DCGAN_MnistDigits.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "DCGAN MnistDigits.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "machine_shape": "hm",
      "authorship_tag": "ABX9TyPdJ2OUX+XN4UqTpaGpr9F8",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/arjun-gangwar/Geneartive-Adversarial-Networks/blob/master/DCGAN_MnistDigits.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "P7mrvA_NWqny",
        "colab_type": "code",
        "outputId": "237d34f1-434b-4e8c-a4d9-b92be17e6dd5",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 306
        }
      },
      "source": [
        "gpu_info = !nvidia-smi\n",
        "gpu_info = '\\n'.join(gpu_info)\n",
        "if gpu_info.find('failed') >= 0:\n",
        "  print('Select the Runtime → \"Change runtime type\" menu to enable a GPU accelerator, ')\n",
        "  print('and then re-execute this cell.')\n",
        "else:\n",
        "  print(gpu_info)"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Sat May  9 14:39:22 2020       \n",
            "+-----------------------------------------------------------------------------+\n",
            "| NVIDIA-SMI 440.82       Driver Version: 418.67       CUDA Version: 10.1     |\n",
            "|-------------------------------+----------------------+----------------------+\n",
            "| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |\n",
            "| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |\n",
            "|===============================+======================+======================|\n",
            "|   0  Tesla P100-PCIE...  Off  | 00000000:00:04.0 Off |                    0 |\n",
            "| N/A   35C    P0    26W / 250W |      0MiB / 16280MiB |      0%      Default |\n",
            "+-------------------------------+----------------------+----------------------+\n",
            "                                                                               \n",
            "+-----------------------------------------------------------------------------+\n",
            "| Processes:                                                       GPU Memory |\n",
            "|  GPU       PID   Type   Process name                             Usage      |\n",
            "|=============================================================================|\n",
            "|  No running processes found                                                 |\n",
            "+-----------------------------------------------------------------------------+\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2dOIl8KZbAKY",
        "colab_type": "text"
      },
      "source": [
        "## Import Utilities"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "k4Yyuh1wWsyg",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import os\n",
        "import tensorflow as tf\n",
        "from tensorflow.keras import models, layers\n",
        "from tensorflow.keras.utils import plot_model\n",
        "%matplotlib inline"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "l0j6bHBJa3eH",
        "colab_type": "text"
      },
      "source": [
        "## Import and Load Dataset"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pgDjmyKoWuzq",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "from tensorflow.keras.datasets.mnist import load_data\n",
        "(trainX, trainy), (testX, testy) = load_data()"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "iVo1TgyAbfSF",
        "colab_type": "code",
        "outputId": "40be4f70-d1b9-4200-bc64-81b1afdc18ca",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 51
        }
      },
      "source": [
        "print(\"train shape: \", trainX.shape, trainy.shape)\n",
        "print(\"test shape: \", testX.shape, testy.shape)"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "train shape:  (60000, 28, 28) (60000,)\n",
            "test shape:  (10000, 28, 28) (10000,)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5BdapOrIb7KW",
        "colab_type": "text"
      },
      "source": [
        "## Explore dataset"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "AazJF-JFb1VK",
        "colab_type": "code",
        "outputId": "2604eaef-c685-476c-e45c-31692559efad",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 589
        }
      },
      "source": [
        "plt.figure(figsize=(10,10))\n",
        "for i in range(25):\n",
        "  plt.subplot(5, 5, i+1)\n",
        "  plt.imshow(trainX[i], cmap='gray_r')\n",
        "  plt.xlabel(trainy[i])\n",
        "  plt.xticks([])\n",
        "  plt.yticks([])"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x720 with 25 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "zHJoXLkcgRDE",
        "colab_type": "text"
      },
      "source": [
        "## Discriminator Model"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FfxKz1zhcr2v",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "from tensorflow.keras.optimizers import Adam"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "sqdP0rEvT6Hw",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "def define_discriminator(in_shape=(28, 28, 1)):\n",
        "  model = tf.keras.Sequential()\n",
        "  model.add(layers.Conv2D(64, (3,3), strides=(2,2), padding='same', input_shape=in_shape))\n",
        "  model.add(layers.LeakyReLU(alpha=0.2))\n",
        "  model.add(layers.Dropout(0.4))\n",
        "  model.add(layers.Conv2D(64, (3,3), strides=(2,2), padding='same'))\n",
        "  model.add(layers.LeakyReLU(alpha=0.2))\n",
        "  model.add(layers.Dropout(0.4))\n",
        "  model.add(layers.Flatten())\n",
        "  model.add(layers.Dense(1, activation='sigmoid'))\n",
        "\n",
        "  opt = Adam(lr=0.0002, beta_1=0.5)\n",
        "  model.compile(loss='binary_crossentropy', optimizer=opt, metrics=['accuracy'])\n",
        "  return model"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pxIfTTnqU5TK",
        "colab_type": "code",
        "outputId": "12d1e00f-c816-4032-94df-28205b5187e7",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 425
        }
      },
      "source": [
        "model = define_discriminator()\n",
        "model.summary()"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Model: \"sequential\"\n",
            "_________________________________________________________________\n",
            "Layer (type)                 Output Shape              Param #   \n",
            "=================================================================\n",
            "conv2d (Conv2D)              (None, 14, 14, 64)        640       \n",
            "_________________________________________________________________\n",
            "leaky_re_lu (LeakyReLU)      (None, 14, 14, 64)        0         \n",
            "_________________________________________________________________\n",
            "dropout (Dropout)            (None, 14, 14, 64)        0         \n",
            "_________________________________________________________________\n",
            "conv2d_1 (Conv2D)            (None, 7, 7, 64)          36928     \n",
            "_________________________________________________________________\n",
            "leaky_re_lu_1 (LeakyReLU)    (None, 7, 7, 64)          0         \n",
            "_________________________________________________________________\n",
            "dropout_1 (Dropout)          (None, 7, 7, 64)          0         \n",
            "_________________________________________________________________\n",
            "flatten (Flatten)            (None, 3136)              0         \n",
            "_________________________________________________________________\n",
            "dense (Dense)                (None, 1)                 3137      \n",
            "=================================================================\n",
            "Total params: 40,705\n",
            "Trainable params: 40,705\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "D0FkT0f5Wqzj",
        "colab_type": "code",
        "outputId": "865a21e5-2725-4cb6-a28e-a8726b98c8ca",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 976
        }
      },
      "source": [
        "plot_model(model, to_file='discriminator_plot.png', show_shapes=True, show_layer_names=True)"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<IPython.core.display.Image object>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "IE-nxawBuBme",
        "colab_type": "text"
      },
      "source": [
        "## Train standalone Discriminator"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4gdGXMORW1Wm",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "def load_real_samples():\n",
        "  (trainX, _), (_, _) = load_data()\n",
        "  X = np.expand_dims(trainX, axis=-1)\n",
        "  X = X.astype('float32')\n",
        "  X = X / 255.0\n",
        "  return X"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "F6sIJ8IZvtce",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "def generate_real_samples(dataset, n_samples):\n",
        "  ix = np.random.randint(0, dataset.shape[0], n_samples)\n",
        "  X = dataset[ix]\n",
        "  y = np.ones((n_samples,1))\n",
        "  return X, y"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lu4ljWQ3x9JW",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "def generate_fake_samples(n_samples):\n",
        "  X = np.random.rand(28*28*n_samples)\n",
        "  X = X.reshape((n_samples, 28, 28, 1))\n",
        "  y = np.zeros((n_samples,1))\n",
        "  return X, y "
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SHhOCGqm3qlL",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "def train_discriminator(model, dataset, n_iter=100, n_batch=256):\n",
        "  half_batch = int(n_batch/2)\n",
        "  for i in range(n_iter):\n",
        "    X_real, y_real = generate_real_samples(dataset, half_batch)\n",
        "    _, real_acc = model.train_on_batch(X_real, y_real)\n",
        "    X_fake, y_fake = generate_fake_samples(half_batch)\n",
        "    _, fake_acc = model.train_on_batch(X_fake, y_fake)\n",
        "    print('>%d real=%.0f%% fake=%.0f%%' % (i+1, real_acc*100, fake_acc*100))"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tF44-u7e5bFT",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "#model = define_discriminator()\n",
        "#dataset = load_real_samples()\n",
        "#train_discriminator(model, dataset)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "FzrXv38Rtu9t",
        "colab_type": "text"
      },
      "source": [
        "## Generator Model"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lHxc1xdc5qdd",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "def define_generator(latent_dim):\n",
        "  model = tf.keras.Sequential()\n",
        "  #128 feature maps and 7x7 resolution image\n",
        "  n_nodes = 128*7*7\n",
        "  model.add(layers.Dense(n_nodes, input_dim=latent_dim))\n",
        "  model.add(layers.LeakyReLU(alpha=0.2))\n",
        "  model.add(layers.Reshape((7,7,128)))\n",
        "  model.add(layers.Conv2DTranspose(128, (4,4), strides=(2,2), padding='same'))\n",
        "  model.add(layers.LeakyReLU(alpha=0.2))\n",
        "  model.add(layers.Conv2DTranspose(128, (4,4), strides=(2,2), padding='same'))\n",
        "  model.add(layers.LeakyReLU(alpha=0.2))\n",
        "  model.add(layers.Conv2D(1, (7,7), activation='sigmoid', padding='same'))\n",
        "  return model"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-E4-ic9TWONI",
        "colab_type": "code",
        "outputId": "09a06d4b-0ee6-49fa-9edf-f1fc5fc2e699",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        }
      },
      "source": [
        "latent_dim = 100\n",
        "model = define_generator(latent_dim)\n",
        "model.summary()\n",
        "plot_model(model, to_file='generator_plot.png', show_shapes=True, show_layer_names=True)"
      ],
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Model: \"sequential_1\"\n",
            "_________________________________________________________________\n",
            "Layer (type)                 Output Shape              Param #   \n",
            "=================================================================\n",
            "dense_1 (Dense)              (None, 6272)              633472    \n",
            "_________________________________________________________________\n",
            "leaky_re_lu_2 (LeakyReLU)    (None, 6272)              0         \n",
            "_________________________________________________________________\n",
            "reshape (Reshape)            (None, 7, 7, 128)         0         \n",
            "_________________________________________________________________\n",
            "conv2d_transpose (Conv2DTran (None, 14, 14, 128)       262272    \n",
            "_________________________________________________________________\n",
            "leaky_re_lu_3 (LeakyReLU)    (None, 14, 14, 128)       0         \n",
            "_________________________________________________________________\n",
            "conv2d_transpose_1 (Conv2DTr (None, 28, 28, 128)       262272    \n",
            "_________________________________________________________________\n",
            "leaky_re_lu_4 (LeakyReLU)    (None, 28, 28, 128)       0         \n",
            "_________________________________________________________________\n",
            "conv2d_2 (Conv2D)            (None, 28, 28, 1)         6273      \n",
            "=================================================================\n",
            "Total params: 1,164,289\n",
            "Trainable params: 1,164,289\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<IPython.core.display.Image object>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "V8J0RQ-mt55l",
        "colab_type": "text"
      },
      "source": [
        "## Sample Image Generation from Untrained Generator"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IlaG8vIe2Pxx",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "def generate_latent_points(latent_dim, n_samples):\n",
        "  x_input = np.random.randn(latent_dim * n_samples)\n",
        "  x_input = x_input.reshape(n_samples, latent_dim)\n",
        "  return x_input"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0lAnb-OxlTvu",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "def generate_fake_samples(g_model, latent_dim, n_samples):\n",
        "  x_input = generate_latent_points(latent_dim, n_samples)\n",
        "  X = g_model.predict(x_input)\n",
        "  y = np.zeros((n_samples,1))\n",
        "  return X, y"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fkexZO8zEYJy",
        "colab_type": "code",
        "outputId": "deb3036f-5919-4743-be8e-edffa19e3837",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 578
        }
      },
      "source": [
        "latent_dim = 100\n",
        "model = define_generator(latent_dim)\n",
        "n_samples = 25\n",
        "X, _ = generate_fake_samples(model, latent_dim, n_samples)\n",
        "plt.figure(figsize=(10,10))\n",
        "for i in range(n_samples):\n",
        "  plt.subplot(5,5,i+1)\n",
        "  plt.imshow(X[i,:,:,0], cmap='gray_r')\n",
        "  plt.xticks([])\n",
        "  plt.yticks([])"
      ],
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x720 with 25 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5kAP-AEDuDRX",
        "colab_type": "text"
      },
      "source": [
        "## GAN Model"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DUiOesT9Jf9q",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "def define_gan(g_model, d_model):\n",
        "  d_model.trainable = False\n",
        "  model = tf.keras.Sequential()\n",
        "  model.add(g_model)\n",
        "  model.add(d_model)\n",
        "  opt = tf.keras.optimizers.Adam(lr=0.0002, beta_1=0.5)\n",
        "  model.compile(loss='binary_crossentropy', optimizer=opt)\n",
        "  return model"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "c7F1UCiNbhhu",
        "colab_type": "code",
        "outputId": "53decc51-4fc7-4b58-90d2-3103e3025dbd",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 516
        }
      },
      "source": [
        "latent_dim = 100\n",
        "d_model = define_discriminator()\n",
        "g_model = define_generator(latent_dim)\n",
        "gan_model = define_gan(g_model, d_model)\n",
        "gan_model.summary()\n",
        "plot_model(gan_model, to_file='gan_model.png', show_layer_names=True, show_shapes=True)"
      ],
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Model: \"sequential_5\"\n",
            "_________________________________________________________________\n",
            "Layer (type)                 Output Shape              Param #   \n",
            "=================================================================\n",
            "sequential_4 (Sequential)    (None, 28, 28, 1)         1164289   \n",
            "_________________________________________________________________\n",
            "sequential_3 (Sequential)    (None, 1)                 40705     \n",
            "=================================================================\n",
            "Total params: 1,204,994\n",
            "Trainable params: 1,164,289\n",
            "Non-trainable params: 40,705\n",
            "_________________________________________________________________\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<IPython.core.display.Image object>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "rLBhKZDVuKgl",
        "colab_type": "text"
      },
      "source": [
        "## Train and Evaluate GAN Model"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gqU1SrlEsyg_",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "def save_plot(examples, epoch, n=10):\n",
        "  for i in range(n * n):\n",
        "    plt.subplot(n, n, 1 + i)\n",
        "    plt.axis('off')\n",
        "    plt.imshow(examples[i, :, :, 0], cmap='gray_r')\n",
        "    filename = 'generated_plot_e%03d.png' % (epoch+1) \n",
        "  plt.savefig(filename)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NVlSSaEBsl7c",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "def summarize_performance(epoch, g_model, d_model, dataset, latent_dim, n_samples=100):\n",
        "  X_real, y_real = generate_real_samples(dataset, n_samples)\n",
        "  _, acc_real = d_model.evaluate(X_real, y_real, verbose=0)\n",
        "  x_fake, y_fake = generate_fake_samples(g_model, latent_dim, n_samples)\n",
        "  _, acc_fake = d_model.evaluate(x_fake, y_fake, verbose=0)\n",
        "  print('>Accuracy real: %.0f%%, fake: %.0f%%' % (acc_real*100, acc_fake*100))\n",
        "  save_plot(x_fake, epoch)\n",
        "  filename = 'generator_model_%03d.h5' % (epoch + 1) \n",
        "  g_model.save(filename)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "W4_vnSiDcAW9",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "def train_gan(g_model, d_model, gan_model, dataset, latent_dim, n_epochs=100, n_batch=256):\n",
        "  bat_per_epo = int(dataset.shape[0]/n_batch)\n",
        "  half_batch = int(n_batch/2)\n",
        "  for i in range(n_epochs):\n",
        "    for j in range(bat_per_epo):\n",
        "      X_real, y_real = generate_real_samples(dataset, half_batch)\n",
        "      X_fake, y_fake = generate_fake_samples(g_model, latent_dim, half_batch)\n",
        "      X, y = np.vstack((X_real, X_fake)), np.vstack((y_real, y_fake))\n",
        "      d_loss, _ = d_model.train_on_batch(X, y)\n",
        "      X_gan = generate_latent_points(latent_dim, n_batch)\n",
        "      y_gan = np.ones((n_batch,1))\n",
        "      g_loss = gan_model.train_on_batch(X_gan, y_gan)\n",
        "      print('>%d, %d/%d, d=%.3f, g=%.3f' % (i+1, j+1, bat_per_epo, d_loss, g_loss))\n",
        "      if (i+1) % 10 == 0 and (j+1) % 50 == 0:\n",
        "        summarize_performance(i, g_model, d_model, dataset, latent_dim)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hMlokeOZo3Hc",
        "colab_type": "code",
        "outputId": "28029f9d-ef9a-47fb-d0ef-b254fe011f26",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        }
      },
      "source": [
        "latent_dim = 100\n",
        "d_model = define_discriminator()\n",
        "g_model = define_generator(latent_dim)\n",
        "gan_model = define_gan(g_model, d_model)\n",
        "dataset = load_real_samples()\n",
        "train_gan(g_model, d_model, gan_model, dataset, latent_dim)"
      ],
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            ">1, 1/234, d=0.706, g=0.681\n",
            ">1, 2/234, d=0.697, g=0.709\n",
            ">1, 3/234, d=0.692, g=0.726\n",
            ">1, 4/234, d=0.680, g=0.753\n",
            ">1, 5/234, d=0.673, g=0.769\n",
            ">1, 6/234, d=0.666, g=0.793\n",
            ">1, 7/234, d=0.656, g=0.811\n",
            ">1, 8/234, d=0.650, g=0.826\n",
            ">1, 9/234, d=0.643, g=0.837\n",
            ">1, 10/234, d=0.646, g=0.845\n",
            ">1, 11/234, d=0.638, g=0.851\n",
            ">1, 12/234, d=0.636, g=0.836\n",
            ">1, 13/234, d=0.642, g=0.825\n",
            ">1, 14/234, d=0.644, g=0.807\n",
            ">1, 15/234, d=0.646, g=0.781\n",
            ">1, 16/234, d=0.644, g=0.762\n",
            ">1, 17/234, d=0.650, g=0.746\n",
            ">1, 18/234, d=0.647, g=0.729\n",
            ">1, 19/234, d=0.645, g=0.720\n",
            ">1, 20/234, d=0.642, g=0.712\n",
            ">1, 21/234, d=0.636, g=0.707\n",
            ">1, 22/234, d=0.632, g=0.702\n",
            ">1, 23/234, d=0.619, g=0.700\n",
            ">1, 24/234, d=0.618, g=0.697\n",
            ">1, 25/234, d=0.606, g=0.697\n",
            ">1, 26/234, d=0.600, g=0.696\n",
            ">1, 27/234, d=0.597, g=0.697\n",
            ">1, 28/234, d=0.580, g=0.696\n",
            ">1, 29/234, d=0.572, g=0.697\n",
            ">1, 30/234, d=0.566, g=0.698\n",
            ">1, 31/234, d=0.553, g=0.698\n",
            ">1, 32/234, d=0.547, g=0.698\n",
            ">1, 33/234, d=0.535, g=0.699\n",
            ">1, 34/234, d=0.525, g=0.700\n",
            ">1, 35/234, d=0.513, g=0.701\n",
            ">1, 36/234, d=0.510, g=0.701\n",
            ">1, 37/234, d=0.491, g=0.703\n",
            ">1, 38/234, d=0.490, g=0.704\n",
            ">1, 39/234, d=0.482, g=0.705\n",
            ">1, 40/234, d=0.471, g=0.707\n",
            ">1, 41/234, d=0.465, g=0.707\n",
            ">1, 42/234, d=0.447, g=0.710\n",
            ">1, 43/234, d=0.442, g=0.711\n",
            ">1, 44/234, d=0.443, g=0.714\n",
            ">1, 45/234, d=0.426, g=0.716\n",
            ">1, 46/234, d=0.421, g=0.719\n",
            ">1, 47/234, d=0.412, g=0.722\n",
            ">1, 48/234, d=0.407, g=0.724\n",
            ">1, 49/234, d=0.400, g=0.728\n",
            ">1, 50/234, d=0.399, g=0.731\n",
            ">1, 51/234, d=0.392, g=0.734\n",
            ">1, 52/234, d=0.386, g=0.739\n",
            ">1, 53/234, d=0.378, g=0.743\n",
            ">1, 54/234, d=0.378, g=0.747\n",
            ">1, 55/234, d=0.374, g=0.753\n",
            ">1, 56/234, d=0.366, g=0.760\n",
            ">1, 57/234, d=0.352, g=0.766\n",
            ">1, 58/234, d=0.355, g=0.775\n",
            ">1, 59/234, d=0.343, g=0.782\n",
            ">1, 60/234, d=0.351, g=0.791\n",
            ">1, 61/234, d=0.337, g=0.802\n",
            ">1, 62/234, d=0.333, g=0.811\n",
            ">1, 63/234, d=0.325, g=0.824\n",
            ">1, 64/234, d=0.320, g=0.838\n",
            ">1, 65/234, d=0.313, g=0.853\n",
            ">1, 66/234, d=0.306, g=0.868\n",
            ">1, 67/234, d=0.298, g=0.886\n",
            ">1, 68/234, d=0.292, g=0.906\n",
            ">1, 69/234, d=0.282, g=0.930\n",
            ">1, 70/234, d=0.275, g=0.953\n",
            ">1, 71/234, d=0.269, g=0.976\n",
            ">1, 72/234, d=0.259, g=1.002\n",
            ">1, 73/234, d=0.255, g=1.036\n",
            ">1, 74/234, d=0.238, g=1.067\n",
            ">1, 75/234, d=0.235, g=1.102\n",
            ">1, 76/234, d=0.227, g=1.138\n",
            ">1, 77/234, d=0.215, g=1.175\n",
            ">1, 78/234, d=0.207, g=1.219\n",
            ">1, 79/234, d=0.193, g=1.265\n",
            ">1, 80/234, d=0.190, g=1.309\n",
            ">1, 81/234, d=0.183, g=1.358\n",
            ">1, 82/234, d=0.166, g=1.405\n",
            ">1, 83/234, d=0.165, g=1.460\n",
            ">1, 84/234, d=0.153, g=1.513\n",
            ">1, 85/234, d=0.145, g=1.570\n",
            ">1, 86/234, d=0.136, g=1.629\n",
            ">1, 87/234, d=0.128, g=1.690\n",
            ">1, 88/234, d=0.117, g=1.755\n",
            ">1, 89/234, d=0.120, g=1.805\n",
            ">1, 90/234, d=0.111, g=1.871\n",
            ">1, 91/234, d=0.102, g=1.928\n",
            ">1, 92/234, d=0.097, g=1.992\n",
            ">1, 93/234, d=0.093, g=2.043\n",
            ">1, 94/234, d=0.089, g=2.096\n",
            ">1, 95/234, d=0.082, g=2.158\n",
            ">1, 96/234, d=0.078, g=2.214\n",
            ">1, 97/234, d=0.073, g=2.274\n",
            ">1, 98/234, d=0.073, g=2.334\n",
            ">1, 99/234, d=0.065, g=2.387\n",
            ">1, 100/234, d=0.065, g=2.446\n",
            ">1, 101/234, d=0.060, g=2.497\n",
            ">1, 102/234, d=0.058, g=2.542\n",
            ">1, 103/234, d=0.057, g=2.584\n",
            ">1, 104/234, d=0.058, g=2.637\n",
            ">1, 105/234, d=0.055, g=2.671\n",
            ">1, 106/234, d=0.053, g=2.706\n",
            ">1, 107/234, d=0.046, g=2.756\n",
            ">1, 108/234, d=0.049, g=2.812\n",
            ">1, 109/234, d=0.041, g=2.841\n",
            ">1, 110/234, d=0.042, g=2.883\n",
            ">1, 111/234, d=0.040, g=2.895\n",
            ">1, 112/234, d=0.045, g=2.797\n",
            ">1, 113/234, d=0.273, g=1.269\n",
            ">1, 114/234, d=2.816, g=0.023\n",
            ">1, 115/234, d=3.413, g=0.012\n",
            ">1, 116/234, d=2.836, g=0.037\n",
            ">1, 117/234, d=2.008, g=0.167\n",
            ">1, 118/234, d=1.262, g=0.609\n",
            ">1, 119/234, d=0.805, g=1.446\n",
            ">1, 120/234, d=0.520, g=2.083\n",
            ">1, 121/234, d=0.461, g=2.490\n",
            ">1, 122/234, d=0.396, g=2.585\n",
            ">1, 123/234, d=0.333, g=2.544\n",
            ">1, 124/234, d=0.332, g=2.435\n",
            ">1, 125/234, d=0.302, g=2.371\n",
            ">1, 126/234, d=0.277, g=2.432\n",
            ">1, 127/234, d=0.272, g=2.410\n",
            ">1, 128/234, d=0.263, g=2.539\n",
            ">1, 129/234, d=0.240, g=2.683\n",
            ">1, 130/234, d=0.209, g=2.728\n",
            ">1, 131/234, d=0.211, g=2.814\n",
            ">1, 132/234, d=0.176, g=2.939\n",
            ">1, 133/234, d=0.150, g=3.062\n",
            ">1, 134/234, d=0.154, g=2.801\n",
            ">1, 135/234, d=0.167, g=2.723\n",
            ">1, 136/234, d=0.187, g=2.749\n",
            ">1, 137/234, d=0.179, g=2.471\n",
            ">1, 138/234, d=0.217, g=2.244\n",
            ">1, 139/234, d=0.249, g=2.080\n",
            ">1, 140/234, d=0.286, g=1.672\n",
            ">1, 141/234, d=0.411, g=1.560\n",
            ">1, 142/234, d=0.440, g=1.299\n",
            ">1, 143/234, d=0.543, g=1.104\n",
            ">1, 144/234, d=0.591, g=0.984\n",
            ">1, 145/234, d=0.747, g=0.874\n",
            ">1, 146/234, d=0.812, g=0.780\n",
            ">1, 147/234, d=0.879, g=0.787\n",
            ">1, 148/234, d=0.925, g=0.779\n",
            ">1, 149/234, d=0.957, g=0.790\n",
            ">1, 150/234, d=0.984, g=0.781\n",
            ">1, 151/234, d=0.982, g=0.782\n",
            ">1, 152/234, d=1.035, g=0.800\n",
            ">1, 153/234, d=1.031, g=0.847\n",
            ">1, 154/234, d=1.017, g=0.843\n",
            ">1, 155/234, d=0.995, g=0.874\n",
            ">1, 156/234, d=0.984, g=0.869\n",
            ">1, 157/234, d=0.992, g=0.878\n",
            ">1, 158/234, d=0.965, g=0.882\n",
            ">1, 159/234, d=0.919, g=0.894\n",
            ">1, 160/234, d=0.899, g=0.905\n",
            ">1, 161/234, d=0.903, g=0.944\n",
            ">1, 162/234, d=0.867, g=0.950\n",
            ">1, 163/234, d=0.854, g=0.951\n",
            ">1, 164/234, d=0.866, g=0.971\n",
            ">1, 165/234, d=0.830, g=0.964\n",
            ">1, 166/234, d=0.840, g=0.913\n",
            ">1, 167/234, d=0.803, g=0.913\n",
            ">1, 168/234, d=0.788, g=0.890\n",
            ">1, 169/234, d=0.797, g=0.870\n",
            ">1, 170/234, d=0.768, g=0.933\n",
            ">1, 171/234, d=0.762, g=0.938\n",
            ">1, 172/234, d=0.751, g=0.918\n",
            ">1, 173/234, d=0.749, g=0.916\n",
            ">1, 174/234, d=0.750, g=0.880\n",
            ">1, 175/234, d=0.724, g=0.858\n",
            ">1, 176/234, d=0.739, g=0.850\n",
            ">1, 177/234, d=0.715, g=0.835\n",
            ">1, 178/234, d=0.721, g=0.837\n",
            ">1, 179/234, d=0.712, g=0.835\n",
            ">1, 180/234, d=0.704, g=0.871\n",
            ">1, 181/234, d=0.691, g=0.909\n",
            ">1, 182/234, d=0.726, g=0.915\n",
            ">1, 183/234, d=0.699, g=0.913\n",
            ">1, 184/234, d=0.699, g=0.873\n",
            ">1, 185/234, d=0.650, g=0.869\n",
            ">1, 186/234, d=0.685, g=0.856\n",
            ">1, 187/234, d=0.674, g=0.852\n",
            ">1, 188/234, d=0.674, g=0.829\n",
            ">1, 189/234, d=0.653, g=0.810\n",
            ">1, 190/234, d=0.685, g=0.854\n",
            ">1, 191/234, d=0.652, g=0.897\n",
            ">1, 192/234, d=0.684, g=0.929\n",
            ">1, 193/234, d=0.650, g=0.993\n",
            ">1, 194/234, d=0.635, g=0.984\n",
            ">1, 195/234, d=0.648, g=0.987\n",
            ">1, 196/234, d=0.665, g=0.952\n",
            ">1, 197/234, d=0.633, g=0.890\n",
            ">1, 198/234, d=0.671, g=0.860\n",
            ">1, 199/234, d=0.671, g=0.794\n",
            ">1, 200/234, d=0.648, g=0.742\n",
            ">1, 201/234, d=0.644, g=0.713\n",
            ">1, 202/234, d=0.648, g=0.675\n",
            ">1, 203/234, d=0.650, g=0.654\n",
            ">1, 204/234, d=0.655, g=0.662\n",
            ">1, 205/234, d=0.626, g=0.614\n",
            ">1, 206/234, d=0.694, g=0.652\n",
            ">1, 207/234, d=0.691, g=0.655\n",
            ">1, 208/234, d=0.703, g=0.745\n",
            ">1, 209/234, d=0.688, g=0.857\n",
            ">1, 210/234, d=0.657, g=0.987\n",
            ">1, 211/234, d=0.658, g=1.019\n",
            ">1, 212/234, d=0.680, g=0.979\n",
            ">1, 213/234, d=0.652, g=0.878\n",
            ">1, 214/234, d=0.713, g=0.803\n",
            ">1, 215/234, d=0.680, g=0.718\n",
            ">1, 216/234, d=0.672, g=0.700\n",
            ">1, 217/234, d=0.662, g=0.679\n",
            ">1, 218/234, d=0.654, g=0.663\n",
            ">1, 219/234, d=0.656, g=0.643\n",
            ">1, 220/234, d=0.663, g=0.628\n",
            ">1, 221/234, d=0.666, g=0.616\n",
            ">1, 222/234, d=0.696, g=0.625\n",
            ">1, 223/234, d=0.678, g=0.639\n",
            ">1, 224/234, d=0.700, g=0.685\n",
            ">1, 225/234, d=0.677, g=0.771\n",
            ">1, 226/234, d=0.655, g=0.844\n",
            ">1, 227/234, d=0.690, g=0.945\n",
            ">1, 228/234, d=0.665, g=0.927\n",
            ">1, 229/234, d=0.670, g=0.876\n",
            ">1, 230/234, d=0.682, g=0.799\n",
            ">1, 231/234, d=0.679, g=0.768\n",
            ">1, 232/234, d=0.664, g=0.754\n",
            ">1, 233/234, d=0.672, g=0.714\n",
            ">1, 234/234, d=0.666, g=0.686\n",
            ">2, 1/234, d=0.665, g=0.698\n",
            ">2, 2/234, d=0.654, g=0.663\n",
            ">2, 3/234, d=0.643, g=0.669\n",
            ">2, 4/234, d=0.662, g=0.666\n",
            ">2, 5/234, d=0.660, g=0.675\n",
            ">2, 6/234, d=0.700, g=0.716\n",
            ">2, 7/234, d=0.647, g=0.740\n",
            ">2, 8/234, d=0.660, g=0.764\n",
            ">2, 9/234, d=0.669, g=0.803\n",
            ">2, 10/234, d=0.654, g=0.837\n",
            ">2, 11/234, d=0.671, g=0.816\n",
            ">2, 12/234, d=0.672, g=0.811\n",
            ">2, 13/234, d=0.671, g=0.810\n",
            ">2, 14/234, d=0.671, g=0.785\n",
            ">2, 15/234, d=0.678, g=0.736\n",
            ">2, 16/234, d=0.656, g=0.720\n",
            ">2, 17/234, d=0.679, g=0.688\n",
            ">2, 18/234, d=0.698, g=0.679\n",
            ">2, 19/234, d=0.702, g=0.664\n",
            ">2, 20/234, d=0.728, g=0.649\n",
            ">2, 21/234, d=0.699, g=0.669\n",
            ">2, 22/234, d=0.696, g=0.707\n",
            ">2, 23/234, d=0.715, g=0.735\n",
            ">2, 24/234, d=0.722, g=0.713\n",
            ">2, 25/234, d=0.709, g=0.730\n",
            ">2, 26/234, d=0.694, g=0.724\n",
            ">2, 27/234, d=0.712, g=0.723\n",
            ">2, 28/234, d=0.718, g=0.696\n",
            ">2, 29/234, d=0.716, g=0.693\n",
            ">2, 30/234, d=0.689, g=0.682\n",
            ">2, 31/234, d=0.712, g=0.685\n",
            ">2, 32/234, d=0.692, g=0.719\n",
            ">2, 33/234, d=0.692, g=0.723\n",
            ">2, 34/234, d=0.692, g=0.721\n",
            ">2, 35/234, d=0.680, g=0.745\n",
            ">2, 36/234, d=0.678, g=0.762\n",
            ">2, 37/234, d=0.672, g=0.750\n",
            ">2, 38/234, d=0.672, g=0.734\n",
            ">2, 39/234, d=0.658, g=0.728\n",
            ">2, 40/234, d=0.664, g=0.738\n",
            ">2, 41/234, d=0.662, g=0.740\n",
            ">2, 42/234, d=0.660, g=0.719\n",
            ">2, 43/234, d=0.665, g=0.723\n",
            ">2, 44/234, d=0.664, g=0.768\n",
            ">2, 45/234, d=0.649, g=0.769\n",
            ">2, 46/234, d=0.655, g=0.786\n",
            ">2, 47/234, d=0.648, g=0.814\n",
            ">2, 48/234, d=0.644, g=0.789\n",
            ">2, 49/234, d=0.668, g=0.796\n",
            ">2, 50/234, d=0.649, g=0.750\n",
            ">2, 51/234, d=0.659, g=0.734\n",
            ">2, 52/234, d=0.661, g=0.723\n",
            ">2, 53/234, d=0.692, g=0.702\n",
            ">2, 54/234, d=0.689, g=0.698\n",
            ">2, 55/234, d=0.693, g=0.686\n",
            ">2, 56/234, d=0.712, g=0.684\n",
            ">2, 57/234, d=0.707, g=0.684\n",
            ">2, 58/234, d=0.722, g=0.718\n",
            ">2, 59/234, d=0.715, g=0.734\n",
            ">2, 60/234, d=0.709, g=0.700\n",
            ">2, 61/234, d=0.706, g=0.691\n",
            ">2, 62/234, d=0.707, g=0.692\n",
            ">2, 63/234, d=0.709, g=0.670\n",
            ">2, 64/234, d=0.723, g=0.670\n",
            ">2, 65/234, d=0.719, g=0.674\n",
            ">2, 66/234, d=0.722, g=0.690\n",
            ">2, 67/234, d=0.722, g=0.708\n",
            ">2, 68/234, d=0.718, g=0.706\n",
            ">2, 69/234, d=0.694, g=0.712\n",
            ">2, 70/234, d=0.740, g=0.730\n",
            ">2, 71/234, d=0.714, g=0.723\n",
            ">2, 72/234, d=0.710, g=0.732\n",
            ">2, 73/234, d=0.702, g=0.733\n",
            ">2, 74/234, d=0.708, g=0.732\n",
            ">2, 75/234, d=0.710, g=0.724\n",
            ">2, 76/234, d=0.700, g=0.736\n",
            ">2, 77/234, d=0.703, g=0.719\n",
            ">2, 78/234, d=0.705, g=0.733\n",
            ">2, 79/234, d=0.692, g=0.733\n",
            ">2, 80/234, d=0.675, g=0.706\n",
            ">2, 81/234, d=0.688, g=0.731\n",
            ">2, 82/234, d=0.678, g=0.739\n",
            ">2, 83/234, d=0.668, g=0.751\n",
            ">2, 84/234, d=0.665, g=0.765\n",
            ">2, 85/234, d=0.674, g=0.755\n",
            ">2, 86/234, d=0.668, g=0.759\n",
            ">2, 87/234, d=0.669, g=0.768\n",
            ">2, 88/234, d=0.665, g=0.753\n",
            ">2, 89/234, d=0.676, g=0.753\n",
            ">2, 90/234, d=0.663, g=0.748\n",
            ">2, 91/234, d=0.668, g=0.754\n",
            ">2, 92/234, d=0.673, g=0.760\n",
            ">2, 93/234, d=0.677, g=0.751\n",
            ">2, 94/234, d=0.672, g=0.745\n",
            ">2, 95/234, d=0.657, g=0.749\n",
            ">2, 96/234, d=0.655, g=0.735\n",
            ">2, 97/234, d=0.661, g=0.749\n",
            ">2, 98/234, d=0.669, g=0.744\n",
            ">2, 99/234, d=0.684, g=0.748\n",
            ">2, 100/234, d=0.661, g=0.758\n",
            ">2, 101/234, d=0.664, g=0.740\n",
            ">2, 102/234, d=0.670, g=0.752\n",
            ">2, 103/234, d=0.668, g=0.757\n",
            ">2, 104/234, d=0.681, g=0.745\n",
            ">2, 105/234, d=0.685, g=0.744\n",
            ">2, 106/234, d=0.681, g=0.732\n",
            ">2, 107/234, d=0.672, g=0.723\n",
            ">2, 108/234, d=0.684, g=0.728\n",
            ">2, 109/234, d=0.664, g=0.759\n",
            ">2, 110/234, d=0.669, g=0.746\n",
            ">2, 111/234, d=0.680, g=0.780\n",
            ">2, 112/234, d=0.673, g=0.784\n",
            ">2, 113/234, d=0.661, g=0.763\n",
            ">2, 114/234, d=0.676, g=0.747\n",
            ">2, 115/234, d=0.649, g=0.765\n",
            ">2, 116/234, d=0.647, g=0.741\n",
            ">2, 117/234, d=0.651, g=0.739\n",
            ">2, 118/234, d=0.671, g=0.735\n",
            ">2, 119/234, d=0.653, g=0.737\n",
            ">2, 120/234, d=0.661, g=0.745\n",
            ">2, 121/234, d=0.656, g=0.747\n",
            ">2, 122/234, d=0.656, g=0.743\n",
            ">2, 123/234, d=0.661, g=0.736\n",
            ">2, 124/234, d=0.653, g=0.756\n",
            ">2, 125/234, d=0.647, g=0.745\n",
            ">2, 126/234, d=0.683, g=0.733\n",
            ">2, 127/234, d=0.679, g=0.730\n",
            ">2, 128/234, d=0.667, g=0.731\n",
            ">2, 129/234, d=0.675, g=0.744\n",
            ">2, 130/234, d=0.666, g=0.728\n",
            ">2, 131/234, d=0.674, g=0.743\n",
            ">2, 132/234, d=0.657, g=0.729\n",
            ">2, 133/234, d=0.675, g=0.712\n",
            ">2, 134/234, d=0.691, g=0.729\n",
            ">2, 135/234, d=0.688, g=0.693\n",
            ">2, 136/234, d=0.687, g=0.695\n",
            ">2, 137/234, d=0.689, g=0.699\n",
            ">2, 138/234, d=0.693, g=0.699\n",
            ">2, 139/234, d=0.701, g=0.701\n",
            ">2, 140/234, d=0.700, g=0.699\n",
            ">2, 141/234, d=0.707, g=0.704\n",
            ">2, 142/234, d=0.697, g=0.697\n",
            ">2, 143/234, d=0.713, g=0.697\n",
            ">2, 144/234, d=0.696, g=0.710\n",
            ">2, 145/234, d=0.710, g=0.689\n",
            ">2, 146/234, d=0.707, g=0.680\n",
            ">2, 147/234, d=0.711, g=0.699\n",
            ">2, 148/234, d=0.696, g=0.708\n",
            ">2, 149/234, d=0.700, g=0.712\n",
            ">2, 150/234, d=0.700, g=0.693\n",
            ">2, 151/234, d=0.703, g=0.687\n",
            ">2, 152/234, d=0.706, g=0.722\n",
            ">2, 153/234, d=0.700, g=0.725\n",
            ">2, 154/234, d=0.692, g=0.725\n",
            ">2, 155/234, d=0.685, g=0.735\n",
            ">2, 156/234, d=0.689, g=0.740\n",
            ">2, 157/234, d=0.673, g=0.752\n",
            ">2, 158/234, d=0.697, g=0.744\n",
            ">2, 159/234, d=0.669, g=0.740\n",
            ">2, 160/234, d=0.681, g=0.756\n",
            ">2, 161/234, d=0.677, g=0.737\n",
            ">2, 162/234, d=0.656, g=0.733\n",
            ">2, 163/234, d=0.677, g=0.744\n",
            ">2, 164/234, d=0.659, g=0.735\n",
            ">2, 165/234, d=0.672, g=0.754\n",
            ">2, 166/234, d=0.673, g=0.755\n",
            ">2, 167/234, d=0.667, g=0.755\n",
            ">2, 168/234, d=0.669, g=0.737\n",
            ">2, 169/234, d=0.662, g=0.749\n",
            ">2, 170/234, d=0.674, g=0.732\n",
            ">2, 171/234, d=0.680, g=0.734\n",
            ">2, 172/234, d=0.679, g=0.725\n",
            ">2, 173/234, d=0.686, g=0.719\n",
            ">2, 174/234, d=0.697, g=0.705\n",
            ">2, 175/234, d=0.686, g=0.724\n",
            ">2, 176/234, d=0.696, g=0.722\n",
            ">2, 177/234, d=0.689, g=0.739\n",
            ">2, 178/234, d=0.682, g=0.731\n",
            ">2, 179/234, d=0.681, g=0.723\n",
            ">2, 180/234, d=0.677, g=0.723\n",
            ">2, 181/234, d=0.701, g=0.723\n",
            ">2, 182/234, d=0.685, g=0.727\n",
            ">2, 183/234, d=0.692, g=0.719\n",
            ">2, 184/234, d=0.695, g=0.714\n",
            ">2, 185/234, d=0.685, g=0.723\n",
            ">2, 186/234, d=0.666, g=0.729\n",
            ">2, 187/234, d=0.689, g=0.719\n",
            ">2, 188/234, d=0.682, g=0.702\n",
            ">2, 189/234, d=0.682, g=0.736\n",
            ">2, 190/234, d=0.682, g=0.733\n",
            ">2, 191/234, d=0.677, g=0.724\n",
            ">2, 192/234, d=0.673, g=0.741\n",
            ">2, 193/234, d=0.686, g=0.719\n",
            ">2, 194/234, d=0.670, g=0.731\n",
            ">2, 195/234, d=0.678, g=0.740\n",
            ">2, 196/234, d=0.680, g=0.732\n",
            ">2, 197/234, d=0.672, g=0.736\n",
            ">2, 198/234, d=0.667, g=0.725\n",
            ">2, 199/234, d=0.661, g=0.744\n",
            ">2, 200/234, d=0.682, g=0.731\n",
            ">2, 201/234, d=0.668, g=0.742\n",
            ">2, 202/234, d=0.666, g=0.735\n",
            ">2, 203/234, d=0.674, g=0.736\n",
            ">2, 204/234, d=0.678, g=0.756\n",
            ">2, 205/234, d=0.684, g=0.751\n",
            ">2, 206/234, d=0.674, g=0.751\n",
            ">2, 207/234, d=0.680, g=0.736\n",
            ">2, 208/234, d=0.685, g=0.723\n",
            ">2, 209/234, d=0.678, g=0.711\n",
            ">2, 210/234, d=0.664, g=0.723\n",
            ">2, 211/234, d=0.671, g=0.744\n",
            ">2, 212/234, d=0.657, g=0.744\n",
            ">2, 213/234, d=0.677, g=0.754\n",
            ">2, 214/234, d=0.679, g=0.724\n",
            ">2, 215/234, d=0.676, g=0.726\n",
            ">2, 216/234, d=0.670, g=0.722\n",
            ">2, 217/234, d=0.677, g=0.728\n",
            ">2, 218/234, d=0.668, g=0.739\n",
            ">2, 219/234, d=0.674, g=0.726\n",
            ">2, 220/234, d=0.672, g=0.745\n",
            ">2, 221/234, d=0.692, g=0.733\n",
            ">2, 222/234, d=0.679, g=0.734\n",
            ">2, 223/234, d=0.668, g=0.743\n",
            ">2, 224/234, d=0.684, g=0.728\n",
            ">2, 225/234, d=0.676, g=0.735\n",
            ">2, 226/234, d=0.673, g=0.718\n",
            ">2, 227/234, d=0.687, g=0.743\n",
            ">2, 228/234, d=0.673, g=0.730\n",
            ">2, 229/234, d=0.685, g=0.737\n",
            ">2, 230/234, d=0.684, g=0.755\n",
            ">2, 231/234, d=0.685, g=0.738\n",
            ">2, 232/234, d=0.673, g=0.752\n",
            ">2, 233/234, d=0.669, g=0.745\n",
            ">2, 234/234, d=0.677, g=0.756\n",
            ">3, 1/234, d=0.681, g=0.739\n",
            ">3, 2/234, d=0.673, g=0.727\n",
            ">3, 3/234, d=0.670, g=0.738\n",
            ">3, 4/234, d=0.674, g=0.724\n",
            ">3, 5/234, d=0.679, g=0.743\n",
            ">3, 6/234, d=0.679, g=0.743\n",
            ">3, 7/234, d=0.681, g=0.748\n",
            ">3, 8/234, d=0.686, g=0.749\n",
            ">3, 9/234, d=0.677, g=0.760\n",
            ">3, 10/234, d=0.681, g=0.746\n",
            ">3, 11/234, d=0.668, g=0.746\n",
            ">3, 12/234, d=0.668, g=0.741\n",
            ">3, 13/234, d=0.679, g=0.715\n",
            ">3, 14/234, d=0.683, g=0.721\n",
            ">3, 15/234, d=0.665, g=0.722\n",
            ">3, 16/234, d=0.681, g=0.728\n",
            ">3, 17/234, d=0.659, g=0.724\n",
            ">3, 18/234, d=0.677, g=0.721\n",
            ">3, 19/234, d=0.674, g=0.726\n",
            ">3, 20/234, d=0.674, g=0.739\n",
            ">3, 21/234, d=0.677, g=0.732\n",
            ">3, 22/234, d=0.689, g=0.738\n",
            ">3, 23/234, d=0.677, g=0.729\n",
            ">3, 24/234, d=0.664, g=0.738\n",
            ">3, 25/234, d=0.679, g=0.731\n",
            ">3, 26/234, d=0.683, g=0.725\n",
            ">3, 27/234, d=0.667, g=0.740\n",
            ">3, 28/234, d=0.690, g=0.723\n",
            ">3, 29/234, d=0.676, g=0.735\n",
            ">3, 30/234, d=0.692, g=0.725\n",
            ">3, 31/234, d=0.673, g=0.724\n",
            ">3, 32/234, d=0.668, g=0.718\n",
            ">3, 33/234, d=0.677, g=0.737\n",
            ">3, 34/234, d=0.681, g=0.731\n",
            ">3, 35/234, d=0.678, g=0.726\n",
            ">3, 36/234, d=0.670, g=0.728\n",
            ">3, 37/234, d=0.671, g=0.725\n",
            ">3, 38/234, d=0.667, g=0.743\n",
            ">3, 39/234, d=0.683, g=0.729\n",
            ">3, 40/234, d=0.683, g=0.745\n",
            ">3, 41/234, d=0.698, g=0.731\n",
            ">3, 42/234, d=0.686, g=0.745\n",
            ">3, 43/234, d=0.673, g=0.738\n",
            ">3, 44/234, d=0.664, g=0.745\n",
            ">3, 45/234, d=0.671, g=0.720\n",
            ">3, 46/234, d=0.678, g=0.720\n",
            ">3, 47/234, d=0.666, g=0.734\n",
            ">3, 48/234, d=0.678, g=0.739\n",
            ">3, 49/234, d=0.678, g=0.735\n",
            ">3, 50/234, d=0.676, g=0.731\n",
            ">3, 51/234, d=0.671, g=0.740\n",
            ">3, 52/234, d=0.665, g=0.752\n",
            ">3, 53/234, d=0.667, g=0.732\n",
            ">3, 54/234, d=0.665, g=0.710\n",
            ">3, 55/234, d=0.675, g=0.727\n",
            ">3, 56/234, d=0.675, g=0.731\n",
            ">3, 57/234, d=0.671, g=0.710\n",
            ">3, 58/234, d=0.664, g=0.717\n",
            ">3, 59/234, d=0.683, g=0.726\n",
            ">3, 60/234, d=0.678, g=0.730\n",
            ">3, 61/234, d=0.679, g=0.744\n",
            ">3, 62/234, d=0.690, g=0.751\n",
            ">3, 63/234, d=0.675, g=0.729\n",
            ">3, 64/234, d=0.685, g=0.738\n",
            ">3, 65/234, d=0.676, g=0.725\n",
            ">3, 66/234, d=0.686, g=0.724\n",
            ">3, 67/234, d=0.695, g=0.708\n",
            ">3, 68/234, d=0.697, g=0.710\n",
            ">3, 69/234, d=0.690, g=0.709\n",
            ">3, 70/234, d=0.691, g=0.706\n",
            ">3, 71/234, d=0.676, g=0.717\n",
            ">3, 72/234, d=0.675, g=0.719\n",
            ">3, 73/234, d=0.692, g=0.726\n",
            ">3, 74/234, d=0.684, g=0.732\n",
            ">3, 75/234, d=0.690, g=0.716\n",
            ">3, 76/234, d=0.699, g=0.723\n",
            ">3, 77/234, d=0.680, g=0.729\n",
            ">3, 78/234, d=0.684, g=0.737\n",
            ">3, 79/234, d=0.691, g=0.724\n",
            ">3, 80/234, d=0.697, g=0.718\n",
            ">3, 81/234, d=0.677, g=0.708\n",
            ">3, 82/234, d=0.686, g=0.705\n",
            ">3, 83/234, d=0.676, g=0.698\n",
            ">3, 84/234, d=0.679, g=0.736\n",
            ">3, 85/234, d=0.675, g=0.735\n",
            ">3, 86/234, d=0.676, g=0.737\n",
            ">3, 87/234, d=0.662, g=0.726\n",
            ">3, 88/234, d=0.683, g=0.725\n",
            ">3, 89/234, d=0.681, g=0.734\n",
            ">3, 90/234, d=0.692, g=0.730\n",
            ">3, 91/234, d=0.691, g=0.734\n",
            ">3, 92/234, d=0.686, g=0.733\n",
            ">3, 93/234, d=0.684, g=0.725\n",
            ">3, 94/234, d=0.677, g=0.738\n",
            ">3, 95/234, d=0.682, g=0.731\n",
            ">3, 96/234, d=0.680, g=0.730\n",
            ">3, 97/234, d=0.687, g=0.732\n",
            ">3, 98/234, d=0.672, g=0.729\n",
            ">3, 99/234, d=0.682, g=0.736\n",
            ">3, 100/234, d=0.692, g=0.722\n",
            ">3, 101/234, d=0.696, g=0.722\n",
            ">3, 102/234, d=0.692, g=0.693\n",
            ">3, 103/234, d=0.695, g=0.706\n",
            ">3, 104/234, d=0.695, g=0.705\n",
            ">3, 105/234, d=0.694, g=0.710\n",
            ">3, 106/234, d=0.694, g=0.705\n",
            ">3, 107/234, d=0.699, g=0.732\n",
            ">3, 108/234, d=0.695, g=0.720\n",
            ">3, 109/234, d=0.686, g=0.720\n",
            ">3, 110/234, d=0.691, g=0.705\n",
            ">3, 111/234, d=0.694, g=0.699\n",
            ">3, 112/234, d=0.692, g=0.701\n",
            ">3, 113/234, d=0.697, g=0.706\n",
            ">3, 114/234, d=0.700, g=0.709\n",
            ">3, 115/234, d=0.704, g=0.709\n",
            ">3, 116/234, d=0.694, g=0.706\n",
            ">3, 117/234, d=0.686, g=0.706\n",
            ">3, 118/234, d=0.693, g=0.700\n",
            ">3, 119/234, d=0.694, g=0.718\n",
            ">3, 120/234, d=0.695, g=0.703\n",
            ">3, 121/234, d=0.694, g=0.718\n",
            ">3, 122/234, d=0.675, g=0.719\n",
            ">3, 123/234, d=0.684, g=0.699\n",
            ">3, 124/234, d=0.678, g=0.710\n",
            ">3, 125/234, d=0.692, g=0.712\n",
            ">3, 126/234, d=0.691, g=0.732\n",
            ">3, 127/234, d=0.684, g=0.718\n",
            ">3, 128/234, d=0.685, g=0.716\n",
            ">3, 129/234, d=0.680, g=0.719\n",
            ">3, 130/234, d=0.676, g=0.715\n",
            ">3, 131/234, d=0.692, g=0.725\n",
            ">3, 132/234, d=0.687, g=0.719\n",
            ">3, 133/234, d=0.689, g=0.728\n",
            ">3, 134/234, d=0.689, g=0.734\n",
            ">3, 135/234, d=0.690, g=0.732\n",
            ">3, 136/234, d=0.694, g=0.701\n",
            ">3, 137/234, d=0.696, g=0.701\n",
            ">3, 138/234, d=0.686, g=0.700\n",
            ">3, 139/234, d=0.672, g=0.691\n",
            ">3, 140/234, d=0.701, g=0.708\n",
            ">3, 141/234, d=0.697, g=0.707\n",
            ">3, 142/234, d=0.691, g=0.716\n",
            ">3, 143/234, d=0.686, g=0.720\n",
            ">3, 144/234, d=0.691, g=0.702\n",
            ">3, 145/234, d=0.681, g=0.697\n",
            ">3, 146/234, d=0.696, g=0.683\n",
            ">3, 147/234, d=0.700, g=0.689\n",
            ">3, 148/234, d=0.690, g=0.707\n",
            ">3, 149/234, d=0.700, g=0.712\n",
            ">3, 150/234, d=0.697, g=0.731\n",
            ">3, 151/234, d=0.692, g=0.720\n",
            ">3, 152/234, d=0.695, g=0.712\n",
            ">3, 153/234, d=0.697, g=0.714\n",
            ">3, 154/234, d=0.688, g=0.719\n",
            ">3, 155/234, d=0.699, g=0.699\n",
            ">3, 156/234, d=0.689, g=0.708\n",
            ">3, 157/234, d=0.684, g=0.719\n",
            ">3, 158/234, d=0.679, g=0.733\n",
            ">3, 159/234, d=0.695, g=0.726\n",
            ">3, 160/234, d=0.693, g=0.726\n",
            ">3, 161/234, d=0.690, g=0.725\n",
            ">3, 162/234, d=0.678, g=0.712\n",
            ">3, 163/234, d=0.694, g=0.719\n",
            ">3, 164/234, d=0.688, g=0.716\n",
            ">3, 165/234, d=0.683, g=0.705\n",
            ">3, 166/234, d=0.692, g=0.701\n",
            ">3, 167/234, d=0.678, g=0.709\n",
            ">3, 168/234, d=0.685, g=0.740\n",
            ">3, 169/234, d=0.681, g=0.727\n",
            ">3, 170/234, d=0.704, g=0.720\n",
            ">3, 171/234, d=0.701, g=0.710\n",
            ">3, 172/234, d=0.692, g=0.718\n",
            ">3, 173/234, d=0.685, g=0.690\n",
            ">3, 174/234, d=0.696, g=0.703\n",
            ">3, 175/234, d=0.703, g=0.720\n",
            ">3, 176/234, d=0.680, g=0.734\n",
            ">3, 177/234, d=0.700, g=0.729\n",
            ">3, 178/234, d=0.697, g=0.727\n",
            ">3, 179/234, d=0.708, g=0.716\n",
            ">3, 180/234, d=0.698, g=0.700\n",
            ">3, 181/234, d=0.703, g=0.701\n",
            ">3, 182/234, d=0.688, g=0.688\n",
            ">3, 183/234, d=0.695, g=0.687\n",
            ">3, 184/234, d=0.701, g=0.691\n",
            ">3, 185/234, d=0.708, g=0.701\n",
            ">3, 186/234, d=0.695, g=0.704\n",
            ">3, 187/234, d=0.694, g=0.701\n",
            ">3, 188/234, d=0.694, g=0.702\n",
            ">3, 189/234, d=0.691, g=0.701\n",
            ">3, 190/234, d=0.702, g=0.680\n",
            ">3, 191/234, d=0.702, g=0.692\n",
            ">3, 192/234, d=0.694, g=0.689\n",
            ">3, 193/234, d=0.705, g=0.692\n",
            ">3, 194/234, d=0.698, g=0.699\n",
            ">3, 195/234, d=0.699, g=0.719\n",
            ">3, 196/234, d=0.706, g=0.707\n",
            ">3, 197/234, d=0.699, g=0.731\n",
            ">3, 198/234, d=0.700, g=0.718\n",
            ">3, 199/234, d=0.698, g=0.724\n",
            ">3, 200/234, d=0.680, g=0.707\n",
            ">3, 201/234, d=0.689, g=0.715\n",
            ">3, 202/234, d=0.692, g=0.722\n",
            ">3, 203/234, d=0.680, g=0.729\n",
            ">3, 204/234, d=0.685, g=0.727\n",
            ">3, 205/234, d=0.695, g=0.712\n",
            ">3, 206/234, d=0.677, g=0.725\n",
            ">3, 207/234, d=0.684, g=0.716\n",
            ">3, 208/234, d=0.698, g=0.720\n",
            ">3, 209/234, d=0.687, g=0.710\n",
            ">3, 210/234, d=0.702, g=0.707\n",
            ">3, 211/234, d=0.689, g=0.696\n",
            ">3, 212/234, d=0.685, g=0.711\n",
            ">3, 213/234, d=0.691, g=0.708\n",
            ">3, 214/234, d=0.701, g=0.724\n",
            ">3, 215/234, d=0.693, g=0.726\n",
            ">3, 216/234, d=0.697, g=0.721\n",
            ">3, 217/234, d=0.705, g=0.717\n",
            ">3, 218/234, d=0.693, g=0.712\n",
            ">3, 219/234, d=0.686, g=0.707\n",
            ">3, 220/234, d=0.700, g=0.687\n",
            ">3, 221/234, d=0.694, g=0.686\n",
            ">3, 222/234, d=0.704, g=0.695\n",
            ">3, 223/234, d=0.685, g=0.713\n",
            ">3, 224/234, d=0.698, g=0.719\n",
            ">3, 225/234, d=0.710, g=0.712\n",
            ">3, 226/234, d=0.697, g=0.715\n",
            ">3, 227/234, d=0.688, g=0.707\n",
            ">3, 228/234, d=0.691, g=0.722\n",
            ">3, 229/234, d=0.700, g=0.707\n",
            ">3, 230/234, d=0.692, g=0.692\n",
            ">3, 231/234, d=0.701, g=0.695\n",
            ">3, 232/234, d=0.704, g=0.703\n",
            ">3, 233/234, d=0.711, g=0.692\n",
            ">3, 234/234, d=0.691, g=0.718\n",
            ">4, 1/234, d=0.693, g=0.719\n",
            ">4, 2/234, d=0.691, g=0.703\n",
            ">4, 3/234, d=0.696, g=0.709\n",
            ">4, 4/234, d=0.696, g=0.707\n",
            ">4, 5/234, d=0.685, g=0.721\n",
            ">4, 6/234, d=0.697, g=0.710\n",
            ">4, 7/234, d=0.687, g=0.730\n",
            ">4, 8/234, d=0.684, g=0.727\n",
            ">4, 9/234, d=0.703, g=0.711\n",
            ">4, 10/234, d=0.686, g=0.721\n",
            ">4, 11/234, d=0.697, g=0.706\n",
            ">4, 12/234, d=0.686, g=0.713\n",
            ">4, 13/234, d=0.699, g=0.699\n",
            ">4, 14/234, d=0.708, g=0.700\n",
            ">4, 15/234, d=0.701, g=0.712\n",
            ">4, 16/234, d=0.689, g=0.716\n",
            ">4, 17/234, d=0.689, g=0.700\n",
            ">4, 18/234, d=0.692, g=0.695\n",
            ">4, 19/234, d=0.700, g=0.691\n",
            ">4, 20/234, d=0.713, g=0.687\n",
            ">4, 21/234, d=0.702, g=0.696\n",
            ">4, 22/234, d=0.703, g=0.687\n",
            ">4, 23/234, d=0.705, g=0.685\n",
            ">4, 24/234, d=0.697, g=0.692\n",
            ">4, 25/234, d=0.696, g=0.692\n",
            ">4, 26/234, d=0.708, g=0.697\n",
            ">4, 27/234, d=0.715, g=0.689\n",
            ">4, 28/234, d=0.711, g=0.700\n",
            ">4, 29/234, d=0.713, g=0.702\n",
            ">4, 30/234, d=0.702, g=0.694\n",
            ">4, 31/234, d=0.694, g=0.685\n",
            ">4, 32/234, d=0.693, g=0.693\n",
            ">4, 33/234, d=0.698, g=0.700\n",
            ">4, 34/234, d=0.692, g=0.696\n",
            ">4, 35/234, d=0.699, g=0.698\n",
            ">4, 36/234, d=0.704, g=0.708\n",
            ">4, 37/234, d=0.690, g=0.722\n",
            ">4, 38/234, d=0.690, g=0.720\n",
            ">4, 39/234, d=0.688, g=0.717\n",
            ">4, 40/234, d=0.704, g=0.715\n",
            ">4, 41/234, d=0.687, g=0.713\n",
            ">4, 42/234, d=0.692, g=0.709\n",
            ">4, 43/234, d=0.695, g=0.706\n",
            ">4, 44/234, d=0.695, g=0.703\n",
            ">4, 45/234, d=0.682, g=0.696\n",
            ">4, 46/234, d=0.685, g=0.717\n",
            ">4, 47/234, d=0.692, g=0.713\n",
            ">4, 48/234, d=0.699, g=0.711\n",
            ">4, 49/234, d=0.684, g=0.720\n",
            ">4, 50/234, d=0.696, g=0.712\n",
            ">4, 51/234, d=0.694, g=0.714\n",
            ">4, 52/234, d=0.682, g=0.719\n",
            ">4, 53/234, d=0.697, g=0.714\n",
            ">4, 54/234, d=0.705, g=0.704\n",
            ">4, 55/234, d=0.685, g=0.707\n",
            ">4, 56/234, d=0.696, g=0.700\n",
            ">4, 57/234, d=0.682, g=0.702\n",
            ">4, 58/234, d=0.691, g=0.710\n",
            ">4, 59/234, d=0.680, g=0.721\n",
            ">4, 60/234, d=0.690, g=0.728\n",
            ">4, 61/234, d=0.695, g=0.727\n",
            ">4, 62/234, d=0.691, g=0.726\n",
            ">4, 63/234, d=0.686, g=0.727\n",
            ">4, 64/234, d=0.684, g=0.711\n",
            ">4, 65/234, d=0.685, g=0.713\n",
            ">4, 66/234, d=0.698, g=0.712\n",
            ">4, 67/234, d=0.699, g=0.714\n",
            ">4, 68/234, d=0.690, g=0.715\n",
            ">4, 69/234, d=0.691, g=0.730\n",
            ">4, 70/234, d=0.683, g=0.726\n",
            ">4, 71/234, d=0.690, g=0.723\n",
            ">4, 72/234, d=0.684, g=0.730\n",
            ">4, 73/234, d=0.691, g=0.703\n",
            ">4, 74/234, d=0.685, g=0.700\n",
            ">4, 75/234, d=0.683, g=0.695\n",
            ">4, 76/234, d=0.691, g=0.698\n",
            ">4, 77/234, d=0.685, g=0.703\n",
            ">4, 78/234, d=0.689, g=0.707\n",
            ">4, 79/234, d=0.696, g=0.717\n",
            ">4, 80/234, d=0.690, g=0.735\n",
            ">4, 81/234, d=0.689, g=0.712\n",
            ">4, 82/234, d=0.701, g=0.711\n",
            ">4, 83/234, d=0.701, g=0.692\n",
            ">4, 84/234, d=0.704, g=0.691\n",
            ">4, 85/234, d=0.690, g=0.680\n",
            ">4, 86/234, d=0.700, g=0.700\n",
            ">4, 87/234, d=0.693, g=0.693\n",
            ">4, 88/234, d=0.697, g=0.711\n",
            ">4, 89/234, d=0.702, g=0.714\n",
            ">4, 90/234, d=0.704, g=0.705\n",
            ">4, 91/234, d=0.702, g=0.702\n",
            ">4, 92/234, d=0.699, g=0.707\n",
            ">4, 93/234, d=0.709, g=0.702\n",
            ">4, 94/234, d=0.703, g=0.702\n",
            ">4, 95/234, d=0.712, g=0.696\n",
            ">4, 96/234, d=0.709, g=0.684\n",
            ">4, 97/234, d=0.700, g=0.689\n",
            ">4, 98/234, d=0.707, g=0.692\n",
            ">4, 99/234, d=0.706, g=0.698\n",
            ">4, 100/234, d=0.703, g=0.707\n",
            ">4, 101/234, d=0.694, g=0.698\n",
            ">4, 102/234, d=0.705, g=0.712\n",
            ">4, 103/234, d=0.718, g=0.685\n",
            ">4, 104/234, d=0.708, g=0.691\n",
            ">4, 105/234, d=0.695, g=0.697\n",
            ">4, 106/234, d=0.715, g=0.699\n",
            ">4, 107/234, d=0.697, g=0.707\n",
            ">4, 108/234, d=0.699, g=0.721\n",
            ">4, 109/234, d=0.697, g=0.714\n",
            ">4, 110/234, d=0.704, g=0.725\n",
            ">4, 111/234, d=0.708, g=0.713\n",
            ">4, 112/234, d=0.704, g=0.722\n",
            ">4, 113/234, d=0.695, g=0.712\n",
            ">4, 114/234, d=0.693, g=0.700\n",
            ">4, 115/234, d=0.691, g=0.682\n",
            ">4, 116/234, d=0.709, g=0.681\n",
            ">4, 117/234, d=0.701, g=0.696\n",
            ">4, 118/234, d=0.687, g=0.702\n",
            ">4, 119/234, d=0.693, g=0.725\n",
            ">4, 120/234, d=0.691, g=0.732\n",
            ">4, 121/234, d=0.684, g=0.729\n",
            ">4, 122/234, d=0.702, g=0.724\n",
            ">4, 123/234, d=0.692, g=0.714\n",
            ">4, 124/234, d=0.685, g=0.685\n",
            ">4, 125/234, d=0.695, g=0.688\n",
            ">4, 126/234, d=0.690, g=0.710\n",
            ">4, 127/234, d=0.696, g=0.693\n",
            ">4, 128/234, d=0.697, g=0.697\n",
            ">4, 129/234, d=0.687, g=0.721\n",
            ">4, 130/234, d=0.701, g=0.715\n",
            ">4, 131/234, d=0.703, g=0.719\n",
            ">4, 132/234, d=0.691, g=0.702\n",
            ">4, 133/234, d=0.686, g=0.711\n",
            ">4, 134/234, d=0.691, g=0.717\n",
            ">4, 135/234, d=0.691, g=0.712\n",
            ">4, 136/234, d=0.693, g=0.713\n",
            ">4, 137/234, d=0.686, g=0.701\n",
            ">4, 138/234, d=0.697, g=0.703\n",
            ">4, 139/234, d=0.682, g=0.701\n",
            ">4, 140/234, d=0.695, g=0.709\n",
            ">4, 141/234, d=0.686, g=0.716\n",
            ">4, 142/234, d=0.693, g=0.725\n",
            ">4, 143/234, d=0.695, g=0.724\n",
            ">4, 144/234, d=0.692, g=0.719\n",
            ">4, 145/234, d=0.692, g=0.710\n",
            ">4, 146/234, d=0.691, g=0.717\n",
            ">4, 147/234, d=0.689, g=0.720\n",
            ">4, 148/234, d=0.690, g=0.726\n",
            ">4, 149/234, d=0.680, g=0.721\n",
            ">4, 150/234, d=0.690, g=0.744\n",
            ">4, 151/234, d=0.684, g=0.743\n",
            ">4, 152/234, d=0.678, g=0.731\n",
            ">4, 153/234, d=0.682, g=0.738\n",
            ">4, 154/234, d=0.687, g=0.723\n",
            ">4, 155/234, d=0.677, g=0.709\n",
            ">4, 156/234, d=0.688, g=0.703\n",
            ">4, 157/234, d=0.686, g=0.699\n",
            ">4, 158/234, d=0.686, g=0.704\n",
            ">4, 159/234, d=0.677, g=0.715\n",
            ">4, 160/234, d=0.684, g=0.729\n",
            ">4, 161/234, d=0.681, g=0.727\n",
            ">4, 162/234, d=0.694, g=0.732\n",
            ">4, 163/234, d=0.684, g=0.724\n",
            ">4, 164/234, d=0.684, g=0.721\n",
            ">4, 165/234, d=0.682, g=0.716\n",
            ">4, 166/234, d=0.689, g=0.710\n",
            ">4, 167/234, d=0.697, g=0.696\n",
            ">4, 168/234, d=0.697, g=0.680\n",
            ">4, 169/234, d=0.700, g=0.704\n",
            ">4, 170/234, d=0.696, g=0.713\n",
            ">4, 171/234, d=0.703, g=0.719\n",
            ">4, 172/234, d=0.697, g=0.718\n",
            ">4, 173/234, d=0.687, g=0.702\n",
            ">4, 174/234, d=0.716, g=0.702\n",
            ">4, 175/234, d=0.702, g=0.699\n",
            ">4, 176/234, d=0.716, g=0.701\n",
            ">4, 177/234, d=0.695, g=0.675\n",
            ">4, 178/234, d=0.706, g=0.692\n",
            ">4, 179/234, d=0.700, g=0.702\n",
            ">4, 180/234, d=0.703, g=0.701\n",
            ">4, 181/234, d=0.700, g=0.709\n",
            ">4, 182/234, d=0.707, g=0.705\n",
            ">4, 183/234, d=0.698, g=0.715\n",
            ">4, 184/234, d=0.709, g=0.714\n",
            ">4, 185/234, d=0.719, g=0.696\n",
            ">4, 186/234, d=0.691, g=0.695\n",
            ">4, 187/234, d=0.695, g=0.679\n",
            ">4, 188/234, d=0.700, g=0.691\n",
            ">4, 189/234, d=0.704, g=0.684\n",
            ">4, 190/234, d=0.705, g=0.692\n",
            ">4, 191/234, d=0.708, g=0.718\n",
            ">4, 192/234, d=0.698, g=0.722\n",
            ">4, 193/234, d=0.699, g=0.721\n",
            ">4, 194/234, d=0.695, g=0.735\n",
            ">4, 195/234, d=0.701, g=0.723\n",
            ">4, 196/234, d=0.683, g=0.720\n",
            ">4, 197/234, d=0.680, g=0.706\n",
            ">4, 198/234, d=0.687, g=0.695\n",
            ">4, 199/234, d=0.692, g=0.691\n",
            ">4, 200/234, d=0.697, g=0.688\n",
            ">4, 201/234, d=0.692, g=0.705\n",
            ">4, 202/234, d=0.687, g=0.722\n",
            ">4, 203/234, d=0.694, g=0.721\n",
            ">4, 204/234, d=0.698, g=0.724\n",
            ">4, 205/234, d=0.681, g=0.730\n",
            ">4, 206/234, d=0.692, g=0.736\n",
            ">4, 207/234, d=0.692, g=0.727\n",
            ">4, 208/234, d=0.686, g=0.717\n",
            ">4, 209/234, d=0.687, g=0.690\n",
            ">4, 210/234, d=0.682, g=0.697\n",
            ">4, 211/234, d=0.679, g=0.695\n",
            ">4, 212/234, d=0.680, g=0.700\n",
            ">4, 213/234, d=0.686, g=0.721\n",
            ">4, 214/234, d=0.693, g=0.734\n",
            ">4, 215/234, d=0.680, g=0.746\n",
            ">4, 216/234, d=0.681, g=0.743\n",
            ">4, 217/234, d=0.681, g=0.741\n",
            ">4, 218/234, d=0.687, g=0.715\n",
            ">4, 219/234, d=0.679, g=0.697\n",
            ">4, 220/234, d=0.681, g=0.700\n",
            ">4, 221/234, d=0.679, g=0.693\n",
            ">4, 222/234, d=0.682, g=0.698\n",
            ">4, 223/234, d=0.688, g=0.705\n",
            ">4, 224/234, d=0.689, g=0.712\n",
            ">4, 225/234, d=0.688, g=0.734\n",
            ">4, 226/234, d=0.691, g=0.740\n",
            ">4, 227/234, d=0.688, g=0.740\n",
            ">4, 228/234, d=0.689, g=0.725\n",
            ">4, 229/234, d=0.676, g=0.714\n",
            ">4, 230/234, d=0.681, g=0.704\n",
            ">4, 231/234, d=0.690, g=0.705\n",
            ">4, 232/234, d=0.685, g=0.692\n",
            ">4, 233/234, d=0.678, g=0.691\n",
            ">4, 234/234, d=0.690, g=0.690\n",
            ">5, 1/234, d=0.690, g=0.690\n",
            ">5, 2/234, d=0.677, g=0.712\n",
            ">5, 3/234, d=0.697, g=0.727\n",
            ">5, 4/234, d=0.691, g=0.741\n",
            ">5, 5/234, d=0.694, g=0.735\n",
            ">5, 6/234, d=0.693, g=0.736\n",
            ">5, 7/234, d=0.694, g=0.706\n",
            ">5, 8/234, d=0.691, g=0.702\n",
            ">5, 9/234, d=0.692, g=0.689\n",
            ">5, 10/234, d=0.691, g=0.684\n",
            ">5, 11/234, d=0.702, g=0.670\n",
            ">5, 12/234, d=0.703, g=0.671\n",
            ">5, 13/234, d=0.702, g=0.699\n",
            ">5, 14/234, d=0.697, g=0.713\n",
            ">5, 15/234, d=0.702, g=0.711\n",
            ">5, 16/234, d=0.703, g=0.722\n",
            ">5, 17/234, d=0.706, g=0.717\n",
            ">5, 18/234, d=0.698, g=0.712\n",
            ">5, 19/234, d=0.704, g=0.697\n",
            ">5, 20/234, d=0.706, g=0.695\n",
            ">5, 21/234, d=0.702, g=0.680\n",
            ">5, 22/234, d=0.692, g=0.674\n",
            ">5, 23/234, d=0.696, g=0.682\n",
            ">5, 24/234, d=0.698, g=0.701\n",
            ">5, 25/234, d=0.693, g=0.713\n",
            ">5, 26/234, d=0.701, g=0.740\n",
            ">5, 27/234, d=0.698, g=0.742\n",
            ">5, 28/234, d=0.689, g=0.732\n",
            ">5, 29/234, d=0.694, g=0.736\n",
            ">5, 30/234, d=0.696, g=0.719\n",
            ">5, 31/234, d=0.688, g=0.719\n",
            ">5, 32/234, d=0.683, g=0.712\n",
            ">5, 33/234, d=0.682, g=0.694\n",
            ">5, 34/234, d=0.682, g=0.700\n",
            ">5, 35/234, d=0.692, g=0.706\n",
            ">5, 36/234, d=0.685, g=0.718\n",
            ">5, 37/234, d=0.679, g=0.708\n",
            ">5, 38/234, d=0.680, g=0.720\n",
            ">5, 39/234, d=0.680, g=0.730\n",
            ">5, 40/234, d=0.678, g=0.746\n",
            ">5, 41/234, d=0.680, g=0.761\n",
            ">5, 42/234, d=0.682, g=0.752\n",
            ">5, 43/234, d=0.680, g=0.758\n",
            ">5, 44/234, d=0.684, g=0.751\n",
            ">5, 45/234, d=0.679, g=0.732\n",
            ">5, 46/234, d=0.677, g=0.713\n",
            ">5, 47/234, d=0.673, g=0.690\n",
            ">5, 48/234, d=0.679, g=0.682\n",
            ">5, 49/234, d=0.677, g=0.684\n",
            ">5, 50/234, d=0.675, g=0.662\n",
            ">5, 51/234, d=0.678, g=0.660\n",
            ">5, 52/234, d=0.686, g=0.679\n",
            ">5, 53/234, d=0.689, g=0.714\n",
            ">5, 54/234, d=0.685, g=0.774\n",
            ">5, 55/234, d=0.670, g=0.837\n",
            ">5, 56/234, d=0.680, g=0.876\n",
            ">5, 57/234, d=0.677, g=0.857\n",
            ">5, 58/234, d=0.697, g=0.783\n",
            ">5, 59/234, d=0.712, g=0.724\n",
            ">5, 60/234, d=0.701, g=0.683\n",
            ">5, 61/234, d=0.697, g=0.659\n",
            ">5, 62/234, d=0.680, g=0.657\n",
            ">5, 63/234, d=0.664, g=0.634\n",
            ">5, 64/234, d=0.666, g=0.608\n",
            ">5, 65/234, d=0.702, g=0.576\n",
            ">5, 66/234, d=0.742, g=0.574\n",
            ">5, 67/234, d=0.737, g=0.689\n",
            ">5, 68/234, d=0.717, g=0.838\n",
            ">5, 69/234, d=0.688, g=0.990\n",
            ">5, 70/234, d=0.671, g=1.052\n",
            ">5, 71/234, d=0.681, g=0.985\n",
            ">5, 72/234, d=0.691, g=0.869\n",
            ">5, 73/234, d=0.714, g=0.751\n",
            ">5, 74/234, d=0.725, g=0.697\n",
            ">5, 75/234, d=0.710, g=0.674\n",
            ">5, 76/234, d=0.681, g=0.672\n",
            ">5, 77/234, d=0.671, g=0.663\n",
            ">5, 78/234, d=0.649, g=0.644\n",
            ">5, 79/234, d=0.658, g=0.611\n",
            ">5, 80/234, d=0.692, g=0.571\n",
            ">5, 81/234, d=0.727, g=0.574\n",
            ">5, 82/234, d=0.744, g=0.635\n",
            ">5, 83/234, d=0.726, g=0.765\n",
            ">5, 84/234, d=0.681, g=0.907\n",
            ">5, 85/234, d=0.678, g=0.994\n",
            ">5, 86/234, d=0.670, g=0.970\n",
            ">5, 87/234, d=0.679, g=0.913\n",
            ">5, 88/234, d=0.694, g=0.824\n",
            ">5, 89/234, d=0.709, g=0.762\n",
            ">5, 90/234, d=0.698, g=0.716\n",
            ">5, 91/234, d=0.687, g=0.694\n",
            ">5, 92/234, d=0.670, g=0.672\n",
            ">5, 93/234, d=0.669, g=0.658\n",
            ">5, 94/234, d=0.671, g=0.639\n",
            ">5, 95/234, d=0.683, g=0.626\n",
            ">5, 96/234, d=0.698, g=0.617\n",
            ">5, 97/234, d=0.707, g=0.631\n",
            ">5, 98/234, d=0.699, g=0.689\n",
            ">5, 99/234, d=0.694, g=0.768\n",
            ">5, 100/234, d=0.690, g=0.813\n",
            ">5, 101/234, d=0.678, g=0.864\n",
            ">5, 102/234, d=0.683, g=0.857\n",
            ">5, 103/234, d=0.690, g=0.826\n",
            ">5, 104/234, d=0.696, g=0.780\n",
            ">5, 105/234, d=0.694, g=0.740\n",
            ">5, 106/234, d=0.702, g=0.709\n",
            ">5, 107/234, d=0.690, g=0.692\n",
            ">5, 108/234, d=0.695, g=0.659\n",
            ">5, 109/234, d=0.691, g=0.663\n",
            ">5, 110/234, d=0.689, g=0.645\n",
            ">5, 111/234, d=0.701, g=0.647\n",
            ">5, 112/234, d=0.695, g=0.651\n",
            ">5, 113/234, d=0.703, g=0.665\n",
            ">5, 114/234, d=0.704, g=0.680\n",
            ">5, 115/234, d=0.693, g=0.722\n",
            ">5, 116/234, d=0.694, g=0.733\n",
            ">5, 117/234, d=0.697, g=0.749\n",
            ">5, 118/234, d=0.698, g=0.760\n",
            ">5, 119/234, d=0.693, g=0.752\n",
            ">5, 120/234, d=0.692, g=0.737\n",
            ">5, 121/234, d=0.703, g=0.728\n",
            ">5, 122/234, d=0.697, g=0.717\n",
            ">5, 123/234, d=0.694, g=0.699\n",
            ">5, 124/234, d=0.687, g=0.693\n",
            ">5, 125/234, d=0.692, g=0.677\n",
            ">5, 126/234, d=0.693, g=0.680\n",
            ">5, 127/234, d=0.686, g=0.672\n",
            ">5, 128/234, d=0.698, g=0.674\n",
            ">5, 129/234, d=0.683, g=0.682\n",
            ">5, 130/234, d=0.696, g=0.694\n",
            ">5, 131/234, d=0.694, g=0.704\n",
            ">5, 132/234, d=0.687, g=0.712\n",
            ">5, 133/234, d=0.692, g=0.739\n",
            ">5, 134/234, d=0.690, g=0.739\n",
            ">5, 135/234, d=0.695, g=0.748\n",
            ">5, 136/234, d=0.693, g=0.742\n",
            ">5, 137/234, d=0.697, g=0.740\n",
            ">5, 138/234, d=0.691, g=0.722\n",
            ">5, 139/234, d=0.683, g=0.714\n",
            ">5, 140/234, d=0.692, g=0.706\n",
            ">5, 141/234, d=0.676, g=0.703\n",
            ">5, 142/234, d=0.690, g=0.703\n",
            ">5, 143/234, d=0.687, g=0.698\n",
            ">5, 144/234, d=0.685, g=0.697\n",
            ">5, 145/234, d=0.680, g=0.709\n",
            ">5, 146/234, d=0.683, g=0.714\n",
            ">5, 147/234, d=0.691, g=0.715\n",
            ">5, 148/234, d=0.687, g=0.722\n",
            ">5, 149/234, d=0.696, g=0.736\n",
            ">5, 150/234, d=0.682, g=0.725\n",
            ">5, 151/234, d=0.680, g=0.722\n",
            ">5, 152/234, d=0.684, g=0.737\n",
            ">5, 153/234, d=0.691, g=0.731\n",
            ">5, 154/234, d=0.689, g=0.714\n",
            ">5, 155/234, d=0.687, g=0.719\n",
            ">5, 156/234, d=0.688, g=0.700\n",
            ">5, 157/234, d=0.686, g=0.703\n",
            ">5, 158/234, d=0.685, g=0.701\n",
            ">5, 159/234, d=0.676, g=0.699\n",
            ">5, 160/234, d=0.688, g=0.708\n",
            ">5, 161/234, d=0.685, g=0.703\n",
            ">5, 162/234, d=0.690, g=0.718\n",
            ">5, 163/234, d=0.676, g=0.736\n",
            ">5, 164/234, d=0.680, g=0.737\n",
            ">5, 165/234, d=0.687, g=0.751\n",
            ">5, 166/234, d=0.695, g=0.744\n",
            ">5, 167/234, d=0.679, g=0.745\n",
            ">5, 168/234, d=0.679, g=0.732\n",
            ">5, 169/234, d=0.685, g=0.721\n",
            ">5, 170/234, d=0.685, g=0.705\n",
            ">5, 171/234, d=0.682, g=0.696\n",
            ">5, 172/234, d=0.680, g=0.683\n",
            ">5, 173/234, d=0.688, g=0.687\n",
            ">5, 174/234, d=0.676, g=0.702\n",
            ">5, 175/234, d=0.692, g=0.684\n",
            ">5, 176/234, d=0.693, g=0.700\n",
            ">5, 177/234, d=0.692, g=0.734\n",
            ">5, 178/234, d=0.687, g=0.738\n",
            ">5, 179/234, d=0.687, g=0.735\n",
            ">5, 180/234, d=0.697, g=0.725\n",
            ">5, 181/234, d=0.694, g=0.713\n",
            ">5, 182/234, d=0.681, g=0.717\n",
            ">5, 183/234, d=0.692, g=0.701\n",
            ">5, 184/234, d=0.695, g=0.698\n",
            ">5, 185/234, d=0.684, g=0.684\n",
            ">5, 186/234, d=0.686, g=0.685\n",
            ">5, 187/234, d=0.694, g=0.679\n",
            ">5, 188/234, d=0.694, g=0.680\n",
            ">5, 189/234, d=0.694, g=0.683\n",
            ">5, 190/234, d=0.700, g=0.697\n",
            ">5, 191/234, d=0.693, g=0.694\n",
            ">5, 192/234, d=0.690, g=0.715\n",
            ">5, 193/234, d=0.695, g=0.713\n",
            ">5, 194/234, d=0.706, g=0.707\n",
            ">5, 195/234, d=0.701, g=0.720\n",
            ">5, 196/234, d=0.716, g=0.716\n",
            ">5, 197/234, d=0.706, g=0.695\n",
            ">5, 198/234, d=0.695, g=0.699\n",
            ">5, 199/234, d=0.707, g=0.694\n",
            ">5, 200/234, d=0.709, g=0.687\n",
            ">5, 201/234, d=0.701, g=0.683\n",
            ">5, 202/234, d=0.709, g=0.679\n",
            ">5, 203/234, d=0.698, g=0.670\n",
            ">5, 204/234, d=0.709, g=0.683\n",
            ">5, 205/234, d=0.708, g=0.698\n",
            ">5, 206/234, d=0.699, g=0.710\n",
            ">5, 207/234, d=0.695, g=0.731\n",
            ">5, 208/234, d=0.686, g=0.735\n",
            ">5, 209/234, d=0.686, g=0.758\n",
            ">5, 210/234, d=0.695, g=0.747\n",
            ">5, 211/234, d=0.693, g=0.756\n",
            ">5, 212/234, d=0.687, g=0.749\n",
            ">5, 213/234, d=0.689, g=0.740\n",
            ">5, 214/234, d=0.689, g=0.721\n",
            ">5, 215/234, d=0.680, g=0.713\n",
            ">5, 216/234, d=0.682, g=0.716\n",
            ">5, 217/234, d=0.678, g=0.712\n",
            ">5, 218/234, d=0.669, g=0.716\n",
            ">5, 219/234, d=0.680, g=0.719\n",
            ">5, 220/234, d=0.679, g=0.731\n",
            ">5, 221/234, d=0.668, g=0.758\n",
            ">5, 222/234, d=0.675, g=0.786\n",
            ">5, 223/234, d=0.665, g=0.806\n",
            ">5, 224/234, d=0.661, g=0.829\n",
            ">5, 225/234, d=0.666, g=0.839\n",
            ">5, 226/234, d=0.664, g=0.809\n",
            ">5, 227/234, d=0.684, g=0.776\n",
            ">5, 228/234, d=0.680, g=0.749\n",
            ">5, 229/234, d=0.675, g=0.716\n",
            ">5, 230/234, d=0.673, g=0.687\n",
            ">5, 231/234, d=0.664, g=0.680\n",
            ">5, 232/234, d=0.660, g=0.673\n",
            ">5, 233/234, d=0.654, g=0.666\n",
            ">5, 234/234, d=0.669, g=0.654\n",
            ">6, 1/234, d=0.676, g=0.655\n",
            ">6, 2/234, d=0.681, g=0.679\n",
            ">6, 3/234, d=0.701, g=0.710\n",
            ">6, 4/234, d=0.685, g=0.766\n",
            ">6, 5/234, d=0.674, g=0.826\n",
            ">6, 6/234, d=0.671, g=0.878\n",
            ">6, 7/234, d=0.674, g=0.866\n",
            ">6, 8/234, d=0.688, g=0.825\n",
            ">6, 9/234, d=0.699, g=0.766\n",
            ">6, 10/234, d=0.698, g=0.728\n",
            ">6, 11/234, d=0.699, g=0.686\n",
            ">6, 12/234, d=0.700, g=0.666\n",
            ">6, 13/234, d=0.684, g=0.649\n",
            ">6, 14/234, d=0.682, g=0.638\n",
            ">6, 15/234, d=0.690, g=0.611\n",
            ">6, 16/234, d=0.684, g=0.592\n",
            ">6, 17/234, d=0.703, g=0.579\n",
            ">6, 18/234, d=0.723, g=0.592\n",
            ">6, 19/234, d=0.724, g=0.638\n",
            ">6, 20/234, d=0.714, g=0.724\n",
            ">6, 21/234, d=0.690, g=0.820\n",
            ">6, 22/234, d=0.690, g=0.852\n",
            ">6, 23/234, d=0.686, g=0.849\n",
            ">6, 24/234, d=0.707, g=0.820\n",
            ">6, 25/234, d=0.703, g=0.766\n",
            ">6, 26/234, d=0.724, g=0.716\n",
            ">6, 27/234, d=0.712, g=0.678\n",
            ">6, 28/234, d=0.706, g=0.658\n",
            ">6, 29/234, d=0.704, g=0.639\n",
            ">6, 30/234, d=0.696, g=0.638\n",
            ">6, 31/234, d=0.693, g=0.624\n",
            ">6, 32/234, d=0.703, g=0.607\n",
            ">6, 33/234, d=0.701, g=0.620\n",
            ">6, 34/234, d=0.706, g=0.617\n",
            ">6, 35/234, d=0.718, g=0.668\n",
            ">6, 36/234, d=0.707, g=0.703\n",
            ">6, 37/234, d=0.703, g=0.754\n",
            ">6, 38/234, d=0.693, g=0.798\n",
            ">6, 39/234, d=0.689, g=0.794\n",
            ">6, 40/234, d=0.698, g=0.818\n",
            ">6, 41/234, d=0.692, g=0.790\n",
            ">6, 42/234, d=0.687, g=0.774\n",
            ">6, 43/234, d=0.695, g=0.750\n",
            ">6, 44/234, d=0.687, g=0.720\n",
            ">6, 45/234, d=0.680, g=0.707\n",
            ">6, 46/234, d=0.679, g=0.700\n",
            ">6, 47/234, d=0.669, g=0.682\n",
            ">6, 48/234, d=0.666, g=0.673\n",
            ">6, 49/234, d=0.673, g=0.663\n",
            ">6, 50/234, d=0.674, g=0.677\n",
            ">6, 51/234, d=0.674, g=0.687\n",
            ">6, 52/234, d=0.677, g=0.713\n",
            ">6, 53/234, d=0.681, g=0.749\n",
            ">6, 54/234, d=0.674, g=0.790\n",
            ">6, 55/234, d=0.670, g=0.816\n",
            ">6, 56/234, d=0.657, g=0.823\n",
            ">6, 57/234, d=0.676, g=0.807\n",
            ">6, 58/234, d=0.682, g=0.796\n",
            ">6, 59/234, d=0.695, g=0.754\n",
            ">6, 60/234, d=0.677, g=0.717\n",
            ">6, 61/234, d=0.690, g=0.685\n",
            ">6, 62/234, d=0.688, g=0.671\n",
            ">6, 63/234, d=0.689, g=0.654\n",
            ">6, 64/234, d=0.694, g=0.649\n",
            ">6, 65/234, d=0.690, g=0.647\n",
            ">6, 66/234, d=0.675, g=0.629\n",
            ">6, 67/234, d=0.692, g=0.633\n",
            ">6, 68/234, d=0.693, g=0.632\n",
            ">6, 69/234, d=0.704, g=0.655\n",
            ">6, 70/234, d=0.699, g=0.685\n",
            ">6, 71/234, d=0.695, g=0.745\n",
            ">6, 72/234, d=0.703, g=0.798\n",
            ">6, 73/234, d=0.681, g=0.811\n",
            ">6, 74/234, d=0.694, g=0.819\n",
            ">6, 75/234, d=0.689, g=0.798\n",
            ">6, 76/234, d=0.703, g=0.760\n",
            ">6, 77/234, d=0.705, g=0.731\n",
            ">6, 78/234, d=0.698, g=0.713\n",
            ">6, 79/234, d=0.701, g=0.681\n",
            ">6, 80/234, d=0.702, g=0.669\n",
            ">6, 81/234, d=0.700, g=0.663\n",
            ">6, 82/234, d=0.693, g=0.644\n",
            ">6, 83/234, d=0.700, g=0.648\n",
            ">6, 84/234, d=0.711, g=0.644\n",
            ">6, 85/234, d=0.709, g=0.643\n",
            ">6, 86/234, d=0.706, g=0.655\n",
            ">6, 87/234, d=0.706, g=0.676\n",
            ">6, 88/234, d=0.708, g=0.706\n",
            ">6, 89/234, d=0.701, g=0.724\n",
            ">6, 90/234, d=0.705, g=0.740\n",
            ">6, 91/234, d=0.702, g=0.736\n",
            ">6, 92/234, d=0.700, g=0.733\n",
            ">6, 93/234, d=0.710, g=0.725\n",
            ">6, 94/234, d=0.701, g=0.718\n",
            ">6, 95/234, d=0.691, g=0.716\n",
            ">6, 96/234, d=0.701, g=0.717\n",
            ">6, 97/234, d=0.689, g=0.723\n",
            ">6, 98/234, d=0.686, g=0.718\n",
            ">6, 99/234, d=0.682, g=0.726\n",
            ">6, 100/234, d=0.671, g=0.739\n",
            ">6, 101/234, d=0.666, g=0.749\n",
            ">6, 102/234, d=0.665, g=0.761\n",
            ">6, 103/234, d=0.660, g=0.775\n",
            ">6, 104/234, d=0.657, g=0.781\n",
            ">6, 105/234, d=0.652, g=0.797\n",
            ">6, 106/234, d=0.650, g=0.828\n",
            ">6, 107/234, d=0.649, g=0.828\n",
            ">6, 108/234, d=0.658, g=0.827\n",
            ">6, 109/234, d=0.646, g=0.813\n",
            ">6, 110/234, d=0.657, g=0.795\n",
            ">6, 111/234, d=0.662, g=0.781\n",
            ">6, 112/234, d=0.672, g=0.750\n",
            ">6, 113/234, d=0.672, g=0.734\n",
            ">6, 114/234, d=0.666, g=0.703\n",
            ">6, 115/234, d=0.676, g=0.688\n",
            ">6, 116/234, d=0.681, g=0.681\n",
            ">6, 117/234, d=0.689, g=0.671\n",
            ">6, 118/234, d=0.680, g=0.668\n",
            ">6, 119/234, d=0.686, g=0.663\n",
            ">6, 120/234, d=0.689, g=0.654\n",
            ">6, 121/234, d=0.693, g=0.665\n",
            ">6, 122/234, d=0.695, g=0.679\n",
            ">6, 123/234, d=0.695, g=0.699\n",
            ">6, 124/234, d=0.701, g=0.712\n",
            ">6, 125/234, d=0.693, g=0.740\n",
            ">6, 126/234, d=0.703, g=0.742\n",
            ">6, 127/234, d=0.692, g=0.732\n",
            ">6, 128/234, d=0.704, g=0.736\n",
            ">6, 129/234, d=0.689, g=0.722\n",
            ">6, 130/234, d=0.699, g=0.704\n",
            ">6, 131/234, d=0.702, g=0.692\n",
            ">6, 132/234, d=0.700, g=0.687\n",
            ">6, 133/234, d=0.708, g=0.674\n",
            ">6, 134/234, d=0.705, g=0.674\n",
            ">6, 135/234, d=0.695, g=0.673\n",
            ">6, 136/234, d=0.712, g=0.672\n",
            ">6, 137/234, d=0.707, g=0.672\n",
            ">6, 138/234, d=0.703, g=0.683\n",
            ">6, 139/234, d=0.703, g=0.710\n",
            ">6, 140/234, d=0.705, g=0.709\n",
            ">6, 141/234, d=0.703, g=0.726\n",
            ">6, 142/234, d=0.708, g=0.728\n",
            ">6, 143/234, d=0.700, g=0.724\n",
            ">6, 144/234, d=0.704, g=0.721\n",
            ">6, 145/234, d=0.703, g=0.707\n",
            ">6, 146/234, d=0.713, g=0.704\n",
            ">6, 147/234, d=0.716, g=0.698\n",
            ">6, 148/234, d=0.712, g=0.696\n",
            ">6, 149/234, d=0.713, g=0.677\n",
            ">6, 150/234, d=0.722, g=0.683\n",
            ">6, 151/234, d=0.712, g=0.681\n",
            ">6, 152/234, d=0.718, g=0.697\n",
            ">6, 153/234, d=0.714, g=0.697\n",
            ">6, 154/234, d=0.713, g=0.718\n",
            ">6, 155/234, d=0.698, g=0.743\n",
            ">6, 156/234, d=0.686, g=0.758\n",
            ">6, 157/234, d=0.685, g=0.778\n",
            ">6, 158/234, d=0.678, g=0.802\n",
            ">6, 159/234, d=0.661, g=0.814\n",
            ">6, 160/234, d=0.652, g=0.831\n",
            ">6, 161/234, d=0.643, g=0.843\n",
            ">6, 162/234, d=0.643, g=0.844\n",
            ">6, 163/234, d=0.631, g=0.847\n",
            ">6, 164/234, d=0.623, g=0.847\n",
            ">6, 165/234, d=0.624, g=0.829\n",
            ">6, 166/234, d=0.637, g=0.816\n",
            ">6, 167/234, d=0.641, g=0.794\n",
            ">6, 168/234, d=0.633, g=0.782\n",
            ">6, 169/234, d=0.641, g=0.764\n",
            ">6, 170/234, d=0.651, g=0.763\n",
            ">6, 171/234, d=0.656, g=0.764\n",
            ">6, 172/234, d=0.654, g=0.765\n",
            ">6, 173/234, d=0.649, g=0.764\n",
            ">6, 174/234, d=0.679, g=0.735\n",
            ">6, 175/234, d=0.662, g=0.724\n",
            ">6, 176/234, d=0.688, g=0.692\n",
            ">6, 177/234, d=0.683, g=0.685\n",
            ">6, 178/234, d=0.688, g=0.668\n",
            ">6, 179/234, d=0.695, g=0.653\n",
            ">6, 180/234, d=0.684, g=0.626\n",
            ">6, 181/234, d=0.683, g=0.621\n",
            ">6, 182/234, d=0.677, g=0.621\n",
            ">6, 183/234, d=0.694, g=0.608\n",
            ">6, 184/234, d=0.709, g=0.623\n",
            ">6, 185/234, d=0.714, g=0.622\n",
            ">6, 186/234, d=0.716, g=0.651\n",
            ">6, 187/234, d=0.712, g=0.691\n",
            ">6, 188/234, d=0.715, g=0.711\n",
            ">6, 189/234, d=0.721, g=0.731\n",
            ">6, 190/234, d=0.730, g=0.749\n",
            ">6, 191/234, d=0.730, g=0.734\n",
            ">6, 192/234, d=0.723, g=0.717\n",
            ">6, 193/234, d=0.732, g=0.683\n",
            ">6, 194/234, d=0.749, g=0.665\n",
            ">6, 195/234, d=0.753, g=0.639\n",
            ">6, 196/234, d=0.754, g=0.626\n",
            ">6, 197/234, d=0.755, g=0.613\n",
            ">6, 198/234, d=0.760, g=0.610\n",
            ">6, 199/234, d=0.759, g=0.619\n",
            ">6, 200/234, d=0.744, g=0.622\n",
            ">6, 201/234, d=0.748, g=0.645\n",
            ">6, 202/234, d=0.734, g=0.672\n",
            ">6, 203/234, d=0.722, g=0.700\n",
            ">6, 204/234, d=0.716, g=0.737\n",
            ">6, 205/234, d=0.706, g=0.772\n",
            ">6, 206/234, d=0.691, g=0.803\n",
            ">6, 207/234, d=0.677, g=0.830\n",
            ">6, 208/234, d=0.668, g=0.844\n",
            ">6, 209/234, d=0.661, g=0.843\n",
            ">6, 210/234, d=0.657, g=0.828\n",
            ">6, 211/234, d=0.651, g=0.820\n",
            ">6, 212/234, d=0.645, g=0.811\n",
            ">6, 213/234, d=0.642, g=0.789\n",
            ">6, 214/234, d=0.642, g=0.760\n",
            ">6, 215/234, d=0.644, g=0.744\n",
            ">6, 216/234, d=0.649, g=0.737\n",
            ">6, 217/234, d=0.657, g=0.721\n",
            ">6, 218/234, d=0.657, g=0.703\n",
            ">6, 219/234, d=0.649, g=0.701\n",
            ">6, 220/234, d=0.677, g=0.704\n",
            ">6, 221/234, d=0.680, g=0.719\n",
            ">6, 222/234, d=0.674, g=0.746\n",
            ">6, 223/234, d=0.674, g=0.774\n",
            ">6, 224/234, d=0.673, g=0.813\n",
            ">6, 225/234, d=0.674, g=0.841\n",
            ">6, 226/234, d=0.672, g=0.834\n",
            ">6, 227/234, d=0.688, g=0.806\n",
            ">6, 228/234, d=0.682, g=0.772\n",
            ">6, 229/234, d=0.676, g=0.748\n",
            ">6, 230/234, d=0.691, g=0.711\n",
            ">6, 231/234, d=0.693, g=0.688\n",
            ">6, 232/234, d=0.699, g=0.681\n",
            ">6, 233/234, d=0.683, g=0.662\n",
            ">6, 234/234, d=0.670, g=0.646\n",
            ">7, 1/234, d=0.672, g=0.648\n",
            ">7, 2/234, d=0.677, g=0.647\n",
            ">7, 3/234, d=0.659, g=0.649\n",
            ">7, 4/234, d=0.669, g=0.645\n",
            ">7, 5/234, d=0.680, g=0.632\n",
            ">7, 6/234, d=0.696, g=0.640\n",
            ">7, 7/234, d=0.688, g=0.677\n",
            ">7, 8/234, d=0.706, g=0.728\n",
            ">7, 9/234, d=0.683, g=0.795\n",
            ">7, 10/234, d=0.667, g=0.841\n",
            ">7, 11/234, d=0.667, g=0.859\n",
            ">7, 12/234, d=0.678, g=0.855\n",
            ">7, 13/234, d=0.683, g=0.810\n",
            ">7, 14/234, d=0.689, g=0.776\n",
            ">7, 15/234, d=0.696, g=0.749\n",
            ">7, 16/234, d=0.699, g=0.695\n",
            ">7, 17/234, d=0.710, g=0.676\n",
            ">7, 18/234, d=0.705, g=0.670\n",
            ">7, 19/234, d=0.705, g=0.641\n",
            ">7, 20/234, d=0.694, g=0.634\n",
            ">7, 21/234, d=0.702, g=0.622\n",
            ">7, 22/234, d=0.714, g=0.606\n",
            ">7, 23/234, d=0.711, g=0.605\n",
            ">7, 24/234, d=0.731, g=0.624\n",
            ">7, 25/234, d=0.731, g=0.651\n",
            ">7, 26/234, d=0.728, g=0.692\n",
            ">7, 27/234, d=0.726, g=0.726\n",
            ">7, 28/234, d=0.736, g=0.776\n",
            ">7, 29/234, d=0.727, g=0.789\n",
            ">7, 30/234, d=0.725, g=0.805\n",
            ">7, 31/234, d=0.709, g=0.796\n",
            ">7, 32/234, d=0.706, g=0.798\n",
            ">7, 33/234, d=0.710, g=0.802\n",
            ">7, 34/234, d=0.690, g=0.801\n",
            ">7, 35/234, d=0.694, g=0.782\n",
            ">7, 36/234, d=0.681, g=0.776\n",
            ">7, 37/234, d=0.691, g=0.757\n",
            ">7, 38/234, d=0.676, g=0.749\n",
            ">7, 39/234, d=0.681, g=0.721\n",
            ">7, 40/234, d=0.683, g=0.720\n",
            ">7, 41/234, d=0.682, g=0.718\n",
            ">7, 42/234, d=0.683, g=0.710\n",
            ">7, 43/234, d=0.676, g=0.702\n",
            ">7, 44/234, d=0.691, g=0.697\n",
            ">7, 45/234, d=0.687, g=0.709\n",
            ">7, 46/234, d=0.686, g=0.719\n",
            ">7, 47/234, d=0.683, g=0.732\n",
            ">7, 48/234, d=0.680, g=0.748\n",
            ">7, 49/234, d=0.690, g=0.743\n",
            ">7, 50/234, d=0.699, g=0.744\n",
            ">7, 51/234, d=0.681, g=0.750\n",
            ">7, 52/234, d=0.694, g=0.742\n",
            ">7, 53/234, d=0.699, g=0.727\n",
            ">7, 54/234, d=0.681, g=0.711\n",
            ">7, 55/234, d=0.697, g=0.697\n",
            ">7, 56/234, d=0.691, g=0.688\n",
            ">7, 57/234, d=0.694, g=0.682\n",
            ">7, 58/234, d=0.693, g=0.677\n",
            ">7, 59/234, d=0.694, g=0.669\n",
            ">7, 60/234, d=0.698, g=0.671\n",
            ">7, 61/234, d=0.689, g=0.668\n",
            ">7, 62/234, d=0.687, g=0.668\n",
            ">7, 63/234, d=0.684, g=0.676\n",
            ">7, 64/234, d=0.674, g=0.673\n",
            ">7, 65/234, d=0.686, g=0.668\n",
            ">7, 66/234, d=0.673, g=0.675\n",
            ">7, 67/234, d=0.686, g=0.683\n",
            ">7, 68/234, d=0.672, g=0.694\n",
            ">7, 69/234, d=0.683, g=0.710\n",
            ">7, 70/234, d=0.684, g=0.722\n",
            ">7, 71/234, d=0.664, g=0.737\n",
            ">7, 72/234, d=0.679, g=0.728\n",
            ">7, 73/234, d=0.670, g=0.735\n",
            ">7, 74/234, d=0.670, g=0.741\n",
            ">7, 75/234, d=0.675, g=0.747\n",
            ">7, 76/234, d=0.681, g=0.730\n",
            ">7, 77/234, d=0.687, g=0.718\n",
            ">7, 78/234, d=0.684, g=0.721\n",
            ">7, 79/234, d=0.689, g=0.712\n",
            ">7, 80/234, d=0.703, g=0.697\n",
            ">7, 81/234, d=0.708, g=0.696\n",
            ">7, 82/234, d=0.697, g=0.682\n",
            ">7, 83/234, d=0.704, g=0.684\n",
            ">7, 84/234, d=0.696, g=0.673\n",
            ">7, 85/234, d=0.691, g=0.689\n",
            ">7, 86/234, d=0.711, g=0.689\n",
            ">7, 87/234, d=0.698, g=0.715\n",
            ">7, 88/234, d=0.690, g=0.713\n",
            ">7, 89/234, d=0.696, g=0.747\n",
            ">7, 90/234, d=0.692, g=0.766\n",
            ">7, 91/234, d=0.677, g=0.790\n",
            ">7, 92/234, d=0.666, g=0.805\n",
            ">7, 93/234, d=0.661, g=0.845\n",
            ">7, 94/234, d=0.661, g=0.828\n",
            ">7, 95/234, d=0.657, g=0.801\n",
            ">7, 96/234, d=0.659, g=0.785\n",
            ">7, 97/234, d=0.671, g=0.765\n",
            ">7, 98/234, d=0.673, g=0.726\n",
            ">7, 99/234, d=0.677, g=0.690\n",
            ">7, 100/234, d=0.681, g=0.676\n",
            ">7, 101/234, d=0.682, g=0.658\n",
            ">7, 102/234, d=0.700, g=0.651\n",
            ">7, 103/234, d=0.693, g=0.633\n",
            ">7, 104/234, d=0.699, g=0.631\n",
            ">7, 105/234, d=0.722, g=0.633\n",
            ">7, 106/234, d=0.705, g=0.625\n",
            ">7, 107/234, d=0.718, g=0.649\n",
            ">7, 108/234, d=0.714, g=0.668\n",
            ">7, 109/234, d=0.717, g=0.691\n",
            ">7, 110/234, d=0.709, g=0.709\n",
            ">7, 111/234, d=0.713, g=0.733\n",
            ">7, 112/234, d=0.711, g=0.737\n",
            ">7, 113/234, d=0.710, g=0.734\n",
            ">7, 114/234, d=0.720, g=0.733\n",
            ">7, 115/234, d=0.713, g=0.712\n",
            ">7, 116/234, d=0.710, g=0.712\n",
            ">7, 117/234, d=0.717, g=0.705\n",
            ">7, 118/234, d=0.719, g=0.689\n",
            ">7, 119/234, d=0.703, g=0.691\n",
            ">7, 120/234, d=0.692, g=0.700\n",
            ">7, 121/234, d=0.698, g=0.696\n",
            ">7, 122/234, d=0.690, g=0.690\n",
            ">7, 123/234, d=0.694, g=0.697\n",
            ">7, 124/234, d=0.691, g=0.711\n",
            ">7, 125/234, d=0.686, g=0.723\n",
            ">7, 126/234, d=0.680, g=0.720\n",
            ">7, 127/234, d=0.680, g=0.726\n",
            ">7, 128/234, d=0.671, g=0.732\n",
            ">7, 129/234, d=0.683, g=0.737\n",
            ">7, 130/234, d=0.679, g=0.725\n",
            ">7, 131/234, d=0.685, g=0.730\n",
            ">7, 132/234, d=0.676, g=0.733\n",
            ">7, 133/234, d=0.673, g=0.733\n",
            ">7, 134/234, d=0.676, g=0.735\n",
            ">7, 135/234, d=0.670, g=0.737\n",
            ">7, 136/234, d=0.676, g=0.729\n",
            ">7, 137/234, d=0.668, g=0.732\n",
            ">7, 138/234, d=0.670, g=0.742\n",
            ">7, 139/234, d=0.673, g=0.722\n",
            ">7, 140/234, d=0.678, g=0.718\n",
            ">7, 141/234, d=0.669, g=0.722\n",
            ">7, 142/234, d=0.671, g=0.723\n",
            ">7, 143/234, d=0.663, g=0.734\n",
            ">7, 144/234, d=0.672, g=0.734\n",
            ">7, 145/234, d=0.668, g=0.742\n",
            ">7, 146/234, d=0.675, g=0.749\n",
            ">7, 147/234, d=0.672, g=0.751\n",
            ">7, 148/234, d=0.671, g=0.751\n",
            ">7, 149/234, d=0.673, g=0.745\n",
            ">7, 150/234, d=0.673, g=0.751\n",
            ">7, 151/234, d=0.674, g=0.746\n",
            ">7, 152/234, d=0.681, g=0.731\n",
            ">7, 153/234, d=0.668, g=0.734\n",
            ">7, 154/234, d=0.684, g=0.720\n",
            ">7, 155/234, d=0.679, g=0.717\n",
            ">7, 156/234, d=0.686, g=0.714\n",
            ">7, 157/234, d=0.685, g=0.715\n",
            ">7, 158/234, d=0.697, g=0.698\n",
            ">7, 159/234, d=0.698, g=0.696\n",
            ">7, 160/234, d=0.699, g=0.684\n",
            ">7, 161/234, d=0.700, g=0.687\n",
            ">7, 162/234, d=0.704, g=0.695\n",
            ">7, 163/234, d=0.701, g=0.696\n",
            ">7, 164/234, d=0.708, g=0.701\n",
            ">7, 165/234, d=0.714, g=0.697\n",
            ">7, 166/234, d=0.701, g=0.688\n",
            ">7, 167/234, d=0.706, g=0.692\n",
            ">7, 168/234, d=0.705, g=0.692\n",
            ">7, 169/234, d=0.707, g=0.705\n",
            ">7, 170/234, d=0.717, g=0.700\n",
            ">7, 171/234, d=0.709, g=0.700\n",
            ">7, 172/234, d=0.714, g=0.686\n",
            ">7, 173/234, d=0.715, g=0.689\n",
            ">7, 174/234, d=0.694, g=0.674\n",
            ">7, 175/234, d=0.710, g=0.675\n",
            ">7, 176/234, d=0.709, g=0.672\n",
            ">7, 177/234, d=0.703, g=0.659\n",
            ">7, 178/234, d=0.696, g=0.667\n",
            ">7, 179/234, d=0.705, g=0.664\n",
            ">7, 180/234, d=0.702, g=0.669\n",
            ">7, 181/234, d=0.695, g=0.674\n",
            ">7, 182/234, d=0.693, g=0.673\n",
            ">7, 183/234, d=0.702, g=0.678\n",
            ">7, 184/234, d=0.701, g=0.672\n",
            ">7, 185/234, d=0.684, g=0.688\n",
            ">7, 186/234, d=0.691, g=0.691\n",
            ">7, 187/234, d=0.694, g=0.700\n",
            ">7, 188/234, d=0.697, g=0.699\n",
            ">7, 189/234, d=0.691, g=0.705\n",
            ">7, 190/234, d=0.692, g=0.711\n",
            ">7, 191/234, d=0.682, g=0.703\n",
            ">7, 192/234, d=0.684, g=0.715\n",
            ">7, 193/234, d=0.685, g=0.704\n",
            ">7, 194/234, d=0.685, g=0.713\n",
            ">7, 195/234, d=0.687, g=0.699\n",
            ">7, 196/234, d=0.677, g=0.697\n",
            ">7, 197/234, d=0.688, g=0.695\n",
            ">7, 198/234, d=0.677, g=0.689\n",
            ">7, 199/234, d=0.683, g=0.674\n",
            ">7, 200/234, d=0.686, g=0.683\n",
            ">7, 201/234, d=0.682, g=0.688\n",
            ">7, 202/234, d=0.679, g=0.694\n",
            ">7, 203/234, d=0.685, g=0.691\n",
            ">7, 204/234, d=0.680, g=0.711\n",
            ">7, 205/234, d=0.685, g=0.708\n",
            ">7, 206/234, d=0.684, g=0.714\n",
            ">7, 207/234, d=0.684, g=0.732\n",
            ">7, 208/234, d=0.684, g=0.749\n",
            ">7, 209/234, d=0.673, g=0.741\n",
            ">7, 210/234, d=0.684, g=0.737\n",
            ">7, 211/234, d=0.684, g=0.732\n",
            ">7, 212/234, d=0.668, g=0.731\n",
            ">7, 213/234, d=0.679, g=0.738\n",
            ">7, 214/234, d=0.660, g=0.727\n",
            ">7, 215/234, d=0.680, g=0.726\n",
            ">7, 216/234, d=0.674, g=0.724\n",
            ">7, 217/234, d=0.678, g=0.720\n",
            ">7, 218/234, d=0.672, g=0.723\n",
            ">7, 219/234, d=0.675, g=0.716\n",
            ">7, 220/234, d=0.677, g=0.734\n",
            ">7, 221/234, d=0.676, g=0.726\n",
            ">7, 222/234, d=0.681, g=0.734\n",
            ">7, 223/234, d=0.681, g=0.718\n",
            ">7, 224/234, d=0.676, g=0.731\n",
            ">7, 225/234, d=0.683, g=0.721\n",
            ">7, 226/234, d=0.689, g=0.719\n",
            ">7, 227/234, d=0.693, g=0.711\n",
            ">7, 228/234, d=0.689, g=0.703\n",
            ">7, 229/234, d=0.700, g=0.706\n",
            ">7, 230/234, d=0.697, g=0.701\n",
            ">7, 231/234, d=0.696, g=0.695\n",
            ">7, 232/234, d=0.692, g=0.691\n",
            ">7, 233/234, d=0.695, g=0.697\n",
            ">7, 234/234, d=0.696, g=0.697\n",
            ">8, 1/234, d=0.691, g=0.697\n",
            ">8, 2/234, d=0.700, g=0.692\n",
            ">8, 3/234, d=0.705, g=0.692\n",
            ">8, 4/234, d=0.700, g=0.702\n",
            ">8, 5/234, d=0.703, g=0.693\n",
            ">8, 6/234, d=0.707, g=0.710\n",
            ">8, 7/234, d=0.707, g=0.703\n",
            ">8, 8/234, d=0.705, g=0.699\n",
            ">8, 9/234, d=0.706, g=0.693\n",
            ">8, 10/234, d=0.700, g=0.688\n",
            ">8, 11/234, d=0.701, g=0.687\n",
            ">8, 12/234, d=0.695, g=0.687\n",
            ">8, 13/234, d=0.698, g=0.700\n",
            ">8, 14/234, d=0.700, g=0.698\n",
            ">8, 15/234, d=0.702, g=0.699\n",
            ">8, 16/234, d=0.704, g=0.702\n",
            ">8, 17/234, d=0.698, g=0.712\n",
            ">8, 18/234, d=0.703, g=0.700\n",
            ">8, 19/234, d=0.702, g=0.711\n",
            ">8, 20/234, d=0.699, g=0.706\n",
            ">8, 21/234, d=0.691, g=0.701\n",
            ">8, 22/234, d=0.693, g=0.707\n",
            ">8, 23/234, d=0.692, g=0.712\n",
            ">8, 24/234, d=0.687, g=0.707\n",
            ">8, 25/234, d=0.692, g=0.712\n",
            ">8, 26/234, d=0.690, g=0.709\n",
            ">8, 27/234, d=0.686, g=0.707\n",
            ">8, 28/234, d=0.684, g=0.710\n",
            ">8, 29/234, d=0.684, g=0.706\n",
            ">8, 30/234, d=0.685, g=0.712\n",
            ">8, 31/234, d=0.687, g=0.713\n",
            ">8, 32/234, d=0.690, g=0.715\n",
            ">8, 33/234, d=0.677, g=0.731\n",
            ">8, 34/234, d=0.681, g=0.740\n",
            ">8, 35/234, d=0.676, g=0.739\n",
            ">8, 36/234, d=0.677, g=0.743\n",
            ">8, 37/234, d=0.678, g=0.740\n",
            ">8, 38/234, d=0.682, g=0.749\n",
            ">8, 39/234, d=0.673, g=0.741\n",
            ">8, 40/234, d=0.663, g=0.741\n",
            ">8, 41/234, d=0.672, g=0.735\n",
            ">8, 42/234, d=0.671, g=0.734\n",
            ">8, 43/234, d=0.665, g=0.741\n",
            ">8, 44/234, d=0.677, g=0.732\n",
            ">8, 45/234, d=0.671, g=0.728\n",
            ">8, 46/234, d=0.670, g=0.737\n",
            ">8, 47/234, d=0.668, g=0.734\n",
            ">8, 48/234, d=0.671, g=0.737\n",
            ">8, 49/234, d=0.667, g=0.741\n",
            ">8, 50/234, d=0.673, g=0.752\n",
            ">8, 51/234, d=0.673, g=0.743\n",
            ">8, 52/234, d=0.671, g=0.744\n",
            ">8, 53/234, d=0.669, g=0.750\n",
            ">8, 54/234, d=0.673, g=0.752\n",
            ">8, 55/234, d=0.679, g=0.742\n",
            ">8, 56/234, d=0.674, g=0.736\n",
            ">8, 57/234, d=0.669, g=0.717\n",
            ">8, 58/234, d=0.686, g=0.719\n",
            ">8, 59/234, d=0.689, g=0.696\n",
            ">8, 60/234, d=0.685, g=0.692\n",
            ">8, 61/234, d=0.679, g=0.689\n",
            ">8, 62/234, d=0.684, g=0.689\n",
            ">8, 63/234, d=0.689, g=0.682\n",
            ">8, 64/234, d=0.698, g=0.695\n",
            ">8, 65/234, d=0.690, g=0.691\n",
            ">8, 66/234, d=0.696, g=0.690\n",
            ">8, 67/234, d=0.690, g=0.698\n",
            ">8, 68/234, d=0.699, g=0.700\n",
            ">8, 69/234, d=0.697, g=0.702\n",
            ">8, 70/234, d=0.705, g=0.710\n",
            ">8, 71/234, d=0.702, g=0.698\n",
            ">8, 72/234, d=0.705, g=0.698\n",
            ">8, 73/234, d=0.709, g=0.688\n",
            ">8, 74/234, d=0.707, g=0.687\n",
            ">8, 75/234, d=0.706, g=0.678\n",
            ">8, 76/234, d=0.703, g=0.673\n",
            ">8, 77/234, d=0.704, g=0.673\n",
            ">8, 78/234, d=0.705, g=0.664\n",
            ">8, 79/234, d=0.705, g=0.659\n",
            ">8, 80/234, d=0.714, g=0.672\n",
            ">8, 81/234, d=0.707, g=0.666\n",
            ">8, 82/234, d=0.713, g=0.664\n",
            ">8, 83/234, d=0.717, g=0.669\n",
            ">8, 84/234, d=0.711, g=0.682\n",
            ">8, 85/234, d=0.705, g=0.682\n",
            ">8, 86/234, d=0.711, g=0.686\n",
            ">8, 87/234, d=0.708, g=0.692\n",
            ">8, 88/234, d=0.704, g=0.698\n",
            ">8, 89/234, d=0.701, g=0.691\n",
            ">8, 90/234, d=0.698, g=0.702\n",
            ">8, 91/234, d=0.702, g=0.712\n",
            ">8, 92/234, d=0.698, g=0.705\n",
            ">8, 93/234, d=0.691, g=0.714\n",
            ">8, 94/234, d=0.688, g=0.709\n",
            ">8, 95/234, d=0.687, g=0.717\n",
            ">8, 96/234, d=0.684, g=0.723\n",
            ">8, 97/234, d=0.681, g=0.727\n",
            ">8, 98/234, d=0.689, g=0.725\n",
            ">8, 99/234, d=0.675, g=0.714\n",
            ">8, 100/234, d=0.675, g=0.730\n",
            ">8, 101/234, d=0.674, g=0.726\n",
            ">8, 102/234, d=0.667, g=0.726\n",
            ">8, 103/234, d=0.668, g=0.731\n",
            ">8, 104/234, d=0.674, g=0.726\n",
            ">8, 105/234, d=0.666, g=0.725\n",
            ">8, 106/234, d=0.672, g=0.724\n",
            ">8, 107/234, d=0.673, g=0.723\n",
            ">8, 108/234, d=0.667, g=0.725\n",
            ">8, 109/234, d=0.673, g=0.725\n",
            ">8, 110/234, d=0.663, g=0.734\n",
            ">8, 111/234, d=0.669, g=0.732\n",
            ">8, 112/234, d=0.669, g=0.728\n",
            ">8, 113/234, d=0.665, g=0.723\n",
            ">8, 114/234, d=0.660, g=0.719\n",
            ">8, 115/234, d=0.671, g=0.717\n",
            ">8, 116/234, d=0.672, g=0.724\n",
            ">8, 117/234, d=0.677, g=0.709\n",
            ">8, 118/234, d=0.679, g=0.704\n",
            ">8, 119/234, d=0.678, g=0.706\n",
            ">8, 120/234, d=0.680, g=0.704\n",
            ">8, 121/234, d=0.678, g=0.710\n",
            ">8, 122/234, d=0.683, g=0.699\n",
            ">8, 123/234, d=0.689, g=0.685\n",
            ">8, 124/234, d=0.681, g=0.678\n",
            ">8, 125/234, d=0.687, g=0.678\n",
            ">8, 126/234, d=0.691, g=0.692\n",
            ">8, 127/234, d=0.697, g=0.689\n",
            ">8, 128/234, d=0.698, g=0.694\n",
            ">8, 129/234, d=0.697, g=0.693\n",
            ">8, 130/234, d=0.695, g=0.704\n",
            ">8, 131/234, d=0.697, g=0.697\n",
            ">8, 132/234, d=0.699, g=0.696\n",
            ">8, 133/234, d=0.709, g=0.691\n",
            ">8, 134/234, d=0.699, g=0.688\n",
            ">8, 135/234, d=0.699, g=0.688\n",
            ">8, 136/234, d=0.695, g=0.683\n",
            ">8, 137/234, d=0.699, g=0.683\n",
            ">8, 138/234, d=0.702, g=0.681\n",
            ">8, 139/234, d=0.701, g=0.679\n",
            ">8, 140/234, d=0.702, g=0.685\n",
            ">8, 141/234, d=0.704, g=0.694\n",
            ">8, 142/234, d=0.702, g=0.693\n",
            ">8, 143/234, d=0.711, g=0.691\n",
            ">8, 144/234, d=0.711, g=0.692\n",
            ">8, 145/234, d=0.702, g=0.686\n",
            ">8, 146/234, d=0.699, g=0.684\n",
            ">8, 147/234, d=0.702, g=0.688\n",
            ">8, 148/234, d=0.706, g=0.686\n",
            ">8, 149/234, d=0.703, g=0.686\n",
            ">8, 150/234, d=0.707, g=0.690\n",
            ">8, 151/234, d=0.705, g=0.690\n",
            ">8, 152/234, d=0.701, g=0.687\n",
            ">8, 153/234, d=0.704, g=0.693\n",
            ">8, 154/234, d=0.699, g=0.680\n",
            ">8, 155/234, d=0.704, g=0.693\n",
            ">8, 156/234, d=0.686, g=0.702\n",
            ">8, 157/234, d=0.690, g=0.706\n",
            ">8, 158/234, d=0.690, g=0.707\n",
            ">8, 159/234, d=0.691, g=0.715\n",
            ">8, 160/234, d=0.683, g=0.714\n",
            ">8, 161/234, d=0.683, g=0.730\n",
            ">8, 162/234, d=0.683, g=0.736\n",
            ">8, 163/234, d=0.672, g=0.736\n",
            ">8, 164/234, d=0.675, g=0.733\n",
            ">8, 165/234, d=0.676, g=0.735\n",
            ">8, 166/234, d=0.667, g=0.721\n",
            ">8, 167/234, d=0.672, g=0.734\n",
            ">8, 168/234, d=0.663, g=0.726\n",
            ">8, 169/234, d=0.671, g=0.735\n",
            ">8, 170/234, d=0.656, g=0.736\n",
            ">8, 171/234, d=0.659, g=0.737\n",
            ">8, 172/234, d=0.665, g=0.734\n",
            ">8, 173/234, d=0.668, g=0.739\n",
            ">8, 174/234, d=0.674, g=0.727\n",
            ">8, 175/234, d=0.666, g=0.725\n",
            ">8, 176/234, d=0.662, g=0.723\n",
            ">8, 177/234, d=0.658, g=0.725\n",
            ">8, 178/234, d=0.670, g=0.727\n",
            ">8, 179/234, d=0.672, g=0.729\n",
            ">8, 180/234, d=0.669, g=0.721\n",
            ">8, 181/234, d=0.672, g=0.731\n",
            ">8, 182/234, d=0.672, g=0.725\n",
            ">8, 183/234, d=0.671, g=0.732\n",
            ">8, 184/234, d=0.668, g=0.719\n",
            ">8, 185/234, d=0.682, g=0.725\n",
            ">8, 186/234, d=0.685, g=0.715\n",
            ">8, 187/234, d=0.673, g=0.706\n",
            ">8, 188/234, d=0.678, g=0.704\n",
            ">8, 189/234, d=0.687, g=0.705\n",
            ">8, 190/234, d=0.672, g=0.695\n",
            ">8, 191/234, d=0.685, g=0.688\n",
            ">8, 192/234, d=0.694, g=0.685\n",
            ">8, 193/234, d=0.686, g=0.688\n",
            ">8, 194/234, d=0.690, g=0.708\n",
            ">8, 195/234, d=0.691, g=0.704\n",
            ">8, 196/234, d=0.693, g=0.702\n",
            ">8, 197/234, d=0.693, g=0.706\n",
            ">8, 198/234, d=0.692, g=0.706\n",
            ">8, 199/234, d=0.700, g=0.703\n",
            ">8, 200/234, d=0.697, g=0.701\n",
            ">8, 201/234, d=0.695, g=0.714\n",
            ">8, 202/234, d=0.702, g=0.697\n",
            ">8, 203/234, d=0.695, g=0.693\n",
            ">8, 204/234, d=0.701, g=0.688\n",
            ">8, 205/234, d=0.703, g=0.675\n",
            ">8, 206/234, d=0.700, g=0.674\n",
            ">8, 207/234, d=0.706, g=0.681\n",
            ">8, 208/234, d=0.707, g=0.669\n",
            ">8, 209/234, d=0.696, g=0.678\n",
            ">8, 210/234, d=0.708, g=0.679\n",
            ">8, 211/234, d=0.705, g=0.683\n",
            ">8, 212/234, d=0.702, g=0.686\n",
            ">8, 213/234, d=0.706, g=0.685\n",
            ">8, 214/234, d=0.700, g=0.690\n",
            ">8, 215/234, d=0.699, g=0.695\n",
            ">8, 216/234, d=0.697, g=0.696\n",
            ">8, 217/234, d=0.702, g=0.713\n",
            ">8, 218/234, d=0.695, g=0.723\n",
            ">8, 219/234, d=0.692, g=0.725\n",
            ">8, 220/234, d=0.693, g=0.739\n",
            ">8, 221/234, d=0.683, g=0.743\n",
            ">8, 222/234, d=0.685, g=0.745\n",
            ">8, 223/234, d=0.680, g=0.737\n",
            ">8, 224/234, d=0.683, g=0.732\n",
            ">8, 225/234, d=0.671, g=0.725\n",
            ">8, 226/234, d=0.674, g=0.725\n",
            ">8, 227/234, d=0.667, g=0.731\n",
            ">8, 228/234, d=0.675, g=0.712\n",
            ">8, 229/234, d=0.666, g=0.721\n",
            ">8, 230/234, d=0.671, g=0.719\n",
            ">8, 231/234, d=0.670, g=0.720\n",
            ">8, 232/234, d=0.676, g=0.723\n",
            ">8, 233/234, d=0.666, g=0.724\n",
            ">8, 234/234, d=0.662, g=0.731\n",
            ">9, 1/234, d=0.673, g=0.737\n",
            ">9, 2/234, d=0.667, g=0.736\n",
            ">9, 3/234, d=0.669, g=0.741\n",
            ">9, 4/234, d=0.673, g=0.747\n",
            ">9, 5/234, d=0.673, g=0.739\n",
            ">9, 6/234, d=0.678, g=0.727\n",
            ">9, 7/234, d=0.672, g=0.724\n",
            ">9, 8/234, d=0.677, g=0.710\n",
            ">9, 9/234, d=0.681, g=0.710\n",
            ">9, 10/234, d=0.687, g=0.692\n",
            ">9, 11/234, d=0.679, g=0.687\n",
            ">9, 12/234, d=0.684, g=0.687\n",
            ">9, 13/234, d=0.688, g=0.686\n",
            ">9, 14/234, d=0.689, g=0.683\n",
            ">9, 15/234, d=0.688, g=0.678\n",
            ">9, 16/234, d=0.691, g=0.694\n",
            ">9, 17/234, d=0.690, g=0.689\n",
            ">9, 18/234, d=0.693, g=0.701\n",
            ">9, 19/234, d=0.692, g=0.703\n",
            ">9, 20/234, d=0.692, g=0.700\n",
            ">9, 21/234, d=0.700, g=0.705\n",
            ">9, 22/234, d=0.694, g=0.709\n",
            ">9, 23/234, d=0.697, g=0.711\n",
            ">9, 24/234, d=0.694, g=0.706\n",
            ">9, 25/234, d=0.697, g=0.697\n",
            ">9, 26/234, d=0.703, g=0.706\n",
            ">9, 27/234, d=0.698, g=0.697\n",
            ">9, 28/234, d=0.698, g=0.681\n",
            ">9, 29/234, d=0.704, g=0.674\n",
            ">9, 30/234, d=0.699, g=0.671\n",
            ">9, 31/234, d=0.713, g=0.666\n",
            ">9, 32/234, d=0.703, g=0.662\n",
            ">9, 33/234, d=0.699, g=0.658\n",
            ">9, 34/234, d=0.698, g=0.658\n",
            ">9, 35/234, d=0.706, g=0.677\n",
            ">9, 36/234, d=0.700, g=0.685\n",
            ">9, 37/234, d=0.696, g=0.694\n",
            ">9, 38/234, d=0.710, g=0.719\n",
            ">9, 39/234, d=0.700, g=0.721\n",
            ">9, 40/234, d=0.695, g=0.728\n",
            ">9, 41/234, d=0.704, g=0.732\n",
            ">9, 42/234, d=0.693, g=0.728\n",
            ">9, 43/234, d=0.695, g=0.704\n",
            ">9, 44/234, d=0.690, g=0.703\n",
            ">9, 45/234, d=0.692, g=0.707\n",
            ">9, 46/234, d=0.686, g=0.698\n",
            ">9, 47/234, d=0.684, g=0.700\n",
            ">9, 48/234, d=0.678, g=0.702\n",
            ">9, 49/234, d=0.677, g=0.697\n",
            ">9, 50/234, d=0.677, g=0.699\n",
            ">9, 51/234, d=0.680, g=0.706\n",
            ">9, 52/234, d=0.672, g=0.700\n",
            ">9, 53/234, d=0.671, g=0.710\n",
            ">9, 54/234, d=0.673, g=0.722\n",
            ">9, 55/234, d=0.674, g=0.732\n",
            ">9, 56/234, d=0.671, g=0.743\n",
            ">9, 57/234, d=0.673, g=0.756\n",
            ">9, 58/234, d=0.668, g=0.759\n",
            ">9, 59/234, d=0.670, g=0.759\n",
            ">9, 60/234, d=0.672, g=0.748\n",
            ">9, 61/234, d=0.675, g=0.728\n",
            ">9, 62/234, d=0.685, g=0.709\n",
            ">9, 63/234, d=0.681, g=0.698\n",
            ">9, 64/234, d=0.676, g=0.684\n",
            ">9, 65/234, d=0.673, g=0.669\n",
            ">9, 66/234, d=0.679, g=0.672\n",
            ">9, 67/234, d=0.665, g=0.663\n",
            ">9, 68/234, d=0.670, g=0.662\n",
            ">9, 69/234, d=0.680, g=0.657\n",
            ">9, 70/234, d=0.692, g=0.671\n",
            ">9, 71/234, d=0.684, g=0.701\n",
            ">9, 72/234, d=0.692, g=0.741\n",
            ">9, 73/234, d=0.684, g=0.779\n",
            ">9, 74/234, d=0.674, g=0.801\n",
            ">9, 75/234, d=0.678, g=0.813\n",
            ">9, 76/234, d=0.683, g=0.786\n",
            ">9, 77/234, d=0.689, g=0.762\n",
            ">9, 78/234, d=0.694, g=0.723\n",
            ">9, 79/234, d=0.697, g=0.700\n",
            ">9, 80/234, d=0.684, g=0.677\n",
            ">9, 81/234, d=0.684, g=0.667\n",
            ">9, 82/234, d=0.679, g=0.654\n",
            ">9, 83/234, d=0.669, g=0.649\n",
            ">9, 84/234, d=0.684, g=0.638\n",
            ">9, 85/234, d=0.697, g=0.632\n",
            ">9, 86/234, d=0.700, g=0.639\n",
            ">9, 87/234, d=0.699, g=0.675\n",
            ">9, 88/234, d=0.700, g=0.720\n",
            ">9, 89/234, d=0.686, g=0.772\n",
            ">9, 90/234, d=0.684, g=0.813\n",
            ">9, 91/234, d=0.683, g=0.823\n",
            ">9, 92/234, d=0.680, g=0.799\n",
            ">9, 93/234, d=0.698, g=0.769\n",
            ">9, 94/234, d=0.701, g=0.739\n",
            ">9, 95/234, d=0.704, g=0.702\n",
            ">9, 96/234, d=0.695, g=0.684\n",
            ">9, 97/234, d=0.693, g=0.663\n",
            ">9, 98/234, d=0.696, g=0.663\n",
            ">9, 99/234, d=0.689, g=0.654\n",
            ">9, 100/234, d=0.691, g=0.641\n",
            ">9, 101/234, d=0.699, g=0.645\n",
            ">9, 102/234, d=0.703, g=0.648\n",
            ">9, 103/234, d=0.699, g=0.679\n",
            ">9, 104/234, d=0.700, g=0.713\n",
            ">9, 105/234, d=0.690, g=0.745\n",
            ">9, 106/234, d=0.693, g=0.777\n",
            ">9, 107/234, d=0.699, g=0.775\n",
            ">9, 108/234, d=0.683, g=0.779\n",
            ">9, 109/234, d=0.688, g=0.754\n",
            ">9, 110/234, d=0.693, g=0.734\n",
            ">9, 111/234, d=0.694, g=0.717\n",
            ">9, 112/234, d=0.685, g=0.703\n",
            ">9, 113/234, d=0.682, g=0.693\n",
            ">9, 114/234, d=0.691, g=0.682\n",
            ">9, 115/234, d=0.685, g=0.666\n",
            ">9, 116/234, d=0.677, g=0.665\n",
            ">9, 117/234, d=0.677, g=0.667\n",
            ">9, 118/234, d=0.681, g=0.675\n",
            ">9, 119/234, d=0.692, g=0.683\n",
            ">9, 120/234, d=0.692, g=0.708\n",
            ">9, 121/234, d=0.680, g=0.744\n",
            ">9, 122/234, d=0.678, g=0.755\n",
            ">9, 123/234, d=0.678, g=0.767\n",
            ">9, 124/234, d=0.674, g=0.772\n",
            ">9, 125/234, d=0.682, g=0.764\n",
            ">9, 126/234, d=0.681, g=0.759\n",
            ">9, 127/234, d=0.680, g=0.728\n",
            ">9, 128/234, d=0.674, g=0.717\n",
            ">9, 129/234, d=0.675, g=0.711\n",
            ">9, 130/234, d=0.675, g=0.697\n",
            ">9, 131/234, d=0.676, g=0.688\n",
            ">9, 132/234, d=0.679, g=0.681\n",
            ">9, 133/234, d=0.682, g=0.682\n",
            ">9, 134/234, d=0.688, g=0.689\n",
            ">9, 135/234, d=0.679, g=0.700\n",
            ">9, 136/234, d=0.682, g=0.713\n",
            ">9, 137/234, d=0.692, g=0.720\n",
            ">9, 138/234, d=0.685, g=0.721\n",
            ">9, 139/234, d=0.683, g=0.739\n",
            ">9, 140/234, d=0.680, g=0.737\n",
            ">9, 141/234, d=0.677, g=0.742\n",
            ">9, 142/234, d=0.680, g=0.729\n",
            ">9, 143/234, d=0.679, g=0.724\n",
            ">9, 144/234, d=0.690, g=0.713\n",
            ">9, 145/234, d=0.690, g=0.708\n",
            ">9, 146/234, d=0.687, g=0.705\n",
            ">9, 147/234, d=0.694, g=0.694\n",
            ">9, 148/234, d=0.682, g=0.691\n",
            ">9, 149/234, d=0.684, g=0.685\n",
            ">9, 150/234, d=0.691, g=0.687\n",
            ">9, 151/234, d=0.693, g=0.686\n",
            ">9, 152/234, d=0.687, g=0.682\n",
            ">9, 153/234, d=0.687, g=0.688\n",
            ">9, 154/234, d=0.697, g=0.698\n",
            ">9, 155/234, d=0.691, g=0.703\n",
            ">9, 156/234, d=0.695, g=0.710\n",
            ">9, 157/234, d=0.696, g=0.705\n",
            ">9, 158/234, d=0.694, g=0.716\n",
            ">9, 159/234, d=0.686, g=0.724\n",
            ">9, 160/234, d=0.693, g=0.712\n",
            ">9, 161/234, d=0.697, g=0.714\n",
            ">9, 162/234, d=0.696, g=0.710\n",
            ">9, 163/234, d=0.697, g=0.712\n",
            ">9, 164/234, d=0.694, g=0.710\n",
            ">9, 165/234, d=0.702, g=0.700\n",
            ">9, 166/234, d=0.698, g=0.691\n",
            ">9, 167/234, d=0.694, g=0.697\n",
            ">9, 168/234, d=0.696, g=0.685\n",
            ">9, 169/234, d=0.691, g=0.688\n",
            ">9, 170/234, d=0.684, g=0.685\n",
            ">9, 171/234, d=0.696, g=0.687\n",
            ">9, 172/234, d=0.689, g=0.694\n",
            ">9, 173/234, d=0.686, g=0.697\n",
            ">9, 174/234, d=0.689, g=0.702\n",
            ">9, 175/234, d=0.683, g=0.712\n",
            ">9, 176/234, d=0.685, g=0.713\n",
            ">9, 177/234, d=0.687, g=0.719\n",
            ">9, 178/234, d=0.681, g=0.734\n",
            ">9, 179/234, d=0.678, g=0.728\n",
            ">9, 180/234, d=0.682, g=0.729\n",
            ">9, 181/234, d=0.681, g=0.735\n",
            ">9, 182/234, d=0.688, g=0.726\n",
            ">9, 183/234, d=0.687, g=0.716\n",
            ">9, 184/234, d=0.679, g=0.705\n",
            ">9, 185/234, d=0.676, g=0.700\n",
            ">9, 186/234, d=0.681, g=0.686\n",
            ">9, 187/234, d=0.685, g=0.689\n",
            ">9, 188/234, d=0.675, g=0.683\n",
            ">9, 189/234, d=0.672, g=0.687\n",
            ">9, 190/234, d=0.681, g=0.689\n",
            ">9, 191/234, d=0.682, g=0.708\n",
            ">9, 192/234, d=0.685, g=0.722\n",
            ">9, 193/234, d=0.679, g=0.738\n",
            ">9, 194/234, d=0.683, g=0.755\n",
            ">9, 195/234, d=0.678, g=0.770\n",
            ">9, 196/234, d=0.680, g=0.742\n",
            ">9, 197/234, d=0.684, g=0.730\n",
            ">9, 198/234, d=0.694, g=0.716\n",
            ">9, 199/234, d=0.687, g=0.708\n",
            ">9, 200/234, d=0.684, g=0.690\n",
            ">9, 201/234, d=0.682, g=0.676\n",
            ">9, 202/234, d=0.688, g=0.670\n",
            ">9, 203/234, d=0.696, g=0.668\n",
            ">9, 204/234, d=0.692, g=0.663\n",
            ">9, 205/234, d=0.689, g=0.662\n",
            ">9, 206/234, d=0.686, g=0.668\n",
            ">9, 207/234, d=0.689, g=0.672\n",
            ">9, 208/234, d=0.687, g=0.691\n",
            ">9, 209/234, d=0.690, g=0.710\n",
            ">9, 210/234, d=0.690, g=0.717\n",
            ">9, 211/234, d=0.687, g=0.725\n",
            ">9, 212/234, d=0.685, g=0.739\n",
            ">9, 213/234, d=0.685, g=0.737\n",
            ">9, 214/234, d=0.689, g=0.738\n",
            ">9, 215/234, d=0.684, g=0.739\n",
            ">9, 216/234, d=0.688, g=0.720\n",
            ">9, 217/234, d=0.695, g=0.715\n",
            ">9, 218/234, d=0.692, g=0.697\n",
            ">9, 219/234, d=0.690, g=0.692\n",
            ">9, 220/234, d=0.690, g=0.685\n",
            ">9, 221/234, d=0.693, g=0.678\n",
            ">9, 222/234, d=0.681, g=0.671\n",
            ">9, 223/234, d=0.690, g=0.665\n",
            ">9, 224/234, d=0.689, g=0.668\n",
            ">9, 225/234, d=0.692, g=0.679\n",
            ">9, 226/234, d=0.695, g=0.702\n",
            ">9, 227/234, d=0.691, g=0.728\n",
            ">9, 228/234, d=0.691, g=0.744\n",
            ">9, 229/234, d=0.689, g=0.763\n",
            ">9, 230/234, d=0.687, g=0.755\n",
            ">9, 231/234, d=0.682, g=0.766\n",
            ">9, 232/234, d=0.693, g=0.750\n",
            ">9, 233/234, d=0.694, g=0.733\n",
            ">9, 234/234, d=0.693, g=0.709\n",
            ">10, 1/234, d=0.695, g=0.703\n",
            ">10, 2/234, d=0.692, g=0.684\n",
            ">10, 3/234, d=0.684, g=0.674\n",
            ">10, 4/234, d=0.689, g=0.667\n",
            ">10, 5/234, d=0.690, g=0.670\n",
            ">10, 6/234, d=0.691, g=0.669\n",
            ">10, 7/234, d=0.691, g=0.674\n",
            ">10, 8/234, d=0.696, g=0.685\n",
            ">10, 9/234, d=0.687, g=0.696\n",
            ">10, 10/234, d=0.689, g=0.729\n",
            ">10, 11/234, d=0.678, g=0.751\n",
            ">10, 12/234, d=0.688, g=0.762\n",
            ">10, 13/234, d=0.686, g=0.762\n",
            ">10, 14/234, d=0.683, g=0.754\n",
            ">10, 15/234, d=0.684, g=0.747\n",
            ">10, 16/234, d=0.691, g=0.731\n",
            ">10, 17/234, d=0.688, g=0.718\n",
            ">10, 18/234, d=0.683, g=0.703\n",
            ">10, 19/234, d=0.683, g=0.696\n",
            ">10, 20/234, d=0.687, g=0.686\n",
            ">10, 21/234, d=0.690, g=0.672\n",
            ">10, 22/234, d=0.686, g=0.673\n",
            ">10, 23/234, d=0.678, g=0.675\n",
            ">10, 24/234, d=0.677, g=0.685\n",
            ">10, 25/234, d=0.682, g=0.686\n",
            ">10, 26/234, d=0.687, g=0.706\n",
            ">10, 27/234, d=0.687, g=0.714\n",
            ">10, 28/234, d=0.683, g=0.729\n",
            ">10, 29/234, d=0.682, g=0.751\n",
            ">10, 30/234, d=0.674, g=0.766\n",
            ">10, 31/234, d=0.677, g=0.771\n",
            ">10, 32/234, d=0.677, g=0.759\n",
            ">10, 33/234, d=0.679, g=0.739\n",
            ">10, 34/234, d=0.685, g=0.726\n",
            ">10, 35/234, d=0.684, g=0.710\n",
            ">10, 36/234, d=0.690, g=0.692\n",
            ">10, 37/234, d=0.679, g=0.680\n",
            ">10, 38/234, d=0.675, g=0.665\n",
            ">10, 39/234, d=0.680, g=0.663\n",
            ">10, 40/234, d=0.674, g=0.668\n",
            ">10, 41/234, d=0.685, g=0.684\n",
            ">10, 42/234, d=0.684, g=0.700\n",
            ">10, 43/234, d=0.682, g=0.724\n",
            ">10, 44/234, d=0.684, g=0.742\n",
            ">10, 45/234, d=0.677, g=0.771\n",
            ">10, 46/234, d=0.677, g=0.773\n",
            ">10, 47/234, d=0.679, g=0.776\n",
            ">10, 48/234, d=0.690, g=0.761\n",
            ">10, 49/234, d=0.681, g=0.747\n",
            ">10, 50/234, d=0.682, g=0.722\n",
            ">Accuracy real: 44%, fake: 66%\n",
            ">10, 51/234, d=0.688, g=0.702\n",
            ">10, 52/234, d=0.687, g=0.685\n",
            ">10, 53/234, d=0.685, g=0.673\n",
            ">10, 54/234, d=0.681, g=0.658\n",
            ">10, 55/234, d=0.682, g=0.648\n",
            ">10, 56/234, d=0.685, g=0.649\n",
            ">10, 57/234, d=0.688, g=0.661\n",
            ">10, 58/234, d=0.694, g=0.671\n",
            ">10, 59/234, d=0.694, g=0.691\n",
            ">10, 60/234, d=0.697, g=0.719\n",
            ">10, 61/234, d=0.690, g=0.745\n",
            ">10, 62/234, d=0.686, g=0.759\n",
            ">10, 63/234, d=0.692, g=0.767\n",
            ">10, 64/234, d=0.684, g=0.754\n",
            ">10, 65/234, d=0.686, g=0.736\n",
            ">10, 66/234, d=0.689, g=0.725\n",
            ">10, 67/234, d=0.689, g=0.709\n",
            ">10, 68/234, d=0.697, g=0.690\n",
            ">10, 69/234, d=0.685, g=0.673\n",
            ">10, 70/234, d=0.682, g=0.672\n",
            ">10, 71/234, d=0.686, g=0.669\n",
            ">10, 72/234, d=0.691, g=0.668\n",
            ">10, 73/234, d=0.687, g=0.675\n",
            ">10, 74/234, d=0.687, g=0.672\n",
            ">10, 75/234, d=0.688, g=0.688\n",
            ">10, 76/234, d=0.684, g=0.705\n",
            ">10, 77/234, d=0.688, g=0.716\n",
            ">10, 78/234, d=0.683, g=0.735\n",
            ">10, 79/234, d=0.678, g=0.745\n",
            ">10, 80/234, d=0.683, g=0.757\n",
            ">10, 81/234, d=0.676, g=0.766\n",
            ">10, 82/234, d=0.681, g=0.754\n",
            ">10, 83/234, d=0.685, g=0.740\n",
            ">10, 84/234, d=0.684, g=0.729\n",
            ">10, 85/234, d=0.677, g=0.716\n",
            ">10, 86/234, d=0.677, g=0.707\n",
            ">10, 87/234, d=0.674, g=0.694\n",
            ">10, 88/234, d=0.682, g=0.692\n",
            ">10, 89/234, d=0.670, g=0.680\n",
            ">10, 90/234, d=0.677, g=0.679\n",
            ">10, 91/234, d=0.680, g=0.674\n",
            ">10, 92/234, d=0.675, g=0.676\n",
            ">10, 93/234, d=0.675, g=0.686\n",
            ">10, 94/234, d=0.679, g=0.696\n",
            ">10, 95/234, d=0.685, g=0.719\n",
            ">10, 96/234, d=0.680, g=0.733\n",
            ">10, 97/234, d=0.675, g=0.758\n",
            ">10, 98/234, d=0.684, g=0.766\n",
            ">10, 99/234, d=0.683, g=0.764\n",
            ">10, 100/234, d=0.673, g=0.755\n",
            ">Accuracy real: 40%, fake: 89%\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:3: MatplotlibDeprecationWarning: Adding an axes using the same arguments as a previous axes currently reuses the earlier instance.  In a future version, a new instance will always be created and returned.  Meanwhile, this warning can be suppressed, and the future behavior ensured, by passing a unique label to each axes instance.\n",
            "  This is separate from the ipykernel package so we can avoid doing imports until\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "\u001b[1;30;43mStreaming output truncated to the last 5000 lines.\u001b[0m\n",
            ">79, 162/234, d=0.696, g=0.706\n",
            ">79, 163/234, d=0.692, g=0.693\n",
            ">79, 164/234, d=0.687, g=0.669\n",
            ">79, 165/234, d=0.695, g=0.691\n",
            ">79, 166/234, d=0.688, g=0.732\n",
            ">79, 167/234, d=0.693, g=0.726\n",
            ">79, 168/234, d=0.684, g=0.724\n",
            ">79, 169/234, d=0.691, g=0.695\n",
            ">79, 170/234, d=0.692, g=0.694\n",
            ">79, 171/234, d=0.691, g=0.699\n",
            ">79, 172/234, d=0.691, g=0.707\n",
            ">79, 173/234, d=0.693, g=0.706\n",
            ">79, 174/234, d=0.685, g=0.690\n",
            ">79, 175/234, d=0.690, g=0.687\n",
            ">79, 176/234, d=0.694, g=0.698\n",
            ">79, 177/234, d=0.690, g=0.716\n",
            ">79, 178/234, d=0.690, g=0.689\n",
            ">79, 179/234, d=0.690, g=0.691\n",
            ">79, 180/234, d=0.692, g=0.706\n",
            ">79, 181/234, d=0.693, g=0.713\n",
            ">79, 182/234, d=0.692, g=0.698\n",
            ">79, 183/234, d=0.691, g=0.704\n",
            ">79, 184/234, d=0.690, g=0.693\n",
            ">79, 185/234, d=0.689, g=0.697\n",
            ">79, 186/234, d=0.691, g=0.702\n",
            ">79, 187/234, d=0.689, g=0.708\n",
            ">79, 188/234, d=0.686, g=0.713\n",
            ">79, 189/234, d=0.696, g=0.691\n",
            ">79, 190/234, d=0.693, g=0.679\n",
            ">79, 191/234, d=0.684, g=0.693\n",
            ">79, 192/234, d=0.689, g=0.708\n",
            ">79, 193/234, d=0.695, g=0.722\n",
            ">79, 194/234, d=0.687, g=0.729\n",
            ">79, 195/234, d=0.691, g=0.725\n",
            ">79, 196/234, d=0.695, g=0.713\n",
            ">79, 197/234, d=0.689, g=0.703\n",
            ">79, 198/234, d=0.682, g=0.701\n",
            ">79, 199/234, d=0.692, g=0.704\n",
            ">79, 200/234, d=0.688, g=0.698\n",
            ">79, 201/234, d=0.697, g=0.690\n",
            ">79, 202/234, d=0.681, g=0.688\n",
            ">79, 203/234, d=0.691, g=0.695\n",
            ">79, 204/234, d=0.696, g=0.718\n",
            ">79, 205/234, d=0.687, g=0.720\n",
            ">79, 206/234, d=0.689, g=0.703\n",
            ">79, 207/234, d=0.696, g=0.695\n",
            ">79, 208/234, d=0.693, g=0.682\n",
            ">79, 209/234, d=0.690, g=0.694\n",
            ">79, 210/234, d=0.692, g=0.716\n",
            ">79, 211/234, d=0.692, g=0.727\n",
            ">79, 212/234, d=0.693, g=0.726\n",
            ">79, 213/234, d=0.694, g=0.692\n",
            ">79, 214/234, d=0.696, g=0.669\n",
            ">79, 215/234, d=0.685, g=0.697\n",
            ">79, 216/234, d=0.695, g=0.732\n",
            ">79, 217/234, d=0.692, g=0.710\n",
            ">79, 218/234, d=0.695, g=0.681\n",
            ">79, 219/234, d=0.698, g=0.675\n",
            ">79, 220/234, d=0.702, g=0.688\n",
            ">79, 221/234, d=0.698, g=0.731\n",
            ">79, 222/234, d=0.683, g=0.740\n",
            ">79, 223/234, d=0.688, g=0.716\n",
            ">79, 224/234, d=0.694, g=0.680\n",
            ">79, 225/234, d=0.685, g=0.656\n",
            ">79, 226/234, d=0.693, g=0.692\n",
            ">79, 227/234, d=0.693, g=0.738\n",
            ">79, 228/234, d=0.692, g=0.737\n",
            ">79, 229/234, d=0.691, g=0.706\n",
            ">79, 230/234, d=0.684, g=0.678\n",
            ">79, 231/234, d=0.689, g=0.676\n",
            ">79, 232/234, d=0.693, g=0.691\n",
            ">79, 233/234, d=0.692, g=0.728\n",
            ">79, 234/234, d=0.696, g=0.705\n",
            ">80, 1/234, d=0.690, g=0.686\n",
            ">80, 2/234, d=0.692, g=0.675\n",
            ">80, 3/234, d=0.699, g=0.681\n",
            ">80, 4/234, d=0.692, g=0.712\n",
            ">80, 5/234, d=0.686, g=0.723\n",
            ">80, 6/234, d=0.692, g=0.708\n",
            ">80, 7/234, d=0.695, g=0.697\n",
            ">80, 8/234, d=0.694, g=0.698\n",
            ">80, 9/234, d=0.690, g=0.717\n",
            ">80, 10/234, d=0.691, g=0.700\n",
            ">80, 11/234, d=0.694, g=0.699\n",
            ">80, 12/234, d=0.693, g=0.683\n",
            ">80, 13/234, d=0.682, g=0.691\n",
            ">80, 14/234, d=0.694, g=0.702\n",
            ">80, 15/234, d=0.690, g=0.714\n",
            ">80, 16/234, d=0.691, g=0.716\n",
            ">80, 17/234, d=0.694, g=0.698\n",
            ">80, 18/234, d=0.686, g=0.690\n",
            ">80, 19/234, d=0.686, g=0.691\n",
            ">80, 20/234, d=0.694, g=0.700\n",
            ">80, 21/234, d=0.692, g=0.706\n",
            ">80, 22/234, d=0.687, g=0.724\n",
            ">80, 23/234, d=0.699, g=0.711\n",
            ">80, 24/234, d=0.689, g=0.703\n",
            ">80, 25/234, d=0.683, g=0.691\n",
            ">80, 26/234, d=0.688, g=0.707\n",
            ">80, 27/234, d=0.695, g=0.721\n",
            ">80, 28/234, d=0.692, g=0.691\n",
            ">80, 29/234, d=0.689, g=0.685\n",
            ">80, 30/234, d=0.696, g=0.694\n",
            ">80, 31/234, d=0.698, g=0.712\n",
            ">80, 32/234, d=0.693, g=0.731\n",
            ">80, 33/234, d=0.693, g=0.706\n",
            ">80, 34/234, d=0.690, g=0.699\n",
            ">80, 35/234, d=0.692, g=0.692\n",
            ">80, 36/234, d=0.700, g=0.711\n",
            ">80, 37/234, d=0.696, g=0.680\n",
            ">80, 38/234, d=0.688, g=0.704\n",
            ">80, 39/234, d=0.691, g=0.692\n",
            ">80, 40/234, d=0.690, g=0.702\n",
            ">80, 41/234, d=0.681, g=0.704\n",
            ">80, 42/234, d=0.694, g=0.696\n",
            ">80, 43/234, d=0.695, g=0.701\n",
            ">80, 44/234, d=0.695, g=0.710\n",
            ">80, 45/234, d=0.685, g=0.697\n",
            ">80, 46/234, d=0.697, g=0.706\n",
            ">80, 47/234, d=0.695, g=0.700\n",
            ">80, 48/234, d=0.691, g=0.699\n",
            ">80, 49/234, d=0.687, g=0.665\n",
            ">80, 50/234, d=0.685, g=0.679\n",
            ">Accuracy real: 71%, fake: 56%\n",
            ">80, 51/234, d=0.695, g=0.730\n",
            ">80, 52/234, d=0.689, g=0.746\n",
            ">80, 53/234, d=0.694, g=0.720\n",
            ">80, 54/234, d=0.703, g=0.696\n",
            ">80, 55/234, d=0.692, g=0.682\n",
            ">80, 56/234, d=0.692, g=0.705\n",
            ">80, 57/234, d=0.695, g=0.700\n",
            ">80, 58/234, d=0.693, g=0.688\n",
            ">80, 59/234, d=0.687, g=0.688\n",
            ">80, 60/234, d=0.696, g=0.682\n",
            ">80, 61/234, d=0.687, g=0.717\n",
            ">80, 62/234, d=0.695, g=0.726\n",
            ">80, 63/234, d=0.684, g=0.702\n",
            ">80, 64/234, d=0.682, g=0.682\n",
            ">80, 65/234, d=0.687, g=0.705\n",
            ">80, 66/234, d=0.687, g=0.709\n",
            ">80, 67/234, d=0.694, g=0.705\n",
            ">80, 68/234, d=0.691, g=0.718\n",
            ">80, 69/234, d=0.689, g=0.698\n",
            ">80, 70/234, d=0.691, g=0.687\n",
            ">80, 71/234, d=0.695, g=0.679\n",
            ">80, 72/234, d=0.693, g=0.703\n",
            ">80, 73/234, d=0.694, g=0.709\n",
            ">80, 74/234, d=0.689, g=0.710\n",
            ">80, 75/234, d=0.698, g=0.700\n",
            ">80, 76/234, d=0.687, g=0.723\n",
            ">80, 77/234, d=0.690, g=0.700\n",
            ">80, 78/234, d=0.692, g=0.685\n",
            ">80, 79/234, d=0.688, g=0.690\n",
            ">80, 80/234, d=0.691, g=0.696\n",
            ">80, 81/234, d=0.682, g=0.697\n",
            ">80, 82/234, d=0.695, g=0.702\n",
            ">80, 83/234, d=0.691, g=0.710\n",
            ">80, 84/234, d=0.681, g=0.707\n",
            ">80, 85/234, d=0.693, g=0.716\n",
            ">80, 86/234, d=0.685, g=0.692\n",
            ">80, 87/234, d=0.690, g=0.700\n",
            ">80, 88/234, d=0.681, g=0.705\n",
            ">80, 89/234, d=0.684, g=0.685\n",
            ">80, 90/234, d=0.692, g=0.703\n",
            ">80, 91/234, d=0.689, g=0.703\n",
            ">80, 92/234, d=0.695, g=0.719\n",
            ">80, 93/234, d=0.684, g=0.699\n",
            ">80, 94/234, d=0.685, g=0.689\n",
            ">80, 95/234, d=0.696, g=0.706\n",
            ">80, 96/234, d=0.696, g=0.731\n",
            ">80, 97/234, d=0.694, g=0.704\n",
            ">80, 98/234, d=0.698, g=0.697\n",
            ">80, 99/234, d=0.685, g=0.694\n",
            ">80, 100/234, d=0.693, g=0.678\n",
            ">Accuracy real: 60%, fake: 58%\n",
            ">80, 101/234, d=0.693, g=0.700\n",
            ">80, 102/234, d=0.694, g=0.713\n",
            ">80, 103/234, d=0.697, g=0.714\n",
            ">80, 104/234, d=0.690, g=0.697\n",
            ">80, 105/234, d=0.687, g=0.680\n",
            ">80, 106/234, d=0.692, g=0.676\n",
            ">80, 107/234, d=0.691, g=0.698\n",
            ">80, 108/234, d=0.688, g=0.738\n",
            ">80, 109/234, d=0.680, g=0.744\n",
            ">80, 110/234, d=0.686, g=0.694\n",
            ">80, 111/234, d=0.685, g=0.672\n",
            ">80, 112/234, d=0.699, g=0.675\n",
            ">80, 113/234, d=0.693, g=0.705\n",
            ">80, 114/234, d=0.685, g=0.708\n",
            ">80, 115/234, d=0.685, g=0.707\n",
            ">80, 116/234, d=0.686, g=0.692\n",
            ">80, 117/234, d=0.693, g=0.678\n",
            ">80, 118/234, d=0.697, g=0.707\n",
            ">80, 119/234, d=0.696, g=0.719\n",
            ">80, 120/234, d=0.698, g=0.746\n",
            ">80, 121/234, d=0.688, g=0.716\n",
            ">80, 122/234, d=0.690, g=0.686\n",
            ">80, 123/234, d=0.693, g=0.676\n",
            ">80, 124/234, d=0.691, g=0.700\n",
            ">80, 125/234, d=0.691, g=0.715\n",
            ">80, 126/234, d=0.696, g=0.698\n",
            ">80, 127/234, d=0.679, g=0.691\n",
            ">80, 128/234, d=0.695, g=0.716\n",
            ">80, 129/234, d=0.684, g=0.728\n",
            ">80, 130/234, d=0.691, g=0.733\n",
            ">80, 131/234, d=0.692, g=0.704\n",
            ">80, 132/234, d=0.684, g=0.660\n",
            ">80, 133/234, d=0.687, g=0.666\n",
            ">80, 134/234, d=0.692, g=0.724\n",
            ">80, 135/234, d=0.688, g=0.762\n",
            ">80, 136/234, d=0.700, g=0.732\n",
            ">80, 137/234, d=0.683, g=0.677\n",
            ">80, 138/234, d=0.699, g=0.670\n",
            ">80, 139/234, d=0.688, g=0.666\n",
            ">80, 140/234, d=0.701, g=0.702\n",
            ">80, 141/234, d=0.686, g=0.752\n",
            ">80, 142/234, d=0.687, g=0.738\n",
            ">80, 143/234, d=0.698, g=0.707\n",
            ">80, 144/234, d=0.684, g=0.684\n",
            ">80, 145/234, d=0.686, g=0.699\n",
            ">80, 146/234, d=0.694, g=0.714\n",
            ">80, 147/234, d=0.684, g=0.722\n",
            ">80, 148/234, d=0.689, g=0.717\n",
            ">80, 149/234, d=0.688, g=0.677\n",
            ">80, 150/234, d=0.687, g=0.685\n",
            ">Accuracy real: 58%, fake: 65%\n",
            ">80, 151/234, d=0.694, g=0.713\n",
            ">80, 152/234, d=0.689, g=0.716\n",
            ">80, 153/234, d=0.687, g=0.706\n",
            ">80, 154/234, d=0.691, g=0.685\n",
            ">80, 155/234, d=0.693, g=0.679\n",
            ">80, 156/234, d=0.684, g=0.708\n",
            ">80, 157/234, d=0.697, g=0.721\n",
            ">80, 158/234, d=0.683, g=0.713\n",
            ">80, 159/234, d=0.682, g=0.693\n",
            ">80, 160/234, d=0.683, g=0.697\n",
            ">80, 161/234, d=0.682, g=0.710\n",
            ">80, 162/234, d=0.689, g=0.708\n",
            ">80, 163/234, d=0.686, g=0.695\n",
            ">80, 164/234, d=0.690, g=0.681\n",
            ">80, 165/234, d=0.688, g=0.688\n",
            ">80, 166/234, d=0.694, g=0.732\n",
            ">80, 167/234, d=0.695, g=0.727\n",
            ">80, 168/234, d=0.692, g=0.700\n",
            ">80, 169/234, d=0.680, g=0.685\n",
            ">80, 170/234, d=0.694, g=0.684\n",
            ">80, 171/234, d=0.691, g=0.711\n",
            ">80, 172/234, d=0.692, g=0.718\n",
            ">80, 173/234, d=0.688, g=0.710\n",
            ">80, 174/234, d=0.691, g=0.697\n",
            ">80, 175/234, d=0.692, g=0.696\n",
            ">80, 176/234, d=0.688, g=0.698\n",
            ">80, 177/234, d=0.688, g=0.710\n",
            ">80, 178/234, d=0.691, g=0.713\n",
            ">80, 179/234, d=0.690, g=0.721\n",
            ">80, 180/234, d=0.696, g=0.715\n",
            ">80, 181/234, d=0.684, g=0.683\n",
            ">80, 182/234, d=0.690, g=0.666\n",
            ">80, 183/234, d=0.695, g=0.711\n",
            ">80, 184/234, d=0.688, g=0.731\n",
            ">80, 185/234, d=0.699, g=0.737\n",
            ">80, 186/234, d=0.691, g=0.685\n",
            ">80, 187/234, d=0.693, g=0.662\n",
            ">80, 188/234, d=0.689, g=0.670\n",
            ">80, 189/234, d=0.694, g=0.694\n",
            ">80, 190/234, d=0.684, g=0.724\n",
            ">80, 191/234, d=0.684, g=0.737\n",
            ">80, 192/234, d=0.687, g=0.705\n",
            ">80, 193/234, d=0.691, g=0.684\n",
            ">80, 194/234, d=0.694, g=0.683\n",
            ">80, 195/234, d=0.680, g=0.706\n",
            ">80, 196/234, d=0.684, g=0.694\n",
            ">80, 197/234, d=0.697, g=0.695\n",
            ">80, 198/234, d=0.693, g=0.691\n",
            ">80, 199/234, d=0.691, g=0.711\n",
            ">80, 200/234, d=0.687, g=0.730\n",
            ">Accuracy real: 5%, fake: 100%\n",
            ">80, 201/234, d=0.685, g=0.712\n",
            ">80, 202/234, d=0.695, g=0.690\n",
            ">80, 203/234, d=0.686, g=0.663\n",
            ">80, 204/234, d=0.692, g=0.678\n",
            ">80, 205/234, d=0.687, g=0.737\n",
            ">80, 206/234, d=0.696, g=0.749\n",
            ">80, 207/234, d=0.698, g=0.719\n",
            ">80, 208/234, d=0.688, g=0.688\n",
            ">80, 209/234, d=0.679, g=0.677\n",
            ">80, 210/234, d=0.689, g=0.690\n",
            ">80, 211/234, d=0.694, g=0.713\n",
            ">80, 212/234, d=0.687, g=0.711\n",
            ">80, 213/234, d=0.692, g=0.696\n",
            ">80, 214/234, d=0.686, g=0.677\n",
            ">80, 215/234, d=0.687, g=0.673\n",
            ">80, 216/234, d=0.692, g=0.695\n",
            ">80, 217/234, d=0.689, g=0.733\n",
            ">80, 218/234, d=0.687, g=0.723\n",
            ">80, 219/234, d=0.689, g=0.716\n",
            ">80, 220/234, d=0.691, g=0.707\n",
            ">80, 221/234, d=0.687, g=0.690\n",
            ">80, 222/234, d=0.693, g=0.665\n",
            ">80, 223/234, d=0.693, g=0.670\n",
            ">80, 224/234, d=0.690, g=0.704\n",
            ">80, 225/234, d=0.689, g=0.723\n",
            ">80, 226/234, d=0.693, g=0.724\n",
            ">80, 227/234, d=0.693, g=0.722\n",
            ">80, 228/234, d=0.700, g=0.700\n",
            ">80, 229/234, d=0.688, g=0.711\n",
            ">80, 230/234, d=0.691, g=0.709\n",
            ">80, 231/234, d=0.687, g=0.714\n",
            ">80, 232/234, d=0.688, g=0.705\n",
            ">80, 233/234, d=0.687, g=0.699\n",
            ">80, 234/234, d=0.691, g=0.717\n",
            ">81, 1/234, d=0.689, g=0.698\n",
            ">81, 2/234, d=0.692, g=0.702\n",
            ">81, 3/234, d=0.696, g=0.685\n",
            ">81, 4/234, d=0.684, g=0.688\n",
            ">81, 5/234, d=0.683, g=0.704\n",
            ">81, 6/234, d=0.690, g=0.721\n",
            ">81, 7/234, d=0.690, g=0.724\n",
            ">81, 8/234, d=0.689, g=0.680\n",
            ">81, 9/234, d=0.691, g=0.657\n",
            ">81, 10/234, d=0.692, g=0.695\n",
            ">81, 11/234, d=0.688, g=0.711\n",
            ">81, 12/234, d=0.688, g=0.721\n",
            ">81, 13/234, d=0.691, g=0.712\n",
            ">81, 14/234, d=0.699, g=0.692\n",
            ">81, 15/234, d=0.695, g=0.681\n",
            ">81, 16/234, d=0.696, g=0.694\n",
            ">81, 17/234, d=0.692, g=0.687\n",
            ">81, 18/234, d=0.686, g=0.708\n",
            ">81, 19/234, d=0.690, g=0.722\n",
            ">81, 20/234, d=0.689, g=0.708\n",
            ">81, 21/234, d=0.694, g=0.687\n",
            ">81, 22/234, d=0.697, g=0.698\n",
            ">81, 23/234, d=0.701, g=0.721\n",
            ">81, 24/234, d=0.691, g=0.706\n",
            ">81, 25/234, d=0.689, g=0.699\n",
            ">81, 26/234, d=0.695, g=0.697\n",
            ">81, 27/234, d=0.688, g=0.707\n",
            ">81, 28/234, d=0.692, g=0.721\n",
            ">81, 29/234, d=0.691, g=0.713\n",
            ">81, 30/234, d=0.688, g=0.713\n",
            ">81, 31/234, d=0.686, g=0.680\n",
            ">81, 32/234, d=0.693, g=0.674\n",
            ">81, 33/234, d=0.689, g=0.672\n",
            ">81, 34/234, d=0.693, g=0.699\n",
            ">81, 35/234, d=0.696, g=0.706\n",
            ">81, 36/234, d=0.682, g=0.693\n",
            ">81, 37/234, d=0.693, g=0.701\n",
            ">81, 38/234, d=0.681, g=0.706\n",
            ">81, 39/234, d=0.695, g=0.699\n",
            ">81, 40/234, d=0.692, g=0.697\n",
            ">81, 41/234, d=0.691, g=0.696\n",
            ">81, 42/234, d=0.692, g=0.708\n",
            ">81, 43/234, d=0.688, g=0.731\n",
            ">81, 44/234, d=0.688, g=0.713\n",
            ">81, 45/234, d=0.695, g=0.695\n",
            ">81, 46/234, d=0.697, g=0.666\n",
            ">81, 47/234, d=0.689, g=0.668\n",
            ">81, 48/234, d=0.692, g=0.691\n",
            ">81, 49/234, d=0.698, g=0.727\n",
            ">81, 50/234, d=0.683, g=0.727\n",
            ">81, 51/234, d=0.696, g=0.699\n",
            ">81, 52/234, d=0.689, g=0.682\n",
            ">81, 53/234, d=0.687, g=0.701\n",
            ">81, 54/234, d=0.692, g=0.722\n",
            ">81, 55/234, d=0.696, g=0.728\n",
            ">81, 56/234, d=0.694, g=0.698\n",
            ">81, 57/234, d=0.696, g=0.689\n",
            ">81, 58/234, d=0.694, g=0.686\n",
            ">81, 59/234, d=0.695, g=0.691\n",
            ">81, 60/234, d=0.683, g=0.698\n",
            ">81, 61/234, d=0.684, g=0.702\n",
            ">81, 62/234, d=0.698, g=0.723\n",
            ">81, 63/234, d=0.685, g=0.730\n",
            ">81, 64/234, d=0.696, g=0.706\n",
            ">81, 65/234, d=0.692, g=0.680\n",
            ">81, 66/234, d=0.690, g=0.695\n",
            ">81, 67/234, d=0.686, g=0.682\n",
            ">81, 68/234, d=0.696, g=0.710\n",
            ">81, 69/234, d=0.689, g=0.710\n",
            ">81, 70/234, d=0.684, g=0.697\n",
            ">81, 71/234, d=0.693, g=0.676\n",
            ">81, 72/234, d=0.693, g=0.692\n",
            ">81, 73/234, d=0.694, g=0.702\n",
            ">81, 74/234, d=0.684, g=0.720\n",
            ">81, 75/234, d=0.694, g=0.712\n",
            ">81, 76/234, d=0.695, g=0.697\n",
            ">81, 77/234, d=0.685, g=0.695\n",
            ">81, 78/234, d=0.690, g=0.705\n",
            ">81, 79/234, d=0.695, g=0.714\n",
            ">81, 80/234, d=0.689, g=0.698\n",
            ">81, 81/234, d=0.692, g=0.708\n",
            ">81, 82/234, d=0.693, g=0.712\n",
            ">81, 83/234, d=0.693, g=0.709\n",
            ">81, 84/234, d=0.691, g=0.691\n",
            ">81, 85/234, d=0.697, g=0.681\n",
            ">81, 86/234, d=0.688, g=0.692\n",
            ">81, 87/234, d=0.690, g=0.714\n",
            ">81, 88/234, d=0.693, g=0.701\n",
            ">81, 89/234, d=0.694, g=0.695\n",
            ">81, 90/234, d=0.694, g=0.696\n",
            ">81, 91/234, d=0.693, g=0.692\n",
            ">81, 92/234, d=0.687, g=0.696\n",
            ">81, 93/234, d=0.693, g=0.709\n",
            ">81, 94/234, d=0.706, g=0.704\n",
            ">81, 95/234, d=0.689, g=0.703\n",
            ">81, 96/234, d=0.692, g=0.705\n",
            ">81, 97/234, d=0.690, g=0.703\n",
            ">81, 98/234, d=0.686, g=0.703\n",
            ">81, 99/234, d=0.689, g=0.701\n",
            ">81, 100/234, d=0.690, g=0.689\n",
            ">81, 101/234, d=0.693, g=0.688\n",
            ">81, 102/234, d=0.687, g=0.690\n",
            ">81, 103/234, d=0.688, g=0.699\n",
            ">81, 104/234, d=0.693, g=0.709\n",
            ">81, 105/234, d=0.684, g=0.709\n",
            ">81, 106/234, d=0.687, g=0.707\n",
            ">81, 107/234, d=0.693, g=0.693\n",
            ">81, 108/234, d=0.691, g=0.694\n",
            ">81, 109/234, d=0.697, g=0.695\n",
            ">81, 110/234, d=0.699, g=0.704\n",
            ">81, 111/234, d=0.688, g=0.713\n",
            ">81, 112/234, d=0.691, g=0.703\n",
            ">81, 113/234, d=0.688, g=0.692\n",
            ">81, 114/234, d=0.705, g=0.701\n",
            ">81, 115/234, d=0.695, g=0.712\n",
            ">81, 116/234, d=0.689, g=0.701\n",
            ">81, 117/234, d=0.697, g=0.701\n",
            ">81, 118/234, d=0.690, g=0.696\n",
            ">81, 119/234, d=0.686, g=0.684\n",
            ">81, 120/234, d=0.687, g=0.675\n",
            ">81, 121/234, d=0.691, g=0.702\n",
            ">81, 122/234, d=0.687, g=0.726\n",
            ">81, 123/234, d=0.690, g=0.715\n",
            ">81, 124/234, d=0.692, g=0.697\n",
            ">81, 125/234, d=0.693, g=0.677\n",
            ">81, 126/234, d=0.692, g=0.694\n",
            ">81, 127/234, d=0.686, g=0.717\n",
            ">81, 128/234, d=0.692, g=0.717\n",
            ">81, 129/234, d=0.687, g=0.711\n",
            ">81, 130/234, d=0.692, g=0.704\n",
            ">81, 131/234, d=0.684, g=0.709\n",
            ">81, 132/234, d=0.692, g=0.700\n",
            ">81, 133/234, d=0.690, g=0.690\n",
            ">81, 134/234, d=0.688, g=0.691\n",
            ">81, 135/234, d=0.685, g=0.699\n",
            ">81, 136/234, d=0.693, g=0.709\n",
            ">81, 137/234, d=0.690, g=0.696\n",
            ">81, 138/234, d=0.682, g=0.703\n",
            ">81, 139/234, d=0.689, g=0.679\n",
            ">81, 140/234, d=0.690, g=0.695\n",
            ">81, 141/234, d=0.690, g=0.692\n",
            ">81, 142/234, d=0.684, g=0.688\n",
            ">81, 143/234, d=0.691, g=0.701\n",
            ">81, 144/234, d=0.695, g=0.715\n",
            ">81, 145/234, d=0.689, g=0.715\n",
            ">81, 146/234, d=0.692, g=0.714\n",
            ">81, 147/234, d=0.684, g=0.698\n",
            ">81, 148/234, d=0.689, g=0.695\n",
            ">81, 149/234, d=0.689, g=0.691\n",
            ">81, 150/234, d=0.696, g=0.705\n",
            ">81, 151/234, d=0.697, g=0.706\n",
            ">81, 152/234, d=0.687, g=0.691\n",
            ">81, 153/234, d=0.687, g=0.697\n",
            ">81, 154/234, d=0.686, g=0.700\n",
            ">81, 155/234, d=0.699, g=0.710\n",
            ">81, 156/234, d=0.684, g=0.723\n",
            ">81, 157/234, d=0.689, g=0.701\n",
            ">81, 158/234, d=0.689, g=0.685\n",
            ">81, 159/234, d=0.692, g=0.698\n",
            ">81, 160/234, d=0.686, g=0.694\n",
            ">81, 161/234, d=0.691, g=0.690\n",
            ">81, 162/234, d=0.689, g=0.700\n",
            ">81, 163/234, d=0.688, g=0.704\n",
            ">81, 164/234, d=0.701, g=0.707\n",
            ">81, 165/234, d=0.694, g=0.709\n",
            ">81, 166/234, d=0.699, g=0.698\n",
            ">81, 167/234, d=0.693, g=0.724\n",
            ">81, 168/234, d=0.692, g=0.727\n",
            ">81, 169/234, d=0.687, g=0.700\n",
            ">81, 170/234, d=0.693, g=0.676\n",
            ">81, 171/234, d=0.694, g=0.679\n",
            ">81, 172/234, d=0.691, g=0.694\n",
            ">81, 173/234, d=0.693, g=0.705\n",
            ">81, 174/234, d=0.687, g=0.715\n",
            ">81, 175/234, d=0.689, g=0.713\n",
            ">81, 176/234, d=0.700, g=0.716\n",
            ">81, 177/234, d=0.698, g=0.704\n",
            ">81, 178/234, d=0.694, g=0.692\n",
            ">81, 179/234, d=0.688, g=0.700\n",
            ">81, 180/234, d=0.694, g=0.709\n",
            ">81, 181/234, d=0.696, g=0.721\n",
            ">81, 182/234, d=0.688, g=0.697\n",
            ">81, 183/234, d=0.689, g=0.679\n",
            ">81, 184/234, d=0.691, g=0.698\n",
            ">81, 185/234, d=0.688, g=0.702\n",
            ">81, 186/234, d=0.695, g=0.708\n",
            ">81, 187/234, d=0.688, g=0.698\n",
            ">81, 188/234, d=0.696, g=0.694\n",
            ">81, 189/234, d=0.692, g=0.714\n",
            ">81, 190/234, d=0.690, g=0.705\n",
            ">81, 191/234, d=0.697, g=0.704\n",
            ">81, 192/234, d=0.698, g=0.683\n",
            ">81, 193/234, d=0.691, g=0.678\n",
            ">81, 194/234, d=0.692, g=0.692\n",
            ">81, 195/234, d=0.680, g=0.721\n",
            ">81, 196/234, d=0.689, g=0.720\n",
            ">81, 197/234, d=0.691, g=0.705\n",
            ">81, 198/234, d=0.691, g=0.688\n",
            ">81, 199/234, d=0.690, g=0.679\n",
            ">81, 200/234, d=0.693, g=0.679\n",
            ">81, 201/234, d=0.689, g=0.701\n",
            ">81, 202/234, d=0.692, g=0.715\n",
            ">81, 203/234, d=0.686, g=0.707\n",
            ">81, 204/234, d=0.686, g=0.692\n",
            ">81, 205/234, d=0.687, g=0.699\n",
            ">81, 206/234, d=0.685, g=0.708\n",
            ">81, 207/234, d=0.693, g=0.713\n",
            ">81, 208/234, d=0.685, g=0.709\n",
            ">81, 209/234, d=0.688, g=0.695\n",
            ">81, 210/234, d=0.695, g=0.706\n",
            ">81, 211/234, d=0.690, g=0.695\n",
            ">81, 212/234, d=0.690, g=0.691\n",
            ">81, 213/234, d=0.685, g=0.700\n",
            ">81, 214/234, d=0.690, g=0.708\n",
            ">81, 215/234, d=0.695, g=0.698\n",
            ">81, 216/234, d=0.682, g=0.708\n",
            ">81, 217/234, d=0.694, g=0.704\n",
            ">81, 218/234, d=0.684, g=0.696\n",
            ">81, 219/234, d=0.695, g=0.683\n",
            ">81, 220/234, d=0.696, g=0.693\n",
            ">81, 221/234, d=0.692, g=0.701\n",
            ">81, 222/234, d=0.695, g=0.705\n",
            ">81, 223/234, d=0.693, g=0.689\n",
            ">81, 224/234, d=0.692, g=0.719\n",
            ">81, 225/234, d=0.687, g=0.722\n",
            ">81, 226/234, d=0.681, g=0.709\n",
            ">81, 227/234, d=0.689, g=0.708\n",
            ">81, 228/234, d=0.694, g=0.705\n",
            ">81, 229/234, d=0.692, g=0.698\n",
            ">81, 230/234, d=0.686, g=0.687\n",
            ">81, 231/234, d=0.694, g=0.685\n",
            ">81, 232/234, d=0.686, g=0.674\n",
            ">81, 233/234, d=0.692, g=0.687\n",
            ">81, 234/234, d=0.687, g=0.710\n",
            ">82, 1/234, d=0.697, g=0.707\n",
            ">82, 2/234, d=0.692, g=0.714\n",
            ">82, 3/234, d=0.693, g=0.721\n",
            ">82, 4/234, d=0.685, g=0.708\n",
            ">82, 5/234, d=0.686, g=0.702\n",
            ">82, 6/234, d=0.688, g=0.689\n",
            ">82, 7/234, d=0.694, g=0.691\n",
            ">82, 8/234, d=0.681, g=0.711\n",
            ">82, 9/234, d=0.689, g=0.721\n",
            ">82, 10/234, d=0.696, g=0.702\n",
            ">82, 11/234, d=0.689, g=0.689\n",
            ">82, 12/234, d=0.690, g=0.712\n",
            ">82, 13/234, d=0.698, g=0.701\n",
            ">82, 14/234, d=0.692, g=0.699\n",
            ">82, 15/234, d=0.690, g=0.703\n",
            ">82, 16/234, d=0.683, g=0.724\n",
            ">82, 17/234, d=0.702, g=0.723\n",
            ">82, 18/234, d=0.695, g=0.706\n",
            ">82, 19/234, d=0.692, g=0.702\n",
            ">82, 20/234, d=0.680, g=0.695\n",
            ">82, 21/234, d=0.689, g=0.689\n",
            ">82, 22/234, d=0.689, g=0.692\n",
            ">82, 23/234, d=0.697, g=0.695\n",
            ">82, 24/234, d=0.704, g=0.713\n",
            ">82, 25/234, d=0.693, g=0.748\n",
            ">82, 26/234, d=0.684, g=0.726\n",
            ">82, 27/234, d=0.686, g=0.707\n",
            ">82, 28/234, d=0.694, g=0.673\n",
            ">82, 29/234, d=0.687, g=0.690\n",
            ">82, 30/234, d=0.687, g=0.686\n",
            ">82, 31/234, d=0.687, g=0.719\n",
            ">82, 32/234, d=0.691, g=0.729\n",
            ">82, 33/234, d=0.689, g=0.722\n",
            ">82, 34/234, d=0.686, g=0.684\n",
            ">82, 35/234, d=0.692, g=0.676\n",
            ">82, 36/234, d=0.685, g=0.699\n",
            ">82, 37/234, d=0.681, g=0.702\n",
            ">82, 38/234, d=0.700, g=0.705\n",
            ">82, 39/234, d=0.698, g=0.679\n",
            ">82, 40/234, d=0.684, g=0.703\n",
            ">82, 41/234, d=0.684, g=0.701\n",
            ">82, 42/234, d=0.699, g=0.703\n",
            ">82, 43/234, d=0.692, g=0.689\n",
            ">82, 44/234, d=0.690, g=0.696\n",
            ">82, 45/234, d=0.687, g=0.703\n",
            ">82, 46/234, d=0.695, g=0.711\n",
            ">82, 47/234, d=0.693, g=0.723\n",
            ">82, 48/234, d=0.685, g=0.714\n",
            ">82, 49/234, d=0.684, g=0.695\n",
            ">82, 50/234, d=0.687, g=0.687\n",
            ">82, 51/234, d=0.689, g=0.695\n",
            ">82, 52/234, d=0.695, g=0.688\n",
            ">82, 53/234, d=0.690, g=0.700\n",
            ">82, 54/234, d=0.687, g=0.706\n",
            ">82, 55/234, d=0.686, g=0.701\n",
            ">82, 56/234, d=0.684, g=0.686\n",
            ">82, 57/234, d=0.693, g=0.686\n",
            ">82, 58/234, d=0.696, g=0.718\n",
            ">82, 59/234, d=0.693, g=0.717\n",
            ">82, 60/234, d=0.700, g=0.709\n",
            ">82, 61/234, d=0.687, g=0.693\n",
            ">82, 62/234, d=0.688, g=0.683\n",
            ">82, 63/234, d=0.692, g=0.701\n",
            ">82, 64/234, d=0.696, g=0.705\n",
            ">82, 65/234, d=0.691, g=0.718\n",
            ">82, 66/234, d=0.689, g=0.702\n",
            ">82, 67/234, d=0.695, g=0.695\n",
            ">82, 68/234, d=0.690, g=0.707\n",
            ">82, 69/234, d=0.693, g=0.709\n",
            ">82, 70/234, d=0.694, g=0.706\n",
            ">82, 71/234, d=0.695, g=0.682\n",
            ">82, 72/234, d=0.688, g=0.683\n",
            ">82, 73/234, d=0.692, g=0.718\n",
            ">82, 74/234, d=0.689, g=0.728\n",
            ">82, 75/234, d=0.682, g=0.698\n",
            ">82, 76/234, d=0.692, g=0.674\n",
            ">82, 77/234, d=0.682, g=0.689\n",
            ">82, 78/234, d=0.695, g=0.714\n",
            ">82, 79/234, d=0.689, g=0.726\n",
            ">82, 80/234, d=0.681, g=0.704\n",
            ">82, 81/234, d=0.688, g=0.689\n",
            ">82, 82/234, d=0.688, g=0.686\n",
            ">82, 83/234, d=0.691, g=0.692\n",
            ">82, 84/234, d=0.691, g=0.712\n",
            ">82, 85/234, d=0.686, g=0.715\n",
            ">82, 86/234, d=0.699, g=0.692\n",
            ">82, 87/234, d=0.680, g=0.694\n",
            ">82, 88/234, d=0.691, g=0.701\n",
            ">82, 89/234, d=0.693, g=0.725\n",
            ">82, 90/234, d=0.690, g=0.715\n",
            ">82, 91/234, d=0.692, g=0.700\n",
            ">82, 92/234, d=0.692, g=0.700\n",
            ">82, 93/234, d=0.688, g=0.705\n",
            ">82, 94/234, d=0.690, g=0.695\n",
            ">82, 95/234, d=0.694, g=0.692\n",
            ">82, 96/234, d=0.696, g=0.687\n",
            ">82, 97/234, d=0.685, g=0.701\n",
            ">82, 98/234, d=0.695, g=0.703\n",
            ">82, 99/234, d=0.688, g=0.708\n",
            ">82, 100/234, d=0.697, g=0.702\n",
            ">82, 101/234, d=0.685, g=0.691\n",
            ">82, 102/234, d=0.689, g=0.705\n",
            ">82, 103/234, d=0.692, g=0.708\n",
            ">82, 104/234, d=0.684, g=0.703\n",
            ">82, 105/234, d=0.698, g=0.710\n",
            ">82, 106/234, d=0.693, g=0.704\n",
            ">82, 107/234, d=0.693, g=0.684\n",
            ">82, 108/234, d=0.695, g=0.690\n",
            ">82, 109/234, d=0.690, g=0.694\n",
            ">82, 110/234, d=0.690, g=0.714\n",
            ">82, 111/234, d=0.691, g=0.698\n",
            ">82, 112/234, d=0.687, g=0.689\n",
            ">82, 113/234, d=0.687, g=0.686\n",
            ">82, 114/234, d=0.697, g=0.713\n",
            ">82, 115/234, d=0.690, g=0.726\n",
            ">82, 116/234, d=0.687, g=0.697\n",
            ">82, 117/234, d=0.689, g=0.700\n",
            ">82, 118/234, d=0.693, g=0.704\n",
            ">82, 119/234, d=0.698, g=0.708\n",
            ">82, 120/234, d=0.694, g=0.720\n",
            ">82, 121/234, d=0.701, g=0.702\n",
            ">82, 122/234, d=0.689, g=0.696\n",
            ">82, 123/234, d=0.687, g=0.690\n",
            ">82, 124/234, d=0.694, g=0.686\n",
            ">82, 125/234, d=0.688, g=0.704\n",
            ">82, 126/234, d=0.687, g=0.737\n",
            ">82, 127/234, d=0.687, g=0.722\n",
            ">82, 128/234, d=0.690, g=0.700\n",
            ">82, 129/234, d=0.694, g=0.673\n",
            ">82, 130/234, d=0.689, g=0.677\n",
            ">82, 131/234, d=0.685, g=0.693\n",
            ">82, 132/234, d=0.690, g=0.720\n",
            ">82, 133/234, d=0.695, g=0.714\n",
            ">82, 134/234, d=0.693, g=0.734\n",
            ">82, 135/234, d=0.703, g=0.727\n",
            ">82, 136/234, d=0.696, g=0.688\n",
            ">82, 137/234, d=0.686, g=0.649\n",
            ">82, 138/234, d=0.692, g=0.668\n",
            ">82, 139/234, d=0.691, g=0.714\n",
            ">82, 140/234, d=0.690, g=0.751\n",
            ">82, 141/234, d=0.697, g=0.748\n",
            ">82, 142/234, d=0.694, g=0.715\n",
            ">82, 143/234, d=0.691, g=0.690\n",
            ">82, 144/234, d=0.687, g=0.683\n",
            ">82, 145/234, d=0.696, g=0.685\n",
            ">82, 146/234, d=0.692, g=0.694\n",
            ">82, 147/234, d=0.692, g=0.706\n",
            ">82, 148/234, d=0.688, g=0.701\n",
            ">82, 149/234, d=0.685, g=0.693\n",
            ">82, 150/234, d=0.689, g=0.692\n",
            ">82, 151/234, d=0.692, g=0.694\n",
            ">82, 152/234, d=0.689, g=0.711\n",
            ">82, 153/234, d=0.686, g=0.708\n",
            ">82, 154/234, d=0.687, g=0.708\n",
            ">82, 155/234, d=0.692, g=0.742\n",
            ">82, 156/234, d=0.695, g=0.719\n",
            ">82, 157/234, d=0.693, g=0.699\n",
            ">82, 158/234, d=0.690, g=0.685\n",
            ">82, 159/234, d=0.707, g=0.693\n",
            ">82, 160/234, d=0.699, g=0.693\n",
            ">82, 161/234, d=0.690, g=0.699\n",
            ">82, 162/234, d=0.697, g=0.706\n",
            ">82, 163/234, d=0.698, g=0.702\n",
            ">82, 164/234, d=0.690, g=0.703\n",
            ">82, 165/234, d=0.681, g=0.731\n",
            ">82, 166/234, d=0.695, g=0.721\n",
            ">82, 167/234, d=0.693, g=0.720\n",
            ">82, 168/234, d=0.689, g=0.695\n",
            ">82, 169/234, d=0.692, g=0.690\n",
            ">82, 170/234, d=0.695, g=0.689\n",
            ">82, 171/234, d=0.693, g=0.678\n",
            ">82, 172/234, d=0.687, g=0.696\n",
            ">82, 173/234, d=0.682, g=0.712\n",
            ">82, 174/234, d=0.701, g=0.722\n",
            ">82, 175/234, d=0.690, g=0.710\n",
            ">82, 176/234, d=0.698, g=0.707\n",
            ">82, 177/234, d=0.695, g=0.715\n",
            ">82, 178/234, d=0.688, g=0.696\n",
            ">82, 179/234, d=0.691, g=0.693\n",
            ">82, 180/234, d=0.690, g=0.698\n",
            ">82, 181/234, d=0.689, g=0.709\n",
            ">82, 182/234, d=0.692, g=0.707\n",
            ">82, 183/234, d=0.689, g=0.700\n",
            ">82, 184/234, d=0.692, g=0.695\n",
            ">82, 185/234, d=0.696, g=0.691\n",
            ">82, 186/234, d=0.689, g=0.698\n",
            ">82, 187/234, d=0.694, g=0.710\n",
            ">82, 188/234, d=0.683, g=0.729\n",
            ">82, 189/234, d=0.697, g=0.725\n",
            ">82, 190/234, d=0.699, g=0.701\n",
            ">82, 191/234, d=0.688, g=0.682\n",
            ">82, 192/234, d=0.685, g=0.682\n",
            ">82, 193/234, d=0.692, g=0.700\n",
            ">82, 194/234, d=0.689, g=0.713\n",
            ">82, 195/234, d=0.694, g=0.690\n",
            ">82, 196/234, d=0.695, g=0.700\n",
            ">82, 197/234, d=0.694, g=0.694\n",
            ">82, 198/234, d=0.691, g=0.696\n",
            ">82, 199/234, d=0.689, g=0.698\n",
            ">82, 200/234, d=0.695, g=0.720\n",
            ">82, 201/234, d=0.694, g=0.723\n",
            ">82, 202/234, d=0.684, g=0.714\n",
            ">82, 203/234, d=0.695, g=0.698\n",
            ">82, 204/234, d=0.692, g=0.695\n",
            ">82, 205/234, d=0.698, g=0.702\n",
            ">82, 206/234, d=0.687, g=0.705\n",
            ">82, 207/234, d=0.692, g=0.682\n",
            ">82, 208/234, d=0.692, g=0.707\n",
            ">82, 209/234, d=0.693, g=0.720\n",
            ">82, 210/234, d=0.691, g=0.714\n",
            ">82, 211/234, d=0.692, g=0.734\n",
            ">82, 212/234, d=0.692, g=0.717\n",
            ">82, 213/234, d=0.698, g=0.718\n",
            ">82, 214/234, d=0.694, g=0.702\n",
            ">82, 215/234, d=0.693, g=0.683\n",
            ">82, 216/234, d=0.696, g=0.702\n",
            ">82, 217/234, d=0.694, g=0.709\n",
            ">82, 218/234, d=0.700, g=0.697\n",
            ">82, 219/234, d=0.688, g=0.694\n",
            ">82, 220/234, d=0.691, g=0.691\n",
            ">82, 221/234, d=0.685, g=0.700\n",
            ">82, 222/234, d=0.693, g=0.695\n",
            ">82, 223/234, d=0.680, g=0.678\n",
            ">82, 224/234, d=0.692, g=0.701\n",
            ">82, 225/234, d=0.698, g=0.715\n",
            ">82, 226/234, d=0.693, g=0.710\n",
            ">82, 227/234, d=0.681, g=0.712\n",
            ">82, 228/234, d=0.695, g=0.702\n",
            ">82, 229/234, d=0.690, g=0.698\n",
            ">82, 230/234, d=0.694, g=0.707\n",
            ">82, 231/234, d=0.690, g=0.696\n",
            ">82, 232/234, d=0.686, g=0.690\n",
            ">82, 233/234, d=0.687, g=0.689\n",
            ">82, 234/234, d=0.682, g=0.690\n",
            ">83, 1/234, d=0.697, g=0.726\n",
            ">83, 2/234, d=0.690, g=0.722\n",
            ">83, 3/234, d=0.697, g=0.698\n",
            ">83, 4/234, d=0.691, g=0.685\n",
            ">83, 5/234, d=0.695, g=0.697\n",
            ">83, 6/234, d=0.694, g=0.710\n",
            ">83, 7/234, d=0.683, g=0.699\n",
            ">83, 8/234, d=0.694, g=0.702\n",
            ">83, 9/234, d=0.684, g=0.695\n",
            ">83, 10/234, d=0.691, g=0.692\n",
            ">83, 11/234, d=0.696, g=0.692\n",
            ">83, 12/234, d=0.698, g=0.711\n",
            ">83, 13/234, d=0.690, g=0.720\n",
            ">83, 14/234, d=0.687, g=0.700\n",
            ">83, 15/234, d=0.692, g=0.696\n",
            ">83, 16/234, d=0.690, g=0.717\n",
            ">83, 17/234, d=0.693, g=0.722\n",
            ">83, 18/234, d=0.687, g=0.709\n",
            ">83, 19/234, d=0.691, g=0.701\n",
            ">83, 20/234, d=0.690, g=0.689\n",
            ">83, 21/234, d=0.686, g=0.697\n",
            ">83, 22/234, d=0.693, g=0.726\n",
            ">83, 23/234, d=0.691, g=0.708\n",
            ">83, 24/234, d=0.688, g=0.689\n",
            ">83, 25/234, d=0.690, g=0.672\n",
            ">83, 26/234, d=0.691, g=0.676\n",
            ">83, 27/234, d=0.698, g=0.709\n",
            ">83, 28/234, d=0.699, g=0.712\n",
            ">83, 29/234, d=0.702, g=0.716\n",
            ">83, 30/234, d=0.698, g=0.710\n",
            ">83, 31/234, d=0.689, g=0.721\n",
            ">83, 32/234, d=0.689, g=0.720\n",
            ">83, 33/234, d=0.692, g=0.702\n",
            ">83, 34/234, d=0.684, g=0.680\n",
            ">83, 35/234, d=0.687, g=0.685\n",
            ">83, 36/234, d=0.689, g=0.685\n",
            ">83, 37/234, d=0.685, g=0.693\n",
            ">83, 38/234, d=0.694, g=0.696\n",
            ">83, 39/234, d=0.694, g=0.705\n",
            ">83, 40/234, d=0.681, g=0.714\n",
            ">83, 41/234, d=0.691, g=0.712\n",
            ">83, 42/234, d=0.696, g=0.705\n",
            ">83, 43/234, d=0.687, g=0.693\n",
            ">83, 44/234, d=0.695, g=0.692\n",
            ">83, 45/234, d=0.689, g=0.690\n",
            ">83, 46/234, d=0.694, g=0.693\n",
            ">83, 47/234, d=0.688, g=0.680\n",
            ">83, 48/234, d=0.688, g=0.693\n",
            ">83, 49/234, d=0.691, g=0.713\n",
            ">83, 50/234, d=0.695, g=0.737\n",
            ">83, 51/234, d=0.702, g=0.723\n",
            ">83, 52/234, d=0.688, g=0.686\n",
            ">83, 53/234, d=0.691, g=0.679\n",
            ">83, 54/234, d=0.685, g=0.681\n",
            ">83, 55/234, d=0.685, g=0.694\n",
            ">83, 56/234, d=0.694, g=0.715\n",
            ">83, 57/234, d=0.696, g=0.709\n",
            ">83, 58/234, d=0.686, g=0.703\n",
            ">83, 59/234, d=0.684, g=0.699\n",
            ">83, 60/234, d=0.686, g=0.681\n",
            ">83, 61/234, d=0.688, g=0.717\n",
            ">83, 62/234, d=0.690, g=0.750\n",
            ">83, 63/234, d=0.697, g=0.712\n",
            ">83, 64/234, d=0.685, g=0.688\n",
            ">83, 65/234, d=0.685, g=0.669\n",
            ">83, 66/234, d=0.690, g=0.698\n",
            ">83, 67/234, d=0.691, g=0.706\n",
            ">83, 68/234, d=0.683, g=0.690\n",
            ">83, 69/234, d=0.686, g=0.670\n",
            ">83, 70/234, d=0.693, g=0.691\n",
            ">83, 71/234, d=0.687, g=0.716\n",
            ">83, 72/234, d=0.689, g=0.727\n",
            ">83, 73/234, d=0.697, g=0.717\n",
            ">83, 74/234, d=0.688, g=0.701\n",
            ">83, 75/234, d=0.690, g=0.699\n",
            ">83, 76/234, d=0.688, g=0.679\n",
            ">83, 77/234, d=0.692, g=0.695\n",
            ">83, 78/234, d=0.685, g=0.719\n",
            ">83, 79/234, d=0.700, g=0.703\n",
            ">83, 80/234, d=0.688, g=0.686\n",
            ">83, 81/234, d=0.690, g=0.687\n",
            ">83, 82/234, d=0.691, g=0.692\n",
            ">83, 83/234, d=0.688, g=0.700\n",
            ">83, 84/234, d=0.694, g=0.718\n",
            ">83, 85/234, d=0.698, g=0.693\n",
            ">83, 86/234, d=0.693, g=0.680\n",
            ">83, 87/234, d=0.686, g=0.679\n",
            ">83, 88/234, d=0.694, g=0.695\n",
            ">83, 89/234, d=0.700, g=0.742\n",
            ">83, 90/234, d=0.687, g=0.722\n",
            ">83, 91/234, d=0.691, g=0.694\n",
            ">83, 92/234, d=0.694, g=0.682\n",
            ">83, 93/234, d=0.687, g=0.680\n",
            ">83, 94/234, d=0.691, g=0.704\n",
            ">83, 95/234, d=0.691, g=0.729\n",
            ">83, 96/234, d=0.687, g=0.711\n",
            ">83, 97/234, d=0.695, g=0.677\n",
            ">83, 98/234, d=0.686, g=0.674\n",
            ">83, 99/234, d=0.698, g=0.697\n",
            ">83, 100/234, d=0.685, g=0.708\n",
            ">83, 101/234, d=0.688, g=0.704\n",
            ">83, 102/234, d=0.696, g=0.690\n",
            ">83, 103/234, d=0.694, g=0.695\n",
            ">83, 104/234, d=0.685, g=0.717\n",
            ">83, 105/234, d=0.696, g=0.728\n",
            ">83, 106/234, d=0.689, g=0.724\n",
            ">83, 107/234, d=0.692, g=0.689\n",
            ">83, 108/234, d=0.701, g=0.666\n",
            ">83, 109/234, d=0.689, g=0.674\n",
            ">83, 110/234, d=0.694, g=0.711\n",
            ">83, 111/234, d=0.690, g=0.730\n",
            ">83, 112/234, d=0.691, g=0.698\n",
            ">83, 113/234, d=0.694, g=0.693\n",
            ">83, 114/234, d=0.685, g=0.694\n",
            ">83, 115/234, d=0.688, g=0.702\n",
            ">83, 116/234, d=0.685, g=0.722\n",
            ">83, 117/234, d=0.693, g=0.711\n",
            ">83, 118/234, d=0.689, g=0.698\n",
            ">83, 119/234, d=0.686, g=0.702\n",
            ">83, 120/234, d=0.692, g=0.719\n",
            ">83, 121/234, d=0.687, g=0.700\n",
            ">83, 122/234, d=0.691, g=0.694\n",
            ">83, 123/234, d=0.692, g=0.687\n",
            ">83, 124/234, d=0.691, g=0.702\n",
            ">83, 125/234, d=0.697, g=0.714\n",
            ">83, 126/234, d=0.685, g=0.702\n",
            ">83, 127/234, d=0.688, g=0.697\n",
            ">83, 128/234, d=0.698, g=0.694\n",
            ">83, 129/234, d=0.698, g=0.690\n",
            ">83, 130/234, d=0.688, g=0.688\n",
            ">83, 131/234, d=0.686, g=0.702\n",
            ">83, 132/234, d=0.691, g=0.714\n",
            ">83, 133/234, d=0.699, g=0.729\n",
            ">83, 134/234, d=0.690, g=0.717\n",
            ">83, 135/234, d=0.683, g=0.703\n",
            ">83, 136/234, d=0.692, g=0.687\n",
            ">83, 137/234, d=0.686, g=0.684\n",
            ">83, 138/234, d=0.692, g=0.697\n",
            ">83, 139/234, d=0.694, g=0.712\n",
            ">83, 140/234, d=0.689, g=0.692\n",
            ">83, 141/234, d=0.687, g=0.691\n",
            ">83, 142/234, d=0.695, g=0.693\n",
            ">83, 143/234, d=0.691, g=0.696\n",
            ">83, 144/234, d=0.698, g=0.713\n",
            ">83, 145/234, d=0.694, g=0.708\n",
            ">83, 146/234, d=0.683, g=0.677\n",
            ">83, 147/234, d=0.684, g=0.682\n",
            ">83, 148/234, d=0.695, g=0.696\n",
            ">83, 149/234, d=0.694, g=0.713\n",
            ">83, 150/234, d=0.691, g=0.707\n",
            ">83, 151/234, d=0.692, g=0.707\n",
            ">83, 152/234, d=0.695, g=0.719\n",
            ">83, 153/234, d=0.686, g=0.715\n",
            ">83, 154/234, d=0.694, g=0.705\n",
            ">83, 155/234, d=0.681, g=0.697\n",
            ">83, 156/234, d=0.693, g=0.682\n",
            ">83, 157/234, d=0.691, g=0.673\n",
            ">83, 158/234, d=0.692, g=0.687\n",
            ">83, 159/234, d=0.694, g=0.689\n",
            ">83, 160/234, d=0.687, g=0.713\n",
            ">83, 161/234, d=0.692, g=0.733\n",
            ">83, 162/234, d=0.687, g=0.711\n",
            ">83, 163/234, d=0.694, g=0.711\n",
            ">83, 164/234, d=0.685, g=0.698\n",
            ">83, 165/234, d=0.688, g=0.709\n",
            ">83, 166/234, d=0.692, g=0.693\n",
            ">83, 167/234, d=0.694, g=0.690\n",
            ">83, 168/234, d=0.699, g=0.699\n",
            ">83, 169/234, d=0.693, g=0.714\n",
            ">83, 170/234, d=0.694, g=0.697\n",
            ">83, 171/234, d=0.690, g=0.689\n",
            ">83, 172/234, d=0.697, g=0.689\n",
            ">83, 173/234, d=0.700, g=0.713\n",
            ">83, 174/234, d=0.692, g=0.720\n",
            ">83, 175/234, d=0.687, g=0.712\n",
            ">83, 176/234, d=0.693, g=0.720\n",
            ">83, 177/234, d=0.693, g=0.724\n",
            ">83, 178/234, d=0.689, g=0.695\n",
            ">83, 179/234, d=0.704, g=0.689\n",
            ">83, 180/234, d=0.692, g=0.692\n",
            ">83, 181/234, d=0.696, g=0.688\n",
            ">83, 182/234, d=0.690, g=0.697\n",
            ">83, 183/234, d=0.693, g=0.687\n",
            ">83, 184/234, d=0.690, g=0.709\n",
            ">83, 185/234, d=0.687, g=0.720\n",
            ">83, 186/234, d=0.693, g=0.726\n",
            ">83, 187/234, d=0.686, g=0.704\n",
            ">83, 188/234, d=0.703, g=0.694\n",
            ">83, 189/234, d=0.689, g=0.695\n",
            ">83, 190/234, d=0.686, g=0.703\n",
            ">83, 191/234, d=0.696, g=0.722\n",
            ">83, 192/234, d=0.688, g=0.707\n",
            ">83, 193/234, d=0.690, g=0.720\n",
            ">83, 194/234, d=0.686, g=0.696\n",
            ">83, 195/234, d=0.695, g=0.709\n",
            ">83, 196/234, d=0.682, g=0.699\n",
            ">83, 197/234, d=0.688, g=0.708\n",
            ">83, 198/234, d=0.696, g=0.693\n",
            ">83, 199/234, d=0.688, g=0.696\n",
            ">83, 200/234, d=0.693, g=0.705\n",
            ">83, 201/234, d=0.690, g=0.702\n",
            ">83, 202/234, d=0.699, g=0.690\n",
            ">83, 203/234, d=0.697, g=0.693\n",
            ">83, 204/234, d=0.690, g=0.705\n",
            ">83, 205/234, d=0.694, g=0.724\n",
            ">83, 206/234, d=0.688, g=0.706\n",
            ">83, 207/234, d=0.691, g=0.684\n",
            ">83, 208/234, d=0.687, g=0.687\n",
            ">83, 209/234, d=0.696, g=0.708\n",
            ">83, 210/234, d=0.689, g=0.723\n",
            ">83, 211/234, d=0.694, g=0.713\n",
            ">83, 212/234, d=0.688, g=0.692\n",
            ">83, 213/234, d=0.689, g=0.690\n",
            ">83, 214/234, d=0.696, g=0.705\n",
            ">83, 215/234, d=0.690, g=0.712\n",
            ">83, 216/234, d=0.688, g=0.701\n",
            ">83, 217/234, d=0.699, g=0.701\n",
            ">83, 218/234, d=0.680, g=0.697\n",
            ">83, 219/234, d=0.687, g=0.703\n",
            ">83, 220/234, d=0.694, g=0.719\n",
            ">83, 221/234, d=0.690, g=0.703\n",
            ">83, 222/234, d=0.691, g=0.688\n",
            ">83, 223/234, d=0.692, g=0.683\n",
            ">83, 224/234, d=0.693, g=0.703\n",
            ">83, 225/234, d=0.695, g=0.708\n",
            ">83, 226/234, d=0.690, g=0.699\n",
            ">83, 227/234, d=0.694, g=0.700\n",
            ">83, 228/234, d=0.693, g=0.699\n",
            ">83, 229/234, d=0.688, g=0.705\n",
            ">83, 230/234, d=0.693, g=0.714\n",
            ">83, 231/234, d=0.693, g=0.700\n",
            ">83, 232/234, d=0.694, g=0.695\n",
            ">83, 233/234, d=0.698, g=0.716\n",
            ">83, 234/234, d=0.692, g=0.709\n",
            ">84, 1/234, d=0.692, g=0.692\n",
            ">84, 2/234, d=0.696, g=0.712\n",
            ">84, 3/234, d=0.697, g=0.699\n",
            ">84, 4/234, d=0.690, g=0.688\n",
            ">84, 5/234, d=0.696, g=0.697\n",
            ">84, 6/234, d=0.689, g=0.708\n",
            ">84, 7/234, d=0.682, g=0.712\n",
            ">84, 8/234, d=0.695, g=0.699\n",
            ">84, 9/234, d=0.700, g=0.703\n",
            ">84, 10/234, d=0.685, g=0.707\n",
            ">84, 11/234, d=0.699, g=0.715\n",
            ">84, 12/234, d=0.692, g=0.698\n",
            ">84, 13/234, d=0.691, g=0.689\n",
            ">84, 14/234, d=0.692, g=0.693\n",
            ">84, 15/234, d=0.684, g=0.685\n",
            ">84, 16/234, d=0.691, g=0.701\n",
            ">84, 17/234, d=0.695, g=0.697\n",
            ">84, 18/234, d=0.696, g=0.694\n",
            ">84, 19/234, d=0.686, g=0.706\n",
            ">84, 20/234, d=0.684, g=0.718\n",
            ">84, 21/234, d=0.697, g=0.710\n",
            ">84, 22/234, d=0.691, g=0.701\n",
            ">84, 23/234, d=0.690, g=0.679\n",
            ">84, 24/234, d=0.689, g=0.684\n",
            ">84, 25/234, d=0.692, g=0.692\n",
            ">84, 26/234, d=0.691, g=0.703\n",
            ">84, 27/234, d=0.685, g=0.719\n",
            ">84, 28/234, d=0.688, g=0.734\n",
            ">84, 29/234, d=0.681, g=0.705\n",
            ">84, 30/234, d=0.692, g=0.681\n",
            ">84, 31/234, d=0.685, g=0.683\n",
            ">84, 32/234, d=0.693, g=0.704\n",
            ">84, 33/234, d=0.690, g=0.699\n",
            ">84, 34/234, d=0.689, g=0.696\n",
            ">84, 35/234, d=0.688, g=0.678\n",
            ">84, 36/234, d=0.688, g=0.685\n",
            ">84, 37/234, d=0.694, g=0.710\n",
            ">84, 38/234, d=0.695, g=0.736\n",
            ">84, 39/234, d=0.684, g=0.731\n",
            ">84, 40/234, d=0.694, g=0.718\n",
            ">84, 41/234, d=0.692, g=0.685\n",
            ">84, 42/234, d=0.695, g=0.675\n",
            ">84, 43/234, d=0.685, g=0.688\n",
            ">84, 44/234, d=0.701, g=0.703\n",
            ">84, 45/234, d=0.689, g=0.707\n",
            ">84, 46/234, d=0.689, g=0.686\n",
            ">84, 47/234, d=0.696, g=0.679\n",
            ">84, 48/234, d=0.683, g=0.691\n",
            ">84, 49/234, d=0.695, g=0.712\n",
            ">84, 50/234, d=0.695, g=0.718\n",
            ">84, 51/234, d=0.697, g=0.709\n",
            ">84, 52/234, d=0.686, g=0.685\n",
            ">84, 53/234, d=0.696, g=0.677\n",
            ">84, 54/234, d=0.692, g=0.704\n",
            ">84, 55/234, d=0.695, g=0.711\n",
            ">84, 56/234, d=0.694, g=0.700\n",
            ">84, 57/234, d=0.688, g=0.701\n",
            ">84, 58/234, d=0.695, g=0.697\n",
            ">84, 59/234, d=0.690, g=0.694\n",
            ">84, 60/234, d=0.700, g=0.701\n",
            ">84, 61/234, d=0.679, g=0.693\n",
            ">84, 62/234, d=0.691, g=0.687\n",
            ">84, 63/234, d=0.690, g=0.706\n",
            ">84, 64/234, d=0.699, g=0.707\n",
            ">84, 65/234, d=0.683, g=0.693\n",
            ">84, 66/234, d=0.687, g=0.699\n",
            ">84, 67/234, d=0.684, g=0.696\n",
            ">84, 68/234, d=0.686, g=0.712\n",
            ">84, 69/234, d=0.693, g=0.708\n",
            ">84, 70/234, d=0.689, g=0.702\n",
            ">84, 71/234, d=0.694, g=0.693\n",
            ">84, 72/234, d=0.691, g=0.708\n",
            ">84, 73/234, d=0.693, g=0.716\n",
            ">84, 74/234, d=0.690, g=0.698\n",
            ">84, 75/234, d=0.695, g=0.680\n",
            ">84, 76/234, d=0.691, g=0.686\n",
            ">84, 77/234, d=0.691, g=0.699\n",
            ">84, 78/234, d=0.694, g=0.717\n",
            ">84, 79/234, d=0.701, g=0.701\n",
            ">84, 80/234, d=0.694, g=0.685\n",
            ">84, 81/234, d=0.692, g=0.677\n",
            ">84, 82/234, d=0.688, g=0.699\n",
            ">84, 83/234, d=0.689, g=0.701\n",
            ">84, 84/234, d=0.696, g=0.701\n",
            ">84, 85/234, d=0.688, g=0.698\n",
            ">84, 86/234, d=0.686, g=0.697\n",
            ">84, 87/234, d=0.696, g=0.707\n",
            ">84, 88/234, d=0.691, g=0.718\n",
            ">84, 89/234, d=0.679, g=0.698\n",
            ">84, 90/234, d=0.695, g=0.699\n",
            ">84, 91/234, d=0.688, g=0.699\n",
            ">84, 92/234, d=0.689, g=0.700\n",
            ">84, 93/234, d=0.688, g=0.715\n",
            ">84, 94/234, d=0.679, g=0.689\n",
            ">84, 95/234, d=0.692, g=0.680\n",
            ">84, 96/234, d=0.683, g=0.691\n",
            ">84, 97/234, d=0.687, g=0.723\n",
            ">84, 98/234, d=0.697, g=0.736\n",
            ">84, 99/234, d=0.690, g=0.725\n",
            ">84, 100/234, d=0.688, g=0.704\n",
            ">84, 101/234, d=0.691, g=0.681\n",
            ">84, 102/234, d=0.689, g=0.691\n",
            ">84, 103/234, d=0.697, g=0.702\n",
            ">84, 104/234, d=0.691, g=0.706\n",
            ">84, 105/234, d=0.691, g=0.702\n",
            ">84, 106/234, d=0.695, g=0.702\n",
            ">84, 107/234, d=0.688, g=0.684\n",
            ">84, 108/234, d=0.694, g=0.713\n",
            ">84, 109/234, d=0.693, g=0.726\n",
            ">84, 110/234, d=0.702, g=0.728\n",
            ">84, 111/234, d=0.696, g=0.701\n",
            ">84, 112/234, d=0.690, g=0.681\n",
            ">84, 113/234, d=0.693, g=0.683\n",
            ">84, 114/234, d=0.687, g=0.697\n",
            ">84, 115/234, d=0.696, g=0.723\n",
            ">84, 116/234, d=0.692, g=0.706\n",
            ">84, 117/234, d=0.687, g=0.700\n",
            ">84, 118/234, d=0.690, g=0.689\n",
            ">84, 119/234, d=0.688, g=0.698\n",
            ">84, 120/234, d=0.688, g=0.705\n",
            ">84, 121/234, d=0.694, g=0.722\n",
            ">84, 122/234, d=0.692, g=0.702\n",
            ">84, 123/234, d=0.698, g=0.680\n",
            ">84, 124/234, d=0.700, g=0.685\n",
            ">84, 125/234, d=0.691, g=0.709\n",
            ">84, 126/234, d=0.686, g=0.709\n",
            ">84, 127/234, d=0.695, g=0.717\n",
            ">84, 128/234, d=0.693, g=0.711\n",
            ">84, 129/234, d=0.694, g=0.701\n",
            ">84, 130/234, d=0.686, g=0.694\n",
            ">84, 131/234, d=0.691, g=0.687\n",
            ">84, 132/234, d=0.690, g=0.680\n",
            ">84, 133/234, d=0.687, g=0.711\n",
            ">84, 134/234, d=0.689, g=0.719\n",
            ">84, 135/234, d=0.694, g=0.724\n",
            ">84, 136/234, d=0.688, g=0.719\n",
            ">84, 137/234, d=0.681, g=0.700\n",
            ">84, 138/234, d=0.688, g=0.690\n",
            ">84, 139/234, d=0.690, g=0.670\n",
            ">84, 140/234, d=0.693, g=0.684\n",
            ">84, 141/234, d=0.696, g=0.698\n",
            ">84, 142/234, d=0.686, g=0.723\n",
            ">84, 143/234, d=0.695, g=0.721\n",
            ">84, 144/234, d=0.689, g=0.699\n",
            ">84, 145/234, d=0.690, g=0.696\n",
            ">84, 146/234, d=0.691, g=0.716\n",
            ">84, 147/234, d=0.678, g=0.726\n",
            ">84, 148/234, d=0.689, g=0.732\n",
            ">84, 149/234, d=0.688, g=0.714\n",
            ">84, 150/234, d=0.688, g=0.705\n",
            ">84, 151/234, d=0.687, g=0.683\n",
            ">84, 152/234, d=0.692, g=0.685\n",
            ">84, 153/234, d=0.692, g=0.700\n",
            ">84, 154/234, d=0.696, g=0.715\n",
            ">84, 155/234, d=0.696, g=0.703\n",
            ">84, 156/234, d=0.690, g=0.695\n",
            ">84, 157/234, d=0.698, g=0.700\n",
            ">84, 158/234, d=0.685, g=0.698\n",
            ">84, 159/234, d=0.694, g=0.709\n",
            ">84, 160/234, d=0.685, g=0.700\n",
            ">84, 161/234, d=0.687, g=0.694\n",
            ">84, 162/234, d=0.683, g=0.705\n",
            ">84, 163/234, d=0.695, g=0.693\n",
            ">84, 164/234, d=0.694, g=0.686\n",
            ">84, 165/234, d=0.690, g=0.684\n",
            ">84, 166/234, d=0.691, g=0.686\n",
            ">84, 167/234, d=0.691, g=0.723\n",
            ">84, 168/234, d=0.696, g=0.728\n",
            ">84, 169/234, d=0.699, g=0.723\n",
            ">84, 170/234, d=0.687, g=0.701\n",
            ">84, 171/234, d=0.693, g=0.701\n",
            ">84, 172/234, d=0.693, g=0.703\n",
            ">84, 173/234, d=0.689, g=0.701\n",
            ">84, 174/234, d=0.689, g=0.684\n",
            ">84, 175/234, d=0.685, g=0.706\n",
            ">84, 176/234, d=0.693, g=0.705\n",
            ">84, 177/234, d=0.685, g=0.713\n",
            ">84, 178/234, d=0.694, g=0.699\n",
            ">84, 179/234, d=0.685, g=0.698\n",
            ">84, 180/234, d=0.694, g=0.690\n",
            ">84, 181/234, d=0.690, g=0.692\n",
            ">84, 182/234, d=0.690, g=0.690\n",
            ">84, 183/234, d=0.699, g=0.699\n",
            ">84, 184/234, d=0.689, g=0.695\n",
            ">84, 185/234, d=0.696, g=0.687\n",
            ">84, 186/234, d=0.692, g=0.691\n",
            ">84, 187/234, d=0.692, g=0.710\n",
            ">84, 188/234, d=0.696, g=0.714\n",
            ">84, 189/234, d=0.691, g=0.713\n",
            ">84, 190/234, d=0.694, g=0.695\n",
            ">84, 191/234, d=0.692, g=0.691\n",
            ">84, 192/234, d=0.693, g=0.708\n",
            ">84, 193/234, d=0.687, g=0.728\n",
            ">84, 194/234, d=0.695, g=0.719\n",
            ">84, 195/234, d=0.689, g=0.704\n",
            ">84, 196/234, d=0.693, g=0.685\n",
            ">84, 197/234, d=0.690, g=0.699\n",
            ">84, 198/234, d=0.688, g=0.702\n",
            ">84, 199/234, d=0.692, g=0.699\n",
            ">84, 200/234, d=0.693, g=0.693\n",
            ">84, 201/234, d=0.693, g=0.691\n",
            ">84, 202/234, d=0.697, g=0.722\n",
            ">84, 203/234, d=0.698, g=0.718\n",
            ">84, 204/234, d=0.695, g=0.683\n",
            ">84, 205/234, d=0.694, g=0.693\n",
            ">84, 206/234, d=0.685, g=0.720\n",
            ">84, 207/234, d=0.699, g=0.718\n",
            ">84, 208/234, d=0.688, g=0.714\n",
            ">84, 209/234, d=0.688, g=0.693\n",
            ">84, 210/234, d=0.692, g=0.707\n",
            ">84, 211/234, d=0.694, g=0.711\n",
            ">84, 212/234, d=0.690, g=0.708\n",
            ">84, 213/234, d=0.688, g=0.686\n",
            ">84, 214/234, d=0.699, g=0.692\n",
            ">84, 215/234, d=0.689, g=0.708\n",
            ">84, 216/234, d=0.688, g=0.717\n",
            ">84, 217/234, d=0.688, g=0.694\n",
            ">84, 218/234, d=0.691, g=0.697\n",
            ">84, 219/234, d=0.693, g=0.719\n",
            ">84, 220/234, d=0.694, g=0.709\n",
            ">84, 221/234, d=0.696, g=0.704\n",
            ">84, 222/234, d=0.689, g=0.694\n",
            ">84, 223/234, d=0.687, g=0.706\n",
            ">84, 224/234, d=0.692, g=0.729\n",
            ">84, 225/234, d=0.691, g=0.708\n",
            ">84, 226/234, d=0.695, g=0.678\n",
            ">84, 227/234, d=0.696, g=0.688\n",
            ">84, 228/234, d=0.693, g=0.698\n",
            ">84, 229/234, d=0.702, g=0.696\n",
            ">84, 230/234, d=0.694, g=0.697\n",
            ">84, 231/234, d=0.693, g=0.696\n",
            ">84, 232/234, d=0.696, g=0.699\n",
            ">84, 233/234, d=0.702, g=0.713\n",
            ">84, 234/234, d=0.699, g=0.710\n",
            ">85, 1/234, d=0.688, g=0.710\n",
            ">85, 2/234, d=0.694, g=0.705\n",
            ">85, 3/234, d=0.697, g=0.698\n",
            ">85, 4/234, d=0.691, g=0.691\n",
            ">85, 5/234, d=0.694, g=0.709\n",
            ">85, 6/234, d=0.692, g=0.702\n",
            ">85, 7/234, d=0.694, g=0.690\n",
            ">85, 8/234, d=0.688, g=0.690\n",
            ">85, 9/234, d=0.690, g=0.685\n",
            ">85, 10/234, d=0.688, g=0.689\n",
            ">85, 11/234, d=0.692, g=0.708\n",
            ">85, 12/234, d=0.694, g=0.718\n",
            ">85, 13/234, d=0.687, g=0.709\n",
            ">85, 14/234, d=0.687, g=0.696\n",
            ">85, 15/234, d=0.693, g=0.694\n",
            ">85, 16/234, d=0.686, g=0.718\n",
            ">85, 17/234, d=0.687, g=0.705\n",
            ">85, 18/234, d=0.688, g=0.691\n",
            ">85, 19/234, d=0.687, g=0.685\n",
            ">85, 20/234, d=0.689, g=0.673\n",
            ">85, 21/234, d=0.689, g=0.692\n",
            ">85, 22/234, d=0.683, g=0.719\n",
            ">85, 23/234, d=0.691, g=0.729\n",
            ">85, 24/234, d=0.685, g=0.706\n",
            ">85, 25/234, d=0.693, g=0.704\n",
            ">85, 26/234, d=0.690, g=0.696\n",
            ">85, 27/234, d=0.690, g=0.691\n",
            ">85, 28/234, d=0.695, g=0.700\n",
            ">85, 29/234, d=0.689, g=0.698\n",
            ">85, 30/234, d=0.692, g=0.703\n",
            ">85, 31/234, d=0.694, g=0.680\n",
            ">85, 32/234, d=0.690, g=0.685\n",
            ">85, 33/234, d=0.689, g=0.711\n",
            ">85, 34/234, d=0.694, g=0.752\n",
            ">85, 35/234, d=0.688, g=0.732\n",
            ">85, 36/234, d=0.692, g=0.696\n",
            ">85, 37/234, d=0.688, g=0.667\n",
            ">85, 38/234, d=0.689, g=0.680\n",
            ">85, 39/234, d=0.693, g=0.709\n",
            ">85, 40/234, d=0.693, g=0.737\n",
            ">85, 41/234, d=0.697, g=0.714\n",
            ">85, 42/234, d=0.700, g=0.688\n",
            ">85, 43/234, d=0.695, g=0.677\n",
            ">85, 44/234, d=0.695, g=0.693\n",
            ">85, 45/234, d=0.689, g=0.707\n",
            ">85, 46/234, d=0.691, g=0.701\n",
            ">85, 47/234, d=0.688, g=0.694\n",
            ">85, 48/234, d=0.685, g=0.689\n",
            ">85, 49/234, d=0.685, g=0.689\n",
            ">85, 50/234, d=0.684, g=0.710\n",
            ">85, 51/234, d=0.699, g=0.706\n",
            ">85, 52/234, d=0.692, g=0.713\n",
            ">85, 53/234, d=0.691, g=0.712\n",
            ">85, 54/234, d=0.693, g=0.704\n",
            ">85, 55/234, d=0.689, g=0.690\n",
            ">85, 56/234, d=0.690, g=0.690\n",
            ">85, 57/234, d=0.691, g=0.709\n",
            ">85, 58/234, d=0.691, g=0.706\n",
            ">85, 59/234, d=0.697, g=0.720\n",
            ">85, 60/234, d=0.688, g=0.712\n",
            ">85, 61/234, d=0.690, g=0.682\n",
            ">85, 62/234, d=0.691, g=0.677\n",
            ">85, 63/234, d=0.689, g=0.695\n",
            ">85, 64/234, d=0.687, g=0.715\n",
            ">85, 65/234, d=0.685, g=0.742\n",
            ">85, 66/234, d=0.689, g=0.713\n",
            ">85, 67/234, d=0.689, g=0.698\n",
            ">85, 68/234, d=0.683, g=0.689\n",
            ">85, 69/234, d=0.698, g=0.696\n",
            ">85, 70/234, d=0.699, g=0.700\n",
            ">85, 71/234, d=0.686, g=0.702\n",
            ">85, 72/234, d=0.695, g=0.703\n",
            ">85, 73/234, d=0.692, g=0.707\n",
            ">85, 74/234, d=0.692, g=0.709\n",
            ">85, 75/234, d=0.688, g=0.716\n",
            ">85, 76/234, d=0.693, g=0.704\n",
            ">85, 77/234, d=0.701, g=0.694\n",
            ">85, 78/234, d=0.687, g=0.696\n",
            ">85, 79/234, d=0.696, g=0.690\n",
            ">85, 80/234, d=0.696, g=0.697\n",
            ">85, 81/234, d=0.690, g=0.693\n",
            ">85, 82/234, d=0.690, g=0.682\n",
            ">85, 83/234, d=0.692, g=0.702\n",
            ">85, 84/234, d=0.687, g=0.724\n",
            ">85, 85/234, d=0.692, g=0.744\n",
            ">85, 86/234, d=0.687, g=0.705\n",
            ">85, 87/234, d=0.688, g=0.674\n",
            ">85, 88/234, d=0.685, g=0.681\n",
            ">85, 89/234, d=0.694, g=0.689\n",
            ">85, 90/234, d=0.690, g=0.709\n",
            ">85, 91/234, d=0.690, g=0.701\n",
            ">85, 92/234, d=0.695, g=0.701\n",
            ">85, 93/234, d=0.686, g=0.706\n",
            ">85, 94/234, d=0.694, g=0.712\n",
            ">85, 95/234, d=0.688, g=0.702\n",
            ">85, 96/234, d=0.689, g=0.688\n",
            ">85, 97/234, d=0.695, g=0.686\n",
            ">85, 98/234, d=0.691, g=0.707\n",
            ">85, 99/234, d=0.696, g=0.724\n",
            ">85, 100/234, d=0.690, g=0.724\n",
            ">85, 101/234, d=0.688, g=0.710\n",
            ">85, 102/234, d=0.695, g=0.694\n",
            ">85, 103/234, d=0.688, g=0.690\n",
            ">85, 104/234, d=0.690, g=0.681\n",
            ">85, 105/234, d=0.693, g=0.687\n",
            ">85, 106/234, d=0.695, g=0.695\n",
            ">85, 107/234, d=0.693, g=0.719\n",
            ">85, 108/234, d=0.695, g=0.720\n",
            ">85, 109/234, d=0.694, g=0.721\n",
            ">85, 110/234, d=0.683, g=0.693\n",
            ">85, 111/234, d=0.685, g=0.675\n",
            ">85, 112/234, d=0.696, g=0.678\n",
            ">85, 113/234, d=0.693, g=0.693\n",
            ">85, 114/234, d=0.688, g=0.699\n",
            ">85, 115/234, d=0.695, g=0.703\n",
            ">85, 116/234, d=0.698, g=0.696\n",
            ">85, 117/234, d=0.692, g=0.696\n",
            ">85, 118/234, d=0.695, g=0.723\n",
            ">85, 119/234, d=0.690, g=0.709\n",
            ">85, 120/234, d=0.686, g=0.711\n",
            ">85, 121/234, d=0.688, g=0.701\n",
            ">85, 122/234, d=0.696, g=0.695\n",
            ">85, 123/234, d=0.698, g=0.703\n",
            ">85, 124/234, d=0.690, g=0.698\n",
            ">85, 125/234, d=0.691, g=0.685\n",
            ">85, 126/234, d=0.691, g=0.676\n",
            ">85, 127/234, d=0.689, g=0.685\n",
            ">85, 128/234, d=0.688, g=0.682\n",
            ">85, 129/234, d=0.691, g=0.694\n",
            ">85, 130/234, d=0.698, g=0.715\n",
            ">85, 131/234, d=0.697, g=0.730\n",
            ">85, 132/234, d=0.694, g=0.722\n",
            ">85, 133/234, d=0.691, g=0.692\n",
            ">85, 134/234, d=0.700, g=0.693\n",
            ">85, 135/234, d=0.695, g=0.705\n",
            ">85, 136/234, d=0.690, g=0.706\n",
            ">85, 137/234, d=0.696, g=0.677\n",
            ">85, 138/234, d=0.690, g=0.673\n",
            ">85, 139/234, d=0.697, g=0.691\n",
            ">85, 140/234, d=0.688, g=0.714\n",
            ">85, 141/234, d=0.692, g=0.714\n",
            ">85, 142/234, d=0.693, g=0.696\n",
            ">85, 143/234, d=0.690, g=0.701\n",
            ">85, 144/234, d=0.686, g=0.702\n",
            ">85, 145/234, d=0.695, g=0.721\n",
            ">85, 146/234, d=0.686, g=0.711\n",
            ">85, 147/234, d=0.689, g=0.688\n",
            ">85, 148/234, d=0.696, g=0.698\n",
            ">85, 149/234, d=0.688, g=0.691\n",
            ">85, 150/234, d=0.691, g=0.705\n",
            ">85, 151/234, d=0.690, g=0.705\n",
            ">85, 152/234, d=0.684, g=0.701\n",
            ">85, 153/234, d=0.692, g=0.692\n",
            ">85, 154/234, d=0.690, g=0.703\n",
            ">85, 155/234, d=0.688, g=0.703\n",
            ">85, 156/234, d=0.696, g=0.687\n",
            ">85, 157/234, d=0.694, g=0.686\n",
            ">85, 158/234, d=0.694, g=0.709\n",
            ">85, 159/234, d=0.700, g=0.723\n",
            ">85, 160/234, d=0.695, g=0.722\n",
            ">85, 161/234, d=0.688, g=0.690\n",
            ">85, 162/234, d=0.698, g=0.680\n",
            ">85, 163/234, d=0.686, g=0.690\n",
            ">85, 164/234, d=0.692, g=0.707\n",
            ">85, 165/234, d=0.686, g=0.722\n",
            ">85, 166/234, d=0.687, g=0.721\n",
            ">85, 167/234, d=0.683, g=0.709\n",
            ">85, 168/234, d=0.697, g=0.682\n",
            ">85, 169/234, d=0.695, g=0.677\n",
            ">85, 170/234, d=0.689, g=0.686\n",
            ">85, 171/234, d=0.685, g=0.706\n",
            ">85, 172/234, d=0.692, g=0.726\n",
            ">85, 173/234, d=0.684, g=0.719\n",
            ">85, 174/234, d=0.698, g=0.692\n",
            ">85, 175/234, d=0.689, g=0.701\n",
            ">85, 176/234, d=0.698, g=0.706\n",
            ">85, 177/234, d=0.694, g=0.720\n",
            ">85, 178/234, d=0.695, g=0.702\n",
            ">85, 179/234, d=0.686, g=0.686\n",
            ">85, 180/234, d=0.699, g=0.674\n",
            ">85, 181/234, d=0.695, g=0.693\n",
            ">85, 182/234, d=0.691, g=0.707\n",
            ">85, 183/234, d=0.696, g=0.712\n",
            ">85, 184/234, d=0.691, g=0.712\n",
            ">85, 185/234, d=0.695, g=0.697\n",
            ">85, 186/234, d=0.690, g=0.703\n",
            ">85, 187/234, d=0.688, g=0.702\n",
            ">85, 188/234, d=0.694, g=0.691\n",
            ">85, 189/234, d=0.690, g=0.699\n",
            ">85, 190/234, d=0.686, g=0.701\n",
            ">85, 191/234, d=0.695, g=0.700\n",
            ">85, 192/234, d=0.701, g=0.704\n",
            ">85, 193/234, d=0.695, g=0.689\n",
            ">85, 194/234, d=0.694, g=0.681\n",
            ">85, 195/234, d=0.690, g=0.688\n",
            ">85, 196/234, d=0.686, g=0.715\n",
            ">85, 197/234, d=0.692, g=0.746\n",
            ">85, 198/234, d=0.689, g=0.729\n",
            ">85, 199/234, d=0.693, g=0.694\n",
            ">85, 200/234, d=0.690, g=0.688\n",
            ">85, 201/234, d=0.693, g=0.706\n",
            ">85, 202/234, d=0.692, g=0.707\n",
            ">85, 203/234, d=0.684, g=0.699\n",
            ">85, 204/234, d=0.692, g=0.680\n",
            ">85, 205/234, d=0.691, g=0.696\n",
            ">85, 206/234, d=0.690, g=0.714\n",
            ">85, 207/234, d=0.697, g=0.726\n",
            ">85, 208/234, d=0.690, g=0.702\n",
            ">85, 209/234, d=0.688, g=0.685\n",
            ">85, 210/234, d=0.696, g=0.678\n",
            ">85, 211/234, d=0.693, g=0.697\n",
            ">85, 212/234, d=0.684, g=0.703\n",
            ">85, 213/234, d=0.701, g=0.710\n",
            ">85, 214/234, d=0.688, g=0.692\n",
            ">85, 215/234, d=0.694, g=0.704\n",
            ">85, 216/234, d=0.684, g=0.711\n",
            ">85, 217/234, d=0.699, g=0.705\n",
            ">85, 218/234, d=0.690, g=0.697\n",
            ">85, 219/234, d=0.687, g=0.698\n",
            ">85, 220/234, d=0.679, g=0.701\n",
            ">85, 221/234, d=0.686, g=0.702\n",
            ">85, 222/234, d=0.695, g=0.698\n",
            ">85, 223/234, d=0.687, g=0.680\n",
            ">85, 224/234, d=0.688, g=0.699\n",
            ">85, 225/234, d=0.679, g=0.703\n",
            ">85, 226/234, d=0.694, g=0.708\n",
            ">85, 227/234, d=0.694, g=0.704\n",
            ">85, 228/234, d=0.690, g=0.708\n",
            ">85, 229/234, d=0.691, g=0.700\n",
            ">85, 230/234, d=0.689, g=0.694\n",
            ">85, 231/234, d=0.685, g=0.692\n",
            ">85, 232/234, d=0.693, g=0.681\n",
            ">85, 233/234, d=0.688, g=0.685\n",
            ">85, 234/234, d=0.694, g=0.713\n",
            ">86, 1/234, d=0.684, g=0.712\n",
            ">86, 2/234, d=0.693, g=0.697\n",
            ">86, 3/234, d=0.695, g=0.687\n",
            ">86, 4/234, d=0.690, g=0.685\n",
            ">86, 5/234, d=0.697, g=0.710\n",
            ">86, 6/234, d=0.688, g=0.710\n",
            ">86, 7/234, d=0.692, g=0.724\n",
            ">86, 8/234, d=0.691, g=0.713\n",
            ">86, 9/234, d=0.684, g=0.703\n",
            ">86, 10/234, d=0.691, g=0.692\n",
            ">86, 11/234, d=0.692, g=0.709\n",
            ">86, 12/234, d=0.686, g=0.693\n",
            ">86, 13/234, d=0.687, g=0.680\n",
            ">86, 14/234, d=0.688, g=0.677\n",
            ">86, 15/234, d=0.689, g=0.721\n",
            ">86, 16/234, d=0.693, g=0.712\n",
            ">86, 17/234, d=0.686, g=0.704\n",
            ">86, 18/234, d=0.685, g=0.686\n",
            ">86, 19/234, d=0.698, g=0.680\n",
            ">86, 20/234, d=0.689, g=0.692\n",
            ">86, 21/234, d=0.684, g=0.718\n",
            ">86, 22/234, d=0.681, g=0.710\n",
            ">86, 23/234, d=0.698, g=0.706\n",
            ">86, 24/234, d=0.682, g=0.711\n",
            ">86, 25/234, d=0.696, g=0.690\n",
            ">86, 26/234, d=0.691, g=0.698\n",
            ">86, 27/234, d=0.692, g=0.703\n",
            ">86, 28/234, d=0.694, g=0.713\n",
            ">86, 29/234, d=0.688, g=0.716\n",
            ">86, 30/234, d=0.692, g=0.694\n",
            ">86, 31/234, d=0.685, g=0.697\n",
            ">86, 32/234, d=0.694, g=0.702\n",
            ">86, 33/234, d=0.687, g=0.715\n",
            ">86, 34/234, d=0.689, g=0.701\n",
            ">86, 35/234, d=0.693, g=0.698\n",
            ">86, 36/234, d=0.690, g=0.712\n",
            ">86, 37/234, d=0.691, g=0.705\n",
            ">86, 38/234, d=0.688, g=0.691\n",
            ">86, 39/234, d=0.690, g=0.681\n",
            ">86, 40/234, d=0.693, g=0.674\n",
            ">86, 41/234, d=0.689, g=0.694\n",
            ">86, 42/234, d=0.686, g=0.719\n",
            ">86, 43/234, d=0.688, g=0.732\n",
            ">86, 44/234, d=0.688, g=0.718\n",
            ">86, 45/234, d=0.694, g=0.694\n",
            ">86, 46/234, d=0.699, g=0.685\n",
            ">86, 47/234, d=0.686, g=0.673\n",
            ">86, 48/234, d=0.691, g=0.691\n",
            ">86, 49/234, d=0.690, g=0.709\n",
            ">86, 50/234, d=0.688, g=0.737\n",
            ">86, 51/234, d=0.688, g=0.708\n",
            ">86, 52/234, d=0.697, g=0.678\n",
            ">86, 53/234, d=0.694, g=0.683\n",
            ">86, 54/234, d=0.701, g=0.720\n",
            ">86, 55/234, d=0.702, g=0.728\n",
            ">86, 56/234, d=0.696, g=0.688\n",
            ">86, 57/234, d=0.691, g=0.670\n",
            ">86, 58/234, d=0.695, g=0.677\n",
            ">86, 59/234, d=0.694, g=0.722\n",
            ">86, 60/234, d=0.684, g=0.732\n",
            ">86, 61/234, d=0.695, g=0.721\n",
            ">86, 62/234, d=0.693, g=0.698\n",
            ">86, 63/234, d=0.684, g=0.670\n",
            ">86, 64/234, d=0.686, g=0.690\n",
            ">86, 65/234, d=0.700, g=0.725\n",
            ">86, 66/234, d=0.692, g=0.713\n",
            ">86, 67/234, d=0.689, g=0.698\n",
            ">86, 68/234, d=0.686, g=0.685\n",
            ">86, 69/234, d=0.699, g=0.678\n",
            ">86, 70/234, d=0.703, g=0.710\n",
            ">86, 71/234, d=0.688, g=0.739\n",
            ">86, 72/234, d=0.685, g=0.733\n",
            ">86, 73/234, d=0.698, g=0.707\n",
            ">86, 74/234, d=0.689, g=0.683\n",
            ">86, 75/234, d=0.692, g=0.687\n",
            ">86, 76/234, d=0.685, g=0.697\n",
            ">86, 77/234, d=0.688, g=0.702\n",
            ">86, 78/234, d=0.690, g=0.698\n",
            ">86, 79/234, d=0.688, g=0.689\n",
            ">86, 80/234, d=0.691, g=0.682\n",
            ">86, 81/234, d=0.690, g=0.694\n",
            ">86, 82/234, d=0.694, g=0.726\n",
            ">86, 83/234, d=0.682, g=0.733\n",
            ">86, 84/234, d=0.699, g=0.708\n",
            ">86, 85/234, d=0.690, g=0.693\n",
            ">86, 86/234, d=0.700, g=0.680\n",
            ">86, 87/234, d=0.693, g=0.692\n",
            ">86, 88/234, d=0.681, g=0.695\n",
            ">86, 89/234, d=0.689, g=0.698\n",
            ">86, 90/234, d=0.690, g=0.696\n",
            ">86, 91/234, d=0.688, g=0.699\n",
            ">86, 92/234, d=0.693, g=0.696\n",
            ">86, 93/234, d=0.684, g=0.709\n",
            ">86, 94/234, d=0.698, g=0.698\n",
            ">86, 95/234, d=0.691, g=0.696\n",
            ">86, 96/234, d=0.689, g=0.693\n",
            ">86, 97/234, d=0.693, g=0.710\n",
            ">86, 98/234, d=0.699, g=0.712\n",
            ">86, 99/234, d=0.691, g=0.704\n",
            ">86, 100/234, d=0.695, g=0.705\n",
            ">86, 101/234, d=0.689, g=0.685\n",
            ">86, 102/234, d=0.690, g=0.682\n",
            ">86, 103/234, d=0.686, g=0.696\n",
            ">86, 104/234, d=0.695, g=0.722\n",
            ">86, 105/234, d=0.691, g=0.726\n",
            ">86, 106/234, d=0.694, g=0.719\n",
            ">86, 107/234, d=0.695, g=0.703\n",
            ">86, 108/234, d=0.693, g=0.699\n",
            ">86, 109/234, d=0.689, g=0.699\n",
            ">86, 110/234, d=0.689, g=0.703\n",
            ">86, 111/234, d=0.696, g=0.703\n",
            ">86, 112/234, d=0.698, g=0.693\n",
            ">86, 113/234, d=0.695, g=0.699\n",
            ">86, 114/234, d=0.692, g=0.693\n",
            ">86, 115/234, d=0.690, g=0.699\n",
            ">86, 116/234, d=0.693, g=0.712\n",
            ">86, 117/234, d=0.691, g=0.705\n",
            ">86, 118/234, d=0.692, g=0.697\n",
            ">86, 119/234, d=0.696, g=0.687\n",
            ">86, 120/234, d=0.692, g=0.692\n",
            ">86, 121/234, d=0.690, g=0.698\n",
            ">86, 122/234, d=0.694, g=0.702\n",
            ">86, 123/234, d=0.688, g=0.702\n",
            ">86, 124/234, d=0.687, g=0.692\n",
            ">86, 125/234, d=0.687, g=0.692\n",
            ">86, 126/234, d=0.694, g=0.702\n",
            ">86, 127/234, d=0.692, g=0.713\n",
            ">86, 128/234, d=0.696, g=0.709\n",
            ">86, 129/234, d=0.690, g=0.679\n",
            ">86, 130/234, d=0.691, g=0.683\n",
            ">86, 131/234, d=0.695, g=0.713\n",
            ">86, 132/234, d=0.686, g=0.723\n",
            ">86, 133/234, d=0.696, g=0.718\n",
            ">86, 134/234, d=0.692, g=0.698\n",
            ">86, 135/234, d=0.694, g=0.688\n",
            ">86, 136/234, d=0.697, g=0.708\n",
            ">86, 137/234, d=0.690, g=0.707\n",
            ">86, 138/234, d=0.688, g=0.689\n",
            ">86, 139/234, d=0.693, g=0.689\n",
            ">86, 140/234, d=0.691, g=0.694\n",
            ">86, 141/234, d=0.694, g=0.718\n",
            ">86, 142/234, d=0.698, g=0.721\n",
            ">86, 143/234, d=0.688, g=0.719\n",
            ">86, 144/234, d=0.692, g=0.696\n",
            ">86, 145/234, d=0.695, g=0.678\n",
            ">86, 146/234, d=0.696, g=0.673\n",
            ">86, 147/234, d=0.687, g=0.703\n",
            ">86, 148/234, d=0.690, g=0.726\n",
            ">86, 149/234, d=0.687, g=0.711\n",
            ">86, 150/234, d=0.690, g=0.682\n",
            ">86, 151/234, d=0.695, g=0.664\n",
            ">86, 152/234, d=0.697, g=0.706\n",
            ">86, 153/234, d=0.696, g=0.742\n",
            ">86, 154/234, d=0.696, g=0.733\n",
            ">86, 155/234, d=0.688, g=0.707\n",
            ">86, 156/234, d=0.690, g=0.695\n",
            ">86, 157/234, d=0.689, g=0.678\n",
            ">86, 158/234, d=0.689, g=0.706\n",
            ">86, 159/234, d=0.683, g=0.710\n",
            ">86, 160/234, d=0.692, g=0.699\n",
            ">86, 161/234, d=0.689, g=0.685\n",
            ">86, 162/234, d=0.693, g=0.685\n",
            ">86, 163/234, d=0.689, g=0.689\n",
            ">86, 164/234, d=0.687, g=0.705\n",
            ">86, 165/234, d=0.693, g=0.697\n",
            ">86, 166/234, d=0.691, g=0.696\n",
            ">86, 167/234, d=0.691, g=0.699\n",
            ">86, 168/234, d=0.685, g=0.696\n",
            ">86, 169/234, d=0.693, g=0.714\n",
            ">86, 170/234, d=0.686, g=0.715\n",
            ">86, 171/234, d=0.695, g=0.695\n",
            ">86, 172/234, d=0.695, g=0.701\n",
            ">86, 173/234, d=0.696, g=0.695\n",
            ">86, 174/234, d=0.696, g=0.703\n",
            ">86, 175/234, d=0.691, g=0.730\n",
            ">86, 176/234, d=0.690, g=0.730\n",
            ">86, 177/234, d=0.683, g=0.702\n",
            ">86, 178/234, d=0.687, g=0.691\n",
            ">86, 179/234, d=0.689, g=0.697\n",
            ">86, 180/234, d=0.687, g=0.700\n",
            ">86, 181/234, d=0.694, g=0.692\n",
            ">86, 182/234, d=0.689, g=0.688\n",
            ">86, 183/234, d=0.689, g=0.697\n",
            ">86, 184/234, d=0.694, g=0.723\n",
            ">86, 185/234, d=0.688, g=0.725\n",
            ">86, 186/234, d=0.692, g=0.702\n",
            ">86, 187/234, d=0.694, g=0.689\n",
            ">86, 188/234, d=0.690, g=0.694\n",
            ">86, 189/234, d=0.691, g=0.702\n",
            ">86, 190/234, d=0.693, g=0.710\n",
            ">86, 191/234, d=0.694, g=0.696\n",
            ">86, 192/234, d=0.689, g=0.698\n",
            ">86, 193/234, d=0.693, g=0.690\n",
            ">86, 194/234, d=0.695, g=0.701\n",
            ">86, 195/234, d=0.685, g=0.713\n",
            ">86, 196/234, d=0.697, g=0.716\n",
            ">86, 197/234, d=0.685, g=0.706\n",
            ">86, 198/234, d=0.688, g=0.705\n",
            ">86, 199/234, d=0.690, g=0.689\n",
            ">86, 200/234, d=0.697, g=0.694\n",
            ">86, 201/234, d=0.687, g=0.702\n",
            ">86, 202/234, d=0.694, g=0.686\n",
            ">86, 203/234, d=0.697, g=0.693\n",
            ">86, 204/234, d=0.688, g=0.693\n",
            ">86, 205/234, d=0.684, g=0.717\n",
            ">86, 206/234, d=0.690, g=0.715\n",
            ">86, 207/234, d=0.683, g=0.712\n",
            ">86, 208/234, d=0.689, g=0.722\n",
            ">86, 209/234, d=0.694, g=0.713\n",
            ">86, 210/234, d=0.689, g=0.703\n",
            ">86, 211/234, d=0.691, g=0.684\n",
            ">86, 212/234, d=0.697, g=0.711\n",
            ">86, 213/234, d=0.688, g=0.706\n",
            ">86, 214/234, d=0.694, g=0.697\n",
            ">86, 215/234, d=0.694, g=0.690\n",
            ">86, 216/234, d=0.693, g=0.701\n",
            ">86, 217/234, d=0.689, g=0.709\n",
            ">86, 218/234, d=0.696, g=0.729\n",
            ">86, 219/234, d=0.696, g=0.708\n",
            ">86, 220/234, d=0.684, g=0.706\n",
            ">86, 221/234, d=0.689, g=0.694\n",
            ">86, 222/234, d=0.694, g=0.692\n",
            ">86, 223/234, d=0.688, g=0.713\n",
            ">86, 224/234, d=0.687, g=0.699\n",
            ">86, 225/234, d=0.697, g=0.691\n",
            ">86, 226/234, d=0.690, g=0.698\n",
            ">86, 227/234, d=0.693, g=0.705\n",
            ">86, 228/234, d=0.699, g=0.712\n",
            ">86, 229/234, d=0.687, g=0.721\n",
            ">86, 230/234, d=0.693, g=0.719\n",
            ">86, 231/234, d=0.686, g=0.706\n",
            ">86, 232/234, d=0.696, g=0.704\n",
            ">86, 233/234, d=0.694, g=0.685\n",
            ">86, 234/234, d=0.691, g=0.684\n",
            ">87, 1/234, d=0.695, g=0.707\n",
            ">87, 2/234, d=0.689, g=0.719\n",
            ">87, 3/234, d=0.684, g=0.721\n",
            ">87, 4/234, d=0.692, g=0.694\n",
            ">87, 5/234, d=0.693, g=0.703\n",
            ">87, 6/234, d=0.686, g=0.686\n",
            ">87, 7/234, d=0.682, g=0.675\n",
            ">87, 8/234, d=0.685, g=0.685\n",
            ">87, 9/234, d=0.691, g=0.708\n",
            ">87, 10/234, d=0.688, g=0.709\n",
            ">87, 11/234, d=0.700, g=0.707\n",
            ">87, 12/234, d=0.694, g=0.694\n",
            ">87, 13/234, d=0.690, g=0.696\n",
            ">87, 14/234, d=0.688, g=0.706\n",
            ">87, 15/234, d=0.682, g=0.725\n",
            ">87, 16/234, d=0.689, g=0.707\n",
            ">87, 17/234, d=0.690, g=0.693\n",
            ">87, 18/234, d=0.687, g=0.713\n",
            ">87, 19/234, d=0.694, g=0.712\n",
            ">87, 20/234, d=0.696, g=0.697\n",
            ">87, 21/234, d=0.689, g=0.680\n",
            ">87, 22/234, d=0.697, g=0.670\n",
            ">87, 23/234, d=0.684, g=0.677\n",
            ">87, 24/234, d=0.689, g=0.706\n",
            ">87, 25/234, d=0.694, g=0.721\n",
            ">87, 26/234, d=0.694, g=0.719\n",
            ">87, 27/234, d=0.693, g=0.711\n",
            ">87, 28/234, d=0.695, g=0.692\n",
            ">87, 29/234, d=0.686, g=0.701\n",
            ">87, 30/234, d=0.692, g=0.711\n",
            ">87, 31/234, d=0.691, g=0.705\n",
            ">87, 32/234, d=0.696, g=0.690\n",
            ">87, 33/234, d=0.699, g=0.690\n",
            ">87, 34/234, d=0.698, g=0.694\n",
            ">87, 35/234, d=0.688, g=0.729\n",
            ">87, 36/234, d=0.694, g=0.718\n",
            ">87, 37/234, d=0.694, g=0.702\n",
            ">87, 38/234, d=0.694, g=0.672\n",
            ">87, 39/234, d=0.689, g=0.671\n",
            ">87, 40/234, d=0.700, g=0.699\n",
            ">87, 41/234, d=0.690, g=0.761\n",
            ">87, 42/234, d=0.688, g=0.737\n",
            ">87, 43/234, d=0.693, g=0.701\n",
            ">87, 44/234, d=0.692, g=0.673\n",
            ">87, 45/234, d=0.690, g=0.670\n",
            ">87, 46/234, d=0.690, g=0.689\n",
            ">87, 47/234, d=0.691, g=0.715\n",
            ">87, 48/234, d=0.689, g=0.732\n",
            ">87, 49/234, d=0.690, g=0.715\n",
            ">87, 50/234, d=0.700, g=0.705\n",
            ">87, 51/234, d=0.700, g=0.693\n",
            ">87, 52/234, d=0.687, g=0.675\n",
            ">87, 53/234, d=0.692, g=0.688\n",
            ">87, 54/234, d=0.687, g=0.703\n",
            ">87, 55/234, d=0.694, g=0.716\n",
            ">87, 56/234, d=0.689, g=0.703\n",
            ">87, 57/234, d=0.684, g=0.689\n",
            ">87, 58/234, d=0.689, g=0.699\n",
            ">87, 59/234, d=0.689, g=0.708\n",
            ">87, 60/234, d=0.687, g=0.720\n",
            ">87, 61/234, d=0.681, g=0.708\n",
            ">87, 62/234, d=0.691, g=0.691\n",
            ">87, 63/234, d=0.693, g=0.677\n",
            ">87, 64/234, d=0.687, g=0.682\n",
            ">87, 65/234, d=0.691, g=0.710\n",
            ">87, 66/234, d=0.696, g=0.713\n",
            ">87, 67/234, d=0.693, g=0.702\n",
            ">87, 68/234, d=0.690, g=0.703\n",
            ">87, 69/234, d=0.690, g=0.707\n",
            ">87, 70/234, d=0.692, g=0.709\n",
            ">87, 71/234, d=0.691, g=0.716\n",
            ">87, 72/234, d=0.687, g=0.704\n",
            ">87, 73/234, d=0.692, g=0.697\n",
            ">87, 74/234, d=0.690, g=0.681\n",
            ">87, 75/234, d=0.693, g=0.669\n",
            ">87, 76/234, d=0.691, g=0.706\n",
            ">87, 77/234, d=0.693, g=0.704\n",
            ">87, 78/234, d=0.694, g=0.693\n",
            ">87, 79/234, d=0.691, g=0.696\n",
            ">87, 80/234, d=0.691, g=0.708\n",
            ">87, 81/234, d=0.693, g=0.725\n",
            ">87, 82/234, d=0.696, g=0.701\n",
            ">87, 83/234, d=0.688, g=0.708\n",
            ">87, 84/234, d=0.688, g=0.702\n",
            ">87, 85/234, d=0.683, g=0.702\n",
            ">87, 86/234, d=0.694, g=0.689\n",
            ">87, 87/234, d=0.691, g=0.682\n",
            ">87, 88/234, d=0.688, g=0.693\n",
            ">87, 89/234, d=0.688, g=0.699\n",
            ">87, 90/234, d=0.691, g=0.720\n",
            ">87, 91/234, d=0.689, g=0.709\n",
            ">87, 92/234, d=0.695, g=0.701\n",
            ">87, 93/234, d=0.686, g=0.697\n",
            ">87, 94/234, d=0.686, g=0.706\n",
            ">87, 95/234, d=0.696, g=0.703\n",
            ">87, 96/234, d=0.691, g=0.711\n",
            ">87, 97/234, d=0.689, g=0.696\n",
            ">87, 98/234, d=0.695, g=0.680\n",
            ">87, 99/234, d=0.684, g=0.681\n",
            ">87, 100/234, d=0.693, g=0.717\n",
            ">87, 101/234, d=0.694, g=0.710\n",
            ">87, 102/234, d=0.694, g=0.711\n",
            ">87, 103/234, d=0.692, g=0.690\n",
            ">87, 104/234, d=0.696, g=0.689\n",
            ">87, 105/234, d=0.686, g=0.692\n",
            ">87, 106/234, d=0.692, g=0.699\n",
            ">87, 107/234, d=0.701, g=0.708\n",
            ">87, 108/234, d=0.690, g=0.694\n",
            ">87, 109/234, d=0.689, g=0.691\n",
            ">87, 110/234, d=0.689, g=0.702\n",
            ">87, 111/234, d=0.690, g=0.715\n",
            ">87, 112/234, d=0.690, g=0.725\n",
            ">87, 113/234, d=0.683, g=0.708\n",
            ">87, 114/234, d=0.694, g=0.701\n",
            ">87, 115/234, d=0.696, g=0.705\n",
            ">87, 116/234, d=0.695, g=0.704\n",
            ">87, 117/234, d=0.695, g=0.686\n",
            ">87, 118/234, d=0.690, g=0.693\n",
            ">87, 119/234, d=0.693, g=0.711\n",
            ">87, 120/234, d=0.689, g=0.714\n",
            ">87, 121/234, d=0.690, g=0.709\n",
            ">87, 122/234, d=0.689, g=0.719\n",
            ">87, 123/234, d=0.693, g=0.724\n",
            ">87, 124/234, d=0.693, g=0.727\n",
            ">87, 125/234, d=0.681, g=0.699\n",
            ">87, 126/234, d=0.694, g=0.681\n",
            ">87, 127/234, d=0.699, g=0.680\n",
            ">87, 128/234, d=0.692, g=0.697\n",
            ">87, 129/234, d=0.692, g=0.714\n",
            ">87, 130/234, d=0.696, g=0.702\n",
            ">87, 131/234, d=0.687, g=0.704\n",
            ">87, 132/234, d=0.685, g=0.681\n",
            ">87, 133/234, d=0.695, g=0.694\n",
            ">87, 134/234, d=0.693, g=0.692\n",
            ">87, 135/234, d=0.691, g=0.695\n",
            ">87, 136/234, d=0.689, g=0.703\n",
            ">87, 137/234, d=0.692, g=0.705\n",
            ">87, 138/234, d=0.696, g=0.721\n",
            ">87, 139/234, d=0.693, g=0.716\n",
            ">87, 140/234, d=0.696, g=0.708\n",
            ">87, 141/234, d=0.693, g=0.704\n",
            ">87, 142/234, d=0.684, g=0.686\n",
            ">87, 143/234, d=0.694, g=0.697\n",
            ">87, 144/234, d=0.688, g=0.695\n",
            ">87, 145/234, d=0.697, g=0.682\n",
            ">87, 146/234, d=0.696, g=0.703\n",
            ">87, 147/234, d=0.690, g=0.712\n",
            ">87, 148/234, d=0.688, g=0.721\n",
            ">87, 149/234, d=0.684, g=0.723\n",
            ">87, 150/234, d=0.687, g=0.705\n",
            ">87, 151/234, d=0.696, g=0.700\n",
            ">87, 152/234, d=0.695, g=0.713\n",
            ">87, 153/234, d=0.698, g=0.719\n",
            ">87, 154/234, d=0.692, g=0.712\n",
            ">87, 155/234, d=0.691, g=0.683\n",
            ">87, 156/234, d=0.693, g=0.687\n",
            ">87, 157/234, d=0.688, g=0.697\n",
            ">87, 158/234, d=0.696, g=0.705\n",
            ">87, 159/234, d=0.692, g=0.698\n",
            ">87, 160/234, d=0.699, g=0.701\n",
            ">87, 161/234, d=0.694, g=0.709\n",
            ">87, 162/234, d=0.693, g=0.722\n",
            ">87, 163/234, d=0.689, g=0.713\n",
            ">87, 164/234, d=0.688, g=0.706\n",
            ">87, 165/234, d=0.693, g=0.691\n",
            ">87, 166/234, d=0.688, g=0.681\n",
            ">87, 167/234, d=0.697, g=0.693\n",
            ">87, 168/234, d=0.698, g=0.706\n",
            ">87, 169/234, d=0.697, g=0.700\n",
            ">87, 170/234, d=0.684, g=0.715\n",
            ">87, 171/234, d=0.696, g=0.706\n",
            ">87, 172/234, d=0.699, g=0.696\n",
            ">87, 173/234, d=0.689, g=0.704\n",
            ">87, 174/234, d=0.693, g=0.697\n",
            ">87, 175/234, d=0.684, g=0.710\n",
            ">87, 176/234, d=0.688, g=0.698\n",
            ">87, 177/234, d=0.689, g=0.691\n",
            ">87, 178/234, d=0.687, g=0.695\n",
            ">87, 179/234, d=0.694, g=0.703\n",
            ">87, 180/234, d=0.700, g=0.698\n",
            ">87, 181/234, d=0.696, g=0.697\n",
            ">87, 182/234, d=0.691, g=0.710\n",
            ">87, 183/234, d=0.691, g=0.714\n",
            ">87, 184/234, d=0.690, g=0.707\n",
            ">87, 185/234, d=0.689, g=0.687\n",
            ">87, 186/234, d=0.700, g=0.689\n",
            ">87, 187/234, d=0.692, g=0.696\n",
            ">87, 188/234, d=0.688, g=0.702\n",
            ">87, 189/234, d=0.688, g=0.706\n",
            ">87, 190/234, d=0.684, g=0.707\n",
            ">87, 191/234, d=0.688, g=0.701\n",
            ">87, 192/234, d=0.696, g=0.706\n",
            ">87, 193/234, d=0.692, g=0.702\n",
            ">87, 194/234, d=0.686, g=0.695\n",
            ">87, 195/234, d=0.689, g=0.698\n",
            ">87, 196/234, d=0.687, g=0.710\n",
            ">87, 197/234, d=0.690, g=0.703\n",
            ">87, 198/234, d=0.692, g=0.717\n",
            ">87, 199/234, d=0.685, g=0.703\n",
            ">87, 200/234, d=0.690, g=0.695\n",
            ">87, 201/234, d=0.690, g=0.691\n",
            ">87, 202/234, d=0.695, g=0.698\n",
            ">87, 203/234, d=0.688, g=0.712\n",
            ">87, 204/234, d=0.693, g=0.721\n",
            ">87, 205/234, d=0.683, g=0.714\n",
            ">87, 206/234, d=0.693, g=0.684\n",
            ">87, 207/234, d=0.698, g=0.682\n",
            ">87, 208/234, d=0.686, g=0.692\n",
            ">87, 209/234, d=0.692, g=0.690\n",
            ">87, 210/234, d=0.694, g=0.699\n",
            ">87, 211/234, d=0.694, g=0.715\n",
            ">87, 212/234, d=0.693, g=0.717\n",
            ">87, 213/234, d=0.698, g=0.687\n",
            ">87, 214/234, d=0.686, g=0.715\n",
            ">87, 215/234, d=0.696, g=0.719\n",
            ">87, 216/234, d=0.691, g=0.703\n",
            ">87, 217/234, d=0.689, g=0.692\n",
            ">87, 218/234, d=0.690, g=0.682\n",
            ">87, 219/234, d=0.687, g=0.702\n",
            ">87, 220/234, d=0.695, g=0.708\n",
            ">87, 221/234, d=0.685, g=0.701\n",
            ">87, 222/234, d=0.684, g=0.694\n",
            ">87, 223/234, d=0.691, g=0.702\n",
            ">87, 224/234, d=0.688, g=0.696\n",
            ">87, 225/234, d=0.691, g=0.709\n",
            ">87, 226/234, d=0.692, g=0.711\n",
            ">87, 227/234, d=0.685, g=0.696\n",
            ">87, 228/234, d=0.691, g=0.692\n",
            ">87, 229/234, d=0.686, g=0.699\n",
            ">87, 230/234, d=0.692, g=0.698\n",
            ">87, 231/234, d=0.690, g=0.712\n",
            ">87, 232/234, d=0.690, g=0.715\n",
            ">87, 233/234, d=0.695, g=0.704\n",
            ">87, 234/234, d=0.693, g=0.697\n",
            ">88, 1/234, d=0.695, g=0.689\n",
            ">88, 2/234, d=0.689, g=0.694\n",
            ">88, 3/234, d=0.691, g=0.717\n",
            ">88, 4/234, d=0.695, g=0.721\n",
            ">88, 5/234, d=0.687, g=0.708\n",
            ">88, 6/234, d=0.695, g=0.700\n",
            ">88, 7/234, d=0.687, g=0.687\n",
            ">88, 8/234, d=0.690, g=0.682\n",
            ">88, 9/234, d=0.693, g=0.697\n",
            ">88, 10/234, d=0.693, g=0.700\n",
            ">88, 11/234, d=0.691, g=0.701\n",
            ">88, 12/234, d=0.695, g=0.713\n",
            ">88, 13/234, d=0.686, g=0.710\n",
            ">88, 14/234, d=0.689, g=0.698\n",
            ">88, 15/234, d=0.688, g=0.678\n",
            ">88, 16/234, d=0.687, g=0.691\n",
            ">88, 17/234, d=0.692, g=0.715\n",
            ">88, 18/234, d=0.692, g=0.735\n",
            ">88, 19/234, d=0.690, g=0.710\n",
            ">88, 20/234, d=0.692, g=0.687\n",
            ">88, 21/234, d=0.690, g=0.683\n",
            ">88, 22/234, d=0.691, g=0.682\n",
            ">88, 23/234, d=0.689, g=0.704\n",
            ">88, 24/234, d=0.695, g=0.710\n",
            ">88, 25/234, d=0.690, g=0.731\n",
            ">88, 26/234, d=0.692, g=0.720\n",
            ">88, 27/234, d=0.689, g=0.693\n",
            ">88, 28/234, d=0.690, g=0.704\n",
            ">88, 29/234, d=0.696, g=0.687\n",
            ">88, 30/234, d=0.698, g=0.706\n",
            ">88, 31/234, d=0.691, g=0.701\n",
            ">88, 32/234, d=0.689, g=0.706\n",
            ">88, 33/234, d=0.695, g=0.713\n",
            ">88, 34/234, d=0.690, g=0.714\n",
            ">88, 35/234, d=0.686, g=0.719\n",
            ">88, 36/234, d=0.689, g=0.709\n",
            ">88, 37/234, d=0.695, g=0.703\n",
            ">88, 38/234, d=0.686, g=0.693\n",
            ">88, 39/234, d=0.690, g=0.701\n",
            ">88, 40/234, d=0.689, g=0.703\n",
            ">88, 41/234, d=0.686, g=0.705\n",
            ">88, 42/234, d=0.688, g=0.696\n",
            ">88, 43/234, d=0.687, g=0.696\n",
            ">88, 44/234, d=0.680, g=0.707\n",
            ">88, 45/234, d=0.693, g=0.731\n",
            ">88, 46/234, d=0.696, g=0.722\n",
            ">88, 47/234, d=0.697, g=0.709\n",
            ">88, 48/234, d=0.690, g=0.679\n",
            ">88, 49/234, d=0.690, g=0.677\n",
            ">88, 50/234, d=0.688, g=0.699\n",
            ">88, 51/234, d=0.685, g=0.716\n",
            ">88, 52/234, d=0.694, g=0.698\n",
            ">88, 53/234, d=0.694, g=0.678\n",
            ">88, 54/234, d=0.692, g=0.667\n",
            ">88, 55/234, d=0.697, g=0.694\n",
            ">88, 56/234, d=0.696, g=0.739\n",
            ">88, 57/234, d=0.691, g=0.748\n",
            ">88, 58/234, d=0.689, g=0.713\n",
            ">88, 59/234, d=0.694, g=0.677\n",
            ">88, 60/234, d=0.691, g=0.673\n",
            ">88, 61/234, d=0.693, g=0.690\n",
            ">88, 62/234, d=0.690, g=0.687\n",
            ">88, 63/234, d=0.682, g=0.694\n",
            ">88, 64/234, d=0.685, g=0.692\n",
            ">88, 65/234, d=0.693, g=0.704\n",
            ">88, 66/234, d=0.691, g=0.728\n",
            ">88, 67/234, d=0.690, g=0.715\n",
            ">88, 68/234, d=0.686, g=0.714\n",
            ">88, 69/234, d=0.688, g=0.705\n",
            ">88, 70/234, d=0.691, g=0.686\n",
            ">88, 71/234, d=0.691, g=0.689\n",
            ">88, 72/234, d=0.693, g=0.697\n",
            ">88, 73/234, d=0.700, g=0.691\n",
            ">88, 74/234, d=0.695, g=0.701\n",
            ">88, 75/234, d=0.688, g=0.697\n",
            ">88, 76/234, d=0.686, g=0.712\n",
            ">88, 77/234, d=0.688, g=0.705\n",
            ">88, 78/234, d=0.689, g=0.709\n",
            ">88, 79/234, d=0.683, g=0.694\n",
            ">88, 80/234, d=0.690, g=0.690\n",
            ">88, 81/234, d=0.692, g=0.701\n",
            ">88, 82/234, d=0.688, g=0.711\n",
            ">88, 83/234, d=0.683, g=0.711\n",
            ">88, 84/234, d=0.694, g=0.707\n",
            ">88, 85/234, d=0.687, g=0.715\n",
            ">88, 86/234, d=0.691, g=0.713\n",
            ">88, 87/234, d=0.692, g=0.696\n",
            ">88, 88/234, d=0.701, g=0.692\n",
            ">88, 89/234, d=0.693, g=0.692\n",
            ">88, 90/234, d=0.691, g=0.687\n",
            ">88, 91/234, d=0.693, g=0.692\n",
            ">88, 92/234, d=0.696, g=0.701\n",
            ">88, 93/234, d=0.686, g=0.720\n",
            ">88, 94/234, d=0.692, g=0.739\n",
            ">88, 95/234, d=0.688, g=0.709\n",
            ">88, 96/234, d=0.683, g=0.685\n",
            ">88, 97/234, d=0.696, g=0.686\n",
            ">88, 98/234, d=0.691, g=0.694\n",
            ">88, 99/234, d=0.698, g=0.721\n",
            ">88, 100/234, d=0.692, g=0.696\n",
            ">88, 101/234, d=0.685, g=0.695\n",
            ">88, 102/234, d=0.696, g=0.693\n",
            ">88, 103/234, d=0.687, g=0.707\n",
            ">88, 104/234, d=0.698, g=0.709\n",
            ">88, 105/234, d=0.685, g=0.708\n",
            ">88, 106/234, d=0.696, g=0.716\n",
            ">88, 107/234, d=0.684, g=0.704\n",
            ">88, 108/234, d=0.689, g=0.680\n",
            ">88, 109/234, d=0.697, g=0.680\n",
            ">88, 110/234, d=0.691, g=0.684\n",
            ">88, 111/234, d=0.693, g=0.698\n",
            ">88, 112/234, d=0.694, g=0.710\n",
            ">88, 113/234, d=0.693, g=0.719\n",
            ">88, 114/234, d=0.691, g=0.707\n",
            ">88, 115/234, d=0.695, g=0.704\n",
            ">88, 116/234, d=0.685, g=0.696\n",
            ">88, 117/234, d=0.694, g=0.720\n",
            ">88, 118/234, d=0.700, g=0.721\n",
            ">88, 119/234, d=0.698, g=0.714\n",
            ">88, 120/234, d=0.688, g=0.702\n",
            ">88, 121/234, d=0.687, g=0.689\n",
            ">88, 122/234, d=0.697, g=0.695\n",
            ">88, 123/234, d=0.701, g=0.687\n",
            ">88, 124/234, d=0.693, g=0.709\n",
            ">88, 125/234, d=0.686, g=0.710\n",
            ">88, 126/234, d=0.698, g=0.685\n",
            ">88, 127/234, d=0.695, g=0.681\n",
            ">88, 128/234, d=0.689, g=0.708\n",
            ">88, 129/234, d=0.694, g=0.713\n",
            ">88, 130/234, d=0.697, g=0.694\n",
            ">88, 131/234, d=0.692, g=0.685\n",
            ">88, 132/234, d=0.693, g=0.691\n",
            ">88, 133/234, d=0.694, g=0.713\n",
            ">88, 134/234, d=0.692, g=0.717\n",
            ">88, 135/234, d=0.693, g=0.705\n",
            ">88, 136/234, d=0.694, g=0.715\n",
            ">88, 137/234, d=0.691, g=0.698\n",
            ">88, 138/234, d=0.693, g=0.690\n",
            ">88, 139/234, d=0.691, g=0.702\n",
            ">88, 140/234, d=0.696, g=0.711\n",
            ">88, 141/234, d=0.693, g=0.686\n",
            ">88, 142/234, d=0.689, g=0.676\n",
            ">88, 143/234, d=0.694, g=0.684\n",
            ">88, 144/234, d=0.687, g=0.706\n",
            ">88, 145/234, d=0.697, g=0.706\n",
            ">88, 146/234, d=0.694, g=0.705\n",
            ">88, 147/234, d=0.693, g=0.691\n",
            ">88, 148/234, d=0.696, g=0.703\n",
            ">88, 149/234, d=0.698, g=0.726\n",
            ">88, 150/234, d=0.698, g=0.718\n",
            ">88, 151/234, d=0.687, g=0.701\n",
            ">88, 152/234, d=0.691, g=0.700\n",
            ">88, 153/234, d=0.682, g=0.695\n",
            ">88, 154/234, d=0.694, g=0.696\n",
            ">88, 155/234, d=0.686, g=0.705\n",
            ">88, 156/234, d=0.694, g=0.711\n",
            ">88, 157/234, d=0.687, g=0.701\n",
            ">88, 158/234, d=0.699, g=0.694\n",
            ">88, 159/234, d=0.688, g=0.689\n",
            ">88, 160/234, d=0.695, g=0.692\n",
            ">88, 161/234, d=0.688, g=0.709\n",
            ">88, 162/234, d=0.690, g=0.727\n",
            ">88, 163/234, d=0.691, g=0.733\n",
            ">88, 164/234, d=0.683, g=0.698\n",
            ">88, 165/234, d=0.694, g=0.683\n",
            ">88, 166/234, d=0.690, g=0.680\n",
            ">88, 167/234, d=0.689, g=0.698\n",
            ">88, 168/234, d=0.693, g=0.708\n",
            ">88, 169/234, d=0.694, g=0.711\n",
            ">88, 170/234, d=0.689, g=0.681\n",
            ">88, 171/234, d=0.691, g=0.677\n",
            ">88, 172/234, d=0.695, g=0.695\n",
            ">88, 173/234, d=0.696, g=0.708\n",
            ">88, 174/234, d=0.697, g=0.726\n",
            ">88, 175/234, d=0.691, g=0.727\n",
            ">88, 176/234, d=0.694, g=0.712\n",
            ">88, 177/234, d=0.691, g=0.689\n",
            ">88, 178/234, d=0.691, g=0.672\n",
            ">88, 179/234, d=0.689, g=0.677\n",
            ">88, 180/234, d=0.692, g=0.713\n",
            ">88, 181/234, d=0.694, g=0.734\n",
            ">88, 182/234, d=0.694, g=0.721\n",
            ">88, 183/234, d=0.684, g=0.697\n",
            ">88, 184/234, d=0.694, g=0.686\n",
            ">88, 185/234, d=0.699, g=0.700\n",
            ">88, 186/234, d=0.691, g=0.719\n",
            ">88, 187/234, d=0.694, g=0.709\n",
            ">88, 188/234, d=0.688, g=0.686\n",
            ">88, 189/234, d=0.684, g=0.672\n",
            ">88, 190/234, d=0.695, g=0.685\n",
            ">88, 191/234, d=0.685, g=0.726\n",
            ">88, 192/234, d=0.692, g=0.734\n",
            ">88, 193/234, d=0.697, g=0.729\n",
            ">88, 194/234, d=0.692, g=0.695\n",
            ">88, 195/234, d=0.696, g=0.686\n",
            ">88, 196/234, d=0.685, g=0.680\n",
            ">88, 197/234, d=0.692, g=0.701\n",
            ">88, 198/234, d=0.696, g=0.711\n",
            ">88, 199/234, d=0.698, g=0.696\n",
            ">88, 200/234, d=0.689, g=0.694\n",
            ">88, 201/234, d=0.694, g=0.706\n",
            ">88, 202/234, d=0.691, g=0.703\n",
            ">88, 203/234, d=0.692, g=0.702\n",
            ">88, 204/234, d=0.685, g=0.702\n",
            ">88, 205/234, d=0.692, g=0.713\n",
            ">88, 206/234, d=0.695, g=0.714\n",
            ">88, 207/234, d=0.695, g=0.689\n",
            ">88, 208/234, d=0.689, g=0.696\n",
            ">88, 209/234, d=0.693, g=0.698\n",
            ">88, 210/234, d=0.687, g=0.717\n",
            ">88, 211/234, d=0.689, g=0.699\n",
            ">88, 212/234, d=0.685, g=0.691\n",
            ">88, 213/234, d=0.699, g=0.695\n",
            ">88, 214/234, d=0.689, g=0.718\n",
            ">88, 215/234, d=0.690, g=0.716\n",
            ">88, 216/234, d=0.695, g=0.706\n",
            ">88, 217/234, d=0.689, g=0.697\n",
            ">88, 218/234, d=0.692, g=0.704\n",
            ">88, 219/234, d=0.687, g=0.703\n",
            ">88, 220/234, d=0.692, g=0.703\n",
            ">88, 221/234, d=0.686, g=0.702\n",
            ">88, 222/234, d=0.693, g=0.695\n",
            ">88, 223/234, d=0.686, g=0.691\n",
            ">88, 224/234, d=0.686, g=0.689\n",
            ">88, 225/234, d=0.688, g=0.701\n",
            ">88, 226/234, d=0.689, g=0.699\n",
            ">88, 227/234, d=0.689, g=0.701\n",
            ">88, 228/234, d=0.695, g=0.707\n",
            ">88, 229/234, d=0.691, g=0.710\n",
            ">88, 230/234, d=0.690, g=0.708\n",
            ">88, 231/234, d=0.690, g=0.696\n",
            ">88, 232/234, d=0.688, g=0.692\n",
            ">88, 233/234, d=0.695, g=0.684\n",
            ">88, 234/234, d=0.687, g=0.693\n",
            ">89, 1/234, d=0.691, g=0.709\n",
            ">89, 2/234, d=0.694, g=0.710\n",
            ">89, 3/234, d=0.686, g=0.712\n",
            ">89, 4/234, d=0.689, g=0.700\n",
            ">89, 5/234, d=0.691, g=0.687\n",
            ">89, 6/234, d=0.697, g=0.685\n",
            ">89, 7/234, d=0.693, g=0.703\n",
            ">89, 8/234, d=0.687, g=0.710\n",
            ">89, 9/234, d=0.691, g=0.698\n",
            ">89, 10/234, d=0.691, g=0.698\n",
            ">89, 11/234, d=0.690, g=0.715\n",
            ">89, 12/234, d=0.690, g=0.704\n",
            ">89, 13/234, d=0.694, g=0.691\n",
            ">89, 14/234, d=0.686, g=0.693\n",
            ">89, 15/234, d=0.691, g=0.703\n",
            ">89, 16/234, d=0.692, g=0.696\n",
            ">89, 17/234, d=0.688, g=0.723\n",
            ">89, 18/234, d=0.700, g=0.718\n",
            ">89, 19/234, d=0.687, g=0.705\n",
            ">89, 20/234, d=0.701, g=0.685\n",
            ">89, 21/234, d=0.683, g=0.678\n",
            ">89, 22/234, d=0.690, g=0.690\n",
            ">89, 23/234, d=0.697, g=0.706\n",
            ">89, 24/234, d=0.687, g=0.703\n",
            ">89, 25/234, d=0.682, g=0.700\n",
            ">89, 26/234, d=0.689, g=0.695\n",
            ">89, 27/234, d=0.693, g=0.705\n",
            ">89, 28/234, d=0.688, g=0.717\n",
            ">89, 29/234, d=0.693, g=0.700\n",
            ">89, 30/234, d=0.697, g=0.702\n",
            ">89, 31/234, d=0.692, g=0.701\n",
            ">89, 32/234, d=0.695, g=0.701\n",
            ">89, 33/234, d=0.691, g=0.689\n",
            ">89, 34/234, d=0.692, g=0.701\n",
            ">89, 35/234, d=0.691, g=0.695\n",
            ">89, 36/234, d=0.693, g=0.691\n",
            ">89, 37/234, d=0.692, g=0.695\n",
            ">89, 38/234, d=0.697, g=0.686\n",
            ">89, 39/234, d=0.698, g=0.701\n",
            ">89, 40/234, d=0.689, g=0.712\n",
            ">89, 41/234, d=0.691, g=0.717\n",
            ">89, 42/234, d=0.691, g=0.710\n",
            ">89, 43/234, d=0.690, g=0.698\n",
            ">89, 44/234, d=0.690, g=0.701\n",
            ">89, 45/234, d=0.691, g=0.703\n",
            ">89, 46/234, d=0.695, g=0.712\n",
            ">89, 47/234, d=0.687, g=0.708\n",
            ">89, 48/234, d=0.692, g=0.688\n",
            ">89, 49/234, d=0.692, g=0.704\n",
            ">89, 50/234, d=0.695, g=0.726\n",
            ">89, 51/234, d=0.682, g=0.719\n",
            ">89, 52/234, d=0.695, g=0.702\n",
            ">89, 53/234, d=0.693, g=0.708\n",
            ">89, 54/234, d=0.695, g=0.703\n",
            ">89, 55/234, d=0.685, g=0.683\n",
            ">89, 56/234, d=0.688, g=0.687\n",
            ">89, 57/234, d=0.684, g=0.693\n",
            ">89, 58/234, d=0.699, g=0.702\n",
            ">89, 59/234, d=0.698, g=0.716\n",
            ">89, 60/234, d=0.686, g=0.708\n",
            ">89, 61/234, d=0.679, g=0.690\n",
            ">89, 62/234, d=0.703, g=0.686\n",
            ">89, 63/234, d=0.682, g=0.712\n",
            ">89, 64/234, d=0.691, g=0.699\n",
            ">89, 65/234, d=0.693, g=0.703\n",
            ">89, 66/234, d=0.699, g=0.695\n",
            ">89, 67/234, d=0.697, g=0.697\n",
            ">89, 68/234, d=0.696, g=0.713\n",
            ">89, 69/234, d=0.690, g=0.710\n",
            ">89, 70/234, d=0.689, g=0.711\n",
            ">89, 71/234, d=0.698, g=0.711\n",
            ">89, 72/234, d=0.691, g=0.703\n",
            ">89, 73/234, d=0.689, g=0.712\n",
            ">89, 74/234, d=0.689, g=0.703\n",
            ">89, 75/234, d=0.693, g=0.675\n",
            ">89, 76/234, d=0.690, g=0.669\n",
            ">89, 77/234, d=0.689, g=0.694\n",
            ">89, 78/234, d=0.687, g=0.705\n",
            ">89, 79/234, d=0.690, g=0.738\n",
            ">89, 80/234, d=0.693, g=0.712\n",
            ">89, 81/234, d=0.688, g=0.693\n",
            ">89, 82/234, d=0.691, g=0.694\n",
            ">89, 83/234, d=0.693, g=0.703\n",
            ">89, 84/234, d=0.693, g=0.698\n",
            ">89, 85/234, d=0.687, g=0.702\n",
            ">89, 86/234, d=0.687, g=0.694\n",
            ">89, 87/234, d=0.693, g=0.690\n",
            ">89, 88/234, d=0.694, g=0.707\n",
            ">89, 89/234, d=0.689, g=0.719\n",
            ">89, 90/234, d=0.687, g=0.725\n",
            ">89, 91/234, d=0.691, g=0.723\n",
            ">89, 92/234, d=0.692, g=0.695\n",
            ">89, 93/234, d=0.686, g=0.668\n",
            ">89, 94/234, d=0.688, g=0.662\n",
            ">89, 95/234, d=0.691, g=0.694\n",
            ">89, 96/234, d=0.682, g=0.734\n",
            ">89, 97/234, d=0.688, g=0.721\n",
            ">89, 98/234, d=0.683, g=0.693\n",
            ">89, 99/234, d=0.695, g=0.692\n",
            ">89, 100/234, d=0.698, g=0.714\n",
            ">89, 101/234, d=0.693, g=0.728\n",
            ">89, 102/234, d=0.693, g=0.702\n",
            ">89, 103/234, d=0.692, g=0.682\n",
            ">89, 104/234, d=0.692, g=0.687\n",
            ">89, 105/234, d=0.693, g=0.717\n",
            ">89, 106/234, d=0.688, g=0.707\n",
            ">89, 107/234, d=0.685, g=0.697\n",
            ">89, 108/234, d=0.688, g=0.689\n",
            ">89, 109/234, d=0.680, g=0.693\n",
            ">89, 110/234, d=0.689, g=0.706\n",
            ">89, 111/234, d=0.690, g=0.710\n",
            ">89, 112/234, d=0.699, g=0.698\n",
            ">89, 113/234, d=0.695, g=0.698\n",
            ">89, 114/234, d=0.682, g=0.709\n",
            ">89, 115/234, d=0.689, g=0.717\n",
            ">89, 116/234, d=0.693, g=0.699\n",
            ">89, 117/234, d=0.695, g=0.698\n",
            ">89, 118/234, d=0.700, g=0.714\n",
            ">89, 119/234, d=0.701, g=0.703\n",
            ">89, 120/234, d=0.686, g=0.699\n",
            ">89, 121/234, d=0.690, g=0.709\n",
            ">89, 122/234, d=0.686, g=0.718\n",
            ">89, 123/234, d=0.692, g=0.695\n",
            ">89, 124/234, d=0.691, g=0.686\n",
            ">89, 125/234, d=0.685, g=0.673\n",
            ">89, 126/234, d=0.683, g=0.712\n",
            ">89, 127/234, d=0.699, g=0.728\n",
            ">89, 128/234, d=0.696, g=0.708\n",
            ">89, 129/234, d=0.690, g=0.693\n",
            ">89, 130/234, d=0.692, g=0.680\n",
            ">89, 131/234, d=0.693, g=0.697\n",
            ">89, 132/234, d=0.694, g=0.722\n",
            ">89, 133/234, d=0.690, g=0.721\n",
            ">89, 134/234, d=0.694, g=0.704\n",
            ">89, 135/234, d=0.689, g=0.684\n",
            ">89, 136/234, d=0.691, g=0.673\n",
            ">89, 137/234, d=0.687, g=0.686\n",
            ">89, 138/234, d=0.692, g=0.703\n",
            ">89, 139/234, d=0.689, g=0.707\n",
            ">89, 140/234, d=0.684, g=0.708\n",
            ">89, 141/234, d=0.690, g=0.696\n",
            ">89, 142/234, d=0.695, g=0.702\n",
            ">89, 143/234, d=0.687, g=0.709\n",
            ">89, 144/234, d=0.688, g=0.727\n",
            ">89, 145/234, d=0.692, g=0.708\n",
            ">89, 146/234, d=0.694, g=0.682\n",
            ">89, 147/234, d=0.692, g=0.671\n",
            ">89, 148/234, d=0.693, g=0.674\n",
            ">89, 149/234, d=0.693, g=0.697\n",
            ">89, 150/234, d=0.693, g=0.703\n",
            ">89, 151/234, d=0.686, g=0.697\n",
            ">89, 152/234, d=0.694, g=0.707\n",
            ">89, 153/234, d=0.697, g=0.728\n",
            ">89, 154/234, d=0.692, g=0.709\n",
            ">89, 155/234, d=0.689, g=0.707\n",
            ">89, 156/234, d=0.693, g=0.690\n",
            ">89, 157/234, d=0.691, g=0.691\n",
            ">89, 158/234, d=0.687, g=0.684\n",
            ">89, 159/234, d=0.690, g=0.688\n",
            ">89, 160/234, d=0.684, g=0.701\n",
            ">89, 161/234, d=0.696, g=0.706\n",
            ">89, 162/234, d=0.689, g=0.704\n",
            ">89, 163/234, d=0.689, g=0.692\n",
            ">89, 164/234, d=0.693, g=0.673\n",
            ">89, 165/234, d=0.689, g=0.676\n",
            ">89, 166/234, d=0.690, g=0.711\n",
            ">89, 167/234, d=0.698, g=0.724\n",
            ">89, 168/234, d=0.685, g=0.725\n",
            ">89, 169/234, d=0.691, g=0.721\n",
            ">89, 170/234, d=0.680, g=0.705\n",
            ">89, 171/234, d=0.694, g=0.688\n",
            ">89, 172/234, d=0.691, g=0.680\n",
            ">89, 173/234, d=0.692, g=0.694\n",
            ">89, 174/234, d=0.685, g=0.696\n",
            ">89, 175/234, d=0.686, g=0.703\n",
            ">89, 176/234, d=0.675, g=0.709\n",
            ">89, 177/234, d=0.688, g=0.696\n",
            ">89, 178/234, d=0.685, g=0.688\n",
            ">89, 179/234, d=0.699, g=0.690\n",
            ">89, 180/234, d=0.687, g=0.713\n",
            ">89, 181/234, d=0.690, g=0.705\n",
            ">89, 182/234, d=0.689, g=0.719\n",
            ">89, 183/234, d=0.681, g=0.709\n",
            ">89, 184/234, d=0.696, g=0.698\n",
            ">89, 185/234, d=0.686, g=0.707\n",
            ">89, 186/234, d=0.687, g=0.686\n",
            ">89, 187/234, d=0.690, g=0.688\n",
            ">89, 188/234, d=0.683, g=0.725\n",
            ">89, 189/234, d=0.694, g=0.695\n",
            ">89, 190/234, d=0.688, g=0.687\n",
            ">89, 191/234, d=0.689, g=0.692\n",
            ">89, 192/234, d=0.688, g=0.698\n",
            ">89, 193/234, d=0.691, g=0.710\n",
            ">89, 194/234, d=0.694, g=0.712\n",
            ">89, 195/234, d=0.688, g=0.711\n",
            ">89, 196/234, d=0.693, g=0.694\n",
            ">89, 197/234, d=0.690, g=0.710\n",
            ">89, 198/234, d=0.693, g=0.718\n",
            ">89, 199/234, d=0.681, g=0.720\n",
            ">89, 200/234, d=0.690, g=0.695\n",
            ">89, 201/234, d=0.692, g=0.685\n",
            ">89, 202/234, d=0.685, g=0.671\n",
            ">89, 203/234, d=0.686, g=0.698\n",
            ">89, 204/234, d=0.687, g=0.698\n",
            ">89, 205/234, d=0.689, g=0.705\n",
            ">89, 206/234, d=0.692, g=0.720\n",
            ">89, 207/234, d=0.693, g=0.699\n",
            ">89, 208/234, d=0.691, g=0.689\n",
            ">89, 209/234, d=0.696, g=0.694\n",
            ">89, 210/234, d=0.689, g=0.714\n",
            ">89, 211/234, d=0.689, g=0.722\n",
            ">89, 212/234, d=0.690, g=0.721\n",
            ">89, 213/234, d=0.692, g=0.697\n",
            ">89, 214/234, d=0.695, g=0.697\n",
            ">89, 215/234, d=0.687, g=0.698\n",
            ">89, 216/234, d=0.692, g=0.707\n",
            ">89, 217/234, d=0.697, g=0.708\n",
            ">89, 218/234, d=0.691, g=0.690\n",
            ">89, 219/234, d=0.690, g=0.668\n",
            ">89, 220/234, d=0.690, g=0.672\n",
            ">89, 221/234, d=0.688, g=0.689\n",
            ">89, 222/234, d=0.697, g=0.724\n",
            ">89, 223/234, d=0.695, g=0.732\n",
            ">89, 224/234, d=0.688, g=0.708\n",
            ">89, 225/234, d=0.690, g=0.691\n",
            ">89, 226/234, d=0.677, g=0.676\n",
            ">89, 227/234, d=0.696, g=0.700\n",
            ">89, 228/234, d=0.696, g=0.708\n",
            ">89, 229/234, d=0.687, g=0.720\n",
            ">89, 230/234, d=0.691, g=0.703\n",
            ">89, 231/234, d=0.683, g=0.699\n",
            ">89, 232/234, d=0.688, g=0.701\n",
            ">89, 233/234, d=0.688, g=0.708\n",
            ">89, 234/234, d=0.693, g=0.715\n",
            ">90, 1/234, d=0.686, g=0.705\n",
            ">90, 2/234, d=0.690, g=0.695\n",
            ">90, 3/234, d=0.687, g=0.703\n",
            ">90, 4/234, d=0.692, g=0.698\n",
            ">90, 5/234, d=0.688, g=0.709\n",
            ">90, 6/234, d=0.692, g=0.709\n",
            ">90, 7/234, d=0.684, g=0.702\n",
            ">90, 8/234, d=0.695, g=0.688\n",
            ">90, 9/234, d=0.689, g=0.698\n",
            ">90, 10/234, d=0.686, g=0.701\n",
            ">90, 11/234, d=0.691, g=0.709\n",
            ">90, 12/234, d=0.698, g=0.699\n",
            ">90, 13/234, d=0.695, g=0.706\n",
            ">90, 14/234, d=0.694, g=0.695\n",
            ">90, 15/234, d=0.690, g=0.694\n",
            ">90, 16/234, d=0.694, g=0.707\n",
            ">90, 17/234, d=0.696, g=0.704\n",
            ">90, 18/234, d=0.686, g=0.706\n",
            ">90, 19/234, d=0.687, g=0.708\n",
            ">90, 20/234, d=0.682, g=0.700\n",
            ">90, 21/234, d=0.683, g=0.691\n",
            ">90, 22/234, d=0.698, g=0.697\n",
            ">90, 23/234, d=0.698, g=0.712\n",
            ">90, 24/234, d=0.685, g=0.715\n",
            ">90, 25/234, d=0.690, g=0.703\n",
            ">90, 26/234, d=0.690, g=0.701\n",
            ">90, 27/234, d=0.690, g=0.694\n",
            ">90, 28/234, d=0.688, g=0.716\n",
            ">90, 29/234, d=0.694, g=0.705\n",
            ">90, 30/234, d=0.691, g=0.698\n",
            ">90, 31/234, d=0.693, g=0.690\n",
            ">90, 32/234, d=0.694, g=0.716\n",
            ">90, 33/234, d=0.695, g=0.702\n",
            ">90, 34/234, d=0.690, g=0.704\n",
            ">90, 35/234, d=0.685, g=0.688\n",
            ">90, 36/234, d=0.697, g=0.697\n",
            ">90, 37/234, d=0.693, g=0.722\n",
            ">90, 38/234, d=0.678, g=0.720\n",
            ">90, 39/234, d=0.695, g=0.699\n",
            ">90, 40/234, d=0.697, g=0.673\n",
            ">90, 41/234, d=0.693, g=0.686\n",
            ">90, 42/234, d=0.684, g=0.715\n",
            ">90, 43/234, d=0.694, g=0.713\n",
            ">90, 44/234, d=0.690, g=0.712\n",
            ">90, 45/234, d=0.696, g=0.700\n",
            ">90, 46/234, d=0.690, g=0.718\n",
            ">90, 47/234, d=0.686, g=0.721\n",
            ">90, 48/234, d=0.693, g=0.688\n",
            ">90, 49/234, d=0.691, g=0.664\n",
            ">90, 50/234, d=0.690, g=0.674\n",
            ">Accuracy real: 73%, fake: 28%\n",
            ">90, 51/234, d=0.696, g=0.690\n",
            ">90, 52/234, d=0.691, g=0.710\n",
            ">90, 53/234, d=0.686, g=0.712\n",
            ">90, 54/234, d=0.691, g=0.713\n",
            ">90, 55/234, d=0.691, g=0.710\n",
            ">90, 56/234, d=0.691, g=0.694\n",
            ">90, 57/234, d=0.691, g=0.687\n",
            ">90, 58/234, d=0.694, g=0.707\n",
            ">90, 59/234, d=0.691, g=0.715\n",
            ">90, 60/234, d=0.687, g=0.693\n",
            ">90, 61/234, d=0.694, g=0.683\n",
            ">90, 62/234, d=0.688, g=0.693\n",
            ">90, 63/234, d=0.681, g=0.701\n",
            ">90, 64/234, d=0.696, g=0.699\n",
            ">90, 65/234, d=0.696, g=0.726\n",
            ">90, 66/234, d=0.698, g=0.716\n",
            ">90, 67/234, d=0.691, g=0.705\n",
            ">90, 68/234, d=0.693, g=0.700\n",
            ">90, 69/234, d=0.685, g=0.696\n",
            ">90, 70/234, d=0.694, g=0.707\n",
            ">90, 71/234, d=0.696, g=0.702\n",
            ">90, 72/234, d=0.693, g=0.695\n",
            ">90, 73/234, d=0.694, g=0.687\n",
            ">90, 74/234, d=0.693, g=0.692\n",
            ">90, 75/234, d=0.698, g=0.711\n",
            ">90, 76/234, d=0.690, g=0.718\n",
            ">90, 77/234, d=0.684, g=0.701\n",
            ">90, 78/234, d=0.687, g=0.678\n",
            ">90, 79/234, d=0.683, g=0.692\n",
            ">90, 80/234, d=0.695, g=0.709\n",
            ">90, 81/234, d=0.699, g=0.725\n",
            ">90, 82/234, d=0.690, g=0.722\n",
            ">90, 83/234, d=0.690, g=0.698\n",
            ">90, 84/234, d=0.688, g=0.685\n",
            ">90, 85/234, d=0.697, g=0.704\n",
            ">90, 86/234, d=0.694, g=0.701\n",
            ">90, 87/234, d=0.693, g=0.709\n",
            ">90, 88/234, d=0.688, g=0.718\n",
            ">90, 89/234, d=0.686, g=0.700\n",
            ">90, 90/234, d=0.692, g=0.690\n",
            ">90, 91/234, d=0.690, g=0.677\n",
            ">90, 92/234, d=0.696, g=0.702\n",
            ">90, 93/234, d=0.688, g=0.707\n",
            ">90, 94/234, d=0.692, g=0.719\n",
            ">90, 95/234, d=0.687, g=0.706\n",
            ">90, 96/234, d=0.689, g=0.698\n",
            ">90, 97/234, d=0.694, g=0.695\n",
            ">90, 98/234, d=0.689, g=0.701\n",
            ">90, 99/234, d=0.698, g=0.711\n",
            ">90, 100/234, d=0.693, g=0.689\n",
            ">Accuracy real: 39%, fake: 78%\n",
            ">90, 101/234, d=0.695, g=0.697\n",
            ">90, 102/234, d=0.699, g=0.703\n",
            ">90, 103/234, d=0.688, g=0.709\n",
            ">90, 104/234, d=0.686, g=0.698\n",
            ">90, 105/234, d=0.691, g=0.698\n",
            ">90, 106/234, d=0.691, g=0.700\n",
            ">90, 107/234, d=0.692, g=0.704\n",
            ">90, 108/234, d=0.698, g=0.705\n",
            ">90, 109/234, d=0.691, g=0.711\n",
            ">90, 110/234, d=0.694, g=0.706\n",
            ">90, 111/234, d=0.690, g=0.697\n",
            ">90, 112/234, d=0.689, g=0.691\n",
            ">90, 113/234, d=0.691, g=0.689\n",
            ">90, 114/234, d=0.701, g=0.684\n",
            ">90, 115/234, d=0.688, g=0.696\n",
            ">90, 116/234, d=0.690, g=0.698\n",
            ">90, 117/234, d=0.688, g=0.713\n",
            ">90, 118/234, d=0.690, g=0.715\n",
            ">90, 119/234, d=0.686, g=0.707\n",
            ">90, 120/234, d=0.687, g=0.710\n",
            ">90, 121/234, d=0.690, g=0.709\n",
            ">90, 122/234, d=0.696, g=0.704\n",
            ">90, 123/234, d=0.690, g=0.697\n",
            ">90, 124/234, d=0.694, g=0.694\n",
            ">90, 125/234, d=0.698, g=0.702\n",
            ">90, 126/234, d=0.696, g=0.709\n",
            ">90, 127/234, d=0.700, g=0.709\n",
            ">90, 128/234, d=0.693, g=0.700\n",
            ">90, 129/234, d=0.686, g=0.701\n",
            ">90, 130/234, d=0.694, g=0.699\n",
            ">90, 131/234, d=0.694, g=0.700\n",
            ">90, 132/234, d=0.698, g=0.721\n",
            ">90, 133/234, d=0.686, g=0.708\n",
            ">90, 134/234, d=0.688, g=0.693\n",
            ">90, 135/234, d=0.689, g=0.689\n",
            ">90, 136/234, d=0.688, g=0.702\n",
            ">90, 137/234, d=0.687, g=0.707\n",
            ">90, 138/234, d=0.689, g=0.710\n",
            ">90, 139/234, d=0.691, g=0.701\n",
            ">90, 140/234, d=0.696, g=0.677\n",
            ">90, 141/234, d=0.692, g=0.681\n",
            ">90, 142/234, d=0.691, g=0.687\n",
            ">90, 143/234, d=0.689, g=0.703\n",
            ">90, 144/234, d=0.692, g=0.719\n",
            ">90, 145/234, d=0.686, g=0.708\n",
            ">90, 146/234, d=0.693, g=0.680\n",
            ">90, 147/234, d=0.694, g=0.679\n",
            ">90, 148/234, d=0.691, g=0.716\n",
            ">90, 149/234, d=0.691, g=0.734\n",
            ">90, 150/234, d=0.691, g=0.714\n",
            ">Accuracy real: 18%, fake: 97%\n",
            ">90, 151/234, d=0.680, g=0.685\n",
            ">90, 152/234, d=0.694, g=0.667\n",
            ">90, 153/234, d=0.699, g=0.684\n",
            ">90, 154/234, d=0.687, g=0.714\n",
            ">90, 155/234, d=0.687, g=0.732\n",
            ">90, 156/234, d=0.696, g=0.702\n",
            ">90, 157/234, d=0.694, g=0.692\n",
            ">90, 158/234, d=0.686, g=0.691\n",
            ">90, 159/234, d=0.697, g=0.696\n",
            ">90, 160/234, d=0.700, g=0.697\n",
            ">90, 161/234, d=0.697, g=0.701\n",
            ">90, 162/234, d=0.696, g=0.693\n",
            ">90, 163/234, d=0.697, g=0.706\n",
            ">90, 164/234, d=0.690, g=0.717\n",
            ">90, 165/234, d=0.695, g=0.714\n",
            ">90, 166/234, d=0.693, g=0.710\n",
            ">90, 167/234, d=0.699, g=0.694\n",
            ">90, 168/234, d=0.688, g=0.690\n",
            ">90, 169/234, d=0.693, g=0.699\n",
            ">90, 170/234, d=0.686, g=0.730\n",
            ">90, 171/234, d=0.691, g=0.719\n",
            ">90, 172/234, d=0.687, g=0.703\n",
            ">90, 173/234, d=0.691, g=0.682\n",
            ">90, 174/234, d=0.699, g=0.669\n",
            ">90, 175/234, d=0.694, g=0.700\n",
            ">90, 176/234, d=0.690, g=0.713\n",
            ">90, 177/234, d=0.691, g=0.709\n",
            ">90, 178/234, d=0.688, g=0.710\n",
            ">90, 179/234, d=0.696, g=0.711\n",
            ">90, 180/234, d=0.689, g=0.708\n",
            ">90, 181/234, d=0.688, g=0.693\n",
            ">90, 182/234, d=0.688, g=0.681\n",
            ">90, 183/234, d=0.689, g=0.704\n",
            ">90, 184/234, d=0.687, g=0.718\n",
            ">90, 185/234, d=0.686, g=0.713\n",
            ">90, 186/234, d=0.692, g=0.697\n",
            ">90, 187/234, d=0.689, g=0.683\n",
            ">90, 188/234, d=0.687, g=0.688\n",
            ">90, 189/234, d=0.689, g=0.690\n",
            ">90, 190/234, d=0.693, g=0.702\n",
            ">90, 191/234, d=0.684, g=0.710\n",
            ">90, 192/234, d=0.691, g=0.695\n",
            ">90, 193/234, d=0.689, g=0.683\n",
            ">90, 194/234, d=0.698, g=0.693\n",
            ">90, 195/234, d=0.690, g=0.696\n",
            ">90, 196/234, d=0.703, g=0.710\n",
            ">90, 197/234, d=0.689, g=0.717\n",
            ">90, 198/234, d=0.699, g=0.719\n",
            ">90, 199/234, d=0.689, g=0.697\n",
            ">90, 200/234, d=0.687, g=0.687\n",
            ">Accuracy real: 65%, fake: 60%\n",
            ">90, 201/234, d=0.692, g=0.684\n",
            ">90, 202/234, d=0.689, g=0.694\n",
            ">90, 203/234, d=0.686, g=0.708\n",
            ">90, 204/234, d=0.689, g=0.706\n",
            ">90, 205/234, d=0.693, g=0.698\n",
            ">90, 206/234, d=0.687, g=0.676\n",
            ">90, 207/234, d=0.687, g=0.682\n",
            ">90, 208/234, d=0.683, g=0.681\n",
            ">90, 209/234, d=0.696, g=0.708\n",
            ">90, 210/234, d=0.688, g=0.707\n",
            ">90, 211/234, d=0.687, g=0.695\n",
            ">90, 212/234, d=0.692, g=0.715\n",
            ">90, 213/234, d=0.691, g=0.723\n",
            ">90, 214/234, d=0.691, g=0.710\n",
            ">90, 215/234, d=0.690, g=0.699\n",
            ">90, 216/234, d=0.693, g=0.693\n",
            ">90, 217/234, d=0.690, g=0.691\n",
            ">90, 218/234, d=0.695, g=0.691\n",
            ">90, 219/234, d=0.695, g=0.698\n",
            ">90, 220/234, d=0.687, g=0.684\n",
            ">90, 221/234, d=0.691, g=0.705\n",
            ">90, 222/234, d=0.689, g=0.712\n",
            ">90, 223/234, d=0.690, g=0.707\n",
            ">90, 224/234, d=0.691, g=0.710\n",
            ">90, 225/234, d=0.689, g=0.706\n",
            ">90, 226/234, d=0.687, g=0.699\n",
            ">90, 227/234, d=0.688, g=0.718\n",
            ">90, 228/234, d=0.686, g=0.696\n",
            ">90, 229/234, d=0.694, g=0.700\n",
            ">90, 230/234, d=0.694, g=0.712\n",
            ">90, 231/234, d=0.687, g=0.691\n",
            ">90, 232/234, d=0.694, g=0.689\n",
            ">90, 233/234, d=0.690, g=0.699\n",
            ">90, 234/234, d=0.696, g=0.697\n",
            ">91, 1/234, d=0.688, g=0.698\n",
            ">91, 2/234, d=0.692, g=0.708\n",
            ">91, 3/234, d=0.690, g=0.698\n",
            ">91, 4/234, d=0.689, g=0.678\n",
            ">91, 5/234, d=0.692, g=0.684\n",
            ">91, 6/234, d=0.689, g=0.699\n",
            ">91, 7/234, d=0.686, g=0.716\n",
            ">91, 8/234, d=0.692, g=0.715\n",
            ">91, 9/234, d=0.696, g=0.698\n",
            ">91, 10/234, d=0.692, g=0.679\n",
            ">91, 11/234, d=0.684, g=0.671\n",
            ">91, 12/234, d=0.691, g=0.682\n",
            ">91, 13/234, d=0.688, g=0.713\n",
            ">91, 14/234, d=0.687, g=0.743\n",
            ">91, 15/234, d=0.694, g=0.723\n",
            ">91, 16/234, d=0.692, g=0.695\n",
            ">91, 17/234, d=0.687, g=0.689\n",
            ">91, 18/234, d=0.693, g=0.719\n",
            ">91, 19/234, d=0.693, g=0.715\n",
            ">91, 20/234, d=0.686, g=0.707\n",
            ">91, 21/234, d=0.686, g=0.688\n",
            ">91, 22/234, d=0.695, g=0.674\n",
            ">91, 23/234, d=0.689, g=0.698\n",
            ">91, 24/234, d=0.690, g=0.694\n",
            ">91, 25/234, d=0.692, g=0.700\n",
            ">91, 26/234, d=0.696, g=0.718\n",
            ">91, 27/234, d=0.687, g=0.729\n",
            ">91, 28/234, d=0.692, g=0.731\n",
            ">91, 29/234, d=0.689, g=0.711\n",
            ">91, 30/234, d=0.695, g=0.703\n",
            ">91, 31/234, d=0.694, g=0.696\n",
            ">91, 32/234, d=0.693, g=0.702\n",
            ">91, 33/234, d=0.681, g=0.702\n",
            ">91, 34/234, d=0.687, g=0.694\n",
            ">91, 35/234, d=0.695, g=0.698\n",
            ">91, 36/234, d=0.693, g=0.704\n",
            ">91, 37/234, d=0.686, g=0.693\n",
            ">91, 38/234, d=0.700, g=0.710\n",
            ">91, 39/234, d=0.694, g=0.712\n",
            ">91, 40/234, d=0.685, g=0.712\n",
            ">91, 41/234, d=0.697, g=0.708\n",
            ">91, 42/234, d=0.685, g=0.707\n",
            ">91, 43/234, d=0.693, g=0.701\n",
            ">91, 44/234, d=0.696, g=0.698\n",
            ">91, 45/234, d=0.696, g=0.691\n",
            ">91, 46/234, d=0.684, g=0.685\n",
            ">91, 47/234, d=0.690, g=0.697\n",
            ">91, 48/234, d=0.690, g=0.716\n",
            ">91, 49/234, d=0.693, g=0.729\n",
            ">91, 50/234, d=0.693, g=0.720\n",
            ">91, 51/234, d=0.694, g=0.699\n",
            ">91, 52/234, d=0.690, g=0.702\n",
            ">91, 53/234, d=0.689, g=0.711\n",
            ">91, 54/234, d=0.695, g=0.701\n",
            ">91, 55/234, d=0.685, g=0.690\n",
            ">91, 56/234, d=0.693, g=0.697\n",
            ">91, 57/234, d=0.694, g=0.707\n",
            ">91, 58/234, d=0.689, g=0.722\n",
            ">91, 59/234, d=0.691, g=0.714\n",
            ">91, 60/234, d=0.690, g=0.701\n",
            ">91, 61/234, d=0.690, g=0.681\n",
            ">91, 62/234, d=0.693, g=0.673\n",
            ">91, 63/234, d=0.691, g=0.709\n",
            ">91, 64/234, d=0.686, g=0.726\n",
            ">91, 65/234, d=0.689, g=0.735\n",
            ">91, 66/234, d=0.687, g=0.690\n",
            ">91, 67/234, d=0.685, g=0.677\n",
            ">91, 68/234, d=0.694, g=0.685\n",
            ">91, 69/234, d=0.687, g=0.695\n",
            ">91, 70/234, d=0.685, g=0.706\n",
            ">91, 71/234, d=0.686, g=0.706\n",
            ">91, 72/234, d=0.688, g=0.710\n",
            ">91, 73/234, d=0.692, g=0.696\n",
            ">91, 74/234, d=0.692, g=0.681\n",
            ">91, 75/234, d=0.689, g=0.688\n",
            ">91, 76/234, d=0.689, g=0.708\n",
            ">91, 77/234, d=0.691, g=0.710\n",
            ">91, 78/234, d=0.697, g=0.715\n",
            ">91, 79/234, d=0.703, g=0.728\n",
            ">91, 80/234, d=0.690, g=0.707\n",
            ">91, 81/234, d=0.687, g=0.692\n",
            ">91, 82/234, d=0.695, g=0.668\n",
            ">91, 83/234, d=0.696, g=0.688\n",
            ">91, 84/234, d=0.693, g=0.714\n",
            ">91, 85/234, d=0.692, g=0.729\n",
            ">91, 86/234, d=0.690, g=0.716\n",
            ">91, 87/234, d=0.696, g=0.682\n",
            ">91, 88/234, d=0.697, g=0.693\n",
            ">91, 89/234, d=0.691, g=0.698\n",
            ">91, 90/234, d=0.687, g=0.702\n",
            ">91, 91/234, d=0.696, g=0.706\n",
            ">91, 92/234, d=0.682, g=0.701\n",
            ">91, 93/234, d=0.690, g=0.695\n",
            ">91, 94/234, d=0.694, g=0.705\n",
            ">91, 95/234, d=0.693, g=0.711\n",
            ">91, 96/234, d=0.699, g=0.687\n",
            ">91, 97/234, d=0.690, g=0.683\n",
            ">91, 98/234, d=0.686, g=0.692\n",
            ">91, 99/234, d=0.688, g=0.706\n",
            ">91, 100/234, d=0.687, g=0.711\n",
            ">91, 101/234, d=0.682, g=0.695\n",
            ">91, 102/234, d=0.697, g=0.693\n",
            ">91, 103/234, d=0.695, g=0.697\n",
            ">91, 104/234, d=0.695, g=0.711\n",
            ">91, 105/234, d=0.690, g=0.711\n",
            ">91, 106/234, d=0.690, g=0.715\n",
            ">91, 107/234, d=0.690, g=0.702\n",
            ">91, 108/234, d=0.699, g=0.703\n",
            ">91, 109/234, d=0.690, g=0.694\n",
            ">91, 110/234, d=0.691, g=0.695\n",
            ">91, 111/234, d=0.694, g=0.693\n",
            ">91, 112/234, d=0.693, g=0.702\n",
            ">91, 113/234, d=0.683, g=0.700\n",
            ">91, 114/234, d=0.692, g=0.704\n",
            ">91, 115/234, d=0.689, g=0.719\n",
            ">91, 116/234, d=0.694, g=0.718\n",
            ">91, 117/234, d=0.692, g=0.695\n",
            ">91, 118/234, d=0.688, g=0.687\n",
            ">91, 119/234, d=0.697, g=0.683\n",
            ">91, 120/234, d=0.686, g=0.682\n",
            ">91, 121/234, d=0.695, g=0.686\n",
            ">91, 122/234, d=0.695, g=0.709\n",
            ">91, 123/234, d=0.682, g=0.711\n",
            ">91, 124/234, d=0.692, g=0.706\n",
            ">91, 125/234, d=0.683, g=0.695\n",
            ">91, 126/234, d=0.698, g=0.696\n",
            ">91, 127/234, d=0.688, g=0.707\n",
            ">91, 128/234, d=0.696, g=0.704\n",
            ">91, 129/234, d=0.689, g=0.706\n",
            ">91, 130/234, d=0.689, g=0.702\n",
            ">91, 131/234, d=0.693, g=0.709\n",
            ">91, 132/234, d=0.690, g=0.696\n",
            ">91, 133/234, d=0.693, g=0.700\n",
            ">91, 134/234, d=0.699, g=0.718\n",
            ">91, 135/234, d=0.697, g=0.707\n",
            ">91, 136/234, d=0.697, g=0.700\n",
            ">91, 137/234, d=0.686, g=0.684\n",
            ">91, 138/234, d=0.692, g=0.687\n",
            ">91, 139/234, d=0.690, g=0.693\n",
            ">91, 140/234, d=0.684, g=0.701\n",
            ">91, 141/234, d=0.688, g=0.717\n",
            ">91, 142/234, d=0.694, g=0.720\n",
            ">91, 143/234, d=0.694, g=0.710\n",
            ">91, 144/234, d=0.691, g=0.688\n",
            ">91, 145/234, d=0.688, g=0.695\n",
            ">91, 146/234, d=0.698, g=0.691\n",
            ">91, 147/234, d=0.681, g=0.697\n",
            ">91, 148/234, d=0.684, g=0.692\n",
            ">91, 149/234, d=0.692, g=0.700\n",
            ">91, 150/234, d=0.697, g=0.702\n",
            ">91, 151/234, d=0.697, g=0.714\n",
            ">91, 152/234, d=0.698, g=0.703\n",
            ">91, 153/234, d=0.690, g=0.704\n",
            ">91, 154/234, d=0.692, g=0.716\n",
            ">91, 155/234, d=0.690, g=0.715\n",
            ">91, 156/234, d=0.696, g=0.698\n",
            ">91, 157/234, d=0.696, g=0.689\n",
            ">91, 158/234, d=0.691, g=0.701\n",
            ">91, 159/234, d=0.691, g=0.702\n",
            ">91, 160/234, d=0.692, g=0.697\n",
            ">91, 161/234, d=0.697, g=0.693\n",
            ">91, 162/234, d=0.693, g=0.710\n",
            ">91, 163/234, d=0.687, g=0.711\n",
            ">91, 164/234, d=0.698, g=0.706\n",
            ">91, 165/234, d=0.688, g=0.712\n",
            ">91, 166/234, d=0.686, g=0.715\n",
            ">91, 167/234, d=0.693, g=0.714\n",
            ">91, 168/234, d=0.696, g=0.699\n",
            ">91, 169/234, d=0.696, g=0.688\n",
            ">91, 170/234, d=0.686, g=0.692\n",
            ">91, 171/234, d=0.691, g=0.684\n",
            ">91, 172/234, d=0.694, g=0.693\n",
            ">91, 173/234, d=0.689, g=0.709\n",
            ">91, 174/234, d=0.689, g=0.717\n",
            ">91, 175/234, d=0.693, g=0.716\n",
            ">91, 176/234, d=0.691, g=0.698\n",
            ">91, 177/234, d=0.694, g=0.698\n",
            ">91, 178/234, d=0.686, g=0.720\n",
            ">91, 179/234, d=0.691, g=0.726\n",
            ">91, 180/234, d=0.694, g=0.718\n",
            ">91, 181/234, d=0.689, g=0.703\n",
            ">91, 182/234, d=0.692, g=0.710\n",
            ">91, 183/234, d=0.681, g=0.702\n",
            ">91, 184/234, d=0.697, g=0.685\n",
            ">91, 185/234, d=0.691, g=0.678\n",
            ">91, 186/234, d=0.692, g=0.696\n",
            ">91, 187/234, d=0.696, g=0.705\n",
            ">91, 188/234, d=0.691, g=0.697\n",
            ">91, 189/234, d=0.690, g=0.704\n",
            ">91, 190/234, d=0.688, g=0.714\n",
            ">91, 191/234, d=0.699, g=0.712\n",
            ">91, 192/234, d=0.687, g=0.710\n",
            ">91, 193/234, d=0.699, g=0.695\n",
            ">91, 194/234, d=0.690, g=0.691\n",
            ">91, 195/234, d=0.693, g=0.700\n",
            ">91, 196/234, d=0.688, g=0.692\n",
            ">91, 197/234, d=0.695, g=0.689\n",
            ">91, 198/234, d=0.690, g=0.699\n",
            ">91, 199/234, d=0.694, g=0.712\n",
            ">91, 200/234, d=0.695, g=0.713\n",
            ">91, 201/234, d=0.684, g=0.708\n",
            ">91, 202/234, d=0.695, g=0.697\n",
            ">91, 203/234, d=0.689, g=0.702\n",
            ">91, 204/234, d=0.684, g=0.692\n",
            ">91, 205/234, d=0.694, g=0.698\n",
            ">91, 206/234, d=0.694, g=0.696\n",
            ">91, 207/234, d=0.693, g=0.710\n",
            ">91, 208/234, d=0.694, g=0.710\n",
            ">91, 209/234, d=0.687, g=0.715\n",
            ">91, 210/234, d=0.682, g=0.704\n",
            ">91, 211/234, d=0.688, g=0.699\n",
            ">91, 212/234, d=0.686, g=0.716\n",
            ">91, 213/234, d=0.697, g=0.723\n",
            ">91, 214/234, d=0.707, g=0.701\n",
            ">91, 215/234, d=0.696, g=0.690\n",
            ">91, 216/234, d=0.691, g=0.689\n",
            ">91, 217/234, d=0.692, g=0.689\n",
            ">91, 218/234, d=0.697, g=0.702\n",
            ">91, 219/234, d=0.699, g=0.705\n",
            ">91, 220/234, d=0.690, g=0.707\n",
            ">91, 221/234, d=0.685, g=0.711\n",
            ">91, 222/234, d=0.681, g=0.701\n",
            ">91, 223/234, d=0.691, g=0.682\n",
            ">91, 224/234, d=0.694, g=0.693\n",
            ">91, 225/234, d=0.692, g=0.689\n",
            ">91, 226/234, d=0.685, g=0.702\n",
            ">91, 227/234, d=0.692, g=0.706\n",
            ">91, 228/234, d=0.694, g=0.710\n",
            ">91, 229/234, d=0.694, g=0.696\n",
            ">91, 230/234, d=0.695, g=0.682\n",
            ">91, 231/234, d=0.692, g=0.691\n",
            ">91, 232/234, d=0.683, g=0.716\n",
            ">91, 233/234, d=0.697, g=0.715\n",
            ">91, 234/234, d=0.690, g=0.706\n",
            ">92, 1/234, d=0.694, g=0.683\n",
            ">92, 2/234, d=0.689, g=0.668\n",
            ">92, 3/234, d=0.695, g=0.711\n",
            ">92, 4/234, d=0.696, g=0.729\n",
            ">92, 5/234, d=0.685, g=0.717\n",
            ">92, 6/234, d=0.689, g=0.694\n",
            ">92, 7/234, d=0.691, g=0.696\n",
            ">92, 8/234, d=0.688, g=0.726\n",
            ">92, 9/234, d=0.695, g=0.708\n",
            ">92, 10/234, d=0.688, g=0.692\n",
            ">92, 11/234, d=0.700, g=0.692\n",
            ">92, 12/234, d=0.696, g=0.699\n",
            ">92, 13/234, d=0.695, g=0.716\n",
            ">92, 14/234, d=0.695, g=0.717\n",
            ">92, 15/234, d=0.693, g=0.721\n",
            ">92, 16/234, d=0.694, g=0.699\n",
            ">92, 17/234, d=0.695, g=0.689\n",
            ">92, 18/234, d=0.691, g=0.692\n",
            ">92, 19/234, d=0.683, g=0.689\n",
            ">92, 20/234, d=0.692, g=0.701\n",
            ">92, 21/234, d=0.693, g=0.706\n",
            ">92, 22/234, d=0.695, g=0.709\n",
            ">92, 23/234, d=0.693, g=0.701\n",
            ">92, 24/234, d=0.689, g=0.709\n",
            ">92, 25/234, d=0.689, g=0.696\n",
            ">92, 26/234, d=0.690, g=0.709\n",
            ">92, 27/234, d=0.694, g=0.705\n",
            ">92, 28/234, d=0.684, g=0.703\n",
            ">92, 29/234, d=0.688, g=0.704\n",
            ">92, 30/234, d=0.697, g=0.699\n",
            ">92, 31/234, d=0.691, g=0.725\n",
            ">92, 32/234, d=0.696, g=0.704\n",
            ">92, 33/234, d=0.700, g=0.688\n",
            ">92, 34/234, d=0.691, g=0.685\n",
            ">92, 35/234, d=0.687, g=0.681\n",
            ">92, 36/234, d=0.695, g=0.709\n",
            ">92, 37/234, d=0.696, g=0.703\n",
            ">92, 38/234, d=0.694, g=0.701\n",
            ">92, 39/234, d=0.689, g=0.708\n",
            ">92, 40/234, d=0.691, g=0.701\n",
            ">92, 41/234, d=0.690, g=0.681\n",
            ">92, 42/234, d=0.694, g=0.678\n",
            ">92, 43/234, d=0.693, g=0.696\n",
            ">92, 44/234, d=0.693, g=0.720\n",
            ">92, 45/234, d=0.686, g=0.733\n",
            ">92, 46/234, d=0.694, g=0.701\n",
            ">92, 47/234, d=0.689, g=0.677\n",
            ">92, 48/234, d=0.696, g=0.683\n",
            ">92, 49/234, d=0.690, g=0.698\n",
            ">92, 50/234, d=0.695, g=0.710\n",
            ">92, 51/234, d=0.693, g=0.701\n",
            ">92, 52/234, d=0.691, g=0.691\n",
            ">92, 53/234, d=0.697, g=0.702\n",
            ">92, 54/234, d=0.695, g=0.717\n",
            ">92, 55/234, d=0.695, g=0.735\n",
            ">92, 56/234, d=0.689, g=0.728\n",
            ">92, 57/234, d=0.688, g=0.691\n",
            ">92, 58/234, d=0.688, g=0.660\n",
            ">92, 59/234, d=0.696, g=0.678\n",
            ">92, 60/234, d=0.693, g=0.710\n",
            ">92, 61/234, d=0.688, g=0.709\n",
            ">92, 62/234, d=0.690, g=0.713\n",
            ">92, 63/234, d=0.687, g=0.703\n",
            ">92, 64/234, d=0.707, g=0.710\n",
            ">92, 65/234, d=0.684, g=0.712\n",
            ">92, 66/234, d=0.692, g=0.691\n",
            ">92, 67/234, d=0.689, g=0.688\n",
            ">92, 68/234, d=0.695, g=0.685\n",
            ">92, 69/234, d=0.693, g=0.697\n",
            ">92, 70/234, d=0.692, g=0.700\n",
            ">92, 71/234, d=0.683, g=0.700\n",
            ">92, 72/234, d=0.695, g=0.711\n",
            ">92, 73/234, d=0.690, g=0.708\n",
            ">92, 74/234, d=0.691, g=0.729\n",
            ">92, 75/234, d=0.692, g=0.714\n",
            ">92, 76/234, d=0.688, g=0.690\n",
            ">92, 77/234, d=0.691, g=0.678\n",
            ">92, 78/234, d=0.690, g=0.701\n",
            ">92, 79/234, d=0.694, g=0.715\n",
            ">92, 80/234, d=0.689, g=0.692\n",
            ">92, 81/234, d=0.689, g=0.698\n",
            ">92, 82/234, d=0.685, g=0.697\n",
            ">92, 83/234, d=0.692, g=0.713\n",
            ">92, 84/234, d=0.688, g=0.713\n",
            ">92, 85/234, d=0.694, g=0.701\n",
            ">92, 86/234, d=0.685, g=0.710\n",
            ">92, 87/234, d=0.691, g=0.710\n",
            ">92, 88/234, d=0.685, g=0.701\n",
            ">92, 89/234, d=0.693, g=0.684\n",
            ">92, 90/234, d=0.688, g=0.692\n",
            ">92, 91/234, d=0.689, g=0.682\n",
            ">92, 92/234, d=0.689, g=0.698\n",
            ">92, 93/234, d=0.696, g=0.696\n",
            ">92, 94/234, d=0.696, g=0.688\n",
            ">92, 95/234, d=0.702, g=0.721\n",
            ">92, 96/234, d=0.690, g=0.735\n",
            ">92, 97/234, d=0.697, g=0.710\n",
            ">92, 98/234, d=0.687, g=0.690\n",
            ">92, 99/234, d=0.692, g=0.674\n",
            ">92, 100/234, d=0.691, g=0.687\n",
            ">92, 101/234, d=0.685, g=0.705\n",
            ">92, 102/234, d=0.692, g=0.711\n",
            ">92, 103/234, d=0.693, g=0.717\n",
            ">92, 104/234, d=0.693, g=0.706\n",
            ">92, 105/234, d=0.693, g=0.708\n",
            ">92, 106/234, d=0.691, g=0.703\n",
            ">92, 107/234, d=0.690, g=0.697\n",
            ">92, 108/234, d=0.684, g=0.682\n",
            ">92, 109/234, d=0.692, g=0.697\n",
            ">92, 110/234, d=0.682, g=0.706\n",
            ">92, 111/234, d=0.685, g=0.701\n",
            ">92, 112/234, d=0.698, g=0.682\n",
            ">92, 113/234, d=0.690, g=0.683\n",
            ">92, 114/234, d=0.686, g=0.707\n",
            ">92, 115/234, d=0.697, g=0.723\n",
            ">92, 116/234, d=0.691, g=0.711\n",
            ">92, 117/234, d=0.682, g=0.701\n",
            ">92, 118/234, d=0.695, g=0.688\n",
            ">92, 119/234, d=0.688, g=0.681\n",
            ">92, 120/234, d=0.693, g=0.694\n",
            ">92, 121/234, d=0.684, g=0.703\n",
            ">92, 122/234, d=0.695, g=0.713\n",
            ">92, 123/234, d=0.693, g=0.696\n",
            ">92, 124/234, d=0.690, g=0.692\n",
            ">92, 125/234, d=0.690, g=0.695\n",
            ">92, 126/234, d=0.694, g=0.730\n",
            ">92, 127/234, d=0.691, g=0.720\n",
            ">92, 128/234, d=0.691, g=0.713\n",
            ">92, 129/234, d=0.692, g=0.686\n",
            ">92, 130/234, d=0.693, g=0.680\n",
            ">92, 131/234, d=0.695, g=0.705\n",
            ">92, 132/234, d=0.688, g=0.724\n",
            ">92, 133/234, d=0.690, g=0.702\n",
            ">92, 134/234, d=0.687, g=0.681\n",
            ">92, 135/234, d=0.690, g=0.678\n",
            ">92, 136/234, d=0.696, g=0.688\n",
            ">92, 137/234, d=0.697, g=0.699\n",
            ">92, 138/234, d=0.695, g=0.702\n",
            ">92, 139/234, d=0.690, g=0.696\n",
            ">92, 140/234, d=0.691, g=0.712\n",
            ">92, 141/234, d=0.687, g=0.705\n",
            ">92, 142/234, d=0.688, g=0.703\n",
            ">92, 143/234, d=0.691, g=0.705\n",
            ">92, 144/234, d=0.685, g=0.696\n",
            ">92, 145/234, d=0.691, g=0.688\n",
            ">92, 146/234, d=0.689, g=0.701\n",
            ">92, 147/234, d=0.696, g=0.719\n",
            ">92, 148/234, d=0.696, g=0.682\n",
            ">92, 149/234, d=0.687, g=0.690\n",
            ">92, 150/234, d=0.693, g=0.710\n",
            ">92, 151/234, d=0.693, g=0.715\n",
            ">92, 152/234, d=0.693, g=0.687\n",
            ">92, 153/234, d=0.690, g=0.692\n",
            ">92, 154/234, d=0.694, g=0.727\n",
            ">92, 155/234, d=0.691, g=0.700\n",
            ">92, 156/234, d=0.694, g=0.679\n",
            ">92, 157/234, d=0.686, g=0.666\n",
            ">92, 158/234, d=0.696, g=0.688\n",
            ">92, 159/234, d=0.688, g=0.716\n",
            ">92, 160/234, d=0.685, g=0.719\n",
            ">92, 161/234, d=0.690, g=0.706\n",
            ">92, 162/234, d=0.692, g=0.698\n",
            ">92, 163/234, d=0.694, g=0.700\n",
            ">92, 164/234, d=0.688, g=0.700\n",
            ">92, 165/234, d=0.692, g=0.726\n",
            ">92, 166/234, d=0.691, g=0.695\n",
            ">92, 167/234, d=0.691, g=0.679\n",
            ">92, 168/234, d=0.689, g=0.694\n",
            ">92, 169/234, d=0.700, g=0.702\n",
            ">92, 170/234, d=0.686, g=0.700\n",
            ">92, 171/234, d=0.690, g=0.695\n",
            ">92, 172/234, d=0.691, g=0.691\n",
            ">92, 173/234, d=0.695, g=0.688\n",
            ">92, 174/234, d=0.697, g=0.711\n",
            ">92, 175/234, d=0.693, g=0.708\n",
            ">92, 176/234, d=0.694, g=0.711\n",
            ">92, 177/234, d=0.696, g=0.701\n",
            ">92, 178/234, d=0.696, g=0.704\n",
            ">92, 179/234, d=0.694, g=0.697\n",
            ">92, 180/234, d=0.698, g=0.673\n",
            ">92, 181/234, d=0.697, g=0.683\n",
            ">92, 182/234, d=0.684, g=0.707\n",
            ">92, 183/234, d=0.696, g=0.700\n",
            ">92, 184/234, d=0.680, g=0.698\n",
            ">92, 185/234, d=0.688, g=0.687\n",
            ">92, 186/234, d=0.696, g=0.699\n",
            ">92, 187/234, d=0.697, g=0.712\n",
            ">92, 188/234, d=0.692, g=0.718\n",
            ">92, 189/234, d=0.686, g=0.718\n",
            ">92, 190/234, d=0.693, g=0.693\n",
            ">92, 191/234, d=0.690, g=0.675\n",
            ">92, 192/234, d=0.687, g=0.676\n",
            ">92, 193/234, d=0.691, g=0.695\n",
            ">92, 194/234, d=0.681, g=0.714\n",
            ">92, 195/234, d=0.693, g=0.704\n",
            ">92, 196/234, d=0.693, g=0.691\n",
            ">92, 197/234, d=0.695, g=0.701\n",
            ">92, 198/234, d=0.687, g=0.704\n",
            ">92, 199/234, d=0.696, g=0.702\n",
            ">92, 200/234, d=0.691, g=0.679\n",
            ">92, 201/234, d=0.687, g=0.679\n",
            ">92, 202/234, d=0.699, g=0.697\n",
            ">92, 203/234, d=0.689, g=0.715\n",
            ">92, 204/234, d=0.683, g=0.718\n",
            ">92, 205/234, d=0.691, g=0.688\n",
            ">92, 206/234, d=0.689, g=0.692\n",
            ">92, 207/234, d=0.690, g=0.702\n",
            ">92, 208/234, d=0.689, g=0.714\n",
            ">92, 209/234, d=0.691, g=0.712\n",
            ">92, 210/234, d=0.691, g=0.691\n",
            ">92, 211/234, d=0.689, g=0.687\n",
            ">92, 212/234, d=0.693, g=0.688\n",
            ">92, 213/234, d=0.693, g=0.696\n",
            ">92, 214/234, d=0.697, g=0.707\n",
            ">92, 215/234, d=0.694, g=0.699\n",
            ">92, 216/234, d=0.694, g=0.698\n",
            ">92, 217/234, d=0.692, g=0.710\n",
            ">92, 218/234, d=0.693, g=0.730\n",
            ">92, 219/234, d=0.698, g=0.716\n",
            ">92, 220/234, d=0.693, g=0.718\n",
            ">92, 221/234, d=0.690, g=0.695\n",
            ">92, 222/234, d=0.692, g=0.685\n",
            ">92, 223/234, d=0.688, g=0.692\n",
            ">92, 224/234, d=0.699, g=0.708\n",
            ">92, 225/234, d=0.689, g=0.714\n",
            ">92, 226/234, d=0.684, g=0.701\n",
            ">92, 227/234, d=0.694, g=0.695\n",
            ">92, 228/234, d=0.692, g=0.715\n",
            ">92, 229/234, d=0.690, g=0.708\n",
            ">92, 230/234, d=0.680, g=0.688\n",
            ">92, 231/234, d=0.697, g=0.689\n",
            ">92, 232/234, d=0.688, g=0.693\n",
            ">92, 233/234, d=0.691, g=0.702\n",
            ">92, 234/234, d=0.692, g=0.703\n",
            ">93, 1/234, d=0.686, g=0.719\n",
            ">93, 2/234, d=0.688, g=0.727\n",
            ">93, 3/234, d=0.691, g=0.724\n",
            ">93, 4/234, d=0.688, g=0.713\n",
            ">93, 5/234, d=0.689, g=0.695\n",
            ">93, 6/234, d=0.698, g=0.670\n",
            ">93, 7/234, d=0.695, g=0.678\n",
            ">93, 8/234, d=0.697, g=0.679\n",
            ">93, 9/234, d=0.696, g=0.713\n",
            ">93, 10/234, d=0.689, g=0.712\n",
            ">93, 11/234, d=0.693, g=0.723\n",
            ">93, 12/234, d=0.694, g=0.700\n",
            ">93, 13/234, d=0.687, g=0.689\n",
            ">93, 14/234, d=0.692, g=0.713\n",
            ">93, 15/234, d=0.692, g=0.722\n",
            ">93, 16/234, d=0.693, g=0.697\n",
            ">93, 17/234, d=0.682, g=0.668\n",
            ">93, 18/234, d=0.693, g=0.679\n",
            ">93, 19/234, d=0.691, g=0.695\n",
            ">93, 20/234, d=0.698, g=0.718\n",
            ">93, 21/234, d=0.696, g=0.709\n",
            ">93, 22/234, d=0.691, g=0.702\n",
            ">93, 23/234, d=0.691, g=0.715\n",
            ">93, 24/234, d=0.689, g=0.703\n",
            ">93, 25/234, d=0.693, g=0.701\n",
            ">93, 26/234, d=0.691, g=0.688\n",
            ">93, 27/234, d=0.693, g=0.698\n",
            ">93, 28/234, d=0.693, g=0.705\n",
            ">93, 29/234, d=0.687, g=0.712\n",
            ">93, 30/234, d=0.699, g=0.702\n",
            ">93, 31/234, d=0.689, g=0.689\n",
            ">93, 32/234, d=0.689, g=0.704\n",
            ">93, 33/234, d=0.691, g=0.722\n",
            ">93, 34/234, d=0.695, g=0.719\n",
            ">93, 35/234, d=0.691, g=0.694\n",
            ">93, 36/234, d=0.690, g=0.686\n",
            ">93, 37/234, d=0.693, g=0.683\n",
            ">93, 38/234, d=0.688, g=0.706\n",
            ">93, 39/234, d=0.696, g=0.703\n",
            ">93, 40/234, d=0.685, g=0.705\n",
            ">93, 41/234, d=0.700, g=0.694\n",
            ">93, 42/234, d=0.686, g=0.701\n",
            ">93, 43/234, d=0.698, g=0.705\n",
            ">93, 44/234, d=0.697, g=0.707\n",
            ">93, 45/234, d=0.685, g=0.682\n",
            ">93, 46/234, d=0.692, g=0.690\n",
            ">93, 47/234, d=0.683, g=0.706\n",
            ">93, 48/234, d=0.691, g=0.714\n",
            ">93, 49/234, d=0.685, g=0.716\n",
            ">93, 50/234, d=0.690, g=0.701\n",
            ">93, 51/234, d=0.699, g=0.678\n",
            ">93, 52/234, d=0.685, g=0.668\n",
            ">93, 53/234, d=0.686, g=0.680\n",
            ">93, 54/234, d=0.696, g=0.725\n",
            ">93, 55/234, d=0.687, g=0.741\n",
            ">93, 56/234, d=0.693, g=0.712\n",
            ">93, 57/234, d=0.691, g=0.691\n",
            ">93, 58/234, d=0.685, g=0.680\n",
            ">93, 59/234, d=0.696, g=0.704\n",
            ">93, 60/234, d=0.693, g=0.701\n",
            ">93, 61/234, d=0.696, g=0.697\n",
            ">93, 62/234, d=0.690, g=0.695\n",
            ">93, 63/234, d=0.687, g=0.694\n",
            ">93, 64/234, d=0.687, g=0.714\n",
            ">93, 65/234, d=0.699, g=0.723\n",
            ">93, 66/234, d=0.681, g=0.714\n",
            ">93, 67/234, d=0.696, g=0.700\n",
            ">93, 68/234, d=0.688, g=0.691\n",
            ">93, 69/234, d=0.690, g=0.687\n",
            ">93, 70/234, d=0.698, g=0.705\n",
            ">93, 71/234, d=0.690, g=0.709\n",
            ">93, 72/234, d=0.690, g=0.709\n",
            ">93, 73/234, d=0.701, g=0.724\n",
            ">93, 74/234, d=0.690, g=0.699\n",
            ">93, 75/234, d=0.696, g=0.694\n",
            ">93, 76/234, d=0.695, g=0.690\n",
            ">93, 77/234, d=0.690, g=0.699\n",
            ">93, 78/234, d=0.698, g=0.707\n",
            ">93, 79/234, d=0.692, g=0.726\n",
            ">93, 80/234, d=0.688, g=0.732\n",
            ">93, 81/234, d=0.691, g=0.708\n",
            ">93, 82/234, d=0.690, g=0.684\n",
            ">93, 83/234, d=0.684, g=0.666\n",
            ">93, 84/234, d=0.692, g=0.682\n",
            ">93, 85/234, d=0.692, g=0.699\n",
            ">93, 86/234, d=0.690, g=0.721\n",
            ">93, 87/234, d=0.692, g=0.696\n",
            ">93, 88/234, d=0.690, g=0.694\n",
            ">93, 89/234, d=0.694, g=0.697\n",
            ">93, 90/234, d=0.689, g=0.693\n",
            ">93, 91/234, d=0.688, g=0.680\n",
            ">93, 92/234, d=0.693, g=0.697\n",
            ">93, 93/234, d=0.686, g=0.695\n",
            ">93, 94/234, d=0.692, g=0.699\n",
            ">93, 95/234, d=0.699, g=0.701\n",
            ">93, 96/234, d=0.694, g=0.708\n",
            ">93, 97/234, d=0.685, g=0.697\n",
            ">93, 98/234, d=0.684, g=0.685\n",
            ">93, 99/234, d=0.693, g=0.694\n",
            ">93, 100/234, d=0.691, g=0.699\n",
            ">93, 101/234, d=0.693, g=0.726\n",
            ">93, 102/234, d=0.685, g=0.711\n",
            ">93, 103/234, d=0.688, g=0.690\n",
            ">93, 104/234, d=0.694, g=0.684\n",
            ">93, 105/234, d=0.691, g=0.685\n",
            ">93, 106/234, d=0.687, g=0.703\n",
            ">93, 107/234, d=0.684, g=0.721\n",
            ">93, 108/234, d=0.689, g=0.716\n",
            ">93, 109/234, d=0.693, g=0.708\n",
            ">93, 110/234, d=0.684, g=0.697\n",
            ">93, 111/234, d=0.685, g=0.686\n",
            ">93, 112/234, d=0.685, g=0.699\n",
            ">93, 113/234, d=0.697, g=0.692\n",
            ">93, 114/234, d=0.696, g=0.694\n",
            ">93, 115/234, d=0.693, g=0.698\n",
            ">93, 116/234, d=0.691, g=0.695\n",
            ">93, 117/234, d=0.688, g=0.704\n",
            ">93, 118/234, d=0.693, g=0.709\n",
            ">93, 119/234, d=0.690, g=0.702\n",
            ">93, 120/234, d=0.696, g=0.681\n",
            ">93, 121/234, d=0.693, g=0.700\n",
            ">93, 122/234, d=0.691, g=0.723\n",
            ">93, 123/234, d=0.701, g=0.746\n",
            ">93, 124/234, d=0.692, g=0.712\n",
            ">93, 125/234, d=0.696, g=0.678\n",
            ">93, 126/234, d=0.690, g=0.673\n",
            ">93, 127/234, d=0.696, g=0.677\n",
            ">93, 128/234, d=0.689, g=0.682\n",
            ">93, 129/234, d=0.692, g=0.729\n",
            ">93, 130/234, d=0.685, g=0.757\n",
            ">93, 131/234, d=0.680, g=0.723\n",
            ">93, 132/234, d=0.695, g=0.687\n",
            ">93, 133/234, d=0.696, g=0.672\n",
            ">93, 134/234, d=0.692, g=0.666\n",
            ">93, 135/234, d=0.697, g=0.719\n",
            ">93, 136/234, d=0.693, g=0.744\n",
            ">93, 137/234, d=0.683, g=0.720\n",
            ">93, 138/234, d=0.698, g=0.692\n",
            ">93, 139/234, d=0.689, g=0.679\n",
            ">93, 140/234, d=0.690, g=0.692\n",
            ">93, 141/234, d=0.689, g=0.706\n",
            ">93, 142/234, d=0.691, g=0.711\n",
            ">93, 143/234, d=0.699, g=0.709\n",
            ">93, 144/234, d=0.685, g=0.693\n",
            ">93, 145/234, d=0.687, g=0.692\n",
            ">93, 146/234, d=0.690, g=0.681\n",
            ">93, 147/234, d=0.694, g=0.697\n",
            ">93, 148/234, d=0.693, g=0.694\n",
            ">93, 149/234, d=0.694, g=0.696\n",
            ">93, 150/234, d=0.688, g=0.706\n",
            ">93, 151/234, d=0.702, g=0.706\n",
            ">93, 152/234, d=0.694, g=0.699\n",
            ">93, 153/234, d=0.692, g=0.698\n",
            ">93, 154/234, d=0.694, g=0.709\n",
            ">93, 155/234, d=0.694, g=0.711\n",
            ">93, 156/234, d=0.692, g=0.707\n",
            ">93, 157/234, d=0.685, g=0.707\n",
            ">93, 158/234, d=0.687, g=0.710\n",
            ">93, 159/234, d=0.691, g=0.685\n",
            ">93, 160/234, d=0.688, g=0.686\n",
            ">93, 161/234, d=0.687, g=0.679\n",
            ">93, 162/234, d=0.686, g=0.689\n",
            ">93, 163/234, d=0.689, g=0.706\n",
            ">93, 164/234, d=0.685, g=0.719\n",
            ">93, 165/234, d=0.693, g=0.718\n",
            ">93, 166/234, d=0.694, g=0.701\n",
            ">93, 167/234, d=0.698, g=0.686\n",
            ">93, 168/234, d=0.697, g=0.687\n",
            ">93, 169/234, d=0.689, g=0.698\n",
            ">93, 170/234, d=0.696, g=0.719\n",
            ">93, 171/234, d=0.690, g=0.721\n",
            ">93, 172/234, d=0.681, g=0.718\n",
            ">93, 173/234, d=0.690, g=0.724\n",
            ">93, 174/234, d=0.691, g=0.721\n",
            ">93, 175/234, d=0.698, g=0.701\n",
            ">93, 176/234, d=0.699, g=0.672\n",
            ">93, 177/234, d=0.696, g=0.672\n",
            ">93, 178/234, d=0.697, g=0.684\n",
            ">93, 179/234, d=0.686, g=0.705\n",
            ">93, 180/234, d=0.692, g=0.723\n",
            ">93, 181/234, d=0.694, g=0.719\n",
            ">93, 182/234, d=0.682, g=0.711\n",
            ">93, 183/234, d=0.699, g=0.691\n",
            ">93, 184/234, d=0.687, g=0.697\n",
            ">93, 185/234, d=0.692, g=0.684\n",
            ">93, 186/234, d=0.691, g=0.696\n",
            ">93, 187/234, d=0.685, g=0.697\n",
            ">93, 188/234, d=0.695, g=0.705\n",
            ">93, 189/234, d=0.692, g=0.711\n",
            ">93, 190/234, d=0.694, g=0.702\n",
            ">93, 191/234, d=0.693, g=0.724\n",
            ">93, 192/234, d=0.690, g=0.705\n",
            ">93, 193/234, d=0.685, g=0.692\n",
            ">93, 194/234, d=0.693, g=0.680\n",
            ">93, 195/234, d=0.683, g=0.694\n",
            ">93, 196/234, d=0.688, g=0.699\n",
            ">93, 197/234, d=0.686, g=0.686\n",
            ">93, 198/234, d=0.691, g=0.688\n",
            ">93, 199/234, d=0.689, g=0.701\n",
            ">93, 200/234, d=0.688, g=0.717\n",
            ">93, 201/234, d=0.696, g=0.703\n",
            ">93, 202/234, d=0.689, g=0.705\n",
            ">93, 203/234, d=0.691, g=0.706\n",
            ">93, 204/234, d=0.690, g=0.709\n",
            ">93, 205/234, d=0.691, g=0.708\n",
            ">93, 206/234, d=0.687, g=0.685\n",
            ">93, 207/234, d=0.694, g=0.678\n",
            ">93, 208/234, d=0.695, g=0.694\n",
            ">93, 209/234, d=0.697, g=0.704\n",
            ">93, 210/234, d=0.697, g=0.717\n",
            ">93, 211/234, d=0.690, g=0.707\n",
            ">93, 212/234, d=0.694, g=0.690\n",
            ">93, 213/234, d=0.692, g=0.675\n",
            ">93, 214/234, d=0.694, g=0.681\n",
            ">93, 215/234, d=0.697, g=0.707\n",
            ">93, 216/234, d=0.684, g=0.718\n",
            ">93, 217/234, d=0.690, g=0.704\n",
            ">93, 218/234, d=0.692, g=0.700\n",
            ">93, 219/234, d=0.695, g=0.696\n",
            ">93, 220/234, d=0.694, g=0.678\n",
            ">93, 221/234, d=0.694, g=0.679\n",
            ">93, 222/234, d=0.695, g=0.715\n",
            ">93, 223/234, d=0.701, g=0.716\n",
            ">93, 224/234, d=0.686, g=0.697\n",
            ">93, 225/234, d=0.696, g=0.690\n",
            ">93, 226/234, d=0.690, g=0.680\n",
            ">93, 227/234, d=0.696, g=0.684\n",
            ">93, 228/234, d=0.685, g=0.701\n",
            ">93, 229/234, d=0.694, g=0.710\n",
            ">93, 230/234, d=0.689, g=0.713\n",
            ">93, 231/234, d=0.696, g=0.707\n",
            ">93, 232/234, d=0.699, g=0.717\n",
            ">93, 233/234, d=0.690, g=0.705\n",
            ">93, 234/234, d=0.702, g=0.687\n",
            ">94, 1/234, d=0.695, g=0.673\n",
            ">94, 2/234, d=0.690, g=0.696\n",
            ">94, 3/234, d=0.686, g=0.718\n",
            ">94, 4/234, d=0.690, g=0.733\n",
            ">94, 5/234, d=0.692, g=0.726\n",
            ">94, 6/234, d=0.692, g=0.687\n",
            ">94, 7/234, d=0.694, g=0.681\n",
            ">94, 8/234, d=0.693, g=0.697\n",
            ">94, 9/234, d=0.694, g=0.713\n",
            ">94, 10/234, d=0.692, g=0.713\n",
            ">94, 11/234, d=0.697, g=0.703\n",
            ">94, 12/234, d=0.693, g=0.689\n",
            ">94, 13/234, d=0.699, g=0.685\n",
            ">94, 14/234, d=0.690, g=0.697\n",
            ">94, 15/234, d=0.691, g=0.711\n",
            ">94, 16/234, d=0.688, g=0.726\n",
            ">94, 17/234, d=0.691, g=0.699\n",
            ">94, 18/234, d=0.684, g=0.701\n",
            ">94, 19/234, d=0.694, g=0.683\n",
            ">94, 20/234, d=0.689, g=0.703\n",
            ">94, 21/234, d=0.694, g=0.704\n",
            ">94, 22/234, d=0.687, g=0.703\n",
            ">94, 23/234, d=0.683, g=0.692\n",
            ">94, 24/234, d=0.687, g=0.685\n",
            ">94, 25/234, d=0.691, g=0.697\n",
            ">94, 26/234, d=0.695, g=0.708\n",
            ">94, 27/234, d=0.693, g=0.725\n",
            ">94, 28/234, d=0.690, g=0.721\n",
            ">94, 29/234, d=0.695, g=0.720\n",
            ">94, 30/234, d=0.686, g=0.708\n",
            ">94, 31/234, d=0.683, g=0.692\n",
            ">94, 32/234, d=0.690, g=0.692\n",
            ">94, 33/234, d=0.693, g=0.710\n",
            ">94, 34/234, d=0.689, g=0.693\n",
            ">94, 35/234, d=0.686, g=0.692\n",
            ">94, 36/234, d=0.686, g=0.699\n",
            ">94, 37/234, d=0.701, g=0.686\n",
            ">94, 38/234, d=0.692, g=0.694\n",
            ">94, 39/234, d=0.697, g=0.689\n",
            ">94, 40/234, d=0.688, g=0.695\n",
            ">94, 41/234, d=0.689, g=0.700\n",
            ">94, 42/234, d=0.696, g=0.708\n",
            ">94, 43/234, d=0.700, g=0.717\n",
            ">94, 44/234, d=0.690, g=0.710\n",
            ">94, 45/234, d=0.697, g=0.709\n",
            ">94, 46/234, d=0.700, g=0.712\n",
            ">94, 47/234, d=0.690, g=0.708\n",
            ">94, 48/234, d=0.688, g=0.689\n",
            ">94, 49/234, d=0.685, g=0.687\n",
            ">94, 50/234, d=0.690, g=0.696\n",
            ">94, 51/234, d=0.694, g=0.710\n",
            ">94, 52/234, d=0.685, g=0.696\n",
            ">94, 53/234, d=0.687, g=0.706\n",
            ">94, 54/234, d=0.696, g=0.694\n",
            ">94, 55/234, d=0.697, g=0.685\n",
            ">94, 56/234, d=0.696, g=0.688\n",
            ">94, 57/234, d=0.698, g=0.689\n",
            ">94, 58/234, d=0.700, g=0.721\n",
            ">94, 59/234, d=0.690, g=0.739\n",
            ">94, 60/234, d=0.689, g=0.727\n",
            ">94, 61/234, d=0.693, g=0.703\n",
            ">94, 62/234, d=0.693, g=0.675\n",
            ">94, 63/234, d=0.688, g=0.671\n",
            ">94, 64/234, d=0.693, g=0.700\n",
            ">94, 65/234, d=0.694, g=0.711\n",
            ">94, 66/234, d=0.690, g=0.699\n",
            ">94, 67/234, d=0.692, g=0.699\n",
            ">94, 68/234, d=0.698, g=0.707\n",
            ">94, 69/234, d=0.694, g=0.716\n",
            ">94, 70/234, d=0.688, g=0.701\n",
            ">94, 71/234, d=0.683, g=0.689\n",
            ">94, 72/234, d=0.697, g=0.696\n",
            ">94, 73/234, d=0.685, g=0.691\n",
            ">94, 74/234, d=0.693, g=0.690\n",
            ">94, 75/234, d=0.698, g=0.714\n",
            ">94, 76/234, d=0.695, g=0.725\n",
            ">94, 77/234, d=0.689, g=0.702\n",
            ">94, 78/234, d=0.698, g=0.685\n",
            ">94, 79/234, d=0.695, g=0.686\n",
            ">94, 80/234, d=0.698, g=0.699\n",
            ">94, 81/234, d=0.686, g=0.733\n",
            ">94, 82/234, d=0.693, g=0.707\n",
            ">94, 83/234, d=0.683, g=0.693\n",
            ">94, 84/234, d=0.690, g=0.701\n",
            ">94, 85/234, d=0.688, g=0.712\n",
            ">94, 86/234, d=0.694, g=0.697\n",
            ">94, 87/234, d=0.691, g=0.680\n",
            ">94, 88/234, d=0.685, g=0.673\n",
            ">94, 89/234, d=0.693, g=0.694\n",
            ">94, 90/234, d=0.691, g=0.706\n",
            ">94, 91/234, d=0.692, g=0.706\n",
            ">94, 92/234, d=0.700, g=0.713\n",
            ">94, 93/234, d=0.682, g=0.717\n",
            ">94, 94/234, d=0.691, g=0.699\n",
            ">94, 95/234, d=0.685, g=0.693\n",
            ">94, 96/234, d=0.689, g=0.697\n",
            ">94, 97/234, d=0.694, g=0.704\n",
            ">94, 98/234, d=0.689, g=0.680\n",
            ">94, 99/234, d=0.691, g=0.688\n",
            ">94, 100/234, d=0.697, g=0.706\n",
            ">94, 101/234, d=0.687, g=0.704\n",
            ">94, 102/234, d=0.696, g=0.691\n",
            ">94, 103/234, d=0.698, g=0.713\n",
            ">94, 104/234, d=0.693, g=0.718\n",
            ">94, 105/234, d=0.690, g=0.725\n",
            ">94, 106/234, d=0.694, g=0.696\n",
            ">94, 107/234, d=0.693, g=0.693\n",
            ">94, 108/234, d=0.693, g=0.676\n",
            ">94, 109/234, d=0.689, g=0.683\n",
            ">94, 110/234, d=0.695, g=0.705\n",
            ">94, 111/234, d=0.692, g=0.714\n",
            ">94, 112/234, d=0.692, g=0.725\n",
            ">94, 113/234, d=0.683, g=0.704\n",
            ">94, 114/234, d=0.688, g=0.701\n",
            ">94, 115/234, d=0.693, g=0.700\n",
            ">94, 116/234, d=0.692, g=0.700\n",
            ">94, 117/234, d=0.692, g=0.693\n",
            ">94, 118/234, d=0.683, g=0.698\n",
            ">94, 119/234, d=0.690, g=0.703\n",
            ">94, 120/234, d=0.693, g=0.699\n",
            ">94, 121/234, d=0.697, g=0.704\n",
            ">94, 122/234, d=0.685, g=0.700\n",
            ">94, 123/234, d=0.688, g=0.695\n",
            ">94, 124/234, d=0.689, g=0.707\n",
            ">94, 125/234, d=0.691, g=0.712\n",
            ">94, 126/234, d=0.696, g=0.706\n",
            ">94, 127/234, d=0.693, g=0.702\n",
            ">94, 128/234, d=0.698, g=0.714\n",
            ">94, 129/234, d=0.692, g=0.714\n",
            ">94, 130/234, d=0.690, g=0.697\n",
            ">94, 131/234, d=0.696, g=0.701\n",
            ">94, 132/234, d=0.685, g=0.690\n",
            ">94, 133/234, d=0.687, g=0.682\n",
            ">94, 134/234, d=0.692, g=0.692\n",
            ">94, 135/234, d=0.687, g=0.694\n",
            ">94, 136/234, d=0.690, g=0.693\n",
            ">94, 137/234, d=0.692, g=0.713\n",
            ">94, 138/234, d=0.687, g=0.722\n",
            ">94, 139/234, d=0.688, g=0.697\n",
            ">94, 140/234, d=0.685, g=0.675\n",
            ">94, 141/234, d=0.687, g=0.677\n",
            ">94, 142/234, d=0.693, g=0.693\n",
            ">94, 143/234, d=0.692, g=0.716\n",
            ">94, 144/234, d=0.694, g=0.718\n",
            ">94, 145/234, d=0.692, g=0.715\n",
            ">94, 146/234, d=0.693, g=0.688\n",
            ">94, 147/234, d=0.694, g=0.666\n",
            ">94, 148/234, d=0.695, g=0.670\n",
            ">94, 149/234, d=0.691, g=0.688\n",
            ">94, 150/234, d=0.694, g=0.743\n",
            ">94, 151/234, d=0.687, g=0.748\n",
            ">94, 152/234, d=0.691, g=0.712\n",
            ">94, 153/234, d=0.692, g=0.686\n",
            ">94, 154/234, d=0.690, g=0.681\n",
            ">94, 155/234, d=0.690, g=0.663\n",
            ">94, 156/234, d=0.688, g=0.680\n",
            ">94, 157/234, d=0.686, g=0.694\n",
            ">94, 158/234, d=0.690, g=0.713\n",
            ">94, 159/234, d=0.686, g=0.708\n",
            ">94, 160/234, d=0.694, g=0.710\n",
            ">94, 161/234, d=0.686, g=0.685\n",
            ">94, 162/234, d=0.692, g=0.680\n",
            ">94, 163/234, d=0.695, g=0.679\n",
            ">94, 164/234, d=0.694, g=0.710\n",
            ">94, 165/234, d=0.697, g=0.739\n",
            ">94, 166/234, d=0.689, g=0.707\n",
            ">94, 167/234, d=0.694, g=0.680\n",
            ">94, 168/234, d=0.686, g=0.690\n",
            ">94, 169/234, d=0.696, g=0.713\n",
            ">94, 170/234, d=0.684, g=0.718\n",
            ">94, 171/234, d=0.686, g=0.716\n",
            ">94, 172/234, d=0.695, g=0.699\n",
            ">94, 173/234, d=0.695, g=0.673\n",
            ">94, 174/234, d=0.693, g=0.680\n",
            ">94, 175/234, d=0.689, g=0.709\n",
            ">94, 176/234, d=0.685, g=0.707\n",
            ">94, 177/234, d=0.695, g=0.692\n",
            ">94, 178/234, d=0.686, g=0.673\n",
            ">94, 179/234, d=0.692, g=0.695\n",
            ">94, 180/234, d=0.692, g=0.731\n",
            ">94, 181/234, d=0.692, g=0.739\n",
            ">94, 182/234, d=0.694, g=0.721\n",
            ">94, 183/234, d=0.692, g=0.695\n",
            ">94, 184/234, d=0.693, g=0.680\n",
            ">94, 185/234, d=0.683, g=0.686\n",
            ">94, 186/234, d=0.695, g=0.706\n",
            ">94, 187/234, d=0.689, g=0.702\n",
            ">94, 188/234, d=0.695, g=0.717\n",
            ">94, 189/234, d=0.686, g=0.713\n",
            ">94, 190/234, d=0.689, g=0.712\n",
            ">94, 191/234, d=0.689, g=0.705\n",
            ">94, 192/234, d=0.693, g=0.694\n",
            ">94, 193/234, d=0.698, g=0.677\n",
            ">94, 194/234, d=0.684, g=0.682\n",
            ">94, 195/234, d=0.691, g=0.704\n",
            ">94, 196/234, d=0.689, g=0.718\n",
            ">94, 197/234, d=0.689, g=0.705\n",
            ">94, 198/234, d=0.691, g=0.684\n",
            ">94, 199/234, d=0.694, g=0.681\n",
            ">94, 200/234, d=0.689, g=0.688\n",
            ">94, 201/234, d=0.690, g=0.690\n",
            ">94, 202/234, d=0.691, g=0.698\n",
            ">94, 203/234, d=0.690, g=0.700\n",
            ">94, 204/234, d=0.699, g=0.721\n",
            ">94, 205/234, d=0.693, g=0.709\n",
            ">94, 206/234, d=0.694, g=0.705\n",
            ">94, 207/234, d=0.694, g=0.704\n",
            ">94, 208/234, d=0.694, g=0.702\n",
            ">94, 209/234, d=0.687, g=0.707\n",
            ">94, 210/234, d=0.694, g=0.720\n",
            ">94, 211/234, d=0.693, g=0.700\n",
            ">94, 212/234, d=0.691, g=0.686\n",
            ">94, 213/234, d=0.695, g=0.693\n",
            ">94, 214/234, d=0.693, g=0.699\n",
            ">94, 215/234, d=0.684, g=0.706\n",
            ">94, 216/234, d=0.694, g=0.695\n",
            ">94, 217/234, d=0.702, g=0.684\n",
            ">94, 218/234, d=0.697, g=0.683\n",
            ">94, 219/234, d=0.694, g=0.696\n",
            ">94, 220/234, d=0.696, g=0.703\n",
            ">94, 221/234, d=0.686, g=0.696\n",
            ">94, 222/234, d=0.693, g=0.689\n",
            ">94, 223/234, d=0.700, g=0.690\n",
            ">94, 224/234, d=0.690, g=0.717\n",
            ">94, 225/234, d=0.691, g=0.718\n",
            ">94, 226/234, d=0.697, g=0.698\n",
            ">94, 227/234, d=0.687, g=0.688\n",
            ">94, 228/234, d=0.691, g=0.716\n",
            ">94, 229/234, d=0.691, g=0.707\n",
            ">94, 230/234, d=0.693, g=0.696\n",
            ">94, 231/234, d=0.690, g=0.685\n",
            ">94, 232/234, d=0.689, g=0.684\n",
            ">94, 233/234, d=0.695, g=0.691\n",
            ">94, 234/234, d=0.694, g=0.696\n",
            ">95, 1/234, d=0.690, g=0.705\n",
            ">95, 2/234, d=0.687, g=0.697\n",
            ">95, 3/234, d=0.688, g=0.707\n",
            ">95, 4/234, d=0.686, g=0.718\n",
            ">95, 5/234, d=0.694, g=0.721\n",
            ">95, 6/234, d=0.702, g=0.727\n",
            ">95, 7/234, d=0.692, g=0.713\n",
            ">95, 8/234, d=0.686, g=0.693\n",
            ">95, 9/234, d=0.694, g=0.691\n",
            ">95, 10/234, d=0.693, g=0.681\n",
            ">95, 11/234, d=0.702, g=0.698\n",
            ">95, 12/234, d=0.693, g=0.722\n",
            ">95, 13/234, d=0.694, g=0.737\n",
            ">95, 14/234, d=0.694, g=0.720\n",
            ">95, 15/234, d=0.689, g=0.694\n",
            ">95, 16/234, d=0.691, g=0.684\n",
            ">95, 17/234, d=0.693, g=0.695\n",
            ">95, 18/234, d=0.684, g=0.690\n",
            ">95, 19/234, d=0.693, g=0.690\n",
            ">95, 20/234, d=0.691, g=0.703\n",
            ">95, 21/234, d=0.683, g=0.701\n",
            ">95, 22/234, d=0.696, g=0.711\n",
            ">95, 23/234, d=0.693, g=0.708\n",
            ">95, 24/234, d=0.693, g=0.707\n",
            ">95, 25/234, d=0.689, g=0.696\n",
            ">95, 26/234, d=0.692, g=0.680\n",
            ">95, 27/234, d=0.693, g=0.691\n",
            ">95, 28/234, d=0.693, g=0.722\n",
            ">95, 29/234, d=0.690, g=0.727\n",
            ">95, 30/234, d=0.683, g=0.710\n",
            ">95, 31/234, d=0.695, g=0.689\n",
            ">95, 32/234, d=0.693, g=0.684\n",
            ">95, 33/234, d=0.689, g=0.695\n",
            ">95, 34/234, d=0.690, g=0.720\n",
            ">95, 35/234, d=0.693, g=0.715\n",
            ">95, 36/234, d=0.694, g=0.697\n",
            ">95, 37/234, d=0.697, g=0.677\n",
            ">95, 38/234, d=0.693, g=0.676\n",
            ">95, 39/234, d=0.684, g=0.701\n",
            ">95, 40/234, d=0.692, g=0.718\n",
            ">95, 41/234, d=0.691, g=0.726\n",
            ">95, 42/234, d=0.699, g=0.711\n",
            ">95, 43/234, d=0.688, g=0.697\n",
            ">95, 44/234, d=0.688, g=0.697\n",
            ">95, 45/234, d=0.687, g=0.710\n",
            ">95, 46/234, d=0.695, g=0.703\n",
            ">95, 47/234, d=0.688, g=0.702\n",
            ">95, 48/234, d=0.691, g=0.703\n",
            ">95, 49/234, d=0.693, g=0.721\n",
            ">95, 50/234, d=0.684, g=0.717\n",
            ">95, 51/234, d=0.686, g=0.709\n",
            ">95, 52/234, d=0.683, g=0.689\n",
            ">95, 53/234, d=0.695, g=0.682\n",
            ">95, 54/234, d=0.686, g=0.671\n",
            ">95, 55/234, d=0.684, g=0.677\n",
            ">95, 56/234, d=0.696, g=0.701\n",
            ">95, 57/234, d=0.692, g=0.726\n",
            ">95, 58/234, d=0.688, g=0.721\n",
            ">95, 59/234, d=0.695, g=0.689\n",
            ">95, 60/234, d=0.685, g=0.689\n",
            ">95, 61/234, d=0.693, g=0.685\n",
            ">95, 62/234, d=0.687, g=0.692\n",
            ">95, 63/234, d=0.694, g=0.704\n",
            ">95, 64/234, d=0.692, g=0.695\n",
            ">95, 65/234, d=0.694, g=0.710\n",
            ">95, 66/234, d=0.687, g=0.729\n",
            ">95, 67/234, d=0.694, g=0.732\n",
            ">95, 68/234, d=0.687, g=0.692\n",
            ">95, 69/234, d=0.681, g=0.678\n",
            ">95, 70/234, d=0.694, g=0.669\n",
            ">95, 71/234, d=0.692, g=0.683\n",
            ">95, 72/234, d=0.687, g=0.708\n",
            ">95, 73/234, d=0.685, g=0.708\n",
            ">95, 74/234, d=0.691, g=0.690\n",
            ">95, 75/234, d=0.690, g=0.695\n",
            ">95, 76/234, d=0.686, g=0.698\n",
            ">95, 77/234, d=0.691, g=0.702\n",
            ">95, 78/234, d=0.682, g=0.685\n",
            ">95, 79/234, d=0.693, g=0.697\n",
            ">95, 80/234, d=0.686, g=0.707\n",
            ">95, 81/234, d=0.693, g=0.713\n",
            ">95, 82/234, d=0.695, g=0.715\n",
            ">95, 83/234, d=0.688, g=0.710\n",
            ">95, 84/234, d=0.687, g=0.700\n",
            ">95, 85/234, d=0.692, g=0.689\n",
            ">95, 86/234, d=0.695, g=0.677\n",
            ">95, 87/234, d=0.687, g=0.686\n",
            ">95, 88/234, d=0.689, g=0.698\n",
            ">95, 89/234, d=0.688, g=0.711\n",
            ">95, 90/234, d=0.696, g=0.715\n",
            ">95, 91/234, d=0.688, g=0.701\n",
            ">95, 92/234, d=0.679, g=0.694\n",
            ">95, 93/234, d=0.685, g=0.693\n",
            ">95, 94/234, d=0.695, g=0.712\n",
            ">95, 95/234, d=0.685, g=0.717\n",
            ">95, 96/234, d=0.688, g=0.702\n",
            ">95, 97/234, d=0.688, g=0.687\n",
            ">95, 98/234, d=0.687, g=0.687\n",
            ">95, 99/234, d=0.680, g=0.692\n",
            ">95, 100/234, d=0.684, g=0.706\n",
            ">95, 101/234, d=0.696, g=0.728\n",
            ">95, 102/234, d=0.690, g=0.714\n",
            ">95, 103/234, d=0.691, g=0.696\n",
            ">95, 104/234, d=0.692, g=0.673\n",
            ">95, 105/234, d=0.692, g=0.687\n",
            ">95, 106/234, d=0.696, g=0.716\n",
            ">95, 107/234, d=0.695, g=0.725\n",
            ">95, 108/234, d=0.682, g=0.713\n",
            ">95, 109/234, d=0.685, g=0.686\n",
            ">95, 110/234, d=0.684, g=0.679\n",
            ">95, 111/234, d=0.696, g=0.675\n",
            ">95, 112/234, d=0.692, g=0.707\n",
            ">95, 113/234, d=0.693, g=0.714\n",
            ">95, 114/234, d=0.688, g=0.703\n",
            ">95, 115/234, d=0.691, g=0.690\n",
            ">95, 116/234, d=0.690, g=0.693\n",
            ">95, 117/234, d=0.699, g=0.719\n",
            ">95, 118/234, d=0.684, g=0.730\n",
            ">95, 119/234, d=0.691, g=0.718\n",
            ">95, 120/234, d=0.692, g=0.692\n",
            ">95, 121/234, d=0.692, g=0.677\n",
            ">95, 122/234, d=0.683, g=0.699\n",
            ">95, 123/234, d=0.692, g=0.721\n",
            ">95, 124/234, d=0.692, g=0.712\n",
            ">95, 125/234, d=0.690, g=0.697\n",
            ">95, 126/234, d=0.689, g=0.682\n",
            ">95, 127/234, d=0.690, g=0.685\n",
            ">95, 128/234, d=0.686, g=0.714\n",
            ">95, 129/234, d=0.693, g=0.719\n",
            ">95, 130/234, d=0.692, g=0.709\n",
            ">95, 131/234, d=0.688, g=0.692\n",
            ">95, 132/234, d=0.692, g=0.692\n",
            ">95, 133/234, d=0.693, g=0.687\n",
            ">95, 134/234, d=0.692, g=0.699\n",
            ">95, 135/234, d=0.686, g=0.698\n",
            ">95, 136/234, d=0.690, g=0.707\n",
            ">95, 137/234, d=0.686, g=0.698\n",
            ">95, 138/234, d=0.689, g=0.694\n",
            ">95, 139/234, d=0.693, g=0.695\n",
            ">95, 140/234, d=0.700, g=0.691\n",
            ">95, 141/234, d=0.691, g=0.700\n",
            ">95, 142/234, d=0.691, g=0.698\n",
            ">95, 143/234, d=0.687, g=0.685\n",
            ">95, 144/234, d=0.690, g=0.707\n",
            ">95, 145/234, d=0.691, g=0.703\n",
            ">95, 146/234, d=0.697, g=0.722\n",
            ">95, 147/234, d=0.689, g=0.720\n",
            ">95, 148/234, d=0.701, g=0.691\n",
            ">95, 149/234, d=0.686, g=0.666\n",
            ">95, 150/234, d=0.692, g=0.695\n",
            ">95, 151/234, d=0.697, g=0.711\n",
            ">95, 152/234, d=0.691, g=0.731\n",
            ">95, 153/234, d=0.693, g=0.720\n",
            ">95, 154/234, d=0.691, g=0.706\n",
            ">95, 155/234, d=0.689, g=0.699\n",
            ">95, 156/234, d=0.689, g=0.687\n",
            ">95, 157/234, d=0.695, g=0.692\n",
            ">95, 158/234, d=0.687, g=0.689\n",
            ">95, 159/234, d=0.688, g=0.700\n",
            ">95, 160/234, d=0.691, g=0.699\n",
            ">95, 161/234, d=0.689, g=0.705\n",
            ">95, 162/234, d=0.696, g=0.713\n",
            ">95, 163/234, d=0.693, g=0.716\n",
            ">95, 164/234, d=0.688, g=0.708\n",
            ">95, 165/234, d=0.691, g=0.695\n",
            ">95, 166/234, d=0.688, g=0.692\n",
            ">95, 167/234, d=0.690, g=0.681\n",
            ">95, 168/234, d=0.689, g=0.689\n",
            ">95, 169/234, d=0.697, g=0.710\n",
            ">95, 170/234, d=0.693, g=0.722\n",
            ">95, 171/234, d=0.695, g=0.709\n",
            ">95, 172/234, d=0.693, g=0.688\n",
            ">95, 173/234, d=0.698, g=0.679\n",
            ">95, 174/234, d=0.692, g=0.689\n",
            ">95, 175/234, d=0.689, g=0.708\n",
            ">95, 176/234, d=0.686, g=0.714\n",
            ">95, 177/234, d=0.691, g=0.702\n",
            ">95, 178/234, d=0.694, g=0.694\n",
            ">95, 179/234, d=0.690, g=0.699\n",
            ">95, 180/234, d=0.704, g=0.708\n",
            ">95, 181/234, d=0.690, g=0.700\n",
            ">95, 182/234, d=0.693, g=0.695\n",
            ">95, 183/234, d=0.689, g=0.694\n",
            ">95, 184/234, d=0.694, g=0.702\n",
            ">95, 185/234, d=0.690, g=0.715\n",
            ">95, 186/234, d=0.686, g=0.713\n",
            ">95, 187/234, d=0.682, g=0.691\n",
            ">95, 188/234, d=0.687, g=0.690\n",
            ">95, 189/234, d=0.685, g=0.688\n",
            ">95, 190/234, d=0.688, g=0.707\n",
            ">95, 191/234, d=0.682, g=0.701\n",
            ">95, 192/234, d=0.696, g=0.709\n",
            ">95, 193/234, d=0.686, g=0.704\n",
            ">95, 194/234, d=0.695, g=0.693\n",
            ">95, 195/234, d=0.697, g=0.706\n",
            ">95, 196/234, d=0.690, g=0.707\n",
            ">95, 197/234, d=0.695, g=0.694\n",
            ">95, 198/234, d=0.687, g=0.689\n",
            ">95, 199/234, d=0.691, g=0.696\n",
            ">95, 200/234, d=0.694, g=0.712\n",
            ">95, 201/234, d=0.692, g=0.709\n",
            ">95, 202/234, d=0.690, g=0.716\n",
            ">95, 203/234, d=0.694, g=0.684\n",
            ">95, 204/234, d=0.691, g=0.681\n",
            ">95, 205/234, d=0.689, g=0.686\n",
            ">95, 206/234, d=0.690, g=0.703\n",
            ">95, 207/234, d=0.693, g=0.710\n",
            ">95, 208/234, d=0.690, g=0.732\n",
            ">95, 209/234, d=0.688, g=0.728\n",
            ">95, 210/234, d=0.689, g=0.708\n",
            ">95, 211/234, d=0.687, g=0.685\n",
            ">95, 212/234, d=0.693, g=0.680\n",
            ">95, 213/234, d=0.698, g=0.701\n",
            ">95, 214/234, d=0.693, g=0.712\n",
            ">95, 215/234, d=0.688, g=0.720\n",
            ">95, 216/234, d=0.699, g=0.696\n",
            ">95, 217/234, d=0.692, g=0.685\n",
            ">95, 218/234, d=0.693, g=0.677\n",
            ">95, 219/234, d=0.692, g=0.699\n",
            ">95, 220/234, d=0.696, g=0.719\n",
            ">95, 221/234, d=0.688, g=0.716\n",
            ">95, 222/234, d=0.696, g=0.700\n",
            ">95, 223/234, d=0.686, g=0.696\n",
            ">95, 224/234, d=0.689, g=0.710\n",
            ">95, 225/234, d=0.690, g=0.726\n",
            ">95, 226/234, d=0.694, g=0.704\n",
            ">95, 227/234, d=0.693, g=0.689\n",
            ">95, 228/234, d=0.688, g=0.687\n",
            ">95, 229/234, d=0.683, g=0.703\n",
            ">95, 230/234, d=0.694, g=0.702\n",
            ">95, 231/234, d=0.695, g=0.692\n",
            ">95, 232/234, d=0.685, g=0.676\n",
            ">95, 233/234, d=0.694, g=0.691\n",
            ">95, 234/234, d=0.690, g=0.704\n",
            ">96, 1/234, d=0.697, g=0.711\n",
            ">96, 2/234, d=0.700, g=0.710\n",
            ">96, 3/234, d=0.695, g=0.696\n",
            ">96, 4/234, d=0.701, g=0.703\n",
            ">96, 5/234, d=0.691, g=0.701\n",
            ">96, 6/234, d=0.687, g=0.699\n",
            ">96, 7/234, d=0.694, g=0.689\n",
            ">96, 8/234, d=0.687, g=0.699\n",
            ">96, 9/234, d=0.692, g=0.693\n",
            ">96, 10/234, d=0.687, g=0.687\n",
            ">96, 11/234, d=0.688, g=0.701\n",
            ">96, 12/234, d=0.692, g=0.703\n",
            ">96, 13/234, d=0.695, g=0.701\n",
            ">96, 14/234, d=0.696, g=0.705\n",
            ">96, 15/234, d=0.687, g=0.686\n",
            ">96, 16/234, d=0.690, g=0.688\n",
            ">96, 17/234, d=0.694, g=0.700\n",
            ">96, 18/234, d=0.697, g=0.714\n",
            ">96, 19/234, d=0.688, g=0.714\n",
            ">96, 20/234, d=0.684, g=0.702\n",
            ">96, 21/234, d=0.689, g=0.685\n",
            ">96, 22/234, d=0.696, g=0.679\n",
            ">96, 23/234, d=0.687, g=0.700\n",
            ">96, 24/234, d=0.698, g=0.713\n",
            ">96, 25/234, d=0.692, g=0.713\n",
            ">96, 26/234, d=0.691, g=0.688\n",
            ">96, 27/234, d=0.694, g=0.676\n",
            ">96, 28/234, d=0.687, g=0.687\n",
            ">96, 29/234, d=0.700, g=0.709\n",
            ">96, 30/234, d=0.687, g=0.725\n",
            ">96, 31/234, d=0.688, g=0.719\n",
            ">96, 32/234, d=0.697, g=0.708\n",
            ">96, 33/234, d=0.692, g=0.670\n",
            ">96, 34/234, d=0.690, g=0.689\n",
            ">96, 35/234, d=0.693, g=0.710\n",
            ">96, 36/234, d=0.685, g=0.716\n",
            ">96, 37/234, d=0.692, g=0.715\n",
            ">96, 38/234, d=0.683, g=0.701\n",
            ">96, 39/234, d=0.694, g=0.690\n",
            ">96, 40/234, d=0.688, g=0.689\n",
            ">96, 41/234, d=0.686, g=0.690\n",
            ">96, 42/234, d=0.689, g=0.705\n",
            ">96, 43/234, d=0.692, g=0.700\n",
            ">96, 44/234, d=0.688, g=0.724\n",
            ">96, 45/234, d=0.691, g=0.724\n",
            ">96, 46/234, d=0.695, g=0.705\n",
            ">96, 47/234, d=0.691, g=0.688\n",
            ">96, 48/234, d=0.688, g=0.694\n",
            ">96, 49/234, d=0.687, g=0.696\n",
            ">96, 50/234, d=0.698, g=0.701\n",
            ">96, 51/234, d=0.685, g=0.699\n",
            ">96, 52/234, d=0.694, g=0.710\n",
            ">96, 53/234, d=0.702, g=0.726\n",
            ">96, 54/234, d=0.691, g=0.717\n",
            ">96, 55/234, d=0.690, g=0.702\n",
            ">96, 56/234, d=0.694, g=0.686\n",
            ">96, 57/234, d=0.696, g=0.666\n",
            ">96, 58/234, d=0.694, g=0.682\n",
            ">96, 59/234, d=0.693, g=0.714\n",
            ">96, 60/234, d=0.692, g=0.742\n",
            ">96, 61/234, d=0.692, g=0.718\n",
            ">96, 62/234, d=0.692, g=0.670\n",
            ">96, 63/234, d=0.689, g=0.665\n",
            ">96, 64/234, d=0.687, g=0.693\n",
            ">96, 65/234, d=0.701, g=0.733\n",
            ">96, 66/234, d=0.700, g=0.734\n",
            ">96, 67/234, d=0.696, g=0.724\n",
            ">96, 68/234, d=0.688, g=0.706\n",
            ">96, 69/234, d=0.696, g=0.693\n",
            ">96, 70/234, d=0.694, g=0.698\n",
            ">96, 71/234, d=0.695, g=0.690\n",
            ">96, 72/234, d=0.692, g=0.690\n",
            ">96, 73/234, d=0.686, g=0.682\n",
            ">96, 74/234, d=0.691, g=0.699\n",
            ">96, 75/234, d=0.685, g=0.725\n",
            ">96, 76/234, d=0.693, g=0.721\n",
            ">96, 77/234, d=0.703, g=0.686\n",
            ">96, 78/234, d=0.690, g=0.683\n",
            ">96, 79/234, d=0.698, g=0.680\n",
            ">96, 80/234, d=0.689, g=0.688\n",
            ">96, 81/234, d=0.686, g=0.706\n",
            ">96, 82/234, d=0.688, g=0.742\n",
            ">96, 83/234, d=0.683, g=0.755\n",
            ">96, 84/234, d=0.699, g=0.716\n",
            ">96, 85/234, d=0.701, g=0.671\n",
            ">96, 86/234, d=0.697, g=0.655\n",
            ">96, 87/234, d=0.693, g=0.683\n",
            ">96, 88/234, d=0.701, g=0.719\n",
            ">96, 89/234, d=0.690, g=0.723\n",
            ">96, 90/234, d=0.693, g=0.704\n",
            ">96, 91/234, d=0.689, g=0.689\n",
            ">96, 92/234, d=0.680, g=0.694\n",
            ">96, 93/234, d=0.690, g=0.713\n",
            ">96, 94/234, d=0.679, g=0.723\n",
            ">96, 95/234, d=0.688, g=0.708\n",
            ">96, 96/234, d=0.683, g=0.685\n",
            ">96, 97/234, d=0.689, g=0.684\n",
            ">96, 98/234, d=0.688, g=0.699\n",
            ">96, 99/234, d=0.690, g=0.698\n",
            ">96, 100/234, d=0.691, g=0.714\n",
            ">96, 101/234, d=0.689, g=0.724\n",
            ">96, 102/234, d=0.690, g=0.711\n",
            ">96, 103/234, d=0.688, g=0.694\n",
            ">96, 104/234, d=0.683, g=0.689\n",
            ">96, 105/234, d=0.685, g=0.691\n",
            ">96, 106/234, d=0.694, g=0.693\n",
            ">96, 107/234, d=0.686, g=0.728\n",
            ">96, 108/234, d=0.693, g=0.705\n",
            ">96, 109/234, d=0.686, g=0.693\n",
            ">96, 110/234, d=0.685, g=0.688\n",
            ">96, 111/234, d=0.689, g=0.700\n",
            ">96, 112/234, d=0.695, g=0.715\n",
            ">96, 113/234, d=0.694, g=0.700\n",
            ">96, 114/234, d=0.697, g=0.688\n",
            ">96, 115/234, d=0.686, g=0.675\n",
            ">96, 116/234, d=0.692, g=0.682\n",
            ">96, 117/234, d=0.699, g=0.725\n",
            ">96, 118/234, d=0.686, g=0.729\n",
            ">96, 119/234, d=0.696, g=0.714\n",
            ">96, 120/234, d=0.690, g=0.689\n",
            ">96, 121/234, d=0.691, g=0.691\n",
            ">96, 122/234, d=0.690, g=0.706\n",
            ">96, 123/234, d=0.688, g=0.710\n",
            ">96, 124/234, d=0.699, g=0.704\n",
            ">96, 125/234, d=0.691, g=0.695\n",
            ">96, 126/234, d=0.688, g=0.682\n",
            ">96, 127/234, d=0.683, g=0.692\n",
            ">96, 128/234, d=0.694, g=0.709\n",
            ">96, 129/234, d=0.691, g=0.720\n",
            ">96, 130/234, d=0.693, g=0.696\n",
            ">96, 131/234, d=0.678, g=0.704\n",
            ">96, 132/234, d=0.691, g=0.701\n",
            ">96, 133/234, d=0.689, g=0.691\n",
            ">96, 134/234, d=0.690, g=0.679\n",
            ">96, 135/234, d=0.685, g=0.687\n",
            ">96, 136/234, d=0.690, g=0.703\n",
            ">96, 137/234, d=0.695, g=0.715\n",
            ">96, 138/234, d=0.692, g=0.696\n",
            ">96, 139/234, d=0.693, g=0.696\n",
            ">96, 140/234, d=0.696, g=0.694\n",
            ">96, 141/234, d=0.697, g=0.684\n",
            ">96, 142/234, d=0.686, g=0.689\n",
            ">96, 143/234, d=0.689, g=0.692\n",
            ">96, 144/234, d=0.686, g=0.698\n",
            ">96, 145/234, d=0.691, g=0.695\n",
            ">96, 146/234, d=0.695, g=0.710\n",
            ">96, 147/234, d=0.694, g=0.715\n",
            ">96, 148/234, d=0.688, g=0.703\n",
            ">96, 149/234, d=0.692, g=0.701\n",
            ">96, 150/234, d=0.690, g=0.705\n",
            ">96, 151/234, d=0.698, g=0.706\n",
            ">96, 152/234, d=0.698, g=0.692\n",
            ">96, 153/234, d=0.691, g=0.695\n",
            ">96, 154/234, d=0.690, g=0.686\n",
            ">96, 155/234, d=0.700, g=0.683\n",
            ">96, 156/234, d=0.689, g=0.704\n",
            ">96, 157/234, d=0.686, g=0.702\n",
            ">96, 158/234, d=0.687, g=0.701\n",
            ">96, 159/234, d=0.692, g=0.699\n",
            ">96, 160/234, d=0.690, g=0.702\n",
            ">96, 161/234, d=0.687, g=0.703\n",
            ">96, 162/234, d=0.697, g=0.697\n",
            ">96, 163/234, d=0.688, g=0.695\n",
            ">96, 164/234, d=0.688, g=0.690\n",
            ">96, 165/234, d=0.688, g=0.697\n",
            ">96, 166/234, d=0.690, g=0.707\n",
            ">96, 167/234, d=0.691, g=0.712\n",
            ">96, 168/234, d=0.692, g=0.697\n",
            ">96, 169/234, d=0.694, g=0.691\n",
            ">96, 170/234, d=0.690, g=0.706\n",
            ">96, 171/234, d=0.688, g=0.708\n",
            ">96, 172/234, d=0.690, g=0.703\n",
            ">96, 173/234, d=0.690, g=0.692\n",
            ">96, 174/234, d=0.693, g=0.693\n",
            ">96, 175/234, d=0.687, g=0.709\n",
            ">96, 176/234, d=0.693, g=0.713\n",
            ">96, 177/234, d=0.689, g=0.711\n",
            ">96, 178/234, d=0.687, g=0.704\n",
            ">96, 179/234, d=0.688, g=0.700\n",
            ">96, 180/234, d=0.693, g=0.706\n",
            ">96, 181/234, d=0.697, g=0.710\n",
            ">96, 182/234, d=0.693, g=0.700\n",
            ">96, 183/234, d=0.687, g=0.673\n",
            ">96, 184/234, d=0.691, g=0.662\n",
            ">96, 185/234, d=0.695, g=0.681\n",
            ">96, 186/234, d=0.687, g=0.711\n",
            ">96, 187/234, d=0.689, g=0.731\n",
            ">96, 188/234, d=0.681, g=0.720\n",
            ">96, 189/234, d=0.692, g=0.708\n",
            ">96, 190/234, d=0.696, g=0.705\n",
            ">96, 191/234, d=0.688, g=0.708\n",
            ">96, 192/234, d=0.694, g=0.695\n",
            ">96, 193/234, d=0.692, g=0.681\n",
            ">96, 194/234, d=0.692, g=0.676\n",
            ">96, 195/234, d=0.689, g=0.692\n",
            ">96, 196/234, d=0.687, g=0.723\n",
            ">96, 197/234, d=0.692, g=0.710\n",
            ">96, 198/234, d=0.689, g=0.704\n",
            ">96, 199/234, d=0.692, g=0.693\n",
            ">96, 200/234, d=0.687, g=0.709\n",
            ">96, 201/234, d=0.699, g=0.706\n",
            ">96, 202/234, d=0.691, g=0.709\n",
            ">96, 203/234, d=0.691, g=0.706\n",
            ">96, 204/234, d=0.701, g=0.713\n",
            ">96, 205/234, d=0.688, g=0.715\n",
            ">96, 206/234, d=0.694, g=0.690\n",
            ">96, 207/234, d=0.688, g=0.695\n",
            ">96, 208/234, d=0.697, g=0.699\n",
            ">96, 209/234, d=0.699, g=0.719\n",
            ">96, 210/234, d=0.684, g=0.713\n",
            ">96, 211/234, d=0.686, g=0.701\n",
            ">96, 212/234, d=0.692, g=0.699\n",
            ">96, 213/234, d=0.692, g=0.694\n",
            ">96, 214/234, d=0.692, g=0.696\n",
            ">96, 215/234, d=0.686, g=0.693\n",
            ">96, 216/234, d=0.693, g=0.685\n",
            ">96, 217/234, d=0.685, g=0.704\n",
            ">96, 218/234, d=0.685, g=0.708\n",
            ">96, 219/234, d=0.690, g=0.691\n",
            ">96, 220/234, d=0.693, g=0.702\n",
            ">96, 221/234, d=0.690, g=0.685\n",
            ">96, 222/234, d=0.687, g=0.694\n",
            ">96, 223/234, d=0.689, g=0.722\n",
            ">96, 224/234, d=0.695, g=0.719\n",
            ">96, 225/234, d=0.690, g=0.692\n",
            ">96, 226/234, d=0.699, g=0.676\n",
            ">96, 227/234, d=0.697, g=0.680\n",
            ">96, 228/234, d=0.694, g=0.714\n",
            ">96, 229/234, d=0.693, g=0.704\n",
            ">96, 230/234, d=0.690, g=0.695\n",
            ">96, 231/234, d=0.682, g=0.692\n",
            ">96, 232/234, d=0.697, g=0.703\n",
            ">96, 233/234, d=0.685, g=0.722\n",
            ">96, 234/234, d=0.691, g=0.725\n",
            ">97, 1/234, d=0.690, g=0.710\n",
            ">97, 2/234, d=0.684, g=0.677\n",
            ">97, 3/234, d=0.700, g=0.681\n",
            ">97, 4/234, d=0.699, g=0.693\n",
            ">97, 5/234, d=0.687, g=0.693\n",
            ">97, 6/234, d=0.690, g=0.709\n",
            ">97, 7/234, d=0.693, g=0.719\n",
            ">97, 8/234, d=0.692, g=0.685\n",
            ">97, 9/234, d=0.688, g=0.677\n",
            ">97, 10/234, d=0.692, g=0.683\n",
            ">97, 11/234, d=0.689, g=0.695\n",
            ">97, 12/234, d=0.698, g=0.723\n",
            ">97, 13/234, d=0.692, g=0.731\n",
            ">97, 14/234, d=0.688, g=0.714\n",
            ">97, 15/234, d=0.685, g=0.692\n",
            ">97, 16/234, d=0.686, g=0.691\n",
            ">97, 17/234, d=0.688, g=0.689\n",
            ">97, 18/234, d=0.690, g=0.705\n",
            ">97, 19/234, d=0.688, g=0.691\n",
            ">97, 20/234, d=0.690, g=0.692\n",
            ">97, 21/234, d=0.689, g=0.685\n",
            ">97, 22/234, d=0.684, g=0.708\n",
            ">97, 23/234, d=0.688, g=0.716\n",
            ">97, 24/234, d=0.688, g=0.699\n",
            ">97, 25/234, d=0.686, g=0.696\n",
            ">97, 26/234, d=0.687, g=0.695\n",
            ">97, 27/234, d=0.690, g=0.709\n",
            ">97, 28/234, d=0.687, g=0.726\n",
            ">97, 29/234, d=0.696, g=0.694\n",
            ">97, 30/234, d=0.684, g=0.679\n",
            ">97, 31/234, d=0.689, g=0.691\n",
            ">97, 32/234, d=0.686, g=0.718\n",
            ">97, 33/234, d=0.692, g=0.712\n",
            ">97, 34/234, d=0.688, g=0.700\n",
            ">97, 35/234, d=0.690, g=0.693\n",
            ">97, 36/234, d=0.693, g=0.691\n",
            ">97, 37/234, d=0.687, g=0.710\n",
            ">97, 38/234, d=0.697, g=0.717\n",
            ">97, 39/234, d=0.694, g=0.702\n",
            ">97, 40/234, d=0.685, g=0.692\n",
            ">97, 41/234, d=0.700, g=0.685\n",
            ">97, 42/234, d=0.690, g=0.689\n",
            ">97, 43/234, d=0.692, g=0.713\n",
            ">97, 44/234, d=0.694, g=0.719\n",
            ">97, 45/234, d=0.694, g=0.701\n",
            ">97, 46/234, d=0.694, g=0.676\n",
            ">97, 47/234, d=0.699, g=0.677\n",
            ">97, 48/234, d=0.698, g=0.699\n",
            ">97, 49/234, d=0.690, g=0.729\n",
            ">97, 50/234, d=0.692, g=0.727\n",
            ">97, 51/234, d=0.696, g=0.712\n",
            ">97, 52/234, d=0.691, g=0.681\n",
            ">97, 53/234, d=0.694, g=0.684\n",
            ">97, 54/234, d=0.693, g=0.701\n",
            ">97, 55/234, d=0.696, g=0.710\n",
            ">97, 56/234, d=0.690, g=0.702\n",
            ">97, 57/234, d=0.692, g=0.687\n",
            ">97, 58/234, d=0.687, g=0.679\n",
            ">97, 59/234, d=0.692, g=0.699\n",
            ">97, 60/234, d=0.696, g=0.720\n",
            ">97, 61/234, d=0.692, g=0.705\n",
            ">97, 62/234, d=0.692, g=0.708\n",
            ">97, 63/234, d=0.690, g=0.706\n",
            ">97, 64/234, d=0.693, g=0.709\n",
            ">97, 65/234, d=0.694, g=0.722\n",
            ">97, 66/234, d=0.697, g=0.696\n",
            ">97, 67/234, d=0.689, g=0.689\n",
            ">97, 68/234, d=0.697, g=0.688\n",
            ">97, 69/234, d=0.701, g=0.690\n",
            ">97, 70/234, d=0.696, g=0.702\n",
            ">97, 71/234, d=0.694, g=0.702\n",
            ">97, 72/234, d=0.689, g=0.686\n",
            ">97, 73/234, d=0.691, g=0.688\n",
            ">97, 74/234, d=0.699, g=0.707\n",
            ">97, 75/234, d=0.693, g=0.749\n",
            ">97, 76/234, d=0.683, g=0.747\n",
            ">97, 77/234, d=0.689, g=0.698\n",
            ">97, 78/234, d=0.689, g=0.671\n",
            ">97, 79/234, d=0.691, g=0.684\n",
            ">97, 80/234, d=0.699, g=0.694\n",
            ">97, 81/234, d=0.694, g=0.710\n",
            ">97, 82/234, d=0.690, g=0.693\n",
            ">97, 83/234, d=0.701, g=0.703\n",
            ">97, 84/234, d=0.698, g=0.715\n",
            ">97, 85/234, d=0.692, g=0.698\n",
            ">97, 86/234, d=0.695, g=0.697\n",
            ">97, 87/234, d=0.690, g=0.697\n",
            ">97, 88/234, d=0.691, g=0.696\n",
            ">97, 89/234, d=0.689, g=0.703\n",
            ">97, 90/234, d=0.696, g=0.699\n",
            ">97, 91/234, d=0.694, g=0.704\n",
            ">97, 92/234, d=0.689, g=0.712\n",
            ">97, 93/234, d=0.696, g=0.702\n",
            ">97, 94/234, d=0.690, g=0.688\n",
            ">97, 95/234, d=0.695, g=0.685\n",
            ">97, 96/234, d=0.687, g=0.701\n",
            ">97, 97/234, d=0.694, g=0.696\n",
            ">97, 98/234, d=0.693, g=0.689\n",
            ">97, 99/234, d=0.692, g=0.685\n",
            ">97, 100/234, d=0.692, g=0.708\n",
            ">97, 101/234, d=0.691, g=0.725\n",
            ">97, 102/234, d=0.691, g=0.729\n",
            ">97, 103/234, d=0.696, g=0.726\n",
            ">97, 104/234, d=0.691, g=0.710\n",
            ">97, 105/234, d=0.687, g=0.678\n",
            ">97, 106/234, d=0.696, g=0.679\n",
            ">97, 107/234, d=0.685, g=0.698\n",
            ">97, 108/234, d=0.698, g=0.702\n",
            ">97, 109/234, d=0.692, g=0.700\n",
            ">97, 110/234, d=0.694, g=0.700\n",
            ">97, 111/234, d=0.690, g=0.712\n",
            ">97, 112/234, d=0.692, g=0.711\n",
            ">97, 113/234, d=0.689, g=0.703\n",
            ">97, 114/234, d=0.688, g=0.704\n",
            ">97, 115/234, d=0.687, g=0.696\n",
            ">97, 116/234, d=0.691, g=0.703\n",
            ">97, 117/234, d=0.696, g=0.696\n",
            ">97, 118/234, d=0.690, g=0.698\n",
            ">97, 119/234, d=0.688, g=0.686\n",
            ">97, 120/234, d=0.690, g=0.696\n",
            ">97, 121/234, d=0.685, g=0.691\n",
            ">97, 122/234, d=0.687, g=0.689\n",
            ">97, 123/234, d=0.698, g=0.694\n",
            ">97, 124/234, d=0.696, g=0.694\n",
            ">97, 125/234, d=0.688, g=0.697\n",
            ">97, 126/234, d=0.684, g=0.698\n",
            ">97, 127/234, d=0.687, g=0.712\n",
            ">97, 128/234, d=0.691, g=0.723\n",
            ">97, 129/234, d=0.693, g=0.700\n",
            ">97, 130/234, d=0.699, g=0.683\n",
            ">97, 131/234, d=0.693, g=0.677\n",
            ">97, 132/234, d=0.687, g=0.678\n",
            ">97, 133/234, d=0.693, g=0.721\n",
            ">97, 134/234, d=0.697, g=0.719\n",
            ">97, 135/234, d=0.685, g=0.708\n",
            ">97, 136/234, d=0.691, g=0.698\n",
            ">97, 137/234, d=0.690, g=0.709\n",
            ">97, 138/234, d=0.691, g=0.703\n",
            ">97, 139/234, d=0.686, g=0.707\n",
            ">97, 140/234, d=0.693, g=0.707\n",
            ">97, 141/234, d=0.696, g=0.695\n",
            ">97, 142/234, d=0.693, g=0.692\n",
            ">97, 143/234, d=0.695, g=0.687\n",
            ">97, 144/234, d=0.694, g=0.688\n",
            ">97, 145/234, d=0.695, g=0.693\n",
            ">97, 146/234, d=0.690, g=0.708\n",
            ">97, 147/234, d=0.687, g=0.713\n",
            ">97, 148/234, d=0.693, g=0.713\n",
            ">97, 149/234, d=0.702, g=0.708\n",
            ">97, 150/234, d=0.696, g=0.696\n",
            ">97, 151/234, d=0.690, g=0.690\n",
            ">97, 152/234, d=0.691, g=0.708\n",
            ">97, 153/234, d=0.691, g=0.697\n",
            ">97, 154/234, d=0.686, g=0.705\n",
            ">97, 155/234, d=0.690, g=0.708\n",
            ">97, 156/234, d=0.687, g=0.707\n",
            ">97, 157/234, d=0.687, g=0.690\n",
            ">97, 158/234, d=0.689, g=0.690\n",
            ">97, 159/234, d=0.697, g=0.689\n",
            ">97, 160/234, d=0.691, g=0.717\n",
            ">97, 161/234, d=0.693, g=0.701\n",
            ">97, 162/234, d=0.695, g=0.697\n",
            ">97, 163/234, d=0.692, g=0.702\n",
            ">97, 164/234, d=0.693, g=0.718\n",
            ">97, 165/234, d=0.694, g=0.717\n",
            ">97, 166/234, d=0.692, g=0.726\n",
            ">97, 167/234, d=0.696, g=0.684\n",
            ">97, 168/234, d=0.695, g=0.682\n",
            ">97, 169/234, d=0.690, g=0.689\n",
            ">97, 170/234, d=0.684, g=0.697\n",
            ">97, 171/234, d=0.692, g=0.698\n",
            ">97, 172/234, d=0.691, g=0.708\n",
            ">97, 173/234, d=0.689, g=0.692\n",
            ">97, 174/234, d=0.688, g=0.687\n",
            ">97, 175/234, d=0.696, g=0.696\n",
            ">97, 176/234, d=0.692, g=0.704\n",
            ">97, 177/234, d=0.692, g=0.692\n",
            ">97, 178/234, d=0.688, g=0.687\n",
            ">97, 179/234, d=0.693, g=0.711\n",
            ">97, 180/234, d=0.691, g=0.722\n",
            ">97, 181/234, d=0.691, g=0.709\n",
            ">97, 182/234, d=0.685, g=0.693\n",
            ">97, 183/234, d=0.694, g=0.685\n",
            ">97, 184/234, d=0.691, g=0.694\n",
            ">97, 185/234, d=0.695, g=0.724\n",
            ">97, 186/234, d=0.692, g=0.707\n",
            ">97, 187/234, d=0.689, g=0.700\n",
            ">97, 188/234, d=0.690, g=0.709\n",
            ">97, 189/234, d=0.687, g=0.712\n",
            ">97, 190/234, d=0.694, g=0.709\n",
            ">97, 191/234, d=0.688, g=0.698\n",
            ">97, 192/234, d=0.693, g=0.696\n",
            ">97, 193/234, d=0.687, g=0.684\n",
            ">97, 194/234, d=0.702, g=0.703\n",
            ">97, 195/234, d=0.697, g=0.716\n",
            ">97, 196/234, d=0.690, g=0.709\n",
            ">97, 197/234, d=0.689, g=0.696\n",
            ">97, 198/234, d=0.688, g=0.678\n",
            ">97, 199/234, d=0.692, g=0.691\n",
            ">97, 200/234, d=0.695, g=0.717\n",
            ">97, 201/234, d=0.696, g=0.712\n",
            ">97, 202/234, d=0.693, g=0.694\n",
            ">97, 203/234, d=0.694, g=0.686\n",
            ">97, 204/234, d=0.698, g=0.691\n",
            ">97, 205/234, d=0.687, g=0.700\n",
            ">97, 206/234, d=0.689, g=0.704\n",
            ">97, 207/234, d=0.688, g=0.699\n",
            ">97, 208/234, d=0.696, g=0.705\n",
            ">97, 209/234, d=0.689, g=0.695\n",
            ">97, 210/234, d=0.691, g=0.683\n",
            ">97, 211/234, d=0.691, g=0.709\n",
            ">97, 212/234, d=0.697, g=0.717\n",
            ">97, 213/234, d=0.686, g=0.743\n",
            ">97, 214/234, d=0.690, g=0.722\n",
            ">97, 215/234, d=0.697, g=0.694\n",
            ">97, 216/234, d=0.684, g=0.685\n",
            ">97, 217/234, d=0.694, g=0.682\n",
            ">97, 218/234, d=0.699, g=0.693\n",
            ">97, 219/234, d=0.690, g=0.713\n",
            ">97, 220/234, d=0.685, g=0.693\n",
            ">97, 221/234, d=0.691, g=0.703\n",
            ">97, 222/234, d=0.687, g=0.703\n",
            ">97, 223/234, d=0.696, g=0.696\n",
            ">97, 224/234, d=0.692, g=0.713\n",
            ">97, 225/234, d=0.692, g=0.707\n",
            ">97, 226/234, d=0.692, g=0.719\n",
            ">97, 227/234, d=0.689, g=0.712\n",
            ">97, 228/234, d=0.693, g=0.705\n",
            ">97, 229/234, d=0.698, g=0.691\n",
            ">97, 230/234, d=0.690, g=0.679\n",
            ">97, 231/234, d=0.694, g=0.691\n",
            ">97, 232/234, d=0.687, g=0.717\n",
            ">97, 233/234, d=0.691, g=0.729\n",
            ">97, 234/234, d=0.691, g=0.701\n",
            ">98, 1/234, d=0.696, g=0.678\n",
            ">98, 2/234, d=0.700, g=0.669\n",
            ">98, 3/234, d=0.691, g=0.692\n",
            ">98, 4/234, d=0.692, g=0.710\n",
            ">98, 5/234, d=0.691, g=0.713\n",
            ">98, 6/234, d=0.686, g=0.707\n",
            ">98, 7/234, d=0.690, g=0.702\n",
            ">98, 8/234, d=0.686, g=0.694\n",
            ">98, 9/234, d=0.688, g=0.696\n",
            ">98, 10/234, d=0.690, g=0.693\n",
            ">98, 11/234, d=0.697, g=0.700\n",
            ">98, 12/234, d=0.686, g=0.711\n",
            ">98, 13/234, d=0.697, g=0.710\n",
            ">98, 14/234, d=0.688, g=0.698\n",
            ">98, 15/234, d=0.696, g=0.708\n",
            ">98, 16/234, d=0.698, g=0.694\n",
            ">98, 17/234, d=0.694, g=0.701\n",
            ">98, 18/234, d=0.692, g=0.701\n",
            ">98, 19/234, d=0.685, g=0.716\n",
            ">98, 20/234, d=0.690, g=0.704\n",
            ">98, 21/234, d=0.691, g=0.705\n",
            ">98, 22/234, d=0.692, g=0.698\n",
            ">98, 23/234, d=0.689, g=0.684\n",
            ">98, 24/234, d=0.687, g=0.688\n",
            ">98, 25/234, d=0.694, g=0.703\n",
            ">98, 26/234, d=0.693, g=0.703\n",
            ">98, 27/234, d=0.702, g=0.701\n",
            ">98, 28/234, d=0.691, g=0.694\n",
            ">98, 29/234, d=0.688, g=0.687\n",
            ">98, 30/234, d=0.692, g=0.689\n",
            ">98, 31/234, d=0.685, g=0.694\n",
            ">98, 32/234, d=0.692, g=0.707\n",
            ">98, 33/234, d=0.688, g=0.707\n",
            ">98, 34/234, d=0.692, g=0.705\n",
            ">98, 35/234, d=0.696, g=0.700\n",
            ">98, 36/234, d=0.691, g=0.711\n",
            ">98, 37/234, d=0.691, g=0.708\n",
            ">98, 38/234, d=0.684, g=0.702\n",
            ">98, 39/234, d=0.690, g=0.687\n",
            ">98, 40/234, d=0.685, g=0.682\n",
            ">98, 41/234, d=0.691, g=0.691\n",
            ">98, 42/234, d=0.691, g=0.692\n",
            ">98, 43/234, d=0.692, g=0.708\n",
            ">98, 44/234, d=0.690, g=0.728\n",
            ">98, 45/234, d=0.693, g=0.711\n",
            ">98, 46/234, d=0.697, g=0.706\n",
            ">98, 47/234, d=0.698, g=0.702\n",
            ">98, 48/234, d=0.689, g=0.688\n",
            ">98, 49/234, d=0.696, g=0.669\n",
            ">98, 50/234, d=0.692, g=0.684\n",
            ">98, 51/234, d=0.692, g=0.698\n",
            ">98, 52/234, d=0.682, g=0.707\n",
            ">98, 53/234, d=0.686, g=0.707\n",
            ">98, 54/234, d=0.685, g=0.707\n",
            ">98, 55/234, d=0.701, g=0.697\n",
            ">98, 56/234, d=0.695, g=0.715\n",
            ">98, 57/234, d=0.689, g=0.717\n",
            ">98, 58/234, d=0.690, g=0.705\n",
            ">98, 59/234, d=0.693, g=0.685\n",
            ">98, 60/234, d=0.684, g=0.684\n",
            ">98, 61/234, d=0.690, g=0.690\n",
            ">98, 62/234, d=0.696, g=0.704\n",
            ">98, 63/234, d=0.692, g=0.733\n",
            ">98, 64/234, d=0.694, g=0.727\n",
            ">98, 65/234, d=0.693, g=0.704\n",
            ">98, 66/234, d=0.693, g=0.685\n",
            ">98, 67/234, d=0.689, g=0.666\n",
            ">98, 68/234, d=0.696, g=0.687\n",
            ">98, 69/234, d=0.691, g=0.751\n",
            ">98, 70/234, d=0.692, g=0.745\n",
            ">98, 71/234, d=0.693, g=0.707\n",
            ">98, 72/234, d=0.684, g=0.682\n",
            ">98, 73/234, d=0.691, g=0.684\n",
            ">98, 74/234, d=0.693, g=0.667\n",
            ">98, 75/234, d=0.690, g=0.696\n",
            ">98, 76/234, d=0.688, g=0.703\n",
            ">98, 77/234, d=0.695, g=0.708\n",
            ">98, 78/234, d=0.687, g=0.706\n",
            ">98, 79/234, d=0.690, g=0.697\n",
            ">98, 80/234, d=0.693, g=0.699\n",
            ">98, 81/234, d=0.690, g=0.720\n",
            ">98, 82/234, d=0.694, g=0.716\n",
            ">98, 83/234, d=0.695, g=0.692\n",
            ">98, 84/234, d=0.690, g=0.686\n",
            ">98, 85/234, d=0.691, g=0.686\n",
            ">98, 86/234, d=0.695, g=0.703\n",
            ">98, 87/234, d=0.697, g=0.705\n",
            ">98, 88/234, d=0.686, g=0.699\n",
            ">98, 89/234, d=0.680, g=0.695\n",
            ">98, 90/234, d=0.691, g=0.674\n",
            ">98, 91/234, d=0.681, g=0.700\n",
            ">98, 92/234, d=0.689, g=0.698\n",
            ">98, 93/234, d=0.695, g=0.698\n",
            ">98, 94/234, d=0.696, g=0.680\n",
            ">98, 95/234, d=0.682, g=0.682\n",
            ">98, 96/234, d=0.692, g=0.689\n",
            ">98, 97/234, d=0.698, g=0.712\n",
            ">98, 98/234, d=0.696, g=0.705\n",
            ">98, 99/234, d=0.695, g=0.697\n",
            ">98, 100/234, d=0.693, g=0.693\n",
            ">98, 101/234, d=0.689, g=0.695\n",
            ">98, 102/234, d=0.693, g=0.708\n",
            ">98, 103/234, d=0.696, g=0.697\n",
            ">98, 104/234, d=0.695, g=0.689\n",
            ">98, 105/234, d=0.688, g=0.691\n",
            ">98, 106/234, d=0.689, g=0.716\n",
            ">98, 107/234, d=0.692, g=0.704\n",
            ">98, 108/234, d=0.691, g=0.705\n",
            ">98, 109/234, d=0.688, g=0.693\n",
            ">98, 110/234, d=0.697, g=0.691\n",
            ">98, 111/234, d=0.688, g=0.696\n",
            ">98, 112/234, d=0.685, g=0.723\n",
            ">98, 113/234, d=0.693, g=0.718\n",
            ">98, 114/234, d=0.698, g=0.697\n",
            ">98, 115/234, d=0.688, g=0.695\n",
            ">98, 116/234, d=0.686, g=0.703\n",
            ">98, 117/234, d=0.685, g=0.711\n",
            ">98, 118/234, d=0.695, g=0.704\n",
            ">98, 119/234, d=0.692, g=0.679\n",
            ">98, 120/234, d=0.692, g=0.695\n",
            ">98, 121/234, d=0.697, g=0.691\n",
            ">98, 122/234, d=0.693, g=0.700\n",
            ">98, 123/234, d=0.691, g=0.712\n",
            ">98, 124/234, d=0.691, g=0.692\n",
            ">98, 125/234, d=0.694, g=0.691\n",
            ">98, 126/234, d=0.687, g=0.693\n",
            ">98, 127/234, d=0.698, g=0.702\n",
            ">98, 128/234, d=0.690, g=0.720\n",
            ">98, 129/234, d=0.699, g=0.715\n",
            ">98, 130/234, d=0.692, g=0.710\n",
            ">98, 131/234, d=0.691, g=0.688\n",
            ">98, 132/234, d=0.690, g=0.679\n",
            ">98, 133/234, d=0.695, g=0.686\n",
            ">98, 134/234, d=0.685, g=0.695\n",
            ">98, 135/234, d=0.690, g=0.706\n",
            ">98, 136/234, d=0.690, g=0.697\n",
            ">98, 137/234, d=0.685, g=0.701\n",
            ">98, 138/234, d=0.687, g=0.706\n",
            ">98, 139/234, d=0.690, g=0.713\n",
            ">98, 140/234, d=0.696, g=0.711\n",
            ">98, 141/234, d=0.690, g=0.712\n",
            ">98, 142/234, d=0.698, g=0.713\n",
            ">98, 143/234, d=0.685, g=0.721\n",
            ">98, 144/234, d=0.684, g=0.703\n",
            ">98, 145/234, d=0.691, g=0.683\n",
            ">98, 146/234, d=0.693, g=0.673\n",
            ">98, 147/234, d=0.696, g=0.678\n",
            ">98, 148/234, d=0.693, g=0.685\n",
            ">98, 149/234, d=0.695, g=0.695\n",
            ">98, 150/234, d=0.686, g=0.706\n",
            ">98, 151/234, d=0.692, g=0.725\n",
            ">98, 152/234, d=0.690, g=0.717\n",
            ">98, 153/234, d=0.691, g=0.699\n",
            ">98, 154/234, d=0.695, g=0.681\n",
            ">98, 155/234, d=0.689, g=0.697\n",
            ">98, 156/234, d=0.701, g=0.716\n",
            ">98, 157/234, d=0.693, g=0.712\n",
            ">98, 158/234, d=0.687, g=0.686\n",
            ">98, 159/234, d=0.679, g=0.676\n",
            ">98, 160/234, d=0.692, g=0.691\n",
            ">98, 161/234, d=0.694, g=0.695\n",
            ">98, 162/234, d=0.697, g=0.716\n",
            ">98, 163/234, d=0.692, g=0.709\n",
            ">98, 164/234, d=0.693, g=0.697\n",
            ">98, 165/234, d=0.687, g=0.690\n",
            ">98, 166/234, d=0.690, g=0.702\n",
            ">98, 167/234, d=0.696, g=0.691\n",
            ">98, 168/234, d=0.690, g=0.695\n",
            ">98, 169/234, d=0.691, g=0.696\n",
            ">98, 170/234, d=0.694, g=0.699\n",
            ">98, 171/234, d=0.683, g=0.702\n",
            ">98, 172/234, d=0.697, g=0.698\n",
            ">98, 173/234, d=0.692, g=0.702\n",
            ">98, 174/234, d=0.690, g=0.692\n",
            ">98, 175/234, d=0.694, g=0.692\n",
            ">98, 176/234, d=0.688, g=0.697\n",
            ">98, 177/234, d=0.687, g=0.708\n",
            ">98, 178/234, d=0.689, g=0.699\n",
            ">98, 179/234, d=0.689, g=0.692\n",
            ">98, 180/234, d=0.701, g=0.690\n",
            ">98, 181/234, d=0.690, g=0.694\n",
            ">98, 182/234, d=0.693, g=0.705\n",
            ">98, 183/234, d=0.696, g=0.716\n",
            ">98, 184/234, d=0.695, g=0.700\n",
            ">98, 185/234, d=0.692, g=0.683\n",
            ">98, 186/234, d=0.691, g=0.680\n",
            ">98, 187/234, d=0.691, g=0.685\n",
            ">98, 188/234, d=0.687, g=0.720\n",
            ">98, 189/234, d=0.691, g=0.718\n",
            ">98, 190/234, d=0.690, g=0.707\n",
            ">98, 191/234, d=0.689, g=0.684\n",
            ">98, 192/234, d=0.692, g=0.685\n",
            ">98, 193/234, d=0.696, g=0.690\n",
            ">98, 194/234, d=0.693, g=0.703\n",
            ">98, 195/234, d=0.696, g=0.712\n",
            ">98, 196/234, d=0.691, g=0.717\n",
            ">98, 197/234, d=0.687, g=0.711\n",
            ">98, 198/234, d=0.696, g=0.705\n",
            ">98, 199/234, d=0.688, g=0.678\n",
            ">98, 200/234, d=0.695, g=0.687\n",
            ">98, 201/234, d=0.692, g=0.705\n",
            ">98, 202/234, d=0.693, g=0.698\n",
            ">98, 203/234, d=0.696, g=0.694\n",
            ">98, 204/234, d=0.696, g=0.698\n",
            ">98, 205/234, d=0.690, g=0.688\n",
            ">98, 206/234, d=0.689, g=0.704\n",
            ">98, 207/234, d=0.689, g=0.715\n",
            ">98, 208/234, d=0.696, g=0.698\n",
            ">98, 209/234, d=0.683, g=0.693\n",
            ">98, 210/234, d=0.688, g=0.684\n",
            ">98, 211/234, d=0.686, g=0.683\n",
            ">98, 212/234, d=0.694, g=0.692\n",
            ">98, 213/234, d=0.693, g=0.703\n",
            ">98, 214/234, d=0.693, g=0.708\n",
            ">98, 215/234, d=0.693, g=0.692\n",
            ">98, 216/234, d=0.689, g=0.692\n",
            ">98, 217/234, d=0.690, g=0.699\n",
            ">98, 218/234, d=0.693, g=0.706\n",
            ">98, 219/234, d=0.686, g=0.700\n",
            ">98, 220/234, d=0.691, g=0.683\n",
            ">98, 221/234, d=0.694, g=0.687\n",
            ">98, 222/234, d=0.690, g=0.693\n",
            ">98, 223/234, d=0.688, g=0.703\n",
            ">98, 224/234, d=0.696, g=0.683\n",
            ">98, 225/234, d=0.690, g=0.681\n",
            ">98, 226/234, d=0.691, g=0.690\n",
            ">98, 227/234, d=0.687, g=0.715\n",
            ">98, 228/234, d=0.696, g=0.736\n",
            ">98, 229/234, d=0.685, g=0.719\n",
            ">98, 230/234, d=0.694, g=0.703\n",
            ">98, 231/234, d=0.692, g=0.683\n",
            ">98, 232/234, d=0.691, g=0.672\n",
            ">98, 233/234, d=0.689, g=0.689\n",
            ">98, 234/234, d=0.686, g=0.707\n",
            ">99, 1/234, d=0.694, g=0.734\n",
            ">99, 2/234, d=0.683, g=0.730\n",
            ">99, 3/234, d=0.690, g=0.691\n",
            ">99, 4/234, d=0.686, g=0.667\n",
            ">99, 5/234, d=0.691, g=0.680\n",
            ">99, 6/234, d=0.697, g=0.701\n",
            ">99, 7/234, d=0.683, g=0.746\n",
            ">99, 8/234, d=0.686, g=0.741\n",
            ">99, 9/234, d=0.692, g=0.713\n",
            ">99, 10/234, d=0.698, g=0.681\n",
            ">99, 11/234, d=0.695, g=0.662\n",
            ">99, 12/234, d=0.687, g=0.681\n",
            ">99, 13/234, d=0.691, g=0.718\n",
            ">99, 14/234, d=0.695, g=0.751\n",
            ">99, 15/234, d=0.688, g=0.728\n",
            ">99, 16/234, d=0.693, g=0.686\n",
            ">99, 17/234, d=0.694, g=0.679\n",
            ">99, 18/234, d=0.693, g=0.678\n",
            ">99, 19/234, d=0.688, g=0.696\n",
            ">99, 20/234, d=0.698, g=0.712\n",
            ">99, 21/234, d=0.689, g=0.700\n",
            ">99, 22/234, d=0.690, g=0.692\n",
            ">99, 23/234, d=0.691, g=0.688\n",
            ">99, 24/234, d=0.685, g=0.697\n",
            ">99, 25/234, d=0.688, g=0.711\n",
            ">99, 26/234, d=0.690, g=0.706\n",
            ">99, 27/234, d=0.694, g=0.704\n",
            ">99, 28/234, d=0.684, g=0.685\n",
            ">99, 29/234, d=0.689, g=0.688\n",
            ">99, 30/234, d=0.694, g=0.702\n",
            ">99, 31/234, d=0.690, g=0.711\n",
            ">99, 32/234, d=0.694, g=0.710\n",
            ">99, 33/234, d=0.686, g=0.705\n",
            ">99, 34/234, d=0.689, g=0.691\n",
            ">99, 35/234, d=0.694, g=0.693\n",
            ">99, 36/234, d=0.689, g=0.699\n",
            ">99, 37/234, d=0.696, g=0.697\n",
            ">99, 38/234, d=0.689, g=0.700\n",
            ">99, 39/234, d=0.682, g=0.707\n",
            ">99, 40/234, d=0.696, g=0.712\n",
            ">99, 41/234, d=0.693, g=0.708\n",
            ">99, 42/234, d=0.687, g=0.694\n",
            ">99, 43/234, d=0.685, g=0.689\n",
            ">99, 44/234, d=0.694, g=0.702\n",
            ">99, 45/234, d=0.702, g=0.709\n",
            ">99, 46/234, d=0.694, g=0.701\n",
            ">99, 47/234, d=0.694, g=0.689\n",
            ">99, 48/234, d=0.683, g=0.691\n",
            ">99, 49/234, d=0.688, g=0.709\n",
            ">99, 50/234, d=0.684, g=0.724\n",
            ">99, 51/234, d=0.699, g=0.703\n",
            ">99, 52/234, d=0.689, g=0.700\n",
            ">99, 53/234, d=0.699, g=0.702\n",
            ">99, 54/234, d=0.685, g=0.705\n",
            ">99, 55/234, d=0.692, g=0.702\n",
            ">99, 56/234, d=0.692, g=0.684\n",
            ">99, 57/234, d=0.687, g=0.685\n",
            ">99, 58/234, d=0.695, g=0.694\n",
            ">99, 59/234, d=0.689, g=0.706\n",
            ">99, 60/234, d=0.690, g=0.713\n",
            ">99, 61/234, d=0.696, g=0.703\n",
            ">99, 62/234, d=0.698, g=0.709\n",
            ">99, 63/234, d=0.698, g=0.703\n",
            ">99, 64/234, d=0.694, g=0.697\n",
            ">99, 65/234, d=0.687, g=0.688\n",
            ">99, 66/234, d=0.689, g=0.687\n",
            ">99, 67/234, d=0.697, g=0.694\n",
            ">99, 68/234, d=0.687, g=0.720\n",
            ">99, 69/234, d=0.692, g=0.723\n",
            ">99, 70/234, d=0.694, g=0.714\n",
            ">99, 71/234, d=0.686, g=0.692\n",
            ">99, 72/234, d=0.694, g=0.691\n",
            ">99, 73/234, d=0.686, g=0.714\n",
            ">99, 74/234, d=0.689, g=0.718\n",
            ">99, 75/234, d=0.694, g=0.707\n",
            ">99, 76/234, d=0.695, g=0.675\n",
            ">99, 77/234, d=0.697, g=0.667\n",
            ">99, 78/234, d=0.693, g=0.683\n",
            ">99, 79/234, d=0.683, g=0.700\n",
            ">99, 80/234, d=0.690, g=0.727\n",
            ">99, 81/234, d=0.689, g=0.721\n",
            ">99, 82/234, d=0.695, g=0.712\n",
            ">99, 83/234, d=0.695, g=0.694\n",
            ">99, 84/234, d=0.685, g=0.682\n",
            ">99, 85/234, d=0.695, g=0.685\n",
            ">99, 86/234, d=0.688, g=0.681\n",
            ">99, 87/234, d=0.691, g=0.693\n",
            ">99, 88/234, d=0.685, g=0.702\n",
            ">99, 89/234, d=0.699, g=0.698\n",
            ">99, 90/234, d=0.690, g=0.702\n",
            ">99, 91/234, d=0.696, g=0.708\n",
            ">99, 92/234, d=0.686, g=0.707\n",
            ">99, 93/234, d=0.698, g=0.694\n",
            ">99, 94/234, d=0.689, g=0.694\n",
            ">99, 95/234, d=0.688, g=0.692\n",
            ">99, 96/234, d=0.687, g=0.688\n",
            ">99, 97/234, d=0.686, g=0.690\n",
            ">99, 98/234, d=0.688, g=0.707\n",
            ">99, 99/234, d=0.691, g=0.717\n",
            ">99, 100/234, d=0.695, g=0.722\n",
            ">99, 101/234, d=0.689, g=0.714\n",
            ">99, 102/234, d=0.690, g=0.691\n",
            ">99, 103/234, d=0.695, g=0.673\n",
            ">99, 104/234, d=0.683, g=0.665\n",
            ">99, 105/234, d=0.698, g=0.695\n",
            ">99, 106/234, d=0.697, g=0.709\n",
            ">99, 107/234, d=0.693, g=0.712\n",
            ">99, 108/234, d=0.700, g=0.728\n",
            ">99, 109/234, d=0.693, g=0.705\n",
            ">99, 110/234, d=0.693, g=0.703\n",
            ">99, 111/234, d=0.686, g=0.693\n",
            ">99, 112/234, d=0.691, g=0.691\n",
            ">99, 113/234, d=0.699, g=0.696\n",
            ">99, 114/234, d=0.697, g=0.729\n",
            ">99, 115/234, d=0.697, g=0.718\n",
            ">99, 116/234, d=0.698, g=0.718\n",
            ">99, 117/234, d=0.693, g=0.708\n",
            ">99, 118/234, d=0.693, g=0.674\n",
            ">99, 119/234, d=0.693, g=0.676\n",
            ">99, 120/234, d=0.689, g=0.698\n",
            ">99, 121/234, d=0.684, g=0.705\n",
            ">99, 122/234, d=0.685, g=0.710\n",
            ">99, 123/234, d=0.690, g=0.703\n",
            ">99, 124/234, d=0.686, g=0.688\n",
            ">99, 125/234, d=0.697, g=0.694\n",
            ">99, 126/234, d=0.692, g=0.702\n",
            ">99, 127/234, d=0.694, g=0.703\n",
            ">99, 128/234, d=0.689, g=0.707\n",
            ">99, 129/234, d=0.696, g=0.695\n",
            ">99, 130/234, d=0.690, g=0.707\n",
            ">99, 131/234, d=0.691, g=0.704\n",
            ">99, 132/234, d=0.697, g=0.714\n",
            ">99, 133/234, d=0.689, g=0.712\n",
            ">99, 134/234, d=0.688, g=0.686\n",
            ">99, 135/234, d=0.688, g=0.684\n",
            ">99, 136/234, d=0.692, g=0.691\n",
            ">99, 137/234, d=0.693, g=0.717\n",
            ">99, 138/234, d=0.688, g=0.718\n",
            ">99, 139/234, d=0.693, g=0.705\n",
            ">99, 140/234, d=0.694, g=0.682\n",
            ">99, 141/234, d=0.688, g=0.694\n",
            ">99, 142/234, d=0.693, g=0.691\n",
            ">99, 143/234, d=0.691, g=0.695\n",
            ">99, 144/234, d=0.693, g=0.716\n",
            ">99, 145/234, d=0.687, g=0.711\n",
            ">99, 146/234, d=0.690, g=0.702\n",
            ">99, 147/234, d=0.691, g=0.697\n",
            ">99, 148/234, d=0.691, g=0.696\n",
            ">99, 149/234, d=0.694, g=0.697\n",
            ">99, 150/234, d=0.685, g=0.711\n",
            ">99, 151/234, d=0.692, g=0.703\n",
            ">99, 152/234, d=0.692, g=0.681\n",
            ">99, 153/234, d=0.691, g=0.680\n",
            ">99, 154/234, d=0.686, g=0.693\n",
            ">99, 155/234, d=0.689, g=0.716\n",
            ">99, 156/234, d=0.688, g=0.722\n",
            ">99, 157/234, d=0.677, g=0.732\n",
            ">99, 158/234, d=0.695, g=0.694\n",
            ">99, 159/234, d=0.693, g=0.673\n",
            ">99, 160/234, d=0.696, g=0.688\n",
            ">99, 161/234, d=0.692, g=0.710\n",
            ">99, 162/234, d=0.689, g=0.705\n",
            ">99, 163/234, d=0.695, g=0.694\n",
            ">99, 164/234, d=0.696, g=0.683\n",
            ">99, 165/234, d=0.686, g=0.697\n",
            ">99, 166/234, d=0.690, g=0.726\n",
            ">99, 167/234, d=0.693, g=0.736\n",
            ">99, 168/234, d=0.696, g=0.716\n",
            ">99, 169/234, d=0.690, g=0.686\n",
            ">99, 170/234, d=0.689, g=0.671\n",
            ">99, 171/234, d=0.686, g=0.684\n",
            ">99, 172/234, d=0.688, g=0.704\n",
            ">99, 173/234, d=0.690, g=0.707\n",
            ">99, 174/234, d=0.693, g=0.704\n",
            ">99, 175/234, d=0.694, g=0.700\n",
            ">99, 176/234, d=0.686, g=0.707\n",
            ">99, 177/234, d=0.691, g=0.716\n",
            ">99, 178/234, d=0.683, g=0.722\n",
            ">99, 179/234, d=0.695, g=0.702\n",
            ">99, 180/234, d=0.687, g=0.692\n",
            ">99, 181/234, d=0.690, g=0.696\n",
            ">99, 182/234, d=0.690, g=0.699\n",
            ">99, 183/234, d=0.685, g=0.700\n",
            ">99, 184/234, d=0.699, g=0.696\n",
            ">99, 185/234, d=0.688, g=0.694\n",
            ">99, 186/234, d=0.686, g=0.700\n",
            ">99, 187/234, d=0.689, g=0.705\n",
            ">99, 188/234, d=0.693, g=0.707\n",
            ">99, 189/234, d=0.693, g=0.687\n",
            ">99, 190/234, d=0.694, g=0.698\n",
            ">99, 191/234, d=0.690, g=0.694\n",
            ">99, 192/234, d=0.691, g=0.695\n",
            ">99, 193/234, d=0.696, g=0.695\n",
            ">99, 194/234, d=0.693, g=0.694\n",
            ">99, 195/234, d=0.691, g=0.707\n",
            ">99, 196/234, d=0.696, g=0.682\n",
            ">99, 197/234, d=0.692, g=0.689\n",
            ">99, 198/234, d=0.687, g=0.704\n",
            ">99, 199/234, d=0.693, g=0.714\n",
            ">99, 200/234, d=0.699, g=0.721\n",
            ">99, 201/234, d=0.689, g=0.700\n",
            ">99, 202/234, d=0.692, g=0.686\n",
            ">99, 203/234, d=0.686, g=0.674\n",
            ">99, 204/234, d=0.695, g=0.691\n",
            ">99, 205/234, d=0.687, g=0.718\n",
            ">99, 206/234, d=0.690, g=0.736\n",
            ">99, 207/234, d=0.696, g=0.719\n",
            ">99, 208/234, d=0.694, g=0.687\n",
            ">99, 209/234, d=0.688, g=0.672\n",
            ">99, 210/234, d=0.688, g=0.680\n",
            ">99, 211/234, d=0.696, g=0.695\n",
            ">99, 212/234, d=0.686, g=0.705\n",
            ">99, 213/234, d=0.692, g=0.715\n",
            ">99, 214/234, d=0.686, g=0.714\n",
            ">99, 215/234, d=0.695, g=0.690\n",
            ">99, 216/234, d=0.690, g=0.693\n",
            ">99, 217/234, d=0.694, g=0.691\n",
            ">99, 218/234, d=0.694, g=0.701\n",
            ">99, 219/234, d=0.696, g=0.707\n",
            ">99, 220/234, d=0.686, g=0.699\n",
            ">99, 221/234, d=0.691, g=0.709\n",
            ">99, 222/234, d=0.694, g=0.718\n",
            ">99, 223/234, d=0.698, g=0.709\n",
            ">99, 224/234, d=0.693, g=0.693\n",
            ">99, 225/234, d=0.687, g=0.694\n",
            ">99, 226/234, d=0.697, g=0.700\n",
            ">99, 227/234, d=0.692, g=0.704\n",
            ">99, 228/234, d=0.693, g=0.721\n",
            ">99, 229/234, d=0.693, g=0.707\n",
            ">99, 230/234, d=0.695, g=0.707\n",
            ">99, 231/234, d=0.697, g=0.712\n",
            ">99, 232/234, d=0.694, g=0.716\n",
            ">99, 233/234, d=0.689, g=0.696\n",
            ">99, 234/234, d=0.693, g=0.683\n",
            ">100, 1/234, d=0.691, g=0.690\n",
            ">100, 2/234, d=0.694, g=0.696\n",
            ">100, 3/234, d=0.697, g=0.712\n",
            ">100, 4/234, d=0.696, g=0.707\n",
            ">100, 5/234, d=0.685, g=0.706\n",
            ">100, 6/234, d=0.689, g=0.693\n",
            ">100, 7/234, d=0.687, g=0.676\n",
            ">100, 8/234, d=0.693, g=0.678\n",
            ">100, 9/234, d=0.691, g=0.704\n",
            ">100, 10/234, d=0.689, g=0.706\n",
            ">100, 11/234, d=0.697, g=0.707\n",
            ">100, 12/234, d=0.698, g=0.691\n",
            ">100, 13/234, d=0.696, g=0.674\n",
            ">100, 14/234, d=0.695, g=0.705\n",
            ">100, 15/234, d=0.690, g=0.701\n",
            ">100, 16/234, d=0.685, g=0.698\n",
            ">100, 17/234, d=0.699, g=0.700\n",
            ">100, 18/234, d=0.689, g=0.699\n",
            ">100, 19/234, d=0.691, g=0.690\n",
            ">100, 20/234, d=0.689, g=0.710\n",
            ">100, 21/234, d=0.688, g=0.708\n",
            ">100, 22/234, d=0.700, g=0.710\n",
            ">100, 23/234, d=0.690, g=0.711\n",
            ">100, 24/234, d=0.688, g=0.699\n",
            ">100, 25/234, d=0.689, g=0.700\n",
            ">100, 26/234, d=0.692, g=0.691\n",
            ">100, 27/234, d=0.699, g=0.687\n",
            ">100, 28/234, d=0.695, g=0.711\n",
            ">100, 29/234, d=0.686, g=0.711\n",
            ">100, 30/234, d=0.696, g=0.695\n",
            ">100, 31/234, d=0.693, g=0.696\n",
            ">100, 32/234, d=0.688, g=0.710\n",
            ">100, 33/234, d=0.692, g=0.725\n",
            ">100, 34/234, d=0.693, g=0.708\n",
            ">100, 35/234, d=0.690, g=0.674\n",
            ">100, 36/234, d=0.686, g=0.663\n",
            ">100, 37/234, d=0.691, g=0.694\n",
            ">100, 38/234, d=0.681, g=0.713\n",
            ">100, 39/234, d=0.685, g=0.728\n",
            ">100, 40/234, d=0.691, g=0.711\n",
            ">100, 41/234, d=0.696, g=0.701\n",
            ">100, 42/234, d=0.688, g=0.701\n",
            ">100, 43/234, d=0.697, g=0.683\n",
            ">100, 44/234, d=0.690, g=0.686\n",
            ">100, 45/234, d=0.694, g=0.702\n",
            ">100, 46/234, d=0.699, g=0.694\n",
            ">100, 47/234, d=0.697, g=0.698\n",
            ">100, 48/234, d=0.693, g=0.694\n",
            ">100, 49/234, d=0.691, g=0.698\n",
            ">100, 50/234, d=0.683, g=0.705\n",
            ">Accuracy real: 12%, fake: 98%\n",
            ">100, 51/234, d=0.681, g=0.708\n",
            ">100, 52/234, d=0.690, g=0.716\n",
            ">100, 53/234, d=0.686, g=0.708\n",
            ">100, 54/234, d=0.694, g=0.689\n",
            ">100, 55/234, d=0.694, g=0.680\n",
            ">100, 56/234, d=0.687, g=0.693\n",
            ">100, 57/234, d=0.688, g=0.694\n",
            ">100, 58/234, d=0.696, g=0.721\n",
            ">100, 59/234, d=0.690, g=0.711\n",
            ">100, 60/234, d=0.697, g=0.705\n",
            ">100, 61/234, d=0.692, g=0.704\n",
            ">100, 62/234, d=0.690, g=0.715\n",
            ">100, 63/234, d=0.697, g=0.719\n",
            ">100, 64/234, d=0.693, g=0.718\n",
            ">100, 65/234, d=0.691, g=0.697\n",
            ">100, 66/234, d=0.688, g=0.690\n",
            ">100, 67/234, d=0.686, g=0.688\n",
            ">100, 68/234, d=0.691, g=0.682\n",
            ">100, 69/234, d=0.691, g=0.688\n",
            ">100, 70/234, d=0.690, g=0.704\n",
            ">100, 71/234, d=0.700, g=0.709\n",
            ">100, 72/234, d=0.701, g=0.710\n",
            ">100, 73/234, d=0.687, g=0.711\n",
            ">100, 74/234, d=0.695, g=0.710\n",
            ">100, 75/234, d=0.694, g=0.689\n",
            ">100, 76/234, d=0.693, g=0.680\n",
            ">100, 77/234, d=0.691, g=0.695\n",
            ">100, 78/234, d=0.693, g=0.721\n",
            ">100, 79/234, d=0.693, g=0.725\n",
            ">100, 80/234, d=0.696, g=0.705\n",
            ">100, 81/234, d=0.687, g=0.676\n",
            ">100, 82/234, d=0.687, g=0.682\n",
            ">100, 83/234, d=0.693, g=0.695\n",
            ">100, 84/234, d=0.692, g=0.729\n",
            ">100, 85/234, d=0.688, g=0.732\n",
            ">100, 86/234, d=0.683, g=0.721\n",
            ">100, 87/234, d=0.703, g=0.689\n",
            ">100, 88/234, d=0.700, g=0.675\n",
            ">100, 89/234, d=0.692, g=0.685\n",
            ">100, 90/234, d=0.689, g=0.697\n",
            ">100, 91/234, d=0.689, g=0.707\n",
            ">100, 92/234, d=0.700, g=0.707\n",
            ">100, 93/234, d=0.689, g=0.707\n",
            ">100, 94/234, d=0.691, g=0.699\n",
            ">100, 95/234, d=0.696, g=0.698\n",
            ">100, 96/234, d=0.690, g=0.701\n",
            ">100, 97/234, d=0.697, g=0.702\n",
            ">100, 98/234, d=0.695, g=0.700\n",
            ">100, 99/234, d=0.688, g=0.692\n",
            ">100, 100/234, d=0.686, g=0.711\n",
            ">Accuracy real: 10%, fake: 100%\n",
            ">100, 101/234, d=0.685, g=0.697\n",
            ">100, 102/234, d=0.691, g=0.690\n",
            ">100, 103/234, d=0.694, g=0.690\n",
            ">100, 104/234, d=0.688, g=0.701\n",
            ">100, 105/234, d=0.695, g=0.714\n",
            ">100, 106/234, d=0.685, g=0.707\n",
            ">100, 107/234, d=0.687, g=0.693\n",
            ">100, 108/234, d=0.693, g=0.691\n",
            ">100, 109/234, d=0.691, g=0.684\n",
            ">100, 110/234, d=0.692, g=0.694\n",
            ">100, 111/234, d=0.688, g=0.701\n",
            ">100, 112/234, d=0.693, g=0.711\n",
            ">100, 113/234, d=0.688, g=0.699\n",
            ">100, 114/234, d=0.691, g=0.693\n",
            ">100, 115/234, d=0.692, g=0.693\n",
            ">100, 116/234, d=0.692, g=0.699\n",
            ">100, 117/234, d=0.689, g=0.710\n",
            ">100, 118/234, d=0.695, g=0.720\n",
            ">100, 119/234, d=0.688, g=0.712\n",
            ">100, 120/234, d=0.690, g=0.701\n",
            ">100, 121/234, d=0.688, g=0.695\n",
            ">100, 122/234, d=0.693, g=0.688\n",
            ">100, 123/234, d=0.693, g=0.700\n",
            ">100, 124/234, d=0.688, g=0.709\n",
            ">100, 125/234, d=0.693, g=0.716\n",
            ">100, 126/234, d=0.695, g=0.702\n",
            ">100, 127/234, d=0.691, g=0.678\n",
            ">100, 128/234, d=0.693, g=0.694\n",
            ">100, 129/234, d=0.697, g=0.699\n",
            ">100, 130/234, d=0.692, g=0.697\n",
            ">100, 131/234, d=0.689, g=0.698\n",
            ">100, 132/234, d=0.687, g=0.708\n",
            ">100, 133/234, d=0.694, g=0.713\n",
            ">100, 134/234, d=0.697, g=0.716\n",
            ">100, 135/234, d=0.692, g=0.703\n",
            ">100, 136/234, d=0.690, g=0.693\n",
            ">100, 137/234, d=0.693, g=0.694\n",
            ">100, 138/234, d=0.688, g=0.684\n",
            ">100, 139/234, d=0.693, g=0.681\n",
            ">100, 140/234, d=0.688, g=0.702\n",
            ">100, 141/234, d=0.688, g=0.713\n",
            ">100, 142/234, d=0.693, g=0.718\n",
            ">100, 143/234, d=0.686, g=0.706\n",
            ">100, 144/234, d=0.695, g=0.680\n",
            ">100, 145/234, d=0.691, g=0.690\n",
            ">100, 146/234, d=0.685, g=0.691\n",
            ">100, 147/234, d=0.686, g=0.701\n",
            ">100, 148/234, d=0.687, g=0.708\n",
            ">100, 149/234, d=0.690, g=0.707\n",
            ">100, 150/234, d=0.695, g=0.695\n",
            ">Accuracy real: 13%, fake: 90%\n",
            ">100, 151/234, d=0.689, g=0.707\n",
            ">100, 152/234, d=0.695, g=0.704\n",
            ">100, 153/234, d=0.696, g=0.706\n",
            ">100, 154/234, d=0.691, g=0.692\n",
            ">100, 155/234, d=0.694, g=0.689\n",
            ">100, 156/234, d=0.693, g=0.701\n",
            ">100, 157/234, d=0.696, g=0.711\n",
            ">100, 158/234, d=0.694, g=0.712\n",
            ">100, 159/234, d=0.698, g=0.703\n",
            ">100, 160/234, d=0.694, g=0.697\n",
            ">100, 161/234, d=0.689, g=0.694\n",
            ">100, 162/234, d=0.696, g=0.703\n",
            ">100, 163/234, d=0.685, g=0.704\n",
            ">100, 164/234, d=0.687, g=0.703\n",
            ">100, 165/234, d=0.695, g=0.698\n",
            ">100, 166/234, d=0.693, g=0.681\n",
            ">100, 167/234, d=0.691, g=0.684\n",
            ">100, 168/234, d=0.697, g=0.696\n",
            ">100, 169/234, d=0.691, g=0.706\n",
            ">100, 170/234, d=0.695, g=0.705\n",
            ">100, 171/234, d=0.688, g=0.715\n",
            ">100, 172/234, d=0.696, g=0.712\n",
            ">100, 173/234, d=0.693, g=0.696\n",
            ">100, 174/234, d=0.691, g=0.698\n",
            ">100, 175/234, d=0.690, g=0.711\n",
            ">100, 176/234, d=0.697, g=0.714\n",
            ">100, 177/234, d=0.694, g=0.698\n",
            ">100, 178/234, d=0.688, g=0.700\n",
            ">100, 179/234, d=0.686, g=0.689\n",
            ">100, 180/234, d=0.694, g=0.690\n",
            ">100, 181/234, d=0.697, g=0.697\n",
            ">100, 182/234, d=0.688, g=0.695\n",
            ">100, 183/234, d=0.698, g=0.694\n",
            ">100, 184/234, d=0.685, g=0.678\n",
            ">100, 185/234, d=0.696, g=0.688\n",
            ">100, 186/234, d=0.700, g=0.707\n",
            ">100, 187/234, d=0.688, g=0.737\n",
            ">100, 188/234, d=0.696, g=0.728\n",
            ">100, 189/234, d=0.697, g=0.706\n",
            ">100, 190/234, d=0.693, g=0.696\n",
            ">100, 191/234, d=0.690, g=0.692\n",
            ">100, 192/234, d=0.688, g=0.689\n",
            ">100, 193/234, d=0.691, g=0.688\n",
            ">100, 194/234, d=0.690, g=0.697\n",
            ">100, 195/234, d=0.692, g=0.692\n",
            ">100, 196/234, d=0.691, g=0.700\n",
            ">100, 197/234, d=0.694, g=0.720\n",
            ">100, 198/234, d=0.690, g=0.719\n",
            ">100, 199/234, d=0.688, g=0.708\n",
            ">100, 200/234, d=0.690, g=0.698\n",
            ">Accuracy real: 29%, fake: 86%\n",
            ">100, 201/234, d=0.690, g=0.675\n",
            ">100, 202/234, d=0.691, g=0.671\n",
            ">100, 203/234, d=0.691, g=0.686\n",
            ">100, 204/234, d=0.690, g=0.692\n",
            ">100, 205/234, d=0.693, g=0.712\n",
            ">100, 206/234, d=0.692, g=0.725\n",
            ">100, 207/234, d=0.685, g=0.716\n",
            ">100, 208/234, d=0.689, g=0.698\n",
            ">100, 209/234, d=0.691, g=0.691\n",
            ">100, 210/234, d=0.690, g=0.692\n",
            ">100, 211/234, d=0.688, g=0.699\n",
            ">100, 212/234, d=0.688, g=0.708\n",
            ">100, 213/234, d=0.689, g=0.698\n",
            ">100, 214/234, d=0.685, g=0.693\n",
            ">100, 215/234, d=0.696, g=0.693\n",
            ">100, 216/234, d=0.689, g=0.701\n",
            ">100, 217/234, d=0.696, g=0.702\n",
            ">100, 218/234, d=0.693, g=0.704\n",
            ">100, 219/234, d=0.685, g=0.706\n",
            ">100, 220/234, d=0.690, g=0.694\n",
            ">100, 221/234, d=0.695, g=0.708\n",
            ">100, 222/234, d=0.702, g=0.701\n",
            ">100, 223/234, d=0.696, g=0.696\n",
            ">100, 224/234, d=0.699, g=0.713\n",
            ">100, 225/234, d=0.694, g=0.719\n",
            ">100, 226/234, d=0.692, g=0.711\n",
            ">100, 227/234, d=0.694, g=0.679\n",
            ">100, 228/234, d=0.692, g=0.672\n",
            ">100, 229/234, d=0.694, g=0.688\n",
            ">100, 230/234, d=0.696, g=0.703\n",
            ">100, 231/234, d=0.687, g=0.707\n",
            ">100, 232/234, d=0.697, g=0.715\n",
            ">100, 233/234, d=0.694, g=0.691\n",
            ">100, 234/234, d=0.691, g=0.691\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 100 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wy0Ya8qJuOPN",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 436
        },
        "outputId": "27ad5207-a1d6-46e8-9dcb-30b81b968c44"
      },
      "source": [
        "img = plt.imread('/content/generated_plot_e010.png')\n",
        "plt.figure(figsize=(10,10))\n",
        "plt.title(\"After epoch 10\")\n",
        "plt.imshow(img)\n",
        "plt.axis('off')"
      ],
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(-0.5, 431.5, 287.5, -0.5)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 26
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "m8ex3-ATCGgn",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 436
        },
        "outputId": "e06ebfea-1d5b-4969-c49b-8319f304050a"
      },
      "source": [
        "img = plt.imread('/content/generated_plot_e100.png')\n",
        "plt.figure(figsize=(10,10))\n",
        "plt.title(\"After epoch 100\")\n",
        "plt.imshow(img)\n",
        "plt.axis('off')"
      ],
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(-0.5, 431.5, 287.5, -0.5)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 27
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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cweVykZOTg16vx+12Ew6HsdvtKTEUu1QsFmNmZobu7m58Ph8mk0m9Bgg/PZHwJJmS7Ljdbo4cOcKFCxeYn5+nrq6Oj370o2RkZGh+IVbiBNR6kkQiQWFhIRaLJSVPtkAgQEtLCy0tLTQ1NXHvvffy8MMPY7Va8fl8TE9PMzw8THp6OgaDQfNjHI1GmZ6e5tVXX6Wzs5NIJEJ+fj6PPfYYTz31FNnZ2RiNRsxms6Zxvp9EIoHf7+fixYtUVVVRX1+fUkNtJpOJxsZG9uzZg8ViIZFIMDk5SXp6OhaLJSVubspwxYEDB2hrayMnJ4fnnnuO4uJisrKy1N6/f/u3f+Ott95icnJS87Z7O9FolLGxMa5evUp2djYWiyUleiKVwuS5uTmuXr3KqVOnOHjwIM899xyFhYUYDAZOnTpFSUkJa9euTYk2sVQ0GmV4eJiRkRG1lzc/P1/rsJat1Lk6/YKYn5+ntbWVgwcP8vrrrzM+Po7VasXpdJKbm5tST26JRILvfe97nDp1irm5Ofbu3csnPvEJMjMzU+rpDUCv15OXl8czzzzDfffdx5o1azAajSQSCc6fP8+BAwc4ffo0v/Ebv4HNZtP8pjE/P8+xY8c4evQoO3bsUHujNm3ahNFoTMmk8lbxeJyFhQUGBwfZvn07tbW1Woek0ul0pKenU1tbSyKRYHZ2loGBAd555x2Gh4cpLS2ltLRU0xhjsRj9/f18+ctfZm5ujpqaGj7/+c+zZs0addaQLMu43W6mpqbw+/3Y7XZWr16dEsnEUnNzc4yPjzM5OcnatWtTpoZHlmWGhoZ44YUXuHLlCoFAgCeeeIK9e/dSWFjIwsICY2NjeDweNclMJco5FolE1OtZKhzX5UokPEmSSCQYGRnhlVde4fTp03R1dWGz2SguLiYYDHLt2jU+//nPs27dOp588knWrFlDZmampjFLkkRtbS3d3d0MDQ1x8OBBrly5Qk1NDQ0NDezatQu73Z4SN+f09HSamppYt24dTqcTg8FAPB7n8uXLfPOb32RwcJDi4mJ2796teZewLMvMzMxw4MABcnNzefTRR9m5cydlZWVqspMKx/QnSSQSeL1eysrKKCsrw+l0ah0ScCOuUCiEz+djdnaWs2fPcu7cObq7uxkfHycUCtHV1UVtbS2rV6/WJMFUphp/97vfZWhoiLq6Ou6++25KS0uRZZnFxUWCwSDz8/McPnyYlpYWZFmmoaGBtWvXpsRNLxaLEQwGmZubo7u7m4GBAYLBoDp0qPVDhVLX53K5qKioYPXq1VRXV1NUVERubq56jfD7/ZpPYriTSCTCwMCA2ps6PDzM6dOnKSgoUJcBET44kfAkQTwex+fzcfDgQd5++218Ph+rV69m69ateDwepqencblcuN1ujh07RkNDA7m5uSmR8FRXV7N79251dkgkEmF2dpYrV66QkZHBjh07NI1RodfryczMJCMjA71eTzQaxeVy8fbbb9Pb20t2djbbt29Xu7G1vrgpM/dKSkooKyvDbrerM3HS09NTZq2g96MUBqenp6tLLGhJ6R2dnJxkcHCQvr4+hoaGuHjxIn19fbhcLnWyQH9/P93d3Wzbto28vDxN4o3FYoyMjKjJ2cTEBGfPngVgZmYGt9vN9PQ0Fy5cYGpqitWrV1NfX58SU9KVIdnLly/T3t5OIBBgaGhInebt8XjUnlQtb8o6nY68vDx10c7CwkJ1wUnlHIxGowSDQeLxuGZx3olS/6nT6YhGo8zNzdHb20sgEMBut4uE56ckEp4kiEajzM/P8z//8z90dnayceNGPvzhD/PhD38Yt9vN2NgYfX19tLS08OqrrzIwMKDOhNKKckEtLS0lNzeXe+65B4PBwNTUFP/zP/+jXpx37NiREjMGJElSn3oTiQQLCwt0dnZy8OBBZFlm/fr13HfffSmzvpHFYqG6uprJyUmCwSBDQ0MsLCxQWFhIbm4uDocDq9WackOHSylPnQaDISXqouBHa+6cPHmSd999l8HBQVwuFwaDAYfDofaiDQ8Pc/36ddxutyYJj3LO2Gw2srOzCYfD6pYcsViMsbExpqenmZycZGBgAJPJRFlZGY2NjZr1RigJZSwWY3p6mo6ODr7//e9z7Ngx8vPz8Xg8RKNRFhYW6O/vJx6PqzMOTSZT0mNWVrKvqKi47etKfU8ikWB6eppAIEA8Hk+J3jOFXq8nKysLnU6n9lzOzc0RCoWw2Wxah7fsiIQnCaLRKG63m97eXjIzM2lqamL//v3k5OSQk5PD6tWr2bhxI2VlZbzyyivqWhapkkhYLBb188rKSvbt28eZM2dobW0lkUikxI1u6SJzi4uL6lBWT08Pv/M7v8PevXtpaGjQOMobJEkiNzeX/fv385u/+ZuMj49jNBqJRqPYbDbsdjsPP/ww9913n3qx1rod3GpprVl6enpKbCcCN4rXT548ybFjx+js7FQThR07drB9+3aam5vp6enha1/72nvadbLpdDoyMjL44z/+Y9555x1kWcZms+FwOJifn1eHimdnZ3n66afJz89n06ZN7Ny5U9PCcFmWGRkZ4YUXXuD06dO4XC7sdjvd3d3EYjGys7NZu3Yt3/ve95ifn6eoqIhPf/rT1NXVAclrx0r7fL/fpyQ7sViMH/7wh2zZsoWioiIyMzNT4nxTErJoNEo8HsdoNFJQUEBTU1NK1CEuRyLhSQJl0bt4PE55eTnFxcU/drE1mUzk5+er4/c+nw9IzbUhlDHwUCiUMkXWylPn97//fa5fv05PTw/t7e3ce++9PPLII9TW1qbUDCKr1Up9fT2f+tSnKC0tpaioiPz8fNLT02ltbcXtdnP8+HE+/vGPp+xMLZ/PR2trq7o3XCq0BYvFwoMPPkhjYyN+v5+CggIqKyvJyMggPT0do9FILBYjMzOTeDyO2+3WLFadTqfWcCl76ynrA+l0OoaHh7l27Ro6nY6nnnqKPXv2aFpUq0yR/uIXv8j58+dJS0vjQx/6EG+++SbBYJB169bx4Q9/mM9+9rPMz8/zta99jY6ODg4cOEB1dXVSt0P4IAkPgN1uZ8uWLbz55pu8/PLLuN1uPvKRj5CVlaX5dTcYDDI2Nsbhw4eJRCKsW7eOPXv2qLNPtY5vOUqdO8AKZjAYyMjIwGq1EggEcLvduFwuMjIyANQiVaPRiCzLhEIhdW+tVKRsdJoqs4kSiQTz8/O88sorvPLKK+pNrLKyks2bN5OZmZkSdTtLGY1GcnNz+fCHP4zdbsdqtaqbxup0OlpaWpicnOTq1ats2rQpJXpPllKGadva2qitrdV8IUeFXq+npqaGkpIS4vE46enpOBwO9bjKsqxu3aIMJW7fvl2TmillGPZ2PU3K7KzW1lZKSkpYv349hYWFmh5jZV+38+fPMzU1hdls5uLFi7jdbmRZprCwkPr6etLS0pBlGZPJRCgU4syZM0xPTydlFXnl+un1egHUeqfb/W2V3p1YLEZ6ejozMzPqumhaz9YKh8P09fVx8uRJOjo6AFizZg3r169Xe/9S6Xq2XIiEJwnS0tLUVXPT0tKwWq0/tsqrspBfKtw0lj6pLz2pli6U5vf7cTgcKXHSJRIJdXuDtrY2YrEYTqeTsrIysrKyiMfjRKPRlKqH0ev1pKenU19fr/7tlWNZVlZGR0cHfr+foaEhNmzYkNSE59aemlv/xrFYDJfLxdDQELOzs+zfv5/MzEzN265yE/hJs8VsNhs5OTmMjY3R399POBzWfOberWKxGG63m76+PlatWkVFRYX6gKQFZZuOU6dOMTY2RigUIhQK0dnZic/nQ6fTEQwGmZqa4uLFiwwODjI2Nsbi4iLT09MMDQ0lrZZHmT0YDAaJRqNkZGRgMBjUAmUl0VlcXGRsbIzu7m6ysrLIyspSJz1obXp6mkuXLnHy5EnGx8exWCzU1NRQXV2dEvEtVyLhSYK0tDRKSkr4zGc+g16vp7S0lIqKih878XU6HUajUV0UTYvhrKWbWirrgCwVj8fp7OxkYmKCsrKylHjSiEajeDweuru7iUaj6PV6IpGIWvjpcrlwOBwpU7CsULaXuJWS/MTjcQKBQNLjSiQS7xkSuLUNLC4ucunSJd59910KCgrYt28fubm5mic8S9uu0n6Vtrm0jaanp7NmzRo8Hg+dnZ14PB7y8vI0j38pn8+Hx+MhEAiwd+9eSkpKNN2vLhKJMD4+zr//+78TDAbVGZvhcFithTl9+jSdnZ2sX7+e7u5ute1mZGTQ3t5OdXV1UpK29PR0EokEExMTXLhwgQ0bNmCz2QiHw2rBr8/no7+/n87OTlpbW7n77rvVOr+CgoKfe4x3orTdlpYWDh48yDvvvEM0GqWqqopVq1ZpvnbUcicSniSQJAmz2cy9994L3Lih3S5LVxaV6u7u5vr16+qTZzIpGxgqPTjKUIAkScRiMa5cucLhw4cxmUw888wzSY3tTvx+P263G5/PR0FBATt37mTbtm00NzdTWVmJzWZLuRVU348yRdnv93P//fcn/YlOSXKi0Sitra1cv36dSCSCw+FAr9dz6NAhpqenycrK4nd/93fJy8tLmfqoWCxGW1sb0WiUrKwsampqfmwYRafTUV9fT39/PxcuXGB6elpduylVXL58matXr2I0Gnnsscc0L6SVZVl9WNuxYweZmZlEo1EmJiYYHBxUhwslScLlcrFv3z6ysrLIz8+nvr6eDRs2JGWZDaXtKkNCzz//PHa7HYPBQDgcxufzEYvFkCSJkpIS1q1bx5e//GUaGxvV92m9J+DQ0BD/+Z//yaVLl1hYWECSJJqamqiqqsLhcGgW20qQOmf4CqachEuHVG49qZTxfGVlTa/XSywWS3aoJBIJBgcHOXnyJB6Ph9zcXHW9h8nJSS5fvkxtbS0bNmxImZV1jUYjOTk53HPPPWzYsIGmpiYqKyvVBdBSYTPLD0LpoRgZGcHtdhOPxzUZNlSG2PR6PV6vl9nZWXp7e+np6VE3sFS276ivr0+p46vX6zEajepCeMXFxdTW1rJq1Sry8/PVczA7O5vs7GwMBgNjY2PU1tZqvo4Q/GhBwitXrjAwMIDNZqOiokKTad1LmUwmVq1axb/8y79gsVgwGAxqvUwoFHrPe/V6PQ6HA6PRiMlkwmazYbPZktZOJEmioqICu91OXV0daWlpeL1eFhcX1X3K8vLycDqdZGdnk5OTk9T47kSZYXrgwAH6+vrw+/3qNih33303xcXFKTUsvxyJhCdJftKJpNPpMJvNFBQUqIvmTU1NUVNTk6QIfxQH3OjCvnr1KgaDQd1/yuv1Yjabqa+vp76+PmWeNtLS0igsLOSRRx5hzZo1lJWVaf5E/L+lPOEFAgF1uneyKcdNr9erxb8Gg4FIJILP56OkpITt27ezYcOGlGkDCmXKf2FhIYuLiwBqLcfSoTm73U5RUREVFRXMzMyohfip0GY8Hg/Xr19nbm6O0tLSlJiCrNfrsdlsbN68+bZ1fbda+h4tjqnVasVisZCbm4ter8fv9xMIBAgGg+rGrBaLJWUmXsCPhuYvXLjAwsKCugZPZWUljY2NZGdna94OljuR8KQIvV6P3W5n69atdHV1EQwGmZiYSHrCo9fryc3Npa6ujs7OTiYnJ3G73ZhMJhwOBw8++CCbN2+moKAgZU4+s9lMcXExjz32WEpdwP43ZFlmdnYWs9mM0+nU7BgrPY4bNmxg7dq1bNmyhR07dhAMBsnLyyM/P5/s7OyUOtZKLCUlJWRkZFBbW8vc3BySJKmrVyusVivV1dVs27ZNLWRNFdPT0wwMDBAOh1m/fr3mPQ+K29XrpUJct6O0X6VuLy0tjezsbI2jen9KwjMyMoLZbCY/P5/Kykqam5tZu3atpjVcK4X0E9bO0H5hjV8Qyt/B5XLR1dX1nu5YLQqXlULEpQWgwHsuvql0sfug626kMuX/4Pf71ZqJVNid/v2uEVrHdjsfJF7lPYlEQl33JhW280gkEvzHf/wH3/72tykuLuYP//APaWho0Dwu4efP5/MxNjbG17/+dUpKStiyZQsbNmx4z87zoh18IHc8SCLhSSFKkhGJRNRl0SH5jfyDLCAnTryfn6W9DanSi7YS3a6da92uZVmmt7eXkZERbDYb62Qvs4kAACAASURBVNevF4vM/YJQpst7vV70ej1paWnveeAVbeADEwmPIAhCqpNlWV1Dxmg0kpGRkRI9T4KwjIiERxAEQRCEFe+OCY/oLxcEQRAEYcUTCY8gCIIgCCueSHgEQRAEQVjxxDo8giAIwi8UZbkNRSrPhFJiDYfDhEIhwuGwunddKsabykTCk0JuXf9m6S7aomGvbMrFNxaLIcuyui6MmJYuLFdLN6FNlZvz0qU/wuEwsVgMnU5Heno6RqMxZeJUyLJMLBbD5/MxOzuL2+1mfn6e3bt3YzabUyrW5UAkPCnG7XYzPj5OOBzGZDJRWlpKVlZW0jeQFJJL2Zeoq6sLj8dDfn4+hYWF5OTkaB2aIPyvzM3N4fP5MBgMFBcXax0OcGO/qtHRUU6cOMGpU6fo7e3Fbrfz6U9/mvr6evLz87HZbFqHqQoGg3R2dvK3f/u36rFUVsIvLCxMif3flhOR8KSIeDyOz+fjxRdf5Pjx47jdbux2O0888QSPP/64JptILrV0ZVoljlTtfVjaUxYMBunp6WF0dJT5+XkqKyvZtGkTVqs1ZXbHDgaD9Pf309LSwosvvojL5aKpqYm9e/fy1FNPaR0eAF6vl+npabxeL7W1tVgslpT9+78fpR3fadFBrZ+Yl7Zdj8fD4OAgra2t+Hw+ZFnGZDKRk5PDRz7ykR/bLiNZ8UWjUfR6/R17Q5T429rauHTpEj6fjz/90z/VdAPUeDzO3Nwcvb29fPWrX6W1tRW3200oFEKn0+Hz+di/fz87d+6kubk5JbbziEQijI2N8ZWvfIVYLMYTTzxBTU0NPp8vpbZCWU5S44r/Cy4WizE/P09HRweHDx9mcHAQk8lEbm4uBQUFmtyYE4kEPp+PkZERsrKysFgsDA8P09LSgl6vx+l0UllZSUVFBRkZGRgMBs0TskQiwdTUFMPDw8zNzRGJRLh+/TpDQ0Pq52VlZbhcLurq6tQ9l7SMOR6Pc/78edra2rh69SobN25kZGQEgKmpKc1iWyqRSDAxMcEPf/hDhoeHeeCBB8jMzFRXg1U2lzWbzdjtds139lYoSU0gEGBxcRGv14vX68Xv9zM2NkYgEFBvHA6Hg1WrVlFRUaHuufTz/j8sHcYMBoP4/X48Hg8tLS0sLCzg8XiYmZlRd6mXZRmDwaAuRtjU1ERpaSkWi+XnGqdCGQpaXFzEbre/77Y3breba9eu0dbWhsFgeM8wvRZmZ2dpb2/n7bff5vTp08zMzCBJEmlpaZhMJiYmJnj33XeRZZns7GzWrFkDaFfTk0gkmJyc5PLly/T29vLII4/Q2NiIw+Hg8uXLuFwu8vLyRA/PT0kkPBpSnuYWFhbo7+/n6NGj9PX1YbfbqaqqYuvWraxfv16T/bQSiQQzMzOcOHGCuro6SktL6e3t5ZVXXkGWZfLz82loaKC5uZn6+noyMzM1PfmUJ7jz589z+fJlJiYm8Pv9nD9/nmg0SlpaGg6Hg1AoRCgUIhgMIsuyuhO1Vhe2cDhMZ2cn3d3dhEIhPvWpT9HW1sbk5OQH2uIjGWKxGKOjo7z11lt0dXUBkJeXh9lsxmq1Yrfb1VWBy8vLKS0tTYkEWCn0VJLeiYkJZmdnWVhYoK+vD7/fj8FgQKfTUV5eDoDT6SQrKytpsSu9kC6Xi5mZGUZGRvjBD37A1NQUgUCASCSCx+Nhfn6eWCwGgMlkwmw2k5WVRU5OTtISHlmWiUQi+Hw+zGbzbc93peakp6eHK1euMDg4yKpVqzRry0o76Ovr48SJE7zxxhvMzc2Rk5OD0+kkMzMTu93O3NwcIyMj6PV68vLyyMvL0/RBLh6PMzQ0xKVLl/D7/dx9991UVFQwNzfH+Pg4RqORVatWJT2u5U4kPBpYevKHw2HOnj3L4cOH+cEPfsDu3bvZsGEDDQ0NNDY2arYjtXLRev7553n88ccpLCykrq6Oxx9/nIGBAfr7+3nxxRc5dOgQv/d7v0dTUxMlJSWaxCrLMouLi7z11lt86UtfoqCggPT0dGZnZ7FYLOzcuZN169ZRW1tLRkYG3/zmNzlx4gRut5vS0lIcDkfSY1YEAgGqqqqorq6moqKCiooKWltbcTqdVFRUaBbXUouLi4yMjNDR0YHL5eKVV16hrKyMoqIi4Mbu3j6fj6ysLLZs2cJv//Zvk52djdFo1DTuSCRCX18ff//3f8/Zs2cZGxsDICcnh9WrV1NTU0N5eTmZmZmsWbOG6upqCgoKkjpMFIvFcLvdDA8PMzExwcLCAvfff/97Xu/p6eGNN95gZmZGLbadnZ0lGAwmdWhDkiS1hyktLe3HjpPSYzk7O8sLL7zA8ePHMZlM7N69G5PJpNkQaCQS4cCBA7z11luMjo7ywAMPsGvXLlatWkVJSQnZ2dkMDAzw/PPPc+3aNb7xjW+g0+nYv38/TqdTkx52v9/P9evX6ejoIC8vj4aGBhwOB263Wx0RiMfjSY9ruRMJj0bi8TiLi4v80z/9E2fPniUWi/HZz36WT37yk1itVkwmk6Y3DFmWCQQCGI1G0tPTyc7OJjs7m5qaGsLhMMFgkLm5OQ4cOMDp06dJT0+nuLhYk4RnYmKCc+fO8Vd/9Vd86EMf4qMf/Sh1dXXqZnw2mw2z2awOtXR2dnL58mVmZmaIRqNJj3eprKwsdu/erR636elpDh48yObNm2lubtY0NkU8Hicej2Mymdi5cye/9Vu/xZo1a8jKylKf+mdnZ2lpaeFb3/oW9913H5s3b9a0/S4uLtLT08MXv/hF2tvbycvL45d/+Zd54oknqKysxGq1qr0UBoNBrUlJ9k3ZZDJRUlJCYWGh+iAkSRKJRAKXy8WVK1f47ne/y/z8PNFoFKvVSn19PX/wB3/A5s2bycrKSlqskiSpx+x2xymRSDA/P8/3vvc9jh07hsPhYNu2bdx7772a1nv5fD6uX79ONBpl165d/OVf/iVlZWXq/0OSJAoLC8nNzeXYsWN8+9vf5i/+4i+Ix+N86EMf0qQnZW5ujoGBAebn5/n85z+v9qalpaWRm5sranj+l0TCk2ShUIiZmRkGBga4cOECZ86coby8nA0bNnDvvffidDrVgjmt6yAsFguZmZnqlE29Xo9er1e71AE8Ho86Dq6FcDhMd3c3p06dIhwOs2PHDmpqasjNzQVuJG5LCyxlWWZ2dha4UbeRrOGAO1GOKfyoliuRSJCZmUl+fr6msSmUGCVJwmazUVpaSmFhIVarFVmW8fl8XLt2jeHhYRYXFzVvt4lEgoGBAY4cOcLAwAB79+6lsbGRdevWsWHDBmw2m5qoBYNBnE6nJueb8vuUhEv53Ov1qteHN998k97eXkKhEE6nk9WrV/P000+zefNmsrOzk55IvN9xUupkDhw4gM/nY9euXdx7770UFhZqPryZSCSw2WxUV1dTVFSkFnwr1wSTyURFRQXbtm3D7Xbzj//4jxw6dIjc3FyqqqqSPkvW7/fj9XqJxWJUVlaqv99ut1NXV8fc3JzmPajLkUh4kkS5wF67do2enh66u7sZGhoiLy+PrVu3sm3bNmpqajSvfVBIkoTJZMJkMhGNRvH5fFgsFoxGo9o7NTQ0hMfjYcOGDepNI9m8Xi99fX10dXVRUlJCXV0d2dnZt03AEokE4XCYyclJDAYDOTk5miVq8OMFkfF4nMnJSex2Ozk5OWRmZmoU2XsFAgH8fj/hcJiFhQUCgQA+n49QKITH42FqaorW1laGhobIz88nIyND02UUZFlmfHycixcvArB7927q6upwOp34fD4WFxdZXFxUe620GjZWJBIJAoEAXq+X+fl5BgcHuXr1KufPn+fUqVP4fD6cTieNjY3s2rWL3bt3k5+fn/RjfKcZWXDjBt3T08Px48fVc3HTpk00NjZitVqTGuetlN4Qq9WqJupL6/aUf+12O+Xl5WzevBlZlunt7WVqaiqp9UdKzdH09DQLCwvIskxGRoYaY1paGjk5OQwPD6trdqXC/WK5EAlPksiyzPz8PC+99BIdHR0EAgG2bt3KY489xqpVq3A6nSk1zVcZr49EIkxOTnL9+nV0Oh1Op5PFxUWuXr3K4cOHSSQSNDU1UVlZqcmJNzU1RU9PD2NjY3z0ox+lvLz8jhdYpct9ZGSEdevWUVpamjJPSUuLPYuKiigsLEyZ9UAmJiYYGxtjcXGRK1eucOHCBdxuN/F4nPb2dnp7e+nt7cVqtbJ3717Kyso0TSSVG0ZfXx8lJSU0NTVhNpuZnp5Wi0BHRkZwOp3cddddrFu3TrNY4cayBNevX6erq4sLFy5w+vRpRkdHWVhYIBwOk5+fz1133cXjjz/OQw89RFZWVkpcK5SbczweZ2BggKNHj/LKK68QjUZ5+OGH2blzZ0rUocXjcWRZJj09nZycnPetybFarZSXl2O32wkEAoTD4aQXXEejUa5evcrU1JTaO61QhjtPnTpFfX09DocjZR6SlwOR8CRJPB5Xu6hLS0v5zGc+w5NPPpkSF67bUZIbn8/H66+/Tk9PD7/5m7+J3W7n9OnTnDhxgsuXL/P1r39d0xvc7Ows09PTJBIJHnvssfddpDEcDtPW1sb4+DhbtmyhoKAgydG+v2AwyOHDh9m7dy+lpaUpM+XUYDCoiaHL5eILX/gCOp1O7bUsKChgz5493HPPPezfvz+pdSW3o9PpsFqtZGVlEYvFcLlczM/PMzAwwPXr17l48SKJRIJ9+/bR3Nys+c2ira2Nb3zjG7z++ut4vd731GdYLBYefvhhPve5z1FeXp4ybQJuDMF6vV7Onj3L888/z4ULF5ifn+fjH/84v/Vbv6UOz2vNZDKpU+ONRuNP/HsrM2eVWVrJFI/H6e3t5eWXX8bn87Fx40asVut71j4zGAx0dXVx8uRJIpEIa9eu1bwNLxci4UkS5akzkUhgt9vVwjOfz0c8HkeSJCwWiyZT0G9Hr9dTWlrKr/7qryJJEgUFBdTX1+Pz+bh06RIej4d77rlH7SXRKuaCggKam5vVqaR3mmKuDBt0dHRgt9spLS1VZxmlgng8ru6VU11drfkwy1JVVVU89NBDZGdnYzabefvtt+no6GBycpKSkhI+97nPsXHjRsrLy9V1jbSMXZIkqqqq2L59O9/61rd44YUX+NCHPkRzczNNTU0MDw+rw592u13zeBcWFtSC5IyMDHbu3ElGRgaTk5NcuHCBCxcucPXqVSwWCyUlJZo8JIXDYfx+P5OTk0xPTzM2Nsbg4CAdHR0MDw+r9VuyLPPOO+8QCoXYtGkTdXV1rF69GofDgdlsVuuVkslisfzYQoJ3+nsHAgEmJiaIRqPk5ubicDiSdryVa9QPf/hDZmZmyM3NpbCwELfbrd4bDAYDDoeDhoYGWlpa1Guz0+lMSozLnUh4kkSWZSYnJwmHw0xNTXH+/HngxnBBIBBAr9dTXFxMQ0NDSiwoJUkS6enp1NXVYTKZyMzMxGKxcO7cObq7uzEajdTX12ueoOXl5bF9+3bWrl37nrHuW8ViMRYXF+nq6mL16tWUlZWpN7tUoCw+F4lEMBqNKbMKNNyobaipqcFisTA3N8fhw4cxm81UV1dz//33c/fdd1NcXIzNZkuJuJVZN1u2bOHSpUsYDAays7MpLS0lEokQj8epqKigpKRE03iXzsrKzMykurqa6upqHnnkERwOB6Ojo9jtdnVB0lAoRHNzM+Xl5UldCViZIt3Z2cmlS5fUKfHKYolLe3fj8ThTU1O0tLQwOjpKW1ubukBpaWkp5eXlVFZWJnXtqw9akK70Bl65cgVJkqisrCQnJydpccbjcfx+P9euXSMQCKgTXA4dOsR9991HaWkpNpsNo9FIQUEBXV1dTE5OEggERMLzAWl/dfoFIcsyHo9HXQjtjTfeYHR0VF17Q1n8LBgMsnXrVvLy8tQLiZYJhbLKss1mIxqNcvr0aQYHB6mpqaGyslKzuBTKdHm483FSptjPzMxw/fp1nn32WcrKyjSfobWUkvDEYrH3bLqYCgwGA3a7nYKCAnp6epicnMThcNDY2MgnPvEJamtrU66OICcnh02bNvGxj30MWZaprKwkKyuL6elpIpEIJSUlFBQUaB6zUgfjcDiora3l4Ycf5oEHHiAtLY3p6Wm1Zu7o0aN4vV50Oh15eXlJre9aWFigra2NAwcOcPz4cYLBIDk5OZSXl7N+/XosFgsej4dQKKQWgsuyTHd3N+3t7eh0OtasWcPGjRvZs2cPpaWlSR8CXzoj61ZLC6+Hh4dpbW3FYDBQW1tLfn5+0tqIsshkf3+/WkPp8/loaWmhrq6OnJwcdaFUs9lMOBwmEAhovrTGciISniTR6XRUV1djMpkYGRnB6/USj8d58MEH0el0zMzMcOHCBS5dusRzzz3H7t27aWho0CRWZRqn2+3G5XJRVFSEyWRifn6e/v5+gsHge+o6UsXSJ+alnysrBV+8eBGj0chdd92VMlO+FUrRsrJFQyr0lMCP4urt7eUHP/gB//Vf/0U8HucjH/kIn/jEJ9Q2qnXicCuLxUJZWRnPPvusOpMlFArh9/spKCigurqavLw8rcMkkUioRfdWq5WmpiZ1fZiCggL27duH3W7nT/7kT9T9n+rq6li3bl3S2ojX6+X69eu0t7ezuLhIWlqaOpW7pKSEoqIi3nnnHeLxOHa7nY997GM88cQTXLt2jXPnznH06FE6OztZXFwkPz+fffv2JSVuhcFgUGc8KqtVK21i6R6BXV1dtLS0cOHCBRwOBzU1NUnr4ZFlGb/fz+DgIO3t7TQ3N/PYY49xzz33EAwGKSkpUWt5YrGY2l6cTmfKTG5YDlLjqvoLQKfTUV9fT0FBAS6XC0mSyMjI4NFHH1UX7HO5XPzpn/4pFy9exGazUVlZqdmwi9fr5Utf+pI6zdtgMKirwqalpZGVlZUSJ9rAwACTk5NEo1Gam5vV9YEU4XCYd999l0OHDtHS0sIDDzzwvjO5tGI0GrHb7ciyzMjICKWlpZrvlK4kvmfOnOHQoUO8/PLLxONxnn76ae69916qqqo0je+DuHU4Q5IkcnNzsdlsms4kUyjbX8zPz7OwsMDY2Nh7knGdTqeuhRUOh5mZmcHj8SS1B7CoqIg9e/YQiUR49dVXGRsbY3Z2lrm5OS5duoROp1OHtkpLS3nyySfZvHkzd911F/v27eOBBx7gb/7mb6irq6OioiLpD0pGo5EdO3Zw6dIlLl++zNzcnLoXHNwYSmpra+Ob3/wmp06dwu1289BDD1FfX5/Uc9Dj8XDt2jVMJhO//uu/rvb0Kw8dIyMjjIyM0NXVxYEDB9ixYwfV1dWa7ge43IiEJ0l0Oh1VVVU8++yzjI+PE4vFKCwspLCwUD350tPTefDBBzly5AhtbW1kZGSwf/9+zGZzUgsVleK5CxcukJ2dzcLCAnNzc7S3tzM+Pq5ugaDllgwKt9utDrPF43H1AqDsBXb+/HlOnDjB5OQk+fn53H///djt9pSYPbKUwWAgPT0dm83G1NQUXq9X03iUoZbz58/z5ptv0t7ejsPhUG9g1dXVWCyWlOvZWerW2JRhAkmS1NWjte6lVIay29vbmZ6epr+/n7q6OtLS0ojH43i9Xs6dO8fs7CxWq5Wqqiry8vKSetwtFgt1dXWYzWZycnI4cuQIg4ODuFwu/H6/usWBzWbD6XSq9V46nQ69Xk9TUxO/9mu/Rl5eHrW1tUm9linHafXq1UxMTHDq1ClefPFFPvKRj6DT6ZidnaWzs5NTp07R0tLC7Ows2dnZ7Nmzh9zc3KQmxco6V5s2bVKvr9FolLGxMc6ePUtXVxejo6PMzs7idDppbm6mtrZW8za8nIiEJ0mUJ8t9+/bh8/mIRqPo9XocDoe61oLZbGb79u10d3erJ+J9992nSQFzIpHA7/fT399PTk4O09PTnD59Gp1OR11dHXV1daSnpyc9rlsZjUb8fj+9vb0cPHiQNWvWUFRUhCzLDA4Ocvz4cUZHRyksLGTr1q0pUWh9O3q9HrPZTG5urrrIn9aLismyzMzMDDMzM5hMJrZt28YjjzzCunXrsFqtKZc0/iSSJGE0GtVi23A4/GM9gsmmPAgVFhaqkxkqKiqwWq1EIhGmpqY4efIk8Xic2tpatm3bRm5ublKTBoPBQEFBAQ6Hg5ycHKxWK+3t7Vy/fp3h4WHGx8fV4ayioiJycnLUmpm0tDSKi4vZv3+/2oupxSyz0tJSdTuJN954A6fTSSKRYHx8nNbWVjo6Ot6zwGNTU5N6bU6WRCJBIpFQHzLHx8cJh8NcunSJo0ePMjo6SjgcJiMjg7vvvpvNmzdTXFycskubpCKR8CSJsnKxsivznd6zevVqfumXfomuri5cLlcSI/wRnU5Heno69fX1nD59mitXrmC1Wpmenmbr1q189KMfpbGxUfOZZABr1qxh586duN1uvvGNb2AwGCgvL8doNDI5OYnP52P37t3s37+f/fv3p0Sv1O0oN+Pq6uqUSCQkSUKn01FZWcl9992H2WxWnzxTLVn8oHQ6HWlpabhcLiYnJykuLtZ0OGBp78PGjRsZHx/n5ZdfZnx8nKysLHw+n7pR744dO3j00Ud54IEHNBnq1Ov12O121qxZQ21tLf39/Vy5coV33nmH7373uywuLqpLVyztFVEe5LSe4JCfn8+mTZtwuVx88YtfZHBwkGAwiM/nU2sS6+vr2b17Nx//+MfZtGlT0tt5WloaGRkZDA4O8tprr5GZmamuHRYMBsnPz2f9+vXs27ePhoaGpPf8rwQi4UlB69evp6amhlgsptkF2eFw8IUvfIG+vj4ikYi6TlB1dTU5OTmaPxkr0tLS2LhxI2azGZfLRU9PDz6fD7PZTENDA7t27eLBBx98zxoxqUqv11NRUaHWeMXjcc2Ll9etW0ddXR3Asr+4KsPG+fn5jI+PU1RURFlZmdZh4XQ6efjhh6muruall17i2LFjRCIRrFYrpaWl/Nmf/Rm7d++muLg4JRJ2nU6n7jS/c+dOjEYjb731FmvXrmXnzp1ah3dbSk/a448/zujoKK+++irxeJycnBwqKip45JFHaGpqoqKiQt2HL9lKS0t57LHHyMnJ4bXXXmN6ehqbzcajjz7K3XffTWZmJna7nczMzGX70KE16ScUv6XO3NhfIEunJis7fCfb0s0VlZVfdTqdup9Wqtz8lII+v9/P6OioupCjMkSUnZ1NTk6OumhXKovH4+q06aysLBwOh7iw/QwpbaWzsxOTyYTT6UyZ2XrRaFRd2M/tdqub3prNZvLz88nKylJXDE4VsiwTjUbp7u7m7NmzFBQUqMMsqSiRSBCNRhkdHWVycpJEIoFer8disZCXl0dGRgZms1mtiUn2uRePx9Wp6dPT04TDYfR6PQUFBWRlZamLNqZSG0hRd/zDiYRHWBGUIttb27OSmC2HxGFp/Frs3v2LQJZlQqEQiUQCg8GQEsOyiuXYhpVZZiMjI6SlpZGbm5sStX13ohxf5SFu6ZYNSz/XytJp8opUiW0ZEQmPIAiCIAgr3h0TntQYlxAEQRAEQfg5EgmPIAiCIAgrnkh4BEEQBEFY8UTCIwiCIAjCiifmtwkf2J0K3MXsAUEQBCHViYRH+Kkoa5ko2x6IfVwEQRCE5UAkPBpaumheIpHAbrermxumIlmWaWlp4Y033mBmZobi4mL+/M//XN03RxAEQRBSlUh4NJJIJAiFQly7do2JiQkikQhFRUWsWrWKjIyMlOs5UZKz3t5eTp48yczMDI2NjXcc5kqmcDiM3+9nZmaGqqoqNWlcuvlmKidk4XCYQCDA4uIiHo+HWCwG3NgYNSsri4KCAnWD2VQhy7K6m3cwGESn06ltOhqNqsvgp8oidIlEglgsRjAYxOVyEYvFMJvNZGRkkJGRkRLtQzmXotEo0WhUbb8zMzNYrVZsNlvKHM/bWbpopiCkIpHwJJmyymc4HGZ0dJSXXnqJzs5OgsEgVVVVPPPMMzQ0NKTUfinKzW1xcZGRkRG8Xi8mk4mSkhLNb8KyLOPxeOjv7+fEiRM899xzZGRkIMsygUBAXZ5fSRiUFYy1XslYuTnE43FmZ2cZHR2lr6+Pq1evEggEkCQJh8NBfX09e/bsUbcW0CrmpasAK1sK+Hw+hoaG1N3Uw+EwExMTLCwssGXLFmpqajS9QS+NNRKJ4PV6GRkZ4cKFC/h8PvLz82lsbGTjxo2a7kyfSCSIx+PE43FCoRBerxe/349Op8NkMnH06FHKy8upra19382HtaAcYyV+ZbsGZfNZ5SPV3NqelyZrS68TWlPiWro6tNJWU+VatpyIhCfJEokEo6OjXLp0iRdffJEjR44QCoWQJIlz584Rj8f57Gc/S11dHVarVetwgRsn2Pz8PEePHuXw4cPEYjGam5v5tV/7Nc1PtEQiQWdnJwcOHOC///u/yczMpLS0lN7eXv71X/+V2tpaHnroIWpqasjNzcVut5OVlYXNZtN8A9R4PE5nZycvvfQSHR0dTE9PqztNG41GDAYD58+fp7W1lU996lPU1dVpdrzD4TCLi4sEg0EWFxe5ePEiV65cwWw2k5mZidPpZH5+npMnT9LV1UVVVRW1tbWaxKpIJBIsLCxw8uRJ+vr66Onp4d1332V8fJxEIkF9fT2PPvoo9fX1mvaozszMMDw8TFdXF2+//Tbj4+OsWrWKhoYG6uvree211ygpKeHRRx9NuYQHwOv1cunSJQYHB5mbm6OmpgabzUZeXh55eXkps1/ZUolEgvn5eTweDwsLC0SjURKJBDabjfz8fPLy8rQOURWNRnG73SwsLBAIBIhEItjtdiwWCw6HIyVHBFKVSHiSRMnQ29raePPNN3n99dfx+Xw89NBD5OfnE41GaW9v58SJE2zbto2MjAzNbxiKUCjE1NQU7777LlNTU9x1113s2LGDiooKQNsubI/HQ19fHx0dHcRiMXVX9/Lycvbs2cPbb79NV1eXenHIGDFpiwAAIABJREFUzc1l+/bt3H///dTX12OxWDSJOxqN4nK5+PKXv8zExAQVFRU8/fTTFBUVkZaWhsViwWAwEIlEGB8fx+l0ahIn3Gi7165d45VXXqGiooJ77rmHBx54gPvvvx+9Xo9eryccDtP6/7H3nsFxnef99rW9YQEsdtE7AaKQAAgWgCAJdoq0JEqRREmWWxQ5sT12XMeZJP6QmciTaP6TsZPYmVijiSwrES1LVqFEsYpgARtIgCCI3nvHAgsssL2+HzjnmFSznVh7lnr3mtGIZWd478Fznuf33LWxkaNHj1JeXk5BQQFJSUmS2ezxeJidneX111/n8OHDLC0toVKpSE9PZ+vWrdhsNnQ6HR6PR7KwrPDvtrS0cPHiRUZHRykuLubJJ5+ktLSUpKQkPB4PSUlJKBQKSWz8JFwuF1NTU7z00ktcvHgRl8slrtuFhQUqKyvZvXs3X/7ylyX1TsLty4UQ+nY6nVy/fp3m5mZ6enqYmprC4/EQDAapqKjgi1/8Ig8//HDEbRQGh165coX09HQA7HY7HR0ddHR0MD09zdLSEm63m4yMDHJycti5cyf33XefZBPe7zVigidChMNhZmZmOHXqFPX19UxMTFBQUMCBAwfIyckhGAyyatUq/uVf/oXm5mbS09PJy8tDpVJJ7kURQkbXr19Hq9VSWVlJeXl5VOQTLC0tMTExwdTUFCaTiZycHLKzs8nKykKn0xEXF0dTUxNWq5WpqSkmJydZWVnBYDCg1WopKysDIivawuGw6CVpbW1ly5YtbN26lZqaGhISElAqleJE+kAggMFgkNTb5/f7mZubo6Ojg9WrVxMXF0dSUtJdU5v7+/vFKd/79+8nNTVVslunx+Ohv7+fhoYGjh07htfrpby8nKKiIkpKSsjNzWVlZYVwOIzRaJRcTGRlZVFVVUVxcTEFBQXk5eWJB5jD4WBycpI1a9ZE1ZTsQCDA7OwsFy5c4Ny5c6hUKsrKyiguLkalUtHb28vKygoDAwOsrKxIJtgFUSmEi9vb23G73fT19TEyMsLMzAwrKysEAgHkcjnp6el3De6MJIFAALvdzrVr1/B6veJ/Qohbr9cTHx+P0Wikra2NYDBISUmJmPMX4/cTPW/QZxjBu9PT00NdXR19fX0YDAY2bdrE9u3bycjIIBwOk5mZyX/8x3/Q1tZGZmYmlZWVpKenSy56rFYrvb299PX1UVtby4YNGygsLJT8oABwOp0sLi6yvLxMTk4OeXl5ZGVlodVqycvLIzs7m7S0NDo6OhgcHKS7u5ubN2+Sl5dHbm4ua9eujfizDQaDzM/Pc/HiRRwOB9XV1Wzbto3s7Oy7PhcOh1GpVGg0GjHpVgh5RRKhknB+fl6chi2IGSFXqqenh6GhIcxmM3v27MFkMkV8fQjv2ezsLE1NTRw9epTOzk527NjBwYMH2bx5Mzk5Oeh0Onw+H8FgEJlMJuacRBrh3ywqKiI/Px8AnU4n5rwsLy8zPz/P0NAQGzZskMwb+VH4fD4mJiY4e/Ys/f39PPnkk+zZs4dNmzYhk8m4cOEC9fX12Gw23G63pLb6/X6ampo4ceIEdXV1BINBXC4XgUCAUCgkiiKj0SiGvKVAWL9Op5OmpiYWFxdRKBSUlZWxfv16DAYDSUlJZGRkMDAwQDAYJBwOR8U+fK8QEzwRwu/3c+LECfr6+tDr9Wzfvp3vf//75ObmolAo8Pl86PV6LBYLo6OjnDt3DqPRyKFDh8jMzJSsXD0cDtPX10dLSwvJycl8/etfZ+PGjSQlJX0oFCCFfYIg0Gg0aLVaLBYLGo0GuVyORqOhvLyc0tJSxsfHaWxs5Kc//SmdnZ24XC5JNuJwOIzT6WRwcJCjR49SW1tLRUXFh/IchGcbCAQ4cuSImAQsRW6BXC5HqVSi1WrR6/ViBZxAd3c3x48fZ2Fhgccee4y8vDzJvBFOp5PTp09z9OhRrl69yqZNm/jBD37A2rVr7wqxeTwe8TtJjbB+4Xc/91AohM1mo6urC7vdTkFBQVTlldjtdoaHh7lx4wYmk4n777+fqqoqNBoNly5d4le/+hUKhYKNGzeK3y3SCM9ybm6O48ePc+HCBebn58W/F/LkhPyd7OxsSktLWb16tST2GgwGVq9ezXPPPceLL75IT08PSqWSb3/72xQVFaFQKAgEAszPz6NUKsULXUJCgiT23ovEBE8ECAQC2Gw2Tpw4gd1uZ+PGjRw6dEjMgZmdnaWjo4NXX32VlZUVfvjDH5KSksL09DTf+c53+PGPf0xhYSFGozHitjudTvr6+ujt7SU7Oxu/309zc7OYlJiWlobBYJDslqFUKlGr1SgUCubn55mYmECn0931rBQKhXh4CIJz48aN1NTURDyUFQgE6Onp4ebNmzgcDtatW0dSUtKHwj8ej4fR0VFee+01GhsbKSsrkyyspVar0Wq1qFQq+vv7qaiowGAw4Pf7sVqt/OxnP8Pn81FVVcXDDz8smdgRvKhvvPEGk5OT1NTU8Nxzz4lhFqGq7I033sDlclFeXs79998fdfkPS0tLXLx4kcuXL3Px4kXy8/PJy8sjMTFRatNEAoEAXq8Xt9vNysoKv/zlLzly5Agul4vGxkaUSiVf+tKXOHjwoKS5XD6fj0uXLjEwMMDS0hIAWq2WwsJCNm3ahF6v5+WXXyYQCFBdXc2WLVskFZYymQyj0chXv/pVFhcXcTgcxMfH43A4RE/qkSNHmJyc5ODBgxQVFUni9b1XiQmeT5lQKMTCwgLXr19nbm4OQHRLOhwOBgcHOXfuHFevXqWzs5P9+/ezY8cO4uLi6Ozs5LXXXuPYsWM88MADbNiwIeJeFLfbjcvlEktlT5w4gc/nIxQKodFoWLt2rZiHJMVNQ6vVihULQigjISEBvV4vijAhB+nWrVs4nU42btxITk4OJpNJkufZ09NDZ2cnKpWKvLw8MVQhlMdOTEzQ1dVFe3s73d3dPPHEExQUFEh2UxbyB5KSkmhpaaG4uBiTyYTD4aCtrQ2Px8PWrVvZsmWLKMoi/VwFMdnY2MjY2Bjp6ekcOHBAfG6BQACHw8HY2Bj9/f3Mzs5it9uJi4vjoYcekjxsfCdCGwW/34/dbsfj8dDZ2UlmZmbUeHlUKhU6nQ6DwcDc3ByNjY2oVCpCoRA+n4/Pf/7zbN++XdLQt8vlYnh4mPfee4/JyUn8fj9qtZry8nKefvppsrOzGR8fJxgMolaryc3NFb3pUiGsQaPRKIbrT548CYDNZmNiYoLe3l7+7M/+jB07dpCXlxc16/ZeICZ4PmWEfI2WlhacTieZmZlkZmaiUqloaGigubmZs2fP0tnZSSAQYMuWLeTm5oov4dLSEt3d3WzevDmidguH79TUFA6HA71eT3Z2NnFxcSwuLuLxeMQN5fr166LbPS0tDYjcgadWqzEYDOh0OlZWVrhx4wYWiwWv10t8fDzBYJChoSFaWloYGBjAaDRSU1NDbm6uJDkRoVCIlZUVVlZW0Gq1pKamolarxYNidHSU69ev09nZyezsLOnp6ezYsYPU1FTJNmLh1pmTk8O1a9e4cOECBoMBh8NBX18ffr+fnJwc8vPzJc0nEMr8l5eXKS8vp6KiQvT0Cbk6BoOBwsJC1Go1Pp+PpqYmNm7cKL6TUhEIBMReNj6fDwC9Xo/ZbGZ4eJi2tjbWrFlDWVlZVPS1UavVGI1GzGYzAwMDWK1WMeestLSUXbt2UVJSIplXSki0v3jxIjdu3MBut6NQKEhISGDdunXs3LkTn8/H2NgYgUBATCdISkqSvD+X0KdtdnaWzs5OTpw4Adwu/7fb7TgcDtLS0sjIyCA+Pl4yW+9FYoLnU0ZYuDdv3sTn87F161ZKS0tZWlripz/9Ke3t7aKrNT09XSxFn5ubY2hoCLvdftfsqkjbfv36dWw2GyUlJXz3u98lKytLrGzw+XxMT09z+vRpurq6qK2t5ZFHHomonRqNhri4OIxGIz6fj8uXL7O0tMTq1aspKCjA7XbT1NTErVu3GB8fZ/369WLZrxQeE41GI/atmZ+fF7v8ut1u5ubmeP3113n33XcJh8OUlpby53/+52Kel5RYLBY2bNjA4cOHmZycFP9cq9WSnp6OXC6XvBdIMBikv7+fQCBAQkICaWlpYh6HUqnEbDZTU1NDWVkZk5OTXLhwgdOnT9PQ0MBDDz0kaZ6c0+kUDzOn04nb7SY1NZWamhqWlpa4efMm1dXVBIPBqBA8Wq0Wk8kkCkWdTid2r961axfbtm3DYrFIZp/T6aS3t5df/epXjI6OolAoMJvN5OXlUVNTg9ls5saNG7S2thIMBlEoFBiNRsnCxqFQSGxA6Xa7mZqaorGxkbq6OjGFQK1WEwgE8Pl8dHR04HA4xEaPMf4wYoLnU2Z5eZmpqSkGBwdFr0lLSwtnzpzh7Nmz4oas0WgIBoP80z/9E+np6czOznLr1i3xxhTpzUO4/T7//POUlJTw8MMPs23bNgByc3Pv6hScmJhIa2srN27c4L777iMuLi5idhqNRgoKCigvL+fy5cv09vbS29sr9ocRbs2Cy/oHP/gB69evlyRZVSaTodVq2bJlCzqdjpMnT9LT04PVamVkZIRz587xzjvvkJGRwRNPPMHDDz9MZWVlxO38KOLj4ykpKaG6upqJiQnS09NZs2YNmzdv5vnnn8fhcEhajRMKhcTeRkJOl8fjueszQiK7IDpdLheTk5O8/vrr7Ny5U7LDzufzUVdXx4kTJ2hpaaGgoIBHHnmE/fv3k5ycTHx8vJgf4/P5JBeW8Dvhnp6eTnp6OgcPHmRiYoLOzk7J8/oAcdTM4OAgCQkJbN68mc2bN1NbW0tVVRUdHR2cPn2a999/H0AchCyVF3VsbIyBgQHa29sZHh6mrq5O7BX1+OOP8/DDD2M2m5mYmODIkSNcuHCBL3zhC6SkpMSSlv8IYoLnU0a4/Qiu9cuXLyOXy3E6nXdVuvh8PmZnZ7l8+TJGoxG/34/b7aaoqIh9+/aJZauRIBQK4XA4eOedd4iPjxfLpj94+xXCM36/H7lcLkl5r1wup6SkhP3793Pu3DmmpqZQq9Wo1WrxOS8uLqLX68nKymLbtm2SNkGTyWRkZGRgNBopKioiISGBy5cvc/XqVW7cuEFSUhJ//dd/zZYtWygoKIia+LxOpyM/P58f/ehHrKysoNfrxVyp5ORkMUdGKoLBIA6HA4fDgUwmw+fzsbi4SCAQ+EjPjdfrxW63Mzs7y+LiomS9V+B2Uv2GDRtITU3lscceIzk5Way+Ebr/qtVqlEpl1Nzm5XI5ycnJ7Nmzh9TUVMxmM8vLywDi+yXl2k1ISCA3N5f169dz69YtZmZm6O3txWAwkJ2dTXNzM729vVitVgDJRzTcvHmTU6dOce7cOfx+PykpKWzbtk0UakJukcViYWZmho6ODtErFOMPJyZ4PmVUKhVGo5HU1FSxBbgQr1epVCQkJIhJisFgEJPJRGpqKgqFglAoRGFhoZg7Eyl8Ph8LCwvcunWLwsJCioqKSElJ+dBsouXlZc6ePcvVq1dRKBRi6WQkkclkmEwm1qxZw1NPPcXk5CQJCQkYDAaUSiUjIyO8/fbbYmOx+Ph4yUMCQsWTEIYbHBxkYGCAQCDArl272Lp1K3l5eVHR2FFAoVCg1+spLS3F7/ejVCqRy+W4XC60Wq1k4aAP2mg0GnG5XAwODlJXV4dcLqewsBCdTie+UwqFgsHBQTo6OhgZGcFisUgqJORyOSkpKWLOmU6nE+11u91i522NRhM1zQeFWW9CA9Lm5mYWFhZQKpWkpaVFxTuWkZHBzp07xT5d7e3tzM/PMzs7S3t7u/jOCd71wcFBhoaGMBgMEb8UCXl8CwsL5Obm8sADD7Bp0yaKi4vJzMwkEAiI0QJhzRqNxliF1h9JdLw9n2HUajVms5nS0lIWFxfJyMjA7/djs9mYm5sTq4WE4YvZ2dnk5+ejVqvx+/2YTCYSExMjutEJ+SSDg4Ps2rWLlJQUcXyA1+tlfn6excVFpqenOXz4MOPj49TU1JCdnS3JhqzRaMjKyuKZZ57BZrNhNpuJj49HrVbT2NjIpUuXmJiYwOfzRcV0dyGBVi6Xs7i4SH9/PzabjezsbA4dOsTq1aujSuzA72y+U3j7fL67BrRK2RhPoVCg0+koLS0VuwDX1dXhcrnYuXMniYmJqFQqMbzZ0NBAQ0MDExMT1NbWSnpwyOXyj+ymLaxVuVyOxWIhPj4+ajw8cDupOjc3F6/XyyuvvMLIyAhqtVrSPkwCSqWS1NRU9u/fj9Vq5erVq8zMzDAxMcHNmzdFz0hSUhJarZaVlRVu3rxJSkoKq1ativh6yM7OpqCggNTUVIqKiti1a5dYWLG8vMz4+DiTk5O0tbXR3NwspjlEQx+pe4mY4PmU0Wq1rFmzhu9///s8/fTTJCYmit00V1ZWMJlM4vwZIekPbm/gKpUKv9+P0WiM6I3J6/WyuLiIy+Wiq6uL/Px8dDodDoeD0dFRTp06RX9/v1g1sHfvXh555BH27NkjWX6BSqUiIyODjIwM8c+CwSAGg0FsSih40qIFv9/Pm2++yfT0NJWVlXzxi19k+/btkh8WfwjhcBiPxyO2uDeZTJJ1qIXb70tiYiLPPvss3d3ddHd3097eLoYJBIRJ2PPz88hkMrKysti/f7/YUDHaCIVCLC0tUVNTQ2FhYVTZKNgyPj5Oc3MzMzMzlJWVRU0X9vj4eDZv3kxhYSFXr16lv7+fqakp5HI5ZrNZ9FSHQiGOHDlCS0sLcXFx1NbWRnwtl5SU4PV6WVhYoK6ujueee07s/JyRkUFDQwM2mw2ZTEZmZibf/OY3ycjIiIrnfC8R/TvrPY4wzFKj0ZCSkoJcLhdDQ+FwWNyA7/z8ByuyIr3JGQwGcnJyqK6uFm8UcrkcrVZLcnIyWq2WoqIiSktL2bdvH5mZmRiNRsn6xHwcMplMrOBKSEgQ51RFA0LfmImJCQ4dOkRFRQXr16+PGvt+H0K36F//+teUl5eTmpoq+W1TJpORn59PdnY2u3fvxuv1YrPZaG1t5cqVK3R0dDA5OUkwGKSsrIyamhoOHDjA+vXrozI0IFTsjIyMsG3btqhqPCgQCAS4dOkSS0tL5OXlsXfvXkwmk+QhrTtJSkpi//797N69m2AwCNwWyEIJeCAQYO3atfT09EhW6q1Wq6moqCA3N5cDBw5QV1fH8PAwo6OjtLW1kZ2dTU1NDRUVFWzbto309PR7Zq+IJmJP7FNGECtC1dC9gFarFUNEIyMjOBwOMbdAyEUSco2ExnkfFG7RgslkYt++fTidzqi7ISuVSrZv3052djbp6emiYIgmG+9EOCD6+voYHh6mu7ub2dlZPv/5z2M2myU/5GQyGUqlEqVSiUajwWAwYDQa0ev1pKWlsXnzZubm5ggGg2LoWOjJE43PXKg8czqdklYQfRxCv5jOzk6SkpLYtGkTu3fvjqp9TkhE1mq1H3shC4VC1NbWsmbNGnQ6nSSeSplMhkajwWw2U1lZSXx8PLOzs9hsNux2O7m5uWRkZJCWlkZaWlpUNcq8l4iuNyhGVKBSqTCZTOzevRubzYbH4yEUCqFWq0lMTBQ9VkIlVLS+eIKHZ9euXYRCoagaISAczhs2bCA+Ph6tVhu1z/GDrKysMDMzg9VqJTs7m6KioqhIBr8T4aBTq9VkZmaSlJREaWmpOCU9MTERvV4vuVfqkxDWSGFhIampqVGX1yV4KRcWFigqKmLTpk2SDOP9Q/k4uxQKBTk5OWRlZUlaqSX8vJOTk0lMTBS73Lvdbsxms5j6EK3P915A9nuSOKXP8IwR4/+IsMZjG8WfhqWlJXp7e5mYmCA7O5v169dHRW+YzyJC6wehEi6avCfBYBC73c4zzzzDww8/TE1NDWvXrpXarBgxPnajjwmeGJ95YoLnT8udOWhS9y/5rPPB/TmanrMQ4uzs7BRbZ8SEb4woICZ4YsSIESPGn5ZwOIzL5UKj0UjSeDRGjI8gJnhixIgRI0aMGJ95PlbwRE+WYYwYMWLEiBEjxqdETPDEiBEjRowYMT7zxARPjBgxYsSIEeMzT6wPT4zPHHdWEYH0k5BjxPjfIqzhOyviYsSI8b8jJnhifGYQDgeHw4Hdbmd+fh65XI5erycuLg6DwYBKpRI760bb4REOh/H5fPh8PnGWWqzM9/+fCF2WPR4PTqcTpVKJwWCI2plfMSKHcJlzOp0oFArUanXUdeGOVmJPKQq4s1IuFAqJG1q0Hcp33jaF/99po5S2Cjb5fD46Ojqor6/nnXfeQaPRUFpaSkVFBRUVFaSkpJCVlSWW0UYDgu2BQICZmRlGR0dJTEwkNTWVlJQUIPLP9s41+VGVnB/0ngm/jmYEm4V3LNreL/idjR6Ph7m5OQYGBmhpaSEtLY3KysqPbOwXDe+d1Hb8oXxwLX+UJ1ggmr+PMLjXYDCQl5cXlXPWopFYWXoUEAqFcDgcDA8PU19fT3x8PKWlpVRVVUXVpix4IBobG+nt7RWnfNfU1JCYmCipN8Ln8zExMcErr7xCQ0MDPT09TExMiDOIhBk5RUVF/M3f/A1r167FYrFIZu+dBAIBpqamuHXrFi+++CK3bt1i9erV7N27l29/+9sYjcaIrwGfz8fc3BxWq5WJiQk8Hg8ajYa4uDgmJyeZmZnB4/FQVlbGAw88ELXzqO5kZWWFvr4+Tp8+zdatWykqKiIjI0Nqs+4iHA4zOjrKiRMnuH79Oj09PZSVlfG1r32NoqIicc6TMNYBkHTw6b0meEKhEMvLy7hcLhYWFpiamqK7u5ulpSVKS0spLS1lzZo1Ud1TKBQKMTQ0xNNPP01RURHf+ta3qKqqktqsaOJjf3AxD49ECDcLq9VKW1sbLS0tXL58mdHRUYqLiwmHw1RWVkbdFOfZ2VnOnTvH1atXGRsbo6mpifb2dnbv3s2mTZskET2CWHzppZfo6OjAZDJRW1uLw+HA7XbjdrtJTk7GbDbT1tZGQ0MDJpOJpKQkSec/CYfWlStXuHjxIufPn2d2dha5XM7ExAQNDQ1s2bKF7du3R3QDdjgcDA0N8eqrr7KwsMDc3BwejwelUineJD0eD16vl9bWVoLBIFVVVWRkZERtCE7wnh07dozf/va3ogCOJsHj8/mYnZ3lF7/4BTabjfT0dB544AFWrVpFYWEhcXFxyGQywuEwNpuN5uZmFAoFu3fvlmSmXSgUwufzUV9fz5o1azCbzVE370vA5/Nhs9kYHh7mvffeQ61WY7VamZubw263o1arGRgYoL29nU2bNnH//fejUqmiaj4c3H7mbrebnp4enE4noVBIapPuKWKCRwKCwSBer5fJyUlu3LjBtWvXaGlpobOzk4SEBAwGA3FxcVKbeRfC5tbY2CiKnMXFRex2OysrK8THx5OVlUVWVhYQudteIBBgcnKS5uZmGhoayM/PZ9OmTaSnpxMIBHC73TidTkwmE3q9HrvdTnt7Oxs2bKCkpERyQTk7O8vFixe5fPkyY2NjVFRUoNfrGRkZwWq10tLSQlVVVURzNzweDzMzMzQ2NhIXF4dcLhfzn5KSkkQvg9PpZGRkhJs3b5Kbm0tqamrUCh6Hw8H4+DgNDQ309fUxPj6O3W6X2iwRISejo6ODGzduUF5eTmVlJTt37iQpKelD07GdTifDw8MoFAq2bt2KTqeLuM1+vx+r1UpdXR16vR6NRhO1gmdiYoKOjg6uX7/OjRs3SExMFIciZ2dnk5qaitfrxeFw0NjYSE1NDRaLJeoEj9frZW5ujsuXL6NQKDCZTBgMBqnNumeICZ4IIbh+g8EgTqeTmZkZTp48yVtvvUVPTw+Li4vExcVRW1vLo48+yrp16yQ/jAUEsTMzM8Nvf/tb2tvb8Xg8pKSksLKyQmdnJ3l5eRQWFpKRkRHRTcLj8dDe3s7Zs2dZWFjghz/8ITU1NaSnp4u3Ya/Xi0wmw+Vy4XQ6ef7555mZmcHv90v2jMPhMMFgkNbWVs6ePcvMzAzFxcV89atfJTExkaNHj9LQ0MD169d56qmnUKvVEbPV7/fj9XoJBoOsW7eOkpISkpKS0Gg0ZGVlkZqaikKhwGazceLECS5cuMDCwoIYYokmhPdudnaW7u5u0SO1srKC0+mU2LrfEQqFWFxcpL6+Hp/PR21tLdu3byctLe2uzwnfx+l0YrfbUSgUOJ3OiAuecDiMw+EQQ4SrV6/GbDZjMpnEtS3k+CmVSjGpVopcNL/fT1NTEydPnuTixYuUlZURFxdHdnY2WVlZ7Nmzh7y8PCYnJ2loaOD06dNMTU2RkJAQVaEtQRT39vZy5MgRMjIyyMvLIzk5WWrT7hligieCBINB2traOHPmDEePHqW1tRWXy4VcLicjI4MHH3yQf/iHf8BsNouHWzS8bA6Hg97eXn7xi1/w/vvvs2/fPnbv3s22bdu4du0a586dIxAIcOvWLbZt2xZR79T09DS3bt2itbWVyspKamtrsVgsdyUk6/V6cRPOyMjAaDQil8slPaCDwSDLy8u8+eabuN1udu7cydNPP011dTUAVqsVm81GW1sbNpuNhISEiAmelJQU9u3bx+bNm4mPj/9E135RURHvvPMODocDn88XEfv+WNxuN1euXOHkyZPMzs6iVqtFj1S0YLfbGRoa4uLFi/zFX/wFNTU1H2tfOBymo6ODmzdvYjabJfGqhUIhpqenef/99xkfH6ezsxO9Xo/NZsPr9dLf34/dbken01FZWcmGDRvQ6XQRLxQIhUJcunSJ//qv/8LhcPDQQw/xd3/3dxiNRpRKJXK5XHyvDAaDmLvm8/miLlwUDAaxWq00NTWxuLjIl770JbZu3UpSUpLUpt0zxARPBPB4PFitVt5++22uXr1KV1cXQ0NDuN1uwuEwqampbNy4kUOHDmGxWCS7DX0UbrebS5cucfz4cY4dO0ZRURGHDh1i27ZtpKR9H8GPAAAgAElEQVSkkJOTQ1VVFVNTU4RCITQaTUTt02q1GAwG4uPjSUpKwmAwoFQqP/Ts/H4/CwsLnDlzBpPJRGJiYsRtvZNQKITL5WJubo6NGzeyfft21q5di1wuZ3h4mPb2drq6uvD7/eJtOVLI5XI0Go0odD4qcT4YDLK4uMj58+eJj48nLi4uajySH6Szs5NLly7R1NQEQF5eHsXFxaSnp0ts2e+Ym5tjZGSEQCDApk2bSExMvOuZC8m2U1NTNDQ0cO7cOXQ6HWvWrJEkpNHT00N9fT3nzp3D5XJx6tQpzp8/TyAQIBgMotVqUSgUKJVK3nzzTb773e+yc+fOiHoj/H4/S0tLvPHGG6ysrFBeXs6TTz5JcnLyXetaeM5er5eFhQUmJibIysqKuvXsdrsZHh7mzJkzopDMz8+PurBbNBMTPBHA4/EwMTHBpUuXaG1tZXZ2FpfLBYBSqaSwsJCqqirWrFnzoVi9VAgekVu3blFfX09DQwNOp5MNGzaQnp6OXC5nfn6ejo4Ouru7USqVZGVlRfzlk8vlKJVKsWfNR/37gUCA2dlZ2tvbaWtrY+vWraSnp0uabyKENq1WK9XV1SQkJDA5OcnAwAA3b97k6tWrLCwsUFBQgF6vj+jNWDgE7nyWwnpYXl6mv7+f+fl5RkdHaWhooKioKKIeqD+EYDCI2+2mt7eXN998k5aWFhYXF5HL5RQXF4uevmggHA4zMTHB4OAgaWlppKSkoNFo7uq3Mjk5SWtrK21tbUxOTlJYWEh+fj4lJSUR68FyZ3jw4sWLnD17luHhYUKhEE6nk8TERHJycsjOzhYrC202G62trZJ4dzweD6OjozQ2NlJeXk5tbS2rV6/+0IVImPgu5CbK5XLRCxwtezHA0NAQbW1tDA0NsW7duruec4w/jJjgiQDC5uvxePB4PPj9fvHvDAYDpaWlbNy48UPxeikJh8MsLy9z/vx5rly5Ql9fnyhqnE4no6OjuFwuXn/9dTo6Oli/fj1ZWVkRf/mEW6RCoSAQCNzVIygUChEMBrHZbHR1ddHQ0IDb7RYriqTswyNUWywuLorVOTMzMzQ3N3P16lXm5uYwGo2sW7eOhIQEyRuLhUIhPB4PPT09nDt3jsnJSebm5piYmKC6ujriouz34fV6mZmZ4dSpUxw5coTJyUkxZ6u0tJTk5GS0Wu1dPVikIhwOMzk5yfj4OHl5eRiNRhQKBaFQCK/XS29vL62trTQ2NtLT00Nqaiq7du2ioKAAs9kcUdv9fj9dXV1cuHCBa9eu4XQ6SUlJIT8/n6qqKrZv305lZSVarRaPx0N3dzezs7NkZ2dH1KMaDofxeDwMDQ0xODjIV77yFTZv3vyhVhSCqBwfH+fy5cvMzMyQmZmJVquN+OUtFAoRCoXE9ygQCIh7msfjoaWlhaamJubn5yktLcVsNkvqpb4XiQmeCJCUlMSOHTtISUnhhRdeoL6+no6ODsLhMKtWraKqqop169ZFjWtS6Ldz69YtXn/9dQYHB/F4PMTFxVFfX8/Q0BCJiYnI5XLeeecd1Go1u3fvFvtXRBKtVovRaESn04mHmiB23G438/Pz1NfXc+bMGTo6Ovj+97/Pjh07JK+CE0rSw+Ewhw8fRqfTkZKSQm1tLampqej1enJzc3nmmWeiolpEyG34z//8T4aGhkhOTiYrKwuLxYLL5cLlchEIBKJC9AgC4vz58/zsZz9jYWFBPEgMBgPl5eUkJCQgl8sJhULI5XIxwVYqe5eXl3E4HFRVVaHT6ZDL5bhcLsbGxnjuueeYnp6mtLSUp59+mr1795KVlRXRZy2s14WFBV5//XVaWlrw+XyUlJTw6KOPct9991FYWHiXoJiensbn8+F2u8nIyIj44ex2uxkfH0cul5Oenv6h90gQOx6Ph8OHD9PX10dRURGPP/54xPtKCXuuw+EgISEBuJ3HZ7Va8Xq9DAwM8MYbb3D9+nWAD3moYl6eP4yY4IkQCoWCoqIiHnnkEbxeL8PDwzgcDqqrq8UbZ7QQDAZZWFjgJz/5CYODg4RCIcxmM+np6axdu5YtW7aQnJyMzWbjl7/8pZgTkZ+fH3FbNRoNCQkJGI1G+vr6WFhYwOfzMTY2xunTpzlx4gQLCwvk5eXx5JNP8vjjj2MwGCTfIHQ6HcXFxbz00ks4HA4MBgPJyclYrVYuXbpERUUF999/PwUFBZLbCrefc2ZmJj/+8Y/x+/3odDq0Wi3Ly8s8//zz9PX1ERcXR3l5udSm4nQ6uXLlCi+++CLz8/OiF0fITfL7/fz85z9nbGyM5eVlvvjFL/Lggw9KJoLlcjmPPPIIW7duFQ/kYDBIb28vr776KiMjI3zve9+jqqqK3NxcSbwPy8vLDAwM8MILLzA9Pc2Xv/xlysvLKSoqIicnR8zZgdsH8ODgIMeOHePatWu4XC5RxEUSlUpFYmIifr8fn8/3oSKFUCjE3NwcR48e5cKFCzz++OPs3LlTkn1seXmZhoYGDh8+TFxcnNhIdXZ2VmxJsbCwANz2/Lz11lvs2rULnU4XcS/fvUxM8EQAmUxGKBRiZmaGuro6bt26hc/nQ6PR0NXVRWtrK2azmYKCgqgog1xcXKSzs5Ouri70ej1GoxGj0SjObFlcXGRpaYnh4WH8fj/FxcVkZmZKEnZRq9WsXr2abdu2sby8zPXr1zEajWLy4fDwMCUlJWzfvp0HHnhA3DykfsZyuRydTkd5eTl+vx+3283MzAwvvfQSBQUFbNu2jcrKyqjwmMDtNaxSqcjIyCAcDqNQKJDL5cTFxbFjxw7a2tpwOp3k5+dLLij7+/vp6upiZGREFDsKhYKUlBT27NlDdXU1gUCA6elpZmdnsdls+P1+0dsTaWQyGcnJycTHx4u/FyqfhoeH+d73vsf27dtJSUmRRDjAbQ+f1+slKSmJBx98kFWrVpGcnCx6V4WftxBCfvXVV2lpaSEcDkviMZHJZGg0GtLS0lCr1czOzrKwsCAmqi8vLzM+Pi5WzW7fvp0tW7awatUqSd65oaEhmpubuXbtGikpKaxatYrMzEzy8/MpLi6moKBArOS7fPkyIyMjYmPQAwcORFXFYTQTEzwRIhQKMTExQVNTExMTE5hMJioqKnA6nbS2tiKTyXC73ZSVlUkuelZWVhgbG2NhYQGj0YhWq0WtVhMMBpmbmxM7GI+NjREKhcjMzMRkMkmyESsUCjIzM9m0aZPYSG55eRmbzYbdbicYDFJRUUFVVRXFxcVRJSCUSiUmkwmHw8H09DQtLS0MDg7y1FNPsW7dOrGXkFQIicqBQAC5XI5KpUKr1Yo2hcNhlEol5eXl9PX1YbVaGRwcpKysTNKEz/n5eebn51lZWRH/TK/Xk52dTW1tLenp6aSkpKDX63E6nQwMDNDZ2Ul+fj5JSUmSNPHTarViTpHdbqelpYWuri4UCgX79+/HYrFImmQvk8nQ6/WsXbuW2tpasV2BgJBvJHSAvnLlCnK5nLVr10a8U7iASqXCYrGQkJDA6OgoIyMjFBQUoFQqmZ6epqmpiWvXronvXF5enhhOihSCIB8dHWVoaAiHw8G6deuorKzEbDaTmJjI6tWrKSgowOVyMTIyQlJSkniOtLa2kpeXJ9nMvXuNmOCJEOFwmLGxMUZGRgiFQqxfv55nn32W119/nRs3btDc3ExHRwf//M//LHa3lWrxejwesZGc1+tlZWVF7LFy7do1lpaWcLvd4kGYlJQkaYdVs9lMQkKCuCmMjo6ytLTEysoKycnJ7N27l8rKSkkOsk9C2OxGRkY4f/48x48fZ/369Rw8eJCMjIyoqHpyuVwsLi6iUqlISUm5SzAKjR2zsrKoqqqir6+Pc+fOUVJSImm14Z0hLMFGs9nMqlWrKCsrw2q14vF48Pl8LC0tUVdXh8vlYt++fdTU1JCZmSmJ3QJjY2McP36c2dlZNm3aREpKiuQ5XAaDgaysLPEQvjN8JSS0T09P097ezosvvsjU1BSPPvoo999/P8XFxZKsBaEzeFZWFq2trVgsFioqKjCZTLS3t3P69GmuXbuGwWCguLhYspCmMD9tYWGBVatW8Vd/9Vds3rxZbHwooNVqSUhIoKSkhH379vHCCy+wsLBAfX09tbW1MbHzBxATPBFESFI1m82Ul5dTVVVFYWEhJ06coK6ujrq6OjZu3Mj+/ftJS0uTzBshDNuUyWQsLi5is9nu+nutVotGo0Gr1bK0tIRCoZDUcyKEW8xmM2azGZvNhs1m4+rVq3znO99hw4YNUevy9fl8HDt2jOvXr6NUKvnWt74VVTOpRkZGePnll4mLi+OrX/0qubm5H/qMWq1m1apVLC8vU19fH9GeQR/FqlWrqKysZGBggK6uLhYXFxkZGWFycpKTJ0+i1+tZXl7G4/EAt4XRysrKhyoopUBoKjgwMIDZbObAgQOSix34nQfqg2G/UCjE4OAg77//PufPn+fatWsEg0F+/OMfs2fPHgoKCiSzWfDwFBYWcvHiRZqamigvL+eBBx5gdHSU8fFxPB4PVVVVWCwWyS4YQriwvLycvXv3smPHjo8VLwqFAr1eT2lpKV/5yle4evUqo6OjBINBySs57wViTyiCCOEhh8PB4OAgk5OTJCYmsnv3buLj4xkeHua1114jPT0djUYj2TTv5ORkampqeOyxxzh37hwrKyt3Nb+zWCzk5uayZs0anE4nFRUVknb7/ODmMDMzg91up6CggPvvv1+c/RRNNyCh6uXkyZPcvHmThIQEnnjiCXJycj6ycaJUZGVlkZOTw/DwMIcPH+ZrX/uaGM64c4MV7BVyYaQkMzOTgwcPUlxcTENDAydOnGBubg632w3cDm/l5+eLzSr3799PeXk56enp4nBUKfD7/dhsNt577z3S09Opqqpi9erVgPRrV/CUCR3KA4EANpuNzs5OXnzxRfr6+giFQhQXF7N161b27t0reUhWLpej1+spKCjg+vXrOJ1OpqenxY7WU1NTmEwmsaO41Jc2vV5PSkqKmN7g9XoJh8NiE8oPPsvS0lIsFgvLy8tRE6qPdmKCJ0LI5XJWrVrF1q1b6enpYW5ujt/+9rfk5+ej0+mYm5sTNxW/3y/p2AODwUBeXh6PP/44WVlZzM/P43K5RNGTk5NDXl4eBQUF+P1+Vq9eHTVN3ADxYMvPzyc3NxeNRiP5gfFBfD6f2CY+OzubkpISqqur70oAjQbi4uKorKwkHA7T09PDa6+9RnZ2NmlpaZhMJmQyGT6fj+7ubsbHxz8U9pICrVYrNhY0mUykp6djt9vxer2EQiGxskWv14uVZUKzP6lsF8qjh4eHmZycZM+ePWzYsEFMZI4WQqGQ+LMWOoJPTEyQmJhIYWEhGzdupLKykvT0dLRardTmolAoKC0tJTExkaWlJW7cuIHT6aS/vx+LxUJlZSXbtm2TdI9QKBSoVCqsVqvoIRMqIT8pp0gY6GuxWKJqz4hmYoInQsjlclavXs1DDz1EUlISLS0tHDt2jJycHEwmE8FgEKPRSHFxMUlJSZK6J9VqNcnJyTzwwANs2rQJq9WK3W4X28YXFBSQkpJCXFyc+KJF0wsntLbPz8+/K98gWhC653Z3dzM8PMzjjz/Ohg0byMvLk9q0u5DJZKjVajZs2IBCoWBycpK33nqLzMxM8vLyxOaNLpeL3t5e1Go1O3fulNxDJZPJxBCMxWJh06ZNH/u5j/q1FIRCIRwOBx0dHQCsW7eOsrKyqMjjupNQKERPTw9NTU309vYyPj5OcXExa9euZfPmzdTU1ESNSBO6hZeVlZGfn097eztNTU10dXXh8Xiora3l4YcfpqqqStKcSaVSicFgYHFxkVOnTqFUKlGr1eTk5Ij9zj6OSA4V/iwQEzwRQtiEDxw4wObNm5mamqKzs5OOjg7kcjnJyck88sgjrFu3DqPRKHkOh3DYZWVlkZWVJaktfywymYy4uDhxXpbUh9kHEQYvvvXWW5SXl1NeXi55ouwnYTQa2bhxI9nZ2Zw9e5b33nuPU6dOsbKyIoqbPXv2sGfPHvbv3x81LfmBjwwFRCM+n4/p6WnOnDlDeXm52EU52pDL5WIFodvtRi6Xi/O8hNy+aEImk1FQUMDTTz/N2bNnqaurY2FhgS9/+cscOHBA8tYPwtrMyclhamoKh8NBRkYGGRkZpKamxgaD/omR/Z4EQ2mzDz+DCFUNoVBIbIgFt92aarX6ruqWe2GjjkacTqdYQSZUXkTTsxRme129epW9e/eKk5ujycY7ETrSCqXHwvMNhUKizUIjQqFsPVq/S7QyOjpKfX09f//3f8+LL75IdXV11DWUE86KYDAohreF9gofHMQZLQg2e71ePB4Pbrdb9KZrtdqPnb8XaYScnUAgIM7xEkr5o+2Z3gN87AOLCR4J+eCzjy3sPw3CAR2twlEo452fnyczMzOqPCKfxJ1zyoT/f/AZ3wvfIxqxWq309vbyzjvv8I1vfIPMzExJWz181vjg2o229frBdypa7LpHiQmeGDFixIhW3G43S0tLjIyMUFZWhk6ni5UZx4jxvyMmeGLEiBEjRowYn3k+VvBIH7yMESNGjBgxYsT4lIkJnhgxYsSIESPGZ56Y4IkRI0aMGDFifOaJZcXF+IP4qFyve6mSIBQKieW00dib56OIVfH937mz+iUQCODxeNDr9ZJM744RI4a0xDw8Mf5ghEMjFApJPiDyj8XhcIhTyb1er9Tm/MEIIi3G/w273c6tW7f42c9+xtjY2D21BmLEiPGnIebhifF78Xq9zM3NcenSJU6cOMGePXuorq6mrKxMatM+kXA4TDAYpLe3l/fff5+LFy9SW1vL9u3bpTbtEwkGg9jtdvr7+zl8+DBr167l/vvvJycnJ+aV+CMQ5tLV1dVx5swZWlpasFqt7N27F4vFEhWznmJEhpWVFRYXF7HZbOLwU+HSFgqF7hooGw2NCGN8OsQEj4Tc6SWJ1oZYAOPj4zQ1NfGb3/yGwcFBVq9eTWlp6YdsjjbC4TAzMzO8++67XLlyhZmZGUwmU9RuaIJAGx4epru7mxs3bnD+/HkSEhLweDxSm/eRfJynLxrWRDAYZHFxkePHj9PQ0MD09DRGoxGNRhO1ayDGnw6hAen4+DjXrl2jv7+fyclJPB4Pfr//rq73iYmJbNmyhfLycoqKiu6aExjjs0NM8EQI4WAIBALiNPRgMIjT6cTlcuHz+QiHwxiNRhISEtDr9VEzl2Zubo7u7m46OjpQKBSsrKywsrJCKBSKyoNDEA4ul4vr169z+vRphoeHsVgs5OXlRd0wUfhdjtHCwgKNjY1cv36dmzdvMjQ0FBUhrTtb9LvdbjGsKawHj8dDOBwWB3ZqtVrJn3M4HMblctHc3Mzg4CAymYw1a9ZgMpmitqmfcEgLP/NoGi8g2OXxeFCr1SiVyo98/4W1IogK4XOR/g7hcBiv10tzczPvvfcePT092Gw2AHEiuc/nw+12o9frmZmZYXFxkbi4OIqKiu7qJB7js0F0vvWfMe7cAObn57FarVitVhwOB62trfT09DA9PY3f76e6upo9e/ZQVlZGXl5e1Lxw8fHx7Ny5UxyLINgbLaLsgzgcDrq6unj22WcZGRnBYDCQlpZGeXl51B12Qm6U3W7nypUr/Pd//zcDAwMsLi6iUqnIyspCp9NJthbuXL9jY2N0d3fjdDoBMBgMXLt2jaGhIQKBAKtWreILX/gCxcXF6PV6yaemGwwG8VBOSUnhkUceITs7O+rWANwtKpeWlpDJZJhMJtRqdVR4U0OhEE6nk56eHrKysjCbzR8bFgwGg1itVrxeLxaLBaPRGGFrb6/Xubk5fvWrX9HY2IhMJiM3N5fi4mLkcjkOh4OFhQUGBweZnZ3lzJkzLCwsYDAYKCwsjPhl7pM8/p9EtJwR9wLR99Z/BhFyMl544QWam5vp7+8XEydVKhUlJSXk5OSg0+l47bXXOHXqFJ///Of50Y9+hFqtlnxBb9q0iTVr1jA/P09PTw9nzpxhdnYWj8cTlYJneXmZxsZGfv7znzM/P08wGKS4uJiDBw9G3UBGuO316+/v58KFCxw9ehS1Wo1Wq0WtVrN69Wp27dol6eTsYDDIzMwMN2/e5N/+7d8YGhoSJ9Knp6cTCARQqVQEg0Hq6+tpaWnh3//93yktLZXUyyN4eHw+H3K5HIvFwtatWyX3PH0c4XAYt9vNb37zG27cuEFWVhZf+tKXyMvLk9o04Lbgcblc1NfXs2XLFnFY7EfR39/PK6+8gtVq5Zvf/CaVlZURf+/cbjcDAwNcuXIFgM2bN/OFL3yBz33uc7hcLjHkefXqVX7yk58wNzdHX18fb7/9Ng8++CApKSmoVKqI2hwKhZibm6O/vx+ZTEZCQgK5ubkoFArRZpVKxdzcHAaDgYSEBBITEyNq471MTPB8yni9XgYHBzl27Bi//vWv8fl8ZGVlsW3bNvLz80lISCA9PR2TyQTcVutNTU0MDg7S2tpKVVWVxN8AVCoVCoWCxcVF3nnnHZRKJRaLBZ1OJ7VpdyEkqV66dInz58+zuLjIU089xYkTJ8jNzaWioiKqQnDCLa6xsZH29nZGRkY4dOgQb7zxBm63G4vFwmOPPUZmZqYkwjIcDjM/P099fT3Nzc20trYSDod55plnyM7OJikpCaPRKH6PiYkJ6urqaGtrEzdnqcRFIBBgaWmJ06dPMzc3h8VioaioiOTk5KgJEd2J1+tlenqaY8eO8dprr2EymcjPz0er1eJ0Ojlz5gwqlYrs7GwqKiqAyN/sFQoFJpOJgwcPYrFYiIuL+9BngsEgy8vL/M///A9dXV2kpKQQHx8fUTsFhDXgcrkoLS2lurqaHTt2YDKZiI+PJxwOo1ar0ev1+Hw+0fa+vj5aWlrYuXNnRAVPOBzG6XTy5ptvUldXh8vlQqPRYDQakclkYphTpVIRDodJSkqiuLiYjRs3UlNTA8S8Pb+PmOD5lLFarbS3t/P+++8zNjbG+vXrqampYceOHaxatQqDwUBcXBwajQa/3095eTltbW1YrVZ6enqoqqqKiliy3+9ncnKSlpYWtmzZgtlsjvjt55MIBoNi6fm1a9cYHR2loKCA5ORkcnJyWLVqFTk5OVKbKSIkTE5PT3Pz5k0WFxfJzc0lOTkZm82GWq1m1apVbNmyBYPBEHHh4Pf7WVpa4tKlS5w8eZKenh5cLhe7d+9m//795OTkYDQaxc3XZrPhcDhwu92kpaVJ3uvI7/djs9m4evUqfr+fdevWUVVVRXx8PCsrK+JhFy2ifWFhgc7OTt5//33m5uZYs2YN+fn5GAwGvF4vjY2NqFQqPB4P5eXlkjxbuVyORqOhsLAQhULxocuDcOEYGRmhqakJnU5HdnY2iYmJktgr5ByFQiEMBgMpKSlkZGSgVCpRqVT4/X78fj9TU1NiXhrc9gx5PB7x95G01+fz0dPTw40bN7Db7SgUCtHe5ORkEhMTiYuLIyEhgdHRUTweDzKZjOrq6qi6zEUrMcHzKSEkH/b29nL16lWampqwWCwcOnSInTt3UlpaetetPRwOI5fLMZvNqNVq7HY7Q0NDUSF2BFf74OAgc3NzJCYmkpycHBUvmPCc3W43fX19nDhxgubmZgwGAwcOHODChQsUFhayZs0aUlNTpTZXREiovH79Oh0dHRQWFrJ//37efPNNpqenKSgooKamhrKyMpRKZUTXgPA8Ozs7efnll2lpaUEul1NRUcGDDz7I6tWrMRqNoggLBoNMTEzQ1tZGZ2cnTz/9NBaLRdLQkcvlYnJyksbGRjH/bM+ePYTDYfr7+wmFQiQlJZGdnS0Kd6nes2AwyMDAAJcuXaK5uZmNGzdy3333UV1djU6nw2q10tvbi0qlIikpSdI9QSaToVarxeqmO3NNBA/FjRs3mJycZPfu3WzcuFHSkIuwR93pHYHboSO73c7o6CjXrl3D6XQSCoVEj4rgCYxkYUYoFMLn82G323G5XHg8HpRKJUqlEoPBwLp16yguLiYtLY3k5GTOnDmD1Wqlq6vrnuuLJhUxwfMpsrCwwLvvvsu7776L1+vlG9/4Bo8++iiZmZkfeokED8WpU6eYnJyktLSUoqIiycUO/K4PT1NTExqNhtLSUgoKCqQ2C7i9SVitVm7dusU//uM/srCwwP79+1m7di0ul4u6ujq+/e1vU1RUhFqtltpcEafTSXd3N6+88gpPPfUUOp2O3/zmN/zrv/4rZrOZAwcO8MQTT3xk2ODTJhQKMT8/z/Hjx5mYmCA/Px+Aqakp/vZv/5aHHnqIsrIysrKyUCgU9PT08N5772G1Wvnc5z7H1772NUwmk6Rrd2xsjPr6evr6+vjLv/xLCgoKmJ2d5eWXX+bdd99FqVRSVVXF448/zu7du9FqtZLZOzMzw/Hjxzly5Aipqak8++yzFBQUoFAoGB0d5f/9v//HyMgIe/fuZdu2bVFx0XA6nSwvL2O320UPikqlYmZmhhdffBGfz0d5eTnV1dWSCV+hSETwnHi9XjHMOjs7y5tvvsmRI0e4cuUKwWAQg8FAQUGBWJwxOjpKeno6FoslIvaurKwwMDBAW1sbbrcbpVJJdnY2X//619mxYwe5ubkkJiaiUCi4desWQ0NDJCcnc99990VtXlq0ERM8nyKnT5+mtbUVm82GyWSitrZW7APzwc1ViDcPDQ2J4YwNGzYA0sdlhbDLuXPn2L9/P0VFRSQlJUlqk8DAwADvvfceJ0+exGq18vWvf509e/YAcOLECQwGA5WVlVGT+CkwOzvL22+/zY4dO8jIyKCjo4Njx44RDAbZt28fGzduJDU1VbJQgF6vp7q6mgcffBCdTsfKygqjo6NMTk4SCARobW3l1q1beDwejh07RmJiIps3bxbFjtSjG5aXl5mamiIUCok5SHK5XAzLeb1efD4f7777LlVVVZIm3w8NDTE3N4der+fBBx9ELpfT3t4uJtEeP1uXfDIAACAASURBVH6cJ598kgMHDlBWVibpcxXCRGfOnOHixYt0dHSQ8v+xd+bBcZ1V3n66W61u9apWq1v7vrTU2mUtlo0t20lsZyMQM0ACAQaGQMGwDDVLUcxC1cfUVA1UTQ3DLAGKbQJhwoQQ4jixHceygx3LsiTLsmxrsWzJ2tVqqaVW78v3h+veUUKchAHrXmfuU+VKylKVT99+7/ue9yy/43Ty6U9/msLCQoLBIBMTE3R0dFBWViaZ4ysUrF+9elWsRRseHubUqVNEo1GOHz/OyZMnGRwcJBqNotfref/738/evXvZtm0bly5d4sknn+Tuu+/mAx/4wG1P3yeTSWZnZ3n55ZcZHx8XO2BTU1NxOBxUVVVhNBqJRCLcuHGDb33rW+Tk5LBz5062b98u+Rlxp6A4PLeRSCQi6uvo9Xqx6l9YnEIYcn19nYmJCQ4fPsz8/DzNzc20tLSQnZ0tpfnATUdsbGyM/v5+otEo27dvJysrS/K2XiEl9PLLL9PV1cXly5dRq9WMjY2hVqsJh8OcP3+etrY28vLyJG+R3kgymcTv93Px4kUKCgpYWVnB5/ORlZVFIBDA6XSSnp4uWX2JWq3GbDbT2NgopqbC4TCFhYUsLy+zvr5OJBLB7/czNjaGx+OhpqZGdCyldnYAsbvFYrGwtLSEwWCgoKCAqqoqmpqaOH36NAsLC6JOjJQI6ZZIJMLIyAgnTpwgMzOThYUFzp8/T05ODu3t7ZSVlcmi5kilUhGJRPB4PAwODlJQUEAoFCIQCLC0tEQwGMTtduN0OiV9toKNyWSSlZUVent7Rf2doaEhJicnxXouof4oFArh9/s5e/Ys58+fp6ysjJWVFRwOx22312w243K52LVrF9evXxfnvq2srIj6R1NTUxw7doyJiQk+8IEPUFNTo3Rp/Q4oDs9t5I2FfcL/b8zBh0IhMY/8zDPPkJKSwvbt22lpacFqtUpit2Aj3LwpDw0NMTg4iNPppLW1VfJ0BfxP2uX48eOMjIygVqvJysri+vXrXLt2Db/fz8rKCn/1V39FZmamrAqshc3V6/Xi8XgwGAwUFxezbds2tFqtKNQmVZharVZjNBqpqKh43d8Lm74w38vr9bKysoLFYqG2tpb6+npJUnBvhsPhoKamhpycHFZXVykvLxffq9XVVdbW1lCr1WInlJTr2WKxkJOTg91u58aNG4yNjaHT6VhbW2N2dpbOzk6amppkU4OmUqmw2+04nU50Oh2xWIz19XWmp6cZHR1Fp9PhdrsljQJvFB+Fm+mioaEhUS9KqNkRiMViXLt2jXPnzrG+vk5XVxczMzN4vV58Pt9td3hUKpUomwDQ19fH4uIicPN9DIVCLC0tMTAwwOHDh0lPT6ehoYHi4mJZ7W1yR3F4biOLi4sEAgHC4TBLS0uMjo6SkZGBVqsVnZ/R0VGeeuopjh49ytjYGI8//jj79++nvLxcFk7FuXPnOHv2rFiEWFxcTFpa2tsWyd1O2wWhvlOnTjE+Pk5eXh7Nzc1s27aNZDLJ6dOnuXDhAn6/n+bmZgwGw22z5X+DWq3GYrFQX19Pb28vzc3N3H333bS1teH1ellaWhJrI+SYmxdSsoFAgBdeeIGGhgY6OjpwuVxSmyZis9moqqqipaWFlZUV9uzZQ0lJCcePH+ef/umfsNls3H///Tz88MOSijoC1NXVYTQa2bVrF8vLy+zYsYOxsTECgQD5+fl84QtfID8/XxY1aEJLf0tLC0ajEYPBIKqwT0xM0NfXR2NjI1u2bNm02pdboVarRZ2gZDJJKBQiHA6/6d6VSCQ4e/YsZ8+eFf/ObDYTjUY3bdCsMM+rpKSEAwcOiB1mwgXp0KFDHDlyhMHBQb797W/T2tqqRHd+RxSH5zbynve8h8HBQTweDzMzM/z5n/85W7ZsEfOuGo2GJ554ghMnTuD3+3nf+97Hl7/8ZbFTS0qSySRra2scPnyYS5cuEQwGAfB4PASDwd86iNVqNVqtVmxVvt22JRIJ6uvr+dd//VesVisOhwOr1Uo4HGZ0dFSs3cnLy5P8Wb4ZxcXF/PVf/zWrq6s4nU6MRiPr6+vMz8+TmZkpeZrl7Zienqa3t5ehoSEeeeQR8vLyZJFuEQiFQqysrABQUFBAV1cXP/3pTxkaGiKZTPK+971P7DiTmpSUFMrLyyktLSWRSDA8PMzTTz9NJBLh4YcfpqioSBaFyhuxWq1s2bKF6upqvF4vU1NTPP/88wQCATQajeRpTUEYs6amRrTHarVis9mYnJwkHo9jMplwOp00Njayf/9+5ufnxZbwcDjMPffcw/79+8Wi/c1EqCkT9rru7m66uroYGxujtbWVpqYm2V3k7gTkvave4VRUVHDXXXcRDoc5ePAg169fx+/3Mzo6yqFDh4jH41y6dAm9Xi+qgAr6NlJHdwSH58aNGywvL7O8vMyJEydYWloSb/hqtVpspy8vL6exsZEdO3aQmZl522bnLC4u4vF48Hq91NfXk5OTg1arFRWpL1y4wKVLl1heXqayslLydMWt0Gq1OJ1ObDYbOp2OUCjE3Nwcc3Nzos6NHKM7cHNsx7lz5zh06BDBYJDa2loyMjJkdSgHg0F8Ph/p6elMTk5y9epV5ubmiEaj3Hfffdx1112SK0ELqFQqMf2dSCQ4c+YMRqORqqoqWltbJZlD9Xao1WpxnpZeryccDmMymdBoNGJNjNQYDAZKS0tJTU0lHA7j9/uJRCJotVra29tpbW2loaGB8vJy8vPzCQQCeL1eHnjgAdRqNUVFRZKJfgrfdzQaZWpqip/+9KdMT09TUVHBRz7yEex2u+wvRXJEeWK3kYyMDJqbm1ldXeXatWtcvHiR2dlZ5ubm0Gg0xGIxMjMzaWhooLOzky1btshilISAIMefnZ0tts1PTk6i0+lEfQiVSkVKSoo4zft22764uCjOvtm2bZv47wn5+jNnzjA5OYlaraayslIWzuObIRwYQvRJqCswGAxUV1fLRufozZibm+PChQv09/djNpspLS0V1WDlQiKRIBaLodFomJmZYX5+nnA4TFFREfv376e2tlbylMsbiUajLC4ucuHCBUpLS6mtrSUnJ0dqs26JcOnZ6BCoVCp0Op0sIjypqaniIFuheUSr1eJ2u7n33nvp6OjA7Xa/btxMLBajtrb2dZcoKfWZhPl6/f395Obm0t7eztatW2V7kZM7isNzmxAWY0VFBSkpKcTjcZ544glmZmbELpeUlBTa2tp4+OGHec973iPpvKQ3olarycjI4MEHHyQnJ4eRkRH8fj979uwhNzcXs9ksHtgpKSk4nU6cTudtD7POzc1x7do1lpaWXid6FovFxAGAPp+PhoYGduzYISsH8u3Q6XRs27aNkpISSYYtvh3CzX1wcJCBgQFmZ2fZsWMHBQUFsgqvC00BggK00EpfUFDAfffdx0MPPYTVapXVDVno3Dtz5gzXr1/nnnvuwe12y8rGWyGMxfB4PCQSCex2O2lpaZJHzzQaDSaTCbvdTjQaxWw2U11dzWc+8xlRIuSN0RutViubIuBwOMzU1BRPPvkkarWavXv3ctddd+F0OqU27Y5F/m/THU5qaiqVlZUUFxfjcrn4t3/7N/r7+/H5fLS3t/ONb3yD4uJijEaj1Kb+Fnq9nn379rF3717xsHvjJrbZzkRhYSEqlQqv10s0GhUjOGtra7z00kuMjIywc+dO2dRnvFOsVisNDQ3U1tZKflDcimQyyeLiIj//+c8ZGhqioKCAz3zmM6IYmpwYGBjgBz/4AV1dXSQSCfbt28f999/PgQMHZPmuRSIRZmZmOHjwIJ/85Cdpb2/flFbo3xdhYOw//uM/cuXKFXQ6HS6XC6PRKLmzlpaWRkVFBZ/73OeYnZ2lqKiIHTt24HK5JLftnbCysoLX66Wuro4DBw7gcrnEmYsK/zvk/63f4QgOQWpqqhiKnJ6exu/3U1FRQVFRkeRdIm+GYI9wU36zn0mB0K2iUql4+eWXaWtrw2q1olKpsFgs4mHhdrtlmxJ6M4TnLDgOclsPiUSCYDDIoUOHuHjxIjqdjubmZmpqajZ99MXbIYw9gJt1HPv27ePBBx8URzWA/J6v1+tlcXGRnJwcmpqaJJs/9bsSi8U4efIk4+PjBINBcnNzaWtru+UU9c1EkFf4oz/6I1HIb2NkT+7P126309TURHFxMVlZWUoa6w+A4vBsAsIitVgs1NXVUVpaSiQSwWazYTAYZH8wy+kl0+l0ZGRkEI/HWVpaEp0fvV5PbW0tVVVV4iRvOdn9TpCzvfF4nPX1dc6fP4/P56O4uFgU9pOb3SqVitLSUt773vfS3NwsOmYOh0N2kSgBoaC2vr4eh8Mhm7TKW7ExpZyfn09JSQl1dXWUl5fLwgkWisEF/SKh5uhOQavVYrVaMZvNsnie7wYUh2eTEIrf7Ha7rGp17jRUKhVGoxGj0UhhYaHYwZKSkkJTU9Prfk/hD0cikRDFz9LT0ykuLqakpESWLf9qtZrq6mqqqqpELSMpi0/fCYlEAr1eT0tLyx1xCRJQqVSUlZWhVqux2WzU1NSQl5cnm2ctOD13IsIauFPtlyOqt2kflL63UEFBQXJisRiBQIDTp08TDofJy8ujuLhYdp1OdyoboyUKCgq/F7d8iRSHR0FB4W0RitaF9l5BzE25ff5hUBweBYU/GIrDo6CgoKCgoPCu55YOz52RKFZQUFBQUFBQ+D1QHB4FBQUFBQWFdz2Kw6OgoKCgoKDwrkdxeBQUFBQUFBTe9SgOj4KCwv855DLRW0FBYfNQhAcV3pJkMkkikSAej4sHhDCcURD1EsT/5IZgr2C7MC0ZlPbf/6sI68Dv96NSqcQhl8p6+P0Rnm0sFhOVgZXnqiAnFIdH4S2JxWIsLCywsLDA6uoqarVa3NCsVis5OTnYbDbZDuNLJBJMTU2xtrZGMpmkoqJCFnN+FKRjZWWFn/70pxiNRvbs2UNRUZHUJr0riMfjBAIBrl+/TllZGXq9XtFpUpAV8jyl/g8SCASYmppicHCQjo4OnE6npE6EIDJ36NAhjh07Rl9fHx6PB41GQyQSITU1FafTyZ49e/joRz9KXl6e7ByJRCLB5cuX+c53vsPVq1exWCz87d/+LW63+46YVSR34vE4q6ur/PrXv6axsZGysjJMJpPUZt0SIfpw/PhxDh8+TGFhIfX19bJ0eARb/X4//f39XLp0ifT0dMrKymhra5NlVDUYDDI6OspXv/pV/uZv/ga32y3bMTobU5obI9Zye6ZvRNiX//M//xOr1UpVVRVut1txLN8hisNzm4lEIkSjUSKRCOvr6+j1evR6vRhKh5sH8+rqKufPn6evrw+Xy4XdbpfU4YlGo/T39/OLX/yCgYEBpqenCQaD4gA+vV5POBzm8OHDFBQUsG3bNioqKmTz4kWjUVZWVvj5z3/OuXPn0Gg0lJaWYrPZZLGpCanCZDJJMBgkGAwSCASIRqOkpqZisVjEoYFyRXB4jh07htVqJTc3V9YOTyQSYX5+nsOHDxMOh8nMzCQnJ0dqs0SEQ3h2dparV68yOTnJxMQEFy9eZHZ2FovFQmVlpTgoV24DJSORCF6vl6GhIVZWVohGo1KbJJJIJAgGg/h8Pubn55mYmGB+fp7l5WXC4TB2u5329nZKSkpEJ01Oz1YgGo2yuLjIsWPHqK2txel0KrVovwPy3U3vcJLJpHjorq+vE4lEWFlZwWazYbPZ0Ol0onMQi8XweDx0d3czMzNDMBgkkUhIansoFOL48eN0dXWxsLBAPB4HwGg04nQ6SU9PR6/XMzMzw6uvvorZbMZms+FwOCS/KSWTSTG0fujQIdbW1qivr6e1tZXMzEzJnLKNNUXCIE7hv0tLSywuLhIMBjEajdTU1FBRUUF6eroktr4TBEd9fHyc1dVVSdfs2xGPx1lZWWFgYIBTp05RWlpKQUGBOElbapLJJPF4HL/fz9mzZzl16hSXL1/m+vXrrKysoNVqSUlJwePxUFRURGVlpeyc4VAoxMrKCoFAAJCXw7CyssL09DQjIyNcuXKF8fFxZmdnWV5eJpFIkJWVhVqtRqPRYLPZZDm8NZlMsra2xujoKJcuXcLlcin1Z78j8npj3mUsLS1x+fJlfD4fFouFaDSKwWD4rQJgn8/H6OgoR44cYcuWLWi1WkkjJYlEAp/Px49//GM8Ho/o7KhUKtxuN/fddx9lZWVoNBqOHz9Ob2+veDt96KGHJJ+gHY/HmZ+f5/jx40xMTNDZ2ckDDzzAAw88gMFgkMQm4fuORqOsra0xPj7OoUOHmJiYYGZmhunpaW7cuMHa2homk4lPf/rTPPbYY1itVkBeh4dALBZjaWmJwsJCnE4nRqNRapPeFOGguHz5Mt///vcZHx+nvb2dnJwc2TgNQiF1X18f//AP/8DIyAjBYBCz2UxjYyMNDQ0sLCwwMTHBM888w4c//GFZ1cgkk0lWVlaYmZkhNzeXrKwsWaS4hfeup6eHw4cP88ILLzAxMUFVVRWlpaV0dHRQUlLCysoKV65cQaPR4Ha70el0Elv+28RiMaampjh48CDJZJKOjg6qq6tlswbuBOTxtr9LWV9fJz09nZycHMrKysS8u/BHSGuMjY0xODhIJBLhkUceobCwUNIak6WlJQYHB8XIjlqtxmAwUFJSwt///d9TX1+P1WolkUiwfft2fvjDH3Lx4kWeffZZmpubKSkpkfQlHB8f59ixYzz55JOUlpbyyCOP0N7eLnk9QSKR4M///M+5ePEiS0tLxONx9Ho99913H3l5eajVakKhEN/5znd44YUX8Hg8fPvb38ZsNktq91uhUqnQ6XRotVrZ3oqnp6f55S9/yauvvsri4iJbt26lqKhIVs9VSGl/4xvfYHx8nLa2NlpaWujo6KC5uZmlpSWeffZZrly5IqZn4vG4bA67WCzG3Nwc165do7GxkezsbNLS0qQ2i2QySX9/P9/5znfo7e0lHo/z8MMP86UvfYnCwkIMBgPJZJJ//dd/xWq1kp6eLhsn+I1MT09z6tQpfv7zn/PII4/gcrmw2WxSm3VHIc9v9l2Cw+HAbrej1WrftB06mUwyODjIwYMHOXPmDA6Hg6qqKoxGo6Q3+sXFRS5cuEAgECCZTOJwOKirq+OTn/wkTU1NWCwWtFotyWSSrKws2tramJ6eZnh4mNHRUQoKCiQpqhSiTOfPn+f06dMsLy/zmc98hoaGBjHVJiXJZJKWlhYKCgrE52q1WikvL8dqtaJSqfD5fGLkZ3l5WVJ734jgoA8MDBCLxVCpVKyurpKSkiLL0HokEuHatWs8//zzzM7OUllZyaOPPsqpU6dYXFxkYmKCYDCIXq+X3Pbl5WWuX7/O5cuX6ejo4MCBAzQ0NJCZmcm1a9c4dOgQfX19qNVqPvCBD8juYF5eXmZ8fJzR0VF27tyJ0WiU3BlLJBJEIhFOnz7N1NQUNpuN5uZmPvWpT+FyudDr9ayurtLd3c3p06f5wAc+QGNjo+wcd6FQ+cKFCwwPD5Ofn88DDzxARkaG5Ov2TkM+b8y7EKPR+LqD3+/3s7i4SCQSETsDXn75ZXp6evB6vezcuVN0kKQiFouJm280GkWlUlFQUEBrayu7du0iIyPjdRtCLBYjFouJRdkzMzOS1nL4fD6x9sFqtdLW1iaG16XeHFQqFU1NTYRCIVJSUrDb7RiNRkwmk+hAGgwGbDYbMzMzJJNJ2RxqQtfQ9evXee211zCZTOTk5KBWqwmHw4TDYWKxmNRmioTDYTweD7/5zW/weDxkZWVRVFREeXk5hw4d4saNGzgcDpaXl2VRuCxoXanVarZv305NTQ1ms5nJyUmOHDlCd3c3Go2G5uZmOjs7SUtLk3w9A2LR/aVLlxgeHsbn81FVVSWL9y2RSLC+vs7FixeJRqMUFRWxa9cumpqaMJlMeL1ehoeHefHFF4nH4+Tl5ZGbmysbhycWixGNRgmHwywtLXHlyhXW19fZvXs31dXVslkDdxLy2E3fhahUKvGwEm7Gk5OTnDx5Eq/XK+aWf/GLX+D1eikvL+fBBx8kLS1N0hdOKKK9ceMGiUQCo9GI2+1m27ZtrzsYEokEsViMiYkJenp6mJ6eFuuRpOgaEKI7165dY3h4mOXlZaqqqigpKSElJYVEIiFpK68g0lhXV3fL3xFs1Gg0pKWlYTKZJK+HEojH46ytrXH06FG6urrEdm6TyYTP5xOLVeWQJkomk3i9XgYHB/nFL37Bvn37aGxsJD09neHhYY4dO8b6+joOh4O5uTlZODxpaWlkZWVRV1fH7t27SUtLY2hoiBdffJFDhw5hs9nYv38/733ve2lqapJFh5awr01PT3PkyBEGBgbQaDRUV1ej0+kkdxyENXv16lXS0tKoqalh9+7dWCwWIpEIo6OjHDt2jGeeeYZHH32UvLw82dShCY0XS0tLzMzMMDExwdDQEDqdjgMHDmCz2SSPoN2JKA7PJhGNRjl8+DDf//73mZiYIBKJiDfi/Px8srKyxLSGlMzPz3P58mX6+/sBaGxs5J577qGzs/N1v+f3+xkfH+f//b//x8WLFwmFQhQWFtLW1iZJhEq4af7qV79ifn6e7Oxs6uvreeaZZ9iyZQsVFRUUFBTIepMQuuOmp6dxOp00NzfLxt6lpSXOnj3Lt771LbZt20ZdXR0tLS2i1ILH42Fubk4WXU+BQIBjx47xxBNP0NPTg1qtpquri6WlJfr6+ggGg1itVlJSUmRTnJqdnc1dd90lpoyPHTvGwYMHefrpp8nIyOCzn/0su3fvxuVySW2qiHAof+tb3+Lll1/GYDCwbds2ioqKZLFuNRqNKI6q0WhwOp3k5uYCMDg4yFNPPcXzzz+P3+8Xa/yk3n8FgsEg3d3dvPDCCzz99NMUFhYSjUYxm8386Ec/4nOf+xylpaWyqJO6k1AcntuM0OGk1Wp56KGHaGpq4urVqwwNDXHmzBlCoRDLy8v09vbyzW9+k29+85s4nU7JbkjBYJC1tTVWVlYAcLvdFBQUiN1Ni4uLnD9/nt7eXk6dOsXp06eJRCLizbSyslKSeo5oNCqG/zs7O2lpacFut/P1r3+dV155hc7OTh566CFqa2s31a7fhWQyyfr6Oh6Ph8zMTLKzs2WzAcdiMQKBgBhxElKyVquV1tZWhoaGCIfD1NTUSF7PMzw8zPj4OLFYjIceekhMsfj9fjIyMnjhhRfIzs6muLhYNqKDQvG30+kUmwRMJhO5ubl87Wtfo7OzUxZ1aAJra2uMjIzwwgsvcOrUKR588EFqamooKytjYmKC4uJitFqtpPZqNBr0ej12u53R0VHGx8cZGhoiPT2d//qv/+LMmTP4/X5KS0txuVyYTCbZPN/U1FTq6upwOBzs37+f9PR0QqEQU1NT9PT08N3vfpcvfOELFBcXyybtfSegPKnbxMYUy9raGhaLBYfDgdFoRK/Xk5qaSlNTEz6fj/HxcSYnJ5mamuKHP/whe/bsobKykuzs7E23O5FIiEKJABaLhbS0NLEl8tChQ3R3dzMyMsK1a9dYXV0VoxF33XWXZFGqWCzG4uIis7OzZGZmUl1djclkoqqqip6eHvr6+sjOzsbtdkuuE3QrYrEYY2Nj+Hw+AFm09QoIz/Kzn/0shYWFVFVVifIJra2tTE9P4/P5ZNE5ZLVaaWxsxGKxUF5ejs1mQ6vViuNRVCoV9fX1Yh2EHNjYvZlIJPD7/cRiMbKzs2lvbxcvQVIjFND29fVx4sQJXnzxRVJTU9m+fTvl5eWEQiGefvppHn30UbKzsyWTgRBISUnB5XLR19fHlStX+NnPfobJZOLUqVN4vV4MBgNarVYWKbiNqNVq0tPTMRgM5Ofno9PpiEajOJ1O4vE4Tz/9NDMzM9jtdqVT63dAcXhuI0LL+fj4OAaDgY6ODqLRKPF4nNzcXHbv3s3Kygrj4+OcP3+egwcP8tRTT6FWq9FqtWJ6YDMP540KwHDzlhSPx/F6vZw9e5af/exnDA0N4fP5xDBxQ0MD27Zto729XbJNWcjXBwIBtFot6enp2O12Ojs7GRgYYGJigvPnz4uRCSl444TujRtsMpkkHA4zMDCA3+8Xb6dywWw2i2KIer1etD2ZTOJ2u+nq6nrdupGS7Oxs0tPT2bp1Kw6HA7hp5+joKEePHiUtLY2mpiZRuE1uxGIxvF4vsViMoqIiCgsLSU1NlY2THgqFOHPmDIcPH2ZgYIBt27ZRXl5OTk4OIyMjvPTSSzQ1NZGWliZpYe3GurkzZ85w9epVXnvtNXQ6HYFAQIzoCCKwcnm+gKhm/8Y9QKfToVKp+PGPf8zc3ByFhYWKw/M7oDg8txG1Wo3X6+X06dOcOnWKuro61tfXaWxs5N5770WtVpORkYHNZqOsrIzKyko+8YlP0NXVJUqdS/ESboyABAIBJicnmZ6e5tvf/jZnzpwhHo+Ls7S+8IUv0NnZSWlpqaQHtJAGgJuqqj6fj+zsbOrq6jCZTKKEvFQIjkA4HBa7cTZGFwRV7iNHjhAKhbDZbLKohxFQq9Wo1eo3DZ8L40YEZ1lqjEbj64pPBWdyenqaV155hdLSUmpqasjLy5PQylsTiUTweDzodDpaWlrEQ04u+P1+sStLq9WSSCS4du0aer0eq9VKVlYWx48fx2azkZmZKa4Zqfay1tZWjEYjMzMzLC8vo1aryc3N5fjx4/T39+NwOMjMzJSs9vBWvNnzMhgMFBYWkp+fj9frFUsPFN4ZisNzG1GpVLS0tOD3+xkeHubo0aPiwdzW1iYO4VSpVKSnp9PS0sJjjz3G4cOHmZiYIBQKSR5y/9GPfsRPfvITEomE2E7tdrupr69n586dPProo68bkyEVqampFBYWUlNTw+HDhxkfH2fv3r10d3czOzvLli1b+KM/+iNJw9bJZJIf/ehHYtfIvffeS3FxMbOzswwNDXHy5El6enrESfQWi0UyqEoCCwAAIABJREFUW38X1Gq1KIbn9Xpl5UgI7fS9vb0cP34cr9fLxz/+cSoqKmT7fCcnJxkcHBQ7nuTGysoKkUhE7ESNxWKsr6+j0WgoKyvjs5/9LN/73vc4ffo0KSkptLS0SOqwCfUwNTU1ooOhUqkYGxtjeHgYh8OBwWCQdA9bW1tjdXUVv99PQUHBW0bGhPdtfn5ecXh+RxSH5zYhLNacnBy2bdtGPB7nX/7lX5iamuLKlSs888wzRKNR7rrrLnFe0vLyMj6fj2g0KmrbbLbDE4/HSSQSr4vwaDQadDodOTk5NDU1cffdd1NbW0tRUREGg0EWNTEajQaHw8GnPvUpjh49ytTUFE899RRLS0s0NTWxa9cuampqJLdzcnKSnp4efD4fY2NjOJ1OFhcXxdbTYDBIZWWl7EY1COm4UChEamqqGPGBm3USNpuNtLQ0WdSZvJHl5WV6enro6enBbDazZ88esrKyZFnsKbTUw836OTlF+QSys7NpbW1lcXGRnp4erl69ytjYGGVlZRQXF9PY2EhzczMLCwucOXOGyspKcUTKZiO872/8roV5dmtra5KnYq9fv87hw4cZGRkhEAiwfft27r77bux2+2/JUgjR1MrKSvEzCHIWCm+P/N74dxkmk4mSkhJSU1MZGRnhN7/5DQsLC/T09AA3c7IFBQWoVCpRqdRisUg25DI1NRWbzUZeXh7r6+uYTCZxKGhJSQltbW1s27aN/Px82Tg7cPPWYzQa6ezsJBaLMTQ0JIrKbd++nebmZrGeQ0rsdjvJZJKpqSnm5uYwGAz4/X4CgQCRSASHwyFOnpfj5PE31iHBzQ7EyspKotGo5BHJjQh2jo+Pc/HiRebm5nC73bjdbkwmk2wPiWg0is1mIzs7W5b1GUJnXjAYJBwOMzs7y+zsLPPz8+IU+traWo4fP87Vq1cZHx+nrq5OFtpBGxFSsIFAgGg0KlmkOhwOMzMzw9WrV/H7/djtdhoaGjAajW/a6aZWq3G5XExMTMh2DcsVxeG5zahUKoxGI+Xl5XzlK18hJyeHY8eO0d3dzaFDh1hYWKCsrIyUlBQGBwcZHx/nwIEDNDU1SXLDt9vt1NTUsHfvXqampnC5XFRVVeFyuairq8Nms8nGydmIUKBYWFjIxz/+cVEYUaPRiAWJUtos/Nv79u1jbm4Or9fLyMgIi4uLqFQqtFotNpuNnTt38pnPfEYcNyEXhOf3ZmtSr9eze/duANlEeDZOpj9x4gTDw8PodDoefvhhsrKyJE/BvhU6nY6SkhJycnJktQbgfwRVOzo6KC4uxuVycezYMYLBILOzs3i9XrGjb2BggLGxMc6cOUN5ebksxk0ICJIKNpuNQCBAOByWLK3ldDrZsmULZrOZxcVFLBYLPp+P9fX1NxXyVKvV1NXVkUwmMZvNsmgUuFNQvc3DUp7kHwjhZuzz+Th9+jTPPfcczz77LIlEAr1eL7afut1uOjs7KSwsxGKxSDKPKhaLEQqF8Pl8Ylj1jQ6D3ByejdxqTUtts1A8OzMzw+DgIE8//TS9vb3Y7XaamprYu3cvTU1NZGVlvensNTnyxmctF3uF9Nvo6CiPP/44JpOJrVu38oUvfAGn0ykbO99IIpHg5Zdf5tSpU+Tm5vKRj3xE8tl6b4awnwnzqgSNJsFpiMVieDwefD4foVAIl8slq9bvZDKJx+PB6/USjUaprKyURDdIeH+E0SLxeFy0Q3hWb7QpmUwSjUYJBoNotVplxMRvc8uHoTg8m8TGG6ff78fr9eLxeICbHntqaipmsxmDwYDZbJa0EFjYyOLxuBiGVl6o3x/hkIhGowQCATweD36/H61Wi9FoxGazibogIB/n4U4kGo3i9Xr59a9/zcmTJ9m6dSsdHR2yTK1sRLgUra6ukpqaisPhkHQkylsh7GnCfrHxkIab7fVCTaAwW0tOn0OQCEkmk2InnJSSFcJ/3+5iKewjwu/KxYmUEYrDIyc23o7gfxb1xhdOThuDwh+ejZsWoGxcf2CEi0VfXx8LCwu4XC6Ki4vFBgG58lZaTQoKCu8IxeFRUFD4v4WQnk0mk2Itl4KCwrsexeFRUFBQUFBQeNdzS4dHiZcqKCgoKCgovOtRHB4FBQUFBQWFdz2Kw6OgoKCgoKDwrkcRHpQAuWqXKCgoKCgovFtRHB4JCAaDrK2tEYvFyM7OVrpHFBQUFBQUbjOKw7PJzM7OcurUKfr6+nj44YdxOByKw/N/nHg8LooRLi0tEQqFMBgMWK1WMjMzpTZPQeFdRywWIxaLATdHo9ypCOrMyWRSVMRXuDWKw7PJTE5OMjAwQG9vL3v37pX9HJRAIMDCwgJLS0vi5HSTyURGRgZOp1MSOfZ3iiDiJmwK8XgctVotqr5KjTD+YHx8nPn5eRYXF7l+/Tp+v5/09HSys7MpLy/H5XKJgwTlykYBRYX/PclkkkAggE6nk+U097dCUGdfX19nenoak8mE1WoV54HJYW0kk0mCwSDDw8Osr6+TlpZGY2Oj7NSshTE0wWAQn89HamoqGo2GUCjE0tIS4XAYvV5PJBIhFAqRlpZGTU0Ner1euUC/BXfWG/UuYHJyksnJSbxer2ydnY0jEG7cuEF3dzcXLlxgfn5enO7udrvZtm0b2dnZb6oGK+XmIahYR6NRfD4fgUCAUChENBrFYDCQn59PamqqpCq2gijejRs3OHLkCFeuXGF6epobN24QDofFadnl5eV8+MMfpry8XJLZam+HsDGHQiHUarU47FAudm6U7N84t0hAsHPjgSe17fPz82RmZspq2OatEN61cDhMLBYjHA6zuLjISy+9RFFREVVVVbJZt8I7Nz8/z/PPP8/6+jpFRUXU1taSmpoqtXnA6ye4ezweZmZmGB0dxWQykZqais/nY2hoiLW1Nex2O4FAgLW1NQoLCykoKECr1cp+zUiJ4vBsMtnZ2WRnZzM/P09ubq4sF6dwC+rt7eV73/se3d3djI+PE4/HgZsh4MrKSvbv389f/uVfije4RCIhiyhEMplkeXmZoaEhvv3tb3PlyhUCgQAGg4Ft27bx+OOPU15ejs1mk8zGUCjE1NQUf/d3f8eVK1fQ6XSUl5dz77330tzcDMDMzAwvvfQSTz31FB/96Edxu92y2Zg3cvz4cU6fPo3D4eBP//RPZXG4bUQYhhuJREgkEni9XnFOnE6nI5FIYLVaSUtLE2/SUpFMJunq6qKyspKSkhLy8vIks+WdkEwmWVlZoauri+XlZVJTU8nLy+PZZ5+lurqaWCyG2+2W2kzg5jpYWVnh2Wef5Wc/+xnbt29nx44dsnqnhL3r+eef5+zZs1y4cIHR0VGi0ejrfi8/P5+UlBRWV1eJRCI8+OCD4jwzhVujODybjNFoxGw2YzQaSU9Pl+UCXV5e5uLFi3z1q19ldXUVl8tFW1sbg4ODXLx4kUgkwtTUFMePHycnJ4esrCz8fj/xeJxdu3ZRUVEh6aExNTXFyZMn+fd//3dxQGs8HhdvnsvLy3ziE5+gs7NTjEhsNktLSxw6dIhTp07xwQ9+kB07dtDQ0IDNZkOn0wFQW1tLR0cHarWa9PR0SZ1JIUISCARISUkhJSUFtVpNJBKht7eXc+fOUVZWJobapUaIUArr9OrVq3g8HiKRCBMTEyQSCTE1m5KSgt1uJyMjg9LSUt73vveJwyQ3k2g0yvLyMi+++CJerxe1Wk1ubu4tf18Oe0csFuPQoUM88cQTNDY28tGPfpRoNEoikcDhcJCXlycLOwGmp6d59dVX+e53v8tdd93F/fffT0dHh9RmiQiRnWeffZbvfve7rK+vk5mZySOPPEJ/fz9ZWVnk5+dTVFSEy+Xi2LFjnD17lqWlJe677z5sNtsdlwbdbJSns8lkZWWRnZ2NTqfj3Llz1NTU4HA4MBgMstgYEokE8/Pz9PT0cOPGDfbt28fWrVux2WykpaUxMjIipjAWFhY4ceIEKSkprK2toVarSSQSFBYWkpaWtumfRwhZ9/X10dXVxcjICFlZWTQ2NpKdnY1Wq6Wvr48bN26wsLBAMBiUxOGJx+P4fD4uXLhAZmYmTU1N1NfXk5eX97pJ3jqdDoPBACCLGgOVSoVWqxVtERyg4eFhlpaWKCwsfF26SEpCoRCzs7M8/fTTdHV1EQqF0Gg0pKWl4ff78fl8JBIJUlNTMZlMpKen43Q6JTswhGd55coVhoeHUavVaLVaLBYLN27cYHJykkAgQCKRIJlMUlBQQFVVFfn5+djtdklsTiQSBINBjh07Jk53V6lUvPbaa2IHan5+vuTrFmB9fZ3x8XF6enrYsmUL9913H7W1tZjNZlnYBxAOh5mfn+fEiROsra3hdrvZsWMH9fX15ObmYjQasdlsOBwO7HY7yWQSs9lMRkaGmJaTy2eRK4rDs8nY7XaKi4spKipiaGiI9fV1GhsbKSoqEm/2UiJEQi5fvkw8Hqejo4OdO3diNBqZn5/nV7/6FXq9Hq1WSyKREPPJ4XAYs9lMdXW1mPraTIQIxMLCAufOnWNwcBCtVovL5WLPnj243W7MZjMWi4XTp09L+qwTiQRra2uMjY1RWFhIaWkpWVlZvxXBUalUskl5Cg7OxiJ1obvM4/GIzoMcNtxkMonX62VwcJDnnnuOsbExysvLKS0tFSOSQ0NDLC8vE41GsVqt2Gw2bDYbFotFkmceiURYWlqiu7sbj8eD1+vF6/WysLDAxYsXOX/+PH6/n1gsRjQaJScnB5/PRzwex2azoVKpNv3Zx2Ix1tbWOH/+PGazGZvNRigU4uTJk1itVvLy8sjKytpUm27F6uoq165dY3h4mEceeYT29nbS09NlFREJhULMzc3R19eHVqultraWzs5OdDodGRkZxGIxAoEA8/PzLC8vMzs7i8lkwu12k5+fL5u9Qs7I59v+P4Jer2fr1q0UFhby3HPP8Z3vfIdHH32U++67j4KCAkDaUHU4HGZlZQWPx0NqaqpYPGk0GnG73RQWFmK320lJSWF5eZnx8XFWV1cxmUzk5eXR1NS06akXodAvFApx5MgRenp6CIfD7Nu3j4985CO0trZisVjEXPeWLVuorq7G6XRuqp0CQuh6enqa6upqTCYTKSkpryti31hsKxRXS+1MvPFQFSI+6enpqNVqHA6HLNJZiUSCS5cu8d///d90d3dTXV3NBz/4Qe6//35KSkrwer38x3/8B9evX8dsNvPBD36Q0tJSLBYLer1+0w9BoW5jcHCQn/zkJxgMBu655x46OzspLS1Fo9GIkRKVSsXCwgLHjh3j5MmThEIhampqNr0ORShWn5ubw+v1Ul9fj8PhwOv10t3dzVe+8hWqqqrECKXUeDwepqenWVxcpK2tDbPZjEajedOIpFTF68FgkKmpKa5du0Z9fT02m41IJMJPfvIT/uu//ou1tTXxYuF0OkkkEuzbt4/7779fVo6bnFGekgQYjUZKS0t5/PHHmZ2dpbe3F5/Px+OPP056erqktgUCAbxeLzMzM8zOzvL973+fGzdu4Ha7mZmZ4c/+7M9IS0tjaGiIp556isXFRRwOBx/60Id49NFHqaur2/ToSSQSYWZmhqeeeoof//jH7Nmzh09+8pO85z3veV2aIjU1laqqKlwul6S3IbVaLaZShFoRQUtD6HK5fv06N27cYGZmhscee0w2zsRGNnbzVVZW4na7JXfKAEZGRjh58iQvv/wyGo2Gz3/+8+zatYu8vDwikQgvvPACY2Nj5OTk8OCDD7J161bJU4bj4+O89tprDA8P86UvfYl7770Xl8uFVqtl+/btr3OGE4kEZrOZgwcPMjg4yPT0NCUlJZtus8fj4dVXXxWjaVevXgWguLiYu+66i/z8/E236VZYLBYxFTQ+Po5KpSIUCrG2tkYoFOL69eukp6dTVFREXV0daWlpm26j3+9nYmKCSCSCRqMhGAyKkiDvfe97KS8vp7CwEKfTSX9/P319fbjdbkpLSzfd1jsVxeGRAJVKhVqtRq1Ws7a2xuDgIIuLi9xzzz00NjZKuvEajUays7MpKSmhr6+P7u5uJiYmsFgsoj5IamoqKysrzMzMUFRUxAMPPMD+/fuprq4WN4rN+gzxeJyxsTFOnz7Niy++yJ49e7j//vtpaGjA4XCIzo6QkpFD2FfQMiopKeH8+fP8+te/xul0Eo1G8Xq9DA8Ps7CwQDQapbCwkEgkIksJA0G2YGZmhubmZkpKSiSXIwAYHBxkeHiYtbU1tFot3d3dLC0tidHKYDDIgQMHKCwspKSkRFwTUtm+vr7O+fPnOXXqFBqNhp07d4o1ZyqV6nW3d+EzpqSkiNEJk8m06TYnEgn8fr+YVjEajYRCIdbX19mzZw/Z2dmyctAtFgt5eXnk5uby7//+7xQVFaHVakXdIEECYHx8nOXlZfbu3Qts3poQOmMXFhZQqVTs3LmTjo4OqqurKSgoICUlBZPJRFpaGhqNhtHRUWw2m9hdqPDOUByeTUYorF1bW+PChQtcu3aNmZkZ1Go1Ho9H8oNNp9ORk5NDfX09J06cYHV1lbW1NTQaDRqNBq1WK7b36vV6duzYwd69e6mtrRXb0zcToY4EoKKigr1791JfXy8eGAKCKFokEkGr1b6uOHizUalUmEwmysvLee655+jv78dgMIjCjpFIBL1ej91ux+VyYTAYZOGobSQUCjE/P8+rr75KWloa+fn5ZGdnS20Wa2trDA0NMTk5SSQSISUlhYGBAa5fvy6mZnNzc8nPz8dqtWKxWABp04ULCwtcvXqVGzdukJmZSVFRkZgKEvYDQRlY+DM9PY1er8fpdGI0Gjfd5ng8TjgcxufzYTKZsNlseL1e1tbWKCkpwWw2yyrNIrxPTqeTrq4uUlNTKSoqwul0EgqFyMrKIhQKEQ6H6evrY8eOHZveeCEU1WdmZlJfXy/W9m18r+LxOH6/n7m5OdLS0sR0uMI7Q3lSm8TGjWt5eZmxsTF+8IMf0N/fTyKREFU0pSYlJYWCggJ27drFqVOnGBkZIRaLkZqait1uZ3V1lampKXQ6HVVVVXz0ox9l69atm97ttFFEzm6309bWxq5duygoKBBFBTf+TjAYxO/3s7i4iNPpxGq1SnYDValUmM1m6uvreeaZZ5idnQVuphO3bNlCZ2cnWVlZ2O128vPzyczMlEWqSGCjztHPfvYz2tvbcblcko/BSCQSzM3NMTQ0xOzsrNg+Pzk5KTq8iUSC4uJiMTqSm5sreSRifHycqakpQqEQ1dXVmM1mYrEYwWBQjEyurq7i8/nw+/0EAgH6+/vJzs6WLP0SiUTEbjeTyYTD4RCFPjMyMiQX9nwjKSkpohRIIpGgqqqKe+65h9raWgDS0tJYXFzktdde4+DBg2LX2WZ9BmFPqKiooL6+HpfLhd1uf917L6S8Z2dnOXfuHFu2bMFms8nuMiRnFIdnE0kmkwwMDHD8+HFefPFFurq6SCaTFBcXU15eTk1NjSwOtoyMDNrb2/nnf/5nMS9vs9morq7moYceIhgM0tTUxBe/+EU6Ozsls1OoH8nMzLyl3kcikeDatWucPXuWV155hVdeeYW/+Iu/4O6776aiokICq2+Snp7Ojh07aGpqIi8vj4qKCurq6mhqasJkMsnqsHgjwWCQ/v5+jhw5QmpqKo899hgVFRWyEHBLJpPk5eURDAaJRqPk5+dTWlpKIpFgcnKSgwcPcvnyZex2O+Xl5bLQDZqfn8fn86HT6WhubiYYDPL888+zsLCAWq0mJSWF3t5eBgYGuHbtGjqdjnvvvZd7772X1tZWSfaMsbExuru7OXfuHBaLRVT4DYfDDA8PE4lEJJGmuBVer5fz589z6NAhYrEYLpeL4uJiHA4HcLNZ49KlS5w/f56FhQVJIu35+fkcOHCAtrY2CgoKfmtdxuNxJicn+eUvf8nQ0BCf+tSnqK6uls0zvhNQHJ5NIpFIcPHiRX784x/T39/PxMQEWq0WnU7Hrl27eOihh2Qj0iXUDRQVFZGTkyP+nSAhn5eXR1VVlegwbLbNgUBAbJ13u93YbDZxw00kEmLKcGpqioMHD3Lx4kVxE/vc5z7H7t27JU+/CLUD165dY3FxkczMTEpKSkgkEhw5coTMzEzy8/PF5y8HhCLl1157jePHjzM+Ps7HPvYxysvLMRqNkq9dtVpNfn4+f/Inf4LP5yMWi5GRkYHD4cDj8fDaa69x9OhRiouLOXDgAHv27JFMeHIjPp+PUCiEVqvF4XBw+fJlnnzySYaGhoCbnysYDGIwGHC5XLS3t/Oxj32MkpISrFbrpj53odbkpZde4uTJk1RUVPDZz36WkpISTp06xXPPPScOwDWbzZI77slkEr/fz8GDB3nppZeYnJyktbWV9vZ2cnJyxBTR0aNH+e///m8ikQj33Xcfdrt90yMnarWatLQ0SkpK3nRG4dzcHD09Pfzyl7+kpqaG4uLiTf/+73QUh2cTCIfDLC0t8etf/5pAIIDNZiMYDLK4uIjb7WbLli243W5Z6PAIqFQqdDqdaJNwQAs36OLiYslGM6yvr3P16lX+8z//k/3795Ofn4/ZbEan04kzaG7cuMHQ0JB4I3Y6ndjtdnbv3k1ubq7khX7RaJSlpSUWFxeB/5l6/Morr/Diiy+KOiFyQWj9n5yc5MiRIywuLlJVVUVHRwcGg0Hyg01Ar9dTXFxMNBolmUyi0+nQ6/VMTU2xsLBAJBJh9+7dNDU1yUa7REi1ra+vMzg4yMDAAENDQ8zMzKBSqbDZbJSUlNDQ0EBTUxM1NTVUVFRIVtvl8XhYWlrCYrFw991309LSgsViYXx8HJvNht/vF+v8pESIAJ8+fZpXXnmFubk5amtr+fCHP4zJZGJubo65uTkuXrwoFow3NDSwc+dOSYYiC7IDbzwHkskkkUiEoaEhzp07x8zMDHfffbfk6ut3IorDc5uJx+Osrq5y+fJljh49SnV1NQ6Hg3A4LM52amxslI0i6duRTCbF4j+pNDYEsbuXX34ZlUpFXl4eFosFg8HAysoKU1NTXL9+nbGxMSoqKmhsbMTpdOJ0OqmpqZFkbMAbCYfDzMzMsLq6Snp6Omtra1y/fp2jR48yNDRERUWF5AXsGxEmu/f399Pd3U1ZWRkdHR1UVFRIWgC+EUGocWPURjgsxsfHuXTpEpFIhG3btonRETmg0WhQqVT4/X7Onj3LwsKCmGozGo24XC46OzvZuXMnLS0t4kVDqmfu8XiIRqNkZ2dz9913k5mZyfr6OuFwWOxABSRfv8I+8dJLL3Hu3DnS09NpaWmhtbWVqakpJiYmGB4e5vTp0wQCAfbu3cvOnTtpaGiQRMjxzRCiqnNzc5w9e5aBgQFSUlKor6+XfepbjigOz20mEAgwMjLCM888QzAYFMcaTE9P09jYyGOPPUZ5eblsBLpuxcYNIBqNijdo4WebidFopLi4mLq6Orq6uohGo2g0GvFGp1KpsFqtuFwuHn/8caqqqsQIkFyiaH6/n4sXLxIMBvH5fJw5c4apqSlUKhVf/OIXaWpqorCwUGozgf9xGubn53nyySfR6/U0NjbS3t5+R9wwPR4Pg4ODXLlyBYvFQkNDAxaLRTaHhdVqxWg0Eo/HGR8fJzU1lYyMDEpKSmhtbeW9730v9fX1WK1WWTxvoT4qFosxNzdHIpHgN7/5DcePH2d0dJRHHnlEcluFwvpjx47xy1/+knA4TElJCTabjR/84Ae89tprouNms9n4/Oc/z/bt28nNzZVFLZqA8O49++yzPP/883g8Hvbs2cPu3bvFDkOFd47i8NxmjEYjtbW1fPrTn+by5cv09vaSmppKbW0tX/va16iqqpK8aPKdIIRaBRn7WCxGMpmU5BZkNptpamriySefpLe3VxQPm5qawmQykZubS25uLkVFRaIWj1xubALCrCRBzbqpqYl9+/bR0dGB2WwWZ1bJhampKY4cOcLMzAx/9Vd/RUtLi6zqi96KV155RRzZ0NzcjNvtlqSV+1bs378fs9lMW1sbPp+PrKwsqqurKS0tpaioSNRekcv6rampYevWrbzyyiv88R//MYlEgoyMDOrq6vjyl7/M+9//fvR6veSaTEIUeGlpiXA4zIkTJ+jp6cFkMlFdXc0nPvEJ3vOe94jRPrm9c3DzwnzmzBmeeOIJvF4vdXV1fPCDH8TpdMrO1jsBxeG5zahUKjEi8aEPfYiFhQXS0tIoKCigtrZWFumVd4parRZVPUOhEPF4XBINCEEVNzMzk9bWVqLRKPF4XJzkbTAYSEtLw2g0irdMuT3j9PR0du/ejUqlIj8/n7KyMiorK8U2UznZKyhZC/okbrebzMzMO2bDLSoq4v3vfz9ra2uUl5eLYwXkgsViobW1lYqKCqLRKHq9Xoz6CEOF5bQejEYj7e3tZGRkUF1dLU5GLy4upqKiYtPFR98MlUqF3W5n3759lJSUEIvFgJvpQ4vFQllZGeXl5eTn52MymWT3zsFNp219fZ3u7m5WV1fJzs7G5XKRn58vuTL4nYri8NxmhI4ni8VCZ2cnkUiE1NRULBaLZFOO/zcIm25paamoBiplUaLwXKWah/X7Iswms9lspKenY7VaxdoTuW1kyWRSdNJbW1vJzs6WTWrwnVBcXCy+axkZGZIUpL4VWq2WnJycOyJiJsxPKywsFIuphandwhqWw7MV0trt7e3U1taKe5VarUav14uq23IZePtWaDQaqqurqaqqoq2t7Y7d8+SA6m0Ky+RTNakgOYlEgkOHDnH16lXy8/N54IEH7ogNQ+H3I5lMiorWQkRS+c4VFG4/gUCAS5cuMTExgdvtpqCgQJJRIncYt9ycFIdH4R0jFAX7/X4xNAzyi0go/GF5sz1C+c4VFG4/wru3sV5SeffeFsXhUfj9EdZKPB4XW4AVFBQUFBRkhOLwKCgoKCgoKLzruaXDc2e0WSgoKCgoKCgo/B4oDo+CgoKCgoLCux7F4VFQUFBONiwIAAAgAElEQVRQUFB416Po8Ci860kkEiQSCZLJJGq1WhHtUlBQuGMQ5mkBiiTE74ni8Ci8Kclkklgsxvr6OhqNBq1WK4rNCS+coM8iOBByehGF6d6rq6tMTU2xurpKPB4nLy+PwsJC2Qy8VNgcYrEYsViMUCgkTlHXarWymE2lIA3CRSgcDhOPx8U1IScF8UQiIQ6/tdlsWK1W2c9dlDOar3/962/187f8ocIfho2dcoI3L0QkNrJZB7Tw7y8vLzM4OMj6+jpqtRqj0Sg6NoKdKysr4oRkuWwUG5213t5e/u3f/o0f/ehH/OpXv0Kj0dDQ0CDLkR7C9y1sxPF4/HU/E9bERrul+gxSrc3fFcFOv9/P/Pw8ly9fZmpqimQySUpKCmlpabK3fWOEEuTzrDdqxMTjceLx/8/eeQfHmd73/bMNu4vtwC4WHVg0gmisIAmAB5LHerpeZMeSLFm2ZCljx5nJJFEm+iPxOBrZcSI7ijLyWC5zke3Esk53lE48kmIB2BsAgugd4KJjgcV2bM8fnPcVyeMV2Rbel5f9zHCGBMDhj88+7/N8319Nir8X7JVb/5iH920sFiMQCOB2u5mdnUWtVqPRaMRxOVLbK5xjCwsL/PEf/zHwYNBsTk6OpHY9Bfz+B30j4+GRAYKKDwQCrK6uEg6HWV9fZ319ncLCQrZv377pA0YDgQDf/va3CQQCtLS0YLPZHjks4vE4q6ur/Pf//t/59Kc/TVVVlWxGZfh8PsbGxjh79ixvvvkmi4uLANjtdtxuNz6fD71eL7uhralUioWFBe7evcvExAThcJiGhgaamprwer0Eg0ESiQTV1dU4HI6Md+Jj4vV6+elPf8p7773HuXPnSCQStLW18dprr/G5z31Ott4+wfvQ09PDyMgITqeTLVu2UFVVJbVpIslkkoGBAa5du0YgEEClUhGNRllfX6esrIy6ujpaW1tlNYE8mUyysrLCtWvXuHLlCleuXMHn83HixAmOHDnC0aNHZXE2pNNplpeX+R//43/w1ltvUVJSwvbt26U266kmI3g2CaFL8fz8PF6vl/X1ddbW1lCr1aysrLC0tMTCwgJGo5GJiQk8Hg+JRIKDBw9SXV29aR6JVCrF8vIy/f39rKys8Prrr1NTU0NeXt4jjQbj8Tgej4eLFy9y8OBBysrKfum2fRTpdBq/309nZyednZ1cuHABo9HI5z73OWpqaigvL6e4uBi73S4rsRAIBFhZWWFycpIf/ehH3L9/n/X1dZLJJDdv3sRqtRIIBDAajdTU1FBZWbmp9sXjccLhMD6fDwC/38/y8jIej4dIJEJ+fj65ubnk5ubidDpl5zUZHx/n8uXL3Lp1C6VSid/vp6+vj9raWlZXV3E6nVKbKJ4PXq+X2dlZwuGw6JG6dOkSKysrFBUVsWvXLj7/+c/jcrkkafwpTCF3u90sLi6yuLjIT37yEyYmJtjY2BBn7CWTSSwWC1u3biUcDnPixAnJG5UmEgkCgQAXL17kpz/9KRMTEwQCAex2O3V1deTm5qJSqSQZiPwkFAoFyWQSj8eD0WgkNzdX7G6f4R+HPD7Z/w9Ip9MEAgEuXbrExMQE6+vrmM1mIpEI09PTzM3N4fV6sVqteL1eNBoN+fn54qyqzbpAotEoHo+H+fl5tm7dytatW3E4HO8bFrmxsYHH4yEWi6HRaCQ/zISQz8DAADdv3mRiYoL8/Hx27tzJM888Q3l5OXl5eeh0OnQ6nSzCb4LLur+/n3v37tHT00N/fz/l5eVkZWXh9XqZnJzEaDSSk5NDYWEhxcXFGAyGTZ3u7PV6mZmZYWhoCIC5uTlWV1dZX1/H6/WSm5tLaWkpW7dupbW1Fb1e/77Qm5T4fD5WV1cJBoNkZ2eTSqXw+Xx4vV4CgYDkgieVSrGysoLb7WZgYIDBwUHR2+t2u1lYWMBsNhONRpmdneXq1auSTMxOpVLE43Fu3brFrVu3mJ6eZnV1ldu3b7O+vk4ikUCpVJKdnY3dbheHDPf393P8+HFJ90QikWBlZYXBwUHeeecd+vv7SSaTOBwOWlpasFqtlJaWUlJSIvlZ9jDC2W+327FYLLLwPD3NZATPJuL3+7ly5Qp3794lGo1y8OBB3G43g4ODLC0todVqCQQC5Ofns3XrVvbs2UNNTc2mbvKHw2rPPfcceXl573NHJ5NJfD4f09PTFBUVYbfb0ev1m2bjk0in02xsbHDhwgUGBwfR6/W89tprtLe3U1hYKLvp3kJ+w+rqKufOnaOjo4ORkREaGhp444038Hq99Pf3c/nyZfLz82lra2P79u00NDRgs9k29eJYW1tjcHCQs2fPEgwGGRsbE6dmezweNBoNVVVVJBIJGhsbcTqdshE7AKFQiEQigUqlEvdBMpkkEokQCAQks0vId/H7/fT29nLt2jUuXbrE9PQ0wWCQdDqNTqejsrKS5uZmNBoN4XCY06dP88orr2z6nk6n04RCIU6dOsWZM2eYmZkBeCS3LCsri9LSUrZs2cLIyAihUIjZ2VlSqZRkHikh/N7b28vZs2e5fPkyJSUluFwuamtrOXToEKFQiLq6Oux2uyxehgBxfI/JZKKwsBCLxSK7c+xpIyN4NgmFQkFJSQl/8Ad/QCwWA8Bms+F2u7ly5Qper5eWlhZ8Ph8FBQXk5+fjdDo3/ZDwer2kUilKS0uprKx84sO/trbGjRs3+Ku/+it27NiB3W6X/M0jFosxNTXFyZMn+Rf/4l9w4sQJtmzZIqu3tYdJp9NEo1H++q//mtOnT2Oz2fja177Gyy+/jMFg4MaNGzgcDt544w1eeOEFSktLMRgMwOYnU5aWlqJQKFCr1fzZn/0Z0WiUqqoqGhsbcTgc1NXVUVlZSX5+PmazWVZiB+D69euMj4+zsLDA/Pw8KpVK9LjOz8+zY8cOSexKpVIsLi7yF3/xF1y8eJH79++zdetW/tN/+k8kk0nMZjMVFRUUFRVhNpvx+XwMDAzw3/7bfxMThDfbwyN4dtVqNXl5eRiNRvx+P4FAAJPJxJYtW/i93/s9RkdHRa91SUmJpMn1w8PDfOc73+H27dtsbGzwrW99i61bt5KTk0M6nWZsbAyDwYBOp5NNOEtAo9FQXFyMXq8nPz8/U6H1T0Ren+4nnHA4jEKhYHZ2loGBASKRCMeOHePFF19Ep9Oh1WpJpVKo1WpUKpV4WW/GYSEkJE9PT+Pz+XA4HO8TO4JXYmhoiP7+fnw+H8eOHcNms0kuLDY2Nujv70er1VJQUPCIWJTbBQwPQodut5sLFy7Q3t7Ojh07qK+vZ319HbfbjdVq5fjx45SWlmIymSStHBFCKVeuXGFoaIgXX3yR48ePs2/fPqxWq1jerVKpxD0jhzWPx+O43W66u7tZXl5Gp9NRWlrK7t276e7uxufzce/ePY4fP77picvhcJi5uTn++I//mLNnz5Kbm8vx48f53d/9XUpLSwFQKpVi1ZBCoWBhYYHBwUHJQrKCyPmd3/kdFhcXUSgU5OXlMTExwdtvv836+jp6vZ733nuPS5cukU6naWhooL29XZLzIRKJ4Ha7+a//9b/S19dHUVERJ06cYP/+/aIwn5ubo6OjA4PBQF5eHjabbdPt/DBisRgTExM4HA5UKhWhUIj5+Xmmp6dxuVzk5eVhsVhk45WSOxnBswkI4Zb/+3//L0tLS8zPz7OwsCC6rJubm6moqBATk6V8GxodHSUQCIgem8dtWVtb4/bt2/T19ZFOp6moqBDzjKQikUiwvr7O9evXqaiooKCgQCyhf5x0Ok0wGCQej6NUKrFYLMDmX9CC4FldXSUQCDA4OMjQ0BBWq5Xm5mby8/OxWq1YrVbJ9kQ6nSYWi3H37l06Ozu5desWVquVtrY2tm3bRkFBgWxd7H6/H7fbzTvvvMP8/DylpaW4XC5aW1sBGBkZIRwOs7q6Sjwe39ScqGQyyf379zl//jwdHR2Ew2H27t3L/v37qaioeCTpW8hNm5ubo6uri3v37tHS0oJGo9n0PSGEWLZu3Up5ebmYr+N0Ounv76e7u5uJiQlmZmYIhUK0tbVx+PBhKioqNn0PR6NR5ufn+dnPfkZ/fz+5ubns2bOHQ4cOkUwm6erqYnl5mcnJSc6dO0ddXR2hUIhUKiUb8SB41O7fv8/GxgZXrlyhq6uLvr4+lpaWyM/PJy8vj5KSEtra2igtLd3Uffw0khE8m4CQnNrT08Pk5CThcBgAq9VKf3+/WMpZX18vhi2kYmlpCb/fT3l5OfDz+HwymSQWi9Hf38/NmzcZHR1Fp9ORm5sruRs4FAoxNzdHb28vR48efWLe0cN4PB5WV1fRaDTU19dL8vYp5BX4/X4mJiaYmJhgbW2NmpoampubMZvNWK1WyQ9fr9fL7du3uXbtGuPj45SWlpKbm4tWqyUajaJUKh85ZOVw2ArlvF1dXVy8eBGr1cqOHTvYt28fBw4c4OrVq6hUKiKRCJFI5JF+R5tBMplkfn5eTK6vr69nx44d7Ny585GQheBR9Xq9dHV1MTIyQjQapa2tTbKXDIVCgcPheMRGlUpFdnY24XCYmZkZVCoV27dvp729nQMHDmC32zfNPmHNPB4Pg4ODXLx4Eb1ez+7du9m5cycOh4OhoSEuXLjA/fv3mZ2dZWRkBJ1ORyAQkJXgSSQShMNhFhcXWV9fJxQKkU6nmZ6eJh6P09vbi9FoxOVyUVJSQmFhoeSedrmTETybgEKhQKvV8vzzz4vJyQ6Hg4qKCt5++21OnTpFR0cH/+bf/BsaGxslHX2QnZ3NxsYG0WiUeDwu/gqFQrjdbr773e9y6dIlgsEgVVVV4gMmVQVGOp1mZmaGmzdvMj8/T1NTE3a7/UMf/LGxMW7fvo1Wq6WqqkqyuLhSqWR5eZmVlRXy8vIoKytjY2OD5eVlCgsLJRU8wsXR19cnXswajQa3282pU6dYWlpi69at1NbWYrFYUKvV77NVqj2cTCYZHh7m9OnTGAwGvvSlL7F9+3aKi4vRarX4fD4xKfhJdv+yicfjbGxsEIlEUKlUnDhxgoMHD7Jly5b3/Ww0GuXKlSv8+Z//OTU1NXzmM59hz549kr9kCKTTaXw+H4ODg9y/f59UKoXT6eRLX/oShw4dwuVybbpNsViMq1evcurUKe7cucMf/MEf0NbWRjQa5cKFC/zd3/0dvb29JBIJdDodhYWFDAwMiFWnclhbISogtDCZm5tjbGxM9FLa7XZu3bolfj8QCLyvGWiG9yP9J/v/CRqNhhMnTjzSLVWpVPLVr36V2tparl69yte//nX+83/+z9TW1mIymSSxMycnh8HBQa5du8aFCxcwmUz4fD5WVlaYm5sjGo2K7fm9Xi8DAwPs2rVLMs9UKBRiYGCA7u5u6uvr2bNnz0c2QCwsLESn04lhLSmwWq0cOHCAv/7rv8Zms2Gz2TCbzSwsLPB//s//IRaLYTKZJGvmKFQP/e///b8xGo28+uqrOBwOzpw5Q0dHh/jmnJ+fj8vlYufOndTV1VFbW4vdbpfU06NSqWhtbaW2tha9Xo/dbketVosN506ePInX66WpqYn29vZN7xuUnZ3Ntm3b+PVf/3UAXnnlFWpqat63F0OhEJOTk/zJn/wJr776Ks888wyNjY2yuJAfJpVKkUgk0Gg0lJWV8R/+w3/g+eeflywfZmhoiNOnT3PmzBnC4TDf/va3+f73v08ymSQUCqHX6/nmN78p9g7r7e3lu9/9rthBXg4kk0nGxsa4du0aPp+PoqIiPvOZz3DgwAEqKipIJBK89NJLqFQqDAYDLpdLdvtCjmRWaBMQDtPHN2Q6ncZgMLB3716ys7PxeDxcvnwZh8NBdnb2prsnFQoFOp1OvBjMZjOBQACNRoPdbqe4uJhAIMCNGzdYWlrC6/Xygx/8AJPJRGVlpZgPs5kEAgExDHfo0CGMRuMHrpsQmpudnSUUCklaWaZSqbBYLOzfv5+srCwxJ0NwxwutAaQSPIlEguXlZebn59m/fz/Nzc1s2bKFffv2MTExIdonJNa63W6mp6fp7Ozkq1/9KjabTdID2GQyodfrxTlw8GCvDA8P09fXh0qlEjsBS5ELk5uby759+yguLqaiouJ9OWfJZJLp6Wnee+89qqur2b9/P5WVlZLk7nwUQom/QqHA6XRy+PBhST9/i8XC7t27xZxIp9OJy+XCZDKRlZWF1WrF5XKh0+nweDz4fD5isRjxeHzTw5sfhMfjoauri46ODgD2799PUVERc3Nz/OxnP2N9fZ1/+S//JWVlZej1etmMw5A7GcEjIUISoMPhoKamhqamJoaGhsTSdCnisUVFRTQ0NKBUKnG5XGKyYTKZJBgMEgwGKSwsxG63YzKZmJiY4M6dO6jVampraze9hfzGxgZ+v5+NjQ3q6+s/8EIQ8qjW1tbo6+tDqVRSVFQk2aGsVCrJysp6pOldMpkkOzubRCJBNBoV2xdIhVqtRq1W4/V6WV5epqysjObmZlwulxgWEi6KyclJRkdHGRoaYnV19ZHKss1G6BH0cDftWCzG8vIy165dw+v1smfPHurq6igoKBD/zmYiNMDMy8t75OuCh0GY8TQ4OEhbWxtlZWWyLPmHn4c/TSYTpaWlFBcXSzquw2az0dzcTFlZGSqVCqPRSGFhISaTCZ1OJ4pL4RmbmZmhpKQEk8kkeQ6MkKQ+PDzM3bt3mZycpKioiPr6evx+P4ODg9y6dQuHw0FWVhZGo1FWYzvkTkbw/JJ4ePBfOp3+0IniCoUCq9XKnj176OjowO/3E4vFNrUCRrCrqamJkpISnnvuOex2O8FgkPn5ecbGxjh//jxLS0vs2LGD6upqCgsLOXnyJFeuXCE7O5uCggJyc3M3tSIjFosRDoeJx+MUFRWJXpKHB5wKYicYDNLX18elS5c4fvw4u3btktWICXgQ+tTr9SiVSknfNjUaDXl5eVRWVtLX18fU1BTz8/N85StfoaCgQOzNI9gouNS7u7tZW1ujuLhYMtufRCAQYGxsjHfeeQedTseRI0fYv3+/7MqQ4edVXOPj46ytrXH06FFZlx5rNBqys7MpLS2lsbFR0mdKoVCIgufDEKo15+bmGBwc5OjRo5SUlEjeTwwelNNfvHiRO3fuEAgEeO655ygoKODMmTP09vYSiUR44YUXyM3NzYidX5CM4Pklkk6nxRkzhYWFHxieSKVSBAIBRkdHMZvNGAwGyTZyXl4edrudcDjM7du3uXDhAleuXGFubo5t27bxzW9+k7q6OrFc+rXXXuO9997D6/XS0dHBkSNHsFgsmyZ4srOzMZvNqFQqOjs7ycvLE3vDwIOxAoFAgNnZWXp6evjOd76DwWDA6XRSUVGxKTZ+XITmfpWVlTidTkkPX6VSiclk4hvf+AZ37tzh1q1bonfk9ddfp6qqipycHFQqFfF4XCyXLSwspKqqSnbl6oODg3R2djIyMsIbb7zB888/z9atW6U264nMzMzwne98h7m5OXbs2CFWTMoRIWTU2tpKdna2WPb/NHDnzh3effddPB4Px48fp7CwUHJRGY/H6ejo4K233sLj8VBWVsahQ4f4m7/5G8bGxsjNzeWLX/wiv/3bvy1ZnufTTEbw/BJJJpOcOXOG/v5+SktLefHFF7Farej1erKyskSvz8TEBD09Pbz33nu88sorFBYWSvaWJFQ9Xb9+nb/8y79kfn6eLVu2cPToUY4fPy4mggqCRqPR8Oyzz+Lz+YhGo5vuEs7NzaWhoYGpqSm+973vsbq6yp49e8jOzmZiYoJbt26xuLiIz+cjFAphMpn4yle+wo4dO2Tn3REqM5RKJQaDAaPRKJktgofMbDbT0tJCdXU1ra2tdHd38/d///dEIhHgQa5MKBRiZmaGnJwcXnnlFaxWq2wSKIVxCIODg/T19aFWq9mzZ4/sBsgKpNNpTp06xcrKCi6Xi9dffx2Qd26GUqlErVaj1WplJ3Q/CI/HQ19fH/Pz83z1q1+lpqaG7OxsSddZ6L7e1dWFz+fDYrFgNpt58803GR8fp7W1lUOHDvGpT30Ks9ksuTh7GpHHqfQJRajE8ng8DA8PMzs7S05ODnq9Hq1WS1ZWFmazWZygXl1dzY4dOySN1QsTxycmJhgZGaGwsJCdO3dy6NAhampq3pdcqVAoxGTAeDy+6f1BtFotW7ZsYW1tjd7eXi5cuCD2CPL7/czPz5NOp7FYLFRWVtLU1ERbW5vs5j0JCDOfHs9BkQIhx8xoNKLRaDAYDBgMBsbGxhgZGRH7B/l8Pqqqqti9eze7du2SjdgR8Pv9zMzMMDc3h8Vioa6uDqPRKLvPPx6P4/F4uH37ttgRWoqy7l+UeDxOMBhEq9XK7rN/HCHEPT09LXaLbm1t/dBih81CmOYuRAUeLh45evQohw4dYseOHTidTklblzzNyHt3PuUolUpsNhtarZbR0VGGh4cxm82id0ej0YhzZgoLCzlx4gQul0vSSgzhzT6VSoldf1taWti2bdsHlp4L1V1ShGCEaht4MDNJCK1oNBqMRiNmsxmHw0F1dTXbt29n//79mEwmWb4dCesuzEmSE0LvKGEtCwoK0Ov1Yr5Zc3MzBw8epLKyUmpT38fS0hJutxuv10tRURGVlZWSD7t9nHQ6TTgcZnh4mPHxcT7/+c/T3NyM1WqV2rSPJBaLEQgEZCEaPg7xeJyhoSFWVlbQ6XRs2bJFFtVviUSCSCRCKBTCbreTSqXQ6XTU19fz6U9/moaGBlkNN30ayQieXyJCw8G8vDx27twJPLg4IpEIPp+PtbU1NBqNWPYrTESW8sFTKpWUl5fz2muvsX37dnF4odwuiIfRarWUlZXxb//tv2VlZUWcRyaIMIvFgsFgIDs7W/ZvoEI5uM/nIx6PS23OE7HZbDz77LO0trby6quvEgqFKC4uJicnR2rTnsidO3eYnp5GqVSybds28vLyJPeePU48HmdxcZG3336brKwsysvLKSoqktqsj4Ug1OUm0p9EKpVibW2Nzs5O5ubmcLlcshnIKfTUaW1t5VOf+hQ5OTnk5eVRVVX1xNmGGX5x5H36fwJ4/vnnOXr0qFjN8nD1UDKZRKPRiH1Y5HIZWywWTCYTtbW1KJXKp8J9qtVqqaioeCTBU6gWk3I+2S+C4K36L//lv6DVamVRMfJhaLVaqqurH6lClCMjIyOsra2Rm5srNmuTGysrK/T09PDDH/6Q73znO+zYsUPSHK5fBKPRyL59+8SJ43JmY2OD06dP09nZSXNzM8eOHZPNuStURn71q18VB/EKYWW5PltPG/L4pD+BCBtUyNX5OD8rl00tiJynBWHdHp4w/7SiUqnEHC65fwbCYSx32tvbycnJISsri61bt8pSnBkMBqqqqvjN3/xNtm3bJtueO09CrVazd+9e1Gq1rENwgicqkUiwc+dOsQJOLuss2CF4nORi1ycJxUe4IeXvo8yQIUOGDyCdTnP//n08Hg8qlYrq6mrJq3GeRDQaxe/3MzU1RUNDA1qt9qkQkwKJREL0pMpVqKfTaSKRCFeuXGF2dhaXy0V1dbXsekZl+CfzgQ93RvBkyJAhQ4YMGT4pfKDgkacUz5AhQ4YMGTJk+GckI3gyZMiQIUOGDJ94MoInQ4YMGTJkyPCJJ1OllSGDDBBy6YR2BU9LO4AM/3x8WD5lZh9kyPBPJyN4MmSQmIcnum9sbODxeDCbzbKaSfVxedKlnbmsP5rHBW86nX6kB4vwZznzQYJN7nbLmcya/vPydJ2mGTJ8Apmenub27dt0dHSwtLREY2Mjzz77LDt37nxqms89TDqdZnV1FbVaLc7hyvDRBAIB+vr6+OY3v8nS0hJlZWW88MILvPHGG7IspX+cVCpFOBxmYmKCcDiM3W7HbrfLtgP304AwUHR0dJRQKCQ2JywtLZX9fpAjGcEjE9bX1+nr66OmpgabzfaRzQql5uEmXhqNRpa9NwTPCSDLbsvCYXbu3Dl6e3sJBAIcP36curo6XC7XUzN5WiCRSBAMBrl06RJutxuXy0VzczMOh0Nq02RPMplkbW2NS5cuMTg4SDweJxQKEYlEsNvttLW1YTabZdebJ51Os7a2xv3791lYWGBmZoabN28SCASoqalh165dHD9+XJbDWp8GgsEgly9f5u2338bn81FQUMCxY8coKSkBMp6eX5SM4JEA4SKOx+Oo1WqUSiV+v587d+7gdDoxm81Sm/iRRCIR1tbWWF5eFpu5SXUYC+spzPOJxWJEo1Gi0SjLy8skk0mys7Ox2Wzk5ubKolW7YPPc3Bzd3d14PB5qamo4evQohYWFmz51/p9KIpFgbW2NkZERfvzjH4tzgYSRKnLh4bEuiURCbJinVqvFdv5S7ON4PI7P56O/vx+z2UxhYSGxWIyZmRk6Ojqorq5Gp9PJZqZdKpUiFouxvr7OnTt3uHfvHtPT00xOTnL37l3C4TDj4+MEg0GampqoqqqSZD8LLzzC2SA0RnySLQ8P7ZXDGSE8U2fPnuWnP/0pANu3b+fw4cOS2vU0kxE8EiBcysvLy9jtdrKysohEIkxOTkr+kH0c0uk0S0tLdHZ20tHRwb/7d/+OioqKTT2MHz7IBE9TOBwmmUyysLDAwsICs7OznD17Fr/fT1VVFW1tbRw/flxsfy/1WicSCS5evMjCwgIul4tXX31VVq3uP4zHcwt8Ph99fX18//vf59133+Vf/+t/TV1dHXa7XTLbHvbuPSyKY7EYwWAQv9+Pz+dDqVRis9kwGAzo9XoxjLiZn0M8Hsfv9zM/P8/zzz/PSy+9xPr6On/7t3/LuXPnOHDgAGazGZ1OJ4v9kUwmWVpa4vr16/zRH/0RU1NThEIhUUACDA0NoVarOXToEJWVlZtuo/D5x+NxwuEwqVQKlUqF0Wh8ZI8I3t9IJEI8HieVSpGTkyN53lQwGGRqaop33nmH5eVlGhsbaW5u5siRI7L0WD8NZASPBKysrDA0NMQPf4zBXOQAACAASURBVPhDfu/3fo/i4mIKCwv58pe/TEVFhSzDQw+TSCRwu92cP38ev99PIpGQZFJyLBbj2rVruN1u5ufnGRkZIRQKMTQ0xMLCArFYjNraWsLhMIODg7z33nt4PB6+8IUvSO5iF5KU+/r6sFqtNDQ0sHPnzqfuEEun03i9Xv7+7/+ed999l4sXL/LGG2/w4osvUlNTI4m3JJlMsrKywuLiIiaTidzcXNbX13G73XR3dzM8PIzH42FpaYnl5WWysrIoKyujtraW3bt38yu/8iub/jlsbGywurrKzMwMVVVVaLVadu3ahU6n45VXXuHkyZNotVqcTqcs9sj9+/c5ffo0f/RHf8Ts7KwoDrRaLVVVVWRlZeF2u0kmk5INFE2n02xsbHDhwgUuX76Mz+fDarVy+PBhVlZWWF1dZWNjA7PZjNPpZGpqitXVVRQKBV//+tcl97KOj49z6dIllpeXSafTHDhwgOPHj8tmuvvTSEbwbDKzs7Ncu3aN69evi2/AQr6OIHbkcKA9CUHUzM3NMTIywtTUFEeOHCE3N3fTc47S6TSBQIBz584xNjbG+vo66+vrZGVlUVxczN69e2lqamLLli0EAgEuXrxIZ2cnY2NjhMNhsrOzJRWWyWQSv9/P/fv3KSoqwmq1ykboLi8vMzc3x+joKB6Ph3g8LlYMLS8vk0gkiMViKBQKysrKmJ2d5erVq8zNzVFbW8tnP/tZSktLJfNG3Lt3j/Pnz9PR0YHZbMbhcBCJRAgEAvj9fvFNv6KigkOHDmE0Gunq6sJut1NSUiKJzYlEgmg0SjAY5M6dOwwPD2OxWCgsLGTXrl309/dTWlpKQUEBLpcLg8EgWYgoEolw7tw5zp49SyqV4tixYxQXF1NcXExBQQFqtZrp6WnOnj37yDDczSYYDDIwMMC3vvUt3G43CoUCm83G1NQUGxsbYug7GAyKP59KpcjNzeU3fuM3KCkpkTSX0mAwiGerWq2msLBQNoL3aSUjeDaJdDpNOBzmxo0bTExMYDKZ2LVrFwaDQXwLlupN6BchFosxPDzM2NgYyWSSXbt2YTKZJHmT12g0lJWVodVqxQPMZDLhdDopLi4WE8Bv374t/nxJSQkajUbyQ+Ph0IrNZsNms0lqj4CQhDowMMBPfvITNjY20Gq16HQ6dDodyWQStVpNOp1Gr9djMBhET4lGo2H//v00NjZiNBo3XcAJgnx+fp7R0VHGx8fZt28fOTk5xGIxbDYbGo0Gi8WCTqcjLy+PwsJCgsEgiUSC2tpaioqKJNkbGxsbBAIBQqEQi4uLDAwMoNVq0Wq1pFIp5ubmuHr1KiqVimeeeYaWlhbUarUktgYCAUZGRrh//z55eXni5y3kHrrdbqampsSEaymS79PpND6fjxs3btDb24vFYqGkpITKykry8vJIpVIoFAoCgQB37txhcHCQWCyGwWDAbDbL4uUjNzeX8vJyLBYL4XBYDLlm+MeTETybgJA7sLCwwLlz57DZbBw7dow9e/YADy6/ZDJJNBqVRRmycHEkk8n3CRmv18udO3cYHx8nLy+P3bt3S1Iyq1QqsVgsvPbaa6RSKdFes9mMVqtFrVaTSqVYWVnh8uXLDA4OotPpOHTokGQC7WFSqRQbGxtsbGyQl5dHbm6u+L3H8wtgc/NJQqEQc3Nz3Lx5E5vNRlFRkbim1dXVWCwWMQl8+/btjIyMYDabycnJ4cUXXyQ/P1+yCyOVSuHxeMR1ff3112lsbBTDrhaLhZycHDEpNRaLcffuXQ4fPiy+QUuB3+9naWmJSCSCQqHg9u3bLC4uolKpmJmZwefz0dXVxeLiIul0ml27dknWo8nv97O4uEgwGKSmpgar1cri4iJjY2N4PB4GBgZYWloiOzubgoICSdoSJBIJlpaWuHDhAqFQiPb2dg4cOEBLSwsOh0NMVBfWs6+vj0QigVarpaioSNwjUuJwOKipqcHpdDI7Oysm1Wf4x5MRPJtEPB7nJz/5CXq9nm3btrF3717g5zkQHo+HlZUV2traZOF9iMfjrKys4HA4xFh2IpHg5MmTXLx4EbPZzBe/+EXJXawPC4XHSSQSvPvuu/zoRz/CYDDw3HPP0djYKIu+MKFQiMHBQUZGRrBYLI8k9wrl6olEAp1Ot+kXW0NDAxUVFXz6059Go9Gg1WrRaDSo1Wr0er14EaRSKQKBAIuLi+Tl5bFz504OHDgg6aEcDAYZGhpCp9Px4osvcuLEiQ/8vIWEd4fDQUFBAVqtVrK9PDo6yu3bt0mn04RCIc6fP49GoyErKwulUonL5aK6upqGhgYOHDgg6R5WqVSoVCrW19fp7Oyks7NTFGpZWVliuFj4OSn2w9LSEv39/Vy9epXy8nK+8IUv0NbW9r7nDMDpdIpVXBaLhS1btmAymSQ/hwH0ej1bt25lYmKCaDQqu6rHp42M4NkEhOS5s2fP8sYbb9DU1CSGr2ZnZzl9+jTz8/Ps27dPkuTfx/H5fAwPD/Otb32L3/iN36C+vh6TycTg4CD/8A//QF1dHa2trbS3t0t+KHzQvx+JRHC73Xz/+99nfX2d+vp6WlpaZNHfSKgke+utt9DpdJhMJjFc5PV6uXXrFqOjo0QiEVpbW2ltbd208IVwaQlNAx+uBnn890LvmO7ubo4cOcKBAwfE9ZUqv8Tr9eJ2u3E4HOzevVsUBk+yZ2NjA5/PJ77tS1X5kkwmmZubY3x8XPxaIpEQvb7Z2dlYLBai0Sj9/f0sLCyQk5NDWVmZJB7h3NxcampqmJqawu12U1BQgN1uJz8/n+LiYoqKivjud79LMpkU22xs9rpOTEzQ19dHLBZj9+7dlJaWPtLuQ6FQ4PV6GR0dpbOzUxQSSqVSFi9E8MBGnU5HfX09Z86cEdspZPjHkxE8m4BQNp1MJikoKMBoNOL1ehkcHOTy5ct0dXWRSqUoKytjcXGRnJwctFqtZG/KarWarKwsFhYWOHnyJP39/RiNRkZGRqisrOTAgQNs27ZNPECkFj2A2NdodXWVxcVFJicnuXHjBrOzs7S3t3P48GHq6upkYWsoFGJhYYHBwUHggcAUEilv3bpFT08Ps7OzaDQaTCYTzc3Nm9oXREhQ/iiXfjKZxOfzYTKZqKyslLykXkio9fv9ZGdnP1Ii/TiJRIKVlRXGx8cpLy8HpNvHc3NzLCws4PP50Ov1lJSUUFtbi9FoJBQK0dXVxcLCAvPz8ygUCvH8KCwslMTe7OxsDh48SGFhIWtra+Tm5oqjUIxGI36/H4VCgcFgwGazSZJ38rB4zc7OFvP2UqkUwWCQubk5enp6uHr1KsPDw2JYXHjm5IJKpcJut6NSqcS+URn+8WQEzyahUCjQ6/X4fD6mp6eJxWJ0dHRw+/ZtgsEgVquV+fl5rl+/zu7du3E6nZIlqGm1Wux2OzU1NSwuLrKwsAA8CMv9+q//Os3NzRQWFspmzlMymWRjY4PZ2VkGBgYYGRmhr6+Pmzdvkp2dzbFjx2hraxO7k0pNNBolEAiwvr5OPB6nv7+flZUV1tbWuH37NuPj44RCIRwOB8FgUBZevyeRSqXw+/04HA6Kioo+NLy4WcTjcaLRqJjE/kHEYjHm5+fp7e2ltLRUkjUW/s2pqSlWVlZQKpXU1taKXr2cnBzW1taIRCL09PTg8/lIp9Pk5uZKticUCgUajYYdO3awdetWYrEYOp1O9ApGo1EuX75MJBLB4XCQn58vyTn2cPJxOBxmY2ODeDxOOp3G4/EwOjrKlStX6OzsZHFxUfx7WVlZ2Gw22fS5USqVZGdnk0qlWF1dZXl5WTaFF08j8rixPuGoVCp0Oh0Gg4E/+7M/E13oc3NzPPPMM9TV1aHT6ejr6+PNN9/k93//92lvb6eoqEgSe7VaLaWlpXz729/m+vXr/OAHP2BsbIzPfvazvP7665J6nx5HeKufnp7me9/7HmfOnGF+fp5IJILJZOJXf/VXOXjwIGVlZbJxVQuVQmVlZXR1dfG//tf/Eg+2xsZGtFoter2e6upq2tvb0el0slnvh0kmkwQCAUwmEwaDQRbhQqGTrl6v/9CO5YFAgLGxMa5du8brr78u2eWRSCQYGBggEAiwZcsWfuu3fosXXnhB/MyFKrlvfOMbbGxskE6nKSwspLS0FIPBIInNAEaj8ZFwmlCYISRX+/1+XC4X27dvl8RjYrPZyMvLQ6PRcPfuXdxuN0VFRRiNRtxuN36/n3A4/D5RbDAYJPOcfRihUIjLly9jNBopKiqipKRE8saITyMZwbNJ6HQ6/uN//I9cuHABn8+H0WikoaEBs9mMRqNhYWGBnp4e9u7dS3FxsaSHGSC6zrdu3SqGrw4dOiR5M67HmZyc5NSpU/z4xz/m+vXrOJ1ODh8+TFNTE83Nzezbtw+LxSIbbxSA2Wxmz549fPvb38bj8RCJRFhaWmJkZIQzZ86g0Wg4evQozz33HM3NzbIUO/AgB+bevXtiMqXUniihz0pxcTEOh+NDy6HX1taIxWLY7XbJeiAJFWW3b9+msbGRtrY29u/fL9othGhPnjzJ7Ows0WiUvLw8XnvtNex2u2wEvMDS0hK3b9/mzTffJCsri7q6OhoaGiSxpbi4mD179nDkyBHOnDnDqVOnUCqVHD9+nLa2NrZv387S0hJ3794V/47QgFBOgkelUmG1WlEoFHR3d7OxsYFer+df/at/JbvP/2lAPrfAJxjhrbO8vJyXXnqJeDwuJsf9+Z//ORMTE8TjcVwuF5/5zGeora2VheAB6OnpwWKxcODAAQoLC2XTGFG4XO/du8f169e5e/cuWVlZ/Nqv/Rqtra1UVFSQm5srih052CygUCjIzs7G5XLhdDoZHBzE7XbT2dnJysoKv/Zrv8aRI0fYsWOHrITa4ySTSVZXV9HpdGi1WsnLeBUKBWazmYqKCuLxOG63W6yGFBBGTMzMzLC6uorJZJIsPCAkKw8NDVFVVUVlZaXoJYtEIszMzHD16lU6Ozvx+/0UFBSwe/dujhw5Ipk3TXjuJiYmxEafpaWlzM/P09XVxfnz51lZWeGzn/0s27ZtIzc3V5K1VavVFBQU8MILL3DlyhVu3LghdrMuLy8XbXW73cCD0NGWLVuor6+XrDXBkxA8vwaDAZ/PRzAYZHZ2llgsJrtz7WlAvqfpJwzBYyLMcUmlUkQiEbGJW3Z2Ntu2bWP79u0YjUbJLw+hImBiYgKn04nL5ZJdS/N0Os3o6ChutxulUklbWxvPPvssDQ0N5Obmim/tcjsUhKRgnU7H0tISAwMD3Lt3j/v371NeXs4zzzxDfX29ZJfFx0EYjREIBAiHw7IpmdXpdLhcLsbGxhgYGGDfvn3k5+c/8jz5/X4mJiYIh8O4XC7JBI8QAkomk4/M8EokEkxOTnLr1i3OnDnD3NwcBoOB2tpa2tvbqa6ulnS4ZTqdZnh4mKGhIZLJJFVVVUxPT3Pv3j3u3r2L1WqlpaWF0tJSSZoOwgOhYDab2bFjBxUVFYyPj3Pnzh2CwSAlJSXcvXuXyclJ/H4/8KDybPfu3ezYsQOLxSKJzU9CqVRitVopKCggGo2KBTByPRfkTkbwSIDg8RF6hbS2tqLVamlqapKsDfvjCL1gFhcXcTgcsrHrcSYnJwmHw1RVVfHlL39ZbIQotWD8KISqsuvXr/PWW28xNjYmzk3au3fvI4JNjgiCx+/3Mzc3JybXStk4Uyipr6mpYWZmhtu3b3Pt2jUOHz6MXq8Xq3TGx8cZGhrCZrPR0tIiaWggkUiQl5dHVlYWoVBI7Bre2dnJ6dOn6ejoICsrS6yOPHHihCy6cvf39/Puu+8yOzuL0+lkZWVFrM565plnaG5uxuFwSGqjXq+nvLyctrY2FhYWmJ6eZmZmBpVKRTgcFnNgsrKyaGho4MSJE7S0tEjuXX8YjUZDfn4+dXV1eL1eNBoNVqs1k7T8jyQjeCREpVKxc+dOqc14IqlUirW1NdbW1kgkErJISH0SwngAwV45eBk+DslkkvX1dd555x3Gx8cpLi7m5Zdf5itf+Ypkc5J+ERKJBBsbG3i9XlZWVvB6vWJlmdTs3LkTp9NJQ0MD3//+9xkdHcVisaDRaIjFYpw9e1ZMqG1sbJTMTsELsbi4yA9+8AN6enqorq5maWmJU6dOsbS0hNPpZP/+/fzO7/wONTU1H5qIvRkI+zI/Px+r1cr169eZmZkBoKysjGeeeYY//MM/lLTbtoAQOn7hhReYnp4mkUhw//59MSynUqnIyclhz549fOMb36CyslJWYgd+3lG+urqa0dFRjEYju3fvlnWoW85kVk0i5H6hpVIpFhcXqaiooKysDKvVKrVJ70OhULBv3z7W1tbo6urinXfeYe/eveIYBLkj5JzU1dWxa9cuXn75ZXFMh9z3h9AULxqNUlRUhM1mkyx88TgKhQKn08m+ffswGAz87Gc/4+rVqywsLKBWq9m2bRsvvfQSjY2N4j6RYr1VKhVVVVX89m//Nh0dHXR1ddHd3U0sFqOkpIRjx47R2tpKU1MTZWVlopdKahQKBdu2bWNpaUkcxtvU1ERbWxsHDx4kLy9PFrl+wr+/fft2vvSlL+FyuUSvVH5+Pjt37qS5uZmWlhaqq6sl7bT9QQhtANrb21ldXSUrK4umpqan4oyQI/K/FTJIglKpJD8/n4MHD1JUVCQ7D4/wsNfX16NSqWhsbESn02Gz2Z4KsaNUKjEYDLz88suEQiFKSkooLi6WxUXxcRBCsiUlJRiNRvLy8mQz2FC4JKxWKw0NDSSTSSorK1lfXxdFRl1dHTk5OZKuteDheeaZZ3A4HLjdbrHaTRiA63K5cDgcsmtNUFJSIs6lEwRaeXm5mBMlJwwGAw0NDajVavLy8vD5fDgcDsrLyykvL6e4uBidTifb505IqH7ppZdQKpWy8KI+rSg+opRUnh3PMvzSeXyApVwPAyEB/GE3tVxtfZyHbVcqlbK60D6KeDzO8vIyP/rRjzCZTOzbt4/y8nJxZIpcEKqyHt4jwlrLZZ8I9gndfgHRPrnuCWFdHx7JIKc1fRxhWG8wGESlUondl5+m80JYa7nnJ8qAD/xAM4InQ4YMGTJkyPBJ4QMFjzxfHzJkyJAhQ4YMGf4ZyQieDBkyZMiQIcMnnozgyZAhQ4YMGTJ84skIngwZMmTIkCHDJ56M4MmQIUOGDBkyfOKRf8OSDBkyZPhnIBaL4fV6efvtt2lvb6e0tFTSURgfRTqdJhaLcefOHYaGhqivr2fXrl2y64mVIcPTQkbwZMiQ4ROP0Deos7OTn/3sZ1RVVeF0OmUreNLpNIFAgOnpaf7hH/4Bp9NJMpmUbV+ep5FQKEQkEgHAZrPJso+Q0O9odXWVRCKBVqslJydHarOeWjJPj0QIb29CZ1U5Izx0j/+SEx/HLjnb/zByX+snITTPk9ueFtbP7/czMjLCD3/4Q4aHhwkEArKeuxaNRpmdneXy5cucP3+enJwc7HZ7puncPxPJZJKFhQUGBgYYHBwkGo3KZs8+jHBP9Pf3c+fOHfr7+/F6vSQSCVnaK3cyHh4JECZlz8zMkJeXJ3b9lBOPP0wf9+GS4g3p8a7Qwp8ftuXhn3n8e1LzpLV9+GvC/0nKtX3Ylg/6uWAwyMLCgug5kXrEh2B7LBbj5s2b/PSnP6Wzs5MXX3yRkpISTCaTpPZ9EOl0muHhYc6ePcuPfvQjvvzlL3PixAny8/NltW8/ig86M6T8Pwg2+f1+Tp06xZkzZ9Dr9fzpn/6pOLVeTiSTSVZXV/nTP/1ThoeHycnJ4eWXX+aLX/wiOTk5srs35E5G8EhAIBBgYmKCP/mTP+FrX/saZWVlsty4qVSK0dFRxsbGmJmZwePxoFAo8Hq9WK1WcaihRqMhJyeHnJwcSaYNJxIJVlZW+PGPf0xeXh6NjY0UFRWRnZ39yM+sr69z7tw5zGYzTU1NlJSUbLqtT0KwbXZ2lu7ubpaXl5mbmyOdTnP8+HFOnDghyf4QvCMTExOsra0BsGfPnideWOvr61y5coXvfve7fP3rX2fbtm2yERSXL1/mhz/8IVNTU/zu7/4un//85yksLJTdGAz4+ctQT08P09PTVFRU8LnPfQ6TySS5gPxFiUQi+Hw+cWhrYWEhJpNJ8iGziUSC69evc+PGDQYGBnA6nQSDQXJycmQneIT9EAwG8Xq93L9/n5mZGWpqajh06BA2m01qE58qnq4n6BPC6uoqg4ODjIyMEIvFZOmaTCaTTE9P8+abbzI3N0c8Hsdut4u5BSsrK0xMTJBOp1Gr1Wzfvp22tjZ279696bO3fD4fIyMjnDx5kqysLPbv309LSwutra2iHV6vl/7+ft566y1OnDhBTU3Nptn3QQju6lu3bnH37l3u3r3L6Ogo8Xgcn89HdnY2eXl5PPvss6jVaknejH0+HxcvXmRiYgKj0cju3bsfyXUQRNHo6Cjd3d1MT0/LZj8L69vV1YXD4aC2tpYjR45QVFQky8nYAsFgkMnJSeLxOO3t7VgsFlnmlzwJYb7W8vIyvb29DA0NMTMzw86dO9Hr9ej1ekkFTzweZ2BggLfffpve3l7xOVtbW6OgoEAyuz4IlUolenWi0Si9vb14vV7Gx8dpaWmR2rynjozg2WT8fj8TExN0d3eLCXNyO8ii0Sher5fLly/T3d1NVlYWRUVFVFZWkkqlCIVCrKysMD09TU9PD4lEAqVSSW1t7aaHXlKpFMvLywwMDNDd3U0ymUSr1eJ0OmlpaUGhUJBIJJibm6Orq4v+/n5eeOEFSd+WhVyXtbU1xsfH6ejoYGhoiLm5OeDBfohEImxsbLC+vi6JgBCEzOTkJNevX2d2dpatW7c+MowzlUoRjUZZWVmhp6eHqakpnE4nVqtVcm+EIHbGxsZYXFykrq6OnTt30tjYKJl4/LgEg0Hm5+dJpVI0NDTIVuykUimSySSxWAylUimuudvtZnx8nJGREebm5giHw6hUKsn/H8J+7erqoq+vj2QySXFxMTabjenpacrLyzGbzbJaa6VSidFopKGhgQsXLqBWq4nFYvj9flnnoMmVjODZJIRLa2RkhAsXLnDmzBny8vLQarWyq7zwer309PTwP//n/6SxsZHnnnuOtrY2cnJySCaTeL1eFhcXGRgY4P79+ywtLWE2mykqKtr0pMpEIsHExATXr1/H4/Gg0WiIRCLE43FxXUOhEPfu3ePMmTMYDAa2bt266ZUOD+cQxWIx5ufnOX/+PN/73vdIJpNUVFTw6quvcuzYMcbGxnjrrbcYHR2ltLSUrKysTT+EBTvfe+89enp6sNls7N27l2QySTweJx6PEw6HmZub48yZM9y4cQONRsMXvvAFqqqqJA9bpFIpvF4vf/u3f4vJZKKpqYlt27ZJLsQ+DsFgkMXFRbKzs7FarVKb80TS6TSJRIJAIMD8/DxZWVkkk0k8Hg9/8zd/w+TkJDt27KC9vZ3W1lbsdjsajUbSsy6VShEIBLh69Spms5nm5mZcLhexWIxLly5RX18vSy+PQqFgZWUFn8/HxsYGKpWK3Nzcp2Ivy43Mim0S6XSatbU13nnnHfr7+7Hb7eTm5pJIJGSn1JPJJAqFgpdffpnf+q3fQq1Ws7a2xr1798Swy/3795mdnSUWi1FdXU1jYyOVlZWbbuvGxgYej4fFxUXS6TQtLS38yq/8CgcOHAAerPu9e/fo6urC7XZz4sQJXC6XZLlG3d3d3Lx5k5s3b9LZ2Ul7ezsvvPACjY2NlJaWotFo6OzsxOfzYbPZOHbsmCQHWzQaZWJigh/84AcsLy+jVqvp6upicHCQjY0NQqEQa2trDA8P4/f7+dVf/VU+9alPsX//flkI+Gg0isfjoa+vj6997WtUVVU9NRVOWq1WLGSIxWJSm/OBhMNhJiYm+MM//EOCwSCpVEr8+r//9/+eXbt2UVBQIJt1V6lU2Gw2vvSlL+FyuTCbzYTDYTo6OnjnnXdYXV0lmUzKSkgIOTxTU1N4vV40Gg3FxcUcO3YMi8UitXlPHfL5ZD/hCL0UxsfHmZ+fBx4cynLL4UkkEqyurjIwMMDVq1dZW1vD7/fj8XgIhUIkEgmysrLIy8tj+/btLCwssG3bNurr6yVJAhXyiVZXV7FarTz//PNs374du91OIpFgeXmZH//4x9y5cwetVkt7ezsGg2FTD+FUKkU4HOb69ev81V/9FT6fD4VCQXt7O7/5m7/Jli1bsNlsqFQqFhcXuXjxIrOzs5SVlZGTk7PpOVHwYG+63W5KSkowGo2oVCpGR0dxOBwolUqCwaAYbguFQvT29uJ0OqmrqyM3N1fysIDf72d+fp5EIoHdbhf3plDOGwqFxL42ZrNZ8nDLw2i1WqxWK8lkkmAwKLU5T0QQOydPnqS/v59IJEI6nUalUmEwGEgkEgCyWld4sLaNjY3odDpUKhXhcJhwOAwghmnlRDKZZGVlhUuXLrGwsIBOp6OyshKbzSYrYfa0kFmxTUKhUKBSqbBareh0Onw+H4FAAJ/PJ4oeORwMqVRKDFcIvSo2NjaIx+NYLBZKS0ux2+1YrVYMBgNer5eCggKsVqskb3KxWExsIGaxWGhsbMRqtYoX3tTUFF1dXYRCIWpqamhsbNz0hNVkMonP5+PatWsMDQ3hcDgoKSmhuLgYlUqFx+NhdXWVSCTC8PAwAwMDWCwWampqMJlMkuwLtVpNbm4uL730EpFIRPRCWiwW1Go10WiUYDDI2toavb29RCIRent7KSws5NixY5jNZkkP5HA4jNfrxWAwoNfrRfE7Pz9PKBRicXERnU5HcXExdXV1svBKCajVanQ6HdFolGg0KrU5TyQejxOJRAgGg5SXlz8iyuPxOPfu3aOwsFCyys0nIdhoNpuBB95hwUtZXFyM0WiU1T6An1egjo2NEQgEcDqdlJeXYzKZZGfr00BG8GwiQtw4nU4zMDAg9i0pLy/HYrHIpjQ9KysLu91OQ0MDZrMZUfxr7gAADqlJREFUvV6P0WgkPz+f5uZmzGYzoVCI4eFhVlZWRMEmhWgTEifhQbfUsrIyMVn18uXLjI2NMTQ0hMvlorm5maqqqk23Uch1GBwcJCsri+LiYkpLS1GpVFy/fh2lUkkymSQcDtPf38/s7CxNTU20trZK1glYr9eLib5KpfKJh2sikcDv93P+/HlOnz7N1NQUf/d3f0dtbS01NTWSCh5BCGdnZxMIBAiFQiwsLHDjxg0WFhZYWFigrKyMw4cPs2XLFlklMiuVSjQaDfF4XPSUyBG9Xk9VVRW1tbVi36V4PM7ExARdXV0UFxfjdDopLS2V1frCA4+7z+cTk/KPHz+O3W6XndckHo+LeZLRaPT/tXcvMXGVfRjAn8NcGAaYGabMhQFmGG5CC1KggwUtpS2tNqaNkZqYplEXmrpxoQs3ujFxp2tZGTW68ZLYmNSYqJSLFJCWyqUQLnJxuF/KDAMMDAPzLcw5glL7ffm+j3N6fH5JN2Xzcjgz5znv+3//L4xGo9Ryg4HnP6esv66KxcXFwWaz4cUXX8Szzz6Le/fuYWZmBteuXZOK+bxer9zDhE6nQ2FhIXJycqQdT+IOi93EnVB+vx83btyAw+FAYWHhgY83KSkJNptNqhVISkpCa2srrl+/jq+//hrRaBQ7OztSIa0cX7rx8fFIS0vDlStX0NfXh87OTnzxxRdYWFiAXq+HyWSC2+1GTk4OEhISkJmZiZKSEjz66KMHPlZRXFzcA9/MxZqIS5cuobKyEj/99BM++ugjdHR0wOVy7emDdNAsFgucTic6Ozvx8ssvSy8TW1tbmJycxMWLF3Hq1CnU1tYqrh+PVquF0WjE9va24pZYRGazGaWlpSgtLf3LZ0osAm5vb8dnn32Gy5cvIycnR3GB55dffsG3336LyclJnDlzBna7Xe5h/UUoFMJ3332HSCQi7TJbWVlBJBJRdGsFpWLgOUCCIECr1cJsNiM5ORkulwsffvghBgYGYLFYFBF4BEGQlrSMRuOeN7PdHy7xIMbFxUUkJyfL9nATA4/FYkFvby/ee+893LlzB36/H06nE263G4ODg5ienkZLSwuuXr164A84QRCQnJyM06dPo6qqCmfOnMH4+DgmJyfhdDpRUFAAg8GA2dlZvPnmm7hw4QKqqqrgcDgOdJy7RSIRzM/Pw+Fw3PftfPf/ifU7Pp8PLS0tOH36NGw2m2xfyCaTCQUFBXj11VexvLyMwsJCeDweaDQafP7556irq0NBQYG0m0xJD45oNCrtNJR7t5tI7K8jzjIAe6/Z7r5Mer0ePp8Pk5OT6O/vx48//giv13vgMxLimMWl9t1d2AcHB9HY2Ii+vj4888wz8Hg8igu+wO8z2GL7EuD3z+XS0hI2NjZk3/X2MGLgOWBiLQ/wxzq4TqeT9W34z9bW1jA2Nobp6WmcPHkSycnJe+pzwuEwpqen0d3djZSUFBQXF8PlcskyVnGJKD8/H+3t7Whra4PL5UJRURGysrLgcDhw/fp1jI2NIRAISA+Rg3zAibUDRqMRCQkJyM/Ph9PpRCgUQlJSEiwWC/x+P4aGhuByuXDq1Cnk5eXJ+rATv2i/+eYbFBYWIi0tTer2u9+102g0iI+Ph16vx/DwMDY2NmStSxML68+dOyd10Q2Hw2hpaUFaWhocDodUrKw0kUgEoVAI0WhUMUssYjuKpqYmHD58GBkZGfvWl4mhQnwRMRqNGBkZkWXJe319HePj4wiHwzAYDEhMTERiYiKmp6fxww8/oKenBzs7O6isrJS95ux+xLpP8brpdDqYTCbo9XpF3rtKp7y/8D/A7m6k4XAYJpMJNptN7mFJtra2EAgE0NjYCIfDAY/HA4vFAp1Oh42NDUxPT6Ovrw9dXV0oKChASUmJbOf8aLVaZGRkoLi4GGazGYuLi6itrUVNTQ0eeeQRxMfHY3R0FMFgEFtbW7LuiBODj8Vi2dNfJRQKwe/3o6urC8XFxSgpKZH9oMi4uDhotVp0dHRgdXUVXq8XLpcLTqdTqh/481ll4sxgIBCQvfZEq9UiOTkZhw8flnryTExMoKGhAc8995y080yJNjY2EAwGERcXp5ijDsSdbbdu3UIwGITP55OKZ4G/zpBpNBokJyfDYDBgZGTkwJfmxANjOzs7pZlUh8MBs9mMtrY2NDQ0YH5+HhkZGdJMnxIDRFxcnBQsBUGQAo9Wq8X29jbC4TA2Nzeh1WqRlJQky47OhwkDjwxisRg2NjbQ39+P9fV1adeOUqSkpMDr9WJychL19fWoqanB8ePHYbfbMTg4iKamJty6dQsjIyN46623pJ1RchAEARkZGXj88cdx4cIF9Pf3w+fzwefzwWw2IxgMYnV1Fdvb2zCZTDAajYr7QhB3YYyMjODy5cvSTig56fV6uN1uuFwufP/999jc3ITb7UZdXR2KioqQmJgoPSBisRjC4TCWlpYwMTEhNZlTksHBQXR2diIQCODs2bPScQ1KtLy8jPn5eZhMJsWcR6bVapGYmAiXy4WvvvoKc3NzOHHiBCorK6HRaPY9bHh7e1vaCXXQLxqxWAzz8/O4du0ampubcfLkSXg8HgiCgE8++QTx8fHIzs5GQUGBItoo/B0xLAqCIL1oiH2P/H4/xsfHYbVa8dhjjylyWU5JGHhksLa2hqGhIbz//vuorq5GXl4eEhIS5B6WJD4+HhkZGXjttdfw7rvvor6+Hh9//DHsdjuGhoYgCALcbjeuXLmC8+fPy74cp9PpkJmZiTfeeAO//vqr1C1V7A9z8+ZNmM1mPPnkk7IHif309vYiEAjg6NGjKCsrU0zdhkajwdWrV3H+/Hm0trbiyy+/xI0bN1BQUIDq6mqUlZVhbW0Nt2/fxt27dzE8PIypqSm8/fbbcDgcinmIiF2tBwYGUFdXB7PZrNjZnVgsJhWzm81m2T9bu1mtVrzwwgvQarVobGzEzZs3UV5ejpdeegmHDh2SetuIx70MDw9jZWVFluaZgiDAYDBI56b9/PPP6OrqgtFoxLlz53Dx4kXk5+cjPT1dUffqn+3s7GB1dRWxWAwGgwGHDh1CdnY2ZmZmMDo6isbGRnR0dKCmpgZHjx5l4HkA5X37/wPMzc2hp6cH8/PzOHbsGNLS0hT1gRMEAXq9HkVFRXj99dfR1NSE7u5uzM7OSoeE5ufnIzMzc9/lDTnGq9FopJmFsbExdHV1YXR0FO3t7dBoNCgrK8MTTzyhqOssHt8wPj4OjUaD6upqxcxAibUYBoMBbrcbRqMRubm5aG9vx+3bt9HQ0ICWlhbMzMxgaWkJWq0Wdrsdzz//PGpraxV1JlFraysCgYC0DV3u+/VB5ubmYLPZ4PF4pJ4xchNnF5KSkvD000+juLgYv/32G4aHh/HOO+8gOzsbTqcTFosFoVAIIyMjmJqagtlsRkVFhSzX3OVy4ZVXXoHP50MkEkFiYiJsNhtSU1ORlpaGxMREGAwGxc70iXaH81AohJ6eHvT29mJwcBDBYBBWqxU+n08xL0pKxsBzwDY3NzExMYHu7m5YrVZ4vV7Zmsv9HUEQkJKSIh3AaTKZsLCwgLKyMhw/fhzp6enSrJQSxi72LklJScHU1BRWV1cxMDCA4eFhVFRUoKSkBB6PR+5h/sXKygoWFhakehONRqOI6wnsLbYWe6qItS/z8/NYWVlBKBSCwWCAw+FAbm4uqqqqkJmZqYiHiHjIaW9vLwDA4/FIyxpKJI53eXkZdrsdmZmZimnaB/yxy9Tj8cButyM9PR16vR5+vx/r6+sIBoPS4cJbW1tIS0tDVlYWsrOzD/yaC4IgHbrpcDiwtbWFhISEPQfbKvU+2E285uJ5etFoFLOzs3t6o3m9Xhw5cgQ6ne6h+J3kxMBzQMQ17MXFRangt6KiAk6nU5HTkOIHx2Kx4MSJEygrK8P6+jocDgf0er0ilwTELwe3242VlRXcvXsXXq8XTz31FI4dO6aYegiRuHwRDAaRmpqKrKwsuYd0X3FxcYiPj0d5eTk8Hg/C4TDW19exuLiInZ0dWCwWWK1WpKamKmoGJRqNYmJiArm5ucjJyVH8W/DOzg6i0agUFJS01L1bQkICPB4PHA4HvF6v1Jld3I1VXl6O1NRU2Gw22frbiN8HSjwQ9N+l0WhgNpuRkZEB4PdlRZ1Oh7KyMuTl5cFut8NqtcrawuJhIjygmEw5hzw95MRdLB988AGam5sRCARQX1+PnJwcRb3V72e/e0Tp4xXflsXzffbrJSS3nZ0dtLW1obm5GTk5Obh06dJDscvi3ylAVcLvIC4ZfvrppygtLcWRI0cU2XdHJF5X8fDe3f+U6D8tRFbq76FkYvG3eN6XRqORXjgf1BvrH+y+F4GB54CIN+6dO3cwNzeHWCyGs2fPslvm/8mf72slXmNxq+/i4iISEhKkN2EljvVhJAbfYDAIg8Gg2K3Huz0M9y0dHPF+2L1Ta7+Gj7QHA4/cxC/fe/fuYWNjA4IgSM36eNP+M4mfvUgkIhWKExHRf4WBh4iIiFTvvoFH2fO7RERERP8DDDxERESkegw8REREpHoMPERERKR6DDxERESkegw8REREpHoMPERERKR6DDxERESkegw8REREpHoMPERERKR6DDxERESkegw8REREpHoMPERERKR6DDxERESkegw8REREpHoMPERERKR6DDxERESkegw8REREpHoMPERERKR6DDxERESkegw8REREpHoMPERERKR6DDxERESkegw8REREpHoMPERERKR6DDxERESkegw8REREpHoMPERERKR6DDxERESkegw8REREpHoMPERERKR6DDxERESkegw8REREpHoMPERERKR6DDxERESkegw8REREpHoMPERERKR6DDxERESkegw8REREpHoMPERERKR6DDxERESkegw8REREpHoMPERERKR6DDxERESkegw8REREpHraB/xcOJBREBEREf0fcYaHiIiIVI+Bh4iIiFSPgYeIiIhUj4GHiIiIVI+Bh4iIiFSPgYeIiIhU71+YBAiBeRmtUAAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 720x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "GZmgXnTOCIWX",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": 0,
      "outputs": []
    }
  ]
}