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    "In my work I often come across probabilistic models where there are strong correlations between parameters.\n",
    "This certainly isn't a special feature of the problems that I work on, and the general advice from MCMC practitioners is that we should reparameterize our models in some form that removes the covariances, but this isn't always practical.\n",
    "One of the reasons why [emcee](https://emcee.readthedocs.io) has been popular in astrophysics (I think) is that it uses an \"affine invariant\" algorithm.\n",
    "This means that when you use emcee, the performance will be (more-or-less) the same for any problems that are affine transformations of each other.\n",
    "In other words, it doesn't care about translations, rotations, or scalings of the parameters.\n",
    "\n",
    "Standard [HMC](https://en.wikipedia.org/wiki/Hamiltonian_Monte_Carlo) methods such as the [NUTS](https://arxiv.org/abs/1111.4246) algorithm implemented in state-of-the-art libraries like [PyMC3](https://docs.pymc.io/) and [Stan](http://mc-stan.org/) do not have this property.\n",
    "[Note: it is actually possible to construct an affine invariant NUTS sampler using some of the ideas from emcee, but there are some limitations and this will hopefully be the topic of a paper that I write someday...]\n",
    "The performance of this method is generally very sensitive to the \"metric\" or \"mass matrix\" that is used and changes in parameterization can make a huge difference in the efficiency of sampling using these packages.\n",
    "To deal with covariances, Stan has support for learning the off-diagonal elements of the mass matrix during burn-in.\n",
    "The basic idea is that (in the Gaussian case) the optimal mass matrix will be equal to the inverse covariance of the posterior.\n",
    "Therefore, you can estimate the sample covariance of burn-in chains and use that as the inverse mass matrix in subsequent samplings.\n",
    "While PyMC3 has the machinery to support this, out of the box it only supports learning of the *diagonal* elements of the mass matrix during the tuning phase (as far as I can tell - please correct me if I'm wrong!).\n",
    "\n",
    "In this blog post, I demonstrate how covariances can cause serious problems for PyMC3 on a simple (but not contrived) toy problem and then I show a way that you can use the existing features in PyMC3 to implement a tuning schedule similar to the one used by Stan and fit for the full dense mass matrix.\n",
    "I have found that this can have a *huge* effect (a few orders of magnitude in the example shown here) on the computational efficiency of PyMC3 on the types of problems that are common in astrophysics.\n",
    "\n",
    "## Sampling an isotropic Gaussian\n",
    "\n",
    "First, let's look at how fast PyMC3 can sample an isotropic 5-D Gaussian."
   ]
  },
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "PyMC3 version 3.11.5\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Auto-assigning NUTS sampler...\n",
      "Initializing NUTS using jitter+adapt_diag...\n",
      "Sequential sampling (2 chains in 1 job)\n",
      "NUTS: [x]\n"
     ]
    },
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       "      <progress value='6000' class='' max='6000' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
       "      100.00% [6000/6000 00:02<00:00 Sampling chain 0, 0 divergences]\n",
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       "        /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
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       "      <progress value='6000' class='' max='6000' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
       "      100.00% [6000/6000 00:02<00:00 Sampling chain 1, 0 divergences]\n",
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     "text": [
      "Sampling 2 chains for 3_000 tune and 3_000 draw iterations (6_000 + 6_000 draws total) took 5 seconds.\n"
     ]
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     "output_type": "stream",
     "text": [
      "time per effective sample: 1.34803 ms\n"
     ]
    }
   ],
   "source": [
    "import time\n",
    "import warnings\n",
    "import pymc3 as pm\n",
    "import arviz as az\n",
    "\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "\n",
    "print(\"PyMC3 version {0}\".format(pm.__version__))\n",
    "\n",
    "ndim = 5\n",
    "\n",
    "with pm.Model() as simple_model:\n",
    "    pm.Normal(\"x\", shape=(ndim,))\n",
    "\n",
    "strt = time.time()\n",
    "with simple_model:\n",
    "    simple_trace = pm.sample(\n",
    "        draws=3000, tune=3000, random_seed=42, chains=2, return_inferencedata=True\n",
    "    )\n",
    "\n",
    "    # About half the time is spent in tuning so correct for that\n",
    "    simple_time = 0.5 * (time.time() - strt)\n",
    "\n",
    "stats = az.summary(simple_trace)\n",
    "simple_time_per_eff = simple_time / stats.ess_bulk.values.min()\n",
    "print(\"time per effective sample: {0:.5f} ms\".format(simple_time_per_eff * 1000))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "On my laptop with two CPUs, I find that the computational cost per effective sample is a fraction of a millisecond.\n",
    "That's how things should be!\n",
    "\n",
    "## Sampling a covariant Gaussian\n",
    "\n",
    "Now let's try an example where the dimensions of our Gaussian are correlated and see how the default performance of PyMC3 compares.\n",
    "First, let's take a look at a [corner plot](https://corner.readthedocs.io) of the posterior that we're targeting."
   ]
  },
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     "shell.execute_reply": "2022-06-06T14:31:12.262203Z"
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   "outputs": [
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8eLVt21a33nqrPvzwQ+3bt0/Lly9XXFycXC6XnE6nwsPDlZCQIEny+XyyWCzKyclRbGys8vLyKn1/jEAsMzNTsbGx5VYz+Xy+YuuNAMu/Aqoqx6SM61XGYrEEtA71V1JSknr06FHX2wAAAABwDFjregM4doxJUFWp5vBvZCwVPyZVFcYkKKko3CksLFRsbKxatmypiIgIZWZm6qqrrirW8+acc86p0nOUdNVVV+ndd99V06ZNtXXrVl1yySXatm2b4uLiFB4erri4OHNvUlHA1axZM+Xl5cnpdFZaneRwOJSXlydJZjPjytaHhoaaVTfG1yXvAwAAAACgJCpwUCaj8kYqOppkhD4VHZOqiFF5k5+fr6ZNmyoiIkIRERHKycnRvn37NHHiRH3zzTfFjk1VVnkTiN69e+vTTz/VkCFDtHPnTvXu3VtvvfVWsXDI4/EoPDzcPF7l9XrNMeMVBSrG/Tabrdh7VNF6/zUlv+aYFAAAAACgPAQ4DVx1R1AblTehoaGKj483f15RE+OSjCBkz549+ve//609e/boyJEjkqScnBy5XC79/fff+v333/Xnn39WuedNoDp16qTPPvtM11xzjTZv3qyBAwdqyZIlGj58eLHKoOjoaElFYVNhYaFSU1OVmJhY4est2UuorPe7ot8BI8IBAAAAAIEgwGngqjuC+mibHGdmZmrAgAH66aefAlpfW+GNoXnz5vr00081YsQIrVmzRv/85z/1wQcf6MYbb1T79u3NZsZS0fSc1NRU2Wy2YhO1ytu3//ta1vtd0e+AEeEAAAAAgEAQ4DRw1Q1iyjvS43a7zSbE5fWJ8fl8GjNmjBneNGvWTHFxcYqLi5PT6VSzZs3kdDrNn8XFxen0009X69atq/4CqyAiIkJvvPGGpkyZoieffFIrVqzQm2++qUsuuUTjx4+XVPS6IyMjFRERob/++ktWq7VYBVJlynq/K/odMCIcAAAAABAIApwGrqZ7q3g8HmVnZ5vXNn5mt9vNCVTLli3TypUrFRoaqs8//1xnnHFGsWsEOkWpNlitVj366KMaOnSo7r33Xq1fv16rV6/WmjVrNGjQIN1xxx0aMGCAcnJy5HA4lJOTU+Z1jGlcJY8+lfV+V/Q7oPcNAAAAACAQTKFChTwej9LT082Gxna7XVFRUeaRo5JTqX799VfdddddkqT777+/VHgTLHr16qWPP/5YX375pS6++GL5fD793//9ny688EL169dPP/30kwoKCiTJfO3+jCBr165dVZ7IBQAAAABAVRHg/H91WRVSF4xgpqzwwf8+o0eLy+VSenq6JKldu3Zq166deewnMzNTknTgwAFdc8018ng8Ou+88zRhwoRj9nqq66yzztLbb7+tH3/8Uddee61CQkK0YcMGXXfddbr11lv17bff6vDhw6UeZ7fblZeXJ5vNVmbA46+i9/po1ea1AQAAAADBo9EGOGlpafr999/173//W16vVxaLRV6vt663dcz4N8+t6D6Hw2GO1/avtPFns9nkcrk0efJk/fzzz3I6nXrxxRdltdbsP6+9e/cqNTW1Rq9pOOWUU/Tyyy/r119/1a233iqbzaYtW7boxhtvVP/+/fXiiy9q//795vvlcDjUrl07RUVFSVKFIUpF7/XRqs1rAwAAAACCR6PsgbN69Wo9++yz2rp1q/Ly8jRo0CC99tprZlDR0BmVNZIUExNT6n6jsa5UFBBEREQoIiJCHo9HPp9PaWlpxSYsZWZmasuWLVq2bJkk6fnnn1d8fLx5BKmk8n5e0vbt282vP/vsM02bNk15eXn6xz/+oauuukpnn322rFarmjdvHtD1jB49FYmNjdXcuXM1efJkPfvss1q8eLFSUlJ00003qXPnzrr99tv1j3/8Q02aNFGLFi0UFxcnl8ulgoICHT58WF6v1+wJZLxHtdmomCbIAAAAANA4NLoKnKVLlyo5OVnt2rXTxIkTlZSUpDfffFPLly+v660dM263WzabrVQDXoPdbpfD4ZDL5VJ2drYZSDidTklSYWGhPB6PPB6PbDabjhw5onvuuUeSNHbsWA0cOLDG9urz+bR06VJNmjRJeXl5kqSNGzfqzjvv1OWXX65XXnlFBw8erLHnM7Rs2VIPPvigtm/frpkzZyoqKko///yzbr31Vt166636+eefzYobu92u/Px8eTweM8zxr8ax2+2Kj4+vcrPiQI65SarWtQEAAAAA9UujCnA+/PBDjR8/Xg8//LCeffZZTZ06VZ988okkmR+GDfW1J47b7a60J4pxLKqiqg0j5MnLyys1ZSkkJKRYhcmUKVPkcrnUtWtXPfjggzX2WvLz8zVz5kzNnz9fknTNNdforbfe0nXXXaeoqCj99ddfeuqpp9SrVy/dfffd+vnnn2vsuQ2xsbGaMmWK/vvf/+qWW25RSEiINm7cqCuvvFJTpkwxq5HsdrvCw8PNfRsB19EI9JgbAAAAAKDhaxQBjs/nk8/n06pVq3TmmWdq5MiRcjgcys/Pl91uV79+/RQXF6f58+frueeeU3p6uiwWS5WeIy8vT1lZWcVudSGQD/aBVIQ4HA5FRUWpXbt2pQIcSdq9e7c8Ho9efPFFbdiwQXa7XS+//LJsNluNvI709HSNHj1a//d//6eQkBBNnjxZkyZNUvv27TV+/HitXbtW06ZNU6dOnZSbm6sVK1Zo4MCBGjJkiN555x3l5+fXyD4MzZs311NPPaUffvhBF198sQoLC7Vs2TKdeOKJmjNnjiwWi0JDQ+V0Os0w52gDnIqCtkBCOAAAAABAw9Eomr5YLBbl5ORow4YNSkxMND/0hoeHa9WqVVq/fr127Nghl8slj8ejJ554QvPmzdPgwYPl8/kCCnNmz56t++67r7ZfSqVqqieKf4VNyebOGRkZysrK0tatWzVz5kxJ0tNPP61OnTod1XMa9u/frwsvvFA7duxQZGSkHnnkEZ155pnF1kREROiKK67Q5Zdfrl27dmnZsmVau3atvvvuO3333XdyOp267LLLNHToUHXu3LnKgVx5TjzxRK1atUpffPGF7rnnHv3www+aNm2aXnnlFX322Wfme2YcOzP49x2SVO7xNX/+v4OK7jOuHcg1AQAAAAD1U6OowJGKPvB36dJF//73v7VixQp9/vnnWrx4sa6++mo98MAD+uijj3TgwAE99thjys/P1x133FGlSpypU6fq0KFD5m337t21/IrK5nA4ar0nSkREhA4cOKBff/1VhYWFOuuss3T99dfXyLUPHTqkK664Qjt27FDr1q21bNmyUuGNP4vFol69emnBggXatGmTxo8fr+bNm8vlcmnJkiW66KKLNGDAAC1cuFB///13jexRks455xx98803evnll9W6dWtt27ZNgwcPVnZ2dpnr/cexV/XoU2WjwjlOBQAAAAANX6MJcCTp6quvVuvWrTVy5EiNGTNGkydP1ujRozVhwgR17NhR4eHhGjVqlG666Sb9+eefWrJkScDXttlsio6OLnZriDwej3JycpSYmKi0tDRJRVUpNVHhkpubq+HDh+s///mP4uPjtWDBAh133HEBP75FixYaN26cNm3apGXLluniiy+WzWbTtm3b9NBDD6lr16666qqrtHr16qM+3iRJVqtV1157rT777DPFx8frp59+0pVXXqnDhw+XamRsHHlyOp1VPvpUWUDDcSoAAAAAaPgaXYDz8ccfa926dVq5cqXCw8PVq1cvNWnSRFarVYWFhYqOjtadd94pq9Wq3Nzcut7yMVHZtCPjaJnxvdHc2Gj83Lp166PeQ2FhoUaNGqUvv/xSUVFRWrNmjRISEqp1rbCwMJ133nl67rnn9P3332vOnDk6/fTT5fV6tX79et1yyy3q3Lmz7rzzTm3evPmo996xY0e99957stvt+uyzz/T2228rNDS0VO+g+Ph481byeFVFFTaVBTTVnXIFAAAAAKg/Gk2A4/P5ZLVa1aJFCw0YMEAFBQU6dOiQORo7NzdXISEhKiws1Pbt29WmTRuddNJJ5mMbsvIqPDwej1JSUpSamiqXyyWpKCyIjIxUs2bNzPHdbdu2Parn9/l8mjRpkt5++22Fh4drxYoV6tq161Fd0xAbG6vrrrtOq1ev1rfffquJEycqMTFRhw8f1muvvabBgwfr4osv1scff3xUv+eePXtq1qxZkqQZM2aYk7qk0gFNye8rq7AhoAEAAAAANKgAx/8DuPG18d+SR3zi4uLUtGlTTZo0SYcOHVKTJk0kFfVgefHFF9WkSRP16dOnzMc2NOVVeLjdbhUWFionJ8f8md1ul9PplNPpNEOdo63AefTRR/X888/LYrHo+eefV9++fY/qeuU5/vjjNXnyZH333Xd69913NXz4cIWHh+vbb7/Vtddeq379+mn16tUqKCio1vVvv/12nXzyyXK5XJo6dapZueQf0Hg8Hu3atUtZWVlmYMMRKAAAAABAZRrUFKq0tDSz90j79u0VFhYmi8WiwsJChYSEFFvbqlUrDR06VPPnz1evXr00ffp0ZWRk6Ouvv9aHH36oDRs2qE2bNnX0So5OoIGTMV0qIiJCERERkkpXG4WGhqqgoEAHDhwwJx8ZwY3RFNh4n0pOqyrPn3/+aX795ptv6sEHH5QkTZkyRd27dzfvD3QUu9GLpzL+lULHHXec7rnnHv3rX//SK6+8opUrV+rnn3/WLbfcooceekijRo3S0KFDKxyL3qpVq1I/mzt3ri688EItXbpUV1xxhbp166bo6GhzKpXb7TaPoNntdvl8PvP9b+hBIQAAAACg+hpMBc4bb7yhyy+/XJ07d1aXLl00ePBgLVq0SJIUEhJSLJjwer0KCQnRE088oZtuukkZGRkaMWKEHnroIe3fv18bN25Ut27d6uiVBBcjpAgJCVFGRoZZUfL333+bPXCqG3R9+umnZngzatQoDR8+vGY2XQXNmzfXhAkT9NFHH2nMmDGKjY1Vamqqpk+frnPOOUeLFi0qd7JUWc455xxdddVV8nq9mj59urxer1wul3nzeDzKy8uT0+mU3W4v1WMIAAAAAICyNIgA56WXXtKIESN07rnnaubMmZoxY4a+/vprjR49WjfeeKN8Pl+x6gajYXF4eLiee+45bdq0SWvXrtWmTZu0Zs0adenSpQ5fTd0zQgWpqAKndevWCg8PV1xcnOx2uxwOhw4cOCCfz6ewsDCzj1BVfP/995o8ebK8Xq+GDBmisWPH1vTLqJKYmBjdeuutWrdunWbMmKFWrVopPT1djzzyiHr37q3nnnsu4B45s2fPVmRkpLZs2aJVq1YpOztbLpdL2dnZ8ng8io2NNdd6PJ5SE6sAAAAAACip3h+h+umnnzRz5kzNmTNHt99+u0JDi17SxRdfrHHjxmnZsmU6dOiQXn31VTVp0kSFhYXy+XwKDQ2V1+tVaGioOnbsqI4dO9bxK6kbHo/HPN7j33S3oKDAHHsdFxdX7DGJiYnasWOHpKL+N1Zr1XLA7du3684771R+fr7OPfdcTZs2LWiOD9ntdo0cOVLXXnut3n33XS1atEg7duzQY489pszMTE2ZMqXSvbZu3Vr33nuvpk6dqgcffFD9+/c3K26M99j/v0Z4k56eLofDQbNiAAAAAEAp9b4CZ+fOnXK73erdu7cZ3hQWFqpr165avHixrrzySq1Zs0Y33nijpKKjQMa69957T/v27auzvQeDsipA7HZ7qTHYJW3btk1S1Y9P5eTkaMyYMcrOzlb37t316KOPmr+P6vB6vTpw4IC2bdumjRs36p133tGSJUv0wQcfqLCwsNrXDQ8P19ChQ7Vu3TrNnDlTkvT8889rwYIFAT1+zJgxSkpK0oEDBzR9+nS1atVKiYmJZgNo/wDHqGCqaBIVAAAAAKBxq/cVOL/99psyMjLMXi1G5YjP51PHjh01Z84c5eTk6PXXX1enTp3MUc9Tp07VI488onnz5mnMmDFVriJpKIwKEP+wxr8SRypqbOxfpbNhwwZNmDBBktS/f/8qPd+GDRu0f/9+xcfH65lnnjGnfwXihx9+0Hfffae0tDSlp6crPT1dLper3KBm3bp1Gj9+vNq1a1elPfqzWq26/vrr5fV69cADD+iJJ55Q+/btNXjw4AofFxYWpqeffloXXXSR3nvvPQ0fPlyrV682X2/Jyifj91ByEpXRc4jKHAAAAABo3Op9anHWWWdJkubMmSNJ5tEoi8Uin8+nDh06aM6cOWrTpo1eeukl/frrr/J6vTr77LM1YMAAXXjhhY02vJH+VwHiH9oYDXeNyhz/Kp2DBw9q6NChysvL06WXXqpp06ZV6fk+/vhjSVLfvn0VHR0d8OM+/fRTTZw4UW+88YbWr1+v//73v9q/f78KCwtltVoVFxenk046Sb1799bgwYPlcDi0fft2jR07Vq+//vpRVeNI0g033KAbbrhBkjRx4kRt3bq10sf07t1bb7zxhpo0aaJ169bp4osvNhsil6x8stvtio+PN4Oc9PT0UiPIAQAAAACNV72vwOnUqZO6dOmipUuXqmfPnho5cqSsVqvZuNjn86lLly568skndfXVV+uXX37RSSedpMGDB+v88883x2c3RkY4YzDCg4KCAklSfn6+8vPzFRERYR6pevTRR3Xw4EGdfPLJevXVV6t8/Omjjz6SVBRuBGrLli1mQNe7d2+dcsopat68ueLj49W8eXPZ7fZSY+KvueYaPfPMM9q8ebNeeuklff3115ozZ446depUpf36u+eee7Rz506tX79eo0aN0saNG5WYmFjhYwYNGqT/+7//02WXXab169frggsu0Pvvv19m5ZPBP7RxOBzmfwEAAAAAjVe9Lz1p3ry5Fi1aJKvVqkceeUSrV6+WJFksFnm9XnNd9+7d1aRJE23fvl1S0dGYxhzeSP+rAvGvtjH63xhVOYWFhcrIyJDdbpfX6zV7wNxzzz1Vfv927NihP/74Q6GhoTrjjDMCfsyMGTNUUFCgvn376r777tNVV12lc889V507d1Z8fHyp8EaSnE6nZs2apUmTJikyMlK//fabrr76ai1cuFBHjhyp0r4NISEhmjdvnk488US5XC4NHTo0oBHj5557rj755BM1a9ZMmzdvVp8+fbRv3z4zxDFCNKPyRiqqJDOOTRmVOQAAAACAxqveBzhS0TGqBQsWaNeuXZo5c6Zef/11SSp2NMrtdqt169Y66aST6mqbQcc/rDEqbPyPVNntduXl5Sk8PFwej0cvvPCCDhw4oI4dO2rYsGFVfj6j+qZ79+4BVZTs379fU6ZMkdvt1qmnnqp77rmnSsfdLBaL+vfvr0WLFunMM89UQUGB5s+fr2uvvVa//vprlfcvSZGRkXrhhRfkdDr1n//8R9dff31Ax7NOP/10ff7552rVqpW2bdum8847T59++qn2799vjmxPS0vT/v375Xa7yw1t/I9XAQAAAAAaj3p/hMpw7bXXKi8vT3feeafGjRun33//3RxPfeDAAS1YsEBWq1Wnn376Md2Xz+eTz+ercE1Nj9Cu7PkMDoejwiDF4XCoXbt2yszMlMvl0qOPPipJGjdunAoLC0sFF7m5uRU+37p16yQVhRmHDx+ucG1WVpbGjBmjjIwMOZ1O9evXT5999lmZa2NjYyu8liRdeuml6tmzp5YtW6Zff/1V11xzjS6//HJdccUVpY6BVXYsKiQkRHPmzNGYMWO0du1a3XnnnWZz7LIYU6ZOOOEEffbZZ7r44ou1Y8cODRs2TGPHjtUVV1yhgoIC5efnm/8W/KvH/B0+fFiFhYVyu91U5QAAAABAI9IgKnCkoiMno0aNMo9QzZgxQ927d9fAgQM1ZMgQvfXWW1q5cmWVx143dna7Xc2aNdOqVauUlpam1q1b69prr63ydXJzc/XVV19Jks4888wK1+bl5Wny5MnKyMhQZGSkhg0bVqVpVWWxWCzq3bu3Hn/8cfXq1UuFhYV66623dM899+jPP/+s8vVOPvlkzZ07V5K0ZMkSvfLKKwE9rn379vrqq6902WWX6ciRI5o7d66mT5+uv//+WxEREYqPj5fT6SzWTNrlchVrdmwcrwIAAAAANB4NJsAxDBw4UJs2bdKDDz6o5s2bKy8vT926ddPXX3+tbt261fX2gl5ZR3QKCgq0bNkySUXVNzabrcrX/eabb5STk6OWLVuqQ4cO5a7zer26//77tXXrVoWHh+uqq66q0rSqysTGxmrcuHG68847FRUVpdTUVE2bNk2rVq0ymzcH6pJLLtHEiRMlSdOnT9cXX3wR8B5WrFihJ554QmFhYdqwYYOGDx+uXbt2mX1xjPHoGRkZKiwsNHvlGKPGS06rAgAAAAA0bA0uwJGkdu3a6Z577tG6deu0fv16PfXUU0c1fagxKWts9VtvvaVdu3bJ6XRq5MiR1bruJ598Ikk677zzyj0y5vP59PTTT2v9+vUKCwvTkCFDFB8fX63nq4jFYtFZZ51VI9U4d9xxh4YMGaLCwkKNHj1av/32W8B7uO2227R+/Xq1b99ee/bs0QUXXKCnn37aDJJCQkIUFxenkJAQM7Axjk9JZf+uAAAAAAANU4MMcKTifWAC7QnTUFWlUsPhcJQ6omNMnhozZky1j+6sX79eknT++eeXu+bLL7/UypUrJUnTpk1Tu3btqvVcgYqJidH48eOLVePce++9uu+++/T7778HdA2LxaJHH31Up59+urKysjRy5EhlZWUFvIfTTjtN33zzjXmkatq0aZo3b56cTmexm39TabfbbVbicJwKAAAAABqHBhvg+Fd51HST4PqmKpUaZY2tNsZ0H81RHWPcdqtWrcpdY1S/nHPOORowYEC1n6uqjGqcM844Q16vV+vWrdOIESM0btw4ff/995UGgDabTc8//7wSEhKUmpqqyZMnVyk0NI5U3X///ZKkVatWme+/cZzKGPFut9tls9nMJsaMGG94UlNTtWXLlgpvKSkpdb1NAAAAAMdYg5lCheI8Ho/cbrc5acr4ujrGjx+vq666SvPnz9dtt92mFi1aVPkaCQkJ2rt3r/76669ye9okJCRIkjIyMqq1z6MRExOjcePGaceOHfrss8+0fv16ffvtt/r222/VqVMnjRo1Sv/4xz/KfXxcXJyeffZZXXnllXr//fd1zjnnaPjw4QE/v8Vi0R133KH7779fO3fu1B9//KGWLVtq9+7dstlsZoAjqcyqG//fN4FO/ZWamqqkpKSAwlK73W5OOAMAAADQ8DXYCpxgUVcNZv2rbo62UqN///7q1q2bPB6PHn/88Wpdwwhndu/efVRraluHDh30wAMP6I033tDQoUNls9m0fft23X333frmm28qfGyPHj109913SyqagrZt27YqPXdkZKTOOOMMSUVHzjwej2w2m/Ly8iTJHNte1u+SfjgNg1FttXz5cv3www8V3lJSUiodeQ8AAACg4SDAqWV1FeBUtT9KRX1ycnNzNWnSJEnS888/X62ApW3btpKKKgzKYwQ4WVlZyszMrPJzSEV7ff7557V48eKjCjPatGmj8ePH6+2339YFF1wgn8+nWbNmac+ePRU+7pZbbtE555yj3Nxc3XbbbcrJyanS8/br109SUYBjt9tltVoVEREhSRW+J/TDaViSkpLUo0ePCm+ENwAAAEDjQoBTy+rqOEtVq27KquDweDzauXOnDh48qF69eql3797Kz8/Xww8/XOX9GB82KwpAmjRpYh7Pqk5I5PV6tXLlSv3xxx/6888/tXTpUuXm5lb5Ov5iYmJ0zz33qHPnzsrOztaUKVMqDOWsVqueeuopxcfHa/v27WZfm0AZAc5nn32miIgIs+dNTk6OYmNjS603gjcqbwAAAACgYaMHTi1zOBw11kTZ7XbXaJ8T/0a7xphqu91u/tx4PkmKiorS7Nmz1adPHy1fvlyTJ08uNZrdOOJTluOOO05SUYDj9XrLXZeQkKD9+/dr586dOuGEEwJ6HdOmTZNU1CjZ2K/FYtHevXv18MMPq2nTprJarZo4cWJA1/v3v/9d6mf9+/c3e9Pcfvvtuvzyy3XdddeV+fjw8HA99NBDuvnmm7V8+XL17dtXl1xySaXP63Q6deaZZyoiIkJpaWn65ZdfdNxxx8nj8SguLk5S6UAwLS1Nhw8fVl5enlq3bm0emZPqbvpaY28aDgAAAAC1gQqceqQu+pwcOnRIhw4dklQ0remiiy5SYWGhZs2aVaXr+Pe3qShYqG4fnNzcXPN9iY6OVrNmzWSxWHTkyBFlZmYedZgRFRWlIUOGyGq1KiUlRd9++22F688++2zddNNNkqQJEyZUeHTMn81mM5slG8eo/MeJSypWcZOTk6MDBw5IKmpuTANj1EcpKSmVTt4K9G8IAAAAaKgIcOqR2uxz4vF4VFBQIJfLZTZSlYqOEMXExJhrxo4dK0lauXKl3n333YCvbwQz2dnZ5kjxitZVJcApKCgwQyZj1HZYWJiaNm0qi8Wi/Px8ZWZmVlghFIiEhARzvPn69esrbWo8duxYde3aVVlZWbrtttt05MiRgJ6nf//+kqQ1a9bI5XIVu8/4PaWnpys9PV2S1KxZM8XFxSk+Pp4eOKhXnE6n7Ha7kpOTddppp1V4S0pKIsQBAABAo1btAKewsFCPPvqoLr74Yt1yyy367bffSq1JSko6qs2huKr0tamoKXF51w4NLTpRV1BQYB6nioyMNI9seTweJSYm6p///Kck6cYbb9TOnTsDvr5RQfL333+Xu87olRPoBzWPx6ODBw/K5/MpPDxcUVFR5n3h4eFm35i8vDy9/vrrFR7fCkSPHj106qmnyufzadKkSfrrr7/KXRsWFqZHH31U0dHR+v777/XYY48F9BxGH5zvv/9eaWlpkopepxGsZWZmKicnRwUFBYqIiFCLFi0UHx9/VK8LqAuJiYlKSUmpdOLW8uXLzb8BAAAAoLGqdoAzefJkLVy4UElJSTp06JBOO+00vffee8XWBPrhHjWvuset/IMcj8cjp9OpxMREMzQ6dOiQbrzxRnXv3l2ZmZkaNWpUwNdu166dJFUYehgVOHv27DGraiqyYsUKFRYWymq1KjY2tlT/FZvNZoY4P/74o1asWKGCgoKA91ySxWLRwIED1apVK2VmZmrcuHEVXq9Nmzbm6PVnnnlGW7durfQ5evTooZiYGLndbrPps1F5YzQzjoiIUGhoqOLj46m8Qb2WmJhY6cQt/p8BAAAAwFEEOCtXrtSHH36oxx57TK+//rqWL1+uf/7zn/r888/NNTQzrTvVGSNuBBF2u10ul0vZ2dmlKnhiYmLkdDr1zDPPSJI2bNgQ8Kjs0047TZL00UcflbumVatWat++vY4cOaJ58+ZVOkUqPz9fUlG1jdVa9j/nJk2aKCYmRlarVT/++KMWLlyow4cPB7TnsoSGhurKK69UdHS0fvnlF61YsaLC9ZdeeqnOPfdc+Xw+bdmypdLrh4SE6LzzzpMkffjhh2Y1VGhoqOLi4o4quKlqZRYAAAAAIDhUO8DJzs42JwtJRR9Sly5dqqFDh+o///lPjWwO1VfV41Yej0f5+fnmUSmbzaa8vLxSjzeaGnfo0EFxcXHyer365ZdfAtrTzTffLEn66quvyu1xY7VaNWfOHMXGxio1NVXz58+vsMLlggsukFTUxLiiHjcRERH617/+pSZNmmjnzp165plnzONJ1REdHa3x48dLKqqs2b9/f4Xr27ZtK0k6ePBgQNcfOnSopKI+OLt27TJDHKfTeVQVN3XRCBsAAAAAcPSqHeD07NlTDzzwQLGeIkOGDNHDDz+s888/Xx9//HGNbBC1z+PxKDw83GwAbLfbFRUVZfajMRobZ2RkKDw8XDExMbJYLOrSpYsk6b///W9Az3PiiSdq4MCB8vl8WrlyZbnr2rZtq8cff1w2m00pKSlaunRpub1rOnTooPDwcEmqNJTo1KmTbr/9dsXFxSkjI0NPP/20tm/fHtDeyzJkyBB17dpVHo9Hjz76aIVrmzZtKknmxKjKDBo0SFFRUdq9e7dWrVpl9iWSil6n/ySq8n5WlrIqs2qiKofKHgAAAACoXdUOcJ544gm98MILZlWF4eabb9b8+fN13XXXKS8v76g3iNpVsvpG+l/DYeMoVXp6uvbs2SObzSar1Wo2NT7llFMkqUoVV7fffrsk6YMPPqiwx81JJ52k2267TSEhIdq8ebNWrVpV7lojjPB4PJVOmmrRooXuuOMOHXfcccrNzdULL7ygTZs2Bbx/f1arVdOnT1dISIjWrVunjRs3lrvWCHACrcCJjIzUtGnTJEnPPvuseeTL+H34BzrS/47AVRaglFWZVRNVOVT2AAAAAEDtqlKA49835NRTT9Vvv/2me+65p9S6oUOH6vfff9dLL7109DtErTKqb4yvywsAIiIiFBkZqU6dOplNjTt16iQp8AocSerTp486deqkvLw8vfPOOxWu7dy5s0aOHClJ+vjjj7Vu3boy14WHhyssLMx8DZVxOBy65ZZbdNppp8nr9erNN9/Uu+++W60JVSeddJKuu+46SdKDDz5Ybs+eZs2aSQq8AkeS7rjjDp188sk6cOCA5s2bJ0nmcbLQ0NBiIYzRI8dut5vVOIFWw9TEePraHHEPAAAAAJBCq7L43HPP1bp16xQXFyep6EPb8ccfX+ba6OhoJScnH/0OjxGfz9fomi4br9eoCgkPD5fH4yn2ITw+Pl4RERHm0Sp/HTp0kPS/AMeYXlWZ0aNHa9y4cVqzZo3Gjx8vm81W5rqCggJ17NhRYWFhWrhwoVatWqUTTjjB7HtjGDhwoFJTU7V+/Xrl5+erX79+Zijlb+LEieXu6YsvvtAXX3whSWWGkmX58ccfJUm9e/fWe++9p927d+vBBx/UlVdeWWzdoEGDzDHfmZmZZthU0pEjR0r97Mknn9TAgQO1aNEiXXXVVerUqVOxChqfzydJxX4/RgPq9PR0tW/fvtI+SA6HI6DgxXiuspT17wMAAAAAUHOqVIGzc+dO9e7du9wGtJL06aefHvWmjoWCgoJiFUUWi6VaFRgNQdOmTc0KjpIf5P2PU5XUrVs3SdLff/8tl8sV8PMNHjxYLVu2VHp6eqnR82W5+uqrNWzYMEnSY489VmYVS0JCgmJjY3XkyBH9+uuvAe+lLFlZWVVaHxERYYaV77//fpkNjatTgSNJffv21bBhw+T1ejVp0qSA/o3a7Xbl5eXJZrNxpAkAAAAAGogqBTibNm2S1+vV2WefXepD8tdff63+/fuXqo4IRu+++66Sk5PVtWtXnXPOORo/frwOHz5c7hjqYFEbzWaNoy/NmzcPeGqVoUWLFuYksqr0wQkLC9P1118vSXrhhRcqrOyQisK10aNHKykpSUeOHNH7779f5hqjJ88vv/xSZjVLoJYtW6Z9+/ZV6TGnn366unTpooKCAr3++uul7q9qE2N/s2fPVmRkpL7//nu98cYb5f7+PR6PGaQlJiYqOjq6VCBHs2EAAAAAqJ+qlFh07NhRmzZtUocOHdSnTx999913+vHHHzV48GD16dNHW7Zs0ZQpU2prrzXixRdf1LXXXquCggINGDBAhw4d0lNPPaXTTjtNH3zwgXJycup6i+WqjWazVRk3Lv0vJDD65VSnD44kDR8+XHa7Xdu2bdNXX31V6Xqr1WoeTXrnnXfKDGjat2+vyMhI5eXl6bfffqvSfvwdPnxYr7zySpUqeSwWi6677jpZrVZ9//33pUarG8cOs7OzqxwutWnTxjzW9eCDD2rHjh1lBjD+jYzL+73SbBgAAAAA6qcql5w0bdpUH3/8sQYNGqRzzjlHPXv21ObNm3Xfffdp165deuihh2pjnzViw4YNuvvuu/Xwww/rlVde0cKFC/Xll1/qoYceksfj0U033aTXX3+92NGqQOXl5SkrK6vYraYdbaNYj8cjt9utvLy8al/D5XJp165d2r59u1wul0488URJ0kcffVSlI2gxMTG66qqrJBVVvASib9++atasmTIyMsoMfaxWq1mF89///lf5+fkB78ff8ccfr4KCAq1evVp//PFHwI9r27at+vfvL0mlqnCM0euSqnTczDB27FglJSUpMzNTixcvLjPA8W9kXB6aDQMAAABA/VTlAMfr9eqNN97Q999/r7y8PFmtVr322muaNm2aYmJiamOPR804ovPpp5+qXbt2Gj58uCIiIuT1ehUdHa1x48bp8ccfV9OmTTV58mStXbtWPp+v0qM9/mbPnq2YmBjzlpCQUOOvo6rVMiW53W7ZbDZzDHh15OTkaP/+/Tpw4IAOHDigvn37ymq1au3atRo7dmyVQpwrrrhCkrR169aA1oeFhen888+XJP30009lrunQoYMiIyOVk5OjzZs3B7wXf1dddZWSkpIkVb2y6PLLL5ck/fnnn8WquUJCQsyw65NPPqnynsLCwjRhwgRJRUfEyvr9VdSvyH/N0fwbAgAAAADUjSoFOAsWLFDHjh01YsQIORwOvf/++7r88st1+eWXVzoSOhj8/PPPyszMNKceWa1W+Xw+NWnSREOGDNGDDz6o6Oho3X333dq5c6csFkvAIc7UqVN16NAh81ZRo+e6UlPVFzabTUeOHFFsbKy6d++u++67T1arVS+++GKVQpzExERJUkZGRrnjt0syjmz9/vvvZd4fEhKi3r17y2KxaMeOHdq1a1dA1/VntVrVvXt3SUWNu6sS5MXExCg2NlaStHfv3mL3XXPNNZKkV199tcp7kmSGgocOHSoWwPgfayvrewAAAABA/VelAGfs2LGKjIzU6tWrtXnzZg0aNEgrV67UiBEjNHToUM2fP7+29nlUjKMrXbp00Z49e7Rt2zZJUmFhoRnShIWF6eKLL9b48eO1a9cu3XHHHfJ6vQGPFrfZbIqOji52CzY1UX0RERGh1q1bm/1mpKJ+NrNnz65yiBMTE2PupWTYUZ4TTjhBkrRjxw4VFhaWuaZFixbq0qWLJOmbb76pVpDRpk0bhYSE6PDhw1VuPNymTRtJ0l9//VXs51dddZVCQkL03Xffmf8Gq6J58+aSpP3798vlchW7FRQUlPq+Nvvc0AwZAAAAAI6tKgU4r776qrZu3WoeE5GKwpHnnntO99xzj26//XZNnjy5pvd41IwKivPPP1/h4eG6+eablZmZqZCQkGIhTnh4uK6//npdcskl2rhxY8ChQn1ytB+8nU6nHA6HIiIizCM7kZGRGj16tF544YUqhTgWi6XcsKM8bdu2VZMmTZSbm6s9e/aUu65r165q1qyZ8vLytHHjxipV0UhFR5aMvVW1iqd169aSSr+mFi1aaMCAAZKkFStWVOmakhQfHy9JyszMlMvl0vbt25WdnS1JCg0NlVTUJDkjI8Ps/5Oenm7eajJsoRkyAAAAABxbVQpwhg8fXm5Fyn333adnn31WTz75ZI1srCYZez7rrLN0zTXXaOvWrbrpppuUlZVVLMQpKCiQw+HQhAkTlJmZeVSTjIJVeR+8Aw127Ha77Ha7bDabOe3IbrfL4/Ho8ssv13PPPVelEKeqAU5ISIiOP/54SeUfozLW9enTRyEhIdq7d2+VJkoZ2rdvL6noGFVVGK+prADwuuuuk6RqNctu2rSpGdT8+eef8nq95rhzI0zLy8tTbGysWdlUUFCg9PT0Ur/zow3yaIYMAAAAAMdWaE1e7LbbbjOPeQQbr9er0NBQPfPMM9q+fbvWrFmjsLAwLVq0SDExMTpy5IjCwsIkSfv27VOLFi3MHi3BItDjXBVxOBxyu92lPnj7Bzslj1hZrUU5nzHFymKxmB/erVarcnJyVFhYqPz8fF122WXKz8/XnXfeqRdffFE2m03PPvtssesZIYRUVFEjSX///Xexn0tFx7XKctJJJ+mXX37Rzp07FRERYR6rKktBQYH+7//+T1u2bNG5556rqKioSt6h/4VJxnu0c+dO7dmzp9T737FjxzIf36JFC0nSnj17dOTIEaWlpZn3de3aVW3atNFff/2l6dOna+rUqeZ9gfx7i4+P1759++T1etW0aVPl5+crPDxcHo9HTqdTiYmJZrBmsVjkdrvNyh3/33lFv+9AGMFdWQKpdqpqRRQAAAAANHZVnkJVmaFDh9b0JQPm/6HQ+Nr4r9VqVWFhoWw2m9auXaszzjhDK1eu1CWXXKI9e/aY4c2hQ4f06aefqn379mratOmxfxG1zOFwqHnz5qUCnMoqKjwej3bt2mWOR/fvpWM81vhQP2zYMC1evFgWi0ULFy6ssJKpqhU40v8aGQfSR+aMM85Qx44dVVBQoB9//LFKU7Li4uIUGhqq3NxcZWZmBvy4Vq1aSSpqzpyXl1fsvrCwMM2aNUuS9MorrwQ8gctgBKT5+flq0aKFEhISio0O959EZfQ8Mm7+gQsVNAAAAABQv9R4gFOX0tLS9Ndff+m3335TQUGBpKKqFaPZbUhIiAoKChQREaH169dr6NCh+uqrr9StWzfdeeedmjRpkm666Sa98cYbWrRokZo1a1aXL+eYqqzBsdvtVnh4uPLz80t96Pd/rBEgXHXVVerbt68k6c033yz3eY0Ap6J+NiUZ47i3b99eaSWH1WrVkCFDFBERoUOHDlWpeXBISIgZmBhHlQIRHR2tyMhI+Xw+/f3336Xu7927ty699FL5fD5Nnz7d7FcTCGM/mZmZcjqd5q2qVTSMEwcAAACA+qXBBDhvvPGGLr/8cnXu3FldunTR4MGDtWjRIklFH8SND/qhoaEqKChQkyZN9Oqrr2rJkiXq06ePXnvtNb399tvy+Xz6+uuvdeqpp9blywk6DodD0dHRateuXUAf+l0ul84991xJ0ltvvVXuuor6xZTn+OOPV0hIiDIzM5Wenl7p+ujoaF122WWSivrmZGRkBPxcRjVNWUFMRYxGxuW9rilTpqhp06b67bff9MILLwR8XSPA8T+WZfB4PEpNTVVqamqx3jYl+90wQQoAAAAA6p8GEeC89NJLGjFihM4991zNnDlTM2bM0Ndff63Ro0frxhtvlM/nK9a/JDQ0VIWFhQoLC9MNN9ygNWvW6Pvvv9fWrVv1yiuvqHPnznX4aoKT3W43++cE+sH/7LPPVkhIiH766adymwgbPXD27t0bcLDSpEkTtWvXTpL073//O6DHdOnSxXyuH3/8UUeOHKn0MdnZ2ebRqf3791epb0tlAU7Tpk117733SpIWLlwYcIWPEeBs27at1O/B4/EoOztb2dnZxe4r2bi6sglSBDwAAAAAEHzqfYDz008/aebMmZozZ44eeOABjRs3Tvfee682btyoc889V8uWLdPQoUOVm5srSSosLFRBQYFCQkKKXSchIaHCxqyNnX8PnEBGRzudTrVp08Y8RjV37twy17Vs2dLsUTNq1Cjz91SZs846S5L07LPPluozU54uXbrIbrcrJydHP/30U5mBjNfr1a5du/TRRx9p9erV2rFjhyQpKiqqSk2kY2JiJKnC92rQoEE64YQTdOTIkYCnZBmVYR988IEZLnk8HrlcLnOfUVFRFfa7qaz/TVVHhBP4AAAAAEDtq/cBzs6dO+V2u9W7d29zilFhYaG6du2qxYsX68orr9SaNWt04403Sio6TmWse+edd8yjMcakpcauvA/jFfXAKYvdbldCQoLGjRsnSXr55Ze1e/fuUuusVqsWL16s6Ohofffdd5o0aVJAlS433XSTWrVqpX379mndunUBvbawsDCddtppslgs+vvvv4uNB3e73UpJSdEnn3yizz//3KyIad26tc4991wNGjQooOcwBBL2WCwWs1In0Oqjyy+/XK1atVJ6errWrl0rqeh3VlBQYE6fKtkTp2S/m8r631S1wXFVAx8AAAAAQNXV+9Tit99+U0ZGhtmrxKiu8fl86tixo+bMmaNBgwbp9ddfN6f/SNLUqVN1xRVXaNWqVVWaTNSQeTwe7dy5s8wqG4fDoZCQkHJHe5fFbrfroosu0llnnaUjR46UW4VzwgknaNGiRQoNDdXbb7+tp556qtJrOxwO8wjS5s2bzUqZysTGxurkk0+WJP3888/6448/tGnTJn322Wf6/ffflZeXpyZNmuiUU07RkCFDNGDAALVr167WAr64uDhJ0oEDBwJaHx4errFjx0qSnnvuOfl8PtntdjOUNIKco1HVBsdMtAIAAACA2lfvAxzjKM2cOXMkFfW38Xq9slgs8vl86tChg+bMmaM2bdropZde0q+//iqv16uzzz5bAwYM0IUXXkj1zf/ndrtls9mUl5dX5qQph8Mhm80WUKWFcazH4/Fo8uTJkqTnn3++zOa7UtFkpocffliS9OSTT2rNmjWVPsfpp5+uIUOGSJLWrFkT8FGq4447Ti1btpTP59PPP/9sNkKOj4/XaaedpmHDhqlHjx6KiooK6HoVqayayJh0VpXGyjfffLPsdrt+/PFHffTRR8Uqb/xHih8rTLQCAAAAgNpX75OLTp06qUuXLlq6dKmWLVsmqehYjtG42OfzqUuXLnryySe1a9cu/fLLL7JarRo8eLDefvttderUqW5fQBAxJk21b99ekkodpapKpYXH41FhYaE8Ho8GDx6snj17KicnR08//XS5jxk+fLhGjx4tSZo4caK2bt1a6fOMHTtWsbGxyszMDPgolcViUbdu3RQdHS2bzaaOHTuqf//+OvPMM9W6desaCfSMI1SVBThVrcCRikKfESNGSJKeeuqpCo9P1RX64gAAAABAzQqt6w0crebNm2vRokUaMGCAHnnkEUVHR2vIkCGyWCxmJY4kde/eXU2aNNH27dslFYU8VTkO1Bj4N3FOT083+5r4906pKBzwDz4cDof54f3AgQMaP368rr32Wi1YsEB33XWXYmNjy7zGE088oX379untt9/WlClT9NZbb5kTp8oSHx+vSZMm6d5779XmzZt1+eWXq2vXrmWuzc7OLvb9qaeeWmavmvj4+HKfz1/JRtj+jOtaLBYVFhaWu854H1wuV8BH+bxer26//XYtXLhQH330kVJSUnT66aebj/d4PPJ4PIqMjDTDtvT0dLlcLjmdzoBfX3mvKRD+fXHKCvyqci0AAAAAQAOowJGKjlEtWLBAu3bt0syZM/X6669LKh4ouN1utW7dWieddFJdbbPe8Hg8crvdZR6lKrmuvCoLh8NhBgUFBQU644wzdOKJJyorK0uLFi0q95pWq1VLly7VaaedpgMHDuhf//qXDh06VOF+u3XrZjYZnjdvnnJycgJ5mbUaIgR6beMIVVUqcKSiyrOLL75YkvTCCy8Uu8+/+sngcrmUl5dnTqsqj/E7NW7VraChLw4AAAAA1KwGEeBI0rXXXqt58+Zpx44dGjdunB588EFJRR+kDxw4oAULFshqter000+v450GP7fbLa/XW2kQYlRZpKWlKT09vVRvnPT0dO3evVuZmZmyWq26+eabJUnPPPNMhX107Ha73nzzTbVq1Uo7duzQbbfdpiNHjlS4lxtuuEHNmzfX/v37tXTp0gBfad2rzhEqw1133SWpaJraX3/9JakogMnJyVF+fn6xaimn0ymbzSan01nhNY3fqX8FVnU4HA41b96cAAcAAAAAakiDCXBCQ0M1atQorV69WpI0Y8YMde/eXQMHDtSQIUP01ltvaeXKlWrTpk0d7zT4ORwO5eXlVdqw2KiykMqefuRyucwqKKfTqfPPP18JCQlyuVyVhiytWrXSCy+8IIfDoW+++UbTp0+vsJ+M3W7XnXfeKUn64IMPAuqfU5sC7YFjVOAcPHiwytPQzjnnHHXr1k05OTlavHixPB6PMjIydPjwYUkqFp7Ex8crKSmp3ONTRuWNVPS3FB8fTwUNAAAAAASRBhPgGAYOHKhNmzbpwQcfVPPmzZWXl6du3brp66+/Vrdu3ep6e0HN/0N8u3btFBUVVeEHeGP6kMPh0MGDB0vd71/14XA4dPzxx+uOO+6QJD3++OP6888/K9xPUlKS5s2bJ6vVqpUrV+qpp56qMBDxP0r15JNPau/evZW+5toS6ESspk2bSpIKCwurXIVjsVjM0Oq1116T2+1WTk6OMjMzAz5GZjAqb6SisMe4BUNDZAAAAABAAwxwpKLw4Z577tG6deu0fv16PfXUU0ybCoB/41n/0dCBTBQyggh/xlQkSWYwNHbsWJ1wwgnav3+/zjvvPKWkpFS4p/79+2vGjBmSio5ePfLIIxWGODfccIPatGkjl8uliRMn6rfffqv0dde0vXv3mhOxKmrALElhYWFq27atJOn777+v8nMNHDhQkpSWlqbw8HBFREQoNja2yg266VmD+iAlJUVbtmyp8JaamlrX2wQAAABqRYMMcKTiR1cqO8aCIv4f4v1DG/9gp6LHlazW8Hg8KigokMvlUnZ2tlJTU5WVlaXFixerQ4cO2rt3r84//3z98MMPFe5rxIgRZoizePFiTZo0qdyeOHa7XY888og6dOigQ4cOacqUKdqyZUs13o3qycvL0/z585Wfn6+TTz5Z/fv3r/QxZ599tiTp448/rvLzGaGazWZTTEyM4uLiFB8fb/bW8ed2u4v1KjK+N0aQU3GDYOV0OmW325WcnKzTTjutwltSUhIhDgAAABqkBhvg+E8BYmRxYPw/xJccA11RdYb/UaqSPw8NDZXT6TR76rhcLrVp00YvvfSSunbtqoyMDA0cOFBffPFFhXsbOXKkHnnkEYWEhGj16tUaNWpUuYFS06ZNNWfOHHXr1k25ubmaNWuW1q9fX703pYqWL1+uPXv2KCYmRrfcckuxSWjl6dOnjyTpk08+qfLzlex3Y1Q9lRXEpKena//+/WY1lBGwVbdRMXCsJCYmKiUlRT/88EOFt+XLl8vj8VQ6bQ0AAACoj0LregMITg6HQ2lpaeYo8fKa31Z2Df9gwePxKCoqSgUFBTr55JP17rvvavjw4fr666916aWXasWKFbrooovKvd6wYcPkdDo1duxYffHFFxo+fLiWLFlS5lq73a5Zs2Zp7ty52rBhgx5//HH169dPvXr1qvLrCNRXX32lL774QhaLRbfeeqtiY2MDelyvXr0UGhqqP/74Qzt27FCHDh0Cfk4jwGnSpIl2796tuLi4CqtocnJylJeXZwZ16enp5u+Y6pvalZqaWmmwUNmRwsYsMTFRiYmJdb0NAAAAoM4Q4KBMdrtdDoejWE8cf8bRqvI++LvdbvNojhHkGGFOfn6++RwffPCBhg0bpo8//ljDhg3TkiVLdPXVV5e7r379+um1117TTTfdpP/+978aNmyYpk2bVuZ0sbCwME2cOFHNmjXTmjVrtH79eh0+fFj9+vWrsaqsnJwcffvtt/riiy+0Y8cOSdJll12mk08+OeBrOBwO9ejRQ5s3b9Ynn3xSpQDHqJ6x2Ww6fPiwIiIiyv19SJLValXTpk3l8XgUHx9frAqHAKf2pKamKikpqcI+Ugb/3lEAAAAAYCDAQbkcDocZ0pRUsuGxP4/Ho127dslms5nX8RceHm5+feTIET377LO6++679c4772jkyJHyeDy65ZZb1Lp16zL31bp1a33xxRe65JJL9Oeff2rKlClatmxZuVPG5s2bp86dO+vBBx/Ud999p6ioKE2cOFFhYWFVeTtMPp9PP//8s1atWqVPP/3UnPgUEhKiiy++WHfffbdCQkLM9VlZWZVe8/TTT9fmzZu1bt063XDDDRWubdKkifm1UYFjt9uVn5+vnJwcZWRkSFKxcM3j8ZgTwex2u+x2u3w+n1kZFUjz4kB7SXFksTSXyyWPx6Ply5crKSmpwrVOp5NKEwAAAAClEOCgXMYH/bJUFu7YbDbzaI5UfsWOx+NRZGSkFi5cqFatWmnhwoUaPXq0Dh06pLvuuqvcvXXs2FGff/65rrjiCm3ZskVXX321nnvuuXKbBt98880qKCjQY489ps8++0yZmZmaOXNmlapODh48qE8++URr167V7t27zZ8nJibq0ksv1aBBg8psHhyIM888U/Pnz9dXX32l3NzcYiFNRbKzsyVJzZo1k1QU6Bw4cEAtW7aUx+Mx+4EYv8vo6Ohir9mokMKxkZSUpB49etT1NgAAAADUQwQ4qJbKwh3jv8aa8ip2jAoQSZo1a5YcDoeeeOIJTZkyRRkZGbr//vvLreho0aKFPvroI1155ZXasGGDbrrpJs2ZM6fcI1jnnXeeYmJidN9992nLli2aOHGipk+frvDwcOXl5SkvL0/5+fnKzc1Vfn6++bPc3Fx999132rRpkwoLCyUVVcGcd955uvTSS9W1a9ejrjo5/vjj1bJlS/3999/65ptv1K9fv4AeZ1TgREZGKiIiQoWFhYqIiDCngqWmpppH1qjqAAAAAID6iwAHNa6scKe8ih2jN056eroKCwt19913y+l0aurUqXrsscd06NAhPfXUU+VOc4qMjNTSpUt1991366233tKkSZP0999/64477igzVOnZs6cef/xxTZs2Tb/99ptGjBhRpdd20kknaeDAgTr33HPVqlWrKj22IhaLReedd55effVVffrppwEHOEZvG4fDYVb/GH1wrFarnE6nXC5XqZ4qRnUOFTgAAAAAUD8Q4OCYKBnqlGxybFTi2O12TZ48WbGxsbrtttu0ePFiRURE6JFHHin32mFhYXryySfVsmVLzZ8/X0888YTS09M1Y8aMYv12DCeeeKKeeuop3Xffffrzzz9ltVpls9nMW3h4eKnv27ZtqwsuuEDHHXdcrbw/ktStWze9+uqrVRp5fujQIUlFfYUyMjLUtm3bYu+z0+kssyGu0bw40P43AAAAAIC6RYCDOuHxeJSdnS2Xy6XExMRiU6rcbreGDBkiq9WqW265Rc8884yGDx9ebpNiqaiCZfLkyWrRooVmzpypl19+WT/++KPmzZunjh07llrfpk0bLVq0SAUFBQoNDa3zxrvfffedZs2aJanoaFggfD6f3n77bUlS+/btFR4erpycHDMMy83NLdbE2AjRjOobSYqOjq50olgg/K9BIAQAAAAANa/scylALbPb7crLy5PNZis1WtmoDrnkkks0bNgweb1e3XXXXfJ6vZVed+TIkVq0aJFiY2P1n//8R4MGDdLLL79c5gQli8WisLCwOg9vPvnkE02YMEFut1t9+vTRsmXLAnrcF198oZ9//ll2u13XX3+9oqKiFBERIalovLlRYeNfbSMVvb/h4eFmoOPfn6i6auIaAAAAAIDyEeCgXB6PR+np6eatZNByNBwOhxITExUVFVWq6sNutys0NFQej0e33nqrIiMjtWnTJr3yyisBXXvgwIH66KOP1KdPH+Xm5mratGkaOXKkDhw4UGP7rymrVq3SzJkzVVBQoMsuu0xvvPGGoqOjA3rs/PnzJUmXXXaZYmJiFBcXZ76X/o2MjffTuM/4Xioaby1JoaGhR1U543A4jvoaAAAAAIDyEeCgXEZVRXp6eo1WV7jd7goDIYfDofj4eOXm5qpp06a69dZbJUn33nuvDh48GNBztGzZUq+88opmzZolm82m9evX6+abb9bXX39dI6/haPl8Pi1cuFBz586Vz+fTlVdeqeeff142my2gx+/atUvvvPOOJOnyyy83K28M/seljO/9GxcbfXEKCgokSfHx8dU+PmVc/2ivAQAAAAAoHwEOymVUVcTHx9dodYVxpMflchU72lNSs2bNFB4erptuukkdOnSQy+XSzJkzA34eq9WqG2+8Ue+//75OPvlkHTp0SDNnztTcuXOVk5NTI6+lOgoKCjR79my9/PLLkqRRo0Zp/PjxCgkJCfgaixYtktfrVa9evXT66acXC048Ho8yMjKUmpqqtLQ0uVwuuVwu82uPx1NjlTcAAAAAgGODJsaNWGW9X4yGtGX1jzkaxkhxowqkrAAhPT1dBw8eNNfMmjVL//znP7V48WJ17txZY8aMMdc2b968wudr3ry5vvnmG02bNk3PPvusPvjgA/3666967rnn1LNnz1Lr9+3bF9DrCLRaxn8K1M6dOzVx4kR9+umnslqtevLJJ3X99ddLUpkTs8qSn5+vJUuWSJJGjx6t+Pj4YuFPbm6uCgsL5fF45PV6zWbGPp9PPp/PDNCMcK6uewABAAAAACpHBQ6OOeO4jXEr69hNenq68vPzlZGRIbvdrgEDBmjChAmSpDvvvNPs/xIom82mWbNmac2aNWrTpo3++OMPDRo0SA8//HCN9vYpz6FDhzR9+nSdccYZ+vTTT9WkSRO9/PLLZnhTFStWrNCBAwfUrl07JScnlxmAZWZmKi4uTpGRkWratKkiIiLUokULNW/enH41AAAAAFAPEeCgVhmNkP1DkrJ+VlJ8fLzCw8PNxrxOp1Nz5szRpEmTJFUvxJGkPn366Msvv9SVV16pwsJCPfHEEzrzzDP11ltv1XilkVR0XOr5559Xjx499Oyzzyo/P1/9+vXTp59+qsGDB1f5ej6fT88++6wkacSIEeUeu4qNjZXD4VC7du0UFRWl5s2bm2EZ/WoAAAAAoP5ptAHO3r179fvvv+ubb76p663UO4EEMIayxksHMnLa4XAoLi5OkpSamqrU1FRlZGRo/PjxGjdunKTqhzgxMTFavHixli5dqrZt2+qvv/7SzTffrIsuukg//PBDla9XFp/Pp88//1wXX3yx7r77bh04cEAnnniiVq5cqbfeeksnn3xyta77zTff6KefflKTJk00cODActdlZmZKorkwAAAAADQUjTLAWbVqlYYNG6bu3bvrH//4h2688caApxshsADGUNZxnUCO8LjdbhUWFiojI0Nut1tut1sZGRnyer26++67i1XiLF++vFqv47LLLtOmTZs0depU2e12fffdd7rgggv02GOP6ciRI9W6piT9+uuvuuGGGzRq1Cjt2LFDcXFxevzxx/XVV19pwIABR9Vz5plnnpEkDR48WB07dix3XWxsrPl1VQI3AAAAAEBwanQBzosvvqgRI0aoZ8+emjp1qq688kotW7ZMK1asqOut1RtV6aFSVgVIIFUhDodDISEhiouLM5spx8XFKSQkRA6HQw8//LDGjx8vSRo7dqy2bt1ardcSERGhiRMnavPmzbr66qslSS+99JJuuukmpaWlVela+/bt07333qvLLrtMGzduVFhYmEaNGqUffvhBN910k0JDj65n+MaNG/Xuu+/KYrFo5syZio+PL3Od3W43fz8ej0e7du1SdnZ2jY2BBwAAAAAce41qCtXHH3+scePGac6cORo1apTsdrtSUlK0fv16paamHtW18/LylJeXZ36flZV1tNsNWkYfldp+jiZNmlS4Zs6cOUpJSdHatWt19dVX65tvvlHTpk2r9XytWrXSggULNGjQII0ZM0ZbtmzR0KFD9fjjj6tXr16l1vt8Pu3atUvff/+9fvjhB/3www/6448/zPsHDRqkiRMnKiEhQTExMdXak7/CwkKz6mjkyJHq0qVLuWuNwEsqagZts9mUl5enli1bSiqqyHG73XI4HBytAgAAAIB6olEEOD6fT16vV6tXr1avXr2UnJyssLAwSVJSUpJ69eqlZs2a6cEHH1R0dLTOPPPMMj+0V2T27Nm67777amP7jZbH45HH4yk3MLJarXruued0zjnnaOfOnbrxxhv11ltvyWqtfmHZxRdfLKfTqXHjxmn79u3617/+pdtvv10jR47U9u3btWXLFv3444/asmWLXC5Xqcf37NlTkyZNUo8ePaq9h7K88sor2rp1q2JiYnTttddq165dcjqd5kh2Yy/GzwzG1y1btjTfQ/8jcAQ4AAAAAFA/NIoAx2KxKCQkRD/88IOOHDliNseVpNdee00ffvihfv/9d7ndbv39999KTEzUuHHjdMcddwT8HFOnTjWP9EhFFTgJCQk1+jrqg5qq7vB4PNq9e7dsNpsklXkt47mefvppXXPNNVq7dq0eeeQRTZ06tdrPK0nt2rXTq6++qoceekhvv/225s2bpwULFpTqixMWFqZTTjlFp512mnr27KkePXoU6z1TUw4dOqSZM2dKkm6++WbFxMQoOztbdrvdPCaVnZ0tSebPDGWFX0bowxhxAAAAAKg/GkWAI0ler1dxcXFat26dZs6cqfPOO08//fSTJkyYoPvvv1///Oc/5XA4tHHjRt1yyy164okn1KNHD/Xu3Tug69tsNjNsaMxqqrrD7XabR3+aN29e5hqXy6XDhw+rbdu2GjdunGbPnq37779fPXv21IABA6r93FJRb5wHHnhA3bp108MPP6z8/HxFRkaqe/fu6t69u3r06KHTTjut0mNeNWHOnDlyuVw6/vjjNXr0aB04cEAhISHm+2u32xUVFWV+XZljcQQOAAAAAFCzGkWA4/V6ZbVa9fjjj2vbtm164IEHtHr1aqWmpuraa6/VhAkTFBERIaloMtHhw4c1cuRIffnllwEHOA1ZoFOTfD5fjVV3GI9v0aJFqWu53W6lp6frr7/+ks1mU0REhJKTk/Xrr79qzZo1uv766/Xdd9+pXbt2xR4XaC8a43idJI0fP14jRoxQWlqaTjzxRIWEhJj3BRrY+Xy+gNb5X9uwbds2LViwQJL02GOPmc9rhDBut1upqanKyclRQkKC7Ha7+XyB/t6MKV/HsidOoO8JAAAAAKBIowhwjJ4onTt3NnuYNG/eXBdeeKHOO+88RUREFPvQe/bZZ8tut2vXrl11ue16qaaqOyq6jsfjMatvmjRpooiICIWHh2vu3Ln6/fff9Z///EdnnXWWTjnlFLVr104JCQnF/tu2bVuFh4cHvBen0ymn03nUr6k6Jk2apIKCAp1//vm69NJLtXv37mL3G+9FYWGhXC5Xufss62ib8TOj2omeOAAAAAAQvBpFgGPwer2KjY1Vv379tGPHDmVlZenAgQOSioIbI8TJyspSy5Ytdfrpp0sqqhYItJoBgfXBOZpeOXa7XRaLRXFxceZjDx06pIiICC1dulSXXnqp9u3bp08//bTMx1ssFrVq1UoJCQk699xzNW3aNLMCK5isXbtWa9euVWhoqB555BFJMseqSzIbFzscDh08eLDY+2g0gDbe37KOthk/M9aWN5YcAAAAAFD3GlWA4z+dKCYmRg6HQytWrFCfPn102mmnyWKx6MCBA5o/f768Xq8uuOACSYEfRUGRQPrgVKdXjtvtNqdSnXTSSWYIFB4erpycHIWHhyshIUG//PKLfvjhB+3evVu7du1SampqsVtubq727t2rvXv36ttvv9WHH36oFStWqFOnTjX5NlSbz+fTRx99pLFjx0qSbr/9dp166qmSisKryMhIuVwuFRQUKDQ0VHFxcaWOc3k8nmLvb1lH24yf2e12+jcBAAAAQJBr0AFOYWFhmX1FfD6fnE6n7r77bt17773617/+pcsuu0wxMTH67LPP9MUXX2jDhg2NcopUTQikD051euUYoYRRLeJfXWJMFjOOXnXp0kWtWrXSRRddVOxYkc/nU3p6ulJTU/Xjjz9qxowZ2rp1q3r16qVXX31VgwcPrv4LryH33HOPHn/8cUlSYmKi7r333lJr7Ha7GWZ5PJ5y7zfe37KOpBk/YyoVAAAAAAS/BhPg/PTTT9qxY4f27dun9u3ba/DgwWWGN9L/KmqGDh2q3NxcLViwQPfff7/atm2rk046SV9//bU6d+58LLffoATSB6c6vXL8QwuDw+EodfzJ4/Ho999/N3//RoBjHBWKjIxUz5491bNnT/Xv31/XXXedvv/+e11xxRWaO3eubrjhhirtqyb98MMPeuKJJyRJV199tWbNmlWsqbLH41Fubq7sdrv5upxOZ6n3s+Q48YrUxVSqskInAAAAAED5GkSAs2zZMk2bNk1er1d///23JKlXr1566KGH1KtXL3PEckkJCQmaNGmSbrjhBm3dulUdO3ZUXFycYmNjj+Hu4a+i3jgOh6PcUMIIZ4yQJzw8XOnp6QoLC9O2bdvMCp3CwsJiIVCHDh20evVq3X333Xr99dd15513KiUlRbNnzy43AKwtXq9Xt99+u3w+n/r376/bb79dUVFRysnJMfebk5NT6jUYAYzR0LgqgczR9CI6GgQ4AAAAAFA11sqXBLdVq1bp1ltv1eTJk/XJJ59oz549mjRpklJTU5WcnKylS5eazV4NBQUF5tehoaFq2bKlLrzwQnXo0IHwpo7598Yxvk9PTzdvxs9L8ng8ys7ONqc0ORwOderUSZmZmUpLS9OePXtkt9sVEhJSKqiIjY3V3LlzNWnSJEnSwoULde211+rw4cO1+EpLe/HFF/Xdd98pKipKM2bMUMeOHRUaGlqswigiIkKhoaGlGha7XC6zL05VwpGS7/exwrQrAAAAAKiaeh3g7N+/X88++6xuueUW3XLLLUpKSlLr1q01Y8YMLVy4UC1bttT06dO1dOlSZWZmmo8LDS0qPFqyZImOHDlSR7tHWRwOh0JDQ81KG6PvTWXhhN1uV35+vjkePCEhQVFRUYqNjVVISIgiIiLMY0dl9YJxOBwaPXq0nn32WdlsNq1du1YXXXSR9u7dW7sv+P/LyMgwe93cdtttOumkk8qcjFWy2sY/uJFUKtypTMn3uyIej0fp6ek1Uj1DgAMAAAAAVVOvj1AVFBToP//5jwYPHmx+cPd6vXI4HBo0aJDi4uJ011136ZFHHlFCQoKGDx9uNjYeO3asFixYoG3btunRRx+t41cCQ1m9XDwej9nvpbwP/na7XQkJCebRIv9byb45LpdLGRkZiouLK9Yfx+v1ql+/flqzZo1GjBihrVu3qn///lq5cqU5Baq2zJgxQxkZGTrxxBM1evRoSUXHpQoKCoodoTL2WlBQoMzMTLNiLDQ0VNHR0bUajFRnclhjkJqaWqrKr6SUlJRjtBsAAAAADVW9DnAOHDig/Px8/f333/J6vfL5fGbfktDQUJ155pmaM2eObr31Vt1333266KKLzA+8U6ZM0aZNmzRy5Mi6ewENTCDj1t1ud5V6rlTU98ZgjIePjIxUZGRksfv8f+bz+SQVVbvk5+crIyND8fHx5vNkZGSosLBQzZs315IlS3TnnXdq586duvDCC/X888/ryiuvNKu3pKKwMBCVrfvuu++0dOlSSUUjw40QUpLS09N16NChUpO3/EOt6OhoSf/rK1OVaVJpaWnKzs5WVFSU2rdvX+HaQKdVBfLvIJA19UFqaqqSkpICqkrybzwNAAAAAFVVr49QnXLKKerTp49ef/11paamKiQkpFh/m5CQEP3jH//Q2LFjtX37dnM0c35+vtq2batvv/1WJ598cl1tv1Gqq54rxpEjI/gIDw8v9WHaOIZVWFio4447Th999JH69u0rt9uta6+9Vm3atNEtt9yiTz75pNi/s6NRWFioO+64Qz6fT3369FGvXr2KHR8z1hw+fLhYQBMfH2/eHA5HsRHr0v96B9Vks2C73a74+Hiqb/wY/6aWL1+uH374ocJbSkqKEhMT63rLAAAAAOqpeluB4/P5ZLFYdM0112jdunUaOnSovvzyS0VERKigoMCslGjSpImuv/56Pf300/r5558lyTxuZVRu4NgJtIqjprndbmVnZ8vlcikxMVEnnXRSsfuNyVXGtCqpaDz3q6++qtmzZ+v111+Xy+XSCy+8oBdeeEFOp1OXXXaZhg0bpr59+xarzKmKJUuWaMuWLYqOjtaDDz5o9ugxAhlJZgVRRcGJ/1Ext9ut1NRU8995yeNX/hVQzZs3D6jKCRVLSkpSjx496nobAAAAABqwehvgGEcwhg0bpi+++EIvvviiLrnkEr333nuKiIgwe934fD7FxsbqxBNP1OHDh83gx/8aOHaOZlx1ZSOvKxtB7nK5ZLPZSvXEkf4XgJTVR2bGjBl68MEH9fHHH+udd97Rhx9+KJfLpSVLlmjJkiXVDnPS09M1Y8YMSdKsWbPUp08fSf87ZibJrLCpjH8Ik56ersLCQu3bt888Umi8JyX72FRl5DhQXwTSc8jpdFIRBQAAgHql3gY4UtFRKLvdrrlz58rlcum9997TgAED9O6776pZs2aSikKajIwMHTp0SL179ya0qccqa6Jb0f12u12JiYlmeOPxeMpteOxyuUr9XJIuuugi9e3bV48++qg2btyod999Vx988EGxMMfhcKhr167q0aOHTjvtNPXo0UMnnHCCGaQYPB6PRo0apYMHD+rUU0/VLbfcUuw+m80W8HSokoxx6a1atVJOTo5sNpv5nlRUAVVZQAYEO6OCLTk5udK1drudY20AAACoV+ptgFNQUKDw8HAdOXJEhw4d0ooVK3TjjTdq5cqVOvvsszVt2jT16tVLOTk5eu6557R9+3a9+OKLdb1tHIXKjl9V5XiWf8+YsiY8+f/cP+xxOp1yuVz6xz/+oT59+uj555/Xhg0b9Oabb2r16tU6cOCAvv76a3399dfF9tW1a1d1795dp512mjp16qTx48dr8+bNCg8P17PPPlusaqesyVlSUUBVcl9GKFPyfTDCKv+fGdcuL5wp2Z8oLS1NktS8eXMCHdQLiYmJSklJCWgqWHJysnmkEgAAAKgP6mWAY/S48Xq96tWrl8466ywtWLBAS5YsUZcuXbRixQqNGDFCYWFhSkxMlM/n08cff6xOnTrV9dZxFCo77lPZ/S6Xy5y45HQ6KzxKVVGoY6zxer3at2+fOnXqpCeeeEKPPvqovvrqK23fvl1bt27Vtm3b9J///Edut7tUqCNJTZs21Ztvvqkzzjij2M/L60lTslGx8bX/Wv+Qx5iwFSj/AMzoGWT8nAAH9UViYiKhDAAAABqkehfglAxvDhw4oKFDh+rIkSNyOByaOnWqxowZo//7v/9TRkaG2rRpo7POOktt2rSp663jGAj0GFB5YU9ZPy8Z6hhr0tLSdPjwYUlSRESEnE6n+vbtq9NPP13XXXedcnJylJ6erv/+97/6888/tXPnTv36669KSUnR8ccfr1dffVUnnnii+Tz+4UtZAU7JfZQVQPmHPFU9flXytUdFRUmSOeWK41UAAAAAUHfqVYDjH9707NlTWVlZWrZsmc455xyFhITI6/UqJCRETZs2DagHAhoOI2Bwu93Fer743y/JrL6pirJCHY/Ho5ycHIWEhCgiIqJUuCMVVfxERETolFNOUdeuXdW0aVPFxcXJ5/MpNzdXERERysnJUU5OjiIiIpSXl1dh+FKyMqesyhtJCg0NPeqQxW63q3379ub36enpFfYfAgAAAADUrnoT4JQV3ixevNgMb6Syx4L7T51Cw2X0b5FUZvNft9ut8PDwYuFGyUbG5XG5XHK5XHI6nWb4Y4wdNypvymK32xUZGSmHw6G4uDhFRERIkg4cOKCCggLl5ORIkvl1ZGRkmVU1gTAqb0JDQ4sdnaqpypm6Gv8OAAAAAChSLwKc8sKbvn37lpruUxLhTfCp6d+Jz+czA4aYmBhJMhvxGqGFfwBhPH+gx43S09OVn5+v9PR0MxwxricVBTIGIyjxeDzKzc0tswFwVFRUsTDEP2CpaB9GlU15Y9LLCliMYCstLc2s4KlOkFPZ3gAAAAAAtateBDihoaEqLCxU9+7dlZ+fH3B4g8bDv4qmrOM+/s2H09PTzTAjkKqS+Pj4YuGN//WM58rMzFRsbKz5nJWNNPf/mfF1eT1w3G630tPTlZGRoaZNmxZ7THnXNBiv0TiexREoAAAAAKif6kWAI0k//vijdu/erTfffJPwBia3211q3HVFwYx/sBIfH19mbxv/ihijr4wR3pQ84mQ8l3GMynjO6hw5Kjllynguj8ejw4cPy+v1Ki8vTy1btgz4mkawU9l+aFIMAAAAAMGt3gQ4PXv21B9//KHo6GjCG5jcbrc5CcoIHyrqaVNZkGFMloqMjFT79u3NwOfgwYNq2rRpqQoWt9tt9scpq0KnJCMo8d+Pf5WQf2jjP7o8JCREVqtVTqez2kegKnpcRRVDAAAAAIC6V28CHEnm8RHAX15eniIiIgKqdqksyCjJCHz8e9/4c7lcysvLk8vlKhbglMcISvbu3SubzWYGRca1/a/vf5zK6XSaTZprA02KAQAAACC41asAByhL69ata2R0tlR0DMs/SKks8HE6nWYFTiCMoMRut6uwsDDgfflX59SGqgZbAAAAAIBjiwAH9VpNV45UNciIj48vt/KmrL4yJXvSSDKbKvs/b8kJWSWrc1D7UlNT5XK5KlyTkpJyjHYDAAAAoLEjwEG9FsxNdwOZRFXWxCzj/ooqbmg6XLtSU1OVlJRkNpSuiN1uD7gCCwAAAACqiwAHqCX+1UHlBS7lVRBVVnFD0+Ha5XK55PF4tHz5ciUlJVW41ul0KjEx8RjtDAAAAEBjRYAD1BL/41gVVdoEGsC43e5iR6poOlz7kpKS1KNHj7reBmpJIEfgCOgAAAAQLAhwUO9ZLJaA1vl8vlreSfnKq8aRVGZlTlnjxo2+OMZUrMqCn0DfF6CxcTqdstvtSk5OrnSt3W5XSkoKIQ4AAADqHAEOGp266B9TXjWOpDIrc4wjUpmZmYqNjTX3S9UNcPQSExOVkpISUJPq5ORkuVwuAhwAAADUOQIcNDqB9I+pSshT1UCoZBBTXg8ct9stp9Mpt9utvLw8ORyOcideAaiaxMREQhkAAADUKwQ4aHQCqWTxD3mM78sLaKraULhk35uyHlNyDQ2LAQAAAKBxI8BBoxNI42D/kKeygKa2jjb598EJDQ2t0vX9q4I4cgUAAAAA9V+jDXD27dunwsJCuVwudevWra63gyBTMuSpKKCpyiSpqjCCo9DQ0CofnfIPnQhwAAAAAKD+s9b1BurCG2+8ocsvv1wnn3yyzjrrLC1fvryut4QgZrfbA5r6VNMcDkeVK29q4rEAAAAAgODT6CpwXn31Vf3rX//SzTffrEGDBsnr9erSSy+VVDRmmtHLKKkuplZJR1fZY7fbCW8AAAAAoAFpVAHOzp079eijj2r69OmaOHGiwsPD5fV6ZbUWFSIdTXiTl5envLw88/usrKyj3i+OjcoCmqo2Ka7o+sb1jnUYBAAAAACo3xrVEars7Gz98ccf6tKli8LDw+Xz+WS1WvXNN99o+vTp6tevn+666y699957Vb727NmzFRMTY94SEhJq4RWgNpScOFXS0R5H8r9+Zc8FAAAAAEBZGlWAk5qaKrfbrRYtWkgqqrhZs2aNLrjgAr3xxhtKSUnRwoULNWrUKM2dO7dK1546daoOHTpk3nbv3l0bLwFl8Pl8Ad0sFkuZN/+ApqwqrPJ64JR3vYquX/K5/G/BLtD3GQAAAABQ8xrVEaqTTz5ZMTExeuqpp7RixQr9+9//1s0336wJEybon//8pyIiIvT1119rzJgxeuaZZ3TWWWfpzDPPDOjaNptNNputll8BakNtj9ouef3aGjfOsazApKamyuVyVbgmJSXlGO0G9UEg/x6cTqcSExOPwW4AAADQWDWqAKdt27bq1auX3n33Xb355pvat2+fhgwZokmTJpkfqocOHSq3260bb7xRX375ZcABDlBXjrZHT2OSmpqqpKQkeTyeStfa7XY5nc5jsCsEK6fTKbvdruTk5ErX2u12paSkEOIAAACg1jSaAMfr9SosLExPP/20+vbtq8cff1zR0dHq06ePHA6HvF6veZTlrLPOks1m086dO+t620ClHA5HsSbJx0J9rfpxuVzyeDxavny5kpKSKlxLRQUSExOVkpISUMVWcnKyXC4X/2YAAABQaxpNgGO1WuXz+XTiiSfqscce04QJE+RyudSmTRtzEpXRvyMrK0utWrVSjx49JDFevL7zDxsa4mjtoxk3Xl31veonKSnJ/PsGKpKYmEgoAwAAgKDQaAIc6X9jwi+55BJ5PB498MADeuedd3Tqqadq7NixCgsLU0ZGhhYsWCBJuuCCC4o9DvWTf9hwNAFOfa06qQ11UfVTGXrboK7RKwcAAAC1qVEFOIbY2FgNHz5cTqdT48aN04QJE7Rs2TK1adNGWVlZ2rZtmz7++GNGgTcQNRU21Peqk5pUF1U/FaG3DeoSvXIAAABwLDS4AMc4DlWZ6OhoXXnllTrnnHP0+OOP67///a9yc3P1j3/8Qy+++KJOOOGEY7BbHAtG2HC0lVR1VXVC5Y/0008/KTIystz7U1JS6G2DOkOvHAAAABwLDSLAeemll7RlyxbNmzdPVqs14BCnsLBQ8fHxeuSRR47BLlHf1VXVCZU/Ut++fStdY7fb1adPHz4Yo05UpVdOTR3lO3z4cI1cBwAAAPVDvQ9wtm3bphtuuEGSFBoaqieeeKLSEKegoEChoaEKCQmRJB05ckRhYWGSaq5hsX9DZNQu472uTKC/15q+XqDKe97CwkLl5OTIbrdX6d/TsdqfwePxyOPxyG63V1qlZLyOyq5p3D9v3jx169atwrVxcXGKjY3lbw5By2azKSIiIqCjVlUR6P9mAQAAoH6r9wFOWlqamjRpovbt22vu3LkqLCzUU089VWGIExpa9LKXLFmiESNGmOGNVHMferOzsyWJPjpABbKzsxUTE1Ph/ZJ05513HqstAfVOZX9HAAAAaBjqbYBjVMp8/vnnOuOMM/TUU0/p5ptv1tNPPy2LxaK5c+dWGOKMHTtWCxYs0LZt2/Too4/W+P5at26t3bt3KyoqqlqhUFZWlhISErR7925FR0fX+P5qWn3br1T/9tyQ9uvz+ZSdna3WrVtXeI2q/B3Vl/eHfdac+rBHqfb2GejfEQAAABqGehvgGB/mXC6XQkJC1LVrVz399NO6/fbbNW/ePEmqMMSZPHmyvvnmG40cObJW9me1WtW2bdujvk50dHRQfzApqb7tV6p/e24o+w2kYqA6f0f15f1hnzWnPuxRqp19UnkDAADQeNTbAMfQs2dPdenSRZJ0xhlnaP78+RozZkypEMeo2PH5fMrPz1dCQoI2b95s9sEBAAAAAAAIVpWPagpy//znP3XVVVeZ359++umaP3++evbsqXnz5umuu+6SVFSxc/jwYc2ePVvff/+9JAU0qQoAAAAAAKCuNYgEwyghNyZx+Ic4Tz/9tMaNGydJmjp1qqZNm6a4uDhJNT+lpybZbDbNnDlTNputrrcSkPq2X6n+7Zn9BtfzVRf7rDn1YY9S/dknAAAAgpvFV4/nj1Y0KlySvv/+e9122236/vvvdfzxx2vfvn366quv1L1792O4SwAAAAAAgKNTbytwCgoKzN42W7duLXaf1+uVVNQf58knn1RYWJgyMzO1adMmwhsAAAAAAFDv1MsAp6CgQKGhofJ6verRo4eWLl2qrKws836jKsfj8eidd95RWFiYNmzYoFNOOaWutgwAAAAAAFBt9W4KlX9406tXLx04cECXXXaZoqKiSq275ZZbtGrVKn3zzTfq3LnzMd2n1+vV3r17FRUVFdS9doC64PP5lJ2drdatW1d4DJK/I6B8/B0BRy/Qv6P/x959xzdR/w8cf6VpmybpXsyWgiiUPQRlKgiIuEAQAQERBHErDhwoiCJDQEUZAuIAUUFQBBFF1K+CgymzIggdzDYpnUnTNs3vjz7ufkmatmlpKeP9fDzyoG0ud5fLXfTzvvfn/RZCCCEuBpdUAMc5eHPttdeSlZXFRx99RPfu3T3+T2loaCi//fZbjUybOnXqFDExMRd8u0JcSlJSUqhfv36pz8t1JET55DoS4vyVdx0JIYQQF4NLpoixp+DN4sWLueGGG9BqtTW9eyVkZmYSGhrK4cOHqVWrVpnLyh1RcaXJysoiJiaGjIwMtYucJ8p1lJKSQnBw8AXcQ3G+HA4HFosFi8WCwWDAYDB4XE6+/ypPriMhzp+315EQQghxMbgkMnAuteAN/P+gpFatWuX+D7MMYMSVqrxzX3k+ODhYBp6XGIfD4dVnJt9/50+uIyHOn3wXCSGEuBRcEgEcX19f7HY7bdu2JT8//6IP3gghhBBCCCGEEEJUpUsigAOwZ88eUlJS+PLLLyV4I4QQQgghhBBCiCvKJRPAufbaazl27BjBwcESvBFCCCGEEEIIIcQV5ZIJ4ACEhYXV9C4IIYQQQgghhBBCXHA+Nb0DQgghhBBCCCGEEKJsEsARQgghhBBCCCGEuMhJAEcIIYQQQgghhBDiIndJ1cC5FGk0GjQaTZWsy+FweL1NIYSoiKr+fpHvISGEEEIIIaqWZOBcQiwWC2lpaVgslpreFSHEFUK+d4QQQgghhLg4SADnEpKbm0thYSG5ubk1vStCiCuEfO8IIYQQQghxcZAAziXEaDTi6+uL0Wis6V0RQlwh5HtHCCGEEEKIi4PUwLmEGAwGDAZDTe+GEOIKIt87QgghhBBCXBwkA0cIIYQQQgghhBDiIicBHCGEEEIIIYQQQoiLnEyhEkIIIYSoAsnJyZhMpnKXi4yMJDY29gLskRBCCCEuJxLAEUIIIYQ4T8nJycTHx2OxWMpd1mAwkJCQIEEcIYQQQlSIBHCEEEIIIc6TyWTCYrGwYsUK4uPjS10uISGB4cOHYzKZJIAjhBBCiAqRAM4VzOFw1Mh2NRpNjWxXiJp0sV9v3i7n7fuQ61xcTryZGpWQkABAfHw87dq1uxC7JYQQQogrjARwRKksFgu5ubkYjUZpIyzEBSTXnhAXj4pOjYqMjLwAeyWEEEKIK5EEcITKfdCYm5tLYWEhubm5MogU4gKqzLUnQR8hqoe3U6NAihMLIYQQonpJAEeo3AeNRqNRHRAKIS6cylx7EnAVonrJ1CghhBBC1DQJ4FxCqvsOu/ug0WAwyEBQiBpQmWvvYgm4On9P1fS+CCGEEEIIcTmRAM4lpLrvsEvARohL18Vy/Tp/T0kARwghhBBCiKrjU9M7ILxnNBrx9fWt8UGRxWIhLS3Nq4KOQojSXY7X0sXyPSWEEEIIIcTlRjJwLiEX4x328vZHCqsKUbrc3FyysrJIS0sjLi7usrhGlO8paSMuhBBCCCFE1ZIMHOFRWZkBFbnD7hzsEUK4MhqN2Gw2dDpdpa+RyzGLRwghhBBCCFGSZOAIj1JTUzl79ixarZZmzZq5ZAZUJBPoYimsKsTFyGAwEBcXV6lrRMluy83NVQNABoNBst6EEEIIIYS4TEkA5xLi7ZQEh8NRJdvLy8tDr9efV9Fk92BPRQaXVf1+ZUrHpcvhcJT7OV/o66OqAiWVnRqpZLcBLhlx7lMcq+r9VpRcl0IIIYQQQlQtCeAIj6Kjo11+T0tLq5I7+tXdSUuIC6U6z2VvgkNKdltISIjLMpL1JoQQQgghxOVJAjjCI2VqBxQHb6qqaHFNDC6d90kGtZe+i2WKUEXP5YrstzfBodIydy6WYudCiLIlJCSUu0xkZCSxsbEXYG+EEEIIcSmQAM4VpjKD34oMVMsbeCqDS6Xw6oUYhDvvkwRwLn0XSxZXeYES92utIvtd04FOCQAJUX0iIyMxGAwMHz683GUNBgMJCQkSxBFCCCEEIAGcK05Zg8jSBnDKz0qXnLIGd94MPC0WC4mJieh0unLXVxVkSsnl5VL5PN2vNW/3uzoCKaWt0/nvF0tgTIjLXWxsLAkJCZhMpjKXS0hIYPjw4ZhMJgngCCGEEAKQAM4Vp6xBpHvLb+flvA24eDN9Q+maY7PZLsggXNknKZZ6ebhUpgi5X2ve7ndlAinlBWjcO1V52talEhgT4nIQGxsrQRkhhBBCVJgEcC5TZWXTlFcU1f1uPFAi4HI+WQLKOqqqKLJM+xDno7qmDlU20ORtFps307NK61TlaVvVFRiTqVlCCCGEEEJUDQngXKYqcxfffQDnaRDpnJ1T2ekWVTlQlGkf4nxdbOeQt1ls3kzPUv7u6+v5q/5CZDNdbMdXCCGEEEKIS5UEcC5j586dIyoqSv3dYrGQmpoKFLcJr8hUKIPB4NKN6mKabuH+PoWoCOVcBi5YYe3z5e30LOXvFekkp1AyZ5y3Wdpry8qyuZi+K4QQQgghhLiU+dT0DojqExYW5vJ7bm4uOTk55OTkuAzM3CkdoiwWi8vfjUajOg3DYDAQFRXlcUBX2uuri/v7FKIilHMZcJk2eL6q8zoo6/rztG3na9dbSuaMc/CnvGU9LVPevgohhBBCCCG8Ixk4lylPd72NRiOBgYHqzw6Hw+NrnQdjer1eLf5bnUVYPSlt/5xV5O6+N+sDpNjxRUij0ZT7uZzv5+t8Lmk0Gq/XV5qanDrkvu3KTJUyGAxYLBY1uFVexp7FYpEgjRBCCCGEENVIAjiXKU8DNoPBQFxcnPq7w+HAZDKRkpKCXq9XO2Iod+2Dg4MrtW2j0Uhqaqpa9Lg6B3WXSkcicfEzGo1VOs2nOoMaypQlpf6NN9uuaDFh9+ORm5tLWlqax21V9bETQgghhBBClCQBnCucyWQiKysLk8kEFA/G/P398fX1LVHQWBkQljdQU5apyuwD6WQjLmaero/qDGooGTYWi8XjNjxtOzc3V73WGzRoUOHryGKxUFhYSEZGBqGhoeq/JpPJ6+8GIYQQQgghROVJDZwrXGRkJMHBwRiNRnQ6HUCJ4A38/+BNCaSkpaWpD/e6F8oyzm3HvVVa3ZCyamxc6Jo7QrizWCxkZ2eTnJxc4hxVrpeqOj+dr6/SgjDKNt2LEOfn5+Pv7+/xOvL0GmcGgwFfX18iIyNd/gXU7wYhhBBCCCFE9ZEMnCtcZGQkkZGRWCwW9S56ad1sTCYT+fn5WCwW/P39S9yBV7JjcnNz0el0HgNB5XGv3eHcCae0IqzSplhcDE6fPk1ISEiJrBgl+FlV56fz9eU+xUm5hp0Drs6dqho0aFCiZpRyjSnrrUhWj/t2hRBCCCGEENVHMnCEV5TgjN1ux2w2k5+fX+IOvBJoqUzHG+ftOL9WCc4ApXayOZ/tCVFV6tSpg1ar9Vh7qirPT+V8LytLTtmmp31xv46crzHlei4tE6e0zJ6oqCi5/oQQQgghhKhmV3QGzh9//EF4eDhNmjSp6V2pcSaTiezsbIKCgtRixu6ULJzQ0FCX1svKHXjnO/2VvRvv/lpvukw5v6YytXKkvs7loTo+R2/XqTxXq1atEudqdRRHLi1LzrkWjbfbVK4xZSql0jbcUyaOp8weZxWplSWEEEIIIYSomCs2A2fRokX06dNHLd57OatIjRiLxaJOiXJnNBqJjIzEZrOd1z6U9rMnnjIGylJWrZyqfI24+FTH5+jtOs8nC6Wi12diYiKJiYkl9knZByg9g8YT5RpzDsAq2TvuGTelZfZA8bFKTk4mOzvb43uRWlVCCCGEEEKcnysyA2fp0qU89thjzJ07ly5dutT07lQ7b2rEREZGlqidAXi8mx4aGuryWiV7JzAw0KVNuXP2gvtA2NPPFWl57P68N7VySuNNlo+4+FX15+h8ToWEhFR6Pc4Zap6mPSUmJqoFxMsLVObm5pKTkwOUntmTlpZGTk4OgYGBlZ7GqBzL5ORkdd+Uv5e2TovFgt1u5/Tp0wQFBXncd6lVJYQQQgghROVdcQGcpUuXMm7cOObPn89DDz2k/t3hcKDRaCq9XpvN5pKZkpWVdV77WZUqMrBVBlaeCqEqA1GA4ODgMtdjsVhISEhQB5KxsbElatt4+llR3mDP/Xnld19fXzULwVvnM+VLVK3zuY6q+nM8n2LczsoqYqxsw9uObUajkcDAQKD0YI/VaiU9Pb3EOt2Dnc4BJeVvzsFai8Wi7lutWrXK3TeDwYBWq6VOnTql7rsESoUQQgghhKi8KyqA8+GHH/Lggw+yYMECHnzwQeD/Azf5+fk4HA5yc3OJiIio8LqnT5/Oq6++WtW7XCVKG9g6B6yUQaZzAESj0ZCamorNZkOv16vdp2w2G7m5uTgcDgwGAxEREej1egwGA0VFRQDk5OTgcDjIzs5WB24Gg0HNHtDr9eqdfeVfu92u7o/D4SAjI4OIiAh1nc6U/VH+rUimRHnZPQ6Ho9x1uB8/UTVKu44cDofXn4sn3tSycV+mqgIOStAEirNjnK9H53/1en2571Gv19OgQQOg+HopLCzEbDaTnp5OeHg4ERERBAQEEB4eTn5+Pvn5+WRlZREaGkpubi56vd4l+KnX64H/D4i6d5Oy2Wxqdp6yb851bpyX1ev1xMTEqNelp+NwPtebt+S6FEIIIYQQl6srpgbOt99+y5gxY3jllVd48MEH0Wg0FBUVodFo+O2333j44Yfp2rUrPXv2ZNq0aWRkZFRo/S+88AKZmZnqIyUlpXreSDVQBq7ud+yVQazSWli5ww7Fg0dlUGowGNRBnvtrw8PD1XUqHayUQafZbHaZquX8O5QdjHHeppLF4G3xWql5c/GqruvIm8/cfZmK1l8qjXNtGufpico23K8dd0pdKuXhXkMmPT2drKws/vvvPywWCxEREURFRVGvXj18fX3VbnHOwSL3rKLSatu4T5dU9sf5+nfmzfsp7T1KfRwhhBBCCCHKdkVk4BQUFHD8+HF0Oh3bt2/n2LFjNGrUCB8fH9asWcPIkSOpX78+kZGRHD16lJdffpljx46xePFiNWBRHp1Op2aS1KTc3NwKd+LJzc3FbreTn59f4jmj0UhOTo5691zJJlCKP7vfsVcomTmhoaFqa2VlcAmQn59PdnY2ZrOZ+vXrY7VaKSwsxGq1quvLzMx0yYZSih5XplOV+3uSqRwXp+q6jrz5zKv7vHDuEqVwPqeV393PbyU7LiMjg9DQ0BLrCAgIICkpiYiICKxWKxERES7Pu3+HecqE8bRNJZDlPl3S0/vwpCJdwc6nPo50kRNCCCGEEFeKKyKA4+fnx7333ouvry/PPvssDz/8MB9++CGJiYk89NBDvPjiiwwfPpwGDRqwc+dO3njjDT788EOuv/56xo4dW9O7XyGVGQgZjUZMJhP+/v4lXmcwGAgICFB/VwacgEtmTmmUaVDOA1S9Xo9er+fIkSMUFRVhNpvVwacyJerEiRMUFRW5TMVwrsnjvo8VGbhJzZsrjzefeXWfF57W73xOK8FXHx8flywW5XqLjIxU1+O+XqPRyKOPPopOp2PhwoVERkaq0xq94R4cVTpPeQqKeHucKvJddD7BMymOLIQQQgghrhRXRAAHICwsjKFDh1JUVMTEiRO57777aN68OSNGjOCpp55S/8f/2muvZcKECXzzzTf8+uuvjB492ussnItBZQZCBoOBBg0aqK9zvqMNqBk4ACkpKeh0Onx8fNTMGk+UKVFKgEa5a2+329UsgfDwcEwmE+np6WodHavVisVioaioiLy8PKxWKyaTySUrR6/Xq38rLWtAORYyoBMVVVZGR1paGmlpaURFRXldLLu0mjGKjIwMNTgDqNloSuDG399fnQrlaV/37NnDqFGjSE1NBaBz58707duXIUOGcOutt5b6/eUctHEPjiqFkH18yp5l65yNp+yfc+e6ihRPr+y1Khl1QgghhBDiSnHFBHCguKbKvffei0aj4aWXXmLLli0sXLhQHTjY7Xa0Wi1du3albt26FBYWXlLBG6hY0MJisaiDvujoaHVAmpaWRmFhIampqVitVpcpLUVFRZw5c4bGjRu7DNjcB6hKB5szZ85Qu3Ztl4GiklUTERFBenq6S5CnsLAQKB4MWq1WrFYr2dnZ6vZDQkLIzMzE39+/RCaOcidemWpS0dbkQoDnjA7l3ElOTkar1apBHG84B0eU352vFaXOTFRUVIkaVM7Le7Jnzx5GjhyJyWSiZcuW+Pn5sXv3blavXs3q1auJiYlh2LBh3HvvvTRv3rzM/XIOJOn1esLDwz0WI3Zfh8lkwmq1qvtst9sxmUxqy3FvrjX3a7Mi16pk1AkhhBBCiCvFFRXAgeIAwJAhQ7BaraSkpKjdqJTgDcC+ffvQarV06tSpJne12uXm5qpdoZwHSsodbZvNpnadCgwMxGKxYLPZqF27troOi8VCSkoKubm55OfnU7duXXU9Pj4+hIWFYbPZ8PHxUQucKl1nDAYD4eHhnDhxQq1LZDAYCAoKwmAwqOs9e/as+tko06zy8/PJzMzEYrEQHR2tbjMjIwO9Xq+2o3Z+XzLVQnjDU0aHcu4oAQ334E1ubi5paWnqc8prlWlRAL6+viQnJ6sBUedzVpky5VxjymKxEBkZ6THzBuDAgQPcfffdmEwm2rZty6ZNmwgJCWHr1q2sXLmSNWvWkJKSwsyZM5k5cyYtWrRg2LBhjBw5kjp16rjUsrFYLGogSQnoOBdfdqZc8+fOnSMgIECtnZWenu5S6Lwi15r7tSnXqhBCCCGEECVdcQEcKJ5ONX78eJfaLsqgw2w28+677+JwOLjjjjtqahcvCKPRSGBgoPqzQhlIKgNZpS6NTqcjPDzcZaCZkpJCUVERaWlphIeHk5CQgJ+fnzro+ueffzh9+jQFBQXY7XZ0Op06qM3MzCQjIwOTyYRer6d27dq0bNmSFi1aEB8fj8PhUIM1SkCpdu3a+Pr6qlO0AgICXII0oaGh+PoWn9buA0Cj0ai2Ra9oppJk7lwazvezKu31yrUQFxfncb0Wi8UlGKpcT8p1o5yTOp0Om81GrVq11Nc6B07S0tLUrDTl+8m5gLjiwIED9OnTxyV4ExYWBkD37t3p3r07b7/9Nhs3bmTlypV89913HDhwgBdffJFJkybRvHlzQkJCCAoKIiIigpCQEAIDA4mMjESr1eLv7090dDTXXnttialJJpOJEydOYLFYCA8PJyYmxiVTLzIyEovFgtVqrXRhcZkWJS6U5ORkdRpgaRISEi7Q3gghhBBClO2yCuAUFhbi6+tLUVFRubUbnAdDv/zyC1u2bMHPz48dO3bw22+/8csvvxAXF1fNe1yzDAZDme9RGTQWFRUBxfVvnLtEKcEbHx8f4uPjsVqt5Obmkp2dzfbt23nttdew2WyV3j8/Pz9iYmKoU6cO9evXJyIigqZNm3LLLbeoAbesrCx1eedBX25ubonaIkpQqqJ39pVsgNTU1ApNCxFVr7wAzflmbpT2+vKm6RgMBjUYCpCYmAgUn5NK8EYpUBwbG6uuyz0LJjc3l6KiIjVrzWKxlJgueODAAW666SaPwRtnAQEB3HXXXdx9992YzWZWr17NypUr2bZtG/v37/fqePj6+nLLLbcwcOBAevXqRWZmJjqdDqPRiFarVetgRUZGqllDyr4qWXtpaWnlXjPux1emRYkLITk5mfj4eK/a1yvnuRBCCCFETbpsAjhfffUVP/30E9OmTSM4ONirII7D4SA7O5tnnnmG3bt3ExsbS6tWrfj9999p1qzZBdrzS4MymCooKODo0aPUrVtXzSaIiYlRn4+IiODjjz/m1VdfpaCggKZNm1KvXj2XwIcSSHHOLMjJyeHYsWMcP35cfRQUFHDs2DGOHTvmsi/R0dEMGTKEG264gVatWrnso/N0KSWzwZlzkMfbbA3nKWUyraNmlRegOd/MDeX1gFeBB+fXKdtMS0tzycaJiooiLS1NzcQpK1DhnBXn7+9Pfn6+y2u8Dd64i4iIYPz48YwfP56kpCQOHz7MuXPnyMjIICMjQ/3Z+W8mk4nExETWr1/P+vXradKkCffffz8DBw6kVatWalFy5/dht9tdgk0yFUpczJSg44oVK4iPjy9z2cjISGJjYy/QngkhhBBCeHZZBHD+/vtvBg4cqLanfvnllwkKCio3iKPRaAgODmbt2rXk5+cTFBSk1l+5kJSaMOXRaDTVsn3nLjnuA19lupPBYCAiIoLTp0/j5+en1qJxLnJqMpn47LPPePHFF7Hb7QwYMIDFixfj5+fnsk5vCkPb7XbOnDmjBnMSExM5duwYW7ZsITU1lXnz5jFv3jyaNGnCkCFDGDhwoNrJSq/XU1hYSHp6uvozoA6E3Ys1lze4dJ9Sphyjmv7criQajQaNRuPyGbgfV4fDcd6ZG8rr09LSyM7OxmQyERsbW2ZASMlQU7JPLBYL+fn56rlYVFSkdk6z2Wyl7qPBUNwNTgmCWK1WwsLC1GX37t3rMm1q3bp1GAyGcrPc3J8PDg6mQ4cOJZbzVLB43759LFmyhM8//5zDhw/z/PPP8/rrrzN8+HBGjhxJw4YNCQgIUKd8Wa1WAgICyMnJUQsb+/j4oNPp1OtQobzHwMBArwNu3gRda+q6lO+DS1d8fDzt2rWr6d0QQgghhCjXZRHAOXfuHMHBwYSGhjJ79mwcDgevvPJKqUEcZaoVFP9P95V+V825G41zFoFSFyA0NFQtqFqnTh31784dZwAWL17MzJkzcTgcDBs2jHfffbfSXby0Wi0xMTHExMTQvXt39e82m43Nmzfz+eefs3HjRg4fPsyrr77K1KlTue666xg0aBADBw4kJycHf39/zp0751Jg2fk9Ok9f8YZM66h5zpku1b0dk8mETqdzOWfKYjKZMJlMZGVlERcXp06Bgv+fvpednU1ycrLLNCpnSi0dvV5PRESE+ndPNW8uxLnYqlUr3n33XV5//XVWrlzJkiVLOHz4MIsWLWLRokV069aN0aNH07NnT0JCQtR9VgqQG41GYmJiPK7buV26c9Hn0oLJyvOS0SOEEEIIIa5Ul0UAZ/PmzbRp04ZPP/2UW265hTlz5gCUGsRRgjcvvvgiHTp0oH///lf0XVHnQIYygEpJScHHx0edTqIMzNzbC2dkZADwySefMHPmTAAeeOABZs2aVe4UtsrQ6XTcdttt3HbbbWRkZPD111/z+eef89tvv/Hnn3/y559/8tJLL9G7d2+ef/55QkJC1AyJU6dOuWTTXKhggLj0GAwGYmNjPQb43DtOKdeC1WrlzJkz6tRCvV6vZtNYLBZOnDhBXl4etWvXLrFeZZnc3Fw1w015fufOndxxxx0lpk2dT32pigoJCeGhhx5i/PjxbNu2jUWLFvHNN9/w22+/8dtvv+Hr60vt2rWJiYmhYcOG1KlTh6ioKBo3bqwWRFa+Y5XMG/j/7+K0tDT1e8g9qONMihsLIYQQQogr2WURwElMTMThcFCvXj1WrVrF3XffXW4QZ/369cyYMYPevXtz8803X9F3c93rdzi3Sy4qKiI3N1cdULq3Ow4NDeWtt95i9uzZADz22GNMnTr1ggTEQkNDGTVqFKNHjyY5OZkvvviCzz77jISEBDZs2EBqaiqrVq1SB8Tp6emkpaWp762sO/1CKNeFc8AGigM4zjVulPNJ6aTm4+OjZp0oGThHjx5Fq9USEBDgcZqmEriA4qCGXq/H4XCwbNkyXnjhBTIyMipU86a6aDQaevToQY8ePTh58iRLly7lgw8+4MyZM5w4cYITJ07wxx9/lHidMj2sZ8+eTJgwAX9/f3x9fYmIiODcuXNq0Ka8rDjJghNCCCGEEFeyqk+RqAGjRo1i5MiRADRt2pS1a9fSvHlz5syZw9SpU8nOzsbHx8elRkGvXr145513ePfddy+KAYHSrcWbbhjVvV6le1N8fDwRERFYrVaKiorUgZVzEGfFihVq8GbixIkXLHjjLjY2lmeffZZdu3axfv16goOD2b59O7feeiv//fcfVqtVrT8CrtPGhCiLcq6YTCY1yBIYGEhgYKDL+QTFhU6vueYa9fpQutb4+/tjNpvR6/VqQMj53DMYDPj6+hIVFYVOp+Pzzz/n+uuv56GHHiIjI4Prr7++xoM37urVq8fkyZNJTEzkv//+Y8uWLSxdupRJkyYxfPhwunbtSv369dFoNFgsFhISEpg/fz4DBgwgLy9PDXwp7x2qL6haXd+vF3obQgghhBDiynZZZOD06dOHvLw89ferr76atWvXctdddzFnzhwcDgdTpkwhMDCQ7OxsZsyYwcCBA3nsscdqcK9dVVdtB0/rVaZqlDZQcu7eFBkZqQa+DAYDJpMJs9msBnamT58OwOTJk3nqqaeqbL8rS6PR0KtXL3744QfuvPNODh48yIABA3j77bfp0qWLmlGRnJysTpMpi7edqsSlr7TPWskKUYIxwcHBLhlrycnJQPF1o7TVdqZcZ02bNsVms6nTEp23YzAYOHz4MEuWLGHlypVkZ2cDxVMGJ02axNNPP60GOS42SsZRTEwM3bp1K/F8fn4+ycnJ7N27l8cee4x9+/Yxfvx41q9fD6Aey+TkZHQ6ncvfKqKsa/VC1M6R+jxCCCGEEKK6XRYZOAABAQEuvytBnObNmzN37lxeffVVUlNTeeWVV5g5cyb+/v41tKeeGY1GfH19q/zOs6f1KgMNT3eKlbvhygDEaDSqGTcAZrOZ/Px8zGYzr7/+OhkZGbRq1YoXX3yxSvf7fLVu3Zpff/2Vli1bYjabeeCBB1i/fj0GgwGr1aoWVy7veDsPykojd94vbt5+PqV91korcOXhfM6YTCby8/PVc6q07lIxMTEEBQURGRmpTs0yGAzk5OSwdOlSOnTowLXXXsv7779PdnY2jRs3ZsaMGRw7doyJEydetMEbb/j7+9O4cWMGDhzIunXr0Ov1bNmyhaeeekoNDlssFnQ6nVp0vKzrrTRlXavV9f16obchhBBCCCGubJfuqMALzpk477zzDuvWrePkyZNs376dFi1a1PTuuaiu2g6e1qtkoXjanqfCvhaLRS3GGhERgdls5tSpU3z00UcAvPnmm5XuNlWdYmNj2bJlC/fffz/ffvstTzzxBMnJyTz77LOYzWY1o8KZUsRZGWB7UzRV7rxf3Lz5fJTsDSgu2OutyMhITCYTERER6vmUlJTEnj171HUq55Tyu/JvdnY2v/76q5pt4+fnx1133cWYMWO44YYbLsvC6h06dODjjz/mnnvu4f3336dRo0Y8++yz6ueitBz3tvOXs7Ku1QtRO0fq8wghhBBCiOp2WQdwoDiIs3LlStq0aYPZbObPP/+kZcuWNb1bNaq8gYZ7K19lCokiJiaGJ598Ervdzm233cZNN910IXa7UoKCgvjiiy+YNGkSb7/9NnPmzCExMZE5c+aU2sbZebDvzaBMOuNc3LwNwul0OpfsM29ERUW5tPtevXo1o0aNqlCHqKuvvpqxY8cycuRIoqKisNvtXr+2PA6Hg6ysLM6dO+fyiIuLo127dlW2nYro378/s2bN4tlnn2XixIk0atSIgQMHunzXOHfE87YmjgRQhBBCCCHE5e6yD+BYLBaWLl1KQEAAv/76K82bN6/pXaox3tZzcW/lqyybkpKCTqfj119/ZfPmzfj6+qqtwy9mWq2W6dOn07x5cx566CHWrFnD0aNHWb58eYlMLGUA6TxgLO+4ycDx4uXtOX++QTiHw8HcuXOZOHEiAM2aNaNOnTolWtY7/67X62natCndunU7r2wbh8PBnj17WLt2LYcPH+bcuXOkp6erwZrSAkI33XQTL730Eq1atar0tivr8ccf59ixYyxcuJARI0ZQr149rr/+eo8d8SqTjeMNJTvKU9ahEEIIIYQQF6PLOoBTUFDAxIkTmT9/Prt27bpogzcXaqqEt1N93Fv5ZmZmcurUKYqKikhNTVXr3YwbN46GDRuSn58PoHboKc/hw4fVn1NSUpgxYwZJSUnUqlWL2rVrU6dOHWrVqkWDBg2oU6cOdevWJTAwsNT1eTv4GjZsGDExMQwbNoy9e/fSt29fvvjiC5dMBB8fH0JDQzGbzSQmJhIeHg6A3W7Hbrfj5+enLuv8c1mcu5+V5XKcMlPTcnNzycrKIi0tjbi4uAq1p/Y2EyYjI4Nnn31WnVI4fvx4Zs+eXWJaYWnXh9VqdfndbDZ7td09e/bw3XffsWnTJrWQcmkCAgIICQkhNDSUwMBA9u7dy5YtW9iyZQu33norTzzxBM2aNfNqu1U1XfLFF1/k6NGjbN68mTvvvJP169cTHx+vfg4BAQFYrVYcDgepqaleFxL39jqq6qmPcv0KIYQQQojqdlkHcCwWC3l5eezevZs2bdrU9O7UOG+zDNzvSFutVvz9/cnPz2fjxo0cPXqUsLCw8y5c/NNPP/H666+rtUfS0tI4cOCAx2WDgoKoU6cOjRs35vrrr+f666+ndu3aFd5mt27d+OWXXxg0aBD//vsv3bp1o0mTJvTp04e7775bDeakp6eTn59Peno64eHhZGZmqsEccekwGo2kpaWh0+kqNFBXsjMMBoPa7rq05e69915++OEHAGbMmMHjjz9ebYP5lJQUvvnmG9avX88///yj/j0gIIAbbriB6667jtDQUEJCQtRHVFRUiSLvycnJvPPOO3z77bd8++23fP/999x777088cQTREdHV8u+u/P19WXhwoUMGjSIv//+m3vvvZcNGzbQuHFj4P+DamazWc3EqcpMN5n6KIQQQgghLjUah7fpAZeogoICrzMlqlJWVhYhISFkZmYSHBx8QbddVR+p0m47PT2d0NBQdDod1113HefOneOtt97iwQcfdFne2y5M//zzD/PmzWPVqlUAtGrVioceeohz585x5swZ9ZGamsqpU6fIysryuJ5GjRpx/fXX06NHDzp27Fhmlg7gEvDJyMjg0Ucf5ZtvvnHJtIiLi+OOO+6gT58+xMbGEhkZSXp6OqdOncJgMNC8eXN1EFmZ86qsKT1X0h18b6+PilxHzlNinI9tZVrBJyYmkpOTQ2BgIDExMR6XOXv2LP3792fnzp3odDqWLVvGXXfdVeo6vc1Qc8/ASUtLY8OGDXzzzTfs2bNH/buvry+dO3fmlltuoUePHqW+t7I67iUkJDB37lx+++03APR6PWPHjmX8+PGlHu+qLlien59P165dSUlJoUuXLnz//fdqO3EoPh5ms9nl/Tl3xnNXU9dRTWy3Oq6jK8nu3btp3749u3btqrGaUGW52PfvciHXhxBCiEvJZZ2BA5UbZF8JlEFtWQVClfbLRUVF5OXlMWPGDM6dO0fLli154IEHKrXd5ORkxo0bx6FDhwAYMWIE48eP99gmWcl8yM3N5fTp05w6dYp9+/bxxx9/cPDgQY4dO8axY8dYuXIlvr6+tG3bli5dutCtWzdatmxZ5kAzNDSUFStWYDab2bhxI+vXr+fHH38kMTGRefPmMW/ePOrVq8cdd9xB69atCQkJISsrS61rUlnSsar6lHZsva1RlJaWhslk8tidzN2+ffsYMGAAycnJREREsGrVKjp37nxe+++uqKiI5cuXM3PmTDU46uPjQ6dOnbj99tvp0qVLhTpmeRIfH8+SJUv466+/ePvtt9mzZw/z5s3jk08+4bHHHmPkyJFlZiBVhbp167Ju3TpuuOEGtm3bxgMPPMAnn3yiBkSULnhms1kN7FRV3anKBPeEEEIIIYSoKZd9Bk5NudgzcJQCob6+vkRFRXlcRsnAsVgsnDp1iv79++NwONi8eTNdunQpsXx5GTjZ2dlcd911pKamEhwczOTJk+natWupy5c1cMzKyuKvv/7izz//5K+//ipRA6R27dqMGzeOe+65R50+Ut6Uq+zsbDZv3sz69evZuHEjOTk56nNXXXUV8+fP5+qrr6Z+/fqAZOCcjwuZgeOthIQEbDYbOp2O2NjYUqdQZWRkEB8fj8lkolGjRnz99ddcffXV5a6/Ihk4OTk5PPzww/z6668ANG/enEGDBnHrrbeqU5xKy0xzV1YGjjOj0cj333/PzJkzOXLkCFB8ToaFhREZGak+lM5bUVFR6t9iY2MrPfVKCZj9+OOP3H777RQWFvL666/z2GOPYbVaMZvN2O12tFqt+rlWVQaON9+D3pIMnEvPxZ7hcrHv3+VCrg8hhBCXkss+A+dK5M1dZaX+Q3ndqADq1KlDfn4+DocDjUbjVYaCJ/v37yc1NZWwsDA+/PBD6tSpU6n1AAQHB9O7d2969+6N0WgkKSmJbdu2sXXrVv744w/OnDnD1KlTWbhwIWPHjmXo0KHlrjMoKIi77rqLwYMHk5eXx08//cS6detYu3Yt//33H5999hlvv/12pfcZpGNVdTrfYxsZGalm4BiNxhJ1YxRWqxWTyQTApk2bSp1iVVmpqamMHj2aAwcOoNfrefHFF7n33nvx8fGp0u2402g09O3bl969e/Pll18yd+5cTp48SXp6Ounp6fz7779lvr5WrVq0atXK5VGROlW9evXinXfe4ZFHHmHSpEkkJCQwceJEAgMDMRgMLgES5bvJfaqce+e88pxPHRzJ3hFCCCGEEBeaZOBUk5q8o5Oamlold5V37dpFVlYWwcHBNG/enMGDB7NhwwaGDBnCsmXLSixfXgbOt99+y3333UfLli1ZunRpudv3duqG++DLZrOxZs0aFi5cyKlTpwAIDw/nqaeeYuzYsQQFBZW5PvfpXD///DN9+/YFYNWqVfTu3RtA7b6l7MP5DuIkA6fyy8H51X7Kzc1Vi+Qq51NOTo76N/dzMS4ujpMnT/LTTz/RqVMnr7bhTQbO0aNHueOOO0hJSSEiIoJly5bRunVrj8tWdQaOew2poqIizGYzJpNJ/Vf5Wfk9LS2NtLQ0tUudu+joaFq1akXLli1p1aoV119/PaGhoS7LOAeEHQ4Hjz/+OIsWLQIgLCyMl156iUcffZTMzEyys7M5fvw4wcHBREdHExsbq77WZDJVWTaNN9yzdyQD59JzsWe4XOz7d7mQ60MIIcSlRDJwLkPe3FUurwZObm4ueXl55Ofnq5kIL774Ihs2bGDVqlVMnDiRJk2aVGi/zp07B1Dt/4Ok0+kYNmwYgwYN4uuvv2bBggWkpKTw8ssv89Zbb/HYY4/x4IMPel0/pEePHowdO5YlS5bw1FNPsXLlSoxGI6GhoeqUG5PJRIMGDeRO/CXKYrGonY6U68H5b3q9HqvVqgYp27Rpw8mTJ9m+fbvXAZzy7Ny5k0GDBmE2m4mNjeWTTz4hLi6uStZdGT4+PkRFRZUIhniqLWWxWDhw4AD79u1TH0eOHCE1NZUff/yRH3/8ESgO6Pz++++lfjdpNBreffddhgwZwhNPPMHevXt55plnWL58ObNnz6Zu3br4+/uTl5enblf5TJR/bTYbaWlpHve9KkkXK3GhJCQklLuMMpVRCCGEEJe36s3JFzXCYDAQFRVVZjBBKfhaWtaMxWKhTp06xMbGUrduXaB40HrLLbdQVFTEzJkzK7xf6enpAOddeNVb/v7+DB48mM2bNzNr1iwaN25Meno6r776Ks2aNWPatGlqUKk806dPp0GDBpw8eZJ58+Zht9ux2WwAHDp0iOzsbLUdurg0ZWRkAMXXRlpaGlCcjWUwGLBaraSkpJCdnY3ZbKZZs2YAbN++vUq2/f3333PrrbdiNptp2bIla9asqdHgTUUZDAY6duzIAw88wLx58/jll184cuQI69evZ9q0adxzzz2EhYWRmprK6tWry11fly5d+Ouvv5g3bx6hoaHs3buX3r178/rrr6PX69UOcUqQzWQy4e/vj8FgwGKxqEGc6n7P5X3PCnE+lFpPw4cPp3379mU+4uPjS9SCE0IIIcTlRwI4Vyij0agOTt0pxWB9fHyIjY11mT7yxBNPAPDFF19w4MCBCm1TGSBf6BRlPz8/Bg4cyO7du1m2bBlNmzYlIyODN954gzZt2rBt27Zy1xEUFMT7778PwJo1a/j333/VFuNGo5GsrCx1Gg78fwcvb1uri5qnTO1JS0vj7NmzWCwWIiIiAPj3338xm81kZmYSERFB8+bNgaoJ4Cxfvpx77rkHi8VCr169+Pzzzy/IFKDqZjAYuPbaaxk9ejRvv/02zzzzDABLly71ON3KnVar5aGHHuLQoUOMHj0ajUbDZ599Rq9evfjqq68oKCjAYrGQn59PZGSk+n1mMBjIycmRwIq45MXGxpKQkMCuXbvKfKxYsQKLxaLW5hJCCCHE5UumUF2GvKnFUFbNFovFgk6nw9fXF6PRSHZ2NlarFb1eT6dOnbjtttvYsGEDr7zyCuvXr1df56kVuDMlgOPr6+vV3fGTJ0+WuwzgdRZN69atqVOnDrNnz2bbtm2sWLGClJQU+vXrx8MPP8wtt9wCQMeOHT2+vkOHDowaNYqPPvqIF154gU6dOhEaGkpmZiZhYWHodDpycnIICAggJyeHnJwcmVp1EXMuQus8HSY3N1etp6PRaLBYLBQVFeFwOAgPDycyMpI+ffrg4+PDiRMnOH36tJqlVpbU1FSX3x0OB/Pnz+ett94CYMCAAUyfPh2z2axeK2VJSkry6n16EywB72tOeVvEXOnWprj99tuZMWMG//33H9999x09evQAyq+dZTQaeeuttxg9ejRPPPEEu3btYsKECSxatIjp06er16Hz8o0bNy73+8jbmjVSJk7UpNjYWJkaJYQQQgiVZOCIEpTsHKW2g9VqpbCwEKvVisFgYOrUqfj5+bFp0yZ++uknr9erBFrKKyJc3bRaLd27d2fevHl069aNwsJC5s2bx4IFC8otNDtlyhRiYmI4ceIEkydPJioqilatWhETE+PS5thgMKj1cWRq1cVJmUao1IJSpsNER0dTu3ZtNVBhMBjUdtlQHHCIjo6mRYsWAOzYsaPC23Y4HEydOlUN3owfP54333yzUq3pLxVGo5HBgwcD8NFHH1X49R06dGDr1q0sXLiQiIgI/v33X4YOHaq2PHfejvP3lxBCCCGEEJcLCeCIEtxrO+j1enx9fdHr9Wp2jtKWe+LEiV7f4Vdq4Lh3u6kpAQEBvPDCC4wcORKA9evXM2nSJHU/PQkKCmLevHkAfPrpp+zYsUPNIFDqFUDxMYyJicHHx4e0tDQSExNlOlU1q+i0tdIG+s7nv1IkNzIykoiICHQ6nbr+Dh06AJUL4KxcuZJPPvkEjUbD5MmTefbZZ6+ILmQjR47Ex8eHrVu3ltuW3BMfHx+1xXqPHj3Iz8/nmWeecfkOcv/8ZCqjEEIIIYS4XMgUKlEupa4EgNlsxt/fn3HjxvH111/z999/s3LlSoYPH17uei5UF6qK0Gg0DB06lAYNGjB79mz27t1Lr169+PTTT4mPj/f4mu7du6tTqR566CG2bNmiPqe0nXZ+ZGdnk52dXSWtxkXp3DNqyuN8XpfGYrFgt9vVz1UJBJhMJtq0aQNUvA7O/v37ef311wF4/vnn1QDi+XA4HPz5558kJiZSUFBQ5qOwsJCAgADq1KmjPurWrUv9+vU9dpiqSvXr16dPnz5s2rSJjz76iDfeeKNS6wkPD2fx4sW0bduWHTt28P777/PQQw+VWK6i54QQQgghhBAXMwngiArLz8+ncePGTJw4kZdeeolXXnmFu+++u9zXKQGc6sjAcTgcnDhxgj179rBv3z60Wi3XXXcd1113nVdTKTp37szcuXN59dVXSUpK4uabb2bZsmX06tXL4/JTpkzh559/JikpiZdeeomlS5eWGOxDcZBAmTImUzqqV3W0dVaCNs4BOZPJhN1uV6dQ7d69m6KiInx8yk9otNvtPPHEE+Tn59O7d2/GjBlTJfu5bNkyl0CiN9xbE+t0Oho0aEDDhg3VR2xsLP7+/lWyj4r777+fTZs28fXXXzNs2DBuvPHGSq0nNjaW119/nSeffJJJkybRr18/AgMDCQ4OVq8/afUthBBCCCEuJxLAEWWyWCzk5OS4/O7v78+JEycYMGAAb7/9NikpKaxYsYIhQ4aUuS5lEJWdnV1l+2c2m/nf//7H7t27SxRG/uGHH/jpp59o164dXbp0KXddcXFxvPPOO7z77rts3bqVYcOGMXfuXI/ZRUFBQSxdupS+ffvy5ZdfUr9+fV599VXMZjOA2g3EYDAQFxenFsxV/iaqnjcZNeBavLi85ZV1Ond4UbJwlDbfOTk5Xgdw/v33X5KSkjAajcyaNatKpk0lJCSowZvu3bsTGhqKv78/fn5++Pr64uvri5+fn/q7n58fOTk5nD59mtOnT3Pq1CnOnj2LzWbj33//dZna5OvrS8OGDbn66qu55ppruOaaa4iIiDiv/W7fvj2dOnXijz/+4N5772X16tV07ty5Uut68MEH+eSTT9i9ezcffPABjz76qEux6Ojo6Muio5cQQgghhBAgAZwrmjcD2dTUVHJycsjPz6d27dpAcQZOUVERhYWFjBo1ijfffJM5c+Zw9913lzkFo0WLFhw9epRjx47Rrl27Su+31Wpl165d/PXXXyUGm82bN6dt27ZYrVa2bt3KyZMn2b59O9u3b+eXX35hwIABtG/fvtTBdnBwMKtXr+aJJ55g1apVPPHEE5w8eZLnnnuuxKC1R48eLFmyRG2THBwczD333INOp8NsNhMaGorFYiEwMFCmclxEKvpZWCwWUlJS0Ol0amHqjIwMl4BceR2PFHv27AGgTZs2VTKVsLCwkA8//BCAm266yWNGjzc1qoqKijh37hyJiYkcP35cfWRlZXHkyBGOHDnCxo0bAQgLC6NZs2bqo2nTphU6pzUaDQsXLmTcuHFs376du+66ixUrVpSa7VYWHx8fHn/8cUaNGsUnn3zCgAEDKCgowN/fH71e7/G7zb37WFlyc3O9DvYJIYQQQghR3SSAcwWryEBWKWSsTAdSMk2eeOIJlixZwpEjR/jmm28YMGBAqeto1aoVX3/9NcePH6/U/h4/fpzNmzezb98+CgoK1L83atSIdu3a0aJFCwICAtS/t2nThqSkJLZu3crBgwfZs2cPe/bsoX79+tx555306tXLZXmFv78/CxYsoH79+sydO5dZs2Zx6tQp3nrrrRKBn5EjR5Kens4zzzzD1KlT8fX1ZeDAgURERACUO5WjIoNJcX6cs6Aq0qVIKdxts9mIiIjgxIkTmM1mTpw4AVSsptPu3bsBziuA6ez777/nxIkTBAUFcc8991R6PT4+PtSvX5/69evTtWtXoHhaYlpaGocPH+bff//lyJEjHD9+nHPnzrFt2za2bdumvrZly5aMGDGCa6+91qvsnKCgID788EMeeeQRfvnlF4YMGcLSpUvp379/hff9rrvu4rnnnuP06dNs3bqVrl274uPjQ2BgoMfP2Pl7z5sAjgRehRBCCCHExUICOFcwb+pDREdHYzAY0Ov1LgMYZVqJ1Wpl9OjRzJ07l7lz59K/f/9SB3AtW7YE4NixYxXe1/T0dGbPnq22+a5Tp45a46a07Wk0GuLi4oiLiyM9PZ2jR4+yadMmTpw4wfz58/n4448ZMGAAQ4YMKRGY0Wg0vPTSS9SrV49nn32WFStW4OPjw9y5c0ts78knn8RsNjN9+nQmT55MaGgoo0aNcul84zy9xzloU5HBpDg/qampZGdnExQUpE5/8kT5fJRzXvnclNpNer2esLAwDh06BKAGNb2hBHDatm1byXfx/8xmM2vWrAFg6NChVV5bSqPREB0dTXR0NN26dQOKs+/S09M5dOiQ+jh79ix79+5l7969tGzZklGjRtG+ffty1x8QEMDChQt56aWXWLt2Lffffz85OTleFUR3ptPpGDNmDNOnT2flypXccsstNGjQoNSAS0Xq4kgNHSGEEEIIcTGRAM4VzL1miKcpVQaDAZ1O57KM1WpFr9djtVrJzs5m4MCBLFq0iP3797Nly5ZSp0IoAZyTJ0+Sl5fnMfulND/++COFhYXExsYyfPhwYmNj1UCKUhy5LOHh4YwdO5Z7772XzZs3s27dOk6fPs3y5ctJTEzkmWee8VisddSoUYSEhDBu3Dg++eQTAgICeOONN0oEcaZOnUp6ejrvv/8+Tz/9NAUFBfTp04eoqKgSA2vnoI2y/1Kn48IrbQqh8vl4Kl6ck5OD1WrFaDSq14W3GThms5mkpCQAtYPV+VixYgV5eXlcffXVdO/e/bzX5w1/f39atGihFnAGOHPmDKtXr+abb75h//79PP3007Rq1YrnnnuOTp06lbu+pUuXEhgYyCeffMIjjzxCdna2x45SZXnggQeYNWsWu3fvJjU1lfj4+ArVOiqNN6+VLDohhBBCCHGhSABHqNwDC54GP3l5edjtdvLy8jAajZjNZmrVqsXw4cNZvHgxb7/9Nv369fO4/piYGKKjo0lNTcVsNtOsWbMy90epuZGXl8f//vc/oHgaVkZGBhkZGepyq1at8ur9NW3aVP25UaNGBAYGcvToUX777Tf27t1Ls2bN8PX15amnnnJ5XVhYGA8//DDvvfceixcvJjU1leHDh3PTTTe5LDdt2jRSU1P56quvePnll7Hb7YwYMQKHw6Eu4zyNJzg4GIvFQlhYGIDLcs7LVnYAWhUFci8WDoejxPEpj/vxi46Odhlkl3a+K1kXer3eZX0Gg0GtbWSz2dTaMkFBQV7tmzLlqFGjRgBkZmZ6XC4/P7/cde3YsYO//voLjUZDhw4d2LlzZ6nLnjx5stz1ATRs2NCr5TwFTMPCwhg0aBB79+7ln3/+Yd++fQwfPpxrrrmG22+/nWuuuabU9d100028/PLL+Pn58cEHH/D8889z9uxZHnnkEZfl6tatW+o66tSpwx133MFXX33F8uXL6datGzk5OdjtdnJycggICMBisagPnU7n8TP2pLzrqKLTrC6n61IIIYQQQlxY5bdNEVcMo9Go1gZJTU3l+PHjJCQkqANc+P+CrQaDAaPRSGxsLEFBQUyYMAE/Pz+2bt3Kn3/+6XH9Go2GVq1aAXDkyBGv92v//v0UFhYSGRlJTEzM+b1Jp32pVasWzZs3R6vVkpWVxb59+7DZbB6X79GjB+PGjQPg66+/ZvXq1SWW0Wq1LFq0iJtuugmLxcK0adP477//1A5GzoNHJajgfDzdKQPD1NRU0tLSXKZkXWksFkuFj4F7gMZgMBAVFeVSl0g5390H4c7LOXegiomJITAwkIiICJdAnDf27dsHoF4DlZWfn8+8efMAaN26NdHR0ee1vqpiNBrp3Lkz99xzjxoM/ffff5kzZw5z584t85rXaDQ8//zzPPnkkwC89dZbfP/99xXa/vjx4wH4/PPPycjIwGAwoNVqXT5Hu90O4PJ35TnlGi3rb6W974rUVBJCCCGEEKKyJIAjVO4DV6vVit1udxnAKIEH5+yGqKgorrnmGoYNGwbAm2++Weo2WrduDXgfwCkoKGD//v1Acd2Qqr57HRoaSsuWLfHz88NisbBv3z5SUlI8LnvzzTdz//33A/DFF1+og2hn/v7+fPzxx3Ts2JHMzEzuuusuDh065DIlxzlgYzAYiIyM9BjAMRqN2Gw2zGYzWVlZLoG0K43FYnEJxnjDfWDtHgRyPt/LGoQrA3/l84uMjCQyMlLNwLnQAZxVq1Zx4sQJDAZDuVOUaoLRaKRLly689tpr3HDDDWi1Wg4fPszs2bOZP38+eXl5Hl+n0Wh49NFHGTt2LAAvvPCCWijaG127dqV58+ZYLBaWLFmifs5K4FQJ6Cifn3sAR7lG3f9W3jnn/r0phBBCCCFEdal0AMdqtTJx4kRuvfVWPvnkEwCmTJlCdHQ09erVY/z48eTk5FTZjooLKzo6mgYNGqhFjHNzc0lLSyM3N9fjYAfg4YcfRqPR8N1333HgwAGP61UGr0ePHvVqPxISEsjLyyM4OJirrrrq/N5UKQIDA2ndujV6vR6bzcakSZNISEjwuOxtt92mBqomT57MkiVLSixjNBr54osvaNasGampqQwePBiz2axm3JQWsHGnBBaUKTtX8h1+JfBVkWPgPrB2z8gpa1mFMvi32Wxq4FLJysjKygK8K2JcUFDAwYMHgfML4Jw5c4YVK1YA0L17d5f6VBeb8PBwhg0bxuuvv0737t3RarXs27ePefPmYbVaS33dhAkTaNOmDVlZWTz55JMuHefKotFoePDBBwFYvHgxBQUFmM1mcnJy1KCs8hk6B3eU7Kr8/HyX5ypzzgkhhBBCCFGdKh3AmTBhAhs2bKBp06ZMmTKF119/nbVr1zJv3jzmzp3Lrl27mDhxYlXuq7iADAaD2sHJaDS6BG1Km/YTHh5Oz549AXjttdc81gVRBq///fdfqXfinSlZC23bti3RKaoqBQQE0KpVK4KCgsjJyWHq1KlqlyF3AwcOZODAgQA899xzrF+/vsQyoaGhrFmzhri4OJKSkhg+fDhms7nC06CMRiPBwcHExcVd0Xf4qyLLoTJTXSwWC0VFRWrAwTkbJzs7G8Cr8/LgwYPk5eURGBhYZges8ixatAibzUbbtm1p0qRJhV9fVFTETz/9xIYNGzh06JBX1+D5Cg8P59577+W5557DYDDw33//8d5776kZTO78/Px4++23CQ4O5u+//2b+/Pleb2vIkCGEhIRw/Phxvv/+e/R6PWfOnKGoqEgNzjhnFSrfa1B8jtntdpKTk12yra7k604IIYQQQlxcKj0i3rBhA9999x1z5sxh9erVTJs2jU8//ZQhQ4Zwzz33sGbNGtatW1eV+youMGXKiVIXxLn2TVRUlMeB8Pjx49Fqtaxfv57ly5eXeL5x48bUqlWLvLw8Pvvss3L3QSnoGh4efv5vqBx+fn60aNGCdu3akZ+fz5tvvklqaqrHZYcOHarWxHnqqafUu/jOateuzVdffUV0dDT79u1jwoQJHD58uEJBHJmeUXUqcywNBgM2mw2dTucyDcdgMKidmD744AP+/vvvMtcTEhICFGcBVWRakLOcnBy1ELKS7VZRJpMJs9mM1Wrl4MGDfPvtt+zYscOlKHh1iYuLY8KECQQEBHD06FF+//33UpetX78+r732GlCcTZOcnOzVNgIDA9VaOM8//zxJSUmEhITg4+OjZsA5179x/l5z/6zPR2VqNgkhhBBCCFGeSgdwMjMzqV+/PgDt27fHbrerbaKhePCanp5+/nsoaoxzO2UlaAOoQR134eHhdOrUiRdeeAEoztL6999/XZbRarVqi+BPP/2Us2fPlrkPSueZU6dOnff78YZWq+WZZ56hYcOGZGVlMWPGDI/TPTQaDa+99hrx8fGYzWaee+45j+uLi4vjk08+QaPRsHbtWtauXcvhw4dJSkrCZDJ5VSRVIYPC81fRY2gwGIiJicFms3H06FF1Ko7FYmHIkCF07NiRvLw8hg4dWmY7+4YNG9K1a1ccDgeffvpppfb9jz/+oLCwkAYNGtC4ceNKrUPpSBUREUFYWBhFRUUkJiayefNmPvvsM44cOVJqZkxViImJ4bbbbgNg7dq1ZdaX6devH126dCE/P5+ZM2d6vY1XXnmFNm3aYDKZePHFF3E4HMTExHicwqj8DsWfaWRkJEFBQecdMC1rup4QQgghhBCVVekATsuWLfn444/V37ds2eLy/Pz5810COuLS5D4oTUtL4+zZs6SlpZX6mieeeIKuXbtisVi47777SgwIe/bsSevWrbHZbCxcuLDM7V/oAA6ATqfj+eefJzQ0lKSkJN59912Pg1p/f3/mz5+PVqvlq6++YsOGDR7X17t3b55//nkA3nvvPZKTk8nNzcVkMnmsJQSeAw2lDQqv5MBORd67xWIhKSmpwgWhlcF8VlYW//33HydOnMBut5OXl8f06dOJjo4mMTGRMWPGlBn8GDFiBADr168vM9hTmt9++w0orn1TGQ6HQw3gNG3alJtuuokePXpQv359NBoNKSkpfPXVVyxZsoQdO3aU2pHtfPXs2ZO6deuSm5tbZpamRqPhpZdeQqvV8v333/PLL794tX6dTseKFSswGAz88ccffPHFF+UGZJynUlVk2pTz+ef8s3SmqnnJycns3r27zEdptc6EEEIIIS5WlQ7gTJ8+nccff1y9m9ytWzf1uc6dOzNlyhTeeeed899DUaPCwsI8/t1qtZbIxFG6VtlsNhYtWkRISAh79+5l06ZNLq/VaDQ8/vjjaDQatmzZwt69e0vdfr169QA4ffq02gL4QoiMjOS5557D19eXv/76i1WrVnlcrm3btjz22GMAPP3006VmnU2ZMoUuXbqQlZXFyy+/rA4WleK47jwFa0obFF7Jd/sr8t5zc3Px9/cvURDamyBQREQE/v7+hISEoNfr1Wk4HTp04L333kOn0/Hdd98xa9asUtdx7bXXEh8fT15ensc29GWxWq1s374dcP2urYiMjAysVitarZZatWqh0WiIjIykU6dO9OvXj+uuu46AgAAyMzP5+eefWbBgAT/99FOZBYcrQ6vVMmTIEAB+/fXXUgueAy7d7Z577jn1uilP06ZN1f/+zJgxg19++aXMbDdPdb28aSPufP6V1YpeXFjJycnEx8fTvn37Mh/Dhw93ycISQgghhLjYVSiA49xVqnv37iQmJqpFa509+eSTHDp0iOuvv/7891DUGCVg4DwIiYqKolatWgAlMnGUga1er6dRo0ZqxsGCBQtKrPuaa67h9ttvB+Cdd94pNTgTHh5OQEAAhYWFpdaj8cRTAeWKatKkiVpPY/Xq1WpBZXcTJ06kSZMmpKamqpk27nx9ffn0008JDw/n4MGDzJ07F51Op7Zlh5KBBPcsjdIGhVfy3f6KvHdPBaEtFguJiYlqVo57RoUygI+MjKRjx440adKEmJgYl2k3Xbp04dVXXwVg6tSp/Pjjjx63r9FoGDlyJFDchr4iBYS3b9+OzWajTp065z19qnbt2mi1WpfnDAYDN9xwAw899BB9+vQhIiKCgoICdu7cyZIlS9i5c2eVBlCbNGlChw4dcDgcTJkypczMpSeeeILQ0FAOHDjAsmXLvN7GqFGjGDx4MHa7nVGjRpVZRNxTwWKTycTZs2fL/N5xPv+u5OvwYqNctytWrGDXrl1lPhISEoiNja3pXRZCCCGE8IpvRRa+8cYb+f7774mIiABQ/3U3ePDg898zUeOUmhHOlIFKbm6uS0BPmYIQEhKivmb8+PHqXfz//vuPZs2aAagD0GnTpvHLL79w5MgRduzYwfDhw122VadOHQAaNWrEoUOHyM7Opl27diX2U2nnDMWBm8LCQhwOBxqNBo1Gg4+PDxqNhq1bt3r1vmvXru3ye6NGjTh27BizZs2id+/e+Pv7A6g1oACeffZZxo0bx+rVq2nQoAF33323+lzz5s2B4qyeRYsWMXjwYJYvX06DBg0YOXIkNpsNvV5PUVGRSzaJc/aTElxQikhbLBZyc3PVANDlfqdf+SzdKecjlB+0cz5OyvG0WCwEBARw+vRpMjMz0ev1hIaGqhkVyjH2NMCzWCzk5ORgs9l4+OGHOXLkCB988AGjRo3ir7/+okGDBi7L16pVi2HDhjF//nxOnDjBr7/+qgY5nR05cqTE3zZv3gwU1xtTgqaergVPfvjhBwCOHTum/k1pae7MOUAZERGBXq8nLS2NvLw8fvrpJ3777Teio6Pp1KmTVwWUSwt4Kpo3b87ff//N33//zYIFC+jTp0+pyw4dOpSFCxcydepUbrnlllIzAwGCg4PVn9999122bdvGiRMnWLJkCZMnT1azeJTrWOF+TXkTBHY+pzQaTZUGb7zZflUEqi9n8fHxXl8nQgghhBCXggpl4CQmJtK1a1e1kKcn7rVwxOUpOjqaWrVqER0dDUBqaiqpqakuGTlRUVHcfPPNQPFAyl1kZCRPP/00UDzNobS7440aNQLg+PHjXu2bMqhxOBxqUKSgoMDLd1ZSq1atCAwMxGq1smfPHo/LtGzZUi3O/NZbb/HXX395XK5fv3489dRTAMydO5d9+/aRm5vL6dOnsVgsajcg9ykdzm3c4cqeNlUVnGueBAUFodfr8fHxwWq1uhx3q9VKenq6xxbUUPydaDabMZlMvP3227Rr1w6z2cywYcM8Dq59fX0ZO3YsAO+//75XBYMLCgrYvXs3ANddd12l3q/NZlNr2gQGBpa7vBKMaNCgAbVq1UKr1VJQUMDJkyf59ddfq6RrldFopEOHDgB8+OGHalt2T/r160fTpk1JT09n9uzZXm8jJCSESZMmAbB8+XK1q50n7tdUdHS0eqyuxPpSQgghhBDi4lOhAM6ff/5JUVERnTt35p9//nF57vfff6dnz55l3kW9mMmdzKpnMBjUVtvLly/3WB/m/vvvJzY2FrPZXGpdkLi4OKC4rkF5NTCcP0etVqtm35wPX19fOnbsqBZ6La2l8YgRI+jXrx92u52XXnqp1OWmTJlCz549sVgsagtyu93OiRMn0Ol0ACVatbsHdGS6xvlRjmdkZCRRUVHExMSg0+mIiYlRj3tkZCRGo5HQ0NASLcQV/v7+am2ZgIAAPvnkE/R6Pdu3b2f//v0etz106FBCQkI4fvy4mh1Tlv3792O1WgkLC6v09CklOGI0GktMnyqLRqMhNDSURo0aER4ejkajITU1lc2bN7Nz587zro/TqlUrYmJiyMzMZMWKFaUup9Vqef311wFYtmwZhw8f9nobI0aMoEmTJpjNZt56661Sl3O/ppTPOScnp0LTN4UQQgghhKguFQrgNG7cmD///JOrrrqKbt26sWPHDvbs2cOtt95Kt27d2L17d6k1QC42hYWFLlOANBpNtbbPvdy43602Go34+PiUCCh06tSJFi1aYLVaPdav8PPzUzMSFi9e7PEziI6Oxmg0qhkA3tBoNGi1Wnx9ffHz88PPz6+ib9FFeHg48fHxAOzZs8fjHXmNRsPzzz9Py5Ytyc7OZsKECS7TuxRarZaPPvqIuLg4UlJSePnll4HibIGMjAx1KoczTwEdKZJaee7HMyoqivj4eKKiotRllBbigYGBJVpQKxk5Pj4+1K5dG71eDxRnlXXu3Bmg1OCM0WhUp06V14UNUIsXd+zYER+fytWdVwI4QUFBlXq9j48PUVFRNGzYkJiYGKA4I+67774jISGh0vVxtFqtmrn27bff8t9//5W6bPfu3bnllluw2+28/PLLXgfdfX19mTp1KgDz5s3jzJkzHpdzvqaUWkhlBaiu5O5vQgghhBCiZlR4NBAWFsbmzZvp168f3bt359prr2X79u28+uqrJCUlMW3atOrYzyr1zTffMHz4cFq3bk337t2ZMGECOTk5lR4cXYk8ZYCEhoa6LKPUCLnnnnuA4sHT2bNnS6xr6NChBAcHc+zYMb799tsSz2s0GjULxz3zy5379CmHw6HWwzlfTZs2JTw8nIKCAnbs2OFxAKnT6Zg5cya1a9cmJSWFCRMmYDKZSiwXHh7O559/jsFg4JdffmHFihXUqlVL7XbkPijMzc0t0fVLVD334+xe3FYpbGwymdDpdNStW5fY2Fi1qLHBYKBr164ApRYzBhg9ejR+fn7s3LmTv//+u8x92rlzJ1AcwKmMwsJCNRBR2QCOws/Pj+uvv56ePXsSHh6O3W7nwIED/Pzzz5XOYmzTpg3du3enqKiI5cuXl7nslClT8Pf355dffvG6rTjAHXfcQceOHbFYLMybN6/c5ZUAtV6vd5kq6mkZuSaFEEIIIcSFUuGIRVFREV988QU7d+7EZrPh4+PDypUrmTRpEiEhIdWxj1Xqww8/ZNiwYRQWFtK7d28yMzN5++23ad++PRs3bqzylrmXK/cMEE8dqwwGAzabjbvuuovY2FhOnjxJ3759S9TPMBqNjBkzBoCXX37ZY30NpRDw77//ztGjR0vdL+dAjVL7RnmcLx8fHzp27IhWqyUtLY2vv/7a43IRERG8+eabGI1G9u/fz4033khCQkKJ5Vq0aMF7770HFHfiOn36NJGRkSWOI5SsgSOqR3nHWamDA8XZI5GRkWrBXyjuxKZMt1H+5kmtWrXo3bs3ANu2bStzn5RpdZWdxuN+TVSFiIgIevbsyXXXXYdWq+XcuXNkZmZWen1XXXUVQLmduRo2bMjQoUMB2Lhxo9fr12g03HnnnQBl1nBTKN9n0dHRpWa6yTRGIYQQQghxoVUogLNgwQIaN27MyJEjMRqNbNiwgf79+9O/f3/WrVtXXftYZf73v//x3HPP8cYbb7B8+XIWLVrEb7/9xrRp07BYLIwZM4bPP//cZWqVt2w2G1lZWS6PS1FlpwV4asNrMBjU7IRvvvmG6Oho9u3bx7333lviGD/++ONcddVVnD17lsmTJ5dYf4sWLWjVqhVFRUV89tlnpU6l8vHxwdfXt0Ttm6qqcRQYGEiLFi2A4sLMnjKKoLhN+tKlS6lXrx6JiYncdNNNHjMyBg8ezO23305hYSHjxo0jICDAZWqPwr0GzuWqpq+j8o6zUgcnMjKyxPlutVpJSUlh1apVAGrL8NIo3XH27t1b5nK33HILUJw5WJlpnlqtVg2um83mCr++NBqNhtjYWLUbYWXX7XA41GvjxhtvLHf5m266CcDrrnIK5TvDvTuYJ95MUbyQ0xhlupYQQgghhIAKBnAeffRRAgMDWbt2Ldu3b6dfv36sWrWKkSNHMmjQIObPn19d+3lelMH7li1baNCgAUOHDlXbNgcHB/PUU08xe/ZswsLCmDhxIt9995069cZb06dPJyQkRH0odSIuNRWZFuBpUGGxWEhKSiIpKUmtE2IymQgODubjjz8mPDyc3bt3M2rUKJe77QEBAbz11ltoNBpWrVpVItih0WgYMGAAV111Ffn5+SxfvrzUAaMSxFFq3/j6+laocGt5GjduTHh4OLm5ucyaNavU86RRo0YsW7aMzp07k5WVxV133cWiRYtKLDd37lyCg4PZvn27mpHjzL2F+OWsOq6jigx+3WvjuPMUqITi4M2///7LtGnTMJvNNGjQgNtuu63MbbVq1Qoov912r169CAwM5PTp06V2NyuPEmTJysqqkmw0Z8r0MU9TBb2RkJBASkoKOp2O7t27l7t8p06d8PHx4b///uPUqVNebycpKQkobjNuNptLfG95+i5LS0tTH8pzNRFMkelaQgghhBACKhjA+fTTT9m7dy/9+/dX/6bRaFi4cCEvvvgijz32GBMnTqzqfawyBw8eJCMjQ52S4OPjg8PhICAggLvuuovXX3+d4OBgnnvuORITE9FoNF4HcV544QUyMzPVhzdp+hejikwL8DSoUArwKkEHk8lEfn4+p06dolWrVixYsACj0ci2bdsYN26cy2CyQ4cOakHj5557rsR0Cl9fX4YOHUrdunXJzc3l448/LjdbSqPR4OPjU6UBHI1Gw7XXXoufnx9bt24ts5NQaGgo69evZ/jw4RQVFfHMM8/w1FNPubzvOnXqqB12Jk2axKFDh1zqsJhMJs6ePVvpAfKlpDquo4oMfitSa0g5v61WKxaLhZSUFLWT0qxZs8otnN2yZUugeEqPpw5tioCAAPr27QvA119/XalssoCAAPWarsosHOC8M3CU66dbt25eZbOEhITQunVroGJZOEpXOIPBgN1ud/mMPZ0jyt9MJpPLczURTJHpWkIIIYQQAioYwBk6dGipxWBfffVV3nvvPebOnVslO1aVlH1u0aIFJ06cUFvQ2u12NUjj5+fHbbfdxoQJE0hKSuLxxx+nqKjI6+K3Op2O4OBgl8elqCLTAjwNKpQsEaPRqGYr+Pv7U7duXXx9fenRowcLFiwgICCAzZs389hjj7l0sJk4cSINGzbk9OnTbNq0qcQ2dTodI0aMICwsjHPnzrF8+fIaaQEfHBzM/fffD8CcOXM4d+5cqcvqdDoWLlzIa6+9hkajYcmSJQwePJj8/Hx1mVGjRtG9e3dyc3N58MEHycrKuiKnS1THdVSRwW9Fag0p9XBMJhMWi4X33nsPm81Gjx49GDBgQLmvDw4OplGjRkD5WTi33HILOp2OxMTEcoselyY8PByAjIyMSneN8kQJ4OTm5la4hlh+fj6//vorAH369PH6dUqh6N9++82r5R0Oh5qB07JlS7Rarcv54OkcUf6m1KVSnquJYIp0nRNCCCGEEAC+Vbmyhx9+2GO3jpqmdCHq1asXb731FuPGjePnn38mNDQUu92OVqvF4XDg7+/Pfffdx/fff89vv/3GqVOnqF+/fk3v/gWnZNEoQZjSKK2VFRqNBqPRqGYmWCwWoqKiXFozA9x7771EREQwYMAA1q1bR0REBO+//74aLFu2bBk9e/Zk165djBkzRm3L7KxLly7cd999nDp1igYNGnD33XeXm2WzefNmr96/p8CRJ8888wy1a9fmzJkzPPvss2q3LXdKllDnzp2ZMmUK06dPZ/PmzQwbNoxnnnlGfd/vvfceHTp0YNu2baxZs4YHH3yQgoICQkND0el06PV6CgoKzrsl+uWqtGCrElBUlBXwMxqN6rlfXlc65Vw3m81s3bqVLVu2oNVqmTVrlsdpSkrmn7O2bdty7NgxDh48yM033wz8f0DEWUREBLfffjtffvkl3377Lb169WL//v1l7p+iS5cuQPH7/vLLL8nIyCA0NFSdwqVYsmSJV+tTAkHOlNbb//77r7r/StHgsvzvf/8jLy+PunXrcvXVV7sENd05B9U6dOgAwK+//kpubq7LZ+/eDQ/g3Llzaj2lli1bYrVayc/PV6fD6fV6tei0cn4of3M/r3Jzc9VsOOfvP28DyefTEc/b72YhhBBCCHF5qvK+2YMGDarqVZ435X+YO3XqxJAhQ9i7dy9jxowhKysLrVarZuIUFhZiNBp5+umnycjI4MiRIzW85zXjfKcImEwmbDaby5Qf96kpffv2ZebMmfj4+LBs2TKeffZZddlu3brxyCOPADB16lSP06RiY2N577330Ov1JCUlsXHjxgueiePr68uAAQPQaDTs37/fY6cpd127dmXy5Mn4+PiwadMmPv/8c/W5Jk2a8NJLLwEwe/ZsTpw4oda+cZ6mciVm5lwIZQ2Oy5paVVBQwJtvvgnAgw8+SLNmzbzeZps2bQC8yqoZNGgQfn5+7N+/nwMHDni9DYVGo1GnbR08eLDKOlLB/7cnz87OrtDrlFbgvXr1qlBg49prr8Xf35/Tp0979T2dmJgIQFRUFBqNhtzcXHJyctSW8BW5pjx9v10oUgtHCCGEEOLKVuUBnItVUVERvr6+vPvuu3Tv3p2vvvqKcePGkZmZiVarpaCgAF/f4oSk06dPU6tWLWJjY2t4r2tGaVMEvC3eGRkZiU6nU4ubguc6LsOGDWPq1KkAvP3223z33Xfqc9OmTaN+/fqcOXOGt956y+N2mjdvzpw5c/Dx8eHQoUP8/PPPFX6v56tevXpqhsM333zj1RSSjh07qgGqpUuXukwDmTBhAi1atMBkMjFp0iSX9Vmt1hK1O0TVKWtw7GlqlXJOr1y5kuPHjxMZGakG4LxVkQBOZGSk2nr8s88+q9B2FI0bN8ZgMJCTk1PutK2KqEwA5+TJkxw5cgQfHx+vuk85MxgMamaeN5l1Sv2buLg49Hq9mmFlNpvJzs4uUby4rKCOp+83d9VV6Fhq4QghhBBCXNkuqwCOcwaG8rPyr4+PD3a7HZ1Ox3fffcd1113HqlWruP322zlx4oQ6LSUzM5MtW7YQFxdHWFjYhX8TF4HS6i14e/c3KiqK+Pj4ElOnnJlMJsxmMw888AAPPvggUNzlTMm2MRqNajvxNWvWlNp9p3PnzvTr1w+AHTt2sH37du/eZBW66aabiIiIIDs72+tMoP79+6vFwKdPn67WZfLz82PRokVoNBrWrVvH+vXr1UGgXq9Xa3dIW+GqV97gOCMjo8TfTCYTixcvBoqzxTxN3ylLy5Yt0Wg0nDp1qtSW9M7uuecefHx8+Ouvv9S22BXh6+vLddddBxQHjaqqTbsSwMnNzfW6vs7//vc/ANq3b+9xWlZ5lGBWWUXEFUr9m9jYWAwGAzExMRgMBoqKisjIyHD5riuvDpI332/VlSkjtXCEEEIIIa5sl1UAJzU1Vb2rq0wP0Gg06oBCq9VSWFiIXq/n559/ZtCgQWzdupU2bdrwxBNP8OyzzzJmzBi++OIL3n///UoNKi5nFb37m5aWRkJCAmlpaURGRqqDPKVuSH5+PmazmcmTJ1O/fn2SkpKYNm2a+voOHTpw9913AzBlypRSs1uaN2+u3sH/+eefK13ktbL8/PzUYMyePXu8Lqz68MMP07FjR2w2G6+88oradatDhw48+uijQHFxcKVDkTKVymAwyFSKalDe4Ng9OBMZGcmKFSvIzs6mbdu2jBgxosLbDAwM5JprrgFg586d5S5fr149tdX2hg0bKCoqqvA2r7rqKurWrYvdbueHH36oVCDInU6nw9fXF4fD4VVQsaioSO0g1atXr0ptU3nd3r17SU1NLXNZJQPHuS29xWLBarWi1+tdPnODwaBmYyqZOBUNmEqmjBBCCCGEqA6XTQDniy++oH///jRv3pwWLVpw66238v777wOoRYqh+A50YWEhAQEBfPrpp3zwwQd069aNlStXqi16f//99xIFPkXF7/4614pQ6or4+/tjsViIiIjA39+fiIgIoqOjeffddwFYtGgRmZmZ6jqefPJJ6tSpw+nTp9XP05OOHTuqhU2///77UjN2qkvDhg3p1q0bUFxfxBtarZZJkyYRFBSEyWRyqaEzZcoUYmJiOHXqVIn3rdRqsdlsMkC8QJwH9UotHKPRqHbJSkpKUuusVJQSfHz33Xe9yt6699578fPz459//mHt2rUVrv2k0Wjo0qULOp2Oc+fOsXHjRjZu3FiZXVelp6erQXNvimxnZmaSlZWFRqOhffv2ldpmrVq11HpD5QW/6tSpA8BPP/2kHi+DwUB4eHiJ7zOlex6gBkkrGjCVTBlRExISEti9e3eZDyWYKYQQQohL02URwPn4448ZOXIkN954I5MnT+aVV17h999/56GHHmL06NFqFyqFr68vdrsdPz8/7r//fr766it27tzJ3r17Wb58Oc2bN6/Bd3P5cK8VoQyClQFSkyZN1Od69uzJNddcQ3Z2Nh988IG6DqPRyPPPPw/AihUrSi1YqtFo6NGjB9dffz1QXBz1l19+uaCFjZWB6NmzZ73OjDAajTRo0ACAf//9V/17YGAgb7zxBlDcnerUqVNq5lJqaio6nc6l2K6SIaA8ZGpV5bkfS+V4KsfaeXrNtGnTaNeuHenp6QwePLhSU5Iee+wxDAYDO3fudKkDVZqGDRvy/PPPo9Fo2LZtGz/++GOFtxkaGsrdd99N8+bN8fHxOa8snPz8fI4dOwYUZwgFBASU+xplOlpoaKgaGKuMtm3bAsWZb2UZPXo0gYGB7Nu3j+XLl5OSkoLBYCA6OrrUWjbK95XSxUwyasTFSummNnz4cNq3b1/mIz4+XoI4QgghxCXskg/g/P3330yePJkZM2bw2muv8dRTT/HSSy+xbds2brzxRj766CMGDRqkTk+x2+0UFhaWaDmt1ESQO6ZVx71WhNFo9HhX2mKxcOLECUaNGgUUZyI4t2G+4YYb6NGjB4WFhUydOrXUqVQajYYbbrhBzWj466+/2Lhxo9c1Oc5XeHg4fn5+FBYWYjabvX6dMq3DOYADcPfdd9OpUycsFguvvPKKWsQYKDGYVDIETCaTTK06T+7HUvlXCeIoQUgorkv0xRdfULt2bRISEhgzZkyFz7fatWurdaCmTZvm1etvuOEGddrexo0bK1X7Sa/X07lzZ+6++26uuuoqr1+XnZ2NyWTi1KlTJCYmkpCQQGFhIQaDgfr163u1DucAzvnwNoATFhbGuHHjAJg3b556fSoDX0+UQLPy3wXJqBEXq9jYWBISEti1a1eZjxUrVqhFuoUQQghxabrkAziJiYnk5ubStWtX9U6u3W6ndevWLF68mIEDB/LVV18xevRooHjairLcunXrOHPmDFBc5FhUD6UFs/Jwb91rsVjQ6XT07duXyMhIUlJS+PLLL13WMXHiRIxGI/v372f8+PEu06zcXXfddfTr1w+NRsOBAwdYu3Yt+fn51foeofgcqlWrFoBXBWkVpQVwNBoNs2fPBmD58uX8888/ahFj+P/jarFY1AyByMhIyRQ4T+7HUvnXYDCoQUjn4+twOHj11VfR6XRs3LiRV199tcLbfPTRRwkNDeXw4cNs2bLFq9d0796dnj17AsVTSL1pY+9JcHCwuh5vHDhwgCNHjpCUlMTp06exWCxoNBoaN27s9ffouXPngKoL4Ozfv98l6OvJ448/jr+/P/v27VMLKJfGuROVFAwXl4LY2FjatWtX5iM+Pr6md1MIIYQQ5+mSj1ocOXIEs9ms1jhQsmscDgeNGzdmxowZ9OvXj88//5wpU6aor3vhhRcYMGAAq1evrlQhUOE9pauLkslw4sQJ0tLS+Pfffzl8+DAWi4XAwEAaN26sFu996623XKY/1a5dm/fee4+goCD27t3L6NGjywyStGzZkoEDB+Lr68uxY8f4/PPP1Rod1UkJ4CiBQW+UFsABuPbaaxk+fDgAzz77rDo9xT3bRskQUB6SKVB57sdSeZQWFDt79ixXXXUVzz33HABz5szh448/rtD3SkhICE888QQAH330kdcBx1tvvZX27dtTVFTERx99dEGmRuh0OoKCgoiIiKBOnTrExcXRunXrCgUNlQDO+Xb6a9iwISEhIdhsNv75558yl61bt65aaPrrr79WgzTuDyVoo2RdOde/kWCOEEIIIYSoSZUvPnCR6NSpEwAzZszgvffew9fXl6KiInx8fHA4HFx11VXMmDGDvXv38vHHHzNkyBCuueYaOnfuTO/evbn55puv2Owb57pAVcFTvRllAASotSb0ej12u5309HT1b3FxcUBxZ6aZM2eye/duTp06pRYGBmjUqBHx8fEMGDCA//77jwceeICvv/66zO4//fv355FHHuH06dMUFBRw3333lXvX35saHoDHuiFKp63k5GQ1Tb289SnTV44cOaIWdnU2ceJE1q5dy65du1i+fDmjR4/GYrG41BbyxNv6P1V9HtSUC1nvyFn9+vU5efIkQ4YM4dy5c7z33ns8/PDDTJs2jf79+3PXXXfRtWtXQkJCylzP008/zZIlSzh16hRbt25l5MiRZS6vBCSnTJnC5MmT2b17NwsWLKBv374MHDiQ6Oho4P+DiuVx7gZVVFTEnj17MJlMREREEB4eTkREBEFBQV4Xay5rGp9ybRgMBq/3T5kG665Vq1b89ttvbN++nauvvrrMTJwnnniCDz/8kG3btvHHH3+oXeBCQ0PJyMggNDRUnSqn/KvRaNSi1c7BHE/XnfJ951yfyl1VXpeXy7UrhBBCCCG8c8lHLq655hpatGjBsmXL+OijjwDU4I1Go8HhcNCiRQvmzp1LUlIShw4dwsfHh1tvvZWvv/5abeErqkdubq5acFfJZGjQoAGBgYGEhYVht9tdiohGRkZy3333AaidqZw1a9aMzZs307hxY1JSUujTpw/79+8vdftt2rThk08+oXbt2phMJhYvXlyh6U0VpbyXitQYqFu3LlqtltzcXE6fPl3i+Tp16vD4448DMGvWLHx8fFwyQ+D/OyOJC0OZvpabm0tsbCytW7cGigsSjxs3jqCgIE6ePMn8+fO56aabqF+/Pg8++CDff/99qdk1er2el19+GYCFCxeSk5Pj1b74+fkxadIkWrZsic1mY926ddx///3Mnj270hk5Pj4+tG/fnptvvplrr72WRo0aERISUmXB7qqqgQOox37v3r3lLnvVVVdx1113AbBy5UpsNpvLVDmbzeYScHavf1NeMeOKdqsSQgghhBCiIi75AE50dDTvv/8+Pj4+zJw5k7Vr1wLFdyadpzC0bduWgIAAdZqKj48Per2+Rvb5SlLagMdsNmO324mIiFCDEIqnnnoKjUbDpk2bPE4rio2N5YcffqBt27aYzWZGjx7Ntm3bSt2Hq666ihUrVhAVFUV2djZLly4lKSmpat6gGyWAk5WVhc1m8+o1fn5+1K1bF4CjR496XOaRRx6hXr16nDx5ktdee81lgOg83UPhXB9HVB3luJpMJrKzs0lOTlan3Oh0OrKzs3nhhRc4duwY69atY9SoUYSHh5OWlsayZcu47bbbqFu3LqNGjWLdunUlCnKPGjWKuLg4zp07pwakvWEwGJg1axZvvPEGbdq0wW638+OPPzJu3Djmzp1b6nlVU5QaVuVlJXmjIgEcgAkTJgDFxZ+VYK5SsNhoNKLT6Uq9bkorZqxMrYKSBcZl2pUQQgghhKgql3wAB4qnUS1YsICkpCQmT57M559/DrgWJs7NzaVu3bo0bdq0pnbzimexWNSuNTk5OVitVqxWa4nBzdVXX82tt94KwPz58z2uKzIykg0bNtCjRw+sViuPPPIIGzduLHXbtWvX5oEHHiA2Npa8vDw++uijMou+OhwObDYb6enppKSkkJaW5tXUh4CAAAIDAwEq1IkqNjYWKD2Ao9frmTx5MlCcmXTw4EH1OffOSFCcAXTmzBlSU1O93ofLTXUMnJVgGRRnkeTm5mIymTAYDGpdGH9/f4qKirjtttv44IMPOHr0KKtWrWLMmDHUqlWLzMxMPv30UwYNGsR1113nkmnj6+vLk08+CcCyZctIT0/3et80Gg3t2rVjxowZvP3223Tu3BmAnTt38sorr/D666+zb98+r85jh8NBYWFhtU1LUwI4VZGB07JlSwCSkpLU2jplad26NX369KGoqIi5c+eSnZ2tniPKtQS4FFp3p3yXJSYmutTJAdQAj3L+paamSlaOEEIIIYSoEpd8DRzFsGHDsNlsPPHEEzz11FMcPXqUSZMmodFoSE9PZ8GCBfj4+NChQ4ea3tUrivuUguzsbOx2O4GBgeogJysrC3Ct5TJ27Fg2bNjAZ599xoQJE2jQoEGJdQcFBbF69WqGDx/Opk2bmDhxIidPnuSBBx7wWBvCYDBw3333sWrVKg4fPsxnn31GkyZN8PPzw2q1kpeX5/KvexHasLAw2rRpQ+vWrdWMGU9CQ0PJycnBZDKVuZyz2NhYtm3bxn///VfqMgMGDGDp0qVs376defPmsWLFCqA4y0m6TpVUXr2SylDO2eDgYKD4fFb+rjyn1E5RFBQU0KVLF7p3787s2bP54Ycf2LRpE19//TUJCQm8/fbbTJo0SV2+T58+NG/enIMHDzJz5kxmzJhR4VonTZs25ZVXXiE5OZkVK1awbds2Dh06xKFDh6hVqxYNGjSgoKAAm82GzWYjPz+f/Px89XebzUZRURFRUVEMGTKELl26VFm9FedrvioycEJDQ2nYsCHHjx9n//79tGrVqtzXPPPMM/zwww/88MMPnD17Vq3Do3yOzq3jPV1bubm5auBNuf6U2jfOyyhBHU9ZOeXVyhFCCCGEEMLdZRPA8fX1ZezYscTExHD//ffzyiuvsGbNGmrVqkVeXh4HDhzgxx9/pF69ejW9q1cU94FNUFAQQUFBREdHk5ubS1ZWFvn5+SUGST179qRjx45s376d0aNHs2nTJvz8/Eqs39/fn1mzZhEeHs7KlSt55513OHToEK+//rrHgZe/vz9Dhw5l/fr17Nq1q9zONcrAKzc3l3PnzvHzzz/z888/ExUVRaNGjWjSpAnh4eHq8omJiZw4cQKoWHaBMtAra5Cs0Wh47LHHGDFihMfpIkqXHGVAmJGRoRZVvhJ5GlRXxTqV9ULx+axMm3MO3jgHcwDy8/NxOBxYLBbi4+OJj4/nuuuuY/z48cyfP5+nn35andLp4+PDc889x/3338+6deuoW7eu2qGqomJjYxk/fjyDBg1i48aN/Pzzz5w9e9brOlBpaWm8++67fPfdd9x3333nXTPM4XDw8ccf43A4iI6OrrLz0263A94X9e3SpYtauNjPz69EEMW5iLEnRqNRzbRTgjDuyyrnSUhISInnqiO4KIQQQgghLn+XTQBH0bdvX/78808+/fRT/ve//2Gz2WjTpg2LFy+WgsU1wH1go3SbcubpLrTRaOSDDz6ga9eu7Nixg6lTp/Laa6953IaPjw8vvvgi11xzDdOmTWPz5s0cPXqUN9980+OUOa1Wy5133snVV1/NmTNn0Ov16PV6AgIC0Ov1hISEoNfrMRgM+Pn5odFoyM/P559//uHvv/8mISGBtLQ00tLS+Ouvv4iMjOSaa66hbt26bNq0CYAWLVqo06K8cfz4cQDi4+PLXE7JRFKKHTsHbZxr4Sit2ZUAwpV4x9/ToNobyrFSitaWtoy/v7/L1DXn4+/8eeTn56vLa7VadeA/ePBg3njjDZKTk1m5ciVjxoxR13/dddcxefJkJk+ezMKFCzEYDIwePRqtVluJI1E85XDkyJEMHjyYffv2ce7cOXQ6HTqdDn9/f3Q6HXq9Xv2bTqdDq9WyZcsWvv76a44ePcrLL79Mp06d6NatW6Xbf//888/8/fffaLVaxowZUyVFkVNTU0lOTkaj0dCmTRuvXuNwONTsKU9dsMo7dwwGg8fvMm/XUR3BRSGEEEIIcfm77AI4UDzIffHFF3nxxRdreldEGcobJEVHRzNz5kzGjx/PO++8Q9euXbn55ptLXX7QoEFcffXVTJgwgePHjzN06FCefPJJRowYUWKgqNFoaN68Oc2bNy+xHk9tv/39/WnVqhWtWrUiLy+PQ4cO8eeff5KUlITJZHLpOlWrVi1uvPFGL47A/1OmTpUXwFGmZCm1eYqKivD393fZfnBwMJGRkaSlpakFouWOv/eUY1Xa9BlAnWajBGecs26cj6/SbUmn02Gz2YiJiXEpnn7//ffz6quv8u677zJ69GiXDJJ77rmH9PR03nnnHebMmcOXX37JuHHjuP322/H396/UewsICKBjx44en/MUHBowYAA9evTg888/55dffuGPP/5gx44ddO3alRtvvBGdTuf1thMTE/nyyy+B4mu1vACIt3bt2gUUTxvzNqPHYrGoWTtKppxyHUdGRrp0xnN+TVUFQSsbXBRCCCGEEFe2y6KIsSfOxTerqxCnqBqlFZvNy8ujT58+alvxBx98kJMnT5a5rtatW/Pll1/Ss2dPCgoKePPNN3nwwQertJhvQEAA7dq1484772TcuHH06tWL2NhYNBoNBoOBW2+9VS2E6o1z585x7tw5NBoNTZo0KXNZJTsIUKdq5efnq129lKyRqKgomjVrpgZwymt/LP6fcqzKGmArg3h/f3+XArhK62mFEhyw2Wzo9XosFotL56kHHniAwMBADh48yI8//lhiO+PHj+e5554jJCSEpKQkXnrpJfr06cMnn3xCXl5eFb3jsoWGhjJ+/HhmzJhBixYtKCws5JdffmH27Nns2LGjRK0ou91OWloae/bsYePGjXzwwQe89tprvPnmm9jtdtq2bUuPHj2qbP927twJQPv27b1+jVKDR6vVYrVasVgsakDOORjqrKItwqX7lBBCCCGEqGqXZQYOuNZCqKrim6J6lJYdEhAQQF5eHlOnTmX37t3s37+fESNGsHz58jJrGYWFhfHOO+/w5ZdfMnPmTP744w/uuusu+vXrV26GS0UFBATQokULWrRoQV5eHhqNpkJZCQDHjh0DiqeXlRdg0Wg01KtXj6NHj5KWlkarVq3UbAKbzVZiOohz1oB7u3bhWVnZEc5T1sqrk+L8vL+/PxkZGdjtdsxms5qJU7t2bYYPH86iRYt455136N27t8s6NBoNo0ePZvDgwaxatYoPP/yQM2fO8MYbbxASEsKAAQO4/fbbL0hgLi4ujkmTJvHtt9+yceNGzGYza9eu5ffff6d58+Zqx6W0tDQ1u8VdTEwMI0eOrNLvZCUD59prr/X6NUoXrKCgIDXIEhkZiclkQq/Xq53FnD/bik57kqw3IYQQQghR1S7bAI648LwdlLlnRJU2MHKexvDJJ5/QvXt3du7cyXXXXcfMmTMZO3YsGo2Gq666yuN2nn/+eQYMGMD999/Pnj17WLlyJcOHD+fll18uc0C1YcMGr96H+2C7NOVN61AyaZo2berVMVQCONnZ2ej1ehwOh1oUVq/Xk5OTo9bA8WYQWdUZatURMFXeY1Vs93zer9JByWQy0aBBgzKDYkrBYyWIFhERgdlsVrN2lEyqUaNG8f777/P999+TkJDgsW4TQKtWrZg0aRLLly9n9uzZHD9+nI8++oi1a9cyduxYxo8f73Hqj7cFi73NLBk9ejQjRoxg3bp1fPLJJ5w5c4YzZ864LBMQEEBsbCyxsbE0aNCAuLg4GjRoQO3atUtMZ/S22Len8zczM5PDhw8D0LVrVwwGg1d1dZQMHOXatFqtGAwGYmJiMJlMpKamYjQa1cw6ZfvO9Y7Km04ldW6EEEIIIURVu2ynUImLW3nTCywWC0lJSSQlJWGxWKhbty7Lly/nmmuuISsri4ceeojevXuX2XYboEmTJvzyyy9MmDABjUbDihUr6NevH/v376+Ot1UpR48eBaBZs2ZeLa9kHyUmJnp8XsnIUQbk586dO/+dvMKUdn4ajUby8/Px9/f3OuCh0Ov11K9fn6CgIHU6ldlsJjo6mu7duwPw7rvvlrmOgIAAxo4dy8GDB1m0aBFNmzYlKyuLOXPm0KpVK1544YUSwZTq4Ofnx6BBg1ixYgXDhw+nb9++PPjgg7zxxhusXLmSb7/9lgULFvD8888zdOhQOnXqRN26daukaLGzXbt24XA4iIuLIzo62uvXObcxV/bJbrern7fVaiU9Pb3E52+xWEhMTCQhIYHs7GyXc8D9nDEYDERFRXmdfSNTroQQQgghRHkkgCNqhHNmiKfaEsrfnaestGrVii+//JKnnnoKvV7Pzz//TOvWrZk3b16pUzaguADxtGnT+Oyzz6hVqxb//fcfd955J4sWLSpRv6MmHDlyBKh4AOfw4cNq7Y60tDS1dofBYECr1aoZAEVFRRUONpSnpgeb1b390uqdGAwGGjRoQHBwcLmZFco+pqamUlhYqGZ5REREAMWZV9nZ2VitVrXO04oVKzCbzeXun6+vL/fccw/btm1jxYoVtG3bFqvVyqJFi2jbtu0FC+QEBwczZswYJk6cyJAhQ+jUqRN16tSp8kBNabZv3w5QamHm0ihTqIKDgwkNDUWv16PVatU6RkajkdDQ0BLnV25uLjk5OeqURedzoKI1ctyd7+uFEEIIIcTlTwI4okY4F9X1VGBX+bsyRUEZODdv3pypU6fyyy+/0LFjR6xWKxMnTqRnz54kJCSUuc0uXbqwefNm+vbtS0FBAdOmTWP48OE1mqFSVFSkZhGVNnXGnRLAKS2A4amYrhJMUB6eMgsqEhDxNNhU1lEdA1BPA+mqHuw6H4OqKPqcm5tLdnY2ZrNZLWKssFqt+Pv7q4GEjh070qRJE6xWK0uWLPF6Gz4+Ptx6661s2bKFNWvW0LFjR/Ly8lwCOVVZwPtiU9kAjpKBExYWhlarVTtPKd81MTExBAYGlsieMRqNBAYGEh0dTYMGDUrUyDmfc0YKjQshhBBCiPJIAEfUCOfpBZ6mGigBG/dBkvLctddey++//87s2bMJDg5m+/btXH/99axdu7bM7YaFhbF48WJmzZqFXq/nt99+4/bbb+fQoUPV8j7L888//2CxWPDz8yu1lo875wCOEqyJioryWP8kOjqaWrVqYTAYKCwsJC0tzWPgo6IBEU+DzerMIPA0lamqB7vu9YJKm/7i7fs0Go3YbDbCwsJK1EpRMj6gOEMsMjKSCRMmALBw4UIKCwsrtO8ajYaePXuyadMm1q5d6xLI6d27N/PmzXPpfnU5OHPmDPv27QMqHsBRCoeHhIQAxedXcnIyycnJasafexAUir974uLiiIuL8/hcRaZMuTvf1wshhBBCiMufBHDEJUuj0TBixAjWr19P586dyc/PZ+TIkXz11Vflvm7o0KF88803xMTEkJSUxB133MHq1asv0J4XS09P5+mnnwagU6dO+Pn5efW6+vXrA3D69OlyB3vKoDA6OhpfX1+ioqI8Bj4qGhDxNNiszgyCqh4se+Lt/nuznFLkNjIykqCgoBLLKoHLkJAQMjMzsVgs3HXXXURGRnL69Gn+97//Veo9aDQaevTooQZyOnTogM1mY8GCBdx6661s2rSpyotWX2hnzpxh0aJFDBw4kPz8fJo3b06DBg28fv23337L22+/DRS3Hlc6gzlP2VSUl7kmhBBCCCHEhSQBHHFJMxgMhIeHs3TpUvr374/dbmfEiBF8+eWX5b62adOmfPvtt9x4443YbDYmTJjA888/T0FB1yZRxwABAABJREFUQbXvd35+Pk899RQnT56kfv36vPbaa16/Vhmsnjlzhvz8/BI1cDxRAh7KozoCIso6LkQApzp4ewy8WU7J0gFcljWbzfz777+YzWb0ej1BQUGEh4fj7++P3W7nzjvvBGDNmjXn9V6UQM7333/P22+/Td26dTl16hRPPvkko0aN4uDBg+e1/gstNzeXL7/8kmHDhnHdddfxxhtvkJKSQnR0NO+//77XHci2b9/OiBEjKCoqYujQoTzwwANotVoiIiJcpmwqLBYLhYWFmEwmqU8jhBBCCCFqnARwxEWltFosJpOJf/75p0SQwmAwUK9ePUJCQliyZAkDBw5Ugzj33HNPuV2qwsLC+Pjjj3n66afRaDR8+umnzJ4926tCspXlcDiYMmUKe/bsISgoiPfee4+wsDCvXx8VFaW2D//hhx+wWq2lds2piJouTHyxq8jxKS1L58SJE6SmpnLixAm1oHFERAS+vr7o9XoGDRoEwNdff13haVSeaDQa+vbty7fffssjjzyCTqfjr7/+YuDAgdx+++28//77ahv7i01hYSG//fYbzz77LN26dWPChAls3boVh8NBhw4dmD59Olu2bCE2Ntar9R09epSBAwditVrp3Lkzs2bNwmg0qvVvYmNjiYyMVAuDK981vr6+REZGlpl1JdeOEEIIIYS4ECSAIy4qpdUXMZlMZGVlceTIkRKDJL1eT3h4OIGBgXz88cc8/PDDaLVavvnmG9q2bcvzzz9PRkZGqdv08fHhySef5JNPPiEsLIzk5GTeeOMNDhw4UOXvLz8/n3nz5rFhwwa0Wi1z5syhUaNGFVqHRqNRB627d+/GarXi4+PjsWtOWdwHndIFp2wVOT5Klg64FptWat84FzRWAjkGg4GOHTsSFhaGyWSq9DQqT/R6PY899hjffvstt956K35+fhw5coS33nqLXr16MWTIED7//PNqDVx6o6ioiH379jF9+nR69OjBuHHj2LBhA1arlYYNG/L000+zdetW1qxZw7333qvWsCnP2bNnueOOOzCZTDRp0oQ5c+Z4nLJosVjUKVVKZ7vSMtecrx+5doQQQgghxIXgW9M7IIQzpfW1+53uyMhIzp07R0hIiFpkVKFkoOj1evR6PS+99BIDBgzgtdde49dff+Wdd97h008/5cknn+Tee+/F19fzaX/jjTfy3XffMWTIEBITE5k/fz79+vXj1ltvPe+2yJmZmaxevZqVK1eqd/ZfeOEFrr/++kqtLzY2lsOHD2MymdDpdC7durzlXrS3tGMP/1/TxX2KyeXO+X2XdXxK43yMdTod9evXJyIiwiWA46ygoIA+ffrwxRdfsGbNGm666aaqeitAcf2kOXPmkJmZyebNm/n222/566+/+Pvvv/n777+ZM2cOHTp0oG/fvvTo0YOgoKAq3b4nOTk5bNu2jf/973/89ttvLll2YWFh9OvXjzvuuIPrr7/e66lS7uu/6667OH78ODExMSxevFgNriUnJwO4dKCyWCxqq3dvpskp50RFzw1ROcnJyWVOFwXK7UgohBBCCHGp0jgu9YqWF6msrCy1QGlwcHBN785lQSkyqgymFampqRQWFmKz2Vz+bjAY+PXXX3niiSc4evQoAM2aNWPWrFncfPPNpW4nPT2dl156iaVLlwLQo0cPli5dqg7qFEoL6LIkJyfz0UcfsXLlSrULUO3atZkwYQL33Xefy7KlDerdBQQE8NBDD/HBBx8wZMgQbrnlFq699lquvvpqdRmr1UpeXl6ZQR3nDAKDwUB0dHSJDAPnwWlhYaFaCLks3gyyvb0+avI6cjgcatcu5dzyVCOltMCWxWJRW3i7H9vS5Obm8tlnnzFu3DgiIyNJSkoqNeBYVFTk1fsoL/h4+vRpvvzySz7//HN27typ/t3f35+ePXty880307t3b7X7WV5enlfbLa0ot8Ph4OjRo/zwww9s3ryZP//802W6WFBQEL169WLw4MH06tVLXY+3Rb51Op36s91up3///nz33XdERkbyww8/0KpVKwC1dhTgEgB1/5xKO37un31lgkvn61K4jqpScnIy8fHxXmUaGgwGEhISvJ5idyXYvXs37du3Z9euXbRr166md+eicblcH0IIIa4MkoEjLhnugRuFctfcZrOpQQb4///ZX7p0KZ9//jmrV6/m0KFD3Hbbbdx8883MmjWLZs2alVifTqdj9uzZdOzYkSeffJKff/6Z+Ph4WrVqRdu2bWnfvj3t2rUjKiqq1MHdnj17WLx4MZs2bVIH2s2aNeOhhx6if//++Pv7n9exUAYlp06dwt/fn3PnzmG1WtVgjMVioaioiLS0tFKzc5TflXbkzkEIi8VCYmKiOhi+UjMMlPedkZFBTk4OgYGBxMXFAcXHKCkpSf0s3Y+vknXj6+vrdfDGYrHQt29fl2lUVZ2F465OnTo89thjjBkzhuPHj7NmzRrWrFnDP//8w6ZNm9i0aRMAzZs3p0+fPtxwww20b9++1MCSO5vNRmJiIkePHmXr1q1s3ryZxMREl2UaN25Mnz59uPnmm+nUqdN5Xx+KN998k++++w69Xs9HH31E3bp11ecMBgM+Pj7qFESdTofJZHK5ViwWC4GBgR4/v4pmvInzZzKZsFgsrFixgvj4+DKXVeoaCSGEEEJcTiSAIy55znfOlQBGcnIy+fn5nDt3jvz8fLp27co999zDunXrmD9/Pt9//z0//vgjY8eOZcqUKSWyawAGDx5MixYtGDNmDAkJCezcuZOdO3eyZMkSoDhToGXLlrRp04ZWrVrRqlUrDhw4wJIlS9ixY4e6nh49evDQQw/RvXv3KrtLrwxMcnNziYqKIiwsjBMnTrgEE/Ly8rDZbGRnZ2MymYiNjS0x4FQydbRarUtwRgk+KJknV+pgVXnfubm55OTkuDynHKO8vDyMRmOJjIzygl5KwEZZVul45Ovry4ABA1i2bFm1TKMqS8OGDXnmmWd4+umnOXToEN999x0//PADO3fu5ODBgxw8eJC33nqL0NBQevToQc+ePenRowdhYWGcOnWKY8eOcezYMY4ePUpiYiL//fcfycnJJbKF/P396dy5M7179+aWW26pcB0ob/z5559MnjwZgJdeeonatWurz1ksFjWLQwlSarVaoDhrR3nObrerUwzFxSM+Pl4ySIQQQghxRZIAjrgsKAMyZcAdGRmJyWQiJCSEY8eOERERQVBQEG+++SYjR47k+eef54cffmDRokV88cUXvPrqq4wdO7ZEVkGzZs34/fffSUxMZNeuXezevZvdu3ezd+9esrOz+f333/n9999L7I+fnx933nknDzzwAG3btq3y96u0EjeZTHTo0IETJ05gt9vJz89Xj4eSOZCcnIxOp3PJzlF+1uv11KtXr0SWgRJ0uNJq3pQmOjq6RAaY8nPt2rUxGAzqdCtlwF9a0EsJ3CgBIOci0gDh4eEMHDiQZcuWsW7dOubNm+d1tktV0Wg0NG/enObNm/PMM89gNpvZsmULP/zwA1u2bCEjI4OvvvqKr776Co1GowayShMYGEjjxo1p2bIlvXv3pnv37gQGBgJUy3vLzMxk+PDh2O12+vXrR+/evV2mVinFis+dO4fdblc7UTlfG8pyZXWeuhLrQgkhhBBCiJojARxxWbBYLC6ZJsqADIoH2iaTSc2yCQ0NZdKkSfTr148FCxbw77//8vjjj7N8+XJWrVpVoqW3RqOhYcOGNGzYUG3zXFhYyI4dO9i7d6/6OHz4MEajkeHDhzNq1Chq1apVbe9Xmad/8uRJcnJy8Pf3Jz8/n/r166uDU2X6lHIcnKdMKQPPqKgoj1PTrtSMm9KUNgXNPejlzTQzJdMGUKdXWSwWNePJbDbTuHFjwsPDMZlMfPzxx4wZM6bq31QFREREMHjwYAYPHkxOTg67d+/mxx9/ZMuWLRw6dIi8vDx8fX1p0KABjRs3plGjRlxzzTVcddVVXHXVVURHR1+wGjEOh4Nx48aRmJhIbGws06ZNw263lwi0ZGRkEBAQgE6n81h/Svl8S5sm6V4EXAghhBBCiOomARxxWTAYDKSkpKiBCyVDRcluiI2NJSAgAIvFwqlTp8jMzOTaa6/ljz/+4NNPP+WVV15hx44dXH/99Xz88cfldofy9fWlWbNmNGvWjKFDhwKog9jqzpZIT09XCyA3atSI06dPEx4eTv369dWBqPK+lSk5ShDHnTJ9R5w/b4NeSsAmODjY5dgrdZyUTJzhw4czb948HnnkEVJSUujbty+tWrWq8WCBr68vHTt2pGPHjrz44oucOXMGq9VKTEyMy7nvbdHhqvbGG2+wZs0a/Pz8mDlzJiEhIWqXKWc6nQ6r1eoS5FSCn861cJRMIXdXal0oIYQQQghRcySAIy4LBoOB8PBwdfCrULIdlKK+J06coKioiJCQEMLCwsjMzOS2226jQYMGPP300xw9epTbb7+dN998k1GjRlVoHwICAqrwHXmWk5ND//79OXjwIFFRUUyZMoXTp0+Tl5entlG3WCykp6ej1+s9FtBVsm5qOhBwpXLOeHKugxMVFYXBYEBpDDhlyhQKCgpYuHAh06dPZ/r06Wi1Wpo1a0b79u1p27Yt7dq1o2XLli7Tgy4059oyNW3Dhg1q3ZtHH32Uq666Su3+5sxgMGA2mwkNDVWvA6U1tXstnNICOJKlJoQQQgghLjQJ4IjLhqfAhHNh49zcXPz9/dVgD6AWpm3cuDGfffYZkydPZuPGjTz55JPs27ePGTNmVFlHnPOVl5fHsGHD2L59O+Hh4Wpr88zMTLRaLenp6URERJCenk5+fr6aXeBOBp4XD+cAo/JZ6fV6tT7RW2+9RXx8PN988w379u0jNTWV/fv3s3//fj766COgONOlZcuWtGvXjnr16pGfn+/yKCgooKCggPz8fGw2G/n5+bRp04aJEydekKDjhXLw4EF1qtngwYMZOHCg2l3Kua4NFF8DMTExLnWh7HY7Wq3WYy0cIYQQQgghLgYSwBGXDefCo8rvzsEKpRNOUFBQiddGRERgMBj4+uuvmTJlCtOnT2fZsmUkJCTw8ccfEx0dfYHehWeFhYWMHj2aX375hcDAQGbMmEH79u3VbIGTJ08CxV2lwsPDSU9PByA7O5uUlBTCw8PVDA9wLfosU0BqjnOAEf5/Co/FYkGv15OXl0fPnj258cYb0Wg02Gw2tm3bxt69ezly5AgHDhzg3LlzanFtb23cuJHvv/+ezz77TJ1ueCkzm81qfZ5OnToxZ84cQkJCADwGYtyLnlssFjIyMtQ6WZ6CnFK0WAghhBBC1DQJ4IjLinNGg/Mgy2QykZKSok4zUor+utNoNDz33HO0bt2asWPH8scff9CjRw+WL19eY21ri4qKePTRR9mwYQM6nY533nmHHj16oNVq1cFnXl4e/v7+WCwWIiIiiIiIwGazcfjwYdLT08nNzcVqtaqtxJXjlJaWRlpaGlDcaUkGplVPGfh7CpZ5KiCdmZmpZohZLBb8/f1JTU0lOjoam81Gjx49uO2227BarZhMJjIzMzlz5gyHDh0iKysLrVaLj48PBoMBPz8/7HY7fn5+hIaGYjQayc/P54033mDXrl1qzac+ffpcsONR1QoKChg+fLhatHjlypXUqVNHfV45353r2rjXurFYLISGhpZYzllubi5ZWVkkJycTEREh14sQQgghhLjgJIAjLlpKLZDyOHeJcS4s6vz3tLQ0srKyyMnJISoqSq2LYbfbsVqtanADwGaz0a9fP/78808GDBjA4cOH6d27Nw899BCTJ09WB9fe1h0pKCjwajlP01kcDgfPPPMMK1euRKvVsmjRIkaMGKFmEGg0Gk6ePEl2djZ5eXnExcWp79toNBIeHk5hYSFZWVlqgEcJGuTm5mKz2cjOzlaXlwHp//O2a1J556nSraisltTOwsLC0Gq1+Pn5ERwcjFarVbNJCgoKsNvtaDQa8vLysNvt1KtXj9tvv93jupTW5koha+W8ueWWW7jvvvvYuXMnd9xxB1OmTGHixImldlxy5qljkyfenvfeXkelfR7PPvssv/76K4GBgXzzzTfqdezMarVit9tJSUnxuH2NRoOvry/5+fnqd4J77Ruj0UhaWhpFRUVkZ2dX+nrx9nvtQnXtEkIIIYQQl47y/29diEuI0WgkOjq6xEA5KiqK4OBgdRqRUrw0KCgIrVZLTk4Of//9N8nJyWRnZ5OcnExMTAx//PEHgwYNwm63895779GkSRMWLFigtoGubq+//jrvvvsuADNmzGDAgAGAa6aRXq/HaDS6ZBCYTCYsFgvR0dE0bNiQ1q1bu3Q9UormRkdHExQURFBQkEylqiZGoxFfX1+vj29GRob6s/I5KY8GDRpQq1YtoqOjiYmJoXbt2sTExJS6LoPB4NKqXDm/IyMj+d///sfQoUNxOBxMnjyZu+66i3Pnzp3v272gli5dyoIFC9BoNCxZsoTatWurUygB9XoAyM/P59SpU2RlZXHq1CnsdjuAGtyKiooiMjLSY+FvKD6WcXFxREVFyfUihBBCCCFqhARwxBUhOjqadu3aER8frw7SIiMjadCgAU2aNCErK4usrCzS09Ox2Wxq4dOQkBC++OILVq9eTePGjUlPT+exxx6jXbt2/Pzzz9W6z++99x6vvfYaADNnzmTs2LFYrVZ1epjSslmv11O/fn3Cw8PJzs7m6NGjZGdnq9N2nAMA7gNTZVAaFxcn2TfVxLnDlDdCQ0O9WldUVBTx8fFERUW5LJObm0taWppLvRYlkKHT6bDZbBgMBgICAli8eDGzZs0iICCAjRs3cv3117Nnz57zebsXhN1uZ8uWLTz++OMATJw4kR49eqhBTYUS6ITiY1e7dm3sdjthYWFq5p3z1Daj0agWQ/dErhchhBBCCFGTZAqVuOIZjUbq1q1LWloa4eHhxMbGlqih07dvX1q3bs2iRYv46KOPOHjwIP369eP2229nxowZNGrUqEr36f3332fChAkAPP7449x2222YzWZ1GlRkZCQGgwGTyYS/v7+aNZCSkvJ/7J13eFNl+8c/SbqSdNLFatlqxRdBEFFkuDcuVEBARVEUcaPgABFlCIoCIqIiCIgoKsqriOAGURFRBKoMgZbZprtJmrZpfn/0d86bpJkddN2f6+KibU7OeXLO8zw5z/fc9/cmLCyMEydOEB0dre6vNgxYxcTVM7V5XpxTAAM5pidfHUW0UKKwFB8dqDTwTk5OVkUdi8XCTTfdpHo+HThwgAEDBjBv3jxuu+22Gn2W6lJRUcGxY8c4fPgwhw8f5siRI+r/mZmZHDlyxCWC5tprr2XChAloNBpVkFFwN4lOSkqiffv2AGRkZKhCra/zLf1eEARBEARBaCiIgCM0OzyVbk5NTVVFEU8GpgaDgU6dOjFlyhSGDx/OzJkzWb16NWvXrmX9+vVMmTKFBx54ICAPEV/s2bOH6dOns2LFCgBuuukmbrrpJnUBrkTduBuyOre3sLCQ5ORkl/0qPizKor861MY+miK1eV4CKfFusVg4dOiQ6h2j9GGz2axGnyh+Lkr0SUhICNHR0S7ROM7CTvfu3fnhhx+49957WbduHaNHj2b79u289NJLaqWzk8GuXbu45ZZb2LNnj99tdTodF154IQsXLlSrrinV5BTcz6fzz56EWk9IvxcEQRAEQRAaCiLgCM0OT6KHs7Gv4pmhbOu+AGzTpg0vvPACl156KW+88Qa//vorEydOZMOGDbzxxhu0bds26Dbt3buXl19+mZUrV6rlzocOHcro0aOx2WycOHGCVq1aER8fz+HDh9WIAKWqFFRGFBw5coSSkhJsNluVqIL8/HwSEhKCbptCoNEhzY3aPi/+Ij7MZrOaCuUs1FksFoqKirDZbC7VxhThxnk7d2EHKiNf5s6dy8yZM1Vvme3bt3P11Vdz/vnn07NnT1XwqQvWrVvH8OHDKSoqQqfT0bp1a7XaU1JSEm3atCEqKoq2bdvSrl072rZtS1JSElarleLiYqByfLqbD3vCuYw4VJo9e4pmAun3giAIgiAIQsNBBByh2eGpdLOCsrjNz89XTYE9ReMA9O7dm549e7J27VqmTZvGN998wymnnMJ//vMfzjvvPPr27Uvfvn19iiZ79+5l1qxZfPDBB6pwc+GFFzJ+/HhSU1OxWq2UlJRgNBopKSnx2F7nNjocDiIiImjRokWVdrt7qwSbGhJIdEhzpLbPi9lspqioCJPJRLt27arsW+m7ycnJLv1YSalT0oIULxf3qkeehB3F3DgrK4s777yT1NRUXnjhBbZs2cKWLVuAyippvXv35rzzzuP888+nT58+AYkl/nA4HLz66qtMmDCBiooK+vfvz/vvv09CQgI5OTlqdI3dblfHZVJSEvHx8eo+lHbo9XqXMeHtujhH4QE+q4RJvxcEQRAEQRAaCiLgCI2Gk+FFoSxuExIS1DLbnqJwDAYD5eXl5ObmMnToUM4++2wmTJjAH3/8wY4dO9ixYwcLFy4EoEOHDpx33nmcd955nHvuuXTq1Il9+/ZVEW4GDBjAs88+S9++fbFYLFitVvR6PVarldzcXLV8uXOql/NC1FkocheNlCgCqIw2UH6X1JCGh9FoVIUYT9dGufaKWbESOaJEZPlLC/IlSERERGC327n11lsZPHgwX3zxBZs2bWLz5s1kZ2fzww8/8MMPPwCVKUzdu3enb9++XHbZZVx44YVBl74uLS1l3LhxLFmyBIA777yTV199VY30cW6n1WpFp9Oh1+tdSpk7fx6l0lZxcTFlZWV06dLFo4DqHoUXSCpVbSPeOkJ9kZ6e7nebhIQEUlNTT0JrBEEQBEEIBo3D/fFsM8LhcAS94AiUwsJCYmJiKCgocDGTFQLHvWtmZ2dTXl5OSEiIS+WdQK9hoF1d8RJRUlWUilXuHD9+nPLycgoLCwkLC6O0tBSdTsfvv//O5s2b+emnn9ixY0eV4yYmJpKTk6MKN+eddx5Dhw7l3HPPpU2bNgDs378fi8VCmzZt6NKli8v7S0pKPC4+nY1pPaWSKN4pYWFhaklxRdQBam0hGcj1CHR8NIZxVBdTqNL/FDxdG2U8lJaWqtffUwSJp/a5R26ZTCa1P1ZUVFBaWkqbNm1c+tThw4fZtm0bP/74I5s2bSIjI8Nln2eeeSaPPfYYN9xwAzqdjrKyMp+f0WQyMXz4cDZv3oxWq+WFF17gkUcecek/OTk5FBcXU1paStu2bf32T2X7v//+m/j4eKKjoznttNM8but8DmojPSrYecjbfBbM/prSOAqE33//nZ49e7Jt2zbOOuus+m5OoyMjI4O0tDSXSm3eMBgMpKenNwsRp6mMD0EQBKF50KwjcA4ePEiHDh3quxlCgJwsLwrFSyQ/P58WLVp4vaFTomNatGhBbm4uYWFhREZGcuONN3LjjTcCUFBQwDfffMPmzZv57bff2L59O9nZ2UClcDN27FiSkpIwm81qBanCwkLy8vIoKCjAbDbTokULl3QR96gbZyFH2QdQRcAxm82q0KQIAgaDQV1ISiROwyGQa6OIK4pZsb9qSs6YTCaKi4uJjIzEYDAQFhaGVqtFr9dz5MgRwsLC1IpOVqsVs9mMVqvl0ksvZciQIaqg89tvv/Hbb7/xwQcf8OeffzJixAgmT57Mww8/zJAhQ4iIiPB4/PT0dG6++WYOHjxIdHQ08+fP55JLLnERJ5UoG6WimnuFKU/o9Xo0Gg1du3atEpXmjiczc2/b1UWkjHjrCCeb1NRU0tPTXXzePJGens7w4cMxmUzNQsARBEEQhMZEsxVw3nzzTZ566im2bNlCp06d6rs5QgC4p0ooi5/aXgAZjUays7OJiYnxuf/Y2FjVVyY6OlpdeCqLQuXJ/kUXXcQ111yD0WgkMzOTH374gejoaHr16kV+fj52u51Dhw6RlJREYWGhKhiVl5cTGxtLTk6Omj5ltVqxWq0AxMTEuDylt1qtqrmtNy8PBbPZjMPhcDFvloVk9ajtKD73iJm8vDyPERrO185XCpCn9jkcDvWfsg9lfDmnYdlsNkpKSigoKMBut2M2m4mMjCQ6Opr27dtz+umnM2bMGGbOnMmrr77K66+/zr///su4ceN44YUXePDBB7n77rtdRNB169Zx6623UlRURGpqKsuXL+fUU09VBamKigpKSkqIjIxEq9XSsmVLbDYbkZGRakUsb6JKVFQUUVFRAZ3nQPt9oKmG7tfNWxuV6+Fv7goksqsZB9AK1SQ1NVVEGUEQBEFoxDRLAeett95izJgxzJs3T8SbRorzoqq2hQeDwUD79u2D2rfzYuzgwYNqdIPRaHR5yt+iRQsuvfRSADWMPSoqit69e1NcXExeXh6FhYXExsbSqlUrNcLHarWqvjgRERGUlpaq71cWh8r/ycnJVRaa7tW1wsLC1DaJSWvDJi4uzutrzuKNe19VXvMUOZKUlKT2WeU1JWXLuT+YTCbCwsJcIsCU1533qdfrueuuuxg2bBiffPIJCxYs4OjRo0ycOJEZM2YwZswYxo0bx8qVK3niiSeoqKjgnHPO4cUXX0Sr1bq0GVAFH+UYUVFRLu2rDf+mQPt9dQVO8ZgSBEEQBEEQahut/02aFm+99RZ333038+fP57777lP/rjyNFhoHRqORkJCQBhk1opgOKykfISEhLpFDSglng8FAbGwsBoNBjbBQfDkqKirUSBvl74rAU1paCuBSRUfZn3NKlWJyqyzki4qKKCoqAnBpk7L/7OzsgLwRhJOHv37uXk3J/ZorAoI7Sp9z7itFRUVkZGRU6VOKB5Tzk3uTyaT2VZPJhMlkoqioCLvdzujRo9m/fz9vv/02aWlpFBQUMHPmTNq3b8/48eOpqKhg6NChLF26FJ1OR2lpKXv37iU7O5vw8HAXUUnp04DLZ3E+L3XZd2uSPtWQ5yhBEARBEAShcdKsInDefvtt7rnnHubNm8e9997r8lpdmRkLjZNAn557ioDQ6/W0aNECvV6v/s15cZmfn68KLc6pL1arFZvNphrTlpSUoNPpyM/Pp2PHjpSWlmK32zl8+DBt27YlJKRy+JpMJhcTY0+RNgaDQU0t8fR5lM+blZVVJTJDqD/8RYl4qqZUXl6u+ixBZaqdO+7ChJLeV1FRQUZGhkulM/fjeyvBrfTZ0tJSUlJSuOmmmxgwYABr1qxh2bJl/Pnnn6pZ8e23347RaCQ2NpZ9+/YRExOjpgd6qxqVnZ2tpgc6C0+K2XggkS7BCjI1iaI5GZFtIrgKgiAIgiA0L5qNgLNkyRJGjx7NK6+8wtixY7Hb7Wi1WjQaDb///jvr169n69at/Oc//2HgwIFccMEFQe3fZrNhs9nU3wsLC2v7IwhO1EUKlbuvTlZWVpUFo6f3OKdIKRECkZGRJCYmYjabycjIIDw8XH2P4pvj7oGh1+tJTk6mtLSU5ORkCgoKOH78OGFhYeTm5qLX68nIyMDhcJCTk0NqaioZGRkUFRURFRWlepcoUTZRUVFqpI3zsRRjXGfzVqXtioBUX2kfMo6Cw70PKYKOzWZTK6j5EuycvW/i4+MpKirCarW6+Di5460Ed2xsLAcOHECn05GZmQlAbm4uvXv3ZsCAAezZs4fo6GgGDBigGhQrIqdz1TdPqVxKH3Zus/IZAL+RLsr+gxF7FDx5EDWUEuAi4AiCIAiCIDQvmryA43A4sNvtTJ8+HfjfAlFZUK9Zs4a7776bkJAQCgsL+fTTT1m2bBkTJkzg7rvvDvg406dPZ8qUKXXyGYSq1IXxrvOiNjExscqC0ROeFrPKwlkxQ1aMhZOTk9VtPO0vPj5eXdharVb0ej0tW7ZUTV2V6lI6nQ69Xo/FYlHLkTtH1yg/JyQkqG1QoiqUtBll4Zedne3ig+MsQjm/drKQcRQ87lFgypgwmUw+qzApkWAKBoOBnJwcAEpLS71WX3OPLHEuNd6mTRuXdC7l9RYtWvCf//xHbZeC0kedI8gUEdF9nLiPeeX3mJgYv300GLHHHU8eRA3F30ai5ARBEARBEJoXTV7A0Wg0hISE8Ouvv9KvXz8mTZqE3W5nwoQJ/PTTTwwZMoQHH3yQm2++mZiYGH744QeeeOIJFixYwIUXXkjnzp0DOs7EiRN55JFH1N8LCwtJSUmpq4/V7KmL9ARvC0RPiz2LxUJWVhaAKvYo7XJeeDobCzvv1xN6vV4VcHJycrDb7erfAY4ePaqWfU5ISCAjI4OwsDB0Oh0JCQnqIlpJf1HSAk0mEzabDZPJpLZVEXbcF6H1XVpcxlHweCuHrUR6ecPT64pI6F7xTRFdnD2WnHH+myIKZWdnk5CQ4FFEKi4uVt/nPHachRz343gSjnz1TfeIOm9ij69oGm9zQEOp3NaUBJyMjIyAylsLgiAIgiA0Z5q8gAOVHg0xMTH8+OOPnHvuuTz77LNYrVb27dvH008/zeOPP64uXFJTU8nOzmbixIls2rQpYAEnPDzcJU1GaHwEs0A0m83qItQ56sE9pSXQMueKiazBYECv16uLWCUqRzE0Dg8PVysCKZE9qampGAwGTCaTx8iFhIQEj9EYyjE8ta++FqgyjoLHk+DhTQRR8HR9vfkkOafl+RoTzkJSQkKCKrwpFdQSEhJc+rL7cdz/5l5lLVjcI+p8jWVvYqW3z3sy/G2aExkZGaSlpQWUEuZsbC0IgiAIgtDcaBYCTkhIiCribNmyhb59+/L888/TqlUr7rjjDlW8cTgchIWFqf43R44cqc9mCw0Yo9FIZGQk4H+B6a3Us/PfLRYLdrsdi8WiRuIokTdQuZiNjo6mtLRUXbwEumhPTEys4uHhfOzaWKC6RzsItUMgXiuezrm/6+B+fd2jt9y39WWA7bydp/7nLOwofVo5vpIK6N4Xnd9TXaHEWaSqTpSNcPJQqpotX76ctLQ0n9sqFdEEQRAEQRCaI81CwAFXEWfz5s107dqVXr16cfHFFwNQUVGBVltZVT0rK4vWrVvTvXt3oFLYkSpVgjMGg4H27dsHtK0SwWAymUhNTXWpTOW8SLXb7VUWl0r0AqCmTzmnOzm/PxjRxVvaTXWpC1Np4eR5rSjH8Za6FMiC2ZcY6KlSliLouFe1Uv73ZsCs4E/ccm6Pr5RAiaZpOKSlpXHWWWfVdzMEQRAEQRAaLM1GwAFXEWffvn3odDr1NUW8ycvLY+XKlSQmJtKzZ09ASozXFw3lvPtbKDq/DlTZ1tnM2FPlJ2Uf0dHRVfafn5+Pw+EgJCSkShSNc+RAsOeqOlEHvo7hvD+Hw+F3X4Fs01gI9LMEeo2ct/N1jWvzHNakL3lDmV8jIyPVaDXld+VYOp3O5diKkOSpv4PrWHMXt4KJsglmTNeXuBPIdWgoc6QgCIIgCIJwcmhWAg5UijgVFRVERESof9u9ezc5OTlkZWXx8ccfs3btWjZt2kTLli3rsaXCycbbos1fFITz64BHY+D27dt79BzxZxjsS2hRtnWu9hPoZ6vtqAPnlJ2mJM7UNzVJSQtGhKjN/hBMZIyn330Ji+6RXu7CaaBRNsGM6WDPS0MQfwRBEARBEISmSZMTcJxTobzh/HpGRgb9+vUjLy+PVq1a0apVKzZt2kS3bt3quqlCA8Pbos2TiOKpwo17BI4zztV13Mtz+xNp3L1KnBeHSpuzsrLUtniKRmgoZY+Fk0dtX3N/kWbVOa4/YdH9deex4r5tMFFlwY7pYJCxJgiCIAiCINQVTULAWbp0Kb///juvvvoqWq02IBFHwWAw8PHHH7Nnzx66detGx44dPYbuC00fb4s2T9EJvirc+Fq0eRNcfFX28SXEKG222Wwuf/e2HVBFQBKaJrVlzqv0QbPZTHh4uNdIs2CO62mfgUTC+BorNY0iCrRqlT/EFFkQBEEQBEGoKxq9gPPPP/9wxx13AJXpUS+99JJfEUfxWIDKihYDBgxgwIABJ63NQsMk2AVgXl5e0GKfN8HFG96EGGVxqLTZ/e/etvOVriU0LWorLUrpg1A5x/qKNAv0uN726U5diSGeomREeBEEQRAEQRAaOo1ewMnKyiIiIoL27dszZ84c7HY7r7zyik8RRxFv3n77bUaOHEloaOjJbrbQBIiLiwtq++qkaHgTYtzx5yvibX/+2ikiT9Mj2Our9JmYmJiAI82qu0936rJClLsAW9uCl4ikgiAIgiAIQm0TWJ5RA0QxSv3uu+8455xzWLlyJWeffTZz587l4YcfBlBFHE/cf//9jB49mqeeeuqktVlofCieNUppYwWj0egzcsAT7gu7QNI0At0ukDYHuj93U+a6wFPbmgK+zn1DIdjr69xnauvzVadf1zbBCrDecD8n1ZkbBEEQBEEQBCEQGq2Ao5RPNZlM6HQ6zjzzTObOnUuvXr149dVX/Yo4TzzxBD169OD2228/mc0WGhneFrvVWYDW5cLOeRFZUwHmZCxAG7LAURNOhvhVU2pyfQP9fA1dyKrNPu5+ThqCOCUIgiAIgiA0TRp9ClWvXr0444wzADjnnHN47bXXGDt2LK+++ioAc+bMQavV4nA40Gg0OBwOSktLSUlJ4ddff0Wn09Vn84UGTm36YtRlOkhWVhbFxcVERkaSlJQUVJvrusS4J5rq4rYx+KjU5PoGaobtLmo0tJS82uzjjeGaC0J1SE9P97tNQkICqampJ6E1giAIgiBAExBwRowYQUFBgfr72Wef7SLiOBwOXnnlFTQaDcXFxcydO5cBAwbQt2/fgCtVCc2XkyFm1DbBtrk+PDsa2zkNlMbYX4IhUDNsZ1GjqXvCNPVrLjQ/EhISMBgMDB8+3O+2BoOB9PR0EXEEQRAE4STR6AUcgJiYGAA1ysZZxJk7dy4ajYY5c+YwceJEXnvtNXbv3g38Lw1LaB7U1/VW/JrqkqSkJNUcOVicF9u1cY4C2UdTGnv19Vnqsz/7izpRKqMp1Eb/qu1x1JT6oCDUJqmpqaSnp2MymXxul56ezvDhwzGZTCLgCIIgCMJJolELOO5VppxvyM8++2wWLFjAfffdx6uvvsratWs5duwY27Zt47TTTquP5gpCUARTLaimaTGS/iEEQzD97WT0L6mcJgi1S2pqqogygiAIgtAAabQ5ROXl5aq3zZ9//unymmJa3KtXL15++WVCQ0PJz8/n559/pkePHvXRXEHwiC+z18ZgiCsIDQF/Y6WhmyoLgiAIgiAIQiA0ygic8vJyQkJCqKiooGfPnvTv35+pU6cSHR0NoEblWCwWPv30U0JDQ/n+++/p2rVrfTZbEKrgyx8kUMPYYJBIBaE2qa/+5H5cfyldTd2HpyGTkZERUCqOIAiCIAiC4J9GJ+A4ize9e/cmNzeXa6+9lqioqCrb3XPPPXz44Yds2bJFxBuhQeJr4RmoYWwwyEJWqE3qqz+5H9dfSpdUiqofMjIySEtLCyjyyWAwkJCQcBJaJQiCIAiC0HhpVAKOs3jTq1cvCgsLWbJkCf379/doSBkbG8uPP/4oaVNCgyUQL5HaXHzKQlaoTeqrPwV7XKkUVT+YTCYsFgvLly8nLS3N57ZSjloQBEEQBME/jUbA8STeLFq0iP79+6PT6apsHxISwrx58+qhpYJQu/hafAabwiILWaE2qa/+VJtjQqh70tLSOOuss+q7GYIgCIIgCI2eRmFi7E28GTBggEfxRhCaC2J0LAiuyJgQBEEQBEEQmiqNIgInJCQEu91Ojx49KC0tFfFGaHIEGzWgbA+V40NSooTmjPP4CSS9yn17QRAEQRAEQWgMNAoBB2D79u1kZmayevVqEW+EJkewZrDK9iEhISQmJp6EFvpuiyyGGwdN9Vo5j5/ExES/Y8h5+6Z0HgRBEARBEISmTaMRcHr16sW///5LdHS0iDdCo8KTwbY7wZqyBrJ9IMcNBofD4fHvnsQnfxFF3vYl1C7Ogo3BYGiyVcicx0Ow481fX6ztcSQITY1AysCLSbUgCIIg1A6NRsABiIuLq+8mCEKdEKzhakMyI/YkJjVVoaCx4X4dmmoVsmDHgxgcC0LNSUhIwGAwMHz4cL/bGgwG0tPTRcQRBEEQhBrSqAQcQRAaBu4RNu6L4aYqFDQ23K+DP6FDKjgJghAoqamppKenYzKZfG6Xnp7O8OHDMZlMIuAIgiAIQg0RAUcQGjn1sej2F2HTkCKEmjPB9onGFDklYlP9kpGREdDCXWjapKamiigjCIIgCCcREXAEoYHjb6FaH4tuibBpmjSm61pb/V6EoODJyMggLS0Ni8Xid1uDwUBCQsJJaJXQ0BGvHEEQBEGoOSLgCEIDx99CtT4W3RJh0zRpTNe1tvp9Y4o6aiiYTCYsFgvLly8nLS3N57ayIBfEK0cQBEEQag8RcAShgeNvodqYFt2CUFvUVr9vTFFHDY20tDTOOuus+m6G0MARrxxBEARBqD1EwBGEBo4INIJQd8j4ckW8bYS6QLxyBEEQBKF2EAFHEARBEJoBf/zxB5GRkV5fz87O5oYbbhBvG6FeEa8cQRAEQfCOCDh1hMPhAKCwsLCeWyI0FpQ+U1toNJpa3Z+v9lksFiwWS8DRDMq48PeZZRzVnNruVxDY9T6Z/a86x63t/dUHwY6jAQMG+N2nXq/no48+8ivOxMfHExsbK2NTqDXCw8PR6/UBeeXo9XqWL19eKyKi2WwG6mauFARBEITaRuOQb6w64fDhw6SkpNR3MwShQZOZmUnbtm29vi7jSBD8I+NIEGqOv3EkCIIgCA0BEXDqiIqKCo4ePUpUVFS1nuAWFhaSkpJCZmYm0dHRddDC2qWxtRcaX5ubUnsdDgdFRUW0bt0arVbrdR/BjKPGcn6knbVHY2gj1F0762Ic1TWN5ZrVlObwOZvKZwx0HAmCIAhCQ0BSqOoIrVZbK09yoqOjG9WNUWNrLzS+NjeV9sbExPh9b3XGUWM5P9LO2qMxtBHqpp11NY7qmsZyzWpKc/icTeEzBjKOBEEQBKEhII8aBEEQBEEQBEEQBEEQGjgi4AiCIAiCIAiCIAiCIDRwRMBpoISHhzN58mTCw8PruykB0djaC42vzdLehnW86iLtrD0aQxuh8bTzZNBczkVz+JzN4TMKgiAIQkNDTIwFQRAEQRAEQRAEQRAaOBKBIwiCIAiCIAiCIAiC0MARAUcQBEEQBEEQBEEQBKGBI2XE64iKigqOHj1KVFQUGo2mvpsjCA0Kh8NBUVERrVu3Rqv1riPLOBIE78g4EoSaI+NIEGpOoONIEISaIwJOHXH06FFSUlLquxmC0KDJzMykbdu2Xl+XcSQI/pFxJAg1R8aRINQcf+NIEISa06wFHJvNVmfVE6KiogD4559/SE5O9rltoE9yAvWbrq8nQ/XVvoZ+XoSqFBYWkpKSoo4TbyivZ2RkEB0d7XPbhj6OGno/re32ORwOLBYLFosFg8GAwWCo0f6EqgQ7jjIzM/2OI0GoCxry/Hf8+HFOPfVUGUeCUAMC/T4SBKHmNFsBZ82aNWzdupWxY8fSunXrWt+/chOSnJzc6BeegdJQF8YWiwWz2YzRaMRoNNbqsYWa4a8vKK9HR0er48j5ejqLAg19HDW38etwOAJa5IiAU3OqM44E4WTibX5xn8/rcz6QcSQINUe+0wWh7mmWAs4///zDDTfcQGxsLOHh4dx99920bNmyvpsl1BFms5ny8nL1JlFo3DhfT29RHYIgCELDR+ZzQRAEQQiOZukyFR8fT6tWrcjPz2fWrFm8/vrrZGVl1XezhDrCaDQSEhIi4k0TQa6nIAhC00Dmc0EQBEEIjmYXgVNRUUFUVBRdu3blmmuuobi4mKlTpwJw3333kZycjMPhCDoE0GazYbPZ1N8LCwtrtd1C9VH8NySss+ETyDjy5aciCIJ8HwmNB5nPBUEQBCE4ml0EjlarJTw8nNTUVH799Vfmz5/PoEGDmDZtGgsWLODo0aPqQj9QTwiA6dOnExMTo/6TSgWCEDwyjgSh5sg4EgRBEARBaJo0OwGnoqICgM6dO5OdnY3BYOD999/nqquuYtq0abz11lsUFRUxefJkvvvuu4D3O3HiRAoKCtR/mZmZtd52i8VCdnY2Foul1vctCA2BkzGOhOCQeafxIeNIaM6YzWaysrIwm8313RRBEARBqHWanYCj1VZ+5P79+5OTk8NPP/1EREQES5YsYdCgQUydOpXzzjuPadOmkZSUFPB+w8PD1coEdVWhwNnsr7Egiz8hGE7GOGpoNPQx0hjnneZOcxxHQtOhpgKMzFmCIAhCU6bZCTgKCQkJVFRUcPToUQBiY2P58MMPadmyJenp6QwbNoyEhIR6bqUrjdHsr65vpMxmc4Ne/AoNn/oWUBr6YqMxzjuCIDRMAplvazonypwlCIIgNGWanYkxVHrbnHLKKXTs2JEtW7YwbNgwAIYPH47FYuHcc8/lww8/JDk5mcceeyyoSBx3NBpNrZnnGo3GWr0h8efxY7FY1NLb1TUZNBqNVcp3B+otFMh5C6YEaW0eVzi5BDKOgvGscsZbH6ru/oLFfYw4HI5aGXsKgfZnb9tVd96RcSQITZ9g50l/39kOh8NlTnTev/O86GtOqu17JUEQBEFoSDTLCBxlYdG2bVv27NkDwLBhw9iwYQOffPIJ69at49xzz+Wdd95p1ouQ2ogMMBgMJCYm1lmVCXnSJtSU+u5DnsZIQ4/KEQRBqA6BzLfe7htkXhQEQRCEZhqBU1FRgVarpU+fPnz22WdcfPHFbN++ndWrV9OvXz80Gg2fffYZeXl5JCYm1ndzTxruT/09Rc80NGojQkFo3jTEMrbVGXu1GbUjCIJQF1R3vlXmN4CYmJjabpYgCIIgNBqaZQSOYmTcu3dvduzYwd69e/noo4+44IIL1Igbo9FI27Zt67OZJx33p1venoLVt2eIIDQVvI2l6kSuydNpQRCaCu5zo9lsJjw8XARqQRAEodnTLAUchfPOO49HH32UZcuW0b9///puTr0TaCpJTRaKtS3+iImxUFsE2zdroy/XpuhS36lggiAI3vA3X3oSbJznRpnfBEEQBKGSZplCpdCiRQteeOEFwsLC6rspDYJAQ5trklplNpspLCwkOzub9u3b1/hJWjAmxoLgi2D7Um30PU9jqbqpUA0xFUwQBAGqzpfu85z76+5zo8xvgiAIglBJs47AAUS8qQY1MSY2Go3YbDbsdjsHDx6sceSMsj+z2SxROEKNCPYJr7/tlSfKyj9P/VMMjAVBaGp4irZxny+VhznKfYD763VdAEEQBEEQGivNOgJHOPkYDAbat2/PwYMHCQ8Pr3HkjFIuVKJwhJoS7BNef9srQkxeXh5xcXEB98/GYB4uCILgDU/Rie7zpdFoJDs7W70PELFGcCYjIwOTyeR3u4SEBFJTU09CiwRBEBoOIuAIHqluGkcg71NEnNpapNZ0wSvVe5oGDe06Kv3SuZJddna23/YFKyQ1tM8tCELzw3keCuQ7WbkPyMrKcpm/ZD4TMjIySEtLCyiq2mAwkJ6eLiKOIAjNChFwBI9U16smUF+Q2sxnr+m+xEenadDQrqN7v8zOzq7V9ikLHaU6S0P53IIgND+c599Ao2kUrxvnlFElOld5XWh+mEwmLBYLy5cvJy0tzet26enpDB8+HJPJJAKOIAjNChFwGhEOhyOg7ZRS6DXl6NGjxMbGBrUwrM30j0A/b01xb/PJPs9C7RBo3wv0utV2/3Nun682BHpcZcEEuHhHuD/Bru3+LONDEJo+wc5/1f3ud35fVlYWRUVFWCwWWrVqJXNIMyctLY2zzjqrvpshCILQ4BABR/BK69atsdlsQd2Q1VWliLoMq5bqFk2D+ryOgfRPJbWgtlAWPjExMV5NkKVfC4JwMnCffwP9znZ/n8FgICoqSjzABEEQBMELIuAIHlFunhpKHrosSoWGTH30T2+ClZggC4JQ31RnTkxKSqp1oVsQBEEQmhoi4AgecV4cWiwWsrKygMobrPoQUAJdlIoBolCbBNqfals0qUk/DiYSyd14VBAEoTq4z1n+5kTn7QH156SkpJPZbEEQBEFodIiAI/jFbDZTXFwM1F9ETqCLUonUEWqT+jDlDua4tXkcEXAEQagu7nOWvznReXtA5iFBEARBCBBtfTdAaPgYjUYiIyOJjIx0MUrNzs4OqMxjTQj2OEaj0cXQVRBqQqD9qbbHg7/j1tbxZLwIglAbKHMJ4HNuUuYu+J/5usxDgiAIghA4EoEj+MVgMNC+fXuXv9VVhIB7GHawxxFDYqE2CSbyq7CwEJPJRLt27WrcB4N5el2TY8l4EQShNlDmkuzsbAoLC8nOzqZ9+/ZV5hdl7goJCSExMdHl/YIgCIIg+EcicBoRJyvqJZDj1tUTM/ewam/HcW9TMOemvs6jUH9U55oH8x6j0UhpaSlhYWFq33Xfj/vfa4L7uGhIfbouPq8gCA0LZZwfPHiQ3bt3q1E1RqMRm81GeHi4xzlAed1sNgc0X5nNZrKysmQ+EQRBEIT/RyJwGhH15e/i6bj+ntxX14TV3fjQ23Hc2xTMuQn2PIoxcuPB27WqjtdLMP3EYDDQrl07j/s/GT4zDcn7SXx1BKFp4Ou7Txnnhw8fxmg0kp2dTWJiohqxqwgu2dnZLu9XDI6r830t84ngifT0dL/bJCQkkJqaehJaIwiCUPeIgNOIqK/ywNU5bqALSvcbxEBTOtzbFEwbg/08DWlxLPjG27WqTh8O9j0nq6y3xWLh4MGDhIeHq8dtSKXDG1JbBEGoPr6++5Rx3rZtW0wmE1A5Nzl/j2dnZ9d4Ppb5RPBGQkICBoOB4cOH+93WYDCQnp4uIo4gCE0CEXAaEYGW+nU4HNXav7eynsrNmBIy7S8SRdkPQExMjM9j+rpB9PU59Ho9er1e/T0YL49gfT+UG0hwfZpY3fPsDY1GU6v7a0o4HA4cDoffaChvN/vO1zzQ61ZTfxjntiYmJuJwOKioqPD7Pn/9wGw2ExERgc1mU/uh83hw/nwWi0Vth9VqJSEhwcV3wpna6s/Bnmvp94Jw8gh0nDunOEVHR1d5nzLnJCYmeo2oUe4bADXFynn/ZrOZpKQkn/NsoPc9QvMjNTWV9PR0VUD0Rnp6OsOHD8dkMomAIwhCk0AEHEHFW1lP5eYq0EgUs9lMeHg4ISEhAaWeKE/t3Pfh/DTPF3Wd4uTvaaJw8vDXB2siutR2PwpkvCgCS7ACJEBycnJAY0NJc4iMjMRkMnkVcARBEBQsFgthYWFev8eVuUv5GSqFHmcU8UX57szLyyMuLo68vDzsdru6jXyfCtUlNTVVRBlBEJodYmLczPBldupsjOrJPDhQ4+JgDI6V6ARPJsXl5eUBmxw6C091hZQ6rX/q8hrUdj8KpK3B9HPn/SpeE/4wGAyEhITQtm1bwsPDSUhI8Lqt2WwW82FBEID/zR2+xOfy8nJMJhNhYWFqKqevfSUmJqr/R0VFodPpAjYzFgRBEAShEonAaWb4igpwjwLw97pCXUXA5Ofn+1xwKgSaI1/TdkrJ5fqnLq+Br35Unb7j3lZP0TbeItB84S06zdv+FcHHH85ikoiUgtC8cZ5HvEUK5ufnVxF6zGazmtKSkJCgPhByn1MSExMlqlUQBEEQqoEIOM2M2jQEVBa1SsqUr4pQzgtgxcvE1xM7gNjY2CrH83QT6Wkhm5WVBeCSXy9mxIIvfHk9BZoO5UvkcRZIPAkviiGjL8xmMxkZGS4Gxp72r/zub4y5f/5gxSRBEJo2FouFjIwM7HY7Op1OfahisViIjY0lJKTyNjIjI0N9LSsrC6vVCuBz/hGDYkEQBEEIHkmhaqJ4S5UyGAx+0y88vdfT35RFLeCSKuIpdcR5AewpbcQ9fcNT+Hag6SZms5ni4mKKi4td0kEkBUoIBE+pVIH0HX8pWN76tNJXA+nXykJKMTD2tn+TyURWVlYVc0d/KZSe0hlriq9jCoLQsLFYLISHh1NYWEh4eDgmk4mioiJycnIoLS1V5xubzYbJZMJgMKDT6QDIyclRH/Ioc4DzfBDI/YggCIIgCK5IBE4TxVvEQCCpIJ7e6744Vf4PCQkhJibGZ0QMuD5pc47AcW6Xc/qGp/Y5V7RQbhSdt8nOzsZkMqHX64mMjFSP661dtZX6VdcmykLNCPb6GI1GsrKysNlsVcrbe6vE5qvymvKawWCokhJoMBjUvhqIIXF4eDg2m43U1NSAUxyd8RVJ5Jya5S6+BhvNE+gxBUGoH3zNi85zFoDNZiMiIoLjx48TFxeHzWYjNjZWnRMSEhIwmUxqylRKSgp79uwhLCxM/c4uLCwkOzsbg8HgErErCIIgCEJwiIDTRPEUmmyxWDh48KDH9At/73UupX3o0CHCw8OJiooKuKKN++LSU5lnZ1HH3djQeRFtMpk8pqIoTwEB2rVr5zESwvmmtbYWlrJAbdgEc32chRhPiwxv+3KuvAau5eaV93hLT3IeG4ow6Ukoca4+pQih3lDSsXwJqZ4+u2JK6h59pyzEqiPgSJqEIDQ8/Im5RUVFZGZmApXpzEePHqWsrAyr1Uq3bt2A/81JiYmJJCYmukTatGrVyiVS8NChQ1RUVABSGlwQBEEQaoIIOE0UT4s3ZZGpRBZ4wttTOWV/2dnZ6j5atmzptx3OC2L39rkLRMrvZrOZf/75h4qKCrRaLa1atXJZ/Hrz6nB+Cuhroa38PZCFZSDRG7JAbdgEY3J96NAhwsLC0Ol0HlOmvO3L+e/ufU/5mz9fHCWdKjIy0mUsOEe/ePoMJpNJ7fdKhI+z95RGo1HHjK++rGxTWlpKeXk5+fn5qg+Vr2o0/ggkMkgQhJOLp0hD59dMJpNa6ttmsxEXF8e///4LQGZmJvHx8WRmZqLX60lNTcVoNKrzGUBUVBRRUVHq/JWQkEBRUZGaNiUIgiAIQvUQAaeJ4mmx5uxRo/wtOzubjIwMAOLj4wHPkQfO+9RqtbRr185lH8oC0vnGLDs7mz179hATE4NOpyM2NlZdFPoyWrVYLFRUVJCbm4vRaKS0tJTo6GgXE+OEhAQsFgsmk0n9PMpTQOe2Ku1QtnFeaNc05UQhmAWqpFvVHf7ER3+YzWbCwsIoLS116d/OeNuXc+QYuHpCKe9RPGzANUJG6dPOY0JJNQikMlRmZiaFhYVYrVYSEhLIyMjgyJEjRERE0KpVK5/m4s7nTRlDzqKRUgnO+em6t3MHrqbhgiDUP4oHjbsArHwfeis4oMxROTk55OXlERERQevWrcnJycFkMpGXl0dZWRnZ2dn8+++/dOzYkYSEBEpLS9Vj/Pnnn+Tm5tK5c2dSUlKkwp0gCIIg1AIi4DRRPC3WPC0+TSYThYWFFBUVER4eTmRkZJXIAyVVwzlNRK/Xq383mUyUlpaqIo7zvnU6HYWFhXTp0gWoXLhWVFQQERFBcXExdrud4uJiIiIiVIFG2U6r1RITE0NERAQRERHs2bOHnJwc4uPjadu2LYcPHyYsLAy73U5oaKjL5yorK8Nut2O1WgkLCyM7OxuNRuMSpeAtBUWj0ag/e4v2cd8uUNwjgITA0Gg0fs93TVPZ3AVOT+W6nfsoVPaPsLAwoNLjwW63U1pail6vp6ysjIKCAqxWK3q9HpvNRlFREQB6vV7t1xEREQC0aNECvV6P1WqlqKhIHU9K9It7f1XSGUpKSrDb7YSHh1NaWsqRI0coKSmhpKSEVq1aqe917svO+3JO8XIu+Zudna1+NuWzO0fmOP+vpEaYzWb0ej0AWq145AvCycLb95n7vKhE1QBERERgtVqJiIigqKgIq9XK4cOH1Xmibdu2lJSUYDKZKCsrIy4uDqPRSHR0NFqtlvz8fBwOBwUFBWRlZamij5KKmZOToxoep6SkEBcXB1Tvu1MQBEEQhEpEwGmiBJo2okSyREdHExkZ6fMJuuI/U1pa6iJqOKcuKSiL3LCwMFJSUlxeq6iowGKxqGVGlcgfi8WilipNSUkhPj7exbQ4Ly9PFWVycnLUKhinn356lbZarVb1RlWn01FSUoJOp1Pb6a0kuafzWJtCi6Rb1R01PbfufcG97LdSTldJIVQiyRSRQxFfALWfKj/n5uai0WjQ6XTo9XpV5HBHGRdWq1VNX3KOzvEUFZeUlMTRo0cZNmwYDoeDV155hYiICFq2bEl8fDxlZWWqt467ibLz/j2ZIivjXVn8KeXOAZf/vbVPEIT6xde86BwFqDwQyc/PR6fTceLECSwWCwcOHFBFGaPRSGhoKC1atAAqRWfn9zgfLyEhgc6dO5Obm0uXLl3ku08QBEEQagkRcJoogaaNOKcdBbpPd0NW56gWBSUNqqSkxOO+lIWvIgYp+/e0kMzNzcVutxMREUFcXBwtWrRQF8fR0dHq/pRIB4PBoC6mlYVyXFwcJSUlajvdF+cnCzFvrDtq22vFvT86V4Fy95pRqKio4OOPPyYvL4+rrrqKtLQ0dQwogmJ8fLzLPpV+arVaKS4uBlAjdhQPCW991WAwUFhYyH333cfu3bsBGDp0KKtWraJt27bqMfyZKCvbgWskkvN7lRLjvsyTBUFoWAQyLyqRqgUFBURERFBSUkJMTAx5eXlotVrKy8tJSUnBbDYTGxurPiApLS2lU6dOLn5ZzsdzvrfQaDTy3ScIgiAItYAIOAIQuDeLr5Qi9+0KCgrQarVVol4iIiJcogqKi4vJzc1Vn+o5t8k5DapFixakpKSorykoi99jx47x448/smnTJqKjo3nuuefQarXqwlk5pnOVHUUAEgR33Bc+ys9RUVEuv+fk5KDX6zl27BgPPPAAGzduBGDatGl06NCBa665hgEDBhAfH6+Kj8p7rVYr5eXlqoij0+nUn90jcLyl8d19993s3r2bpKQkWrVqxZ9//sk111zDu+++y1VXXQXAsWPHVHHTn5myu0+Gp+pwYkwsCI0bi8VCTk4OUDnOS0tLyc/PJywsjKSkJDWiJjc3F71eT0lJiepFp/ys1+sJCQlxeYDj7DknCA2J9PR0v9skJCSQmpp6ElojCIJQfUTAEQDIysqiuLgYnU5HQkKCz0o1gdyYGQwGunTpopYhVcQbZZGo3PDl5uZy7NgxoqOjycvLIzk52eU4FouFNm3aqH9z3r9er2fXrl0sW7aMNWvWsH37dpc2/Prrr3z++eeUl5eTl5enGq0ajUZatWpVo8o6QvPB3TzbuYw9oPo43XTTTezatYvw8HD69u3L5s2bOXDgAHPnzmXu3Ll06dKF5cuXu6RPOaddKcJNeHg4+fn5GAwGoqOjvY653bt3M3bsWLZs2UJUVBSfffYZnTp14pZbbuGbb77h5ptv5uabb+a2226jTZs2auqit3HtTahxforuK5pHEUeh8iY4MjKyhmdeEIS6Qon4KykpQavVcuLECYqLi6moqCA+Ph69Xq9G5VRUVGCz2Th8+DChoaG0atWKpKQk9Hq9GiWYlZVFTk6Oi/AsCA0BxZtp+PDhfrc1GAykp6eLiCMIQoNGBBzBBWWBpogdiveFssBzN3D1dZOmiDTuPiKKaasSYRMeHk52djZRUVGcOHFCXfh52n95eTk//fQTn332GWvXrlXLmir06NGDtLQ0Pv/8c3bu3Mnw4cN55ZVXCAsLIy8vj5iYGAC1uo6nz+9eGctsNrssTCUMvPEQaGSZr+3cRQv3ylEFBQUcPHiQXbt2YTQa+frrr+nRowfFxcVs3LiRtWvX8sEHH7B371727NlDu3btgP/1b6XSi1J+V/HX8Ta+zGYzzz//PC+//DLl5eUYDAY+/PBDunfvDsCaNWsYM2YM7733HitXrmTlypV0796d2267jZEjR3r0f3Lu78pnVoyUlRLBynbeRCBlEaekjImAIwj1j/PcBqhpmhaLhdLSUrKzs6moqKCgoIC8vDxatWqFXq8nPj6evXv3EhoaSnFxMQkJCYSGhhIREaEarufk5Kimx0qka2lpqXxHCg2K1NRU0tPT1fs4b6SnpzN8+HD1e08QBKGhIgKOAFSW/3W+6VIMB93FF+cqNL5SqZxTldwjCZSKNQaDgcjISEpKSjAajRw+fJiQkBAOHjyoRs1kZWWRlZWF2WwmNzeXrVu3kpeXpx4nPDycCy64gGuuuYarrrqKVq1aAbB9+3YuueQSfvzxR5588klefPFFunXrBlQaItvtdhcxyrnd7qkkymJWabPcnDYeAq1M5Ws7d9HCWfiwWCzExMTw888/A9CnTx969OgBVAoY1113Hddddx25ubl88cUXbNu2jT59+qjV1ADV1NhqtRIVFYVWq/U6tj799FMeeughtRz51VdfzezZs2nfvr26TVhYGIsXL+a+++5jwYIFfPjhh/zxxx/88ccfzJw5k5EjRzJs2DCio6NVwcqbgXF4eLjLWPAmhCmiUFlZmSrQCoJQ/zjPbQBFRUWcOHGC5ORkNYImMzMTu91OZGQkhYWF5ObmqvOTzWYjNDSU0tJSDAYDcXFxxMfHqxE8SgqpTqcjPj7eZyEEQagvUlNTRZQRBKHJIAKOAHiPpnEvQ+6c/uQvokF50udt36GhoXz66afMnDmT48ePB9zWFi1acOWVVzJo0CAuueQSj/vu0aMHH374IYMGDWL9+vW0bt2aN998U63wY7fbVS8TZ7xFGCiloeXGtHERaOUT9+2Up9bOUTKeMBgqy/IqBsLnnXeex+369+/PF198wY4dOzhx4gTR0dHk5OQQExPjYrZttVrRaDRVjnnw4EEefPBB/vvf/wLQrl07XnrpJa6++mqvn6lXr14sXryYWbNm8eabb7Jw4UKOHz/Oiy++yMKFC5k5cyaDBg3y2N+NRiOpqakBm3wrpuRt2rQRfxxBaEAYjUaysrKw2WwAnDhxQi0gEB8fz+7du7FYLLRs2ZLjx4+j1WrJyMigpKSEiooKtFotiYmJaLVaWrZs6ZJ6HBkZqVbWE+FGEARBEE4OIuAIXnH2w1B+d4488FU6WImu8fS63W7nvffe4/nnn3dJgYqJiSEuLk6tNNWiRQtiY2Ndfj7llFPo06cPISH/67pKRI87F1xwAUuXLmXYsGG88847pKamct999xEbG+tSSci93UajkezsbDIyMtRtFM8cib5pXHjqw962c37NPfrM1/7Ly8vZunUrUBmB44kBAwYAsHXrVhISErDb7S4ROIqZ8fHjxwkLCyMqKorU1FRKS0uZPn06s2bNwmq1EhoayqOPPsqTTz6pli/3R8uWLXnmmWd44okn+Oijj5g9ezZ//PEH9957L3/++SfTpk2r8h5nDxz3Pu8tBctisaiRdoIgNAyUMXz8+HEOHjyoRqmuX7+eFStWsG3bNmJiYpg2bRrJycnk5OSoflkRERG0b99enasUnM2PRbgRBEEQhJNLsxVwfv31V7Zv387OnTu55JJL6NGjh1rhqKkRqA+IJzylUSn/wsLCfJqiKuGqJpOJjIwMWrRowcaNG5kyZQr79u0DKlO3JkyYwF133eVi7lpb3HDDDbz66qs88MADTJkyhbi4OIYOHUpycnIVMcp5QWoymSgtLcVkMmEwGNi3bx9xcXFVFrRms1k9tyLuNEwCSaNS/Fugsk+Cd58kdw4cOEBmZiZarZZzzjnH4zZnnnkm0dHRFBYWcujQIfr06VOlLUokjtlsprS0lG3btvHEE0+wf/9+AAYOHMj8+fNJS0sDoKysLLAT8P+EhYUxdOhQBg8ezMSJE5kzZw4LFy5kx44drFy50mX+M5lMFBUVERUV5VHAcRe3Aom6kbEiCHWPu+fNwYMHOXLkCMePH+fo0aMsXLiQ77//3iWFuKCggFmzZvH444+TkpJCXFwcJSUlHDlyRI0+VUScw4cPqxE8MTExLn55Un1KEARBEOqeZingLF++nGeffZb8/Hxyc3N54403GDx4MNOmTXPxkmgq+FvA+jLpNRgMmM1m9Ho9DoeD7OxszGYzWq1W9e5QntaHh4cD/1uIKoJMRkYGGzduZMmSJfzzzz8AxMXF8dBDD3HvvfeqxystLXVpl2KK6A+l3Kk37rzzTo4dO8b06dN5+OGHSU5O5oYbblBNY4uLiykvL6eiooKwsDAcDgexsbHk5eWp/4eEhGA2myksLCQ0NBSoTAFzPrfOApQnM+TaQqPR1Or+mjqBpFGZzWY15U/ZLjY2FofDgcPh8CjyKezYsQOA//znP0RGRuJwOKrsX6vVcv755/PFF1/w22+/ccEFF1TZzuFw0KJFC44fP86cOXPUdKnExEReeOEFbrnlFjQajbpg8nQcb5/Nnaeffpru3btz//3389NPP3HWWWcxffp0rrnmGuLj49V9OxwOdZwo6PV6LBaLOh8oKJXhFNz7qa95qCYiszsyPoSmRCDj3GKxqOW+lRRhJWVq9+7drFmzhm+//ZZjx46p7+ncuTO33norAwYMYPDgwRw8eJDVq1dz//33Ex8fz/79+7FarezcuZPc3Fzi4uJo3bq1WiVPr9dTUFCg3gOEh4f79RoTBEEQBKHmNDsBZ9WqVdx5550899xz9O/fH71ez5QpU3j//fe5+OKLGTVqFA6Ho0ktAvwtYH2Z9BqNRnVRptwkVlRUkJCQoEYnmEwmiouLVRHIYrGg1Wrp1KkTv/zyCxMmTOCPP/4AKnPmx40bx7hx49SKUCeDp556iuzsbN566y1uu+024uLiuOCCC7BareqTyJCQEHJzcwkPD1fLqObm5nL48GGXvzmjmL2Wlpa6RCR4MkMW6odAokMMBoPqieScduV8PZ2Nr53FnN9//x3wnj6loPjgfPPNN4wfP179u9Vq5fDhw+h0Ot5//33mzJlDQUEBGo2Gu+66i2eeeUYtzVubXH311XTt2pVRo0axY8cO7rnnHrZv387LL7/s0teVdAlwPZeZmZlqmeGwsDAiIyN9RjH6qmAVqNm0IAhVMZvN2O128vLyyM/Pp6CggEOHDrF8+XK+//57VQSKjIzk+uuvZ8SIEfTu3Vu9z1m4cCE333wz33zzDRdccAGtW7cmLCyM3NxcSkpK2Lt3L506dQIqhZ/4+HjCwsLIz88nPDwcm80mKcaCIAiCcJJoVgLOiRMnePnllxk7diwPPvigWi3llVde4ZdffuGjjz5i1KhR1RJvbDab+sQLoLCwsNbaXVP8LWA9LV4VlLQHZfHlyT/GYDBw+PBhKioqKCwsxGq1Ulpayvjx4/n222+Byqf29957L4888ghxcXF18Cl9o9FomDt3Ljk5OXzyySfcdNNNbNy4kYSEBEwmkxrFU1ZWxs6dO/nnn3/YvHkzv/32G1lZWcTFxbFkyRIiIiI4evQoERERJCcnA6jRR+4pJZ6EHcE3J3McOfu8wP/GibIIcRbr3EuH2+12Nb1u8+bNAJx77rk+j6f44Pzyyy/Y7Xa1z1ksFv7++28mTZrErl27gEoT7jlz5nDWWWfV7od2o0OHDqxbt44nn3ySpUuX8vrrr5Oens68efNUE2O73U5BQQExMTFYLBY0Go1atUZJr1Ci5RRB1NkDS8FX6lSgZtNCYDTk7yOhdlGi14qLizlx4gSHDh1iy5YtvP322+o2559/PiNHjuTaa6/1WCXusssu4/7772f+/Pm89NJL/Oc//6FTp04UFRVx7NgxzGYzVqtV9d1KSEhwKWgQExMj33GCIAiCcJJoVgJOUVERu3bt4v7773e5iWnbti0pKSnk5OS4LKyCYfr06UyZMqU2m3vS8LWwco48UG7QFI+QjIwMl3Sp8vJyIiIi2Lp1K7NnzyYnJ4fQ0FDuvPNOnnjiCdU8MdDUqNpGp9OxZMkScnNz+f777xk0aBCzZs1i586d7N69m127dnHo0CGPpsh5eXnceOONTJo0iQEDBhAREYHNZsNgMKhPIBVBB/4nBkhUQXCczHHkHCUFeCwf7xxp43wNTSYTubm55OTk8OeffwL+I3CcfXB27NhBjx49yMvL4+mnn2bx4sU4HA5iYmKYNGkSo0aNqtY8VB0iIiJ4+eWXGThwIGPHjuW7777jwgsvZPr06Vx11VXodDpatGihbq+INzqdTo24cRa3lPMYGRnp0wzZGalcVbs05u8jITiU9KXi4mIqKir46quv+OCDDwAYOXIkjz32GB07dlS39/b9O3nyZLZs2cK2bdt45plnWLZsGeHh4ZSXlxMfH0/btm3VecB5vDalaGVBEARBaAw0KwGnsLAQi8XiskCvqKhQFyi5ubnV3vfEiRN55JFHXI7VmEyRvS20FA8c90WsyWTCbDaTm5tLixYtMBqNRERE8M033zBx4kSgcsH67rvvcuqpp9bLZ/JEREQEq1ev5uKLL+bPP/9k5MiRVbZp06YNvXv35uyzz+bss88mLS2Nhx9+mA8//JBJkybx9NNPc+2116qeP1FRUURFRVWpyqVE4dhsNjF3DJCTOY7cU3qUiCnF18VsNlNRUUFOTg4pKSlVInUqKipYv3495eXltG7dmnbt2vk8XkhIiOqDc8kll9C2bVsyMzPV9MVhw4Yxc+bMk5pa6Mytt95K9+7dGTJkCP/88w/33HMPt9xyC5dddhm9evWic+fO5ObmqgamKSkpapSSu/+TMm9kZGSo40Sia04ejf37SPCPEnkDlRFXRUVFvPPOO6p4M3bsWGbMmBGwwBIWFsbixYvp378/f/31F++++y5DhgzBYrEQExND69atXdKmRXQVqkNGRoaabu+N9PT0k9QaQRCExkmzEnBSU1Pp0aMHRUVFlJWVERoailarBVBzuBXTUuWmJ1A/nPDwcHWh0hhxj0ZwrlDhvMB1FnKMRqNqZpyQkEBubi5Tp04FYPTo0cyePbtBnpPo6Gg+++wzLr/8cjIzM+nZsydnn322KtookULOLF26lHbt2jF79mxmzpzJeeedp1bZAjxW5ZIonOA5mePIPfJMGQOKt4sSAeOeHgf/E38KCgoAOP300wOaJ4YPH85XX31FYWEhu3fvBuC0005j7ty5DBw4EICSkpLa+ohB07VrV7Zs2cJ9993H+++/z3vvvcd7770HVJo6n3nmmZx11ln06NEDu92uRuM5ewUpP2dkZKhmqs7RaULd09i/jwT/KL5RJSUlfPjhh8yePVtdGI8bN45p06YFHR3Tvn17evfuzYYNGygtLSUxMRGtVktJSYmLX5yvCpSC4I2MjAzS0tJc7i+9YTAYAqoCKQiC0BxpVgJOQkICX331FRqNRq0k5HA4qKiowGQycfrppxMS8r9TYrVaeeGFF7j66qv9pkc0dtw9PsrLy8nPzyc2Nlb9snX2/XAuE67wxBNPkJuby2mnncacOXNczmVDo2XLlmzfvh2oGgLurYrQ1KlT2bt3L59++iljxoxh8+bNFBYWEh4ejk6nIyQkpMoNrcFgIDs7W6JwTgI1rWSk9H3F00URJk0mk0s6lbKtwWBQK6c5pxj5YvDgwVx++eVkZGSQmZlJXFwcvXr1UoXkhkBkZCTvvvsuw4cP58svv2Tr1q388ccf5Ofn8/333/P999+r2yYnJ/Of//yHiy++mOHDhwP/E3+VajVK+WF3lKg/GReCUD22bt3K888/z2+//QZAly5deOmll7jwwgurtb/s7GzVt+66664jNTUVg8FAVlaWavAfGRnp8btOEPyhfJcuX76ctLQ0n9smJCRUuccUBEEQKmm4K+w6wn0xodFosFqt5ObmkpiYqP7darXy2GOPsWjRIoYMGXKym1ltFNPhQBdFzqlTzp/f2aBQSY9QfD+cU9CU9x4/flw1TZw5c2aDFm8Ugn06qdFoeOONN/jjjz84dOgQY8aM4ZVXXsFms6k3uu4okUoShVP31LSSkRKR4yzkKEKNuw+UglKWN1ABByoFktNPP53TTz896DaeTC699FIuvfRSAEpLS9m1axdbt25l69at/Pbbb+zevZsTJ05w4sQJNm7cyLvvvsv48eO54oorMBgMaDQadDqd+rTePYVKEYprWla8NkuQC0JjoKioiGeffZY333yT8vJy9Ho9jz/+OA888ECNIq9Wr15NeXk5nTp1IjY2Vo3o0Wq16HQ6tFqtjDGhxqSlpdW5Qb8gCEJTpuE89q1H7HY7DoeD6OhooPLm6NFHH+Wdd97h119/5YwzzqjnFgaO8yI2kG0zMjIoKipyCWk1Go0kJiaq/5zTppQqVM7VeCwWC08++SSlpaVcfPHF6qKvKRIbG8uKFSsIDQ3l888/Z/ny5X5vaI1GY7VKrFosFrKzswMKNxaqnufqnj+l/ztH2+h0OpfrbLFYyMnJIT8/H6BeKqudTMLCwujRowd33303b731Fn/88Qc5OTl8/fXXPPvss7Ro0YLdu3dzxx13MHr0aLKyskhMTCQhIcHr03qDwaBeL/drFew8Fui2gtBYMJvNZGVlVZm/PvnkE04//XRef/11ysvLue6669i1axfjx4+vcdqcki552WWXAZXG7lA5Vp0rTTmnWwuCIAiCcHIRAef/0Wg0akTGY489xpIlS9i8eTM9evSo55YFRzBigVL+WhFk/GEwGFTPG+V3nU7Hjh07WL16NVqtNijTxMZKr169mDFjBgDTpk0jPT1dTbFRQoSdUaKbPJ1jXyKDLEyDw/08u58/5VwHez4V8dJkMqkGjJmZmWrqJVSN7DvZ5Ofns3PnTjUi6GQQFRVF//79eeqpp9i9ezdjxoxBq9Wydu1azjjjDKZMmYJGoyExMVEtE+58/p2FMvdrFcw8Vl2BVBAaMs5jQpm7Zs2axY033siRI0fo2LEja9eu5eOPP6Z9+/Y1Pt6uXbvYsWMHoaGhXH755ej1ekpLSz2mBUsKlSAIgiDUHw0/z+UkUVFRwZEjR3jsscdYtmxZoxRvwHdJcHeUG7Dk5OQq73FOrVJKrjscDpcUqvj4eOx2O0888QQAI0aMoFOnTlitVp/HPXLkSEDt8+RF44nS0lLKyspUo0Wr1UpERIRqwKgQ6NPJQPKu77rrLn744QfVD+eHH36guLgYk8mETqejc+fOqtCl+C15wlfaj9FoJCsrq4p/TqDnpSkJaYq5eDAoooHSt7OysiguLiYyMjKgMeJ8PJPJxOHDh4mIiMBoNGK32yksLHTxwPF3vv/555+A2m2z2aq0o6CggGPHjnH06FGOHTvGsWPHOHz4MMePH+fEiRMUFxcDlakO/fv3Z8iQIarHQOvWrQM6bqDClqdoI6PRyKxZs7jtttsYP348mzZtYsqUKbz99tu8+OKL3HDDDRQVFVFcXEx2djZt2rRR+3NoaKh6raDSh0MRdwJBquEIjRFv85lzdamQkBB1zMyfP5+FCxcCcMcdd/Dkk0+i1+s5evQoAPv371f3UVpayhdffEFERASXX365y/579+7t8bhK9aq0tDQ19dFsNrtE4irfQ87zZ1P6nhEEQRCExoAIOEBMTAx9+vRh6dKlxMTE8OOPPzZK8SZYfIk9zlWpFAFHKcGuVMmxWCy8//77bN++ncjISJ588slqtaOoqIgDBw5QVFSE2WymuLgYs9lc5ffi4mIsFosq0jj/rIR6OxMeHk7btm1JSUkhJSWFDh06kJqaSmpqKsnJyWqVoeqg0WhYtGiR6ofz0EMPMXv2bGw2G+Hh4eTk5GAwGNDr9YSGhrr4dADqz+4igzPKjXJhYSEHDx6kffv2zXaharFYgjaCdl/YW61WcnJy1P1UxzMlOztbFQWTk5PVKlS1lUJlsVjYvXs3e/fuZe/evezfv5+9e/eqpcZ9ER0dTWFhId999x3fffcd3bp1Y8iQIdx4440nzST5jDPO4IsvvmDNmjU8/fTTZGRkMGzYMAYMGMDzzz9PXFwcYWFhWK1Wj+febDYTHh4uflFCs0X57rPZbLRr146ioiJmzZrF0qVLAXj00Ud56KGHvAonP//8M/PmzePw4cNAZXSePx+/8vJy3n//fQDOO+88APW7TBFxZDwKgiAIQsNABJz/55FHHmHNmjVs3ry5wZuL1jbO0TaKkKB43IBr+XDF2Dg+Ph6r1cqsWbMAmDBhglpSOBi+++47Jk6cGNACNRB0Oh16vR6r1YrNZmP//v0uTyYVQkNDadu2LX369OGBBx4gKioq6GPFxsby3nvvMXDgQNasWcO5557L4MGD1dfLy8uxWq1ER0dXSRFRfvYXCWI0GsnOzm72i1rFVLgm50Cv1xMfH4/NZqO8vJysrKyAhRylv0dERBAWFkZkZCQGg0EVcIIxMVbIyclh27Zt7Nmzh71797Jnzx510eWJhIQEWrVqpf6Lj48nOTmZli1bkpycjF6vZ//+/XzwwQds3LiRHTt2sGPHDt58803uuOMOrr/+elWMrUs0Gg3XX38911xzDS+99BKzZ8/m+++/Z8CAAYwePZqxY8cSGRnp8h5lfAA+06HEsFho6hiNRkwmE+Hh4Rw/fpzHH3+cjz/+GIDJkyczevRoj+87evQo8+fPZ/Pmzep+zGYzr7/+OrGxsVUicZz55ptvOH78OFFRUZxzzjmEh4er9wOSmigIgiAIDQsRcP6f888/n6KiomZ5s+IcbaN8fuXGLTs7m+LiYnJzc9VoFoW5c+dy/PhxUlNTeeCBB7Db7QEf0263s2DBAt544w2gcoEcHx+vprc4/6/8UxZter1e/afk4yu/K+lKZWVlHD9+nMzMTA4fPkxmZiZHjhwhIyODw4cPU1ZWxoEDBzhw4AA//PADM2bMqFbUleKH8+ijj/L000/TrVs3zj33XDXaQ/FGcY+0UX72VznJYDDQvn17n2JPc1jUKn5LnioZBfrZk5KSXN6vCDnu517ZZ0REhCpkWq1W4uPj1bQ45brm5eUBwQs4v/76Kw8++KCa+uRMQkICXbp0oXPnzur/7dq1q5IC6CnlqVOnTkycOJG77rqLTz75hE8//ZQDBw4wadIk5syZw4gRIxg2bNhJ8ewxGAw888wzjBw5kgkTJvDxxx/zxhtvYLPZeOGFF1y2VcaCs1GqJ2paaUwQGhKe5i+DwUC7du0oKCjg/vvv55NPPkGj0TBjxgxuvfXWKvuwWq3Mnz+f119/ndLSUnQ6HTfeeCO33347S5cuZdWqVbz44otER0er0TXuLF++HKgsHX7GGWeg1WqxWCy14q0jCIIgCELtIgKOE81RvIH/Rdt4WxCdOHGC6Ohol21ycnKYOXMmAC+88AJ6vd7jYtQbc+bMYcmSJQAMGzaM8ePHV/GKCcYDx53Q0FA1dUpBWQDb7XaOHz/O33//zYsvvsiRI0e4/fbbmTx5MjfccEPAn0Fh7Nixqh/O6NGjWblyJXFxcS4Lbvd0Huef/UXiKO9VjCzdxYrmsKg1GAxqlThngvnszubGvtLXlH0qaT5Kil5ISIhLf/r3338pLCwEghNw/v33X8aMGUNZWRnt27enR48enHLKKZxyyil06dKlVq5hYmIid999N8OHD2fz5s0sWbKEw4cPM3fuXBYuXEj//v3p06cP55xzDqecckqdpli1a9eOlStXsmLFCkaNGsWSJUs45ZRTePTRR4HgRDhfKYeC0NhQ0qVMJhPt2rVT+39ZWRl33nknX375JTqdjldffZXrrrvO5b1Hjx5lxYoVrFy5kqysLAB69uzJAw88oAovY8aMIT8/n/Xr1zN58mRWrFhRpQ179uxh7dq1AFx11VXExsZSUlISsAeVIAiCIAgnFxFwBI9h0kpalcViITk5Wa1Gofzt3Xffpbi4mG7dunHLLbcEfcyNGzcClalXw4cPr5XPESg6nY42bdrQpk0bevfuzdSpU/niiy+YPHkyAA899FBQ+1P8cHbu3Mn+/fsZOnQoCxYsoHXr1lVugt0Xq8EYsHoTK5rzojbYz+58Dp19HZyvi7JPJd1ISclTom+gUlx87LHHAOjSpUtQAs6xY8coKysjMTGR1atXV4mscTcxrgkGg4HbbruNW2+9lQ0bNvDWW2+xY8cONm7cqI7B2NhYzj77bPr27ct5551XZ4LOrbfeislk4vHHH+e5557j2muvpXPnzkGLcE1VpBSaH87pUkr///vvv7n++uv5559/iIiIYMGCBVx66aXqe37++WcWLVrExo0b1YICbdq04Z577qF///4u3jharZarrrqK9evXU15erm6vYDabufrqqykpKaF79+6cdtpplJSU0KZNG2JjY0/KORAEQRAEIThEwBFccBZuwsLCAFS/D4PBQGZmJsXFxbz77rsAjBo1KugqFDabTa1E5Ssv/2QQFRXFzJkzVT+byZMnEx8fz4gRI4LaT2xsLF9++SWXXnopBw4cYMyYMSxduhS9Xu8iDtQkWsabWNGcF7XBfnZ/UTfOwo6nlEAlnerdd99l7dq1hIaGsnTp0qAED6UqVHFxsTrG6pqQkBCuuOIKLr/8cnbv3s2mTZv45Zdf2LZtG/n5+WzYsIENGzYAlYbMffr0oU+fPgwYMICOHTvWWjseeOAB1q1bx7fffss999zDxo0bm7UAKTRvlHQppf+vXbuW4cOHU1RUREpKCh9//DGtWrUCKkXjBQsWMGPGDDU69bzzzmPkyJFcdtllZGRkVNm/w+HgrbfeAuCKK66gZcuWLq+/9tprZGZm0qpVK5YuXUphYaEabSsCjiAIgiA0TETAEVxQ/HCgctEXHR1dxfh0z5497Nq1i9DQUL/VLTxx6NAhHA4H0dHRJ8WLwx8ajYaJEycC8N5773H//fcDBC3ipKam8tVXX6kizh133MF3331HVFSUi2lxdRerzVmoqS28nUNf10VJocrJycFqtbJ161aeeuopAF588UV69uwZVBsUAcdqtZKXl1ctA+TqotFo6Nq1K127duWee+6hrKyMnTt38ssvv7B161a2bt1KXl4e69atY926dQB07dqVQYMGMWjQINq0aVPj4y9YsICzzjqLTZs2sXjxYsaMGSP9Wmi2KL5u06dP55lnnsHhcNCvXz8+/PBDkpKSOHr0KDabjSeeeILVq1cDcNNNNzF27Fg6d+7sc99btmxhx44dhIWFcfvtt7u8lpuby8svvwzAY489Rnx8PBEREWq0rSAIgiAIDZOTU1tWaDQopsAJCQlq+k9mZiaZmZlYLBbi4+PVJ/XXXHNNtQSYAwcOANC+ffugo3fqCkXEGTZsGA6Hg/vvv59ly5YFvR9FxOnQoQOHDx/m4osvJi8vT62sYzAYpCRrA8TXddHr9YSEVGrdJSUlPPHEE5SVlXH99dczduzYoI8VHh6uVmxTItHqi9DQUHr06MGYMWNYvnw5O3fu5JNPPuHxxx/n/PPPJyQkhF27djF9+nTOPfdcbrjhBhYtWkR2dna1j9mxY0eeffZZoDKFct++fepris+TUgFPEJo6DoeDiRMn8vTTT+NwOLjvvvvYsGGDOkeYTCaGDBnC6tWr0el0vPDCC8yZM8eveGO321m0aBEAgwcPrlIl8qWXXqKgoIDTTjuNm266CavVilarpU2bNi7pooIgCIIgNCxEwBF8YrFYKC4upri4WE2r+uSTTwAYOXJktfZ58OBBADp06FBbzawVFBHn7rvvrjUR5+DBg1x55ZWUlJTUqmgjC92aEcz5MxgMxMfH06JFCyZNmsSJEyfo0KEDixYtqrYAqUSy1LeA405oaCg9e/bk/vvv57333uO3335j2rRp9OnTB41Gw2+//cajjz5Kly5duO6661i+fLlaSj0Yxo0bx9lnn01hYSEPPPAADocDi8XCoUOHKCoq8lhhSxCaAmazmaysLCwWCw6HgyeeeIIXX3wRqDT3nz9/vppa+ddff3H11VezdetWYmJiWL58ObfddltAx1m/fj0HDhwgKiqKYcOGubx25MgRFixYAMAjjzxCQUEBFRUVajVHQRAEQRAaLpJC1QQJtHqTJ9xLijtXhqmoqGDNmjVkZWWRkJDARRdd5OITEmgZ8f379wOVQkdZWZnX7Xbs2BHQ/o4dOxbQdoHm9I8bN47i4mI1nSonJ8djdSrnikTuJCUlsXbtWq6++mr+/fdfBg4cyIYNG0hISCAnJwf4X1Uk9xLonlC8iQwGA5GRkS6eLc3BO0Sj0fgVS4Lp9+5eRM7nVzmfzoafSqnezz//nNDQUFasWEF0dDQVFRVVjEG94WxWnJKSwvbt2zl+/HgVE+PMzMyA9vf7778HtJ1OpwtoO28lhvv27Uvfvn3Jzs7mm2++4dtvvyU9PZ2vv/6ar7/+mgceeIALL7yQ++67zyUdzF+EwMyZM7n00kv58ssv+fDDDxk4cCDh4eHYbDaSkpKqnNdAfYZqMv95oqFECQqNA3/9Lysri+LiYgoKCnj77bfVaozPPPMMV1xxBXv27AHg22+/5dFHH8VisRAXF8f111/Ptm3b2LZtm8f9Opvvl5aWqj51Dz30EN27d1dfCw8PZ+bMmZSUlHDOOedw0UUXUVFRgc1mIzY2Vp2PpN8LgiAIQsNEInAEF4xGo5ruA5UiQ9u2bWnbti2AGn1z7bXX+hQcfKGkUDW0CBwF93SqyZMn89FHHwW9n5SUFP773//SoUMHDhw4wEUXXcRff/2F2WzGbDaTk5Ojlqt2x2w2k52drUYiOAtrUPU6Cf5Rom4U0SYkJMSlCpXz+XXGarXy999/8/zzzwOVwkOwvjfuKOLf4cOHa7Sfk0liYiK33HILixYtYuXKldx11120b9+esrIy1q9fz4gRI/jqq68CFlDS0tJ44IEHgErR9OjRo2i1WlJSUiTFUGjSOBwO5s2bp4o3kydP5tZbb1Vfe/vtt7nvvvuwWCykpKQwbNiwoLyy1q9fz7Fjx0hKSqoSsbN3714WL14MwKxZs0hOTiY6Opr27dvLuBMEQRCERoBE4DRx3MtWe/ubgvK7Ihw4v6eoqIj169cDcOONN1arPQ6HQ02hat++fbX24W2/R48eZffu3aSnp1NWVkarVq1o3bq1+n8wVTXcjY0nT55MWVlZ0KbNKSkpLsbGt9xyC0uXLqVjx44uETjumEwmioqKiIqKUq+TEiECnku/C75Rom4sFguJiYmqcbHi5+Is6ChYrVYOHz7ML7/8QklJCZ06deK+++6rcVtqW8ApLy/n+++/JysrS+0bkZGRGI1GoqOj1d8jIiJqpUR427Ztue222xg5ciS7d+/mpZdeYu/evUydOpWvv/6axx57zG8EDvyvKlV6ejrTp09n3rx5LnOO0ucDWVgqUVSe5jVfc54gnEwSExN57rnn+OCDDwCYMmUKt9xyC1AZOfPss8/y8ccfA3DzzTfTpk2bgKPoFJTom6FDh1YpQjBp0iTsdjsXX3wxZ511FllZWQDyfSIIgiAIjQQRcJo4nspW+ytl7f66xWLh6NGjbN26lYKCAhISEujfv3+12nPs2DGsVishISFqVE91sdvt7Nmzhx9++IHdu3eTn5/v8np2drZLGlZ0dDRt27YlJSVF/T8pKcnrglYRcbRaLcuXL+f555/HZrMF7EGg4F6d6q677uLrr78O6omqCDY1RxFsnPu8EnkTEhKimnY7Y7VaCQ8PZ8uWLQBccskltZJaoPT92hBwCgoKWLlyZUD70mq1GI1GUlJSuOKKK0hISKjRsZWqVosWLeK9995jyZIl/PTTT4wYMYLnnnuOoUOH+jxf4eHhLFq0iP79+/Phhx8ybNgwrrnmGqDy2tjtdkwmk5ra5msMKNfS07zmb84ThJOBw+FgwoQJauTN1KlTuemmmwDIy8tj3Lhx/Pbbb2i1WiZMmMCIESN4++23gzrG3r172bJlC1qtVo3qUfjrr79YtWoVGo2GJ598ErPZTFFREYCIm4IgCILQSBABp4njqTyyv1LW7q9brVbCwsL48ssvgcr0KaUqT7Ds3bsXqFzAVjcFCyoXvnPnzuXEiRPq30JDQ+nSpQtdu3YlMjKSY8eOcezYMY4ePYrJZKKwsJDdu3eze/du9T0JCQkMHz6c0047zeNxNBoNTzzxBOHh4bz99tvMmjWL4uLioKMw3EWcK664gm+++YaoqCg1AsfZhyUhIUHKhtcyns6nwWDAZDJRWlrqkq5mMBgICwtTr81vv/0GwPnnn18rbVEEnKNHj2K324N+wq6Qm5vLokWLKC4uRq/Xc/7556tCRXFxsZquV1xcTElJCRUVFRQVFbF792727NnDgAEDGDBgQI3GIlRGL40cOZJ+/foxffp00tPTefTRR/nhhx+YP3++z/ni3HPP5f7772fevHk8/PDDXHTRReq1slgsWK1WzGYzVqvVp4CjbO9pG39zniDUNXa7nbFjx6rm588//7wayZqZmcmoUaPIzMwkMjKSOXPm0K9fv2odR6k8dckll9C6dWv172VlZWr1t2uuuYbevXsDEBUVBUgEjiAIgiA0FkTAaeJ4W7T6EgbcX1cWsYqpaGpqarXbYzKZADxGOwTKH3/8weuvv05JSQlGo5HTTjuN008/nS5duqjVOwBOPfVU9WdlgZ6Zmcnhw4fJzMzkyJEjmEwmXnnlFfr3788NN9xQJdwcKkWchx56CIPBwLx583j99dcpKCjgtddeCyodJTU1lQ0bNtC7d2/27t3Lpk2bGDhwIFApkpWUlBAWFuaS4qPgbmIs1A5Go9HF/0ZJFYyKiqJ169aqwXRiYiL79u1j5syZ9O/fn+Tk5BodN1DDb1+UlJSwbNkyiouLSU5O5tZbb/UY1aWIQ4qwk5+fz8aNG9m3bx9ff/0127dvZ9CgQV5NjIOhQ4cOvP7663z44YcsWrSITz/9lPDwcObMmeNzrEydOpVPP/2UgwcPMmPGDJ577jkXEcdTVSp342lfEToihgr1hcViIT8/n4ceeojVq1ej0Wh4++231fG2Z88e7rzzTrKzs2nbti0LFy4MKP3QE9999x0rV64E4K677lL/rni5/fLLLxgMBl5++WV1PNRmKrMgCIIgCHWPmBgLXrFYLOzevVutGnXGGWcA8Pfff1d7nyUlJQBVKu8EgsPh4Msvv+SVV16hpKSE0047jZkzZ3LTTTfRtWtXF/HGnbCwMDp06ED//v0ZNmyYWrpVSQX74YcfmDp1qtfPptFouOeee3jyySeBSl+cu+++22cVLU+kpKRw3XXXAfD5558DldFExcXFQKXQ5GnB6stkV6gZ7obGClarldzcXKxWK3PnziU5OZm//vqLAQMGqJFk1eXQoUMAtGvXrlrRN3a7nffff5/s7Gyio6O57bbb/KbkhYSEEBMTQ7t27Rg1ahRDhw4lOjqa3NxclixZwtNPP+0S0VZddDodQ4YMYeHCheh0Oj744AOefvppn+bGkZGRvPzyywDMnj2bvXv3YrFYVMFXEX8OHTrEoUOHVPFGxoTQ0MnOzmb48OGsXr2a0NBQ3n//fW6//XYA/vzzT0aMGEF2djZdunThvffeq7Z4k5ubyyOPPALAbbfdxrnnnqu+9s477/Duu++i0WhYvHgxHTt2rPHnEgRBEAShfhABR/CKYvBaXFzM0aNHVePV9PT0au/TZrMB1RNwli1bxsqVK3E4HAwYMIDx48er4d/VISIigmHDhvHQQw/RokULcnJyeOWVV5g6darXReGwYcOYOXMmISEhfPjhhwwdOjToBaQSNv/FF19QWFhIeHg4BQUF6utKFI4z3kQGoea4m0QnJyeTkJCA1WpVq4R16dKFxYsX06ZNGw4cOMDAgQP59ddfq31MpRJbdZ9+L1q0iH379hEaGsrw4cOJjo4O6v0ajYZu3brxyCOP0K9fP7RaLT/++CMjR45kxYoVQQuTnrjyyit59dVX0Wg0vPPOO7zwwgs+RZxrr72WSy+9lNLSUkaPHs3hw4ex2+1YrVZiY2PV6KiioiL1WsmYEBoyFouF4cOH891336HX6/n0009Vz5stW7Zwxx13UFBQwJlnnsmyZctISkqq1nEcDgfjx48nKyuLLl268PTTT6uvffvtt2rq1MSJE7n55ptr/LkEQRAEQag/RMARvGI0GklMTCQyMhK9Xk+nTp2Aygic6qaAVDcCZ8+ePXz99ddoNBqGDRvGHXfcUW0fHndOO+00Jk2apEbjrFq1iuuvv55ffvnF4/ZXXXUVc+fORa/Xs2HDBq6//voqBsq+GDhwIPHx8eTm5vLLL78QGRlJXFwcdrudnJwcSktLqyxKlWshPgV1gxLNAbic5xMnTpCTkwPAWWedxdq1a+nWrRsmk4lLL71UjaIKlppUYlu7di1r164F4KabbnLxuQiW8PBwrrzySsaNG0e3bt0oKSlh0aJFjBo1it9//73a+1W48cYbefHFFwF47bXXeOWVV7xuq9FoeOWVVwgLC2PTpk1cd9117N27l/j4eHQ6HQkJCeh0OgoKClxSMd3HhFIuXiJzhPqktLSUG2+8kc2bNxMdHc369eu5/PLLAVizZg133303FouF8847j8WLFwdVJdGdnTt3sn79ekJDQ5k3b56a9rxnzx7uu+8+KioquOqqq7j33ntr46MJQpMmPT2d33//3ee/jIyM+m6mIAjNGBFwmhHVWdgkJibSqVMnWrduTYcOHQgPD6ekpERdgAZLdQWcdevWAdCvXz8uu+yyWqkE5IxzNE7r1q05cuQId955p9donP79+7NmzRpiYmL4+eefueqqqzh+/HhAxwoJCeHaa68F4JtvvqFFixbEx8djs9mIjY1VPT2Ek4e3aI6wsDAqKiqwWq3o9XpatWrFF198wWWXXYbVamXw4MFBV4mB6gs427Zt44033gDg0ksv5fTTTw/62J5o2bIlc+fO5cknnyQuLo6MjAwefvhhJk2axL59+2q07+HDh6sRAC+++CKbNm3yuu0pp5zC2rVrSU5OZs+ePVxxxRV8+umnxMfHq9fGbreTnZ2tijjuOFec8oUIPUJdUV5ezvDhw1m/fj0Gg4F169apBuhLly5l8ODBlJWVcckll7Bw4UKMRiN///03//zzT9DHysvL45tvvgFg/PjxaqpzTk4Ot99+O0VFRfTo0YPnn3+e0tJS6fOC4AWleMTw4cPp2bOnz39paWki4giCUG+IiXEDwFdagTM1FS2CLaWblZVFcXExRqORtm3bYjQa6dKlCzt37iQ9Pb1Krr4nA2B3lCgHwG/UivLlmJ2dze+//45Go6F79+5VvjRXrVrl97gA3bp1C2i76667jk2bNrFjxw5WrVrFunXruOSSS9QUMoU77riDt956i3vvvZedO3dy0UUX8cYbb1Qpj+7J0+C6665j8eLF/Pe//6WkpITQ0FDatWsXUKWck9VfmhOeDHAjIyNVwTEyMhKDwaCm7H366aeMGDGCDz/8kPvvv5+jR48yefJkn+fcarWqPyspVK1bt3b5O+BSJc2Z48ePM3/+fCoqKujVqxcpKSkBCamBelYpETf9+/dn165d7Nu3j++//57vv/+eli1bkpaWRkJCQsBmx86mxZdccgl//PEHa9asYdy4cbz77rvq+XY/7+eeey6bN2/mnnvu4euvv+aee+5h/fr1TJ8+HbvdTm5uLgkJCTgcDpf5xGq1YrFY0Gq1hISE+B1Hgc6HgY63QJFx2TgJtB/89ddfTJ48mTVr1hAaGsqcOXOIjo5m165drFixghkzZqjbbtiwwe/30rZt27y+VlZWxp133klZWRkDBgxgypQp6HQ6ysvLGTZsGBkZGXTo0IEVK1aQkpKiRhpKRTahtsnIyPAqqivUJP3+ZJCamkp6enpAn2P48OGYTKYaFfUQBEGoLiLgNCNqo5TuGWecoQo411xzTdDvVzxwfBkOu7N582agMtWpJtWrAiUsLIwLL7yQLl268NVXX1FYWMjHH3/MZZddVqXc+CmnnMKSJUsYM2YMhw8f5vbbb2fZsmW0atXK5zEGDBhAfHw8JpOJH3/8kQsuuEAq5TQwDAaD15uz0NBQ3n77bVq2bMm8efOYNm0aR44cYcGCBX5LcpeVlXH06FGg0sQ4EIqLi1m8eDElJSV06NCBwYMH1zgyxhthYWH06NGDjh07kp6eTmZmJsePH+f48eMkJCQQFxfHaaedFrQQcd999/Hzzz9z/PhxXn/9dR577DGv2yYlJfHRRx8xb948pkyZwscff8y2bduYMWMGXbt2RafTER8fr4o2ioeR3W5Hq9UGNE9IaXGhtnE4HMyaNYs1a9ag1WqZNWsW5513Hg6Hg4ULF7JgwQIARowYwbJly2p8vMWLF7Nr1y4iIyNZunSpaog+c+ZMfvjhB6Kjo1m7dq3L95bFYpE+L9QqGRkZpKWlBRTZZTAYSEhIOAmtqh6pqakiygiC0OCRFKpmhMFgIDExUV3s+AulTkpKIjk5mfj4ePVvSsqGtygBfyjRBoEKOIWFhfzxxx8Aagj6ySIlJYURI0Zw6qmnqhWwdu7c6XG7JUuW0LFjR7Kzs7n//vspKiryue+QkBAGDRoEwMcff1wn7RfqDovFgtVq5ZFHHmHq1KlotVqWLl3KjTfeqFYU88bhw4epqKjAYDC4jC1vlJeXs3TpUnJzc4mPj+f222+vNf8nX8TExNCnTx+uuOIKOnbsiFarxWQysWjRIl566SW2b99ORUVFwPszGo1qFbdPPvnEZ2QBVEbwPPjgg6xfv5527dpx6NAhRowYwQcffKCWeFdEG0XE0el0AS9OlVRFpaKVINSUqVOnsnz5cgCee+45LrroIioqKnjxxRdV8Wbs2LGMHz++xsfasWMHb731FlBpTqwsOn///XemTJkCwKOPPkpiYqKaTmg0GklKShIBR6hVTCYTFouF5cuXs23bNp//0tPTRSARBEGoISLgNBBOth9DID4RiuCjGCICpKWlAdUPhQ22CtWWLVuw2+20a9cu4C995al8baQ+hIWFcfnll6th7hs3bmT79u1VtktMTGTBggUkJCSwb98+HnvsMb+VfK6//noAPvvsM5dUEHfEq+Pk4e9cK6WtTSaTes3uuusuVqxYgV6v58svv+SSSy4hKyvL6zGcS4gHEsWyevVqDhw4QEREBKNGjTrpi6/IyEh69uzJlVdeySmnnEJYWBhHjhzh3XffZcaMGfz8888++68zPXv2VPv9tGnT/PrUAJx99tls2rSJwYMHU15ezvPPP8/NN9/MoUOHsFqtqum3Xq938coJhED9cgJBxmnz5tVXX1W9niZMmMC1115LRUUFkydPVkWdCRMmMGbMmKCi1zyNLbPZzNNPP01FRQWXX365ao5cUlLCyJEjKS8v5+qrr2bEiBGUl5f77JNms5msrKxaGQNC8yYtLY2zzjrL5z8RbwRBEGqOCDgNhNpcSASC0Wj06RPhbTHSsWNHoNJXozoLFcVTJJAInPLycrZu3QoEHn1jsVjYv38///77L9nZ2UG3zxMajYYLLriAnj17AvD99997TF9p1aoV8+fPR6/X8/PPP/PUU0/5FHGc06hWrFjh8hmcz31WVhYnTpzg0KFDskCsBsEsrL2NQ0/CTUhICAkJCcTHx3PjjTeydu1aEhIS2LZtG5dddplXAVERcNw9lbxt+9tvv6HRaBgxYgTJycl+3+MLh8PBjh072Lp1K5mZmUGVC9fr9Zx55plMmjSJyy67DIPBQHZ2NqtWreLFF18kNzc3oP3ce++9tGzZkuPHjzNv3ryA3hMTE8OKFStYuHChWv1twIAB2Gw2VWDOycmp4ifkD3/zYDCc7DlcaDjMnz+fhx9+GKiMsLn11lupqKjgueeeY82aNeh0OqZNm8att94KwOuvvx7wvt3HSEVFBVOnTuXIkSO0bNmSCRMmAJVj+8EHH2T37t0kJSXx9ttvk5iY6NGc3Rnpt4IgCILQuBABp4FQmwuJQHBOp/KE2WymqKhIfcqtkJycTNu2bSkpKWHmzJlBH1d58hhI6kVpaakasaOUMPeHc3nz6pY694RGo+H8889XI5AyMzM9bpeWlsbMmTMJCQlh/fr1jBs3zmtKTUhICLfffjsADz30EJ999hngW0SQG+3gCWaB4m0cOpcZV4QbpWKF8nqrVq0YOXIkAAUFBV6fsitpU9u3b6e0tNRnewoKCoDKKlGnnnqq3/b7o6ioiMLCQmw2G4cOHWLr1q3s3bs3qD5lNBq5/PLLmTRpEtdeey1RUVFkZ2czb948n5FHzu9/8skn0Wg0rF27lpUrVwZ0XI1Gw6hRo9iyZQtt27bl6NGjrFu3zsX/Jlhx0988GAwnew4XGgbz5s3jgQceAODhhx/mnnvuwW6388wzz/DRRx+h1WqZPn266hn31ltvqelUgeAuss6ePZsNGzag0+mYOnWqaqz+9NNP8+abb6LRaHj22WfVFMHExESffVL6rSAIgiA0LkTAaSDU5kKiNjAajdhsNsLDw10EnMjISNXH4uWXX2bv3r1B7TcyMhIgoIWWXq9XvT78+Yo4t1un06HVamvdKE+j0dCyZUsAnwveAQMGMHfuXCIiItiyZQtXXnml12igSZMmcf3111NaWsrQoUP54YcfqtxQK15Eqamp6t8lXSNwglmg+BqH+fn5qgGj++tWq5XQ0FBVhLv33nu9HuPSSy8lMTGR7OxsPv/8c5/tUcSewsLCWkkJzMvLAyrHYWRkJBUVFZw4cYLt27fz/fffc+zYsYCPEx4ezsCBA3nkkUdISkoiPz+f+fPnc+zYMb/v7dmzJ6NGjQIqxctdu3YF/BlOP/107r77bqDSS0ev16v+N/U5fza0OVyoe6ZNm8aDDz4IwGOPPcbs2bMpLy9n4sSJfPbZZ+h0OmbOnMkVV1wBVJYQf/XVV4M6xpgxY9Sfv/nmG1atWoVGo+G5557jrLPOAuDdd99l+vTpQKUfzqWXXhrwd4P44giCIAhC40IEnCZIbSzuDQYD7dq1IyoqysUDB6Bfv37069eP0tJSHn744aAWltHR0Wob/aHRaNTtlUgEf2i1Wjp37kyXLl38VgOqDspNrr+Ihb59+/Lmm28SGxvLtm3buOSSS6qUP4fKaI7Fixdz2WWXYbVaueaaa9i0aRNGo1FdCCoLQ+WfwWCQsPcgqK2FdWxsrMe/WywWLBYL3333Hfv27cNoNHLXXXd53U9YWBgjRowA4J133vEZjRYfH49Op8NsNrN06dKgU4TcUdKcWrVqxZlnnkm3bt1UkSgrK4tNmzbx5Zdfsm/fvoB9bWJjY7n//vtp3bo1RUVFvPbaa14j1Jy57bbb6N27N1arlREjRvg1/nZm6NChAPz444/8+eefQOW5cp+r6lLoFBG1efP888/z9NNPA5XRLzNnzqSsrIzx48ezbt06QkJCeOmll1R/mvfee4/Zs2cDlRXZAkX5DszLy2PatGkA3H777ep+P/74Y1UUmj59OhMnTkSn02GxWOT7QRAEQRCaICLgNEECWdz7WnworwFqOd7c3FysVitWq5WIiAgmTJhAWFgYGzZsUKMOAkGJwAl0IarcvBYWFgZ8jNDQ0IDEG4fDEXRUgyICBHJj3K1bN5YsWUJKSgp79+7lwgsv9FjFKiwsjBUrVnDBBRdQVFTE0KFD+fXXX33u21eqjywqaxdFoFHMcp3/bjKZyMnJISwsjCVLlgBwxx13EBcX53OfN910E1FRUWoakzciIiK44YYb0Ol07Ny5kzlz5ngUAgOhtLRU7bdxcXGqQJqWlkavXr045ZRTCA0Npbi4mO3bt/Pf//6Xv//+O6B9R0VFcd9995GamorZbGbBggXs2LHD53t0Oh2TJk2iTZs27Nu3j3HjxgU8Htu1a0f//v0B+Oijj1z6e3Z2Nrt37yY7O7tOhU4RUZsnFouFxx9/nEmTJgGVlaeee+45bDYbN954I19//TVhYWG8+uqrXHTRRQB8+OGHaoTM6NGjXaJqAmXmzJnk5eXRqVMnNQLtq6++UkWdMWPGMGrUKHUshIWFyfeAIAiCIDRBRMBpggSSMuJr8eH+mtVqpby8HKvVil6vJzIykr59+6qmjY899ljAN4rBpFBB9QScQMjNzeWLL77gyy+/VH12AsE5AieQxWaHDh34+uuvSUtL49ixY1x22WX89NNPVbbT6/V8+umnnHvuueTl5TFkyBC++eYbr+fJW1SJLCqrjzfxy2KxEBYWhsFgqCLgKFEqe/fu5aeffkKr1TJu3Di/xzIYDFx55ZWA/zLy55xzDmPHjqVFixbk5uby2muvsWnTpqDFR+f0KXcT8YiICM4880yuvvpqevToQWRkJGVlZfz1118cPnw4oP0bjUbuvfdeOnXqRElJCQ8//LDfUuFxcXEsWbKEkJAQPv74Y954442AP49iCPvRRx+5RN5kZ2dTWlpKdnZ2nfp7iHdI88PhcDB58mQ1kmbmzJk89dRTWCwWBg0axOeff05ERATz5s1TBcY1a9YwdepUoDJyZty4cUFVoYJKoUbxvZkyZQphYWH89NNPPPPMMzgcDi6//HLuvffeKibrks4nCIIgCE2PkPpugEDQN3P+MBqNfhcVRqMRs9nscTv31yIjI7FYLOoCVjFNfOqpp1i2bBkZGRnMmjWLp556ym/blPdaLBZ0Op3PbSMiImjRogVQKUxERER43K5169Z+jwuVIeye+Oijj1x+97UAV8qf2+12jh49qgpSvigrK1OrlOzYsYOrr76aadOmMWDAAJft0tLSWL16NVdccQU7duxg2LBhvPvuu5x99tkun72iokK9Hs6CkiI8KDfugS7wA+1/tb2/YKhOtFSwOItfBoMBq9WqCmHKQt35synjJCoqirfffhuAQYMG0bp1a4+iYKtWrVx+Hz16NKtWreKbb74hPDxc7eue+tTpp5/O008/zbJly9i+fTtr1qyhW7duDBkypErakDtr1qwB/ieC2u12j5E1//77r/pzVFQUDocDs9nML7/8woEDB9BqK/X+du3a+Tze1VdfzaeffsrBgwd55JFHGDlyJKeffrrX7S+77DIee+wxZsyYwZNPPknr1q0588wzq2zXpUsXl9+vu+46HnzwQfbu3cvu3btJS0sjJydHrXSXmJiIXq9Xz497/6lpP3UX9Oqi3wt1T6Dzyp9//smCBQt48803AXjkkUe47LLL2LJlCw888ADbtm1Dr9dTVlamfofY7XbVTF+r1bJixQr1e+idd95x2f+WLVtYtGgROp2Op556ig4dOgCV328vvfQSUOlvM3ToUDZt2sTjjz9OeXk51157LbNnz0an06nfBzExMSIsCoIgCEITRSJwmilKdQpPT+jcozucjVuVtBGLxYLRaGTWrFlAZWUMT6W13VEEnEBTqGJiYoDaj8CpLqGhoWr0Qk5OTsDvi4mJYcGCBfTr1w+bzcbjjz/Od999V2W72NhYPvvsM0477TSysrK488472b17t8s2SuSHc6SIczSIv6ojgmfcIyoUQQfwOFaUcVJQUMAHH3wA+Bb/3OnWrRv/+c9/KC0tZfXq1X63NxgM3H333dxyyy3odDp27NjB7NmzA0qpcjgcajUb9+gbTyjpVTqdjoqKiqBTGK+77jq6du1KeXk5S5cu9ZtONWzYMC699FLKy8t59NFH1WghX8TExKiVfd577z1ycnI4cuQIdrudlJSUWjcxF5ovDoeD1157TRVvHn30UUaOHElRURH33nsv27ZtIzIyktdff10VOt3FG51O51Xk27t3L++++y4A11xzjSreOBwOxo4di8lkolu3bjz11FNs376da665BqvVyhVXXMH7779Px44d6dChA0lJSWJILAiCIAhNnDoRcI4cOVLnT8uF+sFdPLjlllu4+OKLKS0t5dFHH/V73YNNoVIEnPz8/Oo3msA8awJFWcgrhrCBEhERwaxZs7jiiiuw2+1MmDCBTZs2VdkuMTGR//73v3Tq1IkjR45w/fXX8/vvv7scX6nOpfh8KH+TkPnq4y5c+kuRyc7OJj09XTUv7dOnD7179w7qmEoa0IoVKwKaMzUaDRdccAHjx49XU6rmzp3LDz/84PP95eXlOBwONBqN2ncCOZZi3GyxWIJKNQwJCWHkyJF0794du93OsmXLfKZTaTQapkyZQvv27Tlx4gQTJkxQF7++GDZsGAAffPAB5eXlRERE1Hs1KqFp4XA4eOqpp3jrrbcAGD9+PCNGjKCgoIB77rmHHTt2EBUVxcKFC+nevTsQnHize/duZs+eTUlJCaeddhpXX321+tqvv/7Kxx9/TEhICO+88w4FBQVcffXVFBYW0qdPHz744IOABFlBEARBEJoOdSLg9OjRg+PHj9fFroV6Qom8gUozVJPJREZGBlarlfnz5xMWFsbGjRtZu3atz/04p1AFQm1E4Jw4cYKff/652u93R1nQBxOBoxASEsLkyZO5+OKLKS8v5/HHH/fYtlatWrFhwwa6d++OyWTi8ssvZ926dWpkgmIurYhpSkSVPHmtOe4m3t7EAJPJRH5+Pu+//z4QXPSNwo033khERATp6ekuIp0/2rdvz2OPPUa3bt2w2+188sknLFmyxGtkW2lpKVAZHRNMqk94eLj6+fPz84MS5nU6HcOGDaN37944HA7ef/99n+MwMjKSl156iYiICH766ScWLVrk9xgXX3wxiYmJZGVl8eeff9K2bVtSUlJU42lBqAkOh4OJEycyY8YMAB5//HFuvfVW8vLyGD16NLt37yY2NpY333yTM844AwhOvNmxYwevvPIKpaWldO3alYceekhNLS4oKGDZsmVAZbpy9+7duf/++zl+/DgdO3Zk9erVIlQKgiAIQjOk2gLOhRde6PVffn4+gwcP5sILL6zNttY6zosRiRjyjCLcOJsjGgwGKioqKC4uxmKx0KVLFx599FEAnnjiCZ9PzpUInOLi4oDOubOA46vcsjcOHz7Mn3/+GdDTfAV/2yo3zdWtBhQSEsLzzz/PgAED1Milo0ePVtkuOTmZL7/8kgsuuACz2cyQIUP466+/MJlMqsAgUTe1T6BG0AkJCWzcuJHi4mLatWvHVVddFfSxnNOAFi9eHNR79Xo9t99+O9dff72aUjVv3jyP2waTPuVOdHQ0Wq0Wu91Ofn5+wOXFoXIBO3jwYM4//3wcDgcfffQR+/fv97r9KaecwjPPPAPA66+/7rNCF1QKUjfffDNQGcWklER3TzFUsFgsZGRkkJGRIQKP4JcZM2bw4osvAjBhwgSGDRuG1WrlvvvuY8+ePcTHx/PWW29x2mmnAbB06dKAxZv9+/czd+5cysrK6N69Ow8++KCLx9pbb72F2Wyme/fuTJw4kcWLF7N69WrVI8fdU0sQBEEQhOZBtQUcpdRs3759ue2229R/I0eOJCIigptuuonbbrutNtta62RlZXHkyBH27t0b1KKkOeHsA6KIBQaDgcjISCIjI1Xx4MknnyQmJoaMjAy2b9/udX/t2rUjIiKCwsJCn9spREVFodFoVMEoGKxWK//88w8AqampQb3XF23atAEqF4zu/jSBEhISwvTp0znttNOw2WweK1NB5ef/+OOP6du3L+Xl5Xz77bcA4ndTh/hKnXKuVJWYmEjHjh0BOHr0KH/++We1jjdq1CigstTwli1bgnqvRqOhf//+DBkyBKh8au9tO/ifkBMMWq1WTaWyWq2sWrUqqLGo1Wq59tpr6dWrFw6Hg48//tinSDpo0CBuvPFGHA4HkyZN8uuXNWrUKLRaLZ999hlr1qzBYDBQWlrqMQrHYrFQVFREUVGRVGoTfPLzzz+rpcJfeeUVhgwZgsPh4LnnniM9PZ24uDjefPNNOnfuDFSaEs+ZMwfwL944HA6WL1+O3W6nR48ejB07ltDQUPW1pUuXsnPnTkJDQ3nnnXf4+uuv1dLjQ4YM4YILLqjrjy8IgiAIQgOl2gLOL7/8wsyZM1m8eDF79uzhlltu4bbbbuP2228nPDycm2++uUELOKtWrVKNNs844wyuuuqqoErYNify8/NdjIwNBgOpqakkJCSoqVSAWlVJERk8ERUVxWWXXQYQkHGrVqtV066CSaNyOBzs3r0bu91ObGwsp556asDv9Vcd64wzzqBjx46UlZXx9NNPq6llwRIWFsZ5550HwK5du3xu169fP6DSXyohIcFv5I3ZbPZYElvwj7cS7VAp+p44cYKsrCyg0oPlqquuoqysjNtuu61aXk09e/ZkxIgRQKU5anVEFqU93vq58llsNlu19q9UhNNoNBw7doxly5Z5jBrzhkajYdCgQRiNRk6cOOHR+8mZxx57jJYtW3L48GGvUUUKXbt25YEHHgDgwQcfVOeJ7Oxs/vnnH5cxoFTRi4qKEuFT8EpRURG33nordrudoUOHqumRK1euZN26deh0OmbNmqUKuIsXL+bVV18FKr8/QkJCfKYqVlRUcPDgQSIiIrjttttcfKnWrFnDjz/+iEaj4d5778Vms3HzzTdjt9u59tprmTJlippCKwiCIAhC86PaAo5Go+Huu+/mr7/+Iicnh65du6rlahs6S5cuZeTIkQwcOJDJkyczadIkfvrpJ+69915GjRol6VRuKE/f3bFYLBQXF6upVMpTwW+++cbn/m688UYANm/ezJEjR/wePzo6GghOwDl69Cg5OTlotVq6du1aqyV+NRoNl1xyCe3bt8dkMvHMM8+oHiPBovgm+BJwADp16gTAoUOHqvjdKGKNc0SBYjYtUQZ1i0ajYeHChaSmpnLw4EHGjh1brflj0qRJJCUlsW/fPr788sug35+eng5UlqL3RGhoqJqeYTabq9XGiIgIEhMTiY+Px2w2s2rVKv7666+A328wGLjyyisB+Oqrr7xGC0FlquXkyZMBWL58ud/opkmTJtGhQwdOnDjBU089BVRGC1VUVFQRcFJTU0lNTZXUQ8ErDz74IAcOHCA1NZXXXnsNjUbDtm3b1HLeDz/8ML169QLg7bffZu7cuQDce++9fh8AOBwONQJt0KBBapowVD78+OyzzwAYOXIkrVu35pprrsFsNjNgwADmz5+PXq8XYV4QBEEQmjE1NjFu0aIFCxcuZNWqVcyYMYMrrrii2ovZk8Eff/zB5MmTmTFjBlOnTuXhhx/mqaeeYvPmzQwcOJAlS5YwePDgoCquNFac00E8/Q7/SyfxVm7cOZVKEXB+/vlnn8JB+/btOeecc9R0Cn8oAo6vBZ8zNptNTZ3q1KlTnTxpDwsL44UXXiAyMpJdu3bxyiuvVGtR3LVrVwAOHDjgU6BSBJyDBw9Wec1TWXEgoFLMtYnSf+pCNGooC5akpCSSk5NJSkpS/xYeHs6MGTMIDQ3ls88+q1YkX0xMDNOmTQPgyy+/DCq6pbCwkMOHDwOoXhyeUMZweXl5tefokJAQbr31Vrp06YLdbmf9+vVs3LgxYI+ps88+m9TUVGw2G//97399bnv++eczaNAgNZXK15xsMBh4/fXXAViyZAn//PMPCQkJaknn6uJpTvS2jYilDR+z2UxWVpbXa2WxWHj77bdZsmQJWq2WZcuWERsby5EjRxg/fjx2u50rrrhCrR731ltvqRFiY8eO5Z577vHbBmWsJCUlcfHFF6t///3331XT4kGDBnHWWWfx8ssvk52dTVpaGosXL6asrAybzSbioyAIgiA0Y4K6u/Xle9CrVy+2bNnCDTfcQM+ePdWnvQ2NgwcPYjabOf/889WwZbvdzplnnsmiRYu48cYb+eSTT7jjjjuC2q/NZqOwsNDlX0PH3azVk3mrc+oU/M/U2GKxVHmaHR8fT8uWLSktLfXq6aIwePBgAD7//HO/C59gI3DS09MpLy8nKiqKdu3aBfSe6pCSksLkyZPRaDT897//VZ+cBkN8fDytWrXC4XD4rEKkCDiHDx8mIyOjyjVyF9ksFgt2u/2kLioDNf/1hbdxVB0BJ5DFd7B4Sq8qKSmhR48ePPLII0BlxZhgKkopXHPNNVx22WXY7XaWL18esGn333//DUDbtm3VdENPOJfXNpvN1TIFh0rxctCgQfTt2xeoFMU/+OCDgNLHtFotN9xwAxqNhu3bt7Nv3z6f2z/++OPEx8fz77//Mn36dJ/bDhw4UJ23x40bh9FopFWrVi5zFrjOYf5E7ED6dG30+9qmMX4fnQz8Xasff/xRNeSfMGEC/fr1w2azcdNNN5Gbm8spp5zCpEmT0Gg0vPXWW8yfPx+oFG9Gjx7t9/gOh0Mdd7fccovqe3Ps2DHeeOMNHA4H/fv35/LLL2fOnDlkZWXRpk0blixZQmRkJOHh4RiNRhFwBEEQBKEZE+J/k/8xcOBA1q9fr1b6cEej0TB69OiAbmTqi71795KTk6NWcCgvLyckJASHw0Hnzp2ZMWMGVquV999/n1NOOYVnn302oP1Onz6dKVOm1GHLax+j0YjZbFYjVNx/V3BOP3KO9nDfrqCggB49erBu3Tq+//57Lr/8co/Hbdu2La1bt2bhwoXs37+fLVu2cPvtt1fZTqlAo6RwFRYWenyivnPnTvXn8vJy1Q8kIiLCxWS4e/fuVd5bUFDAgQMH0Ol0dO3aFa1WG7AxsZIqdtFFF7Fx40bmzJlDbm5uFdHonHPO8bmfzp07c+zYMbZu3ap63bgTGxtLTEwMBQUF/Pvvv+j1epfr5n4tLBYLubm5Lt4K3qhO5JDFYlH7irKY8NZ/gsHbOHJfsHg6vnuanPNizblNgX5eX9spi3+DwUBcXBzh4eE89dRT7Ny5k88//5zBgwfz+OOPM3r0aFVUCaQC1GuvvUa3bt34999/OXbsGLfccovXbRcsWADAr7/+ClRWLdu7d2+V7ZQqV1A5PtasWUNRURERERFccskl6ph65513/LYPYPbs2VX+duTIEd566y2Xv91www1e99G+fXsOHDjAihUrGDhwoM9+escddzB79mxmz57NBRdcwOmnn+5120cffZQvv/ySvXv38tJLL6nGr6GhoZjNZiIiIqos4pWfDQaDy2uK35enuc4Z534fSN+qzXRObzTG76PaxtO1MBqNZGVlYbPZ1Gt8/PhxALZt28awYcMoKiqiT58+3HPPPRw/fpwnnniCn3/+GaiMlBwwYIBLqXCdTsebb77Jm2++CeBzzH7//fdkZGTQsmVLZs2ahUajwWaz0a9fP0pLS7ngggv45JNPuPnmmzl48CAJCQksWLBATZlV+llNI8sEQRAEQWi8BHUXcPDgQc4//3wyMzO9bvP111/XuFF1ybnnngtUlgeFypSAiooKNBoNDoeDTp06MWPGDNq0acPSpUvVp9v+mDhxIgUFBeo/X+eooeAeTeDLvFXBV4WeFi1aqE/l/fngaLVaVbRxLr3qiWAicJQn5+Hh4erTTV/k5OSoba/uTXHfvn3p2rUrFRUVvP/++/z7779BvV8xnv3tt9+8bqPRaFTDzEOHDnm8Rs5eOEpElF6vB2o/GsVbtFZNq2J5G0funzeQqAdffdUXgabNKEKmEqWm0Wh44YUX6NKlC9nZ2YwfP5727dvzzDPPqKKiP1JSUnjwwQcBmDNnDidOnPC5fUVFhZo+FUi0WUhICBdeeCEhISEcPXq0WpFCtUHXrl0JCwujqKiIdevW+dy2T58+9OnTh/Lycr8mzzExMWpUxIIFC9i7dy9Wq5XS0lJ1LOj1epeKes7Ra+6/K35TvubEQObNk01j/D46GRgMBoxGI+Hh4S5zx2+//cbQoUMpKirinHPOYdmyZYSGhvLee++xbNkyNBqNakxcUVFRpVR4IBw/fpyMjAw0Gg29evVShbxnnnmGP//8k4SEBBYvXsy4ceP46quvMBgMvP/++/Tp04ekpCSMRqP6vyAIgiAIzZegVqw///wzFRUVnHfeeVWEjZ9++okLL7yQSy+9tFYbWNuccsopnHHGGSxevJglS5YAlTdhDodDFXHOOOMMXn75ZQ4dOhSwgBMeHk50dLTLv6aIcgNsNpurLHBbtGjByJEjAfjzzz/9Llqvv/56oqOjOXToEN99953X7RSTR38CjsPhUEsOK4s1X5SWlqr7TEhI8Lu9NzQaDddeey1t2rTBarWybNkyNm/eHHCkhyLgbNu2zed2ioCTlZXl0cDYWVRISEhw8Wqp7TSP6ooj/gh0HAVy/OoueJRz5U/sck8ZUkqLf/3117z55puceuqp5OfnM23aNDp06MC4ceMCEveGDBlCt27dKC4u9ps2dOLECWw2G+Hh4S6+PL5wFlr/+usvDhw4END7guXQoUNex0BYWJhq4L1q1Spyc3N97uvOO+8kJiaGnTt3+vUYGjRoEDfddBN2u53HH39c9ftxFmni4+PVyDVn0dH998ZKc/k+qg7uc8evv/7K0KFDKS4u5txzz2X58uUYjUb++OMP1RB7/Pjx6n1CeXk5UDnvByreVFRUqAJ9ly5diIuLA2DDhg1q9aqFCxeycOFCli1bhk6n45133qFfv34i2giCIAiC4EJQAk7nzp35+eef6dSpE/369WPr1q1s376dq666in79+vH7778zYcKEumprrZCUlMQbb7yBVqtl5syZqomu8mRNoUePHkRERAQs4DQ1LBYLBw8e5ODBg1UWsr7EgKSkJLp16wbgU5SByoXUkCFDgMoyrN4I1MS4rKwMu92ORqMhIiLC57bwv+gbxVugJoSFhXH77bfTvXt3HA4HGzZsYPXq1QGZxXbu3BmtVsuxY8d8VuVSfHB27typnnv3SBAlesA9csCf4BFshE59Rx3UxfGVcwD4LdMOnquz5efnEx4ezqhRo9i5cycrVqwgLS2NkpISFi1aRNeuXRkxYoTPqko6nY7JkycTEhLCxo0bfUY1ZmRkAJWRO8FEkHXs2FEVUDZt2uRXQKkO27ZtY8uWLZSUlHh8vV27dsTFxVFSUsK7777rc19xcXFqVapXXnnFr3fOnDlziIuLY8+ePaxatcpvWz1VclP+1lAMtIWa4556+eOPPzJs2DDMZjN9+/Zl2bJlGI1GTCYTd911FzabjUsvvZQHHniginjjr1S4M/v27SMvL4+wsDDOPPNMoLLM/V133QXAPffcw5EjR5g5cyZQWVWtTZs2dTIuBUEQBEFo3ASdMxIXF8eGDRu48sor6d+/P7169eLXX39lypQpHDp0iBdeeKEu2lmrnHvuuSxYsIBDhw4xefJk3n//fQCXBZDZbKZ169Y+q7o0ZbKysjh06JBascN5ge9PDLjwwgsB/FaZARgxYgQ6nY4tW7a4eNk4o0TgmM1mNcLGE8pCMSwsTL2WSslWm81GTk4OR48e5cCBA/z9999qekpNom+cCQ0N5dprr+XKK69Eq9Wya9cuVq5c6fd9ERERpKamAgRkZLxnzx51UelJtHG+Ls6ihC/BoyEasZ5slHMA3s+VYoALqD4azgt8Z1FHq9UyZMgQ3n33XV5++WXOPfdcKioq+OCDD+jdu7daccYTp556qppi+MILL3iNPlNSY5KTk4P6rAA9e/akdevWlJeX10nqq0aj4fjx43z77bfqeXV/vXv37mg0GjZt2uRXlBk8eDADBw7EZrMxadIkn9smJyerJZ8XLlzIwYMH2bNnD5mZmR4FGYvFQlFRkYtBuCKONucx0dRwnuf279/PlVdeicVioV+/fixduhSDwYDD4eD+++/n6NGjdOzYkblz56LVarHb7WpEWTDiTWFhIX/88QcA3bp1IyIiArvdzogRIzh+/DhpaWlceOGFqgn6Qw89RN++fSkrK2P//v3S/wRBEARBcCFoAaeiooJVq1bx22+/YbPZ0Gq1vPfeezz99NPqQrsxMGzYMF599VX279/Pww8/zPPPPw9ULipyc3NZsGABWq2Ws88+u55bWn/o9Xp0Op2aMuVs7ulpgWu1WsnNzeWqq64C4IMPPuDbb7/1eYw2bdpw5ZVXApXVezwt9JTjAXz22Wde0zIU0UYRa7Kzszl+/DgnTpwgJyeHzMxMsrKyKCgoUMWeiIiIWu23Go2G3r17q58pkMo8J06cUH1MfIlJSsnxv/76S/VgUEQbwGMp40CFmbpKiWpMBHIOlEU9VPb3zMxMNQrGUzUwgNTUVPr378+bb77JDz/8wCWXXAL8z4TYG2PGjKFdu3ZkZWXxwgsveOz3yrF+/fVXjh07FviHpXK8DBw4kMjISJ8VBquLEjmneIx5oqKiIuBUQ41Gw5NPPgn4FjoVhg8fTrdu3bDZbGzbto2cnByKi4s9isAGg0FNRXMXR5vzmGhqOI/xmTNnYjabOfvss1myZIk6llatWsUPP/xAREQEixcvJjo6mo0bN6oRusGIN3l5eXz11VfYbDbi4uI49dRTKS8v59tvv+Xbb7/FYDBw9913M2LECOx2OzfddBOPPPIILVu2JDQ0lOjoaBFwBEEQBEFwISgBZ8GCBXTu3JmRI0diNBr573//y3XXXcd1113Hp59+WldtrBNCQkIYPXq0mkI1adIkevToweWXX84NN9zARx99xAcffECbNm3quaX1Q1JSEklJSWrFMeXGF/CaVmC1WikvL6dr165qJbK7775brfLhjSeffJKoqCj++usv1ZfIGY1Gw003/R975x3eVPX/8XeSNmlW92C0adlUZKNf9hJUFEFBURAVRJTlYKiIKKKIA2W5AEVQERVQBBUVBxsBZcgqmy4oJOnOaNIm+f3R37nepBk3bdqm7ef1PH2g6c29555173mfz7gPQPlCdfPmzW5TICuVSqhUKgDlIk5paSm3OJRIJFCr1YiNjUXTpk3RvHlzpKamok2bNtWSFaa4uBhAuWuLL9atW4eysjL07dsX3bt393hcu3btEB4eDpPJhLS0NKe/8V2p+AgVZmrbJSoYEFIHfJHGbDbDZrNxggALZuz6/djYWCQlJSEiIgKtWrXiguweOXLEa5DisLAwLFiwAGKxGD/99BNefvnlCgLnoEGD0KRJE5SWluKHH37wO1itTCbDLbfcIihbmb8UFhYiNDQUvXr1chsrxG63c0LMgAED0LJlS5/nZOPJaDT6XNiKRCJ07twZAJCdnY2YmBioVCqP8bEUCoVTqnUhAYw9UR0p7Imqw8Z4UVER57Y3Z84crk9kZ2dz2btmzZqF1q1bw2AwcK7hYrFYsKuiTqfD9u3bYTabERkZiVtuuQV2ux07d+5ETk4OlEolXnjhBS5O05AhQ/Duu+8iNDQUiYmJuPHGG+tFPCaCIAiCIAKLXwLOtGnToFKp8N133+HQoUO44447sGHDBjz88MO499578cEHH1RXOauN22+/HQcOHMCCBQsQHx8Pi8WCTp06Yf/+/W7TTjcUXLN1sBdfo9GI69evuw1QzLK7yOVyLFy4EC1atEBWVhaGDx/uNX5NQkICt7O+ePFizqKBT4sWLXD33XdDJBJh3759+PzzzytkoxGJRAgPD0d0dDTUajWioqIQFxeHRo0aISEhAS1atEBiYiLi4uIQHh4OmUxWbSl92ULal4Bz+fJlzn3llVde8VoeiUSCm2++GYCzBQJz47FarRUWmyTMBBa+SJOUlISEhASfbczcrq5fvw6TyYTw8HAuTtRvv/3m9budO3fG/PnzIRaLsXnzZjz99NNOFiRSqRR33nknNBoNysrK8OOPP+Kvv/5ya8nmCX5Q40ASGhqKPn36uI0VBJS7AhYXFyM8PJwLfu4LpVLJLbaZa6A3UlNTAQA5OTlo3bo1kpKSPLrGSaVSbt4TiiehhlwSg5vly5fDarWiR48e3JxaVlaGqVOnorCwEJ06dcLjjz8OoDxj5dWrVwFAcNDiK1eu4LfffoPVakVcXBxuvfVWhIaGYseOHcjJyUFISAhmz56NV199FaWlpRgwYAAWLFiA0NBQREdHQy6XQy6XIzo6mgQcgiAIgiCc8EvA+fLLL/Hvv//i7rvv5j4TiUT46KOPMGfOHDz55JN4/vnnA13Gaic5ORlz5szBr7/+ih07dmDp0qVo3bp1bRcrKPDkAmQ2myssXNgLp1wuh1qtxsaNGxEfH49///0X9913n8dgpgAwatQodO/eHSUlJXjxxRfdulX06dOHi5lz4sQJrFixwu0CKSwsDGq1GnK5HKGhoZVOD15Z+KmdfS3u165dC4fDgd69e6Nbt24+z92jRw8A5Vnf+Nmn+ItPfvBVtsB0/SHLgMqj1+u54OZt27b16PZmMpmQkZGBs2fPwmAwQCqVclZqvXv3BgD8+uuvPq93zz33YNmyZZDJZNi1axcee+wxJ0E0NDQUQ4YMQZs2beBwOHD06FFs3LjRZwpyPizDWSDxJt4UFxdzdTh+/Hio1WpB5xSJRE4ug75gMcxOnTrltc+7c38TEsSYL9T4EyeMqB10Oh127dqFjz76CADw3HPPcaL54sWL8ffff0OtVuOjjz5CSEgI/vnnH6xZswaAcNepy5cvY8eOHbDZbGjSpAluueUWSCQS7NixA9euXUNISAhuvPFGJ/Fm3rx5iIyMFJQ9kSAIgiCIho1fK9vRo0d7fIGZP38+3n//fSxevDggBatp+IKB0JgMDQHXBVh8fDwSEhIgl8t97jCHh4dj+fLlUKvV2L17N8aPH8/FbnFFJBLh9ddfh0wmw759+zjXNlc6duyIJ554AnK5HOnp6Xjvvff8sjaoCa5fvw6r1eoztfPJkydx6NAhiMViPPLII4LO3bNnTwDAvn37UFpaWiH7FOAcfJUtMPV6vdO/7trNm9tHQ3UJYdYzTAzT6/XIysqC1Wrlghl7+67RaITNZuNiScXExCAkJAT9+vUDUG6B42lM8BkwYAA+/vhjhIeH499//8VDDz3EuekB5ZYBt9xyC26//XbI5XLk5+fju+++89saJ5B4Em+YyGS325GQkMCJWUJhY8ofAefChQtO9eWKpwDg3uY41r4Wi0VwnDCiZmDim6tgrdPp8PXXX6OwsBBt27bFXXfdBaA8ExtL5/32228jOTkZVqsVs2bNgsPhwKhRowRtBNhsNuzduxcOhwMpKSno378/RCKRk3jTvn17HD9+HKWlpRg0aBBeeuklJCUlITExkQQcgiAIgiB8EtDAB1OmTPG6YA1m+MJUdbnVBBu+7pMtSviLGoVC4WTpwf7GFjPs70B5vIB27dphxYoVGD9+PDZv3owZM2Zg6dKlbq/dpEkTvPTSS5g7dy4WLlyIdevWcTF4+PTq1Qu9e/fGM888A61Wi/DwcEyZMkWQu5IQ0tPTBR0XGhrq9nNmbp+UlASZTObWmsvhcHBuY/fffz8GDhwoaKHdsWNHSKVSaLVaZGVloV27dpy5PVBu/SOXyzkrAKPRiIKCAs69jVmLuLMMcF2AevpbbVgViESigI1LIedh4pfRaHQKbFtWVsbVdWxsrNdzKRQKqFQqqFQqxMbGOqWqHzRoEGQyGfLz85Genu4U/8VTP05KSkLr1q0xcuRIXLp0CSaTCR9//DFatWrldFx+fj4WLlyIH374AUePHsXVq1cxZswYpKSkeL3n4cOHw2q1YteuXTCZTIiLi0OPHj0q3KOrG0lpaSn27duHvLw8J7epPn36uL3OgQMHoNfrIZVKMXHiRMHtylwmWR/Oycmp4EYJwCk+lkajQXR0NPLy8nDs2DEugLS7+3BNMe1u/uPD+gZfPGXHN5RnSG0gZIPFaDTCarWisLAQERERsNlsCA0NhUqlwubNmwEA06dPh81mw/z58/HFF1/A4XDgxhtvxLlz57Bo0SIcOHAA586d4yxLp06d6rVMBw4cwIEDBwCUvwstXrwYRqMRI0eOxLVr16BSqfD8889j/vz5sNvtGDp0KBYvXoyQkBDEx8dDKpUGpoIIgiAIgqjXBNy35N577w30KYlaQqlUIj4+XtAuslarhVarddoVj4uLQ3x8PIYNG4bVq1dDJBJh5cqVXMYvdzzzzDPo1KkT8vPzsWTJEo/HNW/eHJ988glatGiBoqIiLF26tEJg39qCxfBhqcHd8fvvv+Po0aMICwvDk08+KfjcYWFhnKvVqVOnoFAonKxEgIrBdCMjIzkLA/bjrk29uX00NJcQfkpxdt+sDpKTk5Gamsq58niDtYVSqYTZbEZ2djays7MREhKCNm3aAIBf/TY1NRXbt29HmzZtcO3aNYwdO7ZCRqaoqCgsWrQIH3zwAeLi4nD9+nUsXboUW7ZsgdVq9Xp+qVSKm2++GRKJBDqdDgcPHsSxY8dw+PBhHDp0CAcOHMCePXuwc+dO/PHHH9i+fTt+/fXXCuKNJ4qLi7F161YA5fHH3Am0vvDHhUoikWDIkCEAgB9++EGwOxT/M61W6/Z7rmOCzZcNZYwEM0qlEhKJBNHR0ZBIJJzo+ttvv0Gr1aJx48YYPXo07HY7fv31V5hMJkRHR6N///4AgNzcXBw8eBBAufWbN8sYh8OBHTt2cOLNyy+/jCVLliAvLw+33nordu7cCbVazYk3ZWVlGDJkCBYsWIAmTZqgWbNm1GcIgiAIghBMzQYHIeoNQoJ08oWEMWPG4L333gMAvP7661i1apXb74SEhOCjjz6CRCLB77//jj179ng8f3x8PFauXInWrVujpKQEH374IffSXZswASc5Odnt3202G959910A5fE/EhIS/Do/cznZuXMngPKYLDqdzq1Ljz/Ci6vbB99tSqFQNKjFKau3+Ph4TjDgW2cIgbngsPZhaawNBgNMJhNuuOEGAMDp06f9KltiYiJ++eUXdOrUCYWFhRg/fjz+/PPPCsfdcsst+OGHH9CtWzc4HA78+eefWLRokU9LtIiICC570/Xr15GRkYHs7Gzk5OTg+vXr0Ol0yMvLQ2FhIQwGA6xWK6RSqU/xBgA2b94Ms9mMpk2bom/fvn7dN8MfAQcA5ybzyy+/eBVwXMeK0Wjk2svdPEduUsEJs6SSy+WIiYlBTEwMFAoF7HY75+I9bdo0yGQyLF++HOnp6ZBIJLjzzjsRGhoKh8OB3377DXa7Hc2aNfMaD89ms+Hnn3/Gv//+CwAYOHAg5s6di6ysLPTv3x+HDx9GbGwsXnjhBU68ueuuu/D8889zFl4EQRAEQRD+QAIOUWn4AY5Z2nFvVgmTJ0/Gyy+/DAB4+umnPca56dy5M5555hkAwKJFi7y+5KpUKkyZMgVdu3aF3W7H559/jl9//bXW4hgVFRUhPz8fIpHIoyvM5s2bcf78eURGRnKZTvyBCTi7d+/2GZPG2yLTV1ybhpxJxzWFdGXqQqFQwGq1Ijc3l4u/wlyqFApFpQUcoDxz1Jo1a9CvXz9YLBY8+eST+PbbbyscFxkZiYceegiPPfYYwsPDodVqsWzZMvz0009ex0jTpk3RvXt3tGrVCm3btkW7du3QoUMHdOrUCTfddBO6d++OXr16oW/fvhgwYABuv/12n+LN6dOncfToUYhEItx///2CM/q44q+AM3jwYEilUmRkZLjNcMdwHSvMisNisVSqnETtwMZqXl4ecnNzuflt27ZtSEtLQ3h4OCZOnIh//vkHc+fOBQD079+fc807fvw4cnJyEBoaioEDB3p0hystLcWWLVtw9uxZiMVi3HHHHejYsSPS0tLQv39/nDt3DklJSZgzZw5efvlllJWVYfjw4XjnnXfQpk0bhIeHNxhBnCAIgiCIwBHQGDhEw4K/YFMoFG7NzFnwVxYb5+WXX0ZOTg4+/vhjjBs3DiqVCrfeemuF77344ov45ptvkJ2djRUrVmDmzJkeyxEaGopx48YhMjISf/zxB7Zu3Yr8/HzBgScDCVsgNmrUyCnmCcNut3PBMidPnozw8HC/r9GzZ0+IRCJkZmYiPT0dKSkpTrGHhOIt5g3bxQbKLTKIcsHSU8YpdyiVSphMJthsNlgslgpBSlu0aAEAOHz4MOx2u999VS6X4/3338fLL7+MzZs348UXX4REInHKEsho3749mjdvjs2bN+Pvv//G9u3bUVBQgOHDh0OlUrk9f0JCglvrsMoIL/n5+di4cSMAoF+/fj7jVXmDtYFWqxV0vEqlwoABA/Drr79i06ZNaNu2raCxwiwIgy1IOuEZ/rwFlFvImM1mSCQSLFy4EAAwceJEiMViPPTQQygtLUWrVq3Qvn17AOWiDLP6jI2NxeXLl2GxWFBSUgKLxeL0k5ubi7KyMoSEhOCuu+5CSkoK9Ho9Bg4ciNzcXLRt2xaTJ0/GjBkzYLPZcPfdd2Pp0qWQyWSIiYnxGEONIAiCIAjCG2SBQ1QKoa45zI1Ep9NxKZVnzZqFYcOGwWq14r777sP27dsrfE+hUHAp6b/77jtkZWV5vY5YLMaIESNw7733QiQSYc+ePfjiiy8EZfgJJJcuXQLg2X1KJBJxQVbdCTxCiIyM5LLrnD9/vkLMG6F4a0MWoNUfl6H6ji8LE3coFAqo1WpoNJoKAmeHDh2gVCpx7tw5vP/++5UqU2hoKBYuXIhx48YBABYsWICzZ8+6PVapVGLs2LGcwHPo0CG8/vrr2Ldvn1Pg30CTn5+PDz74AAUFBYiLi8Ptt99epfMx4evcuXOCLaKGDx8OANiyZQuuXLniZJnhjYYW+6muw5+3WPyb0NBQPPzwwzh8+DBUKhWefPJJPPfcc7h06RI0Gg0GDRrEWdmUlJRwgbFzcnLw559/Yt++fTh8+DBOnjyJ8+fPIzMzE9evX0dZWRnCwsIwcuRIpKSkIC8vD5s2bUJubi66du2KZ599lhNv7rnnHrz99tuQyWSUaYogCIIgiCpBAg5RKdzFS3FNt8wWSAUFBTCbzTAajdDr9SgpKcGyZcswfPhwWCwWjyLOTTfdhB49esBms2HlypWCyjVgwACMHz8eYrEYhw4dwpo1a2p0B53FF2nevLnbv4tEIkyaNAkAsGLFikq7ZzD3GyYYVQbWdmlpaTh9+rTTgpYWrs64qw+TyYT09HRkZGS4FRKMRiNnfeauHjUaDV566SUA5RZnlXGlAsr71KxZs9CtWzcYDAY89thjXgXPAQMG4KmnnkLjxo1hMpmwYcMGLF68GPn5+ZW6vjeYeJObm4uYmBhMnjy50sIlIzk5GRqNBqWlpVzgWF/cfffdCAkJwYULF5CWlgabzebUZq7uhOx34L9sfEIEH6L2uXjxIs6ePQuz2YyoqCjMnDkT33//PaRSKTZs2IDDhw/j008/hUgkwurVqxEWFsZ9V6VSoVOnToiPj0dSUhJatmyJG2+8EV27dkXPnj05d8Hhw4dj1KhRePTRR9GkSRMUFBRg06ZNMJvN6NSpE2bNmoXJkyfDZrNh+PDhmD17NhdMmQRxgqgfpKWl4ciRI15/vLntEgRBVBZyoSICAnPH0el0MJvNTou0yMhITqgQi8WQyWSIiIjA0qVLYTAY8Mcff2DMmDG4cOFCBSuHKVOm4MCBA/j9998xduxYzvLEG127dkVISAg+/fRTHD16FGVlZZgwYUJA79cdxcXF0Gq1EIlEaNasmcfjRo0ahRUrVuDatWvYuHEjxo4d6/e1brjhBnz77bec8MJ3U/OHzMxMZGRkVBDkKnOu+oy7+mBBbtnfAXDtAJTXLRsH7gQcuVyO6dOn488//8T27dvx6KOPeg3a7Y2QkBB88MEHeOihh3Du3Dk8+uijWL9+vceYVC1atMCzzz6LvXv3Ytu2bcjKykJWVhaXYauqIgtQUbyZOnUqoqKiqnxekUiEvn37Yt26ddi9ezduueUWn9+JiYnB4MGD8fPPP2P37t1o1qwZ5HI5Z2Hm6k7oGvOI/zfXdONEcMBEN4PBAKlUitzcXCxcuBCff/45JBIJ1q1bhw4dOqBLly4AyuOw9e3bF9u2bePOIRKJMGDAAL+uW1RUhE2bNsFoNCImJgZz5szBww8/DKvVit69e+P999/nAn2bzWbqMwRRx2EWz0Le3RQKBdLS0rxmJSUIgvAXssAhAgKzUADKXYMsFgv3olpQUAClUonk5GS0bdsWiYmJ3CJp4cKFaNGiBQwGAxcjg0+rVq04l4sPPvhAcHk6duyIxx9/HKGhoThx4gRWrlzJmcZXF8z6plGjRl5f0mUyGWeF89FHH1XKCodZ4Bw7dgznzp2DTqdDVlZWBQsC9uPJeoAJEyqViqxt/ESpVEKlUkGtVnML+7KyMk5Qcx0HAGA2m5Gbmwuz2QygfMG4cuVKREZG4siRI3jzzTcrXZ6IiAh88sknSEpKQlZWFh577DEUFRV5PF4ikaBfv3548cUXcdNNNwEAMjIy8McffyA9Pb1KgcBNJlO1iDeMfv36ASgP5C2U+++/HwDw008/ITQ01MkKx11KcNf08fzsVA01uHcwYzQaYbPZUFxcDKPRiI8++ohzTVy1ahWGDRuGKVOmQKvVol27dpg/f36Vr2kwGLBp0yYUFxcjKioKPXv2xLhx41BSUoKbb74Z77zzDhISEhATE4OQkBBynyLqHJmZmT6tTNLS0mq7mDWKRqNBWloaDh8+7PVn3bp1nEU6QRBEICELHCIgsCDGbCGbkJDA/d9T7BC2oHvwwQfx6quv4vPPP8fEiRMrHDdx4kT8/vvv+Pvvv3Hw4EH873//E1Smdu3aYcqUKfjoo4+QlpaG4uJijBgxAlKptNL36Y2LFy8C8Ow+xaeqVjipqakAgLNnz8JgMOD69evQaDScBQgLnltQUIDIyEi3gYqBcneU2NhYsiaoBAqFAikpKU6f8S1wgPJAwHxhjKUSV6lUiImJgclkQlhYGBYuXIgpU6Zg4cKFGDhwIGcl4C/x8fH49NNPMWbMGJw9exaTJk3C6NGjvfb58PBwjB07FjKZDMePH0dRURH+/fdfpKeno0OHDoiOjvarDCaTCXv27OEsEgIt3gBA9+7dERISgoyMDFy5cgVNmzb1+Z2hQ4ciLCwMly5dwuXLl7kYREBFCyt3vzOYSxUJnsEFyxqWkpKCb7/9Fh9++CEAYPHixRg7diw+++wzbN26FaGhoVi7dq2T61RlMJlM+Pbbb1FYWIjw8HD07dsXP//8M6xWK/r06YPFixdzY4csGom6SGZmJlJTUwW5j7JYfA0FjUZDVjUEQdQaJOA0YKqaatvVlUAkEnE71gwmJrC/A+CybzRq1AiNGjXCuHHjsHDhQvz99984f/48Z13CAgEnJydj3Lhx+Pjjj/HRRx9h0KBBTotKb+4ePXv2RKdOnfDkk08iOzsbP/74I6ZNm+b1Zbpbt24+793hcCAvLw/Xr1+HVquFVqvF+fPnAQA333wzEhMTnerJHY8++igWLlyIDz74AEOHDhW8O6tWq9GqVStIJBKuDZKSkiAWiyGXy+FwOCCXy1FSUoLY2FgYjUZYLBa3Io0/Cwuh/cVT2t26htD7YPXi2vddF/ghISHcOUUiEfLy8qDValFYWIjBgwfjzjvvxE8//YRJkybhwIEDPvuDJ2ElOjoaGzZswPDhw3HkyBGoVCq8//77PrPetGrVCjabDT/++CO++OILFBYWYs+ePWjbti2GDRuGXr16ITQ01GOQZOA/tymj0YjY2FjMmDHDpwAkNICyq8VLamoqTpw4gX379uHOO+/kPvfUT1UqFe688058++232LVrFwYOHAiDwQC73e62rs1mM0wmE5f2neFpzAR6fAg5X1Xn8LqIp8D0NpsNCoUC33//Pd5++20AwOjRo5GSkoKlS5di3rx5AMotsZjLIPCfGO6Lhx9+mPv/5cuXMXLkSOTl5aFp06b44IMPMH78eFitVvTv3x9r1qyB0WiESqXiLFMJoq7BYhmuW7fO5ziJjY0lQYMgCKKGIBcqotJ4ciXQ6XRIS0uDTqeDUqlEXFxchcUsP9CxUqnk4lisXbvW7bWefvppREZG4syZMxgyZIhfJrudOnXCihUroFAocOnSJS72jhBKS0tx/vx57NixA19//TWWLl2KOXPm4LHHHsPUqVPx6quvYsWKFfjuu+9QWFgIqVSKNm3aCDr3iBEjEB8fD61Wi++++07w/QCAVCpFq1atAAAWiwVxcXGcaxrwX5BpVvcymYxrJ9eArUTNoVAoYLVaOTcrs9kMqVQKq9WKDz74AI0aNcLZs2e5xWZladeuHb788kvI5XLs3r0bc+bMESSUSCQSDB8+HKtWrcKtt96KkJAQnDlzBm+//TbGjRuH9evXo7i42O13XWPeCBFvqkKnTp0AAEePHhX8nVGjRgEAvvnmGxgMBs7lzR3MJc7b/EYEByaTCdnZ2di2bRtefvllAMCwYcNw7733IiMjA6+99hpKSkrQsWNHLiNZZfn999/Rq1cvnD59Go0bN8YHH3yAxx57DPn5+ejYsSM+/fRTKBSKgFudEURtkZqaii5dunj9IfGGIAii5iABh3DCn8W9p0xFer0eFovFye/XddHDjxeiUCgwevRoAMC6devcxqqJiYnBd999B41Gg8zMTAwdOhQ//fST4Ptq164dZsyYAbVajczMTCxevNhtfJCioiL8/fff+PLLLzFv3jw8+uijeOmll7By5Up8//33OHDgAC5dusQt6iIjI9G6dWv07t0bI0eOxOzZswVb0shkMjz22GMAgI8//tjvWDjMUokFvvVkSePaTlqtlrMcImoeqVTKWQskJydzWZU0Gg3ee+89AMDy5cuxa9euKl3nf//7H1avXo2QkBD8+OOPWLhwoWCLjejoaDzzzDP47LPPMHbsWERHRyM/Px/r1q3D/Pnz8eWXXzpl13AXsLg6xRsAnJuZPwLObbfdhvDwcFy9ehXHjx/nxDQWkwj4L04RAMHzW3VDoqtnmHizd+9ezJgxA3a7HePHj8cjjzyC69ev49VXX4XBYECrVq3w3HPPQSKRVOo6DocDixcvxrBhw5CXl4du3bph3bp1mDx5MvR6PVq2bIlFixZxmxIWi4WylxEEQRAEEXDItpdwwjUbizc8uRLExsZCr9c7+UPzFz3s84KCAi6a/wMPPIDnnnsO169fxy+//IK77rqrwnlTU1Px888/Y9KkSdizZw8ee+wxTJ8+HWPHjoVY7FuLTExMxPTp07Fs2TJcvXoV7777Lh588EHk5OTg0qVLuHjxottFmVqtRkpKCho1aoSEhAQkJCSgUaNGiIiIqHK2nhEjRuCTTz6BVqvFV199hXHjxgn+LjNpTktLQ15enkf/c4q/EDwoFAqo1WoA4GIP8enWrRuGDx+OLVu2YOLEifjnn38QHh5e6esNGjQIb7zxBp599ll8+eWXiIqKwtSpUwV/PyoqCmPGjMF9992Hffv2YevWrThz5gz++ecf/PPPP0hOTkb37t3x+++/V1vAYk8wC5zz58+jqKhIUD2FhYVh2LBhWLduHb7++ms8++yzkEqlMJlMnPDKxOWQkBDExMRUWPC7m9+qG3/m5YaGyWTCqVOnMH36dFitVtx777346KOPOLExPz8fycnJmDt3bqWDCFssFjz88MNcoP2HH34YM2fOxJ133omcnBw0b94cS5Ysccrmp1Qqqc0IgiAIggg4JOAQTgQiQCdz3eHjbtHDD24cGhqKBx98EEuWLMGqVavcCjhAuWXA+vXr8dprr2HVqlVYsmQJDh8+jNdee03QAq5JkyaYOXMmlixZguvXr2Px4sVOfxeJREhMTETr1q3RqlUrtG7dGo0bN3Ybt6Iy2aNckclkGD16NJYtW4YPPvjALwGncePGAID09HQA5SKZELEmPj6+QrwWomYQUu+TJk3CoUOHkJmZiSeffBJr166tUlyhoUOHoqCgAK+//jref/99nDlzBo888gi6du0q+LyhoaHo378/+vfvj99++w179uzB0aNHkZGRgYyMDACoUfEG+C/mQmZmJo4fP47evXsL+t7999+PdevWYevWrZg9ezasVmuFGDd6vZ77XKVSOX3f3fxW3VDgZM8UFRXh8ccfh8lkwm233YbPPvsMYrEYb775Jq5fv45GjRrh5Zdf5oRTfzEajViyZAkyMzMREhKCd999F0OGDMFtt92G7OxsNG/eHB9++CFatmyJmJgYREREAKA2IwiCIAiieiABh3Ciuqw1+Iseh8PhFNwYKN9Fvffee7F8+XJs27YNf/zxB9q3b+/2XCEhIZg/fz7atWuH5557Drt378aYMWPwzjvvoG3btj7LEh8fj1mzZuG9995DQUEBmjVrhubNm6N58+Zo1qwZmjRpErgb98GRI0e4uD9qtRoOh0PQovrIkSN48cUXAZSnTAfKU9rm5eVxrissvbUr7DPmBka7w7UPc7VQKBRo1aoVlznnm2++QWpqKmbPnl2l848dOxYGgwHLli3D77//jt9//x0tWrTAAw88gGHDhvll5aPRaPDggw9i2LBh+Ouvv7B//36EhYXhiSeeqPG4H6zvlpWVCf5O//79ER4ejry8PGRkZKBjx46cm4tcLuey6TEXT1cBpzYgK7r/YPGjWJ2sWrUKBQUF6NSpEzZs2ACpVIpr167hwoULEIvFmDdvXqX7pdFoxOLFi5GVlYW4uDh8/fXX0Gg0uPXWW3H58mUkJydjw4YNaNGiRQXrHmozgiAIgiCqA4qBQ1QbRqMROp2OEwrY7+zlm7lPmUwmZGZmIiEhAePHjwdQHrTYXSwcPqNGjcLWrVvRtGlTXLlyBY888gg2b94sqGwxMTGYN28elixZgqeffhp33XUX2rVrV6Mv3L/++ismTpyIwsJCtG/fHhs2bBAk3pw6dQp33HEHCgsL0aNHDyxcuBDR0dGwWq2QSqXIy8uDzWaDVqv1GDfDUwBqonZgbjtAed/s27cvF8j4lVdewYYNG6p8jUmTJuGHH37Avffei7CwMFy8eBGvv/46+vXrhxdffBFnz571K6uRWq3GrbfeildeeQXPP/98jYs3NpsNly9fBgC0aNFC8PdCQ0M5a51du3Y5xeNiuAabJoIHk8kEm83GPTdWrlwJoHycsPn7xIkTAMqtFBMSEip1Hb54o1arsX37difxpkmTJli8eDEaN25cadcsgiAIgiAIfyEBh6g29Ho9rl+/zsWVcbdQYp/LZDJYLBbMmzcPcXFxSEtLw+rVq31eo0OHDli/fj369u0Lq9WKV199Fa+88gpKSkp8flckEtVKymuHw4G1a9di1qxZsFqtGDBgAFavXi0opsalS5dw++23Izc3FzfccAM2bNgAjUaD2NhYJCYmQqVSITo6movb4UmkYYGNAVBw1CBAoVAgJCSEEzRtNhtGjBiBCRMmACiPuTFs2DDs3bu3Stdp2bIlXnvtNezatQtz585Fq1atUFJSgu+++w7Tp0/Hk08+iW3btvndH2pjHF25cgUWiwUymcxvq7m+ffsCAHbv3o28vLwKblTMCkcqlXLWUTROah+j0Qiz2Qyr1YqwsDBMmDABBoMB//vf/zBkyBDuOCbgJCcnV/o6fPFm5syZUKlUTuLNG2+8AYVCgatXrwbk3giCIAiCIIRAAg5RgeparPAXqa6fq9VqaDQaNGnSBK+//joA4N133xWUKSk8PBxLlizBtGnTIBaLsWXLFowZMwbbt2+HzWYL6D1UFYfDgbfeegvvvvsuAGD06NFYsmSJoB3crKwsjBo1CteuXUPr1q3x2WefobS0FFlZWcjKygIAzqoJ8JwlDPgvzThQHkMiPT3dZ3vTItY9vuqF/d2btZNSqeRSvisUCkgkEkRFRWHevHkYP348xGIxtm/fjkGDBmHgwIHYvn27X9YyroSHh+PBBx/Eli1b8OWXX2LYsGEIDQ3FpUuX8P777+Ohhx7Ce++9x8W3CUYuXLgAAGjevLnfmYWYgHP06FGoVCooFAq3LjBs/ASLxVpDG4NGoxFarZard61WC4PBAABYsWIFdu7cCYVCgTVr1jgFsj9+/DiAygk47sSbsLAwJ7epX3/9FV27dnXqNyx7WUNpG4IgCIIgagcScIgKeFqs+Lt4iI2NRUJCAmdZwhapQLl1TkZGBs6cOQOTyeQkPIwfPx6dOnWCwWDgxBxfiMViTJgwAR9++CGioqJw+fJlPP/887jvvvvw888/B42Q8+GHH+LLL78EAMyaNQsvvPCCoMVnTk4ORo0ahatXr6Jt27bYtm0bYmJikJeXB71eD4PBwLULs+AAwNW3p3Zj6W5lMpnPxWmwLGKDDV/1wv4udNzI5XLExMQgJiYGarUaCxYswG+//YaRI0dCKpVi//79GDZsGAYNGoQffvgBdru90mUXiUTo0qUL3nrrLXzxxReYOHEimjZtCrPZjJ9//hlPPvkktmzZUiWxqLq4ePEiAP/cpxgdO3ZEeHg4jEYjzp4969Z1krUDyyjkj8VadQktDW0MurvfkpIS/P3333jllVcAAG+//TZatWrl9L3KWuBkZ2dj0aJFFcSbd955B5cvX0ajRo3w448/olWrVmjatClatmyJqKgo5ObmIjc3FzabrcG0DUEQBEEQtQMFMW7AeHJ74GfP4B/Df5l2Z9XhusjzlHGHuVJduXIFSqUSer3eKauLRCLBkiVLMGDAAGzYsAFTpkxB9+7dPd6HVCrl/q/RaDB48GCsWrUKK1aswOXLlzFnzhysXr0aU6ZMwT333MMtxDyxf/9+r39ndOjQQdBx7N6++OILrFixAgCwaNEiPPTQQ07HseDDrmi1WowZMwYZGRlITEzEV199hbi4OJhMJkREROD69etOu8/MDQcoTzF+5coVLgW6O+unlJQUt+3tiqd+0dDxVS/+ZKMxmUxc2mGFQoHCwkIA5VYm77zzDiZMmIDVq1fj559/xokTJzBhwgS0bdsWzz33HMaMGYPQ0NAK52RZcXyRmJiIO++8E++++y727t2LpUuXYvv27Vi5ciW0Wi3ef/99hIeHIyYmRtD5cnNzBR3Hsqn5IiwszOl3Fv+mTZs2Tn/zFTuL0adPH/z00084cuQI7rjjDq/HsvbQ6XSCUkN7S/stVAzz1ZdqywW0unBXL/z7dTgcUCqV+PfffzF79mxYLBYMGDAAw4cPx/Xr17nvWK1WpKWlAQBuuukmNGrUyOt177jjDpSWlmLRokV44403UFpaioSEBPzyyy+c25Rer0dMTAzmz5+P+Ph4SKVSSKVSREREcH1CLBZDJpPR/EgQBEEQRLVCFjhEBZRKJZdq2vVzTy453mC70ezHaDSioKAA0dHRkMlkbmO/9OvXD4888ggAYPr06X5Z0ERGRuK5557DsWPHMGfOHERFReHixYuYOXMm+vfvj6+//hpWq9Wve6gq27dvx/PPPw8AmDFjRgXxxhN5eXkYMmQIzp49i7i4OCxdupQTbwBw92EymZCXlwcAXIBooNxaoLS0FNeuXePEAVc8tXdlj2to+KoX9nchAbK1Wq1T3CjmxsNSZicnJ+PRRx/FypUr8eSTTyIyMhJnzpzBo48+itatW2PJkiW4cuVKle5HJBKhT58+2LRpE95++22EhoZi8+bN6Nu3L06ePFmlcwcS5kLlan0hlH79+gEADh48COA/Fxiz2ex0HD8Yuyc3UFcqO1f6oqGNQebqyepbr9dj7dq1uHz5MqKiovDOO+9UEEsuXryI0tJSKJVKn+INAJw8eRJ9+/bFq6++itLSUgwbNgwHDx50inmTlJSE+fPnIyIiosIcyto6Pj6ec4MkCIIgCIKoLkjAIQRT2cUD243W6/UoKyvjTM3lcjlSU1OdrG8YJpMJM2fOREREBI4ePYo1a9b4Xd7w8HDMnDkTR48exbx58xATE4PMzEw899xz6NevH7744gtYLBa/z+svR44cwRNPPAG73Y7Ro0fj2WefFfS9wsJC3HnnnThx4gTi4+OxZs0apKamQiKRcAuaiIgIlJSUwGazcQtPk8nECQBxcXFISEhA06ZNIZVKKT5DkOHL1YafrQ0od0uUSqXQaDSYPn06Ll++jBkzZnB9e9asWdBoNOjbty+WL19eJTFHJBJh8uTJ+OWXX5CYmIiLFy9iwIAB+PHHHyt9zkBRXFyMS5cuASgPzFwZWByc/fv3c1mNPAVZZ5/zYxV5gy88NLS4NdXJX3/9hR9++AEA8NZbb7nNMMWsb1q2bOnVEqasrAxr165Fjx49cPToUURFRWHt2rX45ptvUFpa6hTz5ttvv8UNN9yAmJiYCu3oKjIRBEEQBEFUJyTgENUO26GMjY3ldq/z8vJw4cIF6HQ6t98xGo2IjIzEzJkzAQDz5s3jLEz8Ra1W46mnnsK+ffvw0ksvIS4uDleuXMGLL76IQYMG4ezZs5W+N19kZGRg7NixMJvNGDhwIN5++21B5vUFBQUYNmwYDh8+jNjYWPzwww/o2rUrEhMTuQU9C3bbuHFjzkKJpT1mv6empqJLly7QaDSCLAeImsU1xkd8fLxT3ChXYmNj0b17d7Rt2xYAcPXqVUyYMAHbt2/H22+/jV69egEA9u3bh+nTp0Oj0WDAgAF47733Ki3m3Hzzzdi7dy8GDx6MkpISvPbaa1iwYIGgTG/VxSuvvAKLxYLk5GQkJiZW6hydOnVCeHg4ioqKcOzYMafU4XwrHCFWN8xKx51I09Di1lQXxcXFePXVV2G323Hfffd5dHtjAo632EgXL17E448/jlWrVqG0tBRDhw7FkSNH8MADDyA7O5sTbxo3boz3338fTZs2RXx8PCIiItxuOBAEQRAEQdQUJOAQ1Q7boWQ/ycnJkEgkUKlUyMzMdLvwYaLPI488gjZt2iA3NxezZs2qUjBVhUKBiRMnYt++fVwsg4yMDNx99934/vvvq3iXFTl16hQmTZqEvLw8dOzYER9//LHbGCXuGDduHP766y9ERkZi27Zt6Ny5Mxd7RK/XQ6/Xw2QyQaFQIDo6movLwD7jW+kAEGw5QNQsrq42rhY37mDHsHTKZrMZiYmJmDx5Mnbv3o2MjAwsWbKEE3P279+PWbNmoUWLFnjttdcqNYZiYmKwadMmvPzyyxCLxfjhhx/wxBNPoKCgoFL3XRmuXLmCNWvWYPTo0di6dSskEgkWLVrkdwYqhkQiQZ8+fQAAf/75J5c63GazISsrixNx3I0dvlsV8J+VjicXxepwp2povPDCC8jMzERiYiLmz5/v8bgzZ84AANLT03H69OkK/f3nn3/Go48+ijNnzkCtVuPTTz/Fxo0b0bhxY5w7dw6DBw/mAha//vrriI+PBwDccMMN6NatGwk4BEEQBEHUKiTgEDWOQqFA69atERERAYVC4Xbhw4SJ0NBQLFiwAGKxGOvXr8dbb71V5euHhYVh/Pjx2L59O3r06AGj0YinnnoKs2bNCoibg8PhwPr16zFu3Dhcu3YNzZs3x7p16/xawP3zzz8AgI8//hidOnXiPmfWNXl5eZzbB1AeC8dVtCGCH1f3C+b+JqQfMncquVzu5PqTmJiIp556Crt378aZM2fw/PPPo0uXLnA4HFiwYAGeeOIJwYF++YjFYjz77LNYvnw5F3tnypQpgoMV+4vD4cDFixfx8ccfY8yYMejfvz8WLlzIjY1nn30WnTt3rvI1AHBCmMlkQmFhoU93Q1d3K37KcVfIxabqnDt3Dh9//DEA4J133kF4eLjHY9u0aQOg3HX1sccew6OPPoqtW7fCZDJh7dq1eO2111BaWooePXpg3bp1GDNmDEQiEfbv34/+/fsjPT0diYmJ+Pjjj9G+fXsuExlBEARBEEQwQAIOUa24xn9gvyuVSiQnJ0Mul8NisXgUN+RyOXr16oUFCxYAKHedeO+99wJStujoaHz55Zd4+umnIRKJsGHDBgwdOhQZGRmVPmdxcTFmzZqFRYsWoaysDLfccgt+/vlnv3dt2a5vWVlZhaCqLDMR+xcAGjVqBLlcDpPJxMUYopgbdQ93Kcc9iTqxsbFo27atV/e4Vq1aYfbs2fjxxx85IfSzzz7DPffcg/z8/EqV8aabbsKKFSsQGxuLixcvYvLkydBqtZU6lyulpaU4duwYli9fjnvuuQf33nsvPvzwQ6SlpUEsFuPmm2/Giy++iJ07d2LChAlVulZZWRn27t0LAOjcuTP0ej0MBgPkcjnUarVPKyjmbsWyJLExXptpxusrLDtU//790bt3b6/Hvvjii/j+++9x2223QSqV4uzZs3jzzTdxxx13YNWqVQCABx98EIsWLeLabPPmzRgyZAjy8vLQvn17fPTRR4iKikKTJk24uDfUVgRBEARBBAOURpyoVrRaLQwGA1QqFZeumm9xI5PJPC4+zWYzzGYz5HI5xo0bh/T0dKxatYoLAvzkk09WuXwhISGYOXMmevTogaeffhoXLlzA3Llz8dBDD2Hw4MGC08Ha7XYcOXIEr7zyCq5cucKd9/777xecxplPQkICTp48ievXrzuJX2azGRERESgsLOTOy08bbjAYUFhYiOjoaKfrGo1Gzr2KiWXsM0/p3omah6VNBspd5VjbMlGHb6nDfmc/DP7fAHBj6NFHH0VsbCymT5+O3377Dd27d8c333zjZOEllGbNmmHFihWYNm0aMjIyMGrUKKSmpqJdu3bcjxDXppKSEhw8eBBHjhzB0aNHcfz4cafA4qGhoejevTsGDBiAO+64Q3AKcyEcO3YMRUVFFbIVyeVyt9dxHUOuwY3ZMfz5jYk7rvObtzTjDR2+KAaUu6J+8803AMrFGV+IRCJ069YN8+bNw9NPP41t27Zh8+bNuHLlCsRiMaZPn46RI0dyxy9fvhzPP/88HA4HBgwYgFWrViEvLw8lJSWceG6z2aitCIIgCIIICkjAIWoUtkDlL3g8iQdms5mzQJHL5Xj22Wdhs9mwevXqgIo4ANCzZ0/88ssvmDlzJv788098+umnOHHiBJ544gmoVCq337l69SoOHDiAgwcP4tChQ1w8kKZNm+Ktt95Cu3btKl0eZoFz/fp1AEB2djakUikkEgkkEgmio6MBwGkBbzKZuONcrXbcLTb5cTtIwAkOFAoF5HI5l7GNCQZ8QQaAW1HH9W86nQ5ms5mLuySXyzFs2DCkpqbi4YcfRnp6Ovr164fly5fjkUce8busSUlJWLFiBZ555hmkp6fjyJEjOHLkCPf3mJgYtGnTBm3atEHbtm3RsmVL2Gw2nD59GidPnsTJkydx/vx5LuA2IzIyEjfffDMGDhyIXr16cePP0zisLLt37wYAdOzYESqVyin2UG5uLtcWQPk8lZmZCZlMBgCcKONa//z5zZtI4zoPEv/Brzej0YjFixejpKQE3bt3x8CBA5GTkyP4XJGRkRgzZgweeOAB/PvvvwgLC0NqaiqAclHmvffew4YNGwAAI0eOxMKFCxEbG4uCggKEhYUB+E8gp7YiCIIgCCIYIAGHqFZY2nG2Y+26I+1tR1Mul3PijVwuR1JSEp555hmIRCJ88sknnIjz6KOPBqSsMTExWLNmDebOnYv169fj77//xqVLl/DUU0+hTZs2MJlMOHXqFE6cOIHjx4/j2rVrTt9XKpUYNGgQZs6cCbVaXaWysPS4ly9fhtlshlQqhdVqRWJiYoWFPLPUUCgUSExM5EQc/qLD3WKTb7mj1WrJEieI4LcN39LG9e+exg8TE2UyGQoKCiCRSDjLkpiYGBw8eBDjxo3DL7/8gscffxwHDx7Em2++yS1ahdK4cWOsX78e6enpOHXqFE6ePIlTp07h0qVLyM3Nxf79+7F//34A5TF0HA5HhaCyCQkJ6Nq1Kzp37owuXbqgWbNmgi3fqsKuXbsAAIMHD0ZSUhI3z+Tm5kKr1aKoqAgtW7ZEfHw8TCYTZDIZLBYLNzbdjRfXdvIk0rgeR/xneQOAiyeUnZ3Npa1/8cUXK90vxGKxU7wki8WC+fPnY+fOnQCAp556Cs899xyUSiXkcjmaNGmC/Px8rk/I5XJIpdKq3SBBEARBEEQAIAGHCBjuXq75ixytVut2R9qdsGMymbhFqFqthlQqhdFohFgsxsMPPwyJRIKVK1f6ZYkjdAd/+fLlePTRRzFhwgRcunQJr776Kjp06IDjx487WQtIJBJ07doVAwYMQP/+/dG1a1e3WaaEZsnhL2yZBc61a9fgcDi4sptMJojFYq6eSkpKYLfbUVJSArFYjJKSEi4FtatlANv11+l0nBuIUqmETqcLqDtHTSy+6yL+1Itr27haAPCtqICKQmhkZCSsViuXkYwJgCz4a1xcHH744QfMnz8fr7/+OlavXo1jx47h66+/RnJysteyubMs69ChA4YNG8b9bjAYcPjwYRw+fBj//PMPDh8+zKUxb9GiBXr27Mn9JCUlCaobodmzQkJ8P9b48W969uzJCaFAeV0WFRVBIpEgNzeXE6EBcK5WLI6Xr3mMEN5uBQUFMBqNsFqtiIqKQkFBAT7//HMYjUZ07NgRt9xyCywWi+C6vemmm9x+rtfrMWLECPz111+QSqV48sknMX78eERGRnLtHBISgqioKISEhHBWVwRBEARBEMFAgxZwHA4HLTZrEE9uA+5cDYxGI4qLiwH8tzhlLgwxMTF46aWXAMBvEUconTp1ws6dOzFz5kxs3LgRR48eBQC0bNkS/fv3x4ABA9CrV69KxbcRAtvlLyws5DJy5eXlVXCb4Vti6HQ6ZGVlobS0FO3bt3e78+/OlYrcOYIXd23DhAKTyeSUOp4f7Jifjtw1Jg5DLBbj+eefx4033ogpU6bg8OHD+N///ocvvvgCgwcPrlK5VSoVevXqxaUyB8rFSLFYzImTjMqkNa8q//77L4qKiqBWq5Gamorc3FzY7XYA5WOqZcuWyM3N5WLh8C1mdDodioqKoNPpkJKS4jRn8ecxinPjHwqFAvn5+ZBKpcjJyYFWq8XatWsBAM8//3xAntUXL17EXXfdhfPnzyMyMhITJkzA/fffj6ioKKdxRnMiQRAEQRDBSoMWcFxfCO12O8RiSsxVXTCrAtcFm7uXZaVSybkhsUUoc2FgFiYs8GSgAxsz1Go1Vq5cidGjR+PatWvo3bs3kpKSAnZ+b7BFLj+WDXMpc3Wl4f9eWFiIkJAQ6PV6p8xXbMEPoELQaHLnCC5cLTk8BcAFnNvSZDLBYDAAcG5Tb+1rMpnQp08ffPPNN3jmmWdw6tQpDB06FC+//DJeeOGFgM6H/EDBtQ2Lf9OrVy8uFXteXh7kcjlXX2yecYVZRslkMidxxnUeIxHAP+RyOZo2bQqTyYSioiJ8/vnnKCwsRNu2bTF8+PAqn/+vv/7CyJEjodPpEB8fj0mTJqFDhw5uU8CTOylBEARBEMFKgxVwDh06hL179+LKlStcbBWxWEwiTi3gboGpUCjcunIkJCQ4xXV56qmn4HA48PHHH/st4tjtdohEIq87uyKRCAMGDBB6KwGDWeBotVqYTCanWAxWq9Up7g0jLi4OLVq0gNlsrrD4ZJY3ISEhblOak/tH8ODLcoMJA+Hh4RWEOLFYXCGAtSuuGaz0ej1atmyJP/74A3PnzsUnn3yC+fPn4++//8aaNWsQFRUV8Husbfbs2QMAGDhwIGJjY6HX6yGTySCRSCq4RZnN5gpxu1hGPf4i312cIhpLnnE357A57uTJk9i2bRsA4Lnnnqv0M9lgMGDTpk1Yu3Yt9u3bBwBo06YNtm7dyrm78l3kCIIgCIIggp0GKeCsW7cOc+bMgdlsRm5uLgDgxx9/xO+//84F2iTXquDC3Y6oUqlEcnIynnrqKYSGhuLDDz/Es88+i9LSUsyYMQNAeaaRrKwsXLhwARcvXsTFixe5/1++fBlNmzbFwoULcc899wRVmzMLnIKCAuTn58NsNiMxMRFyudxjBiKFQgGNRuMxuG1OTg5nYeDJjY0fzJgWn7WDL8sNJgwwSza+IBMbG8v1jczMTABwyq7Eji8uLkZWVhbnIiSVSuFwOPDhhx+ie/fumDZtGrZt24YePXpgw4YN6NChQzXfdc1x7do1Lv5Nv379AHgOCm0ymdymkCZxpmqYTCakp6dzGyYpKSncXBcWFoYJEyaguLgYnTt3xn333ef3+R0OB9avX4+nn36ai6UmFovRp08frF692mlzQEjMJIIgCIIgiGChwZmafPPNN5gwYQKmT5+OP/74A1lZWRg2bBj+/PNPLq5KMC3k6ysmkwk6nY5z66ksSqUSiYmJePHFFzFr1iwAwJw5czBw4EB07NgRUVFRaNu2LYYOHYqnn34ay5cvx7Zt23D27FlYrVZcvnwZo0ePxu233460tLRA3FpASEhIQNOmTWG327Fx40bIZDLOsoKZ/LvGPQGcY9y4IpVKYbPZ3P5NqVRyCxlm/eEPgWpPorx94+LiuPb1Va+ugh5rR4PBAIPBUOG7CoUCFosFNpuNc7myWq2cEPTwww9j9+7daNasGS5duoS+ffti48aN1XfDNUhRURHuueceFBcXo3nz5mjdujUAOMUM4uPOvaa6qK9jyN19GY1GLkMac0XLz8+H1WrF9u3bceXKFcTHx2PLli1+CywFBQV47LHH8Mgjj6CgoACJiYmYMGECfvjhB6xZswbJyckwmUzIzc2td3VNEARBEET9p0FtPel0Onz44YeYOHEiJk2aBLlcDgD45JNP0K5dO5w4caLS57ZYLLBYLNzvRUVFVS5vfYbvJsJ+r6zVBzO7X7BgAdRqNebNm8elLgaA0NBQJCUloVmzZrjxxhvRsmVLtGjRApGRkfj888+xZs0a7Ny5E926dcOUKVMwY8aMagtOLBSxWIynn34azz33HL766itMmzaN6698XBfvniwJFAqFU2pzfiYq9nf2O2sTd5l2PMFvz6osdmkcOaPVamEwGKBSqZCSkuL2GH6b892icnNzOYsr1+M1Gg2XdSk2NhYmkwlWqxW5ublc8N4///wTjz/+OH777Tc8+OCDOHLkCBYsWFDdt1xtWK1WPPDAAzh27Bji4+PxxRdfwGKxQK1WV3ArYygUCqfsddXpahjIoMfBNI7czfUAEB4ejvDwcBiNRhiNRi6FPXsODxgwwK27pzd27tyJqVOnIicnBxKJBJMnT8bs2bM5EYjNobm5udy4YpnZCIIgCIIg6gINygLHaDTixIkTaNWqFfcix4LidunSBWlpaSgqKnJKFS2UN954AxEREdxPTQW7raswiw8mGFTG6sMdzz//PLZt24Y333wTn332Gfbt24e9e/fiq6++wltvvYX58+fj8ccfR8+ePREeHo6ZM2di165duOuuu1BWVobly5fj5ptvxldffcVlpaktJkyYgJiYGGRmZuLHH3/kPtfpdNBqtZwIw7fG4S9CWcpwtuDkZyXyZKXDrD8A/yxx+O1ZFWgc+Ycn4QEAGjdu7NaqhMG3OlEoFLBarcjPz4der+cW1Fu3bsXMmTMBAO+++y6GDRuGvLy8ar+vQGO32zFx4kTs2LEDSqUSK1euRIsWLZwCQHuyTuMTyLnKlUCNISC4xpG7uZ59bjQaOTGloKAAYWFhOH78OACgd+/egq9hNpvxwgsvYMSIEcjJyYFGo8GyZcvwwAMPcJaLMTEx5PZGEARBEESdp0EJOFeuXEFBQQGsVisXP0ImkwEoT3sbEhKC8PBwSCQSv8/9wgsvoLCwkPvJysoKaNnrG3w3kUAuXIDyFOAjRoxAu3btEBERAaVSCYlEgoiICO5l3mw2c1mt2rZti02bNmHr1q1o0aIFtFotpkyZgttvvx3Hjh0LSJkqg0qlwrRp0wAAy5Yt8yi4eBJmvP3O4kJ4wt824bdnVaBx5Ex8fDwSEhIqpN5meBLj+MKeO/R6PbRaLWeFw0SciIgISCQSKJVKyOVySCQSvPHGG1i3bh0UCgV+++039OvXDydPngzsjVYzL7zwAjZs2ICQkBCsWrUK/fr1cxK3FAoFN+8zl0RX90QgsCKLK4EaQ0BwjSN3cz0ApKenQ6vVwm63o6CgADabDYWFhTh8+DAA4QLOiRMnMHDgQKxcuRIAMHz4cKxcuRI333wzpFIprFZrBevFmJgYxMfHczGgCIIgCIIg6goNSsBJTU3FHXfcgYiICE7AYf+WlJQgLCwMdrvdKc21w+GokPbaHTKZjDMJZz+EMIQuXPgWJXzMZjPy8vI4cUYul3OWVCUlJbDZbCgoKIDFYuHSBV+5cgUWi4ULDGw2m9GuXTts2rQJM2fOhEqlwt9//42BAwfimWee4Ra6Nc3kyZOhUqlw5swZ/P777wDKs03Fx8dXcC9wXbR7+z0yMtLrdQO5mPQHGkfO+GoHT0KNp5gunmCChVgsRsuWLZGUlOT03VGjRnFxcS5fvoyBAwfi22+/rfyN1RBWqxULFy7E8uXLAQCrVq3CiBEjYDKZcOzYMRw4cADHjh2DyWTiMrcxSxx+AGOGv/GJaotgHUd8Cz+W9SsuLg5t2rRBTEwMLl68yFnFtmnTxuu5LBYLFi5ciFtuuQVnz55FZGQknnvuOYwZMwZlZWWwWq2wWq1uLW8UCgVZ5BAEQRAEUSdpUDFwoqKi8MEHHyA8PJxLS1pWVobQ0FDk5OQgOTmZSyUuEolgNpuxZMkS9OvXD7169arl0hN8awP+DjizqGLWVezlvLi4GBKJBHl5eU5parOzs7n2ZzuzZrMZRqMREokE06ZNw9ChQ/HOO+/gp59+wmeffYavv/4aQ4YMwahRozB06FAolUrBrnZCXbH4MSsYCoUCEyZMwLJly7B06VIMHz4carXarQUA+4wtKFk2KbbQVCqViIuL4+J4AP/FuQmkRYEQwVPIMXUFofciNDi6P0HUlUolRCIRjEYjRCKR4AUpP26OSCSCyWSC3W5HYWEhRCKR23N17NgRBw4cwP3334+dO3fikUcewYkTJ7BgwQK3VotC+z2LfRIoxGIx8vLysGrVKnzwwQfIyckBAMybNw/33nsvQkNDUVhYiOLiYly9ehVNmjTh4v64xpBynWv4VDZmTUMLks+fJ1mMJUZSUhJnBaNWq7F69WoAQM+ePQG4H1uRkZE4cOAAHnvsMZw+fRoAcNNNN2HatGkQiUQoKChAaWkp4uLiIJfLIRKJKmVVSxAEQRAEEYw0KAsckUiE5ORkREVFcZ+FhITA4XDg+vXraNy4MYDyBUBJSQlmzZqFuXPnkpl1DeJtV9uT+wI/8w4TeGJjY5GQkACNRoPExETYbDZOrGGpuAFwljtyudxJyEhKSsLbb7+NX375BR06dIDFYsH333+PMWPGoFGjRhgzZgy2bNmCkpKS6qwOAMDUqVMhk8lw5MgR7Nu3z+uxLEV0ZmYmd4+ucTsqG+eGCE4qG5eFb4WlVCphtVpht9uh1+uRnZ3t5HrHMvZER0fju+++w9SpUwEA77zzDu66666giYtz7tw5TJs2DcnJyZg7dy5ycnLQpEkTLFy4EI8//jh3TzExMVCr1UhISKgwN8TExHCB0b1ZafDno2C2xgkmcnNzYbVakZOTUyHmkNlsxs6dOwF4dp8yGo2YPn06evXqhdOnT0OtVmPixIlYuHAhmjdvjsaNG6NJkyZo1aoVxGIxJBIJjEYjtQtBEARBEPWGBmWBY7fbOcsLBtsNLS0t5RbvRqMRzz77LD777DMcPnwYbdu2rfGyNlQ87WrrdDrodDq37iRMeGEv6izWAt8ipXnz5lzbKxQKJCcno7CwEGVlZZyAo1AouLgfJpMJCQkJaNu2LY4cOYITJ07gm2++wYYNG3Dp0iV88803+OabbxAeHo5hw4Zh1KhRuOWWWxAaGhrwOmnUqBHGjh2L1atX4+2330bXrl25vzFXj9jYWK5u9Ho9l5qX1VV+fn4FlytWZzWRItmV+rqgqs4sRZ6oTDt6+o7VauVESWYpkZ2dDalUyv0eExODpUuXomfPnpg4cSJ+++039O7dG7t37+bckGoSh8OBXbt2YenSpdi2bRv3eWpqKmbPno377rvPKVMbUJ55KyYmBrm5uSgrK+MEYLPZ7NQ3XbNQ8eEHjtbpdAHLIFXXYFmkhFjyyeVy5OTkoKioCA6HA1arFUB5vWdnZ+Pff/8FALcWrzt27MDUqVORnp4OABgxYgQeeOABhIeHo2XLllAoFJzrFHsGpKenIz09HSaTCTfccENgb5wg6jCZmZk+XcPT0tJqqDQEQRCEPzQYAYe9pDscDhw/fhwdO3YEUC7qMNcV9uI9c+ZMfP7559i7dy86d+5ca2VuiHhaWOp0OlgsFk7E8fRddwsI5hYhk8mcFmjMsorFwGFiTnx8vNMiTCQSoUOHDujQoQMWLFiAf/75hxNwrl69inXr1mHdunWIjo7G7bffjq5du6Jr167o2LFjwMSRp59+GmvXrsXOnTtx+PBhJCcnIzIyEtnZ2VCpVNDr9YiLi4NSqYRGo6ng+sG3OgOchQYScAJHIFNBC8VdBip/v6PVapGbm4uwsDCEhYVBKpUCKF9YS6VSFBYWoqCggOsrMTExGDVqFNq2bYt77rkH58+fx6hRo/DLL79w360MRqMR8+fPx8mTJxEVFYWYmBhERUUhOjqa+539PzIyEr///juWLVvGLfxFIhFuueUWDBs2DAMHDkRsbCzKyso81pE7l6mysjIUFhYiIiICJpPJo4DDpzbF0NqG3+fd3b/JZHISyePj4+FwOLgEAgaDAdeuXcOePXtgNpuhVqvRoUMH7vsFBQWYM2cO1q5dCwBITEzEypUr0bdvXxw7dowT7mNjY2EymRAeHu4k3gvJLkYQDYnMzEykpqYKGhcsnhpBEAQRPDQIAYeJN3a7HV27dkXfvn3x2muvITw8HA6Hg8u6cvz4cUyYMAHr16/H/v37SbypBTwttOLi4ryKN67WN3yYSFFaWoq8vDxIpVKEhIQgOjra6TgWBFmv17stB8tKk5CQgNmzZ2PWrFnYu3cvNm/ejF9++QV5eXlYv3491q9fD6DcFa9Nmzbo3LkzunTpgi5dulRa1ElJScEtt9yC7du347333sOHH36IkJAQJCYmOgVg5d8v/3fXxZWvRVd1U1+tFOriQp65SAHlfTYxMRHAf/Gh2Et+eHg4l9EnNzcXcrkcHTp0wNatW9GnTx/s2bMHgwcPxquvvop+/fr5VQaj0YjPPvsMS5cu5Sws/EEul2PkyJEYN24cmjdvDplMxmU2chVo2O/MTYqfoYgJOkzc9dZPXa2t6muf9oWvPs8Xx+VyOVQqFaxWKwoKClBcXAyZTIbS0lKcO3eOO9+BAwfQs2dPHD16FA888ACys7MBAA8++CAWLVqERo0aASgXc4qLiwHA7fyfnJzs9blBEA0Rll1v3bp1SE1N9XpsbGwsNBpNDZWMIAiCEEK9F3D44s3NN9+MvLw8LhAsAEgkEkgkEvTs2RNffvkllEoliTdBSFxcnNeXcBb7Ra/XQ6PROLnDsRd7tphjCwlmecMCmEZHRyMvL8/pPPxFGYtzkZ+fD7FYjJSUFHTr1g3dunXDvffei3PnzuHChQu4fv06jh49iqtXryItLQ1paWkVRJ2bbroJffv2Rb9+/ZCUlOT13u12OxYsWIDt27cDKF9I8+PYMDyJWO4Wl7UtNNTXxW5dXMgbjUZERkZCoVAgMTGxQvlzc3M599P27ds7LciBche/ZcuWYfLkydi/fz8GDRqEvn374vnnn0efPn28Xluv12P16tVYsWIFJyIlJCTg6aefRllZGXQ6Ha5duwatVguDwQCTyQSDwcAt/pl74ZAhQ6BWq7mAyBKJxEmEYeJrXl4eF/uHL9yw4LrMSkRovTVUtyk+vqz42DwLlIs5LK5QXl4e8vLykJCQgISEBCQmJkIkEuHatWsYPHgwunTpgrS0NO47jz/+OPr374+rV69yVrPZ2dlcBklm0cMvi6/nBkE0ZFJTU9GlS5faLka9R4grGgllBEH4Q70WcPjiTbdu3VBUVIS1a9eib9++XOwbtjDp2bMn/v33X3z99dfkK18H4cd+4bsPMZcIvV4Po9HIveSzmB45OTkoLS1FQUEBJ+rk5eVx53HduWcxG2QyGQoLCzm3js6dO6NRo0a4//77OUHm2rVrOHLkCPbs2YN///0XJ06cwPXr1zlR5/PPPwcANGvWDH379kWvXr3Qp08fNG3alLuvwsJCTJw4Eb/88gsA4N5778WkSZPc1oGnLF2e6qshLzqJ/2B9JSwszGOfCAsLg0ql4v7ORFAm5vzvf//Dt99+i88++wxbtmzB7t27sXv3bvTu3RsvvPBCBSHn4sWLeP/99/Hll19yMXc0Gg0mT56MUaNGcf0zOzsbly5dAlAuBDRu3JiznAsNDYXVaoVer0dJSQnEYjGUSqXb9Ols/BuNRpSUlKBly5bcfZhMJmRnZ0MikSA/Px8pKSkeXahcXQ/rmrVVbcDaMjc3F8XFxZxQl5ubC6PRiNzcXCgUCrRr1w5z587FgQMHsHv3bhw5cgRAefazKVOmQCqVcunCNRoNJBIJSktLYTQaER4eDovFgoSEhNq8VYIgCA72LBo7dqzPYxUKBdLS0kjEIQhCECJHfcrny8OdeLNq1Sr069fPbUpRs9mM4uJixMfHB+T6RUVFiIiIQGFhIcLDwwNyzvpCdXU5dxYo7DO9Xg+DwQCJRMIJJGwxxuLIiMVitGjRAiqVijsPWwjq9XouQCbDbrdz7ljeMpUZjUZuwZueno59+/bh+PHj+Pvvv3H8+PEK6cibN2+OPn364KabbsKyZctw/vx5hIWF4aWXXsLAgQOhVCqRkJAg2ALHF4FOayykfYuKihAZGelzfNSFcRToNOKBvq5QXPshwzWGibu/McsYoDyezscff4zNmzdz44UJOWFhYVi+fDm2bt3Klb9Dhw4YN24c7rrrLgDlgZQTExMhl8uRnZ0NvV6PoqIiJCcnQ6VSOY01vvsXs+xwDVTPjuNb4LBj8vLyEBERwZXT9R5dgxjrdDoUFRXBarUiOTm5UiJoIPuB0PFRm+OorKwMADihzGg0Ii0tDWFhYSgpKUHr1q2Rk5PDZX9s164dQkJCsGLFCkgkEjz88MNcZjSj0YiQkBA0adIEN954o1Pbx8bGVkpMa2hp3YmK1IVxFEiOHDmCrl274vDhw2SBU80IDRY9duzYOt8e9WV8EERdoF5a4Pgr3tjt9gqxEIj6AdspZ8EslUolt4PPFmtxcXE4deoUysrKcOXKFXTu3LnCwoy5YTD3JaB8oZqXl4fo6GiPi1xXl63U1FSkpqYiLy+Pc0M5c+YMfv/9d/z5559IS0vDpUuXcOnSJXz22WcAgPj4eLz++uvo1asX9Hq9k4jk7l4JIpB4s9Zif+PPnfHx8XjjjTcwbNgwbNq0CT/99BP27t2LO++80+m7/fr1w4QJE5CamgqRSASJRMIFTTaZTE4pvfnwXZ18WZLxY95oNBou0C0TdAoKCgAArVu3FjT/K5VK6PV6SKXSBu865S/MRe/vv/9GaWkpSkpKEBcXx6Wgl8vlaNGiBVq0aIG8vDyMHTuWC6pdWFgIlUqFsLAwREZGIikpCcnJyVx7+itaEwRB1AQajYasagiCCDj1UsAJCQmBzWZD586dYbVavYo3ANzu2BJ1D28uRLGxsbDb7QDgtGBgYk6jRo2Ql5fHxdBwxdNCMTw8HCaTiQuOzI5luAbwNJvNXDwIq9UKiUSCvn374rbbbsP169eRkZGBY8eO4dixYzh69CgaN26MWbNmISYmhgvWGRkZCZPJhIyMDO7eaPFCBAIhQqSnbE7Af65VMTExkEgkuPHGG/HUU0/h448/xqZNm+BwODBkyBBMmDABUVFRUKlUyMnJQXR0NMxmMxeUm52PH6uKCS9SqRRms9ltOUwmE0pKSrjxys9CxBd8mFVPWFgYoqOjOfGGXcdVlOLfZ3JyMrlO+QmzvsnJyYFOp0NERAQUCgWkUim0Wi3i4+PRqFEjREVFIS8vj7PIAYDo6GgUFBQgLi4OpaWliIyM5IK2++M2ShAEQRAEUR+olwIOABw9ehRZWVnYtGmTV/GGqHmqy5VEqVRCq9XCYrFwmWEYSqUSKpUKZWVlyM3NRVRUFCwWC2fmmZKSwqXhFolEFTLMuIO5WpWVlUEmk8FisUClUjn1NXaMUqnk0jE7HA6EhIRArVZzblkRERHcbvPAgQMxdOhQyFp38EIAAQAASURBVGQyhISEcBm4rl27xqW9l8vl0Gq1KCkpgcPhqNLixdUVx9O9C203IcfVJ7eFunYvntpXIpGgpKQENpsNJSUlXKB3AB4/5+N6TFJSEifkzJ8/H8899xwUCgVCQkKQlZWF0NBQFBcXIzY2FqWlpYiNjYVKpXKbtrukpAR2ux0ikQhSqRRKpRIhIRUfXxaLBTabDWazGSqVirO+c3WtEolESE5OhtVqhVKpRF5eHpRKJcxms9P3PdWbu8C4da0fVBX+vOFtviwpKUF2djYyMzNx7do1yGQyREREoGnTprh06RLCwsLgcDjQrFkzLjA0UO4SGhUVhaioKKSmpiI9PR1GoxGlpaXQ6XQV4hA1tPonCIIgCKJhUm8FnG7duuHSpUsIDw8n8aaBwMzoPWWGYS/7CoUC+fn5ToswVwsbfzLMsJ1+d6mK3Zn2FxQUcFYzrjv5TZs2RUhISIW/KZVKqNVqqNVqLk5Tbm6uR4sh1wWVEEGqMvdOBC+e2txb+3oKzOtNHPX2XRY43GKxoGXLllAoFNDpdGjSpAksFgs3Br25QrHx5HA4EB8fz/Vnlm6cfcYvA1Aer8ZdtjZ2Pf7xrD7c3QOrR3YvNC4qwq9DoNy9FChvG5PJBJlMBpVKhaZNm0IulyMsLAw2m41LB65QKGA0GqHT6TgrLtZHmFiTkpICrVbLBas3Go2Ij48nyxuCIAiCIBoU9VbAAYCoqKjaLgJRw3jLDMNfJLJsVK6wxRoATkjxBLO+CQkJgUKh4Ez5WUpztVrt1veZpTF2XbTyy+76N4VCgZSUFKfzpKamerxX10U6+12r1XI7154WoZRdp37gSagROkYY/DHhTcDwlK6e/csXTfifMUsOV+GTf30WLJx9bjQauaDJ/HOz7+p0OsGuNd7GHb8eAd9zQkOFL5ylp6fDYDBw4jWrz4SEBK7u+McA5f1Kp9PBbrdzc3N+fj73N6PRiLi4OKSkpCA+Pp7mJ4IgCIIgGiz1WsAhGh5C0mN7W8CyxRpzXfJ1LVfLG/aZv9f2x0KGf32hIgz73WKx+LSuoRTj9QNPfc3f9q2KgOHuWp6uz49nwn7nx7LhX5e5RLL/u7suf2x6uhYTBrzVB6tHFreFqAhfOJPJZE4ubPz5EQDngsbqlbmFxsXFcSIQAM5yy7XPUbB2giAIgiAaMiTgEA0OocKHL1HFnZUM+9dV2PG2ww9U3m3JUxndlY3tiNPudcMgUEKcvwJGZcRIwHnc8MWc2NhYKBQKmM1mzp2Gb5FmMpmcPvfnWkLGAQmawmH16ZpC1l2wYaPRyLlLaTQap5g2DBLNCIIgCIIgnCEBhyB48Hf8MzIy3GaWEgJzkzKZTMjMzOTcAvx1W/K1GPZX+PHmIuPvgptoGPjbZyorRrJj9Xo9J+TwhQBP53X3ua/sRP5YcdD4cI+7enF1YWMumwA4Fzij0YjMzEwYDAbI5XLu7zqdjoszJMQCkiAIgiAIoiFC+bMJwg1GoxFSqZTLUiMUFsfDarVyQhBzBfB2HhZs1dtimJ1fp9M5uSNUNS6H6zUIwhfe+ow/fdJkMnGCDfvdYDDAbre7jRHl7rzuPlcoFBVi5jCBIJD32pDxVC9M2LFYLADAud8xtynWDlarFSqVysniCqA4QwRBEARBEN4gCxyCcIO74KvucA286i7gKgA0atSoUpYvrpY5rtYG/Ov660bi6RoEIQSWTc0Vf1yOjEYjiouLodfrodFooFAouNg2QmPneAqe7JpJqqyszMm6R2h/p/HhHk/1otVqYTAYoFKpEB8fz2Uv49e5w+FAWFgYJ+oA5W1ELlMEQRAEQRDeIQGHIFzwx2WC76rBF1P4LgUikYjbpfbl+uGKOysEd4sm191wf1w+KMYHIRR+Sm3mJlgVlEollxaaxbtxl7ktEBQUFAAApFIpTCYTNy59jRMaH+4RIh6z3/kZw+Li4mA2m7k2Z2Kbp3mSIAiCIAiC+A8ScAjCBX9ieLgTbITGBOEH7BRqPeNpMckXdiobg4QgfBHolNoKhQIajcZrxig+VYlHExkZCavV6hSLhcZJ1XGtx/j4eKe4Nmaz2el4pVLpts2pPQii6mRmZkKv13s9Ji0trYZKQxAEQVQHJOAQQYvD4RB0nEgkCuj5hLpMiEQiQcFQfaVzZgE/q7JwcRV2/HH5CHT91fS5Giq10W7VkVLbn4DClV3kuys33wKnJgn0vObvtX1d39/rus5vrvMaC1TsKxU4/zzVce8EUd/JzMxEamoqF1PMGwqFwq0LLEEQBBH8kIBDEC7wA5/yf6+u8wU6xga5fBDVRW33Lf5Y8ccax125hdwLZaDyjTerQK1Wy/3fVwwwf4Q8giAqwmJ8rVu3DqmpqV6PrU53VYIgCKJ6IQGHINwQaHN+b+fztpAUuoCkhSYRTPjqj5Xtr/yxEgjLNV+QW493XNvRnSjjqf6obgmiekhNTUWXLl1quxgEQRBENUECDkH8P/zFB9s9Zum/3e0es93l+Ph4nwuQylrZCF3kaLVaFBcXQ61WIyUlxa9rEESg8RVUOxCLd19jKlDiZ35+PuLi4ip17vqMyWRCRkYGpFIpALiNK8RvI51OB51Ox32frG4IgiAIgiD8R1zbBSCIYMHd4kMmk3GLUNdjDQYDDAaD27+7olAouEUgW8jodDqfvupKpTIgwWIZLGOMEB/5unAdwjtGo7Fa28FTO/P7rauY4/r3ypwf+G9MeRJQ3F3X3Xm9HQcAUVFRfp27rsLqxNN8p9Vqnf5mNBohlUphtVqd2vHq1atO6dpZG+l0OlgsFly4cAEWiwUmk8lr+xEEQRAEQRAVIQscgvh/XHf0ve3wK5VKqFQq7nehWaTYwq+goACRkZE+LRCExhxhmV98LYirw23BnTUCuUcEB67tEGjLEU/t7CuottB+XZV+5G38arVaGAwGqFQqxMfHex3n7v4W6LhVwYDRaERRURF0Oh1SUlKc7o3fDvz5kf3LbxuZTAabzQatVsvNSUzI0el0aNmyJQBUsGoiCIJoyAjJDkaxiwiCAEjAIeoQ1e224Lqo9LbIVCgUnKsSPxYHUNFdhA9b+LHsDzUduLg6Fp7uFtn1cYFbF3Fth0ALa0LauSqBj/3pR67zg9Dr+hrn7v4WiGDOweaGxdycmNWha9YoISIcX9g2m82cSJaSkoK4uDifoo3RaHRyYyUIgqjvxMbGQqFQYOzYsT6PVSgUSEtLIxGHIBo4JOAQdYZgtergL268lTEYFmzVkUVI6OKOqHlc+1pdy3jmz/n9mR+USiXMZnOtigTBNp8xUdqTxZG3uuLPbUzYTk9Ph8Fg8KsM7ix9CIIg6jMajQZpaWnQ6/Vej0tLS8PYsWOh1+tJwCGIBg4JOESdIVitOny5i/A/D6YFW6AgsabuUJ/byt/5ITIysnoL5INgnM9Y7C9/cTe3CXXr5BOMdUIQBFHdaDQaEmUIghAMCThEnaG2Fp/+WM54K2N9WpwEgzUREXjqcrv6Mz8EKoNVVQgWMS0Q9xqouY1cpwiCIAiCILxDAg5B+MDd7nJlFj3+LtiqurASiUR+f0co3qyJhFy3OstGOONPXQtxYXE4HAG/rhC8XdffseJuLPLPURlruUDXi5DzCb0m/9qu13dt88rUM78+2TFGo5GLpxMMQhVBEARBEER9gNKIE3WSmkxT7S7lcU2kEQ7mVMWBTm9OBAd1tV0DMVZchYyq1kNNzlFVwZ97FVLP7BgAfqWKD8Z5jiAIgiAIItggCxyiTqLValFcXAy1Wo1mzZpV67U8Wc7k5+dXaypcZgkAeE5TXlsuL8Hi/kEElrriwuLa7/kuPJUdE/xzVKV/16QFSiDEIU9tzq9HANxc5EmUYcezYyIiIjzetydrp7rQ9wiCIAiCIGoTssAhiEoSFRVVredXKBScQORp1zuYrXQIorpw7fdsrCgUikqPCf45AlE2QJgFSlWoTusefj3y78lTHQk5xt2566rVF0EQBEEQRG1AAg5RJ4mPj0ejRo0QHx8fsHP64/JQk4sOb9eixQ/REAn2MZGfnw+lUhkQQcgb1Xlufj0KqVP+Mb7mUv6xTDijOYwgCIIgCMI35EJF1Emqw4XHn8ClNelC5O1a5MpENESCfUxUt3Ueo7rFIddAxUKP1+l0XufSYGgjgiAIgiCIuggJOATx/9SnNN81DT+mBdVf/acupxuvboJ5HjEajQgPD6/26wRzHRAEQdRl0tLSfB4TGxsLjUZTA6UhCKI2IAGHIP4fX6mFq2OhWtnzB9sCmgKRNiwqk2a7OvE1HqpzvLieO5itS4S4h3qqK38+D+Y6IAiCqIvExsZCoVBg7NixPo9VKBRIS0sjEYcg6ikNWsBxOBwQiUTcvwThSnUvVCt7/mBbQNOOe8Mi2Nrb13iozvESbGPRG0LK5+l+/P2cIAiCCBwajQZpaWnQ6/Vej0tLS8PYsWOh1+tJwCGIekqDFnBycnLQpEkTEnEIj1T3QrWy5w+2BTTtuDcsgq29fY2H6hwvwTYWvSGkjJ7ux9/PCYIgiMCi0WhIlCEIouEKOOvWrcP48ePx5ZdfYtSoUSTiBCGBbovKnK+6Y7rwz+9wOAR/rzYW0DQ2CCA4+4Gv8VCV8eLrfqtrjhBSz/62hcPh8DnPeLoffz8nCCJwZGZmCrK8IAiCIOo/DVLAsdvt+O6772Cz2fDMM8/AbrfjgQceIBGHIAiCIAiCCBoyMzORmpoqKIaVQqFAbGxsDZSKIAiCqC0apIAjFosRFxcHkUiERo0a4cknn4RYLK6SJY7FYoHFYuF+LyoqCnSxCaLeQ+OIIKoOjSOCqD/o9XqYTCasW7cOqampXo+l7EMEQRD1nwYn4DBxpm/fvti3bx/Gjx+PpUuXYvLkyRCJRLjvvvsqdd433ngD8+fPD3BpiYaC0WgMqqxStQWNI6ImCLYsboGmKuOIPxeRaxRBBA+pqano0qVLbReDIAiCqGUanIDDLGvi4+Nx9uxZ3HrrrWjTpg2mTp2KSZMmwW634/777wcAZGVlISkpSdB5X3jhBcyYMYP7vaioSPB3CaIqmVzq02KUxhEhlKr0+/qeOUnoOHJXh/y6IQGHIKoXim1DEARB+EuDE3AYN9xwA6Kjo3Hw4EE8/PDDeOONN/DCCy9g6tSpCAsLw9atW5Gbm4t169ZBpVL5PJ9MJoNMJquBkhP1kapkcqlPi1EaR4RQqtLv63vmJKHjyF0d1ve6IYhggWLbENWJEOGPXO4Iom7SYAWcpk2bIiYmBjt37sTDDz+Me++9F2FhYZg5cyYeeOABSCQS7N+/HyqVigIbE9VOVaxnaMFFNESq0u+DLQ16beGuDsl1iiCqjlDLGoptQwSa2NhYKBQKjB071uexCoUC3333HeLi4nyek/ofQQQPDVLAsdlskEgkaNWqFa5evcp9PnToULz11lu4dOkSpFIpzp07hw4dOpB4QwQ1tBglGiLU76sO1SFBBB5/LWv69OlDi2MiYGg0GqSlpfkUEHU6HUaMGIHbb7/d5zkVCgXS0tKonxJEkNAgBRyxWAwA6Nu3LxYuXAidToe4uDiMHj0aZ86cwUsvvYSvv/4ao0aNwnfffYe77767dgtMEARBEARB1DrHjh3z6lpPljVEbaPRaAT1KyFCT1paGsaOHYs9e/Z47c8Gg8HvchIEUTkalIBjt9shFos5i5rExESYTCaUlZVh3Lhx+P3337Fx40b0798fbdu2xdtvv+3z4esJh8MBgNK3EsJhfcYVk8kEk8nk9255MFuOsXHh6Z4ZNI4Ihq++Ull8ja/6Oo483Xcw3y9BVAf+jqN+/fr5PKdcLkenTp0EBeGn5xtRW0RGRiIyMtLrMTKZDHK5XJBLFlB9z2qCIP5D5GggI62srAwhISFwOBz4999/0alTJ1y5cgUdOnSATCaD1WrFxo0b0a9fP85Cp7i4GGq1ulLXy87Opuw5BOGDrKwsJCYmevw7jSOC8A2NI4KoOjSOCKLq+BpHBEFUnQYh4DDxxm63o2vXrujbty9ef/11iEQitG3bFjabDV999RW3q8IsdaqC3W7H1atXoVarK7WjydK+ZmVlITw8vEplqQnqWnmBulfm+lReh8OB4uJiNGnSxOtY82cc1ZX6oXIGjrpQRqD6ylkd46i6qSttVlUawn3Wl3sMxDiqq3VRV8sNUNlrC09lFzqOCIKoOvXehYov3tx8883Iy8vD8OHDIZPJEBoaim3btsFoNOKmm27ivhOIiUcsFgdEgQ4PD69Tk3tdKy9Q98pcX8obERHh87uVGUd1pX6onIGjLpQRqJ5yVtc4qm7qSptVlYZwn/XhHgM1jupqXdTVcgNU9trCXdmFjCOCIKpOvRZw+OJNt27dUFRUhLVr16Jv376QSCQAgPbt29dyKQmCIAiCIAiCIAiCILxTb23c3Ik3q1at4sSbBuA5RhAEQRAEQRAEQRBEPaFeCjiexJt+/fpxlje1HQfAFzKZDPPmzYNMJqvtogiirpUXqHtlpvIG1/UqC5UzcNSFMgJ1p5w1QUOpi4Zwnw3hHoVSV+uirpYboLLXFnW57ARRX6i3QYxtNhs6d+4Mq9WKDz/80Em8IQiCIAiCIAiCIAiCqEvU2xg4R48eRVZWFjZt2kTiDUEQBEEQBEEQBEEQdZp6a4EDAPn5+QgPDyfxhiAIgiAIgiAIgiCIOk29FnBqE7vdjqtXr0KtVgd9vB2CqGkcDgeKi4vRpEkTiMWeQ3HROCIIz9A4IoiqQ+OIIKoOjSOCqDpCx1G9daGqba5evYqkpKTaLgZBBDVZWVlITEz0+HcaRwThGxpHBFF1aBwRRNWhcUQQVcfXOCIBp5pQq9UAyhsgPDy8lktD1CeEGs3V1s6GkPJdv34dbdq04caJJ+rCOOLfr8lkgslkgkKhgEKhcDpOaHsEun2Dvb8QlaeoqAhJSUmCx1FmZqbPceRvv/LW5/05n1CoPxOBxt9xFMjnUU3N967jlMYlEWhqcxwRRH1B6DgiAaeaYA+p8PBwmqCIgBLsL0r+eGX6KmNdGEf8+/VWRhJwiOoikOPI334VqPMJhfozUV3UxvOopuZ71/LSuCSqi/rwXkcQtY2vceTZuYogCIIgCIIgCIIgCIIICkjAIQiCIAiCIAiCIAiCCHJIwCEIIuCYTCbodDqYTKbaLkqDxmg0UjsQgmBj1mg01nZRCKLBQs9OgiAIwhck4BAEEXCMRiPKyspoMVjLUDsQQqG+QhC1D41DgiAIwhck4BAEEXCUSiVCQkKgVCpruygNGmoHQijUVwii9qFxSBAEQfiCslARRD3BZDLBaDRCqVS6Tedbk3hKKUxUDX4bC3nBD4a+QNQNqiu9cE3i7/ggiGCjPjw7g+ldhCAIoj5CFjgEUU8g0+v6D7UxQXiGxgdB1D40DgmCIKoXssAhiCDB4XAIOs7TDrlSqeR2vUQikeDzBRohO/j+7vI7HA6f9yP0nFWt59qE38Z1+T6I2kEkEgWsPwR6vAXiupUZH4GGxhvhD4HuL7X1HOQf5/ouUhlqct4gCIKoa5CAQxD1BHIbqP/UB/N6gqgu+HNgbQk4BNHQoXcRgiCI6oVcqAiCIAiCIAiCIAiCIIIcEnAIgiAIgiAIgiAIgiCCHBJwCIIgCIIgCIIgCIIgghwScAiCIAiCIAiCIAiCIIIcEnAIooFgMpmg0+lgMplquyhEAKF2JeoD1I8Jovag8UcQBFF3oCxUBNEAMJlMSE9Ph0wmAwCPmYxMJhOX/rOhZjvi10FdyKRhNBpRVlYGo9HItVlduweiYeFunnHXj2u7TATRUNBqtSguLoZarUZKSkptF8crNFYJQhiZmZnQ6/U+j4uNjYVGo6mBEhGBggQcgggyquPlhL2cmUwmNG7c2ONxtb2ICgb4dRAo8cMfQcXf9lcqlRXKWh33QBCBwt08w+/HtbFA83fuo0UkUR9hljjB3K89jVUakwTxH5mZmUhNTRVkVadQKJCWlkYiTh2CBByCCDKqS0RRKBRQq9Vez+lODHBHbb8oVef1hdaBP/gjqPjb/gqFosJx1XEPBBEo3PVPfj/W6XTVJiR7mjv8HTMkdhP1ifj4eG4MBHu/ViqV0Gq1sFgsQWXFRxDBhF6vh8lkwrp165CamurxuLS0NIwdOxZ79uzxehxAljrBBAk4BFHNOBwOv473tZDw93zAfy9n7s7puqAR8uJT2y9KVbm+SCTy+ndWTw6Ho1J1zXC1umH/93VOhUIBk8lUpXrlt6PQe/BVL4yq1ElVrktUHSF9uib6ga95xtsc6Ou6vsRd17mD3a8v6zjX65JISgSCQM+nlYWNSdd+XV3l8zVOvc1DbKx6s+IjCKKc1NRUdOnSxePfY2NjoVAoMHbsWJ/nIkud4IEEHIIIMoSKKJU9p+uLU2XEkNp+Uart6wuBX69xcXF+1S27L6PRyIk5wXyvBFFZ3C3kqjIH+prPAjV3VMc8TRA1jbsNnJro11XdBPJlxUcQhDA0Gg3S0tJ8xsphljp6vZ4EnCCABByCaGC4vjhVZkHjTRCqCerCi1ogFoomkwllZWUwmUwBEXBq2/WNCG5qI/h1oK35fI27ujB3EA2TuhD7KVBU9fnIt5QlCKJqaDQaEmXqGCTgEEQdIhAveK4vTlVd0NS2O1WwEoiFYiDcqfjUZluReBT81ETwa9d+EGhrOhJoiLpKIObnQATBrwlonBIEQVQeEnAIopbx54UrEC94gbaeqQvuTNVJdQdU9lSvlblubbYVCX3BT030D9d+4M9CLphFwNqwXiLqF4EYf4EIgl9Zgml8BlNZCIIgAo24tgtAEA0d/guXL5RKJUJCQgS94LF0oN5SCPpzbU8oFAq/YrzUNwJRh67n0+l0Ps9XmevWZlv503eJ2kGhUHABz6uLqvQDd31eyDxXEwR6HiAaHoGYn2tznjUajSgqKkJGRgaNR4IgiGqEBByCqGX8eeHiuxz4ekHy9ALDX/AE6mUvWBZRtUGgRTV+3BtvYk5V2q422quhC30NFde+5s8c5oq7Pl8bCzV344cESiIYEDrP8vtwoJ4HSqUSVqsVUqm01oUTNh4BCNoQIQiCqEuQCxVB1DKuJsz+psF1hX0fgNsFhWt2JPYZK0tlqInYGcGKPyborm3nKQMPi3vjLYixkOt66ktVdWci83RCaB9w19cq2//cuX8C7ue5ypZXCO7Kz8omNA07QVSWQPRlV+HT3/Ho6dmVnJxc4T2gNhMd6HS6BvtuQhBE/YUscAgiyPC1o+y6s+S6g8a+D8DtThx/p9hkMiE9PR1FRUVV2qFSKpWwWCwwGo3VstMVrJY9/u5cuu7S+2prhUKBkJCQgL2keyqHv2i1Wly7dg1arbZS3yfqPkIs/AD3fS0Q1iqe5jk2p6WnpzuNS+be4fp5ZSBrG6I2YGNLq9VW2eqM34cr0589jX++BZC38gbK6sfXeWisEgRRHyELHIIIMoSkwQWA9PR0yGQy7nP+LpOvHTB2Dp1OB5lMBovFUqUXHOYWUV07XcEq4FQ1YKSntmJWN3FxcW4tqPR6PRwOB+Lj471e11NfogwgRFXx1LeEBCkW2v+87dx7u77BYOCOYd9TKpXQ6XSw2+1IT09HSkpKQALBE0RNwRctqypKuPZhb/3Z3TgUEnDZW3ldBaDKWuj4egaTZRxBEPUREnCIBoPD4RB0nNAHvdDzCYXFhFAoFIiNjfV4DZFIBKPRiLCwMFgsFqedZ08LJk8vOeyFSsiLk696qc4MNkJewALdHkKo6j17WtyytnR3TyaTCQaDAQ6Hw2e7+bPQZNcSYu7OAt3W5V3NQM8HDQ1P7c8fEyKRqErj0tvijI0Po9HIjQX2uVqthsPhqLBATU5ORmZmJmQyGXfOQM8bgT4f9b/gw+Fw+Gxnoe3mT/uysRUREeFx7q2O56DRaERxcTH0ej00Gk2FjSAh5WXHsvLxn3P8cS6Xy/0qm9BncG28HwA0fgmCqB5IwCGIIIFveeEaE4cvzgD/7ZYlJCQ4iTDuzuktTkQgd5Krc0Ff00KBUJ/96tiJ93ZO1hfEYjHkcnm11IsQqyKyQCA8Ech5wNfizF2MKG/XVyqV0Gg0XFBTZjlIMZ2IukBtieYKhQJ6vR4ymcxtPDZv3xP6DOHHfRNqYerrGgRBEPUVEnAIogYQskBwDV7rLpAt33yZLW50Oh23EAH+s+Rhfy8rK0NISAgXsDhQ5a1r+HNPVQ3yGwjcCXd6vR4GgwEqlQrJyclev8vi07hzw/JGdVpSEQ2bQM8r/DmTwbdk9GQh5Cr8VGa8B+Je6uM8S9QthCRNMJlMnFVwdYwP12dccXExAN+WwTU9fmi8EgQRLFAQY4KoAYSkumWuU+5EG0+BbPnHuX7GXjQq4ytfG6l5qxt/7ikYAh+6a1uhsDggBoPB7+/zg1ASRCDxd14REtDdVaAUMm5c59RABnH1h/o4zxJ1C199kI0nwL/NgMr2beYCqVKpfF6rpscPjVeCIIIFssAhiBrAX6sG/s4y+2GmxWxnmWV8ys3N5b7Hz/5QFfGhPlph+HNPgTTLdrdrV1mLLAAQi8UVTM/dBZhUqVTceQgiGPB3XvF1PLMOYPDnSk/9nlktms1myOVyiESiSo33QMyR9XGeJeoWQpImeBpPfGs3FpuPPYf87dt6vR56vR6xsbHQaDQwm82cUOJpbNb0+KHxShBEsEACDkFUA/zYM8B/O8VC4S8o2OJdr9fDbrdz7lMmkwkymQwlJSVQKpXQ6/XcDhl7wdDpdJVyBaqPfuW1dU8sfbFOp+My37CdPK1Wy7WXuyCtfLPysrIy5ObmcnEI+Od3bWOFQoGUlBRBZfPmbkIQgcTfMeguToZr7JqysjIUFBQgMjKSy9zGjgUqxs9iQcDz8vIQHR1daXcIoffiTazlC046nY5cM4gapyrPRVdrt6pkldLr9bBarZyIUx2x2Px1gXKXvZPGJ0EQwQC5UBFENcBePvgCihCYUOPOJcpsNgMAzGYzdDodAMBisSAsLAw2m4176WEBOoGquQKxRUWwpvCuSapSF0qlEhaLhct8wz4LCSnXz4X2j4KCAo/nZ+fyt4ysb+n1euh0Ou6H2pyoLUwmE9LT03H69Gmkp6e7FSvZZ8wVKjY2lnOJMhqNyMzMRHFxcYV+zKwWJRIJ4uLiBLlpVBUhbhfkmkHUFmy88cca/3nnzSWR74rIf9dw7c9Cnp8KhQIGg6FKbo2+CLQLJ0EQRG1BFjhEg6c6AtOxlxi2G8xeQrxdy2QycSluAWez4YKCAsTExDhZb7CXG5lMxgUpZoIRc6Gqyo5RMATyDRYqWxesvV37AWsXf0yyIyMj3e4Cst/9sbbiu56EhITAarWirKwM+fn5iIqKqnCO+hy8sT7fmzeC9b5Z/Kbc3FzExMRUcA3k9013WXl0Oh1kMhksFgsSEhKc/sasFplFJBN0AP9cDV3rzltdChnj5JpRtzCZTAgPD6/tYgQENt6A/4IGuz7vPLlQuY4/12Di/MQK7HwOh6NCcH723ebNm3ObEf5YpwmdywLtwkkQBFFbkIBDNHiqQ6hwJ5ywnS673Q6xWMy50zD0ej2MRiPMZjMSEhK43S+TyYTIyEhup9n1hYr/f1/xH/yBXl7+o7J1wRfb3LnQ+RLY+H2AZQJh2UAqU0Ym3Oj1ethsNqjVaiQnJ3OfuwpNrvdRH8W8+nxv3gjW+2bxm1isJ9cForfYNsx6UaFQQKPRVOjH7uZOT3XArNHi4uIqjF3XuvNWl0JEdHLNqFvUJwtFfrw0Nl74zxL+RoOnjJe+xin/fHwrOlcBh9WrXq93EpOKioqg1+uRnJzsMRaPkLmsqi6cBBEsZGZmQq/Xez0mLS2thkpD1AYk4BANnuoSKlx3hYxGI+x2Oy5fvoxmzZq5fdkwm82wWq1OPuUAPGahYjtg/Jcrf2LteKMhvbz42sHzJMj52vWrSt/iW2RZLBZERkZ6PV5Ie/Hd8aRSKQDntPOBuA9f9RJslh8NVagMhvt2FytMaPwmd+cqLi7mXE3d4c5igJXBVazR6XSwWq3c567n4dddddQlf5w0tL4Z7ATDvOUJT2PKE+7Gm6fnHd+619tnrvM7/3xGoxEFBQUVNiLYMSzeGz/WVWZmJmw2G7Rardu5obbnsmB7phH1m8zMTKSmpgoSkhUKhcdNP6JuQwIOUedxOBx+He8rMJ2/5/MEP1AtWygUFRWhcePGkEgkXOwahlwu53zA9Xo9EhMTuUwpzNQ/JiYGJSUlKC4uhl6vh0aj4c7tuqslEokE14EQhNaLt+sGK+528Jiptztzb0/fcYX/PaH1x44zGo2ceBMTEwOgvI+wv7N/+RmqXK/p7twFBQWIjo7mjmMxQ65fv44bb7wRGo2mwvfkcjnkcrnH++DXkzerBnZflbH8CHT/Y8c11AVyVQVaoe3hba7RarUwGAywWCxo0qSJk8uGp+/Y7Xa341Iul0OlUsFqtXKBvn21q1KpRFlZGc6fPw+JRAIAXDBkdq3o6GiUlpZyrh3sWvzxwP/dG54sFtzdb3VZSAkdH/V5vq8qQtojUO8R/sL6DQvsrdVqub/Fx8f7HF+e4FvIsM0ivkWb3W4HABgMBthsNhgMBoSFhVU4j8PhQGRkJOdOxT8PO79EIoFcLofdbkdYWBhiYmI4UYpdhyESiXw+nwBwWa183XNl6sbbWK2tcUTjt/7CLE3XrVuH1NRUr8eyrG5E/YMEHKLBUVOuA+ylpKCgAAaDAVarFQkJCbBarUhMTHQy4zebzTCZTEhKSkJRUREX70ahUCA3N5fzUWcv/nq9nlukmEwmZGVlQS6XC56og9V9orbwtIPnThjjw3YSPS3MqgK7Hnvp9gQrY2FhISIiIry60JlMJu4FmL8rw4JiZ2dnV+ph71pP3hbPgdotpV3PqlMTdShU6OQHLPX1HZPJBJvNVsF9VKPRIDY2VpB4wzCbzQgPD0dRURHkcjlyc3NhNpsRERHBLQr9iXnibS5wZ7Hg6X5r26qAEEawzUOs37D53WKx+IxxI/S8SqXSKc4ey3oJ/CesuLopusIXgtgYBoCsrCzIZDKoVKoKFgPMddzbc83TRguDicUqlcqrhV9l64bGKlHTpKamokuXLrVdDKKWIAGHqNe4e7mqqYct373JYDBALpdDrVZDLpc7vRiYzWbOVSo+Ph4qlQq5ubkAgJiYGG5nGQD3XY1Gw6nwubm53O6xEDcfvol1REREtdZBXcHTi5+vl1Hm1uRpYeYvrG3cWYaxvzO/Z/5Lrclk4qx0/F1EKBQKpKam4uLFi5DL5U4ijK+XYv45+McqFIpq39kjEbLq1FQdunOZAMrnOzZP8q/vbY7m79QzscZdTDB/7kcsFqN58+YwmUx49tlnYbVa8fLLL0OhUMBms3EijxC8zQXu5hNP83FVLaSImiFY5iH+s57v8sfvg4Fw+XPtw0ywZBYfri4brs8RV4sb9n+73Y5r166hZcuWbq8pZBPD3djyNyZgZeqGxipBEDVNgxZwWGpfov7i7uWqJh62/F1YhUIBs9mMmJgYbpENlL9cZGdnc5l/mFVObm4urFYrl4WF/8JjNpu54J4KhQJlZWXcLrG7BZK7+2euOZ7i6tRXXMUsITunrn3F9WXU3cJRSDlcz8F/kXW1LHB3D/yy+dOfPe1ksoCvrlY0vl6KKzOmArXgoV3PqlNTdegpfpM34dTbbrtMJoNEIoFCoeACcrN+ye6Hid5CiIiIQHFxMcaPH4/9+/cDAHbv3o33338fvXr1cnKP8iVsehN93bnreZuPXeOZ8M/TkObuYCZY5iFP86pCISzGjZDzs37NF4jYc4K5bLl7Xrh7prmWQSwWo1GjRh6v7+m5yX+euxs/7BnGF4u9UdX3Q5PJxLmt8QUzGq8EQQSSBivgfP/99/j7778xdepUNGnSpLaLQ1QT1f1yxV5qgP8yU7BdYfbiALi3dDGbzcjNzeXi4LAHfExMDHJzczlzfmZ1wyx1XK/H4uC4w939B8sLZ03j+oJbGSGB365MDOHHUvHnHHq93mkByhakDofDa9A5i8VSwYpLKP4IUkJeiitThkD1P9r1rDo1UYeBnm+89VM2JzKEiLRyuRxHjx7FtGnTcPr0aYSHh6Nx48Y4e/Ys7rvvPgwdOhTTpk1D586duXNKpVK/RBpvsPoxGsuzaMXGxnILZDZHMZGf/Vvb1h7EfwTLPFTdz3VPlmVs3HmyAHUdn+7ET4VCgaSkJG78smejNyGI/zt7XrLvu5sbKtNOOp2uwpj0BbO4Bsrf8Vi8n2DoIwRB1B8apIBz9uxZjBgxApGRkZDJZHj88ce9Kv9E3cXdQ9vXS70/Pu16vR7FxcWwWq1cVh/+YhgAF1MhMTGROz/LlKJQKFBQUMC5rjDXKRbAmGUMUigUkMvl3P/ZIsKXFY27++eXT6fTBWR3iF9nwSgMuXNTqKyptDfhwjX+haslFqOgoAAAIJVKuYxQ7GWPCTnu7iE7Oxt2u12wgONOoOG7YPFfyuPi4rzukPI/1+v1XLY0d+OLvzPq7vv0Mls7mEzCY7kEiqq0t7u52N3ij/83/hyZkZHhNC+7Yrfb8cEHH+DVV1+F1WpFXFwcfvjhB7Rt2xZz5szBRx99hB9//BE//vgjevXqhZkzZ6Jz584V5l3+OGNxQnwt/FxdXvR6PSwWC/R6PfcdNoew3/mf1zbBPucHC/68T1QFf8eZv+Vy9+zjP988BfHml0uv18NgMCA3NxdJSUnc50KsUNlzhx0POLtmmkwmLrkD+0yh8D8DD79e3I1JX/Ct//gWOLVBTfU9omEhJD05BU+ufhqkgBMTE4PGjRsjJycHixYtgs1mw9SpUxEfH1/bRSNqAE+WF+xhx0zave2aMPEjOzsbUqkUKpWqwg5TXFwcdDodbDYbt2PLvmswGFBUVISoqCgkJCTA4XBAp9Ph4sWLXBBjuVyOhIQEqNVqAHB62QE8pxavaj1U9VzB+DLvzk3B1wuvUFch/kus6y6lq7UN+25kZCSsVitCQkKQlJTkdD7XF+Hi4mJkZGTg/PnzyM7OhtFohEgkgsViQXFxMXe9wsJCLltOSEgIJBIJysrKIBaLERoaCpVKhdLSUlgsFiQmJmL06NFISUkR5CLFh33uag3GPmcv6UqlslLpoInqw9VCJdgREszYta/KZDLk5uZyIndBQQEkEkmFRUxmZibGjx+PHTt2AADuuOMOrFixAgkJCQCAJUuW4PHHH8eiRYvw9ddfY9++fdi3bx+6d++OZ555Bv37968w7llcsnPnznECJ3/h526uYPcWGxvrtPgEKid+1dSiLdjn/GAhWGLkuCK0XJ5cpwBn0cSTIOMqwuTm5nIJGPjHu1rXeNp44rtL6vV65OTkoH379tyzRyaTQa/Xe3TnYu5NnpID8OvF3Zj0hUJR0WXNldoYo8HU94i6CbM6Hzt2rM9jFQoF0tLSSMSpRhqcgGO326FWq9GuXTvcddddMBgMeO211wAAU6ZM4RbTlFqv/uLJ8oI97NjLgbcdF6PRiOLiYk684T/gbTYbMjMzOdemoqIiHD9+HJcvX8aFCxdw6tQp6PV6lJaWwmq1wmq1ekz5GBMTgy+++AK9evXiXn50Oh0kEgnatGkDwLO5sTcrCH49AKiyJU6wu2VVpnzeXIVcdwxdY8fwBR+9Xl/BVY5ZQvAtBS5fvoyMjAxcunTJ6d+8vLzAVQSPt956C/369cNdd92Fe++9l6sb/ku5J/c8/n26Hu9aT+5eVGn3vnao7pd4oQsToce5jlsmfrP5TqfTYeLEibh27RoGDBiALl26IDIyErGxsdyPRCJxEuQdDge+/PJLTJs2DUVFRVAqlVi0aBEeffTRCs/91NRUfPrpp5g7dy6WLFmCtWvX4sCBA3jggQfQrl07PP744+jfvz8XALmgoADFxcWcVZ27eYMv8PLvLS4uTvAuvzdqatEW7HN+sFDZeqrqIt/X94WWy5PrFPDf842JJmKxGMeOHcNPP/2EPXv2wGq14oYbbkDLli3RsWNH9O7dGzExMcjOzobFYuHGMXuOsOux3//66y8cP34cx48fx4kTJ1BUVMSN77CwMFgsFkRHR6NFixa44YYboFKpIJfL0aJFC4SElC9v2PsRP6EEu39f9eJOtAoENEaJuohGo0FaWhpnCeeJtLQ0jB071u07IRE4GpyAIxaLIZPJoNFocOjQIfz5558wGAxYuHAhAOCJJ57gYuL4I+RYLBZYLBbu96KiosAXnvAbISb4DPawUygUHoNbsx0ck8kEiUSC+Ph4zhXFYrHg4sWLOHbsGC5cuIALFy4gLS0NV65c8avMUqkUYWFhsNvtyM3NxahRo/DFF19g6NChAICSkhKEhYVxLzyu4gHbmbLZbF5TZvIXQZWJBcOv10C5xVTXOKpM+fgvlewlEPhPvOHHweC7T7jGG2K7ixaLBQkJCSgtLcWPP/6IDRs24NixY7h+/bqgskRERCAiIgLh4eGIjIx0+p39XyqVwmazoaysjPtx/b20tBR79+7FwYMHsWPHDuzYsQOzZ8/GkCFDMHLkSNx0000wGo1udzBd65PVBT+AJdulYePJXd+i3fvqxdM48mTFEqjdYH929YUcxx+3JpMJ6enp3NwXGhqKiRMn4s8//wQAnD59mvteixYt0KdPHwwfPhzdunXjUpTn5eVh8uTJ2LhxIwCge/fuWL16tdvMN3yaN2+Ojz76CHPnzsXixYuxatUqnDp1Ck8//TQAoHXr1ujfvz9uvPFGtGvXDk2bNuUs6fh9nD9XBGrOZHXDF0RrYlyx8tfnza5API+8tbO3sVfVRb6v7wspF/s/ALeulwpFeSy5TZs24Y8//sChQ4dQUlLidMylS5ecfo+Li0Pr1q3Rpk0b3HzzzejWrRtKSkpw/vx5HD16FCdPnkRaWhpycnL8vmdGdHQ03n33XfTr14+z9hGJRDAajZBIJJDL5R7Hh9BxWZV5s6bHKEEECo1GQ6JMkNDgBBy73Q6xWIyWLVvi119/hUKhwNdff40HHngACxcuhEQiwfTp0/HOO++gf//+GDBggKDzvvHGG5g/f341l57wF/YSo9VquZdbTw809rBzfbjqdDrodDru5dtoNHLuTWx35tdff8WMGTOQmZnp9twtWrRAhw4duB+NRgO5XI6wsDDIZDKEhYUhLCwMUqkUYrEYAGAwGHDPPfdg586dGDNmDD766CP07dsXSqXSKQYKX2RgwgLbAfYG/yWNLXD4n3urq+raQQqmccR3CWIWJgqFgqtX5o7FF21cY+AA/y08z5w5g19//RXbt293WhQAgFqtRrNmzZCSkuL0k5ycjJSUlGpJ937p0iV88803+Oqrr3D69Gls2bIFW7ZsgVKpxC233II77riDEw3dmcSbTCZkZmZCJpM5ZUtzXdh5elHNz8+vlt1Nwr9xFIix7Gkuqepx/DmIuUFaLBaEhYVh+vTp+PPPPyGXy/H2228jLS0Nu3btwqlTp3Dx4kVcvHgRa9euhUgkQocOHdCnTx98++23yMnJQUhICObNm4fnn3/eo/WjO5o2bYp3330Xs2fPxocffoiffvoJR48exblz53Du3DnuuFatWqFnz5743//+hz59+qBdu3YA/A9wLBSj0YiioiLodDqkpKRUyBJEcTAqR3U/j7yNPX8X+a7t7On7/ONYGVz7BisXE+aZOyBQHndm27Zt2Lt3L3bs2IHs7Gyn8zdt2hSDBw/GrbfeioiICPz777/cz9mzZ7n3qX379uHTTz/1ek/896aOHTsiMjIS+fn5yM3NRV5eHvcv+8nNzUVOTg5yc3Mxfvx4jBgxAq+99ho0Gg03f7CYU1VFyLzpaey5s5gmi1SCIPxB5PDn7aUesX//fgwaNAjbtm1D//79UVBQgAkTJmDr1q1o27Ytzpw5g2PHjnEvXr5wt1OTlJSEwsLCGg8aWV8IRNd0jWsTEhLiFPTOnZ+2zWaD2Wzm/padnQ2r1Qqj0YiEhAQUFhYiOjoacrkcOp0OL774In744QcA5fFL2rVrh3bt2uHGG2/EjTfeiPbt23NxbLxht9srfGY2mzFu3Dhs374dUqkUr776Ku644w5IJBJER0dz5WaxeNjuEgBuJ4xZRLB75ps/skDI/BcaZpHD/9z1RcTbokDIjmxRUREiIiIqjI+aGEcGg8FrjBeGw+Hg6isvLw+RkZFOKdyB/zLSsDrPy8vjMkqFhIRg+/btWL9+PXbt2uUUf6RNmzYYOXIkBg0ahJSUFERGRnL1JrTfCz3OV3s4HA6cPn0a33//PTZu3OgkQqakpGDt2rVo0qQJ17+YhSITtiwWi9dMaO7Q6/UV+ligqM8WAa4EYhyx+ZEtHioz77qbM/w9jo03voWbu/laLBZjwYIFWLZsGcRiMb7++msMGTLE6Rp79uzBnj17sHv3bidhBSi3llm9ejWXVUro/ZaVlbn9vLCwEPv378e+ffuwd+9eHD9+vMI5e/bsicWLF6NVq1bcXOHJytMVfn92JxCzz5mYqlarvc7nQsdHoOaXukBtPY/4Y6+q4pq/Y1AikQAA97ziu4Gz557ZbEZoaCgAIDQ0FDt37sSMGTOQn5/PHRsWFobevXtjwIABGDhwINq2beuxTxiNRpw/f55zizp+/DhOnjwJAGjXrh3at2/P/bRo0UJQHbP7YFitVrz++utYtmwZgHIxdc2aNWjfvj03djwFXAbAbaD5gv+O6M4d33Ueq+y8WFlqY1x6GkeVPY5wz5EjR9C1a1ccPnwYXbp0qe3iVCDYyxfsCB0fDc4ChxEbGwu73Y6rV68CKA8qunHjRiQnJyMtLQ0PPvigX4HLZDKZ4BcyouZwtapx3fXwFuOEBcuLjo5GXl4eIiIiIJfLER8fj7CwMKxcuRIvvfQSCgsLIRaLMWXKFMyePbvCw1zoC4E75HI5vvjiCzz++OPYsmULXnzxRRgMBtx+++2QSqXIy8uDXC6HVCqF1WpFYmIidy95eXlcYE0+xcXFAMqtPtztgrvbuXPdbaou09yaGEfe2t3dsTKZjBPL+PfN3NTMZjP3QiiXy3Hw4EFs2LAB33//vdOLblJSEkaMGIGRI0fixhtvDJqFj0gkQrt27dClSxe88sorOHToEDZs2IBNmzYhPT0d99xzD959910MHjzY6cWX1UNCQoLb8eNNJOO7khCBx59xFIhdX6HWAkajEVeuXEHTpk0riMOsTzChxDVIO/v/+++/zy3Oli5d6iTeAOUuGmycAcC1a9ewZ88e7Nu3D40bN8aTTz4Z0H4XERGBIUOGcOUwmUzYt28fJyAdP34c+/fvxx133IF33nkHt956K+RyuVc3XU9jx1M8EqVSieTkZLdtQHEwKk91P48CaRWlVCqh1WphsVjcnpdlRmPuQ2wu9xYwWCaTcS64CxYswOrVqwGUW8bceeedGDRoEHr06AG5XO5R4HQt40033YSbbrqJ+4xtXLm+J7m6YglFKpVi/vz5GDBgAJ544gmcP38et9xyC958802MHz+e20jxJuJ4gx9f0FuGOf485mvs0RglCMJfGqSA43A40Lp1azRv3hx//fUXxowZAwAYO3YsTCYTevTogY0bNyIhIQGzZs2i7FT1AHe7Lu4WkSZTeXYptiiPiYmpcI5z585h0qRJ2Lt3LwCgY8eOWLp0KTp16lQtZZdKpfjkk0+gUCjw1Vdf4fXXX4fdbseDDz7IuUsB5X7fADjBpqSkBCZTecpym80GuVwOiUQCq9UKuVzOWea4Cgl8lwX2e316wfBHPHA91nVxxXbYgPLd2ldffRXLli3jdq/j4+MxYsQIjBo1Cp06dQoa0cYTYrEY3bt3R/fu3TF79myMGjUKf//9NyZNmoQ33ngDgwcPhs1mqxDLwxVfIlllBUByBwlO+OPBW0B0s9kMpVLJzVmAc/B4dg4WgNSVzZs348UXXwQAzJ49G+PHj/dZtkaNGuG+++7DfffdV8m784+oqCgMHTqUcz/MyMjAgw8+iCNHjmDChAmYPn06nnnmGS5mlDvXRE9jx9vc5U0spbFSf3F1v/Hk1sNSYgPllpVMOPE0f7N3h4KCAsyYMQMHDx4EUB4ncuHChQETtqqyweWN/v37Y9++fZg6dSp+/fVXTJ8+Hdu2bcM777wDtVrNuaF7E3I8jU+2uectjo7JVJ6oQMg7E41RgiD8pXpmziCHLaISExM58+oxY8bgt99+w+bNm/Hzzz+jR48eWLNmTdAvuAjfsEUF34UFKH9ouroXZWZmcpYV7MGenZ0Ng8GAgoICLFy4EF27dsXevXuhUCiwYMEC/P7779Um3jBCQkLw/vvvY8KECXA4HFi4cCG2bNnCZV1gMVLYy0VeXh4nLERGRkIikUCtVkOhUKBx48acdRmLm+MK3+KG1VVcXFy9eMngtzszFXdXB/xjgXLXqwsXLji5YMXGxkIul+PEiRPo3bs3li5dCofDgZEjR+KHH37AxYsXsWTJEvTo0aPOzSXx8fH4+eefMXz4cFitVsycORMrV67kxpJrGnF+PSoUigoWFL7qWgiu/ZIILny1T2xsLGQymZN1q1Kp5PqKa9wpfl85cOAAnnjiCdjtdjz00EOYM2dOtd9PIEhOTsYff/zBzd2LFy/Gww8/jAsXLiAzMxMZGRk4e/as17HDYLv+9UFIJwKDa0B4TxYf7saeJ0wmE+x2O3bs2IHhw4fj4MGDUKlUWLt2Ld599906Y20eGxuLr7/+Gm+99RZkMhl+++03DBw4EFu2bIFOp0Nubq7X75tM5VnvsrKyoNfruc0xiUTi9V2IxilBENVNgxRw2M5D9+7dcf36dQwaNAi//vorNmzYgD59+kClUmHr1q04evQoBdmsB/B3eL3BXlqKioq4B7TJVJ5d6rPPPsOAAQPwyiuvwGKx4LbbbsP+/fsxdepUj7vFgUYsFmPRokWYOXMmAGDOnDnYvXs3YmJiYLVauUB+VqsV0dHRXPwItVqNpKQkbnHEFgdsEe5useXtRbA+4SpEeEKhUMBisSAiIgIFBQWcGKHX63Ho0CH07t0bJ0+eRFxcHDZu3Ih169Zh0KBBNdY3qgu5XI5169bhqaeeAgB88MEHmDZtGs6ePeu0yHStR1dx1N0xlaGh9Mu6iq/2iYuLQ2pqqtNz1VUcZm6LLM0wAFy/fh133303zGYzbr31VixbtqxOCaIymQzvvfceVq5cibCwMOzcuRODBw/G4cOHkZ+fD7vd7nXsuGI0GqHT6UjIJJzGnLeNFndjzxMKhQIHDx7E008/Db1ej9TUVOzatQv33ntvddxCtSISifDEE09g3759aNu2LXJzczFjxgx8//33Pr/LnvsymQy5ubmw2WwAyoUhIc8gNk6r8swjCIJwR4MUcJjJ5s0334zjx4/j/Pnz+PbbbzFgwADupVCpVCIxMbE2i0kECP4OLx+TyYSMjAycOXMGGRkZAMr7RnJyMqKjoxEWFoYff/wRw4cPx4IFC3Dp0iXEx8fj888/x9atW5GcnFzj9yISifDGG2/g7rvvBlC+K83MgG02G/eCAfy3EGA7bswnmy0OmJgDoMJLRn2yuPGGt91u1+OSkpIQFxcHuVwOo9GI7Oxs2Gw2rF+/HlarFT169MA///zDuU7UF8RiMd544w0sWbIEISEh2LlzJ/r27YtJkybh8uXLAITVo+sxTARjWUmYuTr73ZPVXEPol3UVd2KMpwWM69/4AdbVarVTYOydO3dCp9MhKSkJn332GRdYta7x0EMPYceOHUhOTkZmZiZmzpyJgoICj32a1ZGrUCNUDPVW/0Tdhd+u/ow5oSgUCuzfvx82mw0DBw7Ezp070aZNm0AVXzBFRUXYsWMH3nnnHYwePRoPPfQQ1q5diytXrvh9rg4dOuDAgQMYP348HA4HXn/9dWRlZXn9DnvuM0vngoICv67JxqlWq6VxSBBEQKnb28NVpGfPnpg5cybuuusu9O7du7aLQ1QTTKzgZ9Xgu0sVFhaiUaNGAMotDsxmM3bt2oVFixbh8OHDAICYmBjMmDEDkydPhkqlqpX7YIhEIs6EOTIyEnq9nnuhYXFwmI82e6lzFzuB765QHSnB6wL82B0sTbinOuAfy1LJWywW7NixAwAwadKkeh0v6/HHH8egQYPw5ptvYv369di8eTO+//57jBkzBq+88goaNWrkZEXgimvdspdblqqWLVJdP2tofbI+4epSxY9f5BoYnfUHd5mnjh07BgCchWxtUVZWhitXriA9PR0ZGRlo1aoVevTo4dc5OnbsiD///BPDhw/HyZMnMXnyZHz55ZdO2Tr48YD4Qo1OpwPgeVPClUCkiCeCD0/tyjal2PuBP23uGu/l6NGjAIDRo0fXiMWj3W7HmTNncOjQIRw6dAgHDx7E2bNnK2RD27ZtG4DyrFWDBw/GbbfdhptuukmQtatCocBHH32E69evY9u2bRg1ahRefvllPPLIIyguLsaVK1cgl8s5i2X2HYVCgczMTNjtduTm5sJkMkEkEjnNUyxWoOv1mBU3jUOCIAJJgxZwoqOj8frrr3OxQoiGAzPTLy0tRUREBIqKilBUVITi4mIsXboUu3btAlD+AH7mmWcwY8aMoEp3mJeXB6D8Rf7ixYuQSCQIDw9HUlKS04sYw5swITRAcX0OIMsWSnwRx1NwQ74FU0ZGBhdHq3///jVY4tqhefPm+Pzzz/H8889j3rx52Lx5M7788kt89913eOuttzBy5EgniwrX4I/8z9jLLXsJZv3PaDRW+Iyom/DnFtdFJ/9vrG8AcJpnmYXWX3/9BQBO2WuqC6PRiAsXLuDy5cu4fPky0tPTkZ6ejsuXLyMrK6tCtp1nnnkGc+fOrZDO2BuNGzfGjh07MHToUBw8eBD33XcfVq9ezc0hxcXF0Ov1iI2NdXJ5NRgMMJvNMJvN0Gg0lN2mgeKpXY1GI+d+qFarvQYU52MymZCVlcUJP6GhoThy5AgAoFu3bn6Xz+Fw4M0338TRo0chFoshkUi4n5CQEKffJRIJ0tPTcfjwYRQVFVU4V0pKCrp164YuXbrAYDDgt99+wz///INTp07h1KlTWLp0KSIjIzFo0CAMHjwYgwYNcko+4YpYLMaaNWvQr18/nDlzBlOnTsU777yDCRMmoHv37jAajYiJianw3GKB1/Pz86HX6+FwOLjnmVQqdRvUmAWWpnFIEESgadACDgASbxoAJpMJWq0WADhTY/Zwbt++PYxGIw4ePIjPP/8cv/76K+x2OyQSCSZMmIC5c+dy1jnBBBNwbDYbl0KcWd+w+3OX3cFdVgWhGRDq824uWyAVFBRAq9VCIpGgdevWPi1JDh06BKB8V702rW9ycnLw6quvwm63Y/bs2WjWrFm1Xq9du3bYtGkTDh8+jOeeew47d+7EU089hQMHDmDp0qUwmUzcIpS5wnjKruNugVFfhcK6SmXFW9e5hb+I4f9Np9NBKpV6dHU9ffo0gMotJn1RUlKCv//+G7t27cKuXbvwzz//eE2JLJPJkJycjNjYWOzfvx9Lly7F6dOnsWrVKi6YvBCio6Oxfft2jBgxAn/88QcefvhhrF27FkOHDoVer+cW0/yYJSqViovJ4bpgdG2j+iy412eEtJunZzbrD40aNfLrec2POxUfH4+TJ0+ipKQEkZGRaNGihd/3sHLlSrz1f+ydd3hT5fvGP0m6knTRBZRSNrSAgyWK4AK+giCyEURQkCEqKCiIIiIOBAFRQNmyp8pQlCkOQJQpgmzohNKmu026kvz+6O89JmnGSVsUJPd19YKm55ycnJz3vM97P/dzP9Onu72fVqulRYsW3HPPPdx99920bNmyjGfPuHHjSE9P54cffmD37t3s3buXrKwsvvzyS7788ksUCgXdunVj0aJFDs2Wq1Spwu+//86SJUuYPn06V65cYdKkSURHR/Piiy9y1113SduKxhCia5VSqSQ/P5+srCzp+PaeW/n5+dIYtUxYyCXVPPDAAw+c4bYncDy4+ZCfny8r8JQboObn55ObmysRGmL7sLAwsrKymD17NkuWLKGgoACA7t278+677/4rNd9ykZmZCZR6RRQVFVGvXr0yZQf+/v52F0PO2js7w385i2RZTpaSkiK1+BVBly3pJSBayT/88MP/xmljNptZu3YtkyZNkrKX27ZtY+TIkYwdO5aAgIAb+v4tWrRg165dTJs2jSlTprB27VpOnjzJqlWr8PHxkRaalgGsZWbT3gLjv0wU3qqojO/EVo1l+ezWarWkpaVRVFRkdY+EhYVx7do10tPTUalUldLtr6SkhGPHjkmEzaFDh6Rnv0BoaCh169alTp061K5dmzp16lCzZk1q165N9erVpbnkyy+/5KWXXmLXrl107NiRtWvX0qRJE9nn4u/vzzfffMOAAQPYsmULTz31FDNnzmTYsGF2iU5LiDI0oVyyJH3slaiVBx4S6J9HRb43e4QpIJEG4jWtVoufn5/VflDaeVCj0XD48GGglDB1t833sWPHeOuttwB4/vnniYmJwWg0YjKZJI8+4dcnXg8LC6NVq1Y0btxYKoWyHZOWCA0NpU+fPvTp0wez2cyRI0fYtWsXO3fu5PTp02zdupXg4GA++eQTh8fw8/PjxRdfZMiQIXz++efMnDmThIQExo8fz8qVK5kyZQpPPPGEFBcIBU5oaCihoaGSB6K90ikoO7/p9Xri4uLKVd5m79iecemBB7c3PASOB/84bGuabSE3gLHczlG5i1h8e3l54ePjg9FoxGAwUFxczNKlS5k6daqkZmnTpg3vvfeeNDG7MrgrLi52+neB7OxsoLTG+8KFCxw+fJjQ0FA6depk1UmlQYMGso6nUCikcw4KCsLHxweDwSAdy2AwkJ+fT3p6OrVr1y6zCBATv7tdXIQU+N+A2Wx2ed/IhbPPrVarqVq1KiqVCrVajclkIj8/H6PRiE6nk7JwarUas9nMnj17AHjkkUdkfQY5yM3NlbXdwYMHmTVrFkeOHAEgJiaGgIAADh8+zKeffsrq1asZNmwYzz33nKwgXK7Bor02tMOHDyc2NpZRo0Zx6tQp2rVrx7Rp0+jduze+vr4YjUZ8fX2l4FX8bjKZrBaitkSP5TWTe7/Kvc63UhejfxvukreWCwx7z2bbZ7f4Ea+JxaWfn5/k79WkSRP8/PwoKiqSdQ5CdSnwzTffsHnzZg4fPkxeXp7V38LCwrjnnnuknxo1apS5P4qLiyksLCQuLk56rXnz5ixZsoRx48Zx4cIFHn74YZYsWeL282DFihWMHj2aFStWMHbsWOLi4nj//fdRKpVS10xx3Xx9fVGpVJjNZs6fP4/JZEKpVBIcHExhYaGkGHX0nbkzPmxbVHsgH+Wdrypa0ixIEvG8TU9Pp6SkRLrnxf8t1ed+fn74+fmRnp5OYmIiv/zyC1BK4Mh9Tup0OnJychg0aBDFxcU8+uijjB07tsz+zoyAL1y4IP1fbnxVvXp1YmJiiImJYfTo0ezbt48hQ4awYsUKGjVqxIABAwAcljiqVCpefPFFBg8ezOeff86nn37KqVOn6N27N82aNePtt9+mZcuW5Obmkpubi6+vL6GhoVaeO6KLnCXpKsgzocoTz7XCwsIKjSXPuPTAAw/AQ+B4cBNCbgAjtnOmktDr9fj4+KDRaPD396egoACDwcDChQt59913AYiNjWXq1Kl07twZhUJBSkpKpX2W5ORk9u7dy++//86RI0esgpe//vqLl19+2S3vBCgN0MRxGjRoUGaBpNFoSE9Px9fX12oRI66nJ2vjGBERERJRJQJccX8B5OXlkZGRQVRUFImJiSQmJuLj48P999//j52jyWRi5cqVTJs2jYKCAnx8fBgyZAi9e/dGpVLx66+/Mn/+fJKTk5k+fTrfffcdb731Fi1atJB1/JKSEs6dO8fRo0cJDAykc+fODqXolmjXrh27d+/m+eef59ChQ7z00kucPXu2jJRe+AmIRbsYu8JHwFULZQ/+ecgtsxRwRa5bPrPPnj1LWFiYZCBvu70gKCtSPrVkyRLef/996ffg4GDuvfde2rRpw5133kmdOnXKTejFxsayatUqXnvtNf744w8GDBjApEmTeOGFF2Qf08vLi/nz51O7dm3eeecdPv30UxISEliyZInV2LMkN8UCPjs7m8jISAICAqhWrZrbpbHO8F9WXd6sqEhJs/BJsvRws6d8FP83GAzS72q1muTkZHJzc6XSYHc8p8xmM6+//jpJSUnUrFmTadOm/Ssk+cMPP8yrr77KRx99xNtvv02jRo1kzX0BAQGMHz+eUaNG8cknnzBv3jyOHz9O9+7deeihh/joo4/s7ieeY6IMTcQKgmgV19qyvM0zLj3wwIOKwkPgeHDTQW4AI7Yzm81SJyXbQMXSGFOQN2vXrpXIm0mTJvHaa6/J6mAgBzk5Ofz2228cPHiQgwcPSu3JLc85NjaWY8eOsXHjRnQ6HVOmTJG1QBawJIGCgoIoKSkpQ2LVrFlTUuKIzJter6dKlSq3ZGmK6ORwo8knSwVIenq6FNiKxWVSUpJENOzYsQOA++677x+7npcvX2b8+PGSxP3OO+/ktddeo2bNmtI2bdq0oVWrVnz11VesWrWKP//8k759+/L4448zfvx4IiMjrY5ZUlLCX3/9xf79+zl8+DDHjh2zUijMnTuX5557jp49e7q8T6tVq8amTZuYPn068+bNY/78+Rw6dIj169dLyjaDwUBJSYkkSRcKAzlddTy4NSB3gSFKoxITE4mKipIUbpYQBI5cAtIWa9eulcibZ555hj59+hATEyOp0uQq3pwhNDRU8v3YvHkzU6dO5a+//mLWrFkO1aG2UCgUjB8/nlq1ajFy5Ei2bNlCUlIS27Ztk/y1bOdGoXAKCQkp4xUiCB7LbctTNutZJN6csDfGBKlja8ZveQ+K/5vNZtLT08nLy8Pf318afzqdjsuXLwPuETgrV65k165deHt78+mnn/6rTR9GjRrF6dOn+e677xg5ciTffvutU2NjS1SpUoUpU6bw4osvMnv2bD7//HN+/PFHJk2axIIFC8psLzxyAImwEX56lu9pq8yxTTS6UxLlGZceeOCBh8Dx4D8B2ywT/K2+EeTM1atX+e6775gwYQIA48ePZ+LEieV+T6PRyKVLl/jzzz+lnzNnzlhJ3lUqFU2aNOGee+6hVatWNG3aFC8vL/bs2cOUKVP44YcfyMjIcJjdsQdRPuXv709JSYnk1yJUN1BaEuDv7281yVsqcGxxs9dU6/V61Gr1P0Y+CeJLqG1EEBwVFSXdZ+6UT1UUJSUlLFmyhNmzZ0tE1rBhw+jWrZvd8ihvb2+efPJJ/ve//7F+/Xo2bdrEN998w+7duxkxYgQPPPAAhw8f5rfffrNbUuLv70+zZs04d+4cqampfPDBByxZsoTnnnuOYcOGWfkn2MLLy4s333yTDh068Oyzz3L06FHuueceli1bRpcuXcooLQoLCwkMDLwp7zsPygdLosFeKYkwubZUYglSz/I+MJvNHD16FCifAmfLli1MmjQJgJEjRzJ+/Pgbpgrw9vbmzTff5J577mHSpEl8+eWXXLx4keXLl5chTZ2hX79+1KhRgyeffJIjR45w7733snnzZitjVSi9xg0bNnToZyYW81evXsXX1xd/f39q165d0Y/pwU0Ce4kurVZLXl4eRUVFUkJLLoEIpcbahw8fxmw2Ex0dTbVq1WSVMh09epQPP/wQgIkTJ3LHHXe492EqGQqFgo8++oiLFy9y/vx5Ro4cye7du91KlIWFhfHBBx/QtWtXOnfuzM6dO3nzzTd55513gFLFjmXCx1I5qtfrCQ4Olo4l4itRAunxffPAAw8qCg+B48F/Ao5UO1lZWYSFhaHT6diwYQPTpk0DSs31Jk+eLOvYeXl5nD59ukxb2fj4eLvBTd26dbnvvvu4//77ueeee6TsjCU6dOhAcHAw48eP58SJE7z++uvs3r1b1vkIA2N/f3/g79puyy4SAhqNRlbQfrMHEBqNBpVKVWlZJ1eElVarRafTSWobQTqIxZKXl5fU2vhGGxhfu3aNUaNGSW1dH3jgAaZNmyYrsA4JCWHatGk89dRTvPvuuxw5coRPPvmkjLmjv78/LVq0oFWrVrRs2ZKYmBhUKhVFRUV8/fXXLF68WCJy1q9fz9q1ayVFjSM89thj/P777wwYMIDDhw/To0cPxowZw5QpU6wyk+4YLefn56PT6YDSANs2+2zZ9cODfxdijNl7Ngtj0KCgIFQqFWFhYeTn51NUVGSlwvn222+lbi/uLgpPnDjBq6++itls5umnn76h5I2AQqFg6NChxMTEMHToUE6cOEHHjh1ZtGiRW2WWbdu25YcffqBnz55cuXKFDh06sHr1atq1a2d1LS0XkLbdbSxLjO3NQR7cOpCbYNFoNPj6+loltNLT00lKSgJK5wNRrgilyjFb1dtvv/0GyCdMi4uLeeaZZyTfm6effrq8H7NSodVqWbRoEd26deP48eM89dRTLFiwwK6HmzO0adOGZcuW8dRTT7F27VqMRiOvvvoqhYWFREZGSmPQdlxaljrGx8fj6+uLUqnEy8vLbrtxT0mUBx544A48BI4HtzycdQkKDg7GZDLx0Ucf8dlnnwHw9NNPM2PGDFnB/P79+xkzZoxD4z2NRkOTJk244447uPPOO7n77rvLtB0XJsa2aNmyJZ988gnPPfccJ06ccP1B/x9C8q/VaiVSQWSya9asWa7F680eQGg0mkqVZNsSVrYBskajISoqivT0dAwGg3SdjUYjer2en376iezsbKpWrUrz5s0r7bxscf78eQYMGEBaWhqBgYG89dZb9OnTB4VCwZUrV2Qfp2nTpqxfv57vvvuOWbNmkZGRQatWrWjdujWtW7emcePGFBYWltnPx8eHJ598kp49e/L111+zaNEiLl++TLdu3Vi3bh2NGzd2+r61atVi3759TJgwgfnz5/PJJ59QUlLC7Nmzpetqr1uaIwjlBpTt/iG6fqSmpkoScw+R8+9BjDF7ChGNRkN0dDQJCQmSb0RGRgYmkwmDwUBoaCj79u3j2WefBeCJJ57A29vbrfffsGEDRqORjh07MmXKlH/Uj+P+++9n586dDB48mL/++osePXrw6KOP8tprr3HnnXfKOkbDhg3Zt28fffr04fDhwwwePJjt27dLpWR6vV4iM4EymX3xHLP3bL/ZFZceWMPdBItl2dT58+e5fPkyGRkZ1K1bF0AqubUsD05PT+ebb77h888/B6Bbt26yzm3v3r1cvnyZKlWq/Gu+N45Qu3ZtPv30U4YPH87OnTu57777WLRokdtJl169epGcnMz48ePZsGEDx44dk8rw69SpU+YZZxmLCmV0YWGhlPSwLaOy593oGZ8eeOCBM3gIHA9ueVi2xha/iwkxPT2d0aNHs23bNgAmTJjApEmTXHblMZvNLFq0iJkzZ2IymahatSqNGjWiTp06UmvZqKgoqlev7rYJsSWEtN6dDKntQlu0uJRD3jgKDCrD8PJWgu2ixl6ALIJbQdpYmhkLMnDw4MEV+v6dwZK8iYmJYfHixURHR5f7eAqFgi5dutClSxfMZrNbgbYgctq3b88LL7zAmTNn6NmzJytXruSee+5xue/HH39MgwYNePnll5k/fz7FxcWMHj0ak8lEQUGB7M+l0WgkxY6tBN2yi9bNrCa72VFZiwdLBYg9CBJHEPAZGRmkpaVRtWpVsrOzeeaZZygsLOTxxx9nyZIlbr13SUkJu3btAmDQoEFut0KuDNSqVYvt27czefJk1qxZw86dO9m5cyedO3fmtddeo3Xr1i6PER4ezvfff88jjzzCyZMn6devH/v376datWpWHjdardZuZh/sP9tvdsXlfwWVPZbKk2BRq9UoFAp8fHwoLCzk6tWr0uvChwxKFWsvvfQSAC+88AL9+/eXdfwNGzYA8Pjjj/+rvjeO8NBDD7F582ZeeeUVzp8/T7du3Rg9ejSTJ092q6Rq9OjR1K9fn+HDh3PhwgWGDBnC22+/Tb169Zx+t7bmxWlpaS7Hnmd8euCBB67wz0c1HnhQiRDBf1ZWlpSRFCZ+CQkJ9O3bl23btuHt7c3ChQuZPHmyy2Ber9czevRoZsyYgclkok+fPuzbt48vvviCyZMn8/TTT9OuXTuioqIqvHi33N/SO8cZRBtdPz8/QkJCUCqVVnXu4jrYawttGRjcztBoNISHh1uVG9hbAInSLWEGGRoaSnx8PD///DMAQ4cOvSHnZ0neNG7cmPXr11eIvLFFebOk4eHhfP3117Rq1Yrs7Gz69evH3r17Ze0runsALFq0iBkzZmA2m53er7bQarV2u1RZdpuLiIgo812KEhO5rdJvZzh6Rrh7DW3HmO2xLEvhwsLCUCqVhIaG4ufnx8yZMyksLOTBBx9k48aNbvl4APz8889kZGQQEhLCvffe69a+lQmtVsusWbM4cOAAvXr1QqFQSITMgAEDOHXqlMtjBAcHs337durWrUtcXBwdOnTg0qVL0vEt5zNbItPZeTkifDyoPKSmppKSklKmpb27cDaWBMT4tCRloFRt06JFC1q3bk316tXx8fEhLy+P5ORk4uLi+PLLLxk+fDh9+/aVCNOZM2fKmiPy8vL49ttvAfmKnX8DTZo04ZdffpHm608//ZT27dtz9uxZt44jyoIfeugh9Ho9EyZMYMiQIZLK2t5cJjfWsIRnfHrggQeu4CFwPLilkZ+fL7V7Fv96eXlx8eJFOnfuzO+//05wcDA7duxg4MCBLo93+fJlevfuzXfffYe3tzfvvvsu06ZNcytT4w4sg2+5KhyhwBGLmqioKKKjo6XablHqY4+kuZ0DA2cLUMsgS2yXnp5u1WJVYPXq1QB07NiROnXqVPp52pI3a9eupUqVKpX+PuVFcHAw69ev55FHHqGgoIBnnnmGr776Sta+zz//vETirFy5kvnz50sGtoKMtQyA7QXEtoo7QPIlEmoD28WOh7iUD0fPiMq8hva+w+rVqxMWFoZer+frr78G4KOPPipXh0Cx/6OPPlppHQYrgnr16vH555+zf/9+evbsiUKhYOvWrbRu3Zqnn36av/76y+n+1atXZ8eOHVSrVo2zZ8/Sr18/4uPjiY6OJjQ0FJPJxPnz58nNzZX1/dgbIx6S89aGZcmiKImyLK1u2LAhDRs2JCwsjKtXrzJv3jx69erF+PHj2bNnDyUlJXTq1IlVq1bJTkx988036PV66tWrV8Zk+2aDRqNhzpw5rFu3jpCQEP744w/atGnD66+/LjWGkIPIyEi2b9/O+++/j0ql4vvvv6dNmzYcOnTIqszancSEvXMVXeU8Y9IDDzywBw+B48EtDbHY0Gg0ZGVlodFoOHnyJL179yYhIYG6dety4MABHnroIZfH2rVrF+3atePcuXOEh4ezevVqBgwYcENruitC4AQEBEjEkiAexETvzLPHVSbvvwq5C1CxXUZGBnl5eSQlJUlZzaKiItavXw/Ac889V+nnePbs2ZuavBHQaDQsX76cHj16UFJSwosvvsjYsWNltWS2JHEWLVokddayVNBZEji5ubkkJCRY+QaIMZ+fn09aWhqA04D3diYu3YWjZ4TtNazIgt/yOxTHCgoKokqVKkydOhWA/v3706xZM7ePXVJSIpXMPvbYY27vfyPRoEEDFixYwE8//USvXr2AUrLpnnvuYfDgwVy4cMHhvnXr1uW7774jODiYEydO8PDDDzN//nz8/PwoLCwkKChI6lBXnu/GQ3JWPiIiIqhWrZpVYwE5KM/3p9VqHT5HoTQmWLlyJX369KFTp04sX76czMxMqlatytixYzlx4gTbtm1zKzYQ5VP9+vW7qbxvnKFr164cOnSI//3vfxQXFzN//nzuuusuPv30U7s+cPagUqmYMGECP/30E7Vr1yYxMZEHH3yQjz/+mIKCAikes5dIc2ececakBx544Aj/fmrKg/8M7LWLvdHHE3XcOTk5+Pj4sHv3boYMGUJRURH33HMP69evJzw8HL1eT0JCgsP3WbJkCZ988glms5mGDRvy6quvolKpOH78eIXOD6BGjRqytjOZTLKCIBFk+Pr6SuU9lpkfQGph6agG/3Y0yRPXydUiXvgN+Pn5ce3aNQIDA9Hr9ZjNZjZt2oROp6NatWqSl4zc+8AVuWGpvKlTpw6TJk0iKSlJ6iBiC0FYuILwAnGF6tWry9rOstRv8uTJhISEsGzZMtatW8dPP/3E+++/T/PmzaVSP3vo3r072dnZTJ48mXnz5mE2m5kwYQLFxcUolUp8fX0xGo34+vpK3cBENlOj0UhKDWGCC39/v/a8A+z5gFT28+pWWcCUF7bXUK5Pg73rIkymLX/PzMxk37597N+/Hx8fHyZNmmR3QeWq+9q+fftIT0+nSpUq3HXXXWVKSmyRnJzs9O8CJSUlsraTu9iaNm0azzzzDPPmzWPnzp18+eWXbN++naVLl1p1AIqKipL+HxMTw4EDBxg5ciS//PILY8aM4csvv2TOnDlSRxwxZoxGI7m5uVbzAvzd/tgWtj4rnvHhGHKe+wqFosx97uhYtiiPB4owrC4sLKSoqAiFQoGvry9Hjx7l448/ZuvWrRQUFAClKuXOnTvz9NNP87///U8yCLc3thw9x1NTU6Xy2Z49e8oeR+np6bI/jxxYGnk7Q/369a1+/+STT9i/fz8fffQR58+f58033+Szzz7jrbfe4oknnnB5vwYEBNCsWTMOHjzI6NGj+fLLL5k+fTpXr15l/vz5eHt7U1JSglqttpoz1Wq11NkyLy9PmtOUSmWZmMye95HccSl3vFX28TyoGBISElze02fOnPmHzsaDmxkeBY4HtzwyMjLQ6/X8/PPPDBs2jKKiIrp06cL27dtdLnLz8/MZO3Ysc+bMwWw206dPH9555x1CQkL+kXOviALHMjDXaDQUFhaSnp5Oenq6lIl1lMERr6empt42El0RGLnyibBUIFStWlX6jpKSkli+fDlQal7sblccZ7Alb95///2b0hDSFkqlktGjR7N06VIiIyO5evUqQ4YM4eOPP3aZzRw8eLCktpg/fz7Tp08nJCSE0NBQq+4cNWrUQKlUSp4NIrjR6/VSdw/L7UXJzO1yX/9bqExVk0ajwcfHh+nTpwMwcuRIl23qHWHr1q0AdOjQ4aYon3KGRo0aMXfuXLZu3UqrVq0wGAwMGzaMkydPOtynTp06fP/998yaNQuNRsMvv/xCu3btWLhwodVCMSUlhYyMDNLT0zEajWRkZDgsrYXbW515s8HdsSUUO1CqDhHP0KSkJDp06MCGDRsoKCigcePGTJ8+ncuXL7N+/Xq6dOlS7nls8+bNmEwmWrRoQb169cp1jH8bbdu25euvv+a9994jIiKC5ORkRo4cSefOnfn1119lHSMoKIjly5cza9YsFAoFq1atonv37ly5ckUqvdbpdNIPIPm4WSbe7MVqnjF5eyEhIYHY2FhatGjh9GfgwIFSIsuD2xceAseD/wQuXbrEq6++isFgoGPHjqxYsQI/Pz+n+8THxzNgwAB27dqFl5cXb7/9NlOmTKnUhbkrlMfEWCyMvby8yM/PlwKDq1evkpSUJGXtREbOXiAoXtfr9ZVisngzQ5TZCOJGriRZrVbj7+8vZcCvX7/OgQMHAKT2xpUBW8+bW4W8sUSLFi3YtGkTTzzxBGazmeXLl9OtWzeXmaLBgwdL5VTz589nypQpUkZQr9dL2VqNRoO3t7eUQRavCQWa5WuCtHX2PXv8PioOyxbVliVv5b2ua9as4cKFCwQHB/Pqq6+W65xKSkr45ptvgFL/m1sFsbGxLFmyhNatW5Ofn8/QoUOdjh2lUsnzzz/P77//Trt27dDr9UyZMoVOnTpx+fJloNQTTiQFVCoVISEhqFQqTxnhTQ7L7mJyTanF4h8gNDRUUnls2LCBvLw8GjVqxP79+zl69Chjxoxxu6TLHjZu3AhAnz59KnysfxMqlYpevXrx/fff89JLL6HRaDhx4gQ9evTgmWee4eLFiy6PoVAoGDlyJKtWrcLHx4cffviBZ599lvj4eImkEUSqrXebmMM8Zb4eCJXx6tWrOXr0qNOfM2fOVGpjCw9uPXgIHA9uGeh0Os6ePUtCQgJnz57l+PHj6HQ6rl27xksvvURubi7t2rVjzZo1Lk2Hjx8/zpNPPsnFixcJDw9nxYoV9O3b9x/6JH+jIgqcwMBAqzbYGRkZ5ObmUlRUZKVIsJfB+S9mdiyJGktYGqYKhYa9IMl28alWqwkJCZHaiW/evBkozexXlnmxPcPiW428EfD392fq1KnMmTOHKlWqcPbsWbp168aCBQuc3tuWnjiffPIJb7zxBmazGYPBQElJiWTEGRERYWXWLUhKHx8ftz1v5HoLeIge57C9jnKuq71rajAYmDlzJgCvvvpquRWQv/zyCxkZGYSGhrpsb3+zQa1W8/nnn9OsWTOpjbqrxWPdunWt1Di//fYbzZo1Y/Xq1Wg0Gvz9/SUVgMjYWvoOObu3Pff+v4P8/HxycnI4d+4cOTk5spINls87YWAMSObyI0eOpGXLlpVWBnPx4kWOHTuGSqWiR48eFT6e3OTVjYRGo2HUqFEcOnSIQYMGoVKp2LFjBw8++CBvvfWWLH+cHj16sHnzZgICAvjzzz8ZMGAA8fHxFBYWEhoaKiXsbMuBLc33wbF61DMmbw/ExsbSvHlzpz8e8sYDD4HjwS0DnU5HUVERycnJ6HQ6cnJyOHr0KH379iUzM5NWrVqxYcMGpy1nTSYTa9asYejQoeTk5HDXXXexadMm7r777n/ug1jAsv5YLoEjArrQ0FBpQavVagkJCSE8PNyl8sgS5TVZvBlhr7MNWBumarVah8SVo8WnwWDAYDBIwXBlmRfn5eXx1FNP3fSGxe7i4Ycf5quvvqJjx44UFRUxbdo0HnvsMb788kuHfgqWJM6sWbN47rnnyMrKkkpgDAaD1G7a0qzb1gxXwBVBKTfb6TGRdA7b6yjnutq7pkuWLOHq1atERUUxcuTIcp+PKJ/q2rXrTV8+ZQ/+/v4sXryYJk2akJmZyeDBg12q2IQa59ixYzzwwAPo9Xpee+01hgwZInmaCDN2y2ej5fdgb2Houff/HWi1WoqKiggODqaoqEiWIsO2i6LRaOTcuXOcOXMGb2/vSk9OCSP/hx56qEKxw9WrVxk7dix9+/Zl+PDhvPHGG8yePZuVK1eybds2fv31Vy5evEh2dnalezI5QkREBDNmzGDfvn3873//w2g0snjxYgYOHOjSfwtKr8mOHTsIDw+XOsZlZmZazV9paWkOfU6clbd7xqQHHnggcOtFOB7cttBoNGRmZkqL3FOnTvHKK6+QmprKHXfcwVdffUVAQIDD/RMSEpg8eTKHDx8G4MEHH2TWrFlOCZ8bjZ9//hkoNcSTs3gvKipi3bp1QKkpn06nQ6PREB0djUaj4eLFi/j6+qLX6/H39wecGxbbM3e9VSGCV3vdc+QEwfYMAwFJCSIgl2hzhR9++IHU1FRq1KjxnyFvBEJDQ1m8eDEbN25k6tSpnD17lnHjxjF37lyWLl1axlASSkkchULB6NGjWbVqFRs2bKB3797079+fmJgYCgoKJN8b+PveLc/9K3c/R/eEB6WwvY7Orqteryc1NVVSVHl5eREXFwc4Nkp1F+J5WpHuUyaTiZycHKuf3NxcsrKyyM3NtXotICCAO++8k7vvvpuaNWtWisIhMDCQZcuWMWjQIM6dO0enTp345ptvuPPOO53uV69ePXbv3s2CBQuYOHEiP//8M/fddx979+7Fx8dHUqqJOdLy3haqj7S0NGrXrm1VHue59/9ZaDQaatWqVe4mA2IePHfuHAAtW7YkNDS00s4vOzubJUuWADBw4MByH+f8+fN88MEH5OTkAFh5xNiDr6+vRIKEhoZK/w8ODpZeCwoKkt0C3RUaNmzIypUr2b17t2Qa/s477/Dee++53Pfuu+/mhx9+4PHHHycuLo5evXqxb98+atasaXd70fpdxCr5+fkUFhaWMbL2jEkPPPBAwEPgeHBTIC0tjbS0NMLDw62Mh0VLTIE6derg5eWFt7c3PXv25OrVq9SpU4fNmzc7XACbTCYWLVrE5MmTpcXD2LFjefLJJ61KmP5pmM1m1qxZA0Dv3r1lee+sXbuWhIQEqlWrRo8ePaSaajHBV6tWzcrUFcrX0eJ2hKPFp+h0NnDgQD766CMWLFhA7969K/x+O3bsAEo7Mv2XyBsBhUJBv3796NSpE2vWrGHZsmXExcXRs2dPFi1axL333ltmn5EjR1K/fn3ee+89Dh48yNq1a1m7di2PPPIIo0aNolGjRqSkpFgRtUKRI4eUcbf72n+J4Py3kZ+fT15eHoC0ABG/9+nTh48//pikpCQWLFjAyy+/7PbxU1JSuHLlCgqFgtatW5erzCArK4s333xT8pGRg99++w0oJS3vuusu2rRpQ4sWLSq0aK5SpQorVqxg6NChnD59ms6dO7N161ar7lT2oFQqGTVqFJ06deLJJ5/k+PHjDBw4kK1btzotAdFqtaSlpeHr62tVDucOgXA7dja8UajIc0eU/GZmZgJUurp20aJFZGdn06hRIx5//PFyHePw4cPMmjWLoqIi6tWrx+jRoyXPM51OR1paGllZWaSmpqLT6cjMzKSwsJDk5GSn3a5UKhVVqlShXr16dOrUiWbNmlWY0OnYsSPz58/nmWeeYcmSJdx5552yFE1169Zl586ddO7cmcuXL/Pwww+zevVqqlSpglarlUqB9Xo9iYmJ+Pj4AEhKKntkzY2Yjzzj1gMPbk14CBwPbgqkpaVRVFREWloaWq2W1NRUKZsp2i8HBATg5eWFUqmkZ8+enDt3jqpVq7JlyxaqVq1q97iXL1/mhRdeYP/+/QC0atWKd99912EmxBZFRUXs3LmTjIwMGjRoQKNGjSotm3XixAn++usvfHx86NWrl6xzmTVrFgAvvPCClbeB5b8RERFWE/HtkrXR6XRSVrwyP6sIiJ9//nlmz57NL7/8wunTp2nSpEm5j1lQUMCPP/4I3Fpmq+VBUFAQo0aNol+/fgwdOlRaVM6YMYOePXuW2b5Dhw506NCBgwcPMmvWLL755ht++OEHfvjhB5o1a8aIESOsup7Yehw5gz3PFk/g+s9Aq9VKqkAxPsXvYWFhjB49mtdff52ZM2cyaNAgt31wDh06BECTJk0ICgpym8ApLCzknXfekcgbf39/AgMDCQgIIDAwsMzvAQEBXL9+XXqOp6enS/cplCYbWrVqRYsWLWjWrJlbpa0AISEhrFixglGjRvH777/TtWtXNm/ezH333edy37p167JlyxZat27N6dOnefnll/n888+ttrEcC+Hh4dSuXdtKkeMu6e9JFNxYuLvQFs+4yuyoefLkSebOnQvAa6+9Vi5yZOfOnSxevBiTyUTz5s0ZN26cXRW05WcsKiqSFDqC5BE/aWlppKenk5mZidFolF7/7bffiIiIoFOnTnTs2LH8Hxro1KkTY8eOZfbs2YwfP55GjRrRtm1bl/tFRUWxd+9e2rdvz+XLl+nbty8LFy6kVatWVl5Uvr6+FBQU3HCyxh4849YDD25NeAgcD24KhIeHSwqc/Px8cnNzUSgUBAQESNl2jUaD0Whk2LBh/PjjjwQEBLB9+3bq1q1b5nhCdfP222+j1+vRarW8/PLLbqluzp8/z2effUZSUpLV62FhYTRq1IhGjRrRsGFDateuXa5ARqhvunTpIivIWr16NUlJSVStWpX+/fsDf8ulxf8tgwIhyZUbCNwKmRh3zlF4O4hsVkWhVqt55JFHpDIFEciWB/v37yc/P5/q1au7LI2Qi4MHD1JcXEy7du0qrCzLyclhy5YtGI1GHnvsMYcEqTsIDQ1l/fr1jB07lu3bt/PKK68QHx/P9OnT7ZaetGnThjZt2nD27Fk+/vhj1qxZw/Hjxxk5ciQff/wxr732GgMGDECj0Uj+WGKsO4JYnALExcVZlWN5UIob9RzQaDTUrl3b6j0syeYnnniCpUuXcuHCBWbOnMkHH3zg1vEFgSOH4LCFyWRi5syZnD17Fn9/f2bPnl2G5Lcso7REr169KCws5MyZM5w4cYI///yTCxcucOXKFa5cucLGjRsJDQ3lvffec5v0DQwM5JtvvqFXr17s37+fbt268eWXX/Lggw+63DcyMpINGzbQoUMHvv32W+68804mTJgg/d2W2LedJ1JTUyksLJR9H9wuiQJ7+CfmTncX2qI0qbISTidPnuSJJ54gNzeX1q1b0717d7f2N5vNLFu2jJUrVwLQvn17Ro4cKSt28vHxITIyksjIyDJ/E740RqNRUu0cOHCAvXv3kpqaysqVK1m7dq2kSmvevHm5Sh1fffVV/vzzT3bv3s2QIUM4cOCAlVrcEWrWrGlF4owcOZLdu3dbmfFDqXq6Mu4dy3uxIqXjHnjgwc0Nj4mxB/8YnDnoh4eH07hxY8LDw9FqtRJxExYWRnR0NNHR0ZjNZsaPH8+2bdvw8fFh8+bNNGvWrMyxLl++TJcuXXjttdfQ6/W0a9eOX3/9lQEDBsha2BYWFrJixQomTZpEUlISwcHBdOzYkTp16qBUKtHpdBw4cIBly5bx+uuvM3jwYKZMmcK6detITEyUdS0uX77MwYMHUSgUPPnkk7LOafbs2UBpmYlSqZTIm7y8PBITE62uqzvtsgVuBYM823O0vKfCwsKoWrWqlTTZnqmxuzAYDGRkZJCcnCwppdauXSsFyOWBKJ969NFHK+ybUVRUxIwZM3jllVcYP348zzzzDL///nu5jlVcXMy2bdt4/vnn+frrr9m6dSvPP/88M2fOlNVO1RX8/PyYN28ezz//PABz5szh2WefdVreERMTw8KFC7l06RLjx48nMDCQc+fO8dxzz3H33XdLPlD2ulHZwrLTh6+vL5mZmbJb9d4uuNHPAb1ez5kzZ7hy5QqpqanS6+Hh4bz11lsALFiwgPj4eLeO++uvvwLYLc1zheXLl7N//368vLx46623ZCs0BXx9fbn77rulMoutW7cyZcoUHn/8ccLCwkhPT2fMmDHSuHcHAQEBbNmyhfbt25Ofn0+PHj3YtWuXrH3btGnDnDlzAJg2bRrffvst4JpwEKS3ZUmVK/wXOxvKxT8xd7rTZtpgMEilRpWhwBHkTVZWltQswp2kVUlJCdOnT5fIm759+zJq1KhK86uB0vKp0NBQYmNjee6551i+fDljxoyhYcOGlJSU8O233zJw4EC6d+/OunXr3P6ulEol8+fPp169eiQnJzNo0CBZpsbwN4lTt25dkpOTefzxx6UW47bd4SoKd+/F23nceuDBrQyF+Z+ydr/NkJOTQ1BQENnZ2bdsW2ABObeIs4BQ/C0/Px9fX1+8vLxkZS4MBoPV71OmTOGjjz5CoVCwatUqqX2l5WL1woULjB07lry8PPz8/Bg+fDhPPPEESqVS1qL2ypUrfPHFF9KCUnR6Eh1NjEaj5OXg5eVFSkqK1eLT29ubgQMHSqUBgF0/h/Hjx/PVV1/RqVMn5s+fD2A3uySwaNEixowZQ2hoKFu2bKFGjRqS5D0hIQFfX18CAgIkBVNaWhpQtpzKGVwF9ZXVghTkjw/b7cR9JLJLqamplJSU2L2nypsVFfup1WpJ3SGye2azmR49enDhwgU++eQTXnjhhTL3qSMkJCQApcHsgw8+SFZWFl988UWZdseXLl2SdbwZM2ZQWFjI2bNnpTJDpVIptWQNDg6mdu3aDB061OWxzGYz27dv59ChQ2RnZwOl975arbZSoNWoUYNOnTrRqFEjl/eDK2XRd999x9y5czGZTLRq1YrPP/+c4OBgh9sLFVBOTg5ffPEFn376KampqURHR7NhwwZq1KghtX53BeGb4+4zyRkqc3zIRXnHkTNYjrHyBPW2487W9Fun05GYmEhBQQGhoaGEhIRI6g+z2UynTp344Ycf6N+/v7Tgs0RWVlaZ13Jzc6lfvz4mk4mTJ09SvXp1Tp06Jet8Z82aJREb3bt3d3jfym11bFsOUlhYyKZNm6RuUm3btuXRRx+V3eZcqJYKCwsZM2YM+/btw8vLi3fffdeqBNHZ/PHSSy+xfPlygoOD+e233wgKCsJoNKJSqawIb0svqYKCAqtFYEXnBbmh5q04jmznJZD/eeVCHM+V51dOTg7JycmMHDmS/fv3s2DBAp555pky28mdt37++WcGDRpEdnY2d999N1988YXdZhEnTpywu7/BYGDWrFmcOHECpVLJo48+Kqvrp6vuawJyfHji4uLYvXs3R48elUgXX19f2rZtS5cuXayIpEceecTpsS5dusSAAQPQ6/WMGDGC999/3+n2ls+DpKQkHnnkEZKTkxk8eDDPPfccderUoUqVKpXWTMNdBU5ljssbMR/dTjh27BgtWrTg6NGjNG/e/N8+nXLjv/I5/i3IHR8eBY4HlQJnrL/4GyC1/BUkgwh8xP8dYcmSJXz00UdAadZekDeWuHLlCq+++ip5eXnExsaydOlSevToIUt1U1RUxLZt21i4cCGFhYV4e3vToEED6tata9WOVqVSERgYSGRkJN26dWPYsGEMGDCAhx9+mJCQEIqLi/njjz+cvldKSgrbtm0DYNiwYS7PrbCwkBkzZgClwUp6eroUfGm1WqKjowkICChTU+3uAuxWyMRotVoiIiJktS129/MINU9qaiq5ubmSqkmj0ZCVlUVmZiYKhYLhw4cDpSqB8gTpR48eJSsri+Dg4ApNbllZWZw4cYLc3FxUKhWNGzemVatWVK9eHYVCIf195cqVZGRkODxOUlISc+fOZefOnWRnZ6NWq3nwwQfp1asXXbt2pXfv3jRo0ACFQkFycjJLly5l9uzZHD16tEIduR577DHee+89tFothw8fpk+fPrJUF4GBgYwZM4affvqJOnXqkJCQQL9+/STSVg7EvRERESE7q327oKLPAVcZYJFxjoqKQq1WS0bsULpImDZtGgDr1q3j+PHjst7z8OHDmEwmatWqRfXq1WWf6++//8727duB0q6ElVXOaAlfX19pjoDS8smVK1e6rQDw9fVl7ty5dO3alZKSEiZOnMjHH38si1iaOXMm99xzD1lZWfTq1QuTyYRKpbL6jkX7aUtyU4yLnJwcSTEgtnWkpr0dYTsv3Ui4Upbq9Xp8fHxIT08HkAi68uDkyZOyyBtHyMrK4u233+bEiRP4+voyYcIEWeRNZaN27dr079+fqVOn0rNnT6pWrUphYSF79+5l+fLlspU0UNrtTZR3Lly4kI0bN8reNyoqik8++QQoLYn/+eefOXv2rKQEdQR7MbLlGLT8v3h+e+Y0Dzz4b8ND4HhQKXC2kBZ/i4iIkCYWEYTodDoSEhK4fv06CQkJdiexPXv2MHbsWAAmTJjAc889V2abpKQkXn31VXJycoiJieGjjz5ympG0xKVLl/j44485cOAAZrOZsLAwmjZt6lQNIKBQKAgNDaVp06a0adMGgD///JOCggKH+4iA4Z577pEVzCxfvpzk5GTCw8N55JFHCA4OtsrWaLXaMhP21atX3Qqwb9WAvDID59TUVK5fv47BYKCwsFBqxy4WOcXFxeh0Orp3745Wq+XMmTOSEbE72LNnDwAPP/ywFTkoF2azma+//ppTp05RXFyMVqulWbNmhISE4O3tTb169WjevLkUuB8+fJh3332XzZs3W42v7Oxs1qxZw4wZM7hw4QIqlYpmzZrRv39/YmNjJeIzLCyM9u3bM2DAAO688058fX1JSUlh/fr1TJs2jZ9++snp/e4MLVq0YNOmTVSvXp0rV67Qu3dvjh07JmvfqKgovvvuO4nE6dKlS5kSRtHFLiEhgbNnz5KQkIBOp7PyjRIeALfavX+zwN6zw55KRnwXer0etVotKbyys7MxGAykp6ej1+tp3rw5ffr0AWDixImyzkH437Ru3Vr2eV++fJl33nkHs9nMnXfeyQMPPCB7X3ehVCrp0KEDTz75JN7e3ly4cIHRo0eX8VdzBW9vbz766COpBHHBggWMGzfOaQkilJI/q1evpmrVqpw6dYqXXnqJ0NDQMi3gBaljWYKr1WopKirCx8fHyvz7Zi+3vZVhb0xZjh/b8SX+ptPpMBgMKJVKKclT3hIqUTZVXvLm6tWrvPHGG1y+fJnAwECmTJlCixYtynUulQWNRsODDz7IxIkTGTx4MCqVipMnT7Jo0SKXY8gS7du3Z9y4cQCMHTvWZdLOEp07d5Y6iC5btkxWqbe9bSzHoGc8euDB7QcPgeNBpcDZQsheRlej0UiLV19fX7Kzs/H19ZW6CqSlpZGRkcGBAwcYOHAgRqORJ598UvJIsERKSgrjxo0jIyODunXrMn36dFkL+sLCQjZv3syiRYvIyMggKCiIIUOGSK3K3UXt2rUJDQ2luLiYP//80+F7rlu3DkBScjhDQUGBpL4ZPnw4jRo1QqVSSZ/PkXrJ19cXk8lk1yvGHv7LAYD47OLH1UJdrVZTq1Yt/P39pXs2NDRU8mQKCAiQvHBsO7u4gslkYu/evUBpt6XyfJbp06ezfPlyoLRE7s477yyjPFGr1cTExHDXXXfRoEEDSkpK+OGHH3jnnXfYs2cPO3bsYOrUqRw6dAiz2Uzz5s158sknad26tdTO1BYBAQG0adOGN954g86dOxMQEEB2djbffvstH374oaSCcBcNGzbkq6++omnTpmRmZjJw4ECppMUVLEmcK1eu8Nhjj3Hu3DlpoSMC3+TkZIqKikhOTnYaCNviViU2KwNyP7u96+fj42NFlInjGY1GMjIyMBqNpKenk5GRgY+PDwaDgZKSEtLT00lPT+ett97Cx8eHvXv3snv3bpfnKlp5y/W/0el0TJw4Eb1eT61atXj88cf/kdKdO+64g2HDhhEUFERSUhJjxozh6NGjbh1DqVTy8ssvM23aNLy9vfnuu+8YPHiwVDbrCNWrV2f16tV4e3vz1Vdf8f7779v9jnQ6HYCUkNFoNNSqVYvAwEBZykcPnEPOuBJjKjU11UplIZ5dtsklnU5Hamqq1I5arVZLJE95TIwtPW/KQ94UFhYyZcoUUlNTqVatGu+//z4NGjRw+zxuFBQKBc2bN2fkyJH4+Phw/vx55s+f71b8M2HCBDp27EhBQQGDBw+Wxo0cfPTRRwQEBHDp0iX2799PcXGxQ8WjiKmLiorKbCO+Y8949MCD2w8eAseDSoMcEkAEL1BqWikWxA0bNpQCBKHMycnJYdCgQeTm5vLAAw/w+eeflwmy8/Pzee211yQvjJkzZ8qqqc3KyuLTTz+VMrf33HMPY8eOpVGjRuX9+CgUCinD9Mcff9gtrzl27Bh5eXlERETI6iSyePFirl69SmRkJC+++CJardaqRMBeZkaj0eDv74+/v78V0ePsu/mvBgB6vZ64uDhycnJIS0tzeQ0EOWZrLKjRaIiKipLMTYXx9NatW7l+/brs8zlz5gzXr19Ho9G43S3HbDYzefJkDh48iJeXF/Xq1aNBgwZOjSADAgJ46aWXGDlyJJGRkRgMBrZu3cr27dspKiqidu3ajB07lmeffVZ2gK7RaHjkkUd444036NOnj+S7tHHjRhYtWmRXfeEKERERrF27lvbt21NUVMTLL78sW5puSeLExcXxxBNPSB2pBFFco0YNfHx8qFGjhvQ3MWbs3fuW5XT27pnbgdiRS+raXj97ig34W+EREhIi3bM+Pj4UFRUREhIikeYlJSVERERIKpO3337b6fsXFxdLqi25BM77779PamoqNWvWpG/fvpVqpuoKNWrUYNSoUcTGxpKXl8ekSZP45ptv3D5Oz549Wbp0KYGBgRw/fpxOnTq5VBHce++9UgnHO++8wx9//GFVFiWy+YBV0sU2CVOeMrvbYczIgZxxJcYUYNV5ysvLi7CwMKkU3RZqtRqVSoWPj4/0HHZXgZOdnU2PHj0kw2J3yRsoLRPOyMggNDSU999/362yxn8SDRs25MUXX0Sj0RAfH8+CBQtkJyGUSiULFiygbt26JCUlMWrUKNkl1dWrV+edd94BSlV0otubgGViTpTE2eumKYi8yix/94xTDzy4NeAhcDyoNMghAUTwYrl4Cg8Pl35EcBIWFsby5ctJSUmhdu3arF271q4y4KOPPiIpKYnw8HBmzpxJlSpVXJ5nTk4OixYtQqfTERQUxLBhw+jVq5ds/wxniI6OBkqN++wFApmZmUCpWseVN098fLw0yY8ZMwaTyUSVKlWkYEoQYbbBnFarpXbt2kRERFgposR728Ot4H9THgiT2sLCQsLDw13en0IFZhu8WPpDQKkPS8OGDTEajRw5ckT2+YigukaNGlILa7m4fPky58+fx8fHhw8++EDyunEFhUJBkyZNmDBhAgMHDiQkJISQkBAGDx7M2LFjqVOnjlvnIeDl5cU999zDuHHj6NKlCz4+Ply6dInZs2c7NLR0Bo1Gw2effSb5W61du1b2voLE8fX15cKFC1y9elUy+RSd7GJiYoiOjpY6VokFlL1739a3y/ae+S8r1gTkkrr2Fve2ig3xelhYmPQjyqfE30JDQwkNDcXLywu1Wi1dW1f3eEFBgVTCFxUVJeuziQ5y/fr1qzTzUHfg7+/PjBkz6NixIyaTiXnz5rFs2TK3FWytW7dm/fr1hIeHc/78ebumz7YYPnw4DzzwAGazmVOnTll9b0ql0q1SEndwO4wZOZAzrux5dNmOH8vnVVhYGBEREURHRxMaGirN9d7e3m4TOL///jsZGRnUqFGDTZs2uU3ewN+G376+vje9SW2tWrV46aWX8PPzIyEhgX379sneNygoiFWrVuHn58cPP/wgWzkK8Nxzz9GgQQNycnI4fPiw9LpoTJGbm2uVhLCNzW5U0s0zTj3w4NaAh8DxoNJgG8jbY/LFpOOIKBCEjpeXF4sWLQJg8uTJdokZ0QkIYPTo0bK6yOTm5rJo0SLS09OpUqUKzz//PPXr13f7szqCmPREJswWltfGFUaPHk1+fj4tWrSgc+fOkmGs+JxigSl+ty2lsp2I5ZBb/zVotVoCAwOpXbu2RBI6u/eE941t8GLpDwFQrVo1GjZsCMjvlgF/y9mdmQo7guii1qxZM2JiYtzeX6lU0rp1a6ZMmcKUKVNo2bJlpZSNqFQqHnroIV555RWio6MxGAySt467QaBKpWLChAkoFApOnTrllropKipKUtAJAkfA0j9CBMTOAl9b365/Kni+mVARUlfOvgaDQVJ9iNIp4dtx6NAhli5dCsD06dNdvpeA3KyxUL9ZLpz+afj4+DBu3DgGDRoEwIYNG5g9e7bbxuj16tWT1EozZ86URcCIjm62RsaALO+38uB2GDNy4M64crat7TPNktS5fPkyUJoocldddvbsWQBatWpFUFCQW/sKNG/eHG9vb65evVrGl+xmRGRkJO3atQNKG2a4MwYbNWrEiy++CJTGqnIJUJVKJZVR796926rc3Wg0cu3aNcC+xyHcuKSbZ5x64MGtAQ+B48ENgz0m35lDflpaGmfOnCEtLY1Zs2aRnZ1NbGwsvXv3LrOt2Wzm1VdfpaioiHvuuYf777/f5fnk5eWxaNEi0tLSCAoKYvjw4ZVOauTl5QFYtRG3hPjcrhYaV65cYdeuXXh5eTFu3DiJQBCZ6fz8fAoLC60IIdtSKsuJ+HadlN0NlmvVqkVAQIDdYMmy3a5SqZQ6SImAVw4EgZOZmel2BydB4Lhj1GoPCoXihvh9hIWFMWrUKDp06IBCoWDv3r2MGjWK06dPu30c0Q3InWwoQGxsLAB//fWX1euW40Moc5wZF7u6b/6rirXyQq7sXq/Xk5iYyB9//MGZM2coKCiQlIjCAycvL48XXngBs9nM4MGDadu2rdNjqlQqST0plzAUi7Xff/9dIsL/DSgUCp566inGjRuHSqVi9+7d/PTTT24fp0+fPkRGRnL16lVZKhxxvSzNx/V6PSaTiZSUFLv7VLS0wjNmHKM811b43ggSR5gYp6enc+rUKYByqSvPnTsHUKFyco1Gw1133QX87U9VUVy7do2kpKRKb88u8OCDD+Lt7c2pU6fcPufRo0dTvXp1EhMTWbNmjez9HnroIQAOHDhgZayvUqkICgpCp9M5fKbdqFInzzj1oLJw5swZjh075vQnISHh3z7NWxYeAseDGwahaJDb4UWn01FYWMj58+clZc3kyZPtZpC++eYb9uzZg4+PDy+99JLLBWl2djaLFy8mNTWVwMBARowYUe7uDM7gisCRq8ARRrcxMTG0aNECtVpNSEgIarXaqk24IBrsyWzFRAxI3UQ8k7JzuApexLXXaDRSBzF3CJwqVaqgUCgwmUxOS9psodPpuHTpEgqFgpYtW8re75+GSqXi0Ucf5fnnn6dq1aqkpKTw6quvsmLFCrcWyu3btwf+HgdyIRYdf/31l13VjS3h6ZGJVw7k+p8lJSWh0+m4du2apP5o0KCBVDoVGhrKp59+ysWLF6lWrRofffSRrPe39PqSg4YNGxIeHo7BYJDUCv8m/ve///HUU08BpZ4YYh6RCx8fH1599VVAngpHlI0JxZNeryc9PZ3r16+XUV248oPyoOKwHT/uLs4tu3oajUaJhKkIgVMelaclRKKhMgic9PR0fvvtN44cOcL+/fvJzc2t8DFtERAQIHloCfWfXGg0Gl555RUA5syZI1uF07ZtW5RKJfHx8Vy9ehUofZZFR0ejUqmkTpgCwhtHKBc949GDmxFCDThw4EBatGjh9Cc2NtZD4pQTHgLHgxsGYbpmryQFynZQCgsLw9fXlzVr1pCfn0+zZs14/PHHy+yn1+sZP348AK+88opL34OcnBxeffVVUlJSCAgIYPjw4eXqzCAHIvB2pHQRC0hXk65oNd2xY0f8/f1Rq9UYDAap9Mae740jZZNnoq88WJZSNW7cGCgNeOWqaby8vCTVlztdK4T6plGjRjesxKEyUadOHT7//HPat2+PyWRi7dq1jBs3juTkZFn7P/LIIwAcPHhQWmTKgaUCx1Z1Y2tKfTsq0m4U5Cj8hBmnUqmkevXqhIWFUa9ePUkRFRoaSkJCAvPnzwdg7ty5shWScpWNAgqFQlL2iAXrv40+ffoQFRVFZmam1GXOHQwaNEi2CsdWgSPUN4GBgSiVSrf8oDyoOGzHj5w5W/jeiOea8A5UqVSkpqYC7hM4ZrO5UhQ4AC1btkSpVBIXF+dQ1SUHJpPJqk13eno6+/bt4/z58+XqeugMDz/8MCqVikOHDrmtHH3qqaeoXr06V69ela3CCQ4OplmzZkCpCkdAkDgBAQFlSkTFfXG7qqo9uPkRHR3NmTNnOHr0qNOf1atXW3U+9MA9uN8r2QMP3IBoLW45yYhJNz8/H6PRKJE4onuSCF5feOEFKSthiY8//pjExERq1KjBgAEDnLaZNRgMLFy4kKSkJKCUYJk9e7bTc5a7QO7cuXOZ14qLi4FSXxqx+LBUHgjjWr1eT3FxsZVyyNvbW9peyOh79+4t+RVYPuTk+P2IY1t+B/9Eq9wbAbPZfMOk0yKbJSCUSvaulaXqqW7duvj5+VFQUEBiYiJ169Z1+j5CSRYWFkZGRgaZmZl21WXx8fFlXhP3Q6NGjaS/16tXT9bnk7sYlOtVYO++t4eUlBTuvvtu/Pz82LNnD2fPnmXUqFEMHDjQKssvOnpZIiIigmrVqpGSksKuXbt44IEHZHUyadKkCVAq3fX29pZKDf38/KwCYZPJJJUi2hqCgnU75YiICFnKNXF/ivvJkeLtVh2DzmBLTGs0Guk6CILG398fpVJJtWrVACRiTZRQXb9+nWeffRaj0Uj37t3p1KmTVYmPgL3ngBiTeXl50t8jIyOdnvMTTzzB5s2bOX/+PFqt1qWp/Guvveb07wJVq1aV9R0PHz68zGsPP/wwq1at4ptvviEiIoIaNWrINmYuKSnhpZdeYuLEiXz00Uf06tXLrlG6RqORFDh5eXmkp6ejUCikzoViPJjNZmkcGAwGatasKZWRWn4H/8X7+UbC3vPBdvzYi5tsr7PlXCR+h9KYRxDltWrVcphcsEd+JCcnk5ubi5eXF3Xq1MFkMsn2IbNNioWGhnL33Xdz7NgxTp06JT2b5XrybNmyxeHfTCYTf/31F3/99RcXL16URWJERETIet+HH36YPXv2MG/ePCZPnuxwO3sq6+eff57Jkyfz8ccf061bN0mt6wwPPfQQR48e5eDBg4wYMUJ63c/PTyJac3NzJY8ws9ksJUedxYGVHS/JOd6NitE8uPUQHR0tNXXx4MbAo8Dx4IbCUUmKTqcjKSlJ6sojOvxMmzaNgoIC7r//fsmnwBJXrlxhyZIlALzxxhtOO4gYDAYWLVpEUlKSRF7c6GBTdDdx1HlBXAej0ehQZnvkyBGysrIIDAyUVB5iX9Hm2h1otVoiIiL+M5mayq79FtlOnU4nW6mk1+vJzMwsl5GxWASlp6fL2t5gMHD+/HkAmjZtKvt9bhbExMQwaNAgIiIiKCgoYPv27S4VSwqFggceeACAX375RfZ71a5dWyLVUlNTpY5Ttioeg8FAfn4+Op2OxMTEMveSeD458yBwhNtV8Wb7uW07DlqqoOx5ds2ZM4fTp09TpUoVZs2a5dZ7y1U2WqJly5YEBQWRn59PXFycW+/nDNevXyctLY3MzExyc3MxGAyyFXp16tSR/J+2b9/utsJgwIABVK9enWvXrjnt4iYWhnl5eVKCQQTcthl/k8nkdsc8d3C7tS129HywfL2iPiRXrlwB3FfgiHLgunXr2u366S5EDOfOM9xd/PXXXyQlJVWaGqdv375AqSLG3dKOvn37Uq1aNa5du8bGjRtl7SN8cH755ReHBIjBYCAvL096jjhStf8buN3Grwce3CzwEDge3HDo9Xri4uKIi4sjLS1NWhxZKhJUKhXx8fFS7fHUqVPLkC1ms5n33nuP4uJi2rVrJzn420NBQQFLliwhMTERjUbDiBEj/pFMoajNdtR60zLj7KiOW5RPtW7d2orksS0DgbKT5+0wmVb2AllIkUULezlEl16vJzc3l5o1awJlTXOdQWQq5cpGz549i9FoJDw8XFJj3WoIDAyUMpLXrl2TFdBbBv9yg3OVSmXlg6NWq6W21JZQq9VotVqKiookIscWfn5+KJXKchGmt6O03fZzu+o4KMh7KL3Hhe/Zhx9+KDtbLuBOdz8Bb29vHn74YQDJ9LWyIAj6/Px8srOzJX83OejYsSN+fn6kpKRIpZNy4evry+jRowH49NNPHb6nGA/FxcXSd2TpGWWJwsJCq7IqR9uVF+J5npqaWqaT4n8Rjp4PlfXcyM7OlpIDtWvXdmvfyvK/ERBliqdPn76hZRLXrl3j9OnTleKNU7t2be677z7MZrNsEkbA19eXUaNGAfDZZ5/JGvP33Xcf3t7eJCYmcurUKakjX3p6ujTG1Gq1pJDTaDRu+ee5C3djyNs1YeGBB/82yk3gfPrpp9L/S0pKeOedd6hXrx5qtZomTZpIdewe3H6wnQDy8/PJy8sjLy+PtLQ0jEYjarUaHx8fQkNDJYn9tGnTKC4upkOHDjz44INljrt7925++eUXvL29eeuttxwSMoWFhSxdupT4+HjUajUjRowoI6c3m82YTCa7PwaDgcLCQoqKiigpKcFkMsmWhrpS4CiVSoncEdvaQhA4bdq0cZmBy8/PJycnh7i4uNvG2K6yF8gi2+mqzbjtPllZWZJEtDydqOQGtH/++ScAd9xxxz9arlDZZWtBQUF06tQJgKNHj3Lx4kWn2zdv3hyNRkN6erpbCiehWvvrr78kbxXb71Sj0RAdHU1kZKRdFV9YWBjR0dE0bNjQ7Sz47drFw/Zzu7oOolTVZDIxfPhwCgsL6dixI/3793f7vd01MRYQSYDTp09X2r0uymcDAgIkAtFsNpOZmSnLz0mr1Urn9eOPP7rtHyJHhWPZtUvMv/ZUUfn5+fj6+qJWq512PKwIxPMc+M/PXeB4XFTWc0OoycLCwhwmkhyhsvxvBMLCwqTSqf3791fKMW1Rr149vL29KSgo4OzZs8THx7vd4dEWoqx37969kp+QXAgVTkpKiiwCSKPRSIbPe/bskbrxlZSUSM8LjUZDzZo1qVmzJlqtttK7p1rC3Rjydk1YeODBv41yEzivv/669P+JEyfyxRdf8Nprr7F582aGDh3Khx9+yIwZMyrlJD24tWA7AWi1Wil7EB4ejkqlombNmjRq1IiwsDD0ej27du1i27ZtQKn6xhZZWVm8//77ADz33HMOM0slJSUsX76cK1eu4Ofnx4gRI6hRo4bVNq4WpqK8Ii8vj5ycHLKyssjJyXEZ4KelpUkZF0cETklJiSRZt5ctys7O5tChQwA89thj6PV6l4HytWvXJE+P22EylRvousoklUe9ZOmNEhoaKmUq3cngixIq4cvkCkLd4+ieuhEoLi4mIyODjIyMSm2zXL9+fVq0aAHAjh07rFQYtvDx8ZG6grjTTlwQOIL4Eh127H2vYWFhhIeHS9+JgD21mwflh6VqQ/wUFRWh0WhYt24dBw4cQKPRMGfOnHKRlJYeOO6gbdu2eHt7k5GRwbVr19x+X3sQ3WO0Wi1BQUGEhoZKhEl2drYsEqdZs2ZERUVRVFTEu+++6xa5ZKnCmTt3rt3FrGUJlWWJmz3FVEZGBpcvXyY+Pl569jlTVrkL8TyPiIj4z89dlQ3bRhDwN4Ej1KHuoLIJHID7778fQIprKhshISE0bdpUeoanpqZy5syZCpVUxcbGctddd2E0Gvn666/d2tdShfP555/LIpNEwvLgwYOSYjQ7Oxv4e/4SP3BjzcTdjSFv14SFBx782yg3gWMZUCxfvpytW7cycuRIOnXqxNixY9m2bRtz5sypjHO8YbD8DB7zrcqD7QSg0WioXbs2tWvXlhZLlg/769evM27cOEwmEz179uSee+6xOl5JSQmvvPIK165dIzo6mpEjR9p9X5PJxPr167lw4QI+Pj4MGzbMpQGk8MWx9Mfx8fHB29vbpamlJTIyMli1ahUAUVFRduvHi4qKeOWVV8jPz8fHx6cMsQSwevVqSkpKaNy4MeHh4VLJmTNUr15dKvXwTKZ/w1UmyZFnh6tWyLm5uSQkJKDRaKSuFadOnZLdtaJ58+ZAabZNTomEyLZt2bKFxYsXS53IbhQMBgOZmZkYjUaMRiOZmZmSOXdloF27dlSvXp3CwkK2bNni9Hr/73//A+Crr76SLRsXsv1t27aRkZGBwWCwymZawkPU/DOwVG2IblTidUvz519//bVcxxeLN3fVKmq1WjIfF74hlQ2FQkFQUJB0j+Xk5LgkRRUKBV26dEGpVPLjjz+yadMmt95zwIABqNVqrl69ardNuiCef/31V4qKigD7Y0EkXLRaLVevXpXO+0aMGTF3eQgc+bCnhhIxz59//mn3u3cG8Z3KNS52BZPJJBE3NzIBIUyXGzZsiJeXFwaDwW3ljC169+4NlKpw3FX09O3bFx8fH65duyarOYBQoJlMJkkxKoz+xfwlVDnADY3xPDGkBx7cGig3gWOZJfPz87MyW4VSs83KqEe9kUhNTSU5OZkLFy5Uapb5doc7ConU1FRGjx5NfHw80dHRfP7552W2mz17NgcOHECtVjN//ny7JQ9ms5ktW7Zw4sQJVCoVzzzzDLVq1bK7nVgw2JI3CoUCpVIpqYWER4/o0OEoM5yVlcXKlSvJy8sjIiKCfv36ldmmsLCQl156iV27duHt7c2cOXPKdBAwm80sWLAAgGeffdbu9bL1HtBqtQQGBlK7dm3PhGsDV5kkR54d9ra3VN4UFhZKpp5NmjSha9euACxevFjWeTVv3pw+ffpgNpuZOHGiy4z8yy+/TIcOHVAqlZw8eZL333+fvXv3VnoLVbPZTE5OjvTc9vHxkco/srKyZHt4uIJKpaJbt25otVrS09OZMmWKw8/y8MMP06BBA/Ly8mQnBO6//37uuusuDAYDixcvduiDU1HcDn5TlQVbdUdWVpa0+OzUqROvvPIKACNHjmTv3r1uH190ZHN3wQp/KxXkdmErDxQKBQEBAfj4+EjjSRAnjlC1alXat28PwPTp0936bL6+vlJMZk8d2LZtW5o2bYper3faclyj0RAZGYnRaKRKlSqVqrzxoPwQyhv4e/EvlDgtWrSgQ4cOlJSU2FUzO4MgzHfs2FEp57l9+3ZOnjyJn58fQ4YMqZRjOkNQUJCUGLt27VqFSqlatGhBUFAQ2dnZHD9+3K19fX19JZW4aEDgDKKFuEg+2M5Z2dnZ0msegtMDDzyACipwEhMTSUhIoE2bNqxbt87q74sWLZJqX29GbNiwge7du9OkSROaNm1Kly5dWLhw4b99Wjc13FmwyClfOXfuHGPGjOH777/Hy8uLtWvXlmlFuX37dqnr1LRp0xxKe3ft2sXBgwdRKBT0799f6g5UXog234AVmWOLnJwcVq1aRU5ODmFhYQwcOLDMBGswGBg1ahQ//vgjvr6+fP7551Jgbol9+/Zx5swZ/P396d69u2R4bOk9YDQarRQLnmyJNSzvO3FtALv3ojPPDluyTCw2obRbS0BAgLSfaAe8bt06h75GtpgwYQKRkZEkJye7fO74+vryxBNP8Prrr1OvXj2KiorYsmUL33zzTYWzjAKFhYVkZmZKbZtF+UdwcDDe3t6YzWays7PttnUuD/z9/enWrRsqlYoff/xRMi+3hVKplFqrfvbZZ7IUFgqFgpdfflnax8vLq4wPjvh+xY9Qhrhjzno7+E1VFJbEp6VqQ/jfiBK6GTNm0L17d0pKSnjqqac4duyYW+8jCJxLly65fY7/BIEDfytxlEolJSUlfPfddy6Vv/feey/33XcfBQUFjB8/3iXpYwnRsc4egaNQKHjppZeA0jKP69evlxkDer2es2fPcvnyZYKCgggLC/Oo1f5hOIqjLOcjjUaDTqcjNzdX2u6dd94BYNOmTfzxxx+y3+/RRx8FSpVZcucyR9DpdNLcNnToUKpVq1ah48lFWFgYvr6+lJSUVEhJ5OXlJXVC/OGHH9zeXyj7Lly44HQ7o9HIb7/9Ju0jnkNqtRqDwYBer5cUfPb83BzBk2DwwIP/NspN4BQWFkplMZs2bbJahEyYMIGJEyfetB44K1asYNCgQTz00EO8/fbbTJ48mYMHD/L8888zZMgQTzmVA7izYLE117WFXq9n/vz5bNq0CYVCwdKlSyW/C4EzZ87wxhtvADBs2DAee+wxu+914MABdu/eDUD37t25++677W5nT31jDwUFBZLaQKvV4u3tbXe7vLw8Vq1aRWZmJlWqVGHgwIH4+/tbbVNUVMTw4cPZv38/arWaRYsW2W2PDkjqo169elG1alWphaulR0F52ojfTrB3j5ZnoW2vBbLIPluafup0Ou68805JJWJLZDuCv7+/5CO2dOlSWW2Mq1evzpgxY3jqqafQarVkZWXx/fffc/DgwQoRK9nZ2Zw5c4aSkhJpkanVaiVFWnBwsKQ4ysnJkV0q5gqRkZGSWeuiRYsc+tw88MADklpg5syZso7dt29fqlevztWrV5k1axaJiYkkJiZy/vx5EhMTJTm6+FcsWN0xZ70d/KYqivz8fKnk0HIsFRUVYTAYpPtKqVQyf/582rZtS35+Pr169XKLjBEETnx8vNvlfoLASUtLqzSC0hFUKpVEXp08eZITJ0443V6hUPDBBx8QHBzMmTNnrJpHuIIzAgfgqaeeIjQ0lKSkJLZs2UJCQoJEBCQkJEjlu0VFRWRnZ3uIm38BlnNXfn4+8fHxxMfHA3/7EOn1enx9fSksLESj0VBQUECtWrXo1asXAG+//bbs9xNlSCUlJeVSwlni008/JT8/n5iYGHr06FGhY7kDpVIpqXBSUlIqpK5/5JFHgNIY011CSxA4rhQ4J0+eJDc3F39/f0JDQ6UurZZGxsIPxx14EgweePDfhlsEjqVBoMlkwmg0Sp17hAQQYODAgZw/f15ir28mnDhxgrfffpsPP/yQd999l1deeYU333yTAwcO8NBDD7F8+XJ69+5daeUC/yW4KjGxZPu1Wq1UamJvApk9ezbLly8HYN68eTz11FNWf09PT+eFF17AYDDQtm1bxo4da/ecvv32W7Zs2QKUyn+FYV55YTabrVo3igWGLUwmE6tXryY9PZ2goCCefvrpMjXeBQUFrF69mt9//x2tVsuSJUvKkFQCKSkpkonz888/D8DVq1e5evWqVScCexlQT6blb9i7R+UstO3dv5YBsqUSx3Kxr9PpMBqNPP3000ApESGXAO7YsSNt27aluLiY999/X9Z+CoWCe++9l7feeosGDRoApRm+LVu2cOHCBbfIZ7PZzLVr17h48SJGoxEvLy9CQkLK3PMKhYLAwEBJzn3kyBEOHz5cKUR306ZNpY4fb7/9tt3OVAqFQhoTS5culaWU8PHxkYwkV61aRXJyMnl5eaSnp0vzmFDmeHl5odfrSUpKIi4ujqSkJGkx62xM3Y7qN3efNZbzgCWBo9FoCA4OlhadUOqRsXHjRpo2bYpOp6NHjx6yFWbVqlVDrVZTUlLitpImICCA4OBgzGYzycnJbu1bHvj4+EhE//fff+9SJRAREcG7774LwBdffCHbJ0gQOH/++afdsapWqxk2bBgAS5YskcZHSkqKVNIYFhZGREQEDRo0uK3u838CcsaS5dwl/NdEiavwC9JoNAQEBEgdEa9evUpeXh4vv/wyXl5e7N69m59//ln2eQkVTkXKqE6cOMEvv/yCSqXitddec6hgvlEICQlBrVZjNBrd9sWyRGxsLHXq1MFgMLBhwwa39q1Tpw7gWoFz8OBBoLRkKyIiAqVSidFoJCMjg6KiIqljqyMjfkfwJBg88OC/DS93Nn7ooYfYuXNnmTIXW9xxxx0VOqkbibi4OPLz82nbtq1UO2w0GrnrrrtYtGgREydO5KuvvuLZZ5912ILTHgoLC61In4rKT/8JuLsAE4G3PaSmpkpdkKKjo/Hz8yMsLIz09HSpZbfAjBkzJHXWpEmTygTqJSUlDBw4kKSkJMLCwnj88cftZoPOnDnDggULMJvN+Pv789dffzlsN2zbecpVJ6q7776bzp0721XpFBQUsHbtWlJSUoiIiGDNmjVl/HaysrIYMmQISUlJBAcHs3XrVlq2bOnw/b744guMRiOtWrUiICAAnU6Ht7e31C3E0sjY39/falK2zLTc6pO1o3HkTDFlCa1WW+Ya2L5m73tPTU0lNzeXgIAAyU9IEBYiK52SkiLJwAWxo9FoyMvLo1+/fkyfPp2zZ89KZLAtIiIiyrz28ccfc//99/PLL79w5MgRunTpQrNmzVx+Tig1IhVjID4+XlLivPnmm1YB81dffVVmX7PZTEFBgeQR4OXlJSlS5OCvv/7i/Pnz+Pr6OvxeBg4cKOtYTZs2pV69ely6dIlRo0bxwgsv2L2P27Rpw8GDB3nnnXecKnGEoe3QoUP54IMPuHDhAgkJCdx7770olUrUajVVqlSxIlzPnj2LSqUiKyuLGjVqcPXqVSlwt1XVVRSVqfB0dKwbNR9ZPmvkLOg1Gg21atWSSHydTmc1HqtVq2Z1HJVKxbp16+jatStXrlyhT58+7Nu3z+o7cOSXVK9ePU6dOkVCQgKxsbGys9Y1atSgYcOG/P7772RnZ9s1lwfr+zkrK4vvvvsOk8mEt7c3sbGxxMbG4u3tzcmTJ12+Z3h4OPHx8eTk5LB8+XJiY2MdLnKjo6NRq9U8+OCD/PTTT4wbN4533nmnzH3ZqVMnq9/r16+PSqUiIyODxMREIiMjAazKsIYOHcrMmTM5duwYW7ZsoUuXLoSHh1NUVERERISs7/i/rFi+kXGdnHnbdu4S37ltgkL8HhcXh8FgoLCwkDvvvJPevXuzfv16Jk+eLBEqAo7GUdeuXZk7dy579+5FqVSW8epzBBGjmc1mPvnkE6DU06WoqIizZ89K28k9XvXq1UlJScFsNksdyuzh8OHDTo9z7do1rl27JtuDx9bMvEuXLsybN4/NmzfTvHlzQkJCgFKPKmcQf79w4YLT2EUQOG3atJHUgOfPn7ciURMTE/H19cVgMMhuDe8sXi8P5MRf5ekg6IEHHpQPbilw4uLiaNu2rdMMV0VllzcaFy5cID09nerVqwOlZIFKpcJsNlO/fn0+/PBDHnvsMdavX8+UKVNkH3fatGkEBQVJP+Vp4Xgrw2AwSB1fLCHk4gJLly6VyqLGjBkjZcktMW3aNH7++Wepk5S94CYuLo7FixdjNBpRq9UEBwc7nTzckZHWq1ePTp062T1eYWEhGzZsICUlhZCQEJYvX16GvMnIyGDQoEGcOnWK4OBgtm/f7pS8KSoqYtmyZQA8+eSTmEwmMjIy8Pf3t5L3JyUllfHAgf9WpuVmHEcajYbCwkICAwMlxYClGiooKIjAwEAGDBgA4JaXVr169XjxxRcBmDhxotsqqtjYWGbNmsUzzzyDj48Px44dc1mvbzQaJT8lKPXYEUShHAiFTklJCQUFBRVewKlUKvr370+VKlXIzMxk3bp1ds0nJ0yYAMDGjRtlldeEhoZKyqi1a9cSFRVFgwYNiIqKKhPYhoWF4ePjQ506daQOcbeyYeuNGkfledZYelFZkj+26iWdTkdqair+/v7s2rWL8PBwjh07xlNPPSXLjLQiPjii3EHuvsHBwbRv356QkBCKi4s5efIkW7du5dy5c7LMxRUKBXXq1MHb25vCwkLi4+NdjqO+fftSrVo1srOzWbFihcvt1Wo19evXB0oJV3uIiorizTffBEpbjmdnZ+Pv70+NGjVu2Xu/MnEj56PytGsWtgXOvhs/Pz9CQkLQaDS88soraLVaDh8+zKxZs2S9T+vWrQkJCSEzM7Ncrb//+OMP4uLi8PHxoXPnzm7vL6BQKCTSpjK7ILqLpk2bSmVlQiUtB8LEODk52WH8aTabJQKnUaNG6HQ6NBqNpCCC0u+9Zs2a+Pv7e8akBx54IMEtAufQoUOYTCbatGljxahDKYv8yCOPSC72Nyvuu+8+AD788EOgNPNsMplQKBSYzWbq1avHhx9+SI0aNVixYkWZz+kIEydOJDs7W/q50YaINxvUarXVpCPKTMSCV3S7EITNkCFDGD9+fJnjbN26VfKCGThwoN1saEpKCp999hlFRUXExMQQGhrqlLwR3XXkonv37nZbiBcXF7Nx40aSk5Px8/Pjiy++kAJkgbS0NAYOHMjZs2cJDQ1l9erVDj15BLZt20ZqaiqhoaFS69jg4GBCQ0Ol7CuUXmN7HjharZaIiIj/BIHzb42jiIgIqlWrZlclo9FoiI6OpmrVqkRHR1v538DfXUD69+8PlN7D7pRivPLKK0RFRZGUlMTHH3/s9rl7eXnRvXt3SSGwZs0ah52thPLGbDajUChQq9UOPZ4cwVIZZjQaMRgMFe6IpdVqGTRoED4+Ply6dInvv/++zDYtW7akQ4cOGI1G2YsRYdS6fft2zp8/L5VKJSUlWZFlYWFhxMTESD9CxXOr4kaNo4qUjbmzYK1fvz5btmzBz8+Pb7/9lldffdXlPoLAsVeGJ3dfdzo9Va1alc6dO9O2bVv8/f0pKCjg8OHDnD9/nqysLJcEi5eXl0QcZWZmSl2FHMHX15fhw4ejUqk4fvw4P/74o8tzFI0kHPngALz22mu0a9eOvLw8Jk2ahL+/f4U6tlVms4N/GzdyProRbdMjIiKIiIiQVPIxMTG89dZbAEyePFkWIaNSqaQyqu+++86t9zcajWzduhWA9u3bS62wywsxN1UGgVNeLxiFQkHPnj2B0jWQ3Lk9KCiIKlWqAI7LqC5dusT169fx8fEhMjJSmrfDwsIIDw+X5iFH5fNyIWec3exj0QMPPLCGWwRO/fr1OXToEPXq1aNdu3YcPnyY48eP06VLF9q1a8exY8ckY86bFQ0bNqRp06YsW7ZM8mBRKpXSgsZsNtO0aVNmz55NfHy8bALH19eXwMBAq5/bCREREVYTjjDWE2qF7777jpEjR2I0Gunbty9Tp04tQ7qcPn1a8rp54YUXaN68eZn3ycjIYN68eej1emrXrs2wYcNcyjbz8/Pdaidpz/empKSEL7/8UpKy9u/fn9jYWKttUlJSGDhwIBcvXiQiIoLVq1fL6oa1aNEioFSqazQaCQ0NtZJti8m8Zs2ahIWF/SeIGkf4t8aRRqNBq9WSn59vN4CxDaAsu4CEhISg1+sJCwujRYsWGI1Gh12V7EGr1fL+++8DpVnw8i4SOnfuTGRkJFlZWXz55Zd2tzGZTNLCUphilweixalCocBkMlUKiVOtWjX69OkDlJpG2luIv/baa0ApSeZIVWCJhg0bSubn8+bNIyMjQzKIdBXMumNobLvvvx0I/9vzkb1r4Ir8EX4rYg659957pTn6008/Zf78+U7fU5Dp5SFw6tSpg0KhQKfTuWUYqlAoqF27No8//jitWrXCz8+PoqIiEhISuHDhArm5uU6JHH9/f6KiogBISkpyuciMjo6WzGk3bNjg8lnhysgYShfsS5cupUqVKhw/flzqYOQKju5zd5sd3MxGq5U5jv6J54JtpyKNRsPYsWPp27cvRqORQYMGybq/hXLGHpHuDL/99hspKSlotVo6duzo/gewQWUSOK4Mw52hTp06NG/eHLPZzNdffy17P6HOdmRkLLxD77zzTqpXr14h4hT+bi9vO57kjLObfSx64IEH1nC7C1WVKlXYvXs3jz32GA888AAtW7bk999/55133iE+Pl5aiNysiIiIYOHChSiVSqZPny49jMVCRKBZs2b4+fnJJnBuR9i2bLZc4Iqyk/T0dH799VeGDBlCUVERvXr1YubMmWUULgUFBQwbNgyDwcCDDz5olwg0mUwsXLiQrKwsqlWrxsiRIx2aDFuionXrZrOZb775hitXruDt7U2/fv2kEjzL8x80aBBXrlwhMjKStWvXSlldZ/jmm284cOAAKpWKHj16oFarSU9Plz6XUDKJ66rT6TwT7A2CvQBGr9eTkJBg1UUHrLtSQWkJYUpKCt26dQNgwYIFHDlyRPZ7d+3alUceeYSioiLmzp1brvP39vZm8ODBQKmqS5hdWsLyGScM6MtbAqVSqSQSx2w2V4rxe9OmTSWjb3vZ36ZNm0rXeM6cObKOOWbMGABWrlxJYWEharUapVLpNJtp+/3KhV6vJy4ujpycnNt6nDpaDNguYp3NIXq9nocffljqovPyyy9LhvX2IAgcuWVMltBoNNIzXY6HjS1UKhWNGjXiiSeeoGrVqiiVSgoKCrhy5QrJyclWY0yUMKanp0vm2lA6z8TFxbkcjx07duSOO+6gpKREIrgcQShwXHWOq1mzpqR8nT17tsOFu+X3Jb7j1NRU0tLSpB/4W5Xojknvfx03aoHsrNV4eno6BoOBzz77jNq1a3PlyhVGjx7t8pjt27fH29ubixcvyo6BTSYT27dvB0r9mCpKRoA1gVPRUt3z5887VKbKgVBmC58tORBlVI4UOMKQ/I477pDIbZ1Oh06nIy8vj8TERKvvVXzXju4hR4kHMc4Aq7Fqud3tNBY98OC/ALcJHJPJxIYNGzhy5AiFhYUolUrWrl3LpEmTKiyX/Kdw33338dlnnxEfH8/bb7/N+vXrAaxIhfz8fCIjI4mJifm3TvOmg22g4CxI1+v1GAwGdDod33//PXq9nrvvvptVq1bZNaNbs2YNcXFxVK9enc8++8yuMuDChQskJyejVqt54YUXZJuLOjK/k4s//viDM2fOoFQq6dOnj5QxtcSyZcuIi4ujatWqrFmzRuoI4QxLly6VfFP69u1L+/bt0Wg0Vi1BhVeJTqcjMTGRvLy823pheCNhG+SI+1h0/rAlcCwXmyJYbdmyJfXr1yc9PZ2HHnqI+fPny+4uNW3aNJRKJQcPHnSrlMMSzZo1Q6lUUlxcbDdYtVSrGQwGaSFW3ntKqVRalVNVBkR3LUfBtjCjPHr0qKzjXb16FSh9DoSFhREVFUVkZKRVdzFbiO8XXC9CLZGfny+N39s5ELZdDIi5IzU11WrOcLaoFYuR559/ngEDBmAymejfvz979uyx+55NmjQhMDCQlJQUqYzDHQifsuXLl5OUlOT2/lC64KxatapVGV5GRgZxcXFcunSJv/76i9OnT3Px4kXi4uJISUkhKytL2t9e6a4tFAqF1LlNrgInMTHRpUH5E088wXPPPQfAyJEjiY+PL0O2xcfHk5ubKxnviuel6MgnVIm2nkcCtjHE7dTJ7UYtkC3HkCBtRPwl2lAHBQWxcuVKKV53VRoVGBgoqXCmTp0q29dJzHUVjbkEvL29USqVmEymCiuXXDWucIUqVarg4+MDWBuBu9oHsBrjlhDG4itXrpQ6hYmyZNENzpbAEWNNtJS3HF8ajYaioqIyc5utD5kYq7b73i5j0QMP/gtwi8D57LPPqF+/PoMGDUKr1fLtt9/SvXt3unfvXq6A6d/EgAED+OSTT7h06RKvvPIK7733HlA6CWVkZPDZZ5+hVCpp1arVv3ymNw9sg21HAYlOpyMtLY3MzEzUajV//vknUNrmW0yAltDr9ZLq4OWXX5YmPVuI+u0WLVo43MYewsPDpe5B7uLPP/9k586dADz44INSRsUS169fl4xrJ0yY4LCLiYDZbObdd99l9OjRmEwm+vXrx4IFC6RyM2FeLH4XZJZnYXhjYS/I0ev1qFQqAgIC7AY2er2ejIwMyXgwLCyMxYsX07lzZ4qLixk7dixPPvmkwwDOEg0aNKBr164ArFu3rlyf4fLly5hMJoKCgux2+1CpVPj4+KBUKq3InIoEtpV1HAHxvGjcuLHdv4sxeP36dZeBtNFolBQcI0eOJDc3F7VajcFg4OzZsxw6dMiqw5stRMAsl+DSarUEBga6NBr9r8N2MSDmDsBqzrBH9IhxJxYjBoOBjz76iMcff5yioiIGDhwolR5Ywt/fX/JY++CDD9wmFHv37k1MTAwGg4FZs2ZRUFBQ7s/v5eVFZGSktEATpIflNfD395cIxfr169O0aVNiYmJkdXIRC2RXJZBBQUESIXr8+HGXx50+fTqxsbGkpqYybNgwiouLrcg2yznI0sMlKysLtVrt9LsVx7hdyzQqe4EsyDD4e0zl5+eTm5srEZCi1BXgrrvuktrGv/jii3YVmpb44IMP0Gg0HDlyxGFJriUUCoXkgblz585KKXtSKBRSos5VOaIr2DOvdwd//PEHBQUFhISESN5VriDO19E4ffPNNxkwYABGo5H+/fvz7bffSsrWatWqUVhYaEXGCGUoYDexJMalj4+PROhZEqZiTIaFhXnUNh54cIvDLQLnxRdfxN/fn6+//prff/+dxx57jI0bNzJo0CB69+7tskb9ZoKXlxfDhg2TSqgmT55Ms2bN6NSpEz179uSrr75i48aNLhfjtxNsFQqAw4DE0oxNeBI4IsNWrVpFamoqUVFR9OvXz+42BoNBqmEWJRZyoVAo3DZqNZlM7N27l2+++Qaj0UhMTIzD9/34448xGAzcfffddOnSxelxzWYzL730kmSiPWrUKMaOHUtqaqrDUjTxf6VSSc2aNT2T7g2G5X3u4+NDWFhYGfNiy6y0WJTVr1+f6OhooqOjmTFjBu+99x7e3t5s2bKF1q1bc+zYMZfvLTpS7d6926WpqT2IWvuGDRvaXQgqFAp8fHwkzx8R8FVE7l6ZrUOLiookb5s777zT7jZhYWH4+flhNpsldY0jXLx4kYSEBPz8/OjatStJSUlkZGQApVnR4uJipwSOCJjd6RTzX8xiVtS/Q4wp4ZVm+Xyz/N2yBEA8+3x8fPDy8mLjxo107twZg8FAv3797CqwRo0aRXBwMOfPn5eId7nw8vLi5ZdfJiwsjOvXr7vldeEIgqCJiIigZs2a1K9fnyZNmtC4cWMaNWpErVq1qFq1KkFBQfj6+soeS+KZI8fDSnjJyXn+aDQaVqxYga+vL3v27GHx4sVWhExAQAC1atUqc38HBwej1Wql71Io+8TzRcCS1LkZvKL+DVTW57YkBMV112q1FBUVSYkySz8cg8HAuHHjqFmzJomJiS69jmrVqsWkSZMAmDFjhtPnpMD9999PcHAwWVlZUnelikKr1UoqnIoQf7aehe5CfJ777rtPllIO/iZwHI1rlUrFokWLJBJnxIgR/Pzzz4SFheHv709ISAi+vr5lFGthYWGoVCq7CQzLOcuWMBX7ix/bcXy7jkkPPLgV4RaBs2bNGv744w+6d+8uvaZQKPj888954403eOmll6RWr7cKOnXqxKFDh3jvvfeIiIigsLCQu+++m4MHD7rsHnQ7wNajwFYabe+BHxYWhlKpxNvbG4PBIC0q7bXS1uv1zJs3DyhV39hT6AAcPnyY4uJiqlWrVqZtd2WjoKCATZs28dtvvwGlQUmPHj3sTsKnT59m8+bNQGk2xVUAvmnTJr744gvJg6l///4UFhY6NM+FsobQHtxYWAZJtj4otjXmIlhSq9VSJzaNRkNwcDBDhw5l586dREdHExcXR+fOnVm0aJHTLGLLli258847JdNsd2FJ4MiBQqFAqVSW28zYFhVV4Pz1118UFRVRpUoVh2WICoVCUja4KnUR5q2NGzdGq9VK5V4hISHUr1/fyjTXHiwJhpsxuP2nzqWiygl7RI1lmaLlHCPIU0GUZmVlodfrycnJYcWKFdx///3k5ubSs2fPMua8QUFBkufR4sWLpQWuXAQGBvLMM88ApR5M8fHx5fq8lggJCaFatWpUqVKlQsbhlhDqIjnHatasGSCPwIFSP44PPvgAKO3WeerUKacJG3eUNpb3we2qxklNTSUlJYXU1NQKHceWDIuLi5O6WQYEBFh1BBXlc4GBgVIHv0WLFrnsSvX888/TpEkTcnJyZPlbent7Sx2sduzYUWkqnICAAKBUdVJeH5uKJGMzMzM5c+YM8HcnWzkQ86EzwkeQOAMHDpSUODt27CAsLEwiamyfm1AaZ9t6MQJWRKq7ZXu365j0wINbEW4ROP3793e4QH3nnXeYN28es2fPrpQT+ydRq1Yt3njjDXbu3Mm+ffuYM2eO7AXQfx32HuiWk0J+fj45OTnEx8dLwbher0etVqPRaDh9+jRGo5Fq1arZ9Y5Zs2YN6enpREdHSx1obGE2myXJ/P3331+pGX97WLFiBZcuXZLaMz/44IN239NsNvPBBx9gNpt5/PHHueuuu5weV6fTSV10xo4dS8+ePQkICKCoqMhqkraFCPo95M0/C3utO23NbUXplKWCRZQSqNVq7r//fg4fPkz37t0pLi7m9ddfZ/DgwU47gVi2I3d3gX7u3DlAPoFTHtiSNJU5HsUis1mzZk6PW7NmTQCXLV3FAv+uu+6iXr161KxZUyLZYmJiaNasmeyW4ZUZ3FYWGfRPETiV7d9heS3F/y0ViID0mq+vL8nJyVIJxcKFC2nWrBlZWVl07969TNepESNGEB4eTnJyMt9++63b59a8eXPuueceTCYTS5curXB3tRsBcU7uKHBOnDghu6zs+eefp0uXLhQWFvL0009L5IA92FOdyblfPKapFYMtGZaXlycZYtsqbwSRGRoaygMPPEC/fv0wm828+OKLTs3nvby8ePfdd1EqlWzfvp2ffvrJ5XndCBWOUOKZzWYyMzPJyspye1zKVc3Yw2+//YbZbKZ+/fp2S5MdQZyjq/cWneAsSZyvv/7aYfdLS7LblRm/O4pQz5j0wINbB5XjNPb/GDVqFBEREZV5yH8Moo247f9vRVSGDwUgyaAVCgWBgYHScYXaQLyXTqfD19dXWtiIIFGpVEpZixYtWkgmcpcuXQKw6rjTr1+/Ms7+YjGakpJCcnIyKpWKkJAQ6XV3P+/06dOd/v3ixYusXr2a9PR0wsPD+fDDD52aWB86dIjDhw+jVqv54IMPHE7sIuv/5ptvotPpiImJ4YUXXgBKFykBAQH4+/s7NGV29jcPKh+O5P+AVHZkCUvFgE6nk9ohC4SFhfHll18yb948XnvtNb799ltOnz7NunXr7KrSevTowaJFi7hy5Qo//vijpAiwha2nRU5ODmlpaSgUCtRqtWRwaq+jmz1cv37d4d/OnTvHnj17MJlMFBQUEBAQYBWUCom7l5eXdD1cZXcFOnXqBJSavYpnQ58+fex2ehMQnlZxcXFlvEosF7WCwLnjjjsICAiQMrlQ1nRZmDrblpQVFRVJzzZnwa07c4YlgVGRYPlGkLr2Poe9+97Rc9fZ+LE8nuVnz8/PL0OUiu8iKSkJHx8fCgsLJS+qZcuWMXjwYE6ePMkTTzzBTz/9JHkj+fv7M3HiRMaOHcvy5csZNGiQ026F9soQ3njjDQYMGMDFixc5duwYPXv2pHXr1g6PYQm5qgO5Lantlf+K70ilUkl/d7QQF35MeXl5nD59mtDQUFnvu2jRIlq0aMGFCxf44IMPeOutt6S5X3w/6enpKBQKIiIiynx/ru5NR9s4m88t761bdZEZEREhnXtaWprTceIOROMDrVZr9QwUCh2RCNJqtUydOpV9+/Zx7tw5Zs+eLfmE2UO7du0YMWIEn3/+OVOnTuWXX36xe+2F1xLA008/zdy5c/n+++9p1KgRbdu2le5Zucqj9u3bW/1uNBr5448/OH36NHq9Hm9vb9q1a+eQgNfr9Vy8eBGFQkFsbKxs30Rbv0Sz2czvv/8OlLZXF3+X0wHV8nuQQzgtWLAAk8nE2rVr6d+/PytXrqRnz54YDAbpR/hNRUdHExYWhk6nIyEhQVLsCJRnDWNvTP4XxpwHHvwXUX5K2gF69+5d2Yf8R2D5sLuVyRtXcCfzK0wLnQVjGo2G6OhoKbAWQYJarcbHx0cqQ7Lnf/P999+j0+kIDw+XFnH2IFqg1q9fXyJDKhNms5mDBw+ydOlSDAYDjRs3ZsmSJU7Jm6KiIinoefHFF+2qiyyxY8cOVq9ejUKh4LPPPvOUQ93EKK/SQqfTUVRUZNcrwGAw0K1bNzZu3Ci1c23Xrh2LFi0qs61SqeTZZ58FSjviyC0DiYuLA0oD0Mpo4WqJRo0a0aNHD/z8/DAajeTk5FidlyX5XV78/PPPmEwmYmNj7UrDLSHk8HIVOHfccYfV65YtdqH0+0lKSiIvL6/Ms9Ge10RFUVmZzpsxoHbUXtpeVxTxHLS9rpaZ5+rVq+Pv7y+V1Pn6+hIZGcmuXbuIjY0lKSmJTp06WZVWjBgxgmrVqnH16lWpy6Q7CAsLY8SIEQAsXLhQlv/HPwl3SqhUKpXkJyV85OQgPDycZcuWAaVqwJ07d5KQkMDFixelLkdC+VFeVZq7SrT/QomHvVJ0AVfXw9nfIyMjCQsLK/NMECU1ll5GDRo04JNPPgFK/W1sSxFtMX78eKKiokhMTGTGjBkuP2Pnzp2pXbs22dnZvPPOO0ycOLHcnd0EVCoVzZs3p0OHDqjVarKzs/nuu+/Q6XR25x1RNhYUFFShrljnz58nOTkZX19f2rRp49a+chU4AraeOM888ww7duwgIyODvLw8UlJSyM/Pl5JF8HfckZiYaOXPV1n4L4w5Dzz4L6LSCRwPbm64attqz7HeUr5pb4IQwbZldg5KM/qio4yt0qCkpIQ1a9YApR3BHHnfFBYWSr4eoiVqZcJoNLJ582a2bt2KyWSiWbNmzJs3z2VZxaZNm4iLi6NatWqMHj3a6bZ5eXlSd5Rnn32WBx98UDp+cHCw1I3Eg5sD9tqJy0FYWJhkemwLnU5HUlISNWrUYOfOnfTo0YPi4mJGjRpld1HVvXt3QkJCuHr1Kjt27JD1/oLAsdcprTIQGRlJ3759JbVNTk6OpF6oKIFjNpv54YcfAHjooYdcbi8IHGeLgtzcXKkdu2gbLqDT6UhMTOTChQukp6eTlJSE0WikqKhIlsdHRaHVaq0y8f8l2LaXTktLc3sBIOYawKp81LJsIDw8nJ07dxIZGcmFCxf49NNPpf39/PwkleP8+fPL5ZvRvXt3YmNjyc/Plxa7NwvcIXDgbx8cdwgcgA4dOjB27FgAZs2axaVLl6Q2x2q1Gq1Wi7+/v9V9LPxY4uLiXD473VkcCiXAf6UTY3m6dDn6u1arlbz0xE9aWprT69qjRw+6detGSUkJI0eOdFpe5+/vLxE3CxYs4I8//nD62Xx8fJg3bx4DBgzA29ubI0eOMGzYMJYtW1ah7m4A1atXp2vXrtSoUQOTycTVq1eJi4uzSiiUlJRInR8rGlvt3bsXgDZt2rhN3gsCx52ksCBxRIwwfPhwrl69Sk5ODnq9vsycFxYWhtFopKCgoExXqorAXpczDzzw4OaBh8C5zeBsMeIqeLA1cLX9W3p6utViKCcnRyrjsCVw9uzZw7Vr16hSpYrUOtkezp07R0lJCSEhIS6z8u4iPz+fJUuW8Ntvv6FQKOjcuTP9+vVzKY3NzMxkxYoVALz11lsuy5veeust4uPjqVmzptTVAUoXIwEBAVKHIw9uDjjLkAo4Mu+OiYkpEzBamkgqlUqqV6/Oxo0bJbWi5T0h4Ofnx8CBAwFYunSpLGLkRhM4UJrNDAwMlBboeXl5FBQUVJjAuXLlCgkJCXh7e3P//fe73F4QOM66UImsctWqVTGZTGUylAUFBWRkZHDs2DHy8/NRqVRERUWVUS/9VztL3SiI6xUREYGXlxfh4eFuLwAsu7sJ/wuRdbYcjzVq1JAMd6dNm2bVua1v377UqFGDtLQ0Vq1a5fbnUKlUjB8/HpVKxb59+1yqFP5JuEvgiIYMclqJ22Lq1Km0aNGCjIwMZs6ciY+PjzSGRFfE+Ph46dpb+rG4ImbcIUeFIriySo7+bZTHO8jR30XplOhYpNfryc3NJSEhweo7sCR2FAoFn3zyCUFBQRw+fNhlF9mOHTvSvXt3TCYT48aNc1kS5Ofnx5AhQ1i8eDEtW7akuLiYtWvXMn78eH7//fcKqTX9/Px4+OGHadWqFQqFgtzcXM6fPy+1Rs/IyMBsNluV+5cHhYWF7N+/H4BHHnnE7f3lmBjbg0qlYvHixdx1112kpaXxwgsv4Ovri6+vL1FRUVblUqLkNygoSCqjE6iI15qt8tRD4Hjgwc0FD4Fzm8HZYsQ2OLA0lxT7OjJN0+v1GI1GkpOTyc/PJzs7W/K0qVevHiEhIVbbr1u3Dij1vnFWFiU8dJo2bVqppW15eXnMnz+fy5cv4+vry+DBg3nooYdcvofRaGTWrFnk5+dz11138eSTTzrdfvPmzZLPz8yZM1EoFJw9e5aEhASrVrke3Hxw1vLW3cxxcHAwoaGhNGzYEI1Gg0Kh4L333sPLy4sdO3Zw+PDhMvsNGDAAX19fTp8+LZl4O4LZbJbGW2JiIpmZmeX4xPKgVCoJCAiQiE69Xi/5fpTH8NVsNkud3Fq1aiXL70kQONeuXXPoOSJKL6Oiorh69SqZmZnk5uaSmJiIRqMhKioKpVKJRqOhqKjILnnjgfuwzNw6a1nrDJZzjfi/Xq8nISHBioTT6/U8+uij3HnnneTm5vLhhx9Kx/Dx8ZE6Ui1YsEAyeHUHDRo0oG/fvgBs3LiRnJwct49xIyAIHLmlIYLAuXjxolMDdXvw8fFh5cqVqFQqjh07xty5c/Hx8ZFUTTqdjsLCQkkxJVQ5tsoce3CHHL0dDFYFEeOoK6Wc+E2MmcLCQnx9fdHpdBJpY5uEi4yMlNqJv/3220590ADee+89/P39+eOPP3jvvfdklfdGRUUxbdo0pkyZQkREBDqdjjlz5jBnzpwKleUoFApiYmKoX78+vr6+lJSUcOXKFS5evCg9f0JDQysUN/7666/k5+dTtWrVcinAXbURdwatVsuGDRsIDw/nzz//ZM6cOdSoUYPo6GirpJ8welcqlWWSgRUpf7odxpsHHtzK8BA4HkiwDQ5sS6jsdeWx3Fd43/j5+RESEsKPP/4IlC2JKCkpkUobRMtJRxBBYmWaYxcVFfHFF1+Qnp5OlSpVGDVqFLGxsS73MxqNvPvuu+zbtw+VSsWHH37oMLNiNpuZO3cuQ4YMwWw2M3ToUHr37o1er6eoqIjk5GSrQOpmbFF8u8NZy1t3ghvL1sGWi8/69etL3iz2vFxCQkIkgnDKlClOSRmFQkHVqlUB2L9/P1OmTGHJkiWcO3eu0kzNbd/P1uwX5C8oBcxmM8uXL+eXX35BoVDQpUsXWftVrVqVkJAQSkpKHJJbwrD42rVr+Pn5UaVKFYqKiqRyzaioKJo0aUJAQIBsg0sPXKMyPBMs5xrL/6vVaol0g9Lnpslkkjyjdu/ebXWcHj16ULt2bTIzM8ulwgEYMmQIUVFRZGZm8tlnn90Uz+iMjAwA2eb2YWFhREdHYzab+fXXX91+vwYNGkjtk7OysqQue+LYvr6+VoqA2rVrS+bJlYXbRQlX3vEjro8wmxXehPB3Rzd7Sbg+ffrQuHFj9Ho9e/bscfoeVatW5aWXXgJg7ty5dO3aVTKedwaFQkHbtm1ZtmwZ3bt3R6VScfjwYd544w0pFiwv1Go1DRo0kJKEIpno6+tLcHBwhY4txlmjRo3K1cVKKHltG2/IRXBwsPRdmc1micCx9QtzpOSuCAlzu4w3Dzy4VeEhcDxwCHsPcOFNIH7E7yL7HxUVRXh4OJmZmVJWXQTXlscQcDXBigC1PNlTezAajaxdu5akpCQ0Gg3PPfdcma4DjvZ799132b17NyqViqlTp3Lvvfc63HbChAlMnjwZgKFDhzJr1izgb5+UGjVqlPEX8hjF3bywDYTcCW7EItRkMlkZEOr1eqnEsE6dOnb3HT16NNWrVychIYGRI0c69fIYO3Yszz77LPXr18dkMvHHH38wb948Pv30Uw4dOlRh7wFbiG5XItMeHBxst2OOM1y/fp2tW7cC8MILL9CkSRNZ+6lUKons2bZtm91tunTpgkaj4erVq2RkZFCzZk1q1qyJSqWSTFhDQ0OpUaMGQUFB0mtJSUkkJSVJ19pDrrqH8iwaHPmrWSIsLIxatWrRqFGjMp44orzhzJkzVs9QLy8vacG5ePHics0jarWaWbNmERAQQHJyMosWLbLbueqfhHhu1KxZU/Y+goCR0wraFkajUVqE9uzZ0+pv4eHhxMbGutVe2QPHkDN+5DyThHlxWFiYFGtYGhpbdhETSbaff/7Z5fm98sorfP755wQGBnL06FEeeeQRvvjiC1mJAj8/P/r27cuUKVMIDw8nLS2Nt99+uwzx6i6USiVRUVHExMQQGRlJVFQUDRo0qFDrcPg7Pi2v8k7EiD/++KPb6lTR5l2U3zvqFOYqseohYTzw4L8JD4HjASB/kSKIBp1OJ2V1hAt+RkYGarWawMBARowYQWFhIe3bty/TgUrUKavVapcZe5FBEvtUBGazmW3btnHmzBm8vLx45plnZBnc2SNvHBmt6vV6nn76aRYvXgyULqpff/11qcWr8EkRLSBtFyIeuerNiYoGQiJ4Ft+vkHuLsgNHBE5AQABLliwhMDCQ48ePM2bMGIclQ6JLx5gxY5g4cSJt27bFx8eHtLQ0vv32W2bMmMG2bdtcyuTdhY+PjyThdgepqamkpKQApSqHDh06uLV/9+7dAdi1a5dd4tPf358nnngCKDWiFESa8FSxLA0tKirCYDCQnp4u+Xc4K5fzkDqO4Wqs2Lt2tuW6jo4rnteC7BGvNW3alOrVq2MymcoY9Xbr1q3CKpwaNWowatQo/Pz8uHTpEsuXL3dq+nqjIYxMXXU/tERFCJxjx46RlpZGUFAQLVu2JC0tTfL18qBy4aqMCuSrdMQxxDEtYTAYpHtYKKHl3BsKhYLevXvz888/065dO/R6PePHj+eNN96Q3a2tXr16fPDBB7Rq1Qqj0cgXX3zBzp07Ze3rDKKJQEhISIXJG/ibwBGGyO7ijjvuwN/fn/T0dE6ePOnWvitXruTLL7/Ey8uL1atXSwpbDzzwwAPwEDge/D9sAwJ7QbYwxxOTmWUW0mg0ShLWadOmceTIEYKDg1m8eHGZ+l+RBRXkjDNUJoHz448/cujQIRQKBf3796dWrVou9zGbzbz//vuyyJu0tDS6devG999/j6+vLzNmzGDAgAFSZxtnWWZPpuTWhr3v1vY1sdgUGVGxCAsLCyMwMNDhsRs0aMDChQvx9fXlxx9/ZPLkyS6znZGRkfTr14/33nuPrl27Eh4eTlFREb///jtz585l+fLlkjz830B6erpkQNy/f3+6devm9jHuuusuoqOjMRgMDqX//fv3B2D9+vVSCZptGYEwuhSlVcK/w7aUFP7uSuZprVp+2Lt2tuW6trAcS47M9EWr7KNHj1q9bqnC+fjjj3n++efZs2ePQyLUEaKiohg+fDheXl78+eefrF+//oaUJ8pBRRQ4J0+edJt8EZ147rvvvkohruQQoLczSerq+SJX5eas8YRarZbK3u+//35UKpVkJi8HNWrU4Msvv+S9997Dz8+Pw4cPM2zYMKl03hW0Wi0vv/yyRMSvWLHCpdfbPw1RWlteTzlvb2/atWsHIPu6QClBPW7cOAAmT57MHXfcQUZGhpUC11E8KUfN6Aq389i7UUhISODYsWNOf4TnpwceyIGHwPEAcGxgbJt1Foscy9pcX19f1Go1GRkZLFy4kGnTpgHw6aef2s0QCjJGTv1+ZRE4er1easf8+OOPyzakW7duHTt37nRJ3iQmJvLoo49y9OhRQkJCWLVqFY899hgqlYro6Gig9AFenjaPnsn05oNolXvmzBnJWFV0/RDfk06n4/r161IwZelDEBYWJhGhjtQ3lmjRogVz5sxBqVTy1VdfMXv2bFnnqVaruffeexk9ejRDhgyhSZMmKJVKLl68yLx58zh06FC5jIcrgszMTGkBGhERIZnEuguFQiEpbEQZli06duxIvXr10Ol0PPvss5hMJun62/r3CHNXtVpNaGio9HdHXcnKm5W93WFv8emsDAAoM34syR6dTsfZs2epX78+AEeOHCmzf7du3Xj44YcpLi5mx44dDBs2jPvuu4+pU6e65RPVoEEDnn32WRQKBYcOHWLjxo3/+HM5Ozub3NxcFAoFkZGRsvcLCwujQYMGAPzyyy9uvee+ffsAaN68OVBaNhUaGir93XaOcvW7HAL0diZJXRE07iR8HD2nNBoNoaGhkoeKIEDduTeUSiUjRoxgz549NGjQgNzcXN577z2mTZsmq1xRoVDQp08f/ve//wGlZuPutrq/kRAKnNzc3HITlyJmFGNIDj777DPy8/O5++67GTduHAaDgby8PJKTk63GlFDDWxI2Op2O1NRUUlNTpe3cjR9v57F3I5CQkEBsbCwtWrRw+jNw4EArpakHHjiDe46THvyrkBtkynW8tzyebTckIeG1DbL1er2VWSGUThi+vr4cO3aMDz74AKPRSM+ePXnsscfs1g4L5U5QUJDTAMTf319aOOXn5zskfEaOHOn0c166dImVK1cCpaaWQ4cOdbp948aNAThw4AALFiwAYPr06WX2CwoKAkofzt27d+fKlSvUrl2bHTt2UKNGDSvpclpaGj4+PhQUFFCtWjUUCoWUyRdtUW1/F7CcTD0KnZsD+fn55Obmkp6eTlhYGCqVioyMDMlLBUpVJiaTiYCAADQaDXl5eZjNZtLS0lCr1VKms27dulbBYfXq1e2+58CBAzEajbz44ossXLiQN954g6efftrluf7xxx9A6eLzf//7HykpKSxcuJAzZ87w7bffcvnyZUaMGCHbEFUu4WKv7eqRI0ckP6iOHTvy3HPPERMTI+t49hRDDz74IHPnzmX//v1cvHiRkJCQMp5WK1asoH379nz77bdMnjyZF154AbVabWVcrFQqCQ4OJisrC19fXwoKCspcD61WS2pqqlQOaevfVdnP55sd5ZlnoOxc4+h4luUfGo2GtLQ0srKyypA9ooRXjJtjx44BlAmCt23bxp9//snatWvZuHEjqampfPHFF3zxxRfExsbSv39/+vTp43D8iY47d9xxB1WqVGHGjBns37+fo0eP0rVrV3r16kW1atVkkyrXrl2TtZ3tfShMY6tVq1aGRHGFVq1aceHCBX788Ue6du3qdFvRHdJgMHDw4EGgtJuVwWCwmrMMBoPU4lvMUbZzlu3v9uILW8jZ5r8Ae+PIstzWXQhCXqfTcfLkSXx8fNBoNNI4FCo2Pz8/iaQ2GAy0atWK48eP8/PPPzNw4EDpeCJp5wx33HEHR44cYdq0acyYMYO9e/dy9uxZlixZUibpZY9gffPNNzGbzezevZtPPvmE2bNnu2xwIdCjRw9Z28kxWwaslHlCpWQ0GklLS7Mab8786CzRtm1bAA4ePEhubq7UvdEWlslKEXeOHTuW3NxcVCoVJSUlqNVqdDqd9Ozz8vKiqKjIitwG62dueeJHe2NPzvz2bykSb3YIgm316tUuG6YIw3kPPHAFjwLHAyvYtoC1dbsXJSCWHUJEt4MNGzZw7do1IiMjmTFjhsP3EGoaOSVUgiQpr4lcSkoKa9euxWg00q5duzKGys72Gzp0KEajkb59+zJkyBC72yUkJPDII49w+fJl6taty/fffy8tDIVZIJROiIGBgVadOWyzHI6yHp52jjcftFotAQEBRERESARN9erVUalU0sImODgYrVYrjRVRYlhSUoLBYODixYuAPAWOwODBgyVz7GnTprF9+3a3z71atWq89dZbPPvss/j6+vLXX38xfvx4fvnllxuqxvnzzz/5+OOPpbE4dOjQCpMZtWrVonHjxhiNRodGmM2aNZNIoxkzZvDLL7+QkZFRprzNy8vLyvDTFmLhKQJwz5i8sbBU3YjrnJaWRmpqqhVZIYzhhdfa2bNnHSo277jjDqZNm8a5c+f48ssv6dWrF76+vpw5c4bJkyfTpEkTevXqxa5du5ye22OPPcY777xDnTp1MBgMbNq0iQEDBvDee+9VuKuOKwjitzxB/j333APIM6sVOHDgAIWFhURGRtK4cWOCg4PLqADAejzYzlnlMYH3lBW7D2GSL8poiouLyyhw7JVV6fV6iWhw596whI+PD2+//TY//PAD9erVIzk5ma5du7J69WqX+yqVSt544w3uvfdeCgsLmTBhguxSrhsJlUolEcFC0eIuYmNjiYiIQK/X2yWvbLF48WIyMzOpV68ed999t6RkqlmzpkTmijFnWZItxklYWBhVq1aVOreWJ370jL0bg9jYWJo3b+7053Ykb86cOeOyvOxmeB7cbPAQOB5YoTzSSY1Gw2+//cZXX30FwLx585x2l3KHwBHeIAUFBVLmWy6ys7NZuXIlhYWF1K5dm1deeUWWsV1JSQlDhw7l+vXrxMTEMHv2bLsLTVvyZt++fVJrY9tsqL0J0VWQ62xfD/5diFa5jRs3lgypRStPKA2IRfmc5fcmjLvVarWUEXSHwAF49dVXGTFiBGazmYkTJ0rZcXegVCp59NFHmTFjBrGxsRQWFvLVV1/x2WefyTailIv8/HyWL1/OBx98QHFxMa1atWLUqFGVYjIJ0LlzZwCpRNIennnmGZ566ilMJhNjxowhISGB+Ph4zp07Z1XWZklO24MYoxERES7HpKf0UR7EdbKdcyxLpfLz8yXfFkuSVGSjY2JiaNOmDZGRkZjNZo4fP+70Pb28vHj00UdZvnw5586d45NPPuHee+/FZDKxd+9e+vbty9q1a50e48EHH2TZsmVMnz6d5s2bYzKZ2LNnD6+99hpTpkzh2LFjNyQjLQJZOR5utmjZsiUKhYLz58/LVgD98MMPQOnnjY6OtvKHEt+R7XiwnbM8c5g1btSzQcRv4hkeGBhI/fr1rdRotqbtYlzde++9qFQqLl++XKHFUuvWrfntt98YMGAARqORYcOG8cknn7jcz8vLi3fffZc77riDvLw8pk+fXm7SpDIhVOAisekuFAoFDzzwAODaB6ewsJA5c+YA8Nxzz6HRaCgsLCyTSLUkbGwVifZ+94w9D25GiPt04MCBLsvLYmNjPSSODTwEjgdWKA9bn5aWxrBhwwAYMWKENFk5gjsEjq+vryTldkeFU1BQwKpVq8jJySE8PJwBAwbIkgIDTJ06lYMHDxIQEMDKlSvtXovExESJvKlVqxbbt2+nZs2aZSZXcByseYLcmwPCzyYuLq7cAbVl0CS8osT3mJCQQEJCAgaDAbVaTUhICGq12mULcUdQKBRMnz6dTp06UVxczEsvvcTp06fLdd5Vq1aV1Dg+Pj5cvHhRUqlUVI1jMpn44YcfGDNmDN999x1Go5H77ruPl19+GZVKVaFjW6Jjx46oVCpOnTrlcIJXKBTMmTOHpk2bkpaWxoQJE8jNzSU/P1/yLZJj/ujOGPX4CMiDow5Uti2Pq1SpQnh4uNRG3FZJoNFoJBWOKKOSg+DgYAYPHsyOHTs4fvw4AwYMAODFF1902KJeQKFQ0Lp1a2bPns3ixYvp0KEDSqWSP//8k/fff5+xY8fyww8/uG2Y7Azx8fFA+RQ4QUFB3HXXXYB8rxNB4LRo0QKwNkl1NB6cERQeYvPGPRssDdeDg4Np0KABMTExZQgA0YkvIyNDKt+tXbu25HFUXhWO5XksWbKEMWPGAPD666/z9ttvuyQ0/fz8mD59OnXr1iU7O5sPP/zQbQPhylaRCgKnIt0bRRmZqy5fq1ev5urVq1StWpXu3bvj7+8vxZV6vZ68vDyJnBNzVmXBM2Y9+KcRHR3NmTNnOHr0qNOf1atXS/OOB3/D44FzC8GRR0plwrK8x/J3y3OwbeH68ssvc/36dRo1asSkSZNcvoc7JsZQmkUqKCggMTFRmkwtYTQayc/PJycnh9zcXLKysjh8+DCpqan4+/szaNAgWdfLbDazdetWlixZAsDcuXMl00dLZGZm0r17d4m82bRpk1QeY6923V4N8j/xXXogD8LPBqiU70MEW+JfcWxLzwGTySSRDTt27KBx48Z2721HUKlUTJ8+naysLA4dOsTw4cNZsWKFZOTqDoQap0aNGqxbt45Lly7x1VdfsWfPHho2bEjjxo2JiYkpY/rrCGazmYSEBF5//XXi4uKA0o4lzzzzjLR4rEyEhobSqlUrDh06xN69e+nUqZPd7TQaDWvWrKFt27YcPXqUXbt20adPH3x9faVgOC8vD39/f6Kjo6XXyntP3C4eHhWFuE6uymmglPS3JGwsfR+gVGGydetWdu7cybBhw9wu0atTpw7z5s1DqVSyevVqhg4dyqZNmxya11uiQYMGTJo0id69e/Ptt9+yZ88eEhISmD9/PqtWreK+++7j/vvvJzY21m31mclk4syZMxw4cEAaU+VR4AC0adOGEydOcODAAZd+VhkZGRIZ1rx5cxITE8nPz0etVktEgL25zJnvhrueHP/FufJGPRu0Wi1qtVp6djm6XsKTTcQtYrsHHniAw4cP880331j54JQHCoWCadOmERoayuTJk5kxYwZ6vZ6+ffs6HZcBAQHMmjWL4cOHk5qaytSpU+nduzf33Xef1bgpKioiJSUFnU5HUlISycnJJCUl8X/tnXd0FGX3x7+zCZtk05NNoSWhEwSM9CJNXoqggIigwhuawA8pIiJiAwWxICJFQEGKgqJ0C69SpBcRkd4RCISWbHqym7Z7f39wZpjdbEuyye4m93MOR7M7O3Nn5rlPuc8td+7cgVqtxqhRoxAXF1eqeygoKMCVK1cAlNwDB3jglQQ8MCxnZWWZ3bzMzMzEJ598AgCIj49H9erVixjeUlJS4OXlBY1GI4Uymm4WynMvFkd3HKmzDGMvUVFRlTJszBGwAceNKK9OVDSGaDQaREdHGy3cxAVpWloagoODce/ePfz4448AgMWLF9u1yBPDom7fvm2XPHXq1EFSUhJ27NgBjUYDvV6PrKwsZGdnIzs7G1qt1uzOjo+PD+Lj442SlVoiNzcXX3zxheTiOmHCBKnCjRyDwYAxY8bg2rVrqF69OrZs2VJkoDXF3GSNB0TXQcxnI/5/aTFN0iqeW64bgiCgcePGOHHiBObNm4clS5bgxRdfxPjx480aDc2hVCqxaNEixMfH48KFCxg2bBhWr15dIiMO8MCdddy4cTh06BB+/fVXZGRk4NixYzh27BgUCgVq166NRo0awcfHB0FBQWYn4Xfv3sXRo0dx79496Z4HDhyIHj16SDvDjkav10u7o5YSRIrUrVsXU6dOxbvvvovLly+jZs2a0Gg0ZifUoodHSXXUUrJexhh7npNoGE9OTpa8bsyFuvXq1QvvvfceduzYgXnz5kmleIuDQqHAggULkJ2dja1bt2Lw4MH45Zdf7Da6hIWFYfjw4Rg4cCB27tyJbdu2ITU1Fdu3b8f27dsREhKCdu3aoWHDhoiOjra4mCUiJCQk4Pfff8fhw4eNknjHxMQgIiKi2PeWn58v5Yqyx2C8YcMGGAwGNGzYEDExMTAYDEZJjAHzY5k1A4Ut44XporMijpVl3TfYOr9KpTLbV/bv3x/z5s3Dli1bsHbtWocYcV5//XWEhIRg/Pjx+OKLL5CXl4f4+Hirv1Or1Zg2bRpmz56N5ORkLF26FL/88guaNGmCe/fu4fbt20hOTrbo0XP37l3MnDkTXbp0wfDhw+3eLJRz5swZfP3119I8tXr16sU+B/BAj8XKrCEhIWa9T/V6PYYOHYpr164hMjISr776apH3p1KpULNmTeh0Omm8MrfBKs8bZo/uiPoGWM7rxpsRDON6sAHHjSjrTlTekefn50OpVEq7bXLy8/OlRe/ChQtBRHjyySft3u1o2bIlVqxYgb/++gtEZHOXtGPHjsjJycHp06dx/Phxs8coFAr4+fkhICAA/v7+qF69Olq1amXXJCkpKQmzZ8/Gv//+C4VCgdmzZ2PMmDFmj507dy527twJb29vfP7555Jbv4i8coo8YaOpHDwgug5iPpuyOre4u5CVlYXU1FT4+PjAx8cH+/fvx7p167B48WKcOnUKK1euxMqVK9GlSxe8/PLL6N69u81Fo5+fH1asWIGRI0fiwoULGDRoEAYPHoyhQ4caVcywF4VCgQ4dOqB169ZSmfTz58/j/v37uHr1qpR42d/fH9HR0YiOjkbVqlWRlpaGv/76SwoL8/DwQO/evdG3b1+7QiVLwx9//IHr168jICAAffr0sXm8mNxR9OQQ83WZenSIf7OOuhbp6elSTg/5jrNKpUJcXBzmz5+PCRMm4L333kPdunXNGuJt4eHhga+++grp6enYu3cvnnvuOXz++efF2in09fVFv3798PTTT+PMmTM4dOgQ/vzzT6SmpuLXX3/Fr7/+itDQUCnGX6xedfv2bRw/fhz//POPlJ8EeNAe27Rpg8cffxyNGzcuURji6tWrceXKFYSHh2P8+PE2jxerN44cORJqtRparRbh4eFGOYgEQUBeXh7y8vIko4s1A4Lccyc5Odlm1UUeK0uOqX7YonHjxnjttdcwd+5cjBs3DnFxcahTp06p5Rg5ciRyc3MxZcoULF++HIGBgTb1MiIiAnPmzMH27duxbds2JCYmIjEx0egYlUqFGjVqGP2LjIzE77//jt9++w179uzBiRMnMHr0aLs9XFNTU/HNN9/g0KFDAB5sOA4dOtRmagBLLFiwAJs3b4anpydWrVpl9j3MmjUL27Ztg5eXFzZv3mw0RsnDlkSvd1Pkx+Xn5yM/P9/IiGNNd0R98/T0tPiMeDOCYVwPNuC4EWXdico7crVabTHesGrVqvD09EROTo5UYWDKlCl2X+fRRx+Fl5cXUlJS8O+//9r0GFAoFOjVqxeqVq0qhUXJ/0VEREClUpUoKeqpU6fwySefIDMzEwEBAZg2bZrFsuQ7d+7Exx9/DAB4/fXXER4eLpWRFgdIc5VTzMEDYuVDp9NJFah8fHygVCoxdOhQPPfcc9i/fz9WrlyJX375BXv27MGePXtQp04dvPzyy3jxxRet7iAGBwdjxYoVePnll3Hy5EksX74ca9aswcCBAzFy5MgSyapUKlG/fn3Ur18fffv2hUajwfnz53H+/HlcvnwZWVlZOHv2LM6ePQtPT0+pKoZCoUDDhg3RvHlzPP300yW6dnHQ6/VSyKOt5yQi6l1ubm6RcDd58nVRRytK2e+Kgvwdyftb8b2+/PLLuHDhApYsWYLRo0cjOjq6RKEUXl5eWLNmDfr06YMTJ07g9ddfxxdffFGsUEfggTEoLi4OcXFxGD16tBS+dPToUaSkpGDHjh3YsWMHIiMjQURGuTaUSiVat26N9u3bIy4uDlWqVCn2fYjcunULy5YtAwB88MEHVgsNAMClS5dw9OhReHh44MUXXywyZmm1Wuj1emnXvrheMpa8A3x9fZGUlFTEIMQUH3P6IUen00nfiaFXEyZMwLFjx7Bv3z4MGjQIe/bscYgRfty4cdBoNPj444/x2WefISAgAF26dLH6G29vb/Tt2xf/+c9/8McffyA9PR1Vq1ZF9erVUa1aNQQGBpqdZ7300kto3749lixZgtu3b2POnDlo0qQJ+vXrJ3mAm6LX63Hw4EHs2rULubm5UCgU6N69O1544YUSGw8PHjyImTNnAnhQNbJ9+/ZFjlm/fr2U5Pnrr7+WKsUBD3UsPT1dCpkyJ4v4nsX8i6Je2ZOvzV4DaUUMZWQYd4YNOIyEvCNPSkqCXq+XjDjyXTWNRoP09HQsWLAAubm5aN68OTp16lSkXKUllEolmjVrhiNHjuCvv/6yK+RDEAQpwZ45uYuLXq/Hli1b8O2338JgMKBOnTp4++23pZ0PUxISEjB69GgQEZ5//nkMGjQIaWlpRQZVc3kZmIqNvbucPj4+kvFGTm5uLpo1a4ZWrVrh7bffxqeffoodO3bg33//xWuvvYaZM2di/PjxmDp1qkUjZXBwML777jvs3bsXS5cuxdmzZ/Htt99i3bp16Ny5M55++mmLbdse1Go1OnbsiI4dO+LMmTNITEyUKjmJO3/16tVDixYtEBgYWOLrFBe5982gQYPs+o34/M29M3t0Nzk5GRqNBj4+PlJoD+t7+SH3wDH9W9TF2bNn4+zZs9i/fz8GDhyIvXv3Sh4uxcHf3x8bNmxAz549cfXqVbz++utYuHChxUWgLapUqYKWLVuiZcuWSEhIwNmzZ3H8+HGcO3dOCjv09PTEI488gubNm6Nx48YlznUjh4jw4YcfIi8vDx07dsRzzz1n8zei9023bt0shmuJz74kXjLmfiP3Avby8qpQYVPlidwjw7Sogulxer1eOlan0wF4UEm0W7duuHLlCiZMmIBVq1Y5xJA9ffp0XLhwAT/99BNmzZqFgIAAKTm2NXx9fe3yrpQTGxuLzz77DBs2bMCWLVtw5swZXL16FX369EHz5s2N7ufatWvYsmWLpIP16tXDqFGjULt27eLdoIyEhAS8+eabICIMHTrU7GbK8ePHMXHiRAAPjE6xsbHQaDRSfybOJ0VvWmtebfKxyx7PUblBxh6jdEUMZWQYd4YNOIzVjtx0B0f8l5ycjPXr1wMAXnvttWIP7q1atcKRI0ekcpPlyd9//40VK1ZI4R5dunTB+PHjLebP0Ol0iI+PR3p6OmJjYzFt2jQoFArUr18fAIrsHrKrd+XCtBqOJcOAaLwxNeDIDTs1a9bEuHHj8Nxzz+Hw4cPYunUrbty4gdmzZ+POnTuYP3++RSOOQqHAE088gS5duuDQoUNYunQp/vnnH+zcuRO7d+9Ghw4d0LdvX1StWrVU91ulShXUqlULtWrVAhEhLS0Nnp6eJV7UlpSSeN8AxgYcOfLJr/xvOVqtFpcvX4aHhwdSU1NRu3ZtntCWM6YeOAaDwUj3RG+wlStXolu3brh+/Tqef/55/P777yV6T2q1Gps3b8YTTzyBGzdu4M0338Rnn30mVUcsKeJGRrNmzaDT6aRKco888ojdCcPtZdeuXTh48CCqVKmCzz77zOZ4rdfr8d133wEAunfvLiVcN807JA8/tKQvlnbtzf1GXCQClvNxMLaRe2TIjZ3yzQYvL68iHohKpRIeHh7w8fHBp59+iuHDh2PLli1o27atxbDy4iAIAl599VVkZGRg7969ePPNN7Fw4UI0bNiw1Oc2h1KpxODBg9GuXTvMmzcPt2/fxo8//ogTJ05gwIAB8PT0xLZt26TQfJVKhfj4eDzxxBMl8ugWyc7Oxquvvors7Gy0atUKc+bMKaJzd+7cwZAhQ5CXl4d27dqhTZs2SExMhI+Pj5EBx3QeodFoinxu7m9bOl5cgwyHMjKMa8EGHDfCXiOJrVKNppjryMXyrcCDyZyYKFSr1SI9PR2bN29Geno6oqKi0KdPHxQUFNg94Pn6+qJz585YsGAB/vnnHyiVSrOu4S+88IJd57OVuFQkOzsb06ZNk5I4qtVqvP/++xg+fLjRs5XLkp6ejkmTJuH06dMICwvDtGnTpNCt4rrS24JDNcoHRz9n+cRGXhLZdGfZYDAgLy8PHh4eRrtleXl58PPzg0qlgoeHBzw8PBAQEIAhQ4bgjTfewHfffYfXX38dq1atgqenJ5YsWQKFQoEaNWpYlEn0Ejt06BA+/vhj7Nu3D3v37sX+/fvRv39/TJw4EY0bNzb6jTxJqjW6detm13GZmZl2HWdvaVJTw9NPP/2E69evIzAwEBMnTpQMSLbKyIoLb7E6mKks1kIOcnJyEBAQgIyMDNSoUcNokcn6W/bIdU0QBBCR9E8QBKPvQ0NDsXXrVnTt2hUnTpzA2LFj8cMPPxQZp3Jzc21et3bt2vjpp5/Qu3dvnDt3DnPnzsXatWvNjlv2lgw3rWpjqXqavZjLjQE8GPc+/fRTAA/CWJo0aWLzXLt27UJiYiICAgIQFxeHW7duwdvb22iDwtfXFxqNxijUyZSSLhIthca4E87qD0z1QC6HaYi3v7+/FB7l4eFhtEB/7LHHMGHCBHz++ed4++230aZNG6makjns7e9btmyJzZs345lnnsG+ffvw5ptvYufOndKGmIi9SbrtCe9q27YtmjZtivXr12P16tW4fPky5s2bJ92zIAjo1asXRo0ahUaNGtl1XUshiAaDAUOHDsX169dRtWpVbNy4sUghDZ1Oh6FDh+LevXto0KABpk6diszMTOj1equ56zQajVTFqrR5+4prkLFnc5LHQIYpP0puYmYqDCqVqoibrXxCJu4GFhYW4t69e0hPT5fcqydOnFii6jINGjRASEgItFotTp8+7YC7sExqairee+89tGrVCjt37kSVKlUwadIknDlzBiNGjDA76GRnZ+Ojjz5C3bp1sX79eigUCrzzzjuIjY1FXl4e77gzEiqVSoo19/X1Nbtz7OvrKyUW1Gg00iTa1HsHeKBvwcHBCA0NRXh4OP773/9iwYIFEAQBy5cvx8svv2zTSAE8mEw9/vjj2LJlC7Zv344ePXrAYDBg48aN6NixI9q3b4/PP/9c2l13J9LS0vDZZ58BAEaPHl0s7x959RwR8b0AD0MOxM/k78bX1xeRkZFo1qwZYmJi7MoxwDgOua4BDxJSR0RESOGB4vfAg8VOrVq1sHHjRiiVSmzevBnvvPNOsTc4RBo2bIh169bBx8cHu3btwoQJE+zSQ2czd+5c3L17F9HR0VK4hi3E3HZ9+vSBUqkE8GCBb67qjV6vN9IlOZb6Q9NzJCcnS0bT8PBwtzfeOBtTPRGx9j7kvxET+7/xxht4+umnUVBQgBdffNFiXsTi4uXlhR9//BGPPfYYNBoNevbsiZ9//tkh57aEp6cnXnzxRXz99ddo0qQJcnNzkZOTg3r16uGLL77AlClTHBL+KyZe9vLywurVqxEZGWn0PRFhzJgx+PvvvxEaGopvvvkG9erVQ6NGjdC+fXspWbjp2ONo5H2lqH8Mw7gPbMBhpNAp00FdLBkullH09PREUFAQfvvtN9y5cwdBQUEYNmxYia6pUCjQpk0bAJCy/Tua/Px8rFixAt27d8e6deug1+ulhJQfffSR2R2U3NxcLFiwAPXr18e7776L9PR0NG7cGGvXrkXv3r3h6+uLmjVrArBv0JNPTpmKj6WJs/h3VlYWtFqtZCQwNZ6KiXT9/PyM3KgHDRqEZcuWFduII9KyZUusW7cOe/fuRd++faFUKnHhwgXMmjULcXFx6NmzJ9asWWNU9cZVuX//PgYMGIBr165BrVZj+PDhxfq9aJDOz8+XPpOH3ohhIvIy4iKW3i9TckrTR1p6Hzk5OVJuj8cffxxz584F8GBxNWnSJOj1+hLJ2qpVK6xatQoeHh7YsGEDXnrpJXz33Xf466+/kJaWVqJzliXnz5+Xwgxnz55tV2hWZmYmfvrpJwDAkCFDEBkZCbVajZo1axrlVtFqtfDy8pKqUprDHn2Re+kwpceaPhWn/1KpVPDz88Pbb7+NWrVqITExEUOHDi2x7pji7++PLVu2IDY2Fvfv38cLL7yAF154AXfv3nXI+S0RFRWF+fPn480338S0adOwdOlSu71ubPHLL79g3rx5AIDPPvsMjz32WJFjPv30U/zwww/w9PTEggULEB0djXr16iEuLs4ol1d2djZu3bpl9B7VajUiIyNLlc/OFNY/hnFP2IDDWOX69eu4c+cOrl27JsVI79ixAwAwatQou/NOmKNdu3YAgCNHjjhEVhEiws6dO9G7d2/MmTMHWVlZaNSoEbZv344ff/zRbFnMgoICrFixQiqjmZSUhKioKHz++ec4cOAA2rRpg3v37sHHx8fi4s4cPDgycnJzc6HT6YzySZnmlcjLyzMyIog70yNGjMAXX3whGXEmTZpUbA+Apk2bYtWqVbh48SIWLFiAjh07QhAE/PXXX3j//ffRrl07jBgxAlu2bEF2drajb7/U3LhxA8888wwuXbqEiIgI/PDDD8XOvSM+azFhp/iZqecNwHk4yoOy6iPlSfWHDRuG999/HwCwePFiPPfccyU2qnfr1g2LFi0C8CCMb+LEiXjyySdRt25dNGjQAP369cOUKVPw5ZdfYteuXUhISHCKp47BYMAbb7wBvV6P3r17o2vXrnb9btOmTdDpdIiNjUVcXJzkcSqGb8hzRPn7+yM6Otpi/ht7DHP2eOkw9uNIfRJD39577z3J80ysxOkIwsLCcODAAUyZMgWenp74+eef0axZM3z99ddlqjNihakePXrAw8PDIec8f/48JkyYAAAYM2YMBg4cWOSYHTt24N133wXwIHdkw4YNzea4AR7MA7y8vKQ5gPi53ADniA1C1j+GcU84Bw5jlpycHGg0GlSpUgVZWVnIy8uDXq/Hhg0bcObMGQAPyrWWhrZt2wIATp8+LZVJLCkGgwGXL1/G33//jf/9739SUrqwsDC8+uqr6NevH2rVqmX2txcvXsTgwYNx/vx5AA9ir+Pj49GzZ0+Eh4cjLy8POp0Ovr6+0qJPpVJJn4mYS9jIid8YEdE1WpyUWdoFtVYmOT4+HgAwfvx4rFq1CtWqVcO0adOKLUtQUBD++9//4r///S/u3r2LLVu24Mcff8SZM2ewf/9+7N+/HyqVCv3790fnzp3RqlUrp3udnD59GsOGDUNSUhKio6Oxbt06REVFFfs8Yg6cwsJCqd+RT4jFsJC8vDxERUU5/b4rOmXRR+bk5BglN1apVHj77bcRGhqK1157DT///DO6du2Kn376qUTJtwcNGoTw8HDs2LEDV65cwZUrV5CYmAiNRgONRoM///zT6PiaNWti9uzZ6N69u0Puzx6WLVuGv//+G76+vlIpY3v4/vvvAQDx8fHQ6XQwGAxISUlBUFAQ8vLypNwkogHaXAiyVqtFQkKCFH5lTYe4TLhjcbQ+ZWZm4rHHHsPHH3+MV155BbNmzUKHDh3QsWNHh5zfx8cH77//PgYMGIBx48bh+PHjeOWVV9C5c2csXLiw1MnCy4MzZ84gPj4eWq0WHTt2xIwZM4ock5+fj6FDh4KI0KdPHwwePBh+fn5GXnHi2OPh4YHQ0FCkpKTAz8/PqFqYfNM0JycHmZmZSE5ORkxMTIn0iPWPYdwTNuAwRoglcoEHccpiwt6kpCTk5eVJiRdjYmJKXc2mevXqiI2NxYULF/Dll19ixIgRCA4ONpsY0pSCggKcP38ex48fx8mTJ/HPP/8YJdGrUqUKXnrpJYwaNcrqRGb9+vV4+eWXkZOTg5CQEEycOBGDBg2Sdn9EjxsASElJgY+Pj1QFwDSJcVJSUpEEczw4MiIqlQpRUVFWjTeiBwiAIjlZRAYMGAC9Xo+JEydi8eLFGD9+fKk84apWrYqXX34Zzz//PG7cuIFffvkFP//8M65fv461a9dKyVpbtGiBxx9/HK1bt0aDBg1KVaWjuOzfvx9vvfUWdDodGjZsiO+++87uJJemiIbaoKAgpKeno7Cw0MirDjDe/fT19bVaTQcwNt6ysbZ4FKePtPUebBEfHw9vb29MnToVx44dw+OPP46NGzcWSaBqD126dEGXLl2kv3NycvDvv//i4sWLuHLlCq5evYqrV6/i33//xa1btxAfH48nn3wSs2bNspqAvLScPHlSSlwOANOmTStWCXVRP7p06YKUlBTo9Xr4+fnB398fERERdlWbysnJgVKptBpeZen3rD+lwx59Ko4ehYeHIzMzE0899RSOHTuGtWvXYvTo0fj222/RqlUrh8ndpEkT7NmzB1999RWmT5+OvXv3YtSoUVi6dGmpxreyZv369ZgyZQpyc3NRu3ZtLFu2zGxeSI1GI4UoT58+3WKotTg/0Gg0khFa3Pwxl9MoOTkZXl5ediUKL23/yTCM68AGnEqI2ImLSVeBB5NPrVaLW7duwcPDA3q9Hmq1GhEREcjKykJAQACSkpIwYMAA/Pjjj7h9+zYSExNLPREdM2YMJk2ahNWrV2P16tUAHiysQkNDpUSuISEh0n+TkpJw/PhxnDlzpkj1EJVKhcceewwtWrRAt27dUK9ePYvXNRgMeP3117FkyRIAQLNmzTB37lzUr19fSjonj/dXq9VQq9XQaDRmd0IYxh5sTa7F78VEx+bKwBYWFqJ37974/PPPcf36daxbtw6jRo1yiHwxMTGYMGECxo8fj/3792PHjh04cOAA7ty5gyNHjkjhjqGhoWjbti3atWuHdu3aObwim5z169fj008/hcFgQMeOHfHll1+WqmT5b7/9BgD4z3/+A4VCYeThpNVqpXPLJ8y2qunIv+cFaNlhb1Wj8PBwZGdnm10gDRw4EEFBQZgwYQKuXbuG//znP/jxxx8lj9CS4uvri6ZNmyI2NraIzJ9//jm+/PJL/Pbbb9i7dy9ef/119OvXz67NCnu5fPky5syZg23btgF4YPgdM2YMRo4cafc5CgsLpUWmOA/w8PCw6Ylm+l5ELxB7y6Gz/pQv9uqRr6+v1AaUSiXefPNN7N69G9evX0fHjh0xfPhwfPDBB1YrJxUHDw8PvPzyy4iLi0O/fv1w9OhRjBgxAsuXL7eZYLiwsBBnz57F0aNHoVKp0Ldv31KNE7bIz8/H9OnTsXLlSgBA165dsWTJkiIVp0QiIiIknRKr5JliOj/Q6XRSSLVoxElOTpYMMGKyaXv1prhV4RiGcV3YgFMJMVfqWFwYihMutVotLcqysrKQn5+PyMhI1K5dG+3bt8ehQ4cwd+5czJ8/v1SydO/eHU8//TSOHDmC1NRUGAwGpKenG+UvsERQUBCaNWuGVq1aoXnz5mjUqJFdFbEMBgPGjh0rVdIaO3Yshg4ditDQ0CLxyKKxRvxcvkNiilg9gyegTHGR57oR/5lrZ+LnCoUCw4YNw4wZM7BkyRKMHDnSoR4xgiCgU6dO6NSpE4gIN27cwIEDB3DgwAH8+eefSElJwa+//opff/0VAFC/fn3Jrf7RRx91yMLUYDBg/vz5+O677wA8KI3+0UcflfrcogHn2WefNdrZNJ08m1blszZJ5lDJ8sHWc5bvMFsqq61SqdC9e3fs2LEDL7zwAs6ePYunnnoKy5cvR//+/ctE5nfeeQcDBgzAtGnT8Oeff2LmzJn4/vvvMX36dLOJTovDnTt3sGTJEvzyyy8wGAwQBAHPPvsspkyZgujo6GKdSzTeCIKA4OBg6HQ6+Pn52Vzsmb4X0Yhj72KR9af8SUtLs2l4V6lUqFKlCrRaLXQ6HapVq4Y///wTr7/+On788UesXLkSW7duxQcffIBnn33WYWNQu3bt8O2332LkyJE4efIk4uPjsWrVKoSEhEjH6PV6nD9/HqdOncLhw4dx9OhRZGVlSd/PmDEDzzzzDOLj4/Hoo486RC6R+/fvY/LkyTh27BiAB/lsXn/9dav37+HhgWrVquHWrVu4c+eOlItRp9NBq9VKoYjy3Hg6nc4o5Fpe9U0+J7XXGMN6xjAVB4FKWlOTsUpmZiYCAwORkZFRprsA5rD1Sq154Mg/Ez+/dOkS9Ho9QkNDERoaij/++AMDBgyAUqnE+fPnJS8cexOpJSUlmf1cNN6kpKQgJSUF9+/fR2pqKlJSUqT/+vn5oVmzZmjWrBlq1aoFhUIBLy8vu64bFRVlZLxRKBRYtGgR+vbtC5VKJRmvxAWi6aLaFEeHkJjLJVBRsVc/nKlH9mJvF2rtOEseN5bQarVITExEmzZtkJGRgY0bN6JHjx5mjy0oKLBLvtTUVLuOy8rKkibNhw4dwvnz543uzc/PD+3atUOLFi3Qtm1bm/cj5smQo9PpMH36dOzevRsAMG7cOEybNs0uHbG2U/vvv/8iLi4Onp6eOH78OAICAoySSJvTeXv10hn66w56VNZTDK1WazSmeHl5wdPT0y6vgOTkZMTHx2Pnzp0AgA8//BATJkww+y7z8vLskseavhERfvzxR8ycOVPSt/79++PVV18tdg44jUaD5cuXY/369VLoX8+ePTFt2jQ0aNDA4u8seQgAwLlz59C8eXMEBwfj5s2bVsc/EUvt3lq4hrXvWI9Khz36duPGDWRlZcHDw0OqQGrpHZtrz1qtFr///jtmzJiBy5cvA3jgxTxnzhybxhJ7jQ23b9/GpUuXMGzYMKSkpKBOnTqYPn06zp8/j7/++gvHjh0rkmjf398frVu3xq1bt3Dp0iXp80cffRTdu3fHE088YTOnTvXq1a1+f+zYMbzyyivQaDQICAjAkiVLrOa2kut1p06dcOTIESxfvhxDhw4FAClMMSMjA0FBQfDw8DCqRiXXQdGQZm8IlCNDpuzRy4qkR47kn3/+QfPmzXH8+HE0a9bM2eK4HZXt+dmrH+yBUwmx12Kfk5ODmzdvGlUz0Ol0aNWqFdq2bYsjR444xAtHRKFQICQkBCEhIahXr55RmV9HYGq8eeWVV9C9e3ejib5Op0NGRoY0UJp65TBMWWDNs8vS8Wq1Gs8++yxWrlyJJUuWWDTgOBqlUomWLVuiZcuWeOWVV5CWloZDhw7hwIEDOHToENLS0rBjxw6pWl39+vXRtm1btG3bFvXq1SsyETQtS5uZmYmpU6fi7NmzqFKlCmbMmIEnn3zSIQs70fumZcuWUCgUUgUPMUTENGk047qIi5OcnBxpIefn52d3RRVx13v58uWYMWMGvvnmG7z11ltISEjAnDlzHFadRo4gCHj++efRvXt3vPsBeiePAABqDklEQVTuu9i0aRM2b96M3bt3Y/Lkyejbt6/RxgARQa/Xo6CgAAUFBSgsLIROp8OmTZuwdu1aKal+69atMWPGjFJ784iGsJCQkBLlbzNdMFr6PYdyuAY6na5ESXB1Oh0ef/xx7Ny5E8uXL8eCBQvwzz//oFu3bhg2bBjeeuutUhWlEGnQoAG+//57DB06FP/++69k9BDx8/OTQnnbtm2Lxo0bw8PDA0SEo0eP4ttvv8W2bdtw6tQpnDp1Shonn376aSlPob0QEb755ht88skn0Ov1iI2NxapVq1C7dm27zyEah8T8dsDDsV+ch9oKsS5O6D7rGcNUXNiAwwB4GEIlVtEQ8fLygq+vr5SHRjz27bffxlNPPYWVK1fijTfeQI0aNez2hLF3ALI3ft6egclgMGDcuHGS8WbixIno3LkzPD09jTwAMjMzodfrkZiYCD8/P6SkpCA8PNwuOSxRmTxrKiOOeL/y0DtLO6imu3GFhYWIj4/H6tWrsXv3bly9ehWNGjUq8jtzHi7msFcv5W7qABAZGYnY2Fi89NJL0Ov1OHHiBP744w/s3LkTJ06cwOXLl3H58mV88803dp1fJCgoCCtXrpRyk9i7ILD2PrZv3w4AeOKJJ+Dn54eMjAwQETQajZERpySTXdP35sjdT0vncqYDrb3XdnT/J15XXJwAD9tueHh4sRahYl8/fPhwBAcHY/78+fjqq69w+fJlqTy46JFprx7Jk+lbIjw8HKtWrZJywJ0/fx7Tp0/H559/DuBBPo/8/Hzk5+dbfc4tWrTAjBkz0LlzZ4d4hIpjf0REhNX3JvfYlT9v+YLRdPyWn68yhHI4WjcdqUdiuDfw4J2bS4Ir99QW+0Xxnfv7+0v/P3LkSHTp0gULFizAzz//jFWrVuGXX37Bxx9/jPj4+CLt0jR3oSVEY0f16tWxe/duPPPMM7h79y7at28vhes2bdrU4nN+4okn8MQTT0Cj0WDt2rVYvXo1rl+/js2bN2Pz5s14/PHH8eyzz6J27dqIjo5GdHQ0vL29zXqS5+Tk4NVXX8WmTZsAPCgksGTJErvar1w+8Z7u378vfe7t7Q1vb2+z4f9iHyWveCo/nzUvcUEQ7NIznp8yjHvCBhxGQsw7I+6I+/v7w9/fv0i2fJVKhQ4dOqB169Y4evQo5syZg4ULFzpDZLsw9byZM2cO2rRpg+Dg4CLhHeJEpUaNGtDpdFbDPzijP+Mo5G3JkuFS7h0i/u3n54fu3bvj999/x6JFi7B06dLyFLsIHh4eaNGiBVq0aIEpU6YgOTkZe/bswR9//IE9e/bYldsKeOC1s2LFCtStW9dhsmVkZODgwYMAgF69ekGlUsHb21tajAK2vROLo/OO3P3kndSiiIsTceFTnH5YfI86nQ7p6elQKBQYMmQI2rRpg6FDh2LPnj3Ys2cPwsPDMXjwYMTHx+ORRx5x+D20adMGBw4cwNKlS/Hhhx8iLS3N5m88PT3RqFEjTJs2DU899ZRDF2BilUkxkb8lzHmqyZP+yxOBmwvNLol3D+M4TJ+/fNNORCxRLRq35Zt88pxhYgjq2rVrceDAAUyaNAlXrlzBSy+9hBUrVmDJkiVo0qRJqeSNjo7G8ePHARQ1OIhGXEuo1WpMmjQJU6ZMwR9//IHly5dj27ZtOHjwoDQeiERGRiIqKkr6Fx0dDbVajQ8++AAXLlyAp6cnZs6cidGjR9u9wShHTDeQmJho9nu5voh/A7AYRmHNY5TnpwxTsWEDDiMRFBRkFLakVqvh6+uLrKwssy6fr732GgYOHIgVK1Zg6tSppfZUKQvMGW/EeGV57gsRcaIZFhYmDYDipNZ0IORFFeMoTHeuRU84sfoEYBxmpdVqoVQqERwcjLFjx+L333/H999/j1mzZtmVQ6e8CAsLw8CBAzFw4EAYDAYp5EOOwWAo8pmPj4/DdwZ37NiBwsJCNGzYEDExMcjKykJaWhoCAgLMTn4t5QQTFzXR0dE2K7gUx8vA2oTbHT0Wyro0tLiATE5OLnY/nJSUhOzsbOTl5SE6OhoZGRmoWbMmHnvsMdSsWROLFy/Gtm3bkJSUhM8//xyff/454uLiEB8fj+eff96hOlalShVMnDgR//3vf3Hr1i14eXmhSpUqUCqV0n/Ff1WqVCnTHXNxrAsKCkJCQgKAh/MAOWIfBEBa0It9kqenp9EC1LRgAvMQV1lkK5VKaDQaIzl8fX0l7xz5uJOfn1/EkKNWq0FE6NGjB3bv3o1ly5Zh3rx5OHLkCFq2bIlJkybh3XffLVUbKG27VygU6NatG7p164bExESsWbMGx48fR0JCAm7cuIHs7Gzcu3cP9+7dw19//VXk9+Hh4UYeoSVBNODcvn3b7PcajUbKTQQ88ID39/cv4gFlT1ENnp8yTMWGDTgMgIcDQUBAQJFBVsx8n5GRgcDAQGnAMPXCmTt3rpOkN4+p8WblypV49tlnJWOUtcSlwMMBMD09HUFBQUUGQndcVDHOx9yk3bQtaTQa5OfnS0YcoOiuqcFggL+/P3r06CElePvqq68wadIkq9cnIhQUFEh5nsQqGOb+W69ePXTp0sUhi0aFQmFWV0xz4JQVYnnl3r17Q6VSIT09XSrtarogt7TwFBc1SqXS5sRYHnogL/1qCWsTbnf0WCiv0tCl6YfFxae4+aDVatG0aVNMnjwZgwcPxj///IM///wTO3bswMmTJ3Hy5Em88cYb6NWrF4YOHYoePXo4rBR4cHCw2QTD5RniII6NgYGBUqikqRETeBjyKRrP5At8U29dzidlGVdYZFvq01QqFaKjo43CqOSGhPT0dGRnZ8PPzw9RUVHS+QIDAzFu3Dj07NkT77zzDvbs2YO5c+di/fr1WLBgAbp16+aU+5RTo0YNvPnmm9LfRISUlBQkJCTg8uXLSEhIwM2bN6V/9erVw5w5c1C1atVSXxewbMABHoSYZWRkICIiAnl5eYiIiABg3tvG2rjA81OGqdiwAYexWIFKRKVSSeVF8/PzjRL7vvLKK3jxxRexYsUKTJw40WggdyZZWVkYM2YMtmzZAoVCgTfffBMtW7Y0G99szQ01PT0dPj4+ZhNjuuOiinE+5ibt8rZERFCr1bh16xYAWCwnLsbGA8CECRMwbNgwzJw5EzNnznSovGPGjMGiRYsces7y5vz581IC4169esHHx0cKCzCnx5YWnvJFjb0TY3sXaRVtwl1e91OSfljMASKGLIpV4ERDW82aNeHj44MGDRpg9OjRAIDly5fj+++/x/nz5/HTTz/hp59+Qu3atbFy5Uq0a9euLG6tXCEiXL16FQBQtWpV+Pv7AzCfY04edih63FjSIx4jLeMKOm+tT1OpVEVCheSGHDF5uGm+HPGdL1y4EDt27MCnn36Kmzdv4plnnsFzzz2H+fPnW60WWN4IgiB5u8bGxpbZdcQ8kbdv35aet7hh4u/vD7VaDa1WC29vb3h4eEh52YCSFTpg3WOYiotj6yAzLo24E2xqxDDNrSFHPlELDAyEj4+PNJAkJiaiZcuWaNu2LfLz8/H222+Xy33Y4sKFC+jQoQO2bNkCT09PvPvuu2jVqhWuXr2KW7duISsrC1lZWUZ5L/Lz841i+EWCgoKkkCr5brq9JdMZxhRfX1+blXLUajVq1qyJoKAgi0bHxMREZGdnQ6fT4dlnn7VZvtUUhUIBf39/REREoGbNmqhTpw6aNGmCNm3aoHPnztKi9KuvvpIqSrkj27dvR6dOnZCRkYFGjRqhadOmSElJsarD8twO5r4LCwsDALv6Anvet/y8FWXSLd5PWS9OrY1rlt6PuFkh37wQc+mIIcM+Pj5S6XCVSoXOnTtjxYoVWLduHYYOHYqAgABcu3YNTzzxBGbMmGG1fLg78PXXX2PPnj0QBAEdOnSQEruK708MJxafmZh7xJKeMLZxls6b6oY5OWzNddRqNfz8/KDVanHp0iVkZ2cbHSvqWOvWrfHjjz9ixIgR8PDwwIYNG9CuXTuzYUoVmVu3bmHQoEEAgEaNGiEtLQ0pKSlSGXGxH4qKikJERISR8QawPiYxDFP5YANOJUK+EyxHnLyKA4PpRE0McRDjcjUaDVJSUqBUKpGfn4933nkHCoUCmzdvxv79+8v3pmQYDAYsXrwY7du3x6VLl1CtWjXs3LkTo0aNgq+vL4KCguDj4yMlZxbvBXjwDJRKpdEExNzCy9IzZBh7kU+WbS0y5XopR6PRQKvVIiMjAz4+PlAqlTh69ChSU1Olf//++y8uXbqEM2fO4N9//8Xt27dx+/Zt/Pvvv7h//z60Wi00Gg1u3ryJvXv3YsuWLdi6dSu2bNmCxYsXY82aNXjppZcAAOPGjZN2W92J48ePY8CAAcjKykKHDh2wY8cO5OfnQ6/XS14X8qTQ4nO1B3v7Akcu0tiA/BDxWSQlJZl9D7bej/i9uHBSq9UICwtDXl4evLy8oNPppMpnYnixXq9H586d8fHHH2PLli3o2rUrDAYDPvroI3Ts2BGXL18u69suEw4fPozJkycDAGbOnGm2HLlGo8H9+/el3Cfm+qbi6hBTvtjSGTly/TCH6OFhMBig1+uRnp5utAkmGiOqVauGkJAQvPzyy9i8eTNq1KiBhIQEdOvWDXPmzCm3EFpncuvWLXTr1g3Xr19HdHQ05s2bJ1WYAmC0gWiPoUaj0eDixYtmk08zDFM5qNQhVEQEQRCk/1Z0fH19kZSUhLy8PCkfQ3JyspRnQzRUmIYUZWdnS2FTt27dQnZ2Njw8PODj4wMfHx/ExMTgySefxLZt2/D666/j0KFDZksiliU3btzA6NGjceDAAQBA586d8c0330i5DRo2bIiMjAyjpLDiAk4+CMqz/ZtzQXUFl2em4lDcvCdarRY3b97E9evXoVQqERISIn0nlg3V6XRISUmBTqeTwv+USiUUCoV0vE6nk+LwQ0NDJf328fGRdgRzc3Mxbdo0/P7770hISMB7773ncnmurJGeno7BgwejoKAATz31FFasWIGsrCzk5ubC29vbKLcQYD2U0hzO6AtcIWeGqyAvI27Ow8nW+xG/N82FJrYL0xCisLAwREdHw8fHBzqdDpGRkfjyyy+xe/duTJs2DcePH0erVq0wc+ZMDB061G3mFHfu3MGLL76IgoIC/Oc//0G/fv2khMQiOTk5Ur/g7+9vlJg6JycHN2/elPob0WvQNPGqIAgukbC3MmNLZ+SY6oc5VCoV/Pz8JE8c0SAkD6WXGyNq1KiBffv2YfLkyfjpp58wc+ZM7N69GwsXLkSdOnWkTcKKhNx4U6NGDaxduxaBgYFSOXVxTCYim2OPWNwgLS0NCoXCqGqdfL4g6h3rWtlz8+ZNm4a0CxculJM0TGWiUhtw7t69i2rVqlUaI47o0ipfAMiTpYphAcCDxY9o1PH29i5yLtF4k52djRs3biA+Ph6HDx/G2bNnsWrVKowaNapc7omIsHz5crz55pvS5PDVV1/Fq6++WmTgEndTRcQJZn5+fpHqGSKmCWc5rphxJCWpVKTRaKBQKFBYWIjAwECkpKRIxhdxcanRaJCXl4fq1asjNDRUWlyJ6HQ6qYyyTqdDjRo1EBoaCgBSviudToeAgAC8++67Uh6cgQMHlmmOAEdBRPi///s/3LhxAzExMfj666+Ndpx9fHyKJC42l2PA2kRYngvCniTFjsAVDcjOqqQjPovAwECLoW62Fp8qlQpEBOChAc/T09NslSkxfwXwoP2EhIQgNTUVffr0Qbdu3TB8+HDs27cPU6ZMwY4dO7BgwQKjMdUVyc7OxqBBg3Dv3j3UrVsXkydPRmpqKkJCQozGS61Wi6CgIOTl5UnPRvTQFfsk0ZtAvmAXn6lGo0FOTo70DCvLGOoqVaZEbOmMHFP9sHSMaKxJSEgw69Fjqod+fn5Yvnw5OnbsiOnTp+PgwYNo1qwZPDw8ULVqVVSvXh3VqlVDjRo1UL16daP/RkZGQqFwn8CBxMRE9OzZE9evX0fVqlUxf/58VKtWTXpOYh4glUqFvLw8m+9Eo9EgIyMD6enp8PLyQkBAAK5cuYLIyEjpPMBDvWNDf9ly8+ZNxMbG2uVxKHpWMYyjqLQGnLVr12L48OH47rvvMHDgwEpjxDFdAKhUKmnClpycLC1IxJhcU0JDQ6U8OACQmpoqTVJHjhyJuXPnYubMmXj22WeNvAPKgtu3b2PixInYu3cvAKBly5Z4//33UadOHeh0uiLxwwUFBUU+M90lNIV3vJmypLgGQXES4Ovri+DgYKn9FhYWSoYc4EG4o7hYEg07cnx8fODr64v8/HwYDAZcvXoVwcHBRt44In369MFvv/2GrVu3YsyYMdi1a5fR7rwrsnTpUmzduhVVqlTBd999h6CgIOh0OqN+zxRLHk+29L88+whXNCA7q4909LMobpJQ4OECrEaNGti+fTsWLVqEt99+Gzt27EDHjh0xf/589OjRw2EyOpLs7Gz06dMHx44dQ3BwML766isQETw8PCQDr6m+REREGHnqZmVlIT09XfqsZs2aRRYp6enpAB4YwETv38qCq80fyrL/EA139pxfpVJhzJgxaN++PSZNmoRjx45Br9cjMTERiYmJFn8XERGBoUOHYsSIEahZs6YjxXc4cuNNjRo18MEHHyAmJgY6nQ75+fkIDg6WPI7EJMb2GNWuX7+OsLAwhIeHQ6vVwmAwGFWrEo8zraDIOB4xXHTt2rU2N7bUarXLFHlhKgaV0oBjMBiwefNm6PV6TJo0CQaDAc8//3ylMOKYDrAqlQq1a9dGenq61Xhn0/LC4r+0tDR4e3sjJiYGAwYMwNatW3H16lXMnj0bCxYsMHsue63QlnZaiAjffvstXnvtNWRmZsLb2xsffvghXnrpJcmVMSgoyGjHVP7/psjdwQHjsq1yg1dFbheM62Ctnfn6+ko7PmK79Pf3R05ODgoKCmAwGODp6YmGDRtK34vx9XLd9/DwkFzfxd1zccInJqeUM3v2bOzbtw/nzp3D0qVL8dZbb9m8D3tzG1jTTTliQllbnD17Fm+88QYAYO7cuWjbti0AQKlUFrvyiTmPF9Nd9bLyirGnv3FmnyRe21F9pLWdfnPXdfT5TMcBOaZVdgBIYSMqlQoeHh7Iy8tDfHw8OnTogFGjRuHMmTMYPHgwxowZg08//bTIucVQFnvls4XBYLDruCpVqiA7Oxv9+vXD4cOHERgYiN9++w21atVCYWGhVHlRq9UahT2ZehOJ5acDAwMREBBg0dtI9NyRP9/y8lhzJmJIqy3dsLedOgt72584nojIE4QDD6spyvWgVatWOHz4MPR6Pa5du4Zz584hISEBqampSE9Px7179ySjzp07d3D//n3MmTMHc+fORa9evTB69Gh069bN7tCr7Oxs7NixA7/88gt+++03REZGYteuXUZzUtPNDktYu+atW7ck403t2rWxYcMGREZGIj09HXq9HoWFhcjNzUVERIRRriF7Et03bNgQeXl5kr6Z8/Ay7ctczROsohEbG4tmzZo5WwymklEpDTgKhQJhYWEQBAGRkZGYMGECFApFqTxx8vLyjBYYmZmZjhbbociTYcpd+0wNPDk5OTAYDEhMTIRSqcT9+/fh4eGBGzduoEqVKtDr9cjIyED9+vURFhaG999/H4MHD8ayZcswatQoNG7c2KFy3717F2PHjsX//vc/AECzZs2waNEitG3bFsnJyfDy8rKY+LUkWJvUM47H3fTIWch3dsUEufLFglyPk5OTi+R2kYeLREVFSTtJlrzRQkND8dprr+Gdd97Bxx9/jP79+6Nhw4blft+2SE9Px6BBg1BQUIA+ffpg+PDhkmchgCJJygHzE2ARczvKprvqrugVU556VBn6yJycHKk6lVgdxrRNaTQaZGdnIyIiAn/++ScmT56Mr776Cl999RX+97//YfTo0RgxYoQU7uAssrOz0bt3bxw8eBCBgYH46aef8MgjjxglH87Pz0dgYKDU1pOSkqT3LN63SmW5/LSIuZAdsT9yFa8Ua5RWjyq6blgzDJhWN5UbKcwZd5RKJVq3bo327dsjLCysiEHyzp072LBhA9asWYOTJ0/i119/xa+//oqYmBi89NJLGDZsmJTzUM69e/ewbds2/PLLL/jjjz+M3mdqaioGDRqE3377zWFepfKcN7Vq1cK2bdsk7zO1Wo2cnBwpUbr47OzdABCPiYyMNNJDW7iaJxjDlAR7cglVJk8n9wkmdRDibkfHjh0RGxuL4cOHIyAgAGPHjsWGDRtKfN6PPvoIgYGB0j9Xd+8UJ6R6vR4q1YMqKWLJV3EwViqV0Gg0SExMRE5ODu7fv4/g4GApkaG44x8WFob8/HyEhISgV69e6NGjBwwGAyZPnuyQ3SUiwpUrV7BkyRLExcXhf//7H5RKJd5//338/PPPUvlkW+V6uYKL6+NuelRcHNUGzbV1UY/lk+Lk5GQAKGLUVKkelk0WE7eGhobCy8vLomzDhg1D+/btkZ+fj7Fjx9q9428v+fn52LhxI55++mn069cPv//+e7H6DyLC2LFjpbw3q1evhk6nQ1ZWlpRoUMzHIS5KExISkJWVZbUai+k7s7csuC3Ksj9yVz1ytT5alCcnJwfXr1+XkojKvzfnuert7Y25c+di/fr1qFatGm7duoV3330X0dHRGDRoEPbs2eMUzwtT48327dvRoUMHo6TFQUFBkoFKbOs6nQ73799HUlKS0flM+xxTzH0vnhOAS71rc5SnHrla27eHpKQk3L9/HwkJCZKeAA+9b/Lz86W2JB+D5HojL0lvbfMtKCgIzzzzDL744gt8/fXXeP755xEYGIgbN27gnXfeQa1atTBkyBAcOHAAFy5cwJw5c9ChQwdER0dLm35iXrgXXngBCxcuhL+/Pw4cOICJEyc6RB9Nq039/PPPCAkJgZeXl+TFFhMTg9jYWCkZuC0dcgTupHMMY4oYnjlkyBA0b97c6r/Y2FjcvHnT2SKXCwK5uv9mGbFz50706tULZ8+eRUJCAsaNG4fU1FQsWbIEgwYNAvCgM7Z3wDa3U1OzZk1kZGQYVTYqD+Sv1NIOiXxxJ69AJSJWpwIged5ERETA398fPj4+kkdOfn4+gAdup97e3tDpdLhy5Qr69euH3NxcrFu3Dv3797conzn0ej3OnDmDw4cP4+DBgzh06BDu378vfd+gQQP88MMPeOSRRwDAaCFqbTdd3Pnz9PS0mlySQ6XKnszMTAQGBhbRD1fSI0dDRHa3QUcgv5Zp2KLc20av1yMvL09KYmwpF4xWq8WVK1fw5JNPIjs7GwsWLMCYMWMsXt/eEKr79+9j+fLlWLlypZGeA0Djxo0xefJkPP/88zb7jSVLluD1119HlSpVcOjQIbRo0UKqkKPX65Gfn2+U30f0LszLy0N0dLTZe87JyZGSrzr6ndlqC/b0QxVJj+zVD0eHUFlDlCctLU0KH/b19ZWSYJvmzTH3/4IgYOPGjVi6dCmOHj0qnbtevXoYNWoU/vvf/1rNF2d6vwaDAYIgmP3cGmLOGzFs6ptvvkHXrl0BQBrr5bv68jnBjRs3kJ2dDT8/P8TExFi9jr1YetfOGH+dqUdiO3VEfyA/X3kgtou8vDxUq1ZNkt3SvYiGHTni36bzULE9azQapKSkSH23RqORkvL7+vril19+wVdffYVjx45ZlPORRx5Bu3bt0KFDB0REREChUCA4OBjXr1/HoEGDYDAYMHfuXEycONHu0EbTECrTalOLFy9G9erVpTWEI8KXSjt/MPd7R+qbJT0q6XGuzj///IPmzZvj+PHjHEJVxthb7WvIkCFu/z7s1Y9Ka8C5ffs2mjVrhk8//RTx8fHYuHEj3nzzTaSlpWHFihX4+eefkZKSgrVr1xbJB2EPzuyg5K9U3mGbhlhYQ/xdfn6+UUywmMBYnhNHqVRK9ykadBYsWICFCxdCoVAgPDwcERERiIiIQGRkZJH/RkZG4u7duzh06BAOHz6MP//8s4irslKpRP369dG6dWtMmDABjRo1kr6T7yxYG9zsjQNmA07ZU9kGeuBhmdDyikU3zdshD48Sdz3F/DheXl7w8/MzMvTIj5cvSmfNmoVPP/0UKpUKU6ZMwbhx48zmlrFlwLl37x5mzZqFb7/9Vpqsh4WFYciQIcjPz8c333yD7OxsAEB0dDTmzZuHnj17mj3X7t270b9/fxQUFGDBggWYMGGC9J1oxPHy8oK/v7/UN9hr8JXn7zA1gst/X9x3a+v40hhwSnqcM7FXPxyxkLV1HXlJZPlnwIMqbR4eHlAqlRbDCEUvL7nxVKPR4NSpU/j++++xceNGqW2rVCrMnj0b//d//1ck71tOTg7OnTuHU6dOSf/OnDkDX19f9O3bFwMGDECnTp3g6elp1YBz584dDBo0CMeOHUNgYCDmz5+PFi1aSCEn5gy9pomMS9tv2asvrmTAKelxxUFeBa20/YH8fKXFnvdlqifyUF5zOW9M52jW5mxie7506ZJUKTQ0NBR6vR4eHh5SWzUYDEhJScHBgwexdetWbNmyBQUFBejYsSOeeeYZtGvXDl5eXkhLS4OHhwdycnIQFBSEwMBA+Pn5Yc2aNZg6dSoEQUDfvn0xePBgdO/eHVWqVLH5jE6dOoV9+/Zh//79OHDgALKyslCrVi18++23ICJ4eXkhJibGprHF3rHD9HkXVx/NXYcNOCWHDTiuRUV5H2zAsYNGjRqhTZs2WLlyJQDg119/xWuvvYabN2/Cw8MDhw8fRtOmTUuUE8fZBhxzHb0YB2tpV0Q+2Mo/k5cRFw03poYc4MFAKv/88ccfx7lz50p0D35+fmjZsiWaN2+O9u3bIy4uThrQRU8B8boKhcJhk0yADTjlQWUb6AHnJasUrytfVJrzHJBXl9Nqtbh165ZZw87du3cxaNAgHD58GMAD1/bBgwejadOmeOSRR9CwYUP4+flZNODodDosWrQIn332mbSI7dixI4YMGYJWrVrBw8MDvr6+CAgIwPz587F8+XLJM6d///6YM2cOqlatKp1v9+7deO6555Cbm4v+/ftjw4YNRXTY0oJCxNrixF6PPkd7V1VGA449OGIha+tdmfterkcajQZqtdpiQn7TY7RarbR7qFarodfrsXbtWixZsgTnz58HAHTp0gUvv/wyLl26JBlrrly5YvO5qNVq9O3bF8888ww6d+4sbWiIHD58GC+++CLu3buH4OBgrFu3Dg0aNJB+Czz0FpIbeuWeZ8XZ/LGELYOoSGU14NiivA04ZdG/mea+keuEab9syQPHdNzy9vbG7du3JSNPzZo1YTAYjOanPj4+SE1NxZ07d1CtWjWEhoYazW8nTZqEpUuXStcODw/H888/jyFDhkh5HPV6PU6dOoUDBw5g//79OHToUJGNxvr162PTpk1QqVTSdSMiImwaZRISEqBUKq0mA5djry7ZAxtwSk5FMRhUFCrK+7BXPyplEmPRgl+vXj3cuXNH+vypp57CJ598gmvXrkGpVOLy5cto2rSpWy7orRlrTAdKeTyyrbwOKSkpkiu1PIGnuR3L7du34/bt20hISMDNmzeRm5uLO3fu4NatW9BqtcjMzIRGo5ESJDZv3hydOnVCly5dULt2bWlwNC1rDDxwV9VoNMjKypJcus3FEXP2fYZ5gOnkV/65SqVCTk4ONBqNdJyYeNE0MaRCocB3332H3377DQsXLsTFixexePFio2PEOP/Y2Fg0atQIsbGxqF+/Pn7++WfMmDFDKhXbokULfPbZZ2jfvj2AB7utKSkpUCgUiIqKwtSpUzF8+HB88sknWLFiBTZv3oxdu3bhvffew0svvYR9+/ZJxpuePXvi66+/lirnyA02tpKJmkvyaCk5sbyvE0MsxPOXRTUqpmxIS0uzuFiyVH1MbFP2JPAOCgoy+q1SqTTK8TFq1Cj069cPCxcuxKJFi7Bnzx7s2bOnyHnUajUaNGiAxx57DG3atEHTpk1x+/ZtbNq0CVu3boVGo8GKFSuwYsUKqNVq9OnTB/3790fnzp2xatUqTJ48GQUFBWjQoAGWLFmCxo0bF2nb8gWx6K2mUCiMjDelTYIqnicvL48TqroJch1xdP8m1wlreQuBB+XpTZP2itUTdTodQkJCkJqaCm9vb+Tk5Ehe4zqdDoWFhUhJSZGqPvn4+Ej/xGOmT5+OIUOG4Ntvv8WmTZuQlJSEhQsXYuHChYiLi0NkZCQOHz5cxGDj7++PZs2aoWXLlujSpQuaNm0KDw8PafPCnopWoqE0NzfX7mfLusQwTKX0wBE9aj777DN8+OGHuHjxIsLCwvDCCy9g165dmDBhAn744QdcvHgRmzdvRr9+/Yp9DVfxwLHHcGFud9pcCJVWq8WdO3egVCqhVquN8gOlpKSgoKAAHh4e8PHxwe3bt6UcOenp6QgICJDOrdPp4O3tjZCQEKhUKqSkpECv10uDY3BwMEJDQ5GWliYZoUSvG3FHJTU1FSkpKQAeGHiio6OlexGx5nVkDXc02LkblW2nBnC+B44ccyEeycnJknEbgLTraRpWlZSUhNzcXAAPShLv27cPf/75Jy5evCgZYGxRvXp1vPbaaxgwYICUNBV4EOcs9lvySgJarRbbt2/He++9J3n1Pfroo7h06ZJkvPn+++/h5eUFHx+fYu8Wy/tLwLonn/zcABzqdSOHPXDM40gPnOLsYFvLKQUYG3jEv82FL4p/Z2VlQafTQalU4tSpU5g7dy5u3ryJ+vXro06dOmjatClat24tvS/RayA1NRUhISEIDQ1FYWEh9u3bZ2TMEfH390dWVhYAoEePHpgzZ44UQuLh4YEGDRoUuWdxQyUjIwP16tWzO9ywODgqVMiRsAdOUSz1oaVpC/JzyjcUzBkuDAaDVNktLy/PyIgjyiF64Iifp6SkGM0ZU1JSkJqaCgDSfLRGjRpGhpWUlBQkJycjMzMT1apVgyAI2Lt3L9atW4c9e/agoKBAOjYgIABt27ZFq1at0LVrV6moh8FgQHBwMAAYGYaUSiWUSmWRsaE44401HKGX7IFTciqKx0dFoaK8D/bAMYPBYIBCoZA6rBo1akjeJ8OGDcOuXbuwYcMGdO7cGQ0bNsScOXMQGxvrZKlLhqXdY3PId6flSeY8PT2Rn5+PwsJCZGRkQK/XQ6lUSnH68nwaWq0WRISQkBBp4BKNP+L/iwYb0wmGj48PdDoddDodCgoKkJ6eLu2QiG6oIuKOire3N6pXr47c3Fzpe9FYk56ejqCgoGKXaGSYioC1xOWmi0jTXXi5Tss9COTnUCqVyM3NhV6vh16vR+/evREfHy8ZYtPT05GQkIAjR47g2rVruH79Oi5evIiMjAz4+flh/PjxGDlyJIAHfbJcDjExrDm527Rpg7Vr12LLli2YP38+Tp06BQCS8cZgMCA1NVUyCJnzNrKE/Jq2yhyb9imi0Tg5OZk9/VwMS7pQkh1sU/0wlx9K9GQV27H8t6ZtWtyl9/DwQLNmzfD9998DeBgaLI6X8gVWYmIi8vPzkZqaitDQUHh6eqJr167o2rUr5s+fjx07dmDTpk34/fffkZKSAkEQMGLECIwePRpqtRo6nQ4pKSnw9va26I2nUCiKlDq3NZ+w1ueYfl6cuQnjWIqz4Lc0dyqNN5ap0cZcyL5pZcWUlBSpOqI5nZLnfjI3ZxRzM4rHm3rFqFQqZGZmwsPDAzqdDrVq1UK3bt3QrFkzpKWl4Y8//kBubi66dOmCDh06SHNhMUeOaFAFHuZ9Cw0NlXJEmpt7yp9hcSpQiRsowIMwL9Ylhqm8VBoDjmiVJyKcOnUKcXFxePzxx6FSqdC8eXPk5+djw4YN6NixIwBg4MCBePLJJ+Hv7+9kyUtPcQZtcRIq3yERq7dotVopobNSqYROp5NifUXDjnj+1NRUybji5+dnlF/D9HrihNXHxwcZGRkICwuDTqcrUhJZPM7T0xP+/v7S4G4wGIyMNeLuqHi/PMAxFRFLem1pgm1tgQmYX2QCkMKqxH96vR7BwcGSPsoXZlqtFjVr1kT9+vXRrl07aTJNRLh8+TI8PDwQEhIiTXjFc5hew/Q+RW8FX19fDBgwAE8//TQWL14MpVKJjz/+GF5eXkhNTYVer4dWq0VYWFiJjba2jL7mwk9sGX0Y52BJF8R3WBwDv/y9y0vSy9utLaOhaPgBIOlCcdqLGCoibpTIr5ednY3OnTujV69eKCwsxKFDh6DT6SSvAnHhKlbRMnddlUqFqKgou8Kp5SQlJZmtUlXcxb68T+NNF8dTnPdhae5Umk0x0/cqGm7EjQHTdqdSqVCzZk2rhlNrMosGHXG+aIqoQ9WqVZNCscTNRIVCgerVqyM+Ph5KpRIeHh6Sh7k49/Xx8THKySjXR/nGoiibpWdo7xw9JydHyhvnaG841jeGcS8qhQFHNEgYDAY0b94cHTt2xOzZs6WdWr1ej02bNqFTp04AHnrqVATjDWB+0La1M+nr64ukpCRkZWUhICAA4eHhUo4MrVYLQRAQGBgoJRwVB64qVaogMDAQd+7cgYeHB3Jzc1GrVi3k5OQgPT29yA5LRkYGACA9PR3BwcFGOzPyZIx5eXkwGAySO69Wq0VaWhoUCoWUxNiWsYZDoxhn4uj2Z2kybjo5lF83PT0darXarCzyz/z8/ODn5ycZJnQ6nfSZaVU+rVaLjIwM+Pr6GiUXViqVkls5ANSpUwf379+XvOjCwsIQHByM5ORkZGVlISUlBVFRUUUmkr6+vkhJSYFKpZLKnXt6ekrJ50WCgoKkxXFpvGFKYvQ1febJyclITk5GWFhYEfd57ofMUxbPpbjGOGvI5ZN78GRmZiI5OdnuajPifETu5WLPAi4nJ0fKDQXAKFeNSEZGBgoKCqBSqdCtW7ciSWPv3r2LwMBAo5BmU0q6mDMXulPcxb68T6ssC0pHt3tr55O/j5KGZFkyspcklEfUByIqkgtHbNei17xCoUBOTo6U90Ych0wrt8kJCAiQQhBMvXxycnKQmJgoVScUDY83btyQzh8TE2N0bwaDAYWFhUZhvyJVqlQpEu6Qnp5u1YAsYq9hzdfXV7rv4rxDSxTHoMfjFsO4FhXegCM33rRq1Qqpqano27cvvLy8UKVKFfzvf/9DTk4OWrZsKf3G2oDgjpibRNnamTSHuBMuHieez9yET61W49atW9DpdEhISAAAszsspl4zYjlic7sW8oR6JcltwzAVCUuLI2s6bJpY1VYcvj0LsJJOPuXyajQayU3enAFH9AoQjeridcwlK3aGN4zpM09OTkZGRgZSU1M5rMqJlNQD03RBavq33IPnxo0b8PLysqu9lSYsRe5BB0BKMh4RESF9L4Y8m9MjMTF5cZKl2nouIuHh4WbnAcV9/hzyXLaU1Dhny0BTnE1CU3lycnIQGBho1XApN+qVtH2YFuuQJ+oXdcgc8jZsz9hi6tVij7zWjjN9jrVq1SrGXVuH9Y1h3JcKbcCRG29atGiBzMxMrF69Gh07dpQSdTZp0sTJUjqWnJycIol8zU2i7Om45Z41wIOBTO6VlJycbGTIkS+mRKPK/fv3kZWVBX9/f6MKHPJBydQAY2mQlO/m88DDVHZKuziST4wBFNugKz9vUlKSlBDW0vEqlcoovEL+e9FAY/pbc32KHNGoLJZsFn+j0+mMSiQ7KgGrvYSFhSE1NRWBgYEcVuWGmC5IrRlYxL+LG4YFGFc0s1aNR/ytqY5ERERIei2XBXgwjspDU8TvIiMjS9wec3JyjDyO5HMDW+e0Rw9NPXQZ18CWgdHWJqH4t+m7L8n4UtINO1P9Ef/r7+9vFNooGl7MtcPibmiIaQC0Wq1Vr1Brz8HSc3SEnvDmAsO4LxXWgGPOeLNs2TLJeCNWoqpoiJ19WloagoODLQ649i7+TI0mwMM4fqVSKYVUiYOUmBdAHAxFg49arTYacCzFzIvXMV0Qmg6cJd1ZZZjKiqnOmDPo2JoUWkpK6uvrW2yvF/Fc1o6XG2jMhVfJvXc0Gg2CgoKg0+mMPI2Km4fDnnu2hZiDh43M7onpu7PmOePl5WW0OQHY9uCR/95eT1LTRZtcb8VwKn9/f4SFhUmbIAAk2cwt+szJZa29ix5u9nocmT4rzhPlnpQkFFH+m5J66Ijnlo8vQMmqNpnTH7nHplj8QjSkmjOKlnRDQzR8ajQaREdHl3jjpTKGGDIMY54KacCxZLzp1KmT5HlTEY03wMPOXpwMlqaTFwei/Px8acAQjTQAkJ+fL1WeAR7ucIhu3GK5VdGYYy/mFoSWBk5n7K4zTEXAVKfs0S9xApmUlCRNgM0ZWC0hP594LrF/MBf6UZLwKnkSc/G/ctmK22eUdOHJRmb3xZxu2Ot5ANjvwSP/vT1hKvKxVNQ7c6Eg4lhsLdeNOTkBSLnv5HlB5NeMiYkp0QKSDZruS0n6MtPfWPPQKU7ooa3f2aNHGo0GwMOqh2Jif/m1SlNpy9yGxt27d6XqqKUZR1iHGIYBKqgBx9PTE3q9Ho899hjy8/OLGG8qMo40ZMgHInHxJJ8YiqVQxYmjPObXkleOeE5LMfPy+7BnoOJdPYYpO0z1S9RL0/LL9k7wzeUzkO/ImtvFFQ00QNGwTfEYW6En5rwe7O0zeOHJWMJew46lNiT/vegJYGocFRHHUtFTQD4mAw/DqcTr2dNeS9K2S2qYZINm5cWWh05xf2/td7a8XUxzOVqqWFiaPt/cvVWtWhX5+fmlGkc4xJBhGJEKacABgBMnTuDWrVvYuHFjpTHelAWmiyw55iaO4m8AGBltABQxBJm60sp/b+9kryQ7/zwAMswDbO1WWgpdNOcmbs/55ecTPRNu3rwJtVptMYRE7upuLZzKXoq7aOWFJ2MNS2GF9njwmEt4KjeOAjAykso9BcTzWRvTkpOTpfxQ4u+tyQlYTkjMMI6kJP2qpfHKVI80Gg2USqVZY6hKpSqSDN+abPaEGVpKci4iN6zyWMIwjCOosAacFi1a4Nq1awgICGDjTSkwHYjkmfytDUSmuxziIGfJpVW+syhOWO1NeliSnX+GYWx7o1jSL0tu4rbOb3o+jUaDvLw8aDQamzlAbIVTidjqN+ztMzg8k7EHW/k9xGPMtSP5b8WEp+bCRbRarUVPAWvI9UutVtvlecYGS6YscER/mpOTIxnx5d41pnoUHR2NnJwcs7pZXOOkuXPYGyIpwjrFMIyjqVj1sk0IDg5m442DUalUUlJE07Kmpsf5+/vD399fmpRamoD6+vpK+XLklTjkg2JpEa/BxhuGeUhp9MKe39o6Rq1Ww8vLS/IqsHW9qKgoqU+xhKP6DUf2P0zFxVwbl7cda+3I3G/FsA5x3DRNkFwc5Poljt08BjLOwBH9qa+vL/Ly8qQk2vLP5W1b1KHw8PBSt3lzOmr6Gc8vGYYpbyqsBw5T9ljzqhEHMnsSGNubR8AS9ux2cuwwU5Ep6e6mOd0rTnUQW9eydUxYWFixysLas3takrwe5u5Zfh72xnFvyvL92ZPfw1J7lO/oy/+Wy1yasctUvxw1BrI+VB4c9a5L0i+bu77oXWNq9Cyt54uYu9Hc3NH0HPaGSDoC1jWGYczBBhwXgIjsOs7ejtzeClv2XtdUBntduuXHlmTiWJLwKACc1JipdFhz4S5uf2B6LnebQJZkMm3u+cnPIyaY5X7FfZC3e0eE0No7XgqCUMTQaO6alvTNVOaSjp9lSUmKBzi68qe198E57xyHvbpjSz/E/rS041FZGUvE+aq9bbq82rPp/RenH3LkcURkcy5QkjWFq3Lz5k2pWpklLly4UE7SMExR2IDjRpRk0uRozO2iWOrUxWOBBwsgRy4AtVotkpKSpOuYhl7xpI2pTJR0d9PWubRaLRISEqBUKgHA6Qad4ly7OMfaen6OfL5M+eOq70+ewD8wMFD6LCkpCTqdDj4+PtLnts5Rnvroqs9ThHPeOQ5nv2tL1y9tu5fPIcPDwwEA6enpdoXzlifOfv5yXGENUh7cvHkTsbGxdkcQuFqbYSoHbMBxI1yhIze3+5GUlITs7Gz4+fkhJiamyLFlsXstJrMDIOXXkV+XYSoT1kIxSnIuueeJUqk0Kn/qzElcca5dnGNt7epyEkr3xlU9MXJycuDl5WWU5yYnJwfZ2dkA7Kta4wx9tKYPruCx5wpzpYqCs3XHUlsrbbs31TMACAoKKpWsZYE9Y0956Vxl0Suxgu7atWsRGxtr9Vi1Wo2oqKhykoxhHsIGHDfC0YsIZ3X6jriur6+vVAqyog8mDGMPZbGQkydpNJcbprwpzrUdsXPrCotRxjUoi7Zgro36+vrCz89P+n9b13e1RZUr7NKzwbV8EZN1O8MLDCiZh7c5PXMlPSoO5aVzlU2vYmNj0axZM2eLwTBmYQNOJcZRnX54eLi0S2Nukmna6TviuiqVysjbh2EqO2WxkLMngWNJKcmCuDjXdsTOrSssRhnXoCzagiX9Mje2Wbq+eA6tVuvwUOWS4GoGJabscaYXWEk9vM3pmfh7dzPcs84xTOWjQpcRZ6xjmjvGHsRJojw2VKV6WPbUNKGwo67LMIx15HpYWszpuaOxp68oC4rT/3BfxYg4uy3Yun556JM9/YIj+yHGPXCmbpTFtct7bMrJySnVeMs6xzCVD/bAqcSUplpLUlKS5HVTXHfuyuaGyTDuRnnsqDpr19De/sfddmGZssXZIcy2rl8e+sQeaYw5yqKPtFc/ymI+Wd5jE+sVwzDFhT1wGIuY220TdzsAmN2h4J0AhnF/ymNH1d6+ojy8gczhLA8hpnLg6PZlSZ8cqT/O9kJiKg/O7H9VKpVkxCmPcYf1imGY4sIeOC6CK+72mtsVEHc7OOaWYSouruQl56zdyeL2ca7YhzOuS3mNobb0pzjt1pX6BaZiUx76Ya3tl+e4w2MGwzDFhQ04LoIrulBaG0BdLXEiwzCuS2mMG64eaiXiin0447qUpzEkLS0NYWFhZr/jdsu4IuWhH9bafllUT2UYpuy5cOGCzWMqQvl3NuC4AIIgGA0WgiA4WyQA9g2gJZn8ucr9MYw742g9cvT5iEj6f2v9hK3rirm25OezRlnehzXYK7FiY2+7sre9lCfBwcHS/5vehyvOPezBnWStDLijftizSSlS1oZOV2/P9sjn6vfAVGzUajVUKhWGDBli81iVSoULFy64tRGHDTgugrhIcTd40cIwjC0qQz/B4SWMK2JL99x17sEwpaU4fXZlGMMYxp2JiorChQsXoNForB534cIFDBkyBBqNhg04TOWFFy0Mw9iC+wmGcQ6sewxTeliPGMb1iYqKcmujTHHgKlQMwzAMwzAMwzAMwzAuDhtwGIs4q3wvwzCMKdwfMYx9sK4wTPFhvWEYxl1gAw5jkaSkJNy7dw9JSUlFvuOBjmGY8kSeRLI8r2lvP8d9ImMNc+2jrNqMM3SFYUpKeeqGNVhvGIZxF9iAw5QI+UDHCxeGYeylpP2Fr68vPD09yzWJZHEm9Dz5Z6xhrn2UVZuR6wqPz4yrU566YQ17xhhRn7ifZxjGmbABh7FIeHg4IiMjER4eXuQ7+UBn70DLAx/DMCWZmOfk5EgVQMozkWRxjEbOMDAx7oOl9pGWlubwa6lUKoSFhUGlUrFhkXF5zOlGcYwpjjJOyvXGEqxPDMO4AlyFipHQarVGiyRrWfdNv7OnvKJ84ONFDsNUTkpSjlXed5S3AcfW9eT9ZlhYWDlJxrgblsbT4OBgi78xHZNLApc/Zlwdc7phT9WnnJwcZGZmIjk5GTExMeUyNrA+MQzjCrABh5Eo6SLJ3vKKPPAxDFOScqyu3Hc4y7jEuD+22rUj2haXP2YqKr6+vkhOToaXl1e59b+iPgmCUObXYhzPzZs3odForB5z4cKFcpKGYUoOG3DKGCICEVk9xtEDga3rWbqufDJZEplsXZcHPoZxf+ztXxyJr6+vSxpvgNL3m0zFojhtwFa7Lk7bslcvSzo/cFfsuV9n9GmVFUe2K19fX8TExNilI45u96xHJTvGmdy8eROxsbF2hdypVCqo1epykIpxFvYY6tRqNaKiospBmuLDBhxGwlGLJEe4fTMM415UVr1nwzRTVpSF4bKy6ilTMXEl4z7rlmuj0Wig1Wqxdu1axMbGWj3WlRfuTOlQq9VQqVQYMmSIzWNVKhUuXLjgkm2BDTiMw+GQAoapfLDeM4zrw3rKMGUD65Z7EBsbi2bNmjlbDMZJREVF4cKFC3aF0g0ZMgQajYYNOJURrVaLgIAAZ4tRrrhyvgqGYcoGc3rPO5IM41rw+FwULrHOOILKrlusR4y7EBUV5ZJGmeLABpwypjJ2aJw0kWEqH+b0nnckGca14PG5KJVxnsY4nsquW6xHTEXEVXPlsAGnjKnMnTnDMJWbyr4jyTCM68PzNIYpPc7UI64uxTgaV8+VwwacMoYnBgzDVFYq+44kwzCuD/dRDFN6nKVHXF2KKQtcPVcOG3AYhmEYhmEYhmEYl8FezxquLsWUBcXJlVPeoVZswGEYhmEYhmEYhmHKhZMnT8LPz8/i98nJyejfv7/dnjUdOnRg4wxT7hQ31Grz5s0ICwuzeEx2drZd12UDThlBRACAzMxMm8cKguDQa+fk5ECr1doMX3D0dcV7toWjr8u4H6Je2GozxdEjpnywV8/txdX7A0v3q9VqjfpZZ9wH6xEjIm8Dpm2zJLi6XtqLPf0V61HFh4js0gt7231lm++WhR516tTJ5jl9fHywadMmm2FPoaGhCAoKYt1kyp2goCD89ddfSElJsXqcRqPBkCFD0LNnT7vOa0uP2IBTRmRlZQEAW4MZxgpZWVkIDAy0+j0A1KxZs7xEYhi3g/WIYUoP6xHDlB579cgedDodnn32WUeIxTBuhS09EsjR26kMAMBgMODOnTvw9/cvkQU+MzMTNWvWxK1btxAQEFAGEjoWd5MXcD+ZK5K8RISsrCxUq1YNCoXC4jmKo0fu8nxYTsfhDjICZSdnWehRWeMu76y0VIb7rCj36Ag9ctdn4a5yAyy7s7AkuzuORyXBnd+dKRXpXoCKcT/26hF74JQRCoUCNWrUKPV5AgIC3KoRupu8gPvJXFHktWZZFimJHrnL82E5HYc7yAiUjZxlpUdljbu8s9JSGe6zItyjo/TIXZ+Fu8oNsOzOwpzs7joelQR3fnemVKR7Adz/fuzSo3KQg2EYhmEYhmEYhmEYhikFbMBhGIZhGIZhGIZhGIZxcdiA46J4eXlhxowZ8PLycrYoduFu8gLuJzPL61rXKyksp+NwBxkB95GzPKgsz6Iy3GdluEd7cddn4a5yAyy7s3Bn2R1BRbr/inQvQMW7H2twEmOGYRiGYRiGYRiGYRgXhz1wGIZhGIZhGIZhGIZhXBw24DAMwzAMwzAMwzAMw7g4bMBhGIZhGIZhGIZhGIZxcdiAwzAMwzCM0+GUfAzDMAzDMNZhAw5TprjbhJzlLVvcTV7GGHd5f+4iJ2PMjRs3nC1CmcLtsuIivlt3fMfuIrNcTneRuaKQl5fnbBFchoqi6+4ovzkqa9tkA44bcffuXSQmJuLkyZPOFsVuNBoN7t27h3PnzjlbFLMUFhYiOztb+lsQBBgMBidKZJ3MzEzcuXMHd+/eBRG5vLwpKSm4ceMGrl27JslbnriLzty5cwdXr17FkSNHnC2KEe6iH0lJSbh69SpOnz4Ng8HgsnIyllm+fDlat26Nf//919miOAx30Z/ScuTIEVy6dMnZYjiVu3fvAnjwjt1tYWQ6LrtqG01KSsLt27dx5coVFBYWOlucSsPWrVsxc+ZM3Llzx9miuATurOsVTYcqddskxi344YcfqFWrVuTv70/e3t60Zs0aZ4tkk82bN1PXrl0pIiKCvLy8aNKkSXTz5k1niyXx008/0aBBg6h27drUoUMHevXVVykrK8vZYllk69at9OSTT1JISAhFR0fTyJEjqaCggIiIDAaDk6Uryvr166l9+/YUEhJC1atXp2+//bZcr+8uOrN+/Xpq164d+fn5kSAINHz4cEpNTXW2WG6jH5s2baIuXbpQSEgI+fr60nPPPSfphStx7tw5+vXXX+n777+nkydPOlscl2L58uWkUCho8eLFzhbFYbiL/pSWpUuXkp+fHx08eNDZojiNNWvWkKenJ/3444/SZ644Jpvj6NGj9Nlnn9HkyZPp888/lz7X6/XOE8oMP/zwA7Vp04YCAwNJqVRSt27d6Msvv3S2WHZx9OhR+vLLL2n8+PH0008/udQ82BYXL14kQRAoODiY3n//fbp7966zRXIq7qzr7qxD5qjsbZMNOG7A2rVrydvbmyZOnEjvvfceTZ8+nTIyMojIdTuO1atXk7e3Nw0YMIDGjh1Ljz32GAmCQOPGjXO2aEREtHLlSvL19aVnn32WxowZQ02bNiVBEKh+/fq0bds20mq1zhbRiFWrVpFKpaI+ffrQSy+9RPXr1ydBEGjkyJEu2QbWrFlDKpWKhg8fTjNnzqQxY8ZQenq60TFlKbe76MzKlSslOWfPnk0DBgwgQRCcvpB1F/1YsWIF+fj40LBhw+jDDz+kFi1akCAItGrVKmeLZsS3335LNWvWlIx0Y8eOpcLCQmeL5RIsX76cBEGgJUuWGH1uMBhcSleLg7voT2lZvnw5eXp60sKFC50titPQ6/X0zDPPkCAIVLVqVVq3bp30nau33zVr1lDNmjVJrVaTIAgkCAJ17dpV+t5V5F+9ejUplUqaNm0azZs3jz744APy9fWVNjxcRU5zrFmzhurUqUOhoaEkCAJVqVKFXnjhBbp+/bqzRbOL5ORkqlatGgmCQH5+fjR9+nS6f/++s8VyCu6s6+6sQ5ao7G2TDTguzvXr16lp06Y0e/ZsysvLIyLX2xkxZd++fRQZGUmLFi2izMxMIiI6c+YM9evXjwICAujff/91qnx79+4ltVpNCxYskCbSGRkZ9OGHH1KNGjUoMjKSVq5c6TK7pXv27KHw8HD6/PPPpeeZlJREzZo1o6ioKCPDiCt0wteuXaMGDRrQ7NmzKT8/3+i78pDPXXRmx44dFBgYSPPnz6ecnBwiIjp//jyFhobSG2+84TS53EU/fvvtNwoMDKTPP/+csrOziYgoPT2dBEGgOXPmGB3rTL3YtGkT+fr60kcffUQHDx6k7du3FzFmVla+/vprUigU9MUXXzhbFIfhLvpTWqwZ3iobo0ePJoVCQY899hip1Wq32J3/4YcfSKlU0rx58+jUqVOUmJhIffv2JUEQ6J133nG2eBInTpyg6OhomjdvnpFn5cmTJ6lLly4kCAL179+fcnNznSilecRn/PHHH9Phw4fpxIkT1K9fPxIEgVasWEFErts+iB7Mm3Jzc6lbt240ZswYGjx4MAmCQNOnT6d79+4RkWvLXxa4o667sw5ZgtsmG3BcntOnT5Ofnx/99NNPRPSwQR4+fJjeeecd6ty5M73yyiv0888/O1NMInoo24wZM6h169Z09+5do13mBQsWkEqlovT0dKfsQIryvfvuu9S8eXNKSkoiooeLe51ORz/88APFxsZSWFgYrV+/3qm7wOJ1p02bRh07dpTkFZ/p8uXLyd/fnzIyMkin07lMZ3X06FEKDAyk/fv3E9HD53v06FH6+OOPKT4+nl5++WW6du1amRhWXF1nDAYDFRYW0v/93/9Rt27dSKPRGBm6nnzySfrkk09o1qxZtGDBAjp69Gi5yUXk+vohXnPEiBHUo0cPSktLIyKivLw8ys/PpyeeeIJWrFhBX3zxBS1ZskS6D2eg1Wqpd+/eNGzYMMmYKJKRkUE5OTlu5U7vSFatWkWCINCCBQuI6EG/Jral48eP04cffkjPPPMMTZ8+nXbv3u1MUe3CXfTHEaxcuZIUCgUtXbpUkl/8b25uLul0OtJoNM4UsVwQ73nt2rX0yCOP0MKFC6l27doUEhJC69evNzrGlUhKSqKOHTvSuHHjjOZiycnJFB4eTn379nWecCZs2bKF1Go1/fXXX9Jn4hzoypUrktfqCy+84CwRzXLv3j1q1aoVvfrqq6TT6aTPb9y4QVWrVqVevXo5UbriMXLkSHrssccoLS2N+vbtS56enjR9+nS6ffu2dIwrtnNH4q66TuS+OmQPlbltsgHHxfn1119JEAT6888/pc82b95Mfn5+VK9ePSm/TEREBM2bN8+Jkj6kT58+1LBhQ+lv0aq7dOlS6tmzJ02bNo2aNm1Kzz33nJELYlkjKnH//v2pTp06UkiN/Lv8/HzatGkT1alTh2JiYujatWtG35c3er2e2rZtS48//rj0mWhBnzNnDvXu3Zs++OAD6tKlCz399NN04sQJInJuh7V9+3YSBEEy4BA9bLORkZHk7+9PgiBQTEwMbd26lYgcK6+76EzLli0pLi7O6LPvvvuOBEGgevXqUbVq1UihUFBMTIy0yC1L3Ek/tFot1alTh7p06WJk/Fq/fj0JgkDR0dGSe3CdOnXo119/dYqc4oJo9uzZRPRw0rRr1y4aMGAAPfLII1SjRg166623jCYcFRmDwUAFBQVSGOicOXOMdv62bNlCYWFhVLVqVfL19SWFQkG1atWir776yolS28ad9Kc0iP3re++9J8ktGqn2799PI0aMoObNm1PTpk3pgw8+kAysFZkdO3aQp6cnXbx4kbZv305169alkJAQ+uGHH6RjXMlQe/36dQoODqb58+dLn4k62LNnT6pfvz5lZGS4RJjnnDlzSBAEunXrFhFRkbx/V69epd69e5MgCDRjxgxniVmEK1eukK+vb5Hcf4WFhdSqVStq3bq1Szxfa4h6/dFHH1GNGjUoLy+PdDqdtFB+//33KTMz022M7I7A3XSdyH11yBrcNtmA4/Jcu3aNgoKC6PnnnyciolOnTpFaraYZM2bQ1atX6fbt27RhwwYKDw+nWrVq0ZEjR5wsMdFTTz1FERERdPbsWWmAys3NpXr16tEjjzxC3bp1o6FDh5Kvry9FRUXRtm3bylW+6dOnk5eXl2SNFmUUO7O8vDxavHgxCYJATz31lNPDb5566imqW7eu0Y5mTk4OxcTEUKNGjahLly7UrVs38vDwoNq1a9ONGzeIyHmLgr/++osEQZDCgA4cOEBqtZpmzZpF586dI61WK3W6derUcfhOrTvojF6vp549e0oun/v27aMFCxaQp6cnzZo1i27cuEHJycm0detWioiIoKioKDpw4EC5yOYu+tG3b18KDQ2lb775hvbs2UNfffUVCYJAH3zwAV26dIny8vJo7ty5VLNmTapdu7ZTPHFSU1OpWrVqNHLkSOk5btmyhby8vKhVq1bUt29fql69OgmCQM8//3ylCq1KT0+nJk2akLe3N3300UdERHTo0CHy8vKiqVOn0t9//01XrlyhFStWkFqtpkcffZSuXLniZKlt4y76UxLy8/Np0aJF5O3tTb169aKrV69K97Vx40ZSqVRUv359ateuHQUGBpIgCDRixAiXX6iWlsTERAoPD6dvvvmGiIg2bNhAdevWpdDQUNq6dSuNGDGC+vbt6zJhcwcPHpSMp6bzhAEDBlCjRo2cJFlRDhw4UCR/oqgzouxnzpyhGjVqUExMDF24cMEpcppy/PhxEgSBVq9eLX0myt2zZ09q1aqV2+jFoUOHyMfHh/bs2UNERGlpadS/f3/y9PSkxo0bk6enJ509e9a5QpYT7qbrRO6rQ/ZQmdsmG3BcnPz8fOrevTupVCrasGEDLVy4kEaPHi3lfBBZvXo1KRSKIrkfyhOxI/jzzz/p008/peTkZOm75557jpo2bUqnT5+WPvvhhx/Iy8uLXn/99XKVb//+/eTv709xcXHS7qDpJDs7O5v69OlDwcHBktW6vBFl+eabb2jWrFnSDr3BYKAnnniC2rRpY1TN5oMPPiBBEGjSpElOkVdO//79KSQkhM6ePUvff/89jR8/nnJycqRBIyMjg959910SBIHmzp3r0Gu7us6Iz+Ds2bNUq1YtEgSBGjduTAEBARQfH18kvHDt2rXk6elJH374YZnK5W768f3331OTJk1IEARq1KgRBQUF0csvv0w6nc6onb333nskCIJkJChv2rdvT/Xr16cbN27QlStXqF69ejRnzhzJoHT69GkaPnw4CYJAn376qVNkLG/EHcD09HSKjY0lLy8vmj59Or344os0a9Yso3CzvLw8+vjjj10yObUcd9OfkpKamipVnurevTvdvn2bDh06RGFhYfTBBx9IGwjHjh2TEn4uW7bMyVKXPbGxsTR8+HDp719++YXq169P3t7e5OvrS6dOnSIi1/C2SklJod69e9NXX31VZCH31FNPUbNmzUiv1xvJ6qxwv/v371OTJk3Ix8fHSP9NQ/dE78stW7aUu4zmSE5OpmbNmtGiRYuK5ALs0qULtWvXjgoKCoo8Y1fk0qVL5OXlRd999530mV6vpxo1apCHhwfFx8dLeUcqA+6k60Tuq0P2UJnbJhtwXBhxYL148SJFRERQ69atqVu3bjRz5kzpe1HxLl26RD4+PvTyyy87TV4RvV5vtFjOzc2lvXv3FvG0SEhIoKCgIHruuefKVb6CggIaNWqUlLhLdHUXJ9ni4mLfvn0kCILT3e8MBkMRa/6GDRuKZFtPS0sjHx8fmjBhQnmKZ4TYHn/++WcKCQmhWrVqUdeuXemTTz6RjhGf7/3790kQBJo1a5bDru9uOpOWlka7d++ms2fPUvXq1aVdHflk+dq1axQQEEBjxowpF5ncRT/0ej3du3ePduzYQWfPnqXw8HCj3U5R3rS0NPLw8Ch312CxLW7dupW8vLzo//7v/+jSpUs0dOhQun//vpHnxYkTJygoKIg6derkUjt3ZYnciPPII4+QQqGg6tWr086dO6VjRB04evSo5F3l6riL/pSG9PR0Wrx4Mfn5+dF//vMfeuWVV2jy5MlSMnaRAwcOkIeHBw0ZMsRtvA2Ki3hfffr0oR49ehh99/jjj5OnpycFBATQhg0bnCGeWQwGA924cYNSU1Olz0QjQ/PmzemZZ54hood9mFarpdmzZzutVPzhw4fJ19eXGjZsSJs2bZI+l4/nV65cIR8fH6cZ6s2h0WgoJSVF+lvMf9ekSRMaNGiQ0bFarZbefvttl/CilyM+39jYWBo/frz0+QsvvEAhISH0+OOPk4+PD73++usVvgKQO+q6iLvqkDUqe9tUgHFZFAoFiAgNGjTAp59+imvXrmHXrl24du0aDAYDFIqHry8zMxNVq1ZFs2bNAABE5CyxoVAo4OvrK8nh5eWFTp06ITQ01Ei2pKQkhIeHo127duUmm8FggKenJxYtWoSOHTtiy5YtGD16NDIyMuDh4YGCggJ4enoCAO7evYuIiAhERUWVm3zmEAQBfn5+AAC9Xg8AGDBgAMLDw6VnaTAYcPbsWajVajRq1AiAc9qAIAgAgF69emHixInQaDTYu3cv8vPzQUTS8y8sLMSlS5cQGRmJ+vXrO0xed9IZg8GAoKAgdOnSBd7e3sjMzERqaiqAh89RlDMyMhItW7YsczndRT+ICAqFAhEREejWrRsKCwuRkZEBtVoNAMjNzYWHhwf0ej0uX76M6tWro2HDhtJvywOxrbVu3RrPPfccvvrqK3Tv3h3p6ekIDw+HQqGQ9DkuLg7169eHl5eXpOsVHbEfCAwMxKFDh1C1alW0aNEC//nPfwA8aIuiHiQlJaFatWqIi4sD4NzxzRruoj+lJTAwEIMHD8acOXNw/PhxLFy4EPXr14dKpQLwcJx6/PHHUa1aNRQWFsLDw8OZIpcZop537NgRx44dQ3JyMgDghRdewMWLF/Huu++ievXqGDhwILZu3epESR8iCAKio6MRHBwsfebp6Qkiwv3791G1alUAD+4tNzcXU6ZMwTvvvCPN4cqbtm3bYsmSJUhISMCMGTPwww8/SPKJ5OTkoFq1alI/7wqEhoYiJCRE+lsQBOh0OqSmpiIsLEz6XKfTYcqUKfjkk09crv8X++AaNWrg8uXLAIAXX3wRO3fuxJYtW/Dbb7+hbdu2WLVqldG8pSLijrou4q46ZI1K3zadYDRiSkBaWhp9+eWXVL16dQoODqZ58+ZJOyYajYaGDx9OtWvXdrnkWXLkO84pKSk0cuRIaty4MSUkJDj0OuZcUuWfiVZ0rVZLbdq0IUEQqEOHDkau7Onp6TRq1Chq06aN0Q5KWWBLXnt+l5qaSmPGjKGmTZuWuUu+LXnF95yfn0+TJ08mlUpFERER9Msvv0i70cnJyTR69GiqW7cuJSYmlomc7qQzycnJFBkZSa1ataK///5b+jwlJYVGjRpFdevWdZic7qIfxdGLW7duUWRkJMXGxhrlkUlJSaH/+7//o/r165dZO7OHU6dOUceOHcnDw4Patm1L169flzwxCgoK6Pr169S4cWOaNm2aW+VEcQTic9DpdEVCDYge9G0vvvgixcXF0d27d8tbvCK4i/6UB6mpqfTZZ58Zhe3KPW1OnTpVbknYyxtTPf3hhx/I29ub7ty5Q0OHDiW1Wi3lZfjxxx+pefPmdPHiRSdIWhRrfUxERIQU1p6dnU1jx44llUpF//zzT3mJZ5aCggJatmwZ+fj4UGRkpJHnbkpKCo0ePZrq1avn1H7eHtLT06latWr01ltvERFRZmYmjR07lnx8fJz+jM0htpV3332XHn30UeratSuFhITQ7t27jUJC3S0UtDi4s67LqSg6JFLZ2yYbcFwMa27GGRkZtHHjRqpZsyYJgkBNmzalJ598ktq3b09qtVqqQFTe2OMaff78eVqwYAF988039PXXX9Ozzz5LgYGBUqyoI7l37x4lJibS5cuXjRYEcjnli4bnnnuOBEGg0NBQmjhxIk2ZMoWeffZZCggIKBP5SiKvKefPn6c5c+bQ4cOH6dtvv6XBgwdTQECAUY4hZ8orN+J8/PHHVKtWLfL09KQOHTpQ79696fHHH6fQ0NAyb7OupDOW3qc40MybN498fHwoLi6OZsyYQfPmzaOnnnqKAgICHCqnu+hHcfSisLCQxo8fT4IgUP369WnNmjU0f/58GjhwoMOfX0k5evQodenSRQqt+eOPP0in09G5c+do3LhxFB4e7hZJessC0wnyuXPnaP/+/bRx40Z68cUXyd/fv1z6YntwF/0pL+S5zeRoNBp66aWXKDo6mq5fv17+gpUh8iouYt+SmJhIISEhVLVqVQoNDaXdu3cbPZfMzExniFoEuezyHHp6vZ60Wi1FRERI4aZjxowhHx8fOn78uDNENctvv/1GkZGRJAgCxcXFUY8ePahTp07lMp9wBOnp6VS9enV6++23iYho9OjRLmu8kfPLL7+QIAgUFRUlGSsqA+6s65Zwdx0ypbK2TTbgOJETJ07Qxo0badGiRfTLL7/YnfAqKSmJpk6dSr169aInnniCpk6dSpcvXy5jaR9QEpkLCwvpf//7H6nVahIEgSIjI6lDhw505swZh8v3ww8/UJs2bSgwMJCUSiV169aNvvzyS+l7ubxix5yfn08rV66kfv36kVqtprp161L//v3LJXN5ceSVs2bNGhIEgQRBoJCQEGrTpk25GG+KI684oOn1evrnn39o2rRp1KlTJ+rUqRNNnjyZLl26VGI5iuulUN46UxI9uXnzJn344YdUo0YNEgSBatasSd26dXNoO3QX/ShJO8vLy6OXXnqJQkNDSRAECgsLo06dOpVJPyMiPiN72+PZs2dp/PjxFBgYSB4eHhQYGEj16tWj6Ohot5w42UNxdTUhIYFCQkJIEASqVq0aNW/e3GUMHe6iP6WluO1aZM+ePfTOO+/Q+++/T0899RQFBgZWuHYtfzZxcXE0ceJEysrKouzsbKpRowZVrVqV9u7dKx3vSh515mSX52jKy8uj2rVr0zPPPEMjRowgb29vlzQs3Lhxg2bPnk3du3enzp070yuvvFKq+UR5kp6eTlWrVqVhw4bRa6+95hbGG6IHHhpTpkyhffv2uVSbLkvcWddt4c46ZEplbJtEbMBxGqtWraLq1atT1apVpYV469atadeuXVatt85MBFhSmYkehLOcPHmS1qxZQydOnHB46WiiB1WFlEolTZs2jebNm0cffPAB+fr6kiAINHz4cLOLaNPneePGDcrJySmSjLEsKIm8Ivn5+bR9+3Zat24d/f3330YVv1xJXtPONDs7W0rkV5LrT5w40eK5LVHeOlMaPSkoKKC7d+/S77//TlevXpWq2DgCd9GP0shZUFBAV65cod9//53+/fdfoySdjmbz5s00fvx4aQFkb3vMzs6mq1ev0ieffELvvvsufffddy4RxudISqqrRA/CCffu3UvLli2jP//80ynl383hLvpTWkrSrg0GA2VkZFDz5s1JEASKjo6mp59+ms6dO1fW4pYr8gVd8+bNKSoqiv744w/JE+v06dN05MgRl0zYbEl203Y7ZMgQEgSB/Pz83MKw4I6I1dmCgoKMQqZdHXl1wIqOO+t6ZaQytU0RNuA4gfXr15OXlxctXLiQzp07R7dv36apU6dS1apVKTIykubPn19kQS52JiJy1+3yKFXnCJnLkhMnTlB0dDTNmzfP6LonT540ClvQ6XRE9GBibU6+8rLelkZeZ1iYHfV8S9pWL168KBlDJk+eLH1u7Vk4Q2dcVU/cRT/cRS9OnDhBgiCQSqWi119/XTLMWZOhOPmt3BlH6Kqr4S76U1pK0q7lJCQk0JUrV+jevXsubaQqCfJ+5rHHHqM6derQ7t273WIBZ4/s4jtesmQJNWnSxOWNb+5QftsSBw4cIEEQXP4ZV1bcWdeLgzvrEMMGnHLn3r171LFjR5o4cSLl5eUZJVr66aefKC4ujvz9/emTTz4xu/v+9ddfm030WNll3rJlC6nVavrrr7+kz8TO9sqVKzRgwAASBIFeeOGFIr/dunVruSfHLK28d+7cKTdZiZwv7/79+8nHx4diY2NJEAR65ZVXpO9sLS7KS2dcWU/cRT+c3c7sZffu3RQYGEjR0dEkCAJNmTLF6mLX2mK+ok2c3EFXi4u76E9pKU27rmjtWI65Bd0ff/whtQFXvndbspui1WorZMldVyM7O9vZIjBmcGddZyoXbMApZxITEyk4OJg++eQT6TNxYlRQUEAHDx6kFi1aUEhICH3//fdE9HCiOG7cOBIEQaoQwDI/ZM6cOSQIgpRtXJ54jIjo6tWr1Lt3bxIEQUrQR0Q0bdo0EgSBFi5cWK67oyyvfYjnnzlzJnXu3JlOnjxJrVq1IkEQjCqfWDp3eeqMK+uJu7Q3d5HzzTffpE6dOlFiYiI1adLErsWu+LvNmzdXyEmgO+lqcXGXdllauF0XpbgGEFeiuLK7QxtlmLLCnXWdqXywAaecOX36NPn6+tKrr75Ker2+SMdQWFhIu3btorp161KDBg2Mdupv3bpFzZs3L3e3S3eQWXRJHTdunPSZ6Q73mTNnqEaNGhQTE0MXLlwgvV5PP//8M3Xv3r3ck3exvMVj4sSJ1LVrVyIi+vPPP6lly5Z2LQxv3rxJzZo1KxedcWU9cfb7q2hyvvDCC9SxY0ciIrpw4QI1btzY5mL3559/JkEQqHv37hUuvESOO+hqcXGXdllauF2bp7CwkJo0aUINGjRwuwWdO8vOMOUN6wvjLrABxwn07NmTqlatKpXWNHWv1+l0NH/+fBIEQSo1KCZoclZn4uoy379/n5o0aUI+Pj60atUq6XPTvBPr168nQRBo06ZNRPSwdGZ5w/IWj2+//ZaWLVsm/f3XX3+ZXRjK5cnNzSWi8tUZV9UTZ7+/iibn9u3b6euvv5b+vnz5stnFrtwjQavV0sKFC91mMV9S3EVXi4O7tMvSwu3aPMeOHaOgoCDatWuXy7ZRS7iz7AxT3rC+MO4CG3DKEXHSs3r1ahIEgZo3by5N7kwXemlpaVS7dm3q16+f2XOUF+4k8+HDh8nX15caNmwoTaCJHkyiRRmuXLlCPj4+9NFHH5WLTNZgeYtHenq60d/yhaE8z0ZWVhbNnj2bDh48SETl0/7cQU+c/f7sxV3kFBPWisgXu6+99hplZWUREVFmZia99dZbdPz4cWeI6RRcWVdLiru0y9LC7do8qampbrugc2fZGaa8YX1h3AE24DiBnJwcGjFiBAmCQF27dpUWeqZJsp588kn6z3/+4xKTWneR+ZtvviEfHx9q3LgxrVu3TvpclOfkyZNUp04d2rJli1PkM4XlLT7ytmVud3/8+PEkCAJduHChzGSwhKvriSu8P3twFzlNMfVYuH//Pk2aNIk8PDzozJkzzhav3HFlXS0J7touSwu3a4ZhGIZxHdiAU86I4RIZGRnUp08fEgSB2rdvTykpKUbHaTQaateuHU2dOtUZYhrhTjIXFBTQsmXLyMfHhyIjI2nWrFnSdykpKTR69GiqV68eJSYmOk1GOSyvbWwlVjx27Ji0MKxTpw6pVCr6559/HHZ9e3EHPXGX9uYucppDXOxWqVKF6tWrRyqVqtJ4KbiLrpYUd26XpaUyt2uGYRiGcSXYgFOOiKEU+fn5dPPmTcrJyaFBgwaRIAjUoEEDWrNmDV26dIlOnjxJY8aMIbVa7fS4cneUmYjot99+o8jISBIEgeLi4qhHjx7UqVMnCg0NpRMnTjhbvCKwvOaRV3s5efKk0XfyxeKBAwdIqVRSaGgonT592mHXtxd30xN3aW/uIqcpp0+fJoVCQSEhIU5pj87AXXTVEbhruywtlbFdMwzDMIyrIRARgSlzCgsL4enpCYPBgObNm6Nt27ZYsmQJcnJy8Pnnn2PdunW4cOECqlSpgqioKBARNm7ciLi4OJa5hCQkJOC7777Dvn37kJ+fj0cffRQvv/wy6tev72zRzMLyGmPa/jp27IhZs2YhICDA6DitVosZM2Zg6dKlOHr0KB555BGHXL+kcrqLnrhLe3MXOUW0Wi3efPNNfP311/jrr7/KvT06A3fRVUfibu2ytFTGds0wDMMwrggbcMoB+eS2VatWSE5OxqpVq9ChQwdUqVIFer0emZmZ2LZtG1JSUlC9enW0bdsW1atXZ5mZSoml9telSxcIgmB03PDhw7FhwwYcOXIEjz32mEvIyXpSOSkoKMDkyZOxePFiHD9+vNzbozNwF11lSk5lbNcMwzAM46p4OluAio58ctuiRQtkZmZi9erV6NixIzw8PGAwGODh4YHg4GAMGTLE2eICcE+ZLUFE0iJC/v+uCstrvf2ZO39QUBAOHDjgVOONu+qJu7Q3d5FTq9UiNzcX//zzj9M9rMoDd9HVssJd2mVpqWztmmEYhmFcGfbAKUPMTW6XLVuGTp06wcPDw+LvnDkRdEeZmYpDSdtfecN6wliioKAAVapUcbYYZY676CrjGCpLu2YYhmEYV4cNOGWEO05u3VFmpuLgLu3PXeRkmLKCdYBhGIZhGMY5cAhVGeHp6Qm9Xo/HHnsM+fn5bjG5dUeZmYqDu7Q/d5GTYcoK1gGGYRiGYRjnwAacMuTEiRO4desWNm7c6DaTW3eUmak4uEv7cxc5GaasYB1gGIZhGIYpfziEqoxJS0tDQECAW01u3VFmpuLgLu3PXeRkmLKCdYBhGIZhGKZ8YQMOwzAMwzAMwzAMwzCMi6NwtgAMwzAMwzAMwzAMwzCMddiAwzAMwzAMwzAMwzAM4+KwAYdhGIZhGIZhGIZhGMbFYQMOwzAMwzAMwzAMwzCMi8MGHIZhGIZhGIZhGIZhGBeHDTgMwzAMwzAMwzAMwzAuDhtwGIZhGIZhGIZhGIZhXBw24DAMwzAMwzAMwzAMw7g4bMBhGIZhGIZhGIZhGIZxcdiAwzAMwzAMwzAMwzAM4+KwAYdhGIZhGIZhGIZhGMbFYQMOwzAMwzAMwzAMwzCMi8MGHIZhGIZhGIZhGIZhGBeHDTgMwzAMwzAMwzAMwzAuDhtwGIZhGIZhGIZhGIZhXBw24DAMwzAMwzAMwzAMw7g4bMBhGIZhGIZhGIZhGIZxcdiAwzAMwzAMwzAMwzAM4+KwAYepMHz//fcQBAFffPGF0edXr16FWq1Gs2bNkJmZ6STpGMY9YD1imNLDesQwpYf1iGFKD+tRxUMgInK2EAzjCAwGAx599FFkZWXh6tWr8PT0RGpqKtq2bQsiwsGDBxEeHu5sMRnGpWE9YpjSw3rEMKWH9YhhSg/rUcWDPXCYCoNCocDMmTORkJCA77//Hvn5+ejfvz+ys7OxY8cO7pwYxg5Yjxim9LAeMUzpYT1imNLDelTxYA8cpsLRsmVL5OTkoEWLFti2bRv279+PRx55xOiY33//HfHx8ejVqxdWr17tHEEZxoWxpUenT5/G5MmT8ffff8PPzw+DBg3Cxx9/jCpVqjhRaoZxLWzp0f79+zFt2jScOXMGAQEBePrpp/HZZ5/B19fXiVIzjGthz7wOeOBp0KZNG6hUKuzdu7f8BWUYF8aWHgmCAKVSCUEQpM8+/vhjTJo0yQnSMtZgAw5T4di2bRueeuopKJVK7Nu3D23atDH6fs6cOVixYgXCwsJQt25dNuAwjBms6VF2djbq1auHESNGYPr06bhx4wZ69uyJMWPGYNq0aU6UmmFcC2t6pNFoEBMTg/nz52PYsGFITExEr1690Lt3b3z66adOlJphXAtb8zqRZcuWYerUqYiLi2MDDsOYYEuPBEHA9evXERMT4xwBGbvhECqmQmEwGLB69WooFArk5+eb9Qbw9vbGX3/9hbp16zpBQoZxfWzp0f379/Hkk0/i/fffh5eXFxo0aIBnn30W+/fvd5LEDON62NKj/Px8LF26FC+99BI8PT0RExODnj174uzZs06SmGFcD3vmdQCQkpKC9957D+PGjStnCRnG9bFXjxj3gA04TIVi3Lhx+PXXX/G///0PoaGheOedd4ocM3HiRAQGBjpBOoZxD2zpUZ06dbBy5Up4enpKn926dQvVq1cvb1EZxmWxpUfVqlXDf//7XwAAEeH48ePYsmULBg4c6AxxGcYlsWdeBwBvvfUWhg4dinr16pWzhAzj+tirR1OnTkWNGjUQGhqKKVOmID8/v5wlZeyBDThMhWHGjBlYtmwZvvvuO/To0QOvvPIKfv/9dxw8eNDZojGM21ASPfr555+xbds2vPbaa+UoKcO4LsXRo/3790OpVKJdu3YYPnw4hg8f7gSJGcb1sFeP/v77b+zYsQPvvvuukyRlGNfFXj1q06YNnnzySfz777/YtWsXNmzYgNmzZztJasYqxDAVgMWLFxMAWrBggfRZWloaBQQEUKdOncz+ZujQoTR06NDyEZBh3ICS6NGmTZvI39+ftmzZUj5CMoyLUxI90uv1dPLkSWrcuDFNnz69nCRlGNfFXj3S6/XUqlUr2rhxIxERrVq1yqKeMUxloyTjkciSJUsoJiamjCVkSgJ74DBuz4YNGzBhwgS89tprmDhxovR5UFAQxo0bh3379mHnzp1OlJBhXJ+S6NGyZcvw0ksvYcuWLejXr185S8wwrkdJxyOFQoFHH30Ub731FhYvXlyeIjOMy1EcPVqxYgWCgoLw7LPPOktchnFJSrs+iomJwZ07d8pDVKaYcBUqptIybNgwAOAqVAxTAjZu3IixY8di586diIuLc7Y4DON2/Pjjj5g/fz6OHDli9NmkSZNw9+5dJ0rGMO5Dly5d8Pfff8PLywsAkJeXh9zcXAQGBuLEiROoWbOmkyVkGNfn9OnTWLt2LebMmSN9Nm/ePCxfvhwXLlxwomSMOdgDh2EYhikWGRkZGDt2LNauXcvGG4YpIe3bt8fZs2fx2WefIS8vDzdv3sSnn36Kp556ytmiMYzbsH79ely4cAEnT57EyZMnMXPmTLRo0QInT55EtWrVnC0ew7gFYWFhWLp0KRYtWoT8/HycOHEC8+bNw9ixY50tGmMG9sBhKh3e3t4AgIKCAgBAlSpVEB0djUuXLjlTLIZxG9asWYP4+Hhpx1OE9Yhhisfhw4cxadIknD59GiEhIejTpw/mzJmDgIAAZ4vGMG7J6tWrsXr1auzdu9fZojCMW7F371688cYbOHfuHPz8/PDKK6/gjTfegELB/h6uBhtwGIZhGIZhGIZhGIZhXBw2qTEMwzAMwzAMwzAMw7g4bMBhGIZhGIZhGIZhGIZxcdiAwzAMwzAMwzAMwzAM4+KwAYdhGIZhGIZhGIZhGMbFYQMOwzAMwzAMwzAMwzCMi8MGHIZhGIZhGIZhGIZhGBeHDTgMwzAMwzAMwzAMwzAuDhtwGIZhGIZhGIZhGIZhXBw24DAMwzAMwzAMwzAMw7g4bMBhGIZhGIZhGIZhGIZxcdiAwzAMwzAMwzAMwzAM4+L8P4gqk1ysUmEGAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1180x1180 with 25 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "\n",
    "import corner  # https://corner.readthedocs.io\n",
    "\n",
    "# Generate a random positive definite matrix\n",
    "np.random.seed(42)\n",
    "L = np.random.randn(ndim, ndim)\n",
    "L[np.diag_indices_from(L)] = 0.1 * np.exp(L[np.diag_indices_from(L)])\n",
    "L[np.triu_indices_from(L, 1)] = 0.0\n",
    "cov = np.dot(L, L.T)\n",
    "\n",
    "# Draw samples from this Gaussian and plot\n",
    "samples = np.random.multivariate_normal(np.zeros(ndim), cov, size=5000)\n",
    "corner.corner(samples, labels=[\"$x_{{{0}}}$\".format(i) for i in range(1, ndim + 1)]);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This plot will look familiar to any astronomers reading this (and probably some readers from other fields) because our parameters are often correlated and the dynamic range of the parameters can vary drastically.\n",
    "If you used emcee to sample this posterior and the isotropic case above, you would get identical performance (albeit somewhat worse performance than PyMC3) but, as we'll see, the same is not true of PyMC3.\n",
    "Let's try to sample this probability density using PyMC3's default settings."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-06-06T14:31:12.266543Z",
     "iopub.status.busy": "2022-06-06T14:31:12.266291Z",
     "iopub.status.idle": "2022-06-06T14:49:42.483858Z",
     "shell.execute_reply": "2022-06-06T14:49:42.483069Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Auto-assigning NUTS sampler...\n",
      "Initializing NUTS using jitter+adapt_diag...\n",
      "Sequential sampling (2 chains in 1 job)\n",
      "NUTS: [x]\n"
     ]
    },
    {
     "data": {
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       "        /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
       "        background-size: auto;\n",
       "    }\n",
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       "        background: #F44336;\n",
       "    }\n",
       "</style>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
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     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "\n",
       "    <div>\n",
       "      <progress value='6000' class='' max='6000' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
       "      100.00% [6000/6000 09:03<00:00 Sampling chain 0, 0 divergences]\n",
       "    </div>\n",
       "    "
      ],
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       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "\n",
       "<style>\n",
       "    /* Turns off some styling */\n",
       "    progress {\n",
       "        /* gets rid of default border in Firefox and Opera. */\n",
       "        border: none;\n",
       "        /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
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    },
    {
     "data": {
      "text/html": [
       "\n",
       "    <div>\n",
       "      <progress value='6000' class='' max='6000' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
       "      100.00% [6000/6000 08:59<00:00 Sampling chain 1, 0 divergences]\n",
       "    </div>\n",
       "    "
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     "metadata": {},
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    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Sampling 2 chains for 3_000 tune and 3_000 draw iterations (6_000 + 6_000 draws total) took 1083 seconds.\n",
      "The acceptance probability does not match the target. It is 0.8914101254030794, but should be close to 0.8. Try to increase the number of tuning steps.\n",
      "The chain reached the maximum tree depth. Increase max_treedepth, increase target_accept or reparameterize.\n",
      "The chain reached the maximum tree depth. Increase max_treedepth, increase target_accept or reparameterize.\n",
      "The number of effective samples is smaller than 10% for some parameters.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "time per effective sample: 2003.80742 ms\n"
     ]
    }
   ],
   "source": [
    "with pm.Model() as model:\n",
    "    pm.MvNormal(\"x\", mu=np.zeros(ndim), chol=L, shape=(ndim,))\n",
    "\n",
    "with model:\n",
    "    strt = time.time()\n",
    "    default_trace = pm.sample(\n",
    "        draws=3000, tune=3000, random_seed=42, chains=2, return_inferencedata=True\n",
    "    )\n",
    "    default_time = 0.5 * (time.time() - strt)\n",
    "\n",
    "stats = az.summary(default_trace)\n",
    "default_time_per_eff = default_time / stats.ess_bulk.values.min()\n",
    "print(\"time per effective sample: {0:.5f} ms\".format(default_time_per_eff * 1000))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Yes, the units here are the same and the computational efficiency is orders of magnitude worse than the isotropic case.\n",
    "The standard recommendation would be to re-parameterize (we can see that that's what PyMC3 is telling us to do here too), but I'm not really clever or patient enough to do that in every case.\n",
    "So, let's automate this following the procedure from Stan.\n",
    "\n",
    "## Learning the mass matrix in PyMC3\n",
    "\n",
    "In this section, I will demonstrate how we can use the machinery included in the current release of PyMC3 to fit for a dense mass matrix during burn-in.\n",
    "First, let's choose a tuning schedule roughly following section 34.2 from the [Stan manual](https://github.com/stan-dev/stan/releases/download/v2.17.0/stan-reference-2.17.0.pdf)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-06-06T14:49:42.487301Z",
     "iopub.status.busy": "2022-06-06T14:49:42.486917Z",
     "iopub.status.idle": "2022-06-06T14:49:42.491222Z",
     "shell.execute_reply": "2022-06-06T14:49:42.490721Z"
    }
   },
   "outputs": [],
   "source": [
    "n_start = 25\n",
    "n_burn = 500\n",
    "n_tune = 5000\n",
    "n_window = n_start * 2 ** np.arange(np.floor(np.log2((n_tune - n_burn) / n_start)))\n",
    "n_window = np.append(n_window, n_tune - n_burn - np.sum(n_window))\n",
    "n_window = n_window.astype(int)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next, here's a function that takes in a MultiTrace object from PyMC3, estimates the sample covariance, and builds a NUTS step for use in the `sample` method."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-06-06T14:49:42.494568Z",
     "iopub.status.busy": "2022-06-06T14:49:42.493991Z",
     "iopub.status.idle": "2022-06-06T14:49:42.500867Z",
     "shell.execute_reply": "2022-06-06T14:49:42.500258Z"
    }
   },
   "outputs": [],
   "source": [
    "from pymc3.step_methods.hmc.quadpotential import QuadPotentialFull\n",
    "\n",
    "\n",
    "def get_step_for_trace(\n",
    "    trace=None, model=None, regular_window=5, regular_variance=1e-3, **kwargs\n",
    "):\n",
    "    model = pm.modelcontext(model)\n",
    "\n",
    "    # If not given, use the trivial metric\n",
    "    if trace is None:\n",
    "        potential = QuadPotentialFull(np.eye(model.ndim))\n",
    "        return pm.NUTS(potential=potential, **kwargs)\n",
    "\n",
    "    # Loop over samples and convert to the relevant parameter space;\n",
    "    # I'm sure that there's an easier way to do this, but I don't know\n",
    "    # how to make something work in general...\n",
    "    samples = np.empty((len(trace) * trace.nchains, model.ndim))\n",
    "    i = 0\n",
    "    for chain in trace._straces.values():\n",
    "        for p in chain:\n",
    "            samples[i] = model.bijection.map(p)\n",
    "            i += 1\n",
    "\n",
    "    # Compute the sample covariance\n",
    "    cov = np.cov(samples, rowvar=0)\n",
    "\n",
    "    # Stan uses a regularized estimator for the covariance matrix to\n",
    "    # be less sensitive to numerical issues for large parameter spaces.\n",
    "    # In the test case for this blog post, this isn't necessary and it\n",
    "    # actually makes the performance worse so I'll disable it, but I\n",
    "    # wanted to include the implementation here for completeness\n",
    "    N = len(samples)\n",
    "    cov = cov * N / (N + regular_window)\n",
    "    cov[np.diag_indices_from(cov)] += (\n",
    "        regular_variance * regular_window / (N + regular_window)\n",
    "    )\n",
    "\n",
    "    # Use the sample covariance as the inverse metric\n",
    "    potential = QuadPotentialFull(cov)\n",
    "    return pm.NUTS(potential=potential, **kwargs)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally, we can combine our tuning schedule with this proposal estimator to automatically learn the mass matrix during burn-in."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-06-06T14:49:42.504035Z",
     "iopub.status.busy": "2022-06-06T14:49:42.503459Z",
     "iopub.status.idle": "2022-06-06T14:50:00.328395Z",
     "shell.execute_reply": "2022-06-06T14:50:00.327588Z"
    }
   },
   "outputs": [
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      "Only 2 samples in chain.\n",
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      "Sampling 2 chains for 25 tune and 2 draw iterations (50 + 4 draws total) took 1 seconds.\n",
      "The chain reached the maximum tree depth. Increase max_treedepth, increase target_accept or reparameterize.\n",
      "The chain reached the maximum tree depth. Increase max_treedepth, increase target_accept or reparameterize.\n",
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      "Sampling 2 chains for 1_600 tune and 2 draw iterations (3_200 + 4 draws total) took 2 seconds.\n",
      "Only 2 samples in chain.\n",
      "Sequential sampling (2 chains in 1 job)\n",
      "NUTS: [x]\n"
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     "text": [
      "Sampling 2 chains for 1_325 tune and 2 draw iterations (2_650 + 4 draws total) took 2 seconds.\n",
      "Sequential sampling (2 chains in 1 job)\n",
      "NUTS: [x]\n"
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     "text": [
      "Sampling 2 chains for 500 tune and 5_000 draw iterations (1_000 + 10_000 draws total) took 7 seconds.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "time per effective sample: 0.48053 ms\n"
     ]
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   ],
   "source": [
    "np.random.seed(42)\n",
    "\n",
    "strt = time.time()\n",
    "with model:\n",
    "    start = None\n",
    "    burnin_trace = None\n",
    "    for steps in n_window:\n",
    "        step = get_step_for_trace(burnin_trace, regular_window=0)\n",
    "        burnin_trace = pm.sample(\n",
    "            start=start,\n",
    "            tune=steps,\n",
    "            draws=2,\n",
    "            step=step,\n",
    "            compute_convergence_checks=False,\n",
    "            discard_tuned_samples=False,\n",
    "            return_inferencedata=False,\n",
    "        )\n",
    "        start = [t[-1] for t in burnin_trace._straces.values()]\n",
    "\n",
    "    step = get_step_for_trace(burnin_trace, regular_window=0)\n",
    "    dense_trace = pm.sample(\n",
    "        draws=5000, tune=n_burn, step=step, start=start, return_inferencedata=True\n",
    "    )\n",
    "    factor = 5000 / (5000 + np.sum(n_window + 2) + n_burn)\n",
    "    dense_time = factor * (time.time() - strt)\n",
    "\n",
    "stats = az.summary(dense_trace)\n",
    "dense_time_per_eff = dense_time / stats.ess_bulk.values.min()\n",
    "print(\"time per effective sample: {0:.5f} ms\".format(dense_time_per_eff * 1000))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The computational efficiency of this method is similar to PyMC3's default performance on an isotropic Gaussian (within a factor of a few) and corresponds to an improvement of more than *three orders of magnitude* over the default PyMC3 performance on a correlated Gaussian.\n",
    "\n",
    "While I've found that this procedure can substantially improve the sampling efficiency in many real world scenarios (especially during exploratory phases of a project), you shouldn't forget about reparameterization because that can provide even better performance and help identify problems with your model specification.\n",
    "Furthermore, this method might run into numerical issues for high dimensional problems because more samples will be needed to reliably estimate the off-diagonal elements of the mass matrix.\n",
    "Either way, hopefully this is helpful to folks until PyMC3 includes native support for this type of procedure.\n",
    "\n",
    "*Edit: This feature is now available in PyMC3 using the* `init=\"adapt_full\"` *argument to* `pm.sample`."
   ]
  },
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   "metadata": {},
   "outputs": [],
   "source": []
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