diff --git a/.gitignore b/.gitignore
index a049dba8..8b93b2ca 100644
--- a/.gitignore
+++ b/.gitignore
@@ -27,4 +27,4 @@ LocalPreferences.toml
# Custom
tmp/
.vscode/settings.json
-examples/src/.ipynb_checkpoints/
+examples/jupyter-src/.ipynb_checkpoints/
diff --git a/examples/src/inputs.ipynb b/examples/src/inputs.ipynb
index f5d1c9b1..5b1e0b77 100644
--- a/examples/src/inputs.ipynb
+++ b/examples/src/inputs.ipynb
@@ -1,473 +1,233 @@
-{
- "cells": [
- {
- "attachments": {},
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# Simulate an FMU with inputs\n",
- "Tutorial by Tobias Thummerer\n",
- "\n",
- "🚧 This tutorial is under revision and will be replaced by an up-to-date version soon 🚧\n",
- "\n",
- "## License"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 1,
- "metadata": {
- "execution": {
- "iopub.execute_input": "2022-10-22T13:28:04.723000Z",
- "iopub.status.busy": "2022-10-22T13:28:04.017000Z",
- "iopub.status.idle": "2022-10-22T13:28:04.999000Z",
- "shell.execute_reply": "2022-10-22T13:28:04.926000Z"
- }
- },
- "outputs": [],
- "source": [
- "# Copyright (c) 2021 Tobias Thummerer, Lars Mikelsons, Josef Kircher, Johannes Stoljar\n",
- "# Licensed under the MIT license. \n",
- "# See LICENSE (https://github.com/thummeto/FMI.jl/blob/main/LICENSE) file in the project root for details."
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Introduction to the example\n",
- "This example shows how to add custom inputs to a FMU, that are used during simulation.\n",
- "\n",
- "## Other formats\n",
- "Besides, this [Jupyter Notebook](https://github.com/thummeto/FMI.jl/blob/examples/examples/src/inputs.ipynb) there is also a [Julia file](https://github.com/thummeto/FMI.jl/blob/examples/examples/src/inputs.jl) with the same name, which contains only the code cells and for the documentation there is a [Markdown file](https://github.com/thummeto/FMI.jl/blob/examples/examples/src/inputs.md) corresponding to the notebook. \n",
- "\n",
- "## Code section"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 2,
- "metadata": {
- "execution": {
- "iopub.execute_input": "2022-10-22T13:28:05.004000Z",
- "iopub.status.busy": "2022-10-22T13:28:05.004000Z",
- "iopub.status.idle": "2022-10-22T13:28:49.082000Z",
- "shell.execute_reply": "2022-10-22T13:28:49.082000Z"
- },
- "scrolled": false
- },
- "outputs": [],
- "source": [
- "# imports\n",
- "using FMI\n",
- "using FMIZoo\n",
- "using Plots\n",
- "using DifferentialEquations"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Simulation setup\n",
- "\n",
- "Next, the start time and end time of the simulation are set. Finally, a step size is specified to store the results of the simulation at these time steps."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 3,
- "metadata": {
- "execution": {
- "iopub.execute_input": "2022-10-22T13:28:51.448000Z",
- "iopub.status.busy": "2022-10-22T13:28:49.085000Z",
- "iopub.status.idle": "2022-10-22T13:28:52.234000Z",
- "shell.execute_reply": "2022-10-22T13:28:52.233000Z"
- },
- "scrolled": false
- },
- "outputs": [
- {
- "data": {
- "text/plain": [
- "0.0:0.01:8.0"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "tStart = 0.0\n",
- "tStep = 0.01\n",
- "tStop = 8.0\n",
- "tSave = tStart:tStep:tStop"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Import FMU\n",
- "\n",
- "Next, the FMU model from *FMIZoo.jl* is loaded."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 4,
- "metadata": {
- "execution": {
- "iopub.execute_input": "2022-10-22T13:28:52.238000Z",
- "iopub.status.busy": "2022-10-22T13:28:52.237000Z",
- "iopub.status.idle": "2022-10-22T13:28:57.034000Z",
- "shell.execute_reply": "2022-10-22T13:28:57.034000Z"
- },
- "scrolled": false
- },
- "outputs": [
- {
- "data": {
- "text/plain": [
- "Model name:\tSpringPendulumExtForce1D\n",
- "Type:\t\t0"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "# we use an FMU from the FMIZoo.jl\n",
- "fmu = loadFMU(\"SpringPendulumExtForce1D\", \"Dymola\", \"2022x\"; type=:ME) # load FMU in ME-Mode (\"Model Exchange\")"
- ]
- },
- {
- "attachments": {},
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "#### Simulate as Model-Exchange\n",
- "\n",
- "In the function `simulate()` the FMU is simulated with an adaptive step size but with fixed save points `tSave`. In addition, the start and end time are specified. Note, that the dynamics of the input variables are not considered by the steps ize control of the solver, so it is highly recommended to limit the solver step size with the keyword argument `dtmax` if the input is more dynamic than the system."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 5,
- "metadata": {
- "execution": {
- "iopub.execute_input": "2022-10-22T13:29:04.979000Z",
- "iopub.status.busy": "2022-10-22T13:29:04.978000Z",
- "iopub.status.idle": "2022-10-22T13:29:21.052000Z",
- "shell.execute_reply": "2022-10-22T13:29:21.052000Z"
- }
- },
- "outputs": [
- {
- "data": {
- "image/png": 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",
- "image/svg+xml": [
- "\n",
- "\n"
- ],
- "text/html": [
- "\n",
- "\n"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "# input function format \"t\", dependent on `t` (time)\n",
- "function extForce_t(t::Real, u::AbstractArray{<:Real})\n",
- " u[1] = sin(t)\n",
- "end \n",
- "\n",
- "# simulate while setting inputs\n",
- "data_extForce_t = simulate(fmu, (tStart, tStop); # FMU, start and stop time\n",
- " solver = Tsit5(),\n",
- " saveat=tSave, # timepoints for the ODE solution to be saved\n",
- " inputValueReferences=[\"extForce\"], # the value references that should be set (inputs)\n",
- " inputFunction=extForce_t, # the input function to be used\n",
- " dtmax=1e-2, # limit max step size to capture inputs\n",
- " showProgress=false) # disable progress bar\n",
- "plot(data_extForce_t)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 6,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "image/png": 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5RvSxZ403io4meskZ7rr9fu2/9+3GD5Xjb09nzvIhgrw4nvrhDMbjYlF96VeuuYY2pQacU+TFOqcxIa76Cn1OsSRDMYnJQCG+q230Dx08/GGz8NSv6CRv75DfnJWNjk6mbto6LY7jqhWErvoKXUZB8A5CD/q8nzVCQYRrfxQeWYAiQtm6g0Xwr6Pom7bgIVWXmxG6bc7KnVFHneb9Mkqnj1pyxuDX7/o47L278IY6/O3pTIHPsXPRLLy/nEEUXLBJUHeoUpAuA33+pNY5jQlx1x3Q5ZRINZo+t8R16BdK4f27hdlGyseUQb94fDH9eYv4Zauq3wcAULEgdNcf0AVUaHtCGFOq6HYLPTYAeL4KJ+rht6Fvn3RUMnWMhfr7HjWfyAa//yjqyGWjI0UnI/qoUx3l3/mSYv9UBX79EN54KpPs5wGZRfD68fQgJ177o5rX3HVonz6vNOCP6/NK3Yf2a25C33E3HNRLJwh1uSXu+gMj/z3QIz5fjf+xOCTWqVgWnjmavuI7Qd3HcVCxIHTVV0j48AFF6XNLXHUHBjm4dxd+dGEIjaKjefBItL4SN6o0plEU+KGtX0YtOcOXi1F0vKF4wfCOjd4v+7RZ/Nse/OnJAZqJdAg2LGM2t4vrKlRqIRVFd0NlMK8GnZAEDDvGOqcxGdgxyPfY2NRsqQbU55S46itG/nvND8Jf5tL+nvl858Q0akkyde8uNR8NQbWCEGOuqVqXLY1d3oMut8RdX/HYfnyshZpnCkmMzHjSoqhrZtJ3bFfnpuzc9yObmu17NlvU4pOHtn7u5YLafvH3m/kNJ9A5MYHfoFgW3l9O37db2GpT4fmDa6tHsQkoOi6YQfS5JROGbGiMx91YpcsoACTZ0Zm1ZOO+bjw8AAAb6nGfG64oDu02/shC+qUavL9Hha/DCOoUhFx7A4ozBVNidDz67JlD9RVrDwj3HxHWRbu5DH1jFXd2qfApHNr2ZdTCE32/Xp83CzsGufaGCX/rFOCcjcJf5tG/Sg72mJIXSz29hL7wa6FfdSFzroYKfXawLgNdTom7PpDeeG4MPS6YDqG5I7gbK6U9kQNCbGaBu6HSJcCt2/Dji+ggiztOSVIE3DOPvvYHNSuF6hSE7sZKfXawBWXGwGbkuzvaLspw5QahbQRAFAN3z0W3bVfbU4gH+9wNFRGzfuXHZygqct5xwzu/nvCXt2wTCuOoKyU6Ha/IQiemU9epzlnobjioCzqCUZ9d7G6omPq6n9hjF6/9UZixgY/5N5f3Fhf9EjfnXf6O7ULdNMiUdTdW6TJnSDumPrvY3XhwbQWenUgdYwnHdnR5Eep2wTvqDWJXrSAMvrLaGGxu5oAhe7XxkLTD+sIfClHTIGxSV/NMx97vDMVHUjqDX5+KnHuMY/fm8ZEaX7SKHzSK65dI6bt9ZCH9rVX8pFlVy+5ukEBBYVOz+Z5O7Jg6cKlpUDzrK+GML4QkA/X2CfTw79nuS9iBlez6JTQvwqIP+Cu+E7pVXeLZ3VSly5JYEOqyi4fqqx4uFx5cEKYNnKbg8cX0LduwWmuQqlUQSv/wPVwuCGlFsVYZmiEwCO6dh+7coapncHjP5og5S/39FJuWCwhxrb84jvRzcNm3wgtL6XiddPMDiGLg2aPpK79XT04xHurHA71scmawAyFal1HgbqzyftWGenzkB/x8E1V7LnPXXDQrkfIY8VgEC5OoNQvomnNZAw1l7/LftKvqtDEC391B0QwdZ5R2WF3mjOGGqjMzqcAqawfGcRaqLJFaq9IgMhUKQtHl4Htsk9XrCgybA16sxkfOK3Y3ytMV6NxcNMTDx00q2S/wUD/XcshQND+Az0aUHeUo/370T27dJpySTp2QKv2mcJyFOj6V+otaQubcTVVsZgFQEiyULmuGu6naywX378a3bsOfn8zcOQfpJ1HU43Tw5GL630vp8zfxL1SrcIflmqsDbknvhU46rouKvisj3IG7Dy5Aa/aqU4NXoSB0N9ewqbkShmkBwBP7hQvyUHJhkfeXP3QgCu6dh+7dpZJUb8f+H/Uz5lJsIBpcxKzFjn0/t4f9vkP8uEl8aEGoElrWLKBfqcUHVBEyJ6G/SpdV5EUjvGWb8F4D3vJrZo5xaqG7LI3afDrz191YfVWe3U01bIb0gvChvcJASmFiZ43kI3tnRhz12xz04F6VnAtHo0ZB2CTxKazXDc9U4tVliE5IAoyF3i4JB/edFdmIw/Bxkxo2C+f+rRGliwP7rC6rSBjo9RQ34DFc+b3w2CIUJ6lRdDRmA9w9l75+ixpefndzjVQuA11mIdc8sSD86278Zau48VTG91TOgjjqf6fRj+3HL6pLL3Q3V+sy8qUd0+qAl2vwzNIid7MMh/K759IvVOFW1TVMVaMgbK7WZUpTYtTDugp8WibKiqYAgM2c4W6awjUSIiiAu+eh+3cTv1OInNtVs9dQfESAn6coQ/ERjoptAPBUBU6JgHNCXOXniiLUPqwGuzTXXK2TSEGh480AMP5Q+GotfqEaf3oy42+r6sxo6vOT6Tu2CxtVExQmilxLrU6icscjPFwuXFyAjLkFslinLJFwaRH66x7id6ExqFAQck01Ur3tAOAU4J8VwkhzE11moVzWUQA4Mxs5ePiC8NJ/rrr9jCUbRcUGPIKh+AjXwR2dTnhgjxCi4lKjYRCsWUDfso3s3hQeoUXHm6QakM0oHKOU7LGLN24VPjqRTgmo0ElhHPXmCcxFX/P1qkir4LutlM6AouMlHLPLCS9V41vKkC49n2tvACyDoeKWMvrteqyOezSC2gQhHh4UBnsZc5pUA75cg480o5nxh10duswCrjncpvkRKIA75qAHdpNtpnMe3GGYGag6CAAAhhnzXLX77t3uuigfFcWHI3Du1AwqJQL+XUOwJHQ3V7PpUprpdBkFXNPP78IAB+dsFNYupkuC6E22NIW6Yw59rip6gHAttTpJFxwAnjwgnJOLUiMpSh/BJJg5qwz9sBL1cPVM9FfyTVOjUZsg5FpqdWl5ksTFAQAW4dF9+OZZP6+SLqPQ3VwjY8Xhc3NR6zB8ZyX4OOaq3GkoCkoQoqhYzph26EDF3XPDVPQVAB5cQN+3CzuJPYRIvi+z6fnultqR//7pB+H4VOrc3GC3lGtLUEY0dQf5FSTcLYekPXkMcPD0Qby67PAKsxkFbpkO5deX0h81YTXVQ1CbIHS31LLSeac/asLxOjg65WexiqLjKH0Eb7dK9RX+QlNwaxnBgVtCn10Y7A1+R/7KMPvGiHJ/HVHBsMBMzTNRz1SSehB2N9ey6VL6q3TpedxPgvCDRvyjTXxskTTnkmePpt+oE0lPLuRaD7FpeRIO+GwlXp6GRipb6dLz5bJOxevgqpnoARUphWoThNIeex/fj2+cNXaJdOn53KiDcPj5vwK02w7l3URuE86qXYaCOUGq7N+0i5/rZ5f1hrsr3j3z0EN7sYPMljRc6yFpNUI63iyKWOiz97jg6h/wC0vpKIk6dBr1sH4J/cdvhWEyl9oD13JIly6ZIOQwPLH/Z3UQANi0X2jkYeb6UvrDJtygFqVQbYLQ3Von1Slst12sH4Dfjmt3yabny2WR8KCn4bpS9HA5kccxV80efcHsIAe5Y4dw5tJSvq1OdDslmZWPzDFSi5KIVArxYK/IuenEJGmH1aXnc62HbtsurMiijgq61vloTsugFiVR9xBbygAP9oo8RydItuBv1OEZ8TB3VF4mm57LtTcAludpjNfBFUXoITJ3ofGoShCKbqfQ08EkZ0gy2hP78Z9KEDNuhXQZ+WNKfIWfVcXosxbcRGCfQlfNXn3hnGBG+LhJHOTgvBkGXXq+q+7A1B+QlLvmoof3kVdx0d1yiE3LlXxYNjXnUHXtx03iA0dI76x9bCH9Ug3eR6blw91aJ+2CP7YP31j6i0VGhig6JoHrbJHwW/zi+lJ6Q51KcgpVJQi5tgY2OYuiJTDQWB3wURP+Y+EE68Om5clokfAQy8IfCtET+wk7jvGdrQAUY0oNeAQR4M87hfvmI0SBPr/MfSjcXfHmGqm5RiAu75uTzlIyGiYtf/+BuocWhKSgQVIE3DuPvuYHIqspca11bKpkgnBTm8hhODljrM7NpuVxrXVSfYu/mAywshA9uo+wd2FCVCYI69i0HEmGWn8Qn5eLJozFoOOMFIXkqi8zwrUl6OUa3OuWdxb+4Tq0T19QFswI79RjFsGvsxAA6PNKZWkPe8cc+uFyTNb2zLXV61KleTVG8wmXnTtUd1F+qLaRy4vQIA9v1ZG31XJtUmqET+zH15Wg8aZnNj1XXuvUjaXopRpsJ7/6qLoEoUSnMA7DM5X4mpmTLg6bnse1yqwUpkVRp2Wi9QdJ2iNcNeX6vMAFIRbhvt34vvmHG5HqsovdLbUiH+7eEIuTqIxownZnafdlD8M83FJnSeHsEDJPLaLg8UX0bdvJy1qR8ORR2y9u7cQXT3Ta0MmqEQJAWhT12xy09gBpt2ccqhKEbone9rfrcVE8eMkLZtPy3C1yPn8ebpyF/lmBOXI2ZFfdfn1uScAff6cBRzFwcvrh+0LpDGxShiyFfm4po9eQEyYg8hzf1cYE333plzyxHy+yMPqUTK6tQdqRR7M0hZpnpP5BVD1uUeAlXPC1B/AfC1HERA4feU2jHlbPQv86iIdIju8FVQlCUeTbG1iLBKewpyrwn0q8rQyblsu1yS8IZydSRfHwJiGqidBjEzl3wEV/RID7d+MxGfS63Jnu+nDHywDAKRkUj+ErQmrd8R1NjCmVYlgJx7S74PH9wl/nIzY1J9Tvwt+ORI+Uk9T9h7e10AnJgTVXGcMAB6/U4qsmsU7RcUYRC0J/T/BfFDAFcdTSFPR8FRm70GSoRxDy3VYqIhpFRgc5zh672DwEZ2R6Wxldqsym+RFuKKUfJyRkxlV3QJ9bEnAG4fsN2EDDKb+MF9DnlLjrK6SYnX9QADfOQo/uI8MixLU1sFI7CNfsFc7OQXmxFJuaw1kbpR18DDPiqLOy0ZpyMlYbJLWLvlSDl6Wh9Cgv1in5D+W3zkaP7SPJNDUe9QhCrq1ekrd93UF8RRGivW7XjDlNGOgVXY7gvy5ITsmgHDz8j4QaHO76Cl2gdlER4K978F1zxhU3yC52NcjTKvnCPLS3W6zoJWDlOWuDtH2qOxzwfNXh28Facri2egkHn5C756HnKnH7cKi/Rxq49gYmJSv4cUSApyq8BSvA4UO5zILwCBOVF0uY13wMahKEErztvW54ux5fOmOqZUGITc4Mw/s/JRTA9aVk5FG46iv0OTMD++ynzaKA4YyssfeFjjdRDMN3tQc9O7/R03BlMU3EynNtDaxFgn15hIf2ChcXoLQoCgDY1GyuvUHCwSckNZL6vwJiKgty7Q1sanbw42xsFfXoFyUex8Om5nDt8m9Eq8toQkt8eFCRILRKYP95qRqfko58aSjKpobjIOwLl+SjH224tl/RqonocvBdbQHXIP77XuGOOROEjwOALqvY3SiPUriqGL1TT0DsONfewEjhO/fQ4YCXavCtZYedtSg6Higk9NmlGn8ybptNv1pLRvq2VMEK6w5O6h0cQSEb0UnplAgEd4hTkSAMWiMUAdZX4iuLfVoTNjXHLbdp3kMEA5fNQAoPq3M3VbOpuYHVOvimXex0wG8n6b6ry5ohlyA0G2BFFlJ4xTXsHMKOQUa6Wl+P7RMuykeWyJ9/wlqyQ+0mBICkCPh9IQE1vUSXQxjqZ4wpQY7TPCRubsdT5mgyyZl8V5soyBy1SQHcXIYeJsePOwaVCEKRcws9HUxSejCD/K9dZBAs8WqIGIFNzQ1p1LhfXDUTvVqL+xScXO9uOKjPLgrssw/uFW6ZPanXVpc1w91UFfjMguNPJWhdBVZyw16+vZFNyZKqMVm3C56r+kXpZwBgLVl8e4Mk43vn5jL61Vqlewo5ayOblBH8gj9TiS/KR1PWMadYHZ2QzNtkK7Q2wnm5qLIX9tiJVApVIgh5WzNjtARZXCDhkCAAACAASURBVO1fFXhVka8LwqZm8+0NMjYmHE1qJHVKhqIjmN2NlbqABOFuu7i/BybMJvagyyjg2hrkOhHPMVK5MfBeo3JXnrM2slIEbnj4ZwVekYUyfhnEyKZkce0h1wgBIDkC/q8APabsYF3O2sgE7ZHlMDxfhVf5ap3KVoJ1VIfg2hL0CJkV11QiCLn2xiDDAawO+KoNX1zg64KgyBjKEMH32IL5Ugm5vhT9s0K5db/cTVW6rEAE4UN78Q2lSDf5baF0BsZkCY9GMiHXlKCnKpT78kuyL3sY5mFdhXDL7HH9WCxZXEc4BCEA3DwLvVitaL/sYRU8ON5vxMXxVHG8b9aplHDEK/nC5UXos2bcTIIfdwxqEYTWRiY4B+ELVfjsHBTrT84xm5rDKyBey8MRJio1Ej5UpGoi9NgAKDre7O8HD/WLm9rw5VOp6bqMQlnqy3g4MwvV9oNimyTw1iZWohInL1Tjo5LRjLixuzOTnMVbm8JjHUmLos7MVnRNL66jiU0JdsH/VeGrOgiHA3fDdBDxTpwOVhaif5AQSj0GtQjC4E5hWIRnq/ywi3pgLUp5/jxcp9Q8CndTlS5rRgAffGQfXlWMoqc6nbCZBTK6CRkEVxShdUot+spZG4PflwGAx/DYPnxL2QTvCIqMpvQRQl+YytDfUqboml6ctSnI4mqVveLBXnHFuGShyWAt2co5kV9Xgl6sxv3hLgAcLCoRhHxwjpDPW0STHuaZ/PNvK8ci4eHMLNQ4CLuV56x2N1WzmYX+fqrDAW/V4T+VTN3oTpdR4G6Wswb6ZUXorTolvvzYMSi6HAHo4uN5twGnRcHCpInfESY5k7M2Bf8tvqDkml6iy4GHB5jE5GAGeaYS/2EGYn3emxmjRRjsU0J9DwDIjKZOTEfPKjuUejxqEISi2ykMdDNGS8AjPFOJr/DZEDECa1GWIGQQXD0TPak8pdDdVK3L8FsQ/uOAcEEeMhumvpK15PCdLSInW9RsSgQsT0Mv1yhu5fmOFkaKCEYAeHQfvnnW5P1YUjL5jjAJQgC4pQw9tk+JwbpcRxOblB7Mgjt4+E8tvmzKmh6joSg2OYML4/p756ZZ6B8HlHh3vKAGQch1NDPmdEAB/i2tQ+JmKz4/1++PM8kZSsjgGc2lM9BHTbhDEUfDnxBFrrlW56dGOMDBM5X4psl33tFQrI4xp8l7KLmyGP1LeSEzXEcTI4Vd9Dur2OP2VoCXDaNGCABHmqmcGHirXnELzluDXfAN9fhIM5Ud458oZVKylHMon2+icmNgg/LujhfUIAiDtIs+Xy2enze1I2o8FKuj40x8V1vAXy05CXo4Lxc9rSR/Fd/ZiqJiUGSMX596rgovS0M5Pm8HuvR8rkVO6+gxFgoANluVZZfmO5rY5Izgx3niAL6uBE1c2gcAAJjwaoQAcNMs+jHlRepzHcGGJj1Tia/wM1gBDrsJFRSvcNMsmqw8CjUIQq6jOeBwAEGE5yqnjkucDKU9fwBwbQl6+qDgUkxUnbu5hk0v8OsjHIbH9+HVvqmDHti0PLesghAArihW1hEEPMaSoENGGwbEb9rx7wq9NiZLzuQ6moP8Ir84LZMaVl65ec7azARx8tjfIzYMwmkZ/gvClEzlmEYB4LRMysHD1wq7O15QgyDkrY0Bv+2fNotpUTA7MUCbPmvJCkNxKb8oiqfmmqjXDyllR+aaa3QZ/pUYfaMOF8X7F7uky8jnWmRujPV/BeizFtwZqm7tgSCJRvjPCvyHwilKnKDoOADAg71BfpfvUAA3lCKlKYV8R1Mw1qlnKvEfCynG/12ZCVdNAx/x9Cl7hJyKa2oQhFxHc8Bv+/pKIWB1EJT3/Hm4vlRBXRHcLbV+1doWAR4ux6vLpg4WHQ2bmstZGwHL+VfH62BFFnqxWikrL3Juoc8eZNHLQQ5eqpm69DMAsMkZYVYKLylA2zpxVZ9S1A6R54S+roAXfJiH12rxH/0Kk/kJJiEJOwaxcyiwrw4Fl+Sj3XYy+pSBCgShyLmF3k7GnBrAZ5sGxR87xPP8D5MZgU3J4sNVU8N3lqdRvAib2hTwCIoi13JIl+GHafTTZpGmYHmafzo6pY+g44yc3BUXryhCz1RiBaw7AADf1cYYUwD5d6QYw39q8dIUlBU99e1gkjL48ApCAw1XFCkoTJrvbA1mwd+qw4uTqUwflnoCKIpNzuCtYV1/7+hpuGYm/Yjii6R7IF4Q8l1tjNES2MP3fBW+MB9FBlGglElK5+1WRQWOAgAFcF2JIpLreXs7FRGFomJ9/8iacmHCrO0pUUKr7oVJVAwLXymjGQ0ftINQBFh7AF9b4tPtYJIzwn8QuXIm/WYd7lZGxTW+o5lJCtwQ/UwQwQrgsU4p7FC+qhh90IjbhhXxOniHfEEYaB0HHsPz1WIwTx4AUDRDJybzna3BDBIKLs5H2zpxtdxWI67lkC49z/frt9rEpkE4Z5KOS95h03K5VpndhABwRRFar4xsYq6jmTGnBTPCV60iiw4HxE4Jm5Qe5sBRAEiJgF9nKSV9m+sIPFJmX7fYPASn+h8mMwKbHG6NfEoS9XBxvtI7xHkgXhByHU1sSiAP38fNODsaShOCzTVmkzP5MGZQ+UgEA1cUya8UulsPsWl+CMI15fjGWSiAYAEA0KXmcq3yd4i8KB9tasNWBaRy8rYWNrjGZP+swNf44B30wCSly9IM6LoS9JQyOmHxthY2UI1wfSX+4wxqsl5jvsCmZCotcA8AbpyFnq9SYtGlMRAvCAM2R6w/GEg1mfEo8/kDgKtm0m/WyVynn/NHEFb1id934D94DdP3ApuWq4RmNDEsnJ2jiJAZ3tYSjKWuYUD8oWPqxrAjMMYUob87/PV95hipvFh4p0EJCx6gRjjMwxuHAgyTGYFJzlSaRggAWdHUSelKb14NKhCEnK05gAzW+gFxZ5cYmAluDExKlqIyeEZIjoAVWTKXO+Fa63w3jT5cjq+eSQfssqXjzSLPhTOCfzIuL0LPVmLZY2b4zpZgWlX/6yBeWeCPBx3RjDFFFjfB9aUKCJkRRc4W4IK/UYd/lTy2y6O/MIkpwkCP6FaGv3QUq8vQk/uxW+774x3CBaEo8p1tTJLfjpBnKvElBcgQVDzdYZRpGvVw4yy0Tr7kejzYK3JuOiHJl4tbh8T3GvDVPhviJkQhHUqPMFEJevhS1pAZoc8OjA5FRgf2cQcPL1b7lDUxGrmso6dnog4HbOuUecGRIRIZIgP4bGC1jseCEGNKVUKr+jHMTqRKE+A/yqvEOxoJBGFFRcUpp5xiNpujoqKCH80v+B4bioqldD4UZh6FG8OL1UEFaI2GSUrn7e3yZrBNRkkCNcdIvVIrz9zcrXVsWq6PFz+2H/+uECXqg/pGNlUR1lH4KY9Cxgnwna2s/wfEEd6owwvMVK6/FS/N6VynDBsxTcE1JTIHZfC2AEOT9tjF9mE4OV2CwuhsciZnU5x1FABum02vKVdu23CQRBBGRESsXLly3bp1wQ/lL3xAqfTvNeDSBGp8f9HAoFgdHZvI29slGU1ybimjH90nj5WOa61jU30ShHYX/Lsa31ga7NPIKqa+wQV56Ot23D4s2wR4WwtjDtwu+lQFvnqm3wYTJimdt8kTQf2HQvRps5yR+pytNTC76PpKfOkMFEyYzAhMckb4A3d94RgLZdTDuwrw406GBIIwJyfn/PPPz8319ewvIYGdwv51EF8pRZjMCEzYCy36zrEWKoqBj+ToXM+1+aoRrj0gnJWN0oLzkQAAm5rDKaNDqewhM3xngPsyAGy1iX1uOMl/HYVNSpPLNBeng4vy0b/kq/XK25oDWPABDt6sw3+cIc2hnEnO4JSUUz+aO+bQf98ju998UsLqI+Q4rrOzs+4nmpuDvWcBJO5U9Iq1/fBrn7s/+wKr1IOYh1tmozVy1Hfg2up1qTlTXjbAwbqKiVuf+wtryeasTSAq4nW7ogg9VyVbyAxnawnAd+7hqQp8ZbG3XhOTwZjTeTlMox6umYmercROmTzifGdrAMkqrx3Cx1lQaqQ0gpBNzuQVaRoFgNMyKRHg02ZFvJvjCaKqiv9UV1d/8cUXTz31lOe/MTExmzZt0usn9QsNDg56H9DV3giF8wcGBnyfw5N7mP/LAeeQQ8LayHycWWg4CP5MI5wsN8Ltw/rP64Z+ZQ5EHE55FyZEFHius9URmeCcalmerGSOSaJS0JQX+gQVGdPXVIsSgyqwKQmFeohjdB/UupelSLA3+3sX3B3NTGQC7/+adjqpj5p0D8xyDwwEsGchURT7ra2UP7WEpMKCYE48++IB7uKcUAlDL3fBbW1yRcZzfi74ugP6+2fzAwPSTFg0xPJdbQN9fQE3Zw0pN8xA9+1kjo4PNsHG33fBYDCw7BRt9sIqCEtKSq655pqVK1f6/pGYGG997Abt7bHZhbTXa0YzwMHbzVz5WUxM0Fa40bgzC3p3f+19qvJyy2z8jxp0Um6AtzuAP41rq3cYU2ITjd4vc/Cwrob74hQmJsa/iKfJcKXl6vo7I7L8a/wUIq4qwS83MGcWSBGd7NddwEJ/X1dcZh7F6vz9ln/W4bNzxAxjoOGmSRkGR58uJaiKNgFz0xxx9VbhyrIQbmsT3gWRc/cP9sZl5vlV63GLTRwWhDPyJdIHAQBgONYYwQ0xpkBqL4eai4vhwQp+a3/0Mj8rCY9H8s1WiQcHH8HOYewcpuNMvn/kPzX4+FQJfFFjYJIz+A7FRS2PZmUB2tsNe+zhs0twbfWsD3bR9ZV4cRIKvr7PCKwlWyHxMgBwQR7abMWtQ+E2B/HdNjomIQApKIiw/qDfWROjYcypMlYcXJZG8aIMTQp5ezudkORvxeOnD+JVxQFYoL3BJKcrMK3eA6Lgjjnovt1K7M0kgSB0OBwbNmz46quvBEHYsGHDJ598EvyYvsB3tjBJaUD5+iCJAOsOBpupNiEoMgZoRujvlnxkqdDTcPMs9Lc94fMUcu31rGUKQegU4JF9+K65kvprLVm8tUHCAYMhmoXzctHz1WHflztbAwvl/7gJp0XBXGPgmzNjTuPkE4QUwLVylJvnba3+xujaXfBh0xTtjgOATQp3Myy/uCAP2RzKaIzzSyQThDt37vz1r38dVkFoa2H9efj+1y5SAMf6VkHYXxRY8XYMlxWhzVZ8MFztwbi2hik1wmcr8REmKphtdzzKyaDwsKoYPVcZ7gwqvrM1sMZkT1Xgq4ILqGbMafLWoL8kH/1ow4f6w7rifGeLv1mbL1Th32QhY3CJs+NhktIVGy8DADQFf56L/rJLcUqhBMb0xMTEt956K/hx/IW3tfoVF7f2QEjUQQ9McgZna9YXzA7R+METxcB1pfQDe/Arx0rjsvLOlBqhg4eHyvFHJ0o8GSYpg7e3AxaC7MMnFWWJVHoU/LcJSxuo7B2+qy0AjbCyV9zXLZ4TRHtOOCwI24IZIUgiGLh0BvrHAfzk4vA9AHxnqy5zhu/XYxGePojfOF76GTJJGUPbN0o+rIScn4f+tgd/3iIGkJ8TOgj2EfKdfqQMNwyI31rxJQWh+ntZmYpL+cU1M9GXreHo6I2HB0XnMJ1g9nLN05V4oVlidRA89Q3iTPLuxWNYVYyeDm+VGb6zNYBwiXUH8aVFSBfcK8KY0/iuNnkzWK4qRq/U4t4wVv/m/cym/6RZNBngSLP0kkDhGiEA0BTcMx/9eaey6swQLAj9KuXwVAVeWYCiQhZNxiRlKF8QxrBwfSl9/+6Qb8qctYGxZHtx3w5ysGavcM+8kDx+bEqmosqgn5uLdnaJdYFkIwRIANn0Axy8WotXBV13EBkiKVYvDPQEOU4wpEVRp2ag56rCd/jw1yn7VIUQIusUHZsAGOOh/lAMLhVn5yBBhPeUVGiGWEEoir47QoZ4+HeNH53VAoBJTlfU5jsZ18xEX7XiihB7Crn2BtaS7eWCJw/g41PRrMSQ2EaYlCxOSWXQDTSsLEDrw1X0RBR4oc9OJyb79amXavCyNGkCqtmkNLkKrY1wQylaeyBMTQqxcxi7HHRsoo/XV/eJu+3iecGZoL2gfKWQAvjbEfRdOxRUfZRUQSj0d1OsHkX4lO30UjU+xoKy/awg7BdMQjIe6FVgD5QxxLCwuoz+y87Q7hB8ewObkjXZb7td8OR+4d75ITNTJ2fyCusQeUUR+ndNmIqeCN0ddKyRov2wfogA/zwg2UmRMaXyXTKbpueZqNwYeLs+HJJQ6GpjzKm+h6+vPYAvnYH0IfNgMknpnOKtUyelU5ZIeCGMWrt3SBWEfGebj2FaWIQnDuAbgi7oPAWeHiiyxsv5yFXFaItN3NEVwsMYZ21kLZMKwr/vEX6bg/JjQ3UuUZppFADyYqn5JuqtunC89rxnX/aHL1rECAaOTpHmjtCyphKOcOMs9Oi+cCw419nKmHy1i/Zz8NohiWsdj4FRgEbuC2sW0PfswoPKaF5PriD0NVLmoyacoIOjkkMeocSYZas47BcRDNw9F926LYTqCdfeOJlptGFA/HcN/su8EEb0MUkZfGer0hpjXT2TfiosTZL5zjZ/I2X+cUC4tkSyrYAxpfJd8jdjOS0DDfLhSK7nO/04ebxQhU9Kl76mx2hYWSu++s58E3V8KvVQuSJSKcgVhL46CB/dh2+WoqDzlDDJGcq3SHj4fSFqGw5VAVyhvwcoCkXHT/jbO3bgP5XQKRGh+ObDUDo9HZPAd1tD+B3+c0o61eUMR/NYvquNMVl8v76mT9zZJV6QJ9k7wprT+C75NRJEwU2z0COh32d9j5QRRFh7AF8fYuuUXO2RA+DvR6KnD+LGQfldhUQLwqkfvi02sXUIzsoOx5/JEqIRAgCD4KEj0eptQiic1by1cTIH4Rab+K1VvGlWyG8Hk5yptH4giIIrZ6K1oW8e669pdG0FvqwIGaRT0WmPRqiAHiCX5KNddnF/T2hn4vuh/P0GnBIJC0KQNTEaxpzG261Ks4hMSHoUdV0JfdNW+aeqckG4phzfOEuappdTQkQGxQi/zkLJEfBsCPLbuEkEIRbhuh+Fvx0ZwiSWEdiUTAU2ZvtjIfpvM+5whPZb+K522uirIOx1w6u1EruslJBB4UFPw7Ul9MMh7kHGd7X56CN8bL8E3aenhGJ1KCae7+4I9RdJws1laI9d/LxF5mMTmYJQFHm7dUpHyMFe8YcO/Hupq/lNBpNEhml+hMcX0ffsErqlDnTlrI3MRJEyL1ZjmoKL88Nipk5SYofIBD2cl4vWhzS5HmOhx8YYfe1C9VwVPjVDsn54IzBm+QNHPVxZjP7bFELjG3YOiZybjpnYETCaH21ihwNWhMc6lZRByl5koGHtYvrqHwQHL+c0iBSEfI8NRcVRuinq9D20F19bQkeGq9MUiowGRqfk0ttjKEukzs5Bf94psROFtzayyWMFod0Fd+0QnjoqPMo5sMnpnCJTqa4tQU8fFFwh81vxvZ0oKs7HvhMchrUH8I0hsFQzJosS4mUAIE4HlxWFMHz0cGiSD7kTa/biG0vDZZ0ix00DAKdkUEeYKHm7UpApCH0wytcPiP9tDmFx0Qlhk0h6/gDgr0fQ7zVgaSM4OGvT+NyJW7cJ5+UhyQuqTQaTnKnMxljF8dTsROr1Q6Hal4Wudt8jZTbU47yYoHpNTAZjShUUU+Xu+lL61dpQWaT5Lp9idCt7xR9tYbROmcnIoBjhycX0i9V4ZyhzurxDpiD0oabwg3vxqmIU53dHtqBgzMTEa3mI18EjC+nLvxU4iXZmob8bEI1+2aD863bxy1bx/vnhK4L8U2Ms+d1U47lhFv14yPoE+bgve3h0H76pLCQ3hTGl8nalCMLkCLgoHz26LyQKh4+hSQ+V42tm0hHhsk4xSekcIaZRD8kR8Ngi+nffhNBY4h0yBeFUmVKNg+I79fj60nD3H2CSZO5BEwAX5qHUKHhorzRbM9/RxKZkjv7JIAeXbhbWHUXHsJJ8g6+wyRnKLDS1PI3CInzZGpLDL2/3VSPc2Ca6BDg1IzRV7hRjGvVwSxl6oQp3OaUfWfAha7NpUPyoMazWKdl7gATAhXloZgJ123Z5JCGxgtDrKeyvu/GVM6Xv9TUljDmdI8oi4WH9EnpthbC3W4KtmbOOFYQ3bxWWWqjTQrPheoFRaodICkKY38Z3tfuoEa7ZK9w8S+L26CMoocraaNKjqHNyQ6IU+pK1+VA5vqwIJYRxO2ISkvAgARUfx/D0UfR7DeLHTTIYSMkUhF3ecidq+8X3G/GNYVcH4bBGSJJFwkNGFPXoQvrir4Xgi2Hy1iYm+WdB+FET/qJVDGdnuBGYJIXGywDAhfmoohf22KV/4XnffIS7usSDvXBhyCJ4UVQsYBEPD4Ro/AC4Yw56thJ3Sq0UTnnyaB0S3ziEbwjzdoQQY0xR1FnEFxL08Npx9KXf8uFs1eKBQEGIsdDdwRgnfdv/vBPfUEqH8/w1AmO0CD02wIooGuQXF+ejWYnUDVuCnTnX0TiiETYNipd/K7x2HB0bXqOoBzZJoRohAOgQXFeK1oQgv43vaqN9yJ34+15846xgWw96h1aYdTQjirogD63ZK+W7Kbqd2DlExxm9XPPgXvzHGSgplKWUJoQxpxPnpgGAXyVTf55Ln/mlMBDeGqTkCUK+x4ai4ycLEN/VJW5uF68LfdbqhFCsjo5JICWVdQxPL6E3tYn/qQ1qd+asTUxyFgA4BThno3BzGb0oSZ4+1IyyI3ivKEJfteJD/VKefPFgL8WwU7ZkOdgrfmvFlwXdetA7jNHC2xUkCAHgjjn0i9W4dUiyNec72xijxUvuRNOg+PohvDo0EUneYZRR+jwArp6JfpVMnbeJlyqCzxcIFIRe4+Ju3ircPS8ctUsmg0lKJytweYRYFt5dRt+8VdgeaDYFHuoHLNCxCSLAZd8KubFUKHLUfIRJTBEGekQujH3K/SGGhSuL0UOSKoV8l9WXVPq/7cHXldKhfkeUk1M/giUSLitC90rXmHrK0KT7d+MripHZINUX+gGTRKRG6GHtYpqhqN99E5IakBNCpiCcJFLmg0Zsc8Ifw5WsMyHE1ZcZTUkC9fzRzJlfCYHZ6LmOZo+D8O6dQk2/+MLRYUqfnxiPm0TBe8F1pfS79bhJuqInvoSM1vSJn7eEI4KRMVmELmXVPQeAW2fTHzTigxI1pua72r34aKr6xA+b5FEHAYAxpZEYuOeBQfDm8bTNKa78RrLMLu+QJwgni1d2CXDzVvz4IpqR9W9iTKmEaoQeTs+k7p6Lln8iNPtvQeI7mtjkjIfL8YY68aMTmbBlTU2GwsvwJ+rhsiL0d4kSV+BwldEpBOH9u/G1JeHw2jJGi3JSCUeI18Fts+nVW6XxFPJdbfTk4eu3b8ery+j48KYyj0BiKtdoIhj4cDnT74bTP+d7Q2/WIU8QTmYafbgclyVSy9PkVEIAgDGncSQ/fwBweRG6pgQd+7HgrweL62j+H5f+XBXeeCotizloDEyS0htj3VxGb6iTrBKmYPemoADAwV7x81Z8bVg86IxRWcEyI1w9E1X1SZPHyXe1Tbbgm63iHrt4TXgrW42GjkkQORd2Dsk1geCJYOC95XRxAnXk+/xWW2iNpIQKwrEPX22/+OQB4fFF8v85jDKasQXJDaXottno6I/5zVZfnz+nAHsONn7GpX9zOhPSvqO+o3wztVEPV85E9+2SqJqBfQof4d078c2zwhTES8eb8FC/An20OgSPLkTX/yiBzU2YJHdCEOH6H4UHj5SyuZXfUBS58TIj0BQ8sYh+8Eh05lf81T8I1pB1bpFfcvjH4b4TvxCEIsDl3wp3zKEzo+Xff5nEZDzQq8D3318uK0IvHcOcv4n/+wHGPdWWsccuLvyANw60PHx6dkib7voFa05TZsXR0dw8i/64GVdK4bXy7iPc3ilusYVRR0GIjjcLioyg/nUWyoyGJ4PrDSkKvNDfzSQmjf/Vc1U4hoVzcmXeXUmsLzMhv81B+3/LGmgoeZu74Gvh/WbpF5YwQSj0daHIGEr3C7vbugrsFODaEmX8LQjRiclKCxwPjOVp1I4VTHkPKn2Hf6UWTygOq/vEy74VTv6MX13EJfK9sWZfGwCFASIC5+J0cEsZfceOYNUTkXPjoX46zjTZBau3CffMQ+F03DImC29XXLyMh7W/oh/aKwQTqSR0d9DxJkBjlT6bA+7eGb5GK15gTWS7CUeTqIdHF9K157LHpFCft9NTHs39Re54Bj8ZX2W0sle8d5fw3RmM/M/dTzCmNL6zdbIu7WSRGkm9vsS9fSD6wb3CDVuE5WlorpGK04EgQv2A+E272DQoXl6EKs9ho2xN3eY0X/rRhA0UFQsICQM9dEyC3HPxxtUz0T8r+M1WcWlK4KsndHfQ8WZAEx8H32/E3S74XXgDqpVc3CQ/lrqhlF71vfDJSQHugZPVlLlhi7CyAJUmyP8iMOZUZ/VuuWchJQl6WFWMLkrndEjiGARlaFE+M8b44+Dh/E3CA0fQhXHyP3YjsOZUdVgkRjg+lfriFGb3mcyJaZTVIe7sEsu7xQQ99eACuvkC9t75dLwOuI4mNilD7pmOhQjrkIGGvx+Bbtwi4CDso+NdBiN4AqofW0iH+bBIG5WrEQLA6jJkHYYXqwNULnh7+/giPh814W2d4j3zZPQN/owCUzkVC9ka4ZXfC6WJVKhrZPgLY05zt9TKPQvpSY+iflc46VbK21qYZOUJwqR0vrNFn1si90Sm4Lw89NRB/HxV4AVfeHs7kzixXfqRfbgskVoW9oBqxmhxH9oX5i/1HRbBS8fQyz7lj7VQOTF+L874JMJOJ6z6Dr9xfPiagXuHiFOgQlCWCJkSvqud/unY+8g+XN4tPrNEEYev0TBm9ZjmfYezNTNJ6XLPYiyMmYy0Tgpg7WL6zzuFgFsFCXbrhFVG6wfEJ/YLjy2U4U1njClK1ggBYFYiddts+sKvA4kgoDgYxQAAIABJREFUFX6ZxyUC/GEzf0kBdXQQ9m1pQdHxIAiKKn2uWEgThPbDuROv1uJ/7McfnqiUw9doVBC1HAB8RzOrPI2QNSs9g2KEOUbqwjx0U6C53pPlTlz5vbC6jM72X+MJHsZk4bs7QJSt7bgvXF+KkiKom/1f9jG26IfLsd0J4ew+7QvTcy8KAMIEoSdx5/VDePU24bNT6HRl5KuNgY43Y8eg6A5BG1DFgjHf1caYFagRkmQduv8I+lur+GlzIJKD77aOT+5+sRp3OeFGuWrQ6yMoVicM9sry7T5CAbx0DP1Zi+ifs1AUeXv7yMnj02bxyf34rRNoVmEbquYm9BGF3Tev4ME+oJknaiNv3Ya/PIWZGa9EKQgAQFGM0ULQ/hs8fE8HioqjdHL0vvIKY07l7e0KV0pGiGLg+aX05d8Jdv87qgp2K21MHv2T+gHx1m3Cv4+Rs+ggk5giKNs6CgDxOvjwRPqO7cJnLb4+J0J/N9JHUvoIANjVJf5uM//2MiWey8k6CMoISYKwq629gU157RD+/td0iQKik73AmFJVUF/Gd/iOFlZ5DkIAoHQGFBEt9HTKPRFfOc5CnZtLXbrZv7L7eKgfEBrdgInDcNHXwu1zaHnj+BlTChE5tTPiqHeXMyu/4Te2+bTw/E8e2X3d4ulf8OuX0ItlajfmHcaktgj2EEGGIOxzw8Pl+NbPmh1xlu/PYDKUd/IaA6O6DArvcLZmBYaMemDMaWRZh/5+JN06LD6+zw9LHT+uyugt2wSTgbpeJqPoCLTRwtuVWFxmPIuTqLdPYC78mn+7fuqVF7raGJPlO6t44qf8k4vpFVkK3UgZk2Ya9QnlhZqM4tka2iYIe+ziFpt4eia6N6vDzKbqleWNnhjGnOZuqJR7FuGDt7WwqTlyz2JimKR0rrNFXzhH7on4ig7B2yfQiz7kSxOpE33LeeDtVnpU7sS/q/F/m8Vtv2FkPzAyRou7/oDcs/CVo1Ooz09mfvOlsLNLvG++N4cf192xC6dcvJF/+VjGx3skC9Mzgj0AFHqQAQARoMdNxemoq4pR4/nsK8fSCYPWKbvMKITpdhDjbS0KzKb3QKJ1KDOaeut45pL/8bu6fLLUCXYrYzosCD9rEW/fLnx0omwNgEbDGAkrNzjHSO1YwVT0wrz3+E+bJ/Ytb7WJn+5t2+hI+v4MRUtBAEDRcYCxlkExJcrVCCmAW0r4mJifSzjzXe1Ri06ScUq+M92ilnlFJhF6YMxpLgWndU/GkhRq/RL69C/4T05i5hin2G357g5dWh4AfNkqrvyGf385M0MZtZYIMo2OYDbAB8vp9xvx7duFG7fCmVnUPBMVr6OGeXF7O/NFB29zwodix2+WpUfEKmKRveNRCnVZRXJPRNEoVxCOR5ikE6ECoeNM2DkkuhyeuDJ1g51D2OWk44xyT2RiyD2UrMhCWISTPuNfPZZZGOvtSr6rPaLsqFdq8c1bhXeXMcoJ3GDizXigR+Q5iglL8yfpWJGFVmShLTbx02b8+iGxn8MGGvIj4YEj6ONSKdtf2nSTN/pQFIzJwne1a4LQO8QIQtHtxK5hOjZR7on4hieDoqudTcuVeyohh7e1MAortz0axmgRemyAhfGNApTPWdnIZKAu2CSszGHuXQiTea04e8f9jea3+vCm0xSWVoQQHWcSemyMOU3uqQTCoiRqUdLPj83AgCMmhhLdTuwYImUvIvcgGE6U6yMcA2+3Mokpit1tx8OYp0sGhWJzJzxQrA7FxPM9NrknEiBLU6gdK5jdPdSsd/hXarHzlyVQ+jl4aj/v7Onq1CftPFNhUhAAAGjFF1rzl8OhSYTsRdMtXiEwiNEI+a42UiJlPJAYoxEYvK1FsQ5CD4wpje9sG194hRQskfDW0dyWfv0j5cLV3wsLk6isaAqLUNsv7u0Wz03sOj0q5pljJW5MIxWMMUWZ7XkDxkujDwXCmFP5H/4r9yyUDkGC0Fv3bQUyfTIouM6WiLKj5J6FN34qNDVf7okExfI0ankaY3fBNpvYPCQyCC7MRwvMlK6pq79OQf2Qx8AYycip9x1hVHE15UNPmxN5MBAjCAV7O5OcKfcs/IAxpQ7v2CT3LMIBb1O0aRTUpZ0b9XBKBgXws11ueJK+EwqBTkx2l6uqK9lk9c2VCR2TAAKPhwdRZPTUV09XyPERjuv+pXCmS7lbUeS72hQeCqHutGK+u2OyToRKgDFZBNIyKLzD24lJaPZAa27CqSBKEBJlGqXjTNOhBwXfY0ORMQrPEmFMFhVvBLyyNUImMYXvVlewTBdJplGYPofyICBEEGIs9HXRiclTX6kcKIpJTOG7VOUdGQ9va1Fg96Ux/JRB4X/3VRIQujsYBb8aKDpO5DnsHJJ7IhIhikJPB2GCUEWugRBBhiDkeztRVBxxObnT4SCmfAcheDIoouP5HlUZ6EbguzsUfkZkEpNVYx093IBJp9AY3QlhTBaVxStJDhmCULATZhf1MB0OYnxnK5OkaAehB7X2AxEFHg/0MPEmuSfiDcaoHuuo0K1oQ/SETIeNKEjIEITEOQg90NPgIKb8JEIPjClVlfdC6LHRcSaFF82hE5OV357XR/guK1lRewDAmFIFtZumgoQcQUjawwcArKqDFT1wnQT4CMHjJlSjv5Yf15hegTDGFF4tOfW8vX2k0Qcp0LGJ2OUQXQ65J6JcCBGE9nbizBEwDVJZRc6NB3qVHKkxglozKBQeKeOBNlpUU2VN+R7ZCaAoxmRR914UJGQIQoGomkYjMPFmPNQncm65JxIq+K42OjEFEAFPkVoDl/juDlrBSYQeGGOKakyjgp080yhoFUengoAtDDzmCAIfPkCITiSsMalf8LYWloRIGThc6MsKE3daJRjBbmWUbxpNTOa7O9Sx+DxR9dVGUOtBUCoIEIR4eAAwRlFeG7IpFXXHa5ESKQMAlM6AIqKFvi65JyIxPAmmUUofQbE6PNQn90SCReQ5PNRPxyk6RndCGKOaa0oEDwGCkLe30wTaRT2o2yLBdbYSESnjgTGlqq++gdBtVb5pFDz1Zci3joo9NjreTIQvYAyaRugdAu6oYO8g0i4KAJ5Ci6rbfEcgJYnQg/r2ApFzk9IhljapQRDiXhuJdlFQu2kqeAgQhIQa5T2oWyM83JueENS3FwjdHXS8mYgOsUyiGroSCt02EsPXAYCON+PhAdHtknsiCoUEQUhmEqEH9WkhI+DhARAEOiZB7on4ivpMo3w3MUUvD8fLEI7Ya1Nyow9vUBSdqLbGkBJCgiAk2keYmCz0d4sCL/dEpIe3tRBkF4XD1jlVHUr4bispOW3qKC6DuzuIy6YfgTFZVHYQlBACBCGhiTuHQTQdZ1LBFjAenqhIGThcaEpVGwER2fQe1FFcRughIGtzMtTtpgkSpQtCUeCFPjudYJZ7IoGjVuso39nKmFPlnoUfoIhooBk82Cv3RCSDoCondEKS0NtJeiqh2NNJii16PGrdiCRB6YJQ6Omk44wUzcg9kcBRX4yGB66zlaBIGQ+MUVXWIcGu6N70o6FYHYqMITqPEw8PgCiiyBi5JxIgat2IJEHpgpDvaiM0TGsExqhOHzVvIyl3woPKGrMRpBECAJ1ItnWUt1upxCS5ZxE4jMkiqOjhlxalC0KyHYQAoFaLhCjyXW3kaYQqKj0sul2ia5iOiZd7Ir7CEB4vI9jJqF0wGSoO3AsepQtCvttKrlHegyp7UAj93UhvQIYouSfiH7SKuhIeVgdJSCL0wBjJzqDg7e0ogWCNUMWBe8GjeEHYRV4/6DEwRovQ2wlYkHsiUsJ3tjImwtRBUFcEOUEhox5owntQ8N0dVDzJglCt1ikpULwgJLTvxCgohkUx8XyPTe6JSAlZNWVGUFN7XrIchOApN9pNsCAU7FaaZB8haPEyk6N0QUhoJ8IxMEbV1TQhqsroCGpq1S10WwnTCAkvLsPbrSiBpAUfj1oD94JH0YJQdAwSHa88gvosEpyNsGz6w1DU4caE5EOeRphgxv09pAZriKLQ20kR2IBpNOrbiKRC0YIQ93TQxBY0Gg1jShXUZZHgu4jUCOGwm1AN94I4HyEgmo5NFHo75Z5HIAh9XSgyhmJ1ck8kKFQZuCcJyhaEJDdgGo3aihthQegm9daoJqeeOI0QDsfLEGkd5e3Eh6+DSgP3JEEaQfjqq6/+5je/ufDCC7ds2SLJgB5wDzHF9b2jpmBFAOC7bXRMAqGnY1oVhxLR5RDdTjqamCRCD+T2oBDsxIevg0oD9yRBAkH41ltvrV69+tJLL126dOlJJ5106NCh4Mf0gHtshKodYzhc0ITwQosj8AQWVxtBHYcSvsdGJ5CUROiBTiQ1g4K3W0mpZucdLXB0QiQQhI8//vi99957xhlnrFq1asWKFevXrw9+TA+4h9Q2mGOgdAbSCy2Ohrhy26NhTBZC9+LRkOcgBACSNUIVVPbwoL6unJIQrCAURXHXrl1Llizx/Peoo47asWNH0LM6DO7uUEHuhAc1HcR4WwuRIaMA4GmD0NdFauziT/BkCkLaSGoqoQoqe3hgTKkC+a4ByQm2q0NPT4/b7U5IONym3Gg0Wq2TPuhVVVXbtm176aWXDn83w7z22mt6vX7iq0URD/YMMxHUwECQk1QCYpx5sKXOnZIr90T8ZnBwcMxPnNYmfe6sAWLvCxWT0N9Sj4iydI25C05rMxUVT9wtwLoo3m4lbtoAwNvbnfro4XHvAnFwUQlc9R5E4C0YYfyO5B2DwcCyrPdrghWEUVFRFEU5nU7Pfx0OR0zMpGl/mZmZWVlZJ554oue/0dHRJpO3vBx87ROx8QlBzlApWDLxYI+XxVEyY6Y91G2NycxnyPxbAMBpTtM7+g0xBXJPxD9G3wX3QE9kXmkEcbcgOnrQMRht0JMVaSVy7n7HYFxaNhocJPQVHoHLzOv++k3S/wrJ5x+sINTr9WazuaGhITs7GwDq6+vT0yc1mkVERJSUlCxbtszHwVE8wf14x8CYUof3bJZ7FhIgcm5hoIdEu9wIKmjGJHR30EYCbwFF0fFmocfGJJFkWhe6O+h4M3GhSRPCGC283QqiqI4/RyokCJY599xzn3vuOQAYHh5+/fXXzzvvvODHVB+qqenA29vphCRAtNwTCRwVVBzlezpoMjshkFjZRzWRMgBA6fRqCtyTCgkE4Z133rlnz545c+YUFxeXlpaeddZZwY+pPmhPsBb5GRRE5054ID2DgtAkQg90YjJx8TK8vUMdkTIe1BS4JxXBmkYBICUlpby8vKKiIjIyMjeXvGCQ8IAMkRSrFwZ66NhEuecSFLytlVWDICR4IyA0idADk5gskJZBIdjb1ZFE6MFT6EpfMFvuiSgIaSrLIIRKS0s1KegddVhH+c5Wshw846GNFr67g1ztnNAkQg80iaZRVdRXG0EdG5G0KLrWqMpgTBYVWCSIzqb3gAyRFKsTBnrlnkiAEJpE6IFEjZDvVkkSoQfNNDoeTRCGD8aUSnqMBqjCRwiH68uQei8EAsttj0BisIxgV0nRYw9q6wEgBZogDB8qeP5ElwM7h2nCu7IB4T0oeDvBGiGKihM5N0G9kfHwgDq6oo7AmFUSuCchmiAMHyowzR+2i5IZpjEaolMJSU0i9EBRZFUc5VXRd2I0lD4C6SOE/m65J6IgNEEYPlRgmudsLYyJeLsoeOJliBWEfLeVXI0QSIuXEVSURDiCOpqRSYgmCMMHiowBhPBgn9wTCRy+k9TG9GMgN5VQdDlEzo2i4uSeSOCQFS/Dd6lQEKrAOiUtmiAMK6S7CflO4pMIPTBGUoNl+O4OJjGJaOs0WRoh322lVdEVdTQqsE5JiyYIwwpjJvv54zvbVBAyCgB0bCJ2DhMUsjEC0SGjHpjEFIGc4jKC3cqQ65GdBNJrSkiOJgjDCmNO47ta5Z5F4PCdLeoQhEBRTCJJeskIRCcRemCMyQStPN/VzqhPIyTZNOra+Ibk/UQ1QRhWiLZIeLybKJpg79RoCA0cFbo7aMLLfZFkGsVY6OsiXQUfD2NOI3QjEjm36/uPKKldA5ogDCtE+wj5zlZyG9OPhyYzlVAFGiEyRFE0jYf65Z7I1Ah9XSgqlmKmaOtKHMgQRbE6ob9H7on4Dd/VRsWbJe9+ownCsEK0j5Cztfx/e28e2ES19/+fycwkaZouaZo0abqXQqksBdlk38oFRRSVRUXhdy8I4vUiiA884AUuuFz1JyhVEXi8iIKXxSvuguyKbCIUZJG26d5sbbq3aTIzme8f0xtrgdLSzMxJ5rz+aqcz53w60+Y953M+S3CEjHIQWkMgxsvQTlsAJxH+l0DpQUE7bcHnF+UI0Jdy2lGGR/u/xCMSQkGRhYYDAALiXfhG6Iry4Egi5CC4xliBBlNlD4JOCITWyDgDIIMi+LLpfQToNiHtKJMhIQwCAndRGDRJhBxEtDFgdqr+i7e5iWVo7nUqoAmUiqOM0xrojuhbQUSb6IrAC9yjKsplWiSEgU+AeiQAALSjjAymPcKoGKamAni9YhvSCQK6AVNr8CgDco2KC6GLDUQhpB2laEUYDASoRwKwLO20BnoDptZgBClTR9LVDrEN6QR04CcRchDaGCYQVoS000ZEI9coRNCOcrRHGAwQ0QH5IsbUVMhC1JgiRGxD/AkRbQyIj2MfTLB0iA2UJE7GGYRlZThaMigCqgeFt6EWABbjYWsACaHQBGgGT3C0IWwDoQ2w+hpBsyJs8UvD/SnMul1edxMephHbEF6QKUMxUsHUB1IGBeUoI/S87M4gIRSaAN0jpBzlPP0JikjA5dQHzR4hRsplqjCm1im2Ie3RkrIZyGVd2yfgvKN0RRmhj+djZCSEQiNTRwCWDbgMiuBdEQaAg85HEGTT+4A/XoautAarX5SD0AVY4CjtKOOp6D8SQhEIxEJrdEUZGUS5Exx4tIF2BtKDCIKK2z4IbQwDdx5nUHYibE3AfRDRyDUaTAScRwIAQDuCqr4aB6GNhfyzuDXepgbAsjJVmNiG+AdCa4C8T30Q505wBFwGBdojDCoCziPBMjRTWxl8JTZkKjWQBUbRS8AtBwO/uJoPXAt7QQO60hqsuRMcZGB9EHkZpspO8JA7AZAQikLACSFTacUjdRhOiG2I/wmgwFG6yhYExdV8EFEGyHNX6ODNneAgdCa60gp57K4P2mnDw7UYKedjcCSEIhBwVdYoR7C0IbwBIjpgelAETe4EB6GFu+42yzLB9eZxI5giRKZUQR6764N2lPIXuI6EUAQCbkVIVwRh7gQHHjgVR4Mmm54Dj4j2NtaxlEdsQ24OU+uUhagxuUJsQ/glgD6LKHsZEcNL7gRAQigKMlUYwHFvQ43YhnQU2lFGBqkQElojEzCu0aBaEQKZDI/UMbCWuKOdQZ47wRFA8TK0o5S/TyEkhOIQQH9/gItaRq5RsQmyFSFo6UEB6c0P4iqjrQmgFSF/uRMACaFYEDoTFTjbhEHsGg2Y4jIsG0zZ9By41kDD2pWQcVqDO3eCg9DFBYoQ8pc7AZAQikUANQNjmxu9nmY8PEpsQ3gBj4j2NtWzHrfYhtwGtqkOI+XBVvQ8ysDA+hZCV0pECGMD4o3c21QPaJq/TyEkhOJA6GJpR2AIoddpJXSmoK24iGF4FLwOOh/eakeQ+UUBAEQ0vHeedgZ5EiEHER3LVNng78pJO3iMlAFICMWC1MfRlQEihJXWYI2U4QiIbcJgKq7mg9AaoXWN0pU2nIdO6LCBkXJZWCTkJX4AAJS9FAlhEBJAzcC8lUG7QchBRMdCuy7xwdZUBN+KENdC6hpl3S7W04yHRYptiBCQuji6okxsK24DryGjAAmhWARQKitTaQl2IQyADApvtSP4krtlIZCWuKMrrYTWELTbAX+E0Jng36ah7aU8NWDiQEIoGoTOBP+LGADAW2lBrlHR8VY7gq/WK2jxjkJ382mnlaealhBC6ANgRUg5yogYtCIMRgKjVT3LMlywTPBCRMcGghDag881CrhOWPDdfLrSSkQHf8goB6EzUXCvCFmGZqodvL6aICEUDUIfRztgfxGjqx0yVViQRe23AY+KYWorgZcR25Bb4/Wy9dW4Ri+2Hf6H0BohLL1NV1qkUFaGg9DDnspFV1pwjZ7Xov9ICEWD0MVScP/9AQBoR5ks2H1EGE7gYRq6CtJaXwAApqYSU4VjBCm2If4HzuIy0loRamK8DTXQFn0FAND2MpLPkFGAhFBECF0grAgdZXiwCyHgSm9DHC9DV9lkwbgcBC1tsKATQsYpISEEMhmhNcC8KKQd/EbKACSEIkJEG5maCpahxTakPWhHqSw6mDcIOSDfJqSdNixIhRDXGmDr/sEyNFPrDEpH9K2AfJuGspfwmkQIkBCKCEaQeISWgTuVlXKUB71rFHD1NSBeETJVNlmkTmwreIHQ6L0NNSxNiW3I7zBVdjwiOijbUN8KQh9PQRw4SttLkWs0mCF0cbSjVGwr2oN2lOJBHTLKQUTHQu0addqCr6xMC1wzJpheByW1QchB6EzwrghZlu/6agAJobgQeqgDl1m3y+tqxMK1YhvCO5CnEgaxaxRw8TIw3XzaacUlJoSkPo62QyqETK0TU4TIlKG8zoKEUEwIPdQ9UChHGaGLlUJ9jZZmTLBWvGOcNpkmSFeELW8hEC3H6QqLdLLpOWDeIxRggxAgIRQXEm7XKN/1/eABkytlIWo4K96xHrfX1SAL04htCF/gWiNU8TISdI3KQsMBjjN11WIbchNoeynJc8goQEIoLoQe6ip/fNf3gwpovaN0lQ2PignidTlsd56ulNyKEEBcaI2ylxCGRL5nQUIoJnhEtNft8jY3iW3IzaH436OGByI6Fs7GWIzTFnzltltDRMcyTmhcoyzLVNmk0JK3DaQ+nrbD6J2i7aUkn1VGOZAQigqGEbpYaL3zwjglIAHa0q+00xaUVUZ9EJxrFI4NWqamQqYKw+QKsQ0RGiImHs54BdpeSsQk8D0LEkKRIaHdpvZ6aac1uBswtQbaDIqgD2LE5Ap4NmjpSguhk5xfFABAxsRR8K0IvY11LE3h4VF8T4SEUGQIfTyc8TJ0lQ0P02CkXGxDBAKHbKfKB10Z5CtCANM2oQRDRjkIfTyEb+SUvZQw8L4cBEgIRYfQx1Hw/f0BiUXKAM41WmmBxEHXGsZpDfotK3iW49KMlAEAEFoDU1sJVYkfAABtLxFmdwYJociQMTC+iAHuXUwykTIAAJlShZEKph6yCHKWpauCf0WI62ASQkm6RoEMx6OgK71N2UrQilASELo4OBcitIP3+n6wQUDzceyDqa+WKVTB3Q8StPSggOLOS9Y1ClpeyuHapqHtJSQSQimAyRUydQQNU61FDkqQYC2oIKJjYQscZZxWPNiXgwCeVxCWpZ1WyQohERNPQVZojbIVkzG8JxECJIQwQEIZL0PbSyS3IoyOhc01RFcG/wYhaOn+IX6wDFPrlClDg379fStIfTxtLxHbit/xNjd6XY24Roi+K0gIxYfQx8GWysrUVQMZLgsNF9sQQYFlXdIK2mkjooN/RSgLUQOcEH2DVrKRMhyEIR6qDAraVkrGxAtTUwkJofgQMfGwBY7S9hJSYn5RAKkQSmJFCOBoCUlXlBMSaDp2K0gugwKaeAXKVkzyX1yNAwmh+EDoGqXsAgVrQUVLcRloPggAAHSFBZfGGoWIjhU9lZCuKJdoyCgAAABMESJThTHVFWIb0gJtKxagyigHEkLxIWLiKRtcQkjbSyW4IpQpQzFSLrqDrjVMsNdX80HoxN+glfiKEABAGhIoe7HYVrRACRUyCpAQwgAeHgUY2ttUL7Yhv0PZhOgBBiEtafVwwLpdXrdLgPpSMACDXxoJIRED0TYhZS0iDUnCzIWEEAqIGLjitWh7iWDeeaggdCbR1yU+6EoroTUEcQOm1ohf9JxlaadNysEyAAAyJoG2QbEiFDJkFCAhhAQSphcxb1MD63FLZCHSBqhSCSUVxEhEi/wKQlfZZaEREuw70RrCkADJBxFtLSYNiYK9BSIhhAIiJoG2wbIipGzFhCFBIguRNpA6EzwV72inTTqt0mUqkTMokF8UtKwIofggEjJkFCAhhATSkEBB4xqlbcWC7VHDBmSuUUtwN2Bqg7jeUbqinNBLXQhloeEYQcLQEouyFpFGJIQSg4iJh0cIKXuJYFHLsEHoYmmnFZIMCrrSIpEkQg5x30LoinJS8itCAABhSIAhXoGyCpc7AZAQQgIRZfA21LFul9iGAAAAZRXUKQEVmCJEFqJmaqBIpWIqpVX3UnQhRK5RAABpSKSs4sfL0LZi0pgk2HRICOEAwwi9iYIjrV6wiu9wQuigiJdhaYqpryai9GIbIhziphLSjjJCHyfW7PBAQLBN422oYRkaj9AKNiMSQlggYxJh2Kb2NjWw7mY8IlpsQ0SD0MVRFeLHyzBOGx6pAzJcbEOEg9TFiSWELOVh6qokUrugfcgY8VeElLWIjE0SckYkhLBAGhIoCISQshUTBoEK3cKJ+AltAACJ5U5wtOTUi7FBS1da8KgYSb123ArSmCh6KiFlKSKNyULOiIQQFgg4hJC2FQtWzQFOCDgyKCTYKl3EDVoUKeNDFhqOkSIHjlLWIiE3CIEfhbCwsPDChQv+Gk2CkAbxX8SA4FHLEELqRXPQtUaardLFipdBG4StIQyJlLVIRAMoS2HgCeHp06ejo6Pvuuuu4cOHd300yUJojUx9Fetxi2uG8O9isIFHG5maCpahxTVDgq5RAAChj6McIggh5Sgj9FIsrntTSGOSmELIspS9hAg4IUxLSzt9+vSPP/7Y9aEkjUxG6OJEj9eibMWEtF2jGE7gEdGiN0ynKyTnGgVck2oxYqdpRylaEfogjUm0tUis2WmnFVdHyJQqISf1gxBqtdpu3bp1fRyE6N5Rpr4asCwerhHRBhgg9HGUqN5RlqGZOiceFSNQs/OfAAAgAElEQVSiDaJA6uNE2aClHWWkJNut3BTSkCRi4KjwflEAACHkZDU1NUePHnW5WtLG1Wr1zJkzsVsHKDIMwzCMUNaJDx4T77EWKcT7lT3lBYQhsc09l9pTAADgOpPHViLvOVAsA2hHOR6h9QIM/PfOS+QpYFoj7SgT+Df1NtQATMYqQ287r0SegkwfR9lLGJoWJXrcU15AGJPauc+dfQoymawdleHokBBeuHDhueeeu/H49u3bk5KSOm5QTU1NdXU1jrfEKJMkOXnyZLlcfqvzPR6P2y3ynpmgRMe6zxyQi/crN5fmy/Txbe655J4CAEAT4ynLE/G3pmwlWJShtQFSeQqhGqa+urmhHiNv+bHgd6iyAlxn6sjtlcpTADKZOqLJWoyLUeHPXZov7zuinfvc2acgl8sJ4jZK1yEhTE1NfeWVV248HhPTOddNUlLSmDFjZs+e3cHzGYZRqQT1FIsLndi96asPRPyV3ZWWkKT0NgZI7SkAAHBTct2lEyL+1g21FQpDQmsDpPMU6rVGeVONkM6xxtoKuSGxI7dXOk/BFZtMVNtD4lOFn7rOXqxOeYq49X3m4yl0SAjDw8OHDRvm34kRN0JEGbxN9d7mRpkyVBQDKGth6D0TRZkaKoiYeErUVEK6wkJIdcuKiImn7aVCCiGFcidugDQmU5aCkD5DBZ7X29zENNQKHy/th2CZurq65cuXZ2dnUxS1fPny119/vetjShQMIw2JosVrsSxlK5F47gQHHh4FaMrb1CCWAZSEC0CTeqGbVNP2UikX170pRKw4GRSUpZA0CteP14cfhBDDMI1G07Nnz3Xr1mk0mvDw8K6PKVlIYxJlKRJlarrSgodFYooQUWaHDUKk8EUOulK6vfGEv/O0vUSy6+9bQcYmU5ZC4eelLAVkbIrw8/ohajQsLGzZsmVdHwcBRE1lpSyFZKyg9f1ghoiJoxyl8qR04admKY+3vobQSC53goOIiaeO7xNsOtbTzDTUElGo3PYfIHVxTK2T9TRjcqWQ81JlZjJehGQ8VGsULkiRPBIACeEfIfXxYq0I6UoLoTUAmUT/N8mYeLqiXLDS27SjjNCZpFxl/ubIZGRMgvDeKaq8QG4SIUJHov9s0EIakymrCB4JgITwj3AhG6JMTTvKCJ10YzdaSm9XC1R6m7KVoFT6m0LGJlOWAkGn9DKUvUSUTyEkhHAhU0dghFyUAvyUpVAU7zycEPp4sfok044yyW4QcpAC9oal7CWEQdJV5m8FaUqhygUVQspeikdGC+yM5UBCCB2ibFN7mxuZhhoJVnm+FYQulqmyi1J6m6ool/KKEHDbhEIJIY1WhLeANKV4hF0RUmVmeZwIflGAhBBCRBFCylIkStQytGA4gUfqRCm9jQpAkzEJtFC9OSlbMYFyJ25GyweRgH2SPWX5pEmcstVICKGDjBXaIwEAoMrNyC/aBtKQIHBCGwftKCelLYSEUK5RlvIwtZXIEXJTZCFqXB0hZHtIqixfLkbIKEBCCCHCeyQAAFS5WZRgLZghYhJowbtieRtqAWBl6giB54UKUqg7TztKCa0RwwXtPRBAkKZUT1m+QJOxLFVuJkX6FEJCCB1kTDxTXSFwh15PmZkUyTsPLaRehPaQlKOMiJG6p04WGg5kBFNXxfdElK2YNKJImVtCxnWjys3CzEVXlMtCw2Wh4tRjQUIIHzKc0McJmUTBMjTtKCWNKHfiDxCGROEzKGhHmcT9ohzCVJagrFJvQ90+8rhuVJlAQugpyyfjROtri4QQRuSmVCG3CWl7Ka6JweQKwWYMCEiu9LaAwQKgJVIGBTEC0ihEk2rKWkyi3IlbQ8YJ5xqlSvPk8WnCzHUjSAhhhDSleITySAAAPGX5YkUtwwymCJGpwugqu5CTUvZSVPcSAEAaEgVokk7bipBrtB3w8CiMIJkqhwBzeUpz5QndBZjopiAhhBFSQI8EAIAS1SkBM6Tg9WVoeylKawMAkMZEylbE6xSs28XUo9zZ20DGdRNiUciyVJmZjEMrQkQr5KYUyloEvIww01FoRXgLCEMixb+DzkdLNL8WFYAGBLci5NMvTdmKyZh4lDvbPvL4NE9pLt+zUI5SWZhGplLzPdGtQEIII5giBI+MFiiJjWUpSyFaEd4U0iBoBgVdaSG0RiDDBZsRWmQhallIKF3No1OOKhen409gIU/oTpXm8T2Lp/i6PKEH37O0AxJCSJHHpVKCbFNT9lKZOlIWItq7GMwIs1Plg7ahxni/QxqTaT5jp1HuREcg49M8pXl8h4xRJbnyBNH8ogAJIbSQcWke/l/EQEs1BzH/BGGmpcSJUIGjlB3VvfwdMpbfJtVi9YANLPAwDSZX0k4br7N4StCKEHEz5PFpnlIhVoSe0lwSCeEtkClDZSGhwrUEQp0QWkHG8tuSDPUd6yDyhO6ekuv8jc9SHspWIu7uDBJCSCHjUilLAfB6+Z7IU5InYtQy/JDGJL7DF33QthJS8mVlfJBGHqvPM9UOjJBLvJRdB5EndKdKeIyXocryyZgEjJTzN8VtQUIIKbIQNR4exXtLPK+XshSgSJl2EKbECQAAeBm60iLxvhOtIWLi6So7S3n4GJyyFJAm5BftEPLEdHcxjytCT/Fv8kQx/aIACSHM8P0iBgCgbMV4pE6mVPE6S0BDGhKFEUK6woJH6sR9L4YKDCcInYmn5binHLWh7ijy+DTKUsBfb0530TV5ck+eBu8gSAjhRZ7Q3cOzEHpKrov+LgY5hDFJmMBRyobKfbWFNKVS5bx4R6lyM1oRdhBMEUJEGyneWuJ4iq7Jk5AQIm4B33vUAIL0HfghYxLoijIBihtQthLUIbYN8thknrofUGVmOdoR6DDyxHRP4TU+RmZqKgDDEFojH4N3HCSE8ELGpVG2Epam+JvCU/ybPBFFyrQHJlfgEdGUg/f2pDRaEd4AaUrlQwi9zY1MQw2hM/l95GBFkdTTU8SLELoLrojuFwVICGEGI+WEPo6/fmCs20U7bWin5LbwHcfPQVmLkBC2gTSlUpZCv+dxUmVmMjYZFVfrOPLkDHfRVT5G9hRelSffxcfInQIJIdTIE3t4eIvX8pTkkrEpqD33bSGNSTSfmd2AawnptKKyMm2QqdSy0HC60uLfYT1l+cgv2imI6FjW42ZqKv0+srvgigIJIaJ9FInpPHkkAACeomuKpHSeBg8mSFOKh7dIAQ7aUUZoDRhB8jpLIEKaUv1eYokqzUdFJDoHhimS73IXXvHvqN7mRsZpJePFfylBQgg1ct5c86AlajmDp8GDCTKWx8xuDspSSBiTeJ0iQJHHp/m96K6nLA+tCDuLPOUuT4GfhdBTcIVM6AGDUwoJIdQQOpPX7WLqqvw/NMvCELUcEBBRBtbV4G1q4G8KylpEGlG5r5vQUvTZf7BuF1NTSaIA3U6iSO3tLrjs3zHd5l8Vqb39O+adgYQQbjBMntTTU+j/bWrKUSpThuLhUX4fOQjBMMKYzF8eFeAKnaAV4c2Qx6dRZWY/xst4SvPJ2BTU66qzyONSGafd21TvxzHdeZcUaX38OOAdg4QQdhTJGW4ehNBTcEWeIv4edaAgN6XwF74LAKAsRagA9E2RhYbLVGo/xst4Sq6L2/EnUJHh8uSebrPfFoXe5ibKXgJJHjMSQtiRp9zl8bdHAgDgLryqQELYYci4VKqcrxWht6mebW4iomJ4Gj/QIf1aWQIVkbhjFN36uPMv+ms0j/mSPLEHJAFiSAhhRx7fnbKXsm6Xf4f1mH9VpPTy75hBDBmb4uFNCKnyAjI2CaW13Qp5fHc/JhGhsoJ3jKJbH3ee34SwOTdH2b2fv0brIkgIYQcj5XJTituvsaNMTQXrcaNGBx2HNCbRFWU8VflBHWLbR56U7i8hZOqqWE+z6AW9AhR5fBpTU+FtqPHLaO7cHAU0Qih+3GpHqK2t9fLfmQ9aXDGprktnwvR+20NyXTjpikmtrunQH3RDQwNN81V4vn1CQkKUSqUoU7cBI+VEdCxlLZLzkH9GlRegPJZ2kMelUdYilqa67kbzFF2TJ6ajxfcdIsMVqX2ac3NU/Ud3cSSm1snUVfHx33RnBIAQ/vzzz0OHDg0LCxPbEPFgWdbLYPhKv43HMBiGgVXv+WtAnmhqaqqqqlKpoOgSRcZ1o8ry+fjX9ZSbQ4ff7/dhgwZMriD0cVSZWd7l+g8eCDr+BDSKHv3d1893XQjd188rumfC80YSAELY0NAwYsSII0eOiG0IQmg0Go3H44FECOVx3Txl+aH+HpalKbqiHOVOtI8iOcNddLXrQuguvBZx7xN+MUmaKNPvrj/4b8CyXdSw5mvnlOkD/GVV10F7hAhEh5DHd6P8XesLAEBZi4joWNSPt338kk3LUh7KUiBPRGUF7xwi2oiRiq62qvYyzdfPK3siIUQgAg3SlErZiv3ep5sqyydRua/bIU/O8HS50KWnNJeMicfkUOw6By7KjIHNV892ZQR3wVVCa4CqmgcSQgSiQ2ByJaE10v7uVo86IXQEIioGyAi6oktdIT0FV+QoZajLKDMGua6c6coIzVdOK+8a7C97/AISQgSio8j9mtnNQZXmySGovg8/itReXax1CU9ly4BGkdaXtpd0JYnCdfl0SK97/GhS10FCiEB0FDKhu6ck148DsgxN2UpIU6ofxwxWFKm9u1Tfy8t4Cq8pUtGKsKtgOKFMv9t1+fSdXU5ZiwBDk3Fw/c0jIUQgOorfV4S0tYiINqJdq46gSOvblbImnpI8XGuQqSScheU/QnoPc108cWfXui6eCOk73L/2dB0khAGP0+m8fPn3N2Wappubm288rbGxUUCjbjmj2+1mW3USYFn2+PHjAhrVJcjYFNpp82O5O0/xdXlCd3+NFtwQOhPwMnSl9c4ub867oEzr61+TJIsyY6Cn8NqddaJounA8pN9Iv5vURZAQBjx/+9vfrl+/DgAoLi7u2bNnWFhYVFRUnz59TpxoeWV7+eWXIyIiTCZTaGjo3LlzPR4Pd9xoNEb9l2effZY7uHnz5qhW5OX9IWHg4MGDUVFRb731VuuDLMtOmTIlKiqKYRjuyLhx40JCQoxGY2xs7NatW7mD27dvT09P12g0arV61qxZDQ0NAAAMw7Kzs7/55hu+7o5fwXCCjE32Y3s8T0kuKgDdcRTdM925F+7sWqgKegU6mCJEkd7flfNjZy+kyvIBQ8vjoXv5Q0IY2OTl5Z06deqhhx4CAGg0mv/85z8ul6uhoeHxxx+fOXMmd87UqVNLS0tramrMZvPJkyffe6+loEx1dfXJkyfNZrPZbH7ttde4g83NzVlZWeb/kpLyew3M+vr6559/PiUlxeX6w5Jo27ZtDQ0N1dXVviOvvfZafX19XV3drl27nnnmmfz8fACAUqncuXNnQ0NDSUlJXl7e2rVruZMXL178j3/8g68b5G8Uieke/9V99RT/hgpAdxxl9/7N1+9ECFlPs6ckV9ENRcr4DdXdY5t+OdrZqxrPHVENGAdPQRkfSAjvkKVLl3700UcTJkxISkpavHhxTU3Nk08+mZyc/Oijj9bX1wMAGhsbZ8+enZGR0b179/nz59f8t7DnG2+80atXr8TExNGjR3MKsWfPngEDBiQmJg4ePPjYsWNtJvrwww/79euXmJg4dOjQM2faRi1/+OGHDz30EIZhAIDw8PCMjAwAgEwmu++++yoqKrgaoRkZGeHh4QAAg8EwcOBAm83muzwiIkKj0Wg0mtbVWxQKhea/4Pjv/UuXL1++YMGCuLg/lOq2Wq1vvvnmq6++2vrggAEDCIIAAIwYMSI8PJybccaMGXfffbdMJtNqtQ8++ODVqy350UOHDrVYLFeudDVLTBjkyT39JYTe5ia62oFqynQcRY/+7rwc4GU6e6E7/5I8oQfai/UjyoyBlL2UdnbCU80ytOuXo6oB4/iz6o4JgBJrN6WOAoyAVbhDSSD/4zvD+fPnDxw4sGvXrrCwsNGjR//www/r16/fsGHDzJkzs7OzV6xYwbLs9OnTs7OzvV7vkiVLVq5c+e67754+fXrz5s0//vijTqe7evWqWq2ura2dO3fuqVOnMjIyCgoKfN5FjvLy8qVLl54+fTolJSU/P59Tl9YcO3Zs8eLFrY98+OGH9fX1u3bteumll3znX7t27ccffywqKsrJyWm9/MrMzGQYZujQoRs2bEhNbYnj+uKLL8LCwgwGw1NPPbV06VJOZY8fP37hwoXs7Ozvv/++9XQLFy586aWXIiMj2xh24MCBwsLCw4cPjx07dujQoa1/xDDMV199NXXqVO5bDMMGDx589OjRu+4KgP6I8qSM6r3vdL3EFACAKrkuj+uGWqV3HDxcg0fFuIt+62wrzearZ6GqYxIEYDihGjC26fT34ffN7uAlzb+eIgyJRDSMrT8CUgjrKZDxKd1Es7c/1U/8Tx98ed+2q+eFCxdyn90TJ06kKGrUqFEAgBkzZuzfvx8AoFarx4wZc+LEidra2vT09O3bt3NXuVyuixcvjhs3rk+fPgCA6upqlmVzcnKSkpJ8UuTD6/VSFHXx4kWTydS9+00c64WFhSaTqfWRixcvVlRUVFZWRkRE+A5WVlaeO3fut99+02q1vkXed999N2jQoPr6+pUrV06ePPnXX38lCGLixImTJ082mUxnz56dOXNmeHj4/Pnzm5qannnmmT179shkf7gJO3fuxHF86tSp3CZla8xm888//3zt2rUxY8Z4vd7WF65YsYKiqEWLFvmOxMXFFRYW3vzWQwYeocXkCrqivOtNrNyFV+VJqAB05wjJGNh89WxnhdB19Wz0Uy/xZJJkUd8zqeLdZWETH8fwDulIw4mv1LAWlw9IIQwjQdmj4luu1+u5L1QqlUKh4L4OCQlpamoCAOTn548dOzYrKyspKam6urqqqgoAMGTIkJUrV65cuXL69OlTp059++23NRrNzp07169fP3/+/FGjRmVnZ7felouPj9+yZcuGDRtmz56dlZX1zjvvtJE9DMNaB2ECADZs2AAAMJvN6enpEydOTEhIAACMGDFixIgRAICnn356+fLlO3fuBACMGTMGABAaGvruu+9GRET89ttvvXr16tGjZctq5MiRixYt+uKLL+bPn//mm2+mpqZaLBaLxVJRUWE2m3NycjIyMpYsWfLGG28cOnSorKwMAHD48OGBAwdqNBoAwMKFCwEAzc3NvXv3Hjp06KOPPsoN+9JLL3399dfHjh2Ty3+vrsmyLAbftsGtUCT3chdc6boQegqvqkdA+rkALcpeQ6o/WR8x+f/r+CVUeQEmw0lDAn9WSRMiJp40JrnOH1cNvL23kyo305VWZW+48uh9oD1C/3Dj5/jOnTsffPDBDz744O9///vYsWN9xxcuXPjLL79cvny5tLQ0OzsbADBlypRjx44VFxfHxMT87//+b5txZsyYceLEiYKCArlcfmNQSWJiosViudGepKQkkiSdTmeb4z179rTb7W0O0jTt9Xpv9Lt6PB6SJAEABoNBoVBs2bJly5YtRUVFZ8+e3b9/P8Mwo0aN+vrrr7ds2bJ7924AwNatW63WP+wZKJXK5ORkh8PBfbthw4aPPvro4MGDOp2u9WkWiyUxMfHG3wJOFCl3ebpW4gQAALxeT9Fv8iTUhrBzyOO7e10Nnaq15vr1ZEjvobc/D9F51KMfqj/6KWBv75yrP7xXPerBDq4dhQdSs4KAqKioQ4cOVVVVVVZWvvRSi1vml19+qa6uHjx4sEqlwnE8PDy8tLT0zJkzY8aMUSqVCoWC81t+8803n3/++datW/Py8q5duzZixAilUkmSJBfz0prRo0efPXv2kUceAQAcP368rq6uV69ejY2N2dnZJpOJ89xmZ2cPHz5cq9Vevnx5/fr1S5cuBQCcP3++sLAwMzOzoaHhH//4R9++fdPS0gAA//d//9e3b1+9Xn/mzJm33nqLk+p58+bNmzePm/HBBx8cPHjw8uXLAQB79uzhDl6/fj09PX3Xrl04jpeUlBw6dGjo0KFyufybb745derUxo0bAQDvv//+ypUrN23adPXq1atXr4aFhQ0e3FJv8OzZs6tXr+b1cfgReWrv+qOfdnEQylIoi9DKQts+UMRtwLCQ3ve4Lp4IGz+jg1e4cn7UzHyOV6MkizL97rpvt7t+PRXSp71XDcpe0pybo5mxqJ1zxAUJ4R3Sv39/n2s0LS3N5+gzGo2ZmZkAgHnz5uXk5AwZMsRoNC5btmzXrl0AAJZlN2zYkJ+fL5fLJ0+evHDhQofDsXv37lWrVgEA7rnnntdffx0AgGEYt6kmk8m2bdu2bNkymUw2atSoG9Vi9uzZ991332uvvYZhGEmSmzZtMpvNCoVi8ODBBw8e5Kyy2Wzz5s2rqamJjY1dsWIFJ2kYhm3durWgoCAkJGTo0KHvvfcep8EWi2XTpk21tbVxcXEbN2587LHH2szYt2/f5OTkNgdDQ0PHjx/PLYvlcvmhQ4fefPNNr9fbvXv3/fv3p6enAwDsdvuwYcN27Njhu2mcEJ4+fVqv1/fuHTCh7WRMvLfZxdRU4pHRdzyIu+AyKvd1Z4RkjqzZt7mDQkjZir1uF2q9xBcYFn7vkzWfbw3pNbidsK+6r/4VNm4apggR0rTOwQrI7NmzP/zww46fX1dXx7LskSNHxowZw5tRAc/MmTP37dsnthV3zvTp07/44oub/igyMpILJoKNyn+91Pjz4a6NsK7xXCdG4P4XECzLsl6vZfXjHmtRR86t+epfNV9+4K+Z0VO4KRWbVtQf/c+tfuq6csb60p+9lMdf0/HxFNAeYcCTnZ3NeTUDlIULF06ZMkVsKzqHIq2vOy/nzq9nWbf5V0U3VPHrjsAw1d1jm34+dPszvd6mc4dVA8fzb5OkiXzkmbpDuyl7yY0/8jbWVe/ZqJn+LEaQwhvWcZAQBjzR0dEBkYF3K7i0k8BC2T2zuQtCSNmKZSFqPELrR5MkReiQPzX9fOi2TZJdV8/ikToUL8o3RHRsxJS5zg/WehtqWx9nKY9z2zrVgHGKtEyxbOsgSAiDgdzc3GvXfi93UlNTc2PBa4/H43Q6vV7hyhA0Njb66un4YFnW6XT66p0CAOrr648cOSKYVX6B0McBL3vHfWLd188rusP+0QAzhM5EGJJuW+uy8cRX6mH3CWOSxAkdlKXqP9qRvZQqL+COMFWOyk3/i2v0EffNEdW0DoGEMODxer2zZs3ivj5y5IhOp+vRo0dsbOzdd9/tq1v22GOPabXa3r17R0RELFu2jGVZAEBRUVHr+tpcgCgA4Pnnn/cd1GrbrlrWr18fFRX13XfftT7Y2NjYu3fvgQMHct/W1NSkpKTExsb26NEjLi5u37593HEub7J3794ajWbKlCm1tbUAALVavWLFil9//ZWXu8MbyvT+zdfP39m1zdcvKFEB6K4RNurB+qP/aSdwnyovoKxFIf1HC2iUpAmfOCt8/MzK91c61i+q2Pi8/f9fqLxrcNRjSyGsLHojSAgDns8//1yv1/fs2RMA0KtXrytXrtjt9qqqqnvuueevf/0rd86qVauqq6stFsulS5c++OADrvaN1+tlWbbqv/gaUDQ1NS1dupQ72CYTMTc3d8eOHeHh4a2XdACAFStWmEymuro67luVSrV///7a2lq73f7GG2/MmjXL7XYDAB544IGysjKLxWK326urq//5z38CADAMW7BgAfd1AKHscXfztXN3cCFLU57CK/A7iyBHmTEIeJnmq2dvdULd95+EjXkY2sS1oEQ1cJxh9UeRU58Kv3eOcfXHYeOmB4QKAiSEd8yCBQs2bdo0YsQIvV7/1FNPVVRUPPzwwwaDYcqUKZw/sL6+ftq0aUlJSYmJiU888YRPUdasWZOcnJyQkDBo0KDc3FwAwPbt2zMyMkwmU58+fQ4d+kMIwL59+5555hnft5s2bVq3bl0bS7Zv387lEQIA9Ho9l9SB4/iIESN8k6anp3P58snJyUlJSZWVlXfwK3u93qeeeurtt9/2ldHhOHXq1C+//PLUU0/5jsjlcl9BuNGjRzc3N3NNl5KSktRqNQBArVYPHDjQZ8ZDDz30+eefc+cECooe/T3mX1nKc/tT/4jb/CthTJap1HxYJSEwLOK+2bVfb7tpDW5P4VVP8fXQYZOFt0viYAQpT75L0a031MkSNxCor0tMTcVtt8r9CK6ObPNcc3NzT58+/fnnn4eGhg4bNiwrK2vLli19+vR5+OGHN27cuGrVKplM9swzzwwdOpRhmCVLlqxYsWLz5s0//fTTv//97/Pnz2s0mry8vIiIiOrq6meffTYnJyclJcVqtbbpcDRy5Mgnnnhi1apVMTExAICNGze+/fbbrU9gWfaHH35o3fyhqalpx44dDofj008/feWVV3zHT506df78+bNnz0ZHRz/88MPcwbq6OrVaTRDEhAkTNm7caDAYuOOvvvrq6tWrExMTV6xY8ec//5k7+M4772RkZHCl2ny43e6FCxfu3LmTE/XW7N6922Kx7Nu3b/Xq1T4Xa1FR0YEDB8xm89GjR7ncSgBAeHh4cnLyqVOnsrKyOv5QxEWmUpOmVHf+RWXPgZ26sPnqz8oMVADaDyjvGtLw41f1h/eGZc1sfZylqeo9GyMemIuR8ltdi0C0JiCFkHW7KjatALRwQhg67L6wsY+0Ofj0008nJSUBALKysmiaHjRoEADgoYce+vbbbwEAoaGh/fr1++677+x2u1ar/eyzzwAAcrm8trb22LFjf/rTn7ich5qaGpZljxw5otFojMa2ddm1Wm1WVtauXbsWLVp0+vTp+vr6ceP+UNavtra2pqamdQFShmEKCgrKy8ubm5vpVrfI6XTm5+ebzWatVuvxeFQqlV6vv3DhQq9evRwOx7x58+bMmcO5TJ955plXX301LCzs4MGDjzzySEJCwvjx44uKit59990b+0D9/e9/f/TdbdwAABBKSURBVOihhzIyMm4UwtLSUrPZ3CZCp7GxMT8/Pzc3F8MwiqJ8x00mU3Fx8W0fBFQoew1x/Xqq00J45bT2LwFTRgdyNDMWOdYvkiel/+5qZtmaPRtJQ6KqX+BFIyNEw++Zie0QTAn1Y8aM+fTTT7mvn3/++ZUrV3Jf79ixY9KkSSzLXrt2LTY29m9/+9ubb765evVqg8HAnbBt27bhw4eHhoY+8sgjlZWVLMt+//33kyZNUqvVo0ePvn79epuJ9u3b169fP5ZlFyxYwHV3ag0Xb+J0Om+08MCBAxERERRFtTmelZW1Zs2aNgevXr2K47jL5Wpz/M9//vNzzz3Hsuz06dP/8pe/7NmzZ8+ePUaj8X/+538uXrxoNps1Gs2OHTv27NnzwgsvGI3GPXv2NDc3tx6hoqJCrVafO3euzchr164dO3as79tx48Z98EHbxGdoE+o5qAqL5e+Psl5vxy/xWAqta2ffwVwolftWNOdfKl85o+HUfi9N0bVO5/ZX7W8t9rrb/iX7BfQUYAAl1AcSu3btmjZt2ttvv71kyZJ+/X4PEZwzZ86PP/5oNpvr6uq4QM2srKxvv/3WYrGkp6evWLGizTiTJ0+2WCxnzpzZvXv3E0880ean4eHhUVFRN627nZKS0tDQ0CaqhTvOtcJoTWNjI0EQN9bdbmhoUCqVAICePXvW1dXt3bt37969DQ0NP/3006VLl7xe7/jx47/44ou9e/f+9NNPDQ0Ne/fu5eJifERHR4eHh984Y0pKSutInPLycm55HUAQ0UZZuMZd2ImWwq6LJ1ABaP+iSO2tW/hq07nDlmVT7a/Mw8OjdAv/iXrwIjpFQLpGAwK9Xn/gwIGSkpLq6mpf0e0zZ87Y7fZBgwZ5PB63263T6YqLi48fPz5mzBiFQsEdAQBw0sKV5SQI4tFHH50zZ056ejpXtLMNY8aMOX36dK9evQAAu3fvVqlUaWlpdrt93bp19957r0qlcrlcGzZsGDduXFhY2MmTJ3fu3Pn1118DAL755hu3292zZ8+ysrJly5Y9+uijnBC+8soro0ePjoyM/Pbbb7/88stTp04BANasWeObsUePHi+88MIDDzwAWtXd/vzzz5ctW8Z9e/r06evXr/fv35+iqH/96184jnNlRd9+++0+ffoYjca8vLw1a9bMmTOHu7a6urq0tHTIkCF8PAheUWWOdJ0/rkjpaNVQV86PMJceDlDI2GTdX19nGRrDZECGXu4RnQYJ4R0yatSouLiWjnR9+vTxFd1OTEwcPnw4AGDu3LnXr1+fPHlyfHz82rVruVw6hULx8ccfv/jii6Ghoffee++CBQsqKioOHz7MhcAMHz587dq1AICQkJDo6N8LOs+dO7e8vPzxxx+/qSVz5szZuHHj3LlzAQAqlWrz5s3FxcUajWbs2LFLliwBAOA4brVaFy9eXF9fn5aW9tlnn3HFXEiSzM7OLi8v12q106ZNe+65lgr9NpttyZIljY2N6enphw8f5mqIt2bixIlt2iICAEwm08SJE7mvw8LCDhw4sGHDBoVCkZmZeezYMV/fjHXr1lVUVBgMhhdeeIGzGQDw6aefTps2TaVSdfIhiI+q/xj7m3+NmDq/I2H6VLnZ63GhZrw8gTIlEHdM27auvDJnzpwxY8bMnj27g+fX19eHhYUdPXp03bp1AVd8RDBYlh05cuQ777zTt29A1q70er2DBg365JNPfBkXPjQaTWFhYWRkpCiGdZCK7BfUo6d2xOFZ+8VWjJCH39fRv//WcP8Ld3Ahwo+gpwADfDwF5EYIeDAM++STTwL3/9Plcr3//vs3qmCgEDrkT42n9t/2NJahm84dUQ2eIIBJCASiUyAhDAbi4+NTUlLEtuIOCQ0NHTAggPPqQjJHekqu005r+6e5Lp4gjIlEdNsMGQQCITpICBGILoGR8tAhExt++KL90xqOf64e8YAwJiEQiE6BhBCB6CrqkQ82nTvibWjbasOHOzeHdTeF9Aq8sFgEQgogIUQgugoerlENHF+3f+fNf8yytV9vC5vwWKAUIEYgpIYfhPDIkSOTJ082mUzdunVbsmRJm2qZCIQUCM+a6bp4gioz3/ijxrMHAQCo4hcCAS1+yLwpKiqaNWvW+++/X19fP2vWrFWrVr3xxhtdH7Y19fX1v/zyi3/HRMAPw9yksQCcyELDIx6YV7Xjdf2St1uXNaErrbVf/Uv39MtoOYhAQIsfhNDXnQAAMG/evI8//rjrY7YmNjYWADB//nz/DovoIF6vVyZStY7evXuHhARMMxfVgLHugsvOD9Zq//x3rlcJU+Wo3PxixL1PkqZUsa1DIBC3xM+1GI4dO9a/f3//jtmjR4+ff/7Zv2MiOg5KIu44mkf+WvPZe7bX5ofePY6l3I3nDodPeCx06L1i24VAINqjQ5Vl6urqvvrqqxuPjx8/nuuTx/HRRx8tX7780qVLrcuDtSYzM/PixYu+byMjI/Py8tp0eW1NQ0MD18cVISLoKXQWpjyfzr0AcILsdY8syuCXMdFTgAH0FGCgs09BqVSSJNn+OR1aETY2Nn7//fc3Hu/fv79PCPft27ds2bKDBw/eSgUBAJmZmYsXL+54iTUAAFqLwAB6Cp0jvR9I73f70zoJegowgJ4CDPj9KXRICI1G4/bt29s5Yf/+/U8//fTXX3/N9UBAIBAIBCJQ8MMe4ffffz99+vStW7dGRUUVFBQQBJGQkND1YREIBAKBEAD/5BHqdLoVK1ZkZWVlZWXd2Dz2jtm///a1jBF8g54CDKCnAAP79+8Xsl0P4qYcOHDA6/X6d0x42zC53e6IiIjm5ma+rUK0D4YJ+keCuClKpbK2tradyDKEAERERJSUlERERIhtiKTR6/WXL1/W6/V+HBOVWEMgEAiEpEFCiEAgEAhJg4QQgUAgEJLGz5Vl2sdsNp87d27Hjh0dOdnr9VIUlZWVxbdViPbBMAw9BdGhKOree+8Vq9YdgqOpqWnq1Kk4jottiKSpra2dPn36bXPkfUydOnXhwoXtnyNoHMTJkycrKytVKlUHzy8sLExOTubVJMRtQU8BBtBTgAH0FGCgs08hOTk5NfU2xX5RQCACgUAgJA3ytCAQCARC0iAhRCAQCISkQUKIQCAQCEmDhBCBQCAQkgZfs2aN2DbcnDNnzhw8eJBlWaPRKLYtEqWqqurw4cOnT5/Gcdy/BY0QncXtdh87dowgCFTfSyzq6uq++eabn3/+mWVZg8E/bSYRneXkyZNHjx51OBxJSUl+zCaCdEW4atWqGTNmnDlzZsqUKevXrxfbHCny22+/JSUlvffee0eOHBkzZsyyZcvEtkjSvPTSS5MmTfr000/FNkSinD9/vnv37lu2bDly5EinOqoi/Mhjjz02d+7cnJycNWvWDBs2zI+VqGFMn6ioqEhMTLx06VK3bt1ycnJGjRpVXl6OGkMLTF1dndvt1ul0AIDLly/37t3bbrejdaEoXLx4ce7cuREREffee++SJUvENkdyMAzTs2fP55577rZ52Qj+KC8vj4uLs1gsRqORoqiEhITt27dPmDDBL4PDuCI8ePBgz549u3XrBgDIzMzU6XTHjx8X2yjJER4ezqkgAMBgMGAY5vF4xDVJmtA0PX/+/Pfff7/jpTQQ/uWXX36prKycNWvWDz/8cPHiRbHNkSihoaFKpbKpqQkA4PF4KIqKjo721+CClljrIJzy+741mUzl5eUi2oNYt27dhAkTWj8UhGD885//HD169N133y22IdLFbDaHhYWNHj06LS0tJycnIyPjP//5Dyp3JzCRkZG7d+++//77e/XqdeXKldWrV/fv399fg8MohAzDYBjm+5YgCJqmRbRH4mzevPnLL788ceKE2IZIkd9++23nzp3nzp0T2xBJ43K5SkpKdu7cOXz48KampvT09H379j388MNi2yUtKIp66623BgwYcP/996ekpLz77rszZszw12YNjEJoNBodDofvW7vdHhsbK6I9Umb79u0vv/zy0aNHTSaT2LZIkQ0bNkRGRnL7gleuXKmtrQ0NDZ0/f77YdkmL2NhYgiCGDRsGAFCpVIMHD758+TISQoE5cOBAfn7+oUOHZDLZtGnTcnJytm3b5q8gPhiFcOTIkQsWLHA6nVqttrS01Gw2Dx06VGyjpMiePXtWrFhx6NCh25asRfDEvHnzCgsLua/Pnj2blpbWp08fcU2SIEOGDFEoFEVFRVyt57y8vEmTJoltlOTAcZymaa/XyzmlPR6PH9uAwBg1CgB48skn8/LyZs6cuX379uHDh2/cuFFsiyTH5cuXMzMzR4wY0b17d+7I0qVL09LSxLVKykyaNCkrKwtFjYrCiy+++O23386dO/fkyZPnzp07f/58x7voIPxCU1PTgAEDUlNTJ0+efO7cuc8++ywnJyc+Pt4vg0MqhDRNf/LJJ1evXs3MzJw+fTralxYeq9X61VdftT5y//33o+IGIvLdd9/FxcX17t1bbEMkyhdffHHmzJmEhIRZs2ahbC5RaGxs/Pe//11QUGAwGGbOnOnHbC5IhRCBQCAQCGFAKy0EAoFASBokhAgEAoGQNEgIEQgEAiFpkBAiEAgEQtIgIUQgEAiEpEFCiEAgEAhJA2NlGQQCwZGbm3vq1CkAAI7js2bNav9ks9nMlYTFMOzJJ58Uwj4EIihAeYQIhGjs2rUrNjZ25MiRtzrh/ffff/rpp4cMGaJSqQ4fPtz+aN99993LL79cVlZWXFyM/q8RiI6DXKMIhGi8+OKLO3bsuO1p+/fvv60KAgAmTZp04sQJVJIbgegsSAgRiICkqqrK6XSKbQUCEQwgIUQgxCE5ObmwsPCjjz6KioqKior661//2sELN27cGBMTo9Vqo6Oj1Wr1okWLeLUTgQh6ULAMAiEO27Zte/zxxzMzMxcvXgwA6GDTzaNHjy5atGjNmjXTpk3DMCw3N/f69es8W4pABDlICBEIcRg9enRISIjJZBo/fnzHrzp37lxISMiqVaswDAMA9OzZkzcDEQipgFyjCEQg0a9fP5fLdd999+3du7e2tlZscxCIYAAJIQIRSIwfP37r1q1FRUXTp0+Pjo4eP378+fPnxTYKgQhskBAiEAHG3Llzr169WlRUtGnTpqKiogkTJtTX14ttFAIRwCAhRCBEQ61Wu1yuO7s2MTFx7ty5r7/+utPpzMvL869hCISkQMEyCIRo3HXXXYcPH/7yyy9NJpNWq01KSrrtJZs3bwYATJgwIT4+3mazffLJJ2FhYd27d+fdVgQieEErQgRCNNatW5eRkfHEE08MGDBg7dq1HbnE4/EsW7YsJSWFJMn4+PiLFy9+9tlnarWab1MRiCAGrQgRCNFISUk5dOhQpy559tlnFy5cWFhYWFVVpdPpEhIScBznyTwEQiIgIUQgYEen0ymVyrq6Ou5bHMe7det242kff/zxX/7yF6/XK6x1CETAg7pPIBDwUlNTY7VaAQAymaxHjx7tn1xbW2uxWAAAGIalp6cLYR8CERQgIUQgEAiEpEHBMggEAoGQNEgIEQgEAiFpkBAiEAgEQtIgIUQgEAiEpPl/IzemYfgFD1EAAAAASUVORK5CYII=",
- "image/svg+xml": [
- "\n",
- "\n"
- ],
- "text/html": [
- "\n",
- "\n"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "# input function format \"cxt\", dependent on `c` (component), `x` (state) and `t` (time)\n",
- "function extForce_cxt(c::Union{FMU2Component, Nothing}, x::Union{AbstractArray{<:Real}, Nothing}, t::Real, u::AbstractArray{<:Real})\n",
- " x1 = 0.0\n",
- " if x != nothing # this check is important, because inputs may be needed before the system state is known\n",
- " x1 = x[1] \n",
- " end\n",
- " u[1] = sin(t) * x1\n",
- " nothing\n",
- "end \n",
- "\n",
- "# simulate while setting inputs\n",
- "data_extForce_cxt = simulate(fmu, (tStart, tStop); saveat=tSave, inputValueReferences=[\"extForce\"], inputFunction=extForce_cxt, dtmax=1e-2, showProgress=false)\n",
- "plot(data_extForce_cxt)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Unload FMU\n",
- "\n",
- "After plotting the data, the FMU is unloaded and all unpacked data on disc is removed."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 7,
- "metadata": {
- "execution": {
- "iopub.execute_input": "2022-10-22T13:30:01.970000Z",
- "iopub.status.busy": "2022-10-22T13:30:01.970000Z",
- "iopub.status.idle": "2022-10-22T13:30:02.010000Z",
- "shell.execute_reply": "2022-10-22T13:30:02.010000Z"
- }
- },
- "outputs": [],
- "source": [
- "unloadFMU(fmu)"
- ]
- }
- ],
- "metadata": {
- "interpreter": {
- "hash": "037537ff7419c497b9325f7d495147943224d408cf5d5ed915294a5b960167b0"
- },
- "jupytext": {
- "cell_metadata_filter": "-all",
- "comment_magics": "false",
- "notebook_metadata_filter": "-all"
- },
- "kernelspec": {
- "display_name": "Julia 1.10.5",
- "language": "julia",
- "name": "julia-1.10"
- },
- "language_info": {
- "file_extension": ".jl",
- "mimetype": "application/julia",
- "name": "julia",
- "version": "1.10.5"
- },
- "nteract": {
- "version": "0.28.0"
- }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
+{
+ "cells": [
+ {
+ "attachments": {},
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Simulate an FMU with inputs\n",
+ "Tutorial by Tobias Thummerer\n",
+ "\n",
+ "🚧 This tutorial is under revision and will be replaced by an up-to-date version soon 🚧\n",
+ "\n",
+ "## License"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "execution": {
+ "iopub.execute_input": "2022-10-22T13:28:04.723000Z",
+ "iopub.status.busy": "2022-10-22T13:28:04.017000Z",
+ "iopub.status.idle": "2022-10-22T13:28:04.999000Z",
+ "shell.execute_reply": "2022-10-22T13:28:04.926000Z"
+ }
+ },
+ "outputs": [],
+ "source": [
+ "# Copyright (c) 2021 Tobias Thummerer, Lars Mikelsons, Josef Kircher, Johannes Stoljar\n",
+ "# Licensed under the MIT license. \n",
+ "# See LICENSE (https://github.com/thummeto/FMI.jl/blob/main/LICENSE) file in the project root for details."
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Introduction to the example\n",
+ "This example shows how to add custom inputs to a FMU, that are used during simulation.\n",
+ "\n",
+ "## Other formats\n",
+ "Besides, this [Jupyter Notebook](https://github.com/thummeto/FMI.jl/blob/examples/examples/src/inputs.ipynb) there is also a [Julia file](https://github.com/thummeto/FMI.jl/blob/examples/examples/src/inputs.jl) with the same name, which contains only the code cells and for the documentation there is a [Markdown file](https://github.com/thummeto/FMI.jl/blob/examples/examples/src/inputs.md) corresponding to the notebook. \n",
+ "\n",
+ "## Code section"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "execution": {
+ "iopub.execute_input": "2022-10-22T13:28:05.004000Z",
+ "iopub.status.busy": "2022-10-22T13:28:05.004000Z",
+ "iopub.status.idle": "2022-10-22T13:28:49.082000Z",
+ "shell.execute_reply": "2022-10-22T13:28:49.082000Z"
+ }
+ },
+ "outputs": [],
+ "source": [
+ "# imports\n",
+ "using FMI\n",
+ "using FMIZoo\n",
+ "using Plots\n",
+ "using DifferentialEquations"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Simulation setup\n",
+ "\n",
+ "Next, the start time and end time of the simulation are set. Finally, a step size is specified to store the results of the simulation at these time steps."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "execution": {
+ "iopub.execute_input": "2022-10-22T13:28:51.448000Z",
+ "iopub.status.busy": "2022-10-22T13:28:49.085000Z",
+ "iopub.status.idle": "2022-10-22T13:28:52.234000Z",
+ "shell.execute_reply": "2022-10-22T13:28:52.233000Z"
+ }
+ },
+ "outputs": [],
+ "source": [
+ "tStart = 0.0\n",
+ "tStep = 0.01\n",
+ "tStop = 8.0\n",
+ "tSave = tStart:tStep:tStop"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Import FMU\n",
+ "\n",
+ "Next, the FMU model from *FMIZoo.jl* is loaded."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "execution": {
+ "iopub.execute_input": "2022-10-22T13:28:52.238000Z",
+ "iopub.status.busy": "2022-10-22T13:28:52.237000Z",
+ "iopub.status.idle": "2022-10-22T13:28:57.034000Z",
+ "shell.execute_reply": "2022-10-22T13:28:57.034000Z"
+ }
+ },
+ "outputs": [],
+ "source": [
+ "# we use an FMU from the FMIZoo.jl\n",
+ "fmu = loadFMU(\"SpringPendulumExtForce1D\", \"Dymola\", \"2022x\"; type=:ME) # load FMU in ME-Mode (\"Model Exchange\")"
+ ]
+ },
+ {
+ "attachments": {},
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "#### Simulate as Model-Exchange\n",
+ "\n",
+ "In the function `simulate()` the FMU is simulated with an adaptive step size but with fixed save points `tSave`. In addition, the start and end time are specified. Note, that the dynamics of the input variables are not considered by the steps ize control of the solver, so it is highly recommended to limit the solver step size with the keyword argument `dtmax` if the input is more dynamic than the system."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "execution": {
+ "iopub.execute_input": "2022-10-22T13:29:04.979000Z",
+ "iopub.status.busy": "2022-10-22T13:29:04.978000Z",
+ "iopub.status.idle": "2022-10-22T13:29:21.052000Z",
+ "shell.execute_reply": "2022-10-22T13:29:21.052000Z"
+ }
+ },
+ "outputs": [],
+ "source": [
+ "# input function format \"t\", dependent on `t` (time)\n",
+ "function extForce_t(t::Real, u::AbstractArray{<:Real})\n",
+ " u[1] = sin(t)\n",
+ "end \n",
+ "\n",
+ "# simulate while setting inputs\n",
+ "data_extForce_t = simulate(fmu, (tStart, tStop); # FMU, start and stop time\n",
+ " solver = Tsit5(),\n",
+ " saveat=tSave, # timepoints for the ODE solution to be saved\n",
+ " inputValueReferences=[\"extForce\"], # the value references that should be set (inputs)\n",
+ " inputFunction=extForce_t, # the input function to be used\n",
+ " dtmax=1e-2, # limit max step size to capture inputs\n",
+ " showProgress=false) # disable progress bar\n",
+ "plot(data_extForce_t)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# input function format \"cxt\", dependent on `c` (component), `x` (state) and `t` (time)\n",
+ "function extForce_cxt(c::Union{FMU2Component, Nothing}, x::Union{AbstractArray{<:Real}, Nothing}, t::Real, u::AbstractArray{<:Real})\n",
+ " x1 = 0.0\n",
+ " if x != nothing # this check is important, because inputs may be needed before the system state is known\n",
+ " x1 = x[1] \n",
+ " end\n",
+ " u[1] = sin(t) * x1\n",
+ " nothing\n",
+ "end \n",
+ "\n",
+ "# simulate while setting inputs\n",
+ "data_extForce_cxt = simulate(fmu, (tStart, tStop); saveat=tSave, inputValueReferences=[\"extForce\"], inputFunction=extForce_cxt, dtmax=1e-2, showProgress=false)\n",
+ "plot(data_extForce_cxt)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Unload FMU\n",
+ "\n",
+ "After plotting the data, the FMU is unloaded and all unpacked data on disc is removed."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "execution": {
+ "iopub.execute_input": "2022-10-22T13:30:01.970000Z",
+ "iopub.status.busy": "2022-10-22T13:30:01.970000Z",
+ "iopub.status.idle": "2022-10-22T13:30:02.010000Z",
+ "shell.execute_reply": "2022-10-22T13:30:02.010000Z"
+ }
+ },
+ "outputs": [],
+ "source": [
+ "unloadFMU(fmu)"
+ ]
+ }
+ ],
+ "metadata": {
+ "interpreter": {
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+ "display_name": "Julia 1.10.4",
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