diff --git a/tutorials/Flip_flop_Index.ipynb b/tutorials/Flip_flop_Index.ipynb
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+{
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+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "id": "91abca47",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-11-09T04:58:29.280799Z",
+ "start_time": "2023-11-09T04:58:29.275796Z"
+ }
+ },
+ "outputs": [],
+ "source": [
+ "from scipy.stats import skewnorm\n",
+ "import numpy as np\n",
+ "import xarray as xr\n",
+ "import pandas as pd\n",
+ "\n",
+ "from scores.continuous import mse\n",
+ "from scores.continuous import flip_flop_index_proportion_exceeding"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "id": "ac3ef136",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-11-09T04:51:28.537658Z",
+ "start_time": "2023-11-09T04:51:28.521157Z"
+ }
+ },
+ "outputs": [],
+ "source": [
+ "# Create synthetic temperature observations\n",
+ "obs = 40 * np.random.random((100, 100))\n",
+ "obs = xr.DataArray(\n",
+ " data=obs, \n",
+ " dims=[\"time\", \"x\"],\n",
+ " coords={\"time\": pd.date_range(\"2023-01-01\", \"2023-04-10\"), \"x\": np.arange(0, 100)}\n",
+ ")\n",
+ "\n",
+ "# Create forecasts for 7 lead days\n",
+ "fcst1 = xr.DataArray(data=[1]*7, dims=\"lead_day\", coords={\"lead_day\": np.arange(1, 8)})\n",
+ "fcst1 = fcst1 * obs\n",
+ "fcst2 = fcst1.copy()\n",
+ "\n",
+ "# add some noise to the forecasts\n",
+ "# fcst 2 will be set up to flip-flop more than fcst 1\n",
+ "fcst1 += 2 * skewnorm.rvs(4, size=(7, 100, 100))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "id": "593844ac",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-11-09T04:57:02.193648Z",
+ "start_time": "2023-11-09T04:57:02.179379Z"
+ }
+ },
+ "outputs": [],
+ "source": [
+ "flipflop_noise = []\n",
+ "for lead_day in np.arange(1, 8):\n",
+ " noise = 2 * skewnorm.rvs(4, size=(100, 100))\n",
+ " if lead_day % 2 == 0:\n",
+ " noise *= -1\n",
+ " flipflop_noise.append(noise)\n",
+ "flipflop_noise = np.stack(flipflop_noise) \n",
+ "fcst2 += flipflop_noise"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "id": "fadab7f3",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-11-09T04:57:44.034837Z",
+ "start_time": "2023-11-09T04:57:44.020020Z"
+ }
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
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+ "
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+ "array([3.93994022, 4.05165078, 3.93569259, 3.93866259, 3.95555321,\n",
+ " 3.8961911 , 4.05679397])\n",
+ "Coordinates:\n",
+ " * lead_day (lead_day) int64 1 2 3 4 5 6 7
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+ ],
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+ ],
+ "source": [
+ "mse(fcst1, obs, preserve_dims=[\"lead_day\"])"
+ ]
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+ "mse(fcst1, obs)"
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uu+yk7zNt2jSSkpKqH+np6fWJaVy/tKrFz0Lt8l6/bhdBUkc4ehi+e9t0GhERCXL1KiP5+fl4vV5SUlJq7E9JSSEnJ6fWY2666SZ+97vfcc455xAZGUnXrl05//zzTzlMM3nyZAoKCqofu3fvrk9M4/yTWNfuLcAOxUtgXW4Ycpuzvbz2M2IiIiJ11eRX0yxevJjHHnuM//3f/2XlypW89dZbzJs3j0ceeeSkx0RFRZGYmFjjEUx6pMYT4bI4XFrBnsMhOoxx1i3gioTvv4Z935pOIyIiQaxeZSQ5ORm3201ubm6N/bm5uaSmptZ6zJQpU7jlllu444476N+/Pz/5yU947LHHmDZtGj6fr+HJA1hUhJseKc4k1pC6g+/x4ttC7zHOts6OiIjIGahXGfF4PAwePJhFixZV7/P5fCxatIisrKxajyktLcXlqvk2brcbIDSHMKr0SIkHYEteiN2j5nhDf+48f/svOBqipUtERJpcvYdpsrOzmTlzJq+++irr16/nrrvuoqSkhPHjxwMwbtw4Jk+eXP36MWPG8MILLzB79my2b9/OwoULmTJlCmPGjKkuJaGoW1unjGwN5TLSaQQk94SKEvh2juk0IiISpCLqe8DYsWPZv38/Dz30EDk5OQwcOJAFCxZUT2rdtWtXjTMhv/nNb7Asi9/85jfs2bOHNm3aMGbMGB599NHG+y0CkL+MbNkfwmXEsmDI7bDgAVj+Mgy9w9knIiJSD5YdBGMlhYWFJCUlUVBQEDSTWTfnFvHj/1lCnMfN2odHY4Xqh/SRw/BMb6gohds/hI4/Mp1IREQCRF0/v3VvmibSqXUcbpdFSbmXfQWhufQ94Nyvpt+1zrZWZBURkQZQGWkinggXnVrHAiE+iRWcoRqAdXOh9KDRKCIiEnxURppQtzZVk1hDed4IQPtBkDoAvOWw9k3TaUREJMiojDSh6kmsoX5mBCDzBudZV9WIiEg9qYw0obAqI/2uA8vlrMh6YKvpNCIiEkRURppQ13AZpgFISIGuFzrbOjsiIiL1oDLShLpWnRnJLy7ncGm54TTNYMBxQzWBf8W4iIgECJWRJhQfFUG7pGggTM6O9LocPPFwaAfs/sp0GhERCRIqI00srOaNeGKh95XO9urZZrOIiEjQUBlpYv55I2FRRgAyxzrP370NlWVms4iISFBQGWliXcPpzAhAxrmQkAZHD8OmD02nERGRIKAy0sT8C5+F9A3zjudyw4DrnW1dVSMiInWgMtLE/HNGvj90hKMVXsNpmon/qppNH2p5eBEROS2VkSaWHO8hKSYS24Zt+0tMx2keKX0gtT/4KuC7t0ynERGRAKcy0sQsyzp2RU24DNXAcWuO/MtsDhERCXgqI82ga5s4IIwmsQL0uwawnPVGDu82nUZERAKYykgz8J8ZCYuFz/wS06DT2c72d2+bzSIiIgFNZaQZVJeRcDozAlVnR9C8EREROSWVkWbQrU0CANvyS/D6wuieLb2vcu7ku/cb3clXREROSmWkGbRvGUNUhIvySh+7D5aajtN84ttA55HOtoZqRETkJFRGmoHbZdE5OQwnsQL0u9Z5XquhGhERqZ3KSDMJy0msAL2vAFck5H0HeRtMpxERkQCkMtJMwuruvceLaQndLnK2NZFVRERqoTLSTMJy4TO/6qGaN8EOowm8IiJSJyojzeT4MyN2uH0g97wUIqLhwBbIWWM6jYiIBBiVkWaS0ToOy4Kio5XkF5ebjtO8ohKg+8XO9to3zWYREZGAozLSTKIj3aS3jAXCcBIr1FwALdzODImIyCmpjDQj/z1qwrKMdB8NkXFweBd8v9x0GhERCSAqI82oaxv/svAlhpMY4ImFXpc726tfM5tFREQCispIM+oarmuN+A28yXle+wZUHDWbRUREAobKSDOqPjMSrmWk80hISoejBbDhfdNpREQkQKiMNCP/nJE9h49wpNxrOI0BLhdk3uhsr5plNouIiAQMlZFm1CrOQ4vYSGwbtueH4bwRgIFVZWTrx1Cwx2wWEREJCCojzciyLA3VtOoCnUYANnw723QaEREJACojzSysL+/1809k/eafWnNERERURprbsTMjYTpMA9DnamfNkYNbYfdXptOIiIhhKiPN7NhaI2F8ZiQqHvpc5Wyv+qfZLCIiYpzKSDPzrzWyLb8Yny+MhyjOutl5Xvs2lIfxWSIREVEZaW7pLWOIdFscrfCxt+CI6TjmdDwbWmZAeRGs15ojIiLhTGWkmUW4XWS09k9iDeMzAi4XZFZNZF31D7NZRETEKJURAzRvpErmDc7z9n9DUa7ZLCIiYozKiAFd2+ryXgBadoK0QYCt5eFFRMKYyogBYb/w2fH6XOk8r3/XbA4RETFGZcQArTVynN5VZWT7v6H0oNksIiJihMqIAV2qVmHdX1RGwZEKw2kMa90VUvqB7YUN80ynERERA1RGDEiIjiQlMQqAbRqqObYAmoZqRETCksqIIRqqOY5/qGbrJ3C0wGwWERFpdiojhmgS63Ha9oLkHuCrgE0fmk4jIiLNTGXEkOq794b7WiN+/rMj694xm0NERJqdyoghx+5Ro2Ea4NglvlsW6V41IiJhRmXEEP8wzc4DJVR4fYbTBIDUAdCiE1Qegc0LTacREZFmpDJiSGpiNLEeNxVem90HS03HMc+ytACaiEiYUhkxxOWyqtcb0RU1VXpXXeK76UOoOGo2i4iINBuVEYP8QzVbNInV0X4wJKRBeTFs+8R0GhERaSYqIwZ1Sa6axKrLex0uF/Qe42yv01CNiEi4UBkxSHfvrYW/jGz6ALxhvlS+iEiYaFAZmT59OhkZGURHRzN8+HCWLVt2ytcfPnyYCRMm0K5dO6KioujRowfz589vUOBQcvwqrLZtG04TIDpmQWxrOHIIdn5uOo2IiDSDepeROXPmkJ2dzdSpU1m5ciWZmZmMHj2avLy8Wl9fXl7Oj3/8Y3bs2MEbb7zBxo0bmTlzJu3btz/j8MGuc3IclgUFRyo4UFJuOk5gcEdAz8uc7fXvmc0iIiLNot5l5JlnnuHOO+9k/Pjx9OnThxkzZhAbG8tLL71U6+tfeuklDh48yNy5cxkxYgQZGRmMHDmSzMzMk75HWVkZhYWFNR6hKDrSTfsWMYBWYq3Bvxrrhnng0xosIiKhrl5lpLy8nBUrVjBq1KhjP8DlYtSoUSxdurTWY959912ysrKYMGECKSkp9OvXj8ceewyv13vS95k2bRpJSUnVj/T09PrEDCr+oRqtxHqcLiPBkwBF+2DPCtNpRESkidWrjOTn5+P1eklJSamxPyUlhZycnFqP2bZtG2+88QZer5f58+czZcoUnn76aX7/+9+f9H0mT55MQUFB9WP37t31iRlUqueN6MzIMRFR0ONiZ1sLoImIhLwmv5rG5/PRtm1bXnzxRQYPHszYsWN58MEHmTFjxkmPiYqKIjExscYjVOmKmpPwX1Wz4X3Q5F4RkZAWUZ8XJycn43a7yc3NrbE/NzeX1NTUWo9p164dkZGRuN3u6n29e/cmJyeH8vJyPB5PA2KHjuOvqJHjdPsxuKPg4DbIWwcpfU0nEhGRJlKvMyMej4fBgwezaNGi6n0+n49FixaRlZVV6zEjRoxgy5Yt+I6biLhp0ybatWsX9kUEqF4SfvehUo5WnHweTdiJioeuFzrbuqpGRCSk1XuYJjs7m5kzZ/Lqq6+yfv167rrrLkpKShg/fjwA48aNY/LkydWvv+uuuzh48CATJ05k06ZNzJs3j8cee4wJEyY03m8RxNrER5EQHYFtw84DumFeDf6hGpUREZGQVq9hGoCxY8eyf/9+HnroIXJychg4cCALFiyontS6a9cuXK5jHSc9PZ0PP/yQe++9lwEDBtC+fXsmTpzIAw880Hi/RRCzLIuubeJZtfswW/cX0zM1wXSkwNHzUrDckLvWGa5p1cV0IhERaQKWHQRLfxYWFpKUlERBQUFITmb91b9W8+bK7/nVj3vwi4u6m44TWF4dA9uXwI8fgRG/NJ1GRETqoa6f37o3TQDQFTWn4F8ATUM1IiIhS2UkAPjv3qsramrR63Ln+ftlULjPbBYREWkSKiMBoFvVmZFt+4t1w7wfSkyDDkOd7Q3vm80iIiJNQmUkAHRsFYfbZVFS7iW3sMx0nMDT5yrned07ZnOIiEiTUBkJAJ4IF51axQKaN1Ir/yW+Oz+H4v1ms4iISKNTGQkQXapXYlUZOUHLDGg3EGyfhmpEREKQykiA6Fq1EqtumHcSffxX1ejGeSIioUZlJED471GzLV9X1NSqd9W8ke1LoPSg2SwiItKoVEYCRPVaIzozUrvkbtC2L/gqYeMHptOIiEgjUhkJEP61RvYWHKWkrNJwmgDlv6pGQzUiIiFFZSRAtIzz0DrOuYvxdg3V1M4/b2Trx3C00GwWERFpNCojAaRLGy0Lf0ptekFyD/CWw6YPTacREZFGojISQLq20bLwp2RZx+5Vs26u0SgiItJ4VEYCSFetNXJ6/nkjW/4PyvR3EhEJBSojAURX1NRBan9nEbTKo7Bloek0IiLSCFRGAoj/iprt+SV4fbphXq0sS/eqEREJMSojAaRDyxg8bhdllT72HDpiOk7g8s8b2bwQKnVjQRGRYKcyEkAi3K7qK2o25RYZThPA0gZBQjsoL4Ztn5pOIyIiZ0hlJMD0SEkAYFOeyshJuVzQ63Jne8N7ZrOIiMgZUxkJMD1SnHkjm3M1ifWU/GVk4wfg85rNIiIiZ0RlJMB0958Z0TDNqWWcC9FJULIfdi8znUZERM6AykiA8Q/TbMkr1hU1p+KOhB6XONsb3jebRUREzojKSIDp2CqWqAjniprdB0tNxwlsva5wnte/B7aKm4hIsFIZCTBul0W3ts68kY0aqjm1bhdBRDQc3gm535lOIyIiDaQyEoD8QzWbVUZOzRMHXS90tjVUIyIStFRGAlD3qitqNumKmtOrHqpRGRERCVYqIwGoR1tdUVNnPS8Fyw25a+DQDtNpRESkAVRGAlDPVKeMbNtfQqXXZzhNgIttBZ3OdrY3zDObRUREGkRlJAC1bxFDTKSbcq+Pnbqi5vQ0VCMiEtRURgKQy2UdmzeSo6Ga0/KvxrprKRTvN5tFRETqTWUkQHWvnjeiSayn1SId2g0EbNiooRoRkWCjMhKg/Peo0Q3z6qjPlc7zunfM5hARkXpTGQlQPVK11ki99Lnaed72KZQeNBpFRETqR2UkQPkXPtueX0KFrqg5vdZdIaU/2F7YON90GhERqQeVkQCVlhRNfFQEFV6bHfklpuMEhz5XOc/fzTUaQ0RE6kdlJEBZ1rF71GgSax35y8i2xXDkkNEoIiJSdyojAcw/iVU3zKujNj2gbR/wVcDGBabTiIhIHamMBDDdMK8B/GdHdFWNiEjQUBkJYP4yonvU1IO/jGxdBEcLzGYREZE6URkJYP4ysuNAKWWVXsNpgkSbXpDcA7zlsOlD02lERKQOVEYCWEpiFAnREXh9Ntt1RU3dWNaxNUc0VCMiEhRURgKYZVnHDdXoipo68w/VbF4IZRriEhEJdCojAa6HbphXfyl9oVVX8JZpqEZEJAiojAQ4TWJtAMvSVTUiIkFEZSTA9VQZaZi+VzvPmxdCuebbiIgEMpWRAOe/Yd7Og6UcKdcVNXWWOgBadILKI04hERGRgKUyEuCS46NIjvdg27A5T2dH6syyoM+Vzvb6d81mERGRU1IZCQL+eSMbNYm1fvyX+G76ECqOGo0iIiInpzISBHqmqow0SNogSGwP5cWw9WPTaURE5CRURoKAfxKrbphXTy4X9B7jbGuoRkQkYKmMBIEeOjPScL2r5o1snA+V5WaziIhIrVRGgoB/zkheURmHSvSBWi8dfwRxbZ2b5u1YYjqNiIjUQmUkCMRHRdChZQygoZp6c7mh9xXOthZAExEJSCojQaJXqhY/azD/UM2GeeCtNJtFREROoDISJPxDNRs0b6T+Ms6BmJZQegB2fWE6jYiI/IDKSJDwX96rG+Y1gDsSel3ubGuoRkQk4DSojEyfPp2MjAyio6MZPnw4y5Ytq9Nxs2fPxrIsrr766oa8bVirXmsktwjbtg2nCUK9q26ct/598PnMZhERkRrqXUbmzJlDdnY2U6dOZeXKlWRmZjJ69Gjy8vJOedyOHTu47777OPfccxscNpx1SY4nwmVRdLSSfQVaTbTeuoyEqEQozoHv61aeRUSkedS7jDzzzDPceeedjB8/nj59+jBjxgxiY2N56aWXTnqM1+vl5ptv5uGHH6ZLly5nFDhceSJcdGkTB2i9kQaJiIIelzjbGqoREQko9Soj5eXlrFixglGjRh37AS4Xo0aNYunSpSc97ne/+x1t27bl5z//eZ3ep6ysjMLCwhoPgZ6piYAu722wPlVDNeve0VCNiEgAqVcZyc/Px+v1kpKSUmN/SkoKOTk5tR7z2Wef8de//pWZM2fW+X2mTZtGUlJS9SM9Pb0+MUNWz5R4QGdGGqzbReCJh8I9sGeF6TQiIlKlSa+mKSoq4pZbbmHmzJkkJyfX+bjJkydTUFBQ/di9e3cTpgwe1WdGVEYaJjLmuKGauUajiIjIMRH1eXFycjJut5vc3Nwa+3Nzc0lNTT3h9Vu3bmXHjh2MGTOmep+v6vR4REQEGzdupGvXriccFxUVRVRUVH2ihQX/DfO27C+m0usjwq0rs+utz1Ww9g1nqObi34NlmU4kIhL26vVp5vF4GDx4MIsWLare5/P5WLRoEVlZWSe8vlevXqxZs4ZVq1ZVP6688kouuOACVq1apeGXeurQMoZYj5vySh87DpSajhOcuv8YIuOgYDfsWWk6jYiIUM8zIwDZ2dnceuutDBkyhGHDhvHss89SUlLC+PHjARg3bhzt27dn2rRpREdH069fvxrHt2jRAuCE/XJ6LpdF95QEVu8+zKbcIrq1jTcdKfhExkCP0fDdW85QTYfBphOJiIS9ep/nHzt2LE899RQPPfQQAwcOZNWqVSxYsKB6UuuuXbvYt29fowcVh38Sq5aFPwPVV9XMBS0gJyJinGUHwXKehYWFJCUlUVBQQGJiouk4Rv31s+088v46Lumbyoxb9H/1DVJeCn/oChWlcOcn0H6Q6UQiIiGprp/fmgEZZPyTWLXWyBnwxEL3i51tLYAmImKcykiQ8d+jZseBEo5WeA2nCWIaqhERCRgqI0EmOd5DqzgPtg2bc4tNxwlePUZDRAwc2gH7VptOIyIS1lRGgoxlWfSqOjuybl+B4TRBzBPnXOYLGqoRETFMZSQI9W+fBMC336uMnBEN1YiIBASVkSDUv4NTRtbsURk5Iz0ugYhoOLgN9moBNBERU1RGglBmhxYArN9XSFmlJrE2WFQ89K66VcHKv5vNIiISxlRGglCHljG0iI2kwmuzKUeTWM/IWbc4z2vfdNYfERGRZqcyEoQsyzo2b2TPYbNhgl3GudCiE5QVaiKriIghKiNBakDVvJFvd2veyBlxuY6dHflGQzUiIiaojASp/u1bAPCtJrGeuYE3geWCnZ/Dga2m04iIhB2VkSCVme6cGdmUW6SVWM9UUnvoepGzrbMjIiLNTmUkSKUmRpMcH4XXZ7NuX6HpOMFvUNVQzarXwFtpNouISJhRGQlSlmVVzxtZo8XPzlyPSyE2GYpzYMtC02lERMKKykgQ819Rs/r7w2aDhIIID2Te4GxrzRERkWalMhLEdGakkfmvqtm0AIpyzWYREQkjKiNBzL8s/Jb9xZSUaZ7DGWvbCzoMBdsLq18znUZEJGyojASxtgnRtEuKxrbhu72axNoo/GdHVv1TN88TEWkmKiNB7tgdfA+bDRIq+v4EImIgfxPs0c3zRESag8pIkKteiVXzRhpHdCL0vsLZXj3LbBYRkTChMhLk+lfdwXeNVmJtPJk3Os9r34TKMrNZRETCgMpIkBtQNUyzPb+EgiMVhtOEiC7nQ0I7OHIINn1oOo2ISMhTGQlyLeM8pLeKAeA7nR1pHC43DPips62rakREmpzKSAgYoJvmNb7Mm5znzR9BSb7ZLCIiIU5lJAT01+Jnja9tL0g7C3yVsOYN02lEREKaykgI8M8bWbX7sNkgocZ/dkRX1YiINCmVkRDQv0MSLgv2HD5CXuFR03FCR79rwRUJ+1ZD7jrTaUREQpbKSAhIiI6kZ2oiACt2HjKcJoTEtYYeo51tTWQVEWkyKiMhYnCnFgAsVxlpXP41R779F3h1/x8RkaagMhIihnRqBaiMNLruF0NMKyjOgW2fmE4jIhKSVEZCxOBOLQFnrZGjFV7DaUJIhOfYmiMrXzWbRUQkRKmMhIgOLWNomxBFpc9mta6qaVyDbnWeN34AxXlms4iIhCCVkRBhWRZDMpyzIyt2aaimUaX0gQ5DnTVHVukyXxGRxqYyEkIGdawqIztURhrdoHHO88q/gW2bzSIiEmJURkLIkAxnEuuKXYfw+fSB2aj6XgOeeDi4FXZ8ZjqNiEhIURkJIX3aJRIV4eJwaQXb8ktMxwktUfHQ/zpne+XfzGYREQkxKiMhxBPhIjO9BQArdh40GyYU+SeyrnsHSvX3FRFpLCojIWZI1SW+yzVvpPGlnQUp/cFb5iyCJiIijUJlJMT41xvRFTVNwLJgcNXZkZWvaiKriEgjURkJMf4rarbtL+FgSbnhNCGo//UQEQN562DPCtNpRERCgspIiGkZ56FrmzgAVmpp+MYX0wL6Xu1sr3jFYBARkdChMhKCdJ+aJuZfc2Ttm3C0wGwWEZEQoDISgqrnjeiKmqbRMQva9IaKUlg923QaEZGgpzISggZXLQu/+vsCyit9htOEIMuCoT93tr/+iyayioicIZWRENQlOY6WsZGUV/pYu1fDCE0i8wZnRdb8TbB9iek0IiJBTWUkBFmWVT1Us3yHhmqaRFSCU0gAvp5pNouISJBTGQlRwzo7k1i/2HrAcJIQNvQO53nDfCjYYzaLiEgQUxkJUed2bwPAl9sOUFbpNZwmRLXtDZ3OAdury3xFRM6AykiI6pWaQHJ8FEcrfKzQ0vBNxz+RdeWrUKlF5kREGkJlJERZlsV53ZMB+PeWfMNpQljvMRCfAsW5sOE902lERIKSykgIO7dHVRnZvN9wkhDmjoTBtznby/5iNIqISLBSGQlhI7o5ZWTtnkIOFJcZThPCBt8Glht2fQG535lOIyISdFRGQljbhGh6t0sE4DMN1TSdxDTodbmzvXS62SwiIkFIZSTEVc8b2awy0qRGTHSeV8+GA1vNZhERCTIqIyHunO7H5o3YWra86XQYAt0vdi7zXfIH02lERIKKykiIG5rRiqgIF7mFZWzJKzYdJ7SdP8l5/nYO5G8xm0VEJIg0qIxMnz6djIwMoqOjGT58OMuWLTvpa2fOnMm5555Ly5YtadmyJaNGjTrl66VxRUe6q1djXaKhmqbVfjD0uARsH3z6hOk0IiJBo95lZM6cOWRnZzN16lRWrlxJZmYmo0ePJi8vr9bXL168mBtvvJFPPvmEpUuXkp6ezsUXX8yePVo+u7mcV7Uaqy7xbQbnT3ae174B+zeazSIiEiQsu54TCYYPH87QoUN5/vnnAfD5fKSnp/OLX/yCSZMmnfZ4r9dLy5Ytef755xk3blyd3rOwsJCkpCQKCgpITEysT1wBNuQUcsmz/yY60sXqqRcTFeE2HSm0vXYTbJwH/a6F614ynUZExJi6fn7X68xIeXk5K1asYNSoUcd+gMvFqFGjWLp0aZ1+RmlpKRUVFbRq1eqkrykrK6OwsLDGQxquZ0oCbRK0NHyz8c8dWfsW5K03m0VEJAjUq4zk5+fj9XpJSUmpsT8lJYWcnJw6/YwHHniAtLS0GoXmh6ZNm0ZSUlL1Iz09vT4x5Qcsy+JcLQ3ffNoNcJaJx9bcERGROmjWq2kef/xxZs+ezdtvv010dPRJXzd58mQKCgqqH7t3727GlKHp3O5aGr5Zjaw6O/Ld25C7zmwWEZEAV68ykpycjNvtJjc3t8b+3NxcUlNTT3nsU089xeOPP85HH33EgAEDTvnaqKgoEhMTazzkzBy/NHxe0VHDacJAaj/oc5WzveRJs1lERAJcvcqIx+Nh8ODBLFq0qHqfz+dj0aJFZGVlnfS4J598kkceeYQFCxYwZMiQhqeVBmubEE1megsAPlxbtyE1OUMjH3Cev5sLeRuMRhERCWT1HqbJzs5m5syZvPrqq6xfv5677rqLkpISxo8fD8C4ceOYPHly9eufeOIJpkyZwksvvURGRgY5OTnk5ORQXKwFuJrbmAHtAHhv9T7DScJESt9jc0d0dkRE5KTqXUbGjh3LU089xUMPPcTAgQNZtWoVCxYsqJ7UumvXLvbtO/Zh98ILL1BeXs51111Hu3btqh9PPfVU4/0WUieX9XfKyNc7D5JToKGaZuE/O7L2La07IiJyEvVeZ8QErTPSeK574QuW7zzElCv68PNzOpuOEx5m3wwb3of+18O1fzGdRkSk2TTJOiMS/K6oGqp5/9u9hpOEkZH/7TyvfRPyN5vNIiISgFRGwsxlA9rhsuCbXYfZfbDUdJzw0C4Tel7m3LNGd/QVETmBykiYaZsQzfDOrQGYt0YTWZuN/+zImtd1R18RkR9QGQlDV2RqqKbZpZ117I6+i6eZTiMiElBURsLQpf3a4XZZrN1TyI78EtNxwsf5kwHLuaPv9iWm04iIBAyVkTDUKs5TvSKrzo40o7SBMPTnzvb72VBZZjSOiEigUBkJU8euqtG8kWZ14RSIawsHNsPnfzKdRkQkIKiMhKnRfVKJdFtsyClic26R6TjhI6YFXFI1Z2TJH+DAVqNxREQCgcpImEqKjeS87m0AeE9nR5pXv2uhy/ngLYP590HgrzsoItKkVEbC2JUD0wB4c8X3eH36QGw2lgWXPQ1uD2z9GL5723QiERGjVEbC2Oi+qbSMjWTP4SMsWp9rOk54Se4G52Q72wsmw9ECs3lERAxSGQlj0ZFuxg7tCMDflu40nCYMnXMvtOoCxTnw0W9MpxERMUZlJMzdPLwjLgs+25LPlrxi03HCS2Q0XPmcs73yb7B5odk8IiKGqIyEufRWsVzUOwWAf3ypsyPNLuMcGH6Xs/3uL+DIIbN5REQMUBkRbs3KAOCNFd9TXFZpNkw4uughaNUVivY580dERMKMyogwoltrurSJo7iskrdXfm86TvjxxMLVL4DlgtWvwYb5phOJiDQrlRHBsqzqsyOvLt2JrXUvml/H4ZB1t7P93kQoPWg2j4hIM1IZEQCuGdSeOI+bLXnFLN16wHSc8HTBg9CmF5TkwbxfaTE0EQkbKiMCQEJ0JNcM6gDAq0t3mA0TriKjq4Zr3PDdW/DNP0wnEhFpFiojUm1cVicAFq7LZc/hI4bThKn2g+DCqjVH5t8PeRvM5hERaQYqI1Kte0oCZ3dtjc+GVz7fbjpO+BpxD3S9ECqPwOu3QXmp6UQiIk1KZURquPPcLgC8tmw3hUcrDKcJUy4X/OTPEJ8C+9fDgkmmE4mINCmVEanh/J5t6N42nuKySl77apfpOOErvi1c8yJgwcpXYc0bphOJiDQZlRGpwbIs7jzPOTvy8uc7KK/0GU4UxrqcD+fd52y/NxEObDUaR0SkqaiMyAmuGphG24QocgqP8t7qvabjhLeRk6Dj2VBeDK/dqLv7ikhIUhmRE0RFuLltRAYAM/+9TYugmeSOgOtegoQ0yN8Ir48Hr5bsF5HQojIitbp5WCdiPW425BSxZHO+6TjhLbEd3PgaRMbC1kXwoe5fIyKhRWVEapUUG8kNQzsCMHPJNsNphLSBzhU2AMtehGUzjcYREWlMKiNyUrefk4HbZfHZlnzW7tFcBeP6XOnc4Rfggwdg68dm84iINBKVETmpDi1jubx/O8CZOyIB4JxsyLwRbC/861bY+YXpRCIiZ0xlRE7pP6ou83139V5W7DxkOI1gWTDmj9DpHCgrhL9dDd/NNZ1KROSMqIzIKfVrn8R1gztg2zD5rW+17kggiIiCn70Bva4Ab5mzZPxXfzadSkSkwVRG5LQevKw3reM8bMotZsanWngrIETGwE//BkN+DtjwwX/DwqngU1kUkeCjMiKn1TLOw0Nj+gDw/Mdb2JJXbDiRAOByw+VPw4VTnK8/fxbe+S/w6p5CIhJcVEakTq7MTOP8nm0o9/r49Vtr8Pm0EFpAsCxnyfirXwDLDatfgzm3QMUR08lEROpMZUTqxLIsfn91P2I9bpbtOMjsr3ebjiTHG3gT3DALIqJh0wfwj2u1dLyIBA2VEamzDi1j+dXFPQGY9sF6cguPGk4kNfS8BH72FkQlws7P4ZUroHi/6VQiIqelMiL1ctvZGWR2SKLoaCW/mPUNZZVe05HkeBkj4Lb3ITYZcr6Fly+BvA2mU4mInJLKiNSL22Xx9E8zSYiKYNmOgzz49lrdSC/QtMuE2z+EpHQ4sAVeHOlc+qt/TiISoFRGpN66tU3guZvOwmXBGyu+58+6d03gSe4Gd/wfdL0IKo86l/7+41oo3Gc6mYjICVRGpEHO79mWh65wLvd9YsEGPvwux3AiOUFCKvzsTbj0D87E1q2L4IUsrdgqIgFHZUQa7NazM/jZjzpi23DP7FW6mV4gsiwY/h/wH59C6gA4cghevxVm3wyFe02nExEBVEbkDFiWxdQxfTmnWzJHKrzc8epytuQVmY4ltWnbC+5YBOfdD64I2PA+PD8Mls3Uqq0iYpzKiJyRSLeL6TcPolvbeHIKj3LtC0tZtv2g6VhSmwgPXPgb+H9LoP0QKC+C+ffBS6Nh37em04lIGFMZkTOWFBPJv/5fFmd1bEHBkQp+9tevmPetJkoGrJS+8POPnLkknnj4fhn8+Tx4+y4o2GM6nYiEIZURaRSt4jzMuuNHXNwnhfJKH3e/tpK/frbddCw5GZfbmUsy4Svody1gw+pZ8NxgWPQIlGm4TUSaj2UHwSIRhYWFJCUlUVBQQGJiouk4cgpen81v3/2Ov3+5E4CbhnfkoSv6EB3pNpxMTun75fDRb2DXUufr2NYw7P/BsDshtpXZbCIStOr6+a0yIo3Otm3+vGQbj3/grPzZvW08f7rxLHq30z+7gGbbsGEeLHwIDm519kXGwlm3QNYEaNnJbD4RCToqI2Lckk37+dXrq9lfVIbH7WLSpb0YPyIDy7JMR5NT8VbCurnw+R+dJeXBuSNwn6sg627oMNhoPBEJHiojEhAOFJfx3298y6INeQCM7NGGx67pT/sWMYaTyWnZNmz/1CklWz8+tj/9R86Zkl6XO3NPREROQmVEAoZt2/zjy538ft56yip9REe6uPuCbtx5XheiIvRhFhRy1sDS/4U1r4OvwtnXohNk3gD9roM2PczmE5GApDIiAWdzbhEPzl1bvQ5JRutYfntlX87v2dZwMqmzohxnobTlf3VWc/VLHQD9r3euzElqby6fiAQUlREJSLZt8+7qvfx+3nr2F5UBcG73ZG7NyuCCXm1xuzSfJCiUlzqTXde87tzzxlfp7Ldc0OUCOOtm6Hk5REabzSkiRqmMSEArOlrBH/9vMy9/sQOvz/lXMC0pmhuHdWTssHTaJuhDLGiUHHAmvK55A3Z9cWx/dAvofx10HgntB0Fie+deOSISNlRGJCjsPFDCP7/axb+W7+ZwqTMXIcJlMahTS0b2aMN53dvQNy0Rl86YBIeD22DVLOdR+IPVXOPaQNpZVY9BznNCipmcItIsVEYkqByt8DJ/zT7++dUuVuw8VON7reM8ZHVtzbDOrRjSqRU9UxM0nBPofF7YthjWvQN7V0LuOrC9J74uIc05a5LcA1pmOGuZtMyAxA7gjmjm0CLS2Jq0jEyfPp0//OEP5OTkkJmZyXPPPcewYcNO+vrXX3+dKVOmsGPHDrp3784TTzzBZZddVuf3UxkJL7sOlPLp5v0s2bSfL7bkU1Je80MsISqCQZ1a0rtdIl3axNG1TRxd28TTItZjKLGcVsURyFnrFJO9q5zn/RuBk/znx3JDYpoztJPUwXm0SK8qLJ0hKd258Z+IBLQmKyNz5sxh3LhxzJgxg+HDh/Pss8/y+uuvs3HjRtq2PfGqiC+++ILzzjuPadOmccUVVzBr1iyeeOIJVq5cSb9+/Rr1l5HQU+H1sXLnIb7afpCvdxxk5c5DJ5QTv1ZxHrq1iadr23i6tY2ne9t42reMoXWch8ToSA31BJqyYti3GvatcoZ3Du2EQzvg8C7wlp3mYMspKgkpzvBPXDLEtXWWsY9p4cxXiU5ytqMSwJMAUfEQEdXUv5WIHKfJysjw4cMZOnQozz//PAA+n4/09HR+8YtfMGnSpBNeP3bsWEpKSnj//fer9/3oRz9i4MCBzJgxo1F/GQl9lV4fG3KKWLnrEFvyitm6v5ht+0vYV3D0lMe5XRYtYyNpEeshLiqC2Eg3sR43sVERxHncxEVFEBcVQXyUs+1xu/BEuIhwuYh0W0S6XVUPiwi3C4/bhauOt5l0WVbVAyzLqvMcTv8xrqoDwmbup+3DVZJHRNEe3FWPiKLvcRd+T0ThTtwFu3BVHmnYj3Z78EXGYXvi8UXGY3visT1x2BHR2C4PtjsSXJHYrkhstwdcEVX7PNjuCGyXB9zO93FHYltuwHKuIrIsbMtVtV31oGqfKwJcbuf1rgjnmB9ms6wTjj2BZWHjvJf/dbb/tT/cd/x+kTpolZJOVHRso/7Mun5+12tQtry8nBUrVjB58uTqfS6Xi1GjRrF06dJaj1m6dCnZ2dk19o0ePZq5c+ee9H3KysooKzv2f0aFhYX1iSkhLMLtol/7JPq1T6qxv6Ssku35JWzJK2ZLXjGb84rYkldMXmEZRWWVeH02+cXl5BeXG0ouDZMA9Kp6+NkkU0gHaz/JVgHJVgGtKSTZKqCVVUQiJSRZJSRRQqJVQgJHiLacydGWtxy3txyOHqrtzUTC2oYr3qLXkIuMvHe9ykh+fj5er5eUlJoz4FNSUtiwYUOtx+Tk5NT6+pycnJO+z7Rp03j44YfrE03CXFxURK0lBaC80seh0nIOFJdzuLScknIvpeWVHCn3Ulq1XVzmpaSskuKqR4XX5zwqbSp8PsorfVR6nW3/fl8dTiraOKuq27bzel8dz0Pato1tU31MXd4rnBTRkvW0PPEb9g+eq7jxEscR4jh67Nk69nUUFURSSQReIqnEQyURViWRVFbv91BJBJVEVr0mkkqc8xQ2LnxY2Lirni3Asny48VV/PwIfbry4OXGY0YLqn2XhHHey11hVP8/t/Nt1XAbnWAtwVb2v/7UidWHVdjaumQTkdPXJkyfXOJtSWFhIenq6wUQSzDwRLlISo0lJ1NolIiIn09Pge9erjCQnJ+N2u8nNza2xPzc3l9TU1FqPSU1NrdfrAaKiooiK0kQzERGRcFDHKXgOj8fD4MGDWbRoUfU+n8/HokWLyMrKqvWYrKysGq8HWLhw4UlfLyIiIuGl3sM02dnZ3HrrrQwZMoRhw4bx7LPPUlJSwvjx4wEYN24c7du3Z9q0aQBMnDiRkSNH8vTTT3P55Zcze/Zsli9fzosvvti4v4mIiIgEpXqXkbFjx7J//34eeughcnJyGDhwIAsWLKiepLpr1y5cx13zePbZZzNr1ix+85vf8Otf/5ru3bszd+7cOq8xIiIiIqFNy8GLiIhIk6jr53e95oyIiIiINDaVERERETFKZURERESMUhkRERERo1RGRERExCiVERERETFKZURERESMUhkRERERo1RGRERExKh6Lwdvgn+R2MLCQsNJREREpK78n9unW+w9KMpIUVERAOnp6YaTiIiISH0VFRWRlJR00u8Hxb1pfD4fe/fuJSEhAcuyGvxzCgsLSU9PZ/fu3brHTTPQ37t56e/dvPT3bl76ezevxvp727ZNUVERaWlpNW6i+0NBcWbE5XLRoUOHRvt5iYmJ+pe5Genv3bz0925e+ns3L/29m1dj/L1PdUbETxNYRURExCiVERERETEqrMpIVFQUU6dOJSoqynSUsKC/d/PS37t56e/dvPT3bl7N/fcOigmsIiIiErrC6syIiIiIBB6VERERETFKZURERESMUhkRERERo8KmjEyfPp2MjAyio6MZPnw4y5YtMx0pJE2bNo2hQ4eSkJBA27Ztufrqq9m4caPpWGHj8ccfx7Is7rnnHtNRQtaePXv42c9+RuvWrYmJiaF///4sX77cdKyQ5PV6mTJlCp07dyYmJoauXbvyyCOPnPY+J1J3S5YsYcyYMaSlpWFZFnPnzq3xfdu2eeihh2jXrh0xMTGMGjWKzZs3N3qOsCgjc+bMITs7m6lTp7Jy5UoyMzMZPXo0eXl5pqOFnE8//ZQJEybw5ZdfsnDhQioqKrj44ospKSkxHS3kff311/z5z39mwIABpqOErEOHDjFixAgiIyP54IMPWLduHU8//TQtW7Y0HS0kPfHEE7zwwgs8//zzrF+/nieeeIInn3yS5557znS0kFFSUkJmZibTp0+v9ftPPvkkf/rTn5gxYwZfffUVcXFxjB49mqNHjzZuEDsMDBs2zJ4wYUL1116v105LS7OnTZtmMFV4yMvLswH7008/NR0lpBUVFdndu3e3Fy5caI8cOdKeOHGi6Ugh6YEHHrDPOecc0zHCxuWXX27ffvvtNfZdc8019s0332woUWgD7Lfffrv6a5/PZ6emptp/+MMfqvcdPnzYjoqKsl977bVGfe+QPzNSXl7OihUrGDVqVPU+l8vFqFGjWLp0qcFk4aGgoACAVq1aGU4S2iZMmMDll19e499zaXzvvvsuQ4YM4frrr6dt27acddZZzJw503SskHX22WezaNEiNm3aBMDq1av57LPPuPTSSw0nCw/bt28nJyenxn9XkpKSGD58eKN/fgbFjfLORH5+Pl6vl5SUlBr7U1JS2LBhg6FU4cHn83HPPfcwYsQI+vXrZzpOyJo9ezYrV67k66+/Nh0l5G3bto0XXniB7Oxsfv3rX/P111/zy1/+Eo/Hw6233mo6XsiZNGkShYWF9OrVC7fbjdfr5dFHH+Xmm282HS0s5OTkANT6+en/XmMJ+TIi5kyYMIG1a9fy2WefmY4Ssnbv3s3EiRNZuHAh0dHRpuOEPJ/Px5AhQ3jssccAOOuss1i7di0zZsxQGWkC//rXv/jnP//JrFmz6Nu3L6tWreKee+4hLS1Nf+8QE/LDNMnJybjdbnJzc2vsz83NJTU11VCq0Hf33Xfz/vvv88knn9ChQwfTcULWihUryMvLY9CgQURERBAREcGnn37Kn/70JyIiIvB6vaYjhpR27drRp0+fGvt69+7Nrl27DCUKbffffz+TJk3ihhtuoH///txyyy3ce++9TJs2zXS0sOD/jGyOz8+QLyMej4fBgwezaNGi6n0+n49FixaRlZVlMFlosm2bu+++m7fffpuPP/6Yzp07m44U0i666CLWrFnDqlWrqh9Dhgzh5ptvZtWqVbjdbtMRQ8qIESNOuFR906ZNdOrUyVCi0FZaWorLVfNjyu124/P5DCUKL507dyY1NbXG52dhYSFfffVVo39+hsUwTXZ2NrfeeitDhgxh2LBhPPvss5SUlDB+/HjT0ULOhAkTmDVrFu+88w4JCQnV44pJSUnExMQYThd6EhISTpiPExcXR+vWrTVPpwnce++9nH322Tz22GP89Kc/ZdmyZbz44ou8+OKLpqOFpDFjxvDoo4/SsWNH+vbtyzfffMMzzzzD7bffbjpayCguLmbLli3VX2/fvp1Vq1bRqlUrOnbsyD333MPvf/97unfvTufOnZkyZQppaWlcffXVjRukUa/NCWDPPfec3bFjR9vj8djDhg2zv/zyS9ORQhJQ6+Pll182HS1s6NLepvXee+/Z/fr1s6OiouxevXrZL774oulIIauwsNCeOHGi3bFjRzs6Otru0qWL/eCDD9plZWWmo4WMTz75pNb/Zt966622bTuX906ZMsVOSUmxo6Ki7IsuusjeuHFjo+ewbFtL2YmIiIg5IT9nRERERAKbyoiIiIgYpTIiIiIiRqmMiIiIiFEqIyIiImKUyoiIiIgYpTIiIiIiRqmMiIiIiFEqIyJygsWLF2NZFocPH27W933llVdo0aLFGf2MHTt2YFkWq1atOulrTP1+IlI7lRER4fzzz+eee+4xHUNEwpTKiIg0ivLyctMRRCRIqYyIhLnbbruNTz/9lD/+8Y9YloVlWezYsQOAFStWMGTIEGJjYzn77LPZuHFj9XG//e1vGThwIH/5y1/o3Lkz0dHRABw+fJg77riDNm3akJiYyIUXXsjq1aurj1u9ejUXXHABCQkJJCYmMnjwYJYvX14j04cffkjv3r2Jj4/nkksuYd++fdXf8/l8/O53v6NDhw5ERUUxcOBAFixYcMrfcf78+fTo0YOYmBguuOCC6t9PRAKDyohImPvjH/9IVlYWd955J/v27WPfvn2kp6cD8OCDD/L000+zfPlyIiIiTrh1+5YtW3jzzTd56623qudoXH/99eTl5fHBBx+wYsUKBg0axEUXXcTBgwcBuPnmm+nQoQNff/01K1asYNKkSURGRlb/zNLSUp566in+/ve/s2TJEnbt2sV9991XI+/TTz/NU089xbfffsvo0aO58sor2bx5c62/3+7du7nmmmsYM2YMq1at4o477mDSpEmN+ScUkTPV6PcBFpGgM3LkSHvixInVX/tvK/5///d/1fvmzZtnA/aRI0ds27btqVOn2pGRkXZeXl71a/7973/biYmJ9tGjR2v8/K5du9p//vOfbdu27YSEBPuVV16pNcfLL79sA/aWLVuq902fPt1OSUmp/jotLc1+9NFHaxw3dOhQ+7/+679s27bt7du324D9zTff2LZt25MnT7b79OlT4/UPPPCADdiHDh061Z9FRJqJzoyIyEkNGDCgertdu3YA5OXlVe/r1KkTbdq0qf569erVFBcX07p1a+Lj46sf27dvZ+vWrQBkZ2dzxx13MGrUKB5//PHq/X6xsbF07dq1xvv637OwsJC9e/cyYsSIGseMGDGC9evX1/o7rF+/nuHDh9fYl5WVVee/gYg0vQjTAUQkcB0/fGJZFuDM2fCLi4ur8fri4mLatWvH4sWLT/hZ/kt2f/vb33LTTTcxb948PvjgA6ZOncrs2bP5yU9+csJ7+t/Xtu3G+HVEJEDpzIiI4PF48Hq9Z/xzBg0aRE5ODhEREXTr1q3GIzk5ufp1PXr04N577+Wjjz7immuu4eWXX67Tz09MTCQtLY3PP/+8xv7PP/+cPn361HpM7969WbZsWY19X375ZT1/MxFpSiojIkJGRgZfffUVO3bsID8/v8bZj/oYNWoUWVlZXH311Xz00Ufs2LGDL774ggcffJDly5dz5MgR7r77bhYvXszOnTv5/PPP+frrr+ndu3ed3+P+++/niSeeYM6cOWzcuJFJkyaxatUqJk6cWOvr//M//5PNmzdz//33s3HjRmbNmsUrr7zSoN9PRJqGyoiIcN999+F2u+nTpw9t2rRh165dDfo5lmUxf/58zjvvPMaPH0+PHj244YYb2LlzJykpKbjdbg4cOMC4cePo0aMHP/3pT7n00kt5+OGH6/wev/zlL8nOzuZXv/oV/fv3Z8GCBbz77rt079691td37NiRN998k7lz55KZmcmMGTN47LHHGvT7iUjTsGwNxoqIiIhBOjMiIiIiRqmMiIiIiFEqIyIiImKUyoiIiIgYpTIiIiIiRqmMiIiIiFEqIyIiImKUyoiIiIgYpTIiIiIiRqmMiIiIiFEqIyIiImLU/wcMZbk8FJgViwAAAABJRU5ErkJggg==",
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+ "