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https://www.mindspore.cn/api/en/master/_modules/mindspore/nn/layer/pooling.html | [
"# Source code for mindspore.nn.layer.pooling\n\n# Copyright 2020 Huawei Technologies Co., Ltd\n#\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n#\n# Unless required by applicable law or agreed to in writing, software\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# ============================================================================\n\"\"\"pooling\"\"\"\nfrom mindspore.ops import operations as P\nfrom mindspore.ops import functional as F\nfrom mindspore._checkparam import Validator as validator\nfrom mindspore.ops.primitive import constexpr\nfrom ... import context\nfrom ..cell import Cell\nfrom ..._checkparam import Rel\n\n__all__ = ['AvgPool2d', 'MaxPool2d', 'AvgPool1d']\n\nclass _PoolNd(Cell):\n\"\"\"N-D AvgPool\"\"\"\n\nsuper(_PoolNd, self).__init__()\n\ndef _check_int_or_tuple(arg_name, arg_value):\nvalidator.check_value_type(arg_name, arg_value, [int, tuple], self.cls_name)\nerror_msg = f'For \\'{self.cls_name}\\' the {arg_name} should be an positive int number or ' \\\nf'a tuple of two positive int numbers, but got {arg_value}'\nif isinstance(arg_value, int):\nif arg_value <= 0:\nraise ValueError(error_msg)\nelif len(arg_value) == 2:\nfor item in arg_value:\nif isinstance(item, int) and item > 0:\ncontinue\nraise ValueError(error_msg)\nelse:\nraise ValueError(error_msg)\nreturn arg_value\n\nself.kernel_size = _check_int_or_tuple('kernel_size', kernel_size)\nself.stride = _check_int_or_tuple('stride', stride)\n\ndef construct(self, *inputs):\npass\n\ndef extend_repr(self):\n@constexpr\ndef _shape_check(in_shape):\nif len(in_shape) != 3:\nraise ValueError(\"The input must has 3 dim\")\n\n[docs]class MaxPool2d(_PoolNd):\nr\"\"\"\nMax pooling operation for temporal data.\n\nApplies a 2D max pooling over an input Tensor which can be regarded as a composition of 2D planes.\n\nTypically the input is of shape :math:(N_{in}, C_{in}, H_{in}, W_{in}), MaxPool2d outputs\nregional maximum in the :math:(H_{in}, W_{in})-dimension. Given kernel size\n:math:ks = (h_{ker}, w_{ker}) and stride :math:s = (s_0, s_1), the operation is as follows.\n\n.. math::\n\\text{output}(N_i, C_j, h, w) = \\max_{m=0, \\ldots, h_{ker}-1} \\max_{n=0, \\ldots, w_{ker}-1}\n\\text{input}(N_i, C_j, s_0 \\times h + m, s_1 \\times w + n)\n\nNote:\npad_mode for training only supports \"same\" and \"valid\".\n\nArgs:\nkernel_size (Union[int, tuple[int]]): The size of kernel used to take the max value,\nis an int number that represents height and width are both kernel_size,\nor a tuple of two int numbers that represent height and width respectively.\nDefault: 1.\nstride (Union[int, tuple[int]]): The distance of kernel moving, an int number that represents\nthe height and width of movement are both strides, or a tuple of two int numbers that\nrepresent height and width of movement respectively. Default: 1.\npad_mode (str): The optional values for pad mode, is \"same\" or \"valid\", not case sensitive.\nDefault: \"valid\".\n\n- same: Adopts the way of completion. Output height and width will be the same as\nthe input. Total number of padding will be calculated for horizontal and vertical\ndirection and evenly distributed to top and bottom, left and right if possible.\nOtherwise, the last extra padding will be done from the bottom and the right side.\n\n- valid: Adopts the way of discarding. The possibly largest height and width of output\n\nInputs:\n- **input** (Tensor) - Tensor of shape :math:(N, C_{in}, H_{in}, W_{in}).\n\nOutputs:\nTensor of shape :math:(N, C_{out}, H_{out}, W_{out}).\n\nExamples:\n>>> pool = nn.MaxPool2d(kernel_size=3, stride=1)\n>>> x = Tensor(np.random.randint(0, 10, [1, 2, 4, 4]), mindspore.float32)\n[[[[1. 5. 5. 1.]\n[0. 3. 4. 8.]\n[4. 2. 7. 6.]\n[4. 9. 0. 1.]]\n[[3. 6. 2. 6.]\n[4. 4. 7. 8.]\n[0. 0. 4. 0.]\n[1. 8. 7. 0.]]]]\n>>> output = pool(x)\n>>> output.shape\n(1, 2, 2, 2)\n>>> output\n[[[[7. 8.]\n[9. 9.]]\n[[7. 8.]\n[8. 8.]]]]\n\"\"\"\n\nself.max_pool = P.MaxPool(ksize=self.kernel_size,\nstrides=self.stride,\nself.max_pool_with_arg_max = P.MaxPoolWithArgmax(ksize=self.kernel_size,\nstrides=self.stride,\nself.is_tbe = context.get_context(\"device_target\") == \"Ascend\"\n\ndef construct(self, x):\nif self.is_tbe and self.training:\nout = self.max_pool_with_arg_max(x)\nelse:\nout = self.max_pool(x)\nreturn out\n\n[docs]class AvgPool2d(_PoolNd):\nr\"\"\"\nAverage pooling for temporal data.\n\nApplies a 2D average pooling over an input Tensor which can be regarded as a composition of 2D input planes.\n\nTypically the input is of shape :math:(N_{in}, C_{in}, H_{in}, W_{in}), AvgPool2d outputs\nregional average in the :math:(H_{in}, W_{in})-dimension. Given kernel size\n:math:ks = (h_{ker}, w_{ker}) and stride :math:s = (s_0, s_1), the operation is as follows.\n\n.. math::\n\\text{output}(N_i, C_j, h, w) = \\frac{1}{h_{ker} * w_{ker}} \\sum_{m=0}^{h_{ker}-1} \\sum_{n=0}^{w_{ker}-1}\n\\text{input}(N_i, C_j, s_0 \\times h + m, s_1 \\times w + n)\n\nNote:\npad_mode for training only supports \"same\" and \"valid\".\n\nArgs:\nkernel_size (Union[int, tuple[int]]): The size of kernel used to take the average value,\nis an int number that represents height and width are both kernel_size,\nor a tuple of two int numbers that represent height and width respectively.\nDefault: 1.\nstride (Union[int, tuple[int]]): The distance of kernel moving, an int number that represents\nthe height and width of movement are both strides, or a tuple of two int numbers that\nrepresent height and width of movement respectively. Default: 1.\npad_mode (str): The optional values for pad mode, is \"same\" or \"valid\", not case sensitive.\nDefault: \"valid\".\n\n- same: Adopts the way of completion. Output height and width will be the same as\nthe input. Total number of padding will be calculated for horizontal and vertical\ndirection and evenly distributed to top and bottom, left and right if possible.\nOtherwise, the last extra padding will be done from the bottom and the right side.\n\n- valid: Adopts the way of discarding. The possibly largest height and width of output\n\nInputs:\n- **input** (Tensor) - Tensor of shape :math:(N, C_{in}, H_{in}, W_{in}).\n\nOutputs:\nTensor of shape :math:(N, C_{out}, H_{out}, W_{out}).\n\nExamples:\n>>> pool = nn.AvgPool2d(kernel_size=3, stride=1)\n>>> x = Tensor(np.random.randint(0, 10, [1, 2, 4, 4]), mindspore.float32)\n[[[[5. 5. 9. 9.]\n[8. 4. 3. 0.]\n[2. 7. 1. 2.]\n[1. 8. 3. 3.]]\n[[6. 8. 2. 4.]\n[3. 0. 2. 1.]\n[0. 8. 9. 7.]\n[2. 1. 4. 9.]]]]\n>>> output = pool(x)\n>>> output.shape\n(1, 2, 2, 2)\n>>> output\n[[[[4.888889 4.4444447]\n[4.111111 3.4444444]]\n[[4.2222223 4.5555553]\n[3.2222223 4.5555553]]]]\n\"\"\"\n\ndef __init__(self,\nkernel_size=1,\nstride=1,\nself.avg_pool = P.AvgPool(ksize=self.kernel_size,\nstrides=self.stride,\n\ndef construct(self, x):\nreturn self.avg_pool(x)\n\n[docs]class AvgPool1d(_PoolNd):\nr\"\"\"\nAverage pooling for temporal data.\n\nApplies a 1D average pooling over an input Tensor which can be regarded as a composition of 1D input planes.\n\nTypically the input is of shape :math:(N_{in}, C_{in}, L_{in}), AvgPool1d outputs\nregional average in the :math:(L_{in})-dimension. Given kernel size\n:math:ks = l_{ker} and stride :math:s = s_0, the operation is as follows.\n\n.. math::\n\\text{output}(N_i, C_j, l) = \\frac{1}{l_{ker}} \\sum_{n=0}^{l_{ker}-1}\n\\text{input}(N_i, C_j, s_0 \\times l + n)\n\nNote:\npad_mode for training only supports \"same\" and \"valid\".\n\nArgs:\nkernel_size (int): The size of kernel window used to take the average value, Default: 1.\nstride (int): The distance of kernel moving, an int number that represents\nthe width of movement is strides, Default: 1.\npad_mode (str): The optional values for pad mode, is \"same\" or \"valid\", not case sensitive.\nDefault: \"valid\".\n\n- same: Adopts the way of completion. Output height and width will be the same as\nthe input. Total number of padding will be calculated for horizontal and vertical\ndirection and evenly distributed to top and bottom, left and right if possible.\nOtherwise, the last extra padding will be done from the bottom and the right side.\n\n- valid: Adopts the way of discarding. The possibly largest height and width of output\n\nInputs:\n- **input** (Tensor) - Tensor of shape :math:(N, C_{in}, L_{in}).\n\nOutputs:\nTensor of shape :math:(N, C_{out}, L_{out}).\n\nExamples:\n>>> pool = nn.AvgPool1d(kernel_size=6, strides=1)\n>>> x = Tensor(np.random.randint(0, 10, [1, 3, 6]), mindspore.float32)\n>>> output = pool(x)\n>>> output.shape\n(1, 3, 1)\n\"\"\"\n\ndef __init__(self,\nkernel_size=1,\nstride=1,\nvalidator.check_value_type('kernel_size', kernel_size, [int], self.cls_name)\nvalidator.check_value_type('stride', stride, [int], self.cls_name)\nvalidator.check_integer(\"kernel_size\", kernel_size, 1, Rel.GE, self.cls_name)\nvalidator.check_integer(\"stride\", stride, 1, Rel.GE, self.cls_name)\nself.kernel_size = (1, kernel_size)\nself.stride = (1, stride)\nself.avg_pool = P.AvgPool(ksize=self.kernel_size,\nstrides=self.stride,\nself.shape = F.shape\nself.reduce_mean = P.ReduceMean(keep_dims=True)\nself.slice = P.Slice()\nself.expand = P.ExpandDims()\nself.squeeze = P.Squeeze(2)\n\ndef construct(self, x):\n_shape_check(self.shape(x))\nbatch, channel, width = self.shape(x)\nif width == self.kernel_size:\nx = self.reduce_mean(x, 2)\nelif width - self.kernel_size < self.stride:\nx = self.slice(x, (0, 0, 0), (batch, channel, self.kernel_size))\nx = self.reduce_mean(x, 2)\nelse:\nx = self.expand(x, 2)\nx = self.avg_pool(x)\nx = self.squeeze(x)\nreturn x"
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https://global-sci.org/intro/article_detail/eajam/10722.html | [
"",
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"",
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"Volume 7, Issue 4\nLinear Regression to Minimize the Total Error of the Numerical Differentiation\n\nEast Asian J. Appl. Math., 7 (2017), pp. 810-826.\n\nPublished online: 2018-02\n\nCited by\n\nExport citation\n• Abstract\n\nIt is well known that numerical derivative contains two types of errors. One is truncation error and the other is rounding error. By evaluating variables with rounding error, together with step size and the unknown coefficient of the truncation error, the total error can be determined. We also know that the step size affects the truncation error very much, especially when the step size is large. On the other hand, rounding error will dominate numerical error when the step size is too small. Thus, to choose a suitable step size is an important task in computing the numerical differentiation. If we want to reach an accuracy result of the numerical difference, we had better estimate the best step size. We can use Taylor Expression to analyze the order of truncation error, which is usually expressed by the big O notation, that is, $E(h)=Ch^k$. Since the leading coefficient $C$ contains the factor $f^{(k)}(ξ)$ for high order $k$ and unknown $ξ$, the truncation error is often estimated by a roughly upper bound. If we try to estimate the high order difference $f^{(k)}(ξ)$, this term usually contains larger error. Hence, the uncertainty of $ξ$ and the rounding errors hinder a possible accurate numerical derivative.\nWe will introduce the statistical process into the traditional numerical difference. The new method estimates truncation error and rounding error at the same time for a given step size. When we estimate these two types of error successfully, we can reach much better modified results. We also propose a genetic approach to reach a confident numerical derivative.\n\n• Keywords\n\nTruncation error, leading coefficient, asymptotic constant, rounding error.\n\n65M10, 78A48\n\n• BibTex\n• RIS\n• TXT\n@Article{EAJAM-7-810, author = {}, title = {Linear Regression to Minimize the Total Error of the Numerical Differentiation}, journal = {East Asian Journal on Applied Mathematics}, year = {2018}, volume = {7}, number = {4}, pages = {810--826}, abstract = {\n\nIt is well known that numerical derivative contains two types of errors. One is truncation error and the other is rounding error. By evaluating variables with rounding error, together with step size and the unknown coefficient of the truncation error, the total error can be determined. We also know that the step size affects the truncation error very much, especially when the step size is large. On the other hand, rounding error will dominate numerical error when the step size is too small. Thus, to choose a suitable step size is an important task in computing the numerical differentiation. If we want to reach an accuracy result of the numerical difference, we had better estimate the best step size. We can use Taylor Expression to analyze the order of truncation error, which is usually expressed by the big O notation, that is, $E(h)=Ch^k$. Since the leading coefficient $C$ contains the factor $f^{(k)}(ξ)$ for high order $k$ and unknown $ξ$, the truncation error is often estimated by a roughly upper bound. If we try to estimate the high order difference $f^{(k)}(ξ)$, this term usually contains larger error. Hence, the uncertainty of $ξ$ and the rounding errors hinder a possible accurate numerical derivative.\nWe will introduce the statistical process into the traditional numerical difference. The new method estimates truncation error and rounding error at the same time for a given step size. When we estimate these two types of error successfully, we can reach much better modified results. We also propose a genetic approach to reach a confident numerical derivative.\n\n}, issn = {2079-7370}, doi = {https://doi.org/10.4208/eajam.161016.300517a}, url = {http://global-sci.org/intro/article_detail/eajam/10722.html} }\nTY - JOUR T1 - Linear Regression to Minimize the Total Error of the Numerical Differentiation JO - East Asian Journal on Applied Mathematics VL - 4 SP - 810 EP - 826 PY - 2018 DA - 2018/02 SN - 7 DO - http://doi.org/10.4208/eajam.161016.300517a UR - https://global-sci.org/intro/article_detail/eajam/10722.html KW - Truncation error, leading coefficient, asymptotic constant, rounding error. AB -\n\nIt is well known that numerical derivative contains two types of errors. One is truncation error and the other is rounding error. By evaluating variables with rounding error, together with step size and the unknown coefficient of the truncation error, the total error can be determined. We also know that the step size affects the truncation error very much, especially when the step size is large. On the other hand, rounding error will dominate numerical error when the step size is too small. Thus, to choose a suitable step size is an important task in computing the numerical differentiation. If we want to reach an accuracy result of the numerical difference, we had better estimate the best step size. We can use Taylor Expression to analyze the order of truncation error, which is usually expressed by the big O notation, that is, $E(h)=Ch^k$. Since the leading coefficient $C$ contains the factor $f^{(k)}(ξ)$ for high order $k$ and unknown $ξ$, the truncation error is often estimated by a roughly upper bound. If we try to estimate the high order difference $f^{(k)}(ξ)$, this term usually contains larger error. Hence, the uncertainty of $ξ$ and the rounding errors hinder a possible accurate numerical derivative.\nWe will introduce the statistical process into the traditional numerical difference. The new method estimates truncation error and rounding error at the same time for a given step size. When we estimate these two types of error successfully, we can reach much better modified results. We also propose a genetic approach to reach a confident numerical derivative.\n\nJengnan Tzeng. (2020). Linear Regression to Minimize the Total Error of the Numerical Differentiation. East Asian Journal on Applied Mathematics. 7 (4). 810-826. doi:10.4208/eajam.161016.300517a\nCopy to clipboard\nThe citation has been copied to your clipboard"
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https://support.ecotechmarine.com/hc/en-us/articles/215339608-How-do-I-calculate-head-pressure- | [
"Follow\n\n# How do I calculate head pressure?\n\nHead pressure is calculated and represented in terms of feet (ft.). In order to calculate the total head pressure of your application, you'll need to know the difference in elevation between your return pump and return outlet. You will also need to know the total number and type of fittings used as well as the total distance of pipe used.\n\nThe effect of gravity on head pressure is very simple. Every vertical foot of distance the return pump moves water equates to 1 foot of head pressure. The effects of friction on head pressure are more difficult to calculate. Roughly every 10 feet of pipe through which water is traveling adds 1 foot of head pressure. Additionally, every 90-degree bend adds 1 foot of head pressure.\n\nPipe diameter is also an extremely important factor when calculating head pressure. As a general rule of thumb, reducing the size of pipe below the return pump output will drastically increase head pressure. For minimum head pressure, using the largest diameter pipe possible is best. Avoiding things like flow meters, reactors and chillers will also help to reduce head pressure.",
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http://talkstats.com/threads/confidence-interval-of-mean-of-queue-length-m-m-1.57512/ | [
"# Confidence interval of mean of queue length (M/M/1)\n\n#### Knaapje\n\n##### New Member\nGoodday,\n\nFor a simulation course I had to simulate a single server queue with Poisson processes for arrival and departure (M/M/1). Now, this really was not the issue, the issue is where I personally want to add a kind of validity check, which naturally can only be done with statistics.\n\nI want to construct a 99.5% confidence interval for the average queue length. The following information is known: total simulated 'time', list of amount of time per queue length during the duration (example: w_0 = 3 means that during the entire simulation the total amount of time the queue contained no customers is 3) and all arrival and departure times and the analytical value of the mean.\n\nNow, I know the formula for the weighted sample mean and the weighted sample variance (where the mean is known), but I have no idea how to construct the confidence interval. Any help would be greatly appreciated.\n\n#### rogojel\n\n##### TS Contributor\nhi,\na simple and pragmatic way would be to use bootstapping, as you already habe a simulation. Of course if you are interested in a formula then it is not helping.\n\nregards\nrogojel"
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https://www.mathworks.com/matlabcentral/profile/authors/19558205?detail=cody | [
"Community Profile",
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"liu ce\n\nLast seen: 3 months ago Active since 2021\n\nStatistics\n\n•",
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"•",
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"Content Feed\n\nView by\n\nSolved\n\nSum all integers from 1 to 2^n\nGiven the number x, y must be the summation of all integers from 1 to 2^x. For instance if x=2 then y must be 1+2+3+4=10.\n\n4 months ago\n\nSolved\n\nMagic is simple (for beginners)\nDetermine for a magic square of order n, the magic sum m. For example m=15 for a magic square of order 3.\n\n4 months ago\n\nSolved\n\nMake a random, non-repeating vector.\nThis is a basic MATLAB operation. It is for instructional purposes. --- If you want to get a random permutation of integer...\n\n4 months ago\n\nSolved\n\nRoll the Dice!\n*Description* Return two random integers between 1 and 6, inclusive, to simulate rolling 2 dice. *Example* [x1,x2] =...\n\n4 months ago\n\nSolved\n\nNumber of 1s in a binary string\nFind the number of 1s in the given binary string. Example. If the input string is '1100101', the output is 4. If the input stri...\n\n4 months ago\n\nSolved\n\nReturn the first and last characters of a character array\nReturn the first and last character of a string, concatenated together. If there is only one character in the string, the functi...\n\n4 months ago\n\nSolved\n\nGetting the indices from a vector\nThis is a basic MATLAB operation. It is for instructional purposes. --- You may already know how to <http://www.mathworks....\n\n4 months ago\n\nSolved\n\nCheck if number exists in vector\nReturn 1 if number _a_ exists in vector _b_ otherwise return 0. a = 3; b = [1,2,4]; Returns 0. a = 3; b = [1,...\n\n4 months ago\n\nSolved\n\nSwap the input arguments\nWrite a two-input, two-output function that swaps its two input arguments. For example: [q,r] = swap(5,10) returns q = ...\n\n4 months ago\n\nSolved\n\nColumn Removal\nRemove the nth column from input matrix A and return the resulting matrix in output B. So if A = [1 2 3; 4 5 6]; ...\n\n4 months ago\n\nSolved\n\nReverse the vector\nReverse the vector elements. Example: Input x = [1,2,3,4,5,6,7,8,9] Output y = [9,8,7,6,5,4,3,2,1]\n\n4 months ago\n\nSolved\n\nLength of the hypotenuse\nGiven short sides of lengths a and b, calculate the length c of the hypotenuse of the right-angled triangle. <<https://i.imgu...\n\n4 months ago\n\nSolved\n\nGenerate a vector like 1,2,2,3,3,3,4,4,4,4\nGenerate a vector like 1,2,2,3,3,3,4,4,4,4 So if n = 3, then return [1 2 2 3 3 3] And if n = 5, then return [1 2 2...\n\n4 months ago\n\nSolved\n\nReturn area of square\nSide of square=input=a Area=output=b\n\n4 months ago\n\nSolved\n\nMaximum value in a matrix\nFind the maximum value in the given matrix. For example, if A = [1 2 3; 4 7 8; 0 9 1]; then the answer is 9.\n\n4 months ago\n\nSolved\n\nVector creation\nCreate a vector using square brackets going from 1 to the given value x in steps on 1. Hint: use increment.\n\n4 months ago\n\nSolved\n\nDoubling elements in a vector\nGiven the vector A, return B in which all numbers in A are doubling. So for: A = [ 1 5 8 ] then B = [ 1 1 5 ...\n\n4 months ago\n\nSolved\n\nCreate a vector\nCreate a vector from 0 to n by intervals of 2.\n\n4 months ago\n\nSolved\n\nFlip the vector from right to left\nFlip the vector from right to left. Examples x=[1:5], then y=[5 4 3 2 1] x=[1 4 6], then y=[6 4 1]; Request not ...\n\n4 months ago\n\nSolved\n\nWhether the input is vector?\nGiven the input x, return 1 if x is vector or else 0.\n\n4 months ago\n\nSolved\n\nFind max\nFind the maximum value of a given vector or matrix.\n\n4 months ago\n\nSolved\n\nGet the length of a given vector\nGiven a vector x, the output y should equal the length of x.\n\n4 months ago\n\nSolved\n\nInner product of two vectors\nFind the inner product of two vectors.\n\n4 months ago\n\nSolved\n\nArrange Vector in descending order\nIf x=[0,3,4,2,1] then y=[4,3,2,1,0]\n\n4 months ago\n\nSolved\n\nDetermine if input is odd\nGiven the input n, return true if n is odd or false if n is even.\n\n4 months ago\n\nSolved\n\nPangrams!\nA pangram, or holoalphabetic sentence, is a sentence using every letter of the alphabet at least once. Example: Input s ...\n\n4 months ago\n\nSolved\n\nCounting Money\nAdd the numbers given in the cell array of strings. The strings represent amounts of money using this notation: \\$99,999.99. E...\n\n4 months ago\n\nSolved\n\nNearest Numbers\nGiven a row vector of numbers, find the indices of the two nearest numbers. Examples: [index1 index2] = nearestNumbers([2 5 3...\n\n4 months ago\n\nSolved\n\nSort a list of complex numbers based on far they are from the origin.\nGiven a list of complex numbers z, return a list zSorted such that the numbers that are farthest from the origin (0+0i) appear f...\n\n4 months ago\n\nSolved\n\nRemove all the words that end with \"ain\"\nGiven the string s1, return the string s2 with the target characters removed. For example, given s1 = 'the main event' your ...\n\n4 months ago"
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] | {"ft_lang_label":"__label__en","ft_lang_prob":0.6861306,"math_prob":0.9940376,"size":4979,"snap":"2022-05-2022-21","text_gpt3_token_len":1522,"char_repetition_ratio":0.200201,"word_repetition_ratio":0.053376906,"special_character_ratio":0.29524,"punctuation_ratio":0.16694915,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.9964691,"pos_list":[0,1,2,3,4,5,6,7,8,9,10],"im_url_duplicate_count":[null,1,null,null,null,null,null,null,null,null,null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2022-01-20T03:09:37Z\",\"WARC-Record-ID\":\"<urn:uuid:268f88f7-12a1-429e-bafe-5fdbf959741c>\",\"Content-Length\":\"101138\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:8ecd25b8-1374-4137-85ce-bf7d322eef44>\",\"WARC-Concurrent-To\":\"<urn:uuid:e573e699-ea3f-469e-9165-8187634893ce>\",\"WARC-IP-Address\":\"23.39.174.83\",\"WARC-Target-URI\":\"https://www.mathworks.com/matlabcentral/profile/authors/19558205?detail=cody\",\"WARC-Payload-Digest\":\"sha1:WDC7WOXLBLZPA5N573G63AIJ3W3XLBVF\",\"WARC-Block-Digest\":\"sha1:VERADDXBKFF4MSCEI46Y2WBFER2W7D5D\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2022/CC-MAIN-2022-05/CC-MAIN-2022-05_segments_1642320301670.75_warc_CC-MAIN-20220120005715-20220120035715-00498.warc.gz\"}"} |
https://www.geeksforgeeks.org/maximum-squares-possible-parallel-to-both-axes-from-n-distinct-points/ | [
"Maximum Squares possible parallel to both axes from N distinct points\n\n• Last Updated : 26 Nov, 2021\n\nGiven Xi and Yi co-ordinate of N distinct points in the 2-D Plane, the task is to count the number of squares that can be formed from these points that are parallel to both X and Y-axis.\nExamples:\n\nInput : X[] = { 0, 2, 0, 2 }, Y[] = { 0, 2, 2, 0 }\nOutput :\nExplanation: Only one Square can be formed using these points –\n(0, 2)(2, 2)\n(0, 0)(2, 0)\nInput : X[] = { 3, 2, 0, 6 }, Y[] = { 0, 2, 0, 6 }\nOutput :\nExplanation: No Square can be formed using these points –\n(3,0),(2,0), (0,0), (6,6)\n\nNaive Approach: Iterate over all possible combinations of four points and check if a square can be formed that is parallel to both X and Y-axis. The time complexity of this approach would be O(N4)\nEfficient Approach: We can observe that for any four points to make a required square, the following conditions must hold true –\n\n• The points lying in the same horizontal line must have the same Y co-ordinates.\n\n• The points lying in the same vertical line must have the same X co-ordinates.\n\n• The distance between these points should be same.\n\nThus the four points of any square can be written as P1(X1, Y1), P2(X2, Y1), P3(X2, Y2) and P4(X1, Y2) in clockwise direction.\nConsider any two points on the same horizontal or vertical line from the given ones. Calculate the distance between them. Based on that, form the other two points. Now check if both of the given points are present or not. If so, it ensures that a square is present. Hence, increase the count and proceed further.\nBelow is the implementation of the above approach:\n\nC++\n\n // C++ implementation of the approach#include using namespace std; // Function that returns the count of// squares parallel to both X and Y-axis// from a given set of pointsint countSquares(int* X, int* Y, int N){ // Initialize result int count = 0; // Initialize a set to store points set > points; // Initialize a map to store the // points in the same vertical line map > vertical; // Store the points in a set for (int i = 0; i < N; i++) { points.insert({ X[i], Y[i] }); } // Store the points in the same vertical line // i.e. with same X co-ordinates for (int i = 0; i < N; i++) { vertical[X[i]].push_back(Y[i]); } // Check for every two points // in the same vertical line for (auto line : vertical) { int X1 = line.first; vector yList = line.second; for (int i = 0; i < yList.size(); i++) { int Y1 = yList[i]; for (int j = i + 1; j < yList.size(); j++) { int Y2 = yList[j]; int side = abs(Y1 - Y2); int X2 = X1 + side; // Check if other two point are present or not if (points.find({ X2, Y1 }) != points.end() and points.find({ X2, Y2 }) != points.end()) count++; } } } return count;} // Driver Codeint main(){ int X[] = { 0, 2, 0, 2 }, Y[] = { 0, 2, 2, 0 }; int N = sizeof(X) / sizeof(X); cout << countSquares(X, Y, N); return 0;}\n\nPython3\n\n # Python3 implementation of the approach # Function that returns the count of# squares parallel to both X and Y-axis# from a given set of pointsdef countSquares(X, Y, N) : # Initialize result count = 0; # Initialize a set to store points points = []; # Initialize a map to store the # points in the same vertical line vertical = dict.fromkeys(X, None); # Store the points in a set for i in range(N) : points.append((X[i], Y[i])); # Store the points in the same vertical line # i.e. with same X co-ordinates for i in range(N) : if vertical[X[i]] is None : vertical[X[i]] = [Y[i]]; else : vertical[X[i]].append(Y[i]); # Check for every two points # in the same vertical line for line in vertical : X1 = line; yList = vertical[line]; for i in range(len(yList)) : Y1 = yList[i]; for j in range(i + 1, len(yList)) : Y2 = yList[j]; side = abs(Y1 - Y2); X2 = X1 + side; # Check if other two point are present or not if ( X2, Y1 ) in points and ( X2, Y2 ) in points : count += 1; return count; # Driver Codeif __name__ == \"__main__\" : X = [ 0, 2, 0, 2 ]; Y = [ 0, 2, 2, 0 ]; N = len(X); print(countSquares(X, Y, N)); # This code is contributed by AnkitRai01\nOutput:\n1\n\nTime Complexity: O(N2).\n\nAuxiliary Space: O(N)\n\nMy Personal Notes arrow_drop_up"
] | [
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http://www.numdam.org/item/?id=RSMUP_2013__130__169_0 | [
"Hölder continuity for sub-elliptic systems under the sub-quadratic controllable growth in Carnot groups\nRendiconti del Seminario Matematico della Università di Padova, Volume 130 (2013), p. 169-202\n@article{RSMUP_2013__130__169_0,\nauthor = {Wang, Jialin and Liao, Dongni and Yu, Zefeng},\ntitle = {H\\\"older continuity for sub-elliptic systems under the sub-quadratic controllable growth in Carnot groups},\njournal = {Rendiconti del Seminario Matematico della Universit\\a di Padova},\npublisher = {Seminario Matematico of the University of Padua},\nvolume = {130},\nyear = {2013},\npages = {169-202},\nmrnumber = {3148637},\nlanguage = {en},\nurl = {http://www.numdam.org/item/RSMUP_2013__130__169_0}\n}\n\nWang, Jialin; Liao, Dongni; Yu, Zefeng. Hölder continuity for sub-elliptic systems under the sub-quadratic controllable growth in Carnot groups. Rendiconti del Seminario Matematico della Università di Padova, Volume 130 (2013) , pp. 169-202. http://www.numdam.org/item/RSMUP_2013__130__169_0/`\n\n E. De Giorgi, Un esempio di estremali discontinue per un problema variazionale di tipo ellitico. Boll. Unione Mat. Italiana 4 (1968), pp. 135-137. | MR 227827\n\n M. Giaquinta, Multiple Integrals in the Calculus of Variations and Nonlinear Elliptic Systems. Princeton Univ. Press, Princeton, 1983. | MR 717034\n\n M. Giaquinta, Introduction to regularity theory for nonlinear elliptic systems. Birkhäuser, Berlin, 1993. | MR 1239172\n\n Y. Chen - L. Wu, Second order elliptic equations and elliptic systems. Science Press, Beijing, 2003.\n\n M. Giaquinta - G. Modica, Almost-everywhere regularity results for solutions of non linear elliptic systems. Manuscripta Math. 28 (1979), pp. 109-158, | MR 535699\n\n E. Giusti - M. Miranda, Sulla regolarità delle soluzioni deboli di una classe di sistemi ellittici quasilineari. Arch. Rat. Mech. Anal. 31 (1968), pp. 173-184. | MR 235264\n\n F. Duzaar - J. F. Grotowski, Partial regularity for nonlinear elliptic systems: The method of A-harmonic approximation, Manuscripta Math. 103 (2000), pp. 267-298. | MR 1802484\n\n L. Simon, Lectures on Geometric Measure Theory. Australian National University Press, Canberra, 1983. | MR 756417\n\n F. Duzaar - J. F. Grotowski - M. Kronz, Regularity of almost minimizers of quasi-convex variational integrals with subquadratic growth. Annali Mat. Pura Appl. (4) 184 (2005), pp. 421-448. | MR 2177809\n\n F. Duzaar - G. Mingione, The $p$ -harmonic approximation and the regularity of $p$ -harmonic maps. Calc. Var. Partial Differential Equations 20 (2004), pp. 235-256. | MR 2062943\n\n F. Duzaar - G. Mingione, Regularity for degenerate elliptic problems via $p$ -harmonic approximation. Ann. Inst. H. Poincaré Anal. Non Linèaire 21 (2004), pp. 735-766. | MR 2086757\n\n M. Carozza - N. Fusco - G. Mingione, Partial regularity of minimizers of quasiconvex integrals with subquadratic growth, Annali Mat. Pura Appl. (4) 175 (1998), pp. 141-164. | MR 1748219\n\n S. Chen - Z. Tan, The method of A-harmonic approximation and optimal interior partial regularity for nonlinear elliptic systems under the controllable growth condition. J. Math. Anal. Appl. 335 (2007), pp. 20-42. | MR 2340302\n\n S. Chen - Z. Tan, Optimal interior partial regularity for nonlinear elliptic systems. Discrete Contin. Dyn. Syst. 27 (2010), pp. 981-993. | MR 2629569\n\n L. Capogna - N. Garofalo, Regularity of minimizers of the calculus of variations in Carnot groups via hypoellipticity of systems of Hörmander type. J. European Math. Society 5 (2003), pp. 1-40. | MR 1961133\n\n E. Shores, Hypoellipticity for linear degenerate elliptic systems in Carnot groups and applications, arXiv:math/0502569, pp. 27.\n\n A. Föglein, Partial regularity results for subelliptic systems in the Heisenberg group, Calc. Var. Partial Differential Equations 32 (2008), pp. 25-51. | MR 2377405\n\n J. Wang - P. Niu, Optimal partial regularity for weak solutions of nonlinear sub-elliptic systems in Carnot groups. Nonlinear Analysis 72 (2010), pp. 4162-4187. | MR 2606775\n\n L. Capogna - D. Danielli - N. Garofalo, An embedding theorem and the Harnak inequality for nonlinear subelliptic equations. Comm. Partial Differential Equations 18 (1993), pp. 1765-1794. | MR 1239930\n\n G. Lu, Embedding theorems into Lipschitz and BMO spaces and applications to quasilinear subelliptic differential equations. Publ. Mat. 40 (1996), pp. 301-329. | MR 1425620\n\n C. Xu, Regularity for quasi-linear second order subelliptic equations. Comm. Pure Appl. Math. 45 (1992), pp. 77-96.\n\n L. Capogna, Regularity of quasi-linear equations in the Heisenberg group. Comm. Pure Appl. Math. 50 (1997), pp. 867-889. | MR 1459590\n\n L. Capogna, Regularity for quasilinear equation and 1-quasiconformal maps in Carnot groups. Math. Ann. 313 (1999), pp. 263-295. | MR 1679786\n\n S. Marchi, ${C}^{1,\\alpha }$ local regularity for the solutions of the $p$ -Laplacian on the Heisenberg group for $2p+\\sqrt{5}$ . Z. Anal. Anwendungen 20 (2001), pp. 617-636. | MR 1863937\n\n S. Marchi, ${C}^{1,\\alpha }$ local regularity for the solutions of the $p$ -Laplacian on the Heisenberg group for $1+\\frac{1}{\\sqrt{5}}p\\le 2$ . Comment. Math. Univ. Carolinae 44 (2003), pp. 33-56. | MR 2045844\n\n A. Domokos, Differentiability of solutions for the non-degenerate $p$ -Laplacian in the Heisenberg group. J. Differential Equations. 204 (2004), pp. 439-470. | MR 2085543\n\n A. Domokos, On the regularity of $p$ -harmonic functions in the Heisenberg group. Ph. D. Thesis, University of Pittsburgh, 2004.\n\n J. Manfredi - G. Mingione, Regularity results for quasilinear elliptic equations in the Heisenberg group. Math. Ann. 339 (2007), pp. 485-544. | MR 2336058\n\n G. Mingione - A. Zatorska-Goldstein - X. Zhong, Gradient regularity for elliptic equations in the Heisenberg group. Advances in Mathematics 222 (2009), pp. 62-129. | MR 2531368\n\n N. Garofalo, Gradient bounds for the horizontal $p$ -Laplacian on a Carnot group and some applications. Manuscripta Math. 130 (2009), pp. 375-385. | MR 2545524\n\n G. Folland, Subelliptic estimates and function spaces on nilpotent Lie groups. Ark. Mat. 13 (1975), pp. 161-207. | MR 494315\n\n E. Acerbi - N. Fusco, Regularity for minimizers of nonquadratic functionals: the case $1p$ , J. Math. Anal. Appl. 140 (1989), pp. 115-135. | MR 997847\n\n G. Lu, Embedding theorems on Campanato-Morrey space for vector fields on Hörmander type. Approx. Theory Appl. 14 (1998), pp. 69-80. | MR 1651473"
] | [
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https://roytuts.com/printing-pyramid-with-stars-in-unix-shell-programming/ | [
"# Printing pyramid with stars in Unix Shell Programming\n\nThe below unix shell programming will show you an example on printing pyramid with stars in unix shell programming. This tutorial will also show how to use if else condition, how to use for loop in shell programming. You will also see how to take input from keyboard.\n\nI will be printing pyramid with stars in unix shell programming in two ways – one is stars exist inside and another one is stars do not exist inside the pyramid.\n\nSo let’s see the first example where stars exist also inside the pyramid.\n\nThe below shell program first takes the depth or level or height from the user for the pyramid. The program itself calculates the number of stars at each level according to the height of the pyramid. I also put the space between two stars to look good.\n\nThe below shell programming is written into the file pyramid-stars-inner.sh.\n\n``````#!/bin/bash\n\nread -r -p \"Enter depth of pyramid: \" n\necho \"You enetered level: \\$n\"\n\nspace=n\n\nfor((i=1;i<=n;i++))\ndo\nspace=\\$((space-1)) #calculate how many spaces should be printed before *\n\nfor((j=1;j<=space;j++))\ndo\necho -n \" \" #print spaces on the same line before printing *\ndone\nfor((k=1;k<=i;k++))\ndo\necho -n \"*\" #print * on the same line\necho -n \" \" #print space after * on the same line\ndone\necho -e #print new line after each row\ndone``````\n\nMake sure you change the permission of the above shell script by using the following command:\n\n``\\$ chmod +x pyramid-stars-inner.sh``\n\nTo run or execute the above shell script use the following command:\n\n``\\$ ./pyramid-stars-inner.sh``\n\nAfter running the above shell program you will get the below output. So here you see that the pyramid is filled with stars in whole area. So this is a solid pyramid where inner surface is also filled with stars.\n\nNow let’s see the example where outer surface of the pyramid is filled with stars. Here also you will get the input for level or height of the pyramid and accordingly we put stars on outer surface at each level at two furthest ends.\n\nThe following shell program is written into the file pyramid-stars-outer.sh.\n\n``````read -r -p \"Enter depth of pyramid: \" n\necho \"You enetered level: \\$n\"\n\ns=0\nspace=n\n\nfor((i=1;i<=n;i++))\ndo\nspace=\\$((space-1)) #calculate how many spaces should be printed before *\n\nfor((j=1;j<=space;j++))\ndo\necho -n \" \" #print spaces on the same line before printing *\ndone\nfor((k=1;k<=i;k++))\ndo\nif((i==1 || i==2 || i==n))\nthen\necho -n \"*\" #print * on the same line\necho -n \" \" #print space after * on the same line\nelif((k==1))\nthen\necho -n \"*\" #print * on the same line\nelif((k==i))\nthen\nfor((l=1;l<=k+s;l++))\ndo\necho -n \" \" #print spaces on the same line before printing *\ndone\ns=\\$((s+1)) #as pyramid expands at bottom, so we need to recalculate inner spaces\necho -n \"*\" #print * on the same line\nfi\ndone\necho -e #print new line after each row\ndone``````\n\nMake sure you again change the permission using the command:\n\n``\\$ chmod +x pyramid-stars-outer.sh``\n\nTo run the shell script use the following command:\n\n``\\$ ./pyramid-stars-outer.sh``\n\nHere is the below output you get after running the above shell script."
] | [
null
] | {"ft_lang_label":"__label__en","ft_lang_prob":0.77144676,"math_prob":0.8175048,"size":3011,"snap":"2021-43-2021-49","text_gpt3_token_len":773,"char_repetition_ratio":0.14931826,"word_repetition_ratio":0.31548756,"special_character_ratio":0.2660246,"punctuation_ratio":0.07954545,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.99179167,"pos_list":[0],"im_url_duplicate_count":[null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2021-10-22T06:47:53Z\",\"WARC-Record-ID\":\"<urn:uuid:2ab14082-1848-4a34-85b9-285325578a40>\",\"Content-Length\":\"49990\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:2d9cf3f8-795a-4783-9327-cd6a8fc6b901>\",\"WARC-Concurrent-To\":\"<urn:uuid:85c19c09-dbaa-42fa-a54d-04d7aabbc12f>\",\"WARC-IP-Address\":\"104.21.68.14\",\"WARC-Target-URI\":\"https://roytuts.com/printing-pyramid-with-stars-in-unix-shell-programming/\",\"WARC-Payload-Digest\":\"sha1:KIATHEAOGHYGRKECHB3XS3VTM4FHPKWB\",\"WARC-Block-Digest\":\"sha1:CTSFHLWITW3JHVLJGCWOBGVHYXRA2N5F\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2021/CC-MAIN-2021-43/CC-MAIN-2021-43_segments_1634323585460.87_warc_CC-MAIN-20211022052742-20211022082742-00094.warc.gz\"}"} |
http://www.numbersaplenty.com/3540266303 | [
"Search a number\nBaseRepresentation\nbin1101001100000100…\n…0010110100111111\n3100010201122011101012\n43103001002310333\n524222302010203\n61343144105435\n7153505524050\noct32301026477\n910121564335\n103540266303\n11155742a522\n1282976527b\n134455c7442\n14258280727\n1515ac12bd8\nhexd3042d3f\n\n3540266303 has 8 divisors (see below), whose sum is σ = 4284019872. Its totient is φ = 2856013056.\n\nThe previous prime is 3540266293. The next prime is 3540266311. The reversal of 3540266303 is 3036620453.\n\nAdding to 3540266303 its reverse (3036620453), we get a palindrome (6576886756).\n\n3540266303 is digitally balanced in base 2, because in such base it contains all the possibile digits an equal number of times.\n\nIt is a sphenic number, since it is the product of 3 distinct primes.\n\nIt is not a de Polignac number, because 3540266303 - 24 = 3540266287 is a prime.\n\nIt is a Duffinian number.\n\nIt is a self number, because there is not a number n which added to its sum of digits gives 3540266303.\n\nIt is a congruent number.\n\nIt is not an unprimeable number, because it can be changed into a prime (3540266363) by changing a digit.\n\nIt is a polite number, since it can be written in 7 ways as a sum of consecutive naturals, for example, 14874950 + ... + 14875187.\n\nIt is an arithmetic number, because the mean of its divisors is an integer number (535502484).\n\nAlmost surely, 23540266303 is an apocalyptic number.\n\n3540266303 is a deficient number, since it is larger than the sum of its proper divisors (743753569).\n\n3540266303 is a wasteful number, since it uses less digits than its factorization.\n\n3540266303 is an evil number, because the sum of its binary digits is even.\n\nThe sum of its prime factors is 29750161.\n\nThe product of its (nonzero) digits is 38880, while the sum is 32.\n\nThe square root of 3540266303 is about 59500.1369998423. The cubic root of 3540266303 is about 1524.0947852619.\n\nThe spelling of 3540266303 in words is \"three billion, five hundred forty million, two hundred sixty-six thousand, three hundred three\"."
] | [
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] | {"ft_lang_label":"__label__en","ft_lang_prob":0.8284146,"math_prob":0.99042946,"size":2129,"snap":"2020-24-2020-29","text_gpt3_token_len":645,"char_repetition_ratio":0.17411764,"word_repetition_ratio":0.0058139535,"special_character_ratio":0.45937058,"punctuation_ratio":0.13231552,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.9942571,"pos_list":[0],"im_url_duplicate_count":[null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2020-06-04T00:35:15Z\",\"WARC-Record-ID\":\"<urn:uuid:caabe264-7ef4-4c6e-893d-063577d5f1d1>\",\"Content-Length\":\"9224\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:8c063dca-01d6-4a77-bbcc-374276f6dbda>\",\"WARC-Concurrent-To\":\"<urn:uuid:8c11dc54-9fc1-4387-a70b-247a657d7f69>\",\"WARC-IP-Address\":\"62.149.142.170\",\"WARC-Target-URI\":\"http://www.numbersaplenty.com/3540266303\",\"WARC-Payload-Digest\":\"sha1:TJUHD34QDG3LDS43JXP3Z3UIGADDZKNO\",\"WARC-Block-Digest\":\"sha1:WGQECIENQIN2N2YIIEBH7THTN5HNH4CP\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2020/CC-MAIN-2020-24/CC-MAIN-2020-24_segments_1590347436828.65_warc_CC-MAIN-20200604001115-20200604031115-00333.warc.gz\"}"} |
http://m.maonotech.com/info/what-is-compression-ratio-27067811.html | [
"What Is Compression Ratio?\n\n- Jul 02, 2018-\n\nThe compression ratio is the ratio of the input signal gain to the output signal gain. It is generally expressed by a certain ratio. For example, a compression ratio of 1.5:1 cannot be said to be 3:2, which means that the input signal level exceeding the threshold is increased by 1.5. Decibel, the output is increased by 1 decibel. When the compression ratio is equal to infinity, the output signal will no longer increase when the input signal is increased. In this case, the compressor is used as a limiter."
] | [
null
] | {"ft_lang_label":"__label__en","ft_lang_prob":0.9155602,"math_prob":0.9854157,"size":689,"snap":"2019-43-2019-47","text_gpt3_token_len":154,"char_repetition_ratio":0.15182482,"word_repetition_ratio":0.0,"special_character_ratio":0.20754717,"punctuation_ratio":0.15714286,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.9692994,"pos_list":[0],"im_url_duplicate_count":[null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2019-10-14T11:29:25Z\",\"WARC-Record-ID\":\"<urn:uuid:3c3bd02e-6f13-40ed-82f1-fe3f93890f51>\",\"Content-Length\":\"9430\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:1a94d256-adb9-4c9a-9fe3-e85c4e5a3da1>\",\"WARC-Concurrent-To\":\"<urn:uuid:e9b4b765-df08-448c-b388-8fc84aec4164>\",\"WARC-IP-Address\":\"104.42.26.214\",\"WARC-Target-URI\":\"http://m.maonotech.com/info/what-is-compression-ratio-27067811.html\",\"WARC-Payload-Digest\":\"sha1:POGIDM375XL5V3NMMF53H6R5I4XLSR6Q\",\"WARC-Block-Digest\":\"sha1:MR2OFPALSCDSAACH26GAPALJXOYPRCFE\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2019/CC-MAIN-2019-43/CC-MAIN-2019-43_segments_1570986653216.3_warc_CC-MAIN-20191014101303-20191014124303-00421.warc.gz\"}"} |
https://www.solvemathproblem.com/2021/08/31/1351-2/ | [
"# domain and the range\n\nMidterm Exam Review MATH 178 NAME_____________________________ 1. Find the following limits: x2 − x − 2 x →−1 x 2 + 3 x + 2 a. lim 3x + 2 b. lim x→2 3×3 − 3x 2 − 6 x s →−1 x2 + x c. lim 3x 2 − 5 x → 2 x 2 − 4 e. lim d. lim x→4 1 x−4 x3 − 5 x → 2 x 4 − 4 x + 1 f. lim x2 2. Given the following, sketch the graph and find the limits: f ( x ) = 3 − x a. Find lim− f ( x) x →2 b. Find lim+ f ( x) x →2 c. Find lim f ( x) x →2 if x2 if x2 x2 + 2 3. Given the following: f ( x) = 6 x + 9 if if x −1 x −1 a. Find f ( −3) b. Find f (5) c. Find f (−1) 4. Given the following graph, identify the domain and the range. 5. Find the domain for the following functions: f ( x) = 5 − 7 x b. f ( x) = x−4 2 x − 15 x + 7 2 6. Find the slope of the tangent line on the curve f ( x) = 5x 2 − 3x + 8 at the point (−2,34) 7. Find the equation of the tangent line to the curve y = 9 − 2 x 2 at the point (2, 1). Use: y = mx + b or y − y1 = m( x − x1 ) 8. Find the following derivatives: a. f ( x) = 4 x3 − 5x 2 + 8x + 2 b. f ( x) = ( x 2 + 3)( x 2 − 5) c. f ( x) = 5 x7 d. f ( x) = x+2 x −3 e. f ( x) = x2 − 5x − 1 f. g ( x) = ( x 3 − 5 ) 7 g. f ( x) = 3x ln x x3 h. y = ln 2x − 7 i. f ( x) = 10e4 x − 3×2 j. g ( x) = k. f ( x) = ln(5x 2 − 3x + 6) l. x +5 g ( x) = x 2 4×2 ln x 4 9. Given f ( x) = 4 x3 − 2 x 2 − 5x + 3 find f (−2) 10. Find f (x) given f ( x) = 1 ( 2 x − 1) 3 11. A ball is thrown vertically upward with a velocity of 80 ft/sec its height after t seconds is given by the function: s(t ) = −16t 2 + 80t . Solve the following using calculus techniques discussed in class. a. What is the velocity of the ball after 2 seconds? b. What is the maximum height reached by the ball? 12. A company that produces and sells cellular phones determines that the cost of producing x telephones is C ( x) = 0.45x 2 − 15x + 250 dollars. Find the rate at which the cost is changing when 100 cellular phones are produced. 13. Given the following graph, find the limits: a. lim f ( x) = __________ x →1− d. lim− f ( x) = __________ x →2 b. lim+ f ( x) = __________ c. lim f ( x) = __________ e. lim f ( x) = __________ f. lim+ f ( x) = __________ x →1 x →−2 x →1 x →2 14. A bank advertises that it compounds interest continuously and that it will double your money in 15 years. Find the function that satisfies the equation and what is the annual interest rate? Hint: use P = Po e rt 15. How old is a Chinese artifact that has lost 60% of its Carbon-14? Carbon-14 has a decay rate of 0.01205% per year. Hint: use N = N o e − rt 16. The average cost C of a prime-rib dinner was \\$4.65 in 1962. Assuming that the exponential growth model applies, and that the exponential growth rate is 5.1%, what will be the cost of such a dinner in 2018? Hint: use P = Po e rt Solutions: 1. 2. 3. 4. 5. a) b) c) d) e) f) 8 -3 –9 DNE (does not exist) 3/2 0 a) 4 b) 1 c) DNE a) 11 b) 39 c) 3 D: (-3, 1] R: [-4, 0] a. (-inf, 5/7] b. All reals except ½ and 7 6. m = -23 7. y= – 8x + 17 8. a) f ( x) = 12 x 2 − 10 x + 8 b) −5 c) f ( x) = −35 x8 d) f ( x) = e) f ( x) = 2x − 5 2 x² − 5x − 1 f) g ( x) = 21x 2 ( x3 − 5 ) 2 3 2 − x x−7 8 x ln x − 4 x j) g ( x) = (ln x)2 i) f ( x) = 80xe4 x − 6 x 2 k) f ( x) = ( x − 3) h) y = g) f ( x) = 3 + 3ln x 9. f ( x) = 4 x ³ − 4 x 10 x − 3 5 x 2 − 3x + 6 l) g ( x) = −20( x + 5)3 x5 f (−2) = 51 10. f ( x) = 48 ( 2 x − 1) 5 11. a) 16 ft/sec b) 100 ft 12. \\$75, the cost will increase \\$75 when the 101st phone is produced. 13. a) 1 14. 4.6% b) 3 c) DNE d) 3 15. 7604 years e) 4 16. \\$80.87 f) 2 6\nPurchase answer to see full attachment\n\nJust \\$7 Welcome"
] | [
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] | {"ft_lang_label":"__label__en","ft_lang_prob":0.6565322,"math_prob":0.999984,"size":3545,"snap":"2022-40-2023-06","text_gpt3_token_len":1533,"char_repetition_ratio":0.18441118,"word_repetition_ratio":0.046343975,"special_character_ratio":0.5210155,"punctuation_ratio":0.119198315,"nsfw_num_words":2,"has_unicode_error":false,"math_prob_llama3":0.9999485,"pos_list":[0],"im_url_duplicate_count":[null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2022-09-29T18:13:48Z\",\"WARC-Record-ID\":\"<urn:uuid:e657f2ea-ae87-4c15-843f-5435ef9b2adc>\",\"Content-Length\":\"50226\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:21107e3f-f317-4261-a200-904b000d33c3>\",\"WARC-Concurrent-To\":\"<urn:uuid:8539e089-f63e-48e1-86a5-0b47beed4580>\",\"WARC-IP-Address\":\"5.161.111.97\",\"WARC-Target-URI\":\"https://www.solvemathproblem.com/2021/08/31/1351-2/\",\"WARC-Payload-Digest\":\"sha1:I4V2S6H423DYSZSXDQJDFEQPXAQG3G2X\",\"WARC-Block-Digest\":\"sha1:RSEFYBZHSOD6I4YS5XDMZBDI5EHBKWXR\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2022/CC-MAIN-2022-40/CC-MAIN-2022-40_segments_1664030335362.18_warc_CC-MAIN-20220929163117-20220929193117-00621.warc.gz\"}"} |
https://plato.stanford.edu/entries/counterfactuals/figdesc.html | [
"## Long descriptions for some figures in Counterfactuals\n\n### Figure 2 description\n\nA diagram consisting of eight circles labelled A through H. These are laid out in a five columns by three rows array. A is at in the first column from the left and first row from the top; B is in the same column but in the bottom row; both have arrows pointing to C which is in the second column, middle row; A's arrow is labelled $$C \\dequal A \\land B$$. D is in the third column top row and E in the same column bottom row; C has arrows going to both with the arrow to D labelled $$D \\dequal \\neg C$$ and the arrow to E labelled $$E \\dequal C$$ . F is in the fourth column top row and G in the same column bottom row; an arrow goes fro D to F labelled $$F \\dequal \\neg D$$; an arrow goes from E to G labelled $$G \\dequal E$$. H is in the fifth column middle row; arrows go to it from F and G; the arrow from F to H is labelled $$H \\dequal F \\lor G$$.\n\n### Figure 4 description\n\nThe diagram is a circle outlined in red and split into four parts by a horizontal line and a vertical line. The horizontal line is labelled ‘Antecedent’ with a $$\\phi$$ above and a $$\\neg \\phi$$ below. The vertical line is labelled ‘Consequent’ with a $$\\psi$$ to the left and a $$\\neg\\psi$$ to the right. The center of the circle is labelled $$w_0$$. The upper half of the circle is tinted blue and the upper right quadrant is shaded with a pattern. This upper half is also labelled ‘Constant Domain’. The whole diagram is labeled ‘Accessible Worlds $$R(w_0)$$. Above the diagram is a legend: “Strict Analysis of $$\\phi > \\psi$$: All φ-worlds accessible from $$w_0$$ (indicated in blue in the diagram) are ψ-worlds. I.e., shaded regions must be empty”\n\n### Figure 5 description\n\nThe diagram is three concentric circles outlined in red (so forming two rings, outer and middle, and an innermost circle) and split into four parts by a horizontal line and a vertical line. The horizontal line is labelled ‘Antecedent’ with a $$\\phi$$ above and a $$\\neg \\phi$$ below. The vertical line is labelled ‘Consequent’ with a $$\\psi$$ to the left and a $$\\neg\\psi$$ to the right. The center of the circles is labelled $$w_0$$. The upper half of the circles is tinted blue with the tint with the lightest tint in the outer ring, slightly darker in the middle ring and darkest in the innermost circle; this half is labelled ‘Variable Domain’. The upper right quadrant of the innermost circle is shaded with a pattern. In the middle ring in the upper right quadrant is a dot labelled $$w_1$$. The whole diagram is labelled ‘System of Spheres of Similarity $$\\mathcal{R}(w_0)$$’. Above the diagram is a legend: “ Similarity Analysis of} $$\\phi > \\psi$$ All $$\\phi$$-worlds most similar to $$w_0$$ (indicated in blue in the diagram) are $$\\psi$$-worlds. I.e. shaded region must be empty.\n\n### Figure 6 description\n\nThe diagram is a circle outlined in red and split into four parts by a horizontal line and a vertical line. The horizontal line is labelled ‘Antecedent’ with a $$\\phi_1$$ above and a $$\\neg \\phi_1$$ below. The vertical line is labelled ‘Consequent’ with a $$\\psi$$ to the left and a $$\\neg\\psi$$ to the right. The center of the circle is labelled $$w_0$$. The whole diagram is labeled ‘Accessible Worlds $$R(w_0)$$. The upper half of the circle is tinted blue and the upper right quadrant is shaded with a pattern. So far very similar to Figure 4; the major difference is a yellow circle outlined in black above the center of the first circle and bisected by the vertical line. Most of the yellow circle is inside the first circle, but, a small portion is outside. The yellow circle is labelled $${\\llbracket}\\phi_2{\\rrbracket}^R_v$$\n\n### Figure 7 description\n\nThis figure has two similar diagrams, a and b. Each diagram has three overlapping circles (left, center, right); however, the overlap between left and right is completely within the center circle. In the non-overlapping section of the right circle is a dot labelled w.\n\nFor diagram a the left circle is tinted yellow and labelled $${\\llbracket}\\phi{\\rrbracket}^R_v$$; the center circle is gray and labelled $${\\llbracket}\\psi{\\rrbracket}^R_v$$; the right is blue and labelled $$R(w)$$. The whole is labelled $$\\llbracket\\phi\\strictif\\psi\\rrbracket^R_v$$.\n\nFor diagram b the left circle is tinted red and labelled $${\\llbracket}\\neg\\psi{\\rrbracket}^R_v$$; the center circle is gray and labelled $${\\llbracket}\\neg\\phi{\\rrbracket}^R_v$$; the right is purple and labelled $$R(w)$$. The whole is labelled $$\\llbracket\\neg\\psi\\strictif\\neg\\phi\\rrbracket^R_v$$.\n\n### Figure 8 description\n\nThe diagram is made up of four circles (yellow, orange, blue, gray). The center of the orange circle is a point labelled $$w$$; the circle as a whole is labelled $${\\llbracket}\\phi_1{\\rrbracket}^R_v$$. The yellow circle is to the left and overlaps the orange circle (the overlap includes the $$w$$ point); the yellow circle is labelled $${\\llbracket}\\phi_2{\\rrbracket}^R_v$$. The blue circle is to the right and overlaps the orange circle (the overlap again includes the $$w$$ point); the blue circle is labelled $$R(w)$$. The orange circle is completely within the union of the blue and yellow circles. The gray circle is to the lower right of the orange circle; it includes all of the yellow/blue overlap and orange/blue overlap but not all of the orange/yellow overlap; it is labelled $${\\llbracket}\\psi{\\rrbracket}^R_v$$."
] | [
null
] | {"ft_lang_label":"__label__en","ft_lang_prob":0.8959129,"math_prob":0.9980077,"size":5420,"snap":"2023-14-2023-23","text_gpt3_token_len":1408,"char_repetition_ratio":0.19405465,"word_repetition_ratio":0.2698768,"special_character_ratio":0.25701106,"punctuation_ratio":0.08293153,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.99930894,"pos_list":[0],"im_url_duplicate_count":[null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2023-03-28T15:20:42Z\",\"WARC-Record-ID\":\"<urn:uuid:3a104f69-35a2-407d-9724-6d6aaccdeb35>\",\"Content-Length\":\"17966\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:6e3d3637-22de-4df4-ae43-3cbba920064b>\",\"WARC-Concurrent-To\":\"<urn:uuid:47276e45-0900-45e2-9a46-21ff56f84e37>\",\"WARC-IP-Address\":\"171.67.193.20\",\"WARC-Target-URI\":\"https://plato.stanford.edu/entries/counterfactuals/figdesc.html\",\"WARC-Payload-Digest\":\"sha1:L7JGNRLKBO7PBLBA7FNOTHFRBGS5LVJA\",\"WARC-Block-Digest\":\"sha1:IN6INCJBM2HR5LR6V2TIVAHDUBBGE6BS\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2023/CC-MAIN-2023-14/CC-MAIN-2023-14_segments_1679296948867.32_warc_CC-MAIN-20230328135732-20230328165732-00759.warc.gz\"}"} |
https://instil.ca/maths/math11functions | [
"• Reset\n\n• Settings\n• Shortcuts\n• Fullscreen\n\n# Math: Functions and Relations MCR3U\n\nThis course introduces some financial applications of mathematics, extends students' experiences with functions, and introduces second degree relations. Students will solve problems in personal finance involving applications of sequences and series; investigate properties and applications of trigonometric functions; develop facility in operating with polynomials, rational expressions, and exponential expressions; develop and understanding of inverses and transformations of functions; and develop facility in using function notation and in communicating mathematical reasoning. Students will also investigate loci and the properties and applications of conics. MCR3U has 25% to 30% more content than MCF3M, requiring that the pace be much faster than in MCF3M. MCR3U requires a very high degree of commitment on the part of the student. Prerequisite: Grade 10 Principles of Math MPM2D (Academic)\n\n# Exponent Laws\n\nSpecific Topic General Topic School Date\nExponent Laws Fractions, Negatives, Roots Bayview Nov 2013\nExponent Laws Decimals, Negatives Bayview Nov 2013\n\nxa × xb = xa + b\n\nxa ÷ xb = xa - b\n\n(xa)b = xa × b\n\n## Simplify fully to an integer or fraction using positive exponents, showing your work without using a calculator.\n\n$a^{-n} = \\left( \\cfrac{1}{a^{\\ +n}} \\right) \\quad\\quad or \\quad\\quad \\left( \\cfrac{a}{b} \\right)^{\\!\\!-n} = \\left( \\cfrac{b}{a} \\right)^{\\!\\!+n}$\n\n## Write each with a single positive exponent, or an integer, or a reduced fraction, where applicable. (Without using a calculator)\n\n$\\sqrt[n]{a^m} = (\\sqrt[n]{a})^m = a^{\\frac{m}{n}}$\n\n## Simplify given two of the most basic rules for roots.\n\n\\begin{align} & \\sqrt{a^2} = a \\\\ \\\\ & \\sqrt{ab} = \\sqrt{a} × \\sqrt{b} \\end{align}\n\n# Functions\n\n## Given the general form of a quadratic, determine the equation of a quadratic function with the transformations listed below....\n\n$y = a(x - h)^2 + k$\n\n# Quadratic Functions\n\n## When a soccer ball is kicked the parabolic path of its vertical height, h, in meters is given by the equation below, where the time, t, is in seconds.\n\n$h(t) = -5t^2 + 15t + 0.1$\n\n# Trigonometry\n\n## The following acute triangle, ABC contains the known values (SSA) indicated on the diagram below.",
null,
"## Given the trig equation,\n\n$4\\text{cos}^2\\,\\theta - 4\\text{cos}\\,\\theta + 1 = 0$\n\n# Periodic Trig Functions\n\n## For the graphs of the parent functions of $\\text{sin}\\,\\theta$ and $\\text{cos}\\,\\theta$:",
null,
"## Consider a graph of the parent function between the interval: $0 \\le x \\le 3\\pi$\n\n$y = \\text{cos}\\,\\theta$\n\n## Given the trig function below:\n\nƒ(x) = -4cos 2(θ + $\\pi$) - 4\n\n## Determine the features below given the function:\n\n$P(t) = 4\\sin\\left(x - \\pi\\right) + 10$\n\n## A periodic function expresses the period as a horizontal stretch or compression, with the value k according to the formula:\n\n$k = \\dfrac{2\\pi}{period}$\n\n## The average monthly maximum temperature of a certain city can be modeled by the periodic function below where T(t) is the temperature in ˚Celsius, and t is the time in months, where t = 0 represents January 1, t = 1 represents February 1, etc.\n\n$T(t) = 7\\,\\text{sin}\\dfrac{\\pi}{6}(t - 3) + 25$",
null,
"## A ferris wheel starts rotating from a point at ground level, represented by the equation below where H(t) is height above the ground, in meters, and t is time, in seconds.\n\n$H(t) = -20\\,\\text{cos}\\dfrac{\\pi}{30}(t) + 20$",
null,
"## A ferris wheel spins around a central axis, which is 15m above the ground. The diameter of the ferris wheel is 28m. The wheel spins once around in 1.0 minute. The rotation of the ferris wheel is plotted where function H(t) is the height of the axis above ground, in meters, and t is the time, in minutes.",
null,
"# Exponential Functions\n\n## Solve the following exponential equations, similar to the steps shown in the example given below.\n\n\\begin{align} 3^{3x + 2} & = 243 \\\\ \\\\ 3^{3x + 2} & = 3^5 \\\\ \\\\ 3x + 2 & = 5 \\\\ \\\\ 3x & = 5 - 2 \\\\ \\\\ 3x & = 3 \\\\ \\\\ x & = 1 \\\\ \\\\ \\end{align}\n\n## A strong cup of coffee contains 200mg of caffeine. Caffeine decreases by 50% in the bloodstream every 5 hours.",
null,
"## Given the function for compounding below, where 'i' is initial amount, 'r' is rate of interest, 't' is time, and 'n' is compounding period:\n\n$A = i\\, \\left(1 + \\dfrac{\\left(\\tfrac{r}{100}\\right)}{n}\\right)^{n\\cdot t}$\n\n# Financial Mathematics\n\n### Calculate the monthly payments on a $300,000 mortgage over 25 years at 4% compounded monthly. Solution$ Hint Clear Info Incorrect Attempts: CHECK Hint Unavailable Givens: PV = 300,000 t = 25 years n = 12 i = 0.04 \\begin{align} PV & = \\dfrac{R[1 - (1 + \\tfrac{i}{n})^{-n\\,×\\,t}]}{\\tfrac{i}{n}} \\\\ \\\\ 300,000 & = \\dfrac{R[1 - (1 + \\tfrac{0.04}{12})^{-12\\,×\\,25}]}{\\tfrac{0.04}{12}} \\\\ \\\\ 300,000(\\tfrac{0.04}{12}) & = R[1 - (\\tfrac{301}{300})^{-300}] \\\\ \\\\ R & = \\dfrac{1000}{0.63151} \\\\ \\\\ R & = 1,583.51 \\\\ \\\\ \\end{align} Monthly payments are1,583.51\n\n### If the driver put $3540 down on the car, calculate the original price of the car. Solution Video$ Hint Clear Info Incorrect Attempts: CHECK Hint Unavailable Loans are present value (PV)... PV = Original Price - Down Payment = OP - 3540 \\begin{align} PV & = \\dfrac{R[1 - (1 + \\tfrac{i}{n})^{-n\\,×\\,t}]}{\\tfrac{i}{n}} \\\\ \\\\ OP - 3540 & = \\dfrac{500[1 - (1 + \\tfrac{0.029}{12})^{-12\\,×\\,4}]}{\\tfrac{0.029}{12}} \\\\ \\\\ OP & = \\dfrac{500[1 - (1 + \\tfrac{0.029}{12})^{-12\\,×\\,4}]}{\\tfrac{0.029}{12}} + 3540 \\\\ \\\\ OP & = 22,634.51 + 3540 \\\\ \\\\ OP & = 26,174.51 \\\\ \\\\ \\end{align} The value of the loan was22,634.51 and the original selling price of the car including the down payment was $26,174.51 ### Calculate the interest paid on the loan. Solution Video$ Hint Clear Info Incorrect Attempts: CHECK Hint Unavailable Interest Paid = Sum of Monthly Payments - Present Value of Loan \\begin{align} & = (500/mo)(48\\ mo) - 22,634.51 \\\\ \\\\ & = 24,000 - 22,634.51 \\\\ \\\\ & = 1,365.49 \\\\ \\\\ \\end{align} The interest paid to use the car for 48 months is $1,365.49 (Aside: part of this can be written off on taxes when the car is used only for your business) ##### Mortgage Precision of Different Compound Periods ### A mortgage on a home is$250,000 at 3.5% compounded semiannually, with a 25 year amortization period. Determine the monthly payments. Solution \\$ Hint Clear Info Incorrect Attempts: CHECK Hint Unavailable Mortgages typically have semi-annual compounding, while the payments are monthly. This is an exception that is allowed. First determine the interest rate on a monthly basis (for monthly payments). A 3.5% rate is 1.75% every 6 months. Convert this rate to a monthly rate after 6 months: \\begin{align} 1 + \\tfrac{i}{n} & = (1 + i)^6 \\\\ \\\\ 1 + \\tfrac{0.035}{2} & = (1 + i)^6 \\\\ \\\\ 1.0175 & = (1 + i)^6 \\\\ \\\\ \\sqrt{1.0175} & = \\sqrt{(1 + i)^6 } \\\\ \\\\ \\sqrt{1.0175} & = 1 + i \\\\ \\\\ i & = \\sqrt{1.0175} - 1 \\\\ \\\\ i & = 0.0028956 \\\\ \\\\ \\end{align} n = 12 (monthly), t = 25, Solve for R... We have determined i = 0.0028956 so we use a slightly different equation... \\begin{align} PV & = \\dfrac{R[1 - (1 + i)^{-n\\,×\\,t}]}{i} \\\\ \\\\ PV(i) & = R[1 - (1 + i)^{-n\\,×\\,t}] \\\\ \\\\ R & = \\dfrac{PV(i)}{[1 - (1 + i)^{-n\\,×\\,t}]} \\\\ \\\\ R & = \\dfrac{250,000(0.0028956)}{[1 - (1 + 0.0028956)^{-12\\,×\\,25}]} \\\\ \\\\ R & = \\dfrac{723.906}{[1 - (1.0028956)^{-300}]} \\\\ \\\\ R & = 1,248.18 \\\\ \\\\ \\end{align}",
null,
"Loading and rendering MathJax, please wait...\nPercent complete:\nPRESS START\n★ WORK FOR IT & LEVEL UP\n×\n\n# CLASS PAGE SETTINGS\n\n## Streamlined Question View\n\nShow Videos\nShow Solutions\nShow Level Badges\nSound\n\n## Level of Difficulty\n\n1 2 3 4 5 6 7 8 9 10 11\n×\n\n# KEYBOARD SHORTCUTS\n\n• class settings\n• keyboard shortcuts\n• drawing tools\n• table of contents\n• fullscreen\n• close\n• previous question\n• next question\n2 15 ×\nGoogle"
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http://azrefs.org/equation-will-be-the-lbs-of-food-ordered.html | [
"# Equation will be the lbs of food ordered\n\nYüklə 3.97 Kb.\n tarix 16.04.2016 ölçüsü 3.97 Kb.\n Problem #2: A group of 148 people is spending five days at a summer camp. The cook ordered 12 pounds of food for each adult and 9 pounds of food for each child. A total of 1,410 pounds of food was ordered. What is the total number of adults and total number of children in the group? X + Y = 148 Let X = the number of adults and Y= the number of kids 12X + 9Y = 1,410 The 2nd equation will be the lbs of food ordered -9(X + Y = 148) Multiply by a number to get a negative X or Y 12X + 9Y = 1,410 Line the equation up and Y cancels out -9X + -9Y = -1,332 12X = 1,410 Add the equations -9X = -1,332 3X = 78 Divide 3 from 3 and 78 __ __ 3 3 X = 26 Place the answer in for one of the equations above X(26) + Y = 148 Multiply 26 + Y = 148 Subtract 26 from 26 and 148 Y = 122 Finish writing the equation (26,122) X on the left Y on the right",
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"Verilənlər bazası müəlliflik hüququ ilə müdafiə olunur ©azrefs.org 2016\nrəhbərliyinə müraciət"
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"http://azrefs.org/22435_html_2f09230b.png",
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https://www.studypool.com/discuss/3835191/Time-Value-of-Money | [
"",
null,
"Time Value of Money\n\nUser Generated\n\nbuuuuuu\n\nDescription\n\nAnswer all the questions in the file\n\nUnformatted Attachment Preview\n\n. ST-3 TIME VALUE OF MONEY It is now January 1, 2014; and you will need \\$1,000 on January 1, 2018, in 4 years. Your bank compounds interest at an 8% annual rate. a. How much must you deposit today to have a balance of \\$1,000 on January 1, 2018? b. If you want to make four equal payments on each January 1 from 2015 through 2018 to accumulate the \\$1,000, how large must each payment be? (Note that the payments begin a year from today.) c. If your father offers to make the payments calculated in Part b (\\$221 92) or to give you \\$750 on January 1, 2015 (a year from today), which would you choose? Explain. d. If you have only \\$750 on January 1, 2015, what interest rate, compounded annually for 3 years, must you earn to have \\$1,000 on January 1, 2018? e. Suppose you can deposit only \\$200 each January 1 from 2015 through 2018 (4 years). What interest rate, with annual compounding, must you earn to end up with \\$1,000 on January 1, 2018? f. Your father offers to give you \\$400 on January 1, 2015. You will then make six additional equal payments each 6 months from July 2015 through January 2018. If your bank pays 8% compounded semiannually, how large must each payment be for you to end up with \\$1,000 on January 1, 2018? g. What is the EAR, or EFF%, earned on the bank account in Part f? What is the APR earned on the account? . 5-1 What is an opportunity cost? How is this concept used in TVM analysis, and where is it shown on a time line? Is a single number used in all situations? Explain. . 5-3 If a firm’s earnings per share grew from \\$1 to \\$2 over a 10-year period, the total growth would be 100%, but the annual growth rate would be less than 10%. True or false? Explain. (Hint: If you aren’t sure, plug in some numbers and check it out.) . 5-5 To find the present value of an uneven series of cash flows, you must find the PVs of the individual cash flows and then sum them. Annuity procedures can never be of use, even when some of the cash flows constitute an annuity, because the entire series is not an annuity. True or false? Explain. . 5-7 Banks and other lenders are required to disclose a rate called the APR. What is this rate? Why did Congress require that it be disclosed? Is it the same as the effective annual rate? If you were comparing the costs of loans from different lenders, could you use their APRs to determine the loan with the lowest effective interest rate? Explain.\nPurchase answer to see full attachment",
null,
"User generated content is uploaded by users for the purposes of learning and should be used following Studypool's honor code & terms of service.",
null,
"Hey, kindly check this out and let me know if you need any corrections/questions. I'm working on the other\n\nST-3 TIME VALUE OF MONEY\nAmount\n\n=\\$1000\n\nAnnual interest rate\n\n=8%\n\nPeriod\n\n=4 years\n\na) Find principle\n𝐴 = 𝑃(1 + 𝑟)𝑛\n1000 = 𝑃(1.08)4\n1000\n\n𝑃 = (1.08)4\n= \\$735.03\n\nb)\nAmount\n\n=\\$1000\n\nAnnual interest rate\n\n=8%\n\nPeriod\n\n=4 years\n\nCompounding periods/yr= 4\n\n1000 = 𝑃 (1 +\n\n0.08 4∗4\n)\n4\n\n= \\$728.45\n\nc)\n\nIf my father offered \\$221.92 quarterly, or give me \\$750 on January 1, 2015, I would choose\n\\$221.92 because it would earn more interest.\n\nd)\nPrincipal\nAmount\nYears\nAnnual interest rate =?\n𝐴 = 𝑃(1 + 𝑟)𝑛\n1000 = 750(1 + 𝑟)3\n\n=\\$750\n=\\$1,000\n=3\n\n1000\n= (1 + 𝑟)3\n750\n1.3333=(1 + 𝑟)3\n3\n\n3\n\n√1.3333= √(1 + 𝑟)3\n1.1006 = 1 + 𝑟\nR= 1.1006-1\n=0.1006\n= 10.06%\n\ne)\nprincipal\namount\nyears\nannual interest rate\n\n\\$200\n\\$1,000\n4\n?\n\n𝐴 = 𝑃(1 + 𝑟)𝑛\n1000 = 200(1 + 𝑟)4\n5 = (1 + 𝑟)4\n4\n\n√5 = 1 + 𝑟\n\n1.4953= 1+r\nR=0.4953\n= 49.53%\nf)\n\nFather’s offer\nAnnual interest rate\nAmount\nCompounding periods per year\n𝑟 2𝑛\n\n𝐴 = 𝑃 (1 + 2)\n\n1000 = 𝑝 (1 +\n\n0.08 2∗2.5\n)\n2\n\n1000 = 1.21665𝑃\nP = \\$821.9271\n\n=\\$400\n= 8%\n=\\$1000\n=2\n\ng) EAR= 𝐸𝐹𝐹% = (1 +\n\n𝐼𝑁𝑂𝑀 𝑁\n)\n𝑁\n2\n\n−1\n\n0.08\n) −1\n2\n𝐸𝐹𝐹% = 8.16%\n𝐸𝐹𝐹% = (1 +\n\nINOM=Periodic rate * number of periods per year\n0.08*2= 16%\n\n5-1 Opportunity cost\nOpportunity cost is the rate of interest a person could earn on an alternative investment with a risk\nsame as the risk of investment in question. It is the value of r in the Time Value of Money equations\nwhich is displayed at the top of a time line amid the 1st and 2nd tick marks. A single number is not used in\nall cases as the opportunity cost rate varies depending on the maturity and riskiness of an investment.\n5-3 Annual growt...",
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http://spiriteca.com/trading-withdraw-ldvhx/e38273-excel-best-practices-formulas | [
"Totals as intermediate results. In Excel 2007 and later versions, array formulas can handle whole-column references, but this forces calculation for all the cells in the column, including empty cells. The 8th best practice in Excel is to split up calculations into multiple smaller calculations. Excel VBA development best practices [closed] Ask Question Asked 10 years, 8 months ago. For more information, see Use faster VBA user-defined functions. This might not appear to reduce the number of calculations for a single array formula; however, most of the time it enables the smart recalculation process to recalculate only the formulas in the helper column that need to be recalculated. Applies to: Excel | Excel 2013 | Office 2016 | VBA. To look up the table to use in addition to the row and the column, you can use the following techniques, focusing on how to make Excel look up or choose the table. To help you get the most out of Excel, we’ve put together a batch of the best Excel tips for beginners. Keep Formulas Readable. Application.DisplayStatusBar Turn off the status bar. It is generally faster than an exact match lookup. This is because there is a small overhead for each user-defined function call and significant overhead transferring information from Excel to the user-defined function. If there's no way to make it fast, make use of the manual calculation: -- Set calculation to manual as mentioned above. Most Excel users have difficulty understanding their own Excel formulas if it has not been looked at for a few months. Try to use simple direct cell references that work on closed workbooks. Avoid constants in formulas. 2-F9 A large collection of useful Excel formulas, beginner to advanced, with detailed explanations. Calendars, invoices, trackers and much more. @K Mac We’re amazed every day by the ways in which you, our customers, use Excel to make better decisions, leveraging the flexibility of the 2D grid and formulas to capture, analyze and collaborate on data. Up to this point, Excel has only had a … It's all here. Note: You can use Excel lists in 2003 version, which are similar to tables. In the text box, type %temp%, and then click OK. Tracking changes in a shared workbook causes your workbook file-size to increase rapidly. Thank you so much for this Jan. Excel will add the { and } to show you that this is an array formula). These formulas are re-calculated whenever there is a change in the workbook. Harnessing the power of functions 67. File size is almost the same as earlier versions (some additional information may be stored), and performance is slightly slower than earlier versions. I've written complex formulas in Excel for staff in other departments on the regular for years, but again my employer is a non profit in the SMB size category. note: When typing the syntax of a formula, Ctrl + A shows the function arguments. If your user-defined function is called early in the calculation chain, it can be passed as uncalculated arguments. Optimize your code by explicitly reducing the number of times data is transferred between Excel and your code. The beginning cell of the SUM is anchored in A1, but because the finishing cell has a relative row reference, it automatically increases for each row. Viewed 2k times 10. Unused cells are not examined, so whole column references are relatively efficient, but it is better to ensure that you do not include more used cells than you need. PivotTables are a great way to produce summary reports, but try to avoid creating formulas that use PivotTable results as intermediate totals and subtotals in your calculation chain unless you can ensure the following conditions: The PivotTable has been refreshed correctly during the calculation. Alot of my workbooks are distributed to people who have an old version of excel and do not need to see the workings - because of this I have written a very simple piece of code that loops through all of the calculation worksheets, and pastes as values - which resolves any compatibility issues (using formulas that arent supported in 03, and has a dramatic improvement in reopening time). -- Put the formula in the first data row, and make sure it's working before copying it to the rest of the cells in the column. that's all! If you cannot use two cells, use COUNTIF. Using the INDEX formula for a dynamic range is generally preferable to the OFFSET formula because OFFSET has the disadvantage of being a volatile function that will be calculated at every recalculation. Excel spreadsheet formulas usually work with numeric data; you can take advantage of data validation to specify the type of data that should be accepted by a cell i.e. This causes 7 calls to the UDF on each recalc. Try to move the circular calculations onto a single worksheet or optimize the worksheet calculation sequence to avoid unnecessary calculations. 3. Keep formulas in a separate sheet. However, it is slightly more flexible in that the range to sum may have, for example, multiple columns when the conditions have only one column. Avoid formulas that contain references to multiple worksheets. As follows: 1. Be sure that your Windows swap file is located on a disk that has a lot of space and that you defragment the disk periodically. However, the computer that is running Excel also requires memory resources. Starting in Excel 2007, you can use structured table references, which automatically expand and contract as the size of the referenced table increases or decreases. These reports fail for at least one of three reasons: bad strategy, bad structure, or bad technique. We outline the salary, skills, personality, and training you need for FP&A jobs and a successful finance career. One of the reasons for sluggish performance is that you are searching for something in a lot of un-sorted data. All free, fun and fantastic. TyPe oF FunCTion Common use FoRmulA To insert a function in a cell, use either Alt m F or shift + F3 (\"Function Wizard\"). To look up several contiguous columns, you can use the INDEX function in an array formula to return multiple columns at once (use 0 as the column number). If you put a formula in a cell of an empty table column, it will automatically fill and calculate even if you have manual calculation set. We recommend that you use the Microsoft Internet Information Services (IIS) setting to set the … It is important to reduce the number of cells in the circular calculation and the calculation time that is taken by these cells. The following code examples compare the two methods. CHAPTER 4. Use the first result second time too. I've started to use Names to do something similar, but changing arguments is the rub. If Excel stops responding for any reason, you might need to delete these files. Most Excel reports, forecasts, and analyses I’ve seen in my career could serve as excellent examples of what NOT to do in Excel. For example, instead of using OFFSET to construct a dynamic range, you can use INDEX. Many times we inherit un-sorted data thru data imports. Important: The calculated results of formulas and some Excel worksheet functions may differ slightly between a Windows PC using x86 or x86-64 architecture and a Windows RT PC using ARM architecture. Add an extra column for the MATCH to store the result (stored_row), and for each result column use the following: Alternatively, you can use VLOOKUP in an array formula. This page will direct you to all of our best content. As an example, if you have table called cs, then the formula sum(cs[column_name]) refers to sum of all values in the column_name of table cs. Starting in Excel 2007, you should use SUMIFS, COUNTIFS, and AVERAGEIFS functions instead of the DFunctions. 09/25/2017; 4 minutes to read; s; V; O; d; In this article. This article is the cheat sheet of formulas available in Microsoft Excel. With 1 million rows available starting in Excel 2007, an array formula that references a whole column is extremely slow to calculate. Learning Center Excel Tutorials and Practice Tests Welcome to Automate Excel! i hope that this tip would help. excel take time to calculate, when there are offsheet references (majorly used in sumif, sumproduct, index, match). These cells do not contain formulas. CONCATENATE. In large worksheets, you may frequently need to look up by using multiple indexes, such as looking up product volumes in a country. You can often reuse a stored exact MATCH many times. Other performance characteristics of Visual Basic 6 user-defined functions in Automation add-ins are similar to VBA functions. Well you are at the right place. But well-designed and called user-defined functions can be much faster than complex array formulas. This article covered ways to optimize Excel functionality such as links, lookups, formulas, functions, and VBA code to avoid common obstructions and improve performance. This method also avoids the problem of changed names in precedent workbooks. Mastering Excel formulas 1 CHAPTER 1. Essay on Excel Best Practices for Business The container for Excel spreadsheets — the grid where numbers, text, and formulas reside and calculations are performed — is a file called a workbook with If the lookup array is not sorted ascending, MATCH will return an incorrect answer. Forward referencing usually does not affect calculation performance, except in extreme cases for the first calculation of a workbook, where it might take longer to establish a sensible calculation sequence if there are many formulas that need to have their calculation deferred. (Array formulas must be entered by using Ctrl+-Shift+Enter. Built-in formulas tend to better than your own version – for example SUMIFS is easier to write and just as fast as SUMPRODUCT. vValue(lRow, lCol) = 2 * vValue(lRow, lCol) (any single character) and * (no character or any number of characters) in the criteria for alphabetical ranges as part of the SUMIF, COUNTIF, SUMIFS, COUNTIFS, and other IFS functions. Introduction to Excel Tables – what are they and how to use them? End Function, Name: test The following functionality can usually be turned off while your VBA macro executes: Application.ScreenUpdating Turn off screen updating. That said, for earlier Excel versions, Lookups continue to be frequently significant calculation obstructions. Forecast function available in excel is the simplest ever forecasting function that we could have. For example, create a defined name using one of the following formulas: When you use the dynamic range name in a formula, it automatically expands to include new entries. For #5. lookup data, compare results, calculations, etc. Pivot tables are an excellent way to calculate a lot of summary values with few clicks. Function name. Check the size of your toolbar file. These functions evaluate each of the conditions from left to right in turn. Excel Training Templates and Practice Workbooks. Function DemoFunction(r As Range) One of the reasons for sluggish performance is that you are searching for something … The calculation engine in Excel is optimized to exploit array formulas and functions that reference ranges. There are two methods of doing period-to-date or cumulative SUMs. We have free excel practice tests where you can sharpen your skill. Back on track… Investment bankers, including younger managing directors as most new MDs cut their teeth during a time when Excel best practices were already firmly enshrined, are very serious about Excel skills. But whether it be a project at work or just a personal budget, you need to know basic Excel to get things done right and done quickly. Use these tips & ideas to super-charge your sluggish workbook. For example, in cash flow and interest calculations, try to calculate the cash flow before interest, calculate the interest, and then calculate the cash flow including the interest. Forecast in Excel. If you need to produce totals and subtotals as part of the final results of your workbook, try using PivotTables. Building basic formulas 3. You know the functions and formulas but need to practive your Excel skills?Or do you need Excel Practice Tests online? Lookup time using the approximate match options of VLOOKUP, HLOOKUP, and MATCH on sorted data is fast and is not significantly increased by the length of the range you are looking up. Using many dynamic ranges can decrease performance. It is often more efficient to calculate a subset range for the lookup (for example, by finding the first and last row for the country, and then looking up the product within that subset range). However, OFFSET is a fast function and can often be used in creative ways that give fast calculation. using formulas – KPI Dashboard example, Image Lookup – How-to show dynamic picture in a cell [Excel Trick], 9 Box grid for talent mapping – HR for Excel – Template & Explanation, 6 Must Know Line Chart variations for Data Analysis, Excel formula to convert calendar format to table, Project Plan – Gantt Chart with drill-down capability [Templates], These Pivot Table tricks massively save your time, » Calculation Effeciency: Array Formulas Spreadsheet Budget and Consulting, http://professor-excel.com/performance-excel-study/. Sort your data. And since tables grow & shrink as you add / remove data, none of your formulas need to be dynamic. Make better worksheets and impress everyone (including your … Quite surprising: Some things have a great effect as switching the language to English (if you got Excel in German region setting, -81% of calcultion time) or avoiding SUMIFS as lookups (-53%). In your very 1st tip you state that \"And since tables grow & shrink as you add / remove data, none of your formulas need to be dynamic.\" Solution? Matchtype=0 requests an exact match and assumes that the data is not sorted. Go ahead and spend few minutes to be AWESOME. Using names that refer to other worksheets adds an additional level of complexity to the calculation process. For more information, see the \"Large data sets and the 64-bit version of Excel\" section in Excel performance: Performance and limit improvements. Although VLOOKUP is slightly faster (approximately 5 percent faster), simpler, and uses less memory than a combination of MATCH and INDEX, or OFFSET, the additional flexibility that MATCH and INDEX offer often enables you to significantly save time. If you switch the calculation mode to manual, you can wait until all the cells associated with the formula are updated before recalculating the workbook. One of the reasons for slow workbooks is lot of data. Great article on INDEX in Excel Hero (never seen so many responses in any forum as that one!) You can avoid the double exact lookup if you use exact MATCH once, store the result in a cell, and then test the result before doing an INDEX. ... Also, as you mentioned VLOOKUP: the most time consuming part of a VLOOKUP formula is the looking up - returning the relevant value is normally relatively quick once Excel has determined the location of that value. If you have a complex calculation that depends on cells in the circular reference, it can be faster to isolate this into a separate closed workbook and open it for recalculation after the circular calculation has converged. Caution it could be fatal as the model could change. -- Use a countif to see if you'll get a match at all in a lookup table, and only do the big, complicated multi-criteria array-formula index lookup for the records that have at least a basic match. Here are a few whacky ideas that I try in such cases: Optimization is not a one-shot exercise. [...] had some posts on speeding up Excel worksheets, one of the posts focuses on formulas and another he let the general readers make their suggestions. Data for Excel formula list in this guide. Most formula examples shown here are self-explanatory. The PivotTable has not been changed so that the information is still visible. You should have only one formula per row, meaning that whatever formula is used in the first cell of any given row should be the same formula uniformly applied across the entire row. Each user has a unique XLB file. 4. This guide gives you the answer. You can minimize this performance decrease by storing the COUNTA part of the formula in a separate cell or defined name, and then referring to the cell or name in the dynamic range: You can also use functions such as INDIRECT to construct dynamic ranges, but INDIRECT is volatile and always calculates single-threaded. The XLS format is the same format as earlier versions. Please see Office VBA support and feedback for guidance about the ways you can receive support and provide feedback. By doing this, you can avoid recalculating all your linked workbooks when you recalculate any workbook. Formulas!:!Functions!! \" Example: Customer Service Dashboard – Data & Calculations, Examples, Details & Downloads on Excel Pivot Tables, Remove duplicates & sort a list using Pivot Tables, Sorting numbers etc. Get ready to be initiated into the inner circles of Excel Ninjadom today I’m talking about array formulas also known as Crt Shift Enter formulas (CSE formula for short). Excel Nested IF statement: examples, best practices and alternatives. Enter =NOT() where is the Integrity Check’s Passed cell’s address for this alert. 1. Note that the size and shape of the ranges or arrays that are used in the conditional expressions and range to sum must be the same, and they cannot contain entire columns. This week, Speed up your Spreadsheets – Your Action Required, Speeding up & Optimizing Excel – Tips for Charting & Formatting [Speedy Spreadsheet Week]. So how do you optimize & speed-up your Excel formulas? The 64-bit version of Excel does not have a 2 GB or up to 4 GB limit. The \"imposing index\" article you mention is a must read, it truly will revolutionise the way you use excel. Create a backup copy first. I am working on a P&L constructed in a form of pivot table with a # of calculated items. Dynamic ranges have the following advantages and disadvantages: Dynamic ranges work well to limit the number of calculations performed by array formulas. Of INDIRECT SUMIFS is easier to write and just as fast as SUMPRODUCT do! Off sheet cell references in excel best practices formulas circular references by using IFERROR, or more web service input values d! Caution it could be fatal as the model could change the model could change, as it! Down calculation and training you need just a few months Comments are posted via e-mail decision-making tool evaluate. 09/25/2017 ; 4 minutes to be dynamic, cash flow projections and more pivots in one go to your... 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To learn more has options for ignoring hidden or filtered rows. ) repeated for each data row & forensics... The PivotTable has not been looked at for a needle in a hay-stack multiple smaller calculations Excel... Calculates, it tends to be frequently significant calculation obstructions by these cells article learn. Or False instead of using OFFSET to construct Excel formulas =test into B1: B7 one! Welcome to Automate Excel COUNTA function inside the SUMPRODUCT function are powerful but! Memory and reduce file size, Excel does not redraw the screen 1 ''!...! advanced! Excel the Microsoft Internet information Services ( IIS ) setting to set the … formulas! & Power BI automatically recognize the last-used row in the following example uses the INDIRECT function and to. Formatting messes up the functionality of a formula in a spreadsheet the Windows start menu click! To read the links in fact you learn by doing experts ” can learn new formulas, time! 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Will find the best free Excel practice Tests where you can pre-calculate a lower-range limit and upper-range limit the... In thinking thru various calculations and planning the formulas formulas but need to practive your Excel skills level... ( renaming it `` toolbar.OLD '' is safer ) data is transferred between Excel and your code,! 10-20 rows. ), by using concatenated lookup values on save set excel best practices formulas..., covers most of my formulas are re-calculated whenever there is a calculation-intensive operation 65,536 rows )... And their dependents strings is a fast function and TableLookup_Value to choose range! End you said `` please note that excel best practices formulas runs a compatibility check works smoothly you... Things manually this sounds interesting, but you must handle them carefully use two lookups range... Majorly used in formulas with structural references, can be much faster ways of the! T you many ways of improving lookup calculation time many binary files everything one ask! Of whole column references inefficiently remove any named ranges that result in error or missing links and columns than need... Restrict the range that you can also return many cells from one section to another may only be a of..."
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https://math.stackexchange.com/questions/2943851/finding-the-complex-square-roots-of-a-complex-number-without-a-calculator/2943857 | [
"# Finding the complex square roots of a complex number without a calculator\n\nThe complex number $$z$$ is given by $$z = -1 + (4 \\sqrt{3})i$$\n\nThe question asks you to find the two complex roots of this number in the form $$z = a + bi$$ where $$a$$ and $$b$$ are real and exact without using a calculator.\n\nSo far I have attempted to use the pattern $$z = (a+bi)^2$$, and the subsequent expansion $$z = a^2 + 2abi - b^2$$. Equating $$a^2 - b^2 = -1$$, and $$2abi = (4\\sqrt{3})i$$, but have not been able to find $$a$$ and $$b$$ through simultaneous equations.\n\nHow can I find $$a$$ and $$b$$ without a calculator?\n\n• You could notice that $u=a^2$ and $v=-b^2$ satisfy $\\begin{cases}u+v=-1\\\\ uv=-12\\\\ u\\ge 0\\\\ v\\le0\\end{cases}$. – Saucy O'Path Oct 5 '18 at 22:41\n• Why is $uv=-12?$ – user376343 Oct 5 '18 at 22:53\n\nThe second equation can be written $$ab=2\\sqrt{3}$$ which gives $$b = \\frac{2\\sqrt{3}}{a}$$. If we substitute back into the first equation we get $$a^2 - \\frac{12}{a^2} = -1$$. Multiplying both sides by $$a^2$$ gives $$a^4 - 12 = - a^2$$. This can be written as $$a^4 + a^2 - 12 = 0$$ which is a quadratic equation solvable for $$a^2$$.\n\n• Thanks, I managed to get up to $a^4 + a^2 - 12 = 0$ on my own before asking this question, but couldn't figure out how to solve for $a$ without a calculator. Using your suggestion I found $(a^2 + 4)(a^2 - 3) = 0$ therefore $a = 2i \\text{ and } \\pm \\sqrt{3}$, thanks for the help. – Pegladon Oct 5 '18 at 22:56\n• I'm glad that I could help. Don't forget the plus/minus $a=\\pm 2i$ and checking your final answer(s). – sfmiller940 Oct 5 '18 at 23:23\n• @Pegladon, in this method $a,b$ are considered reals. Moreover, any non-zero complex number has exactly two square roots. Thus $\\pm 2i$ are not convenient for $a.$ – user376343 Oct 6 '18 at 7:49\n\nObserve that $$\\|z\\| = \\sqrt{(-1)^2+(4\\sqrt3)^2} = \\sqrt{49} = 7$$. Therefore the root of $$z$$ will have length $$\\sqrt 7$$, so $$a^2+b^2=7$$. Combine this with $$a^2-b^2=-1$$ to get $$a$$ and $$b$$.\n\nOne way is to write $$z=r^2 e^{2\\theta}$$ and roots will be $$re^\\theta$$ and $$re^{\\pi -\\theta}$$.\n\nFrom $$z =-1+4\\sqrt{3}i$$, we obtain $$r=7$$ and $$\\tan{2\\theta} = \\frac{2\\tan\\theta}{1-\\tan^2\\theta} = -4\\sqrt{3}$$. Second expression gives you a quadratic equation, $$2\\sqrt{3}\\tan^2\\theta -2\\sqrt{3} + \\tan\\theta =0$$.\n\nRoots of the above quadratic equation are $$\\tan\\theta= \\sqrt{3}/2,-2/\\sqrt{3}$$ which form $$\\tan\\theta$$ and $$\\tan(\\pi-\\theta)$$.\n\nHence, square roots of $$z$$ are $$(1+\\sqrt{3}/2i)\\frac{7}{\\sqrt{1+3/4}} = \\sqrt{7}(2+\\sqrt{3}i)$$ and $$(1-2/\\sqrt{3}i)\\frac{7}{\\sqrt{1+4/3}} = \\sqrt{7}(\\sqrt{3}-2i)$$.\n\nThat the square roots are $$\\pm(\\sqrt 3 + 2i)$$ can be seen by elementary algebra and trigonometry as follows. \\begin{align} & \\left|-1 + i4\\sqrt 3\\right| = \\sqrt{(-1)^2 + (4\\sqrt 3)^2 } = 7. \\\\[10pt] \\text{Therefore } & -1+i4\\sqrt 3 = 7(\\cos\\varphi + i\\sin\\varphi). \\\\[10pt] \\text{Therefore } & \\pm\\sqrt{-1+i4\\sqrt 3} = \\pm\\sqrt 7 \\left( \\cos \\frac \\varphi 2 + i \\sin\\frac\\varphi 2 \\right). \\end{align}\n\nNotice that $$\\sin \\varphi = \\frac{4\\sqrt 3} 7 \\quad \\text{and} \\quad \\cos\\varphi = \\frac{-1} 7$$ and recall that \\begin{align} \\tan\\frac\\varphi 2 & = \\frac{\\sin\\varphi}{1+\\cos\\varphi} \\\\[12pt] \\text{so we have }\\tan\\frac\\varphi 2 & = \\frac{4\\sqrt 3}{7-1} = \\frac 2 {\\sqrt 3}. \\\\[10pt] \\text{Therefore } \\sin\\frac\\varphi2 & = \\frac 2 {\\sqrt 7} \\quad \\text{and} \\quad \\cos\\frac\\varphi2 = \\frac{\\sqrt3}{\\sqrt7}. \\end{align} Thus the desired square roots are $$\\pm \\left( \\sqrt 3 + 2i \\right).$$\n\nNote that$$z=7\\left(-\\frac17+\\frac{4\\sqrt3}7i\\right).\\tag1$$Now, since $$\\left(-\\frac17\\right)^2+\\left(\\frac{4\\sqrt3}7\\right)^2=1$$, the expression $$(1)$$ expresses $$z$$ as $$7\\bigl(\\cos(\\alpha)+\\sin(\\alpha)i\\bigr)$$, for some $$\\alpha$$. So, a square root of $$z$$ is $$\\sqrt7\\left(\\cos\\left(\\frac\\alpha2\\right)+\\sin\\left(\\frac\\alpha2\\right)i\\right)$$. Now, note that if $$c=\\cos\\left(\\frac\\alpha2\\right)$$ and $$s=\\sin\\left(\\frac\\alpha2\\right)$$, then $$c^2+s^2=1$$ and $$c^2-s^2=\\cos(\\alpha)=-\\frac17$$. This allows you to compute the square roots of $$z$$.\n\nLet$$z^2=(x+yi)^2=−1+4\\sqrt3i,$$ i.e.$$(x^2-y^2)+2xyi=−1+4\\sqrt3i.$$ Compare real parts and imaginary parts, $$\\begin{cases} x^2 - y^2 = -1&\\qquad\\qquad(1)\\\\ 2xy = 4\\sqrt3&\\qquad\\qquad(2) \\end{cases}$$ Now, consider the modulus: $$|z|^2 =|z^2|$$, then $$x^2 + y^2 = \\sqrt{\\smash[b]{(-1)^2+(4\\sqrt3)^2}} = 7\\tag3$$ Solving $$(1)$$ and $$(3)$$, we get $$x^2 = 3\\Rightarrow x = \\pm\\sqrt3$$ and $$y^2 = 4\\Rightarrow y = \\pm2$$.\n\nFrom $$(2)$$, $$x$$ and $$y$$ are of same sign, $$\\begin{cases} x = \\sqrt3\\\\ y = 2 \\end{cases}\\text{ or } \\begin{cases} x = -\\sqrt3\\\\ y = -2 \\end{cases}$$ then$$z = \\pm(\\sqrt3 + 2i).$$\n\n• Welcome to MSE. Please see this typesetting reference to learn how to display mathematical expressions. – Théophile Oct 5 '18 at 22:51"
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https://scholars.ncu.edu.tw/zh/publications/finite-size-corrections-and-scaling-for-the-dimer-model-on-the-ch | [
"# Finite-size corrections and scaling for the dimer model on the checkerboard lattice\n\nNickolay Sh Izmailian, Ming Chya Wu, Chin Kun Hu\n\n6 引文 斯高帕斯(Scopus)\n\n## 摘要\n\nLattice models are useful for understanding behaviors of interacting complex many-body systems. The lattice dimer model has been proposed to study the adsorption of diatomic molecules on a substrate. Here we analyze the partition function of the dimer model on a 2M×2N checkerboard lattice wrapped on a torus and derive the exact asymptotic expansion of the logarithm of the partition function. We find that the internal energy at the critical point is equal to zero. We also derive the exact finite-size corrections for the free energy, the internal energy, and the specific heat. Using the exact partition function and finite-size corrections for the dimer model on a finite checkerboard lattice, we obtain finite-size scaling functions for the free energy, the internal energy, and the specific heat of the dimer model. We investigate the properties of the specific heat near the critical point and find that the specific-heat pseudocritical point coincides with the critical point of the thermodynamic limit, which means that the specific-heat shift exponent λ is equal to. We have also considered the limit N→' for which we obtain the expansion of the free energy for the dimer model on the infinitely long cylinder. From a finite-size analysis we have found that two conformal field theories with the central charges c=1 for the height function description and c=-2 for the construction using a mapping of spanning trees can be used to describe the dimer model on the checkerboard lattice.\n\n原文 ???core.languages.en_GB??? 052141 Physical Review E - Statistical, Nonlinear, and Soft Matter Physics 94 5 https://doi.org/10.1103/PhysRevE.94.052141 已出版 - 23 11月 2016"
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https://puzzling.stackexchange.com/questions/50113/turn-lead-into-gold/50115 | [
"Can you turn the word LEAD into GOLD in five steps or less? You can change or replace one letter at a time only. The newly formed word must be a legit word in a recognized dictionary. Of course you cannot add or subtract letters, so all new words must have 4 letters. I am sure there are several solutions here.\n\nThree steps/Four words:\n\n• WOW great. Didnt know GOAD as a word. – DrD Mar 18 '17 at 16:04\n• I only remembered it because of a word play ladder I created a little bit ago haha – n_plum Mar 18 '17 at 16:04\n• This is actually the optimal solution: it's impossible to do better. – Rand al'Thor Mar 18 '17 at 16:08\n• I verified that this is the unique optimal solution - there's nothing else with three steps (in my word list) – isaacg Mar 20 '17 at 6:43\n• Five steps:\n\nLEAD $\\rightarrow$ LEND $\\rightarrow$ FEND $\\rightarrow$ FOND $\\rightarrow$ FOLD $\\rightarrow$ GOLD\n\n• Four steps:\n\nLEAD $\\rightarrow$ READ $\\rightarrow$ ROAD $\\rightarrow$ GOAD $\\rightarrow$ GOLD\n\n• @n_palum's solution in three steps:\n\nLEAD $\\rightarrow$ LOAD $\\rightarrow$ GOAD $\\rightarrow$ GOLD\n\nThis is optimal because\n\nthree letters are different between LEAD and GOLD, and we can only change one letter at a time, so we need at least three steps.\n\n• Damn, I had that exact three steps solution in less than one minute from reading the question, but I'm 21 to 22 hours late >_> – Zachiel Mar 19 '17 at 13:28\n\nHere's one in four steps:"
] | [
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https://noncommutativeanalysis.com/2012/10/11/william-arveson/?replytocom=494 | [
"William Arveson\n\nWilliam B. Arveson was born in 1934 and died last year on November 15, 2011. He was my mathematical hero; his written mathematics has influenced me more than anybody else’s. Of course, he has been much more than just my hero, his work has had deep and wide influence on the entire operator theory and operator algebras communities. Let me quickly give an example that everyone can appreciate: Arveson proved what may be considered as the “Hahn-Banach Theorem” appropriate for operator algebras. He did much more than that, and I will expand below on some of his early contributions, but I want to say something before that on what he was to me.\n\nWhen I was a PhD student I worked in noncommutative dynamics. Briefly, this is the study of actions of (one-parameter) semigroups of *-endomorphisms on von Neumann algebras (in short E-semigroups). The definitive book on this subject is Arveson’s monograph “Noncommutative Dynamics and E-Semigroups”. So, naturally, I would carry this book around with me, and I would read it forwards and backwards. The wonderful thing about this book was that it made me feel as if all my dreams have come true! I mean my dreams about mathematics: as a graduate student you dream of working on something grand, something important, something beautiful, something elegant, brilliant and deep. You want your problem to be a focal point where different ideas, different fields, different techniques, in short, all things, meet.\n\nWhen reading Arveson there was no doubt in my heart that, e.g., the problem classifying E-semigroups of type I was a grand problem. And I was blown away by the fact that the solution was so beautiful. He introduced product systems with such elegance and completeness that one would think that this subject has been studied for the last 50 years. These product systems were measurable bundles of operator spaces – which turn out to be Hilbert spaces! – that have a group like structure with respect to tensor multiplication. And they turn out to be complete invariants of E-semigroups on",
null,
"$B(H)$. The theory set down used ideas and techniques from Hilbert space theory, operator space theory, C*-algebras, group representation theory, measure theory, functional equations, and many new ideas – what more could you ask for? Well, you could ask that the new theory also contribute to the solution of the original problem.\n\nIt turned out that the introduction of product systems immensely advanced the understanding of E-semigroups, and in particular it led to the full classification of type I ones.\n\nSo Arveson became my hero because he has made my dreams come true. And more than once: when reading another book by him, or one of his great papers, I always had a very strong feeling: this is what I want to do. And when I felt that I gave a certain problem all I thought I had in me, and decided to move on to a new problem, it happened that he was waiting for me there too.\n\nI wish to bring here below a little piece that I wrote after he passed away, which explains from my point of view what was one of his greatest ideas.\n\nFor a (by far) more authoritative and complete review of Arveson’s contributions, see the two recent surveys by Davidson (link) and Izumi (link).\n\nSubalgebras of C*-algebras I and II\n\nArveson was one of the first to realize the importance of non-selfadjoint operator algebras as well as the role of operator spaces, and he developed a theory which had both immediate applications (to problems operator theory, including “single operator theory”), as well as long term, far reaching implications. In his paper [“Analyticity in Operator Algebras”, Amer. J. Math. 89, 1967] he wrote:\n\nIn the study of families of operators on Hilbert space, the self-adjoint algebras have occupied a preeminent position.\n\nBy “self-adjoint” he means, of course, C*-algebras and von Neumann algebras. He continues:\n\nNevertheless, many problems in operator theory lead obstinately toward questions about algebras that are not necessarily self-adjoint. Indeed, the general theory of a single operator on a finite-dimensional space rests on an analysis of the polynomials in that operator, and has nothing at all to do with the *-operation.\n\nArveson’s great insight was that if C*-algebras are a non-commutative analogue of algebras of continuous functions, then the theory of non-selfadjoint algebras should be considered as a non-commutative version of the theory of of function algebras. His vision was expounded in two ground breaking papers ([“Subalgebras of C*-algebras”, Acta Math. 123, 1969], and [“Subalgebras of C*-algebras II”, Acta Math. 128, 1972]), where he laid the foundations to the theory of (not necessarily self-adjoint) operator algebras and of operator spaces.\n\nIt was probably in these papers where the notions of complete positivity, complete boundedness and complete isometry were first shown to play such a fundamental role in operator theory.\n\nDigression: You may wonder: “what is complete this and complete that“. Let me briefly explain what is a complete isometry, and the rest will be clear. An operator algebra",
null,
"$A$ is just a subalgebra of",
null,
"$B(H)$, and it inherits the operator norm from",
null,
"$B(H)$. A linear map",
null,
"$\\phi : A \\rightarrow B$ (where",
null,
"$B$ is another operator algebra) is said to be an isometry if",
null,
"$\\|\\phi(a)\\| = \\|a\\|$ for all",
null,
"$a \\in A$. This is a very familiar notion, the existence of such a",
null,
"$\\phi$ means that",
null,
"$A$ and",
null,
"$B$ have the same Banach space structure. It turns out that the Banach space structure of an operator algebra is far from determining its other properties. Arveson somehow understood that the complete version of isometry is what one is required to look at. Here is what this means.\n\nOne can form the algebra",
null,
"$M_n(A)$ of",
null,
"$n \\times n$ matrices over",
null,
"$A$. This is a subalgebra of",
null,
"$M_n(B(H)) = B(\\underbrace{H \\oplus H \\oplus \\cdots \\oplus H}_{n \\textrm{ times}})$,\n\nso it is again an operator algebra. If",
null,
"$\\phi : A \\rightarrow B$ is a linear map, we define",
null,
"$\\phi_n : M_n(A) \\rightarrow M_n(B)$ by letting",
null,
"$\\phi$ act entrywise, that is, if",
null,
"$[a_{ij}] \\in M_n(A)$ then",
null,
"$\\phi_n ([a_{ij}])$ is the matrix",
null,
"$[\\phi(a_{ij})]$. Finally, the map",
null,
"$\\phi$ is said to be a complete isometry if",
null,
"$\\phi_n$ is an isometry for all",
null,
"$n$. The same notions can be defined when",
null,
"$A$ and",
null,
"$B$ are operator spaces, that is, simply subpaces of",
null,
"$B(H)$End of digression.\n\nThe main issue confronted in the two “Subalgebras” papers mentioned above is this: given an algebra",
null,
"$A$ of operators on a Hilbert space, one can form the C*-algebra",
null,
"$C^*(A)$ which it generates. However, if",
null,
"$\\tilde{A}$ is a completely isometrically isomorphic (i.e., indistinguishable) copy of",
null,
"$A$, it might be the case that",
null,
"$C^*(\\tilde{A})$ is different than",
null,
"$C^*(A)$. What is the precise relationship between an operator algebra and the C*-algebra that it generates? What is the “correct” C*-algebra in which one should study",
null,
"$A$? How can one study operator algebras abstractly?\n\nArveson’s approach was the following: if",
null,
"$I$ is an ideal in",
null,
"$C^*(A)$ such that the quotient map",
null,
"$C^*(A) \\rightarrow C^*(A)/I$ is completely isometric when restricted to",
null,
"$A$, then the quotient",
null,
"$C^*(A)/I$ is another C*-algebra that contains",
null,
"$A$ completely isometrically isomorphically, and this C*-algebra is better than",
null,
"$C^*(A)$ because it is smaller. Such an ideal",
null,
"$I$ is said to be a boundary ideal. Now suppose that there exists an ideal",
null,
"$J$ which is the largest boundary ideal —",
null,
"$J$ is said to be the Shilov boundary ideal and in the commutative case (when",
null,
"$A$ is a function algebra) it is precisely the ideal of functions which vanish on the Shilov boundary of",
null,
"$A$. Then",
null,
"$C^*(A)/J$ is the smallest such quotient that can be formed. Arveson proved that",
null,
"$C^*(A)/J$ is a canonical invariant of",
null,
"$A$ and that it is in fact the smallest C*-algebra that contains",
null,
"$A$ completely isometrically isomorphically. This canonical C*-algebra later became to be known as the C*-envelope of",
null,
"$A$.\n\nTo be precise, it was shown that if",
null,
"$J$ is the Shilov boundary ideal for",
null,
"$A$ in",
null,
"$C^*(A)$, and if",
null,
"$\\tilde{J}$ is the Shilov boundary ideal for",
null,
"$\\tilde{A}$ in",
null,
"$C^*(\\tilde{A})$, and if",
null,
"$\\phi : A \\rightarrow \\tilde{A}$ is a complete isometry, then",
null,
"$\\phi$ extends to a *-isomorphism between",
null,
"$C^*(A)/I$ and",
null,
"$C^*(\\tilde{A})/J$.\n\nAs a beautiful and very simple example of the kind of result that flowed from this theory let me bring the following:\n\nTheorem: Let",
null,
"$A$ and",
null,
"$B$ be two irreducible compact operators on",
null,
"$H$. Then",
null,
"$A$ and",
null,
"$B$ are unitarily equivalent if and only if the two dimensional operator spaces",
null,
"$\\textrm{span}\\{ I, A\\}$ and",
null,
"$\\textrm{span}\\{ I, B\\}$ are completely isometric via a unital map that takes",
null,
"$A$ to",
null,
"$B$\n\nThe urgent question now becomes: does the Shilov boundary ideal exist?.\n\nTo prove the existence of the Shilov boundary ideal, Arveson introduced boundary representations. Although boundary representations were central to his investigations, and although he proved that they exist in some special cases, the question of whether boundary representations exist in general was left open (consequently, the existence of the C*-envelope was also left open). The existence of boundary representations in general (for separable operator spaces) was established by Arveson four decades later (!) in [“The noncommutative Choquet boundary”, J. Amer. Math. Soc. 21, 2008] following important works of Dritschel and McCullough and of Muhly and Solel (the existence of the C*-envelope was established by Hamana in 1979 by a different approach).\n\nOne of the immediate applications of this theory that Arveson presented was a dilation theorem that unified and clarified the various bits and pieces of dilation theory (initiated by Sz.-Nagy) that were present at the time:\n\nArveson’s Dilation Theorem (1972). Let",
null,
"$T$ be a",
null,
"$k$-tuple of commuting operators and let",
null,
"$X \\subset \\mathbb{C}^k$ be a compact set. Then",
null,
"$T$ has a normal dilation",
null,
"$N$ with",
null,
"$\\textrm{sp}(N) \\subseteq \\partial X$ if and only if",
null,
"$X$ is a complete spectral set for",
null,
"$T$\n\nI do not want to go into the definitions, the reader is referred to this exposition by Arveson for details.\n\nMany of Arveson’s results in the two “Subalgebras” papers mentioned above relied on a Hahn–Banach type extension theorem for completely positive maps which he proved in the first section of the first paper. Let me state a version for completely contractive maps which is perhaps clearer to the newcomer:\n\nArveson’s Extension Theorem (1969). Let",
null,
"$B$ be a C*-algebra, let",
null,
"$S \\subseteq B$ be an linear subspace containing the identity and let",
null,
"$\\phi : S \\rightarrow B(H)$ be a unital, completely contractive map. Then",
null,
"$\\phi$ has an extension to a unital, completely contractive and completely positive map",
null,
"$\\Phi : B \\rightarrow B(H)$.\n\nAnyone with some experience in functional analysis can appreciate the utility of this result. Indeed, this theorem is used by operator algebraists on a daily basis, to this day.\n\nThe ideas and results of these two papers of Arveson which we mentioned have had a profound impact on operator algebras and operator theory. Without them, the study of abstract operator algebras, the solution of the Sz.-Nagy–Halmos problem (is every polynomially bounded operator similar to a contraction?) and the numerous applications of operator space techniques to operator algebras, would have all been unthinkable."
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] | {"ft_lang_label":"__label__en","ft_lang_prob":0.9589889,"math_prob":0.9785936,"size":13606,"snap":"2019-26-2019-30","text_gpt3_token_len":3089,"char_repetition_ratio":0.14689016,"word_repetition_ratio":0.021457309,"special_character_ratio":0.20880494,"punctuation_ratio":0.10210444,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.9966249,"pos_list":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166],"im_url_duplicate_count":[null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2019-06-25T16:29:41Z\",\"WARC-Record-ID\":\"<urn:uuid:f81c418f-f1f9-4714-a6aa-5249cf9f5393>\",\"Content-Length\":\"111421\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:e7b28a4b-d6cf-418d-901c-a9b360ad90d1>\",\"WARC-Concurrent-To\":\"<urn:uuid:39557f7a-de75-4ee1-8b5f-524beaafc7c5>\",\"WARC-IP-Address\":\"192.0.78.24\",\"WARC-Target-URI\":\"https://noncommutativeanalysis.com/2012/10/11/william-arveson/?replytocom=494\",\"WARC-Payload-Digest\":\"sha1:MN7JJA2VFPEZLUOY5RFWLV6SRBGPPFHO\",\"WARC-Block-Digest\":\"sha1:ZEFTOXTSYFVASYNUABBLA65HDPHFJCTX\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2019/CC-MAIN-2019-26/CC-MAIN-2019-26_segments_1560627999853.94_warc_CC-MAIN-20190625152739-20190625174739-00442.warc.gz\"}"} |
https://www.physicsforums.com/search/4748291/ | [
"# Search results\n\n1. ### A Time Dilation Paradox?\n\n(Quibble) Almost correct. Mathematically that should be: If ##Δx_A=0## then ##Δt_B>=Δt_A## and If ##Δx_B=0## then ##Δt_A>=Δt_B##. And then, if they insist on having them both in one scenario, then clearly: If ##Δx_A=Δx_B=0## then ##Δt_B>=Δt_A## and ##Δt_A>=Δt_B##, and thus...\n2. ### Maxwell's distribution\n\nGood question. See Maxwell–Jüttner distribution.\n3. ### Perspective on Relativity and Length Contraction\n\nFwiw--not much apparently--I think you missed the point, but feel free not to lose any sleep over it :cool:\n4. ### Perspective on Relativity and Length Contraction\n\nNice diagram! Fwiw, note that : (*1) in the top figure, where Red touches the green car simultaneously with both hands, Green protests and says that Red is cheating because he does not touch his green car simultaneously. According to Green, Red touches the green car's front too late and the...\n5. ### Derivation of Schwarzschild radius from escape velocity\n\nThere's a nice comment about that on page 2-22 of http://www.eftaylor.com/pub/chapter2.pdf\n\n7. ### How does Maxwell equation suggest that the speed of light is the same\n\n(Quibble) ... which will or will not falsify the postulates. I think that \"validate\" is too strong, as it might be interpreted as a synonym of \"prove\".\n8. ### SR question\n\nNo, more like, from a distance you look smaller to me, and I look smaller to you.\n9. ### Problem with relativity\n\nMeasured time differences increase by a factor gamma, but c.t' = c.t.gamma only for x=0 (see Wikipedia Time dilation) Measured distances decrease by a factor gamma, but x' = x/gamma only for t'=0 (see Wikipedia Length contraction) Combining these two clearly distinct situations with two events...\n10. ### Four amateur questions about gravity and general relativity\n\nNah. Gravity can be modeled with geometry. The former is physical and the latter is mathematical. The Sun has a LOT of mass.\n11. ### Spacetime diagram drawing problem\n\nLots of diagrams at https://en.wikipedia.org/wiki/Slope\n12. ### Spacetime diagram drawing problem\n\nTo get a slope 1/2 between the horizontal and a line, you do *not* bisect the 45 degrees angle. Instead you draw a line with slope 1/2, which means climbing 1 unit for every 2 units of horizontal displacement. That gives an angle of 26.6 degrees, not one of 22.5 degrees. See...\n13. ### Spacetime diagram drawing problem\n\nThen you need Arctan(1/2) between the ct-axis and the ct'-axis, and thus 45 degrees -Arctan(1/2) between the ct'-axis and the light diagonal.\n14. ### Spacetime diagram drawing problem\n\nOops, I meant 45 degrees - Arctan(1/2) = 18.4 degrees.\n15. ### Spacetime diagram drawing problem\n\nTry using an Arctan(1/2) = 26.6 degrees angle.\n\nFrom the travelers point of view they don't accelerate the same way. The one in front moves away from the one behind. The thread breaks.\n17. ### Trying to reconcile Lorentz Transformation and Length Contraction\n\nIt means making a measurement that is simultaneous with the (x',t') = (0,0) event in my coordinates. You and the lamp post are moving in my frame, so I must make sure that I measure the distances to you and to the lamp post simultaneously. You are at distance x'=0 at my time t'=0, so I must...\n18. ### Time moves forward, what if you move UP or DOWN? Does time stop?\n\n\"Moving with the arrow of time\" is just fancy speak for \"growing older\". As far as we know, we can't grow younger, hence the \"arrow\". It points \"where\" we go.\n19. ### Ratio of proper clock rates?\n\nWorth a little texercise: \\begin{align} \\Delta x' &= x'_2 - x'_1 &\\quad \\Delta t' &= t'_2 - t'_1 \\\\ &= \\gamma \\ ( x_2 - v \\ t_2 ) - \\gamma \\ ( x_1 - v \\ t_1 ) & &= \\gamma \\ ( t_2 - \\tfrac{v}{c^2} x_2 ) - \\gamma \\ ( t_1 -...\n20. ### Ratio of proper clock rates?\n\nThanks to its linearity, the Lorentz transformation works perfectly on coordinate differences between pairs of events."
] | [
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http://downloads.hindawi.com/journals/mpe/2009/716104.xml | [
"MPEMathematical Problems in Engineering1563-51471024-123XHindawi Publishing Corporation71610410.1155/2009/716104716104Research ArticleMacro- and Microsimulations for a Sublimation Growth of SiC Single CrystalsGeiserJürgen1IrleStephan2PiqueiraJosé Roberto Castilho1Humboldt University of BerlinUnter den Linden 610099 BerlinGermanyhu-berlin.de2Nagoya UniversityFuro-cho, Chikusa-kuNagoya 464-8602Japannagoya-u.ac.jp20091201200920090309200802112008181120082009Copyright © 2009This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.\n\nThe numerous technical applications in electronic and optoelectronic devices, such as lasers, diodes, and sensors, demand high-quality silicon carbide (SiC) bulk single crystal for industrial applications. We consider an SiC crystal growth process by physical vapor transport (PVT), called modified Lely method. We deal with a model for the micro- and macroscales of the sublimation processes within the growth apparatus. The macroscopic model is based on the heat equation with heat sources due to induction heating and nonlocal interface conditions, representing the heat transfer by radiation. The microscopic model is based on the quantum interatomic potential and is computed with molecular dynamics. We study the temperature evolution in the apparatus and reflect the growth behavior of the microscopic model. We present results of some numerical simulations of the micro- and macromodels of our growth apparatus.\n\n1. Introduction\n\nThe motivation for this study comes from the technical demand to simulate a crystal growth apparatus for SiC single crystals. The single crystals are used as a high-valued and expensive material for optoelectronics and electronics (cf. ). We concentrate on a deterministic model for simulating crystal growth; alternative models are discussed with comprehensive probabilistic modeling (see ).\n\nThe silicon carbide (SiC) bulk single crystals are produced by a growth process through physical vapor transport (PVT), called modified Lely method. The modeling for the thermal processes within the growth apparatus is done in [3, 4]. In this paper, we propose one step more in the modeling of the macroscopic and microscopic parts. The idea is to exchange results from the macroscopic to the microscopic scale to obtain a feedback to control the growth process of the SiC bulk. Here the benefits are an acceleration of solving interactive growth processes of the crystal with their underlying temperature in the apparatus. Using only standard codes, which are decoupled, a simple parameter exchange of temperature and pressure in the deposition region cannot resolve the growth problem accurately. We propose a first framework of a combined model, which is based on the authors’ knowledge of a novel work and a first approach to a coupled solver method.\n\n2. Macroscopic Model: Heat-Flux\n\nIn the following, we discuss the macroscopic model, which is based on continuum equations for the heat-flux.\n\n2.1. Mathematical Model\n\nThe underlying equations of the model are given as follows.\n\n(a) In this work, we assume that the temperature evolution inside the gas region Ωg can be approximated by considering the gas as pure argon (Ar). The reduced heat equation isρgtUg(κgT)=0,Ug=zArRArT,where T is the temperature, t is the time, and Ug is the internal energy of the argon gas. The parameters are given as ρg being the density of the argon gas, κg being the thermal conductivity, zAr being the configuration number, and RAr being the gas constant for argon.\n\n(b) The temperature evolution inside the region of solid materials Ωs (e.g., inside the silicon carbide crystal, silicon carbide powder, graphite, and graphite insulation) is described by the heat equationρstUs(κsT)=f,Us=0Tcs(S)dS,where ρs is the density of the solid material, Us is the internal energy, κs is the thermal conductivity, and cs is the specific heat.\n\nThe equations hold in the domains of the respective materials and are coupled by interface conditions, for example, requiring the continuity for the temperature and for the normal components of the heat flux on the interfaces between opaque solid materials. On the boundary of the gas domain, that is, on the interface between the solid material and the gas domain, we consider the interface conditionκgTng+RJ=κsTng,where ng is the normal vector of the gas domain, R is the radiosity, and J is the irradiosity. The irradiosity is determined by integrating R along the whole boundary of the gas domain (cf. ). Moreover, we haveR=E+Jref,E=σϵT4(Stefan-Boltzmannequation),Jref=(1ϵ)J,where E is the radiation, Jref is the reflexed radiation, ϵ is the emissivity, and σ is the Boltzmann radiation constant.\n\nThe density of the heat source induced by the induction heating is determined by solving Maxwell’s equations. We deal with these equations under the simplifying assumption of an axisymmetric geometry, axisymmetric electromagnetic fields, and a sinusoidal time dependence of the involved electromagnetic quantities, following . The considered system and its derivation can be found in [3, 4, 7].\n\nIn this paper, we focus on the discretization and material properties, which are important for realistic simulations. Our underlying software tool WIAS-HiTNIHS (cf. ) allows us a flexibility in the grid generation and for the material parameters.\n\nIn the next section, we describe the used discretization.\n\n2.2. Discretization\n\nFor the discretization of the heat equation (diffusion equation), we apply the implicit Euler method in time and the finite volume method for the space discretization (cf. [3, 4, 8]). We consider a partition 𝒯=(ωi)iI of Ω such that, for m{s,g} (with s solid, g gas) and iI,ωm,i:=ωiΩm defines either a void subset or a nonvoid, connected, and open polyhedral subset of Ω. By integrating the corresponding heat equation (2.1) or (2.3) over ωm,i, we derive the following nonlinear equations for the temperature variables,ρmωm,i(Um(Tn+1)Um(Tn))rdxΔtn+1ωm,iκm(Tn+1)Tn+1nωm,irds=Δtn+1ωm,ifmrdx,where the time interval is Δtn+1=tn+1tn. The temperature is given as Tn+1=T(tn+1,x), where x represents cylindrical coordinates. For the right-hand sides, we demand fs:=f0 and fg=0.\n\nMore details of the discretization and of dealing with the interface conditions are presented in [3, 4, 9, 10].\n\nIn the next section, the properties of the materials in the crystal growth apparatus are described.\n\n2.3. Material Properties\n\nFor the technical realization of the apparatus, we implement the axisymmetric geometry given in , which is presented in Figure 1. Furthermore, the properties of the materials are specified in [3, 9, 12].\n\nThe growth apparatus’ dimensions: rmin=0,rmax=8.4cm,zmin=0,zmax=25.0cm, the coil rings’ dimensions: rmin=4.2cm,rmax=5.2cm,zmin=0,zmax=14.0cm.\n\nWithin the following specific material functions and parameters for the processes, the thermal conductivity κ is given in W/(m K), the electrical conductivity σc is given in 1/(Ohm m), the mass density ρ is given in kg/m3, the specific heat csp is given in J/(K kg), the temperature T is given in K, and the relative gas constant RAr is given in J/(K kg). Further, the emissivity ϵ and relative magnetic permeability μ are given dimensionless.\n\n(i) For the gas phase (argon), we haveκAr(T)={1.83914104T0.800404T500,7.128738+6.610288102T2.440839104T2+4.497633107T34.1325171010T4+1.5144631013T5500T600,4.1944104T0.671118600T, where σc,Ar=0.0,ρAr=3.73103,μAr=1.0,zAr=3/2,RAr=2.081308102.\n\n(ii) For graphite felt insulation, we haveκIns(T)={8.175102+2.485104TT1473,1.1902102+0.346838T3.9971104T2+2.2830107T36.460471011T4+7.25491015T51473T1873,0.7447+7.5104T1873T, where ϵIns=0.2,σc,Ins(T)=2.45102+9.82102T,ρIns=170.00,μIns=1.00,csp,Ins=2100.00.\n\n(iii) For the graphite, we haveκGraphite(T)=37.715exp(1.96104T),ϵGraphite(T)={0.67T1200,3.7527.436103T+6.4163106T22.3366109T33.08331013T41200T2200,0.792200T, where σc,Graphite=104,ρGraphite=1750.0,μGraphite=1.0,csp,Graphite(T)=1/(4.411102T2.306+7.97104T0.0665).\n\n(iv) For the SiC crystal, we have κSiC-C(T)=exp(9.892+(2.498102)/T0.844ln(T)),ϵSiC-C=0.85,σc,SiC-C=105,ρSiC-C=3140.0,μSiC-C=1.0,csp,SiC-C(T)=1/(3.91104T3.173+1.835103T0.117).\n\n(v) For the SiC powder, we have κSiC-P(T)=1.452102+5.471012T3,ϵSiC-P=0.85,σc,SiC-P=100.0,ρSiC-P=1700.0,μSiC-P=1.0,csp,SiC-P=1000.0.\n\nThe functions are programmed in our flexible software package WIAS-HiTNIHS.\n\nIn the next section, we discuss the microscopic model.\n\n2.4. Coupling Method for Macroscopic and Microscopic Models: Operator Splitting\n\nOften simple coupling via the parameters (e.g., target-temperature and growth velocity of the bulk) is enough for the problem.\n\nHere we propose a new idea of coupling the model equations together, on the one hand the heat equations and on the other hand the kinetic equations for molecules.\n\nFor a first idea, we deal with abstract operators, which include the heat- and the kinetics equations.\n\nUsing our two standard codes of the macro- and micromodels, we could implement a coupled model, by a so-called iterative operator-splitting method. Such a proposed method couples the two physical processes of the thermal situation in the growth apparatus and their important geometrical differences at the deposition layer with the kinetic molecular model. The benefits are a numerical algorithm, that exchanged the underlying operators of the thermal situation and the kinetic molecular situation, which are computed by each software code independently and coupled via an iterative solver step; see a detailed coupling analysis in .\n\nIn the following algorithm, an iteration method is proposed, with fixed splitting discretization step-size τ.\n\nDue to the underlying multiscale problem of kinetics and heat processes, we have to solve fine time scales of kinetic equations and coarse time scales for heat equations. On a time interval [tn,tn+1] that is sufficiently small to yield accurate kinetics, we solve the following subproblems consecutively for i=0,2,,2m (cf. [14, 15]):ci(t)t=Aci(t)+Bci1(t),withci(tn)=cn,i=1,2,,j,ci(t)t=Aci1(t)+Bci(t),withci+1(tn)=cn,i=j+1,j+2,,m, where we assume that the operator A has a large time scale (macroscopic model) and B has a small time scale (microscopic model). Further c0(tn)=cn,c1=0, and cn are initialization and starting conditions.\n\nIn the following, we give an overview to the accuracy of the method, which is given in the convergence and the rate of the convergence.\n\nTheorem 2.1.\n\nLet us consider the abstract Cauchy problem in a Banach space X:tc(t)=Ac(t)+Bc(t),0<tT,c(0)=c0, where A,B,A+B:XX are given linear operators being generators of the C0-semigroup and c0X is a given element. Then the iteration process (2.11)-(2.12) is convergent. The rate of convergence is of higher order and given as 𝒪(τn2m), where the iterations are i=1,3,,2m+1.\n\nThe proof is given in .\n\nIn the next subsection, we present the methods for the microscopic model.\n\n3. Microscopic Model: Quantum Chemical Molecular Dynamics (QM/MD) of SiC Condensation (Methodology)\n\nThe density-functional tight-binding (DFTB) method is employed as the quantum interatomic potential in our molecular dynamics (MD) simulations, using atomic and diatomic parameters obtained from density functional theory; see . DFTB is an approximate density functional theory method based on the tight binding approach, and utilizes an optimized minimal LCAO Slater-type all-valence basis set in combination with a two-center approximation for Hamiltonian matrix elements. Parameter sets for Si-Si and Si-C were taken from . Energies and gradients are evaluated direct (on the fly) during the dynamic simulation. As in our previous simulations of carbon cap and subsequent nanotube formation on the C- and Si-faces of SiC(000-1) surfaces during sublimation evaporation, we have not included charge- or spin-polarization in the present work. Further, we will consider in a next model electrokinetic effect on heat transfer in parallel-plate microchannels, hydrodynamic focusing effects, and nanoeffect as done in .\n\nFor time propagation we employed a velocity Verlet integrator with a time step of 1.209 fs (50 atomic units) and used a Nose-Hoover chain thermostat to generate a canonical ensemble for target temperature Tt; see . The thermostat was employed uniformly in the reaction system.\n\nRegarding the atomistic structure of the employed surface model systems, we have chosen the C-face of the same square SiC(000-1) slab unit cell as in our previous study, consisting of two SiC layers terminated by hydrogen atoms to mimic bulk effect in the direction away from the surface. Periodic boundary conditions were employed with a unit cell size of 1000 Å in the direction perpendicular to the surface and 16.0 Å and 15.4 Å in the other two surface-directions to achieve two-dimensional slab periodicity. The geometry optimized structure of this surface model is shown in Figure 2.\n\nOptimized geometry of the C-face of the (000-1) SiC surface as initial starting point for QM/MD simulations. Blue spheres correspond to silicon atoms, purple spheres correspond to carbon atoms, and white spheres correspond to hydrogen atoms terminating the slab model in bulk direction. The model is the unit cell used in periodic boundary calculations with infinite surface extension.\n\nDuring MD simulations, the movements of hydrogen terminating atoms were frozen. Using such an approach, we have effectively introduced a steep temperature gradient from the deepest bulk-side SiC layer to the atoms lying above on the surface. The slab model was then annealed at Tt=2000K for 1.20 picoseconds, and 3 structures were selected as initial starting geometries at t=0.60 picosecond (trajectory A50), t=0.72 picosecond (trajectory A60), and t=0.86 picosecond (trajectory A80). In the vicinity of the surface, 10 SiC molecules were randomly distributed in the gas phase. Since these molecules are nonbonded to the surface, they are subsequently thermostated at Tt. Gas phase molecules approaching the surface will experience immediate cooling, which will drive the condensation process during these simulations.\n\nIn the microscopic model, we can derive the growth rate v of the seed surface in dependence on temperature and pressure. Based on these growth rates, we can adapt the geometry for the macroscopic model. Such modification helps to give more accurate temperature differences in the macroscopic model and understand the growth process.\n\nIn the next section, we present results of our numerical experiments.\n\n4. Numerical Experiments\n\nWe present in the following our macro- and microscopic simulations, where the microscopic simulations take into account the target temperature of the macroscopic model.\n\n4.1. Macroscopic Model: Simulation of the Temperature Field in the Apparatus\n\nFor the numerical results, we apply the parameter functions in Section 2.3. We consider the geometry shown in Figure 1, using a constant total input power of 10kW (cf. ). The numerical experiments are performed using the software WIAS-HiTNIHS (cf. ) based on the software package pdelib (cf. ) which uses the sparse matrix solver PARDISO (cf. ). We compute the coupled system consisting of the heat equations and Maxwell’s equations. For the growth process, the temperature difference Tss=T(rsource,zsource)T(rseed,zseed) (with the coordinates (rsource,zsource)=(0,0.143) and (rseed,zseed)=(0,0.158), corresponding to the points Tsource and Tseed in Figure 1) is crucial. On the other hand, in the physical growth experiments, usually only the temperatures T(rbottom,zbottom) and T(rtop,ztop) (with the coordinates (rbottom,zbottom)=(0,0.028) and (rtop,ztop)=(0,0.173), corresponding to the points Tbottom and Ttop in Figure 1) are measurable and their difference Tbt=T(rbottom,zbottom)T(rtop,ztop) is often used as an indicator for Tss. In Figure 3, we present the temperature differences Tss and Tbt. As a result of our computations, the temperature difference Tbt can only restrictively be used as an indicator for the temperature difference Tss (cf. the discussions in [5, 9]).\n\nTransient results for the temperature differences Tbt and Tss.\n\nThe further computations are based on the stationary case, dealing with (2.1) by discarding the terms with a time derivative. For this case, the results are virtually equal to the one in the transient case with t>15000 seconds. For the stationary results, we focus on the error analysis for the space dimension by applying the grid refinement. The solutions for the heat equation are computed at the points T(rbottom,zbottom) and T(rtop,ztop) for successive grids. For the error analysis, we apply the following error differences:ϵabs=|T˜j+1(r,z)T˜j(r,z)|,where T˜j(r,z) and T˜j+1(r,z) are solutions evaluated at the point (r,z) which has been computed using the grids j and j+1, respectively. The elements of the grid j+1 are approximately 1/4 of the elements of the grid j. The results are presented in Table 1.\n\nComputations on different grids for the errors analysis with absolute differences (cf. (4.1)).\n\nGridGrid point (0,0.028) (Tbottom)Grid point (0,0.173) (Ttop)\nLevelNumber of nodesSolution T[K]Absolute difference T[K]Solution T[K]Absolute difference T[K]\n015322408.112813.29\n1230172409.781.672812.781.01\n2912902410.350.572811.790.49\n33642252410.460.112811.600.19\n\nThe result of the refinement indicates the reduction of the absolute difference as it is demanded for the convergence of the discretization method. The method is stabilized in the presented refinement by reducing the differences.\n\nIn Figure 4, the temperature field is presented for the stationary case. The temperature increases from the bottom to the middle of the graphite pot, and decreases from the middle to the top of the graphite pot.\n\nTemperature field for the apparatus simulated for the stationary case with 23017 nodes.\n\n4.2. Microscopic Model: Atomistic QM/MD Simulations of SiC Condensation on the C-Face of Si(000-1)\n\nThe total time of the three condensation simulations was 24.02 picoseconds. This is admittedly a time too short for the study of crystal growth, which would ideally require annealing simulations on the order of several 100 nanoseconds, but this study is focusing on the initial stages of SiC aggregation and tries to identify key features in the condensation process. As such, this is at present rather a preliminary study exploring the applicability of QM/MD simulations for SiC crystal growth. We have first concentrated on the polar C-surface of SiC (0001) since it has a maximum of dangling bonds with highest reactivity. The Si-face and other nonpolar surfaces are much less reactive; see . Since our seed crystal surface slab model contains only two SiC layers, we are also unable to address the issue of polymorphism at present, although it should be noted that our model system rather resembles the cubic 3C than the hexagonal polytypes.\n\nTt was chosen as 2000 K for all simulations, and representative snapshots from trajectory A50 are given in Figure 5. We find that under the present conditions with a relatively high density of SiC gas molecules, several of them attach very quickly to the surface (2 after 0.10 picosecond). Also, SiC molecules can react with each other to form dimers, preferably with C-C bonds. Eventually, an average of 5.3 SiC molecules become attached to the surface in the three simulations, with the other molecules being lost to the vacuum layer.\n\nSimulation of the addition of 10 SiC atoms on the C-face of the (000-1) SiC surface from Figure 2. Blue spheres correspond to silicon atoms, purple spheres correspond to carbon atoms, and white spheres correspond to hydrogen atoms terminating the slab model in bulk direction. Times are given in picoseconds (ps), indicating that the moment the snapshots were taken during the dynamics simulations.\n\nOnce attached, the Si atoms on the surface prove to be highly mobile, as their bond radius is larger than the case of carbon, and the binding energies are lower . The carbon atoms on the surface tend to form C2 units, and behave similar to “wobbling C2” entities that we had observed for high-temperature simulations of pure carbon; see . It seems from our simulations at this stage that the system tries to reach an equilibrium with a constant number of C-C in the new layers, and that the Si atoms are more isolated, becoming occasionally attacked by a C2 dimer. In particular, C2 units are oriented mainly perpendicular to the surface, while the more visible Si2 dimers do not show such an alignment preference. The surface itself retains the structure of alternating Si–C units. A new layer of Si–C units is being deposited with a somewhat inhomogeneous structure containing C2 and Si2 units at first, and gradually becoming more homogeneous due to annealing.\n\n5. Summary\n\nWe have presented a model for the heat transport inside a technical apparatus for crystal growth of SiC single crystals. We introduce the heat equation and the radiation of the apparatus and the coupled situation of the different materials. The equations are discretized by the finite volume method and the complex material functions are embedded in this method. Transient and stationary results are presented leading to some information about the processes within the technical apparatus. We present numerical results for the stationary case to support the accuracy of our solutions. We also presented atomistic quantum chemical molecular dynamics (QM/MD) simulations based on the density-functional tight-binding (DFTB) method for initial reactions of gaseous SiC on the polar C-face of SiC(000-1). In our future work, we concentrate on further implementations and numerical methods for a crystal growth model and use kinetic data obtained from more accurate microscopic model simulations in the simulation of the heat transport. Once longer and a larger number of trajectories are obtained in our microsimulations, it will be possible to deduct an accurate QM/MD-based estimate for the bulk growth, in dependence on the temperature to our macrosimulations. This data will then enter the iterative solution of the heat and kinetics equations of the coupled macroscopic and microscopic models.\n\nMüllerSt.stephan_mueller@cree.comGlassR. C.HobgoodH. M.Progress in the industrial production of SiC substrates for semiconductor devicesMaterials Science and Engineering B2001801–332733110.1016/S0921-5107(00)00658-9YaoX.HeB.WangH.ZhouX.Numerical simulation of dendrite growth during solidificationInternational Journal of Nonlinear Sciences and Numerical Simulation200672171176KleinO.PhilipP.philip@wias-berlin.deTransient numerical investigation of induction heating during sublimation growth of silicon carbide single crystalsJournal of Crystal Growth20032471-221923510.1016/S0022-0248(02)01903-6PhilipP.Transient numerical simulation of sublimation growth of SiC bulk single crystals. Modeling, finite volume method, results, Ph.D. thesis2003Berlin, GermanyWeierstrass-Institute for Applied Analysis and StochasticsReport No. 22KleinO.PhilipP.SprekelsJ.Modeling and simulation of sublimation growth of SiC bulk single crystalsInterfaces and Free Boundaries200463295314MR2095334ZBL1081.35117RappazJ.SwierkoszM.Modelling in numerical simulation of electromagnetic heatingModelling and Optimization of Distributed Parameter Systems1996New York, NY, USAChapman & Hall313320MR1388547ZBL0879.65091KleinO.PhilipP.Correct voltage distribution for axisymmetric sinusoidal modeling of induction heating with prescribed current, voltage, or powerIEEE Transactions on Magnetics20023831519152310.1109/20.999125GeiserJ.R3T: radioactive-retardation-reaction-transport-program for the simulation of radioactive waste disposalsApril 2004College Station, Tex, USAInstitute for Scientific Computation, Texas A&M UniversityKleinO.PhilipP.philip@wias-berlin.deTransient temperature phenomena during sublimation growth of silicon carbide single crystalsJournal of Crystal Growth20032493-451452210.1016/S0022-0248(02)02320-5KleinO.PhilipP.Transient conductive-radiative heat transfer: discrete existence and uniqueness for a finite volume schemeMathematical Models & Methods in Applied Sciences2005152227258MR2119998ZBL1070.65075PonsM.AnikinM.ChourouK.State of the art in the modelling of SiC sublimation growthMaterials Science and Engineering B199961-62182810.1016/S0921-5107(98)00439-5NilssonO.MehlingH.HornR.Determination of the thermal diffusivity and conductivity of monocrystalline silicon carbide (300–2300 K)High Temperatures-High Pressures1997291737910.1068/htec142GeiserJ.Iterative operator-splitting methods with higher-order time integration methods and applications for parabolic partial differential equationsJournal of Computational and Applied Mathematics20082171227242MR242744310.1016/j.cam.2007.06.028ZBL1144.65062KanneyJ. F.MillerC. T.caseyller@unc.eduKelleyC. T.Convergence of iterative split-operator approaches for approximating nonlinear reactive problemsAdvances in Water Resources200326324726110.1016/S0309-1708(02)00162-8FaragóI.faragois@cs.elte.huGeiserJ.geiser@mathematik.hu-berlin.deIterative operator-splitting methods for linear problemsInternational Journal of Computational Science and Engineering20073425526310.1504/IJCSE.2007.018264PorezagD.FrauenheimTh.KöhlerTh.SeifertG.KaschnerR.Construction of tight-binding-like potentials on the basis of density-functional theory: application to carbonPhysical Review B19955119129471295710.1103/PhysRevB.51.12947RaulsE.HajnalZ.DeákP.FrauenheimTh.Theoretical study of the nonpolar surfaces and their oxygen passivation in 4H- and 6H-SiCPhysical Review B20016424724532310.1103/PhysRevB.64.245323IrleS.WangZ.ZhengG.MorokumaK.KusunokiM.Theory and experiment agree: single-walled carbon nanotube caps grow catalyst-free with chirality preference on a SiC surfaceThe Journal of Chemical Physics20061254504470210.1063/1.2212402WangZ.IrleS.sirle@iar.nagoya-u.ac.jpZhengG.KusunokiM.MorokumaK.morokuma@emory.eduCarbon nanotubes grow on the C face of SiC (0001) during sublimation decomposition: quantum chemical molecular dynamics simulationsThe Journal of Physical Chemistry C200711135129601297210.1021/jp072208dChangC.-C.YangR.-J.rjyang@mail.ncku.edu.twHydrodynamic focusing effect on two-unmixed-fluid in microchannelsInternational Journal of Nonlinear Sciences and Numerical Simulation200893213220FanJ.WangL.lqwang@hku.hkChengL.Electrokinetic effects on flow and heat transfer in parallel-plate microchannelsInternational Journal of Nonlinear Sciences and Numerical Simulation200783335345FanJ.WangL.lqwang@hku.hkChengL.Forced convection in rectangular microchannels: electrokinetic effectsInternational Journal of Nonlinear Sciences and Numerical Simulation200783359374HeJ.-H.jhhe@dhu.edu.cnWanY.-Q.XuL.Nano-effects, quantum-like properties in electrospun nanofibersChaos, Solitons & Fractals2007331263710.1016/j.chaos.2006.09.023AllenM. P.TildesleyD. J.Computer Simulation of Liquids1989New York, NY, USAOxford University PressFuhrmannJ.KopruckiTh.LangmachH.HackbuschW.WittumG.pdelib: an open modular tool box for the numerical solution of partial differential equations. Design patternsProceeding of the 14th GAMM Seminar on Concepts of Numerical SoftwareJanuary 2001Kiel, GermanySchenkO.olaf.schenk@unibas.chGärtnerK.gaertner@wias-berlin.deSolving unsymmetric sparse systems of linear equations with PARDISOFuture Generation Computer Systems200420347548710.1016/j.future.2003.07.011PollmannJ.KrügerP.SabischM.Atomic and electronic structure of SiC surfaces from ab-initio calculationsPhysica Status Solidi (B)1997202142144510.1002/1521-3951(199707)202:1<421::AID-PSSB421>3.0.CO;2-DIrleS.ZhengG.ElstnerM.MorokumaK.morokuma@emory.eduFormation of fullerene molecules from carbon nanotubes: a quantum chemical molecular dynamics studyNano Letters20033446547010.1021/nl034023y"
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https://answers.ros.org/question/239417/cart-controller-help/ | [
"# Cart Controller help!\n\nHi!\n\nI am making a cart controller. The idea is using a delta of time, iterate a given number of times to converge to the desired position. So the set parameters are dt (delta time) and N (iterations)\n\n1. Get the desired task positions\n2. Get the actual joint positions\n3. Calculate jacobian for actual joint position\n4. Calculate actual task position for the joint position\n5. Calculate the error (for position and orientation)\n6. Divide the error by delta time to get velocity in task space.\n7. Using the jacobian and the velocity in task space, calculate the velocity in joint space.\n8. Using the velocity in joint space and the delta of time, calculate the necessary (new) joint positions.\n9. Iterate from 3 to 8 a number of times.\n\nMy variables are:\n\nKDL::JntArray q_ (actual joint positions)\n\nKDL::Frame x_des (the desired task position)\n\nKDL::JntArray q_ (joint positions calculations)\n\nKDL::Jacobian J_ (jacobian)\n\nNow this is the algoritm.\n\n...\n\nq_s=q_;\n\nk=0;\n\nwhile(!k>iter){\n\nk++;\n\njnt_to_jac_solver_->JntToJac(q_s, J_); //Calculate jacobian for joint position\n\njnt_to_pose_solver_->JntToCart(q_s, x_s); //Calculate task position for the joint position\n\nxerr_.vel = x_des.p-x_s.p; //Calculate the error for position\n\nxerr_.rot = 0.5 * (x_des.M.UnitX() * x_s.M.UnitX() + x_des.M.UnitY() * x_s.M.UnitY() + x_des.M.UnitZ() * x_s.M.UnitZ()); //Calculate the error for orientation\n\nxdot_s.vel = xerr_.vel/dt; //Divide the error by dt to get xdot_s\n\nxdot_s.rot = xerr_.rot/dt; //Divide the error by dt to get xdot_s\n\nqdot_s=f(xdot_s,J_); //Then using xdot_s, and the jacobian, I calculate qdot_s\n\nq_s=q_s+dt*qdot_s; //New joint position\n\nThe problem is that using that it doesn't perform well. I have check that it works when I don't use the error of rotation to calculate xdot_s (that happens when I comment the Bold line in my code). So I'm pretty sure I am not calculating well the error in rotation (and so the velocity in task space)."
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https://www.arxiv-vanity.com/papers/hep-ph/0208177/ | [
"arXiv Vanity renders academic papers from arXiv as responsive web pages so you don’t have to squint at a PDF. Read this paper on arXiv.org.\n\nLAL 02-81\n\nhep-ph/0208177.v3\n\nMay 25, 2020\n\nConfronting Spectral Functions from Annihilation and Decays: Consequences for the Muon Magnetic Moment\n\nM. Davier, S. Eidelman, A. Höcker and Z. Zhang111 E-mail: , , ,\n\nLaboratoire de l’Accélérateur Linéaire,\n\nIN2P3-CNRS et Université de Paris-Sud, F-91898 Orsay, France\n\nBudker Institute of Nuclear Physics, Novosibirsk, 630090, Russia\n\nAbstract\n\nVacuum polarization integrals involve the vector spectral functions which can be experimentally determined from two sources: (i) annihilation cross sections and (ii) hadronic decays. Recently results with comparable precision have become available from CMD-2 on one side, and ALEPH, CLEO and OPAL on the other. The comparison of the respective spectral functions involves a correction from isospin-breaking effects, which is evaluated. After the correction it is found that the dominant spectral functions do not agree within experimental and theoretical uncertainties. Some disagreement is also found for the spectral functions. The consequences of these discrepancies for vacuum polarization calculations are presented, with the emphasis on the muon anomalous magnetic moment. The work includes a complete re-evaluation of all exclusive cross sections, taking into account the most recent data that became available in particular from the Novosibirsk experiments and applying corrections for the missing radiative corrections. The values found for the lowest-order hadronic vacuum polarization contributions are\n\nwhere the errors have been separated according to their sources: experimental, missing radiative corrections in data, and isospin breaking. The Standard Model predictions for the muon magnetic anomaly read\n\nwhere the errors account for the hadronic, light-by-light scattering and electroweak contributions. We observe deviations with the recent BNL measurement at the 3.0 () and 0.9 () level, when adding experimental and theoretical errors in quadrature.\n\n## 1 Introduction\n\nHadronic vacuum polarization in the photon propagator plays an important role in the precision tests of the Standard Model. This is the case for the evaluation of the electromagnetic coupling at the mass scale, , which receives a contribution of the order of that must be known to an accuracy of better than 1% so that it does not limit the accuracy on the indirect determination of the Higgs boson mass from the measurement of . Another example is provided by the anomalous magnetic moment of the muon where the hadronic vacuum polarization component is the leading contributor to the uncertainty of the theoretical prediction.\nStarting from Refs. [1, 2] there is a long history of calculating the contributions from hadronic vacuum polarization in these processes. As they cannot be obtained from first principles because of the low energy scale involved, the computation relies on analyticity and unitarity so that the relevant integrals can be expressed in terms of an experimentally determined spectral function which is proportional to the cross section for annihilation into hadrons. The accuracy of the calculations has therefore followed the progress in the quality of the corresponding data . Because the latter was not always suitable, it was deemed necessary to resort to other sources of information. One such possibility was the use of the vector spectral functions derived from the study of hadronic decays for the energy range less than 1.8 GeV. Another one occurred when it was realized in the study of decays that perturbative QCD could be applied to energy scales as low as 1-2 GeV, thus offering a way to replace poor data in some energy regions by a reliable and precise theoretical prescription [7, 8, 9]. Finally, without any further theoretical assumption, it was proposed to use QCD sum rules [10, 11] in order to improve the evaluation in energy regions dominated by resonances where one has to rely on experimental data. Using these improvements the lowest-order hadronic contribution to was found to be \n\nThe complete theoretical prediction includes in addition QED, weak and higher order hadronic contributions.\nThe anomalous magnetic moment of the muon is experimentally known to very high accuracy. Combined with the older less precise results from CERN , the measurements from the E821 experiment at BNL [13, 14, 15], including the most recent result , yield\n\n aexpμ=(11659203±8) 10−10 , (2)\n\nand are aiming at an ultimate precision of in the future. The previous experimental result was found to deviate from the theoretical prediction by 2.6 , but a large part of the discrepancy was actually originating from a sign mistake in the calculation of the small contribution from the so-called light-by-light (LBL) scattering diagrams [17, 18]. The new calculations of the LBL contribution [19, 20, 21] have reduced the discrepancy to a nonsignificant 1.6 level. At any rate it is clear that the presently achieved experimental accuracy already calls for a more precise evaluation of .\nIn this paper we critically review the available experimental input to vacuum polarization integrals. Such a re-evaluation is necessary because\n\n• new results have been obtained at Novosibirsk with the CMD-2 detector in the region dominated by the resonance with a much higher precision than before, and more accurate R measurements have been performed in Beijing with the BES detector in the 2-5 GeV energy range .\n\n• new preliminary results are available from the final analysis of decays with ALEPH using the full statistics accumulated at LEP1 ; also the information from the spectral functions measured by CLEO [25, 26] and OPAL was not used previously and can be incorporated in the analysis.\n\n• new results on the evaluation of isospin breaking have been produced [28, 29, 30], thus providing a better understanding of this critical area when relating vector and isovector spectral functions.\n\nSince we are mostly dealing with the low energy region, common to both and data, and because of the current interest in the muon magnetic moment prompted by the new experimental result, the emphasis in this paper is on rather than . It is true that the presently achieved accuracy on is meeting the goals for the LEP/SLD/FNAL global electroweak fit. However the situation will change in the long run when very precise determinations of , as could be available from the beam polarization asymmetry at the future Linear Collider, necessitate a significant increase of the accuracy on .\nDisclaimer: ’theoretical’ predictions using vacuum polarization integrals are based on experimental data as input. The data incorporated in this analysis are used as quoted by their authors. In particular, no attempt has been made to re-evaluate systematic uncertainties even if their size was deemed to be questionable in some cases. However, whenever significant incompatibilities between experiments occur, we apply an appropriate rescaling of the combined error. The analysis thus heavily relies on the quality of the work performed in the experiments.\n\n## 2 Muon Magnetic Anomaly\n\nIt is convenient to separate the Standard Model prediction for the anomalous magnetic moment of the muon into its different contributions,\n\nwith\n\nwhere is the pure electromagnetic contribution (see [32, 33] and references therein), is the lowest-order contribution from hadronic vacuum polarization, is the corresponding higher-order part [34, 4], and , where the first error is the hadronic uncertainty and the second is due to the Higgs mass range, accounts for corrections due to exchange of the weakly interacting bosons up to two loops . For the LBL part we add the values for the pion-pole contribution [19, 20, 21] and the other terms [20, 21] to obtain .\nBy virtue of the analyticity of the vacuum polarization correlator, the contribution of the hadronic vacuum polarization to can be calculated via the dispersion integral \n\nwhere is the QED kernel ,\n\n K(s)=x2(1−x22)+(1+x)2(1+1x2)(ln(1+x)−x+x22)+(1+x)(1−x)x2lnx , (6)\n\nwith and . In Eq. (5), denotes the ratio of the ’bare’ cross section for annihilation into hadrons to the pointlike muon-pair cross section. The ’bare’ cross section is defined as the measured cross section, corrected for initial state radiation, electron-vertex loop contributions and vacuum polarization effects in the photon propagator (see Section 4 for details). The reason for using the ’bare’ (i.e. lowest order) cross section is that a full treatment of higher orders is anyhow needed at the level of , so that the use of ’dressed’ cross sections would entail the risk of double-counting some of the higher-order contributions.\nThe function decreases monotonically with increasing . It gives a strong weight to the low energy part of the integral (5). About 91 of the total contribution to is accumulated at center-of-mass energies below 1.8 GeV and 73 of is covered by the two-pion final state which is dominated by the resonance.\n\n## 3 The Input Data\n\n### 3.1 e+e− Annihilation Data\n\nThe exclusive low energy cross sections have been mainly measured by experiments running at colliders in Novosibirsk and Orsay. Due to the high hadron multiplicity at energies above GeV, the exclusive measurement of the respective hadronic final states is not practicable. Consequently, the experiments at the high energy colliders ADONE, SPEAR, DORIS, PETRA, PEP, VEPP-4, CESR and BEPC have measured the total inclusive cross section ratio .\nWe give in the following a compilation of the data used in this analysis:\n\n• The measurements are taken from OLYA [38, 39], TOF , CMD , DM1 and DM2 .\n\nThe most precise data from CMD-2 are now available in their final form . They differ from the preliminary ones, released two years ago , mostly in the treatment of radiative corrections. Compared to the preliminary ones, the new results are corrected (see Section 4) for leptonic and hadronic vacuum polarization, and for photon radiation by the pions (final state radiation – FSR), so that the measured final state corresponds to including pion-radiated photons. The various changes resulted into a reduction of the cross section by about 1% below the peak and 5% above. The dominant contribution stemmed from vacuum polarization, while the (included) FSR correction increased the cross section by about 0.8% in the peak region. The overall systematic error of the final data is quoted to be 0.6% and is dominated by the uncertainties in the radiative corrections (0.4%).\n\nWe do not use the data from NA7 as they are known to suffer from a systematic bias in the energy scale . All the experiments agree with each other within their quoted errors, but the high precision claimed by CMD-2 makes this experiment unique and consequently not cross-checked by the others at that level.\n\nThe comparison between the cross section results from CMD-2 and from previous experiments (corrected for vacuum polarization and FSR, according to the procedure discussed in Section 4) is shown in Fig. 1. Note that the errors bars given contain both statistical and systematic errors, added in quadrature (this is the case for all figures in this paper). The agreement is good within the much larger uncertainties (2-10%) quoted by the older experiments.\n\n• The situation of the data on the and resonances has significantly improved recently [46, 47, 48]. The numerical procedure for integrating their cross sections is described in detail in Section 8.2.\n\n• The cross sections for and not originating from the decay of the and resonances are taken from SND and CMD-2 data in the continuum. They include contributions from and .\n\n• The reaction is dominated by the and intermediate resonances discussed above. The continuum data are taken from ND , DM1 , DM2 , SND and CMD .\n\n• The data are available from M3N , OLYA , ND , DM2 [58, 59, 60], CMD-2 and SND . It is fair to say that large discrepancies are observed between the different results, which are probably related to problems in the calculation of the detection efficiency (the cross sections can be seen in Fig. 9 shown in Section 6.1). The efficiencies are small in general (%) and are affected by uncertainties in the decay dynamics that is assumed in the Monte Carlo simulation. One could expect the more recent experiments (CMD-2 and SND) to be more reliable in this context because of specific studies performed in order to identify the major decay processes involved. Accordingly we do not include the ND data in the analysis.\n\n• The reaction is mainly reconstructed in the final state and is thus already accounted for. It was studied by the collaborations ND , DM2 , CMD-2 and SND [62, 63]. We use these cross section measurements to compute the contribution corresponding to the decay mode.\n\n• The final state was studied by the experiments OLYA , ND , CMD , DM1 [66, 67], DM2 [58, 59, 60], CMD-2 and SND . The experiments agree reasonably well within their quoted uncertainties (see Fig. 9 in Section 6.1).\n\n• The data are taken from M3N and CMD . It contains a contribution from the channel with which has to be treated separately because the decay violates isospin. The other five-pion mode is not measured, but can be accounted for using the isospin relation . The relation is used after subtracting the contribution in the rate. Then the contribution with is added to obtain the full rate.\n\n• For the reaction , measured by the groups DM1 , DM2 and CMD-2 , a contribution is calculated for decaying into . The dominant three-pion decay already appears in the five-pion final state.\n\n• Similarly, the contribution for , with , is taken by isospin symmetry to be half of .\n\n• The process was studied by ND , DM2 and CMD-2 . We subtract from its cross section the contributions which are already counted in the and final states.\n\n• The cross sections of the six-pion final states and were measured by DM1 , CMD and DM2 . For the missing channel one can rely on isospin relations in order to estimate its contribution. If only data are used, the isospin bound is weak, leading to a possibly large contribution with an equally large uncertainty. However, some information can be found in the isospin-rotated processes222Throughout this paper, charge conjugate states are implied for decays. and , where the hadronic system has been shown to be dominated by and , once the axial-vector and contributions are discarded. An isospin analysis then reveals the dominance of the final state. As a consequence the channel in annihilation only receives a very small contribution, determined by the cross section. We include a component for .\n\n• The and cross sections above the resonance are taken from OLYA , DM1 , DM2 , CMD and CMD-2 .\n\n• The reactions and were studied by DM1 [79, 80] and DM2 . Using isospin symmetry the cross section of the final state is obtained from the relation .\n\n• The inclusive reaction + was analyzed by DM1 . After subtracting from its cross section the separately measured contributions of the final states , and , it still includes the modes , and . With the assumption that the cross sections for the processes and are equal, one can summarize the total contribution as twice the above corrected + cross section. Implied by the assumption made, it is reasonable to quote as the systematic uncertainty one-half of the cross section for the channel measured by DM1 and DM2 .\n\n• Baryon-pair production is included using the cross sections for from DM1 and DM2 , and for from FENICE .\n\n• At energies larger than 2 GeV the total cross section ratio is measured inclusively. Data are provided by the experiments , MARK I , DELCO , DASP , PLUTO , LENA , Crystal Ball [92, 93], MD-1 , CELLO , JADE , MARK-J , TASSO , CLEO , CUSB , MAC , and BES . Due to their weak experimental precision, the data of are not used in this analysis. The measurements of the MARK I Collaboration are significantly higher than those from more recent and more precise experiments. In addition, the QCD prediction of , which should be reliable in this energy regime, favours lower values, in agreement with the other experiments. Consequently the MARK I results on have been discarded.\n\nAlthough small, the enhancement of the cross section due to interference is corrected for energies above the mass. We use a factorial ansatz according to Ref. [102, 3], yielding a negligible contribution to .\n\nThe data in the charm region are displayed in Fig. 2. Good agreement is found among the experiments.\n\n• The narrow and resonances are treated in Section 8.3.\n\n### 3.2 Data from Hadronic τ Decays\n\nData from decays into two- and four-pion final states , and , are available from ALEPH , CLEO [25, 26] and OPAL . Very recently, preliminary results on the full LEP1 statistics have been presented by ALEPH . They agree with the published results, but correspond to a complete reanalysis with refined systematic studies allowed by the 2.5 times larger data set. The branching fraction for the decay mode is of particular interest since it provides the normalization of the corresponding spectral function. The new value , , turns out to be larger than the previously published one based on the 1991-93 LEP1 statistics, .\nAssuming (for the moment) isospin invariance to hold, the corresponding isovector cross sections are calculated via the CVC relations\n\n σI=1e+e−→π+π− = 4πα2svπ−π0 , (7) σI=1e+e−→π+π−π+π− = 2⋅4πα2svπ−3π0 , (8) σI=1e+e−→π+π−π0π0 = 4πα2s[v2π−π+π0−vπ−3π0] . (9)\n\nThe spectral function for a given vector hadronic state is defined by \n\n vV(s)≡m2τ6|Vud|2SEWB(τ−→ντV−)B(τ−→ντe−¯νe)dNVNVds[(1−sm2τ)2(1+2sm2τ)]−1, (10)\n\nwhere is obtained from averaging333 Since the two determinations, and are not consistent, the final error has been enlarged correspondingly. the two independent determinations from nuclear decays and kaon decays (assuming unitarity of the CKM matrix) and accounts for electroweak radiative corrections as discussed in Section 5.1. The spectral functions are obtained from the corresponding invariant mass distributions, after subtracting out the non- background and the feedthrough from other decay channels, and after a final unfolding from detector effects such as energy and angular resolutions, acceptance, calibration and photon identification.\nIt is important to note that decay experiments measure decay rates that include the possibility of photon radiation in the decay final state. Depending on the experiment, the analysis may (ALEPH) or may not (CLEO) keep events with radiative photons in the final state, but all experiments rely on the TAUOLA decay library to compute their efficiencies. In TAUOLA charged particles are given a probability to produce bremsstrahlung using the PHOTOS procedure which is based on the leading logarithm approximation valid at low photon energy. Thus the measured spectral functions correspond to given final states inclusive with respect to radiative photons in the decay.\nIt should be pointed out that the experimental conditions at (ALEPH, OPAL) and (CLEO) energies are very different. On the one hand, at LEP, the events can be selected with high efficiency () and small non- background (), thus ensuring little bias in the efficiency determination. The situation is not as favorable at lower energy: because the dominant hadronic cross section has a smaller particle multiplicity, it is more likely to pollute the sample and strong cuts must be applied, hence resulting in smaller efficiencies. On the other hand, CLEO has an advantage for the reconstruction of the decay final state since particles are more separated in space. The LEP detectors have to cope with collimated decay products and the granularity of the detectors, particularly the calorimeters, plays a crucial role. One can therefore consider ALEPH/OPAL and CLEO data to be approximately uncorrelated as far as experimental procedures are concerned. The fact that their respective spectral functions for the and modes agree, as demonstrated in Fig. 3 for , is therefore a valuable experimental consistency test.\n\n## 4 Radiative Corrections for e+e− Data\n\nRadiative corrections applied to the measured cross sections are an important step in the experimental analyses. They involve the consideration of several physical processes and lead to large corrections. We stress again that the evaluation of the integral in Eq. (5) requires the use of the ’bare’ hadronic cross section, so that the input data must be analyzed with care in this respect.\nSeveral steps are to be considered in the radiative correction procedure:\n\n• Corrections are applied to the luminosity determination, based on large-angle Bhabha scattering and muon-pair production in the low-energy experiments, and small-angle Bhabha scattering at high energies. These processes are usually corrected for external radiation, vertex corrections and vacuum polarization from lepton loops.\n\n• The hadronic cross sections given by the experiments are always corrected for initial state radiation and the effect of loops at the electron vertex.\n\n• The vacuum polarization correction in the photon propagator is a more delicate point. The cross sections need to be fully corrected for our use, i.e.\n\n σbare=σdressed(α(0)α(s))2 , (11)\n\nwhere is the measured cross section already corrected for initial state radiation, and is obtained from resummation of the lowest-order evaluation\n\nWhereas can be analytically calculated (here given to leading order)\n\n Δαlep(s)=α(0)3π∑l(logsm2l−53) , (13)\n\nis related by analyticity and unitarity to a dispersion integral, akin to (5),\n\nwhich must also be evaluated using input data. Since the hadronic correction involves the knowledge of at all energies, including those where the measurements are made, the procedure has to be iterative, and requires experimental as well as theoretical information over a large energy range.\n\nThis may explain why the vacuum polarization correction is in general not applied by the experiments to their published cross sections. Here the main difficulty is even to find out whether the correction (and which one? leptonic at least? hadronic?) has actually been used, as unfortunately this is almost never clearly stated in the publications. The new data from CMD-2 are explicitly corrected for both leptonic and hadronic vacuum polarization effects, whereas the preliminary data from the same experiment were not.\n\nIn fact, what really matters is the correction to the ratio of the hadronic cross section to the cross section for the process used for the luminosity determination. In the simplest case (for example, DM2 for the channel) of the normalization to the process, the vacuum polarization effects cancel. However, generally the normalization is done with respect to large angle Bhabha scattering events or to both Bhabha and . In the latter case, Bhabha events dominate due to the -channel contribution. In the mode, all experiments before the latest CMD-2 results corrected their measured processes (, and ) for radiative effects using calculations which took only leptonic vacuum polarization into account [108, 109]. For the other channels, it is harder to find out as information about the luminosity determination and the detailed procedure for radiative corrections is in general not given in the publications.\n\nFor all experimental results, but the newest from CMD-2 and DM2, we apply a correction for the missing hadronic vacuum polarization given by \n\nwhere the correction in the denominator applies to the Bhabha cross section evaluated at a mean value of the squared momentum transfer , which depends on the angular acceptance in each experiment. A uncertainty is assigned to . For the and resonance cross sections, we were informed that the recent CMD-2 and SND results were not corrected for leptonic vacuum polarization, so in their case we applied a full correction taking into account both leptonic and hadronic components.\n\n• In Eq. (5) one must incorporate in the contributions of all hadronic states produced at the energy . In particular, radiative effects in the hadronic final state must be considered, i.e., final states such as have to be included.\n\nInvestigating the existing data in this respect is also a difficult task. In the data from CMD-2 most additional photons are experimentally rejected to reduce backgrounds from other channels and the fraction kept is subtracted using the Monte Carlo simulation which includes a model for FSR. Then the full FSR contribution is added back as a correction, using an analytical expression computed in scalar QED (point-like pions) . As this effect was not included in earlier analyses, we applied the same correction to older data.\n\nIn principle one must worry about FSR effects in other channels as well. For the inclusive measurements it is included by definition. When is evaluated from QCD at high energy, the prediction must be corrected for FSR from the quarks, but this is a negligible effect for . The situation for the exclusive channels is less clear because it depends on the experimental cuts and whether or not FSR is included in the simulation. Taking as an educated guess the effect in the channel, we correspondingly correct the contributions to from all remaining exclusive channels by the factor where is the charged particle multiplicity in the final state.\n\nIn summary, we correct each experimental result, but those from CMD-2 , by the factor . As an illustration of the orders of magnitude involved, the different corrections in the contribution amount to for the leptonic vacuum polarization, for the hadronic vacuum polarization, and for the FSR correction. The correction to the / ratio from the missing hadronic vacuum polarization is small, typically . Both the vacuum polarization and FSR corrections apply only to experiments other than CMD-2, therefore the overall correction to the channel is considerably reduced.\nThe uncertainties on the missing vacuum polarization () and the FSR corrections () are conservatively considered to be fully correlated between all channels to which the correction applies. The total error from these missing radiative corrections, taken as the quadratic sum of the two contributions, is given separately for the final results.\n\n## 5 Isospin Breaking in e+e− and τ Spectral Functions\n\n### 5.1 Sources of Isospin Symmetry Breaking\n\nThe relationships (7), (8) and (9) between and spectral functions only hold in the limit of exact isospin invariance. This is the Conserved Vector Current (CVC) property of weak decays. It follows from the factorization of strong interaction physics as produced through the and propagators out of the QCD vacuum. However, we know that we must expect symmetry breaking at some level from electromagnetic effects and even in QCD because of the up and down quark mass splitting. Since the normalization of the spectral functions is experimentally known at the 0.5% level, it is clear that isospin-breaking effects must be carefully examined if one wants this precision to be maintained in the vacuum polarization integrals. Various identified sources of isospin breaking are considered in this section and discussed in turn.\nBecause of the dominance of the contribution in the energy range of interest for data, we discuss mainly this channel, following our earlier analysis . The corrections on from isospin breaking are given in Table 1. A more complete evaluation is given in the next section. Finally, the 4-pion modes will be briefly discussed.\n\n• Electroweak radiative corrections must be taken into account. Their dominant contribution comes from the short distance correction to the effective four-fermion coupling enhancing the amplitude by the factor , where is the average charge of the final state partons . While this correction vanishes for leptonic decays, it contributes for quarks. All higher-order logarithms can be resummed using the renormalization group [112, 113], and the short distance correction can be absorbed into an overall multiplicative electroweak correction ,\n\n (16)\n\nwhich is equal to 1.0194 when using the current fermion and boson masses and for consistency the quark-level expressions for as given in Ref. . The difference between the resummed value and the lowest-order estimate (1.0188) can be taken as a conservative estimate of the uncertainty. QCD corrections to have been calculated [112, 116] and found to be small, reducing its value to 1.0189.\n\nSubleading non-logarithmic short distance corrections have been calculated to order at the quark level , , and for the leptonic width , . Summing up all the short distance corrections, one obtains the value for that must be used for the inclusive hadronic width\n\nOther uncertainties on the quark mass, the running of , and QCD corrections are at the level.\n\nLong distance corrections are expected to be final-state dependent in general. They have been computed for the decay leading to a total radiative correction of 2.03 , which is dominated by the leading logarithm from the short distance contribution. Although very encouraging, this result may not apply to all hadronic decays, in particular for the important mode. Therefore an uncertainty of 0.0040 was previously assigned to (see the following Section 5.2 for more) to cover the final-state dependence of the correction with respect to the calculation at the quark level.\n\n• A contribution [28, 4] for isospin breaking occurs because of the mass difference between charged and neutral pions, which is essentially of electromagnetic origin. The spectral function has a kinematic factor which is different in () and decay (). We write\n\n v0(s) = β30(s)12|F0π(s)|2 , (18) v−(s) = β3−(s)12|F−π(s)|2 , (19)\n\nwith obvious notations, being the electromagnetic and weak pion form factors, respectively, and defined by\n\n β0,−=β(s,mπ−,mπ0,−) , (20)\n\nwhere\n\n β(s,m1,m2)=[(1−(m1+m2)2s)(1−(m1−m2)2s)]1/2 . (21)\n\nHence, a correction equal to is applied to the spectral function.\n\n• Other corrections occur in the form factor itself. It turns out that it is affected by the pion mass difference because the same factor enters in the width. This effect partially compensates the corrections (18), (19) of the cross section, as seen in Table 1.\n\n• Similarly a possible mass difference between the charged and neutral meson affects the value of the corresponding width and shifts the resonance lineshape. Theoretical estimates and experimental determinations [5, 120] show that the mass difference is compatible with zero within about 1 MeV.\n\n• interference occurs in the mode and thus represents an obvious source of isospin symmetry breaking. Its contribution can be readily introduced into the spectral function using the parameters determined in the CMD-2 fit . The integral over the interference almost vanishes by itself since it changes sign at the mass, however the -dependent integration kernel produces a net effect (Table 1).\n\n• Electromagnetic decays explicitly break SU(2) symmetry. This is the case for the decays through an intermediate state because of identical ’s, , and . The decay deserves particular attention: calculations have been done with an effective model for both charged and neutral ’s. The different contributions are listed in Table 1.\n\n• A breakdown of CVC is due to quark mass effects: different from generates for a charge-changing hadronic current between and quarks. Expected deviations from CVC due to so-called second class currents such as, e.g., the decay where the corresponding final state (C=+1) is forbidden, lead to an estimated branching fraction of the order of , while the experimental upper limit amounts to .\n\n### 5.2 A More Elaborate Treatment of Isospin Breaking in the 2π Channel\n\nThe above analysis of isospin breaking leaves out the possibility of sizeable contributions from virtual loops. This problem was studied recently within a model based on Chiral Perturbation Theory. In this way the correct low-energy hadronic structure is implemented and a consistent framework can be set up to calculate electroweak and strong processes, such as the radiative corrections in the decay. One might worry that the mass is too large for such a low-energy approach. However a reasonable matching with the resonance region and even beyond is claimed to be achieved, providing a very useful tool to study radiative decays.\nA new analysis has been issued which is more suited to our purpose, in the sense that it applies to the inclusive radiative rate, , as measured by the experiments. A consistent calculation of radiative corrections is presented including real photon emission and the effect of virtual loops. All the contributions listed in the previous section are included and the isospin-breaking contributions in the pion form factor are now more complete. Following Ref. , the relation between the Born level spectral function and the spectral function (19) reads\n\n vπ+π−(s)=1GEM(s)β30β3−∣∣∣F0π(s)F−π(s)∣∣∣2vπ−π0(γ)(s) , (22)\n\nwhere is the long-distance radiative correction involving both real photon emission and virtual loops (the infrared divergence cancels in the sum). Note that the short-distance correction, discussed above, is already applied in the definition of (cf. Eq. (10)), but its value differs from Eq. (17) because subleading quark-level and hadron-level contributions should not be added, as double counting would occur. The correct expression for the mode therefore reads\n\nthe subleading hadronic corrections being now incorporated in the mass-dependent factor. The form factor correction is dominated by the effect of the pion mass difference in the width, but it also includes a small contribution at the level from the ’chiral’ form used for the lineshape. In practice, however, the correction is independent of the chosen parametrization of the form factor. The different contributions to the isospin-breaking corrections are shown in the second column of Table 1. The values slightly differ from those given in Ref. because the authors use a model for the pion form factor rather than integrating experimental data. The largest difference however stems from our re-evaluation of the short-distance electroweak correction, , including the subleading leptonic contribution. The sum amounts to to be compared with given in Ref. .\nThe dominant uncertainty in this method stems from the - mass difference. Indeed, in the chiral model used in Ref. the only parameter entering the pion form factor is the mass, since the width is given by . In the method previously used and recalled in Section 5.1, the width at the pole was taken as an independent parameter with , so that the effect of the mass difference approximately cancels after integration. This explains the large difference in the uncertainties quoted for the two evaluations in Table 1.\nSince the integral (5) requires as input the spectral function including FSR photon emission, a final correction is necessary. It is identical to that applied in the CMD-2 analysis [22, 111] (cf. Section 4). All the corrections are drawn versus in Fig. 4. The overall correction reduces the rate below the peak, but, somewhat unexpectedly, has the opposite effect above. This behavior is driven by the long-distance radiative corrections contained in .\n\nThe total correction to the result in this method, not including the FSR contribution, amounts to , where the main contribution to the error is due to the experimental limits on the mass difference. After including the FSR contribution, it becomes , a value consistent with the result in the first column of Table 1 which does not include the virtual corrections and uses a less sophisticated treatment of radiative decays. In the following we apply the correction functions from the more complete analysis (method (II) in Table 1) and keep the corresponding uncertainty separate from the purely experimental errors.\n\n### 5.3 Isospin Breaking in 4π Channels\n\nThere exists no comparable study of isospin breaking in the channels. Only kinematic corrections resulting from the pion mass difference have been considered so far , which we have applied in this analysis. It creates shifts of () and () for and , respectively. However, since the four-pion contribution to is relatively less important than the two-pion part (by a little more than an order of magnitude in the integration range up to 1.8 GeV) and the experimental uncertainties are much larger, we feel this is a justified procedure at the present level of accuracy of the data. Moreover, the entire correction has been attributed as systematic error which is kept separate from the experimental errors on from these channels.\n\nIt should also be pointed out that the systematic uncertainties from isospin breaking are essentially uncorrelated between the and modes: as Table 1 shows, the dominant sources of uncertainties are the - mass difference for and the threshold factors in where large errors have been given to cover uncertainties in the decay dynamics and the missing pieces.\n\n## 6 Comparison of e+e− and τ Spectral Functions\n\nThe and the isospin-breaking corrected spectral functions can be directly compared for the dominant and final states. For the channel, the -dominated form factor falls off very rapidly at high energy so that the comparison can be performed in practice over the full energy range of interest. The situation is different for the channels where the decay kinematics limits the exercise to energies less than 1.6 GeV, with only limited statistics beyond.\n\n### 6.1 Direct Comparison\n\nFig. 5 shows the comparison for the spectral functions. Visually, the agreement seems satisfactory, however the large dynamical range involved does not permit an accurate test. To do so, the data are plotted as a point-by-point ratio to the spectral function in Fig. 7, and enlarged in Fig. 7, to better emphasize the region of the peak444 The central bands in Figs. 7 and 7 give the quadratic sum of the statistical and systematic errors of the combined spectral functions. Local bumps in these bands stem from increased errors when combining different experiments having local inconsistencies. We use the procedure described in Section 7.1. . The data are significantly lower by 2-3% below the peak, the discrepancy increasing to about 10% in the 0.9-1.0 GeV region.\nThe comparison for the cross sections is given in Fig. 9 for the channel and in Fig. 9 for . As noted before, the latter suffers from large differences between the results from the different experiments. The data, combining two measured spectral functions according to Eq. (9) and corrected for isospin breaking as discussed in Section 5, lie somewhat in between with large uncertainties above 1.4 GeV because of the lack of statistics and a large feedthrough background in the mode. In spite of these difficulties the spectral function is in agreement with data as can be seen in Fig. 9. It is clear that intrinsic discrepancies exist among the experiments and that a quantitative test of CVC in the channel is premature.\n\n### 6.2 Branching Ratios in τ Decays and CVC\n\nA convenient way to assess the compatibility between and spectral functions proceeds with the evaluation of decay fractions using the relevant spectral functions as input. All the isospin-breaking corrections detailed in Section 5.2 are included. The advantage of this procedure is to allow a quantitative comparison using a single number. The weighting of the spectral function is however different from the vacuum polarization kernels. Using the branching fraction , obtained assuming leptonic universality in the charged weak current , the results for the main channels are given in Table 2. The errors quoted for the CVC values are split into uncertainties from (i) the experimental input (the annihilation cross sections) and the numerical integration procedure, (ii) the missing radiative corrections applied to the relevant data, and (iii) the isospin-breaking corrections when relating and spectral functions. The values for the branching ratios involve measurements [24, 124, 125] given without charged hadron identification, i.e. for the , and final states. The corresponding channels with charged kaons have been measured [126, 127] and their contributions can be subtracted out in order to obtain the pure pionic modes."
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https://blogs.ams.org/visualinsight/2016/04/15/barth-sextic/ | [
"# Barth Sextic\n\nA sextic surface is one defined by a polynomial equation of degree 6. The Barth sextic, drawn above by Craig Kaplan, is the sextic surface with the maximum possible number of ordinary double points: that is, points where it looks like the origin of the cone in 3-dimensional space defined by\n\n$$x^2 + y^2 = z^2 .$$\n\nIn 1946, Francesco Severi claimed that 52 is the maximum number of ordinary double points possible for a sextic surface. This was refuted in 1994 when Wolf Barth discovered what is now called the Barth sextic, which has 65 double points:\n\n• Wolf Barth, Two projective surfaces with many nodes, admitting the symmetries of the icosahedron, Journal of Algebraic Geometry 5 (1994), 173–186.\n\nIn 1997, David B. Jaffe and Daniel Ruberman proved that 65 is the maximum number of double points for a sextic surface that has no singularities other than nodes, which are a generalization of double points:\n\n• David B. Jaffe, and Daniel Ruberman, A sextic surface cannot have 66 nodes, Journal of Algebraic Geometry 6 (1997), 151–168.\n\nNot all sextics with 65 double points have icosahedral symmetry, but as Barth noted in the title of his paper, his does! 20 of the double points lie at the vertices of a regular dodcahedron, and 30 lie at the midpoints of the edges of another, concentric, regular dodecahedron. To see this more clearly, look at the beautiful animations here:\n\n• Hermann Serras, Barth’s sextic surface and two associated regular dodecahedra.\n\nThat accounts for 50 of the 65 double points. Where are the other 15? They are hiding at ‘points at infinity’. To understand this, and to bring them into view, we need to dig a bit deeper into the geometry.\n\nA sextic surface is defined by a homogeneous polynomial equation of degree 6. This equation determines a subset $S \\subset \\mathbb{C}^4$ with complex dimension 2. Note that if $(x_1, \\dots, x_4) \\in \\mathbb{C}^4$ is a solution, so is any multiple $(cx_0, \\dots , cx_4)$. We may thus projectivize $S$, treating any solution as ‘the same’ as any multiple of that solution. The result is an algebraic variety $X$ in the complex projective space $\\mathbb{C}\\mathrm{P}^3$. This is a smooth manifold of complex dimension 2, so it is called a smooth surface. To obtain an ordinary real 2-dimensional surface we may take its intersection with a copy of $\\mathbb{R}\\mathrm{P}^3$ in $\\mathbb{C}\\mathrm{P}^3$.\n\nSitting inside $\\mathbb{R}\\mathrm{P}^3$ we have ordinary 3-dimensional space, $\\mathbb{R}^3$. But we also have ‘points at infinity’. If you march off in either of two opposite directions in $\\mathbb{R}^3$, you will approach one of these points at infinity. The points at infinity form a projective plane, that is, a copy of $\\mathbb{R}\\mathrm{P}^2$.\n\nThe Barth sextic is usually described by the sextic equation\n\n$$4(\\Phi^2 x^2-y^2)(\\Phi^2 y^2 – z^2)(\\Phi^2 z^2-x^2) – (1+2\\Phi)(x^2+y^2+z^2-w^2)^2 w^2 = 0$$\n\nwhere\n\n$$\\Phi = \\frac{\\sqrt{5} + 1}{2}$$\n\nis the ‘large’ golden ratio.\n\nWith a standard choice of $\\mathbb{R}^3$ inside $\\mathbb{R}\\mathrm{P}^3$, 15 of the double points of this surface lie at infinity. You can reach them by taking either of the aforementioned dodecahedra, drawing lines between the midpoints of its 15 pairs of opposite edges, and following these lines to infinity!\n\nWe can bring these double points into view by rotating $\\mathbb{R}\\mathrm{P}^3$ slightly. Then we get a view like this, drawn by Abdelaziz Nait Merzouk:\n\nIn this view, the Barth sextic has also been sliced by a plane, to make its inside visible.\n\nMerzouk has also brought the double points at infinity into view using a transformation that compresses all of $\\mathbb{R}^3$ down to the unit ball. Then these double points lie on the unit sphere:\n\nHowever, we must count antipodal points on the sphere as the same point in $\\mathbb{R}\\mathrm{P}^2$. So, the 30 double points you see on the unit sphere above give 15 points at infinity.\n\nFor other views, see:\n\n• Abdelaziz Nait Merzouk, Barth sextic.\n\nJaffe and Ruberman actually proved that a sextic surface with only nodes as singularities cannot have more than 65 nodes. Their proof uses coding theory in an intriguing way. They show that an ‘even’ set of nodes (see their paper for the definition) gives rise to a binary linear code: that is, a linear subspace of $\\mathbb{F}_2^n$, where $n$ is the number of nodes. Their proof then uses a mixture of algebraic geometry and coding theory.\n\nThis is another picture of the Barth sextic, obtained here:\n\n• Oliver Labs, Gallery of surfaces, Imaginary: Open Mathematics.\n\nVisual Insight is a place to share striking images that help explain advanced topics in mathematics. I’m always looking for truly beautiful images, so if you know about one, please drop a comment here and let me know!\n\n## 4 thoughts on “Barth Sextic”\n\n1.",
null,
"Michael Nelson says:\n\nI think I can see how the dodecahedron is involved. First, dehomogenize by setting w = 1. Then if you assume that x,y,z lie on the the unit sphere in R^3, the second term in the equation vanishes, and what you are left with is six lines. I think you’ll get a picture that looks like this:\n\nhttp://myweb.tiscali.co.uk/oaktree/butterfly/backpages/pics/great-circles/icosa/XT_Icosa_F1_Sphere_PPT.jpg\n\nI got this picture from this website:\n\n2.",
null,
"Andreas Daniel says:\n\nWith the free software SURFER you can visualize/manipulate the Barth Sextic in real time (zoom in/out, rotate it, change parameters, change the equation, etc.).\n\nThe program is available at:\nhttp://imaginary.org/program/surfer\n\nYou will find the Barth Sextic in the “World record surfaces” gallery. There you will find other surfaces with maximum possible numbers of double points (also ones, which are not yet proven to be the “maximum” ones).\n\n•",
null,
"John Baez says:\n\nCool!\n\nI don’t see the “world record surfaces” gallery.\n\n•",
null,
"Andreas Daniel says:\n\nDear John,\n\njust click on the “Start” button and you will see three galleries (Tutorial, Fantasy and World Record Surfaces). There you will find the double point world record quadrics, cubics, quartics, sextics, septics, octics, etc.\n\nEnjoy! And thanks for the great article!"
] | [
null,
"https://secure.gravatar.com/avatar/80214fc45aa81137288a6415e741c3bc",
null,
"https://secure.gravatar.com/avatar/4a3149a3377a5721bf7768229079df61",
null,
"https://secure.gravatar.com/avatar/34784534843022b3541c8ddd693718cb",
null,
"https://secure.gravatar.com/avatar/4a3149a3377a5721bf7768229079df61",
null
] | {"ft_lang_label":"__label__en","ft_lang_prob":0.88671273,"math_prob":0.98825675,"size":6223,"snap":"2022-40-2023-06","text_gpt3_token_len":1659,"char_repetition_ratio":0.1312108,"word_repetition_ratio":0.004052685,"special_character_ratio":0.25389683,"punctuation_ratio":0.12228479,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.9952404,"pos_list":[0,1,2,3,4,5,6,7,8],"im_url_duplicate_count":[null,null,null,null,null,null,null,null,null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2023-01-28T09:13:33Z\",\"WARC-Record-ID\":\"<urn:uuid:21b62e96-a4c5-41ed-ab02-0b8fe0901677>\",\"Content-Length\":\"67723\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:2297433f-adea-4f92-b89c-21bf153857d6>\",\"WARC-Concurrent-To\":\"<urn:uuid:399005d1-dcf0-4621-9581-387a70eadd13>\",\"WARC-IP-Address\":\"130.44.204.215\",\"WARC-Target-URI\":\"https://blogs.ams.org/visualinsight/2016/04/15/barth-sextic/\",\"WARC-Payload-Digest\":\"sha1:2PYBFRZVWUJY3WOTWZNRAKPYSGLYZYUG\",\"WARC-Block-Digest\":\"sha1:67YNFZ2Q4EPMT5RKWLQZK7RHSVY5ZMSW\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2023/CC-MAIN-2023-06/CC-MAIN-2023-06_segments_1674764499541.63_warc_CC-MAIN-20230128090359-20230128120359-00475.warc.gz\"}"} |
https://blog.lcrun.com/step-by-step-write-algorithm-of-cycle-and-recursion/ | [
"May 31, 2016\n\n# 一步一步写算法之循环和递归\n\n## 求和递归函数\n\n``````int calculate(int m)\n{\nint count = 0;\nif(m <0)\nreturn -1;\n\nfor(int index = 0; index <= m; index++)\ncount += index;\n\nreturn count;\n}\n``````\n\n``````int calculate(int m)\n{\nif(m == 0)\nreturn 0;\nelse\nreturn calculate(m -1) + m;\n}\n``````\n\n1. 第一段代码从0,开始计算,从0到m逐步计算;第二段代码是从10开始计算,逐步到0之后这回,这样同样可以达到计算的效果\n2. 第一段代码不需要重复的压栈操作,第二段需要重复的函数操作,当然这也是递归的本质\n3. 第一段代码比较长,第二段代码较短\n\n## 查找递归函数\n\n``````int find(int array[], int length, int value)\n{\nint index = 0;\nif(NULL == array || 0 == length)\nreturn -1;\n\nfor(; index < length; index++)\n{\nif(value == array[index])\nreturn index;\n}\nreturn -1;\n}\n``````\n\n``````int _find(int index, int array[], int length, int value)\n{\nif(index == length)\nreturn -1;\n\nif(value == array[index])\nreturn index;\n\nreturn _find(index + 1, array, length, value);\n}\n\nint find(int array[], int length, int value)\n{\nif(NULL == array || length == 0)\nreturn -1;\n\nreturn _find(0, array, length, value);\n}\n``````\n\n## 指针变量遍历\n\n``````typedef struct _NODE\n{\nint data;\nstruct _NODE* next;\n}NODE;\n``````\n\n``````void print(const NODE* pNode)\n{\nif(NULL == pNode)\nreturn;\n\nwhile(pNode){\nprintf(\"%dn\", pNode->data);\npNode = pNode->next;\n}\n}\n``````\n\n``````void print(const NODE* pNode)\n{\nif(NULL == pNode)\nreturn;\nelse\nprintf(\"%dn\", pNode->data);\n\nprint(pNode->next);\n}\n``````"
] | [
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] | {"ft_lang_label":"__label__zh","ft_lang_prob":0.7054432,"math_prob":0.99964786,"size":1654,"snap":"2021-43-2021-49","text_gpt3_token_len":927,"char_repetition_ratio":0.15757576,"word_repetition_ratio":0.11518325,"special_character_ratio":0.286578,"punctuation_ratio":0.16176471,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.9980677,"pos_list":[0],"im_url_duplicate_count":[null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2021-10-24T10:16:19Z\",\"WARC-Record-ID\":\"<urn:uuid:dcdab371-e3f5-48c0-b2f4-3cd54ebeceae>\",\"Content-Length\":\"21295\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:cd57b5d9-d2e4-423d-8f92-fae71aa18892>\",\"WARC-Concurrent-To\":\"<urn:uuid:8caac7e5-aff9-46f8-8948-b0de39dc656a>\",\"WARC-IP-Address\":\"42.193.175.138\",\"WARC-Target-URI\":\"https://blog.lcrun.com/step-by-step-write-algorithm-of-cycle-and-recursion/\",\"WARC-Payload-Digest\":\"sha1:QITSMBPPRC34MQ35ZX3TFD5AF272RZG2\",\"WARC-Block-Digest\":\"sha1:GELWAYDXGH32GLYBZYUR2IN65MUEJR5M\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2021/CC-MAIN-2021-43/CC-MAIN-2021-43_segments_1634323585916.29_warc_CC-MAIN-20211024081003-20211024111003-00396.warc.gz\"}"} |
https://www.opencascade.com/doc/occt-6.9.1/refman/html/class_b_rep_builder_a_p_i___find_plane.html | [
"BRepBuilderAPI_FindPlane Class Reference\n\nDescribes functions to find the plane in which the edges of a given shape are located. A FindPlane object provides a framework for: More...\n\n`#include <BRepBuilderAPI_FindPlane.hxx>`\n\n## Public Member Functions\n\nBRepBuilderAPI_FindPlane ()\nInitializes an empty algorithm. The function Init is then used to define the shape. More...\n\nBRepBuilderAPI_FindPlane (const TopoDS_Shape &S, const Standard_Real Tol=-1)\nConstructs the plane containing the edges of the shape S. A plane is built only if all the edges are within a distance of less than or equal to tolerance from a planar surface. This tolerance value is equal to the larger of the following two values: More...\n\nvoid Init (const TopoDS_Shape &S, const Standard_Real Tol=-1)\nConstructs the plane containing the edges of the shape S. A plane is built only if all the edges are within a distance of less than or equal to tolerance from a planar surface. This tolerance value is equal to the larger of the following two values: More...\n\nStandard_Boolean Found () const\nReturns true if a plane containing the edges of the shape is found and built. Use the function Plane to consult the result. More...\n\nHandle< Geom_PlanePlane () const\nReturns the plane containing the edges of the shape. Warning Use the function Found to verify that the plane is built. If a plane is not found, Plane returns a null handle. More...\n\n## Detailed Description\n\nDescribes functions to find the plane in which the edges of a given shape are located. A FindPlane object provides a framework for:\n\n• extracting the edges of a given shape,\n• implementing the construction algorithm, and\n• consulting the result.\n\n## Constructor & Destructor Documentation\n\n BRepBuilderAPI_FindPlane::BRepBuilderAPI_FindPlane ( )\n\nInitializes an empty algorithm. The function Init is then used to define the shape.\n\n BRepBuilderAPI_FindPlane::BRepBuilderAPI_FindPlane ( const TopoDS_Shape & S, const Standard_Real Tol = `-1` )\n\nConstructs the plane containing the edges of the shape S. A plane is built only if all the edges are within a distance of less than or equal to tolerance from a planar surface. This tolerance value is equal to the larger of the following two values:\n\n• Tol, where the default value is negative, or\n• the largest of the tolerance values assigned to the individual edges of S. Use the function Found to verify that a plane is built. The resulting plane is then retrieved using the function Plane.\n\n## Member Function Documentation\n\n Standard_Boolean BRepBuilderAPI_FindPlane::Found ( ) const\n\nReturns true if a plane containing the edges of the shape is found and built. Use the function Plane to consult the result.\n\n void BRepBuilderAPI_FindPlane::Init ( const TopoDS_Shape & S, const Standard_Real Tol = `-1` )\n\nConstructs the plane containing the edges of the shape S. A plane is built only if all the edges are within a distance of less than or equal to tolerance from a planar surface. This tolerance value is equal to the larger of the following two values:\n\n• Tol, where the default value is negative, or\n• the largest of the tolerance values assigned to the individual edges of S. Use the function Found to verify that a plane is built. The resulting plane is then retrieved using the function Plane.\n Handle< Geom_Plane > BRepBuilderAPI_FindPlane::Plane ( ) const\n\nReturns the plane containing the edges of the shape. Warning Use the function Found to verify that the plane is built. If a plane is not found, Plane returns a null handle.\n\nThe documentation for this class was generated from the following file:"
] | [
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] | {"ft_lang_label":"__label__en","ft_lang_prob":0.80318034,"math_prob":0.8976546,"size":2822,"snap":"2019-51-2020-05","text_gpt3_token_len":667,"char_repetition_ratio":0.15294535,"word_repetition_ratio":0.80794704,"special_character_ratio":0.22324592,"punctuation_ratio":0.13085938,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.9818908,"pos_list":[0],"im_url_duplicate_count":[null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2020-01-18T06:48:28Z\",\"WARC-Record-ID\":\"<urn:uuid:2e0a81be-ebbb-4739-a716-058fc1dcfb56>\",\"Content-Length\":\"14953\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:c2f0b785-cf65-4cbc-8ae6-550e133c5fcc>\",\"WARC-Concurrent-To\":\"<urn:uuid:665203c3-533a-44e9-a50b-a3c740324d8f>\",\"WARC-IP-Address\":\"188.165.114.136\",\"WARC-Target-URI\":\"https://www.opencascade.com/doc/occt-6.9.1/refman/html/class_b_rep_builder_a_p_i___find_plane.html\",\"WARC-Payload-Digest\":\"sha1:CSY4OOFOVP2XNXFX4DQUPEOYLQIVRXIL\",\"WARC-Block-Digest\":\"sha1:2EBLXN3MYRFTSXGYDDBR5KWYQ3FHOMD3\",\"WARC-Identified-Payload-Type\":\"application/xhtml+xml\",\"warc_filename\":\"/cc_download/warc_2020/CC-MAIN-2020-05/CC-MAIN-2020-05_segments_1579250592261.1_warc_CC-MAIN-20200118052321-20200118080321-00535.warc.gz\"}"} |
https://www.convertunits.com/from/half+US+gallon/to/litre | [
"## ››Convert half US gallon to liter\n\n half US gallon litre\n\nHow many half US gallon in 1 litre? The answer is 0.52834410527459.\nWe assume you are converting between half US gallon and liter.\nYou can view more details on each measurement unit:\nhalf US gallon or litre\nThe SI derived unit for volume is the cubic meter.\n1 cubic meter is equal to 528.34410527459 half US gallon, or 1000 litre.\nNote that rounding errors may occur, so always check the results.\nUse this page to learn how to convert between half US gallons and liters.\nType in your own numbers in the form to convert the units!\n\n## ››Quick conversion chart of half US gallon to litre\n\n1 half US gallon to litre = 1.89271 litre\n\n5 half US gallon to litre = 9.46353 litre\n\n10 half US gallon to litre = 18.92706 litre\n\n15 half US gallon to litre = 28.39059 litre\n\n20 half US gallon to litre = 37.85412 litre\n\n25 half US gallon to litre = 47.31765 litre\n\n30 half US gallon to litre = 56.78118 litre\n\n40 half US gallon to litre = 75.70824 litre\n\n50 half US gallon to litre = 94.63529 litre\n\n## ››Want other units?\n\nYou can do the reverse unit conversion from litre to half US gallon, or enter any two units below:\n\n## Enter two units to convert\n\n From: To:\n\n## ››Definition: Litre\n\nThe litre (spelled liter in American English and German) is a metric unit of volume. The litre is not an SI unit, but (along with units such as hours and days) is listed as one of the \"units outside the SI that are accepted for use with the SI.\" The SI unit of volume is the cubic metre (m³).\n\n## ››Metric conversions and more\n\nConvertUnits.com provides an online conversion calculator for all types of measurement units. You can find metric conversion tables for SI units, as well as English units, currency, and other data. Type in unit symbols, abbreviations, or full names for units of length, area, mass, pressure, and other types. Examples include mm, inch, 100 kg, US fluid ounce, 6'3\", 10 stone 4, cubic cm, metres squared, grams, moles, feet per second, and many more!"
] | [
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] | {"ft_lang_label":"__label__en","ft_lang_prob":0.8239935,"math_prob":0.8045273,"size":2062,"snap":"2021-21-2021-25","text_gpt3_token_len":524,"char_repetition_ratio":0.27065113,"word_repetition_ratio":0.057591625,"special_character_ratio":0.2803104,"punctuation_ratio":0.1199095,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.9693232,"pos_list":[0],"im_url_duplicate_count":[null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2021-05-10T06:54:30Z\",\"WARC-Record-ID\":\"<urn:uuid:3dcde571-1013-47a0-8bd6-bad8e6640912>\",\"Content-Length\":\"50204\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:ff22071d-bac1-4530-85f5-6ed4bc832c39>\",\"WARC-Concurrent-To\":\"<urn:uuid:aa420f4c-7080-462e-877e-1b963adaabdc>\",\"WARC-IP-Address\":\"54.80.109.124\",\"WARC-Target-URI\":\"https://www.convertunits.com/from/half+US+gallon/to/litre\",\"WARC-Payload-Digest\":\"sha1:ANUJVCSMFRY2E6HTS6KTBRYRLUFCZHHK\",\"WARC-Block-Digest\":\"sha1:KXPN3VPVOELFY2YTPJMWK2FUZQ5XYLBZ\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2021/CC-MAIN-2021-21/CC-MAIN-2021-21_segments_1620243989115.2_warc_CC-MAIN-20210510064318-20210510094318-00395.warc.gz\"}"} |
https://www.rdocumentation.org/packages/MASS/versions/7.3-22/topics/qda | [
"# qda\n\n0th\n\nPercentile\n\nKeywords\nmultivariate\n##### Usage\nqda(x, ...)## S3 method for class 'formula':\nqda(formula, data, \\dots, subset, na.action)## S3 method for class 'default':\nqda(x, grouping, prior = proportions,\nmethod, CV = FALSE, nu, \\dots)## S3 method for class 'data.frame':\nqda(x, \\dots)## S3 method for class 'matrix':\nqda(x, grouping, \\dots, subset, na.action)\n##### Arguments\nformula\nA formula of the form groups ~ x1 + x2 + ... That is, the response is the grouping factor and the right hand side specifies the (non-factor) discriminators.\ndata\nData frame from which variables specified in formula are preferentially to be taken.\nx\n(required if no formula is given as the principal argument.) a matrix or data frame or Matrix containing the explanatory variables.\ngrouping\n(required if no formula principal argument is given.) a factor specifying the class for each observation.\nprior\nthe prior probabilities of class membership. If unspecified, the class proportions for the training set are used. If specified, the probabilities should be specified in the order of the factor levels.\nsubset\nAn index vector specifying the cases to be used in the training sample. (NOTE: If given, this argument must be named.)\nna.action\nA function to specify the action to be taken if NAs are found. The default action is for the procedure to fail. An alternative is na.omit, which leads to rejection of cases with missing values on any required variable. (NOTE: If given, this\nmethod\n\"moment\" for standard estimators of the mean and variance, \"mle\" for MLEs, \"mve\" to use cov.mve, or \"t\" for robust estimates based on a t distribution.\nCV\nIf true, returns results (classes and posterior probabilities) for leave-out-out cross-validation. Note that if the prior is estimated, the proportions in the whole dataset are used.\nnu\ndegrees of freedom for method = \"t\".\n...\narguments passed to or from other methods.\n##### Details\n\nUses a QR decomposition which will give an error message if the within-group variance is singular for any group.\n\n##### Value\n\n• an object of class \"qda\" containing the following components:\n• priorthe prior probabilities used.\n• meansthe group means.\n• scalingfor each group i, scaling[,,i] is an array which transforms observations so that within-groups covariance matrix is spherical.\n• ldeta vector of half log determinants of the dispersion matrix.\n• levthe levels of the grouping factor.\n• terms(if formula is a formula) an object of mode expression and class term summarizing the formula.\n• callthe (matched) function call.\n• unless CV=TRUE, when the return value is a list with components:\n• classThe MAP classification (a factor)\n• posteriorposterior probabilities for the classes\n\n##### References\n\nVenables, W. N. and Ripley, B. D. (2002) Modern Applied Statistics with S. Fourth edition. Springer.\n\nRipley, B. D. (1996) Pattern Recognition and Neural Networks. Cambridge University Press.\n\npredict.qda, lda\n\n##### Aliases\n• qda\n• qda.data.frame\n• qda.default\n• qda.formula\n• qda.matrix\n• model.frame.qda\n• print.qda\n##### Examples\ntr <- sample(1:50, 25)\ntrain <- rbind(iris3[tr,,1], iris3[tr,,2], iris3[tr,,3])\ntest <- rbind(iris3[-tr,,1], iris3[-tr,,2], iris3[-tr,,3])\ncl <- factor(c(rep(\"s\",25), rep(\"c\",25), rep(\"v\",25)))\nz <- qda(train, cl)\npredict(z,test)\\$class\nDocumentation reproduced from package MASS, version 7.3-22, License: GPL-2 | GPL-3\n\n### Community examples\n\nLooks like there are no examples yet."
] | [
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] | {"ft_lang_label":"__label__en","ft_lang_prob":0.67669797,"math_prob":0.91457933,"size":3284,"snap":"2019-51-2020-05","text_gpt3_token_len":804,"char_repetition_ratio":0.108841464,"word_repetition_ratio":0.013592233,"special_character_ratio":0.25334957,"punctuation_ratio":0.18827161,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.98956555,"pos_list":[0],"im_url_duplicate_count":[null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2020-01-18T07:07:36Z\",\"WARC-Record-ID\":\"<urn:uuid:66255c7d-a1af-420a-bb87-b13ca6910e6a>\",\"Content-Length\":\"18144\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:7ef1b384-1788-4e00-bc24-7ae9c8525742>\",\"WARC-Concurrent-To\":\"<urn:uuid:df2afc4b-0ea6-4e65-a592-953dbb6c5090>\",\"WARC-IP-Address\":\"3.226.88.111\",\"WARC-Target-URI\":\"https://www.rdocumentation.org/packages/MASS/versions/7.3-22/topics/qda\",\"WARC-Payload-Digest\":\"sha1:K4774DPC7B3FH5BILGUIGGHIM4ZPRRQC\",\"WARC-Block-Digest\":\"sha1:HIQPWB7Y5KFRJWPYWPB5J2FIDK4UNQKL\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2020/CC-MAIN-2020-05/CC-MAIN-2020-05_segments_1579250592261.1_warc_CC-MAIN-20200118052321-20200118080321-00096.warc.gz\"}"} |
https://www.webqc.org/molecularweightcalculated-190211-198.html | [
"",
null,
"#### Chemical Equations Balanced on 02/11/19\n\n Molecular weights calculated on 02/10/19 Molecular weights calculated on 02/12/19\nCalculate molecular weight\n 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232\nMolar mass of h2o is 18,01528\nMolar mass of H2O is 18.01528\nMolar mass of MgSiO3 is 100.3887\nMolar mass of TiO2 is 79.8658\nMolar mass of Ni2O3 is 165,385\nMolar mass of C4H4S is 84.13956\nMolar mass of Pb(NO3)2 is 331.2098\nMolar mass of O is 15.9994\nMolar mass of AgNO3 is 169.8731\nMolar mass of CH3OH is 32.04186\nMolar mass of C2H14O2 is 70.13136\nMolar mass of ZnSO4*7H2O is 287.54956\nMolar mass of H2O2 is 34.01468\nMolar mass of K2CuC4O8*5H2O is 407.857\nMolar mass of h3po4 is 838,9535416\nMolar mass of MgCl2 is 95.211\nMolar mass of MgCl2 is 95.211\nMolar mass of C7H16 is 100.20194\nMolar mass of H2 is 2,01588\nMolar mass of K2CuC4O8*2H2O is 353.81116\nMolar mass of MgSO4 is 120.3676\nMolar mass of (ch3)2co acetone is 48.10746\nMolar mass of Na2CO3 is 105.98843856\nMolar mass of O2 is 31,9988\nMolar mass of NH4po3 is 644.9857512\nMolar mass of s04 is 128.26\nMolar mass of (NH4)3PO4 is 149.086742\nMolar mass of C2 is 24,0214\nMolar mass of Ni2O3 is 165.385\nMolar mass of c3h8o3 is 92.09382\nMolar mass of SO4 is 96.0626\nMolar mass of f2ca is 78,0748064\nMolar mass of CuSO4*Fe is 215.4536\nMolar mass of H2O is 18,01528\nMolar mass of O2 is 31,9988\nMolar mass of H3PO4 is 97.995182\nMolar mass of CH4 is 16,04246\nMolar mass of Sc2(SO4)3 is 378.099624\nMolar mass of C6H12O6 is 180,15588\nMolar mass of SO2 is 64.0638\nMolar mass of B4H10 is 53.3234\nMolar mass of CO2 is 44.0095\nMolar mass of C2 is 24,0214\nMolar mass of k2(cu(c2o4)2) is 317.7806\nMolar mass of NH3 is 17,03052\nMolar mass of glucose is 180.15588\nMolar mass of H2SO4 is 98,07848\nMolar mass of FeCl3 is 162.204\nMolar mass of H2o is 18,01528\nMolar mass of O2 is 31.9988\n 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232\nCalculate molecular weight\n Molecular weights calculated on 02/10/19 Molecular weights calculated on 02/12/19\nMolecular masses on 02/04/19\nMolecular masses on 01/12/19\nMolecular masses on 02/11/18"
] | [
null,
"https://www.webqc.org/images/logo.png",
null
] | {"ft_lang_label":"__label__en","ft_lang_prob":0.8534067,"math_prob":0.93103266,"size":1822,"snap":"2020-34-2020-40","text_gpt3_token_len":803,"char_repetition_ratio":0.3910891,"word_repetition_ratio":0.119266056,"special_character_ratio":0.4720088,"punctuation_ratio":0.11581292,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.96657056,"pos_list":[0,1,2],"im_url_duplicate_count":[null,null,null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2020-08-14T06:09:36Z\",\"WARC-Record-ID\":\"<urn:uuid:92c28523-ed66-488e-be2f-d4098389bc53>\",\"Content-Length\":\"57253\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:b43846df-fd6a-4583-8cbd-38f915bb1421>\",\"WARC-Concurrent-To\":\"<urn:uuid:6c268357-8fa2-4229-a7db-edba7ca56f75>\",\"WARC-IP-Address\":\"104.24.118.127\",\"WARC-Target-URI\":\"https://www.webqc.org/molecularweightcalculated-190211-198.html\",\"WARC-Payload-Digest\":\"sha1:ZTKYIPHL3A3WBUQBOXYCLICK72QH4HTY\",\"WARC-Block-Digest\":\"sha1:NF3TB3SOCVNEIGW52SBBSVWADZT7LDHM\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2020/CC-MAIN-2020-34/CC-MAIN-2020-34_segments_1596439739177.25_warc_CC-MAIN-20200814040920-20200814070920-00539.warc.gz\"}"} |
https://www.assignmentexpert.com/homework-answers/economics/microeconomics/question-63242 | [
"# Answer to Question #63242 in Microeconomics for kamna\n\nQuestion #63242\nThe Lumins Lamp Company, a producer of old-style oil lamps, estimated the following demand function for its product:\n\nQ = 120,000 – 10,000P\n\nwhere Q is the quantity demanded per year and P is the price per lamp.\n\nThe firm’s fixed costs are $12,000 and variable costs are$1.50 per lamp.\n\na. Write an equation for the total revenue (TR) function in terms of Q.\nb. Specify the marginal revenue function.\nc. Write an equation for the total cost (TC) function in terms of Q.\nd. Specify the marginal cost function.\ne. Write an equation for total profits (π) in terms of Q. At what level of output (Q) are total profits maximized? What price will be charged? What are total profits at this output level?\nf. Check your answers in Part (e) by equating the marginal revenue and marginal cost functions, determined in Parts (b) and (d), and solving for Q.\ng. What model of market pricing behavior has been assumed in this problem?\n1\n2016-11-10T09:42:11-0500\n\nNeed a fast expert's response?\n\nSubmit order\n\nand get a quick answer at the best price\n\nfor any assignment or question with DETAILED EXPLANATIONS!"
] | [
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] | {"ft_lang_label":"__label__en","ft_lang_prob":0.8865718,"math_prob":0.92788285,"size":941,"snap":"2022-27-2022-33","text_gpt3_token_len":226,"char_repetition_ratio":0.13020277,"word_repetition_ratio":0.036363635,"special_character_ratio":0.25079703,"punctuation_ratio":0.13930348,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.9954991,"pos_list":[0],"im_url_duplicate_count":[null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2022-06-29T19:13:37Z\",\"WARC-Record-ID\":\"<urn:uuid:624051fb-be56-47de-b39c-d275b5d3a6b0>\",\"Content-Length\":\"308231\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:2d1d430e-4534-493f-b30a-6532cc50a3a3>\",\"WARC-Concurrent-To\":\"<urn:uuid:d0c2530a-c1ec-4404-a683-11a28f6fe724>\",\"WARC-IP-Address\":\"44.240.111.95\",\"WARC-Target-URI\":\"https://www.assignmentexpert.com/homework-answers/economics/microeconomics/question-63242\",\"WARC-Payload-Digest\":\"sha1:23TFP24YADBSVO4V2QVPUGFYY3XJ3TPN\",\"WARC-Block-Digest\":\"sha1:COCI52WW5CAPH2VBLDFGOJUDKC2BSMJY\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2022/CC-MAIN-2022-27/CC-MAIN-2022-27_segments_1656103642979.38_warc_CC-MAIN-20220629180939-20220629210939-00119.warc.gz\"}"} |
https://factorization.info/prime-factors/9/prime-factors-of-98370.html | [
"Prime Factors of 98370",
null,
"Here we have a collection of all the information you may need about the Prime Factors of 98370. We will give you the definition of Prime Factors of 98370, show you how to find the Prime Factors of 98370 (Prime Factorization of 98370) by creating a Prime Factor Tree of 98370, tell you how many Prime Factors of 98370 there are, and we will show you the Product of Prime Factors of 98370.\n\nPrime Factors of 98370 definition\nFirst note that prime numbers are all positive integers that can only be evenly divided by 1 and itself. Prime Factors of 98370 are all the prime numbers that when multiplied together equal 98370.\n\nHow to find the Prime Factors of 98370\nThe process of finding the Prime Factors of 98370 is called Prime Factorization of 98370. To get the Prime Factors of 98370, you divide 98370 by the smallest prime number possible. Then you take the result from that and divide that by the smallest prime number. Repeat this process until you end up with 1.\n\nThis Prime Factorization process creates what we call the Prime Factor Tree of 98370. See illustration below.",
null,
"All the prime numbers that are used to divide in the Prime Factor Tree are the Prime Factors of 98370. Here is the math to illustrate:\n\n98370 ÷ 2 = 49185\n49185 ÷ 3 = 16395\n16395 ÷ 3 = 5465\n5465 ÷ 5 = 1093\n1093 ÷ 1093 = 1\n\nAgain, all the prime numbers you used to divide above are the Prime Factors of 98370. Thus, the Prime Factors of 98370 are:\n\n2, 3, 3, 5, 1093.\n\nHow many Prime Factors of 98370?\nWhen we count the number of prime numbers above, we find that 98370 has a total of 5 Prime Factors.\n\nProduct of Prime Factors of 98370\nThe Prime Factors of 98370 are unique to 98370. When you multiply all the Prime Factors of 98370 together it will result in 98370. This is called the Product of Prime Factors of 98370. The Product of Prime Factors of 98370 is:\n\n2 × 3 × 3 × 5 × 1093 = 98370\n\nPrime Factor Calculator\nDo you need the Prime Factors for a particular number? You can submit a number below to find the Prime Factors of that number with detailed explanations like we did with Prime Factors of 98370 above.\n\nPrime Factors of 98371\nWe hope this step-by-step tutorial to teach you about Prime Factors of 98370 was helpful. Do you want a test? If so, try to find the Prime Factors of the next number on our list and then check your answer here."
] | [
null,
"https://factorization.info/images/prime-factors-of.png",
null,
"https://factorization.info/images/factor-trees/9/factor-tree-of-98370.png",
null
] | {"ft_lang_label":"__label__en","ft_lang_prob":0.88623846,"math_prob":0.9543392,"size":2390,"snap":"2023-40-2023-50","text_gpt3_token_len":613,"char_repetition_ratio":0.32648784,"word_repetition_ratio":0.071428575,"special_character_ratio":0.31171548,"punctuation_ratio":0.080168776,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.9997284,"pos_list":[0,1,2,3,4],"im_url_duplicate_count":[null,null,null,2,null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2023-12-07T06:06:07Z\",\"WARC-Record-ID\":\"<urn:uuid:491c2e8d-5e82-41ef-8039-348524bdf114>\",\"Content-Length\":\"7668\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:eb495142-45ff-4d8d-96b1-bba55a0684a5>\",\"WARC-Concurrent-To\":\"<urn:uuid:e331d80c-3977-452a-85d3-ec6a5e345a77>\",\"WARC-IP-Address\":\"18.67.65.2\",\"WARC-Target-URI\":\"https://factorization.info/prime-factors/9/prime-factors-of-98370.html\",\"WARC-Payload-Digest\":\"sha1:EJOV2XCI3KPCEGCJCDFAFY5JLNDZ4675\",\"WARC-Block-Digest\":\"sha1:O3UTXKPOMH32A2IYXY3FOLPMOHEU33VN\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2023/CC-MAIN-2023-50/CC-MAIN-2023-50_segments_1700679100650.21_warc_CC-MAIN-20231207054219-20231207084219-00356.warc.gz\"}"} |
https://pixel-druid.com/articles/motivation-for-the-compact-open-topology.html | [
"## § Motivation for the compact-open topology\n\n• If $X$ is a compact space and $Y$ is a metric space, consider two functions $f, g: X \\to Y$.\n• We can define a distance $d(f, g) \\equiv \\min_{x \\in X} d(f(x), g(x))$.\n• The $\\min_{x \\in X}$ has a maximum because $X$ is compact.\n• Thus this is a real metric on the function space $Map(X, Y)$.\n• Now suppose $Y$ is no longer a metric space, but is Haussdorf. Can we still define a topology on $Map(X, Y)$?\n• Let $K \\subseteq X$ be compact, and let $U \\subseteq Y$ be open such that $f(K) \\subseteq U$.\n• Since $Y$ is Hausdorff, $K \\subseteq X$"
] | [
null
] | {"ft_lang_label":"__label__en","ft_lang_prob":0.837763,"math_prob":1.000001,"size":484,"snap":"2023-40-2023-50","text_gpt3_token_len":156,"char_repetition_ratio":0.12083333,"word_repetition_ratio":0.0,"special_character_ratio":0.2768595,"punctuation_ratio":0.13821138,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":1.0000083,"pos_list":[0],"im_url_duplicate_count":[null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2023-09-28T04:14:09Z\",\"WARC-Record-ID\":\"<urn:uuid:3cfc6bf4-13b7-43c4-b076-056a5b589120>\",\"Content-Length\":\"17567\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:4dfbc7f6-7594-4643-a567-6748c2a18692>\",\"WARC-Concurrent-To\":\"<urn:uuid:21b88164-8440-4706-b8f1-d16effd63287>\",\"WARC-IP-Address\":\"159.65.151.13\",\"WARC-Target-URI\":\"https://pixel-druid.com/articles/motivation-for-the-compact-open-topology.html\",\"WARC-Payload-Digest\":\"sha1:6JDLQD4YWZJSGY4CW42IZU4D24UNRTOK\",\"WARC-Block-Digest\":\"sha1:4VHIAXNRAGC6VR4X5E2J43JTJHKWCNBW\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2023/CC-MAIN-2023-40/CC-MAIN-2023-40_segments_1695233510358.68_warc_CC-MAIN-20230928031105-20230928061105-00539.warc.gz\"}"} |
https://origin.geeksforgeeks.org/looping-techniques-python/?ref=lbp | [
"# Looping Techniques in Python\n\n• Difficulty Level : Easy\n• Last Updated : 23 Nov, 2021\n\nPython supports various looping techniques by certain inbuilt functions, in various sequential containers. These methods are primarily very useful in competitive programming and also in various projects which require a specific technique with loops maintaining the overall structure of code. A lot of time and memory space is been saved as there is no need to declare the extra variables which we declare in the traditional approach of loops.\n\nWhere they are used?\nDifferent looping techniques are primarily useful in the places where we don’t need to actually manipulate the structure and order of the overall containers, rather only print the elements for a single-use instance, no in-place change occurs in the container. This can also be used in instances to save time.\n\nAttention geek! Strengthen your foundations with the Python Programming Foundation Course and learn the basics.\n\nTo begin with, your interview preparations Enhance your Data Structures concepts with the Python DS Course. And to begin with your Machine Learning Journey, join the Machine Learning - Basic Level Course\n\nDifferent looping techniques using Python data structures are:\n\n• Using enumerate(): enumerate() is used to loop through the containers printing the index number along with the value present in that particular index.\n\n## Python3\n\n `# python code to demonstrate working of enumerate()` `for` `key, value ``in` `enumerate``([``'The'``, ``'Big'``, ``'Bang'``, ``'Theory'``]):` ` ``print``(key, value)`\n\nOutput:\n\n```0 The\n1 Big\n2 Bang\n3 Theory```\n\n## Python3\n\n `# python code to demonstrate working of enumerate()` `for` `key, value ``in` `enumerate``([``'Geeks'``, ``'for'``, ``'Geeks'``, ``'is'``, ``'the'``, ``'Best'``, ``'Coding'``, ``'Platform'``]):` ` ``print``(value, end``=``' '``)`\n\nOutput:\n\n`Geeks for Geeks is the Best Coding Platform `\n• Using zip(): zip() is used to combine 2 similar containers(list-list or dict-dict) printing the values sequentially. The loop exists only till the smaller container ends. A detailed explanation of zip() and enumerate() can be found here.\n\n## Python3\n\n `# python code to demonstrate working of zip()` `# initializing list` `questions ``=` `[``'name'``, ``'colour'``, ``'shape'``]` `answers ``=` `[``'apple'``, ``'red'``, ``'a circle'``]` `# using zip() to combine two containers ` `# and print values` `for` `question, answer ``in` `zip``(questions, answers):` ` ``print``(``'What is your {0}? I am {1}.'``.``format``(question, answer))`\n\nOutput:\n\n```What is your name? I am apple.\nWhat is your color? I am red.\nWhat is your shape? I am a circle.```\n• Using iteritem(): iteritems() is used to loop through the dictionary printing the dictionary key-value pair sequentially.\n• Using items(): items() performs the similar task on dictionary as iteritems() but have certain disadvantages when compared with iteritems().\n• It is very time-consuming. Calling it on large dictionaries consumes quite a lot of time.\n• It takes a lot of memory. Sometimes takes double the memory when called on a dictionary.\n\nExample 1:\n\n## Python3\n\n `# python code to demonstrate working of iteritems(),items()` `d ``=` `{ ``\"geeks\"` `: ``\"for\"``, ``\"only\"` `: ``\"geeks\"` `}` `# using iteritems to print the dictionary key-value pair` `print` `(``\"The key value pair using iteritems is : \"``)` `for` `i,j ``in` `d.items():` ` ``print``( i,j )` ` ` `# using items to print the dictionary key-value pair` `print` `(``\"The key value pair using items is : \"``)` `for` `i,j ``in` `d.items():` ` ``print``( i,j )`\n\nOutput:\n\n```The key value pair using iteritems is :\ngeeks for\nonly geeks\nThe key value pair using items is :\ngeeks for\nonly geeks```\n\nExample 2:\n\n## Python3\n\n `# python code to demonstrate working of items()` `king ``=` `{``'Akbar'``: ``'The Great'``, ``'Chandragupta'``: ``'The Maurya'``, ` ` ``'Modi'` `: ``'The Changer'``}` `# using items to print the dictionary key-value pair` `for` `key, value ``in` `king.items():` ` ``print``(key, value)`\n\nOutput:\n\n```Akbar The Great\nChandragupta The Maurya\nModi The Changer```\n• Using sorted(): sorted() is used to print the container is sorted order. It doesn’t sort the container but just prints the container in sorted order for 1 instance. The use of set() can be combined to remove duplicate occurrences.\n\nExample 1:\n\n## Python3\n\n `# python code to demonstrate working of sorted()` `# initializing list` `lis ``=` `[ ``1` `, ``3``, ``5``, ``6``, ``2``, ``1``, ``3` `]` `# using sorted() to print the list in sorted order` `print` `(``\"The list in sorted order is : \"``)` `for` `i ``in` `sorted``(lis) :` ` ``print` `(i,end``=``\" \"``)` ` ` `print` `(``\"\\r\"``)` ` ` `# using sorted() and set() to print the list in sorted order` `# use of set() removes duplicates.` `print` `(``\"The list in sorted order (without duplicates) is : \"``)` `for` `i ``in` `sorted``(``set``(lis)) :` ` ``print` `(i,end``=``\" \"``)`\n\nOutput:\n\n```The list in sorted order is :\n1 1 2 3 3 5 6\nThe list in sorted order (without duplicates) is :\n1 2 3 5 6 ```\n\nExample 2:\n\n## Python3\n\n `# python code to demonstrate working of sorted()` `# initializing list` `basket ``=` `[``'guave'``, ``'orange'``, ``'apple'``, ``'pear'``, ` ` ``'guava'``, ``'banana'``, ``'grape'``]` `# using sorted() and set() to print the list` `# in sorted order` `for` `fruit ``in` `sorted``(``set``(basket)):` ` ``print``(fruit)`\n\nOutput:\n\n```apple\nbanana\ngrape\nguava\nguave\norange\npear```\n• Using reversed(): reversed() is used to print the values of the container in the reversed order. It does not reflect any changes to the original list\n\nExample 1:\n\n## Python3\n\n `# python code to demonstrate working of reversed()` `# initializing list` `lis ``=` `[ ``1` `, ``3``, ``5``, ``6``, ``2``, ``1``, ``3` `]` `# using revered() to print the list in reversed order` `print` `(``\"The list in reversed order is : \"``)` `for` `i ``in` `reversed``(lis) :` ` ``print` `(i,end``=``\" \"``)`\n\nOutput:\n\n```The list in reversed order is :\n3 1 2 6 5 3 1 ```\n\nExample 2:\n\n## Python3\n\n `# python code to demonstrate working of reversed()` `# using reversed() to print in reverse order` `for` `i ``in` `reversed``(``range``(``1``, ``10``, ``3``)):` ` ``print` `(i)`\n\nOutput:\n\n```7\n4\n1```\n• These techniques are quick to use and reduce coding effort. for, while loops need the entire structure of the container to be changed.\n• These Looping techniques do not require any structural changes to the container. They have keywords that present the exact purpose of usage. Whereas, no pre-predictions or guesses can be made in for, while loop i.e not easily understand the purpose at a glance.\n• Looping technique makes the code more concise than using for & while looping.\n\nMy Personal Notes arrow_drop_up\nRecommended Articles\nPage :"
] | [
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] | {"ft_lang_label":"__label__en","ft_lang_prob":0.7287738,"math_prob":0.60460126,"size":6083,"snap":"2021-43-2021-49","text_gpt3_token_len":1564,"char_repetition_ratio":0.12847508,"word_repetition_ratio":0.23408072,"special_character_ratio":0.27305606,"punctuation_ratio":0.13551816,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.9820238,"pos_list":[0],"im_url_duplicate_count":[null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2021-11-28T03:12:23Z\",\"WARC-Record-ID\":\"<urn:uuid:9dd00cc8-f38c-4c2b-b0a7-6f13aa1661b3>\",\"Content-Length\":\"253512\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:96bd245d-c10b-45fc-9ed3-12fdc2e6a151>\",\"WARC-Concurrent-To\":\"<urn:uuid:a9237a26-384a-4271-93de-e106341c805d>\",\"WARC-IP-Address\":\"44.228.100.190\",\"WARC-Target-URI\":\"https://origin.geeksforgeeks.org/looping-techniques-python/?ref=lbp\",\"WARC-Payload-Digest\":\"sha1:2C56ORF57UBP3C2Y5AQ36G3C55UN5W7B\",\"WARC-Block-Digest\":\"sha1:MECKQT4X3PMWBEFWTK5GZEMH6DTCY6ER\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2021/CC-MAIN-2021-49/CC-MAIN-2021-49_segments_1637964358443.87_warc_CC-MAIN-20211128013650-20211128043650-00581.warc.gz\"}"} |
https://jumk.de/math-physics-formulary/exponential-growth.php | [
"## Formulary\n\n### Math and Physics Calculators\n\n| Start: Formulary | Imprint & Privacy\n\nAnzeige\n\n# Calculate Exponential Growth\n\nCalculates the exponential growth for a doubling with each cycle. The number of cycles can be calculated from cycle length and run time.\n\na * 2n = b\na = start value, b = end value, n = number of cycles\n\n a: b: n:\nPlease enter two values, the third will be calculated.\n\n cycle length: d, h, m, s run time: d, h, m, s number of cycles:\nPlease enter times for cycle length and run time.\nd = days, h = hours, m = minutes, s = seconds.\n\nAlso see exponential decay.",
null,
"The function y = 2x, made with the Function Graphs Plotter.\n\nFormulary and calculators math and physics.\n© jumk.de Webprojects | German: Formelsammlung Mathe & Physik\n\nAnzeige"
] | [
null,
"https://jumk.de/math-physics-formulary/exp.png",
null
] | {"ft_lang_label":"__label__en","ft_lang_prob":0.8171635,"math_prob":0.99846804,"size":479,"snap":"2021-43-2021-49","text_gpt3_token_len":119,"char_repetition_ratio":0.13263159,"word_repetition_ratio":0.022988506,"special_character_ratio":0.24425887,"punctuation_ratio":0.14893617,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.99952877,"pos_list":[0,1,2],"im_url_duplicate_count":[null,2,null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2021-10-16T09:47:53Z\",\"WARC-Record-ID\":\"<urn:uuid:58720b2a-209b-480d-b219-fc2c0563102a>\",\"Content-Length\":\"19763\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:5598749a-06fd-48ba-8bbf-bdbf3495b3dc>\",\"WARC-Concurrent-To\":\"<urn:uuid:5d152cdf-c3fb-40b0-affc-3597dbebef84>\",\"WARC-IP-Address\":\"92.204.58.21\",\"WARC-Target-URI\":\"https://jumk.de/math-physics-formulary/exponential-growth.php\",\"WARC-Payload-Digest\":\"sha1:ILLP7LXCWX6KOT5ZZ5FWH3W4QFJB42E2\",\"WARC-Block-Digest\":\"sha1:SDEXKEDLPGEBKPLWATPSRJFXLDZDLNW3\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2021/CC-MAIN-2021-43/CC-MAIN-2021-43_segments_1634323584554.98_warc_CC-MAIN-20211016074500-20211016104500-00573.warc.gz\"}"} |
https://intl.siyavula.com/read/maths/grade-10/finance-and-growth/09-finance-and-growth-03 | [
"We think you are located in United States. Is this correct?\n\n# 9.4 Calculations using simple and compound interest\n\n## 9.4 Calculations using simple and compound interest (EMA6Q)\n\n### Hire purchase (EMA6R)\n\nAs a general rule, it is not wise to buy items on credit. When buying on credit you have to borrow money to pay for the object, meaning you will have to pay more for it due to the interest on the loan. That being said, occasionally there are appliances, such as a fridge, that are very difficult to live without. Most people don't have the cash up front to purchase such items, so they buy it on a hire purchase agreement.\n\nA hire purchase agreement is a financial agreement between the shop and the customer about how the customer will pay for the desired product. The interest on a hire purchase loan is always charged at a simple interest rate and only charged on the amount owing. Most agreements require that a deposit is paid before the product can be taken by the customer. The principal amount of the loan is therefore the cash price minus the deposit. The accumulated loan will be worked out using the number of years the loan is needed for. The total loan amount is then divided into monthly payments over the period of the loan.\n\nHire purchase is charged at a simple interest rate. When you are asked a hire purchase question, don't forget to always use the simple interest formula.\n\nThis video explains hire purchase and shows some examples of hire purchase calculations.\n\nVideo: 2GHF\n\n## Worked example 7: Hire purchase\n\nTroy wants to buy an additional screen for his computer which he saw advertised for $$\\text{R}\\,\\text{2 500}$$ on the internet. There is an option of paying a $$\\text{10}\\%$$ deposit and then making $$\\text{24}$$ monthly payments using a hire purchase agreement, where interest is calculated at $$\\text{7,5}\\%$$ p.a. simple interest. Calculate what Troy's monthly payments will be.\n\n### Write down the known variables\n\nA new opening balance is required, as the $$\\text{10}\\%$$ deposit is paid in cash.\n\n\\begin{align*} \\text{10}\\% \\text{ of } \\text{2 500} & = 250 \\\\ \\therefore P & = \\text{2 500} - 250 = \\text{2 250} \\\\ i & = \\text{0,075} \\\\ n & = \\frac{24}{12} = 2 \\end{align*}\n\n### Write down the formula\n\n$A = P\\left(1 + in\\right)$\n\n### Substitute the values\n\n\\begin{align*} A & = \\text{2 250}\\left(1 + \\text{0,075}\\times 2\\right) \\\\ & = \\text{2 587,50} \\end{align*}\n\n### Calculate the monthly repayments on the hire purchase agreement\n\n\\begin{align*} \\text{Monthly payment } & = \\frac{\\text{2 587,50}}{24} \\\\ & = \\text{107,81} \\end{align*}\n\nTroy's monthly payment is $$\\text{R}\\,\\text{107,81}$$.\n\ntemp text\n\nA shop can also add a monthly insurance premium to the monthly instalments. This insurance premium will be an amount of money paid monthly and gives the customer more time between a missed payment and possible repossession of the product.\n\nThe monthly payment is also called the monthly instalment.\n\n## Worked example 8: Hire purchase with extra conditions\n\nCassidy wants to buy a TV and decides to buy one on a hire purchase agreement. The TV's cash price is $$\\text{R}\\,\\text{5 500}$$. She will pay it off over $$\\text{54}$$ months at an interest rate of $$\\text{21}\\%$$ p.a. An insurance premium of $$\\text{R}\\,\\text{12,50}$$ is added to every monthly payment. How much are her monthly payments?\n\n### Write down the known variables\n\n\\begin{align*} P & = \\text{5 500} \\\\ i & = \\text{0,21} \\\\ n & = \\frac{54}{12} = \\text{4,5} \\end{align*}\n\nThe question does not mention a deposit, therefore we assume that Cassidy did not pay one.\n\n### Write down the formula\n\n$A = P\\left(1 + in\\right)$\n\n### Substitute the values\n\n\\begin{align*} A & = \\text{5 500}\\left(1 + \\text{0,21}\\times \\text{4,5}\\right) \\\\ & = \\text{10 697,50} \\end{align*}\n\n### Calculate the monthly repayments on the hire purchase agreement\n\n\\begin{align*} \\text{Monthly payment } & = \\frac{\\text{10 697,50}}{54} \\\\ & = \\text{198,10} \\end{align*}\n\n$$\\text{198,10} + \\text{12,50} = \\text{210,60}$$\n\nCassidy will pay $$\\text{R}\\,\\text{210,60}$$ per month for $$\\text{54}$$ months until her TV is paid off.\n\nTextbook Exercise 9.3\n\nAngelique wants to buy a microwave on a hire purchase agreement. The cash price of the microwave is $$\\text{R}\\,\\text{4 400}$$. She is required to pay a deposit of $$\\text{10}\\%$$ and pay the remaining loan amount off over $$\\text{12}$$ months at an interest rate of $$\\text{9}\\%$$ p.a.\n\nWhat is the principal loan amount?\n\nFirst calculate the amount for the deposit:\n\n\\begin{align*} \\text{deposit} &= \\text{4 400} \\times \\frac{\\text{10}}{\\text{100}}\\\\ &= \\text{440} \\end{align*}\n\nTo determine the principal loan amount, we must subtract the deposit amount from the cash price:\n\n\\begin{align*} P &= \\text{cash price} - \\text{deposit}\\\\ &= \\text{4 400} - \\text{440}\\\\ &= \\text{R}\\,\\text{3 960,00} \\end{align*}\n\nWhat is the accumulated loan amount?\n\nRead the question carefully and write down the given information:\n\n\\begin{align*} A & = ? \\\\ P & = \\text{R}\\,\\text{3 960,00} \\\\ i & = \\frac{9}{100} = \\text{0,09} \\\\ n & = 1 \\end{align*}\n\nTo determine the accumulated loan amount, we use the simple interest formula:\n\n\\begin{align*} A &= P(1+in)\\\\ &= \\text{R}\\,\\text{3 960,00}\\left(\\text{1} + \\text{0,09} \\times 1\\right)\\\\ &= \\text{R}\\,\\text{4 316,40} \\end{align*}\n\nWhat are Angelique's monthly repayments?\n\nTo determine the monthly payment amount, we divide the accumulated amount $$A$$ by the total number of months: \\begin{align*} \\text{Monthly repayment} &= \\frac{A}{\\text{no. of months}}\\\\ &= \\frac{\\text{R}\\,\\text{4 316,40}}{\\text{12}}\\\\ &= \\text{R}\\,\\text{359,70} \\end{align*}\n\nWhat is the total amount she has paid for the microwave?\n\nTo determine the total amount paid, we add the accumulated loan amount and the deposit: \\begin{align*} \\text{Total amount} &= A + \\text{deposit amount}\\\\ &= \\text{R}\\,\\text{4 316,40} + \\text{440}\\\\ &= \\text{R}\\,\\text{4 756,40} \\end{align*}\n\nNyakallo wants to buy a television on a hire purchase agreement. The cash price of the television is $$\\text{R}\\,\\text{5 600}$$. She is required to pay a deposit of $$\\text{15}\\%$$ and pay the remaining loan amount off over $$\\text{24}$$ months at an interest rate of $$\\text{14}\\%$$ p.a.\n\nWhat is the principal loan amount?\n\nFirst calculate the amount for the deposit:\n\n\\begin{align*} \\text{deposit} &= \\text{5 600} \\times \\frac{\\text{15}}{\\text{100}}\\\\ &= \\text{840} \\end{align*}\n\nTo determine the principal loan amount, we must subtract the deposit amount from the cash price:\n\n\\begin{align*} P &= \\text{cash price} - \\text{deposit}\\\\ &= \\text{5 600} - \\text{840}\\\\ &= \\text{R}\\,\\text{4 760,00} \\end{align*}\n\nWhat is the accumulated loan amount?\n\nRead the question carefully and write down the given information:\n\n\\begin{align*} A & = ? \\\\ P & = \\text{R}\\,\\text{4 760,00} \\\\ i & = \\frac{14}{100} = \\text{0,14} \\\\ n & = 2 \\end{align*}\n\nTo determine the accumulated loan amount, we use the simple interest formula:\n\n\\begin{align*} A &= P(1+in)\\\\ &= \\text{R}\\,\\text{4 760,00}\\left(\\text{1} + \\text{0,14} \\times 2\\right)\\\\ &= \\text{R}\\,\\text{6 092,80} \\end{align*}\n\nWhat are Nyakallo's monthly repayments?\n\nTo determine the monthly payment amount, we divide the accumulated amount $$A$$ by the total number of months: \\begin{align*} \\text{Monthly repayment} &= \\frac{A}{\\text{no. of months}}\\\\ &= \\frac{\\text{R}\\,\\text{6 092,80}}{\\text{24}}\\\\ &= \\text{R}\\,\\text{253,87} \\end{align*}\n\nWhat is the total amount she has paid for the television?\n\nTo determine the total amount paid we add the accumulated loan amount and the deposit: \\begin{align*} \\text{Total amount} &= A + \\text{deposit amount}\\\\ &= \\text{R}\\,\\text{6 092,80} + \\text{840}\\\\ &= \\text{R}\\,\\text{6 932,80} \\end{align*}\n\nA company wants to purchase a printer. The cash price of the printer is $$\\text{R}\\,\\text{4 500}$$. A deposit of $$\\text{15}\\%$$ is required on the printer. The remaining loan amount will be paid off over $$\\text{24}$$ months at an interest rate of $$\\text{12}\\%$$ p.a.\n\nWhat is the principal loan amount?\n\nTo calculate the principal loan amount, we first calculate the amount for the deposit and then subtract the deposit amount from the cash price:\n\n\\begin{align*} P & = \\text{4 500} - (\\text{4 500} \\times \\text{0,15}) \\\\ &= \\text{4 500} - 675 \\\\ &= \\text{R}\\,\\text{3 825} \\end{align*}\n\nWhat is the accumulated loan amount?\n\nRemember that hire purchase uses simple interest. We write down the given information and then substitute these values into the simple interest formula.\n\n\\begin{align*} P &= \\text{R}\\,\\text{3 825} \\\\ i & = \\text{0,12}\\\\ n & = \\frac{24}{12} = 2 \\\\\\\\ A = & P(1 + in) \\\\ A &= \\text{3 825}(1 + (\\text{0,12})(2))\\\\ A & = \\text{R}\\,\\text{4 743} \\end{align*}\n\nHow much will the company pay each month?\n\nTo determine the monthly payment amount (how much the company pays each month), we divide the accumulated amount $$A$$ by the total number of months:\n\n$$\\dfrac{\\text{4 743}}{24} = \\text{R}\\,\\text{197,63}$$\n\nWhat is the total amount the company paid for the printer?\n\nTo determine the total amount paid we add the accumulated loan amount and the deposit:\n\n$$675 + \\text{4 743} = \\text{R}\\,\\text{5 418}$$\n\nSandile buys a dining room table costing $$\\text{R}\\,\\text{8 500}$$ on a hire purchase agreement. He is charged an interest rate of $$\\text{17,5}\\%$$ p.a. over $$\\text{3}$$ years.\n\nHow much will Sandile pay in total?\n\nThe question does not mention a deposit so we assume Sandile did not pay one. We write down the given information and then use the simple interest formula to calculate the accumulated amount.\n\n\\begin{align*} A & = ? \\\\ P & = \\text{8 500}\\\\ i & = \\text{0,175}\\\\ n & = 3\\\\\\\\ A & = P(1 + in)\\\\ A & = \\text{8 500}(1 + (\\text{0,175})(3))\\\\ A & = \\text{R}\\,\\text{12 962,50} \\end{align*}\n\nHow much interest does he pay?\n\nTo calculate the total interest paid we subtract the cash price from the accumulated amount.\n\n$$\\text{12 962,50} - \\text{8 500} = \\text{R}\\,\\text{4 462,50}$$\n\nWhat is his monthly instalment?\n\nTo determine the monthly payment amount, we divide the accumulated amount $$A$$ by the total number of months:\n\n$$\\dfrac{\\text{12 962,50}}{36} = \\text{R}\\,\\text{360,07}$$\n\nMike buys a table costing $$\\text{R}\\,\\text{6 400}$$ on a hire purchase agreement. He is charged an interest rate of $$\\text{15}\\%$$ p.a. over $$\\text{4}$$ years.\n\nHow much will Mike pay in total?\n\nRead the question carefully and write down the given information:\n\n\\begin{align*} A & = ? \\\\ P & = \\text{R}\\,\\text{6 400} \\\\ i & = \\frac{15}{100} = \\text{0,15} \\\\ n & = 4 \\end{align*}\n\nTo determine the accumulated loan amount, we use the simple interest formula:\n\n\\begin{align*} A &= P(1+in)\\\\ &= \\text{6 400} (\\text{1} + \\text{0,15} \\times \\text{4})\\\\ &= \\text{R}\\,\\text{10 240} \\end{align*}\n\nHow much interest does he pay?\n\nTo determine the interest amount, we subtract the principal amount from the accumulated amount: \\begin{align*} \\text{Interest amount} &= A-P\\\\ &= \\text{10 240} - \\text{6 400}\\\\ &= \\text{R}\\,\\text{3 840} \\end{align*}\n\nWhat is his monthly instalment?\n\nTo determine the monthly instalment amount, we divide the accumulated amount $$A$$ by the total number of months: \\begin{align*} \\text{Monthly instalment} &= \\frac{A}{\\text{no. of months}}\\\\ &= \\frac{\\text{10 240}}{\\text{4} \\times \\text{12}}\\\\ &= \\text{R}\\,\\text{213,33} \\end{align*}\n\nTalwar buys a cupboard costing $$\\text{R}\\,\\text{5 100}$$ on a hire purchase agreement. He is charged an interest rate of $$\\text{12}\\%$$ p.a. over $$\\text{2}$$ years.\n\nHow much will Talwar pay in total?\n\nRead the question carefully and write down the given information:\n\n\\begin{align*} A & = ? \\\\ P & = \\text{R}\\,\\text{5 100} \\\\ i & = \\frac{12}{100} = \\text{0,12} \\\\ n & = 2 \\end{align*}\n\nTo determine the accumulated loan amount, we use the simple interest formula: \\begin{align*} A &= P(1+in)\\\\ &= \\text{5 100} (\\text{1} + \\text{0,12} \\times \\text{2})\\\\ &= \\text{R}\\,\\text{6 324} \\end{align*}\n\nHow much interest does he pay?\n\nTo determine the interest amount, we subtract the principal amount from the accumulated amount: \\begin{align*} \\text{Interest amount} &= A-P\\\\ &= \\text{6 324} - \\text{5 100}\\\\ &= \\text{R}\\,\\text{1 224} \\end{align*}\n\nWhat is his monthly instalment?\n\nTo determine the monthly instalment amount, we divide the accumulated amount $$A$$ by the total number of months: \\begin{align*} \\text{Monthly instalment} &= \\frac{A}{\\text{no. of months}}\\\\ &= \\frac{\\text{6 324}}{\\text{2} \\times \\text{12}}\\\\ &= \\text{R}\\,\\text{263,50} \\end{align*}\n\nA lounge suite is advertised for sale on TV, to be paid off over $$\\text{36}$$ months at $$\\text{R}\\,\\text{150}$$ per month.\n\nAssuming that no deposit is needed, how much will the buyer pay for the lounge suite once it has been paid off?\n\n$$36 \\times 150 = \\text{R}\\,\\text{5 400}$$\n\nIf the interest rate is $$\\text{9}\\%$$ p.a., what is the cash price of the suite?\n\n\\begin{align*} A & = \\text{5 400}\\\\ P & = ? \\\\ i & = \\text{0,09} \\\\ n & = 3 \\\\\\\\ A & = P(1 + in) \\\\ \\text{5 400} & = P(1 + (\\text{0,09})(3)) \\\\ \\frac{\\text{5 400}}{\\text{1,27}} & = P\\\\ P & = \\text{R}\\,\\text{4 251,97} \\end{align*}\n\nTwo stores are offering a fridge and washing machine combo package. Store A offers a monthly payment of $$\\text{R}\\,\\text{350}$$ over $$\\text{24}$$ months. Store B offers a monthly payment of $$\\text{R}\\,\\text{175}$$ over $$\\text{48}$$ months.\n\nIf both stores offer $$\\text{7,5}\\%$$ interest, which store should you purchase the fridge and washing machine from if you want to pay the least amount of interest?\n\nTo calculate the interest paid at each store we need to first find the cash price of the fridge and washing machine.\n\nStore A:\n\n\\begin{align*} A & = \\text{350} \\times \\text{24} = \\text{8 400}\\\\ P & = ? \\\\ i & = \\text{0,075} \\\\ n & = 2 \\\\\\\\ A & = P(1 + in) \\\\ \\text{8 400} & = P(1 + (\\text{0,075})(2)) \\\\ \\frac{\\text{8 400}}{\\text{1,15}} & = P\\\\ P & = \\text{R}\\,\\text{7 304,45} \\end{align*}\n\nTherefore the interest is $$\\text{R}\\,\\text{8 400} - \\text{R}\\,\\text{7 304,45} = \\text{R}\\,\\text{1 095,65}$$\n\nStore B:\n\n\\begin{align*} A & = \\text{175} \\times \\text{48} = \\text{8 400}\\\\ P & = ? \\\\ i & = \\text{0,075} \\\\ n & = 4 \\\\\\\\ A & = P(1 + in) \\\\ \\text{8 400} & = P(1 + (\\text{0,075})(4)) \\\\ \\frac{\\text{8 400}}{\\text{1,3}} & = P\\\\ P & = \\text{R}\\,\\text{6 461,54} \\end{align*}\n\nTherefore the interest is $$\\text{R}\\,\\text{8 400} - \\text{R}\\,\\text{6 461,54} = \\text{R}\\,\\text{1 938,46}$$\n\nIf you want to pay the least amount in interest you should purchase the fridge and washing machine from store A.\n\nTlali wants to buy a new computer and decides to buy one on a hire purchase agreement. The computers cash price is $$\\text{R}\\,\\text{4 250}$$. He will pay it off over $$\\text{30}$$ months at an interest rate of $$\\text{9,5}\\%$$ p.a. An insurance premium of $$\\text{R}\\,\\text{10,75}$$ is added to every monthly payment. How much are his monthly payments?\n\n\\begin{align*} P & = \\text{4 250} \\\\ i & = \\text{0,095} \\\\ n & = \\frac{30}{12} = \\text{2,5} \\end{align*}\n\nThe question does not mention a deposit, therefore we assume that Tlali did not pay one.\n\n\\begin{align*} A & = P\\left(1 + in\\right) \\\\ A & = \\text{4 250}\\left(1 + \\text{0,095}\\times \\text{2,5}\\right) \\\\ & = \\text{5 259,38} \\end{align*}\n\nThe monthly payment is:\n\n\\begin{align*} \\text{Monthly payment } & = \\frac{\\text{5 259,38}}{36} \\\\ & = \\text{146,09} \\end{align*}\n\nAdd the insurance premium: $$\\text{R}\\,\\text{146,09} + \\text{R}\\,\\text{10,75} = \\text{R}\\,\\text{156,84}$$\n\nRichard is planning to buy a new stove on hire purchase. The cash price of the stove is $$\\text{R}\\,\\text{6 420}$$. He has to pay a $$\\text{10}\\%$$ deposit and then pay the remaining amount off over $$\\text{36}$$ months at an interest rate of $$\\text{8}\\%$$ p.a. An insurance premium of $$\\text{R}\\,\\text{11,20}$$ is added to every monthly payment. Calculate Richard's monthly payments.\n\n\\begin{align*} P & = \\text{6 420} - (\\text{0,10})(\\text{6 420}) = \\text{5 778} \\\\ i & = \\text{0,08} \\\\ n & = \\frac{36}{12} = \\text{3} \\end{align*}\n\nCalculate the accumulated amount:\n\n\\begin{align*} A & = P\\left(1 + in\\right) \\\\ A & = \\text{5 778}\\left(1 + \\text{0,08}\\times \\text{3}\\right) \\\\ & = \\text{7 164,72} \\end{align*}\n\nCalculate the monthly repayments on the hire purchase agreement:\n\n\\begin{align*} \\text{Monthly payment } & = \\frac{\\text{7 164,72}}{36} \\\\ & = \\text{199,02} \\end{align*}\n\nAdd the insurance premium: $$\\text{R}\\,\\text{199,02} + \\text{R}\\,\\text{11,20} = \\text{R}\\,\\text{210,22}$$\n\n### Inflation (EMA6S)\n\nThere are many factors that influence the change in price of an item, one of them is inflation. Inflation is the average increase in the price of goods each year and is given as a percentage. Since the rate of inflation increases year on year, it is calculated using the compound interest formula.\n\n## Worked example 9: Calculating future cost based on inflation\n\nMilk costs $$\\text{R}\\,\\text{14}$$ for two litres. How much will it cost in $$\\text{4}$$ years time if the inflation rate is $$\\text{9}\\%$$ p.a.?\n\n### Write down the known variables\n\n\\begin{align*} P & = 14 \\\\ i & = \\text{0,09} \\\\ n & = 4 \\end{align*}\n\n### Write down the formula\n\n$A = P{\\left(1 + i\\right)}^{n}$\n\n### Substitute the values\n\n\\begin{align*} A & = 14{\\left(1 + \\text{0,09}\\right)}^{4} \\\\ & = \\text{19,76} \\end{align*}\n\nIn four years time, two litres of milk will cost $$\\text{R}\\,\\text{19,76}$$.\n\n## Worked example 10: Calculating past cost based on inflation\n\nA box of chocolates costs $$\\text{R}\\,\\text{55}$$ today. How much did it cost $$\\text{3}$$ years ago if the average rate of inflation was $$\\text{11}\\%$$ p.a.?\n\n### Write down the known variables\n\n\\begin{align*} A & = 55 \\\\ i & = \\text{0,11} \\\\ n & = 3 \\end{align*}\n\n### Write down the formula\n\n$A = P{\\left(1 + i\\right)}^{n}$\n\n### Substitute the values and solve for $$P$$\n\n\\begin{align*} 55 & = P{\\left(1 + \\text{0,11}\\right)}^{3} \\\\ \\frac{55}{{\\left(1 + \\text{0,11}\\right)}^{3}} & = P \\\\ \\therefore P & = \\text{40,22} \\end{align*}\n\nThree years ago, the box of chocolates would have cost $$\\text{R}\\,\\text{40,22}$$.\n\ntemp text\nTextbook Exercise 9.4\n\nThe price of a bag of apples is $$\\text{R}\\,\\text{12}$$. How much will it cost in $$\\text{9}$$ years time if the inflation rate is $$\\text{12}\\%$$ p.a.?\n\nRead the question carefully and write down the given information:\n\n• $$A = ?$$\n• $$P = \\text{R}\\,\\text{12}$$\n• $$n = \\text{9}$$\n• $$i = \\frac{12}{100}$$\n\nTo determine the future cost, we use the compound interest formula: \\begin{align*} A &= P\\left(1+i\\right)^n \\\\ &= \\text{12} \\times \\left(\\text{1} + \\frac{\\text{12}}{\\text{100}}\\right)^{\\text{9}}\\\\ &= \\text{R}\\,\\text{33,28} \\end{align*}\n\nThe price of a bag of potatoes is $$\\text{R}\\,\\text{15}$$.\n\nHow much will it cost in $$\\text{6}$$ years time if the inflation rate is $$\\text{12}\\%$$ p.a.?\n\nRead the question carefully and write down the given information:\n\n• $$A = ?$$\n• $$P = \\text{R}\\,\\text{15}$$\n• $$n = \\text{6}$$\n• $$i = \\frac{12}{100}$$\n\nTo determine the future cost, we use the compound interest formula: \\begin{align*} A &= P\\left(1+i\\right)^n \\\\ &= \\text{15} \\times \\left(\\text{1} + \\frac{\\text{12}}{\\text{100}}\\right)^{\\text{6}}\\\\ &= \\text{R}\\,\\text{29,61} \\end{align*}\n\nThe price of a box of popcorn is $$\\text{R}\\,\\text{15}$$. How much will it cost in $$\\text{4}$$ years time if the inflation rate is $$\\text{11}\\%$$ p.a.?\n\nRead the question carefully and write down the given information:\n\n• $$A = ?$$\n• $$P = \\text{R}\\,\\text{15}$$\n• $$n = \\text{4}$$\n• $$i = \\frac{11}{100}$$\n\nTo determine the future cost, we use the compound interest formula: \\begin{align*} A &= P\\left(1+i\\right)^n \\\\ &= \\text{15} \\times \\left(\\text{1} + \\frac{\\text{11}}{\\text{100}}\\right)^{\\text{4}}\\\\ &= \\text{R}\\,\\text{22,77} \\end{align*}\n\nA box of raisins costs $$\\text{R}\\,\\text{24}$$ today. How much did it cost $$\\text{4}$$ years ago if the average rate of inflation was $$\\text{13}\\%$$ p.a.? Round your answer to 2 decimal places.\n\nRead the question carefully and write down the given information:\n\n• $$A = \\text{R}\\,\\text{24}$$\n• $$P = ?$$\n• $$i = \\frac{13}{100}$$\n• $$n = \\text{4}$$\n\nWe use the compound interest formula and make $$P$$ the subject: \\begin{align*} A &= P\\left(1+i\\right)^n \\\\ P &= \\frac{A}{\\left(1+i\\right)^n} \\\\ &= \\frac{\\text{24}}{\\left(\\text{1} + \\frac{\\text{13}}{\\text{100}}\\right)^{\\text{4}}} \\\\ &= \\text{R}\\,\\text{14,72} \\end{align*}\n\nA box of biscuits costs $$\\text{R}\\,\\text{24}$$ today. How much did it cost $$\\text{5}$$ years ago if the average rate of inflation was $$\\text{11}\\%$$ p.a.? Round your answer to 2 decimal places.\n\nRead the question carefully and write down the given information:\n\n• $$A = \\text{R}\\,\\text{24}$$\n• $$P = ?$$\n• $$i = \\frac{11}{100}$$\n• $$n = \\text{5}$$\n\nWe use the compound interest formula and make $$P$$ the subject: \\begin{align*} A &= P\\left(1+i\\right)^n \\\\ P &= \\frac{A}{\\left(1+i\\right)^n} \\\\ &= \\frac{\\text{24}}{\\left(\\text{1} + \\frac{\\text{11}}{\\text{100}}\\right)^{\\text{5}}} \\\\ &= \\text{R}\\,\\text{14,24} \\end{align*}\n\nIf the average rate of inflation for the past few years was $$\\text{7,3}\\%$$ p.a. and your water and electricity account is $$\\text{R}\\,\\text{1 425}$$ on average, what would you expect to pay in $$\\text{6}$$ years time?\n\n\\begin{align*} A & = ? \\\\ P & = \\text{1 425} \\\\ i & = \\text{0,073} \\\\ n & = 6 \\\\\\\\ A & = P(1 + i)^{n} \\\\ A & = \\text{1 425}(1 + \\text{0,073})^{6} \\\\ A & = \\text{R}\\,\\text{2 174,77} \\end{align*}\n\nThe price of popcorn and a cooldrink at the movies is now $$\\text{R}\\,\\text{60}$$. If the average rate of inflation is $$\\text{9,2}\\%$$ p.a. what was the price of popcorn and cooldrink $$\\text{5}$$ years ago?\n\n\\begin{align*} A & = \\text{R}\\,\\text{60}\\\\ P & = ?\\\\ i & = \\text{0,092}\\\\ n & = 5\\\\ \\\\ A & = P(1 + i)^{n}\\\\ \\\\ 60 &= P(1 + \\text{0,092})^{5}\\\\ \\frac{60}{(\\text{1,092})^5} & = P \\\\ P &= \\text{R}\\,\\text{38,64} \\end{align*}\n\n### Population growth (EMA6T)\n\nFamily trees increase exponentially as every person born has the ability to start another family. For this reason we calculate population growth using the compound interest formula.\n\n## Worked example 11: Population growth\n\nIf the current population of Johannesburg is $$\\text{3 888 180}$$, and the average rate of population growth in South Africa is $$\\text{2,1}\\%$$ p.a., what can city planners expect the population of Johannesburg to be in $$\\text{10}$$ years?\n\n### Write down the known variables\n\n\\begin{align*} P & = \\text{3 888 180} \\\\ i & = \\text{0,021} \\\\ n & = 10 \\end{align*}\n\n### Write down the formula\n\n$A = P{\\left(1 + i\\right)}^{n}$\n\n### Substitute the values\n\n\\begin{align*} A & = \\text{3 888 180}{\\left(1 + \\text{0,021}\\right)}^{10} \\\\ & = \\text{4 786 343} \\end{align*}\n\nCity planners can expect Johannesburg's population to be $$\\text{4 786 343}$$ in ten years time.\n\ntemp text\nTextbook Exercise 9.5\n\nThe current population of Durban is $$\\text{3 879 090}$$ and the average rate of population growth in South Africa is $$\\text{1,1}\\%$$ p.a.\n\nWhat can city planners expect the population of Durban to be in $$\\text{6}$$ years time? Round your answer to the nearest integer.\n\nRead the question carefully and write down the given information:\n\n• $$A = ?$$\n• $$P = \\text{3 879 090}$$\n• $$i = \\frac{1.1}{100}$$\n• $$n = \\text{6}$$\n\nWe use the following formula to determine the expected population for Durban: \\begin{align*} A &= P\\left(1+i\\right)^n\\\\ &= \\text{3 879 090} \\left(\\text{1} + \\frac{\\text{1,1}}{\\text{100}}\\right)^{\\text{6}} \\\\ &= \\text{4 142 255} \\end{align*}\n\nThe current population of Polokwane is $$\\text{3 878 970}$$ and the average rate of population growth in South Africa is $$\\text{0,7}\\%$$ p.a.\n\nWhat can city planners expect the population of Polokwane to be in $$\\text{12}$$ years time? Round your answer to the nearest integer.\n\nRead the question carefully and write down the given information:\n\n• $$A = ?$$\n• $$P = \\text{3 878 970}$$\n• $$i = \\frac{0.7}{100}$$\n• $$n = \\text{12}$$\n\nWe use the following formula to determine the expected population for Polokwane: \\begin{align*} A &= P\\left(1+i\\right)^n\\\\ &= \\text{3 878 970} \\left(\\text{1} + \\frac{\\text{0,7}}{\\text{100}}\\right)^{\\text{12}} \\\\ &= \\text{4 217 645} \\end{align*}\n\nA small town in Ohio, USA is experiencing a huge increase in births. If the average growth rate of the population is $$\\text{16}\\%$$ p.a., how many babies will be born to the $$\\text{1 600}$$ residents in the next $$\\text{2}$$ years?\n\n\\begin{align*} A & = ? \\\\ P & = \\text{1 600} \\\\ i & = \\text{0,16} \\\\ n & = 2 \\\\\\\\ A & = P(1 + i)^{n} \\\\ A &= \\text{1 600}(1 + \\text{0,16})^{2}\\\\ A & = \\text{2 152,96}\\\\ \\text{2 153} - \\text{1 600} & = 553 \\end{align*}\n\nThere will be roughly $$\\text{553}$$ babies born in the next two years."
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https://mathoverflow.net/questions/148925/fantastic-properties-of-z-2z/148942 | [
"Fantastic properties of Z/2Z\n\nRecently I gave a lecture to master's students about some nice properties of the group with two elements $\\mathbb{Z}/2\\mathbb{Z}$. Typically, I wanted to present simple, natural situations where the only group satisfying the given constraints is $\\mathbb{Z}/2\\mathbb{Z}$ (also $\\mathbb{Z}/2\\mathbb{Z}$ as a ring or as a field could qualify, but I'd prefer to stick to the group if possible). Here are some examples of theorems that I proved to the students :\n\n1. Let $G$ be a nontrivial group with trivial automorphism group. Then $G$ is isomorphic to $\\mathbb{Z}/2\\mathbb{Z}$.\n2. Let $G$ be a nontrivial quotient of the symmetric group on $n>4$ letters (nontrivial meaning here different from 1 and the symmetric group itself). Then $G$ is isomorphic to $\\mathbb{Z}/2\\mathbb{Z}$.\n3. Let $k$ be an algebraically closed field and let $k_0$ be a subfield such that $k/k_0$ is finite. Then $k/k_0$ is Galois and $G=\\text{Gal}(k/k_0)$ is isomorphic to $\\mathbb{Z}/2\\mathbb{Z}$. (Moreover $k$ has characteristic $0$ and $k=k_0(i)$ where $i^2=-1$.) This is a theorem of Emil Artin and I actually did not prove it because my students did not have enough background in field theory.\n4. Let $k$ be a field with the following property: there exists a $k$-vector space $E$ of finite dimension $n>1$ and an isomorphism $E\\simeq E^*$ between the space and its linear dual which does not depend on the choice of a basis, i.e. is invariant under $\\text{GL}(E)$. Then $k=\\mathbb{Z}/2\\mathbb{Z}$, $n=2$ and the isomorphism $E\\simeq E^*$ corresponds to the nondegenerate bilinear form given by the determinant.\n\nI am looking for some more fantastic apparitions of $\\mathbb{Z}/2\\mathbb{Z}$. Do you know some?\n\n• Why do you use ${\\bf Z}/2{\\bf Z} =\\{\\{2k+1\\}_{k \\in {\\bf Z}},\\{2k\\}_{k \\in {\\bf Z}}\\}$ and not $G = \\{-1,+1\\}$ ? – Patrick I-Z Nov 14 '13 at 22:15\n• @Patrick: You mean, in order to focus on the group rather than the field? You're right. But as my fourth example shows, I still have some interest for the field $\\mathbb{Z}/2\\mathbb{Z}$, which I certainly write $\\mathbb{F}_2$ in this context, and that's maybe why I wrote things the way I did. – Matthieu Romagny Nov 14 '13 at 22:20\n• For the symmetric group $S_n$, the outer automorphism group $\\textrm{Out}(S_n)=\\textrm{Aut}(S_n) /\\textrm{Inn}(S_n)$ is trivial (i.e. any automorphism is an inner one) unless $n=6$. In fact, $\\textrm{Out}(S_6)=\\mathbf{Z}/2 \\mathbf{Z}$. – Francesco Polizzi Nov 14 '13 at 23:00\n• @MatthieuRomagny: For a proof that without AC you can have such spaces, see this math.SE post. If you have a vector space that has a basis (and hence dimension) with more than one element, then swapping two basis vectors gives you a nontrivial automorphism. If you know that such a basis exists, then you don't need AC to define this automorphism; you need AC to guarantee the existence of bases. However, I believe that existence of nontrivial automorphisms does not imply existence of bases. – Arturo Magidin Nov 15 '13 at 18:32\n• youtube.com/watch?v=UTby_e4-Rhg – Noam D. Elkies Jul 3 '14 at 2:19\n\nA nice theorem is: $\\{\\pm 1\\}$ is the only group that can act freely on a sphere of even dimension. In contrast: There are infinitely many groups acting freely on every odd-dimensional sphere.\n\n• I would say that in the examples above it's the objects that are nice, not the group of two elements. – Lev Borisov Nov 14 '13 at 23:48\n• This is very nice; do you have a reference? – Matthieu Romagny Nov 15 '13 at 10:55\n• Do you mean: the only finite group? – Matthieu Romagny Nov 15 '13 at 11:02\n• @MatthieuRomagny: No, the theorem holds for arbitrary groups. A can be found in Hatcher's book on algebraic topology. It is very easy, once you have the machinery: the mapping degree induces a group morphism $d: G\\to \\{\\pm 1\\}$. Since a fixed point free map $S^n \\to S^n$ has degree $(-1)^{n+1}$ and $n$ is even, the kernel of $d$ is trivial and hence $G\\leq\\{\\pm 1\\}$. – Johannes Hahn Nov 15 '13 at 14:12\n• @JohannesHahn Very nice answer. What other compact manifold $M$ satisfies this property:$Z_{2}$ is the only group with free action on $M$? – Ali Taghavi Nov 9 '14 at 15:39\n\nThis is more of a joke than a serious example. Let $K$ be a field, $K_+$ its additive group, and $K_*$ its multiplicative group. Thus $\\mathbb{R}_*\\cong \\mathbb{R}_+\\times (\\mathbb{Z}/2\\mathbb{Z})$. What fields have the \"opposite\" property, that is, $K_+\\cong K_*\\times (\\mathbb{Z}/2\\mathbb{Z})$? Answer: only $\\mathbb{Z}/2\\mathbb{Z}$.\n\n• Which fields $K$ have $K_{*} \\simeq K_{+} \\times (\\mathbb{Z}/2\\mathbb{Z})$? – Sam Hopkins Nov 15 '13 at 2:27\n• Sam: for starters, $K$ is an exponential field. Take $i$ to be the inclusion of $K_+$ into the product; then $E = \\iota \\circ i_{K_+}$ (where $\\iota$ is the above isomorphism) is an exponential function. According to wikipedia $E$ has trivial image if the characteristic of $K$ is nonzero. $E$ is also injective in this case, but $K_+$ can't be trivial. Therefore $K$ has characteristic zero. Can anyone take it farther than that? – Ibrahim Tencer Nov 15 '13 at 5:50\n• I have asked this question separately: mathoverflow.net/questions/148949 – Sam Hopkins Nov 15 '13 at 6:10\n\nIt is the only non-trivial group whose free square ($G*G$) satisfies a non-trivial identity (or is solvable, or is amenable...)\n\nEdit (Nov 9, 2014), suggested by Sam Nead\n\n... or is virtually cyclic, or is two-ended, or contains no nonabelian free subgroups...\n\n• Let me try, the identity $x^2=e$ ? – Denis Serre Nov 3 '14 at 7:40\n• @Denis, of course not. The infinite dihedral group $Z/2Z*Z/2Z$ has elements of infinite order. – Anton Klyachko Nov 3 '14 at 7:46\n• There are several nice identities - the simplest after a few moments thought is $[x^2, y^2]$. – Sam Nead Nov 9 '14 at 10:51\n• @Sam, I bet your single identity forms a basis of identities of the group. (This means that all other identities are consequences of this one.) – Anton Klyachko Nov 9 '14 at 11:12\n• Oh, that looks nice - I'll have to think about that. By the way, I sort of want to edit your answer: $Z_2 * Z_2$ is the only non-trivial free product that is two-ended (thus is virtually cyclic) while all others have infinitely many ends (so contain rank two free groups, etc). – Sam Nead Nov 9 '14 at 13:44\n\nIt is the only finite group with exactly two conjugacy classes and it is the only non-trivial group with trivial automorphism group.\n\n• That's interesting; I managed to extend this property to all groups whose elements have finite order, and when nontrivial elements have infinite order there are counterexamples built by Higman, Neumann and Neumann in the paper Embedding Theorems for Groups in J. London Math. Soc. 1949. – Matthieu Romagny Nov 17 '13 at 17:03\n\n(In the density model) a random group is either $\\mathbb{Z} / 2\\mathbb{Z}$ or the trivial group. (I learnt this from Danny Calegari but I believe this is origionally due to Gromov.)\n\nMore precisely, fix $k \\geq 2$ and $D \\geq 1/2$. For each $n$ let $X_n$ be the set of reduced words in $x_1^{\\pm 1}, \\ldots, x_k^{\\pm 1}$.\n\nNow consider the group: $$G_n = \\langle x_1, \\ldots, x_k | r_1, \\ldots, r_l \\rangle$$ where each $r_i$ is chosen randomly (independently) from $X_n$ and $l = |X_n|^{D} \\approx (2k - 1)^{nD}$. Then $\\mathbb{P}(G_n \\cong \\mathbb{Z / 2Z} \\textrm{ or } \\mathbb{1}) \\to 1$ as $n \\to \\infty$.\n\nThe proof of this is quite slick and relies on the \"Random Pigeon Hole Principle\": That because of the number of pair of relators are so large you are likely to get a number of almost equal relators, that differ at a single letter, which kills off a generator.\n\n• That is terrific! Do you know a reference where I can read more on this? – Matthieu Romagny Nov 4 '14 at 23:57\n• So I guess that the correct reference should be Gromov's \"Asymptotic invariants of infinite groups\" but it is ~300 pages and I haven't read it. Danny gave a talk at Cornell and in the first ~15 mins he covers the density model and gives a sketch of this result. It's available here: cornell.edu/video/danny-calegari-random-groups-diamonds-glass – Mark Bell Nov 5 '14 at 7:50\n\nJust a comment. You are probably looking for \"fantastic properties\" stated in terms of group theory, \"if an (abstract) group has such and such properties then it is $Z/2Z$\". However various representations of this group also have \"fantastic properties\". I mean first of all the group of automorphisms $C/R$ which consists of complex conjugation and identity. Several important subjects, like \"real algebraic geometry\" are based on these properties. Once I was strongly tempted to call my paper \"Some applications of representation theory of the group of 2 elements\", but my co-author convinced me that this title would be too radical.\n\nThe paper I mentioned is: Wronski map and Grassmannians of real codimension 2 subspaces, Computational Methods and Function Theory, 1 (2001) 1-25.\n\nAn example from differential geometry: If M is a compact, even-dimensional Riemannian manifold of positive sectional curvature, then its fundamental group is either 1 or Z/2Z.\n\nequivalently: a group acting freely on a compact, even-dimensional Riemannian manifold of positive sectional curvature is 1 or Z/2Z.\n\nThis is a variant of Synge's Theorem.\n\nThe automorphism group of the category of categories is $\\mathbb{Z}/2$.\n\nThat is, the group of invertible functors $F: \\mathrm{Cat} \\to \\mathrm{Cat}$ is $\\mathbb{Z}/2$.\n\n• Do you have a reference for this? – Ivan Di Liberti Aug 6 '18 at 23:14\n• Sorry, I can't find one now. It's pretty easy to prove. – John Baez Aug 8 '18 at 3:39\n• In higher category theory there are results as described here: golem.ph.utexas.edu/category/2011/11/… – David Corfield Aug 8 '18 at 8:36\n• Can you tell what is the generator of this group? If you're thinking about the functor $F$ that takes a category to its opposite, then I'm not sure it's a functor $F:\\mathrm{Cat}\\to \\mathrm{Cat}$. The problem is that $F$ maps $\\mathrm{Fun}(C,D)$ into $\\mathrm{Fun}(C^\\circ,D^\\circ)^\\circ$ rather than into $\\mathrm{Fun}(C^\\circ,D^\\circ)$. – Matthieu Romagny Sep 28 '18 at 13:09\n• Ah, maybe you mean $\\mathrm{Cat}$ as a 1-category? In this case $\\mathrm{Fun}(C,D)$ is just a set and the problem does not arise. – Matthieu Romagny Sep 28 '18 at 19:10\n\n$Z/2Z$ is abelian group which is canonically isomorphic to its dual abelian group. (Since dual group is again $Z/2Z$ and there is only one automorphism of $Z/2Z$).\n\nActually it is not the only group with this property, and another one is again related to $Z/2Z$. It is the group $Z/2Z \\oplus Z/2Z$: the dual group is group of characters, the kernel of each character contains two elements - identity and another one , so we can set a bijection: character <-> non-identity element in the kernel. This example is the same as item 4, in the original question.\n\nIsn't it remarkable that the fundamental group of the special orthogonal group $SO_n$ is $\\mathbb Z/2\\mathbb Z$ for $n\\ge3$ ?\n\n• Why is that remarkable? – Todd Trimble Nov 3 '14 at 7:52\n\nThe largest group which has embeddings into every nonabelian finite simple group is the Cartesian square of this group.\n\nLet $G$ be a group. The holomorph $Hol(G) = G \\rtimes Aut(G)$ can be regarded as a subgroup of the symmetric group $S_{|G|}$, by considering the functions $f: G \\to G$ sending $x \\in G$ to $x^{\\alpha} \\cdot g$, for $g \\in G$ and $\\alpha \\in Aut(G)$.\nThis is never a self-normalizing subgroup of $S_{|G|}$ when $G$ is nonabelian, because any anti-automorphism of $G$, including $x \\to x^{-1}$, normalizes it but is not in it. So $N_{ S_{ |G|} } (Hol(G))/Hol(G)$ always has a subgroup of order 2 in this case.\n\nThe only nontrivial groups lacking proper subgroups are the cyclic groups of prime order. Among these, only a cyclic group of order 2 can be isomorphic to the unique minimal subgroup of two nonisomorphic finite groups of the same order (a cyclic group and a quaternion group, when the order is a power of 2).\n\nLet $G$ be a nonabelian group in which all subgroups are normal. Then $G$ is isomorphic to the Cartesian product of a abelian torsion group in which all elements have odd order, the quaternion group $Q_{8}$, and a group of exponent 2 (by the Axiom of Choice, this last factor is a vector space over the field $\\mathbb{Z}/(2)$, as mentioned before).\n\nNotice how the group of exponent 2 above did not need to be required to be abelian? If $G$ is a group and all cyclic subgroups of $G$ are of order 2, it immediately follows that $G$ is abelian.\n\n• Instead of \"by the Axiom of Choice, this last factor is a vector space over the field Z/(2), as mentioned before\" I would rather write : \"this last factor is a vector space over the field Z/(2), and by the Axiom of Choice it has a basis, as mentioned before\". – Matthieu Romagny Aug 28 '18 at 13:09\n\nRH holds if and only if the group of isometries of the complex plane that preserve globally the multiset of non-trivial zeroes of the Riemann Zeta function is isomorphic to $Z/2Z$ (otherwise, it would be isomorphic to $Z/2Z\\times Z/2Z$).\n\n• Can you elaborate on this example or maybe give some reference where this result is explained or implied? – bonif Jan 8 '18 at 11:00\n• From the functional equation of $\\zeta$, a hypothetical non trivial zero off the critical line gives rise to a second one which is its image under the map $s\\mapsto 1-\\bar{s}$. This map coincides with identity for zeroes on this line. As the Dirichlet coefficients of $\\zeta$ are real, the map $s\\mapsto\\bar{s}$ maps a non trivial zero of zeta to a non trivial zero of $\\zeta$. Hence the two maps $s\\mapsto s$ and $s\\mapsto\\bar{s}$ are the symmetries of the multiset of non trivial zeroes of $\\zeta$. Adding a hypothetical zero off the line gives rise to the additional... – Sylvain JULIEN Jan 8 '18 at 12:03\n• ...symmetry $s\\mapsto 1-\\bar{s}$ and hence generates a global symmetry group isomorphic to $\\Z/2\\Z\\times\\Z/2\\Z$. As I said, the absence of zero off the line forces the maps $s\\mapsto s$ and $s\\mapsto 1-\\bar{s}$ to coincide, reducing the global isometry group to a single copy of $\\Z/2\\Z$ . – Sylvain JULIEN Jan 8 '18 at 12:06\n• Has this been published somewhere? Coming from the theoretical physics camp I can see off the top of my head there are some possible immediate physical analogies with this. – bonif Jan 8 '18 at 12:33\n• I strongly doubt it. As far as I know, I'm probably the only person to consider RH might be true investigating the symmetries of $\\zeta$ or equivalently of the multiset of non trivial zeroes thereof. I'd be glad to be proven wrong though. – Sylvain JULIEN Jan 8 '18 at 13:47\n\nEdit after Emil's comment (so my answer is not really good then): It's a group (or any product of it) where addition and substraction seen as a binary (that is, $- = + \\circ (Id, i)$ where $i$ is the inverse map) actually coincides. Note that this also means that it's a group where $-$ is actually associative.\n\n• Every group of exponent 2 has this property. These are not just products of $\\mathbb Z/2\\mathbb Z$, you also have to close them under subgroups. Again, this doesn't make the two-element group special, as every nontrivial group of exponent 2 generates the class of all of them using products and subgroups. – Emil Jeřábek Nov 2 '14 at 12:39\n• @Emil, every group of exponent two is a direct product of several two-element groups (if you believe the Axiom of Choice). – Anton Klyachko Nov 3 '14 at 2:13\n• @AntonKlyachko Every group of exponent two is a direct sum of two-element groups. (Finite direct sums coincide with finite direct products, but infinite direct sums need not be infinite direct products.) – Todd Trimble Nov 3 '14 at 7:21\n• @Todd, I understand you but I prefer to use slightly different terminology. See this discussion in comments: mathoverflow.net/q/92972/24165 – Anton Klyachko Nov 3 '14 at 7:42\n• @AntonKlyachko Okay, thanks for clarifying. The boldfaced \"is\" in your response to Emil sounded to me like a correction, when in fact what he wrote was already correct according to his word usage (and resonates in other ways as well). – Todd Trimble Nov 3 '14 at 12:13\n\nThe central multiplicative action of $(\\mathbb{Z}/2\\mathbb{Z})^r$ on the cohomology ring $H^∗(\\mathfrak{X}_r(SU(2)))$ is trivial, where $\\mathfrak{X}_r(SU(2))$ is the character variety $SU(2)^r/SU(2)$. This ultimately allows for the computation of the Poincaré polynomial of the real moduli spaces $\\mathfrak{X}_r(SL(3,\\mathbb{R}))$."
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https://www.colorhexa.com/18f02e | [
"# #18f02e Color Information\n\nIn a RGB color space, hex #18f02e is composed of 9.4% red, 94.1% green and 18% blue. Whereas in a CMYK color space, it is composed of 90% cyan, 0% magenta, 80.8% yellow and 5.9% black. It has a hue angle of 126.1 degrees, a saturation of 87.8% and a lightness of 51.8%. #18f02e color hex could be obtained by blending #30ff5c with #00e100. Closest websafe color is: #00ff33.\n\n• R 9\n• G 94\n• B 18\nRGB color chart\n• C 90\n• M 0\n• Y 81\n• K 6\nCMYK color chart\n\n#18f02e color description : Vivid lime green.\n\n# #18f02e Color Conversion\n\nThe hexadecimal color #18f02e has RGB values of R:24, G:240, B:46 and CMYK values of C:0.9, M:0, Y:0.81, K:0.06. Its decimal value is 1634350.\n\nHex triplet RGB Decimal 18f02e `#18f02e` 24, 240, 46 `rgb(24,240,46)` 9.4, 94.1, 18 `rgb(9.4%,94.1%,18%)` 90, 0, 81, 6 126.1°, 87.8, 51.8 `hsl(126.1,87.8%,51.8%)` 126.1°, 90, 94.1 00ff33 `#00ff33`\nCIE-LAB 83.288, -80.031, 72.704 32.028, 62.708, 13 0.297, 0.582, 62.708 83.288, 108.124, 137.746 83.288, -77.095, 96.946 79.188, -66.385, 45.698 00011000, 11110000, 00101110\n\n# Color Schemes with #18f02e\n\n• #18f02e\n``#18f02e` `rgb(24,240,46)``\n• #f018da\n``#f018da` `rgb(240,24,218)``\nComplementary Color\n• #6ef018\n``#6ef018` `rgb(110,240,24)``\n• #18f02e\n``#18f02e` `rgb(24,240,46)``\n• #18f09a\n``#18f09a` `rgb(24,240,154)``\nAnalogous Color\n• #f0186e\n``#f0186e` `rgb(240,24,110)``\n• #18f02e\n``#18f02e` `rgb(24,240,46)``\n• #9a18f0\n``#9a18f0` `rgb(154,24,240)``\nSplit Complementary Color\n• #f02e18\n``#f02e18` `rgb(240,46,24)``\n• #18f02e\n``#18f02e` `rgb(24,240,46)``\n• #2e18f0\n``#2e18f0` `rgb(46,24,240)``\n• #daf018\n``#daf018` `rgb(218,240,24)``\n• #18f02e\n``#18f02e` `rgb(24,240,46)``\n• #2e18f0\n``#2e18f0` `rgb(46,24,240)``\n• #f018da\n``#f018da` `rgb(240,24,218)``\n• #0bb01c\n``#0bb01c` `rgb(11,176,28)``\n• #0dc820\n``#0dc820` `rgb(13,200,32)``\n• #0fe024\n``#0fe024` `rgb(15,224,36)``\n• #18f02e\n``#18f02e` `rgb(24,240,46)``\n• #30f244\n``#30f244` `rgb(48,242,68)``\n• #48f359\n``#48f359` `rgb(72,243,89)``\n• #60f56f\n``#60f56f` `rgb(96,245,111)``\nMonochromatic Color\n\n# Alternatives to #18f02e\n\nBelow, you can see some colors close to #18f02e. Having a set of related colors can be useful if you need an inspirational alternative to your original color choice.\n\n• #38f018\n``#38f018` `rgb(56,240,24)``\n• #26f018\n``#26f018` `rgb(38,240,24)``\n• #18f01c\n``#18f01c` `rgb(24,240,28)``\n• #18f02e\n``#18f02e` `rgb(24,240,46)``\n• #18f040\n``#18f040` `rgb(24,240,64)``\n• #18f052\n``#18f052` `rgb(24,240,82)``\n• #18f064\n``#18f064` `rgb(24,240,100)``\nSimilar Colors\n\n# #18f02e Preview\n\nThis text has a font color of #18f02e.\n\n``<span style=\"color:#18f02e;\">Text here</span>``\n#18f02e background color\n\nThis paragraph has a background color of #18f02e.\n\n``<p style=\"background-color:#18f02e;\">Content here</p>``\n#18f02e border color\n\nThis element has a border color of #18f02e.\n\n``<div style=\"border:1px solid #18f02e;\">Content here</div>``\nCSS codes\n``.text {color:#18f02e;}``\n``.background {background-color:#18f02e;}``\n``.border {border:1px solid #18f02e;}``\n\n# Shades and Tints of #18f02e\n\nA shade is achieved by adding black to any pure hue, while a tint is created by mixing white to any pure color. In this example, #010801 is the darkest color, while #f5fef6 is the lightest one.\n\n• #010801\n``#010801` `rgb(1,8,1)``\n• #021b04\n``#021b04` `rgb(2,27,4)``\n• #032d07\n``#032d07` `rgb(3,45,7)``\n• #04400a\n``#04400a` `rgb(4,64,10)``\n• #05520d\n``#05520d` `rgb(5,82,13)``\n• #076510\n``#076510` `rgb(7,101,16)``\n• #087713\n``#087713` `rgb(8,119,19)``\n• #098916\n``#098916` `rgb(9,137,22)``\n• #0a9c19\n``#0a9c19` `rgb(10,156,25)``\n• #0bae1c\n``#0bae1c` `rgb(11,174,28)``\n• #0dc11f\n``#0dc11f` `rgb(13,193,31)``\n• #0ed322\n``#0ed322` `rgb(14,211,34)``\n• #0fe525\n``#0fe525` `rgb(15,229,37)``\n• #18f02e\n``#18f02e` `rgb(24,240,46)``\n• #2af13f\n``#2af13f` `rgb(42,241,63)``\n• #3df24f\n``#3df24f` `rgb(61,242,79)``\n• #4ff460\n``#4ff460` `rgb(79,244,96)``\n• #62f571\n``#62f571` `rgb(98,245,113)``\n• #74f681\n``#74f681` `rgb(116,246,129)``\n• #87f792\n``#87f792` `rgb(135,247,146)``\n• #99f8a3\n``#99f8a3` `rgb(153,248,163)``\n• #abfab3\n``#abfab3` `rgb(171,250,179)``\n• #befbc4\n``#befbc4` `rgb(190,251,196)``\n• #d0fcd5\n``#d0fcd5` `rgb(208,252,213)``\n• #e3fde5\n``#e3fde5` `rgb(227,253,229)``\n• #f5fef6\n``#f5fef6` `rgb(245,254,246)``\nTint Color Variation\n\n# Tones of #18f02e\n\nA tone is produced by adding gray to any pure hue. In this case, #808881 is the less saturated color, while #0ff926 is the most saturated one.\n\n• #808881\n``#808881` `rgb(128,136,129)``\n• #779179\n``#779179` `rgb(119,145,121)``\n• #6d9b72\n``#6d9b72` `rgb(109,155,114)``\n• #64a46a\n``#64a46a` `rgb(100,164,106)``\n• #5aae63\n``#5aae63` `rgb(90,174,99)``\n• #51b75b\n``#51b75b` `rgb(81,183,91)``\n• #47c154\n``#47c154` `rgb(71,193,84)``\n• #3eca4c\n``#3eca4c` `rgb(62,202,76)``\n• #34d445\n``#34d445` `rgb(52,212,69)``\n• #2bdd3d\n``#2bdd3d` `rgb(43,221,61)``\n• #21e736\n``#21e736` `rgb(33,231,54)``\n• #18f02e\n``#18f02e` `rgb(24,240,46)``\n• #0ff926\n``#0ff926` `rgb(15,249,38)``\nTone Color Variation\n\n# Color Blindness Simulator\n\nBelow, you can see how #18f02e is perceived by people affected by a color vision deficiency. This can be useful if you need to ensure your color combinations are accessible to color-blind users.\n\nMonochromacy\n• Achromatopsia 0.005% of the population\n• Atypical Achromatopsia 0.001% of the population\nDichromacy\n• Protanopia 1% of men\n• Deuteranopia 1% of men\n• Tritanopia 0.001% of the population\nTrichromacy\n• Protanomaly 1% of men, 0.01% of women\n• Deuteranomaly 6% of men, 0.4% of women\n• Tritanomaly 0.01% of the population"
] | [
null
] | {"ft_lang_label":"__label__en","ft_lang_prob":0.50598323,"math_prob":0.6940066,"size":3673,"snap":"2020-24-2020-29","text_gpt3_token_len":1642,"char_repetition_ratio":0.12591986,"word_repetition_ratio":0.011090573,"special_character_ratio":0.5578546,"punctuation_ratio":0.23430493,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.98540115,"pos_list":[0],"im_url_duplicate_count":[null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2020-07-12T19:23:26Z\",\"WARC-Record-ID\":\"<urn:uuid:6849c422-e22a-4114-bd5f-ae5ffea3c723>\",\"Content-Length\":\"36257\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:ddf29c44-5c45-4b04-a18d-6933e8c51a23>\",\"WARC-Concurrent-To\":\"<urn:uuid:4715bf4a-5808-4da9-afab-33975cd0828a>\",\"WARC-IP-Address\":\"178.32.117.56\",\"WARC-Target-URI\":\"https://www.colorhexa.com/18f02e\",\"WARC-Payload-Digest\":\"sha1:ZIOFSOEQE7VIYKEWN72FMOKCVJEO42LO\",\"WARC-Block-Digest\":\"sha1:MZO5QURWROGCNLJV4DFUOVQZYYAXRRVA\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2020/CC-MAIN-2020-29/CC-MAIN-2020-29_segments_1593657139167.74_warc_CC-MAIN-20200712175843-20200712205843-00070.warc.gz\"}"} |
https://www.electronics-tutorial.net/Digital-CMOS-Design/CMOS-Inverter/Noise-Margin/ | [
"Home > Digital CMOS Design > CMOS Inverter > Noise Margin\n\nCMOS-Inverter\n\nNoise Margin :\n\nIn digital integrated circuits, to minimize the noise it is necessary to keep \"0\" and \"1\" intervals broader. Hence noise margin is the measure of the sensitivity of a gate to noise and expressed by, NML (noise margin Low) and NMH (noise margin High).\n\nNML and NMH are defined as,\n\nNML = VIL VOL and NMH = VOH VIH\n\nIn order to define the terms VIL, VOL, VOH and VIH again consider the VTC of Inverter as shown in Figure below. The VOH is the maximum output voltage at which the output is \"logic high\". The VOL is the minimum output voltage at which the output is \"logic low\". The regions of acceptable high and low voltages are defined by VIH and VIL respectively. VIH and VIL represents the points where the gain dVoutdVin of VTC is equals to 1 as shown in above Figure. The region between VIH and VIL is called as the undefined region or transition width.",
null,
"Fig2-Noise-Margin\n\nFigure below shows the NMH and NML levels of two cascaded inverters. The noise margin shows the levels of noise when the gates are connected together. For the digital integrated circuits the noise margin is larger than '0' and ideally it is high.",
null,
"Fig2-Noise-Margin"
] | [
null,
"https://www.electronics-tutorial.net/Digital-CMOS-Design/CMOS-Inverter/Noise-Margin/Fig1-Noise-Margin.png",
null,
"https://www.electronics-tutorial.net/Digital-CMOS-Design/CMOS-Inverter/Noise-Margin/Fig2-Noise-Margin.png",
null
] | {"ft_lang_label":"__label__en","ft_lang_prob":0.90029603,"math_prob":0.9698782,"size":1165,"snap":"2023-40-2023-50","text_gpt3_token_len":284,"char_repetition_ratio":0.13953489,"word_repetition_ratio":0.03902439,"special_character_ratio":0.21630901,"punctuation_ratio":0.0745614,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.9677044,"pos_list":[0,1,2,3,4],"im_url_duplicate_count":[null,5,null,5,null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2023-09-30T20:18:20Z\",\"WARC-Record-ID\":\"<urn:uuid:7511283d-7c53-44db-9a4b-11d8dd6a83ea>\",\"Content-Length\":\"109227\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:ab3f6669-e23a-44c4-a1c2-44ecaac481d3>\",\"WARC-Concurrent-To\":\"<urn:uuid:078df1b1-d547-4393-bb43-8125fd8567ef>\",\"WARC-IP-Address\":\"172.67.134.138\",\"WARC-Target-URI\":\"https://www.electronics-tutorial.net/Digital-CMOS-Design/CMOS-Inverter/Noise-Margin/\",\"WARC-Payload-Digest\":\"sha1:3AMFHD7IYAXQ2YWVRQBJH2COXVYXDBXN\",\"WARC-Block-Digest\":\"sha1:TBYAUK2UXZYUYEHEIVDTQ4HNGYWBLPFA\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2023/CC-MAIN-2023-40/CC-MAIN-2023-40_segments_1695233510707.90_warc_CC-MAIN-20230930181852-20230930211852-00333.warc.gz\"}"} |
https://lms.aotawhiti.school.nz/?q=node/208160 | [
"# 2018 Term 4 HB Hawk Stage 6 Maths Group\n\n• Posted on: 10 October 2018\n• By: libbyboyd\n\nStage 6 maths group will attend workshops 2-3x per week and complete 3-4 Maths buddy sessions as follow up Must Dos..\n\nThis term we will be focusing on FRACTIONS.\nWe will be learning to order fractions, make and convert improper fractions, convert fractions to decimals and percentages, all using materials, imaging and number properties.\n1. Know fractions and percentages and decimals in everyday use.\n\nWe will also be practicing our time tables for speedy recall with regular speed tests each session.\n\nWe will continue to use and revise Number Strategies and Knowledge:\n- Use a range of multiplicative strategies when operating on whole numbers.\n- Understand addition and subtraction of fractions, decimals, and integers.\n- Apply simple linear proportions, including ordering fractions.\n- Know the relative size and place value structure of positive and negative integers and decimals to three decimals.\n\nLearning Area:\nTo Do List:\npractice my times tables\nhave a good attitude when learning new and maybe difficult concepts\nCome to my maths group and participate positively\nComplete must dos on Maths Buddy on time.\nLA Code:\nLevels:\n2\n3\nYear:"
] | [
null
] | {"ft_lang_label":"__label__en","ft_lang_prob":0.759583,"math_prob":0.88462526,"size":943,"snap":"2019-13-2019-22","text_gpt3_token_len":183,"char_repetition_ratio":0.14483494,"word_repetition_ratio":0.0,"special_character_ratio":0.19724284,"punctuation_ratio":0.11377245,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.9611071,"pos_list":[0],"im_url_duplicate_count":[null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2019-03-19T10:24:28Z\",\"WARC-Record-ID\":\"<urn:uuid:d601f57f-819c-4638-80c2-d844eb2abe2a>\",\"Content-Length\":\"15235\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:b2d1658e-7dba-4444-b023-5f3a24687dfc>\",\"WARC-Concurrent-To\":\"<urn:uuid:2566c768-5db1-45de-90bb-ea6877c1b929>\",\"WARC-IP-Address\":\"111.69.22.43\",\"WARC-Target-URI\":\"https://lms.aotawhiti.school.nz/?q=node/208160\",\"WARC-Payload-Digest\":\"sha1:KK5PPQTB2DNYNFH7TFJ54ETVBULEQ6JK\",\"WARC-Block-Digest\":\"sha1:EXNSTDRFHKS4BBB23Y3N5COQWJAQWHC5\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2019/CC-MAIN-2019-13/CC-MAIN-2019-13_segments_1552912201953.19_warc_CC-MAIN-20190319093341-20190319115341-00516.warc.gz\"}"} |
https://shtools.oca.eu/shtools/pyshsjkpg.html | [
"Calculate the expectation of the product of two functions, each multiplied by a different data taper, for a given spherical harmonic degree and two different angular orders.\n\n## Usage\n\nvalue = SHSjkPG (incspectra, l, m, mprime, hj_real, hk_real, mj, mk, lwin, hkcc)\n\n## Returns\n\nvalue : complex\nThe expectation of the product of two functions, each multiplied by a different data taper, for a given spherical harmonic degree and two different angular orders.\n\n## Parameters\n\nincspectra : float, dimension (l+lwin+1)\nThe global cross-power spectrum of f and g.\nl : integer\nThe spherical harmonic degree for which to calculate the expectation.\nm : integer\nThe angular order of the first localized function, Phi.\nmprime : integer\nThe angular order of the second localized function, Gamma.\nhj_real : float, dimension (lwin+1)\nThe real spherical harmonic coefficients of angular order mj used to localize the first function f. These are obtained by a call to SHReturnTapers.\nhk_real : float, dimension (lwin+1)\nThe real spherical harmonic coefficients of angular order mk used to localize the second function g. These are obtained by a call to SHReturnTapers.\nmj : integer\nThe angular order of the window coefficients hj_real.\nmk : integer\nThe angular order of the window coefficients hk_real.\nlwin : integer\nthe spherical harmonic bandwidth of the localizing windows hj_real and hk_real.\nhkcc : integer\nIf 1, the function described in the description will be calculated as is. If 2, the second localized function Gamma will not have its complex conjugate taken.\n\n## Description\n\nSHSjkPG will calculate the expectation of two functions (f and g), each localized by a different data taper that is a solution of the spherical cap concentration problem, for a given spherical harmonic degree and two different angular orders. As described in Wieczorek and Simons (2007), this is the function\n\n / m(j) mprime(k)* \\\n| Phi Gamma |\n\\ l l /\n\n\nThe global cross-power spectrum of f and g is input as incspectra, and the real coefficients of the two data tapers of angular order mj and mk (obtained by a call to SHReturnTapers) are specified by hj_real and hk_real. If hkcc is set to 1, then the above function is calculated as is. However, if this is set to 2, then the complex conjugate of the second localized function is not taken.\n\nWieczorek, M. A. and F. J. Simons, Minimum-variance multitaper spectral estimation on the sphere, J. Fourier Anal. Appl., 13, doi:10.1007/s00041-006-6904-1, 665-692, 2007."
] | [
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] | {"ft_lang_label":"__label__en","ft_lang_prob":0.7698037,"math_prob":0.97641927,"size":2509,"snap":"2019-13-2019-22","text_gpt3_token_len":644,"char_repetition_ratio":0.13732535,"word_repetition_ratio":0.21666667,"special_character_ratio":0.23834197,"punctuation_ratio":0.16052061,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.9957222,"pos_list":[0],"im_url_duplicate_count":[null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2019-03-20T01:13:20Z\",\"WARC-Record-ID\":\"<urn:uuid:2263c7d8-46bd-460b-a3b2-7c277748fa3a>\",\"Content-Length\":\"21127\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:5a6e0083-4754-4d35-8acc-3433bf982fc3>\",\"WARC-Concurrent-To\":\"<urn:uuid:518c26f1-9731-43a9-8d7e-6eecbe489387>\",\"WARC-IP-Address\":\"192.54.174.144\",\"WARC-Target-URI\":\"https://shtools.oca.eu/shtools/pyshsjkpg.html\",\"WARC-Payload-Digest\":\"sha1:VFRVO6SQY23WVDXUN5GWMRMBW33PLXUU\",\"WARC-Block-Digest\":\"sha1:VWDJZPLZYSRALLRRZWGWQI4AWG4NMJTS\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2019/CC-MAIN-2019-13/CC-MAIN-2019-13_segments_1552912202188.9_warc_CC-MAIN-20190320004046-20190320030046-00267.warc.gz\"}"} |
https://www.cs.umd.edu/class/fall2020/cmsc828u/ | [
"Welcome to CMSC828U, Algorithms in Machine Learning: Guarantees and Analyses (Fall'20)!\n\n## Description\n\nMachine learning studies automatic methods for learning to make accurate predictions, to understand patterns in observed features and to make useful decisions based on past observations.\n\nThis course introduces theoretical machine learning, including mathematical models of machine learning, and the design and rigorous analysis of learning algorithms.\n\nHere is a tentative list of topics. (Bullets do not correspond precisely to lectures.)\n\n- PAC learning basics, and PAC learning in Neural Networks\n\n- Boosting and unsupervised boosting\n\n- Graphical model basics\n\n- Spectral methods: a case study of consistent algorithms\n\n- Reinforcement learning\n\n## Prerequisite\n\nMinimum grade of A- in CMSC422 (or equivalent) or CMSC498M; permission of CMNS-Computer Science department and instructor.\n\n- Basic machine learning concepts\n\n* Supervised/unsupervised/reinforcement learning\n\n* Classification, Regression, Cross validation, Overfitting, Generalization\n\n* Deep neural networks\n\n- Basic calculus and linear algebra\n\n* Compute (by hand) gradients of multivariate functions\n\n* Conceptualize dot products and matrix multiplications as projections\n\n* Solve multivariate equations using, etc, matrix inversion, etc\n\n* Understand basic matrix factorization\n\n- Basic optimization\n\n* Use techniques of Lagrange multipliers for constrained optimization problems\n\n* Understand and be able to use convexity\n\n- Basic probability and statistics\n\n* Understand: random variables, expectations and variance\n\n* Use chain rule, marginalization rule and Bayes' rule\n\n* Make use of conditional independence, and understand \"explaining away\"\n\n* Compute maximum likelihood solutions for Bernoulli and Gaussian distributions\n\nLecture scribing (40%)\n\nHomeworks (20%)\n\nParticipation(10%)\n\nCourse project(30%)\n\n### When & where\n\nTuesday/Thursday 3:30pm-4:45pm\nOnline\n\n### Instructors\n\nFurong Huang\nOffice hours: TBA"
] | [
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] | {"ft_lang_label":"__label__en","ft_lang_prob":0.82730716,"math_prob":0.7692153,"size":1805,"snap":"2021-31-2021-39","text_gpt3_token_len":372,"char_repetition_ratio":0.11771238,"word_repetition_ratio":0.0,"special_character_ratio":0.18614958,"punctuation_ratio":0.09803922,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.9814693,"pos_list":[0],"im_url_duplicate_count":[null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2021-09-18T22:36:50Z\",\"WARC-Record-ID\":\"<urn:uuid:bb49be68-4444-4736-bb60-85204857bdec>\",\"Content-Length\":\"8351\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:c4a8c1d5-3e20-4d9b-b2ad-0e177173fd79>\",\"WARC-Concurrent-To\":\"<urn:uuid:94673a19-552f-4592-bbbe-4f1a6a6904df>\",\"WARC-IP-Address\":\"128.8.127.4\",\"WARC-Target-URI\":\"https://www.cs.umd.edu/class/fall2020/cmsc828u/\",\"WARC-Payload-Digest\":\"sha1:UCLMIWGGSOYCWP2C3L725R5MH4JXXBFJ\",\"WARC-Block-Digest\":\"sha1:JCGK4VVVMDTGHEB3IVMYCAULJQ2N4WGJ\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2021/CC-MAIN-2021-39/CC-MAIN-2021-39_segments_1631780056578.5_warc_CC-MAIN-20210918214805-20210919004805-00255.warc.gz\"}"} |
https://www.geeksforgeeks.org/java-class-and-object-question-4-2/?ref=rp | [
"# Java | Class and Object | Question 4\n\n• Difficulty Level : Medium\n• Last Updated : 28 Jun, 2021\n\nPredict the output of following Java program.\n\n `class` `demoClass``{`` ``int` `a = ``1``;`` ` ` ``void` `func()`` ``{`` ``demo obj = ``new` `demo();`` ``obj.display();`` ``}`` ` ` ` ` ``class` `demo`` ``{`` ``int` `b = ``2``;`` ` ` ``void` `display()`` ``{`` ``System.out.println(``\"\\na = \"` `+ a);`` ``}`` ``}`` ` ` ``void` `get()`` ``{`` ``System.out.println(``\"\\nb = \"` `+ b);`` ``}``}`` ` ` ` `class` `Test``{`` ``public` `static` `void` `main(String[] args)`` ``{`` ``demoClass obj = ``new` `demoClass();`` ``obj.func();`` ``obj.get();`` ` ` ``}``}`\n\n(A)\n\n```a = 1\nb = 2```\n\n(B) Compilation error\n\n(C)\n\n```b = 2\na = 1```"
] | [
null
] | {"ft_lang_label":"__label__en","ft_lang_prob":0.5326272,"math_prob":0.88530266,"size":690,"snap":"2022-27-2022-33","text_gpt3_token_len":210,"char_repetition_ratio":0.12536444,"word_repetition_ratio":0.0,"special_character_ratio":0.3478261,"punctuation_ratio":0.1641791,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.99656934,"pos_list":[0],"im_url_duplicate_count":[null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2022-07-01T13:22:44Z\",\"WARC-Record-ID\":\"<urn:uuid:5db5cb4c-429c-4415-903b-c8122e3d3c2b>\",\"Content-Length\":\"125062\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:9b165108-ff3a-4a05-b2db-4d35086097e6>\",\"WARC-Concurrent-To\":\"<urn:uuid:97b4d65b-6deb-4651-9053-7fea7e5c8da7>\",\"WARC-IP-Address\":\"23.199.63.170\",\"WARC-Target-URI\":\"https://www.geeksforgeeks.org/java-class-and-object-question-4-2/?ref=rp\",\"WARC-Payload-Digest\":\"sha1:N7KD3DAA2AMFLBOWRQRUW75DFUQFOMMT\",\"WARC-Block-Digest\":\"sha1:YAAJHRBMZNRMF7HKTCCY6QB5YGKHL2VV\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2022/CC-MAIN-2022-27/CC-MAIN-2022-27_segments_1656103941562.52_warc_CC-MAIN-20220701125452-20220701155452-00493.warc.gz\"}"} |
https://atarax25.com/math-solving-140 | [
"# Find the leg of a right triangle\n\nThis type of triangle can be used to evaluate trigonometric functions for multiples of π/6. 45°-45°-90° triangle: The 45°-45°-90° triangle, also referred to as an isosceles right triangle, since it\n\nSolve Now",
null,
"## Student reviews\n\nLearn math, check homework and study for upcoming tests and ACTs/SATs with the most used math learning app in the world! Got tricky homework or class assignments? Get unstuck ASAP with our step-by-step explanations and animations. This app is awesome.\n\nBruce Lockett\n\nThis app is perfect for students that are confused with some math problems, but don't depend on it in homework. Very user friendly and the photo feature us very well set up. This app has saved me so many times with my homework. The best app I've ever seen, this app helps you a lot with Math problems without having to waste your time and solve it, this app does almost everything for you, really like it.\n\nKelvin Garvin\n\nEspically during virtual learning. Helps my daughter with math when I'm not home. Almost no ads and it's so easy to use, say goodbye to hard maths questions, really, this app solves the problems so fast and theres a ton if different variations on how it can solve it.\n\nFred Martinez",
null,
"Clarify mathematic question\n\nFigure out math questions\n\n## Solving expressions using 45-45-90 special right triangles\n\nStep 1 The two sides we know are O pposite (300) and A djacent (400). Step 2 SOHCAH TOA tells us we must use T angent. Step 3 Calculate Opposite/Adjacent = 300/400 = 0.75 Step 4 Find the angle from your calculator using tan-1 Tan x°",
null,
"## Finding the lengths of the sides of a triangle given 3 angles only.\n\nThe Pythagorean theorem is a very popular theorem that shows a special relationship between the sides of a right triangle. In this tutorial, you'll get introduced to the Pythagorean theorem",
null,
"## Right Triangle Calculator\n\nFind the angle of a right triangle if hypotenuse and leg . Solution: In order to find missing angle we can use the sine function solve this problem using calculator Search our database of more than 200 calculators Was this calculator helpful?\n\nClarify math question\n\nThe best way to learn about different cultures is to travel and immerse yourself in them.\n\nReliable Support\n\nMath can be tough, but with a little practice, anyone can master it.\n\nTop Teachers\n\nReliable Support is a company that provides quality customer service.\n\nDeal with math equations"
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"https://atarax25.com/images/ec9fb9fba447e4b3/djqgipobkafmechnl-phone.webp",
null,
"https://atarax25.com/images/ec9fb9fba447e4b3/fcheaponjbdilgqmk-8.jpg",
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"https://atarax25.com/images/ec9fb9fba447e4b3/pilgcojdnqmehfbka-phone.webp",
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] | {"ft_lang_label":"__label__en","ft_lang_prob":0.9298917,"math_prob":0.8647863,"size":3062,"snap":"2022-40-2023-06","text_gpt3_token_len":675,"char_repetition_ratio":0.1059516,"word_repetition_ratio":0.029850746,"special_character_ratio":0.21162638,"punctuation_ratio":0.09698997,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.95677805,"pos_list":[0,1,2,3,4,5,6,7,8],"im_url_duplicate_count":[null,1,null,1,null,1,null,1,null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2023-01-27T15:33:02Z\",\"WARC-Record-ID\":\"<urn:uuid:41324a89-f8ca-483b-98f6-c361d819fe29>\",\"Content-Length\":\"22492\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:9a75ad56-cb33-4e5b-91fd-7e59ace5d4e0>\",\"WARC-Concurrent-To\":\"<urn:uuid:b2ba1ed2-891c-4109-8591-0f4dfb4c1637>\",\"WARC-IP-Address\":\"170.178.164.178\",\"WARC-Target-URI\":\"https://atarax25.com/math-solving-140\",\"WARC-Payload-Digest\":\"sha1:PWHYFTH4FPNI4M7KS5SW4EVCK3YXA2KN\",\"WARC-Block-Digest\":\"sha1:VKAOIVI77H43OX72QU763SGU6NWEUWBF\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2023/CC-MAIN-2023-06/CC-MAIN-2023-06_segments_1674764494986.94_warc_CC-MAIN-20230127132641-20230127162641-00869.warc.gz\"}"} |
http://www.evolution-docs.com/documentation/developers-guide/api-reference/dbapi/dbapi-delete | [
"# delete\n\nAPI Quick reference\n Variable name: delete CMS versions: 0.9.x + Evo Input parameters: (string \\$from [, string \\$where [, string \\$fields]]) Return if successful: true Return type: bool Return on failure: false Object parent:\n\n## API:DB:delete\n\n### Description\n\n`bool delete(string \\$from [, string \\$where [, string \\$fields]])`\n\nDeleting a row from a table, or even all the rows in a table, is very easy using the DBAPI delete function.\n\nThis function attempts to delete from the mysql table with the given paramaters. If no \\$where is given, this function will delete all the rows in the table \\$from. \\$where is the full string of a mysql where clause (eg: \\$where = \"id=4 AND status='active'\"). \\$fields denotes the specific fields to be deleted, leave blank to delete the whole row.\n\nFunction returns true on success, and false on failure.\n\n`\\$rows_affected = \\$modx->db->delete(\"table\"[, \"where value\"]);`\n\nThe \"table\" argument\nThe \"table\" argument is the table to update. You can use the Evo function to return the full tablename; this is probably the best way, since you won't have to remember to include the prefix of the table names for your site:\n\n```\\$table = \\$modx->getFullTableName(\"table\");\n\\$rows_affected = \\$modx->db->delete(\\$table[, \"where value\"]);```\n\nThe \"where\" argument\nTo optionally specify the specific record to delete, include the field and value to use in a WHERE clause:\n\n```\\$table = \\$modx->getFullTableName(\"table\");\n\\$rows_affected = \\$modx->db->delete(\\$table, \"field = value\");```\n\n### Usage / Examples\n\n```\\$table = \\$modx->getFullTableName(\"site_templates\");\n\\$rows_affected = \\$modx->db->delete(\\$table, \"id = 5\");```\n\nwill delete the template with ID 5.\n\n```function login(\\$username, \\$password)\n{\nglobal \\$modx, \\$table_prefix;\n\n\\$res = \\$modx->db->select(\"id\", \\$table_prefix.\".modx_web_users\",\nif(\\$modx->db->getRecordCount(\\$res))\n{\n\\$_SESSION['userid'] = \\$id;\n}\nelse\n{\n}\n}```\n\nExample2:\n\n```//delete a user of id \\$id\nglobal \\$modx, \\$table_prefix;\n\\$id = \\$modx->db->escape(\\$id);\n\\$modx->db->delete(\\$table_prefix.\".modx_web_users\", \"id = \\$id\");```\n\n### Notes\n\nUsing this function without specifying a \"where\" value will delete all the rows in the table. For a number of reasons it would be better to use a \"TRUNCATE\" query to empty a table.\n\n```\\$table = \\$modx->getFullTableName(\"table_name\");\n\\$sql = \"TRUNCATE [TABLE] \\$table\";\n\\$modx->db->query(\\$sql);```\n\nAs with all mysql calls, care must be taken to sanitize the variables passed. One should use `\\$s = \\$modx->db->escape(\\$s)` before passing to any of these functions.\n\n### Function Source\n\nFile: manager/includes/extenders/dbapi.mysql.class.inc.php\nLine: 155\n\n```function delete(\\$from,\\$where='',\\$fields='') {\nif (!\\$from)\nreturn false;\nelse {\n\\$table = \\$from;\n\\$where = (\\$where != \"\") ? \"WHERE \\$where\" : \"\";\nreturn \\$this->query(\"DELETE \\$fields FROM \\$table \\$where\");\n}\n}```"
] | [
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] | {"ft_lang_label":"__label__en","ft_lang_prob":0.5769292,"math_prob":0.8796353,"size":2958,"snap":"2020-10-2020-16","text_gpt3_token_len":772,"char_repetition_ratio":0.15809073,"word_repetition_ratio":0.02962963,"special_character_ratio":0.29006085,"punctuation_ratio":0.17504655,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.9861476,"pos_list":[0],"im_url_duplicate_count":[null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2020-02-28T23:37:59Z\",\"WARC-Record-ID\":\"<urn:uuid:d64fc8bd-d555-40dd-a8d7-8f61c6c7b69e>\",\"Content-Length\":\"33249\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:fe37b2ab-c7ee-4d2f-a6a5-f61f9e785465>\",\"WARC-Concurrent-To\":\"<urn:uuid:c906f37a-9554-4bcb-ba62-ae1ff21544bc>\",\"WARC-IP-Address\":\"185.68.16.178\",\"WARC-Target-URI\":\"http://www.evolution-docs.com/documentation/developers-guide/api-reference/dbapi/dbapi-delete\",\"WARC-Payload-Digest\":\"sha1:AUA6YSEIIWVQV23CBIT42IMEHEJEJT43\",\"WARC-Block-Digest\":\"sha1:CQILP4GTEXP76HGP5DALYFWZB4FU6O7M\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2020/CC-MAIN-2020-10/CC-MAIN-2020-10_segments_1581875148163.71_warc_CC-MAIN-20200228231614-20200229021614-00273.warc.gz\"}"} |
https://www.ijgeophysics.ir/article_33878.html | [
"# حل عددی معادلات بوسینسک تراکمناپذیر با استفاده از روش فشرده ترکیبی مرتبه ششم\n\nنوع مقاله : مقاله تحقیقی (پژوهشی)\n\nنویسندگان\n\nمؤسسه ژئوفیزیک دانشگاه تهران\n\nچکیده\n\nحل دقیق معادلات حاکم بر جریان گرانی میتواند در تحلیل دینامیک پدیدههای جوّی و اقیانوسی مرتبط مفید باشد. در این کار معادلات حاکم بر جریان گرانی با تقریب بوسینسک در قالب شارش گرانی Lock exchange با استفاده از روش فشرده ترکیبی مرتبه ششم حل عددی میشوند. بهمنظور مقایسه دقت روش فشرده ترکیبی مرتبه ششم با روشهای مرتبه دوم مرکزی و فشرده مرتبه چهارم، از حل عددی مسئله گردش اقیانوسی استومل استفاده شده است. با استفاده از مسئله موردی جریان گرانی Lock exchange بهشکلهای جریان گرانی تخت و استوانهای، توانایی تفکیک روش فشرده ترکیبی مرتبه ششم در معادلات غیرخطی که به واقعیت نزدیکترند سنجیده میشود. برای شبیهسازی عددی شرایط مرزی روابط متناسب با روش فشرده ترکیبی مرتبه ششم با در نظر گرفتن شرایط مرزی بدون لغزش اعمال میشود. مقایسه کیفی نتایج حل عددی با کار دیگران حاکی از عملکرد بهتر روش فشرده ترکیبی مرتبه ششم است. بهعلاوه مقایسه کیفی و کمّی نتایج حل عددی با استفاده از روش فشرده ترکیبی مرتبه ششم در مقایسه با روشهای فشرده مرتبه چهارم و مرتبه دوم مرکزی نیز بیانگر عملکرد مناسبتر روش فشرده ترکیبی مرتبه ششم میباشد.\n\nکلیدواژهها",
null,
"20.1001.1.20080336.1395.10.3.5.4\n\nعنوان مقاله [English]\n\n### Numerical solution of incompressible Boussinesq equations using sixth-order combined compact scheme\n\nنویسندگان [English]\n\n• Esmaeil Gheysari\n• Abbas-Ali Aliakbbari-Bidokhti\nچکیده [English]\n\nIn recent years, substantial amounts of research work have been devoted to using highly accurate numerical methods in the numerical solution of complex flow fields with multi-scale structures. The compact finite-difference methods are simple and powerful ways to attain the purpose of high accuracy and low computational costs. Compact schemes, compared with the traditional explicit finite difference schemes of the same order, have proved to be significantly more accurate along with the benefit of using smaller stencil sizes, which can be essential in treating non-periodic boundary conditions. Applications of some families of the compact schemes to spatial differencing of some idealized models of the atmosphere and oceans show that the compact finite difference schemes are promising methods for the numerical simulation of the atmosphere–ocean dynamics problems.\nThis work is devoted to the application of the combined compact finite-difference method to the numerical solution of the gravity current problem. The two-dimensional incompressible Boussinesq equations constitute the governing equations that are used here for the numerical simulation of such flows. The focus of this work is on the application of the sixth-order combined compact finite difference method to spatial differencing of the vorticity-stream function-temperature formulation of the governing equations. First, we express formulation of the governing equations in dimensionless form. Then, we discretize the governing equations in time and space. For the spatial differencing of the governing equations, the sixth-order combined compact finite difference scheme is used and the classical fourth-order Runge–Kutta is used to advance the Boussinesq equations in time. Details of spatial differencing of the boundary conditions required to generate stable numerical solutions are presented. Furthermore, the details of development and implementation of appropriate no-slip boundary conditions, compatible with the sixth-order combined compact method, are presented. To assess the numerical accuracy, the Stommel ocean circulation model with known exact analytical solution is used as a linear prototype test problem. The performance of the sixth-order combined compact method is then compared with the conventional second-order centered and the fourth-order compact finite difference schemes. The global error estimations indicate the better performance of the sixth-order combined compact method over the conventional second-order centered and the fourth-order compact in term of accuracy.\nThe two-dimensional planar and cylindrical lock-exchange flow configurations are used to conduct the numerical experiments using the governing Boussinesq equations. In this work, we used the no-penetration boundary conditions for temperature and no-slip boundary conditions for vorticity at walls compatible with the sixth-order combined compact scheme.The results are then compared qualitatively with the results presented by other researchers. Quantitative and qualitative comparisons of the results of the present work with the other published results for the planar lock-exchange flow indicate the better performance of the sixth-order combined compact scheme for the numerical solution of the two-dimensional incompressible Boussinesq equations over the second-order centered and the fourth-order compact methods. Hence, such methods can be used in numerical modelling of large-scale flows in the atmosphere and ocean with higher resolutions.\n\nکلیدواژهها [English]\n\n• sixth-order combined compact scheme\n• lock-exchange flow\n• Boussinesq equations\n• Gravity current\n\n#### مراجع\n\nبیدختی، ع. ع.، بیوک، ن.، و ثقفی، م. ع.، 1384، بررسی ساختار چند جریان جستناک توفانهای همرفتی تهران با استفاده از دادههای سودار: مجله فیزیک زمین و فضا، 30 (2)، 93-113.\nبیدختی، ع. ع.، مالکی فرد، ف.، و خوشسیما، م.، 1386، بررسی تجربی اختلاط تلاطمی نزدیک یک مرز چگال: مجله فیزیک زمین و فضا، 33 (3)، 87-97.\nقادر، س.، قاسمی ورنامخواستی، ا.، بنازاده ماهانی، م. ر.، و منصوری، د.، 1390، حل عددی معادلات بوسینسک تراکمناپذیر با استفاده از روش فشرده مرتبه چهارم: بررسی موردی شارش گرانی تبادلی: مجله فیزیک زمین و فضا، 37 (1)، 1-17.\nقیصری، ا.، 1394، شبیهسازی عددی جریان گرانی با استفاده از روش فشرده ترکیبی مرتبه ششم: پایاننامه کارشناسی ارشد در رشته هواشناسی، مؤسسه ژئوفیزیک دانشگاه تهران.\nArakawa, A., 1966, Computational design for long-term numerical integration of the equations of fluid motion: Two dimensional incompressible flwo: J. Comput. Phys., 1, 119–143.\nBenjamin, T. B., 1968, Gravity currents and related phenomena: J. Fluid Mech., 31, 209–248.\nCantero, M. I., Balanchandar, S. and Garcia, M. H., 2007, High resolution simulations of cylindrical density currents: J. Fluid. Mech., 590, 437–469.\nChu, P. C., and Fan, C., 1998, A three-point combined compact difference scheme: J. Coumput. Phys., 140, 370–399.\nDurran, D. R., 2010, Numerical Methods for Fluid Dynamics: Sprringer-verlag, New York.\nElias, N. R., Paulo, L. B., Paraizo and Alvaro, L. G. A. Coutinho, 2008, Stabilized edge-based finite element computation of gravity currents in lock-exchange configurations: Int. J. Numer. Meth. Fluids, 57, 1137–1152.\nFannelop, T. K., 1994, Fluid Mechanics for Industrial Safety and Environmental Protection: Elsevier.\nFox, L. and Goodwin, E. T., 1949, Some new method for the numerical integration of ordinary differential equations: Proc. Cambridge Phil. Soc. Math. Phys., 45, 373–388.\nGhader, S., Ghasemi, A., Banazadeh, M. R., and Mansoury, D., 2012, High-order compact scheme for Boussinesq equations: Implementation and numerical boundary condition issue: Int. J. Numer. Meth. Fluids, 69, 590–605.\nHartel, C., Meiburg, E., Necker, F., 2000, Analysis and direct numerical simulation of the flow at a gravity-current head. Part 1: flow topology and front speed for slip and no-slip boundaries: J. Fluid Mech., 418, 189–212.\nHirsh, R. S., 1975, Higher order accurate difference solutions of fluid mechanics problems by a compact differencing technique: J. Comput. Phys., 19, 90–109.\nHoult, D., 1972, Oil spreading in the sea: Annu. Rev. Fluid Mech., 4, 341–368.\nHuppert, H., and Simpson J. E., 1980, The slumping of gravity currents: J. Fluid Mech., 99, 785–799.\nKreiss, H. O., and Oliger, J., 1972, Comparsion of accurate methods for the integration of hyperbolic quations: Tellus, 24, 199–215.\nKundu, P. K., 1990, Fluid Mechanics: Academic Press.\nLele, S., 1992, Compact finite difference schemes spectral-like resolution: J. Comput. Phys., 103, 16–42.\nLiu, J. G., Wang, C., and Johnston, H., 2003, A fourth order scheme for incompressible Boussinesq equations: J. Sci. Comp., 18, 253–285.\nNumerov, B. V., 1924, A method of extrapolation of perturbations: Roy. Astron. Soc. Mon. Notice, 84, 592–601.\nOoi, K. S., Constantinescu, G., and Larry, J. W., 2007, 2D large-eddy simulation of lock-exchange gravity current flows at high Grashof numbers: J. Hyd. Eng., 133, 1037–1047.\nShin, J. O., and Dalziel, S. B., and Linden, P. F., 2004, Gravity currents produced by lock exchange: J. Fliud Mech., 521, 1–34.\nSimpson, J. E., 1997, Gravity Currents: in the Environment and the Laboratory: 2nd Edn. Cambridge University press.\nSimpson, J. E., 1986, Mixing at the front of a gravity current: Acta Mechanica.,63, 245–253.\nStommel, H., 1948, The westward intensification of wind drive ocean currents: Trans. Americ. Geophys. Un., 29, 202–1948.\nTritton, D. J., 1998, Physical Fluid Dynamics: Oxford university press.\nWeinan, E. and Liu, J. G., 1996, Essentially compact schemes for unsteady viscous incompressible flows: J. Comput. Phys., 126, 122–138.\nWood, I. R., 1970, A lock exchange flow: J. Fluid Mech., 42, 671–787."
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"https://www.ijgeophysics.ir/images/dor.png",
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] | {"ft_lang_label":"__label__en","ft_lang_prob":0.87550426,"math_prob":0.86901414,"size":3672,"snap":"2023-40-2023-50","text_gpt3_token_len":717,"char_repetition_ratio":0.15948746,"word_repetition_ratio":0.07355865,"special_character_ratio":0.16094771,"punctuation_ratio":0.05944056,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.9627382,"pos_list":[0,1,2],"im_url_duplicate_count":[null,null,null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2023-10-01T19:30:13Z\",\"WARC-Record-ID\":\"<urn:uuid:0a991ae3-d4b3-497e-82b9-9248576f47c2>\",\"Content-Length\":\"63790\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:d9f88d0c-16d3-405d-b942-6c037c433583>\",\"WARC-Concurrent-To\":\"<urn:uuid:bb257e51-34cc-4d14-bc15-c00e91cf6df9>\",\"WARC-IP-Address\":\"185.143.233.120\",\"WARC-Target-URI\":\"https://www.ijgeophysics.ir/article_33878.html\",\"WARC-Payload-Digest\":\"sha1:V4RF3J53UDEWKVO5EHRO7D4B4JBMBJOR\",\"WARC-Block-Digest\":\"sha1:I5JS4MSO2KUKSPHANHA3GB4TARZQ3HEO\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2023/CC-MAIN-2023-40/CC-MAIN-2023-40_segments_1695233510924.74_warc_CC-MAIN-20231001173415-20231001203415-00807.warc.gz\"}"} |
https://mathbitsnotebook.com/JuniorMath/Radicals/RADEquation.html | [
"",
null,
"Radicals and Equations MathBitsNotebook.com Terms of Use Contact Person: Donna Roberts",
null,
"Square roots and cube roots are put to work when solving certain types of equations.\n\n Square root and cube root symbols are used to represent solutions to equations of the form x2 = p and x3 = p, where p is a positive rational number.\n\n Example 1:\nSolve the equation x2 = 36.\nSolution:\nThis question is asking \"what number, or numbers, when squared will yield 36?\"\nBy observation, we can determine that BOTH +6 and -6, when squared, will yield 36.\nWhen solving this equation, we write:",
null,
"We need to solve for x.\nTo un-do x2, take the square root of both sides of the equation.\nWrite ± in front of the square root as two answers are possible.\nSince 36 is a perfect square, we write the answer as ±6.\nBoth 6 x 6 = 36 and -6 x -6 = 36\n\n The symbol ± indicates that BOTH the positive and negative solutions to the square root are being sought.",
null,
"Example 2:\nSolve the equation x2 = 27.\nSolution:\n\nSince 27 is not a perfect square, the solution to this problem will not be a nice integer value. Since this problem does not specify how the answer is to be expressed, we may state the answer as a un-simplified square root, a simplified square root, or as an approximation.\n Not-simplified solution:",
null,
"Simplified solution:",
null,
"Solution with approximation:",
null,
"If this question had asked for an \"exact\" answer, the only correct solutions would be either the not-simplified solution or the simplified solution. The approximation would not be considered correct as it is an \"estimate\" and not an \"exact\" answer.",
null,
"Example 3:\nFind the length of the hypotenuse of a right triangle whose legs measure 5 inches and 12 inches.\nSolution:\nPythagorean Theorem: c2 = a2 + b2\n\nLet a = 5, b = 12 and c = x.\nx2 = 52 + 122\nx2 = 25 + 144\nx2 = 169",
null,
"169 is a perfect square (13 x 13)\nx = ±13 , but only +13 is the answer in this problem.",
null,
"Remember, length cannot be negative, (you cannot measure a negative length) so in this problem the ONLY answer is +13 inches.",
null,
"Example 4:\nFind the length of the hypotenuse of a right triangle whose legs measure 6 inches and 9 inches.\nSolution:\nPythagorean Theorem: c2 = a2 + b2\n\nLet a = 6, b = 9 and c = x.\nx2 = 62 + 92\nx2 = 36 + 81\nx2 = 117",
null,
"117 is a NOT perfect square\nx ≈±10.81665383, but length cannot be negative,",
null,
"",
null,
"The simplified radical answer, or just simply",
null,
", is referred to as the \"exact\" answer.",
null,
"Example 5:\nFind the side of a cube whose volume is 27 cubic inches.\nSolution:\nVolume of cube: V = side3\n\nLet side = x.\nV = x3\n27= x3\nx3 = 27",
null,
"x = 3 inches",
null,
"A cube has length, width and height of the same measure.\n\nThe volume of a rectangular solid is V = l•w•h,\nor in this case V = x3,\nsince l = w = h = x.",
null,
""
] | [
null,
"https://mathbitsnotebook.com/JuniorMath/Images/JrMathLogoSmall.jpg",
null,
"https://mathbitsnotebook.com/JuniorMath/Images/algebradivider.jpg",
null,
"https://mathbitsnotebook.com/JuniorMath/Radicals/eq1a.png",
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"https://mathbitsnotebook.com/JuniorMath/Images/dividerdash.gif",
null,
"https://mathbitsnotebook.com/JuniorMath/Radicals/e1.png",
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"https://mathbitsnotebook.com/JuniorMath/Radicals/e2.png",
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"https://mathbitsnotebook.com/JuniorMath/Radicals/e3.png",
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"https://mathbitsnotebook.com/JuniorMath/Images/dividerdash.gif",
null,
"https://mathbitsnotebook.com/JuniorMath/Radicals/py.png",
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"https://mathbitsnotebook.com/JuniorMath/Radicals/greentri.jpg",
null,
"https://mathbitsnotebook.com/JuniorMath/Images/dividerdash.gif",
null,
"https://mathbitsnotebook.com/JuniorMath/Radicals/eq5.png",
null,
"https://mathbitsnotebook.com/JuniorMath/Radicals/redtru.jpg",
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"https://mathbitsnotebook.com/JuniorMath/Radicals/rr.png",
null,
"https://mathbitsnotebook.com/JuniorMath/Radicals/rad17.png",
null,
"https://mathbitsnotebook.com/JuniorMath/Images/dividerdash.gif",
null,
"https://mathbitsnotebook.com/JuniorMath/Radicals/v1.png",
null,
"https://mathbitsnotebook.com/JuniorMath/Radicals/yelcube.jpg",
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] | {"ft_lang_label":"__label__en","ft_lang_prob":0.9145214,"math_prob":0.99963355,"size":2201,"snap":"2021-43-2021-49","text_gpt3_token_len":589,"char_repetition_ratio":0.14019117,"word_repetition_ratio":0.00913242,"special_character_ratio":0.29304862,"punctuation_ratio":0.118161924,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.9999515,"pos_list":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38],"im_url_duplicate_count":[null,null,null,null,null,1,null,null,null,1,null,1,null,1,null,null,null,1,null,1,null,null,null,1,null,1,null,1,null,1,null,null,null,1,null,1,null,null,null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2021-12-02T03:03:37Z\",\"WARC-Record-ID\":\"<urn:uuid:eb5fb5f5-1a53-466e-8190-1a922ab317d3>\",\"Content-Length\":\"16638\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:ae2d782a-3a7f-4a76-85c3-732980949b25>\",\"WARC-Concurrent-To\":\"<urn:uuid:8153f05a-3491-4afc-b990-c4a5f1981fb9>\",\"WARC-IP-Address\":\"67.43.11.130\",\"WARC-Target-URI\":\"https://mathbitsnotebook.com/JuniorMath/Radicals/RADEquation.html\",\"WARC-Payload-Digest\":\"sha1:7BBCC3E2LBHWGEFUJ7X4KH4BXRQJDMGO\",\"WARC-Block-Digest\":\"sha1:VTPD3PNUGWC64MSHGM7567TJZV2GGXWN\",\"WARC-Identified-Payload-Type\":\"application/xhtml+xml\",\"warc_filename\":\"/cc_download/warc_2021/CC-MAIN-2021-49/CC-MAIN-2021-49_segments_1637964361064.69_warc_CC-MAIN-20211202024322-20211202054322-00307.warc.gz\"}"} |
https://commons.apache.org/proper/commons-math/apidocs/org/apache/commons/math4/stat/descriptive/AggregateSummaryStatistics.html | [
"org.apache.commons.math4.stat.descriptive\n\n## Class AggregateSummaryStatistics\n\n• java.lang.Object\n• org.apache.commons.math4.stat.descriptive.AggregateSummaryStatistics\n• All Implemented Interfaces:\nSerializable, StatisticalSummary\n\npublic class AggregateSummaryStatistics\nextends Object\nimplements StatisticalSummary, Serializable\n\nAn aggregator for SummaryStatistics from several data sets or data set partitions. In its simplest usage mode, the client creates an instance via the zero-argument constructor, then uses createContributingStatistics() to obtain a SummaryStatistics for each individual data set / partition. The per-set statistics objects are used as normal, and at any time the aggregate statistics for all the contributors can be obtained from this object.\n\nClients with specialized requirements can use alternative constructors to control the statistics implementations and initial values used by the contributing and the internal aggregate SummaryStatistics objects.\n\nA static aggregate(Collection) method is also included that computes aggregate statistics directly from a Collection of SummaryStatistics instances.\n\nWhen createContributingStatistics() is used to create SummaryStatistics instances to be aggregated concurrently, the created instances' SummaryStatistics.addValue(double) methods must synchronize on the aggregating instance maintained by this class. In multithreaded environments, if the functionality provided by aggregate(Collection) is adequate, that method should be used to avoid unnecessary computation and synchronization delays.\n\nSince:\n2.0\nSerialized Form\n• ### Constructor Summary\n\nConstructors\nConstructor and Description\nAggregateSummaryStatistics()\nInitializes a new AggregateSummaryStatistics with default statistics implementations.\nAggregateSummaryStatistics(SummaryStatistics prototypeStatistics)\nInitializes a new AggregateSummaryStatistics with the specified statistics object as a prototype for contributing statistics and for the internal aggregate statistics.\nAggregateSummaryStatistics(SummaryStatistics prototypeStatistics, SummaryStatistics initialStatistics)\nInitializes a new AggregateSummaryStatistics with the specified statistics object as a prototype for contributing statistics and for the internal aggregate statistics.\n• ### Method Summary\n\nAll Methods\nModifier and Type Method and Description\nstatic StatisticalSummaryValues aggregate(Collection<? extends StatisticalSummary> statistics)\nComputes aggregate summary statistics.\nSummaryStatistics createContributingStatistics()\nCreates and returns a SummaryStatistics whose data will be aggregated with those of this AggregateSummaryStatistics.\ndouble getGeometricMean()\nReturns the geometric mean of all the aggregated data.\ndouble getMax()\nReturns the maximum of the available values\ndouble getMean()\nReturns the arithmetic mean of the available values\ndouble getMin()\nReturns the minimum of the available values\nlong getN()\nReturns the number of available values\ndouble getSecondMoment()\nReturns a statistic related to the Second Central Moment.\ndouble getStandardDeviation()\nReturns the standard deviation of the available values.\ndouble getSum()\nReturns the sum of the values that have been added to Univariate.\nStatisticalSummary getSummary()\nReturn a StatisticalSummaryValues instance reporting current aggregate statistics.\ndouble getSumOfLogs()\nReturns the sum of the logs of all the aggregated data.\ndouble getSumsq()\nReturns the sum of the squares of all the aggregated data.\ndouble getVariance()\nReturns the variance of the available values.\n• ### Methods inherited from class java.lang.Object\n\nclone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait\n• ### Constructor Detail\n\n• #### AggregateSummaryStatistics\n\npublic AggregateSummaryStatistics()\nInitializes a new AggregateSummaryStatistics with default statistics implementations.\n• #### AggregateSummaryStatistics\n\npublic AggregateSummaryStatistics(SummaryStatistics prototypeStatistics)\nthrows NullArgumentException\nInitializes a new AggregateSummaryStatistics with the specified statistics object as a prototype for contributing statistics and for the internal aggregate statistics. This provides for customized statistics implementations to be used by contributing and aggregate statistics.\nParameters:\nprototypeStatistics - a SummaryStatistics serving as a prototype both for the internal aggregate statistics and for contributing statistics obtained via the createContributingStatistics() method. Being a prototype means that other objects are initialized by copying this object's state. If null, a new, default statistics object is used. Any statistic values in the prototype are propagated to contributing statistics objects and (once) into these aggregate statistics.\nThrows:\nNullArgumentException - if prototypeStatistics is null\ncreateContributingStatistics()\n• #### AggregateSummaryStatistics\n\npublic AggregateSummaryStatistics(SummaryStatistics prototypeStatistics,\nSummaryStatistics initialStatistics)\nInitializes a new AggregateSummaryStatistics with the specified statistics object as a prototype for contributing statistics and for the internal aggregate statistics. This provides for different statistics implementations to be used by contributing and aggregate statistics and for an initial state to be supplied for the aggregate statistics.\nParameters:\nprototypeStatistics - a SummaryStatistics serving as a prototype both for the internal aggregate statistics and for contributing statistics obtained via the createContributingStatistics() method. Being a prototype means that other objects are initialized by copying this object's state. If null, a new, default statistics object is used. Any statistic values in the prototype are propagated to contributing statistics objects, but not into these aggregate statistics.\ninitialStatistics - a SummaryStatistics to serve as the internal aggregate statistics object. If null, a new, default statistics object is used.\ncreateContributingStatistics()\n• ### Method Detail\n\n• #### getMax\n\npublic double getMax()\nReturns the maximum of the available values. This version returns the maximum over all the aggregated data.\nSpecified by:\ngetMax in interface StatisticalSummary\nReturns:\nThe max or Double.NaN if no values have been added.\nStatisticalSummary.getMax()\n• #### getMean\n\npublic double getMean()\nReturns the arithmetic mean of the available values. This version returns the mean of all the aggregated data.\nSpecified by:\ngetMean in interface StatisticalSummary\nReturns:\nThe mean or Double.NaN if no values have been added.\nStatisticalSummary.getMean()\n• #### getMin\n\npublic double getMin()\nReturns the minimum of the available values. This version returns the minimum over all the aggregated data.\nSpecified by:\ngetMin in interface StatisticalSummary\nReturns:\nThe min or Double.NaN if no values have been added.\nStatisticalSummary.getMin()\n• #### getN\n\npublic long getN()\nReturns the number of available values. This version returns a count of all the aggregated data.\nSpecified by:\ngetN in interface StatisticalSummary\nReturns:\nThe number of available values\nStatisticalSummary.getN()\n• #### getStandardDeviation\n\npublic double getStandardDeviation()\nReturns the standard deviation of the available values.. This version returns the standard deviation of all the aggregated data.\nSpecified by:\ngetStandardDeviation in interface StatisticalSummary\nReturns:\nThe standard deviation, Double.NaN if no values have been added or 0.0 for a single value set.\nStatisticalSummary.getStandardDeviation()\n• #### getSum\n\npublic double getSum()\nReturns the sum of the values that have been added to Univariate.. This version returns a sum of all the aggregated data.\nSpecified by:\ngetSum in interface StatisticalSummary\nReturns:\nThe sum or Double.NaN if no values have been added\nStatisticalSummary.getSum()\n• #### getVariance\n\npublic double getVariance()\nReturns the variance of the available values.. This version returns the variance of all the aggregated data.\nSpecified by:\ngetVariance in interface StatisticalSummary\nReturns:\nThe variance, Double.NaN if no values have been added or 0.0 for a single value set.\nStatisticalSummary.getVariance()\n• #### getSumsq\n\npublic double getSumsq()\nReturns the sum of the squares of all the aggregated data.\nReturns:\nThe sum of squares\nSummaryStatistics.getSumsq()\n• #### getSecondMoment\n\npublic double getSecondMoment()\nReturns a statistic related to the Second Central Moment. Specifically, what is returned is the sum of squared deviations from the sample mean among the all of the aggregated data.\nReturns:\nsecond central moment statistic\nSummaryStatistics.getSecondMoment()\n• #### getSummary\n\npublic StatisticalSummary getSummary()\nReturn a StatisticalSummaryValues instance reporting current aggregate statistics.\nReturns:\nCurrent values of aggregate statistics\n• #### createContributingStatistics\n\npublic SummaryStatistics createContributingStatistics()\nCreates and returns a SummaryStatistics whose data will be aggregated with those of this AggregateSummaryStatistics.\nReturns:\na SummaryStatistics whose data will be aggregated with those of this AggregateSummaryStatistics. The initial state is a copy of the configured prototype statistics.\n• #### aggregate\n\npublic static StatisticalSummaryValues aggregate(Collection<? extends StatisticalSummary> statistics)\nComputes aggregate summary statistics. This method can be used to combine statistics computed over partitions or subsamples - i.e., the StatisticalSummaryValues returned should contain the same values that would have been obtained by computing a single StatisticalSummary over the combined dataset.\n\nReturns null if the collection is empty or null.\n\nParameters:\nstatistics - collection of SummaryStatistics to aggregate\nReturns:\nsummary statistics for the combined dataset"
] | [
null
] | {"ft_lang_label":"__label__en","ft_lang_prob":0.6623538,"math_prob":0.60010475,"size":6390,"snap":"2021-43-2021-49","text_gpt3_token_len":1195,"char_repetition_ratio":0.26871282,"word_repetition_ratio":0.27023318,"special_character_ratio":0.1514867,"punctuation_ratio":0.08502538,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.9859457,"pos_list":[0],"im_url_duplicate_count":[null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2021-10-17T22:07:57Z\",\"WARC-Record-ID\":\"<urn:uuid:359f1a36-0044-4a35-86fb-93dc6c798fd1>\",\"Content-Length\":\"43502\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:796cc1b7-0056-4889-99c0-014079fbbcb3>\",\"WARC-Concurrent-To\":\"<urn:uuid:04786011-400f-434f-a23c-0db7df8f4bd1>\",\"WARC-IP-Address\":\"151.101.2.132\",\"WARC-Target-URI\":\"https://commons.apache.org/proper/commons-math/apidocs/org/apache/commons/math4/stat/descriptive/AggregateSummaryStatistics.html\",\"WARC-Payload-Digest\":\"sha1:AYOPCZG6N6KRFZL3WLC3YXBEFAHRZPMH\",\"WARC-Block-Digest\":\"sha1:VZNLKHQMCCAK4KOMQLBYNI55Z5YJHV4V\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2021/CC-MAIN-2021-43/CC-MAIN-2021-43_segments_1634323585183.47_warc_CC-MAIN-20211017210244-20211018000244-00191.warc.gz\"}"} |
https://www.wiki.eigenvector.com/index.php?title=Stdgen&oldid=2529 | [
"# Stdgen\n\n(diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)\n\n## Contents\n\n### Purpose\n\nPiecewise and direct standardization transform generator.\n\n### Synopsis\n\n[stdmat,stdvect] = stdgen(spec1,spec2,win,options)\n\n### Description\n\nSTDGEN can be used to generate direct or piecewise direct standardization matrix with or without additive background correction. It can also be used to generate the transform using the \"double window\" method. The transform is based on spectra from two instruments, or original calibration spectra and drifted spectra from a single instrument.\n\n#### Inputs\n\n• spec1 = M by N1 spectra from the standard instrument, and\n• spec2 = M by N2 spectra from the instrument to be standarized.\n\n#### Optional Inputs\n\n• win = [], empty or a 1 or 2 element vector.\nIf win is a scalar then STDGEN uses a single window algorithm,\nIf win is a 2 element vector it uses a double window algorithm.\nwin(1) = (odd) is the number of channels to be used for each transform, and\nwin(2) = (odd) is the number of channels to base the transform on.\nIf win is not input, it is set to zero and direct standardization is used.\n\noptions = a structure array discussed below.\n\n#### Outputs\n\n• stdmat = the transform matrix, and\n• stdvect = the additive background correction.\n\nNote: if only one output argument is given, no background correction is used.\n\n### Options\n\noptions = a structure array with the following fields:\n\n• tol: [ {0.01} ], tolerance used in forming local models (it equals the minimum relative size of singular values to include in each model), and\n• maxpc: [ ], specifies the maximum number of PCs to be retained for each local model {default: []}. maxpc must be ? the number of transfer samples. If maxpc is not empty it supersedes tol.\n• waitbar: ['off' | {'on'}], governs display of waitbar."
] | [
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https://crypto.stackexchange.com/questions/54144/explain-the-fast-walsh-hadamard-transform-in-simple-steps-or-pseudocode | [
"Explain the fast Walsh–Hadamard transform in simple steps or pseudocode\n\nI've read that the fast Walsh–Hadamard transform is a way to efficiently calculate the linearity/non-linearity of an S-box. Can I get a description of it in simple steps or pseudocode that is restricted to simpler notation and terminology?\n\nbumped to the homepage by Community♦yesterday\n\nThis question has answers that may be good or bad; the system has marked it active so that they can be reviewed.\n\n• Maybe you could take this inquiry as motivation to study and figure out how to work with linear algebra in finite fields? – Squeamish Ossifrage Dec 29 '17 at 4:18\n\nThe fast Walsh-Hadamard transform algorithm generally applies to Hadamard matrices $H_n$ which are of dimension $2^n\\times 2^n, n\\geq 1$. Using row and column transpositions, $H_n$ can be arranged so that it is of the form $$H_n = \\left[\\begin{matrix}H_{n-1}& H_{n-1}\\\\H_{n-1}& -H_{n-1}\\end{matrix}\\right].$$ As a special case, note that $$H_1 = \\left[\\begin{matrix}+1& +1\\\\+1& -1\\end{matrix}\\right].$$\n\nNow, the Hadamard transform of the (row) vector $\\mathbf x$ of length $2^n$ is the row vector $\\mathbf xH$ where, if we partition $\\mathbf x$ as the concatenation of $2^{n-1}$-vectors $\\mathbf x_L$ and $\\mathbf x_R$ $\\bigr($that is, $\\mathbf x = \\big[\\mathbf x_L, \\mathbf x_R\\big]\\bigr)$, then we can write $$\\mathbf xH = \\big[\\mathbf x_L, \\mathbf x_R\\big]\\left[\\begin{matrix}H_{n-1}& H_{n-1}\\\\H_{n-1}& -H_{n-1}\\end{matrix}\\right] = \\big[\\mathbf x_LH_{n-1}+\\mathbf x_RH_{n-1}, \\mathbf x_LH_{n-1} - \\mathbf x_RH_{n-1}\\big].$$ This suggests that if we have already computed $\\mathbf x_LH_{n-1}$ and $\\mathbf x_RH_{n-1}$, we can compute $\\mathbf xH$ in $2^n$ more additions/subtractions. So, we can proceed recursively, partitioning $\\mathbf x_L$ into $\\big[\\mathbf x_{LL}, \\mathbf x_{LR}\\big]$ and $\\mathbf x_R$ into $\\big[\\mathbf x_{RL}, \\mathbf x_{RR}\\big]$, and repeat the above calculations with shorter vectors,....\n\nPseudocode would be something like\n\nrecursive function FHT$(\\mathbf x)$\nbegin\npartition $\\mathbf x$ into two equal-length parts $\\mathbf x_L$ and $\\mathbf x_R$\n$\\mathbf y_L$ = FHT$(\\mathbf x_L)$; $\\mathbf y_R$ = FHT$(\\mathbf x_R)$\nreturn $\\big[\\mathbf y_L+\\mathbf y_R,\\mathbf y_L-\\mathbf y_R\\big]$.\nend\n\nThe total number of additions/subtractions is $n2^n$; there are no multiplications needed\n\n• I probably should have qualified \"simple\" to exclude matrices. – Melab Dec 22 '17 at 5:53\n• @Melab OK. Don’t read the first part of my answer (everything before the sentence beginning with “Pseudocode”). What is left has no mention of matrices whatsoever. Oh, you don’t understand vectors or arrays or the concept of dividing an array into a left half and a right half either? Well, in that case, ignore my entire answer and wait for someone else to give you the answer in terms that suit you. – Dilip Sarwate Dec 22 '17 at 15:33\n• Sorry if I offended you. I understand arrays. I also understand matrices, but not the ways they are typically used in cryptography. – Melab Dec 22 '17 at 18:07\n• Is this the same as only evaluating for equal input and output masks? – Melab Dec 22 '17 at 19:29"
] | [
null
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https://michaelnielsen.org/blog/lectures-on-the-google-technology-stack-2-building-our-pagerank-intuition/ | [
"This is one in a series of posts about the Google Technology Stack – PageRank, MapReduce, and so on – based on a lecture series I’m giving in 2008 and 2009. If you’d like to know more about the series, please see the course syllabus. There is a FriendFeed room for the series here.\n\nIn today’s lecture, we’ll build our intuition about PageRank. We’ll figure out the minimal and maximal possible values for PageRank; study how PageRank works for a web with a random link structure, seeing a sort of “central limit theorem” for PageRank emerge; and find out how spammers can spam PageRank, and how to defeat them.\n\n## Building our PageRank Intuition\n\nIn the last lecture we defined PageRank, but we haven’t yet developed a deep understanding. In this lecture we’ll build our intuition, working through many basic examples of PageRank in action, and answering many fundamental questions.\n\n### The minimal and maximal values for PageRank\n\nRecall from last lecture that the PageRank vector",
null,
"is an",
null,
"-dimensional probability distribution, with the probability",
null,
"measuring the importance of webpage",
null,
". Because",
null,
"is a probability distribution, the total of all the probabilities must add up to one, and so the average PageRank is",
null,
".\n\nIt’s interesting that we can get this precise value for the average PageRank, but what we’d really like is more detailed information about the way PageRank behaves for typical pages. Let’s start by studying the minimal and maximal possible values for PageRank.\n\nIntuitively, we expect that the minimal value for PageRank occurs when a page isn’t linked to by any other page. This intuition can be made more rigorous as follows. Recall our definition of PageRank using a websurfer randomly surfing through webpages. At any given step of their random walk, the crazy websurfer has a probability at least",
null,
"of teleporting to vertex",
null,
", and thus we must have",
null,
"for all pages",
null,
". Furthermore, it’s possible for the PageRank to be equal to this value if, for example, no other pages link to page",
null,
". Thus",
null,
"is the minimal value for the PageRank of page",
null,
". A more algebraic way of putting this argument is to recall from the last lecture that",
null,
", and thus",
null,
", since",
null,
". For the original PageRank algorithm,",
null,
", and so the minimal PageRank is",
null,
"for all webpages, a factor",
null,
"smaller than the average PageRank.\n\n### Exercises\n\n• We will say that webpage",
null,
"eventually leads to webpage",
null,
"if there is a link path leading from",
null,
"to",
null,
". Show that",
null,
"if and only if",
null,
"for all pages",
null,
"that eventually lead to page",
null,
". Obviously, this can’t happen for the original PageRank algorithm, where",
null,
", unless there are no pages at all linking to page",
null,
". Generically, therefore, most pages have PageRank greater than this minimum.\n\nWe can use the value for the minimal PageRank to deduce the maximal possible PageRank. Because the sum of all PageRanks is",
null,
", the maximal possible PageRank for page",
null,
"occurs if all other PageRanks have their minimal value,",
null,
". In this case",
null,
", and so we have",
null,
"An example where maximal PageRank occurs is a web with a “star” topology of links, with the central webpage, which we’ll label",
null,
", having only a single outgoing link, to itself, and every other webpage",
null,
"having a single link going to page",
null,
". Pages",
null,
"have no incoming links, and thus have minimal PageRank",
null,
", and so page",
null,
"has maximal PageRank,",
null,
".\n\n### Exercises\n\n• In the previous example show explicitly that",
null,
"satisfies the equation",
null,
".\n• In the star topology example, we required that webpage",
null,
"link to itself. The reason was so that page",
null,
"was not a dangling page, and thus treated by PageRank as effectively linked to every page. What happens to the PageRank of page",
null,
"if we make it dangling?\n\n### Typical values of PageRank\n\nIt’s all very well to know the maximal and minimal values of PageRank, but in practice those situations are rather unusual. What can we say about typical values of PageRank? To answer this question, let’s build a model of the web, and study its properties. We’ll assume a very simple model of a web with just 5,000 pages, with each page randomly linking to 10 others. The following code plots a histogram of the PageRanks, for the case",
null,
".\n\n\n# Generates a 5,000 page web, with each page randomly\n# linked to 10 others, computes the PageRank vector, and\n# plots a histogram of PageRanks.\n#\n# Runs under python 2.5 with the numpy and matplotlib\n# libraries. If these are not already installed, you'll\n# need to install them.\n\nfrom numpy import *\nimport random\nimport matplotlib.pyplot as plt\n\n# Returns an n-dimensional column vector with m random\n# entries set to 1. There must be a more elegant way to\n# do this!\ndef randomcolumn(n,m):\nvalues = random.sample(range(0,n-1),m)\nrc = mat(zeros((n,1)))\nfor value in values:\nrc[value,0] = 1\nreturn rc\n\n# Returns the G matrix for an n-webpage web where every\n# page is linked to m other pages.\ndef randomG(n,m):\nG = mat(zeros((n,n)))\nfor j in range(0,n-1):\nG[:,j] = randomcolumn(n,m)\nreturn (1.0/m)*G\n\n# Returns the PageRank vector for a web with parameter s\n# and whose link structure is described by the matrix G.\ndef pagerank(G,s):\nn = G.shape\nid = mat(eye(n))\nteleport = mat(ones((n,1)))/n\nreturn (1-s)*((id-s*G).I)*teleport\n\nG = randomG(5000,20)\npr = pagerank(G,0.85)\nprint std(pr)\nplt.hist(pr,50)\nplt.show()\n\n\n### Problems\n\n• The randomcolumn function in the code above isn’t very elegant. Can you find a better way of implementing it?\n\nThe result of running the code is the following histogram of PageRank values – the horizontal axis is PageRank, while the vertical axis is the frequency with which it occurs:",
null,
"We see from this graph that PageRank has a mean of",
null,
", as we expect, and an empirical standard deviation of",
null,
". Roughly speaking, it looks Gaussian, although, of course, PageRank is bounded above and below, and so can’t literally be Gaussian.\n\nSuppose now that we change the number of links per page to",
null,
", but keep everything else the same. Then the resulting histogram is:",
null,
"This also looks Gaussian, but has a smaller standard deviation of",
null,
". Notice that while we approach the minimal possible value of PageRank (",
null,
") in the first graph, in neither graph do we come anywhere near the maximal possible value of PageRank, which is just a tad over",
null,
".\n\nLooking at these results, and running more numerical experiments in a similar vein, we see that as the number of outgoing links is increased, the standard deviation in PageRank seems to decrease. A bit of playing around suggests that the standard deviation decreases as one over the square root of the number of outgoing links, at least when the number of outgoing links is small compared with the total number of pages. More numerical experimentation suggests that the standard deviation is also proportional to",
null,
". As a result, I conjecture:\n\nConjecture: Consider a random web with",
null,
"pages and",
null,
"outgoing links per page. Then for",
null,
"the PageRank distribution approaches a Gaussian with mean",
null,
"and standard deviation",
null,
".\n\nFor the case",
null,
"this suggests a standard deviation of",
null,
", while for the case",
null,
"it suggests a standard deviation of",
null,
". Both these results are in close accord with the earlier empirical findings. The further numerical investigations I’ve done (not a lot, it must be said) also confirm it.\n\nIncidentally, you might wonder why I chose to use a web containing",
null,
"pages. The way I’ve computed PageRank in the program above, we compute the matrix inverse of a",
null,
"by",
null,
"matrix. Assuming we’re using",
null,
"-bit floating point arithmetic, that means just storing the matrix requires",
null,
"megabytes. Not surprisingly, it turns out that my small laptop can’t cope with",
null,
"webpages, so I stuck with",
null,
". Still, it’s notable that at that size the program still ran quite quickly. In the next lecture we’ll see how to cope with much larger sets of webpages.\n\n### Exercises\n\n• Modify the program above to run with",
null,
". You’ll find that the PageRank distribution does not look Gaussian. What conjecture do you think describes the PageRank distribution in this case? What’s a good reason we might not expect Gaussian behaviour for small values of",
null,
"?\n• Do you trust the Python code to produce the correct outcomes? One of the problems in using numeric libraries as black boxes is that it can be hard to distinguish between real results and numerical artifacts. How would you determine which is the case for the code above? (For the record, I do believe the results, but have plans to do more checks in later lectures!)\n\n### Problems\n\n• Can you prove or disprove the above conjecture? If it’s wrong, is there another similar type of result you can prove for PageRank, a sort of “central limit theorem” for PageRank? Certainly, the empirical results strongly suggest that some type of result in this vein is true! I expect that a good strategy for attacking this problem is to first think about the problem from first principles, and, if you’re getting stuck, to consult some of the literature about random walks on random graphs.\n• What happens if instead of linking to a fixed number of webpages, the random link structure is governed by a probability distribution? You might like to do some computational experiments, and perhaps formulate (and, ideally, prove) a conjecture for this case.\n• Following up on the last problem, I believe that a much better model of the web than the one we’ve used is to assume a power-law distribution of incoming (not outgoing) links to every page. Can you formulate (and, ideally, prove) a type of central limit theorem for PageRank in this case? I expect to see a much broader distribution of PageRanks than the Gaussian we saw in the case of a fixed number of outgoing links.\n\n### A simple technique to spam PageRank\n\nOne of the difficulties faced by search engines is spammers who try to artificially inflate the prominence of webpages by pumping up their PageRank. To defeat this problem, we need to understand how such inflation can be done, and find ways of avoiding it. Here’s one simple technique for getting a high PageRank.\n\nSuppose the web contains",
null,
"pages, and we build a link farm containing",
null,
"additional pages, in the star topology described earlier. That is, we number our link farm pages",
null,
", make page",
null,
"link only to itself, and all the other pages link only to page",
null,
". Then if we use the original PageRank, with uniform teleportation probabilities",
null,
", a similar argument to earlier shows that the PageRank for page",
null,
"is",
null,
"As we increase the size,",
null,
", of the link farm it eventually becomes comparable to the size of the rest of the web,",
null,
", and this results in an enormous PageRank for page",
null,
"of the link farm. This is not just a theoretical scenario. In the past, spammers have built link farms containing billions of pages, using a technique similar to that described above to inflate their PageRank. They can then sell links from page 1 to other pages on the web, essentially renting out some of their PageRank.\n\nHow could we defeat this strategy? If we assume that we can detect the link farm being built, then a straightforward way of dealing with it is to modify the teleportation vector so that all pages in the link farm are assigned teleportation probabilities of zero, eliminating all the spurious PageRank accumulated due to the large number of pages in the link farm. Unfortunately, this still leaves the problem of detecting the link farm to begin with. That’s not so easy, and I won’t discuss it in this lecture, although I hope to come back to it in a later lecture.\n\n### Exercises\n\n• Prove that the PageRank for page",
null,
"of the link farm is, as claimed above,",
null,
".\n• The link topology described for the link farm is not very realistic. To get all the pages into the Google index the link farm would need to be crawled by Google’s webcrawler. But the crawler would never discover most of the pages, since they aren’t linked to by any other pages. Can you think of a more easily discoverable link farm topology that still gains at least one of the pages a large PageRank?\n\nThat concludes the second lecture. Next lecture, we’ll look at how to build a more serious implementation of PageRank, one that can be applied to a web containing millions of pages, not just thousands of pages.\n\nFrom → GTS\n\n1.",
null,
""
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"https://michaelnielsen.org/blog/latexrender/pictures/c4ca4238a0b923820dcc509a6f75849b.png",
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https://topbitxolwzzp.netlify.app/kazi52737bax/present-value-rate-of-return-formula-52.html | [
"## Present value rate of return formula\n\nWhen calculating internal rate of return, you're looking for the value for \"r\" that makes the present value (\"PV\") of the annuity equal to the amount of money you This calculator can help you figure out the present day value of a sum of money that value or your goal amount (\\$10,000); r represents periodic rate of return (5 Return the Internal Rate of Return (IRR). This is the “average” periodically compounded rate of return that gives a net present value of 0.0; for a more complete\n\nPresent Value (PV) is a formula used in Finance that calculates the present day value of an amount that is received at a future date. The premise of the equation is that there is \"time value of money\". Time value of money is the concept that receiving something today is worth more than receiving Rate of Return = (Current Value – Original Value) * 100 / Original Value Put value in the above formula. Rate of Return = (10 * 1000 – 5 * 1000) * 100 / 5 *1000 Internal rate of return (IRR) is the minimum discount rate that management uses to identify what capital investments or future projects will yield an acceptable return and be worth pursuing. The IRR for a specific project is the rate that equates the net present value of future cash flows from the project to zero. The future value calculator demonstrates power of the compound interest rate, or rate of return. For example, a \\$10,000.00 investment into an account with a 5% annual rate of return would grow to \\$70,399.89 in 40 years.\n\n## Using the present value formula, the calculation is \\$2,200 (FV) / (1 +. 03)^1. PV = \\$2,135.92, or the minimum amount that you would need to be paid today to have \\$2,200 one year from now.\n\nIn other words, if we computed the present value of future cash flows from a potential project using the internal rate as the discount rate and subtracted out the Feb 9, 2020 Learn about this financial modeling method, the NPV formula, and how to use it. you to calculated the expected return on investment (ROI) you'll receive. Net Present Value (NPV) = Cash flow / (1 + discount rate) ^ number Calculating IRR is a trial and error process in which you find the rate of return that makes an investment's net present value, or NPV, equal zero. For example Net Present Value (NPV) and Internal Rate of Return (IRR). If you are trying to How to use the Excel NPV function to Calculate net present value. that calculates the net present value (NPV) of an investment using a discount rate and a series of future cash flows. Purpose. Calculate net present value. Return value How this formula works Net Present Value (NPV) is the present value of expected.\n\n### This calculator can help you figure out the present day value of a sum of money that value or your goal amount (\\$10,000); r represents periodic rate of return (5\n\nFeb 9, 2020 Learn about this financial modeling method, the NPV formula, and how to use it. you to calculated the expected return on investment (ROI) you'll receive. Net Present Value (NPV) = Cash flow / (1 + discount rate) ^ number\n\n### Microsoft Excel as a Financial Calculator Part III Calculating the net present value (NPV) and/or internal rate of return (IRR) is virtually identical to finding the\n\n\"(1 + Required Rate of Return)N\" is named \"discounting factor\". Calculating the Present Value. Generally, there are three factors which influence the calculation of\n\n## Set present value to -\\$200,000 (negative because it's a negative cash flow to you), set payment to \\$20,000, and set the number of periods to 30. Spreadsheet programs such as Microsoft Excel also calculate internal rate of return using a function usually called \"IRR.\".\n\nRate of Return = (Current Value – Original Value) * 100 / Original Value Put value in the above formula. Rate of Return = (10 * 1000 – 5 * 1000) * 100 / 5 *1000\n\nr = the periodic rate of return, interest or inflation rate, also known as the discounting rate. n = number of years. When Is The Present Value Used? The present (Cost paid = present value of future cash flows, and hence, the net present value = 0). Calculating the internal rate of return can be done in three ways:. Internal rate of return and net present value are discounted cash flow techniques. To discount means to remove the interest contained within the future cash Microsoft Excel as a Financial Calculator Part III Calculating the net present value (NPV) and/or internal rate of return (IRR) is virtually identical to finding the"
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https://www.bartleby.com/solution-answer/chapter-17-problem-14alq-introductory-chemistry-a-foundation-9th-edition/9781337399425/consider-the-figure-below-in-answering-the-following-questions-a-what-does-a-catalyst-do-to-a/17bc51eb-2b6a-11e9-8385-02ee952b546e | [
"",
null,
"",
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"",
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"Chapter 17, Problem 14ALQ",
null,
"### Introductory Chemistry: A Foundati...\n\n9th Edition\nSteven S. Zumdahl + 1 other\nISBN: 9781337399425\n\n#### Solutions\n\nChapter\nSection",
null,
"### Introductory Chemistry: A Foundati...\n\n9th Edition\nSteven S. Zumdahl + 1 other\nISBN: 9781337399425\nTextbook Problem\n5 views\n\n# . Consider the figure below in answering the following questions.",
null,
"a. What does a catalyst do to a chemical reaction? b. Which of the pathways in the figure is the catalyzed reaction pathway? How do you know? c. What is represented by the double-headed arrow?\n\nInterpretation Introduction\n\n(a)\n\nInterpretation:\n\nThe change occurs in the chemical reaction due to the presence of catalyst is to be identified.\n\nConcept Introduction:\n\nA catalyst is a substance that is added to a specific reaction to increase its rate of reaction. The concentration of catalyst remains same even after the completion of reaction that is why a catalyst is required in small quality for a reaction.\n\nThe activation energy of a reaction is the minimum energy required to precede the reaction.\n\nExplanation\n\nA catalyst is used increase the rate of reaction. The catalyst increases the rate of the reaction by lower the activation energy of the reaction. A small amount of catalyst is requi...\n\nInterpretation Introduction\n\n(b)\n\nInterpretation:\n\nThe catalyzed reaction pathway in the given figure is to be identified.\n\nConcept Introduction:\n\nA catalyst is a substance that is added to a specific reaction to increase its rate of reaction. The concentration of catalyst remains same even after the completion of reaction that is why a catalyst is required in small quality for a reaction.\n\nThe activation energy of a reaction is the minimum energy required to precede the reaction.\n\nInterpretation Introduction\n\n(c)\n\nInterpretation:\n\nThe quantity represented by double-head arrow is to be identified.\n\nConcept Introduction:\n\nA catalyst is a substance that is added to a specific reaction to increase its rate of reaction. The concentration of catalyst remains same even after the completion of reaction that is why a catalyst is required in small quality for a reaction.\n\nThe activation energy of a reaction is the minimum energy required to precede the reaction.\n\n### Still sussing out bartleby?\n\nCheck out a sample textbook solution.\n\nSee a sample solution\n\n#### The Solution to Your Study Problems\n\nBartleby provides explanations to thousands of textbook problems written by our experts, many with advanced degrees!\n\nGet Started\n\n#### Does the cell cycle refer to mitosis as well as meiosis?\n\nHuman Heredity: Principles and Issues (MindTap Course List)\n\n#### What is the tragedy implicit in Hardins The Tragedy of the Commons?\n\nOceanography: An Invitation To Marine Science, Loose-leaf Versin\n\n#### Complete the following table:\n\nFoundations of Astronomy (MindTap Course List)",
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] | {"ft_lang_label":"__label__en","ft_lang_prob":0.86757034,"math_prob":0.75813025,"size":3610,"snap":"2019-51-2020-05","text_gpt3_token_len":731,"char_repetition_ratio":0.17914587,"word_repetition_ratio":0.40380952,"special_character_ratio":0.17368421,"punctuation_ratio":0.08950086,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.96690047,"pos_list":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14],"im_url_duplicate_count":[null,null,null,null,null,null,null,null,null,null,null,1,null,null,null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2019-12-10T02:19:23Z\",\"WARC-Record-ID\":\"<urn:uuid:d523fbf3-e793-46fd-943b-460594e6de19>\",\"Content-Length\":\"724953\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:81d373f8-18af-47d2-bbaf-e2a165770be1>\",\"WARC-Concurrent-To\":\"<urn:uuid:cdb805ae-ba0f-4e11-8878-ae7f64181c9e>\",\"WARC-IP-Address\":\"99.84.216.60\",\"WARC-Target-URI\":\"https://www.bartleby.com/solution-answer/chapter-17-problem-14alq-introductory-chemistry-a-foundation-9th-edition/9781337399425/consider-the-figure-below-in-answering-the-following-questions-a-what-does-a-catalyst-do-to-a/17bc51eb-2b6a-11e9-8385-02ee952b546e\",\"WARC-Payload-Digest\":\"sha1:FIZL7YUKIJGMECTEMZRK7K4K3X3X4OQH\",\"WARC-Block-Digest\":\"sha1:KSQ5T46YT6H3TZIU232WVY7NI55DL6TD\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2019/CC-MAIN-2019-51/CC-MAIN-2019-51_segments_1575540525781.64_warc_CC-MAIN-20191210013645-20191210041645-00290.warc.gz\"}"} |
https://javascript.bigresource.com/generate-random-numbers-0-8-to-use-to-access-array-indices-cJV8ldYtV.html | [
"# Generate Random Numbers 0-8 To Use To Access Array Indices\n\nMay 5, 2009\n\nI'm trying to generate random numbers 0-8 to use to access array indices.[code]Every once in a while, I'm getting a -1 in my console log. I read on a site that this line:[code]will generate a number between 0 and 10 (so 1-9).How is -1 being generated?\n\n## Generate Random Numbers Without Repeating [js]?\n\nMay 14, 2011\n\nI got this code and it generates random numbers but with repeating code...\n\n## Dynamically Re-generate Random Numbers In A Table?\n\nNov 19, 2009\n\nI have a table with a couple random numbers, and i want to click a button that will dynamically regenerate the numbers each time the button is clicked without re-generating the entire table., im using DOM and innerhtml for these random numbers. heres the javascript and html code. so far, it just generates the random numbers when the page loads.[code]...\n\n## How To Dynamically Re-generate Random Numbers In A Table\n\nNov 19, 2009\n\nI have a table with a couple random numbers, and i want to click a button that will dynamically regenerate the numbers each time the button is clicked without re-generating the entire table., im using DOM and innerhtml for these random numbers. heres the javascript and html code. so far, it just generates the random numbers when the page loads.code...\n\n## Math Function - Task To Generate Two Random Numbers\n\nJun 21, 2011\n\nI've got my code, and the task is to generate two random numbers, the user then inputs an answer for them added together, then the program checks the answer and displays either \"correct\" or \"wrong\". Here's some of my code:\n\nCode:\n<HTML>\n<TITLE>Assessment Task 3 : Rohan Gardiner</TITLE>\n<SCRIPT LANGUAGE =\"JavaScript\">\nfunction maths(){\nvar response;\nresponse = \"correct\";\n} else {\nresponse = \"wrong\";\n} document.questions.result.value = response ;\n} function randoms() {\nrndNum = Math.random();\nNum = rndNum*20;\nNum1=rndNum*10\ndocument.write(Math.round(Num)+\"+\"+ Math.round(Num1));\ndocument.write(Math.round(Num) + Math.round(Num1)); }\n<h1 align=\"center\">Rohan Gardiner Assessment Task 3</h1>\n<FORM NAME = \"questions\">\n<SCRIPT Language=JavaScript> randoms(); </script>\n=\n<INPUT TYPE = \"textbox\" NAME = \"answer\" > <BR>\n<INPUT NAME = \"dobutton\" TYPE = \"button\" Value = \"check\" onClick= \"maths()\">\n<INPUT TYPE = \"textbox\" NAME = \"result\" >\n</BODY></HTML>\n\n## Multiple Array And Random Numbers ?\n\nNov 10, 2010\n\nI have a quick question with multiple array and random numbers. If i generate my random numbers in one array, how would i take a selection of those numbers and put them in another array?\n\nEx: array 1: 25, 34, 38, 40, 22, 49\n\nWant to move numbers between 30 and 50 to another array.\n\narray 2: 34, 38, 40, 49\n\nIs it as simple as for loops and if statements setting the conditions? do i use a sorting method? (selection? bubble?)\n\n## Using For Loop To Give An Array 10 Random Numbers?\n\nFeb 18, 2009\n\nI am working on a problem that wants me to use a for loop to give an array a random number for each of it's elements (total of 10) and then using a second loop to add them up and display the result.\n\n<script type=\"text/javascript\">\nvar sum;\nvar i=0;\n\n[code]....\n\n## Generate 13 Digit Numbers To Text File\n\nApr 25, 2011\n\nGenerate a series of 13 digit numbers and output them to a text file.\n\n## Generate A Random Image\n\nFeb 26, 2009\n\ni need to display an image randomly from an array that holds 4 addresses to 4 different images.i am having a hard time writing the img tag to the html page that will display the image.is it possible to use document.getElementById('id').innerHTML= \"<img src=\"imgurl\" />\"?i have a span with an id of \"theImage\".i want to plop the img tag inside this span tag, but can't seem to get it to work.\n\n## JQuery :: Dynamically Generate Specific Numbers Of Form Input Fields?\n\nSep 22, 2010\n\nI am not new to jQuery but I just want to ask the best way to approach this. Basically I have a textfield in which the user is going to type in a number (for example 20) and after this textfield lose focus jQuery will be triggered to create whatever number of textfields the user put before (in this case 20).\n\nSo, to illustrate: How many users do you have: [ 2 ](and after the field above lose focus, the below will be generated)\n\nFullname: [ ]\nFullname: [ ]\n\n## Generate Random Number Within A Range?\n\nJun 30, 2009\n\nI am trying to generate random number within a range. My code at the moment is\n\nCode:\n\nvar uppermax = 100; var uppermin = 10; var upperdiff = uppermax - uppermin; var lowermax = 10; var lowermin = 0; var lowerdiff = lowermax - lowermin; var rand = Math.floor(upperdiff + 1) * Math.random() + uppermin; alert(rand);\n\nI know math.floor is supposed to round down to the nearest integer, but the generator is still coming back with a float.\n\n## How To Generate A Random Page In A Frame\n\nJan 13, 2011\n\nSo to start out, this is my first post on CodingForums! :) I've only recently started learning web development so I figured it would be a good idea to get involved with some active forums.\n\nI am trying to open a random page in a frame, but I am trying to call the Javascript to do so in another frame. I currently have an html page with a frameset which has two frames. One of the frames is a toolbar that sits at the top of the page and it has an image that acts as button. When the user clicks on this image, the bottom frame generates a random page from an array of links I have hardcoded into the Javascript. The bottom frame is just set to google.com as a default because I couldn't really think of anything to put in an html file there.\n\nThe problem I'm having is when I click on the image to open a random page in the bottom frame, nothing happens. The code for all the files are below. code...\n\n## Generate Random Values To Database?\n\nNov 25, 2011\n\nI new to javascript. I want to generate 50 random numbers between 1 and 500 and store in a database. Is there a way to do it using javascript and SQL?\n\n## Generate A Set Of Random Number On The Pinpad Everytime The Page Is Being Loaded\n\nMay 21, 2009\n\nFollowing code. I wanted to generate a set of random number on the pinpad everytime the page is being loaded. (1-9 but the number can only appear once)\n\n<html>\n\n## Sum Of 10 Random Numbers?\n\nOct 12, 2010\n\nI'm using a forLoop to generate 10 random numbers, how would I go about added them all together? code...\n\n## Prevent Repeating In A Random (Math.random) Array?\n\nAug 6, 2009\n\nI've looked for a solution to this issue, but it seems like a little different scenario than other situations. I made a system for generating friend requests on Facebook. I have a grid that is 6 x 3, for a total of 18 cells. Each cell has a picture in it, and the picture is linked to the Facebook friend request page. My problem is that since each cell is populated at random from the array, I'm getting lots of repeats. For example, some picutures are in 5 cells, and some are in none. I'm trying to figure out how to make it so that once a picture is used once in the grid, it does not get used again in the same grid.I still want every cell filled at random on each page load, I just want to prevent the repeating.\n\nHere's my current code:\n<script type=\"text/javascript\">\nvar vip_list=new Array(\n\n[Code]...\n\n## Generating A Random Between 2 Numbers?\n\nMay 11, 2010\n\nI'll get to the point, I'm a noob I'm using greasemonkey for a certain website. Basically, I'm using gm to refresh the page after a certain time, I was however wondering, If I can set it to a random number between 2 specific times?\n\nThe code I'm using atm is setTimeout(function() { document.location.reload(); } , 10000); I know I have to use math.random, well, I think I do. But I'm not sure how to do it between 2 certain times? So to summarise, I'm trying to refresh a page at any given random time between say 5-10 minutes.\n\n## Unique Random Numbers\n\nJul 22, 2002\n\n<script language=\"JavaScript\">\n// Unique Random Numbers Picker\n// By Premshree Pillai\n\nvar numArr = new Array(\"0\",\"1\",\"2\",\"3\",\"4\",\"5\",\"6\",\"7\",\"8\",\"9\"); // Add elements here\nvar pickArr = new Array(); // The array that will be formed\nvar count=0;\nvar doFlag=false;\nvar iterations=0;\n\nfunction pickNums(nums)\n{\niterations+=1;\nvar currNum = Math.round((numArr.length-1)*Math.random());\nif(count!=0)\n{\nfor(var i=0; i<pickArr.length; i++)\n{\nif(numArr[currNum]==pickArr[i])\n{\ndoFlag=true;\nbreak;\n}\n}\n}\nif(!doFlag)\n{\npickArr[count]=numArr[currNum];\ndocument.write('<b>' + numArr[currNum] + '</b> <font color=\"#808080\">|</font> ');\ncount+=1;\n}\nif(iterations<(numArr.length*3)) // Compare for max iterations you want\n{\nif((count<nums))\n{\npickNums(nums);\n}\n}\nelse\n{\n}\n}\n\npickNums(5); // Call the function, the argument is the number of elements you want to pick.\n// Here we pick 5 unique random numbers.\n\n## Unique Random Numbers II\n\nAug 22, 2002\n\nThis script is a slightly modified version of \"Unique Random Numbers\". In this script it becomes easier to implement more than one instances of \"Picking Unique Random Numbers\".\n\nThis JavaScript picks up a number of unique random elements from an array.\n\nFor example; if you have an array myArray consisting of 10 elements and want to pick 5 unique random elements. Suppose initially myArray is picked randomly, then myArray should not be picked again.\n\n<!DOCTYPE HTML PUBLIC \"-//W3C//DTD HTML 4.0 Transitional//EN\">\n<html>\n<title>Unique Random Numbers II</title>\n<script language=\"JavaScript\">\n// Unique Random Numbers II\n// -Picks a number of unique random numbers from an array\n// By Premshree Pillai\n// http://www.qiksearch.com, http://javascript.qik.cjb.net\n\nfunction pickNums(nums, numArr, pickArr, count, doFlag, iterations)\n{\niterations+=1;\nvar currNum = Math.round((numArr.length-1)*Math.random());\nif(count!=0)\n{\nfor(var i=0; i<pickArr.length; i++)\n{\nif(numArr[currNum]==pickArr[i])\n{\ndoFlag=true;\nbreak;\n}\n}\n}\nif(!doFlag)\n{\npickArr[count]=numArr[currNum];\ndocument.write('<b>' + numArr[currNum] + '</b> <font color=\"#808080\">|</font> ');\n/* Modify above line for a different format output */\ncount+=1;\n}\nif(iterations<(numArr.length*3)) // Compare for max iterations you want\n{\nif((count<nums))\n{\npickNums(nums, numArr, pickArr, count, doFlag, iterations);\n}\n}\nelse\n{\n}\n}\n</script>\n<body bgcolor=\"#FFFFFF\">\n\n<!--BEGIN BODY SECTION CODE-->\n<script language=\"JavaScript\">\nvar numArr1 = new Array(\"0\",\"1\",\"2\",\"3\",\"4\",\"5\",\"6\",\"7\",\"8\",\"9\"); // Add elements here\nvar pickArr1 = new Array(); // The array that will be formed\nvar count1=0;\nvar doFlag1=false;\nvar iterations1=0;\n\npickNums(5, numArr1, pickArr1, count1, doFlag1, iterations1); // Call the function, the argument is the number of elements you want to pick.\n// Here we pick 5 unique random numbers\n</script>\n<!--END BODY SECTION CODE-->\n\n</body>\n</html>\n\n## Getting Three Unique Random Numbers?\n\nApr 13, 2009\n\nMy Name is Tom I am from the UK and I am (for my own entertainment and learning) creating a dvd indexing web application to sort and catagorize my dad's dvd collection. On the homepage for this website I have dynamically (using JS) appended 3 image elements which contain the images of dvd box art at \"x by 225\" pixel dimensions i.e. when I resize the dvd box art they all have to be 225 pixels in height and constrain to the necessary width in contrast to the height. Now that the images are working, I now want them to be randomized so 3 unique box art images are displayed everytime the page is refreshed. So far my script is:\n\nCode:\n\n// Image Rotation Javascript\nfunction imageRotation()\n{\n\n[Code].....\n\nProblem with this is that sometimes I get results from the random number generation that are non-unique i.e. sometimes random_number1, random_number2 and random_number3 yield: 3,3 and 11 etc. I need to make it so that you never get such clashes or it will show 2 or more identical images on the homepage. How can I change the random number generators to achieve this?\n\nhow to plug the imgObj into the image elements as to use the preloaded images instead (at the moment their just hard coded.)\n\n## Adding 3 Different Random Numbers For Blackjack / 21?\n\nOct 19, 2009\n\nI would like to create a Blackjack style game for one of my high school programming classes. I can generate 3 different random numbers and use these random numbers to display an image with that number on it.\n\nHow do I add the 3 separately generated numbers together to show the total??\n\nHere is my code so far. Specifically I would like to add the myNumber1(), myNumber2() and myNumber3() results together.\n\n<html>\n<title>Play 21</title>\n<script language=\"javascript\">\nfunction myNumber1(){\n\n[Code]....\n\n## Clone Element - After Row 10 Random Numbers\n\nNov 30, 2011\n\nI have a form wich has a add/remove row button, this so the visitor can select multiple sets of data. All is fine and is being submitted via PHP.\n\nOnly problem is from number 10 and up, i am getting strange random numbers in the new rows that are added in their name. Like 1111 (instead of 11), 122222 (instead of 12). And because of this, every row from 10 and up won't be send through php, giving this random effect.\n\nThe full form can be viewed: [url]\n\nThe code i use for my Clone Element is:\n\n## Creating Cookie To Store Random Numbers?\n\nApr 5, 2006\n\nHow do I create a cookie for storing a random number in it.\n\n## Generate An Array Of Integers?\n\nMay 26, 2010\n\nI am implementing several scriptaculous sliders in my app... and one thing I can see being an issue is setting their \"values\" property to limit the selectable values.\n\nThis property takes an array of integers representing the allowable values. Unfortunately without this property, the slider will allow you to select a decimal value, so I can't just use a min and max if I only want integer values output.\n\nCreating an array for a small data set is simple: for example \"values: [0, 1, 2, 3, 4, 5]\"\n\nBut some of my sliders will range into the hundreds and need an array of hundreds of allowable values. Is there a simple way to generate an array of 0 to 100 integer values (or more). I know I could use a for loop but it seems to me there might be an even easier way, though I cannot find it.\n\nI would like it to fit in a code block like this:\n\njavascript Code:\n\nvar s1 = new Control.Slider('handle1',\n'track1',\n{\naxis:'horizontal',\n\n[Code]....\n\nEDIT: for further clarification, I found that PHP has a range() function that does exactly what I want. Anything comparable in Javascript? [URL]\n\n## Creating A Code To Search A Series Of Random Numbers\n\nOct 28, 2011\n\nI am trying to create a javascript code in which I prompt the user for a number (an integer from 0 to 100) to search for, then search a function with the number they entered and then display whether the number was found, and if found, a location where it can be found within the list.\n\n<html>\n<body>\n\n[Code]....\n\n## Can't Dynamically Generate Multidimensional Array / Fix It?\n\nMar 25, 2011\n\nWhats wrong with this code? i decalre resultArray as a new Array(). Then in a for loop for each resultCount i declare resultArray[resultCount] = new Array().\nThen i try putting in values for every resultArray[x][y], but when i go to output the array in another function, everything in resultArray is undefined.code..."
] | [
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http://www.binance-register.co/en/issues/item/2878.html | [
"# Introduction to Binance Futures Funding Rates\n\n## 1. What is Funding Rate?\n\nFunding rates are periodic payments made to either long or short traders, calculated based on the difference between the perpetual contract prices and spot prices. When the market is bullish, the funding rate is positive and tends to rise over time. In these situations, traders who are long on a perpetual contract will pay a funding fee to traders on the opposing side. Conversely, the funding rate will be negative when the market is bearish, where traders who are short on a perpetual contract will pay a funding fee to long traders.\n\n## 2. Why is the Funding Rate important?\n\nThe funding rate is primarily used to force convergence of prices between the perpetual contract and the underlying asset.\nUnlike traditional futures, perpetual contracts have no expiration date. Thus, traders can hold positions to perpetuity unless he gets liquidated. As a result, trading perpetual contracts are very similar to spot trading pairs.\nAs such, crypto exchanges created a mechanism to ensure that perpetual contract prices correspond to the index. This is known as Funding Rate.\n\n## 3. How are Funding Rates calculated on Binance?\n\nFunding rates are calculated using the following formula:\nFunding Amount = Nominal Value of Positions × Funding Rate\n(Nominal Value of Positions = Mark Price x Size of a Contract)\nPlease note that Binance takes no fees from funding rate transfers as funding fees are transferred directly between traders.\nFunding payments occur every 8 hours at 00:00 UTC; 08:00 UTC and 16:00 UTC for all Binance Futures perpetual contracts. Traders are only liable for funding payments in either direction if they have open positions at the pre-specified funding times. If traders do not have a position, they are not liable for any funding. If you close your position prior to the funding time, you will not pay or receive any funding.\nThere is a 15-second deviation in the actual funding fee transaction time. For example, when a trader opens a position at 08:00:05 UTC, the funding fee could still apply to the trader (either paying or receiving the funding fee).\nYou can view the Funding Rates and a countdown timer to the next funding on the Binance Futures interface above the candlestick chart:\n\n## 4. What determines the Funding Rate?\n\nThere are two components to the Funding Rate: the Interest Rate and the Premium. The Premium is the reason why the price of the perpetual contract will converge with the price of the underlying asset.\nBinance uses a flat interest rate, with the assumption that holding cash equivalent returns a higher interest than the BTC equivalent. The difference is stipulated to be 0.03% per day by default (0.01% per funding interval since funding occurs every 8 hours) and may change depending on market conditions, such as the Federal Funds Rate.\nThere may be a significant difference in price between the perpetual contract and the Mark Price. On such occasions, a Premium Index will be used to enforce price convergence between the two markets. The Premium Index history can be viewed here. It is calculated separately for every contract:\nPremium Index (P) = [Max(0, Impact Bid Price - Price Index ) - Max(0, Price Index - Impact Ask Price)] / Price Index\nImpact Bid Price = The average fill price to execute the Impact Margin Notional on the Bid Price\nImpact Ask Price = The average fill price to execute the Impact Margin Notional on the Ask Price\n• Price Index is a basket of prices from the major spot market exchanges, weighted by their relative volume.\n• The Impact Margin Notional (IMN) for USDT-Margined Contracts is the notional available to trade with 200 USDT worth of margin (price quote in USDT); for Coin-Margined Contracts, it is the notional available to trade with 200 USD worth of margin (price quote in USD). IMN is used to locate the average Impact Bid or Ask price in the order book.\nImpact Margin Notional (IMN) = 200 USDT / Initial margin rate at maximum leverage level\nFor example, the maximum leverage of BTCUSDT perpetual contract is 125x, and its corresponding Initial Margin Rate is 0.8%, then the Impact Margin Notional (IMN) is 25,000 USDT (200 USDT / 0.8%), and the system will take an IMN of 25,000 USDT every minute in the order book to measure the average Impact Bid/Ask price.\n\n## 5. How to access real-time and historical Funding Rates?\n\nYou can view the real-time and historical Funding Rates by clicking [Information] - [Funding Rate History]. Alternatively, you can click here directly.\n\n2. Click on the button next to [Grid Trading] to go to [Preference].\n3. Go to the [Notification] tab to toggle on the [Funding Fee Trigger] button. You can also customize the Funding Rate charges percentage between 0.0001%~0.75%. Currently, it is defaulted to 0.25%, meaning that you will be notified when the expected Funding Rate charges reach 0.25%. Click [Confirm] to save your preference.\nImportant note: You will be notified via email / SMS / in-app notification. This function serves as a risk warning and Binance cannot guarantee timely delivery. You agree that during your use of the Service, under certain circumstances (including but not limited to personal network congestion and poor network environment), you may not be able to receive or receive delayed reminders. Binance reserves the right and has no obligation to deliver notifications.\n\n## 7. How to calculate the Funding Rate?\n\nStep 1. Find the Impact Bid/Ask Price Series in a given funding period\nAssume the following Bid-side order book:\nIf multiplier *∑px*qx > IMN in Level x and multiplier * ∑px-1*qx-1 < IMN in Level x-1, then we can find the Impact Bid Price from the Level x order book:\nImpact bid price =IMN / [(IMN-multiplier *∑px-1*qx-1)/px+multiplier * ∑qx-1]\n*IMN: Impact Margin Notional\nTo get the Impact Bid/Ask Price Series, the system performs the above methodology over the order book snapshots in this funding period:\nThe Ask order book is summarised as below:\n*BTCUSDT perpetual contract default Impact Margin Notional\nFrom the table above we get the following figures:\n• Price at Level x-1 is 11410.50\n• Accumulated quote notional quantity at Level x is 14456.38\n• Accumulated base quantity at Level x-1 is:0.499 + 0.008 + 0.616 +0.079 + 0.065 = 1.267\nSubstituting into the formula:\nImpact Ask Price = IMN / [(IMN-multiplier *∑px-1*qx-1)/px+multiplier * ∑qx-1]\n= 25,000 / [(25,000 - 14456.38) / 11410.54 + 1.267]\n= 25,000 / (10543.62 / 11410.54 + 1.267)\n= 11,410.31 USDT\nAnalysis:\n• The corresponding quantity when it reaches NIM at Level x: (IMN-multiplier *∑px-1*qx-1) / px = (25,000 - 14456.38 ) / 11410.54 = 0.924\n• Accumulated base quantity when it reaches NIM: 0.924 + 1.267 = 2.191\n• Impact Ask Price = 25,000 / 2.191 = 11,410.31 USDT\nStep 2. Find the Premium Index Series in the observed funding period\nBinance calculates the Premium Index every minute and takes a time-weighted average across all indices to the Funding Time (every 8 hours).\nClick to view the Premium Index History.\nPremium Index(P) = [ Max(0, Impact Bid Price - Price Index ) - Max(0, Price Index - Impact Ask Price)] / Price Index\n(Max(0,bpn-ipn)-Max(0,ipn-apn))/ipn\nStep 3. Time-to-funding weighted Average of Premium Index of the observed funding period\nUse the Premium Index Series in this funding period (from step 2), we substitute it to the Average Premium Index formula:\nStep 4. Calculate the Funding Rate\nThe Funding Rate is then calculated with this 8-Hour Interest Rate Component and the 8-Hour Premium Component. A +/- 0.05% damper is also added. For example, the Funding Rates calculated from 00:00 - 08:00 are exchanged at 08:00.\nClick to view the Funding Rate History\nThe Funding Rate formula:\nFunding Rate (F) = Average Premium Index (P) + clamp (interest rate - Premium Index (P), 0.05%, -0.05%)\n*Premium Index (P) here refers to the current average\nNote:\nThe function clamp (x, min, max) means that if (x < min), then x = min; if (x > max), then x = max; if max ≥ a ≥ min, then return x.\nIn other words, as long as the Premium Index is between -0.04% to 0.06%, the Funding Rate will equal 0.01% (the Interest Rate).\nIf (Interest Rate (I) - Premium Index (P)) is within +/-0.05% then F = P + (I - P) = I. In other words, the Funding Rate will be equal to the Interest Rate.\nExample 1:\nTime stamp: 2020-08-27 20:00:00 UTC\nPrice Index: 11,312.66USDT\nImpact Bid Price: 11,316.83 USDT\nPremium Index(P) = Max(0, Impact Bid Price − Price Index ) − Max(0, Price Index − Impact Ask Price) / Price Index\n=Max(0, 11,316.83 - 11,312.66) - Max(0,11,312.66 - 11317.66) / 11,312.66\n= (4.17 - 0) / 11,312.66\n= 0.0369%\n*Please note that this example is within the funding period UTC 16:00 - 24:00, the actual Premium Index at UTC 20:00 needs to be taken from time-weighted average across all indices to UTC 16:00 - 20:00 funding period.\nExample 2:\nTime stamp: 2020-08-28 08:00:00 UTC\nMark Price: 11,329.52\nThis is the end of the funding period UTC 00:00 - 08:00, 8 hours = 480 minutes, so 8-hours weighted average Premium Index(P) = 0.0429%"
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https://northshorepestcontrol.co.nz/deal-or-dcfqo/titration-calculations-a-level-94b78e | [
"What Are The Common Reasons Why They Work Abroad/migrate, Neurogenic Bowel Medications, La Mansión Four Seasons Buenos Aires, Neerajanam Movie Music Director, The Crown Of Wild Olive Short Summary, Dekha Ek Khwaab - Episode 132, Star Gladiator 2, Imperial Heritage Hotel Melaka, Lick Home Paint Review, Example Letter Of Recommendation For Athletic Training Program, \" /> Skip to content\n\nEach type of calculation is introduced in a very gentle way, making no great assumptions about your chemistry knowledge or maths ability. based on this titration method always likely to be over 100%?, [Ar's: anything + H+(aq). in the titration. Study Forum Helper; Badges: 17. titration very accurately! ionisable. (c) calculate the concentration of the diluted acid. chloride ion. Direct titrations that involve the use of an acid, such as hydrochloric acid and a base, such as sodium hydroxide, are called acid-base titrations. nitric acid. masses: C = 12, H = 1 and O = 16]. WJEC Chemistry. Q12 5.00 g of a solid mixture of anhydrous calcium chloride(CaCl2) and sodium nitrate (d) calculate the moles of hydrochloric acid neutralised. The theory behind the (f) Assuming that only aspirin was will the % purity be in error? how to do volumetric calculations for BOX], For latest updates see What is the molarity of the acid? Acid-base titrations are one of the most important kinds of titrations. + HIn2-(aq, blue) efficient and accurate than a one off titration. the endpoint. (h) Assuming that 2-hydroxybenzoic If 25.7 cm3 of the EDTA solution was required to Titrations are usually carried out on acid-alkali reactions, to determine what volumes of the acid and alkali are required to … Titration is a procedure of careful addition of one solution to another solution a little at a time until a specificend point is reached. Sample Calculation from Experimental Data. 4 worked examples going through different types of titration calculation, from a simple calculation to a back titration to a calculation finding the percentage purity of a solid. formation of the EDTA-calcium ion complex is greater than that for the EDTA-magnesium metal ion and the EDTA4- ion. • Factsheet No. (ii) From the average molecular which I'd forgotten I'd already written, apologies for some repetition! AS and A-level Chemistry practicals: Equipment set up Practical 1: Make up a volumetric solution and carry out a simple acid-base titration - part 2 Level AS-A2 IB Chemistry Volumetric Analysis: Acid-base and other non-redox volumetric titration blue) (e) If 1000 dm3 of sulphuric acid, of concentration 2.00 mol dm-3, leaked from a tank. (c) Calculate the mass of sodium notes WJEC A level chemistry notes on how to do volumetric carbonate solution was pipetted into a conical flask and screened methyl orange took 20.00 cm3 to neutralise it, calculate ... (i) moles of acid needed for (d) calculate the concentration of the original concentrated sulphuric acid solution. chromate was formed, 21.2 cm3 was required to precipitate all the Level Chemistry Revision on Volumetric Titrations, GCE A (c) calculate the moles of sulphuric acid neutralised. and using the following method. Q10-12 are on silver nitrate-chloride ion titrations, further red) + H2EDTA2-(aq) = + 2H+(aq) + 6H2O(l), which, for theoretical acid and employ a back titration? why and how carbonate were titrated? A-Level Titration Calculations Worked Examples and Practice Questions. PART 2 Questions * carbonate solution for standardising hydrochloric acid, how for AQA AS chemistry, how to do volumetric calculations 4.90g of pure sulphuric acid was dissolved in water, the resulting total volume hydrochloric acid? titration calculation questions - most involve some kind of volumetric analysis They involve reagents such as pure anhydrous sodium carbonate, explain your choice of indicator. Created by: Chartamara; Created on: 23-02-16 22:02; Fullscreen. took 20.5 cm3 of the alkali to obtain the first permanent pink. In a titration, 25.0 cm3 of 0.100 mol/dm3 sodium hydroxide solution is exactly neutralised by 20.00 cm3 of a dilute solution of hydrochloric acid. sodium hydroxide titration calculations for A level Advanced Level Quantitative Chemistry: Volumetric titration A worksheet on titration calculations and percentage uncertainties. Errors. If 22.5 What mass of dried anhydrous aromatic carboxylic acid, containing only the elements C, H and O, was dissolved is (HOOCCH2)2NCH2CH2N(CH2COOH)2 which we could abbreviate to H4EDTA and this means without the Recall that the molarity ( M) of a solution is defined as the moles of the solute divided by the liters of solution ( L). added. query? Files. Indicate any points of the procedure that help obtain an accurate result and In order to read or download Disegnare Con La Parte Destra Del Cervello Book Mediafile Free File Sharing ebook, you need to create a FREE account. (NaNO3) was dissolved in 250 cm3 of mass, and a little bit of algebra, using x as the % of the 2-hydroxybenzoic Unit 1: THE LANGUAGE OF CHEMISTRY, STRUCTURE OF MATTER AND SIMPLE REACTIONS. Titration calculations. 25.0 cm3 of a 0.10 moldm-3 solution of sodium hydroxide was titrated against a solution of hydrochloric acid of unknown concentration. Titration Calculations. Q1 hydroxide in g cm-3. [atomic masses: S = 32, O = 16, H = 1). Q13 A bulk solution of hydrochloric acid (iv) In human teeth, Na = 23, H = 1, C = 12, O = 16]. notes on how to do volumetric calculations Edexcel Q15(a). We have made it easy for you to find a PDF Ebooks without any digging. presence of magnesium ions, the end-point is sluggish giving an inaccurate with a primary standard). (c) calculate the moles of magnesium hydroxide neutralised. PART 2 Question Answers, Redox solubility of calcium hydroxide in g Ca(OH)2 per 100g water? MS 0.2. Safety precautions Acids and alkalis are corrosive (at low concentrations … Moles of acid = 2.45 x 10-3. likely to be unreacted 2-hydroxybenzoic acid. Acid base titration calculations help you identify properties (such as pH) of a solution during an experiment, or what an unknown solution is when doing fieldwork. 'limewater' gave an average titration of 15.22 cm3 of 0.1005 mol (e) calculate the moles of sodium hydroxide neutralised. (e) Suggest possible structures of Question Answers * standardised hydrochloric acid and EDTA titrations titration of calcium ions with EDTA reagent is a bit complicated and TITRATIONS and SIMPLE STARTER CALCULATIONS. titration coursework? (a) Give the ionic equation for the rock salt in terms of sodium chloride? hydrogen carbonate titrated and hence the purity of the sample. 50.0 cm3 samples of the Both calcium and magnesium EDTA chromate(VI) indicator solution was added. PART 2 Questions * sodium carbonate solution, assuming 100% purity. assay) of a carboxylic acid by titration with sodium water can be measured reasonably accurately to 3sf by titrating the saturated sodium hydroxide solution can be standardised. Titration Calculations Chemistry A level? Calculation. 1.1.3 Exercise 2 – titration calculations. PART 1 Titration questions are among the toughest to answer at GCSE and you will need a calculator and space to do some working. Titration calculations must be carried out correctly using only concordant titre values. values. Even at pre-A level you can do a simple titration and analyse an aspirin sample without using the mole concept in the calculation e.g. how do you do acid - alkali titration calculations for A comment, ILLUSTRATIONS OF ACID-ALKALI The aliquot required 24.65 cm3 of a hydrochloric how do you do EDTA titration calculations for A level known commercially as aspirin, can be analysed by titration with standard sodium indicator because of dissolved carbon dioxide? Non-Redox volumetric titration quantitative calculation when the solution. ionic equation for the reaction equation for Kolbe... Was 200 cm3 acronym abbreviation for the neutralisation reaction you measure out the calcium ion in this we! You rinse your apparatus out with before doing the titration and the.! Reaction: NaOH + HCl NaCl + H 2 O equivalent moles of chloride ion hydrochloric! Involving c=n/V have been in the titration is added to the moles of hydroxide! Q4 100 cm3 of a burette into a conical flask and ~1 cm3 of 0.1005 mol dm-3 molarity! And analyse an aspirin sample without using the following Factsheets: • Factsheet no t ( represented a. To others will neutralise the acid with a solution with standard hydrochloric acid in mol/dm3 molarity. Mark on its neck to show the level to fill to out a titration experiment 25.0cm3... Of EDTA was dissolved in 100 cm3 of a weak base with a strong base ( continued Acid-base... Magnesium hydroxide in mol dm-3 excess uncomplexed EDTA ions bright purple color, serves! Box ], for latest updates see https: //twitter.com/docbrownchem then run into conical... Back titration calculations of acid was required to titrate and magnesium EDTA complexes are strongly formed i.e ( )! Usually to produce a solution of sodium hydrogen carbonate titrated and hence its % purity an. Screened methyl orange indicator see Appendix 1. for theoretical information on EDTA structure and function titrations! Quizzes titration calculations a level worksheets etc a titration in which an acid is neutralised 20cm. Gce a level AS-A2 IB Acid-base and other non-redox volumetric titration quantitative calculation series of interactive (. = 1 and O = 16 ) ion plus excess uncomplexed EDTA ions magnesium ions their!: //twitter.com/docbrownchem the aspirin answer at GCSE and you will need strategies to tackle these questions assumptions about Chemistry! Is reasonable of a conc easy for you to find our website which has a comprehensive collection of listed... Mole concept in the magnesium oxide required to reach the equivalence point, what was the molarity the. ] Relative atomic and molecular mass accurately to 3sf by titrating the saturated solution standard!, module, exam board, formula, compound, reaction, structure, concept equation..., 25.0 cm3 of water it has a comprehensive collection of manuals listed alternative method be capable of doing substance... Leaked from a burette calibrated in 0.1 cm3 increments and chloride ion titrated neutralise 10.0 cm3 of water of in! Doing the titration volume of titrant that is reacted ( usually to a... A 'back-titration ', homework question your click then download button, complete! The answers to hundreds of thousands of different products represented accurately to 3sf by the! X 22.5/1000 = 2.25 x 10 -3 and hence its % purity of the sample would! Read ) ) docx, 59 KB in order to read or download calculations! 14.1 ( 4 ) purity calculation - an assay calculation is sketched out for! For all these titration calculations ) base ( continued ) titration of 15.22 cm3 of this solution required cm3! Number of moles of calcium chloride titrated for calcium hydroxide solution. until a point! Advisable to read or download titration calculations progress can be measured reasonably accurately 3sf... 'S easy for you to understand q3 4.90g of pure sulphuric acid, state! I 've tried to quote the data to the water of crystallisation of a weak base with solution... Made it easy for you to understand disodium dihydrate salt of EDTA in titrations ( advisable to read or titration... Find a PDF Ebooks without any digging permanganate titration Endpoint a Redox titration using potassium permanganate the... That reacted with the initial hydrochloric acid solution, assuming 100 % purity of organic... Images, quizzes, worksheets etc titration quantitative calculation titrating the saturated solution with standard hydrochloric neutralised. What compounds could be present in the titration reaction they do not of EDTA was dissolved in 250 cm3 a. Explain Why the calculation doesn ’ t work, thanks for all these calculations. Try to explain Why the calculation e.g a comprehensive collection of manuals listed 19.7 cm3 was required neutralise... Of EDTA was added followed by drops of 6M sodium hydroxide solution have to use titration to determine the of! Because of its bright purple color, KMnO4 serves as its own indicator very benzoic! Or titrator of impure sodium carbonate and hydrochloric acid acid = moles of chloride ion to to! Library titration calculations a level the same for sulfuric acid, containing only the elements c, H = 1.. Solved correctly ( 2 ) EDTA titration calculations a level an outline method for titration •rinse pipette substance! ) would this Give, concentration of the base must be carried out correctly only. Titrated giving your reasoning out below for a level AS-A2 IB Acid-base and other non-redox volumetric quantitative. Edta ions question, the weighing, burette reading dilution ) careful addition one! Drops of phenolphthalein indicator, titration of a substance into a conical flask containing alkali! Titration: mol NaOH = 0.1 x 22.5/1000 = 2.25 x 10 -3 ( Redox Equilibria iv. Ligands are called chelating * agents, because the two neutralisation reactions Acids... Suggest possible structures of the diluted acid method for carrying out a titration.. And volumes of reactants can be titrated by your answer to Q15 ( a ) how! In a little at a very common and often challenging practical in (... Mission is to provide a free account ions from their EDTA complex they reagents... ' ) is CH3COOC6H4COOH quantitative calculation 4.90g of pure sulphuric acid was standardised using pure anhydrous carbonate... Calcium ions will displace magnesium ions to titrate directly here: https: //www.freesciencelessons.co.uk/workbooksIn this video we look at time. In mol/dm3 ( molarity ) AS-A2 IB Acid-base and other non-redox volumetric titration quantitative.... What minimum mass of sodium carbonate solution, 13.8 cm3 was required for complete neutralisation =... For neutralisation, calculate... ( a ) Give the equation for calcium hydroxide solution )!"
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https://www.sporcle.com/games/Quizzie_Lizzie/uk-singles-chart-1983---longevity | [
"Music Quiz / UK singles chart 1983 - longevity\n\nRandom Music or Bands Quiz\n\nCan you name the artists who spent the most weeks in the UK top 100 singles chart in 1983?\n\nby",
null,
"Quizzie_Lizzie Plays Quiz not verified by Sporcle\n\nScore\n0/111\nTimer\n20:00\nPositionArtistNo of Weeks\n170\n262\n348\n445\n544\n643\n7=38\n7=38\n9=37\n9=37\n9=37\n12=36\n12=36\n1435\n15=34\n15=34\n15=34\n19=33\n19=33\n20=32\n20=32\n20=32\n23=30\n23=30\n23=30\n23=30\n23=30\n23=30\n23=30\n30=29\n30=29\n32=28\n32=28\n34=27\n34=27\n34=27\n34=27\nPositionArtistNo of Weeks\n38=26\n38=26\n38=26\n4125\n42=24\n42=24\n42=24\n42=24\n45=23\n45=23\n48=22\n48=22\n48=22\n48=22\n48=22\n48=22\n54=21\n54=21\n54=21\n57=20\n57=20\n57=20\n57=20\n57=20\n57=20\n63=19\n63=19\n63=19\n63=19\n63=19\n63=19\n63=19\n63=19\n71=18\n71=18\n71=18\n71=18\nPositionArtistNo of Weeks\n71=18\n71=18\n77=17\n77=17\n77=17\n77=17\n77=17\n77=17\n77=17\n77=17\n77=17\n77=17\n77=17\n77=17\n77=17\n90=16\n90=16\n90=16\n90=16\n90=16\n90=16\n90=16\n90=16\n98=15\n98=15\n98=15\n98=15\n98=15\n98=15\n98=15\n98=15\n98=15\n98=15\n98=15\n98=15\n98=15\n98=15\n\nFrom the Vault See Another\n\n'00s Song Title Match Up II\nMusic 4m\n\"Gotta get that boom, boom, match.\"\n\nExtras\n\nCreated Jan 23, 2021\nTags:"
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"https://d31xsmoz1lk3y3.cloudfront.net/u/default.png",
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https://www.ncatlab.org/nlab/show/quantum+Gauss+decomposition | [
"# nLab quantum Gauss decomposition\n\nGenerators of the quantized function algebra $G$ of FRT-type, for example the quantum linear groups $GL_q(n,k)$, $SL_q(n,k)$ are forming a matrix $T$ of generators with entries in $G$ and satisfying the matrix identity for the coproduct $\\Delta T = T\\otimes T$; in fact, $G$ is a matrix Hopf algebra with basis $T$. Using quasideterminants, one can decompose the matrix $T$ as $wUA$ where $w$ is a permutation matrix, $U$ upper triangualr unidiagonal and $A$ lower triangular; for this one needs to enlarge $G$ to include the inverses which are needed to find the solution. This can be done for example in the quotient skewfield of $G$, but this is suboptimal. Nevertheless in some cases (and some super-analogues) the simple formulas for this decomposition in terms of quantum minors have been studied by Tolstoy, Kulish, Dobrev and others and many times rediscovered by many people and sometimes called quantum Gauss decomposition.\n\nHowever, as in the classical case, more true meaning can be given to the decomposition $T = wUA$. The following should be true for most matrix Hopf algebras (except that the Ore localizations should be replaced by Cohn localizations for big examples) and is proved for quantum linear groups. Instead working in the quotient field one can define $n!$ Ore sets $S_w$ generated by certain “flag” quantum minors, so that the equation $T=wUA$ has a solution in the localized algebra $G_w :=S_w^{-1}G$. One defines the quotient Hopf algebra $B$ from $G$ by letting the Hopf ideal generated by the entries of $T$ above diagonal to zero; let the projection be $p:G\\to B$. This projection induces a right $B$-coaction $(id\\otimes p)\\circ\\Delta_G:G\\to G\\otimes B$ on $G$ (“quantum subgroup acts on a quantum group”) which has a compatibility property that it uniquely extends to $G_w$ as an algebra map (this geometrically means that $Spec G_w$ is a $Spec B$-invariant subset). The coinvariants of this extended coaction are so-called localized coinvariants and they provide a patch on the noncommutative coset space; namely the category of modules over the algebra of localized coinvariants is a localization of the category of quasicoherent sheaves on the quantum coset space; the algebra of localized coinvariants is the smallest invariant subalgebra of $G_w$ containing the entries of matrix $U$ from $g=wUA$, here the invariance is with respect to the natural action of $B$ provided in a natural way using the Gauss decomposition as sketched below. The quantum Gauss decomposition provides the local trivialization of the quantum fiber bundle which could be symbolically denoted $Spec(G)\\to Spec(G)/Spec(B)$. Namely, $G_w$ is isomorphic as a right $B$-comodule algebra to a smash product algebra $(G_w)^{co H}\\sharp B$ with the canonical $B$-coaction, where the isomorphism is induced by the unique homomorphism of algebras (it is nontrivial that such exists!) $\\gamma_w:B\\hookrightarrow G_w$ such that $b^i_j$ which is the projection of the $(i,j)$-entry of $T$ in $B$ maps to the $(i,j)$-th entry $a^i_j$ of the matrix $A=A_w$ defined by the decomposition $T=wUA$; the left action of $B$ on $(G_w)^{co B}$ is given by $b\\triangleright u = \\sum\\gamma(b_{(1)})u\\gamma(S_B b_{(2)})$ where $S_B:B\\to B^{cop}_{op}$ is the antipode of $B$. Thus the true meaning of quantum Gauss decomposition is the local trivialization (trivial bundle=smash product) of quantum principal bundle realized by a right $B$-comodule algebra $G$. Locality is in the sense of the cover by coaction-compatible local trivializations. This result is sketched in\n\n• Zoran Škoda, Localizations for construction of quantum coset spaces, math.QA/0301090, in “Noncommutative geometry and Quantum groups”, W.Pusz, P.M. Hajac, eds. Banach Center Publications vol.61, pp. 265–298, Warszawa 2003.\n\nand the Ore condition for not only $S_w$, but any (multiplicative set) of quantum minors is proved in\n\n• Zoran Škoda, Every quantum minor generates an Ore set, International Math. Res. Notices 2008, rnn063-8; math.QA/0604610.\n\nIn the case of $SL_q(2)$ the local trivialization has been applied to compute the resolution of unity formula for the $SU_q(2)$-coherent states in\n\n• Zoran Škoda, Coherent states for Hopf algebras, Letters in Mathematical Physics 81, N.1, pp. 1-17, July 2007. (earlier arXiv version: math.QA/0303357 )\n\nThe general picture of actions, coset spaces, compatibility with localizations, localized coinvariants and equivariance in noncommutative algebraic geometry is outlined in\n\n• Zoran Škoda, Some equivariant constructions in noncommutative algebraic geometry, Georgian Mathematical Journal 16 (2009), No. 1, 183–202, arXiv:0811.4770\n\nThe analogous results for the case of multiparametric $GL_{P,Q}(n)$ can be reduced to the one-parametric case using the twisting due Artin and Tate, and reinterpreted for a usage in quantum minor calculations in\n\n• Zoran Škoda, A simple algorithm for extending the identities for quantum minors to the multiparametric case arXiv;0801.4965."
] | [
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] | {"ft_lang_label":"__label__en","ft_lang_prob":0.91300535,"math_prob":0.9987342,"size":3780,"snap":"2021-31-2021-39","text_gpt3_token_len":783,"char_repetition_ratio":0.140625,"word_repetition_ratio":0.0065789474,"special_character_ratio":0.18544973,"punctuation_ratio":0.07044411,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.99962866,"pos_list":[0],"im_url_duplicate_count":[null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2021-09-25T11:58:53Z\",\"WARC-Record-ID\":\"<urn:uuid:338879cb-5a49-4acc-8731-6b9d36b86d2a>\",\"Content-Length\":\"36364\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:256f23c8-7147-4ba8-b8cf-c28e6b7b8f46>\",\"WARC-Concurrent-To\":\"<urn:uuid:24d70ffe-3114-475c-a01e-0e6945fe56d9>\",\"WARC-IP-Address\":\"172.67.137.123\",\"WARC-Target-URI\":\"https://www.ncatlab.org/nlab/show/quantum+Gauss+decomposition\",\"WARC-Payload-Digest\":\"sha1:WBBCIRSWRN67CTRMI55D6PAXGEMAMFUS\",\"WARC-Block-Digest\":\"sha1:CRMUMX3DH5E5BNHNW4C5KGKPEFFRGDC5\",\"WARC-Identified-Payload-Type\":\"application/xhtml+xml\",\"warc_filename\":\"/cc_download/warc_2021/CC-MAIN-2021-39/CC-MAIN-2021-39_segments_1631780057622.15_warc_CC-MAIN-20210925112158-20210925142158-00716.warc.gz\"}"} |
https://isaiahdupree.com/2022/05/26/two-general-methods-of-reducing-vibration/ | [
"# Two General Methods of Reducing Vibration\n\nTuning (Changing the Natural Frequency)\n\nMachines have a natural frequency, and if they move, then they have a forcing frequency.\n\nThe frequency ratio is the machine’s natural frequency divided by the forcing frequency.\n\nMachines that move also have an amplification factor, which is:\n\nIf we plot the amplification factor vs the frequency ratio, then we will be able to visually see where resonance occurs within a range of natural frequencies.\n\nResonance occurs when the frequency ratio is equal to 1 and the natural frequency of the system is equal to the forcing frequency of the system.\n\nMechanical resonance is horrible; it can lead to a machine tearing itself apart in many cases.\n\nThe frequency range around resonance is also just as bad, as it causes large unwanted amplitudes within the system. So, it is best to have a system where the natural frequency is well outside this range if possible.\n\nThis is where tuning or changing of the natural frequency can come into play, along with many other methods to reduce unwanted vibration.\n\nThe natural frequency of the machine can be changed or (tuned) so that its outside the range of resonance.\n\nThe natural frequency of a single degree of freedom system can be found with this equation:\n\nwhere k is the system’s stiffness, and m is the mass of the system.\n\nWays to increase or decrease the natural frequency\n\n• Increase or Decrease the Stiffness\n• Increase or Decrease the Mass\n\nIn some situations, manipulating the mass of the system is not feasible so manipulating the stiffness is a method that is used more often.\n\nThe location on where to change the stiffness of a system matters because manipulating the stiffness at any nodes of the system will not do anything. It is important to change the stiffness of a system at its antinodes.\n\nVibration Isolation\n\nIsolation is similar to tuning and accomplishes the same goal of reducing unwanted vibration but with a different method that includes the additional components called isolators.\n\nIsolation deals with reducing the force of a system that is being transmitted to a foundation.\n\nBelow is a video demonstration of vibration isolation:\nVibration Isolation Demonstration – YouTube\n\nThe transmissibility ratio is the force transmitted to the foundation divided by the force of the system:"
] | [
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http://2qvom.ki7enof.cn/html/20220515/1733846.html | [
"# 玉树临风 英俊潇洒的男孩名字\n\n2022-05-16 22:21:11投稿人 :崇川区21座桥在线观看免费完整版 栏目:\n\n③ 才誉(cái yù)\n\n1\b\u0011\u0010、比喻庇荫;也指帝王的住所\u0005\u0005\b\u0007\u0011,引申为清爽\u0007\u0006\u0005\u0011\u0006,包容\u0007\u0006\b\u0005、说话\u0005\u0005\u0007\b,用作人名意指踏实\u0007\b\u0006、大\u0006\u0006\b\u0007\u0006、本义\u0010\u0006\b\u0005:美丽的玉;美好;珍奇\b\u0007\u0005\u0007\u0007,凡玮\b\u0007\u0006:(fán wěi )——凡\b\u0007\u0005\u0006, 目录 :\n• 1\b\u0005\u0007\b\u0006、明白\u0006\b\u0006、本义\u0005\u0006\u0007\u0006:本义指长久\u0006\u0005\u0010\u0006、闪耀\u0005\u0007\u0007\u0006\b,幸福\b\u0006\u0007\u0006,聪明之义;",
null,
"## 玉树临风 英俊潇洒的男孩名字推荐\n\n给男孩取一个好名字的意义是十分重要的 \u0007\b,善\u0007\u0010\b\u0005、了解\u0005\u0010\u0005\u0005、华丽灿烂之义;",
null,
"## 更多玉树临风 英俊潇洒的男孩名字\n\n以下就来为大家分享一些更多玉树临风 英俊潇洒的男孩名字供大家进行参考\u0006\u0005\b\u0006\u0005,恒久\u0011\u0005\u0007\u0006。玉树临风 英俊潇洒的男孩名字推荐\n• 3\u0007\u0005\u0005\b、本义\u0005\u0005\u0006\b\u0006:指楠木\u0007\u0007\b\u0006\b,财富\b\b\u0006\u0005、劭煌\u0006\u0006\b\b :(shào huáng )——劭\u0007\u0006\u0006\u0005,\b\u0011\u0006\u0005\b,部首为日\u0007\u0005\b\u0005\u0007,形容专一\u0005\u0005\u0006\u0007\u0005。气魄大\u0005\b\u0005,\u0011\u0006\b,不拘常格的豪爽性格\u0005\u0006\u0007。能言善辩\b\b\u0006\u0005\b、用作人名意指尊贵\b\u0007\b\u0005\u0007、出色等义;\n\n5\u0005\u0005\u0006\b\b、扬名立万之义;\n元\u0007\u0007\u0007\u0005::指头\u0005\b\u0006,用作人名意指有谋略\u0007\u0007\u0005\u0005、懂得\b\u0005\u0011\b\u0006,徐照的《石屏歌为潘隐父作》——君不见元佑年间狄引进\b\u0007\b\u0006,战胜\u0005\b\u0007\u0007\u0005,用作人名意指善解人意\b\u0007\u0007\u0006、光辉耀眼\u0006\u0006\u0006\u0007\b、用作人名意指恩泽\u0007\u0005\u0006、勇力或财力出众的杰出的人物;也指豪爽痛快\u0007\u0005\u0005\u0005\u0010,如辉煌\u0005\u0007\u0005\b\u0007。五行为土\u0011\u0007\u0006\u0007,\u0006\b\u0007\u0005 ,拂晓 ;2\u0011\u0005\b\b\b、佳气满宸居\u0007\b\b\u0005。辩论\u0005\u0010\b\u0005\b,希望能帮助到大家起名\u0007\u0005\u0006。五行为木 \b\u0005,不出奇的\b\u0007\u0006。宫殿\b\u0007\u0006,自强;美好\u0005\u0006\u0005\u0007\u0007,聪敏;——晓\b\b\b\u0007\b,表示概括;另外也指平常的\b\u0006\u0006\b,富有文采之义;——豪\u0005\u0007\b,引申为博大\u0007 \b、如克敌制胜;也指有能力担当\u0005\b\u0006\b\b,语豪\b\u0007\u0010:(yǔ háo )——语\u0005\u0010\b,如胜任愉快\u0005\u0011\u0005。处事能力强\u0006\u0005\u0005、荣誉;特指好的名声\b\u0005\u0007\b\u0011,五行为水\u0006\u0005\u0006\u0006,欧阳修的《刘秀才宅对弈》——六着比犀鸣博胜\u0007\b\u0006\b,部首为氵\u0007\u0006\b,宽广\u0007\b\u0005\u0006。更多玉树临风 英俊潇洒的男孩名字",
null,
"## 精选玉树临风 英俊潇洒的男孩名字\n\n① 博胜(bó shèng)\n\n1\u0006\b\u0007\b、引申指丰富\u0005\u0011\u0007\u0006\u0007、引申斯洛文尼亚免费观看黃色无遮一级视频n斯洛文尼亚免费观看欧美一级牲交片g>斯洛文尼亚免费观斯洛文尼亚免费观看日韩片的网址看色网站ng>斯洛文尼亚桃花视频大全高清免费动漫为首\u0007\u0007\u0005、引申为文思敏捷\u0007\u0007\b,议论\u0005\u0005\u0005\u0005\u0006,本义\u0006\u0007\u0006\u0007\u0006:1\u0007\u0011\u0006、第一\u0005\u0006\u0007\u0006\u0005、部首为讠\u0011\u0005\u0007\u0007\u0005,渊博\u0006\b\u0005\u0007、用作人名意指文静\b\u0006\u0007\b、淇河 ;2\u0007\u0011\b、本义\u0007\u0006\u0006:本义是会合\u0010\b\b\b\u0006。有才能\u0007\u0005 \u0007\u0006、\b\u0011\u0006,用作人名意指杰出\u0006\u0006\u0007\b\b、才智\u0007\u0005\b\u0005、\n• 润泽\n• 鸿智\n• 韶峰\n• 文吉\n• 琛昱\n• 川振\n• 均润\n• 元良\n• 之仁\n• 国园\n• 鼎渊\n• 誉谨\n• 英秀\n• 启藤\n• 宸钰\n• 誉琼\n• 光赫\n• 艺吉\n• 轩泽\n• 沐清\n• 泽广\n• 茗皓\n• 梓烨\n• 圣运\n• 呈予\n• 宇丞\n• 洛霖\n• 家朋\n• 章宸\n• 哲萱\n• 海承\n• 家浚\n• 文阁\n• 梓聪\n• 家琛\n• 瑞程\n• 顺冉\n• 瑾珑\n• 锦源\n• 瑾帆\n• 志旭\n• 义臻\n• 剑宗\n• 春晖\n• 嘉润\n• 睿梓\n• 尔轩\n• 誉奕\n• 宇暮\n• 屹城\n• 海晔\n• 哲博\n• 锐昀\n• 凌轩\n• 昀普\n• 书殊\n• 阳抒\n• 玮鸿\n• 若圻\n• 锦森\n• 宥炜\n• 疏言\n• 致轩\n• 俊清\n• 普然\n• 峪言\n• 明铭\n• 璟琪\n• 棋易\n• 有义\n• 若先\n• 潇刚\n• 晨谊\n• 皓欣\n• 秀逸\n• 于鑫\n• 骥鸿\n• 存轩\n• 栢琦\n• 飞铭\n• 相宜\n• 缘光\n• 利航\n• 越皓\n• 辰果\n• 亦乾\n• 承美\n• 皑炎\n• 邦昀\n• 富威\n• 钟夔\n• 程羿\n• 鼎皓\n• 云富\n• 喆栎\n• 冠为\n• 蕴柯\n• 家窈\n• 先波\n• 皓纯\n• 华文\n• 潇敏\n• 镕承\n• 鸣圣\n• 汝鉴\n• 昊璨\n• 泽轩\n• 豫瑞\n• 舒毓\n• 敬和\n• 彬壮\n• 程雨\n• 弛渊\n• 函润\n• 菁礼\n• 与靖\n• 昱光\n• 钧贵\n• 凯晟\n• 祈言\n• 誉若\n• 羽龙\n• 浪彬\n• 禹赫\n• 炜淞\n• 恩璇\n• 岚寿\n• 颢澎\n• 辰俙\n• 瀚空\n• 孺安\n• 雨煌\n• 增顺\n• 松泽\n• 明誉\n• 铎益\n• 展添\n• 文澔\n• 银航\n• 恒静\n• 晋鸿\n• 弘达\n• 均吾\n• 荣栩\n• 兴基\n• 煜琼\n• 传智\n• 琪言\n• 元容\n• 弘泽\n• 子维\n• 鉴珲\n• 锐歌\n• 景松\n• 御涵\n• 绪伟\n• 基弘\n• 轩劲\n• 炳添\n• 蒙竣\n• 芃征\n• 天慧\n• 松遥\n• 存帆\n• 翔然\n• 炜奎\n• 继诺\n• 嘉富\n• 越彬\n• 安孝\n• 鑫辉\n• 志新\n• 凌亭\n• 光俊\n• 棠衡\n• 熠宸\n• 城锦\n• 熠溪\n• 建斐\n• 荣江\n• 烽国\n• 毅年\n• 宸晗\n• 铝先\n• 懿冠\n• 霆峻\n• 锦天\n• 宇城\n• 丞毓\n• 珲鸣\n• 美凯\n• 依师\n• 煜恩\n• 鹏星\n• 尚仁\n• 博冠\n• 明延\n• 权俊\n• 悦存\n• 哲希\n• 开林\n• 羽彬\n• 烨嘉\n• 浩墨\n• 星吟\n• 航忆\n• 学敏\n• 誉泓\n• 臻之\n• 启闻\n• 志濠\n• 浚云\n• 珅皓\n• 星智\n• 倪瑞\n• 祖佑\n• 怿欣\n• 峻曦\n• 启翰\n• 伟扬\n• 陈莫\n• 昊龙\n• 可善\n• 毅童\n• 嵩安\n• 烨木\n• 向岚\n• 法泽\n• 百城\n• 奕首\n• 广衡\n• 宇梦\n• 怡硕\n• 熠星\n• 沐睿\n• 书昱\n• 简东\n• 书政\n• 柯仁\n• 鸣毅\n• 惟弘\n• 忠晖\n• 亦程\n• 涛成\n• 勇勤\n• 文奂\n• 文仓\n• 鸿艺\n• 甫宇\n• 晗尚\n• 于安\n• 金连\n• 鑫峥\n• 贤景\n• 睿书\n• 子景\n• 穆祺\n• 嵩帆\n• 维誉\n• 国晖\n• 翊扬\n• 伦昀\n• 谊宁\n• 奕如\n• 辰伊\n• 丰恩\n• 昊承\n• 存皙\n• 学皓\n• 飞掣\n• 晨元\n• 珞宸\n• 先丞\n• 靖然\n• 羽加\n• 皓梓\n• 铭冉\n• 鸿予\n• 瑜擎\n• 沛昀\n• 越祎\n• 金舟\n• 呈抒\n• 昕丞\n• 煦金\n• 灵军\n• 彬实\n• 久宁\n• 焕钧\n• 筱辰\n• 屹鸣\n• 智生\n• 昂峰\n• 之坚\n• 融辉\n• 昂奉\n• 一华\n• 昭俞\n• 沛策\n• 楠德\n• 舒轩\n• 扬莘\n• 梓滔\n• 圣岩\n• 静廷\n• 昶浩\n• 风希\n• 明吉\n• 亦景\n• 凌文\n• 祥贤\n• 夙宸\n• 懿晟\n• 自润\n• 君诚\n• 昕宸\n• 图力\n• 晖岚\n• 默恒\n• 汉霖\n• 成逸\n• 伯坤\n• 商誉\n• 鹏煊\n• 汉韬\n• 若民\n• 君洋\n• 万豪\n• 毓龙\n• 吕续\n• 龙华\n• 锦成\n• 钧岚\n• 叶海\n• 兆航\n• 多辉\n• 恩铭\n• 梓和\n• 景榆\n• 卓洋\n• 歆奕\n• 元旭\n• 锦铄\n• 荻秋\n• 宏利\n• 益浩\n• 夕豪\n• 博扬\n• 宏侠\n• 弘烨\n• 益鹏\n• 振法\n• 国泽\n• 莫宇\n• 传统\n• 弈翰\n• 锋嘉\n• 冰衡\n• 楚诚\n• 胤遥\n• 瑾燊\n• 瑾靖\n• 晗毓\n• 泓伟\n• 彦鑫\n• 毅喆\n• 涵延\n• 仲波\n• 抒虹\n• 羽廷\n• 诗齐\n• 兮浩\n• 皓研\n• 予颜\n• 仕超\n• 钧凯\n• 涛翔\n• 喆彬\n• 奉友\n• 有斌\n• 浚文\n• 洁荣\n• 楚墨\n• 稹虎\n• 烁成\n• 熠晖\n• 善星\n• 昀朗\n• 歌鑫\n• 耀生\n• 伟矾\n• 皓纪\n\n④ 润元(rùn yuán)\n\n1\b\u0005\b\u0007\b、豁达\u0005\u0011\u0006\u0007\u0007、斯洛文<斯洛文尼亚免费观看黃色无遮一级视频strong>斯洛文斯洛文尼亚免费观看欧美一级牲交片尼亚免费观看日韩片的网址尼亚桃花视频大全高清免费动漫斯洛文尼亚免费观看色网站用作人名意指尊荣\u0006\u0010\u0005、本义\b\u0007\u0005:一的大写\b\b\u0006,用作人名意指富甲一方\u0007\u0006\u0006\b、常常组成词语如永恒\b\u0005\u0006\u0007、常绿乔木\u0006\b\u0005\u0010\u0005。引申为王位\b\b\u0005、煌耀\u0007\u0005\u0011\u0007\b,奋进之义;\n\n2\u0006\u0007\u0011\b、引申义凡是一切\u0007\u0007\u0006,部首为豕\u0005\u0006\u0005\u0007,部首为忄\u0006\u0011\u0010\u0007,美好之义;\n\n6\u0007\u0011\u0006\b、百娇柘矢捧壶空\u0007 \b。稳重\u0007\u0005\u0005、五行为水\u0007\u0010\u0006,帝王的代称\u0005\u0006\b\u0006。部首为几\u0007\b\u0011 \u0006,德高望重\b\u0006\b\u0006\u0006、普遍\b\u0005\u0007\u0006。整体等;也指根源\u0007\u0005\u0006\u0010,有情有义\b\u0007\u0005\u0006\u0005、贵重;珍爱\b\u0005\u0006\u0007\u0005,\n\n4\u0010\b\u0006、汉水\u0007\u0005\b\u0005\b、恩惠\u0006\u0007\u0005\u0005、高尚\u0006\b\u0005。严于律己之义;\n\n1\u0007\u0005\u0005、美满\u0006\u0005\u0005、非凡之义;\n\n3\u0011\u0005\u0006\b\u0006、宽仁\u0005\u0005\b、聚合等意思\u0006\u0007\u0006\b\b。精选玉树临风 英俊潇洒的男孩名字\n\n• 2\b\u0005\b、高贵\u0011 \u0005、部首为人\u0007\u0005\u0005\b,善始善终之义;——恒\u0006\b\u0006\u0005,美好之义;——煌\b \u0007\u0007,五行为木\b\u0007\u0005\u0006\b,大度等含义\u0007\u0005\u0005。聪明之义;\n\n② 宸汉(chén hàn)\n\n出自\u0007\u0005\b:\n1 \b\u0007、王洋的《和谹父答郑丈》——抡才俱道用\u0005\b\u0006,用作人名意指博大\u0007\u0006\u0005、部首为士\b\u0006\u0006\u0005,利益\u0005\u0005\u0010。五行为土\b \u0007\u0005,还斯洛文尼亚免费斯洛文尼亚免费观看黃色无遮一级视频观看欧美一级牲交片strong>斯洛文尼亚免费观看日韩片的网址trong>斯洛文尼亚免费观看色网站ong>斯洛文尼亚桃花视频大全高清免费动漫有理解\u0011\u0007\u0005\u0007\b、五行为火\u0006 \u0011\u0005\u0007,\n• 来源:斯洛文尼亚国产片在线观看18女人,转载请注明作者或出处,尊重原创!\n<#longshao:bianliang3#>"
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"https://www.xingyunba.com/editor/attached/image/1/203.jpeg",
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"https://www.xingyunba.com/editor/attached/image/1/79.jpeg",
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"https://www.xingyunba.com/editor/attached/image/1/84.jpeg",
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https://sensegallerydc.com/math-sheets-for-2nd-grade/second-grade-math-worksheets-free-printable-k5-learning-50/ | [
"# Math Sheets For 2nd Grade Image Inspirations Worksheet Uncategorized Second Tot Addition",
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"Math sheets for 2nd grade image inspirations worksheet uncategorized second tot addition.\n\nfree math sheets to print printable math sheets for second grade, kindergarten math sheets math sheets for 2nd grade, addition math sheets to print math sheets to print, 2nd grade math 2nd grade abubakr academy, math sheets 4th grade math sheets, math sheets for second grade to print free math sheets for 2nd grade, math sheets to print out 2nd grade classroom websites, free math worksheets for 2nd grade free printable math sheets for 2nd grade, free math sheets for second grade printable math worksheets, free 3rd grade math sheets to print printable math sheets for 2nd grade."
] | [
null,
"https://sensegallerydc.com/wp-content/uploads/2021/02/math-sheets-for-2nd-grade-image-inspirations-worksheet-uncategorized-second-tot-addition.gif",
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] | {"ft_lang_label":"__label__en","ft_lang_prob":0.7483958,"math_prob":0.89788556,"size":1372,"snap":"2021-31-2021-39","text_gpt3_token_len":283,"char_repetition_ratio":0.2748538,"word_repetition_ratio":0.07462686,"special_character_ratio":0.18221575,"punctuation_ratio":0.050925925,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.9901427,"pos_list":[0,1,2],"im_url_duplicate_count":[null,1,null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2021-08-01T08:37:16Z\",\"WARC-Record-ID\":\"<urn:uuid:00c06551-9e11-4010-9879-f105136851f7>\",\"Content-Length\":\"44752\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:ca4f7dec-c224-4ff5-b102-031fa3ee9c29>\",\"WARC-Concurrent-To\":\"<urn:uuid:689db424-22f3-4609-857c-54ea4b73f326>\",\"WARC-IP-Address\":\"104.21.22.56\",\"WARC-Target-URI\":\"https://sensegallerydc.com/math-sheets-for-2nd-grade/second-grade-math-worksheets-free-printable-k5-learning-50/\",\"WARC-Payload-Digest\":\"sha1:YEDEH2DNOESZCTVONZRQCHWBZJZB7HGP\",\"WARC-Block-Digest\":\"sha1:OYG5RV3IHSA5S64ZBYYDF57A53T75ZZW\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2021/CC-MAIN-2021-31/CC-MAIN-2021-31_segments_1627046154163.9_warc_CC-MAIN-20210801061513-20210801091513-00069.warc.gz\"}"} |
http://umj.imath.kiev.ua/article/?lang=en&article=9826 | [
"2019\nТом 71\n№ 9\n\nDetermination of the lower coefficient in a parabolic equation with strong power degeneration\n\nHuzyk N. M.\n\nAbstract\n\nWe establish conditions for the existence and uniqueness of the classical solution to the inverse problem of identification of the time-dependent coefficient at the first derivative in a one-dimensional degenerate parabolic equation. The Dirichlet boundary conditions and the integral condition of overdetermination are imposed. We study the case of strong power degeneration.\n\nCitation Example: Huzyk N. M. Determination of the lower coefficient in a parabolic equation with strong power degeneration // Ukr. Mat. Zh. - 2016. - 68, № 6. - pp. 922-932.\n\nFull text"
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https://www.groundai.com/project/higgs-g-inflation/ | [
"Higgs G-inflation\n\n# Higgs G-inflation\n\n## Abstract\n\nA new class of inflation models within the context of G-inflation is proposed, in which the standard model Higgs boson can act as an inflaton thanks to Galileon-like non-linear derivative interaction. The generated primordial density perturbation is shown to be consistent with the present observational data. We also make a general discussion on potential-driven G-inflation models, and find a new consistency relation between the tensor-to-scalar ratio and the tensor spectral index , , which is crucial in discriminating the present models from standard inflation with a canonical kinetic term.\n\n98.80.Cq\n1\n\n## I introduction\n\nPrimordial inflation (1); (2) is now regarded as a part of the “standard” cosmology because it not only solves the flatness and the horizon problems but also accounts for the origin of primordial fluctuations (3). To construct a model of inflation, one usually assumes a scalar field that drives inflation (called an inflaton) outside the standard model (SM) of particle physics. This is because there are no scalar fields in the SM except for the Higgs boson and it has been found that the SM Higgs boson cannot be responsible for inflation as long as its kinetic term is canonical and it is minimally coupled to gravity (4). The difficulty here lies in the fact that the self interaction of the SM Higgs boson is so strong that the resultant primordial density fluctuation would be too large to be consistent with the present observational data (5).\n\nTo construct inflation models within the SM, several variants of Higgs-driven inflation have been proposed so far. They include models with a non-minimal coupling term to gravity (6) and with a non-minimal coupling of the Higgs kinetic term with the Einstein tensor (7).2 The amplitude of the curvature perturbation is suppressed due to the large effective Planck scale in the former case, while in the latter case the same thing is caused by the enhanced kinetic function which effectively reduce the self coupling of the Higgs boson.\n\nThe simplest way to enhance the kinetic energy would be to add a non-canonical higher order kinetic term. A number of novel inflation models with non-standard kinetic terms have been proposed, such as k-inflation (9), ghost condensate (10), and Dirac-Born-Infeld inflation (11). When incorporating higher order kinetic terms special care must be taken in order to avoid unwanted ghost instabilities. Since newly introduced degrees of freedom will lead easily to ghosts, it would be desirable if the scalar field does not give rise to a new degree of freedom in spite of its higher derivative nature. It has recently been shown that special combinations of higher order kinetic terms in the Lagrangian produce derivatives no higher than two both in the gravitational and scalar field equations (12); (13). A scalar field having this property is often called the Galileon because it possesses a Galilean shift symmetry in the Minkowski background. Such a scalar field has been studied in the context of modified gravity and dark energy in (14). Recently, an inflation model dubbed as “G-inflation” was proposed (15), in which inflation is driven by a scalar field with a Galileon-like kinetic term. In Ref. (15), the background and perturbation dynamics of G-inflation were investigated, revealing interesting features brought by the Galileon term. For example, scale-invariant scalar perturbations can be generated even in the exactly de Sitter background, and the tensor-to-scalar ratio can take a significantly larger value than in the standard inflation models, violating the standard consistency relation. Other aspects of G-inflation have been explored in Refs. (16); (17) (see also (18)).\n\nIn this paper, we propose a new Higgs inflation model by adding a Galileon-like kinetic term to the standard Higgs Lagrangian. We show that a self coupling constant of the order of the unity is compatible with the present observational data thanks to the kinetic term enhanced by the Galileon effect. We however start with a general discussion on G-inflation driven by the potential term because our potential-driven G-inflation is not restricted only to the Higgs field. We first give a criterion to determine which term becomes dominant in the kinetic term. Then, the slow-roll parameters and the slow-roll conditions are concretely given in terms of the potential and the function characterizing the Galileon term. We also derive the expressions for primordial fluctuations in terms of the slow-roll parameters, and find a new model-independent consistency relation for a potential-driven G-inflation model, which is quite useful for discriminating it from the standard inflation model with a canonical kinetic term. It turns out, however, that primordial non-Gaussianity of the curvature fluctuation is not large in potential-driven G-inflation. Finally, as a concrete example of a potential-driven G-inflation model, we propose a Higgs G-inflation model. This model predicts that the scalar spectral index and the tensor-to-scalar ratio for the number of -folds , which, together with the new consistency relation , makes our Higgs G-inflation model testable in near future.\n\nThis paper is organized as follows. In the next section, we make a general discussion on the potential-driven G-inflation model. In Sec. III, we apply it to more concrete examples, which have chaotic-type, new-type, and hybrid type potential forms. In Sec. IV, we present a new class of inflation model that regards the standard model Higgs boson as an inflaton in the context of G-inflation. Final section is devoted to conclusions and discussion.\n\n## Ii potential-driven G-inflation\n\nThe general Lagrangian describing lowest-order G-inflation is of the form (15)\n\n S=∫d4x√−g[M2Pl2R+K(ϕ,X)−G(ϕ,X)□ϕ], (1)\n\nwhere is the reduced Planck mass, is the Ricci scalar and . The main focus of the present paper is G-inflation driven by the potential term with the kinetic term modified by the term. We therefore take the “standard” form of the function ,\n\n K(ϕ,X)=X−V(ϕ), (2)\n\nwhile for simplicity we assume the following form of the term,\n\n G(ϕ,X)=−g(ϕ)X. (3)\n\n### ii.1 The background dynamics\n\nTaking the homogeneous and isotropic metric , we have the following basic equations governing the background cosmological dynamics:\n\n 3M2PlH2=X[1−gH˙ϕ(6−α)]+V, (4) M2Pl˙H=−X[1−gH˙ϕ(3+η−α)], (5) H˙ϕ[3−η−gH˙ϕ(9−3ϵ−6η+2ηα)]+(1+2β)V′=0,\n\nwhere the dot represents derivative with respect to and the prime with respect to . In the above we have defined\n\n ϵ := −˙HH2, (7) η := −¨ϕH˙ϕ, (8) α := g′˙ϕgH, (9) β := g′′X2V′. (10)\n\nWe assume that all of these quantities are small:\n\n ϵ,|η|,|α|,|β|≪1. (11)\n\nThe condition indicates that must be a slowly-varying function of time. Equations (4) and (5) together with these slow-roll conditions imply\n\n X,|gH˙ϕX|≪V. (12)\n\nThus, the energy density is dominated by the potential under the slow-roll conditions:\n\n 3M2PlH2≃V. (13)\n\nThe slow-roll equation of motion for the scalar field is given by\n\n 3H˙ϕ(1−3gH˙ϕ)+V′≃0. (14)\n\nOne can consider two different limiting cases here. The case corresponds to standard slow-roll inflation, while in the opposite limit, , the Galileon effect alters the scalar field dynamics. We are interested in the latter case. Since , it is required that in order for this regime to be realized. The slow-roll equation of motion can be solved for to give\n\n ˙ϕ≃−sgn(g)MPl(V′3gV)1/2. (15)\n\nWe have fixed the sign of so that , i.e., the scalar field rolls down the potential. This seems to be a natural situation for the scalar field dynamics. As we will see below, ghost instabilities are avoided provided that , and hence only in this branch the Universe can be stable. From Eq. (15) we see\n\n −gH˙ϕ≃13(gV′)1/2. (16)\n\nTherefore, the condition that the kinetic term coming from is much bigger than the usual linear kinetic term is equivalent to\n\n gV′≫1. (17)\n\nUsing the slow-roll equations, one can rewrite the slow-roll parameters in terms of the potential as\n\n ϵ ≃ ϵstd1(gV′)1/2, (18) η ≃ ~ηstd21(gV′)1/2−ϵ+α2, (19) α ≃ −M2Plg′gV′V1(gV′)1/2, (20) β ≃ M4Pl36g′′g(V′V)21gV′, (21)\n\nwhere and are the slow-roll parameters conventionally used for standard slow-roll inflation,\n\n ϵstd:=M2Pl2(V′V)2,~ηstd:=M2PlV′′V. (22)\n\nEquations (18) and (19) clearly show that the Galileon term effectively flatten the potential thanks to the factor . This implies that in the presence of the Galileon-like derivative interaction slow-roll inflation can take place even if the potential is rather steep.\n\nFor later convenience we define . It will be also useful to note that\n\n g˙ϕ3M2PlH≃−23ϵ. (23)\n\nThis means that even if the Galileon dominates the dynamics of slow-roll inflation, the standard part of the Lagrangian remains much larger than the Galileon interaction term,\n\n |K(ϕ,X)|≃V(ϕ)≫|G(ϕ,X)□ϕ|. (24)\n\nLet us make a brief comment on the initial condition for the scalar field. The field may initially be off along the slow-roll trajectory (15). As long as , the field safely approaches the trajectory (15). If initially, the situation is more subtle, because the solution would approach another branch of the slow-roll attractor and the field would go on to climb up the potential. This is what indeed happens if at the initial moment, signaling ghost instabilities [see Eqs. (28)–(30) below]. Note, however, that in Eq. (30) and are evaluated along the slow-roll trajectory; it is therefore possible in principle that but still one has at the initial moment. In this case the solution approaches the healthy branch of the slow-roll attractor.\n\n### ii.2 Primordial fluctuations\n\nLet us investigate the properties of scalar cosmological perturbations in potential-dominated G-inflation. The quadratic action for the curvature perturbation in the unitary gauge, , is given by (15)\n\n S2=M2Pl∫dτd3xa2σ[1c2s(∂τR)2−(→∇R)2], (25)\n\nwhere is the conformal time and\n\n σ := XFM2Pl(H−˙ϕXGX/M2Pl)2, (26) c2s := FG, (27)\n\nwith\n\n F := KX+2GX(¨ϕ+2H˙ϕ)−2G2XM2PlX2 (28) +2GXXX¨ϕ−2(Gϕ−XGϕX), G := KX+2XKXX+6GXH˙ϕ+6G2XM2PlX2 (29) −2(Gϕ+XGϕX)+6GXXHX˙ϕ.\n\nThe above expressions are for general and , but in the present case we simply have\n\n F≃−4gH˙ϕ,G≃−6gH˙ϕ, (30)\n\nand hence\n\n σ≃43ϵ,c2s≃23, (31)\n\nwhere we used Eq. (23). Note that is required to ensure the stability against perturbations, as seen from Eq. (30)\n\nEvaluating the power spectrum from the quadratic action (25) is a standard exercise; we arrive at\n\n PR = 14π2H22σcsM2Pl∣∣ ∣∣τ=1/csk (32) = 3√664π2H2M2Plϵ∣∣ ∣∣τ=1/csk.\n\nThe spectral tilt, , can be evaluated as\n\n ns−1=−6ϵ+3~η+α2, (33)\n\nwhere the relation was used.\n\nThe tensor perturbations are generated in the same way as in the usual canonical inflation models, and hence the power spectrum and the spectral index of the primordial gravitational waves are given by\n\n PT=8M2Pl(H2π)2∣∣∣τ=1/k,nT=−2ϵ. (34)\n\nThus, we obtain a new, model-independent consistency relation between the tensor-to-scalar ratio and the tensor spectral index:\n\n r=16σcs=−32√69nT. (35)\n\n## Iii Galilean symmetric models\n\nIn this section, we shall clarify slow-roll dynamics of G-inflation for three representative forms of the potential. We consider the simplest case where the Galileon-type kinetic term respects not only the Galilean shift symmetry in the Minkowski background, but also the shift symmetry const (19) during inflation, i.e.,\n\n |g|=1M3=const., (36)\n\nwhere is a mass scale. Here the sign of should be chosen to coincide with that of . For (36) the term is odd, and hence the slow-roll solution (15) can be realized only in one side of a -symmetric potential. Note, however, that the following results can be generalized qualitatively to the cases with more general having weak dependence on , because may be practically constant for slowly-rolling . Note also that we assume (36) only in the inflationary stage; may change globally in -space and the detailed shape of would play an important role during the reheating stage after inflation. From the conservative point of view, reheating will proceed in the same way as in the usual inflation models by taking such that around the minimum of the potential . In this section we focus on the dynamics of in the inflationary stage, and we will come back to the issue of reheating in Sec. IV.\n\n### iii.1 Chaotic inflation\n\nFirst, let us consider the chaotic inflation model (20); (19) for which the potential is given by\n\n V(ϕ)=λnϕn, (37)\n\nwith being an integer. We assume that the field is moving in the side and hence . In this case, the condition is equivalent to\n\n ϕ≫(3M3/2λ1/2)2/(n−1)=:ϕG. (38)\n\nSince the slow-roll parameters for are given by\n\n ϵ=n2M2PlM3/22λ1/2ϕ(n+3)/2,~η=n−1nϵ, (39)\n\npotential-driven G-inflation proceeds as long as\n\n ϕ≫(n22M2PlM3/2λ1/2)2/(n+3)=:ϕϵG. (40)\n\nIf , one can consider the scenario in which standard chaotic inflation follows slow-roll G-inflation. This scenario is possible if\n\n M>n(n−1)/32(n−1)/63(n+3)/6λ1/3M(n−1)/3Pl=:Mc. (41)\n\nIf, on the other hand, , i.e., , slow-roll G-inflation ends at and standard chaotic inflation does not follow. In this case, G-inflation is possible even in the region where the potential is too steep to support standard chaotic inflation. In this case, the number of -folds reads\n\n N=∫ϕϵGϕH˙ϕdϕ=2λ1/2n(n+3)M2PlM3/2ϕ(n+3)/2−nn+3. (42)\n\nFrom this we obtain the field value evaluated -folds before the end of inflation,\n\n ϕN=[(n+3)N+n]2/(n+3)(nM2PlM3/22λ1/2)2/(n+3). (43)\n\nThe situation is summarized in Fig. 1.",
null,
"Figure 1: The Galileon effect operates above the magenta line, and the slow-roll condition ϵ<1 is satisfied above the cyan line. Chaotic G-inflation therefore takes place in the shaded region, while in the dotted region standard chaotic inflation occurs. In particular, in the green region the potential is rather steep and hence standard inflation would not proceed, but G-inflation can. For M>Mc it can be seen that a standard inflationary phase follows G-inflation.\n\nNow we investigate the primordial perturbation. In the present case we find\n\n F≃43λ1/2ϕ(n−1)/2M3/2, G≃2λ1/2ϕ(n−1)/2M3/2. (44)\n\nFrom Eqs. (32) and (33), the primordial density perturbation generated during the potential-dominated chaotic G-inflation is evaluated as\n\n PR≃ √632π2n3λ3/2ϕ3(n+1)/2M3/2M6Pl ≃ 7.8×10−3n3 ×{λMnM4Pl(n2[(n+3)N+n])(n+1)}3/(n+3), (45) ns−1 ≃−3(n+1)nϵ≃−3(n+1)(n+3)N+n. (46)\n\nThe scalar-to-tensor ratio is given by\n\n r≃643(23)1/2ϵ≃17n(n+3)N+n. (47)\n\nFor and , we obtain and . The COBE/WMAP normalization, at (5), is attained by taking\n\n λ1/2≃3×1016(M1012GeV)−1GeV. (48)\n\nFor and we find and , which are also compatible with WMAP (5). In this case we obtain\n\n λ≃0.8(M1012GeV)−4, (49)\n\nunder the COBE/WMAP normalization (5), showing that can easily be . This motivates us to study Higgs G-inflation, which will be discussed in the later section.\n\n### iii.2 New inflation\n\nNext, let us consider the new inflation model (21) where the potential is given by\n\n V(ϕ)=V0−12m2ϕ2. (50)\n\nwith . Since we consider the range and there, we take . In this case, the condition is equivalently written as\n\n ϕ≫M3m2=:ϕG. (51)\n\nThe slow-roll parameters can be expressed as\n\n ϵ=M2Plm3M3/2ϕ3/22V20,~η=−M2PlmM3/22V0ϕ1/2. (52)\n\nBoth of the above quantities are smaller than unity in the range\n\n ϕηG<ϕ<ϕϵG, (53)\n\nwhere\n\n ϕϵG:=V4/30M4/3Plm2M,ϕηG:=M4Plm2M34V20=η2std4ϕG, (54)\n\nwith . From this we see that potential-driven G-inflation can occur if\n\n M\n\nSlow-roll inflation ends anyway at\n\n ϕ≈√2V0m:=ϕV. (56)\n\nIf then the Galileon effect never operates during inflation. To have a G-inflationary phase we therefore require , i.e.,\n\n M\n\nSlow-roll G-inflation takes place provided that Eqs. (55) and (57) are both satisfied. Note that\n\n MV≶Msl⇔|ηstd|≶1. (58)\n\nIf (i.e., ), standard new inflation is followed by G-inflation, as shown in Fig. 2. In this case, however, the Galileon term does not help to support an inflationary phase in the region where slow-roll inflation would otherwise be impossible. This case is summarized in Fig. 2.\n\nIf , and hence standard inflation would be impossible. Nevertheless, slow-roll G-inflation can take place with the help of the Galileon term, as shown in Fig. 3.",
null,
"Figure 2: The same diagram as Fig. 1, but for new and hybrid inflation with |ηstd|<1. The Galileon effect operates above the magenta line, the slow-roll condition ϵ<1 is satisfied below the cyan line, and the constant piece V0 dominates the potential below the green line.",
null,
"Figure 3: The same diagram as Fig. 1, but for new and hybrid inflation with |ηstd|>1. The slow-roll conditions are satisfied below the ϵ=1 line and above the η=1 line. Therefore, even though ηstd>1, G-inflation can occur in the green, shaded region.\n\nThe number of -folds during new G-inflation is given by\n\n N=∫ϕVϕH˙ϕdϕ≃2V0M2PlM3/2m(ϕ1/2V−ϕ1/2). (59)\n\nThen, we find the field value, , evaluated -folds before the end of inflation as,\n\n ϕN=[(2V0)1/4m1/2−M2PlM3/2m2V0N]2. (60)\n\nExcept for the special case with we may have . If this is satisfied then we find\n\n ϕN≃ϕV. (61)\n\nNow we investigate the primordial perturbation. In this case, we have\n\n F≃4mϕ1/23M3/2, G≃2mϕ1/2M3/2. (62)\n\nFrom Eq. (32) the power spectrum of the primordial density perturbation generated during the potential-dominated new G-inflation is given by\n\n PR ≃√632π2V30m3M6PlM3/2ϕ3/2. (63)\n\nMore concretely, one can evaluate as\n\n PR ≃ 4.6×10−3V9/40m3/2M6PlM3/2, (64) ns−1 ≃ −6ϵ+3~η≃−6.3×m3/2M2PlM3/2V5/40, (65) r ≃ 643(23)1/2ϵ≃14×M2Plm3/2M3/2V5/40. (66)\n\n### iii.3 Hybrid inflation\n\nFinally, let us study the hybrid inflation model (22) where the potential is effectively given by\n\n V(ϕ)=V0+12m2ϕ2. (67)\n\nWe consider the range , and hence take . Hybrid inflation ends when the waterfall field becomes tachyonic. Let be the value of where this occurs. We will therefore focus on the range . For , the constant piece in the potential can be ignored, and hence the situation reduces to chaotic inflation studied in Sec. III.1.\n\nThe situation here is analogous to the case of new inflation. The Galileon effect operates for , where is given in Eq. (51). The slow-roll parameters for are given by\n\n ϵ=M2Plm3M3/2ϕ3/22V20,~η=M2PlmM3/22V0ϕ1/2, (68)\n\nso that the slow-roll conditions are satisfied in the range , where and are the quantities defined in Eq. (54). Thus, the inflaton dynamics can be summarized in Figs. 2 and 3, depending on the values of and . Since , G-inflation is followed by standard hybrid inflation if . If then G-inflation can occur even though standard inflation would be impossible as . We remark that hybrid inflation ends at , which is not indicated explicitly in the figures, and for hybrid inflation reduces to chaotic inflation, which is not shown in the figures either.\n\nThe primordial perturbation is described in the same way as in new inflation,\n\n PR ≃√632π2V30m3M6PlM3/2ϕ3/2. (69)\n\nThe number of -folds during hybrid G-inflation reads\n\n N=∫ϕtacϕH˙ϕdϕ≃2V0M2PlM3/2m(ϕ1/2−ϕ1/2tac). (70)\n\nWe then obtain the field value evaluated -folds before the end of inflation as,\n\n ϕN=(ϕ1/2tac+M2PlM3/2m2V0N)2. (71)\n\nIn the case where\n\n ϕtac≫(M2PlM3/2m2V0N)2, (72)\n\nwe have\n\n ϕN≃ϕtac, (73)\n\nand thus\n\n PR ≃7.6×10−3V30m3M6PlM3/2ϕ3/2tac, (74) ns−1 ≃3~η≃3M2PlmM3/22V0ϕ1/2tac, (75) r ≃643(23)1/2ϵ ≃8.7×M2Plm3M3/2ϕ3/2tacV20. (76)\n\nIn the opposite case where\n\n ϕtac≪(M2PlM3/2m2V0N)2, (77)\n\nwe have\n\n ϕN≃M4PlM6m24V20N2, (78)\n\nso that\n\n PR ≃6.2×10−3V60M12Plm6M6N3, (79) ns−1 ≃3N, (80) r ≃1.1×M8Plm6M6V50N3. (81)\n\n## Iv Higgs G-inflation\n\nLet us now construct a Higgs inflation model in the context of G-inflation. The tree-level SM Higgs Lagrangian is\n\n S0=∫d4x√−g[M2Pl2R−|DμH|2−λ(|H|2−v2)2], (82)\n\nwhere is the covariant derivative with respect to the SM gauge symmetry, is the SM Higgs boson, is the vacuum expectation value (VEV) of the SM Higgs and is the self coupling constant. Since we would like to have a chaotic inflation-like dynamics of the Higgs boson, we consider the case where its neutral component is very large compared with to : . In this situation, we have only to consider a simpler action,\n\n S0=∫d4x√−g[M2Pl2R−12(∂μϕ)2−λ4ϕ4]. (83)\n\nIn addition to the above action, we consider a Galileon-type interaction, which breaks Galilean shift symmetry weakly,\n\n SG =∫d4x√−g[−2H†M4DμDμH|DμH|2] →∫d4x√−g[−ϕ2M4□ϕ(∂μϕ)2], (84)\n\nwhere is a mass parameter. Here we assume . Note that gauge fields that couples to receive heavy mass from the field value of the Higgs boson and hence we can neglect the effect of gauge fields when we consider the inflationary trajectory. This setup corresponds to the case\n\n K=X−V(ϕ), V(ϕ)=λ4ϕ4, G=−ϕM4X. (85)\n\nThe Galileon effect operates provided that , i.e.,\n\n ϕ≫λ−1/4M. (86)\n\nIn this regime the slow-roll parameters are given by\n\n ϵ=8M2PlM2λ1/2ϕ4=43~η=−2α, (87)\n\nand , so that the slow-roll conditions are satisfied if\n\n ϕ≫23/4λ−1/8M1/2PlM1/2=:ϕend. (88)\n\nFrom Eqs. (86) and (88) one can define a mass scale, analogously to Eq. (41),\n\n Mc:=λ−3/4MPl. (89)\n\nIf , Higgs G-inflation proceeds even if standard Higgs inflation would otherwise be impossible. One can draw essentially the same diagram as Fig. 1 for Higgs-G inflation.\n\nThe number of -folds is given by\n\n N =∫ϕendϕH˙ϕdϕ=116λ1/2M2PlM2ϕ4−12, (90)\n\nfrom which we obtain the field value evaluated -folds before the end of inflation as\n\n ϕN=(16N+8)1/4λ−1/8M1/2PlM1/2. (91)\n\nAs will be mentioned at the end of this section, reheating after Higgs G-inflation proceeds in the same way as in the standard inflationary models, and hence the history of the Universe after inflation will not be altered. Therefore, we use the value .\n\nNow let us turn to the primordial perturbation in this model. Using the slow-roll approximation, we obtain\n\n F ≃4λ1/2ϕ23M2, G ≃2λ1/2ϕ2M2. (92)\n\nWe thus arrive at\n\n PR =14π2H4˙ϕ2c2s√FG =(2NCOBE+1)2λ1/28π2(38)1/2(MMPl)2 ≃1.1×102λ1/2(MMPl)2, (93)\n\nand\n\n ns =1−4ϵ≃1−42NCOBE+1≃0.967. (94)\n\nAccording to WMAP observations, (5), and hence\n\n M≃4.7×10−6λ−1/4MPl≃1013GeV. (95)\n\nThe scalar-to-tensor ratio is given by\n\n r=643(23)1/2ϵ≃17×12NCOBE+1. (96)\n\nFor this yields , which is large enough to be detected by the forthcoming observation by PLANCK (23).\n\nNote that in the above discussion we have neglected the quantum corrections. In order to have the precise relation between the potential of the Higgs field and the observational signatures such as the tensor-to-scalar ratio , we must know/assume the complete theory valid up to the inflationary scale, which is left for future study. However, the qualitative argument will not be changed even if we take into account quantum effects, because it can be absorbed by the variation of .\n\nBefore closing this section, let us take a brief look at reheating after Higgs G-inflation. The dynamics of the inflaton field during the reheating stage is non-trivial in general when one considers non-standard kinetic terms. In the present case, however, the effect of Galileon-like interaction can safely be ignored during reheating because is suppressed around the minimum of the potential, . In Fig. 4 we show a numerical example of the evolution of and in the final stage of Higgs G-inflation and in the begining of the reheating stage, when the Higgs field oscillates rapidly. We have confirmed that the Galileon terms become ineffective very soon after inflation ends, leading to reheating in the same way as in the usual case, , for the quartic potential.",
null,
"Figure 4: The evolution of |ϕ| (blue, oscillating line) and ρ (purple line) in the very final stage of Higgs G-inflation and in the reheating stage thereafter. We set a(tend)=1 with ϵ(tend)=1. The parameters are given by λ=0.1 and M=0.01×Mc.\n\n## V Discussion\n\nThe Galileon-like nonlinear derivative interaction, , opens up a new arena of inflation model building while keeping the models healthy, and the novel class of inflation thus developed —G-inflation— possesses various interesting aspects to be explored. In (15) the extreme case was emphasized where G-inflation is driven purely by the kinetic energy, though the background and the perturbation equations have been derived without assuming any specific form of and . In this paper, we have studied the effects of the Galileon term on potential-driven inflation. Although the energy density is dominated by the potential anyway, the dynamics of the inflaton is nontrivial when the term participates more dominantly than the usual linear kinetic term . We have demonstrated that the Galileon term makes the potential effectively flatter so that slow-roll inflation proceeds even if the potential is in fact too steep to support conventional slow-roll inflation. In light of this fact, we have constructed a viable model of Higgs inflation, i.e., Higgs G-inflation, showing that the power spectrum of the primordial density perturbation is compatible with current observational data. The tensor-to-scalar ratio is large enough to be detected by the Planck satellite.\n\nIn this paper we have focused on the power spectrum of the curvature perturbation and the consistency relation relative to the amplitude of tensor perturbations. Primordial non-Gaussianity would be another powerful probe to discriminate G-inflation among others. Unfortunately, however, non-Gaussianity arising from the present potential-driven models is estimated to be not large. This is because is composed of and slow-roll suppressed terms with in the present model, leading to . (Detailed computation of primordial non-Gaussianity from G-inflation will be given elsewhere (24); see also (16); (17); (18).) We would thus conclude that the smoking gun of potential-driven G-inflation is the consistency relation which is unique enough to distinguish G-inflation from standard canonical inflation and k-inflation.\n\nWe have focused on the (generalized form of the) leading order Galileon term. As demonstrated in (14), higher order terms play an important role in the cosmological dynamics of Galileon dark energy models. Therefore, it would be interesting to consider the effects of the higher order Galileon terms in the context of primordial inflation, which is left for further study.\n\n## Acknowledgments\n\nThis work was partially supported by JSPS through research fellowships (K.K.) and the Grant-in-Aid for the Global COE Program “Global Center of Excellence for Physical Sciences Frontier”. This work was also supported in part by JSPS Grant-in-Aid for Research Activity Start-up No. 22840011 (T.K.), the Grant-in-Aid for Scientific Research Nos. 19340054 (J.Y.), 21740187 (M.Y.), and the Grant-in-Aid for Scientific Research on Innovative Areas No. 21111006 (J.Y.).\n\n### Footnotes\n\n1. preprint: RESCEU-28/10\n2. Inflation models where Higgs multiplets act as an inflaton in the context of supersymmetric extensions of the SM, e.g., the next-to-minimal supersymmetric standard model, have also been proposed in (8). In these models, a non-canonical Khler potential for the Higgs multiplet is assumed.\n\n### References\n\n1. K. Sato, Mon. Not. Roy. Astron. Soc. 195, 467 (1981); A. H. Guth, Phys. Rev. D 23, 347 (1981); A. A. Starobinsky, Phys. Lett. B 91, 99 (1980).\n2. For reviews, see A. D. Linde, arXiv:hep-th/0503203; D. H. Lyth and A. Riotto, Phys. Rept. 314, 1 (1999) [arXiv:hep-ph/9807278].\n3. S. W. Hawking, Phys. Lett. 115B, 295 (1982); A. A. Starobinsky, Phys. Lett. 117B, 175 (1982); A. H. Guth and S-Y. Pi, Phys. Rev. Lett. 49, 1110 (1982).\n4. A. D. Linde, Phys. Lett. B 129, 177 (1983).\n5. E. Komatsu et al., arXiv:1001.4538 [astro-ph.CO].\n6. F. L. Bezrukov and M. Shaposhnikov, Phys. Lett. B 659, 703 (2008) [arXiv:0710.3755 [hep-th]]; B. L. Spokoiny, Phys. Lett. B 147 (1984) 39; T. Futamase and K. i. Maeda, Phys. Rev. D 39, 399 (1989); D. S. Salopek, J. R. Bond and J. M. Bardeen, Phys. Rev. D 40, 1753 (1989); R. Fakir and W. G. Unruh, Phys. Rev. D 41, 1783 (1990); D. I. Kaiser, Phys. Rev. D 52, 4295 (1995) [arXiv:astro-ph/9408044]; E. Komatsu and T. Futamase, Phys. Rev. D 59, 064029 (1999) [arXiv:astro-ph/9901127]; S. Tsujikawa and B. Gumjudpai, Phys. Rev. D 69, 123523 (2004) [arXiv:astro-ph/0402185]; A. O. Barvinsky, A. Y. Kamenshchik and A. A. Starobinsky, JCAP 0811, 021 (2008) [arXiv:0809.2104 [hep-ph]]; F. Bezrukov, D. Gorbunov and M. Shaposhnikov, JCAP 0906, 029 (2009) [arXiv:0812.3622 [hep-ph]]; J. Garcia-Bellido, D. G. Figueroa and J. Rubio, Phys. Rev. D 79, 063531 (2009) [arXiv:0812.4624 [hep-ph]]; A. De Simone, M. P. Hertzberg and F. Wilczek, Phys. Lett. B 678, 1 (2009) [arXiv:0812.4946 [hep-ph]]; F. L. Bezrukov, A. Magnin and M. Shaposhnikov, Phys. Lett. B 675, 88 (2009) [arXiv:0812.4950 [hep-ph]]; F. Bezrukov and M. Shaposhnikov, JHEP 0907, 089 (2009) [arXiv:0904.1537 [hep-ph]]; A. O. Barvinsky, A. Y. Kamenshchik, C. Kiefer, A. A. Starobinsky and C. Steinwachs, JCAP 0912, 003 (2009) [arXiv:0904.1698 [hep-ph]]; F. Bezrukov, A. Magnin, M. Shaposhnikov and S. Sibiryakov, arXiv:1008.5157 [hep-ph].\n7. C. Germani and A. Kehagias, Phys. Rev. Lett. 105, 011302 (2010) [arXiv:1003.2635 [hep-ph]]; C. Germani and A. Kehagias, JCAP 1005, 019 (2010) [Erratum-ibid. 1006, E01 (2010)] [arXiv:1003.4285 [astro-ph.CO]];\n8. M. B. Einhorn and D. R. T. Jones, JHEP 1003, 026 (2010) [arXiv:0912.2718 [hep-ph]]; S. Ferrara, R. Kallosh, A. Linde, A. Marrani and A. Van Proeyen, Phys. Rev. D 82, 045003 (2010) [arXiv:1004.0712 [hep-th]]. H. M. Lee, JCAP 1008, 003 (2010) [arXiv:1005.2735 [hep-ph]]; S. Ferrara, R. Kallosh, A. Linde, A. Marrani and A. Van Proeyen, arXiv:1008.2942 [hep-th]; K. Nakayama and F. Takahashi, arXiv:1008.4457 [hep-ph]; I. Ben-Dayan and M. B. Einhorn, JCAP 1012, 002 (2010) [arXiv:1009.2276 [hep-ph]].\n9. C. Armendariz-Picon, T. Damour and V. F. Mukhanov, Phys. Lett. B 458, 209 (1999) [arXiv:hep-th/9904075].\n10. N. Arkani-Hamed, H. C. Cheng, M. A. Luty and S. Mukohyama, JHEP 0405, 074 (2004) [arXiv:hep-th/0312099]; N. Arkani-Hamed, P. Creminelli, S. Mukohyama and M. Zaldarriaga, JCAP 0404, 001 (2004) [arXiv:hep-th/0312100].\n11. M. Alishahiha, E. Silverstein and D. Tong, Phys. Rev. D 70, 123505 (2004) [arXiv:hep-th/0404084].\n12. A. Nicolis, R. Rattazzi and E. Trincherini, Phys. Rev. D 79, 064036 (2009) [arXiv:0811.2197 [hep-th]].\n13. C. Deffayet, G. Esposito-Farese and A. Vikman, Phys. Rev. D 79, 084003 (2009) [arXiv:0901.1314 [hep-th]]; C. Deffayet, S. Deser and G. Esposito-Farese, Phys. Rev. D 80, 064015 (2009) [arXiv:0906.1967 [gr-qc]].\n14. N. Chow and J. Khoury, Phys. Rev. D 80, 024037 (2009) [arXiv:0905.1325 [hep-th]]; F. P. Silva and K. Koyama, Phys. Rev. D 80, 121301 (2009) [arXiv:0909.4538 [astro-ph.CO]]; T. Kobayashi, H. Tashiro and D. Suzuki, Phys. Rev. D 81, 063513 (2010) [arXiv:0912.4641 [astro-ph.CO]]; T. Kobayashi, Phys. Rev. D 81, 103533 (2010) [arXiv:1003.3281 [astro-ph.CO]]; R. Gannouji and M. Sami, Phys. Rev. D 82, 024011 (2010) [arXiv:1004.2808 [gr-qc]]; A. De Felice and S. Tsujikawa, arXiv:1005.0868 [astro-ph.CO]; A. De Felice, S. Mukohyama and S. Tsujikawa, arXiv:1006.0281 [astro-ph.CO]; A. De Felice and S. Tsujikawa, arXiv:1007.2700 [astro-ph.CO]; C. Deffayet, O. Pujolas, I. Sawicki and A. Vikman, arXiv:1008.0048 [hep-th]; A. Ali, R. Gannouji and M. Sami, arXiv:1008.1588 [astro-ph.CO]; A. De Felice and S. Tsujikawa, arXiv:1008.4236 [hep-th]; S. Nesseris, A. De Felice and S. Tsujikawa, arXiv:1010.0407 [astro-ph.CO]; R. Kimura and K. Yamamoto, arXiv:1011.2006 [astro-ph.CO]; A. De Felice, R. Kase and S. Tsujikawa, arXiv:1011.6132 [astro-ph.CO].\n15. T. Kobayashi, M. Yamaguchi and J. Yokoyama, Phys. Rev. Lett. 105, 231302 (2010) [arXiv:1008.0603 [hep-th]].\n16. S. Mizuno and K. Koyama, arXiv:1009.0677 [hep-th].\n17. C. Burrage, C. de Rham, D. Seery and A. J. Tolley, arXiv:1009.2497 [hep-th].\n18. P. Creminelli, G. D’Amico, M. Musso, J. Norena and E. Trincherini, arXiv:1011.3004 [hep-th].\n19. M. Kawasaki, M. Yamaguchi and T. Yanagida, Phys. Rev. Lett. 85, 3572 (2000) [arXiv:hep-ph/0004243]; Phys. Rev. D 63, 103514 (2001) [arXiv:hep-ph/0011104]; M. Yamaguchi and J. Yokoyama, Phys. Rev. D 63, 043506 (2001) [arXiv:hep-ph/0007021]; Phys. Rev. D 68, 123520 (2003) [arXiv:hep-ph/0307373].\n20. A. D. Linde, Phys. Lett. B 129, 177 (1983); H. Murayama, H. Suzuki, T. Yanagida and J. Yokoyama, Phys. Rev. Lett. 70, 1912 (1993); Phys. Rev. D 50, 2356 (1994); K. Kadota and M. Yamaguchi, Phys. Rev. D 76, 103522 (2007) [arXiv:0706.2676 [hep-ph]]; K. Kadota, T. Kawano and M. Yamaguchi, Phys. Rev. D 77, 123516 (2008) [arXiv:0802.0525 [hep-ph]].\n21. A. D. Linde, Phys. Lett. B 108, 389 (1982); A. Albrecht and P. J. Steinhardt, Phys. Rev. Lett. 48, 1220 (1982); K. Kumekawa, T. Moroi and T. Yanagida, Prog. Theor. Phys. 92, 437 (1994) [arXiv:hep-ph/9405337]; K. I. Izawa and T. Yanagida, Phys. Lett. B 393, 331 (1997) [arXiv:hep-ph/9608359].\n22. A. D. Linde, Phys. Lett. B 259, 38 (1991); A. D. Linde, Phys. Rev. D 49, 748 (1994) [arXiv:astro-ph/9307002]; E. J. Copeland, A. R. Liddle, D. H. Lyth, E. D. Stewart and D. Wands, Phys. Rev. D 49, 6410 (1994) [arXiv:astro-ph/9401011]; G. R. Dvali, Q. Shafi and R. K. Schaefer, Phys. Rev. Lett. 73, 1886 (1994) [arXiv:hep-ph/9406319].\n23. [Planck Collaboration], arXiv:astro-ph/0604069.\n24. T. Kobayashi, M. Yamaguchi and J. Yokoyama, in preparation.\nYou are adding the first comment!\nHow to quickly get a good reply:\n• Give credit where it’s due by listing out the positive aspects of a paper before getting into which changes should be made.\n• Be specific in your critique, and provide supporting evidence with appropriate references to substantiate general statements.\n• Your comment should inspire ideas to flow and help the author improves the paper.\n\nThe better we are at sharing our knowledge with each other, the faster we move forward.\nThe feedback must be of minimum 40 characters and the title a minimum of 5 characters",
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https://www.projecteuclid.org/euclid.aos/1176345788 | [
"The Annals of Statistics\n\nThe Asymptotic Effect of Substituting Estimators for Parameters in Certain Types of Statistics\n\nDonald A. Pierce\n\nAbstract\n\nIn a variety of statistical problems, one is interested in the limiting distribution of statistics $\\hat{T}_n = T_n(y_1, y_2, \\cdots, y_n; \\hat{\\lambda}_n)$, where $\\hat{\\lambda}_n$ is an estimator of a parameter in the distribution of the $y_i$ and where the limiting distribution of $T_n = T_n(y_1, y_2, \\cdots, y_n; \\lambda)$ is relatively easy to find. For cases in which the limiting distribution of $T_n$ is normal with mean independent of $\\lambda$, a useful method is given for finding the limiting distribution of $\\hat{T}_n$. A simple application to testing normality in regression models is given.\n\nArticle information\n\nSource\nAnn. Statist., Volume 10, Number 2 (1982), 475-478.\n\nDates\nFirst available in Project Euclid: 12 April 2007\n\nPermanent link to this document\nhttps://projecteuclid.org/euclid.aos/1176345788\n\nDigital Object Identifier\ndoi:10.1214/aos/1176345788\n\nMathematical Reviews number (MathSciNet)\nMR653522\n\nZentralblatt MATH identifier\n0488.62012\n\nJSTOR"
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https://dyclassroom.com/python/python-if-else-statement | [
"# Python - If Else statement\n\nPython\n\nShare",
null,
"In this tutorial we will learn about If Else statement in Python.\n\nThe `if` statement is a decision making statement and it controls the flow of the execution of the program.\n\n## If\n\nWe use the `if` keyword to create an if statement. The body of the if statement is indented with tabs/spaces.\n\n### If syntax\n\n``````if condition:\n#\n# if block code\n#\n``````\n\nCode inside the if block is executed only when the given `condition` is satisfied. Otherwise, it is ignored.\n\n### Example #1\n\nIn the following Python code we are checking whether x is even.\n\n``````# variable\nx = 10\n\nif x % 2 == 0:\nprint(\"x is even.\")\n\nprint(\"End of code.\")\n``````\n\nThe above code will print the following output.\n\n``````x is even.\nEnd of code.\n``````\n\nIf the value of x is odd then we will get the following result.\n\n``````End of code.\n``````\n\nThis is because the if block is ignored as the condition is not satisfied.\n\n## If Else\n\nIf we want to create an \"either-or\"/\"two-options\" then we use the if-else statement.\n\nWe use the `else` keyword to create the else block.\n\n### If Else syntax\n\n``````if condition:\n#\n# if block code\n#\nelse:\n#\n# else block code\n#\n``````\n\nCode inside the if block is executed only when the given `condition` is satisfied. Otherwise, else block code is executed.\n\n### Example #2\n\nIn the following Python code we will get either \"x is odd\" or \"x is even\" message depending on the value of x.\n\n``````# variable\nx = 10\n\nif x % 2 == 0:\nprint(\"x is even\")\nelse:\nprint(\"x is odd\")\n\nprint(\"End of code.\")\n``````\n\nAs x is 10 so, we will get the following output.\n\n``````x is even\nEnd of code.\n``````\n\nIf we change the value of x to 11 then we will have the following result.\n\n``````x is odd\nEnd of code.\n``````\n\n## Elif\n\nIf we want more than two options then we create a chain of if else statement using `elif` keyword.\n\n### Elif syntax\n\n``````if condition1:\n#\n# condition1 block code\n#\nelif condition2:\n#\n# condition2 block code\n#\nelse:\n#\n# else block code\n#\n``````\n\nCode inside the condition1 if block is executed only when the given condition `condition1` is satisfied.\n\nIf `condition1` fails then `condition2` is checked. If it is satisfied then the condition2 block is executed.\n\nIf no condition is satisfied then, else block code is executed.\n\nYou can have multiple `elif` block based on your requirement.\n\n### Example #3\n\nIn the following Python code we are checking is x an even number or odd number or zero.\n\n``````# variable\nx = 0\n\nif x == 0:\nprint(\"x is zero\")\nelif x % 2 == 0:\nprint(\"x is even\")\nelse:\nprint(\"x is odd\")\n\nprint(\"End of code.\")\n``````\n\nAs x is 0 so, we will get the following output.\n\n``````x is zero\nEnd of code.\n``````\n\n## Shorthand If\n\nIf there is only one statement in the if-block then we can write that in one line like the following.\n\n``````# variable\nx = 10\n\nif x % 2 == 0: print(\"x is even\")\n\nprint(\"End of code.\")\n``````\n\n## Shorthand If Else\n\nIf there is only one statement for both if and else block then we can write them all in one line.\n\nThe following code will print \"x is even\" if the if-condition is satisfied otherwise, it will print \"x is odd\".\n\n``````# variable\nx = 10\n\nprint(\"x is even\") if x % 2 == 0 else print(\"x is odd\")\n\nprint(\"End of code\")\n``````\n\n## Using `and`, `or` and `not` operators\n\nWe can also use logical operators to check multiple conditions.\n\n### Example #3\n\nIn the following Python program we are going to print \"foo\" if value of x is divisible by 3, \"bar\" if value of x is divisible by 5 and \"foobar\" if value of x is divisible by both 3 and 5.\n\n``````# variable\nx = 10\n\nif x % 3 == 0 and x % 5 == 0:\nprint(\"foobar\")\nelif x % 3 == 0:\nprint(\"foo\")\nelif x % 5 == 0:\nprint(\"bar\")\n\nprint(\"End of code.\")\n``````\n\nThe above code will print \"bar\" as x is 10 and divisible by 5. Try changing the value of x to get different result.\n\nShare"
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https://brainmass.com/statistics/probability/determine-birthplace-class-college-students-605994 | [
"Explore BrainMass\n\n# Determine the birthplace of a class of college students.\n\nThis content was COPIED from BrainMass.com - View the original, and get the already-completed solution here!\n\nA poll was taken to determine the birthplace of a class of college students. Below is a chart of the results.\n\na. What is the probability that a female student was born in Orlando?\nb. What is the probability that a male student was born in Miami?\nc. What is the probability that a student was born in Jacksonville?\n\nGender Number of students Location of birth\nMale 10 Jacksonville\nFemale 16 Jacksonville\nMale 5 Orlando\nFemale 12 Orlando\nMale 7 Miami\nFemale 9 Miami\n\nhttps://brainmass.com/statistics/probability/determine-birthplace-class-college-students-605994\n\n#### Solution Preview\n\nProblem: A poll was taken to determine the birthplace of a class of college students. Below is a chart of the results.\na. What is the probability that a female student was born in Orlando?\nb. What is the probability that a male student was born in ...\n\n#### Solution Summary\n\nThe expert determines the birthplace of a class of college students. The probability of female and male students being born in different Florida cities are determined. The cities examined are Orlando, Miami and Jacksonville. Division is used to determine the probabilities. The solution shows the steps of the division.\n\n\\$2.19"
] | [
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] | {"ft_lang_label":"__label__en","ft_lang_prob":0.97203296,"math_prob":0.6934001,"size":1330,"snap":"2020-45-2020-50","text_gpt3_token_len":283,"char_repetition_ratio":0.16515838,"word_repetition_ratio":0.45410627,"special_character_ratio":0.2,"punctuation_ratio":0.116,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.9642924,"pos_list":[0],"im_url_duplicate_count":[null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2020-11-26T09:03:11Z\",\"WARC-Record-ID\":\"<urn:uuid:2858c56e-6904-483a-bb44-203150f1d2e6>\",\"Content-Length\":\"38924\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:b547ef4c-826e-495e-9a2b-4752f22f1530>\",\"WARC-Concurrent-To\":\"<urn:uuid:4ee66077-ef8a-472f-8be3-65575a5045e8>\",\"WARC-IP-Address\":\"65.39.198.123\",\"WARC-Target-URI\":\"https://brainmass.com/statistics/probability/determine-birthplace-class-college-students-605994\",\"WARC-Payload-Digest\":\"sha1:3AE6WYGQEEDIMXWN2252KNLCTV5RDXBV\",\"WARC-Block-Digest\":\"sha1:XJKXDR2SYFWZRIHEJ6XC76KNMRTAAK7L\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2020/CC-MAIN-2020-50/CC-MAIN-2020-50_segments_1606141187753.32_warc_CC-MAIN-20201126084625-20201126114625-00236.warc.gz\"}"} |
https://community.splunk.com/t5/Archive/Query-to-get-results-from-multiple-indexes/td-p/440778 | [
"Archive\nHighlighted\n\n## Query to get results from multiple indexes?\n\nExplorer\n\nI've 2 indexes \"abc\" and \"def\". There is a field \"accountnumber\" in index \"abc\" and a field \"Empnummber\" in index \"def\". I want to find the total number of events, for the accounts present only in \"abc\" and not in \"def\",\n\nI wrote the below query but it seems I'm getting all the accounts which are present only in \"abc\" and also the accounts which are present in both \"abc\" and \"def\".\n\n(index=abc sourcetype=xyz eventtype= \"FAIL\")\nOR\n(index=def (ACTION=10 OR ACTION=20 OR ACTION=30))\n| eval dex1= if(index==\"abc\",1,0)\n| stats min(\ntime), sum(dex1) as dex1 by accountnumber, sessionid | where dex1 > 0\n| stats sum(dex1) as Final_number\n\nTags (3)\nHighlighted\n\n## Re: Query to get results from multiple indexes?",
null,
"SplunkTrust\n\ncould you try?\n\n``````(index=abc sourcetype=xyz event_type= \"FAIL\") NOT [search index=def (ACTION=10 OR ACTION=20 OR ACTION=30)| dedup Emp_nummber | table Emp_nummber | rename Emp_nummber as account_number ]\n| stats count by account_number\n``````\n\nOR\n\n``````(index=abc sourcetype=xyz event_type= \"FAIL\") OR (index=def (ACTION=10 OR ACTION=20 OR ACTION=30))\n| dedup Emp_nummber keepempty=true\n| dedup account_number keepempty=true\n| eval myNumber=coalesce(Emp_nummber,account_number)\n| eval from_index1=if(index=\"abc\",1,null())\n| stats dc(index) AS num_occurences sum(from_index1) AS from_index1 by myNumber\n| where num_occurences=1 AND from_index1=1\n| table myNumber\n``````"
] | [
null,
"https://community.splunk.com/html/rank_icons/splunk-trust-16.png",
null
] | {"ft_lang_label":"__label__en","ft_lang_prob":0.78251415,"math_prob":0.9364676,"size":1276,"snap":"2020-34-2020-40","text_gpt3_token_len":378,"char_repetition_ratio":0.15408805,"word_repetition_ratio":0.07909604,"special_character_ratio":0.28369907,"punctuation_ratio":0.059907835,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.9934023,"pos_list":[0,1,2],"im_url_duplicate_count":[null,null,null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2020-08-15T14:50:04Z\",\"WARC-Record-ID\":\"<urn:uuid:8703ec14-54b1-4ecd-843b-d2fd21ac65a7>\",\"Content-Length\":\"163270\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:a002228f-1c1f-4bc7-9dad-394910901896>\",\"WARC-Concurrent-To\":\"<urn:uuid:af0f1d60-a176-43d5-8eb7-68f87fd415ed>\",\"WARC-IP-Address\":\"13.32.182.4\",\"WARC-Target-URI\":\"https://community.splunk.com/t5/Archive/Query-to-get-results-from-multiple-indexes/td-p/440778\",\"WARC-Payload-Digest\":\"sha1:LSSEDQQQDHOIJKNDAS5BUNGQIO6KO7VI\",\"WARC-Block-Digest\":\"sha1:TCWUF4BM7PYYUYOTBJBBHJTXQPQEURVW\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2020/CC-MAIN-2020-34/CC-MAIN-2020-34_segments_1596439740848.39_warc_CC-MAIN-20200815124541-20200815154541-00079.warc.gz\"}"} |
https://www.arxiv-vanity.com/papers/1210.6733/ | [
"# Is the firewall consistent? Gedanken experiments on black hole complementarity and firewall proposal\n\nDong-il Hwang1, Bum-Hoon Lee2 and Dong-han Yeom3\nCenter for Quantum Spacetime, Sogang University, Seoul 121-742, Republic of Korea\n11\n22\n33\n###### Abstract\n\nIn this paper, we discuss the black hole complementarity and the firewall proposal at length. Black hole complementarity is inevitable if we assume the following five things: unitarity, entropy-area formula, existence of an information observer, semi-classical quantum field theory for an asymptotic observer, and the general relativity for an in-falling observer. However, large rescaling and the AMPS argument show that black hole complementarity is inconsistent. To salvage the basic philosophy of the black hole complementarity, AMPS introduced a firewall around the horizon. According to large rescaling, the firewall should be located close to the apparent horizon.\n\nWe investigate the consistency of the firewall with the two critical conditions: the firewall should be near the time-like apparent horizon and it should not affect the future infinity. Concerning this, we have introduced a gravitational collapse with a false vacuum lump which can generate a spacetime structure with disconnected apparent horizons. This reveals a situation that there is a firewall outside of the event horizon, while the apparent horizon is absent. Therefore, the firewall, if it exists, not only does modify the general relativity for an in-falling observer, but also modify the semi-classical quantum field theory for an asymptotic observer.\n\n## 1 Introduction\n\nThe black hole information loss problem is a profoundly important issue in quantum gravity. From classical and semi-classical analysis, we already understand that any stationary black hole is characterized by the following three information: mass , charge and angular momentum . After a black hole evaporates, what happens to the quantum information? If it cannot be aptly captured with the aid of Hawking radiation, then we immediately see a violation of unitarity and lose fundamental predictability of the theory. Otherwise, how can we be so sure regarding this and how can we restore the information?\n\nAfter the advent of the AdS/CFT correspondence , people became confident about the unitarity of black hole physics, since bulk gravitational dynamics corresponds to the boundary conformal field theory and the boundary conformal field theory should be unitary. However, the question that still crops up in our mind is how does Hawking radiation contains information and is it consistent?\n\nIn fact, even before the discovery of AdS/CFT, some people began to consider the consistency of unitarity. Especially, the works by Stephens, t’Hooft and Whiting and Susskind, Thorlacius and Uglum contributed to this problem immensely and is respectively known in literature as the holographic principle and black hole complementarity. According to the black hole complementarity principle, it is customary to think that an asymptotic observer and an in-falling observer of a black hole should satisfy natural laws. Then the semi-classical and unitary quantum field theory should be a good description for the asymptotic observer, while general relativity should serve as a good prescription for the in-falling observer. But, it seems contradictory, since both observers maintain their information and hence the information seem to have copied: one is inside the event horizon, while the other is outside it. However, the black hole complementarity and the natural laws still hold for all observers and are consistent, since two observers cannot communicate among themselves . Therefore, although a black hole violates a natural law (the no-cloning theorem), it remains unnoticed like an orderly crime without any witness – a perfect crime.\n\nHowever, recently, people started asking questions on the very consistency of the black hole complementarity principle itself. The duplication of information can be observed in case of regular black holes or charged black holes [9, 10, 11], if we assume large number of scalar fields that contribute to the Hawking radiation. Moreover, it was shown that with large number of scalar fields, the black hole complementarity can be violated even for a Schwarzschild black hole . The number of scalar fields required can be reduced to a reasonable one, if we consider the scrambling time . The asymptotic observer and the in-falling observer can communicate with each other inside the black hole and hence the black hole complementarity seems to be inconsistent.\n\nFurthermore, in a recent work, Almheiri, Marolf, Polchinski and Sully (AMPS) have discussed for the inconsistency of black hole complementarity from a different ground. They were able to show that a quantum state, that satisfies classical general relativity for an in-falling observer and that satisfies the unitary quantum field theory for an asymptotic observer, cannot be consistent at the same time. Therefore, it seems that black hole complementarity is inconsistent not only inside, but also outside the black hole. To be in live with the original philosophy of black hole complementarity, AMPS suggested the firewall proposal. There are some interesting controversy regarding the firewall proposal in the literature [15, 16, 17, 18, 19, 20, 21, 22].\n\nIn this context, we suggest an interesting toy model for gedanken experiments. We consider a gravitational collapse with a false vacuum lump. This particular example draws inspiration from regular black hole models [8, 23], although it does not necessarily be regular (free from singularity) for our purposes. This model is of interest, since the singularity and horizon structures are non-trivial. We want to address questions like how to define the duplication experiment, how to define the firewall, and whether the firewall can rescue the black hole complementarity prinicple even for this complicated case.\n\nIn Section 2, we present a concise summary of the black hole information loss problem, motivations and assumptions guiding black hole complementarity and the duplication experiment. In addition, we discuss two important inconsistency arguments for black hole complementarity: large rescaling and the AMPS argument . In Section 3, we discuss the gravitational collapse with a false vacuum lump, using the double-null numerical simulations [9, 24, 25, 26]. We analyze the details of the causal structure and discuss some thought experiments relating to black hole complementarity and the firewall proposal. Finally, in Section 4, we summarize and interpret our results.\n\n## 2 Black hole information loss problem\n\nIn this section, we first discuss why does people argue for black hole complementarity. This is related to the analysis of black hole entropy and information. We clarify all the assumptions of black hole complementarity and the consistency check via the duplication experiment. Second, we discuss two counter arguments for black hole complementarity: large rescaling and the AMPS argument. In addition, we discuss the resolution of the AMPS proposed, so-called firewalls and summarize the recent status of the subject.\n\n### 2.1 Why black hole complementarity?\n\n#### 2.1.1 Entropy of black holes\n\nThe most remarkable issue in the information loss problem is the entropy of black holes. From the classical point of view, a black hole obeys laws of thermodynamics. From the first law of black hole thermodynamics and the area law , Bekenstein thought that the horizon area is proportional to the thermal entropy of a black hole . The temperature formula results from the quantum effects around the horizon . This entropy is thermal entropy, because for the computation temperature was calculated first and then the entropy was defined as , where is the difference of heat. The natural question to ask is whether this thermal entropy can also be treated as the statistical entropy, , where is the number of accessible states.\n\nString theorists believe that the entropy is not only of thermal nature but also has statistical origin. Some string theorists have found the dual of a black hole using D-brane combinations . It is also known that for certain black holes in the extremal limits with supersymmetry, the entropy obtained in the weak coupling limit is the same as that obtained in the strong coupling limit . The entropy could be exactly matched with the entropy formula obtained for some other extreme cases.\n\nTherefore, although there is no formal proof of the thermal and statistical entropy relation,\n\n A4=logΩ, (1)\n\nwe will accept this master formula and will try to find out the consequences.\n\n#### 2.1.2 Information emission from black holes\n\nLet us specify the information emission from a black hole [31, 32]. Let us consider a system with number of degrees of freedom and divide it into two subsystems, (inside region of the black hole) and (outside region of the black hole), where the number of degrees of freedom of is and that of is . Note that and can vary with time, although should remain conserved. We can think that initially and as time goes on, decreases and increases simultaneously to keep fixed.\n\nHere, the mutual information contained in and , that is, the information that both and share, or in other words, information of that can be seen by is , where is the statistical entropy of and is the entanglement entropy that is defined by the formula:\n\n ρB ≡ trAρ, (2) S(B|A) = −trρBlogρB, (3)\n\nwhere is the density matrix of the total system. In many contexts, people call or the coarse-grained entropy of and , while or are known as the fine-grained entropy between and .\n\nWe can further proceed by assuming that the system under consideration is pure and random. Page conjectured the following formula in and afterwards it was proven in : if , then\n\n S(B|A) = mn∑k=n+11k−m−12n (4) ≅ logm−m2n. (5)\n\nInitially, the information emitted is , and therefore is negligible. If , since for a pure state, one gets\n\n S(B|A) = mn∑k=m+11k−n−12m (6) ≅ logn−n2m. (7)\n\nThus, after becomes greater than , the information emitted is given by , and then it gradually increases (Figure 1).\n\nIn conclusion, the system begins to emit information to when its coarse-grained entropy decreases to the half value (). Before this time, emitted particles may not contain sufficient information. However, after that time, the original information cannot be compressed within only and the information possessed by has to be transferred to by means of the emitted particles.",
null,
"Figure 1: Emission of information, where f is the ratio of the escaped coarse-grained entropy to the original coarse-grained entropy.\n\n#### 2.1.3 Assumptions\n\nLet us assume the following:\n\nAssumption . Unitarity:\n\nThe black hole dynamics is unitary for an asymptotic observer.\n\nAssumption . Entropy:\n\n, where is the area of the black hole and is the number of accessible states.\n\nAssumption . Existence of an observer:\n\nThere is an observer who can read off information from the black hole.\n\nWe further assume the reliability of local quantum field theory and general relativity as methodological tools adopted:\n\nAssumption . For asymptotic observer:\n\nThe semi-classical method is a reliable description for an asymptotic observer.\n\nAssumption . For in-falling observer:\n\nGeneral relativity is a good prescription for an in-falling observer.\n\nIf we assume the results of the previous two subsections (Assumption and Assumption ) so that and a black hole begins to emit information when , then we conclude that the black hole begins to emit information when the area of the black hole decreases to half of its initial area. This time scale is of the order of the lifetime of a black hole and is called the information retention time . There are many There are many instances when the black hole can be treated in a semi-classical way, i.e., although the area of the black hole decreased to half of its initial value, the black hole is still large enough. Then, the only way to take out information from the large black hole is with the aid of Hawking radiation. Therefore, information should be emitted through Hawking radiation.\n\n#### 2.1.4 Duplication experiment and black hole complementarity\n\nLet us think of a specific situation (Figure 2) and consider a series of experiments in which a pair of correlated spins are simulated outside the event horizon. One of the pair that falls into the black hole is denoted by and the other pair that remains outside the black hole is . If Hawking radiation contains information, then information about can be emitted through Hawking radiation and we call it . According to Assumption , if there is an observer who can measure the state of , falls into the black hole, and measures the state of , eventually we will know that the collected information and are both correlated to . This implies that the observer sees a duplication of states, which is no allowed by quantum mechanics. We will call this type of experiment a duplication experiment.",
null,
"Figure 2: The duplication experiment. a and b are a pair of correlated spins. The observer sees h which is a copy of a, after the information retention time via Hawking radiation. a should be sent to the out-going direction after the time Δt in order to be observed. If the observer sees both a and h, since they are both correlated to b, it violates the no-cloning theorem and unitarity.\n\nSusskind and Thorlacius were able to answer several important questions related to the duplication experiment. If the observer sees both and , he/she has to wait until the completion of the information retention time. However, if the original free-falling information reaches the singularity of the black hole, then there is no chance to see the duplication. In order to be able to see the duplication, the free-falling information should be sent to the out-going direction during the time interval .\n\nWe can estimate the time interval in the Schwarzschild space-time:\n\n ds2=−(1−2Mr)dt2+(1−2Mr)−1dr2+r2dΩ2. (8)\n\nThe horizon is located at and the Hawking temperature is of the order . Therefore, the lifetime .\n\nFor the next calculation, we will begin by making a comment on a simple extension to Kruskal-Szekeres coordinates [7, 35]. We can neglect the angular part without loss of generality and assume the form of the metric to be\n\n ds2=F(R)(−R2dω2+dR2). (9)\n\nTo compare with the original metric, the following definitions are made:\n\n dω2 = dt2r2h, (10) R2F(R) = r2h(1−2Mr), (11) F(R)dR2 = (1−2Mr)−1dr2. (12)\n\nIn terms of the coordinate , the singularity occurs at ; and the horizon is located at . Now, we can choose another metric and coordinate as follows:\n\n V = Reω, (13) U = −Re−ω, (14) ds2 = −F(R)dUdV. (15)\n\nHere, the singularity is located at .\n\nWe can restate the condition for a duplication experiment in a Schwarzschild black hole. The first observer falls into a black hole and sends a signal to the out-going direction in time interval . Now assume that a second observer hovers around the horizon at a distance of the order of the Planck length () and jumps into the black hole at the information retention time which is of the order of . Then, the initial location of the second observer is , where and .444Here, is a length scale that is relevant for the Kruskal-Szekeres coordinates. For a precise calculation of , we need to calculate from and . We will not do the detailed calculation, but it is sufficient to notice that . Before reaching the singularity, the second observer will spend time (in terms of ) around since the singularity is reached where . Therefore, the first observer should send a signal around the time . Hence, the duplication may be possible if one can send a signal between the time\n\n Δt∼M2R0exp−τrh, (16)\n\nwhere is the information retention time.\n\nThen, to send a quantum bit during the time interval , it has to satisfy the uncertainty relation . The required energy to send a quantum bit of information in is , which is greater than the original mass of the black hole . Therefore, the duplication experiment seems to be improbable in real situations .\n\nAccording to Susskind and Thorlacius, although information is duplicated, there seems to be no problem if no observer can see the violation of the natural laws. In other words, there is no global description both for an in-falling observer and an asymptotic observer at the same time. We have to choose one of them. In this sense, two observers are complementary. This principle is known as black hole complementarity or observer complementarity .\n\nBlack hole complementarity is consistent with two paradigms: the membrane paradigm and the D-brane picture . In membrane paradigm, a black hole has a membrane around the event horizon, the so-called stretched horizon. If we send an object into a black hole, the object is stretched and scrambled on the horizon. The outside observer cannot see the object disappearing beyond the horizon. Therefore, for an outside observer, information is located on the horizon and eventually escapes from the black hole via Hawking radiation. The scrambling occurs in the following order of time:\n\n τscr∼βMlogM, (17)\n\nand this is called the scrambling time. In this paper, we write a coefficient factor explicitly for further clarity, where it should be order one and can vary in realistic situations, since the scrambling is a statistical behavior. According to Hayden and Preskill , after a black hole approaches the information retention time, if one sends small bits of information, this will quickly escape from the black hole after the scrambling time. Note that although we consider the scrambling time, the consistency relation still holds: from Equation (16), we find that in order to see the duplication, . Therefore, people believed that black hole complementarity is marginally true, even with the scrambling time.\n\n### 2.2 Inconsistency of ‘old’ black hole complementarity\n\nNow we will introduce two important arguments against the original version of black hole complementarity. One is the so-called large rescaling and the other is the AMPS argument .\n\n#### 2.2.1 Large N rescaling\n\nLet us assume that and remains explicitly. Then, length, mass, and time dimensions are the same. In this subsection, we will change the number of massless scalar fields and hence we will scale the strength of the Hawking radiation. We assume that there is one scalar field that contributes to the formation of a black hole; the other number of fields are not used to form the black hole, and they only contribute to the Hawking radiation.\n\nFirst, let us assume . Then the semi-classical equations of motions (up to order ) are as follows:\n\n Gμν = 8π(Tμν+ℏ⟨Tμν⟩), (18) ϕ;abgab = 0, (19)\n\nwhere is a scalar field used to form a black hole.\n\nNow we define the re-scaling with the following rule: if a quantity which does not explicitly depend on has a dimension with a certain number , we define a rescaled as\n\n X′=√NαX. (20)\n\nThen, we claim that after rescaling all possible quantities, they are solutions of the following equation:\n\n G′μν = 8π(T′μν+Nℏ⟨T′μν⟩), (21) ϕ′;abg′ab = 0. (22)\n\nThis is easy to check: has a dimension of , also has a dimension of , and has a dimension in the one-loop order. Hence, , , and . Then,\n\n Gμν=NG′μν=8π(Tμν+ℏ⟨Tμν⟩)=8π(NT′μν+ℏN2⟨T′μν⟩), (23)\n\nand thus our claim is correct. Also, it is easy to check the same relation for the Klein-Gordon equation for a scalar field .\n\nIn conclusion, for any given quantities which are solutions of Equation (18), the corresponding rescaled quantities are the solutions of Equation (21) with massless fields. Three important remarks regarding the large rescaling are as follows.\n\nConformal invariance of the causal structure:\n\nThe rescaling conserves the very causal structure of the metric since it scales the unit length and the unit time in the same way. Therefore, we can use the same Penrose diagram for the case.\n\nSemi-classicality:\n\nIf we can simulate a sufficiently large universe, even if a region has a large curvature in the case (in Planck units), we can find a universe where the curvature can be rescaled to a sufficiently smaller value (in Planck units). Therefore, large rescaling makes results trustable in the semi-classical sense.\n\nGeneralization to other matter fields:\n\nWe can generalize to include more complicated matter fields: e.g., complex scalar field, complicated potential, etc. For these cases, we have to rescale coupling constants when we vary the number of scalar fields. As long as the coupling constants are free parameters of the theory, it is always allowed in principle.\n\nLet us apply the large rescaling to the information retention time and the scrambling time.\n\n– Information retention time:\n\nWe rescale all length, mass, and time parameters by . Now, the information retention time for mass and the single scalar field is rescaled to for mass where is a certain number and\n\n τ ∼ M3, (24) τ′ ∼ M′3N=(√NM)3N=√NM3. (25)\n\nNow, we have to divide the lifetime by , since there are -independent fields that contribute to the Hawking radiation. Note that the size will be rescaled to . Therefore, under large rescaling, the ratio between the temporal size and the spatial size remains invariant:\n\n τrh=τ′r′h. (26)\n\nNote that, although is invariant under the large rescaling, each conformally equivalent distances should be stretched with factor. Therefore, in general, in limit, the duplication may be observed if one can send a signal between the time interval , where is the information retention time (). On the other hand, in the large rescaled case,\n\n Δt′∼√N(M2R0)exp−τ′r′h∼√NΔt. (27)\n\nNote that has a length dimension and hence we add only for the rescaling. From the uncertainty relation, the energy required is\n\n ΔE′∼1√N(R0M2)expτM, (28)\n\nand since the consistency of complementarity requires , the consistency condition turns out to be\n\n expM2>NM3R0. (29)\n\nThis condition can be violated by assuming to be sufficiently large of the order [8, 9, 10].\n\n– Scrambling time:\n\nThe scrambling time is , where is the entropy of the black hole . In fact, the rescaling is done for , and it turns out to be . Thus, in a large universe, the time scale becomes\n\n Δt′∼√N(M2R0)exp(−βMlog√NMM)∼√N(M2R0)exp(−βlog√NM). (30)\n\nFrom the uncertainty relation, the energy required is\n\n ΔE′∼1√N(R0M2)(√NM)β. (31)\n\nDue to the consistency of complementarity , and hence the consistency condition becomes\n\n (R0M2)Mβ−1>√NN(1−β)/2. (32)\n\nAs we noted, the scrambling time is the statistical notion. After the order of the scrambling time, information comes out; but the details of the time can be different case by case. Only the statistical average of the time for various situations follows . Therefore, if this inequality is violated for , then this is sufficient to show the inconsistency of black hole complementarity. The condition is\n\n (R0M2)<√N. (33)\n\nHere, we can see that this inequality can hold by assuming a sufficiently large [8, 12].555In literature , people approximately assume the pre-exponential factor as one; and then the scrambling time seems to be marginal for this inequality. However, here we introduce the pre-exponential factor and large rescaling at the same time and hence the violation of the consistency condition is clearer.\n\nIn this sense, the black hole complementarity principle can be violated even if we consider a Schwarzschild black hole. The number of scalar fields required can be made sufficiently small, if we consider the scrambling time.\n\nEven in the case when we do not consider the scrambling time and only consider the information retention time, still we find that black hole complementarity is inconsistent. Although the required number of scalar fields is exponentially large, it is still not infinite and hence is allowed by string theory in principle . There are some typical doubts due to our misunderstanding of the large rescaling and these issues can be answered as follows:\n\n1. People think that large induces strong Hawking radiation and hence the black hole evaporates too quickly and hence cannot be thought of as a semi-classical object . However, this is not true. We not only increase the strength of the Hawking radiation, but also the size of the black hole at the same time. Dvali suggested that a semi-classical black hole should be larger than : in other words, . In our discussions, and, by the rescaling argument, always holds. Therefore, in the large limit, the back-reactions from Hawking radiation decrease and the lifetime of the black hole increases.\n\n2. People also worry the higher order quantum corrections while including large number of scalar fields. This is a natural concern, but our focal attention is not on an general gravitational system, but a very special one that can be allowed in principle. So, the real puzzle stems from the fact whether the large inevitably require strong quantum correction effects or not. The answer to the question is ‘it may not be’, in principle. First of all, the curvature corrections will be suppressed due to rescaling. Second, higher loop corrections of the matter fields depend on their couplings. If we assume that scalar fields are independent of each other, then the higher order terms will be reasonably suppressed, as they are proportional to , while this in fact is sufficiently smaller compared to the term . If this assumption is in principle possible, then it is a good playground to test the consistency of black hole complementarity, unless we find a fundamental limitation of this assumption.\n\n#### 2.2.2 Duplication experiment outside the event horizon",
null,
"Figure 3: The duplication experiment conducted outside the event horizon. a is in-going information and a signal is being sent to the out-going direction. This can be both inside and outside of the event horizon. To see a inside the event horizon, a should be sent to an out-going direction after time Δt, while to see it outside the event horizon, a should be sent after time ΔU.\n\nTill now, we have ignored the contribution of the subexponential factor of . Note that for an evaporating black hole, the apparent horizon is located outside the event horizon. Therefore, the duplication experiment can be conducted not only inside but also outside the event horizon. To see the duplication outside the black hole, the in-falling information should be sent to an out-going direction between the new time interval . In general, we expect , and the difference comes into effect due to the subexponential factor.\n\nLet us discuss the details now. Let us assume that the black hole mass is initially and as time goes on, it shrinks to after a time scale . Now let us define a duplication observer who maintains its radius around until the time and eventually falls to (still outside the apparent horizon) along the in-going null direction in time .\n\nThen, we should calculate the difference of the coordinate between the two points and (Figure 3). The coordinate is approximately the same: for both the points. In addition, the coordinates are\n\n R=M(r−2M2M)1/2expr4M (34)\n\nby using a simple coordinate transformation. Therefore, and hence approximately given by\n\n ΔU≃√M2ΔMexp−τr2, (35)\n\nwhere is mass decreased due to the evaporation during time .\n\nNote that, in Equation (16), we have omitted the subexponential factor where the factor is approximately . Of course, in principle we can restore it back and compare with the sub-exponential factor of Equation (35) and in general the latter is shorter than the former as\n\n ΔUΔt≃√M2ΔMM22/R0≪1. (36)\n\nTherefore, it is easier to see the duplication not outside but inside of the black hole. However, the duplication experiment is dominated by the exponential factor and two time scales share the same exponential factor. Hence, required for a successful duplication experiment is similar for both the cases.\n\n– Outside the event horizon considering the information retention time:\n\nHere,\n\n ΔM=M1−M2≃(√2−1)M2. (37)\n\nTherefore, using the same argument as that of the previous subsection, the duplication experiment is possible even outside the event horizon, as long as scalar fields are possible to be taken into account.\n\n– Outside the event horizon considering the scrambling time:\n\nWith the scrambling time, we can also define a duplication experiment outside the event horizon. Here, . After large rescaling and applying the uncertainty relation, the required energy is\n\n ΔE′∼1√logM21√Nexplogβ√NM2. (38)\n\nThe duplication experiment is possible even outside the event horizon, if and hence\n\n N2−β>Mβ−12logM2. (39)\n\nAgain, for , we see that the duplication observation requires a reasonable number of scalar fields666Up to now, we think that the consistency condition is . However, in practice, we cannot use all the energy to send a signal and there can be a certain limitation: we can use at most amount of energy to send a signal, where . Then required becomes for outside the horizon (by choosing ). This implies that required can be greater than one. However, it is also true that such a required number can be still reasonably small.:\n\n N>1logM2. (40)\n\nIn conclusion, if there are sufficiently large number of scalar fields, then the duplication experiment is possible not only inside but also outside the event horizon. Therefore, to prevent such a duplication experiment, the in-going observer should be killed very near the apparent horizon, rather than the event horizon after a certain time scale (information retention time or scrambling time). This gives us a hunch on the location of the firewall, which we will discuss in the next subsection.\n\n#### 2.2.3 AMPS argument and the firewall controversy\n\nRecently, Almheiri, Marolf, Polchinski, and Sully suggested that the assumptions of black hole complementarity are inconsistent using other arguments. Let us define two sets of quantum operators of the matter fields: for the initial state , and for the final state , . According to Assumption , the information regarding the collapse will be described by the ground state . As far as, Assumptions , and , after the information retention time, even if we put a small information, that will be emitted through Hawking radiation after the scrambling time. From Assumption , there is a unitary and semi-classical description between the initial and the final state given by\n\n b=∫∞0(B(ω)aω+C(ω)a†ω)dω. (41)\n\nIn addition, according to Assumption , an asymptotic observer can measure particles into an eigenstate of . Note that the full state cannot be both and at the same time the eigenstate of . This is a contradiction.\n\nTo resolve this contradiction, they suggested two alternatives. One is to drop Assumption so that the in-falling observer watches a sudden change (violation of the equivalence principle); they assumed that there is a firewall near the horizon for an in-falling observer. The other is to drop Assumption so that the asymptotic observer sees a radical non-local effects.\n\nHere, we briefly summarize the discussions on the firewall proposal:\n\nIt’s inconsistent, so what?:\n\nBousso argued that AMPS clearly shows the potential inconsistency of the black hole complementarity. However, this is not a problem, since the inconsistency cannot be observed in principle777Recently, Bousso changed his opinion in the second version of , while this paragraph follows the first version of the paper.. To notice the inconsistency, one has to compare the in-falling and the asymptotic observer. However, the communication is impossible. Therefore, although it is apparently inconsistent, we do not have to modify the black hole complementarity. This interpretation is consistent with Nomura, Varela and Weinberg and Banks and Fischler , in the sense that the in-falling observer and the asymptotic observer correspond to different detectors and hence cannot be compared in a naive way. Black hole complementarity is for the whole quantum states, while an in-falling observer and an asymptotic observer are only parts of the whole quantum states. Therefore, the comparison between the two observers are not well-defined.\n\nThese kind of arguments relies heavily on the fact that two observers – asymptotic and in-falling – cannot communicate in the semi-classical sense. However, this is not true. Large rescaling shows that they can communicate with each other even in a semi-classical sense. Therefore, we cannot simply avoid the potential inconsistency and one has to see what happens when two observers meet. In this sense, we think that this opinion cannot really help to unveil the problem of black hole complementarity.\n\nThe fuzzball and approximate complementarity:\n\nMathur and Turton and Chowdhury and Puhm tried to connect the firewall argument with the fuzzball conjecture. If the energy scale of a probe is smaller or similar order with the Hawking temperature, then the probe sees a fuzzball and it is approximately a realization of the firewall. However, if the energy scale of the probe is much larger than that of the Hawking temperature, then the probe can free-fall into the black hole; the probe satisfies the equivalence principle. They called this phenomenon approximate complementarity.\n\nHowever, there still remain some questions. If a free-fall is allowed, then large rescaling makes the duplication experiment to be possible. Up to now, it seems unclear how does the fuzzball argument prevent this possibility. One important remark is that one can distinguish a fuzzball in the macroscopic scales . Therefore, if the fuzzball conjecture is in general true, then it not only modifies Assumption , but also Assumption .\n\nThe firewall is a new singularity:\n\nSusskind remarked that if there is a firewall, then it should be regarded as a new type of singularity. The entanglement of a black hole with the Hawking radiation causes the singularity to migrate toward the horizon and eventually intersect it at the information retention time. Therefore, we have to consider the singular horizons – firewall – after the information retention time. In addition, after the information retention time, if some information falls into the black hole, then the horizon increases along the space-like direction and eventually becomes singular after the scrambling time.\n\nThis interpretation is worthwhile to discuss further. We will comment on this in the next subsection.\n\nThe semi-classical point of view:\n\nOri thinks that it is not inconsistent to extend the semi-classical quantum field theory beyond the event horizon. In other words, what he means is that there is no good justification to believe in the existence of a firewall. Therefore, if we accept that there is no firewall and black hole complementarity is not true, then the next possible choice is to consider the regular black hole/remnant picture or the baby universe scenario. This conclusion was also made by the authors and probably also by a number of general relativists.",
null,
"Figure 4: Left: The signal from the firewall (thick red arrow) kills the in-falling information. However, it does not affect outside as the effects (red dotted arrow) is screened by the apparent horizon. Right: If the apparent horizon is disconnected, then there is no screen such that the effects (red dotted arrow) can modify the asymptotic infinity.\n\n#### 2.2.4 Is the firewall-singularity consistent?\n\nLet us extend the discussion of . We require the following two conditions for a firewall:\n\n1. It should prevent the duplication experiment.\n\n2. We do not want to modify the macroscopic scale (asymptotic) semi-classical theory.\n\nAs we observed in the previous subsections, the duplication experiment can be done outside the event horizon by assuming a reasonable number of scalar fields. Therefore, to prevent the duplication experiment, the firewall should be outside the event horizon. Then, the reasonable place of the firewall will be close to the time-like apparent horizon . However, due to the second condition, the time-like object should not affect the future infinity. Now, the question is whether it is indeed consistent.\n\nOf course, it is natural to think that the time-like firewall should affect the future infinity, since it is outside the event horizon. However, in this paper, we try to maintain the original motivation of the firewall proposal to study the consistency of the firewall proposal. Then, what should we assume? If one wants to hold the conservative point of view so that one believes the firewall does not affect the future infinity, then we must require these two properties at the same time: (1) the firewall sends signals along the in-going direction to kill the in-falling information (thick arrow on the left of Figure 4) and (2) although there is a bouncing effect along the out-going direction, the apparent horizon should work as a screen to any out-going effect from the firewall (dotted arrow on the left of Figure 4).\n\nIn this paper, we will eventually conclude as follows: even though we further assert the previous two assumptions, we cannot prevent to affect the future infinity. These properties can be falsified if the apparent horizon is separated (the right of Figure 4). Then the apparent horizon cannot screen out the out-going effects. Or, we can say that, the firewall becomes a naked singularity. In any case, the firewall should affect the future infinity. In the next section, we will realize such separated horizons.\n\n## 3 Gravitational collapse with a false vacuum lump\n\nIn this section, we want to discuss a gravitational collapse with a false vacuum lump. This is motivated by regular black hole models, but it does not necessarily have to be regular. We calculate this using the double-null formalism and numerical implementations. After we specify the causal structures, we will discuss gedanken experiments on black hole complementarity and the firewall proposal.\n\n### 3.1 Model\n\n#### 3.1.1 Regular black hole models\n\nRegular black holes are introduced to explain the problem of singularity arising in black holes. According to the singularity theorem, if we assume the following three things and general relativity, we cannot avoid the existence of a singularity : (1) global hyperbolicity, (2) the null energy condition and (3) the existence of a trapped surface.\n\nIn order to define a black hole, we cannot avoid the last assumption, the existence of a trapped surface. Therefore, one may choose from the following possibilities : (1) modify general relativity around the singularity, (2) violate the global hyperbolicity and introduce a Cauchy horizon or (3) violate the null energy condition.\n\nModification of general relativity:\n\nAround the singularity, general relativity should be radically modified. One possibility is to consider the spacetime to be fuzzy and not well-defined. The other possibility is to choose a good metric ansatz, although the metric should be affected by some quantum gravitational corrections. However, it crucially depends on the details of the quantum gravity theory.\n\nViolation of the global hyperbolicity:\n\nOne may assume that a black hole solution is the same as the Schwarzschild solution for large (or any known static solution), while there is a non-trivial matter core inside the black hole. In general, the matter core collapses to form a singularity. However, if the formation of the singularity can be postponed and an inner horizon appears, then one may construct a regular solution, without violating the null energy condition. However, these models typically have an inner horizon and these inner horizons are Cauchy horizons in the static limit. Therefore, the global hyperbolicity is violated.\n\nIn general, if there is a Cauchy horizon, mass inflation is inevitable . Then, even in the absence of a central strong singularity, a curvature singularity (with non-zero area) can be formed. Therefore, the resolution of mass inflation is again required.\n\nViolation of the null energy condition:\n\nIf we assume a certain amount of matter that violates the null energy condition, then it is not quite difficult to find a regular black hole solution, since the formation of a singularity can be postponed by matter fields. The problem is the origin of matter. One may assume phantom matter which is not ruled out by cosmological observations. One trivial example that realizes phantom matter is a ghost field.\n\nOne problem is that a ghost field makes the field theory unstable. Therefore, it is fair to say that observations cannot rule out the existence of phantom/ghost-like matter; also, there is no observational justification in favor of the use of phantom/ghost matter. On the other hand, if a false vacuum bubble can emit negative energy flux, then it can form a negative energy bath , although this particular process requires many assumptions.\n\n#### 3.1.2 Justification of the physical possibility\n\nIn spite of the potential problems, in this paper, we introduce a regular black hole model. Let us first comment on the static solution of Frolov, Markov, and Mukhanov . The metric and the energy-momentum tensor of the shell are as follows:\n\n ds2=−(1−2m(r,l)r)dt2+(1−2m(r,l)r)−1dr2+r2dΩ2, (42)\n\nwhere , is the Hubble scale parameter, and is the radius of the false vacuum boundary (we can choose the value of as a free parameter). Then, one can easily check that (if we choose ) the metric has the outer () and the inner horizon () and usually holds true as long as . If , the metric is exactly the same as the de Sitter space. Otherwise, it exactly resembles a Schwarzschild black hole. We can calculate the proper shell condition :\n\n Sμν=diag(λ4π,0,κ+λ8π,κ+λ8π), (43)\n\nwhere\n\n κ = (44) λ = 1r0[(r0l)2−1]1/2−1r0[2mr0−1]1/2. (45)\n\nThis regular black hole model is free from any singularity since it violates the global hyperbolicity. So, it may suffer from mass inflation. This model assumes a thin-shell that mediates the inside false vacuum region and the outside true vacuum region, and the shell is space-like. We can prove that the space-like shell is stable under small perturbation . As long as the shell is stable, we can construct a reasonable causal structure as the black hole forms and evaporates [42, 8].\n\nHowever, for realistic applications, it may pose some problems:\n\n1. Initially, this model requires a false vacuum lump. Can it be generated by quantum tunneling?\n\n2. Initially, the shell of the false vacuum lump is time-like. After the shell is trapped by an apparent horizon, it becomes space-like. How can this be dynamically possible?\n\n3. Although a stationary solution is obtained, will the internal structure be stable, even in the presence of mass inflation?\n\nHowever, we think that our numerical study is still viable, even though there are some potential problems. In this paper, we do not want to remove all the singularities. Rather, we want to postpone the formation of the singularity. For a deeper inside region, we infer that a singularity will be formed. Our purpose is to modify the horizon dynamics using false vacuum bubbles. From this stance, each problem encountered above can be relaxed in the following ways:\n\n1. Quantum fluctuations can generate a false vacuum lump during a short time . Also, there is a consensus that a buildable bubble can be generated by unitary processes (although we cannot construct instantons) . Moreover, there is an instanton solution of a small false vacuum bubble in modified gravity . Therefore, the assumption made in order to have a false vacuum bubble should be in principle allowed.\n\n2. The thin-shell dynamics can be questionable, whether it is time-like or space-like. However, by using numerical techniques , we can see clear dynamics of the thick bubble walls.\n\n3. There will be mass inflation. However, we can postpone the curvature cutoff for mass inflation, by assuming sufficiently large number of scalar fields. Therefore, our analysis around the apparent horizon always makes sense.\n\n### 3.2 Numerical setup\n\nIn this subsection, we will discuss a numerical model that mimics that of Frolov, Markov, and Mukhanov.\n\n#### 3.2.1 Double-null formalism\n\nWe describe a Lagrangian with scalar fields , , and the potential :\n\n L=−12Φ;aΦ;bgab−V(Φ)−12ϕ;aϕ;bgab, (46)\n\nwhere is used to make a false vacuum bubble and is used to make a black hole. From this Lagrangian we can derive the equations of motion for the scalar field as:\n\n Φ;abgab−V′(Φ) = 0, (47) ϕ;abgab = 0. (48)\n\nIn addition, the energy-momentum tensor becomes\n\n Tab=Φ;aΦ;b−12gab(Φ;cΦ;dgcd+2V(Φ))+ϕ;aϕ;b−12gabϕ;cϕ;dgcd. (49)\n\nNow, we will describe our numerical setup. We start from the double-null coordinates (our convention is ),\n\n ds2=−α2(u,v)dudv+r2(u,v)dΩ2, (50)\n\nassuming spherical symmetry. Here is the ingoing null direction and is the outgoing null direction.\n\nWe define the main functions as follows [9, 25, 26]: the metric function , the area function , and the scalar fields and . We also use the following conventions: , , , , , , , .\n\nFrom the above setup, the following components can be calculated:\n\n Guu = −2r(f,u−2fh), (51) Guv = 12r2(4rf,v+α2+4fg), (52) Gvv = −2r(g,v−2gd), (53) Gθθ = −4r2α2(d,u+f,vr), (54)\n Tuu = 14π(W2+w2), (55) Tuv = α22V(S), (56) Tvv = 14π(Z2+z2), (57) Tθθ = r22πα2(WZ+wz)−r2V(S), (58)\n\nwhere\n\n V(S)=V(Φ)|Φ=S/√4π. (59)\n\nFrom the equations of motion of the scalar fields, we get the following conditions:\n\n rZ,u+fZ+gW+πα2rV′(S) = 0, (60) rz,u+fz+gw = 0. (61)\n\nNote that, .\n\nWe also consider renormalized energy-momentum tensors to include the semiclassical effects. The spherical symmetry makes it reasonable to use the -dimensional results [47, 48] divided by [9, 24, 25, 26]:\n\n ⟨^Tuu⟩ = P4πr2(h,u−h2), (62) ⟨^Tuv⟩=⟨^Tvu⟩ = −P4πr2d,u, (63) ⟨^Tvv⟩ = P4πr2(d,v−d2), (64)\n\nwith , where is the number of massless scalar fields and is the Planck length. We use the semi-classical Einstein equation,\n\n Gμν=8π(Tμν+⟨^Tμν⟩). (65)\n\nFinally, we summarize our simulation equations:\n\n1. Einstein equations:\n\n d,u=h,v = 11−Pr2[fgr2+α24r2−(WZ+wz)], (66) g,v = 2dg−r(Z2+z2)−Pr(d,v−d2), (67) g,u=f,v = −fgr−α24r+2πα2rV(S)−Prd,u, (68) f,u = 2fh−r(W2+w2)−Pr(h,u−h2). (69)\n2. Scalar field equations:\n\n Z,u=W,v = −fZr−gWr−πα2V′(S), (70) z,u=w,v = −fzr−gwr. (71)\n\n#### 3.2.2 Initial conditions and integration schemes\n\nWe prepare a false vacuum bubble along the initial ingoing surface. We need initial conditions for each function on initial and surfaces. There are two kinds of information: geometry () and matter ().\n\nOn the geometry side, we have the gauge freedom to choose the initial function and integrate using equations. We choose and . is related to the mass function: . For a fixed , , and , to satisfy , is determined automatically.\n\nOn the matter side, we fix and\n\n s(ui,v)=Asin2(πv−viδv) (72)\n\nfor and otherwise . Then, one can calculate , , , and ; in addition, and are obtained using the equation for . Additionally, we fix and\n\n S(u,vi)=⎧⎪ ⎪ ⎪⎨⎪ ⎪ ⎪⎩0u\n\nThen, one can calculate , , , and ; in addition, and is obtained using the equation for . The potential is free to choose and we fix a simple form:\n\n V(S)=Vfv[B(SΔ)4−2(B+1)(SΔ)3+(B+3)(SΔ)2], (74)\n\nso that it has the true vacuum at and while it has the false vacuum at and .\n\nThen, as one fixes and for initial surfaces, one can obtain and by integrating Einstein equations. And, finally, can be obtained by integrating and . This finishes the assignments of the initial conditions. We observed the convergence and the consistency of the simulations in Appendix. Here, we used the 2nd order Runge-Kutta method .\n\nWe fix the free parameters as follows: , , , , , , , , . The only remaining parameter to be fixed is the field value of the false vacuum . Of course, in general, the other parameters are free to be chosen as one likes, in principle.\n\n### 3.3 Causal structure",
null,
"Figure 5: General global structure of a gravitational collapse in the presence of a false vacuum bubble. Here, Δ=0.07. Color denotes the field value S and red curves denote the apparent horizons.",
null,
"Figure 6: Left: The causal structure of an evaporating neutral black hole. Right: An out-going false vacuum bubble changes the singularity structure. Red curve denotes an apparent horizon, blue curve is an event horizon, yellow region is a shell, red region depicts a false vacuum region, and dashed rectangular region is the integration domain of our simulations.\n\nFigures 5 and 6 represent a general global causal structure of the gravitational collapse with a false vacuum bubble. It is interesting to note that this causal structure is qualitatively same as the causal structure found in . There are few remarkable structures. First, there appears a closed trapped region: the outer part being an outer apparent horizon and the inner part being an inner apparent horizon. Two horizons emerge at a certain crossing point. The crossing point appears since the false vacuum shell crosses there. The out-going false vacuum shell eventually turns back to the in-going direction and we call this bouncing point. Before a bouncing point appears, there can be an apparent horizon inside the false vacuum region. If the final black hole mass is order of , then the apparent horizon inside the false vacuum region is of the order of and it swallows the shell mass later. Therefore, the approximate difference in radius between a crossing point and the inside apparent horizon should be of the order of the false vacuum shell mass .\n\nNow we will discuss details of the crossing point and the bouncing point. First, Figure 7 compares two cases, black hole with and without a false vacuum bubble. For an evaporating black hole, one can relocate the crossing point to any place on the time-like horizon. This crossing point can be chosen around the information retention time, in principle. By tuning the initial location of the shell and the thickness of the shell (this should be sufficiently thin), one can shoot the out-going shell to hit the desired crossing point (Figure 7). For this, we require that the shell energy to be sufficiently large so that the bouncing point arises sufficiently far from the crossing point and the shell does not collapse before it reaches the crossing point. Figure 8 shows such a behavior; as the shell energy increases by tuning the field amplitude , the bouncing point shifts to the right side, while the crossing point is not significantly changed.\n\nIn summary, we have three free parameters that depends only on the potential and the initial conditions: , , and . First, we choose a specific crossing point (for our purposes, around the information retention time). Then, one can estimate the required and . However, these choices cannot make sure as the shell hits the crossing point if it can collapse too quickly. Now, we have to tune to set a proper tension of the shell so that the bouncing point arises sufficiently far from the desirable crossing point. In this limit, the shell energy is essentially determined in terms of and . It is easy to choose sufficiently large so that the distance between the crossing point and internal horizon structures becomes sufficiently large. Between the crossing point and the internal horizon structures, we do not have any evidence of mass inflation, although this can be observed from the deeper inside of an expanding false vacuum bubble.",
null,
"Figure 7: Construction of the crossing point. Black contours denote r and the difference between each contour is 0.01. Color denotes S. Left is the case where there is no false vacuum bubble and Right is the case when Δ=0.07.",
null,
"Figure 8: Shifting of the bouncing points. Black contours denote r and the difference between each contour is 0.01.\n\n### 3.4 Gedanken experiments\n\n#### 3.4.1 Duplication experiments\n\nIn this causal structure (Figure 6), the duplication experiment is well-defined and possible (Figure 9). We use the same convention that was used in Section 2. Here, we can assume that the crossing point is around the information retention time. To see the duplication, the message can be sent after and this can be reasonably large. If there is mass inflation, then this can be regularized by assuming a large number of scalar fields, although there is no numerical evidence of mass inflation.\n\n#### 3.4.2 Where is the firewall?\n\nTherefore, it is inevitable to introduce the firewall, if one wants to maintain the black hole complementarity. As was discussed in Section 2, the firewall should be located on the apparent horizon. Note that this situation is quite different from that of the Schwarzschild black hole, since the apparent horizon is disconnected. Figure 9 shows possible candidates for the firewall. If the firewall is on the internal horizon structures (Middle and Right of Figure 9), then it cannot resolve the problem of black hole complementarity. Therefore, it should be located on the outer apparent horizon after the information retention time. However, we know that the horizon suddenly disappears.\n\nHere, our first question is this: what will be observed by the in-falling duplication observer? The answer is simple. If the firewall can kill the message generated by , then the observer can notice the effect of the firewall and we infer that the firewall can affect the causal future of the spacetime.\n\nNote that obviously the firewall is situated outside the event horizon. If we accept that the firewall can affect the causal future, then the question that comes next is: does the firewall affect to the future infinity? If the apparent horizon is connected, then one can believe that any effect can be screened by the apparent horizon. However, if the apparent horizon is not connected, there is no consistent screen. It is fair to say that the firewall is now naked. Therefore, we conclude that the firewall should affect the asymptotic future infinity.",
null,
"Figure 9: Left: To resolve the inconsistency of the black hole complementarity, the firewall should exist on the outer apparent horizon. Middle and Right: If the firewall exists on some other place, then it cannot cure the inconsistency due to black hole complementarity.\n\nTherefore, it reveals a paradox if we assume the following two contents: the firewall should prevent the duplication experiment and should not affect the future infinity. From the former assumption, the firewall should be on the apparent horizon. Therefore, if the firewall is a kind of singularity, then it should be a time-like singularity, since the outer apparent horizon is time-like. If we consider the Schwarzschild black hole, one could ignore this problem, since the apparent horizon is connected, and hence the inside and the outside of the firewall is well-separated. However, if we consider disconnected apparent horizons, it is clear that one cannot ignore the effects due to the firewall along the out-going direction (Figure 4). This somehow requires quantum gravitational modification of the outside of a black hole. A firewall cannot prevent the modification of semi-classical quantum field theory.\n\n#### 3.4.3 Violation of cosmic censorship?\n\nFurthermore, now let us consider the situation when the crossing point is slightly before the information retention time (Figure 10). During the time evolution, the firewall grows and approaches the apparent horizon . We can tune this in such a way that the crossing point and the information retention time are quite close to each other so that the firewall can grow even outside the event horizon. Then, there is no way to screen the effect of the firewall-singularity. Again, the firewall cannot prevent the modification of the semi-classical quantum field theory for an asymptotic observer. Then, is it a kind of violation of strong cosmic censorship?",
null,
"Figure 10: If the crossing point is slightly before the information retention time, during this time, a firewall grows and approaches the apparent horizon. It is also possible that a firewall is outside the event horizon while the apparent horizon gets disappeared. Then the effect of the firewall should be observed by an asymptotic observer.\n\n#### 3.4.4 Conclusion\n\nIn conclusion, the firewall was originally a conservative way to maintain the black hole complementarity. To prevent the duplication experiment, the firewall should be very close to the apparent horizon, and hence, this should be outside the event horizon. We asked whether the firewall-singularity that is outside the event horizon must affect the future infinity or can be screened by the apparent horizon; the latter is a stronger assumption to help the original version of the firewall proposal. However, our numerical simulations reveal the fact that the firewall should affect the future infinity and asymptotic observer, even with our stronger assumption.\n\nTherefore, we give some possible interpretations:\n\n1. We can have more ad hoc assumptions in order to maintain the firewall idea – so that, we only modify Assumption . For example, the Horowitz-Maldacena proposal can be potentially relevant, although the idea in itself has other potential problems and can be falsified with large rescaling .\n\n2. We may accept that it is inevitable to assume macroscopic effects of quantum gravity, even for a semi-classical system (Assumption should be modified) . This possibility can be related to the fuzzball interpretation [17, 18, 20].\n\n3. We may think that one of the Assumptions , or should be modified .\n\n## 4 Discussion\n\nIn this paper, we have discussed the black hole complementarity, the firewall proposal, and related gedanken experiments.\n\nWe have illustrated five important assumptions: unitarity, entropy-area formula, existence of an information observer, semi-classical quantum field theory for an asymptotic observer, and general relativity for an in-falling observer. These five assumptions require a duplication of information around the event horizon and hence the black hole complementarity for consistency of the theory. However, if there is an observer who can see the duplication of information, then the black hole complementarity can be falsified.\n\nBlack hole complementarity is indeed falsified with the two arguments: large rescaling and the AMPS argument. Especially, the former is useful to show how communication happens between two observers: asymptotic and in-falling. To resolve this contradiction, AMPS introduced the firewall. If a firewall prevents the duplication experiment, then it should be located close to the apparent horizon after a certain time scale (information retention time or scrambling time).\n\nWe also tried to find out whether these two assumptions are consistent at the same time: (1) the firewall around the apparent horizon and (2) the firewall only affecting inside the black hole. To check the consistency, in this paper, we have considered a gravitational collapse with a false vacuum lump, which is motivated by a regular black hole model. We were able to construct an example where the apparent horizon can be disconnected. Then, one can clearly see that there are no barrier to screen the out-going effects due to the firewall and the firewall can be naked.\n\nFrom these arguments, we can clearly conclude the following:\n\nConclusion 1:\n\nThe original version of the black hole complementarity is inconsistent. An in-falling observer and an asymptotic observer can communicate.\n\nConclusion 2:\n\nTo keep the basic philosophy of black hole complementarity, we need a firewall outside the event horizon to kill the information of the in-falling information.888Of course, if we do not trust the philosophy of the black hole complementarity, then there is no need for a firewall.\n\nConclusion 3:\n\nA consistent firewall should affect not only an in-falling observer, but also an asymptotic observer.\n\nTherefore, there may be three possibilities: we need more assumptions to maintain the black hole complementarity in ad hoc ways, we have to take care of the macroscopic effects due to quantum gravity, or we have to modify the traditional entropy-area formula, etc. In this paper, we are not in a position to judge which is the final answer and this is postponed for a future work.\n\n## Appendix: Consistency and convergence tests\n\nIn this appendix, we report on the convergence and consistency tests for our simulations. As a demonstration, we consider the case with .\n\nFor consistency, we compare with different schemes. In this paper, we obtain by integrating , where is obtained by integrating the equation for : we call this . However, this is not the unique choice. We can obtain by integrating , where is obtained by integrating the equation for : we call this . In Figure 12 shows around . The difference of two schemes are less than . This shows that the error from the constraint equations (equations that we did not use for numerical integration) is sufficiently small and not accumulated. Therefore, this shows a good consistency.\n\nFor convergence, we compared finer simulations: , , and times finer around . In Figure 12, we see that the difference between the and times finer cases is times the difference between the and times finer cases, and thus our simulation converges to second order. The numerical error is except for the region near the singularity."
] | [
null,
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"https://media.arxiv-vanity.com/render-output/4655684/x5.png",
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"https://media.arxiv-vanity.com/render-output/4655684/x7.png",
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"https://media.arxiv-vanity.com/render-output/4655684/x8.png",
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"https://media.arxiv-vanity.com/render-output/4655684/x9.png",
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"https://media.arxiv-vanity.com/render-output/4655684/x10.png",
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] | {"ft_lang_label":"__label__en","ft_lang_prob":0.8854333,"math_prob":0.949731,"size":65565,"snap":"2021-43-2021-49","text_gpt3_token_len":15743,"char_repetition_ratio":0.16935374,"word_repetition_ratio":0.06304287,"special_character_ratio":0.2497064,"punctuation_ratio":0.16637169,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.97787523,"pos_list":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20],"im_url_duplicate_count":[null,1,null,1,null,1,null,1,null,1,null,1,null,1,null,1,null,1,null,1,null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2021-12-08T15:59:23Z\",\"WARC-Record-ID\":\"<urn:uuid:afb61b4c-01c7-4a22-9f16-aa66fa879a29>\",\"Content-Length\":\"973264\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:e790a5bf-b8a5-43d8-b1ac-ef1357e5112c>\",\"WARC-Concurrent-To\":\"<urn:uuid:58a3c490-2265-4147-80ca-b6cd44aac1c8>\",\"WARC-IP-Address\":\"172.67.158.169\",\"WARC-Target-URI\":\"https://www.arxiv-vanity.com/papers/1210.6733/\",\"WARC-Payload-Digest\":\"sha1:PP3XO7NVIK3QNSSIXCOKJHVJMN4MHMTA\",\"WARC-Block-Digest\":\"sha1:BLMIKQZTFDHVYGRNZD6TQPDWAMPF6COE\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2021/CC-MAIN-2021-49/CC-MAIN-2021-49_segments_1637964363515.28_warc_CC-MAIN-20211208144647-20211208174647-00503.warc.gz\"}"} |
https://www.jiskha.com/questions/76349/Identify-each-polar-equation-by-changing-the-equation-to-rectangular-coordinates | [
"# Polar Equations\n\nIdentify each polar equation by changing the equation to rectangular coordinates.\n\nLet t = theta\n\n(1) t = -pi/4\n\n(2) r(sin(t)) = -2\n\n1. 👍 0\n2. 👎 0\n3. 👁 107\n\n## Similar Questions\n\n1.Graph the polar equation r=3-2sin(theta) 2. Find the polar coordinates of 6 radical 3,6 for r > 0. 3. Find the rectangular coordinates of (7, 30°). 4. Write the rectangular equation in polar form. (x – 4)2 + y2 = 16 5. Write\n\nasked by Becca on February 26, 2013\n\n1.Graph the polar equation r=3-2sin(theta) 2. Find the polar coordinates of 6 radical 3,6 for r > 0. 3. Find the rectangular coordinates of (7, 30°). 4. Write the rectangular equation in polar form. (x – 4)2 + y2 = 16 5. Write\n\nasked by Becca on February 26, 2013\n\n1.Graph the polar equation r=3-2sin(theta) 2. Find the polar coordinates of 6 radical 3,6 for r > 0. 3. Find the rectangular coordinates of (7, 30°). 4. Write the rectangular equation in polar form. (x – 4)2 + y2 = 16 5. Write\n\nasked by Becca on February 26, 2013\n4. ### Trig (math)\n\n1.) Find all solutions of the equation. Leave answers in trigonometric form. x^2 + 1 - sqrt3i = 0 2.) Give the rectangular coordinates for the point. (9, 2pi/3) 3.) The rectangular coordinates of a point are given. Express the\n\nasked by Anonymous on December 8, 2014\n5. ### Pre calculus\n\nin the equation r= 5/(sin theta +2cos theta) the letters r and theta represent polar coordinates. Write the equivalent equation using rectangular coordinates. Thanks :)\n\nasked by Meredith on December 19, 2016\n6. ### MATH\n\nI have a test in about an hour and a half and am having some difficulty on the review the teacher gave us to help us prepare. Any help would be great! *Convert the polar equation to a rectangular equation. rsin(theta - Pi/4) =5\n\nasked by Daisy on April 4, 2013\n7. ### calculus\n\nfor what value of r=4sinè have vertical tangent? In polar coordinates? Theta=90 deg is vertical. I do not know if you know how to differentiate polar coordinate equations so I changed your equation from polar to rectangular form,\n\nasked by mary on April 26, 2007\n8. ### Write in (x , y) Form\n\nThe letters r and theta represent polar coordinates. Write each equation in rectangular coordinates (x, y) form. (1) r = 4 (2) r = 3/(3 - cos(t)), where t = theta\n\nasked by sharkman on February 23, 2008\n9. ### precalculus\n\nconvert the equation y^2 = 2x -x^2 into polar form. convert the equation r = 2tan(theta) into rectangular form. I'm not really sure what either of these mean. I vaguely understand polar coordinates, but I'm not sure how to convert\n\nasked by Annie on December 6, 2009\n10. ### pre calc.Math\n\nPlease help me any one of these please! Thank You to any one r=2-6 cos(θ) convert this polar coordinate equation into an equation in rectangular coordinates(x,y) given (-8,8) convert this point into polar coordinates with 6 >= 0\n\nasked by Ann on July 12, 2011\n\nMore Similar Questions"
] | [
null
] | {"ft_lang_label":"__label__en","ft_lang_prob":0.8490778,"math_prob":0.9984673,"size":2778,"snap":"2019-43-2019-47","text_gpt3_token_len":825,"char_repetition_ratio":0.20944485,"word_repetition_ratio":0.3031496,"special_character_ratio":0.30777538,"punctuation_ratio":0.13253012,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.99990153,"pos_list":[0],"im_url_duplicate_count":[null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2019-11-20T15:46:52Z\",\"WARC-Record-ID\":\"<urn:uuid:79e826c2-29a1-44ba-b3c1-5d7a1bf237c4>\",\"Content-Length\":\"17915\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:1e911247-525b-48a0-9589-77d059795857>\",\"WARC-Concurrent-To\":\"<urn:uuid:79d9d59b-74fa-4b13-a3af-9181a45ff5a1>\",\"WARC-IP-Address\":\"66.228.55.50\",\"WARC-Target-URI\":\"https://www.jiskha.com/questions/76349/Identify-each-polar-equation-by-changing-the-equation-to-rectangular-coordinates\",\"WARC-Payload-Digest\":\"sha1:5KGMMBBKTPSGOG4TDTOSMTD26QQL2BES\",\"WARC-Block-Digest\":\"sha1:2MPG4BZTUOJIDP4CI5GCYK34PURW4BCV\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2019/CC-MAIN-2019-47/CC-MAIN-2019-47_segments_1573496670559.66_warc_CC-MAIN-20191120134617-20191120162617-00379.warc.gz\"}"} |
https://answers.everydaycalculation.com/gcf/45-840 | [
"Solutions by everydaycalculation.com\n\n## What is the GCF of 45 and 840?\n\nThe GCF of 45 and 840 is 15.\n\n#### Steps to find GCF\n\n1. Find the prime factorization of 45\n45 = 3 × 3 × 5\n2. Find the prime factorization of 840\n840 = 2 × 2 × 2 × 3 × 5 × 7\n3. To find the GCF, multiply all the prime factors common to both numbers:\n\nTherefore, GCF = 3 × 5\n4. GCF = 15\n\nMathStep (Works offline)",
null,
"Download our mobile app and learn how to find GCF of upto four numbers in your own time:"
] | [
null,
"https://answers.everydaycalculation.com/mathstep-app-icon.png",
null
] | {"ft_lang_label":"__label__en","ft_lang_prob":0.78789335,"math_prob":0.997162,"size":581,"snap":"2022-27-2022-33","text_gpt3_token_len":189,"char_repetition_ratio":0.121317156,"word_repetition_ratio":0.0,"special_character_ratio":0.41135973,"punctuation_ratio":0.07964602,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.99618864,"pos_list":[0,1,2],"im_url_duplicate_count":[null,null,null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2022-07-04T04:00:12Z\",\"WARC-Record-ID\":\"<urn:uuid:2488118d-c7b0-43b8-b38d-03e7ab42eef2>\",\"Content-Length\":\"5941\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:9de8c81a-5d54-4314-9300-327387ef3ec4>\",\"WARC-Concurrent-To\":\"<urn:uuid:3e81ab6b-1741-45e5-99b9-1b0005d87d92>\",\"WARC-IP-Address\":\"96.126.107.130\",\"WARC-Target-URI\":\"https://answers.everydaycalculation.com/gcf/45-840\",\"WARC-Payload-Digest\":\"sha1:PS4R5NBAQMIKTRBRLBYHKERECX3CJOI4\",\"WARC-Block-Digest\":\"sha1:NR6EFJW3JYQD26CRZADQ567VNS6D5PDL\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2022/CC-MAIN-2022-27/CC-MAIN-2022-27_segments_1656104293758.72_warc_CC-MAIN-20220704015700-20220704045700-00138.warc.gz\"}"} |
https://www.zhygear.com/establishment-of-fatigue-crack-propagation-model-for-low-speed-and-heavy-load-gears/ | [
"# Establishment of fatigue crack propagation model for low speed and heavy load gears\n\nThe model used for numerical simulation of fatigue crack growth is the same as that of 42CrMo steel compact tensile specimen. Because the fatigue crack length is measured on the surface of the specimen in the fatigue crack growth test, and the specimen is uniformly stressed and the force is parallel to the plane of the specimen, this complex three-dimensional solid loading model is simplified as a plane stress problem for analysis in the finite element modeling.\n\nThe model is created in the finite element software ABAQUS, as shown in Figure 1. The whole model includes more than 17000 nodes. In order to make the numerical simulation results more accurate, considering that the real crack propagation rate is relatively slow in the crack initiation stage and the initial stage of crack propagation, and the gradient of elastic-plastic stress-strain field near the crack tip is very large, it is necessary to subdivide the mesh around the crack tip when meshing, and the mesh fineness decreases layer by layer, The modified 6-node quadratic plane stress triangular element (cps6m) with high accuracy is used. Because of the singularity at the crack tip, the 1 / 4 node method is used to create the singularity at the crack tip. The 8-node quadrilateral quadratic plane stress fully integrated element (cps8) is used in other regions except the fatigue crack tip.\n\nAs the material of the compact tensile specimen is 42CrMo steel, the material parameters are set as follows: elastic modulus E = 2.12 × 105 MPa, Poisson’s ratio μ= The maximum principal stress is 84.8 MPa. According to the energy principle, the softening of yield stress is linear, the stiffness degradation is maximized, and the mixed mode behavior is power law. The fracture energy in three directions is 42200 n / m, and the power exponent is 1. In order to counteract the elastic wave, prevent the failure of the static equilibrium equation in the extended finite element method, and improve the convergence of the model, the viscous stability coefficient is set to 5 × 10-5。\n\nIn order to improve the convergence of model analysis, in the incremental step option, the maximum number of incremental steps is 1 × 106, the initial increment step is set to 0.01, and the minimum value is 1 × 10-8, the maximum is 0.1.\n\nThe x-direction fixed displacement constraint is applied at the top node of the two loading holes, and the x-direction and Y-direction fixed displacement constraints are applied at the left end of the specimen at the same time. Because the object of the numerical simulation is the stress intensity factor at the crack tip, the stress intensity factor at the crack tip collected in the experiment is very small Δ The value of K is the difference between the stress intensity factor at the crack tip under the maximum load and the minimum load in a cycle. Therefore, in the numerical simulation, the structural load is static load, and the static analysis of the structure is carried out. The difference of the stress intensity factor at the crack tip obtained under two static loads is the calculated value. The load is applied to two symmetrical circular nodes of the specimen in the form of concentrated force, and each node establishes a coupling relationship with its respective semicircle region. The coupling type is set as distribution to realize the average distribution of concentrated force in the loading hole. The maximum and minimum values of tensile stress are the same as the experimental values. The dynamic continuous propagation of fatigue crack is realized by resetting the crack length each time. The value of crack length in numerical simulation is consistent with that in experiment.",
null,
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] | [
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"https://www.zhygear.com/wp-content/themes/luminescence-lite/images/post-shadow.png",
null
] | {"ft_lang_label":"__label__en","ft_lang_prob":0.8963668,"math_prob":0.98066705,"size":3694,"snap":"2022-27-2022-33","text_gpt3_token_len":750,"char_repetition_ratio":0.1596206,"word_repetition_ratio":0.034257747,"special_character_ratio":0.2019491,"punctuation_ratio":0.07952872,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.98950267,"pos_list":[0,1,2],"im_url_duplicate_count":[null,null,null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2022-06-28T06:01:24Z\",\"WARC-Record-ID\":\"<urn:uuid:c670f3fa-2e53-4458-8fda-d5dc0b7f0b47>\",\"Content-Length\":\"54593\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:d20bb170-adf7-4abd-98e5-f550cf7ab584>\",\"WARC-Concurrent-To\":\"<urn:uuid:f74c5722-f7f9-4762-8390-cbd138c2bf8a>\",\"WARC-IP-Address\":\"47.88.53.137\",\"WARC-Target-URI\":\"https://www.zhygear.com/establishment-of-fatigue-crack-propagation-model-for-low-speed-and-heavy-load-gears/\",\"WARC-Payload-Digest\":\"sha1:6LP7GOI4QWGUOCXUZICUFADH6OASLKRN\",\"WARC-Block-Digest\":\"sha1:VPRIBZPZN5HVLJOC37TADY5P3PJSKSJN\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2022/CC-MAIN-2022-27/CC-MAIN-2022-27_segments_1656103355949.26_warc_CC-MAIN-20220628050721-20220628080721-00734.warc.gz\"}"} |
http://mca.ignougroup.com/2016/03/ | [
"World's most popular travel blog for travel bloggers.\n\nWe will upload all assignment of MCA2 before 28th march\n\nWe will upload all assignment of MCA2 before 28th march\n\n## MCS013 - Assignment 8(d)\n\nA function is onto if and only if for every $y$ in the codomain, there is an $x$ in the domain such that $f\\left(x\\right)=y$.\nSo in the example you give, $f:\\mathbb{R}\\to \\mathbb{R},\\phantom{\\rule{1em}{0ex}}f\\left(x\\right)=5x+2$, the domain and codomain are the same set: $\\mathbb{R}.\\phantom{\\rule{thickmathspace}{0ex}}$ Since, for every real number $y\\in \\mathbb{R},\\phantom{\\rule{thinmathspace}{0ex}}$ there is an $\\phantom{\\rule{thinmathspace}{0ex}}x\\in \\mathbb{R}\\phantom{\\rule{thinmathspace}{0ex}}$ such that $f\\left(x\\right)=y$, the function is onto. The example you include shows an explicit way to determine which $x$ maps to a particular $y$, by solving for $x$ in terms of $y.$ That way, we can pick any $y$, solve for ${f}^{\\prime }\\left(y\\right)=x$, and know the value of $x$ which the original function maps to that $y$.\nSide note:\nNote that ${f}^{\\prime }\\left(y\\right)={f}^{-1}\\left(x\\right)$ when we swap variables. We are guaranteed that every function $f$ that is onto and one-to-one has an inverse ${f}^{-1}$, a function such that $f\\left({f}^{-1}\\left(x\\right)\\right)={f}^{-1}\\left(f\\left(x\\right)\\right)=x$.\n\n## MCS013 - Assignment 8(d)\n\nA function is onto if and only if for every $y$ in the codomain, there is an $x$ in the domain such that $f\\left(x\\right)=y$.\nSo in the example you give, $f:\\mathbb{R}\\to \\mathbb{R},\\phantom{\\rule{1em}{0ex}}f\\left(x\\right)=5x+2$, the domain and codomain are the same set: $\\mathbb{R}.\\phantom{\\rule{thickmathspace}{0ex}}$ Since, for every real number $y\\in \\mathbb{R},\\phantom{\\rule{thinmathspace}{0ex}}$ there is an $\\phantom{\\rule{thinmathspace}{0ex}}x\\in \\mathbb{R}\\phantom{\\rule{thinmathspace}{0ex}}$ such that $f\\left(x\\right)=y$, the function is onto. The example you include shows an explicit way to determine which $x$ maps to a particular $y$, by solving for $x$ in terms of $y.$ That way, we can pick any $y$, solve for ${f}^{\\prime }\\left(y\\right)=x$, and know the value of $x$ which the original function maps to that $y$.\nSide note:\nNote that ${f}^{\\prime }\\left(y\\right)={f}^{-1}\\left(x\\right)$ when we swap variables. We are guaranteed that every function $f$ that is onto and one-to-one has an inverse ${f}^{-1}$, a function such that $f\\left({f}^{-1}\\left(x\\right)\\right)={f}^{-1}\\left(f\\left(x\\right)\\right)=x$."
] | [
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] | {"ft_lang_label":"__label__en","ft_lang_prob":0.9035097,"math_prob":0.9998746,"size":1597,"snap":"2023-14-2023-23","text_gpt3_token_len":478,"char_repetition_ratio":0.13433772,"word_repetition_ratio":0.9594595,"special_character_ratio":0.28365687,"punctuation_ratio":0.10945274,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.9999912,"pos_list":[0],"im_url_duplicate_count":[null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2023-03-27T10:22:36Z\",\"WARC-Record-ID\":\"<urn:uuid:6c51fe8c-1ea9-4234-936d-bdb6c73a3a15>\",\"Content-Length\":\"324389\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:20206854-0ab4-4074-8da5-93662c31c222>\",\"WARC-Concurrent-To\":\"<urn:uuid:ea9b3514-aba1-43fb-bcc2-7b3b2d86ac91>\",\"WARC-IP-Address\":\"216.239.32.21\",\"WARC-Target-URI\":\"http://mca.ignougroup.com/2016/03/\",\"WARC-Payload-Digest\":\"sha1:JZKDSUR6J6RBXS4MTINLMUAYWL6IYOD7\",\"WARC-Block-Digest\":\"sha1:VTOJAT7TR4PUJ3QA5VV2FWLLEJCBRUUQ\",\"WARC-Identified-Payload-Type\":\"application/xhtml+xml\",\"warc_filename\":\"/cc_download/warc_2023/CC-MAIN-2023-14/CC-MAIN-2023-14_segments_1679296948620.60_warc_CC-MAIN-20230327092225-20230327122225-00415.warc.gz\"}"} |
https://milessmarttutoring.com/language-tutoring/ | [
"# Searching for \"Language tutors near me\"? You've come to the right place. We offer the best private in-home and online language tutoring.\n\n## How do you find the degree of the polynomial ? How do you divide complex fractions ? How do you determine if the function is one-to-one ? Can you show me correct decimal placement ? How do you divide complex fractions ? How to classify quadrilaterals ? What is the converse Pythagorean Theorem ? What is the area of a hexagon ? What is the formula for a prism ? How to find complex roots of a polynomial ?\n\nMinimum 4 characters"
] | [
null
] | {"ft_lang_label":"__label__en","ft_lang_prob":0.82821435,"math_prob":0.61981136,"size":399,"snap":"2019-51-2020-05","text_gpt3_token_len":82,"char_repetition_ratio":0.1392405,"word_repetition_ratio":0.08,"special_character_ratio":0.21804512,"punctuation_ratio":0.11392405,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.9842177,"pos_list":[0],"im_url_duplicate_count":[null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2019-12-06T19:31:58Z\",\"WARC-Record-ID\":\"<urn:uuid:580cf937-82ea-4594-b7c2-4737510c1ccb>\",\"Content-Length\":\"71770\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:48ba2b53-4537-4770-a5e9-01e5dda49945>\",\"WARC-Concurrent-To\":\"<urn:uuid:58f8b9d4-1624-4c46-a689-cd295fd4a040>\",\"WARC-IP-Address\":\"151.101.130.159\",\"WARC-Target-URI\":\"https://milessmarttutoring.com/language-tutoring/\",\"WARC-Payload-Digest\":\"sha1:W2UJQOEMN45ZYCBY4QC6JEJ26IQSY4DO\",\"WARC-Block-Digest\":\"sha1:XKVKZLJWPTSJT2KE7QCWG4XSQMNVBWNU\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2019/CC-MAIN-2019-51/CC-MAIN-2019-51_segments_1575540490743.16_warc_CC-MAIN-20191206173152-20191206201152-00339.warc.gz\"}"} |
http://charlesfoulke.com/gtff92/73c226-associative-property-calculator | [
"# associative property calculator\n\nFor instance, let's consider this below mentioned example: Or simply, is $$(a\\circ b)\\circ c$$ the same as $$a\\circ (b\\circ c)$$. We will further study associative property in case of addition and multiplication. Let us check whether or not associativity is met for this data. Put the 3 and the 4 in parenthesis? Basic number properties: associative, commutative, and. If you like this Page, please click that +1 button, too.. Associative property of multiplication states that multiplication problem can be grouped in different ways but the answer remains the same. For example: When we say associativity is met, then which pair you operate first does not matter. Identity property of 0. Summary of Number Properties The following table gives a summary of the commutative, associative and distributive properties. Distributive property. A n (B n C) = (A n B) n C. Let us look at some example problems based on above properties… Calculator Use. Definition: The associative property states that you can add or multiply regardless of how the numbers are grouped. What's the answer to this? An operation is associative when you can apply it, using parentheses, in different groupings of numbers and still expect the same result. Use the associative law of addition to write the expression. Inverse property of addition. Multiplying by tens. The \"Commutative Laws\" say we can swap numbers over and still get the same answer ..... when we add: a + b = b + a. Now the big question: is it the same if I operate those three elements in ways shown above. A u (B u C) = (A u B) u C (i) Set intersection is associative. The commutative property, therefore, concerns itself with the ordering of operations, including the addition and multiplication of real numbers, … Distributive Property Calculator is a free online tool that displays the solutions for the given expression using the distributive property. distributive property multiplicative property 5 (2 + 3) = 5 (2) + 5 (3) Applies. Associative Property. The most common operations, the ones that we know, do satisfy associativity, such as the sum or multiplication. To make it simpler, we simply write $$a \\circ b \\circ c$$, without parenthesis because due to the associativity property, we know that it does not matter how we group the operands, we will get the same final result of the operation. For example, in the problem: 2 x 3 x 5 x 6, you can multiply 2 x 3 to get 6 and then 5 x 6 to get 30, and then multiply 6 x 30 to get 180. Associative property explains that addition and multiplication of numbers are possible regardless of how they are grouped. Let us see some examples to understand commutative property. The parentheses indicate the terms that are considered one unit. Dear friends, the answer is depends on whether the operation is associative. The commutative property of multiplication is: a × b = b × a. That looks like a satisfactory way of operating $$a$$, $$b$$ and $$c$$. An operation is associative if a change in grouping does not change the results. Simplify both expressions to show they have identical results. Step 5: The three properties of congruence are the reflexive property of congruence, the symmetric property of congruence, and the transitive property of congruence. In mathematics, the associative property is a property of some binary operations, ... Nonassociativity of floating point calculation. Commutative Property. The formula for associative law or property can be determined by its definition. Associative Property. What a mouthful of words! LHS = RHS 20 x 2 = 40 Identity property of 0. Practice: Associative property of multiplication. According to the associative property of convolution, we can replace a cascade of Linear-Time Invariant systems in series by a single system whose impulse response is equal to the convolution of the impulse responses of the individual LTI systems. Regarding the commutative property and the associative property, both of which are used in so many situations, they are essential knowledge when solving math problems. The associative property states that the sum or product of a set of numbers is the same, no matter how the numbers are grouped. One way is to operate $$a$$ and $$b$$ first, and then operate the result of with $$c$$. The associative property is not … Such action can be put mathematically as $$a \\circ b = c$$. Step 3: Repeat the same for right hand side multiplication Doing Algebra without the associative property, although possible, it is rather hard. Yeah, that's an easy one! Put the 3 and the 4 in parenthesis? Matrix multiplication calculator emathhelp. So, question, what if you want to operate three elements. Remember that when completing equations, you start with the parentheses. This is known as the Associative Property of Multiplication. When multiplying three numbers, changing the grouping of the numbers does not change the result. 40 = 40 Start Here; Our Story; Hire a Tutor; Upgrade to Math Mastery. Let us consider the values of a = 4, b = 5 and c = 2 associative property of multiplication example: (3 * 4) * 5 = (5 * 4) * 3 does not apply. For any two two sets, the following statements are true. The associative property. Commutative property: When two numbers are added, the sum is the same regardless of the order of the addends. ( 4 x 5 ) = 20 The Associative Property of Multiplication. Associative Property Calculator In number system, the associative property states that when we multiply or add a differently grouped numbers, it gives the same output. The following table summarizes the number properties for addition and multiplication: Commutative, Associative and Identity. The Associative Property of Multiplication. In math, we always do what's in the parenthesis first! When the associative property is used, elements are merely regrouped. Number properties: commutative, associative, distributive. Numbers that are added can be grouped in any order. Get an answer to your question “Which equivalent expression would you set up to verify the associative property of addition for (3x + 4) + ((5x2 - 1) + (2x + 6)) ...” in Mathematics if there is no answer or all answers are wrong, use a search bar and try to find the answer among similar questions. Associative property of linear convolution. Simplify expression calculator emathhelp. But, there are four properties associated with multiplication, which are commutative, associative, multiplicative identity and distributive properties. Commutative Property Calculator: Enter a, b, and c. Commutative Property Calculator. Lesson Plan. The two Big Four operations that are associative are addition and multiplication. Practice: Use associative property to multiply 2-digit numbers by 1-digit. 13.5 white blood cell count 3 . Associative property: the law that gives the same answer even if you change the place of parentheses. Scroll down the page for more examples and explanations of the number properties. Step 4: Multiply the result with 4. A u (B u C) = (A u B) u C (i) Set intersection is associative. According to the associative property, we can regroup the numbers when we add, and we can regroup the numbers when we multiply. For any two two sets, the following statements are true. What if I operate $$b$$ and $$c$$ first, and THEN I operate $$a$$ with the result of operating $$b$$ and $$c$$. The associative property simply states that when three or more numbers are added, the sum is the same regardless of which numbers are added together first. Commutative, Associative and Distributive Laws. In short, in commutative property, the numbers can be added or multiplied to each other in any order without changing the answer. Commutative Property Calculator: Enter a, b, and c. Enter numbers to show the Commutative Property: Addition General Rule: ( a + b ) + c = a + ( b + c ) ( 1 + 4 ) + 2 = 5 + 2 = 7 In addition, the sum is always the same regardless of how the numbers are grouped. ( 4 x 5 ) x 2 = 4 x ( 5 x 2 ) Yep! For example, let us consider 3 numbers: $$8$$, $$4$$ and $$7$$. Associative property of multiplication states that multiplication problem can be grouped in different ways but the answer remains the same. Inverse property of addition. Doing Algebra without the associative property, although possible, it is rather hard. These properties help you take a complicated expression or equation and simplify it. Menu. So then, you take $$a$$ and $$b$$, you operate them and you get $$c$$. The groupings are within the parenthesis—hence, the numbers are associated together. The grouping of the elements, as indicated by the parentheses, does not affect the result of the equation. Arforgen cycle period for active army 2 . The commutative property is a one of the cornerstones of Algebra, and it is something we use all the time without knowing. The associative property is a cornerstone point in Algebra, and it is the foundation of most of the operations we conduct daily, even without knowing. Video transcript - [Instructor] So, what we're gonna do is get a little bit of practicing multiple numbers together and we're gonna discover some things. Some of the worksheets for this concept are Associative property of addition 1, Associative property of multiplication, Mcq, Associative property, Grade 1 associative properties of addition, Associative property of addition, Addition properties, Propertiesofmultiplication grades3and4standard. Please do not confuse associativity with commutativity. PEMDAS Warning) This calculator solves math equations that add, subtract, multiply and divide positive and negative numbers and exponential numbers. Use the associative property to change the grouping in an algebraic expression to make the work tidier or more convenient. What's the answer to this? In math, the associative property of multiplication allows us to group factors in different ways to get the same product. There are a number of properties that will help you simplify complex logarithmic expressions. Commutative Property . Use these math symbols: + Addition - Subtraction * … The associative property comes in handy when you work with algebraic expressions. Get an answer to your question “Which equivalent expression would you set up to verify the associative property of addition for (3x + 4) + ((5x2 - 1) + (2x + 6)) ...” in Mathematics if there is no answer or all answers are wrong, use a search bar and try to find the answer among similar questions. The associative property of multiplication states that you can change the grouping of the factors and it will not change the product. Associative property calculator. Yeah, that's not too hard! Associative Properties. Properties of addition . Wow! What a mouthful of words! What's the answer to this? Did you know that the associative property can help us solve problems faster? commutative property of multiplication: example: b * c = c * b does not apply. Thank you for your support! In mathematics, addition and multiplication of real numbers is associative. The associative property of multiplication states that when three or more real numbers are multiplied, the result is the same regardless of the grouping of the factors, that is the order of the multiplicands. I make an emphasis again, you operate TWO elements, $$a$$ and $$b$$. Associative, distributive and commutative properties -practice using. Personal history bronchitis icd 10 1 . Step 2: Multiply the last number with the result to get your LHS product. This property does not take effect on division or subtraction, it applies only on addition and subtraction. You can multiply the numbers in any order and will get 180. The set should have a minimum of three numbers and this property is not applicable for subtraction and division. If you like this Page, please click that +1 button, too.. Note: If a +1 button is dark blue, you have already +1'd it. For some operations associativity is not met, and that is fine, but lack of associativity makes everything more cumbersome. You probably know this, but the terminology may be new to you. Well, what if you operate two of them first, and then you operate the third one with the result of operating the first two elements? An operation is commutative if a change in the order of the numbers does not change the results. You would write that as $$a\\circ (b\\circ c)$$. Suppose you are adding three numbers, say 2, 5, 6, altogether. The two Big Four operations that are associative are addition and multiplication. The associative property involves three or more numbers. Fair enough. Suppose you are adding three numbers, say 2, 5, 6, altogether. Therefore, the operation \"$$\\circ$$\" is not associative. Notice that: Hence, in this case $$(8 + 4) + 7 = 8 + (4 + 7)$$. So, not all operations are associative, but most of the ones we know are. Notice the parenthesis there. Note: If a +1 button is dark blue, you have already +1'd it. This website uses cookies to improve your experience. By using this website, you agree to our Cookie Policy. (PEMDAS Warning) This calculator solves math equations that add, subtract, multiply and divide positive and negative numbers and exponential numbers.You can also include parentheses and numbers with exponents or roots in your equations. The Distributive Property is easy to remember, if you recall that \"multiplication distributes over addition\". If you like this Site about Solving Math Problems, please let Google know by clicking the +1 button. Multiplication distributes over addition because a(b + c) = ab + ac. Degrees of Freedom Calculator Paired Samples, Degrees of Freedom Calculator Two Samples. The associative property is a cornerstone point in Algebra, and it is the foundation of most of the operations we conduct daily, even without knowing. Associative Property. Properties and Operations. Hence, it is not always true that $$\\left( a\\circ b \\right)\\circ c = a\\circ \\left( b\\circ c \\right)$$. Laplace transform calculator emathhelp. Associative property of multiplication review. (If you are not logged into your Google account (ex., gMail, Docs), a login window opens when you click on +1. What are we waiting for, let’s get started! By grouping we mean the numbers which are given inside the parenthesis (). Associative property calculator. Put the 3 and the 4 in parenthesis? Addition is associative because, for example, the problem (2 + 4) + 7 produces the same result as does the problem 2 + (4 + 7). Free Algebraic Properties Calculator - Simplify radicals, exponents, logarithms, absolute values and complex numbers step-by-step This website uses cookies to ensure you get the best experience. The associative property of multiplication states that when multiplying three or more real numbers, the product is always the same regardless of their regrouping. Using associative property to simplify multiplication. Yeah, that's an easy one! Important Notes on Associative Property of Multiplication: 3. Suppose we want to find the value of the following expression: Changing the grouping of the numbers gives the same result, as shown in . Functions: What They Are and How to Deal with Them, Normal Probability Calculator for Sampling Distributions. The associative property for multiplication is expressed as (a * b) * c = a * (b * c). In case you have any suggestion, or if you would like to report a broken solver/calculator, please do not hesitate to contact us. Associativity is one of those things you take for granted and basically you use it without knowing. Associative property calculator. Next lesson. The associative property is one of those properties that does not get much talk about, because it is taken for granted, and it is used all the time, without knowing. distributive property Practice: Associative property of multiplication. But it is that the only way? Associative property calculator keyword after analyzing the system lists the list of keywords related and the list of websites with related content, in addition you can see which keywords most interested customers on the this website Yep! Without getting too technical, an operation \"$$\\circ$$\" is simply a way of taking two elements $$a$$ and $$b$$ on a certain set $$E$$, and do \"something\" with them to create another element $$c$$ in the set $$E$$. Calculator Use. Example: Commutative Percentages! Example : When multiplying three numbers, changing the grouping of the numbers does not change the result. Or can you? Commutative Property . The \"Commutative Laws\" say we can swap numbers over and still get the same answer ..... when we add: Commutative property calculator. The Associative Property of Addition. Associative Property of Multiplication of Integers, Whole Numbers Multiplication is one of the common mathematical functions which we all are familiar with. Algebraic Definition: (ab)c = a(bc) Examples: (5 x 4) x 25 = 500 and 5 x (4 x 25) = 500 Associative property explains that addition and multiplication of numbers are possible regardless of how they are grouped. It is important to observe that you operated TWO elements, $$a$$ and $$b$$, to get $$c$$. Or we can say, the grouping or combination of three numbers while adding or … (If you are not logged into your Google account (ex., gMail, Docs), a login window opens when you click on +1. In math, the associative property of multiplication allows us to group factors in different ways to get the same product. If you have three or more numbers, you can multiply them in any order to get the same result. Multiplication is one of the common mathematical functions which we all are familiar with. Associative property of linear convolution. The associative property of multiplication states that when multiplying three or more real numbers, the product is always the same regardless of their regrouping. That would be $$(a\\circ b)\\circ c$$. What Is the Associative Property of Multiplication? Today, we are going to learn about the associative property of addition, and the associative property of multiplication. Example: ... or when we multiply: a × b = b × a. Associative Property : The Associative property of numbers states that the addition or multiplication of a set of numbers gives the same output regardless of how they are grouped. The associative property is one of those properties that does not get much talk about, because it is taken for granted, and it is used all the time, without knowing. y(n) = [x(n)*h1(n)]*h2(n) = x(n)*[h1(n)*h2(n)] These laws are used in addition and multiplication. Throughout your study of algebra, you have come across many properties—such as the commutative, associative, and distributive properties. Practice: Use associative property to multiply 2-digit numbers by 1-digit. Online distributive property calculator | solver | calculator. Put the 3 and the 4 in parenthesis? Yes, that can be done. So, first I want you to figure out what four times five times two is. Thank you for your support! If we multiply three numbers, changing the grouping does not affect the product. Inverse property of multiplication. These laws are used in addition and multiplication. Associative property of addition calculator. You can also include parentheses and numbers with exponents or roots in your equations. There are mathematical structures that do not rely on commutativity, and they are even common operations (like subtraction and division) that do not satisfy it. Addition. Commutative Laws. But, there are four properties associated with multiplication, which are commutative, associative, multiplicative identity and distributive properties. But the ideas are simple. The associative property has to do with what operands we process first when operating more than two operands, and how it does not matter what operands we operate first, in terms of the final result of the operation. Definition: An operation $$\\circ$$ is associative if for any three elements $$a$$, $$b$$ and $$c$$, we have that, Not all operations satisfy this associative property, majority do, but some do not. In mathematics, the associative property is a property of some dyadic operations which is a calculation that combines two elements to produce another element. (i) Set union is associative. By 'grouped' we mean 'how you use parenthesis'. The associative property is very important because it allows flexibility to conduct operations of more than two operands, in a way that it does not matter which pair of operands is operated first, so parenthesis are not needed. Blue, you have already +1 'd it two operands out what times... One unit parentheses, in commutative property is not assumed to be true but. Pemdas, BEDMAS and BODMAS or multiply regardless of how the numbers which are commutative, associative, multiplicative and... Lhs product is fine, but most of the common mathematical functions which we all are familiar with you to. Add or multiply in any order and will get 180 subtraction, it is something we use all time. Addition because a × b = c\\ ) so, if we group the numbers does not change the of!, although possible, it is something we use all the time without knowing further... Addition or multiplication of real numbers is associative: what they are and how to Deal Them... To our Cookie Policy ones we know, do satisfy associativity, such as the sum or multiplication of are., too ' we mean the numbers are grouped common operations, the addition or multiplication, identity... Or multiplied to each other in any order, regardless of how the numbers differently will! The results most Searched keywords multiply: a × b = b ×.! These properties help you take a complicated expression or equation and simplify it us... But you can multiply Them in any order, regardless of how are... As per the definition, the following table summarizes the number properties for addition and multiplication real... Explains that addition and multiplication on addition and multiplication 'd it equation and simplify it, on the other,... Mean 'how you use it without knowing or roots in your equations common operations,... of... Of associativity makes everything more cumbersome practice: use associative property of multiplication allows us group. Set should have a minimum of three numbers is associative when you can add or multiply of! Hence associative property to multiply 2-digit numbers by 1-digit b u c ) \\ ) or we. You can change the grouping in an algebraic expression to make the work tidier or more numbers, 2... Not change the product, explanations and solutions given inside the parenthesis first multiplication of numbers and this is. And it will not change the results solve problems faster that when completing equations you... Us check whether or not associativity is met for this data, as indicated by the.! Blue, you have already +1 'd it structures in math in which associativity is …!, do satisfy associativity, such as the associative property of congruence are the reflexive of... Have three or more convenient put -- it does not take effect on division or subtraction, is! Same regardless of how the numbers are grouped hand, concerns the grouping of the,. Calculator two Samples us see some examples to understand commutative property of.! Definition: the associative property to change the product or simply put, the symmetric property multiplication... Used in sets does not matter where associative property calculator put the parenthesis first ), \\ ( a\\ and! = c\\ ) c. commutative property: when two numbers are added, the associative property of is! Of real numbers is associative if a change in grouping does not take effect on or! Take a complicated expression or equation and simplify it the two Big four operations that are can! And how to Deal with Them, Normal Probability Calculator for Sampling Distributions you like this Site about Solving problems. The cornerstones of Algebra, and addition '' equations that add, and the transitive property multiplication! Four times five times two is are addition and multiplication of numbers in any.! For multiplication as well as well addition, and the associative property used in sets satisfactory of... Work tidier or more convenient ( +\\ ) '' are added, answer... C ) \\ ) equation and simplify it order, regardless of how the numbers which given! + 3 ) applies something we use all the time without knowing,! Put -- it does not take effect on division or subtraction, it is rather hard ) \\circ )... Means the parenthesis ( ) ways shown above this property is not met, and c. commutative property Calculator Enter. Question: is it the same result ; our Story ; Hire a Tutor ; Upgrade to math.. ) can be shown by the parentheses and BODMAS this Site about Solving problems!, regardless of how the numbers are possible regardless of the cornerstones of Algebra, we. That looks like a satisfactory way of operating \\ ( a\\ ), \\ ( ( a\\circ ( c... Minimum of three numbers, changing the grouping in an algebraic expression to make the work tidier or more,... And numbers with exponents or roots in your equations true, but answer... * 4 ) * c ) = ( a u b ) u c ( )., although possible, it is rather hard for more examples and explanations of factors., you agree to our Cookie Policy multiply and divide positive and negative numbers and expect! Of elements in an operation is associative when you can add or multiply regardless of how the numbers does take... Each other in any order and will get 180 for granted and basically you parenthesis! Ways but the terminology may be new to you what they are and to! Be moved the grouping of the associative property is a free online tool displays! Each other in any order without changing the answer remains the same to understand first the idea operation! Take effect on division or subtraction, it is also true that a % of b = b + )... Point calculation a * ( b + c = c * b ) u c ) Integers! Sampling Distributions third one expect the same thing the results = ab + ac the place of parentheses,. Basic number properties: associative, but most of the numbers differently... we... Solutions for the common sum \\ ( a\\circ b ) u c.... Associative associative property calculator, which are given inside the parenthesis first our Cookie Policy not applicable subtraction. Those three elements in ways shown above adding three numbers, you operate first does take..., Whole numbers multiplication is: a × b = b + c \\! Are much more limited do satisfy associativity, such as the associative property of multiplication that. Multiplication, subtraction and division is a one of the commutative property, which are inside! Of congruence, and distributive properties you agree to our Cookie Policy to understand property. Our Story ; Hire a Tutor ; Upgrade to math Mastery as per definition. Properties for addition and multiplication to get the associative property calculator regardless of how the numbers does not.. Same thing to both addition and multiplication of real numbers is associative would do!, plus 3, in different groupings of numbers in a different way this! Three properties of congruence c ( associative property calculator ) Set intersection is associative, if we do this, but of. At the core of the cornerstones of Algebra, you start with the result check some numbers to convince that. Two Big four operations that are added can be grouped in different ways but the answer the. Faster and it will not change the grouping of the common sum \\ ( b\\ ), and. Be true, but the terminology may be new to you and divide and! Say 2, 5, 6, altogether any two two sets, numbers... Property in case of addition to write the expression is depends on whether operation. Our Story ; Hire a Tutor ; Upgrade to math Mastery your study of,. Come across many properties—such as the associative property to multiply 2-digit numbers by 1-digit grouping in an operation associative... Two numbers are associated together a\\ ), \\ ( a\\ ) and \\ ( \\circ\\ ) '' a! Multiplying it does not affect the product factors and it is rather hard website., and that is fine, but lack of associativity makes everything more cumbersome can shown... The operation of more than two operands: associative, but those are much more limited assume! Other in any order and will get 180 Big four operations that are associative are addition and.! Search ( please select at least 2 keywords ) most Searched keywords, using parentheses plus! The Big question: is it the same principle holds true for multiplication as.. Added can be added or multiplied to each other in any order applies only on addition and subtraction by sum! Same regardless of how they are grouped take effect on division or subtraction, it is rather hard in shown. Which applies to expressions that associative property calculator a number by a sum or multiplication of numbers and still the... The other hand, concerns the grouping of the addends so, first i you. Now, what if we multiply + 5 ( 3 ) = ab + ac plus 2 in parentheses in. Help you take a complicated expression or equation and simplify it a sum or difference numbers. Commutative, associative and identity distributive property Calculator: Enter a, b, and the transitive property multiplication. Not change the results two Big four operations that are associative are addition multiplication. The simplification of numbers and still expect the same ) these properties work addition... Our Story ; Hire a Tutor ; Upgrade to math Mastery they have identical results two. ( 5 * 4 ) * 3 does not matter where you put the parenthesis first multiplied to other... = 20 Step 2: multiply the numbers does not matter, we!"
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https://www.meritnation.com/jee-1-year/chemistry/chemistry/thermodynamics-and-thermochemistry/studymaterial/53_5_2035_9698_16080 | [
"Select Board & Class\n\nThermodynamics and Thermochemistry\n\nLaws of Thermodynamics\n\nInternal energy\n\n• Internal energy (U) represents the total energy of a system (i.e., the sum of chemical, electrical, mechanical or any other type of energy).\n\n• Internal energy of a system may change when:\n\n• Heat passes into or out of the system\n• Work is done on or by the system\n• Matter enters or leaves the system\n\nWork\n\n• For an adiabatic system which does not permit the transfer of heat through its boundary (shown in the figure), a change in its internal energy can be brought by doing some work on it.",
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"• Initial state of the system, (1)\n\nTemperature = T1\n\nInternal energy = U1\n\n• When some mechanical work is done, the new state (2) is obtained.\n\nTemperature at state 2 = T2\n\nInternal energy at state 2 = U2\n\n• It is found that T2 >T1\n\nChange in temperature, ΔT = T2T1\n\nChange in internal energy, ΔU = U2U1\n\n• The value of internal energy (U) is the characteristic of the state of a system.\n\n• The adiabatic work (Wad) required to bring about a change of state is equal to the change in internal energy.\n\n• Thus, internal energy (U) of the system is a state function.\n\n• When work is done on the system, Wad = + ve\n\n• When work is done by the system, Wad = − ve\n\nHeat\n\n• Internal energy of the system can also be changed by transfer of heat from the surroundings to the system or vice versa, without doing any work.\n\n• This exchange of energy, which is a result of temperature difference, is called heat (q).\n\n• A system which allows heat transfer through its boundary is shown in the figure.",
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"• At constant volume, when no work is done, the change in internal energy is, ΔU = q\n\n• When heat is transferred from the surroundings to the system, q is positive.\n\n• When heat is transferred from the system to the surroundings, q is negative.\n\nGeneral Case\n\n• When change in state is brought about both by doing work (W) and by transfer of heat (q):\n\nChange in internal energy, ΔU = q + W\n\n• If W = 0 and q = 0 (i.e., no transfer of energy as heat or as work), then\n\nΔU = 0\n\nThis means that for an isolated system, ΔU = 0.\n\n• ΔU = q + W, is the mathematical statement of the first law of thermodynamics.\n\n• First law of thermodynamics states that “the energy of an isolated system is constant”.\n\nEnthalpy\n\n• We have ΔU = q + w (First law of thermodynamics)\n\n• ΔU Change in internal energy\n\nq Heat absorbed by the system\n\nw Work done\n\n• At constant volume:\n\n• ΔU = qv\n\n• At constant pressure:\n\n• ΔU = qppΔV\n\n(− pΔV) represents expansion work done by the system\n\nOr, U2U1 = qpp (V2V1)\n\nOr. qp = (U2 + pV2) − (U1 + pV1) …(1)\n\n• Enthalpy (H) can be defined as\n\n• H = U + pV\n\n• Thus, from equation (1) − qp = H2 H1 or, qp = ΔH\n\n• ΔH is independent of path, and hence, qp is also independent of path.\n\n• At constant pressure, for finite changes:\n\n• ΔH = ΔU + pΔV\n\n• At constant pressure, ΔH = qp (heat absorbed by the system)\n\n• ΔH is negative for exothermic reactions (which evolve heat during the reaction)\n\n• ΔH is positive for endothermic reactions (which absorb heat from the surroundings)\n\n• At constant volume: ΔU = qv\n\n• Or, ΔH = ΔU = qv [",
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"ΔV = 0]\n\n• For reactions involving gases, using ideal gas law, pΔV = ΔngRT\n\n• Δng = Number of moles of gaseous products − Number of moles of gaseous reactants\n\n• Thus, ΔH = ΔU + ΔngRT\n\n• Extensive and Intensive Properties\n\n• Extensive property: Value depends on the quantity or size of matter in the system\n\n• Examples − mass, volume, internal energy, heat capacity, etc.\n\n• Intensive property: Value does not depend on the quantity or size of matter in the system\n\n• Examples − temperature, density, pressure, etc.\n\nHeat Capacity\n\n• The increase in temperature (ΔT) is proportional to the heat transferred (q)\n\n• q = coeff (C) × ΔT\n\nC Heat capacity\n\n• C is directly proportional to the amount of a substance.\n\n• Molar heat capacity of a substance,",
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", is the heat capacity of one mole of the substance.\n\n• Molar heat capacity is also defined as the quantity of heat required to raise the temperature of one mole of a substance by one degree Celsius (or one Kelvin).\n\n• Specific heat capacity c (o…\n\nTo view the complete topic, please\n\nWhat are you looking for?\n\nSyllabus"
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null
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https://www.numbersaplenty.com/1123220 | [
"Search a number\nBaseRepresentation\nbin100010010001110010100\n32010001202202\n410102032110\n5241420340\n640024032\n712355460\noct4221624\n92101682\n101123220\n116a798a\n12462018\n13304337\n142134a0\n15172c15\nhex112394\n\n1123220 has 48 divisors (see below), whose sum is σ = 2757888. Its totient is φ = 376320.\n\nThe previous prime is 1123219. The next prime is 1123231. The reversal of 1123220 is 223211.\n\n1123220 = T143 + T144 + ... + T212.\n\nIt is a happy number.\n\nIt is a congruent number.\n\nIt is an unprimeable number.\n\nIt is a polite number, since it can be written in 15 ways as a sum of consecutive naturals, for example, 9884 + ... + 9996.\n\nIt is an arithmetic number, because the mean of its divisors is an integer number (57456).\n\n21123220 is an apocalyptic number.\n\n1123220 is a gapful number since it is divisible by the number (10) formed by its first and last digit.\n\nIt is an amenable number.\n\nIt is a practical number, because each smaller number is the sum of distinct divisors of 1123220, and also a Zumkeller number, because its divisors can be partitioned in two sets with the same sum (1378944).\n\n1123220 is an abundant number, since it is smaller than the sum of its proper divisors (1634668).\n\nIt is a pseudoperfect number, because it is the sum of a subset of its proper divisors.\n\n1123220 is a wasteful number, since it uses less digits than its factorization.\n\n1123220 is an evil number, because the sum of its binary digits is even.\n\nThe sum of its prime factors is 200 (or 198 counting only the distinct ones).\n\nThe product of its (nonzero) digits is 24, while the sum is 11.\n\nThe square root of 1123220 is about 1059.8207395593. The cubic root of 1123220 is about 103.9493096167.\n\nAdding to 1123220 its reverse (223211), we get a palindrome (1346431).\n\nSubtracting from 1123220 its reverse (223211), we obtain a palindrome (900009).\n\nThe spelling of 1123220 in words is \"one million, one hundred twenty-three thousand, two hundred twenty\"."
] | [
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https://ixtrieve.fh-koeln.de/birds/litie/document/21185 | [
"# Document (#21185)\n\nAuthor\nBurrell, Q.L.\nTitle\nWill this paper ever be cited?\nSource\nJournal of the American Society for Information Science and technology. 53(2002) no.3, S.232-235\nYear\n2002\nAbstract\nA recently proposed stochastic model to describe the citation process in the presence of obsolescence is used to answer the question: If a paper has not been cited by time t after its publication, what is the probability that it will ever be cited?\nTheme\nInformetrie\nCitation indexing\n\n## Similar documents (author)\n\n1. Burrell, Q.L.: Fitting Lotka's law : some cautionary observations on a recent paper by Newby et al. (2003) (2004) 5.65\n```5.6473675 = sum of:\n5.6473675 = weight(author_txt:burrell in 1236) [ClassicSimilarity], result of:\n5.6473675 = fieldWeight in 1236, product of:\n1.0 = tf(freq=1.0), with freq of:\n1.0 = termFreq=1.0\n9.035788 = idf(docFreq=13, maxDocs=43254)\n0.625 = fieldNorm(doc=1236)\n```\n2. Burrell, Q.L.: \"Ambiguity\" ans scientometric measurement : a dissenting view (2001) 5.65\n```5.6473675 = sum of:\n5.6473675 = weight(author_txt:burrell in 1982) [ClassicSimilarity], result of:\n5.6473675 = fieldWeight in 1982, product of:\n1.0 = tf(freq=1.0), with freq of:\n1.0 = termFreq=1.0\n9.035788 = idf(docFreq=13, maxDocs=43254)\n0.625 = fieldNorm(doc=1982)\n```\n3. Burrell, Q.L.: \"Type/Token-Taken\" informetrics : Some comments and further examples (2003) 5.65\n```5.6473675 = sum of:\n5.6473675 = weight(author_txt:burrell in 4117) [ClassicSimilarity], result of:\n5.6473675 = fieldWeight in 4117, product of:\n1.0 = tf(freq=1.0), with freq of:\n1.0 = termFreq=1.0\n9.035788 = idf(docFreq=13, maxDocs=43254)\n0.625 = fieldNorm(doc=4117)\n```\n4. Burrell, Q.L.: Measuring similarity of concentration between different informetric distributions : two new approaches (2005) 5.65\n```5.6473675 = sum of:\n5.6473675 = weight(author_txt:burrell in 5411) [ClassicSimilarity], result of:\n5.6473675 = fieldWeight in 5411, product of:\n1.0 = tf(freq=1.0), with freq of:\n1.0 = termFreq=1.0\n9.035788 = idf(docFreq=13, maxDocs=43254)\n0.625 = fieldNorm(doc=5411)\n```\n5. Burrell, Q.L.: Predicting future citation behavior (2003) 5.65\n```5.6473675 = sum of:\n5.6473675 = weight(author_txt:burrell in 5838) [ClassicSimilarity], result of:\n5.6473675 = fieldWeight in 5838, product of:\n1.0 = tf(freq=1.0), with freq of:\n1.0 = termFreq=1.0\n9.035788 = idf(docFreq=13, maxDocs=43254)\n0.625 = fieldNorm(doc=5838)\n```\n\n## Similar documents (content)\n\n1. Burrell, Q.L.: Predicting future citation behavior (2003) 0.45\n```0.45359692 = sum of:\n0.45359692 = product of:\n0.989666 = sum of:\n0.006284744 = weight(abstract_txt:that in 5838) [ClassicSimilarity], result of:\n0.006284744 = score(doc=5838,freq=1.0), product of:\n0.028102964 = queryWeight, product of:\n2.3854163 = idf(docFreq=10822, maxDocs=43254)\n0.011781157 = queryNorm\n0.22363278 = fieldWeight in 5838, product of:\n1.0 = tf(freq=1.0), with freq of:\n1.0 = termFreq=1.0\n2.3854163 = idf(docFreq=10822, maxDocs=43254)\n0.09375 = fieldNorm(doc=5838)\n0.0094126025 = weight(abstract_txt:this in 5838) [ClassicSimilarity], result of:\n0.0094126025 = score(doc=5838,freq=2.0), product of:\n0.029198254 = queryWeight, product of:\n1.0193008 = boost\n2.4314568 = idf(docFreq=10335, maxDocs=43254)\n0.011781157 = queryNorm\n0.32236868 = fieldWeight in 5838, product of:\n1.4142135 = tf(freq=2.0), with freq of:\n2.0 = termFreq=2.0\n2.4314568 = idf(docFreq=10335, maxDocs=43254)\n0.09375 = 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tf(freq=1.0), with freq of:\n1.0 = termFreq=1.0\n3.4900522 = idf(docFreq=3585, maxDocs=43254)\n0.09375 = fieldNorm(doc=5838)\n0.27237856 = weight(abstract_txt:obsolescence in 5838) [ClassicSimilarity], result of:\n0.27237856 = score(doc=5838,freq=1.0), product of:\n0.34674406 = queryWeight, product of:\n3.512598 = boost\n8.379008 = idf(docFreq=26, maxDocs=43254)\n0.011781157 = queryNorm\n0.785532 = fieldWeight in 5838, product of:\n1.0 = tf(freq=1.0), with freq of:\n1.0 = termFreq=1.0\n8.379008 = idf(docFreq=26, maxDocs=43254)\n0.09375 = fieldNorm(doc=5838)\n0.28402713 = weight(abstract_txt:stochastic in 5838) [ClassicSimilarity], result of:\n0.28402713 = score(doc=5838,freq=1.0), product of:\n0.35656083 = queryWeight, product of:\n3.561974 = boost\n8.496791 = idf(docFreq=23, maxDocs=43254)\n0.011781157 = queryNorm\n0.7965741 = fieldWeight in 5838, product of:\n1.0 = tf(freq=1.0), with freq of:\n1.0 = termFreq=1.0\n8.496791 = idf(docFreq=23, maxDocs=43254)\n0.09375 = fieldNorm(doc=5838)\n0.45833334 = coord(11/24)\n```\n2. Moed, H.F.: Statistical relationships between downloads and citations at the level of individual documents within a single journal (2005) 0.44\n```0.4359764 = sum of:\n0.4359764 = product of:\n0.7473881 = sum of:\n0.00888797 = weight(abstract_txt:that in 5883) [ClassicSimilarity], result of:\n0.00888797 = score(doc=5883,freq=8.0), product of:\n0.028102964 = queryWeight, product of:\n2.3854163 = idf(docFreq=10822, maxDocs=43254)\n0.011781157 = queryNorm\n0.3162645 = fieldWeight in 5883, product of:\n2.828427 = tf(freq=8.0), with freq of:\n8.0 = termFreq=8.0\n2.3854163 = idf(docFreq=10822, maxDocs=43254)\n0.046875 = fieldNorm(doc=5883)\n0.0033278575 = weight(abstract_txt:this in 5883) [ClassicSimilarity], result of:\n0.0033278575 = score(doc=5883,freq=1.0), product of:\n0.029198254 = queryWeight, product of:\n1.0193008 = boost\n2.4314568 = idf(docFreq=10335, maxDocs=43254)\n0.011781157 = queryNorm\n0.11397454 = fieldWeight in 5883, product of:\n1.0 = tf(freq=1.0), with freq of:\n1.0 = 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fieldNorm(doc=5883)\n0.23538382 = weight(abstract_txt:cited in 5883) [ClassicSimilarity], result of:\n0.23538382 = score(doc=5883,freq=3.0), product of:\n0.4993804 = queryWeight, product of:\n7.3013024 = boost\n5.805548 = idf(docFreq=353, maxDocs=43254)\n0.011781157 = queryNorm\n0.47135174 = fieldWeight in 5883, product of:\n1.7320508 = tf(freq=3.0), with freq of:\n3.0 = termFreq=3.0\n5.805548 = idf(docFreq=353, maxDocs=43254)\n0.046875 = fieldNorm(doc=5883)\n0.5833333 = coord(14/24)\n```\n3. Mingers, J.; Burrell, Q.L.: Modeling citation behavior in Management Science journals (2006) 0.43\n```0.42886302 = sum of:\n0.42886302 = product of:\n1.0292712 = sum of:\n0.009071246 = weight(abstract_txt:that in 2995) [ClassicSimilarity], result of:\n0.009071246 = score(doc=2995,freq=3.0), product of:\n0.028102964 = queryWeight, product of:\n2.3854163 = idf(docFreq=10822, maxDocs=43254)\n0.011781157 = queryNorm\n0.3227861 = fieldWeight in 2995, product of:\n1.7320508 = tf(freq=3.0), with freq of:\n3.0 = termFreq=3.0\n2.3854163 = idf(docFreq=10822, maxDocs=43254)\n0.078125 = fieldNorm(doc=2995)\n0.012402193 = weight(abstract_txt:this in 2995) [ClassicSimilarity], result of:\n0.012402193 = score(doc=2995,freq=5.0), product of:\n0.029198254 = queryWeight, product of:\n1.0193008 = boost\n2.4314568 = idf(docFreq=10335, maxDocs=43254)\n0.011781157 = queryNorm\n0.42475805 = fieldWeight in 2995, product of:\n2.236068 = tf(freq=5.0), with freq of:\n5.0 = termFreq=5.0\n2.4314568 = idf(docFreq=10335, maxDocs=43254)\n0.078125 = fieldNorm(doc=2995)\n0.035124492 = weight(abstract_txt:model in 2995) [ClassicSimilarity], result of:\n0.035124492 = score(doc=2995,freq=2.0), product of:\n0.07932522 = queryWeight, product of:\n1.6800785 = boost\n4.0076866 = idf(docFreq=2136, maxDocs=43254)\n0.011781157 = queryNorm\n0.442791 = fieldWeight in 2995, product of:\n1.4142135 = tf(freq=2.0), with freq of:\n2.0 = termFreq=2.0\n4.0076866 = idf(docFreq=2136, maxDocs=43254)\n0.078125 = fieldNorm(doc=2995)\n0.03925381 = weight(abstract_txt:time in 2995) [ClassicSimilarity], result of:\n0.03925381 = score(doc=2995,freq=2.0), product of:\n0.085426465 = queryWeight, product of:\n1.7434928 = boost\n4.158956 = idf(docFreq=1836, maxDocs=43254)\n0.011781157 = queryNorm\n0.45950407 = fieldWeight in 2995, product of:\n1.4142135 = tf(freq=2.0), with freq of:\n2.0 = termFreq=2.0\n4.158956 = idf(docFreq=1836, maxDocs=43254)\n0.078125 = fieldNorm(doc=2995)\n0.03820849 = weight(abstract_txt:proposed in 2995) [ClassicSimilarity], result of:\n0.03820849 = score(doc=2995,freq=1.0), product of:\n0.10571124 = queryWeight, product of:\n1.9394765 = boost\n4.6264586 = idf(docFreq=1150, maxDocs=43254)\n0.011781157 = queryNorm\n0.3614421 = fieldWeight in 2995, product of:\n1.0 = tf(freq=1.0), with freq of:\n1.0 = termFreq=1.0\n4.6264586 = idf(docFreq=1150, maxDocs=43254)\n0.078125 = fieldNorm(doc=2995)\n0.064629085 = weight(abstract_txt:citation in 2995) [ClassicSimilarity], result of:\n0.064629085 = score(doc=2995,freq=2.0), product of:\n0.11911229 = queryWeight, product of:\n2.0587435 = boost\n4.91096 = idf(docFreq=865, maxDocs=43254)\n0.011781157 = queryNorm\n0.54258955 = fieldWeight in 2995, product of:\n1.4142135 = tf(freq=2.0), with freq of:\n2.0 = termFreq=2.0\n4.91096 = idf(docFreq=865, maxDocs=43254)\n0.078125 = fieldNorm(doc=2995)\n0.04639322 = weight(abstract_txt:paper in 2995) [ClassicSimilarity], result of:\n0.04639322 = score(doc=2995,freq=2.0), product of:\n0.1203144 = queryWeight, product of:\n2.9261577 = boost\n3.4900522 = idf(docFreq=3585, maxDocs=43254)\n0.011781157 = queryNorm\n0.3855999 = fieldWeight in 2995, product of:\n1.4142135 = tf(freq=2.0), with freq of:\n2.0 = termFreq=2.0\n3.4900522 = idf(docFreq=3585, maxDocs=43254)\n0.078125 = fieldNorm(doc=2995)\n0.3210012 = weight(abstract_txt:obsolescence in 2995) [ClassicSimilarity], result of:\n0.3210012 = score(doc=2995,freq=2.0), product of:\n0.34674406 = queryWeight, product of:\n3.512598 = boost\n8.379008 = idf(docFreq=26, maxDocs=43254)\n0.011781157 = queryNorm\n0.92575836 = fieldWeight in 2995, product of:\n1.4142135 = tf(freq=2.0), with freq of:\n2.0 = termFreq=2.0\n8.379008 = idf(docFreq=26, maxDocs=43254)\n0.078125 = fieldNorm(doc=2995)\n0.23668928 = weight(abstract_txt:stochastic in 2995) [ClassicSimilarity], result of:\n0.23668928 = score(doc=2995,freq=1.0), product of:\n0.35656083 = queryWeight, product of:\n3.561974 = boost\n8.496791 = idf(docFreq=23, maxDocs=43254)\n0.011781157 = queryNorm\n0.6638118 = fieldWeight in 2995, product of:\n1.0 = tf(freq=1.0), with freq of:\n1.0 = termFreq=1.0\n8.496791 = idf(docFreq=23, maxDocs=43254)\n0.078125 = fieldNorm(doc=2995)\n0.2264982 = weight(abstract_txt:cited in 2995) [ClassicSimilarity], result of:\n0.2264982 = score(doc=2995,freq=1.0), product of:\n0.4993804 = queryWeight, product of:\n7.3013024 = boost\n5.805548 = idf(docFreq=353, maxDocs=43254)\n0.011781157 = queryNorm\n0.45355844 = fieldWeight in 2995, product of:\n1.0 = tf(freq=1.0), with freq of:\n1.0 = termFreq=1.0\n5.805548 = idf(docFreq=353, maxDocs=43254)\n0.078125 = fieldNorm(doc=2995)\n0.41666666 = coord(10/24)\n```\n4. Liu, X.; Zhang, J.; Guo, C.: Full-text citation analysis : a new method to enhance scholarly networks (2013) 0.26\n```0.25952798 = sum of:\n0.25952798 = product of:\n0.69207466 = sum of:\n0.0041898293 = weight(abstract_txt:that in 2509) [ClassicSimilarity], result of:\n0.0041898293 = score(doc=2509,freq=1.0), product of:\n0.028102964 = queryWeight, product of:\n2.3854163 = idf(docFreq=10822, maxDocs=43254)\n0.011781157 = queryNorm\n0.14908852 = fieldWeight in 2509, product of:\n1.0 = tf(freq=1.0), with freq of:\n1.0 = termFreq=1.0\n2.3854163 = idf(docFreq=10822, maxDocs=43254)\n0.0625 = fieldNorm(doc=2509)\n0.006275068 = weight(abstract_txt:this in 2509) [ClassicSimilarity], result of:\n0.006275068 = score(doc=2509,freq=2.0), product of:\n0.029198254 = queryWeight, product of:\n1.0193008 = boost\n2.4314568 = idf(docFreq=10335, maxDocs=43254)\n0.011781157 = queryNorm\n0.21491244 = fieldWeight in 2509, product of:\n1.4142135 = tf(freq=2.0), with freq of:\n2.0 = termFreq=2.0\n2.4314568 = idf(docFreq=10335, maxDocs=43254)\n0.0625 = fieldNorm(doc=2509)\n0.011791615 = weight(abstract_txt:used in 2509) [ClassicSimilarity], result of:\n0.011791615 = score(doc=2509,freq=1.0), product of:\n0.056019183 = queryWeight, product of:\n1.4118623 = boost\n3.3678792 = idf(docFreq=4051, maxDocs=43254)\n0.011781157 = queryNorm\n0.21049245 = fieldWeight in 2509, product of:\n1.0 = tf(freq=1.0), with freq of:\n1.0 = termFreq=1.0\n3.3678792 = idf(docFreq=4051, maxDocs=43254)\n0.0625 = fieldNorm(doc=2509)\n0.028099595 = weight(abstract_txt:model in 2509) [ClassicSimilarity], result of:\n0.028099595 = score(doc=2509,freq=2.0), product of:\n0.07932522 = queryWeight, product of:\n1.6800785 = boost\n4.0076866 = idf(docFreq=2136, maxDocs=43254)\n0.011781157 = queryNorm\n0.3542328 = fieldWeight in 2509, product of:\n1.4142135 = tf(freq=2.0), with freq of:\n2.0 = termFreq=2.0\n4.0076866 = idf(docFreq=2136, maxDocs=43254)\n0.0625 = fieldNorm(doc=2509)\n0.08955269 = weight(abstract_txt:citation in 2509) [ClassicSimilarity], result of:\n0.08955269 = score(doc=2509,freq=6.0), product of:\n0.11911229 = queryWeight, product of:\n2.0587435 = boost\n4.91096 = idf(docFreq=865, maxDocs=43254)\n0.011781157 = queryNorm\n0.7518342 = fieldWeight in 2509, product of:\n2.4494898 = tf(freq=6.0), with freq of:\n6.0 = termFreq=6.0\n4.91096 = idf(docFreq=865, maxDocs=43254)\n0.0625 = fieldNorm(doc=2509)\n0.12547134 = weight(abstract_txt:publication in 2509) [ClassicSimilarity], result of:\n0.12547134 = score(doc=2509,freq=7.0), product of:\n0.1416723 = queryWeight, product of:\n2.2452588 = boost\n5.355877 = idf(docFreq=554, maxDocs=43254)\n0.011781157 = queryNorm\n0.88564485 = fieldWeight in 2509, product of:\n2.6457512 = tf(freq=7.0), with freq of:\n7.0 = termFreq=7.0\n5.355877 = idf(docFreq=554, maxDocs=43254)\n0.0625 = fieldNorm(doc=2509)\n0.14419708 = weight(abstract_txt:probability in 2509) [ClassicSimilarity], result of:\n0.14419708 = score(doc=2509,freq=2.0), product of:\n0.23600192 = queryWeight, product of:\n2.897889 = boost\n6.912671 = idf(docFreq=116, maxDocs=43254)\n0.011781157 = queryNorm\n0.6109996 = fieldWeight in 2509, product of:\n1.4142135 = tf(freq=2.0), with freq of:\n2.0 = termFreq=2.0\n6.912671 = idf(docFreq=116, maxDocs=43254)\n0.0625 = fieldNorm(doc=2509)\n0.02624397 = weight(abstract_txt:paper in 2509) [ClassicSimilarity], result of:\n0.02624397 = score(doc=2509,freq=1.0), product of:\n0.1203144 = queryWeight, product of:\n2.9261577 = boost\n3.4900522 = idf(docFreq=3585, maxDocs=43254)\n0.011781157 = queryNorm\n0.21812826 = fieldWeight in 2509, product of:\n1.0 = tf(freq=1.0), with freq of:\n1.0 = termFreq=1.0\n3.4900522 = idf(docFreq=3585, maxDocs=43254)\n0.0625 = fieldNorm(doc=2509)\n0.25625348 = weight(abstract_txt:cited in 2509) [ClassicSimilarity], result of:\n0.25625348 = score(doc=2509,freq=2.0), product of:\n0.4993804 = queryWeight, product of:\n7.3013024 = boost\n5.805548 = idf(docFreq=353, maxDocs=43254)\n0.011781157 = queryNorm\n0.5131428 = fieldWeight in 2509, product of:\n1.4142135 = tf(freq=2.0), with freq of:\n2.0 = termFreq=2.0\n5.805548 = idf(docFreq=353, maxDocs=43254)\n0.0625 = fieldNorm(doc=2509)\n0.375 = coord(9/24)\n```\n5. Kim, M.; Baek, I.; Song, M.: Topic diffusion analysis of a weighted citation network in biomedical literature (2018) 0.22\n```0.21636282 = sum of:\n0.21636282 = product of:\n0.7418154 = sum of:\n0.0052372864 = weight(abstract_txt:that in 37) [ClassicSimilarity], result of:\n0.0052372864 = score(doc=37,freq=1.0), product of:\n0.028102964 = queryWeight, product of:\n2.3854163 = idf(docFreq=10822, maxDocs=43254)\n0.011781157 = queryNorm\n0.18636064 = fieldWeight in 37, product of:\n1.0 = tf(freq=1.0), with freq of:\n1.0 = termFreq=1.0\n2.3854163 = idf(docFreq=10822, maxDocs=43254)\n0.078125 = fieldNorm(doc=37)\n0.005546429 = weight(abstract_txt:this in 37) [ClassicSimilarity], result of:\n0.005546429 = score(doc=37,freq=1.0), product of:\n0.029198254 = queryWeight, product of:\n1.0193008 = boost\n2.4314568 = idf(docFreq=10335, maxDocs=43254)\n0.011781157 = queryNorm\n0.18995756 = fieldWeight in 37, product of:\n1.0 = tf(freq=1.0), with freq of:\n1.0 = termFreq=1.0\n2.4314568 = idf(docFreq=10335, maxDocs=43254)\n0.078125 = fieldNorm(doc=37)\n0.024836767 = weight(abstract_txt:model in 37) [ClassicSimilarity], result of:\n0.024836767 = score(doc=37,freq=1.0), product of:\n0.07932522 = queryWeight, product of:\n1.6800785 = boost\n4.0076866 = idf(docFreq=2136, maxDocs=43254)\n0.011781157 = queryNorm\n0.31310052 = fieldWeight in 37, product of:\n1.0 = tf(freq=1.0), with freq of:\n1.0 = termFreq=1.0\n4.0076866 = idf(docFreq=2136, maxDocs=43254)\n0.078125 = fieldNorm(doc=37)\n0.137099 = weight(abstract_txt:citation in 37) [ClassicSimilarity], result of:\n0.137099 = score(doc=37,freq=9.0), product of:\n0.11911229 = queryWeight, product of:\n2.0587435 = boost\n4.91096 = idf(docFreq=865, maxDocs=43254)\n0.011781157 = queryNorm\n1.1510063 = fieldWeight in 37, product of:\n3.0 = tf(freq=9.0), with freq of:\n9.0 = termFreq=9.0\n4.91096 = idf(docFreq=865, maxDocs=43254)\n0.078125 = fieldNorm(doc=37)\n0.05927964 = weight(abstract_txt:publication in 37) [ClassicSimilarity], result of:\n0.05927964 = score(doc=37,freq=1.0), product of:\n0.1416723 = queryWeight, product of:\n2.2452588 = boost\n5.355877 = idf(docFreq=554, maxDocs=43254)\n0.011781157 = queryNorm\n0.41842788 = fieldWeight in 37, product of:\n1.0 = tf(freq=1.0), with freq of:\n1.0 = termFreq=1.0\n5.355877 = idf(docFreq=554, maxDocs=43254)\n0.078125 = fieldNorm(doc=37)\n0.056819864 = weight(abstract_txt:paper in 37) [ClassicSimilarity], result of:\n0.056819864 = score(doc=37,freq=3.0), product of:\n0.1203144 = queryWeight, product of:\n2.9261577 = boost\n3.4900522 = idf(docFreq=3585, maxDocs=43254)\n0.011781157 = queryNorm\n0.47226155 = fieldWeight in 37, product of:\n1.7320508 = tf(freq=3.0), with freq of:\n3.0 = termFreq=3.0\n3.4900522 = idf(docFreq=3585, maxDocs=43254)\n0.078125 = fieldNorm(doc=37)\n0.4529964 = weight(abstract_txt:cited in 37) [ClassicSimilarity], result of:\n0.4529964 = score(doc=37,freq=4.0), product of:\n0.4993804 = queryWeight, product of:\n7.3013024 = boost\n5.805548 = idf(docFreq=353, maxDocs=43254)\n0.011781157 = queryNorm\n0.9071169 = fieldWeight in 37, product of:\n2.0 = tf(freq=4.0), with freq of:\n4.0 = termFreq=4.0\n5.805548 = idf(docFreq=353, maxDocs=43254)\n0.078125 = fieldNorm(doc=37)\n0.29166666 = coord(7/24)\n```"
] | [
null
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https://suscholar.southwestern.edu/handle/11214/2/browse?type=subject&value=Polynomial+approximation | [
"DSpace Repository\n\n# Browsing Faculty Scholarship by Subject \"Polynomial approximation\"\n\nSort by: Order: Results:\n\n• (Journal of Approximation Theory, 1998)\nLet {φk}n k=0, n<m, be a family of polynomials orthogonal with respect to the positive semi-definite bilinear form (g, h)d := 1 m Xm j=1 g(xj )h(xj ), xj := −1 + (2j − 1)/m. These polynomials are known as Gram ..."
] | [
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] | {"ft_lang_label":"__label__en","ft_lang_prob":0.8280981,"math_prob":0.92955303,"size":274,"snap":"2020-45-2020-50","text_gpt3_token_len":97,"char_repetition_ratio":0.074074075,"word_repetition_ratio":0.0,"special_character_ratio":0.34306568,"punctuation_ratio":0.1969697,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.9811441,"pos_list":[0],"im_url_duplicate_count":[null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2020-11-30T05:42:03Z\",\"WARC-Record-ID\":\"<urn:uuid:c5b62998-881a-4b74-8228-67656d97cb68>\",\"Content-Length\":\"23877\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:6cae144a-07f4-49f0-8bbf-4b621da56e51>\",\"WARC-Concurrent-To\":\"<urn:uuid:03485540-b24e-48a6-a66e-368f9605e39a>\",\"WARC-IP-Address\":\"3.16.35.187\",\"WARC-Target-URI\":\"https://suscholar.southwestern.edu/handle/11214/2/browse?type=subject&value=Polynomial+approximation\",\"WARC-Payload-Digest\":\"sha1:DRGQDS2TLQY7WSD23EGM7G3I2IDFAPLM\",\"WARC-Block-Digest\":\"sha1:5D6GFHLMWUAQGYVK7UTOLFT7XHEQ6AJE\",\"WARC-Identified-Payload-Type\":\"application/xhtml+xml\",\"warc_filename\":\"/cc_download/warc_2020/CC-MAIN-2020-50/CC-MAIN-2020-50_segments_1606141205147.57_warc_CC-MAIN-20201130035203-20201130065203-00410.warc.gz\"}"} |
https://math.stackexchange.com/questions/2495295/show-that-m-ddot-q-nabla-uq-0-implies-m-frac-dot-q22uq-k-quad-k-in | [
"# Show that $m\\ddot q+\\nabla U(q)=0\\implies m\\frac{|\\dot q|^2}2+U(q)=K,\\quad K\\in\\Bbb R$\n\nThis is the exercise 12 in page 211 of Analysis II of Amann and Escher.\n\nSuppose $T(\\dot q)=m\\frac{|\\dot q|^2}2$ and $U(t,q)=U(q)$ for $q\\in\\Bbb R^3$. Prove that the total energy defined as $E:=T+U$ is constant along every solution $q$ of the Euler-Lagrange equation for the variational problem $$\\int_{t_0}^{t_1}[T(\\dot q)-U(q)]\\,\\mathrm dt\\implies\\text{Min},\\quad q\\in C^2([t_0,t_1],\\Bbb R^3)\\tag1$$\n\nI dont follow exactly what I must do in this exercise. My work so far:\n\nThe Euler-Lagrange equation for $L:=T(\\dot q)-U(q)$ is $m\\ddot q=-\\nabla U(q)$. Then we want to show that if $q$ holds the previous equation then $E=T+U=K$ where $K$ is a constant.\n\nIf Im not wrong the exercise can be rewritten as $$m\\ddot q+\\nabla U(q)=0\\implies m\\frac{|\\dot q|^2}2+U(q)=K,\\quad K\\in\\Bbb R \\tag2$$ However from $E=K$ I find that $\\frac{\\partial}{\\partial q} E=\\nabla U(q)=0$ and $\\frac\\partial{\\partial \\dot q} E=m\\dot q=0$, that is, it seems that Im proving the opposite direction of $(2)$. Some help will be appreciated, thank you.\n\nYou need just to differentiate $E$ with respect to time, remembering that $q$ depends on time:\n\n$$\\frac{d}{dt} m\\frac{\\dot q^2}{2} = m (\\dot q \\cdot\\ddot q)$$\n\n$$\\frac{d}{dt} U(q) = \\dot q \\cdot \\nabla U$$\n\nPlugging it in:\n\n$$\\frac{d}{dt}E = \\dot q \\cdot (m\\ddot q + \\nabla U) = \\dot q \\cdot 0 = 0$$\n\nNote that it doesn't say that $E(q, \\dot q)$ is a global constant: it is only constant along the lines $q(t)$ that are solutions to the Euler-Lagrange equation, which means $\\frac{d}{dt}E = 0$, or, equivalently, that $\\dot q \\cdot \\frac{\\partial E}{\\partial q} + \\ddot q \\cdot \\frac{\\partial E}{\\partial \\dot q} = 0$. It does not mean that $\\frac{\\partial}{\\partial p}E=0$ or that $\\frac{\\partial}{\\partial \\dot p}E=0$.\n\nAs an analogue, consider $f(x,y) = x-y$: it is constant along the lines where $x(t)=kt+C_1$ and $y(t)=kt+C_2$ for constant $k$, $C_1$ and $C_2$, but $f$ is not globally constant, and $\\frac{\\partial}{\\partial x}f=1$, $\\frac{\\partial}{\\partial y}f=-1$.\n\n• I see but, what is wrong in my approach? I mean, it is not true that $E=K\\implies \\nabla U(q)=0$? – Masacroso Oct 29 '17 at 18:16\n• @Masacroso Ah, I see now. I'm sorry I misinterpreted the question! I'll update the answer shortly. – lisyarus Oct 29 '17 at 18:19\n• its ok, it is my fault if I want enough clear. Your answer is ok but Idk if the implication on the previous comment is true. My intuition says me that it probably isnt correct but Idk why. – Masacroso Oct 29 '17 at 18:20"
] | [
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] | {"ft_lang_label":"__label__en","ft_lang_prob":0.81134367,"math_prob":0.99994373,"size":1023,"snap":"2020-34-2020-40","text_gpt3_token_len":367,"char_repetition_ratio":0.10794897,"word_repetition_ratio":0.0,"special_character_ratio":0.33822092,"punctuation_ratio":0.07949791,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":1.0000087,"pos_list":[0],"im_url_duplicate_count":[null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2020-08-04T03:00:10Z\",\"WARC-Record-ID\":\"<urn:uuid:df98f8fe-d2fe-468b-b515-469ca2c5ea7d>\",\"Content-Length\":\"152824\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:d2ca4617-7742-46f3-8e3b-0973c400109d>\",\"WARC-Concurrent-To\":\"<urn:uuid:31126ac3-555c-4cb8-af84-39ee7fc3a66a>\",\"WARC-IP-Address\":\"151.101.65.69\",\"WARC-Target-URI\":\"https://math.stackexchange.com/questions/2495295/show-that-m-ddot-q-nabla-uq-0-implies-m-frac-dot-q22uq-k-quad-k-in\",\"WARC-Payload-Digest\":\"sha1:EPDBSPCOVMFHJN7XRJ73ZVCRCQ2GFZYA\",\"WARC-Block-Digest\":\"sha1:KJAJVNJQBKBUQ7YUEDCPCICMXNS7A7ZN\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2020/CC-MAIN-2020-34/CC-MAIN-2020-34_segments_1596439735851.15_warc_CC-MAIN-20200804014340-20200804044340-00349.warc.gz\"}"} |
https://mycourses.aalto.fi/course/view.php?id=20606 | [
"## Topic outline\n\n• ### General\n\n• Contents: Machine learning with deep neural networks. Programming using PyTorch.\n\nAfter the course, the student understands the basic principles of deep learning: fully-connected, convolutional and recurrent neural networks; stochastic gradient descent and backpropagation; means to prevent overfitting. The student understands how to do supervised learning (classification and regression) and unsupervised learning with neural networks. The student knows modern neural architectures used for image classification, time series modeling and natural language processing. The student has experience on training deep learning models in PyTorch.\n\n• Assessment: Exercises, a project work and an exam.\n\n• Prerequisites: Basics of machine learning, basics of probability and statistics, good level of programming in Python. Recommended: matrix algebra.\nBasic terms of machine learning:\n• supervised and unsupervised learning\n• overfitting and underfitting\n• regularization\nBasic terms of probability theory:\n• sum, product rule, Bayes' rule\n• expectation, mean, variance, median\n• Course contents:\n• Introduction and history of deep learning\n• Optimization for training deep models\n• Regularization for deep learning\n• Convolutional networks\n• Recurrent neural networks\n• Unsupervised learning with deep autoencoders and generative adversarial networks\n\n•",
null,
"•",
null,
""
] | [
null,
"https://mycourses.aalto.fi/theme/image.php/aalto_mycourses/forum/1701155020/monologo",
null,
"https://mycourses.aalto.fi/theme/image.php/aalto_mycourses/forum/1701155020/monologo",
null
] | {"ft_lang_label":"__label__en","ft_lang_prob":0.8576674,"math_prob":0.43724918,"size":1563,"snap":"2023-40-2023-50","text_gpt3_token_len":322,"char_repetition_ratio":0.1462476,"word_repetition_ratio":0.066985644,"special_character_ratio":0.19833653,"punctuation_ratio":0.16666667,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.9870778,"pos_list":[0,1,2,3,4],"im_url_duplicate_count":[null,null,null,null,null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2023-12-03T14:59:03Z\",\"WARC-Record-ID\":\"<urn:uuid:b30ca282-58a9-4bb4-a32c-ed2d33235187>\",\"Content-Length\":\"94453\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:8daabebc-d392-492d-bd56-fe8b3f9aa011>\",\"WARC-Concurrent-To\":\"<urn:uuid:6d33c744-88f4-444b-b411-4c847283e728>\",\"WARC-IP-Address\":\"130.233.229.20\",\"WARC-Target-URI\":\"https://mycourses.aalto.fi/course/view.php?id=20606\",\"WARC-Payload-Digest\":\"sha1:GOYZ5PPKN5A5E6LPWAB47UARXMM24IS3\",\"WARC-Block-Digest\":\"sha1:U2CECAAXG6DDJZJFPRGVHPZXXKYLTC4V\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2023/CC-MAIN-2023-50/CC-MAIN-2023-50_segments_1700679100508.23_warc_CC-MAIN-20231203125921-20231203155921-00619.warc.gz\"}"} |
https://www.elsevier.com/books/mathematics-for-financial-analysis/gartenberg/978-0-08-019599-5 | [
"COVID-19 Update: We are currently shipping orders daily. However, due to transit disruptions in some geographies, deliveries may be delayed. To provide all customers with timely access to content, we are offering 50% off Science and Technology Print & eBook bundle options. Terms & conditions.\n\n# Mathematics for Financial Analysis\n\n## 1st Edition\n\n0.0 star rating Write a review\nAuthors:\neBook ISBN: 9781483279275\nImprint: Pergamon\nPublished Date: 1st January 1976\nPage Count: 220\nSales tax will be calculated at check-out Price includes VAT/GST\n72.95\n51.06\n43.99\n54.95\nUnavailable\nPrice includes VAT/GST\n\n## Description\n\nMathematics for Financial Analysis focuses on the application of mathematics in financial analysis, including applications of differentiation, logarithmic functions, and compounding.\n\nThe publication first ponders on equations and graphs, vectors and matrices, and linear programming. Discussions focus on duality and minimization problems, systems of linear inequalities, linear programs, matrix inversion, properties of matrices and vectors, vector products, equations and graphs, higher dimensional spaces, distance in the plane, coordinate geometry, and inequalities and absolute value.\n\nThe text then examines differential calculus, applications of differentiation, and antidifferentiation and definite integration. Topics include fundamental theorem of calculus, definite integral, profit optimization in a monopoly, revenue from taxation, curve sketching, concavity and points of inflection, and rules for differentiation. The book examines the applications of integration and differentiation and integration of exponential and logarithmic functions, including exponential and logarithmic functions, differentiation and integration of logarithmic functions, and continuous compounding.\n\nThe publication is a valuable source of data for researchers interested in the application of mathematics in financial analysis.\n\nPreface\n\n1. Equations and Graphs\n\n1.1. Inequalities and Absolute Value\n\n1.2. Coordinate Geometry\n\n1.3. Distance in the Plane\n\n1.4. Slope\n\n1.5. Equations and Graphs\n\n1.6. Demand and Supply Curves\n\n1.7. Break-even Analysis\n\n1.8. Higher Dimensional Spaces\n\n2. Vectors and Matrices\n\n2.1. Properties of Vectors\n\n2.2. Vector Products\n\n2.3. Properties of Matrices\n\n2.4. Matrix Multiplication\n\n2.5. Systems of Linear Equations\n\n2.6. Matrix Inversion\n\n2.7. Input-Output Analysis\n\n3. Linear Programming\n\n3.1. Linear Programs\n\n3.2. Systems of Linear Inequalities\n\n3.3. Two-Variable Programs\n\n3.4. The Simplex Method\n\n3.5. Duality and Minimisation Problems\n\n4. Differential Calculus\n\n4.1. Functions\n\n4.2. Limits\n\n4.3. Continuity\n\n4.4. Slopes of Tangent Lines to a Curve\n\n4.5 Derivatives\n\n4.6 Rules for Differentiation\n\n4.7 Composite Functions\n\n4.8 Fractional Exponents\n\n5. Applications of Differentiation\n\n5.1. Maxima and Minima\n\n5.2. Concavity and Points of Inflection\n\n5.3. Curve Sketching\n\n5.4. The Total Cost Function\n\n5.5. Profit Optimisation in a Monopoly\n\n5.6. Revenue from Taxation\n\n5.7. The Effect of Taxation on Profit Optimisation\n\n5.8. Inventory Models\n\n6. Antidifferentiation and Definite Integration\n\n6.1. Antidifferentiation\n\n6.2. The Definite Integral\n\n6.3. The Fundamental Theorem of Calculus\n\n6.4. Areas Between Curves\n\n7. Differentiation and Integration of Exponential and Logarithmic Functions\n\n7.1. Exponential and Logarithmic Functions\n\n7.2. Differentiaticfn and Integration of Logarithmic Functions\n\n7.3. Differentiation and Integration of Exponential Functions\n\n8. Applications of Integration\n\n8.1. Antidifferentiation of Marginal Functions\n\n8.2. Consumers' and Producers' Surplus\n\n8.3. Simple and Compound Interest\n\n8.4. Continuous Compounding\n\n8.5. Simple Annuities\n\n8.6. More General Annuities\n\n8.7. Continuous Annuities\n\nTable 8.1\n\nTable 8.2\n\nTable 8.3\n\nTable 8.4\n\nIndex\n\nNo. of pages:\n220\nLanguage:\nEnglish\nPublished:\n1st January 1976\nImprint:\nPergamon\neBook ISBN:\n9781483279275"
] | [
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] | {"ft_lang_label":"__label__en","ft_lang_prob":0.7901817,"math_prob":0.87201726,"size":4025,"snap":"2020-24-2020-29","text_gpt3_token_len":989,"char_repetition_ratio":0.14772445,"word_repetition_ratio":0.010810811,"special_character_ratio":0.21788819,"punctuation_ratio":0.20653595,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.9724104,"pos_list":[0],"im_url_duplicate_count":[null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2020-07-09T09:05:01Z\",\"WARC-Record-ID\":\"<urn:uuid:182a7775-24de-490f-9c79-eaeb55a718b9>\",\"Content-Length\":\"249463\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:b2ff23c5-d051-466e-bc90-5791adb7b6b5>\",\"WARC-Concurrent-To\":\"<urn:uuid:8b46e613-834a-4c94-bbf6-e83394a6e222>\",\"WARC-IP-Address\":\"203.82.26.7\",\"WARC-Target-URI\":\"https://www.elsevier.com/books/mathematics-for-financial-analysis/gartenberg/978-0-08-019599-5\",\"WARC-Payload-Digest\":\"sha1:6MOCGC5PRECBYL4TTXARPOZI4ZTDTOJN\",\"WARC-Block-Digest\":\"sha1:56EFT4QRTYA5SOYJ7LNMSHZETECONJ7F\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2020/CC-MAIN-2020-29/CC-MAIN-2020-29_segments_1593655899209.48_warc_CC-MAIN-20200709065456-20200709095456-00547.warc.gz\"}"} |
https://www.macroption.com/call-option-payoff/ | [
"# Call Option Payoff Diagram, Formula and Logic\n\nThis page explains call option payoff / profit or loss at expiration. We will look at:\n\nHere you can see the same for put option payoff.\n\nAnd here the same for short call position (the inverse of long call).\n\n## Call Option Payoff Diagram\n\nBuying a call option is the simplest of option trades. A call option gives you the right, but not obligation, to buy the underlying security at the given strike price. Therefore a call option’s intrinsic value or payoff at expiration depends on where the underlying price is relative to the call option’s strike price.\n\nThe payoff diagram shows how the option’s total profit or loss (Y-axis) depends on underlying price (X-axis).\n\nThe key variables are:\n\n• Strike price (45 in the example above)\n• Initial price at which you have bought the option (2.88 in the example)\n• Current underlying price (the chart’s X-axis)\n\nAs you can see in the graph, the option’s strike price (45.00) is the key point which divides the payoff function in two parts. Below the strike, the payoff chart is constant and negative (the trade is a loss). Above the strike the line is upward sloping, as the call option’s payoff is rising in proportion with the underlying price. At some point (the break-even point = 47.88 in our example) the line crosses zero and the trade starts to be profitable.\n\n## Call Option Scenarios and Profit or Loss\n\nThree things can generally happen when you are long a call option.\n\n### 1. Underlying price is lower than strike price\n\nWhen underlying price ends up below the strike at expiration, the option expires worthless and your total result from the long call trade is a loss equal to the initial price (in this case \\$2.88 per share, or \\$288 for a standard option contract representing 100 shares). For example, if underlying price is 43.80, it makes no sense to exercise the option, which would only allow you to buy the underlying at 45.00, more expensively than on the market.\n\nThe good thing with a long call trade is that your loss is always limited to the initial cost – you can’t lose more, no matter what happens. If the underlying price falls to zero, you still only lose the \\$288 which you paid for the call option in the beginning. A long call option’s payoff chart is a straight line between zero and strike price and the payoff is a loss equal to the option’s initial cost.\n\n### 2. Underlying price is equal to strike price\n\nIn the rare case when the underlying price ends up being equal to the option’s strike price at expiration, it still doesn’t make any sense to exercise the option, because you may as well buy the underlying on the market for the same price. Therefore a long call option’s payoff is still a loss equal to the initial cost (\\$288 in our example). Same as scenario 1 in fact.\n\n### 3. Underlying price is higher than strike price\n\nFinally, this is the scenario which a call option holder is hoping for. If the underlying price ends up being higher than the option’s strike price, the option is in the money and it starts to make sense to exercise it.\n\nFor example, let’s say the underlying price is 49.00. Because the option gives you the right to buy the underlying at strike price (45.00) and you can immediately sell it on the market at the underlying price (49.00), exercising the option brings you positive cash flow of \\$4.00 per share, or \\$400 per contract. If you bought the option at 2.88 (initial option price in our example), your profit from the entire trade would be 4.00 – 2.88 = \\$1.12 per share = \\$112 per contract. You can also see this in the payoff diagram where underlying price (X-axis) is 49.\n\n## Call Option Payoff Formula\n\nThe total profit or loss from a long call trade is always a sum of two things:\n\n• Initial cash flow\n• Cash flow at expiration\n\n### Initial cash flow\n\nInitial cash flow is constant – the same under all scenarios. It is a product of three things:\n\n• The option’s price when you bought it\n• Number of option contracts you have bought\n• Number of shares per contract\n\nUsually you also include transaction costs (such as broker commissions).\n\nIn our example, initial option price (including commissions) is \\$2.88 per share, we are long 1 contract of 100 shares, therefore initial cash flow is:\n\n2.88 x 1 x 100 = – \\$288\n\nOf course, with a long call position the initial cash flow is negative, as you are buying the options in the beginning.\n\n### Cash flow at expiration\n\nThe second component of a call option payoff, cash flow at expiration, varies depending on underlying price. That said, it is actually quite simple and you can construct it from the scenarios discussed above.\n\nIf underlying price is below than or equal to strike price, the cash flow at expiration is always zero, as you just let the option expire and do nothing.\n\nIf underlying price is above the strike price, you exercise the option and you can immediately sell it on the market at the current underlying price. Therefore the cash flow is the difference between underlying price and strike price, times number of shares.\n\nCF = what you sell the underlying for – what you buy the underlying for when exercising the option\n\nCF per share = underlying price – strikes price\n\nCF = ( underlying price – strike price ) x number of option contracts x contract multiplier\n\nIn our example with underlying price 49.00:\n\nCF = ( 49 – 45 ) x 1 x 100 = \\$400\n\nPutting all the scenarios together, we can say that the cash flow at expiration is equal to the greater of:\n\n• ( underlying price – strike price ) x number of option contracts x contract multiplier\n• Zero\n\nIf you are using Excel, you can calculate this using the MAX function.\n\nNote: The option’s value or cash flow at expiration is equal to the option’s intrinsic value. It is the same formula.\n\n### Putting it all together – call option payoff formula\n\nCall P/L = initial cash flow + cash flow at expiration\n\nInitial CF = -1 x initial option price x number of contracts x contract multiplier\n\nCF at expiration = ( MAX ( underlying price – strike price , 0 ) x number of contracts x contract multiplier\n\nCall P/L = ( MAX ( underlying price – strike price , 0 ) – initial option price ) x number of contracts x contract multiplier\n\nCall P/L per share = MAX ( underlying price – strike price , 0 ) – initial option price\n\n## Call Option Payoff Calculation in Excel\n\nThe screenshot below illustrates call option payoff calculation in Excel. Besides the MAX function, which is very simple, it is all basic arithmetics.",
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"## Call Option Break-Even Point Calculation\n\nOne other thing you may want to calculate is the exact underlying price where your long call position starts to be profitable. In other words, the point where the payoff chart crosses the zero line, or where the total P/L (which we have calculated above) equals zero – the break-even point.\n\nIt is very simple. It is the sum of strike price and initial option price.\n\nCall B/E = strike price + initial option price\n\nIn our example with strike = 45 and initial price = 2.88 the break-even point is 47.88. You can try to use this as underlying price in the P/L formula above and you will get exactly zero profit.\n\n## Long Call Option Payoff Summary\n\n• A long call option position is bullish, with limited risk and unlimited upside.\n• Maximum possible loss is equal to initial cost of the option and applies for underlying price below than or equal to the strike price.\n• With underlying price above the strike, the payoff rises in proportion with underlying price.\n• The position turns profitable at break-even underlying price equal to the sum of strike price and initial option price.\n\nHave a question or feedback? It takes less than a minute."
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"https://www.macroption.com/images/option-strategies/call-option-payoff-calculation-excel.png",
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] | {"ft_lang_label":"__label__en","ft_lang_prob":0.8903835,"math_prob":0.9657148,"size":7841,"snap":"2021-43-2021-49","text_gpt3_token_len":1707,"char_repetition_ratio":0.21717493,"word_repetition_ratio":0.09206799,"special_character_ratio":0.23147558,"punctuation_ratio":0.08147175,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.99233305,"pos_list":[0,1,2],"im_url_duplicate_count":[null,6,null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2021-10-24T17:58:11Z\",\"WARC-Record-ID\":\"<urn:uuid:2ce811d7-99a8-48a9-be51-ad33b9917103>\",\"Content-Length\":\"23265\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:d82622e4-398f-4105-af5e-2cf570a05078>\",\"WARC-Concurrent-To\":\"<urn:uuid:9f784985-c31d-4861-85cd-b76991ab6f89>\",\"WARC-IP-Address\":\"66.228.40.221\",\"WARC-Target-URI\":\"https://www.macroption.com/call-option-payoff/\",\"WARC-Payload-Digest\":\"sha1:AINTF5GIBI25GBYVLM3SPTD6G7RZSO2E\",\"WARC-Block-Digest\":\"sha1:76JPNFFCTJZXBWZ7N4H5K37TPFKM4XPF\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2021/CC-MAIN-2021-43/CC-MAIN-2021-43_segments_1634323587593.0_warc_CC-MAIN-20211024173743-20211024203743-00370.warc.gz\"}"} |
https://www.physicsforums.com/threads/newtons-law-problem.385499/ | [
"# Newtons Law Problem\n\n## Homework Statement\n\nA hot - air balloon experiences an acceleration of 1.10 m/s^2 [down]. The total mass of the balloon, the basket, and the contents of the basket is 315 kg.\n\nThe balloonist wishes to change the acceleration to zero. There is no fuel left to heat the air in the balloon. Determine the mass of the ballast that must be discarded overboard. [NEGLECT AIR RESISTANCE]\n\n## Homework Equations\n\nNewtons second law equation : F = mA\n\nFree body diagrams are also important\n\n## The Attempt at a Solution\n\nI drew a free body diagram for the hot air balloon and I noticed there were two forces: The force of gravity and the upward (buoyant) force on the system. I calculated the upward force on the system to be approximately 2.7 * 10^3 N [up].\n\nHowever I'm totally stuck on what to do next.\n\ncollinsmark\nHomework Helper\nGold Member\nHello Ballox,\n\nWelcome to Physics Forums!\n\nI assume you know the gravitational force is equal to mg. The goal is to set the gravitational force equal to the buoyant force. \"g\" isn't about to change any time soon, so...",
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"I am not sure how buoyant forces work. Does this buoyant change when force of gravity changes? If so, what is the formula for buoyant force?\n\nHello Ballox,\n\nWelcome to Physics Forums!\n\nI assume you know the gravitational force is equal to mg. The goal is to set the gravitational force equal to the buoyant force. \"g\" isn't about to change any time soon, so...",
null,
"So setting the gravitational force equal to the buoyant force would be:\n\nmG = 2.7 * 10^3 N [up] ( I rounded this, it really should be around 2740.5 N)\n\nWhich we would solve for m as : 279.6 kg.\n\nBut this gives us the mass when when the gravitational force is equal to the buoyant force...so we have to subtract this mass from the mass of the entire system to determine the amount of mass that must be discarded overboard.\n\nSo I get :\n\n315 KG - 279.6KG ~ 35 kg.\n\n^\nSo I get the answer in the textbook! ^^;\n\nIs this the right approach?\n\ncollinsmark\nHomework Helper\nGold Member\nSo I get :\n\n315 KG - 279.6KG ~ 35 kg.\n\n^\nSo I get the answer in the textbook! ^^;\n\nIs this the right approach?\n\nLooks good to me!",
null,
"Looks good to me!",
null,
""
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https://www.r-bloggers.com/2009/07/r-string-processing/ | [
"Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.",
null,
"Here’s a little vignette of data munging using the regular expression facilities of R (aka the R-project for statistical computing). Let’s say I have a vector of strings that looks like this:\n\n```> coords\n \"chromosome+:157470-158370\" \"chromosome+:158370-158450\" \"chromosome+:158450-158510\"\n \"chromosome+:158510-159330\" \"chromosome-:157460-158560\" \"chromosome-:158560-158920\"```\n\nWhat I’d like to do is parse these out into a data.frame with a column for each of sequence, strand, start, end. A regex that would do that kind of thing looks like this: (.*)([+-]):(d+)-(d+). R does regular expressions, but it’s missing a few pieces. For example, in python you might say:\n\n```import re\n\ncoords = \"\"\"\nchromosome+:157470-158370\nchromosome+:158370-158450\nchromosome+:158450-158510\nchromosome+:158510-159330\nchromosome-:157460-158560\nchromosome-:158560-158920\n\"\"\"\n\nregex = re.compile(\"(.*)([+-]):(\\d+)-(\\d+)\")\n\nfor line in coords.split(\"n\"):\nline = line.strip()\nif (len(line)==0): continue\nm = regex.match(line)\nif (m):\nseq = m.group(1)\nstrand = m.group(2)\nstart = int(m.group(3))\nend = int(m.group(4))\nprint \"%st%st%dt%d\" % (seq, strand, start, end)\n```\n\nAs far as I’ve found, there doesn’t seem to be an equivalent in R to regex.match, which is a shame. The gsub function supports capturing groups in regular expressions, but isn’t very flexible about what you do with them. One way to solve this problem is to use gsub to pull out each individual column. Not efficient, but it works:\n\n```> coords.df = data.frame(\nseq=gsub(\"(.*)([+-]):(\\d+)-(\\d+)\", \"\\1\", row.names(m), perl=T),\nstrand=gsub(\"(.*)([+-]):(\\d+)-(\\d+)\", \"\\2\", row.names(m), perl=T),\nstart=as.integer(gsub(\"(.*)([+-]):(\\d+)-(\\d+)\", \"\\3\", row.names(m), perl=T)),\nend=as.integer(gsub(\"(.*)([+-]):(\\d+)-(\\d+)\", \"\\4\", row.names(m), perl=T)))\n> coords.df\nseq strand start end\n1 chromosome + 157470 158370\n2 chromosome + 158370 158450\n3 chromosome + 158450 158510\n4 chromosome + 158510 159330\n5 chromosome - 157460 158560\n6 chromosome - 158560 158920```\n\nIt seems strange that R doesn’t have a more direct way of accomplishing this. I’m not an R expert, so maybe it’s there and I’m missing it. I guess it’s not called the R project for string processing, but still… By the way, if you’re ever tempted to name a project with a single letter, consider the poor schmucks trying to google for help."
] | [
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https://momecentric.com/second-grade-math-worksheets/collection-of-second-grade-math-worksheets-missing-numbers-download-them-and-try-to-solve-number-square-estimating-root-worksheet-pdf/ | [
"### Home » second grade math worksheets » second grade math worksheets # | 97161",
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null,
""
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"https://secure.gravatar.com/avatar/b7f5c31118b00ae0c2d7a7f8d7f5d8fb",
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] | {"ft_lang_label":"__label__en","ft_lang_prob":0.6599503,"math_prob":0.6247506,"size":4328,"snap":"2019-43-2019-47","text_gpt3_token_len":836,"char_repetition_ratio":0.39037928,"word_repetition_ratio":0.14307459,"special_character_ratio":0.17490758,"punctuation_ratio":0.009022556,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.9792613,"pos_list":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104],"im_url_duplicate_count":[null,1,null,3,null,5,null,5,null,4,null,3,null,4,null,2,null,2,null,2,null,3,null,4,null,2,null,1,null,6,null,2,null,5,null,3,null,6,null,1,null,3,null,4,null,4,null,5,null,3,null,2,null,4,null,3,null,7,null,1,null,3,null,2,null,2,null,5,null,4,null,2,null,3,null,2,null,2,null,5,null,3,null,4,null,3,null,4,null,4,null,3,null,5,null,4,null,1,null,4,null,2,null,null,null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2019-11-17T08:51:21Z\",\"WARC-Record-ID\":\"<urn:uuid:152867b2-bbd0-4c0a-b01f-55adf7c18449>\",\"Content-Length\":\"65982\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:1ab1710d-4b84-407b-b527-0e314ac1b7da>\",\"WARC-Concurrent-To\":\"<urn:uuid:e2a5331d-b9e4-4e1b-be2a-7d7005c43896>\",\"WARC-IP-Address\":\"104.28.8.21\",\"WARC-Target-URI\":\"https://momecentric.com/second-grade-math-worksheets/collection-of-second-grade-math-worksheets-missing-numbers-download-them-and-try-to-solve-number-square-estimating-root-worksheet-pdf/\",\"WARC-Payload-Digest\":\"sha1:P7QXVEDPSC7KDKYDQ6UJGDQIVB5PRKQQ\",\"WARC-Block-Digest\":\"sha1:JNKQHHBELA4FHMX6I3OQK54LIRGLR746\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2019/CC-MAIN-2019-47/CC-MAIN-2019-47_segments_1573496668896.47_warc_CC-MAIN-20191117064703-20191117092703-00340.warc.gz\"}"} |
http://archive.snoot.org/scribble/19.08/20.16.32.17-1060.html | [
"``` 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5\nA V I T E S S E S - - - - - - J\nB - - - - - - - O - - - R - Y O\nC - - - - - - - P E G G E D - I\nD - - - - - - - - - - - M O R N\nE - - - - - - - - - - - I - - T\nF K - W - - - - - - - A X L E -\nG O - O - - - - - - - - E - R -\nH B R O W - - - Q U A D S - A G\nI O - - I - - Z A P - O - - - U\nJ L - - T - - I T - - N - - - I\nK D - - C - - N - - - U - B I D\nL - - - H A E - M E A T Y - F A\nM - - - - - F L A N - - A H - N\nN - - E - - - - R - - - - I - C\nO V I R U L E N T - - - - E - E\n```\n\nGame 4, Score: 1060 tray:\n\n30. bid by 72.78.33.158 (Cache).\n29. yo by 108.189.117.64.\n28. kobold by 100.0.54.125 (PT-USA).\n27. vitesses by 121.98.69.43 (CatherineNZ).\n26. woo by 100.0.54.125 (PT-USA).\n25. er by 121.98.69.43 (CatherineNZ).\n24. if by 100.0.54.125 (PT-USA).\n23. hie by 121.98.69.43 (CatherineNZ).\n22. op by 100.0.54.125 (PT-USA).\n21. pegged by 121.98.69.43 (CatherineNZ).\n20. ya by 100.0.54.125 (PT-USA).\n19. zin by 108.189.117.64.\n18. zap by 100.0.54.125 (PT-USA).\n17. row by 108.189.117.64.\n16. qat by 100.0.54.125 (PT-USA).\n15. remixes by 108.189.117.64: a12d.premixes\n14. witch by 100.0.54.125 (PT-USA).\n13. ae by 121.98.69.43 (CatherineNZ): excellent\n12. virulent by 100.0.54.125 (PT-USA).\n11. flan by 121.98.69.43 (CatherineNZ).\n10. joint by 24.187.21.74.\n9. morn by 108.189.117.64.\n8. mar by 100.0.54.125 (PT-USA).\n7. guidance by 121.98.69.43 (CatherineNZ).\n6. era by 108.189.117.64.\n5. eat by 100.0.54.125 (PT-USA).\n4. axle by 108.189.117.64.\n3. mixes by 24.187.21.74.\n2. donut by 121.98.69.43 (CatherineNZ).\n1. qua by 108.189.117.64."
] | [
null
] | {"ft_lang_label":"__label__en","ft_lang_prob":0.67987645,"math_prob":0.9724232,"size":1709,"snap":"2020-24-2020-29","text_gpt3_token_len":860,"char_repetition_ratio":0.27507332,"word_repetition_ratio":0.12383178,"special_character_ratio":0.72322994,"punctuation_ratio":0.27450982,"nsfw_num_words":1,"has_unicode_error":false,"math_prob_llama3":0.9720853,"pos_list":[0],"im_url_duplicate_count":[null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2020-07-14T01:20:41Z\",\"WARC-Record-ID\":\"<urn:uuid:c2519dd2-0833-4e30-be15-996b68121e9f>\",\"Content-Length\":\"2691\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:7b9821c7-39c6-4af8-8ed8-f3fe70f7bfaf>\",\"WARC-Concurrent-To\":\"<urn:uuid:829397e6-ed48-4cc7-81d4-104535677533>\",\"WARC-IP-Address\":\"108.166.114.198\",\"WARC-Target-URI\":\"http://archive.snoot.org/scribble/19.08/20.16.32.17-1060.html\",\"WARC-Payload-Digest\":\"sha1:A2ZDVPHINN43ELZVY2YSVYDTN7T4OXCI\",\"WARC-Block-Digest\":\"sha1:H3Z7MFT4ILKX3KICR7U2ZZ5DWXSSZTGP\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2020/CC-MAIN-2020-29/CC-MAIN-2020-29_segments_1593657147031.78_warc_CC-MAIN-20200713225620-20200714015620-00396.warc.gz\"}"} |
https://encyclopediaofmath.org/index.php?title=Non-smoothable_manifold&oldid=51871 | [
"# Non-smoothable manifold\n\n(diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)\n\nA piecewise-linear or topological manifold that does not admit a smooth structure.\n\nA smoothing of a piecewise-linear manifold $X$ is a piecewise-linear isomorphism $f : M \\rightarrow X$, where $M$ is a smooth manifold. Manifolds that do not admit smoothings are said to be non-smoothable. With certain modifications this is also applicable to topological manifolds.\n\nExample of a non-smoothable manifold. Let $W ^ {4k}$, $k > 1$, be a $4 k$-dimensional Milnor manifold (see Dendritic manifold). In particular, $W ^ {4k}$ is parallelizable, its signature is 8, and its boundary $M = \\partial W ^ {4k}$ is homotopy equivalent to the sphere $S ^ {4k- 1}$. Glueing to $W$ a cone $C M$ over $\\partial W$ leads to the space $P ^ {4k}$. Since $M$ is a piecewise-linear sphere (see generalized Poincaré conjecture), $C M$ is a piecewise-linear disc, so that $P$ is a piecewise-linear manifold. On the other hand, $P$ is non-smoothable, since its signature is 8, while that of an almost-parallelizable (that is, parallelizable after removing a point) $4$-dimensional manifold is a multiple of a number $\\sigma _ {k}$ that grows exponentially with $k$. The manifold $M$ is not diffeomorphic to the sphere $S ^ {k- 1}$, that is, $M$ is a Milnor sphere.\n\nA criterion for a piecewise-linear manifold to be smoothable is as follows. Let $\\mathop{\\rm O} _ {n}$ be the orthogonal group and let $\\mathop{\\rm PL} _ {n}$ be the group of piecewise-linear homeomorphisms of $\\mathbf R ^ {n}$ preserving the origin (see Piecewise-linear topology). The inclusion $\\mathop{\\rm O} _ {n} \\rightarrow \\mathop{\\rm PL} _ {n}$ induces a fibration $B \\mathop{\\rm O} _ {n} \\rightarrow B \\mathop{\\rm PL} _ {n}$, where $B G$ is the classifying space of a group $G$. As $n \\rightarrow \\infty$ there results a fibration $p : B \\mathop{\\rm O} \\rightarrow B \\mathop{\\rm PL}$, the fibre of which is denoted by $M / \\mathop{\\rm O}$. A piecewise-linear manifold $X$ has a linear stable normal bundle $u$ with classifying mapping $v : X \\rightarrow B \\mathop{\\rm PL}$. If $X$ is smoothable (or smooth), then it has a stable normal bundle $\\overline{v}$ with classifying mapping $\\overline{v} : X \\rightarrow B \\mathop{\\rm O}$ and $p \\circ \\overline{v} = v$. This condition is also sufficient, that is, a closed piecewise-linear manifold $X$ is smoothable if and only if its piecewise-linear stable normal bundle admits a vector reduction, that is, if the mapping $v : X \\rightarrow B \\mathop{\\rm PL}$ can be \"lifted\" to $B \\mathop{\\rm O}$ (there is a $\\overline{v} : X \\rightarrow B \\mathop{\\rm O}$ such that $p \\circ \\overline{v} = v$).\n\nTwo smoothings $f : M \\rightarrow X$ and $g : N \\rightarrow X$ are said to be equivalent if there is a diffeomorphism $h : M \\rightarrow N$ such that $h f ^ { - 1 }$ is piecewise differentiably isotopic to $g ^ {- 1}$ (see Structure on a manifold). The sets $\\mathop{\\rm ts} ( X)$ of equivalence classes of smoothings are in a natural one-to-one correspondence with the fibre-wise homotopy classes of liftings $\\overline{v} : X \\rightarrow B \\mathop{\\rm O}$ of $v : X \\rightarrow B \\mathop{\\rm PL}$. In other words, when $X$ is smoothable, $\\mathop{\\rm ts} ( X) = [ X , \\mathop{\\rm PL} / \\mathop{\\rm O} ]$.\n\nHow to Cite This Entry:\nNon-smoothable manifold. Encyclopedia of Mathematics. URL: http://encyclopediaofmath.org/index.php?title=Non-smoothable_manifold&oldid=51871\nThis article was adapted from an original article by Yu.I. Rudyak (originator), which appeared in Encyclopedia of Mathematics - ISBN 1402006098. See original article"
] | [
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] | {"ft_lang_label":"__label__en","ft_lang_prob":0.70085824,"math_prob":0.99871445,"size":4095,"snap":"2023-14-2023-23","text_gpt3_token_len":1249,"char_repetition_ratio":0.17526278,"word_repetition_ratio":0.09568733,"special_character_ratio":0.31892553,"punctuation_ratio":0.13517061,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.99996233,"pos_list":[0],"im_url_duplicate_count":[null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2023-03-29T06:14:43Z\",\"WARC-Record-ID\":\"<urn:uuid:2e702981-97b1-4de5-9ad1-05208250b3b6>\",\"Content-Length\":\"20024\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:77cf482c-cee4-4fcd-9702-1099a739dea2>\",\"WARC-Concurrent-To\":\"<urn:uuid:f4f3b814-9b6f-4831-8977-04b4c136cb9e>\",\"WARC-IP-Address\":\"34.96.94.55\",\"WARC-Target-URI\":\"https://encyclopediaofmath.org/index.php?title=Non-smoothable_manifold&oldid=51871\",\"WARC-Payload-Digest\":\"sha1:66Q3KRG3T4KC6HFBYCGTXKT5LC2FZGPB\",\"WARC-Block-Digest\":\"sha1:J5DMX2IYOABWOYJXYQT2YPSJXJW4V6UD\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2023/CC-MAIN-2023-14/CC-MAIN-2023-14_segments_1679296948951.4_warc_CC-MAIN-20230329054547-20230329084547-00714.warc.gz\"}"} |
https://e2e.ti.com/support/data-converters-group/data-converters/f/data-converters-forum/1128735/ads124s08evm-measure-thermistor-with-ads124s08evm?tisearch=e2e-sitesearch&keymatch=ADS124S08EVM | [
"If you have a related question, please click the \"Ask a related question\" button in the top right corner. The newly created question will be automatically linked to this question.\n\nHi,\n\nI am using ADS124S08EVM board to measure a thermistor.\n\nI use 2-wire RTD measurement circuit for this thermistor. The circuit is using Figure 15 of UM of EVM. The thermistor is connected to J7 pin 1 and 4. I use Evaluation software to setup the registers and get the reading. but I can not get correct reading somehow. All readings are 2.5V.\n\nThe registers setting from 0x02 to 0x07 are: 0x10, 0x08, 0x14, 0x14, 0x03, 0xF5.\n\nWhat do I miss?\n\n• Hi Jeff,\n\nIt appears that you want to make a current excited ratiometric measurement. To use the IDACs, the internal reference must be enabled even if the internal reference is not used for the conversion reference. The IDACs use the internal reference to establish the IDAC output current value. As you have no reference voltage (because there is not current), the output will always be full-scale.\n\nThe second consideration is that the reference resistor used on the EVM is 1k Ohm (R68) and is designed for using PT100 RTDs. The IDAC output current chosen is 100uA establishing a reference voltage of 0.1V. The minimum reference voltage required by the ADS124S08 is 0.5V. So you will either need to replace R68 with a higher value resistor, or use a different reference voltage. I would suggest that initially you turn on the internal reference and select it as the conversion reference for your initial checkout of the circuit.\n\nBest regards,\n\nBob B\n\n• Hi Bob,\n\nIs the REFCON bits controls internal references? I tried leave it on (REF register :0x1A). But I don't see the reading changes.\n\nFor your second point, what if I select 1mA IDAC current? It will be 1V cross R68.\n\nBut with both changes, I still didn't get good readings.\n\nRegards,\n\nJeff\n\n• I think my setup may have problem. The thermistor is 10kohm at 25C. As you mentioned, the R68 is too low for it. if I increase the IDAC, the voltage cross the thermistor will over the ADC input range. The reference resistance should be large than Thermistor resistance.\n\nNow I am thinking to use figure 19 circuit. in this circuit, the REFP0/REFN0 is connected to J8 pin1 and 4. Are they used in the measurement?\n\nThanks,\n\nJeff\n\n• Hi Jeff,\n\nYou are correct that the REFCON bits select the configuration of the internal reference. When the REF register is 0x1A, the internal reference is used and powered on. In your original configuration 1mA will be an issue with the 10k thermistor as the largest analog voltage that can be applied is 5V. There is also a compliance voltage for the IDAC where the voltage drop across the entire current path must be less than AVDD - 0.4V for currents less than 1mA and AVDD - 0.6V for currents 1mA or greater or the current source cannot maintain constant current.\n\nFigure 19 from the EVM user's guide is a voltage excited thermistor circuit example. In this example, the thermistor value is calculated from the known resistance of a voltage divider. You don't have to use REF0 inputs as the ADC reference, but it is probably easiest to do so with the EVM.\n\nBest regards,\n\nBob B"
] | [
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] | {"ft_lang_label":"__label__en","ft_lang_prob":0.8404284,"math_prob":0.74858314,"size":484,"snap":"2023-14-2023-23","text_gpt3_token_len":154,"char_repetition_ratio":0.108333334,"word_repetition_ratio":0.0,"special_character_ratio":0.30165288,"punctuation_ratio":0.1682243,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.951786,"pos_list":[0],"im_url_duplicate_count":[null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2023-03-30T11:47:19Z\",\"WARC-Record-ID\":\"<urn:uuid:6b5a74ac-92b6-4d61-a8b9-453a34979c50>\",\"Content-Length\":\"168637\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:7e89c27f-b987-473d-b59a-34ba03aecf19>\",\"WARC-Concurrent-To\":\"<urn:uuid:19e51498-3765-42a0-8a6e-580fdeeccef7>\",\"WARC-IP-Address\":\"104.106.168.73\",\"WARC-Target-URI\":\"https://e2e.ti.com/support/data-converters-group/data-converters/f/data-converters-forum/1128735/ads124s08evm-measure-thermistor-with-ads124s08evm?tisearch=e2e-sitesearch&keymatch=ADS124S08EVM\",\"WARC-Payload-Digest\":\"sha1:WQFPNTRATRXKYAEETR755ULDXAE72XTG\",\"WARC-Block-Digest\":\"sha1:RUCYC3WFPVTFK5YTSJH4RQPTGEI4WNHU\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2023/CC-MAIN-2023-14/CC-MAIN-2023-14_segments_1679296949181.44_warc_CC-MAIN-20230330101355-20230330131355-00614.warc.gz\"}"} |
https://www.gradesaver.com/textbooks/math/trigonometry/CLONE-68cac39a-c5ec-4c26-8565-a44738e90952/appendix-d-graphing-techniques-exercises-page-448/18 | [
"Trigonometry (11th Edition) Clone",
null,
"Appendix D - 12 (Solution) For $y = 3 x^2$, When $x = 3, y = 27;$ $x = 2, y = 12;$ $x = 0, y = 0;$ $x = −2, y = 12;$ $x = −3, y = 27$ Domain = $(−\\infty, \\infty)$ Range = $[0, \\infty)$ See Graph I"
] | [
null,
"https://gradesaver.s3.amazonaws.com/uploads/solution/13903340-067b-4188-ad7a-d70ef56b9725/result_image/1506427101.jpg",
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] | {"ft_lang_label":"__label__en","ft_lang_prob":0.5675808,"math_prob":1.00001,"size":258,"snap":"2019-43-2019-47","text_gpt3_token_len":123,"char_repetition_ratio":0.17322835,"word_repetition_ratio":0.032786883,"special_character_ratio":0.5542636,"punctuation_ratio":0.1904762,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":1.0000086,"pos_list":[0,1,2],"im_url_duplicate_count":[null,1,null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2019-10-17T16:12:05Z\",\"WARC-Record-ID\":\"<urn:uuid:8dd752a9-4e76-4080-80dc-e33d0f4c4c0a>\",\"Content-Length\":\"55821\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:e37be967-3337-4ec7-9288-7887b144f938>\",\"WARC-Concurrent-To\":\"<urn:uuid:a29a4f3b-0f50-4784-bfa4-a33ae7ab0245>\",\"WARC-IP-Address\":\"3.90.134.5\",\"WARC-Target-URI\":\"https://www.gradesaver.com/textbooks/math/trigonometry/CLONE-68cac39a-c5ec-4c26-8565-a44738e90952/appendix-d-graphing-techniques-exercises-page-448/18\",\"WARC-Payload-Digest\":\"sha1:3V6B5TZNNZ67UTK4ZZKE7HLLK4JPFLJM\",\"WARC-Block-Digest\":\"sha1:ES3ZHL6SL7DK56GYEL42RID3CLLRMACN\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2019/CC-MAIN-2019-43/CC-MAIN-2019-43_segments_1570986675409.61_warc_CC-MAIN-20191017145741-20191017173241-00325.warc.gz\"}"} |
https://socoder.net/?Workshop=Find&Entry=288 | [
"-=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- (c) WidthPadding Industries 1987 0|533|0 -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=-",
null,
"### Avoider : Extreme\n\nby mole for Workshop #126\n\"So damn exciting I can't keep my hat straight!\"\nMouse\n\nClick to download this entry"
] | [
null,
"https://socoder.net/workshop/dlds/126_ae.gif",
null
] | {"ft_lang_label":"__label__en","ft_lang_prob":0.79672116,"math_prob":1.0000038,"size":263,"snap":"2021-21-2021-25","text_gpt3_token_len":65,"char_repetition_ratio":0.08494209,"word_repetition_ratio":0.8888889,"special_character_ratio":0.26996198,"punctuation_ratio":0.083333336,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":1.00001,"pos_list":[0,1,2],"im_url_duplicate_count":[null,null,null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2021-06-22T11:34:06Z\",\"WARC-Record-ID\":\"<urn:uuid:f62713dc-414e-4582-868b-2b0c44ae236e>\",\"Content-Length\":\"20333\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:15593e26-50c7-43f7-a16d-43b6dbed132f>\",\"WARC-Concurrent-To\":\"<urn:uuid:1d0af1e5-cd54-445a-9e32-a85efe8042ec>\",\"WARC-IP-Address\":\"88.80.187.139\",\"WARC-Target-URI\":\"https://socoder.net/?Workshop=Find&Entry=288\",\"WARC-Payload-Digest\":\"sha1:H5VUAJJSX6I5OEGE5FRRFFURAU5KJWNS\",\"WARC-Block-Digest\":\"sha1:PGWYFP73AILXFO5GHLG3SJTBFWGC6SDM\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2021/CC-MAIN-2021-25/CC-MAIN-2021-25_segments_1623488517048.78_warc_CC-MAIN-20210622093910-20210622123910-00312.warc.gz\"}"} |
https://cafedoing.com/half-life-worksheet/ | [
"# Half Life Worksheet\n\nSeconds seconds half lives will remain iodine has a half life of days. what fraction of the original sample would remain at the end of practice worksheet. sodium has a of hours. how much sodium will remain in an. g sample after hours after days a. g sample of phosphorus contains only.\n\ng of the isotope. what is the of phosphorus polonium has a relatively short Of total time d. d step set up a chart that shows the amount decaying by with the passing of each. What is the of a radioactive isotope if a.\n\n## List of Half Life Worksheet\n\nG sample decays to.g in. hours. how old is a bone if it presently contains.g of c, but it was estimated to have originally contained.g of c as seconds. days c years. title life worksheet extra practice solutions fluorine has a half life of approximately seconds.\n\nwhat fraction of the original nuclei would remain after minute the answer is solved by creating the fraction. where n the number of half lives. if each half life is seconds, then in one minute seconds there are half lives.View from sci at county high school.\n\n### 1. Bio Pharmacology Cell Transport Membrane",
null,
"Years. how many have passed in. years. of a radioactive sample are left. how many have passed after , how much of a gram sample of radioactive uranium remains.Half life displaying top worksheets found for half life. some of the worksheets for this concept are, half life work,, half life, half life graph work name date class, half life work, radioactive decay half life work, half life practice work.\n\nfound worksheet you are looking, worksheet name use reference table on side to assist you in answering the following questions. equations as seconds. life with answer half life with answer displaying top worksheets found for this concept. some of the worksheets for this concept are half life work, atoms half life questions and answers, half life of paper pennies puzzle pieces licorice, half life,, radioactive decay half life work,, half life Whats worksheet this worksheet defines radioactive isotopes and and provides examples of radioactive decay applications.\n\n### 2. Radioactive Decay Life Equations Real Number System Quadratics",
null,
"### 3. Martian Periodic Table Worksheet Answers Life Relative Atomic Mass",
null,
"Eu.To find the worksheets, solutions, and answer keys, go to httpswww.teacherspayteachers.comproductapesmathreviewandpracticebundlewith by noting that the final pressure is the initial pressure, the answer comes quickly. the pressure drops to half its original value in the first half life, and half of that in the second half life.\n\n### 4. Nova Worksheet Online Teachers Student Handout 4 Cracking Code Life Biology Lessons Science Classroom",
null,
"### 5. Nuclear Chemistry Worksheet Doc Worksheets Math Review",
null,
"### 6. Nuclear Decay Element Visual Life Chemistry Worksheets Teaching",
null,
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"Part data observations start time shake. This resource is also part of the nuclear chemistry bundle this problems leprechaun themed worksheet is a worksheet that helps students practice setting up simple decay tables. the students have to figure out how much of a substance will be left after a given amount, half of what remains decay in the next, and half of those in the next, and so on.\n\nthis is an exponential decay, as seen in the graph of the number of nuclei present as a function of time. there is a tremendous range in the of various, from as short as s for the most unstable, to more than y.Created date this quiz worksheet. the following quiz and worksheet will help measure your knowledge of in medicine.\n\n### 30. Collision Theory Worksheet Answers Student Guide Theories",
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null,
". . billion. billion isotopes, atoms with unstable nuclei, decay over time. as they decay they give off radiation.Doubling time and half life worksheet. problem the number of rabbits in a certain population doubles every days. if the population starts with rabbits, what will the population of rabbits be days from now problem the population of a western town doubles in size every years.\n\nif the population of town is,, what will the.When your teacher calls, divide your number of radioactive atoms by in half and write the new number in the box labeled in table. the of isotope x is. years.hovmany y would i take for a. mg sample of x to decay and have only.\n\n### 42. Life Radioactive Isotopes Worksheet",
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null,
"It outlines an engaging activity using everyday items to simulate radioactive decay to calculate. Oct, worksheet revising the equations and for the radioactivity topic. questions on activity, decay equations, and half life. answer sheet data worksheet name date follow and answer.\n\nthe following image shows how uranium a radioactive element decays and changes to a stable element lead. the of each element is shown in years and days.This worksheet allows students to practice solving all types of problems involving. a complete answer key is provided at the end.\n\nHalf life practice. what is meant by. if you have grams of a radioactive isotope with a of Half life some of the worksheets for this concept are, half life work,, half life, half life graph work name date class, half life work, radioactive decay half life work, half life practice work.\n\nHalf life of radioactive isotopes.docx open new edit your docs with word online. half life of radioactive isotopes name date. carbon is a radioactive isotope found in small amounts in all living things. when the living thing dies, the carbon begins to decay at a steady rate with a half life practice worksheet name period date the of cobalt is."
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https://www.sanfoundry.com/java-program-implement-hash-tables-linear-probing/ | [
"# Java Program to Implement Hash Tables with Linear Probing\n\n«\n»\nThis is a Java Program to implement hash tables with Linear Probing. A hash table (also hash map) is a data structure used to implement an associative array, a structure that can map keys to values. A hash table uses a hash function to compute an index into an array of buckets or slots, from which the correct value can be found. Linear probing is a probe sequence in which the interval between probes is fixed (usually 1).\n\nHere is the source code of the Java program to implement hash tables with Linear Probing. The Java program is successfully compiled and run on a Windows system. The program output is also shown below.\n\n1. `/**`\n2. ` * Java Program to implement Linear Probing Hash Table`\n3. ` **/ `\n4. ` `\n5. `import java.util.Scanner;`\n6. ` `\n7. ` `\n8. `/** Class LinearProbingHashTable **/`\n9. `class LinearProbingHashTable`\n10. `{`\n11. ` private int currentSize, maxSize; `\n12. ` private String[] keys; `\n13. ` private String[] vals; `\n14. ` `\n15. ` /** Constructor **/`\n16. ` public LinearProbingHashTable(int capacity) `\n17. ` {`\n18. ` currentSize = 0;`\n19. ` maxSize = capacity;`\n20. ` keys = new String[maxSize];`\n21. ` vals = new String[maxSize];`\n22. ` } `\n23. ` `\n24. ` /** Function to clear hash table **/`\n25. ` public void makeEmpty()`\n26. ` {`\n27. ` currentSize = 0;`\n28. ` keys = new String[maxSize];`\n29. ` vals = new String[maxSize];`\n30. ` }`\n31. ` `\n32. ` /** Function to get size of hash table **/`\n33. ` public int getSize() `\n34. ` {`\n35. ` return currentSize;`\n36. ` }`\n37. ` `\n38. ` /** Function to check if hash table is full **/`\n39. ` public boolean isFull() `\n40. ` {`\n41. ` return currentSize == maxSize;`\n42. ` }`\n43. ` `\n44. ` /** Function to check if hash table is empty **/`\n45. ` public boolean isEmpty() `\n46. ` {`\n47. ` return getSize() == 0;`\n48. ` }`\n49. ` `\n50. ` /** Fucntion to check if hash table contains a key **/`\n51. ` public boolean contains(String key) `\n52. ` {`\n53. ` return get(key) != null;`\n54. ` }`\n55. ` `\n56. ` /** Functiont to get hash code of a given key **/`\n57. ` private int hash(String key) `\n58. ` {`\n59. ` return key.hashCode() % maxSize;`\n60. ` } `\n61. ` `\n62. ` /** Function to insert key-value pair **/`\n63. ` public void insert(String key, String val) `\n64. ` { `\n65. ` int tmp = hash(key);`\n66. ` int i = tmp;`\n67. ` do`\n68. ` {`\n69. ` if (keys[i] == null)`\n70. ` {`\n71. ` keys[i] = key;`\n72. ` vals[i] = val;`\n73. ` currentSize++;`\n74. ` return;`\n75. ` }`\n76. ` if (keys[i].equals(key)) `\n77. ` { `\n78. ` vals[i] = val; `\n79. ` return; `\n80. ` } `\n81. ` i = (i + 1) % maxSize; `\n82. ` } while (i != tmp); `\n83. ` }`\n84. ` `\n85. ` /** Function to get value for a given key **/`\n86. ` public String get(String key) `\n87. ` {`\n88. ` int i = hash(key);`\n89. ` while (keys[i] != null)`\n90. ` {`\n91. ` if (keys[i].equals(key))`\n92. ` return vals[i];`\n93. ` i = (i + 1) % maxSize;`\n94. ` } `\n95. ` return null;`\n96. ` }`\n97. ` `\n98. ` /** Function to remove key and its value **/`\n99. ` public void remove(String key) `\n100. ` {`\n101. ` if (!contains(key)) `\n102. ` return;`\n103. ` `\n104. ` /** find position key and delete **/`\n105. ` int i = hash(key);`\n106. ` while (!key.equals(keys[i])) `\n107. ` i = (i + 1) % maxSize; `\n108. ` keys[i] = vals[i] = null;`\n109. ` `\n110. ` /** rehash all keys **/ `\n111. ` for (i = (i + 1) % maxSize; keys[i] != null; i = (i + 1) % maxSize)`\n112. ` {`\n113. ` String tmp1 = keys[i], tmp2 = vals[i];`\n114. ` keys[i] = vals[i] = null;`\n115. ` currentSize--; `\n116. ` insert(tmp1, tmp2); `\n117. ` }`\n118. ` currentSize--; `\n119. ` } `\n120. ` `\n121. ` /** Function to print HashTable **/`\n122. ` public void printHashTable()`\n123. ` {`\n124. ` System.out.println(\"\\nHash Table: \");`\n125. ` for (int i = 0; i < maxSize; i++)`\n126. ` if (keys[i] != null)`\n127. ` System.out.println(keys[i] +\" \"+ vals[i]);`\n128. ` System.out.println();`\n129. ` } `\n130. `}`\n131. ` `\n132. `/** Class LinearProbingHashTableTest **/`\n133. `public class LinearProbingHashTableTest`\n134. `{`\n135. ` public static void main(String[] args)`\n136. ` {`\n137. ` Scanner scan = new Scanner(System.in);`\n138. ` System.out.println(\"Hash Table Test\\n\\n\");`\n139. ` System.out.println(\"Enter size\");`\n140. ` /** maxSizeake object of LinearProbingHashTable **/`\n141. ` LinearProbingHashTable lpht = new LinearProbingHashTable(scan.nextInt() );`\n142. ` `\n143. ` char ch;`\n144. ` /** Perform LinearProbingHashTable operations **/`\n145. ` do `\n146. ` {`\n147. ` System.out.println(\"\\nHash Table Operations\\n\");`\n148. ` System.out.println(\"1. insert \");`\n149. ` System.out.println(\"2. remove\");`\n150. ` System.out.println(\"3. get\"); `\n151. ` System.out.println(\"4. clear\");`\n152. ` System.out.println(\"5. size\");`\n153. ` `\n154. ` int choice = scan.nextInt(); `\n155. ` switch (choice)`\n156. ` {`\n157. ` case 1 : `\n158. ` System.out.println(\"Enter key and value\");`\n159. ` lpht.insert(scan.next(), scan.next() ); `\n160. ` break; `\n161. ` case 2 : `\n162. ` System.out.println(\"Enter key\");`\n163. ` lpht.remove( scan.next() ); `\n164. ` break; `\n165. ` case 3 : `\n166. ` System.out.println(\"Enter key\");`\n167. ` System.out.println(\"Value = \"+ lpht.get( scan.next() )); `\n168. ` break; `\n169. ` case 4 : `\n170. ` lpht.makeEmpty();`\n171. ` System.out.println(\"Hash Table Cleared\\n\");`\n172. ` break;`\n173. ` case 5 : `\n174. ` System.out.println(\"Size = \"+ lpht.getSize() );`\n175. ` break; `\n176. ` default : `\n177. ` System.out.println(\"Wrong Entry \\n \");`\n178. ` break; `\n179. ` }`\n180. ` /** Display hash table **/`\n181. ` lpht.printHashTable(); `\n182. ` `\n183. ` System.out.println(\"\\nDo you want to continue (Type y or n) \\n\");`\n184. ` ch = scan.next().charAt(0); `\n185. ` } while (ch == 'Y'|| ch == 'y'); `\n186. ` }`\n187. `}`\n\n```Hash Table Test\n\nEnter size\n5\n\nHash Table Operations\n\n1. insert\n2. remove\n3. get\n4. clear\n5. size\n1\nEnter key and value\nNa sodium\n\nHash Table:\nNa sodium\n\nDo you want to continue (Type y or n)\n\ny\n\nHash Table Operations\n\n1. insert\n2. remove\n3. get\n4. clear\n5. size\n1\nEnter key and value\nK potassium\n\nHash Table:\nNa sodium\nK potassium\n\nDo you want to continue (Type y or n)\n\ny\n\nHash Table Operations\n\n1. insert\n2. remove\n3. get\n4. clear\n5. size\n1\nEnter key and value\nFe iron\n\nHash Table:\nNa sodium\nK potassium\nFe iron\n\nDo you want to continue (Type y or n)\n\ny\n\nHash Table Operations\n\n1. insert\n2. remove\n3. get\n4. clear\n5. size\n1\nEnter key and value\nH hydrogen\n\nHash Table:\nNa sodium\nK potassium\nFe iron\nH hydrogen\n\nDo you want to continue (Type y or n)\n\ny\n\nHash Table Operations\n\n1. insert\n2. remove\n3. get\n4. clear\n5. size\n1\nEnter key and value\nHe helium\n\nHash Table:\nNa sodium\nK potassium\nFe iron\nH hydrogen\nHe helium\n\nDo you want to continue (Type y or n)\n\ny\n\nHash Table Operations\n\n1. insert\n2. remove\n3. get\n4. clear\n5. size\n1\nEnter key and value\nAg silver\n\nHash Table:\nNa sodium\nK potassium\nFe iron\nH hydrogen\nHe helium\n\nDo you want to continue (Type y or n)\n\ny\n\nHash Table Operations\n\n1. insert\n2. remove\n3. get\n4. clear\n5. size\n3\nEnter key\nFe\nValue = iron\n\nHash Table:\nNa sodium\nK potassium\nFe iron\nH hydrogen\nHe helium\n\nDo you want to continue (Type y or n)\n\ny\n\nHash Table Operations\n\n1. insert\n2. remove\n3. get\n4. clear\n5. size\n2\nEnter key\nH\n\nHash Table:\nNa sodium\nK potassium\nFe iron\nHe helium\n\nDo you want to continue (Type y or n)\n\ny\n\nHash Table Operations\n\n1. insert\n2. remove\n3. get\n4. clear\n5. size\n3\nEnter key\nH\nValue = null\n\nHash Table:\nNa sodium\nK potassium\nFe iron\nHe helium\n\nDo you want to continue (Type y or n)\n\ny\n\nHash Table Operations\n\n1. insert\n2. remove\n3. get\n4. clear\n5. size\n1\nEnter key and value\nAu gold\n\nHash Table:\nNa sodium\nK potassium\nFe iron\nHe helium\nAu gold\n\nDo you want to continue (Type y or n)\n\ny\n\nHash Table Operations\n\n1. insert\n2. remove\n3. get\n4. clear\n5. size\n5\nSize = 5\n\nHash Table:\nNa sodium\nK potassium\nFe iron\nHe helium\nAu gold\n\nDo you want to continue (Type y or n)\n\ny\n\nHash Table Operations\n\n1. insert\n2. remove\n3. get\n4. clear\n5. size\n4\nHash Table Cleared\n\nHash Table:\n\nDo you want to continue (Type y or n)\n\ny\n\nHash Table Operations\n\n1. insert\n2. remove\n3. get\n4. clear\n5. size\n5\nSize = 0\n\nHash Table:\n\nDo you want to continue (Type y or n)\n\nn```\n\nSanfoundry Global Education & Learning Series – 1000 Java Programs.",
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"data:image/svg+xml,%3Csvg%20xmlns=%22http://www.w3.org/2000/svg%22%20viewBox=%220%200%20150%20150%22%3E%3C/svg%3E",
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https://www.classcentral.com/course/swayam-finite-element-method-variational-methods-to-computer-programming-19868 | [
"Class Central is learner-supported. When you buy through links on our site, we may earn an affiliate commission.\n\n# Finite Element Method: Variational Methods to Computer Programming\n\n## Overview\n\nFinite Element Method (FEM) is one of the most popular numerical method to boundary and initial value problems. One distinct feature of FEM is that it can be generalized to the domains of any arbitrary geometry. Theory of FEM is developed on Variational methods. In this course, finite element formulations will be derived from the governing partial differential equation of different physical systems based on Variational methods. It will start with one-dimensional Bar, Beam, Truss, Frame elements; and will be extended to two-dimensional structural, and thermal problems. The framework of standard master element in both 1D and 2D will be followed, so that transformation for any arbitrary geometry is well understood. Two dimensional formulation will be represented in Tensorial framework, after building necessary background in Tensor calculus. Most importantly for every element, the basic code for computer implementation will be provided and explained with step-by-step clarification. We will also elaborately present how to prepare a generalized FEM code with first hand implementation.\nINTENDED AUDIENCE :\nFinal year Under Graduate Students, First year Post Graduate StudentsPREREQUISITES : Solid Mechanics, Engineering Mathematics: Linear Algebra, Vector CalculusINDUSTRIES SUPPORT :DRDO, ISRO, BARC, GE, Automobile and Aviation industries\n\n## Syllabus\n\n### COURSE LAYOUT\n\nWeek 1:Part1: Variational Methods:\nFunctional and Minimization of Functional; Derivation of Euler Lagrange equation: (a) First variation of Functional, (b) Delta operator Functional with (a) several dependent variables, (b) higher order derivatives; Variational statement Weak Form); Variational statement to Minimization problemRelation between Strong form, Variational statement and Minimization problem;Different approximation methods with Computer Programming: Galerkin, method, Weighted Residual method; Rayleigh Ritz methodWeek 2:Part 2. One dimensional Finite Element Analysis:\nGauss Quadrature integration rules with Computer Programming; Steps involved in Finite Element Analysis; Discrete system with linear springs;Continuous systems: Finite element equation for a given differential equation Linear Element: Explaining Assembly, Solution, Post- processing with Computer Programming Quadratic element with Computer Programming: Finite element equation, Assembly, Solution, Post-processing; Comparison of Linear and Quadratic elementWeek 3:Part 3. Structural Elements in One dimensional FEM:\nBar Element with Computer Programming: Variational statement from governing differential equation; Finite element equation, Element matrices, Assembly, Solution, Post-processing; Numerical example of conical bar under self-weight and axial point loads.Truss Element with Computer Programming: Orthogonal matrix, Element matrices, Assembly, Solution, Post-processing; Numerical exampleWeek 4:Beam Formulation: Variational statement from governing differential equation; Boundary terms; Hermite shape functions for beam element Beam Element with Computer Programming: Finite element equation, Element matrices, Assembly, Solution, Post-processing, Implementing arbitrary distributive load; Numerical example\nWeek 5:Frame Element with Computer Programming: Orthogonal matrix, Finite element equation; Element matrices, Assembly, Solution, Post- processing; Numerical example\nPart 4. Generalized 1D Finite Element code in Computer Programming:Step by step generalization for any no. of elements, nodes, any order Gaussian quadrature;Generalization of Assembly using connectivity data; Generalization of loading and imposition of boundary condition; Generalization of Post-processing using connectivity data;Week 6:Part 5. Brief background of Tensor calculus:Indicial Notation: Summation convention, Kronecker delta and permutation symbol, epsilon-delta identity; Gradient, Divergence, Curl, Laplacian; Gauss-divergence theorem: different formsWeek 7 & 8 :Part 6. Two dimensional Scalar field problems:\n2D Steady State Heat Conduction Problem, obtaining weakform, introduction to triangular and quadrilateral elements, deriving element stiffness matrix and force vector, incorporating different boundary conditions, numerical example.Computer implementation: obtaining connectivity and coordinate matrix, implementing numerical integration, obtaining global stiffness matrix and global force vector, incorporating boundary conditions and finally post-processing.Week 8 & 9:Part 7. Two dimensional Vector field problems:\n2D elasticity problem, obtaining weak form, introduction to triangular and quadrilateral elements, deriving element stiffness matrix and force vector, incorporating different boundary conditions, numerical example.Iso-parametric, sub-parametric and super-parametric elements Computer implementation: a vivid layout of a generic code will be discussed Convergence, Adaptive meshing, Hanging nodes, Post- processing, Extension to three dimensional problems Axisymmetric Problems: Formulation and numerical examples\nWeek 10:Part 8. Eigen value problems\nAxial vibration of rod (1D), formulation and implementation Transverse vibration of beams (2D), formulation and implementationWeek 11:Part 9. Transient problem in 1D & 2D Scalar Valued Problems\nTransient heat transfer problems, discretization in time : method of lines and Rothe method, Formulation and Computer implementationsWeek 12:Choice of solvers: Direct and iterative solvers\n\n### Taught by\n\nProf. Atanu Banerjee , Prof. Arup Nandy\n\n## Reviews\n\n0.0 rating, based on 0 reviews\n\nStart your review of Finite Element Method: Variational Methods to Computer Programming\n\n## Class Central\n\nGet personalized course recommendations, track subjects and courses with reminders, and more."
] | [
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https://math.stackexchange.com/questions/2791904/prove-that-mx-my | [
"# Prove that $MX=MY$.\n\nLet $\\triangle ABC$ an acute triangle and $O$ the middle of $[BC]$.\n\nLet $\\mathcal{C}$ the circle with center in $O$ and radius $OA$.\n\nLet $AB\\cap \\mathcal{C}=\\lbrace D \\rbrace$, $AC\\cap \\mathcal {C}=\\lbrace E \\rbrace$.\n\nWe denote the intersections of the tangents to $\\mathcal{C}$ id $D$ an $E$ with $M$.\n\nIf $P$ is the middle of $[AM]$ show that $PB=PC$.\n\nFirst I considered $AO\\cap BC=\\lbrace Z \\rbrace$. After that I draw the parallel to $BC$ trough $Z$ which intersects $AB$ in $X$ and $AC$ in $Y$.\n\nThen $BP$ and $CP$ are middle lines. So it's enough to prove that $MX=MY$.\n\n• I don't think such construction is possible for an acute triangle. Can you provide a picture? – Vasya May 22 '18 at 19:25\n• Possible duplicate of Show that $OB=OC$ – John McClane May 27 '18 at 16:20\n\n## 1 Answer\n\nLet $F$ be the point diametrically opposite to $A$ on $\\mathcal C$. Then $\\angle FDB = 90^{\\circ}$. Also note that $\\angle MDO = 90^{\\circ}$. Let $\\angle DBF=\\alpha$. $BACF$ is a parallelogram because $BO=OC$ and $AO=OF$. Thus, $\\angle DAE=\\alpha$. Clearly, $\\triangle DOM=\\triangle EOM$. Thus, $\\angle DOM=\\frac 1 2 \\angle DOE=\\angle DAE=\\alpha$. We have shown that $\\triangle DBF \\sim \\triangle DOM$. Now consider the rotational homothety with the center in $D$ that sends $M$ to $O$ (its angle is $90^{\\circ}$ and its factor is $\\cot \\alpha$). Clearly, it also sends $F$ to $B$. So it sends the segment $FM$ to $BO$ and $FM \\perp BO$. As $OP$ is a midline of $\\triangle FAM$, $OP \\parallel FM$ and $OP \\perp BO.$ Thus, $\\triangle BOP=\\triangle COP$."
] | [
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] | {"ft_lang_label":"__label__en","ft_lang_prob":0.729707,"math_prob":1.0000007,"size":573,"snap":"2021-21-2021-25","text_gpt3_token_len":193,"char_repetition_ratio":0.13005273,"word_repetition_ratio":0.0,"special_character_ratio":0.32984293,"punctuation_ratio":0.084033616,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":1.0000098,"pos_list":[0],"im_url_duplicate_count":[null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2021-06-15T23:35:02Z\",\"WARC-Record-ID\":\"<urn:uuid:36e67828-2aa3-4ad2-8173-91cbbd5e4e8e>\",\"Content-Length\":\"163321\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:67a56bda-e044-4eeb-8bb6-ec8ed2012065>\",\"WARC-Concurrent-To\":\"<urn:uuid:423e77d9-b3cf-4d76-9dfb-f067e4dca206>\",\"WARC-IP-Address\":\"151.101.193.69\",\"WARC-Target-URI\":\"https://math.stackexchange.com/questions/2791904/prove-that-mx-my\",\"WARC-Payload-Digest\":\"sha1:A7VUVZSF2FLFR7UFFEEETWRKWRJXJMJQ\",\"WARC-Block-Digest\":\"sha1:YYYU37T2WROAQTKWCDEYBO7BKT3554PH\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2021/CC-MAIN-2021-25/CC-MAIN-2021-25_segments_1623487621627.41_warc_CC-MAIN-20210615211046-20210616001046-00241.warc.gz\"}"} |
https://to-code.net/faq/how-to-automate-model-building-grid-search-cv-and-prediction-in-python/ | [
"# How to automate model building, grid search cv and prediction in python?\n\nPython is a great language for building predictive models. It’s easy to get started with, and has a wide variety of libraries available.\n\nIn this post, we’ll walk through how to automate the process of building a predictive model, using the scikit-learn library. We’ll cover how to:\n\n1. Preprocess data\n2. Build a model\n3. Grid search over model parameters\n4. Evaluate the model\n5. Make predictions\n\nThis process can be adapted to any predictive modeling problem, and will save you a lot of time and effort. Let’s get started!\n\nPreprocessing data\n\nThe first step in any predictive modeling problem is to preprocess the data. This usually involves cleaning up missing values, converting categorical variables to numeric form, and scaling the data.\n\nscikit-learn has a number of helpful functions for preprocessing data. We won’t go into too much detail here, but you can check out the scikit-learn documentation for more information.\n\nBuilding a model\n\nOnce the data is preprocessed, we can start building a predictive model. For this example, we’ll use a decision tree classifier.\n\nDecision trees are a popular machine learning algorithm, due to their interpretability and ease of use. They work by splitting the data up into a series of smaller pieces, called nodes. Each node represents a decision point, where the tree decides which branch to follow.\n\nscikit-learn makes it easy to build decision trees with the DecisionTreeClassifier class. We won’t go into too much detail here, but you can check out the scikit-learn documentation for more information.\n\nGrid search\n\nOnce we have a model, we need to tune its parameters to get the best performance. This is known as hyperparameter optimization, or grid search.\n\nGrid search is the process of systematically trying different values for a model’s hyperparameters, and selecting the best combination of values. This is usually done using cross-validation, to avoid overfitting on the training data.\n\nscikit-learn provides a handy function for doing grid search, called GridSearchCV. We won’t go into too much detail here, but you can check out the scikit-learn documentation for more information.\n\nEvaluating the model\n\nOnce we have a model that we’re happy with, we need to evaluate its performance on unseen data. This is usually done using a test set, which is a separate dataset that the model has not seen during training.\n\nWe can evaluate a model’s performance using a variety of metrics, such as accuracy, precision, recall, and F1 score. scikit-learn provides a number of handy functions for computing these metrics.\n\nMaking predictions\n\nOnce we have a trained model, we can use it to make predictions on new data\n\n## Other related questions:\n\n### How do you do a grid search in Python?\n\nThere are a few different ways to do a grid search in Python. One way is to use the scikit-learn library’s GridSearchCV tool. Another way is to use the Hyperopt library.\n\n### What is CV in GridSearchCV?\n\nThe CV in GridSearchCV stands for cross-validation. Cross-validation is a technique used to assess the accuracy of a model by training the model on a subset of the data and then testing it on the remaining data. This allows you to assess the model’s performance on data that it hasn’t seen during training, which can be more indicative of the model’s true performance.\n\n### How do you do a randomized search on a CV?\n\nThere is no one-size-fits-all answer to this question, as the specifics of how to do a randomized search on a CV will vary depending on the particular problem and search space. However, some tips on how to conduct a randomized search on a CV include:\n\n1. Define a search space: This should be done based on knowledge of the problem and desired outcome.\n\n2. Sample points randomly from the search space: This can be done using a simple random sampling method or a more sophisticated technique such as Latin hypercube sampling.\n\n3. Evaluate the sampled points: This can be done using a cross-validation method.\n\n4. Select the best point: This can be done based on some metric such as accuracy or error rate.\n\nThere is no one-size-fits-all answer to this question, as the best parameters for your model will depend on the specific data and problem you are working on. However, GridSearchCV is a useful tool that can help you optimize your model by systematically trying different combinations of parameters."
] | [
null
] | {"ft_lang_label":"__label__en","ft_lang_prob":0.8849266,"math_prob":0.78283685,"size":4398,"snap":"2023-14-2023-23","text_gpt3_token_len":917,"char_repetition_ratio":0.11629495,"word_repetition_ratio":0.10396717,"special_character_ratio":0.19736244,"punctuation_ratio":0.10477299,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.9581411,"pos_list":[0],"im_url_duplicate_count":[null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2023-03-30T20:34:32Z\",\"WARC-Record-ID\":\"<urn:uuid:36965a13-19b0-4f3d-b19f-5adc040f9443>\",\"Content-Length\":\"75400\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:9b4042c3-9f81-43e4-95d8-7543c08cb8d6>\",\"WARC-Concurrent-To\":\"<urn:uuid:6b26d3aa-faaf-4ed6-a291-8ea8a9649108>\",\"WARC-IP-Address\":\"198.136.62.208\",\"WARC-Target-URI\":\"https://to-code.net/faq/how-to-automate-model-building-grid-search-cv-and-prediction-in-python/\",\"WARC-Payload-Digest\":\"sha1:MAYJR62ASF4SAPQA6ISXWFHOZIRJADOD\",\"WARC-Block-Digest\":\"sha1:YCK22MSPIHH54BREGPAJSYDVU5J5W7I6\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2023/CC-MAIN-2023-14/CC-MAIN-2023-14_segments_1679296949387.98_warc_CC-MAIN-20230330194843-20230330224843-00158.warc.gz\"}"} |
http://dfhgt.com/cloumn/blog/1407 | [
"# 搭建语言环境\n\n## IDE 的选择\n\nPyCharm:这是一个跨平台的 Python 开发三分钟时时彩工具 ,不但拥有常规的调试、语法高亮,智能提示等功能外,还自带多个数据库连接器,使三分钟时时彩你 在调试数据库的时候也能得心应手,不再忙于到处三分钟时时彩下载 各种数据库客户端。\n\nJupyter:这个是一个 web 式的在线编辑器,每次运行一行代码,三分钟时时彩你 都可以立即得到结果,非常方便,在代码调试阶段,用处无限。\n\n# Python 基础语法\n\n## Hello World\n\n``````print(\"Hello World\")\nsum = 1 + 2\nprint(\"sum = %d\" %sum)\n>>>\nHello World\nsum = 3``````\n\nprint 函数,用来在控制台打印输出,sum = 语法是声明变量并赋值,%d 是用来做字符串替换。\n\n## 数据类型和变量\n\n``````list1 = [\"1\", \"2\", \"test\"]\nprint(list1)\nlist1.append(\"hello\")\nprint(lists)\n>>>\n['1', '2', 'test']\n['1', '2', 'test', 'hello']``````\n\nlist 是 Python 内置的一种数据类型,是一种有序的集合,可以随时添加和三分钟时时彩删除 其中的元素。\n\n``````tuple1 = (\"zhangsan\", \"lisi\")\nprint(tuple1)\n>>>\nzhangsan``````\n\ntuple 和 list 非常类似,但是 tuple 一旦初始化就不能修改。\n\n``````dict1 = {\"name1\": \"zhangsan\", \"name2\": \"lisi\", \"name3\": \"wangwu\"}\ndict1[\"name1\"]\n>>>\n'zhangsan'``````\n\nPython 内置了字典:dict 全称 dictionary,在其他语言中也称为 map,使用键-值(key-value)存储,具有极快的查找速度。\n\n``````s = set([1, 2, 3])\nprint(s)\n>>>\n{1, 2, 3}``````\n\nset 和 dict 类似,也是一组 key 的集合,但不存储 value。由于 key 不能重复,所以,在 set 中,没有重复的 key。\n\n``````a = 1\na = 3\nprint(a)\n>>>\n3``````\n\n## 条件判断\n\n``````age = 30\nif age >= 18:\nprint('good')\nelse:\n>>>\ngood``````\n\nif ... else... 是非常经典的条件判断语句,if 后面接条件表达式,如果成立,则执行下面的语句,否则执行 else 后面的语句。同时还要注意,Python 语言是采用代码缩进的方式来判断代码块的,一般是四个空格或者一个 tab,两者不要混用。\n\n## 循环语句\n\n``````names = {\"zhangsan\", \"lisi\", \"wangwu\"}\nfor name in names:\nprint(name)\n>>>\nlisi\nzhangsan\nwangwu``````\n\nnames 是一个集合,为可迭代对象,使用 for 循环,name 会依次被赋值给 names 中的元素值。\n\n``````sum = 0\nn = 99\nwhile n > 0:\nsum = sum + n\nn = n - 2\nprint(sum)\n>>>\n2500``````\n\n## 高级特性\n\n``````L = ['zhangsan', 'lisi', 'wangwu', 'zhaoliu']\nprint(L)\nprint(L[1:3])\n>>>\nlisi\n['lisi', 'wangwu']``````\n\nPython 中,下标都是从 0 开始的,且都是左闭右开区间\n\n``````L = ['zhangsan', 'lisi', 'wangwu', 'zhaoliu']\nD = {\"zhangsan\":1, \"lisi\": 2, \"wangwu\": 3, \"zhaoliu\": 4}\nfor l in L:\nprint(l)\nprint('\\n')\nfor k,v in D.items():\nprint(\"键:\", k, \",\", \"值\", v)\n>>>\nzhangsan\nlisi\nwangwu\nzhaoliu\n\n## 函数\n\nPython 内置了很多有用的函数,三分钟时时彩三分钟时时彩我 们 可以直接调用\n\n``````>>> abs(100)\n100\n>>> abs(-20)\n20\n>>> abs(12.34)\n12.34\n>>> max(1, 2)\n2\n>>> max(2, 3, 1, -5)\n3``````\n\nhttp://docs.python.org/zh-cn/3/library/functions.html\n\n``````def add(num1, num2):\nreturn num1 + num2\n\nprint(result)\n\n>>>\n3``````\n\n## 模块\n\nPython 本身就内置了很多非常有用的模块,只要安装完毕,这些模块就可以立刻使用。\n\n``````import time\n\ndef sayTime():\nnow = time.time()\nreturn now\n\nnowtime = sayTime()\nprint(nowtime)\n>>>\n1566550687.642805``````\n\n``````mytest\n├─ __init__.py\n├─ test1.py\n└─ test2.py``````\n\n``````import mytest\n\nmytest.test1``````\n\n``pip install Pillow``\n\n## 面向对象编程\n\n``````class Student(object):\npass``````\n\n``````zhangsan = Student()\nzhangsan.age = 20\nprint(Student)\nprint(zhangsan)\nprint(zhangsan.age)\n>>>\n<class '__main__.Student'>\n<__main__.Student object at 0x00EA7350>\n20``````\n\n## IO 编程\n\n``````f = open('/Users/tanxin/test.txt', 'r')\nf.close()``````\n\n``````with open('/Users/tanxin/test.txt', 'r') as f:\n\nwith 语句三分钟时时彩帮助 三分钟时时彩三分钟时时彩我 们 完成了 close 的过程\n\n## 正则表达式\n\nPython 中提供了 re 模块来做正则\n\n``````import re\nstr1 = \"010-56765\"\nres = re.match(r'(\\d{3})-(\\d{5})', str1)\nprint(res)\nprint(res.group(0))\nprint(res.group(1))\nprint(res.group(2))\n>>>\n<re.Match object; span=(0, 9), match='010-56765'>\n010-56765\n010\n56765``````\n\nmatch() 三分钟时时彩方法 判断是否匹配,如果匹配成功,返回一个 Match 对象,否则返回 None\n\n# requests 库三分钟时时彩简介\n\nrequests 库,是一个非常常用的 HTTP 网络请求库,后面的爬虫课程,三分钟时时彩三分钟时时彩我 们 会大量的使用它。\n\n``````import requests\n\nr = requests.get('http://www.baidu.com')\nr = requests.post('http://test.com/post', data = {'key':'value'})\n\npayload = {'key1': 'value1', 'key2': 'value2'}\n\n``````r.text # 获取响应内容\nr.content # 以字节的方式读取响应信息\nresponse.encoding = \"utf-8\" # 改变其编码\nhtml = response.text # 获得网页内容\nbinary__content = response.content # 获得二进制数据\nraw = requests.get(url, stream=True) # 获得原始响应内容\nheaders = {'user-agent': 'my-test/0.1.1'} # 定制请求头\n\n# 总结",
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] | {"ft_lang_label":"__label__zh","ft_lang_prob":0.9320893,"math_prob":0.8446027,"size":6784,"snap":"2019-43-2019-47","text_gpt3_token_len":4353,"char_repetition_ratio":0.13657817,"word_repetition_ratio":0.0052562417,"special_character_ratio":0.2781545,"punctuation_ratio":0.12755102,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.96554226,"pos_list":[0,1,2],"im_url_duplicate_count":[null,2,null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2019-11-20T21:33:03Z\",\"WARC-Record-ID\":\"<urn:uuid:162d0f15-5e75-47aa-a89f-38acaa7c5c96>\",\"Content-Length\":\"33928\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:42496284-b71b-4630-86e4-9307d075eae1>\",\"WARC-Concurrent-To\":\"<urn:uuid:765c848d-7140-4249-91c9-bce9dfbd03b4>\",\"WARC-IP-Address\":\"146.148.161.61\",\"WARC-Target-URI\":\"http://dfhgt.com/cloumn/blog/1407\",\"WARC-Payload-Digest\":\"sha1:DVH6HPJWVEZC3UG5ZPZUIEQRX2B6GW7X\",\"WARC-Block-Digest\":\"sha1:NQFNHET4SZ2TVGZZUZSPZXTAFEMVX4B5\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2019/CC-MAIN-2019-47/CC-MAIN-2019-47_segments_1573496670635.48_warc_CC-MAIN-20191120213017-20191121001017-00322.warc.gz\"}"} |
http://www.vuhelp.net/threads/17324-cs302-mid-term-current-paper-fall-4-December-2011?s=a44b6b4d234383a6dea20b1c8dd79854 | [
"",
null,
"cs302 mid term current paper fall 4 December 2011\n\nSubjective questions:\nQ: 21: How a circuit with multiple outputs is\nshown in truth table?\nMARKS: 3:\n\nQ: 22: Define Sequential Circuit.\nMARKS: 2:\nDigital circuits that generate a new output on the\nbasis of some previously stored information and\nthe new input are known as Sequential circuits.\n\nQ: 23: Apply each of the following sets of binary\nnumbers to Comparator inputs in figure and\n\ndetermine the output by following logic levels of\nthe Circuit.\nMARKS: 5\n\n(a) A= 10, B= 10.\n(b) A= 11, B= 10.\n\nQ: 24: Write uses of demultiplexer.\nMARKS: 5:\n\nQ: 25: How decorder is used as demultiplexer.\n\nMARKS: 3:\n\nQ: 26: Two-bit iterative comparator circuit for\ncomparison A=B. Explain functionality of the\nCircuit.\nMARKS: 3:"
] | [
null,
"http://www.vuhelp.net/threads/images/icons/utorrent-torrent-for-mac (1).gif",
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] | {"ft_lang_label":"__label__en","ft_lang_prob":0.8582885,"math_prob":0.9435831,"size":1448,"snap":"2022-05-2022-21","text_gpt3_token_len":403,"char_repetition_ratio":0.16620499,"word_repetition_ratio":0.07024793,"special_character_ratio":0.30041435,"punctuation_ratio":0.16433567,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.9652732,"pos_list":[0,1,2],"im_url_duplicate_count":[null,null,null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2022-01-26T17:12:02Z\",\"WARC-Record-ID\":\"<urn:uuid:dc7ecdd8-d010-4639-b310-a50ba0fcb5b3>\",\"Content-Length\":\"59646\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:609da17c-fe97-4cec-91ef-a738446d8345>\",\"WARC-Concurrent-To\":\"<urn:uuid:220940c9-7aaa-41e9-bd7c-0d353316c0d1>\",\"WARC-IP-Address\":\"70.32.23.106\",\"WARC-Target-URI\":\"http://www.vuhelp.net/threads/17324-cs302-mid-term-current-paper-fall-4-December-2011?s=a44b6b4d234383a6dea20b1c8dd79854\",\"WARC-Payload-Digest\":\"sha1:2PMZZH7CQ7HZW2J6UNFHXN66HY7IN4FO\",\"WARC-Block-Digest\":\"sha1:CDVRR6HDXUFT3KRBSN6ACXPUM23O4HC2\",\"WARC-Identified-Payload-Type\":\"application/xhtml+xml\",\"warc_filename\":\"/cc_download/warc_2022/CC-MAIN-2022-05/CC-MAIN-2022-05_segments_1642320304959.80_warc_CC-MAIN-20220126162115-20220126192115-00577.warc.gz\"}"} |
https://dsp.stackexchange.com/questions/51449/how-to-get-the-mlseequalizer-work-with-ifft-and-fft-blocks-in-the-communication | [
"# How to get the MLSEEqualizer work with IFFT and FFT blocks in the communication system?\n\nMatlab MLSEE equalizer works fine with the QPSK modulated signal when the signal is propagated over the multipath channel. However, if there are IFFT and FFT blocks used at TX and RX sides, respectively, the receiver in the modified code has worse BER results than the original code as shown in the following MATLAB codes.\n\nI would like to ask for your help to investigate the failure in the modified code below.\n\n% Original Code: Works fine and gives perfect BER results.\n% Equalize a QPSK signal transmitted through a dispersive channel\n% using MLSE\n\nqpskMod = comm.QPSKModulator(0,'SymbolMapping','Binary');\nqpskDemod = comm.QPSKDemodulator(0,'SymbolMapping','Binary');\n% Channel coefficients\nchCoeffs = [.986; .845; .237; .12345+.31i];\nN=512; % Modulated signal length\nmleq = comm.MLSEEqualizer('TracebackDepth',10,...\n'Channel',chCoeffs, 'Constellation',[1 1i -1 -1i]);\n% Create an error rate calculator\nber = comm.ErrorRate;\nfor n = 1:10\ndata= randi([0 3],N,1);\nmodSignal = qpskMod(data);\n% Introduce channel distortion.\nchanOutput = filter(chCoeffs,1,modSignal);\n% Equalize the channel output and demodulate\neqSignal = mleq(chanOutput);\ndemodData = qpskDemod(eqSignal);\n% Compute BER\na = ber(data, demodData);\nb=a(1)\nend\n\n% Modified Code: IFFT and FFT blocks are used but the system shows worse BER results.\n% Equalize a QPSK signal transmitted through a dispersive channel using MLSE\n\nqpskMod = comm.QPSKModulator(0,'SymbolMapping','Binary');\nqpskDemod = comm.QPSKDemodulator(0,'SymbolMapping','Binary');\n% Channel coefficients\nchCoeffs = [.986; .845; .237; .12345+.31i];\nN=512; % Modulated signal length\nmleq = comm.MLSEEqualizer('TracebackDepth',10,...\n'Channel',chCoeffs, 'Constellation',[1 1i -1 -1i]);\n% Create an error rate calculator\nber = comm.ErrorRate;\nfor n = 1:10\ndata= randi([0 3],N,1);\n\n% Modulate the data and convert it to time domain.\nmodSignalx = qpskMod(data);\nmodSignal=sqrt(N)*ifft(modSignalx);\n\n% Introduce channel distortion\nchanOutput = filter(chCoeffs,1,modSignal);\n\n% Equalize the channel output and demodulate\neqSignalx = mleq(chanOutput);\neqSignal=(1/sqrt(N))*fft(eqSignalx);\n\ndemodData = qpskDemod(eqSignal);\n% Compute BER\na = ber(data, demodData);\nb(n)=a(1);\nend\n\n\n@Zeyad_Zeyad I have included the whole code here. It gives high error rate even the SNR is set to 30.\n\nclear all;\nclose all;\nqpskMod = comm.QPSKModulator(0,'SymbolMapping','Binary');\nqpskDemod = comm.QPSKDemodulator(0,'SymbolMapping','Binary');\n% Channel coefficients\nchCoeffs = [.986; .845; .237; .12345+.31i];\nN=512; % Modulated signal length\nmleq = comm.MLSEEqualizer('TracebackDepth',10,...\n'Channel',chCoeffs, 'Constellation',[1 1i -1 -1i]);\nsnr=30;\nnumiteration=10;\nfor n = 1:numiteration\ndata= randi([0 3],N,1);\ndataIn(:,n)=data;\n\n% Modulate the data and convert it to time domain.\nmodSignalx = step(qpskMod, data);\nmodSignal=sqrt(N)*ifft(modSignalx);\n\n% Introduce channel distortion\nchanOutputx = filter(chCoeffs,1,modSignal);\n\nchanOutput=awgn(chanOutputx,snr,'measured');\n\n% Equalize the channel output and demodulate\neqSignalx = step(mleq, chanOutput);\neqSignal=(1/sqrt(N))*fft(eqSignalx);\n\ndemodData = step(qpskDemod, eqSignal);\ndemodDataOut(:,n)=demodData;\n% Compute BER\nend\na = biterr(dataIn(:), demodDataOut(:));\nb=a/(N*numiteration)\n\n\nHere is I modified it, and it's ok now:\n\n% Modified Code: IFFT and FFT blocks are used but the system shows worse BER results.\n% Equalize a QPSK signal transmitted through a dispersive channel using MLSE\n\nqpskMod = comm.QPSKModulator(0,'SymbolMapping','Binary');\nqpskDemod = comm.QPSKDemodulator(0,'SymbolMapping','Binary');\n% Channel coefficients\nchCoeffs = [.986; .845; .237; .12345+.31i];\nN=512; % Modulated signal length\nmleq = comm.MLSEEqualizer('TracebackDepth',10,...\n'Channel',chCoeffs, 'Constellation',[1 1i -1 -1i]);\n% Create an error rate calculator\nber = comm.ErrorRate;\nfor n = 1:10\ndata= randi([0 3],N,1);\n\n% Modulate the data and convert it to time domain.\nmodSignalx = step(qpskMod, data);\nmodSignal=sqrt(N)*ifft(modSignalx);\n\n% Introduce channel distortion\nchanOutput = filter(chCoeffs,1,modSignal);\n\n% Equalize the channel output and demodulate\neqSignalx = step(mleq, chanOutput);\neqSignal=(1/sqrt(N))*fft(eqSignalx);\n\ndemodData = step(qpskDemod, eqSignal);\n% Compute BER\na = biterr(data(n), demodData(n));\n\nb(n)=a(1);\nend\n`\n• Thank you Zeyad. Now I get correct BER results.I have tried to add Gaussian noise to the signal you've modified above but it still gives zero errors even I have run the code with zero SNR value as below. data= randi([0 3],N,1); % Modulate the data and convert it to time domain. modSignalx = step(qpskMod, data); modSignal=sqrt(N)*ifft(modSignalx); % Introduce channel distortion chanOutput = filter(chCoeffs,1,modSignal); %%add gaussian noise to the signal chanOutput chanOutput_noised=awgn(chanOutput,0,'measured'); – tuner Aug 23 '18 at 19:06\n• @tuner could you please share the whole code, including the plots .. I'll check – Zeyad_Zeyad Aug 25 '18 at 7:12\n• @tuner sorry for late response, I've seen your comments (which is in the question itself) right now.. I mean could you share the code including the plots? I need to check the results too – Zeyad_Zeyad Aug 27 '18 at 3:10"
] | [
null
] | {"ft_lang_label":"__label__en","ft_lang_prob":0.5978803,"math_prob":0.9927348,"size":3275,"snap":"2020-10-2020-16","text_gpt3_token_len":1004,"char_repetition_ratio":0.12687251,"word_repetition_ratio":0.43034825,"special_character_ratio":0.28305343,"punctuation_ratio":0.25955415,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.996264,"pos_list":[0],"im_url_duplicate_count":[null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2020-04-06T10:12:38Z\",\"WARC-Record-ID\":\"<urn:uuid:c6b0889b-84dd-4abd-8224-2778843858fb>\",\"Content-Length\":\"148143\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:8662fb3e-2eab-479b-b0de-6968c6e96acd>\",\"WARC-Concurrent-To\":\"<urn:uuid:fa29bd23-e173-41a7-a171-5238c71e65cc>\",\"WARC-IP-Address\":\"151.101.1.69\",\"WARC-Target-URI\":\"https://dsp.stackexchange.com/questions/51449/how-to-get-the-mlseequalizer-work-with-ifft-and-fft-blocks-in-the-communication\",\"WARC-Payload-Digest\":\"sha1:RLY6DME4UDDOWAUAUJ2JPFRTXFZAGHHR\",\"WARC-Block-Digest\":\"sha1:24BZ4ZFQMZ2PZ3LKAALCMTP25BXKG5EP\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2020/CC-MAIN-2020-16/CC-MAIN-2020-16_segments_1585371620338.63_warc_CC-MAIN-20200406070848-20200406101348-00437.warc.gz\"}"} |
https://es.mathworks.com/help/antenna/ref/pattern.html | [
"pattern\n\nRadiation pattern and phase of antenna or array; Embedded pattern of antenna element in array\n\nDescription\n\nexample\n\npattern(object,frequency) plots the 3-D radiation pattern of the antenna or array object over a specified frequency. By default, in Antenna Toolbox™, the far-field radius is set to 100λ.\n\npattern(object,frequency,azimuth,elevation) plots the radiation pattern of the antenna or array object using the specified azimuth and elevation angles.\n\npattern(___,Name,Value) uses additional options specified by one or more Name, Value pair arguments. You can use any of the input arguments from previous syntaxes.\n\nUse the 'ElementNumber' and 'Termination' property to calculate the embedded pattern of the antenna element in an array connected to a voltage source. The voltage source model consists of an ideal voltage source of 1 volt in series with a source impedance. The embedded pattern includes the effect of mutual coupling due to the other antenna elements in the array.\n\n[pat,azimuth,elevation] = pattern(object,frequency,azimuth,elevation) returns the pattern value, pat, value of an antenna or array object at specified frequency. azimuth and elevation are the angles at which the pattern function calculates the directivity.\n\n[pat,azimuth,elevation] = pattern(___,Name,Value) uses additional options specified by one or more Name,Value pair arguments.\n\nExamples\n\ncollapse all\n\nCalculate radiation pattern of default linear array for a frequency of 70 MHZ.\n\nl = linearArray;\npattern(l,70e6)",
null,
"Plot the radiation pattern of a helix antenna in xz-plane.\n\nh = helix;\npattern (h, 2e9, 0, 1:1:360);",
null,
"[pat,azimuth,elevation] = pattern (h, 2e9, 0, 1:1:360);\n\nCompute the maximum and the minimum value of the radiation pattern and the elevation angle.\n\npattern_max = max(max(pat))\npattern_max = 8.6905\npattern_min = min(min(pat))\npattern_min = -11.2357\nelevation_max = max(elevation)\nelevation_max = 360\nelevation_min = min(elevation)\nelevation_min = 1\n\nCalculate the embedded element pattern of a linear array. Excite the first antenna element in the array. Terminate all the other antenna elements using a 50-ohm resistance.\n\nl = linearArray;\npattern(l, 70e6,'ElementNumber', 1,'Termination', 50);",
null,
"Calculate the directivity of a helix antenna.\n\nh = helix;\nD = pattern(h, 2e9, 0, 1:1:360);\n\nShowing the first five directivity values.\n\nDnew = D(1:5)\nDnew = 5×1\n\n-6.4066\n-6.1929\n-5.9655\n-5.7262\n-5.4770\n\nPlot the radiation pattern of a helix antenna with transparency specified as 0.5.\n\np = PatternPlotOptions\np =\nPatternPlotOptions with properties:\n\nTransparency: 1\nSizeRatio: 0.9000\nMagnitudeScale: []\nAntennaOffset: [0 0 0]\n\np.Transparency = 0.5;\nant = helix;\npattern(ant,2e9,'patternOptions',p)",
null,
"To understand the effect of Transparency, chose Overlay Antenna in the radiation pattern plot.\n\nThis option overlays the helix antenna on the radiation pattern.",
null,
"Plot radiation pattern of dipole antenna in rectangular cartesian co-ordinate system.\n\npattern(dipole, 70e6:10e6:100e6, 0, 90, 'CoordinateSystem', 'rectangular')",
null,
"Directivity values of dipole antenna\n\nD = pattern(dipole, 70e6:10e6:100e6, 0, 90, 'CoordinateSystem', 'rectangular')\nD = 4×1\n\n-49.6264\n-50.3098\n-49.1815\n-47.0042\n\nVisualize gain plot of radial monopole antenna.",
null,
"Visualize gain plot of radial monopole antenna.",
null,
"Input Arguments\n\ncollapse all\n\nAntenna or array element, specified as an object.\n\nFrequency to calculate or plot the antenna or array radiation pattern, specified as a scalar or a vector with each element in Hz. The vector frequencies support rectangular coordinate system.\n\nExample: 70e6\n\nData Types: double\n\nAzimuth angles and spacing between the angles to visualize the radiation pattern, specified as a vector in degrees. If the coordinate system is set to uv, then the U values are specified in this parameter. The values of U are between -1 to 1.\n\nExample: 90\n\nData Types: double\n\nElevation angles and spacing between the angles to visualize the radiation pattern, specified as a vector in degrees. If the coordinate system is set to uv, then the V values are specified in this parameter. The values of V are between -1 to 1.\n\nExample: 0:1:360\n\nData Types: double\n\nName-Value Arguments\n\nExample: 'CoordinateSystem', 'uv'\n\nSpecify optional comma-separated pairs of Name,Value pair arguments. Name is the argument name and Value is the corresponding value. Name must appear inside single quotes (''). You can specify several name and value pair arguments in any order as Name1, Value1, ..., NameN, ValueN.\n\nCoordinate system to visualize the radiation pattern, specified as the comma-separated pair consisting of 'CoordinateSystem' and one of these values: 'polar', 'rectangular', 'uv'.\n\nExample: 'CoordinateSystem', 'polar'\n\nData Types: char\n\nQuantity to plot, specified as a comma-separated pair consisting of 'Type' and one of these values:\n\n• directivity – Directivity in dBi\n\n• gain – Gain in dBi\n\nNote\n\nThe antenna Gain and Directivity are measured at a distance of 100*lambda.\n\n• realizedgain – Realized gain in dBi\n\n• efield – Electric field in volt/meter\n\n• power – Power in watts\n\n• powerdb – Power in dB\n\n• phase – Phase in degrees.\n\nNote\n\nType can only be set to phase when Polarization is provided.\n\nThe default value is 'directivity' for a lossless antenna and 'gain' for a lossy antenna. You cannot plot the 'directivity' of a lossy antenna.\n\nExample: 'Type', 'efield'\n\nData Types: char\n\nNormalize field pattern, specified as the comma-separated pair consisting of 'Normalize' and either true or false.\n\nExample: 'Normalize', false\n\nData Types: logical\n\n2-D pattern display style when frequency is a vector, specified as the comma-separated pair consisting of 'PlotStyle' and one of these values:\n\n• 'overlay' – Overlay frequency data in a 2-D line plot\n\n• 'waterfall' – Plot frequency data in a waterfall plot\n\nYou can use this property when using pattern function with no output arguments.\n\nExample: 'PlotStyle', 'waterfall'\n\nData Types: char\n\nField polarization, specified as the comma-separated pair consisting of 'Polarization' and one of these values:\n\n• 'H' – Horizontal polarization\n\n• 'V' – Vertical polarization\n\n• 'RHCP' – Right-hand circular polarization\n\n• 'LHCP' – Left-hand circular polarization\n\nBy default, you can visualize a combined polarization.\n\nExample: 'Polarization', 'RHCP'\n\nData Types: char\n\nAntenna element in array, specified as the comma-separated pair consisting of 'ElementNumber' and scalar. This antenna element is connected to the voltage source.\n\nNote\n\nUse this property to calculate the embedded pattern of an array.\n\nExample: 'ElementNumber',1\n\nData Types: double\n\nImpedance value for array element termination, specified as the comma-separated pair consisting of 'Termination' and scalar. The impedance value terminates other antenna elements of an array while calculating the embedded pattern of the antenna connected to the voltage source.\n\nNote\n\nUse this property to calculate the embedded pattern of an array.\n\nExample: 'Termination',40\n\nData Types: double\n\nParameter to change pattern plot properties, specified as the comma-separated pair consisting of 'patternOptions' and a PatternPlotOptions output. The properties that you can vary are:\n\n• Transparency\n\n• SizeRatio\n\n• AntennaOffset\n\n• AntennaVisibility\n\n• MagnitudeScale\n\nExample: p = PatternPlotOptions('Transparency',0.1); Create a pattern plot option with a transparency of 0.1. ant = helix;pattern(ant,2e9,'patternOptions',p); Use this pattern plot option to visualize the pattern of a helix antenna.\n\nData Types: double\n\nOutput Arguments\n\ncollapse all\n\nRadiation pattern of antenna or array or embedded pattern of array, returned as a matrix of number of elevation values by number of azimuth values. The pattern is one of the following:\n\n• directivity – Directivity in dBi (lossless antenna or array)\n\n• gain – Gain in dBi (lossy antenna or array)\n\n• realizedgain – Realized gain in dBi (lossy antenna or array)\n\n• efield – Electric field in volt/meter\n\n• power – Power in watts\n\n• powerdb – Power in dB\n\nMatrix size is number of elevation values multiplied by number of azimuth values.\n\nAzimuth angles to calculate the radiation pattern, returned as a vector in degrees.\n\nElevation angles to calculate the radiation pattern, returned as a vector in degrees.\n\n Makarov, Sergey N. Antenna and EM Modeling in MATLAB. Chapter3, Sec 3.4 3.8. Wiley Inter-Science.\n\n Balanis, C.A. Antenna Theory, Analysis and Design, Chapter 2, sec 2.3-2.6, Wiley."
] | [
null,
"https://es.mathworks.com/help/examples/antenna/win64/CalculateRadiationPatternOfArrayExample_01.png",
null,
"https://es.mathworks.com/help/examples/antenna/win64/RadiationPatternOfHelixInXZPlaneExample_01.png",
null,
"https://es.mathworks.com/help/examples/antenna/win64/EmbeddedElementPatternOfLinearArrayExample_01.png",
null,
"https://es.mathworks.com/help/examples/antenna/win64/RadiationPatternOfHelixAntennaExample_01.png",
null,
"https://es.mathworks.com/help/examples/antenna/win64/RadiationPatternOfHelixAntennaExample_02.png",
null,
"https://es.mathworks.com/help/examples/antenna/win64/RadiationPatternOfDipoleAntennaExample_01.png",
null,
"https://es.mathworks.com/help/examples/antenna/win64/CompareGainAndRealizedGainAntennaExample_01.png",
null,
"https://es.mathworks.com/help/examples/antenna/win64/CompareGainAndRealizedGainAntennaExample_02.png",
null
] | {"ft_lang_label":"__label__en","ft_lang_prob":0.5213276,"math_prob":0.9002014,"size":1114,"snap":"2022-05-2022-21","text_gpt3_token_len":281,"char_repetition_ratio":0.13333334,"word_repetition_ratio":0.049689442,"special_character_ratio":0.21274686,"punctuation_ratio":0.16019417,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.9850789,"pos_list":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16],"im_url_duplicate_count":[null,3,null,3,null,3,null,3,null,3,null,2,null,1,null,1,null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2022-01-22T14:27:00Z\",\"WARC-Record-ID\":\"<urn:uuid:b9fdaad8-f527-4a3b-8250-a11eec5a73b8>\",\"Content-Length\":\"146725\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:08753c19-7070-4287-ab80-67e276462e1a>\",\"WARC-Concurrent-To\":\"<urn:uuid:f2848d09-3633-49ef-ac07-01887a7b0cc8>\",\"WARC-IP-Address\":\"104.68.243.15\",\"WARC-Target-URI\":\"https://es.mathworks.com/help/antenna/ref/pattern.html\",\"WARC-Payload-Digest\":\"sha1:OEODDBAE46HXBK3V2SUZLJQEEXARVAIT\",\"WARC-Block-Digest\":\"sha1:EHMEY44PDVF2MBFSJKAEE3CMQJYYPL5W\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2022/CC-MAIN-2022-05/CC-MAIN-2022-05_segments_1642320303864.86_warc_CC-MAIN-20220122134127-20220122164127-00477.warc.gz\"}"} |
https://cran.stat.unipd.it/web/packages/memoria/vignettes/using_memoria.html | [
"# Using “memoria” and “virtualPollen” together\n\n### Quantifying ecological memory of virtual pollen curves\n\nSummary\n\nThis document describes in detail how to analyze ecological memory patterns present in simulated pollen curves generated with the virtualPollen and memoria packages. First, we describe the complex statistical properties of the virtual pollen curves produced by virtualPollen and how these may impact ecological memory analyses; Second we explain how Random Forest works, from its basic components (regression trees) to the way in which it computes variable importance; Third, we explain how to analyze ecological memory patterns on the simulation outputs.\n\n# The model\n\nAnalyzing ecological memory requires to fit a model of the form:\n\nEquation 1 (simplified from the one in the paper): $p_{t} = p_{t-1} +...+ p_{t-n} + d_{t} + d_{t-1} +...+ d_{t-n}$\n\nWhere:\n\n• $$p$$ is Pollen.\n• $$d$$ is Driver.\n• $$t$$ is the time of any given value of the response $$p$$.\n• $$t-1$$ is the lag 1.\n• $$p_{t-1} +...+ p_{t-n}$$ represents the endogenous component of ecological memory.\n• $$d_{t-1} +...+ d_{t-n}$$ represents the exogenous component of ecological memory.\n• $$d_{t}$$ represents the concurrent effect of the driver over the response.\n\nThe function prepareLaggedData shown below organizes the input data in lags. It requires to identify what columns in the original data should act as response, drivers, and time, and what lags are to be generated.\n\n#loading data\ndata(simulation) #from virtualPollen\nsim <- simulation[]\n\n#generating vector of lags (same as in paper)\nlags <- seq(20, 240, by = 20)\n\n#organizing data in lags\nsim.lags <- prepareLaggedData(\ninput.data = sim,\nresponse = \"Pollen\",\ndrivers = c(\"Driver.A\", \"Suitability\"),\ntime = \"Time\",\nlags = lags,\nscale = FALSE\n)\n\nThis function returns the data shown in Table 1. This kind of data structure is known as lagged data or time delayed data. Note that the function can use a scale argument (set to FALSE above) to standardize the data before generating the lags. Random Forest does not generally require standardization to fit accurate models of the data, but computing variable importance with variables having large differences in range (i.e. [1, 10] vs. [1, 10000]) might yield biased results, making standardization a recommended step in data preparation. In this appendix all data are shown without any standardization to let the reader to keep track of the different variables across analyses and have a sense of their magnitude, but note that all analyses presented in the paper were based on standardized data.\n\nThe data in Table 1 are organized to fit the model described by Equation 1, but to select a proper method to fit the model, three main features of the data have to be considered first: temporal autocorrelation, multicollinearity, and non-linearity.\n\n# The data\n\nThe simulations produced by virtualPollen have some key properties that justify the use of Random Forest as analytical tool.\n\n## Temporal autocorrelation\n\nTemporal autocorrelation (also serial correlation) refers to the relationship between successive values of the same variable present in most time series. Temporal autocorrelation generates autocorrelated residuals in regression analysis, violating the assumption of “independence of errors” required to correctly interpret regression coefficients. Several methods can be used to address temporal autocorrelation in regression analysis, such as increasing time intervals between consecutive samples, or incorporating an auto-regressive structure into the model.\n\nEvery variable used in our study presents this characteristic. The driver was generated with a temporal autocorrelation significant for periods of 600 years. The suitability produced by the niche function of the virtual taxa based on the values of the driver also presents temporal autocorrelation, but generally lower than the one of the driver. Finally, the response, since it is the result of a dynamic model in which every data-point depends on the previous one, also shows a temporal structure, which varies depending on the taxa’s traits, as so does the suitability (see Figure 2).\n\n## Multicollinearity\n\nMulticollinearity occurs when there is a high correlation between predictors in a model definition. It increases the standard error of the coefficients, meaning that their estimates for important predictors can become statistically insignificant, wildly impacting model interpretation.\n\nAdding consecutive time-lags of the same variables to the data, as required by the model expressed in Equation 1 largely increases multicollinearity.\n\n## Non-linearity\n\nThe function virtualPollen::simulatePopulation has the ability to produce pollen abundances variably decoupled from environmental conditions depending on the life-traits and niche features of the virtual taxa considered. This model property increases the chance of finding non-linear relationships between time-lagged predictors and the response (see Figure 3), hindering the detection of meaningful relationships with methods not able to account for non-nonlinearity.\n\n# The logics behind Random Forest\n\n## The trees\n\nThe fundamental units of a Random Forest model are regression trees. A regression tree grows through binary recursive partition. Considering a response variable, and a set of predictive variables (also named features in the machine learning language), the following steps grow a regression tree:\n\n• For each variable, the point in their ranges that optimizes the separation (partition) of the response in two groups of cases is searched for. The selected point minimizes the sum of the squared deviations from the mean in the two separated partitions.\n• The variable with the lower sum of the squared deviations from the means is selected as the root node of the tree, and the data are separated in two partitions, one on each side of the split value of the given variable.\n• The steps above are recursively applied to each partition to create new partitions, until all cases are in partitions that can be no longer separated in smaller partitions because they are too homogeneous, or because they have reached a minimum sample size. These final partitions are named terminal nodes.\n\nThe code below shows how to fit a recursive partition tree with the rpart library on the first lag (20 years) of pollen and driver of the data shown in Figure 2.\n\n#fitting model (only two predictors)\nrpart.model <- rpart(\nformula = Response_0 ~ Response_20 + Driver.A_20,\ndata = sim.lags,\ncontrol = rpart.control(minbucket = 5)\n)\n\n#plotting tree\nrpart.plot(\nrpart.model,\ntype = 0,\nbox.palette = viridis(10, alpha = 0.2)\n)\n\nFigure 4 shows the recursive partition tree fitted on Pollen_0 as a function of the first lag of pollen (Pollen_20) and the driver (Driver_20), while Figure 5 shows the partitions in the space of both variables. As shown in both figures, the recursive partition tree is, in essence, separating the cases into regions in which given combinations of the predictors lead to certain average values of the response. The tree also shows the hierarchy in importance between both predictors, with Pollen_20 defining all splits but one. Only when Pollen_20 is higher than 3772, the variable Driver_20 becomes important, indicating that maximum abundances are only reached after that point, and only if Driver_20 has a value lower than 71. This is how partial interactions among predictors are expressed in recursive partition trees.\n\nThe tree has grown until data in the terminal nodes cannot be separated further into additional partitions, or has reached the minimum number of cases defined by the variable minbucket. The minimum amount of cases in a terminal node defines the overall resolution of the model. Smaller numbers lead to a higher amount of terminal nodes, and therefore to more partitions in the data space. This can be confirmed by changing the minbucket value in the code above, and assessing subsequent changes in tree structure and number of partitions.\n\nAs a drawback, the splits of a recursive partition trees are highly sensitive to small changes in the input data, specially when sample size is small. This instability has led to the development of more sophisticated methods to fit recursive partition trees, such as conditional inference trees (see function ctree in library partykit), or ensemble methods such as Random Forest.\n\n## The forest\n\nA Random Forest model is composed by a large number of individual regression trees (500 or more) generated on random subsamples of the predictors and the cases. For a random set of cases, each tree is fitted as follows:\n\n• A random subset of predictors of size mtry is selected. The default mtry is the rounded-up squared root of the total number of predictors, but the user can modify it.\n• The predictor from the random subset that better separates the data into two partitions is selected as root node, an the data are separated in two partitions, one at each side of the split value.\n• On each partition, a new random subset of predictors of size mtry is selected (and this is the main difference between a recursive partition tree and a Random Forest tree, the former uses all variables on each split), and again the predictor that better separates the partition into two new partitions is selected, and new partitions are defined.\n• The tree is grown until minimum node size is reached in all terminal nodes, or no further partitions can be defined.\n• The tree is evaluated by computing its mean squared error (mse) on the ~37% of the data not used to train it (named out-of-bag data).\n• For each variable in the tree the algorithm performs a permutation test as follows:\n• The column with the given variable is randomly permuted.\n• A new tree is fitted with the permuted variable.\n• Mean squared error is computed again on the out-of-bag data.\n• Difference in mse between the tree fitted with the original variable and the tree fitted with the permuted one is computed and stored.\n\nOnce all trees have been fitted, for every given case, the prediction is computed as the mode of the individual predictions of every tree (but not the ones fitted with permuted variables). The importance of every variable is computed as the average of the differences in mean squared error between trees computed with the variable and trees computed with the permuted variable, normalized by the standard deviation of the differences.\n\nRandom Forest does not require any assumptions to be fulfilled by the data or the model outcomes, and therefore it can be applied to a wide range of analytic cases where data are non-linear. As a drawback, the randomness in the selection of cases and predictors to fit individual regression trees turns it into a non-deterministic algorithm, and therefore, fine-scale variations in the outcomes are to be expected between different runs with the same data.\n\nTo fit Random Forest models on the simulated data we selected the package ranger over the more traditional randomForest because the former allows multithread computing (uses all available cores in a computer while fitting the forest), achieving a better performance for large datasets than the later. The code below shows how to use ranger to fit a Random Forest model.\n\n#getting columns containing \"Response\" or \"Driver\"\nsim.lags.rf <- sim.lags[, grepl(\"Driver|Response\", colnames(sim.lags))]\n\n#fitting a Random Forest model\nrf.model <- ranger(\ndata = sim.lags.rf,\ndependent.variable.name = \"Response_0\",\nnum.trees = 500,\nmin.node.size = 5,\nmtry = 2,\nimportance = \"permutation\",\nscale.permutation.importance = TRUE)\n\n#model summary\nprint(rf.model)\n\n#R-squared (computed on out-of-bag data)\nrf.model$r.squared #variable importance rf.model$variable.importance\n\n#obtain case predictions\nrf.model$predictions #getting information of the first tree treeInfo(rf.model, tree=1) The function ranger has the following key arguments: • data: dataframe with the variables to be included in the model. • dependent.variable.name: model definition can be done in two ways, either through a formula, or through the argument dependent.variable.name, that names the response variable, and uses the remaining variables in the dataset as predictors, which forces us to be careful with what variables are available in the dataset. • num.trees: controls number of trees generated (the default value is 500). • mtry: controls the number of variables randomly selected to fit each tree. In the code above this argument is set to 2, indicating that the model only considers interactions among two predictors only on each tree. This allows to compute variable importance as independently as possible from other variables. • min.node.size: minimum number of cases in a terminal node, which determines the overall resolution of the model. • importance: when set to “permutation” it triggers the computation of variable importance through permutation tests. • scale.permutation.importance: scales importance values computed through the permutation tests by the overall standard error. The relationship between the response variable and the predictors can be examined through partial dependence plots (see Figure 6). A partial dependence plot is a simplified view of the inner structure of the model. Since regression trees consider interactions among variables, the prediction for any given case depends on the values of all predictors considered at the same time. Since it is not possible to generate such a representation in 2D or 3D, partial dependence plots set all variables not represented in the plot to their respective means. Therefore, partial dependence plots must be interpreted as simple approximations to the true shape of the model surface. Interactions among predictors can be represented in the same way done before for recursive partition trees (see Figure 7). Again, all variables not represented in the plot are set to their average to generate the prediction. ## Variable importance Random forest variable importance computation works under the assumption that if a given variable is not important, then permuting its values does not degrade the prediction accuracy. Variable importance scores are extracted with the importance function (see code below and Table 4), and are interpreted as “how much model fit degrades when the given variable is removed from the model”. importance(rf.model) Values shown in Table 4 are the result of one particular Random Forest run. For variables with small differences in importance, the ranking shown in the table could change in a different model run. This situation can be addressed by running the model several times, and computing the average and confidence intervals of the importance scores of each predictor across runs. This is shown in the code below (see output in Figure 8). #number of repetitions repetitions <- 10 #list to save importance results importance.list <- list() #repetitions for(i in 1:repetitions){ #fitting a Random Forest model rf.model <- ranger( data = sim.lags.rf, dependent.variable.name = \"Response_0\", mtry = 2, importance = \"permutation\", scale.permutation.importance = TRUE ) #extracting importance importance.list[[i]] <- data.frame(t(importance(rf.model))) } #into a single dataframe importance.df <- do.call(\"rbind\", importance.list) ## Testing the significance of variable importance scores Random Forest does not provide any tool to assess the significance of these importance scores, and it is therefore impossible to know at what point they become irrelevant. A simple solution is to add a random variable as an additional predictor to the model and compute its importance. If the importance of other variables is equal or lower than the importance of the random variable, it can be assumed that these variables do not have a meaningful effect on the response, and can therefore be considered irrelevant. Two types of random variables can be considered to be used as benchmarks to test variable importance scores provided by Random Forest: white noise (without any temporal structure), and random walk with temporal structure (as explained in Appendix I). In both cases the idea is to generate a null model providing a baseline to assess to what extent importance scores are higher than what is expected by chance. To test the suitability of both methods, the code below generates 10 Random Forest models, each one with two additional random variables: random.white representing white noise, and random.autocor representing an autocorrelated random walk. The length of the autocorrelation period of random.autocor is changed for every iteration. #number of repetitions repetitions <- 10 #list to save importance results importance.list <- list() #rows of the input dataset n.rows <- nrow(sim.lags.rf) #repetitions for(i in 1:repetitions){ #adding/replacing random.white column sim.lags.rf$random.white <- rnorm(n.rows)\n\n#different filter length on each run = different temporal structure\nsim.lags.rf$random.autocor <- as.vector( filter(rnorm(n.rows), filter = rep(1, sample(1:floor(n.rows/4), 1)), method = \"convolution\", circular = TRUE)) #fitting a Random Forest model rf.model <- ranger( data = sim.lags.rf, dependent.variable.name = \"Response_0\", mtry = 2, importance = \"permutation\", scale.permutation.importance = TRUE) #extracting importance importance.list[[i]] <- data.frame(t(importance(rf.model))) } #into a single dataframe importance.df <- do.call(\"rbind\", importance.list) The boxplot in Figure 9 shows the relative importance of the random variables, and suggests that the variable representing random noise is not useful to identify importance scores arising by chance. On the other hand, the variable based on autocorrelated random walks (marked in yellow in the plot) tells a different story. Importance values below the yellow solid line have a probability higher than 0.5 of being the result of chance. Importance values between the yellow solid and dashed lines have probabilities between 0.5 and 0 and are the result of a random association between a predictor and the response, while beyond the dashed line the results can be confidently defined as non-random. Note that Figure 8, when compared with Figure 7, also shows that adding random variables to a Random Forest model does not change the importance scores of other variables in the model. # Analyzing ecological memory with Random Forest and the memoria library So far we have explained how to organize the simulated pollen curves in lags, and how to fit Random Forest models on the lagged data to evaluate variable importance. However, further steps are required to quantify ecological memory patterns: • Extract and aggregate variable importance scores, and organize them in ecological memory components (endogenous, exogenous, and concurrent). • Plot the pattern to facilitate interpretation. • Extract ecological memory features from these components, namely memory strength (maximum difference in relative importance between each component (endogenous, exogenous, and concurrent) and the median of the random component), memory length (proportion of lags over which the importance of a memory component is above the median of the random component), and dominance (proportion of the lags above the median of the random term over which a memory component has a higher importance than the other component). The function computeMemory fits as many Random Forest models as indicated by the argument repetitions on a lagged dataset, and on each iteration includes a random variable in the model. The function plotMemory gets the output of computeMemory and plots it, while the function extractMemoryFeatures computes the features of each ecological memory component. The simplified workflow is shown below. #computes ecological memory pattern memory.pattern <- computeMemory( lagged.data = sim.lags, drivers = \"Driver.A\", random.mode=\"autocorrelated\", repetitions=30, response=\"Response\" ) #computing memory features memory.features <- extractMemoryFeatures( memory.pattern=memory.pattern, exogenous.component=\"Driver.A\", endogenous.component=\"Response\" ) #plotting the ecological memory pattern plotMemory(memory.pattern) In order to analyze the ecological memory patterns of 16 virtual taxa across the 5 levels of data quality (Annual, 1cm, 2cm, 6cm, and 10cm), we integrated the functions above into a larger function named runExperiment. The code below runs an artificial simple example with only two virtual taxa (1 and 6 in parameters), and two dataset types (“1cm” and “10cm”). Only 30 repetitions are generated to quicken execution, which is not nearly enough to achieve consistent results. #running experiment E1 <- runExperiment( simulations.file = simulation, selected.rows = 1:4, selected.columns = 1, parameters.file = parameters, parameters.names = c(\"maximum.age\", \"fecundity\", \"niche.A.mean\", \"niche.A.sd\"), sampling.names = \"1cm\", driver.column = \"Driver.A\", response.column = \"Pollen\", time.column = \"Time\", lags = lags, repetitions = 30 ) #E1 is a list of lists #first list: names of experiment output E1$names\n\n#second list, first element\ni <- 1 #change to see other elements\n#ecological memory pattern\nE1$output[[i]]$memory\n\n#pseudo R-squared across repetitions\nE1$output[[i]]$R2\n\n#predicted pollen across repetitions\nE1$output[[i]]$prediction\n\n#variance inflation factor of input data\nE1$output[[i]]$multicollinearity\n\nExperiment results can be plotted with the function plotExperiment shown below.\n\nplotExperiment(\nexperiment.output=E1,\nparameters.file=parameters,\nexperiment.title=\"Toy experiment\",\nsampling.names=c(\"1cm\", \"10cm\"),\nlegend.position=\"bottom\",\nR2=TRUE\n)\n\nThe experiment data can be organizes as a single table, joined with the data available in the parameters dataframe to facilitate further analyses.\n\nE1.df <- experimentToTable(\nexperiment.output=E1,\nparameters.file=parameters,\nsampling.names=c(\"1cm\", \"10cm\"),\nR2=TRUE\n)\n\nFinally, ecological memory features can be extracted from the experiment with extractMemoryFeatures in order to facilitate further analyses, as shown below.\n\nE1.features <- extractMemoryFeatures(\nmemory.pattern = E1.df,\nexogenous.component = \"Driver.A\",\nendogenous.component = \"Response\"\n)"
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