{ "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.4.1" }, "name": "", "signature": "sha256:8f355da03b134e4804198bbac0e6b38e5ea4b98c390ff98dfc982ae585ac7241" }, "nbformat": 3, "nbformat_minor": 0, "worksheets": [ { "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "[![Py4Life](https://raw.githubusercontent.com/Py4Life/TAU2015/gh-pages/img/Py4Life-logo-small.png)](http://py4life.github.io/TAU2015/)\n", "\n", "## Exam - 6.7.2015\n", "\n", "### Tel-Aviv University / 0411-3122 / Spring 2015" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## General instructions\n", "* Exam duration: two hours (9:00-11:00)\n", "* Allowed material: \n", " * full access to the internet.\n", " * Personal laptops are allowed.\n", " * Email, phones, SMS, and messaging are prohibited.\n", " \n", "* Answer all three questions, in the dedicated boxes within the notebook.\n", "* The expected outputs are included. Try to replicate them with your code.\n", "* Make sure you follow the instructions and generate the outputs exactly as described.\n", "* __Exam submission__: Submit your exam __through Moodle__, in the dedicated place.\n", "* You can change your submission as many times as you wish, within the exam time limit.\n", "* Before making your final submission, __make sure all your solutions are there!__\n", "\n", "\n", "Good luck!" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 1) Distance between sequences\n", "\n", "A common task in sequence analysis is to calculate the distance between two DNA sequences of equal lengths. \n", "There are many ways to define this distance, but the most simple one is called the _Hamming distance_. This distance is defined as the number of differences between two sequences of the same length. \n", "For example, the Hamming distance between `AGGTCT` and `AGCTAT` is 2. The distance between two identical sequences is 0. \n", " \n", "__a)__ Write a function that receives two strings, representing DNA sequences, and returns the Hamming distance between them as an integer. Use an assertion to verify that the sequences are of the same length." ] }, { "cell_type": "code", "collapsed": false, "input": [ "def hamming_distance(seq1, seq2):\n", " \"\"\"\n", " Calculates the Hamming distance of two DNA sequences, given as strings.\n", " Returns score as an integer.\n", " Input sequences must have the same length!\n", " \"\"\"\n", " pass \n", " \n", " \n", "assert hamming_distance('AGGTCT', 'AGGTCT') == 0\n", "assert hamming_distance('AGGTCT', 'AGCTAT') == 2" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 3 }, { "cell_type": "markdown", "metadata": {}, "source": [ "A more complex way of evaluating distance between sequences is using a _Cost-matrix_. \n", "Such a matrix describes the cost of each difference between the sequences.\n", "For example, a change from `A` to `G` may have a cost of 1, while a change from `A` to `T` may have a cost of 3. \n", "This method is sometimes called the _Sankoff distance_. \n", "The file `cost_matrix.txt` contains such a matrix, in a tab-delimited format. \n", "Using this matrix, the Sankoff distance between `AGGTCT` and `AGCTAT` is 6. \n", " \n", "__b)__ Write a function that receives a path to a cost matrix file (using the format described above), parses it and stores the information in a data structure of your choice. The function will return this data structure. __In this section, you are not allowed to import any modules!__." ] }, { "cell_type": "code", "collapsed": false, "input": [ "def read_cost_matrix(filename):\n", " \"\"\"\n", " Parses a cost matrix file.\n", " \"\"\"\n", " pass \n", " \n", " \n", "mat = read_cost_matrix('cost_matrix.txt')\n", "assert mat != None" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 11 }, { "cell_type": "markdown", "metadata": {}, "source": [ "__c)__ Write a function that receives two strings, representing DNA sequences, and a cost matrix (formated as defined by the function in section b), and returns the Sankoff distance between the sequences based on the given matrix as an integer. \n", "Use an assertion to verify that the sequences are of the same length." ] }, { "cell_type": "code", "collapsed": false, "input": [ "def sankoff_distance(seq1, seq2, cost_mat):\n", " \"\"\"\n", " Calculates the Sankoff distance of two DNA sequences, given as strings,\n", " based on a given cost matrix.\n", " Returns score as an integer.\n", " Input sequences must have the same length!\n", " \"\"\"\n", " pass \n", " \n", " \n", "assert sankoff_distance('AGGTCT', 'AGGTCT',mat) == 0\n", "assert sankoff_distance('AGGTCT', 'AGCTAT',mat) == 6" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 12 }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 2) 16S Kink-turn\n", "The Kink-turn (usually called K-turn) is a common structural motiff found in many bacterial 16S rRNA sequences. \n", "It introduces a very tight kink into the axis of helical RNA. The motiff occurs in sequences of the form `CGRNNGANC` (where `R` is `A` or `G` and `N` is any nucleotide). \n", " \n", "__a)__ Write a function that receives a list of GenBank accession IDs (as strings) and returns a list of `SeqRecord` objects, fetched from GenBank according to these accessions, like we did in [lecture 6](http://nbviewer.ipython.org/github/Py4Life/TAU2015/blob/master/lecture6.ipynb)." ] }, { "cell_type": "code", "collapsed": false, "input": [ "from Bio import Entrez, SeqIO\n", "Entrez.email = 'A.N.Other@example.com'\n", "\n", "def fetch_gb_records(gb_acc_list):\n", " \"\"\"\n", " Receives a list of GB accessions as strings.\n", " Returns a list of the corresponding SeqRecords.\n", " \"\"\"\n", " pass\n", " \n", "\n", "bacteria_16s_accessions = ['EU014689','AJ578036','AF201899','NR_028978','EU118114','AM158979','AY773947','AJ697941','X81660','X83947']\n", "bacteria_16s_records = fetch_gb_records(bacteria_16s_accessions)\n", "assert len(bacteria_16s_records) == len(bacteria_16s_accessions)" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 15 }, { "cell_type": "markdown", "metadata": {}, "source": [ "__b)__ Write a function that receives a list of `SeqRecord`s and checks for each sequence if it contains a certain motiff, given as a pre-compiled regular expression. \n", "If it does, store the exact sequence of the motiff (__only__ the motiff, not the whole sequence!) in a `dict`. The function returns a `dict` where the keys are the organism names and the values are the motiff sequences, as strings. If a sequence does not include the motiff, do not add it to the `dict`. \n", "Complete the regex to scan the 16S sequences for K-turn motiffs." ] }, { "cell_type": "code", "collapsed": false, "input": [ "import re\n", "\n", "def find_motiff_in_records(rec_list,motiff_regex):\n", " \"\"\"\n", " Receives a list of SeqRecords and searches them for a motiff, given as a regex.\n", " Returns a dictionary where the keys are the organism names and the values are the matched motiffs.\n", " \"\"\"\n", " pass\n", "\n", "kink_turn_regex = re.compile(r'CG[AG][AGCT]{2}GA[AGCT]C')\n", "kink_turn_motiffs_dict = find_motiff_in_records(bacteria_16s_records,kink_turn_regex)" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 23 }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 3) Relation between litter size and birth weight\n", "\n", "In this question we will look for a relation between litter or clutch size (number of offspring per reproductive cycle) and the birth weight (the weight of the offpring) in the animal kingdom.\n", "\n", "For this analysis we will load the [AnAge](http://genomics.senescence.info/download.html#anage) dataset that we used in [lecture 7](http://nbviewer.ipython.org/github/Py4Life/TAU2015/blob/master/lecture7.ipynb).\n", "\n", "First, import the neccesary libraries:" ] }, { "cell_type": "code", "collapsed": true, "input": [ "%matplotlib inline\n", "import matplotlib.pyplot as plt\n", "import numpy as np\n", "import scipy\n", "import pandas as pd\n", "import seaborn as sns\n", "import urllib\n", "import zipfile" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 1 }, { "cell_type": "markdown", "metadata": {}, "source": [ "**a)** Get the zip file containing the data, extract it and read the data to a `DataFrame`. We are interested in the `Litter/Clutch size` and `Birth weight (g)` columns." ] }, { "cell_type": "code", "collapsed": false, "input": [], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 11, "text": [ "('anage_dataset.zip', )" ] } ], "prompt_number": 11 }, { "cell_type": "code", "collapsed": false, "input": [], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 12 }, { "cell_type": "markdown", "metadata": {}, "source": [ "**b)** If you examined the data you might have noticed that some rows have a `NaN` value in our columns of interest. \n", "We need to remove these rows from the data. You can use `np.isnan`, `np.isfinite` or any other method you'd like." ] }, { "cell_type": "code", "collapsed": true, "input": [], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 13 }, { "cell_type": "markdown", "metadata": {}, "source": [ "**c)** Plot a scatter plot of the data to exmaine it. Use the litter size on the x-axis. Don't forget the axis labels." ] }, { "cell_type": "code", "collapsed": false, "input": [], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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"text": [ "" ] } ], "prompt_number": 8 }, { "cell_type": "markdown", "metadata": {}, "source": [ "**d)** We are looking for a possible linear relationship between the variables. \n", "Apply a log transformation on the data (both columns) and plot a new scatter plot of the transformed data (don't forget the axis labels should change to reflect the transformation!)." ] }, { "cell_type": "code", "collapsed": false, "input": [], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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bL5vMvDc34DWlYQ2UcfNN7R93WCwWsuN1yoIBDEYT/sZyRk3MiEK0QoieJJLF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\n4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"text": [ "" ] } ], "prompt_number": 10 }, { "cell_type": "markdown", "metadata": {}, "source": [ "**e)** Perform linear regression on the transformed data and print the intercept and slope of the regression." ] }, { "cell_type": "code", "collapsed": false, "input": [], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "intercept: 5.718, slope: -2.434\n" ] } ], "prompt_number": 30 }, { "cell_type": "markdown", "metadata": {}, "source": [ "**f)** Plot a scatterplot of data together with a line for the linear regression." ] }, { "cell_type": "code", "collapsed": false, "input": [], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 23, "text": [ "[]" ] }, { "metadata": {}, "output_type": "display_data", "png": 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4+vyxzHnnS7ymNKyBQq6e0fRxh8VioWu8TmEwgMFowl9TxNDRGVGIVgjRkUSy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\nqpSqAXwJt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"text": [ "" ] } ], "prompt_number": 23 }, { "cell_type": "code", "collapsed": false, "input": [], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 24, "text": [ "(-5, 15)" ] }, { "metadata": {}, "output_type": "display_data", "png": 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bLoeNQJnzomwRCAQzMx8Hexq4RtO0KzVNuxK4Bqsm9mYsh7uiqfC5CHgmy6IU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\njcWLjo8lM6RzudxURieZyvL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AyVjEqpPVZ3AcEwPBT3aN0dY1VvBaKjPZWXbwaB+v5uxs\nri3ja7dvomcoWnR8MJKypmzlFrtsioTLoZDM5WvtNimvSgtWlP31Ozbx4akhais97N00t4O9YmMV\np3tDnOoJ4XHauP/6tTTWeOkfjdPWFaTC5+KLt2zgfz5xNPcOidFIklg8y+du3lB0vtFIkrYpw2w6\n+iL0jcZoOk8eWCC4GObjYP/FgluxwllV7WbwPLM/xxMZwrE06xoCtPdF6BqIYldk7rpmNWAtJt1/\nw1ruu76leEYAcOc1awjH0sSSGcLj6RlzsFdvruPk2RAyEaLxNNEZalEnHHq5zznr47luGLx+pC+/\n3TM0jtYTmlGZwKbIyDLoOiBZE7pqy5V8d1WZ21HQCBCJpfn5K6eJxNNWPa0Je6dEsZFYmnRGzzdO\nKLLMF2/daM2YtVvDaMbGrQUtS0kiQWd/hGR68oZiGBBNpPn4zAiGYbKtpRKnY3LM4/SM+VAoQSyR\nYV2DH/sMi4sCwcUyH1XZ1xfBjhXNVZvrciVCOfnrafLWH2nDPPtOF2BFeF+9fRM+tx2301Y0SWom\n5wpWB9T/9sguwuMpDh7tK5paBVa+9Hfv2UJoPIVuGLxyuJeXD/fmX5dlcDktQcVt66pwORTGZ3DC\nEhKpdJbhXGQ6kRf2OO1Mdktb1Fa4qQm4SesGEjCeSBONZ/C4bPg8duw2hf7ReL6b7ZMzI/laXBN4\n61h/3sEeOjHIS4e6MUxQm8r5wy/sLvhsEzz9Zgcj4URO8DHLSx+cLRg0bpjw5if9RHNVEodPDfGN\nu7Zgt8n4vQ5uv6qZlw/3YJjWmMFnc8Nn6qs8fOOuzcLJCkrGXHWw/1nTtP9TVdXHZ3jZ1DTt8wto\n14ri6i11/ObDXroHo9gVhftvLOzcmphMBVZutLVjlHuubbng63hcNo62j3CiO2Q9hs8QgcqylF8t\nf+imtfSPxvMTuwwDAl4nO9dbtbDxWSoRJMmaKTuhfBAaT/PaR73EksVlXXvUGs72RzjaMUoyrePI\nVSKk0joOu4LbYbO0wHLYp1UqTCo4GBz4oCefv9V6Q7R1jrLKX9wMMRJOFqRJ4kndWqgyDEysITSD\nY/F8KVz/aJy+kRhrVllzEK7eUoff6yCV1nn67c78Ta1/NE77uQib14iJWILSMFcEOyGf/TzF8wjE\nqsAUTnSNcXYgimGCbug8+3YXN00REPS6ChfBpm9fCGM5+RW7TS5wsIoMBw5180n7KD6PnYduXEel\n30UqnaHC58gtksGxjiB/8fOPuOu6FvTpg1pzJFJ6Xu57guNdwXxedSrhWJquwSiKIpNIpZAkG5V+\nJ+HxNC67zCP71xeUR+1Ra9G6Q3QORHE7FO6+dk3+NdM0c+KR1p+n32jH41C4aVdD3jmCNYvgZHfI\nilolaySiZUsKTOtG5JoS8UpYoxwnrvHL19s50T0GpkkomqLc58w7WYddRK+C0jFXHeyzuZ8/WjRr\nVihPTSldAhiNFHZ23XnNaqLxNEOhBOvq/bSs8nHgUDdlHjtXb6m7oI6mTasrOHxqqEi5VDfg1+93\n4/fYiaey/OI3p5FlibNDMRw2meqAk2AkjW6YjIST/OLAKRy2wmzkxB3U47KhKIWlZ8m0PuNd9Z3W\nfobGEiiy1cU1nsjicSpkdAPDtByz2lyed2ATA25iyQxOu5L/7DZFZnWdj3ePD+Rv5y6Hgm5A10CE\nm3Y1UFvuZktLJVtWV/Dx6RFiyQx2RWbXhio2NAas2QOGyQ0766mr9PDCe2fRDZNbrmzCblf45Iyl\n+HCiO7fIJUm4nDYMw0RRJK5Ua1jX4J/370IgOB9zpQj8wKNAEPgH4C+AzwKngD/WNK04CfgpZSg8\n9wJXhc/J792/DYDBYJzvP3+CTG4WbP9onIf3rZ/3tdY1+PnaHZv4n788WpQiSKayZHWDmnI3Xf0R\nK6LWTeLZLDZForHGS99IjKxuktWLqxFcDsvZZbIGVX4XQ6FEXpXWNCmYpAVW1PzOsQHCMSs69rps\nrK4tYyScpCrgwmFTONYRZI9aWxCBQmEUn0hlOfBBD0e0YcpcdmyKzFg0ma9qGBpL8Ms32nHYFG7b\n28Tm1eU5qXHLafvc1o1q98ZqDMPK157qHsNpV9BNk3RW5++fOU48lUU3DFJpPZ8+cDttfPverVT4\nnJeFsoJgeTFX6PQD4ErgfuA1wIs1wrAd+M7Cm7ZymD54ZS46+iJ55wpwOqfhdCG0rPJTV+Eu2i9J\nEtmsgWlatbbpjI4iS7nB2U7+8KEdNFZ583nP6RGpYUoMjcWx22RqK9w0VHupq/DgsCvYFAlpylwB\nRZao8LmQFav0S9cNovE0uzdWU+ax45iyUDR39S48+3YXH58eJpnRLdUEycRmUzBNq/oiqxtkMgax\nRIbfHO7lTG+EMo+DmnI3FX4XXQNW+Vg0niESt8Qin3izg1DMWnB79u2u/MKaIst4nHZkyRoLuf+K\nBuCeiSAAACAASURBVBqqvfNyrp39EQ4c6ubDU0MFi2oCwWzM9X/VFk3TtqmqagcGgBs1TTOAF1RV\nbV0c81YGTXVljETmJ009fW7r1O13jw9wrH0Un8fB3deuKZgbMJ29m+vQesJ51yVJ1qN9Vjeo9DlR\nZIlzuW4wRbbGDP7XfzySmy1gkFsTKkA3dH70wkn+4KEdfOnWjbxwqJtkSuf6HR4OHu0nGk+TyKUN\nDNMknTUwctO6ZAlsNpnTvWGu376Kt1sHANi8urxApmYm+kZjIEn43A6i8TRZ3eSKDVWsb67g3WN9\nBYtxGd2geobv8NWPejl4tB+ADY1+0hm9oCJDN0wmfH59tYdv3LUFMOddMdDZH+GnB07lI/ixaIrb\n9jbP672CTy9zOdg0gKZpGVVVu3POdYLzTwn5FDG9x32uMatqczm37WnKL0bdm6smONU9xoEPrKxL\nfzBO4o0s37x7yxzXdOKwy2Rzj/lOu4JpWm2iQ6EkXpeNqoCLeDLLeCJD99A4imxFbZIss7rOQ/9I\nvKC5QNetMqv+0Rgbm8r52u2b8q+tawjwqzfbaT9nDVQxTUimMuxYV0Vr5xg2Rabc50RRJG7b28zO\n9VVkdZP6Ks+spWcTrK7zcaxjlDKPHbtN4vrt9dxx9Wrq6wOsrvHwN0+2kkhZ0fiWNRVcsbGaYDTF\nqe4xKv0u9u9u5DtPtxLOdbud0g0CXgfnRmKYQFO1l1VVHs6ci+D3OLj32pYL1vA63RMqSI+c6gkJ\nBys4L3M5WL+qqndjrX1M/J2J7QW3bAWxutaHJJGXrp7e5jqd63fUF6nMjoQL60tHztO4kErreJx2\nxhMZZFnC7VSIp/R8tGf4nTy8bz0/f0XDbpMxphTiS4aJTVGsWQJTHKwJBCMpbEqxQ9yypoLyaRF1\nJmvyhVs3En3uBP2jMdIZnZtzk7NqKzyz2h6JpekaiBDwOlmzysd917UQ8Do42j7CYCrLYW2YkUiS\nP/7yHjY0lvO1OzZxrCOI32Pn9quakSSJW/c0cesea9ZDKJqk//9n772D4zrPNN/fCZ0jciIiwQMm\nMUiiRGVaEpWjR7bHsj2ascceTd5w7+5s7a2avbt169bW3A3j2R3LM5bz2LItWznnTCVSTCDZIAkQ\nJDLQ3UDnPn3OuX+cRgMNNAJJgCDF86tSlZo43f2hCb74zvs97/OMJgsZZ4l0DodNLByg5TSD+69r\ny7c6zsx3YOYv0QrLOMZiEcxXCU4yFRsz/f8B5naQvhjJu0sVHp5Bf661zo8kCoUiuHpGzEwqk+Ol\nj3oZG0+j5FNao4mMWdQ1cxFG0fUaL310spAsMP1rkmgGMdaUuZGlFIl0jnTWLE7JjMbPXg7xx3eu\no76yeHzU6y4usAbws5eOkM7m8HvsiILA/u4wHc1lqDkdXTeKBgTAvLX+xyf2E01kkUSBu69u4ZpL\n6rhhSz3vHxgo9EJ7BmMcPD5GfdDJ1jVTQY2liMazhdwxMD//aDxbWG9a1RiOpmipPfN9waUdVYRj\nGbpORqkIOLnr6pYzfi2Li4f5ZFo7zuE6LmgOnQgXFbBkCb3oQtRXevjazjV8cniEcr+TG7YUp7U+\n98EJ9h0bJacZ9A7H8bpkptfxrKpTmzealkQRTddRNR2XQ87HhwOGqfOsCDi56pI6tq6u4JEnDzAY\nTuKw6eQ0g0Q6R89AjO8+vp9v3rmONasChVv8uvLZu9L+sSRel62w6+0bifNh5yBPvNONrhtcv7m+\nqBi9v3+Ak8MxTHGCwW/fOsYlbRW4nbL5PtO+qbnMumcS8DiQJZEceb9ain8Z2GXxrK0KRUHglm2N\n3LLNagtYLB7Lp20JyM04LVqoLPSNJnjl45PsOjhYEPtnVI3XPu2j80SEXQcHOTJDXfDpkWH6RhMM\nRZIMhZMMz2ghGJhZVQGvg4qAk8Z8emvQ56Dc76S11s+qai815W5kSaSjuZxkWiWd1fItBpnt62up\nrzSL6HA0xf/+3X72dI0W3KZ6hiZmfS+rZgQO1la4+dnLIUajKcYm0jz7QQ/H+6fyynoGJ8jmzIEC\nXTdTbv/pmYPEkiq3bGss9K+VVUHWty4udibgtVNb7kLXTT2w3+vgD29by5qGAG31fh68WcHvnvvA\n0MJiubCEf0vAVRtq2Xt0jJxmxnRP9x6dyVAkyU9eOFyQavWPJfji9avZe3SUvlHz1D+nG7z0US8b\nWsxgwL6ROOFYpnCfr2qmZGkmD+5USKZV7DaJnsEYv37jKGrO1MU+dGsHob4oY+Np2hsCbGir4LEX\nDzEYSZLLmSYKXX1R/uL+S/jxi0cInYwSS6n87yf2UxN0URFwFplzT/LtuzZwtC/K4d4oZT4HLTVe\nXv7oZGFHr6o6h3ujtNWbLY+ZpjgGZs+0syfMNZfUsba5zDR78TsXHcoYiWcYm8gUDq7SWY2MqvHg\nTmXqfQxzd+60n3kf1sLidLEK7BKgNJZR5rMTnjD7ipetnbtfOFMHG8q7+xv5hICsau4ofcaUED+e\nUrFJArpuFhwBcDtk0tnZuV2TAvr2hgB/cf8lROMZqstcOO0y2wO1RdeOjqfM4gpgmIdPtRUevnPP\nBv7Ljz8uDBAMRlLE02rJpFi3U2bT6sqCv8FwNMV0uyoDCE4zv1HV0uO5bodMJJbhtU9N/9or1tVQ\nXb24nqmqakWTbTlNJ5FWSaZN/1q7LPKLV7s4MWSO537lxjWzBh8sLJYDq8AuAYd6wqSzekHUv/fo\nGF/aMduLFCgyPgEoz2s6W+t8TCSypuO/YMa5TNJS66e+0sPxgRiGYeB2yJQHnLMyuWbi99iRJIEX\nP+wlllS5ZHUFW6aFHjZVe/G4bPm+rZkSC+ZklCQWT27FU7kFWx9gpuM6bBIZVQPD1MaWeaf6n1VB\nJ0MzdsIbW8vZ3F7J9548wGjeErFnMEZbU/mcP6DZ/MGV32Mn4HVQFXSaI8qGgc9jZ2AswTPv9WAA\ntWVuBiNmZE8qq/HsBz1cplRhGLC5vXJB1YeFxZmy4E9W3k1rutmLgRl8+D7w4xn62IuSgXCSdCZn\nigl0g/F48dBBOpvj+V29jERTtNWbXgT7j43hcsrcktdSHuubIOi1k3OZqbP9o8nC8x12iZpydyHV\nwO2USZbYTZbit28dp3vA7J0eHzB1oJPz9luVKvYfDzMQTiKLQuEwShIFcroxazR2MdoIh12ipsxN\nPKViYP4ycDsl4ikVj1PmsrXVdJ2aKOzUW2q9/N4Nq8lktUJxBXM33z8ap6li9sFaPKXyo+cPEY5l\nsEkiv3dDG1+9WeGFXSfIaTrbN9Ty5p6+wnq7+qI47bLZQjDMu4hJWdyerhG+ffd6y6LQYllYzK/u\nIeAy4JeYRfYrQCfwZWALliE3FX4nOd0oHIA77cV7vRc/7GX/8THA3Jlpmo4vryl99ZOT3HJFExk1\nhyAIhX/oAuY//sYqL5VBF1lVx+OaahtIM5Js59LyD4wWZ3sNjCUKBdZpl/nmnesYiabwumz48gdB\numFQ5nVik0RyOVONkFH1kgkJM3E5ZO66upkXPuxF0w3WNgV57LWjpFWNllof91/Xxr6jY5waSeCw\niXzxBnOn77BL1JW7GciHQ9pkkcYaH+RmKzI+Pjxs9qQx+9Fv7Onj4Xs3si5vMxiJZYrib9wOGadd\nRtV0NF0v0vmOjKcZGEvOmjabSGQ53j9BwGuntc6SfVucGYspsJuBHaFQKAOgKMr3gdeAG4HPlnFt\nFww9AxNFkqmZPqsj0w52cpqOlu/BGoYZ1903lgQD/B4bsaSKYZga16ff68EmiXz9FoXLOqp44UNT\nfmyThKKcK/O1Sq+tudZXUCSIghn/Mp3PukY50D2G3+Pglm2NecmVyA1b6nlrr5lqUFvm4vK11fzj\nkwdmvU82pxX5DoDp+NU9MEFW1ekbiZPOWx/2DMb4+PAwqUwOu2xmj4Wn7Vof3Knw1md9ZFSNtU1l\nvL+vn4lYmu3raymb1lpZYDCMMp+Dre2V7Mm7Z61tLuOea1vpG47jtEv8yytdhT64JAqFXyyTRGIZ\nHn2us5AacePWBq7bXCybs7BYDIspsNUUj8aqQGUoFMooijI7Q+QiJBLLFM51BGYPGrQ3BOgfM3dm\nDpuEMe2025jsvAjmre+/e3Arv3r9aMHARNV09nSNcu+1rVSXuRgbT3PoRIR39vUzH7pusKtzkKyq\noebM2/FrNtUXdmqabvDRoSF+/cZRMlkNSRKJxtN88471AOzY2kBHU5BURqOx2osomG5bqUxxR+jA\nsTGUpiAfHxrmaN8E1WVO3t8/yGg+tlsUob7Cg5Q/ue8ZmCCV1ZDzn8FHh4YLU21el407r2pBzen8\nj19/Rv9YEl03ePWTU3icMgGPgz+6Yy1XrK2mszvMyHgauyyys8TI6j3XtrJlTSW6YdBU7UMUBTqa\nzB3u793QxksfnUQ3DG68tKGoeAMc7A4XRfJ8fHjYKrAWZ8RiCuxbwLOKovwMs358DXhHURQvsDiH\nk885V26oZe+xMdMsmtkHWTu2NuB12xmOJFldH8DtlDnQHSaRUjnYEy5cZ7YIRFz24r+Wyemmllo/\nLbV+Xt/dh00SUafdPs9UNL366Sk+ODDAUCSFrhsEfQ4+7Bxi65oqvG4b3/3VHj7pHGRiWiT27tAI\n37xj6jXqKoo1rkKJY65/fraT2nI3A2MJbLKE2y4yMjF1+GbmY6kEvQ4CHjtKY5BT09oWLsfs3udQ\nJEn3YAwMc8cfTxnEElmGIyn+/jd7+b+/dSXfvnsD4Yk0PretoJyYyVwmMx1NZYViW4qZa3JaNoYW\nZ8hifnL+AvgT4EuYm7QXgUdCoZAKbF/GtV0wNFV7kKWpMde6/MGMmjN3hqIgzIqnbqrxmTZ/usGR\nk1FEAW67oglJFNm5rZHRCTOBtqnay3Wbin0LqstcxJIZUqPJwi37zZevKrqmO+8HOzkkkFU1cg6Z\nsYk0XX1RegcnSM2YOEum559Aa6h00dUXL/qzjKpzYiiOAOh6DrWEDVB7vZ8bL1tFQ5UXj1OmZyjG\nwe4wPreNu69pnXW9YRiFO4LC3UC+tk+amdtkkZoSk2VLwdY1VRwfmOBQTwSvy8a917Qsy/tYfP5Z\nTOhhFviH/H8WJXjl01NFpimdPRF++9YxDnSHcdklHtjRXtIpXxQFvnJjO5FYBrtNwps/xCrzOfiz\n+zaSVbVZESa6bvDF69v45WtdZtvBMIMUe4eLC19NmYvBsSSiKJBVNRIpFZ/bTn2lh7FJYxlhMbqA\nKeLzFGADc4qq1GxgRcDJ7946jm4YXNpRxeBYEqddIqcZ9AxMFMV6g2kU01LrK7RVsqpW2DvPtHtc\nDkRR4Es72slpujWUYHFWLEamVYVZXG/O/9HLwF+HQtOS/C5yjkxGkOTRDQpBg6msxtPvdfOvvrS5\n5HMFQZg1Jx+NZ3jstS6GIymaa318+QvtxFMqv3r9KOGJNO2rAjhkEcMwC5uqGRw7VTzGevuVZtbV\nCx/GzZ2sZjAcSZFMq2xur+Rgb4STQzFOL15tdotgupTLwBxTDXrsnByJIwgCVQEnR3qj5sRWKsez\n7/XgsMuF4YO39/ZzrG8cTTdoqfPxyeERMqrGptUVXL25gVgsTTyt0tkdxue280fzWDguNVZxtThb\nFtMi+D5wAPi3mP/Cvp3/sy8u47ouKFy2+T/GdGZxmtVJXv74ZEGM3zMY4919A/SPJRjLn7h3nRpH\n0/SiE/2cVnz45LBLXNZRxdP5SGow/Q7ePzDIfde18W8evIyH/99XyIyXbqP3jSb4zetHSWZy3LCl\njmsuqWdNg5+BsWTRdaIA5D1aDMO0O/Q4bVQHXeQ0na1KFfuOjZFM54glTderZD6lwGGTUFWNbD6F\n4ePDw1QGXUiiwJ6uUf7qK1spc+U/2x2n9RFaWJwXLKbArg6FQtOL6d8qirJ3uRZ0IXL5uiqO9k/t\nIGURAh474wnzsOfKDbVzPbUkM2VeyUxu1p/NnNMvtQ8tZXQ92dN02CSCXgej0wrs9Kv/8Yn9hVbC\nY68lqC33FB1OTWKTJWyywAM72nn8reNMJLKcnNaueO79E9RWuMnmD+QcNomsqpHOaIUEWW1yqCEf\nPSOJZlsknlKnCuw8GIZBTtMZHU/jc9sLrZbFMJHI8uZnfWSyGlesq7FGaC2WlMUUWEFRlJpQKDQE\noChKDQsbRl1UzDwsMhD4zt3rOT4wgddlOy0fUl03uLyjipPDZgy4LAlsaa+krsJd0ME6ZHFRfwF+\njx2nTSroUGVJKHjJglnspjNZj1OZXGG3DGYI4sGeMOESsTiabnClYgYOVgSc/Oj5w0Xm4Ub+9bas\nruTIySg2WWQ4kiLoteFz2xiJplFVDadDJuC1F27Ly30O1jaXkYjNrQSMp1R+9VoXJ0fiJFIqbqcN\nh13iy19op32Gn24pDMPg56+ECjrlrr5xHr5nw1lbG1pYTLKYAvv/AbsVRXkOs7DeAfzNsq7qAmPf\nsbGix5pu4Hba2LhIuz0wC+v/emI/XSfNsc67r2nB47TRWOOlOuiiudZHTZmbsYk0LbU+vvvbfQu+\nps9lY9u6Kg6diKIbBvUVHlrrpgpPeKLYE2Cyl+qwSaaPbH7XLIoCq6o86MbsqWiXQ6bM78DjstNc\n4+PBm9fw3d/uL7omp+ls7aiioylI92AMNafjtMsgQGXQyYaWctxOmSvX1TAyniaT1VAag7idtnkL\n7KufnOTUaIJ4SiWeVNF1c62v7z61qAKbzmpFQyBqTmcgnLQKrMWSsRgVwU8VRdkNfAFzQ/I/gb75\nn3Vx4V3EbexCPL/rBJ35gzE1l+WZ93r4uz+7uuia5lpf4RZ2riTbnKbz5DvHOdY3QVWZi3uubmVt\n0ziqprNlhrFJZA6zGFEUeOjWDh57/Si5/PO2rKnih88dmnXtRDLLG7v7uEyppr7SQ0VwdnGKp3L0\njSSoCjjpGZhAFAXSao6GCg/Xbqpny5opAxpJEsmoGs5p31/vUIzOngg+t40r19cUdrkz2ybaaSZJ\nOO0SlX5nwQNBloSSab0WFmfKoipDKBQ6gHnQBYCiKL1A03It6kJjulj/TJmZyZVa4GCsVH9V03W+\n+/g+QqeiSKJALKXy6qen+P2b1pR8jfkSA7asqWJdSzlqTi/0NEuNqIqCQCKt8vibR/mrBzYj6KVf\n8/E3j1EZcBbivw0d2hoCRcX1gwODvPLJSXKa6btw21WtBFwSP385VNAYD0dS3H99GwBb11RyrH8c\nt9NGOqvhdpiGLjdeuqrkGmYiCAJfu0Xh9d2nyGR1rlxfM6+Xr4XF6XKmWy+rBzuNTPb0I2JmctWG\nGj4+NFQoJG0N8/dtSyXZfnpkhFMjcTBA00xXr4nk3JaGV6yr5s3PBgqPJw2rj/RGePOzfkRBYOe2\nVYUCG/DaSaSL2wqT+V7xvLtXIjP3L5vR8XRe/2paGb6x+xTlPgfbN9SS03Re/fQUmm4wOp5mOJLi\n8ddDeBxykclM16mppId1LeV802NnYCxJdZkLWRLxe07vkCvodfDF61cv+noLi9PBmgFcAtpXBRkM\nTxWeM/nt09FUxp/ffwkfHBykzO/kngWmhxoqPUVJti6HTN9IwoxiMQxEQUA3DDa1TfWBk+kcoZNR\nXA6Jykovl3cUF1iPQ+ZY/ziPv3mMbD414eipKH/xxUtorPGVHJW12UQCHgeXrK5ANwyO9o3Pukac\nlHFh9j0FwCabY8HvHxhg+zSVRTanFabPAMaTWeyyVNhtVwaLd5gNVV4aqooNbCwszhfmLLCKoqyf\n40vCfM+7GAl6i3dMk0Ymp8v61nLWt5Yv6tpyv9OM3c7qCAL43Db2Hh0lm9MRMHeWN166qlC8Upkc\njz7XWbD5OxVOEeouPpyLJrL8w+P78HscROMZsnn1wY9fPMxffHETo+OzI2MevEnB45LZ2FbB65+e\nYlfn0OzFGiCJMC08AT2vmxUEgXRWpXcogWEYjI2n0TQDp0MyPVwlge0baunsCeN327nzqubFfZgW\nFucB8xXK55l7zMdy0ZqGKJg7LF03Z+ilhfz0lgDDMNA0AwPThzaZyeGwy1QGnCTSKoIBa1ZNSbKO\n9Y8XiivAhwcGkEosM5XV8Lr1QnGVZRFdNzg5HKMoCybPVRtr6R6Y4OWPTvLJkWF0fbbSQMj/vnHY\nROw2iVhSJacZjE2kuenyVZwYjPHYq0cZHk8hCAKSZBbfoM/BXdubaa71cb3lZmVxATJfbHfLOVzH\nBU3Qa8fI39YanPkO9nQYCJs7Pjl/6zyZSaVpBslUDlkS+d3bxxiPZ7hucz1uR/Eu22GX0bXZvWNB\ngDu3t/D8rhOksjk8ThuCIFDhd1LmtTMYKf7demIwlj+E0glPZEoehPk9DtSchgFc3lHFiaE4x/sn\nyGkGv3vrOLdsayST08jme9mCIFDmc3DPdatprHCRUTX6RxP4XLZZLQILi/MZa9h6CRibSBXt61Lz\nHPQsFTVlbiRJRDPM222/286t2xoRRTORQNV0hiMpPs1bRrTV+7lqfQ2SKOCyS3zj9nUMzhh7BVhV\n6WFP1wjNtT46mspoqPSYmlyXjWh89oHZe/sHUHOmnjSjaiXVD/FUlnRWR9MMjvdN8MXrWmmtM+Vm\n6azGs++b2VmCKKAZZqruRCJLdbmLE4MTfPfxffz0xSN876kDfHrEssCwuHCweqlLQOhU8cGOdg5S\nygJeB4ZhFG7zPU4bl6+t5sPOoXzhNNB0Yco5C7jliiZuvrwRURSoqvKRys4uhpphxqgAtNT6eOi2\ntQyGk3z/qYOkSyTC7jk6SjKtomlme0SWRVMlMA01Z2AOjQlkNZ3fvnWMkyPxglGMbsBQOFUY/xUw\nJWfPvHucjw4MMpHIYrdJVPgdvPlZH5d1zJ3aa2FxPmEV2CXAUaqZuczEElmqy9yks7lCYfrR84fo\n6hsvTGSJGEXpCmpO5+29/UTjGa7a1FAUdT2TVFrlvf0D7D4yQm25m1i69K5c03REQUCQBSRRwCaK\ns0aHwbzt13WDRDpHLiegaWYhlSSYrMeabiAIIAmQy+ns2t+PmG/gZlWNjKoRmEe7e7FxvH+Clz4y\ns892bKlnY9viJwctzg1WgV0CRsbP/ZlfY7UXWRLN3qoAbqdM/1gSWRILfVBZFglOS1d45v2eQvji\nkZNR7LbZETCarpNM5wq+A/GUSlcJ6dUkOc3A57bhyutVc5oOxda0ZtHMR5o3VnlMKVd+9yrpZubX\nyHg6b/4COQN8bhlZkpBFU86l5kxv1ju2myoCNaczOp46bXOXzwvpbI5fv95FJv9L8sl3u6mv9Fhj\nvucZVoFdAhYRtroo3th9ir3HxvB77NxzTcu8U0V1lR5WVXnYd2wMp0Pm0jWV7O4axe2QSWVyCEBV\n0EVLrZ9HnjpAIp1jKGwacE9G0LTVBTjYM+Vl67CJCAjk1Kkd6ELfmqrp5DSDrKqzsbWc9sYA//t3\nB2Zdl8pqSKJAJJ5BkkSkfDH1OCV2bmvkhQ97i6bZ0lmdO69p5J09p/C7baxpDPDlG9fgdtiIp1R+\n8qJpKmOTRb68o532VQt7D3yeSKZzheIK5u5/PJG1Cux5hlVgl4Cg185I9Ox2sQd7wry9bwBdNyew\nfvf2cb5z94Y5r+/sDtM7HC/sUI+eGqeh0kPfaIKqoIv2Bj/rm8t547M+RqNpovEMel51oLrtVASc\ntNUHCJ0aJ6eZ2lm/2854IkM8Pbs3K4mle8uSIBCJma89Op5mT9fsQyhT72oOHAyHU4iSgCAIiAKs\nqvbl03SLD9DUnM7z7/fw4E3tBLwO/G4bYn5r/snh4UIxVnM6r3568qIrsEGvg/oKdyH1oczroH5G\nhprFymMV2CXAJpU2XpmP9w8McLA7TNDr4PbtzYTH04QnTCepUj4DM0lmctO8VAXSqsZf3r6WkWgK\nj8uG321nIpnld+8cN4trfpstCAKGYfDATQqh7jH0yRErAWKpLJo2OwJclgRzMkzXZ+1oszmtMMqa\nUTWGo6XHhidbpwYGsiihGwaSKGDoBqpmUCo8YCKR5ScvHeHrt3QQ8DoIxzL4XOfgBPECQBQFvnFr\nB58cHkHTdS5VqnDMYQBksXJYMq0l4HR7gId6wrzyySn6x5J0nojwxNvHUXMa2fwpvWEYRRlfpWhf\nFSCeVBmJpBiOJAs92boKD363Gcfic9nQ8sGKBnmNriSwZlWQazbVMxJN5ocVzDZHTjNMt62pJHFs\nskBlwMn6ljIc9tk/LnZ54X/UpirAjLYRRRGP24bfYzf9ah0yNkmkMujGLk/9YnHYzPdKZTR++Nwh\n9h0bRRQE4kmV1Q3+QnKvTRa56bLFmbt83nDaZa7dVMcNWxrw5f/OLc4vrB3sEtA7HDut64eixSOn\nI9EU7asCVAScBVXAZGbVXJwYjOF2yvnJJ4Gh8GxNazqrIWJKuXTMnanHZeO+68wk15kG2ppmUFvu\nNnulsQyiJBDwOHDYZXZsbeBIb3jWe7jsEsmFInEE03XLMExVw1g0hSgKSKLIZUoVm1ZXsvfoKIPh\nJJJo4HbIuF02mmr9fNxpGuA89tpRxuNZrt1UhyyJfPH6NnK6QYXfeVEecllcGFg72CWg4jQPFtrq\n/IV+IphDAJe0VVAVcOJz23E7bQuOhmZVjdHxNOFYmtFoikiJIQDDMHA5bQR9TjxOG0GvnW/euY66\nfK9Ozc2+nf/OPRv4yk1r2LqmkuqgC5ss4rJLiKJIKjv7yEtn6vYfSlsamnld5qGWppktDYdNoqbM\nxYmhODZZ5Gs7O6gOuqiv9BLwORAFgWs21XPvta2F13zhw16eea8HwzB9Yx2yiM0KJrQ4j7F2sEvA\n13Yq/Kcff0xWNQ+L1raUzXt9U42Pr+1UOHQiTMDjYPsG00T6O/dsoHcoVojXno/+0QTp/GipAYxG\nZxuxuJ02rt5QywedQ3ix0Vjt5cDxMO/tG+TKS+rweYp3yaJojqhuW1tNMq3SOxwvOHP97q1jLKfG\nVQAAIABJREFUJdchCIUWrtmfLSE7EMgfdOUf53QDtyQiiAIuh9licNglbrx0FW/t7QcEGirdtDUE\nqPY7CHjs/PK1LtSczq7OIcYTWb5yUzt2WWIslibgtuFxWbfIFucfVoFdAmorPPxf37icDzsHaaj1\nc1l75YLPaav301Zf7Pnqcsh0NM1fnCfpHogVmQeqc4yPXbK6gqP946iqTjKlFgIJB98+hl0WiywP\nJ3eDmq7z+u4+MqppHXhiKDbnbXguV5xuW8IPBoddwuOU80MGGppu6jgn4vDVm9oL1+3Y2sDa5jIy\nWY2GKg++gJuJiRRrm8v49l3r+clLR0ikVA6diPCDZzr5g9vW4nXZGE+qZHM6ZT5LomRxfmHdXy0R\nq6q9/N6Odu6+bnXBuHo52dhaXnQ77nHOLoA5TecXr3YxEk0TTWQ51Bslp5kR2VlVM6e88jtLAaZO\noQ0Yyysa1JxOWtXIaaUVscmMZqYUTK6l5A7WPGirKXcTzBfBrKoTTWR58p2eomtry9001/qQJRGv\ny0bQY0c3DFZVe/nTezdQGTCff2okwfeePMBINGWqKLIaw5FkkZeshcVKYxXYJeKdvf38/W/28j9+\nuZvhyOwDp6Vm57ZGrtpQi9spUxFw8pe/d8msa5LpHPGUCvnDJbtNJJczXa+Gwin6R5OFDacBeN0y\nv33rGP/Pzz41d6b5aumyS6xpDMwRGYOZkZWva6WukWWJyoCLGy9twGETCzXYMKDrVKToWk3XyUwb\ndHA7p4psud/Jw/duKOSSRWIZHnnqICcGY+YorgFDkWTBatHCYqWxWgRLwNFT47zw4QmS6RwnRxKE\no0n+6oHNy/qegiDwrbvm8kQ38bpsOGwiJwZjpr+q1876lnL2dI0Q8LqIxNJMbywMjCWRJVMpYLdJ\naLpBud+B2y7xpR3thHojhGcEJYqiUJCXQenJL6ddYm1zGddtqueZ93qKvja9s7H/+BiP5Xut29fX\n8CcPbAHMIisIZkij22njm3es4zdvHuXA8XDBSPxLX2jnkrYKBEFgdDxNwGPHY6kLLFaYFd3BKopy\nm6IohxVF6VIU5d+v5FrOhqN9UcKxDOmsRiKlcqx/YtY1R3ojvLOv38zMOkeoOZ2MquN22nC7bNhk\niaYaHwGvA5dDmrXTm+6VXe53EPDY2NpeyUO3r6XM50Atcfvd0Rg0p7REAVmc0q9Op63OX4jAqat0\nF31Nzhvl6LrBj58/zNh4molEltd2n2L34al0BJfDRrnf9N21ySK/f9MarttUB5j63cde7eLdfQMY\nhoEoCowns0Tmify2sDgXrFiBVRRFAv4XcBuwHviqoijrVmo9Z4PdJhXlVUkzHJ92dQ7y2OtHeX13\nHz9+4TDdA7ML8HIwefDl99gJeOzIskhdhZv2+gCxpGkxOJPJOPB0xuy77u8O8+6+QXTdKCmJWtsU\nxGGXkEQBSZKoLnMXtQkEYGNbRSFq+/dvXIPbIeV1sAI354cEUpkc8bRqGsboBmrO4NgMkxmn3UaZ\n34GRn167fXszd1/dUmhzPL/rBM9+cAJ9crotqzESSZrTahYWK8BK7mCvAI6GQqGeUCikAo8B967g\nes6YjsYgPreMIIAsC3Q0Bou+vv/YlEBf0w0Ods8W7C8HXpeNzaunLOxWVXporfPz1Z1rqC5z4Zwx\nWimJ8O27N3DH9mZsslC4xT7UGyF0MkpzzexwwYYqL/UVbiqDLqrLXNx82aqisVdBgIrAlKNXXYWH\n//ytK/n6ToV/8+XNfPlGM1Lc5TS7VZpuoOsGmq5TW2Hudg92h3nstS6e33UCwzDzyIz8dvuqjbV8\n7RalUPw/ODDIL14Nkc2ZI8eaYfofZEtofi0slpuV7ME2ACenPT4FXLlCazlrDMO8zdU0g5mCqYDH\nTv9YovDY71kazeaerhE+6xrF67Zx67amkq9777WtbGyrQM3ptDcECgqHoM+JzSaSyhYfKJX5HFyq\nVPLih71FO7+crtNS62dP11RQoijAb98+jq4bXKpUceX6GuwiTK9lugHDkRRrm6b+rNzvZMfWhqJ1\nqqpeFM9tGDASSeMQBX771rFCbzcay/DgToWKgIuxiRSCILK+pZw/vnsdP33xCIl0js6eCI8+e4hv\n3NphyssEGI2mCXjtJdUWFhbLxUruYD839217j40SiWfIaQYZVePA8eK01tu2N9FS68PtkNnYWs7V\nG2vneKXF0zM4wdPv9dA7HKezJ8Jv3jxa8jpBEGhvCLCuuaxIPvalm9bgssuF/qldFgnkC7Qkily/\nua5w7apKDx2NZcRSxabbk/VXFAW6TkZpqPQQS80em33m3Z5Zt/szyaimy8ykZEwAwrE0fSMJ4mmV\n0fE0kViGE4Nme8Vuk6gIuAqG4o3VPh6+byMVeRnXyeE4jzx1oJCEK4oC4wmrL2txblnJHWwf0Djt\ncSPmLnZOqqp8y7qgM2U8mWPSlArD3I1NX2sV8H98Y2nd5g+eHC8qmOFY9rQ+nyrg3379cr73+F5U\nTUcSBbYo1YXXeGDnWq7asopUOkdznR+bLJLMFt9mG5hmK5qmk9V0UppBZdXsNoIO/MurXdy8rYmd\nVzabhjIz11NlWvCNJ0yVgiwJXLWxjr6RGLGEWdhzQEYzir7PmiqNoUgSECgv9/AfHtrGP/52H8f7\nxglPZPinpzv5swc209Zg2hkahkFOEKkpdyMuYTrC+fqzORNrneeWlSywnwBrFEVpAfqBrwBfne8J\nIyOnZ6pyrgi45aJpJkkSln2t5W4536s037il1nda71lV5aPSY+P+61o50B0m4LHzhUsbil7DDtid\nEtGI2d5QS2R4pTI5wuNp/B47f/ezT7hhSz02SUCddoAWS2aJxjP89PlOnnnnGH/7R9tw2mf/6P3r\nL2/m56+EyGQ1vnBpAxvaKgh1jxH02kllckii6T8w8/uUdYORaAIjf9D40K0d/PqNoxzsDhNPqfz3\nX3zKV25cw4bW8sJzRkZjVPid2G1nb/FXVXV6n/1KYa3z3LNiBTYUCuUURfkL4CVAAh4NhUKHVmo9\nZ8PMtNW5pp6WkroKD1/bqbDv2Bhel41rN9Ut/KQSbGyrWHSW00wJlk0WuGJtNZ8cGUEUBQxgT9co\nHpeNiYSKbpgZWzltKl48EsuwOzTC1Rtnr7ehysu/f/DSoj9rqfXhdtpw5lMY2htmG2uLokBVmZvR\naArdMHfVX715DS/sOsF7+wfJaQa/eCXEnVc3F953Si9r+RhYLB8rOmgQCoVeAF5YyTUsBTO1rdo5\nGtdsrfPTWudf+MIlIBrPcGJoKglWlgSaqn1UBJxFt9qyLOR1tjK6YaBrBpF4usg97HTsBVdVe3lw\n5xoOHg/j89i59pLS/WtREKgKuhiNptAM8/GdV7UQ9Dp4/oMTGMCz758gGsty2/YmREHI62VNH4Og\n17Eoo3MLi9PBGpVdAmRxZT7GkWiKtz7r49MjI8s+g//Z0VEEwQwgnHTHuvnyVWxbW0Nbvsh7nTL3\nXdNKW70fu03CaZdpqvXxhS0NheK1ZU0lm1YvbIYzndX1Ae65tpUvbG3ANo/BtyAIVAZdZlJCvmdz\nzSV1fHWnUhhoeHf/AL98tauQqFvQy0ZTlo+BxZJjjcouARV+R9Hjc7EPGhtP8+hzhwpz+6dG4tx7\nbeuyvZ/TJpHOahj53assi3xyeIQr19fyjVs7yGQ1bDYRURD46k1rePnjXoYjKa5YV8P6lnLuv2E1\num7gXkAmlVFNg5kzNdEWBDOBYXQ8bWaNCQIbW8vx3bmen710hGQmx8HuMI8mO/nGrR14nLYiH4Ny\nn9OKXrFYMqwd7BIwPMOL9Vzsg7r6okWmKAd7lnd44bKOair8zsIoqt9jN41k8jjsUqEN0NkT5uPD\nI5wYivObN4+x//gYTru8YHHde3SUv/vlHv7brz7jibePF3ahp4uQbxfYZLHwGs21Ph6+bwPl+V+G\nvUNxHnnqIOGJdNHzxmJpEqnZ5uUWFmeCVWCXgFKtOzWn0T0wMav4LhVl3uJdc3DG46XGJov84e1r\ncTttGIYp+J/LFPxAd5hESiWRUtF1fVGTa5qu8+wHPYX+9b7jYxw6y18alQEXdlkqFNnKgIuH791I\nY7UpJRsbT/O9Jw8UPHLBbBmMJ1QisfQZF3gLi0msArsEbFtbU/RYEuHR5w7x05eO8MiTB/jo0NAc\nzzxzOprKuH5zPQGPnfoKDw/c0Lbk7zETM23BRsBrp8znYGS89C+PA8fHGBtPMzaeZjCcwude+HZf\n15nljaAuEPy4GCoCTpx2CSNfuL0uG9+6ax3rmk1j80Q6xw+e6Swq5qI41ZfNadaIrcWZYxXYJWDv\n0eLJLU2HoYhZfAzgjd19y/K+X9jawL/60ma+ffd6qsvcCz/hLNF0A0kScTttOOxySbOYoXCS8EQG\nQRRAMJ/jndEaiKdUDvaE6ZumvrDJIldNm3Crr3Czbppu9Wwo8zlxO22F0V+7LPG1nQrbN5i/GFVN\n5+evhNh1cLDwnMm+7Gg0TbqE/tfi9Nl3bJTfvHGUVz85WThk/LxjHXItAZ4Zk0kzWwaS9PmQ/1zS\nVsEnh4cZGU8jYBb4mUy6Zpm6V/P7dk37fMbjGR597lBh7Pa2K5q4cr1Z6HZe3si6pjLSWY3mWt+S\nDAFMEvDaQYBEWi1ItO6+uoUyn4MXdvViGPD0ez1EYhluvbJpSlYmCIRjGXwu3YrGPguO9EZ44p3u\nwuN4SuW+65b/rmulsQrsEtBe7+e9A1O7H1kSaK3z0z0wgSwJ3LG9eVne9409fezpGsHnsnHvta3L\nvot1OWT++K719I0m8LlsVAZds66pCDjZvqGGXQfNtsjqBj9XrJtqoew7NlbkafDBwcFCgQVT97pc\nBDx2RMGcLBNFEUEQuG5TPQGPg9+8cRRNN3hn3wDReJYHdkxF/4iCQDypklE1KvxOSy97BvQOF2vF\nTw6fO1/klcQqsEvAvu7iFoGaM/j6LQrj8SxOu4TLsfQf85HeCG/v7QcgllR5/K3j/Nl9G5f8fWZi\nt0kLDjf84e3ruP3KZrKqRmNN8Uz5TAnUUu5SF4PPbRbZ8YRZZAE2ra7A57bx85ePkMpo7D8+RiyV\n5es7Owq+CYIokNMMU8rld2KfR49rMZuGGQeiC6Umf16werBLgDRj0EDA3PWU+RzLUlwBIvFM0ePo\njMdz8fbefv7nEmeHDUeSfHBgkMMnpvK1asrds4orwKVKFe315rir2yFz11XLs7ufD4/LTsDjKLJj\nbK3z8/C9GynzmWqMnoEY33/6QAn3LYGxaIpkWsVi8axvKefO7c2srvdzxdpq7rqqZaWXdE6wdrBL\ngG+GD+tSujTNxZqGIG/a+gta2A0tCx8IhU5GeWOPeeCWzOT4zZtp/vz+2WGJp8PAWIIfvXC4cGhx\nw5Z6dmyZ3ZudRJZEvnaLQjqbwy5L5+SzKoXHZeZ8RRPZQr+1Kuji4Xs38NOXjtA3kmAkmuZ7Tx7k\nods6aJjmEiaIItF4hmxOI+i1osIXy+Vrq7l8bfVKL+OcYu1glwBpRk/uXOgnKwJO7ryqmQqfg9X1\nfm6/smnB58zc5S521zsfh05Eik6E981QVMyF0y6vWHGdxO20Uea1F43I+tx2vn3XetY2mTKueErl\nn57p5HBvcfqtKIqkMmYkzbnynrC48LAK7BIwPqNQnQt9+uBYkh89f4gD3WHe2z/IT148vOBz2hsC\nOKb1PNc3n70MauZI62I0rwA5TWdX5yCv7z51TmLO52J6mOIkdpvE125RCodvak7nZy8d4cPOYj3z\nZCTN4Gjcigq3KInVIlgCUupsI+rl5u19fSTTpj7TMIxZWtxSlPudfPPOdXT2hKmv9tNee/Yn9pd3\nVDMwluTwiQhlfgd359NjF+KJt4/Tme/ZfnRomO/cvZ5y/8rcbjvtNsr9IuGYGUEDZnDlPde0EPTa\neemjkxgGPPVuN9F4hp3bGovcwbCiwi3mwCqwS8BKjFQ67TKabhTee3q6wVwYhkHfcBxDN1hV412S\nW3RRFLj32tbTMpoxDIPDvdHC44yqcbx/YsUKLJjqhgq/i7HxtDkkgblDvWFLA0G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"text": [ "" ] } ], "prompt_number": 24 }, { "cell_type": "markdown", "metadata": {}, "source": [ "**g)** predict the birth weight of offspring in a litter with 10 offspring (don't forget the transformation!):" ] }, { "cell_type": "code", "collapsed": false, "input": [], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "In a litter with 10 offspring, the birth weight will be 1.11964209943 grams\n" ] } ], "prompt_number": 35 } ], "metadata": {} } ] }