{
"cells": [
{
"cell_type": "markdown",
"id": "aerial-providence",
"metadata": {},
"source": [
"# Realtime Classification\n",
"\n",
"Let say you want to cut your realtime recording audio by using VAD after that classify using classification models, you can do that with Malaya-Speech!"
]
},
{
"cell_type": "markdown",
"id": "acknowledged-relative",
"metadata": {},
"source": [
"
\n",
"\n",
"This tutorial is available as an IPython notebook at [malaya-speech/example/realtime-classification](https://github.com/huseinzol05/malaya-speech/tree/master/example/realtime-classification).\n",
" \n",
"
\n",
"\n",
"This is an application of malaya-speech Pipeline, read more about malaya-speech Pipeline at [malaya-speech/example/pipeline](https://github.com/huseinzol05/malaya-speech/tree/master/example/pipeline).\n",
" \n",
"
"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "unlikely-patrick",
"metadata": {},
"outputs": [],
"source": [
"import malaya_speech\n",
"from malaya_speech import Pipeline"
]
},
{
"cell_type": "markdown",
"id": "adjustable-saver",
"metadata": {},
"source": [
"### Load VAD model\n",
"\n",
"Fastest and common model people use, is webrtc. Read more about VAD at https://malaya-speech.readthedocs.io/en/latest/load-vad.html"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "starting-roller",
"metadata": {},
"outputs": [],
"source": [
"webrtc = malaya_speech.vad.webrtc()"
]
},
{
"cell_type": "markdown",
"id": "massive-abortion",
"metadata": {},
"source": [
"### Recording interface\n",
"\n",
"So, to start recording audio including realtime VAD and Classification, we need to use `malaya_speech.streaming.record`. We use `pyaudio` library as the backend.\n",
"\n",
"```python\n",
"def record(\n",
" vad,\n",
" asr_model = None,\n",
" classification_model = None,\n",
" device = None,\n",
" input_rate: int = 16000,\n",
" sample_rate: int = 16000,\n",
" blocks_per_second: int = 50,\n",
" padding_ms: int = 300,\n",
" ratio: float = 0.75,\n",
" min_length: float = 0.1,\n",
" filename: str = None,\n",
" spinner: bool = False,\n",
"):\n",
" \"\"\"\n",
" Record an audio using pyaudio library. This record interface required a VAD model.\n",
"\n",
" Parameters\n",
" ----------\n",
" vad: object\n",
" vad model / pipeline.\n",
" asr_model: object\n",
" ASR model / pipeline, will transcribe each subsamples realtime.\n",
" classification_model: object\n",
" classification pipeline, will classify each subsamples realtime.\n",
" device: None\n",
" `device` parameter for pyaudio, check available devices from `sounddevice.query_devices()`.\n",
" input_rate: int, optional (default = 16000)\n",
" sample rate from input device, this will auto resampling.\n",
" sample_rate: int, optional (default = 16000)\n",
" output sample rate.\n",
" blocks_per_second: int, optional (default = 50)\n",
" size of frame returned from pyaudio, frame size = sample rate / (blocks_per_second / 2).\n",
" 50 is good for WebRTC, 30 or less is good for Malaya Speech VAD.\n",
" padding_ms: int, optional (default = 300)\n",
" size of queue to store frames, size = padding_ms // (1000 * blocks_per_second // sample_rate)\n",
" ratio: float, optional (default = 0.75)\n",
" if 75% of the queue is positive, assumed it is a voice activity.\n",
" min_length: float, optional (default=0.1)\n",
" minimum length (s) to accept a subsample.\n",
" filename: str, optional (default=None)\n",
" if None, will auto generate name based on timestamp.\n",
" spinner: bool, optional (default=False)\n",
" if True, will use spinner object from halo library.\n",
"\n",
"\n",
" Returns\n",
" -------\n",
" result : [filename, samples]\n",
" \"\"\"\n",
"```"
]
},
{
"cell_type": "markdown",
"id": "legal-likelihood",
"metadata": {},
"source": [
"**pyaudio will returned int16 bytes, so we need to change to numpy array, normalize it to -1 and +1 floating point**."
]
},
{
"cell_type": "markdown",
"id": "atlantic-automation",
"metadata": {},
"source": [
"### Check available devices"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "received-finland",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"> 0 MacBook Pro Microphone, Core Audio (1 in, 0 out)\n",
"< 1 MacBook Pro Speakers, Core Audio (0 in, 2 out)\n",
" 2 JustStream Audio Driver, Core Audio (2 in, 2 out)"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import sounddevice\n",
"\n",
"sounddevice.query_devices()"
]
},
{
"cell_type": "markdown",
"id": "beneficial-russian",
"metadata": {},
"source": [
"By default it will use `0` index."
]
},
{
"cell_type": "markdown",
"id": "efficient-syria",
"metadata": {},
"source": [
"### Load Classification models\n",
"\n",
"In this example, I am going to use 3 different modules, gender detection, language detection and age detection."
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "appropriate-springfield",
"metadata": {},
"outputs": [],
"source": [
"gender_model = malaya_speech.gender.deep_model(model = 'vggvox-v2')\n",
"language_detection_model = malaya_speech.language_detection.deep_model(model = 'vggvox-v2')\n",
"age_model = malaya_speech.age_detection.deep_model(model = 'vggvox-v2')"
]
},
{
"cell_type": "markdown",
"id": "declared-intelligence",
"metadata": {},
"source": [
"### Classification Pipeline\n",
"\n",
"Because pyaudio will returned int16 bytes, so we need to change to numpy array then normalize to float, feel free to add speech enhancement or any function, but in this example, I just keep it simple. **And needs to end with `classification` map or else `malaya_speech.streaming.record` will throw an error**."
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "nonprofit-boundary",
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
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KXUhDQwMVaTk5OdSLR48e1dTUUO+y2WxLS0tLS0szMzMOh2NqasrhcDgcDpvNNjIyokbM19fXpyaiaW5ubmlpIYRIJJKGhgaxWCwQCIRCIfXf2traysrKiooKqVRKNd6rVy97e3unfzg6Og4aNAgzlQJAxyFQoatrbm4uKSkpLy8vLi6uqKh48uSJQCCora1VBqRUKhUKhXK5nBDS2NgoFosJIXp6eoaGhoQQJpNpYmLCZrOVAczhcMzMzCwsLKysrKytrfv27duvXz99fX2ajxMAujkEKmiaoKAgXV3d06dP010IAGgXDOwAAACgAghUAAAAFUCgAgAAqAACFQAAQAUQqAAAACqAQAUAAFABBCoAAIAKIFABAABUAIEKAACgAghUAAAAFUCgAgAAqAACFQAAQAUQqAAAACqAQAUAAFABBCoAAIAKIFABAABUAIEKAACgAghUAAAAFUCgAgAAqAACFQAAQAUQqAAAACqAQAUAAFABBCoAAIAKIFABAABUAIEKAACgAghUAAAAFUCgAgAAqAACFQAAQAUQqAAAACqAQAUAAFABBCoAAIAKIFABAABUAIEKAACgAiy6CwB4Xbdu3bp//75ysaCggMViHT16VLlmyJAhI0eOpKM0ANAiCFTo9p48ebJixQomk6mjo0MIUSgUhJDVq1cTQuRyuUwmi4mJoblEANACDOqvD0D3JRaLe/fuXV9f3+a7HA6Hz+ezWPjuCACdC9dQodvT1dWdM2cOm81+9i02mz1//nykKQCoAQIVNEFISIhEInl2vUQimTdvnvrrAQAthFO+oAnkcnmfPn34fP5T662srEpLSxkMBi1VAYBWQQ8VNIGOjs78+fOfOuvLZrMXLVqENAUA9UCggoaYN2/eU2d9cb4XANQJp3xBcwwYMKCwsFC5aG9vn5eXR2M9AKBV0EMFzbFo0SLlWV82m71kyRJ66wEArYIeKmiO7OxsFxcX5WJOTo6joyON9QCAVkEPFTSHs7Ozm5sbg8FgMBheXl5IUwBQJwQqaJRFixaxWCwmk7lw4UK6awEA7YJTvqBRiouLbW1tCSElJSV9+/aluxwA0CIIVKBZfX29QCAQCoWCf1Cv6+vrm5qaRCJRXV2dVCoVCARSqbS+vr6lpaW5uZkQ0tjYKBaLWzclFArlcrlyUUdHx9TUtPUGurq6PXr0IIQYGhrq6ekZGxuzWCwzMzMmk2liYqKnp2doaGhiYmJqasr5h/K1kZGRWj4PAOiuEKjQiSQSSUVFRVlZGZ/Pf/LkSXl5+ZMnT/h8PrWGz+fX1NTIZLLWP6Knp0fFmLGxcY8ePXR1dU1MTFgsFofDYbFYxsbGVOxRW1IvlKjtY2Nj2Wz2xIkTxWJxY2Nj6w2UGUy9qKurk8lktbW1Mpmsrq6O2p4KeIFA8FRas1isnj17mpubW1hYWFlZPfWib9++ffr0waDBANoMgQoqUFNTU1hYWFxcXFhYWFRUVFxcTL2uqKhQ5qWRkVGfPn0sLS3Nzc2trKwsLCzMzc179erVuhfI4XAMDAxes5iqqiomk2lmZvaa7TQ1NT3Vda6pqXny5An1zYDP51dWVlZUVCgzm8lkWllZ2dra9u/f38bGxsbGxtbW1sbGZsCAARwO5zWLAYCuD4EKL6e5uTknJyc3Nzc3NzcnJ+fhw4e5ublVVVXUuxYWFlSW9O/fn8oVa2trKysrS0vLp3qTGqOpqamioqKioqL4H9R3i+LiYuXYwubm5k5OToMGDXJ0dHR0dHRycnJ0dNTX16e3cgBQLQQqtEcmk+Xm5mZmZt67dy8zM/P+/ftFRUUKhYLJZNra2lLZQBkwYED//v0REq01NzcXFhY+fvw4JyeH+haSk5NTVFQkl8t1dHT69+/v+Y/Bgwfb29szmUy6SwaAV4dAhf8hlUozMzNv3bqVkZFx7949Lpfb3NzMYrEGDRpE/el3dnZ2cnKyt7fX09Oju9huSSQSUf377Oxs6mtKTk6OTCYzNDR0c3MbMmSIl5eXj4+Pu7s78hWge0GgAqmsrExJSbl161ZKSsp///vfxsZGU1PT4cOHDx482MPDw9PT083NDfHZeVpaWrhcLhWumZmZ//3vf+vr642MjEaMGOHj4zNq1KhRo0aZm5vTXSYAvAACVUvV1tZev349Li4uLi4uJydHR0fHxcVl1KhR1F9wFxcXHR0M+kEPmUzG4/Fu3bp169at1NTU7OxshULh4uIyadKkyZMnT5gw4alngQCgi0CgahGZTHbz5s0///wzLi4uPT1doVB4eXlRf6NHjRqFP9NdU21tbUpKCvXt5+7duzo6OiNGjJg8efKUKVN8fHxwWhig60Cgaj6ZTHbr1q1z586dPXu2oqLCzs5u8uTJkydP9vPz69WrF93VwUuoqqpKSEiIi4v7888/CwoKevXqNW3atDlz5rz55pu6urp0Vweg7RCoGksul1+7du3MmTOXLl2qra0dPnx4UFBQUFAQhozXDFlZWdHR0efPn8/IyOjVq9eMGTPmzZs3adIknKsHoAsCVQOVlpaeOHHi2LFjxcXFPj4+QUFBb7/99oABA+iuCzpFfn5+VFRUdHR0WlqanZ3dsmXLlixZ0qdPH7rrAtA6CFSNEhcXt3///j/++MPMzGzx4sXLly8fNGgQ3UWBmvB4vKNHj546daq+vj4gIOCjjz7y9fWluygALYKzQxoiPj5+3Lhxb7zxRn19fWRkZElJyY4dO5CmWsXV1XXPnj3U+YknT55MmDDBz8/v5s2bdNcFoC0QqN1eUlKSr6/vpEmTDAwMkpOT4+Pjg4OD8dio1tLX11+wYMHNmzdv3LihUCjGjx8/efLk1NRUuusC0HwI1G6svr5+1apV48ePZ7PZSUlJsbGxPj4+dBcFXcX48eMTEhISEhIkEsno0aM//vjjpqYmuosC0GS4htpdxcbGhoaG1tXVffvtt6GhoXSXA13auXPn3n//fRMTk2PHjvn5+dFdDoBmQg+1W9q7d+/UqVM9PDwePHiANFWhhoaGS5cubdiwge5CVGzOnDlcLnfIkCGTJ08OCwujuxwAzYQeavezevXqI0eO7N+/f+XKlXTXommioqLWr18vl8sLCwvprqVT7Nq1a/369Z9++ul3331Hdy0AmgY91G5my5YtR44cOXv2rFalaUREhHp2NHv27JEjR7JYLPXsTv0++eSTiIiInTt37tixg+5aADQNArU7uXHjxldffbV3795Zs2bRXYv6xMfHb9q0SW2709HR0ezBhubPn799+/ZNmzalpaXRXQuARmHigkp3oVAoZs+ePXTo0N27d6t5183NzdHR0XZ2dqWlpb/88ktpaamjo6OOjk5lZeXp06fv3r3r4ODQ+kGdnJycP/7449SpU42NjS4uLtTKkpKSyMjI4cOH37hx48iRI9nZ2R4eHmw2mxBSX1+/Z8+efv36mZmZPbXrhISEwMBAiUTSs2fP8vJy6sna+vr6CxcuREVFPXr0yNzcvCPD+hcXF//0008jR47kcrnh4eGFhYUeHh4MBoN6t6am5tSpU9HR0UKhkMvlVlRUfPjhh+0cS21t7Y8//jhixIgrV66cP39+1KhRQqHwqTU6OjrP/uxff/2VmJh49+7drKwsJycnFouVlpb2559/FhYWOjs7v86/0Uvx8fG5fv36lStXli5dqradAmg+BXQTVH/i9u3bat7v9evXqeF/d+7cGRoa+tlnnxkaGgYFBYWHh8+fPz84OJjBYAQEBCi3371794QJE+RyeUFBwYABAw4ePKhQKCIjI83MzAwMDFauXLl06dJp06YRQkaMGCEWixUKRXR0NCFk/fr1z+49IyNjzJgx5ubmCQkJGRkZCoXi7t27Hh4e0dHRT5482bFjh5GR0cmTJ9s/hIsXL1Lzie7evXvJkiX+/v6EkG+++YZ6Nzs7e8SIEcnJyRKJ5MiRI3p6ek5OTu0cy08//WRoaMhisfbv3z948GBCyCeffPLUmnv37rX5s42NjW5uboSQR48eKctzdnZ++PDha/wTvYrExERCyP3799W8XwANhkDtNrZt22ZjY0PLrnft2kUIOXfuHLW4ceNGQkh0dDS1+MUXX+jp6clkMmrRwcHhgw8+oF4HBgZOmzaNer1gwQIGg/HgwQNqcfPmzYSQw4cPKxSKpqam8PDwsrKyNvceGBioPHCRSOTs7Pzvf/9b+W5ISIiuri6Xy23/EKia4+LiqEUvL69hw4ZRr729vZVZLpfL7ezslIH6vGOZP38+IeT8+fMKhSIrK6vNNc/72YsXLxJCwsPDqcWysrLZs2e3X3xnkMvl5ubme/bsUf+uATSVJl8r0jDl5eW2tra07Jo6p+rh4UEtUuddqa4YIcTZ2VkkEpWVlVGL169f37p1KyGEx+MVFxfn5uZS63v06MFisaj+GSFk48aNLBaL6icZGBgsW7bMysrqeQUoz81evXo1Ozt71KhRyrfefPNNsVh8/Pjx9g/BwMCAKpVadHV1LSoqIoTEx8enpqZOnDhRuaMRI0Yod/e8Y+nbty8hZObMmco2n13zvJ/19/d3cXHZtWuXQqEghPzyyy+LFi1qv/jOwGAwbG1tS0tL1b9rAE2FQO02TExMBAIB3VUQQoi+vn7rReo6aGNjI7XYr1+/tLS0jz76KCsry97eXi6Xt9mIoaGhtbU1n8/vyB6VCcfj8QghRkZGyrfGjRtHCMnKynqpQ2AymVSe3bt3jxDi7u7+7L7aORbqrqXW9y49u+Z5P8tgMNavX5+VlRUTE0MIiYuLmzp16ksVryoCgYDD4dCyawCNhEDtNoYPH87j8SorK+ku5AU2b968devW7du3BwUFMZnM520mEomo2c470qYy5Hr27EkIuXXrlvItW1tbNpv97N1MHVRXV0cIeWqoW+XuOngsbWrnZ+fPn9+vX7+dO3dyuVw3NzdantIpKip69OjR8OHD1b9rAE2FQO02pkyZ0rNnz71799JdSHsKCgq2bt26YMEC6hTr87qnhJCUlJSWlhbq/qD2MRgMmUxGvfb29iaEUCeKKQ8ePJBIJK88iDF1Hjs+Pv7Ztzp+LC/7s7q6uh9//HFCQsL69euXLFnyapW/pp07d1pZWU2YMIGWvQNoJARqt2FgYPDFF1/s2rXrzp07at51fX09IUQkElGLDQ0NhJCamhpqkTrZS71LvXX69Om6urqbN28mJibW1tY2NDRQLUilUuW52aioKF9fXypQeTyej4/P88busbKyqqioyM/Pf/TokYODw+LFixMTE6kroISQpKQkR0fHF46/SPVExWIxtVhVVSUSiRQKxYwZM5ydnU+dOkWFdFlZ2Y0bN0pKSjIzM6kT7G0eC3XI1dXVyvafWtP+50AIWbFihampaVVVlfKisjrdunXr4MGDX375pa6urvr3DqCxaL4pCl6GTCbz8/Pr379/YWGh2naanJxM3X+0ePHi/Pz8hIQELy8vQsj06dO5XG5ycjJ1i9A777yTk5OjUCiWLl3KYrEcHBwOHz4cFRWlq6vr5+dXXV29YsUKJpO5evXq9evXBwcHBwQE1NXVUbu4cuUKg8Fgs9kCgeDZAhISElgsFofD2bdvn0KhaG5u/uCDD9zc3H766adjx45Nnz69qKio/UO4fv06dW552bJl5eXlp0+fNjExIYSEhYVJJJKCgoIRI0YQQuzs7EJCQgICAsaOHXvo0KHm5uY2j+W7777r168fdcipqakKheLYsWNPrWnnc1BWtXLlyh9++EEV/0QvJy8vr2/fvtOnT5fL5erfO4AGw1i+3UxNTc2ECRMaGxtjYmK67Pzh9fX1xsbG1GuRSESN+bBy5coTJ06IxeLi4mJTU1Mq0pSqq6s3b9584MCBNkcpEgqFOjo6yjapNVwut3///tbW1iqpmc/nGxoa9ujRo6GhofVNT20eSwe1/7NTpkw5e/asmm8Lun///vTp0y0tLePi4joyIAYAdJzGjlmqqXr27BkXFzdz5kwfH5+DBw8GBwfTXVEbWpUhCukAACAASURBVCffswlkY2Pz7I9kZmZ6e3s/b8y/Z//0m5qajh49uvWaVatWPa+e0NDQIUOGtF8zNfID+d9biMmLjqV97fzsvXv37Ozs1JymJ0+e/Oijj7y8vM6fP480BVA5BGr3Y2FhER8f/8knn4SEhJw7d+7gwYOWlpZ0F/ViTU1NUqn0qf4fRSqVNjc3L168+HXaVz5L+ixlWNIuPT39s88+8/DwuH79+oULF9S237KystDQ0CtXrqxZs+bbb7/FpVOATkH3OWd4dX/99dfAgQN79ep16NAh6habLisyMpJK/VWrVlEjCGqntLQ0Y2NjU1PTs2fPqmePLS0t+/bt43A4jo6OSUlJ6tkpgHbCNdTuraGhYfPmzYcOHerTp8/nn3/+7rvvds3Oh1AoVP6m6enpUQ+TaCepVKqeCW1EItGxY8e+/fbb6urq1atXf/XVV9r8sQOoAQJVExQXF2/btu348eN9+/b99NNPFy5ciCtk2qy2tvbkyZM7d+6sqqoKDQ3dsGEDNTIiAHQqBKrmKCoq2rZtGzUX99y5c0NDQ1uPeQvaICkp6ejRo+fOnWOxWEuWLNmwYQP1PA8AqAECVdMIhcLIyMijR49mZmZ6eHi8++67QUFBdI2qD+qRn58fHR39008/8Xg8Ly+v0NDQkJCQ1vcYA4AaIFA1VkpKSnh4+Pnz5wUCwfDhw4OCgoKCgqiZTUEzZGVlnT9/Pjo6OiMjo2fPnrNnz16+fDmG5wWgCwJVw4nF4vj4+Ojo6AsXLlRVVXl6ek6dOnXy5MljxozBLSrdUVNT082bN+Pi4mJiYng8nqWlZWBgYFBQ0MSJE2kZZB8AlBCo2kImk924cePChQuxsbEPHz40MDAYM2bM5MmT33jjjSFDhqjhplN4ZTKZ7M6dO3FxcXFxcX///bdIJHJ1dZ0yZcqsWbPGjBnzstPgAEAnQaBqo4qKCmUvp6SkxNjY2NPTc+zYsWPGjPHx8enduzfdBQKpq6tLS0tLSkpKT09PTk6uqamxsLDw9fWdPHnyW2+91b9/f7oLBICnIVC1mkKhuH//fmJiYmpqakpKSl5eHoPBcHZ29vb2HjlypKenp4eHx1OD7kInEQqFmZmZmZmZaWlpKSkpOTk5hBAnJ6dRo0Z5e3uPHz++9SzoANAFIVDh//D5/JSUlNTU1OTk5IyMDIFAwGAwBg4c6PmPwYMHDxw4EOcYX59UKi0oKLh37969e/eoHH38+DEhxMzMbPjw4VSIjho1qlevXnRXCgAdhUCF5yorK+PxeFwuNz09PT09/eHDhzKZjM1m29jY2NnZ2dnZubq6urm52dnZDRgwAFdh21FbW5ufn8/lcnk8Xn5+fn5+flZWVlNTE5PJtLW1dXV1HTZsmJubm6urq6urK4PBoLteAHgVCFToqKamJi6Xm5OT8/Dhw9zc3Nzc3JycHGrGbCMjowEDBtja2trY2PTv39/GxmbAgAE2Njb9+vXTnltPJRJJaWlpUVFRYWFhUVFRcXFxcXFxYWFhQUFBU1MTIcTU1NTR0dHR0dHJycnJyWnQoEGurq641xpAYyBQ4bVUVFRQ+UqlSGFhYXFxcUlJiVgsJoQwmcw+ffpYWVlZWlqam5tbWlr26dOHemFpaWlhYWFmZtY1Bx9+llgsrqmp4fP5FRUVlZWVz74oLy+Xy+WEED09PWtra+UXC1tbWypBLSws6D4IAOhECFRQPblcXlFRoQzX8vLyJ0+e8Pl85QuJRKLc2NDQkNMWExMTAwMDfX19IyMjNpttamrKZDI5HA6LxaLGANLR0XlqyGJqS+WiRCJpaGhovYFAIKB+4evr66VSqUAgkMlkQqFQLBY3NjY2Nze3tLQIhULBP1q/pnqZFF1d3dbfDywsLKysrKytrW1sbGxtbfv06YPTtgBaCIEKNKiurqaStaampnVotVZXV9fS0tLc3NzQ0NA6gDuDrq5ujx49qPw2NTVtneutF83MzKgc7dmzZ6fWAwDdEQIVugehUCiVSpW9SUKI8oUS1QHduXMni8Vas2ZNO11Y6gWHw2EymZiZBwBUAoEKmiYoKEhXV/f06dN0FwIA2gWPOgAAAKgAAhUAAEAFEKgAAAAqgEAFAABQAQQqAACACiBQAQAAVACBCgAAoAIIVAAAABVAoAIAAKgAAhUAAEAFEKgAAAAqgEAFAABQAQQqAACACiBQAQAAVACBCgAAoAIIVAAAABVAoAIAAKgAAhUAAEAFEKgAAAAqgEAFAABQAQQqAACACiBQAQAAVACBCgAAoAIIVAAAABVAoAIAAKgAAhUAAEAFEKgAAAAqgEAFAABQAQQqAACACiBQAQAAVACBCgAAoAIIVAAAABVg0V0AwOtqamoSiUTKRYlEQgipra1VrtHT0zM0NKShMgDQJgyFQkF3DQCvZd++fWvWrGlng8OHD69YsUJt9QCAdkKgQrdXWVnZt29fuVze5rssFquioqJXr15qrgoAtA2uoUK3Z2lp6evry2Qyn32LyWROmTIFaQoAaoBABU2wcOHCNs+1KBSKBQsWqL8eANBCOOULmqCurs7c3FwsFj+1Xk9Pr6qqysjIiJaqAECroIcKmsDExGTq1Kks1v/ctc5isWbNmoU0BQD1QKCChliwYIFMJmu9RiaTzZ8/n656AEDb4JQvaIiWlpbevXs3NjYq1xgbG1dVVenq6tJYFQBoD/RQQUPo6+sHBQWx2Wxqkc1mBwcHI00BQG0QqKA5QkJCqGGSCCESiSQkJITeegBAq+CUL2gOmUxmYWFRU1NDCDE3Ny8vL2/z4VQAgM6AHipoDiaTGRISoqurq6uru3DhQqQpAKgTAhU0yrx588RisVgsxvleAFAzzDYDXYhUKhUKhUKhsLa2ViwWNzY2trS0NDc3NzY2isXi+vp6qVQqEAgUCoVcLhcKha1/VrnGwMCAwWBs376dEGJqaqqj8z/fGjkcDoPB0NHRMTU1ZbFYxsbG1Fw0BgYG+vr6RkZGurq6HA6Hw+GYmpqijwsAHYdAhU6nUCj4/6ioqFC+rq2tFf5DIBAIhcLWD720ZmhoqKenZ2RkxGazTUxMqJxTvlCi4tPW1pYKUZlM9vjx49YbyGSyuro65QuJRNLQ0CASiZqamtrcr5GRkWkrHA7HzMzM3Nzc3NzcwsLC0tLS/B+q+JwAoHvDTUmgGg0NDUVFRcXFxaWlpcXFxUVFRaWlpaWlpVVVVXw+Xznkgo6OjjKEevbs2TqrWkeXmZlZ647jS1WSmZmpq6vr7Oz8Uj/V3Nzc0tJCdYWppKcyvjWBQFBTU0MdEZ/PV85vw2QyqSPq16+ftbW1tbV1//79lS969OjxUpUAQDeFQIWXI5PJioqK8v6Rm5tbUFBQUlIiEAioDXr06EHFCZUuVNJYWVkpc5TBYNB7CCohl8uVXe3y8nIqZanvEyUlJUVFRcper5mZmbW1tZ2dncM/HB0dbWxsnjoXDQDdHQIV2tPU1MTj8TIzM3k83sOHD/Py8vLz86kx6M3MzKhssLe3p+LT1ta2X79+ZmZmdFfdJdTU1FDJWlJSUlJS8ujRI+orCPXNQ09Pz87OztHR0cnJyc3NzcPDw9XV1cDAgO6qAeDVIVDh/ygUitzc3Hv37t2/f5/L5WZmZubn58vlcgMDA1dXVycnJwcHB+q/jo6OmGT01fD5fKpnn5ubm5eXl5OTw+PxWlpamEymnZ2dp6enu7u7u7v7kCFDHBwc6C4WAF4CAlXbCYXC27dvJyUlpaenp6SkVFVVEUKsrKyGDRvm5ubm6uo6bNgwZ2dn3O/aeWQyWWFhIZfL5fF4XC43PT394cOHMpnMxMTEw8Nj7NixY8aM8fb2trCwoLtSAGgPAlUb5eTkJCQk3LhxIyUlpaCggBDi5OQ08h+enp4490ivpqame/fupf0jLy+PEGJvbz9q1ChfX9+JEyei8wrQBSFQtUVhYWFCQkJ8fHxCQkJJSYmRkdG4ceNGjRpFhWjPnj3pLhCeq7q6Oi0tLTU1NSUlJSkpqbGxsX///hMnTvTz85s4caKNjQ3dBQIAIQhUzSaXy1NTUy9cuHDhwoWcnBwDAwMfHx/qr/DIkSOfmo4bugWJRJKamkp9Mbp165ZIJHJxcZk5c2ZgYODIkSM14w5qgG4KgaqBRCJRQkLCb7/9dvHixYqKCkdHx8DAwGnTpo0aNepln+mErqy5uTk5OTkmJubChQv5+fl9+/alknXixInKaewAQG0QqBqFx+NFREScOHGCz+e7urrOmTMnICBg2LBhdNcFnY7L5V6+fPnSpUvJyckcDmfOnDnvv//+kCFD6K4LQIsgUDWBQCD45ZdfTpw4kZ6e7ujouGTJkgULFuDSmnZ6/PhxZGTkjz/+mJ+f7+3tvXTp0uDgYBMTE7rrAtB8CNTuraqq6sCBA3v27BGJRAEBAaGhoZMmTcKFNCCEpKenHz169Oeff2YwGEuXLt20aVOfPn3oLgpAkyFQu6uysrLvv//+6NGjxsbGn3766YoVK9ALgWcJBIKDBw/u3r27paXl/fff//TTTy0tLekuCkAzIVC7H4lE8t13323durVXr17r169fvny5oaEh3UVBl9bY2HjkyJEdO3YIhcKwsLC1a9fiHm8AlUOgdjOpqanLly9/9OjRl19+uWbNGj09Pborgm6jpaVl165dX3/9taura3h4uJeXF90VAWgUzHfRbcjl8s8//3z06NGWlpaZmZmfffaZZqdpfn7+0qVLS0pK6C6kbTweb+fOnStWrPjxxx+jo6N///13uit6MX19/c8///zevXvGxsbe3t5btmzB92kAVVJAd9Dc3BwQEKCvrx8eHi6Xy+kuRx3OnTtHCImJiaG7kDakpKR4e3tLJJJjx44ZGRkRQv7973/TXdRLkMvl+/fv19XVnTNnjkgkorscAA2BHmo3IJFIgoKCkpKSEhISli1bpiU38c6ePZvP50+dOrUjG0dERHSw2Y5v2Y7//Oc/48aNY7FY7733XnZ29us3qJKqOo7BYKxevTo2NvbatWvBwcHK6d8B4HUgULuBTZs23bhx49q1a6NGjaK7FrXq3bt3RzaLj4/ftGmTardsX2xsLIfDoV4rX7wyVVX1snx9fWNiYq5cufLll1+qf+8AmocZFhZGdw3QnvT09KVLl4aHh0+bNk3Nu25ubo6OjrazsystLf3ll19KS0sdHR11dHQqKytPnz599+5dBweH1tdxc3Jy/vjjj1OnTjU2Nrq4uFArS0pKIiMjhw8ffuPGjSNHjmRnZ3t4eFAD49XX1+/Zs+d5c5LL5fLr169XVVX169ePEFJcXPzTTz+NHDmSy+WGh4cXFhZ6eHgwGIyEhITAwECJRNKzZ8/y8vJBgwY973Da3LK+vv7ChQtRUVGPHj0yNzc3NTVt/zMpKCi4fPlyVFRU37595XI5j8d78ODBb7/9Rk0CQ23TTpvPfkQdr78z9O/fv3fv3p9//vnbb7+N6eEAXhfd55zhBd5+++3Ro0erf7/Xr193dHQkhOzcuTM0NPSzzz4zNDQMCgoKDw+fP39+cHAwg8EICAhQbr979+4JEybI5fKCgoIBAwYcPHhQoVBERkaamZkZGBisXLly6dKl1HeCESNGiMVihUIRHR1NCFm/fv2ze+dyubNnzyaEHDp0SKFQXLx40dzcnBCye/fuJUuW+Pv7E0K++eYbhUKRkZExZswYc3PzhISEjIyMdo7o2S3v3r3r4eERHR395MmTHTt2GBkZnTx5sv2PpbKykrr/aO3atcnJycnJyX/99RdpdQ21nTbb/Ig6Xn8nkcvlXl5eISEh6t81gIZBoHZpzc3NBgYGx48fp2Xvu3btIoScO3eOWty4cSMhJDo6mlr84osv9PT0ZDIZtejg4PDBBx9Qr6mx+KnXCxYsYDAYDx48oBY3b95MCDl8+LBCoWhqagoPDy8rK2tz75mZmcpAVe49Li6OWvTy8ho2bJhydzY2Nh05otZbikQiZ2fn1jcThYSE6Orqcrnc9hspLS0lhOzbt49abGhoUAZq+20+7yPqeP2d5IcffjA2NpZIJDTWAKABcA21SysuLm5ubqbreUHqXKWHhwe1SJ2NHDx4MLXo7OwsEonKysqoxevXr2/dupUQwuPxiouLc3NzqfU9evRgsVhubm7U4saNG1ksVmJiIiHEwMBg2bJlVlZWbe79qYeCqDnPnZ2dqUVXV9eioiLlux2/UUu55dWrV7Ozs1tfln7zzTfFYvHx48c72NSz2m/zeR/RS9XfGby8vOrr65X/lADwahCoXRr1d1bRNR4WfGrqN+o6aGNjI7XYr1+/tLS0jz76KCsry97eXi6Xt9mIoaGhtbU1n89/zWKYTGbrj+UVApXH4xFCqIdeKOPGjSOEZGVlvXJV7bfZzkdEb6BSn6SODv4aALwW/C/UpVlbWxsYGNy5c4fuQl5s8+bNW7du3b59e1BQEJPJfN5mIpGooqLCzs5OtXt/hUDt2bMnIeTWrVvKt2xtbdlsdpt3SHVQ+2228xHRG6h37twxMTHB0PkArwmB2qXp6+tPmzbt2LFjXaST+jwFBQVbt25dsGABdWL2ed1TQkhKSkpLSwt1V5GqMBiMDj5J2XpLb29vQgh18pny4MEDiUTi4+PzypW002Y7H1HH6+8Mcrn8+PHjAQEBGN0X4DUhULu6zz//PC0t7eTJk+rfdX19PSFEJBJRi9TdNzU1NdQidbKXepd66/Tp03V1dTdv3kxMTKytrW1oaKBakEqlyvOoUVFRvr6+VKDyeDwfH5/vvvuuzb1TLVdVVVGLdXV1hBCxWEwtVlVVUUP8EEKsrKwqKiry8/MfPXqkPAXdptZbOjg4LF68ODExUXktNikpydHRMTQ0tP2PpaWlhRDS3NzcujCq2sGDBz+vzXY+oo7X3xkOHz6cmZlJy4OwAJqG1luioEPWr19vaGiYkpKizp0mJydT9x8tXrw4Pz8/ISGBujdq+vTpXC43OTmZuvXmnXfeycnJUSgUS5cuZbFYDg4Ohw8fjoqK0tXV9fPzq66uXrFiBZPJXL169fr164ODgwMCAurq6qhdXLlyhcFgsNlsgUDw1N5TUlKox2bc3d0vX758/fp16izxsmXLysvLT58+Tc1VFxYWJpFIEhISWCwWh8NR3nn7PE9t2dzc/MEHH7i5uf3000/Hjh2bPn16UVFR+y3k5+eHhIQQQlxcXP7444+Kiop3332XEDJo0CDqDuR22nzeR9Tx+lUuMTFRX1+/e42bCNBlYbaZbkAqlc6aNSspKeny5ctjxoyhu5znqq+vNzY2pl6LRCLqNt2VK1eeOHFCLBYXFxebmpo+NWlrdXX15s2bDxw48Jp3xAiFQh0dHeXeX2pLoVDI5XL79+9vbW39OjU8tZc222zzI3qp+lUoPj4+MDBwypQpv/76azuXvQGggxCo3YNIJJo3b15MTMyePXtWrFjRjYbzVQZqm+8mJCQUFRUtXrxYVbtbtWrV894KDQ0dMmSI2hrpyqjB8devXx8UFBQREUHdsA0Arwm3IXQPenp6UVFRYWFhq1evPnv27NGjRx0cHOguqkOampqkUmlDQ0Prh0koUqm0ublZhWlKCFGO//csaqwltTXSZWVnZy9fvjw1NTUsLGzTpk3d6MsZQFdH9zlneDm3b98ePHiwgYHBt99+29LSQnc5LxAZGWlpaUkIWbVqFS3j6kFrTU1NX3/9tb6+/vDhw+/evUt3OQCaBqd8ux+JRLJjx46vv/7azMxs/fr1oaGhhoaGdBfVNqFQqPwF09PTo54YAfVraGg4fPjwzp076+vrv/rqq48//hgXTQFUDoHaXZWXl+/YsePIkSOGhoaffPLJypUrX38eMdA8NTU1P/zww969e8Vi8fvvv//pp59iVhmAToJA7d6qqqoOHDiwd+/e5ubmGTNmhIaGTpo0CVfFQC6XJycnnzp1KjIykslkrlq16rPPPqMGcgKAToJA1QRCofDMmTMnTpxIS0uzt7dfsmTJggULbG1t6a4LaFBQUBAREfHTTz89fvx49OjRS5cufeedd9T8QA6AdkKgapSsrKyTJ0/++OOPT548cXV1DQgI8Pf3HzNmDPqsGo/L5V6+fPnSpUvJyckcDmfOnDmrVq1STg0EAGqAQNVAYrH4+vXrv/3228WLF8vKyuzs7AIDA6dOnTpmzBjcFqRJmpqakpKSYmJifv/998ePH9vY2MyYMSMwMHDChAkYmBdA/RComkyhUKSlpV24cOH333/PysrS09Pz8fGZOHGin5+ft7c3HufvjsRicWpqanx8fHx8fEpKilgsdnd3nzlzZmBg4LBhw3AqAoBGCFRtUVJSEv+P4uLiHj16jB071sfHZ+TIkSNHjuzVqxfdBcJz8fn8tLS0tLS0W7du/f33301NTba2tn7/6Nu3L90FAgAhCFTtlJeXFx8ff+PGjdTU1EePHhFC7O3tvb29R44cOWLEiMGDB/fo0YPuGrVaQ0PDvXv3qBBNTU0tKCgghDg6Onp7e/v6+vr5+al8QlkAeH0IVG0nFArv37//999/JyUlpaam8vl8QoiVldWwYcPc3NxcXV3d3Nzc3d2Vw7iDykml0qKiIi6Xm56ezuPxuFxudna2XC43NTV1d3cfO3bsmDFjRo0apQGjHgJoNgQq/I9Hjx7dvXuXy+Xev3///v37eXl5MplMT0/P1dXVycnJwcHBwcHB0dHR0dER4wO8moqKiry8vNzc3Ly8vLy8vJycHB6PJxaLqZndPDw8PDw83N3dhwwZMnDgQLqLBYCXgECF9rS0tHC53AcPHjx48CA3Nzc3Nzc/P5+aYdvExITKVzs7O5t/WFtb9+7dm+6quwQ+n19SUlJSUlJYWFhSUpKfn08lKDXpur6+vvLbibu7u4eHh6urK04DAHRrCFR4OQqFori4OK+VgoKCkpKSqqoqagMDAwNqHlCKubm5ubm5paWlhYUF9VozRpGVSqV8Pr+qqqqysrKysrKqqurJkycl/ygoKJBIJNSW5ubm1tbWAwcOdGjF2toad+QCaBgEKqhGc3NzUVFRcXFxSUmJ8kVpaWlVVRWfz5dKpdRmDAajd+/e5ubmvXv3NjY27t27t6mpKYfDMf0Hh8MxMzMzNTVls9kmJiZsNvvZed86Q319vVQqFQqFEolEKBQKBAKBQEC9EAqFyhe1tbVUjlIXmylsNps6qH79+llbW9vY2Ny5c+fy5cu9e/f+5JNPVq1ahZu8ALQBAhXUgUogPp//5MmTysrK0tLS06dPNzU1jRgxonVo1dXVtfnjenp6hoaGBgYG+vr6PXr00NXVJYQ8m7VGRkatH64Vi8WNjY2tN6BSkxAiEomampqam5tbWloaGxufN/+5aStU6nM4nNZ97t69e1tYWLT50FFlZeWhQ4f27NnDYrFWr1794Ycf4tkkAM2GQAV1KykpmTlzZlFR0fnz58eNG9f6LYVCIfgH1V+USqX19fWt86+hoYE6m0ottv5xgUCgUCh4PB6DwXBxcdHR0TE1NW29ARXJhBBdXd0ePXro6+sbGBhQCW1sbMxisTgcDovFooKTw+G8/lnZ6urq/fv3HzhwQCQSLV26dP369dbW1q/ZJgB0TQhUUKuUlJTAwEALC4uLFy8OGDCgM3YRFBSkq6t7+vTpzmj81TQ0NBw/fnzHjh1PnjyZO3fu559/7uzsTHdRAKBiOnQXAFrk119/9fPz8/LySkpK6qQ07ZqMjIzWrFnz6NGj8PDw27dvu7m5BQQEpKWl0V0XAKgSAhXUQaFQhIWFzZs3b/ny5ZcvXzYxMaG7Ihro6uouWrSIy+VeuHChsrLS29t77Nixly5dorsuAFANBCp0upaWlgULFmzbtu348eN79+7V0dHq3zodHR2qe3rz5k0zM7MZM2YMGzbs3LlzuPgC0N1p9Z82UIOKioqxY8fGxsbGxcUtWbKE7nK6EKp7mp6ebm9vP3fuXE9Pz4iICOXzRQDQ7SBQoRNlZ2f7+Pg0NDSkpqY+dUMvULy8vM6ePZuZmTl06ND33nvP0dFx7969zc3NdNcFAC8NgQqdJSUlZfz48ZaWljdv3sTsKO1zd3ePiIjIzc2dMWPGpk2bbG1tw8LCamtr6a4LAF4CAhU6xYULF/z8/EaPHh0fH49pUjpowIABe/fuLSwsXLVq1b59+2xtbdesWVNWVkZ3XQDQIQhUUL39+/cHBQXNnz8/KirK0NCQ7nK6GXNz87CwsMLCwq+//joqKsrOzm7RokW5ubl01wUAL4BABVWiHo9Zs2bN5s2bw8PDWSwW3RV1V8bGxmvWrMnPzz969GhKSoqzs/M777zD5XLprgsAnguBCiojFosXLly4bdu2iIiIsLAwusvRBHp6eosWLcrOzj5z5gyPx/Pw8AgICLh16xbddQFAGxCooBp1dXVTp069dOlSTEzMggUL6C5Ho+jo6MyZM+f+/fu///57dXX16NGjqUdu8OgqQJeCQAUVqKqqmjRpUlZWVmJi4qRJk+guRzMxGIyAgIDk5GRqRIiZM2cOHTo0IiJCJpPRXRoAEIJAhddXUVHh5+fH5/MTExMHDx5Mdzmaj+qeZmRkeHp6Ll261MnJae/evU9NvAMA6odAhddSWFg4btw4iUSSlJTk4OBAdzlaZPDgwRERETk5Of7+/hs3bhwwYEBYWJhQKKS7LgDthUCFV5ednT127FgTE5PExERM80kLOzu7vXv3Pn78eOXKlXv27LG3tw8LC6uurqa7LgBthECFV3Tnzp3x48cPGDAAQzfQztLSMiws7NGjR6tXrz5w4MCAAQPWrFlTUlJCd10A2gWBCq/i5s2bfn5+7u7uV65cMTU1pbscIISQXr16hYWFPX78eOvWrefPn7e3t6ceuaG7LgBtgUCFlxYfHz9t2jRfX9+YmBgjIyO6y4H/0eZk5rdv36a7LgDNh0CFl3P+VvA7HAAAIABJREFU/PmpU6fOnj37/Pnz+vr6dJcDbXtqMvORI0diMnOAzoZAhZdw/vz54ODg0NDQEydOMJlMusuBF8Bk5gDqhECFjrpy5UpISMi77767b98+BoNBdznwEjCZOYAaIFChQ65evTpr1qyFCxceOXIEadpNYTJzgE6FQIUXu3bt2qxZs+bPn4801QCYzBygkyBQ4QViY2MDAwPnzZsXHh6uo4NfGA2BycwBVA5/H6E9f/7558yZM+fOnXvs2DEqTevr648cObJx48Zjx441NTXRXWB7RCJRbGzsd999l5ycjBHk26T+ycwrKiquX7/eee0D0AiBCs8VFxc3c+bMGTNmHD9+nErThw8fOjk57dy5c/fu3cuXL/f09KyoqKC7zLY9efLExcWlqKho6dKlFy5cmDlzJjL1edQzmTmfz1+3bp2dnd1vv/2m2pYBuggEKrTt5s2bs2bN8vf3//nnn5VPyKxdu/batWs5OTklJSXLli179OjRF198QW+dbVIoFEFBQR4eHsuWLevdu/e2bdsePHjQNUvtOjp7MvPHjx8vWrQI90CBBkOgQhtu3bo1derU6dOnnz59msViUSvT09Pnz5/v6elJCDE3N9+yZYuOjk5ycjKtlbaNz+cnJSUtX76cWmQymYsXLz5w4EBjYyO9hXV9nTeZ+YgRI5ydnVVSJEDXhECFp/F4PH9/fz8/v8jIyNajNwwYMCAkJES5aGVlNWzYMDMzMzpqfAFqXHgPDw/lGnd398bGxpiYGPqK6k4wmTnAK0Cgwv8oKSmZNm2ak5NT674ppVevXk89M1NcXDx16lT1Ftgh9fX1hBArKyvlGgsLC0JITk4ObTV1T5jMHKDjEKjwf6qrq6dMmWJkZPTHH3/06NGj/Y0TExNZLNbatWvVU9tLaWlpYTKZurq6yjWGhoaEkPLycvqK6sYwmTlARyBQ4f9ramqaMWNGQ0PDlStXevbs2f7GMpns3//+98WLF7vmbDNP9a0JIdS5yj59+tBRjobAZOYA7UOgAiGESCSS2bNn5+TkxMbG2tjYvHD7devWffLJJ0OHDlVDba/A0NBQJpOJRCLlGuoksKurK31FaQhMZg7wPAhUIAqFYvny5Tdu3Lh48WJH7sM8evTo0KFDZ8yYoYbaXg0153lxcbFyTVVVFUGgqg4mMwd4FgIVyLp163755Zfz58/7+Pi8cOPffvtNoVAsWrRIuebGjRudWd2rsLOz09PT+/vvv5Vr0tPThwwZ4uTkRGNVmgeTmQO0hkDVdtu2bduzZ8+pU6fefPPNF24cFxe3fft2iURy4MCBAwcO7N27d8WKFZmZmWqo86Xo6+uvXr36+++/p56ebGlpuXTpknK8J1Ctjk9mTg3Bj5uEQWMpQItFREQwGIz9+/d3ZOP09PRnb/3V19evrq7u7Dpfyttvvx0cHCyXyzds2ODv779v375NmzZFRETQXZe2uHnzpr+/P/lntji5XE6tj4mJmTt3LiHEwsIiPDy8vLyc3joBVI6heO0BUKCbunnz5htvvLFmzZrt27fTXYsqBQUF6erqnj59mhAik8mqqqosLS3pLkrr3Llz59tvv42KinJzc1u/fn1ISMizt14DaBicAdNSBQUFQUFBkydP/uabb+iupRMxmUykKS0wmTloIQSqNqqrqwsICLCxsfn1119bDy4IoFqYzBy0CgJV60gkklmzZgmFwkuXLr1wOCSA14fJzEFLIFC1ztq1a1NTUy9evNi3b1+6awEtov7JzAHUDIGqXU6dOnXw4MHjx4932UGOQLOpZzJzAFogULXInTt3VqxYsWnTJurpBQC6dPZk5gC0QKBqi8rKypkzZ44bN27Lli101wJASGdOZg5ACwSqVqDGvjcwMMBtvdDVYDJz0BgIVK2wcePGu3fv/vbbbxwOh+5aANqGycyhu0Ogar5Lly7t3r37hx9+cHNzo7sWgBfAZObQfSFQNVxhYeG7774bGhraen4YgC4Ok5lDd4SxfDWZSCQaM2aMRCJJSUkxMDCguxw1aT2WL2iA6urq/fv3HzhwQCQSLV26dP369dbW1nQXBdAG9FA12dq1a/Py8qKjo7UnTUHzYDJz6C7QQ9VYv//+e2Bg4NmzZ+fMmUN3LZ0rOzu7pKREufjVV1+x2ezPP/9cuaZ///6YWlwziMXiM2fObNu2LScnZ9q0af/+979HjBhBd1EA/x8CVTM9efLE09Nz2rRpJ06coLuWThcZGblw4cJ2NtCGbxVaRS6X//HHH19//fXt27fHjBmzYcOGgIAAuosCQKBqIoVC4e/vn52dnZGRYWJiQnc5na6hoaF3794ikajNdw0MDKqrq3HSWyMlJSVt37798uXLXl5eGzdunD17NoPBoLso0F64hqqB9u7dGxsbGxkZqQ1pSggxMjKaMWMGm81+9i02mz1nzhykqaaiHl1NT0+3t7efO3eup6dnRESEVCqluy7QUghUTcPlcjdt2rR582YfHx+6a1Gf+fPnt/lnVCKRhISEqL8eUCdMZg5dBE75ahSpVDp69GgdHZ2///5bq4YYFIvFvXv3rq+vf2o9h8Ph8/ksFouWqkD9Hj9+vHv37vDwcCMjo1WrVq1Zs8bMzOx5G585c2bmzJk4gQGqgh6qRtmxY0dmZubx48e1Kk0JIbq6uu+8885TZ33ZbPb8+fORplql45OZV1dXv/fee2+99VZTU5P66wSNhEDVHA8fPvzqq6+++uor7RxiMCQkRCKRtF4jkUjmzZtHVz1Ao45MZn7gwAGxWJycnDxlypTGxka6SgVNglO+GkIul/v6+jY2NqamprZ5e47Gk8vlffr04fP5yjVWVlalpaW47VPLiUSiX3/9devWrY8ePQoKCvryyy/d3NwaGxutra0FAgEhhM1me3l5xcbGaslNfNB50EPVEHv37r19+3ZERIR2pikhREdHZ/78+crDZ7PZixcvRppCm5OZb9q0SXnFXSKR3Llz54033qirq6O3VOju0EPVBCUlJS4uLuvWrfvyyy/proVOaWlp3t7eysV79+55enrSWA90NQqF4vLly9988829e/eeug2YzWa7urrGx8f37NmTrvKgu0OgaoI5c+ZkZGQ8ePBAX1+f7lpoNnDgwMePHxNC7O3t8/Ly6C4HuqLjx4+HhobK5fKn1rNYLBcXl4SEhF69etFSGHR3OOXb7f35559RUVF79+5FmhJCFi5cyGaz2Wz2u+++S3ct0BXJ5fL//Oc/bb4llUqzs7MnTJiAeeLg1aCH2r2JxWJPT083N7fo6Gi6a+kSsrOzXVxcCCE5OTmOjo50lwNdzrlz5+bOndvO3z02m+3k9P/Yu++4JrK9YeCTkARCL4HQEaREehGlKquiu1gWC+qq133WhorrVtu6ru5er73tPtcCWFcvriC6Liq2BaRakB56kwChSkJCejLvH+c1l4emQmACnO8ffCaTmTM/wiG/OTNnzrFPSUmhUCgjGRg0BsBH9Ea3I0eO1NfXP3r0COtAhktbW1t7ezuXy+3o6ODxeHw+n81mc7lcPp/P4XBQFAUdNQGhUMjj8XR0dPB4/O7du9XV1VVVVeXvggf8tbS01NXVNTQ0dHR01NXV1dXVdXV1tbS0DAwM4IW+8aC/5qmcWCwuLy+fNm3a06dPDQ0N36dMmUzGZrO7urr4fD7o2cRisVAUFQgE4E5tny8RBJFKpX32hOpvPYIgoHoPsB6Hw+nq6iIIAup/fy91dHTIZDKo/7DvnqLAFuoo1tLSYmtru3Pnzu5TlY0ubDa7vr6+rq6uoaGhvr6+vr4eZND29naw0ONGFx6P19HR0dDQIJPJ4CEHbW1t+SgWBAJBS0urrKwMj8fb2dl1dnZKpVLwlvwbis1m8/l8Ho8n/1KTU1FRAWmVQqEYGBgYGhqamppaWFiYmZlZWFhYWlpqaWmNxIcCDZuOjo5ff/21vr6+oaGhtra2qalJfkKGw+FIJBIejxeJRKDamJqa7t69WyaTsVisjo4OLpfLYrH4fD6fz+/o6AALLBaLx+P1NzGDHKilJBJJQ0MD+b+Vtvty7116rOwv0UokEnmnZfk2XC5XLBYPkJvl1NTUyGSynp4emUxWU1MDC2QyGZxr6unp6erq6urqggX5SzjCVG8woY5iW7ZsuX37dkVFhbq6OtaxvINUKq2rq6vopra2lsFgyL8FtLS0LCwsTE1NjYyM5CnNwMDAyMiIQqFoamrK/9vfeSwGg0EgEExMTN65JWgxdHR0cDictra21tbW7um8paWlsbGxrq5O/tS/tra2hYXFhAkT7O3t7ezsbG1t7ezsLC0t+2wxQEpFKBSCP3FTUxNYaG1tbW5ubmlpaWhoePPmDYvF6urq6jEiNA6Ho1Ao+vr6enp63Sthn7lHvoD0yqDKAORXeert6OiQ138+ny8QCHosgNMFDocDzidYLJZIJOpeoJqaGsivenp6FArF0NDQ2NiYQqF0XzY0NCSRSBj9xhiACXW0qqmpodFop0+fXrduHdax9KG2tjY/Pz8/P7+goIBOp1dXV4P/RgMDAzs7Ozs7OxsbG3njz8LCQpmfqWexWPX19QwGA7Shq6qqKisrKyoq3rx5gyCIqqrqxIkTHR0d3d6ytLTEOuTxSCgUNjQ0NDY2MhiMxsZG0AxtaGgAibN7K41EIhkaGlIoFGNjY7Cgr6/fowUGfvJ4PJlMZmRkhOHvpTy6urrkyVW+0NHR0dHRIT9BAWel3VOvjo4OlUo1NDQ0MzMzNTW1tLQ0MTExNzc3Nzc3MTHpflNmDIAJdbRavnx5Xl5eUVGRkoxVW1tbm5mZ+fz587y8vIKCAhaLhcPhbGxsPDw8nJyc7N4aYKTyUae9vR1k1rKyMjqdnp+fX1NTg6Konp6em5ubu7u7j4+Pn5+fhYUF1pGOKa2trdXV1TU1NTU1Na9fv25oaGAwGEwms6WlBWxAIBCMjY3BBQ8zMzMjIyPwhQ4aTFQqVUdHB9tfYcxjsVjNzc3gSkBLS0tLS0trayv4MzEYjObmZvmVACqVCv5M5ubmVlZWNjY21tbW1tbWo7RHGEyoo1JeXp6Xl1d8fHxoaChWMUgkkpcvX2ZlZWVkZGRlZTGZTCKR6O7u7unpCRpqLi4u4+2mY2dnZ0FBAWia5+Tk5OfnSyQSMzMzPz8/Pz8/X1/fyZMnj7d5CwZNJBKBiwEgd8qTKJfLRRCEQCBYWlpOmDDB3NwcNH3kGdTY2BhehFdmUqm0ubm5vr5efjkBnBW9fv2awWCAXKulpWVtbS3Pr9bW1ra2thMnTlTykeBgQh2VwDBpz549G/nueTU1NY8fP37y5Mnjx49ZLJaOjo63t7e/v39AQICfn5/y380dSTweLycn59WrVxkZGSkpKa2trZqamj4+PvPmzfv0008nTJiAdYBKRCgUVlZWFhcX0+n04uLi6upqOp0uEAgQBNHT07PpxdLSUkmuzUAKJJFIWlpamExm9f8Frv2AsygbGxtHR0cnJydwn0WpztphQh19Hj9+PHv27KdPn06bNm1kjiiTyTIyMm7evJmYmFhRUaGpqRkUFDRnzpzg4GAHB4eRiWG0Q1G0pKTk8ePHjx49evr0aVdXl4ODQ0hIyOLFi319fcdbiwoMoZCbmwtG+CotLWUwGAiCqKqqOjg40Gi0SZMmTZo0ycHBwc7OTnn69UBY4XA4lZWVpaWlJSUl4Gd5eTm4U2tpaUmj0VxcXNzd3T08PGg0GoYXgWBCHX1mzJhBJBIfPnw43AeSSqXp6elxcXG3bt1iMpnOzs7z58+fPXu2n5/fuOq5p3BCoTAjI+PRo0d//fVXSUmJmZnZ4sWLlyxZ4u/vP1YzK5/PLygoyMvLy8nJyc3NLSwsFAgEqqqqzs7Orq6u8gxqbW0NL4lD70MikdTU1JSUlIAUW1BQUFRUJBKJyGSyq6urx1suLi4jOYQcTKijzMuXL6dMmfL333/PmDFj+I7y+vXr6OjoixcvMplMV1fXJUuWLFmyBIxABCkWnU6Pi4u7efMmnU43Nzdfu3btunXrzM3NsY5LARoaGtLT0zMyMtLS0oqKiiQSiba2tru7O2hJeHh4ODo6KvktMWgUEYvFdDo99638/HwOh0MgENzc3MA9qYCAgPd5mm4oYEIdZZYsWfL69euXL18OR+FSqfTevXuRkZEPHjygUqnr1q1buXIlvKg7MoqLi69evXrp0qW2tra5c+eGh4d//PHHo6vBiqJocXGxPInW1tYSCAQPDw9/f39fX19PT8+JEyfCQXmgkSGTySorK3NycrKystLT0/Pz86VS6cSJE/39/QMDA/39/YejhQAT6mhSVVXl4OBw/fr1sLAwxZYsk8ni4+P37NlTXl4+c+bMDRs2hIaGwtbDyBOJRHfu3ImKivr777+tra137NixZs0aJe9909XVlZSUdPfu3fv379fX12toaLi7uwcEBIBvLjDQAQRhq6urKzc3NyMjIz09PT09ncViGRkZzZkzB9zGUtSTVDChjibh4eFPnjwpLy9X4H0miURy7dq1/fv319XVrVq1ateuXXBMeWVQUlJy4MCB69ev29nZ/fjjj8uXL1e2m4uFhYX3799PTEzMyMhAUdTHx+eTTz6ZM2eOu7u7kp8BQOOcRCLJycl5+PDh/fv3X758qaKiEhAQ8Mknn8ydO3eozVYUGiWam5vJZPLZs2cVWOarV6+8vLyIROI//vGP8vJyBZYMKUR1dfWGDRvAfaDnz59jHQ6Komh9ff2pU6fc3d0RBKFQKGFhYVeuXGlvb8c6LggajLa2ttjY2A0bNoDbq46Ojnv37q2urh5caTChjho//PCDkZERj8dTSGksFmvz5s14PD44OLiiokIhZULDpKSkJCgoSEVF5auvvurs7MQkBjabfeHChaCgIDweT6FQvvzyy6ysLKlUikkwEKRw4KGGTZs26evr4/H4mTNnXr58+UP/3WBCHR0EAoGhoeG+ffsUUtqrV68sLS2NjIyuXr2qkAKh4SaTyS5evGhgYGBtbV1QUDCShy4tLd24caO6urqamtqSJUvu3LkjEolGMgAIGklCofDWrVsLFy4kkUiamppbtmx5/yYHTKijQ0xMDIFAqK+vH3pRN27cUFdXDw4ObmtrG3pp0Ehqbm6ePn26pqbm7du3R+BwhYWFCxcuxOFwtra2v/32W0dHxwgcFIKURHt7+8mTJ62trfF4/NKlS4uLi9+5C0yoo8P06dNDQ0OHXs6hQ4dwONzWrVvFYvHQSxs/OBzOX3/9tX37dqwDQUUiUXh4OB6P//XXX4fvKE1NTatXr8bj8e7u7rdv3x5vl3aFQuGTJ0++/vrre/fuYR3LsMCkPldVVX3xxRcMBmMkDzp0EokkNjbW2dlZRUVl7dq1A7dDYEIdBUpLS3E43P3794dYztmzZ3E43G+//aaQqMaVuLi4CRMmWFpaYh3I/3f48GEcDnflypXhKPz333/X09OztLS8ceOGTCYbjkMouVevXm3YsAFBkOjoaKxjGRaY1Oe4uDgEQYb+PYYJqVR67do1U1NTCoXyxx9/9LcZTKijwDfffGNpaSmRSIZSyPPnz0kkkqLuwo5DS5cutbGxwTqK/9qxY4eamlpubq4CyxSJROvXr8fhcF9//TWXy1VgyaNOfn7+GE6o6HvX5yGetPXYvbW1dSilYY7NZm/evBlBkC1btvT5hQwTqrID3ZH2798/lELEYrGbm9usWbPG27U7BVq+fLmtrS3WUfyXRCIJDAycMmWKov6mQqEwNDRUU1Pzzz//VEiBoxqdTkcQ5Pz581gHMlzepz7//fffpqamgz7EEHdXWrGxserq6suWLet940xl3759Q3xIFhpWN27c+OOPP65cuTKUWYpiY2MjIyPv3bs33NP28vn8+Ph4GxubhoaGmJiYhoYGOzs7PB7f3Nx8/fr1vLw8W1tbVVVV+fbl5eX37t27evVqV1eX/JHq+vr6a9euTZ48+enTp5GRkaWlpS4uLmDYJg6Hc+rUKTMzs/4mKudyuRcuXLh161ZdXR2RSDQwMJCP3tfY2BgXF5eQkCCRSGxsbMBKBoNx+fLlKVOm0On06Ojo169fu7i4yIfHe/PmzdWrV+Pj49lsNp1Ob2pq+vLLLwcoraOj49KlS97e3omJibdu3fLx8Rm+sQPxePzkyZN/+uknMMPG0AvcsWPHzZs3Hz58GBwcPPTShg7butTa2nrmzJkFCxZ4enoOUP7A9afP2piQkJCYmFhUVOTp6cnhcM6fP5+Zmfn69WtnZ+cBDtRfaeCtPmtjbx9Un5OTk0NDQ8Visb6+PpPJBEOQ9ncgLpcbGxsbFxfX1tZmbm6upqbWe3eZTJaSktLW1mZmZgb24nA4f/75582bN6uqqgwNDeXDFQ38qWLOycnJ399/7969QqGw55jqmGR46P0FBQUtXLhwiIXMnj1bIX2aBpaSkgJGWTp+/PiGDRu2b9+urq6+ePHi6OjolStXLl++HIfDzZ8/X779yZMng4KCZDJZTU3NhAkTzpw5g6LotWvX9PT0yGTyxo0b16xZExISgiCIt7c3eFQjPj4eQZBt27b1GcCbN2/s7e1TU1O5XO7ChQvBjl9//TWKoklJSevXr8/JyYmNjdXU1Ny8eTOKon/99ZehoSGCICdPnvziiy/mzZuHIMiBAwdAaaWlpd7e3pmZmWKxODIyUlVV1d7eHrzVZ2mXL19WV1cnEAj/+7//6+bmhiBIfn7+MH7cKIqi6Mcff7xgwYKhl5Obm4vD4X7//fehF6UQmNelHi3UPssfuP4MUBudnJzMzc3BZp2dndra2r6+vgMcaODS+qyNvX1ofc7NzfX39zc0NExOTgZ3Fvo7UElJSUhISH5+vlgs/uyzzwwMDKqqqnrsTqfTlyxZgiCIfGiavLw8FxeX+Pj4lpaWY8eOaWpqguvDA3+qyiMqKgqPx/fo+gsTqlJraGjA4/FDvAQnFovV1dUvXLigqKgGcOLECQRB4uLiwMudO3ciCBIfHw9e7t69W1VVVX6J0tbWNiIiAiyHhoaGhISA5VWrVuFwuKKiIvByz549CIKcO3cORVEejxcdHd3Y2Njn0Xft2mVlZQWWX716Bf4nURTlcDg2Njbym4Jr165FECQrK0se4ZMnT8Bbnp6eXl5eYHnq1Knyb1uZTGZjYwO+gAYobeXKlQiC3Lp1C0XRkpKSwX6KH+D06dM6OjpD7zq0ceNGV1dXhYSkKNjWpR4Jtb/yB6g//dVGFEWXLFkiT6hgL3lC7e9Ag6jbPQyiPoeGhlpYWID1/W0mkUjc3d2joqLksZFIpISEhB67oyhaUFAgT6hCoZBGo/3000/yd1esWEEikeh0+sCfqvKQyWQODg5fffVV95VwyE2lFhMTo6Oj8/HHHw+lkLa2Nh6PZ29vr6ioBgAu2ri4uICX4DIRaK4hCEKj0YRCYWNjI5ieLCUlBcwdXVxczGAwOjs7wWYaGhoEAsHJyQm83Llz58GDB1NTU8PDw8lk8rp16/o7elVVVWtrq0gkIpFIbm5uGhoaYNrq69ev8/n87du3g82YTObEiRMrKyt9fHzIZDIIDLzl6OgIJppNSkp6/vz53r17wXocDuft7Z2XlzdwaaampgiCfPrpp93LHFb29vZsNpvFYvV3Dfw95ebmKsmVXjls61IP/ZXfX/1B+q+NgzvQIOp292IHV5/BlmB9f5u1trbm5eXNnTsXrAfXseXzJXe/Ttv9+vyDBw9KS0u7BzlnzpyYmJgLFy4cP358gE9VeeBwuODg4Nzc3O4rYUJVatevX1+8eHH3ijgIoE7LZDIFBfUBekztC+5ddXV1gZdmZmaPHj26e/fu9OnTJ06cCM67e1NXVzc3N29tbX3n4T766KPY2Nj09PQZM2Z0dHSIRCKQJOh0uomJyenTp99ZgoqKCoqiCIKATp7y21pIt6+GAUoD97RGcs41EK3y3F4aPiNcl3p4z/Ll9QfpvzYO7kBDrNuDq8/vs9n+/fs1NDTARVpAnk2R/mtmcXExgiCampryNYGBgQiClJSU9N64+6eqVHpHBROq8iotLc3JyTl69OgQy6FQKOrq6hUVFdOmTVNIYIqyZ8+ep0+fPnz4kEwmgxtafRIKhU1NTXPmzHlngevWrausrNy4ceO//vWv5OTkgwcPgsa9iopKWVmZWCx+/wnpQMvg+fPnFhYW8pXg22EQpQ2f8vJyHR2doU8+5eHh8ejRI4WEhAmF16XBld9df7VxcAcaYt0edH2WZ8T+NpPJZF1dXcnJybNnzx5g9x709fURBMnKygJ5FEEQKysrIpE4xAstIwlF0cePH4Mb83Kjafri8eb69esmJibTp08fYjkqKiqBgYEJCQkKiUpRampq9u/fv2rVKnB5Z4AG9LNnzwQCAeibMDACgWBiYnLp0iVXV9eTJ09+9913YL2bm1tXV9e5c+fkW7JYrDNnzgxQFLjSmJSU1PutQZQ2fBISEoKCgobeQt20aROdTr9y5YpCohphw1GXBld+d/3VRvCWQCD4oAMNsW4Prj7jcDipVDrwZqDkmJgY+fr29vbbt2/32L2HqVOnIgiSmpoqX1NUVCQWi319ffvcXglFRUVVVVWFh4f/n7Ujfy8Xek/29vbffvutQor6448/VFRUSktLFVLaAE6dOoV0690aHR2NIMiLFy/AywsXLsjfBT0UgoKC2Gx2amqqiYmJvr4+h8Pp7OwMDw/H4XDy7nNbtmyZPn06WKbT6T4+PocPH+7z6GfOnPHx8UlOTi4oKCgvL5fPFCEQCCwsLEgk0pEjR4qLi2/cuBEWFgbeBV9M8tma5s6dq6WlJZPJxGIxjUbT1NR8+vQpiqINDQ0mJiaampr5+flcLre/0rZs2YIgyIgNkpyXl4fD4f766y+FlLZt2zYNDY3U1FSFlDZ02NalzMxMBEFOnTo1cPn91R+0/9qZttRpAAAgAElEQVSIoujFixcRBLl48SKXy7148aKVlRWVSn3z5s0ABxpE3e5ucPV58+bNRCKxqqqqsrKyvb29z80kEomHhwfydrbmEydOLFiwQCAQ9Nidy+WC3+6f//wnCOnzzz/X0tJ6/fo1eHn69Gk7OzuhUIj2/1/5gTVoGP39999kMrl7pyoAJlQl9fLly+5fH0MEeuLNnDlzWAd2yMzMBH1GPv/88+rq6uTkZPAM39y5c+l0emZmJuiDsHTpUjD36po1awgEgq2t7blz527evEkikWbMmNHe3h4eHq6iorJly5Zt27YtX758/vz58i+IxMREHA5HJBJZLFbvAG7fvg06dMjNmjWLyWSiKFpcXCzvluXk5JSTk4OiaEpKCniWbt26dUwm8/r169ra2giC7Nu3TywW19TUeHt7IwhiY2OzYsWK+fPnBwQEnD17ls/n91na+fPnwQN2S5cuHYG5SyUSSUBAwNSpUxX1RSMSiRYvXqyhoQF6KWML27r0/PlzcFnYw8MDDJXXZ/m3bt0aoP4MUBs5HA6If9KkSbdu3Vq0aNGcOXPAqEz9/SIfWrd7+9D6jKJocnIygUDQ1dUF45X2t1l9fX1wcDAOh8PhcEFBQfI5PLrv/uzZM/DYjLOz8927d1EU5fP5ERERTk5Oly9fPn/+/Ny5c+vq6tB3/VcqrooN3h9//EEmk1esWNF7sCSYUJXUzp07FTvQ3cuXL1VVVXufUmGr+6k0OKtFUTQ8PJxIJKIoWldXx2aze+zS1ta2adOmPs8MHj16dOnSpYqKirS0tIcPH966dWvFihUHDx6Ub1BbWys/I35PLS0t4FEBDofT461BlKZA33//PZlMVuyjrmKxeOPGjTgc7ssvv8Rq4tVBU2xdes/yB/DO2tjS0gIW+Hz+Ow+kqLr9ofWZxWL1qAn9Haijo6P3PPO9d++9QUZGxmgZMZ/FYoFBnrdu3QqHHhxNaDSaoq73ykVHR+NwuBMnTii2WIWTfwn2KSkp6fLly73XZ2dnm5qa9qjlHR0dkZGRig8RawcOHMDhcMM0nW1MTIyBgYGZmdl//vOf0T5W5eDq0tAptjaOq7qtnCQSyeXLl42NjY2MjG7evNnfZjChKqOKigoEQcDdDsU6duwYDoeLiIhQkosnffrHP/6Bw+F6n0GjKCoWi/ubUevixYs4HO7cuXOVlZVisbiiouI///nPjh07+rw4PHoJhcL169fj8fjTp08P31FaW1vXrFmjoqLi7Ox88+bN0ZtWB1eXhk6xtXGc1G3lJBaLY2JiaDQagUAIDw9/8+bNABvDhKqMjhw5YmBgMEw57+bNmxoaGjNnzlTOmR+uXbtGpVIRBNm8efMHTaUik8mOHz8eFBSkqqqqoaHh4+MTGRkJ+jiMGc3NzdOmTdPS0lJUR6SBFRcXh4WF4fF4GxubX3/9deCvEiU06Lo0dIqtjeOhbiuhtra248ePW1lZqaiorFixoqys7J27wISqjPz9/T///PPhKz83N9fS0tLQ0PD3339Xqr5zKIqyWKyOt3g83iBKACO1jjEymez8+fP6+vo2NjaFhYUjeejy8vLNmzdraGioqqouWrTozz//HC1f5UOvS0On2No4Juu2shEIBDdv3vz0009JJJKmpubWrVurqqrec1+YUJVOc3OziorKcPe0ZLPZW7ZswePxM2fOfJ8zLwhDRUVFgYGBBALhm2++6fPq5Qhgs9mXLl2aMWMGHo83MDDYvHlzRkbG6L0UDEE9SCSSp0+fbtiwQU9PT0VFJTg4+MqVKx/67wYTqtI5f/48mUwememdc3JyJk+ejMfjw8LCYFpVQlVVVRs2bCAQCB4eHop6hmqI6uvrT506BR5iMTAwCAsLi4yM7G+IeQhScq2trbGxsRs2bDA2NkYQxNHRce/evTU1NYMrDYcq5RiJ49nChQslEsmIDWwkkUhiYmL+9a9/VVdXr1y5cteuXWAUcghbdDr9wIEDN27ccHBw+PHHH5ctWzaSQwS/j+Li4vv37ycmJqanp0ulUm9v75CQkDlz5nh6ehIIcExTSHmJxeLs7OyHDx8mJiZmZ2cTicRp06Z98sknc+fOHeIkIjChKheJRGJgYHDw4MHNmzeP5HFlMll8fPyePXvKysq8vLy2bt26fPny7oNcQyNDJBLduXMnKirq77//njRp0o4dO1auXKmiooJ1XAPh8XiZmZkJCQm3b99mMBjq6uoeHh4BAQH+/v4BAQGjaHRWaAzjcrl5eXkZGRnp6elpaWlsNptKpc6ePXv+/Plz5swBY0cMHUyoyiU9PT0wMLCiosLW1nbkjy6VSh88eHDu3LnExERDQ8Mvvvhi1apVjo6OIx/JOFRYWHj16tXLly93dHTMmzdv48aNwcHBytYqfaeSkhLwnZWenl5VVaWiouLm5hYQEODj4+Pp6WlnZzfqfiNolJJKpeXl5Tk5Oc+ePUtLSysqKpJKpfb29n5+foGBgf7+/sNxKQ4mVOWyd+/eK1eu1NbWYhsGg8GIjo6+ePFiQ0ODk5NTWFhYWFgYzKzDobCwMC4uLi4urrS01NLScu3atevWrQPzqo52TCZTnlwLCgrEYrGmpqabm5uHh4enp6eHh4eTk5MyzNgDjQ0ikaioqCj3rfz8/K6uLiKR6OHhAS6W+Pv7g8eohg9MqMrFz8/PxcUlMjIS60AQBEFkMllGRkZcXFx8fHxjY6OTk9P8+fNnz57t5+c3xClaxzmBQJCRkfHo0aO//vqrtLTUwsJi8eLFYWFhvr6+Y3VmU6FQWFhYmJubm5OTk5ubW1hYyOPxSCSSs7Ozq6srjUaj0WiOjo7W1tbw/iv0PiQSSXV1dXFxcWlpaWlpaUFBAZivRkNDw9XV1eMtFxeXkbx1BROqEmGxWIaGhtevXwejSCsPmUyWmZl58+bNxMTE8vJyDQ2N6dOnz549Ozg4eNKkSWM1BygWiqJ0Ov3x48ePHj1KTU3l8Xg0Gi0kJGTx4sVjOI/2RyqVlpaWgpZEUVFRaWlpXV0dgiAkEsnOzm7SpEkODg5OTk4ODg62traKur8FjV5sNruysrK0tLS4uLisrKykpKSyslIkEuFwOEtLSxqN5uLiAjKovb09hn0OYEJVIrdv3w4LC2tpaQGz7yqnpqamR48e3b1798mTJx0dHdra2lOmTPH39/fy8po2bdrQZ7oeS7q6unJzc1+9epWRkZGcnNzW1qapqRkUFAT6QVhZWWEdoBIRCoWVlZXFxcXV1dV0Or24uLi4uJjP5yMIoqenZ/OWiYmJqampjY2No6MjmDQUGkvEYjGDwah+q7GxkclkgmUEQYhEooWFhaOjo5OTE6gD7u7umpqaWEf9XzChKpHNmzdnZ2e/ePEC60Dei1QqffXqVWZmZlZWVmZmZn19PYFAcHNz8/T0dHV1dXNzc3V1HW/5lcVi5efn5+fnFxQU5OTkFBYWSiQSS0tLPz8/X19fPz8/Dw8PJe+yqzwkEklVVVVVVVVNTU11dXVNTQ1Y6OzsRBBERUXFwsLCysrKwsLC1NTUzMzM3NzcxMTE0tKSSqXC68bKTCwWNzc319XVMZnM+vr6hoYGJpNZV1f3+vXr+vp6MCe5rq6utbW1tbW1jY0NWLC1tVX+OwIwoSqRSZMmLVy48MCBA1gHMhgMBiMjI+P58+cgo7x58wZBEGtrazc3NycnJzs7O3t7ezs7OwqFgnWkCtPa2lpeXl5eXl5RUVFUVFRQUPD69WsEQQwMDNzd3d3c3Hx8fPz8/MAkqZCitLe3y1Ms+ApuaGhobGxsbm4G32Z4PJ5KpcrzK4VCMTQ0NDY2NnzLwMAA619ijGtra2t9q6mpqa2traWlRf6XampqAn8pHA5nbGxsZmZmampqYWFhaWkpT5/KfJVuADChKovW1lYqlXr//v2PP/4Y61gUgMFggIZafn5+SUlJRUWFQCBAEERPT8/Ozs7Ozm7ixInm5uZmZmaWlpZmZmbK/LTimzdvGhoa6urqGhoa6uvrq6qqKioqKioqWCwWgiBkMhnc9nN3dwdNc5hBMSESiZqamhgMRmNjY2NjI4PBYDKZDAYDfK23t7fLtyQSiSDLUqlUIyMjCoWir6+vq6urq6urp6en+5aenp5SXU7EHIfDAcMjs94Cyx0dHa2trc3NzS0tLSCVSiQS+V7gozY0NLSwsDAxMQH/9SCDGhsbj7Fu3jChKov4+Phly5a1t7ePycukMpmMwWBUvFVeXl5bW8tgMMDlOwRB1NXVLS0tjY2NqVQqhUIxMDCQ/zQyMtLW1tbW1lZXV1dXV1dgVF1dXXw+v7Ozk81mt7S0tLe3t7W1gZ9tbW3Nzc1NTU11dXXgTh6CIDo6Oubm5jY2NuCcALS5zc3Nx1uXotFIIpGAzNrS0tLS0gKWm5ubwYI8Scj/1gCBQJAnVx0dHS0tLTKZrKmpCRY0NDR0dHTAgra2tnwNHo8nk8lqamo4HE5XVxerX7mHjo4OBEH4fL5AIJBKpZ2dnVwuVyAQgAU+n8/hcDgcjkAgAAt8Pp/L5XZPnOBirByZTAafjJ6eHvg/pVKphoaGFAoFnKmAZSW/SKtYMKEqi6+//jotLe3Vq1dYBzKiOBwOg8EA14Lq6uqamprASa48t3U/1QV0dXXJZDKZTAaNWlVVVXmWxePx3U9HwGyRYJnH44E5UlgsFo/H4/P5bDa7R8lEIlGeyA0MDKhUqrGxMWhAm5ubW1paamhoDNcHASkHgUDQo/klX2az2d0TT0tLS0NDg6amplAo7OrqGrjYHvkVvARv9Zd01dXVez+cJhQKeTxe7427V3WBQABOC0AGlb8cgIaGBplM1tbW1tTUJJPJWlpaWlpa6urqGhoafTbcwQJ8dq43mFCVhaen57Rp006dOoV1IMqFxWK1trZ2dnZ2dnbyeDwejyfPiOCKK8iUYGOxWMzlcsEyk8kUi8Vubm7gpTzv6urqqqurg5Nr+feItra2kZHRmLw2AClce3v7119/fe3atRUrVvz222/gjiybzQbVEqSxrq4ukUgEGoL9vQSl9Zcj2Wy2TCbrsbLHKaOchoaG/GlLEokEzvxAW7nPlyCLg38EWO0VCCZUpdDZ2amvr3/jxo3FixdjHcsYsXfv3ps3b9LpdKwDgcaUhISEjRs3ymSyM2fOLFy4EOtwIOUCx9VUCmBqST8/P6wDGTuoVGpzczPWUUBjR3Nzc1hY2Keffjpz5kw6nQ6zKdTbOLpdrMzS09Pt7e1NTEywDmTsoFKpb968EYvFY6wbIYSJuLi4TZs2aWlpPXr0aNasWViHAykp2EJVCs+fP/f19cU6ijGFSqWC2YOxDgQa3RobG0NDQ5ctW7Z48eLCwkKYTaEBwISKPRRFX716NWXKFKwDGVPAtBLwqi80aCiKRkVF0Wg0Op2elJQUGRkJH0uFBgYTKvZKS0tZLBZMqIoFEyo0FNXV1bNmzYqIiNi8eXNhYWFQUBDWEUGjAEyo2Hv58qWqqqqLiwvWgYwpYCAImFChDyWTyaKiolxdXVtbW7Oysg4dOiR/ZhSCBgYTKvZevnzp4eEBn5JWOCMjI5hQoQ9Cp9N9fX23bNmyZcuW7OzsyZMnYx0RNJrAXr4Y2LVrF5vNdnV1dXFxcXZ2fvHihY+PD9ZBjUHwyRno/UkkkuPHj+/du9fDwyMvL8/R0RHriKDRByZUDHR1dZ07dw6Px4OxMdXU1CQSyQ8//ABSrL29PXzSQyFgQoXeU35+/po1a0pKSn7++efvv/8eTrEHDQ5MqBhwdHRUUVGRj1IrEAhyc3PpdLpYLJbJZHp6etXV1cozpvboRaVSa2pqsI4CUmoCgeDQoUMHDhzw8fHJy8uzt7fHOiJoFIP3UDHg6OjYY8x3FEWFQqFMJsPj8d988w3MpgpBpVKbmpqwjgJSXpmZmR4eHidPnjx69GhKSgrMptAQwYSKgf5uz+BwOAqF8u23345wPGMVvOQL9YfH4+3cuTMwMNDa2rqoqOirr77C4+GXITRU8JIvBigUio6OTu/pw3A43LFjx+AcYYpCpVLBBHDjakZG6J0ePnwYHh7OZrPPnj27YcMGrMOBxg54UoaN3o1UAoHg6Oi4cuVKTOIZk6hUqkwma2trwzoQSFmw2ezw8PBPPvnExcWFTqfDbAopFkyo2HBzc+vRlVcikZw6dQped1IgOFgS1N29e/ecnZ3v3LkTGxubkJBgamqKdUTQWAO/vrExadKk7i+JRCKYFgqreMYkmFAhoKWlZfXq1fPmzfP19aXT6UuWLME6ImhsgveWsOHo6CgWi+UvZTLZ0aNHMYxnTNLV1VVTU4MJdZyLi4uLiIggEol37txZsGAB1uFAYxlsoWKj+z1UIpG4detWOzs7DOMZqwwNDWFCHbeYTOaiRYuWLVu2cOHC0tJSmE2h4QZbqNgwNTXV1NTkcrkIgqipqe3evRvriMYm+OTM+ISi6NWrV8Ej3U+ePJkxYwbWEUHjAmyhYsbBwQFBEBUVlV9++cXAwADrcMYmmFDHoZqamtmzZ3/xxRdLliwpKCiA2RQaMTChYsbd3R1BEDMzs02bNmEdy5hlbGwME+r4AaYEd3V1bWpqysrKioyMhE91QyMJXvJ9X3w+n8PhdHZ2stlssVjM5XJ7/5RIJBwOB0EQqVTa2dnZowSwmfxleXk5giA0Gm3r1q3dNyOTyWD+RTU1NTKZrKqqqq6u3vunurq6tra2lpaWtrb2sP/yoxaVSs3OzsY6CmgkVFZWrlu3LjMz89tvv/3555/hfIjQyBvXCZXP57e1tbW3tzc3N7e3t7e9xWKxQO7kcDhsNhu87J4LuyMSiZqamgQCQUtLS0VFRZ7edHR0ejxUChKk/KW2tjaFQpHJZNXV1d0343A4YKRfPp8vEAgEAgGfzxcKhTwer79fRE9PD2RW8FNbW1tXV1dfX9/Q0JBCoRgYGFAoFAqFYmRkNN6yL7zkOx6Amdf27dtHo9GePXvm6emJdUTQODXGE2pra2tTUxODwWhqaqqvr2cymQ0NDU1NTS0tLW1tbV1dXfItiUSiPPfo6enp6+tPmDBBS0tLR0dHV1dXnqvAGhKJpKGhAVLpoGOrq6trbW318vJ6/11AWhWJRF1dXTweD2T9zs5OFosFFuRramtrc3JyWltb29raumdiEokEfk0TExMTExNzc3NjY2MLCwsTExMzMzMqlTrGRumjUqmtra1SqRROyDVWFRQUrF27tqioaN++fXDmNQhbY+HbE0XRhoaGmpqa6urq6upqsNDQ0MBkMoVCIdhGQ0PD3NwcpBB7e3sqlUrpxtDQcOQneLG0tLS0tPygXVRVVQdxIYvH47W1tbW2toL8CtrijY2NTU1NOTk5TU1Nra2tYEsVFRUqlWpmZmZlZWVtbW1jYwN+WllZkUikDz2uMqBSqVKp9M2bN4aGhljHAimYWCw+ceLETz/95O3tnZubS6PRsI4IGu9wKIpiHcOHaWxsLCkpKSkpKS0tBRm0trYWJE5VVVVra2uQA8zNzU1NTc3MzEASHW+XOj+IUCgEbffGxsbGxsb6+vra2lpwatLR0YEgCB6PNzc3Bx+svb39pEmTHB0dra2tlb85W1JS4ujoWFBQ4OLignUskCJlZWWtW7eutrb2p59+2rZtGxyzE1IGyp5Qa2tr6XR6cXFxaWkp+MlisRAE0dfXp9Fotra23RtSpqamOBwO65DHlI6ODnmjH/wsKyurq6tDUZREIjk4ONBoNJBfHR0dJ02apGwp9s2bNwYGBo8fP541axbWsUCKwefzf/7552PHjs2aNSsyMtLKygrriCDo/1O6hNrY2PjqrRcvXrS0tCAIoqen5+jo6OTkBH7a2NjY2NhgHen4JRKJKioqiouLwblOdXU1nU4XCAREItHOzs6rm+6dsDCBoqiamtrFixfhND5jQ1pa2rp161paWg4fPrx+/Xp4Ag0pFewTakdHR0ZGRnp6+osXL3JycthsNoFAoNFoXl5enp6enp6erq6u8IKtkhOJRKWlpTlv5eXldXV1kUgkZ2fnyZMn+/v7g5mcMYnN3Nz822+/hdO2j3adnZ179uz597//HRIScvbsWXNzc6wjgqCesEmo9fX1aWlp6enpaWlpdDodRVEajebr6+vp6enl5eXq6qqurj7yUUGKIpVKy8vLX716lZOT8+LFi+zsbKFQaGZmFhgYGBAQEBgY6OzsPGI3vby8vGbNmnX48OGRORw0HBITE8PDw4VC4dGjR1evXo11OBDUt5FLqHw+PyUl5f79+4mJiVVVVUQi0cvLC7Rd/P39KRTKyIQBjTyBQPDy5UtwCpWRkdHZ2amnpxccHBwSEvLxxx+DSdaGT0hIiJGR0eXLl4f1KNAw6ejo2LlzZ1RUVFhY2JkzZ+AXBaTMhj2h1tTU3L9///79+8nJyQKBwM3NLSQkZNasWVOnToXN0HFIKpUWFhampKQkJiY+ffpULBZ7enqGhISEhIR4e3sPR7P1iy++aGpqSkxMVHjJ0HBLSEjYuHEjiqKnT59euHAh1uFA0DsMV0Jtb2+Pj4///fffMzMzyWSyn5/fvHnzFi1aZGFhMRyHg0YjPp+fkZGRkJBw586d169fm5mZLV68OCwsLCAgQIFH2blz56NHj3JychRYJjTcmpubIyIibt26tWrVqlOnTunr62MdEQS9m4ITKofDuXXrVkxMzN9//62hobFw4cIVK1YEBQWN0mEBoBFTUFAQGxsbExNTU1Pj5OS0YsWKFStWTJgwYeglnzx58tixYw0NDUMvChoZcXFxmzZt0tbWjoqKgs87QaMJqiCNjY179+7V09NTUVGZNWvWlStXuFyuogqHxo/s7OytW7dSqVQ8Hj9v3rzHjx8PscD//Oc/BAJBKpUqJDxoWNXW1s6ePRuHw23YsIHD4WAdDgR9GAXcssrOzv7ss88sLS0vXLiwa9eulpaWx48fr169Gk6cBA2Cl5fXr7/+ymAwbty40d7eHhwcPGXKlNjYWDBhwCBQqVSJRAKGfIKUFoqiUVFRLi4u1dXVycnJkZGRQxkoG4IwMaSEWllZuWDBAm9v77KyssuXL1dXV2/btg3e7YCGjkgkLlmyJDMzMzMz08rKasWKFU5OToPrWAR6EcM5Z5RZVVXVzJkzIyIiNm/eXFRUNH36dKwjgqDBGGRC7erq2r17t7Ozc01NzcOHD3NyclauXEkkEhUbHAT5+vrGxcWVl5eD/uELFiyoqqr6oBKMjY0RmFCVlUQi+fXXX93c3Nrb27Oysg4dOgTnMYVGr8Ek1KSkJBqNdvbs2SNHjuTm5s6ePVvhYY1PXC43ISFhx44dI3nQ6urqNWvW1NfXj+RBP5SNjU1sbGxSUlJNTY2zs/Phw4fR9+5MZ2BgQCQSYUJVQkVFRf7+/tu2bduyZcvLly8nT56MdUQQNCQfnFAPHz48e/ZsX1/fsrKyrVu3Kttg6KPagwcPtm7d+scff4zkQXNyci5dulRYWDiSBx2cjz76KDc395dfftmzZ8+nn37afTrbAeBwOAqFAhOqUhGLxYcPH548ebKKikp+fv6hQ4fggwDQWPBBXZh27tyJx+NPnjw5LB2kIBRdunSpjY3NOze7cuXKUI7SY/fW1tahlDbyMjMzjYyMfH192Wz2+2zv7u6+a9eu4Y4Kek+5ubkeHh5kMvnQoUMSiQTrcCBIYT6ghXr69OkjR45cuXLl66+/Hr4EP87h8fh3jhaUlJS0a9euQR+i9+6jbjg3X1/fp0+f1tbWrlixQiaTvXN7KpUKW6jKgM/n79y5c/LkyZqamnl5eTt27FBRUcE6KAhSGJV9+/a9z3YVFRWhoaF79+7dsmXLMIfUNz6fHx8fb2Nj09DQEBMT09DQYGdnh8fjm5ubr1+/npeXZ2tr2707Q3l5+b17965evdrV1TVp0iSwsr6+/tq1a5MnT3769GlkZGRpaamLiwvoS8XhcE6dOmVmZqanp9dnAH0WiCAIl8u9cOHCrVu36urqiESigYGBPCM2NjbGxcUlJCRIJJIB5pt78+bN1atX4+Pj2Ww2nU5vamr68ssv+yshOTk5NDRULBbr6+szmUwHB4cBDsTlcmNjY+Pi4tra2szNzdXU1HrvLpPJUlJS2trazMzMwF4cDufPP/+8efNmVVWVoaGhjo4OWM9gMC5fvjxlyhQ6nR4dHf369WsXFxes5s+iUCiBgYE//vijoaGht7f3wBs/fvy4paUFzuCGrYyMjLlz56akpBw8ePDs2bOj7jQOgt7tPVuyq1atcnZ2xur6TEpKip2dHYIgx48f37Bhw/bt29XV1RcvXhwdHb1y5crly5fjcLj58+fLtz958mRQUJBMJqupqZkwYcKZM2dQFL127Zqenh6ZTN64ceOaNWtCQkIQBPH29haJRCiKxsfHIwiybdu2PgPos0AURd+8eWNvb5+amsrlcsFYo97e3l9//TWKoklJSevXr8/JyYmNjdXU1Ny8eXOfJZeWlnp7e2dmZorF4sjISFVVVXt7e/BWnyXk5ub6+/sbGhomJyfn5uYOcKCSkpKQkJD8/HyxWPzZZ58ZGBhUVVX12J1Opy9ZsgRBkLNnz4K98vLyXFxc4uPjW1pajh07pqmpCa4P//XXX4aGhgiCnDx58osvvpg3bx6CIAcOHBjiX3aItm/fbmhoCP6CA9i2bZuXl9fIhAT11tXVtWPHDjweHxISAmanh6Ax6b0SqlAo1NTUlH/nYuLEiRMIgsTFxYGXO3fuRBAkPj4evNy9e7eqqqp8NBxbW9uIiAiwHBoaGhISApZXrVqFw+GKiorAyz179iAIcu7cORRFeTxedHR0Y2Njn0fvr8Bdu3ZZWVmB5VevXoF8g6Ioh8OxsbGRjxW1du1aBEGysrJ6lzx16lR5FpfJZDY2NiChDlBCaGiohYUFWN/fZhKJxN3dPSoqSh4biURKSEjosTuKorO9pxsAACAASURBVAUFBfKEKhQKaTTaTz/9JH93xYoVJBIJTLEHPvMnT56At8Bce31+XCOmrq4Oj8cnJiYOvNmxY8fMzc1HJiSohwcPHlhZWenp6UVGRmIdCwQNr/fqo1tXV8flcqdOnaro5vEHABceXVxcwEtwqdPNzQ28pNFoQqGwsbERTDuckpICxmkqLi5mMBidnZ1gMw0NDQKB4OTkBF7u3Lnz4MGDqamp4eHhZDJ53bp1/R29vwKrqqpaW1tFIhGJRHJzc9PQ0GAwGAiCXL9+nc/nb9++HWzGZDInTpxYWVnp4+PTvdikpKTnz5/v3bsXvMThcN7e3nl5ee8sQX6htb/NWltb8/Ly5s6dC9Z7enpyOBx5R8ru12m7Xyd/8OBBaWlp9yDnzJkTExNz4cKF48ePk8lk8FGDtxwdHR8+fNjfJzYyLCwsTExMSkpKPv744wE2o1KpLS0tKIpidYF6fGKxWDt27IiOjl6yZMm///1vIyMjrCOCoOH1XgkVfA2hWExF3h81NbXuL8F9UPlzFGZmZo8ePbp79+706dMnTpwI2o69qaurm5ubt7a2vvNw/RX40UcfxcbGpqenz5gxo6OjQyQSBQcHIwhCp9NNTExOnz49cLH5+fkIgjg7O8vXyL/xBy7hnZvt379fQ0MDXKQFuj+W0F9eKS4uRhCk+5BvgYGBCIKUlJT03lhFRUWpqsQAqFSqSCRisVj93SCHFO7u3bsbN26USqVxcXGLFy/GOhwIGgnv1cvXwsJCU1Pz+fPnwx2NouzZs2f//v2HDx9evHjxAN0IhUJhU1PTAN2F3lngunXrvvvuu40bN8bFxf30008HDx4ETSUVFZWysjKxWDxwsaCl2+ODBdlu4BLkGbG/zWQyWVdXV3Jy8sC79wCGjczKypKvsbKyIhKJSpuHGAxGY2Ojo6PjwJvB0QdHUktLy+rVq+fPn+/n51dUVASzKTR+vFdCJZFIixYtOnPmzKAHKB9JNTU1+/fvX7VqFbhEOcBjFc+ePRMIBKB/zeAKJBAIJiYmly5dcnV1PXny5HfffQfWu7m5dXV1nTt3Tr4li8U6c+ZMj5LBFeykpKTeBx2gBBwOJ5VKB94MlBwTEyNf397efvv27R679wCu6qempsrXFBUVicViX1/f/j8eLP3222+GhoYzZswYeDOYUEdMXFyck5NTamrqw4cPY2NjDQwMsI4IgkbQe95rraysVFVV/fnnn4fvdu7ATp06hSBIfn4+eBkdHY0gyIsXL8DLCxcuyN8FvWyCgoLYbHZqaqqJiYm+vj6Hw+ns7AwPD8fhcMXFxWCvLVu2TJ8+HSzT6XQfHx8wpl0PAxR45swZHx+f5OTkgoKC8vLyzs5OsItAILCwsCCRSEeOHCkuLr5x40ZYWJj8XTmxWEyj0TQ1NZ8+fYqiaENDg4mJiaamZn5+PpfL7a+EzZs3E4nEqqqqysrK9vb2PjeTSCQeHh4IgoSHhz958uTEiRMLFiwQCAQ9dudyueC3++c//wlC+vzzz7W0tF6/fg1enj592s7OTigUoigKTheqq6vBW3PnztXS0pLJZEP8yw5aVlYWiUQCfcoGJpFIVFRUbty4MQJRjVuNjY2hoaFg5rXeVR2CxoMPGCnp7NmzOBzu8uXLwxdNfzIzM0H/o88//xzM7uTp6YkgyNy5c+l0emZmJuhHs3Tp0vLychRF16xZQyAQbG1tz507d/PmTRKJNGPGjPb29vDwcBUVlS1btmzbtm358uXz58+X/+cnJibicDgikchisXoH0F+Bt2/f7jFL3axZs5hMJoqixcXF9vb2YKWTk1NOTk6fv1pNTQ14jNLGxmbFihXz588PCAg4e/Ysn8/vr4Tk5GQCgaCrq/vbb78NcKD6+vrg4GAcDofD4YKCgurr63vv/uzZM/DYjLOz8927d1EU5fP5ERERTk5Oly9fPn/+/Ny5c8FzDikpKeDa+Lp165hM5vXr17W1tREE2bdvn1gsVtyf+n0VFxcbGxvPnz//PSc6NTIyAh8XpHAymezKlSt6enoTJ05MSkrCOhwIwsyHDT34ww8/4PH4Y8eOYdgueU/dz5FBywxF0fDwcCKRiKJoXV1d71Hr2traNm3a1N8XdJ8FPnr06NKlSxUVFWlpaQ8fPrx169aKFSsOHjwo37K2tlbe2htAS0sLePSl96TKfZbAYrF6NAL6O1BHR0d7e/s7d++9QUZGBoPBeGfkmEhLS6NQKP7+/u859CCKoi4uLrt37x7WqMan6urqmTNnEgiErVu3yh/fgqDx6cMSKoqix48fJxAIixYtampqGo6AhpU8ofYpKSnpg9rf2dnZpqamPQa76OjogM/bDR+RSHTgwAECgRAaGtrV1fX+OwYHB69bt274AhuHpFIpmAbc2dlZfvMFgsazD55t5ttvv33y5El2draDg8OpU6fe2ZFVqfB4PIlEwuVye78lkUj4fP7nn3/+/qUVFBQwmczz589XVVVJJJLKysqYmJhDhw4tW7ZMcSFD//XkyRM3N7d//vOfhw4dunXrlrq6+vvvC4fzVazKysqPPvpoy5YtERERr169eufojxA0LgwuD3d1df34449qamqOjo4PHjxQbJIfJteuXQO9PTdv3gwG7RsimUx2/PjxoKAgVVVVDQ0NHx+fyMhI0H8HUqzKykpwrzc0NFTeK+qDfPfdd1OmTFF4YOOQWCwG04C7u7v31zMAgsanQSZUoKqqasGCBQiCuLu7//7770qeS1gsVsdbPB5PgSW/cyxZaNDS09PBs78ODg5DOXU7cuSIfJBIaNDy8/O9vLzgzGsQ1KcPvuTbnY2NzZ07d7KzsydNmrR27Vpra+tDhw61tbUppOmscDo6OrpvgSdKFQWM0wQpkEgkio2N9fHxCQgIaGhouH79Op1OnzNnzqALhJd8h0ggEOzbt8/b21tNTS03NxfOvAZBvQ0poQJeXl4xMTF1dXXr168/evSosbFxcHDw77//3uetSgga2KtXr7766isLC4vPPvvM0NDw8ePHWVlZYWFhQ/z6plKpAoGAzWYrKs5xJSsry9PT8+jRo7/88ktqaioYSRuCoB4UkFABY2Pjffv2vX79+vLly0Qice3ataampqtXr37w4IFQKFTUUaCxKi8v74cffpgwYcLkyZOTk5O//fbb2trahISEWbNmKaR8OFjS4IApwQMDAy0tLUtKSsAsbFgHBUFKCocOz/jmb968uXnz5u+//56ZmUkmk/38/ObNm7dw4UJLS8vhOBw0GvF4vMzMzISEhNu3bzMYDHNz80WLFq1evdrLy0vhx2IymaampqmpqWC4f+h9pKWlrV27trW19fDhw+vXr4dz9UDQwIYrocq9fv36/v37iYmJSUlJXV1drq6un3zyycyZM319fbvPagKNE1KpNC8vLyUlJTExMS0tTSKReHt7f/LJJyEhIV5eXsPX+pFIJKqqqjdu3AC9haGBsdns7du3R0dHz50799y5c2ZmZlhHBEGjwLAnVDmBQJCamgqSa3l5OYFA8PDwCAgICAwMDAgI6D7RGDTG8Pn8Fy9epKWlpaenZ2ZmcjgcCoUSHBwcEhIyZ86cEfvTGxoa7tu3LyIiYmQON3rdv39/48aNQqHw6NGjq1evxjocCBo1Ri6hdtfY2Jienp6WlpaWllZYWCiTyWg0mq+vr6enp6enJ5ipe+SjghRFKpWWlpbm5OTk5OS8ePEiOztbJBJZWFhMmzbN399/2rRpjo6OI3/90NnZedGiRb/88ssIH3cU6ejo2LlzZ1RUVFhY2JkzZygUCtYRQdBogk1C7Y7NZmdkZKSnpz9//jwnJ4fFYoGHDj3fcnV1Vdr5OCFAKBQWFxfn5uaCJJqfn8/j8UgkkouLi7e3t7+/f2BgoJWVFbZBzpw509bWNjIyEtswlFZcXFxERASBQDhz5kxoaCjW4UDQ6IN9Qu2hsbHx1VvZ2dlNTU0Igujp6Tk6Ojo5OdnY2IAFa2tr2EUCK0KhsLKysri4mE6ng59lZWVSqZRIJNrZ2Xm9NXnyZDU1NayD/a8VK1bweLw///wT60CUTlNTU0RExO3bt1etWvXrr7/C81cIGhylS6g9MBgM8K1d8tabN28QBNHV1aXRaLa2ttbW1tbW1jY2NtbW1mZmZvBhc8Vqa2urrq6uqampqakBC2VlZQwGA0EQNTU1Go1Go9EcHR1pNJqTk5ODg4Myf/7ffPPNs2fPsrKysA5EucTFxW3atElbWzs6OnrmzJlYhwNBoxgB6wDewcLCwsLC4uOPP5avaW5uLi4uLi0tLSkpqa6uzsnJqa6uFggECIKQSCRLS0t5crWwsDAxMTE3Nzc1NYUn3QPg8/kNDQ1MJpPBYDQ1NTEYjNraWpBBORwOgiAEAsHc3Bx8sMHBwZMmTXJ0dJwwYYIyp8/e4GBJPdTW1m7YsOHvv/9et27d8ePHYa97CBoiZU+ovVGpVCqV+tFHH3VfyWQy5U2o6urq0tLSpKSk+vp6Pp8PNiCTyebm5iYmJhYWFlQq1cjIyNDQkEKhGBgYUCgUsIDFbzMSuFxue3t7c3Nze3t7W1tbW1tbe3t7Y2Mjk8msr69vbGwEjX4EQYhEIpVKtbCwsLKyCgkJkTf9LSwsxsDwilQqFdxBgFAUjY6O/v777y0tLTMzM6dOnYp1RBA0Fij7Jd8h6ujoaGxsrK+vlze/6uvrm5ubm5ub29raug+OqKKiIs+vOjo62m/p6uqCBS0tLbCgp6eHx+N1dHRwOJyuru5I/jpdXV0ikYjH4wmFQi6X29nZ2dnZyeFw2Gw2mDOcw+GAlWw2W547QfMdUFVVBb+miYkJOL2QN+JNTU2pVOoYHgfn/v37c+fO5XA447wpVlVVtX79+rS0tO++++7nn39WVVXFOiIIGiNGXwv1g+jp6enp6Tk5OfX5rlAobHurtbVVnoHYbHZnZyeTyeyeqLqnpe7kaRVcVdbV1QW9pYhEYo8vbgKBoKWl1X2NQCCQt6HlIfF4PLDM4XDA7K1isRik0j4DUFFR6Z34bW1tfXx8wPkB+GlkZEShUMZzLpGPPjhuPwSJRHL69Ondu3dPnDjx2bNnwzEiFQSNZ2M8oQ5MVVXVzMzsPUeBEYlEoPHHYrFkMhmLxUJRtMdPBEE6OjrA9qAd2b0EPp/fIyu3tLS0trZ2H64WtH3BsoaGBolE6u+nlpYWyJ3wmd33ZGxsjCBIc3PzxIkTsY4FA4WFhWvXri0sLNyxY8cPP/xAIpGwjgiCxppxnVA/CIlEAndbFVhmVFTU999/f+7cOfgI0AgwMjLC4XDjsF+SWCw+ceLETz/95OXllZOTM2nSJKwjgqCxCSZULNnb23M4nKamJhMTE6xjGfuIRKKent54S6h5eXlr1qwpKyv75Zdfvv/++9HVMRuCRpcx2wNlVADzSpaVlWEdyHgxrjr6gpnXJk+erKWllZeXB6cEh6DhBhMqlkxMTLS1tcvLy7EOZLwYP4+ipqene3h4nDt37syZMykpKXZ2dlhHBEFjH0yoGLOzs4MJdcSMh4TK4/F27tw5ffr0iRMnFhYWbtiwAd6hh6CRARMqxhwcHGBCHTFjPqE+ePBg0qRJUVFRZ8+evXfvnoWFBdYRQdA4AhMqxuzs7OA91BEzhhMqi8UKDw//5JNPpk6dWlZWtmHDBqwjgqBxB/byxZiDg0N1dbVYLB4DY/spv7GaUBMSEjZt2iSVSuPj4xctWoR1OBA0TsEWKsbs7e0lEklNTQ3WgYwLVCqVy+V2dXVhHYjCNDc3L126dMGCBX5+fnQ6HWZTCMIQTKgYs7e3x+Fw8KrvyACjD7a0tGAdiGLExcU5Ozu/fPny0aNHsbGx+vr6WEcEQeMaTKgY09LSMjExgf2SRoZ8OF+sAxkqJpMZGhq6bNmyRYsWFRQUBAcHYx0RBEEwoSoBe3t7mFBHBpVKHe2jD6IoGhUVRaPRioqKkpKSIiMje8y4AEEQVmBCxR5MqCNGVVVVW1t79CbU6urq4ODgiIiI//mf/ykoKAgKCsI6IgiC/gsmVOzZ29vDe6gjZpR29JXJZFFRUW5ubi0tLZmZmb/++qu6ujrWQUEQ9H/AhIo9BwcHJpPZ2dmJdSDjgrGx8ahLqHQ63c/Pb8uWLREREdnZ2d7e3lhHBEFQH2BCxZ69vT2CIBUVFVgHMi6MrhaqRCI5fPiwl5eXSCR6/vz5oUOH4DymEKS0YELFno2NDZFIhLdRR8YoSqj5+fk+Pj4///zzzz///PLlSw8PD6wjgiBoIDChYo9AIFhbW8PbqCNjVCRUgUCwb98+b29vMpmcm5sLZ16DoFEBDj2oFOAQ+SNAIpG0tLSIRKKGhoYrV640Nzc3NTW1tLRQKJRTp05hHd1/ZWZmrl27trGx8ejRo19++SUeD896IWh0gAlVKdjb26ekpGAdxdjEZDJnzZrFZDI7OjrkK9euXQvafGKx+KuvvsIuuv+Dx+P98ssvx44dCw4OfvjwoaWlJdYRQRD0AeDJr1IAj6KiKIp1IGOQiYmJmZkZm83uvlIqlYpEIpFIhKLoRx99hFVs3aWmprq7u0dGRp45cyYxMRFmUwgadWBCVQr29vYcDqepqQnrQMamHTt2yGSyPt/C4XCBgYEjHE8PbDY7PDw8KCjIwcGhqKgIzrwGQaMUTKhKwcHBAUEQ2C9pmMycOdPFxaXPfj1OTk56enojH5LcvXv3nJ2d79y5Exsbm5CQYGZmhmEwEAQNBUyoSsHExERbWxv2Sxo+O3fu7N1IJZFIc+bMwSQeBEE6OjrCw8PnzZvn6+tbVFS0ZMkSrCKBIEghYEJVFnZ2djChDp+lS5eamJjgcLjuK0UiEVbD4cbFxTk4ONy9e/fPP/+MjY2lUCiYhAFBkALBhKos4JMzw4pAIHz33Xc9HkHB4/EBAQEjHElTU9PixYuXLVu2cOHCkpKSTz/9dIQDgCBomMDHZpSFnZ3d9evXsY5CeclkspcvX6amppaXl4MuuxQKxdHRMTAw0NXVtUfTs0/r16/fu3cvl8uVr3F2dtbV1VV4qKWlpTQarc+34uLiNm7cqKur++TJkxkzZij80BAEYQi2UJWFg4NDdXW1WCzGOhClw+Pxjh07NnHiRB8fn5MnT9bW1oL1JSUle/bscXd3NzMzW7t27c2bN3s8G9ODlpZWREQEkUgEL4fpBmpubq6Xl1dmZmaP9bW1tbNnz16+fPmSJUsKCgpgNoWgMQiFlEN2djaCIGVlZVgHolweP35saWmpqan57bffFhYW9nhXKpW+evVq//79fn5+KioqRCIxKCjo8OHDvbcEGhoaCIT/XpW5d++eYqPt6OiwsLBAEGTixIl8Ph+slMlkkZGRmpqaTk5Oz549U+wRIQhSHjChKovOzk4cDvfXX39hHYgSOXbsGB6PX7JkSVNT0zs3bm9vj4mJWbVqlaGhIYIglpaW4eHhd+7c4XK53Tf7/PPPQSNVRUWFzWYrMFqZTLZgwQJQOIFA2LVrF4qiFRUVQUFBBAJhx44dAoFAgYeDIEjZwISqRExNTY8dO4Z1FMriyJEjOBzuxIkTH7qjVCp99uzZTz/95O3tjcfjVVVVg4ODT548CVr/BQUF4Iaru7u7YgM+ePBg905PeDx++/btampqkydPzs/PV+yxIAhSQjgUDnenND766CN7e/vIyEisA8Fe4v9j797jYswb//G/p6bzCRUliWg6KYdKkYQOzFS0lohkb5awFnt/WHYt696TPbCsXSw5reM6U5nRgQ5b1G45lIqidC41dK6pOfz+uH533+62rMPMXDP1ev7hMdc147peNcxrrtP74vH8/f1//PHHtxxo99mzZ9evX+dyuTExMS9evBgxYgSHw0lOTqZu4fLtt99KK3BCQoKXl1fnS12ZTKaJicmqVas2bNjQeT8zAPRWOClJgVAj+tKdgn6NjY3Lli2bP3/+2w9bP3DgwNDQ0N9//726uvqPP/4ICgr6448/7t69SwiJj4/ft29fYWHh2weuqqqaO3dulzONhUJhRUWFUChEmwL0EdhCVSA7d+7cuXNneXk53UFo9s033/zwww95eXnU0VCpKysr8/DwGDVqVEJCQkNDg42NjZ+fH5vN9vDwUFdXf92lCYVCT0/Pv/76q9sztJlM5t27d0eNGiWN4ACg0LCFqkCsra0rKirq6+vpDkInkUj0yy+/rFixQkZtSggxMzOLjIyMiIioqam5ceOGv78/j8fz9vY2NDScPXt2eHh4aWnpqy/tk08+SUtLe8n1TosXLxaJRNIIDgAKDVuoCiQvL8/a2jo9Pd3JyYnuLLRJSkry9PR89OgRi8WS53qfPn3K4/G4XO7Nmzebm5sdHR05HA6bzZ44ceJL9tlevnz53Xff7ek/kYqKiqqqant7++7duxXnrqsAICMoVAUiFAq1tbV/++234OBgurPQ5uuvvw4PD+8YvUH+WltbExMTuVwul8t9/Phxv379fH192Ww2m80eNGhQ51c+fvx4zJgxzc3Nnf8TMRgMVVVVoVCoqanp5ubm6ek5adKkyZMnv8HOZABQLihUxWJtbR0cHLxt2za6g9Bm4cKF9fX1kZGRdAchhJD8/HyqWZOSkgQCwbhx4zgcDofDcXFxaWtrc3Fxyc3NFYvFDAZDRUVFJBLp6upOnjzZy8tr8uTJY8eO7faGcQDQW6FQFcvMmTN1dXVPnz5NdxDacDgcExOTI0eO0B3kf7S0tKSkpMTFxV25cuXRo0eGhoZ6enrUZrSBgcGUKVOmTp3q6enp6OjYZfx9AOg78J9fseDKGYFAoKGhQXeKrrS0tLy9vb/99tuHDx8+efJk3rx5AoGAyWSqqKiMHDnSxsbGyckJbQrQx+H/v2KhChW7DRSZpaXl3r17y8vL6+rqoqOj3d3dT58+7eHhYWJiEhQUdPz48RcvXtCdEQBogEJVLCwWq6GhobKyku4g8M+0tbW9vb1/+umn4uLiJ0+ebN68+cWLF++//76xsbGzs/O2bdsyMjLw3Qig70ChKhZra2tCyKNHj+gOAq/H0tJy7dq1sbGxz58/v3z5spOTU3h4uLOzs6mpaWho6Pnz519+azkA6AVQqIrF1NRUX1+/jx9GVWq6uroBAQEHDhwoKyt78ODBRx99VFFRsWDBAiMjo0mTJn333XcZGRl0ZwQAmUChKhwrKysUau9gb2+/cePG2NjYysrK06dP29vb796929nZ2dLSMiws7Pz58w0NDXRnBACpQaEqHGtraxRqL2NoaDh37twDBw6Ulpamp6eHhYVlZ2fPmzdv4MCBPj4+3333XW5uLt0ZAeBtoVAVjpWVFY6hylpBQcGSJUtea8xeqVBVVXVyctq4cWNycnJVVdXx48dNTU2//fZbOzu7ESNGhIWFRUZGCgQCOacCAKlAoSoca2vrgoKClwy2Dm/vzp07R48ezcrKojGDsbHx3Llzjx8/XlNTk56evmjRooyMjFmzZg0YMMDHx4c6eZjGeADwujBSksLJyMhwdnaW/+jwCsLLy4vFYu3fv1/WK6qpqTEyMpL1Wl5XUVFRxxj9TU1NDg4ObDZ77ty5zs7OdEcDgH+ALVSFw2KxGAwG9vrKmgK2KSHEwsJixYoVERERfD4/Ojray8vr0qVLLi4u9vb2u3btamtrozsgAPSox/tSAV309PRMTU1xXpJUnDhxosu9SB0cHJycnMRicWJioq6urouLCyGktLQ0IiJi5cqViYmJ0dHRZmZmS5cu1dLSoik1IYRoaGj4+vr6+vru2rUrLS3txIkTW7ZsOXDgQHh4uIeHB43BAKAn2EJVRBjRV1p27drVr18/JyensWPHfv/996tWrdLV1c3JyZk3b960adOoS0JPnTrl6Oi4fv36VatWnThxIjMz88MPP/T09FScw9iurq6//PJLbm6ujY3NjBkzbt++TXciAOgGClURoVClZd26dYGBgQ4ODqmpqbm5uV9++aW1tbWdnd3WrVs7XrNw4UI/P7/W1tbVq1cfPnz42rVrW7Zs+euvvxTtjjfm5uaXLl2aMWPGggULumx2A4AiQKEqIhaLhWOoUhEaGkoIKSkp2bBhw8SJEz/66CNqfpcb2ujo6DCZTHt7e2py06ZNTCYzKSlJzmn/kYqKyscff/z06dOSkhK6swBAVyhURWRtbV1RUVFfX093kF4iLCxMKBQePXr0FW+vpq2tPWTIkOrqalkHewNJSUna2toDBw6kOwgAdIVCVUTUBTP5+fl0B+kNjh8/zuPxvvzyy1e/DEkgEFRWVlpaWso02Bs4duzYp59++vnnn2tra9OdBQC6QqEqIktLSzU1NRxGfXuVlZXr1q3rvLM3NTX1H/9Wampqa2urv7+/jNO9KrFYnJCQ4OXltXTp0o8//vjjjz+mOxEAdAOFqoiYTObw4cNxGPXtrVq1qrW1tWNnb1tb26lTpwgh1PB+NTU1Ha8UCoUdA+peuHDB09OT9kIViUQpKSmffvqppaXl1KlTBQJBWlra119/TW8qAOgJrkNVUBgi/+1dunTp8uXL1tbWP//8MyGktbU1PT19woQJaWlpO3bsIIScPXt27Nixfn5+hBAVFZV9+/ZpaWmVlJQ0NTVFRkbSFbu6uvr69etcLjcmJub58+eWlpbz588PDQ21s7OjKxIAvAoUqoJisVgJCQl0p1Bus2fP7mlkzfPnz3eZo6Ki8vPPP5eUlBgYGOjr68s+XVfZ2dlRUVFxcXHU++7q6vrxxx97e3s7OTnJPwwAvAEUqoJisVgHDx6USCQMBoPuLH2Iubm5PFfX2NgYHx8fFRUVFRVVXl4+aNAgX1/f06dP+/r6GhgYyDMJALw9FKqCYrFYDQ0NlZWVpqamdGfp/Zqbm4VCYWNjo66urhxWV1BQEBkZGRUVlZiYKBaLx4wZs2zZsoCAgHHjxuH7E4DyQqEqKGtra0LIo0ePUKiyrQ2VWgAAIABJREFUdurUqZiYGIlEsnHjxmXLlo0ZM0YWa2lubr5161ZkZOTly5dLSkqMjY2nTJly6NChgICA/v37y2KNACBnKFQFZWpqqq+vn5eXN2XKFLqz9HL+/v7UeUnkbyMovb2CgoK4uLjIyMjY2Nj29vaxY8cuWLDA399/4sSJrzjKBAAoCxSq4rKyssKJvnIg9aOVLS0tKSkpcXFxV65cefTokaGh4bRp0/bs2RMQEID9DQC9GApVcWGIfOVCbYzGxcXxeLzGxkY7O7vAwEBvb29PT081NTW60wGAzKFQFReLxTpz5gzdKeBlhEJhamoqdblLRkaGjo7O1KlTd+7c6efnZ2ZmRnc6AJArFKrisra2LigoaG9vx/aNoikqKoqOjo6Li4uOjq6vr7e0tPT39//2228nT56srq5OdzoAoAcKVXGxWCyhUFhYWPjqo7r3Aqqqqop5s8/29vbk5GQul8vlcnNycnR1db29vX/44Qc2my3nq1cBQDGhUBUXi8ViMBiPHj3qU4Wqr69fV1dHd4r/p7y8nMfjcbncuLi4+vp6GxsbDofz008/YWMUALpAoSouPT09ExOTvnZekqWlZWxsLL0ZRCLRvXv3qLEX7ty5o6mp6e7u/umnn86cOdPW1pbebACgsFCoCq0PDpHv4uKya9eu58+fDxgwQM6rfvbs2fXr13k8Xseo9BwO58svv5wyZYqWlpacwwCA0kGhKrQ+eOWMr6+vqqrqpUuX3n//fTmsTiwWp6enc7lcHo+Xnp6upqbm4eHx2WefcTgcarAqAIBXxOjpdhygCHbu3Llz587y8nK6g8jVe++999dff2VmZqqqqspoFc+fP4+JieFyudevX6+urjY3N2ez2RwOx9vbW0dHR0YrBYDeDYWq0CIjI2fOnFlXV0fLDcXokpeX5+DgsGPHjg8//FCKi5VIJPfu3aPOMEpNTWUwGO7u7hwOh81mOzg4SHFFANA3oVAVWl5enrW1dXp6el+7KebWrVt37NiRnJw8bty4t1xUfX19bGwsj8fj8Xjl5eUmJibUxqiPjw9ukQYAUoRCVWhCoVBbW/u3334LDg6mO4tciUQiNpt9//79uLi4N9t8zM7Opo6MJicni8Xi8ePHczgcDoczduxY3CINAGQBJyUpNCaTOXz48EePHtEdRN6o85L8/f0nTZr0888/L1q06FVasKmp6ebNm1SPFhUVGRkZTZ8+/dixY9OnTzc0NJRDbADoy7CFquhmzpypq6t7+vRpuoPQoK2tbcOGDXv37nV1df3uu+8mTZrU7cvy8/OpAYySkpLa2trGjRvHZrP9/PxcXFxwizQAkBsUqqJbv359QkJCeno63UFoc//+/TVr1iQlJVlZWfn6+o4aNYra3Kyqqrp3715iYuLjx4/79evn6+vLZrPZbPagQYPojgwAfREKVdEdPHhw/fr1dXV1ffzIX0ZGxrlz5xITE/Py8l68eEEIGThwoK2trbu7+/Tp0ydOnMhk4vgFANAJn0GKjsViNTQ0VFZW9vF7Uzs5Odna2m7fvj0hIUFTU5PuOAAAXeEIk6Kjxuvpg+clddHW1jZ79uz9+/cXFxfTnQUAoBsoVEVnamqqr6/f1wYg7EIkEi1atOj27ds8Hq9P3XsHAJQIdvkqASsrq75cqBKJZPny5VFRUVwu18XFhe44AADdQ6EqgT44RH4HiUSyatWqkydPXrlyxdPTk+44AAA9wi5fJcBisfrsMdRNmzaFh4efPHmSzWbTnQUA4GVQqErA2tq6oKCgvb2d7iDytm3bth07dvz2229z586lOwsAwD9AoSoBFoslFAoLCwvpDiJXe/bs+eKLL/bt27dw4UK6swAA/DMUqhJgsVgMBqNP7fU9evTounXrvvvuu7CwMLqzAAC8EhSqEtDT0zMxMek75yWdPHny/fff37Zt24YNG+jOAgDwqlCoysHa2rqPFOrVq1f/9a9/ffjhh1u3bqU7CwDAa0ChKoc+cuVMXFzc/PnzQ0NDd+3aRXcWAIDXg0JVDn3hyplbt24FBgbOmTMnPDy8j98JAACUEQpVObBYrIqKivr6erqDyMq9e/f8/Px8fHyOHj2Km5gCgDLCJ5dyoIbIz8/PpzuITGRlZXl7e7u4uPz++++4CxsAKCkUqnKwtLRUU1PrlYdRHz9+PH36dGtr68uXL2toaNAdBwDgDaFQlQOTyRw+fHjvO4xaUlLi4+Njbm5+/fp1HR0duuMAALw5FKrS6H1Xzjx79szX11dPT4/L5erp6dEdBwDgraBQlUYvu3KmpqZm2rRpIpEoOjra0NCQ7jgAAG8Lhao0qEKVSCR0B5GC+vp6NptdX18fGxtrampKdxwAAClAoSoNFovV0NBQWVlJd5C31dzcHBAQUFxcHBsba2FhQXccAADpQKEqDerKGWU/L6mtrW3OnDk5OTk3b96kfiIAgN4Bhao0TE1N9fX1lfowqkgkCgkJSUlJ4fF49vb2dMcBAJAmXESvTKysrJS3UMVicWho6LVr13g8nrOzM91xAACkDIWqTJT3RF+JRLJq1aoLFy5cuXJl8uTJdMcBAJA+7PJVJso7RP7GjRuPHDly4cIFNptNdxYAAJlAoSoTa2vrgoKC9vZ2uoO8ni1btuzcufO3334LCAigOwsAgKygUJUJi8USCoWFhYV0B3kNu3fv/vrrr/fv3x8cHEx3FgAAGUKhKhMWi8VgMJRor++RI0f+/e9/f//998uXL6c7CwCAbKFQlYmenp6JiYmynJd04sSJZcuWffnll+vXr6c7CwCAzKFQlYyyDJF/5cqVJUuWrFmzZvPmzXRnAQCQBxSqklGKK2diY2Pnz5+/fPnyXbt20Z0FAEBOUKhKRvGvnElJSXnnnXfmzZv3888/050FAEB+UKhKhsViVVRU1NfX0x2ke3/++Sebzfb19T18+LCKCv51AUAfgo88JUMNKJ+fn093kG5kZWWx2ewJEyacOXOGycQgXADQt6BQlYylpaWampoCHkbNz8/39fW1tbW9dOmShoYG3XEAAOQNhapkmEzm8OHDFe0waklJiY+Pj4WFBY/H09HRoTsOAAANUKjKR9GunKmqqvLx8TEwMOByuXp6enTHAQCgBwpV+SjUlTM1NTXTpk0Ti8XR0dEDBgygOw4AAG1QqMqHKlSJREJ3EFJXVzdjxozGxsbY2FgTExO64wAA0AmFqnxYLFZDQ0NlZSW9MZqbmwMCAiorK+Pj4y0sLOgNAwBAOxSq8qGunKH3vKS2trZ333334cOHMTExlpaWNCYBAFAQKFTlY2pqqq+vT+Nh1Pb29jlz5ty+fZvH49nZ2dEVAwBAoeDqe6VkZWVFV6GKRKLFixffuHHj+vXrTk5OtGQAAFBAKFSlRNeJvhKJZOXKlRcvXoyIiPDw8JB/AAAAhYVdvkqJriHyN2zYcOzYsYsXL06fPl3+awcAUGQoVKVkbW1dUFDQ3t4uz5Vu3rx59+7dx48f9/f3l+d6AQCUAnb5KiUWiyUUCiMiIlpbWx8+fJiXl1dQUHDr1i01NTUZrXHXrl3bt28/ePDg/PnzZbQKAAClxlCE8QHgVURFReXm5ubl5eXk5OTm5r548YIQoqKioq6uLhAIWCzWw4cPZbTqvXv3rl69eufOnf/+979ltAoAAGWHLVSlcfny5SNHjjCZTKFQ2DFTLBa3trYymUwXFxcZrff48eNr1qz55ptv0KYAAC+BY6hK44svvlBXV+/cph0YDIaMrmC5dOnS0qVLP/nkk08++UQWywcA6DVQqErDzMxs1apV3R4lbW9vHzNmjNTXGBMTs2DBghUrVnz11VdSXzgAQC+DY6jKpKamxsLCorm5uct8BoPB5/P79+//Zoutrq7W0dHR1tbuPPPmzZt+fn7z5s07cuSIigq+eAEA/AN8UCoTIyOj9evXM5ldj3wPHjz4jduUEPLDDz/4+PjU19d3zElLSwsMDORwOIcOHUKbAgC8CmyhKpnGxsahQ4dSp/hSVFRUAgICrly58mYLbGhoGDx4cFNTk6Oj440bNwwNDTMzM6dOneri4nL16lUNDQ0pBQcA6OWw8aFkdHV1N2/erKqq2jGHyWS+zRlJ4eHhLS0tEokkJyfHzc3tjz/+8PX1HTNmzJUrV9CmAACvDluoNKioqDh9+vSNGzcyMzPLysoIIVpaWiNGjHBzc/Px8fHx8Xn5/tvW1tbhw4dXVVV1vHcREREBAQFvkEQkEg0bNqysrIxalJqamqqqqp2dXVJSko6OzhssEACgz0KhylVZWdnWrVuPHz+ur6/v6+vr7Ow8ZMgQFRWVpqamhw8fJicnp6WlEUImTJjA4XDYbPbo0aO7Xc6hQ4fCwsLEYjE1WVJSMmTIkDfI8/vvvy9YsKDzvwEmk2loaJiUlMRisd5ggQAAfRYKVX7OnTsXFhY2YMCArVu3zp8/v9sdqi9evIiNjeVyudevX6+qqhoyZAibzWaz2d7e3np6eh0vE4lENjY2BQUFYrFYX1+/rq7uzSI5OTndv39fJBJ1nslkMvX19ePj4x0dHd9ssQAAfRAKVU62b9++efPmVatW/fDDD1paWv/4erFYfOfOHS6Xy+Vy//rrLyaT6eHhwWazORyOra0tIeTcuXPz58+XSCRTpkyJj49/g0hJSUmenp7dPsVkMnV0dGJjY2U3ABMAQC+Dk5LkYd++fZs3b/7ll19++eWXV2lTQoiKioqzs/PWrVtTU1MrKysPHz48cODA7du329nZWVpafvDBB9ra2nZ2doSQN+6877//vqfB9BkMRlNT0+XLl99syQAAfRC2UGUuPT3d3d19y5Ytn3322VsuSiQSpaWlcblcHo939+5dNTW1tra20NDQrVu3jhgx4rUWlZeXZ2Nj8/d3X01NTSwWBwcHb9u27XWXCQDQl6FQZUsikbi6uuro6Ny4cUO6IyRUVFTweLxNmza1trY2NDSwWCwOh8PhcCZPnvwql7ssX7782LFjne+oqqamJhQKZ8+evX37disrKylGBQDoC1CoshUVFTVz5sx79+7J6ASfv/76y9HR8fbt2zwej8vlPnjwQEdHx8vLizpJeOjQod3+rerq6iFDhrS1tVGTTCZTJBKx2ezt27fjRCQAgDeDQpWtgIAAoVDI4/Hks7ri4mIej8fj8eLi4pqamkaNGkU1q7u7e+fDpdu2bfv666+FQiF1M7hp06bt2LFj7Nix8gkJANAroVBlqKWlZcCAAfv27fvXv/4l51ULBIKkpCQej3ft2rW8vDwDAwMfHx/qCpx+/fqZmZlRgxf6+vp+8803Mrr1GwBAn4JClaG0tDQ3N7fHjx/Te3ZPYWFhbGxsXFwcj8drbGw0NTWtqKgYPXr0zz//7OHhQWMwAIDeBIUqQ7///ntISEhbW5uC3LClubk5Pj5+w4YNL168qKysNDQ09PX15XA406dPNzY2pjsdAIByU4gP+t6qvr5eT09PQdqUEKKtrc3hcHJycioqKnJzcz/55JNnz54tXbrUxMTEzc3tiy++SE9P7xjOEAAAXouifNb3SiKRqPNtYRQBg8GgHtjY2Pzf//1fXFzcixcvoqOjXV1dDx8+7OLiMmjQoKCgoOPHj3e+QxwAAPwjFGpfp62t7e3t/dNPPxUVFT158uSzzz578eLFsmXLjI2NnZ2dt23blpGRgeMCAAD/CIUK/4+lpeXatWtjY2OfP39++fJlJyenQ4cOOTs7m5iYhIaGnj9//o1H4QcA6PWYdAcARaSjoxMQEEDdYzU7OzsqKiouLo660Zubm1tAQIC3t/e4ceM6diADAADO8pWh/fv3b9mypaamhu4g0sHn82/evBkXFxcZGVlRUTFs2DBfX19vb+8ZM2Z0vrUcAEDfhEKVoV5WqB3EYvHdu3epZr19+7a6uvqkSZO8vb0DAgKoG+AAAPRBOIaq9AoKCpYsWVJaWiq3NaqoqDg5OW3cuDE5ObmysvL48eOmpqbfffedvb39iBEjwsLCIiMjW1tb5ZYHAEARoFCV3p07d44ePZqVlUXL2o2NjefOnXv8+PHq6ur09PRFixZlZGTMmjVrwIABPj4+1MnDtAQDAJAz7PKVIbnt8q2pqTEyMpL1Wl5dVVVVdHR0VFRUTExMXV2dpaWlv79/QEDA5MmT1dXV6U4HACAT2ELtDRSqTQkhgwYNCg0NPXfuXFVVVWxs7KxZs6Kjo318fIyNjYODg7lcrlAopDsjAICUYQtVhqS7hXrixAmRSNR5joODg5OTk1gsTkxM1NXVdXFxIYSUlpZGRESsXLkyMTExOjrazMxs6dKlWlpaUsnwNgoKCrhc7rlz55KTkwcNGvT5558vX75cccZlBAB4S/g4Uxq7du3q16+fk5PT2LFjv//++1WrVunq6ubk5MybN2/atGkZGRmEkFOnTjk6Oq5fv37VqlUnTpzIzMz88MMPPT0929vb6Y5PLC0tV69enZSU9OTJk4ULF65du3bixIl8Pp/uXAAA0oFCVRrr1q0LDAx0cHBITU3Nzc398ssvra2t7ezstm7d2vGahQsX+vn5tba2rl69+vDhw9euXduyZctff/115MgRGpN3MXz48B07dty/f5/P5wcEBAgEAroTAQBIAQpVaYSGhhJCSkpKNmzYMHHixI8++oiar6Gh0fllOjo6TCbT3t6emty0aROTyUxKSpJz2n9kY2Nz/fr1jIyMK1eu0J0FAEAKUKhKJiwsTCgUHj169BWPPmpraw8ZMqS6ulrWwd7AiBEjTExMcF0NAPQOKFRlcvz4cR6P9+WXX7JYrFf8KwKBoLKy0tLSUqbB3szJkyeLi4snT55MdxAAAClAoSqNysrKdevWdd7Zm5qa+o9/KzU1tbW11d/fX8bpXk9bW9v27duXLFmyZcsWNzc3uuMAAEgBClVprFq1qrW1tWNnb1tb26lTpwgh1Ek9nS/OEQqFubm51OMLFy54enoqTqGWlZV9//339vb2X3/99TfffPPFF1/QnQgAQDpw+zblcOnSpcuXL1tbW//888+EkNbW1vT09AkTJqSlpe3YsYMQcvbs2bFjx/r5+RFCVFRU9u3bp6WlVVJS0tTUFBkZSXN6QjIzM3k8HpfLTUlJMTAwCA4O3rhxo7m5Od25AACkBoWqHGbPnt3TEBznz5/vMkdFReXnn38uKSkxMDDQ19eXfbruNTY2xsXF8Xg8Ho9XUlIycODAGTNmrF271s/Pr8uZyQAAvQAKtdeia/uvoKCAurNbbGxse3v72LFjFyxY4O/vP3HiRIyLBAC9GAq1t2lubhYKhY2Njbq6unJbaUtLS0pKSlxcXERERG5u7oABA7y8vPbs2ePv7z948GC5xQAAoBEKtVc5depUTEyMRCLZuHHjsmXLxowZI9PVFRYWxsbGxsXFXb9+vaGhwc7ObubMmXv27PH09FRTU5PpqgEAFA0KtVfx9/enzksifxtBSVqEQmFqampUVFRcXFxGRoaOjs7UqVN37NjB4XCGDBkiizUCACgFFGqvYmBgIKMld9ziNDo6ur6+nrrF6bfffotbnAIAUFCo0CORSHTv3r3IyMioqKg7d+5oamq6u7t/8cUXgYGBFhYWdKcDAFAsKFToqrq6OiEhITIyMjIysra21tLS0tvb+/PPP/fx8dHU1KQ7HQCAgkKhAiGEiMXiu3fvUpe73Lp1S0NDY9KkSZs2bQoICLCzs6M7HQCAEkCh9ml8Pv/mzZvU5S6VlZXDhg3z9fVdu3btjBkz9PT06E4HAKBMUKgypKGhoZh3z87OzqZO001ISJBIJG5ubuvWrfP29nZycqI7GgCAskKhypChoWFTU1NLS4uWlhbdWciLFy9iY2O5XO7169erqqrMzMw4HM6qVau8vb2xMQoA8PZQqDJka2srkUiysrLGjx9PV4b79+9To9Lfvn2bEDJhwoR169ax2ezRo0fTFQkAoFdCocrQyJEjTU1NY2Ji5FyoDQ0NHaPSl5aWDho0aMaMGatXr/bx8enfv788kwAA9B2Mnu5hAlKxevXqmJiYhw8fymFc+NzcXC6Xy+Px/vjjD6FQ6OLiwuFwOBzOuHHjMCo9AICsoVBl69GjR3Z2dsePH1+4cKEslt/c3BwfH0/1aGFhoaGhoa+vL4fDmTFjhpGRkSzWCAAA3UKhylxYWFhkZOT9+/eNjY2ltcwnT55wuVwul5uQkCAQCMaMGVNZWbl58+YVK1aoqqpKay0AAPDqUKgy9+LFCycnJwsLCx6P9zYjDQkEgsTEROoMo7y8PAMDAx8fHzabzeFwjIyM1NTULl68OHv2bCkmBwCAV4eTkmSuf//+V65cmTJlysyZM8+fP/+649cXFxdTe3Rv3LjR1NTk4OAQGBjIZrMnTZrEZP7/b59QKJRBcAAAeA0oVHlwdHSMi4sLCAgYO3bsjz/+GBgY+PLXt7e3p6SkUD364MEDHR0db2/vnTt3cjgcc3Nz+WQGAIDXgkKVk3HjxmVkZGzYsGH27NnTpk1bs2aNj49PlwEfysvLqWtdYmNj6+vrra2tORzOjz/+OHnyZBnd3BQAAKQFx1DlLSUl5fPPP4+Pj1dXV3dwcDA3N1dVVW1sbMzNzX369KmWltaUKVOoy10sLS1fcZlCoRDHUAEA6IUtVHlzd3ePi4srKyuLi4vLzMwsKysTi8WDBg1yd3d3dXV1d3dXhHEKAQDgdaFQ6WFmZrZ48WK6UwAAgNRgAB0AAAApQKECAABIAQoVAABAClCoAAAAUoBCBQAAkAIUKgAAgBSgUAEAAKQAhQoAACAFKFQAAAApQKECAABIAQoVAABAClCoAAAAUoBCBQAAkAIUKgAAgBSgUAEAAKQAhQoAACAFKFQAAAApQKECAABIAQoVAABAClCoAAAAUoBCBQAAkAIUKgAAgBSgUAEAAKQAhQoAACAFKFQAAAApQKECAABIAQoVAABAClCoAAAAUoBCBQAAkAIUKgAAgBSgUAEAAKQAhQoAACAFKFQAAAApQKECAABIAQoVAABAClCoAAAAUoBCBQAAkAKGRCKhOwO8CQ8Pj+Tk5J6eZTKZpaWlgwYNkmckAIC+DFuoyio4OLinpxgMhqenJ9oUAECeUKjKKigoSFVVtdunGAxGaGionPMAAPRxKFRlZWRk5OXl1W2nqqqqzpo1S/6RAAD6MhSqEgsJCfn7IXAmk+nv729gYEBLJACAPguFqsQCAwPV1NS6zBSJRCEhIbTkAQDoy1CoSkxPT8/f379Lp2ppabHZbLoiAQD0WShU5bZw4UKhUNgxqaamFhQUpKWlRWMkAIC+CdehKre2tjYjI6OGhoaOOTExMT4+PjRGAgDom7CFqtzU1dXnzJmjrq5OTfbv33/q1Kn0RgIA6JtQqEpvwYIFbW1thBB1dfVFixYxmUy6EwEA9EXY5av0RCLRoEGD+Hw+IeTWrVsTJkygOxEAQF+ELVSlp6qqunDhQkLIkCFD3Nzc6I4DANBHYfegkpFIJM+fP+fz+Q0NDQ0NDdQpviYmJoQQFxeXmJgYauykfv36aWlpDRgwwNDQsOMIKwAAyA52+SooPp+flZVVVFT09OnTp0+fFhcXl5aW1tTUPH/+/HUXpaurO2DAADMzM4tObG1thw0bxmAwZBEeAKAPQqEqisLCwpSUlHv37mVmZj548KCiooIQoqmpOWzYMAsLi6FDh5qbmxsbGxv+l56enoGBgYqKCiHEwMDg3Llz8+fPr6+vF4lEhJD6+vqmpiY+n09tzvL5/LKysqdPnxYVFRUXF1OtrKenZ29v7+DgMHr06AkTJjg6OuKEJgCAN4ZCpVNOTk50dHRycvLt27crKirU1dUdHBwcHBxGjRrl4OBgb29vZmYmi/XW1dXl5ORkZWU9ePDgwYMHd+/era2t1dHRGT9+vLu7u5eXl7u7+98HNQQAgJdAocqbQCCIi4u7du0aj8d7+vSpkZGRu7u7u7v7hAkTnJ2dNTU15R9JIpHk5ubeunUrJSUlJSUlPz/fwMDAx8eHzWYHBAQYGxvLPxIAgNJBocqJWCy+devW+fPnz5w5U11dbWdnFxAQ4O3tPWXKFEXb0VpYWBgbGxsXF8fj8VpaWtzc3EJDQ4ODg/X09OiOBgCguFCoMlddXX3gwIEDBw6UlpaOGzdu4cKF8+bNk9G+XOlqamqKiIg4ffp0dHS0mppacHDwmjVrHB0d6c4FAKCIUKgy9ODBg127dp0+fVpbW3vZsmWLFy+2tbWlO9Sb4PP5v//++969e3Nzc6dOnbp27dqZM2fiDGEAgM4wsINM5OfnL1iwYPTo0WlpaT/99FNJScm3336rpG1KCDE0NPzggw+ys7NjYmK0tbVnz57t4uLC4/HozgUAoEBQqFJWU1OzfPlyOzu7e/funT17Nisra/ny5dra2nTnkgIGg+Hj4xMVFXX37t3BgwdzOJzJkyffvXuX7lwAAAoBhSpNp06dsrOz43K5hw8fzsrKmjNnTq/cL+ro6BgREXH79m2JRDJ+/PgNGzY0NzfTHQoAgGY4hiodNTU1ixcvvn79+ooVK7Zv366vr093InmQSCTh4eEbN24cMGDA6dOnXV1d6U4EAEAbbKFKQXp6upOTU05OTlJS0t69e/tImxJCGAzG8uXLc3JyWCyWp6fngQMH6E4EAEAbFOrbOnv2rIeHh62tbXp6uru7O91xaGBqanrt2rWNGzeuWrUqLCxMLBbTnQgAgAbY5ftWTp06tXjx4rVr1/7www/UsLp9WURExLx584KCgo4cOULd9AYAoO9Aob6533//PSQkZP369d9++y3dWRRFTExMYGDg3Llzjx071itPyAIA6AkK9Q1lZmZOmDBh+fLlu3btojuLYomJifHz8/vhhx/WrVtHdxYAAPlBob6J+vp6JycnMzOzuLg46Y7Em5OTw+Px8vLy3Nzc9PX1mUzmrFmzpLh8+fjuu++2bNmSkJDjtrv5AAAgAElEQVQwceJEurMAAMhJXz/s92a2b9/+4sWL33//XbptmpaWtmTJkrVr144fP37NmjVz5sy5c+eOFJcvNx9//LG3t/fKlStxghIA9B0o1NdWXl6+Z8+ezz77zMTERLpL/vrrrz08PJhM5tKlSx8+fPiKf+v48eMvmaQFg8HYtWtXTk7OyZMn6c4CACAnKNTXtnv3biMjo5UrV0p9yTExMf369aMedzx4uZs3b37yySc9TdLI2tr6vffe2759O91BAADkRLHuxKkULl68GBISoqGhIcVlFhYWJicnCwSChw8fXrhwgRDS2tra5TV5eXmpqamZmZnu7u7vvPMOISQ+Pj4wMJDBYBw4cGDw4MG6urqdJwMCAggh5eXl169fLy0tdXd39/LyohZVUlJy6dKlDz/8MCcn5+rVq0OHDl24cKHUL/tZsmTJoUOHsrOz7e3tpbtkAAAFhEJ9Pffv3y8oKKD6TIp0dHQMDAwIIcbGxtStUltaWjq/YPfu3VevXr1582ZRUdHUqVMrKytXrlzZv39/R0fHvLw8a2traou2y2R8fPyZM2dWrlypp6cXGBgYGhq6d+/eyMjIpUuXVldXSySSzMzM6urqzz77rLS0VOqbtq6uroMHD758+TIKFQD6BAm8jtOnT6upqYlEIqkvuaysjBCyZ88earKxsZEQsnXrVmpy5MiRH3zwAfU4MDCQw+F0PDY3N+9YSOfJhoYGS0vLxsZGanLp0qWEEGpE+02bNhFC4uLiqKfGjRvn5OQk9Z+IyrNgwQJZLBkAQNFgC/X1lJWVmZqayn9QpISEBB0dHUJITk5OSUlJfX19x1Ndxk/omDxz5kxLS8vHH39MTVZUVIwYMeLx48dubm5aWlqEEBsbG+opOzu76OhoWcQeMmRIZmamLJYMAKBoUKivp76+npax783MzGJiYqKiojw9PUeMGJGRkdHxVE+Fmp2dbWpqunfv3n9cuKqqqkQ2lyMbGBjU1dXJYskAAIoGhfp6TExMKisr5b/eLVu2JCYmRkdHa2lpXbx4sfNTPRWqqqrqo0eP2tvb1dTU5Bf0f1VUVJiamtK1dgAAecJlM6/HzMyMz+c3NTXJc6WFhYVfffVVSEgItau282gJDAZDJBJ1Ozl69OimpqZff/2149na2tp9+/bJKzUhhBQVFVHnWAEA9HrYQn09bm5uKioqMTExUj/Rl7pOpuPkXuooqUAgIIRQJyidOXNm/vz59+/fT0pKEggE1NlGpqamlZWVBQUFEonExMSk86S/v7+5ufn69etbW1v9/f2zsrIuXLhw+PDhjoW3tbVR66qpqREIBBKJRLrD2Tc2Nt66dSskJESKywQAUFy0nhKllDw8PBYtWiTdZRYUFCxYsIAQYmtre+3atcrKyvfee48QYm1tTZ2Lu2TJEiaTOXLkyF9//fXChQvq6urTpk3j8/nx8fFMJrNfv37U6cFdJqlbf1NvtL29/Z07dyQSSUJCgqWlJSHk/fffr6ioOHPmDHVUeNu2be3t7VL8oc6ePctkMmtqaqS4TAAAhYXB8V/bwYMH165d+/DhQwsLC3mut6GhQU9Pj3osEAg6Rpaoq6tTUVHpeKrLJCGkqKiIwWAMHTpUnmklEsmECROMjY0jIyPluV4AALqgUF9be3u7vb39hAkTfvvtN7qzKK7z58/Pnz8/PT197NixdGcBAJAHFOqbOHfuXHBwMI/H8/X1pTuLIqqpqRk3btyUKVMUYaR+AAD5QKG+ocWLF0dFRWVkZAwbNozuLIpFLBb7+fnl5OTcuXPH0NCQ7jgAAHKCQn1DTU1Nrq6uGhoacXFx/fv3pzuOopBIJGvXrj148GBycrKzszPdcQAA5AfXob4hHR2diIgIPp/v5eXF5/PpjqMQJBLJ6tWrf/3115MnT6JNAaCvQaG+OUtLy4SEhNra2ilTpjx58oTuODRraWkJDQ09dOjQuXPn5syZQ3ccAAB5Q6G+lWHDhiUmJmpoaDg7O/fl60MKCgomTpzI5XKjoqICAwPpjgMAQAMU6tsyNzdPTk5+9913Z82atXbtWmpUo75DIpEcPXrUycmJwWCkp6f7+PjQnQgAgB4oVCnQ1NQ8dOjQsWPHTp06ZW9vf+3aNboTyUl+fr6Xl9eyZcsWL16ckpIyfPhwuhMBANAGhSo1oaGheXl5M2bM8Pf39/HxSU9PpzuRDNXU1GzatMnR0ZHP56ekpOzevZsauB8AoM9CoUrTgAEDDhw4cOPGjYaGhvHjx8+dOzcrK4vuUFJWU1OzZcuW4cOHHz9+fOfOnRkZGa6urnSHAgCgHwpV+qZNm5aamnr58uVHjx45Ojp6eXlduXKl8z3XlNT9+/eXLl1qbm6+f//+LVu2PH78eNWqVUwmblgEAEAIBnaQKYlEEhsbu2fPHh6PZ2FhsWjRogULFlhbW9Od6/U8f/78/PnzJ0+eTE5Otre3//DDDxctWqStrU13LgAAxYJClYf8/PwDBw6cOXOmvLzcxcUlODg4ICBg5MiRdOd6GT6fHx0dffbs2evXr6uqqs6aNWvp0qVeXl7SvWcqAECvgUKVH7FYHB8ff+rUqStXrrx48cLKyorNZrPZ7EmTJunq6tKdjhBChELh3bt3o6OjuVzun3/+qaKiMm3atAULFrzzzjud7wcHAAB/h0KlgVAovH37NpfL5fF49+/fV1VVdXR0dHd3nzhx4vjx44cPH66iIr9j28+ePbtz586tW7dSUlLS0tKampoGDx5MNb23t7eBgYHckgAAKDUUKs0qKipSUlJSUlJu3759586d9vZ2bW1tOzs7BwcHe3v7ESNGWFhYWFhYDBgw4O3X1dra+vTp06KioqdPn+bk5Dx48CArK6u6upoQYmVlNXHiRHd3d3d3d1tbW+zXBQB4XShUBdLc3JydnZ2ZmZmdnZ2VlZWTk1NeXk49paenZ2FhYWhoaGhoOGDAACMjo379+mlqalJXf+ro6Kirq0skktraWkKIUChsaGhoamp6/vw5n89//vx5dXV1eXl5VVUVtTQDAwMbGxsHB4dRo0aNGjXK0dHR2NiYrp8aAKB3QKEqtNbW1qL/Kikp4fP5VEHy+fza2lqBQNDc3EwIaWxsbG9vJ4RQN5JTU1PT1dXV0dEZ8F+GhoaDBw8eNmwYtb2L+80BAEgdCrU3EAqFampqFy9enD17Nt1ZAAD6KAzsAAAAIAUoVAAAAClAoQIAAEgBChUAAEAKUKgAAABSgEIFAACQAhQqAACAFKBQAQAApACFCgAAIAUoVAAAAClAoQIAAEgBChUAAEAKUKgAAABSgEIFAACQAhQqAACAFKBQAQAApACFCgAAIAUoVAAAAClAoQIAAEgBChUAAEAKUKgAAABSgEIFAACQAhQqAACAFKBQAQAApACFCgAAIAUoVAAAAClAoQIAAEgBChUAAEAKUKgAAABSgEIFAACQAhQqAACAFKBQAQAApACFCgAAIAVMugPAGzp9+nRjYyP1WCwWE0JiY2Nramo6XjB79mwjIyN6wgEA9D0MiURCdwZ4EyEhIadOnVJTU6MmxWIxg8FgMBiEEJFIpKen9+zZM3V1dVozAgD0Idjlq6yCg4MJIe3/JRKJhEIh9VhVVTUoKAhtCgAgT9hCVVbt7e3GxsZ1dXXdPhsfHz9lyhT5JgIA6NOwhaqs1NTUgoODu90MNTY29vDwkH8kAIC+DIWqxIKDg9va2rrMVFdXDw0NVVVVpSUSAECfhV2+SkwikZiZmVVUVHSZn56e7uTkREskAIA+C1uoSozBYCxcuLDLXl8LCwu0KQCA/KFQlVuXvb7q6urvvfcefXEAAPou7PJVelZWVo8fP+6YfPjwobW1NY15AAD6JmyhKr2QkBBqeAcGg+Ho6Ig2BQCgBQpV6YWEhLS3txNCmExmaGgo3XEAAPoo7PLtDcaMGXP//n0Gg1FcXDxkyBC64wAA9EXYQu0NqA3TiRMnok0BAOiCLVRpampqEggEtbW1ra2tLS0tdXV1AoGgsbGxsbFRIBDU1dW1tLS0traKRKL6+npCCPUyQkhDQ4NQKBSLxdRQggKBoLm5mVqmUChsaGjoaXV/H9iBEMJgMPr169ftX9HU1NTS0qIeq6mp6erqEkK0tbU1NDQIIf369WMwGEwmU09PjxCipaWlqampqqqqr69PvaZ///4aGhra2tr6+voaGhp6eno6OjoaGho9rQ4AoO9AofaooaGBz+fX1tbW1tbW/U3n+bW1tc3NzT3VHiFER0dHXV29o40IIf379yeEqKur6+jodLyA/LfSOqqOYmBgoKLSzb6Ezi/7+uuv16xZQxVh5z7uor6+XiQSUY87XtbY2Nje3i6RSGprawkhbW1tTU1NHfPb29sbGxs7viv09DNqampqa2v3+y+D7nR+1sjIiLo3DgBA79AXC1UgEDx79qy6urq6urqmpobP5/P5/Jqampqamo45NTU1XTb+tLS0euoGAwMDHR0dXV3djs01akOwYzNODj9Ufn6+lZWVHFbUsfHd1tbW0NDQeaO8ubm543vG37+FUBvlHRgMhpGRkaGhYcefxsbGRkZG1CQ1x9TUtPMXCwAARdY7C7W1tbWioqK8vLyysrKsrKyysrLz48534VZTU+v8mT5w4MCOSeoBVZn9+vXD3dDeErUF3IH67tLx9YXP5z979ox60HnzWkdHZ8iQIYMGDTIzMxs0aFDHYxMTEzMzM319fRp/IgCAzpS7UJ89e1ZUVFRUVFRcXFxUVFRYWFhcXFxSUvL8+fOO1wwaNKjjg3jIkCEDBw40NzcfOHAgVZ8GBgY05oduNTc38/n86urqioqKqqqqsrKyqqqq0tLSjj+py4QIIdra2kOGDLHoZNiwYUOHDjUzM2MymfT+FADQ1yhHoQoEgsePH+fl5eXl5RUWFlIl+vTpU+qMHhUVFRMTk+HDhw8dOtTCwsLc3LxjC2bQoEHUoAfQm1RVVT179qykpIT6RkV9nSoqKiopKREIBIQQJpNpZmbWUbGs/8LJUwAgOwpXqGKxuKioKD8/Py8v79GjR3l5efn5+UVFRWKxmMFgDB061NLSsvO2CNWg2B8LhBCJRFJRUVH0X1TRFhQUPHnyhDoibmxszGKxrK2traysqIq1srKiznAGAHhL9Bfqs2fPMjMzMzMzs7KyMjMzc3JyWltbCSFGRkadP/uoPzU1NelNC8pIJBIVFRXldZKfn19cXCwWi1VUVCwtLUePHu3g4ODg4ODo6GhpadntOdUAAC8n70IViUTZ2dl37tyh6jMrK6uqqooQYmJi4uDgMHr06FGjRtnY2LBYLOrCEgAZEQgE1I6QBw8eZGVl3b9/v6CgQCQS6ejo2NvbUxU7evRoJycn6tImAICXk0ehVlVV/fnnnxkZGRkZGSkpKS9evFBTU7OysnJycrK3t7ezs3N2djY1NZV1DICXa2try8/Pz8jIyMnJyc7OTk9Pr6ysVFVVtba2dnJymjRpkru7u62tLbZfAaBbMilUiUTy4MGDmzdvpqWl3b59++nTpyoqKjY2Nq6urhMmTHBzc7Ozs1NVVZX6egGkq6SkJDU1NTU1NS0tLSMjo7W1tX///q6urq6urp6enhMnTsTxVwDoIM1CLS8vj42NjYuLi4uLq6ysHDBggJubm6urK/UnLlABpdbe3n7v3j2qXG/fvl1QUKCtrT158mRvb29vb29HR0cM/ATQx71toYpEovj4+MjIyLi4uJycHE1NTXd3d+ojZty4cdg5Br3V06dPqe+ON27cqKmpGTRokJeXF5vNDggIwHdHgL7pDQtVLBYnJSWdO3fuwoUL1dXVY8aM8fHx8fb29vDw6Bh7HaAvEIvF9+7do8o1KSmJEDJjxoygoKCZM2di3ESAPuW1CzU1NfX06dMXLlyoqKgYM2ZMUFBQUFDQiBEjZJQPQInU1tZevXr17NmzcXFxTCaTw+HMnz9/5syZuE4aoC941UJtbm4+efLk/v377927Z29vP2/evKCgIGtra1nnA1BGz58/v3z58tmzZ2/evGlkZLR06dIVK1aYm5vTnQsAZOifC7W+vn7v3r27d++ur6+fN2/eypUrXV1d5RMOQNmVlZUdPHgwPDycz+eHhIR88sknI0eOpDsUAMjEy04aEovFx48fZ7FY27dvnz9/fkFBwbFjxxSqTdva2m7cuPHRRx9xuVxpLbOgoGDJkiWlpaWdZzY1NYWHh3/++eebNm1KTU2V6bqUlyzejsbGxqtXr/7nP/95lVdGRkZu3LhRWquWCjMzs//85z9FRUXh4eG3bt2ytbUNCwurrq6mOxcAyICkB48ePXJ2dlZTU/v3v//9/Pnznl5Gr4yMjOXLlxNCwsPDpbXM8+fPE0K4XG7HnOLi4qlTp1ZUVLS2tn766afa2toFBQUyWpdSk8XbcfToUSMjI2tr63985fnz56nhnaW1aqkTCoWHDh0yMTExMjK6dOkS3XEAQMq6L9QLFy7o6Og4Ozvn5ubKOdDrun//vnQ/wSUSSXV1defJkJCQzz//vGMyPT1dIBC88cJ/++23l6xL2cni7ZgxY8arFKpEIgkKCrK0tJTiqmWhrq7u/fffJ4SsWbNGJBLRHQcApKabXb7Hjh2bN2/e4sWLb926ZWNjI8et5TdB3fZSutfUGxkZdZ68evXq0KFDOyadnJze+KTNmzdvfvLJJy9Zl7KTxduhqqr6igtUUVFR/Euf9fX1w8PDz549e/DgwZCQELFYTHciAJCOrjdh/vPPP8PCwj7++ONvvvmGlkAv0djYeOXKlUePHjk4OEyfPr2ny+fz8vJSU1MzMzPd3d3feecdaqZEIklMTLx3756qqqqNjY2Pj09PM8VicWJioq6urouLy+PHj//444+Ghoa7d+9euHCBECISifh8vo2NzbRp016e6u8x4uPjAwMDGQzGgQMHBg8eHBAQ0Hld1N9qaGjgcrm5ubnm5ua+vr4d54WWlJRcunTpww8/zMnJoQp+4cKF3ZZHS0vL1atXZ86c+ezZMy6XS61IVVW1qqoqIiJCRUVl7ty5+vr6L/91lZaWRkRErFy5MjExMTo62szMbOnSpdQVxg0NDfv27QsKCho+fPirvGvdLv91Q1Ju3boVHR3t6Oj47rvvdsx8/vz5hQsXnj596uzsLJFIOldvt6tWEEFBQcbGxjNmzLC3t9+8eTPdcQBAGrpssU6aNMnLy0sB90Tl5uZyOJz79++3t7cHBwcbGho+efJEIpFkZ2cTQg4dOkS9bNeuXVOmTBGLxYWFhcOGDdu3bx81/9NPP6X2Q/7111/jx4/vaWZ2dvacOXMIIfv375dIJBUVFZcuXSKEbN26NSUlJTExcevWrYSQ77///uWpuo1x9+5dd3d3Y2Pj+Pj4u3fvdlmXRCK5d++eg4PDxYsXnz17tmPHDl1dXWr/cEREhLGxMSFk165d//rXv/z9/Qkh33zzzd9/SwkJCVZWVoSQnTt3Ll++/OOPP9bW1n733XfDw8MXLlw4f/58BoMREBDQ8fpuc548ebJ///5aWlorVqxYsmQJh8MhhLi4uLS1tUkkkosXLxJCNmzY0O3b9Cpvx+uG9PPzGz58uL+/v5+fn62tLSEkJCSEeurhw4cuLi63bt1qb28/cOCAhoYGi8V6+b8EhfLjjz9qampWVFTQHQQApOB/CvXJkyeEkPj4eJrC9EgoFI4ZM+bgwYPUZEZGhrq6emRkpORvn+AjR4784IMPqMeBgYEcDkcikYjFYiMjo46f66uvvupppkQiyczM7FxyT58+JYScOHGCmiwvL6eK7eWpuo1BPTY3N+/4uTqvSyAQ2NjYbN26tePZBQsWqKurZ2dnSySSTZs2EULi4uKop8aNG+fk5NTt7+rHH38khJw/f56apP7ixYsXqcnNmzdraGh0fGHqKWdISAiDwXjw4AE1uWXLFkLIr7/+KpFImpubw8PDy8vLu137q7wdrxvSz89PXV394cOHEolELBbPmjWL/PdMLldX145qF4vFlpaWHYXa06oVSmtrq5GREfXPCQCU3f/sM8zPzyeEjB07VoZbxG+Ey+Xeu3fPz8+Pmhw3blxDQwO1odZFQkLCV199RQjJyckpKSmhfiIGg2FtbT1v3ryrV68SQtavX9/TTELIy+8f0nkv60tSdRuD0nmfZOd1Xb9+/eHDh25ubh1zpk+f3tbWdvjwYUIItbu145C2nZ1dcXFxtwmpfc4ODg7UJDX4xujRo6lJGxsbgUBAfS14SU4dHR0mk2lvb09Nbtq0iclkUuPqaWlpvf/++694u72elv9aIQkh9vb21GsYDMbKlSsJIdeuXaNuZzR16lTqNQwGw8XFpePX+5K3QHFoaGiMGjVKMbMBwOv6n0IdOHAgIaSiooKmMD26f/++jo4OtduT0tNpQWZmZn/++eeaNWtyc3NHjBjRccbHL7/8oq+vHxgY6O3tXVtb+5KZUknVUwzS8wk7OTk5hJDOo796eHgQQnJzc//+YlVVVcmrDXGlqanZeVJNTY0Q0tTU9I85O9PW1h4yZMgbXD35ist/ecgu3NzcVFRUysvLqTOKR40a1fFU59/tK66aduXl5dT/OwBQdv9TqKNGjRoyZEh4eDhdaXoiFoubmpri4+P/8ZVbtmz56quvvvvuu3fffbfzLVfHjBlz586dVatWJSQkjBs37vnz5z3NlEqqnmKQngt1wIABhJDbt293zLGwsFBTU+vfv/9rpXotL8nZmUAgqKystLS0lNHyX4u+vr6urq6lpWV9fT0hJC0trfOzHb9eWaxa6hISEvLy8thsNt1BAEAK/qdQ1dTUNm/evGfPnps3b9IVqFvUvsHTp093zOHz+ZcvX+7yssLCwq+++iokJITaQdqxUSIQCE6cOKGnp7d3795r165Rpxp1O1MqqXqKQQhhMBgikajbpVFDUFG7VSkPHjxob2+fMGHCa6V6dS/J2UVqampra2u3+9ilsvzXcvfu3fr6ejabTf3+u/23KqNVSxefz1+yZImfn9/48ePpzgIAUtD1uosVK1bMnTt31qxZMTExtATq1syZM8eOHfvbb7+tWLHixo0bu3bt6jj7tK6ujhDS2NjY8eeZM2fq6+v/+OOPpKSkFy9eNDY21tfXUyfUEEJ8fX2NjIyMjIwkEsnfZxJCBAIBIaSmpoZaNbUrmM/nU5PUVhE12VOqnmI0NDSYmppWVlYWFBQ8efKkqamp87pGjx69ePHipKSkjoOjycnJVlZW1NhD1Hrb2tqop2pqaqjBJf7+u2poaOj4KTp+Jx0b39R+VOrZl+QkhAiFwo69zRcuXPD09KQKNScnZ8KECd9//32379SrvB0NDQ2vHrLjBR2leP78+Xnz5nl5ec2cOdPGxubEiRPUt5Dy8vLExMTS0tLMzEzqXevpR1ME5eXl1NHfY8eO0Z0FAKTk7+cpCYXCpUuXMpnMjRs3UldKKILS0lIfHx8Gg8FgMKZMmVJaWiqRSNLS0qZPn04IGTt2LHXa55IlS5hM5siRI3/99dcLFy6oq6tPmzatrKzM1NR0/vz558+f37FjB3UmbUtLy99npqamUpeyjBo1Kioq6unTpwsWLCCE2NvbJyYmFhYWLlq0iBBiZWUVExPTU6qeYvD5/Pj4eCaT2a9fvz179nRZFxXpgw8+sLe3P3bs2KFDh/z8/IqLiyUSSUJCArW79f3336+oqDhz5gx1jea2bdva29s7/5Zu3bpFndqzePHigoKC+Pj4cePGEUL8/Pyys7Nv3bpFnfQUFBSUl5f3kpxhYWGqqqqrV6/esGHD/PnzAwIC6uvrqVXweDwGg6GmplZbW9vlPXrFtyMqKuq1QsbExIwdO9bb23vbtm1hYWGfffZZx09dWFhIXcJraWm5YMGCgICASZMm7d+/v6WlpacfTSb/Ol9TTEzM4MGDbW1tqfcXAHqH7oceFIvFP/30k6amppOT0x9//CHnTC/x4sWLf/xM7Pjol0gkra2t1IP29naBQFBUVNT5ld3OlFaqbmNIJJLa2trOT/1dbW1tSkpKSUnJW6Z6Rd3mDAsLU1NTk0gkxcXFdXV1Xf5KTU3NypUrX/Fi5Z5+D6+rubm5p/p59uxZY2OjRCJpaGiQxaqlqKSkhLokKSQk5O/fSABAqb3s9m25ubnr1q2LjY2dNWvW5s2bnZ2dZbqtDIpjxYoVR44c6djD3EV8fHxxcfHixYvlnEqpVVZW7ty5c//+/SYmJjt37qSupgWA3uRlA5/a2tpGR0dHRUWVlZW5uLj4+vpGRET0dE4N9CbNzc1CoZA6tNmFUChsaWlBm766zMzMsLCw4cOHnzp16osvvsjOzkabAvRK/zySOIfD+fPPP6Ojo1VUVN55550RI0b85z//6fbiSOgdTp06RR0h3rhx471797o8y2QyqdPB4OX4fH54eLiHh8fo0aOTkpJ+/PHHgoKCf//73y8fOQQAlNfLdvn+XX5+/oEDB86cOVNeXu7g4BAUFBQUFMRisWSXD+SPOmhKPdbQ0KCuPIFX9Pz58ytXrpw7d+7GjRvq6ur+/v7Lly+fNm2adO/AAwAK6PUKlSIWi5OTk8+dO3fx4sXKysoxY8a8++67Pj4+zs7OCnsFPYBMPXnyJDY2NjIyMjY2VlVVlc1mBwUFBQQE6Ojo0B0NAOTkTQq1g0gkSkpKOnfuXFRUVGlpab9+/aZOnerj4+Pt7U3dTgSgF+Pz+Tdv3oyLi4uNjS0sLNTV1fX29p4zZ87MmTP19PToTgcA8vZWhdpZbm4u9cmSkJDQ0NAwbNgwLy8vd3d3V1dXGxsbxb/tM8CrqKioSE1NvX37dnx8/J07d1RUVFxcXLy9vX18fNzc3KhRiAGgb5JaoXYQCoWpqamxsbE3b97MyMhoaWkxMDBwdXV1dXV1c3NzdXU1NDSU7hoBZKe19f9r795+EmfCOACPHCxWKG0oFJHjJiUqpwAAAARnSURBVGAoColGw53xwv8dLhQDAWObgOUYTqHlPIK6FxMagvh9rlFx1/e5aOpQYhtIfzMDzDu9vr5Op9OpVCqVSpXLZYPBEI1Gz8/PLy8vLy4uXit0DwD4aT4+UJfNZrNsNptKpdLpdDqdliQJIRSJRI6PjxOJxNHRUTwe9/l8n3cCAPwpVVVzuVw2m81mszc3N5lMZjabOZ1O0h1MJpOnp6dkpSoAAFj2uYG6otvtkmTNZDK5XI7U7uY4Lh6Pk3CNx+OHh4fwPQ7wZebzuSzL2YVcLqcoCkKI47hEIpFIJM7OzpLJ5Dsq7QAAfpovDdQV/X5fluV8Pn91dVUoFDKZDFl0nuM4URRjsdivhVgstlIyE4B36PV6xWIxn88XCoVisVgsFm9vb8fjsclk8vv9oiienJzEYjFRFEVRhB+6AAD+yCYDdcXz83OpVMrlcpIkSZIky7IkSaTaudlsDoVC4XD44OAgFAoFg8FgMOj3+2HmDayFMa5UKoqiKIpSKpXIe0mWZbL2E8Mw4XA4shCNRmOx2Gsl6wEA4I2+UaCuNRgM9HC9u7uTZblUKum11TiOCywEg8FAIOD3+30+nyAImz1t8DUGg0G5XFYWyP79/X2j0SBvbJqmSVcsEonoIep2uzd94gCAf9B3D9S1MMa1Wo1M2dXr9UajQfYVRdGXGuY4bm9vz+PxvNz6/X6TybTZSwBvNJlMGo0GeZVXtvV6ndQ9RQhZLBaPx/NrCXmtQ6EQzNwCAL7GXxmor8EYl8vlarVaq9WazSbZVqvVVqtVqVRI2WqEkNFoFASB53mHwyEIgsPhINXFHQ6H0+l0Op1kHz61/VSPj4/dbrfT6XQ6nW6322632+022SeNrVar2WxOp1NyPEVRgiDs7+8LguD1el0ul9frFQTB5/MFAgGY/AcAbNw/Faj/bTQaVatVPWjJXZvcxPX7+HItHavVyvM8y7L2dTiOYxhG/5OmaZZlN3h1GzcajcbjsaZpmqb1er1+v6+t0+v1NE1TVVWftydYliVdGdKb4Xne5XIJguB2uz0ej9vt5nl+U5cGAABv8YMC9S1IrC6PnFRVXYmEfr+vqiqpDr3ydIvFsrOzY7fbKYqyWq27u7sURbEsu9KOEGIYxmg0GgwGsiwAOQAhZLPZTCbT1tbWcjxTFEXT9Muz3d7eXvsTo4eHB304vmw2my1XZBuNRqTiKbmW+Xw+GAwQQuPxGGOMENI07enpCWM8Ho/7/T7GeDAYjEYjjLGqqivtL/+dzWaz2+3L3Q7SEbHb7SzLulwuPTt5nodJeADA3w4C9f2WB2GTyaTX65GM0TQNYzwcDofDIcaYPDqdTvUD0CLDVhLum9Dzm6S72Wy2Wq1Wq9VisTAMQ9M0RVEcx5HDGIaxWCzkANJp0FMT1psEAPwoEKjfwsqgUB8sEsPhcDabvXzWa+0IIY7j/rddHxavDJcBAAC8AwQqAAAA8AFgUg4AAAD4ABCoAAAAwAeAQAUAAAA+wG+3EM85Dm2zWAAAAABJRU5ErkJggg==\n",
"text/plain": [
""
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"p_classification = Pipeline()\n",
"to_float = p_classification.map(malaya_speech.astype.to_ndarray).map(malaya_speech.astype.int_to_float)\n",
"gender = to_float.map(gender_model)\n",
"language_detection = to_float.map(language_detection_model)\n",
"age_detection = to_float.map(age_model)\n",
"combined = gender.zip(language_detection).zip(age_detection).flatten()\n",
"combined.map(lambda x: x, name = 'classification')\n",
"\n",
"p_classification.visualize()"
]
},
{
"cell_type": "markdown",
"id": "ambient-boring",
"metadata": {},
"source": [
"**Again, once you start to run the code below, it will straight away recording your voice**. \n",
"\n",
"If you run in jupyter notebook, press button stop up there to stop recording, if in terminal, press `CTRL + c`."
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "systematic-toddler",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Listening (ctrl-C to stop recording) ... \n",
"\n",
"Sample 0 2021-05-31 23:39:19.638932: ['male', 'not a language', 'not an age']\n",
"Sample 1 2021-05-31 23:39:19.874754: ['male', 'malay', 'teens']\n",
"Sample 2 2021-05-31 23:39:21.262149: ['not a gender', 'not a language', 'not an age']\n",
"Sample 3 2021-05-31 23:39:23.363767: ['not a gender', 'not a language', 'not an age']\n",
"Sample 4 2021-05-31 23:39:28.221167: ['male', 'not a language', 'teens']\n",
"Sample 5 2021-05-31 23:39:31.076877: ['male', 'malay', 'teens']\n",
"Sample 6 2021-05-31 23:39:35.456165: ['male', 'not a language', 'teens']\n",
"Sample 7 2021-05-31 23:39:38.438468: ['male', 'not a language', 'teens']\n",
"Sample 8 2021-05-31 23:39:40.711461: ['male', 'not a language', 'teens']\n",
"saved audio to savewav_2021-05-31_23-39-42_725496.wav\n"
]
}
],
"source": [
"file, samples = malaya_speech.streaming.record(webrtc, classification_model = p_classification)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "functioning-incident",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import IPython.display as ipd\n",
"\n",
"ipd.Audio(file)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "cognitive-intellectual",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"9"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(samples)"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "isolated-regression",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(bytearray, ['male', 'not a language', 'not an age'])"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"type(samples[0][0]), samples[0][1]"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"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": "3.7.7"
}
},
"nbformat": 4,
"nbformat_minor": 5
}