{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "source": [
    "# Hysteresis simulations\n",
    "\n",
    "In this tutorial, we summarise some of the convenience methods offered by Ubermag that can be used for simulating hysteresis. Let us first define a simple system object. For details on how to define simulations, please refer to other tutorials."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import oommfc as mc\n",
    "import discretisedfield as df\n",
    "import micromagneticmodel as mm\n",
    "\n",
    "region = df.Region(p1=(-50e-9, -50e-9, -50e-9), p2=(50e-9, 50e-9, 50e-9))\n",
    "mesh = df.Mesh(region=region, cell=(5e-9, 5e-9, 5e-9))\n",
    "\n",
    "system = mm.System(name='hysteresis')\n",
    "system.energy = mm.Exchange(A=1e-12) + mm.UniaxialAnisotropy(K=4e5, u=(0, 0, 1)) + mm.DMI(D=1e-3, crystalclass='T')# + mm.Demag()\n",
    "\n",
    "def Ms_fun(point):\n",
    "    x, y, z = point\n",
    "    if x**2 + y**2 + z**2 <= 50e-9**2:\n",
    "        return 1e6\n",
    "    else:\n",
    "        return 0\n",
    "    \n",
    "system.m = df.Field(mesh, nvdim=3, value=(0, 0, -1), norm=Ms_fun, valid=\"norm\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now that we have `system` object we can simulate hysteresis using `HysteresisDriver`. Like all other drivers, `HysteresisDriver` has `drive` method. As input arguments it takes `system` object (as usual) and:\n",
    "\n",
    "- `Hmin` - the starting value of magnetic field\n",
    "- `Hmin` - the end value of magnetic field\n",
    "- `n` - the number of points between `Hmin` and `Hmax`\n",
    "\n",
    "For instance, let us say we want to simulate hysteresis between $-1\\,\\text{T}$ and $1\\,\\text{T}$ applied along the $z$-direction in steps of $0.2\\,\\text{T}$. Accordingly, `Hmin` and `Hmax` are: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "Hmin = (0, 0, -1/mm.consts.mu0)\n",
    "Hmax = (0, 0, 1/mm.consts.mu0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The number of steps `n` should be 21, so that the values of magnetic field are: $-1\\,\\text{T}$, $-0.9\\,\\text{T}$, $-0.8\\,\\text{T}$, ..., $0.9\\,\\text{T}$, $1\\,\\text{T}$, $0.9\\,\\text{T}$, $0.8\\,\\text{T}$, ..., $-0.9\\,\\text{T}$, $-1\\,\\text{T}$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "n = 21"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can now create `HysteresisDriver` and drive the system."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running OOMMF (ExeOOMMFRunner)[2023/10/23 16:08]... (1.6 s)\n"
     ]
    }
   ],
   "source": [
    "hd = mc.HysteresisDriver()\n",
    "hd.drive(system, Hmin=Hmin, Hmax=Hmax, n=n)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "After the simulation is complete, we can have a look at the last magnetisation step:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
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1Ksqvfl1FU7lNQVBCR69yIBw8xNAKwk5kOfoQtoKYxMi0Z2E31I3M8fp8xOrqwLKwd0rHkZGhTNtTWBDXBrAsXL2z1WkXFCQyvqbfj7uN9cfbi3tAf6ymeoix2lo8P7JO+r7i7J6F0bQiTqy2Fk+ROm2714sjqxvEYsRq6/Aq1DbsdlIGHIkVCmHWN+ApzFemDeDOz8Ns9GM2NOIuGKhU+4wzUqiutmhosDjl5BQZ/iIIwgFBDK0g7ERXZzZG0916lrOvUm13v/7YmlZ1SVVo3ACcWd1xdOkCgLdokFIjYU/1ktK/HwDugXnYXE5l2obdjqewAABXn2wcGenKtAG8g+LH2Z6Rjiu7txZtw+nAnZe7h9b7hueoQTu+LypQqu0dvOPc8wxWex6eeeaOlOyZZ0l6VlBLDJu2l5DcyCcoCDvhNFx0tvcEIMuhLssJTeZtYDzb5i1UW7zaMAw8BfFyK6mDBu2h9b7TnIFUmYlsxlNUqE/bV9j01ac8W+htKkAeN/ltr43eXjy+geCw4+zVE0eXzkq1U3L6YfN44ia/j1qT37+/g9xcO16vwYknqD0mgmBahraXkNyIoRWENshy9iXD3o0Um1e5dqqvCHtGBq7eao0EgLewEJvbjTsnR712k9lUOSSgGU9hAdhsSocENOMeEM+KN2dTVeLsnoUjKythbFVic7vx5Ocpz85C/MbKXZSPZ1ChliEBZ53l5pRTXLjdYhIEQTgwSNkuQWiD7o4+xCw9a9F78gtI3bBei5Fw5+TgPeooDLu6iWzNOLKySP3JMcqHBEB8PGrqMUcrHxIAcfPmHTJY6bjflngHFyWywKrxHFWEs0eWFm3vYB+GphlbZ5+Vwg8/qD8HBUEmbwm745DJ0C5ZsoSCggKuvPLKVr9ftWoV1157LUOHDmXIkCGMGjWKxYvVznQWDj289nSyXWon4jRj93rJPOMsLdo2l4vO54zUom0YBp1/fsGeG7aTzj//mbYJRJnnjlQ67rcl6aediiNT3eS+lniHDCJlQD8t2h5fAe58teN+mxk61Mk557i1aAuCILTFIWFow+Ewf//733cpQL5x40auuOIKqqurGT9+PI8//jhpaWlcffXVfP311wdpb4VkIcXm0abtSFef5UxoK6ycsKu2zv0W7Z2xd0rTkm0HsHk9ysf9NuNwGHTufEh0L0IHI2bZtL2E5OaQGHIwefJk6urqGLTTRJjJkycTi8V44okn6NI0+3vo0KGMGDGChx56iOeff/4g7K0gCIIgCIKgkqS/JSkpKeHpp5/m1ltvxevdMYHHsizmzp3LiSeemDCzEF8WbsSIESxatIi6urq2JAVBEARB6ICY2LS9hOQmqT9B0zS58847OeaYY/jlL3/Z6r2tW7dSX19PXhsTQfLy8jBNk5KSkgO1q4IgCIIgCIImknrIwfTp0/nuu+94881dl4WsrKwEoHPnXes3Nv+uuY2wb1yZ/2dt2mv/or60UjPm39SXVmql79S4Zr1M7N0VjYdbJ0ZY44epUfqkt27Vpm05HtemDfDpef/Wpu1JkcTIgUSqHAi7I2kN7fbt25kwYQLXXnstAwYM2OX9cNNSmq42Jj04nfHZzsFgUO9OCoIgCIKgDJm8JeyOpD0zxo4dS/fu3fnTn/7U5vspTfUVI5Fda4k2m12PR98sdkEQBEEQBOHAkJQZ2vfff58PP/yQJ554gkgkkjCtsVgMgMbGRrp27QpAVVXVLn9fUVEBQFaWnoLlgiAIgiCox5QhB8JuSEpD++GHH2JZFtdee22b7//kJz/hxhtvpHPnzhQXF+/yfnFxMU6nk4EDB+reVUEQBEEQBEEzSWloR48ezSWXXLLL7++55x4A7rjjDnr16kVFRQVvvPEG5eXliWys3+/ngw8+4NRTTyU1NfWA7vfhiGnFCJl+Umyp2Ay1I1yitbVY0QjOrt2U6gLEGhqINTbi6tFDvXZjI7G6elxH9FSubQaDRKurcXbvrrwgvxkOE62sxNGtGzan2lW3rGiUSHk5ji5dsClejtWyLCLbt2PPyMDeorSfKsKlpdhTU7GnpSnXjpSXY7hStCzeEKmswrAZONqYOLu/RKuqwbJwdO2y58b7SKyuAdPvx9mzu3JtgC1bYnTubOD1Ju2IvEOaWPKOlBQ0k5RnRr9+/Rg2bNgur06dOtGpUyeGDRtGr169uP766/F4PIwePZqPPvqIzz77jOuvv55AIMCYMWMO9r9xWNAQq+GTuleoj6mvKFE1/wO2v/yCcl2A+iWL2frYI1q0G5ctZ+u/H9aiHShZzdb7J2AGQ8q1w1u3sfX+CUQr1H+Wsfp6tt4/gdD6Dcq1MU22PjCBwHffq9cGtk+aTP0XepbTLntuCrXzP9SiXfnKa1S9OUuLdvV/36JyxhtatOs/WkjZw09p0Qb41SWVPPpIozZ9QRD0kJQZ2r2lR48evPTSSzz44IOMGTMGy7I4+uijmTp1Krm5etYwF1oTsgIAuLQtI6tnPJVlWWDIWC1BaBeGDSxT5wa0qFqWRVmZSVb3pMz1HBZIlQNhdxxShnbatGm7/C4nJ4fHH9db41DYPWHTD0CKocHQWpa+upuWiaF4iIQgHDbYjHh8akFfAeK6WotwGLKy1A7XEQRBP4eUoRU6HiErgNNIwWbo6CAstDla04p3yoIg7DuGgWVqytBqDPuy8vg+d5cMbYdFlqgVdocYWkErITOAS0d2lqYEraaOzbLM5B5ykMS7LrQkOT9Iw7Dpy9BqDPyysnjpx+5ZYpo6KjErOWNC0I9EraAFy7JoiFUTNgOk2DxYlhUfl6qIWCBAc6rGjESwolF12n4/WBaGzYYVi2E2LcShAjMQSHxvmSamwtXqWmpj7fSzSu02ft5v7RbnhlLtYFCfdijUKgupVDvc+pxWqW3FYpihHZMGzWBQWTbVsqz4MbcZYFqYoTBWRF1smv4W8aM4NkuKI5SVxY9DVncbsViSrq0sCIcpYmgFLRiGwdcN86mIbsZv1vNVwwdK9bfPmEpg7RoilRVsfnwi2NSdypUzX6dh+XJijX42PzwBFD46rXnvA+oXfAaxGFsfnECsUd1s6rrPPqdm9vsAbH/0ccLbS5VpN369gspXXgOgfNqLBIrVrV8fXL+B0qefB6Bq5iwavlyqTDtaVcXWhyYCUDv/Q2o//FiZthUOs/X+8ZihEA1LllD11tvKtDFg6/h/E6upIfD991RMf1mdts3G9kceI7JtG6H1Gyh96lkMRfFjGAblz7xAcM06IqVlbB8/CezqYrNq+hv4l36N2dDItrsfUhqbL78c4N6767HZ4Pe/rWb9+pgybUEdMWzaXkJyI5+goI00exeiVpig2UBXZy8MhY8JPf1yiNZUE2tsIOWI3so6ZAB3bh7RygqscAhHZmdsbrc67YJ8IqVliayhs2lFOxV4fQVEtm0HIFZbS8qRfdVpFxUmtCOlZXgK8pVpu3NziDat3hfZtg2Pz6dM23nEEZiB+MTEyPZSPIUFyrTtnTpheNwQjRItK8eTr26hFpvTibN7d8xAgGhFJW6FVVkMwyDlyL7E6uqJ1dTi7tdPmTaAO3cAscpqzIZGXNm91MZmQR7RskqsUBhH50ylsTl4sJPycjPukQ2DnBwZkScIyYQYWkEbGY74ggc27PRy5SnVTi3YYXpSC4uUanvzd5ieVJ9abXduDobLFd/OILXaziOOwN45EwCPr1CpkbB36oSrbx8g/j+oNBI2pxNPQdwMOo/oiVNhMX7DMPAWxc8VW2qqUpMPJLSx25WafABPka/F94VKtb1FO849zyB1NxAA3iEttBXvt2fQjtj0HKV2vwcftWOxkCuv1FVmUNhfTMum7SUkN/IJCtpIt8cNbQ9XP1w2dQYIwNXzCBwZGWC3481Vu4SxIyMDV69eAHgVG1qb05nI5LU0LCpoad68ik0K7DBvXsX7DTuOhQ7tZvOm2uTHteP7685Ra/IBvL5CMAycPXsozeQDuPNyMFJStJh8R4/uOLp3A8PAXag2Nu0ZnXD1i99YeYaoNcv9+9tJSzPo1s3GiHPUfpaCIOhHnqkI2kh3xDvhPinqHvM2YxgG3nwf0Zpq5UulAngLCjHsjrhpVoynyEfwhx9I6avWSDRr13++SOnj72a8RT5q3n1PuRGHuHmrNAwt2ik5AzBcrrhBVExzVtyrOBMJ8ax4St++uHNzlGsbDgee/IEYKS7lJt8wDLxHFRFatwF7qvqlhj2DC7BiMRxd1C7Za7MZFBU5GDbMhcslM+k7KjLWVdgdYmgFbTgMFz2c/ci099Cin1rgI1pbo0XbW1CI4VJvlAE8hQWEfliv3EhAfDiAt8inPFsI4Ox1BB5fodIhAc3YO3XC4ytUni2EeFbcW+RTPiQAdmTFdRhxiN+guHMGaNO2pbj0aB9VhM2r3szGtQu11bg9aoiTyy6X4QaCkIyIoRW0ku89TulksJZ4BuRiBtWVM2pJSp++2NPVZ2cBHOnpZJx1hhZtm9NJ55+fr0XbMAy6XHyhFm2ALhf9XIvJB8g8b6QWkw+QftqpyocENJM69BgcmZlatL1FhRgOPV1ASv8jsWt4ugHg7NObNI8e03n1H1Lp1UtWCevISB1aYXeIoRW04rGladO2uVzYXHoyTIbdjrOL+kxkM85u3URbtPesrfEctKfpi03DZsPZTc++G4aBI0vPDYSY2Y6PrBQm7A45MwRBEARBEISkRjK0giAIgiAkBTEpryXsBjkzBEEQBEEQhKRGMrSHKKP636hNe81dQ7Rpm06N66fLXALhUEdn+IT1BZAR1Rucp396kzbtpaepL9nWTNS5Upt2smLKhVzYDZKhFQRBEARBEJIaydAKgiAIgpAUHMwxtJs3b+bMM8/80TbFxcWcccYZbNmypc3377nnHi699NLEz4sXL2bixIl8++232Gw2hg0bxpgxYygoaL0g0apVq/j3v//N0qVLiUajDB48mJtvvpnhw4fvso8TJkxg4cKF+P1+8vLyGD16NCNGjGjnf508iKEVBEEQBEHYA927d+e1115r870777wTp9OZ+PmnP/0pN9xwwy7tevfunfh+6dKlXH311Zxwwgk8+uijxGIxJk+ezKhRo5g5cybZ2dkAbNy4kSuuuIIBAwYwfvx43G43U6ZM4eqrr+bFF19kyJD4MMDa2louv/xyPB4PY8eOpWvXrrz++uvcfPPNTJw48ZA3tWJoBUEQBEFICg7m0rcul4vBgwfv8vv58+ezcuVKXnnllcTvMjMz22zbkocffphu3brx6KOP4mqqqT5o0CDOOOMMHnvsMe69914AJk+eTCwW44knnqBLU23qoUOHMmLECB566CGef/55AKZOnUpZWRmzZs0iLy8PgGHDhrF27VrGjx9/yBtaGUMrYFompqVnKUkzGMQMBvVoh0KYAT0rhZnhMDG/Ju1IhFijX4u2FY0Sa/RrWRrUisXi2rGYem3T1KdtWXHtaFS5NkDM78cMR7Rom4EAZiikR1t3bOrS1hmb4QixBj2xCRAKWViWxpl7hwGmZWh7tYdQKMS9997LRRddxFFHHbXXf1dTU8OSJUs4++yzE2YWoEuXLpx00knMnTsXiF+/5s6dy4knnpgwsxA31yNGjGDRokXU1dUBMGfOHPLz8xNmFuILkZx//vls2LCB4uLidv2PyYIYWoGy2Ebm+l8gYoWVa1e8+Qbbn3tGuS5A1RtvUvrE01q0a+fMY9v4f2vRbvhiMZvu+qcWbf/3K9n0tzu1mInQps1s+tudRMrKlWvHamvZ9Lc7Ca5Zq1wb02TTHXfSuGy5em1gy333U/fJp1q0tz0ymep3ZmvRLpsyjYoZr+y5YTuo/O8blD6pJ+5r35/LtgkPa9Gun7+ETTc9oEUbYNQfKvnDddXa9IUDz/Tp0yktLeWWW27Zp78rKSnBsiwGDhy4y3u5ubnU1NSwbds2tm7dSn19fSuT2kxeXh6maVJSUkI0GmXdunW7bQewcuWhXTVDhhwIhK0gBjYcOPfceF+JxcAu902CIAjbtsfof5x0u/vDwRxysDPhcJhnn32WCy+8kJ49e7Z6b9OmTdx0000sW7aMuro6cnNzueaaazjvvPMAqKysBKBz58676Db/rrKyErPpadue2tXV1RGJRH60XVVVVXv/1aSg45wZwkEjbAVxGSkYhvr6fpZpYtjkNBMEIUnQOCJg+3aTI3ra9W1AOKC8+eablJeXc8011+zy3po1azj66KOZNGkS48ePx+Vy8ec//5n33nsPiA9VAFpNJGum+XfBYJBwOP7ktOWwhLbaNevtqd2hjNwqCk2G1q1F2zJNMDQaWqmxLQgdFI3OUJe0hpv6ZoJBi6pqk5495AZ/fzA70NK3//3vfxkyZAj9+/dv9fvXXnsNt9uN1+tN/O6UU07h/PPPZ9y4cYwcORK3O97nRiK7jr9v/p3H40lkaNtq12x2PR4PKSkpe9XuUKbjnBnCQSNihXChx9CiM0Ore3KFxs5NEA5lkjp0NF1XtpfGJzxKhvbQoKysjOXLl3P66afv8l6XLl1amVmIm8mTTz6Zbdu2UV5eTrdu3QCort51THVFRQUAWVlZZGVlAW0PF2jZLiMjA5fLtcd2hzKSoT2MiVlRTEzCVhC34cWyLGXDDizTBMuKDzlwOBKz7lWYW8uy4mNz44qJbRl2NR1Fy9nwzdsyHGpCZeeZ9lY0Ktq6tVuc08q1W5xzSrVjMWgRK0q1d6qAYcViYBgaYpOki01j558VaW/eEmXb9iZDe4QY2v0h1kEey82bNw/LsjjttNN2eS/WFAP2nc775kf+KSkp5OfnY7fb26w8UFxcTFZWFt27dwfiY2B3187pdDJw4EDsdjt5eXm7bQdQVFS0j/9lciEZ2sMYAxtfBN6mwaymwarh+/DnCsUNtj4xmUjpdiLbt8crHSgyy4ZhUPb8VEIbNhCtrmb7I48p0W2m4uXXCKxchekPsH3io5ghddUfqt9+l8YvvwLTZPvkJ4hUqhukX/vhx9R9HJ9tXz7lBYI/rFem3bBkKTVNs+2r3ngT/zffKtMOrCqmYsarQLy6RP3CL5Rph7dupfTpZwGo//wLaubMVaYdq29g+6OPYYXD+FesoGrmm8q0rWiU7RMfJVZXR3DtWipemqFMG2D75MeJlpXtOD4qY3PKNEIbNhKt0hSbq4ox/X62/0dtbFbN+ICGz77Giplsu/cZImXqqhG89kaAm2+N641/uJ6FX+gpxSYcOJYtW5Ywky354osvGDx4MDNmtI7ZhoYGFi5cSH5+Punp6XTq1IkTTzyR9957r9XY1tLSUj7//HPOPffcxO/OOeccFi5cSHn5jgozfr+fDz74gFNPPZXU1FQARo4cSUlJCatWrUq0M02TWbNmUVBQsMvQiEMNMbSHMTbDRorhJUKYerOaDFs3ZdqGYeDslkW0uppIRTmuHj2UTjpz9epFpLSMWG0t9swMZRkggJQj+xLevCVe49Zmw57q3fMf7SXunAGENmwA0yRaVY2zu7pHQJ78PEJr1wEQ2rAR9wB1Fy9PQT7B1WsACK5egzt/11Iz7cWdl0uwab+Da9biUajtys4msmUrAKEf1uPOzVWm7eiciRUMYkUihDduIkVhZ2FLScHmcWM2NBLZug1Xn2xl2obNhrNbN6JV1UTLKzTE5hEHKDYNtbFZ0I/Qmk3x2KyoxXmEuuvh4EFO1v4Qz9ot/jLMccfuOnFH2DtMy6bttS+sX7+eXr167ZKFHTZsGEOGDOHBBx/kySefZPHixcyePZvf/va3VFVV8Ze//CXR9tZbb6W+vp4bbriBhQsX8uGHHzJ69GgyMjL405/+lGh3/fXX4/F4GD16NB999BGfffYZ119/PYFAgDFjxiTajRo1iiOPPJKbbrqJ999/n0WLFnHrrbeydu1abr/99nYe8eRBDO1hTrOJteOgp0Pt3Zt3YH7i+9RBP75iyj5rF/na/L6ja7sH5kHTY0xvkU+tkcjOxp7eCQBPYYFSI+HonImrdy8AUvr3U2okbCkpePLiRtPRrRsOhSbfsNnw+Arj37vdSk0+gMfXdH7YbHh2Wnt9v7VbnHuJ7Sii5XntKSrUpp1MsekZlIvhbIrNnxQojc3BRTtmsl99VSp2e8d4bC60n9ra2kRmtCUOh4OnnnqKq666iunTp/P73/+eO++8k86dOzNt2jROOeWURNvCwkKef/55wuEw119/Pbfddhu9e/fmxRdfTIyxBejRowcvvfQSWVlZjBkzhhtvvBHDMJg6dSq5LW7SvV4v06ZN46ijjuLOO+/kj3/8I9u2beOJJ57ghBNO0HtAOgAyhvYwJ8PeFaLQ09EPh6G2Dq1nYD4YBva0NFL6HqlU29UnG1taGqbfj6dQrZFwdM7E2asXka1blXeazeYtsHIVnkFqtZvNW8MXi5XvN8QNVnjLVryK97tZO7BylXKTD3Hj07BosXKT36xdO2eucpMP4PX5qOJ1HN26Kc3kw44bK8PhwD1ggFJtV3Y29k6diDU04CnI3/Mf7AOOzpm4snsT3rylleFXgc3twj0oh8CyYrw/Ubvf3bPs9Oxho7rGZNRv1J4nhxsdZQzt+++/v9v30tLSGDNmTKvs6e445phjmDZt2h7b5eTk8Pjjj++xXY8ePZgwYcIe2x2KSIb2MCe9KUOb7VD3mLcZu9dLSt8j8foGKa90YNhseH2FuAf0x+5V30F4B/lwZHXD2aO7cm1PkU9LthCaslY2m3KTn9AGPBomFiS0NZjlZvOmw+S7+sTNm9enNssJO7LiOkx+842VDpNv2Gx4inxNJn/XDNb+4iny4ejWVUtsen9SgOFJwZ2v9gYc4lnaiy7w0LWLTArbHzrKkAOh4yEZ2sMcj5FGF9sRpNu6atH35heQ0qePFm1PkY+oppVPvL5CrLD6pYAhbt5Ca9cpNxIQN2/uvFzl2UKIm7eUAf2VZwshbt7cuTlaTL4tJQVP/kDlQwJgR1Zch8mH+Dmuctzvzto2t55yfd4iH5Fu6sagttIe5MMMBrUsBOM9Jp/gd+uUVTdoyeAiJ+eec2jXARWEg4kY2sMcwzAoTBmupXMASD3qKJxd9Jhlz8A8Yg2NWrRdfftgpOiZuOHonEnG2Wdo0balpNDlwp9p0TZsNrpecpG2c6XLxRdqMfkAnc8bqcXkA6SferIWkw+QeszRODXVjvQW+TDaWKVIBe6BeTh79NCi7cruTScNhhPA0SWDzF+crkX7sku95OboOd6HEzHJpAq7QQytQKotQ5u2q7ueTg3A5nZryzAZNhuuI47Qog3xKg2iLdp71N5pfXiVODIztWnbXC5sWXoytIbNhquXxtjsq+eYi5kVBL2IoRUEQRAEISkwO8ikMKHjIbl7QRAEQRAEIamRDK0gCIIgCEmBjKEVdocY2kMUW0a6Nm2t1xN5mtQ21sHeAUHQiObz26zRtzJXhk1f5YJKbcqCcOghhlYQBEEQhKTAtCTrIbSNGFpBEARBEJKCmEz9EXaDnBmCIAiCIAhCUiMZWkEQBEEQkgIZciDsDsnQCoIgCIIgCEmNGFqBpZWz+LZmvhbt0ueepWzaVC3aFS+/yrZJk7VoV7/7Hpvvu1+Ldt2ChWz469+0aPtXfMv62/5KzO9Xrh3asIH1t/2V8PbtyrWj1dWsv+2vBIpLlGtbsRjrb/srDV8uVa4NsOkf/6R2/odatLdOeJiqmW9p0S596hnKp76gRbvi5VfZ9kgSxuZHn7Hptju1aL/2dgNdC9YRDJpa9A8XTGzaXkJyI5+gQNQKY1oxLdpWLIZlarqAx0zQpW1ZENNzTLAsLE3alsb9tizi2rpKLOk63s3alp4dt6IxLFOTtqkvfizT1BebphmPTx3ojE3TxIpGtUiHwxY1taa2S5YgHO7IGFoBy7IwdN3bSP1UQRCSBUPf+Exb0yVWLon7R0zG0Aq7QTK0AhYWhsYLuayWIAhC0qDJcTYbWsnQCoIeJEMrYGFiaDOdko8QBCGZ0HPNak4amJqGpxwuSJUDYXeIoT2MsSwTMBJDDixLXabWajle0djxswp9q42xkNr2XbRF+0e0W2olk3ZbP0tsWq2GHKjUNk0Lm9GsC7GYhd0uxqw9mFrXXheSGTkzDmNiVpQvK98ibPqpjZSprXRgmpQ9/xzRqioi5eWUT5umTNowDCpeeInwtm3Eamspffo5pRM5ql57neDadZjBIGXPPo/Z0KBMu+ad2fi/+x5Mk/IXphNRWDGg7qOPaVjyJQBVb7xJcM0aZdoNi5dQ9/EnANTOnYd/+dfKtAPffU/1O7MBqF/4OfWfLVSmHdqwkcpXXgWgcfnX1M6Zp0w7WllF2ZRpWJEIwZLVVL81S5m2FQxS+sxzmI2NhDdtovLlV5VpY5qUPzclHptl5ZRP0RCbW7cRq6ul9Jkkis233iPw7fdYMZOK56cT2VaqTHvCYzU8O70OgGvGlPHx5wFl2oIgxBFDexjjsLmwsAiZfmojpaQ6MpVpG3Y7RoqbSHk5kW3bsKWmKh2na8/IILxpM9GqagzDwOZ0KtN2ZGURWvcDZqOfaE0t9k6dlGm7evUiuKoYTJPgmrU4e/ZUpp3Sty+Bb78DwP/NClL69VOm7R4wIGFiG79aRkrOAHXaOQNoXLYciO+3u39/ZdopfbLxf/s9AIHvV+Lq01uZtrNbVyJbt2GFwwRXr8bZo4cybZvHgxUKEautI7R+A44uXZRpG3Y7hstFtCwem/Y0DbG5OQljM7sXwe9L4rG5eh3OI9R9nicf5+a9+fFSeh985OekYz3KtA83YhjaXkJyI4b2MCfL3TfxfXe3OpMC4PUVtvjep1a7aIeep0ix9iBfi++LlGq7C/ITs0O8RYVKjURKvyOxeb0AePIHKjUSzqxuOLt3B8DVtw+O9HRl2jaPB3eTQbZnZuLsdYQybcNux1NYEP/e5cSdm6tMG1qfe54W57tqba/qc1xn/CRpbHp8AxOx6RmkNjaHH+Omezc7AGed6iUlRcyTIKhGDO1hTlZKPwBSHZ1Jc3ZWqu3JLwCbDcPlUm4k4uYtnuXw+AqUaju77TBvqk2K3evBnRPPQKru7FuaN9X7DTv2V7W5AvD4mrXVGom4ZlzbPVCtyY9rx4+zapMPO24CVZt8AE/TjZUOk98qNguTJzZtHg/uvPiNlXew4ri3G/xsRCoA553lVap9uGFahraXkNyIoT3MSXV0xm3vRHe3use8zdg9Htz9++MZmK/cSMTNW6EWIwHgGeTDnpmJq3cv9dpFRXGTn6fWSMAO86bD0Ca0NRhandrN5k2HEU/p1w+b14O3SG22EHZkxXWY/OasuA6Tn9SxeVQRhtNJykD1sXlBs6E9M1W5tiAIUuXgsMcwDLJS+tLDnaNF3+srwubRM17MW+QjUlGhTdsKhbTU5/UW+QitXafcSEDcvKX076fFSKT0OxJX7164eqk3Es6sbrj6ZCvPFkKTecvN0WLym82bDrMMcYPvztMTm54iH7aUFC3a3iIfkfLki03PYB/BVauxudTH5lmneDjpWDe9ekq3uz9IlQNhd0hkCWR7faQ7u2vR9vp82NxuLdqewnycNeomVbUkpd+RGHa7Fm1nVjfSf3qaFm2bx0PnC36mRduw2+ly8UXaFuHoctEvtJh8gMyR52gx+QCdTjpR+ZCAZlKPORpnT3WTk1riLfJhuFxatD0F+UonPLZEa2x260L6iNO1aHu9NsaP7aZFWxAEMbQCkOHS02ECOLOytGnbPB5cmrK/ht1OSr8jtWgDuAeoH+KR0O7fT592su53kmqn9MnWpu3sps9cJXVs5ug7x4cfo+fm/nDClGoEwm4QQysIgiAIQlIQk8lbwm6QwSiCIAiCIAhCUiMZWkEQBEEQkgKZFCbsDjkzBEEQBEEQhKRGMrQHkSv6XqdNe90/fqJN27Jb2rQFYa+RoXS7kqyhqXm/jbC+k6X/W9dq017xMz3l4ABCzu+1aetEFkAQdodkaAVBEARBEISkRjK0giAIgiAkBVK2S9gdkqEVBEEQBEEQkhrJ0AqCIAiCkBTIGFphd0iGNkn4PPQO22LrtWhvf2EKle/O0qJd/tIMKl/7rxbtqrfepuy5KVq0a+d/xLaJj2rRblj8JZvvvV+LdmBVMZvvvhczEFCuHdq8hc1330ukrFy5drSmls1330tw7Trl2lYsxuZ/3kvj1yuUawNsHf8QdQsWatEuffwpat77QIt2+YvTqXztdS3aWmPzw4/YNklXbC5hy30PaNH2L/2GLf/3LyzTVK69bn2U4adv55tvw8q1OxqmZdP2EpIbydAmCX6rjqgV0qIdravF5tazJGOsvh4rJUWLttnQSKyuXo92IECstlaPdihEtLpaj3Y4TLSqGstSP23cikbj2rGYcm0sM64djarXhrh2SFP8VNdgBoN6tOvqcPj9WrRjDQ1YkYgWbbNRY2z6A8RqNMVmUG9sxiqrQUNshkIWxaujhMPJWuZCEPYfMbRJg6Gvso1lgU3uTgVBEHRhGE2Pyk0L7Gq1Y7F472DYDv3H8Qd7yMGVV17J4sWL23xv9OjR/PnPfwZg1apV/Pvf/2bp0qVEo1EGDx7MzTffzPDhw1v9zebNm5kwYQILFy7E7/eTl5fH6NGjGTFiRKt2VVVVPPTQQ8yfP5/a2lqOPPJIrrzySi677LJW7QKBABMnTmT27NlUVFRwxBFHcPHFF/OnP/0J2yHez4uhTRIMDCxdltaydlxsBUEQDms0XWebzIRlWcrn6TePYjjE/UqHoaioiLFjx+7y++7duwOwceNGrrjiCgYMGMD48eNxu91MmTKFq6++mhdffJEhQ4YAUFtby+WXX47H42Hs2LF07dqV119/nZtvvpmJEycmTG0kEuH3v/89FRUV/OUvf6FPnz58+OGH3HXXXQSDQX73u98l9uGWW25hyZIl3HbbbRQUFPDVV1/xn//8h8rKSu644w79B+cgIoY2STAw0HWhtUwTxNAKgnC4o/MymMjQqh9DG2uStB8GhrYjlO1KTU1l8ODBu31/8uTJxGIxnnjiCbp06QLA0KFDGTFiBA899BDPP/88AFOnTqWsrIxZs2aRl5cHwLBhw1i7di3jx49PGNpZs2axatUqnnzySU477bSE3ubNm5k4cSKXXXYZbrebRYsW8fHHH3PnnXdyxRVXJNrV1NTw7LPPcvXVV9OrVy9dh+Wgcxic/ocK8QytjrGRWJYYWkEQBI0YzelTS62htSwLs2lYu2RoDz6WZTF37lxOPPHEhJkFcLlcjBgxgkWLFlFXVwfAnDlzyM/PT5hZiA9NOf/889mwYQPFxcWJdhkZGZxyyimttvWzn/2MxsZGFi5cmGjX/PctueCCCzBNk3nz5mn5nzsKcvp3cPxmPSsji7EwqTZLWRNdrkw7FghQ9trLmIEAkfIyKhRWOrBiMSpefpVYXR3R6moqXnlN2exey7Ko/O8bRCoqiDU0UjHjVcywuskt1bPeJbxlC2YoTOVrrxNtuviooGbOvPhMftOkatY7hLdtU6Zdt+AzAt/Fl7OsnTef4Jq1yrQbln5F45dLAaj//Asav1FXMcC/ciV1nywAoHH519Qvant8WnsIbdhIzez3AQiUlFD74cfKtCMVlVS98SZWNEp4w0aqm7ajgpg/QMXLr2IGgkS2l1I18y1l2gcsNhsb4/+Dyth8uyk2w7pi8wcs06LqrbeVxmb9x58T+C5uTmrfmUewWF1sznjNz7PTGgB4Zmojb76jZxJhR8G0DG0vFWzdupX6+vpWJrWZvLw8TNOkpKSEaDTKunXrdtsOYOXKlQAUFxeTk5OzyxjYttp1796dzMzMVu0GDBiAYRiJdocqYmg7OB4jjSpzOzGiVJhbcRupyrTtHg/hslKiNdUE1qzG5lA3AsWw2zH9fiJbtxHeuAlisR0Ziv3VNgzAILTuB6Ll5cRqarC5nEq0AQyPm8D3qzAbGgiu+wFHeroybUdGOv7lX4Np0rBoCc4ePZRpO7OyaFi8BIC6jz/F1Sdbmbar1xHUfxbPAtR/uoCU7N7KtFP69KHu408AaPhiEa6e6o6Jq3cv6j79DIDGL7/C0bXLHv5i73F07YJ/xbdYoRD+Fd9iT0tTpm33eohsLyVWXU2wZDWGU+H5rTs2DY2x6XYTWNkUmz9ois1YjIbFX6qNze7daPwsHpv18z/DdaS62PzJ0S5eeDluYp+d1sixP9FTVUbYQXV1Nbfffjunn346gwYN4vzzz+fFF18EoLKyEoDOnTvv8nfNv6usrKSuro5IJPKj7aqqqhJf96edy+UiLS0t0e5QRQxtB8cwDLJsOy5+3exqx7+k5hfu+N43SKm2t8iX+N7T4nsl2oNaaA9SrN1iX72K99vjK0wM7/D6CpUZCQB3zgCMphJpnrxcbArLpTl79sTRJX6hdPY6AkcXdcbQnpZGypFHAmDr1AlXnz7KtA2HA09BftOG7HjyB6rTNgw8RUWJn71FhT/Set/xaDwPtcbmAdJOpthMGTgAw+sBwD1wADa3utgcmOugb5942YSfHO2k1xGKSyh0MDpChnbz5s306tWLCRMmMGnSJLKzs/nnP//JM888QzgcrwXscrl2+Ttn041pMBgk1FRGcE/tAEKh0H61a24b1FResKMghjYJyLLHDW2qkYHHUJcFAvAWxDthe0YGrt7qsgYAnsKCeAeh2EhAa/OmumNz9uyRyOSp1ranpZHSL27eVBvxluZNtZFoad5UHxPYsb+qjQTs2F/VJh923FipNvmwY79taWm4+qoz+dDCvCVjbHZJwti02/EMKgDAPShfrbZhMOKMeB3x88/xKNXuiBxsQztp0iQWLFjAzTffzNChQ/npT3/K448/zpAhQ5g4cWKiXaSNGs/NZtfj8ZDSFCN7agfgdrv3q11zW7emevMdBTG0SUCm0Q0nKXSzqZ+d6OrVG3undFILi5SX7rJ36kTKkX21GIm4eRsYNxJtPGLZL23DwOPzaTES0GQmNBgJiBvCll+VajcbQ596Q9uc3fRo2G+PL35jpdrkww7zpsPkx81bZy0mvzkr7tYVm/kaY7OoKTYVZvKb8RT59MXm0fEbwmZjq5Kzfxo3Kj8beegb2oNNZmYmaTsNLzIMgzPPPLNVBrStx/sVFRUAZGVlkZGRgcvl2mM7gG7duu1Xu2AwSENDQ6Ks2KGKlO1KAgzDRpY9m242deMWd2gbePMLlA83aMbj82Hz6rnIeot8RMor9GgP8mGFQsqNRLN2aO065UYC4obQ1bu38mwhxM2bo1s3UjSYfGfPnji7d9diJJozb6qHBMCOGysdhrY5K+7Oy1GuDXHzpvLRd0u8RT4iFZpis0hvbAbXrNUSm+6igTiP6IGjR5Zy7VNOSsFX4CA/79Dv0g/2wgqmaWKaJo6d5pw0m9nU1FQ6d+6cqFDQkuLiYpxOJwMHDsRut5OXl7fbdhCvdwtQWFjI559/jmmarSaGtdXuiy++oLq6utVY2pKSklbtDlWSPkO7cOFCfvOb3zBkyBCGDx/O5Zdfzscft57JvGrVKq699lqGDh3KkCFDGDVq1G5X+uioHGHvT6ZN/YUQIG3IMXgG6Ok0vYN8eDVk9CBu3ryD9QSoO2cAqcN+okXb2bMnnU49WYu2PS2NzPNHatE2HA66XHyhFiNhGAadf3GBFiMBkHH2mVpMPkCn44/XkskHSD36KC0mH+LGUEcmH5pic5DG2ByqKTZ79CBdU2za3G4yLzlfyyI2qV4b992VKQvkaGbjxo0cddRRTJgwodXvY7EYc+fOJTMzk9zcXM455xwWLlxIeXl5oo3f7+eDDz7g1FNPJTU1Prl75MiRlJSUsGrVqkQ70zSZNWsWBQUF9O/fP9Gurq6O+fPnt9rum2++SZcuXTjuuOMS7SzL4q23WldFmTlzJk6nk7POOkvdweiAJPXt3Pz587nuuus49dRTmTRpEpZl8fzzz3Pttdfy8MMPc+655+71ih0dnS42dTNud8abp6fDBHAdcYQ2bXtamtKZ5S0xHA48A3ctp6JE2zC0GQkAb6Fo76Kt8Xh7CtWOiWyJO2eANm3XET21aUtsto2O4QbN/PTUQ3t8ZDMHc2GFvn37cvbZZzNlyhQcDgcnnngifr+fl156iZKSEu655x6cTifXX3897733HqNHj+amm27C6XTy1FNPEQgEGDNmTEJv1KhRvPbaa9x0003cdtttZGZmMmPGDNauXcvTTz+daDdy5EimTp3KnXfeSUNDA9nZ2cyePZuPPvqIcePGJSaHDRkyhPPPP5+HH34Yh8NBQUEBn3/+OdOnT+eGG26ga9euB/yYHUgMS0ul/gPDBRdcQDgc5u233058oIFAgNNPP52cnBxeeuklbr/9dt577z3mz5+fKHIcDocZMWIE/fr1S6zYsTvKy+u17f8Vfa/Tpr3uH3oyGACxFI2njCQY2iZpo1Qjcq7sipwnbaPxXDE96lf+ambFzybuuVE7CTm/16adldVJm/a5n9yiTXv2qf/ZY5twOMyUKVN49dVX2bp1K06nE5/Pxx/+8AfOOOOMRLu1a9fy4IMPsnjxYizL4uijj2bMmDG7rDBWWlrKAw88wIIFCwgEAvh8Pm688UZOPrn1k4K6ujomTJjA3LlzqaurY8CAAVxzzTVccMEFu+zfpEmTmDVrFhUVFWRnZ/Ob3/yG3/72t/txZJKDpDW0lmUxe/ZsunTpwvHHH9/qvV/96ldUVFQwb948jj32WIYPH87kyZNbtbnvvvuYNm0aixYtIv1HahmKod0VMbQHgaSMUs3IubIrcp60jRjaXUhWQ3vOx/9Pm/b7pz2sTVvQT9KOoTUMg/POO28XMxuJRNiwYQN9+/bd6xU7BEEQBEEQhOQlqcfQtsWkSZOoqanh8ssv3+sVOwRBEARB6Pgc7CoHQsflkDK0M2bM4Mknn+Tiiy9mxIgRfPnll8DercRxMDB2s6KHCqxDe7GY9iGPYw880vccWJL1eCdxbBoRfQfdb8W0aSdrFyGGVtgdh4yhfeSRR5g0aRIXXHABd999N8A+rcQhCIIgCIIgJCeHhKG96667mDFjBtdccw233XZbohZf8+oZe7PChiAIgiAIHRvJ0Aq7I+kN7UMPPcTLL7/M3/72N6666qpW7/Xs2XOvVuwQBEEQBEEQkpekrXIAMHfuXB5//HFuvfXWXcxsM3u7YocgCIIgCB0byzK0vYTkJmkNbTQaZdy4cWRnZ3PcccexYsWKXV7hcJjrr78ej8fD6NGj+eijj/jss8+4/vrrd1mxo6OzIvAJm8N6SoyVzZhOzU7LBauiauZbVL87W4t2zZx5VLzymhbt+oWfU/b8VC3ajV9/w/ZHH9OiHVyzlm3/eQRTw2TH8LZtbPvPI0Qq1FcGidbVse0/jxDasFG5thWLse0/j+D/fqVybYDSJ5+mYclSLdrlL06n9qNPtGhXvfEW1e9IbLak8etv2P6IptgsWcP2CY9ghkLKtZcvD3PpryupqNQ3iUwQOjpJO+Rg+/btbNq0CYBLL720zTbz5s0jOzubl156iQcffJAxY8YkVuyYOnUqubm5B3KX94vqaCluQ082Obx1KzZ3ih7t0lJsKXq0o+UVRFpk3pVqV9cQ3rRZi3asvp7g+g16tP1+QuvXY5nqi72boXBcu41JlvtNLEboh/VajDgQ125o1KO9YRMpA/QsURveshWbpomrEpu7EqvTGJuNfkI/bAANsVlTa7HgszAHsWjPAeNgLn0rdGyS1tBmZ2e3OTa2LXJycnj88cc175FuLAwJZEEQBGEn7E01uCwzieufCcJ+krSG9nDDwkpUb9ChnrwFLAVBEJIIDZ7T3jR4MHYYjDiQKgfC7hBDmzSI6RQEQRB2xWgytBpGM3Q4ZPKWsDuSdlLY4Yale8iBtuyvIAiCoO8JG9jtce3YYWBoBWF3iKHt4PjNetYEv8K0TBpiNawPrVCmHQsEqHr/PcxwmGh1FdXz5irTtmIxqt95F9PvJ9bQQPW77ymbqGRZFtWz3ydaV4cZDFL9zmzMsLqJSrXz5hOpqMCKRan5YC7Rujpl2nWfLiC8ZStYFnUff0p4+3Zl2vWLlxD6YT0ADYu/JLjuB2Xajd+sILByFQD+b79VWjEgULKaxq+WA/GZ4A1LlynTDm3aTP1nnzd9v4n6hV8o045UVFI7/0MwTSKlpUqrEcT8Aapnv48VjhCtqqbmA8Wx+XaL2HxntsQmTbG5VU9sNnzxJcF165u+X0JwrbrYfPvtAHPnxWeDvfZfP+9/cGjPDDMtQ9tLSG7E0HZwPEYaWyKriRJme3QdhsIVuO0eD/6VK4lWVuL/7jvMQECZtmG3E966jfDGTYTWriNaWYlhU3O6GYZBrK6O4KpiItu2E/phPTaXU4k2gBmJ4F/+NbHaOhq+XIojPV2ZtmG30/DFIojFqPngA5wKV6qze73UfRQvv1Y9622cPXso03Z07kztB3MAqHn3PZzduinTdnbvTvWsd4C4YXFkqDvezh7dqZ71NgD1n36GoXBWv6NLZ+o++hQzEKBxyVKw1A2OtHs9BL77nmhFBYFvNcTmtpaxWSWxCRh2Bw2fN8Xme2pj05bqpX5+/IaneuY7OI9QF5v9BziY9Ei8gsfESY0MzJORhMLhiRjaDo5hGHRzZCd+7u7sq1Tf6/O1+b0S7aIdep6iZNIuanM7KvC0OMaeggIMu7obFPfAPAxnvDNzD+iP3etVpu3K7o29yWg6srJwdlfX2TsyM3Bl9wbA5vWQ0r+fMm2by4V7YF7TDzY8hfnKtA2bDU9RYeJn7yDF50qLc0/1edjyHJfYjOPx7fgsPYWKYzM/D8MZN/YpOWpj01foIDs7vq85A+z0739oG1pZWEHYHWJok4CsJkPbydYFjy1NqXZqYbxTsHk8uI/sp1Q7Yd5sNjwF6owEtDZvqo1ES/OmutNsad5Ud/Y2lwt3Xp4WbcMw8BTGO3zVxwR27K9qIwE7TJBqkx/Xju+3IytLaUYPwDsovt+qTT60MG+KTT5IbLaFzeXEnR+PTe+gwj203jcMw2DkOfEnD2ec4VaqLQjJhBjaJKCLoxcGNuXZWQBX797Y09PxFhQqNxLNHYQOI9GceXN0V28kDMPA4/NpMRLQ1FlqMPmww7zpMJ3Nmlq0m8ybaiMR1yzUpt1s3lQbN9hh3nSYfInNtknEpmKTD+AZ3HTTpuFcOfecuJE98ww9C2V0JGQMrbA7Du1nE4cIDsNJZ3sPshzqDa1hs+EtKMTTlNlTjafIh82tJ2vgLSrSthqRt8iHFQopNxJx7SJCa9cpNxIQz7w5u3dXbiQgbt7sGelajIQruzf2zpl4CgqUazsyMnD1ydZiOpvNmw6T32ze3Hk5yrVBYrNN7UEaY3NQYdzk91Afm8OHu+jd287xx7mUawtCsiCGNkno4yqgk62LFu3UwYOVDzdoxuvzYfPo6TQ9vkKcleo7BwB3Xq62oo6u3r3odOIJWrQdmRlknHO2Fm2by0Xnn1+gxUgYhkHnC87H7tWzzGv6T0/TYvIB0o4dpsXkA3iPGkTKkepvZCFu3nQtfZu0sZndW19sZqSTed4IPdoOg7F3dSIl5dDPMiqceykcYhiWJafHj1FeXq9Ne1TuLXvd1rL2baWwNX8fpE3bdOz9KbOv2vtaanef9PfxTN/nfRftXdmHph1qv0X7wOrrjk2N56Gl8Xr4xS/+rU3b7tq7pePbQ1ZWJ23ax87+P23aS869T5u2oB/J0CYJOjueZNXWrS/aoi3aHVNftA+sdkfClBUzhd0ghlYQBEEQhKRAymsJu0OqHAiCIAiCIAhJjWRoBUEQBEFICqS8lrA7xNDugVH9b9SmvfbvQ7Rp78vErQ5Fku62duQafmDReR7KZ3lIYUT1faDHvf1nbdpLfqa+1u4OtmrUFoS2EUMrCIIgCEJSIHWZhN0hY2gFQRAEQRCEpEYytIIgCIIgJAVS5UDYHZKhFQRBEARBEJIaMbSKiFlRVgQXUBur0KJfPvO/1C9bqkW76s23qP9ikRbtmg/mUvvhR1q06xZ8RvU7s7VoNyz9isrX/qtF279yFeVTX9CiHVq/gbLnpmCGQsq1I2XllD03hWh1jXLtWEMDZc9NIbxF/WQSKxaj7LkpBFavUa4NUDH9ZRq/WaFFu2rmW9R/sViLttbY/DSJY3OKntgMaozN8OatlD8xjVhDo3LtSMTi+puqWfJlWLl2e7AsQ9tLSG7E0CrCwmRbbB0Bq0GLvr94FeGyUi3agZLVhLdu06Id/OEHQhs2atEOb9pMcM1aLdqR7aUEVupZGjJaWUnjim/1aNfV4f96BVYsplw75vfj/3oFZjCoXNuKRPB/vYJYg6b4+XoFMQ1GHMD/3fdEysq1aMdjU8+M8eC6Hwitl9hsSbRCX2zGamubYtNUr13XQGDZCqywetMZjlj8940gm7eov6a0B9MytL2E5EYMrTKag0HTFEzLwjDk4xIEQRBaY9ia+gZTff8Ti8a/OuzKpQVBKTIpTBFGk6HVVVHEskw4TNbqFgRBEPaBpr7B0lDTKtqUmLXbO0b/I2W7hN0hKT/laIo20wKbfFyCIAjJiUZDaGvSNjUMZ4jF+zS7pL+EDo44JEXoztBiWRi2jnGHLAiCIHQcEsPRNKQvO9qQA5kUlpzMnDmTbdt+fK7Op59+yjPPPNPubYihVUBdrIrS2AYAGsxqtkTUTYaIVFVRt3QJlhkjVl9P3dIlyrRjgQB1ny2EaAyzsTH+vSKsWIy6jz/FCocxQ6H494qyB5ZlUffJAsxAACsaiX8fjijRBqhf+AWx+nos06R+0WJi9fXKtBuWfEm0qgosi8blXxMpK1Om3bj8ayLb4xMHAyuLCW1UN+HH//1Kwhs3ARD6YT2BktXKtIPrfiDYVIEgvGUr/m+/U6Yd3roVf9Mkn0hFBQ1fLVOmHamqouHLpWBZxGprqF+krhpBzB+gbkGL2FyQZLEZDGBFkiw2F+8Um6WKY7O0OTZXKY3NwHfFhDfHJw4GS9YRXKkuNhd8FuLd9+KTQL/9Psrs99VPCBUOD/73f/+XFSt+vBrM2rVrefzxx9u9DTG0CvDaOvFtKN7hrI98p/TBkiMzk8p33sL0+6lduIBYXZ0ybbvHQ/2Cz4iUldH41bKEGVKBYbfj//57Qut+ILiqmOC6dTsmLuyvtmEQ2rQJ/4pvCW/eQuOyZdhcTiXaANGqKhoWLSZWU0PN+3OwpaUp0zYDAeo+/BhiMSpmvIKjSxdl2gA1774HQMULL+Ho3FmZrs3tpur1mQBUvvIadoXHxJ6eTsVLLwNQ/dbbGA51zzYdXbpQPu0lAGo/mIsViarTzsykauabmH4/9QsWEqtTZ67s3haxuXRZwgypwLDb8X/XIjbXaojNb5pi86skjc3pr+DomiyxmUL1jJkAVL/0OrZO6o5J3752/veOeJ9z37h6UlMPfhazI2RoFy5cyG9+8xuGDBnC8OHDufzyy/n4448T71955ZXk5+e3+XrooYdaaa1atYprr72WoUOHMmTIEEaNGsXixbveHG/evJk///nPHHfccQwePJiLL76YDz74YJd2VVVV/P3vf+ekk05i0KBBnH/++cyYMWMfjrA6Vq1axcyZM5k5cyaWZbF48eLEzzu/ZsyYwauvvko02v5rtIyKUYDDcNLVfgQVsS0AdHP0VqZt2Gx4B+bTsDyeWUr1FSnTBvD4fAkj6y3yKdX2FvkINmXyPL5C5dqNXy5t0la73x5fIbXz5jdtpxBD4WQ8j88Hb7wZ/z5/oFLz5inIB7sdYjFS+vbF3qmTMu2UfkdiS03FbGzE3jkT5xE9lWk7u3XF2bMHke2lGCkpuHNzlGnb3G7cOQPi56Fh4PUVKNM2bDY8hYWJ81B1/HiKWsSm4nO8VWwWaYjNJU2xqfqY6IzNouSMTVf/vtg6pWHWN2DvnIGzt7rY7NvHQV6undVrYmRmGJxwnEuZdrIyf/58rrvuOk499VQmTZqEZVk8//zzXHvttTz88MOce+65ABQVFTF27Nhd/r579+6J7zdu3MgVV1zBgAEDGD9+PG63mylTpnD11Vfz4osvMmTIEABqa2u5/PLL8Xg8jB07lq5du/L6669z8803M3HiREaMGAFAJBLh97//PRUVFfzlL3+hT58+fPjhh9x1110Eg0F+97vf6T9ALfj000+ZMGEChmFgGAYvvvjij7a3LIuRI0e2e3tiaBWRZe9DRWwLGbZuuAy3Um1vgY+G5ctwdu2Gs3sPtdpFPurmf6jcSECLDsIw8Co2tC07CNVGoqV58xapvYFwduuKs0cPIqWlyjv7lubNM0ittmGz4fEV0LhkKd4in1IjATvMm2ojATvMm2oj0azd+OVS7J07KzX5zdp185piM09xbA6S2NyZljdWWmIzN4dgcYme2DzKR+Nni/EMKlAem2f81M3qNY2MONuN09kBMrQHefsPPfQQ/fr1Y/LkyTid8acPw4cP5/TTT2fatGkJQ5uamsrgwYN/VGvy5MnEYjGeeOIJujQ9rRs6dCgjRozgoYce4vnnnwdg6tSplJWVMWvWLPLy8gAYNmwYa9euZfz48QlDO2vWLFatWsWTTz7JaaedltDbvHkzEydO5LLLLsPtVutPfow//vGPXHTRRSxfvpwbb7yRkSNHkpub22Zbu91Onz59OOecc9q9PTG0isiyZ7MS6GbPVq7tzcuPdzxFg5RfrOIdhBd3To5yI+HsGu8gbClu5Uai2bxFyiuUG4l45q0A/4pvlZt8aDJvZWV4C9VlC5tpNm+qjUSzdtzQqjUSzdp18z5UbiRgh3lTbSRgh3nTYfKbzZs7Z4DEZhMHJDZLy5Rm8pvxFvkIFpfoic0hcUPrLlK/32f+NIUnnmrk3JEHzgj9GAdz8pZlWVx33XV06dIlYWYBPB4PRx55JNu3b98nrblz53LiiScmzCyAy+VixIgRTJs2jbq6OtLT05kzZw75+fkJMwvx4T3nn38+9913H8XFxeTn5zNnzhwyMjI45ZRTWm3rZz/7GbNnz2bhwoWcccYZ+3EE9p1u3bpx1llnceyxxzJq1CiGDRumbVsyhlYRbpuXdFtXsuzqhhs0Y09NJaVPX+XDDWDHY1MdRgLij9h1aXuLfFqMRLO2jmxhs7aObCHEzZuji/psIcTNm83rVZ4thCbzlpamxUg0mzcdRqLZvOnQbs6Ka4vNIp8Wkw9NsTlIYrMlnqJCLZl8gJSCPGxeD+6CtrNf+8Nxw1107WLj9NNSlGsnG4ZhcN5553H88ce3+n0kEmHDhg307dt3r7W2bt1KfX19K5PaTF5eHqZpUlJSQjQaZd26dbttB7By5UoAiouLycnJwbbTmPid2x0Mpk2bptXMgmRoldLHkU8nm9qJBM2kDxuOu28/LdreQUW4B/TXo13kw6bpEYfH58NZUaFHuyBfy/KxEDdvaccdq0Xb2bUrGWeeocVI2NxuMs8fqcVIGDYbnc89R4uRAEg/5WQtRgIg9SfHaMkWAngHDcI9oJ8ebZ2xWZTEsXm8xtg866d6YtPlJOMXI7G51ZtOt9vg73/rhNdz8IcbAAd/zEEbTJo0iZqaGi6//PLE76qrq7n99tv54osvqKio4Mgjj+Tyyy/niiuuAKCyshKAzm1MEGz+XWVlJXV1dUQikR9tV1VVlfhaULBrUmDndgeLqqoqPvnkE0pLS4lE2q5+YhgGN9xwQ7v0xdAqpJcjR8vFCqDTsOHKZiLvjHfwIG3aKf2O1LbCmbNbVxxd1M0WbonN7Sb1mKO1aBs2G2nHDdeiDZB2wnHatDudcPyeG7UTnfuddsJx2mIz7dhhGmOzSGJzJ5I5NrXGz8n64ufXl3q0aSc7M2bM4Mknn+Tiiy9OjGWFeFWCESNGMGHCBOrq6pgxYwb//Oc/CQaD/OEPfyAcDgPxIQY70zycIRgMEgqF9qodQCgU2qt2B4MlS5YwevRo/H7/j65oJ4a2g6CrwwS0dWrJrK1bX7RFW7Q7pr5oH1htWwda1KcjLYDwyCOPMGnSJC644ALuvvvuxO8nTZqEw+EgrUVZudNPP51f//rXTJw4kV//+tekpMSz6W1lKpvNrsfj2et2AG63e6/aHQwmTJhAKBTiwgsvZMiQIVomp4mhFQRBEARB2AfuuusuZsyYwTXXXMNtt93WKqGVmZm5S3vDMDjzzDP5+uuvWbNmDT17xodAtTUMoKJpuE5WVhYZGRm4XK49toP4BKy9aXcwWLlyJaNGjeL222/Xtg0xtIIgCIIgJAUaVvfdZx566CFefvll/va3v3HVVVft8r5pmpimiWOn+QbNj/xTUlLo2bMnnTt3pri4eJe/Ly4uxul0MnDgQOx2O3l5ebttB/GatwCFhYV8/vnnmKbZamLYzu0OBk6nk8JCtSUCd0aqHAiCIAiCIOwFc+fO5fHHH+fWW29t08xu3LiRo446igkTJrT6fSwWY+7cuWRmZiZqsZ5zzjksXLiQ8vLyRDu/388HH3zAqaeeSmpqKgAjR46kpKSEVatWJdqZpsmsWbMoKCigf//+iXZ1dXXMnz+/1bbffPNNunTpwnHH6RtnvScKCwvZtGmT1m1IhnZPKFrjvC0suzbp5KXjDI8SOjodIFPTLpJ1v4UDjhHVd0F0G8nZAR3MMbTRaJRx48aRnZ3Ncccdx4oVK3Zpk5+fz9lnn82UKVNwOByceOKJ+P1+XnrpJUpKSrjnnnsSk7Suv/563nvvPUaPHs1NN92E0+nkqaeeIhAIMGbMmITmqFGjeO2117jpppu47bbbyMzMZMaMGaxdu5ann3460W7kyJFMnTqVO++8k4aGBrKzs5k9ezYfffQR48aNa1U790Bzyy23cMsttzBixAgGDhyoZRuG9WPTzQTO8V6pTXvNP4/Rpm06kvRjFUMr7C1JeooLB4Ekva5YGq/j31z0H23a6b30ZeJyZtynTXvtZf/3o+9v3ryZM88880fbzJs3j+7duzNlyhReffVVtm7ditPpxOfz8Yc//GGXhQ3Wrl3Lgw8+yOLFi7Esi6OPPpoxY8bssspYaWkpDzzwAAsWLCAQCODz+bjxxhs5+eSTW7Wrq6tjwoQJzJ07l7q6OgYMGMA111zDBRdcsA9HQj1Tp05l+fLlvP/++xx//PH079+/zYoMhmHwl7/8pV3bEEO7B8TQHmCStOMRDgJJeooLB4Ekva6Iod2Vg2lohfZTUBBflnlPltMwjHYvACFDDgRBEARBSAokBZec/Otf/9K+DTG0giAIgiAIgjYuuugi7duQKgeKsCyTkshX1JmVWvSrZr+Lv2TXsh0qqJk7n8avv9GiXffZQuoXLdai3fDlV9R+9IkWbf9331Pz3gdatINr11L1xltatMNbtlL535mYTYW0VRKprKLyvzOJ1tYp1441+qn870zCpWXKtS3TpPL1mYQ2bFSuDVD99rsEiku0aCdtbC6V2NwZrbFZUUXVqzOJ1amPzZpakzvvrWHN2raXKj3gWBpfwgFhw4YNfPbZZ9TW1irVFUOrCAtYH/2eBlPtB9RM3aIvCG/erEW7cdkygmvXadH2f/sdgZWr9tywHQRLVuPX1NmH1m+gYcmXWrTDW7dT99lCLdqRykrqP12AFY0q147V11P/6QJMv1+5thUOUf/pAmI1Ncq1sSzqP11ApEy9WQao/2IRoU0Smy2R2NyVSIW+2DTr6qj/+DNijQHl2vUNJv+Z3MDGLTHl2sLhxcKFCxk5ciQjR47kmmuuoaRkRyLgqquu4uOPP94vfTG0giAIgiAkBZZlaHsJ+lixYgXXXnstpaWlnHjiia3eq6qqYs2aNdxwww0sX7683dsQQysIgiAIgiBo46mnniIzM5O33nqLhx56qFW1gy5duvDmm2/SrVu3VnV19xUxtIIgCIIgJAcyhjYp+eqrr/jNb35Dnz59MIxds+FZWVlcdtllLF26tN3bkCoHgiAIgiAkBTI0IDmpqamhb9++P9qmd+/e1NfXt3sbkqFVQINZQ7VZCkDQ8lMWU1dUOlpdTWDNarAszFCIxjaW2msvsUAA/4pvwQIrEqFx2XJl2lYsRsNXy8A0498v/QpL0TLClmXF9WJRMC0aly3HDKubgdu4/GvMUBgsC//3K4ntR4DtjH/Ft5iB+MSN4LofiJRXKNMOrCxOzHIOb95CeMtWZdrBNWuJVlYBECkvJ/jDemXaoY0bCW/bDkC0uoZAyWpl2uHt2xPVDWINDfi/+16ZdrS6msDq1YCFFQrS+I3EZiI2o1GwNMVmOAxY+FdKbAIEV68lWlkNQLSsnOC69cq0lywNsezr+Oe37ococz8KKtMWDi8yMjIoLy//0TZr164lMzOz3dsQQ6uAFMPDV+H5AKyJLidsqQt6e6dObJ/yPKbfT838eYS2blGmbXO7qXprFpFt22j4YpFSI2HY7dQvWEiwZDWBb7+jcelXGDY1p5thGPhXfEfj0mWENmygdt6H2Fzq1qgO/bCe+k8+JVpVTeWMV7ClpirTjpSVU/PuexCNUvrYE9jTOynTjjU2UPXaGwCUTn4CW6pXmbZlmlRMexGA8menYNjVXToMVwplTz4DQOWMV7AUljWyd+rE9kcfA6D6rbeJKqyiYO/UibJnp2A2+qmdO5/wFolNwzDwf/sdjV8dgNicnmSx+V+NsTnlJQDKn5qCYbcr0+6caePKP8ZLUd76fzVEIx3gubwMOUhKhg4dyssvv7zbDOyiRYuYOnUqQ4cObfc2xNAqwGmkkGnrnvi5m723Mm3D4cCbn5/42evzqdM2jFZ63iJ12jvreVRrD9Kn3VLP4/Mp6+x31nbn5WJLSVGnXVgATWOTXNm9cezHne7OuAf0x3C7AbCnd8KVna1M29mjO45uXQEwnA7cA/OUadtTU0npd2TiZ5XnuOFw4CloEZsqtZM5NjVqe3aKe4lNcOfsFJt91PU/uTlOcgfERyZ63AannexWpi0cXvzpT39i69atXHLJJUyePBnDMHj33XcZP348l112Gb/73e+IRqOMHj263dsQQ6uILFv8IpJudMFtqLv7BvAWxi+09k6dSOmtzkjAjg5CtZFoqQ3qO+SWHYRqbXfOgEQH0dI4q6CleVPd2dtTU0np30+LdkvzptrkG4aR+AzdeXnYXC5l2rDj/HD1VmskWmrbO6k1+SCx2RbuAS1iU7F2Usemryk2iwqVxibAyLPix/v0U1LweDrC+FVD40vQRVFREY899hihUIjnnnsOy7KYPn06Tz/9NMuXL6dHjx489thjFBYWtnsbMilMEVn2bEqiX5FlV9upAXgLCsEw8PqKlF+s3P3jd/fu/v2UGwln93gHYUtJUW4kmjuIaEUFrmx1GQmIP5L1FOTj//Y73Hm5arUNA4/PR/0nnyrvkCHeyYfW/YC3qP0Xhd1qD/LhX/61Fm1PkY+6jz/Fo0m7etY7erSbzJvqbCEkeWz2k9jcGZ2x6Rnsw//V13gGq9ceebabR55sYOTZkp0V9o+TTz6ZOXPm8OWXX7J69WoaGxtJS0tj4MCBDBs2DPt+DpcRQ6uIVFs6XqMTWQqHGzRjT03F3a+f0uEGzTRn3ty5Oeq1mx6bGm51j+5a4i3yESmvUG4kIG7erHBI6WPHltqhdeuUGwloNoafKM8WQty8GS6X8mwh7BjSoMNINJs3HdrN5k2HdtLHZoWm2CzyYYUkNltp+5piM3+gcu3jj00hM9Ng5Fke5drtQsa6JjVOp5MTTjiBE044Qbm2GFqF9HEMpJPRRYt26lFD8OSqNxIA3kFFuHMGaNH2DPJp6Xgg3kE4K9TNRG6lXViAFVG/RCXEzVvqsPYPfP8xnD26k37aqVqMhD01lcxzztbyeRoOB5lnn6nFSBiGQacTjtdiJABSjx6ixeRDEsfmIB9OhVUCWmkXFmhZPhaSOTa9ZJx7FrYUtZl8AKfT4H9uSadnD3WTzYTDl61bt1JaWkr0R2L42GOPbZe2YbVcrkHYhXO8V+51W9MysRl7f7Fa889j9rqtFY1iOPb+/sN07P3Huq/a+4IVi4Fh7P1FfB+GMVmWBbGYvn3XeVxEe/+19+HK1aH2u6No72ts7ot2R4vNfbmudKDP09J4Hf/mov/sddtIxMLp3PuDmN5LXenKnen3/P3atNf/7q/atA93tm/fzk033cS33367x7YrV65s1zbaHbUrVqzgyy+/ZPPmzVRVVVFXV0d6ejpdunQhOzubYcOGMXjw4PbKJyX7Ymb3FV0XWO3aCkvI7KJtGJCsx0W0Rftga0tsivZesi9mVjuysEJScvfdd7NixQp69+7NUUcdhdutfkz2PkVANBpl+vTpTJ06lc2bNwOwuwSvYRj06dOH3/72t/z617/GoTHYBEEQBEEQhI7J4sWLOeuss5g0aVKbS9+qYK9d5jfffMP//M//sH79etxuNyeddBInn3wy/fv3p0uXLqSnp1NXV0dVVRU//PADn376KUuXLuXuu+/mhRde4P777+eoo47S8k8IgiAIgnDoI4Mkk5NwOMyZZ56pzczCXhra1157jX/84x9kZmZy5513ctFFF+Hx7H7G42mnncbvfvc7AoEAr7/+Oo899hiXX345Y8eO5Ze//KWynRcEQRAEQRA6Nn379qW2tlbrNvZq0Ocdd9zBL37xC95//30uv/zyHzWzLfF4PFxxxRV88MEHXHjhhdxxxx37tbMHBZtN30uW8NsVncdE90vYFTnehw4669nrfiUrGo9JDEvbSytyTUlKrrzySl577TVCoZC2bexVhvbuu+/m0ksvbfdGvF4v9957L0cffXS7NQRBEARBEITk46ijjsLn83Heeefx61//mn79+pGym7KBp512Wru2sVeGdn/MrA4dQRAEQRAOQ6TKQVLyi1/8AsMwsCyLhx566EfbHvCyXe+//z4ffvgh5eXlRCKRNtsYhsGUKVPauwlBEARBEAQhyWk2tDppl6F97LHHmDhx4m5LdjWje+cFQRAEQTh8MGSsa1Iybtw47dtol6GdOXMmWVlZ/PWvf6WwsHC34yAOJyzLYmN0FV3tR5Bmy1SuX/vpJ6T07Yv7yH7Kteu/WISjc2c8GtYBb1y2HOx2Uo9Sv8iG/7vvMf1+0o4dplw7uGYt4dJS0k86Ubl2aNNmgiWryTjzp8q1I6VlNH6zgvTTTsXmcirVjtbU0rDkSzqdcBz2tDSl2mYgQN1nC0k95micXbsq1bZMk9r5H+L1+XD1OkKpNkDtx5+QcmRf3P36KddO6ths9JM2XFNsbi8l/WSJzWaiNbU0LlpK2onDsXdSG5t19SYvveznZ+e6ye7dAerJi6E9JGhoaMDv95OamkpqaqoSzXYtbbV9+3auvfZazj//fAYMGEDv3r13+zpcsLAoDi+hLlapRb96/lyC69Zq0a77dAH+777Xol2/eAmNXy3Tou3/ZgX1C7/Qoh0oLqFu/kdatEPrN1A9+30t2uHSUmremY0VbXsY0P4Qramh5p3ZxOoblGubwSA178wmWqEhfiyLmndmE96yRb02UDtnHsE167RoJ21sfr2C+s81xuaHH2nRTtbYjFXXUPOWntisqzP5v7tqWb02qlxbOLyoqKjgH//4ByeffDLHHnssp512GsOGDeP000/n/vvvp6Fh/87fdt1uHXHEEbLylyAIgiAIBxaZFJaUlJaWcumll1JWVobT6eTII4/E4/Hg9/vZsmULzz33HB9//DEzZswgPT29XdtoV4b28ssv59VXXyUcDrdro4IgCIIgCMLhweTJk6mqquLOO+/kyy+/5L333uONN97g/fffZ/Hixdx2222sX7+eJ598st3baFea9aqrrqK2tpaRI0fy85//nN69e+N0tj0m6Be/+EW7d04QBEEQBCGBjKFNShYsWMBvfvMbLr/88l3e83q9XHPNNWzcuJE5c+Zw2223tWsb7TK0y5Yt46WXXqK6uponnniizTaWZWEYhhhaQRAEQRCEw5iysjKKiop+tM2QIUOYOXNmu7fRLkP7r3/9i5qaGk466SR8Pt9hX+Wg0azDJAZAlAhVse10sfdUoh2trcUMBACwYiaBtWvw5OQq0TYDASJl5fEfLItAyWo8A/OUaFuxGMF1P4BlxbWLS3Dn5WLY2jXKpbW2ZREsWU3zrXpw3Q+4srOVzRwOrF6NZcY/z9DmLTgyM5TN6g+uXYsVjU+uiJSVYzjsOLp0UaP9w3qspmFAsZoaYvUNuHp0V6Id2rgJ0++Pazc0ENq8hZRsNZM+w1u3YUXi+20Gg4Q2bCDlyCOVaEfKK+LnIGBFIgTX/YB7QH8l2tHaWkx/PDYxYwTWrMGTK7GpNTZLVmPFJDZbEtqwKXEemg2NhDdtwdVHTWyu+DZMQ2P8s6yqNvliSYjjjz3I/b1kaJMSl8tFTU3Nj7YJBAK7fdq/N7TrClZSUsJVV13FM888w6233sqNN96429fhgMNw8kXgbQBWhRfTYFYr07Z5vWx5ZCKm30/13A/wr2rfChptYbjdlD0/hcj2UuoXfk7D4iXqtO12qme9TXD1GvzffkftvPlKOkyI1zeuW/AZDV9+RWjjRipfeVVpGRz/8m+o++gTotXVlD7+BDaPR5l2cPVaqme9A9EoWx+coFQ7sr2UipdeBmDr+Icx7GqON0Csvp6yp58DoPSxJ7EUrsdtmSbbJj4KQPnUF4hWqYsfw+ViywPjAaj87xuENm1Spm3zeNn2n0mYfj81788h8P0qZdpJHZufNsXmho1UvqwpNquqKX1MYhMgVt9A2eNNsTnpSUyFsWmzGfzslxUAXHtDNWVlpjJt4fAiLy+P9957D9Ns+xyKxWK8/fbb5OW1/8a9XVHl9XopLCxs90YPNVIMD+m2HbUzs+x9lGnbnM541seywDTx+n48Zb8vGIaB1+cD04xrF/mUaQNxvSZtTxJpe5q1LQtPQQGG3a5Oe1BRXBtI6ddPaafp8RUmtJ1Z3XB266ZM252XlzgONreblH5qMqgArt69sKd3SvzsKchXpu3ISMfVu1f8B8XnuM3lxJ3XIjYVaktsto1nUIvYLJTYBHAPzN0Rmx43Kf3Vxaav0EHvXnFtpxN+eloHeBpraXwJ2rj00ktZvnw5v/71r3nttdf4+uuvKSkpYfny5bzyyitccsklfP31122Osd1b2mVoTz/9dBYtWtTujR6KNJvYNCMTj01tYWtvYbxTsHm9uPuqu1gBOzocm02pkYhr7zDfqjtkT4sbKu8exuXsK+68XIymrJLq/Xb17oU9MwNAeWfvyEjH1bePFm2by4m7qbi/x6fWSCTMG+DOyVFqJGDHZ+js0V2pkWipbfN6lZp8SOLY9LWIzUESm3AAYrMgntXSEZsjz3YDcNIJKXRKU5dZbjeWoe8laOOXv/wlo0aNYsWKFfz973/nsssu48ILL+Q3v/kNd911F6tWreLaa6/l5z//ebu30a6z829/+xuVlZX885//5Pvvv6e2tpZAINDm63Ahy5Hd6qtKmg2tt6BQ6cUKdnQQOoxEcwehw0g0dxA6jITN6cQ9cKAWI9HSvHkHqe3YYEcnr9pItNJW3CHDjk5ep7ZqIwE7bqxUZwtBYrMtJDbbxjPY1+qrSkacFTe05zR9FYT2cscdd/Df//6XP/7xj5xxxhkcf/zxnHnmmYwePZq33nqLP//5z/ul365JYT/9aXxZwE8//ZTp06fvtp1hGHz/vZ5VbjoaaUYmbiOVLLt6Q+tITyclu0/C2KqkuYNw5+Yo127uIAxNkwa9vkIi5RXKxv+10i7yYYVCyo0EgKeokODatcqNRFzbR93Hn5JyZF/12r5CsNuVGwkAd27cvHmK1A9lcvWKm7dms6ISR0Y6rj7ZWox40sdmhcRma22NsTmoEBx2PD71SySffEIKqd4dmdqDjSFDA5KaoqKiPVY7aC/tMrRpTbNK0xSv557MGIZBb0cuGTb1F0KA1MGD8Q5UbyQg3kHo6DQhfhG3aeo0PUVFOMvL9WgXFiZmJavGnZdH6jFHa9F29e5FpxOPV54thLh5y/jpaVqMhM3lJP3UU7QYCcMwSDv2WOXZwma8Rx2lxeRDEsfmII2x6ZPY3BlHRjrpZ+iJTbfb4IbRafTtI6uDCvtPVVUVX331FRUVFdTV1ZGZmUn37t055phjyMjI2C9tw7Ksw+J+Z9WqVfz73/9m6dKlRKNRBg8ezM0338zw4cN/9O/OSfvtXm8jZkWxG3sf9GvuGrLXbc1wCJtr7zsf07n3H6sZCmnr2MxIBMNm03IRtywLKxLB5nIp14Z2HJd9GIKl9Zh3JO19uLp0qP0+HLT3NTb34fzucLGZpNrWPl3Hw9hS9v54L/vFw3vdNhCw8Hj2/gTo3GvzXrfdV/pPmqBN+4ebbt2rdu31E4czsViMf/3rX8yYMYNYU+m95vUKAJxOJ7/73e8YM2ZMu7dxWNxybdy4kSuuuIIBAwYwfvx43G43U6ZM4eqrr+bFF19kyJC9N5Y/xr6Y2X1lX8zsPmtrrCNs24+acnvCMAwMTR0maD4uoi3aB1tbYvMQ09Z3vPfFzB7qHCg/cajx5JNP8sILL9CtWzfOOOMMevToQVpaGvX19WzcuJGPP/6Yp556ioyMDP7whz+0axvtdmDRaJRly5ZRWlpKtKkYdVt0hJXCJk+eTCwW44knnqBLU6HsoUOHMmLECB566CGef/75g7uDgiAIgiB0eMRPtI/XX3+dwYMHM2XKFLxe7y7vNzQ0cNVVV/Hyyy8fWENbUlLCtddeS2lp6W7bdJSlby3LYu7cuZx44omJkw/iq1aMGDGCadOmUVdXR3p6+kHcS0EQBEEQOjLiJ9rP9u3b+dOf/tSmmYX4nKzLLruMe+65p93baPfSt9u3b+fYY49lyJAhuN0dY/ZjW2zdupX6+vo2V5/Iy8vDNE1KSkoYNmzYQdg7QRAEQRD2loNZ5UD8RPvp3LnzblcJa8Y0Tbp27fqjbX6Mdhnar7/+ml/+8pfce++97d7wgaKyshKIH8ydaf5dc5s22cMHIAjCj5CsQ+8Oi6mywuGMeXjMB1fKfvuJw5gzzzyTjz76iF/96le7bfPJJ58wYsSIdm+jXUUCLcvi2GOPbfdGDyThpvIurjYmKDibJkUEg8EDuk+CIAiCILSDg7hSmPiJ9nPrrbcSDoe54YYb+PTTTyktLaWxsZHKykoWL17MmDFjiEQi/OlPf2r3Al3tytDm5uZSrqnGoGpSmmaVRiKRXd5rPjk9Gmr3CYIgCIKgmIOYWBY/0X6OO+64xJCD+fPn77bdSSed1OrnfVmgq12G9tprr+W+++7j4osv3q/xDgeCrKwsIF7Md2cqKipatREEQRAEQWgL8RPtp0ePHtq30S5Da7PZGDZsGOeccw7nn38+/fr1azMFD3DFFVfs1w7uLz179qRz584UFxfv8l5xcTFOp5OBA9UvFygIgiAIgmIOYoZW/ET7+bGsrCraZWhvuOEGDMPAsixefvnlxEoPLWku23WwDS3AOeecwxtvvEF5eXni7snv9/PBBx9w6qmnkpqaut/bsCyL0thGMmxd8djULwncsHwZrh49cR1xhHJt/7ffYe/UScsa44HiErDb8OTmKtcOrvsBMxjE6ytUrh3atJloVRWpQ45Srh0uLSO8cRNpxw5Vrh2tqiK4Zi2pPzkGw6F2oY9YQwOB71fiGTQIu1ftYzUzFML/9Te48wfi2M/lD3fGMk0av1xKyoD+WpbWbfhqGa6ePXH1kthsRmJzV7TGZn0Dge9W4T2qCJvi2Gz0m8yZF+KE41z06K5+xcdk40D4CaF97JehTRauv/563nvvPUaPHs1NN92E0+nkqaeeIhAI7Ncyay2xsPgm8imDnCdqMbQVb75B5qmnaTG01bPfw52To6XTrP3oY2wpKVo6zYZFi4mUlWvpNP3frKDxq2VaOs1gyWqq3pylpdMMbd5CxUsv4xlUhF1xpxmpqKTipZfp9dc+6g2t30/FSy/T47prlRtaLIuKl16m2+WXaTG0Va/PJP3007QY2qSNzS8WEymX2GyJztiMVlRSOe1lXH+7FZfi2KyuNrnmumpee6lLhzC0B7NsFxwYP3GoEg6HWbZsGeXl5VoW5GpXVN10003t2tjBokePHrz00ks8+OCDjBkzBsuyOProo5k6dSq5Gi7mgiAIgiAceoifaB9fffUVN9xwAzU1Nbtts78Lcu2Vof3Pf/7DLbfc0q4N6NBpDzk5OTz++OMHZduCIAiCICigA5TPFT+x7zzwwAPU1NRw4okn4vP5EhUjVLJXhvapp55ixYoV3HPPPfTs2XOfN7Jt2zbuuOMOFi1adNAMrSAIgiAIgnDgWb16NaNGjeJvf/ubtm3s1cIKkydPZvny5Zx99tmMHTuWzZs375X45s2b+cc//sGIESP4+uuveeyxx/ZrZwVBEARBOIyxNL4EbaSkpFBUVKR1G3uVoT311FN54403+N///V+mT5/OjBkzGDBgACeddBL9+/ena9eudOrUifr6eiorK/nhhx/47LPPWLduXWJVsfvuu48+ffpo/WcOFgGzITFJzsKkzqwk3aamPm+soR6raYlCy4LQtq2kHNFLibYZDBJrbEz8HN66FVcvNdpWLEakxeIb4a3bcPbsgWFr1+J0rbUti8i2bYmfI2Xl2DMzsbmc+60N8ePQfHWLVtdguFzYU72KtLcltGMNDVixmLJJUOFt2xNLNVvBIJFAEGfXLmq0S8ugaRC/FYkQKSvH2V1NvcVIRQVWNBbXjsUIb9+Oqx1PgtoiWl2D4YhPZLEsi/C2bcomVsbqd8QmWErjR2KzbcJbt8YvhEhsNhPZXobVMjZLy3H2UBObq9dGCYfixyQYgm+/jzDIp+azbC8He1KY0D5OPvlkvvrqq3aPj90bDMvatwWd58yZw9SpU1m2bBnRaHS3JbscDgfHHHMMv/3tbznrrLOU7fCB5hzvlXtsE7QaWRB8C5MYNuzkOobQz+nb49+tGXvMHtuYwSAb77sbMxzGcDrpNGw43S78xZ7/zrnnj9UyTTb/815ijY0Ydjuegny6/+6qPf7d3rLlwX8TrSgHDFy9e3PEzTco097+xFOEflgPpok9M4Pe//tXZZU3Kqa/TOPX32BFo9jcbvr84+97V2ZnLzZf/c5s6j5ZgBUKYbjdZN/xv9jT1JR5qfv0M6rffjeunZLCEX++SZkxbPx6BRUvzUhod7/6t3jy1dRbDK7fQOljTya0u15ysbJZ5tGqKrbcPyGhnXn2mWScdcae/3AvropmMMimsfdgNcVm2vBj6XrxL/Z7n6GDxuZehtf2x3eKzf9TGJsv7RSbY/cyNveCjhib1l5cx/3LV1Ax7WWsYAjDnULWH6/CU7Dn2Fx64UN7bPPV8jAXXlJJIGjhcRs89GAGl1y05xuIrr237LFNe8l98N/atNf8RaoU6KKqqorf//73nHLKKVx66aX07t0bh+JqH/usdvbZZ3P22WfT0NDAF198wfr166mqqqK+vp5OnTrRpUsX+vXrx/HHH09amvryVR0Rt5FKqpFOvVWNSYwse29l2ja3m5S+fQmUlGCFQnh9ezbKe4ths+HJz6Nh8ZdY0SjeInXaAF5fIbVztwLgUVy+x+srJLgqXtzaU1CgtIycp8hHw+IlALhzc5TWjPT4CqmdMw8A1xE9lXWYAN6iQqr++wYA9rRUnApXZvHk5yWyQADunAHKtFP69sFwOrBCIaxwGE9hgTJtR5cuOLp0IbJtG1YohEfhOW5zu0k5si/B4qbYVKid1LFZ1CI2CyU2QW9sugt2is1cdbF59FFOOqUbBIIW4YjFmae7lWm3Gyt5SoYKO/B4PBx11FE888wzPPPMM7ttty9L3e5Mu68GaWlpSZ15VU2WPZv6aDVeoxNeI12ptrewiEBJCUZKCp7+6i5WAJ6iIhoWfwmGgadQbcfmKSqkdm68g1DeIRf5qHp9phZtT/5AsNshFlOunXJkX2xpqZgNjUrNFcTNm/OII4hs24anyKfUSNjcbty5OQSLS/AU5Cs1EobNhtdXSMPiL0npd6RSIwHgHeSjdts2HF274OypdvlFb5GPYHE8NlWafEjy2PzvTC3angKJzZ2xud2483IIrizBU6g2Nm02g7PPcPPiDD/Dh7no3Hn/h6UIhydjx47lzTffBKBr1667XV12f5CzUxHNWdksW2/li040Z2W9A9VerGCHedNhJFL6xjsIRxf1RqK5gzDcbuVGwpaSgjsvV4uRaDZvoL6zh7h5S0ZtT9NkAT3avsRX5bHZrK3Y5IPEZlu0ik3FmeVkjk1Pk7ZnsPqFLM45O6XpawfIzoJMCktSPvroI4455hg++ugjFixYwPz583f7ai9iaBWRbnTFhZsse7ZybWfnLrh6HoHXp36GYHMHoeMi29xB6DASEO8YPPkDlRuJZm0dRgLi5k1HtjCu7dOSLYSmjliDkYD4kAbs9kTHrJKUvn2wpaVqOcebzZsO7aSOzUE+PAUSm621Ncbm4KbYLFIfm6edkkJKSgcytEJSEgqFuOSSS+ihcLjNzqi/2hymGIbBEY7+ZNq6a9H3FhXhLVA3trCVtq8Qt6YVTjxFRdg0FFCOaxfiLFczm3dnvL5CzGBIi7YnP4/QkKO0GImUvn1IO3aoFiPh6NKFTicer8VI2NxuOh0/XOnYwmYMm43UnxyjxUgAeAcVKc/kJ7STNTZ9GmOzqBAzJLHZEkfXzqSdrCc2U702fjcqldwBB3/ZW5AqB8lKQUEBFRUVWrexz1UODjf2pspBMxErjNPY+3Ehe1PloJmY34/du/flafamykFCu9GPzevRchE3QyEMu13LRdwyTcxQCLtH7drlzcQa/ftWEmgfDt8+a+8Doq1Aex+uirr3u8PE5j7sgmWamMEQdm8Hic0k1d6bKgft1d6bKgfN1NWZpKfv/QNdnVUO8sbt/X7vK6tv/7M27cOdZcuWceutt/Lwww9z1FFHadmGZGgVsi9mdl/ZFzO7z9qaLt6AtgwQxDNvusws6D0uoi3aB1tbe2xqMrOQvMc8WbX3xcxqR1JwScl7771Hfn4+v/71r8nLy6N3795tTgwzDIOHH364XdsQQysIgiAIQlIgQw6SkylTpiS+LykpoaSkpM12+/M0ql2GdsmSJfTp04eeP1IY+ttvv+XFF1/kX//6V7t3ThAEQRAEQUhupk6dqn0b7TK0V155Jenp6Tz44IOcdtppbbbZsmULM2fOFEMrCIIgCIIaJEOblAwfPlz7Nto95MDv93Pddddxyy238Kc//UnlPnUotM6ZkwVPdkWOibC3SMd2YEnm452s1xWNx9ymYaKhIOyJcDjM4sWLWbduHYFAgNTUVHJycjj22GP3eyncdv/13//+d2bPns3DDz/M999/z7hx4/BonKAjCIIgCMJhTjLfWB3mvPHGG4wbN466ujognjBsHjOblZXFP//5T04//fR267fb0Hbu3Jlnn32WBx54gOeff57169fz6KOPkp2tfmEBQRAEQRAEITlZsGAB//d//0dqaioXXHABubm5uN1u/H4/xcXFfPTRR9x444289NJL7S7rtV/5XZvNxu23305RURF///vfueSSS3jooYc44YQT9kdWEARBEARhF6TKQXLy3HPP0bdvX1544QWysnZddGXLli2MGjWKp556ikmTJrVrG0qKy11wwQVMnz4dr9fLH//4R5577jkVsoIgCIIgCEKS8+2333LJJZe0aWYBevfuza9+9SuWLl3a7m0oq5ZcWFjI66+/zrBhw3jggQd46CF9q3l0RCzLotosI2QFtOgH1qwhUlWpRTu4fj3h0jIt2qFNmwlv2apFO7xtO6ENG7VoR8orCK77QYt2tLqGQMlqLdqx+noCxSVYsZh6bX+AQHGJlmVHzXCEQHEJscZG5dqWaRIoLiFaW6tcG5pis1JisyUSm7uiMzZNf4DAymItsRkMWnyxOERtralcWzh8aGxspHv37j/aplevXonxte1B6fIfmZmZPPvss/z2t79l/fr1KqU7PBYWX4bnUGlu06JfOm0KjV9/rUW78pX/Uv/ZQi3a1e/OpmbOXC3adR9+TNXMt7RoNyxeQsWL07Vo+7/9jtInn9GiHfxhPaWPPamlY4uUlVH62JNEq6qVa5uNDZQ+9iThzRqWzLQsSh9/kqAmo1L+/DQal2mKzVeTNDY/ktjcGa2xWVpG2aNPa4nNisoY511UwbKvw8q124Wl8SVoIzMzc4++cOPGjWRmZrZ7G+0aQztv3jy6du3a5nvN42qHDRvGqlWr2r1jgiAIgiAIQvJz7LHHMn36dEaMGEFhYeEu73/zzTe88MILnHzyye3eRrsMbe/evffY5qyzzuKss85qj7wgCIIgCMIuyKSw5OS6667jww8/5Je//CXHHHMMubm5eL1eGhsbKSkp4ZtvvsHj8XD99de3exv7V8VWEARBEARBEH6EgQMH8swzz/CPf/yDpUuX7jL5a9CgQYwdO5acnJx2b0MMrSAIgiAIyYFkaJOWoUOHMmvWLNavX8+aNWvw+/2kpqYycOBA+vTps9/6YmgVELIC2LAnfvab9XhtnZRox/x+DMcO7WhNNY7Mzkq0zVCo1YzbaHUNjs6ZSrStWIxYw44Z69GaWuzpnTBs+z8P0bIsYjU7ZqzHGhowUlKwOZ37rQ0QralJfG8Gg2BZ2BStghetbqEdjmCFw9jTUtVpN1/sYzGidXU40tPVaNfUQPMy0JZFtKYWR2aGGu3aWizTbKFdg2M/Jga0JFZfj+Fy7diWwnM81rhTbCrUlthsG4nN3Wk3iZtqY3PzlijhcEKaDRujHNlXbIPQfiKRCNnZ2fTr1y/xu5qaGsLhMK4W1+r2oLTKweFKzIryWSg+o7ck8hXbzfVK9TfdPw4zFKJ2wadUz5unTNdwONg6/iGiVVX4l39N1Rsz1Wnb7ZQ++TThjZsIrllL+ZRpSjpMAMMwqJj+Mv7vVxLetp1tEx/F2M81oFtSPetdGhYtIVZXz5Z/PQh2ddp1H39C7dz5EIux5d5/YcWiyrQbly+n6vWZAGwd/zCx2vaXP9mZ4Np1lD8/DYDSJ54mvEVdNYJIWTnbJ04GoGL6KwRWqptMagaCbPnXAwBUvzObhkWLlWljwJb77scMBqlfsEBpxYBEbFYmYWzOaIrN7dvZNklxbL79Lg2LlxCrr2fLOIlNgNCaHyh/9gUAyh57hvAmdbG5aXOMkReWAzD6pmo+Xai+QsM+I1UOkpbXXnuNk08+mTVr1rT6/Zw5czjxxBN5/fXX90tfDK0CvLZOuIwUACKEyLKpW/7X7vXi7JYFsRixujq8hT5l2obdjrt/P6xQiFh9PZ7CAmXaAJ6BuZh+P2ZjI578gWq1C/MxGxqwgkHcuTmJ9aCVaPsKidXVYUUiuLJ7Y3OpyS4BeIp8xGprwbKwp6fjyFCTSQHwFhXFtZtwZe958ube4iksIFZfD4Dp9+POy1Om7R7QH6spDRSrrcXjU3eOO7tnJTK0sdpaPEXqtO1eL46sbvHYrK3Dq1A7qWOzoEVs5khsgt7YdPvyidU1xWajH3e+utg8dqiLWCzu9CoqTUac6VamLRxefPzxx9xxxx3YbDbsdnur9/r27UtaWhp/+9vfWLiw/WUKxdAqopstfoFy4yXNyFSq7W3q4A2nE49CIwG06uA9vl1LaSjTVtjZQ7yD2PG9Wm1PYT40Zay8g9Rquwf0TzwiVb3fzu5ZOJpWYfEUFSo1Enavl5T+/QBwD8xTaiQMuz1h2Fx9snFkqHkU20zzcbZnpCs1Ei21DadTqckHic228BS0iE3F2kkbm6leUgb0A8CdrzY2HQ6Ds86Im9ifHOOke5Z9D3+hH8PS9xL08dRTT+Hz+ZgzZw55O10rjzvuOGbPno3P52v3srcghlYZWfZ4R9nN3lvpxQrA64t3EJ7cPGVj0Zpp7iBc2dlKMxIA7v7xDkKHkYh3EN20GImW5k21kTDs9vgxR72RAPAWFTZ91aDdZO51aHs07neztsfnUx+bTfur2uSDxGZbSGy2jWdQ0zk+WL32OWfFDe3IszpIdlaGHCQl3333Hb/61a9IS0tr832Px8Mll1yyX+sXiKFVRIaRhQOX0uEGzbiysnBmZSUytSpp7iB0XGSbM286jATEOwYdRgLi5i2eLVRrJAA8g3zYMzKUGwmId8Q6jATsyLw1G0SVeAoLwGbTYiSazZuOc9zZvTuOrG5atCU2d6+tw+RDEsdmk5FtNrYqOeunbhwOGHm2msl3wuGJzWbD7f7xm6L9nRQm0xUVYTNs9LD3pbOthxZ9r69I6fjZVtpFPty5uVq0PUU+bCkp2rSdFRVatL1FRVghPUs9egoLCP2wXouRcA/oj/foIVqMhLN7FqlDf6LFSNi9XlKPOVqLkTDsdrxHDdZiJCB+rqgc99taO4ljs1xisyU6Y9PRPQvvsGOUD9cBSE+3cenFXop8HcMuyNCA5CQ/P5/333+fX/ziF22+H4vFeP3118ndj+udYVmWnB4/wgjPqL1uG7aCuIy9fyyz9u6f7HXbfS3zYjr2/mON1tVh79RJy0U8Fghg2O3Y9vbOax92wYrFMAMB7Lt5hLG/RGvrtHQQoq1Iex+uXB1qv/dFuyPF5j7Q4WJzHw5fRzpXrH25ju+j9rKLHt7rtmXlsX0aP9u51+a9bruv+O54SJv29/f8WZv24c7MmTO5/fbbOemkk7jooovo27cvKSkp1NbWUlxczGuvvUZJSQl33303l1xySbu20TFuuQ4R9sXM7iuqahYeaG27ohqRbWHY7do6TEBbpybaor3X2hKbbZK0n2eSaneEyWAJJAWXlPziF7+gpKSE5557breVDK666qp2m1kQQysIgiAIgiBo5n/+53/45S9/ydtvv01JSQmNjY2kpaWRk5PDueeeS0HB/pUnFEMrCIIgCEJyIBnapCYnJ4dbbrlFi7ZUORAEQRAEQRAOGMFgkEceeYStW7cq05QM7R5QuWzjLtqxPbdpN/LJ7orc2beN+vlGO5BjfmDR+VkKB5x9mRS2r5hJOh88Waoc1NfXM3nyZN5++22qq6vp1asXp556KjfccAOdO3cGYNGiRVx11VW71fjuu+9wNHmQWCzGk08+yRtvvMHWrVvp2rUr5513Hrfccssu5bBmzJjBCy+8wPr160lPT+fMM89kzJgxie0288EHH/DEE0+wevVq3G43J554IrfddhvZ2erLj+5MIBDg0Ucf5bjjjqNXr15KNMX2CIIgCIKQHCSBoY1EIlxzzTWsXbuWm2++mcLCQr799lsmTpzI4sWLeeONN1ot/zp27FiKWqyw14yjRULtnnvu4ZVXXuHGG29k+PDhrF69mgceeID169fz2GOPJdo9/fTTPPjgg/z+97/nH//4B9u2beP+++/nu+++45VXXklovvvuu/z5z3/mwgsv5K9//St1dXVMmDCBUaNGMWvWLDp16qTxCMVRXWRLDK0gCIIgCIIi5s+fz/Llyxk3bhwXXXQRAMceeyyRSIQJEyawePFiTjjhhET7/v37M3jw4N3qbdq0ienTp3P11Vdz3XXXATB06FBM02Ts2LF8+eWXDBs2jMbGRh599FFGjhzJ7bffnvj79PR0rr32Wt555x0uvPBCLMti/PjxDBkyhPvvvz9RFrBfv3787Gc/Y9q0aVx//fU6Do1WZAytIAiCIAjJQRIsfZubm8u9997L2Wef3er3zbP4t23btk968+bNw7IsLrjggla/P//88zEMg7lz5wKwcOFC/H7/Lu1OPfVUMjMzE+1WrlzJli1bOO+881rVuM7NzaWgoCDRLtkQQysIgiAIgqCInJwcLrnkEtJ2qsW8bt06APr27btPesXFxRiGQU5OTqvfZ2Rk0L17d1auXJloB5C306qIhmEwYMCAXdoNHDhwl23l5uZSUlJCLKZ2ks/GjRtb/ZySksJFF11Et27dlG1DDK1C/GY9EUvPkozh0u3EGhu1aEfKy4nW1unRrqoiWl2tRTtaU0OkolKLdqy+nkhZmR7txkbC27Zr0TaDQcLbtmGZpnrtcJjwtm2YkYhybSsajWuHQuq1LYvwtm3E/H7l2gDh0lJiDQ1atCPlFfpiszKJY7M0iWNTsVEAsCIRwlu2Y4bV9z/hsMUP66MEAh1j8Kph6XvppLS0lMcff5yCggKGDh3a6r3Zs2fzy1/+kmOOOYbhw4dzyy23sGHDhsT7lZWVpKWl4WpjVb/OnTtTVVWVaNf8u7baNb+/p3aRSIS6OrXXnREjRvC73/2Od999l0gkgtfr5V//+hf9+/dXtg0xtAr5wj+LLZHVWrQ3Tfw3Dd8s16Jd9twUaud/qEW78tX/UvXmLC3aNe++T8WL07Vo132ygNInntai3bhsOVv//bAW7UDJarY+MAEzGFSuHd66ja33TyCqwajE6uvZ+sAEQus37LnxvmKabH1gAoHvvlevDWyfNJn6LxZr0S57fgq18+Zr0a589b9UzUzS2HxSU2x+tZytEx7Woh0oWc3W+ydgBtXftEXLq9h+97+JbN63R9l7w/oNUY49uYxvvtWTrEkmIpEIa9eu/dFXWRuJkMrKSkaPHk04HObBBx/cZSnrVatWce211/LMM89w/fXXs3DhQq688krq6+sBCIVCbZpZAKfTSbDpeh9qSgi01dbpdCbe31O7lm1UcfTRR/PFF19w6623csoppzBu3DjWrl2rdBsyKUwhFhaGpro5hmFAkpZZEQRBEPRhWU1PZAz1/Y9hM5q2oVy6fRzE/SgtLeW888770TYXXXQR48aNS/y8ceNGrrnmGqqrq3n66adbPeY/5phjWLBgAV27dsVmi+cXf/KTn9C/f/+Ewf1//+//4Xa7iezmyVg4HE6U7Wr+GolEdinltbt2bem1bKOKGTNmsGXLFmbNmsU777zD888/z5QpUzj66KP59a9/zciRI/d7m2JoFaLT0GLYtDxGFgRBEJKcZrdpU9//NEtK9wPZ2dmJ8ad7w6pVq7j66qtxu91Mnz6d3NzcVu+7XC6ysrJ2+btTTjkFt9vNihUrAOjWrRv19fWEw+FdsqqVlZWJyWbN41Grqqp2KbtVWVmZ2FbLdjtTWVmJ2+3WUrard+/ejB49mtGjR1NcXMysWbN49913uf3227n33nu54IILuPTSSyksLGyXvgw5UIiFiWFoOqQ2ydAKgiAIbdDkNnd+lK0Co4MZ2mQZQ7tlyxauueYaunbt2qaZbSbcxrjnaDRKJBIhJSUFgMLCQizLYvXq1kMaKyoqqKioSNSwbTaCO5vuWCzGmjVrGDRo0I+2a/5dYWFhqzq5OsjPz+e2225j/vz5TJkyhdzcXKZPn87FF1/MqFGj+Pjjj/dZUwytQpJ3yIEsLyQIgnBA0HC5TRSot6nv0pslO0w+JQnKdsViMW6++WZcLhfPPfccPXr0aLPd//3f/zF8+PBdMqXz5s0jFosxfPhwAM4++2wcDgdvvvlmq3bNP5977rkAnHjiiWRkZOzSbs6cOTQ2NibaDRw4kJycHGbNmtVqcYMVK1awdu1aRo4cuR///d5TWlrK008/zbhx41i2bBmWZTFkyBDWrl3L6NGj+Z//+Z/dDrVoCxlyoICwFcRBfCC1gUHECuM02h7Ava+Y4RCGwwmGgWWZxPx+7F6vIu1IYnwUgBkIYPN4lGhbsRhWNLpDOxjEcLkwFFxwLcvCajHpqfn/ULVMsRkI7NhW0/9ha7pTVqptmljhMDZFY5VaamOp/TxbaaNBu8VFVal2MNjqvFCqHQphNE2gUK4tsdkmEpttaDf6/397dx4fVXX/f/x1Z59JQhJIwhYQCZBVUVBUVFwQRJSvQmu/WvGrBX4IrVvRuvRrS7HIV6p1QREXKFpc0YK4ICqIIoIsrojsi2whZE/IMuv9/TGZISEJBD0HGPg8H488TGZO3rle7pn7mTPnnguhuv5jGIRqa5Vtd2lpKDpCa5pQVBwkpY3ekbsTwdy5c/nhhx8YN24c+fn5jdadTU5OJj09nRtuuIH58+fzu9/9jltuuYXU1FS+++47pk2bRkZGBtdeey0Abdu2ZcSIEcyYMYPk5GT69OnD2rVrmTJlCsOGDYuOuDqdTsaNG8f48eOZNGkSAwcOZMeOHUyePJlzzz2X/v37R7fh3nvvZcyYMfzpT3/iN7/5DcXFxTz66KNkZGRw/fXXa9s3oVCITz75hLfeeoulS5cSCARo1aoVN954I9dddx0ZGRnU1NQwZcoUZs6cSevWrRvcJOJQDFP1vcdOMJcn3HzYNvtDZXxb8wnVZiVxRiJtbafQzXnmYX9vywOnH7ZNoLKCPdOfI1BchC0pGVfXDNKGXXvY3ws6D//PGvL7yf/n4wQrKrHEeXC0b0/aiJsP+3stYZom+Y8/SbC8AiwGttataX/bHw7/iy0cvdg77XkChYWEfD6srVrR4e4/Hv6E3MIjvXDWK3h37iRYUYktMZH2f7xd2QmieO48ajdswL+vEHvbNNJGjcDepo2S7LKFi6j6+hv8+Xuxd+hAm18Pw3Vql8P/Ygv2eeWXK6lY8jn+PfnYO7QnaeBlxJ3R8/C/2IJ9Xr1uPaXvzce/Zw/29u1JOO8cWl14weF/sQV8e/ZQ+Mrr4ex2bfGcdhrJg9WMPgQrK9n79DT8JSXYWifj6tqVlP8+fN9siWjfrKzE4vbg6NDCvtmCf0vTNMl/7KC+eXsL+mYL/ay+2UKFs17Bu6Ne3xynsG/OOahv/j+VffMTqr76+kDfvLZlfTPkOvzn/PuXraZy4RL8e/Zi79SBxEGX4ul9+HPL11c9cdg2ny6p5c/jK9i4KUDXU62MGRXPiJviDvt7bTruPmybn+u0cY9ry17z2B+V5Nx3333MnTu32efrXzj2448/MmXKFL766iuqq6tJS0ujf//+3HrrrSQlJUV/xzRNZsyYwezZs9mzZw9paWlcc801jB07NroyQcScOXOYOXMm27ZtIykpiUGDBnHnnXc2Whd38eLFTJ06lQ0bNuDxeLj44ou5++67m5zX+0v99NNPvPXWW8ydO5fi4mJM0+T000/nuuuu48orr4xOr6jvnnvu4fPPP2f58uUt+hsyQqtAnJFIiPALT5VZTqqtk7JsW0IrLE4nZiCAv6iQ1gOvUJZtsduxp6XhL9hHqKaGVhdeqCzbMAycnTtT+cUyAOIPWnfvl3JldKVsw0YA3NnZyk6YAK4e3an6+hsArElJyk6YAO6sTCqXfB79WdUJE8CTk03Z+x8AECwvx3nKkS3efcjs3GyK33gTAH/BPtxZmcqyXd0yCBQVhbPz83Hn5ijLtrdvT6gmvP6sf28B7t+oKTgBrAkJGG4XBAIE9hXivkLdx3QN+mZ1Da36Ke6bp3SmcmmM9s2v6vpmsuK+ma2zb2ZR9t58QH3fdOdmUvLv2QD48wtw5TZeLP/n6nuuk/y94XVzt24LMqC/mtHwE93DDz/cYKWDQ8nJyeHZZ589bDvDMBg1ahSjRo06bNthw4YxbNiww7a75JJLuOSSS1q0nb/U5ZdfjmEYuN1urr32Wq6//vrDXvx14YUX8u67LV9aUObQKmAYBinWjgC4jDhaWdS9EALE5YQncmOx4G7izh6/RP3iwZ37864sbFm2uiIFwJOX0+T3SrJzsqNXQngUb7erWwZG3VWqnrqJ/KrY27fHmpwEgDtHbSFhTUjA0Tn8Rs3VLUNpIWGx23Fnho9re/t22Fu3VpZtGEb039ASF6e0kIB6x4fVqrTIh4P6j+JjXGe29M3GtPbNxAQcnevOP1ndlfZNh8Og/yXhIjYr00an9GM/BmZo/BL6ZGZm8te//pXPP/+cBx98sEUrGZx55pk8+uijLf4bUtAqkmILv6Ck2Topv9I0Ljdc0LpOORWrS828q4jICcLerq3SEQk4cILQUUhETxBWa7QYUsWakICz7taEqov8+sWb6iK/fvGm+mRfP1NHtlvrdoeLE9WFRDg7vL2uDLVFPtTrm4qLfJC+2RSL3Y47q65vKi7EG/RNxdkArrzwsk2enuqzrxgYPq4HXKr2+BYnl3nz5nH99dcTF3f4KSsR6enpXHnllS1uLwWtIq2t7TGwkGZVe3IAcKSmYU9NxVO31pxKkROE6hEJOFC8ubOzlBcSkROE6tHCCHdutpYiP5ydo6WQAHDn5GgpJODAiVh1IQEHijd3jvoTsjOjK4bDEf4bitnbt8ealKSlEI+Mins07JNI8ebOkb7ZIDtHY9/M1dc33XlZ4f5zuvrX8csucWGzcfxMN4iBVQ7EsXHsPz84QdgMO2nWTiRZm16e45eKy8nDk6n+hAzhF1pXRldt2aquQm4q215YpCXbk5uD6dVzq0dPTjberduUFxIQHnnz5OZoKSTs7dvjzsnWUkhYExJw52RrKSQsdjue3BzlUwLgQPGmekQvIlwYNr1+5S8Vs30zT2PfzI3Nvuno0gn3aVlYE9Uvhp+YaGHw5S76nKVm5R4hdJFVDg6jJascRNSE9uO2xB++YZ2WrHIQ4S8uwta6TYunM7RklYNodkkJtqQkLS/iwcpKDLu95S/iRzBbI+T3E6qqwlbvStBDOoIj3TRNAsXF2OvuqKKav6jo+Mk+gn1+xNlHsM+Pq31yvGQXF2NLTm553zyCf8sj7ptH4Ij75hE4mfpmS1Y5iGYXFmNPbfmbzZaschCxY2eAzp1aPv6lc5WDnnfqW+XguyfUrHIgjg0ZoVXoSIrZI2Vvo+cFFlA+P68+q4bb50VY7HYsGk6YEB5503VSAyRbsluWrWE0PEL6ZtNiNvsIitkjdSTFrHYyBCeaIXNohRBCCCFETDuO3nYJIYQQQhyCjNCKZsgIrRBCCCGEiGkyQnsYL299Slv28G53aMve/Jc8bdkhm7xFPqHIP2djssr60aX7GNT472lqfD1ccZW+C6BCjg3asnUy5PVKNENGaIUQQgghREyTEVohhBBCxAYZoRXNkBFaIYQQQggR02SEVgghhBAxQebQiubICG2MCJoBQmbL7xpzJEI1NYR8Xj3ZtbWEamv1ZHu9+rJ9PoI1NXqy/X6CVdVass1AgGBVNWZI/bFiBoPh7GBQfXYopC/bNMPZgYDybIBgdTUhn19LdqimhpBX+maDbOmbjYRCJtU1JqHQSVDtmRq/REyTgjZGfFL5Crv9G7Vk7576NCULFmjJ3vfSLIpen60lu+Q/b1Pw3HQt2eUfLyL/UT1XGO9fsZKdf3tQS3b1j+vY+cBftRQT3p272PnAX/HvK1SeHSwvZ+cDf6V28xbl2YRC7Hzgr1R98636bGD3Q5OpWPK5luz8p56h9P0PtGTve3EWRa9J36xv/5cr2TleT9+sWbueXfeOJ1StvhjftDlARve9fP2NnjdWQsQCmXIQIwwMTPSM0AohhIhdoboPNiwnwXJzMuVANEdGaGOIKR1ZCCHEQSIzDSxyRhcnMRmhjREGBtom+RhItSyEEFrVvcYa6odRI9NyLdaTYIhWTlWiGfJ+LkaEpxxITxZCCNFQMBg+N8gIrTiZyeF/nAuZQUzThLqCNmiqu1LbDIazjbr7Qqq8CtwMhRpczWsGg8qu7jVNs8G2mqGQ0qvjG2Qf9LdUZjf1s2THVrZZ75MNpdnBoL5s6ZuHzW7qZ2XZhtrs6hqTyAI4Vgt4vSf4wIesciCaIQXtcc5n1rKy+n1CBNnr38qG2pXKss1ggD1TnyZQWUntls3se/01ZdkAe595lsC+ffj27KFg+r+UfdRmGAb7XpyFd8cOAiWl7H16mpLciOI336Jm3XpCNTXsnTKVkNenLLv0/flUrf4aQiH2PvMc/uISZdnln34Wvdq+8N8vU7t9u7Ls/au/omx++Gr7krfnUb3mB2XZNes3UPTGmwCUL1xE5bIvlWVHjz2gcvmXlH28UFl2sHI/e5+ehunzUf39GkrmzlOWbQYC7J0ylWBFBbWbt1D0yuvKsgH2Tq3XN1+QvglQ+p6+vlmxaAkVn4T7ZtG/XsG79Sdl2W+/XcNf/1YBwP/+pYIFH+pZLk2I450UtMc5lyUO0zQJEaQyVEKyrZ2ybIvDicXtJlS1H19+Ps70dGXZhsWCPSWFQEkpgcIiHG3bYiicO+bo0B7/3gKC5eXYEhMxrFZ12Z0749u9m1BNDVgtWOM8yrJdXbvi/eknCIUIlJZiT0tVlu3u0R3vlq0AeH/agevUU9VlZ2ZSu2kzALWbNuPq0UNZtqt7N2rrtrt28xbcWeqyHenp+HfvAcC7bTuubt2UZduSkzBrazH9fnw7duJUuL8tTicWt4vQ/ir8e/JxdFLcN1Olbx7MlVGvb5ao7ZuuzG54t2wDwn3TmdFFWfYlFztZ/VV4ua5Vq31cfJFTWfbxyDD1fYnYJgVtDEizd677zqCNtYPS7LicnOj3nnrfq+DJPZDnzs3WmK14uxvsE7Xb7erRHWzhazE9uTlqC4n0dKwJCQC4s7OUFhK25CQcHcPHnvPULkoLCYvTibt7uNC0paRgS1VXSBgWC+66f0PD5cLVVV3RCfWOPYsFd3aW2uwcjce49M1GtPbNzulYEuIBcOeo7Zvt21vJzQlvd9++DhIT5bQuTk5y5MeAVFu4oE2ypuKwuJRme7LDJwhbmzbYU9OUZkdOEOFCoqvSbEendKytErQUEvWLN3durtLs+sWb6pN9/eLNozgbDmyv7myVhUQkE9QX+fWzVRf59bNtKSlKRwvhoL6ZIX0TDuqbeRr6Zl5d31ScDXDppeFR2UED1Z4fjksyh1Y0QwraGBBvScJtJJBiU/exY4QtKQlHx454cnKVFxKRE4SOQiJSvOkoJCBcYOkoJCLZOkYLoa4IslhwZ6ktJODA6JjqQqJhtvqTfaR401GIR4o3j+JRTjhQvOko8qVvNp+trW/mhfumKzdTeXb/S8OF7MCToKA1TFPbl4htsg5tDDAMgzR7Zy0FLYRHad2KR1Aj3Lk5WFx6XmQ9uTn4C4u0ZZten/JCAsLFm3fLVuWFBISLN1f3bloKCUendJxdT9VSSNiSk3B1y9BSSFicTtyZPbQU+ZHiTUeRD+H+4+qubt7vwdnSNxtna+ubWd1xZXbD6lHfN3v3stOvn4OOHdRvtxCxImYL2srKSp555hnee+89SktL6dChA/369eMPf/gDycnJ0XbBYJDnn3+euXPnsmfPHtq0acPgwYO54447cGl6Mdeho70HcZZELdnxZ5yJvU0bLdme3BwMu11LtqtHd+zt1V0kV58jPR3Dpme7bclJJF52qZZsi9NJ6/+6Sku2YbHQ5ldDtRQSAK2HXq2lkABIHjxIS5EP0KrfBVqKfIC4XmdgVzinuD5PnvTNg9mSk0gcoK9vJl9zpZZsm83gwb+10pJ93JGBVNGMmCxo/X4/o0aNYsuWLdx+++1kZ2fzww8/MGXKFFauXMncuXOx1p0YJ06cyOzZs7n11lvp06cPmzZt4h//+Afbt29n2jS1S8roFG9N0pbtaNtWW7YtKUlbtsXpxOLUc0WvYbHg6NBeSzaAo4Pai/sk+wTNbqenKATpm83R+u/ZUV92Zg89Rb4QsSImC9pPPvmEb7/9locffpihQ4cCcPbZZ+P3+/nnP//JypUrOe+889i5cyevvfYaI0aMYOzYsQD07t2bUCjEhAkTWL16NWedddax/F8RQgghRAvJ8lqiOTF5UVi3bt146KGHGDBgQIPHs+rmyOXn5wOwaNEiTNNkyJAhDdpdeeWVGIbBwoXqFlkXQgghhBDHRkyO0GZkZJCRkdHo8a1bw4uzd+4cXuZqw4YNGIbRqG1iYiJpaWmsW7dO/8YKIYQQQg0ZoRXNiMmCtikFBQU8++yzZGVl0bt3bwCKi4uJj4/H4XA0ap+cnExJibpbG/4cpk/dbRsPZqi7VXhjsXrU6LmW6eiQF/HGYvnfUxc5To4606Zvp3sMfasWeLUlC3FsHFelid/vZ8eOHYdsk5CQQFpawxsAFBcXM2bMGHw+H4888kj0Kmyv19tkMQtgt9spLy9Xs+FCCCGE0E7m0IrmHFcFbUFBAYMHDz5km6FDh/Lwww9Hf96xYwejRo2itLSU6dOn06PePeZdLhd+v7/JHJ/PF1PLdgkhhBAnPSloRTOOq4I2PT2dDRs2tLj9+vXrGTFiBC6Xi9dee41u3RouQJ6SkkJlZSU+n6/RSG1xcXH0IjIhhBBCCBG7YnKVA4Ddu3czatQo2rRp02QxC5CdnY1pmmzatKnB40VFRRQVFZGr6e4+QgghhFDPMPV9idgWkwVtMBjk9ttvx+FwMHPmTNo2c2OAAQMGYLPZmDdvXoPHIz9fccUV2rdVCCGEECePFStWkJmZ2exXIHDgqu1gMMi0adMYOHAgeXl5XHTRRUyePJna2tpGua+//jpXXXUVeXl59O3bl7/85S+UlpY2avfRRx/xq1/9itNPP50+ffpw5513smvXrkbtVq5cyfDhwznjjDPo1asXo0ePZv369Wp3xlEUkwXt3Llz+eGHH/jv//5v8vPzWbNmTYOvyD9c27ZtGTFiBC+//DLTpk3jq6++4t///jdTpkxh2LBhZGdnH+P/k5b70jufLYE1WrJ3PPp/lCz8UEt2wQszKJz1ipbsojfeJP+pZ7Rkl85fwK5Jk7VkVyxdxk/3/q+W7Oo1P7D97nsJVlcrz/b+9BPb774X3969yrMDpaVsv/teajZsVJ5tBoNsv+te9q/+Snk2wM7xD1L+yWIt2Xv++QQlc9/Rkl3wwgwK//2yluyiN94k/2lNffODBez6P0198wt9fbN2/SZ23Ho/gZLGBcgv9dnSWjpn72ZPflB59nHH1Pil2IQJE3jrrbcafdlsB2Z7Tpw4kaeffpqhQ4fy0ksvMXbsWN544w3++Mc/NsiaPn0648eP54ILLuDFF1/k/vvvZ/HixYwcObJBgTx//nxuu+02MjIymD59OpMmTWLDhg0MHz6cysrKaLuvvvqKESNG4Ha7mTp1Kk888QQVFRUMHz68yeI3FhxXc2hbavXq1QA89thjPPbYY42er3/h2Lhx40hMTGT27NlMnTqVtLQ0Ro4cGb1zWKzw48M09bxYmaEQZlBTdjCIGQppySYYAl3Zpgma9gmmqW9/a9xu0yScreujOV37O5Id0rPhZiCIqSs7GMQ09RzjZiikr2+GQuH+qSXbhICmYyWksW8GQ+HtNtSvNxcMQXmFSVDTcSh+nlNPPZXTTjut2edbejfTqqoqpk6dyqBBg7jvvvuiv9+qVStGjx7N+++/z9VXX41pmjz66KP07NmTyZMnR1d86tKlC1dddRWzZs3i97//PQBPPPEEKSkpTJ06NXqNUV5eHpdeeinTpk3joYce0rVbtInJEdqHH36YDRs2NPtVfxUEwzAYNWoUH330ET/88AOffPIJt99+O3Z7jN332jQxdP1zGUZdtSKEEEKLyGushoLWWndq0Pme8HhxIs2hbendTJctW0Z1dXWjdv369SMpKSnabt26dezevZvBgwdHi1kI3101Kysr2q6srIxVq1YxYMCABhfMt27dmvPPPz9m76IakwXtycjE1LaQvGEYoGkUCJBiWQgh6kbDDUP9addiafAnRIxo6d1MI6s/de/evUE7wzDo2rVro3b1ly+N6NatGxs3biQYDLJx40ZM02y2XVlZGfn5+b/8f/Aok4I2RpiYGLoqWosl/FG1EEIILaKvsRYNI7TWcGYoeBK8jpumvi/FPvjgA371q19x5pln0qdPH+644w5++umn6PMtvZtpcXFx9LGm2kWeP1w7v99PRUXFYdvVz4olMTmH9mRimqHoO3oDA9M0G3yU8Muy67IMIzx3LBTCsKh5j3NwgRz5WcW2N1V8q94vki3ZLcmunxVL2U39LH1TY3Yo1GDKgcrsUMg8MEJrQjBoRgvcE9GxXF6rpXczjVi/fj2jR48mNTWV77//nqlTp/LNN9/w/vvvk5CQ0OK7mXq94RsVN9XWbrdHnz9cu0ibSLumpl5GHmtqlYXjnYzQHudqqeZr32KCBCgO5rMx8LWy7JC3lr0vv0iotobaHT9ROGe2smxCIQpnvkSgtBT/vkIKX5qlLNowDIpefhVffj7B8nIKps/ErHeV5y9V8tYcardsJVRby75/vUho/35l2WXvf0D12h/D++fl1/ArXDGg4tPP2L8qfMFkydx51G7erCx7/8pVVHy2BIDyhYuo/vY7Zdk1a3+k9P0PAKhctpzKL5Ypy/b+tIPiN94EoOrb7yj/eJGy7EBxCftenIXp91O7cROl895Vlm3W1lIwfSahqip8O3ZS/PqbyrKjfbOkRF/f3JNPsKKcghmK++Z/5lC7dSshb2z1zcqPl1C1LNw3y/7zPt6NW5RlvzK7mqeeC1+9/rdJ5cx9r0ZZtmgocjfTQ3099thjnHnmmSxdupRXX32Vyy+/nF69enHzzTfz6KOPUlBQwIwZM4CW38008t+m2h5Ju0ibQ7WLPOZ2u1u+Y44TUtAe59xGPLVmFUEClJr7SLA0/ojg57K63IS8tQQrKvDu/Albcmtl2YbViuFwENhXiD8/H2t8nLIRCQBrYiK+nbsIlJRiGAYWhRf52VJT8W7dRqiqmkBZOdZ677h/KUeHDtSu3wChELWbt2Bv105ZtrNzZ2p+WAtA9fdrcHbpoizb1bVrtIit+vobnBld1WVndKXqm2+B8Ha7Tj1VWbazUzrVP/wIQM2P63Ckd1SWbU9pg39PPqbPR+3GTdjbNb0e9s9hcbsxvV6C5RV4t/+ErU2M9c1dR6FvlsdO33R07UzN9+HjsPrr73F2PUVZdr/znbz3QXg07f0Pa7nofKey7OPSMVy2K3I308NdlO5wOEhNTcVy0CeeF154IS6XizVrwktw1r+b6cGKi4tJS0uLtgOiUxAObpeamtqidi6Xi4SEhGi7ptawLSoqAohmxhIpaGNAiqUDEJ5ykGJRd0IGiMvOO/B9ltp1eT25OdHv3Tk5h2j5C7NzFWfn5dT7Xu3d5FxZmdErODy52UoLCWeXU7B4PAC4M3soLSTsqSnY615cHZ07YWvVSlm2xe3GVVcgW5OSsHdoryzbsFpx54RvcW047Li6N76j4C/hzqt/jKvtP/WPa4/qY1xn/zlK2R7Fd3rU2je7noLhrhtFy83EUNg3T+lk47SccF6vM+ykpliVZYufr6kiNRAI4Pf7cTrDbzpaejfTyJr5kYu+IoLBIJs3byYvL++Q7SKPZWdnY7VayczMxGq1NtsuNTU1WkzHEiloY0CkoE2ypOEw1L779uSEO4w1PgFHe7XFsrvuBKGjkAgXb+GPRCIFiyr2lAPFm+oixepx48oIj0CqPtkbVivu7PC+UL3dcGB7VRdXcOANj+pCAsBTl+3qobbIh/D2gvoiP5wd3m7VRT4c1DebuG34L9Ggb2Zr7Ju5sdY3w1eUe3qqv+X6lYPCxfLAS13Ks483Rkjflyp//vOf6dOnT6OR0kWLFhEMBunTpw/Q8ruZ9u3bl8TExEbtPv74Y6qqqqLtevToQUZGBu+++26DOeFr1qxhy5YtDBo0CAjP8+3bty8LFixoMFe2oKCA5cuXx+xdVKWgjQFJllSs2EizpCvPticl4+iQjiczS9kFYRGRkTcdhUT4BJGtpZCA8MibNSkJR8cO6rNzczEcDuVFPhwognQUtNFsDQWtzmx3drh4qz/yroqzSxcsHrfykXw4MCquo8iP6b6ZW9c3O2jomzk52vqmKy8LLJbwfxW78vLwG4iBl8bevMcT0Q033ADA7373O+bPn8+qVauYPn06DzzwABkZGVx77bVAy+9m6nQ6GTduHAsXLmTSpEmsXr2aOXPmMH78eM4991z69+8f/dv33nsv69at409/+hMrV67kgw8+4M477yQjI4Prr78+2u6uu+6isrKSP/zhDyxbtozFixczZswYEhMTueWWW47i3lJHVjmIARbDShtLe1I1FLQAcTm5ONLUzf+rz52bg8WpZ06XJzcHf918Hx3ZptervJCIZHu3bFVeSEB45M15ahcthYSzyyk4OnbQUkjYU1NwdEpXPloIdcVbtwwtRX6keNMxag3hN1aubhmHb/hzsnX3zUKNfdOnqW/m5eDduk1P38zLxNmjK9Y4j/Ls03Lt9DrDzpk9Y+yGQT9HDKxMlpuby6uvvsqUKVMYP3481dXVpKWlMXToUG699Vbi4uKibVt6N9PrrrsOh8PBzJkzefXVV0lKSmLIkCHceeedDfrCRRddxDPPPMPUqVMZOXIkHo+Hiy++mLvvvjs61QHC0xNefPFFHnvsMX7/+99jtVo577zzePzxx6NzbGONYcoCpIdUWFh5+EY/0w2dW3773fJQEYmWlh9kW8f3anFbX8FerK0Ssbbwqsagq+WHjL+oGMNux5bYwgLrCM5RoZoaAmXlONqru3gjwgwG8e3chbOLuos36qvdug1X1yO4+OkIemnttu24Tu1yxNvUouwj3e4jyT7S7T6CY0XrPtm2HWeXU7QUWN6du7C3a9vyAusIjhN/URGGw6HlzY/2vrlrF85TjqBvHsmxcoTHeMjV8s+qvZu34+zWpcXt1wyZ0uK2X33jo/eZTS8B1eS22H9scdsjlZqq7mK9g/X9zT+1ZS+bfZe2bKGfjNDGiCMpZo+Uo636k06EPaWNtmyL241D09IihtWqrZgFtBWFgLbCDWJ4u2M029lJz6cyEJ6Pqov2vnkkxewR0nmMH0kxe6SOpJiNZcdyHVpxfJOCVgghhBCxQT5UFs2Qi8KEEEIIIURMkxFaIYQQQsQEmXIgmiMjtEIIIYQQIqbJCO0x9MqOadqyf9t2hLbsrQ+fpy075ND49lv9RehHTyxvuxDHmGnV97oy74qWr0RwpHSuRBCzZIRWNENGaIUQQgghREyTEVohhBBCxASZQyuaIyO0QgghhBAipskIrRBCCCFig6xDK5ohI7SCb8yl/GRu1JK97/VXKJo3V0t2yTvvsu/Ff2vJLv/kU/KnTNWSvX/lanY9NFlLds26Dex68CFCNTXKs727drPrwYfw7ytUnh0oK2fXgw9Ru2Wr8mwzGGTXgw9R9d0a5dkAex59nIqly7RkFzz7AmULPtKSXfjKaxS/NUdLdsk777Fv5ktasssXf0r+U5r65qqv2P2gnr75w7c+hl66lz27AlryTxaGqe9LxDYZoRXUsB8f6u/nDhCsrMQMtvxe50ciVFVFsKJCT3ZNDcHycj3ZXi+B0lI92X4fgZJSTA2jGGYgEM4OBpVnY4bC2QE9J/tASSmm16snu7SMUG2tnuyKCmzV1Vqyg/v3Y/r9WrLDfbNST3Z1DcEyPX3TrPUSKNHTN6urQmzfEiCk5+VQiJOeFLQCWRNKCCHQuiRUpJC1WvX9jZOCjKSKZsiUAwGAqfVVQl6BhBAxQtP7+0Ag/DpotcoAghA6yAitwNA5QmvIi7cQIlboe/MdGaG1yDDSLyJzXUVzpGsJIDxCq2PeZV24EELECPVvwk3TJDL13CJTDoTQQgrak5jf9LHWXEUAP5WUsYFvlWWbwSCF/3mT4P5KAmWlFP7nTUxFV0OYpknxf+biLyomWFVF0RtvEvKpu7il9N35+HbvJuT1UfzWHAIKLzwr+3hR+Er+UIiSd9/Hl5+vLLvi8y+o+SF8q8zyhZ9Qu3mLsuz9q7+mavVXAFQu/1LpigHVP66jYslSAKq+/Y7KL1cqy/b+tIOyDz4EoGbjRsoXf6Ys219UTMnceZiBAL6fdlBa93dUCFbXhI/rmlr8ewsoefsdZdlmMEjRG28SrKggUFpK0ey3NPTNIj198726vulT3zfLP1xE7eZtEApROm8+vj17lWW/+q/9fPxe+OK+mc9UsvpLPRconhRCpr4vEdOkoD2J2Q0HNVThpYYyirDjUJZtWK2Eaqrx5efj3bkDMxTEUPRZm2EYYBh4t24jsK+QYFkZFoddSTaA4XZR8+N6Qvv3U7t1G7ZW6laAsCW2ovrb7yAUYv+KVdjbtlWWbU9LZf/KVQBUfPY5jk7pyrIdHdtTWbc0VeWSpTg7dVSW7ezciYpPlwCwf/kKHO3U7RNHxw5UfP4FAFWrv8bWprWybFub1lSv+QHT66V6zQ9Y4+OVZVs9bvx7CwiWllK7cROGXeHxbbUSqq7Gvycf346dENTUNws19E2Xi5p1dX1zm9q+aU1KpPqben2zXZqy7IxMOx/MCy+l99bLVeT2VLdPhBBhUtCe5FLpEP0+hfZKsz3ZudHv47Jz1GbnHshz5+rL9ijOdudkR+cVe3KylRUSAK6MrhhOZ/jvdO+Gpe57Fezt2mFrnRz+vkN7bK3VFYbW+HicXU4BwJKQgKNzJ2XZhs2GOyuz7g9ZcWf2UJdtGLhzDxzjntxsZdnQ8LhWfRwerf4TW30zK9o33blq+2avs524PeHsc/s5cbvl1PuzmRq/REyTXnWSixS0Dpy0Illptier7gRhteLurq6QgIbFmydHbSFhb9c2OpKn+qRZv3hz56nNrl+8Kc+uV7yp3idwoPBRXeTDge1VXeQDeOr2s+oiHw5styU+XmmRD/XeWCku8uGgvqn4WLG3axt9Y6W8bybE4zglvJ89p6nNdjgNzu4b3ieXXO5Wmn2ykRsriOZIQXuS8xjxxNGKNrQLf1yokDUuHleXU3F3zcDidCnNjhRvOgoJwzBw5+RoKSSgrpjQUEjAgVFC1UU+HCjeVI+6wYHtdise5YQDI286tjtSvOko8iPFm44i3xofj/OUU3BpKPINmw13Zo9w30xW+yY58sbKkpCAo5P6vunJywGbDZeGvnn+xS4sFujXX+1roRAiTJbtEqTSngTFo7MRnuwcDJuew8yTm6PlNqwQPrGZXq/yQiKS7d2yVXkhAeFi2ZHeUXmRD+HizZaSglNDkW9v1w57WpqWIj8yKq56SgBE3lj10FLQRoo3V/cM5dkQfmNicak/BqGubxYV6cnOycb0+bT0TXdeNt6t27E41V1PEHHBxS4+7uMkKVmWOfhFdK3GI2KeFLSCNDriIUFLticnV8uJB8CdnY29rboLN+pzZXTVtoauvV07EvpdoCXbGh9P0uBBWrINm43Ww67W8u9pGAbJ1wzRUuQDJA7or6XIB0g491wtI/kAcWecjiNd3QV49Xlyc7QUbhB+Y2UvKdGS7eqWoW0xV3uH9iT0O19LdodONkbepud1VgghBa0AWhl6TvQAjlQ9BSeANT4Oa3yclmzDZsPdo7uebMPQMiUgQrKPbrY7O1Nbtiujq7ZsR/t22rKt8fFKV32oT3ffdOdmackGOPcCmW7wS8lcV9EcmUMrhBBCCCFimozQCiGEECI2yAitaIaM0AohhBBCiJgmI7RCCCGEiAmGrHIgmiEF7QnK4tJ38YGjXM/V/wDeFH0vVqa+zRbHgpzXThy6+6bGzyI7WUPasvUlxzDZKaIZMuVACCGEEELENBmhFUIIIURMkCkHojkyQiuEEEIIIWKajNAKIYQQIjbIAK1ohozQCqpCFXzt/YSa0H7l2QUfz6Xwsw+U5wKUfryQorf+oyW74otl7Jv5by3ZVd99z96np2nJrt28hfwnnyZUW6s825efT/6TT+MvKlaeHaioIP/Jp/H+tEN5thkMkv/k01SvW6c8G6Dg+ensX/WVluzCV16j/LMlWrJL3n6H0vl6+mbZx4somv2WluzK5V+y718vasmu2bCZvf98mlCtV0v+nX8q49+vVGnJFuJkJyO0gmqzkqLQHgxD/aXG3sICrG6P8lyAQFGRluIKIFhahm/Xbj3ZFZXUbv9JT3Z1Nd5t2zFD6i8FDnl94Wy/X3k2wSDebdu1FOIA3u3bCe3XU0h4d+zE2VXPLWp9e/Zgcbv1ZBcUYHE6tWQHiorw7yvUk11ahnennr4ZqtyPd6uevgmwaHEt7drKONIvInNoRTOkZwm8ZjVg4EDPiVMIIZTRWNCYoSAAhlX9qdE0TYqKQ6SmWJVnCyFkhFYAXrMGJy4shob3N9rXfpV360KcbDR8mBQWqns9sah/LaysNPH7oU0bGUf6JQx5yRfNkIJWUGtW4zQ0js7KR0RCiBgQnaqjoaAtLApnp0hB+8vI+UQ0Qwrak5hphgAjPEJr6JnnaugfohVCnGx0DdEGg2CxKL+ewDRNikukoD1Z3HfffcydO7fZ52+99VZuu+025syZw/33399km7Zt27JkyYELQmtqapgyZQoffPABRUVFtG/fnmHDhnHLLbdgqfcGLBgM8vzzzzN37lz27NlDmzZtGDx4MHfccQeug+4g+vrrr/Pyyy+zfft2WrVqRf/+/Rk3bhzJycm/cA8cG1LQnsRChPjet5Qqs5x4I4ldgU2k27oryTaDQYo+/5BgbTWhYIDCT+eTctEgDAXTGkzTpOzDjwhWVBKq9VIy/wOSLrsMi8OuYMuhfOEn+IuKMQN+yj5aSPy5fbC1aqUku+Lzpfj25INpUvHZ57gyu+No105JduWKVfj37gVg/8rVODt3wtX1VCXZVd+twbdnDwDVa34gUFqKJydbSXbNxk34du4CoHbjZoL7q4jvfaaSbO/OXXi3bQ9/v2Mnpj9AQt9zlWT7i4qp/v57CIXwFxRQ/ukSEi/upyQ7WFNDxadLMH1+AqWllH20kKSBlynJNoNByhZ8SKi6GtPvp3T+ApIGDcRQMCppmiZlCz4iUFFByFtL6fwPSFTYN8sWfoK/sAgzEKDso4UknHcO1oQEJdkViz/Hv2cvGAaVn32BK7Mb9nZtlWQ/83wV6zeEL6b8cpWP6hqTXmc4lGSfbIwYuPXtrbfeyg033NDo8R9++IG//e1v9OzZs8Hj06ZNIzU1tcFjdnvDPnPHHXewatUq7r77brKysvj666958sknKS4u5oEHHoi2mzhxIrNnz+bWW2+lT58+bNq0iX/84x9s376dadMOrK4zffp0HnnkEX73u9/xt7/9jfz8fCZPnszatWuZPXs2NlvslYext8VCGatho9qspMbcT425nwSLundlhtVK7b491ObvBMAe30pJMQtgGAbBikpqNmwAwOvxKDthAoT8fqq//Q6A/au+UlZIABhWG/uXrwCgbMFHdLqgr7Jsa5yH4sWfAVD6znt0mvg3Zdm21skUznwJgLL5C+j453uVZdvT0ih45jkAyhd9Qrtbx6rLbpvG3qeeBqBy6Rek3Nj4JPNz2VonU/HZ54Rqaqha/RWOjh2UZVvdbmp+/JFAURGBoiLsKSnKsg2rFd+efHw7wn3TlpiopJiFSN+soHZ9Xd+Mi1PaN836fXO14r5ps7F/2UoAyt7/iPQL1LzxAeicbmX83ysA+OuECtZ+raZQFsen9PR00tPTGzwWCoWYMGECF198Mf36NXzj26NHj0bt61uxYgWfffYZf/3rX6OFcu/evSkrK+Nf//oXI0aMoEOHDuzcuZPXXnuNESNGMHbs2Gi7yN9evXo1Z511FlVVVUydOpVBgwZx3333Rf9Oq1atGD16NO+//z5XX321qt1x1MhnHye5SBFrYCgbnY1md8+Nfh9f73sVPLk5TX6vJDsvt973arPd9UY13dlZGFZ1Vzy7enTHsIffo7q6norVo24aiSO9I9bE8Ci1LTUVe1rqYX6j5WxJiTjSOwJg8bhxntpFWbbF4cDVve64tlhwZ2UqyzYslgb/nqqPQ7fOY7xenjuWsuv3TdX7O+fAseHOy1baN3udeWA09pr/cpGQIKfen8009X1pNHv2bNavX9/sFIND+fjjjzEMgyuvvLLB40OGDCEUCrFo0SIAFi1ahGmaDBkypEG7K6+8EsMwWLhwIQDLli2jurq6Ubt+/fqRlJQUbRdrpFed5BKMcEGbaumES/E82rhudSccw0Jc1yyl2a7u3THqPpLx5Kg9sdUv3lSfNOsXb6pP9haHA1eP7lqyDcOIFm+qi3w4sL2qi3wAT264CFJd5Iezw9ttS03FnqquyA9nh7dbdZEP4I70GcVFPjR8Y6W6/zg6dsBaN/1H9XFoa9MaW9u0cHbPPKXZHdpbSEsLn25v/G2c0mxx/PN6vTz11FP8+te/pkuXLkf8+xs2bCAtLY2kpKQGj3ft2hXDMFhXd9OYDRs2YBgGGRkZDdolJiaSlpbWoB1A9+4NB7EMw6Br167RdrFGCtqTXCtLawA623ooz7YnJOJq3wl3p1OV31zB4rDj7tEdu+LRQogUbzlY3OoLCagr3iwW3NlqCwk4UATpKDojxYnqIgUOjLypLsTDmdnasiPFm459Enlj5c5SX+RH3ljpKPIjo+K2NPVFfmRU3OLx4PwZhcHhuHMzMRx2XIr7pmEY9DrDQVamjbN6qZuCcVIyNX5p8tZbb1FWVsaoUaOafP6VV15hyJAh9OzZk/PPP58///nPFBcfuGlQSUlJkxdqORwO4uPjKSkpAaC4uJj4+Hgcjsbzs5OTkxu0izzWVLv6fzuWyBzak1yCJZk4I5Fki545XfHdcjDsei5+cOfkYEvZpyXbk5eD6fUqLyTC2bl4t2xVXkhAeEqDPS1NeSEB4eLNmthKS5HvSO+INTkJd5bakXwIzxF1pKdrKTojxZuO7MgbK1e3jMM3/hncuTlYDrrqWRVPbg7+oiI92Xk5mAG/lr7pzskkWFKmdN5vRK8z7FzY16Hljozi6PD7/ezYcejbcyckJJCWlhb9ORAIMGPGDAYPHtzsPNlt27Yxbtw4EhIS+PLLL3n++ef58ccfeeutt7DZbHi9XjzNnC/sdju1dXdY9Hq9TRazkXbl5eXRdkCTbe12e/T5WCMF7UnOYbjobj9D24tsfPdcbQWtJzcHv4bCDcJTGsygnstpHekdSeh7npZsW1IiiYMGaMm2OBwkXz1ESyFhGAbJQ67E6tGzHnKrSy7SUuQDxJ99lpYiH8BzWh7OUzrryc7JweLWU9C6c7KxF5doyXZ176YlF8DVrSumT8OtnYFz+zjIypTR2V/KOIbr0BYUFDB48OBDthk6dCgPP/xw9Ocvv/yS3bt38/e//71R28GDB9OvXz9S6l30edZZZ5GcnMyDDz7I3Llzufbaa3G5XPibueW4z+eLLsd1JO0gXKAfvJRX/XaxRgpaQZq1k7ZsZ9uO2rJtrVopW7LnYBaHHc9pai9kizAMA8+ZPQ/f8GeKO/MMyT6K2Z6ep2t7Q+jOytSW7eiUri3blpSENTFRS7bF6dQyfQTAsNtxn66n3593jozOxrr09PTo/NOW+vjjj/F4PJx99tmNnnO5XE0WjwMGDODBBx9kzZo1XHvttaSkpLB169ZG7Wpra9m/f390RDglJYXKykp8Pl+j0dfi4mKy6j4BixTQJSUlJBx0Di0uLm60hFiskDm0QivDMLS+iEu2ZEv28ZetOz8Ws6WYVSSGVjkwTZNFixZx3nnnNTsVwOfzNXos8pG/0+kEIDs7m3379lFaWtqg3caNGwHIrbt2Ijs7G9M02bRpU4N2RUVFFBUVNWgHNCrOg8EgmzdvJi9P7UWRR4sUtEIIIYSIDSGNX4rt2rWLwsLCZgvEm266iYEDBzaas/rhhx8C0KdPHwAGDRqEaZq88847Ddq9/fbb2O12LrssvB7zgAEDsNlszJs3r0G7yM9XXHEFAH379iUxMbFRu48//piqqqpou1gjUw6EEEIIIRTbtm0bQLMXg40YMYIxY8YwatQobrrpJuLj4/nyyy+ZPn06ffr0oX///gD07NmTK6+8kieeeAKbzUZWVhbLly/ntdde4w9/+ANt2rQBwrfLHTFiBDNmzCA5OZk+ffqwdu1apkyZwrBhw6Ijs06nk3HjxjF+/HgmTZrEwIED2bFjB5MnT+bcc8+N/t1YIwWtEEIIIWLCsbwo7EhVVITvDhcX1/TawxdddBEzZ87kmWee4U9/+hN+v5+OHTsycuRIxo4di6XeHfwefvhhnnrqKV544QWKiopIT0/nvvvu46abbmqQOW7cOBITE5k9ezZTp04lLS0tmlffddddh8PhYObMmbz66qskJSUxZMgQ7rzzzpidHmOYZgwdHcdAYWHlsd6E486NmX/Ulr35Hj0XewCY6i/ObyBk19iVYvP1RS955WpM43Fiajy+TZvef8zPBz+mLdvt3KgtO1alpuq5WBfg8rMnaMv+cNV4bdlCPxmhFUIIIURskDE40Qy5KEwIIYQQQsQ0GaEVQgghRGyQEVrRDBmhFUIIIYQQMU0KWqGVN1TNmqolVAcrlGeXr1hO8YL3lecCVKz4kuL33jl8w5+het06Cme9oiW7dvtP7Jv5EiEN9+L27ytk38yXCJSWKc8O7t/Pvpkv4du9R3m2GQyyb+ZL1GzerDwboOi1N6j6fo2W7JJ571D55Qot2WUfLaT8k0+1ZO9fvoqS/2jqP199T/Gst7RkA0z8ewUffVirLV/8QjG0Dq04uqSgFVrVhCrZ49tEiKDybO/uXdRs0VOk+PL3ULNJz9XLgaJiqtf8oCU7WF5O9XdrMIPqX52D1dVUf7eGUK36k73p91P93RqC+/crzwao/n4NQQ2FOED12h/x7yvUkl2zcRO+Pflasr1bt+H9aYeWbN/O3dSu33T4hj8ne89ean84stuPHok33qhh6zb1r1dCDcM0tX2J2CYFrdDKG6oBwGG4NaSb+pYpsliQFe2E+JlMEyyaTi8m2vp9ba1JRblJWqqcGoWINXJRmNDKG6rGwILdcKoPN/Wd2QzDgJDOglaKZXFsaawLMUMhjYuz69vyoqLwJxspKVLQHrdkoEE0Q3qt0Mpr1uA03PpObrrOmYYFQrE4qUruwCCOAzE6QltYGJ5qkJomp0YhYo2M0AqtvKFqHBYd0w0A09RXKFsMmXIgxM9lmmDR1DdNEzT1+8J94TexqTLl4Pglr8uiGdJrhRamabK26guqguXYDAf5vq2YppoRT9M0KftiCaGaGsxAgPJlSwn5/UqyIbzCQaiqCjMYoOLL5QQq1a3QsH/VagIlpZghk6pvvsW/b5+y7Kpvv8NfUABAzbr1eHeou+Cn+sd1+HbsBMC7bTs1G9Vd8FO7dRu1m8IX9/l276H6h7XKsn179kQvwPMXFrH/62+UZftLSti/+iswTYLlZVSuWKksO1hTQ8UXyyAQJFRVFf5eETMYpPzTJZg+HyGvl4rPPsdU+GlExSdLCFZVQTBE5ZJlhHzq+mblki8JVlRCyGT/F6sIlqu7NfkzU/fz6adeLBZYvz7AT9sDyrKFEPpJQSu0MAyDqlAZZcECSgJ72Of7CcNQc7gZhoF39y6qfvwB7+5dVH73NRa7XUk2QKCkmMpVKwmWlVH2ySKs8eruSx6qqaHi088gGKTo9dnYWrdWlg1QNn8BAEUvv4otOVlZrsXlomTO2wAUz34La3y8smxrq1YUvfoGAKXvvIdhU/fBka11awpffhWA8o8XYgbUFSm2pCRK3p5HqLqayqXLwoWWIla3m8qlX+Dft4+qr7/Bv7dAWbZhtVLz4zq8W7dRu34DtVu2YiicHuDbuZua79bi27GLqpVfY3Go65vBohKqvlhFsLSM8vcXYmml7ji02QxeebmGUAhu/X0ZbdtZlWULhUxT35eIaVLQCm1aWVOi33dyZinNjsvKOfB9dq7SbE9OXvR7d1aW0mkN7twD2+3O7KG0eHNnZYI1fBJ2du6MNUFdIe7scgqWuDgArMlJ2Nu3U5ZtT2mDvV1bAAynE1e3DGXZFpcLV0bX8A+GgSdb3XFoWCy4s7OjP3vq/duq4M45kKc6u36eW/V25x7YJ+7T1fZN1+n1s3OU9s3TTj/QF6/9jRuXS+ajCxFLpKAV2rSyhQvaOEsSyTZ1BRCAu3tm9KIT1QWts1OnaDHoyco+TOsjY29zoHhTXUhYXK5oMejOU5ttWCy4c8LFoCdXbSEBB/aF6iIfDhRvqov8+tnW5GSlRX79bNVFPtQ79gwDT47aN5uunB7ROa6enor75qmdsXjcddlqj/G8vAMjyb+9waM0WygkN1YQzZCCVmiTaG0DhEdnVRdAVrcbV5eu2Fq3wZ7WVmm2YbHgycnDsNlwd+umNBvAk5tbV0ioLZbD2TkN/qsnW22RUj9bdZFfP1NLdt2ouI4iPzwq7tFS5EdGxZ2nqC/yrR4Pzq5dsLVNw942TWm2YbXiysvEcLlwdj9VaXZCgoWuXa2cf4GDU0+V66WPV3JjBdEc6bVCG48lEYfhpoNDfVEI4WkHgfIyLSsdxOXmEigtweJQv36uOzeHms2blRcS4exsrIs/Uz5aCOHizeLx4OqudrQQ6oq3+Hjlo4VwYFRcR5EfmdKgIzsypcHVXU//cedkY3HrWYHEnZtFqEbP7WPdp2VDyFRe5APknWZn0BUu5blCCP1OmIL25ptvZvny5fz73//mnHPOiT4eDAZ5/vnnmTt3Lnv27KFNmzYMHjyYO+64A5dLXrh0MgyDHu6zsVs03FSB8HSAYIW6FQjqc3frTrBS3UU+9TlP6UxCnz5asu1t2pB42SVainyLy0XSlYO0FBKGxULyFZdrKfIBWl14gZYiHyCu15nKpwREePJycXVVOxJZP9vi1vMa6M7NwlS48kh9rtxMbct29e/vZOBAPa9XQhEZSRXNOCEK2jlz5rB8+fImn5s4cSKzZ8/m1ltvpU+fPmzatIl//OMfbN++nWnTph3lLT356BqdBbCnpGJvk3L4hj+DYbMR3/ssPdkWC/Hn6iloARLOOzcms+PPO+fwjX5u9rnnaFuzOP7ss5SuElCf57Q8bdnOLqdoKwztHdtrKzyscR48vU/Xkn31NS6NdzgTQugU8wVtcXExkydP5uKLL+bTTz9t8NzOnTt57bXXGDFiBGPHjgWgd+/ehEIhJkyYwOrVqznrLD1FiwjTeXIwDEPbCRnQVkhItmSf8Nkx2jelmI0BWm9JLmJZzF8UNmnSJJKSkhg+fHij5xYtWoRpmgwZMqTB41deeSWGYbBw4cKjtZlCCCGEEEKTmB6h/eyzz3jvvfd46aWXmnxnvWHDBgzDICOj4fy2xMRE0tLSWLdu3dHaVCGEEEL8UjKHVjQjZkdoq6urmTBhAkOHDuXcc5ue11dcXEx8fDwOh6PRc8nJyZSUlOjeTCGEEEIIodlxNULr9/vZcZj7zyckJJCWlsaTTz5JVVUV99xzT7NtvV5vk8UsgN1up7y8/Bdt78lq1obHj/Um/Cw3dr9Ta/6m/1W/PuvRELLLiEcjGqdSmlaN+1vjEMUX//VPbdkO50Zt2WFjNOeLo0ZGaEUzjquCtqCggMGDBx+yzdChQ7nhhhuYNWsWEydOpHXr1s22dblc+JtZOsbn88myXUIIIUQskYJWNOO4KmjT09PZsGHDIdsEAgF+/etfc+aZZ3L55ZdTVVUFQG1tbfS/VVVVxMXFkZKSQmVlJT6fr9FIbXFxMVlZ6hdxF0IIIYQQR9dxVdC2xN69e6MXc/Xq1avR86NHjwbCF4RlZ2djmiabNm0it97tOouKiigqKmrwmBBCCCGOc7Jsl2hGzBW0aWlpvPLKK40eX7duHRMnTuSBBx4gOzsbgAEDBvB///d/zJs3r0HxOm/ePACuuOKKo7PRQgghhBBCm5graB0OR5M3QwgGgwD06NEj+nzbtm0ZMWIEM2bMIDk5mT59+rB27VqmTJnCsGHDooWvEAcr9O+iMlhMV1dP5dk1W7dQvXYtbYb8l/Ls2h0/sf/rr2jzX9coX3zeX1xMxWefk3jZpdhatVKaHayqpuzDj0g4vy+OtmlKs81QiJK33yG+dy+cp3RWmg1Q+t58XN274c7soTy7YvHnWOI9xJ/dW3l25ZJl4Tvi9VV/17r33quluDjETTd5lGeLk5wZOtZbII5TMbtsV0uNGzeOcePGMXfuXG666SZefPFFRo4cyYMPPnisN00cx8qCe9nlO/R87p/Ll59PxfIvtGT79+2jYtkXWi6cCFZWUvn5UkLV1cqzTZ+Xys+XEiwrU56NaVL5+VL8+/apzwYql6/Au3OXluzqb76jdsNmPdnfr6XmRz3H+OLFXua+XaMlWwghmhJzI7TNOeecc5q8oMwwDEaNGsWoUaOOwVYJcZRFbjAiVwKfEEzT1HqLWiFijry2iWbIK6UQJ5BI8WPKi/6JIWQeeJMihBCiWSfMCK0QggPFT0jmmZ0QTBMsUtAKESWrHIhmSEErxIkk8vG0jNCeEEwzJCO0QtQnr22iGTLlQIiD7PFtwW/6MYEC/3a8IXUXt1St/YFQTTivdttW/EVFyrKrN24guH8/AN6dO/Du2a0su3bzFgLFJQD4C4uo3bZdWbZ3xw58e/cCECgro2bjJmXZvr178f4Uvp12cP9+qtf+qCw7UFpat60mZm0tVd+vUZYdqq6h6tvvIRiCYIiqb75Xlm0Gg1St/gZMM/z9qm8wFY3om6bJ7NnV1NSYBALw1n9qqKmRAkQIoZ8UtEIcpDJYzE7fOmrN/ayr+RKHoe4Wyf7CfZR+tAAzECD/heewtkpQlh3cv5/it+cAhLM9ccqyzVCIopdfBaDwXy9iWNW9dBhOJ/uenwFA8euzMX0+ZdnWhAT2Tp0GQOk77xFQuIqCNSGBff96iVBVNeULP8G3S90bCMPtomzefPz5e9m/bAW169StRmBYrVQuWU7t+k3UfL+WqlVfK7vwzDAMPlvi4513a/n2Wz8z/1WF2y0jzEIh09T3JWKaFLRCHCTV3qnB94bCj3w92Qdu8OHq1h2Lw6kuOys7OuXA0b49tqQkZdmurqdiuMKFvTUhAUd6urJse1oatpQ2ABh2G64e3ZVlW+PicHY5JfqzJzdHWbZhs+HOyjyQnacw2zBw5x64Nbf7dLV3NXSfll3ve3XbDXBZ/wPHdP/L1L0ZFEKIQ5GCVoiDJFnbYsMBQJpN7UL89rQ0bG3CxVtcttpCwurx4O6aAdQVtwrVL97cOdlKl5IyDANPTnhfuLp3x+JwKMuGA0Wso2NHpUV+/WxrK7VFPoA7J1zQGg6H0iIfwFOviHXnqT1WLrnEidUa/n7AZeresAkByAitaJYUtEIcxGJYSLGnY8FKa1t7pdmGYURHaT0a7lTnqbvFs1txQQvgyavbboWjnBHuukx3jvrtjmbnasjOyQLDwJ2bo3y9WGe3DAy7HXdOJhaHXWm2rW0atpTWODp1xJacpDQ7KcnC2WfbadfOQl6eXHcsTl6BQIDHHnuMrKws/vjHPzbZJhgMMm3aNAYOHEheXh4XXXQRkydPpra2tlHb119/nauuuoq8vDz69u3LX/7yF0pLSxu1++ijj/jVr37F6aefTp8+fbjzzjvZtavxzV9WrlzJ8OHDOeOMM+jVqxejR49m/fr1jdqtX7+e0aNH07t3b3r27Mnw4cNZuXLlz9gjeklBK0QTUm2daGPrgNVQf0KOy8nB0aEDtqRkDdl5WNxuXJ1POXzjI+TOytIyWggHpjToKJYjUxp0ZFvj4nCe2kVLtsVhx9WjG+7T1E43gLopDaflKB+djRhwmYvLLnMqna4jBBBeklDXl0L5+fnceOONzJkz55Drgk+cOJGnn36aoUOH8tJLLzF27FjeeOONRgXw9OnTGT9+PBdccAEvvvgi999/P4sXL2bkyJEEAoFou/nz53PbbbeRkZHB9OnTmTRpEhs2bGD48OFUVlZG23311VeMGDECt9vN1KlTeeKJJ6ioqGD48OENit8dO3Zwww03UFpayqOPPsqzzz5LfHw8I0aM4LvvvlO4x345efssRBNSbOmYBLVku07tSnyvs7Rk25KTSbrkUozIZ74KWeM8JA0cgMWp/mNkw2Yj6bL+yqcEQLh4SzjvXOVTAiLizuippcgHcJ+Wq2VkGcCdl4PFrWeO62WXOdm2Tf0xKESsuOeee7BarcydO5cLLrigyTY7d+7ktddeY8SIEYwdOxaA3r17EwqFmDBhAqtXr+ass86iqqqKqVOnMmjQIO67777o77dq1YrRo0fz/vvvc/XVV2OaJo8++ig9e/Zk8uTJ0TeUXbp04aqrrmLWrFn8/ve/B+CJJ54gJSWFqVOn4qib5pWXl8ell17KtGnTeOihhwB45plnCAaDPPfcc7Ru3Tq6jQMHDuTxxx/nxRdf1LL/fg4ZoRWiCQ6Lk/b2blqyDauVxL7na8kGSLygn7bsVhddGJvZ/S7UdgvZhL7nKp/3GxF/Tm+scR4t2a7uXXF06qglOyPDxkUXyfxZoUGMzKH97//+b1588UVSU1ObbbNo0SJM02TIkCENHr/yyisxDIOFCxcCsGzZMqqrqxu169evH0lJSdF269atY/fu3QwePLjBpyPdunUjKysr2q6srIxVq1YxYMCAaDEL0Lp1a84///xoO9M0WbhwIX379o0WswAOh4OBAweyYsUKKioqfs7u0UIKWiGaYTH0dQ/Dpu/DEcmW7BZlW63ainwAu12mGwgNYqSgveqqq7Adpv9u2LABwzDIyMho8HhiYiJpaWmsW7cu2g6ge/eGnwQZhkHXrl0btevRo0ejv9WtWzc2btxIMBhk48aNmKbZbLuysjLy8/PZs2cPlZWVjf5uZFtCoRAbN2485P/j0SQFrRBCCCHEUVZcXEx8fHyDUdKI5ORkSkpKou0ijzXVLvL84dr5/X4qKioO2y6S1dJ2xwuZQyuEEEKI2BA6dstr+f1+duzYccg2CQkJpKWltSjP6/U2WcwC2O12ysvLo+2AJtva7fbo84drF2kTaRd5rKl29VdZOFReU6sxHCtS0AohhBBCHEZBQQGDBw8+ZJuhQ4fy8MMPtyjP5XLh9/ubfM7n8+Gqu5lN5L9+vz/6/eHaNZUXaXOodpHH3G43obqVHw6V53a7D/W/eFRJQStOGrM2PXGsN+FnuzGz6TUMVdh0v/olpyJCdo2jKRqnaJoat3vJf/1TW7bbqXM+2y0as4VoGdNUu7zWkUhPT4/OU1UhJSWFyspKfD5fo1HQ4uJisrKyou0ASkpKSEhIaNQucuFZ/XYHKy4uxuVykZCQEG3X1Bq2RUVFAKSmpkYL2qby6rc7XsgcWiGEEEKIoyw7OxvTNNm0aVODx4uKiigqKiK37kY52XU34Tm4mA4Gg2zevJm8vLxDtos8lp2djdVqJTMzE6vV2my71NRU0tLSaNeuHcnJyc22s9vtTV5YdqxIQSuEEEKI2BAy9X0dZQMGDMBmszFv3rwGj0d+vuKKKwDo27cviYmJjdp9/PHHVFVVRdv16NGDjIwM3n333QY3c1izZg1btmxh0KBBQHieb9++fVmwYEGDObAFBQUsX748mgdw+eWXs2zZMgoLC6OPVVdX89FHH9GvXz/i4uJU7AolZMqBEEIIIYQiPp+v0ahmRUUFa9asAcIrBKSnp9O2bVtGjBjBjBkzSE5Opk+fPqxdu5YpU6YwbNiw6Iir0+lk3LhxjB8/nkmTJjFw4EB27NjB5MmTOffcc+nfv3/079x7772MGTOGP/3pT/zmN7+huLiYRx99lIyMDK6//vpou7vuuovrrruOP/zhD4wcORKv18uUKVNITEzkllsOTC/6/e9/z4IFCxgzZgy33XYbdrudF154gZqaGsaNG6dzNx4xwzzUPdkEhYWVh28khGYyh7YJMoe2Eb1zaIVomdTUhMM3+pkGJY/Slr2gdLqSnF27djUoMg9W/8Ix0zSZMWMGs2fPZs+ePaSlpXHNNdcwduzYRqsQzJkzh5kzZ7Jt2zaSkpIYNGgQd955J/Hx8Q3aLV68mKlTp7JhwwY8Hg8XX3wxd999d6P5rt988w2PPfYYa9aswWq1ct5553H33XfTpUuXBu22bNnCI488wsqVKzFNkzPOOINx48Zx2mmn/YK9pJ4UtIchBa04HrS0oK0OVrDPv4N0ZyY2o/GSLE1paUEbKC+n8qvVtOpzDtaDXkCb09KCNlRTQ8UXy4g78wzsbdq06HdaWtCaoRDlixbjyc3B0aF9y37nCAraisWf4zylE86uXVrU/kgK2rfn1pCaZuH881t21y0paMXxQGtBmzhCW/aC8n9pyxb6yRxaIU4g+4NlbKhZQdAMKM8OlJVRumA+wf37lWeHamspe/8DAkUaFuk2Tcre/wDfrt3qs4HyBYuo3bxVS/YLL1Qx/73jZ51HIYQ4XskcWiFOKPKBy4nENNE6tUKImCMfKotmyAitECcgqYFODKYZvl+7EEKIQ5MRWiFOIGZ0hFaKoBOCCVLPCnGAGTp2N1YQxzcZoRVCiOOUKQWtEEK0iBS0QpwgSvz5BMzw/bVrQpXsDza+reHP5d25k1BNNQDBqv1496i7wMq3J59gRQUQvjjM+9NPyrL9hUUEisO3bTT9fmq3blOWHSgrx7dnbzg7GKR24xZl2eXlIb5c7sM0IRSCTxd7lWULEdNMU9+XiGlS0ApxgqgJVfJD9ecAfFn5DhaFM4qC+yvZ+2J4SZv8F54j5FVXYJmhEPlTpgJQ+O+XCZSoK8QNh4Pdkx8FoPg/c/Hu2Kks2+LxsPfRpwlVVVM+fyE1a9cpy27VymDcH8vYsCHAy7OqefedGmXZQghxIpKCVogTRIo9Pfp9vDUZj1XdWpCubt0xrFYALC4Xrs6nKMt2dOyAtdWBbXVnZSrLtiW2wtGxQ/iHUAhPnrqbSFgcdlw9MogMo7pPU5dtGAaXXOqMDhxdNtClLFuImHYC3fpWqCUFrRAnCKfFQytrCgBp9s5Ksy12O+7uPQDwZGVHi1sVDMPAkxMuBl0ZGVjcbmXZAJ7ccLa9bRr2lBSl2ZEi1hLnwXmquiIfoP9l4SLW4YB+/RxKs4WIWWZI35eIaVLQCnECSa0rZFPtaosrAE92ToP/quSuKzojxaeObLeO7LzwvdbdOVlKi3yAvuc5cLmg7/kO4uLkpVoIIQ5Flu0S4gSSau/ETu86Eq1qRyKhrpC1WvH0UDclIMLVrRuGw447N1t5tqNjB6yJiXjycpVn2xJb4eicrnS6QYTLbXD+BU4uvbRlt70V4mRgytQA0QwpaIU4gbSytqGTM0vLYvy2Vq1I6nex8ikBEJ6P2qrfhcqnBEB4SkN8n7NwdlE/ag3gOfM03Dk9tGRfdpmTS6SgFUKIw5KCVogTiGEYnOo6XVt+Uv/+2rITL9OZfSmGRc/H9gkXXYDFqWeO67BhblxuWYhWiCiZ6yqaIROzhDjBWA1971MtDn2jhRZnrGbru2BLilkhhGgZGaEVQgghREyQObSiOTJCK4QQQgghYpqM0AohhBAiNsgcWtEMKWiFiAGzNjx+rDdBKHPLsd4AIYQ44RimacqEFCGEEEIIEbNkDq0QQgghhIhpUtAKIYQQQoiYJgWtEEIIIYSIaVLQCiGEEEKImCYFrRBCCCGEiGlS0AohhBBCiJgmBe0J7OabbyYzM5MVK1Y0eDwYDDJt2jQGDhxIXl4eF110EZMnT6a2tvYYbWlsqqysZPLkyVx44YXk5eUxcOBAJk6cSGlpaYN2sr/VWr9+PaNHj6Z379707NmT4cOHs3LlymO9WSeEZcuWcf3119OzZ0/69OnDb3/7Wz777LMGbWT/67Fq1SqysrK48cYbGzwu+1uIlpGC9gQ1Z84cli9f3uRzEydO5Omnn2bo0KG89NJLjB07ljfeeIM//vGPR3krY5ff72fUqFG8+eab/L//9/+YOXMm119/Pf/5z3+46aabCAaD0bayv9XZsWMHN9xwA6WlpTz66KM8++yzxMfHM2LECL777rtjvXkx7ZNPPuF3v/sd8fHxPPXUUzzyyCM4nU5Gjx7NBx98AMj+18Xn8/GXv/yFg5eFl/0txBEwxQmnqKjI7NOnjzl69GizR48e5pdffhl9bseOHWZmZqY5efLkBr/zyiuvmD169DBXrVp1tDc3Ji1YsMDs0aOHOWfOnAaPP/fcc2aPHj3MZcuWmaYp+1u1e++91+zZs6dZXFwcfczr9ZoXXXSRedNNNx27DTsBXHXVVebAgQNNn88Xfay6utrs06ePef3115umKftfl8cff9w877zzzGHDhpnDhw+PPi77W4iWkxHaE9CkSZNISkpi+PDhjZ5btGgRpmkyZMiQBo9feeWVGIbBwoULj9ZmxrRu3brx0EMPMWDAgAaPZ2VlAZCfnw/I/lbJNE0WLlxI3759ad26dfRxh8PBwIEDWbFiBRUVFcdwC2OXaZqMHTuWCRMmYLfbo4+73W5OOeUU9u7dK/tfk40bNzJ9+nTuuusuPB5P9HHZ30IcGSloTzCfffYZ7733HhMmTMDhcDR6fsOGDRiGQUZGRoPHExMTSUtLY926dUdrU2NaRkYGv/71r4mPj2/w+NatWwHo3LkzIPtbpT179lBZWUn37t0bPde9e3dCoRAbN248BlsW+wzDYPDgwZx77rkNHvf7/fz000907txZ9r8GoVCIv/71r5x55pn86le/avCc7G8hjowUtCeQ6upqJkyYwNChQxudmCKKi4uJj49vsthNTk6mpKRE92aesAoKCnj22WfJysqid+/egOxvlYqLi4HwfjtY5LFIG6HGU089RVlZGb/97W9l/2vw2muvsXbtWiZMmNDoOdnfQhwZ27HeAHFofr+fHTt2HLJNQkICaWlpPPnkk1RVVXHPPfc029br9TZZXAHY7XbKy8t/0fbGuiPZ3/UVFxczZswYfD4fjzzyCIZhALK/VfL5fABN7s/Ix+SycoQ6r7/+Os8//zzDhg1j4MCBrF69GpD9r8revXv55z//yejRo+natWuj5+V4F+LISEF7nCsoKGDw4MGHbDN06FBuuOEGZs2axcSJExvMtzqYy+XC7/c3+ZzP58Plcv2i7Y11Ld3fDz/8cPTnHTt2MGrUKEpLS5k+fTo9evSIPif7Wx2n0wnQ5P6MnPzdbvdR3aYT1dNPP81TTz3FkCFD+Pvf/w7I/ldtwoQJpKWlccsttzT5vOxvIY6MFLTHufT0dDZs2HDINoFAgF//+teceeaZXH755VRVVQEH3r3X1tZSVVVFXFwcKSkpVFZW4vP5Gr3zLy4ujl7UdLJqyf6ub/369YwYMQKXy8Vrr71Gt27dGjwv+1ud1NRUgCanaRQVFTVoI36+8ePH8/rrrzNq1Cjuvvvu6KcNsv/V+fDDD1m8eDHPPfccfr8/WrRGlvurqqqiTZs2gOxvIVpKCtoTwN69e6MXF/Xq1avR86NHjwbCFyhlZ2djmiabNm0iNzc32qaoqIiioqIGj4lD2717N6NGjaJNmzZMnz6dtm3bNmoj+1uddu3akZyc3OQbjg0bNmC32xuMjosj9/jjj/PGG2/wv//7v/zP//xPg+dk/6uzePFiTNOMvjYfrFevXtx6662yv4U4AlLQngDS0tJ45ZVXGj2+bt06Jk6cyAMPPEB2djYAAwYM4P/+7/+YN29eg2Jq3rx5AFxxxRVHZ6NjXDAY5Pbbb8fhcDBz5kxSUlKabCf7W63LL7+cuXPnUlhYGB2dqq6u5qOPPqJfv37ExcUd4y2MXQsXLuTZZ5/l7rvvblTMRsj+V2PMmDH8+te/bvT4xIkTAXjggQfo0KEDRUVFsr+FaCEpaE8ADoeDs846q9HjkY+vevToEX2+bdu2jBgxghkzZpCcnEyfPn1Yu3YtU6ZMYdiwYdHCVxza3Llz+eGHHxg3bhz5+fnRdWcjkpOTSU9Pl/2t2O9//3sWLFjAmDFjuO2227Db7bzwwgvU1NQwbty4Y715MSsQCPDwww+Tnp7OOeecw5o1axq1yczMlP2vSJcuXejSpUujxxMSEgCir9eyv4VoOcM0D7rXnjhhrFixgv/5n//h3//+N+ecc070cdM0mTFjBrNnz2bPnj2kpaVxzTXXMHbs2AaLqovm3XfffcydO7fZ5+tfOCb7W60tW7bwyCOPsHLlSkzT5IwzzmDcuHGcdtppx3rTYtauXbvo37//IdssWrSI9PR02f8a3XjjjQDMmjUr+pjsbyFaRgpaIYQQQggR0+TGCkIIIYQQIqZJQSuEEEIIIWKaFLRCCCGEECKmSUErhBBCCCFimhS0QgghhBAipklBK4QQQgghYpoUtEIIIYQQIqZJQSuEEEIIIWKaFLRCiOPOjz/+yJlnnsmf/vSnY/L3lyxZQk5ODo8//vgx+ftCCCGOjNwpTAhxXCkvL+fqq68mISGBt956C6fTeUy245lnnuHJJ5/kySefZNCgQcdkG4QQQrSMFLRCiOPKPffcw7x583jttdfo1avXMduOYDDI0KFDKSgo4IMPPqB169bHbFuEEEIcmkw5EEIcN9auXcu8efO44IILjmkxC2C1WrnrrrsoKyvj2WefPabbIoQQ4tCkoBVC/GKrV68mOzub66+/noM/9HnrrbfIzMzk3nvvPWzOrFmzABg1alSDx+fMmUNmZiYvvvgiq1at4sYbb6R3796cfvrpXHfddaxcubJB+xtvvJHMzExKSkqYPHkyF154IaeffjpDhgxh0aJFALz77rtcffXV9OzZk0svvZSJEyfi9/sb5PTr14+OHTvy5ptvUl1dfcT7RQghxNEhBa0Q4hc766yzGDlyJF9//TWvvvpq9PGioiL+8Y9/0LFjR/7yl78cMsM0TZYsWUJcXBxnn312k22+++47br/9dvr06cNf/vIXrrvuOtasWcMtt9xCUVFRo/YTJ05k+/bt3HHHHYwcOTL6/b/+9S+eeuophg0bxv3334/T6WTWrFm89NJLDX7fMAwuuOACqqur+fTTT498xwghhDgqbMd6A4QQJ4bbb7+dpUuX8thjj9G/f3/atWvHxIkTqays5JlnniE+Pv6Qv79+/XqKi4u59NJLsdmafmlasGABc+fOJSsrC4BrrrmG8vJy3n77bZYsWcKwYcMatK+oqGD69OnRn4uLi3njjTd46qmn+Pjjj0lJSQEgMzOT6667jsWLFzcaHb7gggt44403WL16NYMHDz7i/SKEEEI/GaEVQijhcDh45JFH8Pv9/O1vf+OTTz7hgw8+YPTo0Zx11lmH/f1t27YBcOqppzbb5rzzzosWsxE9e/YEoKCgoFH7a6+9tsHP2dnZAFx66aXRYhYgJycHgMLCwkYZXbt2BWDXrl2H/X8QQghxbMgIrRBCme7du3PXXXcxadIkVqxYQW5uLrfeemuLfre0tBSANm3aNNumS5cujR5zuVwABAKBRs917Nixwc+RJcCae7ypjMjqBiUlJc1ulxBCiGNLRmiFEEpdc801OJ1OqqurGTp0KHa7vUW/V1FRAUBCQkKzbY50TVqHw9Hk4y3dpvrbU1lZeUR/WwghxNEjBa0QQqkHH3yQQCBARkYGU6ZMIT8/v0W/16pVK+D4Kxwj23OoQlsIIcSxJQWtEEKZ+fPn89577zFy5EieeuopamtrueeeewiFQof93eTkZCB84dbxJLI9cmMFIYQ4fklBK4RQoqCggAkTJpCRkcFtt91GRkYGt956KytXrmTGjBmH/f3IxWCRi8OOF5HtSU9PP8ZbIoQQojlS0AohfjHTNPnzn/9MRUUFkyZNis5dHTlyJLm5uTz55JOsW7fukBlZWVm0adOGFStWNHlx1rGydOlSgBat1CCEEOLYkIJWCPGLvfrqqyxdupSbb76ZM844I/q4zWZj0qRJANx99914vd5mMwzDoF+/flRVVbFq1Srdm9wipmmydOlSPB4PF1988bHeHCGEEM0wzIPvUymEEMfI2rVrGTZsGBdccEGLpino9tlnnzF69Ghuvvlm7r///mO9OUIIIZohI7RCiONGbm4uV199NUuXLuXrr78+ptsSDAZ57LHHSEpKYsyYMcd0W4QQQhyaFLRCiOPKn//8Z9q3b8/48eMPOUVBt+eee47169czYcKE6AoMQgghjk9S0AohjitJSUk888wz7Nq1iwceeOCYbMPnn3/O008/zZgxYxg0aNAx2QYhhBAtJ3NohRBCCCFETJMRWiGEEEIIEdOkoBVCCCGEEDFNClohhBBCCBHTpKAVQgghhBAxTQpaIYQQQggR06SgFUIIIYQQMU0KWiGEEEIIEdOkoBVCCCGEEDFNClohhBBCCBHT/j90mTwj3QO4mwAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 800x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "system.m.sel('y').mpl()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Similarly, table can be viewed:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "tags": [
     "nbval-ignore-output"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>max_mxHxm</th>\n",
       "      <th>E</th>\n",
       "      <th>delta_E</th>\n",
       "      <th>bracket_count</th>\n",
       "      <th>line_min_count</th>\n",
       "      <th>conjugate_cycle_count</th>\n",
       "      <th>cycle_count</th>\n",
       "      <th>cycle_sub_count</th>\n",
       "      <th>energy_calc_count</th>\n",
       "      <th>E_exchange</th>\n",
       "      <th>...</th>\n",
       "      <th>B_hysteresis</th>\n",
       "      <th>Bx_hysteresis</th>\n",
       "      <th>By_hysteresis</th>\n",
       "      <th>Bz_hysteresis</th>\n",
       "      <th>iteration</th>\n",
       "      <th>stage_iteration</th>\n",
       "      <th>stage</th>\n",
       "      <th>mx</th>\n",
       "      <th>my</th>\n",
       "      <th>mz</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.081187</td>\n",
       "      <td>-5.296243e-16</td>\n",
       "      <td>-3.944305e-31</td>\n",
       "      <td>9.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>1.178506e-19</td>\n",
       "      <td>...</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1000.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-6.890111e-21</td>\n",
       "      <td>-4.478572e-20</td>\n",
       "      <td>-0.998400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.079349</td>\n",
       "      <td>-4.769135e-16</td>\n",
       "      <td>-7.888609e-31</td>\n",
       "      <td>16.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>1.301416e-19</td>\n",
       "      <td>...</td>\n",
       "      <td>900.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-900.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-4.375221e-19</td>\n",
       "      <td>-2.067033e-20</td>\n",
       "      <td>-0.998216</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.056383</td>\n",
       "      <td>-4.242133e-16</td>\n",
       "      <td>-9.860761e-32</td>\n",
       "      <td>23.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>1.445097e-19</td>\n",
       "      <td>...</td>\n",
       "      <td>800.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-800.0</td>\n",
       "      <td>47.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>-1.584726e-19</td>\n",
       "      <td>-5.167584e-20</td>\n",
       "      <td>-0.997999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.086409</td>\n",
       "      <td>-3.715256e-16</td>\n",
       "      <td>-1.972152e-31</td>\n",
       "      <td>31.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>64.0</td>\n",
       "      <td>1.614662e-19</td>\n",
       "      <td>...</td>\n",
       "      <td>700.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-700.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>-2.652693e-19</td>\n",
       "      <td>-3.100550e-20</td>\n",
       "      <td>-0.997739</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.053104</td>\n",
       "      <td>-3.188531e-16</td>\n",
       "      <td>-3.944305e-31</td>\n",
       "      <td>40.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>1.816966e-19</td>\n",
       "      <td>...</td>\n",
       "      <td>600.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-600.0</td>\n",
       "      <td>78.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>6.166650e-19</td>\n",
       "      <td>-3.100550e-20</td>\n",
       "      <td>-0.997422</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   max_mxHxm             E       delta_E  bracket_count  line_min_count  \\\n",
       "0   0.081187 -5.296243e-16 -3.944305e-31            9.0             9.0   \n",
       "1   0.079349 -4.769135e-16 -7.888609e-31           16.0            15.0   \n",
       "2   0.056383 -4.242133e-16 -9.860761e-32           23.0            22.0   \n",
       "3   0.086409 -3.715256e-16 -1.972152e-31           31.0            29.0   \n",
       "4   0.053104 -3.188531e-16 -3.944305e-31           40.0            36.0   \n",
       "\n",
       "   conjugate_cycle_count  cycle_count  cycle_sub_count  energy_calc_count  \\\n",
       "0                    1.0          8.0              7.0               19.0   \n",
       "1                    2.0         15.0              6.0               33.0   \n",
       "2                    3.0         22.0              6.0               48.0   \n",
       "3                    4.0         29.0              6.0               64.0   \n",
       "4                    5.0         37.0              7.0               81.0   \n",
       "\n",
       "     E_exchange  ...  B_hysteresis  Bx_hysteresis  By_hysteresis  \\\n",
       "0  1.178506e-19  ...        1000.0            0.0            0.0   \n",
       "1  1.301416e-19  ...         900.0            0.0            0.0   \n",
       "2  1.445097e-19  ...         800.0            0.0            0.0   \n",
       "3  1.614662e-19  ...         700.0            0.0            0.0   \n",
       "4  1.816966e-19  ...         600.0            0.0            0.0   \n",
       "\n",
       "   Bz_hysteresis  iteration  stage_iteration  stage            mx  \\\n",
       "0        -1000.0       18.0             18.0    0.0 -6.890111e-21   \n",
       "1         -900.0       32.0             13.0    1.0 -4.375221e-19   \n",
       "2         -800.0       47.0             14.0    2.0 -1.584726e-19   \n",
       "3         -700.0       62.0             14.0    3.0 -2.652693e-19   \n",
       "4         -600.0       78.0             15.0    4.0  6.166650e-19   \n",
       "\n",
       "             my        mz  \n",
       "0 -4.478572e-20 -0.998400  \n",
       "1 -2.067033e-20 -0.998216  \n",
       "2 -5.167584e-20 -0.997999  \n",
       "3 -3.100550e-20 -0.997739  \n",
       "4 -3.100550e-20 -0.997422  \n",
       "\n",
       "[5 rows x 26 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "system.table.data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "From the table, we can see at what external magnetic field the system was relaxed:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0     1000.0\n",
       "1      900.0\n",
       "2      800.0\n",
       "3      700.0\n",
       "4      600.0\n",
       "5      500.0\n",
       "6      400.0\n",
       "7      300.0\n",
       "8      200.0\n",
       "9      100.0\n",
       "10       0.0\n",
       "11     100.0\n",
       "12     200.0\n",
       "13     300.0\n",
       "14     400.0\n",
       "15     500.0\n",
       "16     600.0\n",
       "17     700.0\n",
       "18     800.0\n",
       "19     900.0\n",
       "20    1000.0\n",
       "21     900.0\n",
       "22     800.0\n",
       "23     700.0\n",
       "24     600.0\n",
       "25     500.0\n",
       "26     400.0\n",
       "27     300.0\n",
       "28     200.0\n",
       "29     100.0\n",
       "30       0.0\n",
       "31     100.0\n",
       "32     200.0\n",
       "33     300.0\n",
       "34     400.0\n",
       "35     500.0\n",
       "36     600.0\n",
       "37     700.0\n",
       "38     800.0\n",
       "39     900.0\n",
       "40    1000.0\n",
       "Name: B_hysteresis, dtype: float64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "system.table.data['B_hysteresis']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The units of $B$ are:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'mT'"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "system.table.units['B_hysteresis']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plotting hysteresis loop"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Using `Table` object, we can plot different values as a function of external magnetic field. For that, as usual, we use `mpl` method. We have to specify to that method what do we want to have on the $y$-axis."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "system.table.mpl(y=['mz'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This does not look like a hysteresis loop as we expected. The reason is that on the horizontal axis we have the magnitude `B` by default, which is always positive. We can change that by passing `Bz` for `x`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "system.table.mpl(x='Bz_hysteresis', y=['mz'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`Table.mpl` is based on `matplotlib.pyplot.plot`, so any keyword argument accepted by it can be passed:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "system.table.mpl(x='Bz_hysteresis', y=['mz'], marker='o', linewidth=2, linestyle='dashed')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## `micromagneticdata` analysis\n",
    "\n",
    "We can also analyse magnetisation fields at different values of external magnetic field as well as building interactive plots using `micromagneticdata` package."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import micromagneticdata as md"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can create a data object by passing system's name."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "data = md.Data(name=system.name)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, we can have a look at all drives we did so far:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "tags": [
     "nbval-ignore-output"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>drive_number</th>\n",
       "      <th>date</th>\n",
       "      <th>time</th>\n",
       "      <th>driver</th>\n",
       "      <th>Hmin</th>\n",
       "      <th>Hmax</th>\n",
       "      <th>n</th>\n",
       "      <th>n_threads</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>2022-10-20</td>\n",
       "      <td>15:13:27</td>\n",
       "      <td>HysteresisDriver</td>\n",
       "      <td>[0, 0, -795774.7154594767]</td>\n",
       "      <td>[0, 0, 795774.7154594767]</td>\n",
       "      <td>21</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>2022-10-20</td>\n",
       "      <td>15:27:16</td>\n",
       "      <td>HysteresisDriver</td>\n",
       "      <td>[0, 0, -795774.7154594767]</td>\n",
       "      <td>[0, 0, 795774.7154594767]</td>\n",
       "      <td>21</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>2023-10-23</td>\n",
       "      <td>16:08:27</td>\n",
       "      <td>HysteresisDriver</td>\n",
       "      <td>[0, 0, -795774.7154594767]</td>\n",
       "      <td>[0, 0, 795774.7154594767]</td>\n",
       "      <td>21</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   drive_number        date      time            driver  \\\n",
       "0             0  2022-10-20  15:13:27  HysteresisDriver   \n",
       "1             1  2022-10-20  15:27:16  HysteresisDriver   \n",
       "2             2  2023-10-23  16:08:27  HysteresisDriver   \n",
       "\n",
       "                         Hmin                       Hmax   n  n_threads  \n",
       "0  [0, 0, -795774.7154594767]  [0, 0, 795774.7154594767]  21        NaN  \n",
       "1  [0, 0, -795774.7154594767]  [0, 0, 795774.7154594767]  21        NaN  \n",
       "2  [0, 0, -795774.7154594767]  [0, 0, 795774.7154594767]  21        NaN  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.info"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There is only one drive with index `0`. We can get if by indexing the data object:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "drive = data[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The number of steps saved is:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "41"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "drive.n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can get an individual step by passing a value between 0 and 40 as an index:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "drive[0].sel('x').mpl()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can also interactively plot all individual steps by using `drive.hv`. For more details on creating interactive plots, please refer to other tutorials."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": [
     "nbval-ignore-output"
    ]
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "(function(root) {\n",
       "  function now() {\n",
       "    return new Date();\n",
       "  }\n",
       "\n",
       "  var force = true;\n",
       "  var py_version = '3.2.2'.replace('rc', '-rc.').replace('.dev', '-dev.');\n",
       "  var is_dev = py_version.indexOf(\"+\") !== -1 || py_version.indexOf(\"-\") !== -1;\n",
       "  var reloading = false;\n",
       "  var Bokeh = root.Bokeh;\n",
       "  var bokeh_loaded = Bokeh != null && (Bokeh.version === py_version || (Bokeh.versions !== undefined && Bokeh.versions.has(py_version)));\n",
       "\n",
       "  if (typeof (root._bokeh_timeout) === \"undefined\" || force) {\n",
       "    root._bokeh_timeout = Date.now() + 5000;\n",
       "    root._bokeh_failed_load = false;\n",
       "  }\n",
       "\n",
       "  function run_callbacks() {\n",
       "    try {\n",
       "      root._bokeh_onload_callbacks.forEach(function(callback) {\n",
       "        if (callback != null)\n",
       "          callback();\n",
       "      });\n",
       "    } finally {\n",
       "      delete root._bokeh_onload_callbacks;\n",
       "    }\n",
       "    console.debug(\"Bokeh: all callbacks have finished\");\n",
       "  }\n",
       "\n",
       "  function load_libs(css_urls, js_urls, js_modules, js_exports, callback) {\n",
       "    if (css_urls == null) css_urls = [];\n",
       "    if (js_urls == null) js_urls = [];\n",
       "    if (js_modules == null) js_modules = [];\n",
       "    if (js_exports == null) js_exports = {};\n",
       "\n",
       "    root._bokeh_onload_callbacks.push(callback);\n",
       "\n",
       "    if (root._bokeh_is_loading > 0) {\n",
       "      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "      return null;\n",
       "    }\n",
       "    if (js_urls.length === 0 && js_modules.length === 0 && Object.keys(js_exports).length === 0) {\n",
       "      run_callbacks();\n",
       "      return null;\n",
       "    }\n",
       "    if (!reloading) {\n",
       "      console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "    }\n",
       "\n",
       "    function on_load() {\n",
       "      root._bokeh_is_loading--;\n",
       "      if (root._bokeh_is_loading === 0) {\n",
       "        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n",
       "        run_callbacks()\n",
       "      }\n",
       "    }\n",
       "    window._bokeh_on_load = on_load\n",
       "\n",
       "    function on_error() {\n",
       "      console.error(\"failed to load \" + url);\n",
       "    }\n",
       "\n",
       "    var skip = [];\n",
       "    if (window.requirejs) {\n",
       "      window.requirejs.config({'packages': {}, 'paths': {'jspanel': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/jspanel', 'jspanel-modal': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/modal/jspanel.modal', 'jspanel-tooltip': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/tooltip/jspanel.tooltip', 'jspanel-hint': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/hint/jspanel.hint', 'jspanel-layout': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/layout/jspanel.layout', 'jspanel-contextmenu': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/contextmenu/jspanel.contextmenu', 'jspanel-dock': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/dock/jspanel.dock', 'gridstack': 'https://cdn.jsdelivr.net/npm/gridstack@7.2.3/dist/gridstack-all', 'notyf': 'https://cdn.jsdelivr.net/npm/notyf@3/notyf.min'}, 'shim': {'jspanel': {'exports': 'jsPanel'}, 'gridstack': {'exports': 'GridStack'}}});\n",
       "      require([\"jspanel\"], function(jsPanel) {\n",
       "\twindow.jsPanel = jsPanel\n",
       "\ton_load()\n",
       "      })\n",
       "      require([\"jspanel-modal\"], function() {\n",
       "\ton_load()\n",
       "      })\n",
       "      require([\"jspanel-tooltip\"], function() {\n",
       "\ton_load()\n",
       "      })\n",
       "      require([\"jspanel-hint\"], function() {\n",
       "\ton_load()\n",
       "      })\n",
       "      require([\"jspanel-layout\"], function() {\n",
       "\ton_load()\n",
       "      })\n",
       "      require([\"jspanel-contextmenu\"], function() {\n",
       "\ton_load()\n",
       "      })\n",
       "      require([\"jspanel-dock\"], function() {\n",
       "\ton_load()\n",
       "      })\n",
       "      require([\"gridstack\"], function(GridStack) {\n",
       "\twindow.GridStack = GridStack\n",
       "\ton_load()\n",
       "      })\n",
       "      require([\"notyf\"], function() {\n",
       "\ton_load()\n",
       "      })\n",
       "      root._bokeh_is_loading = css_urls.length + 9;\n",
       "    } else {\n",
       "      root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length + Object.keys(js_exports).length;\n",
       "    }\n",
       "\n",
       "    var existing_stylesheets = []\n",
       "    var links = document.getElementsByTagName('link')\n",
       "    for (var i = 0; i < links.length; i++) {\n",
       "      var link = links[i]\n",
       "      if (link.href != null) {\n",
       "\texisting_stylesheets.push(link.href)\n",
       "      }\n",
       "    }\n",
       "    for (var i = 0; i < css_urls.length; i++) {\n",
       "      var url = css_urls[i];\n",
       "      if (existing_stylesheets.indexOf(url) !== -1) {\n",
       "\ton_load()\n",
       "\tcontinue;\n",
       "      }\n",
       "      const element = document.createElement(\"link\");\n",
       "      element.onload = on_load;\n",
       "      element.onerror = on_error;\n",
       "      element.rel = \"stylesheet\";\n",
       "      element.type = \"text/css\";\n",
       "      element.href = url;\n",
       "      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n",
       "      document.body.appendChild(element);\n",
       "    }    if (((window['jsPanel'] !== undefined) && (!(window['jsPanel'] instanceof HTMLElement))) || window.requirejs) {\n",
       "      var urls = ['https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/jspanel.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/modal/jspanel.modal.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/tooltip/jspanel.tooltip.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/hint/jspanel.hint.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/layout/jspanel.layout.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/contextmenu/jspanel.contextmenu.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/dock/jspanel.dock.js'];\n",
       "      for (var i = 0; i < urls.length; i++) {\n",
       "        skip.push(urls[i])\n",
       "      }\n",
       "    }    if (((window['GridStack'] !== undefined) && (!(window['GridStack'] instanceof HTMLElement))) || window.requirejs) {\n",
       "      var urls = ['https://cdn.holoviz.org/panel/1.2.3/dist/bundled/gridstack/gridstack@7.2.3/dist/gridstack-all.js'];\n",
       "      for (var i = 0; i < urls.length; i++) {\n",
       "        skip.push(urls[i])\n",
       "      }\n",
       "    }    if (((window['Notyf'] !== undefined) && (!(window['Notyf'] instanceof HTMLElement))) || window.requirejs) {\n",
       "      var urls = ['https://cdn.holoviz.org/panel/1.2.3/dist/bundled/notificationarea/notyf@3/notyf.min.js'];\n",
       "      for (var i = 0; i < urls.length; i++) {\n",
       "        skip.push(urls[i])\n",
       "      }\n",
       "    }    var existing_scripts = []\n",
       "    var scripts = document.getElementsByTagName('script')\n",
       "    for (var i = 0; i < scripts.length; i++) {\n",
       "      var script = scripts[i]\n",
       "      if (script.src != null) {\n",
       "\texisting_scripts.push(script.src)\n",
       "      }\n",
       "    }\n",
       "    for (var i = 0; i < js_urls.length; i++) {\n",
       "      var url = js_urls[i];\n",
       "      if (skip.indexOf(url) !== -1 || existing_scripts.indexOf(url) !== -1) {\n",
       "\tif (!window.requirejs) {\n",
       "\t  on_load();\n",
       "\t}\n",
       "\tcontinue;\n",
       "      }\n",
       "      var element = document.createElement('script');\n",
       "      element.onload = on_load;\n",
       "      element.onerror = on_error;\n",
       "      element.async = false;\n",
       "      element.src = url;\n",
       "      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "      document.head.appendChild(element);\n",
       "    }\n",
       "    for (var i = 0; i < js_modules.length; i++) {\n",
       "      var url = js_modules[i];\n",
       "      if (skip.indexOf(url) !== -1 || existing_scripts.indexOf(url) !== -1) {\n",
       "\tif (!window.requirejs) {\n",
       "\t  on_load();\n",
       "\t}\n",
       "\tcontinue;\n",
       "      }\n",
       "      var element = document.createElement('script');\n",
       "      element.onload = on_load;\n",
       "      element.onerror = on_error;\n",
       "      element.async = false;\n",
       "      element.src = url;\n",
       "      element.type = \"module\";\n",
       "      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "      document.head.appendChild(element);\n",
       "    }\n",
       "    for (const name in js_exports) {\n",
       "      var url = js_exports[name];\n",
       "      if (skip.indexOf(url) >= 0 || root[name] != null) {\n",
       "\tif (!window.requirejs) {\n",
       "\t  on_load();\n",
       "\t}\n",
       "\tcontinue;\n",
       "      }\n",
       "      var element = document.createElement('script');\n",
       "      element.onerror = on_error;\n",
       "      element.async = false;\n",
       "      element.type = \"module\";\n",
       "      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "      element.textContent = `\n",
       "      import ${name} from \"${url}\"\n",
       "      window.${name} = ${name}\n",
       "      window._bokeh_on_load()\n",
       "      `\n",
       "      document.head.appendChild(element);\n",
       "    }\n",
       "    if (!js_urls.length && !js_modules.length) {\n",
       "      on_load()\n",
       "    }\n",
       "  };\n",
       "\n",
       "  function inject_raw_css(css) {\n",
       "    const element = document.createElement(\"style\");\n",
       "    element.appendChild(document.createTextNode(css));\n",
       "    document.body.appendChild(element);\n",
       "  }\n",
       "\n",
       "  var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-3.2.2.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-3.2.2.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-3.2.2.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-3.2.2.min.js\", \"https://cdn.holoviz.org/panel/1.2.3/dist/panel.min.js\"];\n",
       "  var js_modules = [];\n",
       "  var js_exports = {};\n",
       "  var css_urls = [];\n",
       "  var inline_js = [    function(Bokeh) {\n",
       "      Bokeh.set_log_level(\"info\");\n",
       "    },\n",
       "function(Bokeh) {} // ensure no trailing comma for IE\n",
       "  ];\n",
       "\n",
       "  function run_inline_js() {\n",
       "    if ((root.Bokeh !== undefined) || (force === true)) {\n",
       "      for (var i = 0; i < inline_js.length; i++) {\n",
       "        inline_js[i].call(root, root.Bokeh);\n",
       "      }\n",
       "      // Cache old bokeh versions\n",
       "      if (Bokeh != undefined && !reloading) {\n",
       "\tvar NewBokeh = root.Bokeh;\n",
       "\tif (Bokeh.versions === undefined) {\n",
       "\t  Bokeh.versions = new Map();\n",
       "\t}\n",
       "\tif (NewBokeh.version !== Bokeh.version) {\n",
       "\t  Bokeh.versions.set(NewBokeh.version, NewBokeh)\n",
       "\t}\n",
       "\troot.Bokeh = Bokeh;\n",
       "      }} else if (Date.now() < root._bokeh_timeout) {\n",
       "      setTimeout(run_inline_js, 100);\n",
       "    } else if (!root._bokeh_failed_load) {\n",
       "      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
       "      root._bokeh_failed_load = true;\n",
       "    }\n",
       "    root._bokeh_is_initializing = false\n",
       "  }\n",
       "\n",
       "  function load_or_wait() {\n",
       "    // Implement a backoff loop that tries to ensure we do not load multiple\n",
       "    // versions of Bokeh and its dependencies at the same time.\n",
       "    // In recent versions we use the root._bokeh_is_initializing flag\n",
       "    // to determine whether there is an ongoing attempt to initialize\n",
       "    // bokeh, however for backward compatibility we also try to ensure\n",
       "    // that we do not start loading a newer (Panel>=1.0 and Bokeh>3) version\n",
       "    // before older versions are fully initialized.\n",
       "    if (root._bokeh_is_initializing && Date.now() > root._bokeh_timeout) {\n",
       "      root._bokeh_is_initializing = false;\n",
       "      root._bokeh_onload_callbacks = undefined;\n",
       "      console.log(\"Bokeh: BokehJS was loaded multiple times but one version failed to initialize.\");\n",
       "      load_or_wait();\n",
       "    } else if (root._bokeh_is_initializing || (typeof root._bokeh_is_initializing === \"undefined\" && root._bokeh_onload_callbacks !== undefined)) {\n",
       "      setTimeout(load_or_wait, 100);\n",
       "    } else {\n",
       "      Bokeh = root.Bokeh;\n",
       "      bokeh_loaded = Bokeh != null && (Bokeh.version === py_version || (Bokeh.versions !== undefined && Bokeh.versions.has(py_version)));\n",
       "      root._bokeh_is_initializing = true\n",
       "      root._bokeh_onload_callbacks = []\n",
       "      if (!reloading && (!bokeh_loaded || is_dev)) {\n",
       "\troot.Bokeh = undefined;\n",
       "      }\n",
       "      load_libs(css_urls, js_urls, js_modules, js_exports, function() {\n",
       "\tconsole.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "\trun_inline_js();\n",
       "      });\n",
       "    }\n",
       "  }\n",
       "  // Give older versions of the autoload script a head-start to ensure\n",
       "  // they initialize before we start loading newer version.\n",
       "  setTimeout(load_or_wait, 100)\n",
       "}(window));"
      ],
      "application/vnd.holoviews_load.v0+json": "(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  var force = true;\n  var py_version = '3.2.2'.replace('rc', '-rc.').replace('.dev', '-dev.');\n  var is_dev = py_version.indexOf(\"+\") !== -1 || py_version.indexOf(\"-\") !== -1;\n  var reloading = false;\n  var Bokeh = root.Bokeh;\n  var bokeh_loaded = Bokeh != null && (Bokeh.version === py_version || (Bokeh.versions !== undefined && Bokeh.versions.has(py_version)));\n\n  if (typeof (root._bokeh_timeout) === \"undefined\" || force) {\n    root._bokeh_timeout = Date.now() + 5000;\n    root._bokeh_failed_load = false;\n  }\n\n  function run_callbacks() {\n    try {\n      root._bokeh_onload_callbacks.forEach(function(callback) {\n        if (callback != null)\n          callback();\n      });\n    } finally {\n      delete root._bokeh_onload_callbacks;\n    }\n    console.debug(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(css_urls, js_urls, js_modules, js_exports, callback) {\n    if (css_urls == null) css_urls = [];\n    if (js_urls == null) js_urls = [];\n    if (js_modules == null) js_modules = [];\n    if (js_exports == null) js_exports = {};\n\n    root._bokeh_onload_callbacks.push(callback);\n\n    if (root._bokeh_is_loading > 0) {\n      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    }\n    if (js_urls.length === 0 && js_modules.length === 0 && Object.keys(js_exports).length === 0) {\n      run_callbacks();\n      return null;\n    }\n    if (!reloading) {\n      console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n    }\n\n    function on_load() {\n      root._bokeh_is_loading--;\n      if (root._bokeh_is_loading === 0) {\n        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n        run_callbacks()\n      }\n    }\n    window._bokeh_on_load = on_load\n\n    function on_error() {\n      console.error(\"failed to load \" + url);\n    }\n\n    var skip = [];\n    if (window.requirejs) {\n      window.requirejs.config({'packages': {}, 'paths': {'jspanel': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/jspanel', 'jspanel-modal': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/modal/jspanel.modal', 'jspanel-tooltip': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/tooltip/jspanel.tooltip', 'jspanel-hint': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/hint/jspanel.hint', 'jspanel-layout': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/layout/jspanel.layout', 'jspanel-contextmenu': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/contextmenu/jspanel.contextmenu', 'jspanel-dock': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/dock/jspanel.dock', 'gridstack': 'https://cdn.jsdelivr.net/npm/gridstack@7.2.3/dist/gridstack-all', 'notyf': 'https://cdn.jsdelivr.net/npm/notyf@3/notyf.min'}, 'shim': {'jspanel': {'exports': 'jsPanel'}, 'gridstack': {'exports': 'GridStack'}}});\n      require([\"jspanel\"], function(jsPanel) {\n\twindow.jsPanel = jsPanel\n\ton_load()\n      })\n      require([\"jspanel-modal\"], function() {\n\ton_load()\n      })\n      require([\"jspanel-tooltip\"], function() {\n\ton_load()\n      })\n      require([\"jspanel-hint\"], function() {\n\ton_load()\n      })\n      require([\"jspanel-layout\"], function() {\n\ton_load()\n      })\n      require([\"jspanel-contextmenu\"], function() {\n\ton_load()\n      })\n      require([\"jspanel-dock\"], function() {\n\ton_load()\n      })\n      require([\"gridstack\"], function(GridStack) {\n\twindow.GridStack = GridStack\n\ton_load()\n      })\n      require([\"notyf\"], function() {\n\ton_load()\n      })\n      root._bokeh_is_loading = css_urls.length + 9;\n    } else {\n      root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length + Object.keys(js_exports).length;\n    }\n\n    var existing_stylesheets = []\n    var links = document.getElementsByTagName('link')\n    for (var i = 0; i < links.length; i++) {\n      var link = links[i]\n      if (link.href != null) {\n\texisting_stylesheets.push(link.href)\n      }\n    }\n    for (var i = 0; i < css_urls.length; i++) {\n      var url = css_urls[i];\n      if (existing_stylesheets.indexOf(url) !== -1) {\n\ton_load()\n\tcontinue;\n      }\n      const element = document.createElement(\"link\");\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.rel = \"stylesheet\";\n      element.type = \"text/css\";\n      element.href = url;\n      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n      document.body.appendChild(element);\n    }    if (((window['jsPanel'] !== undefined) && (!(window['jsPanel'] instanceof HTMLElement))) || window.requirejs) {\n      var urls = ['https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/jspanel.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/modal/jspanel.modal.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/tooltip/jspanel.tooltip.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/hint/jspanel.hint.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/layout/jspanel.layout.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/contextmenu/jspanel.contextmenu.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/dock/jspanel.dock.js'];\n      for (var i = 0; i < urls.length; i++) {\n        skip.push(urls[i])\n      }\n    }    if (((window['GridStack'] !== undefined) && (!(window['GridStack'] instanceof HTMLElement))) || window.requirejs) {\n      var urls = ['https://cdn.holoviz.org/panel/1.2.3/dist/bundled/gridstack/gridstack@7.2.3/dist/gridstack-all.js'];\n      for (var i = 0; i < urls.length; i++) {\n        skip.push(urls[i])\n      }\n    }    if (((window['Notyf'] !== undefined) && (!(window['Notyf'] instanceof HTMLElement))) || window.requirejs) {\n      var urls = ['https://cdn.holoviz.org/panel/1.2.3/dist/bundled/notificationarea/notyf@3/notyf.min.js'];\n      for (var i = 0; i < urls.length; i++) {\n        skip.push(urls[i])\n      }\n    }    var existing_scripts = []\n    var scripts = document.getElementsByTagName('script')\n    for (var i = 0; i < scripts.length; i++) {\n      var script = scripts[i]\n      if (script.src != null) {\n\texisting_scripts.push(script.src)\n      }\n    }\n    for (var i = 0; i < js_urls.length; i++) {\n      var url = js_urls[i];\n      if (skip.indexOf(url) !== -1 || existing_scripts.indexOf(url) !== -1) {\n\tif (!window.requirejs) {\n\t  on_load();\n\t}\n\tcontinue;\n      }\n      var element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n    for (var i = 0; i < js_modules.length; i++) {\n      var url = js_modules[i];\n      if (skip.indexOf(url) !== -1 || existing_scripts.indexOf(url) !== -1) {\n\tif (!window.requirejs) {\n\t  on_load();\n\t}\n\tcontinue;\n      }\n      var element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      element.type = \"module\";\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n    for (const name in js_exports) {\n      var url = js_exports[name];\n      if (skip.indexOf(url) >= 0 || root[name] != null) {\n\tif (!window.requirejs) {\n\t  on_load();\n\t}\n\tcontinue;\n      }\n      var element = document.createElement('script');\n      element.onerror = on_error;\n      element.async = false;\n      element.type = \"module\";\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      element.textContent = `\n      import ${name} from \"${url}\"\n      window.${name} = ${name}\n      window._bokeh_on_load()\n      `\n      document.head.appendChild(element);\n    }\n    if (!js_urls.length && !js_modules.length) {\n      on_load()\n    }\n  };\n\n  function inject_raw_css(css) {\n    const element = document.createElement(\"style\");\n    element.appendChild(document.createTextNode(css));\n    document.body.appendChild(element);\n  }\n\n  var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-3.2.2.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-3.2.2.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-3.2.2.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-3.2.2.min.js\", \"https://cdn.holoviz.org/panel/1.2.3/dist/panel.min.js\"];\n  var js_modules = [];\n  var js_exports = {};\n  var css_urls = [];\n  var inline_js = [    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\nfunction(Bokeh) {} // ensure no trailing comma for IE\n  ];\n\n  function run_inline_js() {\n    if ((root.Bokeh !== undefined) || (force === true)) {\n      for (var i = 0; i < inline_js.length; i++) {\n        inline_js[i].call(root, root.Bokeh);\n      }\n      // Cache old bokeh versions\n      if (Bokeh != undefined && !reloading) {\n\tvar NewBokeh = root.Bokeh;\n\tif (Bokeh.versions === undefined) {\n\t  Bokeh.versions = new Map();\n\t}\n\tif (NewBokeh.version !== Bokeh.version) {\n\t  Bokeh.versions.set(NewBokeh.version, NewBokeh)\n\t}\n\troot.Bokeh = Bokeh;\n      }} else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(run_inline_js, 100);\n    } else if (!root._bokeh_failed_load) {\n      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n      root._bokeh_failed_load = true;\n    }\n    root._bokeh_is_initializing = false\n  }\n\n  function load_or_wait() {\n    // Implement a backoff loop that tries to ensure we do not load multiple\n    // versions of Bokeh and its dependencies at the same time.\n    // In recent versions we use the root._bokeh_is_initializing flag\n    // to determine whether there is an ongoing attempt to initialize\n    // bokeh, however for backward compatibility we also try to ensure\n    // that we do not start loading a newer (Panel>=1.0 and Bokeh>3) version\n    // before older versions are fully initialized.\n    if (root._bokeh_is_initializing && Date.now() > root._bokeh_timeout) {\n      root._bokeh_is_initializing = false;\n      root._bokeh_onload_callbacks = undefined;\n      console.log(\"Bokeh: BokehJS was loaded multiple times but one version failed to initialize.\");\n      load_or_wait();\n    } else if (root._bokeh_is_initializing || (typeof root._bokeh_is_initializing === \"undefined\" && root._bokeh_onload_callbacks !== undefined)) {\n      setTimeout(load_or_wait, 100);\n    } else {\n      Bokeh = root.Bokeh;\n      bokeh_loaded = Bokeh != null && (Bokeh.version === py_version || (Bokeh.versions !== undefined && Bokeh.versions.has(py_version)));\n      root._bokeh_is_initializing = true\n      root._bokeh_onload_callbacks = []\n      if (!reloading && (!bokeh_loaded || is_dev)) {\n\troot.Bokeh = undefined;\n      }\n      load_libs(css_urls, js_urls, js_modules, js_exports, function() {\n\tconsole.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n\trun_inline_js();\n      });\n    }\n  }\n  // Give older versions of the autoload script a head-start to ensure\n  // they initialize before we start loading newer version.\n  setTimeout(load_or_wait, 100)\n}(window));"
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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       "  var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n",
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       "    var nchildren = toinsert.length;\n",
       "    var html_node = toinsert[nchildren-1].children[0];\n",
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       "    var nodelist = html_node.querySelectorAll(\"script\");\n",
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       "  var render_items = [{\"docid\":\"7046f3c7-8c91-4acb-bee6-0762f0e075e1\",\"roots\":{\"p1002\":\"a7bc5f03-195e-421f-9c7d-be3ff566b647\"},\"root_ids\":[\"p1002\"]}];\n",
       "  var docs = Object.values(docs_json)\n",
       "  if (!docs) {\n",
       "    return\n",
       "  }\n",
       "  const py_version = docs[0].version.replace('rc', '-rc.').replace('.dev', '-dev.')\n",
       "  const is_dev = py_version.indexOf(\"+\") !== -1 || py_version.indexOf(\"-\") !== -1\n",
       "  function embed_document(root) {\n",
       "    var Bokeh = get_bokeh(root)\n",
       "    Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "    for (const render_item of render_items) {\n",
       "      for (const root_id of render_item.root_ids) {\n",
       "\tconst id_el = document.getElementById(root_id)\n",
       "\tif (id_el.children.length && (id_el.children[0].className === 'bk-root')) {\n",
       "\t  const root_el = id_el.children[0]\n",
       "\t  root_el.id = root_el.id + '-rendered'\n",
       "\t}\n",
       "      }\n",
       "    }\n",
       "  }\n",
       "  function get_bokeh(root) {\n",
       "    if (root.Bokeh === undefined) {\n",
       "      return null\n",
       "    } else if (root.Bokeh.version !== py_version && !is_dev) {\n",
       "      if (root.Bokeh.versions === undefined || !root.Bokeh.versions.has(py_version)) {\n",
       "\treturn null\n",
       "      }\n",
       "      return root.Bokeh.versions.get(py_version);\n",
       "    } else if (root.Bokeh.version === py_version) {\n",
       "      return root.Bokeh\n",
       "    }\n",
       "    return null\n",
       "  }\n",
       "  function is_loaded(root) {\n",
       "    var Bokeh = get_bokeh(root)\n",
       "    return (Bokeh != null && Bokeh.Panel !== undefined)\n",
       "  }\n",
       "  if (is_loaded(root)) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    var attempts = 0;\n",
       "    var timer = setInterval(function(root) {\n",
       "      if (is_loaded(root)) {\n",
       "        clearInterval(timer);\n",
       "        embed_document(root);\n",
       "      } else if (document.readyState == \"complete\") {\n",
       "        attempts++;\n",
       "        if (attempts > 200) {\n",
       "          clearInterval(timer);\n",
       "\t  var Bokeh = get_bokeh(root)\n",
       "\t  if (Bokeh == null || Bokeh.Panel == null) {\n",
       "            console.warn(\"Panel: ERROR: Unable to run Panel code because Bokeh or Panel library is missing\");\n",
       "\t  } else {\n",
       "\t    console.warn(\"Panel: WARNING: Attempting to render but not all required libraries could be resolved.\")\n",
       "\t    embed_document(root)\n",
       "\t  }\n",
       "        }\n",
       "      }\n",
       "    }, 25, root)\n",
       "  }\n",
       "})(window);</script>"
      ],
      "text/plain": [
       ":DynamicMap   [z,B_hysteresis]\n",
       "   :Overlay\n",
       "      .Image.I       :Image   [x,y]   (field)\n",
       "      .VectorField.I :VectorField   [x,y]   (angle,mag)"
      ]
     },
     "execution_count": 18,
     "metadata": {
      "application/vnd.holoviews_exec.v0+json": {
       "id": "p1002"
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "drive.hv(kdims=[\"x\", \"y\"])"
   ]
  }
 ],
 "metadata": {
  "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": "3.10.12"
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  "widgets": {
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 },
 "nbformat": 4,
 "nbformat_minor": 4
}