From 0b3e408803ca309817a0d5231df1979027061ae6 Mon Sep 17 00:00:00 2001 From: Marcos Duarte Date: Tue, 19 Sep 2023 00:56:17 -0300 Subject: [PATCH] Criado usando o Colaboratory --- notebooks/BMClab.ipynb | 1443 ++++++++++++++++++++-------------------- 1 file changed, 703 insertions(+), 740 deletions(-) mode change 100755 => 100644 notebooks/BMClab.ipynb diff --git a/notebooks/BMClab.ipynb b/notebooks/BMClab.ipynb old mode 100755 new mode 100644 index 68ac6a1..0101d71 --- a/notebooks/BMClab.ipynb +++ b/notebooks/BMClab.ipynb @@ -1,780 +1,743 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "nbpresent": { - "id": "b939d778-a63f-4c3d-9bb5-a0c2368e8e50" - }, - "slideshow": { - "slide_type": "slide" - }, - "urth": { - "dashboard": { - "hidden": true, - "layout": {} - } - } - }, - "source": [ - "# Laboratório de Biomecânica e Controle Motor\n", - "**[BMClab](https://bmclab.pesquisa.ufabc.edu.br/)@[UFABC](https://www.ufabc.edu.br/): Why, How, What For?**\n", - "\n", - "
\n", - "
\"BMClab
" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": { - "ExecuteTime": { - "end_time": "2018-04-16T22:45:02.183391Z", - "start_time": "2018-04-16T22:45:02.179391Z" - }, - "cell_style": "center", - "nbpresent": { - "id": "f34b8454-e464-41c6-b6ad-aed29e717387" - }, - "slideshow": { - "slide_type": "fragment" - }, - "urth": { - "dashboard": { - "layout": { - "col": 0, - "height": 4, - "row": 0, - "width": 4 - } - } - } - }, - "outputs": [ + "cells": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "01:44 PM, Tuesday, September 20, 2022\n", - "Marcos Duarte, https://bmclab.pesquisa.ufabc.edu.br/\n" - ] - } - ], - "source": [ - "from datetime import datetime\n", - "print(datetime.now().strftime(\"%I:%M %p, %A, %B %d, %Y\"))\n", - "print('Marcos Duarte, https://bmclab.pesquisa.ufabc.edu.br/')" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "slide" - }, - "toc": true - }, - "source": [ - "

Contents

\n", - "
" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "nbpresent": { - "id": "a1123914-0098-4f4e-a058-0f60c30a4ec4" - }, - "slideshow": { - "slide_type": "slide" - }, - "urth": { - "dashboard": { - "layout": { - "col": 0, - "height": 6, - "row": 4, - "width": 12 - } - } - } - }, - "source": [ - "## Stuff in this talk\n", - "\n", - "- [BMClab](http://demotu.org): why and how\n", - "- [BMClab](http://demotu.org) infrastructure, current and future activities \n", - "- Open data science and education \n", - "- Literate programming & Literate computing\n", - "- Advocacy for Python (the programming language)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "ExecuteTime": { - "end_time": "2018-04-16T22:45:04.260557Z", - "start_time": "2018-04-16T22:45:04.252552Z" - }, - "nbpresent": { - "id": "2cc4e37c-dfa0-4239-a62b-5517692c56b9" - }, - "slideshow": { - "slide_type": "slide" - }, - "urth": { - "dashboard": { - "layout": { - "col": 0, - "height": 21, - "row": 10, - "width": 4 - } - } - } - }, - "source": [ - "## [BMClab](https://bmclab.pesquisa.ufabc.edu.br/) website\n", - "\n", - "[Laboratory of Biomechanics and Motor Control](https://bmclab.pesquisa.ufabc.edu.br)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "nbpresent": { - "id": "0cbd523b-0ecc-48e6-b915-61c32b32246f" - }, - "slideshow": { - "slide_type": "slide" - }, - "urth": { - "dashboard": { - "layout": { - "col": 0, - "height": 7, - "row": 31, - "width": 12 - } - } - } - }, - "source": [ - "## Why the [BMClab](https://bmclab.pesquisa.ufabc.edu.br/)\n", - "\n", - "**[Biomedical engineering](https://en.wikipedia.org/wiki/Biomedical_engineering)**: the application of engineering principles and design concepts to medicine and biology for healthcare *and well-being* purposes.\n", - "\n", - "**[Neuroscience of human movement](https://en.wikipedia.org/wiki/Neuroscience)**: the scientific study of the nervous system bases of controlling movement.\n", - "\n", - "**[Biomechanics](https://en.wikipedia.org/wiki/Biomechanics) and [Motor Control](https://en.wikipedia.org/wiki/Motor_control)**: the study of the structure and function of biological systems using the knowledge and methods of the Mechanics and the study of how the biological systems control their movements.\n", - "\n", - "**[BMClab](http://demotu.org)**: In a broad sense, we are interested in knowing how living beings control and execute their movements. We also work to improve the quality of life in society by offering evaluation services in our laboratory and in the dissemination of scientific knowledge." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "nbpresent": { - "id": "217e5f45-bda6-4948-8c2a-a8ecfce99bb9" - }, - "slideshow": { - "slide_type": "slide" - }, - "urth": { - "dashboard": { - "layout": { - "col": 0, - "height": 6, - "row": 38, - "width": 12 - } - } - } - }, - "source": [ - "## [BMClab](https://bmclab.pesquisa.ufabc.edu.br/) lines of research\n", - "\n", - "- Postural control in humans \n", - "- Clinical gait analysis \n", - "- Biomechanics of long distance running \n", - "- Modeling and simulation of the neuromusculoskeletal system\n", - "- ..." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "nbpresent": { - "id": "c64b1ddf-0a73-4c83-8527-576417da242f" - }, - "slideshow": { - "slide_type": "slide" + "cell_type": "markdown", + "metadata": { + "nbpresent": { + "id": "b939d778-a63f-4c3d-9bb5-a0c2368e8e50" + }, + "urth": { + "dashboard": { + "hidden": true, + "layout": {} + } + }, + "id": "MTMMdzcojkBC" + }, + "source": [ + "# Laboratório de Biomecânica e Controle Motor\n", + "**[BMClab](https://bmclab.pesquisa.ufabc.edu.br/)@[UFABC](https://www.ufabc.edu.br/): Why, How, What For?**\n", + "\n", + "
\n", + "
\"BMClab
" + ] }, - "urth": { - "dashboard": { - "layout": { - "col": 0, - "height": 6, - "row": 44, - "width": 12 - } - } - } - }, - "source": [ - "## [BMClab](https://bmclab.pesquisa.ufabc.edu.br/) financial support\n", - "\n", - "The [BMClab](https://bmclab.pesquisa.ufabc.edu.br/) was made possible by the financial support from UFABC and from Brazilian research agencies, nominally: \n", - "- Project \"Controle do equilíbrio e movimento em adultos jovens e idosos sedentários e corredores\" (FAPESP). \n", - "- Project \"Postura e envelhecimento: criação de base de dados pública de sinais de oscilação e simulação computacional de mecanismos de controle\" (FAPESP)." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "nbpresent": { - "id": "7aceb8ec-4232-4e57-8cf2-10d31c898f65" + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "ExecuteTime": { + "end_time": "2018-04-16T22:45:02.183391Z", + "start_time": "2018-04-16T22:45:02.179391Z" + }, + "cell_style": "center", + "nbpresent": { + "id": "f34b8454-e464-41c6-b6ad-aed29e717387" + }, + "urth": { + "dashboard": { + "layout": { + "col": 0, + "height": 4, + "row": 0, + "width": 4 + } + } + }, + "id": "2kmrcsMejkBF", + "outputId": "543533d3-ed0d-4b2b-888a-742748ea8765" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "01:44 PM, Tuesday, September 20, 2022\n", + "Marcos Duarte, https://bmclab.pesquisa.ufabc.edu.br/\n" + ] + } + ], + "source": [ + "from datetime import datetime\n", + "print(datetime.now().strftime(\"%I:%M %p, %A, %B %d, %Y\"))\n", + "print('Marcos Duarte, https://bmclab.pesquisa.ufabc.edu.br/')" + ] }, - "slideshow": { - "slide_type": "slide" + { + "cell_type": "markdown", + "metadata": { + "toc": true, + "id": "JRLdbc5bjkBG" + }, + "source": [ + "

Contents

\n", + "
" + ] }, - "urth": { - "dashboard": { - "layout": { - "col": 0, - "height": 8, - "row": 50, - "width": 12 - } - } - } - }, - "source": [ - "### [BMClab](https://bmclab.pesquisa.ufabc.edu.br/) financial support (II)\n", - "\n", - "The [BMClab](https://bmclab.pesquisa.ufabc.edu.br/) was made possible by the financial support from UFABC and from Brazilian research agencies, nominally: \n", - "- Project \"Estudo do equilíbrio de pessoas com deficiências e idosos: uma base de dados aberta\" (CNPq). \n", - "- Project \"Desenvolvimento de simulador de cadeira de rodas e de serviço de avaliação do movimento e postura para deficientes físicos com próteses/órteses e usuários de cadeira de rodas\" (MCTI-SECIS/CNPq). \n", - "- Project \"Análise de atletas corredores: estudo multicêntrico para compreensão do movimento com implicação para prevenção de lesão e melhora do rendimento\" (ME/CNPq). " - ] - }, - { - "cell_type": "markdown", - "metadata": { - "nbpresent": { - "id": "a4bc4fb9-42b0-4fa6-b5c3-14f4c7b34831" + { + "cell_type": "markdown", + "metadata": { + "nbpresent": { + "id": "a1123914-0098-4f4e-a058-0f60c30a4ec4" + }, + "urth": { + "dashboard": { + "layout": { + "col": 0, + "height": 6, + "row": 4, + "width": 12 + } + } + }, + "id": "_gZ6FIRqjkBG" + }, + "source": [ + "## Stuff in this talk\n", + "\n", + "- [BMClab](http://demotu.org): why and how\n", + "- [BMClab](http://demotu.org) infrastructure, current and future activities\n", + "- Open data science and education \n", + "- Literate programming & Literate computing\n", + "- Advocacy for Python (the programming language)" + ] }, - "slideshow": { - "slide_type": "slide" + { + "cell_type": "markdown", + "metadata": { + "ExecuteTime": { + "end_time": "2018-04-16T22:45:04.260557Z", + "start_time": "2018-04-16T22:45:04.252552Z" + }, + "nbpresent": { + "id": "2cc4e37c-dfa0-4239-a62b-5517692c56b9" + }, + "urth": { + "dashboard": { + "layout": { + "col": 0, + "height": 21, + "row": 10, + "width": 4 + } + } + }, + "id": "tjTZQ7DsjkBH" + }, + "source": [ + "## [BMClab](https://bmclab.pesquisa.ufabc.edu.br/) website\n", + "\n", + "[Laboratory of Biomechanics and Motor Control](https://bmclab.pesquisa.ufabc.edu.br)" + ] }, - "urth": { - "dashboard": { - "layout": { - "col": 4, - "height": 7, - "row": 10, - "width": null - } - } - } - }, - "source": [ - "## [BMClab](https://bmclab.pesquisa.ufabc.edu.br/) infrastructure\n", - "\n", - "180-m$^2$ laboratory organized in spaces for: \n", - "- Data collection with motion capture system, force plates, etc. \n", - "- Data analysis with several computers \n", - "- Subject preparation and evaluation \n", - "- Machine and electronics assembly" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "nbpresent": { - "id": "45213ee3-cb7c-4574-9425-beb4ffec8a8a" + { + "cell_type": "markdown", + "metadata": { + "nbpresent": { + "id": "0cbd523b-0ecc-48e6-b915-61c32b32246f" + }, + "urth": { + "dashboard": { + "layout": { + "col": 0, + "height": 7, + "row": 31, + "width": 12 + } + } + }, + "id": "3ay7V3CDjkBH" + }, + "source": [ + "## Why the [BMClab](https://bmclab.pesquisa.ufabc.edu.br/)\n", + "\n", + "**[Biomedical engineering](https://en.wikipedia.org/wiki/Biomedical_engineering)**: the application of engineering principles and design concepts to medicine and biology for healthcare *and well-being* purposes.\n", + "\n", + "**[Neuroscience of human movement](https://en.wikipedia.org/wiki/Neuroscience)**: the scientific study of the nervous system bases of controlling movement.\n", + "\n", + "**[Biomechanics](https://en.wikipedia.org/wiki/Biomechanics) and [Motor Control](https://en.wikipedia.org/wiki/Motor_control)**: the study of the structure and function of biological systems using the knowledge and methods of the Mechanics and the study of how the biological systems control their movements.\n", + "\n", + "**[BMClab](http://demotu.org)**: In a broad sense, we are interested in knowing how living beings control and execute their movements. We also work to improve the quality of life in society by offering evaluation services in our laboratory and in the dissemination of scientific knowledge." + ] }, - "slideshow": { - "slide_type": "slide" + { + "cell_type": "markdown", + "metadata": { + "nbpresent": { + "id": "217e5f45-bda6-4948-8c2a-a8ecfce99bb9" + }, + "urth": { + "dashboard": { + "layout": { + "col": 0, + "height": 6, + "row": 38, + "width": 12 + } + } + }, + "id": "cu41VwSGjkBH" + }, + "source": [ + "## [BMClab](https://bmclab.pesquisa.ufabc.edu.br/) lines of research\n", + "\n", + "- Postural control in humans \n", + "- Clinical gait analysis \n", + "- Biomechanics of long distance running \n", + "- Modeling and simulation of the neuromusculoskeletal system\n", + "- ..." + ] }, - "urth": { - "dashboard": { - "layout": { - "col": 0, - "height": 26, - "row": 58, - "width": 12 - } - } - } - }, - "source": [ - "
\"BMClab
" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "nbpresent": { - "id": "21d7855d-792b-4bd7-9365-61f456186b0e" + { + "cell_type": "markdown", + "metadata": { + "nbpresent": { + "id": "c64b1ddf-0a73-4c83-8527-576417da242f" + }, + "urth": { + "dashboard": { + "layout": { + "col": 0, + "height": 6, + "row": 44, + "width": 12 + } + } + }, + "id": "Z2CkVo0YjkBH" + }, + "source": [ + "## [BMClab](https://bmclab.pesquisa.ufabc.edu.br/) financial support\n", + "\n", + "The [BMClab](https://bmclab.pesquisa.ufabc.edu.br/) was made possible by the financial support from UFABC and from Brazilian research agencies, nominally: \n", + "- Project \"Controle do equilíbrio e movimento em adultos jovens e idosos sedentários e corredores\" (FAPESP). \n", + "- Project \"Postura e envelhecimento: criação de base de dados pública de sinais de oscilação e simulação computacional de mecanismos de controle\" (FAPESP)." + ] }, - "slideshow": { - "slide_type": "slide" + { + "cell_type": "markdown", + "metadata": { + "nbpresent": { + "id": "7aceb8ec-4232-4e57-8cf2-10d31c898f65" + }, + "urth": { + "dashboard": { + "layout": { + "col": 0, + "height": 8, + "row": 50, + "width": 12 + } + } + }, + "id": "aZxTrejmjkBI" + }, + "source": [ + "### [BMClab](https://bmclab.pesquisa.ufabc.edu.br/) financial support (II)\n", + "\n", + "The [BMClab](https://bmclab.pesquisa.ufabc.edu.br/) was made possible by the financial support from UFABC and from Brazilian research agencies, nominally: \n", + "- Project \"Estudo do equilíbrio de pessoas com deficiências e idosos: uma base de dados aberta\" (CNPq). \n", + "- Project \"Desenvolvimento de simulador de cadeira de rodas e de serviço de avaliação do movimento e postura para deficientes físicos com próteses/órteses e usuários de cadeira de rodas\" (MCTI-SECIS/CNPq). \n", + "- Project \"Análise de atletas corredores: estudo multicêntrico para compreensão do movimento com implicação para prevenção de lesão e melhora do rendimento\" (ME/CNPq). " + ] }, - "urth": { - "dashboard": { - "layout": { - "col": 0, - "height": 9, - "row": 84, - "width": 12 - } - } - } - }, - "source": [ - "### [BMClab](https://bmclab.pesquisa.ufabc.edu.br/) equipment\n", - "\n", - "- 12-camera Motion capture system \n", - "- Six-component instrumented dual-belt treadmill \n", - "- Six-component force plates \n", - "- Pressure distribution transducers \n", - "- Tri-axial accelerometers \n", - "- Wheelchair six-component transducers \n", - "- Six-component torque transducer \n", - "- 10-channel wireless electromyography system \n", - "- ..." - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": { - "ExecuteTime": { - "end_time": "2018-04-16T22:45:20.331960Z", - "start_time": "2018-04-16T22:45:18.775431Z" + { + "cell_type": "markdown", + "metadata": { + "nbpresent": { + "id": "a4bc4fb9-42b0-4fa6-b5c3-14f4c7b34831" + }, + "urth": { + "dashboard": { + "layout": { + "col": 4, + "height": 7, + "row": 10, + "width": null + } + } + }, + "id": "bajjeG0BjkBI" + }, + "source": [ + "## [BMClab](https://bmclab.pesquisa.ufabc.edu.br/) infrastructure\n", + "\n", + "180-m$^2$ laboratory organized in spaces for: \n", + "- Data collection with motion capture system, force plates, etc. \n", + "- Data analysis with several computers \n", + "- Subject preparation and evaluation \n", + "- Machine and electronics assembly" + ] }, - "nbpresent": { - "id": "9496bc91-1c35-4722-88d1-f279a91a46c4" + { + "cell_type": "markdown", + "metadata": { + "nbpresent": { + "id": "45213ee3-cb7c-4574-9425-beb4ffec8a8a" + }, + "urth": { + "dashboard": { + "layout": { + "col": 0, + "height": 26, + "row": 58, + "width": 12 + } + } + }, + "id": "CnzcwNYYjkBI" + }, + "source": [ + "
\"BMClab
" + ] }, - "slideshow": { - "slide_type": "slide" + { + "cell_type": "markdown", + "metadata": { + "nbpresent": { + "id": "21d7855d-792b-4bd7-9365-61f456186b0e" + }, + "urth": { + "dashboard": { + "layout": { + "col": 0, + "height": 9, + "row": 84, + "width": 12 + } + } + }, + "id": "qfP6CoaxjkBI" + }, + "source": [ + "### [BMClab](https://bmclab.pesquisa.ufabc.edu.br/) equipment\n", + "\n", + "- 12-camera Motion capture system \n", + "- Six-component instrumented dual-belt treadmill \n", + "- Six-component force plates \n", + "- Pressure distribution transducers \n", + "- Tri-axial accelerometers \n", + "- Wheelchair six-component transducers \n", + "- Six-component torque transducer \n", + "- 10-channel wireless electromyography system \n", + "- ..." + ] }, - "urth": { - "dashboard": { - "layout": { - "col": 0, - "height": 17, - "row": 93, - "width": 9 - } - } - } - }, - "outputs": [ { - "data": { - "image/jpeg": 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oaK8sWO9tENOZF2dLYuXmeXF6As111R9UiVypS9jnVybm2uor5OZa/uy2NLt0nnVeZpNFHmLIul6MTEvvlcttmjlJyp+L1K1tnU3un1fqTXdOTU9euiC+hut69SHDtdcuiZWNsrIjKu1xZF1M287E85dcF3Mp4lvXrpZosaXBdTtR01uQ6VEzuB46SSk0XOZx5xgukzl5awixkWK7G2n6oseH6mptszMFvy0pG1hXQp2/ocpNPZnydsNMzxdfqDimcRN7Og8TZLtuaTOdOseHK7CZJEYkSQRpIf8AhIvcll6ET9TKgNiAAoABQACFCEF0ApFJoNC7DZRo8P2yJf8AhL1j7lHh/wCXn/4S5N9z3fG/5c8jJDdDvUSfwwb9/Y726jMb3hvB64XZso9SgumC+pm8hRdk5E5X9u/ZHWcTj/YeCqrn2l09Uv1ZzvI29V02vmfK5uTdevjwZX2amn73d/IdFV+8YxX1KuRlqub6IuUx8uLyc3CeQ7Ftfg2co63x6NutxlZ0Rk2/oJCFVk+mEmpfJhg4V93I0Sy49EIaW9eyOi5HHwsm6Lx6NNNbku2y0x3b5ZCxbaZLqNvi7pVySbKjhJPy3Pr12X0LuLQ1o511sb0bVJI5rxJGyd8VDbizcgnFFfNqVle/dA05r7DVSlLJl8T/AAruQ3ZFFE7Ko405eXHqlqP3fqzdwNYdknOqFu3vcvVGbz+JPLy55GO/L82PTNJ+qNyud3+MiOfVKCceuEvdv0LNeRKa1Jp/oRww66cKyqyLlOX09CDEw7o2rXV0/Uvhz8/qPlI9PQ/mjPT7o1+Vqfw7XpEyNaZ0npwy9tKp9VZVt7WFnFXwEGTHU9lc9p61uJJX8MtEeL3giSa0yxipLIKaKk4uDLlb2ht1fUgzPCp17RBYSyj0sjmRuExbXTapbOu4vNV9PQ2cW3pmvwmQ4z1szXWNjy+jKbfzLWZVCeOmRXaep7I7LXKtxRGnO3T8vIlp+477Q9eombjzVzlrsyuoNGkrW4yzzLdv0Rr5Li6+xk8ZQ4Q38y5OXszKqNmTGNnTIhyEpx6oeqKvJxlG5SRJhW+Yul+ppnZaeRcfhmjSwJLIsWo7K0eIldcpr7pvY1ePhVJLW0RqRr4cI1QXZJlDnLUqZNFaXK/GkvQfkVPNpf1RGpWDhZsp2dK+Z0Fbap6mYmHgujI1Lt3NvIfRi6XyJprbluUs6733M5+pZyH1Wyf1IJI3HGmolgRaJoFIJvsRa7kkxqRFIACECgIBQuxdjRQFAAIAAFA0OI7Wzf5S5JlPiF1WWr8pZktPR7/jf8ueR0VtFziMP7fytdbW66vimVE+mtt+x0Pgulum/Ia/lJdv0Nc+eouE8t3Oi5U9K7I5+7j/ADJNt+p01sdopWV/Q+VZt7MXP/wVT7x/YfDjoLt3S/U1nT3BVGdu0kVfs8elJRGfZm38i/06H9KJtvWlGrDjF7S2y2q1CHU0Swgo936FTIyLL7VVTD4feRWKl83b7IWUeuAsaY1x3OcdlmEY9KfZl0dvDIprU7XCfZll4Si/TaG5vwZUZ1JN+6L9FitgtrT90ZYZ08Kt7+BFaWJGuW0jbcV8iG6EdegWuQ56hunrS9DmXrZ2vLw3jzXzRxNi6ZnbC+Hj5J5XcWfbQ3K9SPFl3LkKldbFS9Dbkiwq7Ja6Ytlu2qUV3WjrOJ4/Hhjp9KbKHOU1wTcVoRztjnq5dLJ13RVfaRPXLaKiDIr90UpxNO1biUbY9wuNVJRJ8GXl2p7GuL+QzfS9ma7R2OND7TR6+gz7NKuXf0KvA5e2otnS3UxnX1Ixt0jmM/pXfRTrjXbJJGhm0uTkkijg4tkcnujSVreUqcbq+hj2ZMlf0/M182+MKlD3MxUK2fUl6CBbqI219yDFwG7o9BPJy61E0KEqodTGzTRhWq8bpS76Mq+E3Y9+hcoy/Mn0k9tHXHaRFZEMeU5rXzOmwq+jGUdd9FGilQ127mrjJJdyEZMsGyzKcmtR2N5RxpxmtmlfkfG1FGHzFV16fSnoNVy9j6pt/UY0zVq4i+X4WXKuBsetxN7c7HOKLfsTQqm/SLOsp8PL3gXquEhFfcQ2sxcXHDtn+Fk0OLuf4TuK+Mrj7L+wnjh1R9kTa6jzBoaOY1sMABNhsqlFEFQAGxNC6ANibHdImiDQ4btbY/yl2S3Iz+Nl03S+qNH8R7/j3/VzyVuQsdeLqPrJ6PQPDuOqOHx9Lu4ps4SWNLNynTHv5cerR6Nw+lxuOvyI4c+W8tOmM1NpJogsiXrILRWsieWx2wyU5NLsNGX7jMYrGcq9WKdIckhlctokEKhy7FVQ3rt7mdk8jOFfRhUxsm122y/f8cWn6MyvsKqscq5td9l2vXwwLszm45EldVtJ9467GzTy1iogrI9Evdb9DSilZDU9N/NkcuPpnYptbLax10yo2Z3JZMpY8vIx4LvZNer+htcNK12WRssVnStdS92Q3w8xeSvhr36ItYThRHy4f1mbUq9N6RTutLV3xQ2jKyJtSZD8Z3MW/wARJ/Q5C6O+50XNW6x2vmzBkk4nbB5OT2ZjrUjTpglqRl1tqZo126gdHGtCHM3Y8eiL2RZGbZlL4zJnY5WFul7QjlYZZH3Erlpk8o7RXkullInl3iWuL4a3kLPRqHzK+HHzrYxfuzv+Jprx8SKhrb9SVm5dXMcn4ejjY/UvY5PJq6LGkd54p5OuuryYtORw9m5tv5iRrDK1Jxd3lZC7nbY9srsXa+RwVMZRui0vc7TiLW8dxaM16cVJ3RjkOElvZZnGuqnrUe5UyMaUs1NL3NG7GlLHUdEX9cnyOTKy7t7F7hd2z6X7l3+BHa9tdy5hcd9lkuxTSHN47ytWIoTlZJaUWdZOtXQ0yKvj6/kibVgYVFkZJtG9jw64JSRM8aFfokOoS6gkh1eCl8TG2arekWr7411GVZlwnL1I1U8aYye/cnhjwktSSIapx6OrZVyeWrpk0mQ21FTTH8KFTqi/Y5u3nV7MqT5qTfZlZ7OwldUvxIilm0x/EcdPlrJe5Xnn2y92XVOzsJ8rVH3K8uZr36nIyvsl+JjHZL5jSbUNMa4kgjZUM6Q6R2w2FJoA2BQAIwIF2GxBNASU2uFikjYxrY3uLT/UxNEtFsqZqSfodePPoljsOO4+zHoefWk7p/gfvE6XiclW0qPT0Nfh+RWcVGul1/cda0LSvKtjNfPucM8rctvX1nRtN7iQWEifYjmWuOM8szLX8YiLoetlvIh1tfQbCHw9znY9ONR1JolfaPcdGGiDKnqtpepldoZ27k0hr109yG2SrrTk9Mz8rkOlaiWNTy0ITUW/kMsy+l6UkjAXITuu8uEuqXy2LKi+diU7a4dS7bkXS3KRuQvhJ76lserF1bT7nLZdk8KajO6Mt/0HslxORfq5bQ0zbt19eSnuLKGbLUgxrY5Faa9RmcmobZnTlWJycPOqs766F1L6mJXLaOnxfL+0PzdOLj7mJk0R+22KiO4b7aO2LzZqfT8ZbgtwHRwbZ+kGXsfi7pLTTRtz0xZRasLmOa8eAnKXeJex+CUF3itjaXDbEUW/YZPGsl6RZ1dfFVr1SLUMCmK9CbScbkMLDvhapdLOjx55Ma+lbNGONVH2RIoQXyJtbxSuYu4S7MyPMtbeyeHhyteq2b7srh7jHl1L8SJ2dJjIyVwdNa309y1jY8a10pDsjkqY9upEFGfVOXaSJtVtYkXJS0TWQXl/oNrnv9CnymZ5FLaDSaqyMZaYzJyIQWznquTlZb6js7IbrfcrO2vVyMZS6UySzkFUtnL8fObsb29F66zq7Nk0LtvLOT0tl2rJ/iVIxYVwa2mmTxnJVtewFxZnnOUdmbdVar0190ovN+z5L7liXL19O99wbXr8t14+tmBkWSnPeyPL5B2vSfYpyub9zTK1+rE60U3ZL5idUiotu2KE85FVsAqw7tjXayHYBT9jWO0JogaA4QBBQFANBoA2AaDQbDYAAbADoOG8Q5Fd2PjZM08fajt+qR3Cp3Jae4PumeTvfsek+FM5Z3DVqT3ZT8EiWOmGV9NyP3RlhIvQbNEWe1SXqLFD5R7hFaI67NsWkUbWmaFi6oGbZ2skjGTWHlkclj33vcJaSMa3AunJKdkkvfS9Tq2u5VyauoSusjFr4rD18cJr6xl3LEOM4iFfxVX2S3+KYtvXVvS2VXmT3/JSf9RrbXXG+1ieJhacasZQi3vu9sipxKa/gjHtvYyNmRc30wcV9S/hY0m+qb2S1LJ+NHFrjGtaWiDkP5ItaaitehQ5CbWkZcMvCHAw45uRKMl2gtmtXxVEH91Gdw+RDHldKb11F+zlqoe6Okea1dhhUx/CiVU1RXZIwredgvRlWfO79JF8pt03VXH3SGyyakvvI5C/mLJejKz5GyXuyyVm119ufXD3RTs5eK9GczPLnL3IZXSl7jTPZ0s+cUUVrOffszAbkxrRepto38zdP0ZVfI5Evd/2lbqihFZHei6VJbkXT9ZMt8T1yyEttmdZaoo2/C0IW5acmhYR2OLUlXHfqV+RwIZFMl9C5a1Wl0taM7P5OGOtNmXVzy4p41jbkVcxy30pNmt/CdORLUtEWVbixh1LWwzqKlcoY9G3rZkZedJ2PpfYTOzeuTjAz3LbNM7aNHISi+77FyXLLy9JmE2JsmhYuudk3Ij2/mNTDZUKOGIeGoAQgAKxNgxNBC7DYmg0FSbFbEQ7W0RDRBdAGiAhQCAUBNgABsTYU4EJsEwlKzpPA+b5PKyx5P4b49v1RzZZ4zIeJyeNevwWJv8AQLHrafcd6kTfccpdjLpo2aI9rqa90StjGkpNkrcJ6lHLh0Tc36F7fcbdWrINNbMtS6ZnTtDXV1eo+T02vTQql2MO0qtOiD9URxw4N9olpvbJa9J62WNq0MWEfwEldKi+y0WHJIhnZruGKW2KjExeRmnYl8jQyMhKpttI53JyvNslJPsWR5+TLwp332eY1BtIilZbL1kydVdXcPI37nV5lRxk+7bFii15H1BY31NCu/QItN6LLxlr1I40JS9Qg8oVVE6jpBorF2iVaG2w1En0JJbWgnll277kCbUjVnTB+pH9nqTDWlG2LcR+DnW4VilHZclVW0QSpr2KsdBxXNzypuNjKviSyb6XF9iHh60shKPuavNYf8QpSMtuRVlsfRsbO+2S05MuShDehvl1lYZzUmL0v5F/y6xeiAVnuL+QnQy+4w+gmoFFRRYdLLiUA+AhFWMWP6GWF0CNxDSDoYdLJnKIKUQiLoYdBN1RDcQIekOkm3ETaAgiSL0I0SL0Ipr9RBWIABsAABGOQMoaCQoEACDYAOQJ6BDG9MpHrXH3faeMx7t7c603/YSxnr1Mfwdf53h+qL9a24mrac674+kre+6Eb7FP7Q62CzYN6l2JtrRbb5Rekhv2xxS2tkeTOLXVCSZTts+H10ZUuTfGW2nplZZfR2k+xWvluL7mVkWz36he2m88peqY77at76kcrLKtj27kcsufzZdH2adZLkIp/eIreSra+92OTlk2P8TE65y9ZMsxYy5dtPN5J3Sca38JFjVTtl9CDHolZLUUdDhYbqq20N6cvOTAusnXbKPsmQyy5IucjGMMuafv3KM64y9DcYvg15s/mEc6bfqQ2UPfYiUXFmkacciUo+pC75dfqMpe0JYtSCNSiTlDuPZDhv4SdlcbTPcAkIXTO6gubSKE7pqXqXr0UbYkblSRsbh6layySfqS1+hFd6sNxZ43PePapNmpyHOPIp6Ezmtipk00sO1tvuJ5jIkxSof5svmJ5r+Y1iaAc7GJ1saAVIpsd1MjRIgDqYdTF0BNLsm2HcUTZdGypsXqY3aDY0mzuphsZ1CdY0bTdI5DdipmWiMQViBQAgBCoGAFCAAEACAAHJCdI6PoEnoo7bwDZvCyqv6M0/7To8hdjj/AFr+2ZVe+zgmdlkfdMV1wZ81sr2V7RakNcNnJ6NMyyEktJ6KttVrXabNidW2M8hL1CWOftryNaUdlWeLkS/m5HVOmPqPhGK9hsmMrjXh5H/dS/sI/4PypelTO+jVCcfREWRTGuG9IbsLhHELicqT+6kT1cLdtdbOjjFSkSqBezncYp4HHQpiml3NC2rVXYlorJrY/AzFu1k04bxBW4XQml69jJ81o6XxFjuVDkvw9zlG9o74VwziyrU/UH0Mp9QvWbYXIpL0YklsrxsZIrAi/iy0Wk0zMqs79iaNzTLHLKLkhrI43p+o7rTKxoyxbRQuL8ilkL1DUR1sZekNhPUtDrO6I6RWYJC6ANFQ4aO2EpAAVLYCBoc1pDAmzhVIj2KDZ3UHUN0wUWAvUJ1D41Ni+UyptF1C9yVVD1UBXSbHxrZP5ehyiDaMAAw6gBA2AoDWxAp+wGoUqAAE0RQKhdBoB0QmuwRHP0DLd8DT6Obcf6VTO7yvunAeD3rxBT9Yy/wDI9Aye8SV1wUW+45dxsvUWJxeqBxIp7ROiOXqEqPvoTQ8OnYIfjyUZabIOQuUpRhF7G2QkvRkVNEp2dUgtPrhpEqiSuCS0LVHuRhPVHUUFq+ElS0iO77pBiclUrKZJr1OFyanTfOHyZ6HlRTgzj+XxXLIcoL2OmN045xhtCe5JNdMtPsxmztHGlQqG7DZUXcVJy7suTpjoy67Olk7ynrsw52pbF0+jI/O17kLtcl3GPbZRbV+/cZZJSRWWx/cCPTUh0n2HaGyWyNRExCToDyym0YqTZNGnZNGgJclXpfyHRiy2quwjr6WInZBKDaG+U/kW4pMlVewm2cq+/oTQo6iayrXfQkH0vuDZY4g/7MiVWpIZK5A8k8pRQySihk7iPqbCpOwoyJNBAt0ao7HxrJIxHqJWLky9CoAOb0hiCiAIAohQoqGipgOAQCLChsAAVMWTGoX17BGv4Sf/ALQ439f/AJHo1y3BnI+DuM8u/wC02R+LXwnXWv4WZrrioP1FiMk+7HRZyrvKlSGWQ13HxYs+6DStodFCS7MTr6Som6E0LGpRErti16izsUUQNmh9KK/VKc+3oXKlpEZPIbCVkNr7Cipc1pmFmVrzeo3LfQzMqG2GawOWworFlfGOmjAk9HWeIZ+XxKivWctHJWep3wefOEUhyIhVJxZ1c08e7LMKOpFavJUd7jstYWbFyataivYjFh6xvoOWP9C1GymX3Zpki6H+JFY3VNY6GTq0XpSqj2c47I7OhrakiG6oOInTslnrfZhH1C7R+WL5b+RZjFD1XsHZUSkh6k16lny1oR0p+wPaJWIJNNCyofsN8qSQNGKSTLEJrRTlGSewU5a0VVqyxFeVi3sb8TI3BkDncJ1tkbXcdEqlbBPuDGr1IqWJPWQ1otVxRWKlgiZRGRRLHQYsYewEFRzeoogogAAAVQCAUIBRNjXIaNng2R9QnVsaS1ImbfEcd1SjbdHa9kYDlppo6riM2F1MY7+JexnJ0w8ul4ySrkl6Iv3Wx01sycd7eyz3aMOn6RvbFj6keu4+KM11kTxZIviaS9yvH1LNEJSlGS7pP0EW3StdpZzxItSt1vpXyJXhRi1G2+uFj9ItlGm2C8f5Kk1t40Uv1KU/D+Vlc9l3ZinODlumSl2S9jp1jz/ZlWqseUMlUyaU36Fh4MnNw82DsS30b76KHK5Kr8S8PjQluzurP00aeXKqN+VZi1wlyNVPbfuvYdIXkyRYtcbq5WQsiowepN+xO46rc4zhOC9XF+hzvBUZN3g3PT3O6/qaS9W2WfDOFLifD19mbGVblBuUZv6C4xPsybFad0tR9PmVsyapyFRNrqlHqX1Kfh6yUfCkb8vIjTK2LUbJvWvkHLpS4XGzqciGRPEaU7YPe16Mz0a+zys5WLOnE896lH1evYpPHVmBdl9cVXX3Zc5Llnx8+K3qVGR8Fi+jXqJzNFOP4Y5KWO15VsHNL2RZhGbnXD+JsuNkqKIPaiupss1+CMy7HpseXjwlfFShCT7vts5l2Ss+KT2/Q9aps1Vw3/Y3fuuP8Yl/J/D6nSTTnldvPON8MZefyGVhdcKrcZbl1d9v5FXiuGu5Xlnx8JxrmurqlL0WjuOBhDH8a8vS7vMlOKkm33ZS8L8NnYni7JyL8eVdKc9Tfo9vsaZc9xfhfK5LLzKIXVV/ZJOM5S9BeU8K5XHYDzYX05FCepSrfodN4Rurlnc/a/jpcpSf1Xcj8WWRr8L0fwPXCPH3y3Z0r0KjC4zwll5eHHLyMirDol3jK192Qc3wGRxFEchZVeRjyelOuR1PiLEny3H8RfiVzvwoKPm11PvrsQ+IeH4jH8NWZNVN2NNP+LhZJ7b/AE2Q0yqfBWXZiU5Fudj1K2KklNv3KeB4cyc/lsjj6MmqXkLbsT+F/odzm2uvhuNceM+3/wAVHt076fhRkeDHvxPyTeMsX4P5JfhAxMzwvlcdRHN+0VZGMpJSlW96C3jpwirK/ig++zb8WWqvwvQ+IrhDj7pbs6fVNi8NXG7g6G3t9PcxndOnHjMvbnlFrs0SR9fQ178GLb0ifhOIeVnRlKP8VW9vfuZx5Nmfx9eWRRRO7IrpUWpTaS2dbDwnR9l1KcvO16+yZp53HUSh51VMVfDvBpe47LzZ4XG+bbHdij6Je50lcujz62vyrJ1y+9CTTI2lolulK22dkvWbbYzpK43e0Eqkxn2dFlxHdBSWqqo+grxk130XFX8wcEiLtlXYnfcZRK8qpwXddvma9lPUirOqdXp3XyZWpWexF6k2VV0dM4b6JfsyuiNp633Ldb7FKBcqfYJUyY9SIwQc6yhRAJp6NlANBphNgRseq5P2FWPJ+wNouoVbLMMR+6JFiF0m1LTG9LNGVUK18TWyhfbHeogMl2I3Ma5bGlVIpFnDypY1ynF+hSFT7iwl09B4vkYZMF0vv7mtGW0eaYebZjWKUJNfQ7HieXqyoKLmlP5HHLF6McpW0ltksYkVckyzA5V3hFDQTVsqnCmx1yfpJd9EvsS40V1Sm/SK2WJldTbE47hZYmZbl5F8r77PWUuzLOZj8hNL7LnWURftrY/kMqUb8HLg3HHvXTNPtp+xH4iyL6cXjljS1O2+MP12dNVy7Y2elLj+E+y5f2y++d+T/Tl7Fp8fZLk7M5ZE1OyHQ0n6I1OihZMcd3R85rfRvu0Q1X02ZV1Fc+qdMtSXyMXbW8KqYHG2YPGSxcfJnFt7U/dFW/gsvLXTnclbbU/WPps3bJVU0yuvsjXXH1k3oy/EOZOvD4+eFZ1effGKcfSSZZtm3GGchwsMzBx8LzZRx6fw/MbfxEFxVmDjzdVc18SXubLVfmKh2xV0ltQ33ZUdsZTsrTXVW9SXyJdtzrWTk8XZkQw1ZZKccT07epk+LuQcMRYVdsoqX3oJ9jr4vInxFzwXX9o6tQcvTf1Od8WYcOV5Hi8KmVX26a/jXH0S13OmMrhllPTlOGxsDI8xZ17q0vg0dN5GdPEjTxfNtwitKDa9CN+DsGdmTHH5BTnjwbshvun/AGGPicTc/D9/LQv6fJn0qKfqdHJPT4c5inJ+003fx+99al3ZLnWeLEvs11l8lJekfVk8ac7ja+Gy3mynHLsipQb9Ns6TPy74+N8DFhPVc6m2v7QPNqb83jndVCdlLsXTYvTZG83KWD9i86f2fq6ujfbZ6Dg8Zj8pyHKPMas8q5x2l3QmJwHCR5yuuE1OUV1+XL3/AKgrh8DmeR46LjiZU64v8KfYj5Dk83kpJ5mRO3Xom+yOx/8AVvj8/nORqhJQqpe5OL0oN+xQzPCmJXxmZnYedG+uheifuvVMbRjU+IeWophVVm2RhFaS+SK0OTzq8uzKhkzV9q1Oe+7OlxvCGK8LCycrOVKyUuzf4n6JdijyHhTJx+fp42ias86PVGTfovfYGJ9tyfsf2N3z+z9XV5e+2zqfCWVvAspk+8Jdv0G5/hCiOJfPjs2ORfjd7a+r0Mvwvf0ci699rFoznNxvjvl18lsu8dmxwqvLlH1e9opJd0P6d+x5d6r3de0bFfM0SepNx+WzO5fmuumyimrqUlrqZX8rfsEsdNd0b+xi8MYDi/dBo1rsPt2Rn20SrfdHTHN5c+D+IdBoUT3Ou3ks0dJ6k18hrHS+8/1G6CCMlv4l2G5FWm0nvttEsYb9eyEufVJ69NaRV2zrKt1WQf8AR6l+qM3p0b0ofxVkn7Q0ZFsUvRBuVHAs1leCLFRFqf2FSBDisVnKlsfHHZcjUkSKKC3LSrHG+hJHGXyLSQjaj6hO1qKNCQ9VxRBfmRrT0zPsz5t9mFktall1VfuijdyKXaBnWWyk+7I/UNTFLbfKyW2yLewANgAJKqbLpqNcXJkDEiWjGuvmo1VuTf0Oj4rw6oxV2c1GHybLeRymBxy6cWEZSXukUZuL4Zs0p5Vsak/ZlPlcWvjMmKx7/MTW+3sJncrk5lrlOxpeyRQnuXdvbGljd4zxLbj6heuuJ0+H4gw8iP31F/JnnGhYylF9mzFwldJyWPVoZcJrcZJr9SPleSycXjH/AAfX1ZEnpP1SPNqc/Ipe4WSX9ZoY/iPLq11S6kY6adLyTKarssyzPs8N3VZUI5GQ9ODh26WQZTzcvjeJ1Q1bRbGc238jKxfF6WvOg9fRGvi+KePtSTn0v6ol7ROuK9mZePi8vXlvjbrchx6XbB7SRT4ON8+X5HLtonTC6fVFS+RBleK8WnL8uOpw+aJL/F2BCHwScn8kh5pMZ/Wtyksezj7acrHnfU+/RB92c/n58svH47HwuPux1i3KSU/RJFPJ8Y935MP7TIyfEede3qzoX5TWMq5TH27LleZ4/js6OfZhSszejSkpdkchPxHkfbszKgumWRLfT6qJk3ZFt8uq2cpP6kRvr/XG3V8Ohq8USr8OZPHyrm77ZNq1S1rZS8L5F1PP4+RFqU0+/W/VPsZTH1SdclODakvdFjL0W7NxcLMzpYvE3u7KhLrsT2nJmRwl12DxWRg8nxtt2JdJy+B90YWPzmdjv4bpNfJmli+LMmMl5yUl+g0G87z6yr8GvGwp0Y2FKMoxn6vRJleLI3eJ8XlfsslCitwcOru9p+/9ZrU8vxGdD+OjCMvqgs43hclfA4Jv5MIx+L8RYtHIZ2Xk03wlkWdcXTZ3j9PqPzPF9dviDDz6sSSrx4uLUn8U9/Mbm+FrFJyw5KcP1MfJ4fNx38dMv6kBr8Z4rhi8xnX34zljZrfXBS7onyPE3E1cJm8fx2BbUr12bltNs5OdNkX3hJf1AoSa10v+wDo8vxNTlY3FUeS19jlGU9v10WszxfVZ4ixuQppkoU1uEot+uzjmnF6a0O9uwHZ2eJ+Kx6st8bgThkZafXOT7dyrwkeNx8eMrrI/aN7j9DlhU2mmKsenQipJND1Ag4mxZHHUWp76orZdUTyZe30cb4MhHRKopiaFXYypk61oz8vHTTZqS7lW6K0IxXPWR1IYvUvZdSi9opaPTx14OfDV8BghUKkdXmN2/R+gqjKXoSdhsnJrS9AiLKacPLg+y9X8zPtpbZpOC0N8tBZkzFQySNTRddaQ1xSK1ckCiO0PaECN2/hZRp60tGW8Oab+E7+1Rlja0ZtWJU5tOIdOrj51uHZ+pmcjOVfodtyPEpvqgjk+Zx+jqi13iYt03jxOfnY5MZ7itaYho1oBockOjFv2AZ0iqDfotmpg8TkZckowevmdHieH8fFh5mS129e4Vz3G8FkZrT6XGHzZ0Ucfj+Bx+u3UrdehDyXP1Y0PJw9du2zlsvLty7XO2TbAvcpzd+dJqLcK/ZIy29+vqIS4+PZkWquuLk2ERpOT0ltmtxnAZWc1KUXCHzZ0HEcBTiVq7LUer17kXNeIIY8XThNJrttEEHJcbxnG4LrlJSufucpZ09T6fQlvyLb7HO2bk38yEqkFE9BQAGgAIWK3GXzGd0OUtCrTfcgWFe1tvSE0kE220vZCFUoAJsBBUAuiAFEAocn8hysnH0k/7RgmwjRxeZzMb7lra+TNWnxZZpK+mMzmRQrtYc7xF0U7aEpe/YJcxwlP3aIt/RHEiPuBucr9i5ScZYEOm7fePzKK4POT/kXrZUqslTZGcHqSNuPia9U9LXxfMKzMzisrDUXdW0mVfKs7Polr9DbyfEMsvH8u2CbXuafGcnx32OuORCPVH6Eou+DrHPivLkmnXL3Og0ZuBl4Ntrjh6Ta20jTTPNyTy9fFdw3pE6R4Mw6omyKxJolkiOXoEZ2RX1GdbDpkbFqRRyIbRvG6cOTHcUtBoX0EckemV83KWUAI5L5jXZH5mkOYEbtS9yKV6XuDSaRHJkEslfMilkr5hZjVlyRG5oqTyCN3/UjXV0Ef/SJqHS+L3/8Acf6Rv/8AoKT2uL//AGP9JxIB3dtP/wBITnHT4xf/AJ/9JiZ3iBZkpN4vR1f7zf8AgYgEslamVh8rOp71oOv6DAKymjco+sN/1lvH5Cip7liOf/M1/gZwAdTX4xVNfRTx0YfXzf8ASZ2d4hys3akulP2UjHACV3Nvev3E838v7kYATwvhGSc63JfJS0bWB4kx8CGquMTl/Sd3+k54ANrkfEmXnP08uPyUjKle5PbW3+pEAEnm/T9w8z6EYAP8z6B5n0GABJ5n0E8z6DAAf5n0BWa9hgASeZ9A8z6EYASeZ9A8z6EYASeZ9A836fuRgBJ5v5f3Dzfy/uRgBJ5v5f3Dzfp+5GAEnm/T9w836fuRgBJ5v0/cPN+n7kYAP8z6B5n0GAA/r+geZ9P3GABpcTy0uMzFeqvMWtOPVrf7G+vHfb/4b/1/9JxwGbjL7bxzyx9OyXjzX+zf+v8A6Q/9fP8A6b/1/wDScaBPrxX7c/67B+Ot/wCzv+v/AKRr8b7/ANnf9b/SciA+vE+3P+uql4z6v9n/APW/0kNnixTX/uOv+b/kc2A6Yp9mVbc/EPU+2Lr/AJn+RE+cb/mP7/8AkZIGpNOdkvtqPmZf9z/f/wAhHy8n/Nf3v8jMAqdY0Hykn/N/3hj5Fv8Am/7xSAL1i285v8H7jXlt/h/crADUWPtT/o/uJ9of9H9yAAoAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAD/2Q==\n", + "text/html": [ + "\n", + " \n", + " " + ], + "text/plain": [ + "" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } ], - "text/plain": [ - "" + "source": [ + "from IPython.display import YouTubeVideo\n", + "YouTubeVideo('1ZwYlaqvCSw', width=800, height=480, rel=0)" ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "from IPython.display import YouTubeVideo\n", - "YouTubeVideo('1ZwYlaqvCSw', width=800, height=480, rel=0)" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": { - "ExecuteTime": { - "end_time": "2018-04-16T22:45:30.374714Z", - "start_time": "2018-04-16T22:45:29.257523Z" }, - "slideshow": { - "slide_type": "slide" - } - }, - "outputs": [ { - "data": { - "image/jpeg": 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\n", + "text/html": [ + "\n", + " \n", + " " + ], + "text/plain": [ + "" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } ], - "text/plain": [ - "" + "source": [ + "from IPython.display import YouTubeVideo\n", + "YouTubeVideo('tp_rP9C0ysY', width=800, height=480, rel=0)" ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "from IPython.display import YouTubeVideo\n", - "YouTubeVideo('tp_rP9C0ysY', width=800, height=480, rel=0)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "nbpresent": { - "id": "65e7f85e-289f-4ed1-b23b-3919db13bfd4" }, - "slideshow": { - "slide_type": "slide" - }, - "urth": { - "dashboard": { - "layout": { - "col": 0, - "height": 8, - "row": 110, - "width": 12 - } - } - } - }, - "source": [ - "## [BMClab](https://bmclab.pesquisa.ufabc.edu.br/) services\n", - "\n", - "The [BMClab](https://bmclab.pesquisa.ufabc.edu.br/) (will) offer services for:\n", - "\n", - "- Clinical gait analysis \n", - "- Running biomechanics assessment \n", - "- Wheelchair propulsion assessment \n", - "- General motion capture \n", - "- ..." - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": { - "ExecuteTime": { - "end_time": "2018-04-16T22:46:28.188960Z", - "start_time": "2018-04-16T22:46:27.232756Z" - }, - "nbpresent": { - "id": "96e9ec4a-de32-4db9-a847-a9656124e87f" - }, - "slideshow": { - "slide_type": "slide" + { + "cell_type": "markdown", + "metadata": { + "nbpresent": { + "id": "65e7f85e-289f-4ed1-b23b-3919db13bfd4" + }, + "urth": { + "dashboard": { + "layout": { + "col": 0, + "height": 8, + "row": 110, + "width": 12 + } + } + }, + "id": "T5a04Zp0jkBJ" + }, + "source": [ + "## [BMClab](https://bmclab.pesquisa.ufabc.edu.br/) services\n", + "\n", + "The [BMClab](https://bmclab.pesquisa.ufabc.edu.br/) (will) offer services for:\n", + "\n", + "- Clinical gait analysis \n", + "- Running biomechanics assessment \n", + "- Wheelchair propulsion assessment \n", + "- General motion capture \n", + "- ..." + ] }, - "urth": { - "dashboard": { - "layout": { - "col": 0, - "height": 22, - "row": 118, - "width": 9 - } - } - } - }, - "outputs": [ { - "data": { - "image/jpeg": 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+ "text/html": [ + "\n", + " \n", + " " + ], + "text/plain": [ + "" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } ], - "text/plain": [ - "" + "source": [ + "from IPython.display import YouTubeVideo\n", + "YouTubeVideo('5ZKMVWkOyZA', width=800, height=480, rel=0)" ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "from IPython.display import YouTubeVideo\n", - "YouTubeVideo('5ZKMVWkOyZA', width=800, height=480, rel=0)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "nbpresent": { - "id": "d2228b4a-2c23-451b-b128-e353bd9d7c64" }, - "slideshow": { - "slide_type": "slide" - }, - "urth": { - "dashboard": { - "layout": { - "col": 0, - "height": 7, - "row": 140, - "width": 12 - } - } - } - }, - "source": [ - "## Open data science\n", - "\n", - "> Open science data is a type of open data focused on publishing observations and results of scientific activities available for anyone to analyze and reuse. [[wikipedia.org](https://en.wikipedia.org/wiki/Open_science_data)]\n", - "\n", - "**The [BMClab](https://bmclab.pesquisa.ufabc.edu.br/) is committed to open science data.** \n", - "**[Access our data here](https://bmclab.pesquisa.ufabc.edu.br/datasets/).**" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "nbpresent": { - "id": "adb04f3a-f8af-43fe-87e6-3f0c76eb4eb4" - }, - "slideshow": { - "slide_type": "slide" + { + "cell_type": "markdown", + "metadata": { + "nbpresent": { + "id": "d2228b4a-2c23-451b-b128-e353bd9d7c64" + }, + "urth": { + "dashboard": { + "layout": { + "col": 0, + "height": 7, + "row": 140, + "width": 12 + } + } + }, + "id": "NQCyFqKYjkBJ" + }, + "source": [ + "## Open data science\n", + "\n", + "> Open science data is a type of open data focused on publishing observations and results of scientific activities available for anyone to analyze and reuse. [[wikipedia.org](https://en.wikipedia.org/wiki/Open_science_data)]\n", + "\n", + "**The [BMClab](https://bmclab.pesquisa.ufabc.edu.br/) is committed to open science data.** \n", + "**[Access our data here](https://bmclab.pesquisa.ufabc.edu.br/datasets/).**" + ] }, - "urth": { - "dashboard": { - "layout": { - "col": 0, - "height": 7, - "row": 147, - "width": 12 - } - } - } - }, - "source": [ - "### Open education\n", - "\n", - "> Open education is a collective term to describe institutional practices and programmatic initiatives that broaden access to the learning and training traditionally offered through formal education systems. [[wikipedia.org](https://en.wikipedia.org/wiki/Open_education)]\n", - "\n", - "**The [BMClab](https://bmclab.pesquisa.ufabc.edu.br/) is committed to open education.** \n", - "**[Access our GitHub repository here](https://github.com/demotu/BMC).**" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "nbpresent": { - "id": "54c30a3e-be3b-4935-a561-48ded4c2fd36" + { + "cell_type": "markdown", + "metadata": { + "nbpresent": { + "id": "adb04f3a-f8af-43fe-87e6-3f0c76eb4eb4" + }, + "urth": { + "dashboard": { + "layout": { + "col": 0, + "height": 7, + "row": 147, + "width": 12 + } + } + }, + "id": "o-MXc9j0jkBJ" + }, + "source": [ + "### Open education\n", + "\n", + "> Open education is a collective term to describe institutional practices and programmatic initiatives that broaden access to the learning and training traditionally offered through formal education systems. [[wikipedia.org](https://en.wikipedia.org/wiki/Open_education)]\n", + "\n", + "**The [BMClab](https://bmclab.pesquisa.ufabc.edu.br/) is committed to open education.** \n", + "**[Access our GitHub repository here](https://github.com/demotu/BMC).**" + ] }, - "slideshow": { - "slide_type": "slide" + { + "cell_type": "markdown", + "metadata": { + "nbpresent": { + "id": "54c30a3e-be3b-4935-a561-48ded4c2fd36" + }, + "urth": { + "dashboard": { + "layout": { + "col": 0, + "height": 8, + "row": 154, + "width": 12 + } + } + }, + "id": "WsymxjcojkBJ" + }, + "source": [ + "## Literate programming and literate computing\n", + "\n", + "> Literate programming: Instead of imagining that our main task is to instruct a computer what to do, let us concentrate rather on explaining to human beings what we want a computer to do. [[Donald Knuth (1984)](http://www.literateprogramming.com/knuthweb.pdf)] \n", + "\n", + "\n", + "> Literate computing: A literate computing environment is one that allows users not only to execute commands **interactively** but also to store in a literate document format the results of these commands along with figures and free-form text that can include formatted mathematical expressions. [[Millman KJ and Perez F (2014)](https://osf.io/h9gsd/?action=download&version=1)]" + ] }, - "urth": { - "dashboard": { - "layout": { - "col": 0, - "height": 8, - "row": 154, - "width": 12 - } - } - } - }, - "source": [ - "## Literate programming and literate computing\n", - "\n", - "> Literate programming: Instead of imagining that our main task is to instruct a computer what to do, let us concentrate rather on explaining to human beings what we want a computer to do. [[Donald Knuth (1984)](http://www.literateprogramming.com/knuthweb.pdf)] \n", - "\n", - "\n", - "> Literate computing: A literate computing environment is one that allows users not only to execute commands **interactively** but also to store in a literate document format the results of these commands along with figures and free-form text that can include formatted mathematical expressions. [[Millman KJ and Perez F (2014)](https://osf.io/h9gsd/?action=download&version=1)]" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "nbpresent": { - "id": "350013a7-5873-4ceb-b956-cb1313b94b24" + { + "cell_type": "markdown", + "metadata": { + "nbpresent": { + "id": "350013a7-5873-4ceb-b956-cb1313b94b24" + }, + "urth": { + "dashboard": { + "layout": { + "col": 0, + "height": 6, + "row": 162, + "width": 12 + } + } + }, + "id": "qlQs5A2TjkBJ" + }, + "source": [ + "### Literate computing with [Jupyter Notebook](https://jupyter.org/)\n", + "\n", + "> The Jupyter Notebook is a web application that allows you to create and share documents that contain live code, equations, visualizations and explanatory text. [[jupyter.org](https://jupyter.org/)]\n", + "\n", + "See examples in [A gallery of interesting Jupyter Notebooks](https://github.com/jupyter/jupyter/wiki)" + ] }, - "slideshow": { - "slide_type": "slide" + { + "cell_type": "markdown", + "metadata": { + "nbpresent": { + "id": "047118f9-96d6-4ad3-8a6c-7eb2940d5daf" + }, + "urth": { + "dashboard": { + "layout": { + "col": 0, + "height": 7, + "row": 175, + "width": 12 + } + } + }, + "id": "CIg1MutZjkBJ" + }, + "source": [ + "## Questions?\n", + "\n", + "> [https://bmclab.pesquisa.ufabc.edu.br/) \n", + "> E-mail: bmc.ufabc@gmail.com \n", + "> Tel.: +55 11 2320-6435 \n", + "> [Location Map](https://www.google.com.br/maps/place/Federal+University+of+ABC+-+UFABC/@-23.6803572,-46.5647898,14z/data=!4m2!3m1!1s0x0:0xf1a53d9732f7a8c6)" + ] }, - "urth": { - "dashboard": { - "layout": { - "col": 0, - "height": 6, - "row": 162, - "width": 12 - } - } + { + "cell_type": "markdown", + "metadata": { + "nbpresent": { + "id": "5c704362-c2b8-425a-b153-a66533454d1f" + }, + "urth": { + "dashboard": { + "layout": { + "col": 0, + "height": 7, + "row": 182, + "width": 12 + } + } + }, + "id": "NEcXgKC4jkBK" + }, + "source": [ + "## About these slides\n", + "\n", + "**This document (the webpage version or the slides version) is a *notebook* written using the [Jupyter Notebook](https://jupyter.org/).**\n", + "\n", + "> The Jupyter Notebook is a web application that allows you to create and share documents that contain live code, equations, visualizations and explanatory text. [[jupyter.org](https://jupyter.org/)]" + ] } - }, - "source": [ - "### Literate computing with [Jupyter Notebook](http://jupyter.org/)\n", - "\n", - "> The Jupyter Notebook is a web application that allows you to create and share documents that contain live code, equations, visualizations and explanatory text. [[jupyter.org](http://jupyter.org/)]\n", - "\n", - "See examples in [A gallery of interesting IPython Notebooks](https://github.com/jupyter/jupyter/wiki)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "nbpresent": { - "id": "047118f9-96d6-4ad3-8a6c-7eb2940d5daf" - }, - "slideshow": { - "slide_type": "slide" + ], + "metadata": { + "anaconda-cloud": {}, + "celltoolbar": "Slideshow", + "hide_input": false, + "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": "3.9.13" + }, + "toc": { + "base_numbering": 1, + "nav_menu": {}, + "number_sections": true, + "sideBar": true, + "skip_h1_title": true, + "title_cell": "Contents", + "title_sidebar": "Contents", + "toc_cell": true, + "toc_position": {}, + "toc_section_display": true, + "toc_window_display": false }, "urth": { - "dashboard": { - "layout": { - "col": 0, - "height": 7, - "row": 175, - "width": 12 + "dashboard": { + "cellMargin": 10, + "defaultCellHeight": 20, + "layout": "grid", + "maxColumns": 12 } - } - } - }, - "source": [ - "## Questions?\n", - "\n", - "> [https://bmclab.pesquisa.ufabc.edu.br/) \n", - "> E-mail: bmc.ufabc@gmail.com \n", - "> Tel.: +55 11 2320-6435 \n", - "> [Location Map](https://www.google.com.br/maps/place/Federal+University+of+ABC+-+UFABC/@-23.6803572,-46.5647898,14z/data=!4m2!3m1!1s0x0:0xf1a53d9732f7a8c6)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "nbpresent": { - "id": "5c704362-c2b8-425a-b153-a66533454d1f" }, - "slideshow": { - "slide_type": "slide" + "varInspector": { + "cols": { + "lenName": 16, + "lenType": 16, + "lenVar": 40 + }, + "kernels_config": { + "python": { + "delete_cmd_postfix": "", + "delete_cmd_prefix": "del ", + "library": "var_list.py", + "varRefreshCmd": "print(var_dic_list())" + }, + "r": { + "delete_cmd_postfix": ") ", + "delete_cmd_prefix": "rm(", + "library": "var_list.r", + "varRefreshCmd": "cat(var_dic_list()) " + } + }, + "types_to_exclude": [ + "module", + "function", + "builtin_function_or_method", + "instance", + "_Feature" + ], + "window_display": false }, - "urth": { - "dashboard": { - "layout": { - "col": 0, - "height": 7, - "row": 182, - "width": 12 - } - } + "colab": { + "provenance": [] } - }, - "source": [ - "## About these slides\n", - "\n", - "**This document (the webpage version or the slides version) is a *notebook* written using the [Jupyter Notebook](http://jupyter.org/).**\n", - "\n", - "> The Jupyter Notebook is a web application that allows you to create and share documents that contain live code, equations, visualizations and explanatory text. [[jupyter.org](http://jupyter.org/)]" - ] - } - ], - "metadata": { - "anaconda-cloud": {}, - "celltoolbar": "Slideshow", - "hide_input": false, - "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": "3.9.13" }, - "toc": { - "base_numbering": 1, - "nav_menu": {}, - "number_sections": true, - "sideBar": true, - "skip_h1_title": true, - "title_cell": "Contents", - "title_sidebar": "Contents", - "toc_cell": true, - "toc_position": {}, - "toc_section_display": true, - "toc_window_display": false - }, - "urth": { - "dashboard": { - "cellMargin": 10, - "defaultCellHeight": 20, - "layout": "grid", - "maxColumns": 12 - } - }, - "varInspector": { - "cols": { - "lenName": 16, - "lenType": 16, - "lenVar": 40 - }, - "kernels_config": { - "python": { - "delete_cmd_postfix": "", - "delete_cmd_prefix": "del ", - "library": "var_list.py", - "varRefreshCmd": "print(var_dic_list())" - }, - "r": { - "delete_cmd_postfix": ") ", - "delete_cmd_prefix": "rm(", - "library": "var_list.r", - "varRefreshCmd": "cat(var_dic_list()) " - } - }, - "types_to_exclude": [ - "module", - "function", - "builtin_function_or_method", - "instance", - "_Feature" - ], - "window_display": false - } - }, - "nbformat": 4, - "nbformat_minor": 1 -} + "nbformat": 4, + "nbformat_minor": 0 +} \ No newline at end of file