPJf7b67qxQvezZ8q+urhIlaXfKLw8K0NQTYoO5q/ChN7p17/rw0T5XU9KvwoyZFY2dQc95zBmaAVy4oOZdwikpehhmEipqcMvepdDtZOHp+jkeelrkZAcKKwAopM/xYjNvlb2VY+2XU20774GnIjPPoSplgdN+C/ncLYTQcpQBlfVS0Frg2KUI4KwK+DhHr6Yidw83erZO3jQhG1ykY5FK6LyshZ5OWlkRLYmq1cFPD2EasudlI1JMOl6VHDQqkzvnFQ+h0jLYhjT5Z/nUo882uDE6zqmyM8zcfDQwcswL9QuhLgGbvqRWUf1KpPKczWMyhKEvy1EtL4LTCZqi1JNYJJDXkrhKZ1UuSmqlt0DswPsOylMqwNcHngrigzehXee8BiRODYE3zVpWKgjXm8wpcEUmuPQi+1v27atMmBMwYjHcEx+4lT0150bbnt8bHIzFeg4zGQqiYWvjAwd186xid7OM5mMHhw7jx3D+5HkmDfn9HR8fUymrAfXcdFBI3HmOTF/kJEje2/HdU6G291OhMuuYxjGUJeFCo0g9f2ofhgpMwJmSoltVxSj6mVd598Eskxp4w8eiOjM5/o8LLXc7qttC2PxwKaRirNajcbkzebtzj57XzA08pnsFuqVlZeQhcqyVYcKAqLidCXf3aT0KyFnzMoKys7Nd1Gm9Xk/hq6sN5cvoZmIsBVBfe1CReR2Moah+lJEqA8ZXn04DplUk+1UKk85qA7PpIPZDqaNCFHdi1BNO213KEVwhuDtmfTI+5Nrm/OdiM6yVaiqy0IH9nBNBVJXXk7h169VdPCQq+Lyoh39QPNOPpRZSFlv0fJDJhXmMqhSL0odfxXCYr0PtX+cCNDUS9lZl/C4DRWUvfw/hREcPxKzbVBzKq9tW8dNywnL5ppkUkoaL6Jsoon9yztCiAz9fc1DWOvbiit5qe+leS7/zswBlRqWuhCurUO6/hCIXN+pdcRuJ7XnLeU77x7hiQmJ/SqG234Sm+BjMhCrKkZIbHKJJ+x4ArHXcVjKQlK7nSZpIzQxuYmPFxOgY2IUZz4dp6WbkmLntIwbU4Psi8tUjroW+bAwj5E3U2/snNPpqIjYBGvNTC0MNp+P98LuYVEo7AK36+bAeC9NaTDSZPcsLmpoZuOYoHWdjm3js3uzXo/HMgJl/pbDYQzlDYPex2Qt9r7EqfN3pdv/UJjNRHSWyzGUZcpWXDMpVvzss9/t4MULGZOfPUsZWG8NPPg9tAdwF5DPwS0hb/WrvrLSD5l8FvMMVj/0358T2bHqyTHpiZf3E8jCpNbORDx8LoUn94HYTIKqE8JzTQ0nGzjMdS+KQQQmH1SDJwPyPSy3oRIzIjldoaagzul52sHZFi6Wei6GsRlp1SvUVfUiT8uDVKJny7EmzrSTGtSUcDFRRtdJI+J1OdF4Zj0sNhr3ptA4mjyQpHCfDrmI6lkXSEQwKQ+ojs7Oafs8mJk7RJh2yBeEDy03Bl37Kqg8TRZSyVGNpmkgPQsHa0YStHQyLh8ITUfD9/DB/3KvrUl4fRXM5dNAmr6Nd8Y5mNVQT6CslY7upqoE7QqR3dNOpMcPKrlg2VmHg4oNvo3eHcM7QXiMGFiKcZzVFKspRjTi9Og4LBQrPcePmITEBMlUhbjir/fyT8R+mFi5OVad4sddZAhuh5jiX/mxlyYuDhiTM8tmsq7r5q+xSTE2Abetxl5Vt8NLpozASBhM0TGV4dhoXRSawG28eT6SJ/MCVZUma1OVLMRlzUdjD4+FnMwUfXam17vd+HnEHiPz88QtFSwsFhuk7e+jrvV4E4UI81wkZzYbSY6pVva3bfcHxms1VeezzxTCWq2SMfltg++gWUHzQL2q/FREZ3ot4+6wD8XmMphmIhA/aGQ1DmeZshPCQ2aUdWESt9o7Odz0cbLu6T7jpmKxZV3lHg5TEZ/ZWs/lAH0gUVUH25nIRQY33c/JFI7xGZyEcFXe6/WhUnr2pNXyppAi5BAJ21Xw+4/g9DAajLtMXp3TAzeNOS1Tax5CV1cVOK/ty0CoMg+PD0GRCIrMog+hr0BSpj28KEK4zsuEPPcKac2DOToI7lRB6ZkF5eZsEFG60uGpUcf1qtf6jZPZeYvGODgR48GLRNVu9OzYs/l+1kE5sro8dSBB3yZkOqlCFKCQwjPPlJ2VlQpjla1CnUNQ8Ro0zu0A+wOsm7c3nAVvOeGJDcA2WZkfI54sYrNwrN7EKeHHoaTY33NsLI5DV4bYe2PHW69HUhGf764QV0yK4tDbXeuOyZjdC/hl1cKIiaVoGxmwe2AEwSbJptGku9mMhl5rHNr3t9WZ3W6876vVbSPyfD6qLNbSwEjHZiOfip0rzh4zQmmfS2zetlCdheJMrbFrM2XIe53Twn4xwbF7YZ/fcTq7EbAfWh2ZTkdFJyY8ZvqOq1sbmTsc5GH6+c/1eBPjTvhq+AG6a/XF2vwEHm4Bp4mh2IXeSrUmkCaET65/wM/RlBxTd1wOWfDykAFlCGE56KeaFFwmXxJl6FU16JoyF7LRgsG5K6T2ZMB+qlCMdTwvQk2bslPRwWmoorzY6ThXy9CSoJc5OXN6XhxGklMH428xyNuzzmVU/sk1fHai82xLONvrGlY1nO+5aeuwC98Fpwd4OdG6YlBo64MtvArVnZ8G8+3EiyR9UWnZVSlC8zAw1A75c7b52DsLNzYJHZxCP314blFml/e6jrkXIdhnMkX3Tvv5QFSCCKYqzRnQi1AMXvfWI7Vn68fJu0WvrbfWmm9GqKtc6s68gFkO0/BDLKt03CwTkR0yhRiLFtpOmYjrDl42qiX0Nn9FvbWEx9JzLV03fthEEWdDHYeNjPzcRWZe9zp+NsSp2nG4absda8iYofaYxMTnuEtJ+jI16Hhbw/GxzVxs4Z64wrCRBlNpYtJkLQjiCdQIj1Vg3m5Hz48pE3k+hpoePRK5sTBYnosYffSRiEhcmTkOrcFIUqxI4HyufWMjtH2+3msMZrhu25HgxKEgC/X1/WhOjosgmqpkdXl+KGSZ7t9sNv79ZtkYfjQFz8Ztitp2C69ewaefJrLzVmOAbgWHAfxOqo5fyLjbTcDt5cfoaliWoQt39wNNDA5uqisX+qVuCg/299crTNVXqAhhr1CWy6BswNejMdhXIkJWXbfPRX5wuu6mkInVMrAWoffeYi1CNBTBFDzArNHz9UIK0L4WyVkcFCK5nMP5NpyvCcduVZiwKeBHK5EuK1DovM477YKvx0n1mYd6OpNez+UAlyib68c7+GwKf6WCBwdt8/kEfmujrKt6GOvk1CG8VQ4qute70BG9F2F53MFnucbiw/2a9SI5S69lL52IS4OM07WTV6gIqtQuzAmtE9HJnMiPyxQq2oQ/mvNMfz/bQKCs91qGjtX9Cn9cOTImT2tYFLDI4YQgNOTy8EzR5zwNRLYPClbZKETbHtQzq3/LPYVvJeGxUMlyOZIc857EKk+c+h0rOzbB2kQSKzbHZCf26cRFAWOScUx4NhsVerMCeXeRlWO15i6i8zpF55gExdvFBMhCOBZmiosNWh8pq9xrxMAIRdyg00iTPRuhMTISV/g1kmLLLIPLsrsWizGsNpvdrvNj5KWqRjIVh+dMKTLVZxhGBa2qdAyrEm3XfHk5fvYgIhN7o2KjdFFoTGYA/qEwm+naptPx79Y+t1hpNAJtRuzdTmnnm00iO281go+nCenNXaFJpK2gDgSon0G5AyqYHuTd+CG6XJMztpHIxvBVBvLrFEA2hnoces47cCFjsDwEomP7O016h6lUmxyRpvleRua+hvogI/OhVmhqF0LaVadMryYQp9UCHqwDAdrCLx6L9OwmIkHPT5Si3hajj+hQquDgvNFYfSA2T9ZSz2YdPJur0OCTnbZpczhpgxITSAlOrSYOuY676FRtednDp1MRifNGHcCLIXQ9H0RyTnq4LJRyPgQStMvh4aDwVIPUmiYTMXCDSM9AIE1BoZkAnwfiUweFZhNIURm+HxoXVCGvTCwLYe28iE3jRX5mDh7kCnV9nbCWQ+eb51BWMCvD6wKKSuHXrFJm2FBKFaw7kT+8Ckpee5mU93vYtLyRbim/Ct46wlMUqk9iabtGcuw5VneOSUlcIM/CGxbSiMMpRhri9TEBMnXB1sUpzX2vMMPFxehreZ0q83VIzV3Lj9cfq0X2OvYxwe2ih3GV4pgIwu0QShzuMiXEzMnH4TEjOKen+gO38FHc98mOfTxWu8fX12MYzFpuWCgu9gxZV3YjKJtN+PItR3XHQmagZeZFMn+SZb3FRmlTun6oFPU8H8mO/f3GIde4urVdgymIL1/qkTw7bz+GBnaNKs2eXKlgG3BTuyavpfb4UqGC0/4HMi+Hyd1lIj5WbNBUHxw3NXgc8uv4grGLea7J1EJYzgWihLKsulqvD1MYKl1fHarlDblIUFfJs7KdgetCdk8uQni+FkHMOjUTLXutm7QiNrMGNrVUn5ODiE1GIBiVDMzzg5SPda0srjZXajoEz1Aus/PgpPwMwI92ajlxWen6Fl2oLeMAL0JSBuWmDMcZwm37RSiK+LhVjZ6yD+GwEH6z6szXmdY97qTWfJEHdQhuuqWvHZx6Hbd3enRuVH46pzGs0TIQUfYhxFW7EE70Y2hr5kJBwy/5s6iBZSZSU1VQV/obzUqpOnl49qVM6FUmsrUrpQB2aGyugeIAh7c8O8vwVhGeLJOyY+X2T0/HUEpcgwXGydh+EdtEcTjc7lBu9XK6bgxDxZWHY9JjSoOFgey9bQ9jaMTITtznKg5pfZWP5+s84JcVqdjTEy+7q2BhTPBM7bAJ1giMXWucSRX36Do+RtwV3dLCLUXeQkaxOmPkxIoenp2JzMRmaiNKzo2fl5nTLbV8NhtN2bF6E39uzunvZxhEpuw67e/GxlfXWv9DEB7z7hynn8fXEP+dWWju8lLZWKlNxLsB38LuD2A9h+VDqRNuDs1MJMIFZZpa1YAXnTwe2+9zhsiCglOOyo0VHsx7yMK6IQtm5Ww0JlsfrXwAvBQgn2u9G0ZilBFMrDlMg3nEUtvrFjZzkZ1DocnfChvug9JV9mPadt1BvpFyg4M2fFftq5HgbGoVIuwzjWHSydMzbzUZn+9DkcCwbHA6/jaYjvcFrAtlcE17pbXvclVszrzSzpdtyEhDtXgap7DSSas2FL+5k7pDrvO3geQ4NO5VruysZacQ0DaT7+ZB8OPsQxgMdGyc/Dd9UNieOo37KqzDKSQ69WM/rV1QdsLHo+/ccB+roA4d7vjbKpAReRrOOS2k7pS1/kbr8N5CWUXPjQesDH8H3QAMaiWx9XDVwvPDrxZGe1N4awiPcyI4T59qUjw9HbNa7FdxXKV4txsf19fyOljmlKVX2y/+WNkwHIcIYkOyjed4vSHOGLP3xzV2vky1+TKPz1epPcf7xGONQzh2v4x8HFdIdm5UO+KKx3H4zlL6+173dDrVeawlhXl+4jR5524XAswybWPmaPPPGIGybXY7hdIs7APj2OJU/+l0bIxpRfqMuFidof1+9DXt9yMZNJh/5vuuTpxlY0j22KgcF4a0e7Hfj1lZV1dSEVOdnXcEA/SXsLmC3bn8GXmv0FBfw2SvCTsvNSEtMnicwyfd95ix5YJyE0JWzpScPHh0CGP0Ii+ukHqTd9rHGoM6xudskKozTKFughJTw3IN23koQJgFJckrFFSHzB7nlJru8mCI7uUB6koRRFCoy2VSe+YHKTYOuJ7B6U7P20q+HefhixP5eta1lJBdOWaVNbkIUJPJvPxyCh+utd9ZA9ellp81CpHlg+4FwHmrxqKFhslpJ6PySaeQ12URUvCDilMBF7lUnCdNqFlDIIRO2Vs1Ig0PBrh2UoHmvZa39r3rVJhw7RT29EEFsu/kHhEL+5uxjKgqfN47P5KZzo+enspJqaqcCI+ltBvZqcLfZlapYWhR6m9iiu5Xj8hi1emcZVAzdx28OEitfBe+qt4awjOZqAGkKTvL5RgGsPDUfj+W1b+8VPG11UqE53XE5lfBlxGiGLGCc+wh+jJl55jkfB2CFG9/vPx47PHx4lCUITZ4m9fFxh2ThriInxEOy94y5QZue4Lie2OhKlOO4utdr0f1ZrcbTdB5Pvb5Wi5H4hqnqcck1khaHJ60cRmZ2e3G8ZthOvYqmRr4faGufzmUFX8GcWgtVihXKzUBTRWU3y34FnYfw/VTmD7Q5JHl8re4AapD+LEwk8mzdvAwhy++r9BWjlSePDzikFb4UWEKQhb+h32hEEZmpIWg9pSa4B0w3UI31bH3cykjONW4GSqFqCZ7rW9KKTCLkLmWeR2/6PWMl5LjnEIyk1ZkqOqUsTVpg5qElKjTvYhQ4eHTU24anM4bnafL9ZiHGjv7QqRm3kK+V9hqn8s8nHl5eg55qMac6z4UHr6Y6HnZaVyll7em9PCLaShe2MPLXCGqzyq9f9hLMfroIC/PJpOqsxxEcHpEbvygWjsuE1Eoe3l9dk73fRFIzwUKHU1cKE6IQlEMUnCGQISK8Dw4+YeWTqHT2nHT0qIIr0snIpQVUIQfY3WpkGudQ16IdNWIeC7QZ9llInhF+P5tO+gb6A+qxfMu4K0gPM5JzTk5GVWd+XwMF8WhqmfPVHztk0/eTPG1Y7ITk55jIhOrPnadMQH5uurOXfvHoa2Y6Bjiis1xxpqpOEZgTDWL/UJmnrVrsFDQdqvnyWQkKRbWiuvj2LIs0z6xp8bUoDiDK84mc26s3hybsu1aLdxl17fdjuO3dhd2XbFHyUid3Q9rhfF9/g2ZWhUrO6bmmPpmoVLz8Gy3UneurpK6885hgO4VrF/ASQ7lT5TJVA8qIJcXsD6TL4Ud+JB5t3Xfg4E5qDvYj6wsPCqg1GIHyt4KoZSsD5Yf29ZpEswRQSk77YuDei8S1dk5epGf3I/EqCukAvlAvHIfFKRBZuWTbWg1ceCmRk8fwmZtCasZTK7h5VLqTt3p3JuJVJ0fXcPVTASnzxSyyhBZWk1CJ+9B215M1ffp87lS2B/v4Y+WUqQeHFSI8JBpkrd6PrvgufliqpCXhcZWwUC9y+QN6rOxQOEsEKaLQubpIag4hVPIqkTEZh4+pgyFrvJM9+Y0qDqNk59nEt63Tp6ddlAoq3AiTxNUuXsfhbdqVMsnJ6rE7EV0KiM7jKqzK6VCLnKFzvIcCguH5rAqpWqVLWQNXDoZufcetge4eEfCWfAWER77NRynnpufoeuk4rx8CX/4hyrC9qYmg7uypo6VneNre11I61chPDGZiZWbYzUnDmE5d7sHVoyYCJkvJh6TEQ1TdbpOhHS3G2vj2MRtBmS4rQ4ZObH9QZ/x4SBia9tZleSqEpEytcP8LlaTJi5kCON1mQ/IQnQxuYtLCZhfxsZvoaXvQ0kxonMcxrISBvZ3YkqXhfSur0Xq33TPr4RvBt/A5vfh6kyZSvlaE027gHoN0wGuT0NblUYpyycetsEz8p0hKDouhIicD4qNE7GxDK0skBAfDMfW3DPvgpl5ELExEjPkIjKDA4rgu0HEpw6hsNyrAKEPYZ8u1PnpvTK3mgyevtKxhuADulyq6OC00cS9z+DxSuP74Fok53Ku8Q0Z+A5eLmRannRwMRN5qTudPx9ULbkYxk7pTOB3LuHzmTw+0+Bb6jL4yRaeTQAvonIIBGgdMrG6TJO8G9Rs9CqHjxpd0+BVr+e8Ucjr80Kq0CFTXZ+Zl5qzzhUimg1wmQXlyin86T2cuDFVPQ9KTxsUONAxwpBpfTA6I/JTo3AW6DMOnnnKsK4M3zdWz2dWQBZ+kNX5qPztpyr8aO0yzoPXsS+gaqTq1AM0e1gf4HonD887IvCQffUm3z+cu/2rO06ZtowVSwW/vHxzZMcUj1jZiYsdfplJ+ZgMfZuw1rHP6Phccf2aOFsLRtXDCJKRI9smVqRAX8yz2eidshYQcNsgHadZW9p3XDbAxmO+FgupWTsM63Nl2VnWP8oamTo3hoVi43XcOd2M0Zb1FRentBCbjclIiB3ru4YR99cVybR7bWE7q6r88qXuQ0pDf0fhoV/D6gp2mxDSqDThDxMYFrCoYDGD2VK/pB/m8Ci/mde+G+TcVLEzZccFFcE5FOrKREqGKdy0Q8/GbKu+VijLhUnXlJqyldqTIcKyPQkiT6WMrKaGqpUqdKi1zBqIVq1IyMtz2FtLm0r1eiatwlWZh/ONFKDNVNla5xspJ10xqj2zdjQzzxuFrbzTdjZmHLyYwU9XIkqrSr216kHvq0Hb9JnMyhna97KCV7Xq6FiDUNsnB847FS10bkxlvyrh5zW8Ctlvq1wm51eFjM0ZoY4Noa5NGN/SwzkiKRXy96ydyMo0kJ8iPM+ykMFFqM+DyE/PmLE1BDJkKew2nTqkGM2c/DquAlcHH08ItVKrO3te6G9iW8sz5UJIrgH6Vo/dHlZ7nf9dwVtBeGwSPPY32IRsCsFu92azVmJic1cIC0YydqzImHH2mJzYtl/2iM93/DpWduJ0cJvg7R7G28ZeJzMzmzpi1ZONCFmYyFpGHA5jnRwjpvv9OC5Ti+bz0UsT100y8mKk6bjr+enpeK/KciRYFhKze2jFCI1MWBjLxmv3IfYnmZpk124E+1iV+7awa7HCmced4g2mXlqRwasrme9TGvq7Db+H7V+BVxu4KGE3wG6mib9bQDGDYg5uCYtSk9PSwYPsuyM9N76dYlR4bl4TngfU8yuoPM5L1Zlec9NmojpoebOAdhqKzlVSanwesrO23MwkRR/6h+UwOciwvFwHguT1mDRj+vl8D6drvS4GuFoEJSmTYvPkOihAC+1jdX/aQttYavpqCs8XIjCfnMLZQdlw8xZ+stak/WSrYz2bw2VIp7fsqs9mgRg4kaJ6gB/vRWRe1Xo+6cc6PpkLZm+n5asSag/nPXzUimv2mQjOk6CC5U7qlg/fTYODMz+moDdOYbETRmUnC8TnEN4fgMtgWu786MchfAR5RIKmWfDyZCI6JYytRGqY1Kq3c5iqTlKdwemgFPQsl3/nehLaYGQh9OrgGth0sNrB8zYRnl8ZFqqAkfRYOMJCI/u9Hm9yMogrOx//Uo8JyF2qzpeFsr4qxAW3Xx9PnPY+rkNkBMCIiZEfCxMaMbNwWGzmtXCXZVMZ6TQSZOTUjlNV+mzsWHFtn74fPzdTeSyl34iskS4jVEZG7Dh2LDMv57mIjakicRkBqzgdlxuYzcbPzhTEuO9arCh+F7DQrIWvbGyxymOfhRmxNxsZlVORwXsAr4ytq78Ir9bq4XRwsD0LE42DbA7FEjhTddtZpuq5D76Lb+QMzd4Z3NTgycD1QA7DTAqOCsyI3GBh8gK6Wcja8lJ4rFloN9X7ZhaRnZ0UH5+PmV99rkl9s+Am88mh4+9mWn+y0dgOtdSfxU7L1zOFVLoCvjjXpIuDsw082OhY2xo+P5epuc9FemYt/Pha656s5dmZdvDpSZiwS5GefamQ1QdblQa4qhXuOm/g+VRKTOGVVbXPRUq2hWr27HNVWB4ydVF3gcBsi5EIOacMrs6pBUVBKD6YyZNTe6Wpl4jsbDPV6zk4hZ7yQHrmyJtzCMToPJOiM8lkWp4EIuTNu+PHAoRWtLAL75dOqs00CxlcGfgpuImUnmk2pqG7Quep0f05aXR9wyBi0/UKxTY7uNiqeei7hLeG8FgGDdxWd+LKs9/H5PR1cRySOlaijsnLMfE5rvIcqzFfN5R1THpiFen4eHHYyybWOKxlRMaOFffCMk+LbWP7GYGI2xxYRWdTcCwzykhMnA7v3EgG4r5YNn7z/MSFHtt2JClGhuLqzUZaYsXJfEBmbt7vb99L+5sycmTp9t8FLMRmnqTXkWQYyXzbjqnoyah8T9BD8ym8+stwsVPhuO1UCsf6kVKBp1OolpCd6G/jYa5U9bNv+60c1B2cVBw3iGgRMquKnTKWsL9F++7yeu1LEZt2JpLjvLadrbQ+C++X13CYhcdUqk99gJNrhbrIYH0iA7KFs+pWBQc3c9XhGTKFtNoKLk5CRpFTeKsL9YOKQQToaj6qPyc7EZldJdKTefj0TISmKeXvcYwhL4eIwyrUQfr5qQoU+gx+vIVNpQl+Okjt2ZYjiZkOqsjchPv1qIEHrchPm4XigIHQrAoZmBdD8NXkCm2dDFJ7rnJttw1kFBdFH53CUN7Bs6DqzAMBugrL7bFDxRYPiPychL8Zx+3MLPtTmjoRmtJBMYVlMCk/QIRo4kRyfaHPP8ukfg1hHFWr+jt9B10Lq0Pw7rxjP87eCtOyTXw2oR3XxLHwjPku3kS6buzbOc7Seh0pOQ4xwe2J+pi0fBnpOV4f4/gcVmvH1JNYMYgJGIwkxciBc7fbVZjvJg5/WcjLjMLTqUiFtYsww/nhoNAWaF2coRSPMw7LWXsMI8AxWbLaQLEB2cZpBNnaR9j5LTxm47d7ZCqTqUexKvVNkWU6t6Wix4UGjZTFhNKuzVSqN5F1mPA9ooXDz+HiMdSPoF5qsi0LmKyhmkl1ybrQOPIaluhXee+/ReaWA0vFuemQHrImXR7MyZnCG77QCfOW0eCMVJ9s4KYdhvOqvzPdi3yUHRzmIjllIxJV9nB9rpDVfqFWEZkPVZhzcDspOftM4b2Dg8NEqsG0UbZW3YkAbWaw3MLHT+HhtZSiYs9Ncb9Zo7TsSSdPz+/9CJ5eh4KEfmzgOutEMKowec9aWFfKujoUqudzVasFxYuJ+mo92ak2z4DCWR9udf3PKqk/ba7wU41IUDXI61M4kbNNIT9Q4UODUDQufMjk6sdKxXkgmaUT6Tk4qUunTp/PzgWvjtP4a6eQU+5hP8iv03oZllvGYoT2u8nZccLyZQbZBJjIqH4owt9EIWLnBhm094HgDV7L+gH8ALseLlv4fK/X79rX1VtBeOxXbvwrPfZhwLiuqiT7/5A4DlfFv9iPM6aOVSDbx9bD1/Pv3LUuHs/rSJGRCBgnWZtojcDE27etSEq83Llf9ulY/R0jRmY8thR0q3NjZMTObwUK4XYavI01DgnG47Njxfc0TuG2a5pOx5CnKSamOMUVpK2Csz3izysOn30bxA1CY4XHTNJGuCxMZ+G+9VrhrJSZdf/gd7D5N+HFvwPyc/GQE+BwGrJnWjgsVXdl24Hb6Ff9WSaycPUNFD9XMhYcLBmrLVuoy+n9UGkyvOmEHjKxyCBrta6badvMKcUcJ/LRTINicwByEZg8GJVxyugZCvl3pqG9xPpUCkhbKaTVl1J8ci8D88lGqs6+htONiNXjK92zsld462QnMtjlQb1w8Nk5fHQhIoIfvTWv5vITne00MTeZsrkeb1Sj58kWXk3Uc2tbSMXJUN2efqpjTTq4DuRsCOss/7vNRELMz0MgLUMgJzYOottuv9W7EDrzTr6ZxsFlLnLRIIJxEghOH0jPzqm2zz6QHGfHtR+DKDy1GaQA7bwISxnG3nod+1ENWSXS2+ZS8ypEenZVUJEIPxJbXfvaQXEQ6TxsZVZ+2xuF3oW3gvAMg770LfxgRlQYiYZNHNax+4f08nyZmmNKzXFGUqwswO2J/XWk5vj969Sc47G97n1MtGKyZYQh9pLEVYpNFTLFZTodwz+2bUww4lYQ5ukxomEhLgtX2udrWVyWJg5jjR/zDlnYy1pR2Pitno0VGjRyZsRisxm7uJsqdWzwju+lXbcd75ugrm/3zIrT0o/N4nZuC6uZOpbCWfcQHvoruPrXIft3QfFUk0jVw/4UskK/+AevybkZ1JfoEQqBZIj0/Ep/GjGxcdyYlkHPLnwvxBlbPlP4qkCqUzsLKutB21HIo9NMQr2bQeblvNO+PhcRWWzk8bH2FIdJKE7oRJD2MylAXSnvTgacrhQmaSoRm+VOZMdnuid9CM/VXajt04r8FIOyuvJBmVxdBr/xAv7wETzYKvSVefj8BH7jlVSWJ1uRkTaHzxeBBE1kOj5vpAh1Dh4epEQtGng+Ue2cR3td96tSpujrXISo7qXq4GER1Jt1Ma7Di8xkQZGpndSU2sun49xYOTkHTlFtnheBOM1srglKUJ6FWjxeatAmhBgPfjQQh9PepLdPUGPRYQL7E+iW4TMvVEW6CoSt8Poc2yx87r3u764Xgbro4dUe9t27p+7AW+LhgfFLP67MC7fJjoUGzOD8Q+E4vTxeZhNzrFIcm5aPCdKx0nPXuq9SgGLl5nWkySbQOCwVHzs2I1toxa7PlB0jIFa8z8JKZoS2fWIjctyzLMtUOdk+V2v2aaqL9ccyomKkNvbemAI1mXBTkTnLRo9PWY5hLCNmp6dqUWLXb8+xb8gIh31u39QfVpa6RvPuxNlZsbJjn68V0rSmqNfX345sJbzl8NBfwNX/Cz6/hOcVPH+sUM/hHDZPYbKA/BT6M8iCsXnu4EkOj7KbDPOvfb6bthIhJHGTtWUhqy4sz4A8KBohtNHPpP6QjanplrLui9BaolTxwT5s55wIztVDqTkOqT15mIydV9f4uoH5bkxPd8jPgwtqzzCSmXyAi1Pt3xXy9TSFwmNWpPBQavt9qfc/fyii0eWwDIrUh9cyL29qEZCmUPHBWTDlPpsrLPVyGn7k5fDzhVSfLoSPfmMTuqwDTw8iT5VXe4pXlZ5nA3wy0fKTXqThVSmF5nzQPmeDbuXDQWRkk8vPUwPnXtv0TtWNfwT8BF1D78ZnC4f1iOw0gegY2cmC0tT7sV5P6URmJ4VIT5kptf5He6lHfaH71weiUzZScK4KOIQs3n0H2z282qmP1ruIt0LhiX0MMGbiHIezjOzM59r+h/hFHBOaWG16XZgpVk+Ojc1xOOeYrMTH+LphLFt+/GxkwMYQk5q41YKtN3+LPZuXxBQWO4bdjzgTDEY1K/YBFYUm87oWAXJurL1j208m4zi7blRarBAhjJlgRqjyXKnbcddxu6/WOHS7vd241FSkmFjaZ2jp+FYQ8VcJKznHTed3U3bidHTzM8WhujiMZ76d1Sqlot97DNB+Chf/Cgx/E/hH+htY2P/eUh6QkwGuPFSXMhbXPhhOB/i8VzjjS5EjL45DM+MUmNxWeXwVfv0PwdvDSIqyAap9MAovoJ9wIy+VjSofU3Kj+Ew3CsllXmGs3r6fAknJOnl5yOUByUP4zOrydCXM11rmXTAgA2dr+Gs/0fODlQzNmwnsJroHyz2sAzGaNUpTP9vo+XQHz5dScU52IkN1H0zKTuSmCTPfNihh9QC+k3Iz1PLenBzgFwt4tINfzEXgLms9Tzsd66xTOGo66FhnnTK4Vhk8aKQMbfNQA8jp+qcd/NVayko5jHV+egdPgy/m2mnf1une1k7hLBfuU+6UbdV5KS85IsnWVBS0z8TJt9N7EaSmEpF2KKQ4CcQ3H0KvrBaKRkZr14qgrnuloV/18GoL2+bdVHfgLSI8cTPQOAxghuXJRDVZ4saRVnH3+8SxMRZuE494uW1/PBEbaThOTT9WeGLDtuGusJYtPzY9x14XIxVxlpUti9UnMx9bRpyRAFsW72uhK+tvZaEqIzi73Zj6bdlVZiSG28ZnO5cZpK2CsxETSy3P85EA2T2aTkcCZWnuVqfp2ItkCtXxOCzUZuG3+J59HViNIisweNwNPTYrw6hKWoaYeXfsbz6Fs94DDNB9AVf/GvR/A3QfSjFxUzVsHCYiCcvwK3+7gmEDvg/9k4BXvczMr51wcvStXoIL/zOuD2QnmI/zZlxHCHOUXqpPhsbUllI2ipB2ngXFqKvDccJ4DnW4BqT2zNaBLAWiZL25XAZkqjI922mC7UqY7XWurpLCc7aSn+fjH6nwYJ/D83Ot8zmcr3WPcq8QV93BroaHK6Wkr2uRiM9P4dFaZKfqdV3TTr6eJ2vV2nmw1ST/YK/18w4+Xaquz8O9iMp5o0rNs3APD041efaZFJ/eSSUqerWT2BQiC9kgledQKDS5diK3mZOK8nDQNWxdMAk7tY24dkCve+idtp859fHqnUgMTiTrZS8icxJI0HoIqerIKzQAq0HbWZHCotezy3XtPhBMF+aeXSYlbg+UBzgMgex00Kzgeq1srXcVbwXhgfGXeVx8MFZ2jkNbcTuD7xOxwhPXbznOLrqLzLwumwu+nMTcte1XqT8xYmITe1+O3xsZs2KDVihwsRiJhxGBWJUwTwzcVo3iDCTLpjN1qGlECtp2DHVlmdQNq8MUp5vbvnZsq8ZsKpqRQ1tnfxdmoI5JpJGNphlJmrWxsEKEVttnv/9ylcdCbla08FjRiauFW7ZZrHzBaFZ2TpXDLXSX8B6gh+4zTRz9nwL3G/o7mC1hBlQLERwPZDmsM5GIppeReergWQ+XIfvnGM5+gPVoxjNyUnCjyhhZsjRkl3NDTui1Te6DuhOITj8LPpzQUyrvtV+904RNBotrqRH7pUJhZShAmHUqYLhdqm7Pcq1JNWs1+ebB29LnsF5IDTlbiQhNGoWs2lKZXLlXOMcKEzallJ/1VKTnyRo+OYc//TG8WGj7XRUajvbaZ10rU2vS6fraQl3WreHoVVCXH+5EjCZdSGkv4elW/hzvRRIrDz+bK/vrtBGBydBxV0XonZWLhE17GY+NsDgvYjId1H6iR4pNF7YpHDfVmOfoc924UJzQwTKHFx4uhvCZOCCQYe/gehh7Zzm0vgh1lSyLb5+H0OIQiEwXmpt28DKTEX3Twu4anl2qncS7nEn61hCevlemygcfjJMGjETDJpX5fKxOax2vvy/YueF2SOdYwTFiEJOe49o78MuEJSY2XydF/XWhrLuIlJ07DknF2xjpiMNatsxIS5zNFPtbptPbISYjTqbMmPJiClKWiURZyChWlKwGThxis+wuIw3r9Ui0DPv965U0qxwdd3y34zk3EhpTm6wGkX3edxGeLBvJjZmjJ5MxlGX7xsUGbb8Y5jvqOpG96+uk7rx38DBcw+b/DZ8M0P8UHs8hL1Ub5fA41FIJnptNBv0aaOX1+CCXkPPiLjNzRiipi8hKgcJcXQhf1eBDqQirtJw5kZfqWsrPUIlQkEG1hmEqo7VN5D67sQmxXyoM0pewW2hcPhMh8plIT1MrTd0qLx8mIUOrUZ2ehxcw9CF1HRETn6n6r8vg8lQE6PJkzBSbhDDW7KCQ1nI3elCqHp6diixc1CEE5EOGVyBLP7mGV+G7Z9aJzByCifrRQenogxNRaXIRpY82CldtCjUXbTNlbT1qpOgc8uAR8jqmdWlf9PCsCKqLFykcgv/HSNfgRHjaMP59IEVmPO8zHXcSlltX9crCWuFHYBl9/1dOy68c/FooFeLD3LQr9bfTh2ssD8pga3PI9nDooGlhBay28OoaLjbvZmZWjLeG8Hivie3iYsxuOT0dJyKbUOZzTVD7vUypz59/fxNGfN5j5elYxbkrVHVXVpYd966ModdlcRlet+4uIhSbj418HI/BxmGqSLxd7HWJM6riKsaz2ahU3NU3y87jvdQ7IwqxiTquuwOj0mRVmDebkeTa8ezcXTeSmizTOC2jzM5vviH7DI1sGLE7ru1z3FPMSFxZjsTGVJ640a2NOyZAdl12LDNJW4Xo3W7Mdkt4/zCsYP0X4JNraP+t0D1UX6q6AUqlGFeVMqOmBRxW8vWAQlwNUnqO4TJwk6D2BLXTz+ShuQlhhF/1FPKsuFyEwVoTDJVIQrvQxJp1GlN5kJqwP5PRueo0idR7KUJNLRUHB+0Eqq1CWNtC6ejkcH4JF49gF8zKqxNYhlTxrlCmVpepDk9TwQcv4Wops3PdBu9PUE2KQcd7car2Eov9GMIqeqkwpxtlap3stc+PVnA1kYn5N1/CZwsdZ9HCpBchmQePTpdpPG0Ov6il5Cw7EZDSi6hcVqrbY/6kqVcT0aFQWOznNXy4G8NMtVfo6kGvZZ1TtljZq+ryw0Bku0Bq1pmUpNIpfXzr9NkXyNfTob8VMylbhlaGChPu/ZjKPs8Ueiy7sQ5QEbxG5R5cC+xg3ytEtrpSf7/Le+IzfGsID2gC+vnP4eHDcWKAcfIwA2yWacIbBk2Gq9X3M56Y4ByHsO4KOdlrQzzZHR/v2GvyOhXndef6OqEte2/mYyMVNsHaH3BckM/IiBUYjH0ucbuPshw9O7E3Jm4hYd4Ua2thrSGMaJiHB7StkYi4lo8RG1OFmua2wdp8PpYOH2fzGfExpSpuY2HkJm5fYeTGCHeM2Ohs/p3pdFR1LIPM1puHxzLOYmXHSM5mk7Kz3nf4PWx/Dz5dweFvggc/hbMaigN05+CmUE81oXUFtCvY7xRy2PlQgTc+oMUvTILJtcz14C1EZWSH6H34/3dBBcg77TpMtL9HpOZwGvo85TDZwmwTTNCZwlTWoDQfFLIacticyKMz30rZ2c9Um2coFL4repGh1Qk8fqFtmlJZWZNGnp6fPIOXZwqh9bnaT2S9uqyTqV5P3XGTol63IkAPNwphPV7DaiIVxyMic7aHP3qgOj2nuzEUtK2kGjkPn81FKB7sdGuXraon7zKRknyQ+RjgZS3vz3mj4zeZPodHnQjfMnzvbXMZp/PwEbWB7Hin0FWJzllHH+fBaX3jpP41TmSpcuqB1Q8iNAMiPvFUUDjYBgW+q0R6u1xjyzsRtnaAeq3rWpXQ7mC1gRev4OqekB14ywiPqTyffQbn52MYAcaJzNKPLaRlKc/b7Xc7lrtCTbHqcVdrCSMNcZglzsqJr/PYr2PLv8rDc9c443PCbfICtwlOHM6y16aUxKGmeJu4l5VtH6syccjI+mqZGmedwO3cMYmFcb2NxdQkI5mxEhObrOPaOpbmHd+nzWYkIs6JUMWfkylIRtLgtgJ1bPC2+2nqjhFwqwlkXqKY7FidovgcFoK1dPT78kWS8C3QQfMLePZ/he1vQ/sU/KkU7nkBdaFJnFpKzWQF1QbcVj6Ndcx4HJolPdyU3A3hVdejEJeDfq4JPYMxgytMglZ3Jz9w0/QyA9q51I+ilbKTAYegABUdzFfBjDyVIbnolXo/OSiEM93B9TSEy3LYLsLxdnB5pu1fPNb4TlYiNtdTha7KXstfneoSu+AfmjYiR58/1D16eC0y1JS6BWUvE/IuvH+wVRhnXcP5TiQJr9YS17VUoLODUtQXB3VZ3+V67IM6tgmkqe50r8zAbOTlopJa5JxCXJNuNCdXnZSsk15KTOGVIdahbRzjd/pFBnOvR4aMz3n4rDIndakJ23ZB2cnC53XwejTh2Yd79vIUqmAo3xXyD2WNXq9qaPci1FdrePZSZGe4R99RbxXhAU0Az57Bj388ZgRZHZa4r9Z0KpJT12No5bsMDcQm6Tj8YxNzPCHbMnt/V2gIXk9gjkMox9vGeJ3qc3wOuDuMFRt64/dx6nnca8sISGwUtu1NXTEjcN+PRMNUlK4bVQ7LtooVFbgdArKigRY6i0mJfQYxkTMjsik21tk9z7XOFBQzPceGayN45v2Jw5RGZOJ7Yvd3MhHRtvPEZnojO7EfyQilKTzbrczKm00KZyUE9NB/BlcvYf8RXP8p+OApnBcyNE8uQyiiBlcpfDSZwuIS1ltuZB5nqg56dhUiPLHi02uSYyKVJXNane+gO1V4p9wiMzPabyiUlk4VTMaFJvuhgOkayGC3VKgkRx6erlbK+VDCyZX2n26lMuzn8v7M9lJ3Jgd48gKuTsP5ck3oJ+sQagvqxWKn2jyZ17L5Di6WCmOVe2WN4ZTNZU1DvziVx8f6bOF1DVWv0NbioN5ZD/by4fzhuVSfTSUCsy3gyUYKzoupCFHjRFIypLyctwo9nXTwWQ3Pam23LdRM1A0iJROnsFrvFBbrUB2eYVDIsRp07MWgMNbBya/jnfY9oFBU4casrd5pWeC1dEHhKdA9bENIqyoVhusGqXTlBvxBGVm+ld9n1chQ/+IlrK7v3/fTW0d4vFeI6tmzsZBbXNvGUp7ncz3H1Xavrr47B/lxKCrOuIpDQBYqMpNqHP6Kj3FsYo6JiI3ZJvO71JzXhdCOj3V8/PicRsriAnzH1wGj4mITfxz+seahNt5YFYIxQ8lUoslkNAVbtpIRJfPvWCaVqR+W3m0hL/O8wKjmGAm17ZwbM6ysvcRx7aE41d6u0VLwjazZdtPpSLDjcJUZ6q2+jl2v7XdsUraaRnbdloa+Wr2ZnnAJbzkaOPw+PHsBu78etr8Oj+aweCB1wC1geAD9BsqXUGSoTcAOfIPCV0FBoQC8lB214lY4wwoMkisslHeQldCeSGUhUyjL50DwexS9SFYVlNQs+FWqvRSH4qDQ1uYRLC9EhLoqkLRW214/kOJymMJirdDVZinyUTchQytX5eX9VPs1tTK0qlYhvQNwvlIj1uu52lAswvfRaiYTcwa8PBEpOtkqrLUvRGyWeyksH59rn8Ve9Xb2pR541d1ZHhSS6p3eX06kgjzciahsCvl5VpWyuxwKbV0EwjXr9WjD8oNTbR4XlJ6LWgpR1Sl7q0VkZOXkFzoQyEYgR22mZqWWveWCupOH53n4bn7Vh1AkgVQFcpMhdc91Ugb7XL6dLBP5PXSqr7O+hudf6PvJ3zOyA28h4QFNDL/4hUhNWcKDB7fDDTaJzuea5LJMReec0y/nb0t6YgUkVl7iMFWMuzKs7srSilWC+Pi2f0w6YuLzOvPzXe/jc8Zq013XZ+eJQ1NG1OKifbEKcjiIiMZhIlNxLKxkhMOO3XX6fPb7MfXclBsYj20kwgzIFs4yomG+HRtrXDcozjaLs6yMPBnxiRt0WrjOFBgb07GJOq7IHKekm2fIiFdsyLbrjkN1Vi9otUrFBhO+HMMlXP152D+D1b8NnjxWy4HpVAbibAfzKZxM4ItXMKzlB3JRnZzhIMKR10H0GcC1IkBZqIbswrJhHr5nWpEZXwEFVDspQJZZtD+DyV7+HF+IBPVzvZ5s4cGnCmkVjbbLEfFpCxGnwzSktvfy5+xMzclHv8rVqYjRvoCza1gtpQQ1IXvsUGs8k4Per2cyJvc5XC5EYuYNvFgqu2q2V2r6oRKR+fQcfu2VzvHxmZSi1QSerODlTOO8mIpk9MA0Vyr677yEZ1OZnd0gVahH/qVDJt/PopMSM2lVpbjslY1V9crWyizM6LRvk8tzs0dm5nwI4aeg6uBUO3IWVJu1U2q6rcudCM1m0Oez80jBCvOJcZbnPVQzKE7D/R5g6IBWZGvtYb2BF89hfU/JDvD2tJaIYSrPJ5+oqu52O05K5hOxFOHlcvyVP5mM3bm/DeJwVfz+uHpybGQ2xCGueD9DfFw7tr0/JjavIypf92FjiFPO42MZ4sKIdv/j8FGsjsThRSMhZix2bpz05/ORUGTZ7fRrG9d8Pt4bI0NwuwChkR7zCR2TUCO8plpZWMnGbhW841DW8eds98eUGzNex6bkohizsqwjupmjrSiifb5xeMvCbnZNFs76PsspJNwTtHD4/8EX/wz8wf8Ffn4FL0uFH2Y7KGbQfwj5U8gfQ/EjcFNuYi2ukErjBzSLBhLj6/CoYJjpkfWB/HiFoJyThwcH3Sz4d3r5dw5Lbmr0ZINCV30gUPullveVjtNO5e9xKMyFU3+uIYMvfiIylAd/T1+qF1fRhzDWoEKFmZdxua3gdC2lpys16Vt15osTEZ1y0LGbkPI9O0gFmjdKS9/W8OGlCNimlqenKeCnlyI9oJYUXQ6/dqVxbyp5bf6/j0Jri0wPB/xopzCUd/Bspho+3sn4uy5HT82qFIFbF8FHHv3ovAz3u89CWrrXR5U5qTRXuRSixr6f3fgg2q4HFpmMzFZtOSe0nUD3pOvUpHa/g8Nanc9f7pQd/eyL+xnGivFWKjygSefzz0dy8+TJ7TCHpR9bOMW8PYuF9l+vv/m5Y8JjEz+ME7+9jtPP7Ve+ESBbb6pN7P+x7Q3HNXJe93jd+nj58WsjLHZuu5ZjU/LxuEyhMPUmVmQs1GX1kIwwmIpRliMRsXpK1jfLPkMLTRn5ifty2Wds57JrsrYXts5I02bDjZk8HmNsZM6y2wX+YsJnYVMLvZnvxkh0bMqeTm//HZrB2u5ZrJDFtZti787VVVJ3Er4mvNSb9V+Gwxew+rfA5W/B2SMRiaaV4qNccnBL8BvwHWoxkQMZKjYXMrV8BbTh2Wv5UMoQ256HfTopF0Mmk7SfQjfXBF7uwzqnMdTb4N0ZpB75XOfziAy5LKSodyI7F4+DWhqKARadOqkvV6gqsxPx8ZnI2tUJPH0uj9F6AY8udI7NVNlY870IT1vqHMudxvboGl4t4WoGH76E65nG5GuRn4crmaJfzURwBuDZUvVozrfwi1MRncdbjfOqgpcTkaSyEzl5MRVRzAalsl8FNcd7mPcaRz0E8tNrwr0uRaqsSOHjTkX+qkFNPi3FqvDwPA8NSJ3IyyHcE1zwXpkK5HS/dn1kUtbHTEHw+eSqnNytlHa+H2RSbg+wuoD9Ffh7/r301hIeGENbRiRin4SlSlsmkKkDNslY5eZvAvvlbueNawHBOAkbUYnVEFNLjAQc19s5NjPHJOWuVHXD8fsYx8tfR3xsfHaNx1lkcVp5nLJu12zHMrXCjmv34/RUJMPed52Ip5HE6XRUaYxgte3YQ8vutx3DVJ6Tk7EhqS2P7+/5+VjXxszBzkn92+9/Of3eyIiFEe14ds9itappdI7ZbAxlxcTG7o39nRh5hJGIW3+wwyE1Ck34hmih/RRevoDrvwYvfxMmp7ADsgXkZzBsof8ChlfgZqgWz0yqDXvwM258PX6iCThrQnhqLt9N0QTT8SBlIsugn4bJNROhGUrIWz13ZQh5HTRP1ztoZ1ITyqDsZH2oFj2V8rNYwfYUcApxNVN5dHwmwrOfKoV9PZOSNT3oPLtKvbTaSuTmg+d6Xs/Hmjx9rkykh1d6HpzIDU4hp7KX0vRyoYeZvR9spOT8yc/gxVx+HzfIo/P7D0Vy8gF+tJF/p+oVjqq60dT8qhLpmQ7qpD5t5fspevi1LbwoQ12fTgTI9wpdzXr4qIENqsMzINJSAU96LT9kMiNXgTR1cNNQtCMYj9G+3smYbM6L9SDS6XYiO02rRqD7a2iuoduLIL8PeKsJD2hy+PhjTThFoUl1udTkYlV6Dd5rcrGwC3wz0hMrH68zo5qfJCYKccp6HJKKQ0wxITo+X0yOjvf9VR7HOE6NPw552TIjEKZyxJO3EYQ4xBVXOzYvjZEEMw2b38oIY9y7Kg772D2wWjmmtpjCAqNh3czI9hlttyPJmU7Ha/B+VAJj4mOeJPP6lOVI4OzzPL5PFrozk7KFsUx5ire1fc2YbUrYdpu8OwnfEg20fwQXn0LxAZR/Aopz8DsRnGyh0IZcq0HtCensZNqfoPa4XubkvpZxudwqvOSXWmbNRotBiopD6k6+URis2sAwFRFoZjIZ705kbLYWE1UwUuehng4ONqciAfVBClDZwsm1KjXj4NFztaEog4Ha57BZ6DzToApNDyJJ+4nGfCi1bD9R2Ot6AU8uZGQeghKynWifIZPH5tFK3dWXO6ygMRdzWDRwORVZ6R082oZWFK1Ul5NGBGRXakyzTtldudeYt4VUmVUlf86yCX2rnGrxNLr9tJmUoX0OL3ORnKJXF/Md4TsOOPEiXztu1+PpXWgD4VSU0F7n3IhEDB62Xq1Jhp0UncMaut37Q3JivPWEB/TL/Q//UGTH2hrYJGNpznEIwSZK0KTzq6T/2kR1l2cnVnli8mKT3rGaA+MEGqs9Nq5j1SfGV6k9r4MpJ8eG6eNrjNPCbXwWpoJRiYnHEo8HRkOvKSXx+axvlvl84ntm+8YTv9XXsaajsQJmoS47RqxIWdjMwm/W8sK6tRuxsRDbcXVmO4ZVYY7vr/nF7Hzm34HbBu/j+2PhMSM7bavzW9+s7yqTMOE9RgPdz6H7BPJHUPwGFB+hUMcSmZdBJKdCmVkhtOULQonfYKIN5KZbSOXJB0SKDlo/lCo6yADNQq/LPTSnIWsLhayoFN4i1/Fm19rWFyJCfSF1x+eoknMvZSgf4PKhxjpfw4sP4PQSrs/h8TOlVFuaej7Adg4PX8EnPwoFDHMdu6nhp5/Di3ON6bNHIkF9FhSQLKhUhB9opQoOrms438jrU7Za77OxIvN5yETDK4OqdSIgs07vOyfy0iLf0HWtMBhOBMmhlPaqEyFpg1KWhe+ZyRAyuQgp5JmOXyD/Tog6skaZXZ0fixq6QHIyp+ytnT7Wm75aLVJ4tgP0n39vf43vDN4JwmMm5t/7vZGQmCnWPCJxBpVNKLGxeL2+nb3zZbAJMfbc2CRo6kdcoyduRxD3nDpWbY7JzrHB+Rh3hb2OX9+l7hy/vuvZ/EU2dpukLZRjZCQmBUaU4pR2C1fF543NzkZCrDmoKWOxgmQZYcfnjqsiG3Ex34wZmeO+XXGdneM+YCcnIkAWyosVGTMV27U2zVhFejYbTcjxZ2tZWXEWG4zEy4iOhdpWq+TdSfge0CuM1b+A7mdQ/BTw0F9CNoWb3lez4PdogUYhraEO5lsXVB5Ebnyl7Ky8CenpM/W/KltkhvawP5ca0U1HX4+J4FkXlh1kRG6CYjTZwWEuErS4lHI0eNicifxUrRShfqfnxWpsVbGbKxRUdkHRmcDJBl6ew08/hYszhbv+2kfa9yfP5OvBS0nyKNxVDDIr97UI1Hwnvw5uNCI7RCzaoNSsa4W/Hq7l72EQUZp18vVAUHVabrqub8P3YjVIKbJsrKtCfbimg0hYB1yUqJdZJ5Wn9aEGT9jHZSJOTzu4dCIzuS6NTH8C7J0Ik3Ma/9aL5KwHvU5fO8I7QXiAm4KEoAno8WOFtuK2BnBbUbF0ZVu+3X51Z2oz5MYF5OCXycpxGCNuVGnrY9NyHLayYn1xWOw4DGZjjlUkG8eXhbDuUoriUFT8Hm57emz7WLUxFSc2M8eEJDYiG0ExQmIEaT4fDcRxV3RLZbfChDY2M6VvNuP+MIalLMPJQolxbR0YyYp9Xlbwz+77ZKJjm9pj98YIk13LYjGaqeN6S/a5mLIYh+Pi2j/W822/F9nZbu93BkTCG0QP/WfQP4f8AxEfN4GsQGGhYHz1iOwwKCzlm6B6dHpkPWR7eXS6mfYvtty0mcgD2aGE6XMVE+yW2pZCk/NQqhhhE/4vTr9QfR5ymGyUudUOCkP5XOnsRS/1ZnUWQl2BMGwXUnRmW5GeH3+qFhT5AbahPMbLB7q2s2tuiMvnj0V8VnP40Qt4daLeXFnk9fFOXp3PzrTMoXDWZqKMr+ta41pP4KNLeDETMTvfyYNTtVJ/rmp1SvdBAXIo7FW38MVEis3TvVSbVS4fz/Na95phDFN1XiSo6OBVqTo/AzDx2qYPIbAetaC4dMGMHOa83Gn/BhFJCJ6eH+DP713BO0N4QJPF559rAvmTf1LNQ58+HT0VcDvUtNloooHRf3F9rYnndWGFOCvLJqdYFbH1do54n9iLcpfaYuMzUnDXumNCUnyNT+iryE9MyuJjG5EyshaHd479LnZ9tsx8NkaiLLMpDo9ZSCsmbXF6vKWCW9E/U3gs/GTnXK9vq3UwKig23jhUZiqRkZWiuJ2+bmElGzeMy+w6+n40QVum2l1p7bbMfElxCGu/19/a9bX+Dr+uwpiQ8I3REWY8lInVSbEhmGR9FUJKNRS7EN4aFGKiguIashD+shYVlq2VB+XGeWVM7c+hC1lWxUEkol6H/UqoV9CcwPM/BvMrbVN0QC7lJ/MqXHiYSXjKe4XUyk4hrrJVuKroVdNndQYXD3X+dUiDP71WWOv6RO0phkyG5weX8OpM22xmCledruXjAWV4na/gs4faf1+prcRqKhLhgbMtXIesrEMwKletrrMcAKc09ZODwlyfhRo+J3u1pqiLsaryxwt5gKaN1JppIDHbQiSmCibj2iu7a+L1UU4HZXOVHjZ5CJE5mZt7P1ZY9ijk1UXqT8vYXytBeKcIj+HyEv7iX4Tf/u2xMKH98o7DQPawLKCukyqU52Ntn2PEaoqpL/Ev+zgcYsttWdxcMjYIx5O8He8uw/Dr6vDc9f54neGucJZdV+wLis9rBAZuq1Sm5hwbeS2MFY83zrqKPT2xkmUhMzt+3ObCVJ74/lh15slEdSKGYVSF4l5VcLudBYyvTYWya4k/KzNMm2JkxMhS0I3s2PgsnBaTUnsYSbIw1uGgY61W8OKFSFtSdxJ+CPgO/BZYgptLPfB5UHZAEkEw0foi+Gl2QA39AhGlKbgihLVqKPbQnchzM0xERKq9SJBzqstTbZCaVIi8NAvYnyjzq5tIiWhncPpc+189gfl1IEw9LK/UnqIrRXD6ApbXIkfrU/jxJ1J7mlqKD04EY7WEF4/gx5/pmlbhGFUj5eZ6oUrOu6nCWEUPD9a6FZZJZsbnohcpGpxCTDgpPAOq2nw1gb6VelX0Mg+XeVB7DlJWCi/O12VSZeYHVWj+/SU3jUhXpWoEdW5UeCaDqjF3QUFugmJTd6Eqsh+Nyd7Js1OisW2dxpoDK6/Hdhjr8SQI7yThgdHTY8rEo0ejgdU8F9b1er3WP+V6PYarqkqT6LGn4tg3Y69jk6tNiEYi4nBVPGEbATpuO3EcurJJP+4HFa8/9hHdFd6K3x9vY7CQzrFSEdevOV4Xrz8mP8deH1sWKz0wVsU2omHjgPHzM+JoYbS4XYV5gOJGoxZKMqIUh9Tirui73e0x2mdgWWBxnaS4K3tsgj++L/F9j0Nb1urkcBChvrhQGPbly9RGIuGHw7CGYQX5MpCfWhNxFsJXMn0o/GTljYeQXm5KjyvlwelmCjXtPoBqK+9LvxBJaSodpwpp30MB0xVcPYKTZzpm3kvBmF3B5rHS0g8LTd6nz4Pvx4no+Fzd13dL2MzVd+vyEUw33BQYfPoZ/PyPhUKFwag8ZPDBFyI0DtXwacswpmBoPr0Q+dgsRE7aQiGl85XS3UEhKJA/52oqAtQ7KUov51J8vFOoqUa+nDJ8x3W5ihsO6DFvRWY6r/Fd1qHVRAabUoRqHe7PvA+qGTreIRehKjsRpFdBnbPCjS58bHunz7P3CpdBeB3G1JK8O8d4ZwkPKAzyu78rIvPbvy2lZzq9nVkTZ1sVhSZAm4h3Ox3jdYgJTKz62PHjifaugn52jDiMdOwrMjUonkBt7MdKUBxGg7sJz+ueY9Jmy15X8DDOqjKyExfki9UPu8emntyVvVTXY2adEaG4CrGts2PEHdONZMWm6Zgcxb6ZOCwXqzh2302JiQ3Vxx3k42yxprlNqGLlKfbqxAblw0F/UxcX8Px5IjsJbwANDFeQnUA2Bwpu2gn0aJmbw9DIr+NnUnHI9N71qC6P08Q6RCnqWQPVZ/L2+FB0b/cIXA59B+0pTK617eFE565fiXRUW4W2DidBGWKs0gzK+Pr0N+HDP1BDzfkK1udSaqpWJOsXv64MriFXyOvlY6k9Ta1z1AepOZaN1eew2Cpd/VAqBf1iCY8v9P5yqVo/i72UHLzCWvO9lJVdKZLzcAMvFlJr9qWuexkUmlWpNPYTpMoMXssWe425c0HFCgrNoVBoy/UiKG0gLk2haKQPBMg7EaCKUEQwA4ZQJDEQpJ3T/jidp/cKY3VeBuhEeG7jnSY8oEnpr/01kZ4//sfho49kNrU+R3E2lU2Y1m3dOq7Hfp48H1Uim2hjUhJnN1mF3jh8Eis1MVGJScxxKMhIAozrDXEozBCHyGIch7Zet+yuY8TEyUhJTFpsnLHReLfjJtU7Vojic1v2VJyNFRcXtJBjnEE1nd4mMVZbx85lylJcSTn+bOLnOJRn2xthsRTz1Wo8Rlzi4HDQ35Itjz/r2KRumWim7FxeJmUn4c1iuILhBLJzcCFlfPDgOpGAbC9Fpn8C2RpcI6MyE/k/3FbKkDdFYacJugt1bbJMhmWfydRctNq+6EVGdg9CReYKmjkMYd+2037TK2gXCncVHViK13SjrK3JFtpaqobPFNa6fiBy8+IDOH8Fu0zvh1ykaLYb08qbWorOZC+1p88VqtpO4aNP4JOn8Gufwh98qDG/sKrTPtT/QcTCodDWZcjOWmXq4bXYqSrzLFSdfrSFj09U5HDwCmEN6P7tCvhgr/BTkYkUzaL0ck90n/3Y7LN3Ut3Mk4PXNftB+w0eJr0qOV8istMP6qd1NSidP+E23nnCA9y0obDU39/8TVXfNaOpTXymzqzXo7IQV761idrCJjFByjLtawQoDg/Fx49TqeMifsfEw1SD2DgcI1Zi4n3gtspj6+7y8hy/jknW8XGP0/nhtgk7JkhWPNBq7Dh3u24PjCrKdjtWUDZF5TiEleciPeapsu1sv91uJCF5PmZr2f034hGnpO/3t+977Ncy1cfq5BiRsmuLjeWmItnD7lOcKm8tNUzZSWQn4Y1jgO5zZETORFaoIDvV5NkX4AoRGR9CWX3I6vI1VNdSGVwRQmFTTeDZoInZF6jp6BT6E03es1chu2upczQLVV4eQkimncDsC4XI1o9EkvJBIbHNQ2VvHeZKX1+fhXTyHLpK6k9bi8g8+UwZW84HA3EHXaEQW1uJgJxd6Lq2UxGhOvTUWmxEkB5fwMszeHwpYpR3yuSqg+HbhVDUdAcfP4KH16GwYaEQWI9CWCDFJuvh0UbhqMEp9b1FBKgc1GfrEEjK9CBTcx+UmLoZ9+sHHWufq6LzBI1tcLALc87g5DkqhqDwmOfH67EP6k7CL+NeEB7QJLRew1/+yzKJ/ok/AR98MLYDiAmPKTvm63n1aiQcsb/GJtg4LGVkKCY+8fYw7hOHQuw57qgdqztxJ3W7nmO1JPYVHV/7lyk6x8rO68jRXcQrDoXZ63jCP1a94tBQXDfHqi1btlQc3jpObTf1yEhlnDoOI7ExEmXEIs4Ym05vE1IjRVk2Gtbj6zh+mDJlxMmOHRcujE3Km43+jj7/XKQnZWQlvHEcYHgJPAV3EohNA90BkZ9JIDqmLh+AXoSnn4psZDsRCF8EAkQoOLiGdhnq9VyAn6iTerUHcikzectNLy0fvrM2D0SCmhMRnnon0rN4CftTWL5SkcLFpUjOUIzbnb6E1QP14qoOIkY41eQxheT0Cq7OtHzIRJaGA1wvRRC8g9UC8CJAr06DYrNRNtfJWoRidpBH52IJp9sQCpsro+vqBKoykCLkB9qW6tg+ZCIwj6+Vxl516tJ+yKXc1IEk7Uqdd9ZK8VkXkHVSa0AkaemxPrBUQyBIg+7tNVJ5ukFhsMaJ7Fx6uBy0X8Iv494QHkPfq8v61RX8zu8oxLVcagKczzWZWvuJLJMqFFfFhXHCi828phZYWwWbAOO6LcdEIlZ84snaUujj7CjDXeZkO0ZMLmJ1KCY8r8Pr1sf7x9vEfp9YbYrbTZgPx7Kp7Dg2ViMxZjpuGt13Iwt2H2KTt1VFhrF+TlWJVMQNPW19lt1Wh2JSZfcqzhwzD5XdPyNTNn4jT1aTJ1aujOwYCTOyZcpOIjsJbxuGC2j/EKoa8qejmuNPpFK4Lvh2SpEchuDbQRN6dwKulg/H1YjMrGD/NJAdD8NMpCTrNOEPU6ALClAgLNc/hbOPFbIhh+UXel5/EJIaroIHZwf1RuGwIdN4F5ewn8PmRCGvZioCdZiK+JxcKosr77T9YRI6gk/g5ErXkQ8ha6sT4RnCd86DK/X9ul7Ao0upRFUD13Md73wtgnGxhNOVGpE+Wunerabw9AKogsemUOp5k8PnJ7qJzURKzTJkZm0qdTM/3QUlJ5Mf6KQRcQGlv6+DKlcM+ix2uVSyfaZQm1XJzgLpGgI52g0pM+vLcO8Ij2G9hr/0lxRe+M3fhB//ePT2mIpQlmMxwsNh7AUVqzrwyyGouFifESDbNu6/FRuaY+XIjL+x9+RYZYm9PLFZ+ZjkfJny81U+nrtCXXcd/ziN3MZrqo2RFTP8WojwOFPL7q+RIbsuIxqm2th9hNEzBGMBwzi8ZPcyVoBiBS3ulxUXVLTt7FrjZqh2/Nj/Y6Gr2Ldjyy4u4NNP5d1JlZQT3ip46D+H/gG4U1R9eQJ96DGYlQplMeOm+CB7hbKGMxEaNwdCynaGsreqF9rH/CdtyOYqwv9+sWGst4OKFO7PRH72D0Qm5hdBgak0cc+uYf1QROryqdSi6QZe/Wj06Vx8AI8+FQHKe/mBNkv5dOqd6vQ8ei4ysQum6rJVOnu1h+tTZYKVrcjS509gsQ5tJq4V3np0AV88DNlptbbtM3h+BquJSJL3MiXvSnl++hy2lTKxyh7opegMTubm64lIydOVuqVvKoW86ENLin1QgDp5d9os+JecwltDL9XHvDyDH0NifQhhvWhhlcLoX4p7S3hAk9jHHytb5qc/lan58eMxzOWcvD7b7diAMq6ca8Qorq5sk7j5eWLfS2xatokvJhBGCJwbJ+J4ko6zko69PabqHPtq4vPfRYJi/KphL0M88dv7WPmw4oFwO+vJrjn2Odn1WJd0U9biTuZ2LLtPcY8v2yZWxmwbI672OcThs+12VMqsCnJcLDAmKrGnKQ5fGdmyv5PDQQrhs2eJ7CS8xeih+zm4JWS/BcMefAfuTBO5a8BNlS3l55ro3Rayldb5QhOsbwAvclMMUD9T2MpbXa4OGKC8Dh6eB1o3vRShcXs9Fwfo5lJ05s9FPKpQyLDYi9x0lVLgd6ewfCllpjyIUK3PVcm5L1WJuWxEYuodzAtYL0Woik6enryXCtTU8vq0JTx4CV88DbV0Snj6XMUIsx4uTkd/EB62dcj+6uUHasP33sUCfvxcKezbSn6fqhNB6U0mG9SaYrEPHc+d7u8h1/hMldqUOvaqlP9nGu7VqtQ9zga4DKUCBi81aJeH3lsDXLSwCS00El4P5/3rb5Fz7t7cP+fUfPQ3fgM+/FC9lbJs9PC0rcJg6/XtwnqW2mz1e2Jzsik5ceZVbOw1ghP30zquPGzKiPlVjpuWxoTmOMMrNjLbNnatd4WqjknQl4XBYsXHJn64TWLitg52LKtRFKtDNsY4pBTXxjGSFHdKj83QFjIzFcbq68Qht7jpqfXZiomnLYuzsGLVxs4fkxr7PM7ORIxhDH9aFeXVSsb3+0R2vPdfESB9d3CfvsO+LfIfQfUnZVx2pTw8eQFlrV++ea4JOMtFPNwplCtwC5mZc6T4+HOorxTiygfwM70fZjIl+6AIDXMRnmqnEBUl9KEFhc+BXJP6/GVoQuql9jiU2dVN4PEfqXjhUMjf08wV0ioaLcOFLC+vZ/vL7UtYXiik9PQTtaPYLqT4eNSWYrFSvZ9dLYVlttH6ixN4cCEiVXQyJXsnQtdlCmUt1zIw552ITpNJgdpUsNyoU7obpGjtcpGUk40ytrJWqsxlrevIWz23SGHbo2KE3SATc99reTNA2+vRdHocOrg+wMUaDs0vfeTvLV73HfbeEB5Dlon4/NqvwZMnt2vIXF9LDbKQiBEbC3/Fheum05GA2Lo4m8v2PSYfsdk5bpUQ17yxc9gx42acdozY1Hys2Nz1/quMzcf1fmIVKV5m28LtMJS9PiZAtl2schmRgdteqDgLysJPdq7Y3L1ej8uOCwSaQrcNkr2F0oxIxUpU3OTTVB8jPDGBibuk73ajIhgXNbxPSITn/qL4LSj/mMJU+TmQiciUUygz+XNyD9kJ5LVCYBkhK2gnZSf34EKfLabgKsiD+jIsoVqhIoYzcBlMX4j8VJbqHozM00spPRRSl+qN1JihlLozCf6ZdiqF4+wzFS0kh+vHWjaPiMn1Q1heKoNrt4DFFZxcSNHxDq7P4PSVSEgbTMdfPBXxefgcXjxUmnuXa5tqH7LSBrhaiJRlvUhPdRDxcT3MN0Av78620jI/SNEpWu1DL5Iz2UvJeTYPywYZjvsB8gbopNoUjUJfrg2NQb2I486PP+raFraNyM5m90b+nN5avO477F6HtO7CMMhzcXkpT8+TJ/DwoUjQ6an+iC4uRtIR98iyujuGOLXazLOxqmGTr9WVsXVxS4XjTKfjUFVcnyf26piCES+PEYe47np/vE+sJhkJiWvwxOtjM7WtN6XKGocenysOx1mLCSOMMdmx48SeqPgem6HZzhUbmu0zsXo7du/iUKEdyz6f+Nps7HZN8RfLej32x7qPJCfh/UD3hyIbxR+TEpOdQN+FMFcF1WMkgawQE7qW4tJ9CDhN5O4KsjX4qVSPvA9hMPtxNSBTrVfKerNUGKuZAaWIz+5HUK5h8kLZXm6ArAnhrvDj4vqp1J8hlwry/NcV3tqewOnn8Pw3YPlcfp7tKXz4V+H5R9r34WdSd67ORWzaUgRoNxMBmV9zU4E572Vwnq9lWp5tQh+uqTq7u17HyAb13KoO8OJMpGQWCgg2OVzNAwEKtXgy9L5D3yf7UkrNdqFlQyaytmxgmwfTspdqtCm1TTmIZPZeyk/bS+lpBtj1cLWH7f6H+ut59/HeER6D9wpHrFYynD55In+PTZymQpiqYK0IjNTEVX2PiVEc5rICdub5sTBWXBzPOrPHCoiNMVZz4pRvIwbHAl1MnuIQ112ZWMf349jHc1wL6K66PHG4y4hFXIsoVqtMabF7Y6TCyFVMoOLQmI0t9jF5P34m8XnjsVs4DMb7a+EyU9riMJm9tus9HKTimKKUkPDOo1fWFiisZZlXVEH12KKZehH8IDm4NWSfQn+mde0S3ARyB+UGcNA+Br/Qe3fNTaVjt1FoyjUwTNRQtCugvFSGFkC5g24qkjAMWt9N4Pz3YfOBCEkzgcll8OGUUnGWX8DqocJl1Ra++Cj05mrVQuLqMZx/AfVWoTvvZWReXsoY7Af5fjzy7zgvj8zVUqrPdqpwV3VQm4vJFl78CM724fuqlZ9nfaJjNYUqNHcO2lwNTk396Z0yu/a5SM+uBDqdwweF7OCUtu4GESjfwzrXfl0nYnroYYvCWes1bLa/PAckvB7vXUjry1DXUnmsPUXs2TG/Tlx7x4hNvI0RjjjbK57444yuuF6PwdKjY1Jg28SZTXCbxMQKTkyODF8W1voyxGQnPp+Foexccegr9iTF5MfGbCGjOGXf/DZ2DlNfjNRYdeX4YeQnfsRNPGMVx8iN+W9sTLYd3A5p7XZjyYL3DSmk9R6ggOI3oPzjCltRifwUlX4FFznkcxGFvFDWVe4gKyFbSNHJW8hqeX7yRo+iU0ZYEWr9uALKLVBL0Tl8qBBXf6L9J9fhOyVTeKvaSOFoTkPvrmAk9oEEzV8FgjQBMoXCZpdSj8oGXvy6Ql/tRPtN1jC/BBxcPJGqM1mr51dbwfU5nL2QsuM94McqzSevVJvnwUtVae6DIuMHvd9VUogOhdpgdG4kUnkbvD+9wlw9sLjWc+tCn6tBRKcP36W+l2+n9WN9naENLSIaGLaw7xXGul7BfkVyKb8GKaT1NXA4yLhslX+NzBh5iYmMTbBWzTnukG6m5xjm7YlDYrHfxfpzxZlZMJ7XvCoxcTnu3P06gnOXr+d4m2PE/pk4lBUvj497nJUVPxtpszR2I46xV+Y4zBent9u9uotcxYqT3ZM4vGX+IvPvWGjSssOszYWRpbi+TgpdJdxbdND9gVSY6k+KcLgiZEj1wBR8UEM94X87l+HZVB3X6OFD8cLuA2gHhbJcUCqyVhWXXQ7FBRSvVDE5OyiJafWhDM/koZhh6InlveralCspQ12hc7i9/Dlk4HMZlwcvxQcv/5AfYHIlcrQ5h9Wp1nW5jjMP6elFCwwiIXQhRd7Bei7D8/UJTDawCu00phu4OJOXZnatBqK7idQh30rhqfYiWocKZitYT6UC9V6ZWVmr++l8UHIyxGxakaCuVwr6PhfpyVqtOwyqqrxvYHsF+w2J7HwDJMJzhLjGi02Qps6YIgCjMfk4Y8nMyjASAFN1bAI1FceOaRWD7TzHRAJGBSkunHfsz4nDQjGOvTSxovRVZCdedld46TgtPiaDsZE7bppq9+E4ZBUrQfv9SATNUByrXkZqjKzEZC9Ocbewlu0bd0m313G6un3ucXZZQsK9xADtH4gglH9cyg2FvD2uCoSihaGT6XhwkK+BBrJH4HfKuiqvgCnkzxERmcjYmwXFxO3Az5R2PpzA/A91Dh+UlLaSH4hOatDmw6AedSJL5UakxPeq09NPYHIB9bX8QdulWmE0Ex2jupIitDrXsafXsHokz8zJ50pbLxpYh6ytfSVVyTXyyzy8EulqHeS7kPq+h2dPRHTo4PJEmWz1WiSMQfV6mkyma9fBswdScCZrKT+riRqB5vtQJDDXvdyGkgD5VhxmGHStvlchwZ2DfQe7DWwvoE0G5W+MRHiOYOGQmOzEikGcZQW3Q0xGbKwR5nSq5V2n17G3JG6DcJzyXVV6b2Gh2J9i6pERhJhMHROSY6PzMTn5OuQnXn68re0fk5ljH5CNJb5OI0Lx8Y4VnHjcdt1GOC0MZgTRauTYcY5bT8QtKOJwWDwmq61j62P/T0LCvcUgpWe4gvLXofhNTbTNHypcVTwK30tX4B8HAjSB4pkISw74pSZrDuA7yC+gfyIi1c9Vlye7gO5MpGL7QQh5FVA8h8MHUphyJyUouxZpqF5p/64Ad4DduZplFhuZlJvw/VqtAQ/lBex/LKWlnSmF3Q1Aq/NSigQxyIDcOzh9IXXo09+CRz/T8U4v1eZiQGRkGKTk1CsRmiwTaTmUuoYe8E7nLQ4icd4pZOW9iNtAqAuEsrv6HrK9HtVGBQStmnJP6Lt10PfaeoD9FeyuYHgPQ+zfJZKH5w5UlTK3lkuFP2azcUKPO6ebB2c+v21EtjDUZHK75kzcR8uK6cWNM+OGpM6NbRiMWNh6yxaLi/ndpfbE4axjghMTk5gM3YU4tHUc6oqzyuJQUxyesrCW3Yd4O7hNfmKSYcTGUt7jsN7hMCo9NobDYTxHbHC20JilqBtxsrCWkSEzKW82en5fCU/y8LynyKH4dSg+gvwpMiY/gKwCNvLtFHOFo/Jcae3FS8gnkH0gouNqKEJaeuZh+EgEJUNqiZtC9RLaX4dijVpanEH9InxnAP1CoaxyjQhFyKwq9kAmgpN10C1CvSDg6jdg8blUqW4iElHuYPUUHvyRCIzrRZSWX8D2TGpSVys9vi8CUclEWg5TEZx6I39PV0ohagqgF4GyujxZo+WulbIzDChLrZH5uF4H8/Navp6+BxoZl/tOZMc3IpP7EFLsD7A/wO4aNpdB1Ul/yV8bycPzK8C6bS8Wt03FsZfHwjFWsfm4p5aFT8z8bCGVOGW7rsdj23lsu5goxdlgpjjF5OpYzbHz34VjzwvcVldep+YcG5ZtuW17lxnaiE6cah4bjO2+HYe67lKpYvUlVt1sPzN1w+16O7GZOT5ubCQ3lcrITxxaS0h4b9BL7fEroIX8R+F/awFuoTDRkEMWjMVFD8NDKRdZD4N5c3LIChGm7EpKT95BXwIz+Vny5yIR+UEeIL+GYRr+PztlObUPFNpy/eglygZYPQGc/Dr7hxrXo38dXv1JmLzSuqFXSGr5M3j1Y8DLVN2WUFzD7kNgL3LmD+rOvnwmn1CxCd8XjZqOMsgP1GdStbpc6lBT6D51lcZCJ99RmwG5SN8hfL/0rdpLtG6sAbSrdOyhlarTA8NGJuVdB9tr2D+XPyjhu0FSeF6DooCnT+HRo9FQbE0rTdmZTMZJ9rhHlPe3yY4dM57EbZ/4tYWu4rRuM/reRXCOiU48fhtHTJiMMBi+Klsr/vM4VnRixGqNqTHH9XyODduWhWWEx+rz2Hrb3lQcq69jalHcG8sIkJGWeDxwuwKzPdu2pvxsNio++T6rO5AUngSk9nwE1V8f1J5S4ZZsBsNWHp/cQ7GEwoWihQvIM6k42QD5tTw/Wa5QFWciE246qjtZrmcC+aGQUTfz0D6Sf6dYKyzWPhQJmn4uwoATIWrPodiKcLlByk65DQbsmcJLxVZhLjfA5KUUn77QOetrnXP1RK+vfgynv1AdoJNPdBzvRebaMihVoXih7xUmm70AWjU4LbZ63SNDtTsEBWivtHi/F5nqAinzOyk9rZeSs9vC7gLaS5Kq8w2RKi1/A5ycqDbP+bkmZTMqG+Gx9217uwN6XY8+HBhr98RVmGGcmE3piQsbGmGKCUqs/sQeHlM4bFzWosEIUkx64HYYLCYkd5Gfu/484pDW68JahuOKyXHtoDi13MJTplzFYbB4/+Nu5qb22L2MSVLcYDT25hwTn7YVybm6Eul537udJ8KTYCg+kqE5/0kgLQVkJwpd4WEICkn5GKoWqkfyt2StCIJ7APkqfHe12s/Un9xBcQnDIyhfBbVnCcMpVJ9B/0j1evqlSETWyT+UDdA+0T6+0rpirxBSvwyZUKWI0u5HMP8YDiciT0NQqVyv8R1OgSFUg84V4vJO6xikCm0eyBQ9OJTN5bSOVqboYjVmeh2mImdWd4dWqo/bScnxjVSfoVF4q+th2IV09A4OKzg8h3bzRj7ue4MU0voGWK1EQpbLkdiYqdgIRd+L0FimjxEdC+WYgmNKzDBocjX1Jw75GDmw5cfem5jQTCYjITDSY+c9bnYa96GKw1J3FSZ8Hb5OxtKxYTnO2jo+xrGfB0ZyFhOeWPEx4hJnicUPG0NMfO46zrFJHMYw5vtOdhISYnSfKRXdLZXF5TwM15q4szm4OTfp7Ice/EspPvmJCFLmod+hNhUHHcfNIH8B7U/l08kuoHuilPWsB9awnwGD1Jv8AJvfhskfiUwNc5GObBOyuA7qwF695KY7e3ei+kHsoWmh3wfC0io0NdSBSG2U6UUZ1ocfj1mn9y6H7KWUmYEQXgvxp2Yi9abNddzBA9e6D22oveNz3StCr6xmKnIztIHsHGDYhzo7O+ivEtn5PpEIz5fAe7WgqGtVYo7Tncty9O+YUhB7deLO6aa42PY2AcdNMutaxzEzs5EZU45iVQVuqzjHxua4WrQpQZbpZeM1InLsIbL97FzHJOiYiB2vg18OBx1vZ2OKt42Xxec/VqCs6rXtG2eexebn4ywv807Z52P3aBjGRqDvY5HBhIQvRavUdUoofgzZg/C/1clbMnwODCII2bkUCh5o4nZNCG09VBp25qTCZMHTkj2HYaFMpfxV+E7ptax8BkOFFKUK+Bz8p3B4IgWm+j3YPYLiU/l1XA/bx1JbukoKSjuBbKfQWLdQd/c+EClaqS6tl29mW4HroJ3LQL1/pPFXlzp2vwuEqBFhyjZwCCG0vtQx863OSSAyffD6DF7bDFvoWhGcthgVn+wg9anZwCGRne8VifB8Bdp2JD2np6OfxiZNIxJWW8eICIzrYtNurGCYAdq8KabIGGmxoob7/ejhAS2PlYjYAxMTiNiMbOMzj42lilsYyRArIcdm5S/ztbzOFxT7iI7NyLGR+ZjQ2ZhiFcaOF4837rVlx7qrEemxKTlOQ9/vpbp9HRUrIeF9g99C+7swvITqT0nVEYPRw1XQfx4m7wU0u6BoBxLUA+5zKULZXiGt7CFk18EL1EK3lLqTf4JqAe3BL7RNV4oodT8NGWKfSwFyl9A8hvrn0D8AQko4AA0Un0NvRKaG9gyqF2NIa8iD0Xon8pMdFJ5r91KxGPS6myjU5RqRsPxCnGm4FKnxbRhjJi/OkAF7HasfpN70gzKv+iwoQRuZvfMdtIdQOXmL+pAlfG9IhOdrYL1WavrZ2UhCDofb5CfO+jEVxdQdq8FjWVswenFiMnA84VratFVottBUnF0Ue2SMQNmx4yadMVGIiUHcpsJInClBx7grvd1wTFji11+m2MTEKi5U+DoVJz7+cdgqJmd2vtj8HZMhU732e32+Sd1JSHg9/AG6n0H/LHh6nkIewlkMCvP4UD0ZwqR+APcFSmk/Cdldp+CuwnMB2Rr6F8Hz00E3BUpwJ8BE2VxuihqVXgIzyHuFiood+BeweSSlJTvAcAL1H0H7kdQW52UWHi6hn44m4vZMlZ/dKmRfeZ13yGW8HkKPrc4F8rWVWtNNlZ7fTsFtg4qTA7sQ6troeG6j9hh+q3viOxGvopPC5Xrot3B1Dfu1SFHC949EeL4mXr0aw0vz+W3CYerL4SBCslj8ctp6HN6K1Yssk0fIjnMINS7MlxM3KzXSYx3DbZ2RndjgaxN4PNGb2mTL7Bpe5+sxAmJjPQ5nfd1MppjkxMeI6wcZabmrOOGxr8dwV3p93K7ClseKj21j/bIsKyshIeGr4XfQ/CXInigTqvgpZEsofgJ+IxVneIVIy0ThG3cKZEHh2EoF6j4JBCAUHXQ7yCYiRW4hUuJ+phR2cpGkbAv+VGTIZUoPZyJCQwXU2r8/RWSrh+6R+l/1BeTPREb6MxGSthbpGZZSVnwYR0sgL4OIFU1Qg9A1Ng64gKGEvtY9cRu9917L6KVAuRwKr4y2rEZ1hrawuoTrV9AlovODIhGer4mug5cvxwwsMxCbF2cYpADB6I+xonlx1WU7FuifY7EYl223t9ebEdo5KUwWmjGCFU/4Fp6KCcxx0864/UXs2YnT3I/Vl1i9ukuFsmPHz8ev79oWbmdkxevu8gDFqk1MjkypiclQXOvneNs4FX2z0eN9TkFPSPgmGJ7B4ZlSxes/rWyuYSMlA4C1nlwlQtB7yJ9om/6VUtgxA/Be6enZBNxFCDHZD6+NSIJzUlS40DLOdWy3DesugVnYtgFCzRz3CtolZCuZk90VcClyg1fhQD+AW4MvUV+rXOSFQssHJ7XHh5BTPwO6QHL24TpKPbsyZIxlUOSqVeRdUJUOcLWF9TOFrxJ+eCTC8ytgu5XSc6ysxNlYVtnXwk5GJPb729WVLRsr3tYqK5sHKG44apWALTxmpMpS2q3KsB2zqkZTtIXejLA0jc4V172B22pJXNn4LnwdQvNlBOl162KyFitJx+pSXCDwmPzE72NFxwhj00jV2W5TVlZCwrfB8BJ2/4JCXNlDKH9Dvp3sgUJW+RSyM034PoSW3AMkl4SaNJwH78tnwEop8LxS+jut9mUC7kwKDAdwHwO/Du4XIhk4KUauIcSiwJ8ow4pWCg/bsO6gJ/LwsO+ZaXi9DwQn1F8bvI7hJwqB0SpUlpUKr5ltqAj9/vIBZYcFW0HzClYXsFlDd/i+P5GEL0MiPL8iXr3SRPqTn8CDkLFgrQ+24deGkY3YTxOnoHedFBtLFTdfUKxQeD+SpLgxZ1lqsq5rPSy8ZaTLQlc28Vv2V2ySPk7VhpFYxF3M78rW+iqV5/h1vE+sBH3VI97uWLE5Tjs3YnOs9th7MykfQm+a7TaFshISvkv0X+jR/n/kuSl/DaofQ3kG5UPIZ4EYnIB/DP5TERh/Dv7zQDBO0Iy0Q2RoC76F7DFwgdK7p4Hg9EHxCRlSzqHQVwc8APcS3LUytgjqkC/D+qAqkaNQWI9M2Bc6v6+5UXCyVlWindPyvFTrCR+KJuYHEZ0+k/enaeGwVrhqcw3btUJ5CW8HUuHBb4AsE9n50Y/k5zHCkudSYKxGjoW9zItjHiBTdwxx3RwzQVvquClIprhMp7c9OaZ2GJkBTeqmFtnkbxlgMckxJcnS4WMPkBGKuAHncesHe23nMTJly48JTKzGxGTmmNQce3aMxMSPmMzEDyNrcTaWER3rk7VaJbLzZUiFBxO+K7gTkZ7pn4D6g9Ce54lUkCzU8iEXOfHBNMygkJl/hIhJA64FPwuExRFSvxCBGsC9AP9ECozPtYqtlBiWWs/DoNBkwfcTDNJZBxxkoB6eKgvLB/XG5TIaO1QTqLpSqnqHwmEt8uE0B9i+gPWnsF2Rmny+YaRKy98DTk/hww9Vibks9ZjNRsNtVcmQfDiMxQLPzvR6vx9JkCk2RniqSvuYKmTEx0hQWWrSnk5HInPcLX0yGZcZwbLtjFBZvSDL9DKFKA5r2TFj/89xn6q4ps9dfp9jgnOcqn4X0fkyH87XITtx+MrIzmqlxyH94vpSJMKT8L2ggPJDKM5UmTm/gvp3oFhA2QVzbyGlJCtgeKQ0dhlzYDiV4kLw22SX4AvwS3l4vANq4ErhtKEH5uBqEaZiK6Wn+0BmZZxIV3FQenuxEvkpdnA4V8q4EZvsGppOhuP9GroLWDno1nC41HNKKX97kCotfw+4uhpNyycnUnvMiFzXY2q4mYThNgkxlcFIihmSt9sxjDUMoxpUFCJKpgZZirott15flj0Wh9QOh1+u/GzeIAvBWdq7ZXMZYYmbdhoBibO67qqjc6wGvS509Tpl53WPOGz1OqITG5OtqOD1tchO8uwkJLwhdND+TI8bgfUvKMsrW0BZQXEOk8dQnanjeT6FbCqlJr+A/hxc+P7JKhEWdw39EyhfQPdQXcn9ErpTbetRYcOikRnZ7aXe9F4kZTeD7BU0vTK/sp2qJfcvFZI6BAVn/xK6Lfj1m7uFCd8OSeH5DlBV6rn19KlUl6oS6TGiYs1HLexkKo714LJwkHluttvxGKbuWN2fLBOxuboSwYorD89m3KTHx8edTFRrxnudOw6FDYPWm8pjz3YuM/3GiAlPbGqOSZHV+DmuqHyXohMbjWM16ZgAfZmaExcVNLKz2+m6r6/H60/4aiSFJ+FtgDsR4ckX4YdaAUUZwk0nUC7k6ykA91DkJp8D11DOZDoeMmVSDS/D98keCN8xbcjQ9FuUNr+T36YLBQh9qnr8ziKFtH4AnJ7Cj3+sMNbJyRjmirOpTOkxM/JyeVt1iWvkWAf12UxKhak1VpjP+5E4nZ2NDTXtHCAycziMBuhhGFPcjeBMp2PlYSNQRngsBBYrNxbyMn+PEZNY7YnDVvDLfp24DcSXqTnHoaxjovM6ZWezESm8vk5FBX9VJMKT8E4jQ76gLBid01/Ae4dEeH4glKXMzA8fSqGZTEal4/z8tsHXTM5WnNDUl81Gy/te5MRIkyk0+/1InqpqLEZohMlSzs2jY4pM3AbDSJCdc78fj2cwBShOEzeDdUyYYsQhrDiTyozP9jpWfmIlx4hNfH57WM8ye31MesycvNmoHch6fVuBSvh6SIQnISHhXUYiPD8wzs/hgw/0fHJyu4igVWCez7VtbEy2jC/QZG1KUFy7x0zOMC4zQ7P3o5fHyAqMao3V6rF2GaYIGemIs7lMoTFSY4TKQmw2dtvXiF3s7TEvkREkIyc2tpjQxE1T43RzO7612ohf28MI3NWVHknV+eZIhCchIeFdRjIt/8C4uJDS8NOfasKeTm8TFwu9mAJjqov1zjLiETcotfR06/xt6e6gfZfLUf0w0tT3Wmdp50aU4Da5sHHFndVjwmLHiomNHcMQV3q2GkNNc7vtxTGpsWs89vYYsYnvgWVeWbq5hfCaRr6niwsZk5Oqk5CQkJBwjER4vkc0DXzyicjD48ciHabOWH2YLBt7c1lGlk3idS0lxsJYZniO1aKYGFim1WYz+n4s7bwodO6YjGy3Ore1xrB1MbGxY9T12OfLjNFx3R0bk2V52TlsnFbV2dSimJjFYSzbz67L7kX8OvbqWNq5pZwnspOQkJCQcBcS4fmesd/Ds2ciAZPJSGgsnXyzGY3C5tWpKpERU2YmEx3H0tZNMbGu7eb3MTXHyJEpIsMw+n4sA+xwGMNWm81IpMwPFKe1m/IEI2kxshKHvo7Txi1UZ2pMrCCZyhMbl4/XGYGKiwgeh7Is7Tz1xEpISEhI+DIkwvMD4OJCE/ZiITOzhbbicE+eS4Gx8BGMpOL6Ws9GjoxoxPV6YFxu25oa0zRSfGBsf2HE6+pK541VGYOpLLEx2cJpcVsL70dlx9ScuBqz9fmCkQwZaTrudG5eH1N1rAN9vN5CWW07NgA9HntCQkJCQkKMRHh+IFgtmO1WZuZHj7TcFBSb+MtynMCtPo6pJRYO2+3GdPO6Hj03RhKMzMDtNPKYgFh6u537cBgJmLXGiM3RRqqMhO12t2v+xL6cONwVZ1yZj8gIUezVsXHEtXhM0bEw2/E5rq91rxISEhISEr4KKUvrDaAoRHoePLjde2s+v10vJ67PM5uN7SRAalFMbmy5hbIsHAVjGMpISOzridtBGCmJvUFWo8dMzUZIttvbZmTL9DKiVJajIgMj+TH15rg/lr2P18fb2J/pZiOic3U1kqmE7xYpSyshIeFdRkpLfwsxmymL6+xMrxcLEQnrg2WeFCMP5rGJiYxlZ00mo1nZPDlxo1AzM1vNH1OF4jYPRoQmkzF0ZeeJixAaITFSZSEnS48/LixoRMeUH1N4zJsTV2g+LlRoY93vRfguLnSPEr4/JMKTkJDwLiOlpb+F2G7h939fhOXsTP4e8+jEbSHi7Crz6VjPLQtDmSpjoan9XmGz9Xo0Nls/LRiVJMuuimvbwBg2MmIUd2O3scWZV5Z1FleTjlWg2KQcKzNG6syLVFUjGbL2ENutFJ3NJrWHSEhISEj4ZkgKz1uEolBY6/FjPU+nIkLWZiJWY6pKiodVRv7/t3dvK21FURhGVzwkaIyYG9//EcWoqImxF4vJ2toWetPq/jsGCCqa2JvysddhVoTUk53pqarFogfOZvNxH9BqNWZuVazs92MeWMVTBc9083JttK5TWK2NiKobnOspUf1trf08P6ye7tS+oJeXHjgPD/3fd3/v9NW/5gkPMGeWtGbm7KzHznbbA6imsddk9sWiR8HVVQ+DurenAqWe/NRy2MnJ2BtUx9driay+rg3Lr689eqYbgiuSPk9MrzuCPt8E3dp474qu6a3P9ftPT+Noed2S/PhoqvlXEjzAnAmeGTs/75Gz3fbPb2/7Xp3T0/7U5nAYk9JbG8tLNZW9oqNufK4L+qZHx2u5rJ66LJdjIvvLSw+hev3DYcTM5eV4r9bGslW9Xzkeewjt9/3j+XmctNrterw5Wv49CB5gzgRPiIqSzWZ8rFZjyOh6PQaKttZDZTrXar3+ePKp9uFM9+XU8tl0DladJKvlsYuLET41n+v5ebzebte/fnsblyjudj16ao9RzePiexE8wJwJnnB1A/PNTY+Rq6txImu5HLcx1/dqBldtIq5j7q31n6kTVNMoqmWmOnre2thMXXfl1L6fu7vx+cODzcZzIniAORM8/6Hpvpnr63Eb8vHYo6b2+LT2cXJ6LV9VwNRcrRoxUU9w6rWnlwm6G2f+BA8wZ4IH+COCB5iz3/0fdvKrbwIAJBE8AEA8wQMAxBM8AEA8wQMAxBM8AEA8wQMAxBM8AEA8wQMAxBM8AEA8wQMAxBM8AEA8wQMAxBM8AEA8wQMAxBM8AEA8wQMAxBM8AEA8wQMAxBM8AEA8wQMAxBM8AEA8wQMAxBM8AEA8wQMAxBM8AEA8wQMAxBM8AEA8wQMAxBM8AEA8wQMAxBM8AEA8wQMAxBM8AEA8wQMAxBM8AEA8wQMAxBM8AEA8wQMAxBM8AEA8wQMAxBM8AEA8wQMAxBM8AEA8wQMAxBM8AEA8wQMAxBM8AEA8wQMAxBM8AEA8wQMAxBM8AEA8wQMAxBM8AEA8wQMAxBM8AEA8wQMAxBM8AEA8wQMAxBM8AEA8wQMAxBM8AEA8wQMAxBM8AEA8wQMAxBM8AEA8wQMAxBM8AEA8wQMAxBM8AEC8xfv7+1f/DQAAf5UnPABAPMEDAMQTPABAPMEDAMQTPABAPMEDAMT7AeT8JFNJHVpjAAAAAElFTkSuQmCC", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "modified_image = mi.render(scene, spp=128)\n", "fig = plt.figure(figsize=(10, 10))\n", "fig.add_subplot(1,2,1).imshow(original_image); plt.axis('off'); plt.title('original')\n", "fig.add_subplot(1,2,2).imshow(modified_image); plt.axis('off'); plt.title('modified');" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## See also\n", "\n", "- [mitsuba.traverse()](https://mitsuba.readthedocs.io/en/latest/src/api_reference.html#mitsuba.traverse)\n", "- [mitsuba.SceneParameters](https://mitsuba.readthedocs.io/en/latest/src/api_reference.html##mitsuba.SceneParameters)" ] } ], "metadata": { "celltoolbar": "Edit Metadata", "file_extension": ".py", "interpreter": { "hash": "324262bda25e4aeb89fac5521e5e52d6dea4600b0315b63007798d9c65d5c62c" }, "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.9.12" }, "metadata": { "interpreter": { "hash": "31f2aee4e71d21fbe5cf8b01ff0e069b9275f58929596ceb00d14d90e3e16cd6" } }, "mimetype": "text/x-python", "name": "python", "npconvert_exporter": "python", "pygments_lexer": "ipython3", "version": 3 }, "nbformat": 4, "nbformat_minor": 4 }